511:\n xAccl -= 1024\n\n # ADXL345 address, 0x53(83)\n\n # Read data back from 0x34(52), 2 bytes\n\n # Y-Axis LSB, Y-Axis MSB\n\n data0 = bus.read_byte_data(0x53, 0x34)\n\n data1 = bus.read_byte_data(0x53, 0x35)\n\n # Convert the data to 10-bits\n\n yAccl = ((data1 & 0x03) * 256) + data0\n\n if yAccl > 511:\n yAccl -= 1024\n\n # ADXL345 address, 0x53(83)\n\n # Read data back from 0x36(54), 2 bytes\n\n # Z-Axis LSB, Z-Axis MSB\n\n data0 = bus.read_byte_data(0x53, 0x36)\n\n data1 = bus.read_byte_data(0x53, 0x37)\n\n # Convert the data to 10-bits\n\n zAccl = ((data1 & 0x03) * 256) + data0\n\n if zAccl > 511:\n zAccl -= 1024\n\n # Output data to screen\n\n # print \"Acceleration in X-Axis : %d\" %xAccl\n\n # print \"Acceleration in Y-Axis : %d\" %yAccl\n\n # print \"Acceleration in Z-Axis : %d\" %zAccl\n new_val = xAccl\n self.num_ticks += 1\n\n # grab the existing data, truncate it, and append the new point.\n # This isn't the most efficient thing in the world but it works.\n cur_data = self.viewer.data\n new_data = np.hstack((cur_data[-self.max_num_points + 1:], [new_val]))\n new_index = np.arange(self.num_ticks - len(new_data) + 1,\n self.num_ticks + 0.01)\n\n self.viewer.index = new_index\n self.viewer.data = new_data\n return","def rotate(self,X):\n alpha = random.rand() * 2*pi\n beta = self.beta_sample()\n R = Rotator.rotation_matrix(alpha,beta,0.0)\n X = np.dot(R, X)\n if self.random_flip and (random.rand() > 0.5):\n X[2,:] = -X[2,:]\n X[1,:] = -X[1,:]\n return X","def rotate_x(self,rad):\n DetElement.rotate_x(self,rad) #python2\n #super().rotate_x(rad) #python3\n for tube in self._list_of_tubes:\n self.__update__update_tube_pos_after_rotation(tube)\n tube.rotate_x(rad)","def rotate(self,X):\n alpha = random.rand() * 2*pi\n R = Rotator.rotation_matrix(alpha,0.0,0.0)\n return np.dot(R,X)","def rotate(self,id,x,y,r):\n if id not in self.elements.keys():\n print(\"Id input not registered! Please check your process\")\n return False\n element=self.elements[id]\n state=element.rotate(self.h-1-y,x,-r,self.w,self.h)\n if state==True:\n self.canvas=np.ones((self.h,self.w,3),dtype=np.uint8)*255\n self.sync=False\n return state","def RXX(self, theta:Union[int, float], qubit_expr): \n self.apply_gate_operation(RXX(theta), qubit_expr)","def rotate(self, angle=0.0):\n # TODO: Implement the rotate function. Remember to record the value of\n # rotation degree.\n self.rotDegree = angle\n self.x = rotate(self.x, angle = angle, axes=(0, 1), reshape=False, \n output=None, order=3, mode='constant', cval=0.0, prefilter=True)\n # This rotation isn't working correctly. Get shit for non right anlge rotatations\n # raise NotImplementedError\n #######################################################################\n # #\n # #\n # TODO: YOUR CODE HERE #\n # #\n # #\n #######################################################################","def spin(rxn_class):\n return rxn_class[1]","def add_rxn(self, reaction: db.Reaction):\n # Add two rxn nodes\n rxn_nodes = []\n reaction_id = reaction.id().string()\n\n for i in range(0, 2):\n # Add rxn node between lhs and rhs compound\n rxn_node = ';'.join([reaction_id, str(i)])\n rxn_node += ';'\n self.graph.add_node(rxn_node, color='rxn_node')\n rxn_nodes.append(rxn_node)\n # Convert to strings\n reactants = reaction.get_reactants(db.Side.BOTH)\n reactant_types = reaction.get_reactant_types(db.Side.BOTH)\n weights = self._get_weight(reaction)\n # Add lhs aggregates and connect\n for lhs_cmp, lhs_type in zip([i.string() for i in reactants[0]],\n [i.name for i in reactant_types[0]]):\n if lhs_cmp not in self.graph:\n self.graph.add_node(lhs_cmp, type=lhs_type)\n required_cmps_lhs = [s.string() for s in reactants[0]]\n required_cmps_lhs.remove(lhs_cmp)\n self.graph.add_edge(lhs_cmp, rxn_nodes[0], weight=weights[0], required_compounds=required_cmps_lhs,\n required_compound_costs=None)\n self.graph.add_edge(rxn_nodes[1], lhs_cmp, weight=0.0, required_compounds=None)\n # Add rhs aggregates and connect\n for rhs_cmp, rhs_type in zip([i.string() for i in reactants[1]],\n [i.name for i in reactant_types[1]]):\n if rhs_cmp not in self.graph:\n self.graph.add_node(rhs_cmp, type=rhs_type)\n required_cmps_rhs = [s.string() for s in reactants[1]]\n required_cmps_rhs.remove(rhs_cmp)\n self.graph.add_edge(rhs_cmp, rxn_nodes[1], weight=weights[1], required_compounds=required_cmps_rhs,\n required_compound_costs=None)\n self.graph.add_edge(rxn_nodes[0], rhs_cmp, weight=0.0, required_compounds=None)\n\n # # # Loop over reaction nodes to add required compounds info to downwards edges; might be unnecessary\n node_index = 1\n for node in rxn_nodes:\n for key in self.graph[node].keys():\n self.graph.edges[node, key]['required_compounds'] = \\\n self.graph.edges[key, rxn_nodes[node_index]]['required_compounds']\n node_index -= 1","def ry(self, q0, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_Y, qid=[q0], phase=phase, ctrl=ctrl)\n return self","def __init__(self):\n\n # The Microsoft XBox 360 Wired controller has 11 buttons and 8 axes.\n # Buttons can be 0 (not pressed) or 1 (pressed)\n # Axes are floats and range between -1 and 1. Note that for LT and RT, their \"not pressed\" value is 1 and for the others it is 0. Cross keys only have values -1, 0, and 1. The others have be any value in between -1 and 1.\n num_buttons = 11\n num_axes = 8\n self.inputs = [0 for i in range(num_buttons + num_axes)]\n self.inputs[JoyInput.LT] = self.inputs[JoyInput.RT] = 1\n\n # Dictionary of saved inputs. If an input is not currently saved, you must set it to None.\n # For example, the LS_Y (\"left stick Y\") axis may be saved in self.saved[JoyInput.LS_Y]\n self.saved = {\n JoyInput.LS_Y: None,\n Joystick.RS_ANGLE: None,\n }\n\n # Field variables\n self.depth_state = None # stores the depth state\n self.depth_last_received = 0 # how long since the last depth state callback\n self.depth_pwm_input = 0 # tracks pwm given to depth thrusters\n\n # ROS Subscribers\n rospy.Subscriber(\"/joy\", Joy, self.joy_callback)\n rospy.Subscriber(Topic.YAW_STATE, Float64, self.yaw_state_callback)\n rospy.Subscriber(Topic.DEPTH_STATE, Float64, self.depth_state_callback)\n rospy.Subscriber(Topic.YAW_SETPOINT, Float64, self.yaw_setpoint_callback)\n rospy.Subscriber(Topic.DEPTH_SETPOINT, Int16, self.depth_setpoint_callback)\n\n # ROS Publishers\n # self.topics is a dictionary of dictionaries.\n # 'publisher' contains the rospy.Publisher()\n # 'msg' contains the Int16(), Float64(), or Bool() related to the publisher\n # Use self.publish() rather than using self.topics directly.\n self.topics = {\n Topic.YAW_PWM: {'publisher':rospy.Publisher(Topic.YAW_PWM, Int16, queue_size=10), 'msg':Int16()},\n Topic.YAW_PWM_FEEDBACK: {'publisher':rospy.Publisher(Topic.YAW_PWM_FEEDBACK, Int16, queue_size=10), 'msg':Int16()},\n Topic.YAW_PID: {'publisher':rospy.Publisher(Topic.YAW_PID, Bool, queue_size=10), 'msg':Bool()},\n Topic.YAW_SETPOINT: {'publisher':rospy.Publisher(Topic.YAW_SETPOINT, Float64, queue_size=10), 'msg':Float64()},\n\n Topic.DEPTH_PWM: {'publisher':rospy.Publisher(Topic.DEPTH_PWM, Int16, queue_size=10), 'msg':Int16()},\n Topic.DEPTH_PID: {'publisher':rospy.Publisher(Topic.DEPTH_PID, Bool, queue_size=10), 'msg':Bool()},\n Topic.DEPTH_SETPOINT: {'publisher':rospy.Publisher(Topic.DEPTH_SETPOINT, Int16, queue_size=10), 'msg':Int16()},\n }","def add_frame_shift(self, basis, axis_settings):\n angle, axis = angle_and_axis(basis)\n\n if angle == 0:\n axis = (0,0,1)\n\n if basis.include_translation:\n translation = basis.translation\n else:\n translation = (0,0,0)\n\n self.add_row([basis.axis_name,\"rotation\",\"detector\",basis.depends_on,\n str(axis[0]),str(axis[1]),str(axis[2]),\n str(translation[0]),\n str(translation[1]),\n str(translation[2]),\n basis.equipment_component])\n\n axis_settings.append([basis.axis_name, \"FRAME1\", str(angle), \"0\"])","def rotate(self,X):\n alpha = random.rand() * 2*pi\n\n beta = np.arccos(1.0-2*random.rand())\n psi = random.rand() * 2*pi\n\n R = Rotator.rotation_matrix(alpha,beta,psi)\n return np.dot(R,X)","def gyro_datarate(self):\r\n\t\tGYRO_DATARATE = (LSM330_GYRO_DR_95 | LSM330_GYRO_BW_12_5 | LSM330_GYRO_ND | LSM330_GYRO_XAXIS | LSM330_GYRO_YAXIS | LSM330_GYRO_ZAXIS)\r\n\t\tbus.write_byte_data(LSM330_GYRO_ADDRESS, LSM330_CTRL_REG1_G, GYRO_DATARATE)","def __rshift__(self, other):\n self.connect(other)","def __rx(self,length):\n remaining=length\n out=bytearray()\n if self._rx_cnt>0 and (0==(self._rx_cnt%self.com.bufferlen)):\n self.com.tx_ack()\n rxlen = min(remaining,self.com.bufferlen-(self._rx_cnt%self.com.bufferlen))\n #print(\"first_rxlen=\",rxlen,flush=True)\n dat = self.com.rx(rxlen)\n self._rx_cnt+=rxlen\n remaining -= rxlen\n out += dat\n while(remaining>0):\n self.com.tx_ack()\n rxlen=min(remaining,self.com.bufferlen)\n dat = self.com.rx(rxlen)\n self._rx_cnt+=rxlen\n remaining -= rxlen\n out += dat\n return out","def one_qubit_rotation(self, qubit, symbols):\n # print(symbols, \"hi\")\n return [cirq.rx(symbols[0])(qubit),\n cirq.ry(symbols[1])(qubit),\n cirq.rz(symbols[2])(qubit)]","def get_Grotations(self, x):\n xsh = x.get_shape().as_list()\n angles = [0.,np.pi/2.,np.pi,3.*np.pi/2.]\n rx = []\n for i in range(4):\n # Z4 rotations about the z axis\n perm = [1,0,2,3]\n y = tf.transpose(x, perm=perm)\n y = tf.contrib.image.rotate(y, angles[i])\n y = tf.transpose(y, perm=perm)\n # Rotations in the quotient space (sphere S^2)\n # i) Z4 rotations about y axis\n for j in range(4):\n perm = [2,1,0,3]\n z = tf.transpose(y, perm=perm)\n z = tf.contrib.image.rotate(z, angles[-j])\n z = tf.transpose(z, perm=perm)\n \n rx.append(z)\n # ii) 2 rotations to the poles about the x axis\n perm = [0,2,1,3]\n z = tf.transpose(y, perm=perm)\n z = tf.contrib.image.rotate(z, angles[3])\n z = tf.transpose(z, perm=perm)\n rx.append(z)\n\n z = tf.transpose(y, perm=perm)\n z = tf.contrib.image.rotate(z, angles[1])\n z = tf.transpose(z, perm=perm)\n rx.append(z)\n\n return rx","def right(self, angle):\r\n self.rotation += angle","def rotate(self,angle):\n origin = copy.deepcopy(self._current)\n\n q = [origin.orientation.x,\n origin.orientation.y,\n origin.orientation.z,\n origin.orientation.w] # quaternion nonsense\n\n (roll, pitch, yaw) = euler_from_quaternion(q)\n\n atTarget=False\n\n currentAngle=yaw\n angle=angle+currentAngle\n\n if(angle==currentAngle):\n w=0\n elif(angle>currentAngle):\n w=1\n elif(angle<currentAngle):\n w=-1\n\n move_msg=Twist()\n move_msg.linear.x=0\n move_msg.angular.z=w\n\n\n stop_msg =Twist()\n stop_msg.linear.x=0\n stop_msg.angular.z=0\n\n while(not atTarget and not rospy.is_shutdown()):\n if(currentAngle>=angle):\n atTarget=True\n self._vel_pub.publish(stop_msg)\n print('rotate: stoped')\n else:\n origin = copy.deepcopy(self._current)\n\n q = [origin.orientation.x,\n origin.orientation.y,\n origin.orientation.z,\n origin.orientation.w] # quaternion nonsense\n\n (roll, pitch, yaw) = euler_from_quaternion(q)\n\n currentAngle=yaw\n self._vel_pub.publish(move_msg)\n rospy.sleep(.15)\n print('rotate: moving')\n print('angle: '+str(angle)+'currentAngle: '+str(currentAngle))","def TAY(self, *_):\n self.reg.Y = self.reg.A\n self.reg.N = self.reg.Y << 7\n self.reg.Z = self.reg.Y == 0","def rotating_frame_transformation_operators(operator, t: float, H):\n\n U_RF = (1j*H*t).expm()\n\n return U_RF * H * U_RF.dag()","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def YY(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.YY, qubit_expr)","def yy(target1: QubitInput, target2: QubitInput, angle: float) -> Instruction:\n return Instruction(YY(angle), target=[target1, target2])","def __init__(self):\n self.rot_axis = 1","def startRotatingRight(self,event):\n self.isRotatingRight=True","def setRxConvolved(self, rx_convolved):\n \n self.rx_convolved = rx_convolved","def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self","def ry(self, angle: float) -> \"Mate\":\n a = angle / 180 * pi\n self.x_dir = Mate._rotate(self.x_dir, self.y_dir, a)\n self.z_dir = Mate._rotate(self.z_dir, self.y_dir, a)\n return self","def __frame_rx(self):\n self._rx_cnt=0\n flbytes = self.__rx(self.LENLEN)\n fl = int.from_bytes(flbytes[0:self.LENLEN],byteorder='little',signed=False)\n remaining = fl - len(flbytes)\n\n #print(\"flbytes:\",Utils.hexstr(flbytes))\n #print(\"fl=%d, remaining=%d\"%(fl,remaining),flush=True)\n\n data = flbytes+self.__rx(remaining)\n #remove padding\n data = data[0:fl]\n\n if self._spy_frame_rx is not None:\n self._spy_frame_rx(data)\n\n return data","def TXA(self, *_):\n self.reg.A = self.reg.X\n self.reg.N = self.reg.A << 7\n self.reg.Z = self.reg.A == 0","def Rx(theta,M):\n M = np.array(M)\n n = M.shape[0]\n o = (360. - (theta-90.))*pi/180.\n R = np.array([[1., 0, 0], [0., np.cos(o), -np.sin(o)],[0., np.sin(o), np.cos(o)]])\n if len(M.shape) > 1:\n Mn = []\n for i in range(n):\n pn = R.dot(M[i])\n Mn.append(pn)\n Mn = np.array(Mn)\n else: \n pn = R.dot(M)\n Mn = pn\n return Mn","def TAX(self, *_):\n self.reg.X = self.reg.A\n self.reg.N = self.reg.X << 7\n self.reg.Z = self.reg.X == 0","def ry(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\n return self.rotate(ry=angle, center=center)","def TSX(self, *_):\n self.reg.X = self.reg.S\n self.reg.N = self.reg.X << 7\n self.reg.Z = self.reg.X == 0","def reverseXZrotation(self):\n rot = np.zeros((3, 3), dtype = 'float64')\n rot[0, 0] = np.cos(self.currtheta)\n rot[0, 1] = -np.sin(self.currtheta)\n rot[0, 2] = 0.0\n rot[1, 0] = np.sin(self.currtheta) * np.cos(self.currphi)\n rot[1, 1] = np.cos(self.currtheta) * np.cos(self.currphi)\n rot[1, 2] = - np.sin(self.currphi)\n rot[2, 0] = np.sin(self.currtheta) * np.sin(self.currphi)\n rot[2, 1] = np.cos(self.currtheta) * np.sin(self.currphi)\n rot[2, 2] = np.cos(self.currphi)\n\n self.ds = np.dot(rot, self.ds1)","def rotate_orbit(self):\n try:\n ang = self.orbit_speed * self.time_scale / self.refresh_rate\n self.obj.rotate(angle=ang, axis=vector(0, 1, 0), origin=self.star.obj.pos)\n self.sum_ang += ang\n except ZeroDivisionError:\n print(\"ERROR: REFRESH_RATE is 0\")\n except (AttributeError, TypeError):\n print(\"ERROR: wrong arguments type while initializing!!\")","def roll_pitch_controller(self, acceleration_cmd, attitude, thrust_cmd):\n #Calculate rotation matrix \n R = euler2RM(attitude[0], attitude[1], attitude[2])\n c_d = thrust_cmd/DRONE_MASS_KG\n \n if thrust_cmd > 0.0:\n target_R13 = -np.clip(acceleration_cmd[0].item()/c_d, -self.max_tilt, self.max_tilt) #-min(max(acceleration_cmd[0].item()/c_d, -self.max_tilt), self.max_tilt)\n target_R23 = -np.clip(acceleration_cmd[1].item()/c_d, -self.max_tilt, self.max_tilt) #-min(max(acceleration_cmd[1].item()/c_d, -self.max_tilt), self.max_tilt)\n \n p_cmd = (1/R[2, 2]) * \\\n (-R[1, 0] * self.Kp_roll * (R[0, 2]-target_R13) + \\\n R[0, 0] * self.Kp_pitch * (R[1, 2]-target_R23))\n q_cmd = (1/R[2, 2]) * \\\n (-R[1, 1] * self.Kp_roll * (R[0, 2]-target_R13) + \\\n R[0, 1] * self.Kp_pitch * (R[1, 2]-target_R23))\n else: # Otherwise command no rate\n print(\"negative thrust command\")\n p_cmd = 0.0\n q_cmd = 0.0\n thrust_cmd = 0.0\n return np.array([p_cmd, q_cmd])","def TYA(self, *_):\n self.reg.A = self.reg.Y\n self.reg.N = self.reg.A << 7\n self.reg.Z = self.reg.A == 0","def startAngMovementY(self):\n self.boolrot[1] = True","def rotate(self, angle, axes=(1, 0), reshape=False):\n rotated_data = interpolation.rotate(self.unmasked_data, angle,\n axes=axes, reshape=reshape,\n order=1, cval=numpy.nan)\n if reshape:\n extension = []\n for (rs, s) in zip(rotated_data.shape, self.shape):\n ext_total = rs - s\n ext_start = ext_total // 2\n ext_end = ext_total - ext_start\n extension.append((ext_start, ext_end))\n new_bset = self.bset.extend(extension)\n else:\n new_bset = self.bset\n\n return type(self)(rotated_data, new_bset)","def rotate():\n if counter == counter.max - 1:\n rotator.next = concat(rotator[3:], rotator[3])\n counter.next = 0\n else:\n counter.next = counter + 1\n\n # set initial bits\n if rotator == 0:\n rotator.next = 1","def rot_x_rad(self):\n return self._rot_x_rad","def xy(target1: QubitInput, target2: QubitInput, angle: float) -> Instruction:\n return Instruction(XY(angle), target=[target1, target2])","def rotx(t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[1, 0, 0], [0, c, -s], [0, s, c]])","def circuit_one_qubit_one_param_rx(inpt):\n qml.RX(inpt[0], wires=0)\n return qml.expval(qml.PauliZ(0))","def rotx(t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[1, 0, 0],\n [0, c, -s],\n [0, s, c]])","def rotx(t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[1, 0, 0],\n [0, c, -s],\n [0, s, c]])","def rotx(t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[1, 0, 0],\n [0, c, -s],\n [0, s, c]])","def rotx(t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[1, 0, 0],\n [0, c, -s],\n [0, s, c]])","def line():\n tt.left(90)\n tt.down()\n tt.forward(50)\n tt.up()\n tt.right(90)\n tt.forward(10)\n tt.right(90)\n tt.forward(50)\n tt.left(90)","def _tk1_to_rotations(a: float, b: float, c: float) -> Circuit:\n circ = Circuit(1)\n circ.Rz(c, 0).Rx(b, 0).Rz(a, 0)\n return circ","def rotate(self, angle, axis):\r\n R=self.rotation(angle, axis)\r\n self.mlist = (self*R).mlist\r\n return self","def setRxTime(self, rx_time):\n self.rx_time = rx_time","def interconnect(self):\n assert len(self._readdata) == len(self._readdatavalid)\n ndevs = len(self._readdata)\n av = self\n\n @always_seq(self.clk.posedge, reset=self.reset)\n def rtl_or_combine():\n rddats, valids, waits = 0, 0, 0\n for ii in range(ndevs):\n rddats = rddats | av._readdata[ii]\n valids = valids | av._readdatavalid[ii]\n waits = waits | av._waitrequest[ii]\n\n av.readdata.next = rddats\n av.readdatavalid.next = valids\n av.waitrequest.next = waits\n\n return rtl_or_combine","def rtl_state_and_more():\n if not cso.enable:\n state.next = states.idle\n bcnt.next = 0\n treg.next = 0\n \n itx.read.next = False\n irx.write.next = False\n\n x_sck.next = False\n x_ss.next = False\n else:\n if not cso.freeze:\n # ~~~~ Idle state ~~~~\n if state == states.idle:\n bcnt.next = 7\n treg.next = itx.read_data\n x_sck.next = cso.clock_polarity\n irx.write.next = False\n \n if not itx.empty and not irx.full:\n itx.read.next = True\n x_ss.next = False\n if cso.clock_phase: # Clock in on second phase\n state.next = states.wait_hclk\n else: # Clock in on first phase\n state.next = states.data_in\n else:\n itx.read.next = False\n x_ss.next = True\n\n # ~~~~ Wait half clock period for cpha=1 ~~~~\n elif state == states.wait_hclk:\n itx.read.next = False\n irx.write.next = False\n if ena:\n x_sck.next = not x_sck\n state.next = states.data_in\n\n # ~~~~ Clock data in (and out) ~~~~\n elif state == states.data_in:\n itx.read.next = False\n irx.write.next = False\n if ena: # clk div\n x_sck.next = not x_sck\n rreg.next = concat(rreg[7:0], x_miso)\n \n if cso.clock_phase and bcnt == 0:\n irx.write.next = True\n if itx.empty or irx.full:\n state.next = states.end\n else:\n state.next = states.data_change\n else:\n state.next = states.data_change\n\n # ~~~~ Get ready for next byte out/in ~~~~\n elif state == states.data_change:\n itx.read.next = False\n irx.write.next = False\n if ena:\n x_sck.next = not x_sck\n if bcnt == 0: \n if not cso.clock_phase:\n irx.write.next = True\n \n if itx.empty or irx.full:\n state.next = states.end\n else: # more data to transfer\n bcnt.next = 7\n state.next = states.data_in\n itx.read.next = True\n treg.next = itx.read_data\n else:\n treg.next = concat(treg[7:0], intbv(0)[1:])\n bcnt.next = bcnt - 1 \n state.next = states.data_in\n\n # ~~~~ End state ~~~~\n elif state == states.end:\n itx.read.next = False\n irx.write.next = False\n if ena: # Wait half clock cycle go idle\n state.next = states.idle\n\n # Shouldn't happen, error in logic\n else:\n state.next = states.idle\n assert False, \"SPI Invalid State\"","def __init__(self):\n\n\t###\n\t#subscribers for takeoff and landing \n\n\tself.sub_land = rospy.Subscriber('/ardrone/land', \n Empty,\n self.land)\n\n\tself.sub_takeoff = rospy.Subscriber('/ardrone/takeoff', \n Empty,\n self.takeoff)\n\t###\n\n \n # Desired roll and pitch in radians, yaw rate in radians per second, and\n # climb rate in meters per second\n self.desired_roll = 0\n self.desired_pitch = 0\n self.desired_yaw_rate = 0\n self.desired_climb_rate = 0\n \n # Unit commands for controlling a quadrotor. Commands are in following \n # order: [front_left, front_right, rear_left, rear_right]\n self.unit_hover_cmd = np.array([1., 1., 1., 1.])\n self.unit_roll_cmd = np.array([1., -1., 1., -1.])\n self.unit_pitch_cmd = np.array([-1., -1., 1., 1.])\n self.unit_yaw_cmd = np.array([-1., 1., 1., -1.])\n \n # Onboard controller gains\n self.roll_Pgain = 2.5\n self.roll_Igain = 1.0\n self.roll_Dgain = 1.0\n \n self.pitch_Pgain = 2.5\n self.pitch_Igain = 1.0\n self.pitch_Dgain = 1.0\n \n self.yaw_rate_Pgain = 2.0\n self.yaw_rate_Igain = 0.0\n self.yaw_rate_Dgain = 0.0\n \n self.climb_Pgain = 35.0\n self.climb_Igain = 10.0\n self.climb_Dgain = 0.0\n \n # Motor speed which produces hover\n self.hover_speed = 70.0\n \n # Internal state\n self.internal_state = TransformStamped()\n self.internal_roll_error = 0.0\n self.internal_pitch_error = 0.0\n self.internal_yaw_error = 0.0\n self.internal_climb_error = 0.0\n \n self.internal_old_roll_error = 0.0\n self.internal_old_pitch_error = 0.0\n self.internal_old_yaw_rate_error = 0.0\n self.internal_old_climb_rate_error = 0.0\n \n self.yaw_old = 0.0\n self.z_old = 0.0\n \n # Motor speed envelope\n self.motor_cmd_min = 10\n self.motor_cmd_max = 100","def set_scan_rotation(self, angle):\n raise NotImplementedError","def Rmx(angle=0, units='deg'):\n\n if(units=='deg'):\n angle = angle*pi/180\n\n C = np.cos(angle)\n S = np.sin(angle)\n\n M = np.identity(3)\n\n M[1,1] = +C\n M[1,2] = +S\n M[2,1] = -S\n M[2,2] = +C\n\n return M","def rotate(self, axis, theta):\n return NotImplemented","def rz(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\n return self.rotate(rz=angle, center=center)","def rot(n, x, y, rx, ry):\n if ry == 0:\n if rx == 1:\n x = (n-1) - x\n y = (n-1) - y\n t = x\n x = y\n y = t\n return x, y","def rotate(self, theta, legs):\n U, onew = rotationTensor(theta, self.symmetries, legs)\n B = U @ self\n new = list(onew)\n old = list(legs)\n if B.internallegs != self.internallegs:\n old.append(self.internallegs[0])\n new.append(B.internallegs[0])\n B.swaplegs({n: o for o, n in zip(old, new)})\n return B.couplingAddapt(self.coupling)","def setPlotRotation(ang, x,y):\n dislin.trfrot(ang,x,y)","def two_qubit_rotation(self, bits, symbols):\n circuit = cirq.Circuit()\n circuit += cirq.Circuit(self.one_qubit_rotation(bits[0], symbols[0:3]))\n circuit += cirq.Circuit(self.one_qubit_rotation(bits[1], symbols[3:6]))\n circuit += [cirq.ZZ(*bits)**symbols[6]]\n circuit += [cirq.YY(*bits)**symbols[7]]\n circuit += [cirq.XX(*bits)**symbols[8]]\n circuit += cirq.Circuit(self.one_qubit_rotation(bits[0], symbols[9:12]))\n circuit += cirq.Circuit(self.one_qubit_rotation(bits[1], symbols[12:]))\n return circuit","def apply_rotation_x(self, eta=0.0 ):\n \n eta = radians(eta)\n new_rotation_matrix = [[ 1 , 0 , 0 ],\n [ 0 , +cos(eta) , -sin(eta) ],\n [ 0 , +sin(eta) , +cos(eta) ]] \n \n self.rotation_matrix_exp = np.dot( new_rotation_matrix, self.rotation_matrix_exp )","def _rotate_(self, x: np.array, m: np.array) -> (np.array, np.array):\n # get a random angle\n angle = np.random.randint(0, self.rotate)\n # get a random sign for the angle\n sign = np.random.randint(0, 2)\n x = rotate(x, -sign * angle, reshape=False)\n m = rotate(m, -sign * angle, axes=(0, 1),\n mode='nearest',\n reshape=False)\n return x, m","def rotate(self, rx: float = 0, ry: float = 0, rz: float = 0,\n center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\n transform = self._local_transform\n\n if center is None:\n center_point = self._origin\n elif isinstance(center, Point3D):\n center_point = center\n elif isinstance(center, Point):\n center_point = center.point\n else:\n center_coordinates = list(center)[0:3]\n while len(center_coordinates) < 3:\n center_coordinates.append(0)\n center_point = Point3D.create(*center_coordinates)\n\n if rx != 0:\n rotation = Matrix3D.create()\n rotation.setToRotation(math.radians(rx), self._pos_x, center_point)\n transform.transformBy(rotation)\n if ry != 0:\n rotation = Matrix3D.create()\n rotation.setToRotation(math.radians(ry), self._pos_y, center_point)\n transform.transformBy(rotation)\n if rz != 0:\n rotation = Matrix3D.create()\n rotation.setToRotation(math.radians(rz), self._pos_z, center_point)\n transform.transformBy(rotation)\n self._reset_cache()\n return self","def lrbt_rot(self):\n l, r, b, t = self._ext[0], self._ext[1], self._ext[2], self._ext[3]\n if self.__rot90 % 4 == 1: # -90deg\n self._ext = [b, t, l, r]\n elif self.__rot90 % 4 == 2: # -180deg\n self._ext = [r, l, t, b]\n elif self.__rot90 % 4 == 3: # -270deg\n self._ext = [t, b, r, l]"],"string":"[\n \"def rx(self, angle: float) -> \\\"Mate\\\":\\n a = angle / 180 * pi\\n self.y_dir = Mate._rotate(self.y_dir, self.x_dir, a)\\n self.z_dir = Mate._rotate(self.z_dir, self.x_dir, a)\\n return self\",\n \"def rx(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\\n return self.rotate(angle, center=center)\",\n \"def _r_x(angle: tf.Tensor) -> tf.Tensor:\\n cos = tf.cos(tf.multiply(angle, tf.constant(0.5, dtype=tf.float64)))\\n sin = tf.sin(tf.multiply(angle, tf.constant(0.5, dtype=tf.float64)))\\n sin_complex = tf.complex(tf.constant(0, dtype=tf.float64), sin)\\n cos_complex = tf.complex(cos, tf.constant(0, dtype=tf.float64))\\n rx = tf.stack([[cos_complex, -sin_complex], [-sin_complex, cos_complex]])\\n\\n return rx\",\n \"def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def rx(self):\\n cmd = Command()\\n cmd.set_num(0x1C)\\n cmd.set_subcmd_num(0x00)\\n cmd.set_data([0x00])\\n self.connection.send_cmd(cmd.render())\",\n \"def rx(target: QubitInput, angle: float) -> Iterable[Instruction]:\\n return [Instruction(Rx(angle), target=qubit) for qubit in QubitSet(target)]\",\n \"def Rx(theta, units='deg'):\\n if units == 'deg':\\n theta = np.deg2rad(theta)\\n\\n return np.mat([[1, 0, 0],\\n [0, np.cos(theta), -np.sin(theta)],\\n [0, np.sin(theta), np.cos(theta)]\\n ],\\n dtype='f8'\\n )\",\n \"def rx(self, rx):\\n\\n self.logger.debug(\\\"In 'rx' setter.\\\")\\n\\n self._rx = rx\",\n \"def rot_x(angle):\\n sangle = math.sin(angle)\\n cangle = math.cos(angle)\\n rx = np.array([[1.0, 0.0, 0.0],\\n [0.0, cangle, sangle],\\n [0.0, -sangle, cangle]])\\n return rx\",\n \"def apply_Rx(psi, theta, i, parametrize=False, **gate_opts):\\n mtags = _merge_tags({'RX'}, gate_opts)\\n if parametrize:\\n G = ops.PArray(rx_gate_param_gen, (float(theta),))\\n else:\\n G = qu.Rx(float(theta))\\n psi.gate_(G, int(i), tags=mtags, **gate_opts)\",\n \"def Rx(q):\\n sin_q, cos_q = sin(q), cos(q)\\n return numpy.matrix([\\n [1, 0, 0, 0],\\n [0, cos_q, sin_q, 0],\\n [0, -sin_q, cos_q, 0],\\n [0, 0, 0, 1],\\n ])\",\n \"def read_rotor(self):\\n self.sig_a = self.pin_a.read_digital()\\n self.sig_b = self.pin_b.read_digital()\\n # catch the rising edge of A\\n if self.sig_a and not self.old_sig_a:\\n # if b is also high, clockwise\\n if self.sig_b:\\n self.x += 1\\n\\n else:\\n self.x -= 1\\n if self.x > 9:\\n self.x = 0\\n elif self.x < 0:\\n self.x = 9\\n self.old_sig_a = self.sig_a\\n return self.x\",\n \"def AffineRx(theta, units='deg'):\\n if units == 'deg':\\n theta = np.deg2rad(theta)\\n\\n return np.mat([[1, 0, 0, 0],\\n [0, np.cos(theta), -np.sin(theta), 0],\\n [0, np.sin(theta), np.cos(theta), 0],\\n [0, 0, 0, 1]\\n ],\\n dtype='f8'\\n )\",\n \"def startAngMovementX(self):\\n self.boolrot[0] = True\",\n \"def circuit_one_qubit_one_param_rx_ry(inpt):\\n qml.RX(inpt[0], wires=0)\\n qml.RY(inpt[0], wires=0)\\n return qml.expval(qml.PauliZ(0))\",\n \"def is_rx(self):\\n return not self.is_tx\",\n \"def rotate_axis(self):\\n try:\\n self.obj.rotate(angle=self.rotation_speed * self.time_scale / self.refresh_rate, axis=vector(0, 1, 0))\\n except ZeroDivisionError:\\n print(\\\"ERROR: REFRESH_RATE is 0\\\")\\n except (AttributeError, TypeError):\\n print(\\\"ERROR: wrong arguments type while initializing!!\\\")\",\n \"def _decompose_rotation(self, cmd):\\n \\n axis = None\\n angle = 0\\n gate_name = str(cmd.gate)\\n\\n if \\\"Rz\\\" in gate_name:\\n axis = 'z'\\n elif \\\"Rx\\\" in gate_name:\\n axis = 'x'\\n elif \\\"Ry\\\" in gate_name:\\n axis = 'y' \\n\\n angle = gate_name[gate_name.find(\\\"(\\\")+1:gate_name.find(\\\")\\\")]\\n\\n decomposition = subprocess.check_output(\\\"./gridsynth \\\" + angle, shell=True)[:-1]\\n new_sequence = self._process_decomposition(str(decomposition),cmd.qubits[0])\\n return new_sequence\",\n \"def rx_beacon_packet(self): \\n self.beacon.make_packet()\\n rx_packet = self.beacon.tx_packet()\\n rx_time = np.float128('%.20f'%(time.time()))\\n if self.DEBUG:\\n print 'rx_time: ', repr(rx_time)\\n\\n self.data.set_timestamp_base(rx_time)\\n self.data.set_beacon_packet(rx_packet)\",\n \"def cxr(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def rotate(x_or_y,degree):\\r\\n\\r\\n #axis=0 represents x-axis\\r\\n #axis=1 represents y-axis\\r\\n \\r\\n if x_or_y=='X' or x_or_y=='x':\\r\\n axis=0\\r\\n elif x_or_y=='Y' or x_or_y=='y':\\r\\n axis=1\\r\\n elif x_or_y==0:\\r\\n axis=0\\r\\n elif x_or_y==1:\\r\\n axis=1\\r\\n else:\\r\\n print(\\\"Illeagel argument in rotate_degree\\\")\\r\\n return\\r\\n\\r\\n #decide which pins to use accroding to the axis\\r\\n #info is for debug used it can be eliminated\\r\\n if axis==0:\\r\\n info=\\\"x-axis\\\"\\r\\n stepsPin=xCwPin;\\r\\n cwOrCcwPin=xCcwPin\\r\\n elif axis==1:\\r\\n info=\\\"y-axis\\\"\\r\\n stepsPin=yCwPin;\\r\\n cwOrCcwPin=yCcwPin\\r\\n\\r\\n if degree>0:\\r\\n info=info+\\\" rotate cw\\\"\\r\\n GPIO.output(cwOrCcwPin, True) #cw\\r\\n elif degree<0:\\r\\n info=info+\\\" rotate ccw\\\"\\r\\n GPIO.output(cwOrCcwPin, False) #ccw\\r\\n elif degree==0:\\r\\n return\\r\\n\\r\\n tmp=abs(degree)/0.36\\r\\n steps=round(tmp)\\r\\n\\r\\n info=info+\\\" for \\\"+str(degree)+\\\" degrees \\\"+str(steps)+\\\" steps\\\"\\r\\n\\r\\n i=0\\r\\n while i<steps:\\r\\n GPIO.output(stepsPin, True)\\r\\n time.sleep(0.001)\\r\\n GPIO.output(stepsPin, False)\\r\\n time.sleep(0.05)\\r\\n i=i+1\\r\\n #GPIO.output(cwOrCcwPin, True)\\r\\n\\r\\n if SHOW_ROTATE:\\r\\n print(info)\",\n \"def RXX(self, theta:Union[int, float], qubit_expr): \\n self.apply_gate_operation(RYY(theta), qubit_expr)\",\n \"def XXRotation(angle):\\r\\n return SuperPosition([IGate * IGate, XGate * XGate],\\r\\n [np.cos(angle), np.sin(angle) * 1j],\\r\\n 'R_XX({})'.format(angle))\",\n \"def rotate_x(angle):\\n log.dev(\\\"lib.mathp.rotate_x is deprecated. Use lib.rotation.R1 instead.\\\")\\n\\n cosA = np.cos(angle)\\n sinA = np.sin(angle)\\n R = np.array([[1, 0, 0], [0, cosA, sinA], [0, -sinA, cosA]])\\n return R\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def ROT(self):\\n # The maximum update amount for these element\\n # no dt since YawRate is already mult by dt\\n YawRate_DELTA = (self.YawRate_LIMITS[1] -\\n self.YawRate_LIMITS[0]) / (2.0)\\n\\n # Add either positive or negative or zero delta for each\\n # NOTE: 'High' is open bracket ) so the max is 1\\n YawRate_DIRECTION = np.random.randint(-1, 2, 1)[0]\\n\\n # Now, modify modifiable params AND CLIP\\n self.YawRate += YawRate_DIRECTION * YawRate_DELTA\\n self.YawRate = np.clip(self.YawRate, self.YawRate_LIMITS[0],\\n self.YawRate_LIMITS[1])\",\n \"def createBtnCmd(self, *args):\\r\\n self.cone = cmds.polyCone()\\r\\n cmds.setAttr('%s.rotateX' % self.cone[0], 90)\",\n \"def rotate(X):\\n return X\",\n \"def roll(self):\\n rate = rospy.Rate(50)\\n while not rospy.is_shutdown():\\n self.rc_lock.acquire()\\n rc = self.rc_message\\n self.rc_lock.release()\\n\\n px2_message = PX2()\\n px2_message.Mode = 2\\n px2_message.header.stamp = rospy.Time.now()\\n\\n if rc.enable:\\n px2_message.TarSteeringAngle = rc.steering_angle\\n\\n # Mock rc angle\\n self.px2_lock.acquire()\\n px2_message = self.px2_message\\n self.px2_lock.release()\\n\\n px2_message.TarAcce = rc.acceleration\\n px2_message.Mode = 2\\n if px2_message.TarAcce < 0:\\n px2_message.DecToStop = 0\\n else:\\n px2_message.DecToStop = 1\\n\\n else:\\n self.px2_lock.acquire()\\n target_angle = self.px2_message.TarSteeringAngle\\n target_speed = self.px2_message.TarAcce\\n self.px2_lock.release()\\n\\n self.ecm_lock.acquire()\\n current_speed = self.ecm_message.VehicleSpd\\n self.ecm_lock.release()\\n\\n self.sas_lock.acquire()\\n angle = self.sas_message.SteeringWheelAngle\\n angle_sign = self.sas_message.SteeringWheelAngleSign\\n if angle_sign == 1:\\n angle = -angle\\n self.sas_lock.release()\\n\\n self.inspva_lock.acquire()\\n longitude = self.inspva_message.longitude\\n latitude = self.inspva_message.latitude\\n heading = self.inspva_message.azimuth\\n self.inspva_lock.release()\\n\\n px2_message.TarAcce = target_acce \\n px2_message.TarSteeringAngle = target_angle\\n\\n self.px2_pub.publish(px2_message)\\n rate.sleep()\",\n \"def timer_tick(self, *args):\\n # Generate a new number and increment the tick count\\n\\t #x, y, z=accel.read()\\n\\n # ADXL345 address, 0x53(83)\\n # Select bandwidth rate register, 0x2C(44)\\n #\\t\\t0x0A(10)\\tNormal mode, Output data rate = 100 Hz\\n bus.write_byte_data(0x53, 0x2C, 0x0A)\\n\\n # ADXL345 address, 0x53(83)\\n # Select power control register, 0x2D(45)\\n #\\t\\t0x08(08)\\tAuto Sleep disable\\n bus.write_byte_data(0x53, 0x2D, 0x08)\\n\\n # ADXL345 address, 0x53(83)\\n # Select data format register, 0x31(49)\\n #\\t\\t0x08(08)\\tSelf test disabled, 4-wire interface\\n #\\t\\t\\t\\t\\tFull resolution, Range = +/-2g\\n\\n bus.write_byte_data(0x53, 0x31, 0x08)\\n # time.sleep(0.5)\\n # ADXL345 address, 0x53(83)\\n # Read data back from 0x32(50), 2 bytes\\n # X-Axis LSB, X-Axis MSB\\n\\n data0 = bus.read_byte_data(0x53, 0x32)\\n data1 = bus.read_byte_data(0x53, 0x33)\\n\\n # Convert the data to 10-bits\\n xAccl = ((data1 & 0x03) * 256) + data0\\n\\n if xAccl > 511:\\n xAccl -= 1024\\n # ADXL345 address, 0x53(83)\\n # Read data back from 0x34(52), 2 bytes\\n # Y-Axis LSB, Y-Axis MSB\\n data0 = bus.read_byte_data(0x53, 0x34)\\n data1 = bus.read_byte_data(0x53, 0x35)\\n\\n # Convert the data to 10-bits\\n yAccl = ((data1 & 0x03) * 256) + data0\\n\\n if yAccl > 511:\\n yAccl -= 1024\\n\\n # ADXL345 address, 0x53(83)\\n # Read data back from 0x36(54), 2 bytes\\n # Z-Axis LSB, Z-Axis MSB\\n data0 = bus.read_byte_data(0x53, 0x36)\\n data1 = bus.read_byte_data(0x53, 0x37)\\n\\n # Convert the data to 10-bits\\n zAccl = ((data1 & 0x03) * 256) + data0\\n if zAccl > 511:\\n zAccl -= 1024\\n\\n # Output data to screen\\n # print \\\"Acceleration in X-Axis : %d\\\" %xAccl\\n # print \\\"Acceleration in Y-Axis : %d\\\" %yAccl\\n # print \\\"Acceleration in Z-Axis : %d\\\" %zAccl\\n new_val = zAccl\\n self.num_ticks += 1\\n\\n # grab the existing data, truncate it, and append the new point.\\n # This isn't the most efficient thing in the world but it works.\\n cur_data = self.viewer.data\\n new_data = np.hstack((cur_data[-self.max_num_points+1:], [new_val]))\\n new_index = np.arange(self.num_ticks - len(new_data) + 1,\\n self.num_ticks + 0.01)\\n\\n self.viewer.index = new_index\\n self.viewer.data = new_data\\n return\",\n \"def timer_tick(self, *args):\\n # Generate a new number and increment the tick count\\n # x, y, z=accel.read()\\n\\n # ADXL345 address, 0x53(83)\\n\\n # Select bandwidth rate register, 0x2C(44)\\n\\n #\\t\\t0x0A(10)\\tNormal mode, Output data rate = 100 Hz\\n\\n bus.write_byte_data(0x53, 0x2C, 0x0A)\\n\\n # ADXL345 address, 0x53(83)\\n\\n # Select power control register, 0x2D(45)\\n\\n #\\t\\t0x08(08)\\tAuto Sleep disable\\n\\n bus.write_byte_data(0x53, 0x2D, 0x08)\\n\\n # ADXL345 address, 0x53(83)\\n\\n # Select data format register, 0x31(49)\\n\\n #\\t\\t0x08(08)\\tSelf test disabled, 4-wire interface\\n\\n #\\t\\t\\t\\t\\tFull resolution, Range = +/-2g\\n\\n bus.write_byte_data(0x53, 0x31, 0x08)\\n\\n # time.sleep(0.5)\\n\\n # ADXL345 address, 0x53(83)\\n\\n # Read data back from 0x32(50), 2 bytes\\n\\n # X-Axis LSB, X-Axis MSB\\n\\n data0 = bus.read_byte_data(0x53, 0x32)\\n\\n data1 = bus.read_byte_data(0x53, 0x33)\\n\\n # Convert the data to 10-bits\\n\\n xAccl = ((data1 & 0x03) * 256) + data0\\n\\n if xAccl > 511:\\n xAccl -= 1024\\n\\n # ADXL345 address, 0x53(83)\\n\\n # Read data back from 0x34(52), 2 bytes\\n\\n # Y-Axis LSB, Y-Axis MSB\\n\\n data0 = bus.read_byte_data(0x53, 0x34)\\n\\n data1 = bus.read_byte_data(0x53, 0x35)\\n\\n # Convert the data to 10-bits\\n\\n yAccl = ((data1 & 0x03) * 256) + data0\\n\\n if yAccl > 511:\\n yAccl -= 1024\\n\\n # ADXL345 address, 0x53(83)\\n\\n # Read data back from 0x36(54), 2 bytes\\n\\n # Z-Axis LSB, Z-Axis MSB\\n\\n data0 = bus.read_byte_data(0x53, 0x36)\\n\\n data1 = bus.read_byte_data(0x53, 0x37)\\n\\n # Convert the data to 10-bits\\n\\n zAccl = ((data1 & 0x03) * 256) + data0\\n\\n if zAccl > 511:\\n zAccl -= 1024\\n\\n # Output data to screen\\n\\n # print \\\"Acceleration in X-Axis : %d\\\" %xAccl\\n\\n # print \\\"Acceleration in Y-Axis : %d\\\" %yAccl\\n\\n # print \\\"Acceleration in Z-Axis : %d\\\" %zAccl\\n new_val = xAccl\\n self.num_ticks += 1\\n\\n # grab the existing data, truncate it, and append the new point.\\n # This isn't the most efficient thing in the world but it works.\\n cur_data = self.viewer.data\\n new_data = np.hstack((cur_data[-self.max_num_points + 1:], [new_val]))\\n new_index = np.arange(self.num_ticks - len(new_data) + 1,\\n self.num_ticks + 0.01)\\n\\n self.viewer.index = new_index\\n self.viewer.data = new_data\\n return\",\n \"def rotate(self,X):\\n alpha = random.rand() * 2*pi\\n beta = self.beta_sample()\\n R = Rotator.rotation_matrix(alpha,beta,0.0)\\n X = np.dot(R, X)\\n if self.random_flip and (random.rand() > 0.5):\\n X[2,:] = -X[2,:]\\n X[1,:] = -X[1,:]\\n return X\",\n \"def rotate_x(self,rad):\\n DetElement.rotate_x(self,rad) #python2\\n #super().rotate_x(rad) #python3\\n for tube in self._list_of_tubes:\\n self.__update__update_tube_pos_after_rotation(tube)\\n tube.rotate_x(rad)\",\n \"def rotate(self,X):\\n alpha = random.rand() * 2*pi\\n R = Rotator.rotation_matrix(alpha,0.0,0.0)\\n return np.dot(R,X)\",\n \"def rotate(self,id,x,y,r):\\n if id not in self.elements.keys():\\n print(\\\"Id input not registered! Please check your process\\\")\\n return False\\n element=self.elements[id]\\n state=element.rotate(self.h-1-y,x,-r,self.w,self.h)\\n if state==True:\\n self.canvas=np.ones((self.h,self.w,3),dtype=np.uint8)*255\\n self.sync=False\\n return state\",\n \"def RXX(self, theta:Union[int, float], qubit_expr): \\n self.apply_gate_operation(RXX(theta), qubit_expr)\",\n \"def rotate(self, angle=0.0):\\n # TODO: Implement the rotate function. Remember to record the value of\\n # rotation degree.\\n self.rotDegree = angle\\n self.x = rotate(self.x, angle = angle, axes=(0, 1), reshape=False, \\n output=None, order=3, mode='constant', cval=0.0, prefilter=True)\\n # This rotation isn't working correctly. Get shit for non right anlge rotatations\\n # raise NotImplementedError\\n #######################################################################\\n # #\\n # #\\n # TODO: YOUR CODE HERE #\\n # #\\n # #\\n #######################################################################\",\n \"def spin(rxn_class):\\n return rxn_class[1]\",\n \"def add_rxn(self, reaction: db.Reaction):\\n # Add two rxn nodes\\n rxn_nodes = []\\n reaction_id = reaction.id().string()\\n\\n for i in range(0, 2):\\n # Add rxn node between lhs and rhs compound\\n rxn_node = ';'.join([reaction_id, str(i)])\\n rxn_node += ';'\\n self.graph.add_node(rxn_node, color='rxn_node')\\n rxn_nodes.append(rxn_node)\\n # Convert to strings\\n reactants = reaction.get_reactants(db.Side.BOTH)\\n reactant_types = reaction.get_reactant_types(db.Side.BOTH)\\n weights = self._get_weight(reaction)\\n # Add lhs aggregates and connect\\n for lhs_cmp, lhs_type in zip([i.string() for i in reactants[0]],\\n [i.name for i in reactant_types[0]]):\\n if lhs_cmp not in self.graph:\\n self.graph.add_node(lhs_cmp, type=lhs_type)\\n required_cmps_lhs = [s.string() for s in reactants[0]]\\n required_cmps_lhs.remove(lhs_cmp)\\n self.graph.add_edge(lhs_cmp, rxn_nodes[0], weight=weights[0], required_compounds=required_cmps_lhs,\\n required_compound_costs=None)\\n self.graph.add_edge(rxn_nodes[1], lhs_cmp, weight=0.0, required_compounds=None)\\n # Add rhs aggregates and connect\\n for rhs_cmp, rhs_type in zip([i.string() for i in reactants[1]],\\n [i.name for i in reactant_types[1]]):\\n if rhs_cmp not in self.graph:\\n self.graph.add_node(rhs_cmp, type=rhs_type)\\n required_cmps_rhs = [s.string() for s in reactants[1]]\\n required_cmps_rhs.remove(rhs_cmp)\\n self.graph.add_edge(rhs_cmp, rxn_nodes[1], weight=weights[1], required_compounds=required_cmps_rhs,\\n required_compound_costs=None)\\n self.graph.add_edge(rxn_nodes[0], rhs_cmp, weight=0.0, required_compounds=None)\\n\\n # # # Loop over reaction nodes to add required compounds info to downwards edges; might be unnecessary\\n node_index = 1\\n for node in rxn_nodes:\\n for key in self.graph[node].keys():\\n self.graph.edges[node, key]['required_compounds'] = \\\\\\n self.graph.edges[key, rxn_nodes[node_index]]['required_compounds']\\n node_index -= 1\",\n \"def ry(self, q0, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=ROTATION_Y, qid=[q0], phase=phase, ctrl=ctrl)\\n return self\",\n \"def __init__(self):\\n\\n # The Microsoft XBox 360 Wired controller has 11 buttons and 8 axes.\\n # Buttons can be 0 (not pressed) or 1 (pressed)\\n # Axes are floats and range between -1 and 1. Note that for LT and RT, their \\\"not pressed\\\" value is 1 and for the others it is 0. Cross keys only have values -1, 0, and 1. The others have be any value in between -1 and 1.\\n num_buttons = 11\\n num_axes = 8\\n self.inputs = [0 for i in range(num_buttons + num_axes)]\\n self.inputs[JoyInput.LT] = self.inputs[JoyInput.RT] = 1\\n\\n # Dictionary of saved inputs. If an input is not currently saved, you must set it to None.\\n # For example, the LS_Y (\\\"left stick Y\\\") axis may be saved in self.saved[JoyInput.LS_Y]\\n self.saved = {\\n JoyInput.LS_Y: None,\\n Joystick.RS_ANGLE: None,\\n }\\n\\n # Field variables\\n self.depth_state = None # stores the depth state\\n self.depth_last_received = 0 # how long since the last depth state callback\\n self.depth_pwm_input = 0 # tracks pwm given to depth thrusters\\n\\n # ROS Subscribers\\n rospy.Subscriber(\\\"/joy\\\", Joy, self.joy_callback)\\n rospy.Subscriber(Topic.YAW_STATE, Float64, self.yaw_state_callback)\\n rospy.Subscriber(Topic.DEPTH_STATE, Float64, self.depth_state_callback)\\n rospy.Subscriber(Topic.YAW_SETPOINT, Float64, self.yaw_setpoint_callback)\\n rospy.Subscriber(Topic.DEPTH_SETPOINT, Int16, self.depth_setpoint_callback)\\n\\n # ROS Publishers\\n # self.topics is a dictionary of dictionaries.\\n # 'publisher' contains the rospy.Publisher()\\n # 'msg' contains the Int16(), Float64(), or Bool() related to the publisher\\n # Use self.publish() rather than using self.topics directly.\\n self.topics = {\\n Topic.YAW_PWM: {'publisher':rospy.Publisher(Topic.YAW_PWM, Int16, queue_size=10), 'msg':Int16()},\\n Topic.YAW_PWM_FEEDBACK: {'publisher':rospy.Publisher(Topic.YAW_PWM_FEEDBACK, Int16, queue_size=10), 'msg':Int16()},\\n Topic.YAW_PID: {'publisher':rospy.Publisher(Topic.YAW_PID, Bool, queue_size=10), 'msg':Bool()},\\n Topic.YAW_SETPOINT: {'publisher':rospy.Publisher(Topic.YAW_SETPOINT, Float64, queue_size=10), 'msg':Float64()},\\n\\n Topic.DEPTH_PWM: {'publisher':rospy.Publisher(Topic.DEPTH_PWM, Int16, queue_size=10), 'msg':Int16()},\\n Topic.DEPTH_PID: {'publisher':rospy.Publisher(Topic.DEPTH_PID, Bool, queue_size=10), 'msg':Bool()},\\n Topic.DEPTH_SETPOINT: {'publisher':rospy.Publisher(Topic.DEPTH_SETPOINT, Int16, queue_size=10), 'msg':Int16()},\\n }\",\n \"def add_frame_shift(self, basis, axis_settings):\\n angle, axis = angle_and_axis(basis)\\n\\n if angle == 0:\\n axis = (0,0,1)\\n\\n if basis.include_translation:\\n translation = basis.translation\\n else:\\n translation = (0,0,0)\\n\\n self.add_row([basis.axis_name,\\\"rotation\\\",\\\"detector\\\",basis.depends_on,\\n str(axis[0]),str(axis[1]),str(axis[2]),\\n str(translation[0]),\\n str(translation[1]),\\n str(translation[2]),\\n basis.equipment_component])\\n\\n axis_settings.append([basis.axis_name, \\\"FRAME1\\\", str(angle), \\\"0\\\"])\",\n \"def rotate(self,X):\\n alpha = random.rand() * 2*pi\\n\\n beta = np.arccos(1.0-2*random.rand())\\n psi = random.rand() * 2*pi\\n\\n R = Rotator.rotation_matrix(alpha,beta,psi)\\n return np.dot(R,X)\",\n \"def gyro_datarate(self):\\r\\n\\t\\tGYRO_DATARATE = (LSM330_GYRO_DR_95 | LSM330_GYRO_BW_12_5 | LSM330_GYRO_ND | LSM330_GYRO_XAXIS | LSM330_GYRO_YAXIS | LSM330_GYRO_ZAXIS)\\r\\n\\t\\tbus.write_byte_data(LSM330_GYRO_ADDRESS, LSM330_CTRL_REG1_G, GYRO_DATARATE)\",\n \"def __rshift__(self, other):\\n self.connect(other)\",\n \"def __rx(self,length):\\n remaining=length\\n out=bytearray()\\n if self._rx_cnt>0 and (0==(self._rx_cnt%self.com.bufferlen)):\\n self.com.tx_ack()\\n rxlen = min(remaining,self.com.bufferlen-(self._rx_cnt%self.com.bufferlen))\\n #print(\\\"first_rxlen=\\\",rxlen,flush=True)\\n dat = self.com.rx(rxlen)\\n self._rx_cnt+=rxlen\\n remaining -= rxlen\\n out += dat\\n while(remaining>0):\\n self.com.tx_ack()\\n rxlen=min(remaining,self.com.bufferlen)\\n dat = self.com.rx(rxlen)\\n self._rx_cnt+=rxlen\\n remaining -= rxlen\\n out += dat\\n return out\",\n \"def one_qubit_rotation(self, qubit, symbols):\\n # print(symbols, \\\"hi\\\")\\n return [cirq.rx(symbols[0])(qubit),\\n cirq.ry(symbols[1])(qubit),\\n cirq.rz(symbols[2])(qubit)]\",\n \"def get_Grotations(self, x):\\n xsh = x.get_shape().as_list()\\n angles = [0.,np.pi/2.,np.pi,3.*np.pi/2.]\\n rx = []\\n for i in range(4):\\n # Z4 rotations about the z axis\\n perm = [1,0,2,3]\\n y = tf.transpose(x, perm=perm)\\n y = tf.contrib.image.rotate(y, angles[i])\\n y = tf.transpose(y, perm=perm)\\n # Rotations in the quotient space (sphere S^2)\\n # i) Z4 rotations about y axis\\n for j in range(4):\\n perm = [2,1,0,3]\\n z = tf.transpose(y, perm=perm)\\n z = tf.contrib.image.rotate(z, angles[-j])\\n z = tf.transpose(z, perm=perm)\\n \\n rx.append(z)\\n # ii) 2 rotations to the poles about the x axis\\n perm = [0,2,1,3]\\n z = tf.transpose(y, perm=perm)\\n z = tf.contrib.image.rotate(z, angles[3])\\n z = tf.transpose(z, perm=perm)\\n rx.append(z)\\n\\n z = tf.transpose(y, perm=perm)\\n z = tf.contrib.image.rotate(z, angles[1])\\n z = tf.transpose(z, perm=perm)\\n rx.append(z)\\n\\n return rx\",\n \"def right(self, angle):\\r\\n self.rotation += angle\",\n \"def rotate(self,angle):\\n origin = copy.deepcopy(self._current)\\n\\n q = [origin.orientation.x,\\n origin.orientation.y,\\n origin.orientation.z,\\n origin.orientation.w] # quaternion nonsense\\n\\n (roll, pitch, yaw) = euler_from_quaternion(q)\\n\\n atTarget=False\\n\\n currentAngle=yaw\\n angle=angle+currentAngle\\n\\n if(angle==currentAngle):\\n w=0\\n elif(angle>currentAngle):\\n w=1\\n elif(angle<currentAngle):\\n w=-1\\n\\n move_msg=Twist()\\n move_msg.linear.x=0\\n move_msg.angular.z=w\\n\\n\\n stop_msg =Twist()\\n stop_msg.linear.x=0\\n stop_msg.angular.z=0\\n\\n while(not atTarget and not rospy.is_shutdown()):\\n if(currentAngle>=angle):\\n atTarget=True\\n self._vel_pub.publish(stop_msg)\\n print('rotate: stoped')\\n else:\\n origin = copy.deepcopy(self._current)\\n\\n q = [origin.orientation.x,\\n origin.orientation.y,\\n origin.orientation.z,\\n origin.orientation.w] # quaternion nonsense\\n\\n (roll, pitch, yaw) = euler_from_quaternion(q)\\n\\n currentAngle=yaw\\n self._vel_pub.publish(move_msg)\\n rospy.sleep(.15)\\n print('rotate: moving')\\n print('angle: '+str(angle)+'currentAngle: '+str(currentAngle))\",\n \"def TAY(self, *_):\\n self.reg.Y = self.reg.A\\n self.reg.N = self.reg.Y << 7\\n self.reg.Z = self.reg.Y == 0\",\n \"def rotating_frame_transformation_operators(operator, t: float, H):\\n\\n U_RF = (1j*H*t).expm()\\n\\n return U_RF * H * U_RF.dag()\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def YY(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.YY, qubit_expr)\",\n \"def yy(target1: QubitInput, target2: QubitInput, angle: float) -> Instruction:\\n return Instruction(YY(angle), target=[target1, target2])\",\n \"def __init__(self):\\n self.rot_axis = 1\",\n \"def startRotatingRight(self,event):\\n self.isRotatingRight=True\",\n \"def setRxConvolved(self, rx_convolved):\\n \\n self.rx_convolved = rx_convolved\",\n \"def cxr_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def ry(self, angle: float) -> \\\"Mate\\\":\\n a = angle / 180 * pi\\n self.x_dir = Mate._rotate(self.x_dir, self.y_dir, a)\\n self.z_dir = Mate._rotate(self.z_dir, self.y_dir, a)\\n return self\",\n \"def __frame_rx(self):\\n self._rx_cnt=0\\n flbytes = self.__rx(self.LENLEN)\\n fl = int.from_bytes(flbytes[0:self.LENLEN],byteorder='little',signed=False)\\n remaining = fl - len(flbytes)\\n\\n #print(\\\"flbytes:\\\",Utils.hexstr(flbytes))\\n #print(\\\"fl=%d, remaining=%d\\\"%(fl,remaining),flush=True)\\n\\n data = flbytes+self.__rx(remaining)\\n #remove padding\\n data = data[0:fl]\\n\\n if self._spy_frame_rx is not None:\\n self._spy_frame_rx(data)\\n\\n return data\",\n \"def TXA(self, *_):\\n self.reg.A = self.reg.X\\n self.reg.N = self.reg.A << 7\\n self.reg.Z = self.reg.A == 0\",\n \"def Rx(theta,M):\\n M = np.array(M)\\n n = M.shape[0]\\n o = (360. - (theta-90.))*pi/180.\\n R = np.array([[1., 0, 0], [0., np.cos(o), -np.sin(o)],[0., np.sin(o), np.cos(o)]])\\n if len(M.shape) > 1:\\n Mn = []\\n for i in range(n):\\n pn = R.dot(M[i])\\n Mn.append(pn)\\n Mn = np.array(Mn)\\n else: \\n pn = R.dot(M)\\n Mn = pn\\n return Mn\",\n \"def TAX(self, *_):\\n self.reg.X = self.reg.A\\n self.reg.N = self.reg.X << 7\\n self.reg.Z = self.reg.X == 0\",\n \"def ry(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\\n return self.rotate(ry=angle, center=center)\",\n \"def TSX(self, *_):\\n self.reg.X = self.reg.S\\n self.reg.N = self.reg.X << 7\\n self.reg.Z = self.reg.X == 0\",\n \"def reverseXZrotation(self):\\n rot = np.zeros((3, 3), dtype = 'float64')\\n rot[0, 0] = np.cos(self.currtheta)\\n rot[0, 1] = -np.sin(self.currtheta)\\n rot[0, 2] = 0.0\\n rot[1, 0] = np.sin(self.currtheta) * np.cos(self.currphi)\\n rot[1, 1] = np.cos(self.currtheta) * np.cos(self.currphi)\\n rot[1, 2] = - np.sin(self.currphi)\\n rot[2, 0] = np.sin(self.currtheta) * np.sin(self.currphi)\\n rot[2, 1] = np.cos(self.currtheta) * np.sin(self.currphi)\\n rot[2, 2] = np.cos(self.currphi)\\n\\n self.ds = np.dot(rot, self.ds1)\",\n \"def rotate_orbit(self):\\n try:\\n ang = self.orbit_speed * self.time_scale / self.refresh_rate\\n self.obj.rotate(angle=ang, axis=vector(0, 1, 0), origin=self.star.obj.pos)\\n self.sum_ang += ang\\n except ZeroDivisionError:\\n print(\\\"ERROR: REFRESH_RATE is 0\\\")\\n except (AttributeError, TypeError):\\n print(\\\"ERROR: wrong arguments type while initializing!!\\\")\",\n \"def roll_pitch_controller(self, acceleration_cmd, attitude, thrust_cmd):\\n #Calculate rotation matrix \\n R = euler2RM(attitude[0], attitude[1], attitude[2])\\n c_d = thrust_cmd/DRONE_MASS_KG\\n \\n if thrust_cmd > 0.0:\\n target_R13 = -np.clip(acceleration_cmd[0].item()/c_d, -self.max_tilt, self.max_tilt) #-min(max(acceleration_cmd[0].item()/c_d, -self.max_tilt), self.max_tilt)\\n target_R23 = -np.clip(acceleration_cmd[1].item()/c_d, -self.max_tilt, self.max_tilt) #-min(max(acceleration_cmd[1].item()/c_d, -self.max_tilt), self.max_tilt)\\n \\n p_cmd = (1/R[2, 2]) * \\\\\\n (-R[1, 0] * self.Kp_roll * (R[0, 2]-target_R13) + \\\\\\n R[0, 0] * self.Kp_pitch * (R[1, 2]-target_R23))\\n q_cmd = (1/R[2, 2]) * \\\\\\n (-R[1, 1] * self.Kp_roll * (R[0, 2]-target_R13) + \\\\\\n R[0, 1] * self.Kp_pitch * (R[1, 2]-target_R23))\\n else: # Otherwise command no rate\\n print(\\\"negative thrust command\\\")\\n p_cmd = 0.0\\n q_cmd = 0.0\\n thrust_cmd = 0.0\\n return np.array([p_cmd, q_cmd])\",\n \"def TYA(self, *_):\\n self.reg.A = self.reg.Y\\n self.reg.N = self.reg.A << 7\\n self.reg.Z = self.reg.A == 0\",\n \"def startAngMovementY(self):\\n self.boolrot[1] = True\",\n \"def rotate(self, angle, axes=(1, 0), reshape=False):\\n rotated_data = interpolation.rotate(self.unmasked_data, angle,\\n axes=axes, reshape=reshape,\\n order=1, cval=numpy.nan)\\n if reshape:\\n extension = []\\n for (rs, s) in zip(rotated_data.shape, self.shape):\\n ext_total = rs - s\\n ext_start = ext_total // 2\\n ext_end = ext_total - ext_start\\n extension.append((ext_start, ext_end))\\n new_bset = self.bset.extend(extension)\\n else:\\n new_bset = self.bset\\n\\n return type(self)(rotated_data, new_bset)\",\n \"def rotate():\\n if counter == counter.max - 1:\\n rotator.next = concat(rotator[3:], rotator[3])\\n counter.next = 0\\n else:\\n counter.next = counter + 1\\n\\n # set initial bits\\n if rotator == 0:\\n rotator.next = 1\",\n \"def rot_x_rad(self):\\n return self._rot_x_rad\",\n \"def xy(target1: QubitInput, target2: QubitInput, angle: float) -> Instruction:\\n return Instruction(XY(angle), target=[target1, target2])\",\n \"def rotx(t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[1, 0, 0], [0, c, -s], [0, s, c]])\",\n \"def circuit_one_qubit_one_param_rx(inpt):\\n qml.RX(inpt[0], wires=0)\\n return qml.expval(qml.PauliZ(0))\",\n \"def rotx(t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[1, 0, 0],\\n [0, c, -s],\\n [0, s, c]])\",\n \"def rotx(t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[1, 0, 0],\\n [0, c, -s],\\n [0, s, c]])\",\n \"def rotx(t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[1, 0, 0],\\n [0, c, -s],\\n [0, s, c]])\",\n \"def rotx(t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[1, 0, 0],\\n [0, c, -s],\\n [0, s, c]])\",\n \"def line():\\n tt.left(90)\\n tt.down()\\n tt.forward(50)\\n tt.up()\\n tt.right(90)\\n tt.forward(10)\\n tt.right(90)\\n tt.forward(50)\\n tt.left(90)\",\n \"def _tk1_to_rotations(a: float, b: float, c: float) -> Circuit:\\n circ = Circuit(1)\\n circ.Rz(c, 0).Rx(b, 0).Rz(a, 0)\\n return circ\",\n \"def rotate(self, angle, axis):\\r\\n R=self.rotation(angle, axis)\\r\\n self.mlist = (self*R).mlist\\r\\n return self\",\n \"def setRxTime(self, rx_time):\\n self.rx_time = rx_time\",\n \"def interconnect(self):\\n assert len(self._readdata) == len(self._readdatavalid)\\n ndevs = len(self._readdata)\\n av = self\\n\\n @always_seq(self.clk.posedge, reset=self.reset)\\n def rtl_or_combine():\\n rddats, valids, waits = 0, 0, 0\\n for ii in range(ndevs):\\n rddats = rddats | av._readdata[ii]\\n valids = valids | av._readdatavalid[ii]\\n waits = waits | av._waitrequest[ii]\\n\\n av.readdata.next = rddats\\n av.readdatavalid.next = valids\\n av.waitrequest.next = waits\\n\\n return rtl_or_combine\",\n \"def rtl_state_and_more():\\n if not cso.enable:\\n state.next = states.idle\\n bcnt.next = 0\\n treg.next = 0\\n \\n itx.read.next = False\\n irx.write.next = False\\n\\n x_sck.next = False\\n x_ss.next = False\\n else:\\n if not cso.freeze:\\n # ~~~~ Idle state ~~~~\\n if state == states.idle:\\n bcnt.next = 7\\n treg.next = itx.read_data\\n x_sck.next = cso.clock_polarity\\n irx.write.next = False\\n \\n if not itx.empty and not irx.full:\\n itx.read.next = True\\n x_ss.next = False\\n if cso.clock_phase: # Clock in on second phase\\n state.next = states.wait_hclk\\n else: # Clock in on first phase\\n state.next = states.data_in\\n else:\\n itx.read.next = False\\n x_ss.next = True\\n\\n # ~~~~ Wait half clock period for cpha=1 ~~~~\\n elif state == states.wait_hclk:\\n itx.read.next = False\\n irx.write.next = False\\n if ena:\\n x_sck.next = not x_sck\\n state.next = states.data_in\\n\\n # ~~~~ Clock data in (and out) ~~~~\\n elif state == states.data_in:\\n itx.read.next = False\\n irx.write.next = False\\n if ena: # clk div\\n x_sck.next = not x_sck\\n rreg.next = concat(rreg[7:0], x_miso)\\n \\n if cso.clock_phase and bcnt == 0:\\n irx.write.next = True\\n if itx.empty or irx.full:\\n state.next = states.end\\n else:\\n state.next = states.data_change\\n else:\\n state.next = states.data_change\\n\\n # ~~~~ Get ready for next byte out/in ~~~~\\n elif state == states.data_change:\\n itx.read.next = False\\n irx.write.next = False\\n if ena:\\n x_sck.next = not x_sck\\n if bcnt == 0: \\n if not cso.clock_phase:\\n irx.write.next = True\\n \\n if itx.empty or irx.full:\\n state.next = states.end\\n else: # more data to transfer\\n bcnt.next = 7\\n state.next = states.data_in\\n itx.read.next = True\\n treg.next = itx.read_data\\n else:\\n treg.next = concat(treg[7:0], intbv(0)[1:])\\n bcnt.next = bcnt - 1 \\n state.next = states.data_in\\n\\n # ~~~~ End state ~~~~\\n elif state == states.end:\\n itx.read.next = False\\n irx.write.next = False\\n if ena: # Wait half clock cycle go idle\\n state.next = states.idle\\n\\n # Shouldn't happen, error in logic\\n else:\\n state.next = states.idle\\n assert False, \\\"SPI Invalid State\\\"\",\n \"def __init__(self):\\n\\n\\t###\\n\\t#subscribers for takeoff and landing \\n\\n\\tself.sub_land = rospy.Subscriber('/ardrone/land', \\n Empty,\\n self.land)\\n\\n\\tself.sub_takeoff = rospy.Subscriber('/ardrone/takeoff', \\n Empty,\\n self.takeoff)\\n\\t###\\n\\n \\n # Desired roll and pitch in radians, yaw rate in radians per second, and\\n # climb rate in meters per second\\n self.desired_roll = 0\\n self.desired_pitch = 0\\n self.desired_yaw_rate = 0\\n self.desired_climb_rate = 0\\n \\n # Unit commands for controlling a quadrotor. Commands are in following \\n # order: [front_left, front_right, rear_left, rear_right]\\n self.unit_hover_cmd = np.array([1., 1., 1., 1.])\\n self.unit_roll_cmd = np.array([1., -1., 1., -1.])\\n self.unit_pitch_cmd = np.array([-1., -1., 1., 1.])\\n self.unit_yaw_cmd = np.array([-1., 1., 1., -1.])\\n \\n # Onboard controller gains\\n self.roll_Pgain = 2.5\\n self.roll_Igain = 1.0\\n self.roll_Dgain = 1.0\\n \\n self.pitch_Pgain = 2.5\\n self.pitch_Igain = 1.0\\n self.pitch_Dgain = 1.0\\n \\n self.yaw_rate_Pgain = 2.0\\n self.yaw_rate_Igain = 0.0\\n self.yaw_rate_Dgain = 0.0\\n \\n self.climb_Pgain = 35.0\\n self.climb_Igain = 10.0\\n self.climb_Dgain = 0.0\\n \\n # Motor speed which produces hover\\n self.hover_speed = 70.0\\n \\n # Internal state\\n self.internal_state = TransformStamped()\\n self.internal_roll_error = 0.0\\n self.internal_pitch_error = 0.0\\n self.internal_yaw_error = 0.0\\n self.internal_climb_error = 0.0\\n \\n self.internal_old_roll_error = 0.0\\n self.internal_old_pitch_error = 0.0\\n self.internal_old_yaw_rate_error = 0.0\\n self.internal_old_climb_rate_error = 0.0\\n \\n self.yaw_old = 0.0\\n self.z_old = 0.0\\n \\n # Motor speed envelope\\n self.motor_cmd_min = 10\\n self.motor_cmd_max = 100\",\n \"def set_scan_rotation(self, angle):\\n raise NotImplementedError\",\n \"def Rmx(angle=0, units='deg'):\\n\\n if(units=='deg'):\\n angle = angle*pi/180\\n\\n C = np.cos(angle)\\n S = np.sin(angle)\\n\\n M = np.identity(3)\\n\\n M[1,1] = +C\\n M[1,2] = +S\\n M[2,1] = -S\\n M[2,2] = +C\\n\\n return M\",\n \"def rotate(self, axis, theta):\\n return NotImplemented\",\n \"def rz(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\\n return self.rotate(rz=angle, center=center)\",\n \"def rot(n, x, y, rx, ry):\\n if ry == 0:\\n if rx == 1:\\n x = (n-1) - x\\n y = (n-1) - y\\n t = x\\n x = y\\n y = t\\n return x, y\",\n \"def rotate(self, theta, legs):\\n U, onew = rotationTensor(theta, self.symmetries, legs)\\n B = U @ self\\n new = list(onew)\\n old = list(legs)\\n if B.internallegs != self.internallegs:\\n old.append(self.internallegs[0])\\n new.append(B.internallegs[0])\\n B.swaplegs({n: o for o, n in zip(old, new)})\\n return B.couplingAddapt(self.coupling)\",\n \"def setPlotRotation(ang, x,y):\\n dislin.trfrot(ang,x,y)\",\n \"def two_qubit_rotation(self, bits, symbols):\\n circuit = cirq.Circuit()\\n circuit += cirq.Circuit(self.one_qubit_rotation(bits[0], symbols[0:3]))\\n circuit += cirq.Circuit(self.one_qubit_rotation(bits[1], symbols[3:6]))\\n circuit += [cirq.ZZ(*bits)**symbols[6]]\\n circuit += [cirq.YY(*bits)**symbols[7]]\\n circuit += [cirq.XX(*bits)**symbols[8]]\\n circuit += cirq.Circuit(self.one_qubit_rotation(bits[0], symbols[9:12]))\\n circuit += cirq.Circuit(self.one_qubit_rotation(bits[1], symbols[12:]))\\n return circuit\",\n \"def apply_rotation_x(self, eta=0.0 ):\\n \\n eta = radians(eta)\\n new_rotation_matrix = [[ 1 , 0 , 0 ],\\n [ 0 , +cos(eta) , -sin(eta) ],\\n [ 0 , +sin(eta) , +cos(eta) ]] \\n \\n self.rotation_matrix_exp = np.dot( new_rotation_matrix, self.rotation_matrix_exp )\",\n \"def _rotate_(self, x: np.array, m: np.array) -> (np.array, np.array):\\n # get a random angle\\n angle = np.random.randint(0, self.rotate)\\n # get a random sign for the angle\\n sign = np.random.randint(0, 2)\\n x = rotate(x, -sign * angle, reshape=False)\\n m = rotate(m, -sign * angle, axes=(0, 1),\\n mode='nearest',\\n reshape=False)\\n return x, m\",\n \"def rotate(self, rx: float = 0, ry: float = 0, rz: float = 0,\\n center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\\n transform = self._local_transform\\n\\n if center is None:\\n center_point = self._origin\\n elif isinstance(center, Point3D):\\n center_point = center\\n elif isinstance(center, Point):\\n center_point = center.point\\n else:\\n center_coordinates = list(center)[0:3]\\n while len(center_coordinates) < 3:\\n center_coordinates.append(0)\\n center_point = Point3D.create(*center_coordinates)\\n\\n if rx != 0:\\n rotation = Matrix3D.create()\\n rotation.setToRotation(math.radians(rx), self._pos_x, center_point)\\n transform.transformBy(rotation)\\n if ry != 0:\\n rotation = Matrix3D.create()\\n rotation.setToRotation(math.radians(ry), self._pos_y, center_point)\\n transform.transformBy(rotation)\\n if rz != 0:\\n rotation = Matrix3D.create()\\n rotation.setToRotation(math.radians(rz), self._pos_z, center_point)\\n transform.transformBy(rotation)\\n self._reset_cache()\\n return self\",\n \"def lrbt_rot(self):\\n l, r, b, t = self._ext[0], self._ext[1], self._ext[2], self._ext[3]\\n if self.__rot90 % 4 == 1: # -90deg\\n self._ext = [b, t, l, r]\\n elif self.__rot90 % 4 == 2: # -180deg\\n self._ext = [r, l, t, b]\\n elif self.__rot90 % 4 == 3: # -270deg\\n self._ext = [t, b, r, l]\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.65553564","0.650045","0.5849988","0.5727281","0.562102","0.5599952","0.538176","0.5361661","0.533947","0.53345203","0.5285771","0.5252457","0.5218869","0.51974756","0.5187341","0.50755596","0.5019593","0.5010519","0.49932432","0.49489382","0.49301413","0.49270684","0.4894663","0.48826012","0.48566553","0.4852325","0.48439035","0.48363745","0.48314556","0.4822881","0.48189887","0.48137054","0.48104864","0.48062828","0.4800815","0.47783783","0.4764676","0.47613454","0.4759378","0.47587886","0.4754391","0.47534063","0.47477335","0.4736053","0.47265485","0.47244155","0.4721903","0.47075525","0.4703425","0.47003856","0.46815783","0.46805602","0.46784338","0.46742836","0.46633875","0.46519276","0.46498144","0.46460426","0.46458504","0.46454287","0.4643395","0.46386534","0.46351764","0.46265846","0.46254417","0.46109757","0.46058705","0.46043938","0.46027994","0.46007845","0.45962435","0.4596069","0.45939833","0.45911884","0.45866406","0.45854187","0.45831424","0.4567803","0.4567803","0.4567803","0.4567803","0.45635667","0.45508313","0.4550173","0.45443004","0.45436335","0.45424637","0.453801","0.45318252","0.45302385","0.45260298","0.45163703","0.4513257","0.45029193","0.45013037","0.4499392","0.44985145","0.44978243","0.44870442","0.44838318"],"string":"[\n \"0.65553564\",\n \"0.650045\",\n \"0.5849988\",\n \"0.5727281\",\n \"0.562102\",\n \"0.5599952\",\n \"0.538176\",\n \"0.5361661\",\n \"0.533947\",\n \"0.53345203\",\n \"0.5285771\",\n \"0.5252457\",\n \"0.5218869\",\n \"0.51974756\",\n \"0.5187341\",\n \"0.50755596\",\n \"0.5019593\",\n \"0.5010519\",\n \"0.49932432\",\n \"0.49489382\",\n \"0.49301413\",\n \"0.49270684\",\n \"0.4894663\",\n \"0.48826012\",\n \"0.48566553\",\n \"0.4852325\",\n \"0.48439035\",\n \"0.48363745\",\n \"0.48314556\",\n \"0.4822881\",\n \"0.48189887\",\n \"0.48137054\",\n \"0.48104864\",\n \"0.48062828\",\n \"0.4800815\",\n \"0.47783783\",\n \"0.4764676\",\n \"0.47613454\",\n \"0.4759378\",\n \"0.47587886\",\n \"0.4754391\",\n \"0.47534063\",\n \"0.47477335\",\n \"0.4736053\",\n \"0.47265485\",\n \"0.47244155\",\n \"0.4721903\",\n \"0.47075525\",\n \"0.4703425\",\n \"0.47003856\",\n \"0.46815783\",\n \"0.46805602\",\n \"0.46784338\",\n \"0.46742836\",\n \"0.46633875\",\n \"0.46519276\",\n \"0.46498144\",\n \"0.46460426\",\n \"0.46458504\",\n \"0.46454287\",\n \"0.4643395\",\n \"0.46386534\",\n \"0.46351764\",\n \"0.46265846\",\n \"0.46254417\",\n \"0.46109757\",\n \"0.46058705\",\n \"0.46043938\",\n \"0.46027994\",\n \"0.46007845\",\n \"0.45962435\",\n \"0.4596069\",\n \"0.45939833\",\n \"0.45911884\",\n \"0.45866406\",\n \"0.45854187\",\n \"0.45831424\",\n \"0.4567803\",\n \"0.4567803\",\n \"0.4567803\",\n \"0.4567803\",\n \"0.45635667\",\n \"0.45508313\",\n \"0.4550173\",\n \"0.45443004\",\n \"0.45436335\",\n \"0.45424637\",\n \"0.453801\",\n \"0.45318252\",\n \"0.45302385\",\n \"0.45260298\",\n \"0.45163703\",\n \"0.4513257\",\n \"0.45029193\",\n \"0.45013037\",\n \"0.4499392\",\n \"0.44985145\",\n \"0.44978243\",\n \"0.44870442\",\n \"0.44838318\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.62692696"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81736,"cells":{"query":{"kind":"string","value":"add RY gate (rotation around Yaxis)."},"document":{"kind":"string","value":"def ry(self, q0, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_Y, qid=[q0], phase=phase, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def rot_y(angle):\n sangle = math.sin(angle)\n cangle = math.cos(angle)\n ry = np.array([[cangle, 0.0, -sangle],\n [0.0, 1.0, 0.0],\n [sangle, 0.0, cangle]])\n return ry","def rotate_y(angle):\n log.dev(\"lib.mathp.rotate_y is deprecated. Use lib.rotation.R2 instead.\")\n\n cosA = np.cos(angle)\n sinA = np.sin(angle)\n R = np.array([[cosA, 0, -sinA], [0, 1, 0], [sinA, 0, cosA]])\n return R","def rot_y_rad(self):\n return self._rot_y_rad","def apply_rotation_y(self, phi=0.0 ):\n \n phi = radians(phi)\n new_rotation_matrix = [[ +cos(phi) , 0 , +sin(phi) ],\n [ 0 , 1 , 0 ],\n [ -sin(phi) , 0 , +cos(phi) ]] \n \n self.rotation_matrix_exp = np.dot( new_rotation_matrix, self.rotation_matrix_exp )","def RotationY(theta):\n\n return Rotation([0., 1., 0.], theta)","def multi_rot_Y(angle_rads: numpy.ndarray) -> numpy.ndarray:\n ry = numpy.empty((angle_rads.shape[0], 4, 4))\n ry[...] = numpy.identity(4)\n ry[:, 0, 0] = ry[:, 2, 2] = numpy.cos(angle_rads)\n ry[:, 0, 2] = numpy.sin(angle_rads)\n ry[:, 2, 0] = -ry[:, 0, 2]\n\n return ry","def Ry(theta, units='deg'):\n if units == 'deg':\n theta = np.deg2rad(theta)\n\n return np.mat([[np.cos(theta), 0, np.sin(theta)],\n [0, 1, 0],\n [-np.sin(theta), 0, np.cos(theta)]\n ],\n dtype='f8'\n )","def y_rotation(self):\n before = ('R','r', 'B', 'b', 'L', 'l','F','f','M' , 'z' ,'S', 'x')\n after = ('B','b', 'L', 'l', 'F', 'f','R','r','S' , 'x' ,\"M'\", \"z'\")\n solve = self.solve_helper.maketrans(dict(zip(before, after)))\n solve_trans = self.solve_helper.translate(solve)\n solve_trans = solve_trans.replace(\"\\'\\'\",\"\")\n self.solve_helper = solve_trans","def rotate_y(self, angle):\n angle *= np.pi / 180\n return self.transform(np.matrix([[np.cos(angle), 0, np.sin(angle)],\n [0, 1, 0],\n [-np.sin(angle), 0, np.cos(angle)]]))","def rotate_y(self,rad):\n DetElement.rotate_y(self,rad) #python2\n #super().rotate_y(rad) #python3\n for tube in self._list_of_tubes:\n self.__update__update_tube_pos_after_rotation(tube)\n tube.rotate_y(rad)","def Y(self, qubit_expr): \n self.apply_gate_operation('Y', qubit_expr)","def R(rpy):\n Rx_roll = sp.Matrix(\n [\n [1, 0, 0],\n [0, sp.cos(rpy[0]), -sp.sin(rpy[0])],\n [0, sp.sin(rpy[0]), sp.cos(rpy[0])],\n ]\n )\n Ry_pitch = sp.Matrix(\n [\n [sp.cos(rpy[1]), 0, sp.sin(rpy[1])],\n [0, 1, 0],\n [-sp.sin(rpy[1]), 0, sp.cos(rpy[1])],\n ]\n )\n Rz_yaw = sp.Matrix(\n [\n [sp.cos(rpy[2]), -sp.sin(rpy[2]), 0],\n [sp.sin(rpy[2]), sp.cos(rpy[2]), 0],\n [0, 0, 1],\n ]\n )\n R = Rx_roll * Ry_pitch * Rz_yaw\n return R","def rotate_y(self, angle: float):\n self.vertices = list(\n Matrix44.y_rotate(angle).transform_vertices(self.vertices)\n )\n return self","def ry(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\n return self.rotate(ry=angle, center=center)","def Ycyl(self, R):\n # FIXME: Not implemented yet\n raise NotImplementedError(\"ArnaudProfile.Ycyl not implemented.\")\n return 0.","def ry(self, angle: float) -> \"Mate\":\n a = angle / 180 * pi\n self.x_dir = Mate._rotate(self.x_dir, self.y_dir, a)\n self.z_dir = Mate._rotate(self.z_dir, self.y_dir, a)\n return self","def Ry(q):\n sin_q, cos_q = sin(q), cos(q)\n return numpy.matrix([\n [cos_q, 0, -sin_q, 0],\n [0, 1, 0, 0],\n [sin_q, 0, cos_q, 0],\n [0, 0, 0, 1],\n ])","def add_y(self, y, add):\n return (y + add) % self.y_len","def rotY(theta, mode = 'radians'):\n\n\tif mode != 'radians' and mode != 'degrees':\n\t\traise ValueError('Mode should either be ``radians`` or ``degrees``.')\n\tif mode == 'degrees':\n\t\ttheta = np.deg2rad(theta)\n\treturn np.matrix([[np.cos(theta), 0., np.sin(theta)], [0, 1, 0], \\\n\t\t[-np.sin(theta), 0, np.cos(theta)]])","def apply_Ry(psi, theta, i, parametrize=False, **gate_opts):\n mtags = _merge_tags({'RY'}, gate_opts)\n if parametrize:\n G = ops.PArray(ry_gate_param_gen, (float(theta),))\n else:\n G = qu.Ry(float(theta))\n psi.gate_(G, int(i), tags=mtags, **gate_opts)","def yz_rotation(vector,theta):\r\n R = np.array([[1,0,0],\r\n [0, np.cos(theta),-np.sin(theta)],\r\n [0, np.sin(theta), np.cos(theta)]\r\n ])\r\n return np.dot(R,vector)","def AffineRy(theta, units='deg'):\n if units == 'deg':\n theta = np.deg2rad(theta)\n\n return np.mat([[np.cos(theta), 0, np.sin(theta), 0],\n [0, 1, 0, 0],\n [-np.sin(theta), 0, np.cos(theta), 0],\n [0, 0, 0, 1]\n ],\n dtype='f8'\n )","def rotateYRight(self):\n MV = self.MV\n MV[:3, 0] = 0, 1, 0 # 1st col is right vector, make it point along y axis\n # set middle middle and middle right values to zero:\n MV[1, 1] = 0\n MV[1, 2] = 0\n a = MV[0, 1] # grab top middle value\n b = np.sqrt(1 - a**2) # calc new complementary value to get normalized vectors\n if MV[2, 1] < 0:\n b = -b # keep b -ve, reduce jumping around of axes\n MV[2, 1] = b\n MV[0, 2] = b\n MV[2, 2] = -a # needs to be -ve of MV[0, 1]\n self.MV = MV","def rotateYRight(self):\n MV = self.MV\n MV[:3, 0] = 0, 1, 0 # 1st col is right vector, make it point along y axis\n # set middle middle and middle right values to zero:\n MV[1, 1] = 0\n MV[1, 2] = 0\n a = MV[0, 1] # grab top middle value\n b = np.sqrt(1 - a**2) # calc new complementary value to get normalized vectors\n if MV[2, 1] < 0:\n b = -b # keep b -ve, reduce jumping around of axes\n MV[2, 1] = b\n MV[0, 2] = b\n MV[2, 2] = -a # needs to be -ve of MV[0, 1]\n self.MV = MV","def y_rotmat(theta):\n cos_t = np.cos(theta)\n sin_t = np.sin(theta)\n return np.array([[cos_t, 0, sin_t],\n [0, 1, 0],\n [-sin_t, 0, cos_t]])","def rot_y(theta):\n theta_rad = np.radians(theta)\n rotation_matrix = [[np.cos(theta_rad), 0, np.sin(theta_rad)],\n [0, 1, 0],\n [-np.sin(theta_rad), 0, np.cos(theta_rad)]]\n return np.matrix(rotation_matrix)","def y2(self):\n return self._y + self._y2","def ROT(self):\n # The maximum update amount for these element\n # no dt since YawRate is already mult by dt\n YawRate_DELTA = (self.YawRate_LIMITS[1] -\n self.YawRate_LIMITS[0]) / (2.0)\n\n # Add either positive or negative or zero delta for each\n # NOTE: 'High' is open bracket ) so the max is 1\n YawRate_DIRECTION = np.random.randint(-1, 2, 1)[0]\n\n # Now, modify modifiable params AND CLIP\n self.YawRate += YawRate_DIRECTION * YawRate_DELTA\n self.YawRate = np.clip(self.YawRate, self.YawRate_LIMITS[0],\n self.YawRate_LIMITS[1])","def coordY(r, theta, useradians = True):\r\n if not useradians :\r\n #convert theta to radians\r\n theta = theta / 180 * math.pi\r\n y = r * math.sin(theta)\r\n return y","def rotate_by_y_axis(points2d):\n # define rotation matrix\n transf_matrix = np.column_stack(([1,0], [0,1]))\n\n return np.dot(transf_matrix, points2d.T).T","def yarray(shape, yx=[0, 0], rot=0, dtype=int):\n\n from ..util import rotmat\n\n y, x = np.indices(shape, dtype)[-2:]\n y = y - yx[0]\n x = x - yx[1]\n\n if rot != 0:\n R = rotmat(rot)\n y = x * R[1, 0] + y * R[1, 1]\n\n return y","def ry(target: QubitInput, angle: float) -> Iterable[Instruction]:\n return [Instruction(Ry(angle), target=qubit) for qubit in QubitSet(target)]","def add(self, y):\n return circuit.add(self, y)","def rot_y_deg(self):\n # TODO describe which axis this is\n return math.degrees(self._rot_y_rad)","def rotateRight(self):\n self.faceHeading+=-1*shipRotationSpeed\n self.reDraw()","def test_y_rot(self):\n\n # Create a Matrix representing 90 deg y rot.\n mat = Matrix44.from_rot_y(90)\n # Use from_matrix44()\n quat = Quat.from_matrix44(mat)\n\n # Ensure the quat matches a 90 degree x rotation.\n expected = Quat.from_axis_angle_deg(Vec3(0, 1, 0), 90)\n AssertQuatAlmostEqual(quat, expected, self)","def yline(y,farright, width, dash, grayamount):\r\n aline([[0,y],[farright,y]],width, dash, grayamount)","def get_y(theta, phi, w, r=1):\n return np.sin(phi) * r * np.cos(w) + np.cos(phi) * np.cos(theta) * r * np.sin(w)","def startAngMovementY(self):\n self.boolrot[1] = True","def connector_right(self):\n return RotatedShape(shape_in=self.tail_shaft_circle[1],\n rotation_point=self.tail_shaft_circle[0].center,\n vector=Vector(0, 1, 0),\n angle=radians(90))","def moveRightArm(self, pitch): # add yaw!\n\n\t\tangles = [pitch, 12, 39, 3, -8] # angles in degrees\n\t\tangles = [math.radians(angle) for angle in angles] # convert to radians\n\t\tangles.append(1) # also open hand\n\t\ttimes = [1, 1, 1.5, 1.5, 1.5, 1.5]\n\t\tself.motion.angleInterpolation(\"RArm\", angles, times, True) # move to those arm angles and open hand","def _derY(self, x, y):\n raise NotImplementedError()","def right(self, angle):\r\n self.rotation += angle","def rotate_about_y(self, deg):\n if self.x is None:\n raise AttributeError('rotate_about_y: no X component')\n if self.z is None:\n raise AttributeError('rotate_about_y: no Z component')\n\n sine = sin(radians(deg))\n cosine = cos(radians(deg))\n x_new = self.x*cosine - self.z*sine\n self.z = self.z*cosine + self.x*sine\n self.x = x_new","def rz(self, phi, q): # pylint: disable=invalid-name\n return self.append(RZGate(phi), [q], [])","def right_angle_axes(self, right_angle_axes):\n\n self.container['right_angle_axes'] = right_angle_axes","def INY(self, *_):\n self._dec_or_inc_register('Y', increment=True)","def set_ypos(self, deg):\n if deg < -10:\n deg = -10\n elif deg > 10:\n deg = 10\n deg += 10\n self.kit.servo[8].angle = deg","def rotate_right(self, speed):\n\t\t# You should modify the bias of 4 wheels depending on your hardware.\n\t\tself._front_left_wheel.anticlockwise_rotate(speed + LEFT_FR_BIAS + LEFT_RIGHT_BIAS)\n\t\tself._front_right_wheel.anticlockwise_rotate(speed + RIGHT_FR_BIAS)\n\t\tself._rear_left_wheel.anticlockwise_rotate(speed + 1 + LEFT_RIGHT_BIAS)\n\t\tself._rear_right_wheel.anticlockwise_rotate(speed)","def vel_y(self, *args, **kwargs) -> Any:\n pass","def _get_y(self):\n enabled = self.num_enabled\n\n if self.heart_enabled:\n self._heart_y = 45*(self.num_enabled - enabled) + 75\n enabled -= 1\n if self.speed_enabled:\n self._speed_y = 45*(self.num_enabled - enabled) + 75\n enabled -= 1\n if self.cadence_enabled:\n self._cadence_y = 45*(self.num_enabled - enabled) + 75\n enabled -= 1\n if self.ams_enabled:\n self._ams_y = 45*(self.num_enabled - enabled) + 75\n enabled -= 1","def _create_raindrops_y(self, raindrop_y):\n r_calc = self._calculate_spacing()\n for raindrop_x in range(r_calc[2]):\n self._create_raindrop(raindrop_x, raindrop_y)","def lrbt_rot(self):\n l, r, b, t = self._ext[0], self._ext[1], self._ext[2], self._ext[3]\n if self.__rot90 % 4 == 1: # -90deg\n self._ext = [b, t, l, r]\n elif self.__rot90 % 4 == 2: # -180deg\n self._ext = [r, l, t, b]\n elif self.__rot90 % 4 == 3: # -270deg\n self._ext = [t, b, r, l]","def setRPY(self, roll, pitch, yaw):\n\n currentmat = self.__objbdb.get_homomat()\n currentmatnp = base.pg.mat4ToNp(currentmat)\n newmatnp = rm.rotmat_from_euler(roll, pitch, yaw, axes=\"sxyz\")\n self.setMat(base.pg.npToMat4(newmatnp, currentmatnp[:, 3]))","def DEY(self, *_):\n self._dec_or_inc_register('Y', increment=False)","def yy(target1: QubitInput, target2: QubitInput, angle: float) -> Instruction:\n return Instruction(YY(angle), target=[target1, target2])","def calculate_R2(self):\n\n d1 = self.T - self.Y\n d2 = self.T - self.T.mean()\n\n self.r2 = 1 - d1.dot(d1) / d2.dot(d2)\n self.r2 = format(self.r2, '.3f')\n\n print \"\"\n print \"R2:\", self.r2","def rotxaxis(ya, za, angle):\n\n y = ya * math.cos(angle) - za * math.sin(angle) \n z = ya * math.sin(angle) + za * math.cos(angle)\n \n return y, z","def speedup_y(self):\r\n new_speed = math.sin((self.__direction*math.pi)/180) + self.__y_speed\r\n self.__y_speed = new_speed","def getGYR(self, axis='X'):\r\n\t\tscale = self.getScale(mode='GYR')[0]\r\n\t\tif axis.upper() == 'X':\r\n\t\t\treg = 0x43\r\n\t\telif axis.upper() == 'Y':\r\n\t\t\treg = 0x45\r\n\t\telif axis.upper() == 'Z':\r\n\t\t\treg = 0x47\r\n\t\telse:\r\n\t\t\treturn False\r\n\t\tgyr_H = self.read(reg)\r\n\t\tgyr_L = self.read(reg+1)\r\n\t\tgyrRaw = self.twos_comp(val=(gyr_H*256 + gyr_L),bits=16)\r\n\t\treturn scale*(gyrRaw/float(2**15)), gyrRaw","def y(self):\n pass","def rotate_right(self):\n current = compass.index(self.heading)\n return replace(self, heading=compass[(current + 1) % 4])","def y(self):\n return self._turtle.ycor()","def y(self):\n return self._turtle.ycor()","def right_rotation(self, ang_vel):\n vel = self.om_left_max * self.R + ang_vel * self.L\n om_right = (vel + ang_vel * self.L) / self.R \n return vel, om_right","def y_operators(self) -> List[PauliTerm]:\n # Y = iXZ\n y_operators = [1j * x_op * z_op\n for x_op, z_op in zip(self.x_operators(), self.z_operators())]\n for y_op in y_operators:\n assert y_op.coefficient == 1\n return y_operators","def Get_RawOutY_Value(self):\r\n l = self.__readFromRegister(self.__REG_R_OUT_Y_L, 0xff)\r\n h_u2 = self.__readFromRegister(self.__REG_R_OUT_Y_H, 0xff)\r\n h = bitOps.TwosComplementToByte(h_u2)\r\n if (h < 0):\r\n return (h*256 - l) * self.gain\r\n elif (h >= 0):\r\n return (h*256 + l) * self.gain","def set_y(self, new_y):\r\n self.y = new_y","def rotation3D_y(angle: float) -> np.array:\n c = np.cos(angle)\n s = np.sin(angle)\n return np.array([[c, 0.0, s], [0.0, 1.0, 0.0], [-s, 0.0, c]])","def Rotate(X,Y,sintheta=0,costheta=1):\n X1 = X * costheta - Y * sintheta \n Y1 = X * sintheta + Y * costheta \n return X1,Y1","def on_r_joy_y(self):\r\n self.log()","def rotation_center_y(self, *args, **kwargs) -> Any:\n pass","def moveY(self, slice, dir=1):\n\n for p in self.pieces: # Filter pieces not in slice.\n if slice > 1 or p.y == slice:\n # Use PMatrix2D() to calculate position from rotation.\n t = PMatrix2D()\n t.rotate(dir * HALF_PI)\n t.translate(p.x, p.z)\n p.rY(dir)\n p.pos(round(t.m02), round(p.y), round(t.m12))","def setY(self, y):\r\n\t\tself._y=y","def _derY(self, w, x, y, z):\n raise NotImplementedError()","def move_right(self):\n self.yaw_motor.step_forward()","def rotate_y(p, a=0):\n # turn value to radians\n a = math.radians(a)\n translation_mat = np.matrix([\n [math.cos(a),0,-math.sin(a),0],\n [0,1,0,0],\n [math.sin(a),0,math.cos(a),0],\n [0,0,0,1],\n ], dtype=\"float32\")\n\n new_p = p @ translation_mat\n\n return new_p","def y(self, value):\n self.validate_input(y=value)\n self.__y = value","def ystep(self):\n\n # Update t step\n tprv = self.t\n self.t = self.momentum.update(self.var_momentum())\n\n # Update Y\n if self.opt['Monotone'] and self.k > 0:\n self.Y = self.X + (tprv / self.t) * (self.ZZ - self.X) \\\n + ((tprv - 1.) / self.t) * (self.X - self.Xprv)\n else:\n self.Y = self.X + ((tprv - 1.) / self.t) * (self.X - self.Xprv)","def gen_y(self, y_func):\n assert not np.all(self.x == None)\n assert not np.all(self.act == None)\n self.y = y_func(self.x, self.act, self.ydim, self.generator)","def base_roll_pitch_yaw(self):\n #raise NotImplementedError('Not yet implemented!')\n return np.asarray([self._robot_state.roll, self._robot_state.pitch, self._robot_state.yaw])","def _gen_r(theta, phi):\n return _gen_u(theta, phi - np.pi / 2, phi + np.pi / 2)","def base_roll_pitch_yaw_rate(self):\n return np.asarray([self._robot_state.roll_rate, self._robot_state.pitch_rate, self._robot_state.yaw_rate])","def rotate(Y,Mat):\r\n # Converting angle into radians \r\n Y = radians(Y)\r\n # RM is the Rotation Matrix (3 X 3)\r\n RM=[[cos(Y),-sin(Y),0],[sin(Y),cos(Y),0],[0,0,1]]\r\n Rotate_Matrix = Multiply(RM,Mat)\r\n # Rotate_Matrix[0][0] is the updated x coordinate\r\n # Rotate_Matrix[1][0] is the updated y coordinate\r\n return Rotate_Matrix[0][0],Rotate_Matrix[1][0],Rotate_Matrix[2][0]","def _derY(self, x, y, z):\n raise NotImplementedError()","def __set_y__(self,y):\n\n # Input vaidation\n try:\n y = int(y)\n except:\n raise ValueError('H Bridge direction is not valid')\n \n if(y != 0 and y != 1 and y != -1):\n raise ValueError('H Bridge direction is not valid')\n \n self.direction['y'] = y\n self.HBridges['y'].SetDirection(y)","def Y(self, value):\n self._Y = value","def rotate_rad(self, angle):\n self.beam_angle += angle\n self.xy = rotate(self.xy, angle)\n self.angle += angle","def rotateY(self, angle):\r\n if angle:\r\n c = cos(radians(angle))\r\n s = sin(radians(angle))\r\n self.mtrx = dot([[c, 0, -s, 0],\r\n [0, 1, 0, 0],\r\n [s, 0, c, 0],\r\n [0, 0, 0, 1]],\r\n self.mtrx)\r\n self.rtn[1] = angle\r\n self.was_moved = True","def getNextRight(y, x, majorDir, minorDir):\n x += 1\n if x == SZ:\n y = (y + 1) if minorDir == Direction.DOWN else (y - 1)\n x = SZ - 1\n majorDir = Direction.LEFT\n return y, x, majorDir","def rot(wx, wy, order, dist):\n for _ in range(dist//90):\n if order == \"R\":\n wx, wy = wy, -wx\n elif order == \"L\":\n wx, wy = -wy, wx\n return wx, wy","def rot_axis_angle_to_ypr(degrees: float, q: Quaternion, source: np.ndarray) -> tuple:\n rotation_matrix = get_rotmat(radians(degrees), q[0], q[1], q[2])\n return rotation_matrix_to_ypr(np.matmul(rotation_matrix, source))","def __init__(self, phi):\n super().__init__(\"rz\", 1, [phi])","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def r2(t, y):\n\treturn r2_score(t, y)","def RZZ(self, theta:Union[int, float], qubit_expr): \n self.apply_gate_operation(RZZ(theta), qubit_expr)","def TYA(self, *_):\n self.reg.A = self.reg.Y\n self.reg.N = self.reg.A << 7\n self.reg.Z = self.reg.A == 0","def right_angle_axes(self):\n return self.container['right_angle_axes']","def roty(self, t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[c, 0, s],\n [0, 1, 0],\n [-s, 0, c]])","def RotZYX_to_RPY(r: array):\n\n # Make sure that r is an array and reshape it to be a 3x3 matrix\n r = array(r).reshape((3, 3))\n\n # Compute the corresponding quaternions\n q = Rot_to_quaternion(r)\n\n # Compute the euler angles from the quaternion\n return quaternion_to_RPY(q)"],"string":"[\n \"def rot_y(angle):\\n sangle = math.sin(angle)\\n cangle = math.cos(angle)\\n ry = np.array([[cangle, 0.0, -sangle],\\n [0.0, 1.0, 0.0],\\n [sangle, 0.0, cangle]])\\n return ry\",\n \"def rotate_y(angle):\\n log.dev(\\\"lib.mathp.rotate_y is deprecated. Use lib.rotation.R2 instead.\\\")\\n\\n cosA = np.cos(angle)\\n sinA = np.sin(angle)\\n R = np.array([[cosA, 0, -sinA], [0, 1, 0], [sinA, 0, cosA]])\\n return R\",\n \"def rot_y_rad(self):\\n return self._rot_y_rad\",\n \"def apply_rotation_y(self, phi=0.0 ):\\n \\n phi = radians(phi)\\n new_rotation_matrix = [[ +cos(phi) , 0 , +sin(phi) ],\\n [ 0 , 1 , 0 ],\\n [ -sin(phi) , 0 , +cos(phi) ]] \\n \\n self.rotation_matrix_exp = np.dot( new_rotation_matrix, self.rotation_matrix_exp )\",\n \"def RotationY(theta):\\n\\n return Rotation([0., 1., 0.], theta)\",\n \"def multi_rot_Y(angle_rads: numpy.ndarray) -> numpy.ndarray:\\n ry = numpy.empty((angle_rads.shape[0], 4, 4))\\n ry[...] = numpy.identity(4)\\n ry[:, 0, 0] = ry[:, 2, 2] = numpy.cos(angle_rads)\\n ry[:, 0, 2] = numpy.sin(angle_rads)\\n ry[:, 2, 0] = -ry[:, 0, 2]\\n\\n return ry\",\n \"def Ry(theta, units='deg'):\\n if units == 'deg':\\n theta = np.deg2rad(theta)\\n\\n return np.mat([[np.cos(theta), 0, np.sin(theta)],\\n [0, 1, 0],\\n [-np.sin(theta), 0, np.cos(theta)]\\n ],\\n dtype='f8'\\n )\",\n \"def y_rotation(self):\\n before = ('R','r', 'B', 'b', 'L', 'l','F','f','M' , 'z' ,'S', 'x')\\n after = ('B','b', 'L', 'l', 'F', 'f','R','r','S' , 'x' ,\\\"M'\\\", \\\"z'\\\")\\n solve = self.solve_helper.maketrans(dict(zip(before, after)))\\n solve_trans = self.solve_helper.translate(solve)\\n solve_trans = solve_trans.replace(\\\"\\\\'\\\\'\\\",\\\"\\\")\\n self.solve_helper = solve_trans\",\n \"def rotate_y(self, angle):\\n angle *= np.pi / 180\\n return self.transform(np.matrix([[np.cos(angle), 0, np.sin(angle)],\\n [0, 1, 0],\\n [-np.sin(angle), 0, np.cos(angle)]]))\",\n \"def rotate_y(self,rad):\\n DetElement.rotate_y(self,rad) #python2\\n #super().rotate_y(rad) #python3\\n for tube in self._list_of_tubes:\\n self.__update__update_tube_pos_after_rotation(tube)\\n tube.rotate_y(rad)\",\n \"def Y(self, qubit_expr): \\n self.apply_gate_operation('Y', qubit_expr)\",\n \"def R(rpy):\\n Rx_roll = sp.Matrix(\\n [\\n [1, 0, 0],\\n [0, sp.cos(rpy[0]), -sp.sin(rpy[0])],\\n [0, sp.sin(rpy[0]), sp.cos(rpy[0])],\\n ]\\n )\\n Ry_pitch = sp.Matrix(\\n [\\n [sp.cos(rpy[1]), 0, sp.sin(rpy[1])],\\n [0, 1, 0],\\n [-sp.sin(rpy[1]), 0, sp.cos(rpy[1])],\\n ]\\n )\\n Rz_yaw = sp.Matrix(\\n [\\n [sp.cos(rpy[2]), -sp.sin(rpy[2]), 0],\\n [sp.sin(rpy[2]), sp.cos(rpy[2]), 0],\\n [0, 0, 1],\\n ]\\n )\\n R = Rx_roll * Ry_pitch * Rz_yaw\\n return R\",\n \"def rotate_y(self, angle: float):\\n self.vertices = list(\\n Matrix44.y_rotate(angle).transform_vertices(self.vertices)\\n )\\n return self\",\n \"def ry(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\\n return self.rotate(ry=angle, center=center)\",\n \"def Ycyl(self, R):\\n # FIXME: Not implemented yet\\n raise NotImplementedError(\\\"ArnaudProfile.Ycyl not implemented.\\\")\\n return 0.\",\n \"def ry(self, angle: float) -> \\\"Mate\\\":\\n a = angle / 180 * pi\\n self.x_dir = Mate._rotate(self.x_dir, self.y_dir, a)\\n self.z_dir = Mate._rotate(self.z_dir, self.y_dir, a)\\n return self\",\n \"def Ry(q):\\n sin_q, cos_q = sin(q), cos(q)\\n return numpy.matrix([\\n [cos_q, 0, -sin_q, 0],\\n [0, 1, 0, 0],\\n [sin_q, 0, cos_q, 0],\\n [0, 0, 0, 1],\\n ])\",\n \"def add_y(self, y, add):\\n return (y + add) % self.y_len\",\n \"def rotY(theta, mode = 'radians'):\\n\\n\\tif mode != 'radians' and mode != 'degrees':\\n\\t\\traise ValueError('Mode should either be ``radians`` or ``degrees``.')\\n\\tif mode == 'degrees':\\n\\t\\ttheta = np.deg2rad(theta)\\n\\treturn np.matrix([[np.cos(theta), 0., np.sin(theta)], [0, 1, 0], \\\\\\n\\t\\t[-np.sin(theta), 0, np.cos(theta)]])\",\n \"def apply_Ry(psi, theta, i, parametrize=False, **gate_opts):\\n mtags = _merge_tags({'RY'}, gate_opts)\\n if parametrize:\\n G = ops.PArray(ry_gate_param_gen, (float(theta),))\\n else:\\n G = qu.Ry(float(theta))\\n psi.gate_(G, int(i), tags=mtags, **gate_opts)\",\n \"def yz_rotation(vector,theta):\\r\\n R = np.array([[1,0,0],\\r\\n [0, np.cos(theta),-np.sin(theta)],\\r\\n [0, np.sin(theta), np.cos(theta)]\\r\\n ])\\r\\n return np.dot(R,vector)\",\n \"def AffineRy(theta, units='deg'):\\n if units == 'deg':\\n theta = np.deg2rad(theta)\\n\\n return np.mat([[np.cos(theta), 0, np.sin(theta), 0],\\n [0, 1, 0, 0],\\n [-np.sin(theta), 0, np.cos(theta), 0],\\n [0, 0, 0, 1]\\n ],\\n dtype='f8'\\n )\",\n \"def rotateYRight(self):\\n MV = self.MV\\n MV[:3, 0] = 0, 1, 0 # 1st col is right vector, make it point along y axis\\n # set middle middle and middle right values to zero:\\n MV[1, 1] = 0\\n MV[1, 2] = 0\\n a = MV[0, 1] # grab top middle value\\n b = np.sqrt(1 - a**2) # calc new complementary value to get normalized vectors\\n if MV[2, 1] < 0:\\n b = -b # keep b -ve, reduce jumping around of axes\\n MV[2, 1] = b\\n MV[0, 2] = b\\n MV[2, 2] = -a # needs to be -ve of MV[0, 1]\\n self.MV = MV\",\n \"def rotateYRight(self):\\n MV = self.MV\\n MV[:3, 0] = 0, 1, 0 # 1st col is right vector, make it point along y axis\\n # set middle middle and middle right values to zero:\\n MV[1, 1] = 0\\n MV[1, 2] = 0\\n a = MV[0, 1] # grab top middle value\\n b = np.sqrt(1 - a**2) # calc new complementary value to get normalized vectors\\n if MV[2, 1] < 0:\\n b = -b # keep b -ve, reduce jumping around of axes\\n MV[2, 1] = b\\n MV[0, 2] = b\\n MV[2, 2] = -a # needs to be -ve of MV[0, 1]\\n self.MV = MV\",\n \"def y_rotmat(theta):\\n cos_t = np.cos(theta)\\n sin_t = np.sin(theta)\\n return np.array([[cos_t, 0, sin_t],\\n [0, 1, 0],\\n [-sin_t, 0, cos_t]])\",\n \"def rot_y(theta):\\n theta_rad = np.radians(theta)\\n rotation_matrix = [[np.cos(theta_rad), 0, np.sin(theta_rad)],\\n [0, 1, 0],\\n [-np.sin(theta_rad), 0, np.cos(theta_rad)]]\\n return np.matrix(rotation_matrix)\",\n \"def y2(self):\\n return self._y + self._y2\",\n \"def ROT(self):\\n # The maximum update amount for these element\\n # no dt since YawRate is already mult by dt\\n YawRate_DELTA = (self.YawRate_LIMITS[1] -\\n self.YawRate_LIMITS[0]) / (2.0)\\n\\n # Add either positive or negative or zero delta for each\\n # NOTE: 'High' is open bracket ) so the max is 1\\n YawRate_DIRECTION = np.random.randint(-1, 2, 1)[0]\\n\\n # Now, modify modifiable params AND CLIP\\n self.YawRate += YawRate_DIRECTION * YawRate_DELTA\\n self.YawRate = np.clip(self.YawRate, self.YawRate_LIMITS[0],\\n self.YawRate_LIMITS[1])\",\n \"def coordY(r, theta, useradians = True):\\r\\n if not useradians :\\r\\n #convert theta to radians\\r\\n theta = theta / 180 * math.pi\\r\\n y = r * math.sin(theta)\\r\\n return y\",\n \"def rotate_by_y_axis(points2d):\\n # define rotation matrix\\n transf_matrix = np.column_stack(([1,0], [0,1]))\\n\\n return np.dot(transf_matrix, points2d.T).T\",\n \"def yarray(shape, yx=[0, 0], rot=0, dtype=int):\\n\\n from ..util import rotmat\\n\\n y, x = np.indices(shape, dtype)[-2:]\\n y = y - yx[0]\\n x = x - yx[1]\\n\\n if rot != 0:\\n R = rotmat(rot)\\n y = x * R[1, 0] + y * R[1, 1]\\n\\n return y\",\n \"def ry(target: QubitInput, angle: float) -> Iterable[Instruction]:\\n return [Instruction(Ry(angle), target=qubit) for qubit in QubitSet(target)]\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def rot_y_deg(self):\\n # TODO describe which axis this is\\n return math.degrees(self._rot_y_rad)\",\n \"def rotateRight(self):\\n self.faceHeading+=-1*shipRotationSpeed\\n self.reDraw()\",\n \"def test_y_rot(self):\\n\\n # Create a Matrix representing 90 deg y rot.\\n mat = Matrix44.from_rot_y(90)\\n # Use from_matrix44()\\n quat = Quat.from_matrix44(mat)\\n\\n # Ensure the quat matches a 90 degree x rotation.\\n expected = Quat.from_axis_angle_deg(Vec3(0, 1, 0), 90)\\n AssertQuatAlmostEqual(quat, expected, self)\",\n \"def yline(y,farright, width, dash, grayamount):\\r\\n aline([[0,y],[farright,y]],width, dash, grayamount)\",\n \"def get_y(theta, phi, w, r=1):\\n return np.sin(phi) * r * np.cos(w) + np.cos(phi) * np.cos(theta) * r * np.sin(w)\",\n \"def startAngMovementY(self):\\n self.boolrot[1] = True\",\n \"def connector_right(self):\\n return RotatedShape(shape_in=self.tail_shaft_circle[1],\\n rotation_point=self.tail_shaft_circle[0].center,\\n vector=Vector(0, 1, 0),\\n angle=radians(90))\",\n \"def moveRightArm(self, pitch): # add yaw!\\n\\n\\t\\tangles = [pitch, 12, 39, 3, -8] # angles in degrees\\n\\t\\tangles = [math.radians(angle) for angle in angles] # convert to radians\\n\\t\\tangles.append(1) # also open hand\\n\\t\\ttimes = [1, 1, 1.5, 1.5, 1.5, 1.5]\\n\\t\\tself.motion.angleInterpolation(\\\"RArm\\\", angles, times, True) # move to those arm angles and open hand\",\n \"def _derY(self, x, y):\\n raise NotImplementedError()\",\n \"def right(self, angle):\\r\\n self.rotation += angle\",\n \"def rotate_about_y(self, deg):\\n if self.x is None:\\n raise AttributeError('rotate_about_y: no X component')\\n if self.z is None:\\n raise AttributeError('rotate_about_y: no Z component')\\n\\n sine = sin(radians(deg))\\n cosine = cos(radians(deg))\\n x_new = self.x*cosine - self.z*sine\\n self.z = self.z*cosine + self.x*sine\\n self.x = x_new\",\n \"def rz(self, phi, q): # pylint: disable=invalid-name\\n return self.append(RZGate(phi), [q], [])\",\n \"def right_angle_axes(self, right_angle_axes):\\n\\n self.container['right_angle_axes'] = right_angle_axes\",\n \"def INY(self, *_):\\n self._dec_or_inc_register('Y', increment=True)\",\n \"def set_ypos(self, deg):\\n if deg < -10:\\n deg = -10\\n elif deg > 10:\\n deg = 10\\n deg += 10\\n self.kit.servo[8].angle = deg\",\n \"def rotate_right(self, speed):\\n\\t\\t# You should modify the bias of 4 wheels depending on your hardware.\\n\\t\\tself._front_left_wheel.anticlockwise_rotate(speed + LEFT_FR_BIAS + LEFT_RIGHT_BIAS)\\n\\t\\tself._front_right_wheel.anticlockwise_rotate(speed + RIGHT_FR_BIAS)\\n\\t\\tself._rear_left_wheel.anticlockwise_rotate(speed + 1 + LEFT_RIGHT_BIAS)\\n\\t\\tself._rear_right_wheel.anticlockwise_rotate(speed)\",\n \"def vel_y(self, *args, **kwargs) -> Any:\\n pass\",\n \"def _get_y(self):\\n enabled = self.num_enabled\\n\\n if self.heart_enabled:\\n self._heart_y = 45*(self.num_enabled - enabled) + 75\\n enabled -= 1\\n if self.speed_enabled:\\n self._speed_y = 45*(self.num_enabled - enabled) + 75\\n enabled -= 1\\n if self.cadence_enabled:\\n self._cadence_y = 45*(self.num_enabled - enabled) + 75\\n enabled -= 1\\n if self.ams_enabled:\\n self._ams_y = 45*(self.num_enabled - enabled) + 75\\n enabled -= 1\",\n \"def _create_raindrops_y(self, raindrop_y):\\n r_calc = self._calculate_spacing()\\n for raindrop_x in range(r_calc[2]):\\n self._create_raindrop(raindrop_x, raindrop_y)\",\n \"def lrbt_rot(self):\\n l, r, b, t = self._ext[0], self._ext[1], self._ext[2], self._ext[3]\\n if self.__rot90 % 4 == 1: # -90deg\\n self._ext = [b, t, l, r]\\n elif self.__rot90 % 4 == 2: # -180deg\\n self._ext = [r, l, t, b]\\n elif self.__rot90 % 4 == 3: # -270deg\\n self._ext = [t, b, r, l]\",\n \"def setRPY(self, roll, pitch, yaw):\\n\\n currentmat = self.__objbdb.get_homomat()\\n currentmatnp = base.pg.mat4ToNp(currentmat)\\n newmatnp = rm.rotmat_from_euler(roll, pitch, yaw, axes=\\\"sxyz\\\")\\n self.setMat(base.pg.npToMat4(newmatnp, currentmatnp[:, 3]))\",\n \"def DEY(self, *_):\\n self._dec_or_inc_register('Y', increment=False)\",\n \"def yy(target1: QubitInput, target2: QubitInput, angle: float) -> Instruction:\\n return Instruction(YY(angle), target=[target1, target2])\",\n \"def calculate_R2(self):\\n\\n d1 = self.T - self.Y\\n d2 = self.T - self.T.mean()\\n\\n self.r2 = 1 - d1.dot(d1) / d2.dot(d2)\\n self.r2 = format(self.r2, '.3f')\\n\\n print \\\"\\\"\\n print \\\"R2:\\\", self.r2\",\n \"def rotxaxis(ya, za, angle):\\n\\n y = ya * math.cos(angle) - za * math.sin(angle) \\n z = ya * math.sin(angle) + za * math.cos(angle)\\n \\n return y, z\",\n \"def speedup_y(self):\\r\\n new_speed = math.sin((self.__direction*math.pi)/180) + self.__y_speed\\r\\n self.__y_speed = new_speed\",\n \"def getGYR(self, axis='X'):\\r\\n\\t\\tscale = self.getScale(mode='GYR')[0]\\r\\n\\t\\tif axis.upper() == 'X':\\r\\n\\t\\t\\treg = 0x43\\r\\n\\t\\telif axis.upper() == 'Y':\\r\\n\\t\\t\\treg = 0x45\\r\\n\\t\\telif axis.upper() == 'Z':\\r\\n\\t\\t\\treg = 0x47\\r\\n\\t\\telse:\\r\\n\\t\\t\\treturn False\\r\\n\\t\\tgyr_H = self.read(reg)\\r\\n\\t\\tgyr_L = self.read(reg+1)\\r\\n\\t\\tgyrRaw = self.twos_comp(val=(gyr_H*256 + gyr_L),bits=16)\\r\\n\\t\\treturn scale*(gyrRaw/float(2**15)), gyrRaw\",\n \"def y(self):\\n pass\",\n \"def rotate_right(self):\\n current = compass.index(self.heading)\\n return replace(self, heading=compass[(current + 1) % 4])\",\n \"def y(self):\\n return self._turtle.ycor()\",\n \"def y(self):\\n return self._turtle.ycor()\",\n \"def right_rotation(self, ang_vel):\\n vel = self.om_left_max * self.R + ang_vel * self.L\\n om_right = (vel + ang_vel * self.L) / self.R \\n return vel, om_right\",\n \"def y_operators(self) -> List[PauliTerm]:\\n # Y = iXZ\\n y_operators = [1j * x_op * z_op\\n for x_op, z_op in zip(self.x_operators(), self.z_operators())]\\n for y_op in y_operators:\\n assert y_op.coefficient == 1\\n return y_operators\",\n \"def Get_RawOutY_Value(self):\\r\\n l = self.__readFromRegister(self.__REG_R_OUT_Y_L, 0xff)\\r\\n h_u2 = self.__readFromRegister(self.__REG_R_OUT_Y_H, 0xff)\\r\\n h = bitOps.TwosComplementToByte(h_u2)\\r\\n if (h < 0):\\r\\n return (h*256 - l) * self.gain\\r\\n elif (h >= 0):\\r\\n return (h*256 + l) * self.gain\",\n \"def set_y(self, new_y):\\r\\n self.y = new_y\",\n \"def rotation3D_y(angle: float) -> np.array:\\n c = np.cos(angle)\\n s = np.sin(angle)\\n return np.array([[c, 0.0, s], [0.0, 1.0, 0.0], [-s, 0.0, c]])\",\n \"def Rotate(X,Y,sintheta=0,costheta=1):\\n X1 = X * costheta - Y * sintheta \\n Y1 = X * sintheta + Y * costheta \\n return X1,Y1\",\n \"def on_r_joy_y(self):\\r\\n self.log()\",\n \"def rotation_center_y(self, *args, **kwargs) -> Any:\\n pass\",\n \"def moveY(self, slice, dir=1):\\n\\n for p in self.pieces: # Filter pieces not in slice.\\n if slice > 1 or p.y == slice:\\n # Use PMatrix2D() to calculate position from rotation.\\n t = PMatrix2D()\\n t.rotate(dir * HALF_PI)\\n t.translate(p.x, p.z)\\n p.rY(dir)\\n p.pos(round(t.m02), round(p.y), round(t.m12))\",\n \"def setY(self, y):\\r\\n\\t\\tself._y=y\",\n \"def _derY(self, w, x, y, z):\\n raise NotImplementedError()\",\n \"def move_right(self):\\n self.yaw_motor.step_forward()\",\n \"def rotate_y(p, a=0):\\n # turn value to radians\\n a = math.radians(a)\\n translation_mat = np.matrix([\\n [math.cos(a),0,-math.sin(a),0],\\n [0,1,0,0],\\n [math.sin(a),0,math.cos(a),0],\\n [0,0,0,1],\\n ], dtype=\\\"float32\\\")\\n\\n new_p = p @ translation_mat\\n\\n return new_p\",\n \"def y(self, value):\\n self.validate_input(y=value)\\n self.__y = value\",\n \"def ystep(self):\\n\\n # Update t step\\n tprv = self.t\\n self.t = self.momentum.update(self.var_momentum())\\n\\n # Update Y\\n if self.opt['Monotone'] and self.k > 0:\\n self.Y = self.X + (tprv / self.t) * (self.ZZ - self.X) \\\\\\n + ((tprv - 1.) / self.t) * (self.X - self.Xprv)\\n else:\\n self.Y = self.X + ((tprv - 1.) / self.t) * (self.X - self.Xprv)\",\n \"def gen_y(self, y_func):\\n assert not np.all(self.x == None)\\n assert not np.all(self.act == None)\\n self.y = y_func(self.x, self.act, self.ydim, self.generator)\",\n \"def base_roll_pitch_yaw(self):\\n #raise NotImplementedError('Not yet implemented!')\\n return np.asarray([self._robot_state.roll, self._robot_state.pitch, self._robot_state.yaw])\",\n \"def _gen_r(theta, phi):\\n return _gen_u(theta, phi - np.pi / 2, phi + np.pi / 2)\",\n \"def base_roll_pitch_yaw_rate(self):\\n return np.asarray([self._robot_state.roll_rate, self._robot_state.pitch_rate, self._robot_state.yaw_rate])\",\n \"def rotate(Y,Mat):\\r\\n # Converting angle into radians \\r\\n Y = radians(Y)\\r\\n # RM is the Rotation Matrix (3 X 3)\\r\\n RM=[[cos(Y),-sin(Y),0],[sin(Y),cos(Y),0],[0,0,1]]\\r\\n Rotate_Matrix = Multiply(RM,Mat)\\r\\n # Rotate_Matrix[0][0] is the updated x coordinate\\r\\n # Rotate_Matrix[1][0] is the updated y coordinate\\r\\n return Rotate_Matrix[0][0],Rotate_Matrix[1][0],Rotate_Matrix[2][0]\",\n \"def _derY(self, x, y, z):\\n raise NotImplementedError()\",\n \"def __set_y__(self,y):\\n\\n # Input vaidation\\n try:\\n y = int(y)\\n except:\\n raise ValueError('H Bridge direction is not valid')\\n \\n if(y != 0 and y != 1 and y != -1):\\n raise ValueError('H Bridge direction is not valid')\\n \\n self.direction['y'] = y\\n self.HBridges['y'].SetDirection(y)\",\n \"def Y(self, value):\\n self._Y = value\",\n \"def rotate_rad(self, angle):\\n self.beam_angle += angle\\n self.xy = rotate(self.xy, angle)\\n self.angle += angle\",\n \"def rotateY(self, angle):\\r\\n if angle:\\r\\n c = cos(radians(angle))\\r\\n s = sin(radians(angle))\\r\\n self.mtrx = dot([[c, 0, -s, 0],\\r\\n [0, 1, 0, 0],\\r\\n [s, 0, c, 0],\\r\\n [0, 0, 0, 1]],\\r\\n self.mtrx)\\r\\n self.rtn[1] = angle\\r\\n self.was_moved = True\",\n \"def getNextRight(y, x, majorDir, minorDir):\\n x += 1\\n if x == SZ:\\n y = (y + 1) if minorDir == Direction.DOWN else (y - 1)\\n x = SZ - 1\\n majorDir = Direction.LEFT\\n return y, x, majorDir\",\n \"def rot(wx, wy, order, dist):\\n for _ in range(dist//90):\\n if order == \\\"R\\\":\\n wx, wy = wy, -wx\\n elif order == \\\"L\\\":\\n wx, wy = -wy, wx\\n return wx, wy\",\n \"def rot_axis_angle_to_ypr(degrees: float, q: Quaternion, source: np.ndarray) -> tuple:\\n rotation_matrix = get_rotmat(radians(degrees), q[0], q[1], q[2])\\n return rotation_matrix_to_ypr(np.matmul(rotation_matrix, source))\",\n \"def __init__(self, phi):\\n super().__init__(\\\"rz\\\", 1, [phi])\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def r2(t, y):\\n\\treturn r2_score(t, y)\",\n \"def RZZ(self, theta:Union[int, float], qubit_expr): \\n self.apply_gate_operation(RZZ(theta), qubit_expr)\",\n \"def TYA(self, *_):\\n self.reg.A = self.reg.Y\\n self.reg.N = self.reg.A << 7\\n self.reg.Z = self.reg.A == 0\",\n \"def right_angle_axes(self):\\n return self.container['right_angle_axes']\",\n \"def roty(self, t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[c, 0, s],\\n [0, 1, 0],\\n [-s, 0, c]])\",\n \"def RotZYX_to_RPY(r: array):\\n\\n # Make sure that r is an array and reshape it to be a 3x3 matrix\\n r = array(r).reshape((3, 3))\\n\\n # Compute the corresponding quaternions\\n q = Rot_to_quaternion(r)\\n\\n # Compute the euler angles from the quaternion\\n return quaternion_to_RPY(q)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68476254","0.68437636","0.680894","0.63921726","0.6370722","0.6315495","0.6244407","0.6156097","0.6085259","0.6055177","0.5998596","0.597493","0.59547675","0.5952168","0.5931695","0.5923278","0.5902155","0.5877389","0.5856021","0.58337736","0.5821165","0.5766664","0.57435286","0.57435286","0.573349","0.5726016","0.57148683","0.5647376","0.557858","0.557735","0.5573571","0.5544937","0.552462","0.5508825","0.5461883","0.5450326","0.5444553","0.5411756","0.541089","0.5401461","0.53796184","0.53796095","0.537807","0.536566","0.5361631","0.53482807","0.5345905","0.53378725","0.5315261","0.5310296","0.5299376","0.52894205","0.52870953","0.5265617","0.52526104","0.5240942","0.5232371","0.5224378","0.52093464","0.51780623","0.5164236","0.5158034","0.5146631","0.5146631","0.5134496","0.5127851","0.5121553","0.51194465","0.5107801","0.5104595","0.50992054","0.5095971","0.5089327","0.5084894","0.50760365","0.5075075","0.5064125","0.50589013","0.5051491","0.504915","0.5045744","0.5034353","0.50342095","0.5033688","0.5020369","0.50156164","0.5013851","0.50132346","0.5010866","0.500998","0.50003606","0.4997514","0.49948862","0.4993995","0.49896616","0.49827996","0.49827713","0.4979444","0.4974919","0.49710613"],"string":"[\n \"0.68476254\",\n \"0.68437636\",\n \"0.680894\",\n \"0.63921726\",\n \"0.6370722\",\n \"0.6315495\",\n \"0.6244407\",\n \"0.6156097\",\n \"0.6085259\",\n \"0.6055177\",\n \"0.5998596\",\n \"0.597493\",\n \"0.59547675\",\n \"0.5952168\",\n \"0.5931695\",\n \"0.5923278\",\n \"0.5902155\",\n \"0.5877389\",\n \"0.5856021\",\n \"0.58337736\",\n \"0.5821165\",\n \"0.5766664\",\n \"0.57435286\",\n \"0.57435286\",\n \"0.573349\",\n \"0.5726016\",\n \"0.57148683\",\n \"0.5647376\",\n \"0.557858\",\n \"0.557735\",\n \"0.5573571\",\n \"0.5544937\",\n \"0.552462\",\n \"0.5508825\",\n \"0.5461883\",\n \"0.5450326\",\n \"0.5444553\",\n \"0.5411756\",\n \"0.541089\",\n \"0.5401461\",\n \"0.53796184\",\n \"0.53796095\",\n \"0.537807\",\n \"0.536566\",\n \"0.5361631\",\n \"0.53482807\",\n \"0.5345905\",\n \"0.53378725\",\n \"0.5315261\",\n \"0.5310296\",\n \"0.5299376\",\n \"0.52894205\",\n \"0.52870953\",\n \"0.5265617\",\n \"0.52526104\",\n \"0.5240942\",\n \"0.5232371\",\n \"0.5224378\",\n \"0.52093464\",\n \"0.51780623\",\n \"0.5164236\",\n \"0.5158034\",\n \"0.5146631\",\n \"0.5146631\",\n \"0.5134496\",\n \"0.5127851\",\n \"0.5121553\",\n \"0.51194465\",\n \"0.5107801\",\n \"0.5104595\",\n \"0.50992054\",\n \"0.5095971\",\n \"0.5089327\",\n \"0.5084894\",\n \"0.50760365\",\n \"0.5075075\",\n \"0.5064125\",\n \"0.50589013\",\n \"0.5051491\",\n \"0.504915\",\n \"0.5045744\",\n \"0.5034353\",\n \"0.50342095\",\n \"0.5033688\",\n \"0.5020369\",\n \"0.50156164\",\n \"0.5013851\",\n \"0.50132346\",\n \"0.5010866\",\n \"0.500998\",\n \"0.50003606\",\n \"0.4997514\",\n \"0.49948862\",\n \"0.4993995\",\n \"0.49896616\",\n \"0.49827996\",\n \"0.49827713\",\n \"0.4979444\",\n \"0.4974919\",\n \"0.49710613\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.64825207"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":81737,"cells":{"query":{"kind":"string","value":"add RZ gate (rotation around Zaxis)."},"document":{"kind":"string","value":"def rz(self, q0, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_Z, qid=[q0], phase=phase, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def rz(self, phi, q): # pylint: disable=invalid-name\n return self.append(RZGate(phi), [q], [])","def rotateZ(self, *args, **kwargs):\n ...","def _r_z(angle: tf.Tensor) -> tf.Tensor:\n zero = tf.constant(0, dtype=tf.float64)\n exponent = tf.complex(zero, angle)\n exp = tf.exp(exponent)\n zero_complex = tf.complex(zero, zero)\n one_complex = tf.complex(tf.constant(1, dtype=tf.float64), zero)\n rz = tf.stack([[one_complex, zero_complex], [zero_complex, exp]])\n\n return rz","def RZ(rotRadian: float):\n return np.array([\n [np.cos(rotRadian), -np.sin(rotRadian), 0],\n [np.sin(rotRadian), np.cos(rotRadian), 0],\n [0, 0, 1]\n ])","def rotate_z(angle):\n log.dev(\"lib.mathp.rotate_z is deprecated. Use lib.rotation.R3 instead.\")\n\n cosA = np.cos(angle)\n sinA = np.sin(angle)\n R = np.array([[cosA, sinA, 0], [-sinA, cosA, 0], [0, 0, 1]])\n return R","def xform_Z_rot( self , thetaZrad ):\r\n self.xform_homog( homogeneous_Z( thetaZrad , [ 0 , 0 , 0 ] ) )","def R_ZigZag(rot):\n\n return Ship(\"R Zig-Zag\",\n rotate_shape([Pos(0,0), Pos(0,1), Pos(1,1), Pos(1,2)], rot))","def rz(self, angle: float) -> \"Mate\":\n a = angle / 180 * pi\n self.x_dir = Mate._rotate(self.x_dir, self.z_dir, a)\n self.y_dir = Mate._rotate(self.y_dir, self.z_dir, a)\n return self","def rz(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\n return self.rotate(rz=angle, center=center)","def rotateZ(self, angle):\r\n if angle:\r\n c = cos(radians(angle))\r\n s = sin(radians(angle))\r\n self.mtrx = dot([[c, s, 0, 0],\r\n [-s, c, 0, 0],\r\n [0, 0, 1, 0],\r\n [0, 0, 0, 1]],\r\n self.mtrx)\r\n self.rtn[2] = angle\r\n self.was_moved = True","def rot_z(angle):\n sangle = math.sin(angle)\n cangle = math.cos(angle)\n rz = np.array([[cangle, sangle, 0.0],\n [-sangle, cangle, 0.0],\n [0.0, 0.0, 1.0]])\n return rz","def z_rotation(self):\n before = ('R', 'r', 'U', 'u', 'L', 'l', 'D', 'd', 'M', 'E', 'x', 'y')\n after = ('U', 'u', 'L', 'l', 'D', 'd', 'R', 'r', 'E', 'M\\'', \"y\", \"x'\")\n solve = self.solve_helper.maketrans(dict(zip(before, after)))\n solve_trans = self.solve_helper.translate(solve)\n solve_trans = solve_trans.replace(\"\\'\\'\", \"\")\n self.solve_helper = solve_trans","def apply_Rz(psi, theta, i, parametrize=False, **gate_opts):\n mtags = _merge_tags({'RZ'}, gate_opts)\n if parametrize:\n G = ops.PArray(rz_gate_param_gen, (float(theta),))\n else:\n G = qu.Rz(float(theta))\n psi.gate_(G, int(i), tags=mtags, **gate_opts)","def rotate_z(self,rad):\n DetElement.rotate_z(self,rad) #python2\n #super().rotate_z(rad) #python3\n for tube in self._list_of_tubes:\n self.__update_tube_pos_after_rotation(tube)\n tube.rotate_z(rad)","def rotationMatrix_RzRyRz(self):\n\n R = Compute3DRotationMatrix_RzRyRz(self.exteriorOrientationParameters[3], self.exteriorOrientationParameters[4],\n self.exteriorOrientationParameters[5])\n\n return R","def zx_rotation(vector,theta):\r\n R = np.array([[np.cos(theta),0,np.sin(theta)],\r\n [0,1,0],\r\n [-np.sin(theta),0,np.cos(theta)]\r\n ])\r\n return np.dot(R,vector)","def Omega_rad_z(self, z):\n return self.Omega_gamma_z(z)+self.Omega_ur_z(z)","def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def Rz(theta, units='deg'):\n if units == 'deg':\n theta = np.deg2rad(theta)\n\n return np.mat([[np.cos(theta), -np.sin(theta), 0],\n [np.sin(theta), np.cos(theta), 0],\n [0, 0, 1]\n ],\n dtype='f8'\n )","def rotateZ(self, ang):\n if ang != 0.0:\n x = self.getX() * cos(ang) - self.getY() * sin(ang)\n y = self.getX() * sin(ang) + self.getY() * cos(ang)\n z = self.getZ()\n self.setX(x)\n self.setY(y)\n self.setZ(z)","def rotate_z(self, angle):\n angle *= np.pi / 180\n return self.transform(np.matrix([[np.cos(angle), -np.sin(angle), 0],\n [np.sin(angle), np.cos(angle), 0],\n [0, 0, 1]]))","def apply_rotation_z(self, theta=0.0 ):\n \n theta = radians(theta)\n new_rotation_matrix = [[ +cos(theta) , -sin(theta) , 0 ],\n [ +sin(theta) , +cos(theta) , 0 ],\n [ 0 , 0 , 1 ]] \n \n self.rotation_matrix_exp = np.dot( new_rotation_matrix, self.rotation_matrix_exp )","def RotationZ(theta):\n\n return Rotation([0., 0., 1.], theta)","def L_ZigZag(rot):\n\n return Ship(\"L Zig-Zag\",\n rotate_shape([Pos(0,0), Pos(0,1), Pos(-1,1), Pos(-1,2)], rot))","def _zig(self):\n if self.parent is not None:\n if self is self.parent.left:\n self._rotateClockwise()\n elif self is self.parent.right:\n self._rotateCounterclockwise()","def Z(self, qubit_expr): \n self.apply_gate_operation('Z', qubit_expr)","def Rz(q):\n sin_q, cos_q = sin(q), cos(q)\n return numpy.matrix([\n [cos_q, sin_q, 0, 0],\n [-sin_q, cos_q, 0, 0],\n [0, 0, 1, 0],\n [0, 0, 0, 1],\n ])","def rotateZ(self, angle):\r\n rad = angle * math.pi / 180\r\n cosa = math.cos(rad)\r\n sina = math.sin(rad)\r\n x = self.x * cosa - self.y * sina\r\n y = self.x * sina + self.y * cosa\r\n return Point3D(x, y, self.z)","def _altaz_rotation(self, jd):\n R_lon = rot_z(- self.longitude.radians - jd.gast * TAU / 24.0)\n return einsum('ij...,jk...,kl...->il...', self.R_lat, R_lon, jd.M)","def multi_rot_Z(angle_rads: numpy.ndarray) -> numpy.ndarray:\n rz = numpy.empty((angle_rads.shape[0], 4, 4))\n rz[...] = numpy.identity(4)\n rz[:, 0, 0] = rz[:, 1, 1] = numpy.cos(angle_rads)\n rz[:, 1, 0] = numpy.sin(angle_rads)\n rz[:, 0, 1] = -rz[:, 1, 0]\n return rz","def rotateZ(self, angle):\n rad = angle * math.pi / 180\n cosa = math.cos(rad)\n sina = math.sin(rad)\n x = self.x * cosa - self.y * sina\n y = self.x * sina + self.y * cosa\n return Point3D(x, y, self.z)","def rotateZ(self, angle):\n rad = angle * math.pi / 180\n cosa = math.cos(rad)\n sina = math.sin(rad)\n x = self.x * cosa - self.y * sina\n y = self.x * sina + self.y * cosa\n return Point3D(x, y, self.z)","def rotateZ(self, angle):\n rad = angle * math.pi / 180\n cosa = math.cos(rad)\n sina = math.sin(rad)\n x = self.x * cosa - self.y * sina\n y = self.x * sina + self.y * cosa\n return Point3D(x, y, self.z)","def rotateZ(self, angle):\n rad = angle * math.pi / 180\n cosa = math.cos(rad)\n sina = math.sin(rad)\n x = self.x * cosa - self.y * sina\n y = self.x * sina + self.y * cosa\n return Point3D(x, y, self.z)","def rotateZ(self, angle):\n\t\trad = angle * math.pi / 180\n\t\tcosa = math.cos(rad)\n\t\tsina = math.sin(rad)\n\t\tx = self.x * cosa - self.y * sina\n\t\ty = self.x * sina + self.y * cosa\n\t\treturn Point3D(x, y, self.z)","def AffineRz(theta, units='deg'):\n if units == 'deg':\n theta = np.deg2rad(theta)\n\n return np.mat([[np.cos(theta), -np.sin(theta), 0, 0],\n [np.sin(theta), np.cos(theta), 0, 0],\n [0, 0, 1, 0],\n [0, 0, 0, 1]\n ],\n dtype='f8'\n )","def RZZ(self, theta:Union[int, float], qubit_expr): \n self.apply_gate_operation(RZZ(theta), qubit_expr)","def rotateZ(self, angle):\n rad = math.radians(angle)\n cosa = math.cos(rad)\n sina = math.sin(rad)\n x = self.x * cosa - self.y * sina\n y = self.x * sina + self.y * cosa\n return Point3D(x, y, self.z)","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def yz_rotation(vector,theta):\r\n R = np.array([[1,0,0],\r\n [0, np.cos(theta),-np.sin(theta)],\r\n [0, np.sin(theta), np.cos(theta)]\r\n ])\r\n return np.dot(R,vector)","def keyZ(self):\n if pyxel.btnp(pyxel.KEY_Z):\n self.rotater(1)","def add_rotation(self, rotation, lump, is_mirrored):\n\n if rotation == '0':\n self.rotations = {'0': lump}\n self.is_mirrored = {'0': False}\n self.has_rotations = False\n\n else:\n self.rotations[rotation] = lump\n self.is_mirrored[rotation] = is_mirrored\n self.has_rotations = True","def ZYZRot(A, B, G, scal=1.0):\n from math import cos\n from math import sin\n from math import radians\n\n rot = np.zeros((3, 3))\n ca = cos(radians(A))\n cb = cos(radians(B))\n cg = cos(radians(G))\n sa = sin(radians(A))\n sb = sin(radians(B))\n sg = sin(radians(G))\n rot[0][0] = ((-sg * sa) + (cb * ca * cg)) * scal\n rot[0][1] = ((sg * ca) + (cb * sa * cg)) * scal\n rot[0][2] = ((-cg * sb)) * scal\n rot[1][0] = ((-cg * sa) - (cb * ca * sg)) * scal\n rot[1][1] = ((cg * ca) - (cb * sa * sg)) * scal\n rot[1][2] = ((sg * sb)) * scal\n rot[2][0] = ((sb * ca)) * scal\n rot[2][1] = ((sb * sa)) * scal\n rot[2][2] = (cb) * scal\n return rot","def xzplane(draw, r, y, shift = np.array([1000, 1000, 0, 0]), scale = 300):\n extent = 2.8\n pln = np.array(\n [\n [-extent,y,0],\n [extent,y,0],\n [extent,y,extent*2],\n [-extent,y,extent*2]\n ]\n )\n pln = np.dot(pln, np.transpose(r))\n pln = pln * scale + shift[:3]\n draw.polygon([(pln[0][0],pln[0][1]),(pln[1][0],pln[1][1]),(pln[2][0],pln[2][1]),(pln[3][0],pln[3][1])], (0,102,255,70))","def rotz(t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[c, -s, 0], [s, c, 0], [0, 0, 1]])","def addZ(self,name):\n return self._addVar(name,self._zNames)","def reverseXZrotation(self):\n rot = np.zeros((3, 3), dtype = 'float64')\n rot[0, 0] = np.cos(self.currtheta)\n rot[0, 1] = -np.sin(self.currtheta)\n rot[0, 2] = 0.0\n rot[1, 0] = np.sin(self.currtheta) * np.cos(self.currphi)\n rot[1, 1] = np.cos(self.currtheta) * np.cos(self.currphi)\n rot[1, 2] = - np.sin(self.currphi)\n rot[2, 0] = np.sin(self.currtheta) * np.sin(self.currphi)\n rot[2, 1] = np.cos(self.currtheta) * np.sin(self.currphi)\n rot[2, 2] = np.cos(self.currphi)\n\n self.ds = np.dot(rot, self.ds1)","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def __ComputeDesignMatrix_RzRyRz(self, groundPoints):\n # initialization for readability\n azimuth = self.exteriorOrientationParameters[3]\n phi = self.exteriorOrientationParameters[4]\n kappa = self.exteriorOrientationParameters[5]\n\n # Coordinates subtraction\n dX = groundPoints[:, 0] - self.exteriorOrientationParameters[0]\n dY = groundPoints[:, 1] - self.exteriorOrientationParameters[1]\n dZ = groundPoints[:, 2] - self.exteriorOrientationParameters[2]\n dXYZ = np.vstack([dX, dY, dZ])\n\n rotationMatrixT = self.rotationMatrix_RzRyRz.T\n rotatedG = rotationMatrixT.dot(dXYZ)\n rT1g = rotatedG[0, :]\n rT2g = rotatedG[1, :]\n rT3g = rotatedG[2, :]\n\n focalBySqauredRT3g = self.camera.focalLength / rT3g ** 2\n\n dxdg = rotationMatrixT[0, :][None, :] * rT3g[:, None] - rT1g[:, None] * rotationMatrixT[2, :][None, :]\n dydg = rotationMatrixT[1, :][None, :] * rT3g[:, None] - rT2g[:, None] * rotationMatrixT[2, :][None, :]\n\n dgdX0 = np.array([-1, 0, 0], 'f')\n dgdY0 = np.array([0, -1, 0], 'f')\n dgdZ0 = np.array([0, 0, -1], 'f')\n\n # Derivatives with respect to X0\n dxdX0 = -focalBySqauredRT3g * np.dot(dxdg, dgdX0)\n dydX0 = -focalBySqauredRT3g * np.dot(dydg, dgdX0)\n\n # Derivatives with respect to Y0\n dxdY0 = -focalBySqauredRT3g * np.dot(dxdg, dgdY0)\n dydY0 = -focalBySqauredRT3g * np.dot(dydg, dgdY0)\n\n # Derivatives with respect to Z0\n dxdZ0 = -focalBySqauredRT3g * np.dot(dxdg, dgdZ0)\n dydZ0 = -focalBySqauredRT3g * np.dot(dydg, dgdZ0)\n\n dRTdOmega = Compute3DRotationDerivativeMatrix_RzRyRz(azimuth, phi, kappa, 'azimuth').T\n dRTdPhi = Compute3DRotationDerivativeMatrix_RzRyRz(azimuth, phi, kappa, 'phi').T\n dRTdKappa = Compute3DRotationDerivativeMatrix_RzRyRz(azimuth, phi, kappa, 'kappa').T\n\n gRT3g = dXYZ * rT3g\n\n # Derivatives with respect to Omega\n dxdOmega = -focalBySqauredRT3g * (dRTdOmega[0, :][None, :].dot(gRT3g) -\n rT1g * (dRTdOmega[2, :][None, :].dot(dXYZ)))[0]\n\n dydOmega = -focalBySqauredRT3g * (dRTdOmega[1, :][None, :].dot(gRT3g) -\n rT2g * (dRTdOmega[2, :][None, :].dot(dXYZ)))[0]\n\n # Derivatives with respect to Phi\n dxdPhi = -focalBySqauredRT3g * (dRTdPhi[0, :][None, :].dot(gRT3g) -\n rT1g * (dRTdPhi[2, :][None, :].dot(dXYZ)))[0]\n\n dydPhi = -focalBySqauredRT3g * (dRTdPhi[1, :][None, :].dot(gRT3g) -\n rT2g * (dRTdPhi[2, :][None, :].dot(dXYZ)))[0]\n\n # Derivatives with respect to Kappa\n dxdKappa = -focalBySqauredRT3g * (dRTdKappa[0, :][None, :].dot(gRT3g) -\n rT1g * (dRTdKappa[2, :][None, :].dot(dXYZ)))[0]\n\n dydKappa = -focalBySqauredRT3g * (dRTdKappa[1, :][None, :].dot(gRT3g) -\n rT2g * (dRTdKappa[2, :][None, :].dot(dXYZ)))[0]\n\n # all derivatives of x and y\n dd = np.array([np.vstack([dxdX0, dxdY0, dxdZ0, dxdOmega, dxdPhi, dxdKappa]).T,\n np.vstack([dydX0, dydY0, dydZ0, dydOmega, dydPhi, dydKappa]).T])\n\n a = np.zeros((2 * dd[0].shape[0], 6))\n a[0::2] = dd[0]\n a[1::2] = dd[1]\n\n return a","def __init__(self, phi):\n super().__init__(\"rz\", 1, [phi])","def rotateZ(self, point):\n\n rad = self.offset_rotation.z * math.pi / 180\n\n cosa = math.cos(rad)\n sina = math.sin(rad)\n\n x = point.x * cosa - point.y * sina\n y = point.x * sina + point.y * cosa\n\n return OpenMaya.MVector(x, y, point.z)","def startAngMovementZ(self):\n self.boolrot[2] = True","def rotz(t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[c, -s, 0],\n [s, c, 0],\n [0, 0, 1]])","def rotz(t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[c, -s, 0],\n [s, c, 0],\n [0, 0, 1]])","def rotz(t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[c, -s, 0],\n [s, c, 0],\n [0, 0, 1]])","def rotz(t):\n c = np.cos(t)\n s = np.sin(t)\n return np.array([[c, -s, 0],\n [s, c, 0],\n [0, 0, 1]])","def Rpz(angle=0, units='deg'):\n\n if(units=='deg'):\n angle = angle*pi/180\n\n C = np.cos(angle)\n S = np.sin(angle)\n\n M = np.identity(3)\n\n M[0,0] = +C\n M[0,1] = -S\n M[1,0] = +S\n M[1,1] = +C\n\n return M","def add_vehicle_z_axis(df):\n x = pd.Series(\n np.zeros(df.shape[0]),\n index=df[\"timestamp\"],\n name=\"T_vehicle_attitude_0__NF_body_z_axis_x\",\n )\n y = pd.Series(\n np.zeros(df.shape[0]),\n index=df[\"timestamp\"],\n name=\"T_vehicle_attitude_0__NF_body_z_axis_y\",\n )\n z = pd.Series(\n np.ones(df.shape[0]),\n index=df[\"timestamp\"],\n name=\"T_vehicle_attitude_0__NF_body_z_axis_z\",\n )\n x, y, z = mpd.series_quatrot(\n x,\n y,\n z,\n df[\"T_vehicle_attitude_0__F_q_0\"],\n df[\"T_vehicle_attitude_0__F_q_1\"],\n df[\"T_vehicle_attitude_0__F_q_2\"],\n df[\"T_vehicle_attitude_0__F_q_3\"],\n )\n\n df[x.name] = x.values\n df[y.name] = y.values\n df[z.name] = z.values","def rotZ(theta, mode = 'radians'):\n\n\tif mode != 'radians' and mode != 'degrees':\n\t\traise ValueError('Mode should either be ``radians`` or ``degrees``.')\n\tif mode == 'degrees':\n\t\ttheta = np.deg2rad(theta)\n\treturn np.matrix([[np.cos(theta), -np.sin(theta), 0], [np.sin(theta), np.cos(theta), 0], \\\n\t\t[0., 0., 1.]])","def rotation3Dz(theta):\n rmat = np.zeros((3,3))\n rmat[0,0] = rmat[1,1] = np.cos(theta)\n rmat[0,1] = np.sin(theta)\n rmat[1,0] = -rmat[0,1]\n rmat[2,2] = 1\n return rmat","def rotate_z(self, angle: float):\n self.vertices = list(\n Matrix44.z_rotate(angle).transform_vertices(self.vertices)\n )\n return self","def signed_r_z(rotation_matrix, positions, core):\n arr = np.array\n pos = arr(positions) - core\n rot_pos = arr(rotation_matrix * pos.T).T\n x = rot_pos[:, 0].T\n y = rot_pos[:, 1].T\n z = rot_pos[:, 2].T\n r = (x ** 2 + y ** 2) ** 0.5 * np.sign(-x)\n return r, z","def coord_rotate_rad(x, y, z):\n #-- 1 --\n xt = math.asin ( math.sin(x) * math.sin(y) +\n math.cos(x) * math.cos(y) * math.cos(z) )\n #-- 2 --\n yt = math.acos ( ( math.sin(x) - math.sin(y) * math.sin(xt) ) /\n ( math.cos(y) * math.cos(xt) ) )\n #-- 3 --\n if math.sin(z) > 0.0:\n yt = TWO_PI - yt\n\n #-- 4 --\n return (xt, yt)","def test_z_rot(self):\n\n # Create a Matrix representing 90 deg z rot.\n mat = Matrix44.from_rot_z(90)\n # Use from_matrix44()\n quat = Quat.from_matrix44(mat)\n\n # Ensure the quat matches a 90 degree x rotation.\n expected = Quat.from_axis_angle_deg(Vec3(0, 0, 1), 90)\n AssertQuatAlmostEqual(quat, expected, self)","def rot_z(theta):\n theta_rad = np.radians(theta)\n rotation_matrix = [[np.cos(theta_rad), -np.sin(theta_rad), 0],\n [np.sin(theta_rad), np.cos(theta_rad), 0],\n [0, 0, 1]]\n return np.matrix(rotation_matrix)","def rotateZ(self, theta):\n rot_m = numpy.array([[numpy.sin(theta), numpy.cos(theta)], \\\n [numpy.cos(theta), -numpy.sin(theta)]])\n for sec in self.all:\n for i in range(int(nrn.n3d())):\n xy = numpy.dot([nrn.x3d(i), nrn.y3d(i)], rot_m)\n nrn.pt3dchange(i, float(xy[0]), float(xy[1]), nrn.z3d(i), \\\n nrn.diam3d(i))","def _derZ(self, x, y, z):\n raise NotImplementedError()","def rotate(self, x=0, y=0, z=0):\n\t\tquaternion = R.from_euler('xyz', [x, y, z], degrees=True)\n\t\trotation_matrix = np.array(quaternion.as_matrix())\n\t\trotation_matrix = np.pad(rotation_matrix, [(0, 1), (0, 1)], mode='constant')\n\t\trotation_matrix[3,3] = 1\n\n\t\tself.matrix = np.matmul(self.matrix, rotation_matrix)","def compute_Az(self, r, z, qOc):\n\n kr_cross_r = einsum('r, p -> rp', self.kr, r)\n kz_cross_z = einsum('z, p -> zp', self.kz, z)\n delta_r = np.ones(np.size(r)) * self.ptcl_width_r\n delta_u = einsum('r, p -> rp', self.kr, delta_r)\n convolved_j0 = self.convolved_j0(kr_cross_r, delta_u)\n convolved_cos = einsum('zp, z -> zp', cos(kz_cross_z), self.shape_function_z)\n\n modeQz = self.omegaOtwokr * (self.dc_coords[:,:,1] + self.omega_coords[:,:,1])\n\n self.tanhz = -np.tanh(((z - self.z_mean) ** 2 - self.z_mean ** 2) * self.tanh_width ** 2)\n # We dress the charge instead of the fields proper\n dressed_charge = self.tanhz*qOc\n\n Az = einsum('zr, rp, zp -> p', modeQz, convolved_j0, convolved_cos)*dressed_charge\n\n return Az","def add_desired_z_axis(df):\n x = pd.Series(\n np.zeros(df.shape[0]),\n index=df[\"timestamp\"],\n name=\"T_vehicle_attitude_setpoint_0__NF_body_z_axis_sp_x\",\n )\n y = pd.Series(\n np.zeros(df.shape[0]),\n index=df[\"timestamp\"],\n name=\"T_vehicle_attitude_setpoint_0__NF_body_z_axis_sp_y\",\n )\n z = pd.Series(\n np.ones(df.shape[0]),\n index=df[\"timestamp\"],\n name=\"T_vehicle_attitude_setpoint_0__NF_body_z_axis_sp_z\",\n )\n\n x, y, z = mpd.series_quatrot(\n x,\n y,\n z,\n df[\"T_vehicle_attitude_setpoint_0__F_q_d_0\"],\n df[\"T_vehicle_attitude_setpoint_0__F_q_d_1\"],\n df[\"T_vehicle_attitude_setpoint_0__F_q_d_2\"],\n df[\"T_vehicle_attitude_setpoint_0__F_q_d_3\"],\n )\n df[x.name] = x.values\n df[y.name] = y.values\n df[z.name] = z.values","def ZZRotation(angle):\r\n return Diagonal(2,\r\n np.array([[np.exp(1j * angle), np.exp(-1j * angle)],\r\n [np.exp(-1j * angle), np.exp(1j * angle)]]),\r\n 'R_ZZ({})'.format(angle))","def ComputeExteriorOrientation_RzRyRz(self, imagePoints, groundPoints, epsilon):\n # cameraPoints = self.ImageToCamera(imagePoints)\n cameraPoints = imagePoints\n self.exteriorOrientationParameters[0:3] = np.dot(self.rotationMatrix_RzRyRz, self.exteriorOrientationParameters[0:3])\n self.exteriorOrientationParameters = np.add(self.exteriorOrientationParameters, np.random.normal(0, 0.01, self.exteriorOrientationParameters.shape))\n l0 = self.__ComputeObservationVector_RzRyRz(groundPoints.T)\n l0 = np.reshape(l0, (-1, 1))\n l = cameraPoints.reshape(np.size(cameraPoints), 1) - l0\n A = self.__ComputeDesignMatrix_RzRyRz(groundPoints.T)\n\n N = np.dot(A.T, A)\n u = np.dot(A.T, l)\n deltaX = np.dot(la.inv(N), u)\n\n # update orientation pars\n self.__exteriorOrientationParameters = np.add(self.__exteriorOrientationParameters, np.reshape(deltaX, 6))\n\n while la.norm(deltaX) > epsilon:\n l0 = self.__ComputeObservationVector_RzRyRz(groundPoints.T)\n l0 = np.reshape(l0, (-1, 1))\n l = cameraPoints.reshape(np.size(cameraPoints), 1) - l0\n A = self.__ComputeDesignMatrix_RzRyRz(groundPoints.T)\n N = np.dot(A.T, A)\n u = np.dot(A.T, l)\n deltaX = np.dot(la.inv(N), u)\n # update orientation pars\n self.__exteriorOrientationParameters = np.add(self.__exteriorOrientationParameters, np.reshape(deltaX, 6))\n\n # compute residuals\n l_a = np.reshape(self.__ComputeObservationVector_RzRyRz(groundPoints.T), (-1, 1))\n v = l_a - cameraPoints.reshape(np.size(cameraPoints), 1)\n if (np.size(A, 0) - np.size(deltaX)) != 0:\n sig = np.dot(v.T, v) / (np.size(A, 0) - np.size(deltaX))\n sigmaX = sig[0] * la.inv(N)\n else:\n sigmaX = None\n\n return [self.exteriorOrientationParameters, sigmaX, v]","def _derZ(self, w, x, y, z):\n raise NotImplementedError()","def rotation(x1, z1, x2, z2):\n e1 = np.zeros(shape=(3, 3))\n e2 = np.zeros(shape=(3, 3))\n e1[0, :] = x1 / np.linalg.norm(x1)\n e1[2, :] = z1 / np.linalg.norm(z1)\n e1[1, :] = np.cross(e1[2, :], e1[0, :])\n e2[0, :] = x2 / np.linalg.norm(x2)\n e2[2, :] = z2 / np.linalg.norm(z2)\n e2[1, :] = np.cross(e2[2, :], e2[0, :])\n R = np.zeros(shape=(3, 3))\n for i in range(3):\n for j in range(3):\n R[i, j] = np.dot(e1[i, :], e2[j, :])\n R = np.transpose(R)\n return R","def rotation(x,y,z):\r\n phi = np.arctan(z/sqrt(x**2+y**2))\r\n lamb = np.arctan2(y,x)\r\n G = np.array([[-sin(lamb), cos(lamb), 0],\r\n [-sin(phi) * cos(lamb), -sin(phi) * sin(lamb), cos(phi)],\r\n [cos(phi) * cos(lamb), cos(phi) * sin(lamb), sin(phi)]])\r\n return (G)","def set_z(self, operator_):\n nbr_params = len(signature(operator_).parameters)\n if nbr_params is 2:\n def oper(z):\n if len(z) == self.N+self.M:\n x = z[0:self.N]\n y = z[self.N:self.N+self.M]\n fx, fy, _ = operator_(x,y)\n if fy is None:\n return fx\n return np.concatenate((fx,fy))\n else:\n raise ValueError('set_z(operator_); len of z not correct. Please refer to the documentation.') \n return oper\n elif nbr_params is 3:\n def oper(z):\n if len(z) == self.N+self.M+self.U:\n x = z[0:self.N]\n y = z[self.N:self.N+self.M]\n u = z[self.N+self.M:self.N+self.M+self.U]\n fx, fy, fu = operator_(x,y,u)\n if fy is None:\n return fx\n return np.concatenate((fx,fy,fu))\n else:\n raise ValueError('set_z(operator_); len of z not correct. Please refer to the documentation.') \n return oper\n else : \n raise ValueError('set_z(operator_); operator can only have either 2 or 3 inputs. Please refer to the documentation.')","def rotateAlignXform(self):\n r = np.concatenate(([self.x], [self.y], [self.z]), 0)\n r = np.concatenate((r, np.array([[0,0,0]])), 0)\n r = np.concatenate((r, np.array([0,0,0,1]).reshape(-1,1)), 1)\n return r","def rplot(Qz, R, format):\n # plt.hold(True)\n plt.figure()\n for name,xs in zip(('++','+-','-+','--'),R):\n rr = xs.real\n if (rr>1e-8).any():\n plt.plot(Qz, rr, format, label=name + 'r')\n plt.legend()\n plt.figure()\n for name,xs in zip(('++','+-','-+','--'),R):\n ri = xs.imag\n if (ri>1e-8).any():\n plt.plot(Qz, ri, format, label=name + 'i')\n plt.legend()\n\n plt.figure()\n for name,xs in zip(('++','+-','-+','--'),R):\n phi = np.arctan2(xs.imag, xs.real)\n if (ri>1e-8).any():\n plt.plot(Qz, phi, format, label=name + 'i')\n plt.legend()","def z_rotmat(theta):\n cos_t = np.cos(theta)\n sin_t = np.sin(theta)\n return np.array([[cos_t, -sin_t, 0],\n [sin_t, cos_t, 0],\n [0, 0, 1]])","def compute_Ar(self, r, z, qOc):\n\n kz_cross_z = einsum('z, p -> zp', self.kz, z)\n kr_cross_r = einsum('r, p -> rp', self.kr, r)\n delta_r = np.ones(np.size(r))*self.ptcl_width_r\n delta_u = einsum('r, p -> rp', self.kr, delta_r)\n j1 = self.convolved_j1(kr_cross_r, delta_u)\n convolved_sin = einsum('zp, z -> zp', sin(kz_cross_z), self.shape_function_z)\n\n modeQr = self.omegaOtwokz * (self.dc_coords[:,:,1] - self.omega_coords[:,:,1])\n\n self.tanhz = -np.tanh(((z - self.z_mean) ** 2 - self.z_mean ** 2) * self.tanh_width ** 2)\n # We dress the charge instead of the fields proper\n dressed_charge = self.tanhz*qOc\n\n\n Ar = einsum('zr, rp, zp -> p', modeQr, j1, convolved_sin)*dressed_charge\n\n return Ar","def test_revolute(self):\n # Rotate around the z axis\n r = Joint.revolute(np.array([0, 0, 1]))\n t_mat = r(np.array([np.pi / 2]))\n rot_vec = np.dot(t_mat, np.array([1, 0, 0, 1]))[:3]\n self.assertTrue(np.allclose(\n rot_vec, np.array([0, 1, 0]), rtol=1e-5, atol=1e-5))","def findRotationMatrix(xS, yS, zS):\n dist = zS**2+xS**2\n #make transformation of z-y plane using angle from linear fit\n xS = np.reshape(xS, (-1,1))\n zS = np.reshape(zS, (-1,1))\n turns = np.argpartition(dist, -250)[:-250]\n# #use ransac to obtain a fit of all non-turn points \n# #(use the fact there are more non-turns than turn points\n# reg = linear_model.RANSACRegressor()\n# reg.fit(zS, xS)\n# #use ransac outliers to fit\n# # turns only - fit to align to z-axis\n# turns = np.where(reg.inlier_mask_==False)[0]\n # fit outliers (turns) only\n reg = linear_model.LinearRegression()\n reg.fit(xS[turns], zS[turns]) \n # outliers need to align with z\n theta = np.pi/2.-np.arctan(reg.coef_[0])[0]\n c, s = np.cos(theta), np.sin(theta)\n R = np.matrix([[0,1,0],[c,0, -s], [s,0, c]])\n\n return R","def test_rotate_around_v3_z_axis(self):\n from pedemath.vec3 import rotate_around_vector_v3\n\n vec_a = Vec3(3, 4, 5)\n vec_b = Vec3(0, 0, 1)\n\n result = rotate_around_vector_v3(vec_a, math.pi, vec_b)\n expected = Vec3(-3, -4, 5)\n\n self.assertAlmostEqual(result.x, expected.x)\n self.assertAlmostEqual(result.y, expected.y)\n self.assertAlmostEqual(result.z, expected.z)","def R(rpy):\n Rx_roll = sp.Matrix(\n [\n [1, 0, 0],\n [0, sp.cos(rpy[0]), -sp.sin(rpy[0])],\n [0, sp.sin(rpy[0]), sp.cos(rpy[0])],\n ]\n )\n Ry_pitch = sp.Matrix(\n [\n [sp.cos(rpy[1]), 0, sp.sin(rpy[1])],\n [0, 1, 0],\n [-sp.sin(rpy[1]), 0, sp.cos(rpy[1])],\n ]\n )\n Rz_yaw = sp.Matrix(\n [\n [sp.cos(rpy[2]), -sp.sin(rpy[2]), 0],\n [sp.sin(rpy[2]), sp.cos(rpy[2]), 0],\n [0, 0, 1],\n ]\n )\n R = Rx_roll * Ry_pitch * Rz_yaw\n return R","def rotate(self, z_dim=False):\n self.x_displacement = np.format_float_scientific(\n self.length / 2 * np.cos(self.angle * np.pi / 360), precision=1\n )\n self.y_displacement = np.format_float_scientific(\n self.length / 2 * np.sin(self.angle * np.pi / 360), precision=1\n )\n zd = z_dim\n if zd == True:\n self.z_angle = random.uniform(1, 180)\n self.z_displacement = np.format_float_scientific(\n self.length / 2 * np.sin(self.z_angle * np.pi / 360), precision=1\n )\n else:\n self.z_displacement = 0\n self.z_angle = 0\n return [self.x_displacement, self.y_displacement, self.z_displacement]","def rz(target: QubitInput, angle: float) -> Iterable[Instruction]:\n return [Instruction(Rz(angle), target=qubit) for qubit in QubitSet(target)]","def ryrz_decomposer(gate: OneQubitGate) -> List[Union[RYGate, RZGate]]:\n mat = gate.matrix()\n assert mat.shape == (2, 2)\n assert check_unitarity(mat)\n gamma = cmath.phase(mat[0, 0])\n mat *= cmath.exp(-1j * gamma)\n assert abs(mat[0, 0].imag) < 1e-8\n cos_halftheta = mat[0, 0].real\n sin_halftheta = 1.0 - cos_halftheta ** 2\n try:\n theta = math.acos(cos_halftheta) * 2\n except ValueError: # math domain error\n assert abs(abs(cos_halftheta) - 1.0) < 1e-8\n if cos_halftheta > 0:\n theta = 0.0\n else:\n theta = math.pi\n if abs(sin_halftheta) < 1e-8:\n phi = 0.0\n lam = cmath.phase(mat[1, 1])\n else:\n phi = cmath.phase(mat[1, 0])\n lam = cmath.phase(mat[0, 1])\n if theta < 1e-8:\n return [RZGate(gate.targets, lam + phi)]\n gates = []\n if lam > 1e-8:\n gates.append(RZGate(gate.targets, lam))\n gates.append(RYGate(gate.targets, theta))\n if phi > 1e-8:\n gates.append(RZGate(gate.targets, phi))\n return gates","def rotate_about_z(self, deg):\n if self.x is None:\n raise AttributeError('rotate_about_z: no X component')\n if self.y is None:\n raise AttributeError('rotate_about_z: no Y component')\n\n sine = sin(radians(deg))\n cosine = cos(radians(deg))\n x_new = self.x*cosine - self.y*sine\n self.y = self.y*cosine + self.x*sine\n self.x = x_new","def make_rotation(self, rotation):\n if rotation == \"r\":\n self.facing += 1\n else:\n self.facing -= 1\n\n if self.facing > 3:\n self.facing = self.facing - 4\n elif self.facing < 0:\n self.facing = self.facing + 4","def rose(data, rz, z=None, ax=None, bins=30, bidirectional=True, color_by=np.mean, plot='yes', png=None, tag=None):\n #adapted from Joe Kington: https://stackoverflow.com/questions/16264837/how-would-one-add-a-colorbar-to-this-example\n\n #create arcs (define top of bin arc)\n bin_offset = math.pi/float(bins)\n bins = np.linspace(0, 2.0*math.pi, bins+1) + bin_offset\n\n if (rz == 'yes'):\n azimuths = np.arctan2(data[:,0], data[:,1])\n else:\n azimuths = np.arctan2(data[:,1], data[:,0])\n weight = data[:,-1]\n wSum = np.sum(weight)\n\n azimuths = np.asanyarray(azimuths)\n if color_by == 'count':\n# z = np.ones_like(azimuths)\n z = weight \n color_by = np.sum\n\n if ax is None:\n fig = plt.figure(1)\n ax = plt.subplot(111, projection='polar')\n if bidirectional:\n other = azimuths + math.pi\n azimuths = np.concatenate([azimuths, other])\n weight = np.concatenate([weight, weight]) \n if z is not None:\n z = np.concatenate([z, z])\n\n # Convert to 0-360, in case negative or >360 azimuths are passed in.\n azimuths[azimuths > math.pi*2.0] -= math.pi*2.0\n azimuths[azimuths < 0] += math.pi*2.0\n counts, edges = np.histogram(azimuths, range=[0, math.pi*2.0], bins=bins, weights=weight)\n\n if z is not None:\n idx = np.digitize(azimuths, edges)\n z = np.array([color_by(z[idx == i]) for i in range(1, idx.max() + 1)])\n z = np.ma.masked_invalid(z)\n cmap = plt.get_cmap('jet')\n coll = colored_bar(edges[:-1], counts/wSum, z=z, width=np.diff(edges), ax=ax, cmap=cmap)\n\n ax.set_aspect('equal')\n ax.autoscale()\n\n ax.set_rmin(0)\n ax.set_thetamin(0)\n ax.set_thetamax(360)\n grid = np.linspace(0, 360, 24+1)[:-1]\n ax.set_thetagrids(grid) \n\n if (rz == 'yes'):\n ax.set_theta_direction(-1)\n ax.set_theta_zero_location('N')\n ax.set_xlabel(r'$\\phi$')\n else:\n ax.set_xlabel(r'$\\theta$')\n\n if tag != None:\n plt.title(tag) \n\n if png != None:\n plt.savefig(get_filename(png,tag=tag), dpi=300)\n\n if plot == 'yes': \n plt.show()\n\n return coll","def moveZ(self, delta):\n self.setZ(delta + self.getZ())","def get_rotation_back_angle(w, r):\n # now let us compute the image of the vector (r,0), that is h(r,0)\n\n zeros = torch.zeros_like(r)\n\n origin_circle = torch.stack([r, zeros], dim=-1) # create (B1, B2, .., B_N, r, 0)\n\n h_orig_circle = h(origin_circle, w, r)\n\n return T_2(h_orig_circle)","def get_rz(self):\n return self.rz","def rotate_orbit(self):\n try:\n ang = self.orbit_speed * self.time_scale / self.refresh_rate\n self.obj.rotate(angle=ang, axis=vector(0, 1, 0), origin=self.star.obj.pos)\n self.sum_ang += ang\n except ZeroDivisionError:\n print(\"ERROR: REFRESH_RATE is 0\")\n except (AttributeError, TypeError):\n print(\"ERROR: wrong arguments type while initializing!!\")","def rotateZUp(self):\n MV = self.MV\n MV[:3, 1] = 0, 0, 1 # 2nd col is up vector, make it point along z axis\n # set bottom left and bottom right z values to zero:\n MV[2, 0] = 0\n MV[2, 2] = 0\n a = MV[0, 0] # grab top left value\n b = np.sqrt(1 - a**2) # calc new complementary value to get normalized vectors\n if MV[1, 0] < 0:\n b = -b # keep b -ve, reduce jumping around of axes\n MV[1, 0] = b\n MV[0, 2] = b\n MV[1, 2] = -a # needs to be -ve of MV[0, 0]\n self.MV = MV","def rotateZUp(self):\n MV = self.MV\n MV[:3, 1] = 0, 0, 1 # 2nd col is up vector, make it point along z axis\n # set bottom left and bottom right z values to zero:\n MV[2, 0] = 0\n MV[2, 2] = 0\n a = MV[0, 0] # grab top left value\n b = np.sqrt(1 - a**2) # calc new complementary value to get normalized vectors\n if MV[1, 0] < 0:\n b = -b # keep b -ve, reduce jumping around of axes\n MV[1, 0] = b\n MV[0, 2] = b\n MV[1, 2] = -a # needs to be -ve of MV[0, 0]\n self.MV = MV","def addThreeNodesRig(self):\r\n cam = self.nativePointer()\r\n\r\n # create controls\r\n pos = mxs.star(radius1 = 6.5, radius2 = 5.5, points=16)\r\n trans = mxs.rectangle(length=10.2, width=4.5)\r\n rot = mxs.ngon(radius=2.0, nSides=3, corner_radius=0.5)\r\n\r\n # rename controls\r\n pos.name = str(cam.name) + 'position'\r\n trans.name = str(cam.name) + 'translation'\r\n rot.name = str(cam.name) + 'rotation'\r\n\r\n # rotate controls into place\r\n pos.rotation = mxs.eulerangles(90, 0 , 0)\r\n trans.rotation = mxs.eulerangles(90, 0 , 0)\r\n rot.rotation = mxs.eulerangles(0, 0, -90)\r\n\r\n # reset xforms\r\n mxs.resetxform(pos)\r\n mxs.resetxform(trans)\r\n mxs.resetxform(rot)\r\n\r\n # collapse xforms\r\n mxs.maxOps.CollapseNode(pos, True)\r\n mxs.maxOps.CollapseNode(trans, True)\r\n mxs.maxOps.CollapseNode(rot, True)\r\n\r\n rot.parent = trans\r\n trans.parent = pos\r\n\r\n pos.wirecolor = rot.wirecolor = trans.wirecolor = mxs.color(0, 230, 250)\r\n\r\n # Move the rig to align with the cam\r\n pivrot=cam.rotation\r\n pos.rotation*=pivrot;\r\n #pos.objectoffsetrot*=pivrot;\r\n #pos.objectoffsetpos*=pivrot;\r\n\r\n pos.position = cam.position\r\n #mxs.resetxform(pos)\r\n #pos.rotation = cam.rotation\r\n\r\n\r\n # parent the cam to to rig\r\n cam.parent = rot\r\n\r\n return True","def matrix_rotate_3d_z(deg: float) -> np.matrix:\n from numpy import cos, sin, pi\n rad_z = -deg * pi/180\n c_z = cos(rad_z)\n s_z = sin(rad_z)\n return np.matrix([[c_z, -s_z, 0], [s_z, c_z, 0], [0, 0, 1]])","def zeta1(self,r1,r2,x,z=0):\n## real dynamics\n return (2.0/3.0*(2.0+self.mu)*self.pkj0(r1,z)*self.pkj0(r2,z)-(self.pkj1mk(r1,z)*self.pkj1pk(r2,z)+self.pkj1mk(r2,z)*self.pkj1pk(r1,z))*x+2.0/3.0*(1-self.mu)*self.pkj2(r1,z)*self.pkj2(r2,z)*(-0.5+1.5*x**2))","def generate(self):\n inside = self.crystal.is_inside(self.x,self.y,self.z)\n X = np.vstack((self.x[inside],self.y[inside],self.z[inside]))\n return self.rot.rotate(X)"],"string":"[\n \"def rz(self, phi, q): # pylint: disable=invalid-name\\n return self.append(RZGate(phi), [q], [])\",\n \"def rotateZ(self, *args, **kwargs):\\n ...\",\n \"def _r_z(angle: tf.Tensor) -> tf.Tensor:\\n zero = tf.constant(0, dtype=tf.float64)\\n exponent = tf.complex(zero, angle)\\n exp = tf.exp(exponent)\\n zero_complex = tf.complex(zero, zero)\\n one_complex = tf.complex(tf.constant(1, dtype=tf.float64), zero)\\n rz = tf.stack([[one_complex, zero_complex], [zero_complex, exp]])\\n\\n return rz\",\n \"def RZ(rotRadian: float):\\n return np.array([\\n [np.cos(rotRadian), -np.sin(rotRadian), 0],\\n [np.sin(rotRadian), np.cos(rotRadian), 0],\\n [0, 0, 1]\\n ])\",\n \"def rotate_z(angle):\\n log.dev(\\\"lib.mathp.rotate_z is deprecated. Use lib.rotation.R3 instead.\\\")\\n\\n cosA = np.cos(angle)\\n sinA = np.sin(angle)\\n R = np.array([[cosA, sinA, 0], [-sinA, cosA, 0], [0, 0, 1]])\\n return R\",\n \"def xform_Z_rot( self , thetaZrad ):\\r\\n self.xform_homog( homogeneous_Z( thetaZrad , [ 0 , 0 , 0 ] ) )\",\n \"def R_ZigZag(rot):\\n\\n return Ship(\\\"R Zig-Zag\\\",\\n rotate_shape([Pos(0,0), Pos(0,1), Pos(1,1), Pos(1,2)], rot))\",\n \"def rz(self, angle: float) -> \\\"Mate\\\":\\n a = angle / 180 * pi\\n self.x_dir = Mate._rotate(self.x_dir, self.z_dir, a)\\n self.y_dir = Mate._rotate(self.y_dir, self.z_dir, a)\\n return self\",\n \"def rz(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\\n return self.rotate(rz=angle, center=center)\",\n \"def rotateZ(self, angle):\\r\\n if angle:\\r\\n c = cos(radians(angle))\\r\\n s = sin(radians(angle))\\r\\n self.mtrx = dot([[c, s, 0, 0],\\r\\n [-s, c, 0, 0],\\r\\n [0, 0, 1, 0],\\r\\n [0, 0, 0, 1]],\\r\\n self.mtrx)\\r\\n self.rtn[2] = angle\\r\\n self.was_moved = True\",\n \"def rot_z(angle):\\n sangle = math.sin(angle)\\n cangle = math.cos(angle)\\n rz = np.array([[cangle, sangle, 0.0],\\n [-sangle, cangle, 0.0],\\n [0.0, 0.0, 1.0]])\\n return rz\",\n \"def z_rotation(self):\\n before = ('R', 'r', 'U', 'u', 'L', 'l', 'D', 'd', 'M', 'E', 'x', 'y')\\n after = ('U', 'u', 'L', 'l', 'D', 'd', 'R', 'r', 'E', 'M\\\\'', \\\"y\\\", \\\"x'\\\")\\n solve = self.solve_helper.maketrans(dict(zip(before, after)))\\n solve_trans = self.solve_helper.translate(solve)\\n solve_trans = solve_trans.replace(\\\"\\\\'\\\\'\\\", \\\"\\\")\\n self.solve_helper = solve_trans\",\n \"def apply_Rz(psi, theta, i, parametrize=False, **gate_opts):\\n mtags = _merge_tags({'RZ'}, gate_opts)\\n if parametrize:\\n G = ops.PArray(rz_gate_param_gen, (float(theta),))\\n else:\\n G = qu.Rz(float(theta))\\n psi.gate_(G, int(i), tags=mtags, **gate_opts)\",\n \"def rotate_z(self,rad):\\n DetElement.rotate_z(self,rad) #python2\\n #super().rotate_z(rad) #python3\\n for tube in self._list_of_tubes:\\n self.__update_tube_pos_after_rotation(tube)\\n tube.rotate_z(rad)\",\n \"def rotationMatrix_RzRyRz(self):\\n\\n R = Compute3DRotationMatrix_RzRyRz(self.exteriorOrientationParameters[3], self.exteriorOrientationParameters[4],\\n self.exteriorOrientationParameters[5])\\n\\n return R\",\n \"def zx_rotation(vector,theta):\\r\\n R = np.array([[np.cos(theta),0,np.sin(theta)],\\r\\n [0,1,0],\\r\\n [-np.sin(theta),0,np.cos(theta)]\\r\\n ])\\r\\n return np.dot(R,vector)\",\n \"def Omega_rad_z(self, z):\\n return self.Omega_gamma_z(z)+self.Omega_ur_z(z)\",\n \"def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def Rz(theta, units='deg'):\\n if units == 'deg':\\n theta = np.deg2rad(theta)\\n\\n return np.mat([[np.cos(theta), -np.sin(theta), 0],\\n [np.sin(theta), np.cos(theta), 0],\\n [0, 0, 1]\\n ],\\n dtype='f8'\\n )\",\n \"def rotateZ(self, ang):\\n if ang != 0.0:\\n x = self.getX() * cos(ang) - self.getY() * sin(ang)\\n y = self.getX() * sin(ang) + self.getY() * cos(ang)\\n z = self.getZ()\\n self.setX(x)\\n self.setY(y)\\n self.setZ(z)\",\n \"def rotate_z(self, angle):\\n angle *= np.pi / 180\\n return self.transform(np.matrix([[np.cos(angle), -np.sin(angle), 0],\\n [np.sin(angle), np.cos(angle), 0],\\n [0, 0, 1]]))\",\n \"def apply_rotation_z(self, theta=0.0 ):\\n \\n theta = radians(theta)\\n new_rotation_matrix = [[ +cos(theta) , -sin(theta) , 0 ],\\n [ +sin(theta) , +cos(theta) , 0 ],\\n [ 0 , 0 , 1 ]] \\n \\n self.rotation_matrix_exp = np.dot( new_rotation_matrix, self.rotation_matrix_exp )\",\n \"def RotationZ(theta):\\n\\n return Rotation([0., 0., 1.], theta)\",\n \"def L_ZigZag(rot):\\n\\n return Ship(\\\"L Zig-Zag\\\",\\n rotate_shape([Pos(0,0), Pos(0,1), Pos(-1,1), Pos(-1,2)], rot))\",\n \"def _zig(self):\\n if self.parent is not None:\\n if self is self.parent.left:\\n self._rotateClockwise()\\n elif self is self.parent.right:\\n self._rotateCounterclockwise()\",\n \"def Z(self, qubit_expr): \\n self.apply_gate_operation('Z', qubit_expr)\",\n \"def Rz(q):\\n sin_q, cos_q = sin(q), cos(q)\\n return numpy.matrix([\\n [cos_q, sin_q, 0, 0],\\n [-sin_q, cos_q, 0, 0],\\n [0, 0, 1, 0],\\n [0, 0, 0, 1],\\n ])\",\n \"def rotateZ(self, angle):\\r\\n rad = angle * math.pi / 180\\r\\n cosa = math.cos(rad)\\r\\n sina = math.sin(rad)\\r\\n x = self.x * cosa - self.y * sina\\r\\n y = self.x * sina + self.y * cosa\\r\\n return Point3D(x, y, self.z)\",\n \"def _altaz_rotation(self, jd):\\n R_lon = rot_z(- self.longitude.radians - jd.gast * TAU / 24.0)\\n return einsum('ij...,jk...,kl...->il...', self.R_lat, R_lon, jd.M)\",\n \"def multi_rot_Z(angle_rads: numpy.ndarray) -> numpy.ndarray:\\n rz = numpy.empty((angle_rads.shape[0], 4, 4))\\n rz[...] = numpy.identity(4)\\n rz[:, 0, 0] = rz[:, 1, 1] = numpy.cos(angle_rads)\\n rz[:, 1, 0] = numpy.sin(angle_rads)\\n rz[:, 0, 1] = -rz[:, 1, 0]\\n return rz\",\n \"def rotateZ(self, angle):\\n rad = angle * math.pi / 180\\n cosa = math.cos(rad)\\n sina = math.sin(rad)\\n x = self.x * cosa - self.y * sina\\n y = self.x * sina + self.y * cosa\\n return Point3D(x, y, self.z)\",\n \"def rotateZ(self, angle):\\n rad = angle * math.pi / 180\\n cosa = math.cos(rad)\\n sina = math.sin(rad)\\n x = self.x * cosa - self.y * sina\\n y = self.x * sina + self.y * cosa\\n return Point3D(x, y, self.z)\",\n \"def rotateZ(self, angle):\\n rad = angle * math.pi / 180\\n cosa = math.cos(rad)\\n sina = math.sin(rad)\\n x = self.x * cosa - self.y * sina\\n y = self.x * sina + self.y * cosa\\n return Point3D(x, y, self.z)\",\n \"def rotateZ(self, angle):\\n rad = angle * math.pi / 180\\n cosa = math.cos(rad)\\n sina = math.sin(rad)\\n x = self.x * cosa - self.y * sina\\n y = self.x * sina + self.y * cosa\\n return Point3D(x, y, self.z)\",\n \"def rotateZ(self, angle):\\n\\t\\trad = angle * math.pi / 180\\n\\t\\tcosa = math.cos(rad)\\n\\t\\tsina = math.sin(rad)\\n\\t\\tx = self.x * cosa - self.y * sina\\n\\t\\ty = self.x * sina + self.y * cosa\\n\\t\\treturn Point3D(x, y, self.z)\",\n \"def AffineRz(theta, units='deg'):\\n if units == 'deg':\\n theta = np.deg2rad(theta)\\n\\n return np.mat([[np.cos(theta), -np.sin(theta), 0, 0],\\n [np.sin(theta), np.cos(theta), 0, 0],\\n [0, 0, 1, 0],\\n [0, 0, 0, 1]\\n ],\\n dtype='f8'\\n )\",\n \"def RZZ(self, theta:Union[int, float], qubit_expr): \\n self.apply_gate_operation(RZZ(theta), qubit_expr)\",\n \"def rotateZ(self, angle):\\n rad = math.radians(angle)\\n cosa = math.cos(rad)\\n sina = math.sin(rad)\\n x = self.x * cosa - self.y * sina\\n y = self.x * sina + self.y * cosa\\n return Point3D(x, y, self.z)\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def yz_rotation(vector,theta):\\r\\n R = np.array([[1,0,0],\\r\\n [0, np.cos(theta),-np.sin(theta)],\\r\\n [0, np.sin(theta), np.cos(theta)]\\r\\n ])\\r\\n return np.dot(R,vector)\",\n \"def keyZ(self):\\n if pyxel.btnp(pyxel.KEY_Z):\\n self.rotater(1)\",\n \"def add_rotation(self, rotation, lump, is_mirrored):\\n\\n if rotation == '0':\\n self.rotations = {'0': lump}\\n self.is_mirrored = {'0': False}\\n self.has_rotations = False\\n\\n else:\\n self.rotations[rotation] = lump\\n self.is_mirrored[rotation] = is_mirrored\\n self.has_rotations = True\",\n \"def ZYZRot(A, B, G, scal=1.0):\\n from math import cos\\n from math import sin\\n from math import radians\\n\\n rot = np.zeros((3, 3))\\n ca = cos(radians(A))\\n cb = cos(radians(B))\\n cg = cos(radians(G))\\n sa = sin(radians(A))\\n sb = sin(radians(B))\\n sg = sin(radians(G))\\n rot[0][0] = ((-sg * sa) + (cb * ca * cg)) * scal\\n rot[0][1] = ((sg * ca) + (cb * sa * cg)) * scal\\n rot[0][2] = ((-cg * sb)) * scal\\n rot[1][0] = ((-cg * sa) - (cb * ca * sg)) * scal\\n rot[1][1] = ((cg * ca) - (cb * sa * sg)) * scal\\n rot[1][2] = ((sg * sb)) * scal\\n rot[2][0] = ((sb * ca)) * scal\\n rot[2][1] = ((sb * sa)) * scal\\n rot[2][2] = (cb) * scal\\n return rot\",\n \"def xzplane(draw, r, y, shift = np.array([1000, 1000, 0, 0]), scale = 300):\\n extent = 2.8\\n pln = np.array(\\n [\\n [-extent,y,0],\\n [extent,y,0],\\n [extent,y,extent*2],\\n [-extent,y,extent*2]\\n ]\\n )\\n pln = np.dot(pln, np.transpose(r))\\n pln = pln * scale + shift[:3]\\n draw.polygon([(pln[0][0],pln[0][1]),(pln[1][0],pln[1][1]),(pln[2][0],pln[2][1]),(pln[3][0],pln[3][1])], (0,102,255,70))\",\n \"def rotz(t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[c, -s, 0], [s, c, 0], [0, 0, 1]])\",\n \"def addZ(self,name):\\n return self._addVar(name,self._zNames)\",\n \"def reverseXZrotation(self):\\n rot = np.zeros((3, 3), dtype = 'float64')\\n rot[0, 0] = np.cos(self.currtheta)\\n rot[0, 1] = -np.sin(self.currtheta)\\n rot[0, 2] = 0.0\\n rot[1, 0] = np.sin(self.currtheta) * np.cos(self.currphi)\\n rot[1, 1] = np.cos(self.currtheta) * np.cos(self.currphi)\\n rot[1, 2] = - np.sin(self.currphi)\\n rot[2, 0] = np.sin(self.currtheta) * np.sin(self.currphi)\\n rot[2, 1] = np.cos(self.currtheta) * np.sin(self.currphi)\\n rot[2, 2] = np.cos(self.currphi)\\n\\n self.ds = np.dot(rot, self.ds1)\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def __ComputeDesignMatrix_RzRyRz(self, groundPoints):\\n # initialization for readability\\n azimuth = self.exteriorOrientationParameters[3]\\n phi = self.exteriorOrientationParameters[4]\\n kappa = self.exteriorOrientationParameters[5]\\n\\n # Coordinates subtraction\\n dX = groundPoints[:, 0] - self.exteriorOrientationParameters[0]\\n dY = groundPoints[:, 1] - self.exteriorOrientationParameters[1]\\n dZ = groundPoints[:, 2] - self.exteriorOrientationParameters[2]\\n dXYZ = np.vstack([dX, dY, dZ])\\n\\n rotationMatrixT = self.rotationMatrix_RzRyRz.T\\n rotatedG = rotationMatrixT.dot(dXYZ)\\n rT1g = rotatedG[0, :]\\n rT2g = rotatedG[1, :]\\n rT3g = rotatedG[2, :]\\n\\n focalBySqauredRT3g = self.camera.focalLength / rT3g ** 2\\n\\n dxdg = rotationMatrixT[0, :][None, :] * rT3g[:, None] - rT1g[:, None] * rotationMatrixT[2, :][None, :]\\n dydg = rotationMatrixT[1, :][None, :] * rT3g[:, None] - rT2g[:, None] * rotationMatrixT[2, :][None, :]\\n\\n dgdX0 = np.array([-1, 0, 0], 'f')\\n dgdY0 = np.array([0, -1, 0], 'f')\\n dgdZ0 = np.array([0, 0, -1], 'f')\\n\\n # Derivatives with respect to X0\\n dxdX0 = -focalBySqauredRT3g * np.dot(dxdg, dgdX0)\\n dydX0 = -focalBySqauredRT3g * np.dot(dydg, dgdX0)\\n\\n # Derivatives with respect to Y0\\n dxdY0 = -focalBySqauredRT3g * np.dot(dxdg, dgdY0)\\n dydY0 = -focalBySqauredRT3g * np.dot(dydg, dgdY0)\\n\\n # Derivatives with respect to Z0\\n dxdZ0 = -focalBySqauredRT3g * np.dot(dxdg, dgdZ0)\\n dydZ0 = -focalBySqauredRT3g * np.dot(dydg, dgdZ0)\\n\\n dRTdOmega = Compute3DRotationDerivativeMatrix_RzRyRz(azimuth, phi, kappa, 'azimuth').T\\n dRTdPhi = Compute3DRotationDerivativeMatrix_RzRyRz(azimuth, phi, kappa, 'phi').T\\n dRTdKappa = Compute3DRotationDerivativeMatrix_RzRyRz(azimuth, phi, kappa, 'kappa').T\\n\\n gRT3g = dXYZ * rT3g\\n\\n # Derivatives with respect to Omega\\n dxdOmega = -focalBySqauredRT3g * (dRTdOmega[0, :][None, :].dot(gRT3g) -\\n rT1g * (dRTdOmega[2, :][None, :].dot(dXYZ)))[0]\\n\\n dydOmega = -focalBySqauredRT3g * (dRTdOmega[1, :][None, :].dot(gRT3g) -\\n rT2g * (dRTdOmega[2, :][None, :].dot(dXYZ)))[0]\\n\\n # Derivatives with respect to Phi\\n dxdPhi = -focalBySqauredRT3g * (dRTdPhi[0, :][None, :].dot(gRT3g) -\\n rT1g * (dRTdPhi[2, :][None, :].dot(dXYZ)))[0]\\n\\n dydPhi = -focalBySqauredRT3g * (dRTdPhi[1, :][None, :].dot(gRT3g) -\\n rT2g * (dRTdPhi[2, :][None, :].dot(dXYZ)))[0]\\n\\n # Derivatives with respect to Kappa\\n dxdKappa = -focalBySqauredRT3g * (dRTdKappa[0, :][None, :].dot(gRT3g) -\\n rT1g * (dRTdKappa[2, :][None, :].dot(dXYZ)))[0]\\n\\n dydKappa = -focalBySqauredRT3g * (dRTdKappa[1, :][None, :].dot(gRT3g) -\\n rT2g * (dRTdKappa[2, :][None, :].dot(dXYZ)))[0]\\n\\n # all derivatives of x and y\\n dd = np.array([np.vstack([dxdX0, dxdY0, dxdZ0, dxdOmega, dxdPhi, dxdKappa]).T,\\n np.vstack([dydX0, dydY0, dydZ0, dydOmega, dydPhi, dydKappa]).T])\\n\\n a = np.zeros((2 * dd[0].shape[0], 6))\\n a[0::2] = dd[0]\\n a[1::2] = dd[1]\\n\\n return a\",\n \"def __init__(self, phi):\\n super().__init__(\\\"rz\\\", 1, [phi])\",\n \"def rotateZ(self, point):\\n\\n rad = self.offset_rotation.z * math.pi / 180\\n\\n cosa = math.cos(rad)\\n sina = math.sin(rad)\\n\\n x = point.x * cosa - point.y * sina\\n y = point.x * sina + point.y * cosa\\n\\n return OpenMaya.MVector(x, y, point.z)\",\n \"def startAngMovementZ(self):\\n self.boolrot[2] = True\",\n \"def rotz(t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[c, -s, 0],\\n [s, c, 0],\\n [0, 0, 1]])\",\n \"def rotz(t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[c, -s, 0],\\n [s, c, 0],\\n [0, 0, 1]])\",\n \"def rotz(t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[c, -s, 0],\\n [s, c, 0],\\n [0, 0, 1]])\",\n \"def rotz(t):\\n c = np.cos(t)\\n s = np.sin(t)\\n return np.array([[c, -s, 0],\\n [s, c, 0],\\n [0, 0, 1]])\",\n \"def Rpz(angle=0, units='deg'):\\n\\n if(units=='deg'):\\n angle = angle*pi/180\\n\\n C = np.cos(angle)\\n S = np.sin(angle)\\n\\n M = np.identity(3)\\n\\n M[0,0] = +C\\n M[0,1] = -S\\n M[1,0] = +S\\n M[1,1] = +C\\n\\n return M\",\n \"def add_vehicle_z_axis(df):\\n x = pd.Series(\\n np.zeros(df.shape[0]),\\n index=df[\\\"timestamp\\\"],\\n name=\\\"T_vehicle_attitude_0__NF_body_z_axis_x\\\",\\n )\\n y = pd.Series(\\n np.zeros(df.shape[0]),\\n index=df[\\\"timestamp\\\"],\\n name=\\\"T_vehicle_attitude_0__NF_body_z_axis_y\\\",\\n )\\n z = pd.Series(\\n np.ones(df.shape[0]),\\n index=df[\\\"timestamp\\\"],\\n name=\\\"T_vehicle_attitude_0__NF_body_z_axis_z\\\",\\n )\\n x, y, z = mpd.series_quatrot(\\n x,\\n y,\\n z,\\n df[\\\"T_vehicle_attitude_0__F_q_0\\\"],\\n df[\\\"T_vehicle_attitude_0__F_q_1\\\"],\\n df[\\\"T_vehicle_attitude_0__F_q_2\\\"],\\n df[\\\"T_vehicle_attitude_0__F_q_3\\\"],\\n )\\n\\n df[x.name] = x.values\\n df[y.name] = y.values\\n df[z.name] = z.values\",\n \"def rotZ(theta, mode = 'radians'):\\n\\n\\tif mode != 'radians' and mode != 'degrees':\\n\\t\\traise ValueError('Mode should either be ``radians`` or ``degrees``.')\\n\\tif mode == 'degrees':\\n\\t\\ttheta = np.deg2rad(theta)\\n\\treturn np.matrix([[np.cos(theta), -np.sin(theta), 0], [np.sin(theta), np.cos(theta), 0], \\\\\\n\\t\\t[0., 0., 1.]])\",\n \"def rotation3Dz(theta):\\n rmat = np.zeros((3,3))\\n rmat[0,0] = rmat[1,1] = np.cos(theta)\\n rmat[0,1] = np.sin(theta)\\n rmat[1,0] = -rmat[0,1]\\n rmat[2,2] = 1\\n return rmat\",\n \"def rotate_z(self, angle: float):\\n self.vertices = list(\\n Matrix44.z_rotate(angle).transform_vertices(self.vertices)\\n )\\n return self\",\n \"def signed_r_z(rotation_matrix, positions, core):\\n arr = np.array\\n pos = arr(positions) - core\\n rot_pos = arr(rotation_matrix * pos.T).T\\n x = rot_pos[:, 0].T\\n y = rot_pos[:, 1].T\\n z = rot_pos[:, 2].T\\n r = (x ** 2 + y ** 2) ** 0.5 * np.sign(-x)\\n return r, z\",\n \"def coord_rotate_rad(x, y, z):\\n #-- 1 --\\n xt = math.asin ( math.sin(x) * math.sin(y) +\\n math.cos(x) * math.cos(y) * math.cos(z) )\\n #-- 2 --\\n yt = math.acos ( ( math.sin(x) - math.sin(y) * math.sin(xt) ) /\\n ( math.cos(y) * math.cos(xt) ) )\\n #-- 3 --\\n if math.sin(z) > 0.0:\\n yt = TWO_PI - yt\\n\\n #-- 4 --\\n return (xt, yt)\",\n \"def test_z_rot(self):\\n\\n # Create a Matrix representing 90 deg z rot.\\n mat = Matrix44.from_rot_z(90)\\n # Use from_matrix44()\\n quat = Quat.from_matrix44(mat)\\n\\n # Ensure the quat matches a 90 degree x rotation.\\n expected = Quat.from_axis_angle_deg(Vec3(0, 0, 1), 90)\\n AssertQuatAlmostEqual(quat, expected, self)\",\n \"def rot_z(theta):\\n theta_rad = np.radians(theta)\\n rotation_matrix = [[np.cos(theta_rad), -np.sin(theta_rad), 0],\\n [np.sin(theta_rad), np.cos(theta_rad), 0],\\n [0, 0, 1]]\\n return np.matrix(rotation_matrix)\",\n \"def rotateZ(self, theta):\\n rot_m = numpy.array([[numpy.sin(theta), numpy.cos(theta)], \\\\\\n [numpy.cos(theta), -numpy.sin(theta)]])\\n for sec in self.all:\\n for i in range(int(nrn.n3d())):\\n xy = numpy.dot([nrn.x3d(i), nrn.y3d(i)], rot_m)\\n nrn.pt3dchange(i, float(xy[0]), float(xy[1]), nrn.z3d(i), \\\\\\n nrn.diam3d(i))\",\n \"def _derZ(self, x, y, z):\\n raise NotImplementedError()\",\n \"def rotate(self, x=0, y=0, z=0):\\n\\t\\tquaternion = R.from_euler('xyz', [x, y, z], degrees=True)\\n\\t\\trotation_matrix = np.array(quaternion.as_matrix())\\n\\t\\trotation_matrix = np.pad(rotation_matrix, [(0, 1), (0, 1)], mode='constant')\\n\\t\\trotation_matrix[3,3] = 1\\n\\n\\t\\tself.matrix = np.matmul(self.matrix, rotation_matrix)\",\n \"def compute_Az(self, r, z, qOc):\\n\\n kr_cross_r = einsum('r, p -> rp', self.kr, r)\\n kz_cross_z = einsum('z, p -> zp', self.kz, z)\\n delta_r = np.ones(np.size(r)) * self.ptcl_width_r\\n delta_u = einsum('r, p -> rp', self.kr, delta_r)\\n convolved_j0 = self.convolved_j0(kr_cross_r, delta_u)\\n convolved_cos = einsum('zp, z -> zp', cos(kz_cross_z), self.shape_function_z)\\n\\n modeQz = self.omegaOtwokr * (self.dc_coords[:,:,1] + self.omega_coords[:,:,1])\\n\\n self.tanhz = -np.tanh(((z - self.z_mean) ** 2 - self.z_mean ** 2) * self.tanh_width ** 2)\\n # We dress the charge instead of the fields proper\\n dressed_charge = self.tanhz*qOc\\n\\n Az = einsum('zr, rp, zp -> p', modeQz, convolved_j0, convolved_cos)*dressed_charge\\n\\n return Az\",\n \"def add_desired_z_axis(df):\\n x = pd.Series(\\n np.zeros(df.shape[0]),\\n index=df[\\\"timestamp\\\"],\\n name=\\\"T_vehicle_attitude_setpoint_0__NF_body_z_axis_sp_x\\\",\\n )\\n y = pd.Series(\\n np.zeros(df.shape[0]),\\n index=df[\\\"timestamp\\\"],\\n name=\\\"T_vehicle_attitude_setpoint_0__NF_body_z_axis_sp_y\\\",\\n )\\n z = pd.Series(\\n np.ones(df.shape[0]),\\n index=df[\\\"timestamp\\\"],\\n name=\\\"T_vehicle_attitude_setpoint_0__NF_body_z_axis_sp_z\\\",\\n )\\n\\n x, y, z = mpd.series_quatrot(\\n x,\\n y,\\n z,\\n df[\\\"T_vehicle_attitude_setpoint_0__F_q_d_0\\\"],\\n df[\\\"T_vehicle_attitude_setpoint_0__F_q_d_1\\\"],\\n df[\\\"T_vehicle_attitude_setpoint_0__F_q_d_2\\\"],\\n df[\\\"T_vehicle_attitude_setpoint_0__F_q_d_3\\\"],\\n )\\n df[x.name] = x.values\\n df[y.name] = y.values\\n df[z.name] = z.values\",\n \"def ZZRotation(angle):\\r\\n return Diagonal(2,\\r\\n np.array([[np.exp(1j * angle), np.exp(-1j * angle)],\\r\\n [np.exp(-1j * angle), np.exp(1j * angle)]]),\\r\\n 'R_ZZ({})'.format(angle))\",\n \"def ComputeExteriorOrientation_RzRyRz(self, imagePoints, groundPoints, epsilon):\\n # cameraPoints = self.ImageToCamera(imagePoints)\\n cameraPoints = imagePoints\\n self.exteriorOrientationParameters[0:3] = np.dot(self.rotationMatrix_RzRyRz, self.exteriorOrientationParameters[0:3])\\n self.exteriorOrientationParameters = np.add(self.exteriorOrientationParameters, np.random.normal(0, 0.01, self.exteriorOrientationParameters.shape))\\n l0 = self.__ComputeObservationVector_RzRyRz(groundPoints.T)\\n l0 = np.reshape(l0, (-1, 1))\\n l = cameraPoints.reshape(np.size(cameraPoints), 1) - l0\\n A = self.__ComputeDesignMatrix_RzRyRz(groundPoints.T)\\n\\n N = np.dot(A.T, A)\\n u = np.dot(A.T, l)\\n deltaX = np.dot(la.inv(N), u)\\n\\n # update orientation pars\\n self.__exteriorOrientationParameters = np.add(self.__exteriorOrientationParameters, np.reshape(deltaX, 6))\\n\\n while la.norm(deltaX) > epsilon:\\n l0 = self.__ComputeObservationVector_RzRyRz(groundPoints.T)\\n l0 = np.reshape(l0, (-1, 1))\\n l = cameraPoints.reshape(np.size(cameraPoints), 1) - l0\\n A = self.__ComputeDesignMatrix_RzRyRz(groundPoints.T)\\n N = np.dot(A.T, A)\\n u = np.dot(A.T, l)\\n deltaX = np.dot(la.inv(N), u)\\n # update orientation pars\\n self.__exteriorOrientationParameters = np.add(self.__exteriorOrientationParameters, np.reshape(deltaX, 6))\\n\\n # compute residuals\\n l_a = np.reshape(self.__ComputeObservationVector_RzRyRz(groundPoints.T), (-1, 1))\\n v = l_a - cameraPoints.reshape(np.size(cameraPoints), 1)\\n if (np.size(A, 0) - np.size(deltaX)) != 0:\\n sig = np.dot(v.T, v) / (np.size(A, 0) - np.size(deltaX))\\n sigmaX = sig[0] * la.inv(N)\\n else:\\n sigmaX = None\\n\\n return [self.exteriorOrientationParameters, sigmaX, v]\",\n \"def _derZ(self, w, x, y, z):\\n raise NotImplementedError()\",\n \"def rotation(x1, z1, x2, z2):\\n e1 = np.zeros(shape=(3, 3))\\n e2 = np.zeros(shape=(3, 3))\\n e1[0, :] = x1 / np.linalg.norm(x1)\\n e1[2, :] = z1 / np.linalg.norm(z1)\\n e1[1, :] = np.cross(e1[2, :], e1[0, :])\\n e2[0, :] = x2 / np.linalg.norm(x2)\\n e2[2, :] = z2 / np.linalg.norm(z2)\\n e2[1, :] = np.cross(e2[2, :], e2[0, :])\\n R = np.zeros(shape=(3, 3))\\n for i in range(3):\\n for j in range(3):\\n R[i, j] = np.dot(e1[i, :], e2[j, :])\\n R = np.transpose(R)\\n return R\",\n \"def rotation(x,y,z):\\r\\n phi = np.arctan(z/sqrt(x**2+y**2))\\r\\n lamb = np.arctan2(y,x)\\r\\n G = np.array([[-sin(lamb), cos(lamb), 0],\\r\\n [-sin(phi) * cos(lamb), -sin(phi) * sin(lamb), cos(phi)],\\r\\n [cos(phi) * cos(lamb), cos(phi) * sin(lamb), sin(phi)]])\\r\\n return (G)\",\n \"def set_z(self, operator_):\\n nbr_params = len(signature(operator_).parameters)\\n if nbr_params is 2:\\n def oper(z):\\n if len(z) == self.N+self.M:\\n x = z[0:self.N]\\n y = z[self.N:self.N+self.M]\\n fx, fy, _ = operator_(x,y)\\n if fy is None:\\n return fx\\n return np.concatenate((fx,fy))\\n else:\\n raise ValueError('set_z(operator_); len of z not correct. Please refer to the documentation.') \\n return oper\\n elif nbr_params is 3:\\n def oper(z):\\n if len(z) == self.N+self.M+self.U:\\n x = z[0:self.N]\\n y = z[self.N:self.N+self.M]\\n u = z[self.N+self.M:self.N+self.M+self.U]\\n fx, fy, fu = operator_(x,y,u)\\n if fy is None:\\n return fx\\n return np.concatenate((fx,fy,fu))\\n else:\\n raise ValueError('set_z(operator_); len of z not correct. Please refer to the documentation.') \\n return oper\\n else : \\n raise ValueError('set_z(operator_); operator can only have either 2 or 3 inputs. Please refer to the documentation.')\",\n \"def rotateAlignXform(self):\\n r = np.concatenate(([self.x], [self.y], [self.z]), 0)\\n r = np.concatenate((r, np.array([[0,0,0]])), 0)\\n r = np.concatenate((r, np.array([0,0,0,1]).reshape(-1,1)), 1)\\n return r\",\n \"def rplot(Qz, R, format):\\n # plt.hold(True)\\n plt.figure()\\n for name,xs in zip(('++','+-','-+','--'),R):\\n rr = xs.real\\n if (rr>1e-8).any():\\n plt.plot(Qz, rr, format, label=name + 'r')\\n plt.legend()\\n plt.figure()\\n for name,xs in zip(('++','+-','-+','--'),R):\\n ri = xs.imag\\n if (ri>1e-8).any():\\n plt.plot(Qz, ri, format, label=name + 'i')\\n plt.legend()\\n\\n plt.figure()\\n for name,xs in zip(('++','+-','-+','--'),R):\\n phi = np.arctan2(xs.imag, xs.real)\\n if (ri>1e-8).any():\\n plt.plot(Qz, phi, format, label=name + 'i')\\n plt.legend()\",\n \"def z_rotmat(theta):\\n cos_t = np.cos(theta)\\n sin_t = np.sin(theta)\\n return np.array([[cos_t, -sin_t, 0],\\n [sin_t, cos_t, 0],\\n [0, 0, 1]])\",\n \"def compute_Ar(self, r, z, qOc):\\n\\n kz_cross_z = einsum('z, p -> zp', self.kz, z)\\n kr_cross_r = einsum('r, p -> rp', self.kr, r)\\n delta_r = np.ones(np.size(r))*self.ptcl_width_r\\n delta_u = einsum('r, p -> rp', self.kr, delta_r)\\n j1 = self.convolved_j1(kr_cross_r, delta_u)\\n convolved_sin = einsum('zp, z -> zp', sin(kz_cross_z), self.shape_function_z)\\n\\n modeQr = self.omegaOtwokz * (self.dc_coords[:,:,1] - self.omega_coords[:,:,1])\\n\\n self.tanhz = -np.tanh(((z - self.z_mean) ** 2 - self.z_mean ** 2) * self.tanh_width ** 2)\\n # We dress the charge instead of the fields proper\\n dressed_charge = self.tanhz*qOc\\n\\n\\n Ar = einsum('zr, rp, zp -> p', modeQr, j1, convolved_sin)*dressed_charge\\n\\n return Ar\",\n \"def test_revolute(self):\\n # Rotate around the z axis\\n r = Joint.revolute(np.array([0, 0, 1]))\\n t_mat = r(np.array([np.pi / 2]))\\n rot_vec = np.dot(t_mat, np.array([1, 0, 0, 1]))[:3]\\n self.assertTrue(np.allclose(\\n rot_vec, np.array([0, 1, 0]), rtol=1e-5, atol=1e-5))\",\n \"def findRotationMatrix(xS, yS, zS):\\n dist = zS**2+xS**2\\n #make transformation of z-y plane using angle from linear fit\\n xS = np.reshape(xS, (-1,1))\\n zS = np.reshape(zS, (-1,1))\\n turns = np.argpartition(dist, -250)[:-250]\\n# #use ransac to obtain a fit of all non-turn points \\n# #(use the fact there are more non-turns than turn points\\n# reg = linear_model.RANSACRegressor()\\n# reg.fit(zS, xS)\\n# #use ransac outliers to fit\\n# # turns only - fit to align to z-axis\\n# turns = np.where(reg.inlier_mask_==False)[0]\\n # fit outliers (turns) only\\n reg = linear_model.LinearRegression()\\n reg.fit(xS[turns], zS[turns]) \\n # outliers need to align with z\\n theta = np.pi/2.-np.arctan(reg.coef_[0])[0]\\n c, s = np.cos(theta), np.sin(theta)\\n R = np.matrix([[0,1,0],[c,0, -s], [s,0, c]])\\n\\n return R\",\n \"def test_rotate_around_v3_z_axis(self):\\n from pedemath.vec3 import rotate_around_vector_v3\\n\\n vec_a = Vec3(3, 4, 5)\\n vec_b = Vec3(0, 0, 1)\\n\\n result = rotate_around_vector_v3(vec_a, math.pi, vec_b)\\n expected = Vec3(-3, -4, 5)\\n\\n self.assertAlmostEqual(result.x, expected.x)\\n self.assertAlmostEqual(result.y, expected.y)\\n self.assertAlmostEqual(result.z, expected.z)\",\n \"def R(rpy):\\n Rx_roll = sp.Matrix(\\n [\\n [1, 0, 0],\\n [0, sp.cos(rpy[0]), -sp.sin(rpy[0])],\\n [0, sp.sin(rpy[0]), sp.cos(rpy[0])],\\n ]\\n )\\n Ry_pitch = sp.Matrix(\\n [\\n [sp.cos(rpy[1]), 0, sp.sin(rpy[1])],\\n [0, 1, 0],\\n [-sp.sin(rpy[1]), 0, sp.cos(rpy[1])],\\n ]\\n )\\n Rz_yaw = sp.Matrix(\\n [\\n [sp.cos(rpy[2]), -sp.sin(rpy[2]), 0],\\n [sp.sin(rpy[2]), sp.cos(rpy[2]), 0],\\n [0, 0, 1],\\n ]\\n )\\n R = Rx_roll * Ry_pitch * Rz_yaw\\n return R\",\n \"def rotate(self, z_dim=False):\\n self.x_displacement = np.format_float_scientific(\\n self.length / 2 * np.cos(self.angle * np.pi / 360), precision=1\\n )\\n self.y_displacement = np.format_float_scientific(\\n self.length / 2 * np.sin(self.angle * np.pi / 360), precision=1\\n )\\n zd = z_dim\\n if zd == True:\\n self.z_angle = random.uniform(1, 180)\\n self.z_displacement = np.format_float_scientific(\\n self.length / 2 * np.sin(self.z_angle * np.pi / 360), precision=1\\n )\\n else:\\n self.z_displacement = 0\\n self.z_angle = 0\\n return [self.x_displacement, self.y_displacement, self.z_displacement]\",\n \"def rz(target: QubitInput, angle: float) -> Iterable[Instruction]:\\n return [Instruction(Rz(angle), target=qubit) for qubit in QubitSet(target)]\",\n \"def ryrz_decomposer(gate: OneQubitGate) -> List[Union[RYGate, RZGate]]:\\n mat = gate.matrix()\\n assert mat.shape == (2, 2)\\n assert check_unitarity(mat)\\n gamma = cmath.phase(mat[0, 0])\\n mat *= cmath.exp(-1j * gamma)\\n assert abs(mat[0, 0].imag) < 1e-8\\n cos_halftheta = mat[0, 0].real\\n sin_halftheta = 1.0 - cos_halftheta ** 2\\n try:\\n theta = math.acos(cos_halftheta) * 2\\n except ValueError: # math domain error\\n assert abs(abs(cos_halftheta) - 1.0) < 1e-8\\n if cos_halftheta > 0:\\n theta = 0.0\\n else:\\n theta = math.pi\\n if abs(sin_halftheta) < 1e-8:\\n phi = 0.0\\n lam = cmath.phase(mat[1, 1])\\n else:\\n phi = cmath.phase(mat[1, 0])\\n lam = cmath.phase(mat[0, 1])\\n if theta < 1e-8:\\n return [RZGate(gate.targets, lam + phi)]\\n gates = []\\n if lam > 1e-8:\\n gates.append(RZGate(gate.targets, lam))\\n gates.append(RYGate(gate.targets, theta))\\n if phi > 1e-8:\\n gates.append(RZGate(gate.targets, phi))\\n return gates\",\n \"def rotate_about_z(self, deg):\\n if self.x is None:\\n raise AttributeError('rotate_about_z: no X component')\\n if self.y is None:\\n raise AttributeError('rotate_about_z: no Y component')\\n\\n sine = sin(radians(deg))\\n cosine = cos(radians(deg))\\n x_new = self.x*cosine - self.y*sine\\n self.y = self.y*cosine + self.x*sine\\n self.x = x_new\",\n \"def make_rotation(self, rotation):\\n if rotation == \\\"r\\\":\\n self.facing += 1\\n else:\\n self.facing -= 1\\n\\n if self.facing > 3:\\n self.facing = self.facing - 4\\n elif self.facing < 0:\\n self.facing = self.facing + 4\",\n \"def rose(data, rz, z=None, ax=None, bins=30, bidirectional=True, color_by=np.mean, plot='yes', png=None, tag=None):\\n #adapted from Joe Kington: https://stackoverflow.com/questions/16264837/how-would-one-add-a-colorbar-to-this-example\\n\\n #create arcs (define top of bin arc)\\n bin_offset = math.pi/float(bins)\\n bins = np.linspace(0, 2.0*math.pi, bins+1) + bin_offset\\n\\n if (rz == 'yes'):\\n azimuths = np.arctan2(data[:,0], data[:,1])\\n else:\\n azimuths = np.arctan2(data[:,1], data[:,0])\\n weight = data[:,-1]\\n wSum = np.sum(weight)\\n\\n azimuths = np.asanyarray(azimuths)\\n if color_by == 'count':\\n# z = np.ones_like(azimuths)\\n z = weight \\n color_by = np.sum\\n\\n if ax is None:\\n fig = plt.figure(1)\\n ax = plt.subplot(111, projection='polar')\\n if bidirectional:\\n other = azimuths + math.pi\\n azimuths = np.concatenate([azimuths, other])\\n weight = np.concatenate([weight, weight]) \\n if z is not None:\\n z = np.concatenate([z, z])\\n\\n # Convert to 0-360, in case negative or >360 azimuths are passed in.\\n azimuths[azimuths > math.pi*2.0] -= math.pi*2.0\\n azimuths[azimuths < 0] += math.pi*2.0\\n counts, edges = np.histogram(azimuths, range=[0, math.pi*2.0], bins=bins, weights=weight)\\n\\n if z is not None:\\n idx = np.digitize(azimuths, edges)\\n z = np.array([color_by(z[idx == i]) for i in range(1, idx.max() + 1)])\\n z = np.ma.masked_invalid(z)\\n cmap = plt.get_cmap('jet')\\n coll = colored_bar(edges[:-1], counts/wSum, z=z, width=np.diff(edges), ax=ax, cmap=cmap)\\n\\n ax.set_aspect('equal')\\n ax.autoscale()\\n\\n ax.set_rmin(0)\\n ax.set_thetamin(0)\\n ax.set_thetamax(360)\\n grid = np.linspace(0, 360, 24+1)[:-1]\\n ax.set_thetagrids(grid) \\n\\n if (rz == 'yes'):\\n ax.set_theta_direction(-1)\\n ax.set_theta_zero_location('N')\\n ax.set_xlabel(r'$\\\\phi$')\\n else:\\n ax.set_xlabel(r'$\\\\theta$')\\n\\n if tag != None:\\n plt.title(tag) \\n\\n if png != None:\\n plt.savefig(get_filename(png,tag=tag), dpi=300)\\n\\n if plot == 'yes': \\n plt.show()\\n\\n return coll\",\n \"def moveZ(self, delta):\\n self.setZ(delta + self.getZ())\",\n \"def get_rotation_back_angle(w, r):\\n # now let us compute the image of the vector (r,0), that is h(r,0)\\n\\n zeros = torch.zeros_like(r)\\n\\n origin_circle = torch.stack([r, zeros], dim=-1) # create (B1, B2, .., B_N, r, 0)\\n\\n h_orig_circle = h(origin_circle, w, r)\\n\\n return T_2(h_orig_circle)\",\n \"def get_rz(self):\\n return self.rz\",\n \"def rotate_orbit(self):\\n try:\\n ang = self.orbit_speed * self.time_scale / self.refresh_rate\\n self.obj.rotate(angle=ang, axis=vector(0, 1, 0), origin=self.star.obj.pos)\\n self.sum_ang += ang\\n except ZeroDivisionError:\\n print(\\\"ERROR: REFRESH_RATE is 0\\\")\\n except (AttributeError, TypeError):\\n print(\\\"ERROR: wrong arguments type while initializing!!\\\")\",\n \"def rotateZUp(self):\\n MV = self.MV\\n MV[:3, 1] = 0, 0, 1 # 2nd col is up vector, make it point along z axis\\n # set bottom left and bottom right z values to zero:\\n MV[2, 0] = 0\\n MV[2, 2] = 0\\n a = MV[0, 0] # grab top left value\\n b = np.sqrt(1 - a**2) # calc new complementary value to get normalized vectors\\n if MV[1, 0] < 0:\\n b = -b # keep b -ve, reduce jumping around of axes\\n MV[1, 0] = b\\n MV[0, 2] = b\\n MV[1, 2] = -a # needs to be -ve of MV[0, 0]\\n self.MV = MV\",\n \"def rotateZUp(self):\\n MV = self.MV\\n MV[:3, 1] = 0, 0, 1 # 2nd col is up vector, make it point along z axis\\n # set bottom left and bottom right z values to zero:\\n MV[2, 0] = 0\\n MV[2, 2] = 0\\n a = MV[0, 0] # grab top left value\\n b = np.sqrt(1 - a**2) # calc new complementary value to get normalized vectors\\n if MV[1, 0] < 0:\\n b = -b # keep b -ve, reduce jumping around of axes\\n MV[1, 0] = b\\n MV[0, 2] = b\\n MV[1, 2] = -a # needs to be -ve of MV[0, 0]\\n self.MV = MV\",\n \"def addThreeNodesRig(self):\\r\\n cam = self.nativePointer()\\r\\n\\r\\n # create controls\\r\\n pos = mxs.star(radius1 = 6.5, radius2 = 5.5, points=16)\\r\\n trans = mxs.rectangle(length=10.2, width=4.5)\\r\\n rot = mxs.ngon(radius=2.0, nSides=3, corner_radius=0.5)\\r\\n\\r\\n # rename controls\\r\\n pos.name = str(cam.name) + 'position'\\r\\n trans.name = str(cam.name) + 'translation'\\r\\n rot.name = str(cam.name) + 'rotation'\\r\\n\\r\\n # rotate controls into place\\r\\n pos.rotation = mxs.eulerangles(90, 0 , 0)\\r\\n trans.rotation = mxs.eulerangles(90, 0 , 0)\\r\\n rot.rotation = mxs.eulerangles(0, 0, -90)\\r\\n\\r\\n # reset xforms\\r\\n mxs.resetxform(pos)\\r\\n mxs.resetxform(trans)\\r\\n mxs.resetxform(rot)\\r\\n\\r\\n # collapse xforms\\r\\n mxs.maxOps.CollapseNode(pos, True)\\r\\n mxs.maxOps.CollapseNode(trans, True)\\r\\n mxs.maxOps.CollapseNode(rot, True)\\r\\n\\r\\n rot.parent = trans\\r\\n trans.parent = pos\\r\\n\\r\\n pos.wirecolor = rot.wirecolor = trans.wirecolor = mxs.color(0, 230, 250)\\r\\n\\r\\n # Move the rig to align with the cam\\r\\n pivrot=cam.rotation\\r\\n pos.rotation*=pivrot;\\r\\n #pos.objectoffsetrot*=pivrot;\\r\\n #pos.objectoffsetpos*=pivrot;\\r\\n\\r\\n pos.position = cam.position\\r\\n #mxs.resetxform(pos)\\r\\n #pos.rotation = cam.rotation\\r\\n\\r\\n\\r\\n # parent the cam to to rig\\r\\n cam.parent = rot\\r\\n\\r\\n return True\",\n \"def matrix_rotate_3d_z(deg: float) -> np.matrix:\\n from numpy import cos, sin, pi\\n rad_z = -deg * pi/180\\n c_z = cos(rad_z)\\n s_z = sin(rad_z)\\n return np.matrix([[c_z, -s_z, 0], [s_z, c_z, 0], [0, 0, 1]])\",\n \"def zeta1(self,r1,r2,x,z=0):\\n## real dynamics\\n return (2.0/3.0*(2.0+self.mu)*self.pkj0(r1,z)*self.pkj0(r2,z)-(self.pkj1mk(r1,z)*self.pkj1pk(r2,z)+self.pkj1mk(r2,z)*self.pkj1pk(r1,z))*x+2.0/3.0*(1-self.mu)*self.pkj2(r1,z)*self.pkj2(r2,z)*(-0.5+1.5*x**2))\",\n \"def generate(self):\\n inside = self.crystal.is_inside(self.x,self.y,self.z)\\n X = np.vstack((self.x[inside],self.y[inside],self.z[inside]))\\n return self.rot.rotate(X)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.70971054","0.6867665","0.6615164","0.65454346","0.654375","0.647146","0.64289933","0.64135015","0.6400951","0.62438506","0.62215066","0.6033293","0.6030118","0.60268694","0.60091794","0.5993204","0.5962274","0.59318596","0.590546","0.5898538","0.58605975","0.5840502","0.58221865","0.5789314","0.5760314","0.57466346","0.57445747","0.57053703","0.5696335","0.5683432","0.5674436","0.5674436","0.5674436","0.5674436","0.5673123","0.5672913","0.566597","0.56544787","0.5621596","0.56081516","0.55999017","0.55939305","0.55820894","0.5568093","0.5560411","0.5558731","0.5551307","0.5524201","0.5515225","0.5513784","0.549689","0.54860055","0.54785717","0.54785717","0.54785717","0.54785717","0.5464207","0.54342955","0.54318094","0.53996885","0.5385103","0.5375701","0.53681314","0.53586257","0.5346199","0.53358114","0.5333972","0.5325438","0.53085506","0.5303846","0.53004","0.5294816","0.52844167","0.52821165","0.5277847","0.5276543","0.5274972","0.52715313","0.5246761","0.52335054","0.52001274","0.5182131","0.51789176","0.51764977","0.5166958","0.51552916","0.5152704","0.5150734","0.5145908","0.5136871","0.5129822","0.5126435","0.51235425","0.51196146","0.51181406","0.51181406","0.5111392","0.5104487","0.5091943","0.50567156"],"string":"[\n \"0.70971054\",\n \"0.6867665\",\n \"0.6615164\",\n \"0.65454346\",\n \"0.654375\",\n \"0.647146\",\n \"0.64289933\",\n \"0.64135015\",\n \"0.6400951\",\n \"0.62438506\",\n \"0.62215066\",\n \"0.6033293\",\n \"0.6030118\",\n \"0.60268694\",\n \"0.60091794\",\n \"0.5993204\",\n \"0.5962274\",\n \"0.59318596\",\n \"0.590546\",\n \"0.5898538\",\n \"0.58605975\",\n \"0.5840502\",\n \"0.58221865\",\n \"0.5789314\",\n \"0.5760314\",\n \"0.57466346\",\n \"0.57445747\",\n \"0.57053703\",\n \"0.5696335\",\n \"0.5683432\",\n \"0.5674436\",\n \"0.5674436\",\n \"0.5674436\",\n \"0.5674436\",\n \"0.5673123\",\n \"0.5672913\",\n \"0.566597\",\n \"0.56544787\",\n \"0.5621596\",\n \"0.56081516\",\n \"0.55999017\",\n \"0.55939305\",\n \"0.55820894\",\n \"0.5568093\",\n \"0.5560411\",\n \"0.5558731\",\n \"0.5551307\",\n \"0.5524201\",\n \"0.5515225\",\n \"0.5513784\",\n \"0.549689\",\n \"0.54860055\",\n \"0.54785717\",\n \"0.54785717\",\n \"0.54785717\",\n \"0.54785717\",\n \"0.5464207\",\n \"0.54342955\",\n \"0.54318094\",\n \"0.53996885\",\n \"0.5385103\",\n \"0.5375701\",\n \"0.53681314\",\n \"0.53586257\",\n \"0.5346199\",\n \"0.53358114\",\n \"0.5333972\",\n \"0.5325438\",\n \"0.53085506\",\n \"0.5303846\",\n \"0.53004\",\n \"0.5294816\",\n \"0.52844167\",\n \"0.52821165\",\n \"0.5277847\",\n \"0.5276543\",\n \"0.5274972\",\n \"0.52715313\",\n \"0.5246761\",\n \"0.52335054\",\n \"0.52001274\",\n \"0.5182131\",\n \"0.51789176\",\n \"0.51764977\",\n \"0.5166958\",\n \"0.51552916\",\n \"0.5152704\",\n \"0.5150734\",\n \"0.5145908\",\n \"0.5136871\",\n \"0.5129822\",\n \"0.5126435\",\n \"0.51235425\",\n \"0.51196146\",\n \"0.51181406\",\n \"0.51181406\",\n \"0.5111392\",\n \"0.5104487\",\n \"0.5091943\",\n \"0.50567156\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6309543"},"document_rank":{"kind":"string","value":"9"}}},{"rowIdx":81738,"cells":{"query":{"kind":"string","value":"add P gate (phase shift gate)."},"document":{"kind":"string","value":"def p(self, q0, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=PHASE_SHIFT, qid=[q0], phase=phase, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def add(self, p):\n self._pumps.add(p)","def __add__(self, p: np.ndarray):\n return Quaternion(self.to_array() + p)","def Add(p, q):\n return p*q","def point_addition(self, P, Q):\n\t\traise Exception(NotImplemented)","def PLP(self, *_):\n self.reg.P = self.pop()","def update_p(self, p: float):\n self.p = p\n for k, sequential in self.m_ops.items():\n if sequential[0].is_identity_op():\n sequential[-1].p = p","def addPoly(self,p):\n for t in triangulate(p):\n self.addTri(t)\n return self","def increment(self, prp):\n (prp_phase, prp_set) = prp\n if prp_phase == 1:\n return ((2, prp_set), False)\n elif prp_phase == 2:\n return (constants.DFLT_NTF, False)\n else:\n return (self.get_prp_j(self.id), self.get_all_j(self.id))","def __add__(self, p):\n return Point(self.x + p.x, self.y + p.y)","def PHA(self, *_):\n self.push(self.reg.A)","def __step(self, p):\n action = self.__action(p)\n temp_state = self.state\n\n if self.state == 0:\n if action == 1:\n self.state += 1\n elif self.state == 1:\n if action == 1:\n self.state -= 1\n else:\n self.state += 1\n else:\n if action == 1:\n self.state += 1\n else:\n self.state -= 1\n \n self.trajectory.append([temp_state, action, self.__reward(self.state)])","def ParAdd(A, B):\n return _hypre.ParAdd(A, B)","def __add__(self, other):\n return Base40Pitch(self.base40 + other.base40)","def _evolve_phaseshift_element(self, state, element):\n new_state = PhotonicState()\n for in_modes, in_amp in state.items():\n phases = element.global_U(N).diagonal()\n phase_shift = np.prod([phases[i] for i in in_modes])\n new_state[in_modes] = phase_shift * in_amp \n return new_state","def __iadd__(self, B):\n return _hypre.HypreParMatrix___iadd__(self, B)","def phase(self):\n\n self.theta = np.arctan(np.sqrt(self.P / (1 - self.P)))\n return self","def calc_phase(p, t):\n\n return (t % p)/p","def add(self, p, s, node) -> None:\n self.place.append(p)\n self.station.append(s)\n self.pi.append(node.pi[p, s] if p != float('inf') else float('inf'))\n self.noncoverage.append(node.noncoverage.left + node.noncoverage.right)\n self.cost.append(node.cost)\n self.delay.append(node.delay)\n self.step.append(node.key)","def powerpupgain_fn(self, X, Xp):\n deg = self.order\n v = self.theta\n Y = v[0, 0] + v[0, 1] * X + v[0, 2] * \\\n np.power(Xp, deg) + v[0, 3] * np.multiply(X, np.power(Xp, deg))\n return(Y)","def BPL(self, value):\n if not self.reg.N:\n self.reg.PC += value","def add(self, params):\n if len(params) < 2:\n return\n x = self.reg_dct[params[0]]\n y = self.reg_dct[params[1]]\n self.reg_dct[params[0]] = (x + y) % (2** 32)","def add_pion(self, p):\n self.pions[p.x][p.y] = p\n self.pionsliste.append(p)","def add_ptx(self):\n self.pmos = ptx(width=self.ptx_width,\n tx_type=\"pmos\")\n self.add_mod(self.pmos)","def _step(self, P, W):\n Qa = self.mul(self.ch + 1, P)\n if len(Qa) == 1:\n _log.debug(\"[%d]P is zero\" % (self.ch + 1))\n Qb = R = self.mul(W, P)\n A = [Qa[0]]\n B = [0, Qb[0]] # 0 = [0][0] ((infinity)_x)\n for i in range(1, W):\n Qa = self.add(Qa, P)\n Qb = self.add(Qb, R)\n A.append(Qa[0])\n B.append(Qb[0])\n if len(Qa) == 1:\n _log.debug(\"[%d]P is zero\" % (self.ch + 1 + i))\n break\n return [A, B, set(A).intersection(set(B))]","def __add__(self, B):\n return (Polynomial(self) + B).simplify()","def map(self, second_q_op: ParticleOp) -> PauliSumOp:\n # TODO\n raise NotImplementedError()","def append(ps, p):\n return np.append(ps, [p], axis=0)","def eAdd(P, Q): #adds 2 points by using the slope to find where the line intersects and returns the negation of that point\r\n R = point(0,0,P.c) #creates point object to store result\r\n if (P.x == 0 and P.y == 0) and (Q.x == 0 and Q.y == 0): #(0,0) is the identity\r\n return P #returns the identity\r\n elif P.x == 0 and P.y == 0:\r\n return Q\r\n elif Q.x == 0 and Q.y == 0:\r\n return P\r\n elif P == Q: #in case it is called when double should be\r\n R = eDouble(P)\r\n else: #this preforms the actual addition\r\n i = P.y-Q.y\r\n j = P.x-Q.x\r\n s = (i * modInv(j, P.c.p) ) % P.c.p\r\n R.x = ( ( (s**2) - P.x - Q.x) % P.c.p)\r\n R.y = ( (-P.y + s * (P.x - R.x) ) % P.c.p)\r\n return R","def addFP(self, num=1):\n self.fp += num","def phase(self):\n pass","def add_points(self, P, Q):\n xp, yp = P\n xq, yq = Q\n s = ((yq - yp) * self.inv(xq - xp)) % self.fp\n xr = (s ** 2 - xp - xq) % self.fp\n yr = (s * (xp - xr) - yp) % self.fp\n return (xr, yr)","def _append_phase(self, k, i):\n if not 0 <= i < self.num_qubits:\n raise QiskitError(\"phase qubit out of bounds.\")\n # If the kth bit is flipped, conjugate this gate\n if self.shift[i] == 1:\n k = (7 * k) % 8\n # Take all subsets \\alpha of the support of row i\n # of weight up to 3 and add k*(-2)**(|\\alpha| - 1) mod 8\n # to the corresponding term.\n support = np.arange(self.num_qubits)[np.nonzero(self.linear[i])]\n subsets_2 = itertools.combinations(support, 2)\n subsets_3 = itertools.combinations(support, 3)\n for j in support:\n value = self.poly.get_term([j])\n self.poly.set_term([j], (value + k) % 8)\n for j in subsets_2:\n value = self.poly.get_term(list(j))\n self.poly.set_term(list(j), (value + -2 * k) % 8)\n for j in subsets_3:\n value = self.poly.get_term(list(j))\n self.poly.set_term(list(j), (value + 4 * k) % 8)","def cp(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_P, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def __add__(self, other):\n if other == 0:\n return self\n\n pmf = Pmf()\n for v1, p1 in self.items():\n for v2, p2 in other.items():\n pmf[v1 + v2] += p1 * p2\n return pmf","def __add__(self, other):\n return add_mps(self, other)","def nopupgain_fn(self, X, Xp):\n Y = self.theta[0, 0] + self.theta[0, 1] * X\n return(Y)","def add(self, p):\n\n self.poses.append(CalibrationPoint(p))\n self.selected_point = len(self.poses) - 1\n self.calibration_changed()","def _add_op(value, sample_args, rationals_allowed):\n entropy, sample_args = sample_args.peel()\n if rationals_allowed and sample_args.count >= 3:\n x = number.integer_or_rational(entropy, True)\n else:\n x = number.integer(entropy, True)\n if random.choice([False, True]):\n op_args = [x, value - x]\n else:\n op_args = [value - x, x]\n return ops.Add, op_args, sample_args","def post_build(self, p, pay):\n p += pay\n if self.type in [0, 0x31, 0x32, 0x22]: # for these, field is reserved (0)\n p = p[:1]+chr(0)+p[2:]\n if self.chksum is None:\n ck = checksum(p)\n p = p[:2]+chr(ck>>8)+chr(ck&0xff)+p[4:]\n return p","def e_add(pub, a, b):\n return a * b % pub.n_sq","def add(self, publication: P) -> None:\n ...","def enc_add(pub, m1, m2):\n add_result = m1 * m2 % pub.n_sq\n return add_result","def __call__(self, q: Tensor, p: Tensor, *args, **kwargs) -> Tensor:\n return self.potential(q) + self.kinetic(p)","def Addition(self, paren=False):\n left = self.Term(paren)\n while self.currtok[1].name in {\"PLUS\", \"MINUS\"}:\n op = self.currtok[0]\n self.currtok = next(self.tg)\n right = self.Term(paren)\n left = BinaryExpr(op, left, right, paren)\n return left","def addPol(*pol):\n\n sum = np.zeros((1,))\n for p in pol:\n sum = polyadd(sum, p)\n\n return sum","def app_phase(data_pupil,data_phase,oversize=4):\n return phaseangle(app_complex(data_pupil,data_phase,oversize))","def __add__(\n self,\n other: Union[TensorWrappedPhiTensorPointer, MPCTensor, int, float, np.ndarray],\n ) -> Union[TensorWrappedPhiTensorPointer, MPCTensor]:\n return TensorWrappedPhiTensorPointer._apply_op(self, other, \"__add__\")","def _phi(self, x, d, p):\n ks = np.arange(self.p + 1)\n ks = ks[np.where(2 * (self.p - ks) - d >= 0)][:, np.newaxis]\n return np.sum(\n binom(self.p, ks)\n * (-1) ** ks\n * x[np.newaxis, :] ** (2 * (self.p - ks) - d)\n * perm(2 * (self.p - ks), d),\n axis=0,\n )","def phase(freqs, p0, p1, p2):\n x = utils.reduce_by_midpoint(freqs)\n phi = p0 + p1 * x + p2 * x ** 2\n return np.exp(1j * phi)","def forward(self, ps):\n if self.w is None or len(self.w) != ps.size(-1):\n self.populate_w(ps)\n\n out = (ps*self.w).sum(-1)\n return out","def multiply(self, P):\n if self.getDegree() == -1 or P.getDegree() == -1:\n return Polynomial([])\n \n coefs_of_product = [0] * (self.getDegree() + P.getDegree() + 1)\n for i in range(self.getDegree() + 1):\n for j in range(P.getDegree() + 1):\n coefs_of_product[i + j] += self.__coefficients[i] * P.__coefficients[j]\n return Polynomial(coefs_of_product)","def __iadd__(self, point):\n self.points.append(point)\n return self","def addOp(self, op):\n self.operations << op","def p1(self, p1):\n p0 = self.p0\n u = self.p1 - p0\n v = p1 - p0\n\n scale, rM = self.scale_rot_matrix(u, v)\n self.c = p0 + rM @ (self.c - p0)\n self.r *= scale\n self.r2 = self.r * self.r\n dp = p0 - self.c\n self.a0 = atan2(dp.y, dp.x)","def P(self,numSeg):\n w=self.x/numSeg\n return (w/3)*(self.F(0)+self.sumaImpar(numSeg,w)+self.sumaPar(numSeg,w)+self.F(self.x))","def ADD():\n global pointer, memory, registers\n registers[memory[pointer + 0x02]] += memory[pointer + 0x01]\n pointer += 0x03","def P2G_func(self, dt, P):\n p_C = ti.static(self.p_C)\n p_v = ti.static(self.p_v)\n p_x = ti.static(self.p_x)\n g_m = ti.static(self.g_m)\n g_v = ti.static(self.g_v)\n p_F = ti.static(self.p_F)\n p_Jp = ti.static(self.p_Jp)\n\n base = ti.floor(g_m.getG(p_x[P] - 0.5 * g_m.dx)).cast(Int)\n fx = g_m.getG(p_x[P]) - base.cast(Float)\n\n # Here we adopt quadratic kernels\n w = [0.5 * (1.5 - fx) ** 2, 0.75 - (fx - 1) ** 2, 0.5 * (fx - 0.5) ** 2]\n # dw = [fx - 1.5, -2.0 * (fx - 1), fx - 0.5]\n\n # # TODO affine would do this in P2G.. why\n # p_F[P] = (ti.Matrix.identity(Int, self.dim) + dt * p_C[P]) @ p_F[P]\n\n force = ti.Matrix.zero(Float, self.dim, self.dim)\n # want to decrease branching\n if self.p_material_id[P] == MaType.elastic:\n force = self.elasticP2Gpp(P, dt)\n elif self.p_material_id[P] == MaType.liquid:\n force = self.liquidP2Gpp(P, dt)\n elif self.p_material_id[P] == MaType.snow:\n force = self.snowP2Gpp(P, dt)\n elif self.p_material_id[P] == MaType.sand:\n force = self.sandP2Gpp(P, dt)\n\n affine = force + self.cfg.p_mass * p_C[P]\n for offset in ti.static(ti.grouped(self.stencil_range3())):\n # print(\"P2G: \", offset)\n dpos = g_m.getW(offset.cast(Float) - fx)\n\n weight = 1.0\n for d in ti.static(range(self.dim)):\n weight *= w[offset[d]][d]\n\n # dweight = ts.vecND(self.dim, self.cfg.inv_dx)\n # for d1 in ti.static(range(self.dim)):\n # for d2 in ti.static(range(self.dim)):\n # if d1 == d2:\n # dweight[d1] *= dw[offset[d2]][d2]\n # else:\n # dweight[d1] *= w[offset[d2]][d2]\n\n # force = - self.cfg.p_vol * kirchoff @ dweight\n # TODO ? AFFINE\n # g_v[base + offset] += self.cfg.p_mass * weight * (p_v[P] + p_C[P] @ dpos) # momentum transfer\n # TODO Got lots of simultaneous atomic here\n g_v[base + offset] += weight * (self.cfg.p_mass * self.p_v[P] + affine @ dpos)\n g_m[base + offset] += weight * self.cfg.p_mass\n\n # g_v[base + offset] += dt * force","def Phi(v, p, q):\n \n return np.sum([Y(t,p,q) for t in v])","def globalphase_compiler(self, gate, args):\n pass","def globalphase_compiler(self, gate, args):\n pass","def translate( t, P ): \n assert t.shape[0]==P.n # Dimension match \n if P.type=='AH_polytope':\n return pp.AH_polytope(t=t+P.t,T=P.T,P=P.P)\n elif P.type=='zonotope':\n return pp.zonotope(x=t+P.x,G=P.G)\n elif P.type==\"H_polytope\":\n return pp.H_polytope(H=P.H,h=P.h+np.dot(P.H,t))\n else:\n return ValueError('Polytope type: ',P.type,\" Not recognized\")","def p(self, p: ComType):\n if isinstance(p, complex):\n self._pwr = p\n else:\n self._pwr = complex(p, 0)","def cphaseshift(control: QubitInput, target: QubitInput, angle: float) -> Instruction:\n return Instruction(CPhaseShift(angle), target=[control, target])","def AddPseudoCode(self, pcode):\n self.buffers[self.buffergrade].append(pcode)","def perform_phase_processing(LP_solver=\"pyglpk\"):\n radar = pyart.testing.make_single_ray_radar()\n phidp, kdp = pyart.correct.phase_proc_lp(radar, 0.0, LP_solver=LP_solver)\n return radar, phidp, kdp","def CR(phi):\n return (np.kron(P0,s0) + np.kron(P1,R(phi)))","def perform_phase_processing_gf(LP_solver=\"pyglpk\"):\n radar = pyart.testing.make_single_ray_radar()\n my_gatefilter = pyart.filters.GateFilter(radar)\n my_gatefilter.exclude_below(\"normalized_coherent_power\", 0.5)\n my_gatefilter.exclude_below(\"cross_correlation_ratio\", 0.8)\n phidp, kdp = pyart.correct.phase_proc_lp_gf(\n radar,\n gatefilter=my_gatefilter,\n LP_solver=LP_solver,\n doc=15,\n ncpts=20,\n system_phase=-140.1,\n )\n return radar, phidp, kdp","def p0(self, p0):\n u = self.p0 - self.p1\n v = p0 - self.p1\n scale, rM = self.scale_rot_matrix(u, v)\n self.c = self.p1 + rM @ (self.c - self.p1)\n self.r *= scale\n self.r2 = self.r * self.r\n dp = p0 - self.c\n self.a0 = atan2(dp.y, dp.x)","def _push(register):\n ucode = assemble(SET, PUSH, Z)\n ucode += assemble(SET, Z, register)\n return ucode","def laplacian(self, p):\n wf = self._wf(p)\n return - G * self.d * wf.sum()","def update(self, p):\n current_steps = len(self) - 1\n delta = np.zeros(shape=self.theta.shape) # [y, x, 4]\n subdelta = np.zeros(shape=self.theta.shape)\n ys, xs, _ = delta.shape\n\n for act, state in zip(self.action, self.state_history):\n if not np.isnan(act):\n x, y = state\n delta[y, x, :] += 1\n subdelta[y, x, act] += 1\n\n delta_theta = (subdelta - p * delta) / current_steps\n\n self.theta = self.theta + self.lr * delta_theta\n self.delta = np.sum(np.abs(self.convert(self.theta)-p))","def add(self, p1, p2):\n if p1 is None:\n return p2\n if p2 is None:\n return p1\n x1, y1 = p1\n x2, y2 = p2\n if x1 != x2:\n l = self.div_mod_p(y2 - y1, x2 - x1)\n x3 = (l * l - x1 - x2) % self.p\n y3 = (l * (x1 - x3) - y1) % self.p\n return (x3, y3)\n elif y1 == y2 and y1 != 0:\n l = self.div_mod_p(3 * x1**2 + self.a, 2 * y1)\n x3 = (l**2 - 2 * x1) % self.p\n y3 = (l * (x1 - x3) - y1) % self.p\n return (x3, y3)\n else:\n return None","def __add__(self, other):\n if (len(self.arg) < len(other.arg)):\n summ = Polynomial(other.arg)\n i = len(self.arg) - 1\n for x in self.arg:\n summ.arg[i] = self.arg[i] + summ.arg[i]\n i = i - 1\n else:\n summ = Polynomial(self.arg)\n i = len(other.arg) - 1\n for x in other.arg:\n summ.arg[i] = other.arg[i] + summ.arg[i]\n i = i - 1\n return summ","def PLA(self, *_):\n result = self.pop()\n self.reg.N = result >> 7\n self.reg.Z = result == 0\n self.reg.A = result","def g(self, p):\n re = self._re(p)\n Le = self._Le(p)\n wf = self._wf(p)\n rf = self._rf(p)\n A = Le @ np.einsum('...ij,...j', self.Ee, re)\n B = wf @ np.einsum('...ij,...j', self.Ff, rf)\n return (B - A) * G * self.d","def add_next_pipulse_step(self):\n qubit = self.qubit\n\n adaptive = self.get_param_value('adaptive')\n transition = self.get_param_value('transition_name')\n settings = self.settings.copy({})\n\n if adaptive:\n # Retrieving T2_star and pi-pulse amplitude\n if transition == \"ge\":\n T2_star = qubit.T2_star() if qubit.T2_star() else 0\n amp180 = qubit.ge_amp180() if qubit.ge_amp180() else 0\n elif transition == \"ef\":\n T2_star = qubit.T2_star_ef() if qubit.T2_star_ef() else 0\n amp180 = qubit.ef_amp180() if qubit.ef_amp180() else 0\n else:\n raise ValueError('transition must either be \"ge\" or \"ef\"')\n\n # This has to be solved differently now\n # Amplitudes for Rabi\n # 1) if passed in init\n # 2) v_high based on current pi-pulse amplitude\n # 3) v_high based on default value\n # if rabi_amps is None:\n if amp180:\n rabi_settings = {\n 'Rabi': {\n 'v_max': amp180\n }\n }\n update_nested_dictionary(settings, rabi_settings)\n\n # Delays and artificial detuning for Ramsey\n # if ramsey_delays is None or artificial_detuning is None:\n # defining delta_t for Ramsey\n # 1) if passed in init\n # 2) based on T2_star\n # 3) based on default\n if self.get_param_value(\"use_T2_star\"):\n ramsey_settings = {\n 'Ramsey': {\n 'delta_t': T2_star\n }\n }\n update_nested_dictionary(settings, ramsey_settings)\n\n transition_name = self.get_param_value(\"transition_name\",\n qubit=self.qubit)\n pipulse_settings = {\n \"PiPulseCalibration\": {\n \"General\": {\n \"transition_name\": transition_name,\n }\n }\n }\n update_nested_dictionary(settings, pipulse_settings)\n\n self.add_step(\n PiPulseCalibration,\n 'pi_pulse_calibration',\n {\n 'settings': settings\n }\n )","def phase(self):\r\n return 0.2 * self.weights","def __addOrAndSub(self, VMInstruction):\r\n self.__writer.write(\"@SP\\n\")\r\n self.__writer.write(\"M=M-1\\n\")\r\n self.__writer.write(\"A=M\\n\")\r\n self.__writer.write(\"D=M\\n\")\r\n self.__writer.write(\"@SP\\n\")\r\n self.__writer.write(\"A=M-1\\n\")\r\n self.__writer.write(\"M=M\" + str(self.__compVal(VMInstruction)) + \\\r\n \"D\\n\")","def add_reg_to_reg(self):\n register = self.return_middle_registers(self.opcode)\n sum = self.registers[register[0]] + self.registers[register[1]]\n if sum > 0xFF:\n self.registers[0xF] = 1\n self.registers[register[0]] = sum & 0xFF\n else:\n self.registers[0xF] = 0\n self.registers[register[0]] = sum\n logger.info(\"Added V{} to V{} and got {}\".format(\n register[0],\n register[1],\n self.registers[register[0]]))","def p(e, t):\n return b * e ** 2","def forward(self, inp):\n return inp.dot(self.W) + self.b","def f_UPPS_pc(v, P_0, r_f, d, s, T, wealth, phi, n_s, n_o, K):\n W_T = f_W_T_pc(v, P_0, r_f, d, s, T, wealth, phi, n_s, n_o, K)\n value = pow(W_T, -gamma) * f_W_T_to_P_T_pc(v, P_0, r_f, d, s, T, wealth, phi, n_s, n_o, K) * f_P_T_to_P_0(v, r_f, d, s, T)\n return value","def forward(x, pi, A, B):\n # TODO: Write this function.\n #x = x[1]\n B_col = B[:, x[0]] # [N_z, 1]\n alpha = np.multiply(pi, B_col)\n ret = np.zeros((x.shape[0], pi.shape[0]))\n ret[0] = alpha\n for i in range(1, x.shape[0]):\n B_col = B[:, x[i]]\n sum_term = np.dot(A, alpha) #before: alpha, A\n alpha = np.multiply(B_col, sum_term) #before: sum_term before\n ret[i] = alpha\n return ret","def test_special_PSX(self, angexp):\n a, b, c = angexp[0]\n tgt = U3Gate(a, b, c).to_matrix()\n exp = {(\"p\", \"sx\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\n self.check_oneq_special_cases(tgt, \"PSX\", exp)","def wpqu_union(self, p, q):\n if self.wpqu_connected(p,q):\n return True;\n \n p_pa,q_pa = self.id[p],self.id[q]\n \n if self.sz[p_pa] >= self.sz[q_pa]:\n self.id[q_pa] = p_pa\n self.sz[p_pa] += self.sz[q_pa] \n else:\n self.id[p_pa] = q_pa\n self.sz[q_pa] += self.sz[p_pa] \n return True","def TR_algo7(self, p):\n h = 0\n ve = 0\n vd = self._vd\n m = max(self._compact_M)\n for i in range(m-1, -1, -1):\n mu = self.extract_mask(i)\n mu_norm = sum([bit_component(mu, j) for j in range(self._N)])\n mu = rotate_right(mu, vd+1)\n pi = rotate_right(ve, vd+1) & ((~mu) & 2**self._N-1)\n l = [bit_component(px, i) for px in p]\n # 2. construct a integer whose bits are given by l\n l = sum( [lx*2**j for j, lx in enumerate(l)] )\n l = T(ve, vd, l)\n w = inverse_gc(l)\n r = gcr(w, mu, pi)\n ve = ve ^ rotate_left(e(w), vd+1)\n vd = (vd + d(w) + 1) % self._N\n h = (h << mu_norm) | r\n return h","def elasticP2Gpp(self, P, dt):\n p_Jp = ti.static(self.p_Jp)\n p_F = ti.static(self.p_F)\n\n h = self.cfg.elastic_h\n mu, la = h * self.cfg.mu_0, h * self.cfg.lambda_0\n\n U, sig, V = ti.svd(p_F[P])\n J = 1.0\n\n for d in ti.static(range(self.dim)):\n new_sig = sig[d, d]\n p_Jp[P] *= sig[d, d] / new_sig\n sig[d, d] = new_sig\n J *= new_sig\n\n force = self.kirchoff_FCR(p_F[P], U @ V.transpose(), J, mu, la)\n force *= (-dt * self.cfg.p_vol * 4 * self.cfg.inv_dx ** 2)\n\n return force","def addTP(self, num=1):\n self.tp += num","def forward(self, s, p):\n h1 = F.relu(self.l1_s(s))\n h2 = F.relu(self.l1_p(p))\n cat = torch.cat([h1, h2], dim=1)\n q = F.relu(self.l2(cat))\n q = self.l3(q)\n return q","def expression(self, p):\n num_type, first, second = get_type_first_second_of_binary_operation(p.expression, p.term)\n\n opcode_type = I_for_int_R_for_float(num_type)\n opcode_action = \"ADD\" if p.ADDOP == \"+\" else \"SUB\"\n opcode = opcode_type + opcode_action\n\n temp = next(g_generate_temp_variable_name)\n temp_variables_values_dict[temp] = temp\n\n qaud_code(f\"{opcode} {temp} {first} {second}\")\n return Expression(num_type, temp)","def cphaseshift01(control: QubitInput, target: QubitInput, angle: float) -> Instruction:\n return Instruction(CPhaseShift01(angle), target=[control, target])","def reflect_adp(adp, planev):\n M = np.identity(4)\n M[:3, :3] -= 2.0 * np.outer(planev, planev)\n M[:3, 3] = (2.0 * np.dot(np.array([0, 0, 0]), planev)) * planev\n\n return rotate_adp(adp, M[:3, :3])","def __radd__(self, left):\n return self.value() + left","def lpSum(vector):\n\treturn LpAffineExpression().addInPlace(vector)","def phase_modulation_state(state, phase):\n size = len(state)\n st_mod = np.zeros((size, size), dtype=complex)\n for p1 in range(size):\n for p2 in range(size):\n st_mod[p1, p2] = state[p1, p2] * np.exp(1j * p1 * phase)\n return st_mod","def phase(state, i):\n particles = bin(state >> i + 1).count(\"1\")\n return 1 if particles % 2 == 0 else -1","def mod(p):\n return (p[0]**2 + p[1]**2 + p[2]**2)**0.5","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def computeSPPMI_matrix(P, shifted_k: int, check_sym = True):\n a, b = P.shape\n # print P.shape, type(P)\n P = np.asarray(P)\n # print 'Shape of P: ', P.shape\n assert a == b\n D = np.sum(P)\n cols = np.sum(P, axis = 0) # sum the columns (b,)\n rows = np.sum(P, axis = 1, keepdims=True) # sum the row (a,1)\n P = P / (cols + 1e-10)\n P = P / (rows + 1e-10)\n P = P * D\n PMI = np.log(P + 1e-10)\n S = PMI - np.log(shifted_k)\n mask = S > 0\n SPPMI = np.multiply(S, mask)\n assert np.min(SPPMI) == 0\n if check_sym: np.fill_diagonal(SPPMI, 0) # in-place operation\n assert torch_utils.check_symmetric(SPPMI) == True\n return SPPMI","def g_R_mix_i(s, p, k='x'): # (Validated)\n from numpy import log\n if k == 'y': # 'y' = Vapour phase standard\n V = s.m['V_v'] \n else: # Assume all phases other than vapour are liquid, ex. 'x'\n V = s.m['V_l'] \n \n return (s.m['P'] * V / (p.m['R'] * s.m['T']) - 1.0\n - log(s.m['P'] / (p.m['R'] * s.m['T']))\n - log(V - s.m['b']) \n - s.m['a'] / (p.m['R'] * s.m['T'] * V))"],"string":"[\n \"def add(self, p):\\n self._pumps.add(p)\",\n \"def __add__(self, p: np.ndarray):\\n return Quaternion(self.to_array() + p)\",\n \"def Add(p, q):\\n return p*q\",\n \"def point_addition(self, P, Q):\\n\\t\\traise Exception(NotImplemented)\",\n \"def PLP(self, *_):\\n self.reg.P = self.pop()\",\n \"def update_p(self, p: float):\\n self.p = p\\n for k, sequential in self.m_ops.items():\\n if sequential[0].is_identity_op():\\n sequential[-1].p = p\",\n \"def addPoly(self,p):\\n for t in triangulate(p):\\n self.addTri(t)\\n return self\",\n \"def increment(self, prp):\\n (prp_phase, prp_set) = prp\\n if prp_phase == 1:\\n return ((2, prp_set), False)\\n elif prp_phase == 2:\\n return (constants.DFLT_NTF, False)\\n else:\\n return (self.get_prp_j(self.id), self.get_all_j(self.id))\",\n \"def __add__(self, p):\\n return Point(self.x + p.x, self.y + p.y)\",\n \"def PHA(self, *_):\\n self.push(self.reg.A)\",\n \"def __step(self, p):\\n action = self.__action(p)\\n temp_state = self.state\\n\\n if self.state == 0:\\n if action == 1:\\n self.state += 1\\n elif self.state == 1:\\n if action == 1:\\n self.state -= 1\\n else:\\n self.state += 1\\n else:\\n if action == 1:\\n self.state += 1\\n else:\\n self.state -= 1\\n \\n self.trajectory.append([temp_state, action, self.__reward(self.state)])\",\n \"def ParAdd(A, B):\\n return _hypre.ParAdd(A, B)\",\n \"def __add__(self, other):\\n return Base40Pitch(self.base40 + other.base40)\",\n \"def _evolve_phaseshift_element(self, state, element):\\n new_state = PhotonicState()\\n for in_modes, in_amp in state.items():\\n phases = element.global_U(N).diagonal()\\n phase_shift = np.prod([phases[i] for i in in_modes])\\n new_state[in_modes] = phase_shift * in_amp \\n return new_state\",\n \"def __iadd__(self, B):\\n return _hypre.HypreParMatrix___iadd__(self, B)\",\n \"def phase(self):\\n\\n self.theta = np.arctan(np.sqrt(self.P / (1 - self.P)))\\n return self\",\n \"def calc_phase(p, t):\\n\\n return (t % p)/p\",\n \"def add(self, p, s, node) -> None:\\n self.place.append(p)\\n self.station.append(s)\\n self.pi.append(node.pi[p, s] if p != float('inf') else float('inf'))\\n self.noncoverage.append(node.noncoverage.left + node.noncoverage.right)\\n self.cost.append(node.cost)\\n self.delay.append(node.delay)\\n self.step.append(node.key)\",\n \"def powerpupgain_fn(self, X, Xp):\\n deg = self.order\\n v = self.theta\\n Y = v[0, 0] + v[0, 1] * X + v[0, 2] * \\\\\\n np.power(Xp, deg) + v[0, 3] * np.multiply(X, np.power(Xp, deg))\\n return(Y)\",\n \"def BPL(self, value):\\n if not self.reg.N:\\n self.reg.PC += value\",\n \"def add(self, params):\\n if len(params) < 2:\\n return\\n x = self.reg_dct[params[0]]\\n y = self.reg_dct[params[1]]\\n self.reg_dct[params[0]] = (x + y) % (2** 32)\",\n \"def add_pion(self, p):\\n self.pions[p.x][p.y] = p\\n self.pionsliste.append(p)\",\n \"def add_ptx(self):\\n self.pmos = ptx(width=self.ptx_width,\\n tx_type=\\\"pmos\\\")\\n self.add_mod(self.pmos)\",\n \"def _step(self, P, W):\\n Qa = self.mul(self.ch + 1, P)\\n if len(Qa) == 1:\\n _log.debug(\\\"[%d]P is zero\\\" % (self.ch + 1))\\n Qb = R = self.mul(W, P)\\n A = [Qa[0]]\\n B = [0, Qb[0]] # 0 = [0][0] ((infinity)_x)\\n for i in range(1, W):\\n Qa = self.add(Qa, P)\\n Qb = self.add(Qb, R)\\n A.append(Qa[0])\\n B.append(Qb[0])\\n if len(Qa) == 1:\\n _log.debug(\\\"[%d]P is zero\\\" % (self.ch + 1 + i))\\n break\\n return [A, B, set(A).intersection(set(B))]\",\n \"def __add__(self, B):\\n return (Polynomial(self) + B).simplify()\",\n \"def map(self, second_q_op: ParticleOp) -> PauliSumOp:\\n # TODO\\n raise NotImplementedError()\",\n \"def append(ps, p):\\n return np.append(ps, [p], axis=0)\",\n \"def eAdd(P, Q): #adds 2 points by using the slope to find where the line intersects and returns the negation of that point\\r\\n R = point(0,0,P.c) #creates point object to store result\\r\\n if (P.x == 0 and P.y == 0) and (Q.x == 0 and Q.y == 0): #(0,0) is the identity\\r\\n return P #returns the identity\\r\\n elif P.x == 0 and P.y == 0:\\r\\n return Q\\r\\n elif Q.x == 0 and Q.y == 0:\\r\\n return P\\r\\n elif P == Q: #in case it is called when double should be\\r\\n R = eDouble(P)\\r\\n else: #this preforms the actual addition\\r\\n i = P.y-Q.y\\r\\n j = P.x-Q.x\\r\\n s = (i * modInv(j, P.c.p) ) % P.c.p\\r\\n R.x = ( ( (s**2) - P.x - Q.x) % P.c.p)\\r\\n R.y = ( (-P.y + s * (P.x - R.x) ) % P.c.p)\\r\\n return R\",\n \"def addFP(self, num=1):\\n self.fp += num\",\n \"def phase(self):\\n pass\",\n \"def add_points(self, P, Q):\\n xp, yp = P\\n xq, yq = Q\\n s = ((yq - yp) * self.inv(xq - xp)) % self.fp\\n xr = (s ** 2 - xp - xq) % self.fp\\n yr = (s * (xp - xr) - yp) % self.fp\\n return (xr, yr)\",\n \"def _append_phase(self, k, i):\\n if not 0 <= i < self.num_qubits:\\n raise QiskitError(\\\"phase qubit out of bounds.\\\")\\n # If the kth bit is flipped, conjugate this gate\\n if self.shift[i] == 1:\\n k = (7 * k) % 8\\n # Take all subsets \\\\alpha of the support of row i\\n # of weight up to 3 and add k*(-2)**(|\\\\alpha| - 1) mod 8\\n # to the corresponding term.\\n support = np.arange(self.num_qubits)[np.nonzero(self.linear[i])]\\n subsets_2 = itertools.combinations(support, 2)\\n subsets_3 = itertools.combinations(support, 3)\\n for j in support:\\n value = self.poly.get_term([j])\\n self.poly.set_term([j], (value + k) % 8)\\n for j in subsets_2:\\n value = self.poly.get_term(list(j))\\n self.poly.set_term(list(j), (value + -2 * k) % 8)\\n for j in subsets_3:\\n value = self.poly.get_term(list(j))\\n self.poly.set_term(list(j), (value + 4 * k) % 8)\",\n \"def cp(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_P, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def __add__(self, other):\\n if other == 0:\\n return self\\n\\n pmf = Pmf()\\n for v1, p1 in self.items():\\n for v2, p2 in other.items():\\n pmf[v1 + v2] += p1 * p2\\n return pmf\",\n \"def __add__(self, other):\\n return add_mps(self, other)\",\n \"def nopupgain_fn(self, X, Xp):\\n Y = self.theta[0, 0] + self.theta[0, 1] * X\\n return(Y)\",\n \"def add(self, p):\\n\\n self.poses.append(CalibrationPoint(p))\\n self.selected_point = len(self.poses) - 1\\n self.calibration_changed()\",\n \"def _add_op(value, sample_args, rationals_allowed):\\n entropy, sample_args = sample_args.peel()\\n if rationals_allowed and sample_args.count >= 3:\\n x = number.integer_or_rational(entropy, True)\\n else:\\n x = number.integer(entropy, True)\\n if random.choice([False, True]):\\n op_args = [x, value - x]\\n else:\\n op_args = [value - x, x]\\n return ops.Add, op_args, sample_args\",\n \"def post_build(self, p, pay):\\n p += pay\\n if self.type in [0, 0x31, 0x32, 0x22]: # for these, field is reserved (0)\\n p = p[:1]+chr(0)+p[2:]\\n if self.chksum is None:\\n ck = checksum(p)\\n p = p[:2]+chr(ck>>8)+chr(ck&0xff)+p[4:]\\n return p\",\n \"def e_add(pub, a, b):\\n return a * b % pub.n_sq\",\n \"def add(self, publication: P) -> None:\\n ...\",\n \"def enc_add(pub, m1, m2):\\n add_result = m1 * m2 % pub.n_sq\\n return add_result\",\n \"def __call__(self, q: Tensor, p: Tensor, *args, **kwargs) -> Tensor:\\n return self.potential(q) + self.kinetic(p)\",\n \"def Addition(self, paren=False):\\n left = self.Term(paren)\\n while self.currtok[1].name in {\\\"PLUS\\\", \\\"MINUS\\\"}:\\n op = self.currtok[0]\\n self.currtok = next(self.tg)\\n right = self.Term(paren)\\n left = BinaryExpr(op, left, right, paren)\\n return left\",\n \"def addPol(*pol):\\n\\n sum = np.zeros((1,))\\n for p in pol:\\n sum = polyadd(sum, p)\\n\\n return sum\",\n \"def app_phase(data_pupil,data_phase,oversize=4):\\n return phaseangle(app_complex(data_pupil,data_phase,oversize))\",\n \"def __add__(\\n self,\\n other: Union[TensorWrappedPhiTensorPointer, MPCTensor, int, float, np.ndarray],\\n ) -> Union[TensorWrappedPhiTensorPointer, MPCTensor]:\\n return TensorWrappedPhiTensorPointer._apply_op(self, other, \\\"__add__\\\")\",\n \"def _phi(self, x, d, p):\\n ks = np.arange(self.p + 1)\\n ks = ks[np.where(2 * (self.p - ks) - d >= 0)][:, np.newaxis]\\n return np.sum(\\n binom(self.p, ks)\\n * (-1) ** ks\\n * x[np.newaxis, :] ** (2 * (self.p - ks) - d)\\n * perm(2 * (self.p - ks), d),\\n axis=0,\\n )\",\n \"def phase(freqs, p0, p1, p2):\\n x = utils.reduce_by_midpoint(freqs)\\n phi = p0 + p1 * x + p2 * x ** 2\\n return np.exp(1j * phi)\",\n \"def forward(self, ps):\\n if self.w is None or len(self.w) != ps.size(-1):\\n self.populate_w(ps)\\n\\n out = (ps*self.w).sum(-1)\\n return out\",\n \"def multiply(self, P):\\n if self.getDegree() == -1 or P.getDegree() == -1:\\n return Polynomial([])\\n \\n coefs_of_product = [0] * (self.getDegree() + P.getDegree() + 1)\\n for i in range(self.getDegree() + 1):\\n for j in range(P.getDegree() + 1):\\n coefs_of_product[i + j] += self.__coefficients[i] * P.__coefficients[j]\\n return Polynomial(coefs_of_product)\",\n \"def __iadd__(self, point):\\n self.points.append(point)\\n return self\",\n \"def addOp(self, op):\\n self.operations << op\",\n \"def p1(self, p1):\\n p0 = self.p0\\n u = self.p1 - p0\\n v = p1 - p0\\n\\n scale, rM = self.scale_rot_matrix(u, v)\\n self.c = p0 + rM @ (self.c - p0)\\n self.r *= scale\\n self.r2 = self.r * self.r\\n dp = p0 - self.c\\n self.a0 = atan2(dp.y, dp.x)\",\n \"def P(self,numSeg):\\n w=self.x/numSeg\\n return (w/3)*(self.F(0)+self.sumaImpar(numSeg,w)+self.sumaPar(numSeg,w)+self.F(self.x))\",\n \"def ADD():\\n global pointer, memory, registers\\n registers[memory[pointer + 0x02]] += memory[pointer + 0x01]\\n pointer += 0x03\",\n \"def P2G_func(self, dt, P):\\n p_C = ti.static(self.p_C)\\n p_v = ti.static(self.p_v)\\n p_x = ti.static(self.p_x)\\n g_m = ti.static(self.g_m)\\n g_v = ti.static(self.g_v)\\n p_F = ti.static(self.p_F)\\n p_Jp = ti.static(self.p_Jp)\\n\\n base = ti.floor(g_m.getG(p_x[P] - 0.5 * g_m.dx)).cast(Int)\\n fx = g_m.getG(p_x[P]) - base.cast(Float)\\n\\n # Here we adopt quadratic kernels\\n w = [0.5 * (1.5 - fx) ** 2, 0.75 - (fx - 1) ** 2, 0.5 * (fx - 0.5) ** 2]\\n # dw = [fx - 1.5, -2.0 * (fx - 1), fx - 0.5]\\n\\n # # TODO affine would do this in P2G.. why\\n # p_F[P] = (ti.Matrix.identity(Int, self.dim) + dt * p_C[P]) @ p_F[P]\\n\\n force = ti.Matrix.zero(Float, self.dim, self.dim)\\n # want to decrease branching\\n if self.p_material_id[P] == MaType.elastic:\\n force = self.elasticP2Gpp(P, dt)\\n elif self.p_material_id[P] == MaType.liquid:\\n force = self.liquidP2Gpp(P, dt)\\n elif self.p_material_id[P] == MaType.snow:\\n force = self.snowP2Gpp(P, dt)\\n elif self.p_material_id[P] == MaType.sand:\\n force = self.sandP2Gpp(P, dt)\\n\\n affine = force + self.cfg.p_mass * p_C[P]\\n for offset in ti.static(ti.grouped(self.stencil_range3())):\\n # print(\\\"P2G: \\\", offset)\\n dpos = g_m.getW(offset.cast(Float) - fx)\\n\\n weight = 1.0\\n for d in ti.static(range(self.dim)):\\n weight *= w[offset[d]][d]\\n\\n # dweight = ts.vecND(self.dim, self.cfg.inv_dx)\\n # for d1 in ti.static(range(self.dim)):\\n # for d2 in ti.static(range(self.dim)):\\n # if d1 == d2:\\n # dweight[d1] *= dw[offset[d2]][d2]\\n # else:\\n # dweight[d1] *= w[offset[d2]][d2]\\n\\n # force = - self.cfg.p_vol * kirchoff @ dweight\\n # TODO ? AFFINE\\n # g_v[base + offset] += self.cfg.p_mass * weight * (p_v[P] + p_C[P] @ dpos) # momentum transfer\\n # TODO Got lots of simultaneous atomic here\\n g_v[base + offset] += weight * (self.cfg.p_mass * self.p_v[P] + affine @ dpos)\\n g_m[base + offset] += weight * self.cfg.p_mass\\n\\n # g_v[base + offset] += dt * force\",\n \"def Phi(v, p, q):\\n \\n return np.sum([Y(t,p,q) for t in v])\",\n \"def globalphase_compiler(self, gate, args):\\n pass\",\n \"def globalphase_compiler(self, gate, args):\\n pass\",\n \"def translate( t, P ): \\n assert t.shape[0]==P.n # Dimension match \\n if P.type=='AH_polytope':\\n return pp.AH_polytope(t=t+P.t,T=P.T,P=P.P)\\n elif P.type=='zonotope':\\n return pp.zonotope(x=t+P.x,G=P.G)\\n elif P.type==\\\"H_polytope\\\":\\n return pp.H_polytope(H=P.H,h=P.h+np.dot(P.H,t))\\n else:\\n return ValueError('Polytope type: ',P.type,\\\" Not recognized\\\")\",\n \"def p(self, p: ComType):\\n if isinstance(p, complex):\\n self._pwr = p\\n else:\\n self._pwr = complex(p, 0)\",\n \"def cphaseshift(control: QubitInput, target: QubitInput, angle: float) -> Instruction:\\n return Instruction(CPhaseShift(angle), target=[control, target])\",\n \"def AddPseudoCode(self, pcode):\\n self.buffers[self.buffergrade].append(pcode)\",\n \"def perform_phase_processing(LP_solver=\\\"pyglpk\\\"):\\n radar = pyart.testing.make_single_ray_radar()\\n phidp, kdp = pyart.correct.phase_proc_lp(radar, 0.0, LP_solver=LP_solver)\\n return radar, phidp, kdp\",\n \"def CR(phi):\\n return (np.kron(P0,s0) + np.kron(P1,R(phi)))\",\n \"def perform_phase_processing_gf(LP_solver=\\\"pyglpk\\\"):\\n radar = pyart.testing.make_single_ray_radar()\\n my_gatefilter = pyart.filters.GateFilter(radar)\\n my_gatefilter.exclude_below(\\\"normalized_coherent_power\\\", 0.5)\\n my_gatefilter.exclude_below(\\\"cross_correlation_ratio\\\", 0.8)\\n phidp, kdp = pyart.correct.phase_proc_lp_gf(\\n radar,\\n gatefilter=my_gatefilter,\\n LP_solver=LP_solver,\\n doc=15,\\n ncpts=20,\\n system_phase=-140.1,\\n )\\n return radar, phidp, kdp\",\n \"def p0(self, p0):\\n u = self.p0 - self.p1\\n v = p0 - self.p1\\n scale, rM = self.scale_rot_matrix(u, v)\\n self.c = self.p1 + rM @ (self.c - self.p1)\\n self.r *= scale\\n self.r2 = self.r * self.r\\n dp = p0 - self.c\\n self.a0 = atan2(dp.y, dp.x)\",\n \"def _push(register):\\n ucode = assemble(SET, PUSH, Z)\\n ucode += assemble(SET, Z, register)\\n return ucode\",\n \"def laplacian(self, p):\\n wf = self._wf(p)\\n return - G * self.d * wf.sum()\",\n \"def update(self, p):\\n current_steps = len(self) - 1\\n delta = np.zeros(shape=self.theta.shape) # [y, x, 4]\\n subdelta = np.zeros(shape=self.theta.shape)\\n ys, xs, _ = delta.shape\\n\\n for act, state in zip(self.action, self.state_history):\\n if not np.isnan(act):\\n x, y = state\\n delta[y, x, :] += 1\\n subdelta[y, x, act] += 1\\n\\n delta_theta = (subdelta - p * delta) / current_steps\\n\\n self.theta = self.theta + self.lr * delta_theta\\n self.delta = np.sum(np.abs(self.convert(self.theta)-p))\",\n \"def add(self, p1, p2):\\n if p1 is None:\\n return p2\\n if p2 is None:\\n return p1\\n x1, y1 = p1\\n x2, y2 = p2\\n if x1 != x2:\\n l = self.div_mod_p(y2 - y1, x2 - x1)\\n x3 = (l * l - x1 - x2) % self.p\\n y3 = (l * (x1 - x3) - y1) % self.p\\n return (x3, y3)\\n elif y1 == y2 and y1 != 0:\\n l = self.div_mod_p(3 * x1**2 + self.a, 2 * y1)\\n x3 = (l**2 - 2 * x1) % self.p\\n y3 = (l * (x1 - x3) - y1) % self.p\\n return (x3, y3)\\n else:\\n return None\",\n \"def __add__(self, other):\\n if (len(self.arg) < len(other.arg)):\\n summ = Polynomial(other.arg)\\n i = len(self.arg) - 1\\n for x in self.arg:\\n summ.arg[i] = self.arg[i] + summ.arg[i]\\n i = i - 1\\n else:\\n summ = Polynomial(self.arg)\\n i = len(other.arg) - 1\\n for x in other.arg:\\n summ.arg[i] = other.arg[i] + summ.arg[i]\\n i = i - 1\\n return summ\",\n \"def PLA(self, *_):\\n result = self.pop()\\n self.reg.N = result >> 7\\n self.reg.Z = result == 0\\n self.reg.A = result\",\n \"def g(self, p):\\n re = self._re(p)\\n Le = self._Le(p)\\n wf = self._wf(p)\\n rf = self._rf(p)\\n A = Le @ np.einsum('...ij,...j', self.Ee, re)\\n B = wf @ np.einsum('...ij,...j', self.Ff, rf)\\n return (B - A) * G * self.d\",\n \"def add_next_pipulse_step(self):\\n qubit = self.qubit\\n\\n adaptive = self.get_param_value('adaptive')\\n transition = self.get_param_value('transition_name')\\n settings = self.settings.copy({})\\n\\n if adaptive:\\n # Retrieving T2_star and pi-pulse amplitude\\n if transition == \\\"ge\\\":\\n T2_star = qubit.T2_star() if qubit.T2_star() else 0\\n amp180 = qubit.ge_amp180() if qubit.ge_amp180() else 0\\n elif transition == \\\"ef\\\":\\n T2_star = qubit.T2_star_ef() if qubit.T2_star_ef() else 0\\n amp180 = qubit.ef_amp180() if qubit.ef_amp180() else 0\\n else:\\n raise ValueError('transition must either be \\\"ge\\\" or \\\"ef\\\"')\\n\\n # This has to be solved differently now\\n # Amplitudes for Rabi\\n # 1) if passed in init\\n # 2) v_high based on current pi-pulse amplitude\\n # 3) v_high based on default value\\n # if rabi_amps is None:\\n if amp180:\\n rabi_settings = {\\n 'Rabi': {\\n 'v_max': amp180\\n }\\n }\\n update_nested_dictionary(settings, rabi_settings)\\n\\n # Delays and artificial detuning for Ramsey\\n # if ramsey_delays is None or artificial_detuning is None:\\n # defining delta_t for Ramsey\\n # 1) if passed in init\\n # 2) based on T2_star\\n # 3) based on default\\n if self.get_param_value(\\\"use_T2_star\\\"):\\n ramsey_settings = {\\n 'Ramsey': {\\n 'delta_t': T2_star\\n }\\n }\\n update_nested_dictionary(settings, ramsey_settings)\\n\\n transition_name = self.get_param_value(\\\"transition_name\\\",\\n qubit=self.qubit)\\n pipulse_settings = {\\n \\\"PiPulseCalibration\\\": {\\n \\\"General\\\": {\\n \\\"transition_name\\\": transition_name,\\n }\\n }\\n }\\n update_nested_dictionary(settings, pipulse_settings)\\n\\n self.add_step(\\n PiPulseCalibration,\\n 'pi_pulse_calibration',\\n {\\n 'settings': settings\\n }\\n )\",\n \"def phase(self):\\r\\n return 0.2 * self.weights\",\n \"def __addOrAndSub(self, VMInstruction):\\r\\n self.__writer.write(\\\"@SP\\\\n\\\")\\r\\n self.__writer.write(\\\"M=M-1\\\\n\\\")\\r\\n self.__writer.write(\\\"A=M\\\\n\\\")\\r\\n self.__writer.write(\\\"D=M\\\\n\\\")\\r\\n self.__writer.write(\\\"@SP\\\\n\\\")\\r\\n self.__writer.write(\\\"A=M-1\\\\n\\\")\\r\\n self.__writer.write(\\\"M=M\\\" + str(self.__compVal(VMInstruction)) + \\\\\\r\\n \\\"D\\\\n\\\")\",\n \"def add_reg_to_reg(self):\\n register = self.return_middle_registers(self.opcode)\\n sum = self.registers[register[0]] + self.registers[register[1]]\\n if sum > 0xFF:\\n self.registers[0xF] = 1\\n self.registers[register[0]] = sum & 0xFF\\n else:\\n self.registers[0xF] = 0\\n self.registers[register[0]] = sum\\n logger.info(\\\"Added V{} to V{} and got {}\\\".format(\\n register[0],\\n register[1],\\n self.registers[register[0]]))\",\n \"def p(e, t):\\n return b * e ** 2\",\n \"def forward(self, inp):\\n return inp.dot(self.W) + self.b\",\n \"def f_UPPS_pc(v, P_0, r_f, d, s, T, wealth, phi, n_s, n_o, K):\\n W_T = f_W_T_pc(v, P_0, r_f, d, s, T, wealth, phi, n_s, n_o, K)\\n value = pow(W_T, -gamma) * f_W_T_to_P_T_pc(v, P_0, r_f, d, s, T, wealth, phi, n_s, n_o, K) * f_P_T_to_P_0(v, r_f, d, s, T)\\n return value\",\n \"def forward(x, pi, A, B):\\n # TODO: Write this function.\\n #x = x[1]\\n B_col = B[:, x[0]] # [N_z, 1]\\n alpha = np.multiply(pi, B_col)\\n ret = np.zeros((x.shape[0], pi.shape[0]))\\n ret[0] = alpha\\n for i in range(1, x.shape[0]):\\n B_col = B[:, x[i]]\\n sum_term = np.dot(A, alpha) #before: alpha, A\\n alpha = np.multiply(B_col, sum_term) #before: sum_term before\\n ret[i] = alpha\\n return ret\",\n \"def test_special_PSX(self, angexp):\\n a, b, c = angexp[0]\\n tgt = U3Gate(a, b, c).to_matrix()\\n exp = {(\\\"p\\\", \\\"sx\\\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\\n self.check_oneq_special_cases(tgt, \\\"PSX\\\", exp)\",\n \"def wpqu_union(self, p, q):\\n if self.wpqu_connected(p,q):\\n return True;\\n \\n p_pa,q_pa = self.id[p],self.id[q]\\n \\n if self.sz[p_pa] >= self.sz[q_pa]:\\n self.id[q_pa] = p_pa\\n self.sz[p_pa] += self.sz[q_pa] \\n else:\\n self.id[p_pa] = q_pa\\n self.sz[q_pa] += self.sz[p_pa] \\n return True\",\n \"def TR_algo7(self, p):\\n h = 0\\n ve = 0\\n vd = self._vd\\n m = max(self._compact_M)\\n for i in range(m-1, -1, -1):\\n mu = self.extract_mask(i)\\n mu_norm = sum([bit_component(mu, j) for j in range(self._N)])\\n mu = rotate_right(mu, vd+1)\\n pi = rotate_right(ve, vd+1) & ((~mu) & 2**self._N-1)\\n l = [bit_component(px, i) for px in p]\\n # 2. construct a integer whose bits are given by l\\n l = sum( [lx*2**j for j, lx in enumerate(l)] )\\n l = T(ve, vd, l)\\n w = inverse_gc(l)\\n r = gcr(w, mu, pi)\\n ve = ve ^ rotate_left(e(w), vd+1)\\n vd = (vd + d(w) + 1) % self._N\\n h = (h << mu_norm) | r\\n return h\",\n \"def elasticP2Gpp(self, P, dt):\\n p_Jp = ti.static(self.p_Jp)\\n p_F = ti.static(self.p_F)\\n\\n h = self.cfg.elastic_h\\n mu, la = h * self.cfg.mu_0, h * self.cfg.lambda_0\\n\\n U, sig, V = ti.svd(p_F[P])\\n J = 1.0\\n\\n for d in ti.static(range(self.dim)):\\n new_sig = sig[d, d]\\n p_Jp[P] *= sig[d, d] / new_sig\\n sig[d, d] = new_sig\\n J *= new_sig\\n\\n force = self.kirchoff_FCR(p_F[P], U @ V.transpose(), J, mu, la)\\n force *= (-dt * self.cfg.p_vol * 4 * self.cfg.inv_dx ** 2)\\n\\n return force\",\n \"def addTP(self, num=1):\\n self.tp += num\",\n \"def forward(self, s, p):\\n h1 = F.relu(self.l1_s(s))\\n h2 = F.relu(self.l1_p(p))\\n cat = torch.cat([h1, h2], dim=1)\\n q = F.relu(self.l2(cat))\\n q = self.l3(q)\\n return q\",\n \"def expression(self, p):\\n num_type, first, second = get_type_first_second_of_binary_operation(p.expression, p.term)\\n\\n opcode_type = I_for_int_R_for_float(num_type)\\n opcode_action = \\\"ADD\\\" if p.ADDOP == \\\"+\\\" else \\\"SUB\\\"\\n opcode = opcode_type + opcode_action\\n\\n temp = next(g_generate_temp_variable_name)\\n temp_variables_values_dict[temp] = temp\\n\\n qaud_code(f\\\"{opcode} {temp} {first} {second}\\\")\\n return Expression(num_type, temp)\",\n \"def cphaseshift01(control: QubitInput, target: QubitInput, angle: float) -> Instruction:\\n return Instruction(CPhaseShift01(angle), target=[control, target])\",\n \"def reflect_adp(adp, planev):\\n M = np.identity(4)\\n M[:3, :3] -= 2.0 * np.outer(planev, planev)\\n M[:3, 3] = (2.0 * np.dot(np.array([0, 0, 0]), planev)) * planev\\n\\n return rotate_adp(adp, M[:3, :3])\",\n \"def __radd__(self, left):\\n return self.value() + left\",\n \"def lpSum(vector):\\n\\treturn LpAffineExpression().addInPlace(vector)\",\n \"def phase_modulation_state(state, phase):\\n size = len(state)\\n st_mod = np.zeros((size, size), dtype=complex)\\n for p1 in range(size):\\n for p2 in range(size):\\n st_mod[p1, p2] = state[p1, p2] * np.exp(1j * p1 * phase)\\n return st_mod\",\n \"def phase(state, i):\\n particles = bin(state >> i + 1).count(\\\"1\\\")\\n return 1 if particles % 2 == 0 else -1\",\n \"def mod(p):\\n return (p[0]**2 + p[1]**2 + p[2]**2)**0.5\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def computeSPPMI_matrix(P, shifted_k: int, check_sym = True):\\n a, b = P.shape\\n # print P.shape, type(P)\\n P = np.asarray(P)\\n # print 'Shape of P: ', P.shape\\n assert a == b\\n D = np.sum(P)\\n cols = np.sum(P, axis = 0) # sum the columns (b,)\\n rows = np.sum(P, axis = 1, keepdims=True) # sum the row (a,1)\\n P = P / (cols + 1e-10)\\n P = P / (rows + 1e-10)\\n P = P * D\\n PMI = np.log(P + 1e-10)\\n S = PMI - np.log(shifted_k)\\n mask = S > 0\\n SPPMI = np.multiply(S, mask)\\n assert np.min(SPPMI) == 0\\n if check_sym: np.fill_diagonal(SPPMI, 0) # in-place operation\\n assert torch_utils.check_symmetric(SPPMI) == True\\n return SPPMI\",\n \"def g_R_mix_i(s, p, k='x'): # (Validated)\\n from numpy import log\\n if k == 'y': # 'y' = Vapour phase standard\\n V = s.m['V_v'] \\n else: # Assume all phases other than vapour are liquid, ex. 'x'\\n V = s.m['V_l'] \\n \\n return (s.m['P'] * V / (p.m['R'] * s.m['T']) - 1.0\\n - log(s.m['P'] / (p.m['R'] * s.m['T']))\\n - log(V - s.m['b']) \\n - s.m['a'] / (p.m['R'] * s.m['T'] * V))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6318269","0.59578127","0.5915731","0.5825227","0.5744571","0.5720372","0.5641655","0.559485","0.55680496","0.55604863","0.546399","0.5454236","0.5415402","0.53876317","0.5367949","0.52692","0.5242477","0.5239249","0.5235476","0.52338487","0.5204293","0.5202493","0.51742405","0.5162368","0.5146409","0.5127961","0.51227784","0.5109219","0.51062965","0.5087426","0.50755155","0.5075264","0.5071368","0.5070906","0.50414485","0.50159544","0.50026345","0.49997965","0.49947557","0.4990972","0.49797","0.4962883","0.49582124","0.49567243","0.49566025","0.4949606","0.49411887","0.49335524","0.49304238","0.49289188","0.49257666","0.4918245","0.4913955","0.49134767","0.49064553","0.49006066","0.4899662","0.48995733","0.48982406","0.48982406","0.48980278","0.48910055","0.48899508","0.48825893","0.4880411","0.4876827","0.48723558","0.48716548","0.48626983","0.48604327","0.48552388","0.4851422","0.48512906","0.48486543","0.48483893","0.48480743","0.48339504","0.4833461","0.4830142","0.48286116","0.48281795","0.48244748","0.48244742","0.48240656","0.48233384","0.4823084","0.48187464","0.4818118","0.48175755","0.480873","0.4803001","0.4792388","0.47914803","0.47873816","0.47838795","0.47730923","0.47646105","0.47623116","0.47621483","0.47593248"],"string":"[\n \"0.6318269\",\n \"0.59578127\",\n \"0.5915731\",\n \"0.5825227\",\n \"0.5744571\",\n \"0.5720372\",\n \"0.5641655\",\n \"0.559485\",\n \"0.55680496\",\n \"0.55604863\",\n \"0.546399\",\n \"0.5454236\",\n \"0.5415402\",\n \"0.53876317\",\n \"0.5367949\",\n \"0.52692\",\n \"0.5242477\",\n \"0.5239249\",\n \"0.5235476\",\n \"0.52338487\",\n \"0.5204293\",\n \"0.5202493\",\n \"0.51742405\",\n \"0.5162368\",\n \"0.5146409\",\n \"0.5127961\",\n \"0.51227784\",\n \"0.5109219\",\n \"0.51062965\",\n \"0.5087426\",\n \"0.50755155\",\n \"0.5075264\",\n \"0.5071368\",\n \"0.5070906\",\n \"0.50414485\",\n \"0.50159544\",\n \"0.50026345\",\n \"0.49997965\",\n \"0.49947557\",\n \"0.4990972\",\n \"0.49797\",\n \"0.4962883\",\n \"0.49582124\",\n \"0.49567243\",\n \"0.49566025\",\n \"0.4949606\",\n \"0.49411887\",\n \"0.49335524\",\n \"0.49304238\",\n \"0.49289188\",\n \"0.49257666\",\n \"0.4918245\",\n \"0.4913955\",\n \"0.49134767\",\n \"0.49064553\",\n \"0.49006066\",\n \"0.4899662\",\n \"0.48995733\",\n \"0.48982406\",\n \"0.48982406\",\n \"0.48980278\",\n \"0.48910055\",\n \"0.48899508\",\n \"0.48825893\",\n \"0.4880411\",\n \"0.4876827\",\n \"0.48723558\",\n \"0.48716548\",\n \"0.48626983\",\n \"0.48604327\",\n \"0.48552388\",\n \"0.4851422\",\n \"0.48512906\",\n \"0.48486543\",\n \"0.48483893\",\n \"0.48480743\",\n \"0.48339504\",\n \"0.4833461\",\n \"0.4830142\",\n \"0.48286116\",\n \"0.48281795\",\n \"0.48244748\",\n \"0.48244742\",\n \"0.48240656\",\n \"0.48233384\",\n \"0.4823084\",\n \"0.48187464\",\n \"0.4818118\",\n \"0.48175755\",\n \"0.480873\",\n \"0.4803001\",\n \"0.4792388\",\n \"0.47914803\",\n \"0.47873816\",\n \"0.47838795\",\n \"0.47730923\",\n \"0.47646105\",\n \"0.47623116\",\n \"0.47621483\",\n \"0.47593248\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.61503357"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81739,"cells":{"query":{"kind":"string","value":"add U1 gate (by IBM)."},"document":{"kind":"string","value":"def u1(self, q0, alpha=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_U1, qid=[q0], phase=alpha, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def cu1(self, q0, q1, alpha=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U1, qid=[q0,q1], phase=alpha, ctrl=ctrl)\n return self","def _action_op_u1(self, plaq):\n # if self.link_type == 'U1':\n # return np.cos(plaq)\n return tf.math.cos(plaq)","def ADD (self, n1, n2):","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def server1_add1(c1, c2, pub):\n return add1 (c1, c2, pub)","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def I1_u1(self) -> complex:\n # Should match in amplitude with \"Phase 1 current [A]\"\n # Convert from relative to U12 -> relative to U1\n return - (self.I1_u12() * cmath.rect(1, 150 / 180 * cmath.pi))","def bias_add_v1(value, bias, name=None):\n with ops.name_scope(name, \"BiasAddV1\", [value, bias]) as name:\n value = ops.convert_to_tensor(value, name=\"input\")\n bias = ops.convert_to_tensor(bias, dtype=value.dtype, name=\"bias\")\n return gen_nn_ops.bias_add_v1(value, bias, name=name)","def add_one(x):\n return x + 1","def __add__(self,that):\n return self.__opExpand2(that,np.add)","def __iadd__(self,l):\r\n\t\t\r\n\t\treturn self.add(l)","def test_special_U1X(self):\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \"U1X\", {})\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \"U1X\", {\"u1\": 1})\n self.check_oneq_special_cases(\n U3Gate(-np.pi / 2, 0.2, 0.0).to_matrix(), \"U1X\", {\"u1\": 2, \"rx\": 1}\n )\n self.check_oneq_special_cases(\n U3Gate(np.pi / 2, 0.0, 0.21).to_matrix(), \"U1X\", {\"u1\": 2, \"rx\": 1}\n )\n self.check_oneq_special_cases(\n U3Gate(np.pi / 2, 0.12, 0.2).to_matrix(), \"U1X\", {\"u1\": 2, \"rx\": 1}\n )\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \"U1X\", {\"u1\": 3, \"rx\": 2})","def test_add_consistency1(self) -> None:\n a = Constant(\n 'const1',\n Float32(),\n np.zeros([1, 3, 3])\n )\n b = Constant(\n 'const2',\n Float32(),\n np.zeros([3])\n )\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\n Add(\n 'add1',\n [1, 3, 3],\n Float32(),\n input_ops\n )\n\n print(\"Consistency test for 'Add' #1 passed!\")","def __iadd__(self,that):\n #return self.__opExpand1(that,np.add, out=self)\n return self.__opExpand2(that,np.add, out=self)","def __radd__(self,that):\n return self.__opExpand2(that,np.add)","def plus1(x):\n return x + 1","def add(self, value):","def __add__(self,sample):\n self.add(sample)","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def add(value1, value2):\n return 1 / (1.0 / value1 + 1.0 / value2)","def plus_one(x):\n return x + 1","def server2_add1(b1, b2, pub):\n return (b1 + b2) % pub.n","def server1_add2 (c1, c2, pub):\n #return (c1 + c2) % pub.n\n return e_add(pub, c1, c2)","def x_add_one(nom):\n\tif 'X' in nom and '*' not in nom:\n\t\treturn nom.replace('X', '1*X')\n\treturn nom","def add_n():\n pass","def __add__(self, rhs):\n if isinstance(rhs, UTPS):\n return UTPS(self.tc + rhs.tc)\n elif numpy.isscalar(rhs):\n retval = UTPS(numpy.copy(self.tc))\n retval.tc[0] += rhs\n return retval\n else:\n raise NotImplementedError","def convert_add_scalar(node, **kwargs):\n return scalar_op_helper(node, 'Add', **kwargs)","async def uadd(self, *args: Input):\n # TODO(security) Allow for tuning nbytes\n return await self.sadd(secrets.token_hex(), *args)","def acumula_x1(self, x1, rodada):\n self.x1[rodada].append(x1)","def add(self, y):\n return circuit.add(self, y)","def __iadd__(self, other):\n\n return self + other","def __add__(self, tc): \n tc = TwosComplement(tc)\n bits = self.len if self.len > tc.len else tc.len \n result = self.int + tc.int\n return TwosComplement(result, bits)","def do_add_reg(self, reg0, reg1):\n assert self.safe_register(reg0), f\"register error [{reg0}]\"\n assert self.safe_register(reg1), f\"register error [{reg1}]\"\n _sum = self.registers[reg0] + self.registers[reg1]\n if _sum <= 255:\n self.registers[reg0] = _sum\n else:\n self.registers[reg0] = 255","def convert_addn(node, **kwargs):\n return create_basic_op_node('Sum', node, kwargs)","def I1_u12(self) -> complex:\n return (self.S1_u12() / self.U12()).conjugate()","def add(num1,num2):\n if(num2==0):\n return num1\n return add((num1^num2),(num1&num2)<<1)","def __add__(self, other):\n return union(self, other, check_convex=True)","def add64(a,b):\n return(np.add(a, b, dtype=np.uint64))","def __iadd__(self, tensor):\n return self.add_(tensor)","def __add__(self, other):\r\n return self.add(other)","def ADD():\n global pointer, memory, registers\n registers[memory[pointer + 0x02]] += memory[pointer + 0x01]\n pointer += 0x03","def luk_plus_five(unit: ActiveUnit) -> None:\n unit.mod_luk += 5","def _add_op(value, sample_args, rationals_allowed):\n entropy, sample_args = sample_args.peel()\n if rationals_allowed and sample_args.count >= 3:\n x = number.integer_or_rational(entropy, True)\n else:\n x = number.integer(entropy, True)\n if random.choice([False, True]):\n op_args = [x, value - x]\n else:\n op_args = [value - x, x]\n return ops.Add, op_args, sample_args","def bias_add(in_tensor0, in_tensor1):\n dim_map = {}\n dim_map[\"out_img_shape\"] = te_util.shape_to_list(in_tensor0.shape)\n NAME_INDEX[0] += 1\n\n with tvm.tag_scope('conv_vector_bias_add'):\n c_add_vector = tvm.compute(\n dim_map[\"out_img_shape\"],\n lambda *indice: in_tensor0(*indice) + in_tensor1(indice[\n 1] * CUBE_MKN[in_tensor0.dtype]['mac'][2] + indice[3]),\n name='bias_add_vector' + \"_cc_\" + str(NAME_INDEX[0]))\n return c_add_vector","def increment(self):\r\n return self.add(1)","def S1_u12(self) -> complex:\n return complex(\n self._addr(self.defined_registers['Phase 1 power [W]']['addr']),\n self._addr(self.defined_registers['Phase 1 volt amps reactive [VAr]']['addr']),\n )","def addMe2Me(x):\n return x+x","def __iadd__( self, vector3 ):\n return self.add( vector3 )","def __add__(self, other):\n\n return self._binary_elementwise_op(other, np.add)","def __add__(self, other: 'SInt') -> 'SInt':\r\n # Recoding the addition\r\n if type(other) != self.__class__ or len(self) != len(other):\r\n raise TypeError(\"Wrong type or length for other\")\r\n retenue = [0 for i in range(len(self) + 1)]\r\n new_bin = ''\r\n for i in range(len(self)):\r\n k = int(self.binaire[-(i + 1)]) + int(other.binaire[-(i + 1)]) + retenue[i]\r\n new_bin = ['0', '1', '0', '1'][k] + new_bin\r\n retenue[i + 1] = 1 if k > 1 else 0\r\n if self.signe == other.signe and retenue[-1] != retenue[-2]:\r\n raise OverflowError(\"The sum is over the bytes available\")\r\n H = self.__class__(self.nbBytes)\r\n H.binaire = new_bin\r\n return H","def __radd__(self, other):\n return self + other","def __radd__(self, other):\n return self + other","def su(o1, o2):\n return o1+o2","def add(n1, n2):\n return n1 + n2","def add(n1, n2):\n return n1 + n2","def addU(self,name):\n return self._addVar(name,self._uNames)","def __iadd__(self, other):\n raise NotImplementedError(\"Implement this if needed\")","def __iadd__(self, other: t.Any) -> te.Self:\n return self._op_inplace('__iadd__', other)","def add(self, value):\n return self.number + value","def __add__(self, value):\n out = self.copy()\n out.addMath(Query.Math.Add, value)\n return out","def add(self, params):\n if len(params) < 2:\n return\n x = self.reg_dct[params[0]]\n y = self.reg_dct[params[1]]\n self.reg_dct[params[0]] = (x + y) % (2** 32)","def __iadd__(self, term):\n self.add(term)\n return self","def __add__(self, value):\r\n if isinstance(value, (int, dec.Decimal)):\r\n return self.__class__(self._real + value, self._imag)\r\n elif isinstance(value, self.__class__):\r\n return self.__class__(self._real + value._real, self._imag + value._imag)\r\n raise TypeError(\r\n 'unsupported operand type(s) for +: {!r} and {!r}'.format(\r\n self.__class__.__name__, value.__class__.__name__\r\n )\r\n )","def _add_scalar(self, scalar):\n\n a, b = self, scalar\n\n # Don't bother to salt/obfuscate in a basic operation, do it\n # just before leaving the computer.\n encrypted_scalar = a.public_key.raw_encrypt(b, 1)\n\n sum_ciphertext = a._raw_add(a.ciphertext(False), encrypted_scalar)\n return EncryptedNumber(a.public_key, sum_ciphertext)","def acumula_n1(self, n1, rodada):\n self.n1[rodada].append(n1)","def __add__(self, other):\n \"*** YOUR CODE HERE ***\"","def __add__(self, other):\n pass","def __add__(self, other):\n pass","def __radd__(self, value):\r\n if isinstance(value, (int, dec.Decimal)):\r\n return self.__class__(value + self._real, self._imag)\r\n elif isinstance(value, self.__class__):\r\n return self.__class__(value._real + self._real, value._imag + self._imag)\r\n raise TypeError(\r\n 'unsupported operand type(s) for +: {!r} and {!r}'.format(\r\n value.__class__.__name__, self.__class__.__name__\r\n )\r\n )","def plus(self, a, b):\n return a + b","def double_add(self, x):\n self.add(x*2)","def add(*args):\n\n result = int(args[0]) + int(args[1])\n\n return str(result)","def __iadd__(self, other):\n\n if isinstance(other, float):\n self.iadd_scalar(other)\n else:\n self.iadd(other)","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def add(a,b):\n\treturn a+b","def __iadd__(self, m):\n if self.__mm_type(m):\n ls=len(self)\n for i in self.desc():\n for j in range(ls):\n self.g_val(self.val(i,j)+m.val(i,j),i,j)\n return self","def addition():\r\n error_handler()\r\n f1.delete(0, END)\r\n a1 = float(operand.get())\r\n a2 = float(operator.get())\r\n result = a1 + a2\r\n f1.insert(10, str(result))","def vector_add(v1, v2):\n return v1[0] + v2[0], v1[1] + v2[1]","def union_add(this, that):\n return this.add(that, fill_value=0)","def __add__(self, other):\n return self.add(other)","def __radd__(self, left):\n return self.value() + left","def add(self, x):\n if type(x) is int:\n self.real += x\n else:\n self.real = self.real + x.real\n self.imag = self.imag + x.imag","def add():\n pass","def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\n return self","def __add__(self, B):\n return (Polynomial(self) + B).simplify()","def add_reg_to_reg(self):\n register = self.return_middle_registers(self.opcode)\n sum = self.registers[register[0]] + self.registers[register[1]]\n if sum > 0xFF:\n self.registers[0xF] = 1\n self.registers[register[0]] = sum & 0xFF\n else:\n self.registers[0xF] = 0\n self.registers[register[0]] = sum\n logger.info(\"Added V{} to V{} and got {}\".format(\n register[0],\n register[1],\n self.registers[register[0]]))","def __add__(self, other):\n return add_mps(self, other)","def __add__(self,l):\r\n\t\t\r\n\t\t# add\r\n\t\ta = self.add(l)\r\n\t\t\r\n\t\treturn a","def _arithmetize1(self, operand: Any, op: str) -> Any:\n op_func = getattr(operator, op)\n # Data length might be changed after evaluation\n # operand = recycle_value(operand, self.data.shape[0])\n return op_func(operand)","def add(*args):\n\n # TODO: Fill sum with the correct value, based on the\n # args provided.\n sum = str(args[0] + args[1])\n return sum","def AssignAddHybrid1d(output, value, target=utils.CCE):\n for i in range(output.shape[0]):\n output[i] = output[i] + value[i]\n\n return output","def add(first, second):\n return first + second","def flexibase_add(str1, str2, base1, base2):\n result = int_to_base(tmp, base1)\n return result","def __iadd__(self, increment):\n self.update(self.val + increment)\n return self","def __add__(self, other):\n raise NotImplementedError","def __add__(self, other):\n raise NotImplementedError","def __add__(G, H):\n if isinstance(H, Surreal):\n return Surreal.from_value(G._n + H.n)\n if isinstance(H, numbers.Number):\n return Surreal.from_value(G._n + H)\n if isinstance(H, Game):\n return super().__add__(H)\n\n return NotImplemented","def acumula_ns1(self, ns1, rodada):\n self.ns1[rodada].append(ns1)","def add(num1, num2, Cin):\n Cin=0\n l2=[]\n final=\"\"\n\n \"\"\"Using for loop for starting addition from the last indexed number\"\"\"\n for i in range(len(num1)-1,-1,-1):\n bit1=num1[i]#storing each indexed() value of num1 in bit1\n bit2=num2[i]#storing each indexed() value of num2 in bit2\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\n Cin=Cout#declaring cout as cin for next bit addition\n l2.append(SUM)#adding SUM to l2\n l3=l2[::-1]##reversing the value of l2\n final+=str(l2[-1])#converting the list value to string\n final1=final[::-1]#reversing string value\n return final1 #returning the binary addition as string","def add(self, addr):\n\n val = self.mem.read(addr)\n result = self.alu.add(self.reg.accum, val)\n self.reg.accum = result"],"string":"[\n \"def cu1(self, q0, q1, alpha=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U1, qid=[q0,q1], phase=alpha, ctrl=ctrl)\\n return self\",\n \"def _action_op_u1(self, plaq):\\n # if self.link_type == 'U1':\\n # return np.cos(plaq)\\n return tf.math.cos(plaq)\",\n \"def ADD (self, n1, n2):\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def server1_add1(c1, c2, pub):\\n return add1 (c1, c2, pub)\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def I1_u1(self) -> complex:\\n # Should match in amplitude with \\\"Phase 1 current [A]\\\"\\n # Convert from relative to U12 -> relative to U1\\n return - (self.I1_u12() * cmath.rect(1, 150 / 180 * cmath.pi))\",\n \"def bias_add_v1(value, bias, name=None):\\n with ops.name_scope(name, \\\"BiasAddV1\\\", [value, bias]) as name:\\n value = ops.convert_to_tensor(value, name=\\\"input\\\")\\n bias = ops.convert_to_tensor(bias, dtype=value.dtype, name=\\\"bias\\\")\\n return gen_nn_ops.bias_add_v1(value, bias, name=name)\",\n \"def add_one(x):\\n return x + 1\",\n \"def __add__(self,that):\\n return self.__opExpand2(that,np.add)\",\n \"def __iadd__(self,l):\\r\\n\\t\\t\\r\\n\\t\\treturn self.add(l)\",\n \"def test_special_U1X(self):\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \\\"U1X\\\", {})\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \\\"U1X\\\", {\\\"u1\\\": 1})\\n self.check_oneq_special_cases(\\n U3Gate(-np.pi / 2, 0.2, 0.0).to_matrix(), \\\"U1X\\\", {\\\"u1\\\": 2, \\\"rx\\\": 1}\\n )\\n self.check_oneq_special_cases(\\n U3Gate(np.pi / 2, 0.0, 0.21).to_matrix(), \\\"U1X\\\", {\\\"u1\\\": 2, \\\"rx\\\": 1}\\n )\\n self.check_oneq_special_cases(\\n U3Gate(np.pi / 2, 0.12, 0.2).to_matrix(), \\\"U1X\\\", {\\\"u1\\\": 2, \\\"rx\\\": 1}\\n )\\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \\\"U1X\\\", {\\\"u1\\\": 3, \\\"rx\\\": 2})\",\n \"def test_add_consistency1(self) -> None:\\n a = Constant(\\n 'const1',\\n Float32(),\\n np.zeros([1, 3, 3])\\n )\\n b = Constant(\\n 'const2',\\n Float32(),\\n np.zeros([3])\\n )\\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\\n Add(\\n 'add1',\\n [1, 3, 3],\\n Float32(),\\n input_ops\\n )\\n\\n print(\\\"Consistency test for 'Add' #1 passed!\\\")\",\n \"def __iadd__(self,that):\\n #return self.__opExpand1(that,np.add, out=self)\\n return self.__opExpand2(that,np.add, out=self)\",\n \"def __radd__(self,that):\\n return self.__opExpand2(that,np.add)\",\n \"def plus1(x):\\n return x + 1\",\n \"def add(self, value):\",\n \"def __add__(self,sample):\\n self.add(sample)\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def add(value1, value2):\\n return 1 / (1.0 / value1 + 1.0 / value2)\",\n \"def plus_one(x):\\n return x + 1\",\n \"def server2_add1(b1, b2, pub):\\n return (b1 + b2) % pub.n\",\n \"def server1_add2 (c1, c2, pub):\\n #return (c1 + c2) % pub.n\\n return e_add(pub, c1, c2)\",\n \"def x_add_one(nom):\\n\\tif 'X' in nom and '*' not in nom:\\n\\t\\treturn nom.replace('X', '1*X')\\n\\treturn nom\",\n \"def add_n():\\n pass\",\n \"def __add__(self, rhs):\\n if isinstance(rhs, UTPS):\\n return UTPS(self.tc + rhs.tc)\\n elif numpy.isscalar(rhs):\\n retval = UTPS(numpy.copy(self.tc))\\n retval.tc[0] += rhs\\n return retval\\n else:\\n raise NotImplementedError\",\n \"def convert_add_scalar(node, **kwargs):\\n return scalar_op_helper(node, 'Add', **kwargs)\",\n \"async def uadd(self, *args: Input):\\n # TODO(security) Allow for tuning nbytes\\n return await self.sadd(secrets.token_hex(), *args)\",\n \"def acumula_x1(self, x1, rodada):\\n self.x1[rodada].append(x1)\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def __iadd__(self, other):\\n\\n return self + other\",\n \"def __add__(self, tc): \\n tc = TwosComplement(tc)\\n bits = self.len if self.len > tc.len else tc.len \\n result = self.int + tc.int\\n return TwosComplement(result, bits)\",\n \"def do_add_reg(self, reg0, reg1):\\n assert self.safe_register(reg0), f\\\"register error [{reg0}]\\\"\\n assert self.safe_register(reg1), f\\\"register error [{reg1}]\\\"\\n _sum = self.registers[reg0] + self.registers[reg1]\\n if _sum <= 255:\\n self.registers[reg0] = _sum\\n else:\\n self.registers[reg0] = 255\",\n \"def convert_addn(node, **kwargs):\\n return create_basic_op_node('Sum', node, kwargs)\",\n \"def I1_u12(self) -> complex:\\n return (self.S1_u12() / self.U12()).conjugate()\",\n \"def add(num1,num2):\\n if(num2==0):\\n return num1\\n return add((num1^num2),(num1&num2)<<1)\",\n \"def __add__(self, other):\\n return union(self, other, check_convex=True)\",\n \"def add64(a,b):\\n return(np.add(a, b, dtype=np.uint64))\",\n \"def __iadd__(self, tensor):\\n return self.add_(tensor)\",\n \"def __add__(self, other):\\r\\n return self.add(other)\",\n \"def ADD():\\n global pointer, memory, registers\\n registers[memory[pointer + 0x02]] += memory[pointer + 0x01]\\n pointer += 0x03\",\n \"def luk_plus_five(unit: ActiveUnit) -> None:\\n unit.mod_luk += 5\",\n \"def _add_op(value, sample_args, rationals_allowed):\\n entropy, sample_args = sample_args.peel()\\n if rationals_allowed and sample_args.count >= 3:\\n x = number.integer_or_rational(entropy, True)\\n else:\\n x = number.integer(entropy, True)\\n if random.choice([False, True]):\\n op_args = [x, value - x]\\n else:\\n op_args = [value - x, x]\\n return ops.Add, op_args, sample_args\",\n \"def bias_add(in_tensor0, in_tensor1):\\n dim_map = {}\\n dim_map[\\\"out_img_shape\\\"] = te_util.shape_to_list(in_tensor0.shape)\\n NAME_INDEX[0] += 1\\n\\n with tvm.tag_scope('conv_vector_bias_add'):\\n c_add_vector = tvm.compute(\\n dim_map[\\\"out_img_shape\\\"],\\n lambda *indice: in_tensor0(*indice) + in_tensor1(indice[\\n 1] * CUBE_MKN[in_tensor0.dtype]['mac'][2] + indice[3]),\\n name='bias_add_vector' + \\\"_cc_\\\" + str(NAME_INDEX[0]))\\n return c_add_vector\",\n \"def increment(self):\\r\\n return self.add(1)\",\n \"def S1_u12(self) -> complex:\\n return complex(\\n self._addr(self.defined_registers['Phase 1 power [W]']['addr']),\\n self._addr(self.defined_registers['Phase 1 volt amps reactive [VAr]']['addr']),\\n )\",\n \"def addMe2Me(x):\\n return x+x\",\n \"def __iadd__( self, vector3 ):\\n return self.add( vector3 )\",\n \"def __add__(self, other):\\n\\n return self._binary_elementwise_op(other, np.add)\",\n \"def __add__(self, other: 'SInt') -> 'SInt':\\r\\n # Recoding the addition\\r\\n if type(other) != self.__class__ or len(self) != len(other):\\r\\n raise TypeError(\\\"Wrong type or length for other\\\")\\r\\n retenue = [0 for i in range(len(self) + 1)]\\r\\n new_bin = ''\\r\\n for i in range(len(self)):\\r\\n k = int(self.binaire[-(i + 1)]) + int(other.binaire[-(i + 1)]) + retenue[i]\\r\\n new_bin = ['0', '1', '0', '1'][k] + new_bin\\r\\n retenue[i + 1] = 1 if k > 1 else 0\\r\\n if self.signe == other.signe and retenue[-1] != retenue[-2]:\\r\\n raise OverflowError(\\\"The sum is over the bytes available\\\")\\r\\n H = self.__class__(self.nbBytes)\\r\\n H.binaire = new_bin\\r\\n return H\",\n \"def __radd__(self, other):\\n return self + other\",\n \"def __radd__(self, other):\\n return self + other\",\n \"def su(o1, o2):\\n return o1+o2\",\n \"def add(n1, n2):\\n return n1 + n2\",\n \"def add(n1, n2):\\n return n1 + n2\",\n \"def addU(self,name):\\n return self._addVar(name,self._uNames)\",\n \"def __iadd__(self, other):\\n raise NotImplementedError(\\\"Implement this if needed\\\")\",\n \"def __iadd__(self, other: t.Any) -> te.Self:\\n return self._op_inplace('__iadd__', other)\",\n \"def add(self, value):\\n return self.number + value\",\n \"def __add__(self, value):\\n out = self.copy()\\n out.addMath(Query.Math.Add, value)\\n return out\",\n \"def add(self, params):\\n if len(params) < 2:\\n return\\n x = self.reg_dct[params[0]]\\n y = self.reg_dct[params[1]]\\n self.reg_dct[params[0]] = (x + y) % (2** 32)\",\n \"def __iadd__(self, term):\\n self.add(term)\\n return self\",\n \"def __add__(self, value):\\r\\n if isinstance(value, (int, dec.Decimal)):\\r\\n return self.__class__(self._real + value, self._imag)\\r\\n elif isinstance(value, self.__class__):\\r\\n return self.__class__(self._real + value._real, self._imag + value._imag)\\r\\n raise TypeError(\\r\\n 'unsupported operand type(s) for +: {!r} and {!r}'.format(\\r\\n self.__class__.__name__, value.__class__.__name__\\r\\n )\\r\\n )\",\n \"def _add_scalar(self, scalar):\\n\\n a, b = self, scalar\\n\\n # Don't bother to salt/obfuscate in a basic operation, do it\\n # just before leaving the computer.\\n encrypted_scalar = a.public_key.raw_encrypt(b, 1)\\n\\n sum_ciphertext = a._raw_add(a.ciphertext(False), encrypted_scalar)\\n return EncryptedNumber(a.public_key, sum_ciphertext)\",\n \"def acumula_n1(self, n1, rodada):\\n self.n1[rodada].append(n1)\",\n \"def __add__(self, other):\\n \\\"*** YOUR CODE HERE ***\\\"\",\n \"def __add__(self, other):\\n pass\",\n \"def __add__(self, other):\\n pass\",\n \"def __radd__(self, value):\\r\\n if isinstance(value, (int, dec.Decimal)):\\r\\n return self.__class__(value + self._real, self._imag)\\r\\n elif isinstance(value, self.__class__):\\r\\n return self.__class__(value._real + self._real, value._imag + self._imag)\\r\\n raise TypeError(\\r\\n 'unsupported operand type(s) for +: {!r} and {!r}'.format(\\r\\n value.__class__.__name__, self.__class__.__name__\\r\\n )\\r\\n )\",\n \"def plus(self, a, b):\\n return a + b\",\n \"def double_add(self, x):\\n self.add(x*2)\",\n \"def add(*args):\\n\\n result = int(args[0]) + int(args[1])\\n\\n return str(result)\",\n \"def __iadd__(self, other):\\n\\n if isinstance(other, float):\\n self.iadd_scalar(other)\\n else:\\n self.iadd(other)\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def add(a,b):\\n\\treturn a+b\",\n \"def __iadd__(self, m):\\n if self.__mm_type(m):\\n ls=len(self)\\n for i in self.desc():\\n for j in range(ls):\\n self.g_val(self.val(i,j)+m.val(i,j),i,j)\\n return self\",\n \"def addition():\\r\\n error_handler()\\r\\n f1.delete(0, END)\\r\\n a1 = float(operand.get())\\r\\n a2 = float(operator.get())\\r\\n result = a1 + a2\\r\\n f1.insert(10, str(result))\",\n \"def vector_add(v1, v2):\\n return v1[0] + v2[0], v1[1] + v2[1]\",\n \"def union_add(this, that):\\n return this.add(that, fill_value=0)\",\n \"def __add__(self, other):\\n return self.add(other)\",\n \"def __radd__(self, left):\\n return self.value() + left\",\n \"def add(self, x):\\n if type(x) is int:\\n self.real += x\\n else:\\n self.real = self.real + x.real\\n self.imag = self.imag + x.imag\",\n \"def add():\\n pass\",\n \"def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\\n return self\",\n \"def __add__(self, B):\\n return (Polynomial(self) + B).simplify()\",\n \"def add_reg_to_reg(self):\\n register = self.return_middle_registers(self.opcode)\\n sum = self.registers[register[0]] + self.registers[register[1]]\\n if sum > 0xFF:\\n self.registers[0xF] = 1\\n self.registers[register[0]] = sum & 0xFF\\n else:\\n self.registers[0xF] = 0\\n self.registers[register[0]] = sum\\n logger.info(\\\"Added V{} to V{} and got {}\\\".format(\\n register[0],\\n register[1],\\n self.registers[register[0]]))\",\n \"def __add__(self, other):\\n return add_mps(self, other)\",\n \"def __add__(self,l):\\r\\n\\t\\t\\r\\n\\t\\t# add\\r\\n\\t\\ta = self.add(l)\\r\\n\\t\\t\\r\\n\\t\\treturn a\",\n \"def _arithmetize1(self, operand: Any, op: str) -> Any:\\n op_func = getattr(operator, op)\\n # Data length might be changed after evaluation\\n # operand = recycle_value(operand, self.data.shape[0])\\n return op_func(operand)\",\n \"def add(*args):\\n\\n # TODO: Fill sum with the correct value, based on the\\n # args provided.\\n sum = str(args[0] + args[1])\\n return sum\",\n \"def AssignAddHybrid1d(output, value, target=utils.CCE):\\n for i in range(output.shape[0]):\\n output[i] = output[i] + value[i]\\n\\n return output\",\n \"def add(first, second):\\n return first + second\",\n \"def flexibase_add(str1, str2, base1, base2):\\n result = int_to_base(tmp, base1)\\n return result\",\n \"def __iadd__(self, increment):\\n self.update(self.val + increment)\\n return self\",\n \"def __add__(self, other):\\n raise NotImplementedError\",\n \"def __add__(self, other):\\n raise NotImplementedError\",\n \"def __add__(G, H):\\n if isinstance(H, Surreal):\\n return Surreal.from_value(G._n + H.n)\\n if isinstance(H, numbers.Number):\\n return Surreal.from_value(G._n + H)\\n if isinstance(H, Game):\\n return super().__add__(H)\\n\\n return NotImplemented\",\n \"def acumula_ns1(self, ns1, rodada):\\n self.ns1[rodada].append(ns1)\",\n \"def add(num1, num2, Cin):\\n Cin=0\\n l2=[]\\n final=\\\"\\\"\\n\\n \\\"\\\"\\\"Using for loop for starting addition from the last indexed number\\\"\\\"\\\"\\n for i in range(len(num1)-1,-1,-1):\\n bit1=num1[i]#storing each indexed() value of num1 in bit1\\n bit2=num2[i]#storing each indexed() value of num2 in bit2\\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\\n Cin=Cout#declaring cout as cin for next bit addition\\n l2.append(SUM)#adding SUM to l2\\n l3=l2[::-1]##reversing the value of l2\\n final+=str(l2[-1])#converting the list value to string\\n final1=final[::-1]#reversing string value\\n return final1 #returning the binary addition as string\",\n \"def add(self, addr):\\n\\n val = self.mem.read(addr)\\n result = self.alu.add(self.reg.accum, val)\\n self.reg.accum = result\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6728706","0.6107796","0.6091693","0.60768634","0.6043981","0.59999627","0.5992125","0.5928929","0.58962274","0.58847916","0.58111846","0.5790187","0.57823133","0.5729477","0.5695827","0.5693138","0.5691238","0.56896335","0.568388","0.5657158","0.5656396","0.56461686","0.56267214","0.5622425","0.55920094","0.55900943","0.55765325","0.55759287","0.5573485","0.5558525","0.5558445","0.5549629","0.55206823","0.55011827","0.549901","0.5487753","0.54810935","0.5461205","0.54601824","0.545574","0.5448604","0.54466313","0.5444445","0.5441933","0.54334533","0.54214287","0.5417938","0.54001117","0.5394166","0.53934914","0.5393115","0.5393115","0.539285","0.53921175","0.5377723","0.5377036","0.53723806","0.5369836","0.53697354","0.5367561","0.53672516","0.536613","0.5361434","0.5353281","0.5348965","0.53482217","0.5340855","0.5340855","0.5339779","0.53328115","0.5332705","0.53246516","0.5321864","0.53037965","0.53030366","0.52994186","0.5292875","0.529208","0.52901876","0.52883106","0.52854145","0.528397","0.5277533","0.52734447","0.526966","0.5266032","0.52645195","0.5255837","0.5253396","0.5252713","0.52507055","0.5246954","0.5246002","0.5241427","0.523946","0.523946","0.52378005","0.52320194","0.52318144","0.5227248"],"string":"[\n \"0.6728706\",\n \"0.6107796\",\n \"0.6091693\",\n \"0.60768634\",\n \"0.6043981\",\n \"0.59999627\",\n \"0.5992125\",\n \"0.5928929\",\n \"0.58962274\",\n \"0.58847916\",\n \"0.58111846\",\n \"0.5790187\",\n \"0.57823133\",\n \"0.5729477\",\n \"0.5695827\",\n \"0.5693138\",\n \"0.5691238\",\n \"0.56896335\",\n \"0.568388\",\n \"0.5657158\",\n \"0.5656396\",\n \"0.56461686\",\n \"0.56267214\",\n \"0.5622425\",\n \"0.55920094\",\n \"0.55900943\",\n \"0.55765325\",\n \"0.55759287\",\n \"0.5573485\",\n \"0.5558525\",\n \"0.5558445\",\n \"0.5549629\",\n \"0.55206823\",\n \"0.55011827\",\n \"0.549901\",\n \"0.5487753\",\n \"0.54810935\",\n \"0.5461205\",\n \"0.54601824\",\n \"0.545574\",\n \"0.5448604\",\n \"0.54466313\",\n \"0.5444445\",\n \"0.5441933\",\n \"0.54334533\",\n \"0.54214287\",\n \"0.5417938\",\n \"0.54001117\",\n \"0.5394166\",\n \"0.53934914\",\n \"0.5393115\",\n \"0.5393115\",\n \"0.539285\",\n \"0.53921175\",\n \"0.5377723\",\n \"0.5377036\",\n \"0.53723806\",\n \"0.5369836\",\n \"0.53697354\",\n \"0.5367561\",\n \"0.53672516\",\n \"0.536613\",\n \"0.5361434\",\n \"0.5353281\",\n \"0.5348965\",\n \"0.53482217\",\n \"0.5340855\",\n \"0.5340855\",\n \"0.5339779\",\n \"0.53328115\",\n \"0.5332705\",\n \"0.53246516\",\n \"0.5321864\",\n \"0.53037965\",\n \"0.53030366\",\n \"0.52994186\",\n \"0.5292875\",\n \"0.529208\",\n \"0.52901876\",\n \"0.52883106\",\n \"0.52854145\",\n \"0.528397\",\n \"0.5277533\",\n \"0.52734447\",\n \"0.526966\",\n \"0.5266032\",\n \"0.52645195\",\n \"0.5255837\",\n \"0.5253396\",\n \"0.5252713\",\n \"0.52507055\",\n \"0.5246954\",\n \"0.5246002\",\n \"0.5241427\",\n \"0.523946\",\n \"0.523946\",\n \"0.52378005\",\n \"0.52320194\",\n \"0.52318144\",\n \"0.5227248\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.62217534"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81740,"cells":{"query":{"kind":"string","value":"add U2 gate (by IBM)."},"document":{"kind":"string","value":"def u2(self, q0, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_U2, qid=[q0], phase=alpha, phase1=beta, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def server1_add2 (c1, c2, pub):\n #return (c1 + c2) % pub.n\n return e_add(pub, c1, c2)","def server2_add2 (b1, b2, pub):\n return (b1 + b2) % pub.n","def ADD (self, n1, n2):","def __add__(self, v2):\n\t\treturn Vect2D(self._vec+v2._vec)","def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\n return self","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def addMe2Me(x):\n return x+x","def server2_add1(b1, b2, pub):\n return (b1 + b2) % pub.n","def _add(self, node1, node2):\r\n\r\n self._graph[node1].add(node2)","def x2(self):\n return self._x + self._x2","def __add__(self, other):\n try:\n ox, oy = other\n except Exception:\n return NotImplemented\n return tuple.__new__(Vec2, (self[0] + ox, self[1] + oy))","def __add__(self,that):\n return self.__opExpand2(that,np.add)","def __add__(self, other):\n return Vec2d(self.v[0] + other[0], self.v[1] + other[1])","def addInPlace(self, value1, value2):\n raise NotImplementedError","def __iadd__(self, other):\n\n return self + other","def ts_add2 (c1,c2, pub):\n \n a = server1_add2(c1.alpha, c2.alpha, pub)\n b = server2_add2(c1.beta, c2.beta, pub)\n return CipherTwoServer(a,b)","def double_add(self, x):\n self.add(x*2)","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def I2_u2(self) -> complex:\n return self.I2_u1() * cmath.rect(1, -120 / 180 * cmath.pi)","def acumula_x2(self, x2, rodada):\n self.x2[rodada].append(x2)","def add(self, y):\n return circuit.add(self, y)","def __iadd__(self, other):\n raise NotImplementedError(\"Implement this if needed\")","def add(n1, n2):\n return n1 + n2","def __iadd__(self,that):\n #return self.__opExpand1(that,np.add, out=self)\n return self.__opExpand2(that,np.add, out=self)","def add(num1,num2):\n if(num2==0):\n return num1\n return add((num1^num2),(num1&num2)<<1)","def server1_add1(c1, c2, pub):\n return add1 (c1, c2, pub)","def add(n1, n2):\n return n1 + n2","def add(first, second):\n return first + second","def __radd__(self,that):\n return self.__opExpand2(that,np.add)","def augend_2(exp):\n a2 = cddr(exp) # (a2 a3 ...)\n rests = cdr(a2) # (a3 ... )\n if isNull(rests):\n return car(a2)\n else:\n restp = convertToPythonList(cdr(rests))\n return make_sum_2(car(a2), car(rests), *restp)","def __add__(self, other):\n return union(self, other, check_convex=True)","def acumula_ns2(self, ns2, rodada):\n self.ns2[rodada].append(ns2)","def add_2(number: float):\n return number + 2","def __add__(self, other):\r\n return self.add(other)","def acumula_n2(self, n2, rodada):\n self.n2[rodada].append(n2)","def add(self, a, b):\n return a + b","def __add__(self, tc): \n tc = TwosComplement(tc)\n bits = self.len if self.len > tc.len else tc.len \n result = self.int + tc.int\n return TwosComplement(result, bits)","def addition(self, polynomial2, slot1, slot2):\r\n\r\n self.terms(slot1)\r\n polynomial2.terms(slot2)\r\n\r\n for key in self.__terms:\r\n\r\n if key in polynomial2.__terms:\r\n coeff_1 = int(self.__terms[key])\r\n coeff_2 = int(polynomial2.__terms[key])\r\n sum_of_coeff = coeff_1 + coeff_2\r\n self.__terms[key] = sum_of_coeff\r\n\r\n for key in polynomial2.__terms:\r\n\r\n if key not in self.__terms:\r\n self.__terms[key] = polynomial2.__terms[key]\r\n\r\n print(\"The simplified result:\")\r\n print(\" + \".join(\"x^\".join((str(v), str(k))) for k, v in sorted(self.__terms.items(), reverse=True)))","def addend_in_2(s):\n return head_of_list(plus, s)","def add(a,b):\n\treturn a+b","def su(o1, o2):\n return o1+o2","def __add__(self, other):\n \"*** YOUR CODE HERE ***\"","def add64(a,b):\n return(np.add(a, b, dtype=np.uint64))","def enc_add(pub, m1, m2):\n add_result = m1 * m2 % pub.n_sq\n return add_result","def __add__(self, other):\n pass","def __add__(self, other):\n pass","def plus(self, a, b):\n return a + b","def vector_add(v1, v2):\n return v1[0] + v2[0], v1[1] + v2[1]","def __iadd__( self, vector3 ):\n return self.add( vector3 )","def addOp(self, op):\n self.operations << op","def add(a,b):\r\n return a+b","def addition(self, first_value, second_value):\n return first_value + second_value","def test_U2(self, tol):\n dev = qml.device(\"default.qubit\", wires=1)\n\n @qml.qnode(dev)\n def circuit(x, y):\n qml.QubitStateVector(1j * np.array([1, -1]) / np.sqrt(2), wires=[0])\n qml.U2(x, y, wires=[0])\n return qml.expval(qml.PauliX(0))\n\n phi = -0.234\n lam = 0.654\n\n res = circuit(phi, lam)\n expected = np.sin(lam) * np.sin(phi)\n assert np.allclose(res, expected, atol=tol, rtol=0)\n\n grad_fn = autograd.grad(circuit, argnum=[0, 1])\n res = grad_fn(phi, lam)\n expected = np.array([np.sin(lam) * np.cos(phi), np.cos(lam) * np.sin(phi)])\n assert np.allclose(res, expected, atol=tol, rtol=0)","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\n return self","def __add__(self, other):\n raise NotImplementedError","def __add__(self, other):\n raise NotImplementedError","def add( a, b ):\n return a + b","def __radd__(self, other):\n return self + other","def __radd__(self, other):\n return self + other","def add(num1, num2):\n return num1 + num2","def add(num1, num2):\n return num1 + num2","def add(num1, num2):\n return num1 + num2","def add(num1, num2):\n return num1 + num2","def add(num1, num2):\n return num1 + num2","def __radd__(self, other):\n return self.runtime.add(self, other)","def add(x, y):\n\n return x + y","def __iadd__(self,other):\n return Vector(self.x + other.x, self.y + other.y)\n pass","def _add(self, other):\n raise NotImplementedError(\n \"{} does not support addition\".format(type(self)))","def add(self, value):","def __add__(self, other):\n\n return self._binary_elementwise_op(other, np.add)","def add(num1, num2):\n return num1 + num2","def flexibase_add(str1, str2, base1, base2):\n result = int_to_base(tmp, base1)\n return result","def acumula_w2(self, w2, rodada):\n self.w2[rodada].append(w2)","def __add__(self, other: Any) -> ColumnOperators:\n return self.operate(add, other)","def build_gate_2(gate, tags=None):\n\n def apply_constant_two_qubit_gate(psi, i, j, **gate_opts):\n mtags = _merge_tags(tags, gate_opts)\n psi.gate_(gate, (int(i), int(j)), tags=mtags, **gate_opts)\n\n return apply_constant_two_qubit_gate","def test_add_consistency2(self) -> None:\n a = Constant(\n 'const1',\n Float32(),\n np.zeros([1, 3, 3])\n )\n b = Constant(\n 'const2',\n Float32(),\n np.zeros([2])\n )\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\n try:\n Add(\n 'add1',\n [1, 3, 3],\n Float32(),\n input_ops\n )\n except AssertionError:\n print(\"Consistency test for 'Add' #2 passed!\")\n\n else:\n self.assertTrue(False, \"Consistency test for 'Add' #2 failed.\")","def __add__(self, other):\n return add_mps(self, other)","def __add__(self, other):\n return self.add(other)","def __iadd__(self,l):\r\n\t\t\r\n\t\treturn self.add(l)","def __iadd__(self, other):\n self.x += other.x\n self.y += other.y\n return self","def owner2_add_funds(self, owner2_amount_in_msat: int):\n BLOCKCHAIN_INSTANCE.apply_transaction(self.channel_state.channel_data.owner2, owner2_amount_in_msat)\n self._state.channel_data.total_msat += (owner2_amount_in_msat * (1 - BLOCKCHAIN_INSTANCE.fee))\n self._compute_amount_owner2_can_transfer_to_owner1()","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\n return self","def ADD():\n global pointer, memory, registers\n registers[memory[pointer + 0x02]] += memory[pointer + 0x01]\n pointer += 0x03","def add(self, params):\n if len(params) < 2:\n return\n x = self.reg_dct[params[0]]\n y = self.reg_dct[params[1]]\n self.reg_dct[params[0]] = (x + y) % (2** 32)","async def uadd(self, *args: Input):\n # TODO(security) Allow for tuning nbytes\n return await self.sadd(secrets.token_hex(), *args)","def __add__(self, other):\n return Base40Pitch(self.base40 + other.base40)","def add(a, b):\n return a + b","def add(a, b):\n return a + b","def add(a, b):\n return a + b","def add(a, b):\n return a + b","def add(a, b):\n return a + b","def add(a, b):\n return a + b","def test_add_consistency1(self) -> None:\n a = Constant(\n 'const1',\n Float32(),\n np.zeros([1, 3, 3])\n )\n b = Constant(\n 'const2',\n Float32(),\n np.zeros([3])\n )\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\n Add(\n 'add1',\n [1, 3, 3],\n Float32(),\n input_ops\n )\n\n print(\"Consistency test for 'Add' #1 passed!\")","def addition(a, b):\n pass","def add(self,v2): \n n = len(self.a)\n m = len(v2.a)\n c = []\n if n != m:\n print(\"Incompatible Types\")\n return\n\n for i in range(n):\n c.append(self.a[i]+v2.a[i])\n\n return c","def add(x, y):\n return x + y","def add(x, y):\n return x + y","def add(x, y):\n return x + y","def add(x, y):\n return x + y"],"string":"[\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def server1_add2 (c1, c2, pub):\\n #return (c1 + c2) % pub.n\\n return e_add(pub, c1, c2)\",\n \"def server2_add2 (b1, b2, pub):\\n return (b1 + b2) % pub.n\",\n \"def ADD (self, n1, n2):\",\n \"def __add__(self, v2):\\n\\t\\treturn Vect2D(self._vec+v2._vec)\",\n \"def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\\n return self\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def addMe2Me(x):\\n return x+x\",\n \"def server2_add1(b1, b2, pub):\\n return (b1 + b2) % pub.n\",\n \"def _add(self, node1, node2):\\r\\n\\r\\n self._graph[node1].add(node2)\",\n \"def x2(self):\\n return self._x + self._x2\",\n \"def __add__(self, other):\\n try:\\n ox, oy = other\\n except Exception:\\n return NotImplemented\\n return tuple.__new__(Vec2, (self[0] + ox, self[1] + oy))\",\n \"def __add__(self,that):\\n return self.__opExpand2(that,np.add)\",\n \"def __add__(self, other):\\n return Vec2d(self.v[0] + other[0], self.v[1] + other[1])\",\n \"def addInPlace(self, value1, value2):\\n raise NotImplementedError\",\n \"def __iadd__(self, other):\\n\\n return self + other\",\n \"def ts_add2 (c1,c2, pub):\\n \\n a = server1_add2(c1.alpha, c2.alpha, pub)\\n b = server2_add2(c1.beta, c2.beta, pub)\\n return CipherTwoServer(a,b)\",\n \"def double_add(self, x):\\n self.add(x*2)\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def I2_u2(self) -> complex:\\n return self.I2_u1() * cmath.rect(1, -120 / 180 * cmath.pi)\",\n \"def acumula_x2(self, x2, rodada):\\n self.x2[rodada].append(x2)\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def __iadd__(self, other):\\n raise NotImplementedError(\\\"Implement this if needed\\\")\",\n \"def add(n1, n2):\\n return n1 + n2\",\n \"def __iadd__(self,that):\\n #return self.__opExpand1(that,np.add, out=self)\\n return self.__opExpand2(that,np.add, out=self)\",\n \"def add(num1,num2):\\n if(num2==0):\\n return num1\\n return add((num1^num2),(num1&num2)<<1)\",\n \"def server1_add1(c1, c2, pub):\\n return add1 (c1, c2, pub)\",\n \"def add(n1, n2):\\n return n1 + n2\",\n \"def add(first, second):\\n return first + second\",\n \"def __radd__(self,that):\\n return self.__opExpand2(that,np.add)\",\n \"def augend_2(exp):\\n a2 = cddr(exp) # (a2 a3 ...)\\n rests = cdr(a2) # (a3 ... )\\n if isNull(rests):\\n return car(a2)\\n else:\\n restp = convertToPythonList(cdr(rests))\\n return make_sum_2(car(a2), car(rests), *restp)\",\n \"def __add__(self, other):\\n return union(self, other, check_convex=True)\",\n \"def acumula_ns2(self, ns2, rodada):\\n self.ns2[rodada].append(ns2)\",\n \"def add_2(number: float):\\n return number + 2\",\n \"def __add__(self, other):\\r\\n return self.add(other)\",\n \"def acumula_n2(self, n2, rodada):\\n self.n2[rodada].append(n2)\",\n \"def add(self, a, b):\\n return a + b\",\n \"def __add__(self, tc): \\n tc = TwosComplement(tc)\\n bits = self.len if self.len > tc.len else tc.len \\n result = self.int + tc.int\\n return TwosComplement(result, bits)\",\n \"def addition(self, polynomial2, slot1, slot2):\\r\\n\\r\\n self.terms(slot1)\\r\\n polynomial2.terms(slot2)\\r\\n\\r\\n for key in self.__terms:\\r\\n\\r\\n if key in polynomial2.__terms:\\r\\n coeff_1 = int(self.__terms[key])\\r\\n coeff_2 = int(polynomial2.__terms[key])\\r\\n sum_of_coeff = coeff_1 + coeff_2\\r\\n self.__terms[key] = sum_of_coeff\\r\\n\\r\\n for key in polynomial2.__terms:\\r\\n\\r\\n if key not in self.__terms:\\r\\n self.__terms[key] = polynomial2.__terms[key]\\r\\n\\r\\n print(\\\"The simplified result:\\\")\\r\\n print(\\\" + \\\".join(\\\"x^\\\".join((str(v), str(k))) for k, v in sorted(self.__terms.items(), reverse=True)))\",\n \"def addend_in_2(s):\\n return head_of_list(plus, s)\",\n \"def add(a,b):\\n\\treturn a+b\",\n \"def su(o1, o2):\\n return o1+o2\",\n \"def __add__(self, other):\\n \\\"*** YOUR CODE HERE ***\\\"\",\n \"def add64(a,b):\\n return(np.add(a, b, dtype=np.uint64))\",\n \"def enc_add(pub, m1, m2):\\n add_result = m1 * m2 % pub.n_sq\\n return add_result\",\n \"def __add__(self, other):\\n pass\",\n \"def __add__(self, other):\\n pass\",\n \"def plus(self, a, b):\\n return a + b\",\n \"def vector_add(v1, v2):\\n return v1[0] + v2[0], v1[1] + v2[1]\",\n \"def __iadd__( self, vector3 ):\\n return self.add( vector3 )\",\n \"def addOp(self, op):\\n self.operations << op\",\n \"def add(a,b):\\r\\n return a+b\",\n \"def addition(self, first_value, second_value):\\n return first_value + second_value\",\n \"def test_U2(self, tol):\\n dev = qml.device(\\\"default.qubit\\\", wires=1)\\n\\n @qml.qnode(dev)\\n def circuit(x, y):\\n qml.QubitStateVector(1j * np.array([1, -1]) / np.sqrt(2), wires=[0])\\n qml.U2(x, y, wires=[0])\\n return qml.expval(qml.PauliX(0))\\n\\n phi = -0.234\\n lam = 0.654\\n\\n res = circuit(phi, lam)\\n expected = np.sin(lam) * np.sin(phi)\\n assert np.allclose(res, expected, atol=tol, rtol=0)\\n\\n grad_fn = autograd.grad(circuit, argnum=[0, 1])\\n res = grad_fn(phi, lam)\\n expected = np.array([np.sin(lam) * np.cos(phi), np.cos(lam) * np.sin(phi)])\\n assert np.allclose(res, expected, atol=tol, rtol=0)\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\\n return self\",\n \"def __add__(self, other):\\n raise NotImplementedError\",\n \"def __add__(self, other):\\n raise NotImplementedError\",\n \"def add( a, b ):\\n return a + b\",\n \"def __radd__(self, other):\\n return self + other\",\n \"def __radd__(self, other):\\n return self + other\",\n \"def add(num1, num2):\\n return num1 + num2\",\n \"def add(num1, num2):\\n return num1 + num2\",\n \"def add(num1, num2):\\n return num1 + num2\",\n \"def add(num1, num2):\\n return num1 + num2\",\n \"def add(num1, num2):\\n return num1 + num2\",\n \"def __radd__(self, other):\\n return self.runtime.add(self, other)\",\n \"def add(x, y):\\n\\n return x + y\",\n \"def __iadd__(self,other):\\n return Vector(self.x + other.x, self.y + other.y)\\n pass\",\n \"def _add(self, other):\\n raise NotImplementedError(\\n \\\"{} does not support addition\\\".format(type(self)))\",\n \"def add(self, value):\",\n \"def __add__(self, other):\\n\\n return self._binary_elementwise_op(other, np.add)\",\n \"def add(num1, num2):\\n return num1 + num2\",\n \"def flexibase_add(str1, str2, base1, base2):\\n result = int_to_base(tmp, base1)\\n return result\",\n \"def acumula_w2(self, w2, rodada):\\n self.w2[rodada].append(w2)\",\n \"def __add__(self, other: Any) -> ColumnOperators:\\n return self.operate(add, other)\",\n \"def build_gate_2(gate, tags=None):\\n\\n def apply_constant_two_qubit_gate(psi, i, j, **gate_opts):\\n mtags = _merge_tags(tags, gate_opts)\\n psi.gate_(gate, (int(i), int(j)), tags=mtags, **gate_opts)\\n\\n return apply_constant_two_qubit_gate\",\n \"def test_add_consistency2(self) -> None:\\n a = Constant(\\n 'const1',\\n Float32(),\\n np.zeros([1, 3, 3])\\n )\\n b = Constant(\\n 'const2',\\n Float32(),\\n np.zeros([2])\\n )\\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\\n try:\\n Add(\\n 'add1',\\n [1, 3, 3],\\n Float32(),\\n input_ops\\n )\\n except AssertionError:\\n print(\\\"Consistency test for 'Add' #2 passed!\\\")\\n\\n else:\\n self.assertTrue(False, \\\"Consistency test for 'Add' #2 failed.\\\")\",\n \"def __add__(self, other):\\n return add_mps(self, other)\",\n \"def __add__(self, other):\\n return self.add(other)\",\n \"def __iadd__(self,l):\\r\\n\\t\\t\\r\\n\\t\\treturn self.add(l)\",\n \"def __iadd__(self, other):\\n self.x += other.x\\n self.y += other.y\\n return self\",\n \"def owner2_add_funds(self, owner2_amount_in_msat: int):\\n BLOCKCHAIN_INSTANCE.apply_transaction(self.channel_state.channel_data.owner2, owner2_amount_in_msat)\\n self._state.channel_data.total_msat += (owner2_amount_in_msat * (1 - BLOCKCHAIN_INSTANCE.fee))\\n self._compute_amount_owner2_can_transfer_to_owner1()\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\\n return self\",\n \"def ADD():\\n global pointer, memory, registers\\n registers[memory[pointer + 0x02]] += memory[pointer + 0x01]\\n pointer += 0x03\",\n \"def add(self, params):\\n if len(params) < 2:\\n return\\n x = self.reg_dct[params[0]]\\n y = self.reg_dct[params[1]]\\n self.reg_dct[params[0]] = (x + y) % (2** 32)\",\n \"async def uadd(self, *args: Input):\\n # TODO(security) Allow for tuning nbytes\\n return await self.sadd(secrets.token_hex(), *args)\",\n \"def __add__(self, other):\\n return Base40Pitch(self.base40 + other.base40)\",\n \"def add(a, b):\\n return a + b\",\n \"def add(a, b):\\n return a + b\",\n \"def add(a, b):\\n return a + b\",\n \"def add(a, b):\\n return a + b\",\n \"def add(a, b):\\n return a + b\",\n \"def add(a, b):\\n return a + b\",\n \"def test_add_consistency1(self) -> None:\\n a = Constant(\\n 'const1',\\n Float32(),\\n np.zeros([1, 3, 3])\\n )\\n b = Constant(\\n 'const2',\\n Float32(),\\n np.zeros([3])\\n )\\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\\n Add(\\n 'add1',\\n [1, 3, 3],\\n Float32(),\\n input_ops\\n )\\n\\n print(\\\"Consistency test for 'Add' #1 passed!\\\")\",\n \"def addition(a, b):\\n pass\",\n \"def add(self,v2): \\n n = len(self.a)\\n m = len(v2.a)\\n c = []\\n if n != m:\\n print(\\\"Incompatible Types\\\")\\n return\\n\\n for i in range(n):\\n c.append(self.a[i]+v2.a[i])\\n\\n return c\",\n \"def add(x, y):\\n return x + y\",\n \"def add(x, y):\\n return x + y\",\n \"def add(x, y):\\n return x + y\",\n \"def add(x, y):\\n return x + y\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67444396","0.6484918","0.63779294","0.6370151","0.6348903","0.6310671","0.62745816","0.6087733","0.599484","0.5910055","0.5909812","0.58794576","0.5842368","0.58024174","0.58003265","0.5782124","0.5781626","0.5779789","0.57524997","0.5730032","0.57221794","0.5696927","0.56881535","0.56876713","0.5684858","0.56706107","0.566377","0.56616145","0.5657161","0.56445575","0.56443244","0.5634239","0.5632628","0.5629835","0.56203014","0.5615664","0.561067","0.5601435","0.55994797","0.5595824","0.559485","0.55801487","0.5576442","0.5567748","0.55620015","0.55593","0.55593","0.5557662","0.5556015","0.55407566","0.5526896","0.55186504","0.5518272","0.5509249","0.5507382","0.5505277","0.5505277","0.549936","0.54989505","0.54989505","0.548799","0.548799","0.548799","0.548799","0.548799","0.5485598","0.5484786","0.54827994","0.5476848","0.54744786","0.5473755","0.54735124","0.54644865","0.5463053","0.5462503","0.5459535","0.54571563","0.54534006","0.54521966","0.5446528","0.54441005","0.5443051","0.54400027","0.543005","0.5428048","0.54254514","0.54039806","0.5399712","0.5399712","0.5399712","0.5399712","0.5399712","0.5399712","0.5386234","0.53861046","0.5382554","0.5377602","0.5377602","0.5377602","0.5377602"],"string":"[\n \"0.67444396\",\n \"0.6484918\",\n \"0.63779294\",\n \"0.6370151\",\n \"0.6348903\",\n \"0.6310671\",\n \"0.62745816\",\n \"0.6087733\",\n \"0.599484\",\n \"0.5910055\",\n \"0.5909812\",\n \"0.58794576\",\n \"0.5842368\",\n \"0.58024174\",\n \"0.58003265\",\n \"0.5782124\",\n \"0.5781626\",\n \"0.5779789\",\n \"0.57524997\",\n \"0.5730032\",\n \"0.57221794\",\n \"0.5696927\",\n \"0.56881535\",\n \"0.56876713\",\n \"0.5684858\",\n \"0.56706107\",\n \"0.566377\",\n \"0.56616145\",\n \"0.5657161\",\n \"0.56445575\",\n \"0.56443244\",\n \"0.5634239\",\n \"0.5632628\",\n \"0.5629835\",\n \"0.56203014\",\n \"0.5615664\",\n \"0.561067\",\n \"0.5601435\",\n \"0.55994797\",\n \"0.5595824\",\n \"0.559485\",\n \"0.55801487\",\n \"0.5576442\",\n \"0.5567748\",\n \"0.55620015\",\n \"0.55593\",\n \"0.55593\",\n \"0.5557662\",\n \"0.5556015\",\n \"0.55407566\",\n \"0.5526896\",\n \"0.55186504\",\n \"0.5518272\",\n \"0.5509249\",\n \"0.5507382\",\n \"0.5505277\",\n \"0.5505277\",\n \"0.549936\",\n \"0.54989505\",\n \"0.54989505\",\n \"0.548799\",\n \"0.548799\",\n \"0.548799\",\n \"0.548799\",\n \"0.548799\",\n \"0.5485598\",\n \"0.5484786\",\n \"0.54827994\",\n \"0.5476848\",\n \"0.54744786\",\n \"0.5473755\",\n \"0.54735124\",\n \"0.54644865\",\n \"0.5463053\",\n \"0.5462503\",\n \"0.5459535\",\n \"0.54571563\",\n \"0.54534006\",\n \"0.54521966\",\n \"0.5446528\",\n \"0.54441005\",\n \"0.5443051\",\n \"0.54400027\",\n \"0.543005\",\n \"0.5428048\",\n \"0.54254514\",\n \"0.54039806\",\n \"0.5399712\",\n \"0.5399712\",\n \"0.5399712\",\n \"0.5399712\",\n \"0.5399712\",\n \"0.5399712\",\n \"0.5386234\",\n \"0.53861046\",\n \"0.5382554\",\n \"0.5377602\",\n \"0.5377602\",\n \"0.5377602\",\n \"0.5377602\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6176404"},"document_rank":{"kind":"string","value":"7"}}},{"rowIdx":81741,"cells":{"query":{"kind":"string","value":"add U3 gate (by IBM)."},"document":{"kind":"string","value":"def u3(self, q0, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_U3, qid=[q0], phase=alpha, phase1=beta,\n phase2=gamma, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def __iadd__( self, vector3 ):\n return self.add( vector3 )","def cu3(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U3, qid=[q0,q1], phase=alpha, phase1=beta,\n phase2=gamma, ctrl=ctrl)\n return self","def S3_u32(self) -> complex:\n return complex(\n self._addr(self.defined_registers['Phase 3 power [W]']['addr']),\n self._addr(self.defined_registers['Phase 3 volt amps reactive [VAr]']['addr']),\n )","def add_three(a, b, c):\n return a + b + c","def _r_u3(angle: tf.Tensor) -> tf.Tensor:\n zero = tf.constant(0, dtype=tf.float64)\n cos = tf.cos(tf.multiply(angle[0], tf.constant(0.5, dtype=tf.float64)))\n sin = tf.sin(tf.multiply(angle[0], tf.constant(0.5, dtype=tf.float64)))\n sin_complex = tf.complex(sin, zero)\n cos_complex = tf.complex(cos, zero)\n exponent_phi = tf.complex(zero, angle[1])\n exp_phi = tf.exp(exponent_phi)\n exponent_lambda = tf.complex(zero, angle[2])\n exp_lambda = tf.exp(exponent_lambda)\n exponent_lambda_phi = tf.complex(zero, angle[1] + angle[2])\n exp_lambda_phi = tf.exp(exponent_lambda_phi)\n ru3 = tf.stack([[cos_complex, -tf.multiply(exp_lambda, sin_complex)],\n [tf.multiply(exp_phi, sin_complex), tf.multiply(exp_lambda_phi, cos_complex)]])\n\n return ru3","def add( self, vector3 ):\n self._coords[:3] += vector3._coords[:3]\n return self","def x3(self):\n return self._x + self._x3","def add_mult(num1, num2, num3):\n \n addmult = (num1 + num2) * num3\n return addmult","def I3_u32(self) -> complex:\n return (self.S3_u32() / self.U23()).conjugate()","def test_special_U3(self):\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \"U3\", {})\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \"U3\", {\"u3\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.2, 0.0).to_matrix(), \"U3\", {\"u3\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.0, 0.2).to_matrix(), \"U3\", {\"u3\": 1})\n self.check_oneq_special_cases(U3Gate(0.11, 0.27, 0.3).to_matrix(), \"U3\", {\"u3\": 1})","def test_U3(self, tol):\n dev = qml.device(\"default.qubit\", wires=1)\n\n @qml.qnode(dev)\n def circuit(x, y, z):\n qml.QubitStateVector(1j * np.array([1, -1]) / np.sqrt(2), wires=[0])\n qml.U3(x, y, z, wires=[0])\n return qml.expval(qml.PauliX(0))\n\n theta = 0.543\n phi = -0.234\n lam = 0.654\n\n res = circuit(theta, phi, lam)\n expected = np.sin(lam) * np.sin(phi) - np.cos(theta) * np.cos(lam) * np.cos(phi)\n assert np.allclose(res, expected, atol=tol, rtol=0)\n\n grad_fn = autograd.grad(circuit, argnum=[0, 1, 2])\n res = grad_fn(theta, phi, lam)\n expected = np.array(\n [\n np.sin(theta) * np.cos(lam) * np.cos(phi),\n np.cos(theta) * np.cos(lam) * np.sin(phi) + np.sin(lam) * np.cos(phi),\n np.cos(theta) * np.sin(lam) * np.cos(phi) + np.cos(lam) * np.sin(phi),\n ]\n )\n assert np.allclose(res, expected, atol=tol, rtol=0)","def I3_u3(self) -> complex:\n return self.I3_u1() * cmath.rect(1, 120 / 180 * cmath.pi)","def add_three(v1, v2, v3):\n p = v1 + v2 + v3\n print(\"The sum of the three numbers is: {}\".format(p))\n return p","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def L3G_acquisition(add):\n\n # control register\n CTRL_REG1 = 0x20\n CTRL_REG4 = 0x23\n LOW_ODR = 0x39\n FIFO_CTRL = 0x2e\n # output register\n OUT_X_L = 0x28\n OUT_X_H = 0x29\n OUT_Y_L = 0x2a\n OUT_Y_H = 0x2b\n OUT_Z_L = 0x2c\n OUT_Z_H = 0x2d\n\n # low odr mode, 50Hz, 2000 dps full scale\n bus.write_byte_data(add, CTRL_REG1, 0b10001111)\n bus.write_byte_data(add, CTRL_REG4, 0b00110000)\n bus.write_byte_data(add, LOW_ODR, 0b00000001)\n bus.write_byte_data(add, FIFO_CTRL, 0b01000000)\n\n # accelerator accumulate\n while True:\n uint16_gx = (bus.read_byte_data(add, OUT_X_H) << 8) + \\\n bus.read_byte_data(add, OUT_X_L)\n uint16_gy = (bus.read_byte_data(add, OUT_Y_H) << 8) + \\\n bus.read_byte_data(add, OUT_Y_L)\n uint16_gz = (bus.read_byte_data(add, OUT_Z_H) << 8) + \\\n bus.read_byte_data(add, OUT_Z_L)\n\n gx = twos_comp(uint16_gx, 16)\n gy = twos_comp(uint16_gy, 16)\n gz = twos_comp(uint16_gz, 16)\n\n yield [gx, gy, gz]","def ADD():\n global pointer, memory, registers\n registers[memory[pointer + 0x02]] += memory[pointer + 0x01]\n pointer += 0x03","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def I3_u1(self) -> complex:\n # Should match in amplitude with \"Phase 3 current [A]\"\n # Convert from relative to U32 -> relative to U1\n return - (self.I3_u32() * cmath.rect(1, 90 / 180 * cmath.pi))","def add_operation(self):\n arg1 = self.memory[self.memory[self._cursor + 1]]\n arg2 = self.memory[self.memory[self._cursor + 2]]\n arg3 = self.memory[self._cursor + 3]\n self.memory[arg3] = arg1 + arg2\n # print(f'Cursor: {self._cursor}\\tAssigning position {position} with value {n1 + n2}')\n self._cursor += 4\n return","def luk_plus_five(unit: ActiveUnit) -> None:\n unit.mod_luk += 5","def itkScalarConnectedComponentImageFilterIUL3IUL3_cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUL3IUL3_cast(*args)","def heisen3_sum(v1: Vec3, v2: Vec3) -> Vec3:\n assert v1.shape == v2.shape and v1.shape == (3,)\n # first, do normal sum to get (x + x', y + y', z + z')\n out = v1 + v2\n # then add the xy' part to z + z'\n out[2] += v1[0] * v2[1]\n return out","def ADD (self, n1, n2):","def _action_op_u1(self, plaq):\n # if self.link_type == 'U1':\n # return np.cos(plaq)\n return tf.math.cos(plaq)","def add_vectors(v, u):\n return (v[0] + u[0], v[1] + u[1])","def test_special_U(self):\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \"U\", {})\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \"U\", {\"u\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.2, 0.0).to_matrix(), \"U\", {\"u\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.0, 0.2).to_matrix(), \"U\", {\"u\": 1})\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \"U\", {\"u\": 1})","def getU3(state):\n\n # TODO : do the verifictions of the above constraints\n\n theta=2*math.acos(state[0])\n phi=0\n lam=0\n\n if state[1]<0: theta = -theta\n\n # U3=np.array([\n # [math.cos(theta/2) , np.exp(-1j*lam)*math.sin(theta/2)], \n # [np.exp(1j*phi)*math.sin(theta/2), np.exp(1j*(phi+lam))*math.cos(theta/2)]\n # ])\n # print (U3)\n # print (U3@np.array([[1],[0]]))\n\n return [theta, phi, lam]","def refugia_adj_3(params, ns):\n #11 parameters \n nu1, nuA, nu2, nu3, m1_1, m2_1, m2_2, m2_3, T1a, T1b, T2 = params\n sts = moments.LinearSystem_1D.steady_state_1D(ns[0] + ns[1] + ns[2])\n fs = moments.Spectrum(sts)\n fs = moments.Manips.split_1D_to_2D(fs, ns[0], ns[1] + ns[2])\n ## Population function and migration matrix for T1a\n nu_T1 = [nu1, nuA]\n fs.integrate(nu_T1, T1a)\n ## Population function and migration matrix for T1b\n mig1 = numpy.array([[0, m1_1],[m1_1, 0]])\n fs.integrate(nu_T1, T1b, m=mig1) \n fs = moments.Manips.split_2D_to_3D_2(fs, ns[1], ns[2])\n ## Population function and migration matrix for T2\n nu_T2 = [nu1, nu2, nu3]\n mig2 = numpy.array([[0, m2_1, m2_3],[m2_1, 0, m2_2], [m2_3, m2_2, 0]]) \n fs.integrate(nu_T2, T2, m=mig2)\n return fs","def new(self, u, k1, k2, k3, k4):\n\n v = self.combine(k1, k2, k3, k4)\n\n return u + (self._delta_t / 6.0) * v","def __iadd__(self,l):\r\n\t\t\r\n\t\treturn self.add(l)","def loss_step3(self, y, u, v):\n uv = -0.5 * (y.float().t() @ (u + v))\n return uv","def test_add_consistency1(self) -> None:\n a = Constant(\n 'const1',\n Float32(),\n np.zeros([1, 3, 3])\n )\n b = Constant(\n 'const2',\n Float32(),\n np.zeros([3])\n )\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\n Add(\n 'add1',\n [1, 3, 3],\n Float32(),\n input_ops\n )\n\n print(\"Consistency test for 'Add' #1 passed!\")","def add_n():\n pass","def AssignAddHybrid3d(output, value, target=utils.CCE):\n for i in range(output.shape[0]):\n for j in range(output.shape[1]):\n for k in range(output.shape[2]):\n output[i, j, k] = output[i, j, k] + value[i, j, k]\n\n return output","def add_reg_to_reg(self):\n register = self.return_middle_registers(self.opcode)\n sum = self.registers[register[0]] + self.registers[register[1]]\n if sum > 0xFF:\n self.registers[0xF] = 1\n self.registers[register[0]] = sum & 0xFF\n else:\n self.registers[0xF] = 0\n self.registers[register[0]] = sum\n logger.info(\"Added V{} to V{} and got {}\".format(\n register[0],\n register[1],\n self.registers[register[0]]))","def __iadd__(self, other):\r\n if isinstance(other, vec4):\r\n self.x+=other.x\r\n self.y+=other.y\r\n self.z+=other.z\r\n self.w+=other.w\r\n return self\r\n else:\r\n raise TypeError, \"unsupported operand type for +=\"","def __iadd__(self, tensor):\n return self.add_(tensor)","def __add__(self, v):\n return vector(self.x + v.x, self.y + v.y, self.z + v.z)","def test_add_with_int_arg(self):\n\n from pedemath.vec3 import add_v3\n\n a = Vec3(2, 3, 4)\n b = 5\n\n result = add_v3(a, b)\n\n expected_result = Vec3(7, 8, 9)\n\n self.assertEqual(result, expected_result)","def __iadd__(self,that):\n #return self.__opExpand1(that,np.add, out=self)\n return self.__opExpand2(that,np.add, out=self)","def chain_3(d3f_dg3, dg_dx, d2f_dg2, d2g_dx2, df_dg, d3g_dx3):\r\n return d3f_dg3*(dg_dx**3) + 3*d2f_dg2*dg_dx*d2g_dx2 + df_dg*d3g_dx3","def test_add(vec3_fixture):\n scalar = vec3_fixture + 1\n assert scalar.x1 == vec3_fixture.x1 + 1\n assert scalar.x2 == vec3_fixture.x2 + 1\n assert scalar.x3 == vec3_fixture.x3 + 1\n\n vector = vec3_fixture + Vec3([2, 3, 4])\n assert vector.x1 == vec3_fixture.x1 + 2\n assert vector.x2 == vec3_fixture.x2 + 3\n assert vector.x3 == vec3_fixture.x3 + 4","def __add__(self, tc): \n tc = TwosComplement(tc)\n bits = self.len if self.len > tc.len else tc.len \n result = self.int + tc.int\n return TwosComplement(result, bits)","def sum_u(self):\r\n try:\r\n # add the velocity to the sum\r\n self.usum.vector()[:] += self.u.vector()[:]\r\n except AttributeError:\r\n # initialize the sum\r\n self.usum = self.u.copy(deepcopy=True)","def add(self, params):\n if len(params) < 2:\n return\n x = self.reg_dct[params[0]]\n y = self.reg_dct[params[1]]\n self.reg_dct[params[0]] = (x + y) % (2** 32)","def __add__(self,that):\n return self.__opExpand2(that,np.add)","async def uadd(self, *args: Input):\n # TODO(security) Allow for tuning nbytes\n return await self.sadd(secrets.token_hex(), *args)","def add_operation(self):\n n1 = self.memory[self.memory[self._cursor + 1]]\n n2 = self.memory[self.memory[self._cursor + 2]]\n position = self.memory[self._cursor + 3]\n self.memory[position] = n1 + n2\n # print(f'Cursor: {self._cursor}\\tAssigning position {position} with value {n1} + {n2} = {n1 + n2}')\n return","def union_add(this, that):\n return this.add(that, fill_value=0)","def auxiliar_exercise1(self, param1, param2, param3):\n result = param1 ** 2 + param2 ** 2 + param3 ** 2\n return","def __add__(self, rhs):\n if isinstance(rhs, UTPS):\n return UTPS(self.tc + rhs.tc)\n elif numpy.isscalar(rhs):\n retval = UTPS(numpy.copy(self.tc))\n retval.tc[0] += rhs\n return retval\n else:\n raise NotImplementedError","def k3(self, f, t, u, k2, usereverse=False):\n\n h = self._delta_t / 2.0\n\n v = u + h * k2\n tt = t + h\n\n if usereverse:\n output, storagez, storagew = f(tt, v)\n\n self.storagez.append(storagez)\n self.storagew.append(storagew)\n\n return output\n else:\n return f(tt, v)","def __radd__(self,that):\n return self.__opExpand2(that,np.add)","def addU(self,name):\n return self._addVar(name,self._uNames)","def addOp(self, op):\n self.operations << op","def test_add3(self):\n self.assertEqual(-5, add(-10 , 5), \"should be -5\")","def itkScalarConnectedComponentImageFilterIUC3IUC3_cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUC3IUC3_cast(*args)","def enc_add_const(pub, m, c):\n # Similiar to enc add\n add_const_result = m * powmod(pub.g, c, pub.n_sq) % pub.n_sq\n return add_const_result","def server1_add2 (c1, c2, pub):\n #return (c1 + c2) % pub.n\n return e_add(pub, c1, c2)","def _add_op(value, sample_args, rationals_allowed):\n entropy, sample_args = sample_args.peel()\n if rationals_allowed and sample_args.count >= 3:\n x = number.integer_or_rational(entropy, True)\n else:\n x = number.integer(entropy, True)\n if random.choice([False, True]):\n op_args = [x, value - x]\n else:\n op_args = [value - x, x]\n return ops.Add, op_args, sample_args","def convert_gcm3_AMUA3(den_gmc3):\n return den_gmc3*const_avo/10.0","def test_addmod(self):\n from manticore.platforms import evm\n from manticore.core.smtlib import ConstraintSet, Z3Solver, Operators\n\n constraints = ConstraintSet()\n\n address = 0x41414141414141414141\n data = b\"\"\n caller = 0x42424242424242424242\n value = 0\n bytecode = \"\"\n vm = evm.EVM(constraints, address, data, caller, value, bytecode, gas=23000)\n\n self.assertEqual(vm.ADDMOD(12323, 2343, 20), 6)\n self.assertEqual(vm.ADDMOD(12323, 2343, 0), 0)\n\n A, B, C = (\n 0x780000002090309A004201626B1400041D318000000200008A0080089C042DA7,\n 0xF000000740403F7007C012807BED003BE2CE800000060000FFFFBFF7E4087033,\n 0x338000080FFFFF64AAAACFFCF7DBFA408000000000000270120000001E7C2ACF,\n )\n self.assertEqual(\n vm.ADDMOD(A, B, C),\n 23067954172474524581131069693479689311231082562138745684554374357070230297856,\n )\n a, b, c = (\n constraints.new_bitvec(256),\n constraints.new_bitvec(256),\n constraints.new_bitvec(256),\n )\n constraints.add(a == A)\n constraints.add(b == B)\n constraints.add(c == C)\n result = vm.ADDMOD(a, b, c)\n # 0x32ffffd700d073ae080133f517d922bd000000000007f1611e003fffc9239d00\n self.assertEqual(\n Z3Solver.instance().get_all_values(constraints, result),\n [0x32FFFFD700D073AE080133F517D922BD000000000007F1611E003FFFC9239D00],\n )","def gen_op3(N11, N22, N12, rN11, rN22, rN12):\n raw = N12 / (N11 * N22)\n ref = rN12 / (rN11 * rN22)\n print(\"=====\\n3rd method: raw = N12 / (N11 * N22)\")\n print(\"raw: %.2f | reference: %.2f\" % (raw, ref))\n print(\"OP: 1 - raw = %.3f\\n=====\" % (1 - raw))","def step3(self):\n\t\tif self.b[self.k] == 'e':\n\t\t\tif self.ends(\"icate\"):\t self.r(\"ic\")\n\t\t\telif self.ends(\"ative\"): self.r(\"\")\n\t\t\telif self.ends(\"alize\"): self.r(\"al\")\n\t\telif self.b[self.k] == 'i':\n\t\t\tif self.ends(\"iciti\"):\t self.r(\"ic\")\n\t\telif self.b[self.k] == 'l':\n\t\t\tif self.ends(\"ical\"):\t self.r(\"ic\")\n\t\t\telif self.ends(\"ful\"):\t self.r(\"\")\n\t\telif self.b[self.k] == 's':\n\t\t\tif self.ends(\"ness\"):\t self.r(\"\")","def itkScalarConnectedComponentImageFilterIUS3IUS3_cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUS3IUS3_cast(*args)","def AddOperation(self, op):\n self._operations.append(op)","def test_add():\n z = Complex(1, -2)\n w = Complex(1, 1)\n assert (z + w) == Complex(2, -1)\n assert (z + (1+1j)) == Complex(2, -1)\n assert (z + 2) == Complex(3, -2)\n assert (z + 2.0) == Complex(3, -2)","def r_3(comps: 'list(Compound)', is_input):\r\n react: str\r\n\r\n if is_input:\r\n iSiMe = Compound(\"Zn\")\r\n if len(comps) == 1:\r\n if \"iSi\" in comps[0].comp_type:\r\n iSiMe = comps[0]\r\n else:\r\n if \"iSi\" in comps[0].comp_type:\r\n iSiMe = comps[0]\r\n else:\r\n iSiMe = comps[1]\r\n\r\n me = list(iSiMe.formula.consist.keys())[0].name\r\n if me in [\"Au\", \"Pt\"]:\r\n return \"\"\r\n me_oxs = get_me_oxs(me)\r\n if me_oxs == 0:\r\n return \"\"\r\n if is_me_activer(\"H\", 1, me, me_oxs):\r\n return \"\"\r\n\r\n iSaNo = Compound(iSaNo_create(me, me_oxs, \"NO3\", 1))\r\n\r\n react = f\"{iSiMe} + HNO3 -> {iSaNo} + N2O + H2O\"\r\n else:\r\n iSaNo = Compound(\"Zn(NO3)2\")\r\n if len(comps) == 1:\r\n if \"iSaNo\" in comps[0].comp_type:\r\n iSaNo = comps[0]\r\n elif len(comps) == 2:\r\n if \"iSaNo\" in comps[0].comp_type:\r\n iSaNo = comps[0]\r\n elif \"iSaNo\" in comps[1].comp_type:\r\n iSaNo = comps[1]\r\n else:\r\n if \"iSaNo\" in comps[0].comp_type:\r\n iSaNo = comps[0]\r\n elif \"iSaNo\" in comps[1].comp_type:\r\n iSaNo = comps[1]\r\n else:\r\n iSaNo = comps[2]\r\n\r\n ((me, me_oxs), (an, an_oxs)) = iSa_oxs(iSaNo.formula)\r\n if an != \"NO3\":\r\n return \"\"\r\n if me in [\"Au\", \"Pt\"]:\r\n return \"\"\r\n if is_me_activer(\"H\", 1, me, me_oxs):\r\n return \"\"\r\n\r\n iSiMe = Compound(simple(me))\r\n\r\n react = f\"{iSiMe} + HNO3 -> {iSaNo} + N2O + H2O\"\r\n\r\n return Reaction(react)","def refugia_adj_5(params, ns):\n #17 parameters \n nu1_1, nu1_2, nuA, nu2, nu3, m1_12, m1_21, m3_12, m3_13, m3_21, m3_23, m3_31, m3_32, T1a, T1b, T2, T3 = params\n sts = moments.LinearSystem_1D.steady_state_1D(ns[0] + ns[1] + ns[2])\n fs = moments.Spectrum(sts)\n fs = moments.Manips.split_1D_to_2D(fs, ns[0], ns[1] + ns[2])\n ## Population function and migration matrix for T1a\n nu_T1 = [nu1_1, nuA]\n fs.integrate(nu_T1, T1a)\n ## Population function and migration matrix for T1b\n mig1 = numpy.array([[0, m1_12],[m1_21, 0]])\n fs.integrate(nu_T1, T1b, m=mig1) \n fs = moments.Manips.split_2D_to_3D_2(fs, ns[1], ns[2])\n ## Population function and migration matrix for T2\n nu_T2 = [nu1_2, nu2, nu3]\n fs.integrate(nu_T2, T2)\n ## Population function and migration matrix for T3\n nu_T3 = [nu1_2, nu2, nu3]\n mig3 = numpy.array([[0, m3_12, m3_13],[m3_21, 0, m3_23], [m3_31, m3_32, 0]]) \n fs.integrate(nu_T3, T3, m=mig3) \n return fs","def __add__(self,sample):\n self.add(sample)","def loss(self, z1_rec, z3_rec):\n pass","def add(a,b):\n\treturn a+b","def convert_elementwise_add(node, **kwargs):\n return create_basic_op_node('Add', node, kwargs)","def _add(self, i, k):\n while i < self._size:\n self._bit[i] += k\n i += lsb(i)","def GachaCraftNodeExcelAddGP1103(builder, GP1103):\n return AddGP1103(builder, GP1103)","def convert_addn(node, **kwargs):\n return create_basic_op_node('Sum', node, kwargs)","def _add_utxo(self, item: UtxoIndexItem) -> None:\n raise NotImplementedError","def correlation_4op_3t(self, rho0, oplist, signature, tau):\n\n\n if len(oplist) != 4:\n raise ValueError('Number of operators is not 4.')\n\n a = operator_to_superoperator(oplist[0], signature[0])\n b = operator_to_superoperator(oplist[1], signature[1])\n c = operator_to_superoperator(oplist[2], signature[2])\n d = operator_to_superoperator(oplist[3], signature[3])\n\n for _ in oplist:\n if issparse(_):\n _ = _.toarray()\n\n\n # nmax = max(len(tau3), len(tau2), len(tau1))\n\n # g = -1j * (tau > 0) * self.propagator(tau)\n # G = np.zeros((self.dim, self.dim, len(tau)))\n\n # for n, elem in enumerate(g):\n # G[:,:, n] = g[n]\n\n if self.G is None:\n self.propagator(tau)\n\n G = self.G\n\n # unit operator in Liouville space\n N = self.dim\n idm = self.idm(sp=False)\n\n # print(d.shape, dm2vec(rho0.toarray()).shape)\n if issparse(rho0):\n rho = d.dot(dm2vec(rho0.toarray()))\n else:\n rho = d.dot(dm2vec(rho0))\n\n # print(type(rho), rho.shape)\n\n if issparse(rho): rho = rho.toarray()\n\n tmp = np.tensordot(G, rho, axes=((1), (0)))\n tmp = c.dot(tmp)\n tmp = np.tensordot(G, tmp, axes=([1], [0])) # ajk\n\n # tmp = np.einsum('dcj, ca, abk, b -> djk', G, c, G, rho)\n\n\n '''\n Scipy sparse matrix does not support dimensions more than 2, so\n ndarray has to be used for the tensor products.\n\n This can be improved by using sparse package.\n '''\n tmp = np.tensordot(b.todense(), tmp, axes=([1], [0]))\n # tmp = b.todense().dot(tmp)\n\n tmp = np.tensordot(G, tmp, axes=([1], [0]))\n\n return oe.contract('a, ab, bijk -> ijk', idm, a.todense(), tmp)\n\n # corr = np.einsum('a, ab, bck, bc, cdj, de, efi, f ->kji', idm, \\\n # left(a), G, left(b), left(c), G, left(d).dot(dm2vec(rho0))\n\n # return","def convert_add_scalar(node, **kwargs):\n return scalar_op_helper(node, 'Add', **kwargs)","def add(self, value):","def add(self, addr):\n\n val = self.mem.read(addr)\n result = self.alu.add(self.reg.accum, val)\n self.reg.accum = result","def _add_scalar(self, scalar):\n\n a, b = self, scalar\n\n # Don't bother to salt/obfuscate in a basic operation, do it\n # just before leaving the computer.\n encrypted_scalar = a.public_key.raw_encrypt(b, 1)\n\n sum_ciphertext = a._raw_add(a.ciphertext(False), encrypted_scalar)\n return EncryptedNumber(a.public_key, sum_ciphertext)","def vs3_func_3(ns, traj, vs_def_beads_ids, vs_params):\n i, j, k = vs_def_beads_ids\n ang_deg, d = vs_params # degrees, nm\n ang_rad = np.deg2rad(ang_deg) # retrieve radians\n d = d * 10 # retrieve amgstrom for MDA\n\n for ts in ns.aa2cg_universe.trajectory:\n pos_i = ns.aa2cg_universe.atoms[i].position\n pos_j = ns.aa2cg_universe.atoms[j].position\n pos_k = ns.aa2cg_universe.atoms[k].position\n r_ij = pos_j - pos_i\n r_jk = pos_k - pos_j\n comb_ijk = r_jk - (np.dot(r_ij, r_jk) / np.dot(r_ij, r_ij)) * r_ij\n traj[ts.frame] = pos_i + d * np.cos(ang_rad) * (r_ij / mda.lib.mdamath.norm(r_ij)) + d * np.sin(ang_rad) * (\n comb_ijk / mda.lib.mdamath.norm(comb_ijk))","def __add__(self, other):\r\n if isinstance(other, vec4):\r\n return vec4(self.x+other.x, self.y+other.y, self.z+other.z, self.w+other.w)\r\n else:\r\n raise TypeError, \"unsupported operand type for +\"","def _cmplx_add_ ( s , o ) :\n return o + complex ( s )","def double_add(self, x):\n self.add(x*2)","def test_iadd(self):\n tensor1 = Tensor([2, 4, 6, 8], requires_grad=True)\n tensor2 = Tensor([5, 8, 1, 2])\n \n tensor2 += tensor1\n assert tensor2.data.tolist() == [7, 12, 7, 10]\n\n tensor2 += 1\n assert tensor2.data.tolist() == [8, 13, 8, 11]","def k4(self, f, t, u, k3, usereverse=False):\n\n v = u + self._delta_t * k3\n tt = t + self._delta_t\n\n if usereverse:\n output, storagez, storagew = f(tt, v)\n\n self.storagez.append(storagez)\n self.storagew.append(storagew)\n\n return output\n else:\n return f(tt, v)","def itkHuangThresholdImageFilterIUC3IUS3_cast(obj: 'itkLightObject') -> \"itkHuangThresholdImageFilterIUC3IUS3 *\":\n return _itkHuangThresholdImageFilterPython.itkHuangThresholdImageFilterIUC3IUS3_cast(obj)","def addMe2Me(x):\n return x+x","def u(self, k, m, z):\n result = self.uCen(k, m, z)\n result += self.uSat(k, m, z)\n return result","def u(self, k, m, z):\n result = self.uCen(k, m, z)\n result += self.uSat(k, m, z)\n return result","def matrix_add():","def test_add_consistency2(self) -> None:\n a = Constant(\n 'const1',\n Float32(),\n np.zeros([1, 3, 3])\n )\n b = Constant(\n 'const2',\n Float32(),\n np.zeros([2])\n )\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\n try:\n Add(\n 'add1',\n [1, 3, 3],\n Float32(),\n input_ops\n )\n except AssertionError:\n print(\"Consistency test for 'Add' #2 passed!\")\n\n else:\n self.assertTrue(False, \"Consistency test for 'Add' #2 failed.\")","def itkTernaryAddImageFilterIUS3IUS3IUS3IUS3_cast(*args):\n return _itkTernaryAddImageFilterPython.itkTernaryAddImageFilterIUS3IUS3IUS3IUS3_cast(*args)","def add(a,b):\r\n return a+b","def itkBoundedReciprocalImageFilterIUL3IUL3_cast(*args):\n return _itkBoundedReciprocalImageFilterPython.itkBoundedReciprocalImageFilterIUL3IUL3_cast(*args)","def addition():\r\n error_handler()\r\n f1.delete(0, END)\r\n a1 = float(operand.get())\r\n a2 = float(operator.get())\r\n result = a1 + a2\r\n f1.insert(10, str(result))","def itkTernaryAddImageFilterIUL3IUL3IUL3IUL3_cast(*args):\n return _itkTernaryAddImageFilterPython.itkTernaryAddImageFilterIUL3IUL3IUL3IUL3_cast(*args)","def test_add_to_vx(self, cpu):\n for x in range(0x0, 0xF):\n for v in range(0x0, 0xFF):\n for kk in range(0x0, 0xFF):\n cpu.V_register[x] = v\n cpu.opcode = 0x7000 | (x << 8) | kk\n cpu.add_to_vx()\n assert(cpu.V_register[x] == (v + kk) & 0xFF)"],"string":"[\n \"def __iadd__( self, vector3 ):\\n return self.add( vector3 )\",\n \"def cu3(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U3, qid=[q0,q1], phase=alpha, phase1=beta,\\n phase2=gamma, ctrl=ctrl)\\n return self\",\n \"def S3_u32(self) -> complex:\\n return complex(\\n self._addr(self.defined_registers['Phase 3 power [W]']['addr']),\\n self._addr(self.defined_registers['Phase 3 volt amps reactive [VAr]']['addr']),\\n )\",\n \"def add_three(a, b, c):\\n return a + b + c\",\n \"def _r_u3(angle: tf.Tensor) -> tf.Tensor:\\n zero = tf.constant(0, dtype=tf.float64)\\n cos = tf.cos(tf.multiply(angle[0], tf.constant(0.5, dtype=tf.float64)))\\n sin = tf.sin(tf.multiply(angle[0], tf.constant(0.5, dtype=tf.float64)))\\n sin_complex = tf.complex(sin, zero)\\n cos_complex = tf.complex(cos, zero)\\n exponent_phi = tf.complex(zero, angle[1])\\n exp_phi = tf.exp(exponent_phi)\\n exponent_lambda = tf.complex(zero, angle[2])\\n exp_lambda = tf.exp(exponent_lambda)\\n exponent_lambda_phi = tf.complex(zero, angle[1] + angle[2])\\n exp_lambda_phi = tf.exp(exponent_lambda_phi)\\n ru3 = tf.stack([[cos_complex, -tf.multiply(exp_lambda, sin_complex)],\\n [tf.multiply(exp_phi, sin_complex), tf.multiply(exp_lambda_phi, cos_complex)]])\\n\\n return ru3\",\n \"def add( self, vector3 ):\\n self._coords[:3] += vector3._coords[:3]\\n return self\",\n \"def x3(self):\\n return self._x + self._x3\",\n \"def add_mult(num1, num2, num3):\\n \\n addmult = (num1 + num2) * num3\\n return addmult\",\n \"def I3_u32(self) -> complex:\\n return (self.S3_u32() / self.U23()).conjugate()\",\n \"def test_special_U3(self):\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \\\"U3\\\", {})\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \\\"U3\\\", {\\\"u3\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.2, 0.0).to_matrix(), \\\"U3\\\", {\\\"u3\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.0, 0.2).to_matrix(), \\\"U3\\\", {\\\"u3\\\": 1})\\n self.check_oneq_special_cases(U3Gate(0.11, 0.27, 0.3).to_matrix(), \\\"U3\\\", {\\\"u3\\\": 1})\",\n \"def test_U3(self, tol):\\n dev = qml.device(\\\"default.qubit\\\", wires=1)\\n\\n @qml.qnode(dev)\\n def circuit(x, y, z):\\n qml.QubitStateVector(1j * np.array([1, -1]) / np.sqrt(2), wires=[0])\\n qml.U3(x, y, z, wires=[0])\\n return qml.expval(qml.PauliX(0))\\n\\n theta = 0.543\\n phi = -0.234\\n lam = 0.654\\n\\n res = circuit(theta, phi, lam)\\n expected = np.sin(lam) * np.sin(phi) - np.cos(theta) * np.cos(lam) * np.cos(phi)\\n assert np.allclose(res, expected, atol=tol, rtol=0)\\n\\n grad_fn = autograd.grad(circuit, argnum=[0, 1, 2])\\n res = grad_fn(theta, phi, lam)\\n expected = np.array(\\n [\\n np.sin(theta) * np.cos(lam) * np.cos(phi),\\n np.cos(theta) * np.cos(lam) * np.sin(phi) + np.sin(lam) * np.cos(phi),\\n np.cos(theta) * np.sin(lam) * np.cos(phi) + np.cos(lam) * np.sin(phi),\\n ]\\n )\\n assert np.allclose(res, expected, atol=tol, rtol=0)\",\n \"def I3_u3(self) -> complex:\\n return self.I3_u1() * cmath.rect(1, 120 / 180 * cmath.pi)\",\n \"def add_three(v1, v2, v3):\\n p = v1 + v2 + v3\\n print(\\\"The sum of the three numbers is: {}\\\".format(p))\\n return p\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def L3G_acquisition(add):\\n\\n # control register\\n CTRL_REG1 = 0x20\\n CTRL_REG4 = 0x23\\n LOW_ODR = 0x39\\n FIFO_CTRL = 0x2e\\n # output register\\n OUT_X_L = 0x28\\n OUT_X_H = 0x29\\n OUT_Y_L = 0x2a\\n OUT_Y_H = 0x2b\\n OUT_Z_L = 0x2c\\n OUT_Z_H = 0x2d\\n\\n # low odr mode, 50Hz, 2000 dps full scale\\n bus.write_byte_data(add, CTRL_REG1, 0b10001111)\\n bus.write_byte_data(add, CTRL_REG4, 0b00110000)\\n bus.write_byte_data(add, LOW_ODR, 0b00000001)\\n bus.write_byte_data(add, FIFO_CTRL, 0b01000000)\\n\\n # accelerator accumulate\\n while True:\\n uint16_gx = (bus.read_byte_data(add, OUT_X_H) << 8) + \\\\\\n bus.read_byte_data(add, OUT_X_L)\\n uint16_gy = (bus.read_byte_data(add, OUT_Y_H) << 8) + \\\\\\n bus.read_byte_data(add, OUT_Y_L)\\n uint16_gz = (bus.read_byte_data(add, OUT_Z_H) << 8) + \\\\\\n bus.read_byte_data(add, OUT_Z_L)\\n\\n gx = twos_comp(uint16_gx, 16)\\n gy = twos_comp(uint16_gy, 16)\\n gz = twos_comp(uint16_gz, 16)\\n\\n yield [gx, gy, gz]\",\n \"def ADD():\\n global pointer, memory, registers\\n registers[memory[pointer + 0x02]] += memory[pointer + 0x01]\\n pointer += 0x03\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def I3_u1(self) -> complex:\\n # Should match in amplitude with \\\"Phase 3 current [A]\\\"\\n # Convert from relative to U32 -> relative to U1\\n return - (self.I3_u32() * cmath.rect(1, 90 / 180 * cmath.pi))\",\n \"def add_operation(self):\\n arg1 = self.memory[self.memory[self._cursor + 1]]\\n arg2 = self.memory[self.memory[self._cursor + 2]]\\n arg3 = self.memory[self._cursor + 3]\\n self.memory[arg3] = arg1 + arg2\\n # print(f'Cursor: {self._cursor}\\\\tAssigning position {position} with value {n1 + n2}')\\n self._cursor += 4\\n return\",\n \"def luk_plus_five(unit: ActiveUnit) -> None:\\n unit.mod_luk += 5\",\n \"def itkScalarConnectedComponentImageFilterIUL3IUL3_cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUL3IUL3_cast(*args)\",\n \"def heisen3_sum(v1: Vec3, v2: Vec3) -> Vec3:\\n assert v1.shape == v2.shape and v1.shape == (3,)\\n # first, do normal sum to get (x + x', y + y', z + z')\\n out = v1 + v2\\n # then add the xy' part to z + z'\\n out[2] += v1[0] * v2[1]\\n return out\",\n \"def ADD (self, n1, n2):\",\n \"def _action_op_u1(self, plaq):\\n # if self.link_type == 'U1':\\n # return np.cos(plaq)\\n return tf.math.cos(plaq)\",\n \"def add_vectors(v, u):\\n return (v[0] + u[0], v[1] + u[1])\",\n \"def test_special_U(self):\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \\\"U\\\", {})\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.2, 0.0).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.0, 0.2).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\",\n \"def getU3(state):\\n\\n # TODO : do the verifictions of the above constraints\\n\\n theta=2*math.acos(state[0])\\n phi=0\\n lam=0\\n\\n if state[1]<0: theta = -theta\\n\\n # U3=np.array([\\n # [math.cos(theta/2) , np.exp(-1j*lam)*math.sin(theta/2)], \\n # [np.exp(1j*phi)*math.sin(theta/2), np.exp(1j*(phi+lam))*math.cos(theta/2)]\\n # ])\\n # print (U3)\\n # print (U3@np.array([[1],[0]]))\\n\\n return [theta, phi, lam]\",\n \"def refugia_adj_3(params, ns):\\n #11 parameters \\n nu1, nuA, nu2, nu3, m1_1, m2_1, m2_2, m2_3, T1a, T1b, T2 = params\\n sts = moments.LinearSystem_1D.steady_state_1D(ns[0] + ns[1] + ns[2])\\n fs = moments.Spectrum(sts)\\n fs = moments.Manips.split_1D_to_2D(fs, ns[0], ns[1] + ns[2])\\n ## Population function and migration matrix for T1a\\n nu_T1 = [nu1, nuA]\\n fs.integrate(nu_T1, T1a)\\n ## Population function and migration matrix for T1b\\n mig1 = numpy.array([[0, m1_1],[m1_1, 0]])\\n fs.integrate(nu_T1, T1b, m=mig1) \\n fs = moments.Manips.split_2D_to_3D_2(fs, ns[1], ns[2])\\n ## Population function and migration matrix for T2\\n nu_T2 = [nu1, nu2, nu3]\\n mig2 = numpy.array([[0, m2_1, m2_3],[m2_1, 0, m2_2], [m2_3, m2_2, 0]]) \\n fs.integrate(nu_T2, T2, m=mig2)\\n return fs\",\n \"def new(self, u, k1, k2, k3, k4):\\n\\n v = self.combine(k1, k2, k3, k4)\\n\\n return u + (self._delta_t / 6.0) * v\",\n \"def __iadd__(self,l):\\r\\n\\t\\t\\r\\n\\t\\treturn self.add(l)\",\n \"def loss_step3(self, y, u, v):\\n uv = -0.5 * (y.float().t() @ (u + v))\\n return uv\",\n \"def test_add_consistency1(self) -> None:\\n a = Constant(\\n 'const1',\\n Float32(),\\n np.zeros([1, 3, 3])\\n )\\n b = Constant(\\n 'const2',\\n Float32(),\\n np.zeros([3])\\n )\\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\\n Add(\\n 'add1',\\n [1, 3, 3],\\n Float32(),\\n input_ops\\n )\\n\\n print(\\\"Consistency test for 'Add' #1 passed!\\\")\",\n \"def add_n():\\n pass\",\n \"def AssignAddHybrid3d(output, value, target=utils.CCE):\\n for i in range(output.shape[0]):\\n for j in range(output.shape[1]):\\n for k in range(output.shape[2]):\\n output[i, j, k] = output[i, j, k] + value[i, j, k]\\n\\n return output\",\n \"def add_reg_to_reg(self):\\n register = self.return_middle_registers(self.opcode)\\n sum = self.registers[register[0]] + self.registers[register[1]]\\n if sum > 0xFF:\\n self.registers[0xF] = 1\\n self.registers[register[0]] = sum & 0xFF\\n else:\\n self.registers[0xF] = 0\\n self.registers[register[0]] = sum\\n logger.info(\\\"Added V{} to V{} and got {}\\\".format(\\n register[0],\\n register[1],\\n self.registers[register[0]]))\",\n \"def __iadd__(self, other):\\r\\n if isinstance(other, vec4):\\r\\n self.x+=other.x\\r\\n self.y+=other.y\\r\\n self.z+=other.z\\r\\n self.w+=other.w\\r\\n return self\\r\\n else:\\r\\n raise TypeError, \\\"unsupported operand type for +=\\\"\",\n \"def __iadd__(self, tensor):\\n return self.add_(tensor)\",\n \"def __add__(self, v):\\n return vector(self.x + v.x, self.y + v.y, self.z + v.z)\",\n \"def test_add_with_int_arg(self):\\n\\n from pedemath.vec3 import add_v3\\n\\n a = Vec3(2, 3, 4)\\n b = 5\\n\\n result = add_v3(a, b)\\n\\n expected_result = Vec3(7, 8, 9)\\n\\n self.assertEqual(result, expected_result)\",\n \"def __iadd__(self,that):\\n #return self.__opExpand1(that,np.add, out=self)\\n return self.__opExpand2(that,np.add, out=self)\",\n \"def chain_3(d3f_dg3, dg_dx, d2f_dg2, d2g_dx2, df_dg, d3g_dx3):\\r\\n return d3f_dg3*(dg_dx**3) + 3*d2f_dg2*dg_dx*d2g_dx2 + df_dg*d3g_dx3\",\n \"def test_add(vec3_fixture):\\n scalar = vec3_fixture + 1\\n assert scalar.x1 == vec3_fixture.x1 + 1\\n assert scalar.x2 == vec3_fixture.x2 + 1\\n assert scalar.x3 == vec3_fixture.x3 + 1\\n\\n vector = vec3_fixture + Vec3([2, 3, 4])\\n assert vector.x1 == vec3_fixture.x1 + 2\\n assert vector.x2 == vec3_fixture.x2 + 3\\n assert vector.x3 == vec3_fixture.x3 + 4\",\n \"def __add__(self, tc): \\n tc = TwosComplement(tc)\\n bits = self.len if self.len > tc.len else tc.len \\n result = self.int + tc.int\\n return TwosComplement(result, bits)\",\n \"def sum_u(self):\\r\\n try:\\r\\n # add the velocity to the sum\\r\\n self.usum.vector()[:] += self.u.vector()[:]\\r\\n except AttributeError:\\r\\n # initialize the sum\\r\\n self.usum = self.u.copy(deepcopy=True)\",\n \"def add(self, params):\\n if len(params) < 2:\\n return\\n x = self.reg_dct[params[0]]\\n y = self.reg_dct[params[1]]\\n self.reg_dct[params[0]] = (x + y) % (2** 32)\",\n \"def __add__(self,that):\\n return self.__opExpand2(that,np.add)\",\n \"async def uadd(self, *args: Input):\\n # TODO(security) Allow for tuning nbytes\\n return await self.sadd(secrets.token_hex(), *args)\",\n \"def add_operation(self):\\n n1 = self.memory[self.memory[self._cursor + 1]]\\n n2 = self.memory[self.memory[self._cursor + 2]]\\n position = self.memory[self._cursor + 3]\\n self.memory[position] = n1 + n2\\n # print(f'Cursor: {self._cursor}\\\\tAssigning position {position} with value {n1} + {n2} = {n1 + n2}')\\n return\",\n \"def union_add(this, that):\\n return this.add(that, fill_value=0)\",\n \"def auxiliar_exercise1(self, param1, param2, param3):\\n result = param1 ** 2 + param2 ** 2 + param3 ** 2\\n return\",\n \"def __add__(self, rhs):\\n if isinstance(rhs, UTPS):\\n return UTPS(self.tc + rhs.tc)\\n elif numpy.isscalar(rhs):\\n retval = UTPS(numpy.copy(self.tc))\\n retval.tc[0] += rhs\\n return retval\\n else:\\n raise NotImplementedError\",\n \"def k3(self, f, t, u, k2, usereverse=False):\\n\\n h = self._delta_t / 2.0\\n\\n v = u + h * k2\\n tt = t + h\\n\\n if usereverse:\\n output, storagez, storagew = f(tt, v)\\n\\n self.storagez.append(storagez)\\n self.storagew.append(storagew)\\n\\n return output\\n else:\\n return f(tt, v)\",\n \"def __radd__(self,that):\\n return self.__opExpand2(that,np.add)\",\n \"def addU(self,name):\\n return self._addVar(name,self._uNames)\",\n \"def addOp(self, op):\\n self.operations << op\",\n \"def test_add3(self):\\n self.assertEqual(-5, add(-10 , 5), \\\"should be -5\\\")\",\n \"def itkScalarConnectedComponentImageFilterIUC3IUC3_cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUC3IUC3_cast(*args)\",\n \"def enc_add_const(pub, m, c):\\n # Similiar to enc add\\n add_const_result = m * powmod(pub.g, c, pub.n_sq) % pub.n_sq\\n return add_const_result\",\n \"def server1_add2 (c1, c2, pub):\\n #return (c1 + c2) % pub.n\\n return e_add(pub, c1, c2)\",\n \"def _add_op(value, sample_args, rationals_allowed):\\n entropy, sample_args = sample_args.peel()\\n if rationals_allowed and sample_args.count >= 3:\\n x = number.integer_or_rational(entropy, True)\\n else:\\n x = number.integer(entropy, True)\\n if random.choice([False, True]):\\n op_args = [x, value - x]\\n else:\\n op_args = [value - x, x]\\n return ops.Add, op_args, sample_args\",\n \"def convert_gcm3_AMUA3(den_gmc3):\\n return den_gmc3*const_avo/10.0\",\n \"def test_addmod(self):\\n from manticore.platforms import evm\\n from manticore.core.smtlib import ConstraintSet, Z3Solver, Operators\\n\\n constraints = ConstraintSet()\\n\\n address = 0x41414141414141414141\\n data = b\\\"\\\"\\n caller = 0x42424242424242424242\\n value = 0\\n bytecode = \\\"\\\"\\n vm = evm.EVM(constraints, address, data, caller, value, bytecode, gas=23000)\\n\\n self.assertEqual(vm.ADDMOD(12323, 2343, 20), 6)\\n self.assertEqual(vm.ADDMOD(12323, 2343, 0), 0)\\n\\n A, B, C = (\\n 0x780000002090309A004201626B1400041D318000000200008A0080089C042DA7,\\n 0xF000000740403F7007C012807BED003BE2CE800000060000FFFFBFF7E4087033,\\n 0x338000080FFFFF64AAAACFFCF7DBFA408000000000000270120000001E7C2ACF,\\n )\\n self.assertEqual(\\n vm.ADDMOD(A, B, C),\\n 23067954172474524581131069693479689311231082562138745684554374357070230297856,\\n )\\n a, b, c = (\\n constraints.new_bitvec(256),\\n constraints.new_bitvec(256),\\n constraints.new_bitvec(256),\\n )\\n constraints.add(a == A)\\n constraints.add(b == B)\\n constraints.add(c == C)\\n result = vm.ADDMOD(a, b, c)\\n # 0x32ffffd700d073ae080133f517d922bd000000000007f1611e003fffc9239d00\\n self.assertEqual(\\n Z3Solver.instance().get_all_values(constraints, result),\\n [0x32FFFFD700D073AE080133F517D922BD000000000007F1611E003FFFC9239D00],\\n )\",\n \"def gen_op3(N11, N22, N12, rN11, rN22, rN12):\\n raw = N12 / (N11 * N22)\\n ref = rN12 / (rN11 * rN22)\\n print(\\\"=====\\\\n3rd method: raw = N12 / (N11 * N22)\\\")\\n print(\\\"raw: %.2f | reference: %.2f\\\" % (raw, ref))\\n print(\\\"OP: 1 - raw = %.3f\\\\n=====\\\" % (1 - raw))\",\n \"def step3(self):\\n\\t\\tif self.b[self.k] == 'e':\\n\\t\\t\\tif self.ends(\\\"icate\\\"):\\t self.r(\\\"ic\\\")\\n\\t\\t\\telif self.ends(\\\"ative\\\"): self.r(\\\"\\\")\\n\\t\\t\\telif self.ends(\\\"alize\\\"): self.r(\\\"al\\\")\\n\\t\\telif self.b[self.k] == 'i':\\n\\t\\t\\tif self.ends(\\\"iciti\\\"):\\t self.r(\\\"ic\\\")\\n\\t\\telif self.b[self.k] == 'l':\\n\\t\\t\\tif self.ends(\\\"ical\\\"):\\t self.r(\\\"ic\\\")\\n\\t\\t\\telif self.ends(\\\"ful\\\"):\\t self.r(\\\"\\\")\\n\\t\\telif self.b[self.k] == 's':\\n\\t\\t\\tif self.ends(\\\"ness\\\"):\\t self.r(\\\"\\\")\",\n \"def itkScalarConnectedComponentImageFilterIUS3IUS3_cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUS3IUS3_cast(*args)\",\n \"def AddOperation(self, op):\\n self._operations.append(op)\",\n \"def test_add():\\n z = Complex(1, -2)\\n w = Complex(1, 1)\\n assert (z + w) == Complex(2, -1)\\n assert (z + (1+1j)) == Complex(2, -1)\\n assert (z + 2) == Complex(3, -2)\\n assert (z + 2.0) == Complex(3, -2)\",\n \"def r_3(comps: 'list(Compound)', is_input):\\r\\n react: str\\r\\n\\r\\n if is_input:\\r\\n iSiMe = Compound(\\\"Zn\\\")\\r\\n if len(comps) == 1:\\r\\n if \\\"iSi\\\" in comps[0].comp_type:\\r\\n iSiMe = comps[0]\\r\\n else:\\r\\n if \\\"iSi\\\" in comps[0].comp_type:\\r\\n iSiMe = comps[0]\\r\\n else:\\r\\n iSiMe = comps[1]\\r\\n\\r\\n me = list(iSiMe.formula.consist.keys())[0].name\\r\\n if me in [\\\"Au\\\", \\\"Pt\\\"]:\\r\\n return \\\"\\\"\\r\\n me_oxs = get_me_oxs(me)\\r\\n if me_oxs == 0:\\r\\n return \\\"\\\"\\r\\n if is_me_activer(\\\"H\\\", 1, me, me_oxs):\\r\\n return \\\"\\\"\\r\\n\\r\\n iSaNo = Compound(iSaNo_create(me, me_oxs, \\\"NO3\\\", 1))\\r\\n\\r\\n react = f\\\"{iSiMe} + HNO3 -> {iSaNo} + N2O + H2O\\\"\\r\\n else:\\r\\n iSaNo = Compound(\\\"Zn(NO3)2\\\")\\r\\n if len(comps) == 1:\\r\\n if \\\"iSaNo\\\" in comps[0].comp_type:\\r\\n iSaNo = comps[0]\\r\\n elif len(comps) == 2:\\r\\n if \\\"iSaNo\\\" in comps[0].comp_type:\\r\\n iSaNo = comps[0]\\r\\n elif \\\"iSaNo\\\" in comps[1].comp_type:\\r\\n iSaNo = comps[1]\\r\\n else:\\r\\n if \\\"iSaNo\\\" in comps[0].comp_type:\\r\\n iSaNo = comps[0]\\r\\n elif \\\"iSaNo\\\" in comps[1].comp_type:\\r\\n iSaNo = comps[1]\\r\\n else:\\r\\n iSaNo = comps[2]\\r\\n\\r\\n ((me, me_oxs), (an, an_oxs)) = iSa_oxs(iSaNo.formula)\\r\\n if an != \\\"NO3\\\":\\r\\n return \\\"\\\"\\r\\n if me in [\\\"Au\\\", \\\"Pt\\\"]:\\r\\n return \\\"\\\"\\r\\n if is_me_activer(\\\"H\\\", 1, me, me_oxs):\\r\\n return \\\"\\\"\\r\\n\\r\\n iSiMe = Compound(simple(me))\\r\\n\\r\\n react = f\\\"{iSiMe} + HNO3 -> {iSaNo} + N2O + H2O\\\"\\r\\n\\r\\n return Reaction(react)\",\n \"def refugia_adj_5(params, ns):\\n #17 parameters \\n nu1_1, nu1_2, nuA, nu2, nu3, m1_12, m1_21, m3_12, m3_13, m3_21, m3_23, m3_31, m3_32, T1a, T1b, T2, T3 = params\\n sts = moments.LinearSystem_1D.steady_state_1D(ns[0] + ns[1] + ns[2])\\n fs = moments.Spectrum(sts)\\n fs = moments.Manips.split_1D_to_2D(fs, ns[0], ns[1] + ns[2])\\n ## Population function and migration matrix for T1a\\n nu_T1 = [nu1_1, nuA]\\n fs.integrate(nu_T1, T1a)\\n ## Population function and migration matrix for T1b\\n mig1 = numpy.array([[0, m1_12],[m1_21, 0]])\\n fs.integrate(nu_T1, T1b, m=mig1) \\n fs = moments.Manips.split_2D_to_3D_2(fs, ns[1], ns[2])\\n ## Population function and migration matrix for T2\\n nu_T2 = [nu1_2, nu2, nu3]\\n fs.integrate(nu_T2, T2)\\n ## Population function and migration matrix for T3\\n nu_T3 = [nu1_2, nu2, nu3]\\n mig3 = numpy.array([[0, m3_12, m3_13],[m3_21, 0, m3_23], [m3_31, m3_32, 0]]) \\n fs.integrate(nu_T3, T3, m=mig3) \\n return fs\",\n \"def __add__(self,sample):\\n self.add(sample)\",\n \"def loss(self, z1_rec, z3_rec):\\n pass\",\n \"def add(a,b):\\n\\treturn a+b\",\n \"def convert_elementwise_add(node, **kwargs):\\n return create_basic_op_node('Add', node, kwargs)\",\n \"def _add(self, i, k):\\n while i < self._size:\\n self._bit[i] += k\\n i += lsb(i)\",\n \"def GachaCraftNodeExcelAddGP1103(builder, GP1103):\\n return AddGP1103(builder, GP1103)\",\n \"def convert_addn(node, **kwargs):\\n return create_basic_op_node('Sum', node, kwargs)\",\n \"def _add_utxo(self, item: UtxoIndexItem) -> None:\\n raise NotImplementedError\",\n \"def correlation_4op_3t(self, rho0, oplist, signature, tau):\\n\\n\\n if len(oplist) != 4:\\n raise ValueError('Number of operators is not 4.')\\n\\n a = operator_to_superoperator(oplist[0], signature[0])\\n b = operator_to_superoperator(oplist[1], signature[1])\\n c = operator_to_superoperator(oplist[2], signature[2])\\n d = operator_to_superoperator(oplist[3], signature[3])\\n\\n for _ in oplist:\\n if issparse(_):\\n _ = _.toarray()\\n\\n\\n # nmax = max(len(tau3), len(tau2), len(tau1))\\n\\n # g = -1j * (tau > 0) * self.propagator(tau)\\n # G = np.zeros((self.dim, self.dim, len(tau)))\\n\\n # for n, elem in enumerate(g):\\n # G[:,:, n] = g[n]\\n\\n if self.G is None:\\n self.propagator(tau)\\n\\n G = self.G\\n\\n # unit operator in Liouville space\\n N = self.dim\\n idm = self.idm(sp=False)\\n\\n # print(d.shape, dm2vec(rho0.toarray()).shape)\\n if issparse(rho0):\\n rho = d.dot(dm2vec(rho0.toarray()))\\n else:\\n rho = d.dot(dm2vec(rho0))\\n\\n # print(type(rho), rho.shape)\\n\\n if issparse(rho): rho = rho.toarray()\\n\\n tmp = np.tensordot(G, rho, axes=((1), (0)))\\n tmp = c.dot(tmp)\\n tmp = np.tensordot(G, tmp, axes=([1], [0])) # ajk\\n\\n # tmp = np.einsum('dcj, ca, abk, b -> djk', G, c, G, rho)\\n\\n\\n '''\\n Scipy sparse matrix does not support dimensions more than 2, so\\n ndarray has to be used for the tensor products.\\n\\n This can be improved by using sparse package.\\n '''\\n tmp = np.tensordot(b.todense(), tmp, axes=([1], [0]))\\n # tmp = b.todense().dot(tmp)\\n\\n tmp = np.tensordot(G, tmp, axes=([1], [0]))\\n\\n return oe.contract('a, ab, bijk -> ijk', idm, a.todense(), tmp)\\n\\n # corr = np.einsum('a, ab, bck, bc, cdj, de, efi, f ->kji', idm, \\\\\\n # left(a), G, left(b), left(c), G, left(d).dot(dm2vec(rho0))\\n\\n # return\",\n \"def convert_add_scalar(node, **kwargs):\\n return scalar_op_helper(node, 'Add', **kwargs)\",\n \"def add(self, value):\",\n \"def add(self, addr):\\n\\n val = self.mem.read(addr)\\n result = self.alu.add(self.reg.accum, val)\\n self.reg.accum = result\",\n \"def _add_scalar(self, scalar):\\n\\n a, b = self, scalar\\n\\n # Don't bother to salt/obfuscate in a basic operation, do it\\n # just before leaving the computer.\\n encrypted_scalar = a.public_key.raw_encrypt(b, 1)\\n\\n sum_ciphertext = a._raw_add(a.ciphertext(False), encrypted_scalar)\\n return EncryptedNumber(a.public_key, sum_ciphertext)\",\n \"def vs3_func_3(ns, traj, vs_def_beads_ids, vs_params):\\n i, j, k = vs_def_beads_ids\\n ang_deg, d = vs_params # degrees, nm\\n ang_rad = np.deg2rad(ang_deg) # retrieve radians\\n d = d * 10 # retrieve amgstrom for MDA\\n\\n for ts in ns.aa2cg_universe.trajectory:\\n pos_i = ns.aa2cg_universe.atoms[i].position\\n pos_j = ns.aa2cg_universe.atoms[j].position\\n pos_k = ns.aa2cg_universe.atoms[k].position\\n r_ij = pos_j - pos_i\\n r_jk = pos_k - pos_j\\n comb_ijk = r_jk - (np.dot(r_ij, r_jk) / np.dot(r_ij, r_ij)) * r_ij\\n traj[ts.frame] = pos_i + d * np.cos(ang_rad) * (r_ij / mda.lib.mdamath.norm(r_ij)) + d * np.sin(ang_rad) * (\\n comb_ijk / mda.lib.mdamath.norm(comb_ijk))\",\n \"def __add__(self, other):\\r\\n if isinstance(other, vec4):\\r\\n return vec4(self.x+other.x, self.y+other.y, self.z+other.z, self.w+other.w)\\r\\n else:\\r\\n raise TypeError, \\\"unsupported operand type for +\\\"\",\n \"def _cmplx_add_ ( s , o ) :\\n return o + complex ( s )\",\n \"def double_add(self, x):\\n self.add(x*2)\",\n \"def test_iadd(self):\\n tensor1 = Tensor([2, 4, 6, 8], requires_grad=True)\\n tensor2 = Tensor([5, 8, 1, 2])\\n \\n tensor2 += tensor1\\n assert tensor2.data.tolist() == [7, 12, 7, 10]\\n\\n tensor2 += 1\\n assert tensor2.data.tolist() == [8, 13, 8, 11]\",\n \"def k4(self, f, t, u, k3, usereverse=False):\\n\\n v = u + self._delta_t * k3\\n tt = t + self._delta_t\\n\\n if usereverse:\\n output, storagez, storagew = f(tt, v)\\n\\n self.storagez.append(storagez)\\n self.storagew.append(storagew)\\n\\n return output\\n else:\\n return f(tt, v)\",\n \"def itkHuangThresholdImageFilterIUC3IUS3_cast(obj: 'itkLightObject') -> \\\"itkHuangThresholdImageFilterIUC3IUS3 *\\\":\\n return _itkHuangThresholdImageFilterPython.itkHuangThresholdImageFilterIUC3IUS3_cast(obj)\",\n \"def addMe2Me(x):\\n return x+x\",\n \"def u(self, k, m, z):\\n result = self.uCen(k, m, z)\\n result += self.uSat(k, m, z)\\n return result\",\n \"def u(self, k, m, z):\\n result = self.uCen(k, m, z)\\n result += self.uSat(k, m, z)\\n return result\",\n \"def matrix_add():\",\n \"def test_add_consistency2(self) -> None:\\n a = Constant(\\n 'const1',\\n Float32(),\\n np.zeros([1, 3, 3])\\n )\\n b = Constant(\\n 'const2',\\n Float32(),\\n np.zeros([2])\\n )\\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\\n try:\\n Add(\\n 'add1',\\n [1, 3, 3],\\n Float32(),\\n input_ops\\n )\\n except AssertionError:\\n print(\\\"Consistency test for 'Add' #2 passed!\\\")\\n\\n else:\\n self.assertTrue(False, \\\"Consistency test for 'Add' #2 failed.\\\")\",\n \"def itkTernaryAddImageFilterIUS3IUS3IUS3IUS3_cast(*args):\\n return _itkTernaryAddImageFilterPython.itkTernaryAddImageFilterIUS3IUS3IUS3IUS3_cast(*args)\",\n \"def add(a,b):\\r\\n return a+b\",\n \"def itkBoundedReciprocalImageFilterIUL3IUL3_cast(*args):\\n return _itkBoundedReciprocalImageFilterPython.itkBoundedReciprocalImageFilterIUL3IUL3_cast(*args)\",\n \"def addition():\\r\\n error_handler()\\r\\n f1.delete(0, END)\\r\\n a1 = float(operand.get())\\r\\n a2 = float(operator.get())\\r\\n result = a1 + a2\\r\\n f1.insert(10, str(result))\",\n \"def itkTernaryAddImageFilterIUL3IUL3IUL3IUL3_cast(*args):\\n return _itkTernaryAddImageFilterPython.itkTernaryAddImageFilterIUL3IUL3IUL3IUL3_cast(*args)\",\n \"def test_add_to_vx(self, cpu):\\n for x in range(0x0, 0xF):\\n for v in range(0x0, 0xFF):\\n for kk in range(0x0, 0xFF):\\n cpu.V_register[x] = v\\n cpu.opcode = 0x7000 | (x << 8) | kk\\n cpu.add_to_vx()\\n assert(cpu.V_register[x] == (v + kk) & 0xFF)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7029553","0.6238025","0.60627526","0.5975905","0.5929082","0.5905331","0.5873839","0.5848612","0.58422893","0.5827687","0.57158524","0.563768","0.5590613","0.55825996","0.5567244","0.55254906","0.5499538","0.5457423","0.54275006","0.54163665","0.5363699","0.53537244","0.5349636","0.5335175","0.53005207","0.5282001","0.5279748","0.52724177","0.52636653","0.5261462","0.5254115","0.5227382","0.5225192","0.5215678","0.52126426","0.52079695","0.5194455","0.51745224","0.51538604","0.5153009","0.5146017","0.51448363","0.51415753","0.5135859","0.51165205","0.51146954","0.5100363","0.50908583","0.5087835","0.5085571","0.50728893","0.50660163","0.50518566","0.5051531","0.5044652","0.50341153","0.5022132","0.5021466","0.5017414","0.50138706","0.5010644","0.50079316","0.4986887","0.4985699","0.4983357","0.49783364","0.4970569","0.49619156","0.49602935","0.495921","0.4958302","0.49566147","0.49552366","0.49476808","0.49425927","0.49410036","0.49401635","0.49385455","0.49355733","0.49352905","0.49336088","0.4929945","0.49277943","0.49277538","0.49252045","0.49242908","0.491882","0.49009287","0.4900222","0.48991457","0.4899079","0.4899079","0.4897043","0.48927057","0.48926142","0.48905995","0.48905158","0.48901287","0.48861313","0.487679"],"string":"[\n \"0.7029553\",\n \"0.6238025\",\n \"0.60627526\",\n \"0.5975905\",\n \"0.5929082\",\n \"0.5905331\",\n \"0.5873839\",\n \"0.5848612\",\n \"0.58422893\",\n \"0.5827687\",\n \"0.57158524\",\n \"0.563768\",\n \"0.5590613\",\n \"0.55825996\",\n \"0.5567244\",\n \"0.55254906\",\n \"0.5499538\",\n \"0.5457423\",\n \"0.54275006\",\n \"0.54163665\",\n \"0.5363699\",\n \"0.53537244\",\n \"0.5349636\",\n \"0.5335175\",\n \"0.53005207\",\n \"0.5282001\",\n \"0.5279748\",\n \"0.52724177\",\n \"0.52636653\",\n \"0.5261462\",\n \"0.5254115\",\n \"0.5227382\",\n \"0.5225192\",\n \"0.5215678\",\n \"0.52126426\",\n \"0.52079695\",\n \"0.5194455\",\n \"0.51745224\",\n \"0.51538604\",\n \"0.5153009\",\n \"0.5146017\",\n \"0.51448363\",\n \"0.51415753\",\n \"0.5135859\",\n \"0.51165205\",\n \"0.51146954\",\n \"0.5100363\",\n \"0.50908583\",\n \"0.5087835\",\n \"0.5085571\",\n \"0.50728893\",\n \"0.50660163\",\n \"0.50518566\",\n \"0.5051531\",\n \"0.5044652\",\n \"0.50341153\",\n \"0.5022132\",\n \"0.5021466\",\n \"0.5017414\",\n \"0.50138706\",\n \"0.5010644\",\n \"0.50079316\",\n \"0.4986887\",\n \"0.4985699\",\n \"0.4983357\",\n \"0.49783364\",\n \"0.4970569\",\n \"0.49619156\",\n \"0.49602935\",\n \"0.495921\",\n \"0.4958302\",\n \"0.49566147\",\n \"0.49552366\",\n \"0.49476808\",\n \"0.49425927\",\n \"0.49410036\",\n \"0.49401635\",\n \"0.49385455\",\n \"0.49355733\",\n \"0.49352905\",\n \"0.49336088\",\n \"0.4929945\",\n \"0.49277943\",\n \"0.49277538\",\n \"0.49252045\",\n \"0.49242908\",\n \"0.491882\",\n \"0.49009287\",\n \"0.4900222\",\n \"0.48991457\",\n \"0.4899079\",\n \"0.4899079\",\n \"0.4897043\",\n \"0.48927057\",\n \"0.48926142\",\n \"0.48905995\",\n \"0.48905158\",\n \"0.48901287\",\n \"0.48861313\",\n \"0.487679\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.61557925"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81742,"cells":{"query":{"kind":"string","value":"add CX gate (controlled X gate, controlled NOT gate, CNOT gate)."},"document":{"kind":"string","value":"def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def CX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)","def add(self, y):\n return circuit.add(self, y)","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def _append_cx(self, i, j):\n\n if not 0 <= i < self.num_qubits or not 0 <= j < self.num_qubits:\n raise QiskitError(\"CX qubits are out of bounds.\")\n self.linear[j] = (self.linear[i] + self.linear[j]) % 2\n self.shift[j] = (self.shift[i] + self.shift[j]) % 2","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def dcx(self, addr):\n\n self.reg.idx = self.reg.idx.inc(-1)\n self.reg.zerox_flag = self.reg.idx.eq_zero()","def BCS(self, value):\n if self.reg.C:\n self.reg.PC += value","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def DEX(self, *_):\n self._dec_or_inc_register('X', increment=False)","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def circuitSat(C):","def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self","def inc_xor_gateways(self):\r\n self.num_xor_gateways += 1","def XX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.XX, qubit_expr)","def _process_cnot(self, node):\n id0 = self._process_bit_id(node.children[0])\n id1 = self._process_bit_id(node.children[1])\n if not(len(id0) == len(id1) or len(id0) == 1 or len(id1) == 1):\n raise UnrollerError(\"internal error: qreg size mismatch\",\n \"line=%s\" % node.line, \"file=%s\" % node.file)\n maxidx = max([len(id0), len(id1)])\n for idx in range(maxidx):\n if len(id0) > 1 and len(id1) > 1:\n self.backend.cx(id0[idx], id1[idx])\n elif len(id0) > 1:\n self.backend.cx(id0[idx], id1[0])\n else:\n self.backend.cx(id0[0], id1[idx])","def cy(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CY(), target=[control, target])","def test_simple_cc():\n hs_c = LocalSpace('c', dimension=3)\n hs_q = LocalSpace('q1', basis=('g', 'e'))\n Delta_1 = Symbol('Delta_1')\n Omega_1 = Symbol('Omega_1')\n g_1 = Symbol('g_1')\n a = Destroy(hs=hs_c)\n a_dag = Create(hs=hs_c)\n sig_p = LocalSigma('e', 'g', hs=hs_q)\n sig_m = LocalSigma('g', 'e', hs=hs_q)\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\n assert (\n srepr(simplified.term)\n == \"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \"\n \"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \"\n \"basis=('g', 'e')))), sign=-1)\"\n )\n expanded = simplified.doit()\n assert expanded == jc_expr","def _cmplx_add_ ( s , o ) :\n return o + complex ( s )","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def incr_operand(self):\n pass","def C(self,X):\n return(\n 0\n )","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def add(num1, num2, Cin):\n Cin=0\n l2=[]\n final=\"\"\n\n \"\"\"Using for loop for starting addition from the last indexed number\"\"\"\n for i in range(len(num1)-1,-1,-1):\n bit1=num1[i]#storing each indexed() value of num1 in bit1\n bit2=num2[i]#storing each indexed() value of num2 in bit2\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\n Cin=Cout#declaring cout as cin for next bit addition\n l2.append(SUM)#adding SUM to l2\n l3=l2[::-1]##reversing the value of l2\n final+=str(l2[-1])#converting the list value to string\n final1=final[::-1]#reversing string value\n return final1 #returning the binary addition as string","def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def gate_mfcc(recurrent_net, sample_input):\n length = sample_input.shape[1]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\n select = sigmoid(select)\n return np.sum(select * score) / np.sum(select)","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def test_scalar_coeff_cc():\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\n kappa = Symbol('kappa', real=True)\n a1 = Destroy(hs=hs_1)\n a2 = Destroy(hs=hs_2)\n\n jc_expr = (\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\n )\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == I * kappa * OperatorPlusMinusCC(\n a1.dag() * a2, sign=-1\n )\n expanded = simplified.doit()\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())","def bcc(self, arg):\n\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def cx(x):\n return cw(x - global_min_x)","def gate_lfcc(recurrent_net, sample_input):\n length = sample_input.shape[0]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[i, :])\n select = sigmoid(select)\n score = sigmoid(score)\n return np.sum(select * score) / np.sum(select)","def double_add(self, x):\n self.add(x*2)","def test_ud_cnot():\n program = dedent(\n \"\"\"\\\n register q0[0]\n register q1[1]\n register q2[2]\n register q3[3]\n X q2\n CNOT q2 q0\n \"\"\"\n )\n\n result = run(program, run_gate_array)\n assert isclose(result, [1.0, 0.0, 1.0, 0.0]).all()","def forward(self,\n x: Tensor) \\\n -> Tensor:\n\n x = self.convs[0](x)\n res = x\n for i in range(self.num_rates):\n x = torch.tanh(self.filter_convs[i](\n x)) * torch.sigmoid(self.gate_convs[i](x))\n x = self.convs[i+1](x)\n res = res + x\n return res","def _compute_carry_and_output(self, x, h_tm1, c_tm1):\n x_i, x_f, x_c, x_o = x\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\n i = self.recurrent_activation(\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\n f = self.recurrent_activation(x_f + K.dot(\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\n o = self.recurrent_activation(\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\n return c, o","def iadd(state: State) -> State:\n cell = state.array[state.index] or 0\n return state._replace(acc=state.acc + cell)","def add_component(self, xi):\n assert xi.berkovich_line() is self.berkovich_line(), \"xi must be a point\\\n on the Berkovich line underlying this model\"\n X = self\n if not X.is_component(xi):\n ComponentOfModel(X, xi)\n X._changed = True\n\n \"\"\"\n T = X.tree()\n # we have to first check whether xi is already a component !\n # the first condition should be unnecessary; this is a bug in\n # mclf.berkovich_trees: T.find_point for an empty tree gives an error\n if not X.is_component(xi):\n T, vertex = T.add_point(xi)\n self._tree = T\n component = ComponentOfModel(self, vertex)\n if component.is_horizontal():\n self._horizontal_components.append(component)\n else:\n self._vertical_components.append(component)\n # we report that the model has changed\n self._changed = True\n \"\"\"","def two_activation(self, output_reg):\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\n self._q_neuron.cx(self.inputs[0], self._output[output_reg])\n self._q_neuron.cx(self.inputs[1], self._output[output_reg])","def INX(self, *_):\n self._dec_or_inc_register('X', increment=True)","def gate2zx(box):\n if isinstance(box, (Bra, Ket)):\n dom, cod = (1, 0) if isinstance(box, Bra) else (0, 1)\n return Id(0).tensor(*[\n X(dom, cod, phase=.5 * bit) for bit in box.bitstring])\n if isinstance(box, (Rz, Rx)):\n return (Z if isinstance(box, Rz) else X)(1, 1, box.phase)\n if isinstance(box, CRz):\n return Z(1, 2) @ Z(1, 2, box.phase)\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\n if isinstance(box, CRx):\n return X(1, 2) @ X(1, 2, box.phase)\\\n >> Id(1) @ (Z(2, 1) >> X(1, 0, -box.phase)) @ Id(1)\n if isinstance(box, quantum.CU1):\n return Z(1, 2, box.phase) @ Z(1, 2, box.phase)\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\n standard_gates = {\n quantum.H: H,\n quantum.Z: Z(1, 1, .5),\n quantum.X: X(1, 1, .5),\n quantum.Y: Y(1, 1, .5),\n CZ: Z(1, 2) @ Id(1) >> Id(1) @ Had() @ Id(1) >> Id(1) @ Z(2, 1),\n CX: Z(1, 2) @ Id(1) >> Id(1) @ X(2, 1)}\n return standard_gates[box]","def add(self, x):\n self.sum += (1 / self.counter) * (x - self.sum)\n self.counter += 1","def test_cnot():\n\n program = dedent(\n \"\"\"\\\n register q0[0]\n register q1[1]\n X q0\n CNOT q0 q1\n \"\"\"\n )\n\n result = run(program, run_gate_array, return_distribution=True)\n assert isclose(result, [0.0, 0.0, 0.0, 1.0]).all()","def cX(cb):\n allNodes = b.allNodes(group=cb)\n for n in allNodes:\n allNodes = allNodes + cX(n)\n\n return allNodes","def forward(self, x):\r\n out = x + self.conv_block(x) # add skip connections\r\n return out","def test_cx_gate_nondeterministic_minimal_basis_gates(self):\n shots = 2000\n circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_2q_clifford.cx_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def test_ccx_gate_nondeterministic_minimal_basis_gates(self):\n shots = 2000\n circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_non_clifford.ccx_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def add_neurone(self, couche, nbr=1):\n if self.control == 0:\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\n self.couche[couche] += nbr\n else:\n print(\"Le réseau est deja créé, vous en pouvez plus le modifier\")","def _gate_signal(self, input_channels, output_channels, BatchNorm=False):\n g = Conv2D(output_channels, (1,1), padding=\"same\")(input_channels)\n if BatchNorm:\n g = BatchNormalization()(g)\n g = Activation(\"relu\")(g)\n\n return g","def three_activation(self, output_reg):\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\n self._q_neuron.ccx(self.inputs[1], self.inputs[2], self._output[output_reg])\n self._q_neuron.ccx(self.inputs[0], self.inputs[2], self._output[output_reg])","def test_add_to_vx(self, cpu):\n for x in range(0x0, 0xF):\n for v in range(0x0, 0xFF):\n for kk in range(0x0, 0xFF):\n cpu.V_register[x] = v\n cpu.opcode = 0x7000 | (x << 8) | kk\n cpu.add_to_vx()\n assert(cpu.V_register[x] == (v + kk) & 0xFF)","def _control_predefined(operation, num_ctrl_qubits):\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\n if num_ctrl_qubits == 1:\n import qiskit.extensions.standard.cx\n cgate = qiskit.extensions.standard.cx.CnotGate()\n else:\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n elif operation.name == 'y':\n import qiskit.extensions.standard.cy\n cgate = qiskit.extensions.standard.cy.CyGate()\n elif operation.name == 'z':\n import qiskit.extensions.standard.cz\n cgate = qiskit.extensions.standard.cz.CzGate()\n elif operation.name == 'h':\n import qiskit.extensions.standard.ch\n cgate = qiskit.extensions.standard.ch.CHGate()\n elif operation.name in {'rx', 'ry', 'rz'}:\n if operation.name == 'rx':\n import qiskit.extensions.standard.crx\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\n elif operation.name == 'ry':\n import qiskit.extensions.standard.cry\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\n else: # operation.name == 'rz'\n import qiskit.extensions.standard.crz\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\n if num_ctrl_qubits == 1:\n return cgate\n else:\n # only predefined for one control qubit\n return cgate.control(num_ctrl_qubits - 1)\n elif operation.name == 'swap':\n import qiskit.extensions.standard.cswap\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\n elif operation.name == 'u1':\n import qiskit.extensions.standard.cu1\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\n elif operation.name == 'u3':\n import qiskit.extensions.standard.cu3\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\n elif operation.name == 'cx':\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n else:\n raise QiskitError('No standard controlled gate for \"{}\"'.format(\n operation.name))\n return cgate","def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])","def covar(fx,cx):\n \n fx = np.array(fx)\n cx = np.array(cx)\n \n shape_fx = fx.shape\n shape_cx = cx.shape\n \n \n if shape_fx[1] != shape_cx[0]:\n print('-----------------------------------------')\n print(\"Shapes of fx and cx cannot be multiplied:\")\n print(shape_fx,\"x\",shape_cx)\n print('-----------------------------------------')\n raise ValueError('Input matrices are not compliant')\n \n cy = np.dot(np.dot(fx,cx),fx.T)\n \n print(\"Size of Cy matrix: \",np.shape(cy))\n \n return cy","def forward(self, x):\n x = self.conv(x)\n x = self.bn(x)\n x = self.act(x)\n return x","def forward(self, x):\n x = self.conv(x)\n x = self.bn(x)\n x = self.act(x)\n return x","def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self","def _output_add(block_x, orig_x):\n stride = orig_x.shape[-2] // block_x.shape[-2]\n strides = (stride, stride)\n if block_x.shape[-1] != orig_x.shape[-1]:\n orig_x = nn.avg_pool(orig_x, strides, strides)\n channels_to_add = block_x.shape[-1] - orig_x.shape[-1]\n orig_x = jnp.pad(orig_x, [(0, 0), (0, 0), (0, 0), (0, channels_to_add)])\n return block_x + orig_x","def credit(self, value):\n self._negative_value_raises_an_error(value)\n self.operations.insert(value);","def c(x):\n cost = per_widget_cost * x + fixed_cost\n return cost","def TAX(self, *_):\n self.reg.X = self.reg.A\n self.reg.N = self.reg.X << 7\n self.reg.Z = self.reg.X == 0","def local_inplace_addsd_ccode(node):\r\n if isinstance(node.op, sparse.AddSD) and theano.config.cxx:\r\n out_dtype = scalar.upcast(*node.inputs)\r\n if out_dtype != node.inputs[1].dtype:\r\n return\r\n new_node = AddSD_ccode(format=node.inputs[0].type.format,\r\n inplace=True)(*node.inputs)\r\n return [new_node]\r\n return False","def enable_cl1_direct(self):\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\n self.write_versa5(0x18,0x20)\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\n self.write_versa5(0x13,0x03) ## Switch to clock\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def ADD_I_Vx(self, x):\n\t\tself.I += self.V[x]","def convert_C_instruction(self, instruction):\n comp, dest, jump = self.parse(instruction)\n\n return f\"111{convert_comp(comp)}{convert_dest(dest)}\" \\\n f\"{convert_jump(jump)}\"","def forward(self, x):\n out = x + self.conv_block(x) # add skip connections\n return out","def forward(self, x):\n out = x + self.conv_block(x) # add skip connections\n return out","def forward(self, x):\n out = x + self.conv_block(x) # add skip connections\n return out","def xscalary_plus_z(scalar, x, y, activation=None):\n R = tf.add(tf.scalar_mul(scalar,x), y)\n if activation:\n return activation(R)\n else: \n return R","def custom_constr(x, qr, inverse, depth):\n qc = QuantumCircuit(qr)\n maxi, mini = max(x), min(x)\n n = x.shape[0]\n #qc_wv = Wavelets(n).construct_circuit(register=qr)\n for _ in range(depth):\n qc.h(qr)\n for i in range(n):\n qc.u2(np.pi*(x[(i+1) % n]-mini)/(maxi-mini), 2*np.pi*(x[i]-mini)/(maxi-mini), qr[i])\n for i in range(n):\n qc.cx(qr[i], qr[(i + 1) % n])\n qc.u2(np.pi*(x[(i+1) % n]-mini)/(maxi-mini),\n ((2*np.pi)**2*(x[i]-mini)*(x[(i+1) % n]-mini)/(maxi-mini)**2) % 2*np.pi,\n qr[(i + 1) % n])\n qc.cx(qr[i], qr[(i + 1) % n])\n #qc = qc + qc_wv\n if inverse:\n return qc.inverse()\n return qc","def csw(self, q0, q1, q2, ctrl=None):\n self.cx(q2,q1,ctrl=ctrl).ccx(q0,q1,q2,ctrl=ctrl).cx(q2,q1,ctrl=ctrl)\n return self","def _AddCompound(self, kegg_id, how_many):\n i = self._FindCompoundIndex(kegg_id)\n if i is not None:\n self.reactants[i].coeff += how_many\n else:\n self.reactants += [CompoundWithCoeff.FromId(how_many, kegg_id)]\n \n # clear the cache since the reaction has changed\n self._catalyzing_enzymes = None","def multicoil_cg(x_in,y,nu,x0,mask,S,n,niter):\n x = x0\n x_zf_sum = A_H(y,mask,S)\n# [:,mask.flatten()]\n \n r = (nu*x_zf_sum) + x_in - (nu*A_H(A(x,mask,S),mask,S)) - (n*x)\n p = r\n rtr_old = np.vdot(r.flatten(),r.flatten())\n \n for i in range(0,niter):\n Ap = (nu*A_H(A(p,mask,S),mask,S)) + (n*p)\n alpha = np.real(rtr_old/np.vdot(p.flatten(),Ap.flatten()))\n \n x += (alpha*p)\n r -= (alpha*Ap)\n \n rtr_new = np.vdot(r.flatten(),r.flatten())\n \n if np.sqrt(rtr_new) < 1e-10:\n break\n \n p = r + (rtr_new*p/rtr_old)\n \n rtr_old = rtr_new\n \n \n return x","def _acc_grads(self, x, label):\n ##\n # Forward propagation\n z1 = self.params.W.dot(x) + self.params.b1\n h = tanh(z1)\n z2 = np.dot(self.params.U, h) + self.params.b2\n y_hat = softmax(z2)\n \n y = make_onehot(label, self.outputsize)\n d2 = y_hat - y\n self.grads.b2 += d2\n self.grads.U += np.outer(d2, h) + self.lreg * self.params.U\n d1 = np.dot(self.params.U.T, d2) * tanhd(z1) \n \n self.grads.W += np.outer(d1, x) + self.lreg * self.params.W\n self.grads.b1 += d1","def construct(self, x):\n x = self.conv1(x)\n x = self.bn1(x)\n x = self.relu(x)\n x = self.conv2(x)\n x = self.bn2(x)\n x = self.relu(x)\n x = self.conv3(x)\n x = self.bn3(x)\n x = self.relu(x)\n x = self.conv4(x)\n x = self.bn4(x)\n x = self.relu(x)\n x = self.conv5(x)\n x = self.bn5(x)\n x = self.relu(x)\n x = self.conv6(x)\n x = self.bn6(x)\n x = self.relu(x)\n return x","def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]","def cn_not(control_qbits, not_qbit):\n return (\n hadamard(not_qbit) |\n cn_phase(control_qbits, not_qbit, 0.5) |\n hadamard(not_qbit))","def add_bitwise(x, y):\n\n answer = 0\n carry_in = 0\n k = 1\n iterations_tracker = x | y\n\n while (iterations_tracker):\n x_k = x & k\n y_k = y & k\n\n answer |= x_k ^ y_k ^ carry_in\n carry_out = majority_bitwise(x_k, y_k, carry_in)\n\n carry_in = carry_out << 1\n\n k <<= 1\n iterations_tracker >>= 1\n\n if (carry_in):\n answer |= carry_in\n\n return answer","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\n return self","def bcs(self, arg):\n\n self.pc += arg if self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def TXA(self, *_):\n self.reg.A = self.reg.X\n self.reg.N = self.reg.A << 7\n self.reg.Z = self.reg.A == 0","def TAY(self, *_):\n self.reg.Y = self.reg.A\n self.reg.N = self.reg.Y << 7\n self.reg.Z = self.reg.Y == 0","def TXS(self, *_):\n self.reg.S = self.reg.X\n self.reg.N = self.reg.S << 7\n self.reg.Z = self.reg.S == 0","def add(self, x):\n self.sum += x\n self.n += 1","def incr_cond(self):\n pass","def add_control(operation, num_ctrl_qubits, label):\n if isinstance(operation, UnitaryGate):\n # attempt decomposition\n operation._define()\n if _control_definition_known(operation, num_ctrl_qubits):\n return _control_predefined(operation, num_ctrl_qubits)\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)","def ccx(self, q0, q1, q2, ctrl=None):\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\n return self","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def test_cx_equivalence_1cx(self, seed=1):\n state = np.random.default_rng(seed)\n rnd = 2 * np.pi * state.random(size=12)\n\n qr = QuantumRegister(2, name=\"q\")\n qc = QuantumCircuit(qr)\n\n qc.u(rnd[0], rnd[1], rnd[2], qr[0])\n qc.u(rnd[3], rnd[4], rnd[5], qr[1])\n\n qc.cx(qr[1], qr[0])\n\n qc.u(rnd[6], rnd[7], rnd[8], qr[0])\n qc.u(rnd[9], rnd[10], rnd[11], qr[1])\n\n sim = UnitarySimulatorPy()\n unitary = execute(qc, sim).result().get_unitary()\n self.assertEqual(two_qubit_cnot_decompose.num_basis_gates(unitary), 1)\n self.assertTrue(Operator(two_qubit_cnot_decompose(unitary)).equiv(unitary))","def __init__(self, x):\n self.bit = x\n for i in range(len(x)):\n j = i | (i + 1)\n if j < len(x):\n x[j] += x[i]","def __add__(self, tc): \n tc = TwosComplement(tc)\n bits = self.len if self.len > tc.len else tc.len \n result = self.int + tc.int\n return TwosComplement(result, bits)","def x(self, new_x):\n if new_x is None:\n logging.warning(\"Cochain features were set to None. \")\n else:\n assert self.num_cells == len(new_x)\n self.__x = new_x","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\n return self","def conj(self, *, inplace: bool = False) -> SelfAdjointUnitaryGate:\n if self.power == 1 and not self.is_conjugated() and self.is_transposed(\n ):\n return PowerMatrixGate.T(self, inplace=inplace)\n else:\n return PowerMatrixGate.conj(self, inplace=inplace)","def test_superposition_cnot():\n\n program = dedent(\n \"\"\"\\\n register q0[0]\n register q1[1]\n H q0\n CNOT q0 q1\n \"\"\"\n )\n\n result = run(program, run_gate_array, return_distribution=True)\n assert isclose(result, [0.5, 0.0, 0.0, 0.5]).all()"],"string":"[\n \"def CX(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def _append_cx(self, i, j):\\n\\n if not 0 <= i < self.num_qubits or not 0 <= j < self.num_qubits:\\n raise QiskitError(\\\"CX qubits are out of bounds.\\\")\\n self.linear[j] = (self.linear[i] + self.linear[j]) % 2\\n self.shift[j] = (self.shift[i] + self.shift[j]) % 2\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def dcx(self, addr):\\n\\n self.reg.idx = self.reg.idx.inc(-1)\\n self.reg.zerox_flag = self.reg.idx.eq_zero()\",\n \"def BCS(self, value):\\n if self.reg.C:\\n self.reg.PC += value\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def DEX(self, *_):\\n self._dec_or_inc_register('X', increment=False)\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def circuitSat(C):\",\n \"def cxr(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def inc_xor_gateways(self):\\r\\n self.num_xor_gateways += 1\",\n \"def XX(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.XX, qubit_expr)\",\n \"def _process_cnot(self, node):\\n id0 = self._process_bit_id(node.children[0])\\n id1 = self._process_bit_id(node.children[1])\\n if not(len(id0) == len(id1) or len(id0) == 1 or len(id1) == 1):\\n raise UnrollerError(\\\"internal error: qreg size mismatch\\\",\\n \\\"line=%s\\\" % node.line, \\\"file=%s\\\" % node.file)\\n maxidx = max([len(id0), len(id1)])\\n for idx in range(maxidx):\\n if len(id0) > 1 and len(id1) > 1:\\n self.backend.cx(id0[idx], id1[idx])\\n elif len(id0) > 1:\\n self.backend.cx(id0[idx], id1[0])\\n else:\\n self.backend.cx(id0[0], id1[idx])\",\n \"def cy(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CY(), target=[control, target])\",\n \"def test_simple_cc():\\n hs_c = LocalSpace('c', dimension=3)\\n hs_q = LocalSpace('q1', basis=('g', 'e'))\\n Delta_1 = Symbol('Delta_1')\\n Omega_1 = Symbol('Omega_1')\\n g_1 = Symbol('g_1')\\n a = Destroy(hs=hs_c)\\n a_dag = Create(hs=hs_c)\\n sig_p = LocalSigma('e', 'g', hs=hs_q)\\n sig_m = LocalSigma('g', 'e', hs=hs_q)\\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\\n assert (\\n srepr(simplified.term)\\n == \\\"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \\\"\\n \\\"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \\\"\\n \\\"basis=('g', 'e')))), sign=-1)\\\"\\n )\\n expanded = simplified.doit()\\n assert expanded == jc_expr\",\n \"def _cmplx_add_ ( s , o ) :\\n return o + complex ( s )\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def incr_operand(self):\\n pass\",\n \"def C(self,X):\\n return(\\n 0\\n )\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def add(num1, num2, Cin):\\n Cin=0\\n l2=[]\\n final=\\\"\\\"\\n\\n \\\"\\\"\\\"Using for loop for starting addition from the last indexed number\\\"\\\"\\\"\\n for i in range(len(num1)-1,-1,-1):\\n bit1=num1[i]#storing each indexed() value of num1 in bit1\\n bit2=num2[i]#storing each indexed() value of num2 in bit2\\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\\n Cin=Cout#declaring cout as cin for next bit addition\\n l2.append(SUM)#adding SUM to l2\\n l3=l2[::-1]##reversing the value of l2\\n final+=str(l2[-1])#converting the list value to string\\n final1=final[::-1]#reversing string value\\n return final1 #returning the binary addition as string\",\n \"def cxr_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def gate_mfcc(recurrent_net, sample_input):\\n length = sample_input.shape[1]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\\n select = sigmoid(select)\\n return np.sum(select * score) / np.sum(select)\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def test_scalar_coeff_cc():\\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\\n kappa = Symbol('kappa', real=True)\\n a1 = Destroy(hs=hs_1)\\n a2 = Destroy(hs=hs_2)\\n\\n jc_expr = (\\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\\n )\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == I * kappa * OperatorPlusMinusCC(\\n a1.dag() * a2, sign=-1\\n )\\n expanded = simplified.doit()\\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())\",\n \"def bcc(self, arg):\\n\\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def cx(x):\\n return cw(x - global_min_x)\",\n \"def gate_lfcc(recurrent_net, sample_input):\\n length = sample_input.shape[0]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[i, :])\\n select = sigmoid(select)\\n score = sigmoid(score)\\n return np.sum(select * score) / np.sum(select)\",\n \"def double_add(self, x):\\n self.add(x*2)\",\n \"def test_ud_cnot():\\n program = dedent(\\n \\\"\\\"\\\"\\\\\\n register q0[0]\\n register q1[1]\\n register q2[2]\\n register q3[3]\\n X q2\\n CNOT q2 q0\\n \\\"\\\"\\\"\\n )\\n\\n result = run(program, run_gate_array)\\n assert isclose(result, [1.0, 0.0, 1.0, 0.0]).all()\",\n \"def forward(self,\\n x: Tensor) \\\\\\n -> Tensor:\\n\\n x = self.convs[0](x)\\n res = x\\n for i in range(self.num_rates):\\n x = torch.tanh(self.filter_convs[i](\\n x)) * torch.sigmoid(self.gate_convs[i](x))\\n x = self.convs[i+1](x)\\n res = res + x\\n return res\",\n \"def _compute_carry_and_output(self, x, h_tm1, c_tm1):\\n x_i, x_f, x_c, x_o = x\\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\\n i = self.recurrent_activation(\\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\\n f = self.recurrent_activation(x_f + K.dot(\\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\\n o = self.recurrent_activation(\\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\\n return c, o\",\n \"def iadd(state: State) -> State:\\n cell = state.array[state.index] or 0\\n return state._replace(acc=state.acc + cell)\",\n \"def add_component(self, xi):\\n assert xi.berkovich_line() is self.berkovich_line(), \\\"xi must be a point\\\\\\n on the Berkovich line underlying this model\\\"\\n X = self\\n if not X.is_component(xi):\\n ComponentOfModel(X, xi)\\n X._changed = True\\n\\n \\\"\\\"\\\"\\n T = X.tree()\\n # we have to first check whether xi is already a component !\\n # the first condition should be unnecessary; this is a bug in\\n # mclf.berkovich_trees: T.find_point for an empty tree gives an error\\n if not X.is_component(xi):\\n T, vertex = T.add_point(xi)\\n self._tree = T\\n component = ComponentOfModel(self, vertex)\\n if component.is_horizontal():\\n self._horizontal_components.append(component)\\n else:\\n self._vertical_components.append(component)\\n # we report that the model has changed\\n self._changed = True\\n \\\"\\\"\\\"\",\n \"def two_activation(self, output_reg):\\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\\n self._q_neuron.cx(self.inputs[0], self._output[output_reg])\\n self._q_neuron.cx(self.inputs[1], self._output[output_reg])\",\n \"def INX(self, *_):\\n self._dec_or_inc_register('X', increment=True)\",\n \"def gate2zx(box):\\n if isinstance(box, (Bra, Ket)):\\n dom, cod = (1, 0) if isinstance(box, Bra) else (0, 1)\\n return Id(0).tensor(*[\\n X(dom, cod, phase=.5 * bit) for bit in box.bitstring])\\n if isinstance(box, (Rz, Rx)):\\n return (Z if isinstance(box, Rz) else X)(1, 1, box.phase)\\n if isinstance(box, CRz):\\n return Z(1, 2) @ Z(1, 2, box.phase)\\\\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\\n if isinstance(box, CRx):\\n return X(1, 2) @ X(1, 2, box.phase)\\\\\\n >> Id(1) @ (Z(2, 1) >> X(1, 0, -box.phase)) @ Id(1)\\n if isinstance(box, quantum.CU1):\\n return Z(1, 2, box.phase) @ Z(1, 2, box.phase)\\\\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\\n standard_gates = {\\n quantum.H: H,\\n quantum.Z: Z(1, 1, .5),\\n quantum.X: X(1, 1, .5),\\n quantum.Y: Y(1, 1, .5),\\n CZ: Z(1, 2) @ Id(1) >> Id(1) @ Had() @ Id(1) >> Id(1) @ Z(2, 1),\\n CX: Z(1, 2) @ Id(1) >> Id(1) @ X(2, 1)}\\n return standard_gates[box]\",\n \"def add(self, x):\\n self.sum += (1 / self.counter) * (x - self.sum)\\n self.counter += 1\",\n \"def test_cnot():\\n\\n program = dedent(\\n \\\"\\\"\\\"\\\\\\n register q0[0]\\n register q1[1]\\n X q0\\n CNOT q0 q1\\n \\\"\\\"\\\"\\n )\\n\\n result = run(program, run_gate_array, return_distribution=True)\\n assert isclose(result, [0.0, 0.0, 0.0, 1.0]).all()\",\n \"def cX(cb):\\n allNodes = b.allNodes(group=cb)\\n for n in allNodes:\\n allNodes = allNodes + cX(n)\\n\\n return allNodes\",\n \"def forward(self, x):\\r\\n out = x + self.conv_block(x) # add skip connections\\r\\n return out\",\n \"def test_cx_gate_nondeterministic_minimal_basis_gates(self):\\n shots = 2000\\n circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_2q_clifford.cx_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def test_ccx_gate_nondeterministic_minimal_basis_gates(self):\\n shots = 2000\\n circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_non_clifford.ccx_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def add_neurone(self, couche, nbr=1):\\n if self.control == 0:\\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\\n self.couche[couche] += nbr\\n else:\\n print(\\\"Le réseau est deja créé, vous en pouvez plus le modifier\\\")\",\n \"def _gate_signal(self, input_channels, output_channels, BatchNorm=False):\\n g = Conv2D(output_channels, (1,1), padding=\\\"same\\\")(input_channels)\\n if BatchNorm:\\n g = BatchNormalization()(g)\\n g = Activation(\\\"relu\\\")(g)\\n\\n return g\",\n \"def three_activation(self, output_reg):\\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\\n self._q_neuron.ccx(self.inputs[1], self.inputs[2], self._output[output_reg])\\n self._q_neuron.ccx(self.inputs[0], self.inputs[2], self._output[output_reg])\",\n \"def test_add_to_vx(self, cpu):\\n for x in range(0x0, 0xF):\\n for v in range(0x0, 0xFF):\\n for kk in range(0x0, 0xFF):\\n cpu.V_register[x] = v\\n cpu.opcode = 0x7000 | (x << 8) | kk\\n cpu.add_to_vx()\\n assert(cpu.V_register[x] == (v + kk) & 0xFF)\",\n \"def _control_predefined(operation, num_ctrl_qubits):\\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\\n if num_ctrl_qubits == 1:\\n import qiskit.extensions.standard.cx\\n cgate = qiskit.extensions.standard.cx.CnotGate()\\n else:\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n elif operation.name == 'y':\\n import qiskit.extensions.standard.cy\\n cgate = qiskit.extensions.standard.cy.CyGate()\\n elif operation.name == 'z':\\n import qiskit.extensions.standard.cz\\n cgate = qiskit.extensions.standard.cz.CzGate()\\n elif operation.name == 'h':\\n import qiskit.extensions.standard.ch\\n cgate = qiskit.extensions.standard.ch.CHGate()\\n elif operation.name in {'rx', 'ry', 'rz'}:\\n if operation.name == 'rx':\\n import qiskit.extensions.standard.crx\\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\\n elif operation.name == 'ry':\\n import qiskit.extensions.standard.cry\\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\\n else: # operation.name == 'rz'\\n import qiskit.extensions.standard.crz\\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\\n if num_ctrl_qubits == 1:\\n return cgate\\n else:\\n # only predefined for one control qubit\\n return cgate.control(num_ctrl_qubits - 1)\\n elif operation.name == 'swap':\\n import qiskit.extensions.standard.cswap\\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\\n elif operation.name == 'u1':\\n import qiskit.extensions.standard.cu1\\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\\n elif operation.name == 'u3':\\n import qiskit.extensions.standard.cu3\\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\\n elif operation.name == 'cx':\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n else:\\n raise QiskitError('No standard controlled gate for \\\"{}\\\"'.format(\\n operation.name))\\n return cgate\",\n \"def cz(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CZ(), target=[control, target])\",\n \"def covar(fx,cx):\\n \\n fx = np.array(fx)\\n cx = np.array(cx)\\n \\n shape_fx = fx.shape\\n shape_cx = cx.shape\\n \\n \\n if shape_fx[1] != shape_cx[0]:\\n print('-----------------------------------------')\\n print(\\\"Shapes of fx and cx cannot be multiplied:\\\")\\n print(shape_fx,\\\"x\\\",shape_cx)\\n print('-----------------------------------------')\\n raise ValueError('Input matrices are not compliant')\\n \\n cy = np.dot(np.dot(fx,cx),fx.T)\\n \\n print(\\\"Size of Cy matrix: \\\",np.shape(cy))\\n \\n return cy\",\n \"def forward(self, x):\\n x = self.conv(x)\\n x = self.bn(x)\\n x = self.act(x)\\n return x\",\n \"def forward(self, x):\\n x = self.conv(x)\\n x = self.bn(x)\\n x = self.act(x)\\n return x\",\n \"def cs_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def _output_add(block_x, orig_x):\\n stride = orig_x.shape[-2] // block_x.shape[-2]\\n strides = (stride, stride)\\n if block_x.shape[-1] != orig_x.shape[-1]:\\n orig_x = nn.avg_pool(orig_x, strides, strides)\\n channels_to_add = block_x.shape[-1] - orig_x.shape[-1]\\n orig_x = jnp.pad(orig_x, [(0, 0), (0, 0), (0, 0), (0, channels_to_add)])\\n return block_x + orig_x\",\n \"def credit(self, value):\\n self._negative_value_raises_an_error(value)\\n self.operations.insert(value);\",\n \"def c(x):\\n cost = per_widget_cost * x + fixed_cost\\n return cost\",\n \"def TAX(self, *_):\\n self.reg.X = self.reg.A\\n self.reg.N = self.reg.X << 7\\n self.reg.Z = self.reg.X == 0\",\n \"def local_inplace_addsd_ccode(node):\\r\\n if isinstance(node.op, sparse.AddSD) and theano.config.cxx:\\r\\n out_dtype = scalar.upcast(*node.inputs)\\r\\n if out_dtype != node.inputs[1].dtype:\\r\\n return\\r\\n new_node = AddSD_ccode(format=node.inputs[0].type.format,\\r\\n inplace=True)(*node.inputs)\\r\\n return [new_node]\\r\\n return False\",\n \"def enable_cl1_direct(self):\\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\\n self.write_versa5(0x18,0x20)\\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\\n self.write_versa5(0x13,0x03) ## Switch to clock\\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def ADD_I_Vx(self, x):\\n\\t\\tself.I += self.V[x]\",\n \"def convert_C_instruction(self, instruction):\\n comp, dest, jump = self.parse(instruction)\\n\\n return f\\\"111{convert_comp(comp)}{convert_dest(dest)}\\\" \\\\\\n f\\\"{convert_jump(jump)}\\\"\",\n \"def forward(self, x):\\n out = x + self.conv_block(x) # add skip connections\\n return out\",\n \"def forward(self, x):\\n out = x + self.conv_block(x) # add skip connections\\n return out\",\n \"def forward(self, x):\\n out = x + self.conv_block(x) # add skip connections\\n return out\",\n \"def xscalary_plus_z(scalar, x, y, activation=None):\\n R = tf.add(tf.scalar_mul(scalar,x), y)\\n if activation:\\n return activation(R)\\n else: \\n return R\",\n \"def custom_constr(x, qr, inverse, depth):\\n qc = QuantumCircuit(qr)\\n maxi, mini = max(x), min(x)\\n n = x.shape[0]\\n #qc_wv = Wavelets(n).construct_circuit(register=qr)\\n for _ in range(depth):\\n qc.h(qr)\\n for i in range(n):\\n qc.u2(np.pi*(x[(i+1) % n]-mini)/(maxi-mini), 2*np.pi*(x[i]-mini)/(maxi-mini), qr[i])\\n for i in range(n):\\n qc.cx(qr[i], qr[(i + 1) % n])\\n qc.u2(np.pi*(x[(i+1) % n]-mini)/(maxi-mini),\\n ((2*np.pi)**2*(x[i]-mini)*(x[(i+1) % n]-mini)/(maxi-mini)**2) % 2*np.pi,\\n qr[(i + 1) % n])\\n qc.cx(qr[i], qr[(i + 1) % n])\\n #qc = qc + qc_wv\\n if inverse:\\n return qc.inverse()\\n return qc\",\n \"def csw(self, q0, q1, q2, ctrl=None):\\n self.cx(q2,q1,ctrl=ctrl).ccx(q0,q1,q2,ctrl=ctrl).cx(q2,q1,ctrl=ctrl)\\n return self\",\n \"def _AddCompound(self, kegg_id, how_many):\\n i = self._FindCompoundIndex(kegg_id)\\n if i is not None:\\n self.reactants[i].coeff += how_many\\n else:\\n self.reactants += [CompoundWithCoeff.FromId(how_many, kegg_id)]\\n \\n # clear the cache since the reaction has changed\\n self._catalyzing_enzymes = None\",\n \"def multicoil_cg(x_in,y,nu,x0,mask,S,n,niter):\\n x = x0\\n x_zf_sum = A_H(y,mask,S)\\n# [:,mask.flatten()]\\n \\n r = (nu*x_zf_sum) + x_in - (nu*A_H(A(x,mask,S),mask,S)) - (n*x)\\n p = r\\n rtr_old = np.vdot(r.flatten(),r.flatten())\\n \\n for i in range(0,niter):\\n Ap = (nu*A_H(A(p,mask,S),mask,S)) + (n*p)\\n alpha = np.real(rtr_old/np.vdot(p.flatten(),Ap.flatten()))\\n \\n x += (alpha*p)\\n r -= (alpha*Ap)\\n \\n rtr_new = np.vdot(r.flatten(),r.flatten())\\n \\n if np.sqrt(rtr_new) < 1e-10:\\n break\\n \\n p = r + (rtr_new*p/rtr_old)\\n \\n rtr_old = rtr_new\\n \\n \\n return x\",\n \"def _acc_grads(self, x, label):\\n ##\\n # Forward propagation\\n z1 = self.params.W.dot(x) + self.params.b1\\n h = tanh(z1)\\n z2 = np.dot(self.params.U, h) + self.params.b2\\n y_hat = softmax(z2)\\n \\n y = make_onehot(label, self.outputsize)\\n d2 = y_hat - y\\n self.grads.b2 += d2\\n self.grads.U += np.outer(d2, h) + self.lreg * self.params.U\\n d1 = np.dot(self.params.U.T, d2) * tanhd(z1) \\n \\n self.grads.W += np.outer(d1, x) + self.lreg * self.params.W\\n self.grads.b1 += d1\",\n \"def construct(self, x):\\n x = self.conv1(x)\\n x = self.bn1(x)\\n x = self.relu(x)\\n x = self.conv2(x)\\n x = self.bn2(x)\\n x = self.relu(x)\\n x = self.conv3(x)\\n x = self.bn3(x)\\n x = self.relu(x)\\n x = self.conv4(x)\\n x = self.bn4(x)\\n x = self.relu(x)\\n x = self.conv5(x)\\n x = self.bn5(x)\\n x = self.relu(x)\\n x = self.conv6(x)\\n x = self.bn6(x)\\n x = self.relu(x)\\n return x\",\n \"def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]\",\n \"def cn_not(control_qbits, not_qbit):\\n return (\\n hadamard(not_qbit) |\\n cn_phase(control_qbits, not_qbit, 0.5) |\\n hadamard(not_qbit))\",\n \"def add_bitwise(x, y):\\n\\n answer = 0\\n carry_in = 0\\n k = 1\\n iterations_tracker = x | y\\n\\n while (iterations_tracker):\\n x_k = x & k\\n y_k = y & k\\n\\n answer |= x_k ^ y_k ^ carry_in\\n carry_out = majority_bitwise(x_k, y_k, carry_in)\\n\\n carry_in = carry_out << 1\\n\\n k <<= 1\\n iterations_tracker >>= 1\\n\\n if (carry_in):\\n answer |= carry_in\\n\\n return answer\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\\n return self\",\n \"def bcs(self, arg):\\n\\n self.pc += arg if self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def TXA(self, *_):\\n self.reg.A = self.reg.X\\n self.reg.N = self.reg.A << 7\\n self.reg.Z = self.reg.A == 0\",\n \"def TAY(self, *_):\\n self.reg.Y = self.reg.A\\n self.reg.N = self.reg.Y << 7\\n self.reg.Z = self.reg.Y == 0\",\n \"def TXS(self, *_):\\n self.reg.S = self.reg.X\\n self.reg.N = self.reg.S << 7\\n self.reg.Z = self.reg.S == 0\",\n \"def add(self, x):\\n self.sum += x\\n self.n += 1\",\n \"def incr_cond(self):\\n pass\",\n \"def add_control(operation, num_ctrl_qubits, label):\\n if isinstance(operation, UnitaryGate):\\n # attempt decomposition\\n operation._define()\\n if _control_definition_known(operation, num_ctrl_qubits):\\n return _control_predefined(operation, num_ctrl_qubits)\\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def ccx(self, q0, q1, q2, ctrl=None):\\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\\n return self\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def test_cx_equivalence_1cx(self, seed=1):\\n state = np.random.default_rng(seed)\\n rnd = 2 * np.pi * state.random(size=12)\\n\\n qr = QuantumRegister(2, name=\\\"q\\\")\\n qc = QuantumCircuit(qr)\\n\\n qc.u(rnd[0], rnd[1], rnd[2], qr[0])\\n qc.u(rnd[3], rnd[4], rnd[5], qr[1])\\n\\n qc.cx(qr[1], qr[0])\\n\\n qc.u(rnd[6], rnd[7], rnd[8], qr[0])\\n qc.u(rnd[9], rnd[10], rnd[11], qr[1])\\n\\n sim = UnitarySimulatorPy()\\n unitary = execute(qc, sim).result().get_unitary()\\n self.assertEqual(two_qubit_cnot_decompose.num_basis_gates(unitary), 1)\\n self.assertTrue(Operator(two_qubit_cnot_decompose(unitary)).equiv(unitary))\",\n \"def __init__(self, x):\\n self.bit = x\\n for i in range(len(x)):\\n j = i | (i + 1)\\n if j < len(x):\\n x[j] += x[i]\",\n \"def __add__(self, tc): \\n tc = TwosComplement(tc)\\n bits = self.len if self.len > tc.len else tc.len \\n result = self.int + tc.int\\n return TwosComplement(result, bits)\",\n \"def x(self, new_x):\\n if new_x is None:\\n logging.warning(\\\"Cochain features were set to None. \\\")\\n else:\\n assert self.num_cells == len(new_x)\\n self.__x = new_x\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\\n return self\",\n \"def conj(self, *, inplace: bool = False) -> SelfAdjointUnitaryGate:\\n if self.power == 1 and not self.is_conjugated() and self.is_transposed(\\n ):\\n return PowerMatrixGate.T(self, inplace=inplace)\\n else:\\n return PowerMatrixGate.conj(self, inplace=inplace)\",\n \"def test_superposition_cnot():\\n\\n program = dedent(\\n \\\"\\\"\\\"\\\\\\n register q0[0]\\n register q1[1]\\n H q0\\n CNOT q0 q1\\n \\\"\\\"\\\"\\n )\\n\\n result = run(program, run_gate_array, return_distribution=True)\\n assert isclose(result, [0.5, 0.0, 0.0, 0.5]).all()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.62984484","0.5671249","0.5556696","0.5556419","0.5492904","0.53954756","0.53890973","0.53359663","0.5300576","0.5287976","0.5240326","0.5182423","0.51742876","0.5162475","0.5155768","0.51150185","0.51141423","0.51031303","0.5088816","0.50455844","0.5043136","0.504052","0.50128525","0.49999657","0.49889478","0.49879476","0.49778607","0.49777117","0.49764487","0.49723947","0.49723205","0.49700797","0.49488404","0.49415165","0.49406278","0.49287677","0.49233097","0.49230877","0.49167725","0.49133906","0.4895118","0.48895344","0.48733014","0.4853158","0.48477912","0.48426315","0.48412627","0.4835641","0.4835103","0.48285064","0.48075506","0.47998103","0.47938377","0.47906697","0.47587693","0.47559595","0.47558624","0.475133","0.475133","0.4749933","0.47487748","0.47483754","0.4743566","0.4742448","0.4735121","0.47344598","0.47342417","0.47292358","0.47276413","0.47180295","0.47141996","0.47141996","0.47141996","0.4712501","0.47059104","0.47030643","0.47021842","0.46956694","0.46954265","0.46940002","0.46932015","0.46884263","0.46820122","0.46760076","0.46750537","0.4663475","0.46585858","0.4657836","0.46458757","0.46410167","0.4639381","0.46362188","0.46339676","0.46314287","0.46116936","0.46097","0.46046662","0.46044332","0.46041468","0.4594768"],"string":"[\n \"0.62984484\",\n \"0.5671249\",\n \"0.5556696\",\n \"0.5556419\",\n \"0.5492904\",\n \"0.53954756\",\n \"0.53890973\",\n \"0.53359663\",\n \"0.5300576\",\n \"0.5287976\",\n \"0.5240326\",\n \"0.5182423\",\n \"0.51742876\",\n \"0.5162475\",\n \"0.5155768\",\n \"0.51150185\",\n \"0.51141423\",\n \"0.51031303\",\n \"0.5088816\",\n \"0.50455844\",\n \"0.5043136\",\n \"0.504052\",\n \"0.50128525\",\n \"0.49999657\",\n \"0.49889478\",\n \"0.49879476\",\n \"0.49778607\",\n \"0.49777117\",\n \"0.49764487\",\n \"0.49723947\",\n \"0.49723205\",\n \"0.49700797\",\n \"0.49488404\",\n \"0.49415165\",\n \"0.49406278\",\n \"0.49287677\",\n \"0.49233097\",\n \"0.49230877\",\n \"0.49167725\",\n \"0.49133906\",\n \"0.4895118\",\n \"0.48895344\",\n \"0.48733014\",\n \"0.4853158\",\n \"0.48477912\",\n \"0.48426315\",\n \"0.48412627\",\n \"0.4835641\",\n \"0.4835103\",\n \"0.48285064\",\n \"0.48075506\",\n \"0.47998103\",\n \"0.47938377\",\n \"0.47906697\",\n \"0.47587693\",\n \"0.47559595\",\n \"0.47558624\",\n \"0.475133\",\n \"0.475133\",\n \"0.4749933\",\n \"0.47487748\",\n \"0.47483754\",\n \"0.4743566\",\n \"0.4742448\",\n \"0.4735121\",\n \"0.47344598\",\n \"0.47342417\",\n \"0.47292358\",\n \"0.47276413\",\n \"0.47180295\",\n \"0.47141996\",\n \"0.47141996\",\n \"0.47141996\",\n \"0.4712501\",\n \"0.47059104\",\n \"0.47030643\",\n \"0.47021842\",\n \"0.46956694\",\n \"0.46954265\",\n \"0.46940002\",\n \"0.46932015\",\n \"0.46884263\",\n \"0.46820122\",\n \"0.46760076\",\n \"0.46750537\",\n \"0.4663475\",\n \"0.46585858\",\n \"0.4657836\",\n \"0.46458757\",\n \"0.46410167\",\n \"0.4639381\",\n \"0.46362188\",\n \"0.46339676\",\n \"0.46314287\",\n \"0.46116936\",\n \"0.46097\",\n \"0.46046662\",\n \"0.46044332\",\n \"0.46041468\",\n \"0.4594768\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.57537436"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81743,"cells":{"query":{"kind":"string","value":"operate CY gate (controlled X gate)."},"document":{"kind":"string","value":"def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def cy(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CY(), target=[control, target])","def CX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def covar(fx,cx):\n \n fx = np.array(fx)\n cx = np.array(cx)\n \n shape_fx = fx.shape\n shape_cx = cx.shape\n \n \n if shape_fx[1] != shape_cx[0]:\n print('-----------------------------------------')\n print(\"Shapes of fx and cx cannot be multiplied:\")\n print(shape_fx,\"x\",shape_cx)\n print('-----------------------------------------')\n raise ValueError('Input matrices are not compliant')\n \n cy = np.dot(np.dot(fx,cx),fx.T)\n \n print(\"Size of Cy matrix: \",np.shape(cy))\n \n return cy","def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])","def circuitSat(C):","def estimateCs(y, inp):\n\treturn 1 -(math.tanh(getK1(inp) - (y/getY90(inp)) / (2 * getD0(inp)) + (y/getY90(inp) - 1/3.0)**3 / (3 * getD0(inp))))**2","def YY(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.YY, qubit_expr)","def C(self,X):\n return(\n 0\n )","def Y(self, qubit_expr): \n self.apply_gate_operation('Y', qubit_expr)","def dcx(self, addr):\n\n self.reg.idx = self.reg.idx.inc(-1)\n self.reg.zerox_flag = self.reg.idx.eq_zero()","def TAY(self, *_):\n self.reg.Y = self.reg.A\n self.reg.N = self.reg.Y << 7\n self.reg.Z = self.reg.Y == 0","def run(self, dag):\n\n q_gate_list = ['cx', 'cy', 'cz', 'h', 'x', 'y', 'z']\n\n # Gate sets to be cancelled\n cancellation_sets = defaultdict(lambda: [])\n\n for wire in dag.wires:\n wire_name = \"{0}[{1}]\".format(str(wire.register.name), str(wire.index))\n wire_commutation_set = self.property_set['commutation_set'][wire_name]\n\n for com_set_idx, com_set in enumerate(wire_commutation_set):\n if com_set[0].type in ['in', 'out']:\n continue\n for node in com_set:\n num_qargs = len(node.qargs)\n if num_qargs == 1 and node.name in q_gate_list:\n cancellation_sets[(node.name, wire_name, com_set_idx)].append(node)\n if num_qargs == 1 and node.name in ['u1', 'rz', 't', 's']:\n cancellation_sets[('z_rotation', wire_name, com_set_idx)].append(node)\n elif num_qargs == 2 and node.qargs[0] == wire:\n second_op_name = \"{0}[{1}]\".format(str(node.qargs[1].register.name),\n str(node.qargs[1].index))\n q2_key = (node.name, wire_name, second_op_name,\n self.property_set['commutation_set'][(node, second_op_name)])\n cancellation_sets[q2_key].append(node)\n\n for cancel_set_key in cancellation_sets:\n set_len = len(cancellation_sets[cancel_set_key])\n if ((set_len) > 1 and cancel_set_key[0] in q_gate_list):\n gates_to_cancel = cancellation_sets[cancel_set_key]\n for c_node in gates_to_cancel[:(set_len // 2) * 2]:\n dag.remove_op_node(c_node)\n\n elif((set_len) > 1 and cancel_set_key[0] == 'z_rotation'):\n run = cancellation_sets[cancel_set_key]\n run_qarg = run[0].qargs[0]\n total_angle = 0.0 # lambda\n for current_node in run:\n if (current_node.condition is not None\n or len(current_node.qargs) != 1\n or current_node.qargs[0] != run_qarg):\n raise TranspilerError(\"internal error\")\n\n if current_node.name in ['u1', 'rz']:\n current_angle = float(current_node.op.params[0])\n elif current_node.name == 't':\n current_angle = sympy.pi / 4\n elif current_node.name == 's':\n current_angle = sympy.pi / 2\n\n # Compose gates\n total_angle = current_angle + total_angle\n\n # Replace the data of the first node in the run\n new_op = U1Gate(total_angle)\n new_qarg = QuantumRegister(1, 'q')[0]\n new_dag = DAGCircuit()\n new_dag.add_qreg(new_qarg.register)\n new_dag.apply_operation_back(new_op, [new_qarg])\n dag.substitute_node_with_dag(run[0], new_dag)\n\n # Delete the other nodes in the run\n for current_node in run[1:]:\n dag.remove_op_node(current_node)\n\n return dag","def C(self, y, x):\n return self.minor(y,x).det()*(-1.0)**(y+x+2.0)","def DEY(self, *_):\n self._dec_or_inc_register('Y', increment=False)","def compute_operator(self, Xc, Yc):\n\n U, s, V = self._compute_svd(Xc)\n\n self._Atilde = (np.linalg.multi_dot([U.T.conj(), (Yc), (V)])\n * np.reciprocal(s))\n\n self._compute_eigenquantities()\n self._compute_modes(Yc, U, s, V)\n\n self._slow_modes = (np.abs(old_div(np.log(self.eigenvalues),\n self._eigs_divider))) <= self._rho","def xkcd():","def c( self , y , r , t = 0 ):\n \n u = np.zeros(self.m) # State derivative vector\n \n raise NotImplementedError\n \n return u","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def test_cx_gate_nondeterministic_minimal_basis_gates(self):\n shots = 2000\n circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_2q_clifford.cx_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def cy(self):\n\t\txfrm = self.xfrm\n\t\tif xfrm is None:\n\t\t\treturn None\n\t\treturn xfrm.cy","def estimateCsKnownY90(y, inp):\n\treturn 1 -(math.tanh(getK1(inp) - y / (2 * getD0(inp)) + (y - 1/3.0)**3 / (3 * getD0(inp))))**2","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def test_y_gate_deterministic_minimal_basis_gates(self):\n shots = 100\n circuits = ref_1q_clifford.y_gate_circuits_deterministic(final_measure=True)\n targets = ref_1q_clifford.y_gate_counts_deterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0)","def DEX(self, *_):\n self._dec_or_inc_register('X', increment=False)","def test_cx_equivalence_1cx(self, seed=1):\n state = np.random.default_rng(seed)\n rnd = 2 * np.pi * state.random(size=12)\n\n qr = QuantumRegister(2, name=\"q\")\n qc = QuantumCircuit(qr)\n\n qc.u(rnd[0], rnd[1], rnd[2], qr[0])\n qc.u(rnd[3], rnd[4], rnd[5], qr[1])\n\n qc.cx(qr[1], qr[0])\n\n qc.u(rnd[6], rnd[7], rnd[8], qr[0])\n qc.u(rnd[9], rnd[10], rnd[11], qr[1])\n\n sim = UnitarySimulatorPy()\n unitary = execute(qc, sim).result().get_unitary()\n self.assertEqual(two_qubit_cnot_decompose.num_basis_gates(unitary), 1)\n self.assertTrue(Operator(two_qubit_cnot_decompose(unitary)).equiv(unitary))","def test_ccx_gate_nondeterministic_minimal_basis_gates(self):\n shots = 2000\n circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_non_clifford.ccx_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def CZ(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CZ, qubit_expr)","def test_csc():\n c=14\n assert {'diff':EF.csc(c).der, 'value': EF.csc(c).val}=={'diff':0, 'value': 1/math.sin(c)}","def _control_predefined(operation, num_ctrl_qubits):\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\n if num_ctrl_qubits == 1:\n import qiskit.extensions.standard.cx\n cgate = qiskit.extensions.standard.cx.CnotGate()\n else:\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n elif operation.name == 'y':\n import qiskit.extensions.standard.cy\n cgate = qiskit.extensions.standard.cy.CyGate()\n elif operation.name == 'z':\n import qiskit.extensions.standard.cz\n cgate = qiskit.extensions.standard.cz.CzGate()\n elif operation.name == 'h':\n import qiskit.extensions.standard.ch\n cgate = qiskit.extensions.standard.ch.CHGate()\n elif operation.name in {'rx', 'ry', 'rz'}:\n if operation.name == 'rx':\n import qiskit.extensions.standard.crx\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\n elif operation.name == 'ry':\n import qiskit.extensions.standard.cry\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\n else: # operation.name == 'rz'\n import qiskit.extensions.standard.crz\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\n if num_ctrl_qubits == 1:\n return cgate\n else:\n # only predefined for one control qubit\n return cgate.control(num_ctrl_qubits - 1)\n elif operation.name == 'swap':\n import qiskit.extensions.standard.cswap\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\n elif operation.name == 'u1':\n import qiskit.extensions.standard.cu1\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\n elif operation.name == 'u3':\n import qiskit.extensions.standard.cu3\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\n elif operation.name == 'cx':\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n else:\n raise QiskitError('No standard controlled gate for \"{}\"'.format(\n operation.name))\n return cgate","def electrical_jacobian(self, state, u_in, omega, *_):\n pass","def test_cx_gate_deterministic_minimal_basis_gates(self):\n shots = 100\n circuits = ref_2q_clifford.cx_gate_circuits_deterministic(final_measure=True)\n targets = ref_2q_clifford.cx_gate_counts_deterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0)","def test_cnot():\n\n program = dedent(\n \"\"\"\\\n register q0[0]\n register q1[1]\n X q0\n CNOT q0 q1\n \"\"\"\n )\n\n result = run(program, run_gate_array, return_distribution=True)\n assert isclose(result, [0.0, 0.0, 0.0, 1.0]).all()","def evaluate_c(self, x, out=None, **kwargs):\n return np.zeros(0)","def ccx(self, q0, q1, q2, ctrl=None):\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\n return self","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def compile(self, seq, registers):\n\n # Check which modes are actually being used\n used_modes = []\n for operations in seq:\n modes = [modes_label.ind for modes_label in operations.reg]\n used_modes.append(modes)\n\n used_modes = list(set(item for sublist in used_modes for item in sublist))\n\n # dictionary mapping the used modes to consecutive non-negative integers\n dict_indices = {used_modes[i]: i for i in range(len(used_modes))}\n nmodes = len(used_modes)\n\n # We start with an identity then sequentially update with the gate transformations\n T = np.identity(nmodes, dtype=np.complex128)\n\n # Now we will go through each operation in the sequence `seq` and apply it to T\n for operations in seq:\n name = operations.op.__class__.__name__\n params = par_evaluate(operations.op.p)\n modes = [modes_label.ind for modes_label in operations.reg]\n if name == \"Rgate\":\n G = np.exp(1j * params[0])\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\n elif name == \"LossChannel\":\n G = np.sqrt(params[0])\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\n elif name == \"Interferometer\":\n U = params[0]\n if U.shape == (1, 1):\n T = _apply_one_mode_gate(U[0, 0], T, dict_indices[modes[0]])\n elif U.shape == (2, 2):\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\n else:\n modes = [dict_indices[mode] for mode in modes]\n U_expand = np.eye(nmodes, dtype=np.complex128)\n U_expand[np.ix_(modes, modes)] = U\n T = U_expand @ T\n elif name == \"PassiveChannel\":\n T0 = params[0]\n if T0.shape == (1, 1):\n T = _apply_one_mode_gate(T0[0, 0], T, dict_indices[modes[0]])\n elif T0.shape == (2, 2):\n T = _apply_two_mode_gate(T0, T, dict_indices[modes[0]], dict_indices[modes[1]])\n else:\n modes = [dict_indices[mode] for mode in modes]\n T0_expand = np.eye(nmodes, dtype=np.complex128)\n T0_expand[np.ix_(modes, modes)] = T0\n T = T0_expand @ T\n elif name == \"BSgate\":\n G = _beam_splitter_passive(params[0], params[1])\n T = _apply_two_mode_gate(G, T, dict_indices[modes[0]], dict_indices[modes[1]])\n elif name == \"MZgate\":\n v = np.exp(1j * params[0])\n u = np.exp(1j * params[1])\n U = 0.5 * np.array([[u * (v - 1), 1j * (1 + v)], [1j * u * (1 + v), 1 - v]])\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\n elif name == \"sMZgate\":\n exp_sigma = np.exp(1j * (params[0] + params[1]) / 2)\n delta = (params[0] - params[1]) / 2\n U = exp_sigma * np.array(\n [[np.sin(delta), np.cos(delta)], [np.cos(delta), -np.sin(delta)]]\n )\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\n\n ord_reg = [r for r in list(registers) if r.ind in used_modes]\n ord_reg = sorted(list(ord_reg), key=lambda x: x.ind)\n\n return [Command(ops.PassiveChannel(T), ord_reg)]","def cycloid(x2, y2, N=100):\n\n # First find theta2 from (x2, y2) numerically (by Newton-Rapheson).\n def f(theta):\n return y2/x2 - (1-np.cos(theta))/(theta-np.sin(theta))\n theta2 = newton(f, np.pi/2)\n\n # The radius of the circle generating the cycloid.\n R = y2 / (1 - np.cos(theta2))\n\n theta = np.linspace(0, theta2, N)\n x = R * (theta - np.sin(theta))\n y = R * (1 - np.cos(theta))\n\n # The time of travel\n T = theta2 * np.sqrt(R / g)\n print('T(cycloid) = {:.3f}'.format(T))\n return x, y, T","def test_ud_cnot():\n program = dedent(\n \"\"\"\\\n register q0[0]\n register q1[1]\n register q2[2]\n register q3[3]\n X q2\n CNOT q2 q0\n \"\"\"\n )\n\n result = run(program, run_gate_array)\n assert isclose(result, [1.0, 0.0, 1.0, 0.0]).all()","def bcs(self, arg):\n\n self.pc += arg if self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def test_cz_gate_nondeterministic_minimal_basis_gates(self):\n shots = 2000\n circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_2q_clifford.cz_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def test_cx_equivalence_2cx(self, seed=2):\n state = np.random.default_rng(seed)\n rnd = 2 * np.pi * state.random(size=18)\n\n qr = QuantumRegister(2, name=\"q\")\n qc = QuantumCircuit(qr)\n\n qc.u(rnd[0], rnd[1], rnd[2], qr[0])\n qc.u(rnd[3], rnd[4], rnd[5], qr[1])\n\n qc.cx(qr[1], qr[0])\n\n qc.u(rnd[6], rnd[7], rnd[8], qr[0])\n qc.u(rnd[9], rnd[10], rnd[11], qr[1])\n\n qc.cx(qr[0], qr[1])\n\n qc.u(rnd[12], rnd[13], rnd[14], qr[0])\n qc.u(rnd[15], rnd[16], rnd[17], qr[1])\n\n sim = UnitarySimulatorPy()\n unitary = execute(qc, sim).result().get_unitary()\n self.assertEqual(two_qubit_cnot_decompose.num_basis_gates(unitary), 2)\n self.assertTrue(Operator(two_qubit_cnot_decompose(unitary)).equiv(unitary))","def step1c(self):\n\t\tif (self.ends(\"y\") and self.vowelinstem()):\n\t\t\tself.b = self.b[:self.k] + 'i' + self.b[self.k+1:]","def CPY(self, value):\n self._compare(value, 'Y')","def test_ccx_gate_deterministic_minimal_basis_gates(self):\n shots = 100\n circuits = ref_non_clifford.ccx_gate_circuits_deterministic(final_measure=True)\n targets = ref_non_clifford.ccx_gate_counts_deterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0)","def evaluate_c(self, x, out=None, **kwargs):\n return self._base_nlp.evaluate_c(x, out=out, **kwargs)","def test_ccx_gate_nondeterministic_default_basis_gates(self):\n shots = 2000\n circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_non_clifford.ccx_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots)\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def cy(y):\n return pic_height + ch(y - global_min_y)","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def gcxgcy_to_cxcy(gcxgcy, priors_cxcy):\n\n return torch.cat([gcxgcy[:, :2] * priors_cxcy[:, 2:] / 10 + priors_cxcy[:, :2], # c_x, c_y\n torch.exp(gcxgcy[:, 2:] / 5) * priors_cxcy[:, 2:]], 1) # w, h","def cx():","def C(self,t,K,c0):\n #ode(self.dc_dt,c0,t,args=(k,)).set_integrator('lsoda')\n #ode(self.dc_dt,c0,t,args=(k,)).set_integrator('vode', method='bdf', order=15)\n \n # if we have any negative times we assume they occur before the \n # reaction starts hence all negative times are assigned concentration \n # c0\n \n ## could switch to something like ode15s that the oiginal matlab code \n ## uses - can odeint cope with equations as stiff as we need?\n ## to use integrate.ode need order of arguments in dc_dt to switch\n \n #r = scipy.integrate.ode(self.dc_dt)\n #r = r.set_integrator('vode', method='bdf', order=15,nsteps=3000)\n #r = r.set_initial_value(c0)\n #r = r.set_f_params((K,))\n #r.integrate(t)\n \n static_times = t[t<0]\n dynamic_times = t[t>=0]\n\n static_C = np.array([c0 for _ in static_times])\n\n # odeint always takes the first time point as t0\n # our t0 is always 0 (removing t0 occures before we integrate)\n # so if the first time point is not 0 we add it \n \n if not dynamic_times.any() or dynamic_times[0]:\n #fancy indexing returns a copy so we can do this\n dynamic_times = np.hstack([[0],dynamic_times]) \n dynamic_C = odeint(self.dc_dt,c0,dynamic_times,args=(K,))[1:]\n else:\n dynamic_C = odeint(self.dc_dt,c0,dynamic_times,args=(K,))\n \n if static_C.any():\n return np.vstack([static_C,dynamic_C])\n else:\n return dynamic_C","def csw(self, q0, q1, q2, ctrl=None):\n self.cx(q2,q1,ctrl=ctrl).ccx(q0,q1,q2,ctrl=ctrl).cx(q2,q1,ctrl=ctrl)\n return self","def test_cx_equivalence_0cx(self, seed=0):\n state = np.random.default_rng(seed)\n rnd = 2 * np.pi * state.random(size=6)\n\n qr = QuantumRegister(2, name=\"q\")\n qc = QuantumCircuit(qr)\n\n qc.u(rnd[0], rnd[1], rnd[2], qr[0])\n qc.u(rnd[3], rnd[4], rnd[5], qr[1])\n\n sim = UnitarySimulatorPy()\n unitary = execute(qc, sim).result().get_unitary()\n self.assertEqual(two_qubit_cnot_decompose.num_basis_gates(unitary), 0)\n self.assertTrue(Operator(two_qubit_cnot_decompose(unitary)).equiv(unitary))","def release_cytokine(self) :\n for cy in self.cytokine :\n if self.cytosol.get(cy, False) and self.cytosol[cy] > 0:\n cy(self.pos, tool.rand_2D(1.2))\n self.cytosol[cy] -= 1\n else : \n self.ribosome.mrna(cy, 100)\n self.cytokine.clear()","def _compute_carry_and_output(self, x, h_tm1, c_tm1):\n x_i, x_f, x_c, x_o = x\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\n i = self.recurrent_activation(\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\n f = self.recurrent_activation(x_f + K.dot(\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\n o = self.recurrent_activation(\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\n return c, o","def AlphaCyc(ss, train):\n\n if ss.Win != 0:\n ss.Win.PollEvents() # this is essential for GUI responsiveness while running\n viewUpdt = ss.TrainUpdt.value\n if not train:\n viewUpdt = ss.TestUpdt.value\n\n # update prior weight changes at start, so any DWt values remain visible at end\n # you might want to do this less frequently to achieve a mini-batch update\n # in which case, move it out to the TrainTrial method where the relevant\n # counters are being dealt with.\n if train:\n ss.Net.WtFmDWt()\n\n ss.Net.AlphaCycInit(train)\n ss.Time.AlphaCycStart()\n for qtr in range(4):\n for cyc in range(ss.Time.CycPerQtr):\n ss.Net.Cycle(ss.Time)\n ss.Time.CycleInc()\n if ss.ViewOn:\n if viewUpdt == leabra.Cycle:\n if cyc != ss.Time.CycPerQtr-1: # will be updated by quarter\n ss.UpdateView(train)\n if viewUpdt == leabra.FastSpike:\n if (cyc+1)%10 == 0:\n ss.UpdateView(train)\n ss.Net.QuarterFinal(ss.Time)\n ss.Time.QuarterInc()\n if ss.ViewOn:\n if viewUpdt <= leabra.Quarter:\n ss.UpdateView(train)\n if viewUpdt == leabra.Phase:\n if qtr >= 2:\n ss.UpdateView(train)\n\n if train:\n ss.Net.DWt()\n if ss.ViewOn and viewUpdt == leabra.AlphaCycle:\n ss.UpdateView(train)","def test_cx_gate_nondeterministic_default_basis_gates(self):\n shots = 2000\n circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_2q_clifford.cx_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots)\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def test_number_to_clifford_mapping_single_gate(self):\n transpiled_cliff_list = [\n SXGate(),\n RZGate(np.pi),\n RZGate(-np.pi),\n RZGate(np.pi / 2),\n RZGate(-np.pi / 2),\n ]\n general_cliff_list = [\n IGate(),\n HGate(),\n SdgGate(),\n SGate(),\n XGate(),\n SXGate(),\n YGate(),\n ZGate(),\n ]\n for inst in transpiled_cliff_list + general_cliff_list:\n qc_from_inst = QuantumCircuit(1)\n qc_from_inst.append(inst, [0])\n num = num_from_1q_circuit(qc_from_inst)\n qc_from_num = CliffordUtils.clifford_1_qubit_circuit(num)\n self.assertTrue(Operator(qc_from_num).equiv(Operator(qc_from_inst)))","def INY(self, *_):\n self._dec_or_inc_register('Y', increment=True)","def TYA(self, *_):\n self.reg.A = self.reg.Y\n self.reg.N = self.reg.A << 7\n self.reg.Z = self.reg.A == 0","def casadi_ode(self, t, x, u, w):\n v = u[0]\n thetadot = u[1]\n theta = x[2]\n f = cs.vertcat(v * cs.cos(theta), v * cs.sin(theta), thetadot)\n if self.use_nonlinear_noise_model:\n w_vec = cs.vertcat(self.scale[0]*(cs.cos(theta) * w[0] - cs.sin(theta) * w[1]),\n self.scale[1]*(cs.sin(theta) * w[0] + cs.cos(theta) * w[1]),\n self.scale[2]*(v * w[2]))\n else:\n w_vec = w\n return f + w_vec","def test_cz_gate_nondeterministic_default_basis_gates(self):\n shots = 2000\n circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_2q_clifford.cz_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots)\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def conj(x, *args, **kwargs):\n raise NotImplementedError","def alg(c):\n return c[0]*G[0] + c[1]*G[1] + c[2]*G[2]","def test_cx_gate_nondeterministic_waltz_basis_gates(self):\n shots = 2000\n circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_2q_clifford.cx_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='u1,u2,u3,cx')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def test_cz_gate_deterministic_minimal_basis_gates(self):\n shots = 100\n circuits = ref_2q_clifford.cz_gate_circuits_deterministic(final_measure=True)\n targets = ref_2q_clifford.cz_gate_counts_deterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0)","def _collab_curate(self, sender, amount=0):\n\n curate_params = {'hDAO_amount': 100, 'objkt_id': 100_000}\n self.result = self.collab.curate(curate_params).interpret(\n storage=self.collab_storage, sender=sender, amount=amount)\n\n assert len(self.result.operations) == 1\n assert self.result.operations[0]['parameters']['entrypoint'] == 'curate'\n assert self.result.operations[0]['parameters']['value']['args'][0] == {'int': '100'}\n assert self.result.operations[0]['parameters']['value']['args'][1] == {'int': '100000'}\n self.assertEqual(\n self.result.operations[0]['destination'],\n self.collab_storage['minterAddress']\n )","def open_circ():\n\n set_mode(mode_cc) # set operation mode to CC\n time.sleep(.250)\n set_CC_current(cc_current=0) # set CC mode current to 0 amps\n time.sleep(.1)\n \n oc_vals = get_input_values() # read open circuits levels\n oc_data_point = data_point(oc_vals) # create data point for open circuit measurement\n voc = oc_data_point[3] # open circuit voltage measurement\n print('Open circuit voltage: ', voc)\n write_data_tofile(oc_data_point) # write data to file\n \n return voc","def test_circuit_generation_from_sec(self):\n\n backend = CrossResonanceHamiltonianBackend()\n\n expr = cr_hamiltonian.CrossResonanceHamiltonian(\n qubits=(0, 1),\n flat_top_widths=[500],\n unit=\"ns\",\n amp=0.1,\n sigma=20,\n risefall=2,\n )\n\n nearlest_16 = 576\n\n with pulse.build(default_alignment=\"left\", name=\"cr\") as ref_cr_sched:\n pulse.play(\n pulse.GaussianSquare(\n nearlest_16,\n amp=0.1,\n sigma=20,\n width=500,\n ),\n pulse.ControlChannel(0),\n )\n pulse.delay(nearlest_16, pulse.DriveChannel(0))\n pulse.delay(nearlest_16, pulse.DriveChannel(1))\n\n cr_gate = circuit.Gate(\"cr_gate\", num_qubits=2, params=[500])\n expr_circs = expr.circuits(backend)\n\n x0_circ = QuantumCircuit(2, 1)\n x0_circ.append(cr_gate, [0, 1])\n x0_circ.h(1)\n x0_circ.measure(1, 0)\n\n x1_circ = QuantumCircuit(2, 1)\n x1_circ.x(0)\n x1_circ.append(cr_gate, [0, 1])\n x1_circ.h(1)\n x1_circ.measure(1, 0)\n\n y0_circ = QuantumCircuit(2, 1)\n y0_circ.append(cr_gate, [0, 1])\n y0_circ.sdg(1)\n y0_circ.h(1)\n y0_circ.measure(1, 0)\n\n y1_circ = QuantumCircuit(2, 1)\n y1_circ.x(0)\n y1_circ.append(cr_gate, [0, 1])\n y1_circ.sdg(1)\n y1_circ.h(1)\n y1_circ.measure(1, 0)\n\n z0_circ = QuantumCircuit(2, 1)\n z0_circ.append(cr_gate, [0, 1])\n z0_circ.measure(1, 0)\n\n z1_circ = QuantumCircuit(2, 1)\n z1_circ.x(0)\n z1_circ.append(cr_gate, [0, 1])\n z1_circ.measure(1, 0)\n\n ref_circs = [x0_circ, y0_circ, z0_circ, x1_circ, y1_circ, z1_circ]\n for c in ref_circs:\n c.add_calibration(cr_gate, (0, 1), ref_cr_sched)\n\n self.assertListEqual(expr_circs, ref_circs)","def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self","def test_scalar_coeff_cc():\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\n kappa = Symbol('kappa', real=True)\n a1 = Destroy(hs=hs_1)\n a2 = Destroy(hs=hs_2)\n\n jc_expr = (\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\n )\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == I * kappa * OperatorPlusMinusCC(\n a1.dag() * a2, sign=-1\n )\n expanded = simplified.doit()\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())","def BCS(self, value):\n if self.reg.C:\n self.reg.PC += value","def convert_to_circuit(x):\n y = np.arcsin(x)\n z = np.arccos(x**2)\n qubits = cirq.GridQubit.rect(5, 1)\n circuit = cirq.Circuit()\n for i in range(5):\n circuit.append(cirq.ry(y).on(qubits[i]))\n circuit.append(cirq.rz(z).on(qubits[i]))\n return circuit","def test_simple_cc():\n hs_c = LocalSpace('c', dimension=3)\n hs_q = LocalSpace('q1', basis=('g', 'e'))\n Delta_1 = Symbol('Delta_1')\n Omega_1 = Symbol('Omega_1')\n g_1 = Symbol('g_1')\n a = Destroy(hs=hs_c)\n a_dag = Create(hs=hs_c)\n sig_p = LocalSigma('e', 'g', hs=hs_q)\n sig_m = LocalSigma('g', 'e', hs=hs_q)\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\n assert (\n srepr(simplified.term)\n == \"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \"\n \"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \"\n \"basis=('g', 'e')))), sign=-1)\"\n )\n expanded = simplified.doit()\n assert expanded == jc_expr","def test_cfu_cycles(self):\n # Input: (function, in0, in1, cmd_valid, rsp_ready)\n # Output: (result, rsp_valid, cmd_ready)\n X = None\n DATA = [\n # Nothing\n ((0, 0, 0, 0, 0), (X, 0, 1)),\n # Same cycle instruction, CPU not ready\n ((0, 1, 2, 1, 0), (3, 1, 1)),\n ((0, 0, 0, 0, 1), (3, 1, 0)),\n ((0, 0, 0, 0, 0), (X, 0, 1)),\n # Multi-cycle instruction, CPU ready\n ((3, 3, 0, 1, 1), (X, 0, 1)),\n ((0, 0, 0, 0, 1), (X, 0, 0)),\n ((0, 0, 0, 0, 1), (X, 0, 0)),\n ((0, 0, 0, 0, 1), (6, 1, 0)),\n # Same cycle instruction, CPU ready\n ((0, 5, 3, 1, 1), (8, 1, 1)),\n # Multi-cycle instruction, CPU not ready\n ((3, 2, 0, 1, 0), (X, 0, 1)),\n ((0, 0, 0, 0, 0), (X, 0, 0)),\n ((0, 0, 0, 0, 0), (2, 1, 0)),\n ((0, 0, 0, 0, 1), (2, 1, 0)),\n # Multi-cycle instruction, but always ready next cycle\n ((4, 3, 5, 1, 1), (X, 0, 1)),\n ((0, 0, 0, 0, 1), (8, 1, 0)),\n # CPU not ready\n ((4, 3, 4, 1, 0), (X, 0, 1)),\n ((0, 0, 0, 0, 0), (X, 1, 0)),\n ((0, 0, 0, 0, 0), (X, 1, 0)),\n ((0, 0, 0, 0, 1), (7, 1, 0)),\n # Fallback instruction - same cycle, CPU ready\n ((7, 0, 0, 1, 1), (X, 1, 1)),\n ]\n\n def process():\n for n, (inputs, expected_outputs) in enumerate(DATA):\n func, i0, i1, cmd_valid, rsp_ready = inputs\n exp_result, exp_rsp_valid, exp_cmd_ready = expected_outputs\n yield self.dut.cmd_function_id.eq(func)\n yield self.dut.cmd_in0.eq(i0)\n yield self.dut.cmd_in1.eq(i1)\n yield self.dut.cmd_valid.eq(cmd_valid)\n yield self.dut.rsp_ready.eq(rsp_ready)\n yield Delay(0.1)\n if exp_result is not None:\n self.assertEqual((yield self.dut.rsp_out), exp_result)\n if exp_rsp_valid is not None:\n self.assertEqual((yield self.dut.rsp_valid), exp_rsp_valid)\n # We don't currently support returning non-OK responses, so\n # if our response is valid, it must be OK.\n if exp_rsp_valid:\n self.assertTrue((yield self.dut.rsp_ok))\n if exp_cmd_ready is not None:\n self.assertEqual((yield self.dut.cmd_ready), exp_cmd_ready)\n yield\n self.run_sim(process, False)","def csb(self):\n\n def myfunc(incident_energy):\n return XrayLibWrap_Energy(self.Z, \"csb\", incident_energy)\n\n return myfunc","def _calc_C(self, lambdify=True):\n\n C = None\n C_func = None\n # check to see if we have our term saved in file\n C, C_func = self._load_from_file('C', lambdify)\n\n if C is None and C_func is None:\n # if no saved file was loaded, generate function\n print('Generating centrifugal and Coriolis compensation function')\n\n # first get the inertia matrix\n M = self._calc_M(lambdify=False)\n\n # C_{kj} = sum_i c_{ijk}(q) \\dot{q}_i\n # c_{ijk} = 1/2 * sum_i (\\frac{\\partial M_{kj}}{\\partial q_j} +\n # \\frac{\\partial M_{ki}}{\\partial q_j} - \\frac{\\partial M_{ij}}\n # {\\partial q_k})\n C = sp.zeros(self.N_JOINTS, self.N_JOINTS)\n for kk in range(self.N_JOINTS):\n for jj in range(self.N_JOINTS):\n for ii in range(self.N_JOINTS):\n dMkjdqi = M[kk, jj].diff(self.q[ii])\n dMkidqj = M[kk, ii].diff(self.q[jj])\n dMijdqk = M[ii, jj].diff(self.q[kk])\n C[kk, jj] += .5 * (dMkjdqi + dMkidqj - dMijdqk) * self.dq[ii]\n C[kk, jj] = C[kk, jj]\n C = sp.Matrix(C)\n\n # save to file\n abr_control.utils.os_utils.makedirs(\n '%s/C' % self.config_folder)\n cloudpickle.dump(C, open(\n '%s/C/C' % self.config_folder, 'wb'))\n\n if lambdify is False:\n # if should return expression not function\n return C\n\n if C_func is None:\n C_func = self._generate_and_save_function(\n filename='C', expression=C,\n parameters=self.q+self.dq)\n return C_func","def test_cnot_rxx_decompose(self):\n cnot = Operator(CXGate())\n decomps = [\n cnot_rxx_decompose(),\n cnot_rxx_decompose(plus_ry=True, plus_rxx=True),\n cnot_rxx_decompose(plus_ry=True, plus_rxx=False),\n cnot_rxx_decompose(plus_ry=False, plus_rxx=True),\n cnot_rxx_decompose(plus_ry=False, plus_rxx=False),\n ]\n for decomp in decomps:\n self.assertTrue(cnot.equiv(decomp))","def cx(x):\n return cw(x - global_min_x)","def two_activation(self, output_reg):\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\n self._q_neuron.cx(self.inputs[0], self._output[output_reg])\n self._q_neuron.cx(self.inputs[1], self._output[output_reg])","def bcc(self, arg):\n\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def phasesin14xymult_cfix(param, xyord,crossord,t, x, y):\n # 2010-04-27 11:49 IJC: Created\n # 2010-05-28 15:42 IJC: Added x*y cross-terms\n # 2010-07-21 13:02 IJC: switched to a mostly-additive model\n\n param = array(param,copy=True)\n x = array(x,copy=True)\n y = array(y,copy=True)\n t = array(t,copy=True)\n\n xparam = zeros((0,14),float)\n yparam = zeros((0,14),float)\n crossparam = zeros((0,14),float)\n\n cparam = param[3:17].copy()\n # Ensure that prod(1.+cparam) equals zero\n cparam[0] = 1./(1.+cparam[1::]).prod() - 1.\n if xyord>=1:\n for ii in range(xyord):\n xparam = vstack((xparam,param[17+ii*28:31+ii*28]))\n yparam = vstack((yparam,param[31+ii*28:45+ii*28]))\n\n lastxyparamind = 45+(xyord-1)*28\n if crossord>=1:\n for ii in [0]: #range(crossparam):\n crossparam = vstack((crossparam,param[lastxyparamind:lastxyparamind+(ii+1)*14]))\n\n #cparam -= mean(cparam)\n param[2] = param[2] % (2*pi)\n \n if len(t.shape)==1:\n was1d = True\n t = t.reshape(14, len(t)/14.)\n x = x.reshape(14, len(x)/14.)\n y = y.reshape(14, len(y)/14.)\n else:\n was1d = False\n\n # Subtract the mean from the X and Y data\n x -= x.mean(1).reshape(14,1)\n y -= y.mean(1).reshape(14,1)\n\n # Zeroth-order model:\n ret = param[0] - abs(param[1]) *cos(2*pi*t +param[2])\n\n # Apply constant and X/Y offsets:\n #ret *= (1. + tile(cparam, (t.shape[1],1)).transpose())\n offset_term = (1. + tile(cparam, (t.shape[1],1)).transpose())\n if xyord>=1:\n for ii in range(xyord):\n offset_term += tile(xparam[ii], (t.shape[1],1)).transpose()*x**(ii+1)\n offset_term += tile(yparam[ii], (t.shape[1],1)).transpose()*y**(ii+1)\n\n if crossord>=1:\n for ii in [0]: \n offset_term += tile(crossparam[ii], (t.shape[1],1)).transpose()*x*y\n\n # Apply the (1+c+dx+ey) term:\n ret *= offset_term\n\n if was1d:\n ret = ret.ravel()\n\n return ret","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def test_y_gate_deterministic_default_basis_gates(self):\n shots = 100\n circuits = ref_1q_clifford.y_gate_circuits_deterministic(final_measure=True)\n targets = ref_1q_clifford.y_gate_counts_deterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots)\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0)","def test_cz_gate_nondeterministic_waltz_basis_gates(self):\n shots = 2000\n circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_2q_clifford.cz_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='u1,u2,u3,cx')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def test_ccx_gate_deterministic_default_basis_gates(self):\n shots = 100\n circuits = ref_non_clifford.ccx_gate_circuits_deterministic(final_measure=True)\n targets = ref_non_clifford.ccx_gate_counts_deterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots)\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0)","def convert_C_instruction(self, instruction):\n comp, dest, jump = self.parse(instruction)\n\n return f\"111{convert_comp(comp)}{convert_dest(dest)}\" \\\n f\"{convert_jump(jump)}\"","def set_cylindrical(self, cyl_ang):\n self.FCYL = 1\n self.CIL_ANG = cyl_ang","def DynamicsCo(x, t, T0, alpha, cost_co, cost_ch, K_co, K_ch, n, r):\n y=np.zeros([np.size(x)])\n D=np.zeros([2]) \n #define fitnss\n D[0]=dmax*x[0]**n/(K_co**n+x[0]**n) #cooperator\n D[1]=dmax*x[0]**n/(K_ch**n+x[0]**n) #cheater \n #degradation\n deg=fmax*x[1]/(x[1]+Kd) \n #ODE of eco-evo dynamics\n y[0]=alpha*T0-deg*x[0]-alpha*x[0] #dt/dt\n y[1]=x[1]*(r*(1-cost_co)*(1-x[1]-x[2])-D[0]-alpha)#d Co/dt\n y[2]=x[2]*(r*(1-cost_ch)*(1-x[1]-x[2])-D[1]-alpha) #d Ch/dt\n \n return y","def Cintegrate(phi,\n HC, \n dt):\n\n phip1 = phi-HC.dot(phi)*dt\n \n return phip1","def control(operation, num_ctrl_qubits=1, label=None):\n from math import pi\n # pylint: disable=cyclic-import\n import qiskit.circuit.controlledgate as controlledgate\n from qiskit.circuit.quantumregister import QuantumRegister\n from qiskit.circuit.quantumcircuit import QuantumCircuit\n # pylint: disable=unused-import\n import qiskit.extensions.standard.multi_control_rotation_gates\n import qiskit.extensions.standard.multi_control_toffoli_gate\n import qiskit.extensions.standard.multi_control_u1_gate\n\n q_control = QuantumRegister(num_ctrl_qubits, name='control')\n q_target = QuantumRegister(operation.num_qubits, name='target')\n q_ancillae = None # TODO: add\n\n qc = QuantumCircuit(q_control, q_target)\n\n if operation.name == 'x' or (\n isinstance(operation, controlledgate.ControlledGate) and\n operation.base_gate_name == 'x'):\n qc.mct(q_control[:] + q_target[:-1],\n q_target[-1],\n None,\n mode='noancilla')\n elif operation.name == 'rx':\n qc.mcrx(operation.definition[0][0].params[0], q_control, q_target[0],\n use_basis_gates=True)\n elif operation.name == 'ry':\n qc.mcry(operation.definition[0][0].params[0], q_control, q_target[0],\n q_ancillae, use_basis_gates=True)\n elif operation.name == 'rz':\n qc.mcrz(operation.definition[0][0].params[0], q_control, q_target[0],\n use_basis_gates=True)\n else:\n bgate = _unroll_gate(operation, ['u1', 'u3', 'cx'])\n # now we have a bunch of single qubit rotation gates and cx\n for rule in bgate.definition:\n if rule[0].name == 'u3':\n theta, phi, lamb = rule[0].params\n if phi == -pi/2 and lamb == pi/2:\n qc.mcrx(theta, q_control, q_target[rule[1][0].index],\n use_basis_gates=True)\n elif phi == 0 and lamb == 0:\n qc.mcry(theta, q_control, q_target[rule[1][0].index],\n q_ancillae, mode='noancilla', use_basis_gates=True)\n elif theta == 0 and phi == 0:\n qc.mcrz(lamb, q_control, q_target[rule[1][0].index],\n use_basis_gates=True)\n else:\n qc.mcrz(lamb, q_control, q_target[rule[1][0].index],\n use_basis_gates=True)\n qc.mcry(theta, q_control, q_target[rule[1][0].index],\n q_ancillae, use_basis_gates=True)\n qc.mcrz(phi, q_control, q_target[rule[1][0].index],\n use_basis_gates=True)\n elif rule[0].name == 'u1':\n qc.mcu1(rule[0].params[0], q_control, q_target[rule[1][0].index])\n elif rule[0].name == 'cx':\n qc.mct(q_control[:] + [q_target[rule[1][0].index]],\n q_target[rule[1][1].index],\n None,\n mode='noancilla')\n else:\n raise QiskitError('gate contains non-controllable intructions')\n instr = qc.to_instruction()\n if isinstance(operation, controlledgate.ControlledGate):\n new_num_ctrl_qubits = num_ctrl_qubits + operation.num_ctrl_qubits\n base_name = operation.base_gate_name\n base_gate = operation.base_gate\n base_gate_name = operation.base_gate_name\n else:\n new_num_ctrl_qubits = num_ctrl_qubits\n base_name = operation.name\n base_gate = operation.__class__\n base_gate_name = operation.name\n # In order to maintain some backward compatibility with gate names this\n # uses a naming convention where if the number of controls is <=2 the gate\n # is named like \"cc<base_gate_name>\", else it is named like\n # \"c<num_ctrl_qubits><base_name>\".\n if new_num_ctrl_qubits > 2:\n ctrl_substr = 'c{0:d}'.format(new_num_ctrl_qubits)\n else:\n ctrl_substr = ('{0}' * new_num_ctrl_qubits).format('c')\n new_name = '{0}{1}'.format(ctrl_substr, base_name)\n cgate = controlledgate.ControlledGate(new_name,\n instr.num_qubits,\n operation.params,\n label=label,\n num_ctrl_qubits=new_num_ctrl_qubits,\n definition=instr.definition)\n cgate.base_gate = base_gate\n cgate.base_gate_name = base_gate_name\n return cgate","def Chord( x, y0, y1):\n return 0.5 * x * ( y1 - y0 )","def conj(siso):\n num = siso.num[0][0][::-1].conjugate()\n den = siso.den[0][0][::-1].conjugate()\n return ctrl.tf(num,den,siso.dt)","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def CHARGE(t, x, y):\n Iq, UC, U = x\n E, Umax = y # time discrete state vector\n E_new = E + Cp/2 * U**2\n return array([0.0, UC, 0.0]), array([E_new, U])","def test_cx_gate_deterministic_default_basis_gates(self):\n shots = 100\n circuits = ref_2q_clifford.cx_gate_circuits_deterministic(final_measure=True)\n targets = ref_2q_clifford.cx_gate_counts_deterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots)\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0)","def cs(self):\n\n def myfunc(incident_energy):\n return XrayLibWrap_Energy(self.Z, \"cs\", incident_energy)\n\n return myfunc","def gate(self, operator, target, control=None, control_0=None):\n xp = self.xp\n\n if np.issubdtype(type(target), np.integer):\n target = (target,)\n if np.issubdtype(type(control), np.integer):\n control = (control,)\n if np.issubdtype(type(control_0), np.integer):\n control_0 = (control_0,)\n\n operator = xp.asarray(operator, dtype=self.dtype)\n if operator.shape[0] != 2:\n operator = operator.reshape([2] * int(math.log2(operator.size)))\n\n assert operator.ndim == len(target) * 2, 'You must set operator.size==exp(len(target)*2)'\n\n c_slice = [slice(None)] * self.size\n if control is not None:\n for _c in control:\n c_slice[_c] = slice(1, 2)\n if control_0 is not None:\n for _c in control_0:\n c_slice[_c] = slice(0, 1)\n c_slice = tuple(c_slice)\n\n c_index = list(range(self.size))\n t_index = list(range(self.size))\n for i, _t in enumerate(target):\n t_index[_t] = self.size + i\n o_index = list(range(self.size, self.size + len(target))) + list(target)\n\n # Use following code when numpy bug is removed and cupy can use this einsum format.\n # self.data[c_slice] = xp.einsum(operator, o_index, self.data[c_slice], c_index, t_index)\n\n # Alternative code\n character = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'\n o_index = ''.join([character[i] for i in o_index])\n c_index = ''.join([character[i] for i in c_index])\n t_index = ''.join([character[i] for i in t_index])\n subscripts = '{},{}->{}'.format(o_index, c_index, t_index)\n self.data[c_slice] = xp.einsum(subscripts, operator, self.data[c_slice])","def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self"],"string":"[\n \"def cy(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CY(), target=[control, target])\",\n \"def CX(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def covar(fx,cx):\\n \\n fx = np.array(fx)\\n cx = np.array(cx)\\n \\n shape_fx = fx.shape\\n shape_cx = cx.shape\\n \\n \\n if shape_fx[1] != shape_cx[0]:\\n print('-----------------------------------------')\\n print(\\\"Shapes of fx and cx cannot be multiplied:\\\")\\n print(shape_fx,\\\"x\\\",shape_cx)\\n print('-----------------------------------------')\\n raise ValueError('Input matrices are not compliant')\\n \\n cy = np.dot(np.dot(fx,cx),fx.T)\\n \\n print(\\\"Size of Cy matrix: \\\",np.shape(cy))\\n \\n return cy\",\n \"def cz(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CZ(), target=[control, target])\",\n \"def circuitSat(C):\",\n \"def estimateCs(y, inp):\\n\\treturn 1 -(math.tanh(getK1(inp) - (y/getY90(inp)) / (2 * getD0(inp)) + (y/getY90(inp) - 1/3.0)**3 / (3 * getD0(inp))))**2\",\n \"def YY(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.YY, qubit_expr)\",\n \"def C(self,X):\\n return(\\n 0\\n )\",\n \"def Y(self, qubit_expr): \\n self.apply_gate_operation('Y', qubit_expr)\",\n \"def dcx(self, addr):\\n\\n self.reg.idx = self.reg.idx.inc(-1)\\n self.reg.zerox_flag = self.reg.idx.eq_zero()\",\n \"def TAY(self, *_):\\n self.reg.Y = self.reg.A\\n self.reg.N = self.reg.Y << 7\\n self.reg.Z = self.reg.Y == 0\",\n \"def run(self, dag):\\n\\n q_gate_list = ['cx', 'cy', 'cz', 'h', 'x', 'y', 'z']\\n\\n # Gate sets to be cancelled\\n cancellation_sets = defaultdict(lambda: [])\\n\\n for wire in dag.wires:\\n wire_name = \\\"{0}[{1}]\\\".format(str(wire.register.name), str(wire.index))\\n wire_commutation_set = self.property_set['commutation_set'][wire_name]\\n\\n for com_set_idx, com_set in enumerate(wire_commutation_set):\\n if com_set[0].type in ['in', 'out']:\\n continue\\n for node in com_set:\\n num_qargs = len(node.qargs)\\n if num_qargs == 1 and node.name in q_gate_list:\\n cancellation_sets[(node.name, wire_name, com_set_idx)].append(node)\\n if num_qargs == 1 and node.name in ['u1', 'rz', 't', 's']:\\n cancellation_sets[('z_rotation', wire_name, com_set_idx)].append(node)\\n elif num_qargs == 2 and node.qargs[0] == wire:\\n second_op_name = \\\"{0}[{1}]\\\".format(str(node.qargs[1].register.name),\\n str(node.qargs[1].index))\\n q2_key = (node.name, wire_name, second_op_name,\\n self.property_set['commutation_set'][(node, second_op_name)])\\n cancellation_sets[q2_key].append(node)\\n\\n for cancel_set_key in cancellation_sets:\\n set_len = len(cancellation_sets[cancel_set_key])\\n if ((set_len) > 1 and cancel_set_key[0] in q_gate_list):\\n gates_to_cancel = cancellation_sets[cancel_set_key]\\n for c_node in gates_to_cancel[:(set_len // 2) * 2]:\\n dag.remove_op_node(c_node)\\n\\n elif((set_len) > 1 and cancel_set_key[0] == 'z_rotation'):\\n run = cancellation_sets[cancel_set_key]\\n run_qarg = run[0].qargs[0]\\n total_angle = 0.0 # lambda\\n for current_node in run:\\n if (current_node.condition is not None\\n or len(current_node.qargs) != 1\\n or current_node.qargs[0] != run_qarg):\\n raise TranspilerError(\\\"internal error\\\")\\n\\n if current_node.name in ['u1', 'rz']:\\n current_angle = float(current_node.op.params[0])\\n elif current_node.name == 't':\\n current_angle = sympy.pi / 4\\n elif current_node.name == 's':\\n current_angle = sympy.pi / 2\\n\\n # Compose gates\\n total_angle = current_angle + total_angle\\n\\n # Replace the data of the first node in the run\\n new_op = U1Gate(total_angle)\\n new_qarg = QuantumRegister(1, 'q')[0]\\n new_dag = DAGCircuit()\\n new_dag.add_qreg(new_qarg.register)\\n new_dag.apply_operation_back(new_op, [new_qarg])\\n dag.substitute_node_with_dag(run[0], new_dag)\\n\\n # Delete the other nodes in the run\\n for current_node in run[1:]:\\n dag.remove_op_node(current_node)\\n\\n return dag\",\n \"def C(self, y, x):\\n return self.minor(y,x).det()*(-1.0)**(y+x+2.0)\",\n \"def DEY(self, *_):\\n self._dec_or_inc_register('Y', increment=False)\",\n \"def compute_operator(self, Xc, Yc):\\n\\n U, s, V = self._compute_svd(Xc)\\n\\n self._Atilde = (np.linalg.multi_dot([U.T.conj(), (Yc), (V)])\\n * np.reciprocal(s))\\n\\n self._compute_eigenquantities()\\n self._compute_modes(Yc, U, s, V)\\n\\n self._slow_modes = (np.abs(old_div(np.log(self.eigenvalues),\\n self._eigs_divider))) <= self._rho\",\n \"def xkcd():\",\n \"def c( self , y , r , t = 0 ):\\n \\n u = np.zeros(self.m) # State derivative vector\\n \\n raise NotImplementedError\\n \\n return u\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def test_cx_gate_nondeterministic_minimal_basis_gates(self):\\n shots = 2000\\n circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_2q_clifford.cx_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def cy(self):\\n\\t\\txfrm = self.xfrm\\n\\t\\tif xfrm is None:\\n\\t\\t\\treturn None\\n\\t\\treturn xfrm.cy\",\n \"def estimateCsKnownY90(y, inp):\\n\\treturn 1 -(math.tanh(getK1(inp) - y / (2 * getD0(inp)) + (y - 1/3.0)**3 / (3 * getD0(inp))))**2\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def test_y_gate_deterministic_minimal_basis_gates(self):\\n shots = 100\\n circuits = ref_1q_clifford.y_gate_circuits_deterministic(final_measure=True)\\n targets = ref_1q_clifford.y_gate_counts_deterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0)\",\n \"def DEX(self, *_):\\n self._dec_or_inc_register('X', increment=False)\",\n \"def test_cx_equivalence_1cx(self, seed=1):\\n state = np.random.default_rng(seed)\\n rnd = 2 * np.pi * state.random(size=12)\\n\\n qr = QuantumRegister(2, name=\\\"q\\\")\\n qc = QuantumCircuit(qr)\\n\\n qc.u(rnd[0], rnd[1], rnd[2], qr[0])\\n qc.u(rnd[3], rnd[4], rnd[5], qr[1])\\n\\n qc.cx(qr[1], qr[0])\\n\\n qc.u(rnd[6], rnd[7], rnd[8], qr[0])\\n qc.u(rnd[9], rnd[10], rnd[11], qr[1])\\n\\n sim = UnitarySimulatorPy()\\n unitary = execute(qc, sim).result().get_unitary()\\n self.assertEqual(two_qubit_cnot_decompose.num_basis_gates(unitary), 1)\\n self.assertTrue(Operator(two_qubit_cnot_decompose(unitary)).equiv(unitary))\",\n \"def test_ccx_gate_nondeterministic_minimal_basis_gates(self):\\n shots = 2000\\n circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_non_clifford.ccx_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def CZ(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.CZ, qubit_expr)\",\n \"def test_csc():\\n c=14\\n assert {'diff':EF.csc(c).der, 'value': EF.csc(c).val}=={'diff':0, 'value': 1/math.sin(c)}\",\n \"def _control_predefined(operation, num_ctrl_qubits):\\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\\n if num_ctrl_qubits == 1:\\n import qiskit.extensions.standard.cx\\n cgate = qiskit.extensions.standard.cx.CnotGate()\\n else:\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n elif operation.name == 'y':\\n import qiskit.extensions.standard.cy\\n cgate = qiskit.extensions.standard.cy.CyGate()\\n elif operation.name == 'z':\\n import qiskit.extensions.standard.cz\\n cgate = qiskit.extensions.standard.cz.CzGate()\\n elif operation.name == 'h':\\n import qiskit.extensions.standard.ch\\n cgate = qiskit.extensions.standard.ch.CHGate()\\n elif operation.name in {'rx', 'ry', 'rz'}:\\n if operation.name == 'rx':\\n import qiskit.extensions.standard.crx\\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\\n elif operation.name == 'ry':\\n import qiskit.extensions.standard.cry\\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\\n else: # operation.name == 'rz'\\n import qiskit.extensions.standard.crz\\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\\n if num_ctrl_qubits == 1:\\n return cgate\\n else:\\n # only predefined for one control qubit\\n return cgate.control(num_ctrl_qubits - 1)\\n elif operation.name == 'swap':\\n import qiskit.extensions.standard.cswap\\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\\n elif operation.name == 'u1':\\n import qiskit.extensions.standard.cu1\\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\\n elif operation.name == 'u3':\\n import qiskit.extensions.standard.cu3\\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\\n elif operation.name == 'cx':\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n else:\\n raise QiskitError('No standard controlled gate for \\\"{}\\\"'.format(\\n operation.name))\\n return cgate\",\n \"def electrical_jacobian(self, state, u_in, omega, *_):\\n pass\",\n \"def test_cx_gate_deterministic_minimal_basis_gates(self):\\n shots = 100\\n circuits = ref_2q_clifford.cx_gate_circuits_deterministic(final_measure=True)\\n targets = ref_2q_clifford.cx_gate_counts_deterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0)\",\n \"def test_cnot():\\n\\n program = dedent(\\n \\\"\\\"\\\"\\\\\\n register q0[0]\\n register q1[1]\\n X q0\\n CNOT q0 q1\\n \\\"\\\"\\\"\\n )\\n\\n result = run(program, run_gate_array, return_distribution=True)\\n assert isclose(result, [0.0, 0.0, 0.0, 1.0]).all()\",\n \"def evaluate_c(self, x, out=None, **kwargs):\\n return np.zeros(0)\",\n \"def ccx(self, q0, q1, q2, ctrl=None):\\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\\n return self\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def compile(self, seq, registers):\\n\\n # Check which modes are actually being used\\n used_modes = []\\n for operations in seq:\\n modes = [modes_label.ind for modes_label in operations.reg]\\n used_modes.append(modes)\\n\\n used_modes = list(set(item for sublist in used_modes for item in sublist))\\n\\n # dictionary mapping the used modes to consecutive non-negative integers\\n dict_indices = {used_modes[i]: i for i in range(len(used_modes))}\\n nmodes = len(used_modes)\\n\\n # We start with an identity then sequentially update with the gate transformations\\n T = np.identity(nmodes, dtype=np.complex128)\\n\\n # Now we will go through each operation in the sequence `seq` and apply it to T\\n for operations in seq:\\n name = operations.op.__class__.__name__\\n params = par_evaluate(operations.op.p)\\n modes = [modes_label.ind for modes_label in operations.reg]\\n if name == \\\"Rgate\\\":\\n G = np.exp(1j * params[0])\\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\\n elif name == \\\"LossChannel\\\":\\n G = np.sqrt(params[0])\\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\\n elif name == \\\"Interferometer\\\":\\n U = params[0]\\n if U.shape == (1, 1):\\n T = _apply_one_mode_gate(U[0, 0], T, dict_indices[modes[0]])\\n elif U.shape == (2, 2):\\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n else:\\n modes = [dict_indices[mode] for mode in modes]\\n U_expand = np.eye(nmodes, dtype=np.complex128)\\n U_expand[np.ix_(modes, modes)] = U\\n T = U_expand @ T\\n elif name == \\\"PassiveChannel\\\":\\n T0 = params[0]\\n if T0.shape == (1, 1):\\n T = _apply_one_mode_gate(T0[0, 0], T, dict_indices[modes[0]])\\n elif T0.shape == (2, 2):\\n T = _apply_two_mode_gate(T0, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n else:\\n modes = [dict_indices[mode] for mode in modes]\\n T0_expand = np.eye(nmodes, dtype=np.complex128)\\n T0_expand[np.ix_(modes, modes)] = T0\\n T = T0_expand @ T\\n elif name == \\\"BSgate\\\":\\n G = _beam_splitter_passive(params[0], params[1])\\n T = _apply_two_mode_gate(G, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n elif name == \\\"MZgate\\\":\\n v = np.exp(1j * params[0])\\n u = np.exp(1j * params[1])\\n U = 0.5 * np.array([[u * (v - 1), 1j * (1 + v)], [1j * u * (1 + v), 1 - v]])\\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n elif name == \\\"sMZgate\\\":\\n exp_sigma = np.exp(1j * (params[0] + params[1]) / 2)\\n delta = (params[0] - params[1]) / 2\\n U = exp_sigma * np.array(\\n [[np.sin(delta), np.cos(delta)], [np.cos(delta), -np.sin(delta)]]\\n )\\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n\\n ord_reg = [r for r in list(registers) if r.ind in used_modes]\\n ord_reg = sorted(list(ord_reg), key=lambda x: x.ind)\\n\\n return [Command(ops.PassiveChannel(T), ord_reg)]\",\n \"def cycloid(x2, y2, N=100):\\n\\n # First find theta2 from (x2, y2) numerically (by Newton-Rapheson).\\n def f(theta):\\n return y2/x2 - (1-np.cos(theta))/(theta-np.sin(theta))\\n theta2 = newton(f, np.pi/2)\\n\\n # The radius of the circle generating the cycloid.\\n R = y2 / (1 - np.cos(theta2))\\n\\n theta = np.linspace(0, theta2, N)\\n x = R * (theta - np.sin(theta))\\n y = R * (1 - np.cos(theta))\\n\\n # The time of travel\\n T = theta2 * np.sqrt(R / g)\\n print('T(cycloid) = {:.3f}'.format(T))\\n return x, y, T\",\n \"def test_ud_cnot():\\n program = dedent(\\n \\\"\\\"\\\"\\\\\\n register q0[0]\\n register q1[1]\\n register q2[2]\\n register q3[3]\\n X q2\\n CNOT q2 q0\\n \\\"\\\"\\\"\\n )\\n\\n result = run(program, run_gate_array)\\n assert isclose(result, [1.0, 0.0, 1.0, 0.0]).all()\",\n \"def bcs(self, arg):\\n\\n self.pc += arg if self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def test_cz_gate_nondeterministic_minimal_basis_gates(self):\\n shots = 2000\\n circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_2q_clifford.cz_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def test_cx_equivalence_2cx(self, seed=2):\\n state = np.random.default_rng(seed)\\n rnd = 2 * np.pi * state.random(size=18)\\n\\n qr = QuantumRegister(2, name=\\\"q\\\")\\n qc = QuantumCircuit(qr)\\n\\n qc.u(rnd[0], rnd[1], rnd[2], qr[0])\\n qc.u(rnd[3], rnd[4], rnd[5], qr[1])\\n\\n qc.cx(qr[1], qr[0])\\n\\n qc.u(rnd[6], rnd[7], rnd[8], qr[0])\\n qc.u(rnd[9], rnd[10], rnd[11], qr[1])\\n\\n qc.cx(qr[0], qr[1])\\n\\n qc.u(rnd[12], rnd[13], rnd[14], qr[0])\\n qc.u(rnd[15], rnd[16], rnd[17], qr[1])\\n\\n sim = UnitarySimulatorPy()\\n unitary = execute(qc, sim).result().get_unitary()\\n self.assertEqual(two_qubit_cnot_decompose.num_basis_gates(unitary), 2)\\n self.assertTrue(Operator(two_qubit_cnot_decompose(unitary)).equiv(unitary))\",\n \"def step1c(self):\\n\\t\\tif (self.ends(\\\"y\\\") and self.vowelinstem()):\\n\\t\\t\\tself.b = self.b[:self.k] + 'i' + self.b[self.k+1:]\",\n \"def CPY(self, value):\\n self._compare(value, 'Y')\",\n \"def test_ccx_gate_deterministic_minimal_basis_gates(self):\\n shots = 100\\n circuits = ref_non_clifford.ccx_gate_circuits_deterministic(final_measure=True)\\n targets = ref_non_clifford.ccx_gate_counts_deterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0)\",\n \"def evaluate_c(self, x, out=None, **kwargs):\\n return self._base_nlp.evaluate_c(x, out=out, **kwargs)\",\n \"def test_ccx_gate_nondeterministic_default_basis_gates(self):\\n shots = 2000\\n circuits = ref_non_clifford.ccx_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_non_clifford.ccx_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots)\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def cy(y):\\n return pic_height + ch(y - global_min_y)\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def gcxgcy_to_cxcy(gcxgcy, priors_cxcy):\\n\\n return torch.cat([gcxgcy[:, :2] * priors_cxcy[:, 2:] / 10 + priors_cxcy[:, :2], # c_x, c_y\\n torch.exp(gcxgcy[:, 2:] / 5) * priors_cxcy[:, 2:]], 1) # w, h\",\n \"def cx():\",\n \"def C(self,t,K,c0):\\n #ode(self.dc_dt,c0,t,args=(k,)).set_integrator('lsoda')\\n #ode(self.dc_dt,c0,t,args=(k,)).set_integrator('vode', method='bdf', order=15)\\n \\n # if we have any negative times we assume they occur before the \\n # reaction starts hence all negative times are assigned concentration \\n # c0\\n \\n ## could switch to something like ode15s that the oiginal matlab code \\n ## uses - can odeint cope with equations as stiff as we need?\\n ## to use integrate.ode need order of arguments in dc_dt to switch\\n \\n #r = scipy.integrate.ode(self.dc_dt)\\n #r = r.set_integrator('vode', method='bdf', order=15,nsteps=3000)\\n #r = r.set_initial_value(c0)\\n #r = r.set_f_params((K,))\\n #r.integrate(t)\\n \\n static_times = t[t<0]\\n dynamic_times = t[t>=0]\\n\\n static_C = np.array([c0 for _ in static_times])\\n\\n # odeint always takes the first time point as t0\\n # our t0 is always 0 (removing t0 occures before we integrate)\\n # so if the first time point is not 0 we add it \\n \\n if not dynamic_times.any() or dynamic_times[0]:\\n #fancy indexing returns a copy so we can do this\\n dynamic_times = np.hstack([[0],dynamic_times]) \\n dynamic_C = odeint(self.dc_dt,c0,dynamic_times,args=(K,))[1:]\\n else:\\n dynamic_C = odeint(self.dc_dt,c0,dynamic_times,args=(K,))\\n \\n if static_C.any():\\n return np.vstack([static_C,dynamic_C])\\n else:\\n return dynamic_C\",\n \"def csw(self, q0, q1, q2, ctrl=None):\\n self.cx(q2,q1,ctrl=ctrl).ccx(q0,q1,q2,ctrl=ctrl).cx(q2,q1,ctrl=ctrl)\\n return self\",\n \"def test_cx_equivalence_0cx(self, seed=0):\\n state = np.random.default_rng(seed)\\n rnd = 2 * np.pi * state.random(size=6)\\n\\n qr = QuantumRegister(2, name=\\\"q\\\")\\n qc = QuantumCircuit(qr)\\n\\n qc.u(rnd[0], rnd[1], rnd[2], qr[0])\\n qc.u(rnd[3], rnd[4], rnd[5], qr[1])\\n\\n sim = UnitarySimulatorPy()\\n unitary = execute(qc, sim).result().get_unitary()\\n self.assertEqual(two_qubit_cnot_decompose.num_basis_gates(unitary), 0)\\n self.assertTrue(Operator(two_qubit_cnot_decompose(unitary)).equiv(unitary))\",\n \"def release_cytokine(self) :\\n for cy in self.cytokine :\\n if self.cytosol.get(cy, False) and self.cytosol[cy] > 0:\\n cy(self.pos, tool.rand_2D(1.2))\\n self.cytosol[cy] -= 1\\n else : \\n self.ribosome.mrna(cy, 100)\\n self.cytokine.clear()\",\n \"def _compute_carry_and_output(self, x, h_tm1, c_tm1):\\n x_i, x_f, x_c, x_o = x\\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\\n i = self.recurrent_activation(\\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\\n f = self.recurrent_activation(x_f + K.dot(\\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\\n o = self.recurrent_activation(\\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\\n return c, o\",\n \"def AlphaCyc(ss, train):\\n\\n if ss.Win != 0:\\n ss.Win.PollEvents() # this is essential for GUI responsiveness while running\\n viewUpdt = ss.TrainUpdt.value\\n if not train:\\n viewUpdt = ss.TestUpdt.value\\n\\n # update prior weight changes at start, so any DWt values remain visible at end\\n # you might want to do this less frequently to achieve a mini-batch update\\n # in which case, move it out to the TrainTrial method where the relevant\\n # counters are being dealt with.\\n if train:\\n ss.Net.WtFmDWt()\\n\\n ss.Net.AlphaCycInit(train)\\n ss.Time.AlphaCycStart()\\n for qtr in range(4):\\n for cyc in range(ss.Time.CycPerQtr):\\n ss.Net.Cycle(ss.Time)\\n ss.Time.CycleInc()\\n if ss.ViewOn:\\n if viewUpdt == leabra.Cycle:\\n if cyc != ss.Time.CycPerQtr-1: # will be updated by quarter\\n ss.UpdateView(train)\\n if viewUpdt == leabra.FastSpike:\\n if (cyc+1)%10 == 0:\\n ss.UpdateView(train)\\n ss.Net.QuarterFinal(ss.Time)\\n ss.Time.QuarterInc()\\n if ss.ViewOn:\\n if viewUpdt <= leabra.Quarter:\\n ss.UpdateView(train)\\n if viewUpdt == leabra.Phase:\\n if qtr >= 2:\\n ss.UpdateView(train)\\n\\n if train:\\n ss.Net.DWt()\\n if ss.ViewOn and viewUpdt == leabra.AlphaCycle:\\n ss.UpdateView(train)\",\n \"def test_cx_gate_nondeterministic_default_basis_gates(self):\\n shots = 2000\\n circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_2q_clifford.cx_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots)\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def test_number_to_clifford_mapping_single_gate(self):\\n transpiled_cliff_list = [\\n SXGate(),\\n RZGate(np.pi),\\n RZGate(-np.pi),\\n RZGate(np.pi / 2),\\n RZGate(-np.pi / 2),\\n ]\\n general_cliff_list = [\\n IGate(),\\n HGate(),\\n SdgGate(),\\n SGate(),\\n XGate(),\\n SXGate(),\\n YGate(),\\n ZGate(),\\n ]\\n for inst in transpiled_cliff_list + general_cliff_list:\\n qc_from_inst = QuantumCircuit(1)\\n qc_from_inst.append(inst, [0])\\n num = num_from_1q_circuit(qc_from_inst)\\n qc_from_num = CliffordUtils.clifford_1_qubit_circuit(num)\\n self.assertTrue(Operator(qc_from_num).equiv(Operator(qc_from_inst)))\",\n \"def INY(self, *_):\\n self._dec_or_inc_register('Y', increment=True)\",\n \"def TYA(self, *_):\\n self.reg.A = self.reg.Y\\n self.reg.N = self.reg.A << 7\\n self.reg.Z = self.reg.A == 0\",\n \"def casadi_ode(self, t, x, u, w):\\n v = u[0]\\n thetadot = u[1]\\n theta = x[2]\\n f = cs.vertcat(v * cs.cos(theta), v * cs.sin(theta), thetadot)\\n if self.use_nonlinear_noise_model:\\n w_vec = cs.vertcat(self.scale[0]*(cs.cos(theta) * w[0] - cs.sin(theta) * w[1]),\\n self.scale[1]*(cs.sin(theta) * w[0] + cs.cos(theta) * w[1]),\\n self.scale[2]*(v * w[2]))\\n else:\\n w_vec = w\\n return f + w_vec\",\n \"def test_cz_gate_nondeterministic_default_basis_gates(self):\\n shots = 2000\\n circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_2q_clifford.cz_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots)\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def conj(x, *args, **kwargs):\\n raise NotImplementedError\",\n \"def alg(c):\\n return c[0]*G[0] + c[1]*G[1] + c[2]*G[2]\",\n \"def test_cx_gate_nondeterministic_waltz_basis_gates(self):\\n shots = 2000\\n circuits = ref_2q_clifford.cx_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_2q_clifford.cx_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='u1,u2,u3,cx')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def test_cz_gate_deterministic_minimal_basis_gates(self):\\n shots = 100\\n circuits = ref_2q_clifford.cz_gate_circuits_deterministic(final_measure=True)\\n targets = ref_2q_clifford.cz_gate_counts_deterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0)\",\n \"def _collab_curate(self, sender, amount=0):\\n\\n curate_params = {'hDAO_amount': 100, 'objkt_id': 100_000}\\n self.result = self.collab.curate(curate_params).interpret(\\n storage=self.collab_storage, sender=sender, amount=amount)\\n\\n assert len(self.result.operations) == 1\\n assert self.result.operations[0]['parameters']['entrypoint'] == 'curate'\\n assert self.result.operations[0]['parameters']['value']['args'][0] == {'int': '100'}\\n assert self.result.operations[0]['parameters']['value']['args'][1] == {'int': '100000'}\\n self.assertEqual(\\n self.result.operations[0]['destination'],\\n self.collab_storage['minterAddress']\\n )\",\n \"def open_circ():\\n\\n set_mode(mode_cc) # set operation mode to CC\\n time.sleep(.250)\\n set_CC_current(cc_current=0) # set CC mode current to 0 amps\\n time.sleep(.1)\\n \\n oc_vals = get_input_values() # read open circuits levels\\n oc_data_point = data_point(oc_vals) # create data point for open circuit measurement\\n voc = oc_data_point[3] # open circuit voltage measurement\\n print('Open circuit voltage: ', voc)\\n write_data_tofile(oc_data_point) # write data to file\\n \\n return voc\",\n \"def test_circuit_generation_from_sec(self):\\n\\n backend = CrossResonanceHamiltonianBackend()\\n\\n expr = cr_hamiltonian.CrossResonanceHamiltonian(\\n qubits=(0, 1),\\n flat_top_widths=[500],\\n unit=\\\"ns\\\",\\n amp=0.1,\\n sigma=20,\\n risefall=2,\\n )\\n\\n nearlest_16 = 576\\n\\n with pulse.build(default_alignment=\\\"left\\\", name=\\\"cr\\\") as ref_cr_sched:\\n pulse.play(\\n pulse.GaussianSquare(\\n nearlest_16,\\n amp=0.1,\\n sigma=20,\\n width=500,\\n ),\\n pulse.ControlChannel(0),\\n )\\n pulse.delay(nearlest_16, pulse.DriveChannel(0))\\n pulse.delay(nearlest_16, pulse.DriveChannel(1))\\n\\n cr_gate = circuit.Gate(\\\"cr_gate\\\", num_qubits=2, params=[500])\\n expr_circs = expr.circuits(backend)\\n\\n x0_circ = QuantumCircuit(2, 1)\\n x0_circ.append(cr_gate, [0, 1])\\n x0_circ.h(1)\\n x0_circ.measure(1, 0)\\n\\n x1_circ = QuantumCircuit(2, 1)\\n x1_circ.x(0)\\n x1_circ.append(cr_gate, [0, 1])\\n x1_circ.h(1)\\n x1_circ.measure(1, 0)\\n\\n y0_circ = QuantumCircuit(2, 1)\\n y0_circ.append(cr_gate, [0, 1])\\n y0_circ.sdg(1)\\n y0_circ.h(1)\\n y0_circ.measure(1, 0)\\n\\n y1_circ = QuantumCircuit(2, 1)\\n y1_circ.x(0)\\n y1_circ.append(cr_gate, [0, 1])\\n y1_circ.sdg(1)\\n y1_circ.h(1)\\n y1_circ.measure(1, 0)\\n\\n z0_circ = QuantumCircuit(2, 1)\\n z0_circ.append(cr_gate, [0, 1])\\n z0_circ.measure(1, 0)\\n\\n z1_circ = QuantumCircuit(2, 1)\\n z1_circ.x(0)\\n z1_circ.append(cr_gate, [0, 1])\\n z1_circ.measure(1, 0)\\n\\n ref_circs = [x0_circ, y0_circ, z0_circ, x1_circ, y1_circ, z1_circ]\\n for c in ref_circs:\\n c.add_calibration(cr_gate, (0, 1), ref_cr_sched)\\n\\n self.assertListEqual(expr_circs, ref_circs)\",\n \"def cxr(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def test_scalar_coeff_cc():\\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\\n kappa = Symbol('kappa', real=True)\\n a1 = Destroy(hs=hs_1)\\n a2 = Destroy(hs=hs_2)\\n\\n jc_expr = (\\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\\n )\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == I * kappa * OperatorPlusMinusCC(\\n a1.dag() * a2, sign=-1\\n )\\n expanded = simplified.doit()\\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())\",\n \"def BCS(self, value):\\n if self.reg.C:\\n self.reg.PC += value\",\n \"def convert_to_circuit(x):\\n y = np.arcsin(x)\\n z = np.arccos(x**2)\\n qubits = cirq.GridQubit.rect(5, 1)\\n circuit = cirq.Circuit()\\n for i in range(5):\\n circuit.append(cirq.ry(y).on(qubits[i]))\\n circuit.append(cirq.rz(z).on(qubits[i]))\\n return circuit\",\n \"def test_simple_cc():\\n hs_c = LocalSpace('c', dimension=3)\\n hs_q = LocalSpace('q1', basis=('g', 'e'))\\n Delta_1 = Symbol('Delta_1')\\n Omega_1 = Symbol('Omega_1')\\n g_1 = Symbol('g_1')\\n a = Destroy(hs=hs_c)\\n a_dag = Create(hs=hs_c)\\n sig_p = LocalSigma('e', 'g', hs=hs_q)\\n sig_m = LocalSigma('g', 'e', hs=hs_q)\\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\\n assert (\\n srepr(simplified.term)\\n == \\\"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \\\"\\n \\\"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \\\"\\n \\\"basis=('g', 'e')))), sign=-1)\\\"\\n )\\n expanded = simplified.doit()\\n assert expanded == jc_expr\",\n \"def test_cfu_cycles(self):\\n # Input: (function, in0, in1, cmd_valid, rsp_ready)\\n # Output: (result, rsp_valid, cmd_ready)\\n X = None\\n DATA = [\\n # Nothing\\n ((0, 0, 0, 0, 0), (X, 0, 1)),\\n # Same cycle instruction, CPU not ready\\n ((0, 1, 2, 1, 0), (3, 1, 1)),\\n ((0, 0, 0, 0, 1), (3, 1, 0)),\\n ((0, 0, 0, 0, 0), (X, 0, 1)),\\n # Multi-cycle instruction, CPU ready\\n ((3, 3, 0, 1, 1), (X, 0, 1)),\\n ((0, 0, 0, 0, 1), (X, 0, 0)),\\n ((0, 0, 0, 0, 1), (X, 0, 0)),\\n ((0, 0, 0, 0, 1), (6, 1, 0)),\\n # Same cycle instruction, CPU ready\\n ((0, 5, 3, 1, 1), (8, 1, 1)),\\n # Multi-cycle instruction, CPU not ready\\n ((3, 2, 0, 1, 0), (X, 0, 1)),\\n ((0, 0, 0, 0, 0), (X, 0, 0)),\\n ((0, 0, 0, 0, 0), (2, 1, 0)),\\n ((0, 0, 0, 0, 1), (2, 1, 0)),\\n # Multi-cycle instruction, but always ready next cycle\\n ((4, 3, 5, 1, 1), (X, 0, 1)),\\n ((0, 0, 0, 0, 1), (8, 1, 0)),\\n # CPU not ready\\n ((4, 3, 4, 1, 0), (X, 0, 1)),\\n ((0, 0, 0, 0, 0), (X, 1, 0)),\\n ((0, 0, 0, 0, 0), (X, 1, 0)),\\n ((0, 0, 0, 0, 1), (7, 1, 0)),\\n # Fallback instruction - same cycle, CPU ready\\n ((7, 0, 0, 1, 1), (X, 1, 1)),\\n ]\\n\\n def process():\\n for n, (inputs, expected_outputs) in enumerate(DATA):\\n func, i0, i1, cmd_valid, rsp_ready = inputs\\n exp_result, exp_rsp_valid, exp_cmd_ready = expected_outputs\\n yield self.dut.cmd_function_id.eq(func)\\n yield self.dut.cmd_in0.eq(i0)\\n yield self.dut.cmd_in1.eq(i1)\\n yield self.dut.cmd_valid.eq(cmd_valid)\\n yield self.dut.rsp_ready.eq(rsp_ready)\\n yield Delay(0.1)\\n if exp_result is not None:\\n self.assertEqual((yield self.dut.rsp_out), exp_result)\\n if exp_rsp_valid is not None:\\n self.assertEqual((yield self.dut.rsp_valid), exp_rsp_valid)\\n # We don't currently support returning non-OK responses, so\\n # if our response is valid, it must be OK.\\n if exp_rsp_valid:\\n self.assertTrue((yield self.dut.rsp_ok))\\n if exp_cmd_ready is not None:\\n self.assertEqual((yield self.dut.cmd_ready), exp_cmd_ready)\\n yield\\n self.run_sim(process, False)\",\n \"def csb(self):\\n\\n def myfunc(incident_energy):\\n return XrayLibWrap_Energy(self.Z, \\\"csb\\\", incident_energy)\\n\\n return myfunc\",\n \"def _calc_C(self, lambdify=True):\\n\\n C = None\\n C_func = None\\n # check to see if we have our term saved in file\\n C, C_func = self._load_from_file('C', lambdify)\\n\\n if C is None and C_func is None:\\n # if no saved file was loaded, generate function\\n print('Generating centrifugal and Coriolis compensation function')\\n\\n # first get the inertia matrix\\n M = self._calc_M(lambdify=False)\\n\\n # C_{kj} = sum_i c_{ijk}(q) \\\\dot{q}_i\\n # c_{ijk} = 1/2 * sum_i (\\\\frac{\\\\partial M_{kj}}{\\\\partial q_j} +\\n # \\\\frac{\\\\partial M_{ki}}{\\\\partial q_j} - \\\\frac{\\\\partial M_{ij}}\\n # {\\\\partial q_k})\\n C = sp.zeros(self.N_JOINTS, self.N_JOINTS)\\n for kk in range(self.N_JOINTS):\\n for jj in range(self.N_JOINTS):\\n for ii in range(self.N_JOINTS):\\n dMkjdqi = M[kk, jj].diff(self.q[ii])\\n dMkidqj = M[kk, ii].diff(self.q[jj])\\n dMijdqk = M[ii, jj].diff(self.q[kk])\\n C[kk, jj] += .5 * (dMkjdqi + dMkidqj - dMijdqk) * self.dq[ii]\\n C[kk, jj] = C[kk, jj]\\n C = sp.Matrix(C)\\n\\n # save to file\\n abr_control.utils.os_utils.makedirs(\\n '%s/C' % self.config_folder)\\n cloudpickle.dump(C, open(\\n '%s/C/C' % self.config_folder, 'wb'))\\n\\n if lambdify is False:\\n # if should return expression not function\\n return C\\n\\n if C_func is None:\\n C_func = self._generate_and_save_function(\\n filename='C', expression=C,\\n parameters=self.q+self.dq)\\n return C_func\",\n \"def test_cnot_rxx_decompose(self):\\n cnot = Operator(CXGate())\\n decomps = [\\n cnot_rxx_decompose(),\\n cnot_rxx_decompose(plus_ry=True, plus_rxx=True),\\n cnot_rxx_decompose(plus_ry=True, plus_rxx=False),\\n cnot_rxx_decompose(plus_ry=False, plus_rxx=True),\\n cnot_rxx_decompose(plus_ry=False, plus_rxx=False),\\n ]\\n for decomp in decomps:\\n self.assertTrue(cnot.equiv(decomp))\",\n \"def cx(x):\\n return cw(x - global_min_x)\",\n \"def two_activation(self, output_reg):\\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\\n self._q_neuron.cx(self.inputs[0], self._output[output_reg])\\n self._q_neuron.cx(self.inputs[1], self._output[output_reg])\",\n \"def bcc(self, arg):\\n\\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def phasesin14xymult_cfix(param, xyord,crossord,t, x, y):\\n # 2010-04-27 11:49 IJC: Created\\n # 2010-05-28 15:42 IJC: Added x*y cross-terms\\n # 2010-07-21 13:02 IJC: switched to a mostly-additive model\\n\\n param = array(param,copy=True)\\n x = array(x,copy=True)\\n y = array(y,copy=True)\\n t = array(t,copy=True)\\n\\n xparam = zeros((0,14),float)\\n yparam = zeros((0,14),float)\\n crossparam = zeros((0,14),float)\\n\\n cparam = param[3:17].copy()\\n # Ensure that prod(1.+cparam) equals zero\\n cparam[0] = 1./(1.+cparam[1::]).prod() - 1.\\n if xyord>=1:\\n for ii in range(xyord):\\n xparam = vstack((xparam,param[17+ii*28:31+ii*28]))\\n yparam = vstack((yparam,param[31+ii*28:45+ii*28]))\\n\\n lastxyparamind = 45+(xyord-1)*28\\n if crossord>=1:\\n for ii in [0]: #range(crossparam):\\n crossparam = vstack((crossparam,param[lastxyparamind:lastxyparamind+(ii+1)*14]))\\n\\n #cparam -= mean(cparam)\\n param[2] = param[2] % (2*pi)\\n \\n if len(t.shape)==1:\\n was1d = True\\n t = t.reshape(14, len(t)/14.)\\n x = x.reshape(14, len(x)/14.)\\n y = y.reshape(14, len(y)/14.)\\n else:\\n was1d = False\\n\\n # Subtract the mean from the X and Y data\\n x -= x.mean(1).reshape(14,1)\\n y -= y.mean(1).reshape(14,1)\\n\\n # Zeroth-order model:\\n ret = param[0] - abs(param[1]) *cos(2*pi*t +param[2])\\n\\n # Apply constant and X/Y offsets:\\n #ret *= (1. + tile(cparam, (t.shape[1],1)).transpose())\\n offset_term = (1. + tile(cparam, (t.shape[1],1)).transpose())\\n if xyord>=1:\\n for ii in range(xyord):\\n offset_term += tile(xparam[ii], (t.shape[1],1)).transpose()*x**(ii+1)\\n offset_term += tile(yparam[ii], (t.shape[1],1)).transpose()*y**(ii+1)\\n\\n if crossord>=1:\\n for ii in [0]: \\n offset_term += tile(crossparam[ii], (t.shape[1],1)).transpose()*x*y\\n\\n # Apply the (1+c+dx+ey) term:\\n ret *= offset_term\\n\\n if was1d:\\n ret = ret.ravel()\\n\\n return ret\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def test_y_gate_deterministic_default_basis_gates(self):\\n shots = 100\\n circuits = ref_1q_clifford.y_gate_circuits_deterministic(final_measure=True)\\n targets = ref_1q_clifford.y_gate_counts_deterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots)\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0)\",\n \"def test_cz_gate_nondeterministic_waltz_basis_gates(self):\\n shots = 2000\\n circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_2q_clifford.cz_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='u1,u2,u3,cx')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def test_ccx_gate_deterministic_default_basis_gates(self):\\n shots = 100\\n circuits = ref_non_clifford.ccx_gate_circuits_deterministic(final_measure=True)\\n targets = ref_non_clifford.ccx_gate_counts_deterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots)\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0)\",\n \"def convert_C_instruction(self, instruction):\\n comp, dest, jump = self.parse(instruction)\\n\\n return f\\\"111{convert_comp(comp)}{convert_dest(dest)}\\\" \\\\\\n f\\\"{convert_jump(jump)}\\\"\",\n \"def set_cylindrical(self, cyl_ang):\\n self.FCYL = 1\\n self.CIL_ANG = cyl_ang\",\n \"def DynamicsCo(x, t, T0, alpha, cost_co, cost_ch, K_co, K_ch, n, r):\\n y=np.zeros([np.size(x)])\\n D=np.zeros([2]) \\n #define fitnss\\n D[0]=dmax*x[0]**n/(K_co**n+x[0]**n) #cooperator\\n D[1]=dmax*x[0]**n/(K_ch**n+x[0]**n) #cheater \\n #degradation\\n deg=fmax*x[1]/(x[1]+Kd) \\n #ODE of eco-evo dynamics\\n y[0]=alpha*T0-deg*x[0]-alpha*x[0] #dt/dt\\n y[1]=x[1]*(r*(1-cost_co)*(1-x[1]-x[2])-D[0]-alpha)#d Co/dt\\n y[2]=x[2]*(r*(1-cost_ch)*(1-x[1]-x[2])-D[1]-alpha) #d Ch/dt\\n \\n return y\",\n \"def Cintegrate(phi,\\n HC, \\n dt):\\n\\n phip1 = phi-HC.dot(phi)*dt\\n \\n return phip1\",\n \"def control(operation, num_ctrl_qubits=1, label=None):\\n from math import pi\\n # pylint: disable=cyclic-import\\n import qiskit.circuit.controlledgate as controlledgate\\n from qiskit.circuit.quantumregister import QuantumRegister\\n from qiskit.circuit.quantumcircuit import QuantumCircuit\\n # pylint: disable=unused-import\\n import qiskit.extensions.standard.multi_control_rotation_gates\\n import qiskit.extensions.standard.multi_control_toffoli_gate\\n import qiskit.extensions.standard.multi_control_u1_gate\\n\\n q_control = QuantumRegister(num_ctrl_qubits, name='control')\\n q_target = QuantumRegister(operation.num_qubits, name='target')\\n q_ancillae = None # TODO: add\\n\\n qc = QuantumCircuit(q_control, q_target)\\n\\n if operation.name == 'x' or (\\n isinstance(operation, controlledgate.ControlledGate) and\\n operation.base_gate_name == 'x'):\\n qc.mct(q_control[:] + q_target[:-1],\\n q_target[-1],\\n None,\\n mode='noancilla')\\n elif operation.name == 'rx':\\n qc.mcrx(operation.definition[0][0].params[0], q_control, q_target[0],\\n use_basis_gates=True)\\n elif operation.name == 'ry':\\n qc.mcry(operation.definition[0][0].params[0], q_control, q_target[0],\\n q_ancillae, use_basis_gates=True)\\n elif operation.name == 'rz':\\n qc.mcrz(operation.definition[0][0].params[0], q_control, q_target[0],\\n use_basis_gates=True)\\n else:\\n bgate = _unroll_gate(operation, ['u1', 'u3', 'cx'])\\n # now we have a bunch of single qubit rotation gates and cx\\n for rule in bgate.definition:\\n if rule[0].name == 'u3':\\n theta, phi, lamb = rule[0].params\\n if phi == -pi/2 and lamb == pi/2:\\n qc.mcrx(theta, q_control, q_target[rule[1][0].index],\\n use_basis_gates=True)\\n elif phi == 0 and lamb == 0:\\n qc.mcry(theta, q_control, q_target[rule[1][0].index],\\n q_ancillae, mode='noancilla', use_basis_gates=True)\\n elif theta == 0 and phi == 0:\\n qc.mcrz(lamb, q_control, q_target[rule[1][0].index],\\n use_basis_gates=True)\\n else:\\n qc.mcrz(lamb, q_control, q_target[rule[1][0].index],\\n use_basis_gates=True)\\n qc.mcry(theta, q_control, q_target[rule[1][0].index],\\n q_ancillae, use_basis_gates=True)\\n qc.mcrz(phi, q_control, q_target[rule[1][0].index],\\n use_basis_gates=True)\\n elif rule[0].name == 'u1':\\n qc.mcu1(rule[0].params[0], q_control, q_target[rule[1][0].index])\\n elif rule[0].name == 'cx':\\n qc.mct(q_control[:] + [q_target[rule[1][0].index]],\\n q_target[rule[1][1].index],\\n None,\\n mode='noancilla')\\n else:\\n raise QiskitError('gate contains non-controllable intructions')\\n instr = qc.to_instruction()\\n if isinstance(operation, controlledgate.ControlledGate):\\n new_num_ctrl_qubits = num_ctrl_qubits + operation.num_ctrl_qubits\\n base_name = operation.base_gate_name\\n base_gate = operation.base_gate\\n base_gate_name = operation.base_gate_name\\n else:\\n new_num_ctrl_qubits = num_ctrl_qubits\\n base_name = operation.name\\n base_gate = operation.__class__\\n base_gate_name = operation.name\\n # In order to maintain some backward compatibility with gate names this\\n # uses a naming convention where if the number of controls is <=2 the gate\\n # is named like \\\"cc<base_gate_name>\\\", else it is named like\\n # \\\"c<num_ctrl_qubits><base_name>\\\".\\n if new_num_ctrl_qubits > 2:\\n ctrl_substr = 'c{0:d}'.format(new_num_ctrl_qubits)\\n else:\\n ctrl_substr = ('{0}' * new_num_ctrl_qubits).format('c')\\n new_name = '{0}{1}'.format(ctrl_substr, base_name)\\n cgate = controlledgate.ControlledGate(new_name,\\n instr.num_qubits,\\n operation.params,\\n label=label,\\n num_ctrl_qubits=new_num_ctrl_qubits,\\n definition=instr.definition)\\n cgate.base_gate = base_gate\\n cgate.base_gate_name = base_gate_name\\n return cgate\",\n \"def Chord( x, y0, y1):\\n return 0.5 * x * ( y1 - y0 )\",\n \"def conj(siso):\\n num = siso.num[0][0][::-1].conjugate()\\n den = siso.den[0][0][::-1].conjugate()\\n return ctrl.tf(num,den,siso.dt)\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def CHARGE(t, x, y):\\n Iq, UC, U = x\\n E, Umax = y # time discrete state vector\\n E_new = E + Cp/2 * U**2\\n return array([0.0, UC, 0.0]), array([E_new, U])\",\n \"def test_cx_gate_deterministic_default_basis_gates(self):\\n shots = 100\\n circuits = ref_2q_clifford.cx_gate_circuits_deterministic(final_measure=True)\\n targets = ref_2q_clifford.cx_gate_counts_deterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots)\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0)\",\n \"def cs(self):\\n\\n def myfunc(incident_energy):\\n return XrayLibWrap_Energy(self.Z, \\\"cs\\\", incident_energy)\\n\\n return myfunc\",\n \"def gate(self, operator, target, control=None, control_0=None):\\n xp = self.xp\\n\\n if np.issubdtype(type(target), np.integer):\\n target = (target,)\\n if np.issubdtype(type(control), np.integer):\\n control = (control,)\\n if np.issubdtype(type(control_0), np.integer):\\n control_0 = (control_0,)\\n\\n operator = xp.asarray(operator, dtype=self.dtype)\\n if operator.shape[0] != 2:\\n operator = operator.reshape([2] * int(math.log2(operator.size)))\\n\\n assert operator.ndim == len(target) * 2, 'You must set operator.size==exp(len(target)*2)'\\n\\n c_slice = [slice(None)] * self.size\\n if control is not None:\\n for _c in control:\\n c_slice[_c] = slice(1, 2)\\n if control_0 is not None:\\n for _c in control_0:\\n c_slice[_c] = slice(0, 1)\\n c_slice = tuple(c_slice)\\n\\n c_index = list(range(self.size))\\n t_index = list(range(self.size))\\n for i, _t in enumerate(target):\\n t_index[_t] = self.size + i\\n o_index = list(range(self.size, self.size + len(target))) + list(target)\\n\\n # Use following code when numpy bug is removed and cupy can use this einsum format.\\n # self.data[c_slice] = xp.einsum(operator, o_index, self.data[c_slice], c_index, t_index)\\n\\n # Alternative code\\n character = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'\\n o_index = ''.join([character[i] for i in o_index])\\n c_index = ''.join([character[i] for i in c_index])\\n t_index = ''.join([character[i] for i in t_index])\\n subscripts = '{},{}->{}'.format(o_index, c_index, t_index)\\n self.data[c_slice] = xp.einsum(subscripts, operator, self.data[c_slice])\",\n \"def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6910946","0.6401429","0.5860972","0.5779722","0.57023156","0.5672864","0.5589705","0.55440325","0.5509337","0.5426937","0.53601813","0.5348523","0.53088343","0.52476794","0.5232436","0.5232274","0.5184903","0.5168113","0.5129279","0.51265514","0.5118267","0.5109546","0.50900245","0.50849664","0.50815225","0.5067264","0.50647175","0.50643283","0.5046034","0.50385517","0.503555","0.5026499","0.5022958","0.5022351","0.5020903","0.5019402","0.50096154","0.50045997","0.500447","0.500403","0.50010455","0.49577677","0.49536473","0.49532226","0.49508625","0.49375388","0.49363592","0.49355602","0.49270362","0.49170125","0.49125803","0.49096054","0.4905818","0.49021435","0.48971722","0.48906332","0.48865014","0.48789954","0.48767355","0.48744506","0.4873097","0.48716182","0.48697755","0.48683125","0.48619214","0.48589453","0.48466343","0.48433608","0.4829605","0.48190552","0.48184487","0.48151225","0.4800202","0.4796829","0.4789592","0.47879028","0.47801167","0.47686645","0.4764551","0.47624254","0.4761932","0.47585577","0.47556764","0.4755569","0.4754234","0.4753495","0.47520402","0.47517192","0.47490513","0.47469","0.47462034","0.4744417","0.4738742","0.47327483","0.4732604","0.47249132","0.47237268","0.47204262","0.47197652","0.47189465"],"string":"[\n \"0.6910946\",\n \"0.6401429\",\n \"0.5860972\",\n \"0.5779722\",\n \"0.57023156\",\n \"0.5672864\",\n \"0.5589705\",\n \"0.55440325\",\n \"0.5509337\",\n \"0.5426937\",\n \"0.53601813\",\n \"0.5348523\",\n \"0.53088343\",\n \"0.52476794\",\n \"0.5232436\",\n \"0.5232274\",\n \"0.5184903\",\n \"0.5168113\",\n \"0.5129279\",\n \"0.51265514\",\n \"0.5118267\",\n \"0.5109546\",\n \"0.50900245\",\n \"0.50849664\",\n \"0.50815225\",\n \"0.5067264\",\n \"0.50647175\",\n \"0.50643283\",\n \"0.5046034\",\n \"0.50385517\",\n \"0.503555\",\n \"0.5026499\",\n \"0.5022958\",\n \"0.5022351\",\n \"0.5020903\",\n \"0.5019402\",\n \"0.50096154\",\n \"0.50045997\",\n \"0.500447\",\n \"0.500403\",\n \"0.50010455\",\n \"0.49577677\",\n \"0.49536473\",\n \"0.49532226\",\n \"0.49508625\",\n \"0.49375388\",\n \"0.49363592\",\n \"0.49355602\",\n \"0.49270362\",\n \"0.49170125\",\n \"0.49125803\",\n \"0.49096054\",\n \"0.4905818\",\n \"0.49021435\",\n \"0.48971722\",\n \"0.48906332\",\n \"0.48865014\",\n \"0.48789954\",\n \"0.48767355\",\n \"0.48744506\",\n \"0.4873097\",\n \"0.48716182\",\n \"0.48697755\",\n \"0.48683125\",\n \"0.48619214\",\n \"0.48589453\",\n \"0.48466343\",\n \"0.48433608\",\n \"0.4829605\",\n \"0.48190552\",\n \"0.48184487\",\n \"0.48151225\",\n \"0.4800202\",\n \"0.4796829\",\n \"0.4789592\",\n \"0.47879028\",\n \"0.47801167\",\n \"0.47686645\",\n \"0.4764551\",\n \"0.47624254\",\n \"0.4761932\",\n \"0.47585577\",\n \"0.47556764\",\n \"0.4755569\",\n \"0.4754234\",\n \"0.4753495\",\n \"0.47520402\",\n \"0.47517192\",\n \"0.47490513\",\n \"0.47469\",\n \"0.47462034\",\n \"0.4744417\",\n \"0.4738742\",\n \"0.47327483\",\n \"0.4732604\",\n \"0.47249132\",\n \"0.47237268\",\n \"0.47204262\",\n \"0.47197652\",\n \"0.47189465\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.60488343"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81744,"cells":{"query":{"kind":"string","value":"add CZ gate (controlled Z gate)."},"document":{"kind":"string","value":"def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def CZ(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CZ, qubit_expr)","def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def Z(self, qubit_expr): \n self.apply_gate_operation('Z', qubit_expr)","def addZ(self,name):\n return self._addVar(name,self._zNames)","def addnewaccl(zs,ze,ez=0.,ap=0.,ax=0.,ay=0.,ox=0.,oy=0.,xw=0.,sw=0.,\n et=0.,ts=0.,dt=0.,\n time=None,data=None,func=None):\n # --- Make sure that at least some of the element is in the proper range,\n # --- z >= 0., and if zlatperi != 0, z <= zlatperi.\n assert (zs < ze),\"element start must be less than element end\"\n assert (top.zlatperi == 0.) or (ze > 0.),\"element end must be greater than zero if top.zlatperi is nonzero\"\n assert (top.zlatperi == 0.) or (zs < top.zlatperi),\"element start must be less than zlatperi if top.zlatperi is nonzero\"\n\n # --- Get a dict of the input arguments and their values.\n ldict = locals()\n\n # --- Setup the lattice arrays for the insertion of the new element. If\n # --- there are already accls, then find the place where the new one is to\n # --- be inserted and shift the existing data to open up a space.\n # --- Note that this uses that same check as in resetlat, that zs != ze to\n # --- determine whether or not a accl is defined.\n ie = 0\n # --- Find which element the new one goes before.\n while (ie <= top.naccl and top.acclzs[ie] <= zs and\n top.acclzs[ie] != top.acclze[ie]):\n ie = ie + 1\n\n # --- Increase the size of the arrays if the element will go past the end\n # --- or if the array is full (i.e. the last element is used).\n if ie > top.naccl or top.acclzs[-1] != top.acclze[-1]:\n top.naccl = top.naccl + 100\n gchange(\"Lattice\")\n if isinstance(et,(ndarray,collections.Sequence)) and len(et)-1 > top.ntaccl:\n top.ntaccl = len(et) - 1\n gchange(\"Lattice\")\n\n # --- Setup dictionary relating lattice array with input argument names.\n # --- This is done here so that the references to the lattice arrays\n # --- refer to the updated memory locations after the gchange.\n edict={'zs':top.acclzs,'ze':top.acclze,'ez':top.acclez,\n 'ap':top.acclap,'ax':top.acclax,'ay':top.acclay,\n 'ox':top.acclox,'oy':top.accloy,'xw':top.acclxw,'sw':top.acclsw,\n 'et':top.acclet,'ts':top.acclts,'dt':top.accldt}\n\n # --- Shift the existing data in the arrays to open up a space for the\n # --- new element.\n if ie <= top.naccl:\n for e in edict.itervalues():\n if len(shape(e)) == 1:\n e[ie+1:] = e[ie:-1] + 0\n else:\n # --- acclet is 2-D\n e[:,ie+1:] = e[:,ie:-1] + 0\n\n # --- Insert the new element. Note that edict correlates the lattice array\n # --- with the input arguments and ldict correlate the arguements with\n # --- their values.\n for (xx,e) in edict.iteritems():\n if len(shape(e)) == 1:\n e[ie] = ldict[xx]\n else:\n # --- acclet is 2-D\n e[:,ie] = ldict[xx]\n\n # --- resetlat must be called before the data can be used\n top.lresetlat = true\n\n if (time is not None and data is not None) or func is not None:\n tdle = TimeDependentLatticeElement('acclez',ie,time,data,func)\n return ie,tdle\n\n return ie","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def cPofZ(self,arr,zx):\n sig1=(zx-arr['zmg'])/arr['sigma_pz']\n sig2=(zx-self.zcat)/self.sigmacat\n return (1.-self.Acat)*0.5*(1 + erf(sig1/np.sqrt(2)))+self.Acat*0.5*(1 + erf(sig2/np.sqrt(2)))","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def zonal( self, fields, fun ):\n raise NotImplementedError(\"zonal\")","def set_z(self, value):\n\n # set the zero register if value is zero\n self.p &= ~(const.FLAG_ZERO)\n self.p |= const.FLAG_ZERO if value == 0b0 else 0b0","def set_zn(self, value):\n self.set_z(value)\n self.set_n(value)","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def circuit():\n np.random.seed(1967)\n for gates in gates_per_layers:\n for gate in gates:\n qml.apply(gate)\n return qml.expval(qml.PauliZ(0))","def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def gate2zx(box):\n if isinstance(box, (Bra, Ket)):\n dom, cod = (1, 0) if isinstance(box, Bra) else (0, 1)\n return Id(0).tensor(*[\n X(dom, cod, phase=.5 * bit) for bit in box.bitstring])\n if isinstance(box, (Rz, Rx)):\n return (Z if isinstance(box, Rz) else X)(1, 1, box.phase)\n if isinstance(box, CRz):\n return Z(1, 2) @ Z(1, 2, box.phase)\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\n if isinstance(box, CRx):\n return X(1, 2) @ X(1, 2, box.phase)\\\n >> Id(1) @ (Z(2, 1) >> X(1, 0, -box.phase)) @ Id(1)\n if isinstance(box, quantum.CU1):\n return Z(1, 2, box.phase) @ Z(1, 2, box.phase)\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\n standard_gates = {\n quantum.H: H,\n quantum.Z: Z(1, 1, .5),\n quantum.X: X(1, 1, .5),\n quantum.Y: Y(1, 1, .5),\n CZ: Z(1, 2) @ Id(1) >> Id(1) @ Had() @ Id(1) >> Id(1) @ Z(2, 1),\n CX: Z(1, 2) @ Id(1) >> Id(1) @ X(2, 1)}\n return standard_gates[box]","def z(self, z_position):\n print(f\"z: {z_position}\")\n self.device_control.z = z_position \n yield","def test_add_znode(self):\n z = self.test_start_empty()\n self.test_start_one_value(z)","def addFCSPoint(self, dxpos, dypos, dzpos=None):\n prefix = \"/cli:python /app:fcs /cmd:add\"\n dx = \"/xpos:\" + `int(dxpos)` \n dy = \"/ypos:\" + `int(dypos)`\n if dzpos is None:\n dz = \"/zpos:0\"\n else:\n dz = \"/zpos:\"+dzpos\n \n \n cmd = \" \".join((prefix,dx,dy,dz))\n #print \"FCS command string\"\n #print cmd\n self.sendCMDstring(cmd)","def __set_z__(self,z):\n\n # Input vaidation\n try:\n z = int(z)\n except:\n raise ValueError('H Bridge direction is not valid')\n \n if(z != 0 and z != 1 and z != -1):\n raise ValueError('H Bridge direction is not valid')\n \n self.direction['z'] = z\n self.HBridges['z'].SetDirection(z)","def set_z(self, operator_):\n nbr_params = len(signature(operator_).parameters)\n if nbr_params is 2:\n def oper(z):\n if len(z) == self.N+self.M:\n x = z[0:self.N]\n y = z[self.N:self.N+self.M]\n fx, fy, _ = operator_(x,y)\n if fy is None:\n return fx\n return np.concatenate((fx,fy))\n else:\n raise ValueError('set_z(operator_); len of z not correct. Please refer to the documentation.') \n return oper\n elif nbr_params is 3:\n def oper(z):\n if len(z) == self.N+self.M+self.U:\n x = z[0:self.N]\n y = z[self.N:self.N+self.M]\n u = z[self.N+self.M:self.N+self.M+self.U]\n fx, fy, fu = operator_(x,y,u)\n if fy is None:\n return fx\n return np.concatenate((fx,fy,fu))\n else:\n raise ValueError('set_z(operator_); len of z not correct. Please refer to the documentation.') \n return oper\n else : \n raise ValueError('set_z(operator_); operator can only have either 2 or 3 inputs. Please refer to the documentation.')","def _write_circuit(self, feature_vector_index):\n # grab the feature vector\n feature_vector = self.data.data[feature_vector_index]\n\n # compute the indices to put gates at\n inds = [x for x in range(len(feature_vector)) if feature_vector[x] == 1]\n\n # write the circuit\n self.circuits[feature_vector_index].add_layer(H)\n self.circuits[feature_vector_index].add_at(Z, inds)\n\n # TODO: all encoding classes will need this method.\n # TODO: make a BaseEncoding that implements this","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def keyZ(self):\n if pyxel.btnp(pyxel.KEY_Z):\n self.rotater(1)","def _apply_cz(self, state, axes, **kwargs):\n ndim = self._ndim(state)\n sl_0 = _get_slice(0, axes[0], ndim)\n sl_1 = _get_slice(1, axes[0], ndim)\n\n if axes[1] > axes[0]:\n target_axes = [axes[1] - 1]\n else:\n target_axes = [axes[1]]\n\n state_z = self._apply_z(state[sl_1], axes=target_axes)\n return self._stack([state[sl_0], state_z], axis=axes[0])","def zernikeJac(coeffs, x, y, z):\n\n coeffs = np.ones_like(coeffs)\n coeffs[:2] = 0\n\n jac = np.zeros((len(z),len(coeffs)))\n\n for i in range(2,len(coeffs)):\n cis = np.zeros(36)\n cis[i] = 1.\n jac[i] = zernikePoly(x, y, midPoint(x), midPoint(y), cis)\n\n return jac","def zguider():\n gzero.gxoff = camera.status.guider[0] + gzero.gxoff\n gzero.gyoff = camera.status.guider[1] + gzero.gyoff\n guider(0,0)\n f = open('/data/guidezero','w')\n cPickle.dump(gzero,f)\n f.close()","def _derZ(self, x, y, z):\n raise NotImplementedError()","def ZZ(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.ZZ, qubit_expr)","def _represent_ZGate(self, basis, **options):\n _format = options.get('format', 'sympy')\n n = 1\n definite_state = 0\n for it in reversed(self.qubit_values):\n definite_state += n*it\n n = n*2\n result = [0]*(2**self.dimension)\n result[int(definite_state)] = 1\n if _format == 'sympy':\n return Matrix(result)\n elif _format == 'numpy':\n import numpy as np\n return np.array(result, dtype='complex').transpose()\n elif _format == 'scipy.sparse':\n from scipy import sparse\n return sparse.csr_matrix(result, dtype='complex').transpose()","def assemble_circuit(self, circuit: Circuit):\n\n if self.depth is None:\n return circuit.invert()\n gates_qubits_pairs = find_gates_qubits_pairs(circuit)\n circuit_gates = len(gates_qubits_pairs)\n if circuit_gates == 0:\n raise ValueError(\"The circuit must contain at least a two qubit gate.\")\n repetitions, remainder = divmod(self.depth, circuit_gates)\n assembled_gates_qubits_pairs = []\n for _ in range(repetitions):\n assembled_gates_qubits_pairs += gates_qubits_pairs[:]\n gates_qubits_pairs.reverse()\n assembled_gates_qubits_pairs += gates_qubits_pairs[0:remainder]\n new_circuit = Circuit(circuit.nqubits)\n for qubits in assembled_gates_qubits_pairs:\n # As only the connectivity is important here we can replace everything with CZ gates\n new_circuit.add(gates.CZ(qubits[0], qubits[1]))\n return new_circuit.invert()","def _derZ(self, w, x, y, z):\n raise NotImplementedError()","def test_cz_gate_nondeterministic_waltz_basis_gates(self):\n shots = 2000\n circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_2q_clifford.cz_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='u1,u2,u3,cx')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def generate(self, z):\n\t\tx = z\n\t\tfor i in reversed(range(self.nCouplingLayers)):\n\t\t\tx, _ = self.CouplingLayers[i](x, generating=True)\n\t\t\t\n\t\treturn x","def add_zca_whitening(self, pc=None):\n self.global_pc.is_required = True\n self.global_pc.value = pc\n self.methods.append(self._zca_whitening)\n self.args.append(None)","def _compute_carry_and_output_fused(self, z, c_tm1):\n z0, z1, z2, z3 = z\n i = self.recurrent_activation(z0)\n f = self.recurrent_activation(z1)\n c = f * c_tm1 + i * self.activation(z2)\n o = self.recurrent_activation(z3)\n return c, o","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def zernikeCost(coeffs, x, y, z, w):\n\n zpoly = zernikePoly(x, y, midPoint(x), midPoint(y), coeffs)\n\n return w*(z.flatten() - zpoly.flatten())","def z_flag(self):\n if self.calibrationlogflag:\n self.calibrationlog = DEFAULT_CALIBRATIONLOG_D3S","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def _gyration(self, x, y, v, c):\n xy = self._mobius_add(x, y, c)\n yv = self._mobius_add(y, v, c)\n xyv = self._mobius_add(x, yv, c)\n return self._mobius_add(-xy, xyv, c)","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def circuitSat(C):","def pressZ(self):\n self.enableLastButton('Z')\n self.disableButton('Z')\n self.setMyIndustryData('b')\n self.createIndustryInfo()","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def f(z,c):\n zz = z*z + c\n return zz","def c(self, z, y, r, t):\n \n u = np.zeros( self.m ) \n \n return u","def BNE(self, value):\n if not self.reg.Z:\n self.reg.PC += value","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def construct_qcbm(circuit, n_qubits, depth):\n\n for d in range(depth):\n for i in range(n_qubits):\n circuit.append_gate(Gate('X', target = i, angle = np.random.random()*np.pi*2))\n circuit.append_gate(Gate('Z', target = i, angle = np.random.random()*np.pi*2))\n if n_qubits != 1:\n for i in range(n_qubits):\n circuit.append_gate(Gate('CNOT', control = i, target = (i+1)%n_qubits))\n return circuit","def zncc(template, image):\n std_template = np.std(template)\n if std_template == 0:\n return 0\n\n std_image = np.std(image)\n if std_image == 0:\n return 0\n\n template_t = template - np.mean(template)\n image_t = image - np.mean(image)\n\n cross_correlation = np.mean(np.multiply(template_t, image_t)) / (std_template * std_image)\n return cross_correlation","def AlphaCyc(ss, train):\n\n if ss.Win != 0:\n ss.Win.PollEvents() # this is essential for GUI responsiveness while running\n viewUpdt = ss.TrainUpdt.value\n if not train:\n viewUpdt = ss.TestUpdt.value\n\n # update prior weight changes at start, so any DWt values remain visible at end\n # you might want to do this less frequently to achieve a mini-batch update\n # in which case, move it out to the TrainTrial method where the relevant\n # counters are being dealt with.\n if train:\n ss.Net.WtFmDWt()\n\n ss.Net.AlphaCycInit(train)\n ss.Time.AlphaCycStart()\n for qtr in range(4):\n for cyc in range(ss.Time.CycPerQtr):\n ss.Net.Cycle(ss.Time)\n ss.Time.CycleInc()\n if ss.ViewOn:\n if viewUpdt == leabra.Cycle:\n if cyc != ss.Time.CycPerQtr-1: # will be updated by quarter\n ss.UpdateView(train)\n if viewUpdt == leabra.FastSpike:\n if (cyc+1)%10 == 0:\n ss.UpdateView(train)\n ss.Net.QuarterFinal(ss.Time)\n ss.Time.QuarterInc()\n if ss.ViewOn:\n if viewUpdt <= leabra.Quarter:\n ss.UpdateView(train)\n if viewUpdt == leabra.Phase:\n if qtr >= 2:\n ss.UpdateView(train)\n\n if train:\n ss.Net.DWt()\n if ss.ViewOn and viewUpdt == leabra.AlphaCycle:\n ss.UpdateView(train)","def add_to_zview(self, name, x, fail):\r\n\r\n return \"\"\"\r\n PyArrayObject * add_rval = (PyArrayObject*)PyNumber_InPlaceAdd(\r\n (PyObject*)zview, py_%(x)s);\r\n if (add_rval)\r\n {\r\n assert (PyArray_Check((PyObject*)add_rval));\r\n assert (PyArray_DATA(add_rval) == PyArray_DATA(zview));\r\n Py_DECREF(add_rval);\r\n }\r\n else\r\n {\r\n Py_DECREF(zview);\r\n %(fail)s;\r\n }\"\"\" % locals()","def test_cz_gate_deterministic_waltz_basis_gates(self):\n shots = 100\n circuits = ref_2q_clifford.cz_gate_circuits_deterministic(final_measure=True)\n targets = ref_2q_clifford.cz_gate_counts_deterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='u1,u2,u3,cx')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0)","def CX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)","def _control_predefined(operation, num_ctrl_qubits):\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\n if num_ctrl_qubits == 1:\n import qiskit.extensions.standard.cx\n cgate = qiskit.extensions.standard.cx.CnotGate()\n else:\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n elif operation.name == 'y':\n import qiskit.extensions.standard.cy\n cgate = qiskit.extensions.standard.cy.CyGate()\n elif operation.name == 'z':\n import qiskit.extensions.standard.cz\n cgate = qiskit.extensions.standard.cz.CzGate()\n elif operation.name == 'h':\n import qiskit.extensions.standard.ch\n cgate = qiskit.extensions.standard.ch.CHGate()\n elif operation.name in {'rx', 'ry', 'rz'}:\n if operation.name == 'rx':\n import qiskit.extensions.standard.crx\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\n elif operation.name == 'ry':\n import qiskit.extensions.standard.cry\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\n else: # operation.name == 'rz'\n import qiskit.extensions.standard.crz\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\n if num_ctrl_qubits == 1:\n return cgate\n else:\n # only predefined for one control qubit\n return cgate.control(num_ctrl_qubits - 1)\n elif operation.name == 'swap':\n import qiskit.extensions.standard.cswap\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\n elif operation.name == 'u1':\n import qiskit.extensions.standard.cu1\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\n elif operation.name == 'u3':\n import qiskit.extensions.standard.cu3\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\n elif operation.name == 'cx':\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n else:\n raise QiskitError('No standard controlled gate for \"{}\"'.format(\n operation.name))\n return cgate","def setZ(self, z):\n self.position.setZ(z)","def compute_Az(self, r, z, qOc):\n\n kr_cross_r = einsum('r, p -> rp', self.kr, r)\n kz_cross_z = einsum('z, p -> zp', self.kz, z)\n delta_r = np.ones(np.size(r)) * self.ptcl_width_r\n delta_u = einsum('r, p -> rp', self.kr, delta_r)\n convolved_j0 = self.convolved_j0(kr_cross_r, delta_u)\n convolved_cos = einsum('zp, z -> zp', cos(kz_cross_z), self.shape_function_z)\n\n modeQz = self.omegaOtwokr * (self.dc_coords[:,:,1] + self.omega_coords[:,:,1])\n\n self.tanhz = -np.tanh(((z - self.z_mean) ** 2 - self.z_mean ** 2) * self.tanh_width ** 2)\n # We dress the charge instead of the fields proper\n dressed_charge = self.tanhz*qOc\n\n Az = einsum('zr, rp, zp -> p', modeQz, convolved_j0, convolved_cos)*dressed_charge\n\n return Az","def setZ(self, *args):\n return _libsbml.Point_setZ(self, *args)","def estimateCs(y, inp):\n\treturn 1 -(math.tanh(getK1(inp) - (y/getY90(inp)) / (2 * getD0(inp)) + (y/getY90(inp) - 1/3.0)**3 / (3 * getD0(inp))))**2","def test_special_ZYZ(self, angexp):\n a, b, c, d = angexp[0]\n exp = {(\"rz\", \"ry\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\n tgt = np.exp(1j * d) * RZGate(b).to_matrix() @ RYGate(a).to_matrix() @ RZGate(c).to_matrix()\n self.check_oneq_special_cases(tgt, \"ZYZ\", exp)","def BCS(self, value):\n if self.reg.C:\n self.reg.PC += value","def cy(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CY(), target=[control, target])","def pz_fn(self, z):\n pass","def TAY(self, *_):\n self.reg.Y = self.reg.A\n self.reg.N = self.reg.Y << 7\n self.reg.Z = self.reg.Y == 0","def __init__(self,x_c,z_c,cyl_rad):\n self.x_c = x_c\n self.z_c = z_c\n self.cyl_rad = cyl_rad","def __init__(self,x_c,z_c,cyl_rad):\n self.x_c = x_c\n self.z_c = z_c\n self.cyl_rad = cyl_rad","def __init__(self,x_c,z_c,cyl_rad):\n self.x_c = x_c\n self.z_c = z_c\n self.cyl_rad = cyl_rad","def __init__(self,x_c,z_c,cyl_rad):\n self.x_c = x_c\n self.z_c = z_c\n self.cyl_rad = cyl_rad","def __init__(self,x_c,z_c,cyl_rad):\n self.x_c = x_c\n self.z_c = z_c\n self.cyl_rad = cyl_rad","def pre_defined_circuit(env: 'QEnv', q: List['QRegStorage'], gate_list: List[operatorType]) -> 'QEnv':\n if gate_list:\n for gate in gate_list:\n if gate.bits == 1:\n gate(q[0])\n elif gate.bits == 2:\n gate(q[0], q[1])\n return env","def Es_case_C(z, x, gamma, alp, lamb):\n\n if z == 0 and x == 0 and alp == 0:\n return 0\n \n beta2 = 1-1/gamma**2\n beta = sqrt(beta2)\n \n sin2a = sin(2*alp)\n cos2a = cos(2*alp) \n eta = eta_case_C(z, x, beta2, alp, lamb)\n \n kap = (2*(alp - z) + eta + lamb)/beta # kappa for case C\n #kap = sqrt( lamb**2 + eta**2 + x**2 + 4*(1+x)*sin(alp)**2 + 2*(lamb + eta*(1+x))*sin2a + 2*lamb*eta*cos2a) \n \n N = lamb + sin2a + (eta - beta*kap)*cos2a\n D = kap - beta*(eta + lamb*cos2a + (1+x)*sin2a)\n \n return N/D**3","def test_cz_gate_nondeterministic_minimal_basis_gates(self):\n shots = 2000\n circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_2q_clifford.cz_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def add_neurone(self, couche, nbr=1):\n if self.control == 0:\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\n self.couche[couche] += nbr\n else:\n print(\"Le réseau est deja créé, vous en pouvez plus le modifier\")","def add_computed_gas_concentrations(self):\n # Extract the z-coordinate and T, S, P profile\n zs = self.interp_ds.coords[self.ztsp[0]].values\n Ts = self.interp_ds[self.ztsp[1]].values\n Ss = self.interp_ds[self.ztsp[2]].values\n Ps = self.interp_ds[self.ztsp[3]].values\n \n # Create an air object\n air_names = ['nitrogen', 'oxygen', 'argon', 'carbon_dioxide']\n yk = np.array([0.78084, 0.20946, 0.009340, 0.00036])\n from tamoc import dbm\n air = dbm.FluidMixture(air_names)\n m = air.masses(yk)\n \n # Compute the concentrations adjusted for depth\n Cs = np.zeros((len(zs), len(air_names)))\n for i in range(len(zs)):\n Cs[i,:] = air.solubility(m, Ts[i], 101325., Ss[i])[0,:] * \\\n seawater.density(Ts[i], Ss[i], Ps[i]) / \\\n seawater.density(Ts[i], Ss[i], 101325.)\n \n # Make sure none of these gases are already in the measured profile\n for name in air_names:\n if name in self.interp_ds:\n air_names[air_names.index(name)] = 'computed_' + name\n \n # Add these data to the Profile object\n data = np.hstack((np.atleast_2d(zs).transpose(), Cs))\n names = [self.ztsp[0]] + air_names \n units = [self.ztsp_units[0]] + 4*['kg/m^3']\n self.append(data, names, units)\n \n # Rebuild the interpolator\n self._build_interpolator()","def test_iadd(self):\n qc_cal = QuantumCircuit(2)\n qc_cal.rzx(0.5, 0, 1)\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\n\n qc = QuantumCircuit(2)\n qc &= qc_cal\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)","def createCornerPin():\n i = b.createNode('CornerPinMI')\n i['tile_color'].setValue(int('%02x%02x%02x%02x' % (232.05, 145.095, 0, 255), 16))\n if cc:\n i = gU(i)\n return i","def removeZeroModeFromComa(self):\n#\t\tprint \"BUGGGGGGGGGGGGGGGGGGGGGGG#EFAHR\"\n#\t\treturn\n#\t\tprint 'Remove zm'\n\t\tif self.zeroModesRemovedFromComa:\n\t\t\tprint \"DO NOT REMOVE ZER MODE A SECOND TIME\"\n\t\t\treturn\n\n\t\tself.zeroModesRemovedFromComa = True\n\t\tif len(self.zeroModes) == 0:\n\t\t\treturn\n\t\tdim = len(self.coma)\n\t\ttransformationMatrix = np.identity(dim)\n#\t#\tCMwrite(\"removeZeroModeFromComa\")\n\t\tfor z in range(self.nZero):\n\t\t\tfor i in range(dim/2):\n\t\t\t\tfor j in range(dim/2):\n\t\t\t\t\ttransformationMatrix[2*i ,2*j ] -= self.zeroModes[z][i] * self.zeroModes[z][j]\n\t\t\t\t\ttransformationMatrix[2*i+1,2*j+1] -= self.zeroModes[z][i] * self.zeroModes[z][j]\n\t\tself.coma = np.dot(transformationMatrix, np.dot(self.coma, transformationMatrix)) # no transpose needed, since transformationMatrix is symmetric\n\t\tself.makeComaInv()\n\t\tself.specialCOMAs = {}","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def bcc(self, arg):\n\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def test_special_ZXZ(self, angexp):\n a, b, c, d = angexp[0]\n exp = {(\"rz\", \"rx\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\n tgt = np.exp(1j * d) * RZGate(b).to_matrix() @ RXGate(a).to_matrix() @ RZGate(c).to_matrix()\n self.check_oneq_special_cases(tgt, \"ZXZ\", exp)","def __init__(self, input0, input1, output) :\n Gate.__init__(self, [input0,input1], output)","def add_connector(self):\n \n no = len(self.connectors)\n state = {}\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % no\n \n if len(self.connectors)>0:\n state = self.connectors[-1].get_state()\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % (no)\n else:\n if self.mount == self.MOUNT_THT:\n state[\"p_shape\"] = Con.SHAPE_HOLE\n elif self.mount == self.MOUNT_SMD:\n state[\"p_shape\"] = Con.SHAPE_PAD\n \n c = Con(no)\n c.set_state(state) \n \n self.sch_layers[\"pins\"].add(c.s_svg)\n self.pcb_layers[\"copper1\"].add(c.p_svg)\n self.connectors.append(c)","def zenazi(scx_l, scx_b, scy_l, scy_b, scz_l, scz_b, src_l, src_b):\n # Zenith is the distance from the optical axis (here z)\n costheta = GreatCircle(scz_l,scz_b,src_l,src_b) \n # Azimuth is the combination of the remaining two\n cosx = GreatCircle(scx_l,scx_b,src_l,src_b)\n cosy = GreatCircle(scy_l,scy_b,src_l,src_b)\n \n # check exceptions\n # maybe not for vectorisation\n \"\"\"\n if costheta.size == 1:\n if (costheta > 1.0):\n costheta = 1.0\n if (costheta < -1.0):\n costheta = -1.0\n else:\n costheta[costheta > 1.0] = 1.0\n costheta[costheta < -1.0] = -1.0\n \"\"\"\n # theta = zenith\n theta = np.rad2deg(np.arccos(costheta))\n # phi = azimuth\n phi = np.rad2deg(np.arctan2(cosy,cosx)) # TS January 14: you sure about that? changed y and x\n \n # make azimuth going from 0 to 360 deg\n if phi.size == 1:\n if (phi < 0):\n phi += 360\n else:\n phi[phi < 0] += 360\n \n return theta,phi","def __init__(self, **kwargs):\n\t\tself.__c_version = c_singlezone(**kwargs)","def __call__(self,Zin):\r\n self.Z = np.zeros((self.Nc,))\r\n for ii in range(0,self.Nc):\r\n self.Z[ii] = np.dot(self.W[:,ii],Zin[self.ind[ii,:]])\r\n \r\n return self.Z","def compute_z_curr(Z_opt, z_prev1, z_diff, alpha):\r\n z_curr = alpha * Z_opt + (1 - alpha) * (z_prev1 + z_diff)\r\n return z_curr","def add_control(operation, num_ctrl_qubits, label):\n if isinstance(operation, UnitaryGate):\n # attempt decomposition\n operation._define()\n if _control_definition_known(operation, num_ctrl_qubits):\n return _control_predefined(operation, num_ctrl_qubits)\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)","def __init__(self, input, output) :\n Gate.__init__(self, [input], output)","def plot_eccentricity(self, z=0):\n p = figure(\n title=\"Cut in plane Z=\" + str(z),\n x_axis_label=\"X axis\",\n y_axis_label=\"Y axis\",\n )\n for j in range(0, self.ntheta):\n p.circle(self.xre[z][j], self.yre[z][j], color=\"red\")\n p.circle(self.xri[z][j], self.yri[z][j], color=\"blue\")\n p.circle(0, 0, color=\"blue\")\n p.circle(self.xi, self.yi, color=\"red\")\n p.circle(0, 0, color=\"black\")\n return p","def z(self, value: Number):\n self._translation[2, 0] = value","def f_c(self, z, m):\n\t return (1. - self.f_o(z))*m/(self.ALPHA_1*self.mmax + m)","def zz(x):\r\n return Feature(x, \"ZZ\")","def test_add(self):\n qc_cal = QuantumCircuit(2)\n qc_cal.rzx(0.5, 0, 1)\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\n\n qc = QuantumCircuit(2) & qc_cal\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\n\n qc = qc_cal & QuantumCircuit(2)\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)","def z_defocus(w0, c, d, A, B):\n return lambda z: (\n w0 * np.sqrt(1 + \\\n ((z - c)/d)**2 + A*((z - c)/d)**3 + B*((z - c)/d)**4)\n )"],"string":"[\n \"def CZ(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.CZ, qubit_expr)\",\n \"def cz(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CZ(), target=[control, target])\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def Z(self, qubit_expr): \\n self.apply_gate_operation('Z', qubit_expr)\",\n \"def addZ(self,name):\\n return self._addVar(name,self._zNames)\",\n \"def addnewaccl(zs,ze,ez=0.,ap=0.,ax=0.,ay=0.,ox=0.,oy=0.,xw=0.,sw=0.,\\n et=0.,ts=0.,dt=0.,\\n time=None,data=None,func=None):\\n # --- Make sure that at least some of the element is in the proper range,\\n # --- z >= 0., and if zlatperi != 0, z <= zlatperi.\\n assert (zs < ze),\\\"element start must be less than element end\\\"\\n assert (top.zlatperi == 0.) or (ze > 0.),\\\"element end must be greater than zero if top.zlatperi is nonzero\\\"\\n assert (top.zlatperi == 0.) or (zs < top.zlatperi),\\\"element start must be less than zlatperi if top.zlatperi is nonzero\\\"\\n\\n # --- Get a dict of the input arguments and their values.\\n ldict = locals()\\n\\n # --- Setup the lattice arrays for the insertion of the new element. If\\n # --- there are already accls, then find the place where the new one is to\\n # --- be inserted and shift the existing data to open up a space.\\n # --- Note that this uses that same check as in resetlat, that zs != ze to\\n # --- determine whether or not a accl is defined.\\n ie = 0\\n # --- Find which element the new one goes before.\\n while (ie <= top.naccl and top.acclzs[ie] <= zs and\\n top.acclzs[ie] != top.acclze[ie]):\\n ie = ie + 1\\n\\n # --- Increase the size of the arrays if the element will go past the end\\n # --- or if the array is full (i.e. the last element is used).\\n if ie > top.naccl or top.acclzs[-1] != top.acclze[-1]:\\n top.naccl = top.naccl + 100\\n gchange(\\\"Lattice\\\")\\n if isinstance(et,(ndarray,collections.Sequence)) and len(et)-1 > top.ntaccl:\\n top.ntaccl = len(et) - 1\\n gchange(\\\"Lattice\\\")\\n\\n # --- Setup dictionary relating lattice array with input argument names.\\n # --- This is done here so that the references to the lattice arrays\\n # --- refer to the updated memory locations after the gchange.\\n edict={'zs':top.acclzs,'ze':top.acclze,'ez':top.acclez,\\n 'ap':top.acclap,'ax':top.acclax,'ay':top.acclay,\\n 'ox':top.acclox,'oy':top.accloy,'xw':top.acclxw,'sw':top.acclsw,\\n 'et':top.acclet,'ts':top.acclts,'dt':top.accldt}\\n\\n # --- Shift the existing data in the arrays to open up a space for the\\n # --- new element.\\n if ie <= top.naccl:\\n for e in edict.itervalues():\\n if len(shape(e)) == 1:\\n e[ie+1:] = e[ie:-1] + 0\\n else:\\n # --- acclet is 2-D\\n e[:,ie+1:] = e[:,ie:-1] + 0\\n\\n # --- Insert the new element. Note that edict correlates the lattice array\\n # --- with the input arguments and ldict correlate the arguements with\\n # --- their values.\\n for (xx,e) in edict.iteritems():\\n if len(shape(e)) == 1:\\n e[ie] = ldict[xx]\\n else:\\n # --- acclet is 2-D\\n e[:,ie] = ldict[xx]\\n\\n # --- resetlat must be called before the data can be used\\n top.lresetlat = true\\n\\n if (time is not None and data is not None) or func is not None:\\n tdle = TimeDependentLatticeElement('acclez',ie,time,data,func)\\n return ie,tdle\\n\\n return ie\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def cPofZ(self,arr,zx):\\n sig1=(zx-arr['zmg'])/arr['sigma_pz']\\n sig2=(zx-self.zcat)/self.sigmacat\\n return (1.-self.Acat)*0.5*(1 + erf(sig1/np.sqrt(2)))+self.Acat*0.5*(1 + erf(sig2/np.sqrt(2)))\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def zonal( self, fields, fun ):\\n raise NotImplementedError(\\\"zonal\\\")\",\n \"def set_z(self, value):\\n\\n # set the zero register if value is zero\\n self.p &= ~(const.FLAG_ZERO)\\n self.p |= const.FLAG_ZERO if value == 0b0 else 0b0\",\n \"def set_zn(self, value):\\n self.set_z(value)\\n self.set_n(value)\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def circuit():\\n np.random.seed(1967)\\n for gates in gates_per_layers:\\n for gate in gates:\\n qml.apply(gate)\\n return qml.expval(qml.PauliZ(0))\",\n \"def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def gate2zx(box):\\n if isinstance(box, (Bra, Ket)):\\n dom, cod = (1, 0) if isinstance(box, Bra) else (0, 1)\\n return Id(0).tensor(*[\\n X(dom, cod, phase=.5 * bit) for bit in box.bitstring])\\n if isinstance(box, (Rz, Rx)):\\n return (Z if isinstance(box, Rz) else X)(1, 1, box.phase)\\n if isinstance(box, CRz):\\n return Z(1, 2) @ Z(1, 2, box.phase)\\\\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\\n if isinstance(box, CRx):\\n return X(1, 2) @ X(1, 2, box.phase)\\\\\\n >> Id(1) @ (Z(2, 1) >> X(1, 0, -box.phase)) @ Id(1)\\n if isinstance(box, quantum.CU1):\\n return Z(1, 2, box.phase) @ Z(1, 2, box.phase)\\\\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\\n standard_gates = {\\n quantum.H: H,\\n quantum.Z: Z(1, 1, .5),\\n quantum.X: X(1, 1, .5),\\n quantum.Y: Y(1, 1, .5),\\n CZ: Z(1, 2) @ Id(1) >> Id(1) @ Had() @ Id(1) >> Id(1) @ Z(2, 1),\\n CX: Z(1, 2) @ Id(1) >> Id(1) @ X(2, 1)}\\n return standard_gates[box]\",\n \"def z(self, z_position):\\n print(f\\\"z: {z_position}\\\")\\n self.device_control.z = z_position \\n yield\",\n \"def test_add_znode(self):\\n z = self.test_start_empty()\\n self.test_start_one_value(z)\",\n \"def addFCSPoint(self, dxpos, dypos, dzpos=None):\\n prefix = \\\"/cli:python /app:fcs /cmd:add\\\"\\n dx = \\\"/xpos:\\\" + `int(dxpos)` \\n dy = \\\"/ypos:\\\" + `int(dypos)`\\n if dzpos is None:\\n dz = \\\"/zpos:0\\\"\\n else:\\n dz = \\\"/zpos:\\\"+dzpos\\n \\n \\n cmd = \\\" \\\".join((prefix,dx,dy,dz))\\n #print \\\"FCS command string\\\"\\n #print cmd\\n self.sendCMDstring(cmd)\",\n \"def __set_z__(self,z):\\n\\n # Input vaidation\\n try:\\n z = int(z)\\n except:\\n raise ValueError('H Bridge direction is not valid')\\n \\n if(z != 0 and z != 1 and z != -1):\\n raise ValueError('H Bridge direction is not valid')\\n \\n self.direction['z'] = z\\n self.HBridges['z'].SetDirection(z)\",\n \"def set_z(self, operator_):\\n nbr_params = len(signature(operator_).parameters)\\n if nbr_params is 2:\\n def oper(z):\\n if len(z) == self.N+self.M:\\n x = z[0:self.N]\\n y = z[self.N:self.N+self.M]\\n fx, fy, _ = operator_(x,y)\\n if fy is None:\\n return fx\\n return np.concatenate((fx,fy))\\n else:\\n raise ValueError('set_z(operator_); len of z not correct. Please refer to the documentation.') \\n return oper\\n elif nbr_params is 3:\\n def oper(z):\\n if len(z) == self.N+self.M+self.U:\\n x = z[0:self.N]\\n y = z[self.N:self.N+self.M]\\n u = z[self.N+self.M:self.N+self.M+self.U]\\n fx, fy, fu = operator_(x,y,u)\\n if fy is None:\\n return fx\\n return np.concatenate((fx,fy,fu))\\n else:\\n raise ValueError('set_z(operator_); len of z not correct. Please refer to the documentation.') \\n return oper\\n else : \\n raise ValueError('set_z(operator_); operator can only have either 2 or 3 inputs. Please refer to the documentation.')\",\n \"def _write_circuit(self, feature_vector_index):\\n # grab the feature vector\\n feature_vector = self.data.data[feature_vector_index]\\n\\n # compute the indices to put gates at\\n inds = [x for x in range(len(feature_vector)) if feature_vector[x] == 1]\\n\\n # write the circuit\\n self.circuits[feature_vector_index].add_layer(H)\\n self.circuits[feature_vector_index].add_at(Z, inds)\\n\\n # TODO: all encoding classes will need this method.\\n # TODO: make a BaseEncoding that implements this\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def keyZ(self):\\n if pyxel.btnp(pyxel.KEY_Z):\\n self.rotater(1)\",\n \"def _apply_cz(self, state, axes, **kwargs):\\n ndim = self._ndim(state)\\n sl_0 = _get_slice(0, axes[0], ndim)\\n sl_1 = _get_slice(1, axes[0], ndim)\\n\\n if axes[1] > axes[0]:\\n target_axes = [axes[1] - 1]\\n else:\\n target_axes = [axes[1]]\\n\\n state_z = self._apply_z(state[sl_1], axes=target_axes)\\n return self._stack([state[sl_0], state_z], axis=axes[0])\",\n \"def zernikeJac(coeffs, x, y, z):\\n\\n coeffs = np.ones_like(coeffs)\\n coeffs[:2] = 0\\n\\n jac = np.zeros((len(z),len(coeffs)))\\n\\n for i in range(2,len(coeffs)):\\n cis = np.zeros(36)\\n cis[i] = 1.\\n jac[i] = zernikePoly(x, y, midPoint(x), midPoint(y), cis)\\n\\n return jac\",\n \"def zguider():\\n gzero.gxoff = camera.status.guider[0] + gzero.gxoff\\n gzero.gyoff = camera.status.guider[1] + gzero.gyoff\\n guider(0,0)\\n f = open('/data/guidezero','w')\\n cPickle.dump(gzero,f)\\n f.close()\",\n \"def _derZ(self, x, y, z):\\n raise NotImplementedError()\",\n \"def ZZ(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.ZZ, qubit_expr)\",\n \"def _represent_ZGate(self, basis, **options):\\n _format = options.get('format', 'sympy')\\n n = 1\\n definite_state = 0\\n for it in reversed(self.qubit_values):\\n definite_state += n*it\\n n = n*2\\n result = [0]*(2**self.dimension)\\n result[int(definite_state)] = 1\\n if _format == 'sympy':\\n return Matrix(result)\\n elif _format == 'numpy':\\n import numpy as np\\n return np.array(result, dtype='complex').transpose()\\n elif _format == 'scipy.sparse':\\n from scipy import sparse\\n return sparse.csr_matrix(result, dtype='complex').transpose()\",\n \"def assemble_circuit(self, circuit: Circuit):\\n\\n if self.depth is None:\\n return circuit.invert()\\n gates_qubits_pairs = find_gates_qubits_pairs(circuit)\\n circuit_gates = len(gates_qubits_pairs)\\n if circuit_gates == 0:\\n raise ValueError(\\\"The circuit must contain at least a two qubit gate.\\\")\\n repetitions, remainder = divmod(self.depth, circuit_gates)\\n assembled_gates_qubits_pairs = []\\n for _ in range(repetitions):\\n assembled_gates_qubits_pairs += gates_qubits_pairs[:]\\n gates_qubits_pairs.reverse()\\n assembled_gates_qubits_pairs += gates_qubits_pairs[0:remainder]\\n new_circuit = Circuit(circuit.nqubits)\\n for qubits in assembled_gates_qubits_pairs:\\n # As only the connectivity is important here we can replace everything with CZ gates\\n new_circuit.add(gates.CZ(qubits[0], qubits[1]))\\n return new_circuit.invert()\",\n \"def _derZ(self, w, x, y, z):\\n raise NotImplementedError()\",\n \"def test_cz_gate_nondeterministic_waltz_basis_gates(self):\\n shots = 2000\\n circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_2q_clifford.cz_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='u1,u2,u3,cx')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def generate(self, z):\\n\\t\\tx = z\\n\\t\\tfor i in reversed(range(self.nCouplingLayers)):\\n\\t\\t\\tx, _ = self.CouplingLayers[i](x, generating=True)\\n\\t\\t\\t\\n\\t\\treturn x\",\n \"def add_zca_whitening(self, pc=None):\\n self.global_pc.is_required = True\\n self.global_pc.value = pc\\n self.methods.append(self._zca_whitening)\\n self.args.append(None)\",\n \"def _compute_carry_and_output_fused(self, z, c_tm1):\\n z0, z1, z2, z3 = z\\n i = self.recurrent_activation(z0)\\n f = self.recurrent_activation(z1)\\n c = f * c_tm1 + i * self.activation(z2)\\n o = self.recurrent_activation(z3)\\n return c, o\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def zernikeCost(coeffs, x, y, z, w):\\n\\n zpoly = zernikePoly(x, y, midPoint(x), midPoint(y), coeffs)\\n\\n return w*(z.flatten() - zpoly.flatten())\",\n \"def z_flag(self):\\n if self.calibrationlogflag:\\n self.calibrationlog = DEFAULT_CALIBRATIONLOG_D3S\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def _gyration(self, x, y, v, c):\\n xy = self._mobius_add(x, y, c)\\n yv = self._mobius_add(y, v, c)\\n xyv = self._mobius_add(x, yv, c)\\n return self._mobius_add(-xy, xyv, c)\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def circuitSat(C):\",\n \"def pressZ(self):\\n self.enableLastButton('Z')\\n self.disableButton('Z')\\n self.setMyIndustryData('b')\\n self.createIndustryInfo()\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def f(z,c):\\n zz = z*z + c\\n return zz\",\n \"def c(self, z, y, r, t):\\n \\n u = np.zeros( self.m ) \\n \\n return u\",\n \"def BNE(self, value):\\n if not self.reg.Z:\\n self.reg.PC += value\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def construct_qcbm(circuit, n_qubits, depth):\\n\\n for d in range(depth):\\n for i in range(n_qubits):\\n circuit.append_gate(Gate('X', target = i, angle = np.random.random()*np.pi*2))\\n circuit.append_gate(Gate('Z', target = i, angle = np.random.random()*np.pi*2))\\n if n_qubits != 1:\\n for i in range(n_qubits):\\n circuit.append_gate(Gate('CNOT', control = i, target = (i+1)%n_qubits))\\n return circuit\",\n \"def zncc(template, image):\\n std_template = np.std(template)\\n if std_template == 0:\\n return 0\\n\\n std_image = np.std(image)\\n if std_image == 0:\\n return 0\\n\\n template_t = template - np.mean(template)\\n image_t = image - np.mean(image)\\n\\n cross_correlation = np.mean(np.multiply(template_t, image_t)) / (std_template * std_image)\\n return cross_correlation\",\n \"def AlphaCyc(ss, train):\\n\\n if ss.Win != 0:\\n ss.Win.PollEvents() # this is essential for GUI responsiveness while running\\n viewUpdt = ss.TrainUpdt.value\\n if not train:\\n viewUpdt = ss.TestUpdt.value\\n\\n # update prior weight changes at start, so any DWt values remain visible at end\\n # you might want to do this less frequently to achieve a mini-batch update\\n # in which case, move it out to the TrainTrial method where the relevant\\n # counters are being dealt with.\\n if train:\\n ss.Net.WtFmDWt()\\n\\n ss.Net.AlphaCycInit(train)\\n ss.Time.AlphaCycStart()\\n for qtr in range(4):\\n for cyc in range(ss.Time.CycPerQtr):\\n ss.Net.Cycle(ss.Time)\\n ss.Time.CycleInc()\\n if ss.ViewOn:\\n if viewUpdt == leabra.Cycle:\\n if cyc != ss.Time.CycPerQtr-1: # will be updated by quarter\\n ss.UpdateView(train)\\n if viewUpdt == leabra.FastSpike:\\n if (cyc+1)%10 == 0:\\n ss.UpdateView(train)\\n ss.Net.QuarterFinal(ss.Time)\\n ss.Time.QuarterInc()\\n if ss.ViewOn:\\n if viewUpdt <= leabra.Quarter:\\n ss.UpdateView(train)\\n if viewUpdt == leabra.Phase:\\n if qtr >= 2:\\n ss.UpdateView(train)\\n\\n if train:\\n ss.Net.DWt()\\n if ss.ViewOn and viewUpdt == leabra.AlphaCycle:\\n ss.UpdateView(train)\",\n \"def add_to_zview(self, name, x, fail):\\r\\n\\r\\n return \\\"\\\"\\\"\\r\\n PyArrayObject * add_rval = (PyArrayObject*)PyNumber_InPlaceAdd(\\r\\n (PyObject*)zview, py_%(x)s);\\r\\n if (add_rval)\\r\\n {\\r\\n assert (PyArray_Check((PyObject*)add_rval));\\r\\n assert (PyArray_DATA(add_rval) == PyArray_DATA(zview));\\r\\n Py_DECREF(add_rval);\\r\\n }\\r\\n else\\r\\n {\\r\\n Py_DECREF(zview);\\r\\n %(fail)s;\\r\\n }\\\"\\\"\\\" % locals()\",\n \"def test_cz_gate_deterministic_waltz_basis_gates(self):\\n shots = 100\\n circuits = ref_2q_clifford.cz_gate_circuits_deterministic(final_measure=True)\\n targets = ref_2q_clifford.cz_gate_counts_deterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='u1,u2,u3,cx')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0)\",\n \"def CX(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)\",\n \"def _control_predefined(operation, num_ctrl_qubits):\\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\\n if num_ctrl_qubits == 1:\\n import qiskit.extensions.standard.cx\\n cgate = qiskit.extensions.standard.cx.CnotGate()\\n else:\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n elif operation.name == 'y':\\n import qiskit.extensions.standard.cy\\n cgate = qiskit.extensions.standard.cy.CyGate()\\n elif operation.name == 'z':\\n import qiskit.extensions.standard.cz\\n cgate = qiskit.extensions.standard.cz.CzGate()\\n elif operation.name == 'h':\\n import qiskit.extensions.standard.ch\\n cgate = qiskit.extensions.standard.ch.CHGate()\\n elif operation.name in {'rx', 'ry', 'rz'}:\\n if operation.name == 'rx':\\n import qiskit.extensions.standard.crx\\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\\n elif operation.name == 'ry':\\n import qiskit.extensions.standard.cry\\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\\n else: # operation.name == 'rz'\\n import qiskit.extensions.standard.crz\\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\\n if num_ctrl_qubits == 1:\\n return cgate\\n else:\\n # only predefined for one control qubit\\n return cgate.control(num_ctrl_qubits - 1)\\n elif operation.name == 'swap':\\n import qiskit.extensions.standard.cswap\\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\\n elif operation.name == 'u1':\\n import qiskit.extensions.standard.cu1\\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\\n elif operation.name == 'u3':\\n import qiskit.extensions.standard.cu3\\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\\n elif operation.name == 'cx':\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n else:\\n raise QiskitError('No standard controlled gate for \\\"{}\\\"'.format(\\n operation.name))\\n return cgate\",\n \"def setZ(self, z):\\n self.position.setZ(z)\",\n \"def compute_Az(self, r, z, qOc):\\n\\n kr_cross_r = einsum('r, p -> rp', self.kr, r)\\n kz_cross_z = einsum('z, p -> zp', self.kz, z)\\n delta_r = np.ones(np.size(r)) * self.ptcl_width_r\\n delta_u = einsum('r, p -> rp', self.kr, delta_r)\\n convolved_j0 = self.convolved_j0(kr_cross_r, delta_u)\\n convolved_cos = einsum('zp, z -> zp', cos(kz_cross_z), self.shape_function_z)\\n\\n modeQz = self.omegaOtwokr * (self.dc_coords[:,:,1] + self.omega_coords[:,:,1])\\n\\n self.tanhz = -np.tanh(((z - self.z_mean) ** 2 - self.z_mean ** 2) * self.tanh_width ** 2)\\n # We dress the charge instead of the fields proper\\n dressed_charge = self.tanhz*qOc\\n\\n Az = einsum('zr, rp, zp -> p', modeQz, convolved_j0, convolved_cos)*dressed_charge\\n\\n return Az\",\n \"def setZ(self, *args):\\n return _libsbml.Point_setZ(self, *args)\",\n \"def estimateCs(y, inp):\\n\\treturn 1 -(math.tanh(getK1(inp) - (y/getY90(inp)) / (2 * getD0(inp)) + (y/getY90(inp) - 1/3.0)**3 / (3 * getD0(inp))))**2\",\n \"def test_special_ZYZ(self, angexp):\\n a, b, c, d = angexp[0]\\n exp = {(\\\"rz\\\", \\\"ry\\\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\\n tgt = np.exp(1j * d) * RZGate(b).to_matrix() @ RYGate(a).to_matrix() @ RZGate(c).to_matrix()\\n self.check_oneq_special_cases(tgt, \\\"ZYZ\\\", exp)\",\n \"def BCS(self, value):\\n if self.reg.C:\\n self.reg.PC += value\",\n \"def cy(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CY(), target=[control, target])\",\n \"def pz_fn(self, z):\\n pass\",\n \"def TAY(self, *_):\\n self.reg.Y = self.reg.A\\n self.reg.N = self.reg.Y << 7\\n self.reg.Z = self.reg.Y == 0\",\n \"def __init__(self,x_c,z_c,cyl_rad):\\n self.x_c = x_c\\n self.z_c = z_c\\n self.cyl_rad = cyl_rad\",\n \"def __init__(self,x_c,z_c,cyl_rad):\\n self.x_c = x_c\\n self.z_c = z_c\\n self.cyl_rad = cyl_rad\",\n \"def __init__(self,x_c,z_c,cyl_rad):\\n self.x_c = x_c\\n self.z_c = z_c\\n self.cyl_rad = cyl_rad\",\n \"def __init__(self,x_c,z_c,cyl_rad):\\n self.x_c = x_c\\n self.z_c = z_c\\n self.cyl_rad = cyl_rad\",\n \"def __init__(self,x_c,z_c,cyl_rad):\\n self.x_c = x_c\\n self.z_c = z_c\\n self.cyl_rad = cyl_rad\",\n \"def pre_defined_circuit(env: 'QEnv', q: List['QRegStorage'], gate_list: List[operatorType]) -> 'QEnv':\\n if gate_list:\\n for gate in gate_list:\\n if gate.bits == 1:\\n gate(q[0])\\n elif gate.bits == 2:\\n gate(q[0], q[1])\\n return env\",\n \"def Es_case_C(z, x, gamma, alp, lamb):\\n\\n if z == 0 and x == 0 and alp == 0:\\n return 0\\n \\n beta2 = 1-1/gamma**2\\n beta = sqrt(beta2)\\n \\n sin2a = sin(2*alp)\\n cos2a = cos(2*alp) \\n eta = eta_case_C(z, x, beta2, alp, lamb)\\n \\n kap = (2*(alp - z) + eta + lamb)/beta # kappa for case C\\n #kap = sqrt( lamb**2 + eta**2 + x**2 + 4*(1+x)*sin(alp)**2 + 2*(lamb + eta*(1+x))*sin2a + 2*lamb*eta*cos2a) \\n \\n N = lamb + sin2a + (eta - beta*kap)*cos2a\\n D = kap - beta*(eta + lamb*cos2a + (1+x)*sin2a)\\n \\n return N/D**3\",\n \"def test_cz_gate_nondeterministic_minimal_basis_gates(self):\\n shots = 2000\\n circuits = ref_2q_clifford.cz_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_2q_clifford.cz_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def add_neurone(self, couche, nbr=1):\\n if self.control == 0:\\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\\n self.couche[couche] += nbr\\n else:\\n print(\\\"Le réseau est deja créé, vous en pouvez plus le modifier\\\")\",\n \"def add_computed_gas_concentrations(self):\\n # Extract the z-coordinate and T, S, P profile\\n zs = self.interp_ds.coords[self.ztsp[0]].values\\n Ts = self.interp_ds[self.ztsp[1]].values\\n Ss = self.interp_ds[self.ztsp[2]].values\\n Ps = self.interp_ds[self.ztsp[3]].values\\n \\n # Create an air object\\n air_names = ['nitrogen', 'oxygen', 'argon', 'carbon_dioxide']\\n yk = np.array([0.78084, 0.20946, 0.009340, 0.00036])\\n from tamoc import dbm\\n air = dbm.FluidMixture(air_names)\\n m = air.masses(yk)\\n \\n # Compute the concentrations adjusted for depth\\n Cs = np.zeros((len(zs), len(air_names)))\\n for i in range(len(zs)):\\n Cs[i,:] = air.solubility(m, Ts[i], 101325., Ss[i])[0,:] * \\\\\\n seawater.density(Ts[i], Ss[i], Ps[i]) / \\\\\\n seawater.density(Ts[i], Ss[i], 101325.)\\n \\n # Make sure none of these gases are already in the measured profile\\n for name in air_names:\\n if name in self.interp_ds:\\n air_names[air_names.index(name)] = 'computed_' + name\\n \\n # Add these data to the Profile object\\n data = np.hstack((np.atleast_2d(zs).transpose(), Cs))\\n names = [self.ztsp[0]] + air_names \\n units = [self.ztsp_units[0]] + 4*['kg/m^3']\\n self.append(data, names, units)\\n \\n # Rebuild the interpolator\\n self._build_interpolator()\",\n \"def test_iadd(self):\\n qc_cal = QuantumCircuit(2)\\n qc_cal.rzx(0.5, 0, 1)\\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\\n\\n qc = QuantumCircuit(2)\\n qc &= qc_cal\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\",\n \"def createCornerPin():\\n i = b.createNode('CornerPinMI')\\n i['tile_color'].setValue(int('%02x%02x%02x%02x' % (232.05, 145.095, 0, 255), 16))\\n if cc:\\n i = gU(i)\\n return i\",\n \"def removeZeroModeFromComa(self):\\n#\\t\\tprint \\\"BUGGGGGGGGGGGGGGGGGGGGGGG#EFAHR\\\"\\n#\\t\\treturn\\n#\\t\\tprint 'Remove zm'\\n\\t\\tif self.zeroModesRemovedFromComa:\\n\\t\\t\\tprint \\\"DO NOT REMOVE ZER MODE A SECOND TIME\\\"\\n\\t\\t\\treturn\\n\\n\\t\\tself.zeroModesRemovedFromComa = True\\n\\t\\tif len(self.zeroModes) == 0:\\n\\t\\t\\treturn\\n\\t\\tdim = len(self.coma)\\n\\t\\ttransformationMatrix = np.identity(dim)\\n#\\t#\\tCMwrite(\\\"removeZeroModeFromComa\\\")\\n\\t\\tfor z in range(self.nZero):\\n\\t\\t\\tfor i in range(dim/2):\\n\\t\\t\\t\\tfor j in range(dim/2):\\n\\t\\t\\t\\t\\ttransformationMatrix[2*i ,2*j ] -= self.zeroModes[z][i] * self.zeroModes[z][j]\\n\\t\\t\\t\\t\\ttransformationMatrix[2*i+1,2*j+1] -= self.zeroModes[z][i] * self.zeroModes[z][j]\\n\\t\\tself.coma = np.dot(transformationMatrix, np.dot(self.coma, transformationMatrix)) # no transpose needed, since transformationMatrix is symmetric\\n\\t\\tself.makeComaInv()\\n\\t\\tself.specialCOMAs = {}\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def bcc(self, arg):\\n\\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def test_special_ZXZ(self, angexp):\\n a, b, c, d = angexp[0]\\n exp = {(\\\"rz\\\", \\\"rx\\\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\\n tgt = np.exp(1j * d) * RZGate(b).to_matrix() @ RXGate(a).to_matrix() @ RZGate(c).to_matrix()\\n self.check_oneq_special_cases(tgt, \\\"ZXZ\\\", exp)\",\n \"def __init__(self, input0, input1, output) :\\n Gate.__init__(self, [input0,input1], output)\",\n \"def add_connector(self):\\n \\n no = len(self.connectors)\\n state = {}\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % no\\n \\n if len(self.connectors)>0:\\n state = self.connectors[-1].get_state()\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % (no)\\n else:\\n if self.mount == self.MOUNT_THT:\\n state[\\\"p_shape\\\"] = Con.SHAPE_HOLE\\n elif self.mount == self.MOUNT_SMD:\\n state[\\\"p_shape\\\"] = Con.SHAPE_PAD\\n \\n c = Con(no)\\n c.set_state(state) \\n \\n self.sch_layers[\\\"pins\\\"].add(c.s_svg)\\n self.pcb_layers[\\\"copper1\\\"].add(c.p_svg)\\n self.connectors.append(c)\",\n \"def zenazi(scx_l, scx_b, scy_l, scy_b, scz_l, scz_b, src_l, src_b):\\n # Zenith is the distance from the optical axis (here z)\\n costheta = GreatCircle(scz_l,scz_b,src_l,src_b) \\n # Azimuth is the combination of the remaining two\\n cosx = GreatCircle(scx_l,scx_b,src_l,src_b)\\n cosy = GreatCircle(scy_l,scy_b,src_l,src_b)\\n \\n # check exceptions\\n # maybe not for vectorisation\\n \\\"\\\"\\\"\\n if costheta.size == 1:\\n if (costheta > 1.0):\\n costheta = 1.0\\n if (costheta < -1.0):\\n costheta = -1.0\\n else:\\n costheta[costheta > 1.0] = 1.0\\n costheta[costheta < -1.0] = -1.0\\n \\\"\\\"\\\"\\n # theta = zenith\\n theta = np.rad2deg(np.arccos(costheta))\\n # phi = azimuth\\n phi = np.rad2deg(np.arctan2(cosy,cosx)) # TS January 14: you sure about that? changed y and x\\n \\n # make azimuth going from 0 to 360 deg\\n if phi.size == 1:\\n if (phi < 0):\\n phi += 360\\n else:\\n phi[phi < 0] += 360\\n \\n return theta,phi\",\n \"def __init__(self, **kwargs):\\n\\t\\tself.__c_version = c_singlezone(**kwargs)\",\n \"def __call__(self,Zin):\\r\\n self.Z = np.zeros((self.Nc,))\\r\\n for ii in range(0,self.Nc):\\r\\n self.Z[ii] = np.dot(self.W[:,ii],Zin[self.ind[ii,:]])\\r\\n \\r\\n return self.Z\",\n \"def compute_z_curr(Z_opt, z_prev1, z_diff, alpha):\\r\\n z_curr = alpha * Z_opt + (1 - alpha) * (z_prev1 + z_diff)\\r\\n return z_curr\",\n \"def add_control(operation, num_ctrl_qubits, label):\\n if isinstance(operation, UnitaryGate):\\n # attempt decomposition\\n operation._define()\\n if _control_definition_known(operation, num_ctrl_qubits):\\n return _control_predefined(operation, num_ctrl_qubits)\\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def __init__(self, input, output) :\\n Gate.__init__(self, [input], output)\",\n \"def plot_eccentricity(self, z=0):\\n p = figure(\\n title=\\\"Cut in plane Z=\\\" + str(z),\\n x_axis_label=\\\"X axis\\\",\\n y_axis_label=\\\"Y axis\\\",\\n )\\n for j in range(0, self.ntheta):\\n p.circle(self.xre[z][j], self.yre[z][j], color=\\\"red\\\")\\n p.circle(self.xri[z][j], self.yri[z][j], color=\\\"blue\\\")\\n p.circle(0, 0, color=\\\"blue\\\")\\n p.circle(self.xi, self.yi, color=\\\"red\\\")\\n p.circle(0, 0, color=\\\"black\\\")\\n return p\",\n \"def z(self, value: Number):\\n self._translation[2, 0] = value\",\n \"def f_c(self, z, m):\\n\\t return (1. - self.f_o(z))*m/(self.ALPHA_1*self.mmax + m)\",\n \"def zz(x):\\r\\n return Feature(x, \\\"ZZ\\\")\",\n \"def test_add(self):\\n qc_cal = QuantumCircuit(2)\\n qc_cal.rzx(0.5, 0, 1)\\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\\n\\n qc = QuantumCircuit(2) & qc_cal\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\\n\\n qc = qc_cal & QuantumCircuit(2)\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\",\n \"def z_defocus(w0, c, d, A, B):\\n return lambda z: (\\n w0 * np.sqrt(1 + \\\\\\n ((z - c)/d)**2 + A*((z - c)/d)**3 + B*((z - c)/d)**4)\\n )\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6692847","0.6502453","0.593888","0.57899","0.57899","0.569876","0.56540734","0.56317514","0.55797076","0.55053544","0.54111063","0.53825223","0.53213876","0.5233289","0.52176267","0.52100134","0.5150845","0.51389116","0.51233536","0.50904244","0.505567","0.5043398","0.5030342","0.50059086","0.50047034","0.49708113","0.49624693","0.49603865","0.4941295","0.4894207","0.4884226","0.48529118","0.48426485","0.48420233","0.48390162","0.4827606","0.48194018","0.4815936","0.48085144","0.48032075","0.47958907","0.47945866","0.47756153","0.47653994","0.47589996","0.4758727","0.4754583","0.47527355","0.47455382","0.47451577","0.47303852","0.47144467","0.4709391","0.4706832","0.47057256","0.4700792","0.46966347","0.46946615","0.46884647","0.46815315","0.46744362","0.4670537","0.46561965","0.46506247","0.464937","0.46485308","0.4645627","0.46419933","0.46337855","0.46311438","0.46311438","0.46311438","0.46311438","0.46311438","0.46290135","0.4626027","0.46194246","0.4606172","0.46025887","0.46017095","0.4592815","0.45925775","0.45915678","0.45893273","0.45801342","0.45726722","0.45725194","0.4569159","0.45646256","0.45572385","0.45569143","0.4549294","0.4548017","0.45477036","0.4546135","0.4541755","0.45364997","0.45335132","0.45292872","0.4517012"],"string":"[\n \"0.6692847\",\n \"0.6502453\",\n \"0.593888\",\n \"0.57899\",\n \"0.57899\",\n \"0.569876\",\n \"0.56540734\",\n \"0.56317514\",\n \"0.55797076\",\n \"0.55053544\",\n \"0.54111063\",\n \"0.53825223\",\n \"0.53213876\",\n \"0.5233289\",\n \"0.52176267\",\n \"0.52100134\",\n \"0.5150845\",\n \"0.51389116\",\n \"0.51233536\",\n \"0.50904244\",\n \"0.505567\",\n \"0.5043398\",\n \"0.5030342\",\n \"0.50059086\",\n \"0.50047034\",\n \"0.49708113\",\n \"0.49624693\",\n \"0.49603865\",\n \"0.4941295\",\n \"0.4894207\",\n \"0.4884226\",\n \"0.48529118\",\n \"0.48426485\",\n \"0.48420233\",\n \"0.48390162\",\n \"0.4827606\",\n \"0.48194018\",\n \"0.4815936\",\n \"0.48085144\",\n \"0.48032075\",\n \"0.47958907\",\n \"0.47945866\",\n \"0.47756153\",\n \"0.47653994\",\n \"0.47589996\",\n \"0.4758727\",\n \"0.4754583\",\n \"0.47527355\",\n \"0.47455382\",\n \"0.47451577\",\n \"0.47303852\",\n \"0.47144467\",\n \"0.4709391\",\n \"0.4706832\",\n \"0.47057256\",\n \"0.4700792\",\n \"0.46966347\",\n \"0.46946615\",\n \"0.46884647\",\n \"0.46815315\",\n \"0.46744362\",\n \"0.4670537\",\n \"0.46561965\",\n \"0.46506247\",\n \"0.464937\",\n \"0.46485308\",\n \"0.4645627\",\n \"0.46419933\",\n \"0.46337855\",\n \"0.46311438\",\n \"0.46311438\",\n \"0.46311438\",\n \"0.46311438\",\n \"0.46311438\",\n \"0.46290135\",\n \"0.4626027\",\n \"0.46194246\",\n \"0.4606172\",\n \"0.46025887\",\n \"0.46017095\",\n \"0.4592815\",\n \"0.45925775\",\n \"0.45915678\",\n \"0.45893273\",\n \"0.45801342\",\n \"0.45726722\",\n \"0.45725194\",\n \"0.4569159\",\n \"0.45646256\",\n \"0.45572385\",\n \"0.45569143\",\n \"0.4549294\",\n \"0.4548017\",\n \"0.45477036\",\n \"0.4546135\",\n \"0.4541755\",\n \"0.45364997\",\n \"0.45335132\",\n \"0.45292872\",\n \"0.4517012\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6522352"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81745,"cells":{"query":{"kind":"string","value":"add CXR gate (controlled root X gate)."},"document":{"kind":"string","value":"def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def CX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)","def cX(cb):\n allNodes = b.allNodes(group=cb)\n for n in allNodes:\n allNodes = allNodes + cX(n)\n\n return allNodes","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def _compute_carry_and_output(self, x, h_tm1, c_tm1):\n x_i, x_f, x_c, x_o = x\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\n i = self.recurrent_activation(\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\n f = self.recurrent_activation(x_f + K.dot(\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\n o = self.recurrent_activation(\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\n return c, o","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def _gcl(x, r, D, Ia, Ct):\n\n Area = np.pi * D ** 2.0 / 4.0\n m = 1.0 / (np.sqrt(1.0 - Ct))\n k = np.sqrt((m + 1.0) / 2.0)\n\n a1 = 0.435449861 # empirically determined\n a2 = 0.797853685\n a3 = -0.124807893\n a4 = 0.136821858\n b1 = 15.6298\n b2 = 1.0\n R96 = a1 * (np.exp(a2 * Ct * Ct + a3 * Ct + a4)) * (b1 * Ia + b2) * D\n\n x0 = (9.6 * D) / ((2.0 * R96 / (k * D)) ** 3.0 - 1.0)\n term1 = (k * D / 2.0) ** (5.0 / 2.0)\n term2 = (105.0 / (2.0 * np.pi)) ** (-0.5)\n term3 = (Ct * Area * x0) ** (-5.0 / 6.0)\n c1 = term1 * term2 * term3\n # c45=3*(c1) ** 2\n\n term10 = 0.1111 # * WindSpeed # U/9.0\n term20 = (Ct * Area * (x + x0) ** (-2.0)) ** (1.0 / 3.0)\n term310 = (r ** (3.0 / 2.0))\n term320 = (3.0 * c1 * c1 * Ct * Area * (x + x0)) ** (-0.5)\n term30 = term310 * term320\n term40 = ((35.0 / (2.0 * np.pi)) ** (3.0 / 10.0)) * \\\n (3.0 * c1 * c1) ** (-1.0 / 5.0)\n DU1 = -term10 * term20 * (term30 - term40) ** 2.0\n\n DU = DU1 # + w2 * DU2\n Rw = ((105 * c1 ** 2.0 / (2 * np.pi)) ** (1. / 5.)) * \\\n (Ct * Area * (x + x0)) ** (1. / 3.)\n return DU, Rw","def ccx(self, q0, q1, q2, ctrl=None):\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\n return self","def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def _append_cx(self, i, j):\n\n if not 0 <= i < self.num_qubits or not 0 <= j < self.num_qubits:\n raise QiskitError(\"CX qubits are out of bounds.\")\n self.linear[j] = (self.linear[i] + self.linear[j]) % 2\n self.shift[j] = (self.shift[i] + self.shift[j]) % 2","def C(self,X):\n return(\n 0\n )","def add(self, y):\n return circuit.add(self, y)","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def addX(self,name):\n return self._addVar(name,self._xNames)","def X(self, qubit_expr):\n self.apply_gate_operation('X', qubit_expr)","def add_corridor_constraint(self,seg,r,weight=1.0):\n\n constraint_type = \"cylinder\"\n params = dict()\n params['x1'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg],\n self.qr_polytraj.waypoints['y'][0,seg],\n self.qr_polytraj.waypoints['z'][0,seg]])\n params['x2'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg+1],\n self.qr_polytraj.waypoints['y'][0,seg+1],\n self.qr_polytraj.waypoints['z'][0,seg+1]])\n params['der'] = 0\n params['l'] = r # Give the same radius buffer on the end caps\n params['r'] = r\n params['weight'] = weight\n params['keep_out'] = False\n params['active_seg'] = seg\n\n\n self.qr_polytraj.add_constraint(constraint_type,params,dynamic_weighting=False,sum_func=False)","def cx(x):\n return cw(x - global_min_x)","def x(self, new_x):\n if new_x is None:\n logging.warning(\"Cochain features were set to None. \")\n else:\n assert self.num_cells == len(new_x)\n self.__x = new_x","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def crf_obj(x, train_data, c):\n print(\"Evaluating grad\")\n global iteration\n iteration +=1\n print(iteration)\n # x is a vector as required by the solver.\n logCrf = log_crf_wrapper(x,train_data, 128, 26, from_file=False)\n model = CRFModel(128, 26)\n model.load_X(x,from_file=False)\n W = model._W # column format\n T = model._T # column format\n # Compute the objective value of CRF\n f = (-c *logCrf) + (0.5 * np.sum(W*W)) + (0.5 * np.sum(T*T)) # objective log-likelihood + regularizer\n reg = np.concatenate([W.T.reshape(-1), T.T.reshape(-1)])\n g = grad_crf_wrapper(x, train_data, 128, 26, from_file=False)\n g = -c * g + reg\n return [f, g]","def XX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.XX, qubit_expr)","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def double_add(self, x):\n self.add(x*2)","def _acc_grads(self, x, label):\n ##\n # Forward propagation\n z1 = self.params.W.dot(x) + self.params.b1\n h = tanh(z1)\n z2 = np.dot(self.params.U, h) + self.params.b2\n y_hat = softmax(z2)\n \n y = make_onehot(label, self.outputsize)\n d2 = y_hat - y\n self.grads.b2 += d2\n self.grads.U += np.outer(d2, h) + self.lreg * self.params.U\n d1 = np.dot(self.params.U.T, d2) * tanhd(z1) \n \n self.grads.W += np.outer(d1, x) + self.lreg * self.params.W\n self.grads.b1 += d1","def RXX(self, theta:Union[int, float], qubit_expr): \n self.apply_gate_operation(RYY(theta), qubit_expr)","def add(self, x):\n if type(x) is int:\n self.real += x\n else:\n self.real = self.real + x.real\n self.imag = self.imag + x.imag","def add(self, x):\n self.sum += (1 / self.counter) * (x - self.sum)\n self.counter += 1","def xr(self, q0, ctrl=None):\n self.__add_quantum_gate(kind=ROOT_PAULI_X, qid=[q0], ctrl=ctrl)\n return self","def add_rxn(self, reaction: db.Reaction):\n # Add two rxn nodes\n rxn_nodes = []\n reaction_id = reaction.id().string()\n\n for i in range(0, 2):\n # Add rxn node between lhs and rhs compound\n rxn_node = ';'.join([reaction_id, str(i)])\n rxn_node += ';'\n self.graph.add_node(rxn_node, color='rxn_node')\n rxn_nodes.append(rxn_node)\n # Convert to strings\n reactants = reaction.get_reactants(db.Side.BOTH)\n reactant_types = reaction.get_reactant_types(db.Side.BOTH)\n weights = self._get_weight(reaction)\n # Add lhs aggregates and connect\n for lhs_cmp, lhs_type in zip([i.string() for i in reactants[0]],\n [i.name for i in reactant_types[0]]):\n if lhs_cmp not in self.graph:\n self.graph.add_node(lhs_cmp, type=lhs_type)\n required_cmps_lhs = [s.string() for s in reactants[0]]\n required_cmps_lhs.remove(lhs_cmp)\n self.graph.add_edge(lhs_cmp, rxn_nodes[0], weight=weights[0], required_compounds=required_cmps_lhs,\n required_compound_costs=None)\n self.graph.add_edge(rxn_nodes[1], lhs_cmp, weight=0.0, required_compounds=None)\n # Add rhs aggregates and connect\n for rhs_cmp, rhs_type in zip([i.string() for i in reactants[1]],\n [i.name for i in reactant_types[1]]):\n if rhs_cmp not in self.graph:\n self.graph.add_node(rhs_cmp, type=rhs_type)\n required_cmps_rhs = [s.string() for s in reactants[1]]\n required_cmps_rhs.remove(rhs_cmp)\n self.graph.add_edge(rhs_cmp, rxn_nodes[1], weight=weights[1], required_compounds=required_cmps_rhs,\n required_compound_costs=None)\n self.graph.add_edge(rxn_nodes[0], rhs_cmp, weight=0.0, required_compounds=None)\n\n # # # Loop over reaction nodes to add required compounds info to downwards edges; might be unnecessary\n node_index = 1\n for node in rxn_nodes:\n for key in self.graph[node].keys():\n self.graph.edges[node, key]['required_compounds'] = \\\n self.graph.edges[key, rxn_nodes[node_index]]['required_compounds']\n node_index -= 1","def _cmplx_add_ ( s , o ) :\n return o + complex ( s )","def test_radd():\n # Test for reverse addition with scalar Rnode object and float value\n x = Rnode(0.11)\n z = 0.5 + x\n z.grad_value = 1.0\n\n try:\n assert z.value == x.value + 0.5\n except AssertionError as e:\n print(e)","def RXX(self, theta:Union[int, float], qubit_expr): \n self.apply_gate_operation(RXX(theta), qubit_expr)","def __init__(self):\n super().__init__(\"ccx\", 3, [])","def gate2zx(box):\n if isinstance(box, (Bra, Ket)):\n dom, cod = (1, 0) if isinstance(box, Bra) else (0, 1)\n return Id(0).tensor(*[\n X(dom, cod, phase=.5 * bit) for bit in box.bitstring])\n if isinstance(box, (Rz, Rx)):\n return (Z if isinstance(box, Rz) else X)(1, 1, box.phase)\n if isinstance(box, CRz):\n return Z(1, 2) @ Z(1, 2, box.phase)\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\n if isinstance(box, CRx):\n return X(1, 2) @ X(1, 2, box.phase)\\\n >> Id(1) @ (Z(2, 1) >> X(1, 0, -box.phase)) @ Id(1)\n if isinstance(box, quantum.CU1):\n return Z(1, 2, box.phase) @ Z(1, 2, box.phase)\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\n standard_gates = {\n quantum.H: H,\n quantum.Z: Z(1, 1, .5),\n quantum.X: X(1, 1, .5),\n quantum.Y: Y(1, 1, .5),\n CZ: Z(1, 2) @ Id(1) >> Id(1) @ Had() @ Id(1) >> Id(1) @ Z(2, 1),\n CX: Z(1, 2) @ Id(1) >> Id(1) @ X(2, 1)}\n return standard_gates[box]","def plot_cnxs(self,x_shift,y_shift):\n\n if not self.cnxs: return # Bounce if option not selected\n\n self.node_cnx_crds[:,:2] += x_shift*self.pbc[0]\n self.node_cnx_crds[:,2:] += y_shift*self.pbc[1]\n for cnx_crd in self.node_cnx_crds:\n self.ax.plot(cnx_crd[:2],cnx_crd[2:],c=self.lc,lw=self.lw)\n self.node_cnx_crds[:,:2] -= x_shift*self.pbc[0]\n self.node_cnx_crds[:,2:] -= y_shift*self.pbc[1]","def DEX(self, *_):\n self._dec_or_inc_register('X', increment=False)","def ADD_I_Vx(self, x):\n\t\tself.I += self.V[x]","def _gyration(self, x, y, v, c):\n xy = self._mobius_add(x, y, c)\n yv = self._mobius_add(y, v, c)\n xyv = self._mobius_add(x, yv, c)\n return self._mobius_add(-xy, xyv, c)","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def xscalary_plus_z(scalar, x, y, activation=None):\n R = tf.add(tf.scalar_mul(scalar,x), y)\n if activation:\n return activation(R)\n else: \n return R","def convert_to_circuit(x):\n y = np.arcsin(x)\n z = np.arccos(x**2)\n qubits = cirq.GridQubit.rect(5, 1)\n circuit = cirq.Circuit()\n for i in range(5):\n circuit.append(cirq.ry(y).on(qubits[i]))\n circuit.append(cirq.rz(z).on(qubits[i]))\n return circuit","def add_component(self, xi):\n assert xi.berkovich_line() is self.berkovich_line(), \"xi must be a point\\\n on the Berkovich line underlying this model\"\n X = self\n if not X.is_component(xi):\n ComponentOfModel(X, xi)\n X._changed = True\n\n \"\"\"\n T = X.tree()\n # we have to first check whether xi is already a component !\n # the first condition should be unnecessary; this is a bug in\n # mclf.berkovich_trees: T.find_point for an empty tree gives an error\n if not X.is_component(xi):\n T, vertex = T.add_point(xi)\n self._tree = T\n component = ComponentOfModel(self, vertex)\n if component.is_horizontal():\n self._horizontal_components.append(component)\n else:\n self._vertical_components.append(component)\n # we report that the model has changed\n self._changed = True\n \"\"\"","def _r_x(angle: tf.Tensor) -> tf.Tensor:\n cos = tf.cos(tf.multiply(angle, tf.constant(0.5, dtype=tf.float64)))\n sin = tf.sin(tf.multiply(angle, tf.constant(0.5, dtype=tf.float64)))\n sin_complex = tf.complex(tf.constant(0, dtype=tf.float64), sin)\n cos_complex = tf.complex(cos, tf.constant(0, dtype=tf.float64))\n rx = tf.stack([[cos_complex, -sin_complex], [-sin_complex, cos_complex]])\n\n return rx","def INX(self, *_):\n self._dec_or_inc_register('X', increment=True)","def addx(self, addr):\n\n val = self.mem_if.read(addr, index=self.reg.idx)\n result = self.alu.add(self.reg.accum, val)\n self.reg.accum = result","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def test_add(self):\n qc_cal = QuantumCircuit(2)\n qc_cal.rzx(0.5, 0, 1)\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\n\n qc = QuantumCircuit(2) & qc_cal\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\n\n qc = qc_cal & QuantumCircuit(2)\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def test_iadd(self):\n qc_cal = QuantumCircuit(2)\n qc_cal.rzx(0.5, 0, 1)\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\n\n qc = QuantumCircuit(2)\n qc &= qc_cal\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)","def add_x(self, x, add):\n return (x + add) % self.x_len","def _control_predefined(operation, num_ctrl_qubits):\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\n if num_ctrl_qubits == 1:\n import qiskit.extensions.standard.cx\n cgate = qiskit.extensions.standard.cx.CnotGate()\n else:\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n elif operation.name == 'y':\n import qiskit.extensions.standard.cy\n cgate = qiskit.extensions.standard.cy.CyGate()\n elif operation.name == 'z':\n import qiskit.extensions.standard.cz\n cgate = qiskit.extensions.standard.cz.CzGate()\n elif operation.name == 'h':\n import qiskit.extensions.standard.ch\n cgate = qiskit.extensions.standard.ch.CHGate()\n elif operation.name in {'rx', 'ry', 'rz'}:\n if operation.name == 'rx':\n import qiskit.extensions.standard.crx\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\n elif operation.name == 'ry':\n import qiskit.extensions.standard.cry\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\n else: # operation.name == 'rz'\n import qiskit.extensions.standard.crz\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\n if num_ctrl_qubits == 1:\n return cgate\n else:\n # only predefined for one control qubit\n return cgate.control(num_ctrl_qubits - 1)\n elif operation.name == 'swap':\n import qiskit.extensions.standard.cswap\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\n elif operation.name == 'u1':\n import qiskit.extensions.standard.cu1\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\n elif operation.name == 'u3':\n import qiskit.extensions.standard.cu3\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\n elif operation.name == 'cx':\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n else:\n raise QiskitError('No standard controlled gate for \"{}\"'.format(\n operation.name))\n return cgate","def test_coreg_shift(self):\r\n with gw.open(l8_224077_20200518_B2) as target, gw.open(\r\n l8_224077_20200518_B4\r\n ) as reference:\r\n with tempfile.TemporaryDirectory() as tmp:\r\n # Shift by 1 pixel in each direction\r\n target_shifted = shift(target, x=1, y=1)\r\n tmp_file = Path(tmp) / '_tmp_shift.tif'\r\n target_shifted.gw.save(tmp_file, overwrite=True)\r\n with gw.open(tmp_file) as target_shifted:\r\n # Co-register the shifted data\r\n shifted = gw.coregister(\r\n target=target_shifted,\r\n reference=reference,\r\n ws=(256, 256),\r\n r_b4match=1,\r\n s_b4match=1,\r\n max_shift=5,\r\n resamp_alg_deshift='nearest',\r\n resamp_alg_calc='cubic',\r\n out_gsd=[target_shifted.gw.celly, reference.gw.celly],\r\n q=True,\r\n nodata=(0, 0),\r\n CPUs=1,\r\n )\r\n self.assertFalse(\r\n np.allclose(\r\n target.values[:, :-1, :-1],\r\n target_shifted.values[:, :-1, :-1],\r\n )\r\n )\r\n # Check if the corrected data match the original (unshifted) target\r\n self.assertTrue(\r\n np.allclose(\r\n target.values[:, :-1, :-1],\r\n shifted.values[:, :-1, :-1],\r\n )\r\n )","def CPX(self, value):\n self._compare(value, 'X')","def closure_plus(self):\n cdef StdVectorFst result = self.copy()\n result.set_closure(plus=True)\n return result","def TAX(self, *_):\n self.reg.X = self.reg.A\n self.reg.N = self.reg.X << 7\n self.reg.Z = self.reg.X == 0","def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\n if q_args is None and c_args is None:\n raise GateError(\"Gate needs at least one quantum argument or classical argument\")\n if isinstance(gate, CompositeGate):\n if mapping is None:\n raise GateError(\"Must provide arguments mapping for composite gate inside a composite gate.\")\n else:\n inv_mappimg = dict()\n for key, value in mapping.items():\n inv_mappimg[value] = key\n if gate is self:\n gates = gate.copy.gates\n else:\n gates = gate.gates\n for g in gates:\n new_q_args = None\n new_c_args = None\n if g[1] is not None:\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\n if g[2] is not None:\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\n self.add_gate(gate=g[0], q_args=new_q_args,\n c_args=new_c_args, params=g[3])\n else:\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\n raise GateError(\"Gate must be either a CompositeGate or a string from: \"\n \"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\")\n if q_args is not None:\n for q_arg in q_args:\n if q_arg not in self.q_args:\n self.add_q_arg(q_arg)\n if c_args is not None:\n for c_arg in c_args:\n if c_arg not in self.c_args:\n self.add_c_arg(c_arg)\n if params is not None:\n for param in params:\n if param not in self.params:\n self.add_param(param)\n self._gates.append((gate, q_args, c_args, params))","def addXValue(self,value):\n self.__XValue.append(value)\n self.updateValue()","def gelu_new(x):\n cdf = 0.5 * (1.0 + tf.tanh((np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))\n return x * cdf","def dcx(self, addr):\n\n self.reg.idx = self.reg.idx.inc(-1)\n self.reg.zerox_flag = self.reg.idx.eq_zero()","def cvBall(ctrlName, r=1):\r\n # create circles to get the shapes:\r\n ballX = cmds.circle(n=ctrlName+\"_x\", ch=False, o=True, nr=(1, 0, 0), d=3, s=8, radius=r)\r\n ballY = cmds.circle(n=ctrlName+\"_y\", ch=False, o=True, nr=(0, 1, 0), d=3, s=8, radius=r)\r\n ballZ = cmds.circle(n=ctrlName+\"_z\", ch=False, o=True, nr=(0, 0, 1), d=3, s=8, radius=r)\r\n # parent shapes to transform:\r\n ballCtrl = cmds.group(name=ctrlName, empty=True)\r\n cmds.parent( cmds.listRelatives(ballX, shapes=True, children=True)[0], ballCtrl, relative=True, shape=True)\r\n cmds.parent( cmds.listRelatives(ballY, shapes=True, children=True)[0], ballCtrl, relative=True, shape=True)\r\n cmds.parent( cmds.listRelatives(ballZ, shapes=True, children=True)[0], ballCtrl, relative=True, shape=True)\r\n # delete old x, y and z transforms:\r\n cmds.delete(ballX, ballY, ballZ)\r\n cmds.select(clear=True)\r\n return ballCtrl","def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])","def _process_cnot(self, node):\n id0 = self._process_bit_id(node.children[0])\n id1 = self._process_bit_id(node.children[1])\n if not(len(id0) == len(id1) or len(id0) == 1 or len(id1) == 1):\n raise UnrollerError(\"internal error: qreg size mismatch\",\n \"line=%s\" % node.line, \"file=%s\" % node.file)\n maxidx = max([len(id0), len(id1)])\n for idx in range(maxidx):\n if len(id0) > 1 and len(id1) > 1:\n self.backend.cx(id0[idx], id1[idx])\n elif len(id0) > 1:\n self.backend.cx(id0[idx], id1[0])\n else:\n self.backend.cx(id0[0], id1[idx])","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def x3(self):\n return self._x + self._x3","def addThreeNodesRig(self):\r\n cam = self.nativePointer()\r\n\r\n # create controls\r\n pos = mxs.star(radius1 = 6.5, radius2 = 5.5, points=16)\r\n trans = mxs.rectangle(length=10.2, width=4.5)\r\n rot = mxs.ngon(radius=2.0, nSides=3, corner_radius=0.5)\r\n\r\n # rename controls\r\n pos.name = str(cam.name) + 'position'\r\n trans.name = str(cam.name) + 'translation'\r\n rot.name = str(cam.name) + 'rotation'\r\n\r\n # rotate controls into place\r\n pos.rotation = mxs.eulerangles(90, 0 , 0)\r\n trans.rotation = mxs.eulerangles(90, 0 , 0)\r\n rot.rotation = mxs.eulerangles(0, 0, -90)\r\n\r\n # reset xforms\r\n mxs.resetxform(pos)\r\n mxs.resetxform(trans)\r\n mxs.resetxform(rot)\r\n\r\n # collapse xforms\r\n mxs.maxOps.CollapseNode(pos, True)\r\n mxs.maxOps.CollapseNode(trans, True)\r\n mxs.maxOps.CollapseNode(rot, True)\r\n\r\n rot.parent = trans\r\n trans.parent = pos\r\n\r\n pos.wirecolor = rot.wirecolor = trans.wirecolor = mxs.color(0, 230, 250)\r\n\r\n # Move the rig to align with the cam\r\n pivrot=cam.rotation\r\n pos.rotation*=pivrot;\r\n #pos.objectoffsetrot*=pivrot;\r\n #pos.objectoffsetpos*=pivrot;\r\n\r\n pos.position = cam.position\r\n #mxs.resetxform(pos)\r\n #pos.rotation = cam.rotation\r\n\r\n\r\n # parent the cam to to rig\r\n cam.parent = rot\r\n\r\n return True","def add(self,new_x):\n # TODO add a check here that the new points have the same dimension as the old set\n add_x = np.concatenate((self.all,new_x),axis=0)\n self.all = add_x","def cvChin(ctrlName, r=1):\r\n # create a simple circle curve:\r\n curve = cmds.curve(n=ctrlName, d=3, p=[(0, 0.8*r, -0.5*r), (0, 0.9*r, -0.7*r), (0, 0, -0.5*r), (0, -0.8*r, -0.7*r), (0, -0.8*r, 1.4*r), (0, -0.3*r, 1.3*r), (0, 0, 1.2*r), (0, 0, 0), (0, 0.8*r, -0.3*r), (0, 0.8*r, -0.5*r)] )\r\n # rename curveShape:\r\n renameShape([curve])\r\n return curve","def __iadd__(self, other):\n self.x += other.x\n self.y += other.y\n return self","def brepalgo_ConcatenateWireC0(*args):\n return _BRepAlgo.brepalgo_ConcatenateWireC0(*args)","def _cmplx_factory_ ( cmplxt , re , im ) :\n return cmplxt ( re , im )","def Rgb_add(c1,c2):\n r = c1.r + c2.r\n r = max(0, min(1, r))\n\n g = c1.g + c2.g\n g = max(0, min(1, g))\n\n b = c1.b + c2.b\n b = max(0, min(1, b))\n return Rgb(r,g,b)","def __iadd__(self, other):\n self.center += other.center\n self.radius += other.radius\n return self","def forward(self, x):\n res = self.residual(x)\n x = self.gcn(x)\n x = self.tcn(x) + res\n return self.relu(x)","def xewy_plus_z(x, y, z, activation=None):\n R = tf.add(tf.multiply(x, y), z)\n if activation:\n return activation(R)\n else: \n return R","def ConcatenateWireC0(*args):\n return _BRepAlgo.brepalgo_ConcatenateWireC0(*args)","def add_c_arg(self, c_arg):\n self._c_args.append(c_arg)\n self.add_decompostion(c_arg)","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def gate_lfcc(recurrent_net, sample_input):\n length = sample_input.shape[0]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[i, :])\n select = sigmoid(select)\n score = sigmoid(score)\n return np.sum(select * score) / np.sum(select)","def incr_operand(self):\n pass","def __add__(self, x):\n assert isinstance(x, AxisDistance), 'incorrect type of arg x: should be type AxisDistance, is type {}'.format(type(x))\n tile = self.tile + x.tile\n pixel = self.pixel + x.pixel\n subpixel = self.subpixel + x.subpixel\n return AxisDistance(t=tile, px=pixel, sx=subpixel)","def vec_add_scalar (x, c):\n return [x_i+c for x_i in x]","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def test_add():\n # Test for addition with scalar Rnode object and float value\n x = Rnode(0.11)\n z = x**2 + x\n z.grad_value = 1.0\n\n try:\n assert z.value == x.value **2 + x.value\n assert x.grad() == sum(weight * var.grad()\n for weight, var in x.children)\n except AssertionError as e:\n print(e)","def add(self, x):\n self.sum += x\n self.n += 1","def __add__(self, other):\n if type(other) == int or type(other) == float:\n x = (other * Ccy.currencies[self.unit])\n else:\n x = (other.value / Ccy.currencies[other.unit] * Ccy.currencies[self.unit])\n return Ccy(x + self.value, self.unit)","def evaluate_c(self, x, out=None, **kwargs):\n return np.zeros(0)","def test_add_to_vx(self, cpu):\n for x in range(0x0, 0xF):\n for v in range(0x0, 0xFF):\n for kk in range(0x0, 0xFF):\n cpu.V_register[x] = v\n cpu.opcode = 0x7000 | (x << 8) | kk\n cpu.add_to_vx()\n assert(cpu.V_register[x] == (v + kk) & 0xFF)","def setRLC(self, r, l, c):\n return","def construct(self, x):\n x = self.conv(x)\n h0 = self.up_conv1(x)\n l0 = self.up_conv2(h0)\n h1 = self.up_conv3(l0 - x)\n return h1 + h0","def addExpr( ):\n\n\ttok = tokens.peek( )\n\tif debug: print (\"addExpr: \", tok)\n\tleft = term( )\n\ttok = tokens.peek( )\n\twhile tok == \"+\" or tok == \"-\":\n\t\ttokens.next()\n\t\tright = term( )\n\t\tleft = BinaryExpr( tok, left, right )\n\t\ttok = tokens.peek( )\n\treturn left","def ADD_Vx_byte(self, x, byte):\n\t\tself.V[x] += byte\n\t\tself.V[x] &= 255","def leftshift(x, c):\n return x << c","def acumula_x1(self, x1, rodada):\n self.x1[rodada].append(x1)","def create_carry_condition(new_val, sub_op):\n if not sub_op:\n carry_cond = new_val > 0xFF\n else:\n carry_cond = new_val >= 0\n return carry_cond"],"string":"[\n \"def cxr_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def CX(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)\",\n \"def cX(cb):\\n allNodes = b.allNodes(group=cb)\\n for n in allNodes:\\n allNodes = allNodes + cX(n)\\n\\n return allNodes\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def _compute_carry_and_output(self, x, h_tm1, c_tm1):\\n x_i, x_f, x_c, x_o = x\\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\\n i = self.recurrent_activation(\\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\\n f = self.recurrent_activation(x_f + K.dot(\\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\\n o = self.recurrent_activation(\\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\\n return c, o\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def _gcl(x, r, D, Ia, Ct):\\n\\n Area = np.pi * D ** 2.0 / 4.0\\n m = 1.0 / (np.sqrt(1.0 - Ct))\\n k = np.sqrt((m + 1.0) / 2.0)\\n\\n a1 = 0.435449861 # empirically determined\\n a2 = 0.797853685\\n a3 = -0.124807893\\n a4 = 0.136821858\\n b1 = 15.6298\\n b2 = 1.0\\n R96 = a1 * (np.exp(a2 * Ct * Ct + a3 * Ct + a4)) * (b1 * Ia + b2) * D\\n\\n x0 = (9.6 * D) / ((2.0 * R96 / (k * D)) ** 3.0 - 1.0)\\n term1 = (k * D / 2.0) ** (5.0 / 2.0)\\n term2 = (105.0 / (2.0 * np.pi)) ** (-0.5)\\n term3 = (Ct * Area * x0) ** (-5.0 / 6.0)\\n c1 = term1 * term2 * term3\\n # c45=3*(c1) ** 2\\n\\n term10 = 0.1111 # * WindSpeed # U/9.0\\n term20 = (Ct * Area * (x + x0) ** (-2.0)) ** (1.0 / 3.0)\\n term310 = (r ** (3.0 / 2.0))\\n term320 = (3.0 * c1 * c1 * Ct * Area * (x + x0)) ** (-0.5)\\n term30 = term310 * term320\\n term40 = ((35.0 / (2.0 * np.pi)) ** (3.0 / 10.0)) * \\\\\\n (3.0 * c1 * c1) ** (-1.0 / 5.0)\\n DU1 = -term10 * term20 * (term30 - term40) ** 2.0\\n\\n DU = DU1 # + w2 * DU2\\n Rw = ((105 * c1 ** 2.0 / (2 * np.pi)) ** (1. / 5.)) * \\\\\\n (Ct * Area * (x + x0)) ** (1. / 3.)\\n return DU, Rw\",\n \"def ccx(self, q0, q1, q2, ctrl=None):\\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\\n return self\",\n \"def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def _append_cx(self, i, j):\\n\\n if not 0 <= i < self.num_qubits or not 0 <= j < self.num_qubits:\\n raise QiskitError(\\\"CX qubits are out of bounds.\\\")\\n self.linear[j] = (self.linear[i] + self.linear[j]) % 2\\n self.shift[j] = (self.shift[i] + self.shift[j]) % 2\",\n \"def C(self,X):\\n return(\\n 0\\n )\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def addX(self,name):\\n return self._addVar(name,self._xNames)\",\n \"def X(self, qubit_expr):\\n self.apply_gate_operation('X', qubit_expr)\",\n \"def add_corridor_constraint(self,seg,r,weight=1.0):\\n\\n constraint_type = \\\"cylinder\\\"\\n params = dict()\\n params['x1'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg],\\n self.qr_polytraj.waypoints['y'][0,seg],\\n self.qr_polytraj.waypoints['z'][0,seg]])\\n params['x2'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg+1],\\n self.qr_polytraj.waypoints['y'][0,seg+1],\\n self.qr_polytraj.waypoints['z'][0,seg+1]])\\n params['der'] = 0\\n params['l'] = r # Give the same radius buffer on the end caps\\n params['r'] = r\\n params['weight'] = weight\\n params['keep_out'] = False\\n params['active_seg'] = seg\\n\\n\\n self.qr_polytraj.add_constraint(constraint_type,params,dynamic_weighting=False,sum_func=False)\",\n \"def cx(x):\\n return cw(x - global_min_x)\",\n \"def x(self, new_x):\\n if new_x is None:\\n logging.warning(\\\"Cochain features were set to None. \\\")\\n else:\\n assert self.num_cells == len(new_x)\\n self.__x = new_x\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def crf_obj(x, train_data, c):\\n print(\\\"Evaluating grad\\\")\\n global iteration\\n iteration +=1\\n print(iteration)\\n # x is a vector as required by the solver.\\n logCrf = log_crf_wrapper(x,train_data, 128, 26, from_file=False)\\n model = CRFModel(128, 26)\\n model.load_X(x,from_file=False)\\n W = model._W # column format\\n T = model._T # column format\\n # Compute the objective value of CRF\\n f = (-c *logCrf) + (0.5 * np.sum(W*W)) + (0.5 * np.sum(T*T)) # objective log-likelihood + regularizer\\n reg = np.concatenate([W.T.reshape(-1), T.T.reshape(-1)])\\n g = grad_crf_wrapper(x, train_data, 128, 26, from_file=False)\\n g = -c * g + reg\\n return [f, g]\",\n \"def XX(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.XX, qubit_expr)\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def double_add(self, x):\\n self.add(x*2)\",\n \"def _acc_grads(self, x, label):\\n ##\\n # Forward propagation\\n z1 = self.params.W.dot(x) + self.params.b1\\n h = tanh(z1)\\n z2 = np.dot(self.params.U, h) + self.params.b2\\n y_hat = softmax(z2)\\n \\n y = make_onehot(label, self.outputsize)\\n d2 = y_hat - y\\n self.grads.b2 += d2\\n self.grads.U += np.outer(d2, h) + self.lreg * self.params.U\\n d1 = np.dot(self.params.U.T, d2) * tanhd(z1) \\n \\n self.grads.W += np.outer(d1, x) + self.lreg * self.params.W\\n self.grads.b1 += d1\",\n \"def RXX(self, theta:Union[int, float], qubit_expr): \\n self.apply_gate_operation(RYY(theta), qubit_expr)\",\n \"def add(self, x):\\n if type(x) is int:\\n self.real += x\\n else:\\n self.real = self.real + x.real\\n self.imag = self.imag + x.imag\",\n \"def add(self, x):\\n self.sum += (1 / self.counter) * (x - self.sum)\\n self.counter += 1\",\n \"def xr(self, q0, ctrl=None):\\n self.__add_quantum_gate(kind=ROOT_PAULI_X, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def add_rxn(self, reaction: db.Reaction):\\n # Add two rxn nodes\\n rxn_nodes = []\\n reaction_id = reaction.id().string()\\n\\n for i in range(0, 2):\\n # Add rxn node between lhs and rhs compound\\n rxn_node = ';'.join([reaction_id, str(i)])\\n rxn_node += ';'\\n self.graph.add_node(rxn_node, color='rxn_node')\\n rxn_nodes.append(rxn_node)\\n # Convert to strings\\n reactants = reaction.get_reactants(db.Side.BOTH)\\n reactant_types = reaction.get_reactant_types(db.Side.BOTH)\\n weights = self._get_weight(reaction)\\n # Add lhs aggregates and connect\\n for lhs_cmp, lhs_type in zip([i.string() for i in reactants[0]],\\n [i.name for i in reactant_types[0]]):\\n if lhs_cmp not in self.graph:\\n self.graph.add_node(lhs_cmp, type=lhs_type)\\n required_cmps_lhs = [s.string() for s in reactants[0]]\\n required_cmps_lhs.remove(lhs_cmp)\\n self.graph.add_edge(lhs_cmp, rxn_nodes[0], weight=weights[0], required_compounds=required_cmps_lhs,\\n required_compound_costs=None)\\n self.graph.add_edge(rxn_nodes[1], lhs_cmp, weight=0.0, required_compounds=None)\\n # Add rhs aggregates and connect\\n for rhs_cmp, rhs_type in zip([i.string() for i in reactants[1]],\\n [i.name for i in reactant_types[1]]):\\n if rhs_cmp not in self.graph:\\n self.graph.add_node(rhs_cmp, type=rhs_type)\\n required_cmps_rhs = [s.string() for s in reactants[1]]\\n required_cmps_rhs.remove(rhs_cmp)\\n self.graph.add_edge(rhs_cmp, rxn_nodes[1], weight=weights[1], required_compounds=required_cmps_rhs,\\n required_compound_costs=None)\\n self.graph.add_edge(rxn_nodes[0], rhs_cmp, weight=0.0, required_compounds=None)\\n\\n # # # Loop over reaction nodes to add required compounds info to downwards edges; might be unnecessary\\n node_index = 1\\n for node in rxn_nodes:\\n for key in self.graph[node].keys():\\n self.graph.edges[node, key]['required_compounds'] = \\\\\\n self.graph.edges[key, rxn_nodes[node_index]]['required_compounds']\\n node_index -= 1\",\n \"def _cmplx_add_ ( s , o ) :\\n return o + complex ( s )\",\n \"def test_radd():\\n # Test for reverse addition with scalar Rnode object and float value\\n x = Rnode(0.11)\\n z = 0.5 + x\\n z.grad_value = 1.0\\n\\n try:\\n assert z.value == x.value + 0.5\\n except AssertionError as e:\\n print(e)\",\n \"def RXX(self, theta:Union[int, float], qubit_expr): \\n self.apply_gate_operation(RXX(theta), qubit_expr)\",\n \"def __init__(self):\\n super().__init__(\\\"ccx\\\", 3, [])\",\n \"def gate2zx(box):\\n if isinstance(box, (Bra, Ket)):\\n dom, cod = (1, 0) if isinstance(box, Bra) else (0, 1)\\n return Id(0).tensor(*[\\n X(dom, cod, phase=.5 * bit) for bit in box.bitstring])\\n if isinstance(box, (Rz, Rx)):\\n return (Z if isinstance(box, Rz) else X)(1, 1, box.phase)\\n if isinstance(box, CRz):\\n return Z(1, 2) @ Z(1, 2, box.phase)\\\\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\\n if isinstance(box, CRx):\\n return X(1, 2) @ X(1, 2, box.phase)\\\\\\n >> Id(1) @ (Z(2, 1) >> X(1, 0, -box.phase)) @ Id(1)\\n if isinstance(box, quantum.CU1):\\n return Z(1, 2, box.phase) @ Z(1, 2, box.phase)\\\\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\\n standard_gates = {\\n quantum.H: H,\\n quantum.Z: Z(1, 1, .5),\\n quantum.X: X(1, 1, .5),\\n quantum.Y: Y(1, 1, .5),\\n CZ: Z(1, 2) @ Id(1) >> Id(1) @ Had() @ Id(1) >> Id(1) @ Z(2, 1),\\n CX: Z(1, 2) @ Id(1) >> Id(1) @ X(2, 1)}\\n return standard_gates[box]\",\n \"def plot_cnxs(self,x_shift,y_shift):\\n\\n if not self.cnxs: return # Bounce if option not selected\\n\\n self.node_cnx_crds[:,:2] += x_shift*self.pbc[0]\\n self.node_cnx_crds[:,2:] += y_shift*self.pbc[1]\\n for cnx_crd in self.node_cnx_crds:\\n self.ax.plot(cnx_crd[:2],cnx_crd[2:],c=self.lc,lw=self.lw)\\n self.node_cnx_crds[:,:2] -= x_shift*self.pbc[0]\\n self.node_cnx_crds[:,2:] -= y_shift*self.pbc[1]\",\n \"def DEX(self, *_):\\n self._dec_or_inc_register('X', increment=False)\",\n \"def ADD_I_Vx(self, x):\\n\\t\\tself.I += self.V[x]\",\n \"def _gyration(self, x, y, v, c):\\n xy = self._mobius_add(x, y, c)\\n yv = self._mobius_add(y, v, c)\\n xyv = self._mobius_add(x, yv, c)\\n return self._mobius_add(-xy, xyv, c)\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def xscalary_plus_z(scalar, x, y, activation=None):\\n R = tf.add(tf.scalar_mul(scalar,x), y)\\n if activation:\\n return activation(R)\\n else: \\n return R\",\n \"def convert_to_circuit(x):\\n y = np.arcsin(x)\\n z = np.arccos(x**2)\\n qubits = cirq.GridQubit.rect(5, 1)\\n circuit = cirq.Circuit()\\n for i in range(5):\\n circuit.append(cirq.ry(y).on(qubits[i]))\\n circuit.append(cirq.rz(z).on(qubits[i]))\\n return circuit\",\n \"def add_component(self, xi):\\n assert xi.berkovich_line() is self.berkovich_line(), \\\"xi must be a point\\\\\\n on the Berkovich line underlying this model\\\"\\n X = self\\n if not X.is_component(xi):\\n ComponentOfModel(X, xi)\\n X._changed = True\\n\\n \\\"\\\"\\\"\\n T = X.tree()\\n # we have to first check whether xi is already a component !\\n # the first condition should be unnecessary; this is a bug in\\n # mclf.berkovich_trees: T.find_point for an empty tree gives an error\\n if not X.is_component(xi):\\n T, vertex = T.add_point(xi)\\n self._tree = T\\n component = ComponentOfModel(self, vertex)\\n if component.is_horizontal():\\n self._horizontal_components.append(component)\\n else:\\n self._vertical_components.append(component)\\n # we report that the model has changed\\n self._changed = True\\n \\\"\\\"\\\"\",\n \"def _r_x(angle: tf.Tensor) -> tf.Tensor:\\n cos = tf.cos(tf.multiply(angle, tf.constant(0.5, dtype=tf.float64)))\\n sin = tf.sin(tf.multiply(angle, tf.constant(0.5, dtype=tf.float64)))\\n sin_complex = tf.complex(tf.constant(0, dtype=tf.float64), sin)\\n cos_complex = tf.complex(cos, tf.constant(0, dtype=tf.float64))\\n rx = tf.stack([[cos_complex, -sin_complex], [-sin_complex, cos_complex]])\\n\\n return rx\",\n \"def INX(self, *_):\\n self._dec_or_inc_register('X', increment=True)\",\n \"def addx(self, addr):\\n\\n val = self.mem_if.read(addr, index=self.reg.idx)\\n result = self.alu.add(self.reg.accum, val)\\n self.reg.accum = result\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def test_add(self):\\n qc_cal = QuantumCircuit(2)\\n qc_cal.rzx(0.5, 0, 1)\\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\\n\\n qc = QuantumCircuit(2) & qc_cal\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\\n\\n qc = qc_cal & QuantumCircuit(2)\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def test_iadd(self):\\n qc_cal = QuantumCircuit(2)\\n qc_cal.rzx(0.5, 0, 1)\\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\\n\\n qc = QuantumCircuit(2)\\n qc &= qc_cal\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\",\n \"def add_x(self, x, add):\\n return (x + add) % self.x_len\",\n \"def _control_predefined(operation, num_ctrl_qubits):\\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\\n if num_ctrl_qubits == 1:\\n import qiskit.extensions.standard.cx\\n cgate = qiskit.extensions.standard.cx.CnotGate()\\n else:\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n elif operation.name == 'y':\\n import qiskit.extensions.standard.cy\\n cgate = qiskit.extensions.standard.cy.CyGate()\\n elif operation.name == 'z':\\n import qiskit.extensions.standard.cz\\n cgate = qiskit.extensions.standard.cz.CzGate()\\n elif operation.name == 'h':\\n import qiskit.extensions.standard.ch\\n cgate = qiskit.extensions.standard.ch.CHGate()\\n elif operation.name in {'rx', 'ry', 'rz'}:\\n if operation.name == 'rx':\\n import qiskit.extensions.standard.crx\\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\\n elif operation.name == 'ry':\\n import qiskit.extensions.standard.cry\\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\\n else: # operation.name == 'rz'\\n import qiskit.extensions.standard.crz\\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\\n if num_ctrl_qubits == 1:\\n return cgate\\n else:\\n # only predefined for one control qubit\\n return cgate.control(num_ctrl_qubits - 1)\\n elif operation.name == 'swap':\\n import qiskit.extensions.standard.cswap\\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\\n elif operation.name == 'u1':\\n import qiskit.extensions.standard.cu1\\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\\n elif operation.name == 'u3':\\n import qiskit.extensions.standard.cu3\\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\\n elif operation.name == 'cx':\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n else:\\n raise QiskitError('No standard controlled gate for \\\"{}\\\"'.format(\\n operation.name))\\n return cgate\",\n \"def test_coreg_shift(self):\\r\\n with gw.open(l8_224077_20200518_B2) as target, gw.open(\\r\\n l8_224077_20200518_B4\\r\\n ) as reference:\\r\\n with tempfile.TemporaryDirectory() as tmp:\\r\\n # Shift by 1 pixel in each direction\\r\\n target_shifted = shift(target, x=1, y=1)\\r\\n tmp_file = Path(tmp) / '_tmp_shift.tif'\\r\\n target_shifted.gw.save(tmp_file, overwrite=True)\\r\\n with gw.open(tmp_file) as target_shifted:\\r\\n # Co-register the shifted data\\r\\n shifted = gw.coregister(\\r\\n target=target_shifted,\\r\\n reference=reference,\\r\\n ws=(256, 256),\\r\\n r_b4match=1,\\r\\n s_b4match=1,\\r\\n max_shift=5,\\r\\n resamp_alg_deshift='nearest',\\r\\n resamp_alg_calc='cubic',\\r\\n out_gsd=[target_shifted.gw.celly, reference.gw.celly],\\r\\n q=True,\\r\\n nodata=(0, 0),\\r\\n CPUs=1,\\r\\n )\\r\\n self.assertFalse(\\r\\n np.allclose(\\r\\n target.values[:, :-1, :-1],\\r\\n target_shifted.values[:, :-1, :-1],\\r\\n )\\r\\n )\\r\\n # Check if the corrected data match the original (unshifted) target\\r\\n self.assertTrue(\\r\\n np.allclose(\\r\\n target.values[:, :-1, :-1],\\r\\n shifted.values[:, :-1, :-1],\\r\\n )\\r\\n )\",\n \"def CPX(self, value):\\n self._compare(value, 'X')\",\n \"def closure_plus(self):\\n cdef StdVectorFst result = self.copy()\\n result.set_closure(plus=True)\\n return result\",\n \"def TAX(self, *_):\\n self.reg.X = self.reg.A\\n self.reg.N = self.reg.X << 7\\n self.reg.Z = self.reg.X == 0\",\n \"def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\\n if q_args is None and c_args is None:\\n raise GateError(\\\"Gate needs at least one quantum argument or classical argument\\\")\\n if isinstance(gate, CompositeGate):\\n if mapping is None:\\n raise GateError(\\\"Must provide arguments mapping for composite gate inside a composite gate.\\\")\\n else:\\n inv_mappimg = dict()\\n for key, value in mapping.items():\\n inv_mappimg[value] = key\\n if gate is self:\\n gates = gate.copy.gates\\n else:\\n gates = gate.gates\\n for g in gates:\\n new_q_args = None\\n new_c_args = None\\n if g[1] is not None:\\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\\n if g[2] is not None:\\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\\n self.add_gate(gate=g[0], q_args=new_q_args,\\n c_args=new_c_args, params=g[3])\\n else:\\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\\n raise GateError(\\\"Gate must be either a CompositeGate or a string from: \\\"\\n \\\"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\\\")\\n if q_args is not None:\\n for q_arg in q_args:\\n if q_arg not in self.q_args:\\n self.add_q_arg(q_arg)\\n if c_args is not None:\\n for c_arg in c_args:\\n if c_arg not in self.c_args:\\n self.add_c_arg(c_arg)\\n if params is not None:\\n for param in params:\\n if param not in self.params:\\n self.add_param(param)\\n self._gates.append((gate, q_args, c_args, params))\",\n \"def addXValue(self,value):\\n self.__XValue.append(value)\\n self.updateValue()\",\n \"def gelu_new(x):\\n cdf = 0.5 * (1.0 + tf.tanh((np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))\\n return x * cdf\",\n \"def dcx(self, addr):\\n\\n self.reg.idx = self.reg.idx.inc(-1)\\n self.reg.zerox_flag = self.reg.idx.eq_zero()\",\n \"def cvBall(ctrlName, r=1):\\r\\n # create circles to get the shapes:\\r\\n ballX = cmds.circle(n=ctrlName+\\\"_x\\\", ch=False, o=True, nr=(1, 0, 0), d=3, s=8, radius=r)\\r\\n ballY = cmds.circle(n=ctrlName+\\\"_y\\\", ch=False, o=True, nr=(0, 1, 0), d=3, s=8, radius=r)\\r\\n ballZ = cmds.circle(n=ctrlName+\\\"_z\\\", ch=False, o=True, nr=(0, 0, 1), d=3, s=8, radius=r)\\r\\n # parent shapes to transform:\\r\\n ballCtrl = cmds.group(name=ctrlName, empty=True)\\r\\n cmds.parent( cmds.listRelatives(ballX, shapes=True, children=True)[0], ballCtrl, relative=True, shape=True)\\r\\n cmds.parent( cmds.listRelatives(ballY, shapes=True, children=True)[0], ballCtrl, relative=True, shape=True)\\r\\n cmds.parent( cmds.listRelatives(ballZ, shapes=True, children=True)[0], ballCtrl, relative=True, shape=True)\\r\\n # delete old x, y and z transforms:\\r\\n cmds.delete(ballX, ballY, ballZ)\\r\\n cmds.select(clear=True)\\r\\n return ballCtrl\",\n \"def cz(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CZ(), target=[control, target])\",\n \"def _process_cnot(self, node):\\n id0 = self._process_bit_id(node.children[0])\\n id1 = self._process_bit_id(node.children[1])\\n if not(len(id0) == len(id1) or len(id0) == 1 or len(id1) == 1):\\n raise UnrollerError(\\\"internal error: qreg size mismatch\\\",\\n \\\"line=%s\\\" % node.line, \\\"file=%s\\\" % node.file)\\n maxidx = max([len(id0), len(id1)])\\n for idx in range(maxidx):\\n if len(id0) > 1 and len(id1) > 1:\\n self.backend.cx(id0[idx], id1[idx])\\n elif len(id0) > 1:\\n self.backend.cx(id0[idx], id1[0])\\n else:\\n self.backend.cx(id0[0], id1[idx])\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def x3(self):\\n return self._x + self._x3\",\n \"def addThreeNodesRig(self):\\r\\n cam = self.nativePointer()\\r\\n\\r\\n # create controls\\r\\n pos = mxs.star(radius1 = 6.5, radius2 = 5.5, points=16)\\r\\n trans = mxs.rectangle(length=10.2, width=4.5)\\r\\n rot = mxs.ngon(radius=2.0, nSides=3, corner_radius=0.5)\\r\\n\\r\\n # rename controls\\r\\n pos.name = str(cam.name) + 'position'\\r\\n trans.name = str(cam.name) + 'translation'\\r\\n rot.name = str(cam.name) + 'rotation'\\r\\n\\r\\n # rotate controls into place\\r\\n pos.rotation = mxs.eulerangles(90, 0 , 0)\\r\\n trans.rotation = mxs.eulerangles(90, 0 , 0)\\r\\n rot.rotation = mxs.eulerangles(0, 0, -90)\\r\\n\\r\\n # reset xforms\\r\\n mxs.resetxform(pos)\\r\\n mxs.resetxform(trans)\\r\\n mxs.resetxform(rot)\\r\\n\\r\\n # collapse xforms\\r\\n mxs.maxOps.CollapseNode(pos, True)\\r\\n mxs.maxOps.CollapseNode(trans, True)\\r\\n mxs.maxOps.CollapseNode(rot, True)\\r\\n\\r\\n rot.parent = trans\\r\\n trans.parent = pos\\r\\n\\r\\n pos.wirecolor = rot.wirecolor = trans.wirecolor = mxs.color(0, 230, 250)\\r\\n\\r\\n # Move the rig to align with the cam\\r\\n pivrot=cam.rotation\\r\\n pos.rotation*=pivrot;\\r\\n #pos.objectoffsetrot*=pivrot;\\r\\n #pos.objectoffsetpos*=pivrot;\\r\\n\\r\\n pos.position = cam.position\\r\\n #mxs.resetxform(pos)\\r\\n #pos.rotation = cam.rotation\\r\\n\\r\\n\\r\\n # parent the cam to to rig\\r\\n cam.parent = rot\\r\\n\\r\\n return True\",\n \"def add(self,new_x):\\n # TODO add a check here that the new points have the same dimension as the old set\\n add_x = np.concatenate((self.all,new_x),axis=0)\\n self.all = add_x\",\n \"def cvChin(ctrlName, r=1):\\r\\n # create a simple circle curve:\\r\\n curve = cmds.curve(n=ctrlName, d=3, p=[(0, 0.8*r, -0.5*r), (0, 0.9*r, -0.7*r), (0, 0, -0.5*r), (0, -0.8*r, -0.7*r), (0, -0.8*r, 1.4*r), (0, -0.3*r, 1.3*r), (0, 0, 1.2*r), (0, 0, 0), (0, 0.8*r, -0.3*r), (0, 0.8*r, -0.5*r)] )\\r\\n # rename curveShape:\\r\\n renameShape([curve])\\r\\n return curve\",\n \"def __iadd__(self, other):\\n self.x += other.x\\n self.y += other.y\\n return self\",\n \"def brepalgo_ConcatenateWireC0(*args):\\n return _BRepAlgo.brepalgo_ConcatenateWireC0(*args)\",\n \"def _cmplx_factory_ ( cmplxt , re , im ) :\\n return cmplxt ( re , im )\",\n \"def Rgb_add(c1,c2):\\n r = c1.r + c2.r\\n r = max(0, min(1, r))\\n\\n g = c1.g + c2.g\\n g = max(0, min(1, g))\\n\\n b = c1.b + c2.b\\n b = max(0, min(1, b))\\n return Rgb(r,g,b)\",\n \"def __iadd__(self, other):\\n self.center += other.center\\n self.radius += other.radius\\n return self\",\n \"def forward(self, x):\\n res = self.residual(x)\\n x = self.gcn(x)\\n x = self.tcn(x) + res\\n return self.relu(x)\",\n \"def xewy_plus_z(x, y, z, activation=None):\\n R = tf.add(tf.multiply(x, y), z)\\n if activation:\\n return activation(R)\\n else: \\n return R\",\n \"def ConcatenateWireC0(*args):\\n return _BRepAlgo.brepalgo_ConcatenateWireC0(*args)\",\n \"def add_c_arg(self, c_arg):\\n self._c_args.append(c_arg)\\n self.add_decompostion(c_arg)\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def gate_lfcc(recurrent_net, sample_input):\\n length = sample_input.shape[0]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[i, :])\\n select = sigmoid(select)\\n score = sigmoid(score)\\n return np.sum(select * score) / np.sum(select)\",\n \"def incr_operand(self):\\n pass\",\n \"def __add__(self, x):\\n assert isinstance(x, AxisDistance), 'incorrect type of arg x: should be type AxisDistance, is type {}'.format(type(x))\\n tile = self.tile + x.tile\\n pixel = self.pixel + x.pixel\\n subpixel = self.subpixel + x.subpixel\\n return AxisDistance(t=tile, px=pixel, sx=subpixel)\",\n \"def vec_add_scalar (x, c):\\n return [x_i+c for x_i in x]\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def test_add():\\n # Test for addition with scalar Rnode object and float value\\n x = Rnode(0.11)\\n z = x**2 + x\\n z.grad_value = 1.0\\n\\n try:\\n assert z.value == x.value **2 + x.value\\n assert x.grad() == sum(weight * var.grad()\\n for weight, var in x.children)\\n except AssertionError as e:\\n print(e)\",\n \"def add(self, x):\\n self.sum += x\\n self.n += 1\",\n \"def __add__(self, other):\\n if type(other) == int or type(other) == float:\\n x = (other * Ccy.currencies[self.unit])\\n else:\\n x = (other.value / Ccy.currencies[other.unit] * Ccy.currencies[self.unit])\\n return Ccy(x + self.value, self.unit)\",\n \"def evaluate_c(self, x, out=None, **kwargs):\\n return np.zeros(0)\",\n \"def test_add_to_vx(self, cpu):\\n for x in range(0x0, 0xF):\\n for v in range(0x0, 0xFF):\\n for kk in range(0x0, 0xFF):\\n cpu.V_register[x] = v\\n cpu.opcode = 0x7000 | (x << 8) | kk\\n cpu.add_to_vx()\\n assert(cpu.V_register[x] == (v + kk) & 0xFF)\",\n \"def setRLC(self, r, l, c):\\n return\",\n \"def construct(self, x):\\n x = self.conv(x)\\n h0 = self.up_conv1(x)\\n l0 = self.up_conv2(h0)\\n h1 = self.up_conv3(l0 - x)\\n return h1 + h0\",\n \"def addExpr( ):\\n\\n\\ttok = tokens.peek( )\\n\\tif debug: print (\\\"addExpr: \\\", tok)\\n\\tleft = term( )\\n\\ttok = tokens.peek( )\\n\\twhile tok == \\\"+\\\" or tok == \\\"-\\\":\\n\\t\\ttokens.next()\\n\\t\\tright = term( )\\n\\t\\tleft = BinaryExpr( tok, left, right )\\n\\t\\ttok = tokens.peek( )\\n\\treturn left\",\n \"def ADD_Vx_byte(self, x, byte):\\n\\t\\tself.V[x] += byte\\n\\t\\tself.V[x] &= 255\",\n \"def leftshift(x, c):\\n return x << c\",\n \"def acumula_x1(self, x1, rodada):\\n self.x1[rodada].append(x1)\",\n \"def create_carry_condition(new_val, sub_op):\\n if not sub_op:\\n carry_cond = new_val > 0xFF\\n else:\\n carry_cond = new_val >= 0\\n return carry_cond\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.60456556","0.5788765","0.5551391","0.5473348","0.53226703","0.5244496","0.52266806","0.5173726","0.51487964","0.510389","0.50781316","0.5073143","0.49941725","0.4989037","0.49753806","0.49564382","0.493396","0.49102163","0.48927242","0.48697314","0.48601857","0.48467213","0.48406136","0.48405933","0.48381233","0.48355657","0.48347542","0.48079574","0.48011976","0.47880605","0.47604704","0.47295105","0.472853","0.47265485","0.47202593","0.47159344","0.4714316","0.47102997","0.47034663","0.46962684","0.46934864","0.46828663","0.4678597","0.4671981","0.46711543","0.4666207","0.4661333","0.46399093","0.46340764","0.46290907","0.4622525","0.46194625","0.46007368","0.45954463","0.4591703","0.45877618","0.45807615","0.45736656","0.45707017","0.45665193","0.45616418","0.45539102","0.45356324","0.45328277","0.4528375","0.45273414","0.45201707","0.45061877","0.450379","0.45007342","0.44880685","0.4468666","0.4468487","0.44680563","0.4455504","0.44493106","0.4446258","0.44448805","0.44331762","0.44298285","0.44288918","0.44285518","0.44280267","0.4424444","0.4424174","0.4414677","0.44123524","0.4405948","0.44046623","0.44028437","0.43973246","0.43968406","0.4394881","0.43940687","0.43884733","0.43804395","0.43743944","0.4372584","0.43705246","0.43647325"],"string":"[\n \"0.60456556\",\n \"0.5788765\",\n \"0.5551391\",\n \"0.5473348\",\n \"0.53226703\",\n \"0.5244496\",\n \"0.52266806\",\n \"0.5173726\",\n \"0.51487964\",\n \"0.510389\",\n \"0.50781316\",\n \"0.5073143\",\n \"0.49941725\",\n \"0.4989037\",\n \"0.49753806\",\n \"0.49564382\",\n \"0.493396\",\n \"0.49102163\",\n \"0.48927242\",\n \"0.48697314\",\n \"0.48601857\",\n \"0.48467213\",\n \"0.48406136\",\n \"0.48405933\",\n \"0.48381233\",\n \"0.48355657\",\n \"0.48347542\",\n \"0.48079574\",\n \"0.48011976\",\n \"0.47880605\",\n \"0.47604704\",\n \"0.47295105\",\n \"0.472853\",\n \"0.47265485\",\n \"0.47202593\",\n \"0.47159344\",\n \"0.4714316\",\n \"0.47102997\",\n \"0.47034663\",\n \"0.46962684\",\n \"0.46934864\",\n \"0.46828663\",\n \"0.4678597\",\n \"0.4671981\",\n \"0.46711543\",\n \"0.4666207\",\n \"0.4661333\",\n \"0.46399093\",\n \"0.46340764\",\n \"0.46290907\",\n \"0.4622525\",\n \"0.46194625\",\n \"0.46007368\",\n \"0.45954463\",\n \"0.4591703\",\n \"0.45877618\",\n \"0.45807615\",\n \"0.45736656\",\n \"0.45707017\",\n \"0.45665193\",\n \"0.45616418\",\n \"0.45539102\",\n \"0.45356324\",\n \"0.45328277\",\n \"0.4528375\",\n \"0.45273414\",\n \"0.45201707\",\n \"0.45061877\",\n \"0.450379\",\n \"0.45007342\",\n \"0.44880685\",\n \"0.4468666\",\n \"0.4468487\",\n \"0.44680563\",\n \"0.4455504\",\n \"0.44493106\",\n \"0.4446258\",\n \"0.44448805\",\n \"0.44331762\",\n \"0.44298285\",\n \"0.44288918\",\n \"0.44285518\",\n \"0.44280267\",\n \"0.4424444\",\n \"0.4424174\",\n \"0.4414677\",\n \"0.44123524\",\n \"0.4405948\",\n \"0.44046623\",\n \"0.44028437\",\n \"0.43973246\",\n \"0.43968406\",\n \"0.4394881\",\n \"0.43940687\",\n \"0.43884733\",\n \"0.43804395\",\n \"0.43743944\",\n \"0.4372584\",\n \"0.43705246\",\n \"0.43647325\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.65724874"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81746,"cells":{"query":{"kind":"string","value":"add CXR dagger gate (controlled XR dagger gate)."},"document":{"kind":"string","value":"def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def _gcl(x, r, D, Ia, Ct):\n\n Area = np.pi * D ** 2.0 / 4.0\n m = 1.0 / (np.sqrt(1.0 - Ct))\n k = np.sqrt((m + 1.0) / 2.0)\n\n a1 = 0.435449861 # empirically determined\n a2 = 0.797853685\n a3 = -0.124807893\n a4 = 0.136821858\n b1 = 15.6298\n b2 = 1.0\n R96 = a1 * (np.exp(a2 * Ct * Ct + a3 * Ct + a4)) * (b1 * Ia + b2) * D\n\n x0 = (9.6 * D) / ((2.0 * R96 / (k * D)) ** 3.0 - 1.0)\n term1 = (k * D / 2.0) ** (5.0 / 2.0)\n term2 = (105.0 / (2.0 * np.pi)) ** (-0.5)\n term3 = (Ct * Area * x0) ** (-5.0 / 6.0)\n c1 = term1 * term2 * term3\n # c45=3*(c1) ** 2\n\n term10 = 0.1111 # * WindSpeed # U/9.0\n term20 = (Ct * Area * (x + x0) ** (-2.0)) ** (1.0 / 3.0)\n term310 = (r ** (3.0 / 2.0))\n term320 = (3.0 * c1 * c1 * Ct * Area * (x + x0)) ** (-0.5)\n term30 = term310 * term320\n term40 = ((35.0 / (2.0 * np.pi)) ** (3.0 / 10.0)) * \\\n (3.0 * c1 * c1) ** (-1.0 / 5.0)\n DU1 = -term10 * term20 * (term30 - term40) ** 2.0\n\n DU = DU1 # + w2 * DU2\n Rw = ((105 * c1 ** 2.0 / (2 * np.pi)) ** (1. / 5.)) * \\\n (Ct * Area * (x + x0)) ** (1. / 3.)\n return DU, Rw","def _gyration(self, x, y, v, c):\n xy = self._mobius_add(x, y, c)\n yv = self._mobius_add(y, v, c)\n xyv = self._mobius_add(x, yv, c)\n return self._mobius_add(-xy, xyv, c)","def DEX(self, *_):\n self._dec_or_inc_register('X', increment=False)","def gate(self):\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)","def _acc_grads(self, x, label):\n ##\n # Forward propagation\n z1 = self.params.W.dot(x) + self.params.b1\n h = tanh(z1)\n z2 = np.dot(self.params.U, h) + self.params.b2\n y_hat = softmax(z2)\n \n y = make_onehot(label, self.outputsize)\n d2 = y_hat - y\n self.grads.b2 += d2\n self.grads.U += np.outer(d2, h) + self.lreg * self.params.U\n d1 = np.dot(self.params.U.T, d2) * tanhd(z1) \n \n self.grads.W += np.outer(d1, x) + self.lreg * self.params.W\n self.grads.b1 += d1","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def add_corridor_constraint(self,seg,r,weight=1.0):\n\n constraint_type = \"cylinder\"\n params = dict()\n params['x1'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg],\n self.qr_polytraj.waypoints['y'][0,seg],\n self.qr_polytraj.waypoints['z'][0,seg]])\n params['x2'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg+1],\n self.qr_polytraj.waypoints['y'][0,seg+1],\n self.qr_polytraj.waypoints['z'][0,seg+1]])\n params['der'] = 0\n params['l'] = r # Give the same radius buffer on the end caps\n params['r'] = r\n params['weight'] = weight\n params['keep_out'] = False\n params['active_seg'] = seg\n\n\n self.qr_polytraj.add_constraint(constraint_type,params,dynamic_weighting=False,sum_func=False)","def build_glyCB(self, gCBd: Dihedron): # -> None:\n ...","def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def acc_drag(U,comp):\n def drag_prefix(U):\n return -drag_C*rho_A(U)*V_A(U)\n if comp == 'x':\n return drag_prefix(U)*(U[3]+U[1]*dTheta)\n elif comp == 'y':\n return drag_prefix(U)*(U[4]-U[0]*dTheta)\n elif comp =='z':\n return drag_prefix(U)*(U[5])","def cyclic_merit_lag(x,*args):\n CS = args[0]\n print \"rindex\",CS.rindex\n ht = get_ht(x,CS.rindex)\n hf = time2freq(ht)\n CS.hf = hf\n CS.ht = ht\n cs_model,csplus,csminus,phases = make_model_cs(hf,CS.s0,CS.bw,CS.ref_freq)\n merit = 2*(np.abs(cs_model[:,1:] - CS.cs[:,1:])**2).sum() #ignore zeroth harmonic (dc term)\n \n # the objval list keeps track of how the convergence is going\n CS.objval.append(merit)\n \n #gradient_lag\n diff = cs_model - CS.cs #model - data\n cc1 = cs2cc(diff * csminus)\n \n# original c code for reference:\n# for (ilag=0; ilag<cc1.nlag; ilag++) {\n# gradient->data[ilag] = 0.0 + I * 0.0;\n# int lag = (ilag<=cc1.nlag/2) ? ilag : ilag-cc1.nlag;\n# tau = (double)lag * (double)cs->nchan /\n# ( (double)cc1.nlag * cc1.bw*1.e6 );\n# for (ih=1; ih<cc1.nharm; ih++) {\n# phs = M_PI * tau * (double)ih * cc1.ref_freq;\n# phasor = cos(phs)+I*sin(phs);\n# fftwf_complex *ccval = get_cc(&cc1,ih,ip,ilag);\n# gradient->data[ilag] += 4.0 * (*ccval) * phasor\n# * conj(s0->data[ih]) / (float)cs->nchan;\n# }\n# }\n\n #we reuse phases and csminus, csplus from the make_model_cs call\n\n phasors = np.exp(1j*phases)\n cs0 = np.repeat(CS.s0[np.newaxis,:],CS.nlag,axis=0) #filter2cs\n grad = 4.0 * cc1 * phasors * np.conj(cs0) / CS.nchan\n grad = grad[:,1:].sum(1) # sum over all harmonics to get function of lag\n \n #conjugate(res)\n #calc positive shear\n #multiply\n #cs2cc\n cc2 = cs2cc(np.conj(diff) * csplus)\n grad2 = 4.0 * cc2 * np.conj(phasors) * cs0 / CS.nchan\n \n grad = grad + grad2[:,1:].sum(1)\n CS.grad = grad[:]\n CS.model = cs_model[:]\n\n if CS.iprint:\n print \"merit= %.7e grad= %.7e\" % (merit,(np.abs(grad)**2).sum())\n \n if CS.make_plots:\n if CS.niter % CS.plot_every == 0:\n CS.plotCurrentSolution()\n \n \n \n grad = get_params(grad, CS.rindex)\n CS.niter += 1\n \n return merit,grad","def grad(self, crd):\n grad = np.zeros((2, *crd.shape), dtype=float)\n grad[0, :, :] = 2.*crd\n grad[1, :, :] = 2.*(crd-1)\n return grad","def DR(R,Pc):\n return r1*R*(K1**B1/(K1**B1 + (A/R)**B1))*(S/(S + R*Pc + Pc)) \\\n - gwt*A - r2*R*(K2**B2/(K2**B2 + (A)**B2))*(S/(S + R*Pc + Pc) ) \\\n *(R*M)/(K3 + R*M) + R*gc","def dcx(self, addr):\n\n self.reg.idx = self.reg.idx.inc(-1)\n self.reg.zerox_flag = self.reg.idx.eq_zero()","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def CX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)","def test_append_dangling_gate(self, circuit):\n match = (\n r\"Number of wire IDs \\(2\\) must match the number of wires connected to the gate \\(1\\).\"\n )\n gate = jet.GateFactory.create(\"H\")\n with pytest.raises(ValueError, match=match):\n circuit.append_gate(gate, wire_ids=[0, 1])","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def add_cd_samples(self): \n \n if self.num_hidden == 0:\n \n (self.p_xi_given_x_, self.gibbs_samples), self.gibbs_updates =\\\n theano.scan(self.gibbs_step_fully_visible, n_steps = self.gibbs_steps)\n \n if self.num_hidden > 0:\n \n if \"PCD\" in self.algorithm:\n init_chain = self.persistent_gibbs\n else:\n # positive phase\n _, _, hid_sample = self.get_h_given_v_samples(self.x)\n\n init_chain = hid_sample\n \n (\n [\n vis_inputs,\n vis_outputs,\n vis_samples,\n hid_inputs,\n hid_means,\n hid_samples\n ],\n updates\n ) = theano.scan(\n self.gibbs_step_rbm_hid,\n outputs_info=[None, None, None, None, None, init_chain],\n n_steps= self.gibbs_steps)\n \n self.updates.update(updates)\n \n self.hid_samples = hid_samples[-1]\n \n self.rbm_cd_samples = theano.gradient.disconnected_grad(vis_samples[-1])\n \n self.rbm_vis_outputs = theano.gradient.disconnected_grad(vis_outputs[-1])","def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def cxcy_to_gcxgcy(cxcy, priors_cxcy):\n\n # The 10 and 5 below are referred to as 'variances' in the original Caffe repo, completely empirical\n # They are for some sort of numerical conditioning, for 'scaling the localization gradient'\n # See https://github.com/weiliu89/caffe/issues/155\n return torch.cat([(cxcy[:, :2] - priors_cxcy[:, :2]) / (priors_cxcy[:, 2:] / 10), # g_c_x, g_c_y\n torch.log(cxcy[:, 2:] / priors_cxcy[:, 2:]) * 5], 1) # g_w, g_h","def Rgb_add(c1,c2):\n r = c1.r + c2.r\n r = max(0, min(1, r))\n\n g = c1.g + c2.g\n g = max(0, min(1, g))\n\n b = c1.b + c2.b\n b = max(0, min(1, b))\n return Rgb(r,g,b)","def ccx(self, q0, q1, q2, ctrl=None):\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\n return self","def gru(params, h, x):\n bfg = 0.5\n hx = np.concatenate([h, x], axis=0)\n ru = sigmoid(np.dot(params['wRUHX'], hx) + params['bRU'])\n r, u = np.split(ru, 2, axis=0)\n rhx = np.concatenate([r * h, x])\n c = np.tanh(np.dot(params['wCHX'], rhx) + params['bC'] + bfg)\n return u * h + (1.0 - u) * c","def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def dacc(self, gl, gr, c, phi_l, phi_r, psi_u, psi_d):\n logger.debug('[START] PID[%s] dAcc skeleton', PID)\n # Step 1 : Computing Local Intermediate Values\n gt = Segment([None] * self.__nb_segs)\n i = 0\n for (start, offset) in \\\n self.__global_index[self.__start_index: self.__start_index + self.__nb_segs]:\n seg = Segment(self.__content[start:start + offset])\n logger.debug('[START] PID[%s] dacc_path from %s to %s', PID, start, start + offset)\n if seg.has_critical():\n gt[i] = seg.dacc_path(phi_l, phi_r, psi_u)\n else:\n gt[i] = TaggedValue(seg[0].get_value(), \"L\")\n logger.debug('[END] PID[%s] dacc_path from %s to %s', PID, start, start + offset)\n i = i + 1\n # Step 2 : Gather Local Results\n self.__gather_local_result(gt, i, TAG_COMM_DACC_1)\n # Step 3 : Global Downward Accumulation\n par.at_root(lambda: logger.debug('[START] PID[%s] dacc_global', PID))\n gt2 = (gt.dacc_global(psi_d, c) if PID == 0 else None)\n par.at_root(lambda: logger.debug('[END] PID[%s] dacc_global', PID))\n # Step 4 : Distributing Global Result\n gt2 = self.__distribute_global_result(gt2, TAG_COMM_DACC_2)\n # Step 5 : Local Downward Accumulation\n content = SList([None] * self.__content.length())\n for i in range(len(self.__global_index[self.__start_index: self.__start_index +\n self.__nb_segs])):\n (start, offset) = self.__global_index[self.__start_index: self.__start_index +\n self.__nb_segs][i]\n logger.debug('[START] PID[%s] dacc_local from %s to %s', PID, start, start + offset)\n content[start:start + offset] = \\\n Segment(self.__content[start:start + offset]).dacc_local(gl, gr, gt2[i].get_value())\n logger.debug('[END] PID[%s] dacc_local from %s to %s', PID, start, start + offset)\n logger.debug('[END] PID[%s] dAcc skeleton', PID)\n return PTree.init(self, content)","def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\n if q_args is None and c_args is None:\n raise GateError(\"Gate needs at least one quantum argument or classical argument\")\n if isinstance(gate, CompositeGate):\n if mapping is None:\n raise GateError(\"Must provide arguments mapping for composite gate inside a composite gate.\")\n else:\n inv_mappimg = dict()\n for key, value in mapping.items():\n inv_mappimg[value] = key\n if gate is self:\n gates = gate.copy.gates\n else:\n gates = gate.gates\n for g in gates:\n new_q_args = None\n new_c_args = None\n if g[1] is not None:\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\n if g[2] is not None:\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\n self.add_gate(gate=g[0], q_args=new_q_args,\n c_args=new_c_args, params=g[3])\n else:\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\n raise GateError(\"Gate must be either a CompositeGate or a string from: \"\n \"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\")\n if q_args is not None:\n for q_arg in q_args:\n if q_arg not in self.q_args:\n self.add_q_arg(q_arg)\n if c_args is not None:\n for c_arg in c_args:\n if c_arg not in self.c_args:\n self.add_c_arg(c_arg)\n if params is not None:\n for param in params:\n if param not in self.params:\n self.add_param(param)\n self._gates.append((gate, q_args, c_args, params))","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def __init__(self):\n super().__init__(\"ccx\", 3, [])","def glycosylate(self):\n chid = self.chain.get()\n sequon = self.sequon.get()\n self.sequon_colors[sequon] = [.7, .1, 0]\n key = self.sequon.get()\n residue = self.myGlycosylator.get_residue(key)\n #Build new glycan\n if self.selected_glycan:\n self.myGlycosylator.connect_topology['SELECTED'] = self.selected_glycan[1]\n #build from current glycan\n if key in self.original_glycans:\n original_glycan = self.original_glycanMolecules[key].atom_group\n r,t = self.original_glycans[key]\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\n else:\n original_glycan = None\n connect_tree = None \n #Use current glycan\n else:\n original_glycan = self.original_glycanMolecules[key]\n r,t = self.original_glycans[key]\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\n self.myGlycosylator.connect_topology['SELECTED'] = self.myGlycosylator.build_connect_topology(original_glycan) \n original_glycan = original_glycan.atom_group\n \n segname = 'G'+key.split(',')[2]\n glycan,bonds = self.myGlycosylator.glycosylate('SELECTED', \n template_glycan_tree = connect_tree, \n template_glycan = original_glycan,\n link_residue=residue, link_patch = 'NGLB', chain = 'G', segname=segname)\n new_glycan = glc.Molecule(key)\n new_glycan.set_AtomGroup(glycan, bonds = bonds)\n self.myGlycosylator.assign_patches(new_glycan)\n self.linked_glycanMolecules[key] = new_glycan\n self.linked_glycans[key] = [new_glycan.rootRes, new_glycan.interresidue_connectivity]\n self.names.update(new_glycan.get_names())\n # Update glycoprotein and sequon panels\n self.draw_glycoprotein(chid)\n self.draw_glycan(sequon)","def btnCommand_CXPMGR(self, btn_name):\n\t\tprint(\"Button {} is pressed.\".format(btn_name) )\n\n\t\tif btn_name == 'add':\n\n\t\t\tpass\n\t\telif btn_name == 'del':\n\t\t\tpass\n\t\telif btn_name == 'prev':\n\t\t\tpass\n\t\telif btn_name == 'next':\n\t\t\tpass\n\t\telse:\n\t\t\tprint(\"ERROR, illegal button ID {} !!\".format(btn_name))\n\t\t\treturn\n\n\t\tpass","def add_c_arg(self, c_arg):\n self._c_args.append(c_arg)\n self.add_decompostion(c_arg)","def incr_operand(self):\n pass","def reapply(self, circ):\n self._modifiers(circ.sdg(self.qargs[0]))","def orbit_cross():\n \n # potential\n ham = gp.Hamiltonian(gp.MilkyWayPotential(nucleus=dict(m=0), halo=dict(c=0.95, m=7E11), bulge=dict(m=4E9), disk=dict(m=5.5e10)))\n gc_frame = coord.Galactocentric(galcen_distance=8*u.kpc, z_sun=0*u.pc)\n \n # orbital solution\n pos = np.load('/home/ana/projects/GD1-DR2/data/gd1_orbit.npy')\n phi1, phi2, d, pm1, pm2, vr = pos\n\n c = gc.GD1(phi1=phi1*u.deg, phi2=phi2*u.deg, distance=d*u.kpc, \n pm_phi1_cosphi2=pm1*u.mas/u.yr,\n pm_phi2=pm2*u.mas/u.yr,\n radial_velocity=vr*u.km/u.s)\n w0 = gd.PhaseSpacePosition(c.transform_to(gc_frame).cartesian)\n \n dt = 0.5 * u.Myr\n n_steps = 250\n fit_orbit = ham.integrate_orbit(w0, dt=dt, n_steps=120)\n\n # find gap 6D location at present\n gap_phi0 = -40*u.deg\n model_gd1 = fit_orbit.to_coord_frame(gc.GD1, galactocentric_frame=gc_frame)\n gap_i = np.abs(model_gd1.phi1.wrap_at(180*u.deg) - gap_phi0).argmin()\n gap_w0 = fit_orbit[gap_i]\n \n # gap orbit\n t1 = 0*u.Myr\n t2 = -1*u.Gyr\n dt = -0.5\n t = np.arange(t1.to(u.Myr).value, t2.to(u.Myr).value+dt, dt)\n gap_orbit = ham.integrate_orbit(gap_w0, dt=dt, t1=t1, t2=t2)\n \n \n # plot relative distances as a function of time\n plt.close()\n plt.figure(figsize=(9,5))\n \n lw = 3\n\n # show classicals\n tcls = Table.read('../data/positions_classical.fits')\n ra, dec, d, pmra, pmdec, vr = tcls['ra'], tcls['dec'], tcls['distance'], tcls['pmra'], tcls['pmdec'], tcls['vr']\n cs = coord.ICRS(ra=ra, dec=dec, distance=d, pm_ra_cosdec=pmra, pm_dec=pmdec, radial_velocity=vr)\n ws = gd.PhaseSpacePosition(cs.transform_to(gc_frame).cartesian)\n satellite_orbit = ham.integrate_orbit(ws, dt=dt, t1=t1, t2=t2)\n for e in range(len(tcls)):\n if e==0:\n label = 'Classical\\ndwarfs'\n else:\n label = ''\n rel_distance = np.linalg.norm(gap_orbit.xyz - satellite_orbit.xyz[:,:,e], axis=0)*gap_orbit.xyz[0].unit\n plt.plot(t, rel_distance, '-', color=mpl.cm.Reds(0.9), alpha=0.5, label=label, lw=lw)\n \n # show ultrafaints\n tufd = Table.read('../data/positions_ufd.fits')\n ra, dec, d, pmra, pmdec, vr = tufd['ra'], tufd['dec'], tufd['distance'], tufd['pmra'], tufd['pmdec'], tufd['vr']\n cs = coord.ICRS(ra=ra, dec=dec, distance=d, pm_ra_cosdec=pmra, pm_dec=pmdec, radial_velocity=vr)\n ws = gd.PhaseSpacePosition(cs.transform_to(gc_frame).cartesian)\n satellite_orbit = ham.integrate_orbit(ws, dt=dt, t1=t1, t2=t2)\n for e in range(len(tufd)):\n if e==0:\n label = 'Ultra-faint\\ndwarfs'\n else:\n label = ''\n rel_distance = np.linalg.norm(gap_orbit.xyz - satellite_orbit.xyz[:,:,e], axis=0)*gap_orbit.xyz[0].unit\n plt.plot(t, rel_distance, '-', color=mpl.cm.Reds(0.7), alpha=0.5, label=label, lw=lw)\n \n # show globulars\n tgc = Table.read('../data/positions_globular.fits')\n ra, dec, d, pmra, pmdec, vr = tgc['ra'], tgc['dec'], tgc['distance'], tgc['pmra'], tgc['pmdec'], tgc['vr']\n cs = coord.ICRS(ra=ra, dec=dec, distance=d, pm_ra_cosdec=pmra, pm_dec=pmdec, radial_velocity=vr)\n ws = gd.PhaseSpacePosition(cs.transform_to(gc_frame).cartesian)\n satellite_orbit = ham.integrate_orbit(ws, dt=dt, t1=t1, t2=t2)\n for e in range(len(tgc)):\n if e==0:\n label = 'Globular\\nclusters'\n else:\n label = ''\n rel_distance = np.linalg.norm(gap_orbit.xyz - satellite_orbit.xyz[:,:,e], axis=0)*gap_orbit.xyz[0].unit\n plt.plot(t, rel_distance, '-', color=mpl.cm.Reds(0.5), alpha=0.5, label=label, lw=lw)\n\n plt.plot(t, np.abs(gap_orbit.xyz[2]), '-', color=mpl.cm.Reds(0.3), alpha=0.5, label='Disk', lw=lw, zorder=0)\n #plt.plot(t, np.sqrt(gap_orbit.xyz[0]**2 + gap_orbit.xyz[1]**2), 'r-', alpha=0.2)\n\n plt.ylim(0.1,200)\n plt.gca().set_yscale('log')\n \n plt.legend(loc=2, fontsize='small', markerscale=2)\n plt.xlabel('Time [Myr]')\n plt.ylabel('Relative distance [kpc]')\n \n plt.tight_layout()\n plt.savefig('../plots/satellite_distances.png', dpi=200)\n plt.savefig('../paper/satellite_distances.pdf')","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def gelu_new(x):\n cdf = 0.5 * (1.0 + tf.tanh((np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))\n return x * cdf","def cvBaseGuide(ctrlName, r=1):\r\n # create a simple circle curve:\r\n circle = cmds.circle(n=ctrlName, ch=True, o=True, nr=(0, 0, 1), d=3, s=8, radius=r)[0]\r\n radiusCtrl = cmds.circle(n=ctrlName+\"_radiusCtrl\", ch=True, o=True, nr=(0, 1, 0), d=3, s=8, radius=(r/4.0))[0]\r\n # rename curveShape:\r\n renameShape([circle, radiusCtrl])\r\n # configure system of limits and radius:\r\n cmds.setAttr(radiusCtrl+\".translateX\", r)\r\n cmds.parent(radiusCtrl, circle, relative=True)\r\n cmds.transformLimits(radiusCtrl, tx=(0.01, 1), etx=(True, False))\r\n setLockHide([radiusCtrl], ['ty', 'tz', 'rx', 'ry', 'rz', 'sx', 'sy', 'sz'])\r\n # find makeNurbCircle history of the circles:\r\n historyList = findHistory([circle, radiusCtrl], 'makeNurbCircle')\r\n circleHistory = historyList[0]\r\n radiusCtrlHistory = historyList[1]\r\n # rename and make a connection for circle:\r\n circleHistory = cmds.rename(circleHistory, circle+\"_makeNurbCircle\")\r\n cmds.connectAttr(radiusCtrl+\".tx\", circleHistory+\".radius\", force=True)\r\n radiusCtrlHistory = cmds.rename(radiusCtrlHistory, radiusCtrl+\"_makeNurbCircle\")\r\n # create a mutiplyDivide in order to automatisation the radius of the radiusCtrl:\r\n radiusCtrlMD = cmds.createNode('multiplyDivide', name=radiusCtrl+'_md')\r\n cmds.connectAttr(radiusCtrl+'.translateX', radiusCtrlMD+'.input1X', force=True)\r\n cmds.setAttr(radiusCtrlMD+'.input2X', 0.15)\r\n cmds.connectAttr(radiusCtrlMD+\".outputX\", radiusCtrlHistory+\".radius\", force=True)\r\n # colorize curveShapes:\r\n colorShape([circle, radiusCtrl], 'yellow')\r\n cmds.select(clear=True)\r\n return [circle, radiusCtrl]","def rrdb(x):\n h = dense_block(x)\n h = dense_block(h)\n h = dense_block(h)\n h = tf.keras.layers.Lambda(lambda x: x * 0.2)(h)\n out = tf.keras.layers.Add()([h, x])\n return out","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def add_gates(self, num_gates_to_add):\n pass","def relay_tagged(c, x, tag):\n assert tag.is_constant(int)\n rtag = get_union_ctr(tag.value, None)\n return rtag(c.ref(x))","def GachaCraftNodeExcelAddGP1110(builder, GP1110):\n return AddGP1110(builder, GP1110)","def bcc(self, arg):\n\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def add_operators(self, run):\n if self.rate_variation:\n # UpDownOperator to scale the Gamma distribution for this model's\n # feature rates\n updown = ET.SubElement(run, \"operator\", {\"id\":\"featureClockRateGammaUpDown:%s\" % self.name, \"spec\":\"UpDownOperator\", \"scaleFactor\":\"0.5\",\"weight\":\"0.3\"})\n ET.SubElement(updown, \"parameter\", {\"idref\":\"featureClockRateGammaShape:%s\" % self.name, \"name\":\"up\"})\n ET.SubElement(updown, \"parameter\", {\"idref\":\"featureClockRateGammaScale:%s\" % self.name, \"name\":\"down\"})","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def acumula_x1(self, x1, rodada):\n self.x1[rodada].append(x1)","def gcxgcy_to_cxcy(gcxgcy, priors_cxcy):\n\n return torch.cat([gcxgcy[:, :2] * priors_cxcy[:, 2:] / 10 + priors_cxcy[:, :2], # c_x, c_y\n torch.exp(gcxgcy[:, 2:] / 5) * priors_cxcy[:, 2:]], 1) # w, h","def draw_C(self, frame):\n c = self.get_real_leg()\n cv2.circle(\n frame,\n (\n Utils.ConvertX(c.x),\n Utils.ConvertY(c.y)\n ),\n 8,\n color=Utils.blue,\n thickness=-1\n )","def addFCSPoint(self, dxpos, dypos, dzpos=None):\n prefix = \"/cli:python /app:fcs /cmd:add\"\n dx = \"/xpos:\" + `int(dxpos)` \n dy = \"/ypos:\" + `int(dypos)`\n if dzpos is None:\n dz = \"/zpos:0\"\n else:\n dz = \"/zpos:\"+dzpos\n \n \n cmd = \" \".join((prefix,dx,dy,dz))\n #print \"FCS command string\"\n #print cmd\n self.sendCMDstring(cmd)","def MiyamotoNagaiAccel(self, M, rd, r):\n R = np.sqrt(r[0]**2 + r[1]**2) #Finding magnitude of x and y compnets\n zd = rd/5. #Calculating \"zd\"\n B = rd + np.sqrt(r[2]**2 + zd**2) #Calclating \"B\"\n zstuff = 1/np.sqrt(r[2]**2 + zd**2) #Calculating stuff that only appears in z componet\n MNa = -self.G*M/(R**2+B**2)**1.5 * r * np.array([1,1,zstuff]) #Putting it all together\n\n return MNa","def addBond(self, **kwds):\n print kwds\n self.MagCell.addBond(**kwds)","def push(self, dlr):\n print(f\"{self.name}'s {dlr} matched the dealers hand, push\")\n self.chips += self.bet\n self.lastbet = self.bet\n self.bet = 0","def cmd_dgaus():\n cmds = []\n cmds.append(\"r_m[0.0,-1,1]\")\n cmds.append(\"r_s[1.5,0,10]\")\n cmds.append('Gaussian::gaus_c(x,r_m,r_s)')\n cmds.append(\"rt_m[0.0,-1,1]\")\n cmds.append(\"rt_s[3,0,10]\")\n cmds.append('Gaussian::gaus_t(x,rt_m,rt_s)')\n cmds.append(\"f[0.85]\") # fraction of core\n cmds.append(\"SUM::res(f*gaus_c,gaus_t)\")\n return cmds","def _append_cx(self, i, j):\n\n if not 0 <= i < self.num_qubits or not 0 <= j < self.num_qubits:\n raise QiskitError(\"CX qubits are out of bounds.\")\n self.linear[j] = (self.linear[i] + self.linear[j]) % 2\n self.shift[j] = (self.shift[i] + self.shift[j]) % 2","def add(self, y):\n return circuit.add(self, y)","def dX_gene_reg_fn(x, t, topology, params):\n\tparents = topology.parents\n\ttarget = topology.target\n\tinteractions = topology.interactions\n\n\tbase_synth = params[0]\n\tbase_degr = params[1]\n\n\t# Add basal synthesis and basal degradation terms\n\tdX = base_synth - x[target] * base_degr\n\n\t# Add contributions from each edge\n\tfor i in range(len(parents)):\n\t\tp = parents[i]\n\t\tinter = interactions[i]\n\n\t\tj = 2 + i*3\n\t\tb = params[ j ] \t # Interaction 'Strength'\n\t\tk = params[ j + 1 ] # Hill fn parameter (theta)\n\t\tm = params[ j + 2 ] # Hill fn parameter (m)\n\n\t\t# Value of parent for all t\n\t\tparent_val = x[p]\n\n\t\tif inter == 0:\n\t\t\tdX += (b * parent_val**m) / (parent_val**m + k**m)\n\t\telif inter == 1:\n\t\t\tdX += b / (1 + (parent_val/k)**m)\n\t\n\treturn dX","def gcl(rel_pos, c_t, D, ti):\n x = rel_pos[:, 0]\n r = np.sqrt(rel_pos[:, 1] ** 2.0 + rel_pos[:, 2] ** 2.0)\n DU = np.zeros_like(x)\n ind = x > 0.0\n DU_, Rw = _gcl(x[ind], r[ind], D[ind], ti[ind], c_t[ind])\n DU_[abs(r[ind]) > Rw] = 0.0\n DU_[DU_ < -1.0] = 0.0 # Avoid some weirdiness\n DU[ind] = DU_\n return DU","def get_crd_cc(self, axis, shaped=False):\n return self._src_crds.get_cc(axis, shaped=shaped)","def grad_cc_piece(x,k_ind,m_ind):\n \n g_cc = np.zeros_like(x)\n i = cfg.min_line[k_ind,m_ind] * cfg.nfea + cfg.nfea*sum(cfg.jk[i] for i in range(k_ind)) # starting of the min line\n g_cc[i:i+cfg.nfea-1] = cfg.a[m_ind,:cfg.nfea-1]\n g_cc[i+cfg.nfea-1] = 1.0\n \n return g_cc","def brepalgo_ConcatenateWireC0(*args):\n return _BRepAlgo.brepalgo_ConcatenateWireC0(*args)","def add_rxn(self, reaction: db.Reaction):\n # Add two rxn nodes\n rxn_nodes = []\n reaction_id = reaction.id().string()\n\n for i in range(0, 2):\n # Add rxn node between lhs and rhs compound\n rxn_node = ';'.join([reaction_id, str(i)])\n rxn_node += ';'\n self.graph.add_node(rxn_node, color='rxn_node')\n rxn_nodes.append(rxn_node)\n # Convert to strings\n reactants = reaction.get_reactants(db.Side.BOTH)\n reactant_types = reaction.get_reactant_types(db.Side.BOTH)\n weights = self._get_weight(reaction)\n # Add lhs aggregates and connect\n for lhs_cmp, lhs_type in zip([i.string() for i in reactants[0]],\n [i.name for i in reactant_types[0]]):\n if lhs_cmp not in self.graph:\n self.graph.add_node(lhs_cmp, type=lhs_type)\n required_cmps_lhs = [s.string() for s in reactants[0]]\n required_cmps_lhs.remove(lhs_cmp)\n self.graph.add_edge(lhs_cmp, rxn_nodes[0], weight=weights[0], required_compounds=required_cmps_lhs,\n required_compound_costs=None)\n self.graph.add_edge(rxn_nodes[1], lhs_cmp, weight=0.0, required_compounds=None)\n # Add rhs aggregates and connect\n for rhs_cmp, rhs_type in zip([i.string() for i in reactants[1]],\n [i.name for i in reactant_types[1]]):\n if rhs_cmp not in self.graph:\n self.graph.add_node(rhs_cmp, type=rhs_type)\n required_cmps_rhs = [s.string() for s in reactants[1]]\n required_cmps_rhs.remove(rhs_cmp)\n self.graph.add_edge(rhs_cmp, rxn_nodes[1], weight=weights[1], required_compounds=required_cmps_rhs,\n required_compound_costs=None)\n self.graph.add_edge(rxn_nodes[0], rhs_cmp, weight=0.0, required_compounds=None)\n\n # # # Loop over reaction nodes to add required compounds info to downwards edges; might be unnecessary\n node_index = 1\n for node in rxn_nodes:\n for key in self.graph[node].keys():\n self.graph.edges[node, key]['required_compounds'] = \\\n self.graph.edges[key, rxn_nodes[node_index]]['required_compounds']\n node_index -= 1","def _generate_loss_bonus(self, angles: tf.Variable) -> tf.Tensor:\n # Get the operator for all the cx gates\n cx = tf.constant(self.circuit_model.get_cnot_operator())\n # Start from identity to iterate\n circ = tf.complex(tf.eye(2 ** self.circuit_model.nqubit, dtype=tf.float64), tf.constant(0, dtype=tf.float64))\n for layer in range(self.circuit_model.layers - 1, -1, -1):\n start_angle = 3 * layer * self.circuit_model.nqubit\n rot_u3 = self._r_u3(angles[start_angle:start_angle + 3])\n for qb in range(1, self.circuit_model.nqubit):\n rot_u3 = tf.tensordot(self._r_u3(angles[start_angle + 3 * qb: start_angle + 3 * qb + 3]),\n rot_u3, axes=0)\n\n rot_u3 = self._fix_dimension(rot_u3)\n circ = tf.matmul(circ, cx)\n circ = tf.matmul(circ, rot_u3)\n\n loss = self._get_norm(circ)\n\n return loss","def incr_registers(self):\n pass","def _dcg_idcg(relevance_scores, cg_discount):\n # cg_discount is safe\n dcg_k = relevance_scores / cg_discount\n return tf.reduce_sum(dcg_k)","def coordnav(self,dx,dy,dth): \n self.cg_ant = np.array(self.cg)\n self.coord[0] = self.coord[0] - self.cg[0]\n self.coord[1] = self.coord[1] - self.cg[1] \n self.Rz = rotation.matrix([0,0,1],dth)\n self.coord = np.dot(self.Rz,self.coord)\n \n self.coord[0] = self.coord[0] + self.cg[0] + dx\n self.coord[1] = self.coord[1] + self.cg[1] + dy \n \n self.px = self.coord[:,self.px_index]\n self.Bx = self.px-self.cg \n self.basex = self.Bx/math.sqrt(np.dot(self.Bx,self.Bx))","def gelu(x):\n cdf = 0.5 * (1.0 + tf.tanh(\n (np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))\n return x * cdf","def keypress(self, event):\n stepsize = 0.15 # pixels, i.e. 0.05 arcsec\n if event.key == 'right':\n if self.ccd == 2:\n self.shift_crpix1 -= stepsize\n else:\n self.shift_crpix2 += stepsize\n elif event.key == 'left':\n if self.ccd == 2:\n self.shift_crpix1 += stepsize\n else:\n self.shift_crpix2 -= stepsize\n elif event.key == ']':\n if self.ccd == 2:\n self.shift_crpix1 -= 5*stepsize\n else:\n self.shift_crpix2 += 5*stepsize\n elif event.key == '[':\n if self.ccd == 2:\n self.shift_crpix1 += 5*stepsize\n else:\n self.shift_crpix2 -= 5*stepsize\n elif event.key == 'up':\n if self.ccd == 2:\n self.shift_crpix2 += stepsize\n else:\n self.shift_crpix1 += stepsize\n elif event.key == 'down':\n if self.ccd == 2:\n self.shift_crpix2 -= stepsize\n else:\n self.shift_crpix1 -= stepsize\n elif event.key == \"'\":\n if self.ccd == 2:\n self.shift_crpix2 += 5*stepsize\n else:\n self.shift_crpix1 += 5*stepsize\n elif event.key == '/':\n if self.ccd == 2:\n self.shift_crpix2 -= 5*stepsize\n else:\n self.shift_crpix1 -= 5*stepsize\n elif event.key == '1':\n self.shift_cd1_1 += 1e-8\n elif event.key == '2':\n self.shift_cd1_1 -= 1e-8\n elif event.key == '3':\n self.shift_cd1_2 += 1e-8\n elif event.key == '4':\n self.shift_cd1_2 -= 1e-8\n elif event.key == '5':\n self.shift_cd2_1 += 1e-8\n elif event.key == '6':\n self.shift_cd2_1 -= 1e-8\n elif event.key == '7':\n self.shift_cd2_2 += 2e-8\n elif event.key == '8':\n self.shift_cd2_2 -= 2e-8\n elif event.key == 'r': # Reset\n self.shift_crpix1 = 0.0\n self.shift_crpix2 = 0.0\n self.shift_cd1_1 = 0.0\n self.shift_cd1_2 = 0.0\n self.shift_cd2_1 = 0.0\n self.shift_cd2_2 = 0.0\n elif event.key == 'o': # OK, field does not need fix\n self.mark_done()\n elif event.key == 'w': # Write WCS\n self.write() # Save the results to a csv file\n self.mark_done()\n # Now update the plot for the slight change in WCS parameters\n self.update()","def __radd__(self, gg: Ggplot) -> Ggplot:\n gg += self.to_layer() # Add layer\n return gg","def get_cdr3(dcr, headers):\n\n # NB: A productively rearranged receptor does not necessarily mean that it is the working receptor used in a cell!\n out_data = coll.defaultdict()\n for field in headers:\n out_data[field] = ''\n\n out_data['decombinator_id'] = dcr\n out_data['rev_comp'] = 'F'\n\n # CDR3-defining positions\n start_cdr3 = 0\n end_cdr3 = 0\n\n # 1. Rebuild whole nucleotide sequence from Decombinator assignment\n classifier_elements = dcr.split(', ')\n v = int(classifier_elements[0])\n j = int(classifier_elements[1])\n vdel = int(classifier_elements[2])\n jdel = int(classifier_elements[3])\n ins_nt = classifier_elements[4]\n\n # TODO remove 'split' if and when the gene names in the tag files get properly adjusted to be consistent\n out_data['v_call'] = v_names[v].split('*')[0]\n out_data['j_call'] = j_names[j].split('*')[0]\n\n if vdel == 0:\n v_used = v_regions[v]\n else:\n v_used = v_regions[v][:-vdel]\n\n j_used = j_regions[j][jdel:]\n\n out_data['sequence'] = ''.join([v_used, ins_nt, j_used])\n\n # 2. Translate\n out_data['sequence_aa'] = str(Seq(out_data['sequence']).translate())\n\n # 3. Check whether whole rearrangement is in frame\n if (len(out_data['sequence']) - 1) % 3 == 0:\n out_data['productive'] = 'T'\n out_data['vj_in_frame'] = 'T'\n else:\n out_data['productive'] = 'F'\n out_data['vj_in_frame'] = 'F'\n\n # 4. Check for stop codons in the in-frame rearrangements\n if '*' in out_data['sequence_aa']:\n out_data['productive'] = 'F'\n out_data['stop_codon'] = 'T'\n else:\n out_data['stop_codon'] = 'F'\n\n # 5. Check for conserved cysteine in the V gene\n if out_data['sequence_aa'][v_translate_position[v] - 1] == v_translate_residue[v]:\n start_cdr3 = v_translate_position[v] - 1\n out_data['conserved_c'] = 'T'\n else:\n out_data['productive'] = 'F'\n out_data['conserved_c'] = 'F'\n\n # 5.5 Having found conserved cysteine, only need look downstream to find other end of CDR3\n downstream_c = out_data['sequence_aa'][start_cdr3:]\n\n # 6. Check for presence of FGXG motif (or equivalent)\n site = downstream_c[j_translate_position[j]:j_translate_position[j] + 4]\n\n if re.findall(j_translate_residue[j], site):\n end_cdr3 = len(downstream_c) + j_translate_position[j] + start_cdr3 + 1\n out_data['conserved_f'] = 'T'\n else:\n out_data['productive'] = 'F'\n out_data['conserved_f'] = 'F'\n\n if out_data['productive'] == 'T':\n out_data['junction_aa'] = out_data['sequence_aa'][start_cdr3:end_cdr3]\n out_data['junction'] = out_data['sequence'][start_cdr3 * 3:3 * end_cdr3]\n out_data['cdr1_aa'] = v_cdr1[v]\n out_data['cdr2_aa'] = v_cdr2[v]\n\n return out_data","def gelu(x):\n cdf = 0.5 * (1.0 + tf.tanh(\n (np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))\n return x * cdf","def _cond_gccovgc(signals, x_idx, y_idx, ind_tx, conditional=True):\n d_x, d_y = signals[x_idx, :], signals[y_idx, :]\n n_lags, n_dt = ind_tx.shape\n gc = np.empty(3, dtype=d_x.dtype, order='C')\n # define z past\n z_indices = np.array([k for k in range(signals.shape[0]) if k not in [x_idx, y_idx]])\n d_z = signals[z_indices, :] # other roi selection\n rsh = int(len(z_indices) * (n_lags - 1)) # roi_range = 150-2 = 148; n_lags-1 = 5 --> rsh = 740\n\n x = d_x[ind_tx]\n y = d_y[ind_tx]\n # temporal selection\n x_pres, x_past = x[0], x[1:]\n y_pres, y_past = y[0], y[1:]\n xy_past = np.concatenate((x[1:], y[1:]), axis=0)\n # conditional granger causality case\n if conditional:\n # condition by the past of every other possible sources\n z_past = d_z[..., ind_tx[1:, :]] # (lag_past, dt) selection\n z_past = z_past.reshape(rsh, n_dt)\n # cat with past\n yz_past = np.concatenate((y_past, z_past), axis=0)\n xz_past = np.concatenate((x_past, z_past), axis=0)\n xyz_past = np.concatenate((xy_past, z_past), axis=0)\n else:\n yz_past, xz_past, xyz_past = y_past, x_past, xy_past\n\n # copnorm over the last axis (avoid copnorming several times)\n x_pres = copnorm_nd(x_pres, axis=-1)\n x_pres = np.expand_dims(x_pres, 0)\n x_past = copnorm_nd(x_past, axis=-1)\n y_pres = copnorm_nd(y_pres, axis=-1)\n y_pres = np.expand_dims(y_pres, 0)\n y_past = copnorm_nd(y_past, axis=-1)\n yz_past = copnorm_nd(yz_past, axis=-1)\n xz_past = copnorm_nd(xz_past, axis=-1)\n xyz_past = copnorm_nd(xyz_past, axis=-1)\n\n # -----------------------------------------------------------------\n # Granger Causality measures\n # -----------------------------------------------------------------\n gc[0] = cmi_nd_ggg(y_pres, x_past, yz_past)\n # gc(pairs(:,2) -> pairs(:,1))\n gc[1] = cmi_nd_ggg(x_pres, y_past, xz_past)\n # gc(pairs(:,2) . pairs(:,1))\n gc[2] = cmi_nd_ggg(x_pres, y_pres, xyz_past)\n return gc","def globalphase_compiler(self, gate, args):\n pass","def globalphase_compiler(self, gate, args):\n pass","def cvChin(ctrlName, r=1):\r\n # create a simple circle curve:\r\n curve = cmds.curve(n=ctrlName, d=3, p=[(0, 0.8*r, -0.5*r), (0, 0.9*r, -0.7*r), (0, 0, -0.5*r), (0, -0.8*r, -0.7*r), (0, -0.8*r, 1.4*r), (0, -0.3*r, 1.3*r), (0, 0, 1.2*r), (0, 0, 0), (0, 0.8*r, -0.3*r), (0, 0.8*r, -0.5*r)] )\r\n # rename curveShape:\r\n renameShape([curve])\r\n return curve","def dgdx(self, X):\n \n return 2*(X[0]) - 2","def addX(self,name):\n return self._addVar(name,self._xNames)","def gelu(x):\n cdf = 0.5 * (1.0 + torch.tanh(\n (np.sqrt(2 / np.pi) * (x + 0.044715 * np.power(x, 3)))))\n return x * cdf","def cX(cb):\n allNodes = b.allNodes(group=cb)\n for n in allNodes:\n allNodes = allNodes + cX(n)\n\n return allNodes","def add_rand_circ() -> int:\n r = randint(10, 100)\n x = randint(r, WIDTH - r)\n y = randint(r, HEIGHT - r)\n vx = randint(-10, 10)\n vy = randint(-10, 10)\n color = COLORS[randint(0, len(COLORS) - 1)]\n add_circ(x, y, r, vx, vy, color, int(100 / r))\n return 0","def test_special_XYX(self, angexp):\n a, b, c, d = angexp[0]\n exp = {(\"rx\", \"ry\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\n tgt = np.exp(1j * d) * RXGate(b).to_matrix() @ RYGate(a).to_matrix() @ RXGate(c).to_matrix()\n self.check_oneq_special_cases(tgt, \"XYX\", exp)","def grads(self, inputs):","def add(self, params):\n if len(params) < 2:\n return\n x = self.reg_dct[params[0]]\n y = self.reg_dct[params[1]]\n self.reg_dct[params[0]] = (x + y) % (2** 32)","def __iadd__(self, d_value: float):\n self.increment_value(d_value)\n return self","def double_add(self, x):\n self.add(x*2)","def attraction_g(next_q, q, d, a):\n\n if a == 0:\n if next_q == 0:\n xi_D = 8\n else:\n xi_D = 1\n\n elif a == 1:\n xi_D = 1\n\n elif a == 2:\n if next_q == 0:\n xi_D = 1\n else:\n xi_D = 3\n\n elif a == 3:\n if next_q == 0:\n xi_D = 1\n else:\n xi_D = 2\n\n else:\n if next_q == 0:\n xi_D = 1\n else:\n xi_D = 4\n\n dqq = 0\n if next_q == 1 and q == 0:\n if d[3] == 1:\n dqq = 1\n elif np.sum(d[6:]) == 3:\n dqq = 1\n elif next_q == 0 and q == 1:\n if d[5] == 1:\n dqq = 1\n elif np.sum(d[6:]) == 0:\n dqq = 1\n\n return xi_D + dqq","def dRdE_magnetic(E, m_x, mu_x, target, vlag=232.0, sigmav=156.0, vesc=544.0):\n \n A = Avals[target]\n \n #See Eq. 62 of https://arxiv.org/pdf/1307.5955.pdf, but note\n #that we're using some different normalisations for the operators\n #so there are some extra factors of m_x and m_p lurking around...\n \n amu = 931.5e3 # keV\n q1 = np.sqrt(2*A*amu*E) #Recoil momentum in keV\n \n alpha = 0.007297\n e = np.sqrt(4*np.pi*alpha)\n m_p = 0.9315\n \n #Proton and neutron g-factors\n gp = 5.59\n gn = -3.83\n \n #Bohr Magneton\n #Tesla = 194.6*eV**2 # Tesla in natural units (with e = sqrt(4 pi alpha))\n #muB = 5.7883818e-5*eV/Tesla # Bohr magneton\n mu_B = 297.45 #GeV^-1 (in natural units (with e = sqrt(4 pi alpha)))\n\n cp = [E*0.0 for i in range(11)]\n cn = [E*0.0 for i in range(11)]\n \n #Operator 1\n cp[0] = e*(mu_x*mu_B)/(2.0*m_x)\n \n #Operator 5\n cp[4] = 2*e*(mu_x*mu_B)*m_p/(q1*1e-6)**2\n \n #Operator 4\n cp[3] = gp*e*(mu_x*mu_B)/m_p\n cn[3] = gn*e*(mu_x*mu_B)/m_p\n \n #Operator 6\n cp[5] = -gp*e*(mu_x*mu_B)*m_p/(q1*1e-6)**2\n cn[5] = -gn*e*(mu_x*mu_B)*m_p/(q1*1e-6)**2\n\n return dRdE_NREFT(E, m_x, cp, cn, target, vlag, sigmav, vesc)","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def _add_grad(self, coords:torch.tensor, trust:torch.tensor, \n update:torch.tensor ) -> torch.tensor:\n # view as to avoid deprecated point wise semantics\n step = trust.reshape(-1,1,1)*update.view_as(coords)\n \n coords.data.add_(step)\n return trust #* cutoff_multiplier","def increase_radius(self, character):\n character.bombradius += 1","def _add_grover_step_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n _add_2_bit_oracle_without_ancilla_1_0(qc, register) # Oracle\n add_grover_reflection_no_ancilla(qc, register) # Reflection","def xr_add_cyclic(da, coord):\n from cartopy.util import add_cyclic_point\n\n cyclic_data, cyclic_coord = add_cyclic_point(da.values, coord=da[coord])\n\n coords = da.coords.to_dataset()\n coords[coord] = cyclic_coord\n return xr.DataArray(\n cyclic_data,\n dims=da.dims,\n coords=coords.coords,\n attrs=da.attrs,\n encoding=da.encoding,\n )","def cg(self):\n A = self.clAlphaT / self.clAlphaWF\n B = (1 - self.downwashGradW)\n C = (self.surfaceT * self.tlH) / (self.surfaceW * self.cMACW)\n sm = 0.05 * self.cMACW # static margin, approximated as 5% of aircraft MAC\n return self.ac + A * B * C * self.speedRatio**2 - sm"],"string":"[\n \"def cxr(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def _gcl(x, r, D, Ia, Ct):\\n\\n Area = np.pi * D ** 2.0 / 4.0\\n m = 1.0 / (np.sqrt(1.0 - Ct))\\n k = np.sqrt((m + 1.0) / 2.0)\\n\\n a1 = 0.435449861 # empirically determined\\n a2 = 0.797853685\\n a3 = -0.124807893\\n a4 = 0.136821858\\n b1 = 15.6298\\n b2 = 1.0\\n R96 = a1 * (np.exp(a2 * Ct * Ct + a3 * Ct + a4)) * (b1 * Ia + b2) * D\\n\\n x0 = (9.6 * D) / ((2.0 * R96 / (k * D)) ** 3.0 - 1.0)\\n term1 = (k * D / 2.0) ** (5.0 / 2.0)\\n term2 = (105.0 / (2.0 * np.pi)) ** (-0.5)\\n term3 = (Ct * Area * x0) ** (-5.0 / 6.0)\\n c1 = term1 * term2 * term3\\n # c45=3*(c1) ** 2\\n\\n term10 = 0.1111 # * WindSpeed # U/9.0\\n term20 = (Ct * Area * (x + x0) ** (-2.0)) ** (1.0 / 3.0)\\n term310 = (r ** (3.0 / 2.0))\\n term320 = (3.0 * c1 * c1 * Ct * Area * (x + x0)) ** (-0.5)\\n term30 = term310 * term320\\n term40 = ((35.0 / (2.0 * np.pi)) ** (3.0 / 10.0)) * \\\\\\n (3.0 * c1 * c1) ** (-1.0 / 5.0)\\n DU1 = -term10 * term20 * (term30 - term40) ** 2.0\\n\\n DU = DU1 # + w2 * DU2\\n Rw = ((105 * c1 ** 2.0 / (2 * np.pi)) ** (1. / 5.)) * \\\\\\n (Ct * Area * (x + x0)) ** (1. / 3.)\\n return DU, Rw\",\n \"def _gyration(self, x, y, v, c):\\n xy = self._mobius_add(x, y, c)\\n yv = self._mobius_add(y, v, c)\\n xyv = self._mobius_add(x, yv, c)\\n return self._mobius_add(-xy, xyv, c)\",\n \"def DEX(self, *_):\\n self._dec_or_inc_register('X', increment=False)\",\n \"def gate(self):\\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)\",\n \"def _acc_grads(self, x, label):\\n ##\\n # Forward propagation\\n z1 = self.params.W.dot(x) + self.params.b1\\n h = tanh(z1)\\n z2 = np.dot(self.params.U, h) + self.params.b2\\n y_hat = softmax(z2)\\n \\n y = make_onehot(label, self.outputsize)\\n d2 = y_hat - y\\n self.grads.b2 += d2\\n self.grads.U += np.outer(d2, h) + self.lreg * self.params.U\\n d1 = np.dot(self.params.U.T, d2) * tanhd(z1) \\n \\n self.grads.W += np.outer(d1, x) + self.lreg * self.params.W\\n self.grads.b1 += d1\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def add_corridor_constraint(self,seg,r,weight=1.0):\\n\\n constraint_type = \\\"cylinder\\\"\\n params = dict()\\n params['x1'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg],\\n self.qr_polytraj.waypoints['y'][0,seg],\\n self.qr_polytraj.waypoints['z'][0,seg]])\\n params['x2'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg+1],\\n self.qr_polytraj.waypoints['y'][0,seg+1],\\n self.qr_polytraj.waypoints['z'][0,seg+1]])\\n params['der'] = 0\\n params['l'] = r # Give the same radius buffer on the end caps\\n params['r'] = r\\n params['weight'] = weight\\n params['keep_out'] = False\\n params['active_seg'] = seg\\n\\n\\n self.qr_polytraj.add_constraint(constraint_type,params,dynamic_weighting=False,sum_func=False)\",\n \"def build_glyCB(self, gCBd: Dihedron): # -> None:\\n ...\",\n \"def cs_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def acc_drag(U,comp):\\n def drag_prefix(U):\\n return -drag_C*rho_A(U)*V_A(U)\\n if comp == 'x':\\n return drag_prefix(U)*(U[3]+U[1]*dTheta)\\n elif comp == 'y':\\n return drag_prefix(U)*(U[4]-U[0]*dTheta)\\n elif comp =='z':\\n return drag_prefix(U)*(U[5])\",\n \"def cyclic_merit_lag(x,*args):\\n CS = args[0]\\n print \\\"rindex\\\",CS.rindex\\n ht = get_ht(x,CS.rindex)\\n hf = time2freq(ht)\\n CS.hf = hf\\n CS.ht = ht\\n cs_model,csplus,csminus,phases = make_model_cs(hf,CS.s0,CS.bw,CS.ref_freq)\\n merit = 2*(np.abs(cs_model[:,1:] - CS.cs[:,1:])**2).sum() #ignore zeroth harmonic (dc term)\\n \\n # the objval list keeps track of how the convergence is going\\n CS.objval.append(merit)\\n \\n #gradient_lag\\n diff = cs_model - CS.cs #model - data\\n cc1 = cs2cc(diff * csminus)\\n \\n# original c code for reference:\\n# for (ilag=0; ilag<cc1.nlag; ilag++) {\\n# gradient->data[ilag] = 0.0 + I * 0.0;\\n# int lag = (ilag<=cc1.nlag/2) ? ilag : ilag-cc1.nlag;\\n# tau = (double)lag * (double)cs->nchan /\\n# ( (double)cc1.nlag * cc1.bw*1.e6 );\\n# for (ih=1; ih<cc1.nharm; ih++) {\\n# phs = M_PI * tau * (double)ih * cc1.ref_freq;\\n# phasor = cos(phs)+I*sin(phs);\\n# fftwf_complex *ccval = get_cc(&cc1,ih,ip,ilag);\\n# gradient->data[ilag] += 4.0 * (*ccval) * phasor\\n# * conj(s0->data[ih]) / (float)cs->nchan;\\n# }\\n# }\\n\\n #we reuse phases and csminus, csplus from the make_model_cs call\\n\\n phasors = np.exp(1j*phases)\\n cs0 = np.repeat(CS.s0[np.newaxis,:],CS.nlag,axis=0) #filter2cs\\n grad = 4.0 * cc1 * phasors * np.conj(cs0) / CS.nchan\\n grad = grad[:,1:].sum(1) # sum over all harmonics to get function of lag\\n \\n #conjugate(res)\\n #calc positive shear\\n #multiply\\n #cs2cc\\n cc2 = cs2cc(np.conj(diff) * csplus)\\n grad2 = 4.0 * cc2 * np.conj(phasors) * cs0 / CS.nchan\\n \\n grad = grad + grad2[:,1:].sum(1)\\n CS.grad = grad[:]\\n CS.model = cs_model[:]\\n\\n if CS.iprint:\\n print \\\"merit= %.7e grad= %.7e\\\" % (merit,(np.abs(grad)**2).sum())\\n \\n if CS.make_plots:\\n if CS.niter % CS.plot_every == 0:\\n CS.plotCurrentSolution()\\n \\n \\n \\n grad = get_params(grad, CS.rindex)\\n CS.niter += 1\\n \\n return merit,grad\",\n \"def grad(self, crd):\\n grad = np.zeros((2, *crd.shape), dtype=float)\\n grad[0, :, :] = 2.*crd\\n grad[1, :, :] = 2.*(crd-1)\\n return grad\",\n \"def DR(R,Pc):\\n return r1*R*(K1**B1/(K1**B1 + (A/R)**B1))*(S/(S + R*Pc + Pc)) \\\\\\n - gwt*A - r2*R*(K2**B2/(K2**B2 + (A)**B2))*(S/(S + R*Pc + Pc) ) \\\\\\n *(R*M)/(K3 + R*M) + R*gc\",\n \"def dcx(self, addr):\\n\\n self.reg.idx = self.reg.idx.inc(-1)\\n self.reg.zerox_flag = self.reg.idx.eq_zero()\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def CX(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)\",\n \"def test_append_dangling_gate(self, circuit):\\n match = (\\n r\\\"Number of wire IDs \\\\(2\\\\) must match the number of wires connected to the gate \\\\(1\\\\).\\\"\\n )\\n gate = jet.GateFactory.create(\\\"H\\\")\\n with pytest.raises(ValueError, match=match):\\n circuit.append_gate(gate, wire_ids=[0, 1])\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def add_cd_samples(self): \\n \\n if self.num_hidden == 0:\\n \\n (self.p_xi_given_x_, self.gibbs_samples), self.gibbs_updates =\\\\\\n theano.scan(self.gibbs_step_fully_visible, n_steps = self.gibbs_steps)\\n \\n if self.num_hidden > 0:\\n \\n if \\\"PCD\\\" in self.algorithm:\\n init_chain = self.persistent_gibbs\\n else:\\n # positive phase\\n _, _, hid_sample = self.get_h_given_v_samples(self.x)\\n\\n init_chain = hid_sample\\n \\n (\\n [\\n vis_inputs,\\n vis_outputs,\\n vis_samples,\\n hid_inputs,\\n hid_means,\\n hid_samples\\n ],\\n updates\\n ) = theano.scan(\\n self.gibbs_step_rbm_hid,\\n outputs_info=[None, None, None, None, None, init_chain],\\n n_steps= self.gibbs_steps)\\n \\n self.updates.update(updates)\\n \\n self.hid_samples = hid_samples[-1]\\n \\n self.rbm_cd_samples = theano.gradient.disconnected_grad(vis_samples[-1])\\n \\n self.rbm_vis_outputs = theano.gradient.disconnected_grad(vis_outputs[-1])\",\n \"def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def cxcy_to_gcxgcy(cxcy, priors_cxcy):\\n\\n # The 10 and 5 below are referred to as 'variances' in the original Caffe repo, completely empirical\\n # They are for some sort of numerical conditioning, for 'scaling the localization gradient'\\n # See https://github.com/weiliu89/caffe/issues/155\\n return torch.cat([(cxcy[:, :2] - priors_cxcy[:, :2]) / (priors_cxcy[:, 2:] / 10), # g_c_x, g_c_y\\n torch.log(cxcy[:, 2:] / priors_cxcy[:, 2:]) * 5], 1) # g_w, g_h\",\n \"def Rgb_add(c1,c2):\\n r = c1.r + c2.r\\n r = max(0, min(1, r))\\n\\n g = c1.g + c2.g\\n g = max(0, min(1, g))\\n\\n b = c1.b + c2.b\\n b = max(0, min(1, b))\\n return Rgb(r,g,b)\",\n \"def ccx(self, q0, q1, q2, ctrl=None):\\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\\n return self\",\n \"def gru(params, h, x):\\n bfg = 0.5\\n hx = np.concatenate([h, x], axis=0)\\n ru = sigmoid(np.dot(params['wRUHX'], hx) + params['bRU'])\\n r, u = np.split(ru, 2, axis=0)\\n rhx = np.concatenate([r * h, x])\\n c = np.tanh(np.dot(params['wCHX'], rhx) + params['bC'] + bfg)\\n return u * h + (1.0 - u) * c\",\n \"def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def dacc(self, gl, gr, c, phi_l, phi_r, psi_u, psi_d):\\n logger.debug('[START] PID[%s] dAcc skeleton', PID)\\n # Step 1 : Computing Local Intermediate Values\\n gt = Segment([None] * self.__nb_segs)\\n i = 0\\n for (start, offset) in \\\\\\n self.__global_index[self.__start_index: self.__start_index + self.__nb_segs]:\\n seg = Segment(self.__content[start:start + offset])\\n logger.debug('[START] PID[%s] dacc_path from %s to %s', PID, start, start + offset)\\n if seg.has_critical():\\n gt[i] = seg.dacc_path(phi_l, phi_r, psi_u)\\n else:\\n gt[i] = TaggedValue(seg[0].get_value(), \\\"L\\\")\\n logger.debug('[END] PID[%s] dacc_path from %s to %s', PID, start, start + offset)\\n i = i + 1\\n # Step 2 : Gather Local Results\\n self.__gather_local_result(gt, i, TAG_COMM_DACC_1)\\n # Step 3 : Global Downward Accumulation\\n par.at_root(lambda: logger.debug('[START] PID[%s] dacc_global', PID))\\n gt2 = (gt.dacc_global(psi_d, c) if PID == 0 else None)\\n par.at_root(lambda: logger.debug('[END] PID[%s] dacc_global', PID))\\n # Step 4 : Distributing Global Result\\n gt2 = self.__distribute_global_result(gt2, TAG_COMM_DACC_2)\\n # Step 5 : Local Downward Accumulation\\n content = SList([None] * self.__content.length())\\n for i in range(len(self.__global_index[self.__start_index: self.__start_index +\\n self.__nb_segs])):\\n (start, offset) = self.__global_index[self.__start_index: self.__start_index +\\n self.__nb_segs][i]\\n logger.debug('[START] PID[%s] dacc_local from %s to %s', PID, start, start + offset)\\n content[start:start + offset] = \\\\\\n Segment(self.__content[start:start + offset]).dacc_local(gl, gr, gt2[i].get_value())\\n logger.debug('[END] PID[%s] dacc_local from %s to %s', PID, start, start + offset)\\n logger.debug('[END] PID[%s] dAcc skeleton', PID)\\n return PTree.init(self, content)\",\n \"def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\\n if q_args is None and c_args is None:\\n raise GateError(\\\"Gate needs at least one quantum argument or classical argument\\\")\\n if isinstance(gate, CompositeGate):\\n if mapping is None:\\n raise GateError(\\\"Must provide arguments mapping for composite gate inside a composite gate.\\\")\\n else:\\n inv_mappimg = dict()\\n for key, value in mapping.items():\\n inv_mappimg[value] = key\\n if gate is self:\\n gates = gate.copy.gates\\n else:\\n gates = gate.gates\\n for g in gates:\\n new_q_args = None\\n new_c_args = None\\n if g[1] is not None:\\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\\n if g[2] is not None:\\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\\n self.add_gate(gate=g[0], q_args=new_q_args,\\n c_args=new_c_args, params=g[3])\\n else:\\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\\n raise GateError(\\\"Gate must be either a CompositeGate or a string from: \\\"\\n \\\"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\\\")\\n if q_args is not None:\\n for q_arg in q_args:\\n if q_arg not in self.q_args:\\n self.add_q_arg(q_arg)\\n if c_args is not None:\\n for c_arg in c_args:\\n if c_arg not in self.c_args:\\n self.add_c_arg(c_arg)\\n if params is not None:\\n for param in params:\\n if param not in self.params:\\n self.add_param(param)\\n self._gates.append((gate, q_args, c_args, params))\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def __init__(self):\\n super().__init__(\\\"ccx\\\", 3, [])\",\n \"def glycosylate(self):\\n chid = self.chain.get()\\n sequon = self.sequon.get()\\n self.sequon_colors[sequon] = [.7, .1, 0]\\n key = self.sequon.get()\\n residue = self.myGlycosylator.get_residue(key)\\n #Build new glycan\\n if self.selected_glycan:\\n self.myGlycosylator.connect_topology['SELECTED'] = self.selected_glycan[1]\\n #build from current glycan\\n if key in self.original_glycans:\\n original_glycan = self.original_glycanMolecules[key].atom_group\\n r,t = self.original_glycans[key]\\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\\n else:\\n original_glycan = None\\n connect_tree = None \\n #Use current glycan\\n else:\\n original_glycan = self.original_glycanMolecules[key]\\n r,t = self.original_glycans[key]\\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\\n self.myGlycosylator.connect_topology['SELECTED'] = self.myGlycosylator.build_connect_topology(original_glycan) \\n original_glycan = original_glycan.atom_group\\n \\n segname = 'G'+key.split(',')[2]\\n glycan,bonds = self.myGlycosylator.glycosylate('SELECTED', \\n template_glycan_tree = connect_tree, \\n template_glycan = original_glycan,\\n link_residue=residue, link_patch = 'NGLB', chain = 'G', segname=segname)\\n new_glycan = glc.Molecule(key)\\n new_glycan.set_AtomGroup(glycan, bonds = bonds)\\n self.myGlycosylator.assign_patches(new_glycan)\\n self.linked_glycanMolecules[key] = new_glycan\\n self.linked_glycans[key] = [new_glycan.rootRes, new_glycan.interresidue_connectivity]\\n self.names.update(new_glycan.get_names())\\n # Update glycoprotein and sequon panels\\n self.draw_glycoprotein(chid)\\n self.draw_glycan(sequon)\",\n \"def btnCommand_CXPMGR(self, btn_name):\\n\\t\\tprint(\\\"Button {} is pressed.\\\".format(btn_name) )\\n\\n\\t\\tif btn_name == 'add':\\n\\n\\t\\t\\tpass\\n\\t\\telif btn_name == 'del':\\n\\t\\t\\tpass\\n\\t\\telif btn_name == 'prev':\\n\\t\\t\\tpass\\n\\t\\telif btn_name == 'next':\\n\\t\\t\\tpass\\n\\t\\telse:\\n\\t\\t\\tprint(\\\"ERROR, illegal button ID {} !!\\\".format(btn_name))\\n\\t\\t\\treturn\\n\\n\\t\\tpass\",\n \"def add_c_arg(self, c_arg):\\n self._c_args.append(c_arg)\\n self.add_decompostion(c_arg)\",\n \"def incr_operand(self):\\n pass\",\n \"def reapply(self, circ):\\n self._modifiers(circ.sdg(self.qargs[0]))\",\n \"def orbit_cross():\\n \\n # potential\\n ham = gp.Hamiltonian(gp.MilkyWayPotential(nucleus=dict(m=0), halo=dict(c=0.95, m=7E11), bulge=dict(m=4E9), disk=dict(m=5.5e10)))\\n gc_frame = coord.Galactocentric(galcen_distance=8*u.kpc, z_sun=0*u.pc)\\n \\n # orbital solution\\n pos = np.load('/home/ana/projects/GD1-DR2/data/gd1_orbit.npy')\\n phi1, phi2, d, pm1, pm2, vr = pos\\n\\n c = gc.GD1(phi1=phi1*u.deg, phi2=phi2*u.deg, distance=d*u.kpc, \\n pm_phi1_cosphi2=pm1*u.mas/u.yr,\\n pm_phi2=pm2*u.mas/u.yr,\\n radial_velocity=vr*u.km/u.s)\\n w0 = gd.PhaseSpacePosition(c.transform_to(gc_frame).cartesian)\\n \\n dt = 0.5 * u.Myr\\n n_steps = 250\\n fit_orbit = ham.integrate_orbit(w0, dt=dt, n_steps=120)\\n\\n # find gap 6D location at present\\n gap_phi0 = -40*u.deg\\n model_gd1 = fit_orbit.to_coord_frame(gc.GD1, galactocentric_frame=gc_frame)\\n gap_i = np.abs(model_gd1.phi1.wrap_at(180*u.deg) - gap_phi0).argmin()\\n gap_w0 = fit_orbit[gap_i]\\n \\n # gap orbit\\n t1 = 0*u.Myr\\n t2 = -1*u.Gyr\\n dt = -0.5\\n t = np.arange(t1.to(u.Myr).value, t2.to(u.Myr).value+dt, dt)\\n gap_orbit = ham.integrate_orbit(gap_w0, dt=dt, t1=t1, t2=t2)\\n \\n \\n # plot relative distances as a function of time\\n plt.close()\\n plt.figure(figsize=(9,5))\\n \\n lw = 3\\n\\n # show classicals\\n tcls = Table.read('../data/positions_classical.fits')\\n ra, dec, d, pmra, pmdec, vr = tcls['ra'], tcls['dec'], tcls['distance'], tcls['pmra'], tcls['pmdec'], tcls['vr']\\n cs = coord.ICRS(ra=ra, dec=dec, distance=d, pm_ra_cosdec=pmra, pm_dec=pmdec, radial_velocity=vr)\\n ws = gd.PhaseSpacePosition(cs.transform_to(gc_frame).cartesian)\\n satellite_orbit = ham.integrate_orbit(ws, dt=dt, t1=t1, t2=t2)\\n for e in range(len(tcls)):\\n if e==0:\\n label = 'Classical\\\\ndwarfs'\\n else:\\n label = ''\\n rel_distance = np.linalg.norm(gap_orbit.xyz - satellite_orbit.xyz[:,:,e], axis=0)*gap_orbit.xyz[0].unit\\n plt.plot(t, rel_distance, '-', color=mpl.cm.Reds(0.9), alpha=0.5, label=label, lw=lw)\\n \\n # show ultrafaints\\n tufd = Table.read('../data/positions_ufd.fits')\\n ra, dec, d, pmra, pmdec, vr = tufd['ra'], tufd['dec'], tufd['distance'], tufd['pmra'], tufd['pmdec'], tufd['vr']\\n cs = coord.ICRS(ra=ra, dec=dec, distance=d, pm_ra_cosdec=pmra, pm_dec=pmdec, radial_velocity=vr)\\n ws = gd.PhaseSpacePosition(cs.transform_to(gc_frame).cartesian)\\n satellite_orbit = ham.integrate_orbit(ws, dt=dt, t1=t1, t2=t2)\\n for e in range(len(tufd)):\\n if e==0:\\n label = 'Ultra-faint\\\\ndwarfs'\\n else:\\n label = ''\\n rel_distance = np.linalg.norm(gap_orbit.xyz - satellite_orbit.xyz[:,:,e], axis=0)*gap_orbit.xyz[0].unit\\n plt.plot(t, rel_distance, '-', color=mpl.cm.Reds(0.7), alpha=0.5, label=label, lw=lw)\\n \\n # show globulars\\n tgc = Table.read('../data/positions_globular.fits')\\n ra, dec, d, pmra, pmdec, vr = tgc['ra'], tgc['dec'], tgc['distance'], tgc['pmra'], tgc['pmdec'], tgc['vr']\\n cs = coord.ICRS(ra=ra, dec=dec, distance=d, pm_ra_cosdec=pmra, pm_dec=pmdec, radial_velocity=vr)\\n ws = gd.PhaseSpacePosition(cs.transform_to(gc_frame).cartesian)\\n satellite_orbit = ham.integrate_orbit(ws, dt=dt, t1=t1, t2=t2)\\n for e in range(len(tgc)):\\n if e==0:\\n label = 'Globular\\\\nclusters'\\n else:\\n label = ''\\n rel_distance = np.linalg.norm(gap_orbit.xyz - satellite_orbit.xyz[:,:,e], axis=0)*gap_orbit.xyz[0].unit\\n plt.plot(t, rel_distance, '-', color=mpl.cm.Reds(0.5), alpha=0.5, label=label, lw=lw)\\n\\n plt.plot(t, np.abs(gap_orbit.xyz[2]), '-', color=mpl.cm.Reds(0.3), alpha=0.5, label='Disk', lw=lw, zorder=0)\\n #plt.plot(t, np.sqrt(gap_orbit.xyz[0]**2 + gap_orbit.xyz[1]**2), 'r-', alpha=0.2)\\n\\n plt.ylim(0.1,200)\\n plt.gca().set_yscale('log')\\n \\n plt.legend(loc=2, fontsize='small', markerscale=2)\\n plt.xlabel('Time [Myr]')\\n plt.ylabel('Relative distance [kpc]')\\n \\n plt.tight_layout()\\n plt.savefig('../plots/satellite_distances.png', dpi=200)\\n plt.savefig('../paper/satellite_distances.pdf')\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def gelu_new(x):\\n cdf = 0.5 * (1.0 + tf.tanh((np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))\\n return x * cdf\",\n \"def cvBaseGuide(ctrlName, r=1):\\r\\n # create a simple circle curve:\\r\\n circle = cmds.circle(n=ctrlName, ch=True, o=True, nr=(0, 0, 1), d=3, s=8, radius=r)[0]\\r\\n radiusCtrl = cmds.circle(n=ctrlName+\\\"_radiusCtrl\\\", ch=True, o=True, nr=(0, 1, 0), d=3, s=8, radius=(r/4.0))[0]\\r\\n # rename curveShape:\\r\\n renameShape([circle, radiusCtrl])\\r\\n # configure system of limits and radius:\\r\\n cmds.setAttr(radiusCtrl+\\\".translateX\\\", r)\\r\\n cmds.parent(radiusCtrl, circle, relative=True)\\r\\n cmds.transformLimits(radiusCtrl, tx=(0.01, 1), etx=(True, False))\\r\\n setLockHide([radiusCtrl], ['ty', 'tz', 'rx', 'ry', 'rz', 'sx', 'sy', 'sz'])\\r\\n # find makeNurbCircle history of the circles:\\r\\n historyList = findHistory([circle, radiusCtrl], 'makeNurbCircle')\\r\\n circleHistory = historyList[0]\\r\\n radiusCtrlHistory = historyList[1]\\r\\n # rename and make a connection for circle:\\r\\n circleHistory = cmds.rename(circleHistory, circle+\\\"_makeNurbCircle\\\")\\r\\n cmds.connectAttr(radiusCtrl+\\\".tx\\\", circleHistory+\\\".radius\\\", force=True)\\r\\n radiusCtrlHistory = cmds.rename(radiusCtrlHistory, radiusCtrl+\\\"_makeNurbCircle\\\")\\r\\n # create a mutiplyDivide in order to automatisation the radius of the radiusCtrl:\\r\\n radiusCtrlMD = cmds.createNode('multiplyDivide', name=radiusCtrl+'_md')\\r\\n cmds.connectAttr(radiusCtrl+'.translateX', radiusCtrlMD+'.input1X', force=True)\\r\\n cmds.setAttr(radiusCtrlMD+'.input2X', 0.15)\\r\\n cmds.connectAttr(radiusCtrlMD+\\\".outputX\\\", radiusCtrlHistory+\\\".radius\\\", force=True)\\r\\n # colorize curveShapes:\\r\\n colorShape([circle, radiusCtrl], 'yellow')\\r\\n cmds.select(clear=True)\\r\\n return [circle, radiusCtrl]\",\n \"def rrdb(x):\\n h = dense_block(x)\\n h = dense_block(h)\\n h = dense_block(h)\\n h = tf.keras.layers.Lambda(lambda x: x * 0.2)(h)\\n out = tf.keras.layers.Add()([h, x])\\n return out\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def add_gates(self, num_gates_to_add):\\n pass\",\n \"def relay_tagged(c, x, tag):\\n assert tag.is_constant(int)\\n rtag = get_union_ctr(tag.value, None)\\n return rtag(c.ref(x))\",\n \"def GachaCraftNodeExcelAddGP1110(builder, GP1110):\\n return AddGP1110(builder, GP1110)\",\n \"def bcc(self, arg):\\n\\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def add_operators(self, run):\\n if self.rate_variation:\\n # UpDownOperator to scale the Gamma distribution for this model's\\n # feature rates\\n updown = ET.SubElement(run, \\\"operator\\\", {\\\"id\\\":\\\"featureClockRateGammaUpDown:%s\\\" % self.name, \\\"spec\\\":\\\"UpDownOperator\\\", \\\"scaleFactor\\\":\\\"0.5\\\",\\\"weight\\\":\\\"0.3\\\"})\\n ET.SubElement(updown, \\\"parameter\\\", {\\\"idref\\\":\\\"featureClockRateGammaShape:%s\\\" % self.name, \\\"name\\\":\\\"up\\\"})\\n ET.SubElement(updown, \\\"parameter\\\", {\\\"idref\\\":\\\"featureClockRateGammaScale:%s\\\" % self.name, \\\"name\\\":\\\"down\\\"})\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def acumula_x1(self, x1, rodada):\\n self.x1[rodada].append(x1)\",\n \"def gcxgcy_to_cxcy(gcxgcy, priors_cxcy):\\n\\n return torch.cat([gcxgcy[:, :2] * priors_cxcy[:, 2:] / 10 + priors_cxcy[:, :2], # c_x, c_y\\n torch.exp(gcxgcy[:, 2:] / 5) * priors_cxcy[:, 2:]], 1) # w, h\",\n \"def draw_C(self, frame):\\n c = self.get_real_leg()\\n cv2.circle(\\n frame,\\n (\\n Utils.ConvertX(c.x),\\n Utils.ConvertY(c.y)\\n ),\\n 8,\\n color=Utils.blue,\\n thickness=-1\\n )\",\n \"def addFCSPoint(self, dxpos, dypos, dzpos=None):\\n prefix = \\\"/cli:python /app:fcs /cmd:add\\\"\\n dx = \\\"/xpos:\\\" + `int(dxpos)` \\n dy = \\\"/ypos:\\\" + `int(dypos)`\\n if dzpos is None:\\n dz = \\\"/zpos:0\\\"\\n else:\\n dz = \\\"/zpos:\\\"+dzpos\\n \\n \\n cmd = \\\" \\\".join((prefix,dx,dy,dz))\\n #print \\\"FCS command string\\\"\\n #print cmd\\n self.sendCMDstring(cmd)\",\n \"def MiyamotoNagaiAccel(self, M, rd, r):\\n R = np.sqrt(r[0]**2 + r[1]**2) #Finding magnitude of x and y compnets\\n zd = rd/5. #Calculating \\\"zd\\\"\\n B = rd + np.sqrt(r[2]**2 + zd**2) #Calclating \\\"B\\\"\\n zstuff = 1/np.sqrt(r[2]**2 + zd**2) #Calculating stuff that only appears in z componet\\n MNa = -self.G*M/(R**2+B**2)**1.5 * r * np.array([1,1,zstuff]) #Putting it all together\\n\\n return MNa\",\n \"def addBond(self, **kwds):\\n print kwds\\n self.MagCell.addBond(**kwds)\",\n \"def push(self, dlr):\\n print(f\\\"{self.name}'s {dlr} matched the dealers hand, push\\\")\\n self.chips += self.bet\\n self.lastbet = self.bet\\n self.bet = 0\",\n \"def cmd_dgaus():\\n cmds = []\\n cmds.append(\\\"r_m[0.0,-1,1]\\\")\\n cmds.append(\\\"r_s[1.5,0,10]\\\")\\n cmds.append('Gaussian::gaus_c(x,r_m,r_s)')\\n cmds.append(\\\"rt_m[0.0,-1,1]\\\")\\n cmds.append(\\\"rt_s[3,0,10]\\\")\\n cmds.append('Gaussian::gaus_t(x,rt_m,rt_s)')\\n cmds.append(\\\"f[0.85]\\\") # fraction of core\\n cmds.append(\\\"SUM::res(f*gaus_c,gaus_t)\\\")\\n return cmds\",\n \"def _append_cx(self, i, j):\\n\\n if not 0 <= i < self.num_qubits or not 0 <= j < self.num_qubits:\\n raise QiskitError(\\\"CX qubits are out of bounds.\\\")\\n self.linear[j] = (self.linear[i] + self.linear[j]) % 2\\n self.shift[j] = (self.shift[i] + self.shift[j]) % 2\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def dX_gene_reg_fn(x, t, topology, params):\\n\\tparents = topology.parents\\n\\ttarget = topology.target\\n\\tinteractions = topology.interactions\\n\\n\\tbase_synth = params[0]\\n\\tbase_degr = params[1]\\n\\n\\t# Add basal synthesis and basal degradation terms\\n\\tdX = base_synth - x[target] * base_degr\\n\\n\\t# Add contributions from each edge\\n\\tfor i in range(len(parents)):\\n\\t\\tp = parents[i]\\n\\t\\tinter = interactions[i]\\n\\n\\t\\tj = 2 + i*3\\n\\t\\tb = params[ j ] \\t # Interaction 'Strength'\\n\\t\\tk = params[ j + 1 ] # Hill fn parameter (theta)\\n\\t\\tm = params[ j + 2 ] # Hill fn parameter (m)\\n\\n\\t\\t# Value of parent for all t\\n\\t\\tparent_val = x[p]\\n\\n\\t\\tif inter == 0:\\n\\t\\t\\tdX += (b * parent_val**m) / (parent_val**m + k**m)\\n\\t\\telif inter == 1:\\n\\t\\t\\tdX += b / (1 + (parent_val/k)**m)\\n\\t\\n\\treturn dX\",\n \"def gcl(rel_pos, c_t, D, ti):\\n x = rel_pos[:, 0]\\n r = np.sqrt(rel_pos[:, 1] ** 2.0 + rel_pos[:, 2] ** 2.0)\\n DU = np.zeros_like(x)\\n ind = x > 0.0\\n DU_, Rw = _gcl(x[ind], r[ind], D[ind], ti[ind], c_t[ind])\\n DU_[abs(r[ind]) > Rw] = 0.0\\n DU_[DU_ < -1.0] = 0.0 # Avoid some weirdiness\\n DU[ind] = DU_\\n return DU\",\n \"def get_crd_cc(self, axis, shaped=False):\\n return self._src_crds.get_cc(axis, shaped=shaped)\",\n \"def grad_cc_piece(x,k_ind,m_ind):\\n \\n g_cc = np.zeros_like(x)\\n i = cfg.min_line[k_ind,m_ind] * cfg.nfea + cfg.nfea*sum(cfg.jk[i] for i in range(k_ind)) # starting of the min line\\n g_cc[i:i+cfg.nfea-1] = cfg.a[m_ind,:cfg.nfea-1]\\n g_cc[i+cfg.nfea-1] = 1.0\\n \\n return g_cc\",\n \"def brepalgo_ConcatenateWireC0(*args):\\n return _BRepAlgo.brepalgo_ConcatenateWireC0(*args)\",\n \"def add_rxn(self, reaction: db.Reaction):\\n # Add two rxn nodes\\n rxn_nodes = []\\n reaction_id = reaction.id().string()\\n\\n for i in range(0, 2):\\n # Add rxn node between lhs and rhs compound\\n rxn_node = ';'.join([reaction_id, str(i)])\\n rxn_node += ';'\\n self.graph.add_node(rxn_node, color='rxn_node')\\n rxn_nodes.append(rxn_node)\\n # Convert to strings\\n reactants = reaction.get_reactants(db.Side.BOTH)\\n reactant_types = reaction.get_reactant_types(db.Side.BOTH)\\n weights = self._get_weight(reaction)\\n # Add lhs aggregates and connect\\n for lhs_cmp, lhs_type in zip([i.string() for i in reactants[0]],\\n [i.name for i in reactant_types[0]]):\\n if lhs_cmp not in self.graph:\\n self.graph.add_node(lhs_cmp, type=lhs_type)\\n required_cmps_lhs = [s.string() for s in reactants[0]]\\n required_cmps_lhs.remove(lhs_cmp)\\n self.graph.add_edge(lhs_cmp, rxn_nodes[0], weight=weights[0], required_compounds=required_cmps_lhs,\\n required_compound_costs=None)\\n self.graph.add_edge(rxn_nodes[1], lhs_cmp, weight=0.0, required_compounds=None)\\n # Add rhs aggregates and connect\\n for rhs_cmp, rhs_type in zip([i.string() for i in reactants[1]],\\n [i.name for i in reactant_types[1]]):\\n if rhs_cmp not in self.graph:\\n self.graph.add_node(rhs_cmp, type=rhs_type)\\n required_cmps_rhs = [s.string() for s in reactants[1]]\\n required_cmps_rhs.remove(rhs_cmp)\\n self.graph.add_edge(rhs_cmp, rxn_nodes[1], weight=weights[1], required_compounds=required_cmps_rhs,\\n required_compound_costs=None)\\n self.graph.add_edge(rxn_nodes[0], rhs_cmp, weight=0.0, required_compounds=None)\\n\\n # # # Loop over reaction nodes to add required compounds info to downwards edges; might be unnecessary\\n node_index = 1\\n for node in rxn_nodes:\\n for key in self.graph[node].keys():\\n self.graph.edges[node, key]['required_compounds'] = \\\\\\n self.graph.edges[key, rxn_nodes[node_index]]['required_compounds']\\n node_index -= 1\",\n \"def _generate_loss_bonus(self, angles: tf.Variable) -> tf.Tensor:\\n # Get the operator for all the cx gates\\n cx = tf.constant(self.circuit_model.get_cnot_operator())\\n # Start from identity to iterate\\n circ = tf.complex(tf.eye(2 ** self.circuit_model.nqubit, dtype=tf.float64), tf.constant(0, dtype=tf.float64))\\n for layer in range(self.circuit_model.layers - 1, -1, -1):\\n start_angle = 3 * layer * self.circuit_model.nqubit\\n rot_u3 = self._r_u3(angles[start_angle:start_angle + 3])\\n for qb in range(1, self.circuit_model.nqubit):\\n rot_u3 = tf.tensordot(self._r_u3(angles[start_angle + 3 * qb: start_angle + 3 * qb + 3]),\\n rot_u3, axes=0)\\n\\n rot_u3 = self._fix_dimension(rot_u3)\\n circ = tf.matmul(circ, cx)\\n circ = tf.matmul(circ, rot_u3)\\n\\n loss = self._get_norm(circ)\\n\\n return loss\",\n \"def incr_registers(self):\\n pass\",\n \"def _dcg_idcg(relevance_scores, cg_discount):\\n # cg_discount is safe\\n dcg_k = relevance_scores / cg_discount\\n return tf.reduce_sum(dcg_k)\",\n \"def coordnav(self,dx,dy,dth): \\n self.cg_ant = np.array(self.cg)\\n self.coord[0] = self.coord[0] - self.cg[0]\\n self.coord[1] = self.coord[1] - self.cg[1] \\n self.Rz = rotation.matrix([0,0,1],dth)\\n self.coord = np.dot(self.Rz,self.coord)\\n \\n self.coord[0] = self.coord[0] + self.cg[0] + dx\\n self.coord[1] = self.coord[1] + self.cg[1] + dy \\n \\n self.px = self.coord[:,self.px_index]\\n self.Bx = self.px-self.cg \\n self.basex = self.Bx/math.sqrt(np.dot(self.Bx,self.Bx))\",\n \"def gelu(x):\\n cdf = 0.5 * (1.0 + tf.tanh(\\n (np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))\\n return x * cdf\",\n \"def keypress(self, event):\\n stepsize = 0.15 # pixels, i.e. 0.05 arcsec\\n if event.key == 'right':\\n if self.ccd == 2:\\n self.shift_crpix1 -= stepsize\\n else:\\n self.shift_crpix2 += stepsize\\n elif event.key == 'left':\\n if self.ccd == 2:\\n self.shift_crpix1 += stepsize\\n else:\\n self.shift_crpix2 -= stepsize\\n elif event.key == ']':\\n if self.ccd == 2:\\n self.shift_crpix1 -= 5*stepsize\\n else:\\n self.shift_crpix2 += 5*stepsize\\n elif event.key == '[':\\n if self.ccd == 2:\\n self.shift_crpix1 += 5*stepsize\\n else:\\n self.shift_crpix2 -= 5*stepsize\\n elif event.key == 'up':\\n if self.ccd == 2:\\n self.shift_crpix2 += stepsize\\n else:\\n self.shift_crpix1 += stepsize\\n elif event.key == 'down':\\n if self.ccd == 2:\\n self.shift_crpix2 -= stepsize\\n else:\\n self.shift_crpix1 -= stepsize\\n elif event.key == \\\"'\\\":\\n if self.ccd == 2:\\n self.shift_crpix2 += 5*stepsize\\n else:\\n self.shift_crpix1 += 5*stepsize\\n elif event.key == '/':\\n if self.ccd == 2:\\n self.shift_crpix2 -= 5*stepsize\\n else:\\n self.shift_crpix1 -= 5*stepsize\\n elif event.key == '1':\\n self.shift_cd1_1 += 1e-8\\n elif event.key == '2':\\n self.shift_cd1_1 -= 1e-8\\n elif event.key == '3':\\n self.shift_cd1_2 += 1e-8\\n elif event.key == '4':\\n self.shift_cd1_2 -= 1e-8\\n elif event.key == '5':\\n self.shift_cd2_1 += 1e-8\\n elif event.key == '6':\\n self.shift_cd2_1 -= 1e-8\\n elif event.key == '7':\\n self.shift_cd2_2 += 2e-8\\n elif event.key == '8':\\n self.shift_cd2_2 -= 2e-8\\n elif event.key == 'r': # Reset\\n self.shift_crpix1 = 0.0\\n self.shift_crpix2 = 0.0\\n self.shift_cd1_1 = 0.0\\n self.shift_cd1_2 = 0.0\\n self.shift_cd2_1 = 0.0\\n self.shift_cd2_2 = 0.0\\n elif event.key == 'o': # OK, field does not need fix\\n self.mark_done()\\n elif event.key == 'w': # Write WCS\\n self.write() # Save the results to a csv file\\n self.mark_done()\\n # Now update the plot for the slight change in WCS parameters\\n self.update()\",\n \"def __radd__(self, gg: Ggplot) -> Ggplot:\\n gg += self.to_layer() # Add layer\\n return gg\",\n \"def get_cdr3(dcr, headers):\\n\\n # NB: A productively rearranged receptor does not necessarily mean that it is the working receptor used in a cell!\\n out_data = coll.defaultdict()\\n for field in headers:\\n out_data[field] = ''\\n\\n out_data['decombinator_id'] = dcr\\n out_data['rev_comp'] = 'F'\\n\\n # CDR3-defining positions\\n start_cdr3 = 0\\n end_cdr3 = 0\\n\\n # 1. Rebuild whole nucleotide sequence from Decombinator assignment\\n classifier_elements = dcr.split(', ')\\n v = int(classifier_elements[0])\\n j = int(classifier_elements[1])\\n vdel = int(classifier_elements[2])\\n jdel = int(classifier_elements[3])\\n ins_nt = classifier_elements[4]\\n\\n # TODO remove 'split' if and when the gene names in the tag files get properly adjusted to be consistent\\n out_data['v_call'] = v_names[v].split('*')[0]\\n out_data['j_call'] = j_names[j].split('*')[0]\\n\\n if vdel == 0:\\n v_used = v_regions[v]\\n else:\\n v_used = v_regions[v][:-vdel]\\n\\n j_used = j_regions[j][jdel:]\\n\\n out_data['sequence'] = ''.join([v_used, ins_nt, j_used])\\n\\n # 2. Translate\\n out_data['sequence_aa'] = str(Seq(out_data['sequence']).translate())\\n\\n # 3. Check whether whole rearrangement is in frame\\n if (len(out_data['sequence']) - 1) % 3 == 0:\\n out_data['productive'] = 'T'\\n out_data['vj_in_frame'] = 'T'\\n else:\\n out_data['productive'] = 'F'\\n out_data['vj_in_frame'] = 'F'\\n\\n # 4. Check for stop codons in the in-frame rearrangements\\n if '*' in out_data['sequence_aa']:\\n out_data['productive'] = 'F'\\n out_data['stop_codon'] = 'T'\\n else:\\n out_data['stop_codon'] = 'F'\\n\\n # 5. Check for conserved cysteine in the V gene\\n if out_data['sequence_aa'][v_translate_position[v] - 1] == v_translate_residue[v]:\\n start_cdr3 = v_translate_position[v] - 1\\n out_data['conserved_c'] = 'T'\\n else:\\n out_data['productive'] = 'F'\\n out_data['conserved_c'] = 'F'\\n\\n # 5.5 Having found conserved cysteine, only need look downstream to find other end of CDR3\\n downstream_c = out_data['sequence_aa'][start_cdr3:]\\n\\n # 6. Check for presence of FGXG motif (or equivalent)\\n site = downstream_c[j_translate_position[j]:j_translate_position[j] + 4]\\n\\n if re.findall(j_translate_residue[j], site):\\n end_cdr3 = len(downstream_c) + j_translate_position[j] + start_cdr3 + 1\\n out_data['conserved_f'] = 'T'\\n else:\\n out_data['productive'] = 'F'\\n out_data['conserved_f'] = 'F'\\n\\n if out_data['productive'] == 'T':\\n out_data['junction_aa'] = out_data['sequence_aa'][start_cdr3:end_cdr3]\\n out_data['junction'] = out_data['sequence'][start_cdr3 * 3:3 * end_cdr3]\\n out_data['cdr1_aa'] = v_cdr1[v]\\n out_data['cdr2_aa'] = v_cdr2[v]\\n\\n return out_data\",\n \"def gelu(x):\\n cdf = 0.5 * (1.0 + tf.tanh(\\n (np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))\\n return x * cdf\",\n \"def _cond_gccovgc(signals, x_idx, y_idx, ind_tx, conditional=True):\\n d_x, d_y = signals[x_idx, :], signals[y_idx, :]\\n n_lags, n_dt = ind_tx.shape\\n gc = np.empty(3, dtype=d_x.dtype, order='C')\\n # define z past\\n z_indices = np.array([k for k in range(signals.shape[0]) if k not in [x_idx, y_idx]])\\n d_z = signals[z_indices, :] # other roi selection\\n rsh = int(len(z_indices) * (n_lags - 1)) # roi_range = 150-2 = 148; n_lags-1 = 5 --> rsh = 740\\n\\n x = d_x[ind_tx]\\n y = d_y[ind_tx]\\n # temporal selection\\n x_pres, x_past = x[0], x[1:]\\n y_pres, y_past = y[0], y[1:]\\n xy_past = np.concatenate((x[1:], y[1:]), axis=0)\\n # conditional granger causality case\\n if conditional:\\n # condition by the past of every other possible sources\\n z_past = d_z[..., ind_tx[1:, :]] # (lag_past, dt) selection\\n z_past = z_past.reshape(rsh, n_dt)\\n # cat with past\\n yz_past = np.concatenate((y_past, z_past), axis=0)\\n xz_past = np.concatenate((x_past, z_past), axis=0)\\n xyz_past = np.concatenate((xy_past, z_past), axis=0)\\n else:\\n yz_past, xz_past, xyz_past = y_past, x_past, xy_past\\n\\n # copnorm over the last axis (avoid copnorming several times)\\n x_pres = copnorm_nd(x_pres, axis=-1)\\n x_pres = np.expand_dims(x_pres, 0)\\n x_past = copnorm_nd(x_past, axis=-1)\\n y_pres = copnorm_nd(y_pres, axis=-1)\\n y_pres = np.expand_dims(y_pres, 0)\\n y_past = copnorm_nd(y_past, axis=-1)\\n yz_past = copnorm_nd(yz_past, axis=-1)\\n xz_past = copnorm_nd(xz_past, axis=-1)\\n xyz_past = copnorm_nd(xyz_past, axis=-1)\\n\\n # -----------------------------------------------------------------\\n # Granger Causality measures\\n # -----------------------------------------------------------------\\n gc[0] = cmi_nd_ggg(y_pres, x_past, yz_past)\\n # gc(pairs(:,2) -> pairs(:,1))\\n gc[1] = cmi_nd_ggg(x_pres, y_past, xz_past)\\n # gc(pairs(:,2) . pairs(:,1))\\n gc[2] = cmi_nd_ggg(x_pres, y_pres, xyz_past)\\n return gc\",\n \"def globalphase_compiler(self, gate, args):\\n pass\",\n \"def globalphase_compiler(self, gate, args):\\n pass\",\n \"def cvChin(ctrlName, r=1):\\r\\n # create a simple circle curve:\\r\\n curve = cmds.curve(n=ctrlName, d=3, p=[(0, 0.8*r, -0.5*r), (0, 0.9*r, -0.7*r), (0, 0, -0.5*r), (0, -0.8*r, -0.7*r), (0, -0.8*r, 1.4*r), (0, -0.3*r, 1.3*r), (0, 0, 1.2*r), (0, 0, 0), (0, 0.8*r, -0.3*r), (0, 0.8*r, -0.5*r)] )\\r\\n # rename curveShape:\\r\\n renameShape([curve])\\r\\n return curve\",\n \"def dgdx(self, X):\\n \\n return 2*(X[0]) - 2\",\n \"def addX(self,name):\\n return self._addVar(name,self._xNames)\",\n \"def gelu(x):\\n cdf = 0.5 * (1.0 + torch.tanh(\\n (np.sqrt(2 / np.pi) * (x + 0.044715 * np.power(x, 3)))))\\n return x * cdf\",\n \"def cX(cb):\\n allNodes = b.allNodes(group=cb)\\n for n in allNodes:\\n allNodes = allNodes + cX(n)\\n\\n return allNodes\",\n \"def add_rand_circ() -> int:\\n r = randint(10, 100)\\n x = randint(r, WIDTH - r)\\n y = randint(r, HEIGHT - r)\\n vx = randint(-10, 10)\\n vy = randint(-10, 10)\\n color = COLORS[randint(0, len(COLORS) - 1)]\\n add_circ(x, y, r, vx, vy, color, int(100 / r))\\n return 0\",\n \"def test_special_XYX(self, angexp):\\n a, b, c, d = angexp[0]\\n exp = {(\\\"rx\\\", \\\"ry\\\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\\n tgt = np.exp(1j * d) * RXGate(b).to_matrix() @ RYGate(a).to_matrix() @ RXGate(c).to_matrix()\\n self.check_oneq_special_cases(tgt, \\\"XYX\\\", exp)\",\n \"def grads(self, inputs):\",\n \"def add(self, params):\\n if len(params) < 2:\\n return\\n x = self.reg_dct[params[0]]\\n y = self.reg_dct[params[1]]\\n self.reg_dct[params[0]] = (x + y) % (2** 32)\",\n \"def __iadd__(self, d_value: float):\\n self.increment_value(d_value)\\n return self\",\n \"def double_add(self, x):\\n self.add(x*2)\",\n \"def attraction_g(next_q, q, d, a):\\n\\n if a == 0:\\n if next_q == 0:\\n xi_D = 8\\n else:\\n xi_D = 1\\n\\n elif a == 1:\\n xi_D = 1\\n\\n elif a == 2:\\n if next_q == 0:\\n xi_D = 1\\n else:\\n xi_D = 3\\n\\n elif a == 3:\\n if next_q == 0:\\n xi_D = 1\\n else:\\n xi_D = 2\\n\\n else:\\n if next_q == 0:\\n xi_D = 1\\n else:\\n xi_D = 4\\n\\n dqq = 0\\n if next_q == 1 and q == 0:\\n if d[3] == 1:\\n dqq = 1\\n elif np.sum(d[6:]) == 3:\\n dqq = 1\\n elif next_q == 0 and q == 1:\\n if d[5] == 1:\\n dqq = 1\\n elif np.sum(d[6:]) == 0:\\n dqq = 1\\n\\n return xi_D + dqq\",\n \"def dRdE_magnetic(E, m_x, mu_x, target, vlag=232.0, sigmav=156.0, vesc=544.0):\\n \\n A = Avals[target]\\n \\n #See Eq. 62 of https://arxiv.org/pdf/1307.5955.pdf, but note\\n #that we're using some different normalisations for the operators\\n #so there are some extra factors of m_x and m_p lurking around...\\n \\n amu = 931.5e3 # keV\\n q1 = np.sqrt(2*A*amu*E) #Recoil momentum in keV\\n \\n alpha = 0.007297\\n e = np.sqrt(4*np.pi*alpha)\\n m_p = 0.9315\\n \\n #Proton and neutron g-factors\\n gp = 5.59\\n gn = -3.83\\n \\n #Bohr Magneton\\n #Tesla = 194.6*eV**2 # Tesla in natural units (with e = sqrt(4 pi alpha))\\n #muB = 5.7883818e-5*eV/Tesla # Bohr magneton\\n mu_B = 297.45 #GeV^-1 (in natural units (with e = sqrt(4 pi alpha)))\\n\\n cp = [E*0.0 for i in range(11)]\\n cn = [E*0.0 for i in range(11)]\\n \\n #Operator 1\\n cp[0] = e*(mu_x*mu_B)/(2.0*m_x)\\n \\n #Operator 5\\n cp[4] = 2*e*(mu_x*mu_B)*m_p/(q1*1e-6)**2\\n \\n #Operator 4\\n cp[3] = gp*e*(mu_x*mu_B)/m_p\\n cn[3] = gn*e*(mu_x*mu_B)/m_p\\n \\n #Operator 6\\n cp[5] = -gp*e*(mu_x*mu_B)*m_p/(q1*1e-6)**2\\n cn[5] = -gn*e*(mu_x*mu_B)*m_p/(q1*1e-6)**2\\n\\n return dRdE_NREFT(E, m_x, cp, cn, target, vlag, sigmav, vesc)\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def _add_grad(self, coords:torch.tensor, trust:torch.tensor, \\n update:torch.tensor ) -> torch.tensor:\\n # view as to avoid deprecated point wise semantics\\n step = trust.reshape(-1,1,1)*update.view_as(coords)\\n \\n coords.data.add_(step)\\n return trust #* cutoff_multiplier\",\n \"def increase_radius(self, character):\\n character.bombradius += 1\",\n \"def _add_grover_step_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n _add_2_bit_oracle_without_ancilla_1_0(qc, register) # Oracle\\n add_grover_reflection_no_ancilla(qc, register) # Reflection\",\n \"def xr_add_cyclic(da, coord):\\n from cartopy.util import add_cyclic_point\\n\\n cyclic_data, cyclic_coord = add_cyclic_point(da.values, coord=da[coord])\\n\\n coords = da.coords.to_dataset()\\n coords[coord] = cyclic_coord\\n return xr.DataArray(\\n cyclic_data,\\n dims=da.dims,\\n coords=coords.coords,\\n attrs=da.attrs,\\n encoding=da.encoding,\\n )\",\n \"def cg(self):\\n A = self.clAlphaT / self.clAlphaWF\\n B = (1 - self.downwashGradW)\\n C = (self.surfaceT * self.tlH) / (self.surfaceW * self.cMACW)\\n sm = 0.05 * self.cMACW # static margin, approximated as 5% of aircraft MAC\\n return self.ac + A * B * C * self.speedRatio**2 - sm\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5829941","0.5677816","0.5607042","0.5547162","0.5384019","0.52695274","0.51288795","0.50940967","0.50349534","0.49191833","0.49003875","0.48831064","0.48794276","0.48730922","0.48560813","0.48516476","0.48199007","0.48017424","0.47675318","0.47669303","0.4752315","0.4709782","0.47048095","0.4701373","0.46845475","0.46608168","0.46197426","0.46181497","0.46086314","0.4601211","0.45971385","0.4595519","0.4568017","0.4558522","0.45516652","0.4546031","0.45448664","0.45340464","0.4531419","0.45250878","0.45204037","0.45165548","0.45053595","0.4490498","0.44891968","0.4482371","0.44784498","0.44779766","0.4476945","0.44756308","0.44672042","0.4466313","0.446525","0.44612452","0.4450652","0.44460186","0.4442899","0.44374996","0.44351593","0.44336897","0.44323617","0.4428746","0.442816","0.4421084","0.4415513","0.44092676","0.44058388","0.4404781","0.43972814","0.4395784","0.43916026","0.4386064","0.43857497","0.43822145","0.43784943","0.43780005","0.43758947","0.4371834","0.43625438","0.43579194","0.43579194","0.43553114","0.4354135","0.43530902","0.43515533","0.4349207","0.43449277","0.4343987","0.43436033","0.4343574","0.43433085","0.43384668","0.43352783","0.4329781","0.4322665","0.43214568","0.43181923","0.43175787","0.43146077","0.43117917"],"string":"[\n \"0.5829941\",\n \"0.5677816\",\n \"0.5607042\",\n \"0.5547162\",\n \"0.5384019\",\n \"0.52695274\",\n \"0.51288795\",\n \"0.50940967\",\n \"0.50349534\",\n \"0.49191833\",\n \"0.49003875\",\n \"0.48831064\",\n \"0.48794276\",\n \"0.48730922\",\n \"0.48560813\",\n \"0.48516476\",\n \"0.48199007\",\n \"0.48017424\",\n \"0.47675318\",\n \"0.47669303\",\n \"0.4752315\",\n \"0.4709782\",\n \"0.47048095\",\n \"0.4701373\",\n \"0.46845475\",\n \"0.46608168\",\n \"0.46197426\",\n \"0.46181497\",\n \"0.46086314\",\n \"0.4601211\",\n \"0.45971385\",\n \"0.4595519\",\n \"0.4568017\",\n \"0.4558522\",\n \"0.45516652\",\n \"0.4546031\",\n \"0.45448664\",\n \"0.45340464\",\n \"0.4531419\",\n \"0.45250878\",\n \"0.45204037\",\n \"0.45165548\",\n \"0.45053595\",\n \"0.4490498\",\n \"0.44891968\",\n \"0.4482371\",\n \"0.44784498\",\n \"0.44779766\",\n \"0.4476945\",\n \"0.44756308\",\n \"0.44672042\",\n \"0.4466313\",\n \"0.446525\",\n \"0.44612452\",\n \"0.4450652\",\n \"0.44460186\",\n \"0.4442899\",\n \"0.44374996\",\n \"0.44351593\",\n \"0.44336897\",\n \"0.44323617\",\n \"0.4428746\",\n \"0.442816\",\n \"0.4421084\",\n \"0.4415513\",\n \"0.44092676\",\n \"0.44058388\",\n \"0.4404781\",\n \"0.43972814\",\n \"0.4395784\",\n \"0.43916026\",\n \"0.4386064\",\n \"0.43857497\",\n \"0.43822145\",\n \"0.43784943\",\n \"0.43780005\",\n \"0.43758947\",\n \"0.4371834\",\n \"0.43625438\",\n \"0.43579194\",\n \"0.43579194\",\n \"0.43553114\",\n \"0.4354135\",\n \"0.43530902\",\n \"0.43515533\",\n \"0.4349207\",\n \"0.43449277\",\n \"0.4343987\",\n \"0.43436033\",\n \"0.4343574\",\n \"0.43433085\",\n \"0.43384668\",\n \"0.43352783\",\n \"0.4329781\",\n \"0.4322665\",\n \"0.43214568\",\n \"0.43181923\",\n \"0.43175787\",\n \"0.43146077\",\n \"0.43117917\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6386473"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81747,"cells":{"query":{"kind":"string","value":"add CH gate (controlled H gate)."},"document":{"kind":"string","value":"def ch(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_H, qid=[q0,q1], ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def addchan(channel):","def h(self, q0, ctrl=None):\n self.__add_quantum_gate(kind=HADAMARD, qid=[q0])\n return self","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def _add_control_channel(self, attrs):\n _cable_data = {}\n _cable_data[\"crate\"] = self._crate\n _cable_data[\"module\"] = self._module\n _cable_data[\"channel\"] = int(attrs.get('number', \"\"))\n _cable_data[\"name\"] = str(attrs.get('name', \"\"))\n self._data.append(_cable_data)","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def H(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.H, qubit_expr)","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def setCh(self, ch):\n if (self.model == 'TDS'):\n # according to the manual, RIBanary mode with 2-bit width is\n # the fastest mode for data transfer.\n # but I have to think 1-bit transfer ought to be faster.\n self.write('DATa:SOUrce CH'+str(ch)+\n '; ENCdg RIBinary; STARt 1; STOP 2500; WIDth 1\\n')\n # obtain vertical scale and offset (for calibration)","def add_connector(self):\n \n no = len(self.connectors)\n state = {}\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % no\n \n if len(self.connectors)>0:\n state = self.connectors[-1].get_state()\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % (no)\n else:\n if self.mount == self.MOUNT_THT:\n state[\"p_shape\"] = Con.SHAPE_HOLE\n elif self.mount == self.MOUNT_SMD:\n state[\"p_shape\"] = Con.SHAPE_PAD\n \n c = Con(no)\n c.set_state(state) \n \n self.sch_layers[\"pins\"].add(c.s_svg)\n self.pcb_layers[\"copper1\"].add(c.p_svg)\n self.connectors.append(c)","def connect(self, gate) :\n self.notifyList.append(gate)","def addch(self, stdscr, y, x, text):\n stdscr.addch(y, x, text, curses.color_pair(self.i))","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def add_hand(self, hand):\n self.hands = hand","def add_chnl(self):\n\n # new widget\n chnl = QWidget()\n \n # load elements\n uic.loadUi(self.chnl_ui, chnl)\n\n # connect remove button\n chnl.rmv.clicked.connect(lambda _: self.rmv_chnl(chnl))\n\n # add to list\n self.chnls.append(chnl)\n\n # add to layout\n self.channels_layout.addWidget(chnl)","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def added(self, comp):\n\t\tpass","def add_channel(self, channel):\n self.task.ai_channels.add_ai_voltage_chan(channel)","def __init__(self, *args):\n moose.HHChannel.__init__(self,*args)\n self.Ek = VKDR\n self.Gbar = GKDR\n self.addField('ion')\n self.setField('ion','K')\n self.Xpower = 1 # This will create HHGate instance xGate inside the Na channel\n #self.Ypower = 0 # This will create HHGate instance yGate inside the Na channel\n ## Below gates get created after Xpower or Ypower are set to nonzero values\n ## I don't anymore have to explicitly create these attributes in the class\n #self.xGate = moose.HHGate(self.path + \"/xGate\")\n #self.yGate = moose.HHGate(self.path + \"/yGate\")\n self.xGate.A.xmin = VMIN\n self.xGate.A.xmax = VMAX\n self.xGate.A.xdivs = NDIVS\n self.xGate.B.xmin = VMIN\n self.xGate.B.xmax = VMAX\n self.xGate.B.xdivs = NDIVS\n \n v = VMIN\n\n for i in range(NDIVS+1):\n mtau = calc_KA_mtau(v)\n self.xGate.A[i] = calc_KA_minf(v)/mtau\n self.xGate.B[i] = 1.0/mtau\n v = v + dv","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def one_step(self, x, h):\n concatHX = torch.cat((x, h), 1)\n ft = self.sigmoid(self.linearF(concatHX))\n it = self.sigmoid(self.linearI(concatHX))\n ct = ft*self.cts[-1] + it*self.tanh(self.linearC(concatHX))\n #self.ct = ft*self.ct.clone() + it*self.tanh(self.linearC(concatHX))\n ot = self.sigmoid(self.linearO(concatHX))\n ht = ot*self.tanh(ct)\n \n self.cts.append(ct)\n \n return ht","def add_switch(self, dpid):\n\t\tself.switches.append(dpid)","def one_step(self, x, h):\n concatHX = torch.cat((x, h), 1)\n ft = self.sigmoid(self.linearF(concatHX))\n it = self.sigmoid(self.linearI(concatHX))\n newCt = ft*self.ct.clone() + it*self.tanh(self.linearC(concatHX))\n #self.ct = ft*self.ct.clone() + it*self.tanh(self.linearC(concatHX))\n ot = self.sigmoid(self.linearO(concatHX))\n ht = ot*self.tanh(newCt)\n self.ct = newCt\n \n return ht","def addCardToHand(self, card):\r\n self.hand.append(card)","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def addCoupling(ham: Dict[str, Any], name: str, onQubits: Union[int, List[int]], g: float = 1.0) -> None:\n assert len(onQubits) == 2, \"Coupling term should be defined on two qubits.\"\n # Obtain the system energy level.\n if isinstance(ham[\"circuit\"][\"sys_level\"], int):\n d = ham[\"circuit\"][\"sys_level\"]\n # Construct matrices.\n matrices = [Operator.destroy(d), Operator.create(d)]\n matricesHc = [Operator.create(d), Operator.destroy(d)]\n elif isinstance(ham[\"circuit\"][\"sys_level\"], list):\n sysLevel = ham[\"circuit\"][\"sys_level\"]\n matrices = [Operator.destroy(sysLevel[onQubits[0]]), Operator.create(sysLevel[onQubits[1]])]\n matricesHc = [Operator.create(sysLevel[onQubits[0]]), Operator.destroy(sysLevel[onQubits[1]])]\n # Add drift terms\n addDrift(ham, f\"{name}\", onQubits=onQubits, matrices=matrices, amp=g)\n addDrift(ham, f\"{name}(hc)\", onQubits=onQubits, matrices=matricesHc, amp=g)","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def _add_switch(self, switchdesc):\n # Check switch definition parameters\n switch_attributes = list(switchdesc.keys())\n if not set(switch_attributes).issubset(self.switch_attributes):\n raise ValueError(\n \"Switch definition: '{0}' defined in '{1}' is not supported. \"\n \"Supported switch parameters are '{2}'.\".format(\n json.dumps(switchdesc, indent=2), self._xmlfile,\n self.switch_attributes))\n for mandatory_parameter in self.switch_attributes[:2]:\n if mandatory_parameter not in switch_attributes:\n raise ValueError(\n \"A '{0}' parameter is required in switch definition: \"\n \"'{1}' defined in '{2}'.\".format(\n mandatory_parameter, json.dumps(switchdesc, indent=2),\n self._xmlfile))\n\n # Check the name of the switch is not already reserved\n switch_name = switchdesc[self.switch_attributes[0]][0]\n if switch_name in self._switches:\n raise ValueError(\n \"The switch name '{0}' defined in '{1}' is \"\n \"already used.\".format(switch_name, self._xmlfile))\n\n # Create the switch control\n switch_paths = {}\n for pathdesc in switchdesc[self.switch_attributes[1]]:\n path_name = pathdesc[self.switch_path[0]][0]\n path_boxes = [box[self.unit_attributes[0]]\n for box in pathdesc[self.switch_path[1]]]\n switch_paths[path_name] = path_boxes\n switch_keys = list(switch_paths.keys())\n control = controls[\"Enum\"](\n choices=tuple(switch_keys),\n switch_name=switch_name,\n desc=(\"Switch between paths '{0}:{1}' defined in pipeline '{2}'\"\n \".\".format(switch_name, \"-\".join(switch_keys), self.id)))\n setattr(self.inputs, switch_name, control)\n self._switches[switch_name] = switch_paths\n control.add_observer(\"value\", self._update_activation)\n control.value = switch_keys[0]","def commit_chow(\n self,\n new_tile: tiles.Tile,\n tile1: tiles.Tile,\n tile2: tiles.Tile):\n\n self.exposed_parts.append(Chow([new_tile, tile1, tile2], False))\n self.concealed_part.subtract([tile1, tile2])\n # self.update()","def add(self, y):\n return circuit.add(self, y)","def add_card_to_hand(self, card):\n self.hand.append(card)","def _add_cmd(self, cmd):\n if cmd.gate == Allocate:\n self._active_qubits += 1\n elif cmd.gate == Deallocate:\n self._active_qubits -= 1\n elif cmd.gate == Measure:\n for qureg in cmd.qubits:\n for qubit in qureg:\n self.main_engine.set_measurement_result(qubit, 0)\n elif self._is_rotation(cmd):\n self._num_rotations += 1\n self._rotations.append(self._decompose_rotation(cmd))","def add_connection(self, house):\n if house not in self.connections and house.max_output < self.capacity:\n self.connections.append(house)\n self.capacity = self.capacity - house.max_output\n house.connected_battery = self.id\n # else:\n # print(\"Battery does not have enough capacity to connect this house\")\n # self.reach_capacity = True","def Set_Meas_Additional(self, mode, state, ch=1):\n self.write(f':MEAS{ch}:ADD {mode} {state}')","def add_neurone(self, couche, nbr=1):\n if self.control == 0:\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\n self.couche[couche] += nbr\n else:\n print(\"Le réseau est deja créé, vous en pouvez plus le modifier\")","def hkdr_hf(female, age, bmi, hba1c, acr, hb, chdHist):\n baseSurv = HKDR_HF[\"male_sm\"]\n if female:\n baseSurv = HKDR_HF[\"female_sm\"]\n xFeat = np.array([clean_age(age),\n clean_bmi(bmi),\n clean_hba1c(hba1c),\n np.log10(1+clean_acr(acr)),\n clean_hb(hb),\n chdHist])\n return cox_surv(xFeat,\n HKDR_HF[\"coef\"],\n baseSurv,\n HKDR_HF[\"const\"],\n HKDR_HF[\"shrink\"])","def addOp(self, op):\n self.operations << op","def addChar(self, char):\n self.guessedChars.append(char)","def add_power(self, power):\n\n self.powers.append(power)","def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\n if q_args is None and c_args is None:\n raise GateError(\"Gate needs at least one quantum argument or classical argument\")\n if isinstance(gate, CompositeGate):\n if mapping is None:\n raise GateError(\"Must provide arguments mapping for composite gate inside a composite gate.\")\n else:\n inv_mappimg = dict()\n for key, value in mapping.items():\n inv_mappimg[value] = key\n if gate is self:\n gates = gate.copy.gates\n else:\n gates = gate.gates\n for g in gates:\n new_q_args = None\n new_c_args = None\n if g[1] is not None:\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\n if g[2] is not None:\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\n self.add_gate(gate=g[0], q_args=new_q_args,\n c_args=new_c_args, params=g[3])\n else:\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\n raise GateError(\"Gate must be either a CompositeGate or a string from: \"\n \"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\")\n if q_args is not None:\n for q_arg in q_args:\n if q_arg not in self.q_args:\n self.add_q_arg(q_arg)\n if c_args is not None:\n for c_arg in c_args:\n if c_arg not in self.c_args:\n self.add_c_arg(c_arg)\n if params is not None:\n for param in params:\n if param not in self.params:\n self.add_param(param)\n self._gates.append((gate, q_args, c_args, params))","def add_challenger(self, new_challenger, initial_score: int = 0) -> None:\n self.challengers.append(new_challenger)\n self.scores[new_challenger] = initial_score\n self.isOrdered = initial_score == 0 and self.isOrdered","def add_card(self, card):\r\n self.hand.append(card)","def add_cell(self, cell: Cell):\r\n assert isinstance(cell, Cell)\r\n assert -self.pmax <= cell.gain <= self.pmax\r\n\r\n self[cell.gain].append(cell)\r\n cell.bucket_num = cell.gain + self.pmax\r\n if cell.gain > self.max_gain:\r\n self.max_gain = cell.gain","def add_cogs(self):\n self.add_cog(Voice(self))","def add_child(self, cd, wt: float):\n self.child.append([cd, wt])","def send_breath_controller(self, value=0, ch=None):\n self.send_control_change(BREATH_CONTROLLER, value, ch=ch)","def add_output(self, ch, *, close=True):\n if self._done:\n return False\n\n self._outs.append((ch, close))\n return True","def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def generate_ising_hamiltonian(gc, cost=100., factor=100.):\n H = np.zeros([gc.nnodes*gc.ncolors, gc.nnodes*gc.ncolors])\n # one color per node\n for i in range(gc.nnodes):\n for c1 in range(gc.ncolors):\n for c2 in range(gc.ncolors):\n if c1 == c2:\n H[i*gc.ncolors+c1, i*gc.ncolors+c2] = -cost\n else:\n H[i*gc.ncolors+c1, i*gc.ncolors+c2] = cost\n\n # different color for connected edges\n for i, j in gc.edges:\n if i != j:\n for c in range(gc.ncolors):\n H[i*gc.ncolors+c, j*gc.ncolors+c] = cost/factor \n H[j*gc.ncolors+c, i*gc.ncolors+c] = cost/factor \n return H","def addEdge(self, hub, gene, mi):\n hubid = self.internName(hub)\n geneid = self.internName(gene)\n # s1 = self.DBcurs.execute(\"SELECT support, totmi FROM edges WHERE gene1=? AND gene2=?\", (hubid, geneid))\n # data = s1.fetchone()\n # if data == None:\n # self.DBcurs.execute(\"INSERT INTO edges(gene1, gene2, support, totmi) VALUES (?, ?, ?, ?)\", (hubid, geneid, 1, mi))\n # else:\n # newsupport = data[0] + 1\n # newmi = data[1] + mi\n self.DBcurs.execute(\"UPDATE edges SET support=support+1, totmi=totmi+? WHERE gene1=? AND gene2=?\", (mi, hubid, geneid))","def __call__(self, channel):\n\n state = list(self.states[-1])\n state[INPUT_PINS.index(channel)] = GPIO.input(channel)\n\n with self.lock:\n self.states.append(tuple(state))\n\n if len(self.states) > MIN_MATCHES:\n del self.states[0]\n\n subsequence = tuple(self.states)\n\n if subsequence in self.cw:\n event = \"CW\" # ...clockwise motion.\n elif subsequence in self.ccw:\n event = \"CCW\" # ...counter-clockwise motion.\n else:\n event = \"UNK\" # ...not enough data to decide.\n\n # Send a motion event to the GUI application...\n self.socket.sendto(event, address)\n self.num_events += 1","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def gate_logic(self, pull: str):\r\n self._gate_logic = pull\r\n self.gate_logic_hist.append(pull)\r\n\r\n if self.gate_logic_hist[-2] != pull and self._daq:\r\n msg = Message(\"gate_logic\", pull, self.checksum).message_bytes\r\n self._daq.asynch.transmit(msg)","def do_add_node(self, line=''):\n self.fibbing.add_node()","def draw(self, card):\n self._cards.append(card) # add card to hand\n self.value = self._set_value() # determine value","def cp(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_P, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def add(self, datapath):\n self.logger.info(\"Adding switch dpid=%s\", datapath.id)\n self.switch[datapath.id] = Switch(self._nmeta, self.logger,\n self._config, datapath)\n return 1","def addFanIn(self,gate):\n assert type(gate)==Gate\n if self.gateType == \"INPUT\":\n print \"Inputs cannot have a fanIn.\"\n return\n self.fanIn.append(gate)\n gate.addFanOut(self)","def addPower(self, power):\n self.powers.append(float(power))","def add(self, name, chan_id):\r\n self.channels.append(Channel(name, chan_id))","def extend_circuit(self, circid=None, hops=None):\r\n if circid is None:\r\n circid = 0\r\n if hops is None:\r\n hops = \"\"\r\n plog(\"DEBUG\", \"Extending circuit\")\r\n lines = self.sendAndRecv(\"EXTENDCIRCUIT %d %s\\r\\n\"\r\n %(circid, \",\".join(hops)))\r\n tp,msg,_ = lines[0]\r\n m = re.match(r'EXTENDED (\\S*)', msg)\r\n if not m:\r\n raise ProtocolError(\"Bad extended line %r\",msg)\r\n plog(\"DEBUG\", \"Circuit extended\")\r\n return int(m.group(1))","def build_glyCB(self, gCBd: Dihedron): # -> None:\n ...","def enable_cl1_direct(self):\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\n self.write_versa5(0x18,0x20)\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\n self.write_versa5(0x13,0x03) ## Switch to clock\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew","def add_card(self, card):\n self.hand.append(card)","def add_control(operation, num_ctrl_qubits, label):\n if isinstance(operation, UnitaryGate):\n # attempt decomposition\n operation._define()\n if _control_definition_known(operation, num_ctrl_qubits):\n return _control_predefined(operation, num_ctrl_qubits)\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)","def _add_entanglement_gate(self, gate_method, qubit_1, qubit_2):\r\n sig = signature(gate_method)\r\n\r\n # parametrized gate like a controlled single qubit rotation\r\n if 'theta' in sig.parameters:\r\n try:\r\n gate_method(self.circuit, self.parameters[next(self.indices)], qubit_1, qubit_2)\r\n except KeyError:\r\n raise ValueError(f'Unsupported two qubit rotation gate')\r\n\r\n # non-parametrized gate like CNOT\r\n else:\r\n try:\r\n gate_method(self.circuit, qubit_1, qubit_2)\r\n except KeyError:\r\n raise ValueError(f'Unsupported unparametrized two qubit gate')","def addch(self, posy, posx, character, color_pair):\r\n if posy < 0 or posy > self.height - 1:\r\n return\r\n if posx < 0 or posx > self.width - 1:\r\n return\r\n if posx == self.width - 1 and posy == self.height - 1:\r\n return\r\n self.win.addch(posy, posx, character, color_pair)","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def addFanOut(self,gate):\n assert type(gate)==Gate\n self.fanOut.append(gate)","def add(self, h, name, parent=None, action=None, observation=None,\n particle=None, budget=None, cost=None):\n history = h[:]\n\n # instantiate node\n if action is not None:\n n = ActionNode(self.counter, name, history, parent=parent, action_index=action, cost=cost)\n else:\n n = BeliefNode(self.counter, name, history, parent=parent, obs_index=observation, budget=budget)\n\n if particle is not None:\n n.add_particle(particle)\n\n # add the node to belief tree\n self.nodes[n.id] = n\n self.counter += 1\n\n # register node as parent's child\n if parent is not None:\n parent.add_child(n)\n return n","def _ctrl_hum_set(self, osrs_h):\n data = osrs_h & 0x7\n self._bus.write_byte_data(self.addr, self.CTRL_HUM,\n data)","def AddOperation(self, op):\n self._operations.append(op)","def add(self, component):\n\n self.append(component)\n self.sum.Add(component.th1f)","def draw_card(self,card):\n self.hand.append(card)","def __call__(self, h_, x):\n # h_: the concatenation of previous hidden state\n # and memory cell state\n # x_i/x: the current input state for input gate\n # x_f/x: the current input state for forget gate\n # x_o/x: the current input state for output gate\n # x_c/x: the current input state for candidate cell\n with tf.variable_scope(\n \"cell_{}\".format(self.scope or \"lstm\")):\n x_g, x_c = x\n h_, c_ = tf.split(h_, 2, -1)\n\n h_g = linear(h_, self.d * 3,\n ln=self.ln, scope=\"gate_h\")\n i, f, o = tf.split(\n tf.sigmoid(x_g + h_g), 3, -1)\n\n h_c = linear(h_, self.d,\n ln=self.ln, scope=\"hide_h\")\n h_c = tf.tanh(x_c + h_c)\n\n c = i * h_c + f * c_\n\n h = o * tf.tanh(c)\n\n return tf.concat([h, c], -1)","def add_new_header(self, hdr):\n # if there are any lines in the unchanged-lines buffer, create a \n # new hunk using them, and add it to the last header.\n if self.changedlines:\n self.add_new_hunk()\n\n # create a new header and add it to self.stream\n self.header = header(hdr)\n fileName = self.header.filename()\n if fileName in self.modified:\n self.header.changetype = \"M\"\n elif fileName in self.added:\n self.header.changetype = \"A\"\n elif fileName in self.removed:\n self.header.changetype = \"R\"\n self.stream.append(self.header)","def add(self, name, command):","def add_command(self, name, fct):\r\n self.cmds[name] = fct","def add_card(self, card):\n if not isinstance(card, Card):\n raise TypeError(\"'card' must be a card object.\")\n # append new card to list of cards in the hand\n self.cards.append(card)\n self.total = card + self.total\n # aces require a little more work\n if card.rank == 14:\n self.soft = True\n self.num_aces += 1\n self.num_hard_aces += 1\n # account for soft hands\n if self.total > 21 and self.soft:\n self.total -= 10\n self.num_hard_aces -= 1\n self.soft = False\n # catch the edge case where you're delt 12+ aces\n if self.total > 21:\n self.total -= 10\n self.num_hard_aces -= 1\n self.soft = False\n if self.num_hard_aces > 0:\n self.soft = True\n if self.total > 21:\n self.bust = True","def register(self, cmd):\n\n assert(cmd.name not in self.cmds)\n \n data = cmd.data\n assert(type(data.switches) is dict)\n \n self.cmds[cmd.name] = data","def add(self, node):\n cost = self.costfn(node)\n heapq.heappush(self.heap, (cost, node))\n self.states[node.state] = node","def __add__(G, H):\n if isinstance(H, Surreal):\n return Surreal.from_value(G._n + H.n)\n if isinstance(H, numbers.Number):\n return Surreal.from_value(G._n + H)\n if isinstance(H, Game):\n return super().__add__(H)\n\n return NotImplemented","def add(self, inp, out):\n self.curr_node.input_frequencies[inp] += 1\n if inp not in self.curr_node.children.keys() or out not in self.curr_node.children[inp].keys():\n node = Node(out)\n self.curr_node.children[inp][out] = node\n\n self.curr_node = self.curr_node.children[inp][out]\n self.curr_node.frequency += 1","def set_hamiltonian(self, system):\n system.clear_hamiltonian()\n if 'bh' in system.left_block.operators.keys():\n system.add_to_hamiltonian(left_block_op='bh')\n if 'bh' in system.right_block.operators.keys():\n system.add_to_hamiltonian(right_block_op='bh')\n system.add_to_hamiltonian('c_up', 'c_up_dag', 'id', 'id', -1.)\n system.add_to_hamiltonian('c_up_dag', 'c_up', 'id', 'id', -1.)\n system.add_to_hamiltonian('c_down', 'c_down_dag', 'id', 'id', -1.)\n system.add_to_hamiltonian('c_down_dag', 'c_down', 'id', 'id', -1.)\n system.add_to_hamiltonian('id', 'c_up', 'c_up_dag', 'id', -1.)\n system.add_to_hamiltonian('id', 'c_up_dag', 'c_up', 'id', -1.)\n system.add_to_hamiltonian('id', 'c_down', 'c_down_dag', 'id', -1.)\n system.add_to_hamiltonian('id', 'c_down_dag', 'c_down', 'id', -1.)\n system.add_to_hamiltonian('id', 'id', 'c_up', 'c_up_dag', -1.)\n system.add_to_hamiltonian('id', 'id', 'c_up_dag', 'c_up', -1.)\n system.add_to_hamiltonian('id', 'id', 'c_down', 'c_down_dag', -1.)\n system.add_to_hamiltonian('id', 'id', 'c_down_dag', 'c_down', -1.)\n system.add_to_hamiltonian('u', 'id', 'id', 'id', self.U)\n system.add_to_hamiltonian('id', 'u', 'id', 'id', self.U)\n system.add_to_hamiltonian('id', 'id', 'u', 'id', self.U)\n system.add_to_hamiltonian('id', 'id', 'id', 'u', self.U)","def addEdge(self, hub, gene, mi):\n hubid = self.internName(hub)\n geneid = self.internName(gene)\n self.supportArray[hubid, geneid] += 1\n self.miArray[hubid, geneid] += mi","def get_operator(self):\n\n Operator = []\n\n '''\n print('Create H - 150 & 220 GHz')\n ope=[]\n for i in range(self.nfreqs):\n ope.append(self.H150.operands[i])\n for i in range(self.nfreqs):\n ope.append(self.H220.operands[i])\n self.Hboth = BlockRowOperator(ope, new_axisin=0)\n self.H=self.Hboth\n '''\n\n\n\n H_qubic = self.qubic.get_operator()\n R_qubic = ReshapeOperator(H_qubic.shapeout, H_qubic.shape[0])\n Operator.append(R_qubic(H_qubic))\n\n H_planck = self.planck.get_operator()\n R_planck = ReshapeOperator(H_planck.shapeout, H_planck.shape[0])\n Operator.append(R_planck(H_planck))\n return BlockColumnOperator(Operator, axisout=0)","def selectChannel(self,asic,chan, hsmode= 1 ):\n pass","def add(self, newSym):\n if newSym != \"?\":\n self.n = self.n + 1\n self.has[newSym] = 1 + self.has.get(newSym, 0)\n if self.has[newSym] > self.most:\n self.most = self.has[newSym]\n self.mode = newSym","def update_H(self):","def add(self, state_machine):\n\n self.branches.append(state_machine)","def send_control_change(self, cc=0, value=0, ch=None):\n self.send_channel_message(CONTROL_CHANGE, cc, value, ch=ch)","def add_trait(self, t): \n self.trait_index_to_change = t\n self.player.request_payment(self)\n # toggle add button to say delete or something","def addControl(*args):","def addControl(*args):","def addControl(*args):","def addControl(*args):","def send_foot_controller(self, value=0, ch=None):\n self.send_control_change(FOOT_CONTROLLER, value, ch=ch)","async def register(self, ctx:commands.Context, channel_type):\r\n\r\n if not channel_type in [POOL_CHANNEL, SHOP_CHANNEL]:\r\n await ctx.send(f'{channel_type} is not a valid channel type\\n_Channel types:_\\npool\\nshop')\r\n\r\n channel_type = await self.GetChannelType(ctx.guild, ctx.channel.id)\r\n if channel_type == 'none':\r\n await self.AddSpecializedChannel(ctx.guild, ctx.channel.id, channel_type)\r\n await ctx.send(f'<#{ctx.channel.id}> is now a {channel_type}!')\r\n else:\r\n await ctx.send(f'<#{ctx.channel.id}> is already a {channel_type}!')"],"string":"[\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def addchan(channel):\",\n \"def h(self, q0, ctrl=None):\\n self.__add_quantum_gate(kind=HADAMARD, qid=[q0])\\n return self\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def _add_control_channel(self, attrs):\\n _cable_data = {}\\n _cable_data[\\\"crate\\\"] = self._crate\\n _cable_data[\\\"module\\\"] = self._module\\n _cable_data[\\\"channel\\\"] = int(attrs.get('number', \\\"\\\"))\\n _cable_data[\\\"name\\\"] = str(attrs.get('name', \\\"\\\"))\\n self._data.append(_cable_data)\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def H(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.H, qubit_expr)\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def setCh(self, ch):\\n if (self.model == 'TDS'):\\n # according to the manual, RIBanary mode with 2-bit width is\\n # the fastest mode for data transfer.\\n # but I have to think 1-bit transfer ought to be faster.\\n self.write('DATa:SOUrce CH'+str(ch)+\\n '; ENCdg RIBinary; STARt 1; STOP 2500; WIDth 1\\\\n')\\n # obtain vertical scale and offset (for calibration)\",\n \"def add_connector(self):\\n \\n no = len(self.connectors)\\n state = {}\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % no\\n \\n if len(self.connectors)>0:\\n state = self.connectors[-1].get_state()\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % (no)\\n else:\\n if self.mount == self.MOUNT_THT:\\n state[\\\"p_shape\\\"] = Con.SHAPE_HOLE\\n elif self.mount == self.MOUNT_SMD:\\n state[\\\"p_shape\\\"] = Con.SHAPE_PAD\\n \\n c = Con(no)\\n c.set_state(state) \\n \\n self.sch_layers[\\\"pins\\\"].add(c.s_svg)\\n self.pcb_layers[\\\"copper1\\\"].add(c.p_svg)\\n self.connectors.append(c)\",\n \"def connect(self, gate) :\\n self.notifyList.append(gate)\",\n \"def addch(self, stdscr, y, x, text):\\n stdscr.addch(y, x, text, curses.color_pair(self.i))\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def add_hand(self, hand):\\n self.hands = hand\",\n \"def add_chnl(self):\\n\\n # new widget\\n chnl = QWidget()\\n \\n # load elements\\n uic.loadUi(self.chnl_ui, chnl)\\n\\n # connect remove button\\n chnl.rmv.clicked.connect(lambda _: self.rmv_chnl(chnl))\\n\\n # add to list\\n self.chnls.append(chnl)\\n\\n # add to layout\\n self.channels_layout.addWidget(chnl)\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def added(self, comp):\\n\\t\\tpass\",\n \"def add_channel(self, channel):\\n self.task.ai_channels.add_ai_voltage_chan(channel)\",\n \"def __init__(self, *args):\\n moose.HHChannel.__init__(self,*args)\\n self.Ek = VKDR\\n self.Gbar = GKDR\\n self.addField('ion')\\n self.setField('ion','K')\\n self.Xpower = 1 # This will create HHGate instance xGate inside the Na channel\\n #self.Ypower = 0 # This will create HHGate instance yGate inside the Na channel\\n ## Below gates get created after Xpower or Ypower are set to nonzero values\\n ## I don't anymore have to explicitly create these attributes in the class\\n #self.xGate = moose.HHGate(self.path + \\\"/xGate\\\")\\n #self.yGate = moose.HHGate(self.path + \\\"/yGate\\\")\\n self.xGate.A.xmin = VMIN\\n self.xGate.A.xmax = VMAX\\n self.xGate.A.xdivs = NDIVS\\n self.xGate.B.xmin = VMIN\\n self.xGate.B.xmax = VMAX\\n self.xGate.B.xdivs = NDIVS\\n \\n v = VMIN\\n\\n for i in range(NDIVS+1):\\n mtau = calc_KA_mtau(v)\\n self.xGate.A[i] = calc_KA_minf(v)/mtau\\n self.xGate.B[i] = 1.0/mtau\\n v = v + dv\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def one_step(self, x, h):\\n concatHX = torch.cat((x, h), 1)\\n ft = self.sigmoid(self.linearF(concatHX))\\n it = self.sigmoid(self.linearI(concatHX))\\n ct = ft*self.cts[-1] + it*self.tanh(self.linearC(concatHX))\\n #self.ct = ft*self.ct.clone() + it*self.tanh(self.linearC(concatHX))\\n ot = self.sigmoid(self.linearO(concatHX))\\n ht = ot*self.tanh(ct)\\n \\n self.cts.append(ct)\\n \\n return ht\",\n \"def add_switch(self, dpid):\\n\\t\\tself.switches.append(dpid)\",\n \"def one_step(self, x, h):\\n concatHX = torch.cat((x, h), 1)\\n ft = self.sigmoid(self.linearF(concatHX))\\n it = self.sigmoid(self.linearI(concatHX))\\n newCt = ft*self.ct.clone() + it*self.tanh(self.linearC(concatHX))\\n #self.ct = ft*self.ct.clone() + it*self.tanh(self.linearC(concatHX))\\n ot = self.sigmoid(self.linearO(concatHX))\\n ht = ot*self.tanh(newCt)\\n self.ct = newCt\\n \\n return ht\",\n \"def addCardToHand(self, card):\\r\\n self.hand.append(card)\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def addCoupling(ham: Dict[str, Any], name: str, onQubits: Union[int, List[int]], g: float = 1.0) -> None:\\n assert len(onQubits) == 2, \\\"Coupling term should be defined on two qubits.\\\"\\n # Obtain the system energy level.\\n if isinstance(ham[\\\"circuit\\\"][\\\"sys_level\\\"], int):\\n d = ham[\\\"circuit\\\"][\\\"sys_level\\\"]\\n # Construct matrices.\\n matrices = [Operator.destroy(d), Operator.create(d)]\\n matricesHc = [Operator.create(d), Operator.destroy(d)]\\n elif isinstance(ham[\\\"circuit\\\"][\\\"sys_level\\\"], list):\\n sysLevel = ham[\\\"circuit\\\"][\\\"sys_level\\\"]\\n matrices = [Operator.destroy(sysLevel[onQubits[0]]), Operator.create(sysLevel[onQubits[1]])]\\n matricesHc = [Operator.create(sysLevel[onQubits[0]]), Operator.destroy(sysLevel[onQubits[1]])]\\n # Add drift terms\\n addDrift(ham, f\\\"{name}\\\", onQubits=onQubits, matrices=matrices, amp=g)\\n addDrift(ham, f\\\"{name}(hc)\\\", onQubits=onQubits, matrices=matricesHc, amp=g)\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def _add_switch(self, switchdesc):\\n # Check switch definition parameters\\n switch_attributes = list(switchdesc.keys())\\n if not set(switch_attributes).issubset(self.switch_attributes):\\n raise ValueError(\\n \\\"Switch definition: '{0}' defined in '{1}' is not supported. \\\"\\n \\\"Supported switch parameters are '{2}'.\\\".format(\\n json.dumps(switchdesc, indent=2), self._xmlfile,\\n self.switch_attributes))\\n for mandatory_parameter in self.switch_attributes[:2]:\\n if mandatory_parameter not in switch_attributes:\\n raise ValueError(\\n \\\"A '{0}' parameter is required in switch definition: \\\"\\n \\\"'{1}' defined in '{2}'.\\\".format(\\n mandatory_parameter, json.dumps(switchdesc, indent=2),\\n self._xmlfile))\\n\\n # Check the name of the switch is not already reserved\\n switch_name = switchdesc[self.switch_attributes[0]][0]\\n if switch_name in self._switches:\\n raise ValueError(\\n \\\"The switch name '{0}' defined in '{1}' is \\\"\\n \\\"already used.\\\".format(switch_name, self._xmlfile))\\n\\n # Create the switch control\\n switch_paths = {}\\n for pathdesc in switchdesc[self.switch_attributes[1]]:\\n path_name = pathdesc[self.switch_path[0]][0]\\n path_boxes = [box[self.unit_attributes[0]]\\n for box in pathdesc[self.switch_path[1]]]\\n switch_paths[path_name] = path_boxes\\n switch_keys = list(switch_paths.keys())\\n control = controls[\\\"Enum\\\"](\\n choices=tuple(switch_keys),\\n switch_name=switch_name,\\n desc=(\\\"Switch between paths '{0}:{1}' defined in pipeline '{2}'\\\"\\n \\\".\\\".format(switch_name, \\\"-\\\".join(switch_keys), self.id)))\\n setattr(self.inputs, switch_name, control)\\n self._switches[switch_name] = switch_paths\\n control.add_observer(\\\"value\\\", self._update_activation)\\n control.value = switch_keys[0]\",\n \"def commit_chow(\\n self,\\n new_tile: tiles.Tile,\\n tile1: tiles.Tile,\\n tile2: tiles.Tile):\\n\\n self.exposed_parts.append(Chow([new_tile, tile1, tile2], False))\\n self.concealed_part.subtract([tile1, tile2])\\n # self.update()\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def add_card_to_hand(self, card):\\n self.hand.append(card)\",\n \"def _add_cmd(self, cmd):\\n if cmd.gate == Allocate:\\n self._active_qubits += 1\\n elif cmd.gate == Deallocate:\\n self._active_qubits -= 1\\n elif cmd.gate == Measure:\\n for qureg in cmd.qubits:\\n for qubit in qureg:\\n self.main_engine.set_measurement_result(qubit, 0)\\n elif self._is_rotation(cmd):\\n self._num_rotations += 1\\n self._rotations.append(self._decompose_rotation(cmd))\",\n \"def add_connection(self, house):\\n if house not in self.connections and house.max_output < self.capacity:\\n self.connections.append(house)\\n self.capacity = self.capacity - house.max_output\\n house.connected_battery = self.id\\n # else:\\n # print(\\\"Battery does not have enough capacity to connect this house\\\")\\n # self.reach_capacity = True\",\n \"def Set_Meas_Additional(self, mode, state, ch=1):\\n self.write(f':MEAS{ch}:ADD {mode} {state}')\",\n \"def add_neurone(self, couche, nbr=1):\\n if self.control == 0:\\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\\n self.couche[couche] += nbr\\n else:\\n print(\\\"Le réseau est deja créé, vous en pouvez plus le modifier\\\")\",\n \"def hkdr_hf(female, age, bmi, hba1c, acr, hb, chdHist):\\n baseSurv = HKDR_HF[\\\"male_sm\\\"]\\n if female:\\n baseSurv = HKDR_HF[\\\"female_sm\\\"]\\n xFeat = np.array([clean_age(age),\\n clean_bmi(bmi),\\n clean_hba1c(hba1c),\\n np.log10(1+clean_acr(acr)),\\n clean_hb(hb),\\n chdHist])\\n return cox_surv(xFeat,\\n HKDR_HF[\\\"coef\\\"],\\n baseSurv,\\n HKDR_HF[\\\"const\\\"],\\n HKDR_HF[\\\"shrink\\\"])\",\n \"def addOp(self, op):\\n self.operations << op\",\n \"def addChar(self, char):\\n self.guessedChars.append(char)\",\n \"def add_power(self, power):\\n\\n self.powers.append(power)\",\n \"def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\\n if q_args is None and c_args is None:\\n raise GateError(\\\"Gate needs at least one quantum argument or classical argument\\\")\\n if isinstance(gate, CompositeGate):\\n if mapping is None:\\n raise GateError(\\\"Must provide arguments mapping for composite gate inside a composite gate.\\\")\\n else:\\n inv_mappimg = dict()\\n for key, value in mapping.items():\\n inv_mappimg[value] = key\\n if gate is self:\\n gates = gate.copy.gates\\n else:\\n gates = gate.gates\\n for g in gates:\\n new_q_args = None\\n new_c_args = None\\n if g[1] is not None:\\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\\n if g[2] is not None:\\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\\n self.add_gate(gate=g[0], q_args=new_q_args,\\n c_args=new_c_args, params=g[3])\\n else:\\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\\n raise GateError(\\\"Gate must be either a CompositeGate or a string from: \\\"\\n \\\"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\\\")\\n if q_args is not None:\\n for q_arg in q_args:\\n if q_arg not in self.q_args:\\n self.add_q_arg(q_arg)\\n if c_args is not None:\\n for c_arg in c_args:\\n if c_arg not in self.c_args:\\n self.add_c_arg(c_arg)\\n if params is not None:\\n for param in params:\\n if param not in self.params:\\n self.add_param(param)\\n self._gates.append((gate, q_args, c_args, params))\",\n \"def add_challenger(self, new_challenger, initial_score: int = 0) -> None:\\n self.challengers.append(new_challenger)\\n self.scores[new_challenger] = initial_score\\n self.isOrdered = initial_score == 0 and self.isOrdered\",\n \"def add_card(self, card):\\r\\n self.hand.append(card)\",\n \"def add_cell(self, cell: Cell):\\r\\n assert isinstance(cell, Cell)\\r\\n assert -self.pmax <= cell.gain <= self.pmax\\r\\n\\r\\n self[cell.gain].append(cell)\\r\\n cell.bucket_num = cell.gain + self.pmax\\r\\n if cell.gain > self.max_gain:\\r\\n self.max_gain = cell.gain\",\n \"def add_cogs(self):\\n self.add_cog(Voice(self))\",\n \"def add_child(self, cd, wt: float):\\n self.child.append([cd, wt])\",\n \"def send_breath_controller(self, value=0, ch=None):\\n self.send_control_change(BREATH_CONTROLLER, value, ch=ch)\",\n \"def add_output(self, ch, *, close=True):\\n if self._done:\\n return False\\n\\n self._outs.append((ch, close))\\n return True\",\n \"def cs_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def generate_ising_hamiltonian(gc, cost=100., factor=100.):\\n H = np.zeros([gc.nnodes*gc.ncolors, gc.nnodes*gc.ncolors])\\n # one color per node\\n for i in range(gc.nnodes):\\n for c1 in range(gc.ncolors):\\n for c2 in range(gc.ncolors):\\n if c1 == c2:\\n H[i*gc.ncolors+c1, i*gc.ncolors+c2] = -cost\\n else:\\n H[i*gc.ncolors+c1, i*gc.ncolors+c2] = cost\\n\\n # different color for connected edges\\n for i, j in gc.edges:\\n if i != j:\\n for c in range(gc.ncolors):\\n H[i*gc.ncolors+c, j*gc.ncolors+c] = cost/factor \\n H[j*gc.ncolors+c, i*gc.ncolors+c] = cost/factor \\n return H\",\n \"def addEdge(self, hub, gene, mi):\\n hubid = self.internName(hub)\\n geneid = self.internName(gene)\\n # s1 = self.DBcurs.execute(\\\"SELECT support, totmi FROM edges WHERE gene1=? AND gene2=?\\\", (hubid, geneid))\\n # data = s1.fetchone()\\n # if data == None:\\n # self.DBcurs.execute(\\\"INSERT INTO edges(gene1, gene2, support, totmi) VALUES (?, ?, ?, ?)\\\", (hubid, geneid, 1, mi))\\n # else:\\n # newsupport = data[0] + 1\\n # newmi = data[1] + mi\\n self.DBcurs.execute(\\\"UPDATE edges SET support=support+1, totmi=totmi+? WHERE gene1=? AND gene2=?\\\", (mi, hubid, geneid))\",\n \"def __call__(self, channel):\\n\\n state = list(self.states[-1])\\n state[INPUT_PINS.index(channel)] = GPIO.input(channel)\\n\\n with self.lock:\\n self.states.append(tuple(state))\\n\\n if len(self.states) > MIN_MATCHES:\\n del self.states[0]\\n\\n subsequence = tuple(self.states)\\n\\n if subsequence in self.cw:\\n event = \\\"CW\\\" # ...clockwise motion.\\n elif subsequence in self.ccw:\\n event = \\\"CCW\\\" # ...counter-clockwise motion.\\n else:\\n event = \\\"UNK\\\" # ...not enough data to decide.\\n\\n # Send a motion event to the GUI application...\\n self.socket.sendto(event, address)\\n self.num_events += 1\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def gate_logic(self, pull: str):\\r\\n self._gate_logic = pull\\r\\n self.gate_logic_hist.append(pull)\\r\\n\\r\\n if self.gate_logic_hist[-2] != pull and self._daq:\\r\\n msg = Message(\\\"gate_logic\\\", pull, self.checksum).message_bytes\\r\\n self._daq.asynch.transmit(msg)\",\n \"def do_add_node(self, line=''):\\n self.fibbing.add_node()\",\n \"def draw(self, card):\\n self._cards.append(card) # add card to hand\\n self.value = self._set_value() # determine value\",\n \"def cp(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_P, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def add(self, datapath):\\n self.logger.info(\\\"Adding switch dpid=%s\\\", datapath.id)\\n self.switch[datapath.id] = Switch(self._nmeta, self.logger,\\n self._config, datapath)\\n return 1\",\n \"def addFanIn(self,gate):\\n assert type(gate)==Gate\\n if self.gateType == \\\"INPUT\\\":\\n print \\\"Inputs cannot have a fanIn.\\\"\\n return\\n self.fanIn.append(gate)\\n gate.addFanOut(self)\",\n \"def addPower(self, power):\\n self.powers.append(float(power))\",\n \"def add(self, name, chan_id):\\r\\n self.channels.append(Channel(name, chan_id))\",\n \"def extend_circuit(self, circid=None, hops=None):\\r\\n if circid is None:\\r\\n circid = 0\\r\\n if hops is None:\\r\\n hops = \\\"\\\"\\r\\n plog(\\\"DEBUG\\\", \\\"Extending circuit\\\")\\r\\n lines = self.sendAndRecv(\\\"EXTENDCIRCUIT %d %s\\\\r\\\\n\\\"\\r\\n %(circid, \\\",\\\".join(hops)))\\r\\n tp,msg,_ = lines[0]\\r\\n m = re.match(r'EXTENDED (\\\\S*)', msg)\\r\\n if not m:\\r\\n raise ProtocolError(\\\"Bad extended line %r\\\",msg)\\r\\n plog(\\\"DEBUG\\\", \\\"Circuit extended\\\")\\r\\n return int(m.group(1))\",\n \"def build_glyCB(self, gCBd: Dihedron): # -> None:\\n ...\",\n \"def enable_cl1_direct(self):\\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\\n self.write_versa5(0x18,0x20)\\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\\n self.write_versa5(0x13,0x03) ## Switch to clock\\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew\",\n \"def add_card(self, card):\\n self.hand.append(card)\",\n \"def add_control(operation, num_ctrl_qubits, label):\\n if isinstance(operation, UnitaryGate):\\n # attempt decomposition\\n operation._define()\\n if _control_definition_known(operation, num_ctrl_qubits):\\n return _control_predefined(operation, num_ctrl_qubits)\\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def _add_entanglement_gate(self, gate_method, qubit_1, qubit_2):\\r\\n sig = signature(gate_method)\\r\\n\\r\\n # parametrized gate like a controlled single qubit rotation\\r\\n if 'theta' in sig.parameters:\\r\\n try:\\r\\n gate_method(self.circuit, self.parameters[next(self.indices)], qubit_1, qubit_2)\\r\\n except KeyError:\\r\\n raise ValueError(f'Unsupported two qubit rotation gate')\\r\\n\\r\\n # non-parametrized gate like CNOT\\r\\n else:\\r\\n try:\\r\\n gate_method(self.circuit, qubit_1, qubit_2)\\r\\n except KeyError:\\r\\n raise ValueError(f'Unsupported unparametrized two qubit gate')\",\n \"def addch(self, posy, posx, character, color_pair):\\r\\n if posy < 0 or posy > self.height - 1:\\r\\n return\\r\\n if posx < 0 or posx > self.width - 1:\\r\\n return\\r\\n if posx == self.width - 1 and posy == self.height - 1:\\r\\n return\\r\\n self.win.addch(posy, posx, character, color_pair)\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def addFanOut(self,gate):\\n assert type(gate)==Gate\\n self.fanOut.append(gate)\",\n \"def add(self, h, name, parent=None, action=None, observation=None,\\n particle=None, budget=None, cost=None):\\n history = h[:]\\n\\n # instantiate node\\n if action is not None:\\n n = ActionNode(self.counter, name, history, parent=parent, action_index=action, cost=cost)\\n else:\\n n = BeliefNode(self.counter, name, history, parent=parent, obs_index=observation, budget=budget)\\n\\n if particle is not None:\\n n.add_particle(particle)\\n\\n # add the node to belief tree\\n self.nodes[n.id] = n\\n self.counter += 1\\n\\n # register node as parent's child\\n if parent is not None:\\n parent.add_child(n)\\n return n\",\n \"def _ctrl_hum_set(self, osrs_h):\\n data = osrs_h & 0x7\\n self._bus.write_byte_data(self.addr, self.CTRL_HUM,\\n data)\",\n \"def AddOperation(self, op):\\n self._operations.append(op)\",\n \"def add(self, component):\\n\\n self.append(component)\\n self.sum.Add(component.th1f)\",\n \"def draw_card(self,card):\\n self.hand.append(card)\",\n \"def __call__(self, h_, x):\\n # h_: the concatenation of previous hidden state\\n # and memory cell state\\n # x_i/x: the current input state for input gate\\n # x_f/x: the current input state for forget gate\\n # x_o/x: the current input state for output gate\\n # x_c/x: the current input state for candidate cell\\n with tf.variable_scope(\\n \\\"cell_{}\\\".format(self.scope or \\\"lstm\\\")):\\n x_g, x_c = x\\n h_, c_ = tf.split(h_, 2, -1)\\n\\n h_g = linear(h_, self.d * 3,\\n ln=self.ln, scope=\\\"gate_h\\\")\\n i, f, o = tf.split(\\n tf.sigmoid(x_g + h_g), 3, -1)\\n\\n h_c = linear(h_, self.d,\\n ln=self.ln, scope=\\\"hide_h\\\")\\n h_c = tf.tanh(x_c + h_c)\\n\\n c = i * h_c + f * c_\\n\\n h = o * tf.tanh(c)\\n\\n return tf.concat([h, c], -1)\",\n \"def add_new_header(self, hdr):\\n # if there are any lines in the unchanged-lines buffer, create a \\n # new hunk using them, and add it to the last header.\\n if self.changedlines:\\n self.add_new_hunk()\\n\\n # create a new header and add it to self.stream\\n self.header = header(hdr)\\n fileName = self.header.filename()\\n if fileName in self.modified:\\n self.header.changetype = \\\"M\\\"\\n elif fileName in self.added:\\n self.header.changetype = \\\"A\\\"\\n elif fileName in self.removed:\\n self.header.changetype = \\\"R\\\"\\n self.stream.append(self.header)\",\n \"def add(self, name, command):\",\n \"def add_command(self, name, fct):\\r\\n self.cmds[name] = fct\",\n \"def add_card(self, card):\\n if not isinstance(card, Card):\\n raise TypeError(\\\"'card' must be a card object.\\\")\\n # append new card to list of cards in the hand\\n self.cards.append(card)\\n self.total = card + self.total\\n # aces require a little more work\\n if card.rank == 14:\\n self.soft = True\\n self.num_aces += 1\\n self.num_hard_aces += 1\\n # account for soft hands\\n if self.total > 21 and self.soft:\\n self.total -= 10\\n self.num_hard_aces -= 1\\n self.soft = False\\n # catch the edge case where you're delt 12+ aces\\n if self.total > 21:\\n self.total -= 10\\n self.num_hard_aces -= 1\\n self.soft = False\\n if self.num_hard_aces > 0:\\n self.soft = True\\n if self.total > 21:\\n self.bust = True\",\n \"def register(self, cmd):\\n\\n assert(cmd.name not in self.cmds)\\n \\n data = cmd.data\\n assert(type(data.switches) is dict)\\n \\n self.cmds[cmd.name] = data\",\n \"def add(self, node):\\n cost = self.costfn(node)\\n heapq.heappush(self.heap, (cost, node))\\n self.states[node.state] = node\",\n \"def __add__(G, H):\\n if isinstance(H, Surreal):\\n return Surreal.from_value(G._n + H.n)\\n if isinstance(H, numbers.Number):\\n return Surreal.from_value(G._n + H)\\n if isinstance(H, Game):\\n return super().__add__(H)\\n\\n return NotImplemented\",\n \"def add(self, inp, out):\\n self.curr_node.input_frequencies[inp] += 1\\n if inp not in self.curr_node.children.keys() or out not in self.curr_node.children[inp].keys():\\n node = Node(out)\\n self.curr_node.children[inp][out] = node\\n\\n self.curr_node = self.curr_node.children[inp][out]\\n self.curr_node.frequency += 1\",\n \"def set_hamiltonian(self, system):\\n system.clear_hamiltonian()\\n if 'bh' in system.left_block.operators.keys():\\n system.add_to_hamiltonian(left_block_op='bh')\\n if 'bh' in system.right_block.operators.keys():\\n system.add_to_hamiltonian(right_block_op='bh')\\n system.add_to_hamiltonian('c_up', 'c_up_dag', 'id', 'id', -1.)\\n system.add_to_hamiltonian('c_up_dag', 'c_up', 'id', 'id', -1.)\\n system.add_to_hamiltonian('c_down', 'c_down_dag', 'id', 'id', -1.)\\n system.add_to_hamiltonian('c_down_dag', 'c_down', 'id', 'id', -1.)\\n system.add_to_hamiltonian('id', 'c_up', 'c_up_dag', 'id', -1.)\\n system.add_to_hamiltonian('id', 'c_up_dag', 'c_up', 'id', -1.)\\n system.add_to_hamiltonian('id', 'c_down', 'c_down_dag', 'id', -1.)\\n system.add_to_hamiltonian('id', 'c_down_dag', 'c_down', 'id', -1.)\\n system.add_to_hamiltonian('id', 'id', 'c_up', 'c_up_dag', -1.)\\n system.add_to_hamiltonian('id', 'id', 'c_up_dag', 'c_up', -1.)\\n system.add_to_hamiltonian('id', 'id', 'c_down', 'c_down_dag', -1.)\\n system.add_to_hamiltonian('id', 'id', 'c_down_dag', 'c_down', -1.)\\n system.add_to_hamiltonian('u', 'id', 'id', 'id', self.U)\\n system.add_to_hamiltonian('id', 'u', 'id', 'id', self.U)\\n system.add_to_hamiltonian('id', 'id', 'u', 'id', self.U)\\n system.add_to_hamiltonian('id', 'id', 'id', 'u', self.U)\",\n \"def addEdge(self, hub, gene, mi):\\n hubid = self.internName(hub)\\n geneid = self.internName(gene)\\n self.supportArray[hubid, geneid] += 1\\n self.miArray[hubid, geneid] += mi\",\n \"def get_operator(self):\\n\\n Operator = []\\n\\n '''\\n print('Create H - 150 & 220 GHz')\\n ope=[]\\n for i in range(self.nfreqs):\\n ope.append(self.H150.operands[i])\\n for i in range(self.nfreqs):\\n ope.append(self.H220.operands[i])\\n self.Hboth = BlockRowOperator(ope, new_axisin=0)\\n self.H=self.Hboth\\n '''\\n\\n\\n\\n H_qubic = self.qubic.get_operator()\\n R_qubic = ReshapeOperator(H_qubic.shapeout, H_qubic.shape[0])\\n Operator.append(R_qubic(H_qubic))\\n\\n H_planck = self.planck.get_operator()\\n R_planck = ReshapeOperator(H_planck.shapeout, H_planck.shape[0])\\n Operator.append(R_planck(H_planck))\\n return BlockColumnOperator(Operator, axisout=0)\",\n \"def selectChannel(self,asic,chan, hsmode= 1 ):\\n pass\",\n \"def add(self, newSym):\\n if newSym != \\\"?\\\":\\n self.n = self.n + 1\\n self.has[newSym] = 1 + self.has.get(newSym, 0)\\n if self.has[newSym] > self.most:\\n self.most = self.has[newSym]\\n self.mode = newSym\",\n \"def update_H(self):\",\n \"def add(self, state_machine):\\n\\n self.branches.append(state_machine)\",\n \"def send_control_change(self, cc=0, value=0, ch=None):\\n self.send_channel_message(CONTROL_CHANGE, cc, value, ch=ch)\",\n \"def add_trait(self, t): \\n self.trait_index_to_change = t\\n self.player.request_payment(self)\\n # toggle add button to say delete or something\",\n \"def addControl(*args):\",\n \"def addControl(*args):\",\n \"def addControl(*args):\",\n \"def addControl(*args):\",\n \"def send_foot_controller(self, value=0, ch=None):\\n self.send_control_change(FOOT_CONTROLLER, value, ch=ch)\",\n \"async def register(self, ctx:commands.Context, channel_type):\\r\\n\\r\\n if not channel_type in [POOL_CHANNEL, SHOP_CHANNEL]:\\r\\n await ctx.send(f'{channel_type} is not a valid channel type\\\\n_Channel types:_\\\\npool\\\\nshop')\\r\\n\\r\\n channel_type = await self.GetChannelType(ctx.guild, ctx.channel.id)\\r\\n if channel_type == 'none':\\r\\n await self.AddSpecializedChannel(ctx.guild, ctx.channel.id, channel_type)\\r\\n await ctx.send(f'<#{ctx.channel.id}> is now a {channel_type}!')\\r\\n else:\\r\\n await ctx.send(f'<#{ctx.channel.id}> is already a {channel_type}!')\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.593194","0.55942816","0.55546916","0.5312524","0.53084034","0.5280236","0.5275652","0.52625185","0.5245822","0.52261335","0.522333","0.5186619","0.5178953","0.5166998","0.5163261","0.51590973","0.5119946","0.50677484","0.5060551","0.50518656","0.50383717","0.5033286","0.50279593","0.5003035","0.50018454","0.4963021","0.49535137","0.49384537","0.49383092","0.49142802","0.487261","0.4820035","0.48044905","0.47951812","0.4787159","0.47818425","0.47813693","0.47812063","0.47810772","0.4768232","0.47599664","0.47524312","0.47409052","0.47391036","0.47257894","0.47179222","0.47126114","0.47108316","0.47099152","0.4706234","0.46908876","0.46900263","0.46890604","0.4688107","0.46803436","0.4677579","0.46771628","0.4663716","0.46601486","0.46479124","0.46454298","0.46450448","0.4643814","0.4643415","0.4642533","0.46407485","0.46394363","0.4634796","0.46329042","0.46267867","0.46113572","0.46083248","0.45970616","0.45931423","0.45687726","0.4564739","0.4560787","0.45594314","0.45419517","0.45408234","0.4538661","0.4538648","0.45339116","0.45299047","0.45287058","0.4528358","0.45278016","0.4515556","0.4512599","0.45121315","0.45118698","0.45103198","0.45085078","0.44981858","0.4496927","0.4496927","0.4496927","0.4496927","0.4490925","0.44882768"],"string":"[\n \"0.593194\",\n \"0.55942816\",\n \"0.55546916\",\n \"0.5312524\",\n \"0.53084034\",\n \"0.5280236\",\n \"0.5275652\",\n \"0.52625185\",\n \"0.5245822\",\n \"0.52261335\",\n \"0.522333\",\n \"0.5186619\",\n \"0.5178953\",\n \"0.5166998\",\n \"0.5163261\",\n \"0.51590973\",\n \"0.5119946\",\n \"0.50677484\",\n \"0.5060551\",\n \"0.50518656\",\n \"0.50383717\",\n \"0.5033286\",\n \"0.50279593\",\n \"0.5003035\",\n \"0.50018454\",\n \"0.4963021\",\n \"0.49535137\",\n \"0.49384537\",\n \"0.49383092\",\n \"0.49142802\",\n \"0.487261\",\n \"0.4820035\",\n \"0.48044905\",\n \"0.47951812\",\n \"0.4787159\",\n \"0.47818425\",\n \"0.47813693\",\n \"0.47812063\",\n \"0.47810772\",\n \"0.4768232\",\n \"0.47599664\",\n \"0.47524312\",\n \"0.47409052\",\n \"0.47391036\",\n \"0.47257894\",\n \"0.47179222\",\n \"0.47126114\",\n \"0.47108316\",\n \"0.47099152\",\n \"0.4706234\",\n \"0.46908876\",\n \"0.46900263\",\n \"0.46890604\",\n \"0.4688107\",\n \"0.46803436\",\n \"0.4677579\",\n \"0.46771628\",\n \"0.4663716\",\n \"0.46601486\",\n \"0.46479124\",\n \"0.46454298\",\n \"0.46450448\",\n \"0.4643814\",\n \"0.4643415\",\n \"0.4642533\",\n \"0.46407485\",\n \"0.46394363\",\n \"0.4634796\",\n \"0.46329042\",\n \"0.46267867\",\n \"0.46113572\",\n \"0.46083248\",\n \"0.45970616\",\n \"0.45931423\",\n \"0.45687726\",\n \"0.4564739\",\n \"0.4560787\",\n \"0.45594314\",\n \"0.45419517\",\n \"0.45408234\",\n \"0.4538661\",\n \"0.4538648\",\n \"0.45339116\",\n \"0.45299047\",\n \"0.45287058\",\n \"0.4528358\",\n \"0.45278016\",\n \"0.4515556\",\n \"0.4512599\",\n \"0.45121315\",\n \"0.45118698\",\n \"0.45103198\",\n \"0.45085078\",\n \"0.44981858\",\n \"0.4496927\",\n \"0.4496927\",\n \"0.4496927\",\n \"0.4496927\",\n \"0.4490925\",\n \"0.44882768\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.66249025"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81748,"cells":{"query":{"kind":"string","value":"add CS gate (controlled S gate)."},"document":{"kind":"string","value":"def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def BCS(self, value):\n if self.reg.C:\n self.reg.PC += value","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def add_connector(self):\n \n no = len(self.connectors)\n state = {}\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % no\n \n if len(self.connectors)>0:\n state = self.connectors[-1].get_state()\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % (no)\n else:\n if self.mount == self.MOUNT_THT:\n state[\"p_shape\"] = Con.SHAPE_HOLE\n elif self.mount == self.MOUNT_SMD:\n state[\"p_shape\"] = Con.SHAPE_PAD\n \n c = Con(no)\n c.set_state(state) \n \n self.sch_layers[\"pins\"].add(c.s_svg)\n self.pcb_layers[\"copper1\"].add(c.p_svg)\n self.connectors.append(c)","def circuitSat(C):","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def add(self, sgid, other, proto_spec, direction=\"in\"):\n # returns bool\n # AuthorizeSecurityGroupIngress, AuthorizeSecurityGroupEgress\n if direction == \"in\":\n api = \"AuthorizeSecurityGroupIngress\"\n elif direction == \"out\":\n api = \"AuthorizeSecurityGroupEgress\"\n else:\n raise ValueError(\"direction must be one of ('in', 'out')\")\n return self.modify(api, sgid, other, proto_spec)","def add_state(self, name='Ti', c=2000):\n assert isinstance(name, str), 'name must be a string type'\n if name in self.sta.keys():\n raise Exception('State already defined')\n state = State(c=c, name=name)\n self.sta[name] = state\n self.nodes[name] = state\n self.rc.add_node(state)","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def bcs(self, arg):\n\n self.pc += arg if self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def csw(self, q0, q1, q2, ctrl=None):\n self.cx(q2,q1,ctrl=ctrl).ccx(q0,q1,q2,ctrl=ctrl).cx(q2,q1,ctrl=ctrl)\n return self","def assemble_circuit(\n self,\n circuit: Circuit,\n blocks: list[int],\n psols: list[list[tuple[Circuit, float]]],\n pts: list[CircuitPoint],\n ) -> Circuit:\n circuit_gates = [\n CircuitGate(psol_list[b][0])\n for b, psol_list\n in zip(blocks, psols)\n ]\n locations = [circuit[pt].location for pt in pts]\n operations = [\n Operation(cg, loc, cg._circuit.params)\n for cg, loc\n in zip(circuit_gates, locations)\n ]\n copied_circuit = circuit.copy()\n copied_circuit.batch_replace(pts, operations)\n return copied_circuit","def local_addsd_ccode(node):\r\n if isinstance(node.op, sparse.AddSD) and theano.config.cxx:\r\n new_node = AddSD_ccode(format=node.inputs[0].type.format)(*node.inputs)\r\n return [new_node]\r\n return False","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def add(self, y):\n return circuit.add(self, y)","def manage_addCASSSO(self, id='sso', REQUEST=None):\n\n id = 'sso'\n ob = CASSSO()\n ob.id = id\n self._setObject(id, ob)\n if REQUEST is not None:\n return self.manage_main(self, REQUEST)","def add(self, p, s, node) -> None:\n self.place.append(p)\n self.station.append(s)\n self.pi.append(node.pi[p, s] if p != float('inf') else float('inf'))\n self.noncoverage.append(node.noncoverage.left + node.noncoverage.right)\n self.cost.append(node.cost)\n self.delay.append(node.delay)\n self.step.append(node.key)","def test_scalar_coeff_cc():\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\n kappa = Symbol('kappa', real=True)\n a1 = Destroy(hs=hs_1)\n a2 = Destroy(hs=hs_2)\n\n jc_expr = (\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\n )\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == I * kappa * OperatorPlusMinusCC(\n a1.dag() * a2, sign=-1\n )\n expanded = simplified.doit()\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def __init__(self, input, output) :\n Gate.__init__(self, [input], output)","def coadd(self, step_index):\n if self.drip_config is not None:\n if ('boresight' in self.drip_cal_config\n and 'SLIT' in self.drip_cal_config['boresight']):\n self.current[step_index].set_value('skip_coadd', True)","def scc (self, reset=False):\n if reset or (self.__scc is None):\n self.tarjan(reset)\n return self.__scc","def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\n if q_args is None and c_args is None:\n raise GateError(\"Gate needs at least one quantum argument or classical argument\")\n if isinstance(gate, CompositeGate):\n if mapping is None:\n raise GateError(\"Must provide arguments mapping for composite gate inside a composite gate.\")\n else:\n inv_mappimg = dict()\n for key, value in mapping.items():\n inv_mappimg[value] = key\n if gate is self:\n gates = gate.copy.gates\n else:\n gates = gate.gates\n for g in gates:\n new_q_args = None\n new_c_args = None\n if g[1] is not None:\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\n if g[2] is not None:\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\n self.add_gate(gate=g[0], q_args=new_q_args,\n c_args=new_c_args, params=g[3])\n else:\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\n raise GateError(\"Gate must be either a CompositeGate or a string from: \"\n \"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\")\n if q_args is not None:\n for q_arg in q_args:\n if q_arg not in self.q_args:\n self.add_q_arg(q_arg)\n if c_args is not None:\n for c_arg in c_args:\n if c_arg not in self.c_args:\n self.add_c_arg(c_arg)\n if params is not None:\n for param in params:\n if param not in self.params:\n self.add_param(param)\n self._gates.append((gate, q_args, c_args, params))","def n_cs(self):\n pass","def pk_cs(self, snr=30, headroom = 0):\n # Initialize\n self.pk = np.zeros((self.n_waves, len(self.controls.k0)), dtype=np.csingle)\n # loop over frequencies\n bar = tqdm(total = len(self.controls.k0), desc = 'Calculating Constrained Optim.')\n # print(self.pk.shape)\n for jf, k0 in enumerate(self.controls.k0):\n # get the scaled version of the propagating directions\n k_vec = k0 * self.dir\n # Form the sensing matrix\n h_mtx = np.exp(1j*self.receivers.coord @ k_vec.T)\n H = h_mtx.astype(complex)\n # measured data\n pm = self.pres_s[:,jf].astype(complex)\n # Performing constrained optmization cvxpy\n x_cvx = cp.Variable(h_mtx.shape[1], complex = True)\n # Create the problem\n epsilon = 10**(-(snr-headroom)/10)\n objective = cp.Minimize(cp.pnorm(x_cvx, p=1))\n constraints = [cp.pnorm(pm - cp.matmul(H, x_cvx), p=2) <= epsilon]#[H*x == pm]\n # Create the problem and solve\n problem = cp.Problem(objective, constraints)\n problem.solve(solver=cp.SCS, verbose=True) \n self.pk[:,jf] = x_cvx.value\n bar.update(1)\n bar.close()\n return self.pk","def build_scl(net, ovs, src, dst, next_hop, match=None):\n info(\"### Build service classifier, source:{}, next_hop:{}\\n\".format(src,\n next_hop))\n in_port = get_ofport(\"{}-{}\".format(ovs, src))\n out_port = get_ofport(\"{}-{}\".format(ovs, next_hop))\n ip_dst = net[dst].IP()\n check_output(\n split(\n \"sudo ovs-ofctl add-flow {sw} \\\"nw_dst={ip_dst},icmp,in_port={in_port},actions=output={out_port}\\\"\".format(\n **{\"sw\": ovs, \"in_port\": in_port, \"out_port\": out_port,\n \"ip_dst\": ip_dst}\n )\n )\n )\n ret = check_output(split(\"sudo ovs-ofctl dump-flows {}\".format(ovs)))\n info(\"### Flow table of the switch after adding SFP:\\n\")\n print(ret)","def test_simple_cc():\n hs_c = LocalSpace('c', dimension=3)\n hs_q = LocalSpace('q1', basis=('g', 'e'))\n Delta_1 = Symbol('Delta_1')\n Omega_1 = Symbol('Omega_1')\n g_1 = Symbol('g_1')\n a = Destroy(hs=hs_c)\n a_dag = Create(hs=hs_c)\n sig_p = LocalSigma('e', 'g', hs=hs_q)\n sig_m = LocalSigma('g', 'e', hs=hs_q)\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\n assert (\n srepr(simplified.term)\n == \"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \"\n \"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \"\n \"basis=('g', 'e')))), sign=-1)\"\n )\n expanded = simplified.doit()\n assert expanded == jc_expr","def cy(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CY(), target=[control, target])","def __init__(self, input0, input1, output) :\n Gate.__init__(self, [input0,input1], output)","def csNew(self, an):\n\t\treturn ca - an/self.GA","def construct_circuit(self):\n return self._circuit","def coi(self, s):\n return 2 ** 0.5 * s","def iadd(state: State) -> State:\n cell = state.array[state.index] or 0\n return state._replace(acc=state.acc + cell)","def bcc(self, arg):\n\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def CL(self):","def enc_add_const(pub, m, c):\n # Similiar to enc add\n add_const_result = m * powmod(pub.g, c, pub.n_sq) % pub.n_sq\n return add_const_result","def credit(self, value):\n self._negative_value_raises_an_error(value)\n self.operations.insert(value);","def AddSpecialPoint(self, cp):\n return _gmat_py.SolarSystem_AddSpecialPoint(self, cp)","def csb(self):\n\n def myfunc(incident_energy):\n return XrayLibWrap_Energy(self.Z, \"csb\", incident_energy)\n\n return myfunc","def _write_circuit(self, feature_vector_index):\n # grab the feature vector\n feature_vector = self.data.data[feature_vector_index]\n\n # compute the indices to put gates at\n inds = [x for x in range(len(feature_vector)) if feature_vector[x] == 1]\n\n # write the circuit\n self.circuits[feature_vector_index].add_layer(H)\n self.circuits[feature_vector_index].add_at(Z, inds)\n\n # TODO: all encoding classes will need this method.\n # TODO: make a BaseEncoding that implements this","def connect(self, gate) :\n self.notifyList.append(gate)","def _cmplx_add_ ( s , o ) :\n return o + complex ( s )","def actual_causation():\n # fmt: off\n tpm = np.array([\n [1, 0, 0, 0],\n [0, 1, 0, 0],\n [0, 1, 0, 0],\n [0, 0, 0, 1],\n ])\n cm = np.array([\n [1, 1],\n [1, 1],\n ])\n # fmt: on\n return Network(tpm, cm, node_labels=('OR', 'AND'))","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def _template_circuit(self, amp_param) -> QuantumCircuit:\n gate = Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param])\n\n circuit = QuantumCircuit(1)\n circuit.append(gate, (0,))\n circuit.measure_active()\n\n return circuit","def local_inplace_addsd_ccode(node):\r\n if isinstance(node.op, sparse.AddSD) and theano.config.cxx:\r\n out_dtype = scalar.upcast(*node.inputs)\r\n if out_dtype != node.inputs[1].dtype:\r\n return\r\n new_node = AddSD_ccode(format=node.inputs[0].type.format,\r\n inplace=True)(*node.inputs)\r\n return [new_node]\r\n return False","def block(self, mcs):\n\n self.oracle.add_clause([self.sels[cl_id - 1] for cl_id in mcs])","def add(num1, num2, Cin):\n Cin=0\n l2=[]\n final=\"\"\n\n \"\"\"Using for loop for starting addition from the last indexed number\"\"\"\n for i in range(len(num1)-1,-1,-1):\n bit1=num1[i]#storing each indexed() value of num1 in bit1\n bit2=num2[i]#storing each indexed() value of num2 in bit2\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\n Cin=Cout#declaring cout as cin for next bit addition\n l2.append(SUM)#adding SUM to l2\n l3=l2[::-1]##reversing the value of l2\n final+=str(l2[-1])#converting the list value to string\n final1=final[::-1]#reversing string value\n return final1 #returning the binary addition as string","def _control_predefined(operation, num_ctrl_qubits):\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\n if num_ctrl_qubits == 1:\n import qiskit.extensions.standard.cx\n cgate = qiskit.extensions.standard.cx.CnotGate()\n else:\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n elif operation.name == 'y':\n import qiskit.extensions.standard.cy\n cgate = qiskit.extensions.standard.cy.CyGate()\n elif operation.name == 'z':\n import qiskit.extensions.standard.cz\n cgate = qiskit.extensions.standard.cz.CzGate()\n elif operation.name == 'h':\n import qiskit.extensions.standard.ch\n cgate = qiskit.extensions.standard.ch.CHGate()\n elif operation.name in {'rx', 'ry', 'rz'}:\n if operation.name == 'rx':\n import qiskit.extensions.standard.crx\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\n elif operation.name == 'ry':\n import qiskit.extensions.standard.cry\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\n else: # operation.name == 'rz'\n import qiskit.extensions.standard.crz\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\n if num_ctrl_qubits == 1:\n return cgate\n else:\n # only predefined for one control qubit\n return cgate.control(num_ctrl_qubits - 1)\n elif operation.name == 'swap':\n import qiskit.extensions.standard.cswap\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\n elif operation.name == 'u1':\n import qiskit.extensions.standard.cu1\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\n elif operation.name == 'u3':\n import qiskit.extensions.standard.cu3\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\n elif operation.name == 'cx':\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n else:\n raise QiskitError('No standard controlled gate for \"{}\"'.format(\n operation.name))\n return cgate","def add_comp(self, name, ctype):\n\n name = self.name + '.' + name\n\n assert name not in self.components, 'A component named \\'{}\\' already exists for node \\'{}\\''.format(\n name, self.name)\n\n try:\n cls = co.str_to_comp(ctype)\n except AttributeError:\n try:\n cls = rc.str_to_comp(ctype)\n except AttributeError:\n cls = None\n\n if cls:\n obj = cls(name=name,\n temperature_driven=self.temperature_driven,\n repr_days=self.repr_days)\n else:\n raise ValueError(\n \"%s is not a valid class name! (component is %s, in node %s)\" % (\n ctype, name, self.name))\n\n self.logger.info('Component {} added to {}'.format(name, self.name))\n\n self.components[name] = obj","def _store_cf(cl, context, new_cf):\n try:\n cl.add(new_cf, key=context)\n except TypeError:\n print(type(cl))\n raise","def append_user_gate(self, user_gate):\n self.translation['g_sect'].append(user_gate)","def addControlPoints(self, *controlpoints):\n self.controlpoints.extend(controlpoints)\n self.update()","def modelCS(self,ht=None,hf=None):\n if ht is not None:\n hf = time2freq(ht)\n cs,a,b,c = make_model_cs(hf, self.s0, self.bw, self.ref_freq)\n \n return cs","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def update_control(self):\n self._control_ctr += 0x01","def translate(self):\n self._marshall_gatedefs()\n self._marshall_regdefs()\n\n if not self.circuit:\n self._create_quantum_circuit()\n\n for entry in self.nuq2_ast['c_sect']:\n try:\n op_type = entry['type']\n if op_type is ASTType.OP:\n starting_circuit_size = self.circuit.size()\n self._op_append(entry, self.circuit.qregs, self.circuit.cregs,\n self.circuit.qubits, self.circuit.clbits)\n if self.circuit.size() == starting_circuit_size:\n raise Ast2CircOpNotFoundException(section='c_sect',\n entry=entry)\n elif op_type is ASTType.BARRIER:\n self._barrier_append(entry, self.circuit.qregs, self.circuit.qubits)\n elif op_type is ASTType.MEASURE:\n self._measure_append(entry, self.circuit.qregs, self.circuit.cregs,\n self.circuit.qubits, self.circuit.clbits)\n except NameError as ex:\n raise Ast2CircTranslationException(section='c_sect',\n entry=entry,\n prev_ex=ex)\n\n else: # It's nothing we care about in this stage\n pass\n return self","def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])","def gate(self):\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)","def BVS(self, value):\n if self.reg.V:\n self.reg.PC += value","def add_road(ccTremb):\n pass","def add_stcs(stc1, stc2):\n vertices = [np.union1d(stc1.vertices[0], stc2.vertices[0]),\n np.union1d(stc1.vertices[1], stc2.vertices[1])]\n assert stc1.data.shape[1] == stc2.data.shape[1]\n assert stc1.tmin == stc2.tmin\n assert stc1.tstep == stc2.tstep\n\n data = np.zeros((len(vertices[0]) + len(vertices[1]), stc1.data.shape[1]))\n i = 0\n\n # Left hemisphere\n for vert in vertices[0]:\n if vert in stc1.vertices[0]:\n data[[i]] += stc1.lh_data[stc1.vertices[0] == vert]\n if vert in stc2.vertices[0]:\n data[[i]] += stc2.lh_data[stc2.vertices[0] == vert]\n i += 1\n\n # Right hemisphere\n for vert in vertices[1]:\n if vert in stc1.vertices[1]:\n data[[i]] += stc1.rh_data[stc1.vertices[1] == vert]\n if vert in stc2.vertices[1]:\n data[[i]] += stc2.rh_data[stc2.vertices[1] == vert]\n i += 1\n\n return mne.SourceEstimate(data, vertices, tmin=stc1.tmin, tstep=stc1.tstep)","def _c2c_cost(sclst, eclst):\n def _c2c(point):\n _c_sum = 0\n for pt in eclst.points:\n _c_sum += point.frequency(pt)\n return _c_sum\n return int(sum(map(_c2c, sclst.points)))","def short_circ():\n \n set_mode(mode_cv)\n time.sleep(.250)\n set_CV_volts(0.1)\n time.sleep(.250)\n \n sc_vals = get_input_values()\n sc_data_point = data_point(sc_vals)\n jsc = sc_data_point[4]\n print('Short circuit current: ', jsc)\n write_data_tofile(sc_data_point)\n\n return jsc","def uCSIsCatCc(code):\n ret = libxml2mod.xmlUCSIsCatCc(code)\n return ret","def cs(self):\n\n def myfunc(incident_energy):\n return XrayLibWrap_Energy(self.Z, \"cs\", incident_energy)\n\n return myfunc","def cp(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_P, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def add_control(operation, num_ctrl_qubits, label):\n if isinstance(operation, UnitaryGate):\n # attempt decomposition\n operation._define()\n if _control_definition_known(operation, num_ctrl_qubits):\n return _control_predefined(operation, num_ctrl_qubits)\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)","def gate_mfcc(recurrent_net, sample_input):\n length = sample_input.shape[1]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\n select = sigmoid(select)\n return np.sum(select * score) / np.sum(select)","def add_cogs(self):\n self.add_cog(Voice(self))","def test_circuit_generation_from_sec(self):\n\n backend = CrossResonanceHamiltonianBackend()\n\n expr = cr_hamiltonian.CrossResonanceHamiltonian(\n qubits=(0, 1),\n flat_top_widths=[500],\n unit=\"ns\",\n amp=0.1,\n sigma=20,\n risefall=2,\n )\n\n nearlest_16 = 576\n\n with pulse.build(default_alignment=\"left\", name=\"cr\") as ref_cr_sched:\n pulse.play(\n pulse.GaussianSquare(\n nearlest_16,\n amp=0.1,\n sigma=20,\n width=500,\n ),\n pulse.ControlChannel(0),\n )\n pulse.delay(nearlest_16, pulse.DriveChannel(0))\n pulse.delay(nearlest_16, pulse.DriveChannel(1))\n\n cr_gate = circuit.Gate(\"cr_gate\", num_qubits=2, params=[500])\n expr_circs = expr.circuits(backend)\n\n x0_circ = QuantumCircuit(2, 1)\n x0_circ.append(cr_gate, [0, 1])\n x0_circ.h(1)\n x0_circ.measure(1, 0)\n\n x1_circ = QuantumCircuit(2, 1)\n x1_circ.x(0)\n x1_circ.append(cr_gate, [0, 1])\n x1_circ.h(1)\n x1_circ.measure(1, 0)\n\n y0_circ = QuantumCircuit(2, 1)\n y0_circ.append(cr_gate, [0, 1])\n y0_circ.sdg(1)\n y0_circ.h(1)\n y0_circ.measure(1, 0)\n\n y1_circ = QuantumCircuit(2, 1)\n y1_circ.x(0)\n y1_circ.append(cr_gate, [0, 1])\n y1_circ.sdg(1)\n y1_circ.h(1)\n y1_circ.measure(1, 0)\n\n z0_circ = QuantumCircuit(2, 1)\n z0_circ.append(cr_gate, [0, 1])\n z0_circ.measure(1, 0)\n\n z1_circ = QuantumCircuit(2, 1)\n z1_circ.x(0)\n z1_circ.append(cr_gate, [0, 1])\n z1_circ.measure(1, 0)\n\n ref_circs = [x0_circ, y0_circ, z0_circ, x1_circ, y1_circ, z1_circ]\n for c in ref_circs:\n c.add_calibration(cr_gate, (0, 1), ref_cr_sched)\n\n self.assertListEqual(expr_circs, ref_circs)","def add_computed_gas_concentrations(self):\n # Extract the z-coordinate and T, S, P profile\n zs = self.interp_ds.coords[self.ztsp[0]].values\n Ts = self.interp_ds[self.ztsp[1]].values\n Ss = self.interp_ds[self.ztsp[2]].values\n Ps = self.interp_ds[self.ztsp[3]].values\n \n # Create an air object\n air_names = ['nitrogen', 'oxygen', 'argon', 'carbon_dioxide']\n yk = np.array([0.78084, 0.20946, 0.009340, 0.00036])\n from tamoc import dbm\n air = dbm.FluidMixture(air_names)\n m = air.masses(yk)\n \n # Compute the concentrations adjusted for depth\n Cs = np.zeros((len(zs), len(air_names)))\n for i in range(len(zs)):\n Cs[i,:] = air.solubility(m, Ts[i], 101325., Ss[i])[0,:] * \\\n seawater.density(Ts[i], Ss[i], Ps[i]) / \\\n seawater.density(Ts[i], Ss[i], 101325.)\n \n # Make sure none of these gases are already in the measured profile\n for name in air_names:\n if name in self.interp_ds:\n air_names[air_names.index(name)] = 'computed_' + name\n \n # Add these data to the Profile object\n data = np.hstack((np.atleast_2d(zs).transpose(), Cs))\n names = [self.ztsp[0]] + air_names \n units = [self.ztsp_units[0]] + 4*['kg/m^3']\n self.append(data, names, units)\n \n # Rebuild the interpolator\n self._build_interpolator()","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def addState(self, s=[]):\n k = State(len(self.states))\n if s != []:\n for x in s:\n k.addRow(x[0], x[1][0], x[1][1], x[1][2])\n self.states.append(k)","def add_classifier_state(self,st):\n self.classifier_states.append(st)","def _template_circuit(self, amp_param) -> QuantumCircuit:\n circuit = QuantumCircuit(1)\n circuit.x(0)\n circuit.append(Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param]), (0,))\n circuit.measure_active()\n\n return circuit","def compileInstruction(self, ins):\n pass","def add_layer(self, freeze = True, add = True):\n if add:\n self.num_layers += 1\n if self.conv_dim == 1:\n new_cnn = layers.Conv1D(self.n_filters,\n (self.n_kernels),\n activation='elu',\n input_shape=(None, self.inp_shape[0], self.n_filters),\n padding=\"same\",\n name='cnn_1d_{}'.format(self.num_layers-1),\n kernel_initializer = initializers.get(self.initializer),\n bias_initializer=initializers.get(\"zeros\"),\n kernel_regularizer=self.regularizer,\n bias_regularizer=self.regularizer\n )\n elif self.conv_dim == 2:\n new_cnn = layers.Conv2D(self.n_filters,\n (self.n_kernels, self.n_kernels),\n activation='elu',\n input_shape=(None, self.inp_shape[0],self.inp_shape[1], self.n_filters),\n padding=\"same\",\n name='cnn_2d_{}'.format(self.num_layers-1),\n kernel_initializer=initializers.get(self.initializer),\n bias_initializer=initializers.get(\"zeros\"),\n kernel_regularizer=self.regularizer,\n bias_regularizer=self.regularizer\n )\n self.list_cnn.append(new_cnn)\n\n if freeze:\n for index in range(0,self.num_layers-1):\n self.list_cnn[index].trainable = False\n else:\n for index in range(0,self.num_layers-1):\n self.list_cnn[index].trainable = True","def register_shape_c_code(type, code, version=()):\r\n Shape.c_code_and_version[type] = (code, version)","def add(self, wartosc, czesc, is_int=True):\r\n if not is_int:\r\n wartosc = int.from_bytes(wartosc, byteorder='big')\r\n if czesc:\r\n # czesc starsza\r\n reg_this = int.from_bytes(self.high_byte, byteorder='big')\r\n else:\r\n # czesc mlodsza\r\n reg_this = int.from_bytes(self.low_byte, byteorder='big')\r\n\r\n reg_this += wartosc\r\n if reg_this > 255:\r\n reg_this = reg_this % 255\r\n\r\n if czesc:\r\n # czesc starsza\r\n self.high_byte = reg_this.to_bytes(1, byteorder='big')\r\n else:\r\n # czesc mlodsza\r\n self.low_byte = reg_this.to_bytes(1, byteorder='big')","def _init_sgc(self, init_temp, symbols):\n self._sgc_obj = []\n for ground_state in self._ground_states:\n self._sgc_obj.append(\n SGCMonteCarlo(\n ground_state[\"atoms\"],\n init_temp,\n symbols=symbols))","def add_control_inputs(op, cops):\n flag = True\n try:\n _ = iter(cops)\n except Exception: # pylint: disable=broad-except\n flag = False\n if not flag:\n op._add_control_input(cops)\n else:\n for cop in cops:\n if cop in op.control_inputs:\n raise ValueError(\"{}\".format(cop.name) + \" is already \" +\n \"a control_input of {}\".format(op.name))\n op._add_control_inputs(cops) # pylint: disable=protected-access","def add_couche(self, pos):\n if self.control == 0:\n if pos >= 0 and pos < (self.couche):\n self.couche.insert(pos, 0)\n else:\n print(\"Vous pouvez ajouter une couche dans l'intervale [0,\" + str(len(self.couche)) + \"]\")\n else:\n print(\"Le réseau est deja créé, vous en pouvez plus le modifier\")","def enable_cl1_direct(self):\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\n self.write_versa5(0x18,0x20)\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\n self.write_versa5(0x13,0x03) ## Switch to clock\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew","def add_state(self, state):\n self.states.add(state)","def addFCSPoint(self, dxpos, dypos, dzpos=None):\n prefix = \"/cli:python /app:fcs /cmd:add\"\n dx = \"/xpos:\" + `int(dxpos)` \n dy = \"/ypos:\" + `int(dypos)`\n if dzpos is None:\n dz = \"/zpos:0\"\n else:\n dz = \"/zpos:\"+dzpos\n \n \n cmd = \" \".join((prefix,dx,dy,dz))\n #print \"FCS command string\"\n #print cmd\n self.sendCMDstring(cmd)","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\n return self","def coadd(self, sp, method='pixel'):\n\t\tif method == 'pixel':\n\t\t\tw1 = 1/self.oriNoise**2\n\t\t\tw2 = 1/sp.oriNoise**2\n\t\t\tself.oriFlux = (self.oriFlux*w1 + sp.oriFlux*w2)/(w1 + w2)\n\t\t\tself.oriNoise = np.sqrt(1/(w1 + w2))\n\t\t\t## set up masking criteria\n\t\t\tself.avgFlux = np.mean(self.oriFlux)\n\t\t\tself.stdFlux = np.std(self.oriFlux)\n\t\t\tself.smoothFlux = self.oriFlux\n\t\t\t## set the outliers as the flux below \n\t\t\tif self.apply_sigma_mask:\n\t\t\t\tself.smoothFlux[self.smoothFlux <= self.avgFlux-2*self.stdFlux] = 0\n\t\t\t\tself.mask = np.where(self.smoothFlux <= 0)\n\t\t\telse:\n\t\t\t\tself.mask = []\n\t\t\tself.wave = np.delete(self.oriWave, list(self.mask))\n\t\t\tself.flux = np.delete(self.oriFlux, list(self.mask))\n\t\t\tself.noise = np.delete(self.oriNoise, list(self.mask))\n\n\t\telif method == 'wavelength':\n\t\t\tself_supers = copy.deepcopy(self)\n\t\t\tg = interpolate.interp1d(self.wave, self.flux)\n\t\t\tsp_supers = copy.deepcopy(sp)\n\t\t\tf = interpolate.interp1d(sp.wave, sp.flux)\n\t\t\t## 10x supersample the average difference of \n\t\t\t## the wavelength\n\t\t\t#step0 = np.mean(np.diff(self.wave))/10\n\t\t\t#self_supers.wave = np.arange(self.wave[0],\n\t\t\t#\tself.wave[-1],step0)\n\t\t\tself_supers.flux = g(self_supers.wave)\n\t\t\tself_supers.oriWave = np.arange(self.oriWave[0],\n\t\t\t\tself.oriWave[-1],(self.oriWave[-1]-self.oriWave[0])/10240)\n\t\t\tg1 = interpolate.interp1d(self.oriWave, self.oriFlux)\n\t\t\tself_supers.oriFlux = g1(self_supers.oriWave)\n\n\t\t\t#step = np.mean(np.diff(sp.wave))/10\n\t\t\t#sp_supers.wave = np.arange(sp.wave[0],sp.wave[-1],step)\n\t\t\t#sp_supers.flux = f(sp_supers.wave)\n\t\t\tsp_supers.oriWave = np.arange(sp.oriWave[0],\n\t\t\t\tsp.oriWave[-1],(sp.oriWave[-1]-sp.oriWave[0])/10240)\n\t\t\tf1 = interpolate.interp1d(sp.oriWave, sp.oriFlux)\n\t\t\tsp_supers.oriFlux = f1(sp_supers.oriWave)\n\n\t\t\t## calculate the max cross correlation value\n\t\t\tdef xcorr(a0,b0,shift):\n\t\t\t\t\"\"\"\n\t\t\t\tShift is the index number after supersampling \n\t\t\t\tboth of the spectra.\n\t\t\t\t\"\"\"\n\t\t\t\ta = copy.deepcopy(a0)\n\t\t\t\tb = copy.deepcopy(b0)\n\n\t\t\t\t## shift the wavelength of b\n\t\t\t\tlength = b.oriFlux.shape[0]\n\t\t\t\tif shift >= 0:\n\t\t\t\t\tmask_a = np.arange(0,shift,1)\n\t\t\t\t\ta.oriFlux = np.delete(a.oriFlux,mask_a)\n\t\t\t\t\tmask_b = np.arange(length-1,length-shift-1,-1)\n\t\t\t\t\tb.oriFlux = np.delete(b.oriFlux,mask_b)\n\n\t\t\t\telif shift < 0:\n\t\t\t\t\tmask_a = np.arange(length-1,length+shift-1,-1)\n\t\t\t\t\ta.oriFlux = np.delete(a.oriFlux,mask_a)\n\t\t\t\t\tmask_b = np.arange(0,-shift,1)\n\t\t\t\t\tb.oriFlux = np.delete(b.oriFlux,mask_b)\n\n\t\t\t\t## shift the wavelength of b\n\t\t\t\t#b.wave += shift * step\n\t\t\t\t## discard the points where the wavelength values\n\t\t\t\t## are larger\n\t\t\t\t#condition = (a.wave > b.wave[0]) & (a.wave < b.wave[-1])\n\t\t\t\t\n\t\t\t\t#a.flux = a.flux[np.where(condition)]\n\t\t\t\t#a.wave = a.wave[np.where(condition)]\n\t\t\t\t## resampling the telluric model\n\t\t\t\t#b.flux = np.array(smart.integralResample(xh=b.wave, \n\t\t\t\t#\tyh=b.flux, xl=a.wave))\n\t\t\t\t\n\t\t\t\treturn np.inner(a.oriFlux, b.oriFlux)/\\\n\t\t\t\t(np.average(a.oriFlux)*np.average(b.oriFlux))/a.oriFlux.shape[0]\n\n\t\t\txcorr_list = []\n\t\t\t## mask the ending pixels\n\t\t\tself_supers2 = copy.deepcopy(self_supers)\n\t\t\tsp_supers2 = copy.deepcopy(sp_supers)\n\t\t\tself_supers2.wave = self_supers2.wave[1000:-1000]\n\t\t\tself_supers2.flux = self_supers2.flux[1000:-1000]\n\t\t\tsp_supers2.wave = sp_supers2.wave[1000:-1000]\n\t\t\tsp_supers2.flux = sp_supers2.flux[1000:-1000]\n\t\t\tfor shift in np.arange(-10,10,1):\n\t\t\t\txcorr_list.append(xcorr(self_supers2,sp_supers2,shift))\n\n\t\t\t## dignostic plot for cc result\n\t\t\tfig, ax = plt.subplots()\n\t\t\tax.plot(np.arange(-10,10,1),np.array(xcorr_list),'k-')\n\t\t\tplt.show()\n\t\t\tplt.close()\n\n\t\t\tstep = np.absolute(np.mean(np.diff(sp_supers.wave)))\n\t\t\tbestshift = np.arange(-10*step,10*step,step)[np.argmax(xcorr_list)]\n\t\t\tsp_supers.oriWave += bestshift\n\t\t\t## discard the points where the wavelength values\n\t\t\t## are larger\n\t\t\tcondition = (self.oriWave > sp_supers.oriWave[0])\\\n\t\t\t& (self.oriWave < sp_supers.oriWave[-1])\n\n\t\t\tself.oriFlux = self.oriFlux[np.where(condition)]\n\t\t\tself.oriWave = self.oriWave[np.where(condition)]\n\t\t\tself.oriNoise = self.oriNoise[np.where(condition)]\n\t\t\tsp_supers.oriNoise = sp_supers.oriNoise[np.where(condition)]\n\t\t\tsp_supers.oriFlux = np.array(smart.integralResample(xh=sp_supers.oriWave, \n\t\t\t\tyh=sp_supers.oriFlux, xl=self.oriWave))\n\n\t\t\tw1 = 1/self.oriNoise**2\n\t\t\tw2 = 1/sp_supers.oriNoise**2\n\t\t\tself.oriFlux = (self.oriFlux*w1 + sp_supers.oriFlux*w2)/(w1 + w2)\n\t\t\tself.oriNoise = np.sqrt(1/(w1 + w2))\n\t\t\t## set up masking criteria\n\t\t\tself.avgFlux = np.mean(self.oriFlux)\n\t\t\tself.stdFlux = np.std(self.oriFlux)\n\t\t\tself.smoothFlux = self.oriFlux\n\t\t\t## set the outliers as the flux below \n\t\t\tself.smoothFlux[self.smoothFlux <= self.avgFlux-2*self.stdFlux] = 0\n\t\t\tself.mask = np.where(self.smoothFlux <= 0)\n\t\t\tself.wave = np.delete(self.oriWave, list(self.mask))\n\t\t\tself.flux = np.delete(self.oriFlux, list(self.mask))\n\t\t\tself.noise = np.delete(self.oriNoise, list(self.mask))\n\n\t\treturn self","def add_scoop(self, one_scoop):\n self.scoops.append(one_scoop)","def add_course(graph, course, parent, color):\n if course[-1] == '*':\n # Concurrent course\n color = 'green'\n course = course[:-1]\n child = pydot.Node(course)\n graph.add_node(child)\n edge = pydot.Edge(parent, course, color=color)\n graph.add_edge(edge)"],"string":"[\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def BCS(self, value):\\n if self.reg.C:\\n self.reg.PC += value\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def add_connector(self):\\n \\n no = len(self.connectors)\\n state = {}\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % no\\n \\n if len(self.connectors)>0:\\n state = self.connectors[-1].get_state()\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % (no)\\n else:\\n if self.mount == self.MOUNT_THT:\\n state[\\\"p_shape\\\"] = Con.SHAPE_HOLE\\n elif self.mount == self.MOUNT_SMD:\\n state[\\\"p_shape\\\"] = Con.SHAPE_PAD\\n \\n c = Con(no)\\n c.set_state(state) \\n \\n self.sch_layers[\\\"pins\\\"].add(c.s_svg)\\n self.pcb_layers[\\\"copper1\\\"].add(c.p_svg)\\n self.connectors.append(c)\",\n \"def circuitSat(C):\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def cs_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def add(self, sgid, other, proto_spec, direction=\\\"in\\\"):\\n # returns bool\\n # AuthorizeSecurityGroupIngress, AuthorizeSecurityGroupEgress\\n if direction == \\\"in\\\":\\n api = \\\"AuthorizeSecurityGroupIngress\\\"\\n elif direction == \\\"out\\\":\\n api = \\\"AuthorizeSecurityGroupEgress\\\"\\n else:\\n raise ValueError(\\\"direction must be one of ('in', 'out')\\\")\\n return self.modify(api, sgid, other, proto_spec)\",\n \"def add_state(self, name='Ti', c=2000):\\n assert isinstance(name, str), 'name must be a string type'\\n if name in self.sta.keys():\\n raise Exception('State already defined')\\n state = State(c=c, name=name)\\n self.sta[name] = state\\n self.nodes[name] = state\\n self.rc.add_node(state)\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def bcs(self, arg):\\n\\n self.pc += arg if self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def csw(self, q0, q1, q2, ctrl=None):\\n self.cx(q2,q1,ctrl=ctrl).ccx(q0,q1,q2,ctrl=ctrl).cx(q2,q1,ctrl=ctrl)\\n return self\",\n \"def assemble_circuit(\\n self,\\n circuit: Circuit,\\n blocks: list[int],\\n psols: list[list[tuple[Circuit, float]]],\\n pts: list[CircuitPoint],\\n ) -> Circuit:\\n circuit_gates = [\\n CircuitGate(psol_list[b][0])\\n for b, psol_list\\n in zip(blocks, psols)\\n ]\\n locations = [circuit[pt].location for pt in pts]\\n operations = [\\n Operation(cg, loc, cg._circuit.params)\\n for cg, loc\\n in zip(circuit_gates, locations)\\n ]\\n copied_circuit = circuit.copy()\\n copied_circuit.batch_replace(pts, operations)\\n return copied_circuit\",\n \"def local_addsd_ccode(node):\\r\\n if isinstance(node.op, sparse.AddSD) and theano.config.cxx:\\r\\n new_node = AddSD_ccode(format=node.inputs[0].type.format)(*node.inputs)\\r\\n return [new_node]\\r\\n return False\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def manage_addCASSSO(self, id='sso', REQUEST=None):\\n\\n id = 'sso'\\n ob = CASSSO()\\n ob.id = id\\n self._setObject(id, ob)\\n if REQUEST is not None:\\n return self.manage_main(self, REQUEST)\",\n \"def add(self, p, s, node) -> None:\\n self.place.append(p)\\n self.station.append(s)\\n self.pi.append(node.pi[p, s] if p != float('inf') else float('inf'))\\n self.noncoverage.append(node.noncoverage.left + node.noncoverage.right)\\n self.cost.append(node.cost)\\n self.delay.append(node.delay)\\n self.step.append(node.key)\",\n \"def test_scalar_coeff_cc():\\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\\n kappa = Symbol('kappa', real=True)\\n a1 = Destroy(hs=hs_1)\\n a2 = Destroy(hs=hs_2)\\n\\n jc_expr = (\\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\\n )\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == I * kappa * OperatorPlusMinusCC(\\n a1.dag() * a2, sign=-1\\n )\\n expanded = simplified.doit()\\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def __init__(self, input, output) :\\n Gate.__init__(self, [input], output)\",\n \"def coadd(self, step_index):\\n if self.drip_config is not None:\\n if ('boresight' in self.drip_cal_config\\n and 'SLIT' in self.drip_cal_config['boresight']):\\n self.current[step_index].set_value('skip_coadd', True)\",\n \"def scc (self, reset=False):\\n if reset or (self.__scc is None):\\n self.tarjan(reset)\\n return self.__scc\",\n \"def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\\n if q_args is None and c_args is None:\\n raise GateError(\\\"Gate needs at least one quantum argument or classical argument\\\")\\n if isinstance(gate, CompositeGate):\\n if mapping is None:\\n raise GateError(\\\"Must provide arguments mapping for composite gate inside a composite gate.\\\")\\n else:\\n inv_mappimg = dict()\\n for key, value in mapping.items():\\n inv_mappimg[value] = key\\n if gate is self:\\n gates = gate.copy.gates\\n else:\\n gates = gate.gates\\n for g in gates:\\n new_q_args = None\\n new_c_args = None\\n if g[1] is not None:\\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\\n if g[2] is not None:\\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\\n self.add_gate(gate=g[0], q_args=new_q_args,\\n c_args=new_c_args, params=g[3])\\n else:\\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\\n raise GateError(\\\"Gate must be either a CompositeGate or a string from: \\\"\\n \\\"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\\\")\\n if q_args is not None:\\n for q_arg in q_args:\\n if q_arg not in self.q_args:\\n self.add_q_arg(q_arg)\\n if c_args is not None:\\n for c_arg in c_args:\\n if c_arg not in self.c_args:\\n self.add_c_arg(c_arg)\\n if params is not None:\\n for param in params:\\n if param not in self.params:\\n self.add_param(param)\\n self._gates.append((gate, q_args, c_args, params))\",\n \"def n_cs(self):\\n pass\",\n \"def pk_cs(self, snr=30, headroom = 0):\\n # Initialize\\n self.pk = np.zeros((self.n_waves, len(self.controls.k0)), dtype=np.csingle)\\n # loop over frequencies\\n bar = tqdm(total = len(self.controls.k0), desc = 'Calculating Constrained Optim.')\\n # print(self.pk.shape)\\n for jf, k0 in enumerate(self.controls.k0):\\n # get the scaled version of the propagating directions\\n k_vec = k0 * self.dir\\n # Form the sensing matrix\\n h_mtx = np.exp(1j*self.receivers.coord @ k_vec.T)\\n H = h_mtx.astype(complex)\\n # measured data\\n pm = self.pres_s[:,jf].astype(complex)\\n # Performing constrained optmization cvxpy\\n x_cvx = cp.Variable(h_mtx.shape[1], complex = True)\\n # Create the problem\\n epsilon = 10**(-(snr-headroom)/10)\\n objective = cp.Minimize(cp.pnorm(x_cvx, p=1))\\n constraints = [cp.pnorm(pm - cp.matmul(H, x_cvx), p=2) <= epsilon]#[H*x == pm]\\n # Create the problem and solve\\n problem = cp.Problem(objective, constraints)\\n problem.solve(solver=cp.SCS, verbose=True) \\n self.pk[:,jf] = x_cvx.value\\n bar.update(1)\\n bar.close()\\n return self.pk\",\n \"def build_scl(net, ovs, src, dst, next_hop, match=None):\\n info(\\\"### Build service classifier, source:{}, next_hop:{}\\\\n\\\".format(src,\\n next_hop))\\n in_port = get_ofport(\\\"{}-{}\\\".format(ovs, src))\\n out_port = get_ofport(\\\"{}-{}\\\".format(ovs, next_hop))\\n ip_dst = net[dst].IP()\\n check_output(\\n split(\\n \\\"sudo ovs-ofctl add-flow {sw} \\\\\\\"nw_dst={ip_dst},icmp,in_port={in_port},actions=output={out_port}\\\\\\\"\\\".format(\\n **{\\\"sw\\\": ovs, \\\"in_port\\\": in_port, \\\"out_port\\\": out_port,\\n \\\"ip_dst\\\": ip_dst}\\n )\\n )\\n )\\n ret = check_output(split(\\\"sudo ovs-ofctl dump-flows {}\\\".format(ovs)))\\n info(\\\"### Flow table of the switch after adding SFP:\\\\n\\\")\\n print(ret)\",\n \"def test_simple_cc():\\n hs_c = LocalSpace('c', dimension=3)\\n hs_q = LocalSpace('q1', basis=('g', 'e'))\\n Delta_1 = Symbol('Delta_1')\\n Omega_1 = Symbol('Omega_1')\\n g_1 = Symbol('g_1')\\n a = Destroy(hs=hs_c)\\n a_dag = Create(hs=hs_c)\\n sig_p = LocalSigma('e', 'g', hs=hs_q)\\n sig_m = LocalSigma('g', 'e', hs=hs_q)\\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\\n assert (\\n srepr(simplified.term)\\n == \\\"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \\\"\\n \\\"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \\\"\\n \\\"basis=('g', 'e')))), sign=-1)\\\"\\n )\\n expanded = simplified.doit()\\n assert expanded == jc_expr\",\n \"def cy(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CY(), target=[control, target])\",\n \"def __init__(self, input0, input1, output) :\\n Gate.__init__(self, [input0,input1], output)\",\n \"def csNew(self, an):\\n\\t\\treturn ca - an/self.GA\",\n \"def construct_circuit(self):\\n return self._circuit\",\n \"def coi(self, s):\\n return 2 ** 0.5 * s\",\n \"def iadd(state: State) -> State:\\n cell = state.array[state.index] or 0\\n return state._replace(acc=state.acc + cell)\",\n \"def bcc(self, arg):\\n\\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def CL(self):\",\n \"def enc_add_const(pub, m, c):\\n # Similiar to enc add\\n add_const_result = m * powmod(pub.g, c, pub.n_sq) % pub.n_sq\\n return add_const_result\",\n \"def credit(self, value):\\n self._negative_value_raises_an_error(value)\\n self.operations.insert(value);\",\n \"def AddSpecialPoint(self, cp):\\n return _gmat_py.SolarSystem_AddSpecialPoint(self, cp)\",\n \"def csb(self):\\n\\n def myfunc(incident_energy):\\n return XrayLibWrap_Energy(self.Z, \\\"csb\\\", incident_energy)\\n\\n return myfunc\",\n \"def _write_circuit(self, feature_vector_index):\\n # grab the feature vector\\n feature_vector = self.data.data[feature_vector_index]\\n\\n # compute the indices to put gates at\\n inds = [x for x in range(len(feature_vector)) if feature_vector[x] == 1]\\n\\n # write the circuit\\n self.circuits[feature_vector_index].add_layer(H)\\n self.circuits[feature_vector_index].add_at(Z, inds)\\n\\n # TODO: all encoding classes will need this method.\\n # TODO: make a BaseEncoding that implements this\",\n \"def connect(self, gate) :\\n self.notifyList.append(gate)\",\n \"def _cmplx_add_ ( s , o ) :\\n return o + complex ( s )\",\n \"def actual_causation():\\n # fmt: off\\n tpm = np.array([\\n [1, 0, 0, 0],\\n [0, 1, 0, 0],\\n [0, 1, 0, 0],\\n [0, 0, 0, 1],\\n ])\\n cm = np.array([\\n [1, 1],\\n [1, 1],\\n ])\\n # fmt: on\\n return Network(tpm, cm, node_labels=('OR', 'AND'))\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def _template_circuit(self, amp_param) -> QuantumCircuit:\\n gate = Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param])\\n\\n circuit = QuantumCircuit(1)\\n circuit.append(gate, (0,))\\n circuit.measure_active()\\n\\n return circuit\",\n \"def local_inplace_addsd_ccode(node):\\r\\n if isinstance(node.op, sparse.AddSD) and theano.config.cxx:\\r\\n out_dtype = scalar.upcast(*node.inputs)\\r\\n if out_dtype != node.inputs[1].dtype:\\r\\n return\\r\\n new_node = AddSD_ccode(format=node.inputs[0].type.format,\\r\\n inplace=True)(*node.inputs)\\r\\n return [new_node]\\r\\n return False\",\n \"def block(self, mcs):\\n\\n self.oracle.add_clause([self.sels[cl_id - 1] for cl_id in mcs])\",\n \"def add(num1, num2, Cin):\\n Cin=0\\n l2=[]\\n final=\\\"\\\"\\n\\n \\\"\\\"\\\"Using for loop for starting addition from the last indexed number\\\"\\\"\\\"\\n for i in range(len(num1)-1,-1,-1):\\n bit1=num1[i]#storing each indexed() value of num1 in bit1\\n bit2=num2[i]#storing each indexed() value of num2 in bit2\\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\\n Cin=Cout#declaring cout as cin for next bit addition\\n l2.append(SUM)#adding SUM to l2\\n l3=l2[::-1]##reversing the value of l2\\n final+=str(l2[-1])#converting the list value to string\\n final1=final[::-1]#reversing string value\\n return final1 #returning the binary addition as string\",\n \"def _control_predefined(operation, num_ctrl_qubits):\\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\\n if num_ctrl_qubits == 1:\\n import qiskit.extensions.standard.cx\\n cgate = qiskit.extensions.standard.cx.CnotGate()\\n else:\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n elif operation.name == 'y':\\n import qiskit.extensions.standard.cy\\n cgate = qiskit.extensions.standard.cy.CyGate()\\n elif operation.name == 'z':\\n import qiskit.extensions.standard.cz\\n cgate = qiskit.extensions.standard.cz.CzGate()\\n elif operation.name == 'h':\\n import qiskit.extensions.standard.ch\\n cgate = qiskit.extensions.standard.ch.CHGate()\\n elif operation.name in {'rx', 'ry', 'rz'}:\\n if operation.name == 'rx':\\n import qiskit.extensions.standard.crx\\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\\n elif operation.name == 'ry':\\n import qiskit.extensions.standard.cry\\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\\n else: # operation.name == 'rz'\\n import qiskit.extensions.standard.crz\\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\\n if num_ctrl_qubits == 1:\\n return cgate\\n else:\\n # only predefined for one control qubit\\n return cgate.control(num_ctrl_qubits - 1)\\n elif operation.name == 'swap':\\n import qiskit.extensions.standard.cswap\\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\\n elif operation.name == 'u1':\\n import qiskit.extensions.standard.cu1\\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\\n elif operation.name == 'u3':\\n import qiskit.extensions.standard.cu3\\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\\n elif operation.name == 'cx':\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n else:\\n raise QiskitError('No standard controlled gate for \\\"{}\\\"'.format(\\n operation.name))\\n return cgate\",\n \"def add_comp(self, name, ctype):\\n\\n name = self.name + '.' + name\\n\\n assert name not in self.components, 'A component named \\\\'{}\\\\' already exists for node \\\\'{}\\\\''.format(\\n name, self.name)\\n\\n try:\\n cls = co.str_to_comp(ctype)\\n except AttributeError:\\n try:\\n cls = rc.str_to_comp(ctype)\\n except AttributeError:\\n cls = None\\n\\n if cls:\\n obj = cls(name=name,\\n temperature_driven=self.temperature_driven,\\n repr_days=self.repr_days)\\n else:\\n raise ValueError(\\n \\\"%s is not a valid class name! (component is %s, in node %s)\\\" % (\\n ctype, name, self.name))\\n\\n self.logger.info('Component {} added to {}'.format(name, self.name))\\n\\n self.components[name] = obj\",\n \"def _store_cf(cl, context, new_cf):\\n try:\\n cl.add(new_cf, key=context)\\n except TypeError:\\n print(type(cl))\\n raise\",\n \"def append_user_gate(self, user_gate):\\n self.translation['g_sect'].append(user_gate)\",\n \"def addControlPoints(self, *controlpoints):\\n self.controlpoints.extend(controlpoints)\\n self.update()\",\n \"def modelCS(self,ht=None,hf=None):\\n if ht is not None:\\n hf = time2freq(ht)\\n cs,a,b,c = make_model_cs(hf, self.s0, self.bw, self.ref_freq)\\n \\n return cs\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def update_control(self):\\n self._control_ctr += 0x01\",\n \"def translate(self):\\n self._marshall_gatedefs()\\n self._marshall_regdefs()\\n\\n if not self.circuit:\\n self._create_quantum_circuit()\\n\\n for entry in self.nuq2_ast['c_sect']:\\n try:\\n op_type = entry['type']\\n if op_type is ASTType.OP:\\n starting_circuit_size = self.circuit.size()\\n self._op_append(entry, self.circuit.qregs, self.circuit.cregs,\\n self.circuit.qubits, self.circuit.clbits)\\n if self.circuit.size() == starting_circuit_size:\\n raise Ast2CircOpNotFoundException(section='c_sect',\\n entry=entry)\\n elif op_type is ASTType.BARRIER:\\n self._barrier_append(entry, self.circuit.qregs, self.circuit.qubits)\\n elif op_type is ASTType.MEASURE:\\n self._measure_append(entry, self.circuit.qregs, self.circuit.cregs,\\n self.circuit.qubits, self.circuit.clbits)\\n except NameError as ex:\\n raise Ast2CircTranslationException(section='c_sect',\\n entry=entry,\\n prev_ex=ex)\\n\\n else: # It's nothing we care about in this stage\\n pass\\n return self\",\n \"def cz(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CZ(), target=[control, target])\",\n \"def gate(self):\\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)\",\n \"def BVS(self, value):\\n if self.reg.V:\\n self.reg.PC += value\",\n \"def add_road(ccTremb):\\n pass\",\n \"def add_stcs(stc1, stc2):\\n vertices = [np.union1d(stc1.vertices[0], stc2.vertices[0]),\\n np.union1d(stc1.vertices[1], stc2.vertices[1])]\\n assert stc1.data.shape[1] == stc2.data.shape[1]\\n assert stc1.tmin == stc2.tmin\\n assert stc1.tstep == stc2.tstep\\n\\n data = np.zeros((len(vertices[0]) + len(vertices[1]), stc1.data.shape[1]))\\n i = 0\\n\\n # Left hemisphere\\n for vert in vertices[0]:\\n if vert in stc1.vertices[0]:\\n data[[i]] += stc1.lh_data[stc1.vertices[0] == vert]\\n if vert in stc2.vertices[0]:\\n data[[i]] += stc2.lh_data[stc2.vertices[0] == vert]\\n i += 1\\n\\n # Right hemisphere\\n for vert in vertices[1]:\\n if vert in stc1.vertices[1]:\\n data[[i]] += stc1.rh_data[stc1.vertices[1] == vert]\\n if vert in stc2.vertices[1]:\\n data[[i]] += stc2.rh_data[stc2.vertices[1] == vert]\\n i += 1\\n\\n return mne.SourceEstimate(data, vertices, tmin=stc1.tmin, tstep=stc1.tstep)\",\n \"def _c2c_cost(sclst, eclst):\\n def _c2c(point):\\n _c_sum = 0\\n for pt in eclst.points:\\n _c_sum += point.frequency(pt)\\n return _c_sum\\n return int(sum(map(_c2c, sclst.points)))\",\n \"def short_circ():\\n \\n set_mode(mode_cv)\\n time.sleep(.250)\\n set_CV_volts(0.1)\\n time.sleep(.250)\\n \\n sc_vals = get_input_values()\\n sc_data_point = data_point(sc_vals)\\n jsc = sc_data_point[4]\\n print('Short circuit current: ', jsc)\\n write_data_tofile(sc_data_point)\\n\\n return jsc\",\n \"def uCSIsCatCc(code):\\n ret = libxml2mod.xmlUCSIsCatCc(code)\\n return ret\",\n \"def cs(self):\\n\\n def myfunc(incident_energy):\\n return XrayLibWrap_Energy(self.Z, \\\"cs\\\", incident_energy)\\n\\n return myfunc\",\n \"def cp(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_P, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def add_control(operation, num_ctrl_qubits, label):\\n if isinstance(operation, UnitaryGate):\\n # attempt decomposition\\n operation._define()\\n if _control_definition_known(operation, num_ctrl_qubits):\\n return _control_predefined(operation, num_ctrl_qubits)\\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def gate_mfcc(recurrent_net, sample_input):\\n length = sample_input.shape[1]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\\n select = sigmoid(select)\\n return np.sum(select * score) / np.sum(select)\",\n \"def add_cogs(self):\\n self.add_cog(Voice(self))\",\n \"def test_circuit_generation_from_sec(self):\\n\\n backend = CrossResonanceHamiltonianBackend()\\n\\n expr = cr_hamiltonian.CrossResonanceHamiltonian(\\n qubits=(0, 1),\\n flat_top_widths=[500],\\n unit=\\\"ns\\\",\\n amp=0.1,\\n sigma=20,\\n risefall=2,\\n )\\n\\n nearlest_16 = 576\\n\\n with pulse.build(default_alignment=\\\"left\\\", name=\\\"cr\\\") as ref_cr_sched:\\n pulse.play(\\n pulse.GaussianSquare(\\n nearlest_16,\\n amp=0.1,\\n sigma=20,\\n width=500,\\n ),\\n pulse.ControlChannel(0),\\n )\\n pulse.delay(nearlest_16, pulse.DriveChannel(0))\\n pulse.delay(nearlest_16, pulse.DriveChannel(1))\\n\\n cr_gate = circuit.Gate(\\\"cr_gate\\\", num_qubits=2, params=[500])\\n expr_circs = expr.circuits(backend)\\n\\n x0_circ = QuantumCircuit(2, 1)\\n x0_circ.append(cr_gate, [0, 1])\\n x0_circ.h(1)\\n x0_circ.measure(1, 0)\\n\\n x1_circ = QuantumCircuit(2, 1)\\n x1_circ.x(0)\\n x1_circ.append(cr_gate, [0, 1])\\n x1_circ.h(1)\\n x1_circ.measure(1, 0)\\n\\n y0_circ = QuantumCircuit(2, 1)\\n y0_circ.append(cr_gate, [0, 1])\\n y0_circ.sdg(1)\\n y0_circ.h(1)\\n y0_circ.measure(1, 0)\\n\\n y1_circ = QuantumCircuit(2, 1)\\n y1_circ.x(0)\\n y1_circ.append(cr_gate, [0, 1])\\n y1_circ.sdg(1)\\n y1_circ.h(1)\\n y1_circ.measure(1, 0)\\n\\n z0_circ = QuantumCircuit(2, 1)\\n z0_circ.append(cr_gate, [0, 1])\\n z0_circ.measure(1, 0)\\n\\n z1_circ = QuantumCircuit(2, 1)\\n z1_circ.x(0)\\n z1_circ.append(cr_gate, [0, 1])\\n z1_circ.measure(1, 0)\\n\\n ref_circs = [x0_circ, y0_circ, z0_circ, x1_circ, y1_circ, z1_circ]\\n for c in ref_circs:\\n c.add_calibration(cr_gate, (0, 1), ref_cr_sched)\\n\\n self.assertListEqual(expr_circs, ref_circs)\",\n \"def add_computed_gas_concentrations(self):\\n # Extract the z-coordinate and T, S, P profile\\n zs = self.interp_ds.coords[self.ztsp[0]].values\\n Ts = self.interp_ds[self.ztsp[1]].values\\n Ss = self.interp_ds[self.ztsp[2]].values\\n Ps = self.interp_ds[self.ztsp[3]].values\\n \\n # Create an air object\\n air_names = ['nitrogen', 'oxygen', 'argon', 'carbon_dioxide']\\n yk = np.array([0.78084, 0.20946, 0.009340, 0.00036])\\n from tamoc import dbm\\n air = dbm.FluidMixture(air_names)\\n m = air.masses(yk)\\n \\n # Compute the concentrations adjusted for depth\\n Cs = np.zeros((len(zs), len(air_names)))\\n for i in range(len(zs)):\\n Cs[i,:] = air.solubility(m, Ts[i], 101325., Ss[i])[0,:] * \\\\\\n seawater.density(Ts[i], Ss[i], Ps[i]) / \\\\\\n seawater.density(Ts[i], Ss[i], 101325.)\\n \\n # Make sure none of these gases are already in the measured profile\\n for name in air_names:\\n if name in self.interp_ds:\\n air_names[air_names.index(name)] = 'computed_' + name\\n \\n # Add these data to the Profile object\\n data = np.hstack((np.atleast_2d(zs).transpose(), Cs))\\n names = [self.ztsp[0]] + air_names \\n units = [self.ztsp_units[0]] + 4*['kg/m^3']\\n self.append(data, names, units)\\n \\n # Rebuild the interpolator\\n self._build_interpolator()\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def addState(self, s=[]):\\n k = State(len(self.states))\\n if s != []:\\n for x in s:\\n k.addRow(x[0], x[1][0], x[1][1], x[1][2])\\n self.states.append(k)\",\n \"def add_classifier_state(self,st):\\n self.classifier_states.append(st)\",\n \"def _template_circuit(self, amp_param) -> QuantumCircuit:\\n circuit = QuantumCircuit(1)\\n circuit.x(0)\\n circuit.append(Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param]), (0,))\\n circuit.measure_active()\\n\\n return circuit\",\n \"def compileInstruction(self, ins):\\n pass\",\n \"def add_layer(self, freeze = True, add = True):\\n if add:\\n self.num_layers += 1\\n if self.conv_dim == 1:\\n new_cnn = layers.Conv1D(self.n_filters,\\n (self.n_kernels),\\n activation='elu',\\n input_shape=(None, self.inp_shape[0], self.n_filters),\\n padding=\\\"same\\\",\\n name='cnn_1d_{}'.format(self.num_layers-1),\\n kernel_initializer = initializers.get(self.initializer),\\n bias_initializer=initializers.get(\\\"zeros\\\"),\\n kernel_regularizer=self.regularizer,\\n bias_regularizer=self.regularizer\\n )\\n elif self.conv_dim == 2:\\n new_cnn = layers.Conv2D(self.n_filters,\\n (self.n_kernels, self.n_kernels),\\n activation='elu',\\n input_shape=(None, self.inp_shape[0],self.inp_shape[1], self.n_filters),\\n padding=\\\"same\\\",\\n name='cnn_2d_{}'.format(self.num_layers-1),\\n kernel_initializer=initializers.get(self.initializer),\\n bias_initializer=initializers.get(\\\"zeros\\\"),\\n kernel_regularizer=self.regularizer,\\n bias_regularizer=self.regularizer\\n )\\n self.list_cnn.append(new_cnn)\\n\\n if freeze:\\n for index in range(0,self.num_layers-1):\\n self.list_cnn[index].trainable = False\\n else:\\n for index in range(0,self.num_layers-1):\\n self.list_cnn[index].trainable = True\",\n \"def register_shape_c_code(type, code, version=()):\\r\\n Shape.c_code_and_version[type] = (code, version)\",\n \"def add(self, wartosc, czesc, is_int=True):\\r\\n if not is_int:\\r\\n wartosc = int.from_bytes(wartosc, byteorder='big')\\r\\n if czesc:\\r\\n # czesc starsza\\r\\n reg_this = int.from_bytes(self.high_byte, byteorder='big')\\r\\n else:\\r\\n # czesc mlodsza\\r\\n reg_this = int.from_bytes(self.low_byte, byteorder='big')\\r\\n\\r\\n reg_this += wartosc\\r\\n if reg_this > 255:\\r\\n reg_this = reg_this % 255\\r\\n\\r\\n if czesc:\\r\\n # czesc starsza\\r\\n self.high_byte = reg_this.to_bytes(1, byteorder='big')\\r\\n else:\\r\\n # czesc mlodsza\\r\\n self.low_byte = reg_this.to_bytes(1, byteorder='big')\",\n \"def _init_sgc(self, init_temp, symbols):\\n self._sgc_obj = []\\n for ground_state in self._ground_states:\\n self._sgc_obj.append(\\n SGCMonteCarlo(\\n ground_state[\\\"atoms\\\"],\\n init_temp,\\n symbols=symbols))\",\n \"def add_control_inputs(op, cops):\\n flag = True\\n try:\\n _ = iter(cops)\\n except Exception: # pylint: disable=broad-except\\n flag = False\\n if not flag:\\n op._add_control_input(cops)\\n else:\\n for cop in cops:\\n if cop in op.control_inputs:\\n raise ValueError(\\\"{}\\\".format(cop.name) + \\\" is already \\\" +\\n \\\"a control_input of {}\\\".format(op.name))\\n op._add_control_inputs(cops) # pylint: disable=protected-access\",\n \"def add_couche(self, pos):\\n if self.control == 0:\\n if pos >= 0 and pos < (self.couche):\\n self.couche.insert(pos, 0)\\n else:\\n print(\\\"Vous pouvez ajouter une couche dans l'intervale [0,\\\" + str(len(self.couche)) + \\\"]\\\")\\n else:\\n print(\\\"Le réseau est deja créé, vous en pouvez plus le modifier\\\")\",\n \"def enable_cl1_direct(self):\\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\\n self.write_versa5(0x18,0x20)\\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\\n self.write_versa5(0x13,0x03) ## Switch to clock\\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew\",\n \"def add_state(self, state):\\n self.states.add(state)\",\n \"def addFCSPoint(self, dxpos, dypos, dzpos=None):\\n prefix = \\\"/cli:python /app:fcs /cmd:add\\\"\\n dx = \\\"/xpos:\\\" + `int(dxpos)` \\n dy = \\\"/ypos:\\\" + `int(dypos)`\\n if dzpos is None:\\n dz = \\\"/zpos:0\\\"\\n else:\\n dz = \\\"/zpos:\\\"+dzpos\\n \\n \\n cmd = \\\" \\\".join((prefix,dx,dy,dz))\\n #print \\\"FCS command string\\\"\\n #print cmd\\n self.sendCMDstring(cmd)\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\\n return self\",\n \"def coadd(self, sp, method='pixel'):\\n\\t\\tif method == 'pixel':\\n\\t\\t\\tw1 = 1/self.oriNoise**2\\n\\t\\t\\tw2 = 1/sp.oriNoise**2\\n\\t\\t\\tself.oriFlux = (self.oriFlux*w1 + sp.oriFlux*w2)/(w1 + w2)\\n\\t\\t\\tself.oriNoise = np.sqrt(1/(w1 + w2))\\n\\t\\t\\t## set up masking criteria\\n\\t\\t\\tself.avgFlux = np.mean(self.oriFlux)\\n\\t\\t\\tself.stdFlux = np.std(self.oriFlux)\\n\\t\\t\\tself.smoothFlux = self.oriFlux\\n\\t\\t\\t## set the outliers as the flux below \\n\\t\\t\\tif self.apply_sigma_mask:\\n\\t\\t\\t\\tself.smoothFlux[self.smoothFlux <= self.avgFlux-2*self.stdFlux] = 0\\n\\t\\t\\t\\tself.mask = np.where(self.smoothFlux <= 0)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tself.mask = []\\n\\t\\t\\tself.wave = np.delete(self.oriWave, list(self.mask))\\n\\t\\t\\tself.flux = np.delete(self.oriFlux, list(self.mask))\\n\\t\\t\\tself.noise = np.delete(self.oriNoise, list(self.mask))\\n\\n\\t\\telif method == 'wavelength':\\n\\t\\t\\tself_supers = copy.deepcopy(self)\\n\\t\\t\\tg = interpolate.interp1d(self.wave, self.flux)\\n\\t\\t\\tsp_supers = copy.deepcopy(sp)\\n\\t\\t\\tf = interpolate.interp1d(sp.wave, sp.flux)\\n\\t\\t\\t## 10x supersample the average difference of \\n\\t\\t\\t## the wavelength\\n\\t\\t\\t#step0 = np.mean(np.diff(self.wave))/10\\n\\t\\t\\t#self_supers.wave = np.arange(self.wave[0],\\n\\t\\t\\t#\\tself.wave[-1],step0)\\n\\t\\t\\tself_supers.flux = g(self_supers.wave)\\n\\t\\t\\tself_supers.oriWave = np.arange(self.oriWave[0],\\n\\t\\t\\t\\tself.oriWave[-1],(self.oriWave[-1]-self.oriWave[0])/10240)\\n\\t\\t\\tg1 = interpolate.interp1d(self.oriWave, self.oriFlux)\\n\\t\\t\\tself_supers.oriFlux = g1(self_supers.oriWave)\\n\\n\\t\\t\\t#step = np.mean(np.diff(sp.wave))/10\\n\\t\\t\\t#sp_supers.wave = np.arange(sp.wave[0],sp.wave[-1],step)\\n\\t\\t\\t#sp_supers.flux = f(sp_supers.wave)\\n\\t\\t\\tsp_supers.oriWave = np.arange(sp.oriWave[0],\\n\\t\\t\\t\\tsp.oriWave[-1],(sp.oriWave[-1]-sp.oriWave[0])/10240)\\n\\t\\t\\tf1 = interpolate.interp1d(sp.oriWave, sp.oriFlux)\\n\\t\\t\\tsp_supers.oriFlux = f1(sp_supers.oriWave)\\n\\n\\t\\t\\t## calculate the max cross correlation value\\n\\t\\t\\tdef xcorr(a0,b0,shift):\\n\\t\\t\\t\\t\\\"\\\"\\\"\\n\\t\\t\\t\\tShift is the index number after supersampling \\n\\t\\t\\t\\tboth of the spectra.\\n\\t\\t\\t\\t\\\"\\\"\\\"\\n\\t\\t\\t\\ta = copy.deepcopy(a0)\\n\\t\\t\\t\\tb = copy.deepcopy(b0)\\n\\n\\t\\t\\t\\t## shift the wavelength of b\\n\\t\\t\\t\\tlength = b.oriFlux.shape[0]\\n\\t\\t\\t\\tif shift >= 0:\\n\\t\\t\\t\\t\\tmask_a = np.arange(0,shift,1)\\n\\t\\t\\t\\t\\ta.oriFlux = np.delete(a.oriFlux,mask_a)\\n\\t\\t\\t\\t\\tmask_b = np.arange(length-1,length-shift-1,-1)\\n\\t\\t\\t\\t\\tb.oriFlux = np.delete(b.oriFlux,mask_b)\\n\\n\\t\\t\\t\\telif shift < 0:\\n\\t\\t\\t\\t\\tmask_a = np.arange(length-1,length+shift-1,-1)\\n\\t\\t\\t\\t\\ta.oriFlux = np.delete(a.oriFlux,mask_a)\\n\\t\\t\\t\\t\\tmask_b = np.arange(0,-shift,1)\\n\\t\\t\\t\\t\\tb.oriFlux = np.delete(b.oriFlux,mask_b)\\n\\n\\t\\t\\t\\t## shift the wavelength of b\\n\\t\\t\\t\\t#b.wave += shift * step\\n\\t\\t\\t\\t## discard the points where the wavelength values\\n\\t\\t\\t\\t## are larger\\n\\t\\t\\t\\t#condition = (a.wave > b.wave[0]) & (a.wave < b.wave[-1])\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t#a.flux = a.flux[np.where(condition)]\\n\\t\\t\\t\\t#a.wave = a.wave[np.where(condition)]\\n\\t\\t\\t\\t## resampling the telluric model\\n\\t\\t\\t\\t#b.flux = np.array(smart.integralResample(xh=b.wave, \\n\\t\\t\\t\\t#\\tyh=b.flux, xl=a.wave))\\n\\t\\t\\t\\t\\n\\t\\t\\t\\treturn np.inner(a.oriFlux, b.oriFlux)/\\\\\\n\\t\\t\\t\\t(np.average(a.oriFlux)*np.average(b.oriFlux))/a.oriFlux.shape[0]\\n\\n\\t\\t\\txcorr_list = []\\n\\t\\t\\t## mask the ending pixels\\n\\t\\t\\tself_supers2 = copy.deepcopy(self_supers)\\n\\t\\t\\tsp_supers2 = copy.deepcopy(sp_supers)\\n\\t\\t\\tself_supers2.wave = self_supers2.wave[1000:-1000]\\n\\t\\t\\tself_supers2.flux = self_supers2.flux[1000:-1000]\\n\\t\\t\\tsp_supers2.wave = sp_supers2.wave[1000:-1000]\\n\\t\\t\\tsp_supers2.flux = sp_supers2.flux[1000:-1000]\\n\\t\\t\\tfor shift in np.arange(-10,10,1):\\n\\t\\t\\t\\txcorr_list.append(xcorr(self_supers2,sp_supers2,shift))\\n\\n\\t\\t\\t## dignostic plot for cc result\\n\\t\\t\\tfig, ax = plt.subplots()\\n\\t\\t\\tax.plot(np.arange(-10,10,1),np.array(xcorr_list),'k-')\\n\\t\\t\\tplt.show()\\n\\t\\t\\tplt.close()\\n\\n\\t\\t\\tstep = np.absolute(np.mean(np.diff(sp_supers.wave)))\\n\\t\\t\\tbestshift = np.arange(-10*step,10*step,step)[np.argmax(xcorr_list)]\\n\\t\\t\\tsp_supers.oriWave += bestshift\\n\\t\\t\\t## discard the points where the wavelength values\\n\\t\\t\\t## are larger\\n\\t\\t\\tcondition = (self.oriWave > sp_supers.oriWave[0])\\\\\\n\\t\\t\\t& (self.oriWave < sp_supers.oriWave[-1])\\n\\n\\t\\t\\tself.oriFlux = self.oriFlux[np.where(condition)]\\n\\t\\t\\tself.oriWave = self.oriWave[np.where(condition)]\\n\\t\\t\\tself.oriNoise = self.oriNoise[np.where(condition)]\\n\\t\\t\\tsp_supers.oriNoise = sp_supers.oriNoise[np.where(condition)]\\n\\t\\t\\tsp_supers.oriFlux = np.array(smart.integralResample(xh=sp_supers.oriWave, \\n\\t\\t\\t\\tyh=sp_supers.oriFlux, xl=self.oriWave))\\n\\n\\t\\t\\tw1 = 1/self.oriNoise**2\\n\\t\\t\\tw2 = 1/sp_supers.oriNoise**2\\n\\t\\t\\tself.oriFlux = (self.oriFlux*w1 + sp_supers.oriFlux*w2)/(w1 + w2)\\n\\t\\t\\tself.oriNoise = np.sqrt(1/(w1 + w2))\\n\\t\\t\\t## set up masking criteria\\n\\t\\t\\tself.avgFlux = np.mean(self.oriFlux)\\n\\t\\t\\tself.stdFlux = np.std(self.oriFlux)\\n\\t\\t\\tself.smoothFlux = self.oriFlux\\n\\t\\t\\t## set the outliers as the flux below \\n\\t\\t\\tself.smoothFlux[self.smoothFlux <= self.avgFlux-2*self.stdFlux] = 0\\n\\t\\t\\tself.mask = np.where(self.smoothFlux <= 0)\\n\\t\\t\\tself.wave = np.delete(self.oriWave, list(self.mask))\\n\\t\\t\\tself.flux = np.delete(self.oriFlux, list(self.mask))\\n\\t\\t\\tself.noise = np.delete(self.oriNoise, list(self.mask))\\n\\n\\t\\treturn self\",\n \"def add_scoop(self, one_scoop):\\n self.scoops.append(one_scoop)\",\n \"def add_course(graph, course, parent, color):\\n if course[-1] == '*':\\n # Concurrent course\\n color = 'green'\\n course = course[:-1]\\n child = pydot.Node(course)\\n graph.add_node(child)\\n edge = pydot.Edge(parent, course, color=color)\\n graph.add_edge(edge)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.61474854","0.60933375","0.5538856","0.5500274","0.5416745","0.54130125","0.5370142","0.52709824","0.5245407","0.5190346","0.5103887","0.5103887","0.50913537","0.5075595","0.50684726","0.50532585","0.5031381","0.5031352","0.49834308","0.494981","0.49266437","0.49240425","0.49147874","0.48853943","0.48805797","0.48609388","0.48556724","0.48254126","0.48209462","0.4809693","0.48092306","0.48084202","0.4790486","0.47848716","0.47784784","0.47780722","0.4772206","0.47409967","0.47213957","0.47068217","0.4691322","0.46872598","0.46841756","0.46826816","0.46781933","0.4666755","0.465106","0.46484825","0.46426672","0.46325645","0.46290103","0.4623502","0.4622354","0.4610901","0.4605322","0.4599681","0.45954216","0.45878425","0.45813173","0.45760363","0.4572455","0.45587668","0.45571536","0.4551042","0.4549939","0.45438018","0.45375004","0.4537486","0.4535311","0.45333946","0.45277938","0.45268196","0.4522261","0.4520261","0.45131359","0.4510075","0.45038363","0.4501866","0.44876215","0.4485616","0.4484352","0.44783157","0.44771817","0.44767353","0.4475618","0.4471989","0.44683504","0.44660947","0.44648367","0.44596553","0.4458443","0.44506928","0.4443637","0.443459","0.4433354","0.44325125","0.44310823","0.44310758","0.44303232","0.44296336"],"string":"[\n \"0.61474854\",\n \"0.60933375\",\n \"0.5538856\",\n \"0.5500274\",\n \"0.5416745\",\n \"0.54130125\",\n \"0.5370142\",\n \"0.52709824\",\n \"0.5245407\",\n \"0.5190346\",\n \"0.5103887\",\n \"0.5103887\",\n \"0.50913537\",\n \"0.5075595\",\n \"0.50684726\",\n \"0.50532585\",\n \"0.5031381\",\n \"0.5031352\",\n \"0.49834308\",\n \"0.494981\",\n \"0.49266437\",\n \"0.49240425\",\n \"0.49147874\",\n \"0.48853943\",\n \"0.48805797\",\n \"0.48609388\",\n \"0.48556724\",\n \"0.48254126\",\n \"0.48209462\",\n \"0.4809693\",\n \"0.48092306\",\n \"0.48084202\",\n \"0.4790486\",\n \"0.47848716\",\n \"0.47784784\",\n \"0.47780722\",\n \"0.4772206\",\n \"0.47409967\",\n \"0.47213957\",\n \"0.47068217\",\n \"0.4691322\",\n \"0.46872598\",\n \"0.46841756\",\n \"0.46826816\",\n \"0.46781933\",\n \"0.4666755\",\n \"0.465106\",\n \"0.46484825\",\n \"0.46426672\",\n \"0.46325645\",\n \"0.46290103\",\n \"0.4623502\",\n \"0.4622354\",\n \"0.4610901\",\n \"0.4605322\",\n \"0.4599681\",\n \"0.45954216\",\n \"0.45878425\",\n \"0.45813173\",\n \"0.45760363\",\n \"0.4572455\",\n \"0.45587668\",\n \"0.45571536\",\n \"0.4551042\",\n \"0.4549939\",\n \"0.45438018\",\n \"0.45375004\",\n \"0.4537486\",\n \"0.4535311\",\n \"0.45333946\",\n \"0.45277938\",\n \"0.45268196\",\n \"0.4522261\",\n \"0.4520261\",\n \"0.45131359\",\n \"0.4510075\",\n \"0.45038363\",\n \"0.4501866\",\n \"0.44876215\",\n \"0.4485616\",\n \"0.4484352\",\n \"0.44783157\",\n \"0.44771817\",\n \"0.44767353\",\n \"0.4475618\",\n \"0.4471989\",\n \"0.44683504\",\n \"0.44660947\",\n \"0.44648367\",\n \"0.44596553\",\n \"0.4458443\",\n \"0.44506928\",\n \"0.4443637\",\n \"0.443459\",\n \"0.4433354\",\n \"0.44325125\",\n \"0.44310823\",\n \"0.44310758\",\n \"0.44303232\",\n \"0.44296336\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6095033"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81749,"cells":{"query":{"kind":"string","value":"add CS dagger gate (controlled S dagger gate)."},"document":{"kind":"string","value":"def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def gate(self):\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)","def build_glyCB(self, gCBd: Dihedron): # -> None:\n ...","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def glycosylate(self):\n chid = self.chain.get()\n sequon = self.sequon.get()\n self.sequon_colors[sequon] = [.7, .1, 0]\n key = self.sequon.get()\n residue = self.myGlycosylator.get_residue(key)\n #Build new glycan\n if self.selected_glycan:\n self.myGlycosylator.connect_topology['SELECTED'] = self.selected_glycan[1]\n #build from current glycan\n if key in self.original_glycans:\n original_glycan = self.original_glycanMolecules[key].atom_group\n r,t = self.original_glycans[key]\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\n else:\n original_glycan = None\n connect_tree = None \n #Use current glycan\n else:\n original_glycan = self.original_glycanMolecules[key]\n r,t = self.original_glycans[key]\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\n self.myGlycosylator.connect_topology['SELECTED'] = self.myGlycosylator.build_connect_topology(original_glycan) \n original_glycan = original_glycan.atom_group\n \n segname = 'G'+key.split(',')[2]\n glycan,bonds = self.myGlycosylator.glycosylate('SELECTED', \n template_glycan_tree = connect_tree, \n template_glycan = original_glycan,\n link_residue=residue, link_patch = 'NGLB', chain = 'G', segname=segname)\n new_glycan = glc.Molecule(key)\n new_glycan.set_AtomGroup(glycan, bonds = bonds)\n self.myGlycosylator.assign_patches(new_glycan)\n self.linked_glycanMolecules[key] = new_glycan\n self.linked_glycans[key] = [new_glycan.rootRes, new_glycan.interresidue_connectivity]\n self.names.update(new_glycan.get_names())\n # Update glycoprotein and sequon panels\n self.draw_glycoprotein(chid)\n self.draw_glycan(sequon)","def add_connector(self):\n \n no = len(self.connectors)\n state = {}\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % no\n \n if len(self.connectors)>0:\n state = self.connectors[-1].get_state()\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % (no)\n else:\n if self.mount == self.MOUNT_THT:\n state[\"p_shape\"] = Con.SHAPE_HOLE\n elif self.mount == self.MOUNT_SMD:\n state[\"p_shape\"] = Con.SHAPE_PAD\n \n c = Con(no)\n c.set_state(state) \n \n self.sch_layers[\"pins\"].add(c.s_svg)\n self.pcb_layers[\"copper1\"].add(c.p_svg)\n self.connectors.append(c)","def test_append_dangling_gate(self, circuit):\n match = (\n r\"Number of wire IDs \\(2\\) must match the number of wires connected to the gate \\(1\\).\"\n )\n gate = jet.GateFactory.create(\"H\")\n with pytest.raises(ValueError, match=match):\n circuit.append_gate(gate, wire_ids=[0, 1])","def load_gates(chip):\n for gate_id in chip.gates:\n gate_coord = chip.gates[gate_id]\n gate = gt.Gate(gate_id, gate_coord[\"x\"], gate_coord[\"y\"])\n chip.coordinates[0][gate_coord[\"y\"]][gate_coord[\"x\"]].gate = gate\n\n return chip","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def BCS(self, value):\n if self.reg.C:\n self.reg.PC += value","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def syed_dilation(data, vessel):","def add(self, sgid, other, proto_spec, direction=\"in\"):\n # returns bool\n # AuthorizeSecurityGroupIngress, AuthorizeSecurityGroupEgress\n if direction == \"in\":\n api = \"AuthorizeSecurityGroupIngress\"\n elif direction == \"out\":\n api = \"AuthorizeSecurityGroupEgress\"\n else:\n raise ValueError(\"direction must be one of ('in', 'out')\")\n return self.modify(api, sgid, other, proto_spec)","def add_cd_samples(self): \n \n if self.num_hidden == 0:\n \n (self.p_xi_given_x_, self.gibbs_samples), self.gibbs_updates =\\\n theano.scan(self.gibbs_step_fully_visible, n_steps = self.gibbs_steps)\n \n if self.num_hidden > 0:\n \n if \"PCD\" in self.algorithm:\n init_chain = self.persistent_gibbs\n else:\n # positive phase\n _, _, hid_sample = self.get_h_given_v_samples(self.x)\n\n init_chain = hid_sample\n \n (\n [\n vis_inputs,\n vis_outputs,\n vis_samples,\n hid_inputs,\n hid_means,\n hid_samples\n ],\n updates\n ) = theano.scan(\n self.gibbs_step_rbm_hid,\n outputs_info=[None, None, None, None, None, init_chain],\n n_steps= self.gibbs_steps)\n \n self.updates.update(updates)\n \n self.hid_samples = hid_samples[-1]\n \n self.rbm_cd_samples = theano.gradient.disconnected_grad(vis_samples[-1])\n \n self.rbm_vis_outputs = theano.gradient.disconnected_grad(vis_outputs[-1])","def globalphase_compiler(self, gate, args):\n pass","def globalphase_compiler(self, gate, args):\n pass","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def __init__(self, input, output) :\n Gate.__init__(self, [input], output)","def _insert_CD_state(self, alpha, clear=True):\n # Defines a new thermodynamic state based on the neighboring state\n neighbor_ind = [alpha < p['alpha']\n for p in self.data['CD'].protocol].index(True) - 1\n params_n = self.system.paramsFromAlpha(\n alpha, params_o=self.data['CD'].protocol[neighbor_ind])\n\n # For sampling importance resampling,\n # prepare an augmented matrix for pymbar calculations\n # with a new thermodynamic state\n (u_kln_s, N_k) = self._u_kln(self.data['CD'].Es, self.data['CD'].protocol)\n (K, L, N) = u_kln_s.shape\n\n u_kln_n = self._u_kln(self.data['CD'].Es, [params_n])[0]\n L += 1\n N_k = np.append(N_k, [0])\n\n u_kln = np.zeros([K, L, N])\n u_kln[:, :-1, :] = u_kln_s\n for k in range(K):\n u_kln[k, -1, :] = u_kln_n[k, 0, :]\n\n # Determine SIR weights\n weights = self.run_MBAR(u_kln, N_k, augmented=True)[1][:, -1]\n weights = weights / sum(weights)\n\n # Resampling\n # Convert linear indices to 3 indicies: state, cycle, and snapshot\n cum_N_state = np.cumsum([0] + list(N_k))\n cum_N_cycle = [np.cumsum([0] + [self.data['CD'].Es[k][c]['MM'].shape[0] \\\n for c in range(len(self.data['CD'].Es[k]))]) for k in range(len(self.data['CD'].Es))]\n\n def linear_index_to_snapshot_index(ind):\n state_index = list(ind < cum_N_state).index(True) - 1\n nis_index = ind - cum_N_state[state_index]\n cycle_index = list(nis_index < cum_N_cycle[state_index]).index(True) - 1\n nic_index = nis_index - cum_N_cycle[state_index][cycle_index]\n return (state_index, cycle_index, nic_index)\n\n def snapshot_index_to_linear_index(state_index, cycle_index, nic_index):\n return cum_N_state[state_index] + cum_N_cycle[state_index][\n cycle_index] + nic_index\n\n # Terms to copy\n if self.args.params['CD']['pose'] > -1:\n # Pose BPMF\n terms = ['MM',\\\n 'k_angular_ext','k_spatial_ext','k_angular_int'] + scalables\n else:\n # BPMF\n terms = ['MM', 'site'] + scalables\n\n CD_Es_s = []\n confs_s = []\n for c in range(len(self.data['CD'].Es[0])):\n CD_Es_c = dict([(term, []) for term in terms])\n confs_c = []\n for n_in_c in range(len(self.data['CD'].Es[-1][c]['MM'])):\n if (cum_N_cycle[-1][c] == 0):\n (snapshot_s,snapshot_c,snapshot_n) = linear_index_to_snapshot_index(\\\n np.random.choice(range(len(weights)), size = 1, p = weights)[0])\n else:\n snapshot_c = np.inf\n while (snapshot_c > c):\n (snapshot_s,snapshot_c,snapshot_n) = linear_index_to_snapshot_index(\\\n np.random.choice(range(len(weights)), size = 1, p = weights)[0])\n for term in terms:\n CD_Es_c[term].append(\\\n np.copy(self.data['CD'].Es[snapshot_s][snapshot_c][term][snapshot_n]))\n if self.args.params['CD']['keep_intermediate']:\n # Has not been tested:\n confs_c.append(\\\n np.copy(self.data['CD'].confs['samples'][snapshot_s][snapshot_c]))\n for term in terms:\n CD_Es_c[term] = np.array(CD_Es_c[term])\n CD_Es_s.append(CD_Es_c)\n confs_s.append(confs_c)\n\n # Insert resampled values\n self.data['CD'].protocol.insert(neighbor_ind + 1, params_n)\n self.data['CD'].Es.insert(neighbor_ind + 1, CD_Es_s)\n self.data['CD'].confs['samples'].insert(neighbor_ind + 1, confs_s)\n self.data['CD'].confs['replicas'].insert(neighbor_ind+1, \\\n np.copy(self.data['CD'].confs['replicas'][neighbor_ind]))\n\n if clear:\n self._clear_f_RL()","def _gyration(self, x, y, v, c):\n xy = self._mobius_add(x, y, c)\n yv = self._mobius_add(y, v, c)\n xyv = self._mobius_add(x, yv, c)\n return self._mobius_add(-xy, xyv, c)","def __init__(self, nfeat, nhid, nclass, dropout, alpha):\n super(GCN, self).__init__()\n self.dropout = dropout\n\n self.conv1 = GraphConvolutionLayer(nfeat, nhid, dropout=dropout, alpha=alpha, not_final=True)\n \n self.add_module('conv1', self.conv1)\n\n self.conv2 = GraphConvolutionLayer(nhid, nclass, dropout=dropout, alpha=alpha, not_final=False)","def dcgain(self):\n raise NotImplementedError(\"dcgain not implemented for %s objects\" %\n str(self.__class__))","def dcgain(sys):\n return sys.dcgain()","def __init__(self, input0, input1, output) :\n Gate.__init__(self, [input0,input1], output)","def add_dut(self):\n pass","def connect(self, gate) :\n self.notifyList.append(gate)","def _gcl(x, r, D, Ia, Ct):\n\n Area = np.pi * D ** 2.0 / 4.0\n m = 1.0 / (np.sqrt(1.0 - Ct))\n k = np.sqrt((m + 1.0) / 2.0)\n\n a1 = 0.435449861 # empirically determined\n a2 = 0.797853685\n a3 = -0.124807893\n a4 = 0.136821858\n b1 = 15.6298\n b2 = 1.0\n R96 = a1 * (np.exp(a2 * Ct * Ct + a3 * Ct + a4)) * (b1 * Ia + b2) * D\n\n x0 = (9.6 * D) / ((2.0 * R96 / (k * D)) ** 3.0 - 1.0)\n term1 = (k * D / 2.0) ** (5.0 / 2.0)\n term2 = (105.0 / (2.0 * np.pi)) ** (-0.5)\n term3 = (Ct * Area * x0) ** (-5.0 / 6.0)\n c1 = term1 * term2 * term3\n # c45=3*(c1) ** 2\n\n term10 = 0.1111 # * WindSpeed # U/9.0\n term20 = (Ct * Area * (x + x0) ** (-2.0)) ** (1.0 / 3.0)\n term310 = (r ** (3.0 / 2.0))\n term320 = (3.0 * c1 * c1 * Ct * Area * (x + x0)) ** (-0.5)\n term30 = term310 * term320\n term40 = ((35.0 / (2.0 * np.pi)) ** (3.0 / 10.0)) * \\\n (3.0 * c1 * c1) ** (-1.0 / 5.0)\n DU1 = -term10 * term20 * (term30 - term40) ** 2.0\n\n DU = DU1 # + w2 * DU2\n Rw = ((105 * c1 ** 2.0 / (2 * np.pi)) ** (1. / 5.)) * \\\n (Ct * Area * (x + x0)) ** (1. / 3.)\n return DU, Rw","def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\n if q_args is None and c_args is None:\n raise GateError(\"Gate needs at least one quantum argument or classical argument\")\n if isinstance(gate, CompositeGate):\n if mapping is None:\n raise GateError(\"Must provide arguments mapping for composite gate inside a composite gate.\")\n else:\n inv_mappimg = dict()\n for key, value in mapping.items():\n inv_mappimg[value] = key\n if gate is self:\n gates = gate.copy.gates\n else:\n gates = gate.gates\n for g in gates:\n new_q_args = None\n new_c_args = None\n if g[1] is not None:\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\n if g[2] is not None:\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\n self.add_gate(gate=g[0], q_args=new_q_args,\n c_args=new_c_args, params=g[3])\n else:\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\n raise GateError(\"Gate must be either a CompositeGate or a string from: \"\n \"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\")\n if q_args is not None:\n for q_arg in q_args:\n if q_arg not in self.q_args:\n self.add_q_arg(q_arg)\n if c_args is not None:\n for c_arg in c_args:\n if c_arg not in self.c_args:\n self.add_c_arg(c_arg)\n if params is not None:\n for param in params:\n if param not in self.params:\n self.add_param(param)\n self._gates.append((gate, q_args, c_args, params))","def add_gates(self, num_gates_to_add):\n pass","def addFCSPoint(self, dxpos, dypos, dzpos=None):\n prefix = \"/cli:python /app:fcs /cmd:add\"\n dx = \"/xpos:\" + `int(dxpos)` \n dy = \"/ypos:\" + `int(dypos)`\n if dzpos is None:\n dz = \"/zpos:0\"\n else:\n dz = \"/zpos:\"+dzpos\n \n \n cmd = \" \".join((prefix,dx,dy,dz))\n #print \"FCS command string\"\n #print cmd\n self.sendCMDstring(cmd)","def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def circuitSat(C):","def CL(self):","def addCDSphase(strand, cds):\n cds_region, cds_flag = [], 0\n if strand == '+':\n for cdspos in cds:\n if cds_flag == 0:\n cdspos = (cdspos[0], cdspos[1], 0)\n diff = (cdspos[1]-(cdspos[0]-1))%3\n else:\n xy = 0\n if diff == 0:\n cdspos = (cdspos[0], cdspos[1], 0)\n elif diff == 1:\n cdspos = (cdspos[0], cdspos[1], 2)\n xy = 2\n elif diff == 2:\n cdspos = (cdspos[0], cdspos[1], 1)\n xy = 1\n diff = ((cdspos[1]-(cdspos[0]-1))-xy)%3\n cds_region.append(cdspos)\n cds_flag = 1\n elif strand == '-':\n cds.reverse()\n for cdspos in cds:\n if cds_flag == 0:\n cdspos = (cdspos[0], cdspos[1], 0)\n diff = (cdspos[1]-(cdspos[0]-1))%3\n else:\n xy = 0\n if diff == 0:\n cdspos = (cdspos[0], cdspos[1], 0)\n elif diff == 1:\n cdspos = (cdspos[0], cdspos[1], 2)\n xy = 2\n elif diff == 2:\n cdspos = (cdspos[0], cdspos[1], 1)\n xy = 1\n diff = ((cdspos[1]-(cdspos[0]-1))-xy)%3\n cds_region.append(cdspos)\n cds_flag = 1\n cds_region.reverse()\n return cds_region","def _build_add(self) -> str:\n return dedent(\n \"\"\"\n @SP\n M=M-1\n A=M\n D=M\n @SP\n M=M-1\n A=M\n M=M+D\n @SP\n M=M+1\n \"\"\"\n )","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def insert(n, c, dnodecomm):\n\n _tot[c] += k[n]\n _in[c] += 2 * dnodecomm + network[n][n]\n bl[n] = c","def coadd(self, step_index):\n if self.drip_config is not None:\n if ('boresight' in self.drip_cal_config\n and 'SLIT' in self.drip_cal_config['boresight']):\n self.current[step_index].set_value('skip_coadd', True)","def add_condiments(self):\n print(\"Adding Lemon\")","def add_graph(self):\n \n self.cd_sampling = None\n \n if \"CD\" in self.algorithm:\n\n self.add_cd_samples()\n \n if self.num_hidden ==0:\n \n self.cd_sampling = self.get_cd_samples()\n \n if \"CSS\" in self.algorithm and self.mf_steps > 0: \n \n self.add_mf_updates()\n \n elif \"CSS\" in self.algorithm and self.gibbs_steps > 0:\n \n self.add_cd_samples()\n \n if self.num_hidden ==0:\n \n self.cd_sampling = self.get_cd_samples() \n \n self.add_objective()\n\n self.add_grad_updates() \n \n if self.report_p_tilda:\n \n self.add_p_tilda()\n \n self.add_pseudo_cost_measure()\n\n self.optimize = self.optimization_step()","def cmd_dgaus():\n cmds = []\n cmds.append(\"r_m[0.0,-1,1]\")\n cmds.append(\"r_s[1.5,0,10]\")\n cmds.append('Gaussian::gaus_c(x,r_m,r_s)')\n cmds.append(\"rt_m[0.0,-1,1]\")\n cmds.append(\"rt_s[3,0,10]\")\n cmds.append('Gaussian::gaus_t(x,rt_m,rt_s)')\n cmds.append(\"f[0.85]\") # fraction of core\n cmds.append(\"SUM::res(f*gaus_c,gaus_t)\")\n return cmds","def sdg(self, q):\n if isinstance(q, QuantumRegister):\n instructions = InstructionSet()\n for j in range(q.size):\n instructions.add(self.sdg((q, j)))\n return instructions\n\n self._check_qubit(q)\n return self._attach(SdgGate(q, self))","def train_dagger(): # add arguments as needed\n pass","def append_user_gate(self, user_gate):\n self.translation['g_sect'].append(user_gate)","def system(Vg, Cs, Cd, Cg, Gs, Gd, num_e):\n myset = set.SET()\n # choose between the two lines below for metallic dot or quantum levels\n myset.add_metallic_dot('dot', num_e, -num_e, 0)\n #myset.add_quantum_dot('dot', [0, 1, 2, 3], [1, 1, 1, 1])\n myset.add_lead('source')\n myset.add_lead('drain')\n myset.add_gate('gate')\n #myset.add_link('dl', 'dot', 'source', 5.5e-18, 0.2)\n #myset.add_link('dl', 'dot', 'drain', 5.5e-18, 0.2)\n myset.add_link('dl', 'dot', 'drain', Cd,Gd)\n myset.add_link('dl', 'dot', 'source', Cs, Gs)\n #myset.add_link('dl', 'dot', 'drain', 1e-19, 10e-8)\n #myset.add_link('dl', 'dot', 'drain', Cg, Gg)\n myset.add_link('dg', 'dot', 'gate', Cg)\n return myset","def add_comp(mol, projects):\n\n # Now attribute all this meta-deta to the compound object\n new_comp = Compound()\n comp = calc_cpd(new_comp, mol, projects)\n return comp","def csNew(self, an):\n\t\treturn ca - an/self.GA","def derive(self, code_of_source: str) -> str:\n min_to_change = self.mr_config['min_to_change']\n max_to_change = self.mr_config['max_to_change']\n n_gate_to_change = random.randint(min_to_change, max_to_change)\n max_to_change = min(n_gate_to_change, self.tot_n_x_gates)\n\n sections = metamorph.get_sections(code_of_source)\n source_code_circuit = sections[\"CIRCUIT\"]\n\n x_gates_to_replace = random.sample(\n self.instruction_x_gate, max_to_change)\n\n mr_metadata = {}\n mr_metadata[\"x_gates_to_replace\"] = str(x_gates_to_replace)\n\n changed_section = source_code_circuit\n lines = source_code_circuit.split(\"\\n\")\n\n x_gates_to_replace_reverse_order = sorted(\n x_gates_to_replace, key=lambda x: x[\"lineno\"], reverse=True)\n # we start replacing gates, from the last one because each\n # substitution of an X gate makes the code longer.\n for x_gate in x_gates_to_replace_reverse_order:\n # remove gate\n edit_location = x_gate[\"lineno\"] - 1\n removed_original = lines.pop(edit_location)\n\n h_gate_last = removed_original.replace(\"XGate\", \"HGate\")\n lines.insert(edit_location, h_gate_last)\n s_gate_last = removed_original.replace(\"XGate\", \"SGate\")\n lines.insert(edit_location, s_gate_last)\n s_gate_first = removed_original.replace(\"XGate\", \"SGate\")\n lines.insert(edit_location, s_gate_first)\n h_gate_first = removed_original.replace(\"XGate\", \"HGate\")\n lines.insert(edit_location, h_gate_first)\n\n changed_section = \"\\n\".join(lines)\n\n sections[\"CIRCUIT\"] = changed_section\n\n self.metadata = mr_metadata\n\n return metamorph.reconstruct_sections(sections)","def enable_cl1_direct(self):\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\n self.write_versa5(0x18,0x20)\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\n self.write_versa5(0x13,0x03) ## Switch to clock\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew","def add_cogs(self):\n self.add_cog(Voice(self))","def computeCLgainRemoveNodeD(self, G, PD, nodes, node, dropLidx, dir):\n CL_I = 0.0\n CL_F = 0.0\n if dir==2:\n for i in nodes:\n pos_I = PD.getPOS(node, i, case=2, isSimple=self.isSimple)\n pos_F = PD.getPOS(node, i, case=4, isSimple=self.isSimple, dropLidx=dropLidx)\n if pos_I < 0.0000000001:\n pos_I = 0.0000000001\n elif pos_I > 1.0 - 0.0000000001:\n pos_I = 1.0 - 0.0000000001\n if pos_F < 0.0000000001:\n pos_F = 0.0000000001\n elif pos_F > 1.0 - 0.0000000001:\n pos_F = 1.0 - 0.0000000001\n numE = G.number_of_edges(node, i)\n if self.isSimple:\n CL_I += math.log2(math.pow(1.0-pos_I, 1.0-numE)*math.pow(pos_I, numE))\n CL_F += math.log2(math.pow(1.0-pos_F, 1.0-numE)*math.pow(pos_F, numE))\n else:\n CL_I += math.log2(math.pow(1.0-pos_I, numE)*pos_I)\n CL_F += math.log2(math.pow(1.0-pos_F, numE)*pos_F)\n elif dir==1:\n for i in nodes:\n pos_I = PD.getPOS(i, node, case=2, isSimple=self.isSimple)\n pos_F = PD.getPOS(i, node, case=4, isSimple=self.isSimple, dropLidx=dropLidx)\n if pos_I < 0.0000000001:\n pos_I = 0.0000000001\n elif pos_I > 1.0 - 0.0000000001:\n pos_I = 1.0 - 0.0000000001\n if pos_F < 0.0000000001:\n pos_F = 0.0000000001\n elif pos_F > 1.0 - 0.0000000001:\n pos_F = 1.0 - 0.0000000001\n numE = G.number_of_edges(i, node)\n if self.isSimple:\n CL_I += math.log2(math.pow(1.0-pos_I, 1.0-numE)*math.pow(pos_I, numE))\n CL_F += math.log2(math.pow(1.0-pos_F, 1.0-numE)*math.pow(pos_F, numE))\n else:\n CL_I += math.log2( math.pow( 1.0-pos_I, numE )*pos_I )\n CL_F += math.log2( math.pow( 1.0-pos_F, numE )*pos_F )\n return -CL_I - (-CL_F)","def add_switch(self, dpid):\n\t\tself.switches.append(dpid)","def gate_logic(self, pull: str):\r\n self._gate_logic = pull\r\n self.gate_logic_hist.append(pull)\r\n\r\n if self.gate_logic_hist[-2] != pull and self._daq:\r\n msg = Message(\"gate_logic\", pull, self.checksum).message_bytes\r\n self._daq.asynch.transmit(msg)","def dagger(self) -> Cup:\n return self.cup_factory(self.left, self.right)","def added(self, comp):\n\t\tpass","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def counterions(self):\n\n\t\tprint \"adding counterions\"\n\t\tcopy(self.rootdir+'solvate.top',self.rootdir+'counterions.top')\n\t\tcmd = [gmxpaths['grompp'],\n\t\t\t'-f input-em-steep-in.mdp',\n\t\t\t'-po genion.mdp',\n\t\t\t'-c solvate-minimized.gro',\n\t\t\t'-p counterions.top',\n\t\t\t'-o genion.tpr']\n\t\tcall(cmd,logfile='log-grompp-genion',cwd=self.rootdir)\n\t\tcmd = [gmxpaths['make_ndx'],\n\t\t\t'-f solvate-minimized.gro',\n\t\t\t'-o solvate-waters.ndx']\n\t\tcall(cmd,logfile='log-make-ndx-counterions-check',cwd=self.rootdir,\n\t\t\tinpipe='keep 0\\nr '+self.settings['sol_name']+'\\nkeep 1\\nq\\n')\n\t\tcmd = [gmxpaths['genion'],\n\t\t\t'-s genion.tpr',\n\t\t\t'-o counterions.gro',\n\t\t\t'-conc '+str(self.settings['ion_strength']),\n\t\t\t'-n solvate-waters.ndx',\n\t\t\t'-neutral']\n\t\tcall(cmd,logfile='log-genion',cwd=self.rootdir)\n\t\n\t\tprint \"updating topology with counterions\"\n\t\tself.npoz,self.nneg = [int(checkout([\"awk\",\"'/Will try to add / {print $\"+str(col)+\\\n\t\t\t\"}'\",\"log-genion\"],cwd=self.rootdir)) for col in [5,9]]\n\t\tself.nsol = self.nsol - self.npoz - self.nneg\n\t\tself.write_topology_protein('counterions.top')\n\t\t\n\t\tprint \"minimizing with solvent\"\n\t\tself.minimization_method('counterions')\n\t\t\n\t\tprint \"writing structure with correct residue numbers to structure.pdb\"\n\t\twith open(self.rootdir+'system-input.pdb','r') as fp: lines = fp.readlines()\n\t\tstartres = int([line for line in lines if re.match('^ATOM',line)][0][22:25+1])\t\t\n\t\tprint \"according to the input_filename, the starting residue is %d\"%startres\n\t\tprint \"[WARNING] use struture.pdb for post-processing for the right residue numbers\"\n\t\tcmd = [gmxpaths['editconf'],\n\t\t\t'-f counterions.gro',\n\t\t\t'-o structure.pdb',\n\t\t\t'-resnr %d'%startres]\n\t\tcall(cmd,logfile='log-editconf-structure-pdb',cwd=self.rootdir)","def add_computed_gas_concentrations(self):\n # Extract the z-coordinate and T, S, P profile\n zs = self.interp_ds.coords[self.ztsp[0]].values\n Ts = self.interp_ds[self.ztsp[1]].values\n Ss = self.interp_ds[self.ztsp[2]].values\n Ps = self.interp_ds[self.ztsp[3]].values\n \n # Create an air object\n air_names = ['nitrogen', 'oxygen', 'argon', 'carbon_dioxide']\n yk = np.array([0.78084, 0.20946, 0.009340, 0.00036])\n from tamoc import dbm\n air = dbm.FluidMixture(air_names)\n m = air.masses(yk)\n \n # Compute the concentrations adjusted for depth\n Cs = np.zeros((len(zs), len(air_names)))\n for i in range(len(zs)):\n Cs[i,:] = air.solubility(m, Ts[i], 101325., Ss[i])[0,:] * \\\n seawater.density(Ts[i], Ss[i], Ps[i]) / \\\n seawater.density(Ts[i], Ss[i], 101325.)\n \n # Make sure none of these gases are already in the measured profile\n for name in air_names:\n if name in self.interp_ds:\n air_names[air_names.index(name)] = 'computed_' + name\n \n # Add these data to the Profile object\n data = np.hstack((np.atleast_2d(zs).transpose(), Cs))\n names = [self.ztsp[0]] + air_names \n units = [self.ztsp_units[0]] + 4*['kg/m^3']\n self.append(data, names, units)\n \n # Rebuild the interpolator\n self._build_interpolator()","def add_layer(self, freeze = True, add = True):\n if add:\n self.num_layers += 1\n if self.conv_dim == 1:\n new_cnn = layers.Conv1D(self.n_filters,\n (self.n_kernels),\n activation='elu',\n input_shape=(None, self.inp_shape[0], self.n_filters),\n padding=\"same\",\n name='cnn_1d_{}'.format(self.num_layers-1),\n kernel_initializer = initializers.get(self.initializer),\n bias_initializer=initializers.get(\"zeros\"),\n kernel_regularizer=self.regularizer,\n bias_regularizer=self.regularizer\n )\n elif self.conv_dim == 2:\n new_cnn = layers.Conv2D(self.n_filters,\n (self.n_kernels, self.n_kernels),\n activation='elu',\n input_shape=(None, self.inp_shape[0],self.inp_shape[1], self.n_filters),\n padding=\"same\",\n name='cnn_2d_{}'.format(self.num_layers-1),\n kernel_initializer=initializers.get(self.initializer),\n bias_initializer=initializers.get(\"zeros\"),\n kernel_regularizer=self.regularizer,\n bias_regularizer=self.regularizer\n )\n self.list_cnn.append(new_cnn)\n\n if freeze:\n for index in range(0,self.num_layers-1):\n self.list_cnn[index].trainable = False\n else:\n for index in range(0,self.num_layers-1):\n self.list_cnn[index].trainable = True","def recursive_gate(e):\n if isinstance(e, boolean.BaseElement):\n # TODO: Either make the the same or create a constant component.\n s = Switch()\n b.append(s)\n return s\n elif isinstance(e, boolean.Symbol):\n if e in symbol_dict.keys():\n return symbol_dict[e]\n else:\n s = Switch()\n symbol_dict[e] = s\n b.append(s)\n return s\n elif isinstance(e, boolean.Function):\n # All gates are of type Gate instead of And, Or and Not\n if e.order == (1, 1):\n pre = recursive_gate(e.args[0])\n w = Wire(pre)\n b.append(w)\n\n s = boolean.Symbol(None)\n g = Gate(e.subs({e.args[0]: s}),\n {s: w})\n b.append(g)\n return g\n else:\n input_dict = {}\n expr = e\n for arg in e.args:\n pre = recursive_gate(arg)\n w = Wire(pre)\n b.append(w)\n\n s = boolean.Symbol(None)\n expr = expr.subs({arg: s})\n input_dict[s] = w\n g = Gate(expr,\n input_dict)\n b.append(g)\n return g","def alg(c):\n return c[0]*G[0] + c[1]*G[1] + c[2]*G[2]","def add_dcdisorder(self):\n # Add gaussian noise to pinning energies\n if self.lp['V0_pin_gauss'] > 0:\n self.Omg += self.lp['V0_pin_gauss']*np.random.randn(len(self.xy_inner))\n raise RuntimeError('Adding gaussian disorder: are you sure you want to proceed?')\n if self.lp['V0_spring_gauss'] > 0:\n print 'This is not done correctly here'\n self.OmK += self.lp['V0_spring_gauss'] * np.random.randn(np.shape(self.lattice.KL)[0],\n np.shape(self.lattice.KL)[1])\n sys.exit()\n\n if self.lp['V0_pin_flat'] > 0 or self.lp['V0_spring_flat'] > 0:\n # Note that we multiply by two so that V0_pin_flat is the HALF width of the distribution\n flat_disorder = (np.random.rand(len(self.xy_inner))) * 2 - 1.0\n\n if self.lp['V0_pin_flat'] > 0:\n self.Omg += self.lp['V0_pin_flat'] * flat_disorder\n if self.lp['Omg'] < 0:\n self.Omg[self.Omg > 0] = 0.\n elif self.lp['Omg'] > 0:\n self.Omg[self.Omg < 0] = 0.\n\n print('magnetic_gyro_lattice_class.py: V0_pin_flat=', self.lp['V0_pin_flat'])\n print(self.Omg)\n\n if self.lp['V0_spring_flat'] > 0:\n to_add = self.lp['V0_spring_flat'] * flat_disorder[:, np.newaxis] * np.ones_like(self.OmK)\n self.OmK[np.abs(self.OmK) > 0] += to_add[np.abs(self.OmK) > 0]\n if self.lp['Omk'] < 0:\n self.OmK[self.OmK > 0] = 0.\n elif self.lp['Omk'] > 0:\n self.OmK[self.OmK < 0] = 0.\n\n print('magnetic_gyro_lattice_class.py: OmK after flat disorder= ')\n print(self.OmK)\n # sys.exit()","def test_guider_start_arcsOn(self):\n sopTester.updateModel('mcp', TestHelper.mcpState['arcs'])\n self._guider_start(8, 20, 0, 0)","def G(self, dstrct):\n # Instead of hardcoding the method, it could be supplied as a KWarg\n\n if self.compactness_method == 'CSPC':\n self.G_ = self.CSPC_score(dstrct)\n\n elif self.compactness_method == 'circular':\n self.G_ = self.circular_score(dstrct)\n\n elif self.compactness_method == 'convexity':\n self.G_ = self.convexity_score(dstrct)\n\n elif self.compactness_method == 'average':\n self.G_ = np.mean([self.w_R*self.circular_score(dstrct),\n self.w_C*self.convexity_score(dstrct)])\n elif self.compactness_method == 'sum':\n self.G_ = self.w_R*self.circular_score(dstrct) + \\\n self.w_C*self.convexity_score(dstrct)\n else:\n msg = (\"Valid compactness methods are \"\n \"'CSPC', 'circular', 'convexity', 'average', and 'sum'\")\n raise Exception(msg)\n\n # While all neighbors are unassigned, we want to weight compactness\n multiplier = 2 - any([pt.assigned for pt in dstrct.neighbors])\n # self.G_ *= self.w_G * (2-self.assigned)\n self.G_ *= self.w_G * multiplier\n return self.G_","def GED_n(Gn, lib='gedlibpy', cost='CHEM_1', method='IPFP',\n edit_cost_constant=[], stabilizer='min', repeat=50):\n if lib == 'gedlibpy':\n def convertGraph(G):\n \"\"\"Convert a graph to the proper NetworkX format that can be\n recognized by library gedlibpy.\n \"\"\"\n G_new = nx.Graph()\n for nd, attrs in G.nodes(data=True):\n G_new.add_node(str(nd), chem=attrs['atom_symbol'])\n for nd1, nd2, attrs in G.edges(data=True):\n # G_new.add_edge(str(nd1), str(nd2), valence=attrs['bond_type'])\n G_new.add_edge(str(nd1), str(nd2))\n\n return G_new\n\n # gedlibpy.restart_env()\n gedlibpy.add_nx_graph(convertGraph(g1), \"\")\n gedlibpy.add_nx_graph(convertGraph(g2), \"\")\n\n listID = gedlibpy.get_all_graph_ids()\n gedlibpy.set_edit_cost(cost, edit_cost_constant=edit_cost_constant)\n gedlibpy.init()\n gedlibpy.set_method(method, \"\")\n gedlibpy.init_method()\n\n g = listID[0]\n h = listID[1]\n if stabilizer == None:\n gedlibpy.run_method(g, h)\n pi_forward = gedlibpy.get_forward_map(g, h)\n pi_backward = gedlibpy.get_backward_map(g, h)\n upper = gedlibpy.get_upper_bound(g, h)\n lower = gedlibpy.get_lower_bound(g, h)\n elif stabilizer == 'min':\n upper = np.inf\n for itr in range(repeat):\n gedlibpy.run_method(g, h)\n upper_tmp = gedlibpy.get_upper_bound(g, h)\n if upper_tmp < upper:\n upper = upper_tmp\n pi_forward = gedlibpy.get_forward_map(g, h)\n pi_backward = gedlibpy.get_backward_map(g, h)\n lower = gedlibpy.get_lower_bound(g, h)\n if upper == 0:\n break\n\n dis = upper\n\n # make the map label correct (label remove map as np.inf)\n nodes1 = [n for n in g1.nodes()]\n nodes2 = [n for n in g2.nodes()]\n nb1 = nx.number_of_nodes(g1)\n nb2 = nx.number_of_nodes(g2)\n pi_forward = [nodes2[pi] if pi < nb2 else np.inf for pi in pi_forward]\n pi_backward = [nodes1[pi] if pi <\n nb1 else np.inf for pi in pi_backward]\n\n return dis, pi_forward, pi_backward","def _add_pairblend(self, dgmod, rigid, transform):\n\n assert isinstance(dgmod, cmdx.DGModifier)\n\n pair_blend = dgmod.create_node(\"pairBlend\")\n dgmod.set_attr(pair_blend[\"isHistoricallyInteresting\"], False)\n\n # Establish initial values, before keyframes\n # tm = cmdx.Tm(self._cache[(transform, \"matrix\")])\n\n # Read from matrix, as opposed to the rotate/translate channels\n # to account for jointOrient, pivots and all manner of things\n # translate = tm.translation()\n # rotate = tm.rotation()\n\n translate = self._cache[(transform, \"translate\")]\n rotate = self._cache[(transform, \"rotate\")]\n\n dgmod.set_attr(pair_blend[\"inTranslate1\"], translate)\n dgmod.set_attr(pair_blend[\"inRotate1\"], rotate)\n\n dgmod.connect(rigid[\"outputTranslateX\"], pair_blend[\"inTranslateX2\"])\n dgmod.connect(rigid[\"outputTranslateY\"], pair_blend[\"inTranslateY2\"])\n dgmod.connect(rigid[\"outputTranslateZ\"], pair_blend[\"inTranslateZ2\"])\n dgmod.connect(rigid[\"outputRotateX\"], pair_blend[\"inRotateX2\"])\n dgmod.connect(rigid[\"outputRotateY\"], pair_blend[\"inRotateY2\"])\n dgmod.connect(rigid[\"outputRotateZ\"], pair_blend[\"inRotateZ2\"])\n\n # Let the animator see the raw animation values, no physics\n dgmod.connect(self._tree_root[0][\"simulated\"], pair_blend[\"weight\"])\n\n if self._opts[\"autoKey\"]:\n # Generate default animation curves, it's expected since you can no\n # longer see whether channels are keyed or not, now being green.\n time = cmdx.currentTime()\n mapping = (\n (\"animCurveTL\", translate.x, \"inTranslateX1\"),\n (\"animCurveTL\", translate.y, \"inTranslateY1\"),\n (\"animCurveTL\", translate.z, \"inTranslateZ1\"),\n (\"animCurveTA\", rotate.x, \"inRotateX1\"),\n (\"animCurveTA\", rotate.y, \"inRotateY1\"),\n (\"animCurveTA\", rotate.z, \"inRotateZ1\")\n )\n\n for curve, value, dst in mapping:\n curve = dgmod.create_node(curve)\n curve.key(time, value)\n dgmod.connect(curve[\"output\"], pair_blend[dst])\n\n # Transfer existing animation/connections\n for src, dst in transform.data.get(\"priorConnections\", {}).items():\n dst = pair_blend[dst]\n dgmod.connect(src, dst)\n\n commands._connect_transform(dgmod, pair_blend, transform)\n\n return pair_blend","def _auto_blend(self, dgmod):\n\n assert isinstance(dgmod, cmdx.DGModifier)\n\n root, _ = self._root\n root_rigid = root.shape(type=\"rdRigid\")\n\n for rigid in self._new_rigids:\n\n # Don't bother with the root\n if rigid == root_rigid:\n continue\n\n transform = rigid.parent()\n blend = self._add_pairblend(dgmod, rigid, transform)\n self._auto_influence(dgmod, rigid, blend)","def add_state(self, state):\n if self.rate_variation:\n if not self.feature_rates:\n # Set all rates to 1.0 in a big plate\n plate = ET.SubElement(state, \"plate\", {\n \"var\":\"feature\",\n \"range\":\",\".join(self.features)})\n param = ET.SubElement(plate, \"parameter\", {\n \"id\":\"featureClockRate:%s:$(feature)\" % self.name,\n \"name\":\"stateNode\"})\n param.text=\"1.0\"\n else:\n # Give each rate a custom value\n for f in self.features:\n param = ET.SubElement(state, \"parameter\", {\n \"id\":\"featureClockRate:%s:%s\" % (self.name, f),\n \"name\":\"stateNode\"})\n param.text=str(self.feature_rates.get(f,1.0))\n\n # Give Gamma shape parameter a finite domain\n # Must be > 1.0 for the distribution to be bell-shaped,\n # rather than L-shaped. The domain [1.1,1000] limits feature\n # rate variation to the realms of vague plausibity\n parameter = ET.SubElement(state, \"parameter\", {\"id\":\"featureClockRateGammaShape:%s\" % self.name, \"lower\":\"1.1\",\"upper\":\"100.0\",\"name\":\"stateNode\"})\n parameter.text=\"5.0\"\n # Gamma scale parameter's domain is defined *implicilty*\n # by the fact that the operators maintain shape*scale = 1.0\n parameter = ET.SubElement(state, \"parameter\", {\"id\":\"featureClockRateGammaScale:%s\" % self.name, \"name\":\"stateNode\"})\n parameter.text=\"0.2\"","def get_gate(gate, params, num_ctrl_qubits=None):\n if gate[0] == \"c\":\n return get_gate(gate[1:], params, num_ctrl_qubits).ctrl()\n if gate == \"toffoli\":\n return get_gate(\"ccx\", params, num_ctrl_qubits)\n if gate[0:2] == \"mc\":\n name = gate[2:]\n for _ in range(num_ctrl_qubits):\n name = \"c\" + name\n return get_gate(name, params, num_ctrl_qubits)\n if len(params) == 0:\n return GATE_DIC[gate]\n\n return GATE_DIC[gate](*params)","def makeDstar2D0Pi( name\n , config\n , DecayDescriptor\n , inputSel\n ) :\n\n daugCuts = \"(TRCHI2DOF < %(Daug_TRCHI2DOF_MAX)s)\" % locals()['config']\n combCuts = \"((AM - AM1) < %(Dstar_AMDiff_MAX)s* MeV)\" % locals()['config']\n dstarCuts = \"(VFASPF(VCHI2/VDOF) < %(Dstar_VCHI2VDOF_MAX)s)\" \\\n \"& ((M - M1) < %(Dstar_MDiff_MAX)s* MeV)\" % locals()['config']\n\n _Dstar = CombineParticles( DecayDescriptor = DecayDescriptor\n , DaughtersCuts = { \"pi+\" : daugCuts }\n , CombinationCut = combCuts\n , MotherCut = dstarCuts\n )\n\n return Selection( name+'Sel',\n Algorithm = _Dstar,\n RequiredSelections = inputSel\n )","def condensation(G):\n scc = strongly_connected_components(G)\n mapping = dict([(n,tuple(sorted(c))) for c in scc for n in c])\n cG = nx.DiGraph()\n for u in mapping:\n cG.add_node(mapping[u])\n for _,v,d in G.edges_iter(u, data=True):\n if v not in mapping[u]:\n cG.add_edge(mapping[u], mapping[v])\n return cG","def compile(self):\n m, n = self.input_shape[1], self.input_shape[2]\n\n inp = Input(shape=self.input_shape, traces=True)\n self.add_layer(inp, \"DoG\")\n\n s1 = LIFNodes(shape=(18, m, n), traces=True)\n self.add_layer(s1, \"conv_1\")\n c1 = LIFNodes(shape=(18, m // 2, n // 2), traces=True)\n self.add_layer(c1, \"pool_1\")\n\n s2 = LIFNodes(shape=(24, m // 2, n // 2), traces=True)\n self.add_layer(s2, \"conv_2\")\n c2 = LIFNodes(shape=(24, m // 4, n // 4), traces=True)\n self.add_layer(c2, \"pool_2\")\n\n s3 = LIFNodes(shape=(32, m // 4, n // 4), traces=True)\n self.add_layer(s3, \"conv_3\")\n f = LIFNodes(shape=(32, 1), traces=True)\n self.add_layer(f, \"global_pool\")\n\n conv1 = Conv2dConnection(inp, s1, 5, padding=2, weight_decay=0.01,\n nu=0.01, update_rule=PostPre, decay=0.5)\n self.add_connection(conv1, \"DoG\", \"conv_1\")\n pool1 = MaxPool2dConnection(s1, c1, 2, 2, decay=0.5)\n self.add_connection(pool1, \"conv_1\", \"pool_1\")\n\n conv2 = Conv2dConnection(c1, s2, 3, padding=1, weight_decay=0.01,\n nu=0.01, update_rule=PostPre, decay=0.5)\n self.add_connection(conv2, \"pool_1\", \"conv_2\")\n pool2 = MaxPool2dConnection(s2, c2, 2, 2, decay=0.5)\n self.add_connection(pool2, \"conv_2\", \"pool_2\")\n\n conv3 = Conv2dConnection(c2, s3, 3, padding=1, weight_decay=0.01,\n nu=0.01, update_rule=PostPre, decay=0.5)\n self.add_connection(conv3, \"pool_2\", \"conv_3\")\n global_pool = MaxPool2dConnection(s3, f, (m // 4, n // 4), decay=0.5)\n self.add_connection(global_pool, \"conv_3\", \"global_pool\")\n\n monitor = NetworkMonitor(self, layers=[\"DoG\", \"conv_1\", \"pool_1\",\n \"conv_2\", \"pool_2\",\n \"conv_3\", \"global_pool\"],\n connections=[(\"DoG\", \"conv_1\"),\n (\"pool_1\", \"conv_2\"),\n (\"pool_2\", \"conv_3\")],\n state_vars=[\"w\", \"s\"])\n self.add_monitor(monitor, \"network_monitor\")\n\n return self","def add(num1, num2, Cin):\n Cin=0\n l2=[]\n final=\"\"\n\n \"\"\"Using for loop for starting addition from the last indexed number\"\"\"\n for i in range(len(num1)-1,-1,-1):\n bit1=num1[i]#storing each indexed() value of num1 in bit1\n bit2=num2[i]#storing each indexed() value of num2 in bit2\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\n Cin=Cout#declaring cout as cin for next bit addition\n l2.append(SUM)#adding SUM to l2\n l3=l2[::-1]##reversing the value of l2\n final+=str(l2[-1])#converting the list value to string\n final1=final[::-1]#reversing string value\n return final1 #returning the binary addition as string","def bcs(self, arg):\n\n self.pc += arg if self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def manage_addCASSSO(self, id='sso', REQUEST=None):\n\n id = 'sso'\n ob = CASSSO()\n ob.id = id\n self._setObject(id, ob)\n if REQUEST is not None:\n return self.manage_main(self, REQUEST)","def test_sdg_gate_nondeterministic_minimal_basis_gates(self):\n shots = 2000\n circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_1q_clifford.sdg_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def GAStep(self):\n\n self.updateMatingPool()\n self.newGeneration()","def iadd(state: State) -> State:\n cell = state.array[state.index] or 0\n return state._replace(acc=state.acc + cell)","def addS6(self):\n self.space6 += 1","def setup_ssem(self):\n \n groundBox = box_polygon_shape(-20,-500,1,1) # A tiny box that just acts as the ground body for everything else\n groundBody = self.world.CreateStaticBody(shapes=groundBox)\n self.memory_sender_y = -500\n self.groundBody = groundBody\n # Initial charge for main injector\n self.ball_bearing_block(0,190,cols=16)\n self.add_static_polygon([ (0,20), (100,0), (100,5), (0,25)], -132, 220)\n self.add_static_polygon([ (0,0), (3,0), (3,20), (0,20)], -132, 240)\n self.injector_cranks = []\n self.parts.main_injector_raiser = self.injector(-32,150, groundBody, injector_crank_array=self.injector_cranks)\n\n (self.parts.memory_selector_holdoff, self.parts.memory_follower_holdoff) = self.memory_module(0,0, groundBody)\n self.upper_regenerators = []\n self.parts.accumulator_diverter_lever = self.diverter_set(0,130, groundBody, slope_x=-240, slope_y=180, return_weight=10) # Diverter 1. Splits to subtractor reader.\n\n self.parts.discard_lever_2 = self.diverter_set(-5,-30, groundBody, discard=470) # Diverter 2a. Discard reader-pulse data.\n self.parts.upper_regen_control = self.regenerator(-5,-65, groundBody, self.upper_regenerators) # Regenerator 1. For regenning anything read from memory.\n self.parts.ip_diverter_lever = self.diverter_set(-5,-95, groundBody, slope_x=320, slope_y=170, start_at=3, return_weight=5) # Diverter 1. Splits to instruction counter.\n self.parts.diverter_3 = self.diverter_set(-10,-158, groundBody, slope_x=200, slope_y=310) # Diverter 3; splits to instruction reg/PC\n \n # PC injector\n pc_injector_x = 230\n pc_injector_y = -290\n self.pc_injector_cranks = [] \n self.parts.pc_injector_raiser = self.injector(pc_injector_x,pc_injector_y, groundBody, injector_crank_array=self.pc_injector_cranks, columns=5)\n # Initial charge for PC injector\n self.ball_bearing_block(250,-240,cols=8)\n\n\n sub_pos_x = -15\n sub_pos_y = -220\n self.parts.accumulator_reset_lever = self.subtractor(sub_pos_x,sub_pos_y, groundBody, discard_bands=True, toggle_joint_array=self.accumulator_toggles, comparison_output=True)\n self.dropper = self.slow_drop_unit(groundBody, sub_pos_x-18, sub_pos_y+40)\n\n # The 'skip lever' - the large balance arm which injects one\n # into the program counter when comparison (CMP) succeeds\n skip_lever_x = sub_pos_x - 200\n skip_lever_y = sub_pos_y - 200\n a = fixtureDef(shape=polygonShape(vertices=[(-50,-32), (0,-30), (0,-25), (-50,-30)]), filter=filters[0], density=1.0)\n b = fixtureDef(shape=box_polygon_shape(0,-30,5,30), filter=filters[0], density=1.0)\n c = fixtureDef(shape=box_polygon_shape(-30,-30,5,30), filter=filters[0], density=1.0)\n d = fixtureDef(shape=box_polygon_shape(0,0,300,5), filter=filters[2], density=1.0)\n e = fixtureDef(shape=box_polygon_shape(285,-15,15,15), filter=filters[2], density=2.10)\n f = fixtureDef(shape=box_polygon_shape(150,-50,5,50), filter=filters[0], density=1.0)\n skip_lever=self.add_multifixture([a,b,d,e,f], skip_lever_x, skip_lever_y)\n skip_lever.attachment_point = (150,-50)\n skip_lever.origin = (skip_lever_x,skip_lever_y)\n\n self.revolving_joint(groundBody, skip_lever, (skip_lever_x+150, skip_lever_y+2.5), friction=0)\n self.add_static_polygon(polygonShape(vertices=box_vertices(0, 0, 10,10)), skip_lever_x+270, skip_lever_y-15, filter=filters[2])\n self.parts.cmp_injector = self.horizontal_injector(skip_lever_x-48,skip_lever_y+257, groundBody)\n self.ball_bearing_block(skip_lever_x-30,skip_lever_y+280,cols=1)\n self.add_static_polygon(polygonShape(vertices=[(0,0), (20,0), (0,20)]), skip_lever_x-30,skip_lever_y+230)\n \n self.lower_regenerators = []\n self.parts.lower_regen_control = self.regenerator(-203,-400, groundBody, self.lower_regenerators)\n #Program counter\n self.parts.pc_reset_lever = self.subtractor(400,-320, groundBody, lines=5, toggle_joint_array=self.ip_toggles, is_actually_adder=True)\n # Thing that adds one ball bearing to the PC\n pc_incrementer_x = 457\n pc_incrementer = self.horizontal_injector(pc_incrementer_x,-240, groundBody)\n # Overspill loose ball bearings from the PC incrementer to the PC reader\n overspill_width = pc_incrementer_x - pc_injector_x - 125\n self.add_static_polygon([ (0, 0), (overspill_width,15), (overspill_width,20), (0,5) ], pc_injector_x+125,pc_injector_y+65)\n\n # Block to stop right-side overspill on incrementer\n self.add_static_polygon([ (0, 0), (5,0), (5,20), (0,20) ], pc_incrementer_x+27,-240+40)\n\n\n self.ball_bearing_block(457+20,-250+30,cols=1)\n self.distance_joint(skip_lever, pc_incrementer)\n\n self.connect_regenerators()\n\n # Large collection plates at the bottom\n self.add_static_polygon([ (-300,-600),(700,-550), (700,-610), (-300,-610)])\n self.add_static_polygon([ (600,-610),(700,-610), (850,-400), (800,-400)])\n self.add_static_polygon([ (-500,-400),(-450,-400), (-310,-610), (-400,-610)])\n\n # Instruction decoder ROM\n self.rom_followers = []\n self.rom_selectors = []\n (self.parts.instruction_selector_holdoff, self.parts.instruction_follower_holdoff) = self.add_row_decoder(200, 0, groundBody, self.rom_followers, self.rom_selectors)\n self.labels.append((\"Instruction decoder\", 400,0,0))\n\n self.add_instruction_cranks(groundBody, 550, 140)\n self.parts.sender_eject = self.memory_sender(198,self.memory_sender_y, groundBody)\n self.connect_memory()\n\n # A guard which stops waste data from the subtractor falling into the instruction register\n self.add_static_polygon([ (0,0), (120,120), (120,123), (0,3)], 120, self.memory_sender_y-10)\n\n # Add one final transfer band to move everything back into band 0\n self.transfer_bands.append((-550+10, -550, [ (-300,800)], 1))","def add_corridor_constraint(self,seg,r,weight=1.0):\n\n constraint_type = \"cylinder\"\n params = dict()\n params['x1'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg],\n self.qr_polytraj.waypoints['y'][0,seg],\n self.qr_polytraj.waypoints['z'][0,seg]])\n params['x2'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg+1],\n self.qr_polytraj.waypoints['y'][0,seg+1],\n self.qr_polytraj.waypoints['z'][0,seg+1]])\n params['der'] = 0\n params['l'] = r # Give the same radius buffer on the end caps\n params['r'] = r\n params['weight'] = weight\n params['keep_out'] = False\n params['active_seg'] = seg\n\n\n self.qr_polytraj.add_constraint(constraint_type,params,dynamic_weighting=False,sum_func=False)","def add_conn(self, a1, a2):\n if self.use_pconn:\n raise ValueError(\"Can not add bonds to systems with pconn - well, we can fix this ;) \")\n self.conn[a1].append(a2)\n self.conn[a2].append(a1)\n d,v,imgi = self.get_distvec(a1,a2)\n self.pconn[a1].append(images[imgi])\n d,v,imgi = self.get_distvec(a2,a1)\n self.pconn[a2].append(images[imgi])\n logger.warning('pconn may not be properly updated!!!')\n return","def _dcg_idcg(relevance_scores, cg_discount):\n # cg_discount is safe\n dcg_k = relevance_scores / cg_discount\n return tf.reduce_sum(dcg_k)","def on_custom_mindstorms_gadget_control(self, directive):\n try:\n payload = json.loads(directive.payload.decode(\"utf-8\"))\n print(\"Control payload: {}\".format(payload))\n control_type = payload[\"type\"]\n\n if control_type == \"moveSteps\":\n # Expected params: [direction, steps, speed]\n self.enemy_not_detected = True\n self._moveSteps(payload[\"direction\"], int(payload[\"steps\"]), int(payload[\"speed\"]))\n\n if control_type == \"patrol\":\n self.patrol_mode = True\n self.enemy_not_detected = True\n \n if control_type == \"smash\":\n print(\"SMASHING\")\n \n self.weapon.on_for_degrees(SpeedPercent(100), 300)\n self.weapon.on_for_degrees(SpeedPercent(-50), 300)\n time.sleep(5)\n self._send_event(EventName.SMASH, {'Smashed': 1})\n #self.smash_mode = False\n print(\"1 smashed\")\n self.enemy_not_detected = True\n print(\"+++++ self.patrol_mode = {} y self.enemy_not_detected = {}\".format(self.patrol_mode, self.enemy_not_detected))\n self.leds.set_color(\"LEFT\", \"GREEN\", 1)\n self.leds.set_color(\"RIGHT\", \"GREEN\", 1)\n \n\n except KeyError:\n print(\"Missing expected parameters: {}\".format(directive))","def assemble_operator(self, parameters, space_group='default'):\n operator = super(RWGDominantSystem, self).assemble_operator(parameters, space_group)\n return operator.weak_form()","def glucose_c1(self, g_t, t_G, a_G, d_g_t=0):\n return -(1/t_G)*g_t+(a_G/t_G)*d_g_t","def add_classifier_state(self,st):\n self.classifier_states.append(st)","def cy(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CY(), target=[control, target])","def add_modified_decoherence_noise(\n prog: \"Program\",\n T1: Union[Dict[int, float], float] = 30e-6,\n T2: Union[Dict[int, float], float] = 30e-6,\n gate_time_1q: float = 50e-9,\n gate_time_2q: float = 150e-09,\n ro_fidelity: Union[Dict[int, float], float] = 0.95,\n) -> \"Program\":\n gates = _get_program_gates(prog)\n #definitions = {\n # def_gate.name: def_gate.matrix for def_gate in prog.defined_gates #figure out what is it for \n #}\n noise_model = _modified_decoherence_noise_model(\n gates,\n T1=T1,\n T2=T2,\n gate_time_1q=gate_time_1q,\n gate_time_2q=gate_time_2q,\n ro_fidelity=ro_fidelity\n )\n return apply_modified_noise_model(prog, noise_model)","def GED(g1, g2, lib='gedlibpy', cost='CHEM_1', method='IPFP',\n edit_cost_constant=[], stabilizer='min', repeat=50):\n if lib == 'gedlibpy':\n def convertGraph(G):\n \"\"\"Convert a graph to the proper NetworkX format that can be\n recognized by library gedlibpy.\n \"\"\"\n G_new = nx.Graph()\n for nd, attrs in G.nodes(data=True):\n G_new.add_node(str(nd), chem=attrs['atom_symbol'])\n# G_new.add_node(str(nd), x=str(attrs['attributes'][0]),\n# y=str(attrs['attributes'][1]))\n for nd1, nd2, attrs in G.edges(data=True):\n G_new.add_edge(str(nd1), str(nd2), valence=attrs['bond_type'])\n# G_new.add_edge(str(nd1), str(nd2))\n\n return G_new\n\n gedlibpy.restart_env()\n gedlibpy.add_nx_graph(convertGraph(g1), \"\")\n gedlibpy.add_nx_graph(convertGraph(g2), \"\")\n\n listID = gedlibpy.get_all_graph_ids()\n gedlibpy.set_edit_cost(cost, edit_cost_constant=edit_cost_constant)\n gedlibpy.init()\n gedlibpy.set_method(method, \"\")\n gedlibpy.init_method()\n\n g = listID[0]\n h = listID[1]\n if stabilizer == None:\n gedlibpy.run_method(g, h)\n pi_forward = gedlibpy.get_forward_map(g, h)\n pi_backward = gedlibpy.get_backward_map(g, h)\n upper = gedlibpy.get_upper_bound(g, h)\n lower = gedlibpy.get_lower_bound(g, h)\n elif stabilizer == 'mean':\n # @todo: to be finished...\n upper_list = [np.inf] * repeat\n for itr in range(repeat):\n gedlibpy.run_method(g, h)\n upper_list[itr] = gedlibpy.get_upper_bound(g, h)\n pi_forward = gedlibpy.get_forward_map(g, h)\n pi_backward = gedlibpy.get_backward_map(g, h)\n lower = gedlibpy.get_lower_bound(g, h)\n upper = np.mean(upper_list)\n elif stabilizer == 'median':\n if repeat % 2 == 0:\n repeat += 1\n upper_list = [np.inf] * repeat\n pi_forward_list = [0] * repeat\n pi_backward_list = [0] * repeat\n for itr in range(repeat):\n gedlibpy.run_method(g, h)\n upper_list[itr] = gedlibpy.get_upper_bound(g, h)\n pi_forward_list[itr] = gedlibpy.get_forward_map(g, h)\n pi_backward_list[itr] = gedlibpy.get_backward_map(g, h)\n lower = gedlibpy.get_lower_bound(g, h)\n upper = np.median(upper_list)\n idx_median = upper_list.index(upper)\n pi_forward = pi_forward_list[idx_median]\n pi_backward = pi_backward_list[idx_median]\n elif stabilizer == 'min':\n upper = np.inf\n for itr in range(repeat):\n gedlibpy.run_method(g, h)\n upper_tmp = gedlibpy.get_upper_bound(g, h)\n if upper_tmp < upper:\n upper = upper_tmp\n pi_forward = gedlibpy.get_forward_map(g, h)\n pi_backward = gedlibpy.get_backward_map(g, h)\n lower = gedlibpy.get_lower_bound(g, h)\n if upper == 0:\n break\n elif stabilizer == 'max':\n upper = 0\n for itr in range(repeat):\n gedlibpy.run_method(g, h)\n upper_tmp = gedlibpy.get_upper_bound(g, h)\n if upper_tmp > upper:\n upper = upper_tmp\n pi_forward = gedlibpy.get_forward_map(g, h)\n pi_backward = gedlibpy.get_backward_map(g, h)\n lower = gedlibpy.get_lower_bound(g, h)\n elif stabilizer == 'gaussian':\n pass\n\n dis = upper\n\n # make the map label correct (label remove map as np.inf)\n nodes1 = [n for n in g1.nodes()]\n nodes2 = [n for n in g2.nodes()]\n nb1 = nx.number_of_nodes(g1)\n nb2 = nx.number_of_nodes(g2)\n pi_forward = [nodes2[pi] if pi < nb2 else np.inf for pi in pi_forward]\n pi_backward = [nodes1[pi] if pi <\n nb1 else np.inf for pi in pi_backward]\n\n return dis, pi_forward, pi_backward","def __init__(self, *args):\n moose.HHChannel.__init__(self,*args)\n self.Ek = VKDR\n self.Gbar = GKDR\n self.addField('ion')\n self.setField('ion','K')\n self.Xpower = 1 # This will create HHGate instance xGate inside the Na channel\n #self.Ypower = 0 # This will create HHGate instance yGate inside the Na channel\n ## Below gates get created after Xpower or Ypower are set to nonzero values\n ## I don't anymore have to explicitly create these attributes in the class\n #self.xGate = moose.HHGate(self.path + \"/xGate\")\n #self.yGate = moose.HHGate(self.path + \"/yGate\")\n self.xGate.A.xmin = VMIN\n self.xGate.A.xmax = VMAX\n self.xGate.A.xdivs = NDIVS\n self.xGate.B.xmin = VMIN\n self.xGate.B.xmax = VMAX\n self.xGate.B.xdivs = NDIVS\n \n v = VMIN\n\n for i in range(NDIVS+1):\n mtau = calc_KA_mtau(v)\n self.xGate.A[i] = calc_KA_minf(v)/mtau\n self.xGate.B[i] = 1.0/mtau\n v = v + dv","def __init__(self, *args):\n _gdi_.GCDC_swiginit(self,_gdi_.new_GCDC(*args))\n self.__dc = args[0] # save a ref so the other dc will not be deleted before self","def add_carboxyl(atom, atom_list, added_functional_groups, ct):\n \n global anywhere_map\n global edge_map\n current_size = len(atom_list)\n placed = 0\n alpha = random.randint(0,359)\n x = atom.x\n y = atom.y\n z = atom.z\n while (placed <= 359):\n alpha += 1\n carbon_atom = Atom(current_size + 1, 'C4', 'C1A', str(added_functional_groups + 1), float(\"{0:.3f}\".format(x)), float(\"{0:.3f}\".format(y)), float(\"{0:.3f}\".format(ct * 1.52 + z)))\n atom_list.append(carbon_atom)\n if ((len(identify_bonds(carbon_atom, atom_list)) == 1) and (identify_bonds(carbon_atom, atom_list)[0][0].atom_number == atom.atom_number)):\n h = math.sin(math.radians(60)) * 1.20\n oxygen_atom_1 = Atom(current_size + 2, 'OJ', 'C1A', str(added_functional_groups + 1), float(\"{0:.3f}\".format(carbon_atom.x - math.cos(math.radians(alpha)) * h)), float(\"{0:.3f}\".format(carbon_atom.y - math.sin(math.radians(alpha)) * h)), float(\"{0:.3f}\".format(carbon_atom.z + ct * math.cos(math.radians(60)) * 1.20)))\n atom_list.append(oxygen_atom_1)\n if ((len(identify_bonds(oxygen_atom_1, atom_list)) == 1) and (identify_bonds(oxygen_atom_1, atom_list)[0][0].atom_number == carbon_atom.atom_number)):\n h = math.sin(math.radians(60)) * 1.34\n oxygen_atom_2 = Atom(current_size + 3, 'OK', 'C1A', str(added_functional_groups + 1), float(\"{0:.3f}\".format(carbon_atom.x - math.cos(math.radians(alpha + 180)) * h)), float(\"{0:.3f}\".format(carbon_atom.y - math.sin(math.radians(alpha+180)) * h)), float(\"{0:.3f}\".format(carbon_atom.z + ct * math.cos(math.radians(60)) * 1.34)) )\n atom_list.append(oxygen_atom_2)\n if ((len(identify_bonds(oxygen_atom_2, atom_list)) == 1) and (identify_bonds(oxygen_atom_2, atom_list)[0][0].atom_number == carbon_atom.atom_number)):\n hydrogen_atom = Atom(current_size + 4, 'HK', 'C1A', str(added_functional_groups + 1), float(\"{0:.3f}\".format(oxygen_atom_2.x)), float(\"{0:.3f}\".format(oxygen_atom_2.y)), float(\"{0:.3f}\".format(oxygen_atom_2.z+ct*0.98)))\n atom_list.append(hydrogen_atom)\n if ((len(identify_bonds(hydrogen_atom, atom_list)) == 1) and (identify_bonds(hydrogen_atom, atom_list)[0][0].atom_number == oxygen_atom_2.atom_number)):\n placed = 888\n if atom in edge_map: edge_map.remove(atom)\n if atom in anywhere_map: anywhere_map.remove(atom)\n CY = Atom(atom.atom_number, 'CY', 'C1A', carbon_atom.residue_number, atom.x, atom.y, atom.z)\n atom_list.append(CY)\n atom_list.remove(atom)\n del atom\n else:\n placed += 5\n del hydrogen_atom\n del atom_list[current_size + 3]\n del oxygen_atom_2\n del atom_list[current_size + 2]\n del oxygen_atom_1\n del atom_list[current_size + 1]\n del carbon_atom\n del atom_list[current_size + 0]\n else:\n placed += 5\n del oxygen_atom_2\n del atom_list[current_size + 2]\n del oxygen_atom_1\n del atom_list[current_size + 1]\n del carbon_atom\n del atom_list[current_size + 0]\n else:\n placed += 5\n del oxygen_atom_1\n del atom_list[current_size + 1]\n del carbon_atom\n del atom_list[current_size + 0]\n else:\n placed += 5\n del carbon_atom \n del atom_list[current_size + 0]\n return atom_list","def add_disease(self, disease):\n self.diseases.append(disease)","def s_dg(self, q0, ctrl=None):\n self.__add_quantum_gate(kind=PHASE_SHIFT_S_, qid=[q0], ctrl=ctrl)\n return self"],"string":"[\n \"def gate(self):\\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)\",\n \"def build_glyCB(self, gCBd: Dihedron): # -> None:\\n ...\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def glycosylate(self):\\n chid = self.chain.get()\\n sequon = self.sequon.get()\\n self.sequon_colors[sequon] = [.7, .1, 0]\\n key = self.sequon.get()\\n residue = self.myGlycosylator.get_residue(key)\\n #Build new glycan\\n if self.selected_glycan:\\n self.myGlycosylator.connect_topology['SELECTED'] = self.selected_glycan[1]\\n #build from current glycan\\n if key in self.original_glycans:\\n original_glycan = self.original_glycanMolecules[key].atom_group\\n r,t = self.original_glycans[key]\\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\\n else:\\n original_glycan = None\\n connect_tree = None \\n #Use current glycan\\n else:\\n original_glycan = self.original_glycanMolecules[key]\\n r,t = self.original_glycans[key]\\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\\n self.myGlycosylator.connect_topology['SELECTED'] = self.myGlycosylator.build_connect_topology(original_glycan) \\n original_glycan = original_glycan.atom_group\\n \\n segname = 'G'+key.split(',')[2]\\n glycan,bonds = self.myGlycosylator.glycosylate('SELECTED', \\n template_glycan_tree = connect_tree, \\n template_glycan = original_glycan,\\n link_residue=residue, link_patch = 'NGLB', chain = 'G', segname=segname)\\n new_glycan = glc.Molecule(key)\\n new_glycan.set_AtomGroup(glycan, bonds = bonds)\\n self.myGlycosylator.assign_patches(new_glycan)\\n self.linked_glycanMolecules[key] = new_glycan\\n self.linked_glycans[key] = [new_glycan.rootRes, new_glycan.interresidue_connectivity]\\n self.names.update(new_glycan.get_names())\\n # Update glycoprotein and sequon panels\\n self.draw_glycoprotein(chid)\\n self.draw_glycan(sequon)\",\n \"def add_connector(self):\\n \\n no = len(self.connectors)\\n state = {}\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % no\\n \\n if len(self.connectors)>0:\\n state = self.connectors[-1].get_state()\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % (no)\\n else:\\n if self.mount == self.MOUNT_THT:\\n state[\\\"p_shape\\\"] = Con.SHAPE_HOLE\\n elif self.mount == self.MOUNT_SMD:\\n state[\\\"p_shape\\\"] = Con.SHAPE_PAD\\n \\n c = Con(no)\\n c.set_state(state) \\n \\n self.sch_layers[\\\"pins\\\"].add(c.s_svg)\\n self.pcb_layers[\\\"copper1\\\"].add(c.p_svg)\\n self.connectors.append(c)\",\n \"def test_append_dangling_gate(self, circuit):\\n match = (\\n r\\\"Number of wire IDs \\\\(2\\\\) must match the number of wires connected to the gate \\\\(1\\\\).\\\"\\n )\\n gate = jet.GateFactory.create(\\\"H\\\")\\n with pytest.raises(ValueError, match=match):\\n circuit.append_gate(gate, wire_ids=[0, 1])\",\n \"def load_gates(chip):\\n for gate_id in chip.gates:\\n gate_coord = chip.gates[gate_id]\\n gate = gt.Gate(gate_id, gate_coord[\\\"x\\\"], gate_coord[\\\"y\\\"])\\n chip.coordinates[0][gate_coord[\\\"y\\\"]][gate_coord[\\\"x\\\"]].gate = gate\\n\\n return chip\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def BCS(self, value):\\n if self.reg.C:\\n self.reg.PC += value\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def syed_dilation(data, vessel):\",\n \"def add(self, sgid, other, proto_spec, direction=\\\"in\\\"):\\n # returns bool\\n # AuthorizeSecurityGroupIngress, AuthorizeSecurityGroupEgress\\n if direction == \\\"in\\\":\\n api = \\\"AuthorizeSecurityGroupIngress\\\"\\n elif direction == \\\"out\\\":\\n api = \\\"AuthorizeSecurityGroupEgress\\\"\\n else:\\n raise ValueError(\\\"direction must be one of ('in', 'out')\\\")\\n return self.modify(api, sgid, other, proto_spec)\",\n \"def add_cd_samples(self): \\n \\n if self.num_hidden == 0:\\n \\n (self.p_xi_given_x_, self.gibbs_samples), self.gibbs_updates =\\\\\\n theano.scan(self.gibbs_step_fully_visible, n_steps = self.gibbs_steps)\\n \\n if self.num_hidden > 0:\\n \\n if \\\"PCD\\\" in self.algorithm:\\n init_chain = self.persistent_gibbs\\n else:\\n # positive phase\\n _, _, hid_sample = self.get_h_given_v_samples(self.x)\\n\\n init_chain = hid_sample\\n \\n (\\n [\\n vis_inputs,\\n vis_outputs,\\n vis_samples,\\n hid_inputs,\\n hid_means,\\n hid_samples\\n ],\\n updates\\n ) = theano.scan(\\n self.gibbs_step_rbm_hid,\\n outputs_info=[None, None, None, None, None, init_chain],\\n n_steps= self.gibbs_steps)\\n \\n self.updates.update(updates)\\n \\n self.hid_samples = hid_samples[-1]\\n \\n self.rbm_cd_samples = theano.gradient.disconnected_grad(vis_samples[-1])\\n \\n self.rbm_vis_outputs = theano.gradient.disconnected_grad(vis_outputs[-1])\",\n \"def globalphase_compiler(self, gate, args):\\n pass\",\n \"def globalphase_compiler(self, gate, args):\\n pass\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def __init__(self, input, output) :\\n Gate.__init__(self, [input], output)\",\n \"def _insert_CD_state(self, alpha, clear=True):\\n # Defines a new thermodynamic state based on the neighboring state\\n neighbor_ind = [alpha < p['alpha']\\n for p in self.data['CD'].protocol].index(True) - 1\\n params_n = self.system.paramsFromAlpha(\\n alpha, params_o=self.data['CD'].protocol[neighbor_ind])\\n\\n # For sampling importance resampling,\\n # prepare an augmented matrix for pymbar calculations\\n # with a new thermodynamic state\\n (u_kln_s, N_k) = self._u_kln(self.data['CD'].Es, self.data['CD'].protocol)\\n (K, L, N) = u_kln_s.shape\\n\\n u_kln_n = self._u_kln(self.data['CD'].Es, [params_n])[0]\\n L += 1\\n N_k = np.append(N_k, [0])\\n\\n u_kln = np.zeros([K, L, N])\\n u_kln[:, :-1, :] = u_kln_s\\n for k in range(K):\\n u_kln[k, -1, :] = u_kln_n[k, 0, :]\\n\\n # Determine SIR weights\\n weights = self.run_MBAR(u_kln, N_k, augmented=True)[1][:, -1]\\n weights = weights / sum(weights)\\n\\n # Resampling\\n # Convert linear indices to 3 indicies: state, cycle, and snapshot\\n cum_N_state = np.cumsum([0] + list(N_k))\\n cum_N_cycle = [np.cumsum([0] + [self.data['CD'].Es[k][c]['MM'].shape[0] \\\\\\n for c in range(len(self.data['CD'].Es[k]))]) for k in range(len(self.data['CD'].Es))]\\n\\n def linear_index_to_snapshot_index(ind):\\n state_index = list(ind < cum_N_state).index(True) - 1\\n nis_index = ind - cum_N_state[state_index]\\n cycle_index = list(nis_index < cum_N_cycle[state_index]).index(True) - 1\\n nic_index = nis_index - cum_N_cycle[state_index][cycle_index]\\n return (state_index, cycle_index, nic_index)\\n\\n def snapshot_index_to_linear_index(state_index, cycle_index, nic_index):\\n return cum_N_state[state_index] + cum_N_cycle[state_index][\\n cycle_index] + nic_index\\n\\n # Terms to copy\\n if self.args.params['CD']['pose'] > -1:\\n # Pose BPMF\\n terms = ['MM',\\\\\\n 'k_angular_ext','k_spatial_ext','k_angular_int'] + scalables\\n else:\\n # BPMF\\n terms = ['MM', 'site'] + scalables\\n\\n CD_Es_s = []\\n confs_s = []\\n for c in range(len(self.data['CD'].Es[0])):\\n CD_Es_c = dict([(term, []) for term in terms])\\n confs_c = []\\n for n_in_c in range(len(self.data['CD'].Es[-1][c]['MM'])):\\n if (cum_N_cycle[-1][c] == 0):\\n (snapshot_s,snapshot_c,snapshot_n) = linear_index_to_snapshot_index(\\\\\\n np.random.choice(range(len(weights)), size = 1, p = weights)[0])\\n else:\\n snapshot_c = np.inf\\n while (snapshot_c > c):\\n (snapshot_s,snapshot_c,snapshot_n) = linear_index_to_snapshot_index(\\\\\\n np.random.choice(range(len(weights)), size = 1, p = weights)[0])\\n for term in terms:\\n CD_Es_c[term].append(\\\\\\n np.copy(self.data['CD'].Es[snapshot_s][snapshot_c][term][snapshot_n]))\\n if self.args.params['CD']['keep_intermediate']:\\n # Has not been tested:\\n confs_c.append(\\\\\\n np.copy(self.data['CD'].confs['samples'][snapshot_s][snapshot_c]))\\n for term in terms:\\n CD_Es_c[term] = np.array(CD_Es_c[term])\\n CD_Es_s.append(CD_Es_c)\\n confs_s.append(confs_c)\\n\\n # Insert resampled values\\n self.data['CD'].protocol.insert(neighbor_ind + 1, params_n)\\n self.data['CD'].Es.insert(neighbor_ind + 1, CD_Es_s)\\n self.data['CD'].confs['samples'].insert(neighbor_ind + 1, confs_s)\\n self.data['CD'].confs['replicas'].insert(neighbor_ind+1, \\\\\\n np.copy(self.data['CD'].confs['replicas'][neighbor_ind]))\\n\\n if clear:\\n self._clear_f_RL()\",\n \"def _gyration(self, x, y, v, c):\\n xy = self._mobius_add(x, y, c)\\n yv = self._mobius_add(y, v, c)\\n xyv = self._mobius_add(x, yv, c)\\n return self._mobius_add(-xy, xyv, c)\",\n \"def __init__(self, nfeat, nhid, nclass, dropout, alpha):\\n super(GCN, self).__init__()\\n self.dropout = dropout\\n\\n self.conv1 = GraphConvolutionLayer(nfeat, nhid, dropout=dropout, alpha=alpha, not_final=True)\\n \\n self.add_module('conv1', self.conv1)\\n\\n self.conv2 = GraphConvolutionLayer(nhid, nclass, dropout=dropout, alpha=alpha, not_final=False)\",\n \"def dcgain(self):\\n raise NotImplementedError(\\\"dcgain not implemented for %s objects\\\" %\\n str(self.__class__))\",\n \"def dcgain(sys):\\n return sys.dcgain()\",\n \"def __init__(self, input0, input1, output) :\\n Gate.__init__(self, [input0,input1], output)\",\n \"def add_dut(self):\\n pass\",\n \"def connect(self, gate) :\\n self.notifyList.append(gate)\",\n \"def _gcl(x, r, D, Ia, Ct):\\n\\n Area = np.pi * D ** 2.0 / 4.0\\n m = 1.0 / (np.sqrt(1.0 - Ct))\\n k = np.sqrt((m + 1.0) / 2.0)\\n\\n a1 = 0.435449861 # empirically determined\\n a2 = 0.797853685\\n a3 = -0.124807893\\n a4 = 0.136821858\\n b1 = 15.6298\\n b2 = 1.0\\n R96 = a1 * (np.exp(a2 * Ct * Ct + a3 * Ct + a4)) * (b1 * Ia + b2) * D\\n\\n x0 = (9.6 * D) / ((2.0 * R96 / (k * D)) ** 3.0 - 1.0)\\n term1 = (k * D / 2.0) ** (5.0 / 2.0)\\n term2 = (105.0 / (2.0 * np.pi)) ** (-0.5)\\n term3 = (Ct * Area * x0) ** (-5.0 / 6.0)\\n c1 = term1 * term2 * term3\\n # c45=3*(c1) ** 2\\n\\n term10 = 0.1111 # * WindSpeed # U/9.0\\n term20 = (Ct * Area * (x + x0) ** (-2.0)) ** (1.0 / 3.0)\\n term310 = (r ** (3.0 / 2.0))\\n term320 = (3.0 * c1 * c1 * Ct * Area * (x + x0)) ** (-0.5)\\n term30 = term310 * term320\\n term40 = ((35.0 / (2.0 * np.pi)) ** (3.0 / 10.0)) * \\\\\\n (3.0 * c1 * c1) ** (-1.0 / 5.0)\\n DU1 = -term10 * term20 * (term30 - term40) ** 2.0\\n\\n DU = DU1 # + w2 * DU2\\n Rw = ((105 * c1 ** 2.0 / (2 * np.pi)) ** (1. / 5.)) * \\\\\\n (Ct * Area * (x + x0)) ** (1. / 3.)\\n return DU, Rw\",\n \"def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\\n if q_args is None and c_args is None:\\n raise GateError(\\\"Gate needs at least one quantum argument or classical argument\\\")\\n if isinstance(gate, CompositeGate):\\n if mapping is None:\\n raise GateError(\\\"Must provide arguments mapping for composite gate inside a composite gate.\\\")\\n else:\\n inv_mappimg = dict()\\n for key, value in mapping.items():\\n inv_mappimg[value] = key\\n if gate is self:\\n gates = gate.copy.gates\\n else:\\n gates = gate.gates\\n for g in gates:\\n new_q_args = None\\n new_c_args = None\\n if g[1] is not None:\\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\\n if g[2] is not None:\\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\\n self.add_gate(gate=g[0], q_args=new_q_args,\\n c_args=new_c_args, params=g[3])\\n else:\\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\\n raise GateError(\\\"Gate must be either a CompositeGate or a string from: \\\"\\n \\\"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\\\")\\n if q_args is not None:\\n for q_arg in q_args:\\n if q_arg not in self.q_args:\\n self.add_q_arg(q_arg)\\n if c_args is not None:\\n for c_arg in c_args:\\n if c_arg not in self.c_args:\\n self.add_c_arg(c_arg)\\n if params is not None:\\n for param in params:\\n if param not in self.params:\\n self.add_param(param)\\n self._gates.append((gate, q_args, c_args, params))\",\n \"def add_gates(self, num_gates_to_add):\\n pass\",\n \"def addFCSPoint(self, dxpos, dypos, dzpos=None):\\n prefix = \\\"/cli:python /app:fcs /cmd:add\\\"\\n dx = \\\"/xpos:\\\" + `int(dxpos)` \\n dy = \\\"/ypos:\\\" + `int(dypos)`\\n if dzpos is None:\\n dz = \\\"/zpos:0\\\"\\n else:\\n dz = \\\"/zpos:\\\"+dzpos\\n \\n \\n cmd = \\\" \\\".join((prefix,dx,dy,dz))\\n #print \\\"FCS command string\\\"\\n #print cmd\\n self.sendCMDstring(cmd)\",\n \"def cxr_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def circuitSat(C):\",\n \"def CL(self):\",\n \"def addCDSphase(strand, cds):\\n cds_region, cds_flag = [], 0\\n if strand == '+':\\n for cdspos in cds:\\n if cds_flag == 0:\\n cdspos = (cdspos[0], cdspos[1], 0)\\n diff = (cdspos[1]-(cdspos[0]-1))%3\\n else:\\n xy = 0\\n if diff == 0:\\n cdspos = (cdspos[0], cdspos[1], 0)\\n elif diff == 1:\\n cdspos = (cdspos[0], cdspos[1], 2)\\n xy = 2\\n elif diff == 2:\\n cdspos = (cdspos[0], cdspos[1], 1)\\n xy = 1\\n diff = ((cdspos[1]-(cdspos[0]-1))-xy)%3\\n cds_region.append(cdspos)\\n cds_flag = 1\\n elif strand == '-':\\n cds.reverse()\\n for cdspos in cds:\\n if cds_flag == 0:\\n cdspos = (cdspos[0], cdspos[1], 0)\\n diff = (cdspos[1]-(cdspos[0]-1))%3\\n else:\\n xy = 0\\n if diff == 0:\\n cdspos = (cdspos[0], cdspos[1], 0)\\n elif diff == 1:\\n cdspos = (cdspos[0], cdspos[1], 2)\\n xy = 2\\n elif diff == 2:\\n cdspos = (cdspos[0], cdspos[1], 1)\\n xy = 1\\n diff = ((cdspos[1]-(cdspos[0]-1))-xy)%3\\n cds_region.append(cdspos)\\n cds_flag = 1\\n cds_region.reverse()\\n return cds_region\",\n \"def _build_add(self) -> str:\\n return dedent(\\n \\\"\\\"\\\"\\n @SP\\n M=M-1\\n A=M\\n D=M\\n @SP\\n M=M-1\\n A=M\\n M=M+D\\n @SP\\n M=M+1\\n \\\"\\\"\\\"\\n )\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def insert(n, c, dnodecomm):\\n\\n _tot[c] += k[n]\\n _in[c] += 2 * dnodecomm + network[n][n]\\n bl[n] = c\",\n \"def coadd(self, step_index):\\n if self.drip_config is not None:\\n if ('boresight' in self.drip_cal_config\\n and 'SLIT' in self.drip_cal_config['boresight']):\\n self.current[step_index].set_value('skip_coadd', True)\",\n \"def add_condiments(self):\\n print(\\\"Adding Lemon\\\")\",\n \"def add_graph(self):\\n \\n self.cd_sampling = None\\n \\n if \\\"CD\\\" in self.algorithm:\\n\\n self.add_cd_samples()\\n \\n if self.num_hidden ==0:\\n \\n self.cd_sampling = self.get_cd_samples()\\n \\n if \\\"CSS\\\" in self.algorithm and self.mf_steps > 0: \\n \\n self.add_mf_updates()\\n \\n elif \\\"CSS\\\" in self.algorithm and self.gibbs_steps > 0:\\n \\n self.add_cd_samples()\\n \\n if self.num_hidden ==0:\\n \\n self.cd_sampling = self.get_cd_samples() \\n \\n self.add_objective()\\n\\n self.add_grad_updates() \\n \\n if self.report_p_tilda:\\n \\n self.add_p_tilda()\\n \\n self.add_pseudo_cost_measure()\\n\\n self.optimize = self.optimization_step()\",\n \"def cmd_dgaus():\\n cmds = []\\n cmds.append(\\\"r_m[0.0,-1,1]\\\")\\n cmds.append(\\\"r_s[1.5,0,10]\\\")\\n cmds.append('Gaussian::gaus_c(x,r_m,r_s)')\\n cmds.append(\\\"rt_m[0.0,-1,1]\\\")\\n cmds.append(\\\"rt_s[3,0,10]\\\")\\n cmds.append('Gaussian::gaus_t(x,rt_m,rt_s)')\\n cmds.append(\\\"f[0.85]\\\") # fraction of core\\n cmds.append(\\\"SUM::res(f*gaus_c,gaus_t)\\\")\\n return cmds\",\n \"def sdg(self, q):\\n if isinstance(q, QuantumRegister):\\n instructions = InstructionSet()\\n for j in range(q.size):\\n instructions.add(self.sdg((q, j)))\\n return instructions\\n\\n self._check_qubit(q)\\n return self._attach(SdgGate(q, self))\",\n \"def train_dagger(): # add arguments as needed\\n pass\",\n \"def append_user_gate(self, user_gate):\\n self.translation['g_sect'].append(user_gate)\",\n \"def system(Vg, Cs, Cd, Cg, Gs, Gd, num_e):\\n myset = set.SET()\\n # choose between the two lines below for metallic dot or quantum levels\\n myset.add_metallic_dot('dot', num_e, -num_e, 0)\\n #myset.add_quantum_dot('dot', [0, 1, 2, 3], [1, 1, 1, 1])\\n myset.add_lead('source')\\n myset.add_lead('drain')\\n myset.add_gate('gate')\\n #myset.add_link('dl', 'dot', 'source', 5.5e-18, 0.2)\\n #myset.add_link('dl', 'dot', 'drain', 5.5e-18, 0.2)\\n myset.add_link('dl', 'dot', 'drain', Cd,Gd)\\n myset.add_link('dl', 'dot', 'source', Cs, Gs)\\n #myset.add_link('dl', 'dot', 'drain', 1e-19, 10e-8)\\n #myset.add_link('dl', 'dot', 'drain', Cg, Gg)\\n myset.add_link('dg', 'dot', 'gate', Cg)\\n return myset\",\n \"def add_comp(mol, projects):\\n\\n # Now attribute all this meta-deta to the compound object\\n new_comp = Compound()\\n comp = calc_cpd(new_comp, mol, projects)\\n return comp\",\n \"def csNew(self, an):\\n\\t\\treturn ca - an/self.GA\",\n \"def derive(self, code_of_source: str) -> str:\\n min_to_change = self.mr_config['min_to_change']\\n max_to_change = self.mr_config['max_to_change']\\n n_gate_to_change = random.randint(min_to_change, max_to_change)\\n max_to_change = min(n_gate_to_change, self.tot_n_x_gates)\\n\\n sections = metamorph.get_sections(code_of_source)\\n source_code_circuit = sections[\\\"CIRCUIT\\\"]\\n\\n x_gates_to_replace = random.sample(\\n self.instruction_x_gate, max_to_change)\\n\\n mr_metadata = {}\\n mr_metadata[\\\"x_gates_to_replace\\\"] = str(x_gates_to_replace)\\n\\n changed_section = source_code_circuit\\n lines = source_code_circuit.split(\\\"\\\\n\\\")\\n\\n x_gates_to_replace_reverse_order = sorted(\\n x_gates_to_replace, key=lambda x: x[\\\"lineno\\\"], reverse=True)\\n # we start replacing gates, from the last one because each\\n # substitution of an X gate makes the code longer.\\n for x_gate in x_gates_to_replace_reverse_order:\\n # remove gate\\n edit_location = x_gate[\\\"lineno\\\"] - 1\\n removed_original = lines.pop(edit_location)\\n\\n h_gate_last = removed_original.replace(\\\"XGate\\\", \\\"HGate\\\")\\n lines.insert(edit_location, h_gate_last)\\n s_gate_last = removed_original.replace(\\\"XGate\\\", \\\"SGate\\\")\\n lines.insert(edit_location, s_gate_last)\\n s_gate_first = removed_original.replace(\\\"XGate\\\", \\\"SGate\\\")\\n lines.insert(edit_location, s_gate_first)\\n h_gate_first = removed_original.replace(\\\"XGate\\\", \\\"HGate\\\")\\n lines.insert(edit_location, h_gate_first)\\n\\n changed_section = \\\"\\\\n\\\".join(lines)\\n\\n sections[\\\"CIRCUIT\\\"] = changed_section\\n\\n self.metadata = mr_metadata\\n\\n return metamorph.reconstruct_sections(sections)\",\n \"def enable_cl1_direct(self):\\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\\n self.write_versa5(0x18,0x20)\\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\\n self.write_versa5(0x13,0x03) ## Switch to clock\\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew\",\n \"def add_cogs(self):\\n self.add_cog(Voice(self))\",\n \"def computeCLgainRemoveNodeD(self, G, PD, nodes, node, dropLidx, dir):\\n CL_I = 0.0\\n CL_F = 0.0\\n if dir==2:\\n for i in nodes:\\n pos_I = PD.getPOS(node, i, case=2, isSimple=self.isSimple)\\n pos_F = PD.getPOS(node, i, case=4, isSimple=self.isSimple, dropLidx=dropLidx)\\n if pos_I < 0.0000000001:\\n pos_I = 0.0000000001\\n elif pos_I > 1.0 - 0.0000000001:\\n pos_I = 1.0 - 0.0000000001\\n if pos_F < 0.0000000001:\\n pos_F = 0.0000000001\\n elif pos_F > 1.0 - 0.0000000001:\\n pos_F = 1.0 - 0.0000000001\\n numE = G.number_of_edges(node, i)\\n if self.isSimple:\\n CL_I += math.log2(math.pow(1.0-pos_I, 1.0-numE)*math.pow(pos_I, numE))\\n CL_F += math.log2(math.pow(1.0-pos_F, 1.0-numE)*math.pow(pos_F, numE))\\n else:\\n CL_I += math.log2(math.pow(1.0-pos_I, numE)*pos_I)\\n CL_F += math.log2(math.pow(1.0-pos_F, numE)*pos_F)\\n elif dir==1:\\n for i in nodes:\\n pos_I = PD.getPOS(i, node, case=2, isSimple=self.isSimple)\\n pos_F = PD.getPOS(i, node, case=4, isSimple=self.isSimple, dropLidx=dropLidx)\\n if pos_I < 0.0000000001:\\n pos_I = 0.0000000001\\n elif pos_I > 1.0 - 0.0000000001:\\n pos_I = 1.0 - 0.0000000001\\n if pos_F < 0.0000000001:\\n pos_F = 0.0000000001\\n elif pos_F > 1.0 - 0.0000000001:\\n pos_F = 1.0 - 0.0000000001\\n numE = G.number_of_edges(i, node)\\n if self.isSimple:\\n CL_I += math.log2(math.pow(1.0-pos_I, 1.0-numE)*math.pow(pos_I, numE))\\n CL_F += math.log2(math.pow(1.0-pos_F, 1.0-numE)*math.pow(pos_F, numE))\\n else:\\n CL_I += math.log2( math.pow( 1.0-pos_I, numE )*pos_I )\\n CL_F += math.log2( math.pow( 1.0-pos_F, numE )*pos_F )\\n return -CL_I - (-CL_F)\",\n \"def add_switch(self, dpid):\\n\\t\\tself.switches.append(dpid)\",\n \"def gate_logic(self, pull: str):\\r\\n self._gate_logic = pull\\r\\n self.gate_logic_hist.append(pull)\\r\\n\\r\\n if self.gate_logic_hist[-2] != pull and self._daq:\\r\\n msg = Message(\\\"gate_logic\\\", pull, self.checksum).message_bytes\\r\\n self._daq.asynch.transmit(msg)\",\n \"def dagger(self) -> Cup:\\n return self.cup_factory(self.left, self.right)\",\n \"def added(self, comp):\\n\\t\\tpass\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def counterions(self):\\n\\n\\t\\tprint \\\"adding counterions\\\"\\n\\t\\tcopy(self.rootdir+'solvate.top',self.rootdir+'counterions.top')\\n\\t\\tcmd = [gmxpaths['grompp'],\\n\\t\\t\\t'-f input-em-steep-in.mdp',\\n\\t\\t\\t'-po genion.mdp',\\n\\t\\t\\t'-c solvate-minimized.gro',\\n\\t\\t\\t'-p counterions.top',\\n\\t\\t\\t'-o genion.tpr']\\n\\t\\tcall(cmd,logfile='log-grompp-genion',cwd=self.rootdir)\\n\\t\\tcmd = [gmxpaths['make_ndx'],\\n\\t\\t\\t'-f solvate-minimized.gro',\\n\\t\\t\\t'-o solvate-waters.ndx']\\n\\t\\tcall(cmd,logfile='log-make-ndx-counterions-check',cwd=self.rootdir,\\n\\t\\t\\tinpipe='keep 0\\\\nr '+self.settings['sol_name']+'\\\\nkeep 1\\\\nq\\\\n')\\n\\t\\tcmd = [gmxpaths['genion'],\\n\\t\\t\\t'-s genion.tpr',\\n\\t\\t\\t'-o counterions.gro',\\n\\t\\t\\t'-conc '+str(self.settings['ion_strength']),\\n\\t\\t\\t'-n solvate-waters.ndx',\\n\\t\\t\\t'-neutral']\\n\\t\\tcall(cmd,logfile='log-genion',cwd=self.rootdir)\\n\\t\\n\\t\\tprint \\\"updating topology with counterions\\\"\\n\\t\\tself.npoz,self.nneg = [int(checkout([\\\"awk\\\",\\\"'/Will try to add / {print $\\\"+str(col)+\\\\\\n\\t\\t\\t\\\"}'\\\",\\\"log-genion\\\"],cwd=self.rootdir)) for col in [5,9]]\\n\\t\\tself.nsol = self.nsol - self.npoz - self.nneg\\n\\t\\tself.write_topology_protein('counterions.top')\\n\\t\\t\\n\\t\\tprint \\\"minimizing with solvent\\\"\\n\\t\\tself.minimization_method('counterions')\\n\\t\\t\\n\\t\\tprint \\\"writing structure with correct residue numbers to structure.pdb\\\"\\n\\t\\twith open(self.rootdir+'system-input.pdb','r') as fp: lines = fp.readlines()\\n\\t\\tstartres = int([line for line in lines if re.match('^ATOM',line)][0][22:25+1])\\t\\t\\n\\t\\tprint \\\"according to the input_filename, the starting residue is %d\\\"%startres\\n\\t\\tprint \\\"[WARNING] use struture.pdb for post-processing for the right residue numbers\\\"\\n\\t\\tcmd = [gmxpaths['editconf'],\\n\\t\\t\\t'-f counterions.gro',\\n\\t\\t\\t'-o structure.pdb',\\n\\t\\t\\t'-resnr %d'%startres]\\n\\t\\tcall(cmd,logfile='log-editconf-structure-pdb',cwd=self.rootdir)\",\n \"def add_computed_gas_concentrations(self):\\n # Extract the z-coordinate and T, S, P profile\\n zs = self.interp_ds.coords[self.ztsp[0]].values\\n Ts = self.interp_ds[self.ztsp[1]].values\\n Ss = self.interp_ds[self.ztsp[2]].values\\n Ps = self.interp_ds[self.ztsp[3]].values\\n \\n # Create an air object\\n air_names = ['nitrogen', 'oxygen', 'argon', 'carbon_dioxide']\\n yk = np.array([0.78084, 0.20946, 0.009340, 0.00036])\\n from tamoc import dbm\\n air = dbm.FluidMixture(air_names)\\n m = air.masses(yk)\\n \\n # Compute the concentrations adjusted for depth\\n Cs = np.zeros((len(zs), len(air_names)))\\n for i in range(len(zs)):\\n Cs[i,:] = air.solubility(m, Ts[i], 101325., Ss[i])[0,:] * \\\\\\n seawater.density(Ts[i], Ss[i], Ps[i]) / \\\\\\n seawater.density(Ts[i], Ss[i], 101325.)\\n \\n # Make sure none of these gases are already in the measured profile\\n for name in air_names:\\n if name in self.interp_ds:\\n air_names[air_names.index(name)] = 'computed_' + name\\n \\n # Add these data to the Profile object\\n data = np.hstack((np.atleast_2d(zs).transpose(), Cs))\\n names = [self.ztsp[0]] + air_names \\n units = [self.ztsp_units[0]] + 4*['kg/m^3']\\n self.append(data, names, units)\\n \\n # Rebuild the interpolator\\n self._build_interpolator()\",\n \"def add_layer(self, freeze = True, add = True):\\n if add:\\n self.num_layers += 1\\n if self.conv_dim == 1:\\n new_cnn = layers.Conv1D(self.n_filters,\\n (self.n_kernels),\\n activation='elu',\\n input_shape=(None, self.inp_shape[0], self.n_filters),\\n padding=\\\"same\\\",\\n name='cnn_1d_{}'.format(self.num_layers-1),\\n kernel_initializer = initializers.get(self.initializer),\\n bias_initializer=initializers.get(\\\"zeros\\\"),\\n kernel_regularizer=self.regularizer,\\n bias_regularizer=self.regularizer\\n )\\n elif self.conv_dim == 2:\\n new_cnn = layers.Conv2D(self.n_filters,\\n (self.n_kernels, self.n_kernels),\\n activation='elu',\\n input_shape=(None, self.inp_shape[0],self.inp_shape[1], self.n_filters),\\n padding=\\\"same\\\",\\n name='cnn_2d_{}'.format(self.num_layers-1),\\n kernel_initializer=initializers.get(self.initializer),\\n bias_initializer=initializers.get(\\\"zeros\\\"),\\n kernel_regularizer=self.regularizer,\\n bias_regularizer=self.regularizer\\n )\\n self.list_cnn.append(new_cnn)\\n\\n if freeze:\\n for index in range(0,self.num_layers-1):\\n self.list_cnn[index].trainable = False\\n else:\\n for index in range(0,self.num_layers-1):\\n self.list_cnn[index].trainable = True\",\n \"def recursive_gate(e):\\n if isinstance(e, boolean.BaseElement):\\n # TODO: Either make the the same or create a constant component.\\n s = Switch()\\n b.append(s)\\n return s\\n elif isinstance(e, boolean.Symbol):\\n if e in symbol_dict.keys():\\n return symbol_dict[e]\\n else:\\n s = Switch()\\n symbol_dict[e] = s\\n b.append(s)\\n return s\\n elif isinstance(e, boolean.Function):\\n # All gates are of type Gate instead of And, Or and Not\\n if e.order == (1, 1):\\n pre = recursive_gate(e.args[0])\\n w = Wire(pre)\\n b.append(w)\\n\\n s = boolean.Symbol(None)\\n g = Gate(e.subs({e.args[0]: s}),\\n {s: w})\\n b.append(g)\\n return g\\n else:\\n input_dict = {}\\n expr = e\\n for arg in e.args:\\n pre = recursive_gate(arg)\\n w = Wire(pre)\\n b.append(w)\\n\\n s = boolean.Symbol(None)\\n expr = expr.subs({arg: s})\\n input_dict[s] = w\\n g = Gate(expr,\\n input_dict)\\n b.append(g)\\n return g\",\n \"def alg(c):\\n return c[0]*G[0] + c[1]*G[1] + c[2]*G[2]\",\n \"def add_dcdisorder(self):\\n # Add gaussian noise to pinning energies\\n if self.lp['V0_pin_gauss'] > 0:\\n self.Omg += self.lp['V0_pin_gauss']*np.random.randn(len(self.xy_inner))\\n raise RuntimeError('Adding gaussian disorder: are you sure you want to proceed?')\\n if self.lp['V0_spring_gauss'] > 0:\\n print 'This is not done correctly here'\\n self.OmK += self.lp['V0_spring_gauss'] * np.random.randn(np.shape(self.lattice.KL)[0],\\n np.shape(self.lattice.KL)[1])\\n sys.exit()\\n\\n if self.lp['V0_pin_flat'] > 0 or self.lp['V0_spring_flat'] > 0:\\n # Note that we multiply by two so that V0_pin_flat is the HALF width of the distribution\\n flat_disorder = (np.random.rand(len(self.xy_inner))) * 2 - 1.0\\n\\n if self.lp['V0_pin_flat'] > 0:\\n self.Omg += self.lp['V0_pin_flat'] * flat_disorder\\n if self.lp['Omg'] < 0:\\n self.Omg[self.Omg > 0] = 0.\\n elif self.lp['Omg'] > 0:\\n self.Omg[self.Omg < 0] = 0.\\n\\n print('magnetic_gyro_lattice_class.py: V0_pin_flat=', self.lp['V0_pin_flat'])\\n print(self.Omg)\\n\\n if self.lp['V0_spring_flat'] > 0:\\n to_add = self.lp['V0_spring_flat'] * flat_disorder[:, np.newaxis] * np.ones_like(self.OmK)\\n self.OmK[np.abs(self.OmK) > 0] += to_add[np.abs(self.OmK) > 0]\\n if self.lp['Omk'] < 0:\\n self.OmK[self.OmK > 0] = 0.\\n elif self.lp['Omk'] > 0:\\n self.OmK[self.OmK < 0] = 0.\\n\\n print('magnetic_gyro_lattice_class.py: OmK after flat disorder= ')\\n print(self.OmK)\\n # sys.exit()\",\n \"def test_guider_start_arcsOn(self):\\n sopTester.updateModel('mcp', TestHelper.mcpState['arcs'])\\n self._guider_start(8, 20, 0, 0)\",\n \"def G(self, dstrct):\\n # Instead of hardcoding the method, it could be supplied as a KWarg\\n\\n if self.compactness_method == 'CSPC':\\n self.G_ = self.CSPC_score(dstrct)\\n\\n elif self.compactness_method == 'circular':\\n self.G_ = self.circular_score(dstrct)\\n\\n elif self.compactness_method == 'convexity':\\n self.G_ = self.convexity_score(dstrct)\\n\\n elif self.compactness_method == 'average':\\n self.G_ = np.mean([self.w_R*self.circular_score(dstrct),\\n self.w_C*self.convexity_score(dstrct)])\\n elif self.compactness_method == 'sum':\\n self.G_ = self.w_R*self.circular_score(dstrct) + \\\\\\n self.w_C*self.convexity_score(dstrct)\\n else:\\n msg = (\\\"Valid compactness methods are \\\"\\n \\\"'CSPC', 'circular', 'convexity', 'average', and 'sum'\\\")\\n raise Exception(msg)\\n\\n # While all neighbors are unassigned, we want to weight compactness\\n multiplier = 2 - any([pt.assigned for pt in dstrct.neighbors])\\n # self.G_ *= self.w_G * (2-self.assigned)\\n self.G_ *= self.w_G * multiplier\\n return self.G_\",\n \"def GED_n(Gn, lib='gedlibpy', cost='CHEM_1', method='IPFP',\\n edit_cost_constant=[], stabilizer='min', repeat=50):\\n if lib == 'gedlibpy':\\n def convertGraph(G):\\n \\\"\\\"\\\"Convert a graph to the proper NetworkX format that can be\\n recognized by library gedlibpy.\\n \\\"\\\"\\\"\\n G_new = nx.Graph()\\n for nd, attrs in G.nodes(data=True):\\n G_new.add_node(str(nd), chem=attrs['atom_symbol'])\\n for nd1, nd2, attrs in G.edges(data=True):\\n # G_new.add_edge(str(nd1), str(nd2), valence=attrs['bond_type'])\\n G_new.add_edge(str(nd1), str(nd2))\\n\\n return G_new\\n\\n # gedlibpy.restart_env()\\n gedlibpy.add_nx_graph(convertGraph(g1), \\\"\\\")\\n gedlibpy.add_nx_graph(convertGraph(g2), \\\"\\\")\\n\\n listID = gedlibpy.get_all_graph_ids()\\n gedlibpy.set_edit_cost(cost, edit_cost_constant=edit_cost_constant)\\n gedlibpy.init()\\n gedlibpy.set_method(method, \\\"\\\")\\n gedlibpy.init_method()\\n\\n g = listID[0]\\n h = listID[1]\\n if stabilizer == None:\\n gedlibpy.run_method(g, h)\\n pi_forward = gedlibpy.get_forward_map(g, h)\\n pi_backward = gedlibpy.get_backward_map(g, h)\\n upper = gedlibpy.get_upper_bound(g, h)\\n lower = gedlibpy.get_lower_bound(g, h)\\n elif stabilizer == 'min':\\n upper = np.inf\\n for itr in range(repeat):\\n gedlibpy.run_method(g, h)\\n upper_tmp = gedlibpy.get_upper_bound(g, h)\\n if upper_tmp < upper:\\n upper = upper_tmp\\n pi_forward = gedlibpy.get_forward_map(g, h)\\n pi_backward = gedlibpy.get_backward_map(g, h)\\n lower = gedlibpy.get_lower_bound(g, h)\\n if upper == 0:\\n break\\n\\n dis = upper\\n\\n # make the map label correct (label remove map as np.inf)\\n nodes1 = [n for n in g1.nodes()]\\n nodes2 = [n for n in g2.nodes()]\\n nb1 = nx.number_of_nodes(g1)\\n nb2 = nx.number_of_nodes(g2)\\n pi_forward = [nodes2[pi] if pi < nb2 else np.inf for pi in pi_forward]\\n pi_backward = [nodes1[pi] if pi <\\n nb1 else np.inf for pi in pi_backward]\\n\\n return dis, pi_forward, pi_backward\",\n \"def _add_pairblend(self, dgmod, rigid, transform):\\n\\n assert isinstance(dgmod, cmdx.DGModifier)\\n\\n pair_blend = dgmod.create_node(\\\"pairBlend\\\")\\n dgmod.set_attr(pair_blend[\\\"isHistoricallyInteresting\\\"], False)\\n\\n # Establish initial values, before keyframes\\n # tm = cmdx.Tm(self._cache[(transform, \\\"matrix\\\")])\\n\\n # Read from matrix, as opposed to the rotate/translate channels\\n # to account for jointOrient, pivots and all manner of things\\n # translate = tm.translation()\\n # rotate = tm.rotation()\\n\\n translate = self._cache[(transform, \\\"translate\\\")]\\n rotate = self._cache[(transform, \\\"rotate\\\")]\\n\\n dgmod.set_attr(pair_blend[\\\"inTranslate1\\\"], translate)\\n dgmod.set_attr(pair_blend[\\\"inRotate1\\\"], rotate)\\n\\n dgmod.connect(rigid[\\\"outputTranslateX\\\"], pair_blend[\\\"inTranslateX2\\\"])\\n dgmod.connect(rigid[\\\"outputTranslateY\\\"], pair_blend[\\\"inTranslateY2\\\"])\\n dgmod.connect(rigid[\\\"outputTranslateZ\\\"], pair_blend[\\\"inTranslateZ2\\\"])\\n dgmod.connect(rigid[\\\"outputRotateX\\\"], pair_blend[\\\"inRotateX2\\\"])\\n dgmod.connect(rigid[\\\"outputRotateY\\\"], pair_blend[\\\"inRotateY2\\\"])\\n dgmod.connect(rigid[\\\"outputRotateZ\\\"], pair_blend[\\\"inRotateZ2\\\"])\\n\\n # Let the animator see the raw animation values, no physics\\n dgmod.connect(self._tree_root[0][\\\"simulated\\\"], pair_blend[\\\"weight\\\"])\\n\\n if self._opts[\\\"autoKey\\\"]:\\n # Generate default animation curves, it's expected since you can no\\n # longer see whether channels are keyed or not, now being green.\\n time = cmdx.currentTime()\\n mapping = (\\n (\\\"animCurveTL\\\", translate.x, \\\"inTranslateX1\\\"),\\n (\\\"animCurveTL\\\", translate.y, \\\"inTranslateY1\\\"),\\n (\\\"animCurveTL\\\", translate.z, \\\"inTranslateZ1\\\"),\\n (\\\"animCurveTA\\\", rotate.x, \\\"inRotateX1\\\"),\\n (\\\"animCurveTA\\\", rotate.y, \\\"inRotateY1\\\"),\\n (\\\"animCurveTA\\\", rotate.z, \\\"inRotateZ1\\\")\\n )\\n\\n for curve, value, dst in mapping:\\n curve = dgmod.create_node(curve)\\n curve.key(time, value)\\n dgmod.connect(curve[\\\"output\\\"], pair_blend[dst])\\n\\n # Transfer existing animation/connections\\n for src, dst in transform.data.get(\\\"priorConnections\\\", {}).items():\\n dst = pair_blend[dst]\\n dgmod.connect(src, dst)\\n\\n commands._connect_transform(dgmod, pair_blend, transform)\\n\\n return pair_blend\",\n \"def _auto_blend(self, dgmod):\\n\\n assert isinstance(dgmod, cmdx.DGModifier)\\n\\n root, _ = self._root\\n root_rigid = root.shape(type=\\\"rdRigid\\\")\\n\\n for rigid in self._new_rigids:\\n\\n # Don't bother with the root\\n if rigid == root_rigid:\\n continue\\n\\n transform = rigid.parent()\\n blend = self._add_pairblend(dgmod, rigid, transform)\\n self._auto_influence(dgmod, rigid, blend)\",\n \"def add_state(self, state):\\n if self.rate_variation:\\n if not self.feature_rates:\\n # Set all rates to 1.0 in a big plate\\n plate = ET.SubElement(state, \\\"plate\\\", {\\n \\\"var\\\":\\\"feature\\\",\\n \\\"range\\\":\\\",\\\".join(self.features)})\\n param = ET.SubElement(plate, \\\"parameter\\\", {\\n \\\"id\\\":\\\"featureClockRate:%s:$(feature)\\\" % self.name,\\n \\\"name\\\":\\\"stateNode\\\"})\\n param.text=\\\"1.0\\\"\\n else:\\n # Give each rate a custom value\\n for f in self.features:\\n param = ET.SubElement(state, \\\"parameter\\\", {\\n \\\"id\\\":\\\"featureClockRate:%s:%s\\\" % (self.name, f),\\n \\\"name\\\":\\\"stateNode\\\"})\\n param.text=str(self.feature_rates.get(f,1.0))\\n\\n # Give Gamma shape parameter a finite domain\\n # Must be > 1.0 for the distribution to be bell-shaped,\\n # rather than L-shaped. The domain [1.1,1000] limits feature\\n # rate variation to the realms of vague plausibity\\n parameter = ET.SubElement(state, \\\"parameter\\\", {\\\"id\\\":\\\"featureClockRateGammaShape:%s\\\" % self.name, \\\"lower\\\":\\\"1.1\\\",\\\"upper\\\":\\\"100.0\\\",\\\"name\\\":\\\"stateNode\\\"})\\n parameter.text=\\\"5.0\\\"\\n # Gamma scale parameter's domain is defined *implicilty*\\n # by the fact that the operators maintain shape*scale = 1.0\\n parameter = ET.SubElement(state, \\\"parameter\\\", {\\\"id\\\":\\\"featureClockRateGammaScale:%s\\\" % self.name, \\\"name\\\":\\\"stateNode\\\"})\\n parameter.text=\\\"0.2\\\"\",\n \"def get_gate(gate, params, num_ctrl_qubits=None):\\n if gate[0] == \\\"c\\\":\\n return get_gate(gate[1:], params, num_ctrl_qubits).ctrl()\\n if gate == \\\"toffoli\\\":\\n return get_gate(\\\"ccx\\\", params, num_ctrl_qubits)\\n if gate[0:2] == \\\"mc\\\":\\n name = gate[2:]\\n for _ in range(num_ctrl_qubits):\\n name = \\\"c\\\" + name\\n return get_gate(name, params, num_ctrl_qubits)\\n if len(params) == 0:\\n return GATE_DIC[gate]\\n\\n return GATE_DIC[gate](*params)\",\n \"def makeDstar2D0Pi( name\\n , config\\n , DecayDescriptor\\n , inputSel\\n ) :\\n\\n daugCuts = \\\"(TRCHI2DOF < %(Daug_TRCHI2DOF_MAX)s)\\\" % locals()['config']\\n combCuts = \\\"((AM - AM1) < %(Dstar_AMDiff_MAX)s* MeV)\\\" % locals()['config']\\n dstarCuts = \\\"(VFASPF(VCHI2/VDOF) < %(Dstar_VCHI2VDOF_MAX)s)\\\" \\\\\\n \\\"& ((M - M1) < %(Dstar_MDiff_MAX)s* MeV)\\\" % locals()['config']\\n\\n _Dstar = CombineParticles( DecayDescriptor = DecayDescriptor\\n , DaughtersCuts = { \\\"pi+\\\" : daugCuts }\\n , CombinationCut = combCuts\\n , MotherCut = dstarCuts\\n )\\n\\n return Selection( name+'Sel',\\n Algorithm = _Dstar,\\n RequiredSelections = inputSel\\n )\",\n \"def condensation(G):\\n scc = strongly_connected_components(G)\\n mapping = dict([(n,tuple(sorted(c))) for c in scc for n in c])\\n cG = nx.DiGraph()\\n for u in mapping:\\n cG.add_node(mapping[u])\\n for _,v,d in G.edges_iter(u, data=True):\\n if v not in mapping[u]:\\n cG.add_edge(mapping[u], mapping[v])\\n return cG\",\n \"def compile(self):\\n m, n = self.input_shape[1], self.input_shape[2]\\n\\n inp = Input(shape=self.input_shape, traces=True)\\n self.add_layer(inp, \\\"DoG\\\")\\n\\n s1 = LIFNodes(shape=(18, m, n), traces=True)\\n self.add_layer(s1, \\\"conv_1\\\")\\n c1 = LIFNodes(shape=(18, m // 2, n // 2), traces=True)\\n self.add_layer(c1, \\\"pool_1\\\")\\n\\n s2 = LIFNodes(shape=(24, m // 2, n // 2), traces=True)\\n self.add_layer(s2, \\\"conv_2\\\")\\n c2 = LIFNodes(shape=(24, m // 4, n // 4), traces=True)\\n self.add_layer(c2, \\\"pool_2\\\")\\n\\n s3 = LIFNodes(shape=(32, m // 4, n // 4), traces=True)\\n self.add_layer(s3, \\\"conv_3\\\")\\n f = LIFNodes(shape=(32, 1), traces=True)\\n self.add_layer(f, \\\"global_pool\\\")\\n\\n conv1 = Conv2dConnection(inp, s1, 5, padding=2, weight_decay=0.01,\\n nu=0.01, update_rule=PostPre, decay=0.5)\\n self.add_connection(conv1, \\\"DoG\\\", \\\"conv_1\\\")\\n pool1 = MaxPool2dConnection(s1, c1, 2, 2, decay=0.5)\\n self.add_connection(pool1, \\\"conv_1\\\", \\\"pool_1\\\")\\n\\n conv2 = Conv2dConnection(c1, s2, 3, padding=1, weight_decay=0.01,\\n nu=0.01, update_rule=PostPre, decay=0.5)\\n self.add_connection(conv2, \\\"pool_1\\\", \\\"conv_2\\\")\\n pool2 = MaxPool2dConnection(s2, c2, 2, 2, decay=0.5)\\n self.add_connection(pool2, \\\"conv_2\\\", \\\"pool_2\\\")\\n\\n conv3 = Conv2dConnection(c2, s3, 3, padding=1, weight_decay=0.01,\\n nu=0.01, update_rule=PostPre, decay=0.5)\\n self.add_connection(conv3, \\\"pool_2\\\", \\\"conv_3\\\")\\n global_pool = MaxPool2dConnection(s3, f, (m // 4, n // 4), decay=0.5)\\n self.add_connection(global_pool, \\\"conv_3\\\", \\\"global_pool\\\")\\n\\n monitor = NetworkMonitor(self, layers=[\\\"DoG\\\", \\\"conv_1\\\", \\\"pool_1\\\",\\n \\\"conv_2\\\", \\\"pool_2\\\",\\n \\\"conv_3\\\", \\\"global_pool\\\"],\\n connections=[(\\\"DoG\\\", \\\"conv_1\\\"),\\n (\\\"pool_1\\\", \\\"conv_2\\\"),\\n (\\\"pool_2\\\", \\\"conv_3\\\")],\\n state_vars=[\\\"w\\\", \\\"s\\\"])\\n self.add_monitor(monitor, \\\"network_monitor\\\")\\n\\n return self\",\n \"def add(num1, num2, Cin):\\n Cin=0\\n l2=[]\\n final=\\\"\\\"\\n\\n \\\"\\\"\\\"Using for loop for starting addition from the last indexed number\\\"\\\"\\\"\\n for i in range(len(num1)-1,-1,-1):\\n bit1=num1[i]#storing each indexed() value of num1 in bit1\\n bit2=num2[i]#storing each indexed() value of num2 in bit2\\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\\n Cin=Cout#declaring cout as cin for next bit addition\\n l2.append(SUM)#adding SUM to l2\\n l3=l2[::-1]##reversing the value of l2\\n final+=str(l2[-1])#converting the list value to string\\n final1=final[::-1]#reversing string value\\n return final1 #returning the binary addition as string\",\n \"def bcs(self, arg):\\n\\n self.pc += arg if self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def manage_addCASSSO(self, id='sso', REQUEST=None):\\n\\n id = 'sso'\\n ob = CASSSO()\\n ob.id = id\\n self._setObject(id, ob)\\n if REQUEST is not None:\\n return self.manage_main(self, REQUEST)\",\n \"def test_sdg_gate_nondeterministic_minimal_basis_gates(self):\\n shots = 2000\\n circuits = ref_1q_clifford.sdg_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_1q_clifford.sdg_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def GAStep(self):\\n\\n self.updateMatingPool()\\n self.newGeneration()\",\n \"def iadd(state: State) -> State:\\n cell = state.array[state.index] or 0\\n return state._replace(acc=state.acc + cell)\",\n \"def addS6(self):\\n self.space6 += 1\",\n \"def setup_ssem(self):\\n \\n groundBox = box_polygon_shape(-20,-500,1,1) # A tiny box that just acts as the ground body for everything else\\n groundBody = self.world.CreateStaticBody(shapes=groundBox)\\n self.memory_sender_y = -500\\n self.groundBody = groundBody\\n # Initial charge for main injector\\n self.ball_bearing_block(0,190,cols=16)\\n self.add_static_polygon([ (0,20), (100,0), (100,5), (0,25)], -132, 220)\\n self.add_static_polygon([ (0,0), (3,0), (3,20), (0,20)], -132, 240)\\n self.injector_cranks = []\\n self.parts.main_injector_raiser = self.injector(-32,150, groundBody, injector_crank_array=self.injector_cranks)\\n\\n (self.parts.memory_selector_holdoff, self.parts.memory_follower_holdoff) = self.memory_module(0,0, groundBody)\\n self.upper_regenerators = []\\n self.parts.accumulator_diverter_lever = self.diverter_set(0,130, groundBody, slope_x=-240, slope_y=180, return_weight=10) # Diverter 1. Splits to subtractor reader.\\n\\n self.parts.discard_lever_2 = self.diverter_set(-5,-30, groundBody, discard=470) # Diverter 2a. Discard reader-pulse data.\\n self.parts.upper_regen_control = self.regenerator(-5,-65, groundBody, self.upper_regenerators) # Regenerator 1. For regenning anything read from memory.\\n self.parts.ip_diverter_lever = self.diverter_set(-5,-95, groundBody, slope_x=320, slope_y=170, start_at=3, return_weight=5) # Diverter 1. Splits to instruction counter.\\n self.parts.diverter_3 = self.diverter_set(-10,-158, groundBody, slope_x=200, slope_y=310) # Diverter 3; splits to instruction reg/PC\\n \\n # PC injector\\n pc_injector_x = 230\\n pc_injector_y = -290\\n self.pc_injector_cranks = [] \\n self.parts.pc_injector_raiser = self.injector(pc_injector_x,pc_injector_y, groundBody, injector_crank_array=self.pc_injector_cranks, columns=5)\\n # Initial charge for PC injector\\n self.ball_bearing_block(250,-240,cols=8)\\n\\n\\n sub_pos_x = -15\\n sub_pos_y = -220\\n self.parts.accumulator_reset_lever = self.subtractor(sub_pos_x,sub_pos_y, groundBody, discard_bands=True, toggle_joint_array=self.accumulator_toggles, comparison_output=True)\\n self.dropper = self.slow_drop_unit(groundBody, sub_pos_x-18, sub_pos_y+40)\\n\\n # The 'skip lever' - the large balance arm which injects one\\n # into the program counter when comparison (CMP) succeeds\\n skip_lever_x = sub_pos_x - 200\\n skip_lever_y = sub_pos_y - 200\\n a = fixtureDef(shape=polygonShape(vertices=[(-50,-32), (0,-30), (0,-25), (-50,-30)]), filter=filters[0], density=1.0)\\n b = fixtureDef(shape=box_polygon_shape(0,-30,5,30), filter=filters[0], density=1.0)\\n c = fixtureDef(shape=box_polygon_shape(-30,-30,5,30), filter=filters[0], density=1.0)\\n d = fixtureDef(shape=box_polygon_shape(0,0,300,5), filter=filters[2], density=1.0)\\n e = fixtureDef(shape=box_polygon_shape(285,-15,15,15), filter=filters[2], density=2.10)\\n f = fixtureDef(shape=box_polygon_shape(150,-50,5,50), filter=filters[0], density=1.0)\\n skip_lever=self.add_multifixture([a,b,d,e,f], skip_lever_x, skip_lever_y)\\n skip_lever.attachment_point = (150,-50)\\n skip_lever.origin = (skip_lever_x,skip_lever_y)\\n\\n self.revolving_joint(groundBody, skip_lever, (skip_lever_x+150, skip_lever_y+2.5), friction=0)\\n self.add_static_polygon(polygonShape(vertices=box_vertices(0, 0, 10,10)), skip_lever_x+270, skip_lever_y-15, filter=filters[2])\\n self.parts.cmp_injector = self.horizontal_injector(skip_lever_x-48,skip_lever_y+257, groundBody)\\n self.ball_bearing_block(skip_lever_x-30,skip_lever_y+280,cols=1)\\n self.add_static_polygon(polygonShape(vertices=[(0,0), (20,0), (0,20)]), skip_lever_x-30,skip_lever_y+230)\\n \\n self.lower_regenerators = []\\n self.parts.lower_regen_control = self.regenerator(-203,-400, groundBody, self.lower_regenerators)\\n #Program counter\\n self.parts.pc_reset_lever = self.subtractor(400,-320, groundBody, lines=5, toggle_joint_array=self.ip_toggles, is_actually_adder=True)\\n # Thing that adds one ball bearing to the PC\\n pc_incrementer_x = 457\\n pc_incrementer = self.horizontal_injector(pc_incrementer_x,-240, groundBody)\\n # Overspill loose ball bearings from the PC incrementer to the PC reader\\n overspill_width = pc_incrementer_x - pc_injector_x - 125\\n self.add_static_polygon([ (0, 0), (overspill_width,15), (overspill_width,20), (0,5) ], pc_injector_x+125,pc_injector_y+65)\\n\\n # Block to stop right-side overspill on incrementer\\n self.add_static_polygon([ (0, 0), (5,0), (5,20), (0,20) ], pc_incrementer_x+27,-240+40)\\n\\n\\n self.ball_bearing_block(457+20,-250+30,cols=1)\\n self.distance_joint(skip_lever, pc_incrementer)\\n\\n self.connect_regenerators()\\n\\n # Large collection plates at the bottom\\n self.add_static_polygon([ (-300,-600),(700,-550), (700,-610), (-300,-610)])\\n self.add_static_polygon([ (600,-610),(700,-610), (850,-400), (800,-400)])\\n self.add_static_polygon([ (-500,-400),(-450,-400), (-310,-610), (-400,-610)])\\n\\n # Instruction decoder ROM\\n self.rom_followers = []\\n self.rom_selectors = []\\n (self.parts.instruction_selector_holdoff, self.parts.instruction_follower_holdoff) = self.add_row_decoder(200, 0, groundBody, self.rom_followers, self.rom_selectors)\\n self.labels.append((\\\"Instruction decoder\\\", 400,0,0))\\n\\n self.add_instruction_cranks(groundBody, 550, 140)\\n self.parts.sender_eject = self.memory_sender(198,self.memory_sender_y, groundBody)\\n self.connect_memory()\\n\\n # A guard which stops waste data from the subtractor falling into the instruction register\\n self.add_static_polygon([ (0,0), (120,120), (120,123), (0,3)], 120, self.memory_sender_y-10)\\n\\n # Add one final transfer band to move everything back into band 0\\n self.transfer_bands.append((-550+10, -550, [ (-300,800)], 1))\",\n \"def add_corridor_constraint(self,seg,r,weight=1.0):\\n\\n constraint_type = \\\"cylinder\\\"\\n params = dict()\\n params['x1'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg],\\n self.qr_polytraj.waypoints['y'][0,seg],\\n self.qr_polytraj.waypoints['z'][0,seg]])\\n params['x2'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg+1],\\n self.qr_polytraj.waypoints['y'][0,seg+1],\\n self.qr_polytraj.waypoints['z'][0,seg+1]])\\n params['der'] = 0\\n params['l'] = r # Give the same radius buffer on the end caps\\n params['r'] = r\\n params['weight'] = weight\\n params['keep_out'] = False\\n params['active_seg'] = seg\\n\\n\\n self.qr_polytraj.add_constraint(constraint_type,params,dynamic_weighting=False,sum_func=False)\",\n \"def add_conn(self, a1, a2):\\n if self.use_pconn:\\n raise ValueError(\\\"Can not add bonds to systems with pconn - well, we can fix this ;) \\\")\\n self.conn[a1].append(a2)\\n self.conn[a2].append(a1)\\n d,v,imgi = self.get_distvec(a1,a2)\\n self.pconn[a1].append(images[imgi])\\n d,v,imgi = self.get_distvec(a2,a1)\\n self.pconn[a2].append(images[imgi])\\n logger.warning('pconn may not be properly updated!!!')\\n return\",\n \"def _dcg_idcg(relevance_scores, cg_discount):\\n # cg_discount is safe\\n dcg_k = relevance_scores / cg_discount\\n return tf.reduce_sum(dcg_k)\",\n \"def on_custom_mindstorms_gadget_control(self, directive):\\n try:\\n payload = json.loads(directive.payload.decode(\\\"utf-8\\\"))\\n print(\\\"Control payload: {}\\\".format(payload))\\n control_type = payload[\\\"type\\\"]\\n\\n if control_type == \\\"moveSteps\\\":\\n # Expected params: [direction, steps, speed]\\n self.enemy_not_detected = True\\n self._moveSteps(payload[\\\"direction\\\"], int(payload[\\\"steps\\\"]), int(payload[\\\"speed\\\"]))\\n\\n if control_type == \\\"patrol\\\":\\n self.patrol_mode = True\\n self.enemy_not_detected = True\\n \\n if control_type == \\\"smash\\\":\\n print(\\\"SMASHING\\\")\\n \\n self.weapon.on_for_degrees(SpeedPercent(100), 300)\\n self.weapon.on_for_degrees(SpeedPercent(-50), 300)\\n time.sleep(5)\\n self._send_event(EventName.SMASH, {'Smashed': 1})\\n #self.smash_mode = False\\n print(\\\"1 smashed\\\")\\n self.enemy_not_detected = True\\n print(\\\"+++++ self.patrol_mode = {} y self.enemy_not_detected = {}\\\".format(self.patrol_mode, self.enemy_not_detected))\\n self.leds.set_color(\\\"LEFT\\\", \\\"GREEN\\\", 1)\\n self.leds.set_color(\\\"RIGHT\\\", \\\"GREEN\\\", 1)\\n \\n\\n except KeyError:\\n print(\\\"Missing expected parameters: {}\\\".format(directive))\",\n \"def assemble_operator(self, parameters, space_group='default'):\\n operator = super(RWGDominantSystem, self).assemble_operator(parameters, space_group)\\n return operator.weak_form()\",\n \"def glucose_c1(self, g_t, t_G, a_G, d_g_t=0):\\n return -(1/t_G)*g_t+(a_G/t_G)*d_g_t\",\n \"def add_classifier_state(self,st):\\n self.classifier_states.append(st)\",\n \"def cy(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CY(), target=[control, target])\",\n \"def add_modified_decoherence_noise(\\n prog: \\\"Program\\\",\\n T1: Union[Dict[int, float], float] = 30e-6,\\n T2: Union[Dict[int, float], float] = 30e-6,\\n gate_time_1q: float = 50e-9,\\n gate_time_2q: float = 150e-09,\\n ro_fidelity: Union[Dict[int, float], float] = 0.95,\\n) -> \\\"Program\\\":\\n gates = _get_program_gates(prog)\\n #definitions = {\\n # def_gate.name: def_gate.matrix for def_gate in prog.defined_gates #figure out what is it for \\n #}\\n noise_model = _modified_decoherence_noise_model(\\n gates,\\n T1=T1,\\n T2=T2,\\n gate_time_1q=gate_time_1q,\\n gate_time_2q=gate_time_2q,\\n ro_fidelity=ro_fidelity\\n )\\n return apply_modified_noise_model(prog, noise_model)\",\n \"def GED(g1, g2, lib='gedlibpy', cost='CHEM_1', method='IPFP',\\n edit_cost_constant=[], stabilizer='min', repeat=50):\\n if lib == 'gedlibpy':\\n def convertGraph(G):\\n \\\"\\\"\\\"Convert a graph to the proper NetworkX format that can be\\n recognized by library gedlibpy.\\n \\\"\\\"\\\"\\n G_new = nx.Graph()\\n for nd, attrs in G.nodes(data=True):\\n G_new.add_node(str(nd), chem=attrs['atom_symbol'])\\n# G_new.add_node(str(nd), x=str(attrs['attributes'][0]),\\n# y=str(attrs['attributes'][1]))\\n for nd1, nd2, attrs in G.edges(data=True):\\n G_new.add_edge(str(nd1), str(nd2), valence=attrs['bond_type'])\\n# G_new.add_edge(str(nd1), str(nd2))\\n\\n return G_new\\n\\n gedlibpy.restart_env()\\n gedlibpy.add_nx_graph(convertGraph(g1), \\\"\\\")\\n gedlibpy.add_nx_graph(convertGraph(g2), \\\"\\\")\\n\\n listID = gedlibpy.get_all_graph_ids()\\n gedlibpy.set_edit_cost(cost, edit_cost_constant=edit_cost_constant)\\n gedlibpy.init()\\n gedlibpy.set_method(method, \\\"\\\")\\n gedlibpy.init_method()\\n\\n g = listID[0]\\n h = listID[1]\\n if stabilizer == None:\\n gedlibpy.run_method(g, h)\\n pi_forward = gedlibpy.get_forward_map(g, h)\\n pi_backward = gedlibpy.get_backward_map(g, h)\\n upper = gedlibpy.get_upper_bound(g, h)\\n lower = gedlibpy.get_lower_bound(g, h)\\n elif stabilizer == 'mean':\\n # @todo: to be finished...\\n upper_list = [np.inf] * repeat\\n for itr in range(repeat):\\n gedlibpy.run_method(g, h)\\n upper_list[itr] = gedlibpy.get_upper_bound(g, h)\\n pi_forward = gedlibpy.get_forward_map(g, h)\\n pi_backward = gedlibpy.get_backward_map(g, h)\\n lower = gedlibpy.get_lower_bound(g, h)\\n upper = np.mean(upper_list)\\n elif stabilizer == 'median':\\n if repeat % 2 == 0:\\n repeat += 1\\n upper_list = [np.inf] * repeat\\n pi_forward_list = [0] * repeat\\n pi_backward_list = [0] * repeat\\n for itr in range(repeat):\\n gedlibpy.run_method(g, h)\\n upper_list[itr] = gedlibpy.get_upper_bound(g, h)\\n pi_forward_list[itr] = gedlibpy.get_forward_map(g, h)\\n pi_backward_list[itr] = gedlibpy.get_backward_map(g, h)\\n lower = gedlibpy.get_lower_bound(g, h)\\n upper = np.median(upper_list)\\n idx_median = upper_list.index(upper)\\n pi_forward = pi_forward_list[idx_median]\\n pi_backward = pi_backward_list[idx_median]\\n elif stabilizer == 'min':\\n upper = np.inf\\n for itr in range(repeat):\\n gedlibpy.run_method(g, h)\\n upper_tmp = gedlibpy.get_upper_bound(g, h)\\n if upper_tmp < upper:\\n upper = upper_tmp\\n pi_forward = gedlibpy.get_forward_map(g, h)\\n pi_backward = gedlibpy.get_backward_map(g, h)\\n lower = gedlibpy.get_lower_bound(g, h)\\n if upper == 0:\\n break\\n elif stabilizer == 'max':\\n upper = 0\\n for itr in range(repeat):\\n gedlibpy.run_method(g, h)\\n upper_tmp = gedlibpy.get_upper_bound(g, h)\\n if upper_tmp > upper:\\n upper = upper_tmp\\n pi_forward = gedlibpy.get_forward_map(g, h)\\n pi_backward = gedlibpy.get_backward_map(g, h)\\n lower = gedlibpy.get_lower_bound(g, h)\\n elif stabilizer == 'gaussian':\\n pass\\n\\n dis = upper\\n\\n # make the map label correct (label remove map as np.inf)\\n nodes1 = [n for n in g1.nodes()]\\n nodes2 = [n for n in g2.nodes()]\\n nb1 = nx.number_of_nodes(g1)\\n nb2 = nx.number_of_nodes(g2)\\n pi_forward = [nodes2[pi] if pi < nb2 else np.inf for pi in pi_forward]\\n pi_backward = [nodes1[pi] if pi <\\n nb1 else np.inf for pi in pi_backward]\\n\\n return dis, pi_forward, pi_backward\",\n \"def __init__(self, *args):\\n moose.HHChannel.__init__(self,*args)\\n self.Ek = VKDR\\n self.Gbar = GKDR\\n self.addField('ion')\\n self.setField('ion','K')\\n self.Xpower = 1 # This will create HHGate instance xGate inside the Na channel\\n #self.Ypower = 0 # This will create HHGate instance yGate inside the Na channel\\n ## Below gates get created after Xpower or Ypower are set to nonzero values\\n ## I don't anymore have to explicitly create these attributes in the class\\n #self.xGate = moose.HHGate(self.path + \\\"/xGate\\\")\\n #self.yGate = moose.HHGate(self.path + \\\"/yGate\\\")\\n self.xGate.A.xmin = VMIN\\n self.xGate.A.xmax = VMAX\\n self.xGate.A.xdivs = NDIVS\\n self.xGate.B.xmin = VMIN\\n self.xGate.B.xmax = VMAX\\n self.xGate.B.xdivs = NDIVS\\n \\n v = VMIN\\n\\n for i in range(NDIVS+1):\\n mtau = calc_KA_mtau(v)\\n self.xGate.A[i] = calc_KA_minf(v)/mtau\\n self.xGate.B[i] = 1.0/mtau\\n v = v + dv\",\n \"def __init__(self, *args):\\n _gdi_.GCDC_swiginit(self,_gdi_.new_GCDC(*args))\\n self.__dc = args[0] # save a ref so the other dc will not be deleted before self\",\n \"def add_carboxyl(atom, atom_list, added_functional_groups, ct):\\n \\n global anywhere_map\\n global edge_map\\n current_size = len(atom_list)\\n placed = 0\\n alpha = random.randint(0,359)\\n x = atom.x\\n y = atom.y\\n z = atom.z\\n while (placed <= 359):\\n alpha += 1\\n carbon_atom = Atom(current_size + 1, 'C4', 'C1A', str(added_functional_groups + 1), float(\\\"{0:.3f}\\\".format(x)), float(\\\"{0:.3f}\\\".format(y)), float(\\\"{0:.3f}\\\".format(ct * 1.52 + z)))\\n atom_list.append(carbon_atom)\\n if ((len(identify_bonds(carbon_atom, atom_list)) == 1) and (identify_bonds(carbon_atom, atom_list)[0][0].atom_number == atom.atom_number)):\\n h = math.sin(math.radians(60)) * 1.20\\n oxygen_atom_1 = Atom(current_size + 2, 'OJ', 'C1A', str(added_functional_groups + 1), float(\\\"{0:.3f}\\\".format(carbon_atom.x - math.cos(math.radians(alpha)) * h)), float(\\\"{0:.3f}\\\".format(carbon_atom.y - math.sin(math.radians(alpha)) * h)), float(\\\"{0:.3f}\\\".format(carbon_atom.z + ct * math.cos(math.radians(60)) * 1.20)))\\n atom_list.append(oxygen_atom_1)\\n if ((len(identify_bonds(oxygen_atom_1, atom_list)) == 1) and (identify_bonds(oxygen_atom_1, atom_list)[0][0].atom_number == carbon_atom.atom_number)):\\n h = math.sin(math.radians(60)) * 1.34\\n oxygen_atom_2 = Atom(current_size + 3, 'OK', 'C1A', str(added_functional_groups + 1), float(\\\"{0:.3f}\\\".format(carbon_atom.x - math.cos(math.radians(alpha + 180)) * h)), float(\\\"{0:.3f}\\\".format(carbon_atom.y - math.sin(math.radians(alpha+180)) * h)), float(\\\"{0:.3f}\\\".format(carbon_atom.z + ct * math.cos(math.radians(60)) * 1.34)) )\\n atom_list.append(oxygen_atom_2)\\n if ((len(identify_bonds(oxygen_atom_2, atom_list)) == 1) and (identify_bonds(oxygen_atom_2, atom_list)[0][0].atom_number == carbon_atom.atom_number)):\\n hydrogen_atom = Atom(current_size + 4, 'HK', 'C1A', str(added_functional_groups + 1), float(\\\"{0:.3f}\\\".format(oxygen_atom_2.x)), float(\\\"{0:.3f}\\\".format(oxygen_atom_2.y)), float(\\\"{0:.3f}\\\".format(oxygen_atom_2.z+ct*0.98)))\\n atom_list.append(hydrogen_atom)\\n if ((len(identify_bonds(hydrogen_atom, atom_list)) == 1) and (identify_bonds(hydrogen_atom, atom_list)[0][0].atom_number == oxygen_atom_2.atom_number)):\\n placed = 888\\n if atom in edge_map: edge_map.remove(atom)\\n if atom in anywhere_map: anywhere_map.remove(atom)\\n CY = Atom(atom.atom_number, 'CY', 'C1A', carbon_atom.residue_number, atom.x, atom.y, atom.z)\\n atom_list.append(CY)\\n atom_list.remove(atom)\\n del atom\\n else:\\n placed += 5\\n del hydrogen_atom\\n del atom_list[current_size + 3]\\n del oxygen_atom_2\\n del atom_list[current_size + 2]\\n del oxygen_atom_1\\n del atom_list[current_size + 1]\\n del carbon_atom\\n del atom_list[current_size + 0]\\n else:\\n placed += 5\\n del oxygen_atom_2\\n del atom_list[current_size + 2]\\n del oxygen_atom_1\\n del atom_list[current_size + 1]\\n del carbon_atom\\n del atom_list[current_size + 0]\\n else:\\n placed += 5\\n del oxygen_atom_1\\n del atom_list[current_size + 1]\\n del carbon_atom\\n del atom_list[current_size + 0]\\n else:\\n placed += 5\\n del carbon_atom \\n del atom_list[current_size + 0]\\n return atom_list\",\n \"def add_disease(self, disease):\\n self.diseases.append(disease)\",\n \"def s_dg(self, q0, ctrl=None):\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S_, qid=[q0], ctrl=ctrl)\\n return self\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5338038","0.5312894","0.52970165","0.5271169","0.517592","0.51653695","0.515889","0.5066648","0.50336796","0.5003395","0.5001316","0.49954224","0.4991093","0.49732873","0.49150544","0.4883801","0.48823026","0.48561972","0.48432097","0.48432097","0.48407978","0.47819588","0.4773641","0.47598237","0.4758414","0.47531796","0.47511643","0.4735614","0.46829173","0.46771306","0.46645576","0.4657111","0.4652728","0.46474424","0.46468112","0.4623847","0.46188587","0.4618165","0.4610556","0.4596291","0.45954317","0.45810905","0.45736066","0.45647842","0.456346","0.4553023","0.45511892","0.4545104","0.45188287","0.45143566","0.45104927","0.4506319","0.45035154","0.45022345","0.44962394","0.44952098","0.44859466","0.44830066","0.44747677","0.4462041","0.44615677","0.44552755","0.44439995","0.44331142","0.44268733","0.44268644","0.44262064","0.4410897","0.44096363","0.440778","0.4407684","0.44040257","0.44029272","0.44021368","0.4384388","0.4383934","0.43809703","0.43764403","0.43759742","0.43754295","0.4360915","0.43547574","0.43500277","0.43500096","0.434632","0.4342199","0.43397585","0.43325195","0.43286932","0.4328634","0.43264663","0.43255213","0.432486","0.43246737","0.432167","0.43213636","0.43200117","0.4315827","0.43026376","0.4301908"],"string":"[\n \"0.5338038\",\n \"0.5312894\",\n \"0.52970165\",\n \"0.5271169\",\n \"0.517592\",\n \"0.51653695\",\n \"0.515889\",\n \"0.5066648\",\n \"0.50336796\",\n \"0.5003395\",\n \"0.5001316\",\n \"0.49954224\",\n \"0.4991093\",\n \"0.49732873\",\n \"0.49150544\",\n \"0.4883801\",\n \"0.48823026\",\n \"0.48561972\",\n \"0.48432097\",\n \"0.48432097\",\n \"0.48407978\",\n \"0.47819588\",\n \"0.4773641\",\n \"0.47598237\",\n \"0.4758414\",\n \"0.47531796\",\n \"0.47511643\",\n \"0.4735614\",\n \"0.46829173\",\n \"0.46771306\",\n \"0.46645576\",\n \"0.4657111\",\n \"0.4652728\",\n \"0.46474424\",\n \"0.46468112\",\n \"0.4623847\",\n \"0.46188587\",\n \"0.4618165\",\n \"0.4610556\",\n \"0.4596291\",\n \"0.45954317\",\n \"0.45810905\",\n \"0.45736066\",\n \"0.45647842\",\n \"0.456346\",\n \"0.4553023\",\n \"0.45511892\",\n \"0.4545104\",\n \"0.45188287\",\n \"0.45143566\",\n \"0.45104927\",\n \"0.4506319\",\n \"0.45035154\",\n \"0.45022345\",\n \"0.44962394\",\n \"0.44952098\",\n \"0.44859466\",\n \"0.44830066\",\n \"0.44747677\",\n \"0.4462041\",\n \"0.44615677\",\n \"0.44552755\",\n \"0.44439995\",\n \"0.44331142\",\n \"0.44268733\",\n \"0.44268644\",\n \"0.44262064\",\n \"0.4410897\",\n \"0.44096363\",\n \"0.440778\",\n \"0.4407684\",\n \"0.44040257\",\n \"0.44029272\",\n \"0.44021368\",\n \"0.4384388\",\n \"0.4383934\",\n \"0.43809703\",\n \"0.43764403\",\n \"0.43759742\",\n \"0.43754295\",\n \"0.4360915\",\n \"0.43547574\",\n \"0.43500277\",\n \"0.43500096\",\n \"0.434632\",\n \"0.4342199\",\n \"0.43397585\",\n \"0.43325195\",\n \"0.43286932\",\n \"0.4328634\",\n \"0.43264663\",\n \"0.43255213\",\n \"0.432486\",\n \"0.43246737\",\n \"0.432167\",\n \"0.43213636\",\n \"0.43200117\",\n \"0.4315827\",\n \"0.43026376\",\n \"0.4301908\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5636926"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81750,"cells":{"query":{"kind":"string","value":"add CT gate (controlled T gate)."},"document":{"kind":"string","value":"def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def __init__(self, input, output) :\n Gate.__init__(self, [input], output)","def add_junction(ccTremb):\n pass","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def _process_gate(self, node, opaque=False):\n self.gates[node.name] = {}\n de_gate = self.gates[node.name]\n de_gate[\"opaque\"] = opaque\n de_gate[\"n_args\"] = node.n_args()\n de_gate[\"n_bits\"] = node.n_bits()\n if node.n_args() > 0:\n de_gate[\"args\"] = [element.name for element in node.arguments.children]\n else:\n de_gate[\"args\"] = []\n de_gate[\"bits\"] = [c.name for c in node.bitlist.children]\n if opaque:\n de_gate[\"body\"] = None\n else:\n de_gate[\"body\"] = node.body\n self.backend.define_gate(node.name, copy.deepcopy(de_gate))","def __init__(self, input0, input1, output) :\n Gate.__init__(self, [input0,input1], output)","def _template_circuit(self, amp_param) -> QuantumCircuit:\n gate = Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param])\n\n circuit = QuantumCircuit(1)\n circuit.append(gate, (0,))\n circuit.measure_active()\n\n return circuit","def __add__(self, tc): \n tc = TwosComplement(tc)\n bits = self.len if self.len > tc.len else tc.len \n result = self.int + tc.int\n return TwosComplement(result, bits)","def add_control(operation, num_ctrl_qubits, label):\n if isinstance(operation, UnitaryGate):\n # attempt decomposition\n operation._define()\n if _control_definition_known(operation, num_ctrl_qubits):\n return _control_predefined(operation, num_ctrl_qubits)\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)","def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\n if q_args is None and c_args is None:\n raise GateError(\"Gate needs at least one quantum argument or classical argument\")\n if isinstance(gate, CompositeGate):\n if mapping is None:\n raise GateError(\"Must provide arguments mapping for composite gate inside a composite gate.\")\n else:\n inv_mappimg = dict()\n for key, value in mapping.items():\n inv_mappimg[value] = key\n if gate is self:\n gates = gate.copy.gates\n else:\n gates = gate.gates\n for g in gates:\n new_q_args = None\n new_c_args = None\n if g[1] is not None:\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\n if g[2] is not None:\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\n self.add_gate(gate=g[0], q_args=new_q_args,\n c_args=new_c_args, params=g[3])\n else:\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\n raise GateError(\"Gate must be either a CompositeGate or a string from: \"\n \"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\")\n if q_args is not None:\n for q_arg in q_args:\n if q_arg not in self.q_args:\n self.add_q_arg(q_arg)\n if c_args is not None:\n for c_arg in c_args:\n if c_arg not in self.c_args:\n self.add_c_arg(c_arg)\n if params is not None:\n for param in params:\n if param not in self.params:\n self.add_param(param)\n self._gates.append((gate, q_args, c_args, params))","def _control_predefined(operation, num_ctrl_qubits):\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\n if num_ctrl_qubits == 1:\n import qiskit.extensions.standard.cx\n cgate = qiskit.extensions.standard.cx.CnotGate()\n else:\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n elif operation.name == 'y':\n import qiskit.extensions.standard.cy\n cgate = qiskit.extensions.standard.cy.CyGate()\n elif operation.name == 'z':\n import qiskit.extensions.standard.cz\n cgate = qiskit.extensions.standard.cz.CzGate()\n elif operation.name == 'h':\n import qiskit.extensions.standard.ch\n cgate = qiskit.extensions.standard.ch.CHGate()\n elif operation.name in {'rx', 'ry', 'rz'}:\n if operation.name == 'rx':\n import qiskit.extensions.standard.crx\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\n elif operation.name == 'ry':\n import qiskit.extensions.standard.cry\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\n else: # operation.name == 'rz'\n import qiskit.extensions.standard.crz\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\n if num_ctrl_qubits == 1:\n return cgate\n else:\n # only predefined for one control qubit\n return cgate.control(num_ctrl_qubits - 1)\n elif operation.name == 'swap':\n import qiskit.extensions.standard.cswap\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\n elif operation.name == 'u1':\n import qiskit.extensions.standard.cu1\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\n elif operation.name == 'u3':\n import qiskit.extensions.standard.cu3\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\n elif operation.name == 'cx':\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n else:\n raise QiskitError('No standard controlled gate for \"{}\"'.format(\n operation.name))\n return cgate","def append_user_gate(self, user_gate):\n self.translation['g_sect'].append(user_gate)","def add(self, ct):\n self[ct._id] = ct","def add_inputt(self, name='T', control=False):\n inpt = InputT(name=name)\n self.nodes[name] = inpt\n self.rc.add_node(inpt)\n if control: # control input\n if name in self.inp.keys():\n raise Exception('Input temperature already defined')\n self.inp[name] = inpt\n else: # disturbance\n if name in self.dist.keys():\n raise Exception('Input temperature already defined')\n self.dist[name] = inpt","def __iadd__(self, tensor):\n return self.add_(tensor)","def _add_entanglement_gate(self, gate_method, qubit_1, qubit_2):\r\n sig = signature(gate_method)\r\n\r\n # parametrized gate like a controlled single qubit rotation\r\n if 'theta' in sig.parameters:\r\n try:\r\n gate_method(self.circuit, self.parameters[next(self.indices)], qubit_1, qubit_2)\r\n except KeyError:\r\n raise ValueError(f'Unsupported two qubit rotation gate')\r\n\r\n # non-parametrized gate like CNOT\r\n else:\r\n try:\r\n gate_method(self.circuit, qubit_1, qubit_2)\r\n except KeyError:\r\n raise ValueError(f'Unsupported unparametrized two qubit gate')","def addTN(self, num=1):\n self.tn += num","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def add_connector(self):\n \n no = len(self.connectors)\n state = {}\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % no\n \n if len(self.connectors)>0:\n state = self.connectors[-1].get_state()\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % (no)\n else:\n if self.mount == self.MOUNT_THT:\n state[\"p_shape\"] = Con.SHAPE_HOLE\n elif self.mount == self.MOUNT_SMD:\n state[\"p_shape\"] = Con.SHAPE_PAD\n \n c = Con(no)\n c.set_state(state) \n \n self.sch_layers[\"pins\"].add(c.s_svg)\n self.pcb_layers[\"copper1\"].add(c.p_svg)\n self.connectors.append(c)","def add_road(ccTremb):\n pass","def __add__(self, tensor):\n return self.add(tensor)","def _template_circuit(self, amp_param) -> QuantumCircuit:\n circuit = QuantumCircuit(1)\n circuit.x(0)\n circuit.append(Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param]), (0,))\n circuit.measure_active()\n\n return circuit","def add(self, y):\n return circuit.add(self, y)","def connect(self, gate) :\n self.notifyList.append(gate)","def actual_causation():\n # fmt: off\n tpm = np.array([\n [1, 0, 0, 0],\n [0, 1, 0, 0],\n [0, 1, 0, 0],\n [0, 0, 0, 1],\n ])\n cm = np.array([\n [1, 1],\n [1, 1],\n ])\n # fmt: on\n return Network(tpm, cm, node_labels=('OR', 'AND'))","def __init__(self, gate: Gate, tag: Any) -> None:\n\n if not isinstance(gate, Gate):\n raise TypeError('Expected gate object, got %s' % type(gate))\n\n self.gate = gate\n self.tag = tag\n self.name = 'Tagged(%s:%s)' % (gate.get_name(), tag)\n self.num_params = gate.get_num_params()\n self.size = gate.get_size()\n self.radixes = gate.get_radixes()\n\n # If input is a constant gate, we can cache the unitary.\n if self.num_params == 0:\n self.utry = gate.get_unitary()","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def add_new_control_point(moment_data, new_control_point, new_frame_id,\n runtime_bucket, is_vehicle=False):\n change_type = \"ped_controls\"\n if is_vehicle:\n change_type = \"vehicle_controls\"\n prev_controls = \\\n moment_data[runtime_bucket[\"cur_moment_idx\"]][change_type]\n new_frame_id = \"%s\" % new_frame_id # json's fault\n #if prev_controls.has_key(new_frame_id):\n if new_frame_id in prev_controls:\n # add to the existing frame\n moment_data[runtime_bucket[\"cur_moment_idx\"]][change_type][\n new_frame_id].append(new_control_point)\n else:\n # a new frame\n moment_data[runtime_bucket[\"cur_moment_idx\"]][change_type][\n new_frame_id] = [new_control_point]\n\n # get the new traj data\n person_data, vehicle_data = get_trajs(\n moment_data, runtime_bucket[\"cur_moment_idx\"])\n runtime_bucket[\"person_data\"] = person_data\n runtime_bucket[\"vehicle_data\"] = vehicle_data","def addOp(self, op):\n self.operations << op","def add_state(self, name='Ti', c=2000):\n assert isinstance(name, str), 'name must be a string type'\n if name in self.sta.keys():\n raise Exception('State already defined')\n state = State(c=c, name=name)\n self.sta[name] = state\n self.nodes[name] = state\n self.rc.add_node(state)","def gate_lfcc(recurrent_net, sample_input):\n length = sample_input.shape[0]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[i, :])\n select = sigmoid(select)\n score = sigmoid(score)\n return np.sum(select * score) / np.sum(select)","def iadd(state: State) -> State:\n cell = state.array[state.index] or 0\n return state._replace(acc=state.acc + cell)","def cy(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CY(), target=[control, target])","def addTP(self, num=1):\n self.tp += num","def addToTfLink(G,i,j,siso):\n m,n,r = np.shape(G.num)\n dt = G.dt\n\n #Create a new transfer fuction Add, that is zero except the i,jth entry \n Addnum = []\n Addden = []\n rowN = [np.array([0.])]*n\n rowD = [np.array([1.])]*n\n\n for k in range(m):\n Addnum.append(list(rowN))\n Addden.append(list(rowD))\n\n #Make the i,jth entry of Add equal to siso\n Addnum[i][j] = siso.num[0][0]\n Addden[i][j] = siso.den[0][0]\n Add = ctrl.tf(Addnum,Addden,dt)\n\n #Use the control library + function to add the new transfer function to G\n Gplus = G + Add\n return Gplus","def addToTfLink(G,i,j,siso):\n m,n,r = np.shape(G.num)\n dt = G.dt\n\n #Create a new transfer fuction Add, that is zero except the i,jth entry \n Addnum = []\n Addden = []\n rowN = [np.array([0.])]*n\n rowD = [np.array([1.])]*n\n\n for k in range(m):\n Addnum.append(list(rowN))\n Addden.append(list(rowD))\n\n #Make the i,jth entry of Add equal to siso\n Addnum[i][j] = siso.num[0][0]\n Addden[i][j] = siso.den[0][0]\n Add = ctrl.tf(Addnum,Addden,dt)\n\n #Use the control library + function to add the new transfer function to G\n Gplus = G + Add\n return Gplus","def user_gate_definition(self, filenum, linenum, txt):\n txt = txt.strip()\n gate_decl = QTRegEx.GATE_DECL.match(txt)\n gate_name = gate_decl.group(1)\n possible_gate_params = gate_name.split('(')\n gate_param_list = None\n if len(possible_gate_params) > 1:\n gate_param_list = possible_gate_params[1].strip(') ').split(',')\n gate_regs = gate_decl.group(2).strip(\"{}\") # watch out for no space before '{' !!\n gate_reg_list = gate_regs.split(',')\n gate_ops = QTRegEx.GATE_OPS.match(txt)\n gate_ops_raw_list = QTRegEx.GATE_OPS_LIST.findall(gate_ops.group(1))\n gate_ops_list = []\n for op_raw in gate_ops_raw_list:\n op_raw = op_raw.strip()\n op = QTRegEx.GATE_OP.match(op_raw).group(1)\n op_params = QTRegEx.GATE_OP_PARAMS.match(op_raw)\n if op_params:\n op_param_list = op_params.group(1).split(',')\n else:\n op_param_list = None\n op_regs = QTRegEx.GATE_OP_REGS.match(op_raw)\n if op_regs:\n op_reg_list = op_regs.group(1).split(',')\n else:\n op_reg_list = None\n gate_ops_list.append({'op': op,\n 'op_param_list': op_param_list,\n 'op_reg_list': op_reg_list})\n gate = {'source': txt if self.save_gate_source else None,\n 'filenum': filenum,\n 'linenum': linenum, 'gate_name': gate_name,\n 'gate_param_list': gate_param_list,\n 'gate_ops_raw_list': gate_ops_raw_list,\n 'gate_ops_list': gate_ops_list,\n 'gate_reg_list': gate_reg_list}\n\n self.append_user_gate(gate)","def get_gate(gate, params, num_ctrl_qubits=None):\n if gate[0] == \"c\":\n return get_gate(gate[1:], params, num_ctrl_qubits).ctrl()\n if gate == \"toffoli\":\n return get_gate(\"ccx\", params, num_ctrl_qubits)\n if gate[0:2] == \"mc\":\n name = gate[2:]\n for _ in range(num_ctrl_qubits):\n name = \"c\" + name\n return get_gate(name, params, num_ctrl_qubits)\n if len(params) == 0:\n return GATE_DIC[gate]\n\n return GATE_DIC[gate](*params)","def gate_operation(self, operation, qubit_expr, params=None):\n operation = QuantumCircuit._parse_gate_operation(operation)\n if params is not None:\n operation = operation(**params) \n qubit = self.qr.get(qubit_expr) \n return operation(qubit)","def AddOperation(self, op):\n self._operations.append(op)","def build_gate_1(gate, tags=None):\n\n def apply_constant_single_qubit_gate(psi, i, **gate_opts):\n mtags = _merge_tags(tags, gate_opts)\n psi.gate_(gate, int(i), tags=mtags, **gate_opts)\n\n return apply_constant_single_qubit_gate","def gru_cell(self, Xt, h_t_minus_1):\n # 1.update gate: decides how much past information is kept and how much new information is added.\n z_t = tf.nn.sigmoid(tf.matmul(Xt, self.W_z) + tf.matmul(h_t_minus_1,self.U_z) + self.b_z) # z_t:[batch_size,self.hidden_size]\n # 2.reset gate: controls how much the past state contributes to the candidate state.\n r_t = tf.nn.sigmoid(tf.matmul(Xt, self.W_r) + tf.matmul(h_t_minus_1,self.U_r) + self.b_r) # r_t:[batch_size,self.hidden_size]\n # candiate state h_t~\n h_t_candiate = tf.nn.tanh(tf.matmul(Xt, self.W_h) +r_t * (tf.matmul(h_t_minus_1, self.U_h)) + self.b_h) # h_t_candiate:[batch_size,self.hidden_size]\n # new state: a linear combine of pervious hidden state and the current new state h_t~\n h_t = (1 - z_t) * h_t_minus_1 + z_t * h_t_candiate # h_t:[batch_size*num_sentences,hidden_size]\n return h_t","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def addTribuf(self, tribuf_id, ip, ctrl, op):\n # Eliminating basic outlier conditions\n if tribuf_id in self.dGrph:\n print('tribuf_id already exists. No node added.')\n return\n \n self.dGrph[tribuf_id] = [(ip, ctrl), [ctrl], [op, None]]","def test_append_dangling_gate(self, circuit):\n match = (\n r\"Number of wire IDs \\(2\\) must match the number of wires connected to the gate \\(1\\).\"\n )\n gate = jet.GateFactory.create(\"H\")\n with pytest.raises(ValueError, match=match):\n circuit.append_gate(gate, wire_ids=[0, 1])","def get_CC_operators():\n i = symbols('i', below_fermi=True, cls=Dummy)\n a = symbols('a', above_fermi=True, cls=Dummy)\n t_ai = AntiSymmetricTensor('t', (a,), (i,))\n ai = NO(Fd(a)*F(i))\n i, j = symbols('i,j', below_fermi=True, cls=Dummy)\n a, b = symbols('a,b', above_fermi=True, cls=Dummy)\n t_abij = AntiSymmetricTensor('t', (a, b), (i, j))\n abji = NO(Fd(a)*Fd(b)*F(j)*F(i))\n\n T1 = t_ai*ai\n T2 = Rational(1, 4)*t_abij*abji\n return (T1, T2)","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def test_addTcfModelFile(self):\n print ('Testing add tcf ModelFile...')\n\n tuflow = copy.deepcopy(self.tuflow)\n loader = TuflowLoader()\n tcf = tuflow.control_files['TCF']\n geom = tcf.contains(command='Geometry Control')[0]\n \n line = \"Geometry Control File == ..\\\\model\\\\test_tgc2.tgc\"\n tgc_part = factory.TuflowFactory.getTuflowPart(line, tcf.mainfile)[0]\n tgc_control = loader.loadControlFile(tgc_part)\n tcf.addControlFile(tgc_part, tgc_control, after=geom)\n \n assert(tgc_part in tuflow.control_files['TGC'].control_files)\n \n test_part = tuflow.control_files['TGC'].contains(filename='shiptest_tgc2_v1_DTM_2m')\n assert(len(test_part) == 1)\n \n index = tcf.parts.index(tgc_part)\n assert(index == tcf.parts.index(geom) + 1)\n del tuflow\n\n print ('pass')","def apply_gate(self, gate_id, *gate_args, gate_round=None, **gate_opts):\n\n # unique tag\n tags = {f'GATE_{len(self.gates)}'}\n\n # parse which 'round' of gates\n if (gate_round is not None):\n tags.add(f'ROUND_{gate_round}')\n elif isinstance(gate_id, numbers.Integral) or gate_id.isdigit():\n # gate round given as first entry of qasm line\n tags.add(f'ROUND_{gate_id}')\n gate_id, gate_args = gate_args[0], gate_args[1:]\n\n gate_id = gate_id.upper()\n gate_fn = GATE_FUNCTIONS[gate_id]\n\n # overide any default gate opts\n opts = {**self.gate_opts, **gate_opts}\n\n # handle parametrize kwarg for non-parametrizable gates\n if ('parametrize' in opts) and (gate_id not in ALL_PARAM_GATES):\n parametrize = opts.pop('parametrize')\n if parametrize:\n msg = f\"The gate '{gate_id}' cannot be parametrized.\"\n raise ValueError(msg)\n # can pop+ignore if False\n\n # gate the TN!\n gate_fn(self._psi, *gate_args, tags=tags, **opts)\n\n # keep track of the gates applied\n self.gates.append((gate_id, *gate_args))","def add_trait(self, t): \n self.trait_index_to_change = t\n self.player.request_payment(self)\n # toggle add button to say delete or something","def credit(self, value):\n self._negative_value_raises_an_error(value)\n self.operations.insert(value);","def triplicateBlck(self, blck_id):\n # Eliminating basic outlier conditions\n if blck_id not in self.dGrph:\n print('blck_id: ', blck_id, ' does not exist. Triplication aborted.')\n return\n\n # identifying the type of block and triplicating\n test = len(self.dGrph[blck_id][1])\n if test == 3: # ari block\n ip = self.dGrph[blck_id][0]\n config = self.dGrph[blck_id][2]\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\n new_ops = []\n for i in range(3):\n temp_op = []\n for original_op in self.dGrph[blck_id][1]:\n temp_op.append([original_op[0]+'_trip728'+str(i), None])\n new_ops.append(temp_op)\n\n self.dGrph[new_ids[0]] = [ip, new_ops[0], config]\n self.dGrph[new_ids[1]] = [ip, new_ops[1], config]\n self.dGrph[new_ids[2]] = [ip, new_ops[2], config]\n\n # for first output\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0][0], new_ops[1][0][0]], new_ids[0]+'_and0_o')\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0][0], new_ops[2][0][0]], new_ids[1]+'_and0_o')\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0][0], new_ops[2][0][0]], new_ids[2]+'_and0_o')\n\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0][0])\n\n # for second output\n self.__addGate(new_ids[0]+'_and1', 'A', [new_ops[0][1][0], new_ops[1][1][0]], new_ids[0]+'_and1_o')\n self.__addGate(new_ids[1]+'_and1', 'A', [new_ops[0][1][0], new_ops[2][1][0]], new_ids[1]+'_and1_o')\n self.__addGate(new_ids[2]+'_and1', 'A', [new_ops[1][1][0], new_ops[2][1][0]], new_ids[2]+'_and1_o')\n\n self.__addGate(new_ids[0]+'_or1', 'O', [new_ids[0]+'_and1_o', new_ids[1]+'_and1_o', new_ids[2]+'_and1_o'], self.dGrph[blck_id][1][1][0])\n\n # for third output\n self.__addGate(new_ids[0]+'_and2', 'A', [new_ops[0][2][0], new_ops[1][2][0]], new_ids[0]+'_and2_o')\n self.__addGate(new_ids[1]+'_and2', 'A', [new_ops[0][2][0], new_ops[2][2][0]], new_ids[1]+'_and2_o')\n self.__addGate(new_ids[2]+'_and2', 'A', [new_ops[1][2][0], new_ops[2][2][0]], new_ids[2]+'_and2_o')\n\n self.__addGate(new_ids[0]+'_or2', 'O', [new_ids[0]+'_and2_o', new_ids[1]+'_and2_o', new_ids[2]+'_and2_o'], self.dGrph[blck_id][1][2][0])\n\n del self.dGrph[blck_id]\n\n elif test == 2: # cfg block\n ip = self.dGrph[blck_id][0]\n config = self.dGrph[blck_id][2]\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\n new_ops = [[self.dGrph[blck_id][2][0] + '_trip7280', None], [self.dGrph[blck_id][2][0] + '_trip7281', None], [self.dGrph[blck_id][2][0] + '_trip7282', None]]\n\n self.dGrph[new_ids[0]] = [ip, new_ops[0], config]\n self.dGrph[new_ids[1]] = [ip, new_ops[1], config]\n self.dGrph[new_ids[2]] = [ip, new_ops[2], config]\n\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0], new_ops[1][0]], new_ids[0]+'_and0_o')\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0], new_ops[2][0]], new_ids[1]+'_and0_o')\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0], new_ops[2][0]], new_ids[2]+'_and0_o')\n\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0])\n\n del self.dGrph[blck_id]\n\n elif test == 1: # tribuf\n ip = self.dGrph[blck_id][0]\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\n new_ops = [[self.dGrph[blck_id][2][0] + '_trip7280', None], [self.dGrph[blck_id][2][0] + '_trip7281', None], [self.dGrph[blck_id][2][0] + '_trip7282', None]]\n\n self.dGrph[new_ids[0]] = [ip, [ip[1]], new_ops[0]]\n self.dGrph[new_ids[1]] = [ip, [ip[1]], new_ops[1]]\n self.dGrph[new_ids[2]] = [ip, [ip[1]], new_ops[2]]\n\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0], new_ops[1][0]], new_ids[0]+'_and0_o')\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0], new_ops[2][0]], new_ids[1]+'_and0_o')\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0], new_ops[2][0]], new_ids[2]+'_and0_o')\n\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0])\n\n del self.dGrph[blck_id]\n \n else:\n print('Unknown error!!!!!!\\n')","def __call__(self, *qubit_indices: int) -> \"GateOperation\":\n return GateOperation(self, qubit_indices)","def parameterise_gate(self, gate:Union[cirq.Gate, Callable]): \n if isinstance(gate, cirq.Gate):\n if isinstance(gate, (cirq.XXPowGate, cirq.YYPowGate, cirq.ZZPowGate)):\n param = self.new_param()\n return gate**param\n return gate\n elif isclass(gate) and issubclass(gate, cirq.Gate):\n parameters = ParameterisedCircuit._get_gate_parameters(gate)\n n_param = len(parameters)\n params = self.new_param(size=n_param, as_array=True)\n kwargs = {parameters[i]:params[i] for i in range(n_param)}\n return gate(**kwargs) \n else:\n n_param = ParameterisedCircuit._get_parameter_count(gate)\n params = self.new_param(size=n_param)\n params = tuple(params) if isinstance(params, np.ndarray) else (params,) \n return gate(*params)","def add_state(self, state):\n if self.rate_variation:\n if not self.feature_rates:\n # Set all rates to 1.0 in a big plate\n plate = ET.SubElement(state, \"plate\", {\n \"var\":\"feature\",\n \"range\":\",\".join(self.features)})\n param = ET.SubElement(plate, \"parameter\", {\n \"id\":\"featureClockRate:%s:$(feature)\" % self.name,\n \"name\":\"stateNode\"})\n param.text=\"1.0\"\n else:\n # Give each rate a custom value\n for f in self.features:\n param = ET.SubElement(state, \"parameter\", {\n \"id\":\"featureClockRate:%s:%s\" % (self.name, f),\n \"name\":\"stateNode\"})\n param.text=str(self.feature_rates.get(f,1.0))\n\n # Give Gamma shape parameter a finite domain\n # Must be > 1.0 for the distribution to be bell-shaped,\n # rather than L-shaped. The domain [1.1,1000] limits feature\n # rate variation to the realms of vague plausibity\n parameter = ET.SubElement(state, \"parameter\", {\"id\":\"featureClockRateGammaShape:%s\" % self.name, \"lower\":\"1.1\",\"upper\":\"100.0\",\"name\":\"stateNode\"})\n parameter.text=\"5.0\"\n # Gamma scale parameter's domain is defined *implicilty*\n # by the fact that the operators maintain shape*scale = 1.0\n parameter = ET.SubElement(state, \"parameter\", {\"id\":\"featureClockRateGammaScale:%s\" % self.name, \"name\":\"stateNode\"})\n parameter.text=\"0.2\"","def AddTE(self, te):\n self._totalte += te","def addControl(*args):","def addControl(*args):","def addControl(*args):","def addControl(*args):","def T(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.T, qubit_expr)","def ct(self, ct):\n\n self._ct = ct","def _add_ctc_loss(pred, seq_len, num_label, loss_type):\n label = mx.sym.Variable('label')\n if loss_type == 'warpctc':\n print(\"Using WarpCTC Loss\")\n sm = _add_warp_ctc_loss(pred, seq_len, num_label, label)\n else:\n print(\"Using MXNet CTC Loss\")\n assert loss_type == 'ctc'\n sm = _add_mxnet_ctc_loss(pred, seq_len, label)\n return sm","def addFanIn(self,gate):\n assert type(gate)==Gate\n if self.gateType == \"INPUT\":\n print \"Inputs cannot have a fanIn.\"\n return\n self.fanIn.append(gate)\n gate.addFanOut(self)","def gate(self):\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)","def add():\n pass","def _threshold(self, circuit, register, ctrl_string, measure_flag_qubit=True):\n # Determine the number of controls\n ncontrols = (ctrl_string + \"1\").index(\"1\")\n\n # Edge case in which no operations are added\n if ncontrols == 0:\n return\n\n # Make sure there is at least one control\n if ncontrols == len(ctrl_string):\n raise ValueError(\"Argument ctrl_string should have at least one '1'.\")\n\n # Add the ancilla register of three qubits to the circuit\n ancilla = QuantumRegister(3, name=\"threshold\")\n circuit.add_register(ancilla)\n\n # ==============================\n # Add the gates for thresholding\n # ==============================\n\n # Do the first \"anti-controlled\" Tofolli\n for ii in range(ncontrols):\n circuit.x(register[ii])\n mct(circuit, register[:ncontrols], ancilla[0], None, mode=\"noancilla\")\n for ii in range(ncontrols):\n circuit.x(register[ii])\n\n # Do the second Tofolli\n mct(circuit, register[:ncontrols], ancilla[1], None, mode=\"noancilla\")\n\n # Do the copy CNOTs in the ancilla register\n circuit.cx(ancilla[0], ancilla[2])\n circuit.cx(ancilla[1], ancilla[2])\n\n # Uncompute the second Tofolli\n mct(circuit, register[:ncontrols], ancilla[1], None, mode=\"noancilla\")\n\n # Uncompute the first \"anti-controlled\" Tofolli\n for ii in range(ncontrols):\n circuit.x(register[ii])\n mct(circuit, register[:ncontrols], ancilla[0], None, mode=\"noancilla\")\n for ii in range(ncontrols):\n circuit.x(register[ii])\n\n # Add the \"flag qubit\" measurement, if desired\n if measure_flag_qubit:\n creg = ClassicalRegister(1, name=\"flag\")\n circuit.add_register(creg)\n circuit.measure(ancilla[2], creg[0])","def t_dg(self, q0, ctrl=None):\n self.__add_quantum_gate(kind=PHASE_SHIFT_T_, qid=[q0], ctrl=ctrl)\n return self","def compile(self, seq, registers):\n\n # Check which modes are actually being used\n used_modes = []\n for operations in seq:\n modes = [modes_label.ind for modes_label in operations.reg]\n used_modes.append(modes)\n\n used_modes = list(set(item for sublist in used_modes for item in sublist))\n\n # dictionary mapping the used modes to consecutive non-negative integers\n dict_indices = {used_modes[i]: i for i in range(len(used_modes))}\n nmodes = len(used_modes)\n\n # We start with an identity then sequentially update with the gate transformations\n T = np.identity(nmodes, dtype=np.complex128)\n\n # Now we will go through each operation in the sequence `seq` and apply it to T\n for operations in seq:\n name = operations.op.__class__.__name__\n params = par_evaluate(operations.op.p)\n modes = [modes_label.ind for modes_label in operations.reg]\n if name == \"Rgate\":\n G = np.exp(1j * params[0])\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\n elif name == \"LossChannel\":\n G = np.sqrt(params[0])\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\n elif name == \"Interferometer\":\n U = params[0]\n if U.shape == (1, 1):\n T = _apply_one_mode_gate(U[0, 0], T, dict_indices[modes[0]])\n elif U.shape == (2, 2):\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\n else:\n modes = [dict_indices[mode] for mode in modes]\n U_expand = np.eye(nmodes, dtype=np.complex128)\n U_expand[np.ix_(modes, modes)] = U\n T = U_expand @ T\n elif name == \"PassiveChannel\":\n T0 = params[0]\n if T0.shape == (1, 1):\n T = _apply_one_mode_gate(T0[0, 0], T, dict_indices[modes[0]])\n elif T0.shape == (2, 2):\n T = _apply_two_mode_gate(T0, T, dict_indices[modes[0]], dict_indices[modes[1]])\n else:\n modes = [dict_indices[mode] for mode in modes]\n T0_expand = np.eye(nmodes, dtype=np.complex128)\n T0_expand[np.ix_(modes, modes)] = T0\n T = T0_expand @ T\n elif name == \"BSgate\":\n G = _beam_splitter_passive(params[0], params[1])\n T = _apply_two_mode_gate(G, T, dict_indices[modes[0]], dict_indices[modes[1]])\n elif name == \"MZgate\":\n v = np.exp(1j * params[0])\n u = np.exp(1j * params[1])\n U = 0.5 * np.array([[u * (v - 1), 1j * (1 + v)], [1j * u * (1 + v), 1 - v]])\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\n elif name == \"sMZgate\":\n exp_sigma = np.exp(1j * (params[0] + params[1]) / 2)\n delta = (params[0] - params[1]) / 2\n U = exp_sigma * np.array(\n [[np.sin(delta), np.cos(delta)], [np.cos(delta), -np.sin(delta)]]\n )\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\n\n ord_reg = [r for r in list(registers) if r.ind in used_modes]\n ord_reg = sorted(list(ord_reg), key=lambda x: x.ind)\n\n return [Command(ops.PassiveChannel(T), ord_reg)]","def gate_mfcc(recurrent_net, sample_input):\n length = sample_input.shape[1]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\n select = sigmoid(select)\n return np.sum(select * score) / np.sum(select)","def build_glyCB(self, gCBd: Dihedron): # -> None:\n ...","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def _AddCompound(self, kegg_id, how_many):\n i = self._FindCompoundIndex(kegg_id)\n if i is not None:\n self.reactants[i].coeff += how_many\n else:\n self.reactants += [CompoundWithCoeff.FromId(how_many, kegg_id)]\n \n # clear the cache since the reaction has changed\n self._catalyzing_enzymes = None","def test_has_gate(self):\n sched = Schedule()\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), (0,), sched)\n inst_map.add(CXGate(), [0, 1], sched)\n\n self.assertTrue(inst_map.has(U1Gate(0), [0]))\n self.assertTrue(inst_map.has(CXGate(), (0, 1)))\n with self.assertRaises(PulseError):\n inst_map.assert_has(\"dne\", [0])\n with self.assertRaises(PulseError):\n inst_map.assert_has(CXGate(), 100)","def addFanOut(self,gate):\n assert type(gate)==Gate\n self.fanOut.append(gate)","def __init__(self, T, i, do_not_contract=False):\n self.ind = i\n # Contraction\n if not do_not_contract:\n rten = T.T\n itype = []\n icopy = []\n i = list(i)\n inum = 0\n while True:\n curind = i[inum]\n try:\n cind = i.index(-curind, inum + 1)\n rten = np.array(np.sum(np.diagonal(rten, axis1=inum, axis2=cind), axis=-1))\n i.remove(curind)\n i.remove(-curind)\n except ValueError:\n itype.append(curind.contrv)\n icopy.append(curind)\n inum += 1\n finally:\n if inum >= len(i):\n break\n self.ind = icopy\n self.tensor = Tensor(ind=tuple(itype), arr=rten.copy())\n else:\n self.tensor = T","def comp_add_ao(self):\n scene = self.set_as_active()\n scene.use_nodes = True\n tree = scene.node_tree\n tree.nodes.clear()\n\n # creating the nodes\n node_rlayer = tree.nodes.new('CompositorNodeRLayers')\n node_rlayer.location = -300, 100\n node_rlayer.scene = scene\n node_rlayer.layer = w_var.rlname\n\n node_mixcolor = tree.nodes.new('CompositorNodeMixRGB')\n node_mixcolor.location = 0, 50\n node_mixcolor.blend_type = 'MULTIPLY'\n node_mixcolor.inputs[0].default_value = 0.730\n\n node_comp = tree.nodes.new('CompositorNodeComposite')\n node_comp.location = 300, 130\n\n node_viewer = tree.nodes.new('CompositorNodeViewer')\n node_viewer.location = 300, -100\n\n # connecting the nodes\n links = tree.links\n links.new(node_rlayer.outputs[0], node_mixcolor.inputs[1])\n links.new(node_rlayer.outputs[10], node_mixcolor.inputs[2])\n links.new(node_mixcolor.outputs[0], node_comp.inputs[0])\n links.new(node_mixcolor.outputs[0], node_viewer.inputs[0])\n\n for node in tree.nodes:\n node.select = False","def add_fe_tt_advised(self, flow_dict):\n ofproto = self.datapath.ofproto\n parser = self.datapath.ofproto_parser\n #*** Check it's TCP:\n if flow_dict['proto'] != 'tcp':\n self.logger.error(\"Unsupported proto=%s\", flow_dict['proto'])\n return 0\n\n #*** Convert IP addresses strings to integers:\n ipv4_src = _ipv4_t2i(str(flow_dict['ip_A']))\n ipv4_dst = _ipv4_t2i(str(flow_dict['ip_B']))\n\n #*** Build match:\n match = parser.OFPMatch(eth_type=0x0800,\n ipv4_src=ipv4_src,\n ipv4_dst=ipv4_dst,\n ip_proto=6,\n tcp_src=flow_dict['tp_A'],\n tcp_dst=flow_dict['tp_B']\n )\n\n #*** Set QoS actions (if any):\n queue = 0\n self.logger.debug(\"flow_dict=%s\", flow_dict)\n\n if flow_dict['actions'] and 'qos_treatment' in flow_dict:\n qos = flow_dict['qos_treatment']\n self.logger.debug(\"qos_treatment=%s\", qos)\n queue = self._nmeta.main_policy.qos_treatment.\\\n get_policy_qos_treatment_value(qos)\n self.logger.debug(\"queue=%s\", queue)\n if queue:\n actions = [parser.OFPActionSetQueue(queue)]\n else:\n actions = []\n\n inst = [parser.OFPInstructionActions(\n ofproto.OFPIT_APPLY_ACTIONS, actions),\n parser.OFPInstructionGotoTable(self.ft_tt + 1)]\n priority = 1\n mod = parser.OFPFlowMod(datapath=self.datapath, table_id=self.ft_tt,\n priority=priority,\n idle_timeout=self.fe_idle_timeout_qos,\n match=match, instructions=inst)\n self.logger.debug(\"Installing dynamic treatment forward FE dpid=%s\",\n self.dpid)\n self.datapath.send_msg(mod)\n #*** Build counter match (reversed flow):\n match = parser.OFPMatch(eth_type=0x0800,\n ipv4_src=ipv4_dst,\n ipv4_dst=ipv4_src,\n ip_proto=6,\n tcp_src=flow_dict['tp_B'],\n tcp_dst=flow_dict['tp_A']\n )\n mod = parser.OFPFlowMod(datapath=self.datapath, table_id=self.ft_tt,\n priority=priority,\n idle_timeout=self.fe_idle_timeout_qos,\n match=match, instructions=inst)\n self.logger.debug(\"Installing dynamic treatment reverse FE dpid=%s\",\n self.dpid)\n self.datapath.send_msg(mod)","def __iadd__(self, term):\n self.add(term)\n return self","def coadd(self, step_index):\n if self.drip_config is not None:\n if ('boresight' in self.drip_cal_config\n and 'SLIT' in self.drip_cal_config['boresight']):\n self.current[step_index].set_value('skip_coadd', True)","def _compute_carry_and_output(self, x, h_tm1, c_tm1):\n x_i, x_f, x_c, x_o = x\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\n i = self.recurrent_activation(\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\n f = self.recurrent_activation(x_f + K.dot(\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\n o = self.recurrent_activation(\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\n return c, o","def __add__(self, other):\n if isinstance(other, Trit):\n value = (other,)\n else:\n value = tuple(other)\n return Trits(self.trits + value)","def add(num1, num2, Cin):\n Cin=0\n l2=[]\n final=\"\"\n\n \"\"\"Using for loop for starting addition from the last indexed number\"\"\"\n for i in range(len(num1)-1,-1,-1):\n bit1=num1[i]#storing each indexed() value of num1 in bit1\n bit2=num2[i]#storing each indexed() value of num2 in bit2\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\n Cin=Cout#declaring cout as cin for next bit addition\n l2.append(SUM)#adding SUM to l2\n l3=l2[::-1]##reversing the value of l2\n final+=str(l2[-1])#converting the list value to string\n final1=final[::-1]#reversing string value\n return final1 #returning the binary addition as string","def circuitSat(C):","def add_node(self, new_node: 'GraphNode'):\n self.operator.add_node(new_node)","def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self","def __init__(self, name, gate):\n self.name = name\n self.gate = gate\n self.value = None","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def __init__(self,\n sub_gate: raw_types.Gate,\n control_qubits: Sequence[Optional[raw_types.Qid]] = None,\n num_controls: int = None) -> None:\n if num_controls is None:\n num_controls = 1 if control_qubits is None else len(control_qubits)\n if control_qubits is None:\n control_qubits = ()\n if num_controls < len(control_qubits):\n raise ValueError('More specified control qubits than num_controls')\n\n # Leave unspecified controls as Nones.\n self.control_qubits = ((None,) * (num_controls - len(control_qubits)) +\n tuple(control_qubits)) # type: ignore\n\n # Flatten nested ControlledGates.\n if isinstance(sub_gate, ControlledGate):\n self.sub_gate = sub_gate.sub_gate # type: ignore\n self.control_qubits += sub_gate.control_qubits\n else:\n self.sub_gate = sub_gate","def tls_control_system():\n eps1 = lambda t, args: 0.5\n eps2 = lambda t, args: 1\n H1 = [0.5 * sigmaz(), [sigmap(), eps1], [sigmam(), eps1]]\n H2 = [0.5 * sigmaz(), [sigmaz(), eps2]]\n c_ops = [0.1 * sigmap()]\n objectives = [\n krotov.Objective(\n initial_state=ket('0'), target=ket('1'), H=H1, c_ops=c_ops\n ),\n krotov.Objective(\n initial_state=ket('0'), target=ket('1'), H=H2, c_ops=c_ops\n ),\n ]\n controls = [eps1, eps2]\n controls_mapping = krotov.conversions.extract_controls_mapping(\n objectives, controls\n )\n return objectives, controls, controls_mapping","def _push_node_back(self, dag: DAGCircuit, node: DAGOpNode):\n node_start_time = self.property_set[\"node_start_time\"]\n conditional_latency = self.property_set.get(\"conditional_latency\", 0)\n clbit_write_latency = self.property_set.get(\"clbit_write_latency\", 0)\n\n if isinstance(node.op, Gate):\n alignment = self.pulse_align\n elif isinstance(node.op, Measure):\n alignment = self.acquire_align\n elif isinstance(node.op, Delay) or getattr(node.op, \"_directive\", False):\n # Directive or delay. These can start at arbitrary time.\n alignment = None\n else:\n raise TranspilerError(f\"Unknown operation type for {repr(node)}.\")\n\n this_t0 = node_start_time[node]\n\n if alignment is not None:\n misalignment = node_start_time[node] % alignment\n if misalignment != 0:\n shift = max(0, alignment - misalignment)\n else:\n shift = 0\n this_t0 += shift\n node_start_time[node] = this_t0\n\n # Compute shifted t1 of this node separately for qreg and creg\n new_t1q = this_t0 + node.op.duration\n this_qubits = set(node.qargs)\n if isinstance(node.op, Measure):\n # creg access ends at the end of instruction\n new_t1c = new_t1q\n this_clbits = set(node.cargs)\n else:\n if node.op.condition_bits:\n # conditional access ends at the beginning of node start time\n new_t1c = this_t0\n this_clbits = set(node.op.condition_bits)\n else:\n new_t1c = None\n this_clbits = set()\n\n # Check immediate successors for overlap\n for next_node in self._get_next_gate(dag, node):\n # Compute next node start time separately for qreg and creg\n next_t0q = node_start_time[next_node]\n next_qubits = set(next_node.qargs)\n if isinstance(next_node.op, Measure):\n # creg access starts after write latency\n next_t0c = next_t0q + clbit_write_latency\n next_clbits = set(next_node.cargs)\n else:\n if next_node.op.condition_bits:\n # conditional access starts before node start time\n next_t0c = next_t0q - conditional_latency\n next_clbits = set(next_node.op.condition_bits)\n else:\n next_t0c = None\n next_clbits = set()\n # Compute overlap if there is qubits overlap\n if any(this_qubits & next_qubits):\n qreg_overlap = new_t1q - next_t0q\n else:\n qreg_overlap = 0\n # Compute overlap if there is clbits overlap\n if any(this_clbits & next_clbits):\n creg_overlap = new_t1c - next_t0c\n else:\n creg_overlap = 0\n\n # Shift next node if there is finite overlap in either in qubits or clbits\n overlap = max(qreg_overlap, creg_overlap)\n node_start_time[next_node] = node_start_time[next_node] + overlap"],"string":"[\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def __init__(self, input, output) :\\n Gate.__init__(self, [input], output)\",\n \"def add_junction(ccTremb):\\n pass\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def _process_gate(self, node, opaque=False):\\n self.gates[node.name] = {}\\n de_gate = self.gates[node.name]\\n de_gate[\\\"opaque\\\"] = opaque\\n de_gate[\\\"n_args\\\"] = node.n_args()\\n de_gate[\\\"n_bits\\\"] = node.n_bits()\\n if node.n_args() > 0:\\n de_gate[\\\"args\\\"] = [element.name for element in node.arguments.children]\\n else:\\n de_gate[\\\"args\\\"] = []\\n de_gate[\\\"bits\\\"] = [c.name for c in node.bitlist.children]\\n if opaque:\\n de_gate[\\\"body\\\"] = None\\n else:\\n de_gate[\\\"body\\\"] = node.body\\n self.backend.define_gate(node.name, copy.deepcopy(de_gate))\",\n \"def __init__(self, input0, input1, output) :\\n Gate.__init__(self, [input0,input1], output)\",\n \"def _template_circuit(self, amp_param) -> QuantumCircuit:\\n gate = Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param])\\n\\n circuit = QuantumCircuit(1)\\n circuit.append(gate, (0,))\\n circuit.measure_active()\\n\\n return circuit\",\n \"def __add__(self, tc): \\n tc = TwosComplement(tc)\\n bits = self.len if self.len > tc.len else tc.len \\n result = self.int + tc.int\\n return TwosComplement(result, bits)\",\n \"def add_control(operation, num_ctrl_qubits, label):\\n if isinstance(operation, UnitaryGate):\\n # attempt decomposition\\n operation._define()\\n if _control_definition_known(operation, num_ctrl_qubits):\\n return _control_predefined(operation, num_ctrl_qubits)\\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\\n if q_args is None and c_args is None:\\n raise GateError(\\\"Gate needs at least one quantum argument or classical argument\\\")\\n if isinstance(gate, CompositeGate):\\n if mapping is None:\\n raise GateError(\\\"Must provide arguments mapping for composite gate inside a composite gate.\\\")\\n else:\\n inv_mappimg = dict()\\n for key, value in mapping.items():\\n inv_mappimg[value] = key\\n if gate is self:\\n gates = gate.copy.gates\\n else:\\n gates = gate.gates\\n for g in gates:\\n new_q_args = None\\n new_c_args = None\\n if g[1] is not None:\\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\\n if g[2] is not None:\\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\\n self.add_gate(gate=g[0], q_args=new_q_args,\\n c_args=new_c_args, params=g[3])\\n else:\\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\\n raise GateError(\\\"Gate must be either a CompositeGate or a string from: \\\"\\n \\\"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\\\")\\n if q_args is not None:\\n for q_arg in q_args:\\n if q_arg not in self.q_args:\\n self.add_q_arg(q_arg)\\n if c_args is not None:\\n for c_arg in c_args:\\n if c_arg not in self.c_args:\\n self.add_c_arg(c_arg)\\n if params is not None:\\n for param in params:\\n if param not in self.params:\\n self.add_param(param)\\n self._gates.append((gate, q_args, c_args, params))\",\n \"def _control_predefined(operation, num_ctrl_qubits):\\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\\n if num_ctrl_qubits == 1:\\n import qiskit.extensions.standard.cx\\n cgate = qiskit.extensions.standard.cx.CnotGate()\\n else:\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n elif operation.name == 'y':\\n import qiskit.extensions.standard.cy\\n cgate = qiskit.extensions.standard.cy.CyGate()\\n elif operation.name == 'z':\\n import qiskit.extensions.standard.cz\\n cgate = qiskit.extensions.standard.cz.CzGate()\\n elif operation.name == 'h':\\n import qiskit.extensions.standard.ch\\n cgate = qiskit.extensions.standard.ch.CHGate()\\n elif operation.name in {'rx', 'ry', 'rz'}:\\n if operation.name == 'rx':\\n import qiskit.extensions.standard.crx\\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\\n elif operation.name == 'ry':\\n import qiskit.extensions.standard.cry\\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\\n else: # operation.name == 'rz'\\n import qiskit.extensions.standard.crz\\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\\n if num_ctrl_qubits == 1:\\n return cgate\\n else:\\n # only predefined for one control qubit\\n return cgate.control(num_ctrl_qubits - 1)\\n elif operation.name == 'swap':\\n import qiskit.extensions.standard.cswap\\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\\n elif operation.name == 'u1':\\n import qiskit.extensions.standard.cu1\\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\\n elif operation.name == 'u3':\\n import qiskit.extensions.standard.cu3\\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\\n elif operation.name == 'cx':\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n else:\\n raise QiskitError('No standard controlled gate for \\\"{}\\\"'.format(\\n operation.name))\\n return cgate\",\n \"def append_user_gate(self, user_gate):\\n self.translation['g_sect'].append(user_gate)\",\n \"def add(self, ct):\\n self[ct._id] = ct\",\n \"def add_inputt(self, name='T', control=False):\\n inpt = InputT(name=name)\\n self.nodes[name] = inpt\\n self.rc.add_node(inpt)\\n if control: # control input\\n if name in self.inp.keys():\\n raise Exception('Input temperature already defined')\\n self.inp[name] = inpt\\n else: # disturbance\\n if name in self.dist.keys():\\n raise Exception('Input temperature already defined')\\n self.dist[name] = inpt\",\n \"def __iadd__(self, tensor):\\n return self.add_(tensor)\",\n \"def _add_entanglement_gate(self, gate_method, qubit_1, qubit_2):\\r\\n sig = signature(gate_method)\\r\\n\\r\\n # parametrized gate like a controlled single qubit rotation\\r\\n if 'theta' in sig.parameters:\\r\\n try:\\r\\n gate_method(self.circuit, self.parameters[next(self.indices)], qubit_1, qubit_2)\\r\\n except KeyError:\\r\\n raise ValueError(f'Unsupported two qubit rotation gate')\\r\\n\\r\\n # non-parametrized gate like CNOT\\r\\n else:\\r\\n try:\\r\\n gate_method(self.circuit, qubit_1, qubit_2)\\r\\n except KeyError:\\r\\n raise ValueError(f'Unsupported unparametrized two qubit gate')\",\n \"def addTN(self, num=1):\\n self.tn += num\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def add_connector(self):\\n \\n no = len(self.connectors)\\n state = {}\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % no\\n \\n if len(self.connectors)>0:\\n state = self.connectors[-1].get_state()\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % (no)\\n else:\\n if self.mount == self.MOUNT_THT:\\n state[\\\"p_shape\\\"] = Con.SHAPE_HOLE\\n elif self.mount == self.MOUNT_SMD:\\n state[\\\"p_shape\\\"] = Con.SHAPE_PAD\\n \\n c = Con(no)\\n c.set_state(state) \\n \\n self.sch_layers[\\\"pins\\\"].add(c.s_svg)\\n self.pcb_layers[\\\"copper1\\\"].add(c.p_svg)\\n self.connectors.append(c)\",\n \"def add_road(ccTremb):\\n pass\",\n \"def __add__(self, tensor):\\n return self.add(tensor)\",\n \"def _template_circuit(self, amp_param) -> QuantumCircuit:\\n circuit = QuantumCircuit(1)\\n circuit.x(0)\\n circuit.append(Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param]), (0,))\\n circuit.measure_active()\\n\\n return circuit\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def connect(self, gate) :\\n self.notifyList.append(gate)\",\n \"def actual_causation():\\n # fmt: off\\n tpm = np.array([\\n [1, 0, 0, 0],\\n [0, 1, 0, 0],\\n [0, 1, 0, 0],\\n [0, 0, 0, 1],\\n ])\\n cm = np.array([\\n [1, 1],\\n [1, 1],\\n ])\\n # fmt: on\\n return Network(tpm, cm, node_labels=('OR', 'AND'))\",\n \"def __init__(self, gate: Gate, tag: Any) -> None:\\n\\n if not isinstance(gate, Gate):\\n raise TypeError('Expected gate object, got %s' % type(gate))\\n\\n self.gate = gate\\n self.tag = tag\\n self.name = 'Tagged(%s:%s)' % (gate.get_name(), tag)\\n self.num_params = gate.get_num_params()\\n self.size = gate.get_size()\\n self.radixes = gate.get_radixes()\\n\\n # If input is a constant gate, we can cache the unitary.\\n if self.num_params == 0:\\n self.utry = gate.get_unitary()\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def add_new_control_point(moment_data, new_control_point, new_frame_id,\\n runtime_bucket, is_vehicle=False):\\n change_type = \\\"ped_controls\\\"\\n if is_vehicle:\\n change_type = \\\"vehicle_controls\\\"\\n prev_controls = \\\\\\n moment_data[runtime_bucket[\\\"cur_moment_idx\\\"]][change_type]\\n new_frame_id = \\\"%s\\\" % new_frame_id # json's fault\\n #if prev_controls.has_key(new_frame_id):\\n if new_frame_id in prev_controls:\\n # add to the existing frame\\n moment_data[runtime_bucket[\\\"cur_moment_idx\\\"]][change_type][\\n new_frame_id].append(new_control_point)\\n else:\\n # a new frame\\n moment_data[runtime_bucket[\\\"cur_moment_idx\\\"]][change_type][\\n new_frame_id] = [new_control_point]\\n\\n # get the new traj data\\n person_data, vehicle_data = get_trajs(\\n moment_data, runtime_bucket[\\\"cur_moment_idx\\\"])\\n runtime_bucket[\\\"person_data\\\"] = person_data\\n runtime_bucket[\\\"vehicle_data\\\"] = vehicle_data\",\n \"def addOp(self, op):\\n self.operations << op\",\n \"def add_state(self, name='Ti', c=2000):\\n assert isinstance(name, str), 'name must be a string type'\\n if name in self.sta.keys():\\n raise Exception('State already defined')\\n state = State(c=c, name=name)\\n self.sta[name] = state\\n self.nodes[name] = state\\n self.rc.add_node(state)\",\n \"def gate_lfcc(recurrent_net, sample_input):\\n length = sample_input.shape[0]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[i, :])\\n select = sigmoid(select)\\n score = sigmoid(score)\\n return np.sum(select * score) / np.sum(select)\",\n \"def iadd(state: State) -> State:\\n cell = state.array[state.index] or 0\\n return state._replace(acc=state.acc + cell)\",\n \"def cy(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CY(), target=[control, target])\",\n \"def addTP(self, num=1):\\n self.tp += num\",\n \"def addToTfLink(G,i,j,siso):\\n m,n,r = np.shape(G.num)\\n dt = G.dt\\n\\n #Create a new transfer fuction Add, that is zero except the i,jth entry \\n Addnum = []\\n Addden = []\\n rowN = [np.array([0.])]*n\\n rowD = [np.array([1.])]*n\\n\\n for k in range(m):\\n Addnum.append(list(rowN))\\n Addden.append(list(rowD))\\n\\n #Make the i,jth entry of Add equal to siso\\n Addnum[i][j] = siso.num[0][0]\\n Addden[i][j] = siso.den[0][0]\\n Add = ctrl.tf(Addnum,Addden,dt)\\n\\n #Use the control library + function to add the new transfer function to G\\n Gplus = G + Add\\n return Gplus\",\n \"def addToTfLink(G,i,j,siso):\\n m,n,r = np.shape(G.num)\\n dt = G.dt\\n\\n #Create a new transfer fuction Add, that is zero except the i,jth entry \\n Addnum = []\\n Addden = []\\n rowN = [np.array([0.])]*n\\n rowD = [np.array([1.])]*n\\n\\n for k in range(m):\\n Addnum.append(list(rowN))\\n Addden.append(list(rowD))\\n\\n #Make the i,jth entry of Add equal to siso\\n Addnum[i][j] = siso.num[0][0]\\n Addden[i][j] = siso.den[0][0]\\n Add = ctrl.tf(Addnum,Addden,dt)\\n\\n #Use the control library + function to add the new transfer function to G\\n Gplus = G + Add\\n return Gplus\",\n \"def user_gate_definition(self, filenum, linenum, txt):\\n txt = txt.strip()\\n gate_decl = QTRegEx.GATE_DECL.match(txt)\\n gate_name = gate_decl.group(1)\\n possible_gate_params = gate_name.split('(')\\n gate_param_list = None\\n if len(possible_gate_params) > 1:\\n gate_param_list = possible_gate_params[1].strip(') ').split(',')\\n gate_regs = gate_decl.group(2).strip(\\\"{}\\\") # watch out for no space before '{' !!\\n gate_reg_list = gate_regs.split(',')\\n gate_ops = QTRegEx.GATE_OPS.match(txt)\\n gate_ops_raw_list = QTRegEx.GATE_OPS_LIST.findall(gate_ops.group(1))\\n gate_ops_list = []\\n for op_raw in gate_ops_raw_list:\\n op_raw = op_raw.strip()\\n op = QTRegEx.GATE_OP.match(op_raw).group(1)\\n op_params = QTRegEx.GATE_OP_PARAMS.match(op_raw)\\n if op_params:\\n op_param_list = op_params.group(1).split(',')\\n else:\\n op_param_list = None\\n op_regs = QTRegEx.GATE_OP_REGS.match(op_raw)\\n if op_regs:\\n op_reg_list = op_regs.group(1).split(',')\\n else:\\n op_reg_list = None\\n gate_ops_list.append({'op': op,\\n 'op_param_list': op_param_list,\\n 'op_reg_list': op_reg_list})\\n gate = {'source': txt if self.save_gate_source else None,\\n 'filenum': filenum,\\n 'linenum': linenum, 'gate_name': gate_name,\\n 'gate_param_list': gate_param_list,\\n 'gate_ops_raw_list': gate_ops_raw_list,\\n 'gate_ops_list': gate_ops_list,\\n 'gate_reg_list': gate_reg_list}\\n\\n self.append_user_gate(gate)\",\n \"def get_gate(gate, params, num_ctrl_qubits=None):\\n if gate[0] == \\\"c\\\":\\n return get_gate(gate[1:], params, num_ctrl_qubits).ctrl()\\n if gate == \\\"toffoli\\\":\\n return get_gate(\\\"ccx\\\", params, num_ctrl_qubits)\\n if gate[0:2] == \\\"mc\\\":\\n name = gate[2:]\\n for _ in range(num_ctrl_qubits):\\n name = \\\"c\\\" + name\\n return get_gate(name, params, num_ctrl_qubits)\\n if len(params) == 0:\\n return GATE_DIC[gate]\\n\\n return GATE_DIC[gate](*params)\",\n \"def gate_operation(self, operation, qubit_expr, params=None):\\n operation = QuantumCircuit._parse_gate_operation(operation)\\n if params is not None:\\n operation = operation(**params) \\n qubit = self.qr.get(qubit_expr) \\n return operation(qubit)\",\n \"def AddOperation(self, op):\\n self._operations.append(op)\",\n \"def build_gate_1(gate, tags=None):\\n\\n def apply_constant_single_qubit_gate(psi, i, **gate_opts):\\n mtags = _merge_tags(tags, gate_opts)\\n psi.gate_(gate, int(i), tags=mtags, **gate_opts)\\n\\n return apply_constant_single_qubit_gate\",\n \"def gru_cell(self, Xt, h_t_minus_1):\\n # 1.update gate: decides how much past information is kept and how much new information is added.\\n z_t = tf.nn.sigmoid(tf.matmul(Xt, self.W_z) + tf.matmul(h_t_minus_1,self.U_z) + self.b_z) # z_t:[batch_size,self.hidden_size]\\n # 2.reset gate: controls how much the past state contributes to the candidate state.\\n r_t = tf.nn.sigmoid(tf.matmul(Xt, self.W_r) + tf.matmul(h_t_minus_1,self.U_r) + self.b_r) # r_t:[batch_size,self.hidden_size]\\n # candiate state h_t~\\n h_t_candiate = tf.nn.tanh(tf.matmul(Xt, self.W_h) +r_t * (tf.matmul(h_t_minus_1, self.U_h)) + self.b_h) # h_t_candiate:[batch_size,self.hidden_size]\\n # new state: a linear combine of pervious hidden state and the current new state h_t~\\n h_t = (1 - z_t) * h_t_minus_1 + z_t * h_t_candiate # h_t:[batch_size*num_sentences,hidden_size]\\n return h_t\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def addTribuf(self, tribuf_id, ip, ctrl, op):\\n # Eliminating basic outlier conditions\\n if tribuf_id in self.dGrph:\\n print('tribuf_id already exists. No node added.')\\n return\\n \\n self.dGrph[tribuf_id] = [(ip, ctrl), [ctrl], [op, None]]\",\n \"def test_append_dangling_gate(self, circuit):\\n match = (\\n r\\\"Number of wire IDs \\\\(2\\\\) must match the number of wires connected to the gate \\\\(1\\\\).\\\"\\n )\\n gate = jet.GateFactory.create(\\\"H\\\")\\n with pytest.raises(ValueError, match=match):\\n circuit.append_gate(gate, wire_ids=[0, 1])\",\n \"def get_CC_operators():\\n i = symbols('i', below_fermi=True, cls=Dummy)\\n a = symbols('a', above_fermi=True, cls=Dummy)\\n t_ai = AntiSymmetricTensor('t', (a,), (i,))\\n ai = NO(Fd(a)*F(i))\\n i, j = symbols('i,j', below_fermi=True, cls=Dummy)\\n a, b = symbols('a,b', above_fermi=True, cls=Dummy)\\n t_abij = AntiSymmetricTensor('t', (a, b), (i, j))\\n abji = NO(Fd(a)*Fd(b)*F(j)*F(i))\\n\\n T1 = t_ai*ai\\n T2 = Rational(1, 4)*t_abij*abji\\n return (T1, T2)\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def test_addTcfModelFile(self):\\n print ('Testing add tcf ModelFile...')\\n\\n tuflow = copy.deepcopy(self.tuflow)\\n loader = TuflowLoader()\\n tcf = tuflow.control_files['TCF']\\n geom = tcf.contains(command='Geometry Control')[0]\\n \\n line = \\\"Geometry Control File == ..\\\\\\\\model\\\\\\\\test_tgc2.tgc\\\"\\n tgc_part = factory.TuflowFactory.getTuflowPart(line, tcf.mainfile)[0]\\n tgc_control = loader.loadControlFile(tgc_part)\\n tcf.addControlFile(tgc_part, tgc_control, after=geom)\\n \\n assert(tgc_part in tuflow.control_files['TGC'].control_files)\\n \\n test_part = tuflow.control_files['TGC'].contains(filename='shiptest_tgc2_v1_DTM_2m')\\n assert(len(test_part) == 1)\\n \\n index = tcf.parts.index(tgc_part)\\n assert(index == tcf.parts.index(geom) + 1)\\n del tuflow\\n\\n print ('pass')\",\n \"def apply_gate(self, gate_id, *gate_args, gate_round=None, **gate_opts):\\n\\n # unique tag\\n tags = {f'GATE_{len(self.gates)}'}\\n\\n # parse which 'round' of gates\\n if (gate_round is not None):\\n tags.add(f'ROUND_{gate_round}')\\n elif isinstance(gate_id, numbers.Integral) or gate_id.isdigit():\\n # gate round given as first entry of qasm line\\n tags.add(f'ROUND_{gate_id}')\\n gate_id, gate_args = gate_args[0], gate_args[1:]\\n\\n gate_id = gate_id.upper()\\n gate_fn = GATE_FUNCTIONS[gate_id]\\n\\n # overide any default gate opts\\n opts = {**self.gate_opts, **gate_opts}\\n\\n # handle parametrize kwarg for non-parametrizable gates\\n if ('parametrize' in opts) and (gate_id not in ALL_PARAM_GATES):\\n parametrize = opts.pop('parametrize')\\n if parametrize:\\n msg = f\\\"The gate '{gate_id}' cannot be parametrized.\\\"\\n raise ValueError(msg)\\n # can pop+ignore if False\\n\\n # gate the TN!\\n gate_fn(self._psi, *gate_args, tags=tags, **opts)\\n\\n # keep track of the gates applied\\n self.gates.append((gate_id, *gate_args))\",\n \"def add_trait(self, t): \\n self.trait_index_to_change = t\\n self.player.request_payment(self)\\n # toggle add button to say delete or something\",\n \"def credit(self, value):\\n self._negative_value_raises_an_error(value)\\n self.operations.insert(value);\",\n \"def triplicateBlck(self, blck_id):\\n # Eliminating basic outlier conditions\\n if blck_id not in self.dGrph:\\n print('blck_id: ', blck_id, ' does not exist. Triplication aborted.')\\n return\\n\\n # identifying the type of block and triplicating\\n test = len(self.dGrph[blck_id][1])\\n if test == 3: # ari block\\n ip = self.dGrph[blck_id][0]\\n config = self.dGrph[blck_id][2]\\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\\n new_ops = []\\n for i in range(3):\\n temp_op = []\\n for original_op in self.dGrph[blck_id][1]:\\n temp_op.append([original_op[0]+'_trip728'+str(i), None])\\n new_ops.append(temp_op)\\n\\n self.dGrph[new_ids[0]] = [ip, new_ops[0], config]\\n self.dGrph[new_ids[1]] = [ip, new_ops[1], config]\\n self.dGrph[new_ids[2]] = [ip, new_ops[2], config]\\n\\n # for first output\\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0][0], new_ops[1][0][0]], new_ids[0]+'_and0_o')\\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0][0], new_ops[2][0][0]], new_ids[1]+'_and0_o')\\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0][0], new_ops[2][0][0]], new_ids[2]+'_and0_o')\\n\\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0][0])\\n\\n # for second output\\n self.__addGate(new_ids[0]+'_and1', 'A', [new_ops[0][1][0], new_ops[1][1][0]], new_ids[0]+'_and1_o')\\n self.__addGate(new_ids[1]+'_and1', 'A', [new_ops[0][1][0], new_ops[2][1][0]], new_ids[1]+'_and1_o')\\n self.__addGate(new_ids[2]+'_and1', 'A', [new_ops[1][1][0], new_ops[2][1][0]], new_ids[2]+'_and1_o')\\n\\n self.__addGate(new_ids[0]+'_or1', 'O', [new_ids[0]+'_and1_o', new_ids[1]+'_and1_o', new_ids[2]+'_and1_o'], self.dGrph[blck_id][1][1][0])\\n\\n # for third output\\n self.__addGate(new_ids[0]+'_and2', 'A', [new_ops[0][2][0], new_ops[1][2][0]], new_ids[0]+'_and2_o')\\n self.__addGate(new_ids[1]+'_and2', 'A', [new_ops[0][2][0], new_ops[2][2][0]], new_ids[1]+'_and2_o')\\n self.__addGate(new_ids[2]+'_and2', 'A', [new_ops[1][2][0], new_ops[2][2][0]], new_ids[2]+'_and2_o')\\n\\n self.__addGate(new_ids[0]+'_or2', 'O', [new_ids[0]+'_and2_o', new_ids[1]+'_and2_o', new_ids[2]+'_and2_o'], self.dGrph[blck_id][1][2][0])\\n\\n del self.dGrph[blck_id]\\n\\n elif test == 2: # cfg block\\n ip = self.dGrph[blck_id][0]\\n config = self.dGrph[blck_id][2]\\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\\n new_ops = [[self.dGrph[blck_id][2][0] + '_trip7280', None], [self.dGrph[blck_id][2][0] + '_trip7281', None], [self.dGrph[blck_id][2][0] + '_trip7282', None]]\\n\\n self.dGrph[new_ids[0]] = [ip, new_ops[0], config]\\n self.dGrph[new_ids[1]] = [ip, new_ops[1], config]\\n self.dGrph[new_ids[2]] = [ip, new_ops[2], config]\\n\\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0], new_ops[1][0]], new_ids[0]+'_and0_o')\\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0], new_ops[2][0]], new_ids[1]+'_and0_o')\\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0], new_ops[2][0]], new_ids[2]+'_and0_o')\\n\\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0])\\n\\n del self.dGrph[blck_id]\\n\\n elif test == 1: # tribuf\\n ip = self.dGrph[blck_id][0]\\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\\n new_ops = [[self.dGrph[blck_id][2][0] + '_trip7280', None], [self.dGrph[blck_id][2][0] + '_trip7281', None], [self.dGrph[blck_id][2][0] + '_trip7282', None]]\\n\\n self.dGrph[new_ids[0]] = [ip, [ip[1]], new_ops[0]]\\n self.dGrph[new_ids[1]] = [ip, [ip[1]], new_ops[1]]\\n self.dGrph[new_ids[2]] = [ip, [ip[1]], new_ops[2]]\\n\\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0], new_ops[1][0]], new_ids[0]+'_and0_o')\\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0], new_ops[2][0]], new_ids[1]+'_and0_o')\\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0], new_ops[2][0]], new_ids[2]+'_and0_o')\\n\\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0])\\n\\n del self.dGrph[blck_id]\\n \\n else:\\n print('Unknown error!!!!!!\\\\n')\",\n \"def __call__(self, *qubit_indices: int) -> \\\"GateOperation\\\":\\n return GateOperation(self, qubit_indices)\",\n \"def parameterise_gate(self, gate:Union[cirq.Gate, Callable]): \\n if isinstance(gate, cirq.Gate):\\n if isinstance(gate, (cirq.XXPowGate, cirq.YYPowGate, cirq.ZZPowGate)):\\n param = self.new_param()\\n return gate**param\\n return gate\\n elif isclass(gate) and issubclass(gate, cirq.Gate):\\n parameters = ParameterisedCircuit._get_gate_parameters(gate)\\n n_param = len(parameters)\\n params = self.new_param(size=n_param, as_array=True)\\n kwargs = {parameters[i]:params[i] for i in range(n_param)}\\n return gate(**kwargs) \\n else:\\n n_param = ParameterisedCircuit._get_parameter_count(gate)\\n params = self.new_param(size=n_param)\\n params = tuple(params) if isinstance(params, np.ndarray) else (params,) \\n return gate(*params)\",\n \"def add_state(self, state):\\n if self.rate_variation:\\n if not self.feature_rates:\\n # Set all rates to 1.0 in a big plate\\n plate = ET.SubElement(state, \\\"plate\\\", {\\n \\\"var\\\":\\\"feature\\\",\\n \\\"range\\\":\\\",\\\".join(self.features)})\\n param = ET.SubElement(plate, \\\"parameter\\\", {\\n \\\"id\\\":\\\"featureClockRate:%s:$(feature)\\\" % self.name,\\n \\\"name\\\":\\\"stateNode\\\"})\\n param.text=\\\"1.0\\\"\\n else:\\n # Give each rate a custom value\\n for f in self.features:\\n param = ET.SubElement(state, \\\"parameter\\\", {\\n \\\"id\\\":\\\"featureClockRate:%s:%s\\\" % (self.name, f),\\n \\\"name\\\":\\\"stateNode\\\"})\\n param.text=str(self.feature_rates.get(f,1.0))\\n\\n # Give Gamma shape parameter a finite domain\\n # Must be > 1.0 for the distribution to be bell-shaped,\\n # rather than L-shaped. The domain [1.1,1000] limits feature\\n # rate variation to the realms of vague plausibity\\n parameter = ET.SubElement(state, \\\"parameter\\\", {\\\"id\\\":\\\"featureClockRateGammaShape:%s\\\" % self.name, \\\"lower\\\":\\\"1.1\\\",\\\"upper\\\":\\\"100.0\\\",\\\"name\\\":\\\"stateNode\\\"})\\n parameter.text=\\\"5.0\\\"\\n # Gamma scale parameter's domain is defined *implicilty*\\n # by the fact that the operators maintain shape*scale = 1.0\\n parameter = ET.SubElement(state, \\\"parameter\\\", {\\\"id\\\":\\\"featureClockRateGammaScale:%s\\\" % self.name, \\\"name\\\":\\\"stateNode\\\"})\\n parameter.text=\\\"0.2\\\"\",\n \"def AddTE(self, te):\\n self._totalte += te\",\n \"def addControl(*args):\",\n \"def addControl(*args):\",\n \"def addControl(*args):\",\n \"def addControl(*args):\",\n \"def T(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.T, qubit_expr)\",\n \"def ct(self, ct):\\n\\n self._ct = ct\",\n \"def _add_ctc_loss(pred, seq_len, num_label, loss_type):\\n label = mx.sym.Variable('label')\\n if loss_type == 'warpctc':\\n print(\\\"Using WarpCTC Loss\\\")\\n sm = _add_warp_ctc_loss(pred, seq_len, num_label, label)\\n else:\\n print(\\\"Using MXNet CTC Loss\\\")\\n assert loss_type == 'ctc'\\n sm = _add_mxnet_ctc_loss(pred, seq_len, label)\\n return sm\",\n \"def addFanIn(self,gate):\\n assert type(gate)==Gate\\n if self.gateType == \\\"INPUT\\\":\\n print \\\"Inputs cannot have a fanIn.\\\"\\n return\\n self.fanIn.append(gate)\\n gate.addFanOut(self)\",\n \"def gate(self):\\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)\",\n \"def add():\\n pass\",\n \"def _threshold(self, circuit, register, ctrl_string, measure_flag_qubit=True):\\n # Determine the number of controls\\n ncontrols = (ctrl_string + \\\"1\\\").index(\\\"1\\\")\\n\\n # Edge case in which no operations are added\\n if ncontrols == 0:\\n return\\n\\n # Make sure there is at least one control\\n if ncontrols == len(ctrl_string):\\n raise ValueError(\\\"Argument ctrl_string should have at least one '1'.\\\")\\n\\n # Add the ancilla register of three qubits to the circuit\\n ancilla = QuantumRegister(3, name=\\\"threshold\\\")\\n circuit.add_register(ancilla)\\n\\n # ==============================\\n # Add the gates for thresholding\\n # ==============================\\n\\n # Do the first \\\"anti-controlled\\\" Tofolli\\n for ii in range(ncontrols):\\n circuit.x(register[ii])\\n mct(circuit, register[:ncontrols], ancilla[0], None, mode=\\\"noancilla\\\")\\n for ii in range(ncontrols):\\n circuit.x(register[ii])\\n\\n # Do the second Tofolli\\n mct(circuit, register[:ncontrols], ancilla[1], None, mode=\\\"noancilla\\\")\\n\\n # Do the copy CNOTs in the ancilla register\\n circuit.cx(ancilla[0], ancilla[2])\\n circuit.cx(ancilla[1], ancilla[2])\\n\\n # Uncompute the second Tofolli\\n mct(circuit, register[:ncontrols], ancilla[1], None, mode=\\\"noancilla\\\")\\n\\n # Uncompute the first \\\"anti-controlled\\\" Tofolli\\n for ii in range(ncontrols):\\n circuit.x(register[ii])\\n mct(circuit, register[:ncontrols], ancilla[0], None, mode=\\\"noancilla\\\")\\n for ii in range(ncontrols):\\n circuit.x(register[ii])\\n\\n # Add the \\\"flag qubit\\\" measurement, if desired\\n if measure_flag_qubit:\\n creg = ClassicalRegister(1, name=\\\"flag\\\")\\n circuit.add_register(creg)\\n circuit.measure(ancilla[2], creg[0])\",\n \"def t_dg(self, q0, ctrl=None):\\n self.__add_quantum_gate(kind=PHASE_SHIFT_T_, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def compile(self, seq, registers):\\n\\n # Check which modes are actually being used\\n used_modes = []\\n for operations in seq:\\n modes = [modes_label.ind for modes_label in operations.reg]\\n used_modes.append(modes)\\n\\n used_modes = list(set(item for sublist in used_modes for item in sublist))\\n\\n # dictionary mapping the used modes to consecutive non-negative integers\\n dict_indices = {used_modes[i]: i for i in range(len(used_modes))}\\n nmodes = len(used_modes)\\n\\n # We start with an identity then sequentially update with the gate transformations\\n T = np.identity(nmodes, dtype=np.complex128)\\n\\n # Now we will go through each operation in the sequence `seq` and apply it to T\\n for operations in seq:\\n name = operations.op.__class__.__name__\\n params = par_evaluate(operations.op.p)\\n modes = [modes_label.ind for modes_label in operations.reg]\\n if name == \\\"Rgate\\\":\\n G = np.exp(1j * params[0])\\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\\n elif name == \\\"LossChannel\\\":\\n G = np.sqrt(params[0])\\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\\n elif name == \\\"Interferometer\\\":\\n U = params[0]\\n if U.shape == (1, 1):\\n T = _apply_one_mode_gate(U[0, 0], T, dict_indices[modes[0]])\\n elif U.shape == (2, 2):\\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n else:\\n modes = [dict_indices[mode] for mode in modes]\\n U_expand = np.eye(nmodes, dtype=np.complex128)\\n U_expand[np.ix_(modes, modes)] = U\\n T = U_expand @ T\\n elif name == \\\"PassiveChannel\\\":\\n T0 = params[0]\\n if T0.shape == (1, 1):\\n T = _apply_one_mode_gate(T0[0, 0], T, dict_indices[modes[0]])\\n elif T0.shape == (2, 2):\\n T = _apply_two_mode_gate(T0, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n else:\\n modes = [dict_indices[mode] for mode in modes]\\n T0_expand = np.eye(nmodes, dtype=np.complex128)\\n T0_expand[np.ix_(modes, modes)] = T0\\n T = T0_expand @ T\\n elif name == \\\"BSgate\\\":\\n G = _beam_splitter_passive(params[0], params[1])\\n T = _apply_two_mode_gate(G, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n elif name == \\\"MZgate\\\":\\n v = np.exp(1j * params[0])\\n u = np.exp(1j * params[1])\\n U = 0.5 * np.array([[u * (v - 1), 1j * (1 + v)], [1j * u * (1 + v), 1 - v]])\\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n elif name == \\\"sMZgate\\\":\\n exp_sigma = np.exp(1j * (params[0] + params[1]) / 2)\\n delta = (params[0] - params[1]) / 2\\n U = exp_sigma * np.array(\\n [[np.sin(delta), np.cos(delta)], [np.cos(delta), -np.sin(delta)]]\\n )\\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n\\n ord_reg = [r for r in list(registers) if r.ind in used_modes]\\n ord_reg = sorted(list(ord_reg), key=lambda x: x.ind)\\n\\n return [Command(ops.PassiveChannel(T), ord_reg)]\",\n \"def gate_mfcc(recurrent_net, sample_input):\\n length = sample_input.shape[1]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\\n select = sigmoid(select)\\n return np.sum(select * score) / np.sum(select)\",\n \"def build_glyCB(self, gCBd: Dihedron): # -> None:\\n ...\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def _AddCompound(self, kegg_id, how_many):\\n i = self._FindCompoundIndex(kegg_id)\\n if i is not None:\\n self.reactants[i].coeff += how_many\\n else:\\n self.reactants += [CompoundWithCoeff.FromId(how_many, kegg_id)]\\n \\n # clear the cache since the reaction has changed\\n self._catalyzing_enzymes = None\",\n \"def test_has_gate(self):\\n sched = Schedule()\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), (0,), sched)\\n inst_map.add(CXGate(), [0, 1], sched)\\n\\n self.assertTrue(inst_map.has(U1Gate(0), [0]))\\n self.assertTrue(inst_map.has(CXGate(), (0, 1)))\\n with self.assertRaises(PulseError):\\n inst_map.assert_has(\\\"dne\\\", [0])\\n with self.assertRaises(PulseError):\\n inst_map.assert_has(CXGate(), 100)\",\n \"def addFanOut(self,gate):\\n assert type(gate)==Gate\\n self.fanOut.append(gate)\",\n \"def __init__(self, T, i, do_not_contract=False):\\n self.ind = i\\n # Contraction\\n if not do_not_contract:\\n rten = T.T\\n itype = []\\n icopy = []\\n i = list(i)\\n inum = 0\\n while True:\\n curind = i[inum]\\n try:\\n cind = i.index(-curind, inum + 1)\\n rten = np.array(np.sum(np.diagonal(rten, axis1=inum, axis2=cind), axis=-1))\\n i.remove(curind)\\n i.remove(-curind)\\n except ValueError:\\n itype.append(curind.contrv)\\n icopy.append(curind)\\n inum += 1\\n finally:\\n if inum >= len(i):\\n break\\n self.ind = icopy\\n self.tensor = Tensor(ind=tuple(itype), arr=rten.copy())\\n else:\\n self.tensor = T\",\n \"def comp_add_ao(self):\\n scene = self.set_as_active()\\n scene.use_nodes = True\\n tree = scene.node_tree\\n tree.nodes.clear()\\n\\n # creating the nodes\\n node_rlayer = tree.nodes.new('CompositorNodeRLayers')\\n node_rlayer.location = -300, 100\\n node_rlayer.scene = scene\\n node_rlayer.layer = w_var.rlname\\n\\n node_mixcolor = tree.nodes.new('CompositorNodeMixRGB')\\n node_mixcolor.location = 0, 50\\n node_mixcolor.blend_type = 'MULTIPLY'\\n node_mixcolor.inputs[0].default_value = 0.730\\n\\n node_comp = tree.nodes.new('CompositorNodeComposite')\\n node_comp.location = 300, 130\\n\\n node_viewer = tree.nodes.new('CompositorNodeViewer')\\n node_viewer.location = 300, -100\\n\\n # connecting the nodes\\n links = tree.links\\n links.new(node_rlayer.outputs[0], node_mixcolor.inputs[1])\\n links.new(node_rlayer.outputs[10], node_mixcolor.inputs[2])\\n links.new(node_mixcolor.outputs[0], node_comp.inputs[0])\\n links.new(node_mixcolor.outputs[0], node_viewer.inputs[0])\\n\\n for node in tree.nodes:\\n node.select = False\",\n \"def add_fe_tt_advised(self, flow_dict):\\n ofproto = self.datapath.ofproto\\n parser = self.datapath.ofproto_parser\\n #*** Check it's TCP:\\n if flow_dict['proto'] != 'tcp':\\n self.logger.error(\\\"Unsupported proto=%s\\\", flow_dict['proto'])\\n return 0\\n\\n #*** Convert IP addresses strings to integers:\\n ipv4_src = _ipv4_t2i(str(flow_dict['ip_A']))\\n ipv4_dst = _ipv4_t2i(str(flow_dict['ip_B']))\\n\\n #*** Build match:\\n match = parser.OFPMatch(eth_type=0x0800,\\n ipv4_src=ipv4_src,\\n ipv4_dst=ipv4_dst,\\n ip_proto=6,\\n tcp_src=flow_dict['tp_A'],\\n tcp_dst=flow_dict['tp_B']\\n )\\n\\n #*** Set QoS actions (if any):\\n queue = 0\\n self.logger.debug(\\\"flow_dict=%s\\\", flow_dict)\\n\\n if flow_dict['actions'] and 'qos_treatment' in flow_dict:\\n qos = flow_dict['qos_treatment']\\n self.logger.debug(\\\"qos_treatment=%s\\\", qos)\\n queue = self._nmeta.main_policy.qos_treatment.\\\\\\n get_policy_qos_treatment_value(qos)\\n self.logger.debug(\\\"queue=%s\\\", queue)\\n if queue:\\n actions = [parser.OFPActionSetQueue(queue)]\\n else:\\n actions = []\\n\\n inst = [parser.OFPInstructionActions(\\n ofproto.OFPIT_APPLY_ACTIONS, actions),\\n parser.OFPInstructionGotoTable(self.ft_tt + 1)]\\n priority = 1\\n mod = parser.OFPFlowMod(datapath=self.datapath, table_id=self.ft_tt,\\n priority=priority,\\n idle_timeout=self.fe_idle_timeout_qos,\\n match=match, instructions=inst)\\n self.logger.debug(\\\"Installing dynamic treatment forward FE dpid=%s\\\",\\n self.dpid)\\n self.datapath.send_msg(mod)\\n #*** Build counter match (reversed flow):\\n match = parser.OFPMatch(eth_type=0x0800,\\n ipv4_src=ipv4_dst,\\n ipv4_dst=ipv4_src,\\n ip_proto=6,\\n tcp_src=flow_dict['tp_B'],\\n tcp_dst=flow_dict['tp_A']\\n )\\n mod = parser.OFPFlowMod(datapath=self.datapath, table_id=self.ft_tt,\\n priority=priority,\\n idle_timeout=self.fe_idle_timeout_qos,\\n match=match, instructions=inst)\\n self.logger.debug(\\\"Installing dynamic treatment reverse FE dpid=%s\\\",\\n self.dpid)\\n self.datapath.send_msg(mod)\",\n \"def __iadd__(self, term):\\n self.add(term)\\n return self\",\n \"def coadd(self, step_index):\\n if self.drip_config is not None:\\n if ('boresight' in self.drip_cal_config\\n and 'SLIT' in self.drip_cal_config['boresight']):\\n self.current[step_index].set_value('skip_coadd', True)\",\n \"def _compute_carry_and_output(self, x, h_tm1, c_tm1):\\n x_i, x_f, x_c, x_o = x\\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\\n i = self.recurrent_activation(\\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\\n f = self.recurrent_activation(x_f + K.dot(\\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\\n o = self.recurrent_activation(\\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\\n return c, o\",\n \"def __add__(self, other):\\n if isinstance(other, Trit):\\n value = (other,)\\n else:\\n value = tuple(other)\\n return Trits(self.trits + value)\",\n \"def add(num1, num2, Cin):\\n Cin=0\\n l2=[]\\n final=\\\"\\\"\\n\\n \\\"\\\"\\\"Using for loop for starting addition from the last indexed number\\\"\\\"\\\"\\n for i in range(len(num1)-1,-1,-1):\\n bit1=num1[i]#storing each indexed() value of num1 in bit1\\n bit2=num2[i]#storing each indexed() value of num2 in bit2\\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\\n Cin=Cout#declaring cout as cin for next bit addition\\n l2.append(SUM)#adding SUM to l2\\n l3=l2[::-1]##reversing the value of l2\\n final+=str(l2[-1])#converting the list value to string\\n final1=final[::-1]#reversing string value\\n return final1 #returning the binary addition as string\",\n \"def circuitSat(C):\",\n \"def add_node(self, new_node: 'GraphNode'):\\n self.operator.add_node(new_node)\",\n \"def cs_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def __init__(self, name, gate):\\n self.name = name\\n self.gate = gate\\n self.value = None\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def __init__(self,\\n sub_gate: raw_types.Gate,\\n control_qubits: Sequence[Optional[raw_types.Qid]] = None,\\n num_controls: int = None) -> None:\\n if num_controls is None:\\n num_controls = 1 if control_qubits is None else len(control_qubits)\\n if control_qubits is None:\\n control_qubits = ()\\n if num_controls < len(control_qubits):\\n raise ValueError('More specified control qubits than num_controls')\\n\\n # Leave unspecified controls as Nones.\\n self.control_qubits = ((None,) * (num_controls - len(control_qubits)) +\\n tuple(control_qubits)) # type: ignore\\n\\n # Flatten nested ControlledGates.\\n if isinstance(sub_gate, ControlledGate):\\n self.sub_gate = sub_gate.sub_gate # type: ignore\\n self.control_qubits += sub_gate.control_qubits\\n else:\\n self.sub_gate = sub_gate\",\n \"def tls_control_system():\\n eps1 = lambda t, args: 0.5\\n eps2 = lambda t, args: 1\\n H1 = [0.5 * sigmaz(), [sigmap(), eps1], [sigmam(), eps1]]\\n H2 = [0.5 * sigmaz(), [sigmaz(), eps2]]\\n c_ops = [0.1 * sigmap()]\\n objectives = [\\n krotov.Objective(\\n initial_state=ket('0'), target=ket('1'), H=H1, c_ops=c_ops\\n ),\\n krotov.Objective(\\n initial_state=ket('0'), target=ket('1'), H=H2, c_ops=c_ops\\n ),\\n ]\\n controls = [eps1, eps2]\\n controls_mapping = krotov.conversions.extract_controls_mapping(\\n objectives, controls\\n )\\n return objectives, controls, controls_mapping\",\n \"def _push_node_back(self, dag: DAGCircuit, node: DAGOpNode):\\n node_start_time = self.property_set[\\\"node_start_time\\\"]\\n conditional_latency = self.property_set.get(\\\"conditional_latency\\\", 0)\\n clbit_write_latency = self.property_set.get(\\\"clbit_write_latency\\\", 0)\\n\\n if isinstance(node.op, Gate):\\n alignment = self.pulse_align\\n elif isinstance(node.op, Measure):\\n alignment = self.acquire_align\\n elif isinstance(node.op, Delay) or getattr(node.op, \\\"_directive\\\", False):\\n # Directive or delay. These can start at arbitrary time.\\n alignment = None\\n else:\\n raise TranspilerError(f\\\"Unknown operation type for {repr(node)}.\\\")\\n\\n this_t0 = node_start_time[node]\\n\\n if alignment is not None:\\n misalignment = node_start_time[node] % alignment\\n if misalignment != 0:\\n shift = max(0, alignment - misalignment)\\n else:\\n shift = 0\\n this_t0 += shift\\n node_start_time[node] = this_t0\\n\\n # Compute shifted t1 of this node separately for qreg and creg\\n new_t1q = this_t0 + node.op.duration\\n this_qubits = set(node.qargs)\\n if isinstance(node.op, Measure):\\n # creg access ends at the end of instruction\\n new_t1c = new_t1q\\n this_clbits = set(node.cargs)\\n else:\\n if node.op.condition_bits:\\n # conditional access ends at the beginning of node start time\\n new_t1c = this_t0\\n this_clbits = set(node.op.condition_bits)\\n else:\\n new_t1c = None\\n this_clbits = set()\\n\\n # Check immediate successors for overlap\\n for next_node in self._get_next_gate(dag, node):\\n # Compute next node start time separately for qreg and creg\\n next_t0q = node_start_time[next_node]\\n next_qubits = set(next_node.qargs)\\n if isinstance(next_node.op, Measure):\\n # creg access starts after write latency\\n next_t0c = next_t0q + clbit_write_latency\\n next_clbits = set(next_node.cargs)\\n else:\\n if next_node.op.condition_bits:\\n # conditional access starts before node start time\\n next_t0c = next_t0q - conditional_latency\\n next_clbits = set(next_node.op.condition_bits)\\n else:\\n next_t0c = None\\n next_clbits = set()\\n # Compute overlap if there is qubits overlap\\n if any(this_qubits & next_qubits):\\n qreg_overlap = new_t1q - next_t0q\\n else:\\n qreg_overlap = 0\\n # Compute overlap if there is clbits overlap\\n if any(this_clbits & next_clbits):\\n creg_overlap = new_t1c - next_t0c\\n else:\\n creg_overlap = 0\\n\\n # Shift next node if there is finite overlap in either in qubits or clbits\\n overlap = max(qreg_overlap, creg_overlap)\\n node_start_time[next_node] = node_start_time[next_node] + overlap\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6381244","0.6276733","0.6038881","0.60035855","0.597752","0.5808486","0.55988115","0.55569977","0.55378765","0.5425379","0.53594565","0.5328162","0.5316508","0.52781427","0.5276781","0.52332044","0.52280194","0.5162224","0.5160193","0.5147565","0.51399696","0.5130555","0.5118275","0.5109535","0.510099","0.508524","0.5081088","0.5069889","0.5043363","0.5027079","0.5016284","0.5006875","0.4996428","0.49771732","0.49402967","0.49382403","0.48944634","0.48893484","0.48748034","0.48703498","0.4858765","0.48494005","0.4843296","0.4843296","0.48246828","0.48179868","0.48155424","0.48126358","0.48105907","0.48042634","0.47913972","0.47862524","0.478104","0.4761843","0.4761484","0.4761484","0.475408","0.47426638","0.47383836","0.4726018","0.47099385","0.47060046","0.47040924","0.47010124","0.4700901","0.46990022","0.46990022","0.46990022","0.46990022","0.46910736","0.46821555","0.46821162","0.46747434","0.4674501","0.46735585","0.46705115","0.46650067","0.46542233","0.46454427","0.46446648","0.46353537","0.4634074","0.46316323","0.46189663","0.4618888","0.4606999","0.46068543","0.46038085","0.46032232","0.45987624","0.4598194","0.45974576","0.45973206","0.45954508","0.45906907","0.45891908","0.45852533","0.4584947","0.45839858","0.45829257"],"string":"[\n \"0.6381244\",\n \"0.6276733\",\n \"0.6038881\",\n \"0.60035855\",\n \"0.597752\",\n \"0.5808486\",\n \"0.55988115\",\n \"0.55569977\",\n \"0.55378765\",\n \"0.5425379\",\n \"0.53594565\",\n \"0.5328162\",\n \"0.5316508\",\n \"0.52781427\",\n \"0.5276781\",\n \"0.52332044\",\n \"0.52280194\",\n \"0.5162224\",\n \"0.5160193\",\n \"0.5147565\",\n \"0.51399696\",\n \"0.5130555\",\n \"0.5118275\",\n \"0.5109535\",\n \"0.510099\",\n \"0.508524\",\n \"0.5081088\",\n \"0.5069889\",\n \"0.5043363\",\n \"0.5027079\",\n \"0.5016284\",\n \"0.5006875\",\n \"0.4996428\",\n \"0.49771732\",\n \"0.49402967\",\n \"0.49382403\",\n \"0.48944634\",\n \"0.48893484\",\n \"0.48748034\",\n \"0.48703498\",\n \"0.4858765\",\n \"0.48494005\",\n \"0.4843296\",\n \"0.4843296\",\n \"0.48246828\",\n \"0.48179868\",\n \"0.48155424\",\n \"0.48126358\",\n \"0.48105907\",\n \"0.48042634\",\n \"0.47913972\",\n \"0.47862524\",\n \"0.478104\",\n \"0.4761843\",\n \"0.4761484\",\n \"0.4761484\",\n \"0.475408\",\n \"0.47426638\",\n \"0.47383836\",\n \"0.4726018\",\n \"0.47099385\",\n \"0.47060046\",\n \"0.47040924\",\n \"0.47010124\",\n \"0.4700901\",\n \"0.46990022\",\n \"0.46990022\",\n \"0.46990022\",\n \"0.46990022\",\n \"0.46910736\",\n \"0.46821555\",\n \"0.46821162\",\n \"0.46747434\",\n \"0.4674501\",\n \"0.46735585\",\n \"0.46705115\",\n \"0.46650067\",\n \"0.46542233\",\n \"0.46454427\",\n \"0.46446648\",\n \"0.46353537\",\n \"0.4634074\",\n \"0.46316323\",\n \"0.46189663\",\n \"0.4618888\",\n \"0.4606999\",\n \"0.46068543\",\n \"0.46038085\",\n \"0.46032232\",\n \"0.45987624\",\n \"0.4598194\",\n \"0.45974576\",\n \"0.45973206\",\n \"0.45954508\",\n \"0.45906907\",\n \"0.45891908\",\n \"0.45852533\",\n \"0.4584947\",\n \"0.45839858\",\n \"0.45829257\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.61273205"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81751,"cells":{"query":{"kind":"string","value":"add CT dagger gate (controlled T dagger gate)."},"document":{"kind":"string","value":"def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def build_glyCB(self, gCBd: Dihedron): # -> None:\n ...","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def add_dut(self):\n pass","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def test_append_dangling_gate(self, circuit):\n match = (\n r\"Number of wire IDs \\(2\\) must match the number of wires connected to the gate \\(1\\).\"\n )\n gate = jet.GateFactory.create(\"H\")\n with pytest.raises(ValueError, match=match):\n circuit.append_gate(gate, wire_ids=[0, 1])","def train_dagger(): # add arguments as needed\n pass","def gate(self):\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def glycosylate(self):\n chid = self.chain.get()\n sequon = self.sequon.get()\n self.sequon_colors[sequon] = [.7, .1, 0]\n key = self.sequon.get()\n residue = self.myGlycosylator.get_residue(key)\n #Build new glycan\n if self.selected_glycan:\n self.myGlycosylator.connect_topology['SELECTED'] = self.selected_glycan[1]\n #build from current glycan\n if key in self.original_glycans:\n original_glycan = self.original_glycanMolecules[key].atom_group\n r,t = self.original_glycans[key]\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\n else:\n original_glycan = None\n connect_tree = None \n #Use current glycan\n else:\n original_glycan = self.original_glycanMolecules[key]\n r,t = self.original_glycans[key]\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\n self.myGlycosylator.connect_topology['SELECTED'] = self.myGlycosylator.build_connect_topology(original_glycan) \n original_glycan = original_glycan.atom_group\n \n segname = 'G'+key.split(',')[2]\n glycan,bonds = self.myGlycosylator.glycosylate('SELECTED', \n template_glycan_tree = connect_tree, \n template_glycan = original_glycan,\n link_residue=residue, link_patch = 'NGLB', chain = 'G', segname=segname)\n new_glycan = glc.Molecule(key)\n new_glycan.set_AtomGroup(glycan, bonds = bonds)\n self.myGlycosylator.assign_patches(new_glycan)\n self.linked_glycanMolecules[key] = new_glycan\n self.linked_glycans[key] = [new_glycan.rootRes, new_glycan.interresidue_connectivity]\n self.names.update(new_glycan.get_names())\n # Update glycoprotein and sequon panels\n self.draw_glycoprotein(chid)\n self.draw_glycan(sequon)","def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self","def load_gates(chip):\n for gate_id in chip.gates:\n gate_coord = chip.gates[gate_id]\n gate = gt.Gate(gate_id, gate_coord[\"x\"], gate_coord[\"y\"])\n chip.coordinates[0][gate_coord[\"y\"]][gate_coord[\"x\"]].gate = gate\n\n return chip","def __init__(self, input, output) :\n Gate.__init__(self, [input], output)","def _add_entanglement_gate(self, gate_method, qubit_1, qubit_2):\r\n sig = signature(gate_method)\r\n\r\n # parametrized gate like a controlled single qubit rotation\r\n if 'theta' in sig.parameters:\r\n try:\r\n gate_method(self.circuit, self.parameters[next(self.indices)], qubit_1, qubit_2)\r\n except KeyError:\r\n raise ValueError(f'Unsupported two qubit rotation gate')\r\n\r\n # non-parametrized gate like CNOT\r\n else:\r\n try:\r\n gate_method(self.circuit, qubit_1, qubit_2)\r\n except KeyError:\r\n raise ValueError(f'Unsupported unparametrized two qubit gate')","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def make_gate_output(self, ungate=[]):\n\n pattern = self.gate_output.activator.off * np.ones((self.gate_output.size,1))\n\n # Ungate provided keys\n for k in self.default_gates + ungate:\n i = self.gate_map.get_gate_index(k)\n pattern[i,0] = self.gate_output.activator.on\n\n return pattern","def _process_gate(self, node, opaque=False):\n self.gates[node.name] = {}\n de_gate = self.gates[node.name]\n de_gate[\"opaque\"] = opaque\n de_gate[\"n_args\"] = node.n_args()\n de_gate[\"n_bits\"] = node.n_bits()\n if node.n_args() > 0:\n de_gate[\"args\"] = [element.name for element in node.arguments.children]\n else:\n de_gate[\"args\"] = []\n de_gate[\"bits\"] = [c.name for c in node.bitlist.children]\n if opaque:\n de_gate[\"body\"] = None\n else:\n de_gate[\"body\"] = node.body\n self.backend.define_gate(node.name, copy.deepcopy(de_gate))","def _add_pairblend(self, dgmod, rigid, transform):\n\n assert isinstance(dgmod, cmdx.DGModifier)\n\n pair_blend = dgmod.create_node(\"pairBlend\")\n dgmod.set_attr(pair_blend[\"isHistoricallyInteresting\"], False)\n\n # Establish initial values, before keyframes\n # tm = cmdx.Tm(self._cache[(transform, \"matrix\")])\n\n # Read from matrix, as opposed to the rotate/translate channels\n # to account for jointOrient, pivots and all manner of things\n # translate = tm.translation()\n # rotate = tm.rotation()\n\n translate = self._cache[(transform, \"translate\")]\n rotate = self._cache[(transform, \"rotate\")]\n\n dgmod.set_attr(pair_blend[\"inTranslate1\"], translate)\n dgmod.set_attr(pair_blend[\"inRotate1\"], rotate)\n\n dgmod.connect(rigid[\"outputTranslateX\"], pair_blend[\"inTranslateX2\"])\n dgmod.connect(rigid[\"outputTranslateY\"], pair_blend[\"inTranslateY2\"])\n dgmod.connect(rigid[\"outputTranslateZ\"], pair_blend[\"inTranslateZ2\"])\n dgmod.connect(rigid[\"outputRotateX\"], pair_blend[\"inRotateX2\"])\n dgmod.connect(rigid[\"outputRotateY\"], pair_blend[\"inRotateY2\"])\n dgmod.connect(rigid[\"outputRotateZ\"], pair_blend[\"inRotateZ2\"])\n\n # Let the animator see the raw animation values, no physics\n dgmod.connect(self._tree_root[0][\"simulated\"], pair_blend[\"weight\"])\n\n if self._opts[\"autoKey\"]:\n # Generate default animation curves, it's expected since you can no\n # longer see whether channels are keyed or not, now being green.\n time = cmdx.currentTime()\n mapping = (\n (\"animCurveTL\", translate.x, \"inTranslateX1\"),\n (\"animCurveTL\", translate.y, \"inTranslateY1\"),\n (\"animCurveTL\", translate.z, \"inTranslateZ1\"),\n (\"animCurveTA\", rotate.x, \"inRotateX1\"),\n (\"animCurveTA\", rotate.y, \"inRotateY1\"),\n (\"animCurveTA\", rotate.z, \"inRotateZ1\")\n )\n\n for curve, value, dst in mapping:\n curve = dgmod.create_node(curve)\n curve.key(time, value)\n dgmod.connect(curve[\"output\"], pair_blend[dst])\n\n # Transfer existing animation/connections\n for src, dst in transform.data.get(\"priorConnections\", {}).items():\n dst = pair_blend[dst]\n dgmod.connect(src, dst)\n\n commands._connect_transform(dgmod, pair_blend, transform)\n\n return pair_blend","def add_junction(ccTremb):\n pass","def __init__(self, input0, input1, output) :\n Gate.__init__(self, [input0,input1], output)","def dagger(self) -> Cup:\n return self.cup_factory(self.left, self.right)","def build_gate_1(gate, tags=None):\n\n def apply_constant_single_qubit_gate(psi, i, **gate_opts):\n mtags = _merge_tags(tags, gate_opts)\n psi.gate_(gate, int(i), tags=mtags, **gate_opts)\n\n return apply_constant_single_qubit_gate","def _auto_blend(self, dgmod):\n\n assert isinstance(dgmod, cmdx.DGModifier)\n\n root, _ = self._root\n root_rigid = root.shape(type=\"rdRigid\")\n\n for rigid in self._new_rigids:\n\n # Don't bother with the root\n if rigid == root_rigid:\n continue\n\n transform = rigid.parent()\n blend = self._add_pairblend(dgmod, rigid, transform)\n self._auto_influence(dgmod, rigid, blend)","def construct_TDI(self, t, Orbit):\n\t\n\tself.make_padded_delta_l(t)\n\n\tp12 = td.Phase(1,2, t, self.delta_l_padded[0,1,:])\n\tp21 = td.Phase(2,1, t, self.delta_l_padded[1,0,:])\n\n\tp13 = td.Phase(1,3, t, self.delta_l_padded[0,2,:])\n\tp31 = td.Phase(3,1, t, self.delta_l_padded[2,0,:])\n\n\tp23 = td.Phase(2,3, t, self.delta_l_padded[1,2,:])\n\tp32 = td.Phase(3,2, t, self.delta_l_padded[2,1,:])\n \n\tp12.FT_phase(Orbit)\n\tp21.FT_phase(Orbit)\n\tp13.FT_phase(Orbit)\n\tp31.FT_phase(Orbit)\n\tp23.FT_phase(Orbit)\n\tp32.FT_phase(Orbit)\n\n\ttdi_GW = td.TDI(p12, p21, p13, p31, p23, p32, Orbit)\n\t\n\treturn tdi_GW","def append_user_gate(self, user_gate):\n self.translation['g_sect'].append(user_gate)","def triplicateBlck(self, blck_id):\n # Eliminating basic outlier conditions\n if blck_id not in self.dGrph:\n print('blck_id: ', blck_id, ' does not exist. Triplication aborted.')\n return\n\n # identifying the type of block and triplicating\n test = len(self.dGrph[blck_id][1])\n if test == 3: # ari block\n ip = self.dGrph[blck_id][0]\n config = self.dGrph[blck_id][2]\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\n new_ops = []\n for i in range(3):\n temp_op = []\n for original_op in self.dGrph[blck_id][1]:\n temp_op.append([original_op[0]+'_trip728'+str(i), None])\n new_ops.append(temp_op)\n\n self.dGrph[new_ids[0]] = [ip, new_ops[0], config]\n self.dGrph[new_ids[1]] = [ip, new_ops[1], config]\n self.dGrph[new_ids[2]] = [ip, new_ops[2], config]\n\n # for first output\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0][0], new_ops[1][0][0]], new_ids[0]+'_and0_o')\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0][0], new_ops[2][0][0]], new_ids[1]+'_and0_o')\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0][0], new_ops[2][0][0]], new_ids[2]+'_and0_o')\n\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0][0])\n\n # for second output\n self.__addGate(new_ids[0]+'_and1', 'A', [new_ops[0][1][0], new_ops[1][1][0]], new_ids[0]+'_and1_o')\n self.__addGate(new_ids[1]+'_and1', 'A', [new_ops[0][1][0], new_ops[2][1][0]], new_ids[1]+'_and1_o')\n self.__addGate(new_ids[2]+'_and1', 'A', [new_ops[1][1][0], new_ops[2][1][0]], new_ids[2]+'_and1_o')\n\n self.__addGate(new_ids[0]+'_or1', 'O', [new_ids[0]+'_and1_o', new_ids[1]+'_and1_o', new_ids[2]+'_and1_o'], self.dGrph[blck_id][1][1][0])\n\n # for third output\n self.__addGate(new_ids[0]+'_and2', 'A', [new_ops[0][2][0], new_ops[1][2][0]], new_ids[0]+'_and2_o')\n self.__addGate(new_ids[1]+'_and2', 'A', [new_ops[0][2][0], new_ops[2][2][0]], new_ids[1]+'_and2_o')\n self.__addGate(new_ids[2]+'_and2', 'A', [new_ops[1][2][0], new_ops[2][2][0]], new_ids[2]+'_and2_o')\n\n self.__addGate(new_ids[0]+'_or2', 'O', [new_ids[0]+'_and2_o', new_ids[1]+'_and2_o', new_ids[2]+'_and2_o'], self.dGrph[blck_id][1][2][0])\n\n del self.dGrph[blck_id]\n\n elif test == 2: # cfg block\n ip = self.dGrph[blck_id][0]\n config = self.dGrph[blck_id][2]\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\n new_ops = [[self.dGrph[blck_id][2][0] + '_trip7280', None], [self.dGrph[blck_id][2][0] + '_trip7281', None], [self.dGrph[blck_id][2][0] + '_trip7282', None]]\n\n self.dGrph[new_ids[0]] = [ip, new_ops[0], config]\n self.dGrph[new_ids[1]] = [ip, new_ops[1], config]\n self.dGrph[new_ids[2]] = [ip, new_ops[2], config]\n\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0], new_ops[1][0]], new_ids[0]+'_and0_o')\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0], new_ops[2][0]], new_ids[1]+'_and0_o')\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0], new_ops[2][0]], new_ids[2]+'_and0_o')\n\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0])\n\n del self.dGrph[blck_id]\n\n elif test == 1: # tribuf\n ip = self.dGrph[blck_id][0]\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\n new_ops = [[self.dGrph[blck_id][2][0] + '_trip7280', None], [self.dGrph[blck_id][2][0] + '_trip7281', None], [self.dGrph[blck_id][2][0] + '_trip7282', None]]\n\n self.dGrph[new_ids[0]] = [ip, [ip[1]], new_ops[0]]\n self.dGrph[new_ids[1]] = [ip, [ip[1]], new_ops[1]]\n self.dGrph[new_ids[2]] = [ip, [ip[1]], new_ops[2]]\n\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0], new_ops[1][0]], new_ids[0]+'_and0_o')\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0], new_ops[2][0]], new_ids[1]+'_and0_o')\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0], new_ops[2][0]], new_ids[2]+'_and0_o')\n\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0])\n\n del self.dGrph[blck_id]\n \n else:\n print('Unknown error!!!!!!\\n')","def add_gates(self, num_gates_to_add):\n pass","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def _gyration(self, x, y, v, c):\n xy = self._mobius_add(x, y, c)\n yv = self._mobius_add(y, v, c)\n xyv = self._mobius_add(x, yv, c)\n return self._mobius_add(-xy, xyv, c)","def _g(self, x: torch.Tensor, params: Scenario):\n # Extract batch size and set up a tensor for holding the result\n batch_size = x.shape[0]\n g = torch.zeros((batch_size, self.n_dims, self.n_controls))\n g = g.type_as(x)\n\n # Extract state variables\n theta = x[:, TurtleBot2D.THETA]\n\n # Effect on x\n g[:, TurtleBot2D.X, TurtleBot2D.V] = torch.cos(theta)\n\n # Effect on y\n g[:, TurtleBot2D.Y, TurtleBot2D.V] = torch.sin(theta)\n\n # Effect on theta\n g[:, TurtleBot2D.THETA, TurtleBot2D.THETA_DOT] = 1.0\n\n return g","def cmd_dgaus():\n cmds = []\n cmds.append(\"r_m[0.0,-1,1]\")\n cmds.append(\"r_s[1.5,0,10]\")\n cmds.append('Gaussian::gaus_c(x,r_m,r_s)')\n cmds.append(\"rt_m[0.0,-1,1]\")\n cmds.append(\"rt_s[3,0,10]\")\n cmds.append('Gaussian::gaus_t(x,rt_m,rt_s)')\n cmds.append(\"f[0.85]\") # fraction of core\n cmds.append(\"SUM::res(f*gaus_c,gaus_t)\")\n return cmds","def connect(self, gate) :\n self.notifyList.append(gate)","def t_dg(self, q0, ctrl=None):\n self.__add_quantum_gate(kind=PHASE_SHIFT_T_, qid=[q0], ctrl=ctrl)\n return self","def dagger(self):\n return cat.Arrow.dagger(self)","def insert(n, c, dnodecomm):\n\n _tot[c] += k[n]\n _in[c] += 2 * dnodecomm + network[n][n]\n bl[n] = c","def globalphase_compiler(self, gate, args):\n pass","def globalphase_compiler(self, gate, args):\n pass","def recursive_gate(e):\n if isinstance(e, boolean.BaseElement):\n # TODO: Either make the the same or create a constant component.\n s = Switch()\n b.append(s)\n return s\n elif isinstance(e, boolean.Symbol):\n if e in symbol_dict.keys():\n return symbol_dict[e]\n else:\n s = Switch()\n symbol_dict[e] = s\n b.append(s)\n return s\n elif isinstance(e, boolean.Function):\n # All gates are of type Gate instead of And, Or and Not\n if e.order == (1, 1):\n pre = recursive_gate(e.args[0])\n w = Wire(pre)\n b.append(w)\n\n s = boolean.Symbol(None)\n g = Gate(e.subs({e.args[0]: s}),\n {s: w})\n b.append(g)\n return g\n else:\n input_dict = {}\n expr = e\n for arg in e.args:\n pre = recursive_gate(arg)\n w = Wire(pre)\n b.append(w)\n\n s = boolean.Symbol(None)\n expr = expr.subs({arg: s})\n input_dict[s] = w\n g = Gate(expr,\n input_dict)\n b.append(g)\n return g","def glucose_c1(self, g_t, t_G, a_G, d_g_t=0):\n return -(1/t_G)*g_t+(a_G/t_G)*d_g_t","def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self","def add_distractor(self, distractor_phrase: Phrase, main_phrase: Phrase):\n if distractor_phrase.phrase_string not in self.phrase_string_map:\n self.phrase_string_map[distractor_phrase.phrase_string] = distractor_phrase\n self.distractor_index[distractor_phrase.phrase_string] = distractor_phrase\n self.is_distractor_of[distractor_phrase.phrase_string].add(main_phrase.phrase_string)\n self.has_distractors[main_phrase.phrase_string].add(distractor_phrase.phrase_string)\n self.phrase_type[distractor_phrase.phrase_string].add(\"distractor\")\n self._index_phrase_words(distractor_phrase)\n self._index_phrase_tokens(distractor_phrase)","def gen_gr_fiber(th,sigma,mu,iopt,tilt):\n hkl, uvw = basal_fib(iopt)\n if iopt==0:\n g_casa = miller2mat(hkl,uvw)\n g_sasa = nd_rot(th)\n elif iopt==1:\n g_casa = miller2mat_RT(uvw=uvw,xyz=hkl)\n g_sasa = rd_rot(th)\n g = np.dot(g_casa,g_sasa)\n if tilt!=0:\n g_tilt = rd_rot(tilt)\n g = np.dot(g_tilt.T,g)\n\n dth = gauss(mu=mu, sigma=sigma)\n return rot_vectang(th=dth, r=g)","def define_gan(g_model, d_model):\r\n # make weights in the discriminator (some shared with the q model) as not trainable\r\n d_model.trainable = False\r\n # connect g outputs to d inputs\r\n d_output = d_model(g_model.output)\r\n # define composite model\r\n model = Model(g_model.input, d_output)\r\n # compile model\r\n opt = Adam(lr=0.0001, beta_1=0.5)\r\n model.compile(loss=['binary_crossentropy'], optimizer=opt)\r\n return model","def add_condiments(self):\n print(\"Adding Lemon\")","def get_gate(gate, params, num_ctrl_qubits=None):\n if gate[0] == \"c\":\n return get_gate(gate[1:], params, num_ctrl_qubits).ctrl()\n if gate == \"toffoli\":\n return get_gate(\"ccx\", params, num_ctrl_qubits)\n if gate[0:2] == \"mc\":\n name = gate[2:]\n for _ in range(num_ctrl_qubits):\n name = \"c\" + name\n return get_gate(name, params, num_ctrl_qubits)\n if len(params) == 0:\n return GATE_DIC[gate]\n\n return GATE_DIC[gate](*params)","def __init__(self, gate: Gate, tag: Any) -> None:\n\n if not isinstance(gate, Gate):\n raise TypeError('Expected gate object, got %s' % type(gate))\n\n self.gate = gate\n self.tag = tag\n self.name = 'Tagged(%s:%s)' % (gate.get_name(), tag)\n self.num_params = gate.get_num_params()\n self.size = gate.get_size()\n self.radixes = gate.get_radixes()\n\n # If input is a constant gate, we can cache the unitary.\n if self.num_params == 0:\n self.utry = gate.get_unitary()","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def __init__(self, nfeat, nhid, nclass, dropout, alpha):\n super(GCN, self).__init__()\n self.dropout = dropout\n\n self.conv1 = GraphConvolutionLayer(nfeat, nhid, dropout=dropout, alpha=alpha, not_final=True)\n \n self.add_module('conv1', self.conv1)\n\n self.conv2 = GraphConvolutionLayer(nhid, nclass, dropout=dropout, alpha=alpha, not_final=False)","def add_hydroxyl(atom, atom_list, added_functional_groups, ct):\n global anywhere_map\n global edge_map\n current_size = len(atom_list)\n placed = 0\n alpha = random.randint(0,359)\n while (placed <= 359):\n alpha += 1\n oxygen_atom = Atom(current_size + 1, 'OL', 'H1A', str(added_functional_groups + 1), atom.x, atom.y, ct * 1.49 + atom.z)\n atom_list.append(oxygen_atom)\n if ((len(identify_bonds(oxygen_atom, atom_list)) == 1) and (identify_bonds(oxygen_atom, atom_list)[0][0].atom_number == atom.atom_number)):\n h = math.sin(math.radians(19)) * 0.98\n h_sp = math.cos(math.radians(19)) * 0.98\n hydrogen_atom = Atom(current_size + 2, 'HK', 'H1A', str(added_functional_groups + 1), float(\"{0:.3f}\".format(oxygen_atom.x - math.cos(math.radians(alpha)) * h_sp)), float(\"{0:.3f}\".format(oxygen_atom.y - math.sin(math.radians(alpha)) * h_sp)), float(\"{0:.3f}\".format(oxygen_atom.z + ct * h)))\n atom_list.append(hydrogen_atom)\n if ((len(identify_bonds(hydrogen_atom, atom_list)) == 1) and (identify_bonds(hydrogen_atom, atom_list)[0][0].atom_number == oxygen_atom.atom_number)):\n placed = 888\n if atom in edge_map: edge_map.remove(atom)\n if atom in anywhere_map: anywhere_map.remove(atom) \n CY = Atom(atom.atom_number, 'CY', 'H1A', oxygen_atom.residue_number, atom.x, atom.y, atom.z)\n atom_list.append(CY)\n atom_list.remove(atom) \n del atom \n else:\n placed += 5\n del hydrogen_atom\n del atom_list[current_size + 1]\n del oxygen_atom\n del atom_list[current_size + 0]\n else:\n placed += 5\n del oxygen_atom\n del atom_list[current_size + 0]\n return atom_list","def dX_gene_reg_fn(x, t, topology, params):\n\tparents = topology.parents\n\ttarget = topology.target\n\tinteractions = topology.interactions\n\n\tbase_synth = params[0]\n\tbase_degr = params[1]\n\n\t# Add basal synthesis and basal degradation terms\n\tdX = base_synth - x[target] * base_degr\n\n\t# Add contributions from each edge\n\tfor i in range(len(parents)):\n\t\tp = parents[i]\n\t\tinter = interactions[i]\n\n\t\tj = 2 + i*3\n\t\tb = params[ j ] \t # Interaction 'Strength'\n\t\tk = params[ j + 1 ] # Hill fn parameter (theta)\n\t\tm = params[ j + 2 ] # Hill fn parameter (m)\n\n\t\t# Value of parent for all t\n\t\tparent_val = x[p]\n\n\t\tif inter == 0:\n\t\t\tdX += (b * parent_val**m) / (parent_val**m + k**m)\n\t\telif inter == 1:\n\t\t\tdX += b / (1 + (parent_val/k)**m)\n\t\n\treturn dX","def gate_pass(self, goal):\n def rc_to_obj(self, goal):\n \"\"\"Add constant rc commands to depth and heading hold\"\"\"\n channels = self.depth_heading_rc(goal)\n channels[self.xchannel] = goal.x_rc_vel\n yrc_cmd = self.get_obj_y(goal, True)\n channels[self.ychannel] = yrc_cmd\n return channels\n\n def is_term(self, goal):\n \"\"\"terminate when the gate is a certain size\"\"\"\n return self.object_width > self.maxwidth\n\n self.behavior_loop(goal, rc_to_obj, is_term)","def dagger(self) -> Cap:\n return self.cap_factory(self.left, self.right)","def _ice_dgdt(temp,pres):\n # Reduced variables\n tn = temp/_TTP\n pn = pres/_PTPE\n _PI0 = _PATM/_PTPE\n g_t = 0.\n \n # Power series and entropy components\n g_t += -_GCOEFFS[4]\n \n # Residual terms including complex numbers\n sr = [_GCOEFFS[1], complex(0.0,0.0)]\n for (k,rk) in enumerate(_GCOEFFS[2]):\n sr[1] += rk * (pn-_PI0)**k\n for (tk,s) in zip(_GCOEFFS[3],sr):\n term = -numpy.log(tk-tn) + numpy.log(tk+tn) - 2*tn/tk\n g_t += (s*term).real\n return g_t","def __init__(self, nfeat, nhid, nclass, dropout, alpha, nheads):\n super(GAT, self).__init__()\n self.dropout = dropout\n\n self.attentions = [GraphAttentionLayer(nfeat, nhid, dropout=dropout, alpha=alpha, concat=True) for _ in range(nheads)]\n for i, attention in enumerate(self.attentions):\n self.add_module('attention_{}'.format(i), attention)\n\n self.out_att = GraphAttentionLayer(nhid * nheads, nclass, dropout=dropout, alpha=alpha, concat=False)","def _gcl(x, r, D, Ia, Ct):\n\n Area = np.pi * D ** 2.0 / 4.0\n m = 1.0 / (np.sqrt(1.0 - Ct))\n k = np.sqrt((m + 1.0) / 2.0)\n\n a1 = 0.435449861 # empirically determined\n a2 = 0.797853685\n a3 = -0.124807893\n a4 = 0.136821858\n b1 = 15.6298\n b2 = 1.0\n R96 = a1 * (np.exp(a2 * Ct * Ct + a3 * Ct + a4)) * (b1 * Ia + b2) * D\n\n x0 = (9.6 * D) / ((2.0 * R96 / (k * D)) ** 3.0 - 1.0)\n term1 = (k * D / 2.0) ** (5.0 / 2.0)\n term2 = (105.0 / (2.0 * np.pi)) ** (-0.5)\n term3 = (Ct * Area * x0) ** (-5.0 / 6.0)\n c1 = term1 * term2 * term3\n # c45=3*(c1) ** 2\n\n term10 = 0.1111 # * WindSpeed # U/9.0\n term20 = (Ct * Area * (x + x0) ** (-2.0)) ** (1.0 / 3.0)\n term310 = (r ** (3.0 / 2.0))\n term320 = (3.0 * c1 * c1 * Ct * Area * (x + x0)) ** (-0.5)\n term30 = term310 * term320\n term40 = ((35.0 / (2.0 * np.pi)) ** (3.0 / 10.0)) * \\\n (3.0 * c1 * c1) ** (-1.0 / 5.0)\n DU1 = -term10 * term20 * (term30 - term40) ** 2.0\n\n DU = DU1 # + w2 * DU2\n Rw = ((105 * c1 ** 2.0 / (2 * np.pi)) ** (1. / 5.)) * \\\n (Ct * Area * (x + x0)) ** (1. / 3.)\n return DU, Rw","def generate_random_DC_crack_coupled_tensor():\n # 1. Generate random DC MT and crack MT:\n # generate DC MT:\n DC_MT_to_rot = np.vstack(([0.,0.,1.],[0.,0.,0.], [1.,0.,0.])) # DC moment tensor\n # generate crack MT (from Tape 2013, eq. 41 and Fig. 6):\n # To randomly generate lune_perim_angle (from Tape 2013 eq. 41 and Fig. 6):\n # --- To randomly generate lune_perim_angle (from Tape 2013 eq. 41 and Fig. 6) ---:\n # Get between small range:\n theta_lune_sphere = np.random.uniform(-1.,1.)*np.pi/2.\n random_num = random.random()\n if random_num <= 0.5:\n phi_lune_sphere = 0. #np.pi/6. #0. #np.pi/6.\n elif random_num > 0.5:\n phi_lune_sphere = np.pi/3 #-1.*np.pi/6. #np.pi/3 #-1.*np.pi/6.\n # calculate lune_perim_angle, allowing for outside tan(-pi/2->pi/2):\n lune_perim_angle = np.arctan(np.sin(phi_lune_sphere)/np.sin(theta_lune_sphere)) # Generates uniform distribution of lune crack angle in Lune plot space #random.random()*2.*np.pi # Random number in uniform distribution betwen 0 and 2 pi\n # And redistribute evenly everywhere on boundary:\n random_num = random.random()\n if random_num>0.25 and random_num<=0.5:\n lune_perim_angle = lune_perim_angle+np.pi # Allow to use full 2 pi space\n if random_num>0.5 and random_num<=0.75:\n lune_perim_angle = lune_perim_angle+np.pi/2 # Allow to use full 2 pi space\n if random_num>0.75 and random_num<=1.0:\n lune_perim_angle = lune_perim_angle+3*np.pi/2 # Allow to use full 2 pi space\n # --- ---\n # random_num = random.random()\n # if random_num <= 0.5:\n # theta_lune_sphere = random.random()*np.pi/2.\n # elif random_num > 0.5:\n # theta_lune_sphere = -1.*random.random()*np.pi/2.\n # random_num = random.random()\n # if random_num <= 0.5:\n # phi_lune_sphere = np.pi/6.\n # elif random_num > 0.5:\n # phi_lune_sphere = -1.*np.pi/6.\n # lune_perim_angle = np.arctan(np.sin(phi_lune_sphere)/np.sin(theta_lune_sphere)) # Generates uniform distribution of lune crack angle in Lune plot space #random.random()*2.*np.pi # Random number in uniform distribution betwen 0 and 2 pi\n crack_MT_to_rot = ((((4*(np.sin(lune_perim_angle)**2)) + (np.cos(lune_perim_angle)**2))**-0.5)/np.sqrt(3.)) * np.vstack(([np.cos(lune_perim_angle)-(np.sqrt(2)*np.sin(lune_perim_angle)),0.,0.],[0.,np.cos(lune_perim_angle)-(np.sqrt(2)*np.sin(lune_perim_angle)),0.], [0.,0.,np.cos(lune_perim_angle)+(2.*np.sqrt(2)*np.sin(lune_perim_angle))])) # crack moment tensor\n # 2. Combine DC and crack tensors:\n random_amp_frac = random.random() # random number between 0. and 1., for relative amplitude of DC and crack fractions.\n DC_crack_MT_to_rot =random_amp_frac*DC_MT_to_rot + (1.-random_amp_frac)*crack_MT_to_rot\n # 3. Randomly rotate DC-crack MT to random orientation:\n # Get a random sample 3-vector on a 3-unit sphere to use to calculate random theta and phi rotation angles:\n a_unnormalised = np.array([np.random.normal(loc=0.0, scale=1.0), np.random.normal(loc=0.0, scale=1.0), np.random.normal(loc=0.0, scale=1.0)], dtype=float) # Generate 3 indepdendent normal deviates\n a_normalised = a_unnormalised/(np.sum(a_unnormalised**2)**-0.5) # Normallise sample onto unit 3-sphere - As in Muller (1959)\n # And normallise so that vector magnitude = 1:\n a_normalised = a_normalised/((np.sum(a_normalised**2))**0.5)\n x = a_normalised[0]\n y = a_normalised[1]\n z = a_normalised[2]\n theta = np.arctan2(np.sqrt((x**2)+(y**2)),z) #np.arccos(z)\n phi = np.arctan2(y,x) #np.arccos(x/np.sin(theta))\n DC_crack_MT_rotated = rot_mt_by_theta_phi(DC_crack_MT_to_rot, theta, phi)\n # 4. Normalise and get 6 MT:\n # Get 6 MT:\n DC_crack_six_MT_rotated = get_six_MT_from_full_MT_array(DC_crack_MT_rotated)\n # And normallise so that moment tensor magnitude = 1:\n DC_crack_six_MT_rotated_normalised = DC_crack_six_MT_rotated/((np.sum(DC_crack_six_MT_rotated**2))**0.5)\n # And set to correct dimensions (so matrix multiplication in forward model works correctly):\n DC_crack_six_MT_rotated_normalised = np.reshape(DC_crack_six_MT_rotated_normalised, (6, 1))\n return DC_crack_six_MT_rotated_normalised, random_amp_frac","def get_t_d(conf, r_inputs, d_data):\n # to crop out unstable part for temporal discriminator, details in TecoGAN supplemental paper\n crop_size_dt = int(conf.train.crop_size * 4 * conf.gan.crop_dt)\n offset_dt = (conf.train.crop_size * 4 - crop_size_dt) // 2\n crop_size_dt = conf.train.crop_size * 4 - offset_dt*2\n paddings = (0, 0, offset_dt, offset_dt, offset_dt, offset_dt, 0, 0)\n\n with nn.parameter_scope(\"discriminator\"):\n real_warp = warp_by_flow(d_data.t_targets, d_data.t_vel)\n real_warp = space_to_depth_disc(real_warp, d_data.t_batch)\n\n # equivalent to tf.image.crop_to_bounding_box\n real_warp = real_warp[:, offset_dt:offset_dt +\n crop_size_dt, offset_dt:offset_dt+crop_size_dt, :]\n real_warp = F.pad(real_warp, paddings)\n before_warp = space_to_depth_disc(d_data.t_targets, d_data.t_batch)\n t_input = space_to_depth_disc(\n r_inputs[:, :d_data.t_size, :, :, :], d_data.t_batch)\n # resizing using bilinear interpolation\n input_hi = F.interpolate(t_input, scale=(4, 4), mode='linear',\n channel_last=True)\n real_warp = F.concatenate(before_warp, real_warp, input_hi)\n\n tdiscrim_real_output, real_layers = discriminator(real_warp)\n\n fake_warp = warp_by_flow(d_data.t_gen_output, d_data.t_vel)\n fake_warp = space_to_depth_disc(fake_warp, d_data.t_batch)\n fake_warp = fake_warp[:, offset_dt:offset_dt +\n crop_size_dt, offset_dt:offset_dt+crop_size_dt, :]\n fake_warp = F.pad(fake_warp, paddings)\n before_warp = space_to_depth_disc(\n d_data.t_gen_output, d_data.t_batch, inplace=False)\n fake_warp = F.concatenate(before_warp, fake_warp, input_hi)\n tdiscrim_fake_output, fake_layers = discriminator(fake_warp)\n\n temporal_disc = collections.namedtuple('temporal_disc', 'tdiscrim_real_output,'\n 'real_layers, tdiscrim_fake_output, fake_layers')\n return temporal_disc(\n tdiscrim_real_output=tdiscrim_real_output,\n real_layers=real_layers,\n tdiscrim_fake_output=tdiscrim_fake_output,\n fake_layers=fake_layers\n )","def descent_acc(thrust, drone_mass, g=9.81, drag = 0.):\n output = (-thrust - drone_mass * g + drag) / drone_mass\n return output","def add_modified_decoherence_noise(\n prog: \"Program\",\n T1: Union[Dict[int, float], float] = 30e-6,\n T2: Union[Dict[int, float], float] = 30e-6,\n gate_time_1q: float = 50e-9,\n gate_time_2q: float = 150e-09,\n ro_fidelity: Union[Dict[int, float], float] = 0.95,\n) -> \"Program\":\n gates = _get_program_gates(prog)\n #definitions = {\n # def_gate.name: def_gate.matrix for def_gate in prog.defined_gates #figure out what is it for \n #}\n noise_model = _modified_decoherence_noise_model(\n gates,\n T1=T1,\n T2=T2,\n gate_time_1q=gate_time_1q,\n gate_time_2q=gate_time_2q,\n ro_fidelity=ro_fidelity\n )\n return apply_modified_noise_model(prog, noise_model)","def add_diameter(self, dia):\n self.diameters.append(dia)","def add_ground(f, c):\n return f.per(dmp_add_ground(f.rep, f.dom.convert(c), f.lev, f.dom))","def _ice_d2gdtdp(temp,pres):\n # Reduced variables\n tn = temp/_TTP\n pn = pres/_PTPE\n _PI0 = _PATM/_PTPE\n \n # Residual terms including complex numbers\n s = complex(0.0,0.0)\n for (k,rk) in enumerate(_GCOEFFS[2]):\n if k > 0:\n s += rk * k*(pn-_PI0)**(k-1) / _PTPE\n tk = _GCOEFFS[3][1]\n term = -numpy.log(tk-tn) + numpy.log(tk+tn) - 2*tn/tk\n g_tp = (s*term).real\n return g_tp","def test_tdg_gate_nondeterministic_minimal_basis_gates(self):\n shots = 2000\n circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_non_clifford.tdg_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def pgd_feat_create_adv_graph(self, sess, feats, y, eps, eta):\n init_delta = tf.random_uniform(shape = tf.shape(self.featurizations), minval = -eps, maxval = eps)\n delta = tf.Variable(init_delta, name = \"delta_feat\", validate_shape = False)\n\n #Define new featurizations\n featurizations_perturbed = self.featurizations + delta\n\n #Find predictions and new loss\n initial = tf.contrib.layers.xavier_initializer(dtype = tf.float32)\n bias_initial = tf.initializers.zeros\n\n scope = 'fc_' + str(len(self.hidden_sizes))\n predictions = fully_connected_layer(featurizations_perturbed, self.num_classes, scope, initial, bias_initial, tf.identity)\n\n loss_vector = tf.nn.softmax_cross_entropy_with_logits(logits=predictions, labels=self.y)\n loss_tilde = tf.reduce_mean(loss_vector)\n\n optimization_step = tf.assign(delta, tf.squeeze(tf.clip_by_value(delta + eta * tf.math.sign(tf.gradients(loss_tilde, delta)), clip_value_min = -eps, clip_value_max = eps)))\n\n return optimization_step, featurizations_perturbed, loss_tilde, delta","def _add_train_op(self):\n with tf.device(\"/gpu:0\"):\n learning_rate_D = 0.0004 # tf.train.exponential_decay(0.001, self.global_step_D,\n # 100000, 0.96, staircase=True)\n learning_rate_G = 0.0004 # tf.train.exponential_decay(0.001, self.global_step_G,\n # 100000, 0.96, staircase=True)\n learning_rate_D_in = 0.0004 # tf.train.exponential_decay(0.001, self.global_step_D,\n # 100000, 0.96, staircase=True)\n self._train_op_D = tf.train.AdamOptimizer(learning_rate_D,beta1=0.5).minimize(self._D_loss,\n global_step=self.global_step_D,\n var_list=self.discriminator._theta)\n self._train_op_D_in = tf.train.AdamOptimizer(learning_rate_D_in,beta1=0.5).minimize(self._D_in_loss,\n global_step=self.global_step_D_in,\n var_list=self.discriminator_inner._theta)\n\n self._train_op_G = tf.train.AdamOptimizer(learning_rate_G,beta1=0.5).minimize(self._G_loss,\n global_step=self.global_step_G,\n var_list=self.generator._theta)","def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\n if q_args is None and c_args is None:\n raise GateError(\"Gate needs at least one quantum argument or classical argument\")\n if isinstance(gate, CompositeGate):\n if mapping is None:\n raise GateError(\"Must provide arguments mapping for composite gate inside a composite gate.\")\n else:\n inv_mappimg = dict()\n for key, value in mapping.items():\n inv_mappimg[value] = key\n if gate is self:\n gates = gate.copy.gates\n else:\n gates = gate.gates\n for g in gates:\n new_q_args = None\n new_c_args = None\n if g[1] is not None:\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\n if g[2] is not None:\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\n self.add_gate(gate=g[0], q_args=new_q_args,\n c_args=new_c_args, params=g[3])\n else:\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\n raise GateError(\"Gate must be either a CompositeGate or a string from: \"\n \"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\")\n if q_args is not None:\n for q_arg in q_args:\n if q_arg not in self.q_args:\n self.add_q_arg(q_arg)\n if c_args is not None:\n for c_arg in c_args:\n if c_arg not in self.c_args:\n self.add_c_arg(c_arg)\n if params is not None:\n for param in params:\n if param not in self.params:\n self.add_param(param)\n self._gates.append((gate, q_args, c_args, params))","def _insert_CD_state(self, alpha, clear=True):\n # Defines a new thermodynamic state based on the neighboring state\n neighbor_ind = [alpha < p['alpha']\n for p in self.data['CD'].protocol].index(True) - 1\n params_n = self.system.paramsFromAlpha(\n alpha, params_o=self.data['CD'].protocol[neighbor_ind])\n\n # For sampling importance resampling,\n # prepare an augmented matrix for pymbar calculations\n # with a new thermodynamic state\n (u_kln_s, N_k) = self._u_kln(self.data['CD'].Es, self.data['CD'].protocol)\n (K, L, N) = u_kln_s.shape\n\n u_kln_n = self._u_kln(self.data['CD'].Es, [params_n])[0]\n L += 1\n N_k = np.append(N_k, [0])\n\n u_kln = np.zeros([K, L, N])\n u_kln[:, :-1, :] = u_kln_s\n for k in range(K):\n u_kln[k, -1, :] = u_kln_n[k, 0, :]\n\n # Determine SIR weights\n weights = self.run_MBAR(u_kln, N_k, augmented=True)[1][:, -1]\n weights = weights / sum(weights)\n\n # Resampling\n # Convert linear indices to 3 indicies: state, cycle, and snapshot\n cum_N_state = np.cumsum([0] + list(N_k))\n cum_N_cycle = [np.cumsum([0] + [self.data['CD'].Es[k][c]['MM'].shape[0] \\\n for c in range(len(self.data['CD'].Es[k]))]) for k in range(len(self.data['CD'].Es))]\n\n def linear_index_to_snapshot_index(ind):\n state_index = list(ind < cum_N_state).index(True) - 1\n nis_index = ind - cum_N_state[state_index]\n cycle_index = list(nis_index < cum_N_cycle[state_index]).index(True) - 1\n nic_index = nis_index - cum_N_cycle[state_index][cycle_index]\n return (state_index, cycle_index, nic_index)\n\n def snapshot_index_to_linear_index(state_index, cycle_index, nic_index):\n return cum_N_state[state_index] + cum_N_cycle[state_index][\n cycle_index] + nic_index\n\n # Terms to copy\n if self.args.params['CD']['pose'] > -1:\n # Pose BPMF\n terms = ['MM',\\\n 'k_angular_ext','k_spatial_ext','k_angular_int'] + scalables\n else:\n # BPMF\n terms = ['MM', 'site'] + scalables\n\n CD_Es_s = []\n confs_s = []\n for c in range(len(self.data['CD'].Es[0])):\n CD_Es_c = dict([(term, []) for term in terms])\n confs_c = []\n for n_in_c in range(len(self.data['CD'].Es[-1][c]['MM'])):\n if (cum_N_cycle[-1][c] == 0):\n (snapshot_s,snapshot_c,snapshot_n) = linear_index_to_snapshot_index(\\\n np.random.choice(range(len(weights)), size = 1, p = weights)[0])\n else:\n snapshot_c = np.inf\n while (snapshot_c > c):\n (snapshot_s,snapshot_c,snapshot_n) = linear_index_to_snapshot_index(\\\n np.random.choice(range(len(weights)), size = 1, p = weights)[0])\n for term in terms:\n CD_Es_c[term].append(\\\n np.copy(self.data['CD'].Es[snapshot_s][snapshot_c][term][snapshot_n]))\n if self.args.params['CD']['keep_intermediate']:\n # Has not been tested:\n confs_c.append(\\\n np.copy(self.data['CD'].confs['samples'][snapshot_s][snapshot_c]))\n for term in terms:\n CD_Es_c[term] = np.array(CD_Es_c[term])\n CD_Es_s.append(CD_Es_c)\n confs_s.append(confs_c)\n\n # Insert resampled values\n self.data['CD'].protocol.insert(neighbor_ind + 1, params_n)\n self.data['CD'].Es.insert(neighbor_ind + 1, CD_Es_s)\n self.data['CD'].confs['samples'].insert(neighbor_ind + 1, confs_s)\n self.data['CD'].confs['replicas'].insert(neighbor_ind+1, \\\n np.copy(self.data['CD'].confs['replicas'][neighbor_ind]))\n\n if clear:\n self._clear_f_RL()","def dcgain(self):\n raise NotImplementedError(\"dcgain not implemented for %s objects\" %\n str(self.__class__))","def discriminator(self, inpt, reuse, is_train):\n with tf.variable_scope(\"discriminator\"):\n if reuse:\n tf.get_variable_scope().reuse_variables()\n net = conv2d(x=inpt, num_kernels=self.d_init, name=\"conv1\", activation=lkrelu, padding=\"SAME\",\n alpha=0.02, is_train=is_train, stddv=self.stddv)\n net = conv2d(x=net, num_kernels=self.d_init*2, name=\"conv2\", activation=lkrelu, padding=\"SAME\",\n alpha=0.02, is_train=is_train, stddv=self.stddv)\n net = conv2d(x=net, num_kernels=self.d_init*4, name=\"conv3\", activation=lkrelu, padding=\"SAME\",\n alpha=0.02, is_train=is_train, stddv=self.stddv)\n net = conv2d(x=net, num_kernels=self.d_init*8, name=\"conv4\", activation=lkrelu, padding=\"SAME\",\n alpha=0.02, is_train=is_train, stddv=self.stddv)\n net = dense_layer(x=net, num_neurons=1, name=\"output\", activation=tf.identity, is_train=is_train,\n stddv=self.stddv)\n return net","def _build_add(self) -> str:\n return dedent(\n \"\"\"\n @SP\n M=M-1\n A=M\n D=M\n @SP\n M=M-1\n A=M\n M=M+D\n @SP\n M=M+1\n \"\"\"\n )","def user_gate_definition(self, filenum, linenum, txt):\n txt = txt.strip()\n gate_decl = QTRegEx.GATE_DECL.match(txt)\n gate_name = gate_decl.group(1)\n possible_gate_params = gate_name.split('(')\n gate_param_list = None\n if len(possible_gate_params) > 1:\n gate_param_list = possible_gate_params[1].strip(') ').split(',')\n gate_regs = gate_decl.group(2).strip(\"{}\") # watch out for no space before '{' !!\n gate_reg_list = gate_regs.split(',')\n gate_ops = QTRegEx.GATE_OPS.match(txt)\n gate_ops_raw_list = QTRegEx.GATE_OPS_LIST.findall(gate_ops.group(1))\n gate_ops_list = []\n for op_raw in gate_ops_raw_list:\n op_raw = op_raw.strip()\n op = QTRegEx.GATE_OP.match(op_raw).group(1)\n op_params = QTRegEx.GATE_OP_PARAMS.match(op_raw)\n if op_params:\n op_param_list = op_params.group(1).split(',')\n else:\n op_param_list = None\n op_regs = QTRegEx.GATE_OP_REGS.match(op_raw)\n if op_regs:\n op_reg_list = op_regs.group(1).split(',')\n else:\n op_reg_list = None\n gate_ops_list.append({'op': op,\n 'op_param_list': op_param_list,\n 'op_reg_list': op_reg_list})\n gate = {'source': txt if self.save_gate_source else None,\n 'filenum': filenum,\n 'linenum': linenum, 'gate_name': gate_name,\n 'gate_param_list': gate_param_list,\n 'gate_ops_raw_list': gate_ops_raw_list,\n 'gate_ops_list': gate_ops_list,\n 'gate_reg_list': gate_reg_list}\n\n self.append_user_gate(gate)","def set_ddg_flag(self, is_new_hunk):\n Gumtree.gumtree.setDDGFlag(is_new_hunk)","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def dbgain_from_pt(self, grid=None, pt_1=None):\n assert pt_1 is not None\n assert grid is not None\n\n def dbgain(pt_2):\n return [self.dbgain(pt_1, pt_2)]\n\n return FunctionVectorField(grid=grid, fun=dbgain)","def layer(i):\n with tf.name_scope('layer_{}'.format(i)):\n # displacement gate\n Dgate(tf.clip_by_value(d_r[i], -disp_clip, disp_clip), d_phi[i]) | q[0]\n # rotation gate\n Rgate(r1[i]) | q[0]\n # squeeze gate\n Sgate(tf.clip_by_value(sq_r[i], -sq_clip, sq_clip), sq_phi[i]) | q[0]\n # rotation gate\n Rgate(r2[i]) | q[0]\n # Kerr gate\n Kgate(tf.clip_by_value(kappa1[i], -kerr_clip, kerr_clip)) | q[0]","def add_state(self, state):\n if self.rate_variation:\n if not self.feature_rates:\n # Set all rates to 1.0 in a big plate\n plate = ET.SubElement(state, \"plate\", {\n \"var\":\"feature\",\n \"range\":\",\".join(self.features)})\n param = ET.SubElement(plate, \"parameter\", {\n \"id\":\"featureClockRate:%s:$(feature)\" % self.name,\n \"name\":\"stateNode\"})\n param.text=\"1.0\"\n else:\n # Give each rate a custom value\n for f in self.features:\n param = ET.SubElement(state, \"parameter\", {\n \"id\":\"featureClockRate:%s:%s\" % (self.name, f),\n \"name\":\"stateNode\"})\n param.text=str(self.feature_rates.get(f,1.0))\n\n # Give Gamma shape parameter a finite domain\n # Must be > 1.0 for the distribution to be bell-shaped,\n # rather than L-shaped. The domain [1.1,1000] limits feature\n # rate variation to the realms of vague plausibity\n parameter = ET.SubElement(state, \"parameter\", {\"id\":\"featureClockRateGammaShape:%s\" % self.name, \"lower\":\"1.1\",\"upper\":\"100.0\",\"name\":\"stateNode\"})\n parameter.text=\"5.0\"\n # Gamma scale parameter's domain is defined *implicilty*\n # by the fact that the operators maintain shape*scale = 1.0\n parameter = ET.SubElement(state, \"parameter\", {\"id\":\"featureClockRateGammaScale:%s\" % self.name, \"name\":\"stateNode\"})\n parameter.text=\"0.2\"","def test_tdg_gate_nondeterministic_default_basis_gates(self):\n shots = 2000\n circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic(final_measure=True)\n targets = ref_non_clifford.tdg_gate_counts_nondeterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots)\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)","def add_dcdisorder(self):\n # Add gaussian noise to pinning energies\n if self.lp['V0_pin_gauss'] > 0:\n self.Omg += self.lp['V0_pin_gauss']*np.random.randn(len(self.xy_inner))\n raise RuntimeError('Adding gaussian disorder: are you sure you want to proceed?')\n if self.lp['V0_spring_gauss'] > 0:\n print 'This is not done correctly here'\n self.OmK += self.lp['V0_spring_gauss'] * np.random.randn(np.shape(self.lattice.KL)[0],\n np.shape(self.lattice.KL)[1])\n sys.exit()\n\n if self.lp['V0_pin_flat'] > 0 or self.lp['V0_spring_flat'] > 0:\n # Note that we multiply by two so that V0_pin_flat is the HALF width of the distribution\n flat_disorder = (np.random.rand(len(self.xy_inner))) * 2 - 1.0\n\n if self.lp['V0_pin_flat'] > 0:\n self.Omg += self.lp['V0_pin_flat'] * flat_disorder\n if self.lp['Omg'] < 0:\n self.Omg[self.Omg > 0] = 0.\n elif self.lp['Omg'] > 0:\n self.Omg[self.Omg < 0] = 0.\n\n print('magnetic_gyro_lattice_class.py: V0_pin_flat=', self.lp['V0_pin_flat'])\n print(self.Omg)\n\n if self.lp['V0_spring_flat'] > 0:\n to_add = self.lp['V0_spring_flat'] * flat_disorder[:, np.newaxis] * np.ones_like(self.OmK)\n self.OmK[np.abs(self.OmK) > 0] += to_add[np.abs(self.OmK) > 0]\n if self.lp['Omk'] < 0:\n self.OmK[self.OmK > 0] = 0.\n elif self.lp['Omk'] > 0:\n self.OmK[self.OmK < 0] = 0.\n\n print('magnetic_gyro_lattice_class.py: OmK after flat disorder= ')\n print(self.OmK)\n # sys.exit()","def grads(self, inputs):","def GAStep(self):\n\n self.updateMatingPool()\n self.newGeneration()","def computeCLgainRemoveNodeD(self, G, PD, nodes, node, dropLidx, dir):\n CL_I = 0.0\n CL_F = 0.0\n if dir==2:\n for i in nodes:\n pos_I = PD.getPOS(node, i, case=2, isSimple=self.isSimple)\n pos_F = PD.getPOS(node, i, case=4, isSimple=self.isSimple, dropLidx=dropLidx)\n if pos_I < 0.0000000001:\n pos_I = 0.0000000001\n elif pos_I > 1.0 - 0.0000000001:\n pos_I = 1.0 - 0.0000000001\n if pos_F < 0.0000000001:\n pos_F = 0.0000000001\n elif pos_F > 1.0 - 0.0000000001:\n pos_F = 1.0 - 0.0000000001\n numE = G.number_of_edges(node, i)\n if self.isSimple:\n CL_I += math.log2(math.pow(1.0-pos_I, 1.0-numE)*math.pow(pos_I, numE))\n CL_F += math.log2(math.pow(1.0-pos_F, 1.0-numE)*math.pow(pos_F, numE))\n else:\n CL_I += math.log2(math.pow(1.0-pos_I, numE)*pos_I)\n CL_F += math.log2(math.pow(1.0-pos_F, numE)*pos_F)\n elif dir==1:\n for i in nodes:\n pos_I = PD.getPOS(i, node, case=2, isSimple=self.isSimple)\n pos_F = PD.getPOS(i, node, case=4, isSimple=self.isSimple, dropLidx=dropLidx)\n if pos_I < 0.0000000001:\n pos_I = 0.0000000001\n elif pos_I > 1.0 - 0.0000000001:\n pos_I = 1.0 - 0.0000000001\n if pos_F < 0.0000000001:\n pos_F = 0.0000000001\n elif pos_F > 1.0 - 0.0000000001:\n pos_F = 1.0 - 0.0000000001\n numE = G.number_of_edges(i, node)\n if self.isSimple:\n CL_I += math.log2(math.pow(1.0-pos_I, 1.0-numE)*math.pow(pos_I, numE))\n CL_F += math.log2(math.pow(1.0-pos_F, 1.0-numE)*math.pow(pos_F, numE))\n else:\n CL_I += math.log2( math.pow( 1.0-pos_I, numE )*pos_I )\n CL_F += math.log2( math.pow( 1.0-pos_F, numE )*pos_F )\n return -CL_I - (-CL_F)","def DiagonalGate():\n\n def f(x): # pylint: disable=invalid-name\n # x : [batch, 1, length, depth]\n x = jnp.pad(x, [(0, 0), (0, 0), (1, 1), (0, 0)],\n mode='constant', constant_values=0.0)\n depth = x.shape[-1] // 3\n assert 3 * depth == x.shape[-1], ('Depth must be divisible by 3', depth,\n x.shape)\n xs = [\n x[:, :, :-2, :depth], x[:, :, 1:-1, depth:2 * depth],\n x[:, :, 2:, 2 * depth:3 * depth]\n ]\n return jnp.concatenate(xs, axis=3)\n return tl.Fn('DiagonalGate', f)","def DynamicsCoop(x, t, T0, alpha, cost, K, n, r):\n \n #defune the degradation effect\n deg=fmax*x[1]/(x[1]+Kd)\n D=dmax*x[0]**n/(x[0]**n+K**n)\n #define ODEs\n y=np.zeros([np.size(x)])\n y[0]=alpha*T0-deg*x[0]-alpha*x[0] #dt/dt\n y[1]=x[1]*(r*(1-cost)*(1-x[1])-D-alpha)#d Co/dt\n \n return y","def _add_grover_step_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n _add_2_bit_oracle_without_ancilla_1_0(qc, register) # Oracle\n add_grover_reflection_no_ancilla(qc, register) # Reflection","def addDielectric(default_dielectric=20):\n \n parser.add_option(\"-D\",\"--dielectric\",action=\"store\",type=\"float\",\n dest=\"dielectric\",\n help=\"Dielectric constant for UHBD calculations (default=20)\",\n default=default_dielectric)","def alg(c):\n return c[0]*G[0] + c[1]*G[1] + c[2]*G[2]","def add_operators(self, run):\n if self.rate_variation:\n # UpDownOperator to scale the Gamma distribution for this model's\n # feature rates\n updown = ET.SubElement(run, \"operator\", {\"id\":\"featureClockRateGammaUpDown:%s\" % self.name, \"spec\":\"UpDownOperator\", \"scaleFactor\":\"0.5\",\"weight\":\"0.3\"})\n ET.SubElement(updown, \"parameter\", {\"idref\":\"featureClockRateGammaShape:%s\" % self.name, \"name\":\"up\"})\n ET.SubElement(updown, \"parameter\", {\"idref\":\"featureClockRateGammaScale:%s\" % self.name, \"name\":\"down\"})","def add_dart(self):\r\n dart_id = self.maxid\r\n for i in self.alphas:\r\n self.alphas[i][dart_id] = dart_id\r\n self.maxid = dart_id +1\r\n return dart_id","def add_carboxyl(atom, atom_list, added_functional_groups, ct):\n \n global anywhere_map\n global edge_map\n current_size = len(atom_list)\n placed = 0\n alpha = random.randint(0,359)\n x = atom.x\n y = atom.y\n z = atom.z\n while (placed <= 359):\n alpha += 1\n carbon_atom = Atom(current_size + 1, 'C4', 'C1A', str(added_functional_groups + 1), float(\"{0:.3f}\".format(x)), float(\"{0:.3f}\".format(y)), float(\"{0:.3f}\".format(ct * 1.52 + z)))\n atom_list.append(carbon_atom)\n if ((len(identify_bonds(carbon_atom, atom_list)) == 1) and (identify_bonds(carbon_atom, atom_list)[0][0].atom_number == atom.atom_number)):\n h = math.sin(math.radians(60)) * 1.20\n oxygen_atom_1 = Atom(current_size + 2, 'OJ', 'C1A', str(added_functional_groups + 1), float(\"{0:.3f}\".format(carbon_atom.x - math.cos(math.radians(alpha)) * h)), float(\"{0:.3f}\".format(carbon_atom.y - math.sin(math.radians(alpha)) * h)), float(\"{0:.3f}\".format(carbon_atom.z + ct * math.cos(math.radians(60)) * 1.20)))\n atom_list.append(oxygen_atom_1)\n if ((len(identify_bonds(oxygen_atom_1, atom_list)) == 1) and (identify_bonds(oxygen_atom_1, atom_list)[0][0].atom_number == carbon_atom.atom_number)):\n h = math.sin(math.radians(60)) * 1.34\n oxygen_atom_2 = Atom(current_size + 3, 'OK', 'C1A', str(added_functional_groups + 1), float(\"{0:.3f}\".format(carbon_atom.x - math.cos(math.radians(alpha + 180)) * h)), float(\"{0:.3f}\".format(carbon_atom.y - math.sin(math.radians(alpha+180)) * h)), float(\"{0:.3f}\".format(carbon_atom.z + ct * math.cos(math.radians(60)) * 1.34)) )\n atom_list.append(oxygen_atom_2)\n if ((len(identify_bonds(oxygen_atom_2, atom_list)) == 1) and (identify_bonds(oxygen_atom_2, atom_list)[0][0].atom_number == carbon_atom.atom_number)):\n hydrogen_atom = Atom(current_size + 4, 'HK', 'C1A', str(added_functional_groups + 1), float(\"{0:.3f}\".format(oxygen_atom_2.x)), float(\"{0:.3f}\".format(oxygen_atom_2.y)), float(\"{0:.3f}\".format(oxygen_atom_2.z+ct*0.98)))\n atom_list.append(hydrogen_atom)\n if ((len(identify_bonds(hydrogen_atom, atom_list)) == 1) and (identify_bonds(hydrogen_atom, atom_list)[0][0].atom_number == oxygen_atom_2.atom_number)):\n placed = 888\n if atom in edge_map: edge_map.remove(atom)\n if atom in anywhere_map: anywhere_map.remove(atom)\n CY = Atom(atom.atom_number, 'CY', 'C1A', carbon_atom.residue_number, atom.x, atom.y, atom.z)\n atom_list.append(CY)\n atom_list.remove(atom)\n del atom\n else:\n placed += 5\n del hydrogen_atom\n del atom_list[current_size + 3]\n del oxygen_atom_2\n del atom_list[current_size + 2]\n del oxygen_atom_1\n del atom_list[current_size + 1]\n del carbon_atom\n del atom_list[current_size + 0]\n else:\n placed += 5\n del oxygen_atom_2\n del atom_list[current_size + 2]\n del oxygen_atom_1\n del atom_list[current_size + 1]\n del carbon_atom\n del atom_list[current_size + 0]\n else:\n placed += 5\n del oxygen_atom_1\n del atom_list[current_size + 1]\n del carbon_atom\n del atom_list[current_size + 0]\n else:\n placed += 5\n del carbon_atom \n del atom_list[current_size + 0]\n return atom_list","def add():\n pass","def add_connector(self):\n \n no = len(self.connectors)\n state = {}\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % no\n \n if len(self.connectors)>0:\n state = self.connectors[-1].get_state()\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % (no)\n else:\n if self.mount == self.MOUNT_THT:\n state[\"p_shape\"] = Con.SHAPE_HOLE\n elif self.mount == self.MOUNT_SMD:\n state[\"p_shape\"] = Con.SHAPE_PAD\n \n c = Con(no)\n c.set_state(state) \n \n self.sch_layers[\"pins\"].add(c.s_svg)\n self.pcb_layers[\"copper1\"].add(c.p_svg)\n self.connectors.append(c)","def GED_n(Gn, lib='gedlibpy', cost='CHEM_1', method='IPFP',\n edit_cost_constant=[], stabilizer='min', repeat=50):\n if lib == 'gedlibpy':\n def convertGraph(G):\n \"\"\"Convert a graph to the proper NetworkX format that can be\n recognized by library gedlibpy.\n \"\"\"\n G_new = nx.Graph()\n for nd, attrs in G.nodes(data=True):\n G_new.add_node(str(nd), chem=attrs['atom_symbol'])\n for nd1, nd2, attrs in G.edges(data=True):\n # G_new.add_edge(str(nd1), str(nd2), valence=attrs['bond_type'])\n G_new.add_edge(str(nd1), str(nd2))\n\n return G_new\n\n # gedlibpy.restart_env()\n gedlibpy.add_nx_graph(convertGraph(g1), \"\")\n gedlibpy.add_nx_graph(convertGraph(g2), \"\")\n\n listID = gedlibpy.get_all_graph_ids()\n gedlibpy.set_edit_cost(cost, edit_cost_constant=edit_cost_constant)\n gedlibpy.init()\n gedlibpy.set_method(method, \"\")\n gedlibpy.init_method()\n\n g = listID[0]\n h = listID[1]\n if stabilizer == None:\n gedlibpy.run_method(g, h)\n pi_forward = gedlibpy.get_forward_map(g, h)\n pi_backward = gedlibpy.get_backward_map(g, h)\n upper = gedlibpy.get_upper_bound(g, h)\n lower = gedlibpy.get_lower_bound(g, h)\n elif stabilizer == 'min':\n upper = np.inf\n for itr in range(repeat):\n gedlibpy.run_method(g, h)\n upper_tmp = gedlibpy.get_upper_bound(g, h)\n if upper_tmp < upper:\n upper = upper_tmp\n pi_forward = gedlibpy.get_forward_map(g, h)\n pi_backward = gedlibpy.get_backward_map(g, h)\n lower = gedlibpy.get_lower_bound(g, h)\n if upper == 0:\n break\n\n dis = upper\n\n # make the map label correct (label remove map as np.inf)\n nodes1 = [n for n in g1.nodes()]\n nodes2 = [n for n in g2.nodes()]\n nb1 = nx.number_of_nodes(g1)\n nb2 = nx.number_of_nodes(g2)\n pi_forward = [nodes2[pi] if pi < nb2 else np.inf for pi in pi_forward]\n pi_backward = [nodes1[pi] if pi <\n nb1 else np.inf for pi in pi_backward]\n\n return dis, pi_forward, pi_backward","def _insert_op(self, op):","def test_tdg_gate_deterministic_minimal_basis_gates(self):\n shots = 100\n circuits = ref_non_clifford.tdg_gate_circuits_deterministic(final_measure=True)\n targets = ref_non_clifford.tdg_gate_counts_deterministic(shots)\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\n result = job.result()\n self.is_completed(result)\n self.compare_counts(result, circuits, targets, delta=0)","def add_epoxy(atom, atom_list, added_functional_groups, ct):\n global anywhere_map\n global edge_map\n current_size = len(atom_list)\n list_of_n = [x[0] for x in identify_bonds(atom, atom_list) if (x[0].atom_name != \"CY\")]\n if (len(list_of_n) != 0):\n atom2 = random.choice(list_of_n)\n epoxy_atom = Atom( current_size + 1, 'OE', 'E1A', str(added_functional_groups + 1), float(\"{0:.3f}\".format(abs(atom.x - atom2.x) / 2 + min(atom.x, atom2.x))), float(\"{0:.3f}\".format(abs(atom.y - atom2.y) / 2 + min(atom.y, atom2.y))), float(\"{0:.3f}\".format(ct * 1.46 * math.sin(math.radians(60)))) )\n atom_list.append(epoxy_atom)\n if ((len(identify_bonds(epoxy_atom, atom_list)) == 2) and ((identify_bonds(epoxy_atom, atom_list)[0][0].atom_number == atom.atom_number) or (identify_bonds(epoxy_atom, atom_list)[1][0].atom_number == atom.atom_number)) and ((identify_bonds(epoxy_atom, atom_list)[0][0].atom_number == atom2.atom_number) or ((identify_bonds(epoxy_atom, atom_list)[1][0].atom_number == atom2.atom_number)))):\n CY = Atom(atom.atom_number, 'CY', 'E1A', epoxy_atom.residue_number, atom.x, atom.y, atom.z)\n CY2 = Atom(atom2.atom_number, 'CZ', 'E1A', epoxy_atom.residue_number, atom2.x, atom2.y, atom2.z)\n atom_list.remove(atom); atom_list.remove(atom2)\n atom_list.append(CY); atom_list.append(CY2) \n if atom in edge_map: edge_map.remove(atom)\n if atom in anywhere_map: anywhere_map.remove(atom)\n if atom2 in edge_map: edge_map.remove(atom2)\n if atom2 in anywhere_map: anywhere_map.remove(atom2)\n else:\n atom_list.remove(epoxy_atom)\n del epoxy_atom\n return atom_list","def differentiate(hp):\n if hp.force_skip:\n G.add_edge(\"input\", \"output\")\n for node in G.nodes(data=True):\n node_id, node_data = node\n log(\"differentiate\", node_id, node_data)\n node_data[\"output\"] = None\n node_data[\"op\"] = None\n if node_data[\"shape\"] is \"square\" or \"output\" in node_id:\n if node_id == \"output\":\n d_out = node_data[\"output_shape\"][-1]\n node_type = hp.last_layer\n activation = \"tanh\"\n else:\n node_type = str(np.random.choice(['sepconv1d', 'transformer',\n 'k_conv1', 'k_conv2', 'k_conv3',\n \"deep\", \"wide_deep\"],\n 1, p=hp.layer_distribution).item(0))\n activation = str(np.random.choice([ 'tanh', 'linear', 'relu', 'selu',\n 'elu', 'sigmoid', 'hard_sigmoid', 'exponential', 'softmax',\n 'softplus', 'softsign', 'gaussian', 'sin', 'cos', 'swish'],\n 1, p=hp.activation_distribution).item(0))\n d_out = None\n node_data[\"force_residual\"] = random.random() < hp.p_force_residual\n node_data[\"activation\"] = clean_activation(activation)\n node_data[\"node_type\"] = node_type\n node_data['style'] = \"\"\n if node_type == 'sepconv1d':\n if d_out is None:\n d_out = safe_sample(hp.min_filters, hp.max_filters)\n node_data[\"filters\"] = d_out\n node_data[\"kernel_size\"] = 1\n if node_type == \"transformer\":\n if d_out is None:\n d_out = safe_sample(hp.min_units, hp.max_units) * hp.attn_heads\n node_data[\"d_model\"] = d_out\n node_data[\"n_heads\"] = 2 if d_out % 2 == 0 else 1\n if \"k_conv\" in node_type or node_type in [\"deep\", \"wide_deep\"]:\n layers = design_layers(hp, d_out, activation)\n if d_out is None:\n d_out = layers[-1][0]\n node_data[\"stddev\"] = hp.stddev\n node_data['layers'] = layers\n node_data[\"d_out\"] = d_out\n if node_type in [\"deep\", \"wide_deep\"]:\n node_data['kernel'] = node_type\n else:\n node_data['kernel'] = \"wide_deep\" if random.random() < hp.p_wide_deep else \"deep\"\n label = f\"{node_type}\"\n log(f\"set {node_id} to {label}\")\n node_data[\"label\"] = label\n node_data[\"color\"] = \"green\"\n # we handle recurrent shapes:\n try:\n feedback_node_id = f\"{node_id}_feedback\"\n input_shape = (None, d_out)\n log(f\"attempt to set input_shape for {feedback_node_id} to {input_shape}\")\n feedback_node = G.node[feedback_node_id]\n feedback_node[\"input_shape\"] = input_shape\n node_data[\"gives_feedback\"] = True\n except Exception as e:\n log(\"ERROR HANDLING FEEDBACK SHAPE:\", e)","def compute_gains(self, t, add_noise=True):\n #get the basis funtion at a time step\n basis, Dbasis = self.get_basis(t)\n\n if t < self._time_steps-1:\n basis_t_dt, _ = self.get_basis(t+1)\n else:\n basis_t_dt = np.zeros_like(basis)\n\n\n #part 1 equation 46\n B_pseudo = np.linalg.pinv(self._B)\n\n #equation 12 for t\n Sigma_t = np.dot(np.dot(basis, self._sigma_W), basis.T)\n\n #equation 12 for t+dt\n Sigma_t_dt = np.dot(np.dot(basis_t_dt, self._sigma_W), basis_t_dt.T)\n\n #Cross correlation between t, t+dt, Equation 49\n Ct = np.dot(np.dot(basis, self._sigma_W), basis_t_dt.T)\n\n #System noise Equation 51\n Sigma_s = (1./self._dt)* ( Sigma_t_dt - np.dot( np.dot( Ct.T, np.linalg.inv(Sigma_t) ), Ct) )\n\n #control noise Equation 52\n Sigma_u = np.dot(np.dot(B_pseudo, Sigma_s), B_pseudo.T)\n\n #part 2 equation 46\n tmp1 = np.dot(np.dot(Dbasis, self._sigma_W), basis.T)\n\n #part 3 equation 46\n tmp2 = np.dot(self._A, Sigma_t) + 0.5*Sigma_s\n\n #compute feedback gain; complete equation 46\n K = np.dot( np.dot(B_pseudo, (tmp1-tmp2) ), np.linalg.inv(Sigma_t))\n\n #part 1 equation 48\n tmp3 = np.dot(Dbasis, self._mean_W)\n\n #part 2 equation 48\n tmp4 = np.dot( (self._A + np.dot(self._B, K)), np.dot(basis, self._mean_W) )\n\n #compute feedforward gain; complete equation 48\n k = np.dot(B_pseudo, (tmp3-tmp4))\n\n return K, k, Sigma_u","def test_superposition_ud_cnot():\n program = dedent(\n \"\"\"\\\n register q0[0]\n register q1[1]\n H q1\n CNOT q1 q0\n \"\"\"\n )\n\n result = run(program, run_gate_array, return_distribution=True)\n assert isclose(result, [0.5, 0.0, 0.0, 0.5]).all()"],"string":"[\n \"def build_glyCB(self, gCBd: Dihedron): # -> None:\\n ...\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def add_dut(self):\\n pass\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def test_append_dangling_gate(self, circuit):\\n match = (\\n r\\\"Number of wire IDs \\\\(2\\\\) must match the number of wires connected to the gate \\\\(1\\\\).\\\"\\n )\\n gate = jet.GateFactory.create(\\\"H\\\")\\n with pytest.raises(ValueError, match=match):\\n circuit.append_gate(gate, wire_ids=[0, 1])\",\n \"def train_dagger(): # add arguments as needed\\n pass\",\n \"def gate(self):\\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def glycosylate(self):\\n chid = self.chain.get()\\n sequon = self.sequon.get()\\n self.sequon_colors[sequon] = [.7, .1, 0]\\n key = self.sequon.get()\\n residue = self.myGlycosylator.get_residue(key)\\n #Build new glycan\\n if self.selected_glycan:\\n self.myGlycosylator.connect_topology['SELECTED'] = self.selected_glycan[1]\\n #build from current glycan\\n if key in self.original_glycans:\\n original_glycan = self.original_glycanMolecules[key].atom_group\\n r,t = self.original_glycans[key]\\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\\n else:\\n original_glycan = None\\n connect_tree = None \\n #Use current glycan\\n else:\\n original_glycan = self.original_glycanMolecules[key]\\n r,t = self.original_glycans[key]\\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\\n self.myGlycosylator.connect_topology['SELECTED'] = self.myGlycosylator.build_connect_topology(original_glycan) \\n original_glycan = original_glycan.atom_group\\n \\n segname = 'G'+key.split(',')[2]\\n glycan,bonds = self.myGlycosylator.glycosylate('SELECTED', \\n template_glycan_tree = connect_tree, \\n template_glycan = original_glycan,\\n link_residue=residue, link_patch = 'NGLB', chain = 'G', segname=segname)\\n new_glycan = glc.Molecule(key)\\n new_glycan.set_AtomGroup(glycan, bonds = bonds)\\n self.myGlycosylator.assign_patches(new_glycan)\\n self.linked_glycanMolecules[key] = new_glycan\\n self.linked_glycans[key] = [new_glycan.rootRes, new_glycan.interresidue_connectivity]\\n self.names.update(new_glycan.get_names())\\n # Update glycoprotein and sequon panels\\n self.draw_glycoprotein(chid)\\n self.draw_glycan(sequon)\",\n \"def cs_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def load_gates(chip):\\n for gate_id in chip.gates:\\n gate_coord = chip.gates[gate_id]\\n gate = gt.Gate(gate_id, gate_coord[\\\"x\\\"], gate_coord[\\\"y\\\"])\\n chip.coordinates[0][gate_coord[\\\"y\\\"]][gate_coord[\\\"x\\\"]].gate = gate\\n\\n return chip\",\n \"def __init__(self, input, output) :\\n Gate.__init__(self, [input], output)\",\n \"def _add_entanglement_gate(self, gate_method, qubit_1, qubit_2):\\r\\n sig = signature(gate_method)\\r\\n\\r\\n # parametrized gate like a controlled single qubit rotation\\r\\n if 'theta' in sig.parameters:\\r\\n try:\\r\\n gate_method(self.circuit, self.parameters[next(self.indices)], qubit_1, qubit_2)\\r\\n except KeyError:\\r\\n raise ValueError(f'Unsupported two qubit rotation gate')\\r\\n\\r\\n # non-parametrized gate like CNOT\\r\\n else:\\r\\n try:\\r\\n gate_method(self.circuit, qubit_1, qubit_2)\\r\\n except KeyError:\\r\\n raise ValueError(f'Unsupported unparametrized two qubit gate')\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def make_gate_output(self, ungate=[]):\\n\\n pattern = self.gate_output.activator.off * np.ones((self.gate_output.size,1))\\n\\n # Ungate provided keys\\n for k in self.default_gates + ungate:\\n i = self.gate_map.get_gate_index(k)\\n pattern[i,0] = self.gate_output.activator.on\\n\\n return pattern\",\n \"def _process_gate(self, node, opaque=False):\\n self.gates[node.name] = {}\\n de_gate = self.gates[node.name]\\n de_gate[\\\"opaque\\\"] = opaque\\n de_gate[\\\"n_args\\\"] = node.n_args()\\n de_gate[\\\"n_bits\\\"] = node.n_bits()\\n if node.n_args() > 0:\\n de_gate[\\\"args\\\"] = [element.name for element in node.arguments.children]\\n else:\\n de_gate[\\\"args\\\"] = []\\n de_gate[\\\"bits\\\"] = [c.name for c in node.bitlist.children]\\n if opaque:\\n de_gate[\\\"body\\\"] = None\\n else:\\n de_gate[\\\"body\\\"] = node.body\\n self.backend.define_gate(node.name, copy.deepcopy(de_gate))\",\n \"def _add_pairblend(self, dgmod, rigid, transform):\\n\\n assert isinstance(dgmod, cmdx.DGModifier)\\n\\n pair_blend = dgmod.create_node(\\\"pairBlend\\\")\\n dgmod.set_attr(pair_blend[\\\"isHistoricallyInteresting\\\"], False)\\n\\n # Establish initial values, before keyframes\\n # tm = cmdx.Tm(self._cache[(transform, \\\"matrix\\\")])\\n\\n # Read from matrix, as opposed to the rotate/translate channels\\n # to account for jointOrient, pivots and all manner of things\\n # translate = tm.translation()\\n # rotate = tm.rotation()\\n\\n translate = self._cache[(transform, \\\"translate\\\")]\\n rotate = self._cache[(transform, \\\"rotate\\\")]\\n\\n dgmod.set_attr(pair_blend[\\\"inTranslate1\\\"], translate)\\n dgmod.set_attr(pair_blend[\\\"inRotate1\\\"], rotate)\\n\\n dgmod.connect(rigid[\\\"outputTranslateX\\\"], pair_blend[\\\"inTranslateX2\\\"])\\n dgmod.connect(rigid[\\\"outputTranslateY\\\"], pair_blend[\\\"inTranslateY2\\\"])\\n dgmod.connect(rigid[\\\"outputTranslateZ\\\"], pair_blend[\\\"inTranslateZ2\\\"])\\n dgmod.connect(rigid[\\\"outputRotateX\\\"], pair_blend[\\\"inRotateX2\\\"])\\n dgmod.connect(rigid[\\\"outputRotateY\\\"], pair_blend[\\\"inRotateY2\\\"])\\n dgmod.connect(rigid[\\\"outputRotateZ\\\"], pair_blend[\\\"inRotateZ2\\\"])\\n\\n # Let the animator see the raw animation values, no physics\\n dgmod.connect(self._tree_root[0][\\\"simulated\\\"], pair_blend[\\\"weight\\\"])\\n\\n if self._opts[\\\"autoKey\\\"]:\\n # Generate default animation curves, it's expected since you can no\\n # longer see whether channels are keyed or not, now being green.\\n time = cmdx.currentTime()\\n mapping = (\\n (\\\"animCurveTL\\\", translate.x, \\\"inTranslateX1\\\"),\\n (\\\"animCurveTL\\\", translate.y, \\\"inTranslateY1\\\"),\\n (\\\"animCurveTL\\\", translate.z, \\\"inTranslateZ1\\\"),\\n (\\\"animCurveTA\\\", rotate.x, \\\"inRotateX1\\\"),\\n (\\\"animCurveTA\\\", rotate.y, \\\"inRotateY1\\\"),\\n (\\\"animCurveTA\\\", rotate.z, \\\"inRotateZ1\\\")\\n )\\n\\n for curve, value, dst in mapping:\\n curve = dgmod.create_node(curve)\\n curve.key(time, value)\\n dgmod.connect(curve[\\\"output\\\"], pair_blend[dst])\\n\\n # Transfer existing animation/connections\\n for src, dst in transform.data.get(\\\"priorConnections\\\", {}).items():\\n dst = pair_blend[dst]\\n dgmod.connect(src, dst)\\n\\n commands._connect_transform(dgmod, pair_blend, transform)\\n\\n return pair_blend\",\n \"def add_junction(ccTremb):\\n pass\",\n \"def __init__(self, input0, input1, output) :\\n Gate.__init__(self, [input0,input1], output)\",\n \"def dagger(self) -> Cup:\\n return self.cup_factory(self.left, self.right)\",\n \"def build_gate_1(gate, tags=None):\\n\\n def apply_constant_single_qubit_gate(psi, i, **gate_opts):\\n mtags = _merge_tags(tags, gate_opts)\\n psi.gate_(gate, int(i), tags=mtags, **gate_opts)\\n\\n return apply_constant_single_qubit_gate\",\n \"def _auto_blend(self, dgmod):\\n\\n assert isinstance(dgmod, cmdx.DGModifier)\\n\\n root, _ = self._root\\n root_rigid = root.shape(type=\\\"rdRigid\\\")\\n\\n for rigid in self._new_rigids:\\n\\n # Don't bother with the root\\n if rigid == root_rigid:\\n continue\\n\\n transform = rigid.parent()\\n blend = self._add_pairblend(dgmod, rigid, transform)\\n self._auto_influence(dgmod, rigid, blend)\",\n \"def construct_TDI(self, t, Orbit):\\n\\t\\n\\tself.make_padded_delta_l(t)\\n\\n\\tp12 = td.Phase(1,2, t, self.delta_l_padded[0,1,:])\\n\\tp21 = td.Phase(2,1, t, self.delta_l_padded[1,0,:])\\n\\n\\tp13 = td.Phase(1,3, t, self.delta_l_padded[0,2,:])\\n\\tp31 = td.Phase(3,1, t, self.delta_l_padded[2,0,:])\\n\\n\\tp23 = td.Phase(2,3, t, self.delta_l_padded[1,2,:])\\n\\tp32 = td.Phase(3,2, t, self.delta_l_padded[2,1,:])\\n \\n\\tp12.FT_phase(Orbit)\\n\\tp21.FT_phase(Orbit)\\n\\tp13.FT_phase(Orbit)\\n\\tp31.FT_phase(Orbit)\\n\\tp23.FT_phase(Orbit)\\n\\tp32.FT_phase(Orbit)\\n\\n\\ttdi_GW = td.TDI(p12, p21, p13, p31, p23, p32, Orbit)\\n\\t\\n\\treturn tdi_GW\",\n \"def append_user_gate(self, user_gate):\\n self.translation['g_sect'].append(user_gate)\",\n \"def triplicateBlck(self, blck_id):\\n # Eliminating basic outlier conditions\\n if blck_id not in self.dGrph:\\n print('blck_id: ', blck_id, ' does not exist. Triplication aborted.')\\n return\\n\\n # identifying the type of block and triplicating\\n test = len(self.dGrph[blck_id][1])\\n if test == 3: # ari block\\n ip = self.dGrph[blck_id][0]\\n config = self.dGrph[blck_id][2]\\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\\n new_ops = []\\n for i in range(3):\\n temp_op = []\\n for original_op in self.dGrph[blck_id][1]:\\n temp_op.append([original_op[0]+'_trip728'+str(i), None])\\n new_ops.append(temp_op)\\n\\n self.dGrph[new_ids[0]] = [ip, new_ops[0], config]\\n self.dGrph[new_ids[1]] = [ip, new_ops[1], config]\\n self.dGrph[new_ids[2]] = [ip, new_ops[2], config]\\n\\n # for first output\\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0][0], new_ops[1][0][0]], new_ids[0]+'_and0_o')\\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0][0], new_ops[2][0][0]], new_ids[1]+'_and0_o')\\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0][0], new_ops[2][0][0]], new_ids[2]+'_and0_o')\\n\\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0][0])\\n\\n # for second output\\n self.__addGate(new_ids[0]+'_and1', 'A', [new_ops[0][1][0], new_ops[1][1][0]], new_ids[0]+'_and1_o')\\n self.__addGate(new_ids[1]+'_and1', 'A', [new_ops[0][1][0], new_ops[2][1][0]], new_ids[1]+'_and1_o')\\n self.__addGate(new_ids[2]+'_and1', 'A', [new_ops[1][1][0], new_ops[2][1][0]], new_ids[2]+'_and1_o')\\n\\n self.__addGate(new_ids[0]+'_or1', 'O', [new_ids[0]+'_and1_o', new_ids[1]+'_and1_o', new_ids[2]+'_and1_o'], self.dGrph[blck_id][1][1][0])\\n\\n # for third output\\n self.__addGate(new_ids[0]+'_and2', 'A', [new_ops[0][2][0], new_ops[1][2][0]], new_ids[0]+'_and2_o')\\n self.__addGate(new_ids[1]+'_and2', 'A', [new_ops[0][2][0], new_ops[2][2][0]], new_ids[1]+'_and2_o')\\n self.__addGate(new_ids[2]+'_and2', 'A', [new_ops[1][2][0], new_ops[2][2][0]], new_ids[2]+'_and2_o')\\n\\n self.__addGate(new_ids[0]+'_or2', 'O', [new_ids[0]+'_and2_o', new_ids[1]+'_and2_o', new_ids[2]+'_and2_o'], self.dGrph[blck_id][1][2][0])\\n\\n del self.dGrph[blck_id]\\n\\n elif test == 2: # cfg block\\n ip = self.dGrph[blck_id][0]\\n config = self.dGrph[blck_id][2]\\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\\n new_ops = [[self.dGrph[blck_id][2][0] + '_trip7280', None], [self.dGrph[blck_id][2][0] + '_trip7281', None], [self.dGrph[blck_id][2][0] + '_trip7282', None]]\\n\\n self.dGrph[new_ids[0]] = [ip, new_ops[0], config]\\n self.dGrph[new_ids[1]] = [ip, new_ops[1], config]\\n self.dGrph[new_ids[2]] = [ip, new_ops[2], config]\\n\\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0], new_ops[1][0]], new_ids[0]+'_and0_o')\\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0], new_ops[2][0]], new_ids[1]+'_and0_o')\\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0], new_ops[2][0]], new_ids[2]+'_and0_o')\\n\\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0])\\n\\n del self.dGrph[blck_id]\\n\\n elif test == 1: # tribuf\\n ip = self.dGrph[blck_id][0]\\n new_ids = [blck_id+'_tripd780', blck_id+'_tripd781', blck_id+'_tripd782']\\n new_ops = [[self.dGrph[blck_id][2][0] + '_trip7280', None], [self.dGrph[blck_id][2][0] + '_trip7281', None], [self.dGrph[blck_id][2][0] + '_trip7282', None]]\\n\\n self.dGrph[new_ids[0]] = [ip, [ip[1]], new_ops[0]]\\n self.dGrph[new_ids[1]] = [ip, [ip[1]], new_ops[1]]\\n self.dGrph[new_ids[2]] = [ip, [ip[1]], new_ops[2]]\\n\\n self.__addGate(new_ids[0]+'_and0', 'A', [new_ops[0][0], new_ops[1][0]], new_ids[0]+'_and0_o')\\n self.__addGate(new_ids[1]+'_and0', 'A', [new_ops[0][0], new_ops[2][0]], new_ids[1]+'_and0_o')\\n self.__addGate(new_ids[2]+'_and0', 'A', [new_ops[1][0], new_ops[2][0]], new_ids[2]+'_and0_o')\\n\\n self.__addGate(new_ids[0]+'_or0', 'O', [new_ids[0]+'_and0_o', new_ids[1]+'_and0_o', new_ids[2]+'_and0_o'], self.dGrph[blck_id][1][0])\\n\\n del self.dGrph[blck_id]\\n \\n else:\\n print('Unknown error!!!!!!\\\\n')\",\n \"def add_gates(self, num_gates_to_add):\\n pass\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def _gyration(self, x, y, v, c):\\n xy = self._mobius_add(x, y, c)\\n yv = self._mobius_add(y, v, c)\\n xyv = self._mobius_add(x, yv, c)\\n return self._mobius_add(-xy, xyv, c)\",\n \"def _g(self, x: torch.Tensor, params: Scenario):\\n # Extract batch size and set up a tensor for holding the result\\n batch_size = x.shape[0]\\n g = torch.zeros((batch_size, self.n_dims, self.n_controls))\\n g = g.type_as(x)\\n\\n # Extract state variables\\n theta = x[:, TurtleBot2D.THETA]\\n\\n # Effect on x\\n g[:, TurtleBot2D.X, TurtleBot2D.V] = torch.cos(theta)\\n\\n # Effect on y\\n g[:, TurtleBot2D.Y, TurtleBot2D.V] = torch.sin(theta)\\n\\n # Effect on theta\\n g[:, TurtleBot2D.THETA, TurtleBot2D.THETA_DOT] = 1.0\\n\\n return g\",\n \"def cmd_dgaus():\\n cmds = []\\n cmds.append(\\\"r_m[0.0,-1,1]\\\")\\n cmds.append(\\\"r_s[1.5,0,10]\\\")\\n cmds.append('Gaussian::gaus_c(x,r_m,r_s)')\\n cmds.append(\\\"rt_m[0.0,-1,1]\\\")\\n cmds.append(\\\"rt_s[3,0,10]\\\")\\n cmds.append('Gaussian::gaus_t(x,rt_m,rt_s)')\\n cmds.append(\\\"f[0.85]\\\") # fraction of core\\n cmds.append(\\\"SUM::res(f*gaus_c,gaus_t)\\\")\\n return cmds\",\n \"def connect(self, gate) :\\n self.notifyList.append(gate)\",\n \"def t_dg(self, q0, ctrl=None):\\n self.__add_quantum_gate(kind=PHASE_SHIFT_T_, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def dagger(self):\\n return cat.Arrow.dagger(self)\",\n \"def insert(n, c, dnodecomm):\\n\\n _tot[c] += k[n]\\n _in[c] += 2 * dnodecomm + network[n][n]\\n bl[n] = c\",\n \"def globalphase_compiler(self, gate, args):\\n pass\",\n \"def globalphase_compiler(self, gate, args):\\n pass\",\n \"def recursive_gate(e):\\n if isinstance(e, boolean.BaseElement):\\n # TODO: Either make the the same or create a constant component.\\n s = Switch()\\n b.append(s)\\n return s\\n elif isinstance(e, boolean.Symbol):\\n if e in symbol_dict.keys():\\n return symbol_dict[e]\\n else:\\n s = Switch()\\n symbol_dict[e] = s\\n b.append(s)\\n return s\\n elif isinstance(e, boolean.Function):\\n # All gates are of type Gate instead of And, Or and Not\\n if e.order == (1, 1):\\n pre = recursive_gate(e.args[0])\\n w = Wire(pre)\\n b.append(w)\\n\\n s = boolean.Symbol(None)\\n g = Gate(e.subs({e.args[0]: s}),\\n {s: w})\\n b.append(g)\\n return g\\n else:\\n input_dict = {}\\n expr = e\\n for arg in e.args:\\n pre = recursive_gate(arg)\\n w = Wire(pre)\\n b.append(w)\\n\\n s = boolean.Symbol(None)\\n expr = expr.subs({arg: s})\\n input_dict[s] = w\\n g = Gate(expr,\\n input_dict)\\n b.append(g)\\n return g\",\n \"def glucose_c1(self, g_t, t_G, a_G, d_g_t=0):\\n return -(1/t_G)*g_t+(a_G/t_G)*d_g_t\",\n \"def cxr_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def add_distractor(self, distractor_phrase: Phrase, main_phrase: Phrase):\\n if distractor_phrase.phrase_string not in self.phrase_string_map:\\n self.phrase_string_map[distractor_phrase.phrase_string] = distractor_phrase\\n self.distractor_index[distractor_phrase.phrase_string] = distractor_phrase\\n self.is_distractor_of[distractor_phrase.phrase_string].add(main_phrase.phrase_string)\\n self.has_distractors[main_phrase.phrase_string].add(distractor_phrase.phrase_string)\\n self.phrase_type[distractor_phrase.phrase_string].add(\\\"distractor\\\")\\n self._index_phrase_words(distractor_phrase)\\n self._index_phrase_tokens(distractor_phrase)\",\n \"def gen_gr_fiber(th,sigma,mu,iopt,tilt):\\n hkl, uvw = basal_fib(iopt)\\n if iopt==0:\\n g_casa = miller2mat(hkl,uvw)\\n g_sasa = nd_rot(th)\\n elif iopt==1:\\n g_casa = miller2mat_RT(uvw=uvw,xyz=hkl)\\n g_sasa = rd_rot(th)\\n g = np.dot(g_casa,g_sasa)\\n if tilt!=0:\\n g_tilt = rd_rot(tilt)\\n g = np.dot(g_tilt.T,g)\\n\\n dth = gauss(mu=mu, sigma=sigma)\\n return rot_vectang(th=dth, r=g)\",\n \"def define_gan(g_model, d_model):\\r\\n # make weights in the discriminator (some shared with the q model) as not trainable\\r\\n d_model.trainable = False\\r\\n # connect g outputs to d inputs\\r\\n d_output = d_model(g_model.output)\\r\\n # define composite model\\r\\n model = Model(g_model.input, d_output)\\r\\n # compile model\\r\\n opt = Adam(lr=0.0001, beta_1=0.5)\\r\\n model.compile(loss=['binary_crossentropy'], optimizer=opt)\\r\\n return model\",\n \"def add_condiments(self):\\n print(\\\"Adding Lemon\\\")\",\n \"def get_gate(gate, params, num_ctrl_qubits=None):\\n if gate[0] == \\\"c\\\":\\n return get_gate(gate[1:], params, num_ctrl_qubits).ctrl()\\n if gate == \\\"toffoli\\\":\\n return get_gate(\\\"ccx\\\", params, num_ctrl_qubits)\\n if gate[0:2] == \\\"mc\\\":\\n name = gate[2:]\\n for _ in range(num_ctrl_qubits):\\n name = \\\"c\\\" + name\\n return get_gate(name, params, num_ctrl_qubits)\\n if len(params) == 0:\\n return GATE_DIC[gate]\\n\\n return GATE_DIC[gate](*params)\",\n \"def __init__(self, gate: Gate, tag: Any) -> None:\\n\\n if not isinstance(gate, Gate):\\n raise TypeError('Expected gate object, got %s' % type(gate))\\n\\n self.gate = gate\\n self.tag = tag\\n self.name = 'Tagged(%s:%s)' % (gate.get_name(), tag)\\n self.num_params = gate.get_num_params()\\n self.size = gate.get_size()\\n self.radixes = gate.get_radixes()\\n\\n # If input is a constant gate, we can cache the unitary.\\n if self.num_params == 0:\\n self.utry = gate.get_unitary()\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def __init__(self, nfeat, nhid, nclass, dropout, alpha):\\n super(GCN, self).__init__()\\n self.dropout = dropout\\n\\n self.conv1 = GraphConvolutionLayer(nfeat, nhid, dropout=dropout, alpha=alpha, not_final=True)\\n \\n self.add_module('conv1', self.conv1)\\n\\n self.conv2 = GraphConvolutionLayer(nhid, nclass, dropout=dropout, alpha=alpha, not_final=False)\",\n \"def add_hydroxyl(atom, atom_list, added_functional_groups, ct):\\n global anywhere_map\\n global edge_map\\n current_size = len(atom_list)\\n placed = 0\\n alpha = random.randint(0,359)\\n while (placed <= 359):\\n alpha += 1\\n oxygen_atom = Atom(current_size + 1, 'OL', 'H1A', str(added_functional_groups + 1), atom.x, atom.y, ct * 1.49 + atom.z)\\n atom_list.append(oxygen_atom)\\n if ((len(identify_bonds(oxygen_atom, atom_list)) == 1) and (identify_bonds(oxygen_atom, atom_list)[0][0].atom_number == atom.atom_number)):\\n h = math.sin(math.radians(19)) * 0.98\\n h_sp = math.cos(math.radians(19)) * 0.98\\n hydrogen_atom = Atom(current_size + 2, 'HK', 'H1A', str(added_functional_groups + 1), float(\\\"{0:.3f}\\\".format(oxygen_atom.x - math.cos(math.radians(alpha)) * h_sp)), float(\\\"{0:.3f}\\\".format(oxygen_atom.y - math.sin(math.radians(alpha)) * h_sp)), float(\\\"{0:.3f}\\\".format(oxygen_atom.z + ct * h)))\\n atom_list.append(hydrogen_atom)\\n if ((len(identify_bonds(hydrogen_atom, atom_list)) == 1) and (identify_bonds(hydrogen_atom, atom_list)[0][0].atom_number == oxygen_atom.atom_number)):\\n placed = 888\\n if atom in edge_map: edge_map.remove(atom)\\n if atom in anywhere_map: anywhere_map.remove(atom) \\n CY = Atom(atom.atom_number, 'CY', 'H1A', oxygen_atom.residue_number, atom.x, atom.y, atom.z)\\n atom_list.append(CY)\\n atom_list.remove(atom) \\n del atom \\n else:\\n placed += 5\\n del hydrogen_atom\\n del atom_list[current_size + 1]\\n del oxygen_atom\\n del atom_list[current_size + 0]\\n else:\\n placed += 5\\n del oxygen_atom\\n del atom_list[current_size + 0]\\n return atom_list\",\n \"def dX_gene_reg_fn(x, t, topology, params):\\n\\tparents = topology.parents\\n\\ttarget = topology.target\\n\\tinteractions = topology.interactions\\n\\n\\tbase_synth = params[0]\\n\\tbase_degr = params[1]\\n\\n\\t# Add basal synthesis and basal degradation terms\\n\\tdX = base_synth - x[target] * base_degr\\n\\n\\t# Add contributions from each edge\\n\\tfor i in range(len(parents)):\\n\\t\\tp = parents[i]\\n\\t\\tinter = interactions[i]\\n\\n\\t\\tj = 2 + i*3\\n\\t\\tb = params[ j ] \\t # Interaction 'Strength'\\n\\t\\tk = params[ j + 1 ] # Hill fn parameter (theta)\\n\\t\\tm = params[ j + 2 ] # Hill fn parameter (m)\\n\\n\\t\\t# Value of parent for all t\\n\\t\\tparent_val = x[p]\\n\\n\\t\\tif inter == 0:\\n\\t\\t\\tdX += (b * parent_val**m) / (parent_val**m + k**m)\\n\\t\\telif inter == 1:\\n\\t\\t\\tdX += b / (1 + (parent_val/k)**m)\\n\\t\\n\\treturn dX\",\n \"def gate_pass(self, goal):\\n def rc_to_obj(self, goal):\\n \\\"\\\"\\\"Add constant rc commands to depth and heading hold\\\"\\\"\\\"\\n channels = self.depth_heading_rc(goal)\\n channels[self.xchannel] = goal.x_rc_vel\\n yrc_cmd = self.get_obj_y(goal, True)\\n channels[self.ychannel] = yrc_cmd\\n return channels\\n\\n def is_term(self, goal):\\n \\\"\\\"\\\"terminate when the gate is a certain size\\\"\\\"\\\"\\n return self.object_width > self.maxwidth\\n\\n self.behavior_loop(goal, rc_to_obj, is_term)\",\n \"def dagger(self) -> Cap:\\n return self.cap_factory(self.left, self.right)\",\n \"def _ice_dgdt(temp,pres):\\n # Reduced variables\\n tn = temp/_TTP\\n pn = pres/_PTPE\\n _PI0 = _PATM/_PTPE\\n g_t = 0.\\n \\n # Power series and entropy components\\n g_t += -_GCOEFFS[4]\\n \\n # Residual terms including complex numbers\\n sr = [_GCOEFFS[1], complex(0.0,0.0)]\\n for (k,rk) in enumerate(_GCOEFFS[2]):\\n sr[1] += rk * (pn-_PI0)**k\\n for (tk,s) in zip(_GCOEFFS[3],sr):\\n term = -numpy.log(tk-tn) + numpy.log(tk+tn) - 2*tn/tk\\n g_t += (s*term).real\\n return g_t\",\n \"def __init__(self, nfeat, nhid, nclass, dropout, alpha, nheads):\\n super(GAT, self).__init__()\\n self.dropout = dropout\\n\\n self.attentions = [GraphAttentionLayer(nfeat, nhid, dropout=dropout, alpha=alpha, concat=True) for _ in range(nheads)]\\n for i, attention in enumerate(self.attentions):\\n self.add_module('attention_{}'.format(i), attention)\\n\\n self.out_att = GraphAttentionLayer(nhid * nheads, nclass, dropout=dropout, alpha=alpha, concat=False)\",\n \"def _gcl(x, r, D, Ia, Ct):\\n\\n Area = np.pi * D ** 2.0 / 4.0\\n m = 1.0 / (np.sqrt(1.0 - Ct))\\n k = np.sqrt((m + 1.0) / 2.0)\\n\\n a1 = 0.435449861 # empirically determined\\n a2 = 0.797853685\\n a3 = -0.124807893\\n a4 = 0.136821858\\n b1 = 15.6298\\n b2 = 1.0\\n R96 = a1 * (np.exp(a2 * Ct * Ct + a3 * Ct + a4)) * (b1 * Ia + b2) * D\\n\\n x0 = (9.6 * D) / ((2.0 * R96 / (k * D)) ** 3.0 - 1.0)\\n term1 = (k * D / 2.0) ** (5.0 / 2.0)\\n term2 = (105.0 / (2.0 * np.pi)) ** (-0.5)\\n term3 = (Ct * Area * x0) ** (-5.0 / 6.0)\\n c1 = term1 * term2 * term3\\n # c45=3*(c1) ** 2\\n\\n term10 = 0.1111 # * WindSpeed # U/9.0\\n term20 = (Ct * Area * (x + x0) ** (-2.0)) ** (1.0 / 3.0)\\n term310 = (r ** (3.0 / 2.0))\\n term320 = (3.0 * c1 * c1 * Ct * Area * (x + x0)) ** (-0.5)\\n term30 = term310 * term320\\n term40 = ((35.0 / (2.0 * np.pi)) ** (3.0 / 10.0)) * \\\\\\n (3.0 * c1 * c1) ** (-1.0 / 5.0)\\n DU1 = -term10 * term20 * (term30 - term40) ** 2.0\\n\\n DU = DU1 # + w2 * DU2\\n Rw = ((105 * c1 ** 2.0 / (2 * np.pi)) ** (1. / 5.)) * \\\\\\n (Ct * Area * (x + x0)) ** (1. / 3.)\\n return DU, Rw\",\n \"def generate_random_DC_crack_coupled_tensor():\\n # 1. Generate random DC MT and crack MT:\\n # generate DC MT:\\n DC_MT_to_rot = np.vstack(([0.,0.,1.],[0.,0.,0.], [1.,0.,0.])) # DC moment tensor\\n # generate crack MT (from Tape 2013, eq. 41 and Fig. 6):\\n # To randomly generate lune_perim_angle (from Tape 2013 eq. 41 and Fig. 6):\\n # --- To randomly generate lune_perim_angle (from Tape 2013 eq. 41 and Fig. 6) ---:\\n # Get between small range:\\n theta_lune_sphere = np.random.uniform(-1.,1.)*np.pi/2.\\n random_num = random.random()\\n if random_num <= 0.5:\\n phi_lune_sphere = 0. #np.pi/6. #0. #np.pi/6.\\n elif random_num > 0.5:\\n phi_lune_sphere = np.pi/3 #-1.*np.pi/6. #np.pi/3 #-1.*np.pi/6.\\n # calculate lune_perim_angle, allowing for outside tan(-pi/2->pi/2):\\n lune_perim_angle = np.arctan(np.sin(phi_lune_sphere)/np.sin(theta_lune_sphere)) # Generates uniform distribution of lune crack angle in Lune plot space #random.random()*2.*np.pi # Random number in uniform distribution betwen 0 and 2 pi\\n # And redistribute evenly everywhere on boundary:\\n random_num = random.random()\\n if random_num>0.25 and random_num<=0.5:\\n lune_perim_angle = lune_perim_angle+np.pi # Allow to use full 2 pi space\\n if random_num>0.5 and random_num<=0.75:\\n lune_perim_angle = lune_perim_angle+np.pi/2 # Allow to use full 2 pi space\\n if random_num>0.75 and random_num<=1.0:\\n lune_perim_angle = lune_perim_angle+3*np.pi/2 # Allow to use full 2 pi space\\n # --- ---\\n # random_num = random.random()\\n # if random_num <= 0.5:\\n # theta_lune_sphere = random.random()*np.pi/2.\\n # elif random_num > 0.5:\\n # theta_lune_sphere = -1.*random.random()*np.pi/2.\\n # random_num = random.random()\\n # if random_num <= 0.5:\\n # phi_lune_sphere = np.pi/6.\\n # elif random_num > 0.5:\\n # phi_lune_sphere = -1.*np.pi/6.\\n # lune_perim_angle = np.arctan(np.sin(phi_lune_sphere)/np.sin(theta_lune_sphere)) # Generates uniform distribution of lune crack angle in Lune plot space #random.random()*2.*np.pi # Random number in uniform distribution betwen 0 and 2 pi\\n crack_MT_to_rot = ((((4*(np.sin(lune_perim_angle)**2)) + (np.cos(lune_perim_angle)**2))**-0.5)/np.sqrt(3.)) * np.vstack(([np.cos(lune_perim_angle)-(np.sqrt(2)*np.sin(lune_perim_angle)),0.,0.],[0.,np.cos(lune_perim_angle)-(np.sqrt(2)*np.sin(lune_perim_angle)),0.], [0.,0.,np.cos(lune_perim_angle)+(2.*np.sqrt(2)*np.sin(lune_perim_angle))])) # crack moment tensor\\n # 2. Combine DC and crack tensors:\\n random_amp_frac = random.random() # random number between 0. and 1., for relative amplitude of DC and crack fractions.\\n DC_crack_MT_to_rot =random_amp_frac*DC_MT_to_rot + (1.-random_amp_frac)*crack_MT_to_rot\\n # 3. Randomly rotate DC-crack MT to random orientation:\\n # Get a random sample 3-vector on a 3-unit sphere to use to calculate random theta and phi rotation angles:\\n a_unnormalised = np.array([np.random.normal(loc=0.0, scale=1.0), np.random.normal(loc=0.0, scale=1.0), np.random.normal(loc=0.0, scale=1.0)], dtype=float) # Generate 3 indepdendent normal deviates\\n a_normalised = a_unnormalised/(np.sum(a_unnormalised**2)**-0.5) # Normallise sample onto unit 3-sphere - As in Muller (1959)\\n # And normallise so that vector magnitude = 1:\\n a_normalised = a_normalised/((np.sum(a_normalised**2))**0.5)\\n x = a_normalised[0]\\n y = a_normalised[1]\\n z = a_normalised[2]\\n theta = np.arctan2(np.sqrt((x**2)+(y**2)),z) #np.arccos(z)\\n phi = np.arctan2(y,x) #np.arccos(x/np.sin(theta))\\n DC_crack_MT_rotated = rot_mt_by_theta_phi(DC_crack_MT_to_rot, theta, phi)\\n # 4. Normalise and get 6 MT:\\n # Get 6 MT:\\n DC_crack_six_MT_rotated = get_six_MT_from_full_MT_array(DC_crack_MT_rotated)\\n # And normallise so that moment tensor magnitude = 1:\\n DC_crack_six_MT_rotated_normalised = DC_crack_six_MT_rotated/((np.sum(DC_crack_six_MT_rotated**2))**0.5)\\n # And set to correct dimensions (so matrix multiplication in forward model works correctly):\\n DC_crack_six_MT_rotated_normalised = np.reshape(DC_crack_six_MT_rotated_normalised, (6, 1))\\n return DC_crack_six_MT_rotated_normalised, random_amp_frac\",\n \"def get_t_d(conf, r_inputs, d_data):\\n # to crop out unstable part for temporal discriminator, details in TecoGAN supplemental paper\\n crop_size_dt = int(conf.train.crop_size * 4 * conf.gan.crop_dt)\\n offset_dt = (conf.train.crop_size * 4 - crop_size_dt) // 2\\n crop_size_dt = conf.train.crop_size * 4 - offset_dt*2\\n paddings = (0, 0, offset_dt, offset_dt, offset_dt, offset_dt, 0, 0)\\n\\n with nn.parameter_scope(\\\"discriminator\\\"):\\n real_warp = warp_by_flow(d_data.t_targets, d_data.t_vel)\\n real_warp = space_to_depth_disc(real_warp, d_data.t_batch)\\n\\n # equivalent to tf.image.crop_to_bounding_box\\n real_warp = real_warp[:, offset_dt:offset_dt +\\n crop_size_dt, offset_dt:offset_dt+crop_size_dt, :]\\n real_warp = F.pad(real_warp, paddings)\\n before_warp = space_to_depth_disc(d_data.t_targets, d_data.t_batch)\\n t_input = space_to_depth_disc(\\n r_inputs[:, :d_data.t_size, :, :, :], d_data.t_batch)\\n # resizing using bilinear interpolation\\n input_hi = F.interpolate(t_input, scale=(4, 4), mode='linear',\\n channel_last=True)\\n real_warp = F.concatenate(before_warp, real_warp, input_hi)\\n\\n tdiscrim_real_output, real_layers = discriminator(real_warp)\\n\\n fake_warp = warp_by_flow(d_data.t_gen_output, d_data.t_vel)\\n fake_warp = space_to_depth_disc(fake_warp, d_data.t_batch)\\n fake_warp = fake_warp[:, offset_dt:offset_dt +\\n crop_size_dt, offset_dt:offset_dt+crop_size_dt, :]\\n fake_warp = F.pad(fake_warp, paddings)\\n before_warp = space_to_depth_disc(\\n d_data.t_gen_output, d_data.t_batch, inplace=False)\\n fake_warp = F.concatenate(before_warp, fake_warp, input_hi)\\n tdiscrim_fake_output, fake_layers = discriminator(fake_warp)\\n\\n temporal_disc = collections.namedtuple('temporal_disc', 'tdiscrim_real_output,'\\n 'real_layers, tdiscrim_fake_output, fake_layers')\\n return temporal_disc(\\n tdiscrim_real_output=tdiscrim_real_output,\\n real_layers=real_layers,\\n tdiscrim_fake_output=tdiscrim_fake_output,\\n fake_layers=fake_layers\\n )\",\n \"def descent_acc(thrust, drone_mass, g=9.81, drag = 0.):\\n output = (-thrust - drone_mass * g + drag) / drone_mass\\n return output\",\n \"def add_modified_decoherence_noise(\\n prog: \\\"Program\\\",\\n T1: Union[Dict[int, float], float] = 30e-6,\\n T2: Union[Dict[int, float], float] = 30e-6,\\n gate_time_1q: float = 50e-9,\\n gate_time_2q: float = 150e-09,\\n ro_fidelity: Union[Dict[int, float], float] = 0.95,\\n) -> \\\"Program\\\":\\n gates = _get_program_gates(prog)\\n #definitions = {\\n # def_gate.name: def_gate.matrix for def_gate in prog.defined_gates #figure out what is it for \\n #}\\n noise_model = _modified_decoherence_noise_model(\\n gates,\\n T1=T1,\\n T2=T2,\\n gate_time_1q=gate_time_1q,\\n gate_time_2q=gate_time_2q,\\n ro_fidelity=ro_fidelity\\n )\\n return apply_modified_noise_model(prog, noise_model)\",\n \"def add_diameter(self, dia):\\n self.diameters.append(dia)\",\n \"def add_ground(f, c):\\n return f.per(dmp_add_ground(f.rep, f.dom.convert(c), f.lev, f.dom))\",\n \"def _ice_d2gdtdp(temp,pres):\\n # Reduced variables\\n tn = temp/_TTP\\n pn = pres/_PTPE\\n _PI0 = _PATM/_PTPE\\n \\n # Residual terms including complex numbers\\n s = complex(0.0,0.0)\\n for (k,rk) in enumerate(_GCOEFFS[2]):\\n if k > 0:\\n s += rk * k*(pn-_PI0)**(k-1) / _PTPE\\n tk = _GCOEFFS[3][1]\\n term = -numpy.log(tk-tn) + numpy.log(tk+tn) - 2*tn/tk\\n g_tp = (s*term).real\\n return g_tp\",\n \"def test_tdg_gate_nondeterministic_minimal_basis_gates(self):\\n shots = 2000\\n circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_non_clifford.tdg_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def pgd_feat_create_adv_graph(self, sess, feats, y, eps, eta):\\n init_delta = tf.random_uniform(shape = tf.shape(self.featurizations), minval = -eps, maxval = eps)\\n delta = tf.Variable(init_delta, name = \\\"delta_feat\\\", validate_shape = False)\\n\\n #Define new featurizations\\n featurizations_perturbed = self.featurizations + delta\\n\\n #Find predictions and new loss\\n initial = tf.contrib.layers.xavier_initializer(dtype = tf.float32)\\n bias_initial = tf.initializers.zeros\\n\\n scope = 'fc_' + str(len(self.hidden_sizes))\\n predictions = fully_connected_layer(featurizations_perturbed, self.num_classes, scope, initial, bias_initial, tf.identity)\\n\\n loss_vector = tf.nn.softmax_cross_entropy_with_logits(logits=predictions, labels=self.y)\\n loss_tilde = tf.reduce_mean(loss_vector)\\n\\n optimization_step = tf.assign(delta, tf.squeeze(tf.clip_by_value(delta + eta * tf.math.sign(tf.gradients(loss_tilde, delta)), clip_value_min = -eps, clip_value_max = eps)))\\n\\n return optimization_step, featurizations_perturbed, loss_tilde, delta\",\n \"def _add_train_op(self):\\n with tf.device(\\\"/gpu:0\\\"):\\n learning_rate_D = 0.0004 # tf.train.exponential_decay(0.001, self.global_step_D,\\n # 100000, 0.96, staircase=True)\\n learning_rate_G = 0.0004 # tf.train.exponential_decay(0.001, self.global_step_G,\\n # 100000, 0.96, staircase=True)\\n learning_rate_D_in = 0.0004 # tf.train.exponential_decay(0.001, self.global_step_D,\\n # 100000, 0.96, staircase=True)\\n self._train_op_D = tf.train.AdamOptimizer(learning_rate_D,beta1=0.5).minimize(self._D_loss,\\n global_step=self.global_step_D,\\n var_list=self.discriminator._theta)\\n self._train_op_D_in = tf.train.AdamOptimizer(learning_rate_D_in,beta1=0.5).minimize(self._D_in_loss,\\n global_step=self.global_step_D_in,\\n var_list=self.discriminator_inner._theta)\\n\\n self._train_op_G = tf.train.AdamOptimizer(learning_rate_G,beta1=0.5).minimize(self._G_loss,\\n global_step=self.global_step_G,\\n var_list=self.generator._theta)\",\n \"def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\\n if q_args is None and c_args is None:\\n raise GateError(\\\"Gate needs at least one quantum argument or classical argument\\\")\\n if isinstance(gate, CompositeGate):\\n if mapping is None:\\n raise GateError(\\\"Must provide arguments mapping for composite gate inside a composite gate.\\\")\\n else:\\n inv_mappimg = dict()\\n for key, value in mapping.items():\\n inv_mappimg[value] = key\\n if gate is self:\\n gates = gate.copy.gates\\n else:\\n gates = gate.gates\\n for g in gates:\\n new_q_args = None\\n new_c_args = None\\n if g[1] is not None:\\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\\n if g[2] is not None:\\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\\n self.add_gate(gate=g[0], q_args=new_q_args,\\n c_args=new_c_args, params=g[3])\\n else:\\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\\n raise GateError(\\\"Gate must be either a CompositeGate or a string from: \\\"\\n \\\"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\\\")\\n if q_args is not None:\\n for q_arg in q_args:\\n if q_arg not in self.q_args:\\n self.add_q_arg(q_arg)\\n if c_args is not None:\\n for c_arg in c_args:\\n if c_arg not in self.c_args:\\n self.add_c_arg(c_arg)\\n if params is not None:\\n for param in params:\\n if param not in self.params:\\n self.add_param(param)\\n self._gates.append((gate, q_args, c_args, params))\",\n \"def _insert_CD_state(self, alpha, clear=True):\\n # Defines a new thermodynamic state based on the neighboring state\\n neighbor_ind = [alpha < p['alpha']\\n for p in self.data['CD'].protocol].index(True) - 1\\n params_n = self.system.paramsFromAlpha(\\n alpha, params_o=self.data['CD'].protocol[neighbor_ind])\\n\\n # For sampling importance resampling,\\n # prepare an augmented matrix for pymbar calculations\\n # with a new thermodynamic state\\n (u_kln_s, N_k) = self._u_kln(self.data['CD'].Es, self.data['CD'].protocol)\\n (K, L, N) = u_kln_s.shape\\n\\n u_kln_n = self._u_kln(self.data['CD'].Es, [params_n])[0]\\n L += 1\\n N_k = np.append(N_k, [0])\\n\\n u_kln = np.zeros([K, L, N])\\n u_kln[:, :-1, :] = u_kln_s\\n for k in range(K):\\n u_kln[k, -1, :] = u_kln_n[k, 0, :]\\n\\n # Determine SIR weights\\n weights = self.run_MBAR(u_kln, N_k, augmented=True)[1][:, -1]\\n weights = weights / sum(weights)\\n\\n # Resampling\\n # Convert linear indices to 3 indicies: state, cycle, and snapshot\\n cum_N_state = np.cumsum([0] + list(N_k))\\n cum_N_cycle = [np.cumsum([0] + [self.data['CD'].Es[k][c]['MM'].shape[0] \\\\\\n for c in range(len(self.data['CD'].Es[k]))]) for k in range(len(self.data['CD'].Es))]\\n\\n def linear_index_to_snapshot_index(ind):\\n state_index = list(ind < cum_N_state).index(True) - 1\\n nis_index = ind - cum_N_state[state_index]\\n cycle_index = list(nis_index < cum_N_cycle[state_index]).index(True) - 1\\n nic_index = nis_index - cum_N_cycle[state_index][cycle_index]\\n return (state_index, cycle_index, nic_index)\\n\\n def snapshot_index_to_linear_index(state_index, cycle_index, nic_index):\\n return cum_N_state[state_index] + cum_N_cycle[state_index][\\n cycle_index] + nic_index\\n\\n # Terms to copy\\n if self.args.params['CD']['pose'] > -1:\\n # Pose BPMF\\n terms = ['MM',\\\\\\n 'k_angular_ext','k_spatial_ext','k_angular_int'] + scalables\\n else:\\n # BPMF\\n terms = ['MM', 'site'] + scalables\\n\\n CD_Es_s = []\\n confs_s = []\\n for c in range(len(self.data['CD'].Es[0])):\\n CD_Es_c = dict([(term, []) for term in terms])\\n confs_c = []\\n for n_in_c in range(len(self.data['CD'].Es[-1][c]['MM'])):\\n if (cum_N_cycle[-1][c] == 0):\\n (snapshot_s,snapshot_c,snapshot_n) = linear_index_to_snapshot_index(\\\\\\n np.random.choice(range(len(weights)), size = 1, p = weights)[0])\\n else:\\n snapshot_c = np.inf\\n while (snapshot_c > c):\\n (snapshot_s,snapshot_c,snapshot_n) = linear_index_to_snapshot_index(\\\\\\n np.random.choice(range(len(weights)), size = 1, p = weights)[0])\\n for term in terms:\\n CD_Es_c[term].append(\\\\\\n np.copy(self.data['CD'].Es[snapshot_s][snapshot_c][term][snapshot_n]))\\n if self.args.params['CD']['keep_intermediate']:\\n # Has not been tested:\\n confs_c.append(\\\\\\n np.copy(self.data['CD'].confs['samples'][snapshot_s][snapshot_c]))\\n for term in terms:\\n CD_Es_c[term] = np.array(CD_Es_c[term])\\n CD_Es_s.append(CD_Es_c)\\n confs_s.append(confs_c)\\n\\n # Insert resampled values\\n self.data['CD'].protocol.insert(neighbor_ind + 1, params_n)\\n self.data['CD'].Es.insert(neighbor_ind + 1, CD_Es_s)\\n self.data['CD'].confs['samples'].insert(neighbor_ind + 1, confs_s)\\n self.data['CD'].confs['replicas'].insert(neighbor_ind+1, \\\\\\n np.copy(self.data['CD'].confs['replicas'][neighbor_ind]))\\n\\n if clear:\\n self._clear_f_RL()\",\n \"def dcgain(self):\\n raise NotImplementedError(\\\"dcgain not implemented for %s objects\\\" %\\n str(self.__class__))\",\n \"def discriminator(self, inpt, reuse, is_train):\\n with tf.variable_scope(\\\"discriminator\\\"):\\n if reuse:\\n tf.get_variable_scope().reuse_variables()\\n net = conv2d(x=inpt, num_kernels=self.d_init, name=\\\"conv1\\\", activation=lkrelu, padding=\\\"SAME\\\",\\n alpha=0.02, is_train=is_train, stddv=self.stddv)\\n net = conv2d(x=net, num_kernels=self.d_init*2, name=\\\"conv2\\\", activation=lkrelu, padding=\\\"SAME\\\",\\n alpha=0.02, is_train=is_train, stddv=self.stddv)\\n net = conv2d(x=net, num_kernels=self.d_init*4, name=\\\"conv3\\\", activation=lkrelu, padding=\\\"SAME\\\",\\n alpha=0.02, is_train=is_train, stddv=self.stddv)\\n net = conv2d(x=net, num_kernels=self.d_init*8, name=\\\"conv4\\\", activation=lkrelu, padding=\\\"SAME\\\",\\n alpha=0.02, is_train=is_train, stddv=self.stddv)\\n net = dense_layer(x=net, num_neurons=1, name=\\\"output\\\", activation=tf.identity, is_train=is_train,\\n stddv=self.stddv)\\n return net\",\n \"def _build_add(self) -> str:\\n return dedent(\\n \\\"\\\"\\\"\\n @SP\\n M=M-1\\n A=M\\n D=M\\n @SP\\n M=M-1\\n A=M\\n M=M+D\\n @SP\\n M=M+1\\n \\\"\\\"\\\"\\n )\",\n \"def user_gate_definition(self, filenum, linenum, txt):\\n txt = txt.strip()\\n gate_decl = QTRegEx.GATE_DECL.match(txt)\\n gate_name = gate_decl.group(1)\\n possible_gate_params = gate_name.split('(')\\n gate_param_list = None\\n if len(possible_gate_params) > 1:\\n gate_param_list = possible_gate_params[1].strip(') ').split(',')\\n gate_regs = gate_decl.group(2).strip(\\\"{}\\\") # watch out for no space before '{' !!\\n gate_reg_list = gate_regs.split(',')\\n gate_ops = QTRegEx.GATE_OPS.match(txt)\\n gate_ops_raw_list = QTRegEx.GATE_OPS_LIST.findall(gate_ops.group(1))\\n gate_ops_list = []\\n for op_raw in gate_ops_raw_list:\\n op_raw = op_raw.strip()\\n op = QTRegEx.GATE_OP.match(op_raw).group(1)\\n op_params = QTRegEx.GATE_OP_PARAMS.match(op_raw)\\n if op_params:\\n op_param_list = op_params.group(1).split(',')\\n else:\\n op_param_list = None\\n op_regs = QTRegEx.GATE_OP_REGS.match(op_raw)\\n if op_regs:\\n op_reg_list = op_regs.group(1).split(',')\\n else:\\n op_reg_list = None\\n gate_ops_list.append({'op': op,\\n 'op_param_list': op_param_list,\\n 'op_reg_list': op_reg_list})\\n gate = {'source': txt if self.save_gate_source else None,\\n 'filenum': filenum,\\n 'linenum': linenum, 'gate_name': gate_name,\\n 'gate_param_list': gate_param_list,\\n 'gate_ops_raw_list': gate_ops_raw_list,\\n 'gate_ops_list': gate_ops_list,\\n 'gate_reg_list': gate_reg_list}\\n\\n self.append_user_gate(gate)\",\n \"def set_ddg_flag(self, is_new_hunk):\\n Gumtree.gumtree.setDDGFlag(is_new_hunk)\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def dbgain_from_pt(self, grid=None, pt_1=None):\\n assert pt_1 is not None\\n assert grid is not None\\n\\n def dbgain(pt_2):\\n return [self.dbgain(pt_1, pt_2)]\\n\\n return FunctionVectorField(grid=grid, fun=dbgain)\",\n \"def layer(i):\\n with tf.name_scope('layer_{}'.format(i)):\\n # displacement gate\\n Dgate(tf.clip_by_value(d_r[i], -disp_clip, disp_clip), d_phi[i]) | q[0]\\n # rotation gate\\n Rgate(r1[i]) | q[0]\\n # squeeze gate\\n Sgate(tf.clip_by_value(sq_r[i], -sq_clip, sq_clip), sq_phi[i]) | q[0]\\n # rotation gate\\n Rgate(r2[i]) | q[0]\\n # Kerr gate\\n Kgate(tf.clip_by_value(kappa1[i], -kerr_clip, kerr_clip)) | q[0]\",\n \"def add_state(self, state):\\n if self.rate_variation:\\n if not self.feature_rates:\\n # Set all rates to 1.0 in a big plate\\n plate = ET.SubElement(state, \\\"plate\\\", {\\n \\\"var\\\":\\\"feature\\\",\\n \\\"range\\\":\\\",\\\".join(self.features)})\\n param = ET.SubElement(plate, \\\"parameter\\\", {\\n \\\"id\\\":\\\"featureClockRate:%s:$(feature)\\\" % self.name,\\n \\\"name\\\":\\\"stateNode\\\"})\\n param.text=\\\"1.0\\\"\\n else:\\n # Give each rate a custom value\\n for f in self.features:\\n param = ET.SubElement(state, \\\"parameter\\\", {\\n \\\"id\\\":\\\"featureClockRate:%s:%s\\\" % (self.name, f),\\n \\\"name\\\":\\\"stateNode\\\"})\\n param.text=str(self.feature_rates.get(f,1.0))\\n\\n # Give Gamma shape parameter a finite domain\\n # Must be > 1.0 for the distribution to be bell-shaped,\\n # rather than L-shaped. The domain [1.1,1000] limits feature\\n # rate variation to the realms of vague plausibity\\n parameter = ET.SubElement(state, \\\"parameter\\\", {\\\"id\\\":\\\"featureClockRateGammaShape:%s\\\" % self.name, \\\"lower\\\":\\\"1.1\\\",\\\"upper\\\":\\\"100.0\\\",\\\"name\\\":\\\"stateNode\\\"})\\n parameter.text=\\\"5.0\\\"\\n # Gamma scale parameter's domain is defined *implicilty*\\n # by the fact that the operators maintain shape*scale = 1.0\\n parameter = ET.SubElement(state, \\\"parameter\\\", {\\\"id\\\":\\\"featureClockRateGammaScale:%s\\\" % self.name, \\\"name\\\":\\\"stateNode\\\"})\\n parameter.text=\\\"0.2\\\"\",\n \"def test_tdg_gate_nondeterministic_default_basis_gates(self):\\n shots = 2000\\n circuits = ref_non_clifford.tdg_gate_circuits_nondeterministic(final_measure=True)\\n targets = ref_non_clifford.tdg_gate_counts_nondeterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots)\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0.05 * shots)\",\n \"def add_dcdisorder(self):\\n # Add gaussian noise to pinning energies\\n if self.lp['V0_pin_gauss'] > 0:\\n self.Omg += self.lp['V0_pin_gauss']*np.random.randn(len(self.xy_inner))\\n raise RuntimeError('Adding gaussian disorder: are you sure you want to proceed?')\\n if self.lp['V0_spring_gauss'] > 0:\\n print 'This is not done correctly here'\\n self.OmK += self.lp['V0_spring_gauss'] * np.random.randn(np.shape(self.lattice.KL)[0],\\n np.shape(self.lattice.KL)[1])\\n sys.exit()\\n\\n if self.lp['V0_pin_flat'] > 0 or self.lp['V0_spring_flat'] > 0:\\n # Note that we multiply by two so that V0_pin_flat is the HALF width of the distribution\\n flat_disorder = (np.random.rand(len(self.xy_inner))) * 2 - 1.0\\n\\n if self.lp['V0_pin_flat'] > 0:\\n self.Omg += self.lp['V0_pin_flat'] * flat_disorder\\n if self.lp['Omg'] < 0:\\n self.Omg[self.Omg > 0] = 0.\\n elif self.lp['Omg'] > 0:\\n self.Omg[self.Omg < 0] = 0.\\n\\n print('magnetic_gyro_lattice_class.py: V0_pin_flat=', self.lp['V0_pin_flat'])\\n print(self.Omg)\\n\\n if self.lp['V0_spring_flat'] > 0:\\n to_add = self.lp['V0_spring_flat'] * flat_disorder[:, np.newaxis] * np.ones_like(self.OmK)\\n self.OmK[np.abs(self.OmK) > 0] += to_add[np.abs(self.OmK) > 0]\\n if self.lp['Omk'] < 0:\\n self.OmK[self.OmK > 0] = 0.\\n elif self.lp['Omk'] > 0:\\n self.OmK[self.OmK < 0] = 0.\\n\\n print('magnetic_gyro_lattice_class.py: OmK after flat disorder= ')\\n print(self.OmK)\\n # sys.exit()\",\n \"def grads(self, inputs):\",\n \"def GAStep(self):\\n\\n self.updateMatingPool()\\n self.newGeneration()\",\n \"def computeCLgainRemoveNodeD(self, G, PD, nodes, node, dropLidx, dir):\\n CL_I = 0.0\\n CL_F = 0.0\\n if dir==2:\\n for i in nodes:\\n pos_I = PD.getPOS(node, i, case=2, isSimple=self.isSimple)\\n pos_F = PD.getPOS(node, i, case=4, isSimple=self.isSimple, dropLidx=dropLidx)\\n if pos_I < 0.0000000001:\\n pos_I = 0.0000000001\\n elif pos_I > 1.0 - 0.0000000001:\\n pos_I = 1.0 - 0.0000000001\\n if pos_F < 0.0000000001:\\n pos_F = 0.0000000001\\n elif pos_F > 1.0 - 0.0000000001:\\n pos_F = 1.0 - 0.0000000001\\n numE = G.number_of_edges(node, i)\\n if self.isSimple:\\n CL_I += math.log2(math.pow(1.0-pos_I, 1.0-numE)*math.pow(pos_I, numE))\\n CL_F += math.log2(math.pow(1.0-pos_F, 1.0-numE)*math.pow(pos_F, numE))\\n else:\\n CL_I += math.log2(math.pow(1.0-pos_I, numE)*pos_I)\\n CL_F += math.log2(math.pow(1.0-pos_F, numE)*pos_F)\\n elif dir==1:\\n for i in nodes:\\n pos_I = PD.getPOS(i, node, case=2, isSimple=self.isSimple)\\n pos_F = PD.getPOS(i, node, case=4, isSimple=self.isSimple, dropLidx=dropLidx)\\n if pos_I < 0.0000000001:\\n pos_I = 0.0000000001\\n elif pos_I > 1.0 - 0.0000000001:\\n pos_I = 1.0 - 0.0000000001\\n if pos_F < 0.0000000001:\\n pos_F = 0.0000000001\\n elif pos_F > 1.0 - 0.0000000001:\\n pos_F = 1.0 - 0.0000000001\\n numE = G.number_of_edges(i, node)\\n if self.isSimple:\\n CL_I += math.log2(math.pow(1.0-pos_I, 1.0-numE)*math.pow(pos_I, numE))\\n CL_F += math.log2(math.pow(1.0-pos_F, 1.0-numE)*math.pow(pos_F, numE))\\n else:\\n CL_I += math.log2( math.pow( 1.0-pos_I, numE )*pos_I )\\n CL_F += math.log2( math.pow( 1.0-pos_F, numE )*pos_F )\\n return -CL_I - (-CL_F)\",\n \"def DiagonalGate():\\n\\n def f(x): # pylint: disable=invalid-name\\n # x : [batch, 1, length, depth]\\n x = jnp.pad(x, [(0, 0), (0, 0), (1, 1), (0, 0)],\\n mode='constant', constant_values=0.0)\\n depth = x.shape[-1] // 3\\n assert 3 * depth == x.shape[-1], ('Depth must be divisible by 3', depth,\\n x.shape)\\n xs = [\\n x[:, :, :-2, :depth], x[:, :, 1:-1, depth:2 * depth],\\n x[:, :, 2:, 2 * depth:3 * depth]\\n ]\\n return jnp.concatenate(xs, axis=3)\\n return tl.Fn('DiagonalGate', f)\",\n \"def DynamicsCoop(x, t, T0, alpha, cost, K, n, r):\\n \\n #defune the degradation effect\\n deg=fmax*x[1]/(x[1]+Kd)\\n D=dmax*x[0]**n/(x[0]**n+K**n)\\n #define ODEs\\n y=np.zeros([np.size(x)])\\n y[0]=alpha*T0-deg*x[0]-alpha*x[0] #dt/dt\\n y[1]=x[1]*(r*(1-cost)*(1-x[1])-D-alpha)#d Co/dt\\n \\n return y\",\n \"def _add_grover_step_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n _add_2_bit_oracle_without_ancilla_1_0(qc, register) # Oracle\\n add_grover_reflection_no_ancilla(qc, register) # Reflection\",\n \"def addDielectric(default_dielectric=20):\\n \\n parser.add_option(\\\"-D\\\",\\\"--dielectric\\\",action=\\\"store\\\",type=\\\"float\\\",\\n dest=\\\"dielectric\\\",\\n help=\\\"Dielectric constant for UHBD calculations (default=20)\\\",\\n default=default_dielectric)\",\n \"def alg(c):\\n return c[0]*G[0] + c[1]*G[1] + c[2]*G[2]\",\n \"def add_operators(self, run):\\n if self.rate_variation:\\n # UpDownOperator to scale the Gamma distribution for this model's\\n # feature rates\\n updown = ET.SubElement(run, \\\"operator\\\", {\\\"id\\\":\\\"featureClockRateGammaUpDown:%s\\\" % self.name, \\\"spec\\\":\\\"UpDownOperator\\\", \\\"scaleFactor\\\":\\\"0.5\\\",\\\"weight\\\":\\\"0.3\\\"})\\n ET.SubElement(updown, \\\"parameter\\\", {\\\"idref\\\":\\\"featureClockRateGammaShape:%s\\\" % self.name, \\\"name\\\":\\\"up\\\"})\\n ET.SubElement(updown, \\\"parameter\\\", {\\\"idref\\\":\\\"featureClockRateGammaScale:%s\\\" % self.name, \\\"name\\\":\\\"down\\\"})\",\n \"def add_dart(self):\\r\\n dart_id = self.maxid\\r\\n for i in self.alphas:\\r\\n self.alphas[i][dart_id] = dart_id\\r\\n self.maxid = dart_id +1\\r\\n return dart_id\",\n \"def add_carboxyl(atom, atom_list, added_functional_groups, ct):\\n \\n global anywhere_map\\n global edge_map\\n current_size = len(atom_list)\\n placed = 0\\n alpha = random.randint(0,359)\\n x = atom.x\\n y = atom.y\\n z = atom.z\\n while (placed <= 359):\\n alpha += 1\\n carbon_atom = Atom(current_size + 1, 'C4', 'C1A', str(added_functional_groups + 1), float(\\\"{0:.3f}\\\".format(x)), float(\\\"{0:.3f}\\\".format(y)), float(\\\"{0:.3f}\\\".format(ct * 1.52 + z)))\\n atom_list.append(carbon_atom)\\n if ((len(identify_bonds(carbon_atom, atom_list)) == 1) and (identify_bonds(carbon_atom, atom_list)[0][0].atom_number == atom.atom_number)):\\n h = math.sin(math.radians(60)) * 1.20\\n oxygen_atom_1 = Atom(current_size + 2, 'OJ', 'C1A', str(added_functional_groups + 1), float(\\\"{0:.3f}\\\".format(carbon_atom.x - math.cos(math.radians(alpha)) * h)), float(\\\"{0:.3f}\\\".format(carbon_atom.y - math.sin(math.radians(alpha)) * h)), float(\\\"{0:.3f}\\\".format(carbon_atom.z + ct * math.cos(math.radians(60)) * 1.20)))\\n atom_list.append(oxygen_atom_1)\\n if ((len(identify_bonds(oxygen_atom_1, atom_list)) == 1) and (identify_bonds(oxygen_atom_1, atom_list)[0][0].atom_number == carbon_atom.atom_number)):\\n h = math.sin(math.radians(60)) * 1.34\\n oxygen_atom_2 = Atom(current_size + 3, 'OK', 'C1A', str(added_functional_groups + 1), float(\\\"{0:.3f}\\\".format(carbon_atom.x - math.cos(math.radians(alpha + 180)) * h)), float(\\\"{0:.3f}\\\".format(carbon_atom.y - math.sin(math.radians(alpha+180)) * h)), float(\\\"{0:.3f}\\\".format(carbon_atom.z + ct * math.cos(math.radians(60)) * 1.34)) )\\n atom_list.append(oxygen_atom_2)\\n if ((len(identify_bonds(oxygen_atom_2, atom_list)) == 1) and (identify_bonds(oxygen_atom_2, atom_list)[0][0].atom_number == carbon_atom.atom_number)):\\n hydrogen_atom = Atom(current_size + 4, 'HK', 'C1A', str(added_functional_groups + 1), float(\\\"{0:.3f}\\\".format(oxygen_atom_2.x)), float(\\\"{0:.3f}\\\".format(oxygen_atom_2.y)), float(\\\"{0:.3f}\\\".format(oxygen_atom_2.z+ct*0.98)))\\n atom_list.append(hydrogen_atom)\\n if ((len(identify_bonds(hydrogen_atom, atom_list)) == 1) and (identify_bonds(hydrogen_atom, atom_list)[0][0].atom_number == oxygen_atom_2.atom_number)):\\n placed = 888\\n if atom in edge_map: edge_map.remove(atom)\\n if atom in anywhere_map: anywhere_map.remove(atom)\\n CY = Atom(atom.atom_number, 'CY', 'C1A', carbon_atom.residue_number, atom.x, atom.y, atom.z)\\n atom_list.append(CY)\\n atom_list.remove(atom)\\n del atom\\n else:\\n placed += 5\\n del hydrogen_atom\\n del atom_list[current_size + 3]\\n del oxygen_atom_2\\n del atom_list[current_size + 2]\\n del oxygen_atom_1\\n del atom_list[current_size + 1]\\n del carbon_atom\\n del atom_list[current_size + 0]\\n else:\\n placed += 5\\n del oxygen_atom_2\\n del atom_list[current_size + 2]\\n del oxygen_atom_1\\n del atom_list[current_size + 1]\\n del carbon_atom\\n del atom_list[current_size + 0]\\n else:\\n placed += 5\\n del oxygen_atom_1\\n del atom_list[current_size + 1]\\n del carbon_atom\\n del atom_list[current_size + 0]\\n else:\\n placed += 5\\n del carbon_atom \\n del atom_list[current_size + 0]\\n return atom_list\",\n \"def add():\\n pass\",\n \"def add_connector(self):\\n \\n no = len(self.connectors)\\n state = {}\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % no\\n \\n if len(self.connectors)>0:\\n state = self.connectors[-1].get_state()\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % (no)\\n else:\\n if self.mount == self.MOUNT_THT:\\n state[\\\"p_shape\\\"] = Con.SHAPE_HOLE\\n elif self.mount == self.MOUNT_SMD:\\n state[\\\"p_shape\\\"] = Con.SHAPE_PAD\\n \\n c = Con(no)\\n c.set_state(state) \\n \\n self.sch_layers[\\\"pins\\\"].add(c.s_svg)\\n self.pcb_layers[\\\"copper1\\\"].add(c.p_svg)\\n self.connectors.append(c)\",\n \"def GED_n(Gn, lib='gedlibpy', cost='CHEM_1', method='IPFP',\\n edit_cost_constant=[], stabilizer='min', repeat=50):\\n if lib == 'gedlibpy':\\n def convertGraph(G):\\n \\\"\\\"\\\"Convert a graph to the proper NetworkX format that can be\\n recognized by library gedlibpy.\\n \\\"\\\"\\\"\\n G_new = nx.Graph()\\n for nd, attrs in G.nodes(data=True):\\n G_new.add_node(str(nd), chem=attrs['atom_symbol'])\\n for nd1, nd2, attrs in G.edges(data=True):\\n # G_new.add_edge(str(nd1), str(nd2), valence=attrs['bond_type'])\\n G_new.add_edge(str(nd1), str(nd2))\\n\\n return G_new\\n\\n # gedlibpy.restart_env()\\n gedlibpy.add_nx_graph(convertGraph(g1), \\\"\\\")\\n gedlibpy.add_nx_graph(convertGraph(g2), \\\"\\\")\\n\\n listID = gedlibpy.get_all_graph_ids()\\n gedlibpy.set_edit_cost(cost, edit_cost_constant=edit_cost_constant)\\n gedlibpy.init()\\n gedlibpy.set_method(method, \\\"\\\")\\n gedlibpy.init_method()\\n\\n g = listID[0]\\n h = listID[1]\\n if stabilizer == None:\\n gedlibpy.run_method(g, h)\\n pi_forward = gedlibpy.get_forward_map(g, h)\\n pi_backward = gedlibpy.get_backward_map(g, h)\\n upper = gedlibpy.get_upper_bound(g, h)\\n lower = gedlibpy.get_lower_bound(g, h)\\n elif stabilizer == 'min':\\n upper = np.inf\\n for itr in range(repeat):\\n gedlibpy.run_method(g, h)\\n upper_tmp = gedlibpy.get_upper_bound(g, h)\\n if upper_tmp < upper:\\n upper = upper_tmp\\n pi_forward = gedlibpy.get_forward_map(g, h)\\n pi_backward = gedlibpy.get_backward_map(g, h)\\n lower = gedlibpy.get_lower_bound(g, h)\\n if upper == 0:\\n break\\n\\n dis = upper\\n\\n # make the map label correct (label remove map as np.inf)\\n nodes1 = [n for n in g1.nodes()]\\n nodes2 = [n for n in g2.nodes()]\\n nb1 = nx.number_of_nodes(g1)\\n nb2 = nx.number_of_nodes(g2)\\n pi_forward = [nodes2[pi] if pi < nb2 else np.inf for pi in pi_forward]\\n pi_backward = [nodes1[pi] if pi <\\n nb1 else np.inf for pi in pi_backward]\\n\\n return dis, pi_forward, pi_backward\",\n \"def _insert_op(self, op):\",\n \"def test_tdg_gate_deterministic_minimal_basis_gates(self):\\n shots = 100\\n circuits = ref_non_clifford.tdg_gate_circuits_deterministic(final_measure=True)\\n targets = ref_non_clifford.tdg_gate_counts_deterministic(shots)\\n job = execute(circuits, QasmSimulator(), shots=shots, basis_gates='U,CX')\\n result = job.result()\\n self.is_completed(result)\\n self.compare_counts(result, circuits, targets, delta=0)\",\n \"def add_epoxy(atom, atom_list, added_functional_groups, ct):\\n global anywhere_map\\n global edge_map\\n current_size = len(atom_list)\\n list_of_n = [x[0] for x in identify_bonds(atom, atom_list) if (x[0].atom_name != \\\"CY\\\")]\\n if (len(list_of_n) != 0):\\n atom2 = random.choice(list_of_n)\\n epoxy_atom = Atom( current_size + 1, 'OE', 'E1A', str(added_functional_groups + 1), float(\\\"{0:.3f}\\\".format(abs(atom.x - atom2.x) / 2 + min(atom.x, atom2.x))), float(\\\"{0:.3f}\\\".format(abs(atom.y - atom2.y) / 2 + min(atom.y, atom2.y))), float(\\\"{0:.3f}\\\".format(ct * 1.46 * math.sin(math.radians(60)))) )\\n atom_list.append(epoxy_atom)\\n if ((len(identify_bonds(epoxy_atom, atom_list)) == 2) and ((identify_bonds(epoxy_atom, atom_list)[0][0].atom_number == atom.atom_number) or (identify_bonds(epoxy_atom, atom_list)[1][0].atom_number == atom.atom_number)) and ((identify_bonds(epoxy_atom, atom_list)[0][0].atom_number == atom2.atom_number) or ((identify_bonds(epoxy_atom, atom_list)[1][0].atom_number == atom2.atom_number)))):\\n CY = Atom(atom.atom_number, 'CY', 'E1A', epoxy_atom.residue_number, atom.x, atom.y, atom.z)\\n CY2 = Atom(atom2.atom_number, 'CZ', 'E1A', epoxy_atom.residue_number, atom2.x, atom2.y, atom2.z)\\n atom_list.remove(atom); atom_list.remove(atom2)\\n atom_list.append(CY); atom_list.append(CY2) \\n if atom in edge_map: edge_map.remove(atom)\\n if atom in anywhere_map: anywhere_map.remove(atom)\\n if atom2 in edge_map: edge_map.remove(atom2)\\n if atom2 in anywhere_map: anywhere_map.remove(atom2)\\n else:\\n atom_list.remove(epoxy_atom)\\n del epoxy_atom\\n return atom_list\",\n \"def differentiate(hp):\\n if hp.force_skip:\\n G.add_edge(\\\"input\\\", \\\"output\\\")\\n for node in G.nodes(data=True):\\n node_id, node_data = node\\n log(\\\"differentiate\\\", node_id, node_data)\\n node_data[\\\"output\\\"] = None\\n node_data[\\\"op\\\"] = None\\n if node_data[\\\"shape\\\"] is \\\"square\\\" or \\\"output\\\" in node_id:\\n if node_id == \\\"output\\\":\\n d_out = node_data[\\\"output_shape\\\"][-1]\\n node_type = hp.last_layer\\n activation = \\\"tanh\\\"\\n else:\\n node_type = str(np.random.choice(['sepconv1d', 'transformer',\\n 'k_conv1', 'k_conv2', 'k_conv3',\\n \\\"deep\\\", \\\"wide_deep\\\"],\\n 1, p=hp.layer_distribution).item(0))\\n activation = str(np.random.choice([ 'tanh', 'linear', 'relu', 'selu',\\n 'elu', 'sigmoid', 'hard_sigmoid', 'exponential', 'softmax',\\n 'softplus', 'softsign', 'gaussian', 'sin', 'cos', 'swish'],\\n 1, p=hp.activation_distribution).item(0))\\n d_out = None\\n node_data[\\\"force_residual\\\"] = random.random() < hp.p_force_residual\\n node_data[\\\"activation\\\"] = clean_activation(activation)\\n node_data[\\\"node_type\\\"] = node_type\\n node_data['style'] = \\\"\\\"\\n if node_type == 'sepconv1d':\\n if d_out is None:\\n d_out = safe_sample(hp.min_filters, hp.max_filters)\\n node_data[\\\"filters\\\"] = d_out\\n node_data[\\\"kernel_size\\\"] = 1\\n if node_type == \\\"transformer\\\":\\n if d_out is None:\\n d_out = safe_sample(hp.min_units, hp.max_units) * hp.attn_heads\\n node_data[\\\"d_model\\\"] = d_out\\n node_data[\\\"n_heads\\\"] = 2 if d_out % 2 == 0 else 1\\n if \\\"k_conv\\\" in node_type or node_type in [\\\"deep\\\", \\\"wide_deep\\\"]:\\n layers = design_layers(hp, d_out, activation)\\n if d_out is None:\\n d_out = layers[-1][0]\\n node_data[\\\"stddev\\\"] = hp.stddev\\n node_data['layers'] = layers\\n node_data[\\\"d_out\\\"] = d_out\\n if node_type in [\\\"deep\\\", \\\"wide_deep\\\"]:\\n node_data['kernel'] = node_type\\n else:\\n node_data['kernel'] = \\\"wide_deep\\\" if random.random() < hp.p_wide_deep else \\\"deep\\\"\\n label = f\\\"{node_type}\\\"\\n log(f\\\"set {node_id} to {label}\\\")\\n node_data[\\\"label\\\"] = label\\n node_data[\\\"color\\\"] = \\\"green\\\"\\n # we handle recurrent shapes:\\n try:\\n feedback_node_id = f\\\"{node_id}_feedback\\\"\\n input_shape = (None, d_out)\\n log(f\\\"attempt to set input_shape for {feedback_node_id} to {input_shape}\\\")\\n feedback_node = G.node[feedback_node_id]\\n feedback_node[\\\"input_shape\\\"] = input_shape\\n node_data[\\\"gives_feedback\\\"] = True\\n except Exception as e:\\n log(\\\"ERROR HANDLING FEEDBACK SHAPE:\\\", e)\",\n \"def compute_gains(self, t, add_noise=True):\\n #get the basis funtion at a time step\\n basis, Dbasis = self.get_basis(t)\\n\\n if t < self._time_steps-1:\\n basis_t_dt, _ = self.get_basis(t+1)\\n else:\\n basis_t_dt = np.zeros_like(basis)\\n\\n\\n #part 1 equation 46\\n B_pseudo = np.linalg.pinv(self._B)\\n\\n #equation 12 for t\\n Sigma_t = np.dot(np.dot(basis, self._sigma_W), basis.T)\\n\\n #equation 12 for t+dt\\n Sigma_t_dt = np.dot(np.dot(basis_t_dt, self._sigma_W), basis_t_dt.T)\\n\\n #Cross correlation between t, t+dt, Equation 49\\n Ct = np.dot(np.dot(basis, self._sigma_W), basis_t_dt.T)\\n\\n #System noise Equation 51\\n Sigma_s = (1./self._dt)* ( Sigma_t_dt - np.dot( np.dot( Ct.T, np.linalg.inv(Sigma_t) ), Ct) )\\n\\n #control noise Equation 52\\n Sigma_u = np.dot(np.dot(B_pseudo, Sigma_s), B_pseudo.T)\\n\\n #part 2 equation 46\\n tmp1 = np.dot(np.dot(Dbasis, self._sigma_W), basis.T)\\n\\n #part 3 equation 46\\n tmp2 = np.dot(self._A, Sigma_t) + 0.5*Sigma_s\\n\\n #compute feedback gain; complete equation 46\\n K = np.dot( np.dot(B_pseudo, (tmp1-tmp2) ), np.linalg.inv(Sigma_t))\\n\\n #part 1 equation 48\\n tmp3 = np.dot(Dbasis, self._mean_W)\\n\\n #part 2 equation 48\\n tmp4 = np.dot( (self._A + np.dot(self._B, K)), np.dot(basis, self._mean_W) )\\n\\n #compute feedforward gain; complete equation 48\\n k = np.dot(B_pseudo, (tmp3-tmp4))\\n\\n return K, k, Sigma_u\",\n \"def test_superposition_ud_cnot():\\n program = dedent(\\n \\\"\\\"\\\"\\\\\\n register q0[0]\\n register q1[1]\\n H q1\\n CNOT q1 q0\\n \\\"\\\"\\\"\\n )\\n\\n result = run(program, run_gate_array, return_distribution=True)\\n assert isclose(result, [0.5, 0.0, 0.0, 0.5]).all()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.57742953","0.56914765","0.55658096","0.55089957","0.53045684","0.5290461","0.5265818","0.5198308","0.512335","0.5066861","0.50638485","0.50114036","0.49884704","0.49417618","0.4919655","0.49066445","0.4892633","0.48817962","0.48796433","0.48612082","0.48464134","0.48419595","0.47861785","0.47808108","0.47763473","0.4752954","0.47349954","0.47319773","0.47076613","0.4707389","0.4698529","0.46865618","0.46808618","0.46728992","0.46695","0.46568337","0.4655444","0.46496743","0.46496743","0.46383023","0.46327984","0.46233416","0.46159303","0.46096084","0.4606412","0.45816466","0.45804754","0.45791405","0.4572528","0.4569272","0.45661128","0.45478514","0.45455617","0.45407802","0.4539629","0.45374665","0.45347932","0.45278242","0.4522379","0.4516118","0.45150328","0.45149565","0.4496333","0.4489109","0.44725287","0.44678056","0.4454641","0.4452874","0.44503078","0.44492579","0.44491047","0.44419783","0.44369987","0.44336468","0.44321644","0.4431241","0.44274575","0.44258547","0.4422276","0.4413001","0.4405928","0.44040456","0.44037625","0.43970597","0.43963417","0.43958122","0.43922344","0.43905762","0.438877","0.43882367","0.4387691","0.43864536","0.43859813","0.43851233","0.43818793","0.43770662","0.436999","0.4368733","0.4365836","0.43586397"],"string":"[\n \"0.57742953\",\n \"0.56914765\",\n \"0.55658096\",\n \"0.55089957\",\n \"0.53045684\",\n \"0.5290461\",\n \"0.5265818\",\n \"0.5198308\",\n \"0.512335\",\n \"0.5066861\",\n \"0.50638485\",\n \"0.50114036\",\n \"0.49884704\",\n \"0.49417618\",\n \"0.4919655\",\n \"0.49066445\",\n \"0.4892633\",\n \"0.48817962\",\n \"0.48796433\",\n \"0.48612082\",\n \"0.48464134\",\n \"0.48419595\",\n \"0.47861785\",\n \"0.47808108\",\n \"0.47763473\",\n \"0.4752954\",\n \"0.47349954\",\n \"0.47319773\",\n \"0.47076613\",\n \"0.4707389\",\n \"0.4698529\",\n \"0.46865618\",\n \"0.46808618\",\n \"0.46728992\",\n \"0.46695\",\n \"0.46568337\",\n \"0.4655444\",\n \"0.46496743\",\n \"0.46496743\",\n \"0.46383023\",\n \"0.46327984\",\n \"0.46233416\",\n \"0.46159303\",\n \"0.46096084\",\n \"0.4606412\",\n \"0.45816466\",\n \"0.45804754\",\n \"0.45791405\",\n \"0.4572528\",\n \"0.4569272\",\n \"0.45661128\",\n \"0.45478514\",\n \"0.45455617\",\n \"0.45407802\",\n \"0.4539629\",\n \"0.45374665\",\n \"0.45347932\",\n \"0.45278242\",\n \"0.4522379\",\n \"0.4516118\",\n \"0.45150328\",\n \"0.45149565\",\n \"0.4496333\",\n \"0.4489109\",\n \"0.44725287\",\n \"0.44678056\",\n \"0.4454641\",\n \"0.4452874\",\n \"0.44503078\",\n \"0.44492579\",\n \"0.44491047\",\n \"0.44419783\",\n \"0.44369987\",\n \"0.44336468\",\n \"0.44321644\",\n \"0.4431241\",\n \"0.44274575\",\n \"0.44258547\",\n \"0.4422276\",\n \"0.4413001\",\n \"0.4405928\",\n \"0.44040456\",\n \"0.44037625\",\n \"0.43970597\",\n \"0.43963417\",\n \"0.43958122\",\n \"0.43922344\",\n \"0.43905762\",\n \"0.438877\",\n \"0.43882367\",\n \"0.4387691\",\n \"0.43864536\",\n \"0.43859813\",\n \"0.43851233\",\n \"0.43818793\",\n \"0.43770662\",\n \"0.436999\",\n \"0.4368733\",\n \"0.4365836\",\n \"0.43586397\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5654775"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81752,"cells":{"query":{"kind":"string","value":"add CP gate (controlled P gate)."},"document":{"kind":"string","value":"def cp(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_P, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def BCS(self, value):\n if self.reg.C:\n self.reg.PC += value","def AddSpecialPoint(self, cp):\n return _gmat_py.SolarSystem_AddSpecialPoint(self, cp)","def BPL(self, value):\n if not self.reg.N:\n self.reg.PC += value","def cp(temp,pres):\n g_tt = liq_g(2,0,temp,pres)\n cp = -temp * g_tt\n return cp","def add_control(operation, num_ctrl_qubits, label):\n if isinstance(operation, UnitaryGate):\n # attempt decomposition\n operation._define()\n if _control_definition_known(operation, num_ctrl_qubits):\n return _control_predefined(operation, num_ctrl_qubits)\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)","def test_scalar_coeff_cc():\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\n kappa = Symbol('kappa', real=True)\n a1 = Destroy(hs=hs_1)\n a2 = Destroy(hs=hs_2)\n\n jc_expr = (\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\n )\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == I * kappa * OperatorPlusMinusCC(\n a1.dag() * a2, sign=-1\n )\n expanded = simplified.doit()\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def add_connector(self):\n \n no = len(self.connectors)\n state = {}\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % no\n \n if len(self.connectors)>0:\n state = self.connectors[-1].get_state()\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % (no)\n else:\n if self.mount == self.MOUNT_THT:\n state[\"p_shape\"] = Con.SHAPE_HOLE\n elif self.mount == self.MOUNT_SMD:\n state[\"p_shape\"] = Con.SHAPE_PAD\n \n c = Con(no)\n c.set_state(state) \n \n self.sch_layers[\"pins\"].add(c.s_svg)\n self.pcb_layers[\"copper1\"].add(c.p_svg)\n self.connectors.append(c)","def AddOperation(self, op):\n self._operations.append(op)","def addOp(self, op):\n self.operations << op","def addControlPoints(self, *controlpoints):\n self.controlpoints.extend(controlpoints)\n self.update()","def enc_add_const(pub, m, c):\n # Similiar to enc add\n add_const_result = m * powmod(pub.g, c, pub.n_sq) % pub.n_sq\n return add_const_result","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\n if q_args is None and c_args is None:\n raise GateError(\"Gate needs at least one quantum argument or classical argument\")\n if isinstance(gate, CompositeGate):\n if mapping is None:\n raise GateError(\"Must provide arguments mapping for composite gate inside a composite gate.\")\n else:\n inv_mappimg = dict()\n for key, value in mapping.items():\n inv_mappimg[value] = key\n if gate is self:\n gates = gate.copy.gates\n else:\n gates = gate.gates\n for g in gates:\n new_q_args = None\n new_c_args = None\n if g[1] is not None:\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\n if g[2] is not None:\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\n self.add_gate(gate=g[0], q_args=new_q_args,\n c_args=new_c_args, params=g[3])\n else:\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\n raise GateError(\"Gate must be either a CompositeGate or a string from: \"\n \"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\")\n if q_args is not None:\n for q_arg in q_args:\n if q_arg not in self.q_args:\n self.add_q_arg(q_arg)\n if c_args is not None:\n for c_arg in c_args:\n if c_arg not in self.c_args:\n self.add_c_arg(c_arg)\n if params is not None:\n for param in params:\n if param not in self.params:\n self.add_param(param)\n self._gates.append((gate, q_args, c_args, params))","def addPoly(self,p):\n for t in triangulate(p):\n self.addTri(t)\n return self","def add_comp(mol, projects):\n\n # Now attribute all this meta-deta to the compound object\n new_comp = Compound()\n comp = calc_cpd(new_comp, mol, projects)\n return comp","def add(self, y):\n return circuit.add(self, y)","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def compCoeff_CGP(i, A, c, N):\n Ap = np.copy(A)\n out = c[i, 0] * np.eye(N)\n j = 1\n while j <= i:\n # compute A to the power p\n if j > 1:\n Ap = Ap.dot(A)\n\n # add to the polynome\n out += c[i, j] * Ap\n j += 1\n\n return out","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def _template_circuit(self, amp_param) -> QuantumCircuit:\n gate = Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param])\n\n circuit = QuantumCircuit(1)\n circuit.append(gate, (0,))\n circuit.measure_active()\n\n return circuit","def connect(self, gate) :\n self.notifyList.append(gate)","def __iadd__(self, point):\n self.points.append(point)\n return self","def bcc(self, arg):\n\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def __init__(self, input, output) :\n Gate.__init__(self, [input], output)","def __add__(self, B):\n return (Polynomial(self) + B).simplify()","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def _control_predefined(operation, num_ctrl_qubits):\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\n if num_ctrl_qubits == 1:\n import qiskit.extensions.standard.cx\n cgate = qiskit.extensions.standard.cx.CnotGate()\n else:\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n elif operation.name == 'y':\n import qiskit.extensions.standard.cy\n cgate = qiskit.extensions.standard.cy.CyGate()\n elif operation.name == 'z':\n import qiskit.extensions.standard.cz\n cgate = qiskit.extensions.standard.cz.CzGate()\n elif operation.name == 'h':\n import qiskit.extensions.standard.ch\n cgate = qiskit.extensions.standard.ch.CHGate()\n elif operation.name in {'rx', 'ry', 'rz'}:\n if operation.name == 'rx':\n import qiskit.extensions.standard.crx\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\n elif operation.name == 'ry':\n import qiskit.extensions.standard.cry\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\n else: # operation.name == 'rz'\n import qiskit.extensions.standard.crz\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\n if num_ctrl_qubits == 1:\n return cgate\n else:\n # only predefined for one control qubit\n return cgate.control(num_ctrl_qubits - 1)\n elif operation.name == 'swap':\n import qiskit.extensions.standard.cswap\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\n elif operation.name == 'u1':\n import qiskit.extensions.standard.cu1\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\n elif operation.name == 'u3':\n import qiskit.extensions.standard.cu3\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\n elif operation.name == 'cx':\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n else:\n raise QiskitError('No standard controlled gate for \"{}\"'.format(\n operation.name))\n return cgate","def add_compartment(self, Vp=1, Qp=1):\n self.__n_compartments += 1\n self.__compartments.append({'Vp': Vp, 'Qp': Qp})","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def test_simple_cc():\n hs_c = LocalSpace('c', dimension=3)\n hs_q = LocalSpace('q1', basis=('g', 'e'))\n Delta_1 = Symbol('Delta_1')\n Omega_1 = Symbol('Omega_1')\n g_1 = Symbol('g_1')\n a = Destroy(hs=hs_c)\n a_dag = Create(hs=hs_c)\n sig_p = LocalSigma('e', 'g', hs=hs_q)\n sig_m = LocalSigma('g', 'e', hs=hs_q)\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\n assert (\n srepr(simplified.term)\n == \"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \"\n \"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \"\n \"basis=('g', 'e')))), sign=-1)\"\n )\n expanded = simplified.doit()\n assert expanded == jc_expr","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def add_operator(self, operator: Callable) -> None:\n self.operators.append(operator)","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def credit(self, value):\n self._negative_value_raises_an_error(value)\n self.operations.insert(value);","def add_control_inputs(op, cops):\n flag = True\n try:\n _ = iter(cops)\n except Exception: # pylint: disable=broad-except\n flag = False\n if not flag:\n op._add_control_input(cops)\n else:\n for cop in cops:\n if cop in op.control_inputs:\n raise ValueError(\"{}\".format(cop.name) + \" is already \" +\n \"a control_input of {}\".format(op.name))\n op._add_control_inputs(cops) # pylint: disable=protected-access","def add_op(self, op):\n self._operations.append(op)","def add(self, p, s, node) -> None:\n self.place.append(p)\n self.station.append(s)\n self.pi.append(node.pi[p, s] if p != float('inf') else float('inf'))\n self.noncoverage.append(node.noncoverage.left + node.noncoverage.right)\n self.cost.append(node.cost)\n self.delay.append(node.delay)\n self.step.append(node.key)","def __init__(self, input0, input1, output) :\n Gate.__init__(self, [input0,input1], output)","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def __add__(self, p):\n return Point(self.x + p.x, self.y + p.y)","def add(self, p):\n self._pumps.add(p)","def construct_circuit(self):\n return self._circuit","def circuit():\n np.random.seed(1967)\n for gates in gates_per_layers:\n for gate in gates:\n qml.apply(gate)\n return qml.expval(qml.PauliZ(0))","def _template_circuit(self, amp_param) -> QuantumCircuit:\n circuit = QuantumCircuit(1)\n circuit.x(0)\n circuit.append(Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param]), (0,))\n circuit.measure_active()\n\n return circuit","def compCGP_C(M):\n # we store the coedd as a lower triangular matrix\n # random polynomial coefficients\n c = 0.5 * np.random.uniform(-1.0, -0.45, size=(M + 1, M + 1)) +\\\n 0.5 * np.random.uniform(0.45, 1.0, size=(M + 1, M + 1))\n for i in np.arange(M + 1):\n c[i, :] /= 2**(np.arange(M + 1) + i)\n c /= 1.5\n c = np.tril(c)\n c[0, 0] = 0\n c[1, 0] = 0\n c[1, 1] = 1\n\n return c","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\n return self","def __add__(self, other):\n return Base40Interval(self.base40 + other.base40)","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\n return self","def DPc(R,Pc):\n return r2*(K2**B2/(K2**B2 + (A)**B2))*(S/(S + R*Pc + Pc)) \\\n *(R*M)/(K3 + R*M)*Pc - gc*Pc","def bcs(self, arg):\n\n self.pc += arg if self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def globalphase_compiler(self, gate, args):\n pass","def globalphase_compiler(self, gate, args):\n pass","def circuitSat(C):","def add_new_control_point(moment_data, new_control_point, new_frame_id,\n runtime_bucket, is_vehicle=False):\n change_type = \"ped_controls\"\n if is_vehicle:\n change_type = \"vehicle_controls\"\n prev_controls = \\\n moment_data[runtime_bucket[\"cur_moment_idx\"]][change_type]\n new_frame_id = \"%s\" % new_frame_id # json's fault\n #if prev_controls.has_key(new_frame_id):\n if new_frame_id in prev_controls:\n # add to the existing frame\n moment_data[runtime_bucket[\"cur_moment_idx\"]][change_type][\n new_frame_id].append(new_control_point)\n else:\n # a new frame\n moment_data[runtime_bucket[\"cur_moment_idx\"]][change_type][\n new_frame_id] = [new_control_point]\n\n # get the new traj data\n person_data, vehicle_data = get_trajs(\n moment_data, runtime_bucket[\"cur_moment_idx\"])\n runtime_bucket[\"person_data\"] = person_data\n runtime_bucket[\"vehicle_data\"] = vehicle_data","def alg(c):\n return c[0]*G[0] + c[1]*G[1] + c[2]*G[2]","def addFP(self, num=1):\n self.fp += num","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def prove_CP() -> Proof:\n # Optional Task 6.7d","def assemble_circuit(\n self,\n circuit: Circuit,\n blocks: list[int],\n psols: list[list[tuple[Circuit, float]]],\n pts: list[CircuitPoint],\n ) -> Circuit:\n circuit_gates = [\n CircuitGate(psol_list[b][0])\n for b, psol_list\n in zip(blocks, psols)\n ]\n locations = [circuit[pt].location for pt in pts]\n operations = [\n Operation(cg, loc, cg._circuit.params)\n for cg, loc\n in zip(circuit_gates, locations)\n ]\n copied_circuit = circuit.copy()\n copied_circuit.batch_replace(pts, operations)\n return copied_circuit","def constraint(self, c):\n self.add_constraint(c)","def actual_causation():\n # fmt: off\n tpm = np.array([\n [1, 0, 0, 0],\n [0, 1, 0, 0],\n [0, 1, 0, 0],\n [0, 0, 0, 1],\n ])\n cm = np.array([\n [1, 1],\n [1, 1],\n ])\n # fmt: on\n return Network(tpm, cm, node_labels=('OR', 'AND'))","def BVC(self, value):\n if not self.reg.V:\n self.reg.PC += value","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def point_addition(self, P, Q):\n\t\traise Exception(NotImplemented)","def add_pilot_compute_service(self, pjs):\n self.pilot_job_services.append(pjs)\n CoordinationAdaptor.update_cds(self.url, self)","def _econ_append_pc(pp, cf_file, sites_per_worker=None):\n multi_h5_res, hsds = check_res_file(cf_file)\n if multi_h5_res:\n res_cls = MultiFileResource\n res_kwargs = {}\n else:\n res_cls = Resource\n res_kwargs = {'hsds': hsds}\n\n with res_cls(cf_file, **res_kwargs) as f:\n gid0 = f.meta['gid'].values[0]\n gid1 = f.meta['gid'].values[-1]\n\n i0 = pp.index(gid0)\n i1 = pp.index(gid1) + 1\n pc = PointsControl.split(i0, i1, pp, sites_per_split=sites_per_worker)\n\n return pc","def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]","def addition(self):\n\t\treturn lambda anything: self.__class__(\n\t\t\t(self[:], disj, checked_proposition(anything)[:])\n\t\t)","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def add(self, p):\n\n self.poses.append(CalibrationPoint(p))\n self.selected_point = len(self.poses) - 1\n self.calibration_changed()","def gate_mfcc(recurrent_net, sample_input):\n length = sample_input.shape[1]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\n select = sigmoid(select)\n return np.sum(select * score) / np.sum(select)","def get_bprop_assign_add(self):\n\n def bprop(x, y, out, dout):\n return zeros_like(x), zeros_like(y)\n return bprop","def __add__(self, other)\n \n def __mul__(self, other):\n print(\"Standard multiplication with\", other.which)\n print(other.which)\n \n if isinstance(other, int):\n print(\"Other is int\")\n self.coefficients *= other\n \n return self\n \n else:\n print(\"Other operator is spin operator\")\n summandsNew = []\n coeffsNew = []\n for otherSummandIndex, otherSummand in enumerate(other.summands):\n for thisSummandIndex, thisSummand in enumerate(self.summands):\n summandsNew.append(flatten([thisSummand, otherSummand]))\n coeffsNew.append(self.coefficients[thisSummandIndex]*other.coefficients[otherSummandIndex])\n print(summandsNew) \n self.coeffs = coeffsNew\n self.summands = summandsNew\n \n return self","def add_node(self, new_node: 'GraphNode'):\n self.operator.add_node(new_node)","def _compose(self, other):\n if self.num_qubits != other.num_qubits:\n raise QiskitError(\"Multiplication on different number of qubits.\")\n result = CNOTDihedral(num_qubits=self.num_qubits)\n result.shift = [\n (x[0] + x[1]) % 2 for x in zip(self._z2matvecmul(other.linear, self.shift), other.shift)\n ]\n result.linear = self._z2matmul(other.linear, self.linear)\n # Compute x' = B1*x + c1 using the p_j identity\n new_vars = []\n for i in range(self.num_qubits):\n support = np.arange(other.num_qubits)[np.nonzero(self.linear[i])]\n poly = SpecialPolynomial(self.num_qubits)\n poly.set_pj(support)\n if self.shift[i] == 1:\n poly = -1 * poly\n poly.weight_0 = (poly.weight_0 + 1) % 8\n new_vars.append(poly)\n # p' = p1 + p2(x')\n result.poly = self.poly + other.poly.evaluate(new_vars)\n return result","def path_cost(self, c, state1, action, state2):\n return c + 1","def path_cost(self, c, state1, action, state2):\n return c + 1","def path_cost(self, c, state1, action, state2):\n return c + 1","def parameterise_gate(self, gate:Union[cirq.Gate, Callable]): \n if isinstance(gate, cirq.Gate):\n if isinstance(gate, (cirq.XXPowGate, cirq.YYPowGate, cirq.ZZPowGate)):\n param = self.new_param()\n return gate**param\n return gate\n elif isclass(gate) and issubclass(gate, cirq.Gate):\n parameters = ParameterisedCircuit._get_gate_parameters(gate)\n n_param = len(parameters)\n params = self.new_param(size=n_param, as_array=True)\n kwargs = {parameters[i]:params[i] for i in range(n_param)}\n return gate(**kwargs) \n else:\n n_param = ParameterisedCircuit._get_parameter_count(gate)\n params = self.new_param(size=n_param)\n params = tuple(params) if isinstance(params, np.ndarray) else (params,) \n return gate(*params)","def __add__(self, other):\n if type(other) == int or type(other) == float:\n x = (other * Ccy.currencies[self.unit])\n else:\n x = (other.value / Ccy.currencies[other.unit] * Ccy.currencies[self.unit])\n return Ccy(x + self.value, self.unit)","def _AddCompound(self, kegg_id, how_many):\n i = self._FindCompoundIndex(kegg_id)\n if i is not None:\n self.reactants[i].coeff += how_many\n else:\n self.reactants += [CompoundWithCoeff.FromId(how_many, kegg_id)]\n \n # clear the cache since the reaction has changed\n self._catalyzing_enzymes = None","def __iadd__(self, other: PointOrIterableOrScalar) -> PointType:\n return self.__iop(other, operator.add)","def __add__(self, other):\n \"*** YOUR CODE HERE ***\"","def path_cost(self, c, state1, action, state2):\n # This should probably just be 1 every state....\n return c + 1","def path_cost(self, c, state1, action, state2):\n # This should probably just be 1 every state....\n return c + 1","def __mul__(self, other):\r\n if isinstance(other, Operation):\r\n return Circuit().append(self, list(range(len(self.shape))), 0).append(\r\n other, list(range(len(self.shape), len(self.shape) + len(other.shape))), 0)\r\n else:\r\n return NotImplemented","def gate_operation(self, operation, qubit_expr, params=None):\n operation = QuantumCircuit._parse_gate_operation(operation)\n if params is not None:\n operation = operation(**params) \n qubit = self.qr.get(qubit_expr) \n return operation(qubit)","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def path_cost(self, c, state1, action, state2):\n\t\treturn c + 1","def add(self, proc: ImageProcessor):\n self.chain.append(proc)\n return self","def cpf(self, cpf):\n self._cpf = cpf","def _add_op(value, sample_args, rationals_allowed):\n entropy, sample_args = sample_args.peel()\n if rationals_allowed and sample_args.count >= 3:\n x = number.integer_or_rational(entropy, True)\n else:\n x = number.integer(entropy, True)\n if random.choice([False, True]):\n op_args = [x, value - x]\n else:\n op_args = [value - x, x]\n return ops.Add, op_args, sample_args","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self"],"string":"[\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def BCS(self, value):\\n if self.reg.C:\\n self.reg.PC += value\",\n \"def AddSpecialPoint(self, cp):\\n return _gmat_py.SolarSystem_AddSpecialPoint(self, cp)\",\n \"def BPL(self, value):\\n if not self.reg.N:\\n self.reg.PC += value\",\n \"def cp(temp,pres):\\n g_tt = liq_g(2,0,temp,pres)\\n cp = -temp * g_tt\\n return cp\",\n \"def add_control(operation, num_ctrl_qubits, label):\\n if isinstance(operation, UnitaryGate):\\n # attempt decomposition\\n operation._define()\\n if _control_definition_known(operation, num_ctrl_qubits):\\n return _control_predefined(operation, num_ctrl_qubits)\\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def test_scalar_coeff_cc():\\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\\n kappa = Symbol('kappa', real=True)\\n a1 = Destroy(hs=hs_1)\\n a2 = Destroy(hs=hs_2)\\n\\n jc_expr = (\\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\\n )\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == I * kappa * OperatorPlusMinusCC(\\n a1.dag() * a2, sign=-1\\n )\\n expanded = simplified.doit()\\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def add_connector(self):\\n \\n no = len(self.connectors)\\n state = {}\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % no\\n \\n if len(self.connectors)>0:\\n state = self.connectors[-1].get_state()\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % (no)\\n else:\\n if self.mount == self.MOUNT_THT:\\n state[\\\"p_shape\\\"] = Con.SHAPE_HOLE\\n elif self.mount == self.MOUNT_SMD:\\n state[\\\"p_shape\\\"] = Con.SHAPE_PAD\\n \\n c = Con(no)\\n c.set_state(state) \\n \\n self.sch_layers[\\\"pins\\\"].add(c.s_svg)\\n self.pcb_layers[\\\"copper1\\\"].add(c.p_svg)\\n self.connectors.append(c)\",\n \"def AddOperation(self, op):\\n self._operations.append(op)\",\n \"def addOp(self, op):\\n self.operations << op\",\n \"def addControlPoints(self, *controlpoints):\\n self.controlpoints.extend(controlpoints)\\n self.update()\",\n \"def enc_add_const(pub, m, c):\\n # Similiar to enc add\\n add_const_result = m * powmod(pub.g, c, pub.n_sq) % pub.n_sq\\n return add_const_result\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\\n if q_args is None and c_args is None:\\n raise GateError(\\\"Gate needs at least one quantum argument or classical argument\\\")\\n if isinstance(gate, CompositeGate):\\n if mapping is None:\\n raise GateError(\\\"Must provide arguments mapping for composite gate inside a composite gate.\\\")\\n else:\\n inv_mappimg = dict()\\n for key, value in mapping.items():\\n inv_mappimg[value] = key\\n if gate is self:\\n gates = gate.copy.gates\\n else:\\n gates = gate.gates\\n for g in gates:\\n new_q_args = None\\n new_c_args = None\\n if g[1] is not None:\\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\\n if g[2] is not None:\\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\\n self.add_gate(gate=g[0], q_args=new_q_args,\\n c_args=new_c_args, params=g[3])\\n else:\\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\\n raise GateError(\\\"Gate must be either a CompositeGate or a string from: \\\"\\n \\\"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\\\")\\n if q_args is not None:\\n for q_arg in q_args:\\n if q_arg not in self.q_args:\\n self.add_q_arg(q_arg)\\n if c_args is not None:\\n for c_arg in c_args:\\n if c_arg not in self.c_args:\\n self.add_c_arg(c_arg)\\n if params is not None:\\n for param in params:\\n if param not in self.params:\\n self.add_param(param)\\n self._gates.append((gate, q_args, c_args, params))\",\n \"def addPoly(self,p):\\n for t in triangulate(p):\\n self.addTri(t)\\n return self\",\n \"def add_comp(mol, projects):\\n\\n # Now attribute all this meta-deta to the compound object\\n new_comp = Compound()\\n comp = calc_cpd(new_comp, mol, projects)\\n return comp\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def compCoeff_CGP(i, A, c, N):\\n Ap = np.copy(A)\\n out = c[i, 0] * np.eye(N)\\n j = 1\\n while j <= i:\\n # compute A to the power p\\n if j > 1:\\n Ap = Ap.dot(A)\\n\\n # add to the polynome\\n out += c[i, j] * Ap\\n j += 1\\n\\n return out\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def _template_circuit(self, amp_param) -> QuantumCircuit:\\n gate = Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param])\\n\\n circuit = QuantumCircuit(1)\\n circuit.append(gate, (0,))\\n circuit.measure_active()\\n\\n return circuit\",\n \"def connect(self, gate) :\\n self.notifyList.append(gate)\",\n \"def __iadd__(self, point):\\n self.points.append(point)\\n return self\",\n \"def bcc(self, arg):\\n\\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def __init__(self, input, output) :\\n Gate.__init__(self, [input], output)\",\n \"def __add__(self, B):\\n return (Polynomial(self) + B).simplify()\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def _control_predefined(operation, num_ctrl_qubits):\\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\\n if num_ctrl_qubits == 1:\\n import qiskit.extensions.standard.cx\\n cgate = qiskit.extensions.standard.cx.CnotGate()\\n else:\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n elif operation.name == 'y':\\n import qiskit.extensions.standard.cy\\n cgate = qiskit.extensions.standard.cy.CyGate()\\n elif operation.name == 'z':\\n import qiskit.extensions.standard.cz\\n cgate = qiskit.extensions.standard.cz.CzGate()\\n elif operation.name == 'h':\\n import qiskit.extensions.standard.ch\\n cgate = qiskit.extensions.standard.ch.CHGate()\\n elif operation.name in {'rx', 'ry', 'rz'}:\\n if operation.name == 'rx':\\n import qiskit.extensions.standard.crx\\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\\n elif operation.name == 'ry':\\n import qiskit.extensions.standard.cry\\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\\n else: # operation.name == 'rz'\\n import qiskit.extensions.standard.crz\\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\\n if num_ctrl_qubits == 1:\\n return cgate\\n else:\\n # only predefined for one control qubit\\n return cgate.control(num_ctrl_qubits - 1)\\n elif operation.name == 'swap':\\n import qiskit.extensions.standard.cswap\\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\\n elif operation.name == 'u1':\\n import qiskit.extensions.standard.cu1\\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\\n elif operation.name == 'u3':\\n import qiskit.extensions.standard.cu3\\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\\n elif operation.name == 'cx':\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n else:\\n raise QiskitError('No standard controlled gate for \\\"{}\\\"'.format(\\n operation.name))\\n return cgate\",\n \"def add_compartment(self, Vp=1, Qp=1):\\n self.__n_compartments += 1\\n self.__compartments.append({'Vp': Vp, 'Qp': Qp})\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def test_simple_cc():\\n hs_c = LocalSpace('c', dimension=3)\\n hs_q = LocalSpace('q1', basis=('g', 'e'))\\n Delta_1 = Symbol('Delta_1')\\n Omega_1 = Symbol('Omega_1')\\n g_1 = Symbol('g_1')\\n a = Destroy(hs=hs_c)\\n a_dag = Create(hs=hs_c)\\n sig_p = LocalSigma('e', 'g', hs=hs_q)\\n sig_m = LocalSigma('g', 'e', hs=hs_q)\\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\\n assert (\\n srepr(simplified.term)\\n == \\\"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \\\"\\n \\\"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \\\"\\n \\\"basis=('g', 'e')))), sign=-1)\\\"\\n )\\n expanded = simplified.doit()\\n assert expanded == jc_expr\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def add_operator(self, operator: Callable) -> None:\\n self.operators.append(operator)\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def credit(self, value):\\n self._negative_value_raises_an_error(value)\\n self.operations.insert(value);\",\n \"def add_control_inputs(op, cops):\\n flag = True\\n try:\\n _ = iter(cops)\\n except Exception: # pylint: disable=broad-except\\n flag = False\\n if not flag:\\n op._add_control_input(cops)\\n else:\\n for cop in cops:\\n if cop in op.control_inputs:\\n raise ValueError(\\\"{}\\\".format(cop.name) + \\\" is already \\\" +\\n \\\"a control_input of {}\\\".format(op.name))\\n op._add_control_inputs(cops) # pylint: disable=protected-access\",\n \"def add_op(self, op):\\n self._operations.append(op)\",\n \"def add(self, p, s, node) -> None:\\n self.place.append(p)\\n self.station.append(s)\\n self.pi.append(node.pi[p, s] if p != float('inf') else float('inf'))\\n self.noncoverage.append(node.noncoverage.left + node.noncoverage.right)\\n self.cost.append(node.cost)\\n self.delay.append(node.delay)\\n self.step.append(node.key)\",\n \"def __init__(self, input0, input1, output) :\\n Gate.__init__(self, [input0,input1], output)\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def __add__(self, p):\\n return Point(self.x + p.x, self.y + p.y)\",\n \"def add(self, p):\\n self._pumps.add(p)\",\n \"def construct_circuit(self):\\n return self._circuit\",\n \"def circuit():\\n np.random.seed(1967)\\n for gates in gates_per_layers:\\n for gate in gates:\\n qml.apply(gate)\\n return qml.expval(qml.PauliZ(0))\",\n \"def _template_circuit(self, amp_param) -> QuantumCircuit:\\n circuit = QuantumCircuit(1)\\n circuit.x(0)\\n circuit.append(Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param]), (0,))\\n circuit.measure_active()\\n\\n return circuit\",\n \"def compCGP_C(M):\\n # we store the coedd as a lower triangular matrix\\n # random polynomial coefficients\\n c = 0.5 * np.random.uniform(-1.0, -0.45, size=(M + 1, M + 1)) +\\\\\\n 0.5 * np.random.uniform(0.45, 1.0, size=(M + 1, M + 1))\\n for i in np.arange(M + 1):\\n c[i, :] /= 2**(np.arange(M + 1) + i)\\n c /= 1.5\\n c = np.tril(c)\\n c[0, 0] = 0\\n c[1, 0] = 0\\n c[1, 1] = 1\\n\\n return c\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\\n return self\",\n \"def __add__(self, other):\\n return Base40Interval(self.base40 + other.base40)\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\\n return self\",\n \"def DPc(R,Pc):\\n return r2*(K2**B2/(K2**B2 + (A)**B2))*(S/(S + R*Pc + Pc)) \\\\\\n *(R*M)/(K3 + R*M)*Pc - gc*Pc\",\n \"def bcs(self, arg):\\n\\n self.pc += arg if self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def globalphase_compiler(self, gate, args):\\n pass\",\n \"def globalphase_compiler(self, gate, args):\\n pass\",\n \"def circuitSat(C):\",\n \"def add_new_control_point(moment_data, new_control_point, new_frame_id,\\n runtime_bucket, is_vehicle=False):\\n change_type = \\\"ped_controls\\\"\\n if is_vehicle:\\n change_type = \\\"vehicle_controls\\\"\\n prev_controls = \\\\\\n moment_data[runtime_bucket[\\\"cur_moment_idx\\\"]][change_type]\\n new_frame_id = \\\"%s\\\" % new_frame_id # json's fault\\n #if prev_controls.has_key(new_frame_id):\\n if new_frame_id in prev_controls:\\n # add to the existing frame\\n moment_data[runtime_bucket[\\\"cur_moment_idx\\\"]][change_type][\\n new_frame_id].append(new_control_point)\\n else:\\n # a new frame\\n moment_data[runtime_bucket[\\\"cur_moment_idx\\\"]][change_type][\\n new_frame_id] = [new_control_point]\\n\\n # get the new traj data\\n person_data, vehicle_data = get_trajs(\\n moment_data, runtime_bucket[\\\"cur_moment_idx\\\"])\\n runtime_bucket[\\\"person_data\\\"] = person_data\\n runtime_bucket[\\\"vehicle_data\\\"] = vehicle_data\",\n \"def alg(c):\\n return c[0]*G[0] + c[1]*G[1] + c[2]*G[2]\",\n \"def addFP(self, num=1):\\n self.fp += num\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def prove_CP() -> Proof:\\n # Optional Task 6.7d\",\n \"def assemble_circuit(\\n self,\\n circuit: Circuit,\\n blocks: list[int],\\n psols: list[list[tuple[Circuit, float]]],\\n pts: list[CircuitPoint],\\n ) -> Circuit:\\n circuit_gates = [\\n CircuitGate(psol_list[b][0])\\n for b, psol_list\\n in zip(blocks, psols)\\n ]\\n locations = [circuit[pt].location for pt in pts]\\n operations = [\\n Operation(cg, loc, cg._circuit.params)\\n for cg, loc\\n in zip(circuit_gates, locations)\\n ]\\n copied_circuit = circuit.copy()\\n copied_circuit.batch_replace(pts, operations)\\n return copied_circuit\",\n \"def constraint(self, c):\\n self.add_constraint(c)\",\n \"def actual_causation():\\n # fmt: off\\n tpm = np.array([\\n [1, 0, 0, 0],\\n [0, 1, 0, 0],\\n [0, 1, 0, 0],\\n [0, 0, 0, 1],\\n ])\\n cm = np.array([\\n [1, 1],\\n [1, 1],\\n ])\\n # fmt: on\\n return Network(tpm, cm, node_labels=('OR', 'AND'))\",\n \"def BVC(self, value):\\n if not self.reg.V:\\n self.reg.PC += value\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def point_addition(self, P, Q):\\n\\t\\traise Exception(NotImplemented)\",\n \"def add_pilot_compute_service(self, pjs):\\n self.pilot_job_services.append(pjs)\\n CoordinationAdaptor.update_cds(self.url, self)\",\n \"def _econ_append_pc(pp, cf_file, sites_per_worker=None):\\n multi_h5_res, hsds = check_res_file(cf_file)\\n if multi_h5_res:\\n res_cls = MultiFileResource\\n res_kwargs = {}\\n else:\\n res_cls = Resource\\n res_kwargs = {'hsds': hsds}\\n\\n with res_cls(cf_file, **res_kwargs) as f:\\n gid0 = f.meta['gid'].values[0]\\n gid1 = f.meta['gid'].values[-1]\\n\\n i0 = pp.index(gid0)\\n i1 = pp.index(gid1) + 1\\n pc = PointsControl.split(i0, i1, pp, sites_per_split=sites_per_worker)\\n\\n return pc\",\n \"def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]\",\n \"def addition(self):\\n\\t\\treturn lambda anything: self.__class__(\\n\\t\\t\\t(self[:], disj, checked_proposition(anything)[:])\\n\\t\\t)\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def add(self, p):\\n\\n self.poses.append(CalibrationPoint(p))\\n self.selected_point = len(self.poses) - 1\\n self.calibration_changed()\",\n \"def gate_mfcc(recurrent_net, sample_input):\\n length = sample_input.shape[1]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\\n select = sigmoid(select)\\n return np.sum(select * score) / np.sum(select)\",\n \"def get_bprop_assign_add(self):\\n\\n def bprop(x, y, out, dout):\\n return zeros_like(x), zeros_like(y)\\n return bprop\",\n \"def __add__(self, other)\\n \\n def __mul__(self, other):\\n print(\\\"Standard multiplication with\\\", other.which)\\n print(other.which)\\n \\n if isinstance(other, int):\\n print(\\\"Other is int\\\")\\n self.coefficients *= other\\n \\n return self\\n \\n else:\\n print(\\\"Other operator is spin operator\\\")\\n summandsNew = []\\n coeffsNew = []\\n for otherSummandIndex, otherSummand in enumerate(other.summands):\\n for thisSummandIndex, thisSummand in enumerate(self.summands):\\n summandsNew.append(flatten([thisSummand, otherSummand]))\\n coeffsNew.append(self.coefficients[thisSummandIndex]*other.coefficients[otherSummandIndex])\\n print(summandsNew) \\n self.coeffs = coeffsNew\\n self.summands = summandsNew\\n \\n return self\",\n \"def add_node(self, new_node: 'GraphNode'):\\n self.operator.add_node(new_node)\",\n \"def _compose(self, other):\\n if self.num_qubits != other.num_qubits:\\n raise QiskitError(\\\"Multiplication on different number of qubits.\\\")\\n result = CNOTDihedral(num_qubits=self.num_qubits)\\n result.shift = [\\n (x[0] + x[1]) % 2 for x in zip(self._z2matvecmul(other.linear, self.shift), other.shift)\\n ]\\n result.linear = self._z2matmul(other.linear, self.linear)\\n # Compute x' = B1*x + c1 using the p_j identity\\n new_vars = []\\n for i in range(self.num_qubits):\\n support = np.arange(other.num_qubits)[np.nonzero(self.linear[i])]\\n poly = SpecialPolynomial(self.num_qubits)\\n poly.set_pj(support)\\n if self.shift[i] == 1:\\n poly = -1 * poly\\n poly.weight_0 = (poly.weight_0 + 1) % 8\\n new_vars.append(poly)\\n # p' = p1 + p2(x')\\n result.poly = self.poly + other.poly.evaluate(new_vars)\\n return result\",\n \"def path_cost(self, c, state1, action, state2):\\n return c + 1\",\n \"def path_cost(self, c, state1, action, state2):\\n return c + 1\",\n \"def path_cost(self, c, state1, action, state2):\\n return c + 1\",\n \"def parameterise_gate(self, gate:Union[cirq.Gate, Callable]): \\n if isinstance(gate, cirq.Gate):\\n if isinstance(gate, (cirq.XXPowGate, cirq.YYPowGate, cirq.ZZPowGate)):\\n param = self.new_param()\\n return gate**param\\n return gate\\n elif isclass(gate) and issubclass(gate, cirq.Gate):\\n parameters = ParameterisedCircuit._get_gate_parameters(gate)\\n n_param = len(parameters)\\n params = self.new_param(size=n_param, as_array=True)\\n kwargs = {parameters[i]:params[i] for i in range(n_param)}\\n return gate(**kwargs) \\n else:\\n n_param = ParameterisedCircuit._get_parameter_count(gate)\\n params = self.new_param(size=n_param)\\n params = tuple(params) if isinstance(params, np.ndarray) else (params,) \\n return gate(*params)\",\n \"def __add__(self, other):\\n if type(other) == int or type(other) == float:\\n x = (other * Ccy.currencies[self.unit])\\n else:\\n x = (other.value / Ccy.currencies[other.unit] * Ccy.currencies[self.unit])\\n return Ccy(x + self.value, self.unit)\",\n \"def _AddCompound(self, kegg_id, how_many):\\n i = self._FindCompoundIndex(kegg_id)\\n if i is not None:\\n self.reactants[i].coeff += how_many\\n else:\\n self.reactants += [CompoundWithCoeff.FromId(how_many, kegg_id)]\\n \\n # clear the cache since the reaction has changed\\n self._catalyzing_enzymes = None\",\n \"def __iadd__(self, other: PointOrIterableOrScalar) -> PointType:\\n return self.__iop(other, operator.add)\",\n \"def __add__(self, other):\\n \\\"*** YOUR CODE HERE ***\\\"\",\n \"def path_cost(self, c, state1, action, state2):\\n # This should probably just be 1 every state....\\n return c + 1\",\n \"def path_cost(self, c, state1, action, state2):\\n # This should probably just be 1 every state....\\n return c + 1\",\n \"def __mul__(self, other):\\r\\n if isinstance(other, Operation):\\r\\n return Circuit().append(self, list(range(len(self.shape))), 0).append(\\r\\n other, list(range(len(self.shape), len(self.shape) + len(other.shape))), 0)\\r\\n else:\\r\\n return NotImplemented\",\n \"def gate_operation(self, operation, qubit_expr, params=None):\\n operation = QuantumCircuit._parse_gate_operation(operation)\\n if params is not None:\\n operation = operation(**params) \\n qubit = self.qr.get(qubit_expr) \\n return operation(qubit)\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def path_cost(self, c, state1, action, state2):\\n\\t\\treturn c + 1\",\n \"def add(self, proc: ImageProcessor):\\n self.chain.append(proc)\\n return self\",\n \"def cpf(self, cpf):\\n self._cpf = cpf\",\n \"def _add_op(value, sample_args, rationals_allowed):\\n entropy, sample_args = sample_args.peel()\\n if rationals_allowed and sample_args.count >= 3:\\n x = number.integer_or_rational(entropy, True)\\n else:\\n x = number.integer(entropy, True)\\n if random.choice([False, True]):\\n op_args = [x, value - x]\\n else:\\n op_args = [value - x, x]\\n return ops.Add, op_args, sample_args\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def cs_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\\n return self\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5904704","0.5707195","0.56965774","0.5647329","0.56336844","0.55492866","0.5349251","0.53450406","0.52863276","0.5273215","0.5263506","0.5254979","0.52324307","0.5214165","0.5191327","0.5182098","0.51805395","0.5169316","0.51630926","0.51592803","0.515315","0.51451474","0.51293314","0.5085484","0.50667167","0.50638175","0.5048495","0.5043423","0.50427836","0.5021548","0.5014238","0.49886066","0.49641576","0.49633637","0.4953432","0.4950759","0.4947763","0.49470386","0.4939548","0.49301916","0.49181622","0.48926735","0.48918173","0.48906004","0.48906004","0.48861173","0.4881314","0.48718944","0.48708656","0.4863456","0.48387572","0.4826239","0.48258805","0.48225388","0.48216614","0.48022735","0.47961068","0.47961068","0.4781896","0.4781488","0.4768157","0.47615305","0.47566402","0.47298142","0.47281703","0.47208038","0.47204536","0.47179508","0.47053662","0.46966743","0.46919554","0.4686536","0.46854606","0.46733728","0.46675012","0.46657917","0.46657848","0.4661229","0.46575475","0.4655412","0.46549964","0.46485612","0.46485612","0.46485612","0.46470648","0.4646638","0.46381903","0.46345687","0.46289843","0.4627503","0.4627503","0.46256435","0.4621628","0.46142924","0.46127802","0.4602133","0.46016654","0.45962325","0.45957646","0.45954257"],"string":"[\n \"0.5904704\",\n \"0.5707195\",\n \"0.56965774\",\n \"0.5647329\",\n \"0.56336844\",\n \"0.55492866\",\n \"0.5349251\",\n \"0.53450406\",\n \"0.52863276\",\n \"0.5273215\",\n \"0.5263506\",\n \"0.5254979\",\n \"0.52324307\",\n \"0.5214165\",\n \"0.5191327\",\n \"0.5182098\",\n \"0.51805395\",\n \"0.5169316\",\n \"0.51630926\",\n \"0.51592803\",\n \"0.515315\",\n \"0.51451474\",\n \"0.51293314\",\n \"0.5085484\",\n \"0.50667167\",\n \"0.50638175\",\n \"0.5048495\",\n \"0.5043423\",\n \"0.50427836\",\n \"0.5021548\",\n \"0.5014238\",\n \"0.49886066\",\n \"0.49641576\",\n \"0.49633637\",\n \"0.4953432\",\n \"0.4950759\",\n \"0.4947763\",\n \"0.49470386\",\n \"0.4939548\",\n \"0.49301916\",\n \"0.49181622\",\n \"0.48926735\",\n \"0.48918173\",\n \"0.48906004\",\n \"0.48906004\",\n \"0.48861173\",\n \"0.4881314\",\n \"0.48718944\",\n \"0.48708656\",\n \"0.4863456\",\n \"0.48387572\",\n \"0.4826239\",\n \"0.48258805\",\n \"0.48225388\",\n \"0.48216614\",\n \"0.48022735\",\n \"0.47961068\",\n \"0.47961068\",\n \"0.4781896\",\n \"0.4781488\",\n \"0.4768157\",\n \"0.47615305\",\n \"0.47566402\",\n \"0.47298142\",\n \"0.47281703\",\n \"0.47208038\",\n \"0.47204536\",\n \"0.47179508\",\n \"0.47053662\",\n \"0.46966743\",\n \"0.46919554\",\n \"0.4686536\",\n \"0.46854606\",\n \"0.46733728\",\n \"0.46675012\",\n \"0.46657917\",\n \"0.46657848\",\n \"0.4661229\",\n \"0.46575475\",\n \"0.4655412\",\n \"0.46549964\",\n \"0.46485612\",\n \"0.46485612\",\n \"0.46485612\",\n \"0.46470648\",\n \"0.4646638\",\n \"0.46381903\",\n \"0.46345687\",\n \"0.46289843\",\n \"0.4627503\",\n \"0.4627503\",\n \"0.46256435\",\n \"0.4621628\",\n \"0.46142924\",\n \"0.46127802\",\n \"0.4602133\",\n \"0.46016654\",\n \"0.45962325\",\n \"0.45957646\",\n \"0.45954257\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.61328435"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81753,"cells":{"query":{"kind":"string","value":"add CRX gate (controlled RX gate)."},"document":{"kind":"string","value":"def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self","def bcc(self, arg):\n\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def setRxConvolved(self, rx_convolved):\n \n self.rx_convolved = rx_convolved","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def CX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def adc(self, signal):","def _add_mxnet_ctc_loss(pred, seq_len, label):\n pred_ctc = mx.sym.Reshape(data=pred, shape=(-4, seq_len, -1, 0))\n\n loss = mx.sym.contrib.ctc_loss(data=pred_ctc, label=label)\n ctc_loss = mx.sym.MakeLoss(loss)\n\n softmax_class = mx.symbol.SoftmaxActivation(data=pred)\n softmax_loss = mx.sym.MakeLoss(softmax_class)\n softmax_loss = mx.sym.BlockGrad(softmax_loss)\n return mx.sym.Group([softmax_loss, ctc_loss])","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def _add_control_channel(self, attrs):\n _cable_data = {}\n _cable_data[\"crate\"] = self._crate\n _cable_data[\"module\"] = self._module\n _cable_data[\"channel\"] = int(attrs.get('number', \"\"))\n _cable_data[\"name\"] = str(attrs.get('name', \"\"))\n self._data.append(_cable_data)","def test_add(self):\n qc_cal = QuantumCircuit(2)\n qc_cal.rzx(0.5, 0, 1)\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\n\n qc = QuantumCircuit(2) & qc_cal\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\n\n qc = qc_cal & QuantumCircuit(2)\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def BCS(self, value):\n if self.reg.C:\n self.reg.PC += value","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def create_carry_condition(new_val, sub_op):\n if not sub_op:\n carry_cond = new_val > 0xFF\n else:\n carry_cond = new_val >= 0\n return carry_cond","def _compute_carry_and_output(self, x, h_tm1, c_tm1):\n x_i, x_f, x_c, x_o = x\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\n i = self.recurrent_activation(\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\n f = self.recurrent_activation(x_f + K.dot(\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\n o = self.recurrent_activation(\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\n return c, o","def cy(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CY(), target=[control, target])","def two_activation(self, output_reg):\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\n self._q_neuron.cx(self.inputs[0], self._output[output_reg])\n self._q_neuron.cx(self.inputs[1], self._output[output_reg])","def _add_ctc_loss(pred, seq_len, num_label, loss_type):\n label = mx.sym.Variable('label')\n if loss_type == 'warpctc':\n print(\"Using WarpCTC Loss\")\n sm = _add_warp_ctc_loss(pred, seq_len, num_label, label)\n else:\n print(\"Using MXNet CTC Loss\")\n assert loss_type == 'ctc'\n sm = _add_mxnet_ctc_loss(pred, seq_len, label)\n return sm","def test_iadd(self):\n qc_cal = QuantumCircuit(2)\n qc_cal.rzx(0.5, 0, 1)\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\n\n qc = QuantumCircuit(2)\n qc &= qc_cal\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)","def add(self, y):\n return circuit.add(self, y)","def connect(self, gate) :\n self.notifyList.append(gate)","def _template_circuit(self, amp_param) -> QuantumCircuit:\n gate = Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param])\n\n circuit = QuantumCircuit(1)\n circuit.append(gate, (0,))\n circuit.measure_active()\n\n return circuit","def rx(self):\n cmd = Command()\n cmd.set_num(0x1C)\n cmd.set_subcmd_num(0x00)\n cmd.set_data([0x00])\n self.connection.send_cmd(cmd.render())","def gate_mfcc(recurrent_net, sample_input):\n length = sample_input.shape[1]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\n select = sigmoid(select)\n return np.sum(select * score) / np.sum(select)","def __add_credit_cc(self):\n log.debug(\"Displaying __add_credit_cc\")\n # Create a keyboard to be sent later\n presets = self.cfg.ccard[\"payment_presets\"]\n keyboard = [[telegram.KeyboardButton(str(self.Price(preset)))] for preset in presets]\n keyboard.append([telegram.KeyboardButton(self.loc.get(\"menu_all_cancel\"))])\n # Boolean variable to check if the user has cancelled the action\n cancelled = False\n # Loop used to continue asking if there's an error during the input\n while not cancelled:\n # Send the message and the keyboard\n self.bot.send_message(self.chat.id, self.loc.get(\"payment_cc_amount\"),\n reply_markup=telegram.ReplyKeyboardMarkup(keyboard, one_time_keyboard=True))\n # Wait until a valid amount is sent\n selection = self.__wait_for_regex(r\"([0-9]+(?:[.,][0-9]+)?|\" + self.loc.get(\"menu_all_cancel\") + r\")\",\n cancellable=True)\n # If the user cancelled the action\n if isinstance(selection, CancelSignal):\n # Exit the loop\n cancelled = True\n continue\n # Convert the amount to an integer\n value = self.Price(selection)\n # Ensure the amount is within the range\n if value > self.Price(self.cfg.ccard[\"max_amount\"]):\n self.bot.send_message(self.chat.id,\n self.loc.get(\"error_payment_amount_over_max\",\n max_amount=self.Price(self.cfg.ccard[\"max_amount\"])))\n continue\n elif value < self.Price(self.cfg.ccard[\"min_amount\"]):\n self.bot.send_message(self.chat.id,\n self.loc.get(\"error_payment_amount_under_min\",\n min_amount=self.Price(self.cfg.ccard[\"min_amount\"])))\n continue\n break\n # If the user cancelled the action...\n else:\n # Exit the function\n return\n # Issue the payment invoice\n self.__make_payment(amount=value)","def bcs(self, arg):\n\n self.pc += arg if self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def adc_cal():\n def r(x):\n return (ord(x[0]) | ord(x[1]) << 8, ord(x[2]) | ord(x[3]) << 8)\n return r","def gate_lfcc(recurrent_net, sample_input):\n length = sample_input.shape[0]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[i, :])\n select = sigmoid(select)\n score = sigmoid(score)\n return np.sum(select * score) / np.sum(select)","def control(operation, num_ctrl_qubits=1, label=None):\n from math import pi\n # pylint: disable=cyclic-import\n import qiskit.circuit.controlledgate as controlledgate\n from qiskit.circuit.quantumregister import QuantumRegister\n from qiskit.circuit.quantumcircuit import QuantumCircuit\n # pylint: disable=unused-import\n import qiskit.extensions.standard.multi_control_rotation_gates\n import qiskit.extensions.standard.multi_control_toffoli_gate\n import qiskit.extensions.standard.multi_control_u1_gate\n\n q_control = QuantumRegister(num_ctrl_qubits, name='control')\n q_target = QuantumRegister(operation.num_qubits, name='target')\n q_ancillae = None # TODO: add\n\n qc = QuantumCircuit(q_control, q_target)\n\n if operation.name == 'x' or (\n isinstance(operation, controlledgate.ControlledGate) and\n operation.base_gate_name == 'x'):\n qc.mct(q_control[:] + q_target[:-1],\n q_target[-1],\n None,\n mode='noancilla')\n elif operation.name == 'rx':\n qc.mcrx(operation.definition[0][0].params[0], q_control, q_target[0],\n use_basis_gates=True)\n elif operation.name == 'ry':\n qc.mcry(operation.definition[0][0].params[0], q_control, q_target[0],\n q_ancillae, use_basis_gates=True)\n elif operation.name == 'rz':\n qc.mcrz(operation.definition[0][0].params[0], q_control, q_target[0],\n use_basis_gates=True)\n else:\n bgate = _unroll_gate(operation, ['u1', 'u3', 'cx'])\n # now we have a bunch of single qubit rotation gates and cx\n for rule in bgate.definition:\n if rule[0].name == 'u3':\n theta, phi, lamb = rule[0].params\n if phi == -pi/2 and lamb == pi/2:\n qc.mcrx(theta, q_control, q_target[rule[1][0].index],\n use_basis_gates=True)\n elif phi == 0 and lamb == 0:\n qc.mcry(theta, q_control, q_target[rule[1][0].index],\n q_ancillae, mode='noancilla', use_basis_gates=True)\n elif theta == 0 and phi == 0:\n qc.mcrz(lamb, q_control, q_target[rule[1][0].index],\n use_basis_gates=True)\n else:\n qc.mcrz(lamb, q_control, q_target[rule[1][0].index],\n use_basis_gates=True)\n qc.mcry(theta, q_control, q_target[rule[1][0].index],\n q_ancillae, use_basis_gates=True)\n qc.mcrz(phi, q_control, q_target[rule[1][0].index],\n use_basis_gates=True)\n elif rule[0].name == 'u1':\n qc.mcu1(rule[0].params[0], q_control, q_target[rule[1][0].index])\n elif rule[0].name == 'cx':\n qc.mct(q_control[:] + [q_target[rule[1][0].index]],\n q_target[rule[1][1].index],\n None,\n mode='noancilla')\n else:\n raise QiskitError('gate contains non-controllable intructions')\n instr = qc.to_instruction()\n if isinstance(operation, controlledgate.ControlledGate):\n new_num_ctrl_qubits = num_ctrl_qubits + operation.num_ctrl_qubits\n base_name = operation.base_gate_name\n base_gate = operation.base_gate\n base_gate_name = operation.base_gate_name\n else:\n new_num_ctrl_qubits = num_ctrl_qubits\n base_name = operation.name\n base_gate = operation.__class__\n base_gate_name = operation.name\n # In order to maintain some backward compatibility with gate names this\n # uses a naming convention where if the number of controls is <=2 the gate\n # is named like \"cc<base_gate_name>\", else it is named like\n # \"c<num_ctrl_qubits><base_name>\".\n if new_num_ctrl_qubits > 2:\n ctrl_substr = 'c{0:d}'.format(new_num_ctrl_qubits)\n else:\n ctrl_substr = ('{0}' * new_num_ctrl_qubits).format('c')\n new_name = '{0}{1}'.format(ctrl_substr, base_name)\n cgate = controlledgate.ControlledGate(new_name,\n instr.num_qubits,\n operation.params,\n label=label,\n num_ctrl_qubits=new_num_ctrl_qubits,\n definition=instr.definition)\n cgate.base_gate = base_gate\n cgate.base_gate_name = base_gate_name\n return cgate","def add_reactive(self, reactive):\n\t\tself._reactives.append(reactive)","def _control_predefined(operation, num_ctrl_qubits):\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\n if num_ctrl_qubits == 1:\n import qiskit.extensions.standard.cx\n cgate = qiskit.extensions.standard.cx.CnotGate()\n else:\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n elif operation.name == 'y':\n import qiskit.extensions.standard.cy\n cgate = qiskit.extensions.standard.cy.CyGate()\n elif operation.name == 'z':\n import qiskit.extensions.standard.cz\n cgate = qiskit.extensions.standard.cz.CzGate()\n elif operation.name == 'h':\n import qiskit.extensions.standard.ch\n cgate = qiskit.extensions.standard.ch.CHGate()\n elif operation.name in {'rx', 'ry', 'rz'}:\n if operation.name == 'rx':\n import qiskit.extensions.standard.crx\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\n elif operation.name == 'ry':\n import qiskit.extensions.standard.cry\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\n else: # operation.name == 'rz'\n import qiskit.extensions.standard.crz\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\n if num_ctrl_qubits == 1:\n return cgate\n else:\n # only predefined for one control qubit\n return cgate.control(num_ctrl_qubits - 1)\n elif operation.name == 'swap':\n import qiskit.extensions.standard.cswap\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\n elif operation.name == 'u1':\n import qiskit.extensions.standard.cu1\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\n elif operation.name == 'u3':\n import qiskit.extensions.standard.cu3\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\n elif operation.name == 'cx':\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n else:\n raise QiskitError('No standard controlled gate for \"{}\"'.format(\n operation.name))\n return cgate","def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def read_bits_c(self, ctrl_pin):\n while True:\n self.read_bits(ctrl_pin)\n time.sleep(1)","def enable_cl1_direct(self):\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\n self.write_versa5(0x18,0x20)\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\n self.write_versa5(0x13,0x03) ## Switch to clock\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew","def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\n return self","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def _template_circuit(self, amp_param) -> QuantumCircuit:\n circuit = QuantumCircuit(1)\n circuit.x(0)\n circuit.append(Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param]), (0,))\n circuit.measure_active()\n\n return circuit","def ccx(self, q0, q1, q2, ctrl=None):\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\n return self","def add_corridor_constraint(self,seg,r,weight=1.0):\n\n constraint_type = \"cylinder\"\n params = dict()\n params['x1'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg],\n self.qr_polytraj.waypoints['y'][0,seg],\n self.qr_polytraj.waypoints['z'][0,seg]])\n params['x2'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg+1],\n self.qr_polytraj.waypoints['y'][0,seg+1],\n self.qr_polytraj.waypoints['z'][0,seg+1]])\n params['der'] = 0\n params['l'] = r # Give the same radius buffer on the end caps\n params['r'] = r\n params['weight'] = weight\n params['keep_out'] = False\n params['active_seg'] = seg\n\n\n self.qr_polytraj.add_constraint(constraint_type,params,dynamic_weighting=False,sum_func=False)","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def add_rxn(self, reaction: db.Reaction):\n # Add two rxn nodes\n rxn_nodes = []\n reaction_id = reaction.id().string()\n\n for i in range(0, 2):\n # Add rxn node between lhs and rhs compound\n rxn_node = ';'.join([reaction_id, str(i)])\n rxn_node += ';'\n self.graph.add_node(rxn_node, color='rxn_node')\n rxn_nodes.append(rxn_node)\n # Convert to strings\n reactants = reaction.get_reactants(db.Side.BOTH)\n reactant_types = reaction.get_reactant_types(db.Side.BOTH)\n weights = self._get_weight(reaction)\n # Add lhs aggregates and connect\n for lhs_cmp, lhs_type in zip([i.string() for i in reactants[0]],\n [i.name for i in reactant_types[0]]):\n if lhs_cmp not in self.graph:\n self.graph.add_node(lhs_cmp, type=lhs_type)\n required_cmps_lhs = [s.string() for s in reactants[0]]\n required_cmps_lhs.remove(lhs_cmp)\n self.graph.add_edge(lhs_cmp, rxn_nodes[0], weight=weights[0], required_compounds=required_cmps_lhs,\n required_compound_costs=None)\n self.graph.add_edge(rxn_nodes[1], lhs_cmp, weight=0.0, required_compounds=None)\n # Add rhs aggregates and connect\n for rhs_cmp, rhs_type in zip([i.string() for i in reactants[1]],\n [i.name for i in reactant_types[1]]):\n if rhs_cmp not in self.graph:\n self.graph.add_node(rhs_cmp, type=rhs_type)\n required_cmps_rhs = [s.string() for s in reactants[1]]\n required_cmps_rhs.remove(rhs_cmp)\n self.graph.add_edge(rhs_cmp, rxn_nodes[1], weight=weights[1], required_compounds=required_cmps_rhs,\n required_compound_costs=None)\n self.graph.add_edge(rxn_nodes[0], rhs_cmp, weight=0.0, required_compounds=None)\n\n # # # Loop over reaction nodes to add required compounds info to downwards edges; might be unnecessary\n node_index = 1\n for node in rxn_nodes:\n for key in self.graph[node].keys():\n self.graph.edges[node, key]['required_compounds'] = \\\n self.graph.edges[key, rxn_nodes[node_index]]['required_compounds']\n node_index -= 1","def __init__(self):\n super().__init__(\"ccx\", 3, [])","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def rtl_state_and_more():\n if not cso.enable:\n state.next = states.idle\n bcnt.next = 0\n treg.next = 0\n \n itx.read.next = False\n irx.write.next = False\n\n x_sck.next = False\n x_ss.next = False\n else:\n if not cso.freeze:\n # ~~~~ Idle state ~~~~\n if state == states.idle:\n bcnt.next = 7\n treg.next = itx.read_data\n x_sck.next = cso.clock_polarity\n irx.write.next = False\n \n if not itx.empty and not irx.full:\n itx.read.next = True\n x_ss.next = False\n if cso.clock_phase: # Clock in on second phase\n state.next = states.wait_hclk\n else: # Clock in on first phase\n state.next = states.data_in\n else:\n itx.read.next = False\n x_ss.next = True\n\n # ~~~~ Wait half clock period for cpha=1 ~~~~\n elif state == states.wait_hclk:\n itx.read.next = False\n irx.write.next = False\n if ena:\n x_sck.next = not x_sck\n state.next = states.data_in\n\n # ~~~~ Clock data in (and out) ~~~~\n elif state == states.data_in:\n itx.read.next = False\n irx.write.next = False\n if ena: # clk div\n x_sck.next = not x_sck\n rreg.next = concat(rreg[7:0], x_miso)\n \n if cso.clock_phase and bcnt == 0:\n irx.write.next = True\n if itx.empty or irx.full:\n state.next = states.end\n else:\n state.next = states.data_change\n else:\n state.next = states.data_change\n\n # ~~~~ Get ready for next byte out/in ~~~~\n elif state == states.data_change:\n itx.read.next = False\n irx.write.next = False\n if ena:\n x_sck.next = not x_sck\n if bcnt == 0: \n if not cso.clock_phase:\n irx.write.next = True\n \n if itx.empty or irx.full:\n state.next = states.end\n else: # more data to transfer\n bcnt.next = 7\n state.next = states.data_in\n itx.read.next = True\n treg.next = itx.read_data\n else:\n treg.next = concat(treg[7:0], intbv(0)[1:])\n bcnt.next = bcnt - 1 \n state.next = states.data_in\n\n # ~~~~ End state ~~~~\n elif state == states.end:\n itx.read.next = False\n irx.write.next = False\n if ena: # Wait half clock cycle go idle\n state.next = states.idle\n\n # Shouldn't happen, error in logic\n else:\n state.next = states.idle\n assert False, \"SPI Invalid State\"","def L3G_acquisition(add):\n\n # control register\n CTRL_REG1 = 0x20\n CTRL_REG4 = 0x23\n LOW_ODR = 0x39\n FIFO_CTRL = 0x2e\n # output register\n OUT_X_L = 0x28\n OUT_X_H = 0x29\n OUT_Y_L = 0x2a\n OUT_Y_H = 0x2b\n OUT_Z_L = 0x2c\n OUT_Z_H = 0x2d\n\n # low odr mode, 50Hz, 2000 dps full scale\n bus.write_byte_data(add, CTRL_REG1, 0b10001111)\n bus.write_byte_data(add, CTRL_REG4, 0b00110000)\n bus.write_byte_data(add, LOW_ODR, 0b00000001)\n bus.write_byte_data(add, FIFO_CTRL, 0b01000000)\n\n # accelerator accumulate\n while True:\n uint16_gx = (bus.read_byte_data(add, OUT_X_H) << 8) + \\\n bus.read_byte_data(add, OUT_X_L)\n uint16_gy = (bus.read_byte_data(add, OUT_Y_H) << 8) + \\\n bus.read_byte_data(add, OUT_Y_L)\n uint16_gz = (bus.read_byte_data(add, OUT_Z_H) << 8) + \\\n bus.read_byte_data(add, OUT_Z_L)\n\n gx = twos_comp(uint16_gx, 16)\n gy = twos_comp(uint16_gy, 16)\n gz = twos_comp(uint16_gz, 16)\n\n yield [gx, gy, gz]","def convert_to_circuit(x):\n y = np.arcsin(x)\n z = np.arccos(x**2)\n qubits = cirq.GridQubit.rect(5, 1)\n circuit = cirq.Circuit()\n for i in range(5):\n circuit.append(cirq.ry(y).on(qubits[i]))\n circuit.append(cirq.rz(z).on(qubits[i]))\n return circuit","def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def add_control(operation, num_ctrl_qubits, label):\n if isinstance(operation, UnitaryGate):\n # attempt decomposition\n operation._define()\n if _control_definition_known(operation, num_ctrl_qubits):\n return _control_predefined(operation, num_ctrl_qubits)\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def csw(self, q0, q1, q2, ctrl=None):\n self.cx(q2,q1,ctrl=ctrl).ccx(q0,q1,q2,ctrl=ctrl).cx(q2,q1,ctrl=ctrl)\n return self","def circuitSat(C):","def test_coreg_shift(self):\r\n with gw.open(l8_224077_20200518_B2) as target, gw.open(\r\n l8_224077_20200518_B4\r\n ) as reference:\r\n with tempfile.TemporaryDirectory() as tmp:\r\n # Shift by 1 pixel in each direction\r\n target_shifted = shift(target, x=1, y=1)\r\n tmp_file = Path(tmp) / '_tmp_shift.tif'\r\n target_shifted.gw.save(tmp_file, overwrite=True)\r\n with gw.open(tmp_file) as target_shifted:\r\n # Co-register the shifted data\r\n shifted = gw.coregister(\r\n target=target_shifted,\r\n reference=reference,\r\n ws=(256, 256),\r\n r_b4match=1,\r\n s_b4match=1,\r\n max_shift=5,\r\n resamp_alg_deshift='nearest',\r\n resamp_alg_calc='cubic',\r\n out_gsd=[target_shifted.gw.celly, reference.gw.celly],\r\n q=True,\r\n nodata=(0, 0),\r\n CPUs=1,\r\n )\r\n self.assertFalse(\r\n np.allclose(\r\n target.values[:, :-1, :-1],\r\n target_shifted.values[:, :-1, :-1],\r\n )\r\n )\r\n # Check if the corrected data match the original (unshifted) target\r\n self.assertTrue(\r\n np.allclose(\r\n target.values[:, :-1, :-1],\r\n shifted.values[:, :-1, :-1],\r\n )\r\n )","def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]","def YY(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.YY, qubit_expr)","def extend_circuit(self, circid=None, hops=None):\r\n if circid is None:\r\n circid = 0\r\n if hops is None:\r\n hops = \"\"\r\n plog(\"DEBUG\", \"Extending circuit\")\r\n lines = self.sendAndRecv(\"EXTENDCIRCUIT %d %s\\r\\n\"\r\n %(circid, \",\".join(hops)))\r\n tp,msg,_ = lines[0]\r\n m = re.match(r'EXTENDED (\\S*)', msg)\r\n if not m:\r\n raise ProtocolError(\"Bad extended line %r\",msg)\r\n plog(\"DEBUG\", \"Circuit extended\")\r\n return int(m.group(1))","def update_control(self):\n self._control_ctr += 0x01","def get_crd_cc(self, axis, shaped=False):\n return self._src_crds.get_cc(axis, shaped=shaped)","def compile(self, seq, registers):\n\n # Check which modes are actually being used\n used_modes = []\n for operations in seq:\n modes = [modes_label.ind for modes_label in operations.reg]\n used_modes.append(modes)\n\n used_modes = list(set(item for sublist in used_modes for item in sublist))\n\n # dictionary mapping the used modes to consecutive non-negative integers\n dict_indices = {used_modes[i]: i for i in range(len(used_modes))}\n nmodes = len(used_modes)\n\n # We start with an identity then sequentially update with the gate transformations\n T = np.identity(nmodes, dtype=np.complex128)\n\n # Now we will go through each operation in the sequence `seq` and apply it to T\n for operations in seq:\n name = operations.op.__class__.__name__\n params = par_evaluate(operations.op.p)\n modes = [modes_label.ind for modes_label in operations.reg]\n if name == \"Rgate\":\n G = np.exp(1j * params[0])\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\n elif name == \"LossChannel\":\n G = np.sqrt(params[0])\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\n elif name == \"Interferometer\":\n U = params[0]\n if U.shape == (1, 1):\n T = _apply_one_mode_gate(U[0, 0], T, dict_indices[modes[0]])\n elif U.shape == (2, 2):\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\n else:\n modes = [dict_indices[mode] for mode in modes]\n U_expand = np.eye(nmodes, dtype=np.complex128)\n U_expand[np.ix_(modes, modes)] = U\n T = U_expand @ T\n elif name == \"PassiveChannel\":\n T0 = params[0]\n if T0.shape == (1, 1):\n T = _apply_one_mode_gate(T0[0, 0], T, dict_indices[modes[0]])\n elif T0.shape == (2, 2):\n T = _apply_two_mode_gate(T0, T, dict_indices[modes[0]], dict_indices[modes[1]])\n else:\n modes = [dict_indices[mode] for mode in modes]\n T0_expand = np.eye(nmodes, dtype=np.complex128)\n T0_expand[np.ix_(modes, modes)] = T0\n T = T0_expand @ T\n elif name == \"BSgate\":\n G = _beam_splitter_passive(params[0], params[1])\n T = _apply_two_mode_gate(G, T, dict_indices[modes[0]], dict_indices[modes[1]])\n elif name == \"MZgate\":\n v = np.exp(1j * params[0])\n u = np.exp(1j * params[1])\n U = 0.5 * np.array([[u * (v - 1), 1j * (1 + v)], [1j * u * (1 + v), 1 - v]])\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\n elif name == \"sMZgate\":\n exp_sigma = np.exp(1j * (params[0] + params[1]) / 2)\n delta = (params[0] - params[1]) / 2\n U = exp_sigma * np.array(\n [[np.sin(delta), np.cos(delta)], [np.cos(delta), -np.sin(delta)]]\n )\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\n\n ord_reg = [r for r in list(registers) if r.ind in used_modes]\n ord_reg = sorted(list(ord_reg), key=lambda x: x.ind)\n\n return [Command(ops.PassiveChannel(T), ord_reg)]","def _add_warp_ctc_loss(pred, seq_len, num_label, label):\n label = mx.sym.Reshape(data=label, shape=(-1,))\n label = mx.sym.Cast(data=label, dtype='int32')\n return mx.sym.WarpCTC(data=pred, label=label, label_length=num_label, input_length=seq_len)","def three_activation(self, output_reg):\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\n self._q_neuron.ccx(self.inputs[1], self.inputs[2], self._output[output_reg])\n self._q_neuron.ccx(self.inputs[0], self.inputs[2], self._output[output_reg])","def add_road(ccTremb):\n pass","def enable_cl2_copy_ad9866(self):\n self.write_versa5(0x62,0x3b) ## Clock2 CMOS1 output, 3.3V\n self.write_versa5(0x2c,0x01) ## Enable aux output on clock 1\n self.write_versa5(0x31,0x0c) ## Use clock1 aux output as input for clock2\n self.write_versa5(0x63,0x01) ## Enable clock2","def _process_cnot(self, node):\n id0 = self._process_bit_id(node.children[0])\n id1 = self._process_bit_id(node.children[1])\n if not(len(id0) == len(id1) or len(id0) == 1 or len(id1) == 1):\n raise UnrollerError(\"internal error: qreg size mismatch\",\n \"line=%s\" % node.line, \"file=%s\" % node.file)\n maxidx = max([len(id0), len(id1)])\n for idx in range(maxidx):\n if len(id0) > 1 and len(id1) > 1:\n self.backend.cx(id0[idx], id1[idx])\n elif len(id0) > 1:\n self.backend.cx(id0[idx], id1[0])\n else:\n self.backend.cx(id0[0], id1[idx])","def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])","def add_scan(self, newdat: base.MSGdata_Type) -> None:\n add_lst = [cont for tag, cont in newdat if (tag == 'EP' or tag == 'BC') and cont[:4] == 'CHEM']\n add_lst.sort()\n if len(add_lst) > 0:\n for cont in add_lst:\n self._register_RFID_token(cont)\n self.post_add_scan_CB()","def addTrafficCross(self, byte):\n self.byte_cross_group += byte","def _gcl(x, r, D, Ia, Ct):\n\n Area = np.pi * D ** 2.0 / 4.0\n m = 1.0 / (np.sqrt(1.0 - Ct))\n k = np.sqrt((m + 1.0) / 2.0)\n\n a1 = 0.435449861 # empirically determined\n a2 = 0.797853685\n a3 = -0.124807893\n a4 = 0.136821858\n b1 = 15.6298\n b2 = 1.0\n R96 = a1 * (np.exp(a2 * Ct * Ct + a3 * Ct + a4)) * (b1 * Ia + b2) * D\n\n x0 = (9.6 * D) / ((2.0 * R96 / (k * D)) ** 3.0 - 1.0)\n term1 = (k * D / 2.0) ** (5.0 / 2.0)\n term2 = (105.0 / (2.0 * np.pi)) ** (-0.5)\n term3 = (Ct * Area * x0) ** (-5.0 / 6.0)\n c1 = term1 * term2 * term3\n # c45=3*(c1) ** 2\n\n term10 = 0.1111 # * WindSpeed # U/9.0\n term20 = (Ct * Area * (x + x0) ** (-2.0)) ** (1.0 / 3.0)\n term310 = (r ** (3.0 / 2.0))\n term320 = (3.0 * c1 * c1 * Ct * Area * (x + x0)) ** (-0.5)\n term30 = term310 * term320\n term40 = ((35.0 / (2.0 * np.pi)) ** (3.0 / 10.0)) * \\\n (3.0 * c1 * c1) ** (-1.0 / 5.0)\n DU1 = -term10 * term20 * (term30 - term40) ** 2.0\n\n DU = DU1 # + w2 * DU2\n Rw = ((105 * c1 ** 2.0 / (2 * np.pi)) ** (1. / 5.)) * \\\n (Ct * Area * (x + x0)) ** (1. / 3.)\n return DU, Rw","def continuous_adc(self):\n try:\n self._hydrabus.write(b\"\\x15\")\n while 1:\n v = self._hydrabus.read(2)\n except KeyboardInterrupt:\n self._hydrabus.write(b\"\\x00\")\n self._hydrabus.reset()\n return True","def rx(self, q0, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_X, qid=[q0], phase=phase, ctrl=ctrl)\n return self","def _add_cmd(self, cmd):\n if cmd.gate == Allocate:\n self._active_qubits += 1\n elif cmd.gate == Deallocate:\n self._active_qubits -= 1\n elif cmd.gate == Measure:\n for qureg in cmd.qubits:\n for qubit in qureg:\n self.main_engine.set_measurement_result(qubit, 0)\n elif self._is_rotation(cmd):\n self._num_rotations += 1\n self._rotations.append(self._decompose_rotation(cmd))","def add_clr(self, kind, min_lr, max_lr, cycle_length):\n if kind == 0:\n self.callbacks.append(CyclicLR(base_lr=min_lr, max_lr=max_lr, step_size=cycle_length/2, mode='triangular2',\n plot=True, save_plot_prefix=self.config.exp_name))\n elif kind == 1:\n self.callbacks.append(CyclicLR_1(min_lr=min_lr, max_lr=max_lr, cycle_length=cycle_length, plot=True,\n save_plot_prefix=self.config.exp_name))\n elif kind == 2:\n self.callbacks.append(CyclicLR_2(min_lr=min_lr, max_lr=max_lr, cycle_length=cycle_length, plot=True,\n save_plot_prefix=self.config.exp_name))\n else:\n raise ValueError('param `kind` not understood : {}'.format(kind))\n print('Logging Info - Callback Added: CLR_{}...'.format(kind))","def gate_operation(self, operation, qubit_expr, params=None):\n operation = QuantumCircuit._parse_gate_operation(operation)\n if params is not None:\n operation = operation(**params) \n qubit = self.qr.get(qubit_expr) \n return operation(qubit)","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def getRxConvolved(self):\n \n return self.rx_convolved","def add_readout(self, gate:Union[str, cirq.Gate]='XX',\n readout_qubit:Optional['cirq.GridQubit']=None):\n parsed_gate = QuantumCircuit._parse_gate_operation(gate)\n readout_qubit = cirq.GridQubit(-1, -1) if readout_qubit is None else readout_qubit\n for qubit in self.qubits:\n final_gate = self.parameterise_gate(parsed_gate)\n self.apply_gate_operation(final_gate, (readout_qubit, qubit))\n if self.flatten_circuit:\n self.flatten() \n self._readout_qubit = readout_qubit","def cvChin(ctrlName, r=1):\r\n # create a simple circle curve:\r\n curve = cmds.curve(n=ctrlName, d=3, p=[(0, 0.8*r, -0.5*r), (0, 0.9*r, -0.7*r), (0, 0, -0.5*r), (0, -0.8*r, -0.7*r), (0, -0.8*r, 1.4*r), (0, -0.3*r, 1.3*r), (0, 0, 1.2*r), (0, 0, 0), (0, 0.8*r, -0.3*r), (0, 0.8*r, -0.5*r)] )\r\n # rename curveShape:\r\n renameShape([curve])\r\n return curve","def gate(self):\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)","def rx(self, rx):\n\n self.logger.debug(\"In 'rx' setter.\")\n\n self._rx = rx","def add_connector(self):\n \n no = len(self.connectors)\n state = {}\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % no\n \n if len(self.connectors)>0:\n state = self.connectors[-1].get_state()\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % (no)\n else:\n if self.mount == self.MOUNT_THT:\n state[\"p_shape\"] = Con.SHAPE_HOLE\n elif self.mount == self.MOUNT_SMD:\n state[\"p_shape\"] = Con.SHAPE_PAD\n \n c = Con(no)\n c.set_state(state) \n \n self.sch_layers[\"pins\"].add(c.s_svg)\n self.pcb_layers[\"copper1\"].add(c.p_svg)\n self.connectors.append(c)","def convert_C_instruction(self, instruction):\n comp, dest, jump = self.parse(instruction)\n\n return f\"111{convert_comp(comp)}{convert_dest(dest)}\" \\\n f\"{convert_jump(jump)}\"","def plot_cnxs(self,x_shift,y_shift):\n\n if not self.cnxs: return # Bounce if option not selected\n\n self.node_cnx_crds[:,:2] += x_shift*self.pbc[0]\n self.node_cnx_crds[:,2:] += y_shift*self.pbc[1]\n for cnx_crd in self.node_cnx_crds:\n self.ax.plot(cnx_crd[:2],cnx_crd[2:],c=self.lc,lw=self.lw)\n self.node_cnx_crds[:,:2] -= x_shift*self.pbc[0]\n self.node_cnx_crds[:,2:] -= y_shift*self.pbc[1]","def __init__(self,\n sub_gate: raw_types.Gate,\n control_qubits: Sequence[Optional[raw_types.Qid]] = None,\n num_controls: int = None) -> None:\n if num_controls is None:\n num_controls = 1 if control_qubits is None else len(control_qubits)\n if control_qubits is None:\n control_qubits = ()\n if num_controls < len(control_qubits):\n raise ValueError('More specified control qubits than num_controls')\n\n # Leave unspecified controls as Nones.\n self.control_qubits = ((None,) * (num_controls - len(control_qubits)) +\n tuple(control_qubits)) # type: ignore\n\n # Flatten nested ControlledGates.\n if isinstance(sub_gate, ControlledGate):\n self.sub_gate = sub_gate.sub_gate # type: ignore\n self.control_qubits += sub_gate.control_qubits\n else:\n self.sub_gate = sub_gate","def ch(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_H, qid=[q0,q1], ctrl=ctrl)\n return self","def _tk1_to_rotations(a: float, b: float, c: float) -> Circuit:\n circ = Circuit(1)\n circ.Rz(c, 0).Rx(b, 0).Rz(a, 0)\n return circ","def construct_qcbm(circuit, n_qubits, depth):\n\n for d in range(depth):\n for i in range(n_qubits):\n circuit.append_gate(Gate('X', target = i, angle = np.random.random()*np.pi*2))\n circuit.append_gate(Gate('Z', target = i, angle = np.random.random()*np.pi*2))\n if n_qubits != 1:\n for i in range(n_qubits):\n circuit.append_gate(Gate('CNOT', control = i, target = (i+1)%n_qubits))\n return circuit","def _compute_carry_and_output_fused(self, z, c_tm1):\n z0, z1, z2, z3 = z\n i = self.recurrent_activation(z0)\n f = self.recurrent_activation(z1)\n c = f * c_tm1 + i * self.activation(z2)\n o = self.recurrent_activation(z3)\n return c, o","def cphaseshift10(control: QubitInput, target: QubitInput, angle: float) -> Instruction:\n return Instruction(CPhaseShift10(angle), target=[control, target])"],"string":"[\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def cxr(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def cxr_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def bcc(self, arg):\\n\\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def setRxConvolved(self, rx_convolved):\\n \\n self.rx_convolved = rx_convolved\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def CX(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def adc(self, signal):\",\n \"def _add_mxnet_ctc_loss(pred, seq_len, label):\\n pred_ctc = mx.sym.Reshape(data=pred, shape=(-4, seq_len, -1, 0))\\n\\n loss = mx.sym.contrib.ctc_loss(data=pred_ctc, label=label)\\n ctc_loss = mx.sym.MakeLoss(loss)\\n\\n softmax_class = mx.symbol.SoftmaxActivation(data=pred)\\n softmax_loss = mx.sym.MakeLoss(softmax_class)\\n softmax_loss = mx.sym.BlockGrad(softmax_loss)\\n return mx.sym.Group([softmax_loss, ctc_loss])\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def _add_control_channel(self, attrs):\\n _cable_data = {}\\n _cable_data[\\\"crate\\\"] = self._crate\\n _cable_data[\\\"module\\\"] = self._module\\n _cable_data[\\\"channel\\\"] = int(attrs.get('number', \\\"\\\"))\\n _cable_data[\\\"name\\\"] = str(attrs.get('name', \\\"\\\"))\\n self._data.append(_cable_data)\",\n \"def test_add(self):\\n qc_cal = QuantumCircuit(2)\\n qc_cal.rzx(0.5, 0, 1)\\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\\n\\n qc = QuantumCircuit(2) & qc_cal\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\\n\\n qc = qc_cal & QuantumCircuit(2)\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def BCS(self, value):\\n if self.reg.C:\\n self.reg.PC += value\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def create_carry_condition(new_val, sub_op):\\n if not sub_op:\\n carry_cond = new_val > 0xFF\\n else:\\n carry_cond = new_val >= 0\\n return carry_cond\",\n \"def _compute_carry_and_output(self, x, h_tm1, c_tm1):\\n x_i, x_f, x_c, x_o = x\\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\\n i = self.recurrent_activation(\\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\\n f = self.recurrent_activation(x_f + K.dot(\\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\\n o = self.recurrent_activation(\\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\\n return c, o\",\n \"def cy(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CY(), target=[control, target])\",\n \"def two_activation(self, output_reg):\\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\\n self._q_neuron.cx(self.inputs[0], self._output[output_reg])\\n self._q_neuron.cx(self.inputs[1], self._output[output_reg])\",\n \"def _add_ctc_loss(pred, seq_len, num_label, loss_type):\\n label = mx.sym.Variable('label')\\n if loss_type == 'warpctc':\\n print(\\\"Using WarpCTC Loss\\\")\\n sm = _add_warp_ctc_loss(pred, seq_len, num_label, label)\\n else:\\n print(\\\"Using MXNet CTC Loss\\\")\\n assert loss_type == 'ctc'\\n sm = _add_mxnet_ctc_loss(pred, seq_len, label)\\n return sm\",\n \"def test_iadd(self):\\n qc_cal = QuantumCircuit(2)\\n qc_cal.rzx(0.5, 0, 1)\\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\\n\\n qc = QuantumCircuit(2)\\n qc &= qc_cal\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def connect(self, gate) :\\n self.notifyList.append(gate)\",\n \"def _template_circuit(self, amp_param) -> QuantumCircuit:\\n gate = Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param])\\n\\n circuit = QuantumCircuit(1)\\n circuit.append(gate, (0,))\\n circuit.measure_active()\\n\\n return circuit\",\n \"def rx(self):\\n cmd = Command()\\n cmd.set_num(0x1C)\\n cmd.set_subcmd_num(0x00)\\n cmd.set_data([0x00])\\n self.connection.send_cmd(cmd.render())\",\n \"def gate_mfcc(recurrent_net, sample_input):\\n length = sample_input.shape[1]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\\n select = sigmoid(select)\\n return np.sum(select * score) / np.sum(select)\",\n \"def __add_credit_cc(self):\\n log.debug(\\\"Displaying __add_credit_cc\\\")\\n # Create a keyboard to be sent later\\n presets = self.cfg.ccard[\\\"payment_presets\\\"]\\n keyboard = [[telegram.KeyboardButton(str(self.Price(preset)))] for preset in presets]\\n keyboard.append([telegram.KeyboardButton(self.loc.get(\\\"menu_all_cancel\\\"))])\\n # Boolean variable to check if the user has cancelled the action\\n cancelled = False\\n # Loop used to continue asking if there's an error during the input\\n while not cancelled:\\n # Send the message and the keyboard\\n self.bot.send_message(self.chat.id, self.loc.get(\\\"payment_cc_amount\\\"),\\n reply_markup=telegram.ReplyKeyboardMarkup(keyboard, one_time_keyboard=True))\\n # Wait until a valid amount is sent\\n selection = self.__wait_for_regex(r\\\"([0-9]+(?:[.,][0-9]+)?|\\\" + self.loc.get(\\\"menu_all_cancel\\\") + r\\\")\\\",\\n cancellable=True)\\n # If the user cancelled the action\\n if isinstance(selection, CancelSignal):\\n # Exit the loop\\n cancelled = True\\n continue\\n # Convert the amount to an integer\\n value = self.Price(selection)\\n # Ensure the amount is within the range\\n if value > self.Price(self.cfg.ccard[\\\"max_amount\\\"]):\\n self.bot.send_message(self.chat.id,\\n self.loc.get(\\\"error_payment_amount_over_max\\\",\\n max_amount=self.Price(self.cfg.ccard[\\\"max_amount\\\"])))\\n continue\\n elif value < self.Price(self.cfg.ccard[\\\"min_amount\\\"]):\\n self.bot.send_message(self.chat.id,\\n self.loc.get(\\\"error_payment_amount_under_min\\\",\\n min_amount=self.Price(self.cfg.ccard[\\\"min_amount\\\"])))\\n continue\\n break\\n # If the user cancelled the action...\\n else:\\n # Exit the function\\n return\\n # Issue the payment invoice\\n self.__make_payment(amount=value)\",\n \"def bcs(self, arg):\\n\\n self.pc += arg if self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def adc_cal():\\n def r(x):\\n return (ord(x[0]) | ord(x[1]) << 8, ord(x[2]) | ord(x[3]) << 8)\\n return r\",\n \"def gate_lfcc(recurrent_net, sample_input):\\n length = sample_input.shape[0]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[i, :])\\n select = sigmoid(select)\\n score = sigmoid(score)\\n return np.sum(select * score) / np.sum(select)\",\n \"def control(operation, num_ctrl_qubits=1, label=None):\\n from math import pi\\n # pylint: disable=cyclic-import\\n import qiskit.circuit.controlledgate as controlledgate\\n from qiskit.circuit.quantumregister import QuantumRegister\\n from qiskit.circuit.quantumcircuit import QuantumCircuit\\n # pylint: disable=unused-import\\n import qiskit.extensions.standard.multi_control_rotation_gates\\n import qiskit.extensions.standard.multi_control_toffoli_gate\\n import qiskit.extensions.standard.multi_control_u1_gate\\n\\n q_control = QuantumRegister(num_ctrl_qubits, name='control')\\n q_target = QuantumRegister(operation.num_qubits, name='target')\\n q_ancillae = None # TODO: add\\n\\n qc = QuantumCircuit(q_control, q_target)\\n\\n if operation.name == 'x' or (\\n isinstance(operation, controlledgate.ControlledGate) and\\n operation.base_gate_name == 'x'):\\n qc.mct(q_control[:] + q_target[:-1],\\n q_target[-1],\\n None,\\n mode='noancilla')\\n elif operation.name == 'rx':\\n qc.mcrx(operation.definition[0][0].params[0], q_control, q_target[0],\\n use_basis_gates=True)\\n elif operation.name == 'ry':\\n qc.mcry(operation.definition[0][0].params[0], q_control, q_target[0],\\n q_ancillae, use_basis_gates=True)\\n elif operation.name == 'rz':\\n qc.mcrz(operation.definition[0][0].params[0], q_control, q_target[0],\\n use_basis_gates=True)\\n else:\\n bgate = _unroll_gate(operation, ['u1', 'u3', 'cx'])\\n # now we have a bunch of single qubit rotation gates and cx\\n for rule in bgate.definition:\\n if rule[0].name == 'u3':\\n theta, phi, lamb = rule[0].params\\n if phi == -pi/2 and lamb == pi/2:\\n qc.mcrx(theta, q_control, q_target[rule[1][0].index],\\n use_basis_gates=True)\\n elif phi == 0 and lamb == 0:\\n qc.mcry(theta, q_control, q_target[rule[1][0].index],\\n q_ancillae, mode='noancilla', use_basis_gates=True)\\n elif theta == 0 and phi == 0:\\n qc.mcrz(lamb, q_control, q_target[rule[1][0].index],\\n use_basis_gates=True)\\n else:\\n qc.mcrz(lamb, q_control, q_target[rule[1][0].index],\\n use_basis_gates=True)\\n qc.mcry(theta, q_control, q_target[rule[1][0].index],\\n q_ancillae, use_basis_gates=True)\\n qc.mcrz(phi, q_control, q_target[rule[1][0].index],\\n use_basis_gates=True)\\n elif rule[0].name == 'u1':\\n qc.mcu1(rule[0].params[0], q_control, q_target[rule[1][0].index])\\n elif rule[0].name == 'cx':\\n qc.mct(q_control[:] + [q_target[rule[1][0].index]],\\n q_target[rule[1][1].index],\\n None,\\n mode='noancilla')\\n else:\\n raise QiskitError('gate contains non-controllable intructions')\\n instr = qc.to_instruction()\\n if isinstance(operation, controlledgate.ControlledGate):\\n new_num_ctrl_qubits = num_ctrl_qubits + operation.num_ctrl_qubits\\n base_name = operation.base_gate_name\\n base_gate = operation.base_gate\\n base_gate_name = operation.base_gate_name\\n else:\\n new_num_ctrl_qubits = num_ctrl_qubits\\n base_name = operation.name\\n base_gate = operation.__class__\\n base_gate_name = operation.name\\n # In order to maintain some backward compatibility with gate names this\\n # uses a naming convention where if the number of controls is <=2 the gate\\n # is named like \\\"cc<base_gate_name>\\\", else it is named like\\n # \\\"c<num_ctrl_qubits><base_name>\\\".\\n if new_num_ctrl_qubits > 2:\\n ctrl_substr = 'c{0:d}'.format(new_num_ctrl_qubits)\\n else:\\n ctrl_substr = ('{0}' * new_num_ctrl_qubits).format('c')\\n new_name = '{0}{1}'.format(ctrl_substr, base_name)\\n cgate = controlledgate.ControlledGate(new_name,\\n instr.num_qubits,\\n operation.params,\\n label=label,\\n num_ctrl_qubits=new_num_ctrl_qubits,\\n definition=instr.definition)\\n cgate.base_gate = base_gate\\n cgate.base_gate_name = base_gate_name\\n return cgate\",\n \"def add_reactive(self, reactive):\\n\\t\\tself._reactives.append(reactive)\",\n \"def _control_predefined(operation, num_ctrl_qubits):\\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\\n if num_ctrl_qubits == 1:\\n import qiskit.extensions.standard.cx\\n cgate = qiskit.extensions.standard.cx.CnotGate()\\n else:\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n elif operation.name == 'y':\\n import qiskit.extensions.standard.cy\\n cgate = qiskit.extensions.standard.cy.CyGate()\\n elif operation.name == 'z':\\n import qiskit.extensions.standard.cz\\n cgate = qiskit.extensions.standard.cz.CzGate()\\n elif operation.name == 'h':\\n import qiskit.extensions.standard.ch\\n cgate = qiskit.extensions.standard.ch.CHGate()\\n elif operation.name in {'rx', 'ry', 'rz'}:\\n if operation.name == 'rx':\\n import qiskit.extensions.standard.crx\\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\\n elif operation.name == 'ry':\\n import qiskit.extensions.standard.cry\\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\\n else: # operation.name == 'rz'\\n import qiskit.extensions.standard.crz\\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\\n if num_ctrl_qubits == 1:\\n return cgate\\n else:\\n # only predefined for one control qubit\\n return cgate.control(num_ctrl_qubits - 1)\\n elif operation.name == 'swap':\\n import qiskit.extensions.standard.cswap\\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\\n elif operation.name == 'u1':\\n import qiskit.extensions.standard.cu1\\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\\n elif operation.name == 'u3':\\n import qiskit.extensions.standard.cu3\\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\\n elif operation.name == 'cx':\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n else:\\n raise QiskitError('No standard controlled gate for \\\"{}\\\"'.format(\\n operation.name))\\n return cgate\",\n \"def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def read_bits_c(self, ctrl_pin):\\n while True:\\n self.read_bits(ctrl_pin)\\n time.sleep(1)\",\n \"def enable_cl1_direct(self):\\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\\n self.write_versa5(0x18,0x20)\\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\\n self.write_versa5(0x13,0x03) ## Switch to clock\\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew\",\n \"def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\\n return self\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def _template_circuit(self, amp_param) -> QuantumCircuit:\\n circuit = QuantumCircuit(1)\\n circuit.x(0)\\n circuit.append(Gate(name=self.__rabi_gate_name__, num_qubits=1, params=[amp_param]), (0,))\\n circuit.measure_active()\\n\\n return circuit\",\n \"def ccx(self, q0, q1, q2, ctrl=None):\\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\\n return self\",\n \"def add_corridor_constraint(self,seg,r,weight=1.0):\\n\\n constraint_type = \\\"cylinder\\\"\\n params = dict()\\n params['x1'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg],\\n self.qr_polytraj.waypoints['y'][0,seg],\\n self.qr_polytraj.waypoints['z'][0,seg]])\\n params['x2'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg+1],\\n self.qr_polytraj.waypoints['y'][0,seg+1],\\n self.qr_polytraj.waypoints['z'][0,seg+1]])\\n params['der'] = 0\\n params['l'] = r # Give the same radius buffer on the end caps\\n params['r'] = r\\n params['weight'] = weight\\n params['keep_out'] = False\\n params['active_seg'] = seg\\n\\n\\n self.qr_polytraj.add_constraint(constraint_type,params,dynamic_weighting=False,sum_func=False)\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def add_rxn(self, reaction: db.Reaction):\\n # Add two rxn nodes\\n rxn_nodes = []\\n reaction_id = reaction.id().string()\\n\\n for i in range(0, 2):\\n # Add rxn node between lhs and rhs compound\\n rxn_node = ';'.join([reaction_id, str(i)])\\n rxn_node += ';'\\n self.graph.add_node(rxn_node, color='rxn_node')\\n rxn_nodes.append(rxn_node)\\n # Convert to strings\\n reactants = reaction.get_reactants(db.Side.BOTH)\\n reactant_types = reaction.get_reactant_types(db.Side.BOTH)\\n weights = self._get_weight(reaction)\\n # Add lhs aggregates and connect\\n for lhs_cmp, lhs_type in zip([i.string() for i in reactants[0]],\\n [i.name for i in reactant_types[0]]):\\n if lhs_cmp not in self.graph:\\n self.graph.add_node(lhs_cmp, type=lhs_type)\\n required_cmps_lhs = [s.string() for s in reactants[0]]\\n required_cmps_lhs.remove(lhs_cmp)\\n self.graph.add_edge(lhs_cmp, rxn_nodes[0], weight=weights[0], required_compounds=required_cmps_lhs,\\n required_compound_costs=None)\\n self.graph.add_edge(rxn_nodes[1], lhs_cmp, weight=0.0, required_compounds=None)\\n # Add rhs aggregates and connect\\n for rhs_cmp, rhs_type in zip([i.string() for i in reactants[1]],\\n [i.name for i in reactant_types[1]]):\\n if rhs_cmp not in self.graph:\\n self.graph.add_node(rhs_cmp, type=rhs_type)\\n required_cmps_rhs = [s.string() for s in reactants[1]]\\n required_cmps_rhs.remove(rhs_cmp)\\n self.graph.add_edge(rhs_cmp, rxn_nodes[1], weight=weights[1], required_compounds=required_cmps_rhs,\\n required_compound_costs=None)\\n self.graph.add_edge(rxn_nodes[0], rhs_cmp, weight=0.0, required_compounds=None)\\n\\n # # # Loop over reaction nodes to add required compounds info to downwards edges; might be unnecessary\\n node_index = 1\\n for node in rxn_nodes:\\n for key in self.graph[node].keys():\\n self.graph.edges[node, key]['required_compounds'] = \\\\\\n self.graph.edges[key, rxn_nodes[node_index]]['required_compounds']\\n node_index -= 1\",\n \"def __init__(self):\\n super().__init__(\\\"ccx\\\", 3, [])\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def rtl_state_and_more():\\n if not cso.enable:\\n state.next = states.idle\\n bcnt.next = 0\\n treg.next = 0\\n \\n itx.read.next = False\\n irx.write.next = False\\n\\n x_sck.next = False\\n x_ss.next = False\\n else:\\n if not cso.freeze:\\n # ~~~~ Idle state ~~~~\\n if state == states.idle:\\n bcnt.next = 7\\n treg.next = itx.read_data\\n x_sck.next = cso.clock_polarity\\n irx.write.next = False\\n \\n if not itx.empty and not irx.full:\\n itx.read.next = True\\n x_ss.next = False\\n if cso.clock_phase: # Clock in on second phase\\n state.next = states.wait_hclk\\n else: # Clock in on first phase\\n state.next = states.data_in\\n else:\\n itx.read.next = False\\n x_ss.next = True\\n\\n # ~~~~ Wait half clock period for cpha=1 ~~~~\\n elif state == states.wait_hclk:\\n itx.read.next = False\\n irx.write.next = False\\n if ena:\\n x_sck.next = not x_sck\\n state.next = states.data_in\\n\\n # ~~~~ Clock data in (and out) ~~~~\\n elif state == states.data_in:\\n itx.read.next = False\\n irx.write.next = False\\n if ena: # clk div\\n x_sck.next = not x_sck\\n rreg.next = concat(rreg[7:0], x_miso)\\n \\n if cso.clock_phase and bcnt == 0:\\n irx.write.next = True\\n if itx.empty or irx.full:\\n state.next = states.end\\n else:\\n state.next = states.data_change\\n else:\\n state.next = states.data_change\\n\\n # ~~~~ Get ready for next byte out/in ~~~~\\n elif state == states.data_change:\\n itx.read.next = False\\n irx.write.next = False\\n if ena:\\n x_sck.next = not x_sck\\n if bcnt == 0: \\n if not cso.clock_phase:\\n irx.write.next = True\\n \\n if itx.empty or irx.full:\\n state.next = states.end\\n else: # more data to transfer\\n bcnt.next = 7\\n state.next = states.data_in\\n itx.read.next = True\\n treg.next = itx.read_data\\n else:\\n treg.next = concat(treg[7:0], intbv(0)[1:])\\n bcnt.next = bcnt - 1 \\n state.next = states.data_in\\n\\n # ~~~~ End state ~~~~\\n elif state == states.end:\\n itx.read.next = False\\n irx.write.next = False\\n if ena: # Wait half clock cycle go idle\\n state.next = states.idle\\n\\n # Shouldn't happen, error in logic\\n else:\\n state.next = states.idle\\n assert False, \\\"SPI Invalid State\\\"\",\n \"def L3G_acquisition(add):\\n\\n # control register\\n CTRL_REG1 = 0x20\\n CTRL_REG4 = 0x23\\n LOW_ODR = 0x39\\n FIFO_CTRL = 0x2e\\n # output register\\n OUT_X_L = 0x28\\n OUT_X_H = 0x29\\n OUT_Y_L = 0x2a\\n OUT_Y_H = 0x2b\\n OUT_Z_L = 0x2c\\n OUT_Z_H = 0x2d\\n\\n # low odr mode, 50Hz, 2000 dps full scale\\n bus.write_byte_data(add, CTRL_REG1, 0b10001111)\\n bus.write_byte_data(add, CTRL_REG4, 0b00110000)\\n bus.write_byte_data(add, LOW_ODR, 0b00000001)\\n bus.write_byte_data(add, FIFO_CTRL, 0b01000000)\\n\\n # accelerator accumulate\\n while True:\\n uint16_gx = (bus.read_byte_data(add, OUT_X_H) << 8) + \\\\\\n bus.read_byte_data(add, OUT_X_L)\\n uint16_gy = (bus.read_byte_data(add, OUT_Y_H) << 8) + \\\\\\n bus.read_byte_data(add, OUT_Y_L)\\n uint16_gz = (bus.read_byte_data(add, OUT_Z_H) << 8) + \\\\\\n bus.read_byte_data(add, OUT_Z_L)\\n\\n gx = twos_comp(uint16_gx, 16)\\n gy = twos_comp(uint16_gy, 16)\\n gz = twos_comp(uint16_gz, 16)\\n\\n yield [gx, gy, gz]\",\n \"def convert_to_circuit(x):\\n y = np.arcsin(x)\\n z = np.arccos(x**2)\\n qubits = cirq.GridQubit.rect(5, 1)\\n circuit = cirq.Circuit()\\n for i in range(5):\\n circuit.append(cirq.ry(y).on(qubits[i]))\\n circuit.append(cirq.rz(z).on(qubits[i]))\\n return circuit\",\n \"def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def add_control(operation, num_ctrl_qubits, label):\\n if isinstance(operation, UnitaryGate):\\n # attempt decomposition\\n operation._define()\\n if _control_definition_known(operation, num_ctrl_qubits):\\n return _control_predefined(operation, num_ctrl_qubits)\\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def cs_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def csw(self, q0, q1, q2, ctrl=None):\\n self.cx(q2,q1,ctrl=ctrl).ccx(q0,q1,q2,ctrl=ctrl).cx(q2,q1,ctrl=ctrl)\\n return self\",\n \"def circuitSat(C):\",\n \"def test_coreg_shift(self):\\r\\n with gw.open(l8_224077_20200518_B2) as target, gw.open(\\r\\n l8_224077_20200518_B4\\r\\n ) as reference:\\r\\n with tempfile.TemporaryDirectory() as tmp:\\r\\n # Shift by 1 pixel in each direction\\r\\n target_shifted = shift(target, x=1, y=1)\\r\\n tmp_file = Path(tmp) / '_tmp_shift.tif'\\r\\n target_shifted.gw.save(tmp_file, overwrite=True)\\r\\n with gw.open(tmp_file) as target_shifted:\\r\\n # Co-register the shifted data\\r\\n shifted = gw.coregister(\\r\\n target=target_shifted,\\r\\n reference=reference,\\r\\n ws=(256, 256),\\r\\n r_b4match=1,\\r\\n s_b4match=1,\\r\\n max_shift=5,\\r\\n resamp_alg_deshift='nearest',\\r\\n resamp_alg_calc='cubic',\\r\\n out_gsd=[target_shifted.gw.celly, reference.gw.celly],\\r\\n q=True,\\r\\n nodata=(0, 0),\\r\\n CPUs=1,\\r\\n )\\r\\n self.assertFalse(\\r\\n np.allclose(\\r\\n target.values[:, :-1, :-1],\\r\\n target_shifted.values[:, :-1, :-1],\\r\\n )\\r\\n )\\r\\n # Check if the corrected data match the original (unshifted) target\\r\\n self.assertTrue(\\r\\n np.allclose(\\r\\n target.values[:, :-1, :-1],\\r\\n shifted.values[:, :-1, :-1],\\r\\n )\\r\\n )\",\n \"def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]\",\n \"def YY(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.YY, qubit_expr)\",\n \"def extend_circuit(self, circid=None, hops=None):\\r\\n if circid is None:\\r\\n circid = 0\\r\\n if hops is None:\\r\\n hops = \\\"\\\"\\r\\n plog(\\\"DEBUG\\\", \\\"Extending circuit\\\")\\r\\n lines = self.sendAndRecv(\\\"EXTENDCIRCUIT %d %s\\\\r\\\\n\\\"\\r\\n %(circid, \\\",\\\".join(hops)))\\r\\n tp,msg,_ = lines[0]\\r\\n m = re.match(r'EXTENDED (\\\\S*)', msg)\\r\\n if not m:\\r\\n raise ProtocolError(\\\"Bad extended line %r\\\",msg)\\r\\n plog(\\\"DEBUG\\\", \\\"Circuit extended\\\")\\r\\n return int(m.group(1))\",\n \"def update_control(self):\\n self._control_ctr += 0x01\",\n \"def get_crd_cc(self, axis, shaped=False):\\n return self._src_crds.get_cc(axis, shaped=shaped)\",\n \"def compile(self, seq, registers):\\n\\n # Check which modes are actually being used\\n used_modes = []\\n for operations in seq:\\n modes = [modes_label.ind for modes_label in operations.reg]\\n used_modes.append(modes)\\n\\n used_modes = list(set(item for sublist in used_modes for item in sublist))\\n\\n # dictionary mapping the used modes to consecutive non-negative integers\\n dict_indices = {used_modes[i]: i for i in range(len(used_modes))}\\n nmodes = len(used_modes)\\n\\n # We start with an identity then sequentially update with the gate transformations\\n T = np.identity(nmodes, dtype=np.complex128)\\n\\n # Now we will go through each operation in the sequence `seq` and apply it to T\\n for operations in seq:\\n name = operations.op.__class__.__name__\\n params = par_evaluate(operations.op.p)\\n modes = [modes_label.ind for modes_label in operations.reg]\\n if name == \\\"Rgate\\\":\\n G = np.exp(1j * params[0])\\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\\n elif name == \\\"LossChannel\\\":\\n G = np.sqrt(params[0])\\n T = _apply_one_mode_gate(G, T, dict_indices[modes[0]])\\n elif name == \\\"Interferometer\\\":\\n U = params[0]\\n if U.shape == (1, 1):\\n T = _apply_one_mode_gate(U[0, 0], T, dict_indices[modes[0]])\\n elif U.shape == (2, 2):\\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n else:\\n modes = [dict_indices[mode] for mode in modes]\\n U_expand = np.eye(nmodes, dtype=np.complex128)\\n U_expand[np.ix_(modes, modes)] = U\\n T = U_expand @ T\\n elif name == \\\"PassiveChannel\\\":\\n T0 = params[0]\\n if T0.shape == (1, 1):\\n T = _apply_one_mode_gate(T0[0, 0], T, dict_indices[modes[0]])\\n elif T0.shape == (2, 2):\\n T = _apply_two_mode_gate(T0, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n else:\\n modes = [dict_indices[mode] for mode in modes]\\n T0_expand = np.eye(nmodes, dtype=np.complex128)\\n T0_expand[np.ix_(modes, modes)] = T0\\n T = T0_expand @ T\\n elif name == \\\"BSgate\\\":\\n G = _beam_splitter_passive(params[0], params[1])\\n T = _apply_two_mode_gate(G, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n elif name == \\\"MZgate\\\":\\n v = np.exp(1j * params[0])\\n u = np.exp(1j * params[1])\\n U = 0.5 * np.array([[u * (v - 1), 1j * (1 + v)], [1j * u * (1 + v), 1 - v]])\\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n elif name == \\\"sMZgate\\\":\\n exp_sigma = np.exp(1j * (params[0] + params[1]) / 2)\\n delta = (params[0] - params[1]) / 2\\n U = exp_sigma * np.array(\\n [[np.sin(delta), np.cos(delta)], [np.cos(delta), -np.sin(delta)]]\\n )\\n T = _apply_two_mode_gate(U, T, dict_indices[modes[0]], dict_indices[modes[1]])\\n\\n ord_reg = [r for r in list(registers) if r.ind in used_modes]\\n ord_reg = sorted(list(ord_reg), key=lambda x: x.ind)\\n\\n return [Command(ops.PassiveChannel(T), ord_reg)]\",\n \"def _add_warp_ctc_loss(pred, seq_len, num_label, label):\\n label = mx.sym.Reshape(data=label, shape=(-1,))\\n label = mx.sym.Cast(data=label, dtype='int32')\\n return mx.sym.WarpCTC(data=pred, label=label, label_length=num_label, input_length=seq_len)\",\n \"def three_activation(self, output_reg):\\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\\n self._q_neuron.ccx(self.inputs[1], self.inputs[2], self._output[output_reg])\\n self._q_neuron.ccx(self.inputs[0], self.inputs[2], self._output[output_reg])\",\n \"def add_road(ccTremb):\\n pass\",\n \"def enable_cl2_copy_ad9866(self):\\n self.write_versa5(0x62,0x3b) ## Clock2 CMOS1 output, 3.3V\\n self.write_versa5(0x2c,0x01) ## Enable aux output on clock 1\\n self.write_versa5(0x31,0x0c) ## Use clock1 aux output as input for clock2\\n self.write_versa5(0x63,0x01) ## Enable clock2\",\n \"def _process_cnot(self, node):\\n id0 = self._process_bit_id(node.children[0])\\n id1 = self._process_bit_id(node.children[1])\\n if not(len(id0) == len(id1) or len(id0) == 1 or len(id1) == 1):\\n raise UnrollerError(\\\"internal error: qreg size mismatch\\\",\\n \\\"line=%s\\\" % node.line, \\\"file=%s\\\" % node.file)\\n maxidx = max([len(id0), len(id1)])\\n for idx in range(maxidx):\\n if len(id0) > 1 and len(id1) > 1:\\n self.backend.cx(id0[idx], id1[idx])\\n elif len(id0) > 1:\\n self.backend.cx(id0[idx], id1[0])\\n else:\\n self.backend.cx(id0[0], id1[idx])\",\n \"def cz(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CZ(), target=[control, target])\",\n \"def add_scan(self, newdat: base.MSGdata_Type) -> None:\\n add_lst = [cont for tag, cont in newdat if (tag == 'EP' or tag == 'BC') and cont[:4] == 'CHEM']\\n add_lst.sort()\\n if len(add_lst) > 0:\\n for cont in add_lst:\\n self._register_RFID_token(cont)\\n self.post_add_scan_CB()\",\n \"def addTrafficCross(self, byte):\\n self.byte_cross_group += byte\",\n \"def _gcl(x, r, D, Ia, Ct):\\n\\n Area = np.pi * D ** 2.0 / 4.0\\n m = 1.0 / (np.sqrt(1.0 - Ct))\\n k = np.sqrt((m + 1.0) / 2.0)\\n\\n a1 = 0.435449861 # empirically determined\\n a2 = 0.797853685\\n a3 = -0.124807893\\n a4 = 0.136821858\\n b1 = 15.6298\\n b2 = 1.0\\n R96 = a1 * (np.exp(a2 * Ct * Ct + a3 * Ct + a4)) * (b1 * Ia + b2) * D\\n\\n x0 = (9.6 * D) / ((2.0 * R96 / (k * D)) ** 3.0 - 1.0)\\n term1 = (k * D / 2.0) ** (5.0 / 2.0)\\n term2 = (105.0 / (2.0 * np.pi)) ** (-0.5)\\n term3 = (Ct * Area * x0) ** (-5.0 / 6.0)\\n c1 = term1 * term2 * term3\\n # c45=3*(c1) ** 2\\n\\n term10 = 0.1111 # * WindSpeed # U/9.0\\n term20 = (Ct * Area * (x + x0) ** (-2.0)) ** (1.0 / 3.0)\\n term310 = (r ** (3.0 / 2.0))\\n term320 = (3.0 * c1 * c1 * Ct * Area * (x + x0)) ** (-0.5)\\n term30 = term310 * term320\\n term40 = ((35.0 / (2.0 * np.pi)) ** (3.0 / 10.0)) * \\\\\\n (3.0 * c1 * c1) ** (-1.0 / 5.0)\\n DU1 = -term10 * term20 * (term30 - term40) ** 2.0\\n\\n DU = DU1 # + w2 * DU2\\n Rw = ((105 * c1 ** 2.0 / (2 * np.pi)) ** (1. / 5.)) * \\\\\\n (Ct * Area * (x + x0)) ** (1. / 3.)\\n return DU, Rw\",\n \"def continuous_adc(self):\\n try:\\n self._hydrabus.write(b\\\"\\\\x15\\\")\\n while 1:\\n v = self._hydrabus.read(2)\\n except KeyboardInterrupt:\\n self._hydrabus.write(b\\\"\\\\x00\\\")\\n self._hydrabus.reset()\\n return True\",\n \"def rx(self, q0, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=ROTATION_X, qid=[q0], phase=phase, ctrl=ctrl)\\n return self\",\n \"def _add_cmd(self, cmd):\\n if cmd.gate == Allocate:\\n self._active_qubits += 1\\n elif cmd.gate == Deallocate:\\n self._active_qubits -= 1\\n elif cmd.gate == Measure:\\n for qureg in cmd.qubits:\\n for qubit in qureg:\\n self.main_engine.set_measurement_result(qubit, 0)\\n elif self._is_rotation(cmd):\\n self._num_rotations += 1\\n self._rotations.append(self._decompose_rotation(cmd))\",\n \"def add_clr(self, kind, min_lr, max_lr, cycle_length):\\n if kind == 0:\\n self.callbacks.append(CyclicLR(base_lr=min_lr, max_lr=max_lr, step_size=cycle_length/2, mode='triangular2',\\n plot=True, save_plot_prefix=self.config.exp_name))\\n elif kind == 1:\\n self.callbacks.append(CyclicLR_1(min_lr=min_lr, max_lr=max_lr, cycle_length=cycle_length, plot=True,\\n save_plot_prefix=self.config.exp_name))\\n elif kind == 2:\\n self.callbacks.append(CyclicLR_2(min_lr=min_lr, max_lr=max_lr, cycle_length=cycle_length, plot=True,\\n save_plot_prefix=self.config.exp_name))\\n else:\\n raise ValueError('param `kind` not understood : {}'.format(kind))\\n print('Logging Info - Callback Added: CLR_{}...'.format(kind))\",\n \"def gate_operation(self, operation, qubit_expr, params=None):\\n operation = QuantumCircuit._parse_gate_operation(operation)\\n if params is not None:\\n operation = operation(**params) \\n qubit = self.qr.get(qubit_expr) \\n return operation(qubit)\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def getRxConvolved(self):\\n \\n return self.rx_convolved\",\n \"def add_readout(self, gate:Union[str, cirq.Gate]='XX',\\n readout_qubit:Optional['cirq.GridQubit']=None):\\n parsed_gate = QuantumCircuit._parse_gate_operation(gate)\\n readout_qubit = cirq.GridQubit(-1, -1) if readout_qubit is None else readout_qubit\\n for qubit in self.qubits:\\n final_gate = self.parameterise_gate(parsed_gate)\\n self.apply_gate_operation(final_gate, (readout_qubit, qubit))\\n if self.flatten_circuit:\\n self.flatten() \\n self._readout_qubit = readout_qubit\",\n \"def cvChin(ctrlName, r=1):\\r\\n # create a simple circle curve:\\r\\n curve = cmds.curve(n=ctrlName, d=3, p=[(0, 0.8*r, -0.5*r), (0, 0.9*r, -0.7*r), (0, 0, -0.5*r), (0, -0.8*r, -0.7*r), (0, -0.8*r, 1.4*r), (0, -0.3*r, 1.3*r), (0, 0, 1.2*r), (0, 0, 0), (0, 0.8*r, -0.3*r), (0, 0.8*r, -0.5*r)] )\\r\\n # rename curveShape:\\r\\n renameShape([curve])\\r\\n return curve\",\n \"def gate(self):\\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)\",\n \"def rx(self, rx):\\n\\n self.logger.debug(\\\"In 'rx' setter.\\\")\\n\\n self._rx = rx\",\n \"def add_connector(self):\\n \\n no = len(self.connectors)\\n state = {}\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % no\\n \\n if len(self.connectors)>0:\\n state = self.connectors[-1].get_state()\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % (no)\\n else:\\n if self.mount == self.MOUNT_THT:\\n state[\\\"p_shape\\\"] = Con.SHAPE_HOLE\\n elif self.mount == self.MOUNT_SMD:\\n state[\\\"p_shape\\\"] = Con.SHAPE_PAD\\n \\n c = Con(no)\\n c.set_state(state) \\n \\n self.sch_layers[\\\"pins\\\"].add(c.s_svg)\\n self.pcb_layers[\\\"copper1\\\"].add(c.p_svg)\\n self.connectors.append(c)\",\n \"def convert_C_instruction(self, instruction):\\n comp, dest, jump = self.parse(instruction)\\n\\n return f\\\"111{convert_comp(comp)}{convert_dest(dest)}\\\" \\\\\\n f\\\"{convert_jump(jump)}\\\"\",\n \"def plot_cnxs(self,x_shift,y_shift):\\n\\n if not self.cnxs: return # Bounce if option not selected\\n\\n self.node_cnx_crds[:,:2] += x_shift*self.pbc[0]\\n self.node_cnx_crds[:,2:] += y_shift*self.pbc[1]\\n for cnx_crd in self.node_cnx_crds:\\n self.ax.plot(cnx_crd[:2],cnx_crd[2:],c=self.lc,lw=self.lw)\\n self.node_cnx_crds[:,:2] -= x_shift*self.pbc[0]\\n self.node_cnx_crds[:,2:] -= y_shift*self.pbc[1]\",\n \"def __init__(self,\\n sub_gate: raw_types.Gate,\\n control_qubits: Sequence[Optional[raw_types.Qid]] = None,\\n num_controls: int = None) -> None:\\n if num_controls is None:\\n num_controls = 1 if control_qubits is None else len(control_qubits)\\n if control_qubits is None:\\n control_qubits = ()\\n if num_controls < len(control_qubits):\\n raise ValueError('More specified control qubits than num_controls')\\n\\n # Leave unspecified controls as Nones.\\n self.control_qubits = ((None,) * (num_controls - len(control_qubits)) +\\n tuple(control_qubits)) # type: ignore\\n\\n # Flatten nested ControlledGates.\\n if isinstance(sub_gate, ControlledGate):\\n self.sub_gate = sub_gate.sub_gate # type: ignore\\n self.control_qubits += sub_gate.control_qubits\\n else:\\n self.sub_gate = sub_gate\",\n \"def ch(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_H, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def _tk1_to_rotations(a: float, b: float, c: float) -> Circuit:\\n circ = Circuit(1)\\n circ.Rz(c, 0).Rx(b, 0).Rz(a, 0)\\n return circ\",\n \"def construct_qcbm(circuit, n_qubits, depth):\\n\\n for d in range(depth):\\n for i in range(n_qubits):\\n circuit.append_gate(Gate('X', target = i, angle = np.random.random()*np.pi*2))\\n circuit.append_gate(Gate('Z', target = i, angle = np.random.random()*np.pi*2))\\n if n_qubits != 1:\\n for i in range(n_qubits):\\n circuit.append_gate(Gate('CNOT', control = i, target = (i+1)%n_qubits))\\n return circuit\",\n \"def _compute_carry_and_output_fused(self, z, c_tm1):\\n z0, z1, z2, z3 = z\\n i = self.recurrent_activation(z0)\\n f = self.recurrent_activation(z1)\\n c = f * c_tm1 + i * self.activation(z2)\\n o = self.recurrent_activation(z3)\\n return c, o\",\n \"def cphaseshift10(control: QubitInput, target: QubitInput, angle: float) -> Instruction:\\n return Instruction(CPhaseShift10(angle), target=[control, target])\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6399722","0.6240949","0.58750856","0.5635678","0.5619368","0.534809","0.53249425","0.53150433","0.52717066","0.52563894","0.52543056","0.5253364","0.5244658","0.5180739","0.5163616","0.51406276","0.513891","0.50769234","0.50509804","0.5044092","0.50190896","0.50163305","0.5001805","0.50009304","0.4996484","0.49835938","0.49757254","0.4950203","0.49382794","0.4937984","0.49096358","0.49012566","0.48959398","0.48758256","0.48604652","0.48454267","0.48251027","0.4809628","0.48090166","0.4775293","0.47749522","0.4769314","0.47656205","0.47584057","0.47500074","0.47393495","0.47362813","0.47325787","0.47153658","0.47134143","0.4708978","0.47080833","0.47027883","0.46956405","0.46797416","0.46698654","0.4668147","0.4659187","0.46525377","0.46433672","0.46416706","0.4640586","0.46262994","0.4626139","0.4625639","0.46254984","0.46131408","0.46098936","0.45939928","0.45767784","0.4566363","0.45631325","0.45553356","0.4552015","0.45406038","0.453788","0.4525444","0.4525384","0.45230088","0.45183337","0.45092967","0.44985905","0.44923708","0.44898486","0.4482529","0.4482529","0.44811898","0.44711515","0.44647273","0.4464011","0.44544464","0.44484463","0.44472504","0.44389334","0.44253922","0.44223592","0.44079152","0.4405804","0.44028428","0.44014683"],"string":"[\n \"0.6399722\",\n \"0.6240949\",\n \"0.58750856\",\n \"0.5635678\",\n \"0.5619368\",\n \"0.534809\",\n \"0.53249425\",\n \"0.53150433\",\n \"0.52717066\",\n \"0.52563894\",\n \"0.52543056\",\n \"0.5253364\",\n \"0.5244658\",\n \"0.5180739\",\n \"0.5163616\",\n \"0.51406276\",\n \"0.513891\",\n \"0.50769234\",\n \"0.50509804\",\n \"0.5044092\",\n \"0.50190896\",\n \"0.50163305\",\n \"0.5001805\",\n \"0.50009304\",\n \"0.4996484\",\n \"0.49835938\",\n \"0.49757254\",\n \"0.4950203\",\n \"0.49382794\",\n \"0.4937984\",\n \"0.49096358\",\n \"0.49012566\",\n \"0.48959398\",\n \"0.48758256\",\n \"0.48604652\",\n \"0.48454267\",\n \"0.48251027\",\n \"0.4809628\",\n \"0.48090166\",\n \"0.4775293\",\n \"0.47749522\",\n \"0.4769314\",\n \"0.47656205\",\n \"0.47584057\",\n \"0.47500074\",\n \"0.47393495\",\n \"0.47362813\",\n \"0.47325787\",\n \"0.47153658\",\n \"0.47134143\",\n \"0.4708978\",\n \"0.47080833\",\n \"0.47027883\",\n \"0.46956405\",\n \"0.46797416\",\n \"0.46698654\",\n \"0.4668147\",\n \"0.4659187\",\n \"0.46525377\",\n \"0.46433672\",\n \"0.46416706\",\n \"0.4640586\",\n \"0.46262994\",\n \"0.4626139\",\n \"0.4625639\",\n \"0.46254984\",\n \"0.46131408\",\n \"0.46098936\",\n \"0.45939928\",\n \"0.45767784\",\n \"0.4566363\",\n \"0.45631325\",\n \"0.45553356\",\n \"0.4552015\",\n \"0.45406038\",\n \"0.453788\",\n \"0.4525444\",\n \"0.4525384\",\n \"0.45230088\",\n \"0.45183337\",\n \"0.45092967\",\n \"0.44985905\",\n \"0.44923708\",\n \"0.44898486\",\n \"0.4482529\",\n \"0.4482529\",\n \"0.44811898\",\n \"0.44711515\",\n \"0.44647273\",\n \"0.4464011\",\n \"0.44544464\",\n \"0.44484463\",\n \"0.44472504\",\n \"0.44389334\",\n \"0.44253922\",\n \"0.44223592\",\n \"0.44079152\",\n \"0.4405804\",\n \"0.44028428\",\n \"0.44014683\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.630366"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81754,"cells":{"query":{"kind":"string","value":"add CRY gate (controlled RY gate)."},"document":{"kind":"string","value":"def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def step1c(self):\n\t\tif (self.ends(\"y\") and self.vowelinstem()):\n\t\t\tself.b = self.b[:self.k] + 'i' + self.b[self.k+1:]","def addch(self, stdscr, y, x, text):\n stdscr.addch(y, x, text, curses.color_pair(self.i))","def _latex_(self):\n return \"\\\\Bold{C}\"","def cy(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CY(), target=[control, target])","def operator_c(buf, input_line, pos1, pos2, overwrite=False):\n operator_d(buf, input_line, pos1, pos2, overwrite)\n set_mode(\"INSERT\")","def add_tex_to_binning(self, binning_dict):\n if 'reco' in binning_dict['name']:\n sub_string = 'reco'\n elif 'true' in binning_dict['name']:\n sub_string = 'true'\n else:\n sub_string = None\n if 'energy' in binning_dict['name']:\n binning_dict['tex'] = r'$E_{%s}$'%sub_string\n elif 'coszen' in binning_dict['name']:\n binning_dict['tex'] = r'$\\cos\\theta_{Z,%s}$'%sub_string","def test_drawing_ascii():\r\n from pennylane import numpy as np\r\n\r\n x = np.array(0.1, requires_grad=True)\r\n y = np.array([0.2, 0.3], requires_grad=True)\r\n z = np.array(0.4, requires_grad=True)\r\n\r\n dev = qml.device(\"default.qubit\", wires=2)\r\n\r\n @qml.beta.qnode(dev, interface=\"autograd\")\r\n def circuit(p1, p2=y, **kwargs):\r\n qml.RX(p1, wires=0)\r\n qml.RY(p2[0] * p2[1], wires=1)\r\n qml.RX(kwargs[\"p3\"], wires=0)\r\n qml.CNOT(wires=[0, 1])\r\n return qml.expval(qml.PauliZ(0) @ qml.PauliX(1))\r\n\r\n result = qml.draw(circuit, charset=\"ascii\")(p1=x, p3=z)\r\n expected = \"\"\"\\\r\n 0: --RX(0.1)---RX(0.4)--+C--+| <Z @ X> \r\n 1: --RY(0.06)-----------+X--+| <Z @ X> \r\n\"\"\"\r\n\r\n assert result == expected","def add(text):\n orig = dispb[\"text\"]\n new = orig + text\n ops = [\"+\",\"-\",\"*\",\"/\"]\n # conditions\n # length 21\n if len(new) > 21:\n dispb[\"text\"] = orig\n return 0\n \n # one calc at a time\n if len(orig) > 0:\n if (orig[-1] in ops) & (text in ops):\n dispb[\"text\"] = orig\n return 0\n\n dispb[\"text\"] = new\n return 0","def cb_plus(event):\n delta_alpha = pm_rate\n # Increase Alpha \n sAlpha0.set_val( np.clip(sAlpha0.val + delta_alpha, alpha_min[0], alpha_max[0]) )\n sAlpha1.set_val( np.clip(sAlpha1.val + delta_alpha, alpha_min[1], alpha_max[1]) )\n sAlpha2.set_val( np.clip(sAlpha2.val + delta_alpha, alpha_min[2], alpha_max[2]) )\n print(\"+++\")","def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self","def operate_cipher(self):","def placeCrate (self, crates_char, row, column):","def secret_char(c):\n return \"\\\\raisebox{{0.07ex}}{{{}}}\".format(c)","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def draw_instruction():\r\n arcade.draw_text(\r\n \"This is a game of Santa, Reindeer, Snowman\", 0, 50, arcade.color.WHITE, 15\r\n )\r\n arcade.draw_text(\r\n \"Santa beats snowman, snowman beats reindeer, reindeer beats santa\",\r\n 0,\r\n 30,\r\n arcade.color.WHITE,\r\n 13,\r\n )\r\n arcade.draw_text(\r\n \"Press button 1 for santa, 2 for reindeer, and 3 for snowman\",\r\n 0,\r\n 10,\r\n arcade.color.WHITE,\r\n 15,\r\n )\r\n arcade.draw_text(\r\n \"User Choice\", WINDOW_WIDTH - 175, WINDOW_HEIGHT - 60, arcade.color.WHITE, 15\r\n )\r\n arcade.draw_text(\"CPU Choice\", 75, WINDOW_HEIGHT - 60, arcade.color.WHITE, 15)","def add_cogs(self):\n self.add_cog(Voice(self))","def risePen(gcode):\r\n gcode.append(\"M300 S46\")\r\n #gcode.append(\"G0 Z0.1000\")\r","def clowder_command(cmd):\n\n return colored(cmd, attrs=['bold'])","def cr(self):\n self._write('\\x0d')","def createBtnCmd(self, *args):\r\n self.cone = cmds.polyCone()\r\n cmds.setAttr('%s.rotateX' % self.cone[0], 90)","def make_control_character():\n # Add one character made up of one codepoint each from\n # (High Surrogates + High Private Use Surrogates) and Low Surrogates.\n # We expect each such pair to behave as a single high-codepoint\n # character.\n controls = ('0000', '001F')\n return [unicode_char(char)\n for char in range(int(controls[0], 16), int(controls[1], 16)+1)]","def charpoly_berk(self):\n return self.rep.charpoly()","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def morphstring_add(self, stringz):\n self.textEdit_morph.setTextColor(QColor(0, 0, 0, 255))\n stringz += f\" kernel: {self.spinBox.value()} shape: {self.comboBox.currentIndex()}\"\n self.textEdit_morph.append(stringz)","def _gyration(self, x, y, v, c):\n xy = self._mobius_add(x, y, c)\n yv = self._mobius_add(y, v, c)\n xyv = self._mobius_add(x, yv, c)\n return self._mobius_add(-xy, xyv, c)","def read_carry(self):\n return self.CARRY","def csi_to_conky(match: re.Match) -> str:\n # Convert the string of code;code;code to a list of ints\n try:\n codes= [0 if _=='' else int(_) for _ in match.group(1).split(';')]\n except IndexError: \n print('csi_to_conky called with no group match', file=sys.stderr)\n return match.group(0) # if no group has matched return the string as is\n except ValueError as err: # problem converting to int\n print(f'csi_to_conky: {err}', file=sys.stderr)\n return match.group(0)\n \n # Initialize the string to be returned\n result=''\n\n # consume the list one code at a time, first to last\n while len(codes)>0:\n code=codes.pop(0)\n if code==0: # Reset\n # Clear the string and init it with default color and font\n result = '${color}${font}'\n continue\n \n elif code==1: # Bold\n result += '${font DejaVu Sans Mono:style=bold}'\n continue\n \n elif code>29 and code<38: # Set foreground color (0 to 7)\n result += conky_set_fg(code -30)\n continue\n \n elif code==38: # Advanced ANSI\n try:\n type=codes.pop(0)\n if type==2: # ESC[38;2;R;G;Bm => TODO\n # for now just consume the next 3 values in the list\n del codes[0:3]\n continue\n elif type==5: # ESC[38;5;xxm \n result += eightbit_to_conky(codes.pop(0))\n continue\n else:\n raise ValueError(f'Improper value {type} after code 38')\n except (IndexError, ValueError) as err:\n print(f'csi_to_conky: {err} while parsing advanced ANSI sequence {code};{type}', file=sys.stderr)\n continue\n \n elif code==39: # default fg\n result +='${color}'\n continue\n \n else:\n print(f'code {code} not implemented', file=sys.stderr)\n continue \n\n return result","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def cesar(text, num, rshift):\n shift = num if rshift else -num\n codedtext = []\n for line in text:\n codedline = \"\"\n line = line.lower()\n for char in line:\n newchar = ord(char) + shift\n if newchar > 126:\n newchar = 32 + ord(char) - 127 + shift\n elif newchar < 32:\n newchar = 127 + ord(char) - 32 + shift\n codedline += chr(newchar)\n shift = -shift\n codedtext.append(codedline)\n return codedtext","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def show_c(text):\n complement = text.replace(\"_\", \" \")\n return 'C %s' % complement","def _parse_corot(self) -> Generator[None, str, None]:\n style = \"\"\n formatted_text = self._formatted_text\n\n while True:\n # NOTE: CSI is a special token within a stream of characters that\n # introduces an ANSI control sequence used to set the\n # style attributes of the following characters.\n csi = False\n\n c = yield\n\n # Everything between \\001 and \\002 should become a ZeroWidthEscape.\n if c == \"\\001\":\n escaped_text = \"\"\n while c != \"\\002\":\n c = yield\n if c == \"\\002\":\n formatted_text.append((\"[ZeroWidthEscape]\", escaped_text))\n c = yield\n break\n else:\n escaped_text += c\n\n # Check for CSI\n if c == \"\\x1b\":\n # Start of color escape sequence.\n square_bracket = yield\n if square_bracket == \"[\":\n csi = True\n else:\n continue\n elif c == \"\\x9b\":\n csi = True\n\n if csi:\n # Got a CSI sequence. Color codes are following.\n current = \"\"\n params = []\n\n while True:\n char = yield\n\n # Construct number\n if char.isdigit():\n current += char\n\n # Eval number\n else:\n # Limit and save number value\n params.append(min(int(current or 0), 9999))\n\n # Get delimiter token if present\n if char == \";\":\n current = \"\"\n\n # Check and evaluate color codes\n elif char == \"m\":\n # Set attributes and token.\n self._select_graphic_rendition(params)\n style = self._create_style_string()\n break\n\n # Check and evaluate cursor forward\n elif char == \"C\":\n for i in range(params[0]):\n # add <SPACE> using current style\n formatted_text.append((style, \" \"))\n break\n\n else:\n # Ignore unsupported sequence.\n break\n else:\n # Add current character.\n # NOTE: At this point, we could merge the current character\n # into the previous tuple if the style did not change,\n # however, it's not worth the effort given that it will\n # be \"Exploded\" once again when it's rendered to the\n # output.\n formatted_text.append((style, c))","def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self","def braan_s(self):\n self.handle_key('e')\n self.handle_key('y')\n \n # advance gram with hexed g\n self.handle_key('<heks>')\n self.handle_key('g')\n \n self.handle_key('n')\n self.handle_key('n')\n \n # advance wurd\n self.handle_key('<trgr>')\n \n self.handle_key('g')\n self.handle_key('u')\n self.handle_key('n')\n \n # advance gram with hexed g\n self.handle_key('<heks>')\n self.handle_key('g')\n\n self.handle_key('u')\n\n # advance line\n self.handle_key('<heks>')\n self.handle_key('<trgr>')\n \n self.handle_key('e')\n self.handle_key('e')\n self.handle_key('t')\n\n # advance wurd\n self.handle_key('<trgr>')\n\n self.handle_key('y')\n self.handle_key('o')\n self.handle_key('r')\n\n # advance wurd\n self.handle_key('<trgr>')\n \n self.handle_key('b')\n self.handle_key('r')\n self.handle_key('a')\n self.handle_key('a')\n self.handle_key('n')\n\n # advance gram with hexed g\n self.handle_key('<heks>')\n self.handle_key('g')\n\n self.handle_key('s')\n\n # advance line\n self.handle_key('<heks>')\n self.handle_key('<trgr>')\n\n self.handle_key('a')\n self.handle_key('n')\n self.handle_key('d')\n \n # advance line\n self.handle_key('<heks>')\n self.handle_key('<trgr>')\n\n self.handle_key('s')\n self.handle_key('t')\n self.handle_key('e')\n self.handle_key('e')\n self.handle_key('l')\n\n # advance wurd\n self.handle_key('<trgr>')\n\n self.handle_key('y')\n self.handle_key('o')\n self.handle_key('r')\n\n # advance wurd\n self.handle_key('<trgr>')\n \n self.handle_key('n')\n self.handle_key('a')\n self.handle_key('l')\n self.handle_key('e')\n self.handle_key('g')\n self.handle_key('g')\n\n # advance line\n self.handle_key('<heks>')\n self.handle_key('<trgr>')","def paintText(self, text):\n return '@paint '+text * 2","def key_cc(buf, input_line, cur, count):\n weechat.command(\"\", \"/input delete_line\")\n set_mode(\"INSERT\")","def lowerPen(gcode):\r\n gcode.append(\"M300 S43\")\r\n #gcode.append(\"G0 Z0\")\r","def asm(self, text):\n self.text.append(text)","def encrypt(inp):\n # prepare plaintext\n prefix = \"comment1=cooking%20MCs;userdata=\"\n suffix = \";comment2=%20like%20a%20pound%20of%20bacon\"\n pt = inp.replace(\";\", \"\").replace(\"=\", \"\") # remove invalid character\n pt = prefix + pt + suffix # add prefix and suffix\n pt_encoded = pt.encode(\"utf-8\")\n pt_padded = pkcs7.add(pt_encoded, aes.S_BLOCK)\n\n # encrypt\n ct = aes.cbc_encrypt(pt_padded, KEY, IV)\n\n return ct","def glycosylate(self):\n chid = self.chain.get()\n sequon = self.sequon.get()\n self.sequon_colors[sequon] = [.7, .1, 0]\n key = self.sequon.get()\n residue = self.myGlycosylator.get_residue(key)\n #Build new glycan\n if self.selected_glycan:\n self.myGlycosylator.connect_topology['SELECTED'] = self.selected_glycan[1]\n #build from current glycan\n if key in self.original_glycans:\n original_glycan = self.original_glycanMolecules[key].atom_group\n r,t = self.original_glycans[key]\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\n else:\n original_glycan = None\n connect_tree = None \n #Use current glycan\n else:\n original_glycan = self.original_glycanMolecules[key]\n r,t = self.original_glycans[key]\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\n self.myGlycosylator.connect_topology['SELECTED'] = self.myGlycosylator.build_connect_topology(original_glycan) \n original_glycan = original_glycan.atom_group\n \n segname = 'G'+key.split(',')[2]\n glycan,bonds = self.myGlycosylator.glycosylate('SELECTED', \n template_glycan_tree = connect_tree, \n template_glycan = original_glycan,\n link_residue=residue, link_patch = 'NGLB', chain = 'G', segname=segname)\n new_glycan = glc.Molecule(key)\n new_glycan.set_AtomGroup(glycan, bonds = bonds)\n self.myGlycosylator.assign_patches(new_glycan)\n self.linked_glycanMolecules[key] = new_glycan\n self.linked_glycans[key] = [new_glycan.rootRes, new_glycan.interresidue_connectivity]\n self.names.update(new_glycan.get_names())\n # Update glycoprotein and sequon panels\n self.draw_glycoprotein(chid)\n self.draw_glycan(sequon)","def add(self, y):\n return circuit.add(self, y)","def encrypt(text,key):\r\n aes = pyaes.AESModeOfOperationCTR(key)\r\n ciphertext = aes.encrypt(text)\r\n return ciphertext","def tx(self):\n cmd = Command()\n cmd.set_num(0x1C)\n cmd.set_subcmd_num(0x00)\n cmd.set_data([0x01])\n self.connection.send_cmd(cmd.render())","def encipher(self):\n ciphertext = \"\"\n for pt, key_char in zip(self.text, self.key):\n char_index = self.char_block.alphabet.index(pt)\n ciphertext += self.char_block.rows[key_char][char_index]\n print(ciphertext)","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def create_brake_command(apply_brake, pcm_override, pcm_cancel_cmd, chime, idx):\n pump_on = apply_brake > 0\n brakelights = apply_brake > 0\n brake_rq = apply_brake > 0\n\n pcm_fault_cmd = False\n amount = struct.pack(\"!H\", (apply_brake << 6) + pump_on)\n msg = amount + struct.pack(\"BBB\", (pcm_override << 4) |\n (pcm_fault_cmd << 2) |\n (pcm_cancel_cmd << 1) | brake_rq, 0x80,\n brakelights << 7) + chr(chime) + \"\\x00\"\n return make_can_msg(0x1fa, msg, idx, 0)","def encode(self, text):\n if self.verbatim:\n return text\n # compile the regexps once. do it here so one can see them.\n #\n # first the braces.\n if not self.__dict__.has_key('encode_re_braces'):\n self.encode_re_braces = re.compile(r'([{}])')\n text = self.encode_re_braces.sub(r'{\\\\\\1}',text)\n if not self.__dict__.has_key('encode_re_bslash'):\n # find backslash: except in the form '{\\{}' or '{\\}}'.\n self.encode_re_bslash = re.compile(r'(?<!{)(\\\\)(?![{}]})')\n # then the backslash: except in the form from line above:\n # either '{\\{}' or '{\\}}'.\n text = self.encode_re_bslash.sub(r'{\\\\textbackslash}', text)\n\n # then dollar\n text = text.replace(\"$\", '{\\\\$}')\n if not ( self.literal_block or self.literal or self.mathmode ):\n # the vertical bar: in mathmode |,\\vert or \\mid\n # in textmode \\textbar\n text = text.replace(\"|\", '{\\\\textbar}')\n text = text.replace(\"<\", '{\\\\textless}')\n text = text.replace(\">\", '{\\\\textgreater}')\n # then\n text = text.replace(\"&\", '{\\\\&}')\n # the ^:\n # * verb|^| does not work in mbox.\n # * mathmode has wedge. hat{~} would also work.\n # text = text.replace(\"^\", '{\\\\ensuremath{^\\\\wedge}}')\n text = text.replace(\"^\", '{\\\\textasciicircum}')\n text = text.replace(\"%\", '{\\\\%}')\n text = text.replace(\"#\", '{\\\\#}')\n text = text.replace(\"~\", '{\\\\textasciitilde}')\n # Separate compound characters, e.g. \"--\" to \"-{}-\". (The\n # actual separation is done later; see below.)\n separate_chars = '-'\n if self.literal_block or self.literal:\n # In monospace-font, we also separate \",,\", \"``\" and \"''\"\n # and some other characters which can't occur in\n # non-literal text.\n separate_chars += ',`\\'\"<>'\n # pdflatex does not produce doublequotes for ngerman.\n text = self.babel.double_quotes_in_tt(text)\n if self.font_encoding == 'OT1':\n # We're using OT1 font-encoding and have to replace\n # underscore by underlined blank, because this has\n # correct width.\n text = text.replace('_', '{\\\\underline{ }}')\n # And the tt-backslash doesn't work in OT1, so we use\n # a mirrored slash.\n text = text.replace('\\\\textbackslash', '\\\\reflectbox{/}')\n else:\n text = text.replace('_', '{\\\\_}')\n else:\n text = self.babel.quote_quotes(text)\n text = text.replace(\"_\", '{\\\\_}')\n for char in separate_chars * 2:\n # Do it twice (\"* 2\") becaues otherwise we would replace\n # \"---\" by \"-{}--\".\n text = text.replace(char + char, char + '{}' + char)\n if self.insert_newline or self.literal_block:\n # Insert a blank before the newline, to avoid\n # ! LaTeX Error: There's no line here to end.\n text = text.replace(\"\\n\", '~\\\\\\\\\\n')\n elif self.mbox_newline:\n if self.literal_block:\n closings = \"}\" * len(self.literal_block_stack)\n openings = \"\".join(self.literal_block_stack)\n else:\n closings = \"\"\n openings = \"\"\n text = text.replace(\"\\n\", \"%s}\\\\\\\\\\n\\\\mbox{%s\" % (closings,openings))\n # lines starting with \"[\" give errors.\n text = text.replace('[', '{[}')\n if self.insert_none_breaking_blanks:\n text = text.replace(' ', '~')\n if self.latex_encoding != 'utf8':\n text = self.unicode_to_latex(text)\n return text","def escape_control_characters(text: str, keep_spacing=True) -> str:\n if not isinstance(text, str):\n raise ValueError(\"text type must be unicode but is {}\".format(type(text).__name__))\n\n trans = _control_char_trans_newline if keep_spacing else _control_char_trans\n return text.translate(trans)","def arthur(self):\n\t\tthismsg = \"\\r\\n\"+self.ESC+\"34m\"+self.A220+self.ESC+\"1;44m\"+self.A176+self.ESC+\"0;34m\"+self.A220+self.A223+self.A176+self.ESC+\"C\"+self.A178+self.A176+self.A254+self.ESC+\"2C\"+self.A220+self.A254+self.ESC+\"6C\"+self.A220+self.A178+self.ESC+\"C\"+self.A220+self.A178+self.ESC+\"C\"+self.ESC+\"1;44m\"+self.A177+self.ESC+\"40m\"+self.A223+self.ESC+\"0;34m\"+self.A223+self.ESC+\"1m\"+self.A223+self.A223+self.ESC+\"0;34m\"+self.A223+self.ESC+\"1m\"+self.A223+self.ESC+\"0;34m\"+self.A223+self.A223+self.A223+self.A223+self.ESC+\"1m\"+self.A223+self.ESC+\"0;34m\"+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.ESC+\"C\"+self.A223+\"\\r\\n\"\n\t\tthismsg += self.ESC+\"C\"+self.A223+self.ESC+\"2C\"+self.A176+self.A223+self.A223+self.ESC+\"1;37m\"+self.A220+self.A220+self.A220+self.A220+self.ESC+\"0m\"+self.A220+self.ESC+\"1m\"+self.A223+self.A223+self.ESC+\"0m\"+self.A223+self.ESC+\"1m\"+self.A223+self.A223+self.ESC+\"0m\"+self.A223+self.ESC+\"1m\"+self.A223+self.A220+self.ESC+\"0m\"+self.A220+self.A220+self.A220+self.A220+self.ESC+\"C\"+self.ESC+\"34m\"+self.A223+self.ESC+\"3C\"+self.ESC+\"1;37mSaga\"+self.ESC+\"Cof\"+self.ESC+\"Cthe\"+self.ESC+\"CRed\"+self.ESC+\"CDragon\"+self.ESC+\"C-\"+self.ESC+\"C\"+self.ESC+\"34mKing\"+self.ESC+\"CArthurs\"+self.ESC+\"CWeapons \"+self.ESC+\"C\"+self.ESC+\"0;34m\"+self.A219+\"\\r\\n\"\n\t\tthismsg += self.A223+self.ESC+\"1;37m\"+self.A220+self.A223+self.A223+self.A223+self.A223+self.A223+self.ESC+\"C\"+self.ESC+\"0m\"+self.A220+self.A220+self.A220+self.A220+self.A220+self.A219+self.A219+self.A219+self.ESC+\"30;47m\"+self.A223+self.ESC+\"37;40m\"+self.A219+self.A220+self.A220+self.A220+self.A220+self.A220+self.ESC+\"C\"+self.A223+self.ESC+\"1;30m\"+self.A223+self.ESC+\"0m\"+self.A223+self.ESC+\"1;30m\"+self.A223+self.A223+self.A220+self.ESC+\"4C\"+self.ESC+\"0;34m\"+self.A220+self.A220+self.A220+self.A220+self.ESC+\"C\"+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.ESC+\"C\"+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A178+self.A220+self.A220+self.A220+self.A220+self.ESC+\"C\"+self.A220+self.A220+\"\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"1m\"+self.A219+self.ESC+\"C\"+self.A220+self.ESC+\"47m\"+self.A219+self.A219+self.A223+self.A178+self.A177+self.A176+self.ESC+\"0m\"+self.A219+self.A223+self.ESC+\"1m\"+self.A220+self.ESC+\"0m\"+self.A223+self.A219+self.A219+self.ESC+\"30;47m\"+self.A223+self.A176+self.ESC+\"37;40m\"+self.A219+self.A219+self.A223+self.A220+self.A223+self.A219+self.A219+self.A219+self.A219+self.A219+self.A219+self.A220+self.ESC+\"C\"+self.ESC+\"1;30;47m\"+self.A178+self.ESC+\"C\"+self.ESC+\"0;34m\"+self.A176+self.ESC+\"3C\"+self.A178+self.ESC+\"20C\"+self.A223+self.ESC+\"17C\"+self.ESC+\"1m\"+self.A220+self.A220+self.A220+self.A220+\"\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"0m \"+self.ESC+\"1m\"+self.A219+self.ESC+\"C\"+self.ESC+\"47m\"+self.A219+self.A219+self.A178+self.ESC+\"0m\"+self.A219+self.ESC+\"30;47m\"+self.A176+self.ESC+\"37;40m\"+self.A219+self.A219+self.A219+self.ESC+\"C\"+self.ESC+\"1m\"+self.A219+self.ESC+\"47m\"+self.A178+self.ESC+\"40m\"+self.A220+self.ESC+\"0m\"+self.A223+self.A219+self.A219+self.A223+self.A220+self.ESC+\"1;47m\"+self.A176+self.ESC+\"0m\"+self.A219+self.ESC+\"C\"+self.A219+self.A219+self.ESC+\"1;47m\"+self.A176+self.A176+self.A176+self.A176+self.ESC+\"30m\"+self.A176+self.ESC+\"C\"+self.ESC+\"40m\"+self.A219+self.ESC+\"3C\"+self.ESC+\"0;34mYou\"+self.ESC+\"Cwalk\"+self.ESC+\"Cinto\"+self.ESC+\"Cthe\"+self.ESC+\"Cwell\"+self.ESC+\"Cknown\"+self.ESC+\"Cweapons\"+self.ESC+\"6C\"+self.ESC+\"1m\"+self.A219+self.ESC+\"44m\"+self.A178+self.ESC+\"0;34m\"+self.A219+\"\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"1m\"+self.A219+self.ESC+\"C\"+self.ESC+\"47m\"+self.A178+self.A178+self.A178+\" \"+self.ESC+\"0;30;47m\"+self.A223+self.A177+self.ESC+\"37;40m\"+self.A219+self.A219+self.A219+self.ESC+\"C\"+self.ESC+\"1m\"+self.A219+self.ESC+\"C\"+self.ESC+\"47m\"+self.A178+self.ESC+\"40m\"+self.A220+self.ESC+\"C\"+self.ESC+\"47m\"+self.A177+self.A176+\" \"+self.ESC+\"C\"+self.ESC+\"0m\"+self.A219+self.ESC+\"1;47m\"+self.A176+self.A176+self.A177+self.A177+self.A177+self.A176+self.ESC+\"30m\"+self.A176+self.ESC+\"C\"+self.ESC+\"40m\"+self.A219+self.ESC+\"3C\"+self.ESC+\"0;34mshop,\"+self.ESC+\"Cyou\"+self.ESC+\"Cpause\"+self.ESC+\"Cto\"+self.ESC+\"Clook\"+self.ESC+\"Caround\"+self.ESC+\"Cat\"+self.ESC+\"Call\"+self.ESC+\"Cof\"+self.ESC+\"2C\"+self.A222+self.ESC+\"1;44m\"+self.A177+self.ESC+\"0;34m\"+self.A219+\"\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"1m\"+self.A219+self.ESC+\"C\"+self.A223+self.ESC+\"47m\"+self.A178+self.A177+self.ESC+\"0m\"+self.A219+self.A219+self.A219+self.A219+self.A219+self.A219+self.A219+self.ESC+\"C\"+self.ESC+\"1m\"+self.A219+self.ESC+\"C\"+self.ESC+\"47m\"+self.A178+self.A177+self.ESC+\"0m\"+self.A220+self.A223+self.A220+self.ESC+\"1;47m\"+self.A176+self.A176+self.A177+self.A177+self.A176+self.A176+self.A176+self.ESC+\"30m\"+self.A176+self.ESC+\"0m\"+self.A223+self.ESC+\"C\"+self.ESC+\"1;30m\"+self.A219+self.ESC+\"3C\"+self.ESC+\"0;34mthe\"+self.ESC+\"Cmany\"+self.ESC+\"Cimplements\"+self.ESC+\"Cof\"+self.ESC+\"Cdestruction.\"+self.ESC+\"2CA\"+self.ESC+\"37m \"+self.ESC+\"4C\"+self.ESC+\"1;34;44m\"+self.A176+self.ESC+\"0;34m\"+self.A219+\"\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"C \"+self.ESC+\"1m\"+self.A219+self.ESC+\"C\"+self.ESC+\"47m\"+self.A177+self.A176+self.ESC+\"0m\"+self.A219+self.A219+self.A219+self.A219+self.A219+self.A219+self.A223+self.ESC+\"1m\"+self.A220+self.ESC+\"C\"+self.ESC+\"47m\"+self.A178+self.ESC+\"40m\"+self.A220+self.A223+self.ESC+\"47m\"+self.A177+self.A176+self.ESC+\"0m\"+self.A220+self.A223+self.ESC+\"1;47m\"+self.A177+self.A176+self.A176+self.ESC+\"0m\"+self.A219+self.ESC+\"30;47m\"+self.A220+self.A176+self.ESC+\"1m\"+self.A177+self.ESC+\"C\"+self.ESC+\"40m\"+self.A178+self.ESC+\"4C\"+self.ESC+\"0;34mfat\"+self.ESC+\"Cman\"+self.ESC+\"Cwoddles\"+self.ESC+\"Cinto\"+self.ESC+\"Cthe\"+self.ESC+\"Croom,\"+self.ESC+\"Cand\"+self.ESC+\"2C \"+self.ESC+\"37m \"+self.ESC+\"2C\"+self.ESC+\"1;34;44m\"+self.A176+self.ESC+\"0;30;44m\"+self.A176+self.ESC+\"40m\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"C \"+self.ESC+\"1m\"+self.A219+self.ESC+\"C\"+self.ESC+\"47m\"+self.A176+\" \"+self.ESC+\"0m\"+self.A219+self.A219+self.A223+self.ESC+\"33m\"+self.A220+self.ESC+\"37m\"+self.A223+self.ESC+\"1m\"+self.A220+self.ESC+\"47m\"+self.A178+self.A178+self.A177+self.ESC+\"0m\"+self.A220+self.ESC+\"1m\"+self.A223+self.ESC+\"47m\"+self.A177+self.A176+self.ESC+\"0;30;47m\"+self.A176+self.A223+self.ESC+\"1m\"+self.A176+self.ESC+\"0m\"+self.A220+self.A223+self.ESC+\"33m\"+self.A220+self.ESC+\"37m\"+self.A223+self.A219+self.A219+self.ESC+\"1;30;47m\"+self.A178+self.ESC+\"C\"+self.ESC+\"40m\"+self.A178+self.ESC+\"4C\"+self.ESC+\"0;34masks\"+self.ESC+\"C\\\"\"+self.ESC+\"1mWadaya\"+self.ESC+\"Cwant\"+self.ESC+\"Ckid?\"+self.ESC+\"0;34m\\\"\"+self.ESC+\"17C\"+self.ESC+\"37m \"+self.ESC+\"2C\"+self.ESC+\"1;34;44m\"+self.A176+self.ESC+\"0;30;44m\"+self.A176+self.ESC+\"40m\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"C \"+self.ESC+\"1m\"+self.A219+self.ESC+\"C\"+self.ESC+\"47m\"+self.A176+self.ESC+\"0m\"+self.A219+self.ESC+\"30;47m\"+self.A254+self.A176+self.ESC+\"37;40m\"+self.A223+self.ESC+\"1;33m\"+self.A220+self.ESC+\"43m\"+self.A177+self.ESC+\"0;33m\"+self.A220+self.ESC+\"1;37m\"+self.A223+self.ESC+\"47m\"+self.A177+self.A176+self.ESC+\"0m\"+self.A223+self.A220+self.A220+self.A223+self.A223+self.ESC+\"1;47m \"+self.ESC+\"0m\"+self.A223+self.ESC+\"33m\"+self.A220+self.ESC+\"1;43m\"+self.A177+self.ESC+\"C\"+self.ESC+\"0m\"+self.A219+self.A219+self.ESC+\"1;30m\"+self.A219+self.A223+self.ESC+\"C\"+self.A178+self.ESC+\"47C\"+self.ESC+\"0;34m\"+self.A219+self.ESC+\"30;44m\"+self.A177+self.ESC+\"40m\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"34m\"+self.A176+self.ESC+\"C \"+self.ESC+\"1;37;47m\"+self.A178+self.ESC+\"C\"+self.A176+self.ESC+\"0m\"+self.A223+self.ESC+\"1;33m\"+self.A220+self.ESC+\"43m\"+self.A178+self.ESC+\"40m\"+self.A223+self.ESC+\"C\"+self.ESC+\"43m\"+self.A176+self.ESC+\"0;33m\"+self.A223+self.A220+self.ESC+\"C\"+self.ESC+\"1;37;47m\"+self.A177+self.A177+self.A176+self.ESC+\"0m\"+self.A219+self.A223+self.ESC+\"1;33m\"+self.A220+self.ESC+\"43m\"+self.A178+self.ESC+\"C\"+self.ESC+\"0;33m\"+self.A223+self.ESC+\"1;43m\"+self.A176+self.ESC+\"0;33m\"+self.A220+self.ESC+\"37m\"+self.A223+self.ESC+\"1;30m\"+self.A219+self.ESC+\"C\"+self.A178+self.ESC+\"6C\"+self.ESC+\"0;34m[\"+self.ESC+\"1mB\"+self.ESC+\"0;34m]\"+self.ESC+\"1muy\"+self.ESC+\"CWeapon\"+self.ESC+\"30C\"+self.ESC+\"0;34m\"+self.A219+self.ESC+\"30;44m\"+self.A177+self.ESC+\"40m\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"34m\"+self.A178+self.ESC+\"C \"+self.ESC+\"1;37;47m\"+self.A177+self.ESC+\"2C\"+self.ESC+\"40m\"+self.A223+self.ESC+\"33m\"+self.A219+self.A220+self.ESC+\"0;33m\"+self.A178+self.A223+self.ESC+\"37m\"+self.A220+self.A219+self.A220+self.ESC+\"1;47m\"+self.A177+self.A176+self.A176+self.ESC+\"0m\"+self.A219+self.A220+self.ESC+\"1m\"+self.A223+self.ESC+\"0m\"+self.A220+self.A220+self.ESC+\"1;33m\"+self.A223+self.A220+self.A220+self.ESC+\"43m\"+self.A177+self.ESC+\"0;33m\"+self.A223+self.ESC+\"2C\"+self.ESC+\"1;30m\"+self.A219+self.ESC+\"6C\"+self.ESC+\"0;34m[\"+self.ESC+\"1mS\"+self.ESC+\"0;34m]\"+self.ESC+\"1mell\"+self.ESC+\"CWeapon\"+self.ESC+\"29C\"+self.ESC+\"0;34m\"+self.A219+self.ESC+\"30;44m\"+self.A177+self.ESC+\"40m\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"34m\"+self.A176+self.A176+self.ESC+\"C \"+self.ESC+\"1;37;47m\"+self.A176+self.ESC+\"C\"+self.ESC+\"0m\"+self.A223+self.A220+self.A220+self.A220+self.A219+self.ESC+\"1;47m\"+self.A176+self.A176+self.A176+self.A176+self.ESC+\"0;30;47m\"+self.A176+self.ESC+\"37;40m\"+self.A219+self.A219+self.A219+self.A219+self.ESC+\"1;30;47m\"+self.A176+self.ESC+\"0m\"+self.A219+self.A219+self.A220+self.A220+self.ESC+\"1;30m\"+self.A220+self.A223+self.ESC+\"C\"+self.A219+self.ESC+\"7C\"+self.ESC+\"0;34m[\"+self.ESC+\"1mY\"+self.ESC+\"0;34m]\"+self.ESC+\"1mour\"+self.ESC+\"CStats\"+self.ESC+\"30C\"+self.ESC+\"0;34m\"+self.A219+self.ESC+\"30;44m\"+self.A178+self.ESC+\"40m\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"C\"+self.ESC+\"34m\"+self.A176+self.ESC+\"C \"+self.ESC+\"37m\"+self.A223+self.A220+self.ESC+\"C\"+self.A223+self.A223+self.A219+self.A219+self.A219+self.A219+self.A219+self.ESC+\"30;47m\"+self.A220+self.A177+self.ESC+\"37;40m\"+self.A219+self.A219+self.A219+self.ESC+\"1;30;47m\"+self.A220+self.A220+self.A178+self.ESC+\"40m\"+self.A223+self.A223+self.ESC+\"C\"+self.A220+self.A223+self.ESC+\"0;34m\"+self.A176+self.ESC+\"7C[\"+self.ESC+\"1mR\"+self.ESC+\"0;34m]\"+self.ESC+\"1meturn\"+self.ESC+\"Cto\"+self.ESC+\"CTown\"+self.ESC+\"25C\"+self.ESC+\"0;34m\"+self.A222+self.ESC+\"1;44m\"+self.A177+self.ESC+\"0;30;44m\"+self.A178+self.ESC+\"40m\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"34m\"+self.A220+self.ESC+\"1;44m\"+self.A176+self.ESC+\"0;34m\"+self.A220+self.ESC+\"C\"+self.A178+self.A220+self.ESC+\"37m\"+self.A223+self.A223+self.A220+self.A220+self.ESC+\"C\"+self.A223+self.A223+self.A223+self.ESC+\"1;30;47m\"+self.A176+self.A177+self.A219+self.ESC+\"40m\"+self.A223+self.A223+self.A223+self.ESC+\"C\"+self.A220+self.A220+self.A223+self.A223+self.ESC+\"C\"+self.ESC+\"0;34m\"+self.A220+self.A219+self.A176+self.ESC+\"47C\"+self.A219+self.ESC+\"1;44m\"+self.A176+self.ESC+\"0;30;44m\"+self.A178+self.ESC+\"40m\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"C\"+self.ESC+\"34m\"+self.A223+self.ESC+\"C\"+self.A220+self.A254+self.A178+self.A219+self.A219+self.A220+self.A220+self.ESC+\"37m\"+self.A223+self.A223+self.A223+self.A220+self.ESC+\"C\"+self.ESC+\"1;30m\"+self.A223+self.ESC+\"C\"+self.A220+self.A223+self.A223+self.A223+self.ESC+\"C\"+self.ESC+\"0;34m\"+self.A176+self.A176+self.A223+self.A178+self.A178+self.A176+self.ESC+\"2C\"+self.ESC+\"1;44m\"+self.A176+self.ESC+\"0;34m\"+self.A223+self.A223+self.A223+self.A178+self.A223+self.A223+self.ESC+\"C\"+self.A223+self.A178+self.A223+self.ESC+\"C\"+self.A223+self.A223+self.ESC+\"C\"+self.A223+self.A176+self.ESC+\"C\"+self.A223+self.ESC+\"C\"+self.A223+self.A223+self.ESC+\"C\"+self.A223+self.A223+self.ESC+\"30;44m\"+self.A177+self.ESC+\"19C\"+self.ESC+\"34;40m\"+self.A223+self.A223+self.A223+self.A223+\"\\r\\n\"\n\t\tthismsg += self.ESC+\"A\"+self.ESC+\"79C\"+self.ESC+\"37m \"+self.ESC+\"34m\"+self.A177+self.A178+self.A219+self.A220+self.ESC+\"C\"+self.A176+self.A223+self.A178+self.A178+self.A178+self.A178+self.A223+self.A176+self.ESC+\"C\"+self.ESC+\"37m\"+self.A223+self.ESC+\"1;30m\"+self.A220+self.A223+self.ESC+\"C\"+self.ESC+\"0;34m\"+self.A223+self.A178+self.A176+self.ESC+\"4C\"+self.A176+self.ESC+\"C\"+self.A220+self.A219+self.ESC+\"30;44m\"+self.A176+\" \"+self.ESC+\"34;40m\"+self.A254+self.ESC+\"37m \"+self.ESC+\"34m\"+self.A220+self.ESC+\"30;44m\"+self.A176+self.A178+self.ESC+\"34;40m\"+self.A219+self.A219+self.A219+self.ESC+\"30;44m\"+self.A176+self.ESC+\"34;40m\"+self.A219+self.A220+self.A219+self.A219+self.A219+self.A219+self.A219+self.A222+self.A219+self.A219+\"\\r\\n\"\n\t\treturn thismsg","def getGraphicsControlExt(duration=0.1):\n bb = '\\x21\\xF9\\x04'\n bb += '\\x08' # no transparancy\n bb += intToBin( int(duration*100) ) # in 100th of seconds\n bb += '\\x00' # no transparant color\n bb += '\\x00' # end\n return bb","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def addch(self, posy, posx, character, color_pair):\r\n if posy < 0 or posy > self.height - 1:\r\n return\r\n if posx < 0 or posx > self.width - 1:\r\n return\r\n if posx == self.width - 1 and posy == self.height - 1:\r\n return\r\n self.win.addch(posy, posx, character, color_pair)","def add_command(self):\n self.write(\"@SP\\nAM=M-1\\nD=M\\nA=A-1\\nM=M+D\\n\")","def draw(self, data):\n data = data.translate(\n self.g1_charset if self.charset else self.g0_charset)\n\n for char in data:\n char_width = wcwidth(char)\n if (self.cursor.x == self.columns and char_width >= 1) \\\n or (self.cursor.x == self.columns - 1 and char_width >= 2):\n if mo.DECAWM in self.mode:\n last = self.buffer[self.cursor.y][self.columns - 1]\n self.buffer[self.cursor.y][self.columns - 1] = \\\n last._replace(linefeed=True)\n self.dirty.add(self.cursor.y)\n self.carriage_return()\n self.linefeed()\n elif char_width > 0:\n self.cursor.x -= char_width\n\n if mo.IRM in self.mode and char_width > 0:\n self.insert_characters(char_width)\n\n line = self.buffer[self.cursor.y]\n if char_width == 1:\n if is_windows and self.cursor.x == self.columns - 1:\n # always put a linefeed marker when cursor is at the last column\n line[self.cursor.x] = self.cursor.attrs._replace(data=char, linefeed=True)\n else:\n line[self.cursor.x] = self.cursor.attrs._replace(data=char)\n\n elif char_width == 2:\n line[self.cursor.x] = self.cursor.attrs._replace(data=char)\n if is_windows and self.cursor.x == self.columns - 2:\n # always put a linefeed marker when the next char is at the last column\n line[self.cursor.x + 1] = self.cursor.attrs._replace(data=\"\", linefeed=True)\n elif self.cursor.x + 1 < self.columns:\n line[self.cursor.x + 1] = self.cursor.attrs._replace(data=\"\")\n\n elif char_width == 0 and unicodedata.combining(char):\n # unfornately, sublime text doesn't render decomposed double char correctly\n pos = None\n for (row, col) in [\n (self.cursor.y, self.cursor.x),\n (self.cursor.y - 1, self.columns)]:\n if row < 0:\n continue\n if col >= 2:\n last = line[col - 2]\n if wcswidth(last.data) >= 2:\n pos = (row, col - 2)\n break\n if col >= 1:\n last = line[col - 1]\n pos = (row, col - 1)\n break\n\n if pos:\n normalized = unicodedata.normalize(\"NFC\", last.data + char)\n self.buffer[pos[0]][pos[1]] = last._replace(data=normalized)\n self.dirty.add(pos[0])\n else:\n break\n\n if char_width > 0:\n self.cursor.x = min(self.cursor.x + char_width, self.columns)\n\n self.dirty.add(self.cursor.y)","def addChar (self, c) :\r\n # Notice the \\n so we can notice when new lines begin\r\n if (c=='\\n') :\r\n self.lineNumber_ += 1\r\n self.charNumber_ = 0\r\n \r\n # Keep the last 1024 or so characters\r\n if (self.data_.full()) :\r\n self.data_.get()\r\n self.data_.put(c)\r\n self.charNumber_ += 1","def encode(self, text):\n if self.verbatim:\n return text\n # compile the regexps once. do it here so one can see them.\n #\n # first the braces.\n if not self.__dict__.has_key('encode_re_braces'):\n self.encode_re_braces = re.compile(r'([{}])')\n text = self.encode_re_braces.sub(r'{\\\\\\1}',text)\n if not self.__dict__.has_key('encode_re_bslash'):\n # find backslash: except in the form '{\\{}' or '{\\}}'.\n self.encode_re_bslash = re.compile(r'(?<!{)(\\\\)(?![{}]})')\n # then the backslash: except in the form from line above:\n # either '{\\{}' or '{\\}}'.\n text = self.encode_re_bslash.sub(r'{\\\\textbackslash}', text)\n\n # then dollar\n text = text.replace(\"$\", '{\\\\$}')\n # then all that needs math mode\n text = text.replace(\"<\", '{$<$}')\n text = text.replace(\">\", '{$>$}')\n # then\n text = text.replace(\"&\", '{\\\\&}')\n text = text.replace(\"_\", '{\\\\_}')\n # the ^:\n # * verb|^| does not work in mbox.\n # * mathmode has wedge. hat{~} would also work.\n text = text.replace(\"^\", '{\\\\ensuremath{^\\\\wedge}}')\n text = text.replace(\"%\", '{\\\\%}')\n text = text.replace(\"#\", '{\\\\#}')\n text = text.replace(\"~\", '{\\\\~{}}')\n if self.insert_newline:\n # HACK: insert a blank before the newline, to avoid \n # ! LaTeX Error: There's no line here to end.\n text = text.replace(\"\\n\", '~\\\\\\\\\\n')\n elif self.mbox_newline:\n text = text.replace(\"\\n\", '}\\\\\\\\\\n\\\\mbox{')\n if self.insert_none_breaking_blanks:\n text = text.replace(' ', '~')\n # unicode !!! \n text = text.replace(u'\\u2020', '{$\\\\dagger$}')\n return text","def add_junction(ccTremb):\n pass","def cmd_cb():\n cmds = []\n #cmds.append(\"r_m[0.0,-1,1]\")\n cmds.append(\"r_m[0.0]\")\n cmds.append('r_a[1.7,0,10]')\n cmds.append('r_n[1.5,0,10]')\n cmds.append(\"r_s[2.5,0,10]\")\n cmds.append('RooCBShape::res(x,r_m,r_s,r_a,r_n)')\n return cmds","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def update_control(self):\n self._control_ctr += 0x01","def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])","def _derive_modifiers(self, tx):\n return [tx + str(pixel) for pixel in self.adjacent_pixels]","def addControl(*args):","def addControl(*args):","def addControl(*args):","def addControl(*args):","def blueline(self):\n\t\treturn self.ESC+\"34m-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-\"+self.ESC+\"0m\\r\\n\"","def wdraw_rotated_text(self, wx, wy, text, angle, color, font):\r\n dx, dy = self.w_to_d(wx, wy)\r\n self.canvas.create_text(dx, dy, text=text, angle=angle, fill=color, font=font)","def gen_c_code(self, comp, dest, jump):\r\n return '111' + self.comp(comp) + self.dest(dest) + self.jump(jump)","def paint(self):\r\n self.win.bkgd(\" \", COLOR_PAIR[\"con_text\"])","def color_letter(self, letter, lst_labels, plain_text_widget, encrypted_text_widget):\r\n new_letter, txt_encryption = self.simulator_enigma.encrypt_letter(letter)\r\n lst_encryption_letter_stages = [i[-1] for i in txt_encryption.split(\"\\n\")]\r\n lst_encryption_letter_stages.remove(')')\r\n self.simulator_encryption.append((txt_encryption, lst_encryption_letter_stages))\r\n lst_labels[ord(new_letter) - 65].config(bg=\"yellow\")\r\n lst_labels[ord(new_letter) - 65].after(300, lambda: lst_labels[ord(new_letter) -\r\n 65].config(bg=\"khaki\"))\r\n\r\n plain_text_widget.config(state=NORMAL)\r\n plain_text_widget.insert(END, letter)\r\n plain_text_widget.config(state=DISABLED)\r\n encrypted_text_widget.config(state=NORMAL)\r\n encrypted_text_widget.insert(END, new_letter)\r\n encrypted_text_widget.config(state=DISABLED)","def append_circuit(self, lines: Tuple[int, int], circuit: ACircuit, content: str) -> None:","def cvChin(ctrlName, r=1):\r\n # create a simple circle curve:\r\n curve = cmds.curve(n=ctrlName, d=3, p=[(0, 0.8*r, -0.5*r), (0, 0.9*r, -0.7*r), (0, 0, -0.5*r), (0, -0.8*r, -0.7*r), (0, -0.8*r, 1.4*r), (0, -0.3*r, 1.3*r), (0, 0, 1.2*r), (0, 0, 0), (0, 0.8*r, -0.3*r), (0, 0.8*r, -0.5*r)] )\r\n # rename curveShape:\r\n renameShape([curve])\r\n return curve","def set_crystal(self, file_refl, a_bragg=0.0, thickness=0.1,\\\n tune_auto=0, tune_units=0, tune_ev=0.0, tune_ang=0.0):\n self.F_CRYSTAL = 1\n self.FILE_REFL = adjust_shadow_string(file_refl)\n\n if a_bragg != 0.0: self.set_asymmetric_cut(a_bragg, thickness)\n\n if tune_auto == 0:\n self.F_CENTRAL = 0\n else:\n self.set_auto_tuning(f_phot_cent=tune_units,\n phot_cent=tune_ev,\n r_lambda=tune_ang)","def __add_credit_cc(self):\n log.debug(\"Displaying __add_credit_cc\")\n # Create a keyboard to be sent later\n presets = self.cfg.ccard[\"payment_presets\"]\n keyboard = [[telegram.KeyboardButton(str(self.Price(preset)))] for preset in presets]\n keyboard.append([telegram.KeyboardButton(self.loc.get(\"menu_all_cancel\"))])\n # Boolean variable to check if the user has cancelled the action\n cancelled = False\n # Loop used to continue asking if there's an error during the input\n while not cancelled:\n # Send the message and the keyboard\n self.bot.send_message(self.chat.id, self.loc.get(\"payment_cc_amount\"),\n reply_markup=telegram.ReplyKeyboardMarkup(keyboard, one_time_keyboard=True))\n # Wait until a valid amount is sent\n selection = self.__wait_for_regex(r\"([0-9]+(?:[.,][0-9]+)?|\" + self.loc.get(\"menu_all_cancel\") + r\")\",\n cancellable=True)\n # If the user cancelled the action\n if isinstance(selection, CancelSignal):\n # Exit the loop\n cancelled = True\n continue\n # Convert the amount to an integer\n value = self.Price(selection)\n # Ensure the amount is within the range\n if value > self.Price(self.cfg.ccard[\"max_amount\"]):\n self.bot.send_message(self.chat.id,\n self.loc.get(\"error_payment_amount_over_max\",\n max_amount=self.Price(self.cfg.ccard[\"max_amount\"])))\n continue\n elif value < self.Price(self.cfg.ccard[\"min_amount\"]):\n self.bot.send_message(self.chat.id,\n self.loc.get(\"error_payment_amount_under_min\",\n min_amount=self.Price(self.cfg.ccard[\"min_amount\"])))\n continue\n break\n # If the user cancelled the action...\n else:\n # Exit the function\n return\n # Issue the payment invoice\n self.__make_payment(amount=value)","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def tikzcode(self):\n tex = \"\"\n tex += r\"\\draw\"\n if len(self.options):\n options = ', '.join(self.options)\n tex += \"[{options}] \".format(options=options)\n tex += \"({a.xpos:.4f},{a.ypos:.4f}) \".format(a=self.node_a)\n tex += \"to\"\n # if the nodes are arranged, then they have angle in/out\n inout = []\n inout.append('out={angle!s}'.format(angle=self.node_a.angle_inout))\n inout.append('in={angle!s}'.format(angle=self.node_b.angle_inout))\n if inout:\n tex += \"[\" + \", \".join(inout) + \"] \"\n tex += \"({b.xpos:.4f},{b.ypos:.4f})\".format(b=self.node_b)\n tex += \";\\n\"\n return tex","def encrypt(cleartext):\n base_encode = {'16': base64.b16encode,\n '32': base64.b32encode, '64': base64.b64encode}\n ciphertext = cleartext+''\n\n for i in range(encrypt_times):\n base = random.choice(['16', '32', '64'])\n ciphertext = base_encode[base](ciphertext)\n\n return ciphertext","def TAY(self, *_):\n self.reg.Y = self.reg.A\n self.reg.N = self.reg.Y << 7\n self.reg.Z = self.reg.Y == 0","def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","async def aesthetic(self, ctx, *, text):\n out = \"\"\n for char in text:\n out += utils.fullwidth_transform.get(char, char)\n await ctx.send(out)","def add(num1, num2, Cin):\n Cin=0\n l2=[]\n final=\"\"\n\n \"\"\"Using for loop for starting addition from the last indexed number\"\"\"\n for i in range(len(num1)-1,-1,-1):\n bit1=num1[i]#storing each indexed() value of num1 in bit1\n bit2=num2[i]#storing each indexed() value of num2 in bit2\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\n Cin=Cout#declaring cout as cin for next bit addition\n l2.append(SUM)#adding SUM to l2\n l3=l2[::-1]##reversing the value of l2\n final+=str(l2[-1])#converting the list value to string\n final1=final[::-1]#reversing string value\n return final1 #returning the binary addition as string","def basic_char_setup( self ):\n\t\tsmall_bar = 3 # number of points per bar\n\t\twide_bar = round(small_bar * 2.25,0) # 2.25 x small_bar\n\t\tdpl = 50 # dots per line 300dpi/6lpi = 50dpl\n\t\tself._nb = bytes( self.owner.PRINTER_ESC +\n\t\t\t\t\t\t ( '*c%02ia%ib0P' % (small_bar, self.bc_height*dpl) ) + \n\t\t\t\t\t\t self.owner.PRINTER_ESC + \n\t\t\t\t\t\t (\"*p+%02iX\" % small_bar) )\n\t\tself._wb = bytes( self.owner.PRINTER_ESC +\n\t\t\t\t\t\t ('*c%02ia%ib0P' % (wide_bar, self.bc_height*dpl) )+\n\t\t\t\t\t\t self.owner.PRINTER_ESC +\n\t\t\t\t\t\t ('*p+%02iX' % wide_bar ) )\n\t\tself._ns = bytes( self.owner.PRINTER_ESC + ( '*p+%02iX' % small_bar ) )\n\t\tself._ws = bytes( self.owner.PRINTER_ESC + ( '*p+%02iX' % wide_bar ) )\n \n\t\t# DONE nb = bc39_esc+\"*c\"+TRANSFORM(small_bar,'99')+\"a\"+Alltrim(STR(bc39_height*dpl))+\"b0P\"+bc39_esc+\"*p+\"+TRANSFORM(small_bar,'99')+\"X\"\n\t\t# DONE wb = bc39_esc+\"*c\"+TRANSFORM(wide_bar,'99')+\"a\"+Alltrim(STR(bc39_height*dpl))+\"b0P\"+bc39_esc+\"*p+\"+TRANSFORM(wide_bar,'99')+\"X\"\n\t\t# DONE ns = bc39_esc+\"*p+\"+TRANSFORM(small_bar,'99')+\"X\"\n\t\t# DONE ws = bc39_esc+\"*p+\"+TRANSFORM(wide_bar,'99')+\"X\"\n \n\t\t# adjust cusor position to start at top of line and return to bottom of line\n\t\tself._bc_start = bytes( self.owner.PRINTER_ESC + '*p-50Y' )\n\t\tself._bc_end = bytes( self.owner.PRINTER_ESC + '*p+50Y' )\n\t\t# DONE bc39_start = bc39_esc+\"*p-50Y\"\n\t\t# DONE bc39_END = bc39_esc+\"*p+50Y\"\n\n\t\t# setup the structure allowing to print the code codebar section for various LETTERS\n\t\tself._char39 = { u'1' : 'wb+ns+nb+ws+nb+ns+nb+ns+wb' , \n\t\t\t\t\t\t u'2' : 'nb+ns+wb+ws+nb+ns+nb+ns+wb' , \n\t\t\t\t\t\t u'3' : 'wb+ns+wb+ws+nb+ns+nb+ns+nb' , \n\t\t\t\t\t\t u'4' : 'nb+ns+nb+ws+wb+ns+nb+ns+wb' , \n\t\t\t\t\t\t u'5' : 'wb+ns+nb+ws+wb+ns+nb+ns+nb' , \n\t\t\t\t\t\t u'6' : 'nb+ns+wb+ws+wb+ns+nb+ns+nb' , \n\t\t\t\t\t\t u'7' : 'nb+ns+nb+ws+nb+ns+wb+ns+wb' , \n\t\t\t\t\t\t u'8' : 'wb+ns+nb+ws+nb+ns+wb+ns+nb' , \n\t\t\t\t\t\t u'9' : 'nb+ns+wb+ws+nb+ns+wb+ns+nb' , \n\t\t\t\t\t\t u'0' : 'nb+ns+nb+ws+wb+ns+wb+ns+nb' , \n\t\t\t\t\t\t u'A' : 'wb+ns+nb+ns+nb+ws+nb+ns+wb' , \n\t\t\t\t\t\t u'B' : 'nb+ns+wb+ns+nb+ws+nb+ns+wb' , \n\t\t\t\t\t\t u'C' : 'wb+ns+wb+ns+nb+ws+nb+ns+nb' , \n\t\t\t\t\t\t u'D' : 'nb+ns+nb+ns+wb+ws+nb+ns+wb' , \n\t\t\t\t\t\t u'E' : 'wb+ns+nb+ns+wb+ws+nb+ns+nb' , \n\t\t\t\t\t\t u'F' : 'nb+ns+wb+ns+wb+ws+nb+ns+nb' , \n\t\t\t\t\t\t u'G' : 'nb+ns+nb+ns+nb+ws+wb+ns+wb' , \n\t\t\t\t\t\t u'H' : 'wb+ns+nb+ns+nb+ws+wb+ns+nb' , \n\t\t\t\t\t\t u'I' : 'nb+ns+wb+ns+nb+ws+wb+ns+nb' , \n\t\t\t\t\t\t u'J' : 'nb+ns+nb+ns+wb+ws+wb+ns+nb' , \n\t\t\t\t\t\t u'K' : 'wb+ns+nb+ns+nb+ns+nb+ws+wb' , \n\t\t\t\t\t\t u'L' : 'nb+ns+wb+ns+nb+ns+nb+ws+wb' , \n\t\t\t\t\t\t u'M' : 'wb+ns+wb+ns+nb+ns+nb+ws+nb' , \n\t\t\t\t\t\t u'N' : 'nb+ns+nb+ns+wb+ns+nb+ws+wb' , \n\t\t\t\t\t\t u'O' : 'wb+ns+nb+ns+wb+ns+nb+ws+nb' , \n\t\t\t\t\t\t u'P' : 'nb+ns+wb+ns+wb+ns+nb+ws+nb' , \n\t\t\t\t\t\t u'Q' : 'nb+ns+nb+ns+nb+ns+wb+ws+wb' , \n\t\t\t\t\t\t u'R' : 'wb+ns+nb+ns+nb+ns+wb+ws+nb' , \n\t\t\t\t\t\t u'S' : 'nb+ns+wb+ns+nb+ns+wb+ws+nb' , \n\t\t\t\t\t\t u'T' : 'nb+ns+nb+ns+wb+ns+wb+ws+nb' , \n\t\t\t\t\t\t u'U' : 'wb+ws+nb+ns+nb+ns+nb+ns+wb' , \n\t\t\t\t\t\t u'V' : 'nb+ws+wb+ns+nb+ns+nb+ns+wb' , \n\t\t\t\t\t\t u'W' : 'wb+ws+wb+ns+nb+ns+nb+ns+nb' , \n\t\t\t\t\t\t u'X' : 'nb+ws+nb+ns+wb+ns+nb+ns+wb' , \n\t\t\t\t\t\t u'Y' : 'wb+ws+nb+ns+wb+ns+nb+ns+nb' , \n\t\t\t\t\t\t u'Z' : 'nb+ws+wb+ns+wb+ns+nb+ns+nb' , \n\t\t\t\t\t\t u'-' : 'nb+ws+nb+ns+nb+ns+wb+ns+wb' , \n\t\t\t\t\t\t u'.' : 'wb+ws+nb+ns+nb+ns+wb+ns+nb' , \n\t\t\t\t\t\t u' ' : 'nb+ws+wb+ns+nb+ns+wb+ns+nb' , \n\t\t\t\t\t\t u'*' : 'nb+ws+nb+ns+wb+ns+wb+ns+nb' , \n\t\t\t\t\t\t u'$' : 'nb+ws+nb+ws+nb+ws+nb+ns+nb' , \n\t\t\t\t\t\t u'/' : 'nb+ws+nb+ws+nb+ns+nb+ws+nb' , \n\t\t\t\t\t\t u'+' : 'nb+ws+nb+ns+nb+ws+nb+ws+nb' , \n\t\t\t\t\t\t u'%' : 'nb+ns+nb+ws+nb+ws+nb+ws+nb' }","def add_char(self, coord, char, modify=False):\n if modify:\n range_y, range_x = self._map_dims\n new_coord = [coord[0]+range_y[0]-1, coord[1]+range_x[0]-1]\n self._screen.addch(new_coord[0], new_coord[1], char)\n self._screen.refresh()\n return new_coord\n else:\n self._screen.addch(coord[0], coord[1], char)\n self._screen.refresh()\n return coord","def keypress(self, event):\n stepsize = 0.15 # pixels, i.e. 0.05 arcsec\n if event.key == 'right':\n if self.ccd == 2:\n self.shift_crpix1 -= stepsize\n else:\n self.shift_crpix2 += stepsize\n elif event.key == 'left':\n if self.ccd == 2:\n self.shift_crpix1 += stepsize\n else:\n self.shift_crpix2 -= stepsize\n elif event.key == ']':\n if self.ccd == 2:\n self.shift_crpix1 -= 5*stepsize\n else:\n self.shift_crpix2 += 5*stepsize\n elif event.key == '[':\n if self.ccd == 2:\n self.shift_crpix1 += 5*stepsize\n else:\n self.shift_crpix2 -= 5*stepsize\n elif event.key == 'up':\n if self.ccd == 2:\n self.shift_crpix2 += stepsize\n else:\n self.shift_crpix1 += stepsize\n elif event.key == 'down':\n if self.ccd == 2:\n self.shift_crpix2 -= stepsize\n else:\n self.shift_crpix1 -= stepsize\n elif event.key == \"'\":\n if self.ccd == 2:\n self.shift_crpix2 += 5*stepsize\n else:\n self.shift_crpix1 += 5*stepsize\n elif event.key == '/':\n if self.ccd == 2:\n self.shift_crpix2 -= 5*stepsize\n else:\n self.shift_crpix1 -= 5*stepsize\n elif event.key == '1':\n self.shift_cd1_1 += 1e-8\n elif event.key == '2':\n self.shift_cd1_1 -= 1e-8\n elif event.key == '3':\n self.shift_cd1_2 += 1e-8\n elif event.key == '4':\n self.shift_cd1_2 -= 1e-8\n elif event.key == '5':\n self.shift_cd2_1 += 1e-8\n elif event.key == '6':\n self.shift_cd2_1 -= 1e-8\n elif event.key == '7':\n self.shift_cd2_2 += 2e-8\n elif event.key == '8':\n self.shift_cd2_2 -= 2e-8\n elif event.key == 'r': # Reset\n self.shift_crpix1 = 0.0\n self.shift_crpix2 = 0.0\n self.shift_cd1_1 = 0.0\n self.shift_cd1_2 = 0.0\n self.shift_cd2_1 = 0.0\n self.shift_cd2_2 = 0.0\n elif event.key == 'o': # OK, field does not need fix\n self.mark_done()\n elif event.key == 'w': # Write WCS\n self.write() # Save the results to a csv file\n self.mark_done()\n # Now update the plot for the slight change in WCS parameters\n self.update()","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def gcode_text(self):\n return os.linesep.join(map(str, self.gcode))","def cctw_command(self, mask=False):\n entry = self.entry.nxname\n if mask:\n name = entry + '_masked_transform'\n else:\n name = entry + '_transform'\n dir = os.path.dirname(self.entry['data'].nxsignal.nxfilename)\n filename = self.entry.nxfilename\n parfile = os.path.join(dir, entry+'_transform.pars')\n command = ['cctw transform']\n command.append(f'--parameters {parfile}')\n if 'pixel_mask' in self.entry['instrument/detector']:\n command.append(\n fr'--mask {filename}\\#/{entry}/instrument/detector/pixel_mask')\n if mask and 'data_mask' in self.entry['data']:\n command.append(f'--mask3d {filename}\\\\#/{entry}/data/data_mask')\n if 'monitor_weight' in self.entry['data']:\n command.append(\n fr'--weights {filename}\\#/{entry}/data/monitor_weight')\n if 'polarization' in self.entry['instrument/detector']:\n command.append(\n fr'--weights {filename}\\#/{entry}'\n '/instrument/detector/polarization')\n raw_filename = self.entry['data/data'].nxfilename\n raw_filepath = self.entry['data/data'].nxfilepath\n command.append(fr'{raw_filename}\\#/{raw_filepath}')\n command.append(fr'--output {dir}/{name}.nxs\\#/entry/data')\n command.append('--normalization 0')\n return ' '.join(command)","def increase_radius(self, character):\n character.bombradius += 1","def writec(text, color='black', style='normal'):\n\n sys.stdout.write(strc(text, color, style))","def ch(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_H, qid=[q0,q1], ctrl=ctrl)\n return self","def update(w, g, alpha = 0.03):\n return w + alpha * g","def enable_cl1_direct(self):\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\n self.write_versa5(0x18,0x20)\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\n self.write_versa5(0x13,0x03) ## Switch to clock\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew","def draw_cat():\n print '_-_-_-_-_-_-_\\n' \\\n '\\ /\\n' \\\n '| ^_____^ |\\n' \\\n '/ (.) (.) \\\\\\n' \\\n '| ( t ) | Miaowww\\n' \\\n '\\ ==/ /\\n' \\\n '| |\\n' \\\n '\\'\"\\'\"\\'\"\\'\"\\'\"\\'\"\\''\n\n print '''\n_-_-_-_-_-_-_\n\\ /\n| ^_____^ |\n/ (.) (.) \\\\\n| ( t ) | Miaowww\n\\ ==/ /\n| |\n'\"'\"'\"'\"'\"'\"'\n'''\n\n print r'_-_-_-_-_-_-_'\n print r'\\ /'\n print r'| ^_____^ |'\n print '/ (.) (.) \\\\'\n print r'| ( t ) | Miaowww'\n print r'\\ ==/ /'\n print r'| |'\n print '\\'\"\\'\"\\'\"\\'\"\\'\"\\'\"\\''\n\n print \"\"\"\n_-_-_-_-_-_-_\n\\ /\n| ^_____^ |\n/ (.) (.) \\\\\n| ( t ) | Miaowww\n\\ ==/ /\n| |\n'\"'\"'\"'\"'\"'\"'\n\"\"\"","def cipherFromReflector(self, char):\n inputCharNum = self.GetNumByChar(char) #Finds the index of the value for the input character to find the internal wiring connection\n outputChar = self.chrNum(inputCharNum) #Finds the ASCII code of the index value to find the external rotor connection \n return outputChar #Returns the external character that the wiring is connected to","def _text8(self, font, text, x0, y0, color=WHITE, background=BLACK):\n for char in text:\n ch = ord(char)\n if (font.FIRST <= ch < font.LAST\n and x0+font.WIDTH <= self.width\n and y0+font.HEIGHT <= self.height):\n\n if font.HEIGHT == 8:\n passes = 1\n size = 8\n each = 0\n else:\n passes = 2\n size = 16\n each = 8\n\n for line in range(passes):\n idx = (ch-font.FIRST)*size+(each*line)\n buffer = struct.pack(\n '>64H',\n color if font.FONT[idx] & _BIT7 else background,\n color if font.FONT[idx] & _BIT6 else background,\n color if font.FONT[idx] & _BIT5 else background,\n color if font.FONT[idx] & _BIT4 else background,\n color if font.FONT[idx] & _BIT3 else background,\n color if font.FONT[idx] & _BIT2 else background,\n color if font.FONT[idx] & _BIT1 else background,\n color if font.FONT[idx] & _BIT0 else background,\n color if font.FONT[idx+1] & _BIT7 else background,\n color if font.FONT[idx+1] & _BIT6 else background,\n color if font.FONT[idx+1] & _BIT5 else background,\n color if font.FONT[idx+1] & _BIT4 else background,\n color if font.FONT[idx+1] & _BIT3 else background,\n color if font.FONT[idx+1] & _BIT2 else background,\n color if font.FONT[idx+1] & _BIT1 else background,\n color if font.FONT[idx+1] & _BIT0 else background,\n color if font.FONT[idx+2] & _BIT7 else background,\n color if font.FONT[idx+2] & _BIT6 else background,\n color if font.FONT[idx+2] & _BIT5 else background,\n color if font.FONT[idx+2] & _BIT4 else background,\n color if font.FONT[idx+2] & _BIT3 else background,\n color if font.FONT[idx+2] & _BIT2 else background,\n color if font.FONT[idx+2] & _BIT1 else background,\n color if font.FONT[idx+2] & _BIT0 else background,\n color if font.FONT[idx+3] & _BIT7 else background,\n color if font.FONT[idx+3] & _BIT6 else background,\n color if font.FONT[idx+3] & _BIT5 else background,\n color if font.FONT[idx+3] & _BIT4 else background,\n color if font.FONT[idx+3] & _BIT3 else background,\n color if font.FONT[idx+3] & _BIT2 else background,\n color if font.FONT[idx+3] & _BIT1 else background,\n color if font.FONT[idx+3] & _BIT0 else background,\n color if font.FONT[idx+4] & _BIT7 else background,\n color if font.FONT[idx+4] & _BIT6 else background,\n color if font.FONT[idx+4] & _BIT5 else background,\n color if font.FONT[idx+4] & _BIT4 else background,\n color if font.FONT[idx+4] & _BIT3 else background,\n color if font.FONT[idx+4] & _BIT2 else background,\n color if font.FONT[idx+4] & _BIT1 else background,\n color if font.FONT[idx+4] & _BIT0 else background,\n color if font.FONT[idx+5] & _BIT7 else background,\n color if font.FONT[idx+5] & _BIT6 else background,\n color if font.FONT[idx+5] & _BIT5 else background,\n color if font.FONT[idx+5] & _BIT4 else background,\n color if font.FONT[idx+5] & _BIT3 else background,\n color if font.FONT[idx+5] & _BIT2 else background,\n color if font.FONT[idx+5] & _BIT1 else background,\n color if font.FONT[idx+5] & _BIT0 else background,\n color if font.FONT[idx+6] & _BIT7 else background,\n color if font.FONT[idx+6] & _BIT6 else background,\n color if font.FONT[idx+6] & _BIT5 else background,\n color if font.FONT[idx+6] & _BIT4 else background,\n color if font.FONT[idx+6] & _BIT3 else background,\n color if font.FONT[idx+6] & _BIT2 else background,\n color if font.FONT[idx+6] & _BIT1 else background,\n color if font.FONT[idx+6] & _BIT0 else background,\n color if font.FONT[idx+7] & _BIT7 else background,\n color if font.FONT[idx+7] & _BIT6 else background,\n color if font.FONT[idx+7] & _BIT5 else background,\n color if font.FONT[idx+7] & _BIT4 else background,\n color if font.FONT[idx+7] & _BIT3 else background,\n color if font.FONT[idx+7] & _BIT2 else background,\n color if font.FONT[idx+7] & _BIT1 else background,\n color if font.FONT[idx+7] & _BIT0 else background\n )\n self.blit_buffer(buffer, x0, y0+8*line, 8, 8)\n\n x0 += 8","def CarryExpression(n, c):\n combinations = Combinations(n, c)\n bit_and_list = []\n for ii in range(len(combinations)):\n bit_and_list.append('&'.join('a[%d]' % jj for jj in combinations[ii]))\n carry_expression = '|'.join(bit_and_list)\n return carry_expression"],"string":"[\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def step1c(self):\\n\\t\\tif (self.ends(\\\"y\\\") and self.vowelinstem()):\\n\\t\\t\\tself.b = self.b[:self.k] + 'i' + self.b[self.k+1:]\",\n \"def addch(self, stdscr, y, x, text):\\n stdscr.addch(y, x, text, curses.color_pair(self.i))\",\n \"def _latex_(self):\\n return \\\"\\\\\\\\Bold{C}\\\"\",\n \"def cy(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CY(), target=[control, target])\",\n \"def operator_c(buf, input_line, pos1, pos2, overwrite=False):\\n operator_d(buf, input_line, pos1, pos2, overwrite)\\n set_mode(\\\"INSERT\\\")\",\n \"def add_tex_to_binning(self, binning_dict):\\n if 'reco' in binning_dict['name']:\\n sub_string = 'reco'\\n elif 'true' in binning_dict['name']:\\n sub_string = 'true'\\n else:\\n sub_string = None\\n if 'energy' in binning_dict['name']:\\n binning_dict['tex'] = r'$E_{%s}$'%sub_string\\n elif 'coszen' in binning_dict['name']:\\n binning_dict['tex'] = r'$\\\\cos\\\\theta_{Z,%s}$'%sub_string\",\n \"def test_drawing_ascii():\\r\\n from pennylane import numpy as np\\r\\n\\r\\n x = np.array(0.1, requires_grad=True)\\r\\n y = np.array([0.2, 0.3], requires_grad=True)\\r\\n z = np.array(0.4, requires_grad=True)\\r\\n\\r\\n dev = qml.device(\\\"default.qubit\\\", wires=2)\\r\\n\\r\\n @qml.beta.qnode(dev, interface=\\\"autograd\\\")\\r\\n def circuit(p1, p2=y, **kwargs):\\r\\n qml.RX(p1, wires=0)\\r\\n qml.RY(p2[0] * p2[1], wires=1)\\r\\n qml.RX(kwargs[\\\"p3\\\"], wires=0)\\r\\n qml.CNOT(wires=[0, 1])\\r\\n return qml.expval(qml.PauliZ(0) @ qml.PauliX(1))\\r\\n\\r\\n result = qml.draw(circuit, charset=\\\"ascii\\\")(p1=x, p3=z)\\r\\n expected = \\\"\\\"\\\"\\\\\\r\\n 0: --RX(0.1)---RX(0.4)--+C--+| <Z @ X> \\r\\n 1: --RY(0.06)-----------+X--+| <Z @ X> \\r\\n\\\"\\\"\\\"\\r\\n\\r\\n assert result == expected\",\n \"def add(text):\\n orig = dispb[\\\"text\\\"]\\n new = orig + text\\n ops = [\\\"+\\\",\\\"-\\\",\\\"*\\\",\\\"/\\\"]\\n # conditions\\n # length 21\\n if len(new) > 21:\\n dispb[\\\"text\\\"] = orig\\n return 0\\n \\n # one calc at a time\\n if len(orig) > 0:\\n if (orig[-1] in ops) & (text in ops):\\n dispb[\\\"text\\\"] = orig\\n return 0\\n\\n dispb[\\\"text\\\"] = new\\n return 0\",\n \"def cb_plus(event):\\n delta_alpha = pm_rate\\n # Increase Alpha \\n sAlpha0.set_val( np.clip(sAlpha0.val + delta_alpha, alpha_min[0], alpha_max[0]) )\\n sAlpha1.set_val( np.clip(sAlpha1.val + delta_alpha, alpha_min[1], alpha_max[1]) )\\n sAlpha2.set_val( np.clip(sAlpha2.val + delta_alpha, alpha_min[2], alpha_max[2]) )\\n print(\\\"+++\\\")\",\n \"def cxr(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def operate_cipher(self):\",\n \"def placeCrate (self, crates_char, row, column):\",\n \"def secret_char(c):\\n return \\\"\\\\\\\\raisebox{{0.07ex}}{{{}}}\\\".format(c)\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def draw_instruction():\\r\\n arcade.draw_text(\\r\\n \\\"This is a game of Santa, Reindeer, Snowman\\\", 0, 50, arcade.color.WHITE, 15\\r\\n )\\r\\n arcade.draw_text(\\r\\n \\\"Santa beats snowman, snowman beats reindeer, reindeer beats santa\\\",\\r\\n 0,\\r\\n 30,\\r\\n arcade.color.WHITE,\\r\\n 13,\\r\\n )\\r\\n arcade.draw_text(\\r\\n \\\"Press button 1 for santa, 2 for reindeer, and 3 for snowman\\\",\\r\\n 0,\\r\\n 10,\\r\\n arcade.color.WHITE,\\r\\n 15,\\r\\n )\\r\\n arcade.draw_text(\\r\\n \\\"User Choice\\\", WINDOW_WIDTH - 175, WINDOW_HEIGHT - 60, arcade.color.WHITE, 15\\r\\n )\\r\\n arcade.draw_text(\\\"CPU Choice\\\", 75, WINDOW_HEIGHT - 60, arcade.color.WHITE, 15)\",\n \"def add_cogs(self):\\n self.add_cog(Voice(self))\",\n \"def risePen(gcode):\\r\\n gcode.append(\\\"M300 S46\\\")\\r\\n #gcode.append(\\\"G0 Z0.1000\\\")\\r\",\n \"def clowder_command(cmd):\\n\\n return colored(cmd, attrs=['bold'])\",\n \"def cr(self):\\n self._write('\\\\x0d')\",\n \"def createBtnCmd(self, *args):\\r\\n self.cone = cmds.polyCone()\\r\\n cmds.setAttr('%s.rotateX' % self.cone[0], 90)\",\n \"def make_control_character():\\n # Add one character made up of one codepoint each from\\n # (High Surrogates + High Private Use Surrogates) and Low Surrogates.\\n # We expect each such pair to behave as a single high-codepoint\\n # character.\\n controls = ('0000', '001F')\\n return [unicode_char(char)\\n for char in range(int(controls[0], 16), int(controls[1], 16)+1)]\",\n \"def charpoly_berk(self):\\n return self.rep.charpoly()\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def morphstring_add(self, stringz):\\n self.textEdit_morph.setTextColor(QColor(0, 0, 0, 255))\\n stringz += f\\\" kernel: {self.spinBox.value()} shape: {self.comboBox.currentIndex()}\\\"\\n self.textEdit_morph.append(stringz)\",\n \"def _gyration(self, x, y, v, c):\\n xy = self._mobius_add(x, y, c)\\n yv = self._mobius_add(y, v, c)\\n xyv = self._mobius_add(x, yv, c)\\n return self._mobius_add(-xy, xyv, c)\",\n \"def read_carry(self):\\n return self.CARRY\",\n \"def csi_to_conky(match: re.Match) -> str:\\n # Convert the string of code;code;code to a list of ints\\n try:\\n codes= [0 if _=='' else int(_) for _ in match.group(1).split(';')]\\n except IndexError: \\n print('csi_to_conky called with no group match', file=sys.stderr)\\n return match.group(0) # if no group has matched return the string as is\\n except ValueError as err: # problem converting to int\\n print(f'csi_to_conky: {err}', file=sys.stderr)\\n return match.group(0)\\n \\n # Initialize the string to be returned\\n result=''\\n\\n # consume the list one code at a time, first to last\\n while len(codes)>0:\\n code=codes.pop(0)\\n if code==0: # Reset\\n # Clear the string and init it with default color and font\\n result = '${color}${font}'\\n continue\\n \\n elif code==1: # Bold\\n result += '${font DejaVu Sans Mono:style=bold}'\\n continue\\n \\n elif code>29 and code<38: # Set foreground color (0 to 7)\\n result += conky_set_fg(code -30)\\n continue\\n \\n elif code==38: # Advanced ANSI\\n try:\\n type=codes.pop(0)\\n if type==2: # ESC[38;2;R;G;Bm => TODO\\n # for now just consume the next 3 values in the list\\n del codes[0:3]\\n continue\\n elif type==5: # ESC[38;5;xxm \\n result += eightbit_to_conky(codes.pop(0))\\n continue\\n else:\\n raise ValueError(f'Improper value {type} after code 38')\\n except (IndexError, ValueError) as err:\\n print(f'csi_to_conky: {err} while parsing advanced ANSI sequence {code};{type}', file=sys.stderr)\\n continue\\n \\n elif code==39: # default fg\\n result +='${color}'\\n continue\\n \\n else:\\n print(f'code {code} not implemented', file=sys.stderr)\\n continue \\n\\n return result\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def cesar(text, num, rshift):\\n shift = num if rshift else -num\\n codedtext = []\\n for line in text:\\n codedline = \\\"\\\"\\n line = line.lower()\\n for char in line:\\n newchar = ord(char) + shift\\n if newchar > 126:\\n newchar = 32 + ord(char) - 127 + shift\\n elif newchar < 32:\\n newchar = 127 + ord(char) - 32 + shift\\n codedline += chr(newchar)\\n shift = -shift\\n codedtext.append(codedline)\\n return codedtext\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def show_c(text):\\n complement = text.replace(\\\"_\\\", \\\" \\\")\\n return 'C %s' % complement\",\n \"def _parse_corot(self) -> Generator[None, str, None]:\\n style = \\\"\\\"\\n formatted_text = self._formatted_text\\n\\n while True:\\n # NOTE: CSI is a special token within a stream of characters that\\n # introduces an ANSI control sequence used to set the\\n # style attributes of the following characters.\\n csi = False\\n\\n c = yield\\n\\n # Everything between \\\\001 and \\\\002 should become a ZeroWidthEscape.\\n if c == \\\"\\\\001\\\":\\n escaped_text = \\\"\\\"\\n while c != \\\"\\\\002\\\":\\n c = yield\\n if c == \\\"\\\\002\\\":\\n formatted_text.append((\\\"[ZeroWidthEscape]\\\", escaped_text))\\n c = yield\\n break\\n else:\\n escaped_text += c\\n\\n # Check for CSI\\n if c == \\\"\\\\x1b\\\":\\n # Start of color escape sequence.\\n square_bracket = yield\\n if square_bracket == \\\"[\\\":\\n csi = True\\n else:\\n continue\\n elif c == \\\"\\\\x9b\\\":\\n csi = True\\n\\n if csi:\\n # Got a CSI sequence. Color codes are following.\\n current = \\\"\\\"\\n params = []\\n\\n while True:\\n char = yield\\n\\n # Construct number\\n if char.isdigit():\\n current += char\\n\\n # Eval number\\n else:\\n # Limit and save number value\\n params.append(min(int(current or 0), 9999))\\n\\n # Get delimiter token if present\\n if char == \\\";\\\":\\n current = \\\"\\\"\\n\\n # Check and evaluate color codes\\n elif char == \\\"m\\\":\\n # Set attributes and token.\\n self._select_graphic_rendition(params)\\n style = self._create_style_string()\\n break\\n\\n # Check and evaluate cursor forward\\n elif char == \\\"C\\\":\\n for i in range(params[0]):\\n # add <SPACE> using current style\\n formatted_text.append((style, \\\" \\\"))\\n break\\n\\n else:\\n # Ignore unsupported sequence.\\n break\\n else:\\n # Add current character.\\n # NOTE: At this point, we could merge the current character\\n # into the previous tuple if the style did not change,\\n # however, it's not worth the effort given that it will\\n # be \\\"Exploded\\\" once again when it's rendered to the\\n # output.\\n formatted_text.append((style, c))\",\n \"def cxr_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def braan_s(self):\\n self.handle_key('e')\\n self.handle_key('y')\\n \\n # advance gram with hexed g\\n self.handle_key('<heks>')\\n self.handle_key('g')\\n \\n self.handle_key('n')\\n self.handle_key('n')\\n \\n # advance wurd\\n self.handle_key('<trgr>')\\n \\n self.handle_key('g')\\n self.handle_key('u')\\n self.handle_key('n')\\n \\n # advance gram with hexed g\\n self.handle_key('<heks>')\\n self.handle_key('g')\\n\\n self.handle_key('u')\\n\\n # advance line\\n self.handle_key('<heks>')\\n self.handle_key('<trgr>')\\n \\n self.handle_key('e')\\n self.handle_key('e')\\n self.handle_key('t')\\n\\n # advance wurd\\n self.handle_key('<trgr>')\\n\\n self.handle_key('y')\\n self.handle_key('o')\\n self.handle_key('r')\\n\\n # advance wurd\\n self.handle_key('<trgr>')\\n \\n self.handle_key('b')\\n self.handle_key('r')\\n self.handle_key('a')\\n self.handle_key('a')\\n self.handle_key('n')\\n\\n # advance gram with hexed g\\n self.handle_key('<heks>')\\n self.handle_key('g')\\n\\n self.handle_key('s')\\n\\n # advance line\\n self.handle_key('<heks>')\\n self.handle_key('<trgr>')\\n\\n self.handle_key('a')\\n self.handle_key('n')\\n self.handle_key('d')\\n \\n # advance line\\n self.handle_key('<heks>')\\n self.handle_key('<trgr>')\\n\\n self.handle_key('s')\\n self.handle_key('t')\\n self.handle_key('e')\\n self.handle_key('e')\\n self.handle_key('l')\\n\\n # advance wurd\\n self.handle_key('<trgr>')\\n\\n self.handle_key('y')\\n self.handle_key('o')\\n self.handle_key('r')\\n\\n # advance wurd\\n self.handle_key('<trgr>')\\n \\n self.handle_key('n')\\n self.handle_key('a')\\n self.handle_key('l')\\n self.handle_key('e')\\n self.handle_key('g')\\n self.handle_key('g')\\n\\n # advance line\\n self.handle_key('<heks>')\\n self.handle_key('<trgr>')\",\n \"def paintText(self, text):\\n return '@paint '+text * 2\",\n \"def key_cc(buf, input_line, cur, count):\\n weechat.command(\\\"\\\", \\\"/input delete_line\\\")\\n set_mode(\\\"INSERT\\\")\",\n \"def lowerPen(gcode):\\r\\n gcode.append(\\\"M300 S43\\\")\\r\\n #gcode.append(\\\"G0 Z0\\\")\\r\",\n \"def asm(self, text):\\n self.text.append(text)\",\n \"def encrypt(inp):\\n # prepare plaintext\\n prefix = \\\"comment1=cooking%20MCs;userdata=\\\"\\n suffix = \\\";comment2=%20like%20a%20pound%20of%20bacon\\\"\\n pt = inp.replace(\\\";\\\", \\\"\\\").replace(\\\"=\\\", \\\"\\\") # remove invalid character\\n pt = prefix + pt + suffix # add prefix and suffix\\n pt_encoded = pt.encode(\\\"utf-8\\\")\\n pt_padded = pkcs7.add(pt_encoded, aes.S_BLOCK)\\n\\n # encrypt\\n ct = aes.cbc_encrypt(pt_padded, KEY, IV)\\n\\n return ct\",\n \"def glycosylate(self):\\n chid = self.chain.get()\\n sequon = self.sequon.get()\\n self.sequon_colors[sequon] = [.7, .1, 0]\\n key = self.sequon.get()\\n residue = self.myGlycosylator.get_residue(key)\\n #Build new glycan\\n if self.selected_glycan:\\n self.myGlycosylator.connect_topology['SELECTED'] = self.selected_glycan[1]\\n #build from current glycan\\n if key in self.original_glycans:\\n original_glycan = self.original_glycanMolecules[key].atom_group\\n r,t = self.original_glycans[key]\\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\\n else:\\n original_glycan = None\\n connect_tree = None \\n #Use current glycan\\n else:\\n original_glycan = self.original_glycanMolecules[key]\\n r,t = self.original_glycans[key]\\n connect_tree = self.myGlycosylator.build_connectivity_tree(r, t)\\n self.myGlycosylator.connect_topology['SELECTED'] = self.myGlycosylator.build_connect_topology(original_glycan) \\n original_glycan = original_glycan.atom_group\\n \\n segname = 'G'+key.split(',')[2]\\n glycan,bonds = self.myGlycosylator.glycosylate('SELECTED', \\n template_glycan_tree = connect_tree, \\n template_glycan = original_glycan,\\n link_residue=residue, link_patch = 'NGLB', chain = 'G', segname=segname)\\n new_glycan = glc.Molecule(key)\\n new_glycan.set_AtomGroup(glycan, bonds = bonds)\\n self.myGlycosylator.assign_patches(new_glycan)\\n self.linked_glycanMolecules[key] = new_glycan\\n self.linked_glycans[key] = [new_glycan.rootRes, new_glycan.interresidue_connectivity]\\n self.names.update(new_glycan.get_names())\\n # Update glycoprotein and sequon panels\\n self.draw_glycoprotein(chid)\\n self.draw_glycan(sequon)\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def encrypt(text,key):\\r\\n aes = pyaes.AESModeOfOperationCTR(key)\\r\\n ciphertext = aes.encrypt(text)\\r\\n return ciphertext\",\n \"def tx(self):\\n cmd = Command()\\n cmd.set_num(0x1C)\\n cmd.set_subcmd_num(0x00)\\n cmd.set_data([0x01])\\n self.connection.send_cmd(cmd.render())\",\n \"def encipher(self):\\n ciphertext = \\\"\\\"\\n for pt, key_char in zip(self.text, self.key):\\n char_index = self.char_block.alphabet.index(pt)\\n ciphertext += self.char_block.rows[key_char][char_index]\\n print(ciphertext)\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def create_brake_command(apply_brake, pcm_override, pcm_cancel_cmd, chime, idx):\\n pump_on = apply_brake > 0\\n brakelights = apply_brake > 0\\n brake_rq = apply_brake > 0\\n\\n pcm_fault_cmd = False\\n amount = struct.pack(\\\"!H\\\", (apply_brake << 6) + pump_on)\\n msg = amount + struct.pack(\\\"BBB\\\", (pcm_override << 4) |\\n (pcm_fault_cmd << 2) |\\n (pcm_cancel_cmd << 1) | brake_rq, 0x80,\\n brakelights << 7) + chr(chime) + \\\"\\\\x00\\\"\\n return make_can_msg(0x1fa, msg, idx, 0)\",\n \"def encode(self, text):\\n if self.verbatim:\\n return text\\n # compile the regexps once. do it here so one can see them.\\n #\\n # first the braces.\\n if not self.__dict__.has_key('encode_re_braces'):\\n self.encode_re_braces = re.compile(r'([{}])')\\n text = self.encode_re_braces.sub(r'{\\\\\\\\\\\\1}',text)\\n if not self.__dict__.has_key('encode_re_bslash'):\\n # find backslash: except in the form '{\\\\{}' or '{\\\\}}'.\\n self.encode_re_bslash = re.compile(r'(?<!{)(\\\\\\\\)(?![{}]})')\\n # then the backslash: except in the form from line above:\\n # either '{\\\\{}' or '{\\\\}}'.\\n text = self.encode_re_bslash.sub(r'{\\\\\\\\textbackslash}', text)\\n\\n # then dollar\\n text = text.replace(\\\"$\\\", '{\\\\\\\\$}')\\n if not ( self.literal_block or self.literal or self.mathmode ):\\n # the vertical bar: in mathmode |,\\\\vert or \\\\mid\\n # in textmode \\\\textbar\\n text = text.replace(\\\"|\\\", '{\\\\\\\\textbar}')\\n text = text.replace(\\\"<\\\", '{\\\\\\\\textless}')\\n text = text.replace(\\\">\\\", '{\\\\\\\\textgreater}')\\n # then\\n text = text.replace(\\\"&\\\", '{\\\\\\\\&}')\\n # the ^:\\n # * verb|^| does not work in mbox.\\n # * mathmode has wedge. hat{~} would also work.\\n # text = text.replace(\\\"^\\\", '{\\\\\\\\ensuremath{^\\\\\\\\wedge}}')\\n text = text.replace(\\\"^\\\", '{\\\\\\\\textasciicircum}')\\n text = text.replace(\\\"%\\\", '{\\\\\\\\%}')\\n text = text.replace(\\\"#\\\", '{\\\\\\\\#}')\\n text = text.replace(\\\"~\\\", '{\\\\\\\\textasciitilde}')\\n # Separate compound characters, e.g. \\\"--\\\" to \\\"-{}-\\\". (The\\n # actual separation is done later; see below.)\\n separate_chars = '-'\\n if self.literal_block or self.literal:\\n # In monospace-font, we also separate \\\",,\\\", \\\"``\\\" and \\\"''\\\"\\n # and some other characters which can't occur in\\n # non-literal text.\\n separate_chars += ',`\\\\'\\\"<>'\\n # pdflatex does not produce doublequotes for ngerman.\\n text = self.babel.double_quotes_in_tt(text)\\n if self.font_encoding == 'OT1':\\n # We're using OT1 font-encoding and have to replace\\n # underscore by underlined blank, because this has\\n # correct width.\\n text = text.replace('_', '{\\\\\\\\underline{ }}')\\n # And the tt-backslash doesn't work in OT1, so we use\\n # a mirrored slash.\\n text = text.replace('\\\\\\\\textbackslash', '\\\\\\\\reflectbox{/}')\\n else:\\n text = text.replace('_', '{\\\\\\\\_}')\\n else:\\n text = self.babel.quote_quotes(text)\\n text = text.replace(\\\"_\\\", '{\\\\\\\\_}')\\n for char in separate_chars * 2:\\n # Do it twice (\\\"* 2\\\") becaues otherwise we would replace\\n # \\\"---\\\" by \\\"-{}--\\\".\\n text = text.replace(char + char, char + '{}' + char)\\n if self.insert_newline or self.literal_block:\\n # Insert a blank before the newline, to avoid\\n # ! LaTeX Error: There's no line here to end.\\n text = text.replace(\\\"\\\\n\\\", '~\\\\\\\\\\\\\\\\\\\\n')\\n elif self.mbox_newline:\\n if self.literal_block:\\n closings = \\\"}\\\" * len(self.literal_block_stack)\\n openings = \\\"\\\".join(self.literal_block_stack)\\n else:\\n closings = \\\"\\\"\\n openings = \\\"\\\"\\n text = text.replace(\\\"\\\\n\\\", \\\"%s}\\\\\\\\\\\\\\\\\\\\n\\\\\\\\mbox{%s\\\" % (closings,openings))\\n # lines starting with \\\"[\\\" give errors.\\n text = text.replace('[', '{[}')\\n if self.insert_none_breaking_blanks:\\n text = text.replace(' ', '~')\\n if self.latex_encoding != 'utf8':\\n text = self.unicode_to_latex(text)\\n return text\",\n \"def escape_control_characters(text: str, keep_spacing=True) -> str:\\n if not isinstance(text, str):\\n raise ValueError(\\\"text type must be unicode but is {}\\\".format(type(text).__name__))\\n\\n trans = _control_char_trans_newline if keep_spacing else _control_char_trans\\n return text.translate(trans)\",\n \"def arthur(self):\\n\\t\\tthismsg = \\\"\\\\r\\\\n\\\"+self.ESC+\\\"34m\\\"+self.A220+self.ESC+\\\"1;44m\\\"+self.A176+self.ESC+\\\"0;34m\\\"+self.A220+self.A223+self.A176+self.ESC+\\\"C\\\"+self.A178+self.A176+self.A254+self.ESC+\\\"2C\\\"+self.A220+self.A254+self.ESC+\\\"6C\\\"+self.A220+self.A178+self.ESC+\\\"C\\\"+self.A220+self.A178+self.ESC+\\\"C\\\"+self.ESC+\\\"1;44m\\\"+self.A177+self.ESC+\\\"40m\\\"+self.A223+self.ESC+\\\"0;34m\\\"+self.A223+self.ESC+\\\"1m\\\"+self.A223+self.A223+self.ESC+\\\"0;34m\\\"+self.A223+self.ESC+\\\"1m\\\"+self.A223+self.ESC+\\\"0;34m\\\"+self.A223+self.A223+self.A223+self.A223+self.ESC+\\\"1m\\\"+self.A223+self.ESC+\\\"0;34m\\\"+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.A223+self.ESC+\\\"C\\\"+self.A223+\\\"\\\\r\\\\n\\\"\\n\\t\\tthismsg += self.ESC+\\\"C\\\"+self.A223+self.ESC+\\\"2C\\\"+self.A176+self.A223+self.A223+self.ESC+\\\"1;37m\\\"+self.A220+self.A220+self.A220+self.A220+self.ESC+\\\"0m\\\"+self.A220+self.ESC+\\\"1m\\\"+self.A223+self.A223+self.ESC+\\\"0m\\\"+self.A223+self.ESC+\\\"1m\\\"+self.A223+self.A223+self.ESC+\\\"0m\\\"+self.A223+self.ESC+\\\"1m\\\"+self.A223+self.A220+self.ESC+\\\"0m\\\"+self.A220+self.A220+self.A220+self.A220+self.ESC+\\\"C\\\"+self.ESC+\\\"34m\\\"+self.A223+self.ESC+\\\"3C\\\"+self.ESC+\\\"1;37mSaga\\\"+self.ESC+\\\"Cof\\\"+self.ESC+\\\"Cthe\\\"+self.ESC+\\\"CRed\\\"+self.ESC+\\\"CDragon\\\"+self.ESC+\\\"C-\\\"+self.ESC+\\\"C\\\"+self.ESC+\\\"34mKing\\\"+self.ESC+\\\"CArthurs\\\"+self.ESC+\\\"CWeapons \\\"+self.ESC+\\\"C\\\"+self.ESC+\\\"0;34m\\\"+self.A219+\\\"\\\\r\\\\n\\\"\\n\\t\\tthismsg += self.A223+self.ESC+\\\"1;37m\\\"+self.A220+self.A223+self.A223+self.A223+self.A223+self.A223+self.ESC+\\\"C\\\"+self.ESC+\\\"0m\\\"+self.A220+self.A220+self.A220+self.A220+self.A220+self.A219+self.A219+self.A219+self.ESC+\\\"30;47m\\\"+self.A223+self.ESC+\\\"37;40m\\\"+self.A219+self.A220+self.A220+self.A220+self.A220+self.A220+self.ESC+\\\"C\\\"+self.A223+self.ESC+\\\"1;30m\\\"+self.A223+self.ESC+\\\"0m\\\"+self.A223+self.ESC+\\\"1;30m\\\"+self.A223+self.A223+self.A220+self.ESC+\\\"4C\\\"+self.ESC+\\\"0;34m\\\"+self.A220+self.A220+self.A220+self.A220+self.ESC+\\\"C\\\"+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.ESC+\\\"C\\\"+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A220+self.A178+self.A220+self.A220+self.A220+self.A220+self.ESC+\\\"C\\\"+self.A220+self.A220+\\\"\\\\r\\\\n\\\"\\n\\t\\tthismsg += self.ESC+\\\"A\\\"+self.ESC+\\\"79C\\\"+self.ESC+\\\"37m \\\"+self.ESC+\\\"1m\\\"+self.A219+self.ESC+\\\"C\\\"+self.A220+self.ESC+\\\"47m\\\"+self.A219+self.A219+self.A223+self.A178+self.A177+self.A176+self.ESC+\\\"0m\\\"+self.A219+self.A223+self.ESC+\\\"1m\\\"+self.A220+self.ESC+\\\"0m\\\"+self.A223+self.A219+self.A219+self.ESC+\\\"30;47m\\\"+self.A223+self.A176+self.ESC+\\\"37;40m\\\"+self.A219+self.A219+self.A223+self.A220+self.A223+self.A219+self.A219+self.A219+self.A219+self.A219+self.A219+self.A220+self.ESC+\\\"C\\\"+self.ESC+\\\"1;30;47m\\\"+self.A178+self.ESC+\\\"C\\\"+self.ESC+\\\"0;34m\\\"+self.A176+self.ESC+\\\"3C\\\"+self.A178+self.ESC+\\\"20C\\\"+self.A223+self.ESC+\\\"17C\\\"+self.ESC+\\\"1m\\\"+self.A220+self.A220+self.A220+self.A220+\\\"\\\\r\\\\n\\\"\\n\\t\\tthismsg += self.ESC+\\\"A\\\"+self.ESC+\\\"79C\\\"+self.ESC+\\\"0m 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self.ESC+\\\"A\\\"+self.ESC+\\\"79C\\\"+self.ESC+\\\"37m \\\"+self.ESC+\\\"1m\\\"+self.A219+self.ESC+\\\"C\\\"+self.ESC+\\\"47m\\\"+self.A178+self.A178+self.A178+\\\" \\\"+self.ESC+\\\"0;30;47m\\\"+self.A223+self.A177+self.ESC+\\\"37;40m\\\"+self.A219+self.A219+self.A219+self.ESC+\\\"C\\\"+self.ESC+\\\"1m\\\"+self.A219+self.ESC+\\\"C\\\"+self.ESC+\\\"47m\\\"+self.A178+self.ESC+\\\"40m\\\"+self.A220+self.ESC+\\\"C\\\"+self.ESC+\\\"47m\\\"+self.A177+self.A176+\\\" 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self.ESC+\\\"A\\\"+self.ESC+\\\"79C\\\"+self.ESC+\\\"37m \\\"+self.ESC+\\\"C \\\"+self.ESC+\\\"1m\\\"+self.A219+self.ESC+\\\"C\\\"+self.ESC+\\\"47m\\\"+self.A176+\\\" \\\"+self.ESC+\\\"0m\\\"+self.A219+self.A219+self.A223+self.ESC+\\\"33m\\\"+self.A220+self.ESC+\\\"37m\\\"+self.A223+self.ESC+\\\"1m\\\"+self.A220+self.ESC+\\\"47m\\\"+self.A178+self.A178+self.A177+self.ESC+\\\"0m\\\"+self.A220+self.ESC+\\\"1m\\\"+self.A223+self.ESC+\\\"47m\\\"+self.A177+self.A176+self.ESC+\\\"0;30;47m\\\"+self.A176+self.A223+self.ESC+\\\"1m\\\"+self.A176+self.ESC+\\\"0m\\\"+self.A220+self.A223+self.ESC+\\\"33m\\\"+self.A220+self.ESC+\\\"37m\\\"+self.A223+self.A219+self.A219+self.ESC+\\\"1;30;47m\\\"+self.A178+self.ESC+\\\"C\\\"+self.ESC+\\\"40m\\\"+self.A178+self.ESC+\\\"4C\\\"+self.ESC+\\\"0;34masks\\\"+self.ESC+\\\"C\\\\\\\"\\\"+self.ESC+\\\"1mWadaya\\\"+self.ESC+\\\"Cwant\\\"+self.ESC+\\\"Ckid?\\\"+self.ESC+\\\"0;34m\\\\\\\"\\\"+self.ESC+\\\"17C\\\"+self.ESC+\\\"37m 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self.ESC+\\\"A\\\"+self.ESC+\\\"79C\\\"+self.ESC+\\\"37m \\\"+self.ESC+\\\"34m\\\"+self.A178+self.ESC+\\\"C \\\"+self.ESC+\\\"1;37;47m\\\"+self.A177+self.ESC+\\\"2C\\\"+self.ESC+\\\"40m\\\"+self.A223+self.ESC+\\\"33m\\\"+self.A219+self.A220+self.ESC+\\\"0;33m\\\"+self.A178+self.A223+self.ESC+\\\"37m\\\"+self.A220+self.A219+self.A220+self.ESC+\\\"1;47m\\\"+self.A177+self.A176+self.A176+self.ESC+\\\"0m\\\"+self.A219+self.A220+self.ESC+\\\"1m\\\"+self.A223+self.ESC+\\\"0m\\\"+self.A220+self.A220+self.ESC+\\\"1;33m\\\"+self.A223+self.A220+self.A220+self.ESC+\\\"43m\\\"+self.A177+self.ESC+\\\"0;33m\\\"+self.A223+self.ESC+\\\"2C\\\"+self.ESC+\\\"1;30m\\\"+self.A219+self.ESC+\\\"6C\\\"+self.ESC+\\\"0;34m[\\\"+self.ESC+\\\"1mS\\\"+self.ESC+\\\"0;34m]\\\"+self.ESC+\\\"1mell\\\"+self.ESC+\\\"CWeapon\\\"+self.ESC+\\\"29C\\\"+self.ESC+\\\"0;34m\\\"+self.A219+self.ESC+\\\"30;44m\\\"+self.A177+self.ESC+\\\"40m\\\\r\\\\n\\\"\\n\\t\\tthismsg += self.ESC+\\\"A\\\"+self.ESC+\\\"79C\\\"+self.ESC+\\\"37m 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\\\"+self.ESC+\\\"34m\\\"+self.A220+self.ESC+\\\"1;44m\\\"+self.A176+self.ESC+\\\"0;34m\\\"+self.A220+self.ESC+\\\"C\\\"+self.A178+self.A220+self.ESC+\\\"37m\\\"+self.A223+self.A223+self.A220+self.A220+self.ESC+\\\"C\\\"+self.A223+self.A223+self.A223+self.ESC+\\\"1;30;47m\\\"+self.A176+self.A177+self.A219+self.ESC+\\\"40m\\\"+self.A223+self.A223+self.A223+self.ESC+\\\"C\\\"+self.A220+self.A220+self.A223+self.A223+self.ESC+\\\"C\\\"+self.ESC+\\\"0;34m\\\"+self.A220+self.A219+self.A176+self.ESC+\\\"47C\\\"+self.A219+self.ESC+\\\"1;44m\\\"+self.A176+self.ESC+\\\"0;30;44m\\\"+self.A178+self.ESC+\\\"40m\\\\r\\\\n\\\"\\n\\t\\tthismsg += self.ESC+\\\"A\\\"+self.ESC+\\\"79C\\\"+self.ESC+\\\"37m \\\"+self.ESC+\\\"C\\\"+self.ESC+\\\"34m\\\"+self.A223+self.ESC+\\\"C\\\"+self.A220+self.A254+self.A178+self.A219+self.A219+self.A220+self.A220+self.ESC+\\\"37m\\\"+self.A223+self.A223+self.A223+self.A220+self.ESC+\\\"C\\\"+self.ESC+\\\"1;30m\\\"+self.A223+self.ESC+\\\"C\\\"+self.A220+self.A223+self.A223+self.A223+self.ESC+\\\"C\\\"+self.ESC+\\\"0;34m\\\"+self.A176+self.A176+self.A223+self.A178+self.A178+self.A176+self.ESC+\\\"2C\\\"+self.ESC+\\\"1;44m\\\"+self.A176+self.ESC+\\\"0;34m\\\"+self.A223+self.A223+self.A223+self.A178+self.A223+self.A223+self.ESC+\\\"C\\\"+self.A223+self.A178+self.A223+self.ESC+\\\"C\\\"+self.A223+self.A223+self.ESC+\\\"C\\\"+self.A223+self.A176+self.ESC+\\\"C\\\"+self.A223+self.ESC+\\\"C\\\"+self.A223+self.A223+self.ESC+\\\"C\\\"+self.A223+self.A223+self.ESC+\\\"30;44m\\\"+self.A177+self.ESC+\\\"19C\\\"+self.ESC+\\\"34;40m\\\"+self.A223+self.A223+self.A223+self.A223+\\\"\\\\r\\\\n\\\"\\n\\t\\tthismsg += self.ESC+\\\"A\\\"+self.ESC+\\\"79C\\\"+self.ESC+\\\"37m \\\"+self.ESC+\\\"34m\\\"+self.A177+self.A178+self.A219+self.A220+self.ESC+\\\"C\\\"+self.A176+self.A223+self.A178+self.A178+self.A178+self.A178+self.A223+self.A176+self.ESC+\\\"C\\\"+self.ESC+\\\"37m\\\"+self.A223+self.ESC+\\\"1;30m\\\"+self.A220+self.A223+self.ESC+\\\"C\\\"+self.ESC+\\\"0;34m\\\"+self.A223+self.A178+self.A176+self.ESC+\\\"4C\\\"+self.A176+self.ESC+\\\"C\\\"+self.A220+self.A219+self.ESC+\\\"30;44m\\\"+self.A176+\\\" \\\"+self.ESC+\\\"34;40m\\\"+self.A254+self.ESC+\\\"37m \\\"+self.ESC+\\\"34m\\\"+self.A220+self.ESC+\\\"30;44m\\\"+self.A176+self.A178+self.ESC+\\\"34;40m\\\"+self.A219+self.A219+self.A219+self.ESC+\\\"30;44m\\\"+self.A176+self.ESC+\\\"34;40m\\\"+self.A219+self.A220+self.A219+self.A219+self.A219+self.A219+self.A219+self.A222+self.A219+self.A219+\\\"\\\\r\\\\n\\\"\\n\\t\\treturn thismsg\",\n \"def getGraphicsControlExt(duration=0.1):\\n bb = '\\\\x21\\\\xF9\\\\x04'\\n bb += '\\\\x08' # no transparancy\\n bb += intToBin( int(duration*100) ) # in 100th of seconds\\n bb += '\\\\x00' # no transparant color\\n bb += '\\\\x00' # end\\n return bb\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def addch(self, posy, posx, character, color_pair):\\r\\n if posy < 0 or posy > self.height - 1:\\r\\n return\\r\\n if posx < 0 or posx > self.width - 1:\\r\\n return\\r\\n if posx == self.width - 1 and posy == self.height - 1:\\r\\n return\\r\\n self.win.addch(posy, posx, character, color_pair)\",\n \"def add_command(self):\\n self.write(\\\"@SP\\\\nAM=M-1\\\\nD=M\\\\nA=A-1\\\\nM=M+D\\\\n\\\")\",\n \"def draw(self, data):\\n data = data.translate(\\n self.g1_charset if self.charset else self.g0_charset)\\n\\n for char in data:\\n char_width = wcwidth(char)\\n if (self.cursor.x == self.columns and char_width >= 1) \\\\\\n or (self.cursor.x == self.columns - 1 and char_width >= 2):\\n if mo.DECAWM in self.mode:\\n last = self.buffer[self.cursor.y][self.columns - 1]\\n self.buffer[self.cursor.y][self.columns - 1] = \\\\\\n last._replace(linefeed=True)\\n self.dirty.add(self.cursor.y)\\n self.carriage_return()\\n self.linefeed()\\n elif char_width > 0:\\n self.cursor.x -= char_width\\n\\n if mo.IRM in self.mode and char_width > 0:\\n self.insert_characters(char_width)\\n\\n line = self.buffer[self.cursor.y]\\n if char_width == 1:\\n if is_windows and self.cursor.x == self.columns - 1:\\n # always put a linefeed marker when cursor is at the last column\\n line[self.cursor.x] = self.cursor.attrs._replace(data=char, linefeed=True)\\n else:\\n line[self.cursor.x] = self.cursor.attrs._replace(data=char)\\n\\n elif char_width == 2:\\n line[self.cursor.x] = self.cursor.attrs._replace(data=char)\\n if is_windows and self.cursor.x == self.columns - 2:\\n # always put a linefeed marker when the next char is at the last column\\n line[self.cursor.x + 1] = self.cursor.attrs._replace(data=\\\"\\\", linefeed=True)\\n elif self.cursor.x + 1 < self.columns:\\n line[self.cursor.x + 1] = self.cursor.attrs._replace(data=\\\"\\\")\\n\\n elif char_width == 0 and unicodedata.combining(char):\\n # unfornately, sublime text doesn't render decomposed double char correctly\\n pos = None\\n for (row, col) in [\\n (self.cursor.y, self.cursor.x),\\n (self.cursor.y - 1, self.columns)]:\\n if row < 0:\\n continue\\n if col >= 2:\\n last = line[col - 2]\\n if wcswidth(last.data) >= 2:\\n pos = (row, col - 2)\\n break\\n if col >= 1:\\n last = line[col - 1]\\n pos = (row, col - 1)\\n break\\n\\n if pos:\\n normalized = unicodedata.normalize(\\\"NFC\\\", last.data + char)\\n self.buffer[pos[0]][pos[1]] = last._replace(data=normalized)\\n self.dirty.add(pos[0])\\n else:\\n break\\n\\n if char_width > 0:\\n self.cursor.x = min(self.cursor.x + char_width, self.columns)\\n\\n self.dirty.add(self.cursor.y)\",\n \"def addChar (self, c) :\\r\\n # Notice the \\\\n so we can notice when new lines begin\\r\\n if (c=='\\\\n') :\\r\\n self.lineNumber_ += 1\\r\\n self.charNumber_ = 0\\r\\n \\r\\n # Keep the last 1024 or so characters\\r\\n if (self.data_.full()) :\\r\\n self.data_.get()\\r\\n self.data_.put(c)\\r\\n self.charNumber_ += 1\",\n \"def encode(self, text):\\n if self.verbatim:\\n return text\\n # compile the regexps once. do it here so one can see them.\\n #\\n # first the braces.\\n if not self.__dict__.has_key('encode_re_braces'):\\n self.encode_re_braces = re.compile(r'([{}])')\\n text = self.encode_re_braces.sub(r'{\\\\\\\\\\\\1}',text)\\n if not self.__dict__.has_key('encode_re_bslash'):\\n # find backslash: except in the form '{\\\\{}' or '{\\\\}}'.\\n self.encode_re_bslash = re.compile(r'(?<!{)(\\\\\\\\)(?![{}]})')\\n # then the backslash: except in the form from line above:\\n # either '{\\\\{}' or '{\\\\}}'.\\n text = self.encode_re_bslash.sub(r'{\\\\\\\\textbackslash}', text)\\n\\n # then dollar\\n text = text.replace(\\\"$\\\", '{\\\\\\\\$}')\\n # then all that needs math mode\\n text = text.replace(\\\"<\\\", '{$<$}')\\n text = text.replace(\\\">\\\", '{$>$}')\\n # then\\n text = text.replace(\\\"&\\\", '{\\\\\\\\&}')\\n text = text.replace(\\\"_\\\", '{\\\\\\\\_}')\\n # the ^:\\n # * verb|^| does not work in mbox.\\n # * mathmode has wedge. hat{~} would also work.\\n text = text.replace(\\\"^\\\", '{\\\\\\\\ensuremath{^\\\\\\\\wedge}}')\\n text = text.replace(\\\"%\\\", '{\\\\\\\\%}')\\n text = text.replace(\\\"#\\\", '{\\\\\\\\#}')\\n text = text.replace(\\\"~\\\", '{\\\\\\\\~{}}')\\n if self.insert_newline:\\n # HACK: insert a blank before the newline, to avoid \\n # ! LaTeX Error: There's no line here to end.\\n text = text.replace(\\\"\\\\n\\\", '~\\\\\\\\\\\\\\\\\\\\n')\\n elif self.mbox_newline:\\n text = text.replace(\\\"\\\\n\\\", '}\\\\\\\\\\\\\\\\\\\\n\\\\\\\\mbox{')\\n if self.insert_none_breaking_blanks:\\n text = text.replace(' ', '~')\\n # unicode !!! \\n text = text.replace(u'\\\\u2020', '{$\\\\\\\\dagger$}')\\n return text\",\n \"def add_junction(ccTremb):\\n pass\",\n \"def cmd_cb():\\n cmds = []\\n #cmds.append(\\\"r_m[0.0,-1,1]\\\")\\n cmds.append(\\\"r_m[0.0]\\\")\\n cmds.append('r_a[1.7,0,10]')\\n cmds.append('r_n[1.5,0,10]')\\n cmds.append(\\\"r_s[2.5,0,10]\\\")\\n cmds.append('RooCBShape::res(x,r_m,r_s,r_a,r_n)')\\n return cmds\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def update_control(self):\\n self._control_ctr += 0x01\",\n \"def cz(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CZ(), target=[control, target])\",\n \"def _derive_modifiers(self, tx):\\n return [tx + str(pixel) for pixel in self.adjacent_pixels]\",\n \"def addControl(*args):\",\n \"def addControl(*args):\",\n \"def addControl(*args):\",\n \"def addControl(*args):\",\n \"def blueline(self):\\n\\t\\treturn self.ESC+\\\"34m-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-\\\"+self.ESC+\\\"0m\\\\r\\\\n\\\"\",\n \"def wdraw_rotated_text(self, wx, wy, text, angle, color, font):\\r\\n dx, dy = self.w_to_d(wx, wy)\\r\\n self.canvas.create_text(dx, dy, text=text, angle=angle, fill=color, font=font)\",\n \"def gen_c_code(self, comp, dest, jump):\\r\\n return '111' + self.comp(comp) + self.dest(dest) + self.jump(jump)\",\n \"def paint(self):\\r\\n self.win.bkgd(\\\" \\\", COLOR_PAIR[\\\"con_text\\\"])\",\n \"def color_letter(self, letter, lst_labels, plain_text_widget, encrypted_text_widget):\\r\\n new_letter, txt_encryption = self.simulator_enigma.encrypt_letter(letter)\\r\\n lst_encryption_letter_stages = [i[-1] for i in txt_encryption.split(\\\"\\\\n\\\")]\\r\\n lst_encryption_letter_stages.remove(')')\\r\\n self.simulator_encryption.append((txt_encryption, lst_encryption_letter_stages))\\r\\n lst_labels[ord(new_letter) - 65].config(bg=\\\"yellow\\\")\\r\\n lst_labels[ord(new_letter) - 65].after(300, lambda: lst_labels[ord(new_letter) -\\r\\n 65].config(bg=\\\"khaki\\\"))\\r\\n\\r\\n plain_text_widget.config(state=NORMAL)\\r\\n plain_text_widget.insert(END, letter)\\r\\n plain_text_widget.config(state=DISABLED)\\r\\n encrypted_text_widget.config(state=NORMAL)\\r\\n encrypted_text_widget.insert(END, new_letter)\\r\\n encrypted_text_widget.config(state=DISABLED)\",\n \"def append_circuit(self, lines: Tuple[int, int], circuit: ACircuit, content: str) -> None:\",\n \"def cvChin(ctrlName, r=1):\\r\\n # create a simple circle curve:\\r\\n curve = cmds.curve(n=ctrlName, d=3, p=[(0, 0.8*r, -0.5*r), (0, 0.9*r, -0.7*r), (0, 0, -0.5*r), (0, -0.8*r, -0.7*r), (0, -0.8*r, 1.4*r), (0, -0.3*r, 1.3*r), (0, 0, 1.2*r), (0, 0, 0), (0, 0.8*r, -0.3*r), (0, 0.8*r, -0.5*r)] )\\r\\n # rename curveShape:\\r\\n renameShape([curve])\\r\\n return curve\",\n \"def set_crystal(self, file_refl, a_bragg=0.0, thickness=0.1,\\\\\\n tune_auto=0, tune_units=0, tune_ev=0.0, tune_ang=0.0):\\n self.F_CRYSTAL = 1\\n self.FILE_REFL = adjust_shadow_string(file_refl)\\n\\n if a_bragg != 0.0: self.set_asymmetric_cut(a_bragg, thickness)\\n\\n if tune_auto == 0:\\n self.F_CENTRAL = 0\\n else:\\n self.set_auto_tuning(f_phot_cent=tune_units,\\n phot_cent=tune_ev,\\n r_lambda=tune_ang)\",\n \"def __add_credit_cc(self):\\n log.debug(\\\"Displaying __add_credit_cc\\\")\\n # Create a keyboard to be sent later\\n presets = self.cfg.ccard[\\\"payment_presets\\\"]\\n keyboard = [[telegram.KeyboardButton(str(self.Price(preset)))] for preset in presets]\\n keyboard.append([telegram.KeyboardButton(self.loc.get(\\\"menu_all_cancel\\\"))])\\n # Boolean variable to check if the user has cancelled the action\\n cancelled = False\\n # Loop used to continue asking if there's an error during the input\\n while not cancelled:\\n # Send the message and the keyboard\\n self.bot.send_message(self.chat.id, self.loc.get(\\\"payment_cc_amount\\\"),\\n reply_markup=telegram.ReplyKeyboardMarkup(keyboard, one_time_keyboard=True))\\n # Wait until a valid amount is sent\\n selection = self.__wait_for_regex(r\\\"([0-9]+(?:[.,][0-9]+)?|\\\" + self.loc.get(\\\"menu_all_cancel\\\") + r\\\")\\\",\\n cancellable=True)\\n # If the user cancelled the action\\n if isinstance(selection, CancelSignal):\\n # Exit the loop\\n cancelled = True\\n continue\\n # Convert the amount to an integer\\n value = self.Price(selection)\\n # Ensure the amount is within the range\\n if value > self.Price(self.cfg.ccard[\\\"max_amount\\\"]):\\n self.bot.send_message(self.chat.id,\\n self.loc.get(\\\"error_payment_amount_over_max\\\",\\n max_amount=self.Price(self.cfg.ccard[\\\"max_amount\\\"])))\\n continue\\n elif value < self.Price(self.cfg.ccard[\\\"min_amount\\\"]):\\n self.bot.send_message(self.chat.id,\\n self.loc.get(\\\"error_payment_amount_under_min\\\",\\n min_amount=self.Price(self.cfg.ccard[\\\"min_amount\\\"])))\\n continue\\n break\\n # If the user cancelled the action...\\n else:\\n # Exit the function\\n return\\n # Issue the payment invoice\\n self.__make_payment(amount=value)\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def tikzcode(self):\\n tex = \\\"\\\"\\n tex += r\\\"\\\\draw\\\"\\n if len(self.options):\\n options = ', '.join(self.options)\\n tex += \\\"[{options}] \\\".format(options=options)\\n tex += \\\"({a.xpos:.4f},{a.ypos:.4f}) \\\".format(a=self.node_a)\\n tex += \\\"to\\\"\\n # if the nodes are arranged, then they have angle in/out\\n inout = []\\n inout.append('out={angle!s}'.format(angle=self.node_a.angle_inout))\\n inout.append('in={angle!s}'.format(angle=self.node_b.angle_inout))\\n if inout:\\n tex += \\\"[\\\" + \\\", \\\".join(inout) + \\\"] \\\"\\n tex += \\\"({b.xpos:.4f},{b.ypos:.4f})\\\".format(b=self.node_b)\\n tex += \\\";\\\\n\\\"\\n return tex\",\n \"def encrypt(cleartext):\\n base_encode = {'16': base64.b16encode,\\n '32': base64.b32encode, '64': base64.b64encode}\\n ciphertext = cleartext+''\\n\\n for i in range(encrypt_times):\\n base = random.choice(['16', '32', '64'])\\n ciphertext = base_encode[base](ciphertext)\\n\\n return ciphertext\",\n \"def TAY(self, *_):\\n self.reg.Y = self.reg.A\\n self.reg.N = self.reg.Y << 7\\n self.reg.Z = self.reg.Y == 0\",\n \"def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"async def aesthetic(self, ctx, *, text):\\n out = \\\"\\\"\\n for char in text:\\n out += utils.fullwidth_transform.get(char, char)\\n await ctx.send(out)\",\n \"def add(num1, num2, Cin):\\n Cin=0\\n l2=[]\\n final=\\\"\\\"\\n\\n \\\"\\\"\\\"Using for loop for starting addition from the last indexed number\\\"\\\"\\\"\\n for i in range(len(num1)-1,-1,-1):\\n bit1=num1[i]#storing each indexed() value of num1 in bit1\\n bit2=num2[i]#storing each indexed() value of num2 in bit2\\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\\n Cin=Cout#declaring cout as cin for next bit addition\\n l2.append(SUM)#adding SUM to l2\\n l3=l2[::-1]##reversing the value of l2\\n final+=str(l2[-1])#converting the list value to string\\n final1=final[::-1]#reversing string value\\n return final1 #returning the binary addition as string\",\n \"def basic_char_setup( self ):\\n\\t\\tsmall_bar = 3 # number of points per bar\\n\\t\\twide_bar = round(small_bar * 2.25,0) # 2.25 x small_bar\\n\\t\\tdpl = 50 # dots per line 300dpi/6lpi = 50dpl\\n\\t\\tself._nb = bytes( self.owner.PRINTER_ESC +\\n\\t\\t\\t\\t\\t\\t ( '*c%02ia%ib0P' % (small_bar, self.bc_height*dpl) ) + \\n\\t\\t\\t\\t\\t\\t self.owner.PRINTER_ESC + \\n\\t\\t\\t\\t\\t\\t (\\\"*p+%02iX\\\" % small_bar) )\\n\\t\\tself._wb = bytes( self.owner.PRINTER_ESC +\\n\\t\\t\\t\\t\\t\\t ('*c%02ia%ib0P' % (wide_bar, self.bc_height*dpl) )+\\n\\t\\t\\t\\t\\t\\t self.owner.PRINTER_ESC +\\n\\t\\t\\t\\t\\t\\t ('*p+%02iX' % wide_bar ) )\\n\\t\\tself._ns = bytes( self.owner.PRINTER_ESC + ( '*p+%02iX' % small_bar ) )\\n\\t\\tself._ws = bytes( self.owner.PRINTER_ESC + ( '*p+%02iX' % wide_bar ) )\\n \\n\\t\\t# DONE nb = bc39_esc+\\\"*c\\\"+TRANSFORM(small_bar,'99')+\\\"a\\\"+Alltrim(STR(bc39_height*dpl))+\\\"b0P\\\"+bc39_esc+\\\"*p+\\\"+TRANSFORM(small_bar,'99')+\\\"X\\\"\\n\\t\\t# DONE wb = bc39_esc+\\\"*c\\\"+TRANSFORM(wide_bar,'99')+\\\"a\\\"+Alltrim(STR(bc39_height*dpl))+\\\"b0P\\\"+bc39_esc+\\\"*p+\\\"+TRANSFORM(wide_bar,'99')+\\\"X\\\"\\n\\t\\t# DONE ns = bc39_esc+\\\"*p+\\\"+TRANSFORM(small_bar,'99')+\\\"X\\\"\\n\\t\\t# DONE ws = bc39_esc+\\\"*p+\\\"+TRANSFORM(wide_bar,'99')+\\\"X\\\"\\n \\n\\t\\t# adjust cusor position to start at top of line and return to bottom of line\\n\\t\\tself._bc_start = bytes( self.owner.PRINTER_ESC + '*p-50Y' )\\n\\t\\tself._bc_end = bytes( self.owner.PRINTER_ESC + '*p+50Y' )\\n\\t\\t# DONE bc39_start = bc39_esc+\\\"*p-50Y\\\"\\n\\t\\t# DONE bc39_END = bc39_esc+\\\"*p+50Y\\\"\\n\\n\\t\\t# setup the structure allowing to print the code codebar section for various LETTERS\\n\\t\\tself._char39 = { u'1' : 'wb+ns+nb+ws+nb+ns+nb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'2' : 'nb+ns+wb+ws+nb+ns+nb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'3' : 'wb+ns+wb+ws+nb+ns+nb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'4' : 'nb+ns+nb+ws+wb+ns+nb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'5' : 'wb+ns+nb+ws+wb+ns+nb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'6' : 'nb+ns+wb+ws+wb+ns+nb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'7' : 'nb+ns+nb+ws+nb+ns+wb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'8' : 'wb+ns+nb+ws+nb+ns+wb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'9' : 'nb+ns+wb+ws+nb+ns+wb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'0' : 'nb+ns+nb+ws+wb+ns+wb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'A' : 'wb+ns+nb+ns+nb+ws+nb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'B' : 'nb+ns+wb+ns+nb+ws+nb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'C' : 'wb+ns+wb+ns+nb+ws+nb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'D' : 'nb+ns+nb+ns+wb+ws+nb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'E' : 'wb+ns+nb+ns+wb+ws+nb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'F' : 'nb+ns+wb+ns+wb+ws+nb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'G' : 'nb+ns+nb+ns+nb+ws+wb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'H' : 'wb+ns+nb+ns+nb+ws+wb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'I' : 'nb+ns+wb+ns+nb+ws+wb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'J' : 'nb+ns+nb+ns+wb+ws+wb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'K' : 'wb+ns+nb+ns+nb+ns+nb+ws+wb' , \\n\\t\\t\\t\\t\\t\\t u'L' : 'nb+ns+wb+ns+nb+ns+nb+ws+wb' , \\n\\t\\t\\t\\t\\t\\t u'M' : 'wb+ns+wb+ns+nb+ns+nb+ws+nb' , \\n\\t\\t\\t\\t\\t\\t u'N' : 'nb+ns+nb+ns+wb+ns+nb+ws+wb' , \\n\\t\\t\\t\\t\\t\\t u'O' : 'wb+ns+nb+ns+wb+ns+nb+ws+nb' , \\n\\t\\t\\t\\t\\t\\t u'P' : 'nb+ns+wb+ns+wb+ns+nb+ws+nb' , \\n\\t\\t\\t\\t\\t\\t u'Q' : 'nb+ns+nb+ns+nb+ns+wb+ws+wb' , \\n\\t\\t\\t\\t\\t\\t u'R' : 'wb+ns+nb+ns+nb+ns+wb+ws+nb' , \\n\\t\\t\\t\\t\\t\\t u'S' : 'nb+ns+wb+ns+nb+ns+wb+ws+nb' , \\n\\t\\t\\t\\t\\t\\t u'T' : 'nb+ns+nb+ns+wb+ns+wb+ws+nb' , \\n\\t\\t\\t\\t\\t\\t u'U' : 'wb+ws+nb+ns+nb+ns+nb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'V' : 'nb+ws+wb+ns+nb+ns+nb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'W' : 'wb+ws+wb+ns+nb+ns+nb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'X' : 'nb+ws+nb+ns+wb+ns+nb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'Y' : 'wb+ws+nb+ns+wb+ns+nb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'Z' : 'nb+ws+wb+ns+wb+ns+nb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'-' : 'nb+ws+nb+ns+nb+ns+wb+ns+wb' , \\n\\t\\t\\t\\t\\t\\t u'.' : 'wb+ws+nb+ns+nb+ns+wb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u' ' : 'nb+ws+wb+ns+nb+ns+wb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'*' : 'nb+ws+nb+ns+wb+ns+wb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'$' : 'nb+ws+nb+ws+nb+ws+nb+ns+nb' , \\n\\t\\t\\t\\t\\t\\t u'/' : 'nb+ws+nb+ws+nb+ns+nb+ws+nb' , \\n\\t\\t\\t\\t\\t\\t u'+' : 'nb+ws+nb+ns+nb+ws+nb+ws+nb' , \\n\\t\\t\\t\\t\\t\\t u'%' : 'nb+ns+nb+ws+nb+ws+nb+ws+nb' }\",\n \"def add_char(self, coord, char, modify=False):\\n if modify:\\n range_y, range_x = self._map_dims\\n new_coord = [coord[0]+range_y[0]-1, coord[1]+range_x[0]-1]\\n self._screen.addch(new_coord[0], new_coord[1], char)\\n self._screen.refresh()\\n return new_coord\\n else:\\n self._screen.addch(coord[0], coord[1], char)\\n self._screen.refresh()\\n return coord\",\n \"def keypress(self, event):\\n stepsize = 0.15 # pixels, i.e. 0.05 arcsec\\n if event.key == 'right':\\n if self.ccd == 2:\\n self.shift_crpix1 -= stepsize\\n else:\\n self.shift_crpix2 += stepsize\\n elif event.key == 'left':\\n if self.ccd == 2:\\n self.shift_crpix1 += stepsize\\n else:\\n self.shift_crpix2 -= stepsize\\n elif event.key == ']':\\n if self.ccd == 2:\\n self.shift_crpix1 -= 5*stepsize\\n else:\\n self.shift_crpix2 += 5*stepsize\\n elif event.key == '[':\\n if self.ccd == 2:\\n self.shift_crpix1 += 5*stepsize\\n else:\\n self.shift_crpix2 -= 5*stepsize\\n elif event.key == 'up':\\n if self.ccd == 2:\\n self.shift_crpix2 += stepsize\\n else:\\n self.shift_crpix1 += stepsize\\n elif event.key == 'down':\\n if self.ccd == 2:\\n self.shift_crpix2 -= stepsize\\n else:\\n self.shift_crpix1 -= stepsize\\n elif event.key == \\\"'\\\":\\n if self.ccd == 2:\\n self.shift_crpix2 += 5*stepsize\\n else:\\n self.shift_crpix1 += 5*stepsize\\n elif event.key == '/':\\n if self.ccd == 2:\\n self.shift_crpix2 -= 5*stepsize\\n else:\\n self.shift_crpix1 -= 5*stepsize\\n elif event.key == '1':\\n self.shift_cd1_1 += 1e-8\\n elif event.key == '2':\\n self.shift_cd1_1 -= 1e-8\\n elif event.key == '3':\\n self.shift_cd1_2 += 1e-8\\n elif event.key == '4':\\n self.shift_cd1_2 -= 1e-8\\n elif event.key == '5':\\n self.shift_cd2_1 += 1e-8\\n elif event.key == '6':\\n self.shift_cd2_1 -= 1e-8\\n elif event.key == '7':\\n self.shift_cd2_2 += 2e-8\\n elif event.key == '8':\\n self.shift_cd2_2 -= 2e-8\\n elif event.key == 'r': # Reset\\n self.shift_crpix1 = 0.0\\n self.shift_crpix2 = 0.0\\n self.shift_cd1_1 = 0.0\\n self.shift_cd1_2 = 0.0\\n self.shift_cd2_1 = 0.0\\n self.shift_cd2_2 = 0.0\\n elif event.key == 'o': # OK, field does not need fix\\n self.mark_done()\\n elif event.key == 'w': # Write WCS\\n self.write() # Save the results to a csv file\\n self.mark_done()\\n # Now update the plot for the slight change in WCS parameters\\n self.update()\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def gcode_text(self):\\n return os.linesep.join(map(str, self.gcode))\",\n \"def cctw_command(self, mask=False):\\n entry = self.entry.nxname\\n if mask:\\n name = entry + '_masked_transform'\\n else:\\n name = entry + '_transform'\\n dir = os.path.dirname(self.entry['data'].nxsignal.nxfilename)\\n filename = self.entry.nxfilename\\n parfile = os.path.join(dir, entry+'_transform.pars')\\n command = ['cctw transform']\\n command.append(f'--parameters {parfile}')\\n if 'pixel_mask' in self.entry['instrument/detector']:\\n command.append(\\n fr'--mask {filename}\\\\#/{entry}/instrument/detector/pixel_mask')\\n if mask and 'data_mask' in self.entry['data']:\\n command.append(f'--mask3d {filename}\\\\\\\\#/{entry}/data/data_mask')\\n if 'monitor_weight' in self.entry['data']:\\n command.append(\\n fr'--weights {filename}\\\\#/{entry}/data/monitor_weight')\\n if 'polarization' in self.entry['instrument/detector']:\\n command.append(\\n fr'--weights {filename}\\\\#/{entry}'\\n '/instrument/detector/polarization')\\n raw_filename = self.entry['data/data'].nxfilename\\n raw_filepath = self.entry['data/data'].nxfilepath\\n command.append(fr'{raw_filename}\\\\#/{raw_filepath}')\\n command.append(fr'--output {dir}/{name}.nxs\\\\#/entry/data')\\n command.append('--normalization 0')\\n return ' '.join(command)\",\n \"def increase_radius(self, character):\\n character.bombradius += 1\",\n \"def writec(text, color='black', style='normal'):\\n\\n sys.stdout.write(strc(text, color, style))\",\n \"def ch(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_H, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def update(w, g, alpha = 0.03):\\n return w + alpha * g\",\n \"def enable_cl1_direct(self):\\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\\n self.write_versa5(0x18,0x20)\\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\\n self.write_versa5(0x13,0x03) ## Switch to clock\\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew\",\n \"def draw_cat():\\n print '_-_-_-_-_-_-_\\\\n' \\\\\\n '\\\\ /\\\\n' \\\\\\n '| ^_____^ |\\\\n' \\\\\\n '/ (.) (.) \\\\\\\\\\\\n' \\\\\\n '| ( t ) | Miaowww\\\\n' \\\\\\n '\\\\ ==/ /\\\\n' \\\\\\n '| |\\\\n' \\\\\\n '\\\\'\\\"\\\\'\\\"\\\\'\\\"\\\\'\\\"\\\\'\\\"\\\\'\\\"\\\\''\\n\\n print '''\\n_-_-_-_-_-_-_\\n\\\\ /\\n| ^_____^ |\\n/ (.) (.) \\\\\\\\\\n| ( t ) | Miaowww\\n\\\\ ==/ /\\n| |\\n'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'\\n'''\\n\\n print r'_-_-_-_-_-_-_'\\n print r'\\\\ /'\\n print r'| ^_____^ |'\\n print '/ (.) (.) \\\\\\\\'\\n print r'| ( t ) | Miaowww'\\n print r'\\\\ ==/ /'\\n print r'| |'\\n print '\\\\'\\\"\\\\'\\\"\\\\'\\\"\\\\'\\\"\\\\'\\\"\\\\'\\\"\\\\''\\n\\n print \\\"\\\"\\\"\\n_-_-_-_-_-_-_\\n\\\\ /\\n| ^_____^ |\\n/ (.) (.) \\\\\\\\\\n| ( t ) | Miaowww\\n\\\\ ==/ /\\n| |\\n'\\\"'\\\"'\\\"'\\\"'\\\"'\\\"'\\n\\\"\\\"\\\"\",\n \"def cipherFromReflector(self, char):\\n inputCharNum = self.GetNumByChar(char) #Finds the index of the value for the input character to find the internal wiring connection\\n outputChar = self.chrNum(inputCharNum) #Finds the ASCII code of the index value to find the external rotor connection \\n return outputChar #Returns the external character that the wiring is connected to\",\n \"def _text8(self, font, text, x0, y0, color=WHITE, background=BLACK):\\n for char in text:\\n ch = ord(char)\\n if (font.FIRST <= ch < font.LAST\\n and x0+font.WIDTH <= self.width\\n and y0+font.HEIGHT <= self.height):\\n\\n if font.HEIGHT == 8:\\n passes = 1\\n size = 8\\n each = 0\\n else:\\n passes = 2\\n size = 16\\n each = 8\\n\\n for line in range(passes):\\n idx = (ch-font.FIRST)*size+(each*line)\\n buffer = struct.pack(\\n '>64H',\\n color if font.FONT[idx] & _BIT7 else background,\\n color if font.FONT[idx] & _BIT6 else background,\\n color if font.FONT[idx] & _BIT5 else background,\\n color if font.FONT[idx] & _BIT4 else background,\\n color if font.FONT[idx] & _BIT3 else background,\\n color if font.FONT[idx] & _BIT2 else background,\\n color if font.FONT[idx] & _BIT1 else background,\\n color if font.FONT[idx] & _BIT0 else background,\\n color if font.FONT[idx+1] & _BIT7 else background,\\n color if font.FONT[idx+1] & _BIT6 else background,\\n color if font.FONT[idx+1] & _BIT5 else background,\\n color if font.FONT[idx+1] & _BIT4 else background,\\n color if font.FONT[idx+1] & _BIT3 else background,\\n color if font.FONT[idx+1] & _BIT2 else background,\\n color if font.FONT[idx+1] & _BIT1 else background,\\n color if font.FONT[idx+1] & _BIT0 else background,\\n color if font.FONT[idx+2] & _BIT7 else background,\\n color if font.FONT[idx+2] & _BIT6 else background,\\n color if font.FONT[idx+2] & _BIT5 else background,\\n color if font.FONT[idx+2] & _BIT4 else background,\\n color if font.FONT[idx+2] & _BIT3 else background,\\n color if font.FONT[idx+2] & _BIT2 else background,\\n color if font.FONT[idx+2] & _BIT1 else background,\\n color if font.FONT[idx+2] & _BIT0 else background,\\n color if font.FONT[idx+3] & _BIT7 else background,\\n color if font.FONT[idx+3] & _BIT6 else background,\\n color if font.FONT[idx+3] & _BIT5 else background,\\n color if font.FONT[idx+3] & _BIT4 else background,\\n color if font.FONT[idx+3] & _BIT3 else background,\\n color if font.FONT[idx+3] & _BIT2 else background,\\n color if font.FONT[idx+3] & _BIT1 else background,\\n color if font.FONT[idx+3] & _BIT0 else background,\\n color if font.FONT[idx+4] & _BIT7 else background,\\n color if font.FONT[idx+4] & _BIT6 else background,\\n color if font.FONT[idx+4] & _BIT5 else background,\\n color if font.FONT[idx+4] & _BIT4 else background,\\n color if font.FONT[idx+4] & _BIT3 else background,\\n color if font.FONT[idx+4] & _BIT2 else background,\\n color if font.FONT[idx+4] & _BIT1 else background,\\n color if font.FONT[idx+4] & _BIT0 else background,\\n color if font.FONT[idx+5] & _BIT7 else background,\\n color if font.FONT[idx+5] & _BIT6 else background,\\n color if font.FONT[idx+5] & _BIT5 else background,\\n color if font.FONT[idx+5] & _BIT4 else background,\\n color if font.FONT[idx+5] & _BIT3 else background,\\n color if font.FONT[idx+5] & _BIT2 else background,\\n color if font.FONT[idx+5] & _BIT1 else background,\\n color if font.FONT[idx+5] & _BIT0 else background,\\n color if font.FONT[idx+6] & _BIT7 else background,\\n color if font.FONT[idx+6] & _BIT6 else background,\\n color if font.FONT[idx+6] & _BIT5 else background,\\n color if font.FONT[idx+6] & _BIT4 else background,\\n color if font.FONT[idx+6] & _BIT3 else background,\\n color if font.FONT[idx+6] & _BIT2 else background,\\n color if font.FONT[idx+6] & _BIT1 else background,\\n color if font.FONT[idx+6] & _BIT0 else background,\\n color if font.FONT[idx+7] & _BIT7 else background,\\n color if font.FONT[idx+7] & _BIT6 else background,\\n color if font.FONT[idx+7] & _BIT5 else background,\\n color if font.FONT[idx+7] & _BIT4 else background,\\n color if font.FONT[idx+7] & _BIT3 else background,\\n color if font.FONT[idx+7] & _BIT2 else background,\\n color if font.FONT[idx+7] & _BIT1 else background,\\n color if font.FONT[idx+7] & _BIT0 else background\\n )\\n self.blit_buffer(buffer, x0, y0+8*line, 8, 8)\\n\\n x0 += 8\",\n \"def CarryExpression(n, c):\\n combinations = Combinations(n, c)\\n bit_and_list = []\\n for ii in range(len(combinations)):\\n bit_and_list.append('&'.join('a[%d]' % jj for jj in combinations[ii]))\\n carry_expression = '|'.join(bit_and_list)\\n return carry_expression\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5383607","0.53207576","0.523361","0.5175593","0.5152383","0.5134093","0.50781554","0.50374013","0.50269675","0.5018746","0.5007231","0.49872983","0.4968603","0.49366578","0.49154067","0.4913415","0.4904036","0.48859322","0.48642954","0.48608968","0.4823194","0.48041394","0.47934917","0.47675365","0.4764392","0.47469935","0.4736335","0.4711743","0.47007933","0.46969554","0.46892917","0.46833885","0.46717405","0.46582538","0.4656031","0.46527916","0.4643501","0.46424416","0.46379787","0.46370283","0.4635935","0.46323973","0.46309435","0.46299964","0.46171525","0.461368","0.46056035","0.45987973","0.45970577","0.4594562","0.45889935","0.45791456","0.4532386","0.45294183","0.45263004","0.4521067","0.45114428","0.45053577","0.45029742","0.4501257","0.44847825","0.44767722","0.44755235","0.44748256","0.4470399","0.44666776","0.44666776","0.44666776","0.44666776","0.44653714","0.4462128","0.4459306","0.44583777","0.4455269","0.4454549","0.44500294","0.44449645","0.444173","0.44385457","0.44287694","0.44191277","0.44180316","0.4416951","0.4413709","0.441264","0.44078442","0.44054365","0.43993756","0.43871507","0.4375419","0.43641078","0.43615437","0.43610802","0.43598863","0.435569","0.43544662","0.43538505","0.435163","0.43415117","0.43404716"],"string":"[\n \"0.5383607\",\n \"0.53207576\",\n \"0.523361\",\n \"0.5175593\",\n \"0.5152383\",\n \"0.5134093\",\n \"0.50781554\",\n \"0.50374013\",\n \"0.50269675\",\n \"0.5018746\",\n \"0.5007231\",\n \"0.49872983\",\n \"0.4968603\",\n \"0.49366578\",\n \"0.49154067\",\n \"0.4913415\",\n \"0.4904036\",\n \"0.48859322\",\n \"0.48642954\",\n \"0.48608968\",\n \"0.4823194\",\n \"0.48041394\",\n \"0.47934917\",\n \"0.47675365\",\n \"0.4764392\",\n \"0.47469935\",\n \"0.4736335\",\n \"0.4711743\",\n \"0.47007933\",\n \"0.46969554\",\n \"0.46892917\",\n \"0.46833885\",\n \"0.46717405\",\n \"0.46582538\",\n \"0.4656031\",\n \"0.46527916\",\n \"0.4643501\",\n \"0.46424416\",\n \"0.46379787\",\n \"0.46370283\",\n \"0.4635935\",\n \"0.46323973\",\n \"0.46309435\",\n \"0.46299964\",\n \"0.46171525\",\n \"0.461368\",\n \"0.46056035\",\n \"0.45987973\",\n \"0.45970577\",\n \"0.4594562\",\n \"0.45889935\",\n \"0.45791456\",\n \"0.4532386\",\n \"0.45294183\",\n \"0.45263004\",\n \"0.4521067\",\n \"0.45114428\",\n \"0.45053577\",\n \"0.45029742\",\n \"0.4501257\",\n \"0.44847825\",\n \"0.44767722\",\n \"0.44755235\",\n \"0.44748256\",\n \"0.4470399\",\n \"0.44666776\",\n \"0.44666776\",\n \"0.44666776\",\n \"0.44666776\",\n \"0.44653714\",\n \"0.4462128\",\n \"0.4459306\",\n \"0.44583777\",\n \"0.4455269\",\n \"0.4454549\",\n \"0.44500294\",\n \"0.44449645\",\n \"0.444173\",\n \"0.44385457\",\n \"0.44287694\",\n \"0.44191277\",\n \"0.44180316\",\n \"0.4416951\",\n \"0.4413709\",\n \"0.441264\",\n \"0.44078442\",\n \"0.44054365\",\n \"0.43993756\",\n \"0.43871507\",\n \"0.4375419\",\n \"0.43641078\",\n \"0.43615437\",\n \"0.43610802\",\n \"0.43598863\",\n \"0.435569\",\n \"0.43544662\",\n \"0.43538505\",\n \"0.435163\",\n \"0.43415117\",\n \"0.43404716\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.54176253"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81755,"cells":{"query":{"kind":"string","value":"add CRZ gate (controlled RZ gate)."},"document":{"kind":"string","value":"def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def rz(self, phi, q): # pylint: disable=invalid-name\n return self.append(RZGate(phi), [q], [])","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def add_corridor_constraint(self,seg,r,weight=1.0):\n\n constraint_type = \"cylinder\"\n params = dict()\n params['x1'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg],\n self.qr_polytraj.waypoints['y'][0,seg],\n self.qr_polytraj.waypoints['z'][0,seg]])\n params['x2'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg+1],\n self.qr_polytraj.waypoints['y'][0,seg+1],\n self.qr_polytraj.waypoints['z'][0,seg+1]])\n params['der'] = 0\n params['l'] = r # Give the same radius buffer on the end caps\n params['r'] = r\n params['weight'] = weight\n params['keep_out'] = False\n params['active_seg'] = seg\n\n\n self.qr_polytraj.add_constraint(constraint_type,params,dynamic_weighting=False,sum_func=False)","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def test_add(self):\n qc_cal = QuantumCircuit(2)\n qc_cal.rzx(0.5, 0, 1)\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\n\n qc = QuantumCircuit(2) & qc_cal\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\n\n qc = qc_cal & QuantumCircuit(2)\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)","def test_iadd(self):\n qc_cal = QuantumCircuit(2)\n qc_cal.rzx(0.5, 0, 1)\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\n\n qc = QuantumCircuit(2)\n qc &= qc_cal\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)","def rz(self, q0, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_Z, qid=[q0], phase=phase, ctrl=ctrl)\n return self","def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self","def _r_z(angle: tf.Tensor) -> tf.Tensor:\n zero = tf.constant(0, dtype=tf.float64)\n exponent = tf.complex(zero, angle)\n exp = tf.exp(exponent)\n zero_complex = tf.complex(zero, zero)\n one_complex = tf.complex(tf.constant(1, dtype=tf.float64), zero)\n rz = tf.stack([[one_complex, zero_complex], [zero_complex, exp]])\n\n return rz","def Z(self, qubit_expr): \n self.apply_gate_operation('Z', qubit_expr)","def addnewaccl(zs,ze,ez=0.,ap=0.,ax=0.,ay=0.,ox=0.,oy=0.,xw=0.,sw=0.,\n et=0.,ts=0.,dt=0.,\n time=None,data=None,func=None):\n # --- Make sure that at least some of the element is in the proper range,\n # --- z >= 0., and if zlatperi != 0, z <= zlatperi.\n assert (zs < ze),\"element start must be less than element end\"\n assert (top.zlatperi == 0.) or (ze > 0.),\"element end must be greater than zero if top.zlatperi is nonzero\"\n assert (top.zlatperi == 0.) or (zs < top.zlatperi),\"element start must be less than zlatperi if top.zlatperi is nonzero\"\n\n # --- Get a dict of the input arguments and their values.\n ldict = locals()\n\n # --- Setup the lattice arrays for the insertion of the new element. If\n # --- there are already accls, then find the place where the new one is to\n # --- be inserted and shift the existing data to open up a space.\n # --- Note that this uses that same check as in resetlat, that zs != ze to\n # --- determine whether or not a accl is defined.\n ie = 0\n # --- Find which element the new one goes before.\n while (ie <= top.naccl and top.acclzs[ie] <= zs and\n top.acclzs[ie] != top.acclze[ie]):\n ie = ie + 1\n\n # --- Increase the size of the arrays if the element will go past the end\n # --- or if the array is full (i.e. the last element is used).\n if ie > top.naccl or top.acclzs[-1] != top.acclze[-1]:\n top.naccl = top.naccl + 100\n gchange(\"Lattice\")\n if isinstance(et,(ndarray,collections.Sequence)) and len(et)-1 > top.ntaccl:\n top.ntaccl = len(et) - 1\n gchange(\"Lattice\")\n\n # --- Setup dictionary relating lattice array with input argument names.\n # --- This is done here so that the references to the lattice arrays\n # --- refer to the updated memory locations after the gchange.\n edict={'zs':top.acclzs,'ze':top.acclze,'ez':top.acclez,\n 'ap':top.acclap,'ax':top.acclax,'ay':top.acclay,\n 'ox':top.acclox,'oy':top.accloy,'xw':top.acclxw,'sw':top.acclsw,\n 'et':top.acclet,'ts':top.acclts,'dt':top.accldt}\n\n # --- Shift the existing data in the arrays to open up a space for the\n # --- new element.\n if ie <= top.naccl:\n for e in edict.itervalues():\n if len(shape(e)) == 1:\n e[ie+1:] = e[ie:-1] + 0\n else:\n # --- acclet is 2-D\n e[:,ie+1:] = e[:,ie:-1] + 0\n\n # --- Insert the new element. Note that edict correlates the lattice array\n # --- with the input arguments and ldict correlate the arguements with\n # --- their values.\n for (xx,e) in edict.iteritems():\n if len(shape(e)) == 1:\n e[ie] = ldict[xx]\n else:\n # --- acclet is 2-D\n e[:,ie] = ldict[xx]\n\n # --- resetlat must be called before the data can be used\n top.lresetlat = true\n\n if (time is not None and data is not None) or func is not None:\n tdle = TimeDependentLatticeElement('acclez',ie,time,data,func)\n return ie,tdle\n\n return ie","def R_ZigZag(rot):\n\n return Ship(\"R Zig-Zag\",\n rotate_shape([Pos(0,0), Pos(0,1), Pos(1,1), Pos(1,2)], rot))","def test_radd():\n # Test for reverse addition with scalar Rnode object and float value\n x = Rnode(0.11)\n z = 0.5 + x\n z.grad_value = 1.0\n\n try:\n assert z.value == x.value + 0.5\n except AssertionError as e:\n print(e)","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def addZ(self,name):\n return self._addVar(name,self._zNames)","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def ramraddrrst(self):\n return 0","def __radd__(self, other: Any) -> ColumnOperators:\n return self.reverse_operate(add, other)","def test_add_znode(self):\n z = self.test_start_empty()\n self.test_start_one_value(z)","def RZZ(self, theta:Union[int, float], qubit_expr): \n self.apply_gate_operation(RZZ(theta), qubit_expr)","def setRLC(self, r, l, c):\n return","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def _compute_carry_and_output_fused(self, z, c_tm1):\n z0, z1, z2, z3 = z\n i = self.recurrent_activation(z0)\n f = self.recurrent_activation(z1)\n c = f * c_tm1 + i * self.activation(z2)\n o = self.recurrent_activation(z3)\n return c, o","def xewy_plus_z(x, y, z, activation=None):\n R = tf.add(tf.multiply(x, y), z)\n if activation:\n return activation(R)\n else: \n return R","def __radd__(self, other):\n other = _to_complex(other)\n return ComplexVal(other.r + self.r, other.i + self.i)","def Omega_rad_z(self, z):\n return self.Omega_gamma_z(z)+self.Omega_ur_z(z)","def add_road(ccTremb):\n pass","def xzplane(draw, r, y, shift = np.array([1000, 1000, 0, 0]), scale = 300):\n extent = 2.8\n pln = np.array(\n [\n [-extent,y,0],\n [extent,y,0],\n [extent,y,extent*2],\n [-extent,y,extent*2]\n ]\n )\n pln = np.dot(pln, np.transpose(r))\n pln = pln * scale + shift[:3]\n draw.polygon([(pln[0][0],pln[0][1]),(pln[1][0],pln[1][1]),(pln[2][0],pln[2][1]),(pln[3][0],pln[3][1])], (0,102,255,70))","def add(self, y):\n return circuit.add(self, y)","def apply_Rz(psi, theta, i, parametrize=False, **gate_opts):\n mtags = _merge_tags({'RZ'}, gate_opts)\n if parametrize:\n G = ops.PArray(rz_gate_param_gen, (float(theta),))\n else:\n G = qu.Rz(float(theta))\n psi.gate_(G, int(i), tags=mtags, **gate_opts)","def __radd__(self, left):\n return self.value() + left","def compute_CRR(self, FAR):\r\n print('Computing CRR')\r\n return (np.ones((1, len(FAR))) - FAR)[0]","def CR(phi):\n return (np.kron(P0,s0) + np.kron(P1,R(phi)))","def _zadd(self, key, pk, ts=None, ttl=None):\n return self.r.eval(self.LUA_ZADD, 1, key, ts or self._time(), pk)","def cr(self, x, y, z, k):\n\n if k == 0:\n cr_eq = \"maT*exp(-((x-mxT)**2+(y-myT)**2+(z-mzT)**2)/(2*msT**2))\"\n elif k == 1:\n cr_eq = \"1/sqrt((x-mxT)**2+(y-myT)**2+(z-mzT)**2)\"\n elif k == 1.5:\n cr_eq = \"1/sqrt((x-mxT)**2+(y-myT)**2+(z-mzT)**2)**1.5\"\n elif k == 2:\n cr_eq = \"1/((x-mxT)**2+(y-myT)**2+(z-mzT)**2)\"\n\n me = ne.evaluate(cr_eq,\n local_dict={'x': x,\n 'y': y,\n 'z': z,\n 'mxT': self.mxT,\n 'myT': self.myT,\n 'mzT': self.mzT,\n 'msT': self.msT,\n 'maT': self.maT})\n\n mesum = np.sum(me, axis=0)\n cr = me/mesum\n return cr","def ROL(self, value):\n carry = value << 7\n result = ((value << 1) & 0b11111110) | self.reg.C\n self.reg.C = carry\n self.reg.N = result >> 7\n self.reg.Z = result == 0\n return result","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def keyZ(self):\n if pyxel.btnp(pyxel.KEY_Z):\n self.rotater(1)","def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]","def increase_right_boundary(self):\n self.R = self.R + 1.0\n self.Ne = self.Ne + 1","def add_neurone(self, couche, nbr=1):\n if self.control == 0:\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\n self.couche[couche] += nbr\n else:\n print(\"Le réseau est deja créé, vous en pouvez plus le modifier\")","def compute_z_curr(Z_opt, z_prev1, z_diff, alpha):\r\n z_curr = alpha * Z_opt + (1 - alpha) * (z_prev1 + z_diff)\r\n return z_curr","def addThreeNodesRig(self):\r\n cam = self.nativePointer()\r\n\r\n # create controls\r\n pos = mxs.star(radius1 = 6.5, radius2 = 5.5, points=16)\r\n trans = mxs.rectangle(length=10.2, width=4.5)\r\n rot = mxs.ngon(radius=2.0, nSides=3, corner_radius=0.5)\r\n\r\n # rename controls\r\n pos.name = str(cam.name) + 'position'\r\n trans.name = str(cam.name) + 'translation'\r\n rot.name = str(cam.name) + 'rotation'\r\n\r\n # rotate controls into place\r\n pos.rotation = mxs.eulerangles(90, 0 , 0)\r\n trans.rotation = mxs.eulerangles(90, 0 , 0)\r\n rot.rotation = mxs.eulerangles(0, 0, -90)\r\n\r\n # reset xforms\r\n mxs.resetxform(pos)\r\n mxs.resetxform(trans)\r\n mxs.resetxform(rot)\r\n\r\n # collapse xforms\r\n mxs.maxOps.CollapseNode(pos, True)\r\n mxs.maxOps.CollapseNode(trans, True)\r\n mxs.maxOps.CollapseNode(rot, True)\r\n\r\n rot.parent = trans\r\n trans.parent = pos\r\n\r\n pos.wirecolor = rot.wirecolor = trans.wirecolor = mxs.color(0, 230, 250)\r\n\r\n # Move the rig to align with the cam\r\n pivrot=cam.rotation\r\n pos.rotation*=pivrot;\r\n #pos.objectoffsetrot*=pivrot;\r\n #pos.objectoffsetpos*=pivrot;\r\n\r\n pos.position = cam.position\r\n #mxs.resetxform(pos)\r\n #pos.rotation = cam.rotation\r\n\r\n\r\n # parent the cam to to rig\r\n cam.parent = rot\r\n\r\n return True","def compute_Ar(self, r, z, qOc):\n\n kz_cross_z = einsum('z, p -> zp', self.kz, z)\n kr_cross_r = einsum('r, p -> rp', self.kr, r)\n delta_r = np.ones(np.size(r))*self.ptcl_width_r\n delta_u = einsum('r, p -> rp', self.kr, delta_r)\n j1 = self.convolved_j1(kr_cross_r, delta_u)\n convolved_sin = einsum('zp, z -> zp', sin(kz_cross_z), self.shape_function_z)\n\n modeQr = self.omegaOtwokz * (self.dc_coords[:,:,1] - self.omega_coords[:,:,1])\n\n self.tanhz = -np.tanh(((z - self.z_mean) ** 2 - self.z_mean ** 2) * self.tanh_width ** 2)\n # We dress the charge instead of the fields proper\n dressed_charge = self.tanhz*qOc\n\n\n Ar = einsum('zr, rp, zp -> p', modeQr, j1, convolved_sin)*dressed_charge\n\n return Ar","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def _write_circuit(self, feature_vector_index):\n # grab the feature vector\n feature_vector = self.data.data[feature_vector_index]\n\n # compute the indices to put gates at\n inds = [x for x in range(len(feature_vector)) if feature_vector[x] == 1]\n\n # write the circuit\n self.circuits[feature_vector_index].add_layer(H)\n self.circuits[feature_vector_index].add_at(Z, inds)\n\n # TODO: all encoding classes will need this method.\n # TODO: make a BaseEncoding that implements this","def __radd__(self, other):\n return self + other","def __radd__(self, other):\n return self + other","def add_ROCR(self, timeperiod=10,\n type='line', color='tertiary', **kwargs):\n\n if not self.has_close:\n raise Exception()\n\n utils.kwargs_check(kwargs, VALID_TA_KWARGS)\n if 'kind' in kwargs:\n type = kwargs['kind']\n\n name = 'ROCR({})'.format(str(timeperiod))\n self.sec[name] = dict(type=type, color=color)\n self.ind[name] = talib.ROCR(self.df[self.cl].values,\n timeperiod)","def test_special_ZYZ(self, angexp):\n a, b, c, d = angexp[0]\n exp = {(\"rz\", \"ry\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\n tgt = np.exp(1j * d) * RZGate(b).to_matrix() @ RYGate(a).to_matrix() @ RZGate(c).to_matrix()\n self.check_oneq_special_cases(tgt, \"ZYZ\", exp)","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def Z_high(C, R_L, f):\n return Xcap(C,f) + R_L","def compute_Az(self, r, z, qOc):\n\n kr_cross_r = einsum('r, p -> rp', self.kr, r)\n kz_cross_z = einsum('z, p -> zp', self.kz, z)\n delta_r = np.ones(np.size(r)) * self.ptcl_width_r\n delta_u = einsum('r, p -> rp', self.kr, delta_r)\n convolved_j0 = self.convolved_j0(kr_cross_r, delta_u)\n convolved_cos = einsum('zp, z -> zp', cos(kz_cross_z), self.shape_function_z)\n\n modeQz = self.omegaOtwokr * (self.dc_coords[:,:,1] + self.omega_coords[:,:,1])\n\n self.tanhz = -np.tanh(((z - self.z_mean) ** 2 - self.z_mean ** 2) * self.tanh_width ** 2)\n # We dress the charge instead of the fields proper\n dressed_charge = self.tanhz*qOc\n\n Az = einsum('zr, rp, zp -> p', modeQz, convolved_j0, convolved_cos)*dressed_charge\n\n return Az","def rotateZ(self, *args, **kwargs):\n ...","def __radd__(self, other):\n return self.runtime.add(self, other)","def z_rec_EH(self):\n # Approximation for drag epoch redshift\n om_m = self.omega_m-np.sum(self.omega_nu)\n om_b = self.omega_b\n g1 = 0.0783*om_b**-0.238/(1.+39.5*om_b**0.763)\n g2 = 0.560/(1+21.1*om_b**1.81)\n z_r = 1048*(1+0.00124*om_b**-0.738)*(1+g1*om_m**g2)\n return z_r","def RCL(self, loc):\n cmd = f\"*RCL {loc}\"\n self.instr.write(cmd)","def rz(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\n return self.rotate(rz=angle, center=center)","def plus(self, layer):\n\n input1 = self.node(layer)\n if not input1:\n return\n LOGGER.debug('Plus layer to last:%s', layer)\n if not self.last_node:\n self.last_node = nuke.nodes.Constant()\n\n if layer not in self.layers():\n input1 = nuke.nodes.Shuffle(inputs=[input1], out=layer)\n self.last_node = nuke.nodes.Merge2(\n inputs=[self.last_node, input1], operation='plus',\n also_merge=layer if layer not in self.layers() else 'none',\n label=utf8(self.l10n(layer)),\n output='rgb')","def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])","def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def RZ(rotRadian: float):\n return np.array([\n [np.cos(rotRadian), -np.sin(rotRadian), 0],\n [np.sin(rotRadian), np.cos(rotRadian), 0],\n [0, 0, 1]\n ])","def CZ(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CZ, qubit_expr)","def test_special_ZXZ(self, angexp):\n a, b, c, d = angexp[0]\n exp = {(\"rz\", \"rx\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\n tgt = np.exp(1j * d) * RZGate(b).to_matrix() @ RXGate(a).to_matrix() @ RZGate(c).to_matrix()\n self.check_oneq_special_cases(tgt, \"ZXZ\", exp)","def read_carry(self):\n return self.CARRY","def R_op(self, inputs, eval_points):\r\n raise NotImplementedError(\r\n \"%s of class %s does not \"\r\n \"implement R_op. If this is a theano op, write to the \"\r\n \"theano-dev mailing list for assistance. If it is your \"\r\n \"own op, implement the R_op method.\" %\r\n (self, self.__class__.__name__))","def circuit():\n np.random.seed(1967)\n for gates in gates_per_layers:\n for gate in gates:\n qml.apply(gate)\n return qml.expval(qml.PauliZ(0))","def __radd__(self, other):\n if other == 0:\n return self\n else:\n return self.__add__(other)","def __radd__(self, other):\n if other == 0:\n return self\n else:\n return self.__add__(other)","def __rshift__(self, other: Any) -> ColumnOperators:\n return self.operate(rshift, other)","def gate2zx(box):\n if isinstance(box, (Bra, Ket)):\n dom, cod = (1, 0) if isinstance(box, Bra) else (0, 1)\n return Id(0).tensor(*[\n X(dom, cod, phase=.5 * bit) for bit in box.bitstring])\n if isinstance(box, (Rz, Rx)):\n return (Z if isinstance(box, Rz) else X)(1, 1, box.phase)\n if isinstance(box, CRz):\n return Z(1, 2) @ Z(1, 2, box.phase)\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\n if isinstance(box, CRx):\n return X(1, 2) @ X(1, 2, box.phase)\\\n >> Id(1) @ (Z(2, 1) >> X(1, 0, -box.phase)) @ Id(1)\n if isinstance(box, quantum.CU1):\n return Z(1, 2, box.phase) @ Z(1, 2, box.phase)\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\n standard_gates = {\n quantum.H: H,\n quantum.Z: Z(1, 1, .5),\n quantum.X: X(1, 1, .5),\n quantum.Y: Y(1, 1, .5),\n CZ: Z(1, 2) @ Id(1) >> Id(1) @ Had() @ Id(1) >> Id(1) @ Z(2, 1),\n CX: Z(1, 2) @ Id(1) >> Id(1) @ X(2, 1)}\n return standard_gates[box]","def __radd__(self,that):\n return self.__opExpand2(that,np.add)","def incr_circuit_remix_count(self, circuit_id):\n key = ':'.join(\n [CIRCUIT_NMBR_RMX_1, \n str(circuit_id), \n CIRCUIT_NMBR_RMX_2]\n )\n self.RS.incr(key)","def MiyamotoNagaiAccel(self, M, rd, r):\n R = np.sqrt(r[0]**2 + r[1]**2) #Finding magnitude of x and y compnets\n zd = rd/5. #Calculating \"zd\"\n B = rd + np.sqrt(r[2]**2 + zd**2) #Calclating \"B\"\n zstuff = 1/np.sqrt(r[2]**2 + zd**2) #Calculating stuff that only appears in z componet\n MNa = -self.G*M/(R**2+B**2)**1.5 * r * np.array([1,1,zstuff]) #Putting it all together\n\n return MNa","def __init__(self,x_c,z_c,cyl_rad):\n self.x_c = x_c\n self.z_c = z_c\n self.cyl_rad = cyl_rad","def __init__(self,x_c,z_c,cyl_rad):\n self.x_c = x_c\n self.z_c = z_c\n self.cyl_rad = cyl_rad","def __init__(self,x_c,z_c,cyl_rad):\n self.x_c = x_c\n self.z_c = z_c\n self.cyl_rad = cyl_rad","def __init__(self,x_c,z_c,cyl_rad):\n self.x_c = x_c\n self.z_c = z_c\n self.cyl_rad = cyl_rad","def __init__(self,x_c,z_c,cyl_rad):\n self.x_c = x_c\n self.z_c = z_c\n self.cyl_rad = cyl_rad","def __radd__(self, other):\n return self.__add__(other)","def __radd__(self, other):\n return self.__add__(other)","def __radd__(self, other):\n return self.__add__(other)","def __radd__(self, other):\n return self.__add__(other)","def __radd__(self, other):\n return self.__add__(other)","def __radd__(self, other):\n return self.__add__(other)","def __radd__(self, other):\n return self.__add__(other)","def ryrz_decomposer(gate: OneQubitGate) -> List[Union[RYGate, RZGate]]:\n mat = gate.matrix()\n assert mat.shape == (2, 2)\n assert check_unitarity(mat)\n gamma = cmath.phase(mat[0, 0])\n mat *= cmath.exp(-1j * gamma)\n assert abs(mat[0, 0].imag) < 1e-8\n cos_halftheta = mat[0, 0].real\n sin_halftheta = 1.0 - cos_halftheta ** 2\n try:\n theta = math.acos(cos_halftheta) * 2\n except ValueError: # math domain error\n assert abs(abs(cos_halftheta) - 1.0) < 1e-8\n if cos_halftheta > 0:\n theta = 0.0\n else:\n theta = math.pi\n if abs(sin_halftheta) < 1e-8:\n phi = 0.0\n lam = cmath.phase(mat[1, 1])\n else:\n phi = cmath.phase(mat[1, 0])\n lam = cmath.phase(mat[0, 1])\n if theta < 1e-8:\n return [RZGate(gate.targets, lam + phi)]\n gates = []\n if lam > 1e-8:\n gates.append(RZGate(gate.targets, lam))\n gates.append(RYGate(gate.targets, theta))\n if phi > 1e-8:\n gates.append(RZGate(gate.targets, phi))\n return gates","def L_ZigZag(rot):\n\n return Ship(\"L Zig-Zag\",\n rotate_shape([Pos(0,0), Pos(0,1), Pos(-1,1), Pos(-1,2)], rot))","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def ccNew(self, cs, ta, qa, z, m):\n\t\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0","def __radd__(self, other):\n\n return self.__add__(other)","def xform_Z_rot( self , thetaZrad ):\r\n self.xform_homog( homogeneous_Z( thetaZrad , [ 0 , 0 , 0 ] ) )","def __radd__(self, other: t.Any) -> InspectableSet[_C]:\n return self._op_copy('__radd__', other)","def Rgb_add(c1,c2):\n r = c1.r + c2.r\n r = max(0, min(1, r))\n\n g = c1.g + c2.g\n g = max(0, min(1, g))\n\n b = c1.b + c2.b\n b = max(0, min(1, b))\n return Rgb(r,g,b)","def Z_bandpass(C, L, R_L, f):\n return 1/(1/Xind(L, f) + 1/Xcap(C, f) + 1/R_L)"],"string":"[\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def rz(self, phi, q): # pylint: disable=invalid-name\\n return self.append(RZGate(phi), [q], [])\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def cxr(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def add_corridor_constraint(self,seg,r,weight=1.0):\\n\\n constraint_type = \\\"cylinder\\\"\\n params = dict()\\n params['x1'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg],\\n self.qr_polytraj.waypoints['y'][0,seg],\\n self.qr_polytraj.waypoints['z'][0,seg]])\\n params['x2'] = np.array([ self.qr_polytraj.waypoints['x'][0,seg+1],\\n self.qr_polytraj.waypoints['y'][0,seg+1],\\n self.qr_polytraj.waypoints['z'][0,seg+1]])\\n params['der'] = 0\\n params['l'] = r # Give the same radius buffer on the end caps\\n params['r'] = r\\n params['weight'] = weight\\n params['keep_out'] = False\\n params['active_seg'] = seg\\n\\n\\n self.qr_polytraj.add_constraint(constraint_type,params,dynamic_weighting=False,sum_func=False)\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def test_add(self):\\n qc_cal = QuantumCircuit(2)\\n qc_cal.rzx(0.5, 0, 1)\\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\\n\\n qc = QuantumCircuit(2) & qc_cal\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\\n\\n qc = qc_cal & QuantumCircuit(2)\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\",\n \"def test_iadd(self):\\n qc_cal = QuantumCircuit(2)\\n qc_cal.rzx(0.5, 0, 1)\\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\\n\\n qc = QuantumCircuit(2)\\n qc &= qc_cal\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\",\n \"def rz(self, q0, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=ROTATION_Z, qid=[q0], phase=phase, ctrl=ctrl)\\n return self\",\n \"def cxr_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def _r_z(angle: tf.Tensor) -> tf.Tensor:\\n zero = tf.constant(0, dtype=tf.float64)\\n exponent = tf.complex(zero, angle)\\n exp = tf.exp(exponent)\\n zero_complex = tf.complex(zero, zero)\\n one_complex = tf.complex(tf.constant(1, dtype=tf.float64), zero)\\n rz = tf.stack([[one_complex, zero_complex], [zero_complex, exp]])\\n\\n return rz\",\n \"def Z(self, qubit_expr): \\n self.apply_gate_operation('Z', qubit_expr)\",\n \"def addnewaccl(zs,ze,ez=0.,ap=0.,ax=0.,ay=0.,ox=0.,oy=0.,xw=0.,sw=0.,\\n et=0.,ts=0.,dt=0.,\\n time=None,data=None,func=None):\\n # --- Make sure that at least some of the element is in the proper range,\\n # --- z >= 0., and if zlatperi != 0, z <= zlatperi.\\n assert (zs < ze),\\\"element start must be less than element end\\\"\\n assert (top.zlatperi == 0.) or (ze > 0.),\\\"element end must be greater than zero if top.zlatperi is nonzero\\\"\\n assert (top.zlatperi == 0.) or (zs < top.zlatperi),\\\"element start must be less than zlatperi if top.zlatperi is nonzero\\\"\\n\\n # --- Get a dict of the input arguments and their values.\\n ldict = locals()\\n\\n # --- Setup the lattice arrays for the insertion of the new element. If\\n # --- there are already accls, then find the place where the new one is to\\n # --- be inserted and shift the existing data to open up a space.\\n # --- Note that this uses that same check as in resetlat, that zs != ze to\\n # --- determine whether or not a accl is defined.\\n ie = 0\\n # --- Find which element the new one goes before.\\n while (ie <= top.naccl and top.acclzs[ie] <= zs and\\n top.acclzs[ie] != top.acclze[ie]):\\n ie = ie + 1\\n\\n # --- Increase the size of the arrays if the element will go past the end\\n # --- or if the array is full (i.e. the last element is used).\\n if ie > top.naccl or top.acclzs[-1] != top.acclze[-1]:\\n top.naccl = top.naccl + 100\\n gchange(\\\"Lattice\\\")\\n if isinstance(et,(ndarray,collections.Sequence)) and len(et)-1 > top.ntaccl:\\n top.ntaccl = len(et) - 1\\n gchange(\\\"Lattice\\\")\\n\\n # --- Setup dictionary relating lattice array with input argument names.\\n # --- This is done here so that the references to the lattice arrays\\n # --- refer to the updated memory locations after the gchange.\\n edict={'zs':top.acclzs,'ze':top.acclze,'ez':top.acclez,\\n 'ap':top.acclap,'ax':top.acclax,'ay':top.acclay,\\n 'ox':top.acclox,'oy':top.accloy,'xw':top.acclxw,'sw':top.acclsw,\\n 'et':top.acclet,'ts':top.acclts,'dt':top.accldt}\\n\\n # --- Shift the existing data in the arrays to open up a space for the\\n # --- new element.\\n if ie <= top.naccl:\\n for e in edict.itervalues():\\n if len(shape(e)) == 1:\\n e[ie+1:] = e[ie:-1] + 0\\n else:\\n # --- acclet is 2-D\\n e[:,ie+1:] = e[:,ie:-1] + 0\\n\\n # --- Insert the new element. Note that edict correlates the lattice array\\n # --- with the input arguments and ldict correlate the arguements with\\n # --- their values.\\n for (xx,e) in edict.iteritems():\\n if len(shape(e)) == 1:\\n e[ie] = ldict[xx]\\n else:\\n # --- acclet is 2-D\\n e[:,ie] = ldict[xx]\\n\\n # --- resetlat must be called before the data can be used\\n top.lresetlat = true\\n\\n if (time is not None and data is not None) or func is not None:\\n tdle = TimeDependentLatticeElement('acclez',ie,time,data,func)\\n return ie,tdle\\n\\n return ie\",\n \"def R_ZigZag(rot):\\n\\n return Ship(\\\"R Zig-Zag\\\",\\n rotate_shape([Pos(0,0), Pos(0,1), Pos(1,1), Pos(1,2)], rot))\",\n \"def test_radd():\\n # Test for reverse addition with scalar Rnode object and float value\\n x = Rnode(0.11)\\n z = 0.5 + x\\n z.grad_value = 1.0\\n\\n try:\\n assert z.value == x.value + 0.5\\n except AssertionError as e:\\n print(e)\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def addZ(self,name):\\n return self._addVar(name,self._zNames)\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def ramraddrrst(self):\\n return 0\",\n \"def __radd__(self, other: Any) -> ColumnOperators:\\n return self.reverse_operate(add, other)\",\n \"def test_add_znode(self):\\n z = self.test_start_empty()\\n self.test_start_one_value(z)\",\n \"def RZZ(self, theta:Union[int, float], qubit_expr): \\n self.apply_gate_operation(RZZ(theta), qubit_expr)\",\n \"def setRLC(self, r, l, c):\\n return\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def _compute_carry_and_output_fused(self, z, c_tm1):\\n z0, z1, z2, z3 = z\\n i = self.recurrent_activation(z0)\\n f = self.recurrent_activation(z1)\\n c = f * c_tm1 + i * self.activation(z2)\\n o = self.recurrent_activation(z3)\\n return c, o\",\n \"def xewy_plus_z(x, y, z, activation=None):\\n R = tf.add(tf.multiply(x, y), z)\\n if activation:\\n return activation(R)\\n else: \\n return R\",\n \"def __radd__(self, other):\\n other = _to_complex(other)\\n return ComplexVal(other.r + self.r, other.i + self.i)\",\n \"def Omega_rad_z(self, z):\\n return self.Omega_gamma_z(z)+self.Omega_ur_z(z)\",\n \"def add_road(ccTremb):\\n pass\",\n \"def xzplane(draw, r, y, shift = np.array([1000, 1000, 0, 0]), scale = 300):\\n extent = 2.8\\n pln = np.array(\\n [\\n [-extent,y,0],\\n [extent,y,0],\\n [extent,y,extent*2],\\n [-extent,y,extent*2]\\n ]\\n )\\n pln = np.dot(pln, np.transpose(r))\\n pln = pln * scale + shift[:3]\\n draw.polygon([(pln[0][0],pln[0][1]),(pln[1][0],pln[1][1]),(pln[2][0],pln[2][1]),(pln[3][0],pln[3][1])], (0,102,255,70))\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def apply_Rz(psi, theta, i, parametrize=False, **gate_opts):\\n mtags = _merge_tags({'RZ'}, gate_opts)\\n if parametrize:\\n G = ops.PArray(rz_gate_param_gen, (float(theta),))\\n else:\\n G = qu.Rz(float(theta))\\n psi.gate_(G, int(i), tags=mtags, **gate_opts)\",\n \"def __radd__(self, left):\\n return self.value() + left\",\n \"def compute_CRR(self, FAR):\\r\\n print('Computing CRR')\\r\\n return (np.ones((1, len(FAR))) - FAR)[0]\",\n \"def CR(phi):\\n return (np.kron(P0,s0) + np.kron(P1,R(phi)))\",\n \"def _zadd(self, key, pk, ts=None, ttl=None):\\n return self.r.eval(self.LUA_ZADD, 1, key, ts or self._time(), pk)\",\n \"def cr(self, x, y, z, k):\\n\\n if k == 0:\\n cr_eq = \\\"maT*exp(-((x-mxT)**2+(y-myT)**2+(z-mzT)**2)/(2*msT**2))\\\"\\n elif k == 1:\\n cr_eq = \\\"1/sqrt((x-mxT)**2+(y-myT)**2+(z-mzT)**2)\\\"\\n elif k == 1.5:\\n cr_eq = \\\"1/sqrt((x-mxT)**2+(y-myT)**2+(z-mzT)**2)**1.5\\\"\\n elif k == 2:\\n cr_eq = \\\"1/((x-mxT)**2+(y-myT)**2+(z-mzT)**2)\\\"\\n\\n me = ne.evaluate(cr_eq,\\n local_dict={'x': x,\\n 'y': y,\\n 'z': z,\\n 'mxT': self.mxT,\\n 'myT': self.myT,\\n 'mzT': self.mzT,\\n 'msT': self.msT,\\n 'maT': self.maT})\\n\\n mesum = np.sum(me, axis=0)\\n cr = me/mesum\\n return cr\",\n \"def ROL(self, value):\\n carry = value << 7\\n result = ((value << 1) & 0b11111110) | self.reg.C\\n self.reg.C = carry\\n self.reg.N = result >> 7\\n self.reg.Z = result == 0\\n return result\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def keyZ(self):\\n if pyxel.btnp(pyxel.KEY_Z):\\n self.rotater(1)\",\n \"def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]\",\n \"def increase_right_boundary(self):\\n self.R = self.R + 1.0\\n self.Ne = self.Ne + 1\",\n \"def add_neurone(self, couche, nbr=1):\\n if self.control == 0:\\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\\n self.couche[couche] += nbr\\n else:\\n print(\\\"Le réseau est deja créé, vous en pouvez plus le modifier\\\")\",\n \"def compute_z_curr(Z_opt, z_prev1, z_diff, alpha):\\r\\n z_curr = alpha * Z_opt + (1 - alpha) * (z_prev1 + z_diff)\\r\\n return z_curr\",\n \"def addThreeNodesRig(self):\\r\\n cam = self.nativePointer()\\r\\n\\r\\n # create controls\\r\\n pos = mxs.star(radius1 = 6.5, radius2 = 5.5, points=16)\\r\\n trans = mxs.rectangle(length=10.2, width=4.5)\\r\\n rot = mxs.ngon(radius=2.0, nSides=3, corner_radius=0.5)\\r\\n\\r\\n # rename controls\\r\\n pos.name = str(cam.name) + 'position'\\r\\n trans.name = str(cam.name) + 'translation'\\r\\n rot.name = str(cam.name) + 'rotation'\\r\\n\\r\\n # rotate controls into place\\r\\n pos.rotation = mxs.eulerangles(90, 0 , 0)\\r\\n trans.rotation = mxs.eulerangles(90, 0 , 0)\\r\\n rot.rotation = mxs.eulerangles(0, 0, -90)\\r\\n\\r\\n # reset xforms\\r\\n mxs.resetxform(pos)\\r\\n mxs.resetxform(trans)\\r\\n mxs.resetxform(rot)\\r\\n\\r\\n # collapse xforms\\r\\n mxs.maxOps.CollapseNode(pos, True)\\r\\n mxs.maxOps.CollapseNode(trans, True)\\r\\n mxs.maxOps.CollapseNode(rot, True)\\r\\n\\r\\n rot.parent = trans\\r\\n trans.parent = pos\\r\\n\\r\\n pos.wirecolor = rot.wirecolor = trans.wirecolor = mxs.color(0, 230, 250)\\r\\n\\r\\n # Move the rig to align with the cam\\r\\n pivrot=cam.rotation\\r\\n pos.rotation*=pivrot;\\r\\n #pos.objectoffsetrot*=pivrot;\\r\\n #pos.objectoffsetpos*=pivrot;\\r\\n\\r\\n pos.position = cam.position\\r\\n #mxs.resetxform(pos)\\r\\n #pos.rotation = cam.rotation\\r\\n\\r\\n\\r\\n # parent the cam to to rig\\r\\n cam.parent = rot\\r\\n\\r\\n return True\",\n \"def compute_Ar(self, r, z, qOc):\\n\\n kz_cross_z = einsum('z, p -> zp', self.kz, z)\\n kr_cross_r = einsum('r, p -> rp', self.kr, r)\\n delta_r = np.ones(np.size(r))*self.ptcl_width_r\\n delta_u = einsum('r, p -> rp', self.kr, delta_r)\\n j1 = self.convolved_j1(kr_cross_r, delta_u)\\n convolved_sin = einsum('zp, z -> zp', sin(kz_cross_z), self.shape_function_z)\\n\\n modeQr = self.omegaOtwokz * (self.dc_coords[:,:,1] - self.omega_coords[:,:,1])\\n\\n self.tanhz = -np.tanh(((z - self.z_mean) ** 2 - self.z_mean ** 2) * self.tanh_width ** 2)\\n # We dress the charge instead of the fields proper\\n dressed_charge = self.tanhz*qOc\\n\\n\\n Ar = einsum('zr, rp, zp -> p', modeQr, j1, convolved_sin)*dressed_charge\\n\\n return Ar\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def _write_circuit(self, feature_vector_index):\\n # grab the feature vector\\n feature_vector = self.data.data[feature_vector_index]\\n\\n # compute the indices to put gates at\\n inds = [x for x in range(len(feature_vector)) if feature_vector[x] == 1]\\n\\n # write the circuit\\n self.circuits[feature_vector_index].add_layer(H)\\n self.circuits[feature_vector_index].add_at(Z, inds)\\n\\n # TODO: all encoding classes will need this method.\\n # TODO: make a BaseEncoding that implements this\",\n \"def __radd__(self, other):\\n return self + other\",\n \"def __radd__(self, other):\\n return self + other\",\n \"def add_ROCR(self, timeperiod=10,\\n type='line', color='tertiary', **kwargs):\\n\\n if not self.has_close:\\n raise Exception()\\n\\n utils.kwargs_check(kwargs, VALID_TA_KWARGS)\\n if 'kind' in kwargs:\\n type = kwargs['kind']\\n\\n name = 'ROCR({})'.format(str(timeperiod))\\n self.sec[name] = dict(type=type, color=color)\\n self.ind[name] = talib.ROCR(self.df[self.cl].values,\\n timeperiod)\",\n \"def test_special_ZYZ(self, angexp):\\n a, b, c, d = angexp[0]\\n exp = {(\\\"rz\\\", \\\"ry\\\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\\n tgt = np.exp(1j * d) * RZGate(b).to_matrix() @ RYGate(a).to_matrix() @ RZGate(c).to_matrix()\\n self.check_oneq_special_cases(tgt, \\\"ZYZ\\\", exp)\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def Z_high(C, R_L, f):\\n return Xcap(C,f) + R_L\",\n \"def compute_Az(self, r, z, qOc):\\n\\n kr_cross_r = einsum('r, p -> rp', self.kr, r)\\n kz_cross_z = einsum('z, p -> zp', self.kz, z)\\n delta_r = np.ones(np.size(r)) * self.ptcl_width_r\\n delta_u = einsum('r, p -> rp', self.kr, delta_r)\\n convolved_j0 = self.convolved_j0(kr_cross_r, delta_u)\\n convolved_cos = einsum('zp, z -> zp', cos(kz_cross_z), self.shape_function_z)\\n\\n modeQz = self.omegaOtwokr * (self.dc_coords[:,:,1] + self.omega_coords[:,:,1])\\n\\n self.tanhz = -np.tanh(((z - self.z_mean) ** 2 - self.z_mean ** 2) * self.tanh_width ** 2)\\n # We dress the charge instead of the fields proper\\n dressed_charge = self.tanhz*qOc\\n\\n Az = einsum('zr, rp, zp -> p', modeQz, convolved_j0, convolved_cos)*dressed_charge\\n\\n return Az\",\n \"def rotateZ(self, *args, **kwargs):\\n ...\",\n \"def __radd__(self, other):\\n return self.runtime.add(self, other)\",\n \"def z_rec_EH(self):\\n # Approximation for drag epoch redshift\\n om_m = self.omega_m-np.sum(self.omega_nu)\\n om_b = self.omega_b\\n g1 = 0.0783*om_b**-0.238/(1.+39.5*om_b**0.763)\\n g2 = 0.560/(1+21.1*om_b**1.81)\\n z_r = 1048*(1+0.00124*om_b**-0.738)*(1+g1*om_m**g2)\\n return z_r\",\n \"def RCL(self, loc):\\n cmd = f\\\"*RCL {loc}\\\"\\n self.instr.write(cmd)\",\n \"def rz(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Component':\\n return self.rotate(rz=angle, center=center)\",\n \"def plus(self, layer):\\n\\n input1 = self.node(layer)\\n if not input1:\\n return\\n LOGGER.debug('Plus layer to last:%s', layer)\\n if not self.last_node:\\n self.last_node = nuke.nodes.Constant()\\n\\n if layer not in self.layers():\\n input1 = nuke.nodes.Shuffle(inputs=[input1], out=layer)\\n self.last_node = nuke.nodes.Merge2(\\n inputs=[self.last_node, input1], operation='plus',\\n also_merge=layer if layer not in self.layers() else 'none',\\n label=utf8(self.l10n(layer)),\\n output='rgb')\",\n \"def cz(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CZ(), target=[control, target])\",\n \"def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def RZ(rotRadian: float):\\n return np.array([\\n [np.cos(rotRadian), -np.sin(rotRadian), 0],\\n [np.sin(rotRadian), np.cos(rotRadian), 0],\\n [0, 0, 1]\\n ])\",\n \"def CZ(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.CZ, qubit_expr)\",\n \"def test_special_ZXZ(self, angexp):\\n a, b, c, d = angexp[0]\\n exp = {(\\\"rz\\\", \\\"rx\\\")[g]: angexp[1][g] for g in (0, 1) if angexp[1][g]}\\n tgt = np.exp(1j * d) * RZGate(b).to_matrix() @ RXGate(a).to_matrix() @ RZGate(c).to_matrix()\\n self.check_oneq_special_cases(tgt, \\\"ZXZ\\\", exp)\",\n \"def read_carry(self):\\n return self.CARRY\",\n \"def R_op(self, inputs, eval_points):\\r\\n raise NotImplementedError(\\r\\n \\\"%s of class %s does not \\\"\\r\\n \\\"implement R_op. If this is a theano op, write to the \\\"\\r\\n \\\"theano-dev mailing list for assistance. If it is your \\\"\\r\\n \\\"own op, implement the R_op method.\\\" %\\r\\n (self, self.__class__.__name__))\",\n \"def circuit():\\n np.random.seed(1967)\\n for gates in gates_per_layers:\\n for gate in gates:\\n qml.apply(gate)\\n return qml.expval(qml.PauliZ(0))\",\n \"def __radd__(self, other):\\n if other == 0:\\n return self\\n else:\\n return self.__add__(other)\",\n \"def __radd__(self, other):\\n if other == 0:\\n return self\\n else:\\n return self.__add__(other)\",\n \"def __rshift__(self, other: Any) -> ColumnOperators:\\n return self.operate(rshift, other)\",\n \"def gate2zx(box):\\n if isinstance(box, (Bra, Ket)):\\n dom, cod = (1, 0) if isinstance(box, Bra) else (0, 1)\\n return Id(0).tensor(*[\\n X(dom, cod, phase=.5 * bit) for bit in box.bitstring])\\n if isinstance(box, (Rz, Rx)):\\n return (Z if isinstance(box, Rz) else X)(1, 1, box.phase)\\n if isinstance(box, CRz):\\n return Z(1, 2) @ Z(1, 2, box.phase)\\\\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\\n if isinstance(box, CRx):\\n return X(1, 2) @ X(1, 2, box.phase)\\\\\\n >> Id(1) @ (Z(2, 1) >> X(1, 0, -box.phase)) @ Id(1)\\n if isinstance(box, quantum.CU1):\\n return Z(1, 2, box.phase) @ Z(1, 2, box.phase)\\\\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\\n standard_gates = {\\n quantum.H: H,\\n quantum.Z: Z(1, 1, .5),\\n quantum.X: X(1, 1, .5),\\n quantum.Y: Y(1, 1, .5),\\n CZ: Z(1, 2) @ Id(1) >> Id(1) @ Had() @ Id(1) >> Id(1) @ Z(2, 1),\\n CX: Z(1, 2) @ Id(1) >> Id(1) @ X(2, 1)}\\n return standard_gates[box]\",\n \"def __radd__(self,that):\\n return self.__opExpand2(that,np.add)\",\n \"def incr_circuit_remix_count(self, circuit_id):\\n key = ':'.join(\\n [CIRCUIT_NMBR_RMX_1, \\n str(circuit_id), \\n CIRCUIT_NMBR_RMX_2]\\n )\\n self.RS.incr(key)\",\n \"def MiyamotoNagaiAccel(self, M, rd, r):\\n R = np.sqrt(r[0]**2 + r[1]**2) #Finding magnitude of x and y compnets\\n zd = rd/5. #Calculating \\\"zd\\\"\\n B = rd + np.sqrt(r[2]**2 + zd**2) #Calclating \\\"B\\\"\\n zstuff = 1/np.sqrt(r[2]**2 + zd**2) #Calculating stuff that only appears in z componet\\n MNa = -self.G*M/(R**2+B**2)**1.5 * r * np.array([1,1,zstuff]) #Putting it all together\\n\\n return MNa\",\n \"def __init__(self,x_c,z_c,cyl_rad):\\n self.x_c = x_c\\n self.z_c = z_c\\n self.cyl_rad = cyl_rad\",\n \"def __init__(self,x_c,z_c,cyl_rad):\\n self.x_c = x_c\\n self.z_c = z_c\\n self.cyl_rad = cyl_rad\",\n \"def __init__(self,x_c,z_c,cyl_rad):\\n self.x_c = x_c\\n self.z_c = z_c\\n self.cyl_rad = cyl_rad\",\n \"def __init__(self,x_c,z_c,cyl_rad):\\n self.x_c = x_c\\n self.z_c = z_c\\n self.cyl_rad = cyl_rad\",\n \"def __init__(self,x_c,z_c,cyl_rad):\\n self.x_c = x_c\\n self.z_c = z_c\\n self.cyl_rad = cyl_rad\",\n \"def __radd__(self, other):\\n return self.__add__(other)\",\n \"def __radd__(self, other):\\n return self.__add__(other)\",\n \"def __radd__(self, other):\\n return self.__add__(other)\",\n \"def __radd__(self, other):\\n return self.__add__(other)\",\n \"def __radd__(self, other):\\n return self.__add__(other)\",\n \"def __radd__(self, other):\\n return self.__add__(other)\",\n \"def __radd__(self, other):\\n return self.__add__(other)\",\n \"def ryrz_decomposer(gate: OneQubitGate) -> List[Union[RYGate, RZGate]]:\\n mat = gate.matrix()\\n assert mat.shape == (2, 2)\\n assert check_unitarity(mat)\\n gamma = cmath.phase(mat[0, 0])\\n mat *= cmath.exp(-1j * gamma)\\n assert abs(mat[0, 0].imag) < 1e-8\\n cos_halftheta = mat[0, 0].real\\n sin_halftheta = 1.0 - cos_halftheta ** 2\\n try:\\n theta = math.acos(cos_halftheta) * 2\\n except ValueError: # math domain error\\n assert abs(abs(cos_halftheta) - 1.0) < 1e-8\\n if cos_halftheta > 0:\\n theta = 0.0\\n else:\\n theta = math.pi\\n if abs(sin_halftheta) < 1e-8:\\n phi = 0.0\\n lam = cmath.phase(mat[1, 1])\\n else:\\n phi = cmath.phase(mat[1, 0])\\n lam = cmath.phase(mat[0, 1])\\n if theta < 1e-8:\\n return [RZGate(gate.targets, lam + phi)]\\n gates = []\\n if lam > 1e-8:\\n gates.append(RZGate(gate.targets, lam))\\n gates.append(RYGate(gate.targets, theta))\\n if phi > 1e-8:\\n gates.append(RZGate(gate.targets, phi))\\n return gates\",\n \"def L_ZigZag(rot):\\n\\n return Ship(\\\"L Zig-Zag\\\",\\n rotate_shape([Pos(0,0), Pos(0,1), Pos(-1,1), Pos(-1,2)], rot))\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def ccNew(self, cs, ta, qa, z, m):\\n\\t\\treturn self.cmNew(cs, ta, qa) + self.f_c(z, m)*self.C0\",\n \"def __radd__(self, other):\\n\\n return self.__add__(other)\",\n \"def xform_Z_rot( self , thetaZrad ):\\r\\n self.xform_homog( homogeneous_Z( thetaZrad , [ 0 , 0 , 0 ] ) )\",\n \"def __radd__(self, other: t.Any) -> InspectableSet[_C]:\\n return self._op_copy('__radd__', other)\",\n \"def Rgb_add(c1,c2):\\n r = c1.r + c2.r\\n r = max(0, min(1, r))\\n\\n g = c1.g + c2.g\\n g = max(0, min(1, g))\\n\\n b = c1.b + c2.b\\n b = max(0, min(1, b))\\n return Rgb(r,g,b)\",\n \"def Z_bandpass(C, L, R_L, f):\\n return 1/(1/Xind(L, f) + 1/Xcap(C, f) + 1/R_L)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6958848","0.61419284","0.6064584","0.56396747","0.5535329","0.5404921","0.5390143","0.53515494","0.5310394","0.52780074","0.5277078","0.5226025","0.5192308","0.5169303","0.5124667","0.5121535","0.5059638","0.5004625","0.4980288","0.49734604","0.49685302","0.49619305","0.49591866","0.49554476","0.4940226","0.4939979","0.49140128","0.48604304","0.4853728","0.48525372","0.48105377","0.47789901","0.4772763","0.4768502","0.47517192","0.4747804","0.47284153","0.4726921","0.4704824","0.4695906","0.4690964","0.46853676","0.4672385","0.46718022","0.4670453","0.46670988","0.46648774","0.463921","0.46362442","0.46293703","0.462875","0.46279216","0.46279216","0.4623888","0.46169174","0.46092904","0.46081424","0.4607649","0.46064448","0.4603356","0.4598935","0.4592849","0.45919698","0.45918056","0.45782888","0.4562928","0.45589614","0.4553349","0.4552684","0.45484146","0.45450303","0.45403233","0.45400986","0.45400986","0.45329818","0.45292476","0.4528141","0.45184994","0.45164716","0.4514154","0.4514154","0.4514154","0.4514154","0.4514154","0.45070645","0.45070645","0.45070645","0.45070645","0.45070645","0.45070645","0.45070645","0.4505582","0.44968358","0.44962606","0.44962606","0.44936958","0.4483902","0.44797146","0.44785246","0.44733125"],"string":"[\n \"0.6958848\",\n \"0.61419284\",\n \"0.6064584\",\n \"0.56396747\",\n \"0.5535329\",\n \"0.5404921\",\n \"0.5390143\",\n \"0.53515494\",\n \"0.5310394\",\n \"0.52780074\",\n \"0.5277078\",\n \"0.5226025\",\n \"0.5192308\",\n \"0.5169303\",\n \"0.5124667\",\n \"0.5121535\",\n \"0.5059638\",\n \"0.5004625\",\n \"0.4980288\",\n \"0.49734604\",\n \"0.49685302\",\n \"0.49619305\",\n \"0.49591866\",\n \"0.49554476\",\n \"0.4940226\",\n \"0.4939979\",\n \"0.49140128\",\n \"0.48604304\",\n \"0.4853728\",\n \"0.48525372\",\n \"0.48105377\",\n \"0.47789901\",\n \"0.4772763\",\n \"0.4768502\",\n \"0.47517192\",\n \"0.4747804\",\n \"0.47284153\",\n \"0.4726921\",\n \"0.4704824\",\n \"0.4695906\",\n \"0.4690964\",\n \"0.46853676\",\n \"0.4672385\",\n \"0.46718022\",\n \"0.4670453\",\n \"0.46670988\",\n \"0.46648774\",\n \"0.463921\",\n \"0.46362442\",\n \"0.46293703\",\n \"0.462875\",\n \"0.46279216\",\n \"0.46279216\",\n \"0.4623888\",\n \"0.46169174\",\n \"0.46092904\",\n \"0.46081424\",\n \"0.4607649\",\n \"0.46064448\",\n \"0.4603356\",\n \"0.4598935\",\n \"0.4592849\",\n \"0.45919698\",\n \"0.45918056\",\n \"0.45782888\",\n \"0.4562928\",\n \"0.45589614\",\n \"0.4553349\",\n \"0.4552684\",\n \"0.45484146\",\n \"0.45450303\",\n \"0.45403233\",\n \"0.45400986\",\n \"0.45400986\",\n \"0.45329818\",\n \"0.45292476\",\n \"0.4528141\",\n \"0.45184994\",\n \"0.45164716\",\n \"0.4514154\",\n \"0.4514154\",\n \"0.4514154\",\n \"0.4514154\",\n \"0.4514154\",\n \"0.45070645\",\n \"0.45070645\",\n \"0.45070645\",\n \"0.45070645\",\n \"0.45070645\",\n \"0.45070645\",\n \"0.45070645\",\n \"0.4505582\",\n \"0.44968358\",\n \"0.44962606\",\n \"0.44962606\",\n \"0.44936958\",\n \"0.4483902\",\n \"0.44797146\",\n \"0.44785246\",\n \"0.44733125\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.66018766"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81756,"cells":{"query":{"kind":"string","value":"add CU1 gate (controlled U1 gate)."},"document":{"kind":"string","value":"def cu1(self, q0, q1, alpha=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U1, qid=[q0,q1], phase=alpha, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\n return self","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def I1_u1(self) -> complex:\n # Should match in amplitude with \"Phase 1 current [A]\"\n # Convert from relative to U12 -> relative to U1\n return - (self.I1_u12() * cmath.rect(1, 150 / 180 * cmath.pi))","def _action_op_u1(self, plaq):\n # if self.link_type == 'U1':\n # return np.cos(plaq)\n return tf.math.cos(plaq)","def test_special_U1X(self):\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \"U1X\", {})\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \"U1X\", {\"u1\": 1})\n self.check_oneq_special_cases(\n U3Gate(-np.pi / 2, 0.2, 0.0).to_matrix(), \"U1X\", {\"u1\": 2, \"rx\": 1}\n )\n self.check_oneq_special_cases(\n U3Gate(np.pi / 2, 0.0, 0.21).to_matrix(), \"U1X\", {\"u1\": 2, \"rx\": 1}\n )\n self.check_oneq_special_cases(\n U3Gate(np.pi / 2, 0.12, 0.2).to_matrix(), \"U1X\", {\"u1\": 2, \"rx\": 1}\n )\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \"U1X\", {\"u1\": 3, \"rx\": 2})","def u1(self, q0, alpha=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_U1, qid=[q0], phase=alpha, ctrl=ctrl)\n return self","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def enable_cl1_direct(self):\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\n self.write_versa5(0x18,0x20)\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\n self.write_versa5(0x13,0x03) ## Switch to clock\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def server1_add1(c1, c2, pub):\n return add1 (c1, c2, pub)","def ControlledU(U):\n\n d = U.rank // 2 + 1\n shape = [2] * 2 * d\n t = np.zeros(shape, dtype=np.complex128)\n\n # If the first bit is zero, fill in as the identity operator.\n t[:, 0, ...] = Identity(d)[:, 0, ...]\n # Else, fill in as Identity tensored with U (Identity for the first bit,\n # which remains unchanged.\n t[:, 1, ...] = (Identity() * U)[:, 1, ...]\n return Operator(t)","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def _add_grover_step_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n _add_2_bit_oracle_without_ancilla_1_0(qc, register) # Oracle\n add_grover_reflection_no_ancilla(qc, register) # Reflection","def build_gate_1(gate, tags=None):\n\n def apply_constant_single_qubit_gate(psi, i, **gate_opts):\n mtags = _merge_tags(tags, gate_opts)\n psi.gate_(gate, int(i), tags=mtags, **gate_opts)\n\n return apply_constant_single_qubit_gate","def enable_cl1_pll1(self):\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\n self.write_versa5(0x18,0x20)\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\n self.write_versa5(0x13,0x03) ## Switch to clock\n self.write_versa5(0x10,0x40) ## Enable clock input only, won't lock to master","def _add_grover_step_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n _add_2_bit_oracle_with_ancilla_1_0(qc, register, ancilla) # Oracle\n add_grover_reflection_no_ancilla(qc, register) # Reflection","def c1(self):\n return self.__c1","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def acumula_x1(self, x1, rodada):\n self.x1[rodada].append(x1)","def __init__(self, input0, input1, output) :\n Gate.__init__(self, [input0,input1], output)","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def add_neurone(self, couche, nbr=1):\n if self.control == 0:\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\n self.couche[couche] += nbr\n else:\n print(\"Le réseau est deja créé, vous en pouvez plus le modifier\")","def disable_cl1(self):\n self.write_versa5(0x10,0xc4) ## Enable xtal and clock\n self.write_versa5(0x21,0x81) ## Use and enable divider\n self.write_versa5(0x13,0x00) ## Use CL1 input instead of xtal\n self.write_versa5(0x10,0x80) ## Enable xtal input only\n self.write_versa5(0x17,0x04) ## Change top multiplier to 0x44\n self.write_versa5(0x18,0x40)","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def I1_u12(self) -> complex:\n return (self.S1_u12() / self.U12()).conjugate()","def add_grover_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n # Mark states with a 1 at a later determined position by flipping their amplitude\n qc.x(ancilla)\n qc.h(ancilla)\n # Mix input states\n qc.h(register)\n # Execute Grover iteration just once\n _add_grover_step_with_ancilla_1_0(qc, register, ancilla)","def acumula_n1(self, n1, rodada):\n self.n1[rodada].append(n1)","def NUT1(self,NUT1b,n=2.0):\n if self.tipo == 'contra':\n return n*NUT1b\n if self.tipo == 'paralelo':\n return n*NUT1b\n if self.tipo == 'misto':\n return n*NUT1b","def calc_c1(self):\n dc1hw_s = self.src_shape[0]\n _, d_d, h_d, w_d, _ = self.dst_shape\n c_1 = dc1hw_s // (d_d * h_d * w_d)\n return c_1","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def bias_add_v1(value, bias, name=None):\n with ops.name_scope(name, \"BiasAddV1\", [value, bias]) as name:\n value = ops.convert_to_tensor(value, name=\"input\")\n bias = ops.convert_to_tensor(bias, dtype=value.dtype, name=\"bias\")\n return gen_nn_ops.bias_add_v1(value, bias, name=name)","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def actual_causation():\n # fmt: off\n tpm = np.array([\n [1, 0, 0, 0],\n [0, 1, 0, 0],\n [0, 1, 0, 0],\n [0, 0, 0, 1],\n ])\n cm = np.array([\n [1, 1],\n [1, 1],\n ])\n # fmt: on\n return Network(tpm, cm, node_labels=('OR', 'AND'))","def p1(self, p1):\n p0 = self.p0\n u = self.p1 - p0\n v = p1 - p0\n\n scale, rM = self.scale_rot_matrix(u, v)\n self.c = p0 + rM @ (self.c - p0)\n self.r *= scale\n self.r2 = self.r * self.r\n dp = p0 - self.c\n self.a0 = atan2(dp.y, dp.x)","def test_add_consistency1(self) -> None:\n a = Constant(\n 'const1',\n Float32(),\n np.zeros([1, 3, 3])\n )\n b = Constant(\n 'const2',\n Float32(),\n np.zeros([3])\n )\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\n Add(\n 'add1',\n [1, 3, 3],\n Float32(),\n input_ops\n )\n\n print(\"Consistency test for 'Add' #1 passed!\")","def _define(self):\n from qiskit.extensions.standard.u1 import U1Gate\n definition = []\n q = QuantumRegister(1, \"q\")\n rule = [\n (U1Gate(self.params[0]), [q[0]], [])\n ]\n for inst in rule:\n definition.append(inst)\n self.definition = definition","def S1_u12(self) -> complex:\n return complex(\n self._addr(self.defined_registers['Phase 1 power [W]']['addr']),\n self._addr(self.defined_registers['Phase 1 volt amps reactive [VAr]']['addr']),\n )","def cu3(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U3, qid=[q0,q1], phase=alpha, phase1=beta,\n phase2=gamma, ctrl=ctrl)\n return self","def add_grover_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.h(register) # Mix states initially\n _add_grover_step_without_ancilla_1_0(qc, register) # Repeat Grover iteration just once","def ch(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_H, qid=[q0,q1], ctrl=ctrl)\n return self","def add(self, y):\n return circuit.add(self, y)","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def acumula_ns1(self, ns1, rodada):\n self.ns1[rodada].append(ns1)","def bias_add(in_tensor0, in_tensor1):\n dim_map = {}\n dim_map[\"out_img_shape\"] = te_util.shape_to_list(in_tensor0.shape)\n NAME_INDEX[0] += 1\n\n with tvm.tag_scope('conv_vector_bias_add'):\n c_add_vector = tvm.compute(\n dim_map[\"out_img_shape\"],\n lambda *indice: in_tensor0(*indice) + in_tensor1(indice[\n 1] * CUBE_MKN[in_tensor0.dtype]['mac'][2] + indice[3]),\n name='bias_add_vector' + \"_cc_\" + str(NAME_INDEX[0]))\n return c_add_vector","def glucose_c1(self, g_t, t_G, a_G, d_g_t=0):\n return -(1/t_G)*g_t+(a_G/t_G)*d_g_t","def Controlled2(U):\n '''Generalized controlled unitary tensor construction\n Parameters:\n -----------\n U: input tensor which is assumed to be a square Matrix\n\n Returns:\n --------\n Controlled unitary\n\n '''\n shp = U.shape\n new_ten = scipy.linalg.block_diag(np.eye(*shp), U)\n return new_ten.reshape(2, shp[0], 2, shp[1], 2, shp[2])","def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self","def x_add_one(nom):\n\tif 'X' in nom and '*' not in nom:\n\t\treturn nom.replace('X', '1*X')\n\treturn nom","def add_one(x):\n return x + 1","def Bn1(self,phi0=0):\n\t\treturn self.x[1,:]*_np.sin(self.phi0)+self.x[2,:]*_np.cos(self.phi0)","def acumula_t1(self, t1, rodada):\n self.t1[rodada].append(t1)","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def b1relu( regularizers, x):\n N, M, F = x.get_shape()\n b = _bias_variable(regularizers,[1, 1, int(F)], regularization=True)\n return tf.nn.relu(x + b)","def AssignAddHybrid1d(output, value, target=utils.CCE):\n for i in range(output.shape[0]):\n output[i] = output[i] + value[i]\n\n return output","def calcT1(g2, g1):\n idop = FermiOp(g2.orbs, 3, 3)\n idop.data = np.eye(int(binom(g2.orbs, 3)))\n\n return p2N(g2, 3) - p2N(g1, 3) + idop","def add(num1, num2, Cin):\n Cin=0\n l2=[]\n final=\"\"\n\n \"\"\"Using for loop for starting addition from the last indexed number\"\"\"\n for i in range(len(num1)-1,-1,-1):\n bit1=num1[i]#storing each indexed() value of num1 in bit1\n bit2=num2[i]#storing each indexed() value of num2 in bit2\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\n Cin=Cout#declaring cout as cin for next bit addition\n l2.append(SUM)#adding SUM to l2\n l3=l2[::-1]##reversing the value of l2\n final+=str(l2[-1])#converting the list value to string\n final1=final[::-1]#reversing string value\n return final1 #returning the binary addition as string","def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def ADD (self, n1, n2):","def cp(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_P, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def test_special_U(self):\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \"U\", {})\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \"U\", {\"u\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.2, 0.0).to_matrix(), \"U\", {\"u\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.0, 0.2).to_matrix(), \"U\", {\"u\": 1})\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \"U\", {\"u\": 1})","def get_roi_onec0_posl1_ub_cost(fm_h, fm_w, fm_c0, dtype, pooled_h, pooled_w):\n return get_roi_onec0_posl1_ub_rois_cost(pooled_h, pooled_w) + \\\n get_roi_onec0_posl1_ub_fm_cost(fm_h, fm_w, fm_c0, dtype,\n pooled_h, pooled_w)","def conv_1x1_bn(self, inp, oup):\n return nn.Sequential(\n nn.Conv2d(inp, oup, 1, 1, 0, bias=False),\n self.get_bn_module(oup),\n nn.ReLU6(inplace=True)\n )","def do_add_reg(self, reg0, reg1):\n assert self.safe_register(reg0), f\"register error [{reg0}]\"\n assert self.safe_register(reg1), f\"register error [{reg1}]\"\n _sum = self.registers[reg0] + self.registers[reg1]\n if _sum <= 255:\n self.registers[reg0] = _sum\n else:\n self.registers[reg0] = 255","def __add__(self, other):\n if type(other) == int or type(other) == float:\n x = (other * Ccy.currencies[self.unit])\n else:\n x = (other.value / Ccy.currencies[other.unit] * Ccy.currencies[self.unit])\n return Ccy(x + self.value, self.unit)","def crelu(features, name=None, axis=-1):\n with ops.name_scope(name, \"CRelu\", [features]) as name:\n features = ops.convert_to_tensor(features, name=\"features\")\n c = array_ops.concat([features, -features], axis, name=name) # pylint: disable=invalid-unary-operand-type\n return gen_nn_ops.relu(c)","def _tk1_to_rotations(a: float, b: float, c: float) -> Circuit:\n circ = Circuit(1)\n circ.Rz(c, 0).Rx(b, 0).Rz(a, 0)\n return circ","def unit(g, node_1, node_2):\n return 1","def acumula_nq1(self, nq1, rodada):\n self.nq1[rodada].append(nq1)","def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self","def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def cbrt1(self):\r\n getcontext().prec += 2\r\n mod = cbrt(abs(self))\r\n try:\r\n arg = atan2(self._imag, self._real) / 3\r\n except InvalidOperationError:\r\n arg = 0\r\n val = self.__class__.from_polar(mod, arg)\r\n getcontext().prec -= 2\r\n return +val","def enable_cl2_copy_ad9866(self):\n self.write_versa5(0x62,0x3b) ## Clock2 CMOS1 output, 3.3V\n self.write_versa5(0x2c,0x01) ## Enable aux output on clock 1\n self.write_versa5(0x31,0x0c) ## Use clock1 aux output as input for clock2\n self.write_versa5(0x63,0x01) ## Enable clock2","def transform_t1_to_bo(t1, umat):\n if isinstance(t1, np.ndarray) and t1.ndim == 2:\n nocc, nvir = t1.shape\n umat_occ = umat[:nocc, :nocc]\n umat_vir = umat[nocc:, nocc:]\n return reduce(np.dot, (umat_occ.conj().T, t1, umat_vir))\n else: # UHF\n spin = len(t1)\n return [transform_t1_to_bo(t1[s], umat[s]) for s in range(spin)]","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def ts_add1(c1, c2, pub):\n a = server1_add1(c1.alpha, c2.alpha, pub)\n b = server2_add1(c1.beta, c2.beta, pub)\n return CipherTwoServer(a, b)","def gen_op1(N11, N22, N12, rN11, rN22, rN12):\n raw = N12 / (N11 + N22)\n ref = rN12 / (rN11 + rN22)\n print(\"=====\\n1st method: raw = N12/(N11+N22)\")\n print(\"raw: %.2f | ref: %.2f\" % (raw, ref) )\n print(\"1 - raw/ref = %.3f\\n=====\" % (1.0 - raw / ref))","def conjugate(self, ???):","def server1_add2 (c1, c2, pub):\n #return (c1 + c2) % pub.n\n return e_add(pub, c1, c2)","def BCS(self, value):\n if self.reg.C:\n self.reg.PC += value","def __init__(self, nfeat, nhid, nclass, dropout, alpha):\n super(GCN, self).__init__()\n self.dropout = dropout\n\n self.conv1 = GraphConvolutionLayer(nfeat, nhid, dropout=dropout, alpha=alpha, not_final=True)\n \n self.add_module('conv1', self.conv1)\n\n self.conv2 = GraphConvolutionLayer(nhid, nclass, dropout=dropout, alpha=alpha, not_final=False)","def acumula_w1(self, w1, rodada):\n self.w1[rodada].append(w1)","def add_conv_type1(model, depth, input_shape=None):\n if input_shape is not None:\n model.add(Convolution2D(depth, 5, 5, subsample=(2, 2), \\\n input_shape=input_shape))\n else:\n model.add(Convolution2D(depth, 5, 5, subsample=(2, 2), \\\n activation='relu', W_regularizer=l2(0.05)))","def convert_relu6(g, op, block):\n\n x = g.get_node(op.input(\"X\")[0])\n out = _op.clip(x, 0.0, 6.0)\n g.add_node(op.output(\"Out\")[0], out)","def step1c(self):\n\t\tif (self.ends(\"y\") and self.vowelinstem()):\n\t\t\tself.b = self.b[:self.k] + 'i' + self.b[self.k+1:]","def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def _generic_canonical_add(mi1, c1, mi2, c2):\r\n\r\n len1, dim1 = mi1.shape\r\n len2, dim2 = mi2.shape # assume m1 and m2 are same dimension -> expand_dim of the mi with smaller dim\r\n\r\n mi1r = mi1.reshape(len1, 1,dim1)\r\n mi2r = mi2.reshape(1, len2,dim1)\r\n\r\n add_cond = np.equal(mi1r, mi2r).all(axis=2, keepdims=False) # where are mi1 and mi2 equal along the dim?\r\n add_cond1 = add_cond.any(axis=1) # added condition for m1,c1\r\n\r\n not_add_cond1 = np.logical_not(add_cond1) # not added condition for m1,c1\r\n add_cond2 = add_cond.any(axis=0) # add condition for m2,c2\r\n not_add_cond2 = np.logical_not(add_cond2) # not added condition for m2,c2\r\n\r\n # build resulting mi\r\n added_mi = mi1[add_cond1,:] # shall be the same as mi2[add_cond2,:]\r\n not_added_mi = np.concatenate((mi1[not_add_cond1,:], mi2[not_add_cond2,:]), axis=0) # collect the rest\r\n res_mi = np.concatenate((added_mi, not_added_mi), axis=0) # summed mi shall be the first\r\n sort_args = np.lexsort(res_mi.T,axis=-1)\r\n\r\n # build resulting coeffs\r\n added_c = c1[add_cond1] + c2[add_cond2]\r\n not_added_c = np.concatenate((c1[not_add_cond1], c2[not_add_cond2]))\r\n res_c = np.concatenate((added_c, not_added_c))\r\n\r\n return res_mi[sort_args], res_c[sort_args]","def plus_one(x):\n return x + 1","def _compute_carry_and_output(self, x, h_tm1, c_tm1):\n x_i, x_f, x_c, x_o = x\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\n i = self.recurrent_activation(\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\n f = self.recurrent_activation(x_f + K.dot(\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\n o = self.recurrent_activation(\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\n return c, o","def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self","def pro_avfid_superoperator_compsubspace(U,L1):\n\n if U.type=='oper':\n inner = U.dag()*U_target\n part_idx = [0, 1, 3, 4] # only computational subspace\n ptrace = 0\n for i in part_idx:\n ptrace += inner[i, i]\n dim = 4 # 2 qubits comp subspace \n\n return np.real(((np.abs(ptrace))**2+dim*(1-L1))/(dim*(dim+1)))\n\n elif U.type=='super':\n kraus_form = qtp.to_kraus(U)\n dim=4 # 2 qubits in the computational subspace\n part_idx = [0, 1, 3, 4] # only computational subspace\n psum=0\n for A_k in kraus_form:\n ptrace = 0\n inner = U_target_diffdims.dag()*A_k # otherwise dimension mismatch\n for i in part_idx:\n ptrace += inner[i, i]\n psum += (np.abs(ptrace))**2\n\n return np.real((dim*(1-L1) + psum) / (dim*(dim + 1)))","def r_1(comps: 'list(Compound)', is_input):\r\n react: str\r\n\r\n if is_input:\r\n iSiMe = Compound(\"Cu\")\r\n if len(comps) == 1:\r\n if \"iSi\" in comps[0].comp_type:\r\n iSiMe = comps[0]\r\n else:\r\n if \"iSi\" in comps[0].comp_type:\r\n iSiMe = comps[0]\r\n else:\r\n iSiMe = comps[1]\r\n\r\n me = list(iSiMe.formula.consist.keys())[0].name\r\n if me in [\"Au\", \"Pt\"]:\r\n return \"\"\r\n me_oxs = get_me_oxs(me)\r\n if me_oxs == 0:\r\n return \"\"\r\n\r\n iSaNo = Compound(iSaNo_create(me, me_oxs, \"NO3\", 1))\r\n\r\n react = f\"{iSiMe} + HNO3 -> {iSaNo} + NO2 + H2O\"\r\n else:\r\n iSaNo = Compound(\"Cu(NO3)2\")\r\n if len(comps) == 1:\r\n if \"iSaNo\" in comps[0].comp_type:\r\n iSaNo = comps[0]\r\n elif len(comps) == 2:\r\n if \"iSaNo\" in comps[0].comp_type:\r\n iSaNo = comps[0]\r\n elif \"iSaNo\" in comps[1].comp_type:\r\n iSaNo = comps[1]\r\n else:\r\n if \"iSaNo\" in comps[0].comp_type:\r\n iSaNo = comps[0]\r\n elif \"iSaNo\" in comps[1].comp_type:\r\n iSaNo = comps[1]\r\n else:\r\n iSaNo = comps[2]\r\n\r\n ((me, me_oxs), (an, an_oxs)) = iSa_oxs(iSaNo.formula)\r\n if an != \"NO3\":\r\n return \"\"\r\n if me in [\"Au\", \"Pt\"]:\r\n return \"\"\r\n\r\n iSiMe = Compound(simple(me))\r\n\r\n react = f\"{iSiMe} + HNO3 -> {iSaNo} + NO2 + H2O\"\r\n\r\n return Reaction(react)","def conjugate(self):\n pass","def test_native_single_qubit_gates(self, valkmusa, gate):\n\n QB1, QB2 = valkmusa.qubits\n valkmusa.validate_operation(gate(QB2))\n valkmusa.validate_operation(gate(QB1).with_tags('tag_foo'))","def I2_u1(self) -> complex:\n # \"Phase 2 current [A]\" is wrong. We need to calculate it ourselves\n return - self.I1_u1() - self.I3_u1()","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def compress_G1(pt: G1Uncompressed) -> G1Compressed:\n if is_inf(pt):\n # Set c_flag = 1 and b_flag = 1. leave a_flag = x = 0\n return G1Compressed(POW_2_383 + POW_2_382)\n else:\n x, y = normalize(pt)\n # Record y's leftmost bit to the a_flag\n a_flag = (y.n * 2) // q\n # Set c_flag = 1 and b_flag = 0\n return G1Compressed(x.n + a_flag * POW_2_381 + POW_2_383)","def plus1(x):\n return x + 1","def GachaCraftNodeExcelAddLv1Exp(builder, Lv1Exp):\n return AddLv1Exp(builder, Lv1Exp)"],"string":"[\n \"def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\\n return self\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def I1_u1(self) -> complex:\\n # Should match in amplitude with \\\"Phase 1 current [A]\\\"\\n # Convert from relative to U12 -> relative to U1\\n return - (self.I1_u12() * cmath.rect(1, 150 / 180 * cmath.pi))\",\n \"def _action_op_u1(self, plaq):\\n # if self.link_type == 'U1':\\n # return np.cos(plaq)\\n return tf.math.cos(plaq)\",\n \"def test_special_U1X(self):\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \\\"U1X\\\", {})\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \\\"U1X\\\", {\\\"u1\\\": 1})\\n self.check_oneq_special_cases(\\n U3Gate(-np.pi / 2, 0.2, 0.0).to_matrix(), \\\"U1X\\\", {\\\"u1\\\": 2, \\\"rx\\\": 1}\\n )\\n self.check_oneq_special_cases(\\n U3Gate(np.pi / 2, 0.0, 0.21).to_matrix(), \\\"U1X\\\", {\\\"u1\\\": 2, \\\"rx\\\": 1}\\n )\\n self.check_oneq_special_cases(\\n U3Gate(np.pi / 2, 0.12, 0.2).to_matrix(), \\\"U1X\\\", {\\\"u1\\\": 2, \\\"rx\\\": 1}\\n )\\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \\\"U1X\\\", {\\\"u1\\\": 3, \\\"rx\\\": 2})\",\n \"def u1(self, q0, alpha=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=ROTATION_U1, qid=[q0], phase=alpha, ctrl=ctrl)\\n return self\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def enable_cl1_direct(self):\\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\\n self.write_versa5(0x18,0x20)\\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\\n self.write_versa5(0x13,0x03) ## Switch to clock\\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def server1_add1(c1, c2, pub):\\n return add1 (c1, c2, pub)\",\n \"def ControlledU(U):\\n\\n d = U.rank // 2 + 1\\n shape = [2] * 2 * d\\n t = np.zeros(shape, dtype=np.complex128)\\n\\n # If the first bit is zero, fill in as the identity operator.\\n t[:, 0, ...] = Identity(d)[:, 0, ...]\\n # Else, fill in as Identity tensored with U (Identity for the first bit,\\n # which remains unchanged.\\n t[:, 1, ...] = (Identity() * U)[:, 1, ...]\\n return Operator(t)\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def _add_grover_step_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n _add_2_bit_oracle_without_ancilla_1_0(qc, register) # Oracle\\n add_grover_reflection_no_ancilla(qc, register) # Reflection\",\n \"def build_gate_1(gate, tags=None):\\n\\n def apply_constant_single_qubit_gate(psi, i, **gate_opts):\\n mtags = _merge_tags(tags, gate_opts)\\n psi.gate_(gate, int(i), tags=mtags, **gate_opts)\\n\\n return apply_constant_single_qubit_gate\",\n \"def enable_cl1_pll1(self):\\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\\n self.write_versa5(0x18,0x20)\\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\\n self.write_versa5(0x13,0x03) ## Switch to clock\\n self.write_versa5(0x10,0x40) ## Enable clock input only, won't lock to master\",\n \"def _add_grover_step_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n _add_2_bit_oracle_with_ancilla_1_0(qc, register, ancilla) # Oracle\\n add_grover_reflection_no_ancilla(qc, register) # Reflection\",\n \"def c1(self):\\n return self.__c1\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def acumula_x1(self, x1, rodada):\\n self.x1[rodada].append(x1)\",\n \"def __init__(self, input0, input1, output) :\\n Gate.__init__(self, [input0,input1], output)\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def add_neurone(self, couche, nbr=1):\\n if self.control == 0:\\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\\n self.couche[couche] += nbr\\n else:\\n print(\\\"Le réseau est deja créé, vous en pouvez plus le modifier\\\")\",\n \"def disable_cl1(self):\\n self.write_versa5(0x10,0xc4) ## Enable xtal and clock\\n self.write_versa5(0x21,0x81) ## Use and enable divider\\n self.write_versa5(0x13,0x00) ## Use CL1 input instead of xtal\\n self.write_versa5(0x10,0x80) ## Enable xtal input only\\n self.write_versa5(0x17,0x04) ## Change top multiplier to 0x44\\n self.write_versa5(0x18,0x40)\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def I1_u12(self) -> complex:\\n return (self.S1_u12() / self.U12()).conjugate()\",\n \"def add_grover_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n # Mark states with a 1 at a later determined position by flipping their amplitude\\n qc.x(ancilla)\\n qc.h(ancilla)\\n # Mix input states\\n qc.h(register)\\n # Execute Grover iteration just once\\n _add_grover_step_with_ancilla_1_0(qc, register, ancilla)\",\n \"def acumula_n1(self, n1, rodada):\\n self.n1[rodada].append(n1)\",\n \"def NUT1(self,NUT1b,n=2.0):\\n if self.tipo == 'contra':\\n return n*NUT1b\\n if self.tipo == 'paralelo':\\n return n*NUT1b\\n if self.tipo == 'misto':\\n return n*NUT1b\",\n \"def calc_c1(self):\\n dc1hw_s = self.src_shape[0]\\n _, d_d, h_d, w_d, _ = self.dst_shape\\n c_1 = dc1hw_s // (d_d * h_d * w_d)\\n return c_1\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def bias_add_v1(value, bias, name=None):\\n with ops.name_scope(name, \\\"BiasAddV1\\\", [value, bias]) as name:\\n value = ops.convert_to_tensor(value, name=\\\"input\\\")\\n bias = ops.convert_to_tensor(bias, dtype=value.dtype, name=\\\"bias\\\")\\n return gen_nn_ops.bias_add_v1(value, bias, name=name)\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def actual_causation():\\n # fmt: off\\n tpm = np.array([\\n [1, 0, 0, 0],\\n [0, 1, 0, 0],\\n [0, 1, 0, 0],\\n [0, 0, 0, 1],\\n ])\\n cm = np.array([\\n [1, 1],\\n [1, 1],\\n ])\\n # fmt: on\\n return Network(tpm, cm, node_labels=('OR', 'AND'))\",\n \"def p1(self, p1):\\n p0 = self.p0\\n u = self.p1 - p0\\n v = p1 - p0\\n\\n scale, rM = self.scale_rot_matrix(u, v)\\n self.c = p0 + rM @ (self.c - p0)\\n self.r *= scale\\n self.r2 = self.r * self.r\\n dp = p0 - self.c\\n self.a0 = atan2(dp.y, dp.x)\",\n \"def test_add_consistency1(self) -> None:\\n a = Constant(\\n 'const1',\\n Float32(),\\n np.zeros([1, 3, 3])\\n )\\n b = Constant(\\n 'const2',\\n Float32(),\\n np.zeros([3])\\n )\\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\\n Add(\\n 'add1',\\n [1, 3, 3],\\n Float32(),\\n input_ops\\n )\\n\\n print(\\\"Consistency test for 'Add' #1 passed!\\\")\",\n \"def _define(self):\\n from qiskit.extensions.standard.u1 import U1Gate\\n definition = []\\n q = QuantumRegister(1, \\\"q\\\")\\n rule = [\\n (U1Gate(self.params[0]), [q[0]], [])\\n ]\\n for inst in rule:\\n definition.append(inst)\\n self.definition = definition\",\n \"def S1_u12(self) -> complex:\\n return complex(\\n self._addr(self.defined_registers['Phase 1 power [W]']['addr']),\\n self._addr(self.defined_registers['Phase 1 volt amps reactive [VAr]']['addr']),\\n )\",\n \"def cu3(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U3, qid=[q0,q1], phase=alpha, phase1=beta,\\n phase2=gamma, ctrl=ctrl)\\n return self\",\n \"def add_grover_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.h(register) # Mix states initially\\n _add_grover_step_without_ancilla_1_0(qc, register) # Repeat Grover iteration just once\",\n \"def ch(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_H, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def acumula_ns1(self, ns1, rodada):\\n self.ns1[rodada].append(ns1)\",\n \"def bias_add(in_tensor0, in_tensor1):\\n dim_map = {}\\n dim_map[\\\"out_img_shape\\\"] = te_util.shape_to_list(in_tensor0.shape)\\n NAME_INDEX[0] += 1\\n\\n with tvm.tag_scope('conv_vector_bias_add'):\\n c_add_vector = tvm.compute(\\n dim_map[\\\"out_img_shape\\\"],\\n lambda *indice: in_tensor0(*indice) + in_tensor1(indice[\\n 1] * CUBE_MKN[in_tensor0.dtype]['mac'][2] + indice[3]),\\n name='bias_add_vector' + \\\"_cc_\\\" + str(NAME_INDEX[0]))\\n return c_add_vector\",\n \"def glucose_c1(self, g_t, t_G, a_G, d_g_t=0):\\n return -(1/t_G)*g_t+(a_G/t_G)*d_g_t\",\n \"def Controlled2(U):\\n '''Generalized controlled unitary tensor construction\\n Parameters:\\n -----------\\n U: input tensor which is assumed to be a square Matrix\\n\\n Returns:\\n --------\\n Controlled unitary\\n\\n '''\\n shp = U.shape\\n new_ten = scipy.linalg.block_diag(np.eye(*shp), U)\\n return new_ten.reshape(2, shp[0], 2, shp[1], 2, shp[2])\",\n \"def cs_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def x_add_one(nom):\\n\\tif 'X' in nom and '*' not in nom:\\n\\t\\treturn nom.replace('X', '1*X')\\n\\treturn nom\",\n \"def add_one(x):\\n return x + 1\",\n \"def Bn1(self,phi0=0):\\n\\t\\treturn self.x[1,:]*_np.sin(self.phi0)+self.x[2,:]*_np.cos(self.phi0)\",\n \"def acumula_t1(self, t1, rodada):\\n self.t1[rodada].append(t1)\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def b1relu( regularizers, x):\\n N, M, F = x.get_shape()\\n b = _bias_variable(regularizers,[1, 1, int(F)], regularization=True)\\n return tf.nn.relu(x + b)\",\n \"def AssignAddHybrid1d(output, value, target=utils.CCE):\\n for i in range(output.shape[0]):\\n output[i] = output[i] + value[i]\\n\\n return output\",\n \"def calcT1(g2, g1):\\n idop = FermiOp(g2.orbs, 3, 3)\\n idop.data = np.eye(int(binom(g2.orbs, 3)))\\n\\n return p2N(g2, 3) - p2N(g1, 3) + idop\",\n \"def add(num1, num2, Cin):\\n Cin=0\\n l2=[]\\n final=\\\"\\\"\\n\\n \\\"\\\"\\\"Using for loop for starting addition from the last indexed number\\\"\\\"\\\"\\n for i in range(len(num1)-1,-1,-1):\\n bit1=num1[i]#storing each indexed() value of num1 in bit1\\n bit2=num2[i]#storing each indexed() value of num2 in bit2\\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\\n Cin=Cout#declaring cout as cin for next bit addition\\n l2.append(SUM)#adding SUM to l2\\n l3=l2[::-1]##reversing the value of l2\\n final+=str(l2[-1])#converting the list value to string\\n final1=final[::-1]#reversing string value\\n return final1 #returning the binary addition as string\",\n \"def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def ADD (self, n1, n2):\",\n \"def cp(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_P, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def test_special_U(self):\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \\\"U\\\", {})\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.2, 0.0).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.0, 0.2).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\",\n \"def get_roi_onec0_posl1_ub_cost(fm_h, fm_w, fm_c0, dtype, pooled_h, pooled_w):\\n return get_roi_onec0_posl1_ub_rois_cost(pooled_h, pooled_w) + \\\\\\n get_roi_onec0_posl1_ub_fm_cost(fm_h, fm_w, fm_c0, dtype,\\n pooled_h, pooled_w)\",\n \"def conv_1x1_bn(self, inp, oup):\\n return nn.Sequential(\\n nn.Conv2d(inp, oup, 1, 1, 0, bias=False),\\n self.get_bn_module(oup),\\n nn.ReLU6(inplace=True)\\n )\",\n \"def do_add_reg(self, reg0, reg1):\\n assert self.safe_register(reg0), f\\\"register error [{reg0}]\\\"\\n assert self.safe_register(reg1), f\\\"register error [{reg1}]\\\"\\n _sum = self.registers[reg0] + self.registers[reg1]\\n if _sum <= 255:\\n self.registers[reg0] = _sum\\n else:\\n self.registers[reg0] = 255\",\n \"def __add__(self, other):\\n if type(other) == int or type(other) == float:\\n x = (other * Ccy.currencies[self.unit])\\n else:\\n x = (other.value / Ccy.currencies[other.unit] * Ccy.currencies[self.unit])\\n return Ccy(x + self.value, self.unit)\",\n \"def crelu(features, name=None, axis=-1):\\n with ops.name_scope(name, \\\"CRelu\\\", [features]) as name:\\n features = ops.convert_to_tensor(features, name=\\\"features\\\")\\n c = array_ops.concat([features, -features], axis, name=name) # pylint: disable=invalid-unary-operand-type\\n return gen_nn_ops.relu(c)\",\n \"def _tk1_to_rotations(a: float, b: float, c: float) -> Circuit:\\n circ = Circuit(1)\\n circ.Rz(c, 0).Rx(b, 0).Rz(a, 0)\\n return circ\",\n \"def unit(g, node_1, node_2):\\n return 1\",\n \"def acumula_nq1(self, nq1, rodada):\\n self.nq1[rodada].append(nq1)\",\n \"def cxr(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def cbrt1(self):\\r\\n getcontext().prec += 2\\r\\n mod = cbrt(abs(self))\\r\\n try:\\r\\n arg = atan2(self._imag, self._real) / 3\\r\\n except InvalidOperationError:\\r\\n arg = 0\\r\\n val = self.__class__.from_polar(mod, arg)\\r\\n getcontext().prec -= 2\\r\\n return +val\",\n \"def enable_cl2_copy_ad9866(self):\\n self.write_versa5(0x62,0x3b) ## Clock2 CMOS1 output, 3.3V\\n self.write_versa5(0x2c,0x01) ## Enable aux output on clock 1\\n self.write_versa5(0x31,0x0c) ## Use clock1 aux output as input for clock2\\n self.write_versa5(0x63,0x01) ## Enable clock2\",\n \"def transform_t1_to_bo(t1, umat):\\n if isinstance(t1, np.ndarray) and t1.ndim == 2:\\n nocc, nvir = t1.shape\\n umat_occ = umat[:nocc, :nocc]\\n umat_vir = umat[nocc:, nocc:]\\n return reduce(np.dot, (umat_occ.conj().T, t1, umat_vir))\\n else: # UHF\\n spin = len(t1)\\n return [transform_t1_to_bo(t1[s], umat[s]) for s in range(spin)]\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def ts_add1(c1, c2, pub):\\n a = server1_add1(c1.alpha, c2.alpha, pub)\\n b = server2_add1(c1.beta, c2.beta, pub)\\n return CipherTwoServer(a, b)\",\n \"def gen_op1(N11, N22, N12, rN11, rN22, rN12):\\n raw = N12 / (N11 + N22)\\n ref = rN12 / (rN11 + rN22)\\n print(\\\"=====\\\\n1st method: raw = N12/(N11+N22)\\\")\\n print(\\\"raw: %.2f | ref: %.2f\\\" % (raw, ref) )\\n print(\\\"1 - raw/ref = %.3f\\\\n=====\\\" % (1.0 - raw / ref))\",\n \"def conjugate(self, ???):\",\n \"def server1_add2 (c1, c2, pub):\\n #return (c1 + c2) % pub.n\\n return e_add(pub, c1, c2)\",\n \"def BCS(self, value):\\n if self.reg.C:\\n self.reg.PC += value\",\n \"def __init__(self, nfeat, nhid, nclass, dropout, alpha):\\n super(GCN, self).__init__()\\n self.dropout = dropout\\n\\n self.conv1 = GraphConvolutionLayer(nfeat, nhid, dropout=dropout, alpha=alpha, not_final=True)\\n \\n self.add_module('conv1', self.conv1)\\n\\n self.conv2 = GraphConvolutionLayer(nhid, nclass, dropout=dropout, alpha=alpha, not_final=False)\",\n \"def acumula_w1(self, w1, rodada):\\n self.w1[rodada].append(w1)\",\n \"def add_conv_type1(model, depth, input_shape=None):\\n if input_shape is not None:\\n model.add(Convolution2D(depth, 5, 5, subsample=(2, 2), \\\\\\n input_shape=input_shape))\\n else:\\n model.add(Convolution2D(depth, 5, 5, subsample=(2, 2), \\\\\\n activation='relu', W_regularizer=l2(0.05)))\",\n \"def convert_relu6(g, op, block):\\n\\n x = g.get_node(op.input(\\\"X\\\")[0])\\n out = _op.clip(x, 0.0, 6.0)\\n g.add_node(op.output(\\\"Out\\\")[0], out)\",\n \"def step1c(self):\\n\\t\\tif (self.ends(\\\"y\\\") and self.vowelinstem()):\\n\\t\\t\\tself.b = self.b[:self.k] + 'i' + self.b[self.k+1:]\",\n \"def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def _generic_canonical_add(mi1, c1, mi2, c2):\\r\\n\\r\\n len1, dim1 = mi1.shape\\r\\n len2, dim2 = mi2.shape # assume m1 and m2 are same dimension -> expand_dim of the mi with smaller dim\\r\\n\\r\\n mi1r = mi1.reshape(len1, 1,dim1)\\r\\n mi2r = mi2.reshape(1, len2,dim1)\\r\\n\\r\\n add_cond = np.equal(mi1r, mi2r).all(axis=2, keepdims=False) # where are mi1 and mi2 equal along the dim?\\r\\n add_cond1 = add_cond.any(axis=1) # added condition for m1,c1\\r\\n\\r\\n not_add_cond1 = np.logical_not(add_cond1) # not added condition for m1,c1\\r\\n add_cond2 = add_cond.any(axis=0) # add condition for m2,c2\\r\\n not_add_cond2 = np.logical_not(add_cond2) # not added condition for m2,c2\\r\\n\\r\\n # build resulting mi\\r\\n added_mi = mi1[add_cond1,:] # shall be the same as mi2[add_cond2,:]\\r\\n not_added_mi = np.concatenate((mi1[not_add_cond1,:], mi2[not_add_cond2,:]), axis=0) # collect the rest\\r\\n res_mi = np.concatenate((added_mi, not_added_mi), axis=0) # summed mi shall be the first\\r\\n sort_args = np.lexsort(res_mi.T,axis=-1)\\r\\n\\r\\n # build resulting coeffs\\r\\n added_c = c1[add_cond1] + c2[add_cond2]\\r\\n not_added_c = np.concatenate((c1[not_add_cond1], c2[not_add_cond2]))\\r\\n res_c = np.concatenate((added_c, not_added_c))\\r\\n\\r\\n return res_mi[sort_args], res_c[sort_args]\",\n \"def plus_one(x):\\n return x + 1\",\n \"def _compute_carry_and_output(self, x, h_tm1, c_tm1):\\n x_i, x_f, x_c, x_o = x\\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\\n i = self.recurrent_activation(\\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\\n f = self.recurrent_activation(x_f + K.dot(\\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\\n o = self.recurrent_activation(\\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\\n return c, o\",\n \"def cxr_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def pro_avfid_superoperator_compsubspace(U,L1):\\n\\n if U.type=='oper':\\n inner = U.dag()*U_target\\n part_idx = [0, 1, 3, 4] # only computational subspace\\n ptrace = 0\\n for i in part_idx:\\n ptrace += inner[i, i]\\n dim = 4 # 2 qubits comp subspace \\n\\n return np.real(((np.abs(ptrace))**2+dim*(1-L1))/(dim*(dim+1)))\\n\\n elif U.type=='super':\\n kraus_form = qtp.to_kraus(U)\\n dim=4 # 2 qubits in the computational subspace\\n part_idx = [0, 1, 3, 4] # only computational subspace\\n psum=0\\n for A_k in kraus_form:\\n ptrace = 0\\n inner = U_target_diffdims.dag()*A_k # otherwise dimension mismatch\\n for i in part_idx:\\n ptrace += inner[i, i]\\n psum += (np.abs(ptrace))**2\\n\\n return np.real((dim*(1-L1) + psum) / (dim*(dim + 1)))\",\n \"def r_1(comps: 'list(Compound)', is_input):\\r\\n react: str\\r\\n\\r\\n if is_input:\\r\\n iSiMe = Compound(\\\"Cu\\\")\\r\\n if len(comps) == 1:\\r\\n if \\\"iSi\\\" in comps[0].comp_type:\\r\\n iSiMe = comps[0]\\r\\n else:\\r\\n if \\\"iSi\\\" in comps[0].comp_type:\\r\\n iSiMe = comps[0]\\r\\n else:\\r\\n iSiMe = comps[1]\\r\\n\\r\\n me = list(iSiMe.formula.consist.keys())[0].name\\r\\n if me in [\\\"Au\\\", \\\"Pt\\\"]:\\r\\n return \\\"\\\"\\r\\n me_oxs = get_me_oxs(me)\\r\\n if me_oxs == 0:\\r\\n return \\\"\\\"\\r\\n\\r\\n iSaNo = Compound(iSaNo_create(me, me_oxs, \\\"NO3\\\", 1))\\r\\n\\r\\n react = f\\\"{iSiMe} + HNO3 -> {iSaNo} + NO2 + H2O\\\"\\r\\n else:\\r\\n iSaNo = Compound(\\\"Cu(NO3)2\\\")\\r\\n if len(comps) == 1:\\r\\n if \\\"iSaNo\\\" in comps[0].comp_type:\\r\\n iSaNo = comps[0]\\r\\n elif len(comps) == 2:\\r\\n if \\\"iSaNo\\\" in comps[0].comp_type:\\r\\n iSaNo = comps[0]\\r\\n elif \\\"iSaNo\\\" in comps[1].comp_type:\\r\\n iSaNo = comps[1]\\r\\n else:\\r\\n if \\\"iSaNo\\\" in comps[0].comp_type:\\r\\n iSaNo = comps[0]\\r\\n elif \\\"iSaNo\\\" in comps[1].comp_type:\\r\\n iSaNo = comps[1]\\r\\n else:\\r\\n iSaNo = comps[2]\\r\\n\\r\\n ((me, me_oxs), (an, an_oxs)) = iSa_oxs(iSaNo.formula)\\r\\n if an != \\\"NO3\\\":\\r\\n return \\\"\\\"\\r\\n if me in [\\\"Au\\\", \\\"Pt\\\"]:\\r\\n return \\\"\\\"\\r\\n\\r\\n iSiMe = Compound(simple(me))\\r\\n\\r\\n react = f\\\"{iSiMe} + HNO3 -> {iSaNo} + NO2 + H2O\\\"\\r\\n\\r\\n return Reaction(react)\",\n \"def conjugate(self):\\n pass\",\n \"def test_native_single_qubit_gates(self, valkmusa, gate):\\n\\n QB1, QB2 = valkmusa.qubits\\n valkmusa.validate_operation(gate(QB2))\\n valkmusa.validate_operation(gate(QB1).with_tags('tag_foo'))\",\n \"def I2_u1(self) -> complex:\\n # \\\"Phase 2 current [A]\\\" is wrong. We need to calculate it ourselves\\n return - self.I1_u1() - self.I3_u1()\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def compress_G1(pt: G1Uncompressed) -> G1Compressed:\\n if is_inf(pt):\\n # Set c_flag = 1 and b_flag = 1. leave a_flag = x = 0\\n return G1Compressed(POW_2_383 + POW_2_382)\\n else:\\n x, y = normalize(pt)\\n # Record y's leftmost bit to the a_flag\\n a_flag = (y.n * 2) // q\\n # Set c_flag = 1 and b_flag = 0\\n return G1Compressed(x.n + a_flag * POW_2_381 + POW_2_383)\",\n \"def plus1(x):\\n return x + 1\",\n \"def GachaCraftNodeExcelAddLv1Exp(builder, Lv1Exp):\\n return AddLv1Exp(builder, Lv1Exp)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.58692527","0.58496964","0.57497954","0.57320833","0.5699937","0.5659775","0.55907893","0.5577817","0.55392885","0.54260707","0.53691983","0.5344864","0.53429586","0.5311072","0.5285583","0.5258641","0.5211102","0.5174425","0.5146771","0.513239","0.5119667","0.50905377","0.507165","0.50582045","0.50546247","0.5010025","0.49912497","0.4987193","0.4983299","0.4959338","0.49530807","0.49528903","0.4928817","0.49201226","0.4910783","0.4899361","0.4894973","0.48928514","0.48683262","0.4860914","0.48494375","0.48419","0.48336014","0.48292792","0.48201907","0.48065153","0.47961602","0.47916552","0.47884637","0.47654742","0.47650865","0.47647926","0.47486794","0.47425705","0.47423145","0.47284052","0.4727802","0.47273543","0.47156304","0.47110838","0.47089207","0.47082043","0.46990186","0.46986136","0.46963602","0.46799704","0.46725452","0.46691698","0.46690795","0.46661398","0.46517104","0.46510953","0.46452457","0.46098325","0.45977765","0.4597681","0.45952508","0.4585289","0.45837602","0.4578624","0.45772532","0.45740846","0.456187","0.45617697","0.45522156","0.45490032","0.4534921","0.45333147","0.45324504","0.4525484","0.45237964","0.45109692","0.4508094","0.45049798","0.4500819","0.44993278","0.44969997","0.44951683","0.4492893","0.44871494"],"string":"[\n \"0.58692527\",\n \"0.58496964\",\n \"0.57497954\",\n \"0.57320833\",\n \"0.5699937\",\n \"0.5659775\",\n \"0.55907893\",\n \"0.5577817\",\n \"0.55392885\",\n \"0.54260707\",\n \"0.53691983\",\n \"0.5344864\",\n \"0.53429586\",\n \"0.5311072\",\n \"0.5285583\",\n \"0.5258641\",\n \"0.5211102\",\n \"0.5174425\",\n \"0.5146771\",\n \"0.513239\",\n \"0.5119667\",\n \"0.50905377\",\n \"0.507165\",\n \"0.50582045\",\n \"0.50546247\",\n \"0.5010025\",\n \"0.49912497\",\n \"0.4987193\",\n \"0.4983299\",\n \"0.4959338\",\n \"0.49530807\",\n \"0.49528903\",\n \"0.4928817\",\n \"0.49201226\",\n \"0.4910783\",\n \"0.4899361\",\n \"0.4894973\",\n \"0.48928514\",\n \"0.48683262\",\n \"0.4860914\",\n \"0.48494375\",\n \"0.48419\",\n \"0.48336014\",\n \"0.48292792\",\n \"0.48201907\",\n \"0.48065153\",\n \"0.47961602\",\n \"0.47916552\",\n \"0.47884637\",\n \"0.47654742\",\n \"0.47650865\",\n \"0.47647926\",\n \"0.47486794\",\n \"0.47425705\",\n \"0.47423145\",\n \"0.47284052\",\n \"0.4727802\",\n \"0.47273543\",\n \"0.47156304\",\n \"0.47110838\",\n \"0.47089207\",\n \"0.47082043\",\n \"0.46990186\",\n \"0.46986136\",\n \"0.46963602\",\n \"0.46799704\",\n \"0.46725452\",\n \"0.46691698\",\n \"0.46690795\",\n \"0.46661398\",\n \"0.46517104\",\n \"0.46510953\",\n \"0.46452457\",\n \"0.46098325\",\n \"0.45977765\",\n \"0.4597681\",\n \"0.45952508\",\n \"0.4585289\",\n \"0.45837602\",\n \"0.4578624\",\n \"0.45772532\",\n \"0.45740846\",\n \"0.456187\",\n \"0.45617697\",\n \"0.45522156\",\n \"0.45490032\",\n \"0.4534921\",\n \"0.45333147\",\n \"0.45324504\",\n \"0.4525484\",\n \"0.45237964\",\n \"0.45109692\",\n \"0.4508094\",\n \"0.45049798\",\n \"0.4500819\",\n \"0.44993278\",\n \"0.44969997\",\n \"0.44951683\",\n \"0.4492893\",\n \"0.44871494\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7375347"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81757,"cells":{"query":{"kind":"string","value":"add CU2 gate (controlled U2 gate)."},"document":{"kind":"string","value":"def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def I2_u2(self) -> complex:\n return self.I2_u1() * cmath.rect(1, -120 / 180 * cmath.pi)","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def u2(self, q0, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_U2, qid=[q0], phase=alpha, phase1=beta, ctrl=ctrl)\n return self","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def __add__(self, v2):\n\t\treturn Vect2D(self._vec+v2._vec)","def build_gate_2(gate, tags=None):\n\n def apply_constant_two_qubit_gate(psi, i, j, **gate_opts):\n mtags = _merge_tags(tags, gate_opts)\n psi.gate_(gate, (int(i), int(j)), tags=mtags, **gate_opts)\n\n return apply_constant_two_qubit_gate","def test_U2(self, tol):\n dev = qml.device(\"default.qubit\", wires=1)\n\n @qml.qnode(dev)\n def circuit(x, y):\n qml.QubitStateVector(1j * np.array([1, -1]) / np.sqrt(2), wires=[0])\n qml.U2(x, y, wires=[0])\n return qml.expval(qml.PauliX(0))\n\n phi = -0.234\n lam = 0.654\n\n res = circuit(phi, lam)\n expected = np.sin(lam) * np.sin(phi)\n assert np.allclose(res, expected, atol=tol, rtol=0)\n\n grad_fn = autograd.grad(circuit, argnum=[0, 1])\n res = grad_fn(phi, lam)\n expected = np.array([np.sin(lam) * np.cos(phi), np.cos(lam) * np.sin(phi)])\n assert np.allclose(res, expected, atol=tol, rtol=0)","def enable_cl2_copy_ad9866(self):\n self.write_versa5(0x62,0x3b) ## Clock2 CMOS1 output, 3.3V\n self.write_versa5(0x2c,0x01) ## Enable aux output on clock 1\n self.write_versa5(0x31,0x0c) ## Use clock1 aux output as input for clock2\n self.write_versa5(0x63,0x01) ## Enable clock2","def _ucbpe_2ucb(x):\n mu, sigma = gp.eval(x, uncert_form='std')\n return mu + 2 * beta_th * sigma","def _ucbpe_2ucb(x):\n mu, sigma = gp.eval(x, uncert_form='std')\n return mu + 2 * beta_th * sigma","def __add_boundary_contrib_operator2(self, bc, b_idx):\n if bc is not None:\n if bc.boundary_condition_type is configuration.BoundaryConditionType.ROBIN:\n fe_op.add_value(self.operator2, -0.5 * (self.timestep ** 2) * bc.param, b_idx, b_idx)\n elif bc.boundary_condition_type is configuration.BoundaryConditionType.ABSORBING:\n fe_op.add_value(self.operator2, 0.5 * self.timestep * bc.param, b_idx, b_idx)","def acumula_n2(self, n2, rodada):\n self.n2[rodada].append(n2)","def server1_add2 (c1, c2, pub):\n #return (c1 + c2) % pub.n\n return e_add(pub, c1, c2)","def two_activation(self, output_reg):\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\n self._q_neuron.cx(self.inputs[0], self._output[output_reg])\n self._q_neuron.cx(self.inputs[1], self._output[output_reg])","def acumula_x2(self, x2, rodada):\n self.x2[rodada].append(x2)","def ts_add2 (c1,c2, pub):\n \n a = server1_add2(c1.alpha, c2.alpha, pub)\n b = server2_add2(c1.beta, c2.beta, pub)\n return CipherTwoServer(a,b)","def acumula_ns2(self, ns2, rodada):\n self.ns2[rodada].append(ns2)","def owner2_add_funds(self, owner2_amount_in_msat: int):\n BLOCKCHAIN_INSTANCE.apply_transaction(self.channel_state.channel_data.owner2, owner2_amount_in_msat)\n self._state.channel_data.total_msat += (owner2_amount_in_msat * (1 - BLOCKCHAIN_INSTANCE.fee))\n self._compute_amount_owner2_can_transfer_to_owner1()","def chain_2(d2f_dg2, dg_dx, df_dg, d2g_dx2):\r\n return d2f_dg2*(dg_dx**2) + df_dg*d2g_dx2","def acc_j2(U,comp):\n if comp == 'x' or comp == 'y':\n return (1 - 1.5*J2*(R/r(U))**2*(5*(U[2]/r(U))**2-1))\n elif comp =='z':\n return (1 - 1.5*J2*(R/r(U))**2*(5*(U[2]/r(U))**2-3))","def x2(self):\n return self._x + self._x2","def gen_chip2_and_write(tup):\n cfpath, gfpath, bbox, theta, new_size, filter_list = tup\n chipBGR = ctool.compute_chip(gfpath, bbox, theta, new_size, filter_list)\n #printDBG('write chip: %r' % cfpath)\n gtool.imwrite(cfpath, chipBGR)\n return cfpath","def I2_u1(self) -> complex:\n # \"Phase 2 current [A]\" is wrong. We need to calculate it ourselves\n return - self.I1_u1() - self.I3_u1()","def acumula_t2(self, t2, rodada):\n self.t2[rodada].append(t2)","def add_conv_type2(model, depth):\n model.add(Convolution2D(depth, 3, 3, subsample=(1, 1)))","def map_to_curve_G2(u: FQ2) -> G2Uncompressed:\n (x, y, z) = optimized_swu_G2(u)\n return iso_map_G2(x, y, z)","def y2(self):\n return self._y + self._y2","def add_op2_data(cls, data, comment=''):\n sid = data[0]\n node = data[1]\n mag = data[2]\n g1 = data[3]\n g2 = data[4]\n return cls(sid, node, mag, g1, g2, comment=comment)","def itkScalarConnectedComponentImageFilterIUC2IUC2_cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUC2IUC2_cast(*args)","def shift_2_cust(self, sol_in2, cust, c_loc, curr_temp, sol_type2, sa_lns):\r\n\r\n route_ing = copy.deepcopy(sol_in2[c_loc[0]])\r\n route_new = route_ing\r\n move_to_route = c_loc[0]\r\n orgn_type1 = sol_type2[c_loc[0]]\r\n cust_folw = route_ing[c_loc[1]+1]\r\n origin_cost1 = check_violation(route_ing, orgn_type1)[1]\r\n route_ing.remove(cust) # remove c in the current route\r\n del route_ing[c_loc[1]] # remove customer following c\r\n new_type1 = route_type(route_ing)\r\n adjust_cost1 = check_violation(route_ing, new_type1)[1]\r\n best_cut_cost0 = -1000\r\n best_cut_cost = best_cut_cost0 # best cost cut of moving this customer\r\n for j, rou in enumerate(sol_in2):\r\n orgn_type2 = sol_type2[j]\r\n origin_cost2 = check_violation(rou, orgn_type2)[1]\r\n if j == c_loc[0]: # moving in the same route\r\n for k in range(1, len(route_ing)):\r\n if k == c_loc[1]:\r\n continue\r\n rou_test = route_ing[:k] + [cust, cust_folw] + route_ing[k:]\r\n if check_violation(rou_test, orgn_type2)[0]:\r\n adjust_cost2 = check_violation(rou_test, orgn_type2)[1]\r\n cost_cut_test = origin_cost1 - adjust_cost2\r\n if cost_cut_test > best_cut_cost:\r\n best_cut_cost = cost_cut_test\r\n route_new = rou_test\r\n move_to_route = j\r\n\r\n\r\n else: # moving to a different route\r\n for k in range(1, len(rou)):\r\n rou_test = rou[:k] + [cust, cust_folw] + rou[k:]\r\n if check_violation(rou_test, 5)[0]:\r\n new_type2 = route_type(rou_test)\r\n adjust_cost2 = check_violation(rou_test, new_type2)[1]\r\n cost_cut_test = origin_cost1 + origin_cost2 - adjust_cost1 - adjust_cost2\r\n if cost_cut_test > best_cut_cost:\r\n best_cut_cost = cost_cut_test\r\n route_new = rou_test\r\n move_to_route = j\r\n\r\n\r\n if best_cut_cost > 1e-5:\r\n # print('shift2 good', best_cut_cost)\r\n sol_in2[move_to_route] = route_new\r\n sol_type2[move_to_route] = route_type(route_new)\r\n if move_to_route != c_loc[0]: # moving to a different route\r\n sol_in2[c_loc[0]] = route_ing\r\n sol_type2[c_loc[0]] = route_type(route_ing)\r\n\r\n elif sa_lns and best_cut_cost < -1e-5:\r\n prb = random.uniform(0, 1)\r\n if np.exp(best_cut_cost / curr_temp) > prb:\r\n # print('shift2', best_cut_cost)\r\n sol_in2[move_to_route] = route_new\r\n sol_type2[move_to_route] = route_type(route_new)\r\n if move_to_route != c_loc[0]: # moving to a different route\r\n sol_in2[c_loc[0]] = route_ing\r\n sol_type2[c_loc[0]] = route_type(route_ing)\r\n\r\n # return sol_in2\r","def acumula_nq2(self, nq2, rodada):\n self.nq2[rodada].append(nq2)","def itkScalarConnectedComponentImageFilterIUL2IUL2_cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUL2IUL2_cast(*args)","def acumula_w2(self, w2, rodada):\n self.w2[rodada].append(w2)","def enable_cl2_61p44(self):\n self.write_versa5(0x62,0x3b) ## Clock2 CMOS1 output, 3.3V\n self.write_versa5(0x2c,0x00) ## Disable aux output on clock 1\n self.write_versa5(0x31,0x81) ## Use divider for clock2\n ## VCO multiplier is shared for all outputs, set to 68 by firmware\n ## VCO = 38.4*68 = 2611.2 MHz\n ## There is a hardwired divide by 2 in the Versa 5 at the VCO output\n ## VCO to Dividers = 2611.2 MHZ/2 = 1305.6\n ## Target frequency of 61.44 requires dividers of 1305.6/61.44 = 21.25\n ## Frational dividers are supported\n ## Set integer portion of divider 21 = 0x15, 12 bits split across 2 registers\n self.write_versa5(0x3d,0x01)\n self.write_versa5(0x3e,0x50)\n ## Set fractional portion, 30 bits, 2**24 * .25 = 0x400000\n self.write_versa5(0x32,0x01) ## [29:22]\n self.write_versa5(0x33,0x00) ## [21:14]\n self.write_versa5(0x34,0x00) ## [13:6]\n self.write_versa5(0x35,0x00) ## [5:0] and disable ss\n self.write_versa5(0x63,0x01) ## Enable clock2","def add(self, y):\n return circuit.add(self, y)","def glucose_c2(self, m_t, g_t, t_G):\n return -(1/t_G)*m_t+(1/t_G)*g_t","def add_cf_arc(self, e1, e2, pr = 1.0):\n if isinstance(e1, str):\n e1 = self.get_element_by_name(e1)\n if isinstance(e2, str):\n e2 = self.get_element_by_name(e2) \n a = cf_arc(e1, e2, pr)\n e1.CO.add(a)\n e2.CI.add(a)\n self.ACF.append(a)","def add_card_two(self, card):\n self.add_card(card)\n self._check_blackjack()","def basic_block2(self, input_feats, name1, name2, is_train, use_batch_norm, c):\n branch2a_feats = convolution_no_bias(input_feats, 1, 1, c, 1, 1, name1+'_branch2a')\n branch2a_feats = batch_norm(branch2a_feats, name2+'_branch2a', is_train, use_batch_norm)\n branch2a_feats = nonlinear(branch2a_feats, 'relu')\n\n branch2b_feats = convolution_no_bias(branch2a_feats, 3, 3, c, 1, 1, name1+'_branch2b')\n branch2b_feats = batch_norm(branch2b_feats, name2+'_branch2b', is_train, use_batch_norm)\n branch2b_feats = nonlinear(branch2b_feats, 'relu')\n\n branch2c_feats = convolution_no_bias(branch2b_feats, 1, 1, 4*c, 1, 1, name1+'_branch2c')\n branch2c_feats = batch_norm(branch2c_feats, name2+'_branch2c', is_train, use_batch_norm)\n\n output_feats = input_feats + branch2c_feats\n output_feats = nonlinear(output_feats, 'relu')\n return output_feats","def cue_integration_output(self, cue1, cue2):\r\n pi_left = cue1[0:8]\r\n\r\n pi_l = np.zeros((self.num_neuron, int(self.nt)))\r\n pi_l[:, int(self.ni):] = np.repeat(pi_left.reshape(self.num_neuron, 1), int(self.nt - self.ni), axis=1)\r\n\r\n pi_right = cue1[8:]\r\n pi_r = np.zeros((self.num_neuron, int(self.nt)))\r\n pi_r[:, int(self.ni):] = np.repeat(pi_right.reshape(self.num_neuron, 1), int(self.nt - self.ni), axis=1)\r\n\r\n v_left = cue2[0:8]\r\n v_l = np.zeros((self.num_neuron, int(self.nt)))\r\n v_l[:, int(self.ni):] = np.repeat(v_left.reshape(self.num_neuron, 1), int(self.nt - self.ni), axis=1)\r\n v_right = cue2[8:]\r\n v_r = np.zeros((self.num_neuron, int(self.nt)))\r\n v_r[:, int(self.ni):] = np.repeat(v_right.reshape(self.num_neuron, 1), int(self.nt - self.ni), axis=1)\r\n\r\n # generate the array for integration cells and the uniform inhibitory cell\r\n it_l = np.zeros((self.num_neuron, int(self.nt)))\r\n it_l[:, 0] = 0.1 * np.ones(self.num_neuron, )\r\n it_r = np.zeros((self.num_neuron, int(self.nt)))\r\n it_r[:, 0] = 0.1 * np.ones(self.num_neuron, )\r\n ul = np.zeros((1, int(self.nt)))\r\n ur = np.zeros((1, int(self.nt)))\r\n # iteration to the stable state\r\n for t in range(1, int(self.nt)):\r\n it_l[:, t] = it_l[:, t - 1] + (-it_l[:, t - 1] + np.max(\r\n [np.zeros((self.num_neuron,)),\r\n self.gammaE + np.dot(self.W_E_E, it_l[:, t - 1]) + self.W_E_I * ul[:, t - 1] + pi_l[:, t - 1]\r\n + v_l[:, t - 1]], axis=0)) * self.dt / self.tauE\r\n ul[:, t] = ul[:, t - 1] + (\r\n -ul[:, t - 1] + np.max([0, self.gammaI + self.W_I_E * np.sum(it_l[:, t - 1]) + self.W_I_I * ul[:, t - 1]],\r\n axis=0)) * self.dt / self.tauI\r\n\r\n it_r[:, t] = it_r[:, t - 1] + (-it_r[:, t - 1] + np.max(\r\n [np.zeros((self.num_neuron,)),\r\n self.gammaE + np.dot(self.W_E_E, it_r[:, t - 1]) + self.W_E_I * ur[:, t - 1] + pi_r[:, t - 1]\r\n + v_r[:, t - 1]], axis=0)) * self.dt / self.tauE\r\n ur[:, t] = ur[:, t - 1] + (\r\n -ur[:, t - 1] + np.max([0, self.gammaI + self.W_I_E * np.sum(it_r[:, t - 1]) + self.W_I_I * ur[:, t - 1]],\r\n axis=0)) * self.dt / self.tauI\r\n\r\n # get the final iteration as the output\r\n # update the neuron activation\r\n self.integration_neuron = np.hstack([it_l[:, -1], it_r[:, -1]])\r\n self.integration_neuron = noisy_sigmoid(self.integration_neuron, 5.0, 2.5, 0)\r\n self.inhibition_neuron = np.hstack([ul[-1], ur[-1]])\r\n\r\n return self.integration_neuron","def _add(self, node1, node2):\r\n\r\n self._graph[node1].add(node2)","def server2_add2 (b1, b2, pub):\n return (b1 + b2) % pub.n","def add_op2_data(cls, data, comment=''):\n sid = data[0]\n cid = data[1]\n unused_a = data[2]\n N = array(data[3:6])\n mb = data[6]\n scale = 1.\n assert len(data) == 7\n return GRAV(sid, scale, N, cid=cid, mb=mb, comment=comment)","def ab2_cd(CFL, uold1, uold2, unew):\n\n unew[1:-1] = uold1[1:-1] - 0.75 * CFL * (uold1[2:] - uold1[:-2]) +\\\n 0.25 * CFL * (uold2[2:] - uold2[:-2])\n unew[-1] = uold1[-1] - 1.5 * CFL * (uold1[-1] - uold1[-2]) +\\\n 0.5 * CFL * (uold2[-1] - uold2[-2])\n\n return unew","def add_op2_data(cls, data, comment=''):\n sid = data[0]\n node = data[1]\n mag = data[2]\n g1 = data[3]\n g2 = data[4]\n g3 = data[5]\n g4 = data[6]\n return cls(sid, node, mag, g1, g2, g3, g4, comment=comment)","def itkBinaryContourImageFilterIUC2IUC2_cast(obj: 'itkLightObject') -> \"itkBinaryContourImageFilterIUC2IUC2 *\":\n return _itkBinaryContourImageFilterPython.itkBinaryContourImageFilterIUC2IUC2_cast(obj)","def itkHuangThresholdImageFilterIUC2IUS2_cast(obj: 'itkLightObject') -> \"itkHuangThresholdImageFilterIUC2IUS2 *\":\n return _itkHuangThresholdImageFilterPython.itkHuangThresholdImageFilterIUC2IUS2_cast(obj)","def append_user_gate(self, user_gate):\n self.translation['g_sect'].append(user_gate)","def __init__(self, input0, input1, output) :\n Gate.__init__(self, [input0,input1], output)","def ADD (self, n1, n2):","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def upscale_2x_block(self, output_channel, filter_, activate):\n return self.add_layer(upscale_2x_block, output_channel, filter_, activate)","def cu_for_merge(self, best1, best2, undo=True):\n\t\t#TODO - Might want to consider adding the instance to the merged node.\n\t\tfirst = best1\n\t\tsecond = best2\n\n\t\tif second < first:\n\t\t\ttemp = first \n\t\t\tfirst = second \n\t\t\tsecond = temp\n\n\t\tfirst_c = self.tree.children[first]\n\t\tsecond_c = self.tree.children[second]\n\n\t\tnew_c = self.tree.makeTree(self.tree.root, self.tree)\n\t\tnew_c.utility.update_counts_from_node(first_c)\n\t\tnew_c.utility.update_counts_from_node(second_c)\n\n\t\tself.tree.children.pop(second)\n\t\tself.tree.children.pop(first)\n\t\tself.tree.children.append(new_c)\n\n\t\tcu = self.utility.category_utility()\n\n\t\tif undo:\n\t\t\tself.tree.children.pop()\n\t\t\tself.tree.children.insert(first,first_c)\n\t\t\tself.tree.children.insert(second,second_c)\n\t\telse:\n\t\t\t# If we aren't undoing the merge then we have to add the leaves\n\t\t\tnew_c.children.append(first_c)\n\t\t\tfirst_c.parent = new_c\n\t\t\tnew_c.children.append(second_c)\n\t\t\tsecond_c.parent = new_c\n\t\t\tself.tree.mergedNodes.append([first_c, second_c])\n\t\t\tself.tree.splitMergeOrder.append(\"m\")\n\t\t\tfor m in self.tree.mergedNodes:\n\t\t\t\tif len(m) > 2 and first_c in m and second_c in m:\n\t\t\t\t\tm.remove(first_c)\n\t\t\t\t\tm.remove(second_c)\n\t\t\t\t\tm.append(new_c)\n\t\t\tfor s in self.tree.splitNodes:\n\t\t\t\tif len(s) > 2 and first_c in s and second_c in s:\n\t\t\t\t\ts.remove(first_c)\n\t\t\t\t\ts.remove(second_c)\n\t\t\t\t\ts.append(new_c)\n\t\treturn cu","def chain_2(d2f_dg2, dg_dx, df_dg, d2g_dx2):\n if np.all(dg_dx==1.) and np.all(d2g_dx2 == 0):\n return d2f_dg2\n dg_dx_2 = np.clip(dg_dx, -np.inf, _lim_val_square)**2\n #dg_dx_2 = dg_dx**2\n return d2f_dg2*(dg_dx_2) + df_dg*d2g_dx2","def fully_connected2(self):\n self.weights2 = tf.get_variable(\"weights2\", shape=[14, 12],\n initializer=tf.contrib.layers.xavier_initializer()) \n self.bias2 = tf.get_variable('bias2',dtype = tf.float32, \n initializer = tf.random_normal([1]))\n self.hidden_layer2 = tf.matmul(self.data, self.weights2, name = 'hidden_layer2') + self.bias2\n \n self.data = tf.nn.relu(self.hidden_layer2)\n \n self.fully_connected3()","def itkScalarConnectedComponentImageFilterIUS2IUS2_cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUS2IUS2_cast(*args)","def setchi2(self,name,chi2):\n if (name not in KFNode.names):\n warning(' state not in node ',name)\n self.chi2[name]=chi2\n return","def server1_add1(c1, c2, pub):\n return add1 (c1, c2, pub)","def EnableI2c(self):\n\n try:\n\n if os.path.exists('/sys/bus/i2c/devices/i2c-0/0-0060'):\n result = \" - I2C device already enabled!\"\n\n else:\n\n with open('/sys/bus/i2c/devices/i2c-0/new_device', 'a') as f:\n # 'echo '+i2c_device.driver+' '+i2c_device.addr+ '\n f.write('mpl3115 0x60')\n result = \" - I2C device enabled!\"\n\n LOG.info(result)\n\n except Exception as err:\n LOG.error(\"Error enabling I2C (device1): \" + str(err))","def GachaCraftNodeExcelAddGP1102(builder, GP1102):\n return AddGP1102(builder, GP1102)","def add_op2_data(cls, data, comment=''):\n sid = data[0]\n node = data[1]\n cid = data[2]\n mag = data[3]\n xyz = array(data[4:7])\n return cls(sid, node, mag, xyz, cid=cid, comment=comment)","def imu_init(self, chain: machine.I2C = None, freq=400000, debug=False):\n if self.antenny_config.get(\"use_bno055\"):\n print(\"use_bno055 found in config: {}\".format(self.antenny_config.get_name()))\n if chain is None:\n i2c_bno_scl = self.antenny_config.get(\"i2c_bno_scl\")\n i2c_bno_sda = self.antenny_config.get(\"i2c_bno_sda\")\n self.i2c_bno = self.i2c_init(1, i2c_bno_scl, i2c_bno_sda, freq=freq)\n else:\n self.i2c_bno = chain\n self.imu = Bno055ImuController(\n self.i2c_bno,\n crystal=False,\n address=self.antenny_config.get(\"i2c_bno_address\"),\n sign=(0, 0, 0)\n )\n self.imu_load()\n self.imu.upload_calibration_profile()\n print(\"IMU connected\")\n elif self.antenny_config.get(\"use_bno08x_i2c\"):\n print(\"use_bno08x_i2c found in config: {}\".format(self.antenny_config.get_name()))\n if chain is None:\n i2c_bno_scl = self.antenny_config.get(\"i2c_bno_scl\")\n i2c_bno_sda = self.antenny_config.get(\"i2c_bno_sda\")\n self.i2c_bno = self.i2c_init(1, i2c_bno_scl, i2c_bno_sda, freq=freq)\n else:\n self.i2c_bno = chain\n ps0 = machine.Pin(self.antenny_config.get(\"bno_ps0\"), machine.Pin.OUT)\n ps1 = machine.Pin(self.antenny_config.get(\"bno_ps1\"), machine.Pin.OUT)\n reset = machine.Pin(self.antenny_config.get(\"bno_rst\"), machine.Pin.OUT)\n ps0.off()\n ps1.off()\n self.imu = Bno08xImuController(\n self.i2c_bno,\n debug=debug,\n reset=reset\n )\n self.imu.reset_calibration()\n print(\"IMU connected\")\n elif self.antenny_config.get(\"use_bno08x_rvc\"):\n print(\"use_bno08x_rvc found in config: {}\".format(self.antenny_config.get_name()))\n tx = self.antenny_config.get(\"i2c_bno_scl\")\n rx = self.antenny_config.get(\"i2c_bno_sda\")\n reset = machine.Pin(self.antenny_config.get(\"bno_rst\"), machine.Pin.OUT)\n ps0 = self.antenny_config.get(\"bno_ps0\")\n ps1 = self.antenny_config.get(\"bno_ps1\")\n if ps0 is not None and ps1 is not None:\n ps0 = machine.Pin(ps0, machine.Pin.OUT)\n ps1 = machine.Pin(ps1, machine.Pin.OUT)\n ps0.on()\n ps1.off()\n uart_bno = self.uart_init(1, rx, tx, baud=115200)\n self.imu = Bno08xUARTImuController(\n uart_bno,\n reset=reset\n )\n self.imu.reset_calibration()\n time.sleep(.5)\n self.imu.start()\n print(\"IMU connected\")\n else:\n self.imu = MockImuController()\n print(\"According to your config, ou do not have an IMU connected\")\n return self.imu","def cu1(self, q0, q1, alpha=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U1, qid=[q0,q1], phase=alpha, ctrl=ctrl)\n return self","def test_circuit_decompose(self):\n dec = TwoQubitDecomposeUpToDiagonal()\n u4 = scipy.stats.unitary_group.rvs(4, random_state=47)\n dmat, circ2cx = dec(u4)\n\n qc1 = QuantumCircuit(2)\n qc1.append(UnitaryGate(u4), range(2))\n\n qc2 = QuantumCircuit(2)\n qc2.compose(circ2cx, range(2), front=False, inplace=True)\n qc2.append(UnitaryGate(dmat), range(2))\n\n self.assertEqual(Operator(u4), Operator(qc1))\n self.assertEqual(Operator(qc1), Operator(qc2))","def augend_2(exp):\n a2 = cddr(exp) # (a2 a3 ...)\n rests = cdr(a2) # (a3 ... )\n if isNull(rests):\n return car(a2)\n else:\n restp = convertToPythonList(cdr(rests))\n return make_sum_2(car(a2), car(rests), *restp)","def l2_reg_cost(cost):\n\n return cost + tf.losses.get_regularization_losses()","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def sendTwoC(self):\n startC = self.countCannibalOnStart()\n if startC < 2:\n return None\n else:\n newStart = self.start[0:2] + str(startC-2) + self.start[3]\n newEnd = self.end[0:2] + str(5-startC) + self.end[3]\n return MissionaryState(newStart,newEnd,\"sendTwoC\")","def _gen_u2(phi, lmbda):\n return _gen_u(0, phi, lmbda)","def AssignAddHybrid2d(output, value, target=utils.CCE):\n for i in range(output.shape[0]):\n for j in range(output.shape[1]):\n output[i, j] = output[i, j] + value[i, j]\n\n return output","def l2_reg_cost(cost):\n return cost + tf.losses.get_regularization_losses()","def l2_reg_cost(cost):\n return cost + tf.losses.get_regularization_losses()","def l2_reg_cost(cost):\n return cost + tf.losses.get_regularization_losses()","def addInPlace(self, value1, value2):\n raise NotImplementedError","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\n return self","def Controlled2(U):\n '''Generalized controlled unitary tensor construction\n Parameters:\n -----------\n U: input tensor which is assumed to be a square Matrix\n\n Returns:\n --------\n Controlled unitary\n\n '''\n shp = U.shape\n new_ten = scipy.linalg.block_diag(np.eye(*shp), U)\n return new_ten.reshape(2, shp[0], 2, shp[1], 2, shp[2])","def __add__(self, polynomial_2: Polynomial) -> Polynomial:\n\n if self.degree > polynomial_2.degree:\n coefficients = self.coefficients[:]\n for i in range(polynomial_2.degree + 1):\n coefficients[i] += polynomial_2.coefficients[i]\n return Polynomial(self.degree, coefficients)\n else:\n coefficients = polynomial_2.coefficients[:]\n for i in range(self.degree + 1):\n coefficients[i] += self.coefficients[i]\n return Polynomial(polynomial_2.degree, coefficients)","def GachaCraftNodeExcelAddLv2Exp(builder, Lv2Exp):\n return AddLv2Exp(builder, Lv2Exp)","def set_action2(self, action2, feature):\n assert feature not in self._action2\n self._action2[feature] = action2","def __init__(self, input_dim, hidden_dim, bias=True, node_n=48, dtype=float):\n super(GCNGRU_Block, self).__init__()\n self.hidden_dim = hidden_dim\n self.node_n = node_n\n\n self.gc1 = GraphConvolution(input_dim + hidden_dim, 2*self.hidden_dim, node_n=node_n, bias=bias)\n self.gc2 = GraphConvolution(input_dim + hidden_dim, self.hidden_dim, node_n=node_n, bias=bias)","def SetKernel(self, _arg: 'itkFlatStructuringElement2') -> \"void\":\n return _itkClosingByReconstructionImageFilterPython.itkClosingByReconstructionImageFilterIUC2IUC2SE2_SetKernel(self, _arg)","def __add__(self, other):\n return Vec2d(self.v[0] + other[0], self.v[1] + other[1])","def __add__(self, other):\n try:\n ox, oy = other\n except Exception:\n return NotImplemented\n return tuple.__new__(Vec2, (self[0] + ox, self[1] + oy))","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\n return self","def complex_sum(c_1,c_2):\n return c_1 + c_2","def _add_grover_step_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n _add_2_bit_oracle_without_ancilla_1_0(qc, register) # Oracle\n add_grover_reflection_no_ancilla(qc, register) # Reflection","def addMe2Me(x):\n return x+x","def __add__(self, second_rule):\n return AndRule(self, second_rule)","def costInsertion(el1,el2):\r\n return 2","def JC(lcsc1c2, Pc1, Pc2):\n\n JC = 1/(2*lcsc1c2 - (Pc1 + Pc2))\n return JC","def calc_CO2_compensation_point(self, Tleaf):\n\n # Rubisco specificity for CO2 relative to O2\n tau = self.Q10_func(self.gamma25, self.Q10_gamma, Tleaf)\n gamma = self.Oa / (2.0 * tau)\n\n return gamma","def itkBinaryContourImageFilterIUS2IUS2_cast(obj: 'itkLightObject') -> \"itkBinaryContourImageFilterIUS2IUS2 *\":\n return _itkBinaryContourImageFilterPython.itkBinaryContourImageFilterIUS2IUS2_cast(obj)","def f2(self,k1,k2,cosTheta):\n ans = (1.0 + self.mu) +(k1/k2 + k2/k1)*cosTheta + (1.0 - self.mu)*cosTheta**2\n return ans","def get_iou_cuboid(cu1, cu2):\n polygon_1 = Polygon([(cu1[0][0], cu1[0][1]), (cu1[1][0], cu1[1][1]), (cu1[2][0], cu1[2][1]), (cu1[3][0], cu1[3][1])])\n polygon_2 = Polygon([(cu2[0][0], cu2[0][1]), (cu2[1][0], cu2[1][1]), (cu2[2][0], cu2[2][1]), (cu2[3][0], cu2[3][1])])\n intersect_2d = polygon_1.intersection(polygon_2).area\n inter_vol = intersect_2d * max(0.0, min(cu1[0][2], cu2[0][2]) - max(cu1[4][2], cu2[4][2]))\n vol1 = polygon_1.area * (cu1[0][2] - cu1[4][2])\n vol2 = polygon_2.area * (cu2[0][2] - cu2[4][2])\n return inter_vol / (vol1 + vol2 - inter_vol)","def _upfirdn_2d_cuda(x, k, upx, upy, downx, downy, padx0, padx1, pady0, pady1, gpu=True):\r\n\r\n x = tf.convert_to_tensor(x)\r\n k = np.asarray(k, dtype=np.float32)\r\n majorDim, inH, inW, minorDim = x.shape.as_list()\r\n kernelH, kernelW = k.shape\r\n assert inW >= 1 and inH >= 1\r\n assert kernelW >= 1 and kernelH >= 1\r\n assert isinstance(upx, int) and isinstance(upy, int)\r\n assert isinstance(downx, int) and isinstance(downy, int)\r\n assert isinstance(padx0, int) and isinstance(padx1, int)\r\n assert isinstance(pady0, int) and isinstance(pady1, int)\r\n\r\n outW = (inW * upx + padx0 + padx1 - kernelW) // downx + 1\r\n outH = (inH * upy + pady0 + pady1 - kernelH) // downy + 1\r\n assert outW >= 1 and outH >= 1\r\n\r\n kc = tf.constant(k, dtype=x.dtype)\r\n gkc = tf.constant(k[::-1, ::-1], dtype=x.dtype)\r\n gpadx0 = kernelW - padx0 - 1\r\n gpady0 = kernelH - pady0 - 1\r\n gpadx1 = inW * upx - outW * downx + padx0 - upx + 1\r\n gpady1 = inH * upy - outH * downy + pady0 - upy + 1\r\n\r\n # add plugin _e_\r\n @tf.custom_gradient\r\n def func(x):\r\n y = Oncuda._get_plugin('upfirdn_2d').up_fir_dn2d(x=x, k=kc, upx=upx, upy=upy, downx=downx, downy=downy, padx0=padx0, padx1=padx1, pady0=pady0, pady1=pady1)\r\n y.set_shape([majorDim, outH, outW, minorDim])\r\n\r\n @tf.custom_gradient\r\n def grad(dy):\r\n dx = Oncuda._get_plugin('upfirdn_2d').up_fir_dn2d(x=dy, k=gkc, upx=downx, upy=downy, downx=upx, downy=upy, padx0=gpadx0, padx1=gpadx1, pady0=gpady0, pady1=gpady1)\r\n dx.set_shape([majorDim, inH, inW, minorDim])\r\n return dx, func\r\n return y, grad\r\n return func(x)","def GetReplaceCO2Link(self, query=None):\n other = self.Clone()\n co2_id = 'C00011'\n bic_id = 'C00288'\n other._ReplaceCompound(co2_id, bic_id) \n other.TryBalanceWithWater()\n link = other.GetHyperlink(query)\n return link","def Rgb_add(c1,c2):\n r = c1.r + c2.r\n r = max(0, min(1, r))\n\n g = c1.g + c2.g\n g = max(0, min(1, g))\n\n b = c1.b + c2.b\n b = max(0, min(1, b))\n return Rgb(r,g,b)","def prepend_operators(\n self, c2_prepared: Caffe2Rep, input_names: List[str]\n ) -> Tuple[Caffe2Rep, List[str]]:\n return onnx.add_feats_numericalize_ops(c2_prepared, self.vocab_map, input_names)"],"string":"[\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def I2_u2(self) -> complex:\\n return self.I2_u1() * cmath.rect(1, -120 / 180 * cmath.pi)\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def u2(self, q0, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=ROTATION_U2, qid=[q0], phase=alpha, phase1=beta, ctrl=ctrl)\\n return self\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def __add__(self, v2):\\n\\t\\treturn Vect2D(self._vec+v2._vec)\",\n \"def build_gate_2(gate, tags=None):\\n\\n def apply_constant_two_qubit_gate(psi, i, j, **gate_opts):\\n mtags = _merge_tags(tags, gate_opts)\\n psi.gate_(gate, (int(i), int(j)), tags=mtags, **gate_opts)\\n\\n return apply_constant_two_qubit_gate\",\n \"def test_U2(self, tol):\\n dev = qml.device(\\\"default.qubit\\\", wires=1)\\n\\n @qml.qnode(dev)\\n def circuit(x, y):\\n qml.QubitStateVector(1j * np.array([1, -1]) / np.sqrt(2), wires=[0])\\n qml.U2(x, y, wires=[0])\\n return qml.expval(qml.PauliX(0))\\n\\n phi = -0.234\\n lam = 0.654\\n\\n res = circuit(phi, lam)\\n expected = np.sin(lam) * np.sin(phi)\\n assert np.allclose(res, expected, atol=tol, rtol=0)\\n\\n grad_fn = autograd.grad(circuit, argnum=[0, 1])\\n res = grad_fn(phi, lam)\\n expected = np.array([np.sin(lam) * np.cos(phi), np.cos(lam) * np.sin(phi)])\\n assert np.allclose(res, expected, atol=tol, rtol=0)\",\n \"def enable_cl2_copy_ad9866(self):\\n self.write_versa5(0x62,0x3b) ## Clock2 CMOS1 output, 3.3V\\n self.write_versa5(0x2c,0x01) ## Enable aux output on clock 1\\n self.write_versa5(0x31,0x0c) ## Use clock1 aux output as input for clock2\\n self.write_versa5(0x63,0x01) ## Enable clock2\",\n \"def _ucbpe_2ucb(x):\\n mu, sigma = gp.eval(x, uncert_form='std')\\n return mu + 2 * beta_th * sigma\",\n \"def _ucbpe_2ucb(x):\\n mu, sigma = gp.eval(x, uncert_form='std')\\n return mu + 2 * beta_th * sigma\",\n \"def __add_boundary_contrib_operator2(self, bc, b_idx):\\n if bc is not None:\\n if bc.boundary_condition_type is configuration.BoundaryConditionType.ROBIN:\\n fe_op.add_value(self.operator2, -0.5 * (self.timestep ** 2) * bc.param, b_idx, b_idx)\\n elif bc.boundary_condition_type is configuration.BoundaryConditionType.ABSORBING:\\n fe_op.add_value(self.operator2, 0.5 * self.timestep * bc.param, b_idx, b_idx)\",\n \"def acumula_n2(self, n2, rodada):\\n self.n2[rodada].append(n2)\",\n \"def server1_add2 (c1, c2, pub):\\n #return (c1 + c2) % pub.n\\n return e_add(pub, c1, c2)\",\n \"def two_activation(self, output_reg):\\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\\n self._q_neuron.cx(self.inputs[0], self._output[output_reg])\\n self._q_neuron.cx(self.inputs[1], self._output[output_reg])\",\n \"def acumula_x2(self, x2, rodada):\\n self.x2[rodada].append(x2)\",\n \"def ts_add2 (c1,c2, pub):\\n \\n a = server1_add2(c1.alpha, c2.alpha, pub)\\n b = server2_add2(c1.beta, c2.beta, pub)\\n return CipherTwoServer(a,b)\",\n \"def acumula_ns2(self, ns2, rodada):\\n self.ns2[rodada].append(ns2)\",\n \"def owner2_add_funds(self, owner2_amount_in_msat: int):\\n BLOCKCHAIN_INSTANCE.apply_transaction(self.channel_state.channel_data.owner2, owner2_amount_in_msat)\\n self._state.channel_data.total_msat += (owner2_amount_in_msat * (1 - BLOCKCHAIN_INSTANCE.fee))\\n self._compute_amount_owner2_can_transfer_to_owner1()\",\n \"def chain_2(d2f_dg2, dg_dx, df_dg, d2g_dx2):\\r\\n return d2f_dg2*(dg_dx**2) + df_dg*d2g_dx2\",\n \"def acc_j2(U,comp):\\n if comp == 'x' or comp == 'y':\\n return (1 - 1.5*J2*(R/r(U))**2*(5*(U[2]/r(U))**2-1))\\n elif comp =='z':\\n return (1 - 1.5*J2*(R/r(U))**2*(5*(U[2]/r(U))**2-3))\",\n \"def x2(self):\\n return self._x + self._x2\",\n \"def gen_chip2_and_write(tup):\\n cfpath, gfpath, bbox, theta, new_size, filter_list = tup\\n chipBGR = ctool.compute_chip(gfpath, bbox, theta, new_size, filter_list)\\n #printDBG('write chip: %r' % cfpath)\\n gtool.imwrite(cfpath, chipBGR)\\n return cfpath\",\n \"def I2_u1(self) -> complex:\\n # \\\"Phase 2 current [A]\\\" is wrong. We need to calculate it ourselves\\n return - self.I1_u1() - self.I3_u1()\",\n \"def acumula_t2(self, t2, rodada):\\n self.t2[rodada].append(t2)\",\n \"def add_conv_type2(model, depth):\\n model.add(Convolution2D(depth, 3, 3, subsample=(1, 1)))\",\n \"def map_to_curve_G2(u: FQ2) -> G2Uncompressed:\\n (x, y, z) = optimized_swu_G2(u)\\n return iso_map_G2(x, y, z)\",\n \"def y2(self):\\n return self._y + self._y2\",\n \"def add_op2_data(cls, data, comment=''):\\n sid = data[0]\\n node = data[1]\\n mag = data[2]\\n g1 = data[3]\\n g2 = data[4]\\n return cls(sid, node, mag, g1, g2, comment=comment)\",\n \"def itkScalarConnectedComponentImageFilterIUC2IUC2_cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUC2IUC2_cast(*args)\",\n \"def shift_2_cust(self, sol_in2, cust, c_loc, curr_temp, sol_type2, sa_lns):\\r\\n\\r\\n route_ing = copy.deepcopy(sol_in2[c_loc[0]])\\r\\n route_new = route_ing\\r\\n move_to_route = c_loc[0]\\r\\n orgn_type1 = sol_type2[c_loc[0]]\\r\\n cust_folw = route_ing[c_loc[1]+1]\\r\\n origin_cost1 = check_violation(route_ing, orgn_type1)[1]\\r\\n route_ing.remove(cust) # remove c in the current route\\r\\n del route_ing[c_loc[1]] # remove customer following c\\r\\n new_type1 = route_type(route_ing)\\r\\n adjust_cost1 = check_violation(route_ing, new_type1)[1]\\r\\n best_cut_cost0 = -1000\\r\\n best_cut_cost = best_cut_cost0 # best cost cut of moving this customer\\r\\n for j, rou in enumerate(sol_in2):\\r\\n orgn_type2 = sol_type2[j]\\r\\n origin_cost2 = check_violation(rou, orgn_type2)[1]\\r\\n if j == c_loc[0]: # moving in the same route\\r\\n for k in range(1, len(route_ing)):\\r\\n if k == c_loc[1]:\\r\\n continue\\r\\n rou_test = route_ing[:k] + [cust, cust_folw] + route_ing[k:]\\r\\n if check_violation(rou_test, orgn_type2)[0]:\\r\\n adjust_cost2 = check_violation(rou_test, orgn_type2)[1]\\r\\n cost_cut_test = origin_cost1 - adjust_cost2\\r\\n if cost_cut_test > best_cut_cost:\\r\\n best_cut_cost = cost_cut_test\\r\\n route_new = rou_test\\r\\n move_to_route = j\\r\\n\\r\\n\\r\\n else: # moving to a different route\\r\\n for k in range(1, len(rou)):\\r\\n rou_test = rou[:k] + [cust, cust_folw] + rou[k:]\\r\\n if check_violation(rou_test, 5)[0]:\\r\\n new_type2 = route_type(rou_test)\\r\\n adjust_cost2 = check_violation(rou_test, new_type2)[1]\\r\\n cost_cut_test = origin_cost1 + origin_cost2 - adjust_cost1 - adjust_cost2\\r\\n if cost_cut_test > best_cut_cost:\\r\\n best_cut_cost = cost_cut_test\\r\\n route_new = rou_test\\r\\n move_to_route = j\\r\\n\\r\\n\\r\\n if best_cut_cost > 1e-5:\\r\\n # print('shift2 good', best_cut_cost)\\r\\n sol_in2[move_to_route] = route_new\\r\\n sol_type2[move_to_route] = route_type(route_new)\\r\\n if move_to_route != c_loc[0]: # moving to a different route\\r\\n sol_in2[c_loc[0]] = route_ing\\r\\n sol_type2[c_loc[0]] = route_type(route_ing)\\r\\n\\r\\n elif sa_lns and best_cut_cost < -1e-5:\\r\\n prb = random.uniform(0, 1)\\r\\n if np.exp(best_cut_cost / curr_temp) > prb:\\r\\n # print('shift2', best_cut_cost)\\r\\n sol_in2[move_to_route] = route_new\\r\\n sol_type2[move_to_route] = route_type(route_new)\\r\\n if move_to_route != c_loc[0]: # moving to a different route\\r\\n sol_in2[c_loc[0]] = route_ing\\r\\n sol_type2[c_loc[0]] = route_type(route_ing)\\r\\n\\r\\n # return sol_in2\\r\",\n \"def acumula_nq2(self, nq2, rodada):\\n self.nq2[rodada].append(nq2)\",\n \"def itkScalarConnectedComponentImageFilterIUL2IUL2_cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUL2IUL2_cast(*args)\",\n \"def acumula_w2(self, w2, rodada):\\n self.w2[rodada].append(w2)\",\n \"def enable_cl2_61p44(self):\\n self.write_versa5(0x62,0x3b) ## Clock2 CMOS1 output, 3.3V\\n self.write_versa5(0x2c,0x00) ## Disable aux output on clock 1\\n self.write_versa5(0x31,0x81) ## Use divider for clock2\\n ## VCO multiplier is shared for all outputs, set to 68 by firmware\\n ## VCO = 38.4*68 = 2611.2 MHz\\n ## There is a hardwired divide by 2 in the Versa 5 at the VCO output\\n ## VCO to Dividers = 2611.2 MHZ/2 = 1305.6\\n ## Target frequency of 61.44 requires dividers of 1305.6/61.44 = 21.25\\n ## Frational dividers are supported\\n ## Set integer portion of divider 21 = 0x15, 12 bits split across 2 registers\\n self.write_versa5(0x3d,0x01)\\n self.write_versa5(0x3e,0x50)\\n ## Set fractional portion, 30 bits, 2**24 * .25 = 0x400000\\n self.write_versa5(0x32,0x01) ## [29:22]\\n self.write_versa5(0x33,0x00) ## [21:14]\\n self.write_versa5(0x34,0x00) ## [13:6]\\n self.write_versa5(0x35,0x00) ## [5:0] and disable ss\\n self.write_versa5(0x63,0x01) ## Enable clock2\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def glucose_c2(self, m_t, g_t, t_G):\\n return -(1/t_G)*m_t+(1/t_G)*g_t\",\n \"def add_cf_arc(self, e1, e2, pr = 1.0):\\n if isinstance(e1, str):\\n e1 = self.get_element_by_name(e1)\\n if isinstance(e2, str):\\n e2 = self.get_element_by_name(e2) \\n a = cf_arc(e1, e2, pr)\\n e1.CO.add(a)\\n e2.CI.add(a)\\n self.ACF.append(a)\",\n \"def add_card_two(self, card):\\n self.add_card(card)\\n self._check_blackjack()\",\n \"def basic_block2(self, input_feats, name1, name2, is_train, use_batch_norm, c):\\n branch2a_feats = convolution_no_bias(input_feats, 1, 1, c, 1, 1, name1+'_branch2a')\\n branch2a_feats = batch_norm(branch2a_feats, name2+'_branch2a', is_train, use_batch_norm)\\n branch2a_feats = nonlinear(branch2a_feats, 'relu')\\n\\n branch2b_feats = convolution_no_bias(branch2a_feats, 3, 3, c, 1, 1, name1+'_branch2b')\\n branch2b_feats = batch_norm(branch2b_feats, name2+'_branch2b', is_train, use_batch_norm)\\n branch2b_feats = nonlinear(branch2b_feats, 'relu')\\n\\n branch2c_feats = convolution_no_bias(branch2b_feats, 1, 1, 4*c, 1, 1, name1+'_branch2c')\\n branch2c_feats = batch_norm(branch2c_feats, name2+'_branch2c', is_train, use_batch_norm)\\n\\n output_feats = input_feats + branch2c_feats\\n output_feats = nonlinear(output_feats, 'relu')\\n return output_feats\",\n \"def cue_integration_output(self, cue1, cue2):\\r\\n pi_left = cue1[0:8]\\r\\n\\r\\n pi_l = np.zeros((self.num_neuron, int(self.nt)))\\r\\n pi_l[:, int(self.ni):] = np.repeat(pi_left.reshape(self.num_neuron, 1), int(self.nt - self.ni), axis=1)\\r\\n\\r\\n pi_right = cue1[8:]\\r\\n pi_r = np.zeros((self.num_neuron, int(self.nt)))\\r\\n pi_r[:, int(self.ni):] = np.repeat(pi_right.reshape(self.num_neuron, 1), int(self.nt - self.ni), axis=1)\\r\\n\\r\\n v_left = cue2[0:8]\\r\\n v_l = np.zeros((self.num_neuron, int(self.nt)))\\r\\n v_l[:, int(self.ni):] = np.repeat(v_left.reshape(self.num_neuron, 1), int(self.nt - self.ni), axis=1)\\r\\n v_right = cue2[8:]\\r\\n v_r = np.zeros((self.num_neuron, int(self.nt)))\\r\\n v_r[:, int(self.ni):] = np.repeat(v_right.reshape(self.num_neuron, 1), int(self.nt - self.ni), axis=1)\\r\\n\\r\\n # generate the array for integration cells and the uniform inhibitory cell\\r\\n it_l = np.zeros((self.num_neuron, int(self.nt)))\\r\\n it_l[:, 0] = 0.1 * np.ones(self.num_neuron, )\\r\\n it_r = np.zeros((self.num_neuron, int(self.nt)))\\r\\n it_r[:, 0] = 0.1 * np.ones(self.num_neuron, )\\r\\n ul = np.zeros((1, int(self.nt)))\\r\\n ur = np.zeros((1, int(self.nt)))\\r\\n # iteration to the stable state\\r\\n for t in range(1, int(self.nt)):\\r\\n it_l[:, t] = it_l[:, t - 1] + (-it_l[:, t - 1] + np.max(\\r\\n [np.zeros((self.num_neuron,)),\\r\\n self.gammaE + np.dot(self.W_E_E, it_l[:, t - 1]) + self.W_E_I * ul[:, t - 1] + pi_l[:, t - 1]\\r\\n + v_l[:, t - 1]], axis=0)) * self.dt / self.tauE\\r\\n ul[:, t] = ul[:, t - 1] + (\\r\\n -ul[:, t - 1] + np.max([0, self.gammaI + self.W_I_E * np.sum(it_l[:, t - 1]) + self.W_I_I * ul[:, t - 1]],\\r\\n axis=0)) * self.dt / self.tauI\\r\\n\\r\\n it_r[:, t] = it_r[:, t - 1] + (-it_r[:, t - 1] + np.max(\\r\\n [np.zeros((self.num_neuron,)),\\r\\n self.gammaE + np.dot(self.W_E_E, it_r[:, t - 1]) + self.W_E_I * ur[:, t - 1] + pi_r[:, t - 1]\\r\\n + v_r[:, t - 1]], axis=0)) * self.dt / self.tauE\\r\\n ur[:, t] = ur[:, t - 1] + (\\r\\n -ur[:, t - 1] + np.max([0, self.gammaI + self.W_I_E * np.sum(it_r[:, t - 1]) + self.W_I_I * ur[:, t - 1]],\\r\\n axis=0)) * self.dt / self.tauI\\r\\n\\r\\n # get the final iteration as the output\\r\\n # update the neuron activation\\r\\n self.integration_neuron = np.hstack([it_l[:, -1], it_r[:, -1]])\\r\\n self.integration_neuron = noisy_sigmoid(self.integration_neuron, 5.0, 2.5, 0)\\r\\n self.inhibition_neuron = np.hstack([ul[-1], ur[-1]])\\r\\n\\r\\n return self.integration_neuron\",\n \"def _add(self, node1, node2):\\r\\n\\r\\n self._graph[node1].add(node2)\",\n \"def server2_add2 (b1, b2, pub):\\n return (b1 + b2) % pub.n\",\n \"def add_op2_data(cls, data, comment=''):\\n sid = data[0]\\n cid = data[1]\\n unused_a = data[2]\\n N = array(data[3:6])\\n mb = data[6]\\n scale = 1.\\n assert len(data) == 7\\n return GRAV(sid, scale, N, cid=cid, mb=mb, comment=comment)\",\n \"def ab2_cd(CFL, uold1, uold2, unew):\\n\\n unew[1:-1] = uold1[1:-1] - 0.75 * CFL * (uold1[2:] - uold1[:-2]) +\\\\\\n 0.25 * CFL * (uold2[2:] - uold2[:-2])\\n unew[-1] = uold1[-1] - 1.5 * CFL * (uold1[-1] - uold1[-2]) +\\\\\\n 0.5 * CFL * (uold2[-1] - uold2[-2])\\n\\n return unew\",\n \"def add_op2_data(cls, data, comment=''):\\n sid = data[0]\\n node = data[1]\\n mag = data[2]\\n g1 = data[3]\\n g2 = data[4]\\n g3 = data[5]\\n g4 = data[6]\\n return cls(sid, node, mag, g1, g2, g3, g4, comment=comment)\",\n \"def itkBinaryContourImageFilterIUC2IUC2_cast(obj: 'itkLightObject') -> \\\"itkBinaryContourImageFilterIUC2IUC2 *\\\":\\n return _itkBinaryContourImageFilterPython.itkBinaryContourImageFilterIUC2IUC2_cast(obj)\",\n \"def itkHuangThresholdImageFilterIUC2IUS2_cast(obj: 'itkLightObject') -> \\\"itkHuangThresholdImageFilterIUC2IUS2 *\\\":\\n return _itkHuangThresholdImageFilterPython.itkHuangThresholdImageFilterIUC2IUS2_cast(obj)\",\n \"def append_user_gate(self, user_gate):\\n self.translation['g_sect'].append(user_gate)\",\n \"def __init__(self, input0, input1, output) :\\n Gate.__init__(self, [input0,input1], output)\",\n \"def ADD (self, n1, n2):\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def upscale_2x_block(self, output_channel, filter_, activate):\\n return self.add_layer(upscale_2x_block, output_channel, filter_, activate)\",\n \"def cu_for_merge(self, best1, best2, undo=True):\\n\\t\\t#TODO - Might want to consider adding the instance to the merged node.\\n\\t\\tfirst = best1\\n\\t\\tsecond = best2\\n\\n\\t\\tif second < first:\\n\\t\\t\\ttemp = first \\n\\t\\t\\tfirst = second \\n\\t\\t\\tsecond = temp\\n\\n\\t\\tfirst_c = self.tree.children[first]\\n\\t\\tsecond_c = self.tree.children[second]\\n\\n\\t\\tnew_c = self.tree.makeTree(self.tree.root, self.tree)\\n\\t\\tnew_c.utility.update_counts_from_node(first_c)\\n\\t\\tnew_c.utility.update_counts_from_node(second_c)\\n\\n\\t\\tself.tree.children.pop(second)\\n\\t\\tself.tree.children.pop(first)\\n\\t\\tself.tree.children.append(new_c)\\n\\n\\t\\tcu = self.utility.category_utility()\\n\\n\\t\\tif undo:\\n\\t\\t\\tself.tree.children.pop()\\n\\t\\t\\tself.tree.children.insert(first,first_c)\\n\\t\\t\\tself.tree.children.insert(second,second_c)\\n\\t\\telse:\\n\\t\\t\\t# If we aren't undoing the merge then we have to add the leaves\\n\\t\\t\\tnew_c.children.append(first_c)\\n\\t\\t\\tfirst_c.parent = new_c\\n\\t\\t\\tnew_c.children.append(second_c)\\n\\t\\t\\tsecond_c.parent = new_c\\n\\t\\t\\tself.tree.mergedNodes.append([first_c, second_c])\\n\\t\\t\\tself.tree.splitMergeOrder.append(\\\"m\\\")\\n\\t\\t\\tfor m in self.tree.mergedNodes:\\n\\t\\t\\t\\tif len(m) > 2 and first_c in m and second_c in m:\\n\\t\\t\\t\\t\\tm.remove(first_c)\\n\\t\\t\\t\\t\\tm.remove(second_c)\\n\\t\\t\\t\\t\\tm.append(new_c)\\n\\t\\t\\tfor s in self.tree.splitNodes:\\n\\t\\t\\t\\tif len(s) > 2 and first_c in s and second_c in s:\\n\\t\\t\\t\\t\\ts.remove(first_c)\\n\\t\\t\\t\\t\\ts.remove(second_c)\\n\\t\\t\\t\\t\\ts.append(new_c)\\n\\t\\treturn cu\",\n \"def chain_2(d2f_dg2, dg_dx, df_dg, d2g_dx2):\\n if np.all(dg_dx==1.) and np.all(d2g_dx2 == 0):\\n return d2f_dg2\\n dg_dx_2 = np.clip(dg_dx, -np.inf, _lim_val_square)**2\\n #dg_dx_2 = dg_dx**2\\n return d2f_dg2*(dg_dx_2) + df_dg*d2g_dx2\",\n \"def fully_connected2(self):\\n self.weights2 = tf.get_variable(\\\"weights2\\\", shape=[14, 12],\\n initializer=tf.contrib.layers.xavier_initializer()) \\n self.bias2 = tf.get_variable('bias2',dtype = tf.float32, \\n initializer = tf.random_normal([1]))\\n self.hidden_layer2 = tf.matmul(self.data, self.weights2, name = 'hidden_layer2') + self.bias2\\n \\n self.data = tf.nn.relu(self.hidden_layer2)\\n \\n self.fully_connected3()\",\n \"def itkScalarConnectedComponentImageFilterIUS2IUS2_cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUS2IUS2_cast(*args)\",\n \"def setchi2(self,name,chi2):\\n if (name not in KFNode.names):\\n warning(' state not in node ',name)\\n self.chi2[name]=chi2\\n return\",\n \"def server1_add1(c1, c2, pub):\\n return add1 (c1, c2, pub)\",\n \"def EnableI2c(self):\\n\\n try:\\n\\n if os.path.exists('/sys/bus/i2c/devices/i2c-0/0-0060'):\\n result = \\\" - I2C device already enabled!\\\"\\n\\n else:\\n\\n with open('/sys/bus/i2c/devices/i2c-0/new_device', 'a') as f:\\n # 'echo '+i2c_device.driver+' '+i2c_device.addr+ '\\n f.write('mpl3115 0x60')\\n result = \\\" - I2C device enabled!\\\"\\n\\n LOG.info(result)\\n\\n except Exception as err:\\n LOG.error(\\\"Error enabling I2C (device1): \\\" + str(err))\",\n \"def GachaCraftNodeExcelAddGP1102(builder, GP1102):\\n return AddGP1102(builder, GP1102)\",\n \"def add_op2_data(cls, data, comment=''):\\n sid = data[0]\\n node = data[1]\\n cid = data[2]\\n mag = data[3]\\n xyz = array(data[4:7])\\n return cls(sid, node, mag, xyz, cid=cid, comment=comment)\",\n \"def imu_init(self, chain: machine.I2C = None, freq=400000, debug=False):\\n if self.antenny_config.get(\\\"use_bno055\\\"):\\n print(\\\"use_bno055 found in config: {}\\\".format(self.antenny_config.get_name()))\\n if chain is None:\\n i2c_bno_scl = self.antenny_config.get(\\\"i2c_bno_scl\\\")\\n i2c_bno_sda = self.antenny_config.get(\\\"i2c_bno_sda\\\")\\n self.i2c_bno = self.i2c_init(1, i2c_bno_scl, i2c_bno_sda, freq=freq)\\n else:\\n self.i2c_bno = chain\\n self.imu = Bno055ImuController(\\n self.i2c_bno,\\n crystal=False,\\n address=self.antenny_config.get(\\\"i2c_bno_address\\\"),\\n sign=(0, 0, 0)\\n )\\n self.imu_load()\\n self.imu.upload_calibration_profile()\\n print(\\\"IMU connected\\\")\\n elif self.antenny_config.get(\\\"use_bno08x_i2c\\\"):\\n print(\\\"use_bno08x_i2c found in config: {}\\\".format(self.antenny_config.get_name()))\\n if chain is None:\\n i2c_bno_scl = self.antenny_config.get(\\\"i2c_bno_scl\\\")\\n i2c_bno_sda = self.antenny_config.get(\\\"i2c_bno_sda\\\")\\n self.i2c_bno = self.i2c_init(1, i2c_bno_scl, i2c_bno_sda, freq=freq)\\n else:\\n self.i2c_bno = chain\\n ps0 = machine.Pin(self.antenny_config.get(\\\"bno_ps0\\\"), machine.Pin.OUT)\\n ps1 = machine.Pin(self.antenny_config.get(\\\"bno_ps1\\\"), machine.Pin.OUT)\\n reset = machine.Pin(self.antenny_config.get(\\\"bno_rst\\\"), machine.Pin.OUT)\\n ps0.off()\\n ps1.off()\\n self.imu = Bno08xImuController(\\n self.i2c_bno,\\n debug=debug,\\n reset=reset\\n )\\n self.imu.reset_calibration()\\n print(\\\"IMU connected\\\")\\n elif self.antenny_config.get(\\\"use_bno08x_rvc\\\"):\\n print(\\\"use_bno08x_rvc found in config: {}\\\".format(self.antenny_config.get_name()))\\n tx = self.antenny_config.get(\\\"i2c_bno_scl\\\")\\n rx = self.antenny_config.get(\\\"i2c_bno_sda\\\")\\n reset = machine.Pin(self.antenny_config.get(\\\"bno_rst\\\"), machine.Pin.OUT)\\n ps0 = self.antenny_config.get(\\\"bno_ps0\\\")\\n ps1 = self.antenny_config.get(\\\"bno_ps1\\\")\\n if ps0 is not None and ps1 is not None:\\n ps0 = machine.Pin(ps0, machine.Pin.OUT)\\n ps1 = machine.Pin(ps1, machine.Pin.OUT)\\n ps0.on()\\n ps1.off()\\n uart_bno = self.uart_init(1, rx, tx, baud=115200)\\n self.imu = Bno08xUARTImuController(\\n uart_bno,\\n reset=reset\\n )\\n self.imu.reset_calibration()\\n time.sleep(.5)\\n self.imu.start()\\n print(\\\"IMU connected\\\")\\n else:\\n self.imu = MockImuController()\\n print(\\\"According to your config, ou do not have an IMU connected\\\")\\n return self.imu\",\n \"def cu1(self, q0, q1, alpha=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U1, qid=[q0,q1], phase=alpha, ctrl=ctrl)\\n return self\",\n \"def test_circuit_decompose(self):\\n dec = TwoQubitDecomposeUpToDiagonal()\\n u4 = scipy.stats.unitary_group.rvs(4, random_state=47)\\n dmat, circ2cx = dec(u4)\\n\\n qc1 = QuantumCircuit(2)\\n qc1.append(UnitaryGate(u4), range(2))\\n\\n qc2 = QuantumCircuit(2)\\n qc2.compose(circ2cx, range(2), front=False, inplace=True)\\n qc2.append(UnitaryGate(dmat), range(2))\\n\\n self.assertEqual(Operator(u4), Operator(qc1))\\n self.assertEqual(Operator(qc1), Operator(qc2))\",\n \"def augend_2(exp):\\n a2 = cddr(exp) # (a2 a3 ...)\\n rests = cdr(a2) # (a3 ... )\\n if isNull(rests):\\n return car(a2)\\n else:\\n restp = convertToPythonList(cdr(rests))\\n return make_sum_2(car(a2), car(rests), *restp)\",\n \"def l2_reg_cost(cost):\\n\\n return cost + tf.losses.get_regularization_losses()\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def sendTwoC(self):\\n startC = self.countCannibalOnStart()\\n if startC < 2:\\n return None\\n else:\\n newStart = self.start[0:2] + str(startC-2) + self.start[3]\\n newEnd = self.end[0:2] + str(5-startC) + self.end[3]\\n return MissionaryState(newStart,newEnd,\\\"sendTwoC\\\")\",\n \"def _gen_u2(phi, lmbda):\\n return _gen_u(0, phi, lmbda)\",\n \"def AssignAddHybrid2d(output, value, target=utils.CCE):\\n for i in range(output.shape[0]):\\n for j in range(output.shape[1]):\\n output[i, j] = output[i, j] + value[i, j]\\n\\n return output\",\n \"def l2_reg_cost(cost):\\n return cost + tf.losses.get_regularization_losses()\",\n \"def l2_reg_cost(cost):\\n return cost + tf.losses.get_regularization_losses()\",\n \"def l2_reg_cost(cost):\\n return cost + tf.losses.get_regularization_losses()\",\n \"def addInPlace(self, value1, value2):\\n raise NotImplementedError\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\\n return self\",\n \"def Controlled2(U):\\n '''Generalized controlled unitary tensor construction\\n Parameters:\\n -----------\\n U: input tensor which is assumed to be a square Matrix\\n\\n Returns:\\n --------\\n Controlled unitary\\n\\n '''\\n shp = U.shape\\n new_ten = scipy.linalg.block_diag(np.eye(*shp), U)\\n return new_ten.reshape(2, shp[0], 2, shp[1], 2, shp[2])\",\n \"def __add__(self, polynomial_2: Polynomial) -> Polynomial:\\n\\n if self.degree > polynomial_2.degree:\\n coefficients = self.coefficients[:]\\n for i in range(polynomial_2.degree + 1):\\n coefficients[i] += polynomial_2.coefficients[i]\\n return Polynomial(self.degree, coefficients)\\n else:\\n coefficients = polynomial_2.coefficients[:]\\n for i in range(self.degree + 1):\\n coefficients[i] += self.coefficients[i]\\n return Polynomial(polynomial_2.degree, coefficients)\",\n \"def GachaCraftNodeExcelAddLv2Exp(builder, Lv2Exp):\\n return AddLv2Exp(builder, Lv2Exp)\",\n \"def set_action2(self, action2, feature):\\n assert feature not in self._action2\\n self._action2[feature] = action2\",\n \"def __init__(self, input_dim, hidden_dim, bias=True, node_n=48, dtype=float):\\n super(GCNGRU_Block, self).__init__()\\n self.hidden_dim = hidden_dim\\n self.node_n = node_n\\n\\n self.gc1 = GraphConvolution(input_dim + hidden_dim, 2*self.hidden_dim, node_n=node_n, bias=bias)\\n self.gc2 = GraphConvolution(input_dim + hidden_dim, self.hidden_dim, node_n=node_n, bias=bias)\",\n \"def SetKernel(self, _arg: 'itkFlatStructuringElement2') -> \\\"void\\\":\\n return _itkClosingByReconstructionImageFilterPython.itkClosingByReconstructionImageFilterIUC2IUC2SE2_SetKernel(self, _arg)\",\n \"def __add__(self, other):\\n return Vec2d(self.v[0] + other[0], self.v[1] + other[1])\",\n \"def __add__(self, other):\\n try:\\n ox, oy = other\\n except Exception:\\n return NotImplemented\\n return tuple.__new__(Vec2, (self[0] + ox, self[1] + oy))\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\\n return self\",\n \"def complex_sum(c_1,c_2):\\n return c_1 + c_2\",\n \"def _add_grover_step_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n _add_2_bit_oracle_without_ancilla_1_0(qc, register) # Oracle\\n add_grover_reflection_no_ancilla(qc, register) # Reflection\",\n \"def addMe2Me(x):\\n return x+x\",\n \"def __add__(self, second_rule):\\n return AndRule(self, second_rule)\",\n \"def costInsertion(el1,el2):\\r\\n return 2\",\n \"def JC(lcsc1c2, Pc1, Pc2):\\n\\n JC = 1/(2*lcsc1c2 - (Pc1 + Pc2))\\n return JC\",\n \"def calc_CO2_compensation_point(self, Tleaf):\\n\\n # Rubisco specificity for CO2 relative to O2\\n tau = self.Q10_func(self.gamma25, self.Q10_gamma, Tleaf)\\n gamma = self.Oa / (2.0 * tau)\\n\\n return gamma\",\n \"def itkBinaryContourImageFilterIUS2IUS2_cast(obj: 'itkLightObject') -> \\\"itkBinaryContourImageFilterIUS2IUS2 *\\\":\\n return _itkBinaryContourImageFilterPython.itkBinaryContourImageFilterIUS2IUS2_cast(obj)\",\n \"def f2(self,k1,k2,cosTheta):\\n ans = (1.0 + self.mu) +(k1/k2 + k2/k1)*cosTheta + (1.0 - self.mu)*cosTheta**2\\n return ans\",\n \"def get_iou_cuboid(cu1, cu2):\\n polygon_1 = Polygon([(cu1[0][0], cu1[0][1]), (cu1[1][0], cu1[1][1]), (cu1[2][0], cu1[2][1]), (cu1[3][0], cu1[3][1])])\\n polygon_2 = Polygon([(cu2[0][0], cu2[0][1]), (cu2[1][0], cu2[1][1]), (cu2[2][0], cu2[2][1]), (cu2[3][0], cu2[3][1])])\\n intersect_2d = polygon_1.intersection(polygon_2).area\\n inter_vol = intersect_2d * max(0.0, min(cu1[0][2], cu2[0][2]) - max(cu1[4][2], cu2[4][2]))\\n vol1 = polygon_1.area * (cu1[0][2] - cu1[4][2])\\n vol2 = polygon_2.area * (cu2[0][2] - cu2[4][2])\\n return inter_vol / (vol1 + vol2 - inter_vol)\",\n \"def _upfirdn_2d_cuda(x, k, upx, upy, downx, downy, padx0, padx1, pady0, pady1, gpu=True):\\r\\n\\r\\n x = tf.convert_to_tensor(x)\\r\\n k = np.asarray(k, dtype=np.float32)\\r\\n majorDim, inH, inW, minorDim = x.shape.as_list()\\r\\n kernelH, kernelW = k.shape\\r\\n assert inW >= 1 and inH >= 1\\r\\n assert kernelW >= 1 and kernelH >= 1\\r\\n assert isinstance(upx, int) and isinstance(upy, int)\\r\\n assert isinstance(downx, int) and isinstance(downy, int)\\r\\n assert isinstance(padx0, int) and isinstance(padx1, int)\\r\\n assert isinstance(pady0, int) and isinstance(pady1, int)\\r\\n\\r\\n outW = (inW * upx + padx0 + padx1 - kernelW) // downx + 1\\r\\n outH = (inH * upy + pady0 + pady1 - kernelH) // downy + 1\\r\\n assert outW >= 1 and outH >= 1\\r\\n\\r\\n kc = tf.constant(k, dtype=x.dtype)\\r\\n gkc = tf.constant(k[::-1, ::-1], dtype=x.dtype)\\r\\n gpadx0 = kernelW - padx0 - 1\\r\\n gpady0 = kernelH - pady0 - 1\\r\\n gpadx1 = inW * upx - outW * downx + padx0 - upx + 1\\r\\n gpady1 = inH * upy - outH * downy + pady0 - upy + 1\\r\\n\\r\\n # add plugin _e_\\r\\n @tf.custom_gradient\\r\\n def func(x):\\r\\n y = Oncuda._get_plugin('upfirdn_2d').up_fir_dn2d(x=x, k=kc, upx=upx, upy=upy, downx=downx, downy=downy, padx0=padx0, padx1=padx1, pady0=pady0, pady1=pady1)\\r\\n y.set_shape([majorDim, outH, outW, minorDim])\\r\\n\\r\\n @tf.custom_gradient\\r\\n def grad(dy):\\r\\n dx = Oncuda._get_plugin('upfirdn_2d').up_fir_dn2d(x=dy, k=gkc, upx=downx, upy=downy, downx=upx, downy=upy, padx0=gpadx0, padx1=gpadx1, pady0=gpady0, pady1=gpady1)\\r\\n dx.set_shape([majorDim, inH, inW, minorDim])\\r\\n return dx, func\\r\\n return y, grad\\r\\n return func(x)\",\n \"def GetReplaceCO2Link(self, query=None):\\n other = self.Clone()\\n co2_id = 'C00011'\\n bic_id = 'C00288'\\n other._ReplaceCompound(co2_id, bic_id) \\n other.TryBalanceWithWater()\\n link = other.GetHyperlink(query)\\n return link\",\n \"def Rgb_add(c1,c2):\\n r = c1.r + c2.r\\n r = max(0, min(1, r))\\n\\n g = c1.g + c2.g\\n g = max(0, min(1, g))\\n\\n b = c1.b + c2.b\\n b = max(0, min(1, b))\\n return Rgb(r,g,b)\",\n \"def prepend_operators(\\n self, c2_prepared: Caffe2Rep, input_names: List[str]\\n ) -> Tuple[Caffe2Rep, List[str]]:\\n return onnx.add_feats_numericalize_ops(c2_prepared, self.vocab_map, input_names)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.63387585","0.60368437","0.59752756","0.5968923","0.5940657","0.58799356","0.5746586","0.5703197","0.56583536","0.56360215","0.55208397","0.55208397","0.54839325","0.54210496","0.5384276","0.53551805","0.5338436","0.53347147","0.53148663","0.528607","0.52110845","0.5173364","0.5155979","0.5130234","0.510886","0.5094067","0.5078864","0.5061639","0.5050256","0.50334674","0.5031138","0.5026039","0.50034887","0.5002777","0.49978447","0.4996723","0.4989537","0.4982089","0.4978359","0.4954198","0.49480593","0.49380705","0.49286523","0.49261197","0.48970845","0.48857668","0.48801506","0.48790205","0.48715666","0.48665318","0.4864252","0.48426595","0.48346135","0.48287752","0.4823998","0.48205888","0.48174617","0.4816432","0.47819746","0.47776118","0.4776948","0.47612423","0.4757027","0.47556975","0.4749511","0.4741741","0.47394317","0.473783","0.47295266","0.47230408","0.47199938","0.47187462","0.47161752","0.47161752","0.47161752","0.47117308","0.47085285","0.47082403","0.47045243","0.4699186","0.46875405","0.46850768","0.46809384","0.46782017","0.46679333","0.46670341","0.46524885","0.46493298","0.46472308","0.4646859","0.4641775","0.46377042","0.4636444","0.46341142","0.46293935","0.4627711","0.46160117","0.46159896","0.46066862","0.45984378"],"string":"[\n \"0.63387585\",\n \"0.60368437\",\n \"0.59752756\",\n \"0.5968923\",\n \"0.5940657\",\n \"0.58799356\",\n \"0.5746586\",\n \"0.5703197\",\n \"0.56583536\",\n \"0.56360215\",\n \"0.55208397\",\n \"0.55208397\",\n \"0.54839325\",\n \"0.54210496\",\n \"0.5384276\",\n \"0.53551805\",\n \"0.5338436\",\n \"0.53347147\",\n \"0.53148663\",\n \"0.528607\",\n \"0.52110845\",\n \"0.5173364\",\n \"0.5155979\",\n \"0.5130234\",\n \"0.510886\",\n \"0.5094067\",\n \"0.5078864\",\n \"0.5061639\",\n \"0.5050256\",\n \"0.50334674\",\n \"0.5031138\",\n \"0.5026039\",\n \"0.50034887\",\n \"0.5002777\",\n \"0.49978447\",\n \"0.4996723\",\n \"0.4989537\",\n \"0.4982089\",\n \"0.4978359\",\n \"0.4954198\",\n \"0.49480593\",\n \"0.49380705\",\n \"0.49286523\",\n \"0.49261197\",\n \"0.48970845\",\n \"0.48857668\",\n \"0.48801506\",\n \"0.48790205\",\n \"0.48715666\",\n \"0.48665318\",\n \"0.4864252\",\n \"0.48426595\",\n \"0.48346135\",\n \"0.48287752\",\n \"0.4823998\",\n \"0.48205888\",\n \"0.48174617\",\n \"0.4816432\",\n \"0.47819746\",\n \"0.47776118\",\n \"0.4776948\",\n \"0.47612423\",\n \"0.4757027\",\n \"0.47556975\",\n \"0.4749511\",\n \"0.4741741\",\n \"0.47394317\",\n \"0.473783\",\n \"0.47295266\",\n \"0.47230408\",\n \"0.47199938\",\n \"0.47187462\",\n \"0.47161752\",\n \"0.47161752\",\n \"0.47161752\",\n \"0.47117308\",\n \"0.47085285\",\n \"0.47082403\",\n \"0.47045243\",\n \"0.4699186\",\n \"0.46875405\",\n \"0.46850768\",\n \"0.46809384\",\n \"0.46782017\",\n \"0.46679333\",\n \"0.46670341\",\n \"0.46524885\",\n \"0.46493298\",\n \"0.46472308\",\n \"0.4646859\",\n \"0.4641775\",\n \"0.46377042\",\n \"0.4636444\",\n \"0.46341142\",\n \"0.46293935\",\n \"0.4627711\",\n \"0.46160117\",\n \"0.46159896\",\n \"0.46066862\",\n \"0.45984378\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.70731705"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81758,"cells":{"query":{"kind":"string","value":"add CU3 gate (controlled U3 gate)."},"document":{"kind":"string","value":"def cu3(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U3, qid=[q0,q1], phase=alpha, phase1=beta,\n phase2=gamma, ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def u3(self, q0, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_U3, qid=[q0], phase=alpha, phase1=beta,\n phase2=gamma, ctrl=ctrl)\n return self","def test_special_U3(self):\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \"U3\", {})\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \"U3\", {\"u3\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.2, 0.0).to_matrix(), \"U3\", {\"u3\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.0, 0.2).to_matrix(), \"U3\", {\"u3\": 1})\n self.check_oneq_special_cases(U3Gate(0.11, 0.27, 0.3).to_matrix(), \"U3\", {\"u3\": 1})","def __iadd__( self, vector3 ):\n return self.add( vector3 )","def test_U3(self, tol):\n dev = qml.device(\"default.qubit\", wires=1)\n\n @qml.qnode(dev)\n def circuit(x, y, z):\n qml.QubitStateVector(1j * np.array([1, -1]) / np.sqrt(2), wires=[0])\n qml.U3(x, y, z, wires=[0])\n return qml.expval(qml.PauliX(0))\n\n theta = 0.543\n phi = -0.234\n lam = 0.654\n\n res = circuit(theta, phi, lam)\n expected = np.sin(lam) * np.sin(phi) - np.cos(theta) * np.cos(lam) * np.cos(phi)\n assert np.allclose(res, expected, atol=tol, rtol=0)\n\n grad_fn = autograd.grad(circuit, argnum=[0, 1, 2])\n res = grad_fn(theta, phi, lam)\n expected = np.array(\n [\n np.sin(theta) * np.cos(lam) * np.cos(phi),\n np.cos(theta) * np.cos(lam) * np.sin(phi) + np.sin(lam) * np.cos(phi),\n np.cos(theta) * np.sin(lam) * np.cos(phi) + np.cos(lam) * np.sin(phi),\n ]\n )\n assert np.allclose(res, expected, atol=tol, rtol=0)","def I3_u3(self) -> complex:\n return self.I3_u1() * cmath.rect(1, 120 / 180 * cmath.pi)","def _r_u3(angle: tf.Tensor) -> tf.Tensor:\n zero = tf.constant(0, dtype=tf.float64)\n cos = tf.cos(tf.multiply(angle[0], tf.constant(0.5, dtype=tf.float64)))\n sin = tf.sin(tf.multiply(angle[0], tf.constant(0.5, dtype=tf.float64)))\n sin_complex = tf.complex(sin, zero)\n cos_complex = tf.complex(cos, zero)\n exponent_phi = tf.complex(zero, angle[1])\n exp_phi = tf.exp(exponent_phi)\n exponent_lambda = tf.complex(zero, angle[2])\n exp_lambda = tf.exp(exponent_lambda)\n exponent_lambda_phi = tf.complex(zero, angle[1] + angle[2])\n exp_lambda_phi = tf.exp(exponent_lambda_phi)\n ru3 = tf.stack([[cos_complex, -tf.multiply(exp_lambda, sin_complex)],\n [tf.multiply(exp_phi, sin_complex), tf.multiply(exp_lambda_phi, cos_complex)]])\n\n return ru3","def three_activation(self, output_reg):\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\n self._q_neuron.ccx(self.inputs[1], self.inputs[2], self._output[output_reg])\n self._q_neuron.ccx(self.inputs[0], self.inputs[2], self._output[output_reg])","def S3_u32(self) -> complex:\n return complex(\n self._addr(self.defined_registers['Phase 3 power [W]']['addr']),\n self._addr(self.defined_registers['Phase 3 volt amps reactive [VAr]']['addr']),\n )","def L3G_acquisition(add):\n\n # control register\n CTRL_REG1 = 0x20\n CTRL_REG4 = 0x23\n LOW_ODR = 0x39\n FIFO_CTRL = 0x2e\n # output register\n OUT_X_L = 0x28\n OUT_X_H = 0x29\n OUT_Y_L = 0x2a\n OUT_Y_H = 0x2b\n OUT_Z_L = 0x2c\n OUT_Z_H = 0x2d\n\n # low odr mode, 50Hz, 2000 dps full scale\n bus.write_byte_data(add, CTRL_REG1, 0b10001111)\n bus.write_byte_data(add, CTRL_REG4, 0b00110000)\n bus.write_byte_data(add, LOW_ODR, 0b00000001)\n bus.write_byte_data(add, FIFO_CTRL, 0b01000000)\n\n # accelerator accumulate\n while True:\n uint16_gx = (bus.read_byte_data(add, OUT_X_H) << 8) + \\\n bus.read_byte_data(add, OUT_X_L)\n uint16_gy = (bus.read_byte_data(add, OUT_Y_H) << 8) + \\\n bus.read_byte_data(add, OUT_Y_L)\n uint16_gz = (bus.read_byte_data(add, OUT_Z_H) << 8) + \\\n bus.read_byte_data(add, OUT_Z_L)\n\n gx = twos_comp(uint16_gx, 16)\n gy = twos_comp(uint16_gy, 16)\n gz = twos_comp(uint16_gz, 16)\n\n yield [gx, gy, gz]","def add( self, vector3 ):\n self._coords[:3] += vector3._coords[:3]\n return self","def I3_u32(self) -> complex:\n return (self.S3_u32() / self.U23()).conjugate()","def chain_3(d3f_dg3, dg_dx, d2f_dg2, d2g_dx2, df_dg, d3g_dx3):\r\n return d3f_dg3*(dg_dx**3) + 3*d2f_dg2*dg_dx*d2g_dx2 + df_dg*d3g_dx3","def add_three(a, b, c):\n return a + b + c","def x3(self):\n return self._x + self._x3","def getU3(state):\n\n # TODO : do the verifictions of the above constraints\n\n theta=2*math.acos(state[0])\n phi=0\n lam=0\n\n if state[1]<0: theta = -theta\n\n # U3=np.array([\n # [math.cos(theta/2) , np.exp(-1j*lam)*math.sin(theta/2)], \n # [np.exp(1j*phi)*math.sin(theta/2), np.exp(1j*(phi+lam))*math.cos(theta/2)]\n # ])\n # print (U3)\n # print (U3@np.array([[1],[0]]))\n\n return [theta, phi, lam]","def computeCRCD3(self, u0, u1, u2, u3, u4, u5, u6, u7):\n tmp = u0\n bs = [u1, u2, u3, u4, u5, u6, u7]\n for val in bs:\n for j in range(16):\n if tmp & (1 << 15):\n tmp <<= 1\n if val & (1 << 15):\n tmp += 1\n tmp ^= 0x8005\n else:\n tmp <<= 1\n if val & (1 << 15):\n tmp += 1\n val <<= 1\n tmp &= 0xffff\n return tmp","def test_special_U(self):\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \"U\", {})\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \"U\", {\"u\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.2, 0.0).to_matrix(), \"U\", {\"u\": 1})\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.0, 0.2).to_matrix(), \"U\", {\"u\": 1})\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \"U\", {\"u\": 1})","def itkScalarConnectedComponentImageFilterIUL3IUL3_cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUL3IUL3_cast(*args)","def itkScalarConnectedComponentImageFilterIUC3IUC3_cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUC3IUC3_cast(*args)","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def I3_u1(self) -> complex:\n # Should match in amplitude with \"Phase 3 current [A]\"\n # Convert from relative to U32 -> relative to U1\n return - (self.I3_u32() * cmath.rect(1, 90 / 180 * cmath.pi))","def AssignAddHybrid3d(output, value, target=utils.CCE):\n for i in range(output.shape[0]):\n for j in range(output.shape[1]):\n for k in range(output.shape[2]):\n output[i, j, k] = output[i, j, k] + value[i, j, k]\n\n return output","def chain_3(d3f_dg3, dg_dx, d2f_dg2, d2g_dx2, df_dg, d3g_dx3):\n if np.all(dg_dx==1.) and np.all(d2g_dx2==0) and np.all(d3g_dx3==0):\n return d3f_dg3\n dg_dx_3 = np.clip(dg_dx, -np.inf, _lim_val_cube)**3\n return d3f_dg3*(dg_dx_3) + 3*d2f_dg2*dg_dx*d2g_dx2 + df_dg*d3g_dx3","def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\n return self","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def step3(self):\n\t\tif self.b[self.k] == 'e':\n\t\t\tif self.ends(\"icate\"):\t self.r(\"ic\")\n\t\t\telif self.ends(\"ative\"): self.r(\"\")\n\t\t\telif self.ends(\"alize\"): self.r(\"al\")\n\t\telif self.b[self.k] == 'i':\n\t\t\tif self.ends(\"iciti\"):\t self.r(\"ic\")\n\t\telif self.b[self.k] == 'l':\n\t\t\tif self.ends(\"ical\"):\t self.r(\"ic\")\n\t\t\telif self.ends(\"ful\"):\t self.r(\"\")\n\t\telif self.b[self.k] == 's':\n\t\t\tif self.ends(\"ness\"):\t self.r(\"\")","def itkScalarConnectedComponentImageFilterIUS3IUS3_cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUS3IUS3_cast(*args)","def convert_gcm3_AMUA3(den_gmc3):\n return den_gmc3*const_avo/10.0","def vs3_func_3(ns, traj, vs_def_beads_ids, vs_params):\n i, j, k = vs_def_beads_ids\n ang_deg, d = vs_params # degrees, nm\n ang_rad = np.deg2rad(ang_deg) # retrieve radians\n d = d * 10 # retrieve amgstrom for MDA\n\n for ts in ns.aa2cg_universe.trajectory:\n pos_i = ns.aa2cg_universe.atoms[i].position\n pos_j = ns.aa2cg_universe.atoms[j].position\n pos_k = ns.aa2cg_universe.atoms[k].position\n r_ij = pos_j - pos_i\n r_jk = pos_k - pos_j\n comb_ijk = r_jk - (np.dot(r_ij, r_jk) / np.dot(r_ij, r_ij)) * r_ij\n traj[ts.frame] = pos_i + d * np.cos(ang_rad) * (r_ij / mda.lib.mdamath.norm(r_ij)) + d * np.sin(ang_rad) * (\n comb_ijk / mda.lib.mdamath.norm(comb_ijk))","def refugia_adj_3(params, ns):\n #11 parameters \n nu1, nuA, nu2, nu3, m1_1, m2_1, m2_2, m2_3, T1a, T1b, T2 = params\n sts = moments.LinearSystem_1D.steady_state_1D(ns[0] + ns[1] + ns[2])\n fs = moments.Spectrum(sts)\n fs = moments.Manips.split_1D_to_2D(fs, ns[0], ns[1] + ns[2])\n ## Population function and migration matrix for T1a\n nu_T1 = [nu1, nuA]\n fs.integrate(nu_T1, T1a)\n ## Population function and migration matrix for T1b\n mig1 = numpy.array([[0, m1_1],[m1_1, 0]])\n fs.integrate(nu_T1, T1b, m=mig1) \n fs = moments.Manips.split_2D_to_3D_2(fs, ns[1], ns[2])\n ## Population function and migration matrix for T2\n nu_T2 = [nu1, nu2, nu3]\n mig2 = numpy.array([[0, m2_1, m2_3],[m2_1, 0, m2_2], [m2_3, m2_2, 0]]) \n fs.integrate(nu_T2, T2, m=mig2)\n return fs","def itkHuangThresholdImageFilterIUC3IUS3_cast(obj: 'itkLightObject') -> \"itkHuangThresholdImageFilterIUC3IUS3 *\":\n return _itkHuangThresholdImageFilterPython.itkHuangThresholdImageFilterIUC3IUS3_cast(obj)","def loss_step3(self, y, u, v):\n uv = -0.5 * (y.float().t() @ (u + v))\n return uv","def correlation_4op_3t(self, rho0, oplist, signature, tau):\n\n\n if len(oplist) != 4:\n raise ValueError('Number of operators is not 4.')\n\n a = operator_to_superoperator(oplist[0], signature[0])\n b = operator_to_superoperator(oplist[1], signature[1])\n c = operator_to_superoperator(oplist[2], signature[2])\n d = operator_to_superoperator(oplist[3], signature[3])\n\n for _ in oplist:\n if issparse(_):\n _ = _.toarray()\n\n\n # nmax = max(len(tau3), len(tau2), len(tau1))\n\n # g = -1j * (tau > 0) * self.propagator(tau)\n # G = np.zeros((self.dim, self.dim, len(tau)))\n\n # for n, elem in enumerate(g):\n # G[:,:, n] = g[n]\n\n if self.G is None:\n self.propagator(tau)\n\n G = self.G\n\n # unit operator in Liouville space\n N = self.dim\n idm = self.idm(sp=False)\n\n # print(d.shape, dm2vec(rho0.toarray()).shape)\n if issparse(rho0):\n rho = d.dot(dm2vec(rho0.toarray()))\n else:\n rho = d.dot(dm2vec(rho0))\n\n # print(type(rho), rho.shape)\n\n if issparse(rho): rho = rho.toarray()\n\n tmp = np.tensordot(G, rho, axes=((1), (0)))\n tmp = c.dot(tmp)\n tmp = np.tensordot(G, tmp, axes=([1], [0])) # ajk\n\n # tmp = np.einsum('dcj, ca, abk, b -> djk', G, c, G, rho)\n\n\n '''\n Scipy sparse matrix does not support dimensions more than 2, so\n ndarray has to be used for the tensor products.\n\n This can be improved by using sparse package.\n '''\n tmp = np.tensordot(b.todense(), tmp, axes=([1], [0]))\n # tmp = b.todense().dot(tmp)\n\n tmp = np.tensordot(G, tmp, axes=([1], [0]))\n\n return oe.contract('a, ab, bijk -> ijk', idm, a.todense(), tmp)\n\n # corr = np.einsum('a, ab, bck, bc, cdj, de, efi, f ->kji', idm, \\\n # left(a), G, left(b), left(c), G, left(d).dot(dm2vec(rho0))\n\n # return","def create_p3_feature(C3, C4, C5, feature_size=256):\n P5 = keras.layers.Conv2D(feature_size, kernel_size=1, strides=1, padding='same', name='C5_reduced')(C5)\n P5_upsampled = layers.UpsampleLike(name='P5_upsampled')([P5, C4])\n\n # add P5 elementwise to C4\n P4 = keras.layers.Conv2D(feature_size, kernel_size=1, strides=1, padding='same', name='C4_reduced')(C4)\n P4 = keras.layers.Add(name='P4_merged')([P5_upsampled, P4])\n P4_upsampled = layers.UpsampleLike(name='P4_upsampled')([P4, C3])\n\n # add P4 elementwise to C3\n P3 = keras.layers.Conv2D(feature_size, kernel_size=1, strides=1, padding='same', name='C3_reduced')(C3)\n P3 = keras.layers.Add(name='P3_merged')([P4_upsampled, P3])\n P3 = keras.layers.Conv2D(feature_size, kernel_size=3, strides=1, padding='same', name='P3')(P3)\n\n return P3","def fully_connected3(self):\n self.weights3 = tf.get_variable(\"weights3\", shape=[12, 10],\n initializer=tf.contrib.layers.xavier_initializer()) \n \n self.bias3 = tf.get_variable('bias3', dtype = tf.float32, \n initializer = tf.random_normal([1])) \n self.hidden_layer3 = tf.matmul(self.data, self.weights3) + self.bias3\n \n self.initialize_and_train()","def itkBinaryContourImageFilterIUC3IUC3_cast(obj: 'itkLightObject') -> \"itkBinaryContourImageFilterIUC3IUC3 *\":\n return _itkBinaryContourImageFilterPython.itkBinaryContourImageFilterIUC3IUC3_cast(obj)","def _action_op_u1(self, plaq):\n # if self.link_type == 'U1':\n # return np.cos(plaq)\n return tf.math.cos(plaq)","def GachaCraftNodeExcelAddGP1103(builder, GP1103):\n return AddGP1103(builder, GP1103)","def cu1(self, q0, q1, alpha=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U1, qid=[q0,q1], phase=alpha, ctrl=ctrl)\n return self","def k3(self, f, t, u, k2, usereverse=False):\n\n h = self._delta_t / 2.0\n\n v = u + h * k2\n tt = t + h\n\n if usereverse:\n output, storagez, storagew = f(tt, v)\n\n self.storagez.append(storagez)\n self.storagew.append(storagew)\n\n return output\n else:\n return f(tt, v)","def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])","def r_3(comps: 'list(Compound)', is_input):\r\n react: str\r\n\r\n if is_input:\r\n iSiMe = Compound(\"Zn\")\r\n if len(comps) == 1:\r\n if \"iSi\" in comps[0].comp_type:\r\n iSiMe = comps[0]\r\n else:\r\n if \"iSi\" in comps[0].comp_type:\r\n iSiMe = comps[0]\r\n else:\r\n iSiMe = comps[1]\r\n\r\n me = list(iSiMe.formula.consist.keys())[0].name\r\n if me in [\"Au\", \"Pt\"]:\r\n return \"\"\r\n me_oxs = get_me_oxs(me)\r\n if me_oxs == 0:\r\n return \"\"\r\n if is_me_activer(\"H\", 1, me, me_oxs):\r\n return \"\"\r\n\r\n iSaNo = Compound(iSaNo_create(me, me_oxs, \"NO3\", 1))\r\n\r\n react = f\"{iSiMe} + HNO3 -> {iSaNo} + N2O + H2O\"\r\n else:\r\n iSaNo = Compound(\"Zn(NO3)2\")\r\n if len(comps) == 1:\r\n if \"iSaNo\" in comps[0].comp_type:\r\n iSaNo = comps[0]\r\n elif len(comps) == 2:\r\n if \"iSaNo\" in comps[0].comp_type:\r\n iSaNo = comps[0]\r\n elif \"iSaNo\" in comps[1].comp_type:\r\n iSaNo = comps[1]\r\n else:\r\n if \"iSaNo\" in comps[0].comp_type:\r\n iSaNo = comps[0]\r\n elif \"iSaNo\" in comps[1].comp_type:\r\n iSaNo = comps[1]\r\n else:\r\n iSaNo = comps[2]\r\n\r\n ((me, me_oxs), (an, an_oxs)) = iSa_oxs(iSaNo.formula)\r\n if an != \"NO3\":\r\n return \"\"\r\n if me in [\"Au\", \"Pt\"]:\r\n return \"\"\r\n if is_me_activer(\"H\", 1, me, me_oxs):\r\n return \"\"\r\n\r\n iSiMe = Compound(simple(me))\r\n\r\n react = f\"{iSiMe} + HNO3 -> {iSaNo} + N2O + H2O\"\r\n\r\n return Reaction(react)","def Closure_Phase(self, uv1, uv2, uv3):\n phi1 = self.Phase(*uv1)\n phi2 = self.Phase(*uv2)\n phi3 = self.Phase(*uv3)\n cphi = phi1 - phi2 + phi3\n cphi[cphi < -pi] += 2 * pi\n cphi[cphi > pi] -= 2 * pi\n return cphi","def ControlledU(U):\n\n d = U.rank // 2 + 1\n shape = [2] * 2 * d\n t = np.zeros(shape, dtype=np.complex128)\n\n # If the first bit is zero, fill in as the identity operator.\n t[:, 0, ...] = Identity(d)[:, 0, ...]\n # Else, fill in as Identity tensored with U (Identity for the first bit,\n # which remains unchanged.\n t[:, 1, ...] = (Identity() * U)[:, 1, ...]\n return Operator(t)","def updateATOM3instance( self, atom3i ):\r\n self.cb = atom3i.cb \r\n self.atom3i = atom3i","def addThreeNodesRig(self):\r\n cam = self.nativePointer()\r\n\r\n # create controls\r\n pos = mxs.star(radius1 = 6.5, radius2 = 5.5, points=16)\r\n trans = mxs.rectangle(length=10.2, width=4.5)\r\n rot = mxs.ngon(radius=2.0, nSides=3, corner_radius=0.5)\r\n\r\n # rename controls\r\n pos.name = str(cam.name) + 'position'\r\n trans.name = str(cam.name) + 'translation'\r\n rot.name = str(cam.name) + 'rotation'\r\n\r\n # rotate controls into place\r\n pos.rotation = mxs.eulerangles(90, 0 , 0)\r\n trans.rotation = mxs.eulerangles(90, 0 , 0)\r\n rot.rotation = mxs.eulerangles(0, 0, -90)\r\n\r\n # reset xforms\r\n mxs.resetxform(pos)\r\n mxs.resetxform(trans)\r\n mxs.resetxform(rot)\r\n\r\n # collapse xforms\r\n mxs.maxOps.CollapseNode(pos, True)\r\n mxs.maxOps.CollapseNode(trans, True)\r\n mxs.maxOps.CollapseNode(rot, True)\r\n\r\n rot.parent = trans\r\n trans.parent = pos\r\n\r\n pos.wirecolor = rot.wirecolor = trans.wirecolor = mxs.color(0, 230, 250)\r\n\r\n # Move the rig to align with the cam\r\n pivrot=cam.rotation\r\n pos.rotation*=pivrot;\r\n #pos.objectoffsetrot*=pivrot;\r\n #pos.objectoffsetpos*=pivrot;\r\n\r\n pos.position = cam.position\r\n #mxs.resetxform(pos)\r\n #pos.rotation = cam.rotation\r\n\r\n\r\n # parent the cam to to rig\r\n cam.parent = rot\r\n\r\n return True","def itkHuangThresholdImageFilterIUS3IUC3_cast(obj: 'itkLightObject') -> \"itkHuangThresholdImageFilterIUS3IUC3 *\":\n return _itkHuangThresholdImageFilterPython.itkHuangThresholdImageFilterIUS3IUC3_cast(obj)","def process_block_to_add(coupling_point: Point, coupling_angle : Angle, conjugation_angle : Angle, cc_bond_length:float, block_to_add: Building_Block):\n\n\t#load data for block_to_add\n\tcoord_xyz = top.read_xyz_file(block_to_add.path)\n\tcoord_xyz_save = np.copy(coord_xyz)\n\n\t\n\n\t#rotate around z axis for conjugation, rotate around y for right orientation,shift to coupling point and shift by c-c bond length in right direction\n\tfor i in range(0,coord_xyz.shape[1]):\n\t\t\n\t\t#conjugation x' = cos(phi)*x-sin(phi)*y\n\t\tcoord_xyz[1,i] = coord_xyz_save[1,i]*np.cos(conjugation_angle)-np.sin(conjugation_angle)*coord_xyz_save[2,i]\n\t\t#conjugation y' = sin(phi)*x+cos(phi)*y\n\t\tcoord_xyz[2,i] = coord_xyz_save[1,i]*np.sin(conjugation_angle)+np.cos(conjugation_angle)*coord_xyz_save[2,i]\n\n\t\tcoord_xyz_save = np.copy(coord_xyz)\n\n\t\t#rotation around y: x' = cos(phi)*x+sin(phi)*z\n\t\tcoord_xyz[1,i] = coord_xyz_save[1,i]*np.cos(coupling_angle)+np.sin(coupling_angle)*coord_xyz_save[3,i]\n\t\t#rotation around y: z' = cos(phi)*z-sin(phi)*x\n\t\tcoord_xyz[3,i] = -coord_xyz_save[1,i]*np.sin(coupling_angle)+np.cos(coupling_angle)*coord_xyz_save[3,i]\n\n\t\t#shift to coupling point x -> x+x_c\n\t\tcoord_xyz[1,i] = coord_xyz[1,i]+coupling_point.x\n\t\t#shift to coupling point y -> y+y_c\n\t\tcoord_xyz[2,i] = coord_xyz[2,i]+coupling_point.y\n\t\t#shift to coupling point z -> z+z_c\n\t\tcoord_xyz[3,i] = coord_xyz[3,i]+coupling_point.z\n\n\t\t#shift by C-C bond length in e_c direction sin=-0.866 cos=-0.499\n\t\tcoord_xyz[1,i] = coord_xyz[1,i]+cc_bond_length*np.sin(coupling_angle)\n\t\t#shift by C-C bond length in e_c direction\n\t\tcoord_xyz[3,i] = coord_xyz[3,i]+cc_bond_length*np.cos(coupling_angle)\n\treturn coord_xyz","def itkBinaryContourImageFilterIUS3IUS3_cast(obj: 'itkLightObject') -> \"itkBinaryContourImageFilterIUS3IUS3 *\":\n return _itkBinaryContourImageFilterPython.itkBinaryContourImageFilterIUS3IUS3_cast(obj)","def itkBoundedReciprocalImageFilterIUC3IUC3_cast(*args):\n return _itkBoundedReciprocalImageFilterPython.itkBoundedReciprocalImageFilterIUC3IUC3_cast(*args)","def upconv_block(i, filters, shape, activation='relu', padding='same',\n data_format='channels_first'):\n c1 = Conv3D(filters, shape, activation=activation,\n padding=padding, data_format=data_format)(i)\n c2 = Conv3D(filters, shape, activation=activation,\n padding=padding, data_format=data_format)(c1)\n u = UpSampling3D(size=(1, 2, 2), data_format=data_format)(c2)\n c3 = Conv3D(int(filters / 2),\n (1, 2, 2),\n activation=activation,\n padding=padding,\n data_format=data_format)(u)\n return c3","def new(self, u, k1, k2, k3, k4):\n\n v = self.combine(k1, k2, k3, k4)\n\n return u + (self._delta_t / 6.0) * v","def _delayandsum3(data, offsets, ifactor2, steeramp, out, autopower):\n gridsize, numchannels = offsets.shape\n for gi in nb.prange(gridsize):\n out[gi] = 0\n autopower[gi] = 0\n for mi in range(numchannels):\n ind = offsets[gi,mi]\n r = (data[ind,mi] * (1-ifactor2[gi,mi]) \\\n + data[ind+1,mi] * ifactor2[gi,mi]) * steeramp[gi,mi]\n out[gi] += r\n autopower[gi] += r*r","def comp_add_ao(self):\n scene = self.set_as_active()\n scene.use_nodes = True\n tree = scene.node_tree\n tree.nodes.clear()\n\n # creating the nodes\n node_rlayer = tree.nodes.new('CompositorNodeRLayers')\n node_rlayer.location = -300, 100\n node_rlayer.scene = scene\n node_rlayer.layer = w_var.rlname\n\n node_mixcolor = tree.nodes.new('CompositorNodeMixRGB')\n node_mixcolor.location = 0, 50\n node_mixcolor.blend_type = 'MULTIPLY'\n node_mixcolor.inputs[0].default_value = 0.730\n\n node_comp = tree.nodes.new('CompositorNodeComposite')\n node_comp.location = 300, 130\n\n node_viewer = tree.nodes.new('CompositorNodeViewer')\n node_viewer.location = 300, -100\n\n # connecting the nodes\n links = tree.links\n links.new(node_rlayer.outputs[0], node_mixcolor.inputs[1])\n links.new(node_rlayer.outputs[10], node_mixcolor.inputs[2])\n links.new(node_mixcolor.outputs[0], node_comp.inputs[0])\n links.new(node_mixcolor.outputs[0], node_viewer.inputs[0])\n\n for node in tree.nodes:\n node.select = False","def _ice_d3gdt3(temp,pres):\n # Reduced variables\n tn = temp/_TTP\n pn = pres/_PTPE\n _PI0 = _PATM/_PTPE\n g_ttt = 0.\n \n # Residual terms including complex numbers\n sr = [_GCOEFFS[1], complex(0.0,0.0)]\n for (k,rk) in enumerate(_GCOEFFS[2]):\n sr[1] += rk * (pn-_PI0)**k\n for (tk,s) in zip(_GCOEFFS[3],sr):\n term = 1./(tk-tn)**2 - 1./(tk+tn)**2\n g_ttt += (s * term).real / _TTP**2\n return g_ttt","def _rewrite_cg(expr):\n j1, m1, j2, m2, j3, m3 = symbols(\n 'j1 m1 j2 m2 j3 m3', cls=Wild\n )\n return expr.replace(\n CG(j1, m1, j2, m2, j3, m3),\n _NEG_UNITY ** (-j1 + j2 - m3) * sqrt(2 * j3 + 1) * Wigner3j(\n j1, m1, j2, m2, j3, -m3\n )\n )","def get_tx_gain3(self, tx_gain3):\n\t\treturn self._tx_gain3","def reduce_3sat_to_3col(instance, G = None):\n G = Graph() if G is None else G\n\n # add common gadget\n G.add_named_vertex('T')\n G.add_named_vertex('F')\n G.add_named_vertex('X')\n G.add_edge('T', 'F')\n G.add_edge('F', 'X')\n G.add_edge('X', 'T')\n\n\n # add gadget for variables\n variables = sorted(set([abs(v) for clause in instance for v in clause]))\n\n for v in variables:\n G.add_named_vertex(v)\n G.add_named_vertex(-v)\n G.add_edge('X', v)\n G.add_edge('X', -v)\n G.add_edge(v, -v)\n\n G.set_vertex_index(max(variables) + 1)\n # add the clause gadgets\n for a, b, c in instance:\n g1, g2, g3, g4, g5 = [G.add_vertex() for _i in range(5)]\n\n # triangle 1,2,3\n G.add_edge(g1, g2) # 1\n G.add_edge(g2, g3) # 2\n G.add_edge(g3, g1) # 3\n\n # bridge betwen triangle 1,2,3T and 4,5,T\n G.add_edge(g3, g4) # 4\n\n # triangle 3,4,5\n G.add_edge(g4, g5) # 5\n G.add_edge(g5, 'T') # 6\n G.add_edge('T', g4) # 7\n\n # edges for clause a,b,c\n G.add_edge(a, g1) # 8\n G.add_edge(b, g2) # 9\n G.add_edge(c, g5) # 10\n\n return G","def f3a_abSymmetrized_old(self,a,b,c):\n return (self.f3a_ab(a,b,c) + self.f3a_ab(a,b,-c) +\\\n self.f3ab_a(a,b,c) + self.f3ab_a(a,b,-c) +\\\n self.f3ba_a(a,b,c) + self.f3ba_a(a,b,-c))/6.","def convert_AMUA3_gcm3(den_AMUA3):\n return den_AMUA3/const_avo*10.0","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def add_mult(num1, num2, num3):\n \n addmult = (num1 + num2) * num3\n return addmult","def convert_conv3d(g, op, block):\n\n dilations = op.attr(\"dilations\")\n groups = op.attr(\"groups\")\n paddings = op.attr(\"paddings\")\n padding_algorithm = op.attr(\"padding_algorithm\")\n strides = op.attr(\"strides\")\n\n kernel = g.get_node(op.input(\"Filter\")[0])\n input_x = g.get_node(op.input(\"Input\")[0])\n data_layout = op.attr(\"data_format\")\n out_channels, _, k_d, k_h, k_w = infer_shape(kernel)\n if padding_algorithm == \"VALID\":\n paddings = [0, 0, 0]\n elif padding_algorithm == \"SAME\":\n dilations = [1, 1, 1]\n input_x = autopad(input_x, strides, [k_d, k_h, k_w], dilations)\n paddings = [0, 0, 0]\n elif padding_algorithm == \"EXPLICIT\":\n if len(paddings) == 3:\n paddings = [\n paddings[0],\n paddings[1],\n paddings[2],\n paddings[0],\n paddings[1],\n paddings[2],\n ]\n elif len(paddings) == 6:\n paddings = [\n paddings[0],\n paddings[3],\n paddings[1],\n paddings[4],\n paddings[2],\n paddings[5],\n ]\n else:\n msg = f'Value {padding_algorithm} in attribute \"padding\" of operator Conv is not \"valid.\"'\n raise tvm.error.OpAttributeInvalid(msg)\n\n out = _op.nn.conv3d(\n input_x,\n kernel,\n strides=strides,\n padding=paddings,\n dilation=dilations,\n groups=groups,\n channels=out_channels,\n kernel_size=[k_d, k_h, k_w],\n data_layout=data_layout,\n )\n g.add_node(op.output(\"Output\")[0], out)","def convert_relu6(g, op, block):\n\n x = g.get_node(op.input(\"X\")[0])\n out = _op.clip(x, 0.0, 6.0)\n g.add_node(op.output(\"Out\")[0], out)","def cifar100_aug3():\n normalize = transforms.Normalize(mean=(0.5071, 0.4865, 0.4409), std=(0.2673, 0.2564, 0.2762))\n transform_t = transforms.Compose([\n transforms.RandomCrop(32, 4),\n transforms.RandomHorizontalFlip(),\n transforms.ToTensor(),\n normalize,\n ])\n transform_v = transforms.Compose([\n transforms.ToTensor(),\n normalize,\n ])\n return cifar100_altaug(transform_t, transform_v)","def set_tx_gain3(self, tx_gain3):\n\t\tif (tx_gain3 in range(-13, 19)):\n\t\t\tself._tx_gain3 = tx_gain3\n\t\telse:\n\t\t\tsys.stderr.write(\"\\nERROR : %s tx_gain3 must be an integer between -13 and 18 so it can't be %s !\\n\" % (self._target_id, tx_gain3))\n\t\t\tsys.exit(1)","def setup_threeCtrl(lf_lidrails, rt_lidrails):\n # Declare control variables\n lf_up = ['lf_lid01_tp01_ccc', 'lf_lid01_tp02_ccc', 'lf_lid01_tp03_ccc']\n lf_dn = ['lf_lid01_dn01_ccc', 'lf_lid01_dn02_ccc', 'lf_lid01_dn03_ccc']\n rt_up = ['rt_lid01_tp01_ccc', 'rt_lid01_tp02_ccc', 'rt_lid01_tp03_ccc']\n rt_dn = ['rt_lid01_dn01_ccc', 'rt_lid01_dn02_ccc', 'rt_lid01_dn03_ccc']\n\n # Connect lidRails ramps to lid profile controls\n\n # ========\n # lf_up\n\n # inner\n cmds.connectAttr(lf_up[0] + '.tx', lf_lidrails + '.offsettop[0].offsettop_Position', f=True)\n cmds.connectAttr(lf_up[0] + '.ty', lf_lidrails + '.offsettop[0].offsettop_FloatValue', f=True)\n # mid\n lf_lid01_um01_adn = cmds.createNode('addDoubleLinear', n='lf_lid01_um01_addDoubleLinear')\n cmds.connectAttr(lf_up[1] + '.tx', lf_lid01_um01_adn + '.input1', f=True)\n cmds.setAttr(lf_lid01_um01_adn + '.input2', 0.5)\n cmds.connectAttr(lf_lid01_um01_adn + '.output', lf_lidrails + '.offsettop[1].offsettop_Position', f=True)\n cmds.connectAttr(lf_up[1] + '.ty', lf_lidrails + '.offsettop[1].offsettop_FloatValue', f=True)\n # outer\n lf_lid01_uo01_adn = cmds.createNode('addDoubleLinear', n='lf_lid01_uo01_addDoubleLinear')\n cmds.connectAttr(lf_up[2] + '.tx', lf_lid01_uo01_adn + '.input1', f=True)\n cmds.setAttr(lf_lid01_uo01_adn + '.input2', 1.0)\n cmds.connectAttr(lf_lid01_uo01_adn + '.output', lf_lidrails + '.offsettop[2].offsettop_Position', f=True)\n cmds.connectAttr(lf_up[2] + '.ty', lf_lidrails + '.offsettop[2].offsettop_FloatValue', f=True)\n\n # ========\n # lf_dn\n\n # Reverse node\n lf_dn_rvn = cmds.createNode('reverse', n='lf_lid01_dn01_reverse')\n # inner\n cmds.connectAttr(lf_dn[0] + '.tx', lf_lidrails + '.offsetbottom[0].offsetbottom_Position', f=True)\n cmds.connectAttr(lf_dn[0] + '.ty', lf_dn_rvn + '.inputX', f=True)\n cmds.connectAttr(lf_dn_rvn + '.outputX', lf_lidrails + '.offsetbottom[0].offsetbottom_FloatValue', f=True)\n # mid\n lf_lid01_dm01_adn = cmds.createNode('addDoubleLinear', n='lf_lid01_dm01_addDoubleLinear')\n cmds.connectAttr(lf_dn[1] + '.tx', lf_lid01_dm01_adn + '.input1', f=True)\n cmds.setAttr(lf_lid01_dm01_adn + '.input2', 0.5)\n cmds.connectAttr(lf_lid01_dm01_adn + '.output', lf_lidrails + '.offsetbottom[1].offsetbottom_Position', f=True)\n cmds.connectAttr(lf_dn[1] + '.ty', lf_dn_rvn + '.inputY', f=True)\n cmds.connectAttr(lf_dn_rvn + '.outputY', lf_lidrails + '.offsetbottom[1].offsetbottom_FloatValue', f=True)\n # outer\n lf_lid01_do01_adn = cmds.createNode('addDoubleLinear', n='lf_lid01_do01_addDoubleLinear')\n cmds.connectAttr(lf_dn[2] + '.tx', lf_lid01_do01_adn + '.input1', f=True)\n cmds.setAttr(lf_lid01_do01_adn + '.input2', 1.0)\n cmds.connectAttr(lf_lid01_do01_adn + '.output', lf_lidrails + '.offsetbottom[2].offsetbottom_Position', f=True)\n cmds.connectAttr(lf_dn[2] + '.ty', lf_dn_rvn + '.inputZ', f=True)\n cmds.connectAttr(lf_dn_rvn + '.outputZ', lf_lidrails + '.offsetbottom[2].offsetbottom_FloatValue', f=True)\n\n # ========\n # rt_up\n\n # inner\n rt_lid01_ui01_asn = cmds.createNode('plusMinusAverage', n='rt_lid01_ui01_plusMinusAverage')\n cmds.setAttr(rt_lid01_ui01_asn + '.operation', 2)\n cmds.setAttr(rt_lid01_ui01_asn + '.input1D[0]', 1.0)\n cmds.connectAttr(rt_up[0] + '.tx', rt_lid01_ui01_asn + '.input1D[1]', f=True)\n cmds.connectAttr(rt_lid01_ui01_asn + '.output1D', rt_lidrails + '.offsettop[2].offsettop_Position', f=True)\n cmds.connectAttr(rt_up[0] + '.ty', rt_lidrails + '.offsettop[2].offsettop_FloatValue', f=True)\n # mid\n rt_lid01_um01_mdn = cmds.createNode('multDoubleLinear', n='rt_lid01_um01_multDoubleLinear')\n rt_lid01_um01_adn = cmds.createNode('addDoubleLinear', n='rt_lid01_um01_addDoubleLinear')\n cmds.connectAttr(rt_up[1] + '.tx', rt_lid01_um01_mdn + '.input1', f=True)\n cmds.setAttr(rt_lid01_um01_mdn + '.input2', -1.0)\n cmds.connectAttr(rt_lid01_um01_mdn + '.output', rt_lid01_um01_adn + '.input1', f=True)\n cmds.setAttr(rt_lid01_um01_adn + '.input2', 0.5)\n cmds.connectAttr(rt_lid01_um01_adn + '.output', rt_lidrails + '.offsettop[1].offsettop_Position', f=True)\n cmds.connectAttr(rt_up[1] + '.ty', rt_lidrails + '.offsettop[1].offsettop_FloatValue', f=True)\n # outer\n rt_lid01_uo_mdn = cmds.createNode('multDoubleLinear', n='rt_lid01_uo_multDoubleLinear')\n cmds.connectAttr(rt_up[2] + '.tx', rt_lid01_uo_mdn + '.input1', f=True)\n cmds.setAttr(rt_lid01_uo_mdn + '.input2', -1.0)\n cmds.connectAttr(rt_lid01_uo_mdn + '.output', rt_lidrails + '.offsettop[0].offsettop_Position', f=True)\n cmds.connectAttr(rt_up[2] + '.ty', rt_lidrails + '.offsettop[0].offsettop_FloatValue', f=True)\n\n # ========\n # rt_dn\n\n # Reverse node\n rt_dn_rvn = cmds.createNode('reverse', n='rt_lid01_dn01_reverse')\n # inner\n rt_lid01_di01_asn = cmds.createNode('plusMinusAverage', n='rt_lid01_di01_plusMinusAverage')\n cmds.setAttr(rt_lid01_di01_asn + '.operation', 2)\n cmds.setAttr(rt_lid01_di01_asn + '.input1D[0]', 1.0)\n cmds.connectAttr(rt_dn[0] + '.tx', rt_lid01_di01_asn + '.input1D[1]', f=True)\n cmds.connectAttr(rt_lid01_di01_asn + '.output1D', rt_lidrails + '.offsetbottom[0].offsetbottom_Position', f=True)\n cmds.connectAttr(rt_dn[0] + '.ty', rt_dn_rvn + '.inputX', f=True)\n cmds.connectAttr(rt_dn_rvn + '.outputX', rt_lidrails + '.offsetbottom[0].offsetbottom_FloatValue', f=True)\n # mid\n rt_lid01_dm01_asn = cmds.createNode('plusMinusAverage', n='rt_lid01_dm01_plusMinusAverage')\n cmds.setAttr(rt_lid01_dm01_asn + '.operation', 2)\n cmds.setAttr(rt_lid01_dm01_asn + '.input1D[0]', 0.5)\n cmds.connectAttr(rt_dn[1] + '.tx', rt_lid01_dm01_asn + '.input1D[1]', f=True)\n cmds.connectAttr(rt_lid01_dm01_asn + '.output1D', rt_lidrails + '.offsetbottom[1].offsetbottom_Position', f=True)\n cmds.connectAttr(rt_dn[1] + '.ty', rt_dn_rvn + '.inputY', f=True)\n cmds.connectAttr(rt_dn_rvn + '.outputY', rt_lidrails + '.offsetbottom[1].offsetbottom_FloatValue', f=True)\n # outer\n rt_lid01_do01_mdn = cmds.createNode('multDoubleLinear', n='rt_lid01_do01_multDoubleLinear')\n cmds.connectAttr(rt_dn[2] + '.tx', rt_lid01_do01_mdn + '.input1', f=True)\n cmds.setAttr(rt_lid01_do01_mdn + '.input2', -1.0)\n cmds.connectAttr(rt_lid01_do01_mdn + '.output', rt_lidrails + '.offsetbottom[2].offsetbottom_Position', f=True)\n cmds.connectAttr(rt_dn[2] + '.ty', rt_dn_rvn + '.inputZ', f=True)\n cmds.connectAttr(rt_dn_rvn + '.outputZ', rt_lidrails + '.offsetbottom[2].offsetbottom_FloatValue', f=True)","def test_f3_circuit_maker(self):\n fho = tfho.test_file_handle_object()\n W = 5\n D = 6\n gate_maker = g.TYPE_TO_FAM3_GATE_GEN[g.TEST_TYPES.RANDOM]\n # family 3 files:\n circuit_file_name = \"circuit_file\"\n circuit_file = fho.get_file_object(circuit_file_name, 'w')\n input_file_name = \"input_file\"\n input_file = fho.get_file_object(input_file_name, 'w')\n output_file_name = \"output_file\"\n output_file = fho.get_file_object(output_file_name, 'w')\n F = 3\n # make a family 3 circuit:\n sr.seed(self.rand_seed)\n gen = g.f3_circuit_maker(W, D, circuit_file, input_file, output_file,\n gate_maker)\n gen.generate()\n # obtain strings representing the contents of all the resulting files:\n circuit_string = fho.get_file(circuit_file_name).getvalue()\n input_string = fho.get_file(input_file_name).getvalue()\n output_string = fho.get_file(output_file_name).getvalue()\n # make sure that the input begins and ends with a bracket:\n self.assertEqual(\"[\", input_string[0])\n self.assertEqual(\"]\", input_string[-1])\n # make sure that each input element is a bit:\n for bit in input_string[1:-1]:\n self.assertTrue((bit == '0') or (bit == '1'))\n # make sure that the output is a bit:\n self.assertTrue((output_string == '0') or (output_string == '1'))\n # make sure that the circuit header contains the correct values:\n circuit_header = circuit_string.split(\"\\n\")[0]\n (W_string, D_string, F_string) = circuit_header.split(\",\")\n W_value = int(W_string.split(\"=\")[-1])\n D_value = int(D_string.split(\"=\")[-1])\n F_value = int(F_string.split(\"=\")[-1])\n self.assertEqual(W, W_value)\n self.assertEqual(D, D_value)\n self.assertEqual(F, F_value)","def f3a_ab(self,a,b,c):\n ans = ((b*b/a) * (b*c - a)/(a*a + b*b - 2.*a*b*c)) * self.g2(a,b,-c) +\\\n 7. * (b*c/a) * self.f2(a,b,-c)/2.\n\n return ans/18.","def updater(c0, u, delta_t):\n c1 = c0 + u * delta_t\n return c1","def vs3_func_4(ns, traj, vs_def_beads_ids, vs_params):\n i, j, k = vs_def_beads_ids\n a, b, c = vs_params # weight, weight, nm**(-1)\n c = c / 10 # retrieve amgstrom**(-1) for MDA\n\n for ts in ns.aa2cg_universe.trajectory:\n pos_i = ns.aa2cg_universe.atoms[i].position\n pos_j = ns.aa2cg_universe.atoms[j].position\n pos_k = ns.aa2cg_universe.atoms[k].position\n r_ij = pos_j - pos_i\n r_ik = pos_k - pos_i\n traj[ts.frame] = pos_i + a * r_ij + b * r_ik - c * (\n r_ij / mda.lib.mdamath.norm(r_ij) * r_ik / mda.lib.mdamath.norm(r_ik))","def f3ba_a(self,a,b,c):\n ans = self.g2(a,b,c)*(7.*(b*b + a*b*c) - (b/a)**2 * (a*a + a*b*c))/\\\n (a*a+b*b+2.*a*b*c)\n\n return ans/18.","def add_three(v1, v2, v3):\n p = v1 + v2 + v3\n print(\"The sum of the three numbers is: {}\".format(p))\n return p","def cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUL3IUL3_cast(*args)","def New(*args, **kargs):\n obj = itkScalarConnectedComponentImageFilterIUC3IUC3.__New_orig__()\n import itkTemplate\n itkTemplate.New(obj, *args, **kargs)\n return obj","def cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUS3IUS3_cast(*args)","def itkSpeckleNoiseImageFilterIUC3IUC3_cast(*args):\n return _itkSpeckleNoiseImageFilterPython.itkSpeckleNoiseImageFilterIUC3IUC3_cast(*args)","def add_clay_to_selected(self):\n scene = self.set_as_active()\n\n # if the user selected a material, use it\n if w_var.cb_mat_clay:\n clay_mat = bpy.data.materials[w_var.mat_clay_name]\n\n # else, create a new one with the color selected\n else:\n clay_color = w_var.color_clay\n\n # separating rgb and alpha\n clay_color_rgb = clay_color[0:3]\n clay_color_alpha = clay_color[-1]\n clay_mat = bpy.data.materials.new('clay')\n \n renderengine = scene.wirebomb.data_renderengine\n \n if renderengine == 'CYCLES':\n clay_mat.use_nodes = True\n tree = clay_mat.node_tree\n tree.nodes.clear()\n\n # creating the nodes\n node_transparent = tree.nodes.new('ShaderNodeBsdfTransparent')\n node_transparent.location = -300, 100\n\n node_diffuse = tree.nodes.new('ShaderNodeBsdfDiffuse')\n node_diffuse.location = -300, -100\n node_diffuse.inputs[0].default_value = clay_color_rgb + (1.0, )\n node_diffuse.color = clay_color_rgb\n node_diffuse.name = 'addon_clay_color' # referencing to this ID in the real-time change\n\n node_mixshader = tree.nodes.new('ShaderNodeMixShader')\n node_mixshader.location = 0, 50\n node_mixshader.inputs[0].default_value = clay_color_alpha\n node_mixshader.name = 'addon_clay_alpha' # referencing to this ID in the real-time change\n\n node_output = tree.nodes.new('ShaderNodeOutputMaterial')\n node_output.location = 300, 50\n\n # connecting the nodes\n tree.links.new(node_transparent.outputs[0], node_mixshader.inputs[1])\n tree.links.new(node_diffuse.outputs[0], node_mixshader.inputs[2])\n tree.links.new(node_mixshader.outputs[0], node_output.inputs[0])\n\n for node in tree.nodes:\n node.select = False\n\n # sets the viewport color\n clay_mat.diffuse_color = clay_color_rgb\n \n elif renderengine == 'BLENDER_RENDER':\n clay_mat.diffuse_color = clay_color_rgb\n clay_mat.use_transparency = True\n clay_mat.alpha = clay_color_alpha\n\n previous_area = bpy.context.area.type\n bpy.context.area.type = 'VIEW_3D'\n previous_layers = tuple(scene.layers)\n\n # can't enter edit mode on objects on inactive layers\n scene.layers = (True,)*20\n\n for obj in scene.objects:\n if obj.select:\n # only enters edit mode on active object\n scene.objects.active = obj\n obj.data.materials.append(clay_mat)\n clay_index = obj.data.materials.find(clay_mat.name)\n obj.active_material_index = clay_index\n\n bpy.ops.object.mode_set(mode='EDIT')\n bpy.ops.mesh.select_all(action='SELECT')\n bpy.ops.object.material_slot_assign()\n bpy.ops.mesh.select_all(action='SELECT')\n bpy.ops.object.mode_set(mode='OBJECT')\n\n bpy.context.area.type = previous_area\n scene.layers = previous_layers\n\n return clay_mat","def shift_3_cust(self, sol_in6, cust, c_loc, curr_temp, sol_type6, sa_lns):\r\n\r\n route_ing = copy.deepcopy(sol_in6[c_loc[0]])\r\n route_new = route_ing\r\n move_to_route = c_loc[0]\r\n orgn_type1 = sol_type6[c_loc[0]]\r\n cust_folw1 = route_ing[c_loc[1] + 1]\r\n cust_folw2 = route_ing[c_loc[1] + 2]\r\n origin_cost1 = check_violation(route_ing, orgn_type1)[1]\r\n route_ing.remove(cust) # remove c in the current route\r\n del route_ing[c_loc[1]] # remove customer following c\r\n del route_ing[c_loc[1]] # remove customer following following c\r\n new_type1 = route_type(route_ing)\r\n adjust_cost1 = check_violation(route_ing, new_type1)[1]\r\n best_cut_cost0 = -1000\r\n best_cut_cost = best_cut_cost0 # best cost cut of moving this customer\r\n for j, rou in enumerate(sol_in6):\r\n orgn_type2 = sol_type6[j]\r\n origin_cost2 = check_violation(rou, orgn_type2)[1]\r\n if j == c_loc[0]: # moving in the same route\r\n for k in range(1, len(route_ing)):\r\n if k == c_loc[1]:\r\n continue\r\n rou_test = route_ing[:k] + [cust, cust_folw1, cust_folw2] + route_ing[k:]\r\n if check_violation(rou_test, orgn_type2)[0]:\r\n adjust_cost2 = check_violation(rou_test, orgn_type2)[1]\r\n cost_cut_test = origin_cost1 - adjust_cost2\r\n if cost_cut_test > best_cut_cost:\r\n best_cut_cost = cost_cut_test\r\n route_new = rou_test\r\n move_to_route = j\r\n\r\n else: # moving to a different route\r\n for k in range(1, len(rou)):\r\n rou_test = rou[:k] + [cust, cust_folw1, cust_folw2] + rou[k:]\r\n if check_violation(rou_test, 5)[0]:\r\n new_type2 = route_type(rou_test)\r\n adjust_cost2 = check_violation(rou_test, new_type2)[1]\r\n cost_cut_test = origin_cost1 + origin_cost2 - adjust_cost1 - adjust_cost2\r\n if cost_cut_test > best_cut_cost:\r\n best_cut_cost = cost_cut_test\r\n route_new = rou_test\r\n move_to_route = j\r\n\r\n\r\n if best_cut_cost > 1e-5:\r\n # print('shift3 good', best_cut_cost)\r\n sol_in6[move_to_route] = route_new\r\n sol_type6[move_to_route] = route_type(route_new)\r\n if move_to_route != c_loc[0]: # moving to a different route\r\n sol_in6[c_loc[0]] = route_ing\r\n sol_type6[c_loc[0]] = route_type(route_ing)\r\n\r\n elif sa_lns and best_cut_cost < -1e-5:\r\n\r\n prb = random.uniform(0, 1)\r\n if np.exp(best_cut_cost / curr_temp) > prb:\r\n # print('shift3', best_cut_cost)\r\n sol_in6[move_to_route] = route_new\r\n sol_type6[move_to_route] = route_type(route_new)\r\n if move_to_route != c_loc[0]: # moving to a different route\r\n sol_in6[c_loc[0]] = route_ing\r\n sol_type6[c_loc[0]] = route_type(route_ing)","def write_reg3(self, value: int) -> None:\n self.length_ctr_load = value >> 3\n\n # TODO Restart envelope","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def y3(self):\n return self._y + self._y3","def append_user_gate(self, user_gate):\n self.translation['g_sect'].append(user_gate)","def cast(*args):\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUC3IUC3_cast(*args)","def itkContourDirectedMeanDistanceImageFilterIUC3IUC3_cast(*args):\n return _itkContourDirectedMeanDistanceImageFilterPython.itkContourDirectedMeanDistanceImageFilterIUC3IUC3_cast(*args)","def format_transfer_case_three(self, tik_instance):\n ub_ori_data = self.ub_memory\n ub_trans_data = ub_ori_data\n\n loop_memory = ub_ori_data - ub_ori_data % \\\n (CUBE_SIZE * CUBE_SIZE * self.dst_shape[-3] + CUBE_SIZE)\n num_data_one_loop = self.dst_shape[-4] * self.dst_shape[-3] * \\\n self.dst_shape[-2] * self.dst_shape[-1]\n num_data_one_loop_padding = num_data_one_loop + self.dst_shape[-4] * \\\n self.dst_shape[-1]\n loop_times = (num_data_one_loop_padding + loop_memory - 1) // \\\n loop_memory\n if len(self.dst_shape) == 4:\n total_core_loop_num = loop_times\n else:\n total_core_loop_num = functools_reduce(lambda x1, x2: x1 * x2,\n self.dst_shape[:-4]) * \\\n loop_times\n core_number = _set_core_num(total_core_loop_num)\n\n with tik_instance.for_range(0, core_number, block_num=core_number) \\\n as num_core:\n ub_ori = tik_instance.Tensor(self.dtype,\n (ub_ori_data,),\n name=\"ub_ori\",\n scope=tik.scope_ubuf)\n ub_trans = tik_instance.Tensor(self.dtype,\n (ub_trans_data,),\n name=\"ub_trans\",\n scope=tik.scope_ubuf)\n core_loop, sum_core = _cal_core(tik_instance, total_core_loop_num,\n num_core, core_number)\n\n with tik_instance.for_range(0, core_loop) as num_core_loop:\n total_core_loop = sum_core + num_core_loop\n num_loop_time = total_core_loop % loop_times\n num_outer_axis = (total_core_loop - num_loop_time) // \\\n loop_times\n\n handling_times = tik_instance.Scalar(\"uint64\")\n is_last = tik_instance.Scalar(\"uint64\")\n is_last.set_as(0)\n handling_times.set_as(loop_memory // (CUBE_SIZE * CUBE_SIZE *\n self.dst_shape[-3] +\n CUBE_SIZE))\n\n with tik_instance.if_scope(num_loop_time == loop_times - 1):\n if num_data_one_loop_padding % loop_memory == 0:\n remainder = loop_memory\n else:\n remainder = num_data_one_loop_padding % loop_memory\n handling_times.set_as((remainder + CUBE_SIZE * CUBE_SIZE *\n self.dst_shape[-3] + CUBE_SIZE -\n 1) // (CUBE_SIZE * CUBE_SIZE *\n self.dst_shape[-3] +\n CUBE_SIZE))\n is_last.set_as(1)\n\n src_ub_index = 0\n src_gm_index = num_outer_axis * self.src_shape[-1] * \\\n self.src_shape[-2] + loop_memory // \\\n (CUBE_SIZE * CUBE_SIZE * self.dst_shape[-3] +\n CUBE_SIZE) * num_loop_time * CUBE_SIZE\n with tik_instance.for_range(0, self.src_shape[-2]) as num_cube:\n tik_instance.data_move(ub_ori[src_ub_index +\n num_cube *\n handling_times *\n self.dst_shape[-1]],\n self.src_gm[src_gm_index +\n num_cube *\n self.src_shape[-1]],\n 0, 1,\n (handling_times * CUBE_SIZE +\n self.num_data - 1) //\n self.num_data, 0, 0)\n\n self.data_rearrange_case_one(tik_instance, ub_ori, ub_trans,\n handling_times, is_last)\n dst_gm_index = num_outer_axis * num_data_one_loop + \\\n loop_memory // \\\n (CUBE_SIZE * CUBE_SIZE * self.dst_shape[-3] +\n CUBE_SIZE) * (CUBE_SIZE * CUBE_SIZE *\n self.dst_shape[-3]) * \\\n num_loop_time\n tik_instance.data_move(self.dst_gm[dst_gm_index], ub_trans[0],\n 0, handling_times,\n CUBE_SIZE * self.dst_shape[-3] *\n CUBE_SIZE // self.num_data,\n self.num_byte // 2, 0)\n\n return tik_instance","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def f3ab_a(self,a,b,c):\n ans = 7*b*c/a * self.f2(b,a,-c)/2. + \\\n (b*b/a)*(b*c-a)/(a*a+b*b-2.*a*b*c)*self.g2(b,a,-c) +\\\n self.g2(a,b,c)*(7.*(b*b + a*b*c) - (b/a)**2 * (a*a + a*b*c))/\\\n (a*a+b*b+2.*a*b*c)\n\n return ans/18.","def itkBoundedReciprocalImageFilterIUL3IUL3_cast(*args):\n return _itkBoundedReciprocalImageFilterPython.itkBoundedReciprocalImageFilterIUL3IUL3_cast(*args)","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def c3d(self):\n model = Sequential()\n # 1st layer group\n model.add(Conv3D(64, 3, 3, 3, activation='relu',\n border_mode='same', name='conv1',\n subsample=(1, 1, 1),\n input_shape=self.input_shape))\n model.add(MaxPooling3D(pool_size=(1, 2, 2), strides=(1, 2, 2),\n border_mode='valid', name='pool1'))\n # 2nd layer group\n model.add(Conv3D(128, 3, 3, 3, activation='relu',\n border_mode='same', name='conv2',\n subsample=(1, 1, 1)))\n model.add(MaxPooling3D(pool_size=(2, 2, 2), strides=(2, 2, 2),\n border_mode='valid', name='pool2'))\n # 3rd layer group\n model.add(Conv3D(256, 3, 3, 3, activation='relu',\n border_mode='same', name='conv3a',\n subsample=(1, 1, 1)))\n model.add(Conv3D(256, 3, 3, 3, activation='relu',\n border_mode='same', name='conv3b',\n subsample=(1, 1, 1)))\n model.add(MaxPooling3D(pool_size=(2, 2, 2), strides=(2, 2, 2),\n border_mode='valid', name='pool3'))\n # 4th layer group\n model.add(Conv3D(512, 3, 3, 3, activation='relu',\n border_mode='same', name='conv4a',\n subsample=(1, 1, 1)))\n model.add(Conv3D(512, 3, 3, 3, activation='relu',\n border_mode='same', name='conv4b',\n subsample=(1, 1, 1)))\n model.add(MaxPooling3D(pool_size=(2, 2, 2), strides=(2, 2, 2),\n border_mode='valid', name='pool4'))\n\n # 5th layer group\n model.add(Conv3D(512, 3, 3, 3, activation='relu',\n border_mode='same', name='conv5a',\n subsample=(1, 1, 1)))\n model.add(Conv3D(512, 3, 3, 3, activation='relu',\n border_mode='same', name='conv5b',\n subsample=(1, 1, 1)))\n model.add(ZeroPadding3D(padding=(0, 1, 1)))\n # model.add(MaxPooling3D(pool_size=(2, 2, 2), strides=(2, 2, 2),\n # border_mode='valid', name='pool5', dim_ordering=\"tf\"))\n model.add(MaxPooling3D(pool_size=(2, 2, 2), strides=(2, 2, 2),\n border_mode='same', name='pool5', dim_ordering=\"tf\"))\n model.add(Flatten())\n\n # FC layers group\n model.add(Dense(4096, activation='relu', name='fc6'))\n model.add(Dropout(0.5))\n model.add(Dense(4096, activation='relu', name='fc7'))\n model.add(Dropout(0.5))\n model.add(Dense(self.nb_classes, activation='softmax'))\n for layer in model.layers:\n print(layer.output_shape)\n return model","def add_control(operation, num_ctrl_qubits, label):\n if isinstance(operation, UnitaryGate):\n # attempt decomposition\n operation._define()\n if _control_definition_known(operation, num_ctrl_qubits):\n return _control_predefined(operation, num_ctrl_qubits)\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)","def _ice_d3gdp3(temp,pres):\n \n # Reduced variables\n tn = temp/_TTP\n pn = pres/_PTPE\n _PI0 = _PATM/_PTPE\n g_ppp = 0.\n \n # Power series terms\n for (l,n) in enumerate(_GCOEFFS[0]):\n if l > 2:\n g_ppp += n * l*(l-1)*(l-2) * (pn-_PI0)**(l-3)\n g_ppp /= _PTPE**3\n return g_ppp","def enc_add_const(pub, m, c):\n # Similiar to enc add\n add_const_result = m * powmod(pub.g, c, pub.n_sq) % pub.n_sq\n return add_const_result","def _ucb_acq(x):\n mu, sigma = gp.eval(x, uncert_form='std')\n return mu + beta_th * sigma","def _ucb_acq(x):\n mu, sigma = gp.eval(x, uncert_form='std')\n return mu + beta_th * sigma","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def itkHuangThresholdImageFilterIUC3IUC3_cast(obj: 'itkLightObject') -> \"itkHuangThresholdImageFilterIUC3IUC3 *\":\n return _itkHuangThresholdImageFilterPython.itkHuangThresholdImageFilterIUC3IUC3_cast(obj)","def itkBinaryContourImageFilterIF3IF3_cast(obj: 'itkLightObject') -> \"itkBinaryContourImageFilterIF3IF3 *\":\n return _itkBinaryContourImageFilterPython.itkBinaryContourImageFilterIF3IF3_cast(obj)","def heisen3_sum(v1: Vec3, v2: Vec3) -> Vec3:\n assert v1.shape == v2.shape and v1.shape == (3,)\n # first, do normal sum to get (x + x', y + y', z + z')\n out = v1 + v2\n # then add the xy' part to z + z'\n out[2] += v1[0] * v2[1]\n return out"],"string":"[\n \"def u3(self, q0, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=ROTATION_U3, qid=[q0], phase=alpha, phase1=beta,\\n phase2=gamma, ctrl=ctrl)\\n return self\",\n \"def test_special_U3(self):\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \\\"U3\\\", {})\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \\\"U3\\\", {\\\"u3\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.2, 0.0).to_matrix(), \\\"U3\\\", {\\\"u3\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.0, 0.2).to_matrix(), \\\"U3\\\", {\\\"u3\\\": 1})\\n self.check_oneq_special_cases(U3Gate(0.11, 0.27, 0.3).to_matrix(), \\\"U3\\\", {\\\"u3\\\": 1})\",\n \"def __iadd__( self, vector3 ):\\n return self.add( vector3 )\",\n \"def test_U3(self, tol):\\n dev = qml.device(\\\"default.qubit\\\", wires=1)\\n\\n @qml.qnode(dev)\\n def circuit(x, y, z):\\n qml.QubitStateVector(1j * np.array([1, -1]) / np.sqrt(2), wires=[0])\\n qml.U3(x, y, z, wires=[0])\\n return qml.expval(qml.PauliX(0))\\n\\n theta = 0.543\\n phi = -0.234\\n lam = 0.654\\n\\n res = circuit(theta, phi, lam)\\n expected = np.sin(lam) * np.sin(phi) - np.cos(theta) * np.cos(lam) * np.cos(phi)\\n assert np.allclose(res, expected, atol=tol, rtol=0)\\n\\n grad_fn = autograd.grad(circuit, argnum=[0, 1, 2])\\n res = grad_fn(theta, phi, lam)\\n expected = np.array(\\n [\\n np.sin(theta) * np.cos(lam) * np.cos(phi),\\n np.cos(theta) * np.cos(lam) * np.sin(phi) + np.sin(lam) * np.cos(phi),\\n np.cos(theta) * np.sin(lam) * np.cos(phi) + np.cos(lam) * np.sin(phi),\\n ]\\n )\\n assert np.allclose(res, expected, atol=tol, rtol=0)\",\n \"def I3_u3(self) -> complex:\\n return self.I3_u1() * cmath.rect(1, 120 / 180 * cmath.pi)\",\n \"def _r_u3(angle: tf.Tensor) -> tf.Tensor:\\n zero = tf.constant(0, dtype=tf.float64)\\n cos = tf.cos(tf.multiply(angle[0], tf.constant(0.5, dtype=tf.float64)))\\n sin = tf.sin(tf.multiply(angle[0], tf.constant(0.5, dtype=tf.float64)))\\n sin_complex = tf.complex(sin, zero)\\n cos_complex = tf.complex(cos, zero)\\n exponent_phi = tf.complex(zero, angle[1])\\n exp_phi = tf.exp(exponent_phi)\\n exponent_lambda = tf.complex(zero, angle[2])\\n exp_lambda = tf.exp(exponent_lambda)\\n exponent_lambda_phi = tf.complex(zero, angle[1] + angle[2])\\n exp_lambda_phi = tf.exp(exponent_lambda_phi)\\n ru3 = tf.stack([[cos_complex, -tf.multiply(exp_lambda, sin_complex)],\\n [tf.multiply(exp_phi, sin_complex), tf.multiply(exp_lambda_phi, cos_complex)]])\\n\\n return ru3\",\n \"def three_activation(self, output_reg):\\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\\n self._q_neuron.ccx(self.inputs[1], self.inputs[2], self._output[output_reg])\\n self._q_neuron.ccx(self.inputs[0], self.inputs[2], self._output[output_reg])\",\n \"def S3_u32(self) -> complex:\\n return complex(\\n self._addr(self.defined_registers['Phase 3 power [W]']['addr']),\\n self._addr(self.defined_registers['Phase 3 volt amps reactive [VAr]']['addr']),\\n )\",\n \"def L3G_acquisition(add):\\n\\n # control register\\n CTRL_REG1 = 0x20\\n CTRL_REG4 = 0x23\\n LOW_ODR = 0x39\\n FIFO_CTRL = 0x2e\\n # output register\\n OUT_X_L = 0x28\\n OUT_X_H = 0x29\\n OUT_Y_L = 0x2a\\n OUT_Y_H = 0x2b\\n OUT_Z_L = 0x2c\\n OUT_Z_H = 0x2d\\n\\n # low odr mode, 50Hz, 2000 dps full scale\\n bus.write_byte_data(add, CTRL_REG1, 0b10001111)\\n bus.write_byte_data(add, CTRL_REG4, 0b00110000)\\n bus.write_byte_data(add, LOW_ODR, 0b00000001)\\n bus.write_byte_data(add, FIFO_CTRL, 0b01000000)\\n\\n # accelerator accumulate\\n while True:\\n uint16_gx = (bus.read_byte_data(add, OUT_X_H) << 8) + \\\\\\n bus.read_byte_data(add, OUT_X_L)\\n uint16_gy = (bus.read_byte_data(add, OUT_Y_H) << 8) + \\\\\\n bus.read_byte_data(add, OUT_Y_L)\\n uint16_gz = (bus.read_byte_data(add, OUT_Z_H) << 8) + \\\\\\n bus.read_byte_data(add, OUT_Z_L)\\n\\n gx = twos_comp(uint16_gx, 16)\\n gy = twos_comp(uint16_gy, 16)\\n gz = twos_comp(uint16_gz, 16)\\n\\n yield [gx, gy, gz]\",\n \"def add( self, vector3 ):\\n self._coords[:3] += vector3._coords[:3]\\n return self\",\n \"def I3_u32(self) -> complex:\\n return (self.S3_u32() / self.U23()).conjugate()\",\n \"def chain_3(d3f_dg3, dg_dx, d2f_dg2, d2g_dx2, df_dg, d3g_dx3):\\r\\n return d3f_dg3*(dg_dx**3) + 3*d2f_dg2*dg_dx*d2g_dx2 + df_dg*d3g_dx3\",\n \"def add_three(a, b, c):\\n return a + b + c\",\n \"def x3(self):\\n return self._x + self._x3\",\n \"def getU3(state):\\n\\n # TODO : do the verifictions of the above constraints\\n\\n theta=2*math.acos(state[0])\\n phi=0\\n lam=0\\n\\n if state[1]<0: theta = -theta\\n\\n # U3=np.array([\\n # [math.cos(theta/2) , np.exp(-1j*lam)*math.sin(theta/2)], \\n # [np.exp(1j*phi)*math.sin(theta/2), np.exp(1j*(phi+lam))*math.cos(theta/2)]\\n # ])\\n # print (U3)\\n # print (U3@np.array([[1],[0]]))\\n\\n return [theta, phi, lam]\",\n \"def computeCRCD3(self, u0, u1, u2, u3, u4, u5, u6, u7):\\n tmp = u0\\n bs = [u1, u2, u3, u4, u5, u6, u7]\\n for val in bs:\\n for j in range(16):\\n if tmp & (1 << 15):\\n tmp <<= 1\\n if val & (1 << 15):\\n tmp += 1\\n tmp ^= 0x8005\\n else:\\n tmp <<= 1\\n if val & (1 << 15):\\n tmp += 1\\n val <<= 1\\n tmp &= 0xffff\\n return tmp\",\n \"def test_special_U(self):\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, -0.1).to_matrix(), \\\"U\\\", {})\\n self.check_oneq_special_cases(U3Gate(0.0, 0.1, 0.2).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.2, 0.0).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\\n self.check_oneq_special_cases(U3Gate(np.pi / 2, 0.0, 0.2).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\\n self.check_oneq_special_cases(U3Gate(0.1, 0.2, 0.3).to_matrix(), \\\"U\\\", {\\\"u\\\": 1})\",\n \"def itkScalarConnectedComponentImageFilterIUL3IUL3_cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUL3IUL3_cast(*args)\",\n \"def itkScalarConnectedComponentImageFilterIUC3IUC3_cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUC3IUC3_cast(*args)\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def I3_u1(self) -> complex:\\n # Should match in amplitude with \\\"Phase 3 current [A]\\\"\\n # Convert from relative to U32 -> relative to U1\\n return - (self.I3_u32() * cmath.rect(1, 90 / 180 * cmath.pi))\",\n \"def AssignAddHybrid3d(output, value, target=utils.CCE):\\n for i in range(output.shape[0]):\\n for j in range(output.shape[1]):\\n for k in range(output.shape[2]):\\n output[i, j, k] = output[i, j, k] + value[i, j, k]\\n\\n return output\",\n \"def chain_3(d3f_dg3, dg_dx, d2f_dg2, d2g_dx2, df_dg, d3g_dx3):\\n if np.all(dg_dx==1.) and np.all(d2g_dx2==0) and np.all(d3g_dx3==0):\\n return d3f_dg3\\n dg_dx_3 = np.clip(dg_dx, -np.inf, _lim_val_cube)**3\\n return d3f_dg3*(dg_dx_3) + 3*d2f_dg2*dg_dx*d2g_dx2 + df_dg*d3g_dx3\",\n \"def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\\n return self\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def step3(self):\\n\\t\\tif self.b[self.k] == 'e':\\n\\t\\t\\tif self.ends(\\\"icate\\\"):\\t self.r(\\\"ic\\\")\\n\\t\\t\\telif self.ends(\\\"ative\\\"): self.r(\\\"\\\")\\n\\t\\t\\telif self.ends(\\\"alize\\\"): self.r(\\\"al\\\")\\n\\t\\telif self.b[self.k] == 'i':\\n\\t\\t\\tif self.ends(\\\"iciti\\\"):\\t self.r(\\\"ic\\\")\\n\\t\\telif self.b[self.k] == 'l':\\n\\t\\t\\tif self.ends(\\\"ical\\\"):\\t self.r(\\\"ic\\\")\\n\\t\\t\\telif self.ends(\\\"ful\\\"):\\t self.r(\\\"\\\")\\n\\t\\telif self.b[self.k] == 's':\\n\\t\\t\\tif self.ends(\\\"ness\\\"):\\t self.r(\\\"\\\")\",\n \"def itkScalarConnectedComponentImageFilterIUS3IUS3_cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUS3IUS3_cast(*args)\",\n \"def convert_gcm3_AMUA3(den_gmc3):\\n return den_gmc3*const_avo/10.0\",\n \"def vs3_func_3(ns, traj, vs_def_beads_ids, vs_params):\\n i, j, k = vs_def_beads_ids\\n ang_deg, d = vs_params # degrees, nm\\n ang_rad = np.deg2rad(ang_deg) # retrieve radians\\n d = d * 10 # retrieve amgstrom for MDA\\n\\n for ts in ns.aa2cg_universe.trajectory:\\n pos_i = ns.aa2cg_universe.atoms[i].position\\n pos_j = ns.aa2cg_universe.atoms[j].position\\n pos_k = ns.aa2cg_universe.atoms[k].position\\n r_ij = pos_j - pos_i\\n r_jk = pos_k - pos_j\\n comb_ijk = r_jk - (np.dot(r_ij, r_jk) / np.dot(r_ij, r_ij)) * r_ij\\n traj[ts.frame] = pos_i + d * np.cos(ang_rad) * (r_ij / mda.lib.mdamath.norm(r_ij)) + d * np.sin(ang_rad) * (\\n comb_ijk / mda.lib.mdamath.norm(comb_ijk))\",\n \"def refugia_adj_3(params, ns):\\n #11 parameters \\n nu1, nuA, nu2, nu3, m1_1, m2_1, m2_2, m2_3, T1a, T1b, T2 = params\\n sts = moments.LinearSystem_1D.steady_state_1D(ns[0] + ns[1] + ns[2])\\n fs = moments.Spectrum(sts)\\n fs = moments.Manips.split_1D_to_2D(fs, ns[0], ns[1] + ns[2])\\n ## Population function and migration matrix for T1a\\n nu_T1 = [nu1, nuA]\\n fs.integrate(nu_T1, T1a)\\n ## Population function and migration matrix for T1b\\n mig1 = numpy.array([[0, m1_1],[m1_1, 0]])\\n fs.integrate(nu_T1, T1b, m=mig1) \\n fs = moments.Manips.split_2D_to_3D_2(fs, ns[1], ns[2])\\n ## Population function and migration matrix for T2\\n nu_T2 = [nu1, nu2, nu3]\\n mig2 = numpy.array([[0, m2_1, m2_3],[m2_1, 0, m2_2], [m2_3, m2_2, 0]]) \\n fs.integrate(nu_T2, T2, m=mig2)\\n return fs\",\n \"def itkHuangThresholdImageFilterIUC3IUS3_cast(obj: 'itkLightObject') -> \\\"itkHuangThresholdImageFilterIUC3IUS3 *\\\":\\n return _itkHuangThresholdImageFilterPython.itkHuangThresholdImageFilterIUC3IUS3_cast(obj)\",\n \"def loss_step3(self, y, u, v):\\n uv = -0.5 * (y.float().t() @ (u + v))\\n return uv\",\n \"def correlation_4op_3t(self, rho0, oplist, signature, tau):\\n\\n\\n if len(oplist) != 4:\\n raise ValueError('Number of operators is not 4.')\\n\\n a = operator_to_superoperator(oplist[0], signature[0])\\n b = operator_to_superoperator(oplist[1], signature[1])\\n c = operator_to_superoperator(oplist[2], signature[2])\\n d = operator_to_superoperator(oplist[3], signature[3])\\n\\n for _ in oplist:\\n if issparse(_):\\n _ = _.toarray()\\n\\n\\n # nmax = max(len(tau3), len(tau2), len(tau1))\\n\\n # g = -1j * (tau > 0) * self.propagator(tau)\\n # G = np.zeros((self.dim, self.dim, len(tau)))\\n\\n # for n, elem in enumerate(g):\\n # G[:,:, n] = g[n]\\n\\n if self.G is None:\\n self.propagator(tau)\\n\\n G = self.G\\n\\n # unit operator in Liouville space\\n N = self.dim\\n idm = self.idm(sp=False)\\n\\n # print(d.shape, dm2vec(rho0.toarray()).shape)\\n if issparse(rho0):\\n rho = d.dot(dm2vec(rho0.toarray()))\\n else:\\n rho = d.dot(dm2vec(rho0))\\n\\n # print(type(rho), rho.shape)\\n\\n if issparse(rho): rho = rho.toarray()\\n\\n tmp = np.tensordot(G, rho, axes=((1), (0)))\\n tmp = c.dot(tmp)\\n tmp = np.tensordot(G, tmp, axes=([1], [0])) # ajk\\n\\n # tmp = np.einsum('dcj, ca, abk, b -> djk', G, c, G, rho)\\n\\n\\n '''\\n Scipy sparse matrix does not support dimensions more than 2, so\\n ndarray has to be used for the tensor products.\\n\\n This can be improved by using sparse package.\\n '''\\n tmp = np.tensordot(b.todense(), tmp, axes=([1], [0]))\\n # tmp = b.todense().dot(tmp)\\n\\n tmp = np.tensordot(G, tmp, axes=([1], [0]))\\n\\n return oe.contract('a, ab, bijk -> ijk', idm, a.todense(), tmp)\\n\\n # corr = np.einsum('a, ab, bck, bc, cdj, de, efi, f ->kji', idm, \\\\\\n # left(a), G, left(b), left(c), G, left(d).dot(dm2vec(rho0))\\n\\n # return\",\n \"def create_p3_feature(C3, C4, C5, feature_size=256):\\n P5 = keras.layers.Conv2D(feature_size, kernel_size=1, strides=1, padding='same', name='C5_reduced')(C5)\\n P5_upsampled = layers.UpsampleLike(name='P5_upsampled')([P5, C4])\\n\\n # add P5 elementwise to C4\\n P4 = keras.layers.Conv2D(feature_size, kernel_size=1, strides=1, padding='same', name='C4_reduced')(C4)\\n P4 = keras.layers.Add(name='P4_merged')([P5_upsampled, P4])\\n P4_upsampled = layers.UpsampleLike(name='P4_upsampled')([P4, C3])\\n\\n # add P4 elementwise to C3\\n P3 = keras.layers.Conv2D(feature_size, kernel_size=1, strides=1, padding='same', name='C3_reduced')(C3)\\n P3 = keras.layers.Add(name='P3_merged')([P4_upsampled, P3])\\n P3 = keras.layers.Conv2D(feature_size, kernel_size=3, strides=1, padding='same', name='P3')(P3)\\n\\n return P3\",\n \"def fully_connected3(self):\\n self.weights3 = tf.get_variable(\\\"weights3\\\", shape=[12, 10],\\n initializer=tf.contrib.layers.xavier_initializer()) \\n \\n self.bias3 = tf.get_variable('bias3', dtype = tf.float32, \\n initializer = tf.random_normal([1])) \\n self.hidden_layer3 = tf.matmul(self.data, self.weights3) + self.bias3\\n \\n self.initialize_and_train()\",\n \"def itkBinaryContourImageFilterIUC3IUC3_cast(obj: 'itkLightObject') -> \\\"itkBinaryContourImageFilterIUC3IUC3 *\\\":\\n return _itkBinaryContourImageFilterPython.itkBinaryContourImageFilterIUC3IUC3_cast(obj)\",\n \"def _action_op_u1(self, plaq):\\n # if self.link_type == 'U1':\\n # return np.cos(plaq)\\n return tf.math.cos(plaq)\",\n \"def GachaCraftNodeExcelAddGP1103(builder, GP1103):\\n return AddGP1103(builder, GP1103)\",\n \"def cu1(self, q0, q1, alpha=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U1, qid=[q0,q1], phase=alpha, ctrl=ctrl)\\n return self\",\n \"def k3(self, f, t, u, k2, usereverse=False):\\n\\n h = self._delta_t / 2.0\\n\\n v = u + h * k2\\n tt = t + h\\n\\n if usereverse:\\n output, storagez, storagew = f(tt, v)\\n\\n self.storagez.append(storagez)\\n self.storagew.append(storagew)\\n\\n return output\\n else:\\n return f(tt, v)\",\n \"def cz(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CZ(), target=[control, target])\",\n \"def r_3(comps: 'list(Compound)', is_input):\\r\\n react: str\\r\\n\\r\\n if is_input:\\r\\n iSiMe = Compound(\\\"Zn\\\")\\r\\n if len(comps) == 1:\\r\\n if \\\"iSi\\\" in comps[0].comp_type:\\r\\n iSiMe = comps[0]\\r\\n else:\\r\\n if \\\"iSi\\\" in comps[0].comp_type:\\r\\n iSiMe = comps[0]\\r\\n else:\\r\\n iSiMe = comps[1]\\r\\n\\r\\n me = list(iSiMe.formula.consist.keys())[0].name\\r\\n if me in [\\\"Au\\\", \\\"Pt\\\"]:\\r\\n return \\\"\\\"\\r\\n me_oxs = get_me_oxs(me)\\r\\n if me_oxs == 0:\\r\\n return \\\"\\\"\\r\\n if is_me_activer(\\\"H\\\", 1, me, me_oxs):\\r\\n return \\\"\\\"\\r\\n\\r\\n iSaNo = Compound(iSaNo_create(me, me_oxs, \\\"NO3\\\", 1))\\r\\n\\r\\n react = f\\\"{iSiMe} + HNO3 -> {iSaNo} + N2O + H2O\\\"\\r\\n else:\\r\\n iSaNo = Compound(\\\"Zn(NO3)2\\\")\\r\\n if len(comps) == 1:\\r\\n if \\\"iSaNo\\\" in comps[0].comp_type:\\r\\n iSaNo = comps[0]\\r\\n elif len(comps) == 2:\\r\\n if \\\"iSaNo\\\" in comps[0].comp_type:\\r\\n iSaNo = comps[0]\\r\\n elif \\\"iSaNo\\\" in comps[1].comp_type:\\r\\n iSaNo = comps[1]\\r\\n else:\\r\\n if \\\"iSaNo\\\" in comps[0].comp_type:\\r\\n iSaNo = comps[0]\\r\\n elif \\\"iSaNo\\\" in comps[1].comp_type:\\r\\n iSaNo = comps[1]\\r\\n else:\\r\\n iSaNo = comps[2]\\r\\n\\r\\n ((me, me_oxs), (an, an_oxs)) = iSa_oxs(iSaNo.formula)\\r\\n if an != \\\"NO3\\\":\\r\\n return \\\"\\\"\\r\\n if me in [\\\"Au\\\", \\\"Pt\\\"]:\\r\\n return \\\"\\\"\\r\\n if is_me_activer(\\\"H\\\", 1, me, me_oxs):\\r\\n return \\\"\\\"\\r\\n\\r\\n iSiMe = Compound(simple(me))\\r\\n\\r\\n react = f\\\"{iSiMe} + HNO3 -> {iSaNo} + N2O + H2O\\\"\\r\\n\\r\\n return Reaction(react)\",\n \"def Closure_Phase(self, uv1, uv2, uv3):\\n phi1 = self.Phase(*uv1)\\n phi2 = self.Phase(*uv2)\\n phi3 = self.Phase(*uv3)\\n cphi = phi1 - phi2 + phi3\\n cphi[cphi < -pi] += 2 * pi\\n cphi[cphi > pi] -= 2 * pi\\n return cphi\",\n \"def ControlledU(U):\\n\\n d = U.rank // 2 + 1\\n shape = [2] * 2 * d\\n t = np.zeros(shape, dtype=np.complex128)\\n\\n # If the first bit is zero, fill in as the identity operator.\\n t[:, 0, ...] = Identity(d)[:, 0, ...]\\n # Else, fill in as Identity tensored with U (Identity for the first bit,\\n # which remains unchanged.\\n t[:, 1, ...] = (Identity() * U)[:, 1, ...]\\n return Operator(t)\",\n \"def updateATOM3instance( self, atom3i ):\\r\\n self.cb = atom3i.cb \\r\\n self.atom3i = atom3i\",\n \"def addThreeNodesRig(self):\\r\\n cam = self.nativePointer()\\r\\n\\r\\n # create controls\\r\\n pos = mxs.star(radius1 = 6.5, radius2 = 5.5, points=16)\\r\\n trans = mxs.rectangle(length=10.2, width=4.5)\\r\\n rot = mxs.ngon(radius=2.0, nSides=3, corner_radius=0.5)\\r\\n\\r\\n # rename controls\\r\\n pos.name = str(cam.name) + 'position'\\r\\n trans.name = str(cam.name) + 'translation'\\r\\n rot.name = str(cam.name) + 'rotation'\\r\\n\\r\\n # rotate controls into place\\r\\n pos.rotation = mxs.eulerangles(90, 0 , 0)\\r\\n trans.rotation = mxs.eulerangles(90, 0 , 0)\\r\\n rot.rotation = mxs.eulerangles(0, 0, -90)\\r\\n\\r\\n # reset xforms\\r\\n mxs.resetxform(pos)\\r\\n mxs.resetxform(trans)\\r\\n mxs.resetxform(rot)\\r\\n\\r\\n # collapse xforms\\r\\n mxs.maxOps.CollapseNode(pos, True)\\r\\n mxs.maxOps.CollapseNode(trans, True)\\r\\n mxs.maxOps.CollapseNode(rot, True)\\r\\n\\r\\n rot.parent = trans\\r\\n trans.parent = pos\\r\\n\\r\\n pos.wirecolor = rot.wirecolor = trans.wirecolor = mxs.color(0, 230, 250)\\r\\n\\r\\n # Move the rig to align with the cam\\r\\n pivrot=cam.rotation\\r\\n pos.rotation*=pivrot;\\r\\n #pos.objectoffsetrot*=pivrot;\\r\\n #pos.objectoffsetpos*=pivrot;\\r\\n\\r\\n pos.position = cam.position\\r\\n #mxs.resetxform(pos)\\r\\n #pos.rotation = cam.rotation\\r\\n\\r\\n\\r\\n # parent the cam to to rig\\r\\n cam.parent = rot\\r\\n\\r\\n return True\",\n \"def itkHuangThresholdImageFilterIUS3IUC3_cast(obj: 'itkLightObject') -> \\\"itkHuangThresholdImageFilterIUS3IUC3 *\\\":\\n return _itkHuangThresholdImageFilterPython.itkHuangThresholdImageFilterIUS3IUC3_cast(obj)\",\n \"def process_block_to_add(coupling_point: Point, coupling_angle : Angle, conjugation_angle : Angle, cc_bond_length:float, block_to_add: Building_Block):\\n\\n\\t#load data for block_to_add\\n\\tcoord_xyz = top.read_xyz_file(block_to_add.path)\\n\\tcoord_xyz_save = np.copy(coord_xyz)\\n\\n\\t\\n\\n\\t#rotate around z axis for conjugation, rotate around y for right orientation,shift to coupling point and shift by c-c bond length in right direction\\n\\tfor i in range(0,coord_xyz.shape[1]):\\n\\t\\t\\n\\t\\t#conjugation x' = cos(phi)*x-sin(phi)*y\\n\\t\\tcoord_xyz[1,i] = coord_xyz_save[1,i]*np.cos(conjugation_angle)-np.sin(conjugation_angle)*coord_xyz_save[2,i]\\n\\t\\t#conjugation y' = sin(phi)*x+cos(phi)*y\\n\\t\\tcoord_xyz[2,i] = coord_xyz_save[1,i]*np.sin(conjugation_angle)+np.cos(conjugation_angle)*coord_xyz_save[2,i]\\n\\n\\t\\tcoord_xyz_save = np.copy(coord_xyz)\\n\\n\\t\\t#rotation around y: x' = cos(phi)*x+sin(phi)*z\\n\\t\\tcoord_xyz[1,i] = coord_xyz_save[1,i]*np.cos(coupling_angle)+np.sin(coupling_angle)*coord_xyz_save[3,i]\\n\\t\\t#rotation around y: z' = cos(phi)*z-sin(phi)*x\\n\\t\\tcoord_xyz[3,i] = -coord_xyz_save[1,i]*np.sin(coupling_angle)+np.cos(coupling_angle)*coord_xyz_save[3,i]\\n\\n\\t\\t#shift to coupling point x -> x+x_c\\n\\t\\tcoord_xyz[1,i] = coord_xyz[1,i]+coupling_point.x\\n\\t\\t#shift to coupling point y -> y+y_c\\n\\t\\tcoord_xyz[2,i] = coord_xyz[2,i]+coupling_point.y\\n\\t\\t#shift to coupling point z -> z+z_c\\n\\t\\tcoord_xyz[3,i] = coord_xyz[3,i]+coupling_point.z\\n\\n\\t\\t#shift by C-C bond length in e_c direction sin=-0.866 cos=-0.499\\n\\t\\tcoord_xyz[1,i] = coord_xyz[1,i]+cc_bond_length*np.sin(coupling_angle)\\n\\t\\t#shift by C-C bond length in e_c direction\\n\\t\\tcoord_xyz[3,i] = coord_xyz[3,i]+cc_bond_length*np.cos(coupling_angle)\\n\\treturn coord_xyz\",\n \"def itkBinaryContourImageFilterIUS3IUS3_cast(obj: 'itkLightObject') -> \\\"itkBinaryContourImageFilterIUS3IUS3 *\\\":\\n return _itkBinaryContourImageFilterPython.itkBinaryContourImageFilterIUS3IUS3_cast(obj)\",\n \"def itkBoundedReciprocalImageFilterIUC3IUC3_cast(*args):\\n return _itkBoundedReciprocalImageFilterPython.itkBoundedReciprocalImageFilterIUC3IUC3_cast(*args)\",\n \"def upconv_block(i, filters, shape, activation='relu', padding='same',\\n data_format='channels_first'):\\n c1 = Conv3D(filters, shape, activation=activation,\\n padding=padding, data_format=data_format)(i)\\n c2 = Conv3D(filters, shape, activation=activation,\\n padding=padding, data_format=data_format)(c1)\\n u = UpSampling3D(size=(1, 2, 2), data_format=data_format)(c2)\\n c3 = Conv3D(int(filters / 2),\\n (1, 2, 2),\\n activation=activation,\\n padding=padding,\\n data_format=data_format)(u)\\n return c3\",\n \"def new(self, u, k1, k2, k3, k4):\\n\\n v = self.combine(k1, k2, k3, k4)\\n\\n return u + (self._delta_t / 6.0) * v\",\n \"def _delayandsum3(data, offsets, ifactor2, steeramp, out, autopower):\\n gridsize, numchannels = offsets.shape\\n for gi in nb.prange(gridsize):\\n out[gi] = 0\\n autopower[gi] = 0\\n for mi in range(numchannels):\\n ind = offsets[gi,mi]\\n r = (data[ind,mi] * (1-ifactor2[gi,mi]) \\\\\\n + data[ind+1,mi] * ifactor2[gi,mi]) * steeramp[gi,mi]\\n out[gi] += r\\n autopower[gi] += r*r\",\n \"def comp_add_ao(self):\\n scene = self.set_as_active()\\n scene.use_nodes = True\\n tree = scene.node_tree\\n tree.nodes.clear()\\n\\n # creating the nodes\\n node_rlayer = tree.nodes.new('CompositorNodeRLayers')\\n node_rlayer.location = -300, 100\\n node_rlayer.scene = scene\\n node_rlayer.layer = w_var.rlname\\n\\n node_mixcolor = tree.nodes.new('CompositorNodeMixRGB')\\n node_mixcolor.location = 0, 50\\n node_mixcolor.blend_type = 'MULTIPLY'\\n node_mixcolor.inputs[0].default_value = 0.730\\n\\n node_comp = tree.nodes.new('CompositorNodeComposite')\\n node_comp.location = 300, 130\\n\\n node_viewer = tree.nodes.new('CompositorNodeViewer')\\n node_viewer.location = 300, -100\\n\\n # connecting the nodes\\n links = tree.links\\n links.new(node_rlayer.outputs[0], node_mixcolor.inputs[1])\\n links.new(node_rlayer.outputs[10], node_mixcolor.inputs[2])\\n links.new(node_mixcolor.outputs[0], node_comp.inputs[0])\\n links.new(node_mixcolor.outputs[0], node_viewer.inputs[0])\\n\\n for node in tree.nodes:\\n node.select = False\",\n \"def _ice_d3gdt3(temp,pres):\\n # Reduced variables\\n tn = temp/_TTP\\n pn = pres/_PTPE\\n _PI0 = _PATM/_PTPE\\n g_ttt = 0.\\n \\n # Residual terms including complex numbers\\n sr = [_GCOEFFS[1], complex(0.0,0.0)]\\n for (k,rk) in enumerate(_GCOEFFS[2]):\\n sr[1] += rk * (pn-_PI0)**k\\n for (tk,s) in zip(_GCOEFFS[3],sr):\\n term = 1./(tk-tn)**2 - 1./(tk+tn)**2\\n g_ttt += (s * term).real / _TTP**2\\n return g_ttt\",\n \"def _rewrite_cg(expr):\\n j1, m1, j2, m2, j3, m3 = symbols(\\n 'j1 m1 j2 m2 j3 m3', cls=Wild\\n )\\n return expr.replace(\\n CG(j1, m1, j2, m2, j3, m3),\\n _NEG_UNITY ** (-j1 + j2 - m3) * sqrt(2 * j3 + 1) * Wigner3j(\\n j1, m1, j2, m2, j3, -m3\\n )\\n )\",\n \"def get_tx_gain3(self, tx_gain3):\\n\\t\\treturn self._tx_gain3\",\n \"def reduce_3sat_to_3col(instance, G = None):\\n G = Graph() if G is None else G\\n\\n # add common gadget\\n G.add_named_vertex('T')\\n G.add_named_vertex('F')\\n G.add_named_vertex('X')\\n G.add_edge('T', 'F')\\n G.add_edge('F', 'X')\\n G.add_edge('X', 'T')\\n\\n\\n # add gadget for variables\\n variables = sorted(set([abs(v) for clause in instance for v in clause]))\\n\\n for v in variables:\\n G.add_named_vertex(v)\\n G.add_named_vertex(-v)\\n G.add_edge('X', v)\\n G.add_edge('X', -v)\\n G.add_edge(v, -v)\\n\\n G.set_vertex_index(max(variables) + 1)\\n # add the clause gadgets\\n for a, b, c in instance:\\n g1, g2, g3, g4, g5 = [G.add_vertex() for _i in range(5)]\\n\\n # triangle 1,2,3\\n G.add_edge(g1, g2) # 1\\n G.add_edge(g2, g3) # 2\\n G.add_edge(g3, g1) # 3\\n\\n # bridge betwen triangle 1,2,3T and 4,5,T\\n G.add_edge(g3, g4) # 4\\n\\n # triangle 3,4,5\\n G.add_edge(g4, g5) # 5\\n G.add_edge(g5, 'T') # 6\\n G.add_edge('T', g4) # 7\\n\\n # edges for clause a,b,c\\n G.add_edge(a, g1) # 8\\n G.add_edge(b, g2) # 9\\n G.add_edge(c, g5) # 10\\n\\n return G\",\n \"def f3a_abSymmetrized_old(self,a,b,c):\\n return (self.f3a_ab(a,b,c) + self.f3a_ab(a,b,-c) +\\\\\\n self.f3ab_a(a,b,c) + self.f3ab_a(a,b,-c) +\\\\\\n self.f3ba_a(a,b,c) + self.f3ba_a(a,b,-c))/6.\",\n \"def convert_AMUA3_gcm3(den_AMUA3):\\n return den_AMUA3/const_avo*10.0\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def add_mult(num1, num2, num3):\\n \\n addmult = (num1 + num2) * num3\\n return addmult\",\n \"def convert_conv3d(g, op, block):\\n\\n dilations = op.attr(\\\"dilations\\\")\\n groups = op.attr(\\\"groups\\\")\\n paddings = op.attr(\\\"paddings\\\")\\n padding_algorithm = op.attr(\\\"padding_algorithm\\\")\\n strides = op.attr(\\\"strides\\\")\\n\\n kernel = g.get_node(op.input(\\\"Filter\\\")[0])\\n input_x = g.get_node(op.input(\\\"Input\\\")[0])\\n data_layout = op.attr(\\\"data_format\\\")\\n out_channels, _, k_d, k_h, k_w = infer_shape(kernel)\\n if padding_algorithm == \\\"VALID\\\":\\n paddings = [0, 0, 0]\\n elif padding_algorithm == \\\"SAME\\\":\\n dilations = [1, 1, 1]\\n input_x = autopad(input_x, strides, [k_d, k_h, k_w], dilations)\\n paddings = [0, 0, 0]\\n elif padding_algorithm == \\\"EXPLICIT\\\":\\n if len(paddings) == 3:\\n paddings = [\\n paddings[0],\\n paddings[1],\\n paddings[2],\\n paddings[0],\\n paddings[1],\\n paddings[2],\\n ]\\n elif len(paddings) == 6:\\n paddings = [\\n paddings[0],\\n paddings[3],\\n paddings[1],\\n paddings[4],\\n paddings[2],\\n paddings[5],\\n ]\\n else:\\n msg = f'Value {padding_algorithm} in attribute \\\"padding\\\" of operator Conv is not \\\"valid.\\\"'\\n raise tvm.error.OpAttributeInvalid(msg)\\n\\n out = _op.nn.conv3d(\\n input_x,\\n kernel,\\n strides=strides,\\n padding=paddings,\\n dilation=dilations,\\n groups=groups,\\n channels=out_channels,\\n kernel_size=[k_d, k_h, k_w],\\n data_layout=data_layout,\\n )\\n g.add_node(op.output(\\\"Output\\\")[0], out)\",\n \"def convert_relu6(g, op, block):\\n\\n x = g.get_node(op.input(\\\"X\\\")[0])\\n out = _op.clip(x, 0.0, 6.0)\\n g.add_node(op.output(\\\"Out\\\")[0], out)\",\n \"def cifar100_aug3():\\n normalize = transforms.Normalize(mean=(0.5071, 0.4865, 0.4409), std=(0.2673, 0.2564, 0.2762))\\n transform_t = transforms.Compose([\\n transforms.RandomCrop(32, 4),\\n transforms.RandomHorizontalFlip(),\\n transforms.ToTensor(),\\n normalize,\\n ])\\n transform_v = transforms.Compose([\\n transforms.ToTensor(),\\n normalize,\\n ])\\n return cifar100_altaug(transform_t, transform_v)\",\n \"def set_tx_gain3(self, tx_gain3):\\n\\t\\tif (tx_gain3 in range(-13, 19)):\\n\\t\\t\\tself._tx_gain3 = tx_gain3\\n\\t\\telse:\\n\\t\\t\\tsys.stderr.write(\\\"\\\\nERROR : %s tx_gain3 must be an integer between -13 and 18 so it can't be %s !\\\\n\\\" % (self._target_id, tx_gain3))\\n\\t\\t\\tsys.exit(1)\",\n \"def setup_threeCtrl(lf_lidrails, rt_lidrails):\\n # Declare control variables\\n lf_up = ['lf_lid01_tp01_ccc', 'lf_lid01_tp02_ccc', 'lf_lid01_tp03_ccc']\\n lf_dn = ['lf_lid01_dn01_ccc', 'lf_lid01_dn02_ccc', 'lf_lid01_dn03_ccc']\\n rt_up = ['rt_lid01_tp01_ccc', 'rt_lid01_tp02_ccc', 'rt_lid01_tp03_ccc']\\n rt_dn = ['rt_lid01_dn01_ccc', 'rt_lid01_dn02_ccc', 'rt_lid01_dn03_ccc']\\n\\n # Connect lidRails ramps to lid profile controls\\n\\n # ========\\n # lf_up\\n\\n # inner\\n cmds.connectAttr(lf_up[0] + '.tx', lf_lidrails + '.offsettop[0].offsettop_Position', f=True)\\n cmds.connectAttr(lf_up[0] + '.ty', lf_lidrails + '.offsettop[0].offsettop_FloatValue', f=True)\\n # mid\\n lf_lid01_um01_adn = cmds.createNode('addDoubleLinear', n='lf_lid01_um01_addDoubleLinear')\\n cmds.connectAttr(lf_up[1] + '.tx', lf_lid01_um01_adn + '.input1', f=True)\\n cmds.setAttr(lf_lid01_um01_adn + '.input2', 0.5)\\n cmds.connectAttr(lf_lid01_um01_adn + '.output', lf_lidrails + '.offsettop[1].offsettop_Position', f=True)\\n cmds.connectAttr(lf_up[1] + '.ty', lf_lidrails + '.offsettop[1].offsettop_FloatValue', f=True)\\n # outer\\n lf_lid01_uo01_adn = cmds.createNode('addDoubleLinear', n='lf_lid01_uo01_addDoubleLinear')\\n cmds.connectAttr(lf_up[2] + '.tx', lf_lid01_uo01_adn + '.input1', f=True)\\n cmds.setAttr(lf_lid01_uo01_adn + '.input2', 1.0)\\n cmds.connectAttr(lf_lid01_uo01_adn + '.output', lf_lidrails + '.offsettop[2].offsettop_Position', f=True)\\n cmds.connectAttr(lf_up[2] + '.ty', lf_lidrails + '.offsettop[2].offsettop_FloatValue', f=True)\\n\\n # ========\\n # lf_dn\\n\\n # Reverse node\\n lf_dn_rvn = cmds.createNode('reverse', n='lf_lid01_dn01_reverse')\\n # inner\\n cmds.connectAttr(lf_dn[0] + '.tx', lf_lidrails + '.offsetbottom[0].offsetbottom_Position', f=True)\\n cmds.connectAttr(lf_dn[0] + '.ty', lf_dn_rvn + '.inputX', f=True)\\n cmds.connectAttr(lf_dn_rvn + '.outputX', lf_lidrails + '.offsetbottom[0].offsetbottom_FloatValue', f=True)\\n # mid\\n lf_lid01_dm01_adn = cmds.createNode('addDoubleLinear', n='lf_lid01_dm01_addDoubleLinear')\\n cmds.connectAttr(lf_dn[1] + '.tx', lf_lid01_dm01_adn + '.input1', f=True)\\n cmds.setAttr(lf_lid01_dm01_adn + '.input2', 0.5)\\n cmds.connectAttr(lf_lid01_dm01_adn + '.output', lf_lidrails + '.offsetbottom[1].offsetbottom_Position', f=True)\\n cmds.connectAttr(lf_dn[1] + '.ty', lf_dn_rvn + '.inputY', f=True)\\n cmds.connectAttr(lf_dn_rvn + '.outputY', lf_lidrails + '.offsetbottom[1].offsetbottom_FloatValue', f=True)\\n # outer\\n lf_lid01_do01_adn = cmds.createNode('addDoubleLinear', n='lf_lid01_do01_addDoubleLinear')\\n cmds.connectAttr(lf_dn[2] + '.tx', lf_lid01_do01_adn + '.input1', f=True)\\n cmds.setAttr(lf_lid01_do01_adn + '.input2', 1.0)\\n cmds.connectAttr(lf_lid01_do01_adn + '.output', lf_lidrails + '.offsetbottom[2].offsetbottom_Position', f=True)\\n cmds.connectAttr(lf_dn[2] + '.ty', lf_dn_rvn + '.inputZ', f=True)\\n cmds.connectAttr(lf_dn_rvn + '.outputZ', lf_lidrails + '.offsetbottom[2].offsetbottom_FloatValue', f=True)\\n\\n # ========\\n # rt_up\\n\\n # inner\\n rt_lid01_ui01_asn = cmds.createNode('plusMinusAverage', n='rt_lid01_ui01_plusMinusAverage')\\n cmds.setAttr(rt_lid01_ui01_asn + '.operation', 2)\\n cmds.setAttr(rt_lid01_ui01_asn + '.input1D[0]', 1.0)\\n cmds.connectAttr(rt_up[0] + '.tx', rt_lid01_ui01_asn + '.input1D[1]', f=True)\\n cmds.connectAttr(rt_lid01_ui01_asn + '.output1D', rt_lidrails + '.offsettop[2].offsettop_Position', f=True)\\n cmds.connectAttr(rt_up[0] + '.ty', rt_lidrails + '.offsettop[2].offsettop_FloatValue', f=True)\\n # mid\\n rt_lid01_um01_mdn = cmds.createNode('multDoubleLinear', n='rt_lid01_um01_multDoubleLinear')\\n rt_lid01_um01_adn = cmds.createNode('addDoubleLinear', n='rt_lid01_um01_addDoubleLinear')\\n cmds.connectAttr(rt_up[1] + '.tx', rt_lid01_um01_mdn + '.input1', f=True)\\n cmds.setAttr(rt_lid01_um01_mdn + '.input2', -1.0)\\n cmds.connectAttr(rt_lid01_um01_mdn + '.output', rt_lid01_um01_adn + '.input1', f=True)\\n cmds.setAttr(rt_lid01_um01_adn + '.input2', 0.5)\\n cmds.connectAttr(rt_lid01_um01_adn + '.output', rt_lidrails + '.offsettop[1].offsettop_Position', f=True)\\n cmds.connectAttr(rt_up[1] + '.ty', rt_lidrails + '.offsettop[1].offsettop_FloatValue', f=True)\\n # outer\\n rt_lid01_uo_mdn = cmds.createNode('multDoubleLinear', n='rt_lid01_uo_multDoubleLinear')\\n cmds.connectAttr(rt_up[2] + '.tx', rt_lid01_uo_mdn + '.input1', f=True)\\n cmds.setAttr(rt_lid01_uo_mdn + '.input2', -1.0)\\n cmds.connectAttr(rt_lid01_uo_mdn + '.output', rt_lidrails + '.offsettop[0].offsettop_Position', f=True)\\n cmds.connectAttr(rt_up[2] + '.ty', rt_lidrails + '.offsettop[0].offsettop_FloatValue', f=True)\\n\\n # ========\\n # rt_dn\\n\\n # Reverse node\\n rt_dn_rvn = cmds.createNode('reverse', n='rt_lid01_dn01_reverse')\\n # inner\\n rt_lid01_di01_asn = cmds.createNode('plusMinusAverage', n='rt_lid01_di01_plusMinusAverage')\\n cmds.setAttr(rt_lid01_di01_asn + '.operation', 2)\\n cmds.setAttr(rt_lid01_di01_asn + '.input1D[0]', 1.0)\\n cmds.connectAttr(rt_dn[0] + '.tx', rt_lid01_di01_asn + '.input1D[1]', f=True)\\n cmds.connectAttr(rt_lid01_di01_asn + '.output1D', rt_lidrails + '.offsetbottom[0].offsetbottom_Position', f=True)\\n cmds.connectAttr(rt_dn[0] + '.ty', rt_dn_rvn + '.inputX', f=True)\\n cmds.connectAttr(rt_dn_rvn + '.outputX', rt_lidrails + '.offsetbottom[0].offsetbottom_FloatValue', f=True)\\n # mid\\n rt_lid01_dm01_asn = cmds.createNode('plusMinusAverage', n='rt_lid01_dm01_plusMinusAverage')\\n cmds.setAttr(rt_lid01_dm01_asn + '.operation', 2)\\n cmds.setAttr(rt_lid01_dm01_asn + '.input1D[0]', 0.5)\\n cmds.connectAttr(rt_dn[1] + '.tx', rt_lid01_dm01_asn + '.input1D[1]', f=True)\\n cmds.connectAttr(rt_lid01_dm01_asn + '.output1D', rt_lidrails + '.offsetbottom[1].offsetbottom_Position', f=True)\\n cmds.connectAttr(rt_dn[1] + '.ty', rt_dn_rvn + '.inputY', f=True)\\n cmds.connectAttr(rt_dn_rvn + '.outputY', rt_lidrails + '.offsetbottom[1].offsetbottom_FloatValue', f=True)\\n # outer\\n rt_lid01_do01_mdn = cmds.createNode('multDoubleLinear', n='rt_lid01_do01_multDoubleLinear')\\n cmds.connectAttr(rt_dn[2] + '.tx', rt_lid01_do01_mdn + '.input1', f=True)\\n cmds.setAttr(rt_lid01_do01_mdn + '.input2', -1.0)\\n cmds.connectAttr(rt_lid01_do01_mdn + '.output', rt_lidrails + '.offsetbottom[2].offsetbottom_Position', f=True)\\n cmds.connectAttr(rt_dn[2] + '.ty', rt_dn_rvn + '.inputZ', f=True)\\n cmds.connectAttr(rt_dn_rvn + '.outputZ', rt_lidrails + '.offsetbottom[2].offsetbottom_FloatValue', f=True)\",\n \"def test_f3_circuit_maker(self):\\n fho = tfho.test_file_handle_object()\\n W = 5\\n D = 6\\n gate_maker = g.TYPE_TO_FAM3_GATE_GEN[g.TEST_TYPES.RANDOM]\\n # family 3 files:\\n circuit_file_name = \\\"circuit_file\\\"\\n circuit_file = fho.get_file_object(circuit_file_name, 'w')\\n input_file_name = \\\"input_file\\\"\\n input_file = fho.get_file_object(input_file_name, 'w')\\n output_file_name = \\\"output_file\\\"\\n output_file = fho.get_file_object(output_file_name, 'w')\\n F = 3\\n # make a family 3 circuit:\\n sr.seed(self.rand_seed)\\n gen = g.f3_circuit_maker(W, D, circuit_file, input_file, output_file,\\n gate_maker)\\n gen.generate()\\n # obtain strings representing the contents of all the resulting files:\\n circuit_string = fho.get_file(circuit_file_name).getvalue()\\n input_string = fho.get_file(input_file_name).getvalue()\\n output_string = fho.get_file(output_file_name).getvalue()\\n # make sure that the input begins and ends with a bracket:\\n self.assertEqual(\\\"[\\\", input_string[0])\\n self.assertEqual(\\\"]\\\", input_string[-1])\\n # make sure that each input element is a bit:\\n for bit in input_string[1:-1]:\\n self.assertTrue((bit == '0') or (bit == '1'))\\n # make sure that the output is a bit:\\n self.assertTrue((output_string == '0') or (output_string == '1'))\\n # make sure that the circuit header contains the correct values:\\n circuit_header = circuit_string.split(\\\"\\\\n\\\")[0]\\n (W_string, D_string, F_string) = circuit_header.split(\\\",\\\")\\n W_value = int(W_string.split(\\\"=\\\")[-1])\\n D_value = int(D_string.split(\\\"=\\\")[-1])\\n F_value = int(F_string.split(\\\"=\\\")[-1])\\n self.assertEqual(W, W_value)\\n self.assertEqual(D, D_value)\\n self.assertEqual(F, F_value)\",\n \"def f3a_ab(self,a,b,c):\\n ans = ((b*b/a) * (b*c - a)/(a*a + b*b - 2.*a*b*c)) * self.g2(a,b,-c) +\\\\\\n 7. * (b*c/a) * self.f2(a,b,-c)/2.\\n\\n return ans/18.\",\n \"def updater(c0, u, delta_t):\\n c1 = c0 + u * delta_t\\n return c1\",\n \"def vs3_func_4(ns, traj, vs_def_beads_ids, vs_params):\\n i, j, k = vs_def_beads_ids\\n a, b, c = vs_params # weight, weight, nm**(-1)\\n c = c / 10 # retrieve amgstrom**(-1) for MDA\\n\\n for ts in ns.aa2cg_universe.trajectory:\\n pos_i = ns.aa2cg_universe.atoms[i].position\\n pos_j = ns.aa2cg_universe.atoms[j].position\\n pos_k = ns.aa2cg_universe.atoms[k].position\\n r_ij = pos_j - pos_i\\n r_ik = pos_k - pos_i\\n traj[ts.frame] = pos_i + a * r_ij + b * r_ik - c * (\\n r_ij / mda.lib.mdamath.norm(r_ij) * r_ik / mda.lib.mdamath.norm(r_ik))\",\n \"def f3ba_a(self,a,b,c):\\n ans = self.g2(a,b,c)*(7.*(b*b + a*b*c) - (b/a)**2 * (a*a + a*b*c))/\\\\\\n (a*a+b*b+2.*a*b*c)\\n\\n return ans/18.\",\n \"def add_three(v1, v2, v3):\\n p = v1 + v2 + v3\\n print(\\\"The sum of the three numbers is: {}\\\".format(p))\\n return p\",\n \"def cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUL3IUL3_cast(*args)\",\n \"def New(*args, **kargs):\\n obj = itkScalarConnectedComponentImageFilterIUC3IUC3.__New_orig__()\\n import itkTemplate\\n itkTemplate.New(obj, *args, **kargs)\\n return obj\",\n \"def cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUS3IUS3_cast(*args)\",\n \"def itkSpeckleNoiseImageFilterIUC3IUC3_cast(*args):\\n return _itkSpeckleNoiseImageFilterPython.itkSpeckleNoiseImageFilterIUC3IUC3_cast(*args)\",\n \"def add_clay_to_selected(self):\\n scene = self.set_as_active()\\n\\n # if the user selected a material, use it\\n if w_var.cb_mat_clay:\\n clay_mat = bpy.data.materials[w_var.mat_clay_name]\\n\\n # else, create a new one with the color selected\\n else:\\n clay_color = w_var.color_clay\\n\\n # separating rgb and alpha\\n clay_color_rgb = clay_color[0:3]\\n clay_color_alpha = clay_color[-1]\\n clay_mat = bpy.data.materials.new('clay')\\n \\n renderengine = scene.wirebomb.data_renderengine\\n \\n if renderengine == 'CYCLES':\\n clay_mat.use_nodes = True\\n tree = clay_mat.node_tree\\n tree.nodes.clear()\\n\\n # creating the nodes\\n node_transparent = tree.nodes.new('ShaderNodeBsdfTransparent')\\n node_transparent.location = -300, 100\\n\\n node_diffuse = tree.nodes.new('ShaderNodeBsdfDiffuse')\\n node_diffuse.location = -300, -100\\n node_diffuse.inputs[0].default_value = clay_color_rgb + (1.0, )\\n node_diffuse.color = clay_color_rgb\\n node_diffuse.name = 'addon_clay_color' # referencing to this ID in the real-time change\\n\\n node_mixshader = tree.nodes.new('ShaderNodeMixShader')\\n node_mixshader.location = 0, 50\\n node_mixshader.inputs[0].default_value = clay_color_alpha\\n node_mixshader.name = 'addon_clay_alpha' # referencing to this ID in the real-time change\\n\\n node_output = tree.nodes.new('ShaderNodeOutputMaterial')\\n node_output.location = 300, 50\\n\\n # connecting the nodes\\n tree.links.new(node_transparent.outputs[0], node_mixshader.inputs[1])\\n tree.links.new(node_diffuse.outputs[0], node_mixshader.inputs[2])\\n tree.links.new(node_mixshader.outputs[0], node_output.inputs[0])\\n\\n for node in tree.nodes:\\n node.select = False\\n\\n # sets the viewport color\\n clay_mat.diffuse_color = clay_color_rgb\\n \\n elif renderengine == 'BLENDER_RENDER':\\n clay_mat.diffuse_color = clay_color_rgb\\n clay_mat.use_transparency = True\\n clay_mat.alpha = clay_color_alpha\\n\\n previous_area = bpy.context.area.type\\n bpy.context.area.type = 'VIEW_3D'\\n previous_layers = tuple(scene.layers)\\n\\n # can't enter edit mode on objects on inactive layers\\n scene.layers = (True,)*20\\n\\n for obj in scene.objects:\\n if obj.select:\\n # only enters edit mode on active object\\n scene.objects.active = obj\\n obj.data.materials.append(clay_mat)\\n clay_index = obj.data.materials.find(clay_mat.name)\\n obj.active_material_index = clay_index\\n\\n bpy.ops.object.mode_set(mode='EDIT')\\n bpy.ops.mesh.select_all(action='SELECT')\\n bpy.ops.object.material_slot_assign()\\n bpy.ops.mesh.select_all(action='SELECT')\\n bpy.ops.object.mode_set(mode='OBJECT')\\n\\n bpy.context.area.type = previous_area\\n scene.layers = previous_layers\\n\\n return clay_mat\",\n \"def shift_3_cust(self, sol_in6, cust, c_loc, curr_temp, sol_type6, sa_lns):\\r\\n\\r\\n route_ing = copy.deepcopy(sol_in6[c_loc[0]])\\r\\n route_new = route_ing\\r\\n move_to_route = c_loc[0]\\r\\n orgn_type1 = sol_type6[c_loc[0]]\\r\\n cust_folw1 = route_ing[c_loc[1] + 1]\\r\\n cust_folw2 = route_ing[c_loc[1] + 2]\\r\\n origin_cost1 = check_violation(route_ing, orgn_type1)[1]\\r\\n route_ing.remove(cust) # remove c in the current route\\r\\n del route_ing[c_loc[1]] # remove customer following c\\r\\n del route_ing[c_loc[1]] # remove customer following following c\\r\\n new_type1 = route_type(route_ing)\\r\\n adjust_cost1 = check_violation(route_ing, new_type1)[1]\\r\\n best_cut_cost0 = -1000\\r\\n best_cut_cost = best_cut_cost0 # best cost cut of moving this customer\\r\\n for j, rou in enumerate(sol_in6):\\r\\n orgn_type2 = sol_type6[j]\\r\\n origin_cost2 = check_violation(rou, orgn_type2)[1]\\r\\n if j == c_loc[0]: # moving in the same route\\r\\n for k in range(1, len(route_ing)):\\r\\n if k == c_loc[1]:\\r\\n continue\\r\\n rou_test = route_ing[:k] + [cust, cust_folw1, cust_folw2] + route_ing[k:]\\r\\n if check_violation(rou_test, orgn_type2)[0]:\\r\\n adjust_cost2 = check_violation(rou_test, orgn_type2)[1]\\r\\n cost_cut_test = origin_cost1 - adjust_cost2\\r\\n if cost_cut_test > best_cut_cost:\\r\\n best_cut_cost = cost_cut_test\\r\\n route_new = rou_test\\r\\n move_to_route = j\\r\\n\\r\\n else: # moving to a different route\\r\\n for k in range(1, len(rou)):\\r\\n rou_test = rou[:k] + [cust, cust_folw1, cust_folw2] + rou[k:]\\r\\n if check_violation(rou_test, 5)[0]:\\r\\n new_type2 = route_type(rou_test)\\r\\n adjust_cost2 = check_violation(rou_test, new_type2)[1]\\r\\n cost_cut_test = origin_cost1 + origin_cost2 - adjust_cost1 - adjust_cost2\\r\\n if cost_cut_test > best_cut_cost:\\r\\n best_cut_cost = cost_cut_test\\r\\n route_new = rou_test\\r\\n move_to_route = j\\r\\n\\r\\n\\r\\n if best_cut_cost > 1e-5:\\r\\n # print('shift3 good', best_cut_cost)\\r\\n sol_in6[move_to_route] = route_new\\r\\n sol_type6[move_to_route] = route_type(route_new)\\r\\n if move_to_route != c_loc[0]: # moving to a different route\\r\\n sol_in6[c_loc[0]] = route_ing\\r\\n sol_type6[c_loc[0]] = route_type(route_ing)\\r\\n\\r\\n elif sa_lns and best_cut_cost < -1e-5:\\r\\n\\r\\n prb = random.uniform(0, 1)\\r\\n if np.exp(best_cut_cost / curr_temp) > prb:\\r\\n # print('shift3', best_cut_cost)\\r\\n sol_in6[move_to_route] = route_new\\r\\n sol_type6[move_to_route] = route_type(route_new)\\r\\n if move_to_route != c_loc[0]: # moving to a different route\\r\\n sol_in6[c_loc[0]] = route_ing\\r\\n sol_type6[c_loc[0]] = route_type(route_ing)\",\n \"def write_reg3(self, value: int) -> None:\\n self.length_ctr_load = value >> 3\\n\\n # TODO Restart envelope\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def y3(self):\\n return self._y + self._y3\",\n \"def append_user_gate(self, user_gate):\\n self.translation['g_sect'].append(user_gate)\",\n \"def cast(*args):\\n return _itkScalarConnectedComponentImageFilterPython.itkScalarConnectedComponentImageFilterIUC3IUC3_cast(*args)\",\n \"def itkContourDirectedMeanDistanceImageFilterIUC3IUC3_cast(*args):\\n return _itkContourDirectedMeanDistanceImageFilterPython.itkContourDirectedMeanDistanceImageFilterIUC3IUC3_cast(*args)\",\n \"def format_transfer_case_three(self, tik_instance):\\n ub_ori_data = self.ub_memory\\n ub_trans_data = ub_ori_data\\n\\n loop_memory = ub_ori_data - ub_ori_data % \\\\\\n (CUBE_SIZE * CUBE_SIZE * self.dst_shape[-3] + CUBE_SIZE)\\n num_data_one_loop = self.dst_shape[-4] * self.dst_shape[-3] * \\\\\\n self.dst_shape[-2] * self.dst_shape[-1]\\n num_data_one_loop_padding = num_data_one_loop + self.dst_shape[-4] * \\\\\\n self.dst_shape[-1]\\n loop_times = (num_data_one_loop_padding + loop_memory - 1) // \\\\\\n loop_memory\\n if len(self.dst_shape) == 4:\\n total_core_loop_num = loop_times\\n else:\\n total_core_loop_num = functools_reduce(lambda x1, x2: x1 * x2,\\n self.dst_shape[:-4]) * \\\\\\n loop_times\\n core_number = _set_core_num(total_core_loop_num)\\n\\n with tik_instance.for_range(0, core_number, block_num=core_number) \\\\\\n as num_core:\\n ub_ori = tik_instance.Tensor(self.dtype,\\n (ub_ori_data,),\\n name=\\\"ub_ori\\\",\\n scope=tik.scope_ubuf)\\n ub_trans = tik_instance.Tensor(self.dtype,\\n (ub_trans_data,),\\n name=\\\"ub_trans\\\",\\n scope=tik.scope_ubuf)\\n core_loop, sum_core = _cal_core(tik_instance, total_core_loop_num,\\n num_core, core_number)\\n\\n with tik_instance.for_range(0, core_loop) as num_core_loop:\\n total_core_loop = sum_core + num_core_loop\\n num_loop_time = total_core_loop % loop_times\\n num_outer_axis = (total_core_loop - num_loop_time) // \\\\\\n loop_times\\n\\n handling_times = tik_instance.Scalar(\\\"uint64\\\")\\n is_last = tik_instance.Scalar(\\\"uint64\\\")\\n is_last.set_as(0)\\n handling_times.set_as(loop_memory // (CUBE_SIZE * CUBE_SIZE *\\n self.dst_shape[-3] +\\n CUBE_SIZE))\\n\\n with tik_instance.if_scope(num_loop_time == loop_times - 1):\\n if num_data_one_loop_padding % loop_memory == 0:\\n remainder = loop_memory\\n else:\\n remainder = num_data_one_loop_padding % loop_memory\\n handling_times.set_as((remainder + CUBE_SIZE * CUBE_SIZE *\\n self.dst_shape[-3] + CUBE_SIZE -\\n 1) // (CUBE_SIZE * CUBE_SIZE *\\n self.dst_shape[-3] +\\n CUBE_SIZE))\\n is_last.set_as(1)\\n\\n src_ub_index = 0\\n src_gm_index = num_outer_axis * self.src_shape[-1] * \\\\\\n self.src_shape[-2] + loop_memory // \\\\\\n (CUBE_SIZE * CUBE_SIZE * self.dst_shape[-3] +\\n CUBE_SIZE) * num_loop_time * CUBE_SIZE\\n with tik_instance.for_range(0, self.src_shape[-2]) as num_cube:\\n tik_instance.data_move(ub_ori[src_ub_index +\\n num_cube *\\n handling_times *\\n self.dst_shape[-1]],\\n self.src_gm[src_gm_index +\\n num_cube *\\n self.src_shape[-1]],\\n 0, 1,\\n (handling_times * CUBE_SIZE +\\n self.num_data - 1) //\\n self.num_data, 0, 0)\\n\\n self.data_rearrange_case_one(tik_instance, ub_ori, ub_trans,\\n handling_times, is_last)\\n dst_gm_index = num_outer_axis * num_data_one_loop + \\\\\\n loop_memory // \\\\\\n (CUBE_SIZE * CUBE_SIZE * self.dst_shape[-3] +\\n CUBE_SIZE) * (CUBE_SIZE * CUBE_SIZE *\\n self.dst_shape[-3]) * \\\\\\n num_loop_time\\n tik_instance.data_move(self.dst_gm[dst_gm_index], ub_trans[0],\\n 0, handling_times,\\n CUBE_SIZE * self.dst_shape[-3] *\\n CUBE_SIZE // self.num_data,\\n self.num_byte // 2, 0)\\n\\n return tik_instance\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def f3ab_a(self,a,b,c):\\n ans = 7*b*c/a * self.f2(b,a,-c)/2. + \\\\\\n (b*b/a)*(b*c-a)/(a*a+b*b-2.*a*b*c)*self.g2(b,a,-c) +\\\\\\n self.g2(a,b,c)*(7.*(b*b + a*b*c) - (b/a)**2 * (a*a + a*b*c))/\\\\\\n (a*a+b*b+2.*a*b*c)\\n\\n return ans/18.\",\n \"def itkBoundedReciprocalImageFilterIUL3IUL3_cast(*args):\\n return _itkBoundedReciprocalImageFilterPython.itkBoundedReciprocalImageFilterIUL3IUL3_cast(*args)\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def c3d(self):\\n model = Sequential()\\n # 1st layer group\\n model.add(Conv3D(64, 3, 3, 3, activation='relu',\\n border_mode='same', name='conv1',\\n subsample=(1, 1, 1),\\n input_shape=self.input_shape))\\n model.add(MaxPooling3D(pool_size=(1, 2, 2), strides=(1, 2, 2),\\n border_mode='valid', name='pool1'))\\n # 2nd layer group\\n model.add(Conv3D(128, 3, 3, 3, activation='relu',\\n border_mode='same', name='conv2',\\n subsample=(1, 1, 1)))\\n model.add(MaxPooling3D(pool_size=(2, 2, 2), strides=(2, 2, 2),\\n border_mode='valid', name='pool2'))\\n # 3rd layer group\\n model.add(Conv3D(256, 3, 3, 3, activation='relu',\\n border_mode='same', name='conv3a',\\n subsample=(1, 1, 1)))\\n model.add(Conv3D(256, 3, 3, 3, activation='relu',\\n border_mode='same', name='conv3b',\\n subsample=(1, 1, 1)))\\n model.add(MaxPooling3D(pool_size=(2, 2, 2), strides=(2, 2, 2),\\n border_mode='valid', name='pool3'))\\n # 4th layer group\\n model.add(Conv3D(512, 3, 3, 3, activation='relu',\\n border_mode='same', name='conv4a',\\n subsample=(1, 1, 1)))\\n model.add(Conv3D(512, 3, 3, 3, activation='relu',\\n border_mode='same', name='conv4b',\\n subsample=(1, 1, 1)))\\n model.add(MaxPooling3D(pool_size=(2, 2, 2), strides=(2, 2, 2),\\n border_mode='valid', name='pool4'))\\n\\n # 5th layer group\\n model.add(Conv3D(512, 3, 3, 3, activation='relu',\\n border_mode='same', name='conv5a',\\n subsample=(1, 1, 1)))\\n model.add(Conv3D(512, 3, 3, 3, activation='relu',\\n border_mode='same', name='conv5b',\\n subsample=(1, 1, 1)))\\n model.add(ZeroPadding3D(padding=(0, 1, 1)))\\n # model.add(MaxPooling3D(pool_size=(2, 2, 2), strides=(2, 2, 2),\\n # border_mode='valid', name='pool5', dim_ordering=\\\"tf\\\"))\\n model.add(MaxPooling3D(pool_size=(2, 2, 2), strides=(2, 2, 2),\\n border_mode='same', name='pool5', dim_ordering=\\\"tf\\\"))\\n model.add(Flatten())\\n\\n # FC layers group\\n model.add(Dense(4096, activation='relu', name='fc6'))\\n model.add(Dropout(0.5))\\n model.add(Dense(4096, activation='relu', name='fc7'))\\n model.add(Dropout(0.5))\\n model.add(Dense(self.nb_classes, activation='softmax'))\\n for layer in model.layers:\\n print(layer.output_shape)\\n return model\",\n \"def add_control(operation, num_ctrl_qubits, label):\\n if isinstance(operation, UnitaryGate):\\n # attempt decomposition\\n operation._define()\\n if _control_definition_known(operation, num_ctrl_qubits):\\n return _control_predefined(operation, num_ctrl_qubits)\\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def _ice_d3gdp3(temp,pres):\\n \\n # Reduced variables\\n tn = temp/_TTP\\n pn = pres/_PTPE\\n _PI0 = _PATM/_PTPE\\n g_ppp = 0.\\n \\n # Power series terms\\n for (l,n) in enumerate(_GCOEFFS[0]):\\n if l > 2:\\n g_ppp += n * l*(l-1)*(l-2) * (pn-_PI0)**(l-3)\\n g_ppp /= _PTPE**3\\n return g_ppp\",\n \"def enc_add_const(pub, m, c):\\n # Similiar to enc add\\n add_const_result = m * powmod(pub.g, c, pub.n_sq) % pub.n_sq\\n return add_const_result\",\n \"def _ucb_acq(x):\\n mu, sigma = gp.eval(x, uncert_form='std')\\n return mu + beta_th * sigma\",\n \"def _ucb_acq(x):\\n mu, sigma = gp.eval(x, uncert_form='std')\\n return mu + beta_th * sigma\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def itkHuangThresholdImageFilterIUC3IUC3_cast(obj: 'itkLightObject') -> \\\"itkHuangThresholdImageFilterIUC3IUC3 *\\\":\\n return _itkHuangThresholdImageFilterPython.itkHuangThresholdImageFilterIUC3IUC3_cast(obj)\",\n \"def itkBinaryContourImageFilterIF3IF3_cast(obj: 'itkLightObject') -> \\\"itkBinaryContourImageFilterIF3IF3 *\\\":\\n return _itkBinaryContourImageFilterPython.itkBinaryContourImageFilterIF3IF3_cast(obj)\",\n \"def heisen3_sum(v1: Vec3, v2: Vec3) -> Vec3:\\n assert v1.shape == v2.shape and v1.shape == (3,)\\n # first, do normal sum to get (x + x', y + y', z + z')\\n out = v1 + v2\\n # then add the xy' part to z + z'\\n out[2] += v1[0] * v2[1]\\n return out\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6172833","0.60709476","0.59816235","0.597661","0.58950996","0.5756811","0.57265884","0.56782377","0.5533537","0.54784715","0.54042715","0.53975767","0.5389443","0.5381317","0.5351581","0.5308488","0.52944463","0.5283771","0.5253617","0.5241266","0.5219336","0.52027386","0.5189306","0.51650304","0.51120806","0.50613695","0.505782","0.50476617","0.5037182","0.49985173","0.4995795","0.49792442","0.49759465","0.4975661","0.49683616","0.49410525","0.49391478","0.49135047","0.49067074","0.48944905","0.48916858","0.4881397","0.48809263","0.48796245","0.48592055","0.48478174","0.48413253","0.4839383","0.483924","0.48379546","0.4831639","0.48258933","0.48194575","0.4812527","0.47997674","0.47866642","0.4784007","0.47808337","0.47717714","0.47675472","0.47608942","0.47585684","0.47472185","0.47131762","0.47130042","0.4711748","0.46990588","0.46987948","0.46979263","0.46939352","0.4682809","0.46793234","0.46776557","0.4666223","0.46655193","0.46635628","0.4654365","0.4648526","0.46435186","0.4637428","0.46321058","0.46296725","0.46287328","0.4628695","0.46244526","0.46231052","0.4617553","0.46154284","0.4614858","0.4610428","0.4601441","0.45978075","0.4597093","0.45967388","0.45963642","0.45963642","0.4591162","0.4590852","0.45894235","0.45880792"],"string":"[\n \"0.6172833\",\n \"0.60709476\",\n \"0.59816235\",\n \"0.597661\",\n \"0.58950996\",\n \"0.5756811\",\n \"0.57265884\",\n \"0.56782377\",\n \"0.5533537\",\n \"0.54784715\",\n \"0.54042715\",\n \"0.53975767\",\n \"0.5389443\",\n \"0.5381317\",\n \"0.5351581\",\n \"0.5308488\",\n \"0.52944463\",\n \"0.5283771\",\n \"0.5253617\",\n \"0.5241266\",\n \"0.5219336\",\n \"0.52027386\",\n \"0.5189306\",\n \"0.51650304\",\n \"0.51120806\",\n \"0.50613695\",\n \"0.505782\",\n \"0.50476617\",\n \"0.5037182\",\n \"0.49985173\",\n \"0.4995795\",\n \"0.49792442\",\n \"0.49759465\",\n \"0.4975661\",\n \"0.49683616\",\n \"0.49410525\",\n \"0.49391478\",\n \"0.49135047\",\n \"0.49067074\",\n \"0.48944905\",\n \"0.48916858\",\n \"0.4881397\",\n \"0.48809263\",\n \"0.48796245\",\n \"0.48592055\",\n \"0.48478174\",\n \"0.48413253\",\n \"0.4839383\",\n \"0.483924\",\n \"0.48379546\",\n \"0.4831639\",\n \"0.48258933\",\n \"0.48194575\",\n \"0.4812527\",\n \"0.47997674\",\n \"0.47866642\",\n \"0.4784007\",\n \"0.47808337\",\n \"0.47717714\",\n \"0.47675472\",\n \"0.47608942\",\n \"0.47585684\",\n \"0.47472185\",\n \"0.47131762\",\n \"0.47130042\",\n \"0.4711748\",\n \"0.46990588\",\n \"0.46987948\",\n \"0.46979263\",\n \"0.46939352\",\n \"0.4682809\",\n \"0.46793234\",\n \"0.46776557\",\n \"0.4666223\",\n \"0.46655193\",\n \"0.46635628\",\n \"0.4654365\",\n \"0.4648526\",\n \"0.46435186\",\n \"0.4637428\",\n \"0.46321058\",\n \"0.46296725\",\n \"0.46287328\",\n \"0.4628695\",\n \"0.46244526\",\n \"0.46231052\",\n \"0.4617553\",\n \"0.46154284\",\n \"0.4614858\",\n \"0.4610428\",\n \"0.4601441\",\n \"0.45978075\",\n \"0.4597093\",\n \"0.45967388\",\n \"0.45963642\",\n \"0.45963642\",\n \"0.4591162\",\n \"0.4590852\",\n \"0.45894235\",\n \"0.45880792\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.69713616"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81759,"cells":{"query":{"kind":"string","value":"add CCX gate (toffoli gate, controlled controlled X gate)."},"document":{"kind":"string","value":"def ccx(self, q0, q1, q2, ctrl=None):\n self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)\n self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def CX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)","def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self","def __init__(self):\n super().__init__(\"ccx\", 3, [])","def add(self, y):\n return circuit.add(self, y)","def bcc(self, arg):\n\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\n self.pc = c_uint16(self.pc).value","def x(self, new_x):\n if new_x is None:\n logging.warning(\"Cochain features were set to None. \")\n else:\n assert self.num_cells == len(new_x)\n self.__x = new_x","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def addFCSPoint(self, dxpos, dypos, dzpos=None):\n prefix = \"/cli:python /app:fcs /cmd:add\"\n dx = \"/xpos:\" + `int(dxpos)` \n dy = \"/ypos:\" + `int(dypos)`\n if dzpos is None:\n dz = \"/zpos:0\"\n else:\n dz = \"/zpos:\"+dzpos\n \n \n cmd = \" \".join((prefix,dx,dy,dz))\n #print \"FCS command string\"\n #print cmd\n self.sendCMDstring(cmd)","def cX(cb):\n allNodes = b.allNodes(group=cb)\n for n in allNodes:\n allNodes = allNodes + cX(n)\n\n return allNodes","def _compute_carry_and_output(self, x, h_tm1, c_tm1):\n x_i, x_f, x_c, x_o = x\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\n i = self.recurrent_activation(\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\n f = self.recurrent_activation(x_f + K.dot(\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\n o = self.recurrent_activation(\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\n return c, o","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def XX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.XX, qubit_expr)","def _cmplx_add_ ( s , o ) :\n return o + complex ( s )","def add_component(self, xi):\n assert xi.berkovich_line() is self.berkovich_line(), \"xi must be a point\\\n on the Berkovich line underlying this model\"\n X = self\n if not X.is_component(xi):\n ComponentOfModel(X, xi)\n X._changed = True\n\n \"\"\"\n T = X.tree()\n # we have to first check whether xi is already a component !\n # the first condition should be unnecessary; this is a bug in\n # mclf.berkovich_trees: T.find_point for an empty tree gives an error\n if not X.is_component(xi):\n T, vertex = T.add_point(xi)\n self._tree = T\n component = ComponentOfModel(self, vertex)\n if component.is_horizontal():\n self._horizontal_components.append(component)\n else:\n self._vertical_components.append(component)\n # we report that the model has changed\n self._changed = True\n \"\"\"","def _add_mxnet_ctc_loss(pred, seq_len, label):\n pred_ctc = mx.sym.Reshape(data=pred, shape=(-4, seq_len, -1, 0))\n\n loss = mx.sym.contrib.ctc_loss(data=pred_ctc, label=label)\n ctc_loss = mx.sym.MakeLoss(loss)\n\n softmax_class = mx.symbol.SoftmaxActivation(data=pred)\n softmax_loss = mx.sym.MakeLoss(softmax_class)\n softmax_loss = mx.sym.BlockGrad(softmax_loss)\n return mx.sym.Group([softmax_loss, ctc_loss])","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def gate_lfcc(recurrent_net, sample_input):\n length = sample_input.shape[0]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[i, :])\n select = sigmoid(select)\n score = sigmoid(score)\n return np.sum(select * score) / np.sum(select)","def BCS(self, value):\n if self.reg.C:\n self.reg.PC += value","def gate2zx(box):\n if isinstance(box, (Bra, Ket)):\n dom, cod = (1, 0) if isinstance(box, Bra) else (0, 1)\n return Id(0).tensor(*[\n X(dom, cod, phase=.5 * bit) for bit in box.bitstring])\n if isinstance(box, (Rz, Rx)):\n return (Z if isinstance(box, Rz) else X)(1, 1, box.phase)\n if isinstance(box, CRz):\n return Z(1, 2) @ Z(1, 2, box.phase)\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\n if isinstance(box, CRx):\n return X(1, 2) @ X(1, 2, box.phase)\\\n >> Id(1) @ (Z(2, 1) >> X(1, 0, -box.phase)) @ Id(1)\n if isinstance(box, quantum.CU1):\n return Z(1, 2, box.phase) @ Z(1, 2, box.phase)\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\n standard_gates = {\n quantum.H: H,\n quantum.Z: Z(1, 1, .5),\n quantum.X: X(1, 1, .5),\n quantum.Y: Y(1, 1, .5),\n CZ: Z(1, 2) @ Id(1) >> Id(1) @ Had() @ Id(1) >> Id(1) @ Z(2, 1),\n CX: Z(1, 2) @ Id(1) >> Id(1) @ X(2, 1)}\n return standard_gates[box]","def gate_mfcc(recurrent_net, sample_input):\n length = sample_input.shape[1]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\n select = sigmoid(select)\n return np.sum(select * score) / np.sum(select)","def add_junction(ccTremb):\n pass","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def add_point(self, x, fx):\n\t\tself.v.append([x,fx])\n\t\tself.poli = None","def _append_cx(self, i, j):\n\n if not 0 <= i < self.num_qubits or not 0 <= j < self.num_qubits:\n raise QiskitError(\"CX qubits are out of bounds.\")\n self.linear[j] = (self.linear[i] + self.linear[j]) % 2\n self.shift[j] = (self.shift[i] + self.shift[j]) % 2","def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self","def _acc_grads(self, x, label):\n ##\n # Forward propagation\n z1 = self.params.W.dot(x) + self.params.b1\n h = tanh(z1)\n z2 = np.dot(self.params.U, h) + self.params.b2\n y_hat = softmax(z2)\n \n y = make_onehot(label, self.outputsize)\n d2 = y_hat - y\n self.grads.b2 += d2\n self.grads.U += np.outer(d2, h) + self.lreg * self.params.U\n d1 = np.dot(self.params.U.T, d2) * tanhd(z1) \n \n self.grads.W += np.outer(d1, x) + self.lreg * self.params.W\n self.grads.b1 += d1","def _add_ctc_loss(pred, seq_len, num_label, loss_type):\n label = mx.sym.Variable('label')\n if loss_type == 'warpctc':\n print(\"Using WarpCTC Loss\")\n sm = _add_warp_ctc_loss(pred, seq_len, num_label, label)\n else:\n print(\"Using MXNet CTC Loss\")\n assert loss_type == 'ctc'\n sm = _add_mxnet_ctc_loss(pred, seq_len, label)\n return sm","def construct(self, x):\n xx = self.expert(x)\n x1 = self.gate1(x)\n x2 = self.gate2(x)\n x1 = self.shared_output1(xx, x1)\n x2 = self.shared_output2(xx, x2)\n x1 = self.tower_layer1(x1)\n x1 = self.output_layer1(x1)\n x2 = self.tower_layer2(x2)\n x2 = self.output_layer2(x2)\n\n return x1, x2","def Coaxial(movableAxis: str, fixedAxis: str, flip: Boolean) -> \"Feature\":\n return Feature()","def _add_warp_ctc_loss(pred, seq_len, num_label, label):\n label = mx.sym.Reshape(data=label, shape=(-1,))\n label = mx.sym.Cast(data=label, dtype='int32')\n return mx.sym.WarpCTC(data=pred, label=label, label_length=num_label, input_length=seq_len)","def CPX(self, value):\n self._compare(value, 'X')","def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def TAX(self, *_):\n self.reg.X = self.reg.A\n self.reg.N = self.reg.X << 7\n self.reg.Z = self.reg.X == 0","def add(num1, num2, Cin):\n Cin=0\n l2=[]\n final=\"\"\n\n \"\"\"Using for loop for starting addition from the last indexed number\"\"\"\n for i in range(len(num1)-1,-1,-1):\n bit1=num1[i]#storing each indexed() value of num1 in bit1\n bit2=num2[i]#storing each indexed() value of num2 in bit2\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\n Cin=Cout#declaring cout as cin for next bit addition\n l2.append(SUM)#adding SUM to l2\n l3=l2[::-1]##reversing the value of l2\n final+=str(l2[-1])#converting the list value to string\n final1=final[::-1]#reversing string value\n return final1 #returning the binary addition as string","def coadd(self, step_index):\n if self.drip_config is not None:\n if ('boresight' in self.drip_cal_config\n and 'SLIT' in self.drip_cal_config['boresight']):\n self.current[step_index].set_value('skip_coadd', True)","def add_point(self, x, fx):\n\t\ti = 0\n\t\twhile i < self.N:\n\t\t\tif self.puntos[i] < x < self.puntos[i+1]:\n\t\t\t\tself.puntos[i+1:i+1] = [x]\n\t\t\t\tself.imagenes[i+1:i+1] = [fx]\n\t\t\t\tself.N = self.N + 1\n\t\t\t\tself.rellenado = False\n\t\t\t\ti = self.N\n\t\t\ti = i+1","def addTrafficCross(self, byte):\n self.byte_cross_group += byte","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def GachaCraftNodeExcelAddGP1100(builder, GP1100):\n return AddGP1100(builder, GP1100)","def __add_credit_cc(self):\n log.debug(\"Displaying __add_credit_cc\")\n # Create a keyboard to be sent later\n presets = self.cfg.ccard[\"payment_presets\"]\n keyboard = [[telegram.KeyboardButton(str(self.Price(preset)))] for preset in presets]\n keyboard.append([telegram.KeyboardButton(self.loc.get(\"menu_all_cancel\"))])\n # Boolean variable to check if the user has cancelled the action\n cancelled = False\n # Loop used to continue asking if there's an error during the input\n while not cancelled:\n # Send the message and the keyboard\n self.bot.send_message(self.chat.id, self.loc.get(\"payment_cc_amount\"),\n reply_markup=telegram.ReplyKeyboardMarkup(keyboard, one_time_keyboard=True))\n # Wait until a valid amount is sent\n selection = self.__wait_for_regex(r\"([0-9]+(?:[.,][0-9]+)?|\" + self.loc.get(\"menu_all_cancel\") + r\")\",\n cancellable=True)\n # If the user cancelled the action\n if isinstance(selection, CancelSignal):\n # Exit the loop\n cancelled = True\n continue\n # Convert the amount to an integer\n value = self.Price(selection)\n # Ensure the amount is within the range\n if value > self.Price(self.cfg.ccard[\"max_amount\"]):\n self.bot.send_message(self.chat.id,\n self.loc.get(\"error_payment_amount_over_max\",\n max_amount=self.Price(self.cfg.ccard[\"max_amount\"])))\n continue\n elif value < self.Price(self.cfg.ccard[\"min_amount\"]):\n self.bot.send_message(self.chat.id,\n self.loc.get(\"error_payment_amount_under_min\",\n min_amount=self.Price(self.cfg.ccard[\"min_amount\"])))\n continue\n break\n # If the user cancelled the action...\n else:\n # Exit the function\n return\n # Issue the payment invoice\n self.__make_payment(amount=value)","def plot_cnxs(self,x_shift,y_shift):\n\n if not self.cnxs: return # Bounce if option not selected\n\n self.node_cnx_crds[:,:2] += x_shift*self.pbc[0]\n self.node_cnx_crds[:,2:] += y_shift*self.pbc[1]\n for cnx_crd in self.node_cnx_crds:\n self.ax.plot(cnx_crd[:2],cnx_crd[2:],c=self.lc,lw=self.lw)\n self.node_cnx_crds[:,:2] -= x_shift*self.pbc[0]\n self.node_cnx_crds[:,2:] -= y_shift*self.pbc[1]","def test_add_to_vx(self, cpu):\n for x in range(0x0, 0xF):\n for v in range(0x0, 0xFF):\n for kk in range(0x0, 0xFF):\n cpu.V_register[x] = v\n cpu.opcode = 0x7000 | (x << 8) | kk\n cpu.add_to_vx()\n assert(cpu.V_register[x] == (v + kk) & 0xFF)","def convert_to_circuit(x):\n y = np.arcsin(x)\n z = np.arccos(x**2)\n qubits = cirq.GridQubit.rect(5, 1)\n circuit = cirq.Circuit()\n for i in range(5):\n circuit.append(cirq.ry(y).on(qubits[i]))\n circuit.append(cirq.rz(z).on(qubits[i]))\n return circuit","def forward(self, x):\r\n out = x + self.conv_block(x) # add skip connections\r\n return out","def construct(self, x):\n x = self.conv(x)\n h0 = self.up_conv1(x)\n l0 = self.up_conv2(h0)\n h1 = self.up_conv3(l0 - x)\n return h1 + h0","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def connect(self, gate) :\n self.notifyList.append(gate)","def forward(self,\n x: Tensor) \\\n -> Tensor:\n\n x = self.convs[0](x)\n res = x\n for i in range(self.num_rates):\n x = torch.tanh(self.filter_convs[i](\n x)) * torch.sigmoid(self.gate_convs[i](x))\n x = self.convs[i+1](x)\n res = res + x\n return res","def C(self,X):\n return(\n 0\n )","def enable_cl1_direct(self):\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\n self.write_versa5(0x18,0x20)\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\n self.write_versa5(0x13,0x03) ## Switch to clock\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew","def two_activation(self, output_reg):\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\n self._q_neuron.cx(self.inputs[0], self._output[output_reg])\n self._q_neuron.cx(self.inputs[1], self._output[output_reg])","def _control_predefined(operation, num_ctrl_qubits):\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\n if num_ctrl_qubits == 1:\n import qiskit.extensions.standard.cx\n cgate = qiskit.extensions.standard.cx.CnotGate()\n else:\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n elif operation.name == 'y':\n import qiskit.extensions.standard.cy\n cgate = qiskit.extensions.standard.cy.CyGate()\n elif operation.name == 'z':\n import qiskit.extensions.standard.cz\n cgate = qiskit.extensions.standard.cz.CzGate()\n elif operation.name == 'h':\n import qiskit.extensions.standard.ch\n cgate = qiskit.extensions.standard.ch.CHGate()\n elif operation.name in {'rx', 'ry', 'rz'}:\n if operation.name == 'rx':\n import qiskit.extensions.standard.crx\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\n elif operation.name == 'ry':\n import qiskit.extensions.standard.cry\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\n else: # operation.name == 'rz'\n import qiskit.extensions.standard.crz\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\n if num_ctrl_qubits == 1:\n return cgate\n else:\n # only predefined for one control qubit\n return cgate.control(num_ctrl_qubits - 1)\n elif operation.name == 'swap':\n import qiskit.extensions.standard.cswap\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\n elif operation.name == 'u1':\n import qiskit.extensions.standard.cu1\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\n elif operation.name == 'u3':\n import qiskit.extensions.standard.cu3\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\n elif operation.name == 'cx':\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n else:\n raise QiskitError('No standard controlled gate for \"{}\"'.format(\n operation.name))\n return cgate","def GachaCraftNodeExcelAddGP1110(builder, GP1110):\n return AddGP1110(builder, GP1110)","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\n return self","def forward(self, x):\n out = x + self.conv_block(x) # add skip connections\n return out","def forward(self, x):\n out = x + self.conv_block(x) # add skip connections\n return out","def forward(self, x):\n out = x + self.conv_block(x) # add skip connections\n return out","def double_add(self, x):\n self.add(x*2)","def add_bitline_contacts(self):\n\n stack=(\"metal1\", \"via1\", \"metal2\")\n pos = self.lower_pmos_inst.get_pin(\"S\").center()\n self.add_contact_center(layers=stack,\n offset=pos)\n pos = self.lower_pmos_inst.get_pin(\"D\").center()\n self.add_contact_center(layers=stack,\n offset=pos)\n pos = self.upper_pmos1_inst.get_pin(\"S\").center()\n self.add_contact_center(layers=stack,\n offset=pos)\n pos = self.upper_pmos2_inst.get_pin(\"D\").center()\n self.add_contact_center(layers=stack,\n offset=pos)","def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])","def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\n if q_args is None and c_args is None:\n raise GateError(\"Gate needs at least one quantum argument or classical argument\")\n if isinstance(gate, CompositeGate):\n if mapping is None:\n raise GateError(\"Must provide arguments mapping for composite gate inside a composite gate.\")\n else:\n inv_mappimg = dict()\n for key, value in mapping.items():\n inv_mappimg[value] = key\n if gate is self:\n gates = gate.copy.gates\n else:\n gates = gate.gates\n for g in gates:\n new_q_args = None\n new_c_args = None\n if g[1] is not None:\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\n if g[2] is not None:\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\n self.add_gate(gate=g[0], q_args=new_q_args,\n c_args=new_c_args, params=g[3])\n else:\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\n raise GateError(\"Gate must be either a CompositeGate or a string from: \"\n \"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\")\n if q_args is not None:\n for q_arg in q_args:\n if q_arg not in self.q_args:\n self.add_q_arg(q_arg)\n if c_args is not None:\n for c_arg in c_args:\n if c_arg not in self.c_args:\n self.add_c_arg(c_arg)\n if params is not None:\n for param in params:\n if param not in self.params:\n self.add_param(param)\n self._gates.append((gate, q_args, c_args, params))","def construct(self, x):\n x = self.conv(x)\n l0 = self.down_conv1(x)\n h0 = self.down_conv2(l0)\n l1 = self.down_conv3(h0 - x)\n return l1 + l0","def cy(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CY(), target=[control, target])","def convert_C_instruction(self, instruction):\n comp, dest, jump = self.parse(instruction)\n\n return f\"111{convert_comp(comp)}{convert_dest(dest)}\" \\\n f\"{convert_jump(jump)}\"","def forward(self, x):\n x = self.conv(x)\n x = self.bn(x)\n x = self.act(x)\n return x","def forward(self, x):\n x = self.conv(x)\n x = self.bn(x)\n x = self.act(x)\n return x","def TSX(self, *_):\n self.reg.X = self.reg.S\n self.reg.N = self.reg.X << 7\n self.reg.Z = self.reg.X == 0","def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)","def putcfix(self,cfix_): # 3\n res = self.__obj.putcfix(cfix_)\n if res != 0:\n result,msg = self.__getlasterror(res)\n raise Error(rescode(res),msg)","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def comp_add_ao(self):\n scene = self.set_as_active()\n scene.use_nodes = True\n tree = scene.node_tree\n tree.nodes.clear()\n\n # creating the nodes\n node_rlayer = tree.nodes.new('CompositorNodeRLayers')\n node_rlayer.location = -300, 100\n node_rlayer.scene = scene\n node_rlayer.layer = w_var.rlname\n\n node_mixcolor = tree.nodes.new('CompositorNodeMixRGB')\n node_mixcolor.location = 0, 50\n node_mixcolor.blend_type = 'MULTIPLY'\n node_mixcolor.inputs[0].default_value = 0.730\n\n node_comp = tree.nodes.new('CompositorNodeComposite')\n node_comp.location = 300, 130\n\n node_viewer = tree.nodes.new('CompositorNodeViewer')\n node_viewer.location = 300, -100\n\n # connecting the nodes\n links = tree.links\n links.new(node_rlayer.outputs[0], node_mixcolor.inputs[1])\n links.new(node_rlayer.outputs[10], node_mixcolor.inputs[2])\n links.new(node_mixcolor.outputs[0], node_comp.inputs[0])\n links.new(node_mixcolor.outputs[0], node_viewer.inputs[0])\n\n for node in tree.nodes:\n node.select = False","def acosh(self, x):\n return self.arccosh(x)","def INX(self, *_):\n self._dec_or_inc_register('X', increment=True)","def addXValue(self,value):\n self.__XValue.append(value)\n self.updateValue()","def add_cogs(self):\n self.add_cog(Voice(self))","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\n return self","def transform(self, X):\n return self.act_on(X)","def test_scalar_coeff_cc():\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\n kappa = Symbol('kappa', real=True)\n a1 = Destroy(hs=hs_1)\n a2 = Destroy(hs=hs_2)\n\n jc_expr = (\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\n )\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == I * kappa * OperatorPlusMinusCC(\n a1.dag() * a2, sign=-1\n )\n expanded = simplified.doit()\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())","def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\n return self","def add_connector(self):\n \n no = len(self.connectors)\n state = {}\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % no\n \n if len(self.connectors)>0:\n state = self.connectors[-1].get_state()\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % (no)\n else:\n if self.mount == self.MOUNT_THT:\n state[\"p_shape\"] = Con.SHAPE_HOLE\n elif self.mount == self.MOUNT_SMD:\n state[\"p_shape\"] = Con.SHAPE_PAD\n \n c = Con(no)\n c.set_state(state) \n \n self.sch_layers[\"pins\"].add(c.s_svg)\n self.pcb_layers[\"copper1\"].add(c.p_svg)\n self.connectors.append(c)","def test_simple_cc():\n hs_c = LocalSpace('c', dimension=3)\n hs_q = LocalSpace('q1', basis=('g', 'e'))\n Delta_1 = Symbol('Delta_1')\n Omega_1 = Symbol('Omega_1')\n g_1 = Symbol('g_1')\n a = Destroy(hs=hs_c)\n a_dag = Create(hs=hs_c)\n sig_p = LocalSigma('e', 'g', hs=hs_q)\n sig_m = LocalSigma('g', 'e', hs=hs_q)\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\n assert (\n srepr(simplified.term)\n == \"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \"\n \"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \"\n \"basis=('g', 'e')))), sign=-1)\"\n )\n expanded = simplified.doit()\n assert expanded == jc_expr","def add_feature(x, x1):\n if x is None:\n x = x1\n else:\n x = np.concatenate((x, x1), axis=1)\n return x","def get_CC_operators():\n i = symbols('i', below_fermi=True, cls=Dummy)\n a = symbols('a', above_fermi=True, cls=Dummy)\n t_ai = AntiSymmetricTensor('t', (a,), (i,))\n ai = NO(Fd(a)*F(i))\n i, j = symbols('i,j', below_fermi=True, cls=Dummy)\n a, b = symbols('a,b', above_fermi=True, cls=Dummy)\n t_abij = AntiSymmetricTensor('t', (a, b), (i, j))\n abji = NO(Fd(a)*Fd(b)*F(j)*F(i))\n\n T1 = t_ai*ai\n T2 = Rational(1, 4)*t_abij*abji\n return (T1, T2)","def __add__(self, x):\n assert isinstance(x, AxisDistance), 'incorrect type of arg x: should be type AxisDistance, is type {}'.format(type(x))\n tile = self.tile + x.tile\n pixel = self.pixel + x.pixel\n subpixel = self.subpixel + x.subpixel\n return AxisDistance(t=tile, px=pixel, sx=subpixel)","def process_block_to_add(coupling_point: Point, coupling_angle : Angle, conjugation_angle : Angle, cc_bond_length:float, block_to_add: Building_Block):\n\n\t#load data for block_to_add\n\tcoord_xyz = top.read_xyz_file(block_to_add.path)\n\tcoord_xyz_save = np.copy(coord_xyz)\n\n\t\n\n\t#rotate around z axis for conjugation, rotate around y for right orientation,shift to coupling point and shift by c-c bond length in right direction\n\tfor i in range(0,coord_xyz.shape[1]):\n\t\t\n\t\t#conjugation x' = cos(phi)*x-sin(phi)*y\n\t\tcoord_xyz[1,i] = coord_xyz_save[1,i]*np.cos(conjugation_angle)-np.sin(conjugation_angle)*coord_xyz_save[2,i]\n\t\t#conjugation y' = sin(phi)*x+cos(phi)*y\n\t\tcoord_xyz[2,i] = coord_xyz_save[1,i]*np.sin(conjugation_angle)+np.cos(conjugation_angle)*coord_xyz_save[2,i]\n\n\t\tcoord_xyz_save = np.copy(coord_xyz)\n\n\t\t#rotation around y: x' = cos(phi)*x+sin(phi)*z\n\t\tcoord_xyz[1,i] = coord_xyz_save[1,i]*np.cos(coupling_angle)+np.sin(coupling_angle)*coord_xyz_save[3,i]\n\t\t#rotation around y: z' = cos(phi)*z-sin(phi)*x\n\t\tcoord_xyz[3,i] = -coord_xyz_save[1,i]*np.sin(coupling_angle)+np.cos(coupling_angle)*coord_xyz_save[3,i]\n\n\t\t#shift to coupling point x -> x+x_c\n\t\tcoord_xyz[1,i] = coord_xyz[1,i]+coupling_point.x\n\t\t#shift to coupling point y -> y+y_c\n\t\tcoord_xyz[2,i] = coord_xyz[2,i]+coupling_point.y\n\t\t#shift to coupling point z -> z+z_c\n\t\tcoord_xyz[3,i] = coord_xyz[3,i]+coupling_point.z\n\n\t\t#shift by C-C bond length in e_c direction sin=-0.866 cos=-0.499\n\t\tcoord_xyz[1,i] = coord_xyz[1,i]+cc_bond_length*np.sin(coupling_angle)\n\t\t#shift by C-C bond length in e_c direction\n\t\tcoord_xyz[3,i] = coord_xyz[3,i]+cc_bond_length*np.cos(coupling_angle)\n\treturn coord_xyz","def turn_fcc_on(self):\n raise NotImplementedError","def GachaCraftNodeExcelAddGP1101(builder, GP1101):\n return AddGP1101(builder, GP1101)","def add_point(self, x, fx, dx):\n\t\tself.v.append([x, fx, dx])\n\t\tself.v.append([x, fx, dx])\n\t\tself.poli = None","def _process_cnot(self, node):\n id0 = self._process_bit_id(node.children[0])\n id1 = self._process_bit_id(node.children[1])\n if not(len(id0) == len(id1) or len(id0) == 1 or len(id1) == 1):\n raise UnrollerError(\"internal error: qreg size mismatch\",\n \"line=%s\" % node.line, \"file=%s\" % node.file)\n maxidx = max([len(id0), len(id1)])\n for idx in range(maxidx):\n if len(id0) > 1 and len(id1) > 1:\n self.backend.cx(id0[idx], id1[idx])\n elif len(id0) > 1:\n self.backend.cx(id0[idx], id1[0])\n else:\n self.backend.cx(id0[0], id1[idx])","def add(self, x):\n if type(x) is int:\n self.real += x\n else:\n self.real = self.real + x.real\n self.imag = self.imag + x.imag","def add_neurone(self, couche, nbr=1):\n if self.control == 0:\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\n self.couche[couche] += nbr\n else:\n print(\"Le réseau est deja créé, vous en pouvez plus le modifier\")","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def dcx(self, addr):\n\n self.reg.idx = self.reg.idx.inc(-1)\n self.reg.zerox_flag = self.reg.idx.eq_zero()"],"string":"[\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def CX(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)\",\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def cxr(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def __init__(self):\\n super().__init__(\\\"ccx\\\", 3, [])\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def bcc(self, arg):\\n\\n self.pc += arg if not self.p & const.FLAG_CARRY else 0\\n self.pc = c_uint16(self.pc).value\",\n \"def x(self, new_x):\\n if new_x is None:\\n logging.warning(\\\"Cochain features were set to None. \\\")\\n else:\\n assert self.num_cells == len(new_x)\\n self.__x = new_x\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def addFCSPoint(self, dxpos, dypos, dzpos=None):\\n prefix = \\\"/cli:python /app:fcs /cmd:add\\\"\\n dx = \\\"/xpos:\\\" + `int(dxpos)` \\n dy = \\\"/ypos:\\\" + `int(dypos)`\\n if dzpos is None:\\n dz = \\\"/zpos:0\\\"\\n else:\\n dz = \\\"/zpos:\\\"+dzpos\\n \\n \\n cmd = \\\" \\\".join((prefix,dx,dy,dz))\\n #print \\\"FCS command string\\\"\\n #print cmd\\n self.sendCMDstring(cmd)\",\n \"def cX(cb):\\n allNodes = b.allNodes(group=cb)\\n for n in allNodes:\\n allNodes = allNodes + cX(n)\\n\\n return allNodes\",\n \"def _compute_carry_and_output(self, x, h_tm1, c_tm1):\\n x_i, x_f, x_c, x_o = x\\n h_tm1_i, h_tm1_f, h_tm1_c, h_tm1_o = h_tm1\\n i = self.recurrent_activation(\\n x_i + K.dot(h_tm1_i, self.recurrent_kernel[:, :self.units]))\\n f = self.recurrent_activation(x_f + K.dot(\\n h_tm1_f, self.recurrent_kernel[:, self.units:self.units * 2]))\\n c = f * c_tm1 + i * self.activation(x_c + K.dot(\\n h_tm1_c, self.recurrent_kernel[:, self.units * 2:self.units * 3]))\\n o = self.recurrent_activation(\\n x_o + K.dot(h_tm1_o, self.recurrent_kernel[:, self.units * 3:]))\\n return c, o\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def XX(self, qubit_expr):\\n self.apply_gate_operation(cirq.ops.XX, qubit_expr)\",\n \"def _cmplx_add_ ( s , o ) :\\n return o + complex ( s )\",\n \"def add_component(self, xi):\\n assert xi.berkovich_line() is self.berkovich_line(), \\\"xi must be a point\\\\\\n on the Berkovich line underlying this model\\\"\\n X = self\\n if not X.is_component(xi):\\n ComponentOfModel(X, xi)\\n X._changed = True\\n\\n \\\"\\\"\\\"\\n T = X.tree()\\n # we have to first check whether xi is already a component !\\n # the first condition should be unnecessary; this is a bug in\\n # mclf.berkovich_trees: T.find_point for an empty tree gives an error\\n if not X.is_component(xi):\\n T, vertex = T.add_point(xi)\\n self._tree = T\\n component = ComponentOfModel(self, vertex)\\n if component.is_horizontal():\\n self._horizontal_components.append(component)\\n else:\\n self._vertical_components.append(component)\\n # we report that the model has changed\\n self._changed = True\\n \\\"\\\"\\\"\",\n \"def _add_mxnet_ctc_loss(pred, seq_len, label):\\n pred_ctc = mx.sym.Reshape(data=pred, shape=(-4, seq_len, -1, 0))\\n\\n loss = mx.sym.contrib.ctc_loss(data=pred_ctc, label=label)\\n ctc_loss = mx.sym.MakeLoss(loss)\\n\\n softmax_class = mx.symbol.SoftmaxActivation(data=pred)\\n softmax_loss = mx.sym.MakeLoss(softmax_class)\\n softmax_loss = mx.sym.BlockGrad(softmax_loss)\\n return mx.sym.Group([softmax_loss, ctc_loss])\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def gate_lfcc(recurrent_net, sample_input):\\n length = sample_input.shape[0]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[i, :])\\n select = sigmoid(select)\\n score = sigmoid(score)\\n return np.sum(select * score) / np.sum(select)\",\n \"def BCS(self, value):\\n if self.reg.C:\\n self.reg.PC += value\",\n \"def gate2zx(box):\\n if isinstance(box, (Bra, Ket)):\\n dom, cod = (1, 0) if isinstance(box, Bra) else (0, 1)\\n return Id(0).tensor(*[\\n X(dom, cod, phase=.5 * bit) for bit in box.bitstring])\\n if isinstance(box, (Rz, Rx)):\\n return (Z if isinstance(box, Rz) else X)(1, 1, box.phase)\\n if isinstance(box, CRz):\\n return Z(1, 2) @ Z(1, 2, box.phase)\\\\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\\n if isinstance(box, CRx):\\n return X(1, 2) @ X(1, 2, box.phase)\\\\\\n >> Id(1) @ (Z(2, 1) >> X(1, 0, -box.phase)) @ Id(1)\\n if isinstance(box, quantum.CU1):\\n return Z(1, 2, box.phase) @ Z(1, 2, box.phase)\\\\\\n >> Id(1) @ (X(2, 1) >> Z(1, 0, -box.phase)) @ Id(1)\\n standard_gates = {\\n quantum.H: H,\\n quantum.Z: Z(1, 1, .5),\\n quantum.X: X(1, 1, .5),\\n quantum.Y: Y(1, 1, .5),\\n CZ: Z(1, 2) @ Id(1) >> Id(1) @ Had() @ Id(1) >> Id(1) @ Z(2, 1),\\n CX: Z(1, 2) @ Id(1) >> Id(1) @ X(2, 1)}\\n return standard_gates[box]\",\n \"def gate_mfcc(recurrent_net, sample_input):\\n length = sample_input.shape[1]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\\n select = sigmoid(select)\\n return np.sum(select * score) / np.sum(select)\",\n \"def add_junction(ccTremb):\\n pass\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def add_point(self, x, fx):\\n\\t\\tself.v.append([x,fx])\\n\\t\\tself.poli = None\",\n \"def _append_cx(self, i, j):\\n\\n if not 0 <= i < self.num_qubits or not 0 <= j < self.num_qubits:\\n raise QiskitError(\\\"CX qubits are out of bounds.\\\")\\n self.linear[j] = (self.linear[i] + self.linear[j]) % 2\\n self.shift[j] = (self.shift[i] + self.shift[j]) % 2\",\n \"def cxr_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def _acc_grads(self, x, label):\\n ##\\n # Forward propagation\\n z1 = self.params.W.dot(x) + self.params.b1\\n h = tanh(z1)\\n z2 = np.dot(self.params.U, h) + self.params.b2\\n y_hat = softmax(z2)\\n \\n y = make_onehot(label, self.outputsize)\\n d2 = y_hat - y\\n self.grads.b2 += d2\\n self.grads.U += np.outer(d2, h) + self.lreg * self.params.U\\n d1 = np.dot(self.params.U.T, d2) * tanhd(z1) \\n \\n self.grads.W += np.outer(d1, x) + self.lreg * self.params.W\\n self.grads.b1 += d1\",\n \"def _add_ctc_loss(pred, seq_len, num_label, loss_type):\\n label = mx.sym.Variable('label')\\n if loss_type == 'warpctc':\\n print(\\\"Using WarpCTC Loss\\\")\\n sm = _add_warp_ctc_loss(pred, seq_len, num_label, label)\\n else:\\n print(\\\"Using MXNet CTC Loss\\\")\\n assert loss_type == 'ctc'\\n sm = _add_mxnet_ctc_loss(pred, seq_len, label)\\n return sm\",\n \"def construct(self, x):\\n xx = self.expert(x)\\n x1 = self.gate1(x)\\n x2 = self.gate2(x)\\n x1 = self.shared_output1(xx, x1)\\n x2 = self.shared_output2(xx, x2)\\n x1 = self.tower_layer1(x1)\\n x1 = self.output_layer1(x1)\\n x2 = self.tower_layer2(x2)\\n x2 = self.output_layer2(x2)\\n\\n return x1, x2\",\n \"def Coaxial(movableAxis: str, fixedAxis: str, flip: Boolean) -> \\\"Feature\\\":\\n return Feature()\",\n \"def _add_warp_ctc_loss(pred, seq_len, num_label, label):\\n label = mx.sym.Reshape(data=label, shape=(-1,))\\n label = mx.sym.Cast(data=label, dtype='int32')\\n return mx.sym.WarpCTC(data=pred, label=label, label_length=num_label, input_length=seq_len)\",\n \"def CPX(self, value):\\n self._compare(value, 'X')\",\n \"def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def TAX(self, *_):\\n self.reg.X = self.reg.A\\n self.reg.N = self.reg.X << 7\\n self.reg.Z = self.reg.X == 0\",\n \"def add(num1, num2, Cin):\\n Cin=0\\n l2=[]\\n final=\\\"\\\"\\n\\n \\\"\\\"\\\"Using for loop for starting addition from the last indexed number\\\"\\\"\\\"\\n for i in range(len(num1)-1,-1,-1):\\n bit1=num1[i]#storing each indexed() value of num1 in bit1\\n bit2=num2[i]#storing each indexed() value of num2 in bit2\\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\\n Cin=Cout#declaring cout as cin for next bit addition\\n l2.append(SUM)#adding SUM to l2\\n l3=l2[::-1]##reversing the value of l2\\n final+=str(l2[-1])#converting the list value to string\\n final1=final[::-1]#reversing string value\\n return final1 #returning the binary addition as string\",\n \"def coadd(self, step_index):\\n if self.drip_config is not None:\\n if ('boresight' in self.drip_cal_config\\n and 'SLIT' in self.drip_cal_config['boresight']):\\n self.current[step_index].set_value('skip_coadd', True)\",\n \"def add_point(self, x, fx):\\n\\t\\ti = 0\\n\\t\\twhile i < self.N:\\n\\t\\t\\tif self.puntos[i] < x < self.puntos[i+1]:\\n\\t\\t\\t\\tself.puntos[i+1:i+1] = [x]\\n\\t\\t\\t\\tself.imagenes[i+1:i+1] = [fx]\\n\\t\\t\\t\\tself.N = self.N + 1\\n\\t\\t\\t\\tself.rellenado = False\\n\\t\\t\\t\\ti = self.N\\n\\t\\t\\ti = i+1\",\n \"def addTrafficCross(self, byte):\\n self.byte_cross_group += byte\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def GachaCraftNodeExcelAddGP1100(builder, GP1100):\\n return AddGP1100(builder, GP1100)\",\n \"def __add_credit_cc(self):\\n log.debug(\\\"Displaying __add_credit_cc\\\")\\n # Create a keyboard to be sent later\\n presets = self.cfg.ccard[\\\"payment_presets\\\"]\\n keyboard = [[telegram.KeyboardButton(str(self.Price(preset)))] for preset in presets]\\n keyboard.append([telegram.KeyboardButton(self.loc.get(\\\"menu_all_cancel\\\"))])\\n # Boolean variable to check if the user has cancelled the action\\n cancelled = False\\n # Loop used to continue asking if there's an error during the input\\n while not cancelled:\\n # Send the message and the keyboard\\n self.bot.send_message(self.chat.id, self.loc.get(\\\"payment_cc_amount\\\"),\\n reply_markup=telegram.ReplyKeyboardMarkup(keyboard, one_time_keyboard=True))\\n # Wait until a valid amount is sent\\n selection = self.__wait_for_regex(r\\\"([0-9]+(?:[.,][0-9]+)?|\\\" + self.loc.get(\\\"menu_all_cancel\\\") + r\\\")\\\",\\n cancellable=True)\\n # If the user cancelled the action\\n if isinstance(selection, CancelSignal):\\n # Exit the loop\\n cancelled = True\\n continue\\n # Convert the amount to an integer\\n value = self.Price(selection)\\n # Ensure the amount is within the range\\n if value > self.Price(self.cfg.ccard[\\\"max_amount\\\"]):\\n self.bot.send_message(self.chat.id,\\n self.loc.get(\\\"error_payment_amount_over_max\\\",\\n max_amount=self.Price(self.cfg.ccard[\\\"max_amount\\\"])))\\n continue\\n elif value < self.Price(self.cfg.ccard[\\\"min_amount\\\"]):\\n self.bot.send_message(self.chat.id,\\n self.loc.get(\\\"error_payment_amount_under_min\\\",\\n min_amount=self.Price(self.cfg.ccard[\\\"min_amount\\\"])))\\n continue\\n break\\n # If the user cancelled the action...\\n else:\\n # Exit the function\\n return\\n # Issue the payment invoice\\n self.__make_payment(amount=value)\",\n \"def plot_cnxs(self,x_shift,y_shift):\\n\\n if not self.cnxs: return # Bounce if option not selected\\n\\n self.node_cnx_crds[:,:2] += x_shift*self.pbc[0]\\n self.node_cnx_crds[:,2:] += y_shift*self.pbc[1]\\n for cnx_crd in self.node_cnx_crds:\\n self.ax.plot(cnx_crd[:2],cnx_crd[2:],c=self.lc,lw=self.lw)\\n self.node_cnx_crds[:,:2] -= x_shift*self.pbc[0]\\n self.node_cnx_crds[:,2:] -= y_shift*self.pbc[1]\",\n \"def test_add_to_vx(self, cpu):\\n for x in range(0x0, 0xF):\\n for v in range(0x0, 0xFF):\\n for kk in range(0x0, 0xFF):\\n cpu.V_register[x] = v\\n cpu.opcode = 0x7000 | (x << 8) | kk\\n cpu.add_to_vx()\\n assert(cpu.V_register[x] == (v + kk) & 0xFF)\",\n \"def convert_to_circuit(x):\\n y = np.arcsin(x)\\n z = np.arccos(x**2)\\n qubits = cirq.GridQubit.rect(5, 1)\\n circuit = cirq.Circuit()\\n for i in range(5):\\n circuit.append(cirq.ry(y).on(qubits[i]))\\n circuit.append(cirq.rz(z).on(qubits[i]))\\n return circuit\",\n \"def forward(self, x):\\r\\n out = x + self.conv_block(x) # add skip connections\\r\\n return out\",\n \"def construct(self, x):\\n x = self.conv(x)\\n h0 = self.up_conv1(x)\\n l0 = self.up_conv2(h0)\\n h1 = self.up_conv3(l0 - x)\\n return h1 + h0\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def connect(self, gate) :\\n self.notifyList.append(gate)\",\n \"def forward(self,\\n x: Tensor) \\\\\\n -> Tensor:\\n\\n x = self.convs[0](x)\\n res = x\\n for i in range(self.num_rates):\\n x = torch.tanh(self.filter_convs[i](\\n x)) * torch.sigmoid(self.gate_convs[i](x))\\n x = self.convs[i+1](x)\\n res = res + x\\n return res\",\n \"def C(self,X):\\n return(\\n 0\\n )\",\n \"def enable_cl1_direct(self):\\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\\n self.write_versa5(0x18,0x20)\\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\\n self.write_versa5(0x13,0x03) ## Switch to clock\\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew\",\n \"def two_activation(self, output_reg):\\n self._q_neuron.ccx(self.inputs[0], self.inputs[1], self._output[output_reg])\\n self._q_neuron.cx(self.inputs[0], self._output[output_reg])\\n self._q_neuron.cx(self.inputs[1], self._output[output_reg])\",\n \"def _control_predefined(operation, num_ctrl_qubits):\\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\\n if num_ctrl_qubits == 1:\\n import qiskit.extensions.standard.cx\\n cgate = qiskit.extensions.standard.cx.CnotGate()\\n else:\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n elif operation.name == 'y':\\n import qiskit.extensions.standard.cy\\n cgate = qiskit.extensions.standard.cy.CyGate()\\n elif operation.name == 'z':\\n import qiskit.extensions.standard.cz\\n cgate = qiskit.extensions.standard.cz.CzGate()\\n elif operation.name == 'h':\\n import qiskit.extensions.standard.ch\\n cgate = qiskit.extensions.standard.ch.CHGate()\\n elif operation.name in {'rx', 'ry', 'rz'}:\\n if operation.name == 'rx':\\n import qiskit.extensions.standard.crx\\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\\n elif operation.name == 'ry':\\n import qiskit.extensions.standard.cry\\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\\n else: # operation.name == 'rz'\\n import qiskit.extensions.standard.crz\\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\\n if num_ctrl_qubits == 1:\\n return cgate\\n else:\\n # only predefined for one control qubit\\n return cgate.control(num_ctrl_qubits - 1)\\n elif operation.name == 'swap':\\n import qiskit.extensions.standard.cswap\\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\\n elif operation.name == 'u1':\\n import qiskit.extensions.standard.cu1\\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\\n elif operation.name == 'u3':\\n import qiskit.extensions.standard.cu3\\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\\n elif operation.name == 'cx':\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n else:\\n raise QiskitError('No standard controlled gate for \\\"{}\\\"'.format(\\n operation.name))\\n return cgate\",\n \"def GachaCraftNodeExcelAddGP1110(builder, GP1110):\\n return AddGP1110(builder, GP1110)\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\\n return self\",\n \"def forward(self, x):\\n out = x + self.conv_block(x) # add skip connections\\n return out\",\n \"def forward(self, x):\\n out = x + self.conv_block(x) # add skip connections\\n return out\",\n \"def forward(self, x):\\n out = x + self.conv_block(x) # add skip connections\\n return out\",\n \"def double_add(self, x):\\n self.add(x*2)\",\n \"def add_bitline_contacts(self):\\n\\n stack=(\\\"metal1\\\", \\\"via1\\\", \\\"metal2\\\")\\n pos = self.lower_pmos_inst.get_pin(\\\"S\\\").center()\\n self.add_contact_center(layers=stack,\\n offset=pos)\\n pos = self.lower_pmos_inst.get_pin(\\\"D\\\").center()\\n self.add_contact_center(layers=stack,\\n offset=pos)\\n pos = self.upper_pmos1_inst.get_pin(\\\"S\\\").center()\\n self.add_contact_center(layers=stack,\\n offset=pos)\\n pos = self.upper_pmos2_inst.get_pin(\\\"D\\\").center()\\n self.add_contact_center(layers=stack,\\n offset=pos)\",\n \"def cz(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CZ(), target=[control, target])\",\n \"def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\\n if q_args is None and c_args is None:\\n raise GateError(\\\"Gate needs at least one quantum argument or classical argument\\\")\\n if isinstance(gate, CompositeGate):\\n if mapping is None:\\n raise GateError(\\\"Must provide arguments mapping for composite gate inside a composite gate.\\\")\\n else:\\n inv_mappimg = dict()\\n for key, value in mapping.items():\\n inv_mappimg[value] = key\\n if gate is self:\\n gates = gate.copy.gates\\n else:\\n gates = gate.gates\\n for g in gates:\\n new_q_args = None\\n new_c_args = None\\n if g[1] is not None:\\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\\n if g[2] is not None:\\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\\n self.add_gate(gate=g[0], q_args=new_q_args,\\n c_args=new_c_args, params=g[3])\\n else:\\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\\n raise GateError(\\\"Gate must be either a CompositeGate or a string from: \\\"\\n \\\"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\\\")\\n if q_args is not None:\\n for q_arg in q_args:\\n if q_arg not in self.q_args:\\n self.add_q_arg(q_arg)\\n if c_args is not None:\\n for c_arg in c_args:\\n if c_arg not in self.c_args:\\n self.add_c_arg(c_arg)\\n if params is not None:\\n for param in params:\\n if param not in self.params:\\n self.add_param(param)\\n self._gates.append((gate, q_args, c_args, params))\",\n \"def construct(self, x):\\n x = self.conv(x)\\n l0 = self.down_conv1(x)\\n h0 = self.down_conv2(l0)\\n l1 = self.down_conv3(h0 - x)\\n return l1 + l0\",\n \"def cy(control: QubitInput, target: QubitInput) -> Instruction:\\n return Instruction(CY(), target=[control, target])\",\n \"def convert_C_instruction(self, instruction):\\n comp, dest, jump = self.parse(instruction)\\n\\n return f\\\"111{convert_comp(comp)}{convert_dest(dest)}\\\" \\\\\\n f\\\"{convert_jump(jump)}\\\"\",\n \"def forward(self, x):\\n x = self.conv(x)\\n x = self.bn(x)\\n x = self.act(x)\\n return x\",\n \"def forward(self, x):\\n x = self.conv(x)\\n x = self.bn(x)\\n x = self.act(x)\\n return x\",\n \"def TSX(self, *_):\\n self.reg.X = self.reg.S\\n self.reg.N = self.reg.X << 7\\n self.reg.Z = self.reg.X == 0\",\n \"def __init__(self, theta):\\n super().__init__(\\\"crz\\\", 2, [theta], num_ctrl_qubits=1)\\n self.base_gate = RZGate(theta)\",\n \"def putcfix(self,cfix_): # 3\\n res = self.__obj.putcfix(cfix_)\\n if res != 0:\\n result,msg = self.__getlasterror(res)\\n raise Error(rescode(res),msg)\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def comp_add_ao(self):\\n scene = self.set_as_active()\\n scene.use_nodes = True\\n tree = scene.node_tree\\n tree.nodes.clear()\\n\\n # creating the nodes\\n node_rlayer = tree.nodes.new('CompositorNodeRLayers')\\n node_rlayer.location = -300, 100\\n node_rlayer.scene = scene\\n node_rlayer.layer = w_var.rlname\\n\\n node_mixcolor = tree.nodes.new('CompositorNodeMixRGB')\\n node_mixcolor.location = 0, 50\\n node_mixcolor.blend_type = 'MULTIPLY'\\n node_mixcolor.inputs[0].default_value = 0.730\\n\\n node_comp = tree.nodes.new('CompositorNodeComposite')\\n node_comp.location = 300, 130\\n\\n node_viewer = tree.nodes.new('CompositorNodeViewer')\\n node_viewer.location = 300, -100\\n\\n # connecting the nodes\\n links = tree.links\\n links.new(node_rlayer.outputs[0], node_mixcolor.inputs[1])\\n links.new(node_rlayer.outputs[10], node_mixcolor.inputs[2])\\n links.new(node_mixcolor.outputs[0], node_comp.inputs[0])\\n links.new(node_mixcolor.outputs[0], node_viewer.inputs[0])\\n\\n for node in tree.nodes:\\n node.select = False\",\n \"def acosh(self, x):\\n return self.arccosh(x)\",\n \"def INX(self, *_):\\n self._dec_or_inc_register('X', increment=True)\",\n \"def addXValue(self,value):\\n self.__XValue.append(value)\\n self.updateValue()\",\n \"def add_cogs(self):\\n self.add_cog(Voice(self))\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\\n return self\",\n \"def transform(self, X):\\n return self.act_on(X)\",\n \"def test_scalar_coeff_cc():\\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\\n kappa = Symbol('kappa', real=True)\\n a1 = Destroy(hs=hs_1)\\n a2 = Destroy(hs=hs_2)\\n\\n jc_expr = (\\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\\n )\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == I * kappa * OperatorPlusMinusCC(\\n a1.dag() * a2, sign=-1\\n )\\n expanded = simplified.doit()\\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())\",\n \"def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)\\n return self\",\n \"def add_connector(self):\\n \\n no = len(self.connectors)\\n state = {}\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % no\\n \\n if len(self.connectors)>0:\\n state = self.connectors[-1].get_state()\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % (no)\\n else:\\n if self.mount == self.MOUNT_THT:\\n state[\\\"p_shape\\\"] = Con.SHAPE_HOLE\\n elif self.mount == self.MOUNT_SMD:\\n state[\\\"p_shape\\\"] = Con.SHAPE_PAD\\n \\n c = Con(no)\\n c.set_state(state) \\n \\n self.sch_layers[\\\"pins\\\"].add(c.s_svg)\\n self.pcb_layers[\\\"copper1\\\"].add(c.p_svg)\\n self.connectors.append(c)\",\n \"def test_simple_cc():\\n hs_c = LocalSpace('c', dimension=3)\\n hs_q = LocalSpace('q1', basis=('g', 'e'))\\n Delta_1 = Symbol('Delta_1')\\n Omega_1 = Symbol('Omega_1')\\n g_1 = Symbol('g_1')\\n a = Destroy(hs=hs_c)\\n a_dag = Create(hs=hs_c)\\n sig_p = LocalSigma('e', 'g', hs=hs_q)\\n sig_m = LocalSigma('g', 'e', hs=hs_q)\\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\\n assert (\\n srepr(simplified.term)\\n == \\\"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \\\"\\n \\\"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \\\"\\n \\\"basis=('g', 'e')))), sign=-1)\\\"\\n )\\n expanded = simplified.doit()\\n assert expanded == jc_expr\",\n \"def add_feature(x, x1):\\n if x is None:\\n x = x1\\n else:\\n x = np.concatenate((x, x1), axis=1)\\n return x\",\n \"def get_CC_operators():\\n i = symbols('i', below_fermi=True, cls=Dummy)\\n a = symbols('a', above_fermi=True, cls=Dummy)\\n t_ai = AntiSymmetricTensor('t', (a,), (i,))\\n ai = NO(Fd(a)*F(i))\\n i, j = symbols('i,j', below_fermi=True, cls=Dummy)\\n a, b = symbols('a,b', above_fermi=True, cls=Dummy)\\n t_abij = AntiSymmetricTensor('t', (a, b), (i, j))\\n abji = NO(Fd(a)*Fd(b)*F(j)*F(i))\\n\\n T1 = t_ai*ai\\n T2 = Rational(1, 4)*t_abij*abji\\n return (T1, T2)\",\n \"def __add__(self, x):\\n assert isinstance(x, AxisDistance), 'incorrect type of arg x: should be type AxisDistance, is type {}'.format(type(x))\\n tile = self.tile + x.tile\\n pixel = self.pixel + x.pixel\\n subpixel = self.subpixel + x.subpixel\\n return AxisDistance(t=tile, px=pixel, sx=subpixel)\",\n \"def process_block_to_add(coupling_point: Point, coupling_angle : Angle, conjugation_angle : Angle, cc_bond_length:float, block_to_add: Building_Block):\\n\\n\\t#load data for block_to_add\\n\\tcoord_xyz = top.read_xyz_file(block_to_add.path)\\n\\tcoord_xyz_save = np.copy(coord_xyz)\\n\\n\\t\\n\\n\\t#rotate around z axis for conjugation, rotate around y for right orientation,shift to coupling point and shift by c-c bond length in right direction\\n\\tfor i in range(0,coord_xyz.shape[1]):\\n\\t\\t\\n\\t\\t#conjugation x' = cos(phi)*x-sin(phi)*y\\n\\t\\tcoord_xyz[1,i] = coord_xyz_save[1,i]*np.cos(conjugation_angle)-np.sin(conjugation_angle)*coord_xyz_save[2,i]\\n\\t\\t#conjugation y' = sin(phi)*x+cos(phi)*y\\n\\t\\tcoord_xyz[2,i] = coord_xyz_save[1,i]*np.sin(conjugation_angle)+np.cos(conjugation_angle)*coord_xyz_save[2,i]\\n\\n\\t\\tcoord_xyz_save = np.copy(coord_xyz)\\n\\n\\t\\t#rotation around y: x' = cos(phi)*x+sin(phi)*z\\n\\t\\tcoord_xyz[1,i] = coord_xyz_save[1,i]*np.cos(coupling_angle)+np.sin(coupling_angle)*coord_xyz_save[3,i]\\n\\t\\t#rotation around y: z' = cos(phi)*z-sin(phi)*x\\n\\t\\tcoord_xyz[3,i] = -coord_xyz_save[1,i]*np.sin(coupling_angle)+np.cos(coupling_angle)*coord_xyz_save[3,i]\\n\\n\\t\\t#shift to coupling point x -> x+x_c\\n\\t\\tcoord_xyz[1,i] = coord_xyz[1,i]+coupling_point.x\\n\\t\\t#shift to coupling point y -> y+y_c\\n\\t\\tcoord_xyz[2,i] = coord_xyz[2,i]+coupling_point.y\\n\\t\\t#shift to coupling point z -> z+z_c\\n\\t\\tcoord_xyz[3,i] = coord_xyz[3,i]+coupling_point.z\\n\\n\\t\\t#shift by C-C bond length in e_c direction sin=-0.866 cos=-0.499\\n\\t\\tcoord_xyz[1,i] = coord_xyz[1,i]+cc_bond_length*np.sin(coupling_angle)\\n\\t\\t#shift by C-C bond length in e_c direction\\n\\t\\tcoord_xyz[3,i] = coord_xyz[3,i]+cc_bond_length*np.cos(coupling_angle)\\n\\treturn coord_xyz\",\n \"def turn_fcc_on(self):\\n raise NotImplementedError\",\n \"def GachaCraftNodeExcelAddGP1101(builder, GP1101):\\n return AddGP1101(builder, GP1101)\",\n \"def add_point(self, x, fx, dx):\\n\\t\\tself.v.append([x, fx, dx])\\n\\t\\tself.v.append([x, fx, dx])\\n\\t\\tself.poli = None\",\n \"def _process_cnot(self, node):\\n id0 = self._process_bit_id(node.children[0])\\n id1 = self._process_bit_id(node.children[1])\\n if not(len(id0) == len(id1) or len(id0) == 1 or len(id1) == 1):\\n raise UnrollerError(\\\"internal error: qreg size mismatch\\\",\\n \\\"line=%s\\\" % node.line, \\\"file=%s\\\" % node.file)\\n maxidx = max([len(id0), len(id1)])\\n for idx in range(maxidx):\\n if len(id0) > 1 and len(id1) > 1:\\n self.backend.cx(id0[idx], id1[idx])\\n elif len(id0) > 1:\\n self.backend.cx(id0[idx], id1[0])\\n else:\\n self.backend.cx(id0[0], id1[idx])\",\n \"def add(self, x):\\n if type(x) is int:\\n self.real += x\\n else:\\n self.real = self.real + x.real\\n self.imag = self.imag + x.imag\",\n \"def add_neurone(self, couche, nbr=1):\\n if self.control == 0:\\n if couche >= 0 and couche <= len(self.couche) - 1 and nbr > 0:\\n self.couche[couche] += nbr\\n else:\\n print(\\\"Le réseau est deja créé, vous en pouvez plus le modifier\\\")\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def dcx(self, addr):\\n\\n self.reg.idx = self.reg.idx.inc(-1)\\n self.reg.zerox_flag = self.reg.idx.eq_zero()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.63400793","0.5722614","0.57119","0.555426","0.5540648","0.5507331","0.5357815","0.53444254","0.53307414","0.5300384","0.52716064","0.5259016","0.51508355","0.51378155","0.5125027","0.50955683","0.50826627","0.5060708","0.5052761","0.50502384","0.5042433","0.50361955","0.5028113","0.501739","0.49904606","0.49827895","0.49558023","0.49454027","0.49413055","0.49387133","0.49306285","0.49275154","0.49191692","0.4911906","0.48949254","0.4891133","0.48897487","0.48868576","0.48842978","0.48834804","0.4883471","0.48832268","0.48793194","0.4870021","0.4864878","0.4860748","0.48505068","0.4837893","0.48374802","0.4826746","0.48220903","0.48055902","0.48050493","0.47862312","0.47809646","0.47751972","0.4764396","0.4761964","0.4744529","0.47367695","0.47357383","0.47322404","0.4725362","0.4725362","0.4725362","0.4723732","0.47226053","0.47183886","0.4711792","0.47083125","0.4695727","0.4681242","0.46793783","0.46793783","0.46792564","0.46744177","0.46723935","0.46722788","0.4671138","0.4669094","0.46670374","0.4664925","0.46622598","0.46607774","0.46576053","0.46538228","0.46515697","0.46494338","0.4644736","0.46400017","0.46344063","0.4630945","0.46298826","0.46251923","0.46243593","0.4623382","0.46210787","0.46194237","0.46154925","0.46149096","0.46081978"],"string":"[\n \"0.63400793\",\n \"0.5722614\",\n \"0.57119\",\n \"0.555426\",\n \"0.5540648\",\n \"0.5507331\",\n \"0.5357815\",\n \"0.53444254\",\n \"0.53307414\",\n \"0.5300384\",\n \"0.52716064\",\n \"0.5259016\",\n \"0.51508355\",\n \"0.51378155\",\n \"0.5125027\",\n \"0.50955683\",\n \"0.50826627\",\n \"0.5060708\",\n \"0.5052761\",\n \"0.50502384\",\n \"0.5042433\",\n \"0.50361955\",\n \"0.5028113\",\n \"0.501739\",\n \"0.49904606\",\n \"0.49827895\",\n \"0.49558023\",\n \"0.49454027\",\n \"0.49413055\",\n \"0.49387133\",\n \"0.49306285\",\n \"0.49275154\",\n \"0.49191692\",\n \"0.4911906\",\n \"0.48949254\",\n \"0.4891133\",\n \"0.48897487\",\n \"0.48868576\",\n \"0.48842978\",\n \"0.48834804\",\n \"0.4883471\",\n \"0.48832268\",\n \"0.48793194\",\n \"0.4870021\",\n \"0.4864878\",\n \"0.4860748\",\n \"0.48505068\",\n \"0.4837893\",\n \"0.48374802\",\n \"0.4826746\",\n \"0.48220903\",\n \"0.48055902\",\n \"0.48050493\",\n \"0.47862312\",\n \"0.47809646\",\n \"0.47751972\",\n \"0.4764396\",\n \"0.4761964\",\n \"0.4744529\",\n \"0.47367695\",\n \"0.47357383\",\n \"0.47322404\",\n \"0.4725362\",\n \"0.4725362\",\n \"0.4725362\",\n \"0.4723732\",\n \"0.47226053\",\n \"0.47183886\",\n \"0.4711792\",\n \"0.47083125\",\n \"0.4695727\",\n \"0.4681242\",\n \"0.46793783\",\n \"0.46793783\",\n \"0.46792564\",\n \"0.46744177\",\n \"0.46723935\",\n \"0.46722788\",\n \"0.4671138\",\n \"0.4669094\",\n \"0.46670374\",\n \"0.4664925\",\n \"0.46622598\",\n \"0.46607774\",\n \"0.46576053\",\n \"0.46538228\",\n \"0.46515697\",\n \"0.46494338\",\n \"0.4644736\",\n \"0.46400017\",\n \"0.46344063\",\n \"0.4630945\",\n \"0.46298826\",\n \"0.46251923\",\n \"0.46243593\",\n \"0.4623382\",\n \"0.46210787\",\n \"0.46194237\",\n \"0.46154925\",\n \"0.46149096\",\n \"0.46081978\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":81760,"cells":{"query":{"kind":"string","value":"add CSW gate (fredkin gate, controlled swap gate)."},"document":{"kind":"string","value":"def csw(self, q0, q1, q2, ctrl=None):\n self.cx(q2,q1,ctrl=ctrl).ccx(q0,q1,q2,ctrl=ctrl).cx(q2,q1,ctrl=ctrl)\n return self"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits > 0:\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\n else:\n circuit = circuit.compose(gate[0], qbits[i])\n\n return circuit","def test_append_two_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"CNOT\")\n circuit.append_gate(gate, wire_ids=[2, 3])\n assert gate.indices == [\"2-1\", \"3-1\", \"2-0\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=1, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def cs(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\n return self","def circuitSat(C):","def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\n return self","def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])","def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=False),\n jet.Wire(1, depth=0, closed=False),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=1, closed=False),\n ]","def cs_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\n return self","def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])","def welding_state_add(self, ws1, ws2):\n\n if ws2 is None:\n return ws1\n\n if ws2.amperage is not None:\n ws1.amperage += ws2.amperage\n\n if ws2.voltage is not None:\n ws1.voltage += ws2.voltage\n\n if ws2.filler_speed is not None:\n ws1.filler_speed += ws2.filler_speed\n\n if ws2.default_arc_length is not None:\n ws1.default_arc_length += ws2.default_arc_length\n\n if ws2.mode is not None:\n ws1.mode = ws2.mode\n\n if ws2.speed is not None:\n ws1.speed += ws2.speed\n\n return ws1","def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n qc.x(register[0])","def ct(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\n return self","def BCS(self, value):\n if self.reg.C:\n self.reg.PC += value","def _update_sym_const(self,name,G1,remove_nodes,new_inst, const_list):\n logger.debug(f\"updating symmetry block constraints of subcircuit {name}, nodes: {remove_nodes}, new name: {new_inst}\")\n if self._if_const(name):\n for const in const_list:\n if hasattr(const, 'pairs'):\n for pair in const.pairs:\n if len(pair) == 2:\n if pair[0] in remove_nodes and pair[1] in remove_nodes:\n pair[0] = new_inst\n pair.pop()\n logger.debug(f\"updated symmetric pair constraint to self symmetry:{const}\")\n elif pair[0] in remove_nodes and pair[1] not in remove_nodes:\n pair[0] = new_inst\n elif pair[1] in remove_nodes and pair[0] not in remove_nodes:\n pair[1] = new_inst\n elif len(pair) == 1:\n if pair[0] in remove_nodes:\n pair[0] = new_inst\n logger.debug(f\"updated symmetric pair constraint to self symmetry:{const}\")","def add_connector(self):\n \n no = len(self.connectors)\n state = {}\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % no\n \n if len(self.connectors)>0:\n state = self.connectors[-1].get_state()\n state[\"s_pin\"] = no\n state[\"p_pin\"] = no\n state[\"s_label\"] = \"C%d\" % (no)\n else:\n if self.mount == self.MOUNT_THT:\n state[\"p_shape\"] = Con.SHAPE_HOLE\n elif self.mount == self.MOUNT_SMD:\n state[\"p_shape\"] = Con.SHAPE_PAD\n \n c = Con(no)\n c.set_state(state) \n \n self.sch_layers[\"pins\"].add(c.s_svg)\n self.pcb_layers[\"copper1\"].add(c.p_svg)\n self.connectors.append(c)","def cox_cc_loss_single_ctrl(g_case: Tensor, g_control: Tensor, shrink: float = 0.) -> Tensor:\n loss = F.softplus(g_control - g_case).mean()\n if shrink != 0:\n loss += shrink * (g_case.abs().mean() + g_control.abs().mean())\n return loss","def convert_swish(g, op, block):\n\n x = g.get_node(op.input(\"X\")[0])\n beta = op.attr(\"beta\")\n assert beta == 1.0, \"Only support beta==1.0 for PaddlePaddle's swish\"\n out = x * _op.tensor.sigmoid(x)\n g.add_node(op.output(\"Out\")[0], out)","def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self","def local_addsd_ccode(node):\r\n if isinstance(node.op, sparse.AddSD) and theano.config.cxx:\r\n new_node = AddSD_ccode(format=node.inputs[0].type.format)(*node.inputs)\r\n return [new_node]\r\n return False","def test_scalar_coeff_cc():\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\n kappa = Symbol('kappa', real=True)\n a1 = Destroy(hs=hs_1)\n a2 = Destroy(hs=hs_2)\n\n jc_expr = (\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\n )\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == I * kappa * OperatorPlusMinusCC(\n a1.dag() * a2, sign=-1\n )\n expanded = simplified.doit()\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())","def add(self, y):\n return circuit.add(self, y)","def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\"classical\")\n \n if ancillas == None:\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\n \n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\n\n for i in range(len(qbits)):\n if gate[0].num_clbits() > 0:\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\n else:\n dag.compose(gate[0], qubits = qbits[i])\n\n return dag","def add(num1, num2, Cin):\n Cin=0\n l2=[]\n final=\"\"\n\n \"\"\"Using for loop for starting addition from the last indexed number\"\"\"\n for i in range(len(num1)-1,-1,-1):\n bit1=num1[i]#storing each indexed() value of num1 in bit1\n bit2=num2[i]#storing each indexed() value of num2 in bit2\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\n Cin=Cout#declaring cout as cin for next bit addition\n l2.append(SUM)#adding SUM to l2\n l3=l2[::-1]##reversing the value of l2\n final+=str(l2[-1])#converting the list value to string\n final1=final[::-1]#reversing string value\n return final1 #returning the binary addition as string","def __le__(self, *args):\n return _ida_hexrays.cswitch_t___le__(self, *args)","def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\n strategy = self.insert_strategy\n self.append(gate_ops, strategy=strategy)","def local_inplace_addsd_ccode(node):\r\n if isinstance(node.op, sparse.AddSD) and theano.config.cxx:\r\n out_dtype = scalar.upcast(*node.inputs)\r\n if out_dtype != node.inputs[1].dtype:\r\n return\r\n new_node = AddSD_ccode(format=node.inputs[0].type.format,\r\n inplace=True)(*node.inputs)\r\n return [new_node]\r\n return False","def add_junction(ccTremb):\n pass","def ct_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\n return self","def cswap(control: QubitInput, target1: QubitInput, target2: QubitInput) -> Instruction:\n return Instruction(CSwap(), target=[control, target1, target2])","def __add__(self, tc): \n tc = TwosComplement(tc)\n bits = self.len if self.len > tc.len else tc.len \n result = self.int + tc.int\n return TwosComplement(result, bits)","def enc_add_const(pub, m, c):\n # Similiar to enc add\n add_const_result = m * powmod(pub.g, c, pub.n_sq) % pub.n_sq\n return add_const_result","def s_dg(self, q0, ctrl=None):\n self.__add_quantum_gate(kind=PHASE_SHIFT_S_, qid=[q0], ctrl=ctrl)\n return self","def _write_circuit(self, feature_vector_index):\n # grab the feature vector\n feature_vector = self.data.data[feature_vector_index]\n\n # compute the indices to put gates at\n inds = [x for x in range(len(feature_vector)) if feature_vector[x] == 1]\n\n # write the circuit\n self.circuits[feature_vector_index].add_layer(H)\n self.circuits[feature_vector_index].add_at(Z, inds)\n\n # TODO: all encoding classes will need this method.\n # TODO: make a BaseEncoding that implements this","def recursive_gate(e):\n if isinstance(e, boolean.BaseElement):\n # TODO: Either make the the same or create a constant component.\n s = Switch()\n b.append(s)\n return s\n elif isinstance(e, boolean.Symbol):\n if e in symbol_dict.keys():\n return symbol_dict[e]\n else:\n s = Switch()\n symbol_dict[e] = s\n b.append(s)\n return s\n elif isinstance(e, boolean.Function):\n # All gates are of type Gate instead of And, Or and Not\n if e.order == (1, 1):\n pre = recursive_gate(e.args[0])\n w = Wire(pre)\n b.append(w)\n\n s = boolean.Symbol(None)\n g = Gate(e.subs({e.args[0]: s}),\n {s: w})\n b.append(g)\n return g\n else:\n input_dict = {}\n expr = e\n for arg in e.args:\n pre = recursive_gate(arg)\n w = Wire(pre)\n b.append(w)\n\n s = boolean.Symbol(None)\n expr = expr.subs({arg: s})\n input_dict[s] = w\n g = Gate(expr,\n input_dict)\n b.append(g)\n return g","def coadd(self, step_index):\n if self.drip_config is not None:\n if ('boresight' in self.drip_cal_config\n and 'SLIT' in self.drip_cal_config['boresight']):\n self.current[step_index].set_value('skip_coadd', True)","def enable_cl1_direct(self):\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\n self.write_versa5(0x18,0x20)\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\n self.write_versa5(0x13,0x03) ## Switch to clock\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew","def apply_const_shift_operator(model, operator):\n for term in operator:\n dif = take_derivative_shift_op(model, term)\n try:\n total += dif\n except NameError:\n total = dif\n return total","def cg_apply_ws(A, B, w0, w1, w2, w3, pars):\n # We manually loop over one of the legs to lower the memory cost.\n vects = []\n # Generate the vectors to sum over in this manual loop,\n # for non-symmetric tensors:\n if A.qhape is None:\n dim = A.shape[5]\n for j in range(dim):\n vect = type(A).zeros([dim])\n vect[j] = 1.\n vects.append(vect)\n # and for symmetric tensors:\n else:\n qim = A.qhape[5]\n dim = A.shape[5]\n direction = A.dirs[5]\n for i, q in enumerate(qim):\n qdim = dim[i]\n for j in range(qdim):\n vect = type(A).zeros([dim], qhape=[qim], dirs=[-direction],\n charge=-direction*q, invar=True)\n vect[(q,)][j] = 1.\n vects.append(vect)\n # Compute the networks with the middle leg replaced with\n # vect \\otimes vect, and sum them all up.\n result = None\n for vect in vects:\n Ared = ncon((A, vect), ([-1,-2,-3,-4,-5,6], [6]))\n Bred = ncon((B, vect.conjugate()), ([-1,-2,-3,-4,5,-6], [5]))\n term = ncon((Ared, Bred,\n w0, w1, w2, w3),\n ([1,2,11,12,-5], [13,14,3,4,-6],\n [-1,1,13], [-2,2,14], [-3,11,3], [-4,12,4]))\n if result is None:\n result = term\n else:\n result += term\n return result","def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.ccx(register[1], register[0], ancilla)\n qc.x(register[0])","def cz(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n return self","def connect(self, gate) :\n self.notifyList.append(gate)","def BCC(self, value):\n if not self.reg.C:\n self.reg.PC += value","def inc_xor_gateways(self):\r\n self.num_xor_gateways += 1","def _control_predefined(operation, num_ctrl_qubits):\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\n if num_ctrl_qubits == 1:\n import qiskit.extensions.standard.cx\n cgate = qiskit.extensions.standard.cx.CnotGate()\n else:\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n elif operation.name == 'y':\n import qiskit.extensions.standard.cy\n cgate = qiskit.extensions.standard.cy.CyGate()\n elif operation.name == 'z':\n import qiskit.extensions.standard.cz\n cgate = qiskit.extensions.standard.cz.CzGate()\n elif operation.name == 'h':\n import qiskit.extensions.standard.ch\n cgate = qiskit.extensions.standard.ch.CHGate()\n elif operation.name in {'rx', 'ry', 'rz'}:\n if operation.name == 'rx':\n import qiskit.extensions.standard.crx\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\n elif operation.name == 'ry':\n import qiskit.extensions.standard.cry\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\n else: # operation.name == 'rz'\n import qiskit.extensions.standard.crz\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\n if num_ctrl_qubits == 1:\n return cgate\n else:\n # only predefined for one control qubit\n return cgate.control(num_ctrl_qubits - 1)\n elif operation.name == 'swap':\n import qiskit.extensions.standard.cswap\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\n elif operation.name == 'u1':\n import qiskit.extensions.standard.cu1\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\n elif operation.name == 'u3':\n import qiskit.extensions.standard.cu3\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\n elif operation.name == 'cx':\n import qiskit.extensions.standard.ccx\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\n else:\n raise QiskitError('No standard controlled gate for \"{}\"'.format(\n operation.name))\n return cgate","def gate(self):\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)","def test_add_gate(self):\n sched = Schedule()\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\n inst_map = InstructionScheduleMap()\n\n inst_map.add(U1Gate(0), 1, sched)\n inst_map.add(U1Gate(0), 0, sched)\n\n self.assertIn(\"u1\", inst_map.instructions)\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\n self.assertTrue(\"u1\" in inst_map.qubit_instructions(0))\n\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), (), sched)\n with self.assertRaises(PulseError):\n inst_map.add(U1Gate(0), 1, \"not a schedule\")","def alg(c):\n return c[0]*G[0] + c[1]*G[1] + c[2]*G[2]","def SO4_circuit(a_alpha, a_theta, a_beta, b_alpha, b_theta, b_beta):\n # return np.kron(S1_inv, I2) @ np.kron(I2, S1_inv) @ np.kron(I2, R1_inv) @ CNOT2 \\\n # @ np.kron(I2, R_z(b_beta)) @ np.kron(I2, R_y(b_theta)) @ np.kron(I2, R_z(b_alpha)) \\\n # @ np.kron(R_z(a_beta), I2) @ np.kron(R_y(a_theta), I2) @ np.kron(R_z(a_alpha), I2) \\\n # @ CNOT2 @ np.kron(I2, R1) @ np.kron(I2, S1) @ np.kron(S1, I2)\n\n return np.linalg.inv(magic_gate) \\\n @ np.kron(I2, R_z(b_beta)) @ np.kron(I2, R_y(b_theta)) @ np.kron(I2, R_z(b_alpha)) \\\n @ np.kron(R_z(a_beta), I2) @ np.kron(R_y(a_theta), I2) @ np.kron(R_z(a_alpha), I2) \\\n @ magic_gate","def update_control(self):\n self._control_ctr += 0x01","def fc_forward(x, w, b):\n out = None\n ###########################################################################\n # TODO: Implement the forward pass. Store the result in out. #\n ###########################################################################\n out = np.dot(x, w) + b\n ###########################################################################\n # END OF YOUR CODE #\n ###########################################################################\n cache = (x, w, b)\n return out, cache","def circuit():\n np.random.seed(1967)\n for gates in gates_per_layers:\n for gate in gates:\n qml.apply(gate)\n return qml.expval(qml.PauliZ(0))","def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\n return self","def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]","def _add_switchs(self):\r\n lst = self.model.get_all_switch()\r\n\r\n for itm in lst:\r\n self._add_switch(itm)","def addOp(self, op):\n self.operations << op","def test_append_two_wire_state(self, circuit):\n state = jet.QubitRegister(size=2)\n circuit.append_state(state, wire_ids=[0, 1])\n assert state.indices == [\"0-0\", \"1-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(state, [0, 1])\n assert list(circuit.wires) == [\n jet.Wire(0, depth=0, closed=True),\n jet.Wire(1, depth=0, closed=True),\n jet.Wire(2, depth=0, closed=False),\n jet.Wire(3, depth=0, closed=False),\n ]","def fc_forward(x, w, b):\n out = None\n ###########################################################################\n # TODO: Implement the forward pass. Store the result in out. #\n ###########################################################################\n out = np.matmul(x, w)\n out += b\n ###########################################################################\n # END OF YOUR CODE #\n ###########################################################################\n cache = (x, w, b)\n return out, cache","def add_state(self, name='Ti', c=2000):\n assert isinstance(name, str), 'name must be a string type'\n if name in self.sta.keys():\n raise Exception('State already defined')\n state = State(c=c, name=name)\n self.sta[name] = state\n self.nodes[name] = state\n self.rc.add_node(state)","def iadd(state: State) -> State:\n cell = state.array[state.index] or 0\n return state._replace(acc=state.acc + cell)","def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\n if q_args is None and c_args is None:\n raise GateError(\"Gate needs at least one quantum argument or classical argument\")\n if isinstance(gate, CompositeGate):\n if mapping is None:\n raise GateError(\"Must provide arguments mapping for composite gate inside a composite gate.\")\n else:\n inv_mappimg = dict()\n for key, value in mapping.items():\n inv_mappimg[value] = key\n if gate is self:\n gates = gate.copy.gates\n else:\n gates = gate.gates\n for g in gates:\n new_q_args = None\n new_c_args = None\n if g[1] is not None:\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\n if g[2] is not None:\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\n self.add_gate(gate=g[0], q_args=new_q_args,\n c_args=new_c_args, params=g[3])\n else:\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\n raise GateError(\"Gate must be either a CompositeGate or a string from: \"\n \"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\")\n if q_args is not None:\n for q_arg in q_args:\n if q_arg not in self.q_args:\n self.add_q_arg(q_arg)\n if c_args is not None:\n for c_arg in c_args:\n if c_arg not in self.c_args:\n self.add_c_arg(c_arg)\n if params is not None:\n for param in params:\n if param not in self.params:\n self.add_param(param)\n self._gates.append((gate, q_args, c_args, params))","def add(self, sgid, other, proto_spec, direction=\"in\"):\n # returns bool\n # AuthorizeSecurityGroupIngress, AuthorizeSecurityGroupEgress\n if direction == \"in\":\n api = \"AuthorizeSecurityGroupIngress\"\n elif direction == \"out\":\n api = \"AuthorizeSecurityGroupEgress\"\n else:\n raise ValueError(\"direction must be one of ('in', 'out')\")\n return self.modify(api, sgid, other, proto_spec)","def gate_mfcc(recurrent_net, sample_input):\n length = sample_input.shape[1]\n score, select = np.zeros(length), np.zeros(length)\n for i in range(length):\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\n select = sigmoid(select)\n return np.sum(select * score) / np.sum(select)","def brepalgo_ConcatenateWireC0(*args):\n return _BRepAlgo.brepalgo_ConcatenateWireC0(*args)","def ADD():\n global pointer, memory, registers\n registers[memory[pointer + 0x02]] += memory[pointer + 0x01]\n pointer += 0x03","def coupler_symmetric(\n bend: Callable = bend_s,\n gap: float = 0.234,\n wg_width: float = 0.5,\n layer: Tuple[int, int] = pp.LAYER.WG,\n layers_cladding: List[Tuple[int, int]] = [pp.LAYER.WGCLAD],\n cladding_offset: float = 3.0,\n) -> Component:\n bend = pp.call_if_func(\n bend,\n width=wg_width,\n layer=layer,\n layers_cladding=layers_cladding,\n cladding_offset=cladding_offset,\n pins=False,\n )\n\n w = bend.ports[\"W0\"].width\n y = (w + gap) / 2\n\n c = pp.Component()\n top_bend = bend.ref(position=(0, y), port_id=\"W0\")\n bottom_bend = bend.ref(position=(0, -y), port_id=\"W0\", v_mirror=True)\n\n c.add(top_bend)\n c.add(bottom_bend)\n\n # Using absorb here to have a flat cell and avoid\n # to have deeper hierarchy than needed\n c.absorb(top_bend)\n c.absorb(bottom_bend)\n\n port_width = 2 * w + gap\n c.add_port(name=\"W0\", midpoint=[0, 0], width=port_width, orientation=180)\n c.add_port(port=bottom_bend.ports[\"E0\"], name=\"E0\")\n c.add_port(port=top_bend.ports[\"E0\"], name=\"E1\")\n\n return c","def fully_connect(self, x, w, b, name=\"\"):\n return tf.nn.relu(tf.matmul(x, w) + b, name=name)","def __ge__(self, *args):\n return _ida_hexrays.cswitch_t___ge__(self, *args)","def ch(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_H, qid=[q0,q1], ctrl=ctrl)\n return self","def addToTfLink(G,i,j,siso):\n m,n,r = np.shape(G.num)\n dt = G.dt\n\n #Create a new transfer fuction Add, that is zero except the i,jth entry \n Addnum = []\n Addden = []\n rowN = [np.array([0.])]*n\n rowD = [np.array([1.])]*n\n\n for k in range(m):\n Addnum.append(list(rowN))\n Addden.append(list(rowD))\n\n #Make the i,jth entry of Add equal to siso\n Addnum[i][j] = siso.num[0][0]\n Addden[i][j] = siso.den[0][0]\n Add = ctrl.tf(Addnum,Addden,dt)\n\n #Use the control library + function to add the new transfer function to G\n Gplus = G + Add\n return Gplus","def addToTfLink(G,i,j,siso):\n m,n,r = np.shape(G.num)\n dt = G.dt\n\n #Create a new transfer fuction Add, that is zero except the i,jth entry \n Addnum = []\n Addden = []\n rowN = [np.array([0.])]*n\n rowD = [np.array([1.])]*n\n\n for k in range(m):\n Addnum.append(list(rowN))\n Addden.append(list(rowD))\n\n #Make the i,jth entry of Add equal to siso\n Addnum[i][j] = siso.num[0][0]\n Addden[i][j] = siso.den[0][0]\n Add = ctrl.tf(Addnum,Addden,dt)\n\n #Use the control library + function to add the new transfer function to G\n Gplus = G + Add\n return Gplus","def set_sw(self, phasecal, s12_value=None):\n s12_value = 3 if s12_value is None else s12_value\n # TBF: we'll have to look at the LO pickled data to\n # determine the switches being used\n\n # switches = ifpath.get_lo_sw()\n # for sw in switches:\n # self.seq.add_param(self.mng_name, sw[0], sw[1])\n # if sw[0] == \"S13\":\n # s12_value = \"4\"\n # self.seq.add_param(self.mng_name, \"S12\", str(s12_value))\n\n if phasecal in [\"on\"]:\n self.seq.add_param(self.mng_name, \"S1\", \"cross\")\n self.seq.add_param(self.mng_name, \"S11\", \"thru\")\n self.seq.add_param(self.mng_name, \"S3\", \"4\")\n self.seq.add_param(self.mng_name, \"phaseCalMode\", phasecal)\n self.seq.add_param(self.mng_name, \"phaseCalCtl\", \"On\")\n elif phasecal in [\"M1-disconnect\", \"M5-disconnect\"]:\n self.seq.add_param(self.mng_name, \"S1\", \"cross\")\n self.seq.add_param(self.mng_name, \"S11\", \"cross\")\n self.seq.add_param(self.mng_name, \"S3\", \"4\")\n self.seq.add_param(self.mng_name, \"phaseCalMode\", phasecal[0:2])\n self.seq.add_param(self.mng_name, \"phaseCalCtl\", \"On\")\n elif phasecal in [\"M1\", \"M5\"]:\n self.seq.add_param(self.mng_name, \"S3\", \"4\")\n self.seq.add_param(self.mng_name, \"S1\", \"cross\")\n self.seq.add_param(self.mng_name, \"S11\", \"thru\")\n self.seq.add_param(self.mng_name, \"phaseCalMode\", phasecal)\n self.seq.add_param(self.mng_name, \"phaseCalCtl\", \"On\")\n else:\n self.seq.add_param(self.mng_name, \"S3\", \"3\")\n self.seq.add_param(self.mng_name, \"S1\", \"cross\")\n self.seq.add_param(self.mng_name, \"S11\", \"cross\")\n self.seq.add_param(self.mng_name, \"phaseCalCtl\", \"Off\")\n\n if self.rcvr_name not in (\"Rcvr26_40\", \"RcvrArray18_26\", \"Rcvr68_92\"):\n self.seq.add_param(self.mng_name, \"loConfig\", \"TrackA_BNotUsed\", 1)\n self.seq.add_param(self.mng_name, \"testTonePowerLevel\", \"-110\", 4)\n self.seq.add_param(self.mng_name, \"testToneFreq\", \"17000\", 1)","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\n return self","def _cmplx_add_ ( s , o ) :\n return o + complex ( s )","def test_add_consistency1(self) -> None:\n a = Constant(\n 'const1',\n Float32(),\n np.zeros([1, 3, 3])\n )\n b = Constant(\n 'const2',\n Float32(),\n np.zeros([3])\n )\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\n Add(\n 'add1',\n [1, 3, 3],\n Float32(),\n input_ops\n )\n\n print(\"Consistency test for 'Add' #1 passed!\")","def test_simple_cc():\n hs_c = LocalSpace('c', dimension=3)\n hs_q = LocalSpace('q1', basis=('g', 'e'))\n Delta_1 = Symbol('Delta_1')\n Omega_1 = Symbol('Omega_1')\n g_1 = Symbol('g_1')\n a = Destroy(hs=hs_c)\n a_dag = Create(hs=hs_c)\n sig_p = LocalSigma('e', 'g', hs=hs_q)\n sig_m = LocalSigma('g', 'e', hs=hs_q)\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\n\n simplified = rewrite_with_operator_pm_cc(jc_expr)\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\n assert (\n srepr(simplified.term)\n == \"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \"\n \"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \"\n \"basis=('g', 'e')))), sign=-1)\"\n )\n expanded = simplified.doit()\n assert expanded == jc_expr","def BVS(self, value):\n if self.reg.V:\n self.reg.PC += value","def update_g_switches(self, sw_arr):\n\n if len(sw_arr) != 6:\n raise Exception('CTC Recived Erronious Green Switch Array')\n for i in range(len(sw_arr)):\n if sw_arr[i]:\n self.switches_green_arr[i].pointing_to = self.switches_green_arr[i].greater_block\n else:\n self.switches_green_arr[i].pointing_to = self.switches_green_arr[i].less_block","def control(self, num_ctrl_qubits=1, label=None):\n if num_ctrl_qubits == 1:\n return CrzGate(self.params[0])\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)","def __iadd__(self, other):\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\n return self","def conv_block(inp, cweight, bweight):\n conv = tf.nn.conv2d(inp, cweight, strides=[1, 1, 1, 1], padding='SAME')\n conv = tf.nn.bias_add(conv, bweight)\n relu = tf.nn.leaky_relu(conv)\n return relu","def add_layer(self, freeze = True, add = True):\n if add:\n self.num_layers += 1\n if self.conv_dim == 1:\n new_cnn = layers.Conv1D(self.n_filters,\n (self.n_kernels),\n activation='elu',\n input_shape=(None, self.inp_shape[0], self.n_filters),\n padding=\"same\",\n name='cnn_1d_{}'.format(self.num_layers-1),\n kernel_initializer = initializers.get(self.initializer),\n bias_initializer=initializers.get(\"zeros\"),\n kernel_regularizer=self.regularizer,\n bias_regularizer=self.regularizer\n )\n elif self.conv_dim == 2:\n new_cnn = layers.Conv2D(self.n_filters,\n (self.n_kernels, self.n_kernels),\n activation='elu',\n input_shape=(None, self.inp_shape[0],self.inp_shape[1], self.n_filters),\n padding=\"same\",\n name='cnn_2d_{}'.format(self.num_layers-1),\n kernel_initializer=initializers.get(self.initializer),\n bias_initializer=initializers.get(\"zeros\"),\n kernel_regularizer=self.regularizer,\n bias_regularizer=self.regularizer\n )\n self.list_cnn.append(new_cnn)\n\n if freeze:\n for index in range(0,self.num_layers-1):\n self.list_cnn[index].trainable = False\n else:\n for index in range(0,self.num_layers-1):\n self.list_cnn[index].trainable = True","def add_clay_to_selected(self):\n scene = self.set_as_active()\n\n # if the user selected a material, use it\n if w_var.cb_mat_clay:\n clay_mat = bpy.data.materials[w_var.mat_clay_name]\n\n # else, create a new one with the color selected\n else:\n clay_color = w_var.color_clay\n\n # separating rgb and alpha\n clay_color_rgb = clay_color[0:3]\n clay_color_alpha = clay_color[-1]\n clay_mat = bpy.data.materials.new('clay')\n \n renderengine = scene.wirebomb.data_renderengine\n \n if renderengine == 'CYCLES':\n clay_mat.use_nodes = True\n tree = clay_mat.node_tree\n tree.nodes.clear()\n\n # creating the nodes\n node_transparent = tree.nodes.new('ShaderNodeBsdfTransparent')\n node_transparent.location = -300, 100\n\n node_diffuse = tree.nodes.new('ShaderNodeBsdfDiffuse')\n node_diffuse.location = -300, -100\n node_diffuse.inputs[0].default_value = clay_color_rgb + (1.0, )\n node_diffuse.color = clay_color_rgb\n node_diffuse.name = 'addon_clay_color' # referencing to this ID in the real-time change\n\n node_mixshader = tree.nodes.new('ShaderNodeMixShader')\n node_mixshader.location = 0, 50\n node_mixshader.inputs[0].default_value = clay_color_alpha\n node_mixshader.name = 'addon_clay_alpha' # referencing to this ID in the real-time change\n\n node_output = tree.nodes.new('ShaderNodeOutputMaterial')\n node_output.location = 300, 50\n\n # connecting the nodes\n tree.links.new(node_transparent.outputs[0], node_mixshader.inputs[1])\n tree.links.new(node_diffuse.outputs[0], node_mixshader.inputs[2])\n tree.links.new(node_mixshader.outputs[0], node_output.inputs[0])\n\n for node in tree.nodes:\n node.select = False\n\n # sets the viewport color\n clay_mat.diffuse_color = clay_color_rgb\n \n elif renderengine == 'BLENDER_RENDER':\n clay_mat.diffuse_color = clay_color_rgb\n clay_mat.use_transparency = True\n clay_mat.alpha = clay_color_alpha\n\n previous_area = bpy.context.area.type\n bpy.context.area.type = 'VIEW_3D'\n previous_layers = tuple(scene.layers)\n\n # can't enter edit mode on objects on inactive layers\n scene.layers = (True,)*20\n\n for obj in scene.objects:\n if obj.select:\n # only enters edit mode on active object\n scene.objects.active = obj\n obj.data.materials.append(clay_mat)\n clay_index = obj.data.materials.find(clay_mat.name)\n obj.active_material_index = clay_index\n\n bpy.ops.object.mode_set(mode='EDIT')\n bpy.ops.mesh.select_all(action='SELECT')\n bpy.ops.object.material_slot_assign()\n bpy.ops.mesh.select_all(action='SELECT')\n bpy.ops.object.mode_set(mode='OBJECT')\n\n bpy.context.area.type = previous_area\n scene.layers = previous_layers\n\n return clay_mat","def _add_switch(self, switchdesc):\n # Check switch definition parameters\n switch_attributes = list(switchdesc.keys())\n if not set(switch_attributes).issubset(self.switch_attributes):\n raise ValueError(\n \"Switch definition: '{0}' defined in '{1}' is not supported. \"\n \"Supported switch parameters are '{2}'.\".format(\n json.dumps(switchdesc, indent=2), self._xmlfile,\n self.switch_attributes))\n for mandatory_parameter in self.switch_attributes[:2]:\n if mandatory_parameter not in switch_attributes:\n raise ValueError(\n \"A '{0}' parameter is required in switch definition: \"\n \"'{1}' defined in '{2}'.\".format(\n mandatory_parameter, json.dumps(switchdesc, indent=2),\n self._xmlfile))\n\n # Check the name of the switch is not already reserved\n switch_name = switchdesc[self.switch_attributes[0]][0]\n if switch_name in self._switches:\n raise ValueError(\n \"The switch name '{0}' defined in '{1}' is \"\n \"already used.\".format(switch_name, self._xmlfile))\n\n # Create the switch control\n switch_paths = {}\n for pathdesc in switchdesc[self.switch_attributes[1]]:\n path_name = pathdesc[self.switch_path[0]][0]\n path_boxes = [box[self.unit_attributes[0]]\n for box in pathdesc[self.switch_path[1]]]\n switch_paths[path_name] = path_boxes\n switch_keys = list(switch_paths.keys())\n control = controls[\"Enum\"](\n choices=tuple(switch_keys),\n switch_name=switch_name,\n desc=(\"Switch between paths '{0}:{1}' defined in pipeline '{2}'\"\n \".\".format(switch_name, \"-\".join(switch_keys), self.id)))\n setattr(self.inputs, switch_name, control)\n self._switches[switch_name] = switch_paths\n control.add_observer(\"value\", self._update_activation)\n control.value = switch_keys[0]","def test_add(self):\n qc_cal = QuantumCircuit(2)\n qc_cal.rzx(0.5, 0, 1)\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\n\n qc = QuantumCircuit(2) & qc_cal\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\n\n qc = qc_cal & QuantumCircuit(2)\n\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\"test\")})\n self.assertEqual(qc_cal.calibrations, qc.calibrations)","def add_control(operation, num_ctrl_qubits, label):\n if isinstance(operation, UnitaryGate):\n # attempt decomposition\n operation._define()\n if _control_definition_known(operation, num_ctrl_qubits):\n return _control_predefined(operation, num_ctrl_qubits)\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)","def BVC(self, value):\n if not self.reg.V:\n self.reg.PC += value","def incr_registers(self):\n pass","def build_scl(net, ovs, src, dst, next_hop, match=None):\n info(\"### Build service classifier, source:{}, next_hop:{}\\n\".format(src,\n next_hop))\n in_port = get_ofport(\"{}-{}\".format(ovs, src))\n out_port = get_ofport(\"{}-{}\".format(ovs, next_hop))\n ip_dst = net[dst].IP()\n check_output(\n split(\n \"sudo ovs-ofctl add-flow {sw} \\\"nw_dst={ip_dst},icmp,in_port={in_port},actions=output={out_port}\\\"\".format(\n **{\"sw\": ovs, \"in_port\": in_port, \"out_port\": out_port,\n \"ip_dst\": ip_dst}\n )\n )\n )\n ret = check_output(split(\"sudo ovs-ofctl dump-flows {}\".format(ovs)))\n info(\"### Flow table of the switch after adding SFP:\\n\")\n print(ret)","def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self","def parameterise_gate(self, gate:Union[cirq.Gate, Callable]): \n if isinstance(gate, cirq.Gate):\n if isinstance(gate, (cirq.XXPowGate, cirq.YYPowGate, cirq.ZZPowGate)):\n param = self.new_param()\n return gate**param\n return gate\n elif isclass(gate) and issubclass(gate, cirq.Gate):\n parameters = ParameterisedCircuit._get_gate_parameters(gate)\n n_param = len(parameters)\n params = self.new_param(size=n_param, as_array=True)\n kwargs = {parameters[i]:params[i] for i in range(n_param)}\n return gate(**kwargs) \n else:\n n_param = ParameterisedCircuit._get_parameter_count(gate)\n params = self.new_param(size=n_param)\n params = tuple(params) if isinstance(params, np.ndarray) else (params,) \n return gate(*params)","def sincshift2d(image, dx, dy, sincrad=10, dampfac=3.25):\n s = np.arange(-sincrad, sincrad+1.0)\n sincx = _sincfunc(s, -dx, dampfac=dampfac)\n sincy = _sincfunc(s, -dy, dampfac=dampfac)\n kernel = np.outer(sincy, sincx)\n newimage = convolve2d(image, kernel, mode='same')\n return newimage","def add_switch(self, dpid):\n\t\tself.switches.append(dpid)","def __init__(self, input, output) :\n Gate.__init__(self, [input], output)","def __init__(self, input0, input1, output) :\n Gate.__init__(self, [input0,input1], output)","def ff_add(a, b):\n return a ^ b","def inc(self, params):\n reg = params[0]\n if self.reg_dct[reg] == (2 ** 32) - 1:\n self.reg_dct[reg] = 0\n else:\n self.reg_dct[reg] += 1","def _add_splines(c, b1, d, b2):\n if b1 == S.Zero or c == S.Zero:\n rv = piecewise_fold(d * b2)\n elif b2 == S.Zero or d == S.Zero:\n rv = piecewise_fold(c * b1)\n else:\n new_args = []\n n_intervals = len(b1.args)\n # Just combining the Piecewise without any fancy optimization\n p1 = piecewise_fold(c * b1)\n p2 = piecewise_fold(d * b2)\n\n # Search all Piecewise arguments except (0, True)\n p2args = list(p2.args[:-1])\n\n # This merging algorithm assumes the conditions in\n # p1 and p2 are sorted\n for arg in p1.args[:-1]:\n # Conditional of Piecewise are And objects\n # the args of the And object is a tuple of two\n # Relational objects the numerical value is in the .rhs\n # of the Relational object\n expr = arg.expr\n cond = arg.cond\n\n lower = cond.args[0].rhs\n\n # Check p2 for matching conditions that can be merged\n for i, arg2 in enumerate(p2args):\n expr2 = arg2.expr\n cond2 = arg2.cond\n\n lower_2 = cond2.args[0].rhs\n upper_2 = cond2.args[1].rhs\n\n if cond2 == cond:\n # Conditions match, join expressions\n expr += expr2\n # Remove matching element\n del p2args[i]\n # No need to check the rest\n break\n elif lower_2 < lower and upper_2 <= lower:\n # Check if arg2 condition smaller than arg1,\n # add to new_args by itself (no match expected\n # in p1)\n new_args.append(arg2)\n del p2args[i]\n break\n\n # Checked all, add expr and cond\n new_args.append((expr, cond))\n\n # Add remaining items from p2args\n new_args.extend(p2args)\n\n # Add final (0, True)\n new_args.append((0, True))\n\n rv = Piecewise(*new_args)\n\n return rv.expand()","def __init__(self, incoming, n_units, W_ci, W_ig, W_og, W_fg,\n b_ci=tf.zeros, b_ig=tf.zeros, b_og=tf.zeros, b_fg=tf.zeros,\n a_ci=tf.tanh, a_ig=tf.sigmoid, a_og=tf.sigmoid, a_fg=tf.sigmoid, a_out=tf.nn.elu,\n c_init=tf.zeros, h_init=tf.zeros, learn_c_init=False, learn_h_init=False, forgetgate=True, comb='add',\n store_states=False, return_states=False, output_dropout=False, precomp_fwds=True, W_red_rec=None,\n a_reduce_recurrents=None, tickerstep_biases=None, learn_tickerstep_biases=True,\n dilation_rate=(1, 1), name='ConvLSTMLayer'):\n super(ConvLSTMLayer, self).__init__()\n with tf.variable_scope(name) as self.layer_scope:\n self.incoming, self.incoming_shape = get_input(incoming)\n self.n_units = n_units\n self.lstm_inlets = ['ci', 'ig', 'og', 'fg']\n if return_states:\n store_states = True\n \n #\n # Initialize weights and biases\n #\n \n # Turn W inits into lists [forward_pass, backward_pass]\n W_ci, W_ig, W_og, W_fg = [v[:2] if isinstance(v, list) else [v, v] for v in [W_ci, W_ig, W_og, W_fg]]\n \n # Check if feature dimensions to produce agree for all weight windows with n_units\n W_dims = [[w[0].get_shape().as_list()[3], w[1].get_shape().as_list()[3]] for w in [W_ci, W_ig, W_og, W_fg]]\n W_dims = np.array(W_dims).flatten()\n if np.any(W_dims != n_units):\n raise ValueError(\"Feature dimensions to produce must agree with n_units!\")\n \n # TODO: make all gates optional (list with keys and function for splitting)\n if not forgetgate:\n def a_fg(x):\n return tf.ones(x.get_shape().as_list())\n \n # Make W and b tf variables\n W_ci, W_ig, W_og, W_fg = [[tofov(w, shape=None, var_params=dict(name=n + suffix)) for w, suffix in\n zip(v, ['_fwd', '_bwd'])] for v, n in\n zip([W_ci, W_ig, W_og, W_fg], ['W_ci', 'W_ig', 'W_og', 'W_fg'])]\n b_ci, b_ig, b_og, b_fg = [tofov(b, shape=[n_units], var_params=dict(name=n)) for b, n in\n zip([b_ci, b_ig, b_og, b_fg], ['b_ci', 'b_ig', 'b_og', 'b_fg'])]\n \n # Pack weights for fwd and bwd connections by concatenating them at sliding mask feature dimension\n # TODO: enable parallel calculation on multi-gpu\n W_fwd_conc = tf.concat(axis=3, values=[W[0] for W in [W_ci, W_ig, W_og, W_fg]], name='W_fwd_conc')\n W_bwd_conc = tf.concat(axis=3, values=[W[1] for W in [W_ci, W_ig, W_og, W_fg]], name='W_bwd_conc')\n \n # Initialize kernel for reducing recurrent features\n self.reduce_recurrents = None\n self.W_red_rec = W_red_rec\n if a_reduce_recurrents is not None:\n self.W_red_rec = tofov(W_red_rec, var_params=dict(name='W_red_rec'))\n \n def reduce_recurrents(h_prev):\n \"\"\"Reduces features of internal recurrent connections h_prev\"\"\"\n return a_reduce_recurrents(conv2d(h_prev, self.W_red_rec))\n \n self.reduce_recurrents = reduce_recurrents\n \n # Initialize bias for tickersteps\n if tickerstep_biases is not None:\n self.W_tickers = OrderedDict(zip_longest(self.lstm_inlets,\n [tofov(tickerstep_biases, shape=[n_units],\n var_params=dict(name='W_tickers_' + g,\n trainable=learn_tickerstep_biases))\n for g in self.lstm_inlets]))\n else:\n self.W_tickers = None\n \n #\n # Create mask for output dropout\n # apply dropout to n_units dimension of outputs, keeping dropout mask the same for all samples,\n # sequence positions, and pixel coordinates\n #\n output_shape = self.get_output_shape()\n if output_dropout:\n out_do_mask = tf.ones(shape=[output_shape[0], output_shape[2], output_shape[3], output_shape[4]],\n dtype=tf.float32, name='out_do_mask')\n out_do_mask = tf.nn.dropout(out_do_mask, keep_prob=1. - output_dropout,\n noise_shape=[1, 1, 1, output_shape[4]])\n \n def out_do(x):\n \"\"\"Function for applying dropout mask to outputs\"\"\"\n if output_dropout:\n return out_do_mask * x\n else:\n return x\n \n # Redefine a_out to include dropout (sneaky, sneaky)\n a_out_nodropout = a_out\n \n def a_out(x):\n return a_out_nodropout(out_do(x))\n \n #\n # Handle initializations for h (outputs) and c (cell states) as Variable if overwriteable or tensor if not\n # shape=(samples, x, y, n_units)\n #\n h_init = out_do(tofov(h_init, shape=[output_shape[0], output_shape[2], output_shape[3], output_shape[4]],\n var_params=dict(trainable=learn_h_init)))\n c_init = tofov(c_init, shape=[output_shape[0], output_shape[2], output_shape[3], output_shape[4]],\n var_params=dict(trainable=learn_c_init))\n \n # Initialize lists to store LSTM activations and cell states\n h = [h_init] # [-1, x, y, n_units]\n c = [c_init] # [-1, x, y, n_units]\n \n self.precomp_fwds = precomp_fwds\n self.store_states = store_states\n self.return_states = return_states\n \n self.W_fwd = OrderedDict(zip(self.lstm_inlets, [W[0] for W in [W_ci, W_ig, W_og, W_fg]]))\n self.W_bwd = OrderedDict(zip(self.lstm_inlets, [W[1] for W in [W_ci, W_ig, W_og, W_fg]]))\n \n self.W_fwd_conc = W_fwd_conc\n self.W_bwd_conc = W_bwd_conc\n self.a = OrderedDict(ci=a_ci, ig=a_ig, og=a_og, fg=a_fg, out=a_out)\n self.b = OrderedDict(ci=b_ci, ig=b_ig, og=b_og, fg=b_fg)\n self.h = h\n self.c = c\n self.comb = comb\n self.max_seq_len = None\n self.external_rec = None\n \n self.dilation_rate = dilation_rate\n \n self.out = tf.expand_dims(h_init, 1)\n self.name = name","def wave_add_new():\n return _u2i(_pigpio_command(_control, _PI_CMD_WVNEW, 0, 0))","def add(self, params):\n if len(params) < 2:\n return\n x = self.reg_dct[params[0]]\n y = self.reg_dct[params[1]]\n self.reg_dct[params[0]] = (x + y) % (2** 32)"],"string":"[\n \"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToCircuit == None:\\n return None\\n\\n gate = self._gatesToCircuit[gate.qasm()]\\n \\n circuit = circuit.copy()\\n\\n if cregs == None:\\n cregs = _makeCregsCircuit(circuit,len(qregs[0]),gate[0].num_clbits,name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasCircuit(circuit,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits > 0:\\n circuit = circuit.compose(gate[0], qbits[i], cregs[i])\\n else:\\n circuit = circuit.compose(gate[0], qbits[i])\\n\\n return circuit\",\n \"def test_append_two_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"CNOT\\\")\\n circuit.append_gate(gate, wire_ids=[2, 3])\\n assert gate.indices == [\\\"2-1\\\", \\\"3-1\\\", \\\"2-0\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [2, 3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=1, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def cs(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def circuitSat(C):\",\n \"def cy(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def ccx(self, ctl1, ctl2, tgt):\\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])\",\n \"def test_append_one_wire_gate(self, circuit):\\n gate = jet.GateFactory.create(\\\"H\\\")\\n circuit.append_gate(gate, wire_ids=[3])\\n assert gate.indices == [\\\"3-1\\\", \\\"3-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=False),\\n jet.Wire(1, depth=0, closed=False),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=1, closed=False),\\n ]\",\n \"def cs_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def crz(self, theta, ctl, tgt):\\n return self.append(CrzGate(theta), [ctl, tgt], [])\",\n \"def welding_state_add(self, ws1, ws2):\\n\\n if ws2 is None:\\n return ws1\\n\\n if ws2.amperage is not None:\\n ws1.amperage += ws2.amperage\\n\\n if ws2.voltage is not None:\\n ws1.voltage += ws2.voltage\\n\\n if ws2.filler_speed is not None:\\n ws1.filler_speed += ws2.filler_speed\\n\\n if ws2.default_arc_length is not None:\\n ws1.default_arc_length += ws2.default_arc_length\\n\\n if ws2.mode is not None:\\n ws1.mode = ws2.mode\\n\\n if ws2.speed is not None:\\n ws1.speed += ws2.speed\\n\\n return ws1\",\n \"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.cz(register[1], register[0])\\n qc.x(register[0])\",\n \"def ct(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def BCS(self, value):\\n if self.reg.C:\\n self.reg.PC += value\",\n \"def _update_sym_const(self,name,G1,remove_nodes,new_inst, const_list):\\n logger.debug(f\\\"updating symmetry block constraints of subcircuit {name}, nodes: {remove_nodes}, new name: {new_inst}\\\")\\n if self._if_const(name):\\n for const in const_list:\\n if hasattr(const, 'pairs'):\\n for pair in const.pairs:\\n if len(pair) == 2:\\n if pair[0] in remove_nodes and pair[1] in remove_nodes:\\n pair[0] = new_inst\\n pair.pop()\\n logger.debug(f\\\"updated symmetric pair constraint to self symmetry:{const}\\\")\\n elif pair[0] in remove_nodes and pair[1] not in remove_nodes:\\n pair[0] = new_inst\\n elif pair[1] in remove_nodes and pair[0] not in remove_nodes:\\n pair[1] = new_inst\\n elif len(pair) == 1:\\n if pair[0] in remove_nodes:\\n pair[0] = new_inst\\n logger.debug(f\\\"updated symmetric pair constraint to self symmetry:{const}\\\")\",\n \"def add_connector(self):\\n \\n no = len(self.connectors)\\n state = {}\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % no\\n \\n if len(self.connectors)>0:\\n state = self.connectors[-1].get_state()\\n state[\\\"s_pin\\\"] = no\\n state[\\\"p_pin\\\"] = no\\n state[\\\"s_label\\\"] = \\\"C%d\\\" % (no)\\n else:\\n if self.mount == self.MOUNT_THT:\\n state[\\\"p_shape\\\"] = Con.SHAPE_HOLE\\n elif self.mount == self.MOUNT_SMD:\\n state[\\\"p_shape\\\"] = Con.SHAPE_PAD\\n \\n c = Con(no)\\n c.set_state(state) \\n \\n self.sch_layers[\\\"pins\\\"].add(c.s_svg)\\n self.pcb_layers[\\\"copper1\\\"].add(c.p_svg)\\n self.connectors.append(c)\",\n \"def cox_cc_loss_single_ctrl(g_case: Tensor, g_control: Tensor, shrink: float = 0.) -> Tensor:\\n loss = F.softplus(g_control - g_case).mean()\\n if shrink != 0:\\n loss += shrink * (g_case.abs().mean() + g_control.abs().mean())\\n return loss\",\n \"def convert_swish(g, op, block):\\n\\n x = g.get_node(op.input(\\\"X\\\")[0])\\n beta = op.attr(\\\"beta\\\")\\n assert beta == 1.0, \\\"Only support beta==1.0 for PaddlePaddle's swish\\\"\\n out = x * _op.tensor.sigmoid(x)\\n g.add_node(op.output(\\\"Out\\\")[0], out)\",\n \"def cx(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def local_addsd_ccode(node):\\r\\n if isinstance(node.op, sparse.AddSD) and theano.config.cxx:\\r\\n new_node = AddSD_ccode(format=node.inputs[0].type.format)(*node.inputs)\\r\\n return [new_node]\\r\\n return False\",\n \"def test_scalar_coeff_cc():\\n hs_1 = LocalSpace('q1', basis=('g', 'e'))\\n hs_2 = LocalSpace('q2', basis=('g', 'e'))\\n kappa = Symbol('kappa', real=True)\\n a1 = Destroy(hs=hs_1)\\n a2 = Destroy(hs=hs_2)\\n\\n jc_expr = (\\n I / 2 * (2 * kappa * (a1.dag() * a2) - 2 * kappa * (a1 * a2.dag()))\\n )\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == I * kappa * OperatorPlusMinusCC(\\n a1.dag() * a2, sign=-1\\n )\\n expanded = simplified.doit()\\n assert expanded == I * kappa * (a1.dag() * a2 - a1 * a2.dag())\",\n \"def add(self, y):\\n return circuit.add(self, y)\",\n \"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\\n if self._gates == None or self._gatesToDag == None:\\n return None\\n \\n gate = self._gatesToDag[gate.qasm()]\\n\\n if cregs == None:\\n cregs = _makeCregsDag(dag,len(qregs[0]),gate[0].num_clbits(),name=\\\"classical\\\")\\n \\n if ancillas == None:\\n ancillas = _makeAncillasDag(dag,len(qregs[0]),gate[1])\\n \\n qbits = _combineQregsAncillas(qregs,ancillas,singleQbit=False)\\n\\n for i in range(len(qbits)):\\n if gate[0].num_clbits() > 0:\\n dag.compose(gate[0], qubits = qbits[i], clbits = cregs[i])\\n else:\\n dag.compose(gate[0], qubits = qbits[i])\\n\\n return dag\",\n \"def add(num1, num2, Cin):\\n Cin=0\\n l2=[]\\n final=\\\"\\\"\\n\\n \\\"\\\"\\\"Using for loop for starting addition from the last indexed number\\\"\\\"\\\"\\n for i in range(len(num1)-1,-1,-1):\\n bit1=num1[i]#storing each indexed() value of num1 in bit1\\n bit2=num2[i]#storing each indexed() value of num2 in bit2\\n S1=g.XOR(bit1, bit2)#calling XOR() method of gates module and passing value in it.\\n S2=g.NAND(S1, Cin)#calling NAND() method of gates module and passing value in it.\\n S3=g.OR(S1, Cin)#calling OR() method of gates module and passing value in it.\\n SUM=g.AND(S2, S3)#calling AND() method of gates module and passing value in it.\\n C1=g.AND(bit1, bit2)#calling AND() method of gates module and passing value in it.\\n C2=g.AND(S1, Cin)#calling AND() method of gates module and passing value in it.\\n C3=g.NOR(C1, C2)#calling NOR() method of gates module and passing value in it.\\n Cout=g.NOT(C3)#calling NOT() method of gates module and passing value in it.\\n Cin=Cout#declaring cout as cin for next bit addition\\n l2.append(SUM)#adding SUM to l2\\n l3=l2[::-1]##reversing the value of l2\\n final+=str(l2[-1])#converting the list value to string\\n final1=final[::-1]#reversing string value\\n return final1 #returning the binary addition as string\",\n \"def __le__(self, *args):\\n return _ida_hexrays.cswitch_t___le__(self, *args)\",\n \"def apply_gate_operation(self, operation:[str, cirq.Gate], qubit_expr, params:Optional[Dict]=None):\\n gate_ops = self.get_gate_operation(operation, qubit_expr, params)\\n strategy = self.insert_strategy\\n self.append(gate_ops, strategy=strategy)\",\n \"def local_inplace_addsd_ccode(node):\\r\\n if isinstance(node.op, sparse.AddSD) and theano.config.cxx:\\r\\n out_dtype = scalar.upcast(*node.inputs)\\r\\n if out_dtype != node.inputs[1].dtype:\\r\\n return\\r\\n new_node = AddSD_ccode(format=node.inputs[0].type.format,\\r\\n inplace=True)(*node.inputs)\\r\\n return [new_node]\\r\\n return False\",\n \"def add_junction(ccTremb):\\n pass\",\n \"def ct_dg(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def cswap(control: QubitInput, target1: QubitInput, target2: QubitInput) -> Instruction:\\n return Instruction(CSwap(), target=[control, target1, target2])\",\n \"def __add__(self, tc): \\n tc = TwosComplement(tc)\\n bits = self.len if self.len > tc.len else tc.len \\n result = self.int + tc.int\\n return TwosComplement(result, bits)\",\n \"def enc_add_const(pub, m, c):\\n # Similiar to enc add\\n add_const_result = m * powmod(pub.g, c, pub.n_sq) % pub.n_sq\\n return add_const_result\",\n \"def s_dg(self, q0, ctrl=None):\\n self.__add_quantum_gate(kind=PHASE_SHIFT_S_, qid=[q0], ctrl=ctrl)\\n return self\",\n \"def _write_circuit(self, feature_vector_index):\\n # grab the feature vector\\n feature_vector = self.data.data[feature_vector_index]\\n\\n # compute the indices to put gates at\\n inds = [x for x in range(len(feature_vector)) if feature_vector[x] == 1]\\n\\n # write the circuit\\n self.circuits[feature_vector_index].add_layer(H)\\n self.circuits[feature_vector_index].add_at(Z, inds)\\n\\n # TODO: all encoding classes will need this method.\\n # TODO: make a BaseEncoding that implements this\",\n \"def recursive_gate(e):\\n if isinstance(e, boolean.BaseElement):\\n # TODO: Either make the the same or create a constant component.\\n s = Switch()\\n b.append(s)\\n return s\\n elif isinstance(e, boolean.Symbol):\\n if e in symbol_dict.keys():\\n return symbol_dict[e]\\n else:\\n s = Switch()\\n symbol_dict[e] = s\\n b.append(s)\\n return s\\n elif isinstance(e, boolean.Function):\\n # All gates are of type Gate instead of And, Or and Not\\n if e.order == (1, 1):\\n pre = recursive_gate(e.args[0])\\n w = Wire(pre)\\n b.append(w)\\n\\n s = boolean.Symbol(None)\\n g = Gate(e.subs({e.args[0]: s}),\\n {s: w})\\n b.append(g)\\n return g\\n else:\\n input_dict = {}\\n expr = e\\n for arg in e.args:\\n pre = recursive_gate(arg)\\n w = Wire(pre)\\n b.append(w)\\n\\n s = boolean.Symbol(None)\\n expr = expr.subs({arg: s})\\n input_dict[s] = w\\n g = Gate(expr,\\n input_dict)\\n b.append(g)\\n return g\",\n \"def coadd(self, step_index):\\n if self.drip_config is not None:\\n if ('boresight' in self.drip_cal_config\\n and 'SLIT' in self.drip_cal_config['boresight']):\\n self.current[step_index].set_value('skip_coadd', True)\",\n \"def enable_cl1_direct(self):\\n self.write_versa5(0x17,0x02) ## Change top multiplier to 0x22\\n self.write_versa5(0x18,0x20)\\n self.write_versa5(0x10,0xc0) ## Enable xtal and clock\\n self.write_versa5(0x13,0x03) ## Switch to clock\\n self.write_versa5(0x10,0x44) ## Enable clock input only and refmode\\n self.write_versa5(0x21,0x0c) ## Use previous channel, direct input, may have skew\",\n \"def apply_const_shift_operator(model, operator):\\n for term in operator:\\n dif = take_derivative_shift_op(model, term)\\n try:\\n total += dif\\n except NameError:\\n total = dif\\n return total\",\n \"def cg_apply_ws(A, B, w0, w1, w2, w3, pars):\\n # We manually loop over one of the legs to lower the memory cost.\\n vects = []\\n # Generate the vectors to sum over in this manual loop,\\n # for non-symmetric tensors:\\n if A.qhape is None:\\n dim = A.shape[5]\\n for j in range(dim):\\n vect = type(A).zeros([dim])\\n vect[j] = 1.\\n vects.append(vect)\\n # and for symmetric tensors:\\n else:\\n qim = A.qhape[5]\\n dim = A.shape[5]\\n direction = A.dirs[5]\\n for i, q in enumerate(qim):\\n qdim = dim[i]\\n for j in range(qdim):\\n vect = type(A).zeros([dim], qhape=[qim], dirs=[-direction],\\n charge=-direction*q, invar=True)\\n vect[(q,)][j] = 1.\\n vects.append(vect)\\n # Compute the networks with the middle leg replaced with\\n # vect \\\\otimes vect, and sum them all up.\\n result = None\\n for vect in vects:\\n Ared = ncon((A, vect), ([-1,-2,-3,-4,-5,6], [6]))\\n Bred = ncon((B, vect.conjugate()), ([-1,-2,-3,-4,5,-6], [5]))\\n term = ncon((Ared, Bred,\\n w0, w1, w2, w3),\\n ([1,2,11,12,-5], [13,14,3,4,-6],\\n [-1,1,13], [-2,2,14], [-3,11,3], [-4,12,4]))\\n if result is None:\\n result = term\\n else:\\n result += term\\n return result\",\n \"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\\n if len(list(register)) != 2:\\n raise ValueError(f\\\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\\\")\\n\\n qc.x(register[0])\\n qc.ccx(register[1], register[0], ancilla)\\n qc.x(register[0])\",\n \"def cz(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def connect(self, gate) :\\n self.notifyList.append(gate)\",\n \"def BCC(self, value):\\n if not self.reg.C:\\n self.reg.PC += value\",\n \"def inc_xor_gateways(self):\\r\\n self.num_xor_gateways += 1\",\n \"def _control_predefined(operation, num_ctrl_qubits):\\n if operation.name == 'x' and num_ctrl_qubits in [1, 2]:\\n if num_ctrl_qubits == 1:\\n import qiskit.extensions.standard.cx\\n cgate = qiskit.extensions.standard.cx.CnotGate()\\n else:\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n elif operation.name == 'y':\\n import qiskit.extensions.standard.cy\\n cgate = qiskit.extensions.standard.cy.CyGate()\\n elif operation.name == 'z':\\n import qiskit.extensions.standard.cz\\n cgate = qiskit.extensions.standard.cz.CzGate()\\n elif operation.name == 'h':\\n import qiskit.extensions.standard.ch\\n cgate = qiskit.extensions.standard.ch.CHGate()\\n elif operation.name in {'rx', 'ry', 'rz'}:\\n if operation.name == 'rx':\\n import qiskit.extensions.standard.crx\\n cgate = qiskit.extensions.standard.crx.CrxGate(*operation.params)\\n elif operation.name == 'ry':\\n import qiskit.extensions.standard.cry\\n cgate = qiskit.extensions.standard.cry.CryGate(*operation.params)\\n else: # operation.name == 'rz'\\n import qiskit.extensions.standard.crz\\n cgate = qiskit.extensions.standard.crz.CrzGate(*operation.params)\\n if num_ctrl_qubits == 1:\\n return cgate\\n else:\\n # only predefined for one control qubit\\n return cgate.control(num_ctrl_qubits - 1)\\n elif operation.name == 'swap':\\n import qiskit.extensions.standard.cswap\\n cgate = qiskit.extensions.standard.cswap.FredkinGate()\\n elif operation.name == 'u1':\\n import qiskit.extensions.standard.cu1\\n cgate = qiskit.extensions.standard.cu1.Cu1Gate(*operation.params)\\n elif operation.name == 'u3':\\n import qiskit.extensions.standard.cu3\\n cgate = qiskit.extensions.standard.cu3.Cu3Gate(*operation.params)\\n elif operation.name == 'cx':\\n import qiskit.extensions.standard.ccx\\n cgate = qiskit.extensions.standard.ccx.ToffoliGate()\\n else:\\n raise QiskitError('No standard controlled gate for \\\"{}\\\"'.format(\\n operation.name))\\n return cgate\",\n \"def gate(self):\\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)\",\n \"def test_add_gate(self):\\n sched = Schedule()\\n sched.append(Play(Waveform(np.ones(5)), DriveChannel(0)))\\n inst_map = InstructionScheduleMap()\\n\\n inst_map.add(U1Gate(0), 1, sched)\\n inst_map.add(U1Gate(0), 0, sched)\\n\\n self.assertIn(\\\"u1\\\", inst_map.instructions)\\n self.assertEqual(inst_map.qubits_with_instruction(U1Gate(0)), [0, 1])\\n self.assertTrue(\\\"u1\\\" in inst_map.qubit_instructions(0))\\n\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), (), sched)\\n with self.assertRaises(PulseError):\\n inst_map.add(U1Gate(0), 1, \\\"not a schedule\\\")\",\n \"def alg(c):\\n return c[0]*G[0] + c[1]*G[1] + c[2]*G[2]\",\n \"def SO4_circuit(a_alpha, a_theta, a_beta, b_alpha, b_theta, b_beta):\\n # return np.kron(S1_inv, I2) @ np.kron(I2, S1_inv) @ np.kron(I2, R1_inv) @ CNOT2 \\\\\\n # @ np.kron(I2, R_z(b_beta)) @ np.kron(I2, R_y(b_theta)) @ np.kron(I2, R_z(b_alpha)) \\\\\\n # @ np.kron(R_z(a_beta), I2) @ np.kron(R_y(a_theta), I2) @ np.kron(R_z(a_alpha), I2) \\\\\\n # @ CNOT2 @ np.kron(I2, R1) @ np.kron(I2, S1) @ np.kron(S1, I2)\\n\\n return np.linalg.inv(magic_gate) \\\\\\n @ np.kron(I2, R_z(b_beta)) @ np.kron(I2, R_y(b_theta)) @ np.kron(I2, R_z(b_alpha)) \\\\\\n @ np.kron(R_z(a_beta), I2) @ np.kron(R_y(a_theta), I2) @ np.kron(R_z(a_alpha), I2) \\\\\\n @ magic_gate\",\n \"def update_control(self):\\n self._control_ctr += 0x01\",\n \"def fc_forward(x, w, b):\\n out = None\\n ###########################################################################\\n # TODO: Implement the forward pass. Store the result in out. #\\n ###########################################################################\\n out = np.dot(x, w) + b\\n ###########################################################################\\n # END OF YOUR CODE #\\n ###########################################################################\\n cache = (x, w, b)\\n return out, cache\",\n \"def circuit():\\n np.random.seed(1967)\\n for gates in gates_per_layers:\\n for gate in gates:\\n qml.apply(gate)\\n return qml.expval(qml.PauliZ(0))\",\n \"def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\\n return self\",\n \"def add_bcs(self, RHS, bc_left, cff0 ,cff1, cff2):\\n RHS[0] += cff0 * self.c[0]/(2*self.dx)*bc_left\\n RHS[0] += cff1 * self.c[0]/(2*self.dx)*self.bcs[1]\\n RHS[0] += cff2 * self.c[0]/(2*self.dx)*self.bcs[2]\",\n \"def _add_switchs(self):\\r\\n lst = self.model.get_all_switch()\\r\\n\\r\\n for itm in lst:\\r\\n self._add_switch(itm)\",\n \"def addOp(self, op):\\n self.operations << op\",\n \"def test_append_two_wire_state(self, circuit):\\n state = jet.QubitRegister(size=2)\\n circuit.append_state(state, wire_ids=[0, 1])\\n assert state.indices == [\\\"0-0\\\", \\\"1-0\\\"]\\n assert list(circuit.operations)[-1] == jet.Operation(state, [0, 1])\\n assert list(circuit.wires) == [\\n jet.Wire(0, depth=0, closed=True),\\n jet.Wire(1, depth=0, closed=True),\\n jet.Wire(2, depth=0, closed=False),\\n jet.Wire(3, depth=0, closed=False),\\n ]\",\n \"def fc_forward(x, w, b):\\n out = None\\n ###########################################################################\\n # TODO: Implement the forward pass. Store the result in out. #\\n ###########################################################################\\n out = np.matmul(x, w)\\n out += b\\n ###########################################################################\\n # END OF YOUR CODE #\\n ###########################################################################\\n cache = (x, w, b)\\n return out, cache\",\n \"def add_state(self, name='Ti', c=2000):\\n assert isinstance(name, str), 'name must be a string type'\\n if name in self.sta.keys():\\n raise Exception('State already defined')\\n state = State(c=c, name=name)\\n self.sta[name] = state\\n self.nodes[name] = state\\n self.rc.add_node(state)\",\n \"def iadd(state: State) -> State:\\n cell = state.array[state.index] or 0\\n return state._replace(acc=state.acc + cell)\",\n \"def add_gate(self, gate, q_args=None, c_args=None, params=None, mapping=None):\\n if q_args is None and c_args is None:\\n raise GateError(\\\"Gate needs at least one quantum argument or classical argument\\\")\\n if isinstance(gate, CompositeGate):\\n if mapping is None:\\n raise GateError(\\\"Must provide arguments mapping for composite gate inside a composite gate.\\\")\\n else:\\n inv_mappimg = dict()\\n for key, value in mapping.items():\\n inv_mappimg[value] = key\\n if gate is self:\\n gates = gate.copy.gates\\n else:\\n gates = gate.gates\\n for g in gates:\\n new_q_args = None\\n new_c_args = None\\n if g[1] is not None:\\n new_q_args = [inv_mappimg[q_arg] for q_arg in g[1]]\\n if g[2] is not None:\\n new_q_args = [inv_mappimg[c_arg] for c_arg in g[2]]\\n self.add_gate(gate=g[0], q_args=new_q_args,\\n c_args=new_c_args, params=g[3])\\n else:\\n if gate not in ['id', 'x', 'y', 'z', 'rx', 'ry', 'rz', 'h', 'cx', 'barrier', 'measure']:\\n raise GateError(\\\"Gate must be either a CompositeGate or a string from: \\\"\\n \\\"[id, x, y, z, rx, ry, rz, h, cx, barrier, measure]\\\")\\n if q_args is not None:\\n for q_arg in q_args:\\n if q_arg not in self.q_args:\\n self.add_q_arg(q_arg)\\n if c_args is not None:\\n for c_arg in c_args:\\n if c_arg not in self.c_args:\\n self.add_c_arg(c_arg)\\n if params is not None:\\n for param in params:\\n if param not in self.params:\\n self.add_param(param)\\n self._gates.append((gate, q_args, c_args, params))\",\n \"def add(self, sgid, other, proto_spec, direction=\\\"in\\\"):\\n # returns bool\\n # AuthorizeSecurityGroupIngress, AuthorizeSecurityGroupEgress\\n if direction == \\\"in\\\":\\n api = \\\"AuthorizeSecurityGroupIngress\\\"\\n elif direction == \\\"out\\\":\\n api = \\\"AuthorizeSecurityGroupEgress\\\"\\n else:\\n raise ValueError(\\\"direction must be one of ('in', 'out')\\\")\\n return self.modify(api, sgid, other, proto_spec)\",\n \"def gate_mfcc(recurrent_net, sample_input):\\n length = sample_input.shape[1]\\n score, select = np.zeros(length), np.zeros(length)\\n for i in range(length):\\n select[i], score[i] = recurrent_net.activate(sample_input[:, i])\\n select = sigmoid(select)\\n return np.sum(select * score) / np.sum(select)\",\n \"def brepalgo_ConcatenateWireC0(*args):\\n return _BRepAlgo.brepalgo_ConcatenateWireC0(*args)\",\n \"def ADD():\\n global pointer, memory, registers\\n registers[memory[pointer + 0x02]] += memory[pointer + 0x01]\\n pointer += 0x03\",\n \"def coupler_symmetric(\\n bend: Callable = bend_s,\\n gap: float = 0.234,\\n wg_width: float = 0.5,\\n layer: Tuple[int, int] = pp.LAYER.WG,\\n layers_cladding: List[Tuple[int, int]] = [pp.LAYER.WGCLAD],\\n cladding_offset: float = 3.0,\\n) -> Component:\\n bend = pp.call_if_func(\\n bend,\\n width=wg_width,\\n layer=layer,\\n layers_cladding=layers_cladding,\\n cladding_offset=cladding_offset,\\n pins=False,\\n )\\n\\n w = bend.ports[\\\"W0\\\"].width\\n y = (w + gap) / 2\\n\\n c = pp.Component()\\n top_bend = bend.ref(position=(0, y), port_id=\\\"W0\\\")\\n bottom_bend = bend.ref(position=(0, -y), port_id=\\\"W0\\\", v_mirror=True)\\n\\n c.add(top_bend)\\n c.add(bottom_bend)\\n\\n # Using absorb here to have a flat cell and avoid\\n # to have deeper hierarchy than needed\\n c.absorb(top_bend)\\n c.absorb(bottom_bend)\\n\\n port_width = 2 * w + gap\\n c.add_port(name=\\\"W0\\\", midpoint=[0, 0], width=port_width, orientation=180)\\n c.add_port(port=bottom_bend.ports[\\\"E0\\\"], name=\\\"E0\\\")\\n c.add_port(port=top_bend.ports[\\\"E0\\\"], name=\\\"E1\\\")\\n\\n return c\",\n \"def fully_connect(self, x, w, b, name=\\\"\\\"):\\n return tf.nn.relu(tf.matmul(x, w) + b, name=name)\",\n \"def __ge__(self, *args):\\n return _ida_hexrays.cswitch_t___ge__(self, *args)\",\n \"def ch(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_H, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def addToTfLink(G,i,j,siso):\\n m,n,r = np.shape(G.num)\\n dt = G.dt\\n\\n #Create a new transfer fuction Add, that is zero except the i,jth entry \\n Addnum = []\\n Addden = []\\n rowN = [np.array([0.])]*n\\n rowD = [np.array([1.])]*n\\n\\n for k in range(m):\\n Addnum.append(list(rowN))\\n Addden.append(list(rowD))\\n\\n #Make the i,jth entry of Add equal to siso\\n Addnum[i][j] = siso.num[0][0]\\n Addden[i][j] = siso.den[0][0]\\n Add = ctrl.tf(Addnum,Addden,dt)\\n\\n #Use the control library + function to add the new transfer function to G\\n Gplus = G + Add\\n return Gplus\",\n \"def addToTfLink(G,i,j,siso):\\n m,n,r = np.shape(G.num)\\n dt = G.dt\\n\\n #Create a new transfer fuction Add, that is zero except the i,jth entry \\n Addnum = []\\n Addden = []\\n rowN = [np.array([0.])]*n\\n rowD = [np.array([1.])]*n\\n\\n for k in range(m):\\n Addnum.append(list(rowN))\\n Addden.append(list(rowD))\\n\\n #Make the i,jth entry of Add equal to siso\\n Addnum[i][j] = siso.num[0][0]\\n Addden[i][j] = siso.den[0][0]\\n Add = ctrl.tf(Addnum,Addden,dt)\\n\\n #Use the control library + function to add the new transfer function to G\\n Gplus = G + Add\\n return Gplus\",\n \"def set_sw(self, phasecal, s12_value=None):\\n s12_value = 3 if s12_value is None else s12_value\\n # TBF: we'll have to look at the LO pickled data to\\n # determine the switches being used\\n\\n # switches = ifpath.get_lo_sw()\\n # for sw in switches:\\n # self.seq.add_param(self.mng_name, sw[0], sw[1])\\n # if sw[0] == \\\"S13\\\":\\n # s12_value = \\\"4\\\"\\n # self.seq.add_param(self.mng_name, \\\"S12\\\", str(s12_value))\\n\\n if phasecal in [\\\"on\\\"]:\\n self.seq.add_param(self.mng_name, \\\"S1\\\", \\\"cross\\\")\\n self.seq.add_param(self.mng_name, \\\"S11\\\", \\\"thru\\\")\\n self.seq.add_param(self.mng_name, \\\"S3\\\", \\\"4\\\")\\n self.seq.add_param(self.mng_name, \\\"phaseCalMode\\\", phasecal)\\n self.seq.add_param(self.mng_name, \\\"phaseCalCtl\\\", \\\"On\\\")\\n elif phasecal in [\\\"M1-disconnect\\\", \\\"M5-disconnect\\\"]:\\n self.seq.add_param(self.mng_name, \\\"S1\\\", \\\"cross\\\")\\n self.seq.add_param(self.mng_name, \\\"S11\\\", \\\"cross\\\")\\n self.seq.add_param(self.mng_name, \\\"S3\\\", \\\"4\\\")\\n self.seq.add_param(self.mng_name, \\\"phaseCalMode\\\", phasecal[0:2])\\n self.seq.add_param(self.mng_name, \\\"phaseCalCtl\\\", \\\"On\\\")\\n elif phasecal in [\\\"M1\\\", \\\"M5\\\"]:\\n self.seq.add_param(self.mng_name, \\\"S3\\\", \\\"4\\\")\\n self.seq.add_param(self.mng_name, \\\"S1\\\", \\\"cross\\\")\\n self.seq.add_param(self.mng_name, \\\"S11\\\", \\\"thru\\\")\\n self.seq.add_param(self.mng_name, \\\"phaseCalMode\\\", phasecal)\\n self.seq.add_param(self.mng_name, \\\"phaseCalCtl\\\", \\\"On\\\")\\n else:\\n self.seq.add_param(self.mng_name, \\\"S3\\\", \\\"3\\\")\\n self.seq.add_param(self.mng_name, \\\"S1\\\", \\\"cross\\\")\\n self.seq.add_param(self.mng_name, \\\"S11\\\", \\\"cross\\\")\\n self.seq.add_param(self.mng_name, \\\"phaseCalCtl\\\", \\\"Off\\\")\\n\\n if self.rcvr_name not in (\\\"Rcvr26_40\\\", \\\"RcvrArray18_26\\\", \\\"Rcvr68_92\\\"):\\n self.seq.add_param(self.mng_name, \\\"loConfig\\\", \\\"TrackA_BNotUsed\\\", 1)\\n self.seq.add_param(self.mng_name, \\\"testTonePowerLevel\\\", \\\"-110\\\", 4)\\n self.seq.add_param(self.mng_name, \\\"testToneFreq\\\", \\\"17000\\\", 1)\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self.components, other.components)]\\n return self\",\n \"def _cmplx_add_ ( s , o ) :\\n return o + complex ( s )\",\n \"def test_add_consistency1(self) -> None:\\n a = Constant(\\n 'const1',\\n Float32(),\\n np.zeros([1, 3, 3])\\n )\\n b = Constant(\\n 'const2',\\n Float32(),\\n np.zeros([3])\\n )\\n input_ops = {'A': cast(Operator, a), 'B': cast(Operator, b)}\\n Add(\\n 'add1',\\n [1, 3, 3],\\n Float32(),\\n input_ops\\n )\\n\\n print(\\\"Consistency test for 'Add' #1 passed!\\\")\",\n \"def test_simple_cc():\\n hs_c = LocalSpace('c', dimension=3)\\n hs_q = LocalSpace('q1', basis=('g', 'e'))\\n Delta_1 = Symbol('Delta_1')\\n Omega_1 = Symbol('Omega_1')\\n g_1 = Symbol('g_1')\\n a = Destroy(hs=hs_c)\\n a_dag = Create(hs=hs_c)\\n sig_p = LocalSigma('e', 'g', hs=hs_q)\\n sig_m = LocalSigma('g', 'e', hs=hs_q)\\n coeff = (-I / 2) * (Omega_1 * g_1 / Delta_1)\\n jc_expr = coeff * (a * sig_p - a_dag * sig_m)\\n\\n simplified = rewrite_with_operator_pm_cc(jc_expr)\\n assert simplified == coeff * OperatorPlusMinusCC(a * sig_p, sign=-1)\\n assert (\\n srepr(simplified.term)\\n == \\\"OperatorPlusMinusCC(OperatorTimes(Destroy(hs=LocalSpace('c', \\\"\\n \\\"dimension=3)), LocalSigma('e', 'g', hs=LocalSpace('q1', \\\"\\n \\\"basis=('g', 'e')))), sign=-1)\\\"\\n )\\n expanded = simplified.doit()\\n assert expanded == jc_expr\",\n \"def BVS(self, value):\\n if self.reg.V:\\n self.reg.PC += value\",\n \"def update_g_switches(self, sw_arr):\\n\\n if len(sw_arr) != 6:\\n raise Exception('CTC Recived Erronious Green Switch Array')\\n for i in range(len(sw_arr)):\\n if sw_arr[i]:\\n self.switches_green_arr[i].pointing_to = self.switches_green_arr[i].greater_block\\n else:\\n self.switches_green_arr[i].pointing_to = self.switches_green_arr[i].less_block\",\n \"def control(self, num_ctrl_qubits=1, label=None):\\n if num_ctrl_qubits == 1:\\n return CrzGate(self.params[0])\\n return super().control(num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def __iadd__(self, other):\\n self.components = [c1 + c2 for (c1, c2) in zip(self, other)]\\n return self\",\n \"def conv_block(inp, cweight, bweight):\\n conv = tf.nn.conv2d(inp, cweight, strides=[1, 1, 1, 1], padding='SAME')\\n conv = tf.nn.bias_add(conv, bweight)\\n relu = tf.nn.leaky_relu(conv)\\n return relu\",\n \"def add_layer(self, freeze = True, add = True):\\n if add:\\n self.num_layers += 1\\n if self.conv_dim == 1:\\n new_cnn = layers.Conv1D(self.n_filters,\\n (self.n_kernels),\\n activation='elu',\\n input_shape=(None, self.inp_shape[0], self.n_filters),\\n padding=\\\"same\\\",\\n name='cnn_1d_{}'.format(self.num_layers-1),\\n kernel_initializer = initializers.get(self.initializer),\\n bias_initializer=initializers.get(\\\"zeros\\\"),\\n kernel_regularizer=self.regularizer,\\n bias_regularizer=self.regularizer\\n )\\n elif self.conv_dim == 2:\\n new_cnn = layers.Conv2D(self.n_filters,\\n (self.n_kernels, self.n_kernels),\\n activation='elu',\\n input_shape=(None, self.inp_shape[0],self.inp_shape[1], self.n_filters),\\n padding=\\\"same\\\",\\n name='cnn_2d_{}'.format(self.num_layers-1),\\n kernel_initializer=initializers.get(self.initializer),\\n bias_initializer=initializers.get(\\\"zeros\\\"),\\n kernel_regularizer=self.regularizer,\\n bias_regularizer=self.regularizer\\n )\\n self.list_cnn.append(new_cnn)\\n\\n if freeze:\\n for index in range(0,self.num_layers-1):\\n self.list_cnn[index].trainable = False\\n else:\\n for index in range(0,self.num_layers-1):\\n self.list_cnn[index].trainable = True\",\n \"def add_clay_to_selected(self):\\n scene = self.set_as_active()\\n\\n # if the user selected a material, use it\\n if w_var.cb_mat_clay:\\n clay_mat = bpy.data.materials[w_var.mat_clay_name]\\n\\n # else, create a new one with the color selected\\n else:\\n clay_color = w_var.color_clay\\n\\n # separating rgb and alpha\\n clay_color_rgb = clay_color[0:3]\\n clay_color_alpha = clay_color[-1]\\n clay_mat = bpy.data.materials.new('clay')\\n \\n renderengine = scene.wirebomb.data_renderengine\\n \\n if renderengine == 'CYCLES':\\n clay_mat.use_nodes = True\\n tree = clay_mat.node_tree\\n tree.nodes.clear()\\n\\n # creating the nodes\\n node_transparent = tree.nodes.new('ShaderNodeBsdfTransparent')\\n node_transparent.location = -300, 100\\n\\n node_diffuse = tree.nodes.new('ShaderNodeBsdfDiffuse')\\n node_diffuse.location = -300, -100\\n node_diffuse.inputs[0].default_value = clay_color_rgb + (1.0, )\\n node_diffuse.color = clay_color_rgb\\n node_diffuse.name = 'addon_clay_color' # referencing to this ID in the real-time change\\n\\n node_mixshader = tree.nodes.new('ShaderNodeMixShader')\\n node_mixshader.location = 0, 50\\n node_mixshader.inputs[0].default_value = clay_color_alpha\\n node_mixshader.name = 'addon_clay_alpha' # referencing to this ID in the real-time change\\n\\n node_output = tree.nodes.new('ShaderNodeOutputMaterial')\\n node_output.location = 300, 50\\n\\n # connecting the nodes\\n tree.links.new(node_transparent.outputs[0], node_mixshader.inputs[1])\\n tree.links.new(node_diffuse.outputs[0], node_mixshader.inputs[2])\\n tree.links.new(node_mixshader.outputs[0], node_output.inputs[0])\\n\\n for node in tree.nodes:\\n node.select = False\\n\\n # sets the viewport color\\n clay_mat.diffuse_color = clay_color_rgb\\n \\n elif renderengine == 'BLENDER_RENDER':\\n clay_mat.diffuse_color = clay_color_rgb\\n clay_mat.use_transparency = True\\n clay_mat.alpha = clay_color_alpha\\n\\n previous_area = bpy.context.area.type\\n bpy.context.area.type = 'VIEW_3D'\\n previous_layers = tuple(scene.layers)\\n\\n # can't enter edit mode on objects on inactive layers\\n scene.layers = (True,)*20\\n\\n for obj in scene.objects:\\n if obj.select:\\n # only enters edit mode on active object\\n scene.objects.active = obj\\n obj.data.materials.append(clay_mat)\\n clay_index = obj.data.materials.find(clay_mat.name)\\n obj.active_material_index = clay_index\\n\\n bpy.ops.object.mode_set(mode='EDIT')\\n bpy.ops.mesh.select_all(action='SELECT')\\n bpy.ops.object.material_slot_assign()\\n bpy.ops.mesh.select_all(action='SELECT')\\n bpy.ops.object.mode_set(mode='OBJECT')\\n\\n bpy.context.area.type = previous_area\\n scene.layers = previous_layers\\n\\n return clay_mat\",\n \"def _add_switch(self, switchdesc):\\n # Check switch definition parameters\\n switch_attributes = list(switchdesc.keys())\\n if not set(switch_attributes).issubset(self.switch_attributes):\\n raise ValueError(\\n \\\"Switch definition: '{0}' defined in '{1}' is not supported. \\\"\\n \\\"Supported switch parameters are '{2}'.\\\".format(\\n json.dumps(switchdesc, indent=2), self._xmlfile,\\n self.switch_attributes))\\n for mandatory_parameter in self.switch_attributes[:2]:\\n if mandatory_parameter not in switch_attributes:\\n raise ValueError(\\n \\\"A '{0}' parameter is required in switch definition: \\\"\\n \\\"'{1}' defined in '{2}'.\\\".format(\\n mandatory_parameter, json.dumps(switchdesc, indent=2),\\n self._xmlfile))\\n\\n # Check the name of the switch is not already reserved\\n switch_name = switchdesc[self.switch_attributes[0]][0]\\n if switch_name in self._switches:\\n raise ValueError(\\n \\\"The switch name '{0}' defined in '{1}' is \\\"\\n \\\"already used.\\\".format(switch_name, self._xmlfile))\\n\\n # Create the switch control\\n switch_paths = {}\\n for pathdesc in switchdesc[self.switch_attributes[1]]:\\n path_name = pathdesc[self.switch_path[0]][0]\\n path_boxes = [box[self.unit_attributes[0]]\\n for box in pathdesc[self.switch_path[1]]]\\n switch_paths[path_name] = path_boxes\\n switch_keys = list(switch_paths.keys())\\n control = controls[\\\"Enum\\\"](\\n choices=tuple(switch_keys),\\n switch_name=switch_name,\\n desc=(\\\"Switch between paths '{0}:{1}' defined in pipeline '{2}'\\\"\\n \\\".\\\".format(switch_name, \\\"-\\\".join(switch_keys), self.id)))\\n setattr(self.inputs, switch_name, control)\\n self._switches[switch_name] = switch_paths\\n control.add_observer(\\\"value\\\", self._update_activation)\\n control.value = switch_keys[0]\",\n \"def test_add(self):\\n qc_cal = QuantumCircuit(2)\\n qc_cal.rzx(0.5, 0, 1)\\n qc_cal.add_calibration(RZXGate, (0, 1), params=[0.5], schedule=Schedule())\\n\\n qc = QuantumCircuit(2) & qc_cal\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\\n\\n qc = qc_cal & QuantumCircuit(2)\\n\\n self.assertEqual(qc.calibrations[RZXGate], {((0, 1), (0.5,)): Schedule(name=\\\"test\\\")})\\n self.assertEqual(qc_cal.calibrations, qc.calibrations)\",\n \"def add_control(operation, num_ctrl_qubits, label):\\n if isinstance(operation, UnitaryGate):\\n # attempt decomposition\\n operation._define()\\n if _control_definition_known(operation, num_ctrl_qubits):\\n return _control_predefined(operation, num_ctrl_qubits)\\n return control(operation, num_ctrl_qubits=num_ctrl_qubits, label=label)\",\n \"def BVC(self, value):\\n if not self.reg.V:\\n self.reg.PC += value\",\n \"def incr_registers(self):\\n pass\",\n \"def build_scl(net, ovs, src, dst, next_hop, match=None):\\n info(\\\"### Build service classifier, source:{}, next_hop:{}\\\\n\\\".format(src,\\n next_hop))\\n in_port = get_ofport(\\\"{}-{}\\\".format(ovs, src))\\n out_port = get_ofport(\\\"{}-{}\\\".format(ovs, next_hop))\\n ip_dst = net[dst].IP()\\n check_output(\\n split(\\n \\\"sudo ovs-ofctl add-flow {sw} \\\\\\\"nw_dst={ip_dst},icmp,in_port={in_port},actions=output={out_port}\\\\\\\"\\\".format(\\n **{\\\"sw\\\": ovs, \\\"in_port\\\": in_port, \\\"out_port\\\": out_port,\\n \\\"ip_dst\\\": ip_dst}\\n )\\n )\\n )\\n ret = check_output(split(\\\"sudo ovs-ofctl dump-flows {}\\\".format(ovs)))\\n info(\\\"### Flow table of the switch after adding SFP:\\\\n\\\")\\n print(ret)\",\n \"def cxr(self, q0, q1, ctrl=None):\\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\\n return self\",\n \"def parameterise_gate(self, gate:Union[cirq.Gate, Callable]): \\n if isinstance(gate, cirq.Gate):\\n if isinstance(gate, (cirq.XXPowGate, cirq.YYPowGate, cirq.ZZPowGate)):\\n param = self.new_param()\\n return gate**param\\n return gate\\n elif isclass(gate) and issubclass(gate, cirq.Gate):\\n parameters = ParameterisedCircuit._get_gate_parameters(gate)\\n n_param = len(parameters)\\n params = self.new_param(size=n_param, as_array=True)\\n kwargs = {parameters[i]:params[i] for i in range(n_param)}\\n return gate(**kwargs) \\n else:\\n n_param = ParameterisedCircuit._get_parameter_count(gate)\\n params = self.new_param(size=n_param)\\n params = tuple(params) if isinstance(params, np.ndarray) else (params,) \\n return gate(*params)\",\n \"def sincshift2d(image, dx, dy, sincrad=10, dampfac=3.25):\\n s = np.arange(-sincrad, sincrad+1.0)\\n sincx = _sincfunc(s, -dx, dampfac=dampfac)\\n sincy = _sincfunc(s, -dy, dampfac=dampfac)\\n kernel = np.outer(sincy, sincx)\\n newimage = convolve2d(image, kernel, mode='same')\\n return newimage\",\n \"def add_switch(self, dpid):\\n\\t\\tself.switches.append(dpid)\",\n \"def __init__(self, input, output) :\\n Gate.__init__(self, [input], output)\",\n \"def __init__(self, input0, input1, output) :\\n Gate.__init__(self, [input0,input1], output)\",\n \"def ff_add(a, b):\\n return a ^ b\",\n \"def inc(self, params):\\n reg = params[0]\\n if self.reg_dct[reg] == (2 ** 32) - 1:\\n self.reg_dct[reg] = 0\\n else:\\n self.reg_dct[reg] += 1\",\n \"def _add_splines(c, b1, d, b2):\\n if b1 == S.Zero or c == S.Zero:\\n rv = piecewise_fold(d * b2)\\n elif b2 == S.Zero or d == S.Zero:\\n rv = piecewise_fold(c * b1)\\n else:\\n new_args = []\\n n_intervals = len(b1.args)\\n # Just combining the Piecewise without any fancy optimization\\n p1 = piecewise_fold(c * b1)\\n p2 = piecewise_fold(d * b2)\\n\\n # Search all Piecewise arguments except (0, True)\\n p2args = list(p2.args[:-1])\\n\\n # This merging algorithm assumes the conditions in\\n # p1 and p2 are sorted\\n for arg in p1.args[:-1]:\\n # Conditional of Piecewise are And objects\\n # the args of the And object is a tuple of two\\n # Relational objects the numerical value is in the .rhs\\n # of the Relational object\\n expr = arg.expr\\n cond = arg.cond\\n\\n lower = cond.args[0].rhs\\n\\n # Check p2 for matching conditions that can be merged\\n for i, arg2 in enumerate(p2args):\\n expr2 = arg2.expr\\n cond2 = arg2.cond\\n\\n lower_2 = cond2.args[0].rhs\\n upper_2 = cond2.args[1].rhs\\n\\n if cond2 == cond:\\n # Conditions match, join expressions\\n expr += expr2\\n # Remove matching element\\n del p2args[i]\\n # No need to check the rest\\n break\\n elif lower_2 < lower and upper_2 <= lower:\\n # Check if arg2 condition smaller than arg1,\\n # add to new_args by itself (no match expected\\n # in p1)\\n new_args.append(arg2)\\n del p2args[i]\\n break\\n\\n # Checked all, add expr and cond\\n new_args.append((expr, cond))\\n\\n # Add remaining items from p2args\\n new_args.extend(p2args)\\n\\n # Add final (0, True)\\n new_args.append((0, True))\\n\\n rv = Piecewise(*new_args)\\n\\n return rv.expand()\",\n \"def __init__(self, incoming, n_units, W_ci, W_ig, W_og, W_fg,\\n b_ci=tf.zeros, b_ig=tf.zeros, b_og=tf.zeros, b_fg=tf.zeros,\\n a_ci=tf.tanh, a_ig=tf.sigmoid, a_og=tf.sigmoid, a_fg=tf.sigmoid, a_out=tf.nn.elu,\\n c_init=tf.zeros, h_init=tf.zeros, learn_c_init=False, learn_h_init=False, forgetgate=True, comb='add',\\n store_states=False, return_states=False, output_dropout=False, precomp_fwds=True, W_red_rec=None,\\n a_reduce_recurrents=None, tickerstep_biases=None, learn_tickerstep_biases=True,\\n dilation_rate=(1, 1), name='ConvLSTMLayer'):\\n super(ConvLSTMLayer, self).__init__()\\n with tf.variable_scope(name) as self.layer_scope:\\n self.incoming, self.incoming_shape = get_input(incoming)\\n self.n_units = n_units\\n self.lstm_inlets = ['ci', 'ig', 'og', 'fg']\\n if return_states:\\n store_states = True\\n \\n #\\n # Initialize weights and biases\\n #\\n \\n # Turn W inits into lists [forward_pass, backward_pass]\\n W_ci, W_ig, W_og, W_fg = [v[:2] if isinstance(v, list) else [v, v] for v in [W_ci, W_ig, W_og, W_fg]]\\n \\n # Check if feature dimensions to produce agree for all weight windows with n_units\\n W_dims = [[w[0].get_shape().as_list()[3], w[1].get_shape().as_list()[3]] for w in [W_ci, W_ig, W_og, W_fg]]\\n W_dims = np.array(W_dims).flatten()\\n if np.any(W_dims != n_units):\\n raise ValueError(\\\"Feature dimensions to produce must agree with n_units!\\\")\\n \\n # TODO: make all gates optional (list with keys and function for splitting)\\n if not forgetgate:\\n def a_fg(x):\\n return tf.ones(x.get_shape().as_list())\\n \\n # Make W and b tf variables\\n W_ci, W_ig, W_og, W_fg = [[tofov(w, shape=None, var_params=dict(name=n + suffix)) for w, suffix in\\n zip(v, ['_fwd', '_bwd'])] for v, n in\\n zip([W_ci, W_ig, W_og, W_fg], ['W_ci', 'W_ig', 'W_og', 'W_fg'])]\\n b_ci, b_ig, b_og, b_fg = [tofov(b, shape=[n_units], var_params=dict(name=n)) for b, n in\\n zip([b_ci, b_ig, b_og, b_fg], ['b_ci', 'b_ig', 'b_og', 'b_fg'])]\\n \\n # Pack weights for fwd and bwd connections by concatenating them at sliding mask feature dimension\\n # TODO: enable parallel calculation on multi-gpu\\n W_fwd_conc = tf.concat(axis=3, values=[W[0] for W in [W_ci, W_ig, W_og, W_fg]], name='W_fwd_conc')\\n W_bwd_conc = tf.concat(axis=3, values=[W[1] for W in [W_ci, W_ig, W_og, W_fg]], name='W_bwd_conc')\\n \\n # Initialize kernel for reducing recurrent features\\n self.reduce_recurrents = None\\n self.W_red_rec = W_red_rec\\n if a_reduce_recurrents is not None:\\n self.W_red_rec = tofov(W_red_rec, var_params=dict(name='W_red_rec'))\\n \\n def reduce_recurrents(h_prev):\\n \\\"\\\"\\\"Reduces features of internal recurrent connections h_prev\\\"\\\"\\\"\\n return a_reduce_recurrents(conv2d(h_prev, self.W_red_rec))\\n \\n self.reduce_recurrents = reduce_recurrents\\n \\n # Initialize bias for tickersteps\\n if tickerstep_biases is not None:\\n self.W_tickers = OrderedDict(zip_longest(self.lstm_inlets,\\n [tofov(tickerstep_biases, shape=[n_units],\\n var_params=dict(name='W_tickers_' + g,\\n trainable=learn_tickerstep_biases))\\n for g in self.lstm_inlets]))\\n else:\\n self.W_tickers = None\\n \\n #\\n # Create mask for output dropout\\n # apply dropout to n_units dimension of outputs, keeping dropout mask the same for all samples,\\n # sequence positions, and pixel coordinates\\n #\\n output_shape = self.get_output_shape()\\n if output_dropout:\\n out_do_mask = tf.ones(shape=[output_shape[0], output_shape[2], output_shape[3], output_shape[4]],\\n dtype=tf.float32, name='out_do_mask')\\n out_do_mask = tf.nn.dropout(out_do_mask, keep_prob=1. - output_dropout,\\n noise_shape=[1, 1, 1, output_shape[4]])\\n \\n def out_do(x):\\n \\\"\\\"\\\"Function for applying dropout mask to outputs\\\"\\\"\\\"\\n if output_dropout:\\n return out_do_mask * x\\n else:\\n return x\\n \\n # Redefine a_out to include dropout (sneaky, sneaky)\\n a_out_nodropout = a_out\\n \\n def a_out(x):\\n return a_out_nodropout(out_do(x))\\n \\n #\\n # Handle initializations for h (outputs) and c (cell states) as Variable if overwriteable or tensor if not\\n # shape=(samples, x, y, n_units)\\n #\\n h_init = out_do(tofov(h_init, shape=[output_shape[0], output_shape[2], output_shape[3], output_shape[4]],\\n var_params=dict(trainable=learn_h_init)))\\n c_init = tofov(c_init, shape=[output_shape[0], output_shape[2], output_shape[3], output_shape[4]],\\n var_params=dict(trainable=learn_c_init))\\n \\n # Initialize lists to store LSTM activations and cell states\\n h = [h_init] # [-1, x, y, n_units]\\n c = [c_init] # [-1, x, y, n_units]\\n \\n self.precomp_fwds = precomp_fwds\\n self.store_states = store_states\\n self.return_states = return_states\\n \\n self.W_fwd = OrderedDict(zip(self.lstm_inlets, [W[0] for W in [W_ci, W_ig, W_og, W_fg]]))\\n self.W_bwd = OrderedDict(zip(self.lstm_inlets, [W[1] for W in [W_ci, W_ig, W_og, W_fg]]))\\n \\n self.W_fwd_conc = W_fwd_conc\\n self.W_bwd_conc = W_bwd_conc\\n self.a = OrderedDict(ci=a_ci, ig=a_ig, og=a_og, fg=a_fg, out=a_out)\\n self.b = OrderedDict(ci=b_ci, ig=b_ig, og=b_og, fg=b_fg)\\n self.h = h\\n self.c = c\\n self.comb = comb\\n self.max_seq_len = None\\n self.external_rec = None\\n \\n self.dilation_rate = dilation_rate\\n \\n self.out = tf.expand_dims(h_init, 1)\\n self.name = name\",\n \"def wave_add_new():\\n return _u2i(_pigpio_command(_control, _PI_CMD_WVNEW, 0, 0))\",\n \"def add(self, params):\\n if len(params) < 2:\\n return\\n x = self.reg_dct[params[0]]\\n y = self.reg_dct[params[1]]\\n self.reg_dct[params[0]] = (x + y) % (2** 32)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.59902334","0.5926082","0.5785358","0.567691","0.5651704","0.5646367","0.5568842","0.5285402","0.5262861","0.5240311","0.5238952","0.52281916","0.5196213","0.51387995","0.5098061","0.50610805","0.50459075","0.49702364","0.49483865","0.49053276","0.48835528","0.4880057","0.48631072","0.48603404","0.4858691","0.4857373","0.48555","0.48502526","0.48475435","0.48404273","0.48340434","0.48153314","0.48009178","0.47878623","0.4760673","0.4749629","0.4748059","0.47478744","0.47476655","0.4744934","0.47368914","0.47349435","0.47221342","0.47192833","0.47183537","0.47171977","0.4712278","0.4709299","0.47073674","0.47065318","0.47054648","0.4688444","0.46824688","0.4677998","0.46722046","0.46692842","0.46550414","0.46529117","0.46506542","0.46504974","0.46492252","0.46409243","0.46327","0.46239045","0.46134365","0.46123028","0.46121737","0.46062982","0.46041626","0.46041626","0.46034077","0.4602424","0.4601841","0.45988646","0.45979846","0.45959148","0.45936984","0.45924908","0.4586978","0.45794287","0.4578603","0.45701215","0.45651385","0.45610067","0.45576093","0.45519167","0.45386598","0.4538641","0.45365277","0.4535645","0.4532647","0.45325753","0.45324063","0.452807","0.45266646","0.45242032","0.45227394","0.45207033","0.4519512","0.45148548"],"string":"[\n \"0.59902334\",\n \"0.5926082\",\n \"0.5785358\",\n \"0.567691\",\n \"0.5651704\",\n \"0.5646367\",\n \"0.5568842\",\n \"0.5285402\",\n \"0.5262861\",\n \"0.5240311\",\n \"0.5238952\",\n \"0.52281916\",\n \"0.5196213\",\n \"0.51387995\",\n \"0.5098061\",\n \"0.50610805\",\n \"0.50459075\",\n \"0.49702364\",\n \"0.49483865\",\n \"0.49053276\",\n \"0.48835528\",\n \"0.4880057\",\n \"0.48631072\",\n \"0.48603404\",\n \"0.4858691\",\n \"0.4857373\",\n \"0.48555\",\n \"0.48502526\",\n \"0.48475435\",\n \"0.48404273\",\n \"0.48340434\",\n \"0.48153314\",\n \"0.48009178\",\n \"0.47878623\",\n \"0.4760673\",\n \"0.4749629\",\n \"0.4748059\",\n \"0.47478744\",\n \"0.47476655\",\n \"0.4744934\",\n \"0.47368914\",\n \"0.47349435\",\n \"0.47221342\",\n \"0.47192833\",\n \"0.47183537\",\n \"0.47171977\",\n \"0.4712278\",\n \"0.4709299\",\n \"0.47073674\",\n \"0.47065318\",\n \"0.47054648\",\n \"0.4688444\",\n \"0.46824688\",\n \"0.4677998\",\n \"0.46722046\",\n \"0.46692842\",\n \"0.46550414\",\n \"0.46529117\",\n \"0.46506542\",\n \"0.46504974\",\n \"0.46492252\",\n \"0.46409243\",\n \"0.46327\",\n \"0.46239045\",\n \"0.46134365\",\n \"0.46123028\",\n \"0.46121737\",\n \"0.46062982\",\n \"0.46041626\",\n \"0.46041626\",\n \"0.46034077\",\n \"0.4602424\",\n \"0.4601841\",\n \"0.45988646\",\n \"0.45979846\",\n \"0.45959148\",\n \"0.45936984\",\n \"0.45924908\",\n \"0.4586978\",\n \"0.45794287\",\n \"0.4578603\",\n \"0.45701215\",\n \"0.45651385\",\n \"0.45610067\",\n \"0.45576093\",\n \"0.45519167\",\n \"0.45386598\",\n \"0.4538641\",\n \"0.45365277\",\n \"0.4535645\",\n \"0.4532647\",\n \"0.45325753\",\n \"0.45324063\",\n \"0.452807\",\n \"0.45266646\",\n \"0.45242032\",\n \"0.45227394\",\n \"0.45207033\",\n \"0.4519512\",\n \"0.45148548\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.56252754"},"document_rank":{"kind":"string","value":"6"}}},{"rowIdx":81761,"cells":{"query":{"kind":"string","value":"Ensure that we have snapshots for a given volume"},"document":{"kind":"string","value":"def run(connection, volume_id, interval='daily', max_snapshots=0, name=''):\n try:\n volumes = connection.get_all_volumes([volume_id])\n except EC2ResponseError as error:\n logging.error(kayvee.formatLog(\"ebs-snapshots\", \"error\", \"failed to connect to AWS\", {\"msg\": error.message}))\n return\n\n for volume in volumes:\n _ensure_snapshot(connection, volume, interval, name)\n _remove_old_snapshots(connection, volume, max_snapshots)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def snapshot_volumes(self) -> bool:\n return pulumi.get(self, \"snapshot_volumes\")","def get_volume_snapshots(self, volume):\n LOG.debug('get_volume_snapshot starts')\n pool_name = self.configuration.rbd_pool\n volume_name = 'volume-%s' % encodeutils.safe_encode(volume[\"id\"])\n snaps_on_vol = self._get_volume_snapshots(pool_name, volume_name)\n snapshots = list()\n if snaps_on_vol is not None:\n for snap in snaps_on_vol:\n snap_name = str(snap[\"name\"])\n item = dict()\n if snap_name.startswith(\"snapshot-\"):\n # snapshot directly created on volume.\n item[\"type\"] = \"volume_snap\"\n item[\"uuid\"] = snap_name[len('snapshot-'):]\n elif snap_name.startswith(\"volume-\") and \\\n snap_name.endswith(\".clone_snap\"):\n # snapshot used for create volume on volume.\n item[\"type\"] = \"clone_snap\"\n item[\"uuid\"] = snap_name[len(\"volume-\"):-len(\".clone_snap\")]\n elif snap_name.startswith(\"backup.\") and \".snap.\" in snap_name:\n # snapshot used for backup volume.\n item[\"type\"] = \"backup_snap\"\n item[\"uuid\"] = \\\n snap_name[len(\"backup.\"):snap_name.index(\".snap.\")]\n else:\n item[\"type\"] = \"\"\n item[\"uuid\"] = \"\"\n snapshots.append(item)\n\n LOG.debug('volume snapshots: %s', snapshots)\n LOG.debug('get_volume_snapshots finished.')\n return snapshots","def create_volume_from_snapshot(snapshots, objects_created,\n wait_for_available=120):\n if type(snapshots) is not list:\n snapshots = [snapshots]\n v = []\n for snapshot in snapshots:\n command = 'cinder create --snapshot-id %s --name %s' % \\\n (snapshot['id'], snapshot['display_name'])\n volume_from_snapshot = parse_output(Popen(\n command.split(), stdout=STDOUT, stderr=STDERR).communicate()[0])\n volume_from_snapshot['device'] = snapshot['device']\n volume_from_snapshot['bootable'] = snapshot['bootable']\n v.append(volume_from_snapshot)\n if wait_for_available > 0:\n wait = 0\n again = False\n while wait < wait_for_available:\n time.sleep(5)\n wait += 5\n again = False\n for volume in v:\n command = 'cinder show %s' % volume['id']\n status = parse_output(Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n )['status']\n if status == 'error':\n # clean up and create volume again\n command = 'cinder delete %s' % volume['id']\n a = Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n command = 'cinder create --snapshot-id %s' % \\\n volume['snapshot_id']\n volume_info = parse_output(Popen(\n command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0])\n volume_info['bootable'] = volume['bootable']\n volume_info['device'] = volume['device']\n volume = volume_info\n again = True\n break\n elif status == 'creating':\n again = True\n break\n elif status == 'available':\n volume['status'] = status\n pass\n if again:\n continue\n else:\n break\n if again: # Loop ended due to timeout\n print 'Error creating volume from snapshot!'\n print 'The following entities were created in the process:'\n print_objects_created(objects_created)\n sys.exit(-1)\n return v","def test_create_volume_from_snapshot(self, mock_ghn):\n ctxt = context.get_admin_context()\n extra_specs = {}\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\n snap = {'id': '1', 'name': 'volume1', 'display_name': '',\n 'volume_type_id': type_ref['id'], 'size': 10,\n 'provider_id': 'space_orig'}\n volume = {'id': '2', 'name': 'volume2', 'display_name': '',\n 'volume_type_id': type_ref['id'], 'size': 10}\n pid = self.driver.create_volume_from_snapshot(volume, snap)\n # We must copy entier underlying storage, ~12GB, not just 10GB\n self.assertEqual(11444 * units.Mi, self.dd_count)\n self.assertEqual('1M', self.bs)\n # Check space-create command\n expected = {'redundancy': '0', 'group': 'xanadu',\n 'name': 'volume2', 'mode': '0777',\n 'user': 'kane', 'net': 'net1',\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\n 'size': '12'}\n self.assertDictMatch(expected, self.created)\n # Check the returned provider\n expected_pid = {'provider_id': 'volume2'}\n self.assertDictMatch(expected_pid, pid)","def test_volume_snapshot_create_get_list_delete(self):\n volume = self.create_volume()\n self.addCleanup(self.delete_volume, volume['id'])\n\n s_name = data_utils.rand_name(self.__class__.__name__ + '-Snapshot')\n # Create snapshot\n snapshot = self.snapshots_client.create_snapshot(\n volume_id=volume['id'],\n display_name=s_name)['snapshot']\n\n def delete_snapshot(snapshot_id):\n waiters.wait_for_volume_resource_status(self.snapshots_client,\n snapshot_id,\n 'available')\n # Delete snapshot\n self.snapshots_client.delete_snapshot(snapshot_id)\n self.snapshots_client.wait_for_resource_deletion(snapshot_id)\n\n self.addCleanup(delete_snapshot, snapshot['id'])\n self.assertEqual(volume['id'], snapshot['volumeId'])\n # Get snapshot\n fetched_snapshot = self.snapshots_client.show_snapshot(\n snapshot['id'])['snapshot']\n self.assertEqual(s_name, fetched_snapshot['displayName'])\n self.assertEqual(volume['id'], fetched_snapshot['volumeId'])\n # Fetch all snapshots\n snapshots = self.snapshots_client.list_snapshots()['snapshots']\n self.assertIn(snapshot['id'], map(lambda x: x['id'], snapshots))","def create_volume_snapshot(volumes, source_instance, objects_created,\n wait_for_available=50):\n if type(volumes) is not list:\n volumes = [volumes]\n s = []\n for volume in volumes:\n command = 'cinder snapshot-create --force True --name %s %s' % \\\n (volume['name'], volume['id'])\n snapshot_info = parse_output(Popen(command.split(), stdout=STDOUT).communicate()[0])\n if volume['bootable'] == 'true':\n snapshot_info['bootable'] = True\n else:\n snapshot_info['bootable'] = False\n att = volume['attachments'].replace(\"'\", \"\\\"\").replace(\n \"u\\\"\", \"\\\"\").replace(\" None,\", \" \\\"None\\\",\")\n snapshot_info['device'] = get(json.loads(att), 'server_id',\n source_instance['id'])[0]['device']\n s.append(snapshot_info)\n if wait_for_available > 0:\n wait = 0\n again = False\n while wait < wait_for_available:\n time.sleep(5)\n wait += 5\n again = False\n for snapshot in s:\n command = 'cinder snapshot-show %s' % snapshot['id']\n status = parse_output(Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n )['status']\n if status == 'error':\n # clean up and take snapshot again\n command = 'cinder snapshot-delete %s' % snapshot['id']\n a = Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n command = 'cinder snapshot-create --force True %s' % \\\n snapshot['volume_id']\n snapshot_info = parse_output(Popen(command.split(),\n stdout=STDOUT, stderr=STDERR\n ).communicate()[0])\n snapshot_info['bootable'] = snapshot['bootable']\n snapshot_info['device'] = snapshot['device']\n snapshot = snapshot_info\n again = True\n break\n elif status == 'creating':\n again = True\n break\n elif status == 'available':\n snapshot['status'] = status\n pass\n if again:\n continue\n else:\n break\n if again: # Loop ended due to timeout\n print 'Error creating volume snapshot!'\n print 'The following entities were created in the process:'\n print_objects_created(objects_created)\n sys.exit(-1)\n return s","def snapshot_volumes(self) -> pulumi.Input[bool]:\n return pulumi.get(self, \"snapshot_volumes\")","def _ensure_snapshot(connection, volume, interval, name):\n if interval not in VALID_INTERVALS:\n logging.warning(kayvee.formatLog(\"ebs-snapshots\", \"warning\", \"invalid snapshotting interval\", {\n \"volume\": volume.id,\n \"interval\": interval\n }))\n return\n\n snapshots = connection.get_all_snapshots(filters={'volume-id': volume.id})\n\n # Create a snapshot if we don't have any\n if not snapshots:\n _create_snapshot(connection, volume, name)\n return\n\n min_delta = 3600 * 24 * 365 * 10 # 10 years :)\n for snapshot in snapshots:\n timestamp = datetime.datetime.strptime(\n snapshot.start_time,\n '%Y-%m-%dT%H:%M:%S.000Z')\n delta_seconds = int(\n (datetime.datetime.utcnow() - timestamp).total_seconds())\n\n if delta_seconds < min_delta:\n min_delta = delta_seconds\n\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", 'The newest snapshot for {} is {} seconds old'.format(volume.id, min_delta)))\n\n if interval == 'hourly' and min_delta > 3600:\n _create_snapshot(connection, volume, name)\n elif interval == 'daily' and min_delta > 3600*24:\n _create_snapshot(connection, volume, name)\n elif interval == 'weekly' and min_delta > 3600*24*7:\n _create_snapshot(connection, volume, name)\n elif interval == 'monthly' and min_delta > 3600*24*30:\n _create_snapshot(connection, volume, name)\n elif interval == 'yearly' and min_delta > 3600*24*365:\n _create_snapshot(connection, volume, name)\n else:\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", \"no snapshot needed\", {\"volume\": volume.id}))","def get_snapshots(vol_name):\n\n l = None\n try:\n cmd = 'gluster snapshot info volume %s --xml' % vol_name\n d, err = xml_parse.run_gluster_command(cmd)\n if err:\n raise Exception(err)\n if d:\n if d[\"op_status\"][\"op_ret\"] == 0:\n l, err = xml_parse.get_snapshots(d[\"root\"])\n if err:\n raise Exception(err)\n except Exception, e:\n return None, 'Error getting volume snapshots: %s' % str(e)\n else:\n return l, None","def test_backup_can_use_snapshots(self):\n use_snaps = self.driver.backup_use_temp_snapshot()\n self.assertTrue(use_snaps)","def _verify_cache_volume(self, context, img_meta,\n img_service, cachevol_props):\n lcfg = self.configuration\n cache_dir = '%s/' % lcfg.zfssa_cache_directory\n cache_vol_obj = Volume()\n cache_vol_obj.provider_location = self.mount_path + '/' + cache_dir\n cache_vol_obj._name_id = cachevol_props['id']\n cachevol_name = cache_dir + cache_vol_obj.name\n\n LOG.debug('Verifying cache volume %s:', cachevol_name)\n\n try:\n cache_vol = self.zfssa.get_volume(cachevol_name)\n except exception.VolumeNotFound:\n # There is no existing cache volume, create one:\n LOG.debug('Cache volume not found. Creating one...')\n return self._create_cache_volume(context,\n img_meta,\n img_service,\n cachevol_props)\n\n # A cache volume does exist, check if it's updated:\n if ((cache_vol['updated_at'] != cachevol_props['updated_at']) or\n (cache_vol['image_id'] != cachevol_props['image_id'])):\n if cache_vol['numclones'] > 0:\n # The cache volume is updated, but has clones\n exception_msg = (_('Cannot delete '\n 'cache volume: %(cachevol_name)s. '\n 'It was updated at %(updated_at)s '\n 'and currently has %(numclones)d '\n 'volume instances.'),\n {'cachevol_name': cachevol_name,\n 'updated_at': cachevol_props['updated_at'],\n 'numclones': cache_vol['numclones']})\n LOG.error(exception_msg)\n raise exception.VolumeBackendAPIException(data=exception_msg)\n\n # The cache volume is updated, but has no clone, so we delete it\n # and re-create a new one:\n super(ZFSSANFSDriver, self).delete_volume(cache_vol_obj)\n return self._create_cache_volume(context,\n img_meta,\n img_service,\n cachevol_props)\n\n return cachevol_name","def create_volume_snapshot(self, volume, name=None, description=None,\n check=True):\n cmd = 'cinder snapshot-create'\n if name:\n cmd += ' --name ' + name\n if description is not None:\n cmd += ' --description ' + moves.shlex_quote(description)\n\n cmd += ' ' + volume.id\n\n exit_code, stdout, stderr = self.execute_command(\n cmd, timeout=config.SNAPSHOT_AVAILABLE_TIMEOUT, check=check)\n\n snapshot_table = output_parser.table(stdout)\n snapshot = {key: value for key, value in snapshot_table['values']}\n\n return snapshot","def create_volume_from_snapshot(self, snapshot, volume, volume_db):\n self.authenticate_user()\n\n if self.configuration.vipr_emulate_snapshot == 'True':\n self.create_cloned_volume(volume, snapshot)\n return\n\n ctxt = context.get_admin_context()\n\n src_snapshot_name = None\n\n #src_snapshot_name = snapshot['display_name']\n src_vol_ref = volume_db.volume_get(ctxt, snapshot['volume_id'])\n new_volume_name = self._get_volume_name(volume)\n number_of_volumes = 1\n\n try:\n src_vol_name, src_vol_uri = self._get_vipr_volume_name(src_vol_ref, True)\n src_snapshot_name = self._get_vipr_snapshot_name(snapshot , src_vol_uri)\n\n (storageresType, storageresTypename) = self.volume_obj.get_storageAttributes(\n src_vol_name\n , None\n , src_snapshot_name)\n\n resource_id = self.volume_obj.storageResource_query(storageresType,\n src_vol_name,\n None,\n src_snapshot_name,\n self.configuration.vipr_project,\n self.configuration.vipr_tenant)\n\n self.volume_obj.clone(\n new_volume_name,\n number_of_volumes,\n resource_id,\n sync=True)\n\n except vipr_utils.SOSError as e:\n if(e.err_code == vipr_utils.SOSError.SOS_FAILURE_ERR):\n raise vipr_utils.SOSError(\n vipr_utils.SOSError.SOS_FAILURE_ERR,\n \"Snapshot \" +\n src_snapshot_name +\n \": clone failed\\n\" +\n e.err_text)\n else:\n with excutils.save_and_reraise_exception():\n LOG.exception(\n _(\"Snapshot : %s clone failed\") % src_snapshot_name)","def create_volume_from_snapshot(self, volume, snapshot):\n snap_name = self.get_snap_name(snapshot.id)\n view_name = self.get_view_name(volume.id)\n vol_name = self.get_volume_name(volume.id)\n cview = src_attach_info = dest_attach_info = None\n rpolicy = self.get_policy()\n properties = volume_utils.brick_get_connector_properties(\n self.configuration.use_multipath_for_image_xfer,\n self.configuration.enforce_multipath_for_image_xfer)\n LOG.debug(\"Searching for snapshot: %s in K2.\", snap_name)\n snap_rs = self.client.search(\"snapshots\", short_name=snap_name)\n if hasattr(snap_rs, 'hits') and snap_rs.total != 0:\n snap = snap_rs.hits[0]\n LOG.debug(\"Creating a view: %(view)s from snapshot: %(snap)s\",\n {'view': view_name, 'snap': snap_name})\n try:\n cview = self.client.new(\"snapshots\",\n short_name=view_name,\n source=snap, retention_policy=rpolicy,\n is_exposable=True).save()\n except Exception as ex:\n LOG.exception(\"Creating a view: %(view)s from snapshot: \"\n \"%(snap)s failed\", {\"view\": view_name,\n \"snap\": snap_name})\n raise KaminarioCinderDriverException(reason=ex)\n\n else:\n msg = _(\"Snapshot: %s search failed in K2.\") % snap_name\n LOG.error(msg)\n raise KaminarioCinderDriverException(reason=msg)\n\n try:\n conn = self.initialize_connection(cview, properties)\n src_attach_info = self._connect_device(conn)\n self.create_volume(volume)\n conn = self.initialize_connection(volume, properties)\n dest_attach_info = self._connect_device(conn)\n volume_utils.copy_volume(src_attach_info['device']['path'],\n dest_attach_info['device']['path'],\n snapshot.volume.size * units.Ki,\n self.configuration.volume_dd_blocksize,\n sparse=True)\n self._kaminario_disconnect_volume(src_attach_info,\n dest_attach_info)\n self.terminate_connection(volume, properties)\n self.terminate_connection(cview, properties)\n cview.delete()\n except Exception as ex:\n self._kaminario_disconnect_volume(src_attach_info,\n dest_attach_info)\n self.terminate_connection(cview, properties)\n self.terminate_connection(volume, properties)\n cview.delete()\n self.delete_volume(volume)\n LOG.exception(\"Copy to volume: %(vol)s from view: %(view)s \"\n \"failed\", {\"vol\": vol_name, \"view\": view_name})\n raise KaminarioCinderDriverException(reason=ex)","def create_volume_from_snapshot(self, volume, snapshot):\n self._ensure_shares_mounted()\n\n snapshot_vol = self._get_snapshot_volume(snapshot)\n nfs_share = snapshot_vol['provider_location']\n volume['provider_location'] = nfs_share\n nms = self.share2nms[nfs_share]\n\n vol, dataset = self._get_share_datasets(nfs_share)\n snapshot_name = '%s/%s/%s@%s' % (vol, dataset, snapshot['volume_name'],\n snapshot['name'])\n folder = '%s/%s' % (dataset, volume['name'])\n nms.folder.clone(snapshot_name, '%s/%s' % (vol, folder))\n\n try:\n self._share_folder(nms, vol, folder)\n except utils.NexentaException:\n try:\n nms.folder.destroy('%s/%s' % (vol, folder), '')\n except utils.NexentaException:\n LOG.warning(\"Cannot destroy cloned folder: \"\n \"%(vol)s/%(folder)s\",\n {'vol': vol, 'folder': folder})\n raise\n\n if self._get_nfs_server_version(nfs_share) < 4:\n sub_share, mnt_path = self._get_subshare_mount_point(nfs_share,\n volume)\n self._ensure_share_mounted(sub_share, mnt_path)\n\n if (('size' in volume) and (\n volume['size'] > snapshot['volume_size'])):\n self.extend_volume(volume, volume['size'])\n\n return {'provider_location': volume['provider_location']}","def test_live_migration_src_check_volume_node_not_alive(self):\n\n instance_id = self._create_instance()\n i_ref = db.instance_get(self.context, instance_id)\n dic = {'instance_id': instance_id, 'size': 1}\n v_ref = db.volume_create(self.context, {'instance_id': instance_id,\n 'size': 1})\n t1 = utils.utcnow() - datetime.timedelta(1)\n dic = {'created_at': t1, 'updated_at': t1, 'binary': 'nova-volume',\n 'topic': 'volume', 'report_count': 0}\n s_ref = db.service_create(self.context, dic)\n\n self.assertRaises(exception.VolumeServiceUnavailable,\n self.scheduler.driver.schedule_live_migration,\n self.context, instance_id, i_ref['host'])\n\n db.instance_destroy(self.context, instance_id)\n db.service_destroy(self.context, s_ref['id'])\n db.volume_destroy(self.context, v_ref['id'])","def test_view_volume(self, volume, volumes_steps):\n volumes_steps.view_volume(volume.name)","def test_clone_delete_snap(self):\n\n # pylint: disable=too-many-statements, too-many-locals\n # Enabling Volume options on the volume and validating\n g.log.info(\"Enabling volume options for volume %s \", self.volname)\n options = {\" features.uss\": \"enable\"}\n ret = set_volume_options(self.mnode, self.volname, options)\n self.assertTrue(ret, (\"Failed to set volume options for volume %s\"\n % self.volname))\n g.log.info(\"Successfully set volume options\"\n \"for volume %s\", self.volname)\n\n # Validate feature.uss enabled or not\n g.log.info(\"Validating feature.uss is enabled\")\n option = \"features.uss\"\n vol_option = get_volume_options(self.mnode, self.volname, option)\n self.assertEqual(vol_option['features.uss'], 'enable', \"Failed\"\n \" to validate \"\n \"volume options\")\n g.log.info(\"Successfully validated volume options\"\n \"for volume %s\", self.volname)\n\n # Creating snapshot\n g.log.info(\"Starting to Create snapshot\")\n for snap_count in range(0, 2):\n ret, _, _ = snap_create(self.mnode, self.volname,\n \"snap%s\" % snap_count)\n self.assertEqual(ret, 0, (\"Failed to create snapshot for volume %s\"\n % self.volname))\n g.log.info(\"Snapshot snap%s created successfully\"\n \"for volume %s\", snap_count, self.volname)\n\n # Activating snapshot\n g.log.info(\"Starting to Activate Snapshot\")\n for snap_count in range(0, 2):\n ret, _, _ = snap_activate(self.mnode, \"snap%s\" % snap_count)\n self.assertEqual(ret, 0, (\"Failed to Activate snapshot snap%s\"\n % snap_count))\n g.log.info(\"Snapshot snap%s activated successfully\", snap_count)\n\n # Reset volume:\n g.log.info(\"Starting to Reset Volume\")\n ret, _, _ = volume_reset(self.mnode, self.volname, force=False)\n self.assertEqual(ret, 0, (\"Failed to reset volume %s\" % self.volname))\n g.log.info(\"Reset Volume on volume %s is Successful\", self.volname)\n\n # Validate feature.uss enabled or not\n g.log.info(\"Validating feature.uss is enabled\")\n option = \"features.uss\"\n vol_option = get_volume_options(self.mnode, self.volname, option)\n self.assertEqual(vol_option['features.uss'], 'off', \"Failed\"\n \" to validate \"\n \"volume options\")\n g.log.info(\"Successfully validated volume options\"\n \"for volume %s\", self.volname)\n\n # Verify volume's all process are online\n g.log.info(\"Starting to Verify volume's all process are online\")\n ret = verify_all_process_of_volume_are_online(self.mnode, self.volname)\n self.assertTrue(ret, (\"Volume %s : All process are\"\n \"not online\" % self.volname))\n g.log.info(\"Volume %s : All process are online\", self.volname)\n\n # Creating and starting a Clone of snapshot\n g.log.info(\"Starting to Clone Snapshot\")\n for clone_count in range(0, 2):\n ret, _, _ = snap_clone(self.mnode, \"snap%s\" % clone_count,\n \"clone%s\" % clone_count)\n self.assertEqual(ret, 0, (\"Failed to clone clone%s volume\"\n % clone_count))\n g.log.info(\"clone%s volume created successfully\", clone_count)\n\n # Start Cloned volume\n g.log.info(\"starting to Validate clone volumes are started\")\n for clone_count in range(0, 2):\n ret, _, _ = volume_start(self.mnode, \"clone%s\" % clone_count)\n self.assertEqual(ret, 0, (\"Failed to start clone%s\"\n % clone_count))\n g.log.info(\"clone%s started successfully\", clone_count)\n g.log.info(\"All the clone volumes are started Successfully\")\n\n # Validate Volume start of cloned volume\n g.log.info(\"Starting to Validate Volume start\")\n for clone_count in range(0, 2):\n vol_info = get_volume_info(self.mnode, \"clone%s\" % clone_count)\n if vol_info[\"clone%s\" % clone_count]['statusStr'] != 'Started':\n raise ExecutionError(\"Failed to get volume info for clone%s\"\n % clone_count)\n g.log.info(\"Volume clone%s is in Started state\", clone_count)\n\n # Validate feature.uss enabled or not\n g.log.info(\"Validating feature.uss is enabled\")\n option = \"features.uss\"\n for clone_count in range(0, 2):\n vol_option = get_volume_options(self.mnode, \"clone%s\"\n % clone_count, option)\n self.assertEqual(vol_option['features.uss'], 'enable', \"Failed\"\n \" to validate\"\n \"volume options\")\n g.log.info(\"Successfully validated volume options\"\n \"for volume clone%s\", clone_count)\n\n # Mount both the cloned volumes\n g.log.info(\"Mounting Cloned Volumes\")\n for mount_obj in range(0, 2):\n self.mpoint = \"/mnt/clone%s\" % mount_obj\n cmd = \"mkdir -p %s\" % self.mpoint\n ret, _, _ = g.run(self.clients[0], cmd)\n self.assertEqual(ret, 0, (\"Creation of directory %s\"\n \"for mounting\"\n \"volume %s failed: Directory already\"\n \"present\"\n % (self.mpoint, \"clone%s\" % mount_obj)))\n g.log.info(\"Creation of directory %s for mounting volume %s \"\n \"success\", self.mpoint, (\"clone%s\" % mount_obj))\n ret, _, _ = mount_volume(\"clone%s\" % mount_obj, self.mount_type,\n self.mpoint, self.mnode, self.clients[0])\n self.assertEqual(ret, 0, (\"clone%s is not mounted\"\n % mount_obj))\n g.log.info(\"clone%s is mounted Successfully\", mount_obj)\n\n # Perform I/O on mount\n # Start I/O on all mounts\n g.log.info(\"Starting to Perform I/O on Mountpoint\")\n all_mounts_procs = []\n for mount_obj in range(0, 2):\n cmd = (\"cd /mnt/clone%s/; for i in {1..10};\"\n \"do touch file$i; done; cd;\") % mount_obj\n proc = g.run(self.clients[0], cmd)\n all_mounts_procs.append(proc)\n g.log.info(\"I/O on mountpoint is successful\")\n\n # create snapshot\n g.log.info(\"Starting to Create snapshot of clone volume\")\n ret0, _, _ = snap_create(self.mnode, \"clone0\", \"snap2\")\n self.assertEqual(ret0, 0, \"Failed to create the snapshot\"\n \"snap2 from clone0\")\n g.log.info(\"Snapshots snap2 created successfully from clone0\")\n ret1, _, _ = snap_create(self.mnode, \"clone1\", \"snap3\")\n self.assertEqual(ret1, 0, \"Failed to create the snapshot snap3\"\n \"from clone1\")\n g.log.info(\"Snapshots snap3 created successfully from clone1\")\n\n # Listing all Snapshots present\n g.log.info(\"Starting to list all snapshots\")\n ret, _, _ = snap_list(self.mnode)\n self.assertEqual(ret, 0, (\"Failed to list snapshots present\"))\n g.log.info(\"Snapshots successfully listed\")","def snapshots_created(self):\n # log.debug(\"Getting snaps created for volume {0}\".format(self.volume_id))\n snaps_info = []\n for snap in self._derived_snapshots:\n snap_info = {}\n try:\n if snap.volume_id == self.volume_id:\n snap.update()\n snap_info['snap_id'] = snap.id\n snap_info['snap_progress'] = snap.progress\n snap_info['snap_status'] = snap.status\n snap_info['snap_desc'] = snap.description\n snaps_info.append(snap_info)\n except EC2ResponseError, e:\n log.warning(\"EC2ResponseError getting snapshot status: {0} \"\n \"(code {1}; status {2})\"\n .format(e.message, e.error_code, e.status))\n return snaps_info","def migrate_volume(self, ctxt, volume, host):\n LOG.debug('Enter: migrate_volume: id=%(id)s, host=%(host)s',\n {'id': volume['id'], 'host': host})\n\n false_ret = (False, None)\n\n if volume['status'] not in ('available', 'retyping'):\n LOG.warning(\"Volume status must be 'available' or 'retyping'.\"\n \" Current volume status: %s\", volume['status'])\n return false_ret\n\n if 'capabilities' not in host:\n LOG.warning(\"Unsupported host. No capabilities found\")\n return false_ret\n\n capabilities = host['capabilities']\n ns_shares = capabilities['ns_shares']\n dst_parts = capabilities['location_info'].split(':')\n dst_host, dst_volume = dst_parts[1:]\n\n if (capabilities.get('vendor_name') != 'Nexenta' or\n dst_parts[0] != self.__class__.__name__ or\n capabilities['free_capacity_gb'] < volume['size']):\n return false_ret\n\n nms = self.share2nms[volume['provider_location']]\n ssh_bindings = nms.appliance.ssh_list_bindings()\n shares = []\n for bind in ssh_bindings:\n for share in ns_shares:\n if (share.startswith(ssh_bindings[bind][3]) and\n ns_shares[share] >= volume['size']):\n shares.append(share)\n if len(shares) == 0:\n LOG.warning(\"Remote NexentaStor appliance at %s should be \"\n \"SSH-bound.\", share)\n return false_ret\n share = sorted(shares, key=ns_shares.get, reverse=True)[0]\n snapshot = {\n 'volume_name': volume['name'],\n 'volume_id': volume['id'],\n 'name': utils.get_migrate_snapshot_name(volume)\n }\n self.create_snapshot(snapshot)\n location = volume['provider_location']\n src = '%(share)s/%(volume)s@%(snapshot)s' % {\n 'share': location.split(':')[1].split('volumes/')[1],\n 'volume': volume['name'],\n 'snapshot': snapshot['name']\n }\n dst = ':'.join([dst_host, dst_volume.split('/volumes/')[1]])\n try:\n nms.appliance.execute(self._get_zfs_send_recv_cmd(src, dst))\n except utils.NexentaException as exc:\n LOG.warning(\"Cannot send source snapshot %(src)s to \"\n \"destination %(dst)s. Reason: %(exc)s\",\n {'src': src, 'dst': dst, 'exc': exc})\n return false_ret\n finally:\n try:\n self.delete_snapshot(snapshot)\n except utils.NexentaException as exc:\n LOG.warning(\"Cannot delete temporary source snapshot \"\n \"%(src)s on NexentaStor Appliance: %(exc)s\",\n {'src': src, 'exc': exc})\n try:\n self.delete_volume(volume)\n except utils.NexentaException as exc:\n LOG.warning(\"Cannot delete source volume %(volume)s on \"\n \"NexentaStor Appliance: %(exc)s\",\n {'volume': volume['name'], 'exc': exc})\n\n dst_nms = self._get_nms_for_url(capabilities['nms_url'])\n dst_snapshot = '%s/%s@%s' % (dst_volume.split('volumes/')[1],\n volume['name'], snapshot['name'])\n try:\n dst_nms.snapshot.destroy(dst_snapshot, '')\n except utils.NexentaException as exc:\n LOG.warning(\"Cannot delete temporary destination snapshot \"\n \"%(dst)s on NexentaStor Appliance: %(exc)s\",\n {'dst': dst_snapshot, 'exc': exc})\n return True, {'provider_location': share}","def create_volume_from_snapshot(self, volume, snapshot):\n snapshotname = huawei_utils.encode_name(snapshot['id'])\n\n snapshot_id = snapshot.get('provider_location', None)\n if snapshot_id is None:\n snapshot_id = self.restclient.get_snapshotid_by_name(snapshotname)\n if snapshot_id is None:\n err_msg = (_(\n 'create_volume_from_snapshot: Snapshot %(name)s '\n 'does not exist.')\n % {'name': snapshotname})\n LOG.error(err_msg)\n raise exception.VolumeBackendAPIException(data=err_msg)\n\n lun_info = self.create_volume(volume)\n\n tgt_lun_id = lun_info['ID']\n luncopy_name = huawei_utils.encode_name(volume['id'])\n\n LOG.info(_LI(\n 'create_volume_from_snapshot: src_lun_id: %(src_lun_id)s, '\n 'tgt_lun_id: %(tgt_lun_id)s, copy_name: %(copy_name)s.'),\n {'src_lun_id': snapshot_id,\n 'tgt_lun_id': tgt_lun_id,\n 'copy_name': luncopy_name})\n\n event_type = 'LUNReadyWaitInterval'\n\n wait_interval = huawei_utils.get_wait_interval(self.xml_file_path,\n event_type)\n\n def _volume_ready():\n result = self.restclient.get_lun_info(tgt_lun_id)\n\n if (result['HEALTHSTATUS'] == constants.STATUS_HEALTH\n and result['RUNNINGSTATUS'] == constants.STATUS_VOLUME_READY):\n return True\n return False\n\n huawei_utils.wait_for_condition(self.xml_file_path,\n _volume_ready,\n wait_interval,\n wait_interval * 10)\n\n self._copy_volume(volume, luncopy_name,\n snapshot_id, tgt_lun_id)\n\n return {'ID': lun_info['ID'],\n 'lun_info': lun_info}","def assert_valid_volume(wells,exception_info='invalid volume'):\n wells = ensure_list(wells)\n \n assert all([well.volume >= get_well_dead_volume(well) for well in wells]), exception_info\n assert all([well.volume <= get_well_max_volume(well) for well in wells]), exception_info","def create_volume_from_snapshot(self, volume, snapshot):\n\n free_size = self._get_spdk_lvs_free_space(\n self._get_spdk_lvs_uuid(\n self._get_spdk_volume_name(snapshot.name)))\n\n if free_size < volume.size:\n raise exception.VolumeBackendAPIException(\n data=_('Not enough space to create snapshot with SPDK'))\n\n return self._create_volume(volume, snapshot)","def test_present_wo_existing_volumes():\n docker_create_volume = Mock(return_value=\"created\")\n docker_remove_volume = Mock(return_value=\"removed\")\n __salt__ = {\n \"docker.create_volume\": docker_create_volume,\n \"docker.remove_volume\": docker_remove_volume,\n \"docker.volumes\": Mock(return_value={\"Volumes\": None}),\n }\n with patch.dict(docker_state.__dict__, {\"__salt__\": __salt__}):\n ret = docker_state.present(\n \"volume_foo\",\n driver=\"bar\",\n force=True,\n )\n docker_create_volume.assert_called_with(\n \"volume_foo\", driver=\"bar\", driver_opts=None\n )\n assert ret == {\n \"name\": \"volume_foo\",\n \"comment\": \"\",\n \"changes\": {\"created\": \"created\"},\n \"result\": True,\n }","def test_create_snapshot(self, mock_ghn):\n # Now snapshot the volume and check commands\n snapshot = {'volume_name': 'volume10',\n 'volume_id': 'xxx', 'display_name': 'snap10',\n 'name': '123abc', 'volume_size': 10, 'id': '123abc',\n 'volume': {'provider_id': 'space10'}}\n ret = self.driver.create_snapshot(snapshot)\n # We must copy entier underlying storage, ~12GB, not just 10GB\n self.assertEqual(11444 * units.Mi, self.dd_count)\n self.assertEqual('1M', self.bs)\n # Check space-create command\n expected = {'redundancy': '0', 'group': 'xanadu',\n 'name': snapshot['display_name'], 'mode': '0777',\n 'user': 'kane', 'net': 'net1',\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\n 'size': '12'}\n self.assertDictMatch(expected, self.created)\n # Check the returned provider\n expected_pid = {'provider_id': 'snap10'}\n self.assertDictMatch(expected_pid, ret)","def test_aws_service_api_volume_get(self):\n pass","def test_snapshot(self):\n # Try to create a snapshot with a wrong machine_uuid.\n status = self.proxy.snapshot.create(\n PROVIDER_ID, \"Doesn't exist\"\n )\n self.check_xmlrpc_command_result(status, has_error=True)\n\n # Try to create a snapshot with a wrong provider.\n status = self.proxy.snapshot.create(\n \"Doesn't exist\", self.machine_uuid\n )\n self.check_xmlrpc_command_result(status, has_error=True)\n\n # Create a snapshot.\n status = self.proxy.snapshot.create(\n PROVIDER_ID, self.machine_uuid\n )\n self.check_xmlrpc_command_result(status)\n\n # Try to destroy snapshots with a wrong provider.\n status = self.proxy.snapshot.destroy(\n \"Doesn't exist\", self.machine_uuid\n )\n self.check_xmlrpc_command_result(status, has_error=True)\n\n # Destroy snapshots.\n status = self.proxy.snapshot.destroy(\n PROVIDER_ID, self.machine_uuid\n )\n self.check_xmlrpc_command_result(status)","def test_snapshots(self):\n snapshots_dir = REPO_ROOT / \"tests\" / \"snapshots\"\n snapshot_files = set(f.name for f in snapshots_dir.glob(\"*.txt\"))\n assert snapshot_files == SNAPSHOTS_USED","def _tag_volume():\n if dry:\n print('Would tag the new volume.')\n return True\n\n while True:\n # waiting for the volume to be up to tag it\n i = _fetch('vm')\n v = [x for x in i.volumes.all()]\n if len(v) == 0:\n # volumes should actually be already there once the IP is up\n time.sleep(1)\n else:\n for x in v:\n print('Tagging volume ' + x.id + '.')\n _tag_resource(x)\n break","def snapshot(self, snapshot, keep=0):\n if keep:\n until = util.today() + datetime.timedelta(days=keep)\n snapshot = snapshot + \"-keep-until-\" + until.strftime(\"%Y%m%d\")\n if snapshot in [x.snapname for x in self.ceph.root.snapshots]:\n self.log.info(\"snapshot-exists\", snapshot=snapshot)\n return\n self.log.info(\"snapshot-create\", name=snapshot)\n with self.frozen_vm() as frozen:\n if frozen:\n self.ceph.root.snapshots.create(snapshot)\n else:\n self.log.error(\"snapshot-ignore\", reason=\"not frozen\")\n raise RuntimeError(\"VM not frozen, not making snapshot.\")","def test_migrate_volume(self, volume, volumes_steps):\n old_host, _ = volumes_steps.migrate_volume(volume.name)\n volumes_steps.migrate_volume(volume.name, old_host)","def test_volumes_get(self):\n pass","def snapshot(self, name):\r\n return self.driver.create_volume_snapshot(volume=self, name=name)","def test_delete_snapshot(self):\n ctxt = context.get_admin_context()\n extra_specs = {}\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\n snapshot = {'id': '1', 'name': 'volume1',\n 'display_name': '',\n 'volume_type_id': type_ref['id'],\n 'size': 10,\n 'provider_id': 'snap10'}\n self.driver.delete_snapshot(snapshot)\n expected = {'name': 'snap10'}\n self.assertDictMatch(expected, self.deleted)","def test_retype_setup_fail_volume_is_available(self, mock_notify):\n elevated = context.get_admin_context()\n project_id = self.context.project_id\n\n db.volume_type_create(elevated, {'name': 'old', 'extra_specs': {}})\n old_vol_type = db.volume_type_get_by_name(elevated, 'old')\n db.volume_type_create(elevated, {'name': 'new', 'extra_specs': {}})\n new_vol_type = db.volume_type_get_by_name(elevated, 'new')\n db.quota_create(elevated, project_id, 'volumes_new', 0)\n\n volume = tests_utils.create_volume(self.context, size=1,\n host=CONF.host, status='available',\n volume_type_id=old_vol_type['id'])\n\n api = cinder.volume.api.API()\n self.assertRaises(exception.VolumeLimitExceeded, api.retype,\n self.context, volume, new_vol_type['id'])\n\n volume = db.volume_get(elevated, volume.id)\n # FIXME: restore when Bug #1803648 is figured out\n # mock_notify.assert_not_called()\n self.assertEqual('available', volume['status'])","def issnapshot_available(self, item_name):\n return False","def test_aws_service_api_volume_patch(self):\n pass","def _assert_source_detached(self, volume):\n if (volume['status'] != \"available\" or\n volume['attach_status'] == fields.VolumeAttachStatus.ATTACHED):\n LOG.error(\"Volume must be detached for clone operation.\")\n raise exception.VolumeAttached(volume_id=volume['id'])","def show_volume_snapshot(self, snapshot, check=True):\n cmd = 'cinder snapshot-show ' + snapshot.id\n\n exit_code, stdout, stderr = self.execute_command(\n cmd, timeout=config.SNAPSHOT_SHOW_TIMEOUT, check=check)\n\n snapshot_table = output_parser.table(stdout)\n show_result = {key: value for key, value in snapshot_table['values']}\n\n if check:\n assert_that(show_result['id'], is_(snapshot.id))\n if snapshot.name:\n assert_that(show_result['name'], is_(snapshot.name))\n if snapshot.description:\n assert_that(show_result['description'],\n is_(snapshot.description))","def test_07_migrate_vm_live_with_snapshots(self):\n global vm\n # Get ROOT Volume\n vol_for_snap = list_volumes(\n self.apiclient,\n virtualmachineid=vm.id,\n listall=True)\n for vol in vol_for_snap:\n snapshot = Snapshot.create(\n self.apiclient,\n volume_id=vol.id\n )\n snapshot.validateState(\n self.apiclient,\n snapshotstate=\"backedup\",\n )\n # Migrate all volumes and VMs\n\n destinationHost, vol_list = self.helper.get_destination_pools_hosts(self.apiclient, vm, self.host)\n for v in vol_list:\n self.helper.check_storpool_volume_iops(self.spapi, v)\n vm = self.helper.migrateVm(self.apiclient, self.virtual_machine_live_migration_1, destinationHost)\n\n destinationHost, vol_list = self.helper.get_destination_pools_hosts(self.apiclient, vm, self.host)\n for v in vol_list:\n self.helper.check_storpool_volume_iops(self.spapi, v)","def test_least_busy_host_gets_volume(self):\n volume1 = self.start_service('volume', host='host1')\n volume2 = self.start_service('volume', host='host2')\n volume_id1 = self._create_volume()\n volume1.create_volume(self.context, volume_id1)\n volume_id2 = self._create_volume()\n host = self.scheduler.driver.schedule_create_volume(self.context,\n volume_id2)\n self.assertEqual(host, 'host2')\n volume1.delete_volume(self.context, volume_id1)\n db.volume_destroy(self.context, volume_id2)\n volume1.kill()\n volume2.kill()","def test_update_volume_stats_error(self):\n self._fail_host_storage = True\n actual = self.driver.get_volume_stats(True)\n self.assertEqual('HGST', actual['vendor_name'])\n self.assertEqual('hgst', actual['storage_protocol'])\n self.assertEqual('unknown', actual['total_capacity_gb'])\n self.assertEqual('unknown', actual['free_capacity_gb'])\n self.assertEqual(0, actual['reserved_percentage'])","def check_volume(vol, srf_names, verbose=True):\n if verbose:\n print(\" checking volume for validity\")\n print(\" ----------------------------\")\n # check if dict\n if not isinstance(vol, dict):\n if verbose:\n print(\" vol is not of type dict\")\n return False\n # check for keys in gli dict\n in_vol_keys = set(vol)\n if in_vol_keys == VOL_KEYS:\n if verbose:\n print(\" vol keys are valid\")\n else:\n if verbose:\n print(\" vol keys are not valid!\")\n print(\" needs: \" + \" \".join(VOL_KEYS))\n print(\" found: \" + \" \".join(map(str, in_vol_keys)))\n print(\" missing: \" + \" \".join(map(str, VOL_KEYS - in_vol_keys)))\n print(\" corrupted: \" + \" \".join(map(str, in_vol_keys - VOL_KEYS)))\n return False\n # check NAME\n if (\n isinstance(vol[\"NAME\"], STRTYPE)\n and not has_whitespaces(vol[\"NAME\"])\n and len(vol[\"NAME\"]) > 0\n ):\n if verbose:\n print(\" vol['NAME'] valid\")\n print(\" NAME: '\" + vol[\"NAME\"] + \"'\")\n else:\n if verbose:\n print(\" vol['NAME'] not valid\")\n return False\n # check SURFACES\n if (\n isinstance(vol[\"SURFACES\"], list)\n and len(vol[\"SURFACES\"]) > 0\n and all(srf in srf_names for srf in vol[\"SURFACES\"])\n ):\n if verbose:\n print(\" vol['SURFACES'] valid\")\n else:\n if verbose:\n print(\" vol['SURFACES'] not valid\")\n return False\n # check TYPE\n if vol[\"TYPE\"] is None or isinstance(vol[\"TYPE\"], int):\n if verbose:\n print(\" vol['TYPE'] valid\")\n else:\n if verbose:\n print(\" vol['TYPE'] not valid\")\n return False\n # check MAT_GROUP\n if vol[\"MAT_GROUP\"] is None or isinstance(vol[\"MAT_GROUP\"], int):\n if verbose:\n print(\" vol['MAT_GROUP'] valid\")\n else:\n if verbose:\n print(\" vol['MAT_GROUP'] not valid\")\n return False\n # check LAYER\n if vol[\"LAYER\"] is None or isinstance(vol[\"LAYER\"], int):\n if verbose:\n print(\" vol['LAYER'] valid\")\n else:\n if verbose:\n print(\" vol['LAYER'] not valid\")\n return False\n # finally\n if verbose:\n print(\" ------------\")\n print(\" vol is valid\")\n print(\"\")\n return True","def create_snapshot(self, volume_id, notes='No longer needed'):\r\n\r\n self.iscsi_svc.createSnapshot(notes, id=volume_id)","def creation_validation(**_):\n\n for property_key in constants.VOLUME_REQUIRED_PROPERTIES:\n utils.validate_node_property(property_key, ctx.node.properties)\n\n volume_object = _get_volumes_from_id(utils.get_resource_id())\n\n if ctx.node.properties['use_external_resource'] and not volume_object:\n raise NonRecoverableError(\n 'External resource, but the supplied '\n 'EBS volume does not exist in the account.')\n\n if not ctx.node.properties['use_external_resource'] and volume_object:\n raise NonRecoverableError(\n 'Not external resource, but the supplied '\n 'EBS volume exists in the account.')","def volumes(self):","def get_snapshots(self):\r\n ec2 = self.get_ec2_connection()\r\n rs = ec2.get_all_snapshots()\r\n all_vols = [self.volume_id] + self.past_volume_ids\r\n snaps = []\r\n for snapshot in rs:\r\n if snapshot.volume_id in all_vols:\r\n if snapshot.progress == '100%':\r\n snapshot.date = dateutil.parser.parse(snapshot.start_time)\r\n snapshot.keep = True\r\n snaps.append(snapshot)\r\n snaps.sort(cmp=lambda x,y: cmp(x.date, y.date))\r\n return snaps","def test_least_busy_host_gets_volume_no_queue(self):\n volume1 = service.Service('host1',\n 'nova-volume',\n 'volume',\n FLAGS.volume_manager)\n volume1.start()\n volume2 = service.Service('host2',\n 'nova-volume',\n 'volume',\n FLAGS.volume_manager)\n volume2.start()\n volume_id1 = self._create_volume()\n volume1.create_volume(self.context, volume_id1)\n volume_id2 = self._create_volume()\n host = self.scheduler.driver.schedule_create_volume(self.context,\n volume_id2)\n self.assertEqual(host, 'host2')\n volume1.delete_volume(self.context, volume_id1)\n db.volume_destroy(self.context, volume_id2)","def test_no_snapshots(self):\n def get_snapshots(*_args, **_kwargs):\n return {}\n self.mock(snapshots.gce.Project, 'get_snapshots', get_snapshots)\n\n key = self.create_entity('project', 'name', ['key:value'])\n urls = snapshots.fetch(key)\n self.failIf(urls)","def volume_exists(vil, vol_name):\n\n exists = False\n try:\n if not vil:\n vil, err = get_basic_volume_info_all()\n if err:\n raise Exception(err)\n if vil:\n for v in vil:\n if v[\"name\"] == vol_name:\n exists = True\n except Exception, e:\n return False, 'Error checking for volume existance : %s' % str(e)\n else:\n return exists, None","def test_update_volume_stats_cached(self):\n self._fail_host_storage = True\n actual = self.driver.get_volume_stats(False)\n self.assertEqual('HGST', actual['vendor_name'])\n self.assertEqual('hgst', actual['storage_protocol'])\n self.assertEqual(90, actual['total_capacity_gb'])\n self.assertEqual(87, actual['free_capacity_gb'])\n self.assertEqual(0, actual['reserved_percentage'])","def _wait_until_volume_available(self, volume, maybe_in_use=False):\n ok_states = [\"creating\"] # it's ok to wait if the volume is in this\n tries = 0\n if maybe_in_use:\n ok_states.append(\"in_use\")\n logger.info(\"Volume: %s is in state: %s\", volume.name, volume.state)\n while volume.state in ok_states:\n sleep(3)\n volume = self.get_volume(volume.name)\n tries = tries + 1\n if tries > 10:\n logger.info(\"Maximum amount of tries reached..\")\n break\n if volume.state == \"notfound\":\n logger.error(\"no volume was found for: %s\", volume.name)\n break\n logger.info(\" ... %s\", volume.state)\n if volume.state != \"available\":\n # OVH uses a non-standard state of 3 to indicate an available\n # volume\n logger.info(\"Volume %s is %s (not available)\", volume.name, volume.state)\n logger.info(\n \"The volume %s is not available, but will continue anyway...\",\n volume.name,\n )\n return True","def test_06_create_snapshots_in_project(self):\n # Validate the following\n # 1. Create a project\n # 2. Add some snapshots to the project\n # 3. Verify snapshot created inside project can only be used in inside\n # the project\n\n if not self.snapshotSupported:\n self.skipTest(\"Snapshot is not supported on %s\" % self.hypervisor)\n\n self.debug(\"Deploying VM for Project: %s\" % self.project.id)\n virtual_machine_1 = VirtualMachine.create(\n self.apiclient,\n self.services[\"server\"],\n templateid=self.template.id,\n serviceofferingid=self.service_offering.id,\n projectid=self.project.id\n )\n self.cleanup.append(virtual_machine_1)\n # Verify VM state\n self.assertEqual(\n virtual_machine_1.state,\n 'Running',\n \"Check VM state is Running or not\"\n )\n\n # Get the Root disk of VM\n volumes = list_volumes(\n self.apiclient,\n projectid=self.project.id,\n type='ROOT',\n listall=True\n )\n self.assertEqual(\n isinstance(volumes, list),\n True,\n \"Check for list volume response return valid data\"\n )\n\n self.debug(\"Creating snapshot from volume: %s\" % volumes[0].id)\n # Create a snapshot from the ROOTDISK\n snapshot = Snapshot.create(self.apiclient,\n volumes[0].id,\n projectid=self.project.id\n )\n self.cleanup.append(snapshot)\n # Verify Snapshot state\n self.assertEqual(\n snapshot.state in [\n 'BackedUp',\n 'CreatedOnPrimary',\n 'Allocated'\n ],\n True,\n \"Check Snapshot state is in one of the mentioned possible states, \\\n It is currently: %s\" % snapshot.state\n )\n\n snapshots = Snapshot.list(\n self.apiclient,\n account=self.account.name,\n domainid=self.account.domainid\n )\n self.assertEqual(\n snapshots,\n None,\n \"Snapshots should not be available outside the project\"\n )\n return","def sync_volume_record( volume ):\n \n logger.info( \"Sync Volume = %s\\n\\n\" % volume.name )\n \n principal_id = volume.owner_id.email\n config = observer_core.get_config()\n \n max_UGs = None \n max_RGs = None\n volume_principal_id = observer_core.make_volume_principal_id( principal_id, volume.name )\n\n # get the observer secret \n try:\n max_UGs = CONFIG.SYNDICATE_UG_QUOTA \n max_RGs = CONFIG.SYNDICATE_RG_QUOTA\n observer_secret = observer_core.get_syndicate_observer_secret( config.SYNDICATE_OBSERVER_SECRET )\n except Exception, e:\n traceback.print_exc()\n logger.error(\"config is missing SYNDICATE_OBSERVER_SECRET, SYNDICATE_UG_QUOTA, SYNDICATE_RG_QUOTA\")\n raise e\n \n # volume owner must exist as a Syndicate user...\n try:\n rc, user = observer_core.ensure_principal_exists( volume_principal_id, observer_secret, is_admin=False, max_UGs=max_UGs, max_RGs=max_RGs)\n assert rc == True, \"Failed to create or read volume principal '%s'\" % volume_principal_id\n except Exception, e:\n traceback.print_exc()\n logger.error(\"Failed to ensure principal '%s' exists\" % volume_principal_id )\n raise e\n\n # volume must exist \n # create or update the Volume\n try:\n new_volume = observer_core.ensure_volume_exists( volume_principal_id, volume, user=user )\n except Exception, e:\n traceback.print_exc()\n logger.error(\"Failed to ensure volume '%s' exists\" % volume.name )\n raise e\n \n # did we create the Volume?\n if new_volume is not None:\n # we're good\n pass \n \n # otherwise, just update it \n else:\n try:\n rc = observer_core.update_volume( volume )\n except Exception, e:\n traceback.print_exc()\n logger.error(\"Failed to update volume '%s', exception = %s\" % (volume.name, e.message))\n raise e\n \n return True","def snapshots(self, owner=None, restorable_by=None):\r\n rs = self.connection.get_all_snapshots(owner=owner,\r\n restorable_by=restorable_by)\r\n mine = []\r\n for snap in rs:\r\n if snap.volume_id == self.id:\r\n mine.append(snap)\r\n return mine","def delete_volume_snapshot(volume_snapshots):\n if type(volume_snapshots) is not list:\n volumes = [volume_snapshots]\n command = 'cinder snapshot-delete %s' % \\\n \" \".join(snapshot['id'] for snapshot in volume_snapshots)\n d = Popen(command.split(), stdout=STDOUT, stderr=STDERR).communicate()[0]","def ensure_export(self, context, volume):\n pass","def test_snapshot_unspecified(self):\n key = self.create_entity('project', None, [])\n urls = snapshots.fetch(key)\n self.failIf(urls)","def ensure_volume_exists( user_email, opencloud_volume, user=None ):\n client = connect_syndicate()\n\n try:\n volume = client.read_volume( opencloud_volume.name )\n except Exception, e:\n # transport error \n logger.exception(e)\n raise e\n\n if volume is None:\n # the volume does not exist....try to create it \n vol_name = opencloud_volume.name\n vol_blocksize = opencloud_volume.blocksize\n vol_description = opencloud_volume.description\n vol_private = opencloud_volume.private\n vol_archive = opencloud_volume.archive \n vol_default_gateway_caps = opencloud_caps_to_syndicate_caps( opencloud_volume.cap_read_data, opencloud_volume.cap_write_data, opencloud_volume.cap_host_data )\n\n try:\n vol_info = client.create_volume( user_email, vol_name, vol_description, vol_blocksize,\n private=vol_private,\n archive=vol_archive,\n active=True,\n default_gateway_caps=vol_default_gateway_caps,\n store_private_key=False,\n metadata_private_key=\"MAKE_METADATA_KEY\" )\n\n except Exception, e:\n # transport error\n logger.exception(e)\n raise e\n\n else:\n # successfully created the volume!\n return vol_info\n\n else:\n \n # volume already exists. Verify its owned by this user.\n if user is None:\n try:\n user = client.read_user( volume['owner_id'] )\n except Exception, e:\n # transport error, or user doesn't exist (either is unacceptable)\n logger.exception(e)\n raise e\n\n if user is None or user['email'] != user_email:\n raise Exception(\"Volume '%s' already exists, but is NOT owned by '%s'\" % (opencloud_volume.name, user_email) )\n\n # we're good!\n return None","def test_attachment_create_volume_in_error_state(self):\n volume_params = {'status': 'available'}\n\n vref = tests_utils.create_volume(self.context, **volume_params)\n vref.status = \"error\"\n self.assertRaises(exception.InvalidVolume,\n self.volume_api.attachment_create,\n self.context,\n vref,\n fake.UUID2)","def create(self, filesystem=None):\n if not self.size and not self.from_snapshot_id and not self.from_archive:\n log.error('Cannot add a {0} volume without a size, snapshot ID or '\n 'archive url; aborting.'.format(self.fs))\n return False\n # If creating the volume from a snaphost, get the expected volume size\n if self.from_snapshot_id and not self.volume:\n self.snapshot = self.app.cloud_interface.get_snapshot(self.from_snapshot_id)\n if not self.snapshot:\n log.error(\"Did not retrieve Snapshot object for {0}; aborting.\"\n .format(self.from_snapshot_id))\n return False\n # We need a size to be able to create a volume, so if none\n # is specified, use snapshot size\n if not self.size:\n si = self.app.cloud_interface.get_snapshot_info(self.from_snapshot_id)\n self.size = si.get('volume_size')\n # If it does not already exist, create the volume\n if self.status == volume_status.NONE:\n log.debug(\"Creating a new volume of size '%s' in zone '%s' from \"\n \"snapshot '%s' for %s.\"\n % (self.size, self.app.cloud_interface.get_zone(),\n self.from_snapshot_id, self.fs))\n self.volume = self.app.cloud_interface.create_volume(\n self.size,\n self.app.cloud_interface.get_zone(),\n snapshot=self.from_snapshot_id)\n if self.volume:\n # When creating from a snapshot in Euca, volume.size may be None\n self.size = int(self.volume.size or 0)\n log.debug(\"Created a new volume of size '%s' from snapshot '%s' \"\n \"with ID '%s' in zone '%s' for %s.\"\n % (self.size, self.from_snapshot_id, self.volume_id,\n self.app.cloud_interface.get_zone(), self.fs))\n else:\n log.warning(\"No volume object - did not create a volume?\")\n return False\n else:\n log.debug(\"Tried to create a volume for %s but it is in state '%s' \"\n \"(volume ID: %s)\" % (self.fs, self.status, self.volume_id))\n return False\n # Add tags to newly created volumes (do this outside the inital if/else\n # to ensure the tags get assigned even if using an existing volume vs.\n # creating a new one)\n self.app.cloud_interface.add_tag(\n self.volume, 'Name', self.app.config['cluster_name'])\n self.app.cloud_interface.add_tag(\n self.volume, 'bucketName', self.app.config['bucket_cluster'])\n if self.fs:\n self.app.cloud_interface.add_tag(\n self.volume, 'filesystem', self.fs.get_full_name())\n self.app.cloud_interface.add_tag(\n self.volume, 'roles', ServiceRole.to_string(self.fs.svc_roles))\n return True","def volume_in_use(self):\n return self._volume_status_check(STATUS_IN_USE, False, 0, 0)","def verify_no_snapshot_reingestion(c: Composition) -> None:\n c.run(\"testdrive\", \"wait-for-snapshot.td\", \"postgres-disable-select-permission.td\")\n\n restart_mz(c)\n\n c.run(\n \"testdrive\",\n \"delete-rows-t1.td\",\n \"delete-rows-t2.td\",\n \"alter-table.td\",\n \"alter-mz.td\",\n )","def snap_status(mnode, snapname=\"\", volname=\"\"):\n\n if snapname != \"\" and volname != \"\":\n g.log.error(\"Incorrect cmd. snap status cli accepts either \"\n \"snapname or volname\")\n return (-1, None, None)\n\n if volname != '':\n volname = \"volume %s\" % volname\n\n cmd = \"gluster snapshot status %s %s\" % (snapname, volname)\n return g.run(mnode, cmd)","def test_volume_extend(self, volume, volumes_steps):\n volumes_steps.extend_volume(volume.name)","def test_aws_service_api_volumes_get(self):\n pass","def migrate_volume(self, volume, host):\n false_ret = (False, None)\n if volume['attach_status'] == fields.VolumeAttachStatus.ATTACHED:\n return false_ret\n if 'location_info' not in host['capabilities']:\n return false_ret\n info = host['capabilities']['location_info']\n try:\n (dest_type, dest_id,\n dest_back_name, dest_owner) = info.split(':')\n except ValueError:\n return false_ret\n\n reqd_dest_type = '%sVolumeDriver' % self.vendor_name\n if not (dest_type == reqd_dest_type and\n dest_id == self.serialNumber and\n dest_owner == self.owner):\n return false_ret\n if volume['name_id']:\n source_name = self._get_vol_name(volume['name_id'])\n else:\n source_name = self._get_vol_name(volume['id'])\n # the array does not support duplicate names\n dest_name = \"m%s\" % source_name[1:]\n\n self.client_login()\n try:\n self.client.copy_volume(source_name, dest_name,\n dest_back_name, self.backend_type)\n self.client.delete_volume(source_name)\n self.client.modify_volume_name(dest_name, source_name)\n return (True, None)\n except stx_exception.RequestError as ex:\n LOG.exception(\"Error migrating volume: %s\", source_name)\n raise exception.Invalid(ex)\n finally:\n self.client_logout()","def booted_from_volume(volumes_list):\n if any('/dev/vda' in volume['attachments'] for volume in\n volumes_list):\n return True\n return False","def test_delete_source_volume_in_migration(self):\n self._test_delete_volume_in_migration('migrating')","def manage(self, volume_id, ref, name=None, description=None,\n metadata=None):\n body = {'snapshot': {'volume_id': volume_id,\n 'ref': ref,\n 'name': name,\n 'description': description,\n 'metadata': metadata\n }\n }\n return self._create('/os-snapshot-manage', body, 'snapshot')","def check_snapshots(grafana_server):\n print(info + \" Checking if snapshot api requires authentiation...\" + end)\n \n response = send_request(grafana_server+\"/api/snapshots\", \"POST\")\n \n if (response) == 401:\n print(bad + \" Snapshot endpoint requires authentication! Host not vulnerable.\" + end)\n elif (response) == 415:\n print(good + \" Snapshot endpoint doesn't seem to require authentication! Host may be vulnerable.\" + end)\n else:\n print(info + \" Didn't received expected status code when checking snapshot API. Check again.\" + end)\n\n return","def bootable_volume(volumes):\n for volume in volumes:\n if '/dev/vda' in volume['attachments']:\n return volume","def database_volume_snapshot_delete(volume_snapshot_uuid):\n db = database_get()\n session = db.session()\n query = session.query(model.VolumeSnapshot)\n query.filter(model.VolumeSnapshot.uuid == volume_snapshot_uuid).delete()\n session.commit()","def test_aws_service_api_snapshots_get(self):\n pass","def test_create_volume(self, mock_ghn):\n ctxt = context.get_admin_context()\n extra_specs = {}\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\n volume = {'id': '1', 'name': 'volume1',\n 'display_name': '',\n 'volume_type_id': type_ref['id'],\n 'size': 10}\n ret = self.driver.create_volume(volume)\n expected = {'redundancy': '0', 'group': 'xanadu',\n 'name': 'volume10', 'mode': '0777',\n 'user': 'kane', 'net': 'net1',\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\n 'size': '12'}\n self.assertDictMatch(expected, self.created)\n # Check the returned provider, note that provider_id is hashed\n expected_pid = {'provider_id': 'volume10'}\n self.assertDictMatch(expected_pid, ret)","def find_recovery_on_volume(volume):\n return _find(volume, RECOVERY_ON_VOLUME_TABLE)","def test_snapshot_compatibility(microvm_factory, guest_kernel, rootfs):\n vm = microvm_factory.build(guest_kernel, rootfs)\n vm.spawn()\n vm.basic_config(\n vcpu_count=2,\n mem_size_mib=256,\n )\n\n # Add a memory balloon with stats enabled.\n vm.api.balloon.put(amount_mib=0, deflate_on_oom=True, stats_polling_interval_s=1)\n\n vm.start()\n vm.snapshot_full()","def test_update_volume_stats(self):\n actual = self.driver.get_volume_stats(True)\n self.assertEqual('HGST', actual['vendor_name'])\n self.assertEqual('hgst', actual['storage_protocol'])\n self.assertEqual(90, actual['total_capacity_gb'])\n self.assertEqual(87, actual['free_capacity_gb'])\n self.assertEqual(0, actual['reserved_percentage'])","def test_snapshots_size(self):\n snapshots_dir = REPO_ROOT / \"tests\" / \"snapshots\"\n small_snapshots = []\n for f in snapshots_dir.glob(\"*.txt\"):\n if f.stat().st_size <= 150:\n small_snapshots.append(f\"- {f.name}\")\n if small_snapshots:\n offenders = \"\\n\".join(small_snapshots)\n assert False, (\n \"Very small snapshot files are problematic.\\n\"\n \"Offending snapshot files:\\n\"\n f\"{offenders}\\n\"\n \"Consider refacotring them to avoid using snapshots. Tests that use \"\n \"snapshots are harder to reason about when they fail. Whenever possilbe \"\n \"a test with inline data is much easier to reason about and refactor.\"\n )","def execute(self):\n\n c = self.config\n regions = dict((x.name, x) for x in boto.ec2.regions(\n aws_access_key_id=c['access_key'],\n aws_secret_access_key=c['secret_access_key']))\n connect = regions[c['region']].connect(\n aws_access_key_id=c['access_key'],\n aws_secret_access_key=c['secret_access_key'])\n volume = connect.get_all_volumes([c['volume_id']])[0]\n volume.create_snapshot(c['volume_id'])\n snapshots = {}\n for x in connect.get_all_snapshots():\n if x.volume_id == c['volume_id']:\n snapshots.update({x.id: x.start_time})\n snapshots = sorted(snapshots.items(), key=lambda (k, v): (v, k), reverse=True)\n for i in range(int(c['keep']), len(snapshots)):\n connect.delete_snapshot(snapshots[i][0])","def create_snapshot(volume_name, volume_id):\n\tif cliargs.verbose:\n\t\tprint \"Will snapshot '%s' and tag it with '%s'\" % (volume_id, volume_name)\n\n\tresponse = ec2.create_snapshot(VolumeId=volume_id, Description=volume_name)\n\tif response:\n\t\tec2.create_tags(Resources=[response[\"SnapshotId\"]], Tags=[{\"Key\": \"Name\", \"Value\": volume_name}])","def checkForVolumeWarnings(self,master,merge):\n warnings = \"\"\n if not master:\n warnings = \"Missing master volume\"\n if merge:\n if not master.GetImageData() or not merge.GetImageData():\n return \"Missing image data\"\n if master.GetImageData().GetDimensions() != merge.GetImageData().GetDimensions():\n warnings += \"Volume dimensions do not match\\n\"\n if master.GetImageData().GetSpacing() != merge.GetImageData().GetSpacing():\n warnings += \"Volume spacings do not match\\n\"\n if master.GetImageData().GetOrigin() != merge.GetImageData().GetOrigin():\n warnings += \"Volume spacings do not match\\n\"\n # if merge.GetScalarType() != vtk.VTK_SHORT:\n # warnings += \"Label map must be of type Short (Use Cast Scalar Volume to fix)\\n\"\n # if master.GetLabelMap():\n # if master.GetImageData().GetScalarType() != vtk.VTK_SHORT:\n # warnings += \"Label map must be of type Short (Use Cast Scalar Volume to fix)\\n\"\n masterIJKToRAS = vtk.vtkMatrix4x4()\n mergeIJKToRAS = vtk.vtkMatrix4x4()\n master.GetIJKToRASMatrix(masterIJKToRAS)\n merge.GetIJKToRASMatrix(mergeIJKToRAS)\n for row in range(4):\n for column in range(4):\n if masterIJKToRAS.GetElement(row,column) != mergeIJKToRAS.GetElement(row,column):\n warnings += \"Volume geometry does not match (Resample to fix)\\n\"\n print(\"coor: \" + str(row) + \" \" + str(column) + \" \" + str(masterIJKToRAS.GetElement(row,column)) + \" \" + str(mergeIJKToRAS.GetElement(row,column)))\n break\n else:\n warnings += \"Missing merge volume\"\n return warnings","def create_snapshot(args, **_):\n\n volume_id = \\\n utils.get_external_resource_id_or_raise(\n 'create snapshot', ctx.instance)\n\n ctx.logger.info(\n 'Trying to create a snapshot of EBS volume {0}.'\n .format(volume_id))\n\n volume_object = _get_volumes_from_id(volume_id)\n\n if not args:\n snapshot_desc = \\\n unicode(datetime.datetime.now()) + \\\n ctx.instance.runtime_properties[constants.EXTERNAL_RESOURCE_ID]\n args = dict(description=snapshot_desc)\n\n try:\n new_snapshot = volume_object.create_snapshot(**args)\n except (boto.exception.EC2ResponseError,\n boto.exception.BotoServerError) as e:\n raise NonRecoverableError('{0}'.format(str(e)))\n\n ctx.logger.info(\n 'Created snapshot of EBS volume {0}.'.format(volume_id))\n\n if constants.VOLUME_SNAPSHOT_ATTRIBUTE not in \\\n ctx.instance.runtime_properties:\n ctx.instance.runtime_properties[\n constants.VOLUME_SNAPSHOT_ATTRIBUTE] = list()\n\n ctx.instance.runtime_properties[\n constants.VOLUME_SNAPSHOT_ATTRIBUTE].append(new_snapshot.id)","def _create_snapshot(connection, volume, name=''):\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", \"creating new snapshot\", {\"volume\": volume.id}))\n snapshot = volume.create_snapshot(\n description=\"automatic snapshot by ebs-snapshots\")\n if not name:\n name = '{}-snapshot'.format(volume.id)\n connection.create_tags(\n [snapshot.id], dict(Name=name, creator='ebs-snapshots'))\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", \"created snapshot successfully\", {\n \"name\": name,\n \"volume\": volume.id,\n \"snapshot\": snapshot.id\n }))\n return snapshot","def derived_snapshots(self):\n start_time = time.time()\n log.debug(\"Getting snaps derived from volume {0}.\".format(self.volume_id))\n derived_snapshots = []\n for snap in self.app.cloud_interface.get_all_snapshots():\n try:\n if snap.volume_id == self.volume_id:\n derived_snapshots.append(snap)\n except EC2ResponseError, e:\n log.warning(\"EC2ResponseError getting snapshot status: {0} \"\n \"(code {1}; status {2})\"\n .format(e.message, e.error_code, e.status))\n log.debug(\"Got snaps derived from volume {0} in {1} seconds: {2}\"\n .format(self.volume_id, time.time() - start_time, derived_snapshots))\n return derived_snapshots","def test_csi_volumesnapshot_basic(set_random_backupstore, # NOQA\n volumesnapshotclass, # NOQA\n volumesnapshot, # NOQA\n client, # NOQA\n core_api, # NOQA\n volume_name, # NOQA\n csi_pv, # NOQA\n pvc, # NOQA\n pod_make, # NOQA\n volsnapshotclass_delete_policy, # NOQA\n backup_is_deleted): # NOQA\n\n csisnapclass = \\\n volumesnapshotclass(name=\"snapshotclass\",\n deletepolicy=volsnapshotclass_delete_policy)\n\n pod_name, pv_name, pvc_name, md5sum = \\\n prepare_pod_with_data_in_mb(client, core_api,\n csi_pv, pvc, pod_make,\n volume_name,\n data_path=\"/data/test\")\n\n # Create volumeSnapshot test\n csivolsnap = volumesnapshot(volume_name + \"-volumesnapshot\",\n \"default\",\n csisnapclass[\"metadata\"][\"name\"],\n \"persistentVolumeClaimName\",\n pvc_name)\n\n volume = client.by_id_volume(volume_name)\n\n for i in range(RETRY_COUNTS):\n snapshots = volume.snapshotList()\n if len(snapshots) == 2:\n break\n time.sleep(RETRY_INTERVAL)\n\n lh_snapshot = None\n snapshots = volume.snapshotList()\n for snapshot in snapshots:\n if snapshot[\"name\"] == \"snapshot-\" + csivolsnap[\"metadata\"][\"uid\"]:\n lh_snapshot = snapshot\n assert lh_snapshot is not None\n\n wait_for_volumesnapshot_ready(csivolsnap[\"metadata\"][\"name\"],\n csivolsnap[\"metadata\"][\"namespace\"])\n\n bv1, b = find_backup(client, volume_name, lh_snapshot[\"name\"])\n\n assert b[\"snapshotName\"] == lh_snapshot[\"name\"]\n\n restore_pvc_name = pvc[\"metadata\"][\"name\"] + \"-restore\"\n restore_pvc_size = pvc[\"spec\"][\"resources\"][\"requests\"][\"storage\"]\n\n restore_csi_volume_snapshot(core_api,\n client,\n csivolsnap,\n restore_pvc_name,\n restore_pvc_size)\n\n restore_pod = pod_make()\n restore_pod_name = restore_pod[\"metadata\"][\"name\"]\n restore_pod['spec']['volumes'] = [create_pvc_spec(restore_pvc_name)]\n\n create_and_wait_pod(core_api, restore_pod)\n restore_md5sum = \\\n get_pod_data_md5sum(core_api, restore_pod_name, path=\"/data/test\")\n assert restore_md5sum == md5sum\n\n # Delete volumeSnapshot test\n delete_volumesnapshot(csivolsnap[\"metadata\"][\"name\"], \"default\")\n\n if backup_is_deleted is False:\n find_backup(client, volume_name, b[\"snapshotName\"])\n else:\n wait_for_backup_delete(client, volume_name, b[\"name\"])","def _attach_volume(self):\n return []","def test_finish_resize_with_volumes(self):\n\n # create instance\n instance = self._create_fake_instance_obj()\n request_spec = objects.RequestSpec()\n\n # create volume\n volume = {'instance_uuid': None,\n 'device_name': None,\n 'id': uuids.volume,\n 'size': 200,\n 'attach_status': 'detached'}\n bdm = objects.BlockDeviceMapping(\n **{'context': self.context,\n 'source_type': 'volume',\n 'destination_type': 'volume',\n 'volume_id': uuids.volume,\n 'instance_uuid': instance['uuid'],\n 'device_name': '/dev/vdc'})\n bdm.create()\n\n # stub out volume attach\n def fake_volume_get(self, context, volume_id, microversion=None):\n return volume\n self.stub_out('nova.volume.cinder.API.get', fake_volume_get)\n\n def fake_volume_check_availability_zone(self, context,\n volume_id, instance):\n pass\n self.stub_out('nova.volume.cinder.API.check_availability_zone',\n fake_volume_check_availability_zone)\n\n def fake_get_volume_encryption_metadata(self, context, volume_id):\n return {}\n self.stub_out('nova.volume.cinder.API.get_volume_encryption_metadata',\n fake_get_volume_encryption_metadata)\n\n orig_connection_data = {\n 'target_discovered': True,\n 'target_iqn': 'iqn.2010-10.org.openstack:%s.1' % uuids.volume_id,\n 'target_portal': '127.0.0.0.1:3260',\n 'volume_id': uuids.volume_id,\n }\n connection_info = {\n 'driver_volume_type': 'iscsi',\n 'data': orig_connection_data,\n }\n\n def fake_init_conn(self, context, volume_id, session):\n return connection_info\n self.stub_out('nova.volume.cinder.API.initialize_connection',\n fake_init_conn)\n\n def fake_attach(self, context, volume_id, instance_uuid, device_name,\n mode='rw'):\n volume['instance_uuid'] = instance_uuid\n volume['device_name'] = device_name\n self.stub_out('nova.volume.cinder.API.attach', fake_attach)\n\n # stub out virt driver attach\n def fake_get_volume_connector(*args, **kwargs):\n return {}\n self.stub_out('nova.virt.fake.FakeDriver.get_volume_connector',\n fake_get_volume_connector)\n\n def fake_attach_volume(*args, **kwargs):\n pass\n self.stub_out('nova.virt.fake.FakeDriver.attach_volume',\n fake_attach_volume)\n\n # attach volume to instance\n self.compute.attach_volume(self.context, instance, bdm)\n\n # assert volume attached correctly\n self.assertEqual(volume['device_name'], '/dev/vdc')\n disk_info = db.block_device_mapping_get_all_by_instance(\n self.context, instance.uuid)\n self.assertEqual(len(disk_info), 1)\n for bdm in disk_info:\n self.assertEqual(bdm['device_name'], volume['device_name'])\n self.assertEqual(bdm['connection_info'],\n jsonutils.dumps(connection_info))\n\n # begin resize\n flavor = self.default_flavor\n instance.task_state = task_states.RESIZE_PREP\n instance.save()\n self.compute.prep_resize(self.context, instance=instance,\n flavor=flavor,\n image={}, request_spec=request_spec,\n filter_properties={}, node=None,\n clean_shutdown=True, migration=None,\n host_list=[])\n\n # fake out detach for prep_resize (and later terminate)\n def fake_terminate_connection(self, context, volume, connector):\n connection_info['data'] = None\n self.stub_out('nova.volume.cinder.API.terminate_connection',\n fake_terminate_connection)\n\n migration = objects.Migration.get_by_instance_and_status(\n self.context.elevated(),\n instance.uuid, 'pre-migrating')\n self.compute.resize_instance(self.context, instance=instance,\n migration=migration, image={},\n # TODO(stephenfin): Why a JSON string?\n flavor=jsonutils.to_primitive(flavor),\n clean_shutdown=True, request_spec=request_spec)\n\n # assert bdm is unchanged\n disk_info = db.block_device_mapping_get_all_by_instance(\n self.context, instance.uuid)\n self.assertEqual(len(disk_info), 1)\n for bdm in disk_info:\n self.assertEqual(bdm['device_name'], volume['device_name'])\n cached_connection_info = jsonutils.loads(bdm['connection_info'])\n self.assertEqual(cached_connection_info['data'],\n orig_connection_data)\n # but connection was terminated\n self.assertIsNone(connection_info['data'])\n\n # stub out virt driver finish_migration\n def fake(*args, **kwargs):\n pass\n self.stub_out('nova.virt.fake.FakeDriver.finish_migration', fake)\n\n instance.task_state = task_states.RESIZE_MIGRATED\n instance.save()\n\n # new initialize connection\n new_connection_data = dict(orig_connection_data)\n new_iqn = 'iqn.2010-10.org.openstack:%s.2' % uuids.volume_id,\n new_connection_data['target_iqn'] = new_iqn\n\n def fake_init_conn_with_data(self, context, volume, session):\n connection_info['data'] = new_connection_data\n return connection_info\n self.stub_out('nova.volume.cinder.API.initialize_connection',\n fake_init_conn_with_data)\n\n self.compute.finish_resize(self.context,\n migration=migration,\n disk_info={}, image={}, instance=instance,\n request_spec=request_spec)\n\n # assert volume attached correctly\n disk_info = db.block_device_mapping_get_all_by_instance(\n self.context, instance['uuid'])\n self.assertEqual(len(disk_info), 1)\n for bdm in disk_info:\n self.assertEqual(bdm['connection_info'],\n jsonutils.dumps(connection_info))\n\n # stub out detach\n def fake_detach(self, context, volume_uuid):\n volume['device_path'] = None\n volume['instance_uuid'] = None\n self.stub_out('nova.volume.cinder.API.detach', fake_detach)\n\n # clean up\n self.compute.terminate_instance(self.context, instance, [])","def setupVolumes(volumes: Volumes) -> None:\n volumesList = readProcessJson(\n [\"podman\", \"volume\", \"ls\", \"--format\", \"json\"])\n existingVolumes: Set[str] = set()\n if volumesList:\n for volume in volumesList:\n existingVolumes.add(volume['name'])\n for volume in volumes.values():\n if volume.name not in existingVolumes:\n log.info(f\"Creating volume {volume.name}\")\n execute([\"podman\", \"volume\", \"create\", volume.name])\n if volume.files:\n for file in volume.files:\n path = Path(\"~/.local/share/containers/storage/volumes/\"\n f\"{volume.name}/_data/{file.name}\").expanduser()\n if not path.exists():\n log.info(f\"Writting {path}\")\n path.write_text(file.content)","def load_snapshot_subhalos(base_path, snap_num, subvolumes, fields=None, matches=False):\n return load_snapshot(base_path, snap_num, subvolumes, \"Galprop\", fields, matches)","def setup_volumes():\n\n fix_path()\n\n # Get what we want from the ZK tree\n logical_volumes = {}\n expected_sdvols = set()\n f = open('/etc/zim/volumes')\n for line in f:\n line = line.strip()\n if not line:\n continue\n sdvols = line.split()\n mount_point = sdvols.pop(0)\n if len(sdvols) == 1:\n dev = sdvols[0]\n if dev[0] == '/':\n ln(mount_point, dev)\n else:\n single(mount_point, '/dev/'+dev)\n continue\n\n if len(sdvols) < 1:\n raise ValueError(line)\n\n if lvname(sdvols[0]):\n lvm(mount_point, sdvols)\n continue\n\n\n # RAID10:\n assert len(set(sdvol[:3] for sdvol in sdvols)) == 1, (\n \"Multiple device prefixes\")\n sdprefix = sdvols[0][:3]\n logical_volumes[sdprefix] = LogicalVolume(\n sdprefix, sdvols, mount_point)\n expected_sdvols.update(sdvols)\n\n if logical_volumes:\n\n # Wait for all of our expected sd volumes to appear. (They may be\n # attaching.)\n for v in expected_sdvols:\n wait_for_device('/dev/' + v)\n\n # The volumes may have been set up before on a previous machine.\n # Scan for them:\n s('mdadm --examine --scan >>/etc/mdadm.conf')\n f = open('/etc/mdadm.conf')\n if f.read().strip():\n s('mdadm -A --scan')\n f.close()\n\n # Read /proc/mdstat to find out about existing raid volumes:\n mdstat = re.compile(r'md(\\w+) : (\\w+) (\\w+) (.+)$').match\n mdstatsd = re.compile(r'(sd(\\w+))\\[\\d+\\](\\(F\\))?$').match\n for line in open('/proc/mdstat'):\n if not line.strip():\n continue\n m = mdstat(line)\n if not m:\n assert (line.startswith('Personalities') or\n line.startswith(' ') or\n line.startswith('unused devices')), (\n \"unexpected line\", line\n )\n continue\n mdnum, status, rtype, data = m.group(1, 2, 3, 4)\n data = [mdstatsd(d).groups() for d in data.strip().split()]\n\n assert not [d for d in data if d[2]], (\n \"Failed volume\", line\n )\n\n data = [d[0] for d in data]\n if not [d for d in data if d in expected_sdvols]:\n # Hm, not one weore interested in.\n print 'skipping', line\n continue\n\n assert not [d for d in data if d not in expected_sdvols], (\n \"Unexpected volume\", data\n )\n\n assert status == 'active', status\n assert rtype == 'raid10', rtype\n\n logical_volumes[data[0][:3]].add_md(mdnum, data)\n\n # Scan for logical volumes:\n lv_pat = re.compile('Found volume group \"vg_(sd\\w+)\"').search\n for line in p('vgscan'):\n m = lv_pat(line)\n if not m:\n continue\n name = m.group(1)\n if name in logical_volumes:\n logical_volumes[name].has_logical_volume()\n\n # Record the physical volums in each logical_volume so we can see\n # if any are missing:\n PV = re.compile(\"PV /dev/md(\\w+) +VG vg_(sd\\w+) \").search\n for line in p(\"pvscan\"):\n m = PV(line)\n if not m:\n continue\n mdnum, vgname = m.groups()\n logical_volumes[vgname].pvs.add(mdnum)\n\n # Finally, create any missing raid volumes and logical volumes\n for lv in logical_volumes.values():\n lv.setup()\n\n os.rename('/etc/zim/volumes', '/etc/zim/volumes-setup')","def test_upload_volume_to_image(self, volume, images_steps, volumes_steps):\n image_name = next(generate_ids('image', length=20))\n volumes_steps.upload_volume_to_image(volume.name, image_name)\n\n images_steps.page_images().table_images.row(\n name=image_name).wait_for_presence(30)\n images_steps.delete_image(image_name)","def perform_snapshot(context, region, installed_region='us-east-1'):\n LOG.info('Reviewing snapshots in region %s', region)\n\n # fetch these, in case we need to figure out what applies to an instance\n configurations = dynamo.list_configurations(context, installed_region)\n LOG.debug('Fetched all possible configuration rules from DynamoDB')\n\n # build a list of any IDs (anywhere) that we should ignore\n ignore_ids = utils.build_ignore_list(configurations)\n\n # setup some lookup tables\n cache_data = utils.build_cache_maps(context, configurations, region, installed_region)\n all_instances = cache_data['instance_id_to_data']\n instance_configs = cache_data['instance_id_to_config']\n volume_snap_recent = cache_data['volume_id_to_most_recent_snapshot_date']\n\n for instance_id in set(all_instances.keys()):\n # before we go do some work\n if timeout_check(context, 'perform_snapshot'):\n break\n\n if instance_id in ignore_ids:\n continue\n\n snapshot_settings = instance_configs[instance_id]\n\n # parse out snapshot settings\n retention, frequency = utils.parse_snapshot_settings(snapshot_settings)\n\n # grab the data about this instance id, if we don't already have it\n instance_data = all_instances[instance_id]\n\n ami_id = instance_data['ImageId']\n LOG.info('Reviewing snapshots in region %s on instance %s', region, instance_id)\n\n for dev in instance_data.get('BlockDeviceMappings', []):\n # before we go make a bunch more API calls\n if timeout_check(context, 'perform_snapshot'):\n break\n\n # we probably should have been using volume keys from one of the\n # caches here, but since we're not, we're going to have to check here too\n LOG.debug('Considering device %s', dev)\n volume_id = dev['Ebs']['VolumeId']\n\n if volume_id in ignore_ids:\n continue\n\n # find snapshots\n recent = volume_snap_recent.get(volume_id)\n now = datetime.datetime.now(dateutil.tz.tzutc())\n\n # snapshot due?\n if should_perform_snapshot(frequency, now, volume_id, recent):\n LOG.debug('Performing snapshot for %s, calculating tags', volume_id)\n else:\n LOG.debug('NOT Performing snapshot for %s', volume_id)\n continue\n\n # perform actual snapshot and create tag: retention + now() as a Y-M-D\n delete_on_dt = now + retention\n delete_on = delete_on_dt.strftime('%Y-%m-%d')\n\n volume_data = utils.get_volume(volume_id, region=region)\n expected_tags = utils.calculate_relevant_tags(\n instance_data.get('Tags', None),\n volume_data.get('Tags', None))\n\n utils.snapshot_and_tag(\n instance_id,\n ami_id,\n volume_id,\n delete_on,\n region,\n additional_tags=expected_tags)","def test_change_volume_status(self, volume, volumes_steps):\n volumes_steps.change_volume_status(volume.name, 'Error')\n volumes_steps.change_volume_status(volume.name, 'Available')","def test_delete__volume(self):\n arglist = [\n '--volume',\n self.projects[0].id,\n ]\n verifylist = [\n ('service', 'volume'),\n ('project', self.projects[0].id),\n ]\n\n parsed_args = self.check_parser(self.cmd, arglist, verifylist)\n\n result = self.cmd.take_action(parsed_args)\n\n self.assertIsNone(result)\n self.projects_mock.get.assert_called_once_with(self.projects[0].id)\n self.compute_quotas_mock.delete.assert_not_called()\n self.volume_quotas_mock.delete.assert_called_once_with(\n self.projects[0].id,\n )\n self.network_mock.delete_quota.assert_not_called()","def test_aws_service_api_volume_delete(self):\n pass","def __mount_ebs_volume( self ):\n ebs_volume_size = self.instance_tag( 'ebs_volume_size' ) or '0'\n ebs_volume_size = int( ebs_volume_size )\n if ebs_volume_size:\n instance_name = self.instance_tag( 'Name' )\n cluster_ordinal = int( self.instance_tag( 'cluster_ordinal' ) )\n volume_name = '%s__%d' % (instance_name, cluster_ordinal)\n volume = EC2VolumeHelper( ec2=self.ec2,\n availability_zone=self.availability_zone,\n name=volume_name,\n size=ebs_volume_size,\n volume_type=\"gp2\" )\n # TODO: handle case where volume is already attached\n device_ext = '/dev/sdf'\n device = '/dev/xvdf'\n volume.attach( self.instance_id, device_ext )\n\n # Wait for inode to appear and make sure its a block device\n while True:\n try:\n assert stat.S_ISBLK( os.stat( device ).st_mode )\n break\n except OSError as e:\n if e.errno == errno.ENOENT:\n time.sleep( 1 )\n else:\n raise\n\n # Only format empty volumes\n volume_label = volume_label_hash( volume_name )\n if check_output( [ 'file', '-sL', device ] ).strip( ) == device + ': data':\n check_call( [ 'mkfs', '-t', 'ext4', device ] )\n check_call( [ 'e2label', device, volume_label ] )\n else:\n # If the volume is not empty, verify the file system label\n actual_label = check_output( [ 'e2label', device ] ).strip( )\n if actual_label != volume_label:\n raise AssertionError(\n \"Expected volume label '%s' (derived from '%s') but got '%s'\" %\n (volume_label, volume_name, actual_label) )\n current_mount_point = self.__mount_point( device )\n if current_mount_point is None:\n mkdir_p( self.persistent_dir )\n check_call( [ 'mount', device, self.persistent_dir ] )\n elif current_mount_point == self.persistent_dir:\n pass\n else:\n raise RuntimeError(\n \"Can't mount device %s on '%s' since it is already mounted on '%s'\" % (\n device, self.persistent_dir, current_mount_point) )\n else:\n # No persistent volume is attached and the root volume is off limits, so we will need\n # to place persistent data on the ephemeral volume.\n self.persistent_dir = self.ephemeral_dir","def get_volume_snapshots(\n self,\n references=None, # type: List[models.ReferenceType]\n sources=None, # type: List[models.ReferenceType]\n authorization=None, # type: str\n x_request_id=None, # type: str\n destroyed=None, # type: bool\n filter=None, # type: str\n ids=None, # type: List[str]\n limit=None, # type: int\n names=None, # type: List[str]\n offset=None, # type: int\n sort=None, # type: List[str]\n source_ids=None, # type: List[str]\n source_names=None, # type: List[str]\n total_item_count=None, # type: bool\n total_only=None, # type: bool\n async_req=False, # type: bool\n _return_http_data_only=False, # type: bool\n _preload_content=True, # type: bool\n _request_timeout=None, # type: Optional[int]\n ):\n # type: (...) -> models.VolumeSnapshotGetResponse\n kwargs = dict(\n authorization=authorization,\n x_request_id=x_request_id,\n destroyed=destroyed,\n filter=filter,\n ids=ids,\n limit=limit,\n names=names,\n offset=offset,\n sort=sort,\n source_ids=source_ids,\n source_names=source_names,\n total_item_count=total_item_count,\n total_only=total_only,\n async_req=async_req,\n _return_http_data_only=_return_http_data_only,\n _preload_content=_preload_content,\n _request_timeout=_request_timeout,\n )\n kwargs = {k: v for k, v in kwargs.items() if v is not None}\n endpoint = self._volume_snapshots_api.api20_volume_snapshots_get_with_http_info\n _process_references(references, ['ids', 'names'], kwargs)\n _process_references(sources, ['source_ids', 'source_names'], kwargs)\n return self._call_api(endpoint, kwargs)","def _create_snapshot(self, name=None, metadata=None):\n req = fakes.HTTPRequest.blank('/v3/snapshots')\n req.environ['cinder.context'] = self.ctx\n snap = {\"volume_id\": fake.VOLUME_ID,\n \"display_name\": name or \"Volume Test Name\",\n \"description\": \"Volume Test Desc\"\n }\n if metadata:\n snap[\"metadata\"] = metadata\n body = {\"snapshot\": snap}\n self.controller.create(req, body=body)","def ensure_volume_access_right_exists( user_email, volume_name, caps, allowed_gateways=[msconfig.GATEWAY_TYPE_UG] ):\n client = connect_syndicate()\n return syndicate_provisioning.ensure_volume_access_right_exists( client, user_email, volume_name, caps, allowed_gateways )"],"string":"[\n \"def snapshot_volumes(self) -> bool:\\n return pulumi.get(self, \\\"snapshot_volumes\\\")\",\n \"def get_volume_snapshots(self, volume):\\n LOG.debug('get_volume_snapshot starts')\\n pool_name = self.configuration.rbd_pool\\n volume_name = 'volume-%s' % encodeutils.safe_encode(volume[\\\"id\\\"])\\n snaps_on_vol = self._get_volume_snapshots(pool_name, volume_name)\\n snapshots = list()\\n if snaps_on_vol is not None:\\n for snap in snaps_on_vol:\\n snap_name = str(snap[\\\"name\\\"])\\n item = dict()\\n if snap_name.startswith(\\\"snapshot-\\\"):\\n # snapshot directly created on volume.\\n item[\\\"type\\\"] = \\\"volume_snap\\\"\\n item[\\\"uuid\\\"] = snap_name[len('snapshot-'):]\\n elif snap_name.startswith(\\\"volume-\\\") and \\\\\\n snap_name.endswith(\\\".clone_snap\\\"):\\n # snapshot used for create volume on volume.\\n item[\\\"type\\\"] = \\\"clone_snap\\\"\\n item[\\\"uuid\\\"] = snap_name[len(\\\"volume-\\\"):-len(\\\".clone_snap\\\")]\\n elif snap_name.startswith(\\\"backup.\\\") and \\\".snap.\\\" in snap_name:\\n # snapshot used for backup volume.\\n item[\\\"type\\\"] = \\\"backup_snap\\\"\\n item[\\\"uuid\\\"] = \\\\\\n snap_name[len(\\\"backup.\\\"):snap_name.index(\\\".snap.\\\")]\\n else:\\n item[\\\"type\\\"] = \\\"\\\"\\n item[\\\"uuid\\\"] = \\\"\\\"\\n snapshots.append(item)\\n\\n LOG.debug('volume snapshots: %s', snapshots)\\n LOG.debug('get_volume_snapshots finished.')\\n return snapshots\",\n \"def create_volume_from_snapshot(snapshots, objects_created,\\n wait_for_available=120):\\n if type(snapshots) is not list:\\n snapshots = [snapshots]\\n v = []\\n for snapshot in snapshots:\\n command = 'cinder create --snapshot-id %s --name %s' % \\\\\\n (snapshot['id'], snapshot['display_name'])\\n volume_from_snapshot = parse_output(Popen(\\n command.split(), stdout=STDOUT, stderr=STDERR).communicate()[0])\\n volume_from_snapshot['device'] = snapshot['device']\\n volume_from_snapshot['bootable'] = snapshot['bootable']\\n v.append(volume_from_snapshot)\\n if wait_for_available > 0:\\n wait = 0\\n again = False\\n while wait < wait_for_available:\\n time.sleep(5)\\n wait += 5\\n again = False\\n for volume in v:\\n command = 'cinder show %s' % volume['id']\\n status = parse_output(Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n )['status']\\n if status == 'error':\\n # clean up and create volume again\\n command = 'cinder delete %s' % volume['id']\\n a = Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n command = 'cinder create --snapshot-id %s' % \\\\\\n volume['snapshot_id']\\n volume_info = parse_output(Popen(\\n command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0])\\n volume_info['bootable'] = volume['bootable']\\n volume_info['device'] = volume['device']\\n volume = volume_info\\n again = True\\n break\\n elif status == 'creating':\\n again = True\\n break\\n elif status == 'available':\\n volume['status'] = status\\n pass\\n if again:\\n continue\\n else:\\n break\\n if again: # Loop ended due to timeout\\n print 'Error creating volume from snapshot!'\\n print 'The following entities were created in the process:'\\n print_objects_created(objects_created)\\n sys.exit(-1)\\n return v\",\n \"def test_create_volume_from_snapshot(self, mock_ghn):\\n ctxt = context.get_admin_context()\\n extra_specs = {}\\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\\n snap = {'id': '1', 'name': 'volume1', 'display_name': '',\\n 'volume_type_id': type_ref['id'], 'size': 10,\\n 'provider_id': 'space_orig'}\\n volume = {'id': '2', 'name': 'volume2', 'display_name': '',\\n 'volume_type_id': type_ref['id'], 'size': 10}\\n pid = self.driver.create_volume_from_snapshot(volume, snap)\\n # We must copy entier underlying storage, ~12GB, not just 10GB\\n self.assertEqual(11444 * units.Mi, self.dd_count)\\n self.assertEqual('1M', self.bs)\\n # Check space-create command\\n expected = {'redundancy': '0', 'group': 'xanadu',\\n 'name': 'volume2', 'mode': '0777',\\n 'user': 'kane', 'net': 'net1',\\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\\n 'size': '12'}\\n self.assertDictMatch(expected, self.created)\\n # Check the returned provider\\n expected_pid = {'provider_id': 'volume2'}\\n self.assertDictMatch(expected_pid, pid)\",\n \"def test_volume_snapshot_create_get_list_delete(self):\\n volume = self.create_volume()\\n self.addCleanup(self.delete_volume, volume['id'])\\n\\n s_name = data_utils.rand_name(self.__class__.__name__ + '-Snapshot')\\n # Create snapshot\\n snapshot = self.snapshots_client.create_snapshot(\\n volume_id=volume['id'],\\n display_name=s_name)['snapshot']\\n\\n def delete_snapshot(snapshot_id):\\n waiters.wait_for_volume_resource_status(self.snapshots_client,\\n snapshot_id,\\n 'available')\\n # Delete snapshot\\n self.snapshots_client.delete_snapshot(snapshot_id)\\n self.snapshots_client.wait_for_resource_deletion(snapshot_id)\\n\\n self.addCleanup(delete_snapshot, snapshot['id'])\\n self.assertEqual(volume['id'], snapshot['volumeId'])\\n # Get snapshot\\n fetched_snapshot = self.snapshots_client.show_snapshot(\\n snapshot['id'])['snapshot']\\n self.assertEqual(s_name, fetched_snapshot['displayName'])\\n self.assertEqual(volume['id'], fetched_snapshot['volumeId'])\\n # Fetch all snapshots\\n snapshots = self.snapshots_client.list_snapshots()['snapshots']\\n self.assertIn(snapshot['id'], map(lambda x: x['id'], snapshots))\",\n \"def create_volume_snapshot(volumes, source_instance, objects_created,\\n wait_for_available=50):\\n if type(volumes) is not list:\\n volumes = [volumes]\\n s = []\\n for volume in volumes:\\n command = 'cinder snapshot-create --force True --name %s %s' % \\\\\\n (volume['name'], volume['id'])\\n snapshot_info = parse_output(Popen(command.split(), stdout=STDOUT).communicate()[0])\\n if volume['bootable'] == 'true':\\n snapshot_info['bootable'] = True\\n else:\\n snapshot_info['bootable'] = False\\n att = volume['attachments'].replace(\\\"'\\\", \\\"\\\\\\\"\\\").replace(\\n \\\"u\\\\\\\"\\\", \\\"\\\\\\\"\\\").replace(\\\" None,\\\", \\\" \\\\\\\"None\\\\\\\",\\\")\\n snapshot_info['device'] = get(json.loads(att), 'server_id',\\n source_instance['id'])[0]['device']\\n s.append(snapshot_info)\\n if wait_for_available > 0:\\n wait = 0\\n again = False\\n while wait < wait_for_available:\\n time.sleep(5)\\n wait += 5\\n again = False\\n for snapshot in s:\\n command = 'cinder snapshot-show %s' % snapshot['id']\\n status = parse_output(Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n )['status']\\n if status == 'error':\\n # clean up and take snapshot again\\n command = 'cinder snapshot-delete %s' % snapshot['id']\\n a = Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n command = 'cinder snapshot-create --force True %s' % \\\\\\n snapshot['volume_id']\\n snapshot_info = parse_output(Popen(command.split(),\\n stdout=STDOUT, stderr=STDERR\\n ).communicate()[0])\\n snapshot_info['bootable'] = snapshot['bootable']\\n snapshot_info['device'] = snapshot['device']\\n snapshot = snapshot_info\\n again = True\\n break\\n elif status == 'creating':\\n again = True\\n break\\n elif status == 'available':\\n snapshot['status'] = status\\n pass\\n if again:\\n continue\\n else:\\n break\\n if again: # Loop ended due to timeout\\n print 'Error creating volume snapshot!'\\n print 'The following entities were created in the process:'\\n print_objects_created(objects_created)\\n sys.exit(-1)\\n return s\",\n \"def snapshot_volumes(self) -> pulumi.Input[bool]:\\n return pulumi.get(self, \\\"snapshot_volumes\\\")\",\n \"def _ensure_snapshot(connection, volume, interval, name):\\n if interval not in VALID_INTERVALS:\\n logging.warning(kayvee.formatLog(\\\"ebs-snapshots\\\", \\\"warning\\\", \\\"invalid snapshotting interval\\\", {\\n \\\"volume\\\": volume.id,\\n \\\"interval\\\": interval\\n }))\\n return\\n\\n snapshots = connection.get_all_snapshots(filters={'volume-id': volume.id})\\n\\n # Create a snapshot if we don't have any\\n if not snapshots:\\n _create_snapshot(connection, volume, name)\\n return\\n\\n min_delta = 3600 * 24 * 365 * 10 # 10 years :)\\n for snapshot in snapshots:\\n timestamp = datetime.datetime.strptime(\\n snapshot.start_time,\\n '%Y-%m-%dT%H:%M:%S.000Z')\\n delta_seconds = int(\\n (datetime.datetime.utcnow() - timestamp).total_seconds())\\n\\n if delta_seconds < min_delta:\\n min_delta = delta_seconds\\n\\n logging.info(kayvee.formatLog(\\\"ebs-snapshots\\\", \\\"info\\\", 'The newest snapshot for {} is {} seconds old'.format(volume.id, min_delta)))\\n\\n if interval == 'hourly' and min_delta > 3600:\\n _create_snapshot(connection, volume, name)\\n elif interval == 'daily' and min_delta > 3600*24:\\n _create_snapshot(connection, volume, name)\\n elif interval == 'weekly' and min_delta > 3600*24*7:\\n _create_snapshot(connection, volume, name)\\n elif interval == 'monthly' and min_delta > 3600*24*30:\\n _create_snapshot(connection, volume, name)\\n elif interval == 'yearly' and min_delta > 3600*24*365:\\n _create_snapshot(connection, volume, name)\\n else:\\n logging.info(kayvee.formatLog(\\\"ebs-snapshots\\\", \\\"info\\\", \\\"no snapshot needed\\\", {\\\"volume\\\": volume.id}))\",\n \"def get_snapshots(vol_name):\\n\\n l = None\\n try:\\n cmd = 'gluster snapshot info volume %s --xml' % vol_name\\n d, err = xml_parse.run_gluster_command(cmd)\\n if err:\\n raise Exception(err)\\n if d:\\n if d[\\\"op_status\\\"][\\\"op_ret\\\"] == 0:\\n l, err = xml_parse.get_snapshots(d[\\\"root\\\"])\\n if err:\\n raise Exception(err)\\n except Exception, e:\\n return None, 'Error getting volume snapshots: %s' % str(e)\\n else:\\n return l, None\",\n \"def test_backup_can_use_snapshots(self):\\n use_snaps = self.driver.backup_use_temp_snapshot()\\n self.assertTrue(use_snaps)\",\n \"def _verify_cache_volume(self, context, img_meta,\\n img_service, cachevol_props):\\n lcfg = self.configuration\\n cache_dir = '%s/' % lcfg.zfssa_cache_directory\\n cache_vol_obj = Volume()\\n cache_vol_obj.provider_location = self.mount_path + '/' + cache_dir\\n cache_vol_obj._name_id = cachevol_props['id']\\n cachevol_name = cache_dir + cache_vol_obj.name\\n\\n LOG.debug('Verifying cache volume %s:', cachevol_name)\\n\\n try:\\n cache_vol = self.zfssa.get_volume(cachevol_name)\\n except exception.VolumeNotFound:\\n # There is no existing cache volume, create one:\\n LOG.debug('Cache volume not found. Creating one...')\\n return self._create_cache_volume(context,\\n img_meta,\\n img_service,\\n cachevol_props)\\n\\n # A cache volume does exist, check if it's updated:\\n if ((cache_vol['updated_at'] != cachevol_props['updated_at']) or\\n (cache_vol['image_id'] != cachevol_props['image_id'])):\\n if cache_vol['numclones'] > 0:\\n # The cache volume is updated, but has clones\\n exception_msg = (_('Cannot delete '\\n 'cache volume: %(cachevol_name)s. '\\n 'It was updated at %(updated_at)s '\\n 'and currently has %(numclones)d '\\n 'volume instances.'),\\n {'cachevol_name': cachevol_name,\\n 'updated_at': cachevol_props['updated_at'],\\n 'numclones': cache_vol['numclones']})\\n LOG.error(exception_msg)\\n raise exception.VolumeBackendAPIException(data=exception_msg)\\n\\n # The cache volume is updated, but has no clone, so we delete it\\n # and re-create a new one:\\n super(ZFSSANFSDriver, self).delete_volume(cache_vol_obj)\\n return self._create_cache_volume(context,\\n img_meta,\\n img_service,\\n cachevol_props)\\n\\n return cachevol_name\",\n \"def create_volume_snapshot(self, volume, name=None, description=None,\\n check=True):\\n cmd = 'cinder snapshot-create'\\n if name:\\n cmd += ' --name ' + name\\n if description is not None:\\n cmd += ' --description ' + moves.shlex_quote(description)\\n\\n cmd += ' ' + volume.id\\n\\n exit_code, stdout, stderr = self.execute_command(\\n cmd, timeout=config.SNAPSHOT_AVAILABLE_TIMEOUT, check=check)\\n\\n snapshot_table = output_parser.table(stdout)\\n snapshot = {key: value for key, value in snapshot_table['values']}\\n\\n return snapshot\",\n \"def create_volume_from_snapshot(self, snapshot, volume, volume_db):\\n self.authenticate_user()\\n\\n if self.configuration.vipr_emulate_snapshot == 'True':\\n self.create_cloned_volume(volume, snapshot)\\n return\\n\\n ctxt = context.get_admin_context()\\n\\n src_snapshot_name = None\\n\\n #src_snapshot_name = snapshot['display_name']\\n src_vol_ref = volume_db.volume_get(ctxt, snapshot['volume_id'])\\n new_volume_name = self._get_volume_name(volume)\\n number_of_volumes = 1\\n\\n try:\\n src_vol_name, src_vol_uri = self._get_vipr_volume_name(src_vol_ref, True)\\n src_snapshot_name = self._get_vipr_snapshot_name(snapshot , src_vol_uri)\\n\\n (storageresType, storageresTypename) = self.volume_obj.get_storageAttributes(\\n src_vol_name\\n , None\\n , src_snapshot_name)\\n\\n resource_id = self.volume_obj.storageResource_query(storageresType,\\n src_vol_name,\\n None,\\n src_snapshot_name,\\n self.configuration.vipr_project,\\n self.configuration.vipr_tenant)\\n\\n self.volume_obj.clone(\\n new_volume_name,\\n number_of_volumes,\\n resource_id,\\n sync=True)\\n\\n except vipr_utils.SOSError as e:\\n if(e.err_code == vipr_utils.SOSError.SOS_FAILURE_ERR):\\n raise vipr_utils.SOSError(\\n vipr_utils.SOSError.SOS_FAILURE_ERR,\\n \\\"Snapshot \\\" +\\n src_snapshot_name +\\n \\\": clone failed\\\\n\\\" +\\n e.err_text)\\n else:\\n with excutils.save_and_reraise_exception():\\n LOG.exception(\\n _(\\\"Snapshot : %s clone failed\\\") % src_snapshot_name)\",\n \"def create_volume_from_snapshot(self, volume, snapshot):\\n snap_name = self.get_snap_name(snapshot.id)\\n view_name = self.get_view_name(volume.id)\\n vol_name = self.get_volume_name(volume.id)\\n cview = src_attach_info = dest_attach_info = None\\n rpolicy = self.get_policy()\\n properties = volume_utils.brick_get_connector_properties(\\n self.configuration.use_multipath_for_image_xfer,\\n self.configuration.enforce_multipath_for_image_xfer)\\n LOG.debug(\\\"Searching for snapshot: %s in K2.\\\", snap_name)\\n snap_rs = self.client.search(\\\"snapshots\\\", short_name=snap_name)\\n if hasattr(snap_rs, 'hits') and snap_rs.total != 0:\\n snap = snap_rs.hits[0]\\n LOG.debug(\\\"Creating a view: %(view)s from snapshot: %(snap)s\\\",\\n {'view': view_name, 'snap': snap_name})\\n try:\\n cview = self.client.new(\\\"snapshots\\\",\\n short_name=view_name,\\n source=snap, retention_policy=rpolicy,\\n is_exposable=True).save()\\n except Exception as ex:\\n LOG.exception(\\\"Creating a view: %(view)s from snapshot: \\\"\\n \\\"%(snap)s failed\\\", {\\\"view\\\": view_name,\\n \\\"snap\\\": snap_name})\\n raise KaminarioCinderDriverException(reason=ex)\\n\\n else:\\n msg = _(\\\"Snapshot: %s search failed in K2.\\\") % snap_name\\n LOG.error(msg)\\n raise KaminarioCinderDriverException(reason=msg)\\n\\n try:\\n conn = self.initialize_connection(cview, properties)\\n src_attach_info = self._connect_device(conn)\\n self.create_volume(volume)\\n conn = self.initialize_connection(volume, properties)\\n dest_attach_info = self._connect_device(conn)\\n volume_utils.copy_volume(src_attach_info['device']['path'],\\n dest_attach_info['device']['path'],\\n snapshot.volume.size * units.Ki,\\n self.configuration.volume_dd_blocksize,\\n sparse=True)\\n self._kaminario_disconnect_volume(src_attach_info,\\n dest_attach_info)\\n self.terminate_connection(volume, properties)\\n self.terminate_connection(cview, properties)\\n cview.delete()\\n except Exception as ex:\\n self._kaminario_disconnect_volume(src_attach_info,\\n dest_attach_info)\\n self.terminate_connection(cview, properties)\\n self.terminate_connection(volume, properties)\\n cview.delete()\\n self.delete_volume(volume)\\n LOG.exception(\\\"Copy to volume: %(vol)s from view: %(view)s \\\"\\n \\\"failed\\\", {\\\"vol\\\": vol_name, \\\"view\\\": view_name})\\n raise KaminarioCinderDriverException(reason=ex)\",\n \"def create_volume_from_snapshot(self, volume, snapshot):\\n self._ensure_shares_mounted()\\n\\n snapshot_vol = self._get_snapshot_volume(snapshot)\\n nfs_share = snapshot_vol['provider_location']\\n volume['provider_location'] = nfs_share\\n nms = self.share2nms[nfs_share]\\n\\n vol, dataset = self._get_share_datasets(nfs_share)\\n snapshot_name = '%s/%s/%s@%s' % (vol, dataset, snapshot['volume_name'],\\n snapshot['name'])\\n folder = '%s/%s' % (dataset, volume['name'])\\n nms.folder.clone(snapshot_name, '%s/%s' % (vol, folder))\\n\\n try:\\n self._share_folder(nms, vol, folder)\\n except utils.NexentaException:\\n try:\\n nms.folder.destroy('%s/%s' % (vol, folder), '')\\n except utils.NexentaException:\\n LOG.warning(\\\"Cannot destroy cloned folder: \\\"\\n \\\"%(vol)s/%(folder)s\\\",\\n {'vol': vol, 'folder': folder})\\n raise\\n\\n if self._get_nfs_server_version(nfs_share) < 4:\\n sub_share, mnt_path = self._get_subshare_mount_point(nfs_share,\\n volume)\\n self._ensure_share_mounted(sub_share, mnt_path)\\n\\n if (('size' in volume) and (\\n volume['size'] > snapshot['volume_size'])):\\n self.extend_volume(volume, volume['size'])\\n\\n return {'provider_location': volume['provider_location']}\",\n \"def test_live_migration_src_check_volume_node_not_alive(self):\\n\\n instance_id = self._create_instance()\\n i_ref = db.instance_get(self.context, instance_id)\\n dic = {'instance_id': instance_id, 'size': 1}\\n v_ref = db.volume_create(self.context, {'instance_id': instance_id,\\n 'size': 1})\\n t1 = utils.utcnow() - datetime.timedelta(1)\\n dic = {'created_at': t1, 'updated_at': t1, 'binary': 'nova-volume',\\n 'topic': 'volume', 'report_count': 0}\\n s_ref = db.service_create(self.context, dic)\\n\\n self.assertRaises(exception.VolumeServiceUnavailable,\\n self.scheduler.driver.schedule_live_migration,\\n self.context, instance_id, i_ref['host'])\\n\\n db.instance_destroy(self.context, instance_id)\\n db.service_destroy(self.context, s_ref['id'])\\n db.volume_destroy(self.context, v_ref['id'])\",\n \"def test_view_volume(self, volume, volumes_steps):\\n volumes_steps.view_volume(volume.name)\",\n \"def test_clone_delete_snap(self):\\n\\n # pylint: disable=too-many-statements, too-many-locals\\n # Enabling Volume options on the volume and validating\\n g.log.info(\\\"Enabling volume options for volume %s \\\", self.volname)\\n options = {\\\" features.uss\\\": \\\"enable\\\"}\\n ret = set_volume_options(self.mnode, self.volname, options)\\n self.assertTrue(ret, (\\\"Failed to set volume options for volume %s\\\"\\n % self.volname))\\n g.log.info(\\\"Successfully set volume options\\\"\\n \\\"for volume %s\\\", self.volname)\\n\\n # Validate feature.uss enabled or not\\n g.log.info(\\\"Validating feature.uss is enabled\\\")\\n option = \\\"features.uss\\\"\\n vol_option = get_volume_options(self.mnode, self.volname, option)\\n self.assertEqual(vol_option['features.uss'], 'enable', \\\"Failed\\\"\\n \\\" to validate \\\"\\n \\\"volume options\\\")\\n g.log.info(\\\"Successfully validated volume options\\\"\\n \\\"for volume %s\\\", self.volname)\\n\\n # Creating snapshot\\n g.log.info(\\\"Starting to Create snapshot\\\")\\n for snap_count in range(0, 2):\\n ret, _, _ = snap_create(self.mnode, self.volname,\\n \\\"snap%s\\\" % snap_count)\\n self.assertEqual(ret, 0, (\\\"Failed to create snapshot for volume %s\\\"\\n % self.volname))\\n g.log.info(\\\"Snapshot snap%s created successfully\\\"\\n \\\"for volume %s\\\", snap_count, self.volname)\\n\\n # Activating snapshot\\n g.log.info(\\\"Starting to Activate Snapshot\\\")\\n for snap_count in range(0, 2):\\n ret, _, _ = snap_activate(self.mnode, \\\"snap%s\\\" % snap_count)\\n self.assertEqual(ret, 0, (\\\"Failed to Activate snapshot snap%s\\\"\\n % snap_count))\\n g.log.info(\\\"Snapshot snap%s activated successfully\\\", snap_count)\\n\\n # Reset volume:\\n g.log.info(\\\"Starting to Reset Volume\\\")\\n ret, _, _ = volume_reset(self.mnode, self.volname, force=False)\\n self.assertEqual(ret, 0, (\\\"Failed to reset volume %s\\\" % self.volname))\\n g.log.info(\\\"Reset Volume on volume %s is Successful\\\", self.volname)\\n\\n # Validate feature.uss enabled or not\\n g.log.info(\\\"Validating feature.uss is enabled\\\")\\n option = \\\"features.uss\\\"\\n vol_option = get_volume_options(self.mnode, self.volname, option)\\n self.assertEqual(vol_option['features.uss'], 'off', \\\"Failed\\\"\\n \\\" to validate \\\"\\n \\\"volume options\\\")\\n g.log.info(\\\"Successfully validated volume options\\\"\\n \\\"for volume %s\\\", self.volname)\\n\\n # Verify volume's all process are online\\n g.log.info(\\\"Starting to Verify volume's all process are online\\\")\\n ret = verify_all_process_of_volume_are_online(self.mnode, self.volname)\\n self.assertTrue(ret, (\\\"Volume %s : All process are\\\"\\n \\\"not online\\\" % self.volname))\\n g.log.info(\\\"Volume %s : All process are online\\\", self.volname)\\n\\n # Creating and starting a Clone of snapshot\\n g.log.info(\\\"Starting to Clone Snapshot\\\")\\n for clone_count in range(0, 2):\\n ret, _, _ = snap_clone(self.mnode, \\\"snap%s\\\" % clone_count,\\n \\\"clone%s\\\" % clone_count)\\n self.assertEqual(ret, 0, (\\\"Failed to clone clone%s volume\\\"\\n % clone_count))\\n g.log.info(\\\"clone%s volume created successfully\\\", clone_count)\\n\\n # Start Cloned volume\\n g.log.info(\\\"starting to Validate clone volumes are started\\\")\\n for clone_count in range(0, 2):\\n ret, _, _ = volume_start(self.mnode, \\\"clone%s\\\" % clone_count)\\n self.assertEqual(ret, 0, (\\\"Failed to start clone%s\\\"\\n % clone_count))\\n g.log.info(\\\"clone%s started successfully\\\", clone_count)\\n g.log.info(\\\"All the clone volumes are started Successfully\\\")\\n\\n # Validate Volume start of cloned volume\\n g.log.info(\\\"Starting to Validate Volume start\\\")\\n for clone_count in range(0, 2):\\n vol_info = get_volume_info(self.mnode, \\\"clone%s\\\" % clone_count)\\n if vol_info[\\\"clone%s\\\" % clone_count]['statusStr'] != 'Started':\\n raise ExecutionError(\\\"Failed to get volume info for clone%s\\\"\\n % clone_count)\\n g.log.info(\\\"Volume clone%s is in Started state\\\", clone_count)\\n\\n # Validate feature.uss enabled or not\\n g.log.info(\\\"Validating feature.uss is enabled\\\")\\n option = \\\"features.uss\\\"\\n for clone_count in range(0, 2):\\n vol_option = get_volume_options(self.mnode, \\\"clone%s\\\"\\n % clone_count, option)\\n self.assertEqual(vol_option['features.uss'], 'enable', \\\"Failed\\\"\\n \\\" to validate\\\"\\n \\\"volume options\\\")\\n g.log.info(\\\"Successfully validated volume options\\\"\\n \\\"for volume clone%s\\\", clone_count)\\n\\n # Mount both the cloned volumes\\n g.log.info(\\\"Mounting Cloned Volumes\\\")\\n for mount_obj in range(0, 2):\\n self.mpoint = \\\"/mnt/clone%s\\\" % mount_obj\\n cmd = \\\"mkdir -p %s\\\" % self.mpoint\\n ret, _, _ = g.run(self.clients[0], cmd)\\n self.assertEqual(ret, 0, (\\\"Creation of directory %s\\\"\\n \\\"for mounting\\\"\\n \\\"volume %s failed: Directory already\\\"\\n \\\"present\\\"\\n % (self.mpoint, \\\"clone%s\\\" % mount_obj)))\\n g.log.info(\\\"Creation of directory %s for mounting volume %s \\\"\\n \\\"success\\\", self.mpoint, (\\\"clone%s\\\" % mount_obj))\\n ret, _, _ = mount_volume(\\\"clone%s\\\" % mount_obj, self.mount_type,\\n self.mpoint, self.mnode, self.clients[0])\\n self.assertEqual(ret, 0, (\\\"clone%s is not mounted\\\"\\n % mount_obj))\\n g.log.info(\\\"clone%s is mounted Successfully\\\", mount_obj)\\n\\n # Perform I/O on mount\\n # Start I/O on all mounts\\n g.log.info(\\\"Starting to Perform I/O on Mountpoint\\\")\\n all_mounts_procs = []\\n for mount_obj in range(0, 2):\\n cmd = (\\\"cd /mnt/clone%s/; for i in {1..10};\\\"\\n \\\"do touch file$i; done; cd;\\\") % mount_obj\\n proc = g.run(self.clients[0], cmd)\\n all_mounts_procs.append(proc)\\n g.log.info(\\\"I/O on mountpoint is successful\\\")\\n\\n # create snapshot\\n g.log.info(\\\"Starting to Create snapshot of clone volume\\\")\\n ret0, _, _ = snap_create(self.mnode, \\\"clone0\\\", \\\"snap2\\\")\\n self.assertEqual(ret0, 0, \\\"Failed to create the snapshot\\\"\\n \\\"snap2 from clone0\\\")\\n g.log.info(\\\"Snapshots snap2 created successfully from clone0\\\")\\n ret1, _, _ = snap_create(self.mnode, \\\"clone1\\\", \\\"snap3\\\")\\n self.assertEqual(ret1, 0, \\\"Failed to create the snapshot snap3\\\"\\n \\\"from clone1\\\")\\n g.log.info(\\\"Snapshots snap3 created successfully from clone1\\\")\\n\\n # Listing all Snapshots present\\n g.log.info(\\\"Starting to list all snapshots\\\")\\n ret, _, _ = snap_list(self.mnode)\\n self.assertEqual(ret, 0, (\\\"Failed to list snapshots present\\\"))\\n g.log.info(\\\"Snapshots successfully listed\\\")\",\n \"def snapshots_created(self):\\n # log.debug(\\\"Getting snaps created for volume {0}\\\".format(self.volume_id))\\n snaps_info = []\\n for snap in self._derived_snapshots:\\n snap_info = {}\\n try:\\n if snap.volume_id == self.volume_id:\\n snap.update()\\n snap_info['snap_id'] = snap.id\\n snap_info['snap_progress'] = snap.progress\\n snap_info['snap_status'] = snap.status\\n snap_info['snap_desc'] = snap.description\\n snaps_info.append(snap_info)\\n except EC2ResponseError, e:\\n log.warning(\\\"EC2ResponseError getting snapshot status: {0} \\\"\\n \\\"(code {1}; status {2})\\\"\\n .format(e.message, e.error_code, e.status))\\n return snaps_info\",\n \"def migrate_volume(self, ctxt, volume, host):\\n LOG.debug('Enter: migrate_volume: id=%(id)s, host=%(host)s',\\n {'id': volume['id'], 'host': host})\\n\\n false_ret = (False, None)\\n\\n if volume['status'] not in ('available', 'retyping'):\\n LOG.warning(\\\"Volume status must be 'available' or 'retyping'.\\\"\\n \\\" Current volume status: %s\\\", volume['status'])\\n return false_ret\\n\\n if 'capabilities' not in host:\\n LOG.warning(\\\"Unsupported host. No capabilities found\\\")\\n return false_ret\\n\\n capabilities = host['capabilities']\\n ns_shares = capabilities['ns_shares']\\n dst_parts = capabilities['location_info'].split(':')\\n dst_host, dst_volume = dst_parts[1:]\\n\\n if (capabilities.get('vendor_name') != 'Nexenta' or\\n dst_parts[0] != self.__class__.__name__ or\\n capabilities['free_capacity_gb'] < volume['size']):\\n return false_ret\\n\\n nms = self.share2nms[volume['provider_location']]\\n ssh_bindings = nms.appliance.ssh_list_bindings()\\n shares = []\\n for bind in ssh_bindings:\\n for share in ns_shares:\\n if (share.startswith(ssh_bindings[bind][3]) and\\n ns_shares[share] >= volume['size']):\\n shares.append(share)\\n if len(shares) == 0:\\n LOG.warning(\\\"Remote NexentaStor appliance at %s should be \\\"\\n \\\"SSH-bound.\\\", share)\\n return false_ret\\n share = sorted(shares, key=ns_shares.get, reverse=True)[0]\\n snapshot = {\\n 'volume_name': volume['name'],\\n 'volume_id': volume['id'],\\n 'name': utils.get_migrate_snapshot_name(volume)\\n }\\n self.create_snapshot(snapshot)\\n location = volume['provider_location']\\n src = '%(share)s/%(volume)s@%(snapshot)s' % {\\n 'share': location.split(':')[1].split('volumes/')[1],\\n 'volume': volume['name'],\\n 'snapshot': snapshot['name']\\n }\\n dst = ':'.join([dst_host, dst_volume.split('/volumes/')[1]])\\n try:\\n nms.appliance.execute(self._get_zfs_send_recv_cmd(src, dst))\\n except utils.NexentaException as exc:\\n LOG.warning(\\\"Cannot send source snapshot %(src)s to \\\"\\n \\\"destination %(dst)s. Reason: %(exc)s\\\",\\n {'src': src, 'dst': dst, 'exc': exc})\\n return false_ret\\n finally:\\n try:\\n self.delete_snapshot(snapshot)\\n except utils.NexentaException as exc:\\n LOG.warning(\\\"Cannot delete temporary source snapshot \\\"\\n \\\"%(src)s on NexentaStor Appliance: %(exc)s\\\",\\n {'src': src, 'exc': exc})\\n try:\\n self.delete_volume(volume)\\n except utils.NexentaException as exc:\\n LOG.warning(\\\"Cannot delete source volume %(volume)s on \\\"\\n \\\"NexentaStor Appliance: %(exc)s\\\",\\n {'volume': volume['name'], 'exc': exc})\\n\\n dst_nms = self._get_nms_for_url(capabilities['nms_url'])\\n dst_snapshot = '%s/%s@%s' % (dst_volume.split('volumes/')[1],\\n volume['name'], snapshot['name'])\\n try:\\n dst_nms.snapshot.destroy(dst_snapshot, '')\\n except utils.NexentaException as exc:\\n LOG.warning(\\\"Cannot delete temporary destination snapshot \\\"\\n \\\"%(dst)s on NexentaStor Appliance: %(exc)s\\\",\\n {'dst': dst_snapshot, 'exc': exc})\\n return True, {'provider_location': share}\",\n \"def create_volume_from_snapshot(self, volume, snapshot):\\n snapshotname = huawei_utils.encode_name(snapshot['id'])\\n\\n snapshot_id = snapshot.get('provider_location', None)\\n if snapshot_id is None:\\n snapshot_id = self.restclient.get_snapshotid_by_name(snapshotname)\\n if snapshot_id is None:\\n err_msg = (_(\\n 'create_volume_from_snapshot: Snapshot %(name)s '\\n 'does not exist.')\\n % {'name': snapshotname})\\n LOG.error(err_msg)\\n raise exception.VolumeBackendAPIException(data=err_msg)\\n\\n lun_info = self.create_volume(volume)\\n\\n tgt_lun_id = lun_info['ID']\\n luncopy_name = huawei_utils.encode_name(volume['id'])\\n\\n LOG.info(_LI(\\n 'create_volume_from_snapshot: src_lun_id: %(src_lun_id)s, '\\n 'tgt_lun_id: %(tgt_lun_id)s, copy_name: %(copy_name)s.'),\\n {'src_lun_id': snapshot_id,\\n 'tgt_lun_id': tgt_lun_id,\\n 'copy_name': luncopy_name})\\n\\n event_type = 'LUNReadyWaitInterval'\\n\\n wait_interval = huawei_utils.get_wait_interval(self.xml_file_path,\\n event_type)\\n\\n def _volume_ready():\\n result = self.restclient.get_lun_info(tgt_lun_id)\\n\\n if (result['HEALTHSTATUS'] == constants.STATUS_HEALTH\\n and result['RUNNINGSTATUS'] == constants.STATUS_VOLUME_READY):\\n return True\\n return False\\n\\n huawei_utils.wait_for_condition(self.xml_file_path,\\n _volume_ready,\\n wait_interval,\\n wait_interval * 10)\\n\\n self._copy_volume(volume, luncopy_name,\\n snapshot_id, tgt_lun_id)\\n\\n return {'ID': lun_info['ID'],\\n 'lun_info': lun_info}\",\n \"def assert_valid_volume(wells,exception_info='invalid volume'):\\n wells = ensure_list(wells)\\n \\n assert all([well.volume >= get_well_dead_volume(well) for well in wells]), exception_info\\n assert all([well.volume <= get_well_max_volume(well) for well in wells]), exception_info\",\n \"def create_volume_from_snapshot(self, volume, snapshot):\\n\\n free_size = self._get_spdk_lvs_free_space(\\n self._get_spdk_lvs_uuid(\\n self._get_spdk_volume_name(snapshot.name)))\\n\\n if free_size < volume.size:\\n raise exception.VolumeBackendAPIException(\\n data=_('Not enough space to create snapshot with SPDK'))\\n\\n return self._create_volume(volume, snapshot)\",\n \"def test_present_wo_existing_volumes():\\n docker_create_volume = Mock(return_value=\\\"created\\\")\\n docker_remove_volume = Mock(return_value=\\\"removed\\\")\\n __salt__ = {\\n \\\"docker.create_volume\\\": docker_create_volume,\\n \\\"docker.remove_volume\\\": docker_remove_volume,\\n \\\"docker.volumes\\\": Mock(return_value={\\\"Volumes\\\": None}),\\n }\\n with patch.dict(docker_state.__dict__, {\\\"__salt__\\\": __salt__}):\\n ret = docker_state.present(\\n \\\"volume_foo\\\",\\n driver=\\\"bar\\\",\\n force=True,\\n )\\n docker_create_volume.assert_called_with(\\n \\\"volume_foo\\\", driver=\\\"bar\\\", driver_opts=None\\n )\\n assert ret == {\\n \\\"name\\\": \\\"volume_foo\\\",\\n \\\"comment\\\": \\\"\\\",\\n \\\"changes\\\": {\\\"created\\\": \\\"created\\\"},\\n \\\"result\\\": True,\\n }\",\n \"def test_create_snapshot(self, mock_ghn):\\n # Now snapshot the volume and check commands\\n snapshot = {'volume_name': 'volume10',\\n 'volume_id': 'xxx', 'display_name': 'snap10',\\n 'name': '123abc', 'volume_size': 10, 'id': '123abc',\\n 'volume': {'provider_id': 'space10'}}\\n ret = self.driver.create_snapshot(snapshot)\\n # We must copy entier underlying storage, ~12GB, not just 10GB\\n self.assertEqual(11444 * units.Mi, self.dd_count)\\n self.assertEqual('1M', self.bs)\\n # Check space-create command\\n expected = {'redundancy': '0', 'group': 'xanadu',\\n 'name': snapshot['display_name'], 'mode': '0777',\\n 'user': 'kane', 'net': 'net1',\\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\\n 'size': '12'}\\n self.assertDictMatch(expected, self.created)\\n # Check the returned provider\\n expected_pid = {'provider_id': 'snap10'}\\n self.assertDictMatch(expected_pid, ret)\",\n \"def test_aws_service_api_volume_get(self):\\n pass\",\n \"def test_snapshot(self):\\n # Try to create a snapshot with a wrong machine_uuid.\\n status = self.proxy.snapshot.create(\\n PROVIDER_ID, \\\"Doesn't exist\\\"\\n )\\n self.check_xmlrpc_command_result(status, has_error=True)\\n\\n # Try to create a snapshot with a wrong provider.\\n status = self.proxy.snapshot.create(\\n \\\"Doesn't exist\\\", self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status, has_error=True)\\n\\n # Create a snapshot.\\n status = self.proxy.snapshot.create(\\n PROVIDER_ID, self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status)\\n\\n # Try to destroy snapshots with a wrong provider.\\n status = self.proxy.snapshot.destroy(\\n \\\"Doesn't exist\\\", self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status, has_error=True)\\n\\n # Destroy snapshots.\\n status = self.proxy.snapshot.destroy(\\n PROVIDER_ID, self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status)\",\n \"def test_snapshots(self):\\n snapshots_dir = REPO_ROOT / \\\"tests\\\" / \\\"snapshots\\\"\\n snapshot_files = set(f.name for f in snapshots_dir.glob(\\\"*.txt\\\"))\\n assert snapshot_files == SNAPSHOTS_USED\",\n \"def _tag_volume():\\n if dry:\\n print('Would tag the new volume.')\\n return True\\n\\n while True:\\n # waiting for the volume to be up to tag it\\n i = _fetch('vm')\\n v = [x for x in i.volumes.all()]\\n if len(v) == 0:\\n # volumes should actually be already there once the IP is up\\n time.sleep(1)\\n else:\\n for x in v:\\n print('Tagging volume ' + x.id + '.')\\n _tag_resource(x)\\n break\",\n \"def snapshot(self, snapshot, keep=0):\\n if keep:\\n until = util.today() + datetime.timedelta(days=keep)\\n snapshot = snapshot + \\\"-keep-until-\\\" + until.strftime(\\\"%Y%m%d\\\")\\n if snapshot in [x.snapname for x in self.ceph.root.snapshots]:\\n self.log.info(\\\"snapshot-exists\\\", snapshot=snapshot)\\n return\\n self.log.info(\\\"snapshot-create\\\", name=snapshot)\\n with self.frozen_vm() as frozen:\\n if frozen:\\n self.ceph.root.snapshots.create(snapshot)\\n else:\\n self.log.error(\\\"snapshot-ignore\\\", reason=\\\"not frozen\\\")\\n raise RuntimeError(\\\"VM not frozen, not making snapshot.\\\")\",\n \"def test_migrate_volume(self, volume, volumes_steps):\\n old_host, _ = volumes_steps.migrate_volume(volume.name)\\n volumes_steps.migrate_volume(volume.name, old_host)\",\n \"def test_volumes_get(self):\\n pass\",\n \"def snapshot(self, name):\\r\\n return self.driver.create_volume_snapshot(volume=self, name=name)\",\n \"def test_delete_snapshot(self):\\n ctxt = context.get_admin_context()\\n extra_specs = {}\\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\\n snapshot = {'id': '1', 'name': 'volume1',\\n 'display_name': '',\\n 'volume_type_id': type_ref['id'],\\n 'size': 10,\\n 'provider_id': 'snap10'}\\n self.driver.delete_snapshot(snapshot)\\n expected = {'name': 'snap10'}\\n self.assertDictMatch(expected, self.deleted)\",\n \"def test_retype_setup_fail_volume_is_available(self, mock_notify):\\n elevated = context.get_admin_context()\\n project_id = self.context.project_id\\n\\n db.volume_type_create(elevated, {'name': 'old', 'extra_specs': {}})\\n old_vol_type = db.volume_type_get_by_name(elevated, 'old')\\n db.volume_type_create(elevated, {'name': 'new', 'extra_specs': {}})\\n new_vol_type = db.volume_type_get_by_name(elevated, 'new')\\n db.quota_create(elevated, project_id, 'volumes_new', 0)\\n\\n volume = tests_utils.create_volume(self.context, size=1,\\n host=CONF.host, status='available',\\n volume_type_id=old_vol_type['id'])\\n\\n api = cinder.volume.api.API()\\n self.assertRaises(exception.VolumeLimitExceeded, api.retype,\\n self.context, volume, new_vol_type['id'])\\n\\n volume = db.volume_get(elevated, volume.id)\\n # FIXME: restore when Bug #1803648 is figured out\\n # mock_notify.assert_not_called()\\n self.assertEqual('available', volume['status'])\",\n \"def issnapshot_available(self, item_name):\\n return False\",\n \"def test_aws_service_api_volume_patch(self):\\n pass\",\n \"def _assert_source_detached(self, volume):\\n if (volume['status'] != \\\"available\\\" or\\n volume['attach_status'] == fields.VolumeAttachStatus.ATTACHED):\\n LOG.error(\\\"Volume must be detached for clone operation.\\\")\\n raise exception.VolumeAttached(volume_id=volume['id'])\",\n \"def show_volume_snapshot(self, snapshot, check=True):\\n cmd = 'cinder snapshot-show ' + snapshot.id\\n\\n exit_code, stdout, stderr = self.execute_command(\\n cmd, timeout=config.SNAPSHOT_SHOW_TIMEOUT, check=check)\\n\\n snapshot_table = output_parser.table(stdout)\\n show_result = {key: value for key, value in snapshot_table['values']}\\n\\n if check:\\n assert_that(show_result['id'], is_(snapshot.id))\\n if snapshot.name:\\n assert_that(show_result['name'], is_(snapshot.name))\\n if snapshot.description:\\n assert_that(show_result['description'],\\n is_(snapshot.description))\",\n \"def test_07_migrate_vm_live_with_snapshots(self):\\n global vm\\n # Get ROOT Volume\\n vol_for_snap = list_volumes(\\n self.apiclient,\\n virtualmachineid=vm.id,\\n listall=True)\\n for vol in vol_for_snap:\\n snapshot = Snapshot.create(\\n self.apiclient,\\n volume_id=vol.id\\n )\\n snapshot.validateState(\\n self.apiclient,\\n snapshotstate=\\\"backedup\\\",\\n )\\n # Migrate all volumes and VMs\\n\\n destinationHost, vol_list = self.helper.get_destination_pools_hosts(self.apiclient, vm, self.host)\\n for v in vol_list:\\n self.helper.check_storpool_volume_iops(self.spapi, v)\\n vm = self.helper.migrateVm(self.apiclient, self.virtual_machine_live_migration_1, destinationHost)\\n\\n destinationHost, vol_list = self.helper.get_destination_pools_hosts(self.apiclient, vm, self.host)\\n for v in vol_list:\\n self.helper.check_storpool_volume_iops(self.spapi, v)\",\n \"def test_least_busy_host_gets_volume(self):\\n volume1 = self.start_service('volume', host='host1')\\n volume2 = self.start_service('volume', host='host2')\\n volume_id1 = self._create_volume()\\n volume1.create_volume(self.context, volume_id1)\\n volume_id2 = self._create_volume()\\n host = self.scheduler.driver.schedule_create_volume(self.context,\\n volume_id2)\\n self.assertEqual(host, 'host2')\\n volume1.delete_volume(self.context, volume_id1)\\n db.volume_destroy(self.context, volume_id2)\\n volume1.kill()\\n volume2.kill()\",\n \"def test_update_volume_stats_error(self):\\n self._fail_host_storage = True\\n actual = self.driver.get_volume_stats(True)\\n self.assertEqual('HGST', actual['vendor_name'])\\n self.assertEqual('hgst', actual['storage_protocol'])\\n self.assertEqual('unknown', actual['total_capacity_gb'])\\n self.assertEqual('unknown', actual['free_capacity_gb'])\\n self.assertEqual(0, actual['reserved_percentage'])\",\n \"def check_volume(vol, srf_names, verbose=True):\\n if verbose:\\n print(\\\" checking volume for validity\\\")\\n print(\\\" ----------------------------\\\")\\n # check if dict\\n if not isinstance(vol, dict):\\n if verbose:\\n print(\\\" vol is not of type dict\\\")\\n return False\\n # check for keys in gli dict\\n in_vol_keys = set(vol)\\n if in_vol_keys == VOL_KEYS:\\n if verbose:\\n print(\\\" vol keys are valid\\\")\\n else:\\n if verbose:\\n print(\\\" vol keys are not valid!\\\")\\n print(\\\" needs: \\\" + \\\" \\\".join(VOL_KEYS))\\n print(\\\" found: \\\" + \\\" \\\".join(map(str, in_vol_keys)))\\n print(\\\" missing: \\\" + \\\" \\\".join(map(str, VOL_KEYS - in_vol_keys)))\\n print(\\\" corrupted: \\\" + \\\" \\\".join(map(str, in_vol_keys - VOL_KEYS)))\\n return False\\n # check NAME\\n if (\\n isinstance(vol[\\\"NAME\\\"], STRTYPE)\\n and not has_whitespaces(vol[\\\"NAME\\\"])\\n and len(vol[\\\"NAME\\\"]) > 0\\n ):\\n if verbose:\\n print(\\\" vol['NAME'] valid\\\")\\n print(\\\" NAME: '\\\" + vol[\\\"NAME\\\"] + \\\"'\\\")\\n else:\\n if verbose:\\n print(\\\" vol['NAME'] not valid\\\")\\n return False\\n # check SURFACES\\n if (\\n isinstance(vol[\\\"SURFACES\\\"], list)\\n and len(vol[\\\"SURFACES\\\"]) > 0\\n and all(srf in srf_names for srf in vol[\\\"SURFACES\\\"])\\n ):\\n if verbose:\\n print(\\\" vol['SURFACES'] valid\\\")\\n else:\\n if verbose:\\n print(\\\" vol['SURFACES'] not valid\\\")\\n return False\\n # check TYPE\\n if vol[\\\"TYPE\\\"] is None or isinstance(vol[\\\"TYPE\\\"], int):\\n if verbose:\\n print(\\\" vol['TYPE'] valid\\\")\\n else:\\n if verbose:\\n print(\\\" vol['TYPE'] not valid\\\")\\n return False\\n # check MAT_GROUP\\n if vol[\\\"MAT_GROUP\\\"] is None or isinstance(vol[\\\"MAT_GROUP\\\"], int):\\n if verbose:\\n print(\\\" vol['MAT_GROUP'] valid\\\")\\n else:\\n if verbose:\\n print(\\\" vol['MAT_GROUP'] not valid\\\")\\n return False\\n # check LAYER\\n if vol[\\\"LAYER\\\"] is None or isinstance(vol[\\\"LAYER\\\"], int):\\n if verbose:\\n print(\\\" vol['LAYER'] valid\\\")\\n else:\\n if verbose:\\n print(\\\" vol['LAYER'] not valid\\\")\\n return False\\n # finally\\n if verbose:\\n print(\\\" ------------\\\")\\n print(\\\" vol is valid\\\")\\n print(\\\"\\\")\\n return True\",\n \"def create_snapshot(self, volume_id, notes='No longer needed'):\\r\\n\\r\\n self.iscsi_svc.createSnapshot(notes, id=volume_id)\",\n \"def creation_validation(**_):\\n\\n for property_key in constants.VOLUME_REQUIRED_PROPERTIES:\\n utils.validate_node_property(property_key, ctx.node.properties)\\n\\n volume_object = _get_volumes_from_id(utils.get_resource_id())\\n\\n if ctx.node.properties['use_external_resource'] and not volume_object:\\n raise NonRecoverableError(\\n 'External resource, but the supplied '\\n 'EBS volume does not exist in the account.')\\n\\n if not ctx.node.properties['use_external_resource'] and volume_object:\\n raise NonRecoverableError(\\n 'Not external resource, but the supplied '\\n 'EBS volume exists in the account.')\",\n \"def volumes(self):\",\n \"def get_snapshots(self):\\r\\n ec2 = self.get_ec2_connection()\\r\\n rs = ec2.get_all_snapshots()\\r\\n all_vols = [self.volume_id] + self.past_volume_ids\\r\\n snaps = []\\r\\n for snapshot in rs:\\r\\n if snapshot.volume_id in all_vols:\\r\\n if snapshot.progress == '100%':\\r\\n snapshot.date = dateutil.parser.parse(snapshot.start_time)\\r\\n snapshot.keep = True\\r\\n snaps.append(snapshot)\\r\\n snaps.sort(cmp=lambda x,y: cmp(x.date, y.date))\\r\\n return snaps\",\n \"def test_least_busy_host_gets_volume_no_queue(self):\\n volume1 = service.Service('host1',\\n 'nova-volume',\\n 'volume',\\n FLAGS.volume_manager)\\n volume1.start()\\n volume2 = service.Service('host2',\\n 'nova-volume',\\n 'volume',\\n FLAGS.volume_manager)\\n volume2.start()\\n volume_id1 = self._create_volume()\\n volume1.create_volume(self.context, volume_id1)\\n volume_id2 = self._create_volume()\\n host = self.scheduler.driver.schedule_create_volume(self.context,\\n volume_id2)\\n self.assertEqual(host, 'host2')\\n volume1.delete_volume(self.context, volume_id1)\\n db.volume_destroy(self.context, volume_id2)\",\n \"def test_no_snapshots(self):\\n def get_snapshots(*_args, **_kwargs):\\n return {}\\n self.mock(snapshots.gce.Project, 'get_snapshots', get_snapshots)\\n\\n key = self.create_entity('project', 'name', ['key:value'])\\n urls = snapshots.fetch(key)\\n self.failIf(urls)\",\n \"def volume_exists(vil, vol_name):\\n\\n exists = False\\n try:\\n if not vil:\\n vil, err = get_basic_volume_info_all()\\n if err:\\n raise Exception(err)\\n if vil:\\n for v in vil:\\n if v[\\\"name\\\"] == vol_name:\\n exists = True\\n except Exception, e:\\n return False, 'Error checking for volume existance : %s' % str(e)\\n else:\\n return exists, None\",\n \"def test_update_volume_stats_cached(self):\\n self._fail_host_storage = True\\n actual = self.driver.get_volume_stats(False)\\n self.assertEqual('HGST', actual['vendor_name'])\\n self.assertEqual('hgst', actual['storage_protocol'])\\n self.assertEqual(90, actual['total_capacity_gb'])\\n self.assertEqual(87, actual['free_capacity_gb'])\\n self.assertEqual(0, actual['reserved_percentage'])\",\n \"def _wait_until_volume_available(self, volume, maybe_in_use=False):\\n ok_states = [\\\"creating\\\"] # it's ok to wait if the volume is in this\\n tries = 0\\n if maybe_in_use:\\n ok_states.append(\\\"in_use\\\")\\n logger.info(\\\"Volume: %s is in state: %s\\\", volume.name, volume.state)\\n while volume.state in ok_states:\\n sleep(3)\\n volume = self.get_volume(volume.name)\\n tries = tries + 1\\n if tries > 10:\\n logger.info(\\\"Maximum amount of tries reached..\\\")\\n break\\n if volume.state == \\\"notfound\\\":\\n logger.error(\\\"no volume was found for: %s\\\", volume.name)\\n break\\n logger.info(\\\" ... %s\\\", volume.state)\\n if volume.state != \\\"available\\\":\\n # OVH uses a non-standard state of 3 to indicate an available\\n # volume\\n logger.info(\\\"Volume %s is %s (not available)\\\", volume.name, volume.state)\\n logger.info(\\n \\\"The volume %s is not available, but will continue anyway...\\\",\\n volume.name,\\n )\\n return True\",\n \"def test_06_create_snapshots_in_project(self):\\n # Validate the following\\n # 1. Create a project\\n # 2. Add some snapshots to the project\\n # 3. Verify snapshot created inside project can only be used in inside\\n # the project\\n\\n if not self.snapshotSupported:\\n self.skipTest(\\\"Snapshot is not supported on %s\\\" % self.hypervisor)\\n\\n self.debug(\\\"Deploying VM for Project: %s\\\" % self.project.id)\\n virtual_machine_1 = VirtualMachine.create(\\n self.apiclient,\\n self.services[\\\"server\\\"],\\n templateid=self.template.id,\\n serviceofferingid=self.service_offering.id,\\n projectid=self.project.id\\n )\\n self.cleanup.append(virtual_machine_1)\\n # Verify VM state\\n self.assertEqual(\\n virtual_machine_1.state,\\n 'Running',\\n \\\"Check VM state is Running or not\\\"\\n )\\n\\n # Get the Root disk of VM\\n volumes = list_volumes(\\n self.apiclient,\\n projectid=self.project.id,\\n type='ROOT',\\n listall=True\\n )\\n self.assertEqual(\\n isinstance(volumes, list),\\n True,\\n \\\"Check for list volume response return valid data\\\"\\n )\\n\\n self.debug(\\\"Creating snapshot from volume: %s\\\" % volumes[0].id)\\n # Create a snapshot from the ROOTDISK\\n snapshot = Snapshot.create(self.apiclient,\\n volumes[0].id,\\n projectid=self.project.id\\n )\\n self.cleanup.append(snapshot)\\n # Verify Snapshot state\\n self.assertEqual(\\n snapshot.state in [\\n 'BackedUp',\\n 'CreatedOnPrimary',\\n 'Allocated'\\n ],\\n True,\\n \\\"Check Snapshot state is in one of the mentioned possible states, \\\\\\n It is currently: %s\\\" % snapshot.state\\n )\\n\\n snapshots = Snapshot.list(\\n self.apiclient,\\n account=self.account.name,\\n domainid=self.account.domainid\\n )\\n self.assertEqual(\\n snapshots,\\n None,\\n \\\"Snapshots should not be available outside the project\\\"\\n )\\n return\",\n \"def sync_volume_record( volume ):\\n \\n logger.info( \\\"Sync Volume = %s\\\\n\\\\n\\\" % volume.name )\\n \\n principal_id = volume.owner_id.email\\n config = observer_core.get_config()\\n \\n max_UGs = None \\n max_RGs = None\\n volume_principal_id = observer_core.make_volume_principal_id( principal_id, volume.name )\\n\\n # get the observer secret \\n try:\\n max_UGs = CONFIG.SYNDICATE_UG_QUOTA \\n max_RGs = CONFIG.SYNDICATE_RG_QUOTA\\n observer_secret = observer_core.get_syndicate_observer_secret( config.SYNDICATE_OBSERVER_SECRET )\\n except Exception, e:\\n traceback.print_exc()\\n logger.error(\\\"config is missing SYNDICATE_OBSERVER_SECRET, SYNDICATE_UG_QUOTA, SYNDICATE_RG_QUOTA\\\")\\n raise e\\n \\n # volume owner must exist as a Syndicate user...\\n try:\\n rc, user = observer_core.ensure_principal_exists( volume_principal_id, observer_secret, is_admin=False, max_UGs=max_UGs, max_RGs=max_RGs)\\n assert rc == True, \\\"Failed to create or read volume principal '%s'\\\" % volume_principal_id\\n except Exception, e:\\n traceback.print_exc()\\n logger.error(\\\"Failed to ensure principal '%s' exists\\\" % volume_principal_id )\\n raise e\\n\\n # volume must exist \\n # create or update the Volume\\n try:\\n new_volume = observer_core.ensure_volume_exists( volume_principal_id, volume, user=user )\\n except Exception, e:\\n traceback.print_exc()\\n logger.error(\\\"Failed to ensure volume '%s' exists\\\" % volume.name )\\n raise e\\n \\n # did we create the Volume?\\n if new_volume is not None:\\n # we're good\\n pass \\n \\n # otherwise, just update it \\n else:\\n try:\\n rc = observer_core.update_volume( volume )\\n except Exception, e:\\n traceback.print_exc()\\n logger.error(\\\"Failed to update volume '%s', exception = %s\\\" % (volume.name, e.message))\\n raise e\\n \\n return True\",\n \"def snapshots(self, owner=None, restorable_by=None):\\r\\n rs = self.connection.get_all_snapshots(owner=owner,\\r\\n restorable_by=restorable_by)\\r\\n mine = []\\r\\n for snap in rs:\\r\\n if snap.volume_id == self.id:\\r\\n mine.append(snap)\\r\\n return mine\",\n \"def delete_volume_snapshot(volume_snapshots):\\n if type(volume_snapshots) is not list:\\n volumes = [volume_snapshots]\\n command = 'cinder snapshot-delete %s' % \\\\\\n \\\" \\\".join(snapshot['id'] for snapshot in volume_snapshots)\\n d = Popen(command.split(), stdout=STDOUT, stderr=STDERR).communicate()[0]\",\n \"def ensure_export(self, context, volume):\\n pass\",\n \"def test_snapshot_unspecified(self):\\n key = self.create_entity('project', None, [])\\n urls = snapshots.fetch(key)\\n self.failIf(urls)\",\n \"def ensure_volume_exists( user_email, opencloud_volume, user=None ):\\n client = connect_syndicate()\\n\\n try:\\n volume = client.read_volume( opencloud_volume.name )\\n except Exception, e:\\n # transport error \\n logger.exception(e)\\n raise e\\n\\n if volume is None:\\n # the volume does not exist....try to create it \\n vol_name = opencloud_volume.name\\n vol_blocksize = opencloud_volume.blocksize\\n vol_description = opencloud_volume.description\\n vol_private = opencloud_volume.private\\n vol_archive = opencloud_volume.archive \\n vol_default_gateway_caps = opencloud_caps_to_syndicate_caps( opencloud_volume.cap_read_data, opencloud_volume.cap_write_data, opencloud_volume.cap_host_data )\\n\\n try:\\n vol_info = client.create_volume( user_email, vol_name, vol_description, vol_blocksize,\\n private=vol_private,\\n archive=vol_archive,\\n active=True,\\n default_gateway_caps=vol_default_gateway_caps,\\n store_private_key=False,\\n metadata_private_key=\\\"MAKE_METADATA_KEY\\\" )\\n\\n except Exception, e:\\n # transport error\\n logger.exception(e)\\n raise e\\n\\n else:\\n # successfully created the volume!\\n return vol_info\\n\\n else:\\n \\n # volume already exists. Verify its owned by this user.\\n if user is None:\\n try:\\n user = client.read_user( volume['owner_id'] )\\n except Exception, e:\\n # transport error, or user doesn't exist (either is unacceptable)\\n logger.exception(e)\\n raise e\\n\\n if user is None or user['email'] != user_email:\\n raise Exception(\\\"Volume '%s' already exists, but is NOT owned by '%s'\\\" % (opencloud_volume.name, user_email) )\\n\\n # we're good!\\n return None\",\n \"def test_attachment_create_volume_in_error_state(self):\\n volume_params = {'status': 'available'}\\n\\n vref = tests_utils.create_volume(self.context, **volume_params)\\n vref.status = \\\"error\\\"\\n self.assertRaises(exception.InvalidVolume,\\n self.volume_api.attachment_create,\\n self.context,\\n vref,\\n fake.UUID2)\",\n \"def create(self, filesystem=None):\\n if not self.size and not self.from_snapshot_id and not self.from_archive:\\n log.error('Cannot add a {0} volume without a size, snapshot ID or '\\n 'archive url; aborting.'.format(self.fs))\\n return False\\n # If creating the volume from a snaphost, get the expected volume size\\n if self.from_snapshot_id and not self.volume:\\n self.snapshot = self.app.cloud_interface.get_snapshot(self.from_snapshot_id)\\n if not self.snapshot:\\n log.error(\\\"Did not retrieve Snapshot object for {0}; aborting.\\\"\\n .format(self.from_snapshot_id))\\n return False\\n # We need a size to be able to create a volume, so if none\\n # is specified, use snapshot size\\n if not self.size:\\n si = self.app.cloud_interface.get_snapshot_info(self.from_snapshot_id)\\n self.size = si.get('volume_size')\\n # If it does not already exist, create the volume\\n if self.status == volume_status.NONE:\\n log.debug(\\\"Creating a new volume of size '%s' in zone '%s' from \\\"\\n \\\"snapshot '%s' for %s.\\\"\\n % (self.size, self.app.cloud_interface.get_zone(),\\n self.from_snapshot_id, self.fs))\\n self.volume = self.app.cloud_interface.create_volume(\\n self.size,\\n self.app.cloud_interface.get_zone(),\\n snapshot=self.from_snapshot_id)\\n if self.volume:\\n # When creating from a snapshot in Euca, volume.size may be None\\n self.size = int(self.volume.size or 0)\\n log.debug(\\\"Created a new volume of size '%s' from snapshot '%s' \\\"\\n \\\"with ID '%s' in zone '%s' for %s.\\\"\\n % (self.size, self.from_snapshot_id, self.volume_id,\\n self.app.cloud_interface.get_zone(), self.fs))\\n else:\\n log.warning(\\\"No volume object - did not create a volume?\\\")\\n return False\\n else:\\n log.debug(\\\"Tried to create a volume for %s but it is in state '%s' \\\"\\n \\\"(volume ID: %s)\\\" % (self.fs, self.status, self.volume_id))\\n return False\\n # Add tags to newly created volumes (do this outside the inital if/else\\n # to ensure the tags get assigned even if using an existing volume vs.\\n # creating a new one)\\n self.app.cloud_interface.add_tag(\\n self.volume, 'Name', self.app.config['cluster_name'])\\n self.app.cloud_interface.add_tag(\\n self.volume, 'bucketName', self.app.config['bucket_cluster'])\\n if self.fs:\\n self.app.cloud_interface.add_tag(\\n self.volume, 'filesystem', self.fs.get_full_name())\\n self.app.cloud_interface.add_tag(\\n self.volume, 'roles', ServiceRole.to_string(self.fs.svc_roles))\\n return True\",\n \"def volume_in_use(self):\\n return self._volume_status_check(STATUS_IN_USE, False, 0, 0)\",\n \"def verify_no_snapshot_reingestion(c: Composition) -> None:\\n c.run(\\\"testdrive\\\", \\\"wait-for-snapshot.td\\\", \\\"postgres-disable-select-permission.td\\\")\\n\\n restart_mz(c)\\n\\n c.run(\\n \\\"testdrive\\\",\\n \\\"delete-rows-t1.td\\\",\\n \\\"delete-rows-t2.td\\\",\\n \\\"alter-table.td\\\",\\n \\\"alter-mz.td\\\",\\n )\",\n \"def snap_status(mnode, snapname=\\\"\\\", volname=\\\"\\\"):\\n\\n if snapname != \\\"\\\" and volname != \\\"\\\":\\n g.log.error(\\\"Incorrect cmd. snap status cli accepts either \\\"\\n \\\"snapname or volname\\\")\\n return (-1, None, None)\\n\\n if volname != '':\\n volname = \\\"volume %s\\\" % volname\\n\\n cmd = \\\"gluster snapshot status %s %s\\\" % (snapname, volname)\\n return g.run(mnode, cmd)\",\n \"def test_volume_extend(self, volume, volumes_steps):\\n volumes_steps.extend_volume(volume.name)\",\n \"def test_aws_service_api_volumes_get(self):\\n pass\",\n \"def migrate_volume(self, volume, host):\\n false_ret = (False, None)\\n if volume['attach_status'] == fields.VolumeAttachStatus.ATTACHED:\\n return false_ret\\n if 'location_info' not in host['capabilities']:\\n return false_ret\\n info = host['capabilities']['location_info']\\n try:\\n (dest_type, dest_id,\\n dest_back_name, dest_owner) = info.split(':')\\n except ValueError:\\n return false_ret\\n\\n reqd_dest_type = '%sVolumeDriver' % self.vendor_name\\n if not (dest_type == reqd_dest_type and\\n dest_id == self.serialNumber and\\n dest_owner == self.owner):\\n return false_ret\\n if volume['name_id']:\\n source_name = self._get_vol_name(volume['name_id'])\\n else:\\n source_name = self._get_vol_name(volume['id'])\\n # the array does not support duplicate names\\n dest_name = \\\"m%s\\\" % source_name[1:]\\n\\n self.client_login()\\n try:\\n self.client.copy_volume(source_name, dest_name,\\n dest_back_name, self.backend_type)\\n self.client.delete_volume(source_name)\\n self.client.modify_volume_name(dest_name, source_name)\\n return (True, None)\\n except stx_exception.RequestError as ex:\\n LOG.exception(\\\"Error migrating volume: %s\\\", source_name)\\n raise exception.Invalid(ex)\\n finally:\\n self.client_logout()\",\n \"def booted_from_volume(volumes_list):\\n if any('/dev/vda' in volume['attachments'] for volume in\\n volumes_list):\\n return True\\n return False\",\n \"def test_delete_source_volume_in_migration(self):\\n self._test_delete_volume_in_migration('migrating')\",\n \"def manage(self, volume_id, ref, name=None, description=None,\\n metadata=None):\\n body = {'snapshot': {'volume_id': volume_id,\\n 'ref': ref,\\n 'name': name,\\n 'description': description,\\n 'metadata': metadata\\n }\\n }\\n return self._create('/os-snapshot-manage', body, 'snapshot')\",\n \"def check_snapshots(grafana_server):\\n print(info + \\\" Checking if snapshot api requires authentiation...\\\" + end)\\n \\n response = send_request(grafana_server+\\\"/api/snapshots\\\", \\\"POST\\\")\\n \\n if (response) == 401:\\n print(bad + \\\" Snapshot endpoint requires authentication! Host not vulnerable.\\\" + end)\\n elif (response) == 415:\\n print(good + \\\" Snapshot endpoint doesn't seem to require authentication! Host may be vulnerable.\\\" + end)\\n else:\\n print(info + \\\" Didn't received expected status code when checking snapshot API. Check again.\\\" + end)\\n\\n return\",\n \"def bootable_volume(volumes):\\n for volume in volumes:\\n if '/dev/vda' in volume['attachments']:\\n return volume\",\n \"def database_volume_snapshot_delete(volume_snapshot_uuid):\\n db = database_get()\\n session = db.session()\\n query = session.query(model.VolumeSnapshot)\\n query.filter(model.VolumeSnapshot.uuid == volume_snapshot_uuid).delete()\\n session.commit()\",\n \"def test_aws_service_api_snapshots_get(self):\\n pass\",\n \"def test_create_volume(self, mock_ghn):\\n ctxt = context.get_admin_context()\\n extra_specs = {}\\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\\n volume = {'id': '1', 'name': 'volume1',\\n 'display_name': '',\\n 'volume_type_id': type_ref['id'],\\n 'size': 10}\\n ret = self.driver.create_volume(volume)\\n expected = {'redundancy': '0', 'group': 'xanadu',\\n 'name': 'volume10', 'mode': '0777',\\n 'user': 'kane', 'net': 'net1',\\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\\n 'size': '12'}\\n self.assertDictMatch(expected, self.created)\\n # Check the returned provider, note that provider_id is hashed\\n expected_pid = {'provider_id': 'volume10'}\\n self.assertDictMatch(expected_pid, ret)\",\n \"def find_recovery_on_volume(volume):\\n return _find(volume, RECOVERY_ON_VOLUME_TABLE)\",\n \"def test_snapshot_compatibility(microvm_factory, guest_kernel, rootfs):\\n vm = microvm_factory.build(guest_kernel, rootfs)\\n vm.spawn()\\n vm.basic_config(\\n vcpu_count=2,\\n mem_size_mib=256,\\n )\\n\\n # Add a memory balloon with stats enabled.\\n vm.api.balloon.put(amount_mib=0, deflate_on_oom=True, stats_polling_interval_s=1)\\n\\n vm.start()\\n vm.snapshot_full()\",\n \"def test_update_volume_stats(self):\\n actual = self.driver.get_volume_stats(True)\\n self.assertEqual('HGST', actual['vendor_name'])\\n self.assertEqual('hgst', actual['storage_protocol'])\\n self.assertEqual(90, actual['total_capacity_gb'])\\n self.assertEqual(87, actual['free_capacity_gb'])\\n self.assertEqual(0, actual['reserved_percentage'])\",\n \"def test_snapshots_size(self):\\n snapshots_dir = REPO_ROOT / \\\"tests\\\" / \\\"snapshots\\\"\\n small_snapshots = []\\n for f in snapshots_dir.glob(\\\"*.txt\\\"):\\n if f.stat().st_size <= 150:\\n small_snapshots.append(f\\\"- {f.name}\\\")\\n if small_snapshots:\\n offenders = \\\"\\\\n\\\".join(small_snapshots)\\n assert False, (\\n \\\"Very small snapshot files are problematic.\\\\n\\\"\\n \\\"Offending snapshot files:\\\\n\\\"\\n f\\\"{offenders}\\\\n\\\"\\n \\\"Consider refacotring them to avoid using snapshots. Tests that use \\\"\\n \\\"snapshots are harder to reason about when they fail. Whenever possilbe \\\"\\n \\\"a test with inline data is much easier to reason about and refactor.\\\"\\n )\",\n \"def execute(self):\\n\\n c = self.config\\n regions = dict((x.name, x) for x in boto.ec2.regions(\\n aws_access_key_id=c['access_key'],\\n aws_secret_access_key=c['secret_access_key']))\\n connect = regions[c['region']].connect(\\n aws_access_key_id=c['access_key'],\\n aws_secret_access_key=c['secret_access_key'])\\n volume = connect.get_all_volumes([c['volume_id']])[0]\\n volume.create_snapshot(c['volume_id'])\\n snapshots = {}\\n for x in connect.get_all_snapshots():\\n if x.volume_id == c['volume_id']:\\n snapshots.update({x.id: x.start_time})\\n snapshots = sorted(snapshots.items(), key=lambda (k, v): (v, k), reverse=True)\\n for i in range(int(c['keep']), len(snapshots)):\\n connect.delete_snapshot(snapshots[i][0])\",\n \"def create_snapshot(volume_name, volume_id):\\n\\tif cliargs.verbose:\\n\\t\\tprint \\\"Will snapshot '%s' and tag it with '%s'\\\" % (volume_id, volume_name)\\n\\n\\tresponse = ec2.create_snapshot(VolumeId=volume_id, Description=volume_name)\\n\\tif response:\\n\\t\\tec2.create_tags(Resources=[response[\\\"SnapshotId\\\"]], Tags=[{\\\"Key\\\": \\\"Name\\\", \\\"Value\\\": volume_name}])\",\n \"def checkForVolumeWarnings(self,master,merge):\\n warnings = \\\"\\\"\\n if not master:\\n warnings = \\\"Missing master volume\\\"\\n if merge:\\n if not master.GetImageData() or not merge.GetImageData():\\n return \\\"Missing image data\\\"\\n if master.GetImageData().GetDimensions() != merge.GetImageData().GetDimensions():\\n warnings += \\\"Volume dimensions do not match\\\\n\\\"\\n if master.GetImageData().GetSpacing() != merge.GetImageData().GetSpacing():\\n warnings += \\\"Volume spacings do not match\\\\n\\\"\\n if master.GetImageData().GetOrigin() != merge.GetImageData().GetOrigin():\\n warnings += \\\"Volume spacings do not match\\\\n\\\"\\n # if merge.GetScalarType() != vtk.VTK_SHORT:\\n # warnings += \\\"Label map must be of type Short (Use Cast Scalar Volume to fix)\\\\n\\\"\\n # if master.GetLabelMap():\\n # if master.GetImageData().GetScalarType() != vtk.VTK_SHORT:\\n # warnings += \\\"Label map must be of type Short (Use Cast Scalar Volume to fix)\\\\n\\\"\\n masterIJKToRAS = vtk.vtkMatrix4x4()\\n mergeIJKToRAS = vtk.vtkMatrix4x4()\\n master.GetIJKToRASMatrix(masterIJKToRAS)\\n merge.GetIJKToRASMatrix(mergeIJKToRAS)\\n for row in range(4):\\n for column in range(4):\\n if masterIJKToRAS.GetElement(row,column) != mergeIJKToRAS.GetElement(row,column):\\n warnings += \\\"Volume geometry does not match (Resample to fix)\\\\n\\\"\\n print(\\\"coor: \\\" + str(row) + \\\" \\\" + str(column) + \\\" \\\" + str(masterIJKToRAS.GetElement(row,column)) + \\\" \\\" + str(mergeIJKToRAS.GetElement(row,column)))\\n break\\n else:\\n warnings += \\\"Missing merge volume\\\"\\n return warnings\",\n \"def create_snapshot(args, **_):\\n\\n volume_id = \\\\\\n utils.get_external_resource_id_or_raise(\\n 'create snapshot', ctx.instance)\\n\\n ctx.logger.info(\\n 'Trying to create a snapshot of EBS volume {0}.'\\n .format(volume_id))\\n\\n volume_object = _get_volumes_from_id(volume_id)\\n\\n if not args:\\n snapshot_desc = \\\\\\n unicode(datetime.datetime.now()) + \\\\\\n ctx.instance.runtime_properties[constants.EXTERNAL_RESOURCE_ID]\\n args = dict(description=snapshot_desc)\\n\\n try:\\n new_snapshot = volume_object.create_snapshot(**args)\\n except (boto.exception.EC2ResponseError,\\n boto.exception.BotoServerError) as e:\\n raise NonRecoverableError('{0}'.format(str(e)))\\n\\n ctx.logger.info(\\n 'Created snapshot of EBS volume {0}.'.format(volume_id))\\n\\n if constants.VOLUME_SNAPSHOT_ATTRIBUTE not in \\\\\\n ctx.instance.runtime_properties:\\n ctx.instance.runtime_properties[\\n constants.VOLUME_SNAPSHOT_ATTRIBUTE] = list()\\n\\n ctx.instance.runtime_properties[\\n constants.VOLUME_SNAPSHOT_ATTRIBUTE].append(new_snapshot.id)\",\n \"def _create_snapshot(connection, volume, name=''):\\n logging.info(kayvee.formatLog(\\\"ebs-snapshots\\\", \\\"info\\\", \\\"creating new snapshot\\\", {\\\"volume\\\": volume.id}))\\n snapshot = volume.create_snapshot(\\n description=\\\"automatic snapshot by ebs-snapshots\\\")\\n if not name:\\n name = '{}-snapshot'.format(volume.id)\\n connection.create_tags(\\n [snapshot.id], dict(Name=name, creator='ebs-snapshots'))\\n logging.info(kayvee.formatLog(\\\"ebs-snapshots\\\", \\\"info\\\", \\\"created snapshot successfully\\\", {\\n \\\"name\\\": name,\\n \\\"volume\\\": volume.id,\\n \\\"snapshot\\\": snapshot.id\\n }))\\n return snapshot\",\n \"def derived_snapshots(self):\\n start_time = time.time()\\n log.debug(\\\"Getting snaps derived from volume {0}.\\\".format(self.volume_id))\\n derived_snapshots = []\\n for snap in self.app.cloud_interface.get_all_snapshots():\\n try:\\n if snap.volume_id == self.volume_id:\\n derived_snapshots.append(snap)\\n except EC2ResponseError, e:\\n log.warning(\\\"EC2ResponseError getting snapshot status: {0} \\\"\\n \\\"(code {1}; status {2})\\\"\\n .format(e.message, e.error_code, e.status))\\n log.debug(\\\"Got snaps derived from volume {0} in {1} seconds: {2}\\\"\\n .format(self.volume_id, time.time() - start_time, derived_snapshots))\\n return derived_snapshots\",\n \"def test_csi_volumesnapshot_basic(set_random_backupstore, # NOQA\\n volumesnapshotclass, # NOQA\\n volumesnapshot, # NOQA\\n client, # NOQA\\n core_api, # NOQA\\n volume_name, # NOQA\\n csi_pv, # NOQA\\n pvc, # NOQA\\n pod_make, # NOQA\\n volsnapshotclass_delete_policy, # NOQA\\n backup_is_deleted): # NOQA\\n\\n csisnapclass = \\\\\\n volumesnapshotclass(name=\\\"snapshotclass\\\",\\n deletepolicy=volsnapshotclass_delete_policy)\\n\\n pod_name, pv_name, pvc_name, md5sum = \\\\\\n prepare_pod_with_data_in_mb(client, core_api,\\n csi_pv, pvc, pod_make,\\n volume_name,\\n data_path=\\\"/data/test\\\")\\n\\n # Create volumeSnapshot test\\n csivolsnap = volumesnapshot(volume_name + \\\"-volumesnapshot\\\",\\n \\\"default\\\",\\n csisnapclass[\\\"metadata\\\"][\\\"name\\\"],\\n \\\"persistentVolumeClaimName\\\",\\n pvc_name)\\n\\n volume = client.by_id_volume(volume_name)\\n\\n for i in range(RETRY_COUNTS):\\n snapshots = volume.snapshotList()\\n if len(snapshots) == 2:\\n break\\n time.sleep(RETRY_INTERVAL)\\n\\n lh_snapshot = None\\n snapshots = volume.snapshotList()\\n for snapshot in snapshots:\\n if snapshot[\\\"name\\\"] == \\\"snapshot-\\\" + csivolsnap[\\\"metadata\\\"][\\\"uid\\\"]:\\n lh_snapshot = snapshot\\n assert lh_snapshot is not None\\n\\n wait_for_volumesnapshot_ready(csivolsnap[\\\"metadata\\\"][\\\"name\\\"],\\n csivolsnap[\\\"metadata\\\"][\\\"namespace\\\"])\\n\\n bv1, b = find_backup(client, volume_name, lh_snapshot[\\\"name\\\"])\\n\\n assert b[\\\"snapshotName\\\"] == lh_snapshot[\\\"name\\\"]\\n\\n restore_pvc_name = pvc[\\\"metadata\\\"][\\\"name\\\"] + \\\"-restore\\\"\\n restore_pvc_size = pvc[\\\"spec\\\"][\\\"resources\\\"][\\\"requests\\\"][\\\"storage\\\"]\\n\\n restore_csi_volume_snapshot(core_api,\\n client,\\n csivolsnap,\\n restore_pvc_name,\\n restore_pvc_size)\\n\\n restore_pod = pod_make()\\n restore_pod_name = restore_pod[\\\"metadata\\\"][\\\"name\\\"]\\n restore_pod['spec']['volumes'] = [create_pvc_spec(restore_pvc_name)]\\n\\n create_and_wait_pod(core_api, restore_pod)\\n restore_md5sum = \\\\\\n get_pod_data_md5sum(core_api, restore_pod_name, path=\\\"/data/test\\\")\\n assert restore_md5sum == md5sum\\n\\n # Delete volumeSnapshot test\\n delete_volumesnapshot(csivolsnap[\\\"metadata\\\"][\\\"name\\\"], \\\"default\\\")\\n\\n if backup_is_deleted is False:\\n find_backup(client, volume_name, b[\\\"snapshotName\\\"])\\n else:\\n wait_for_backup_delete(client, volume_name, b[\\\"name\\\"])\",\n \"def _attach_volume(self):\\n return []\",\n \"def test_finish_resize_with_volumes(self):\\n\\n # create instance\\n instance = self._create_fake_instance_obj()\\n request_spec = objects.RequestSpec()\\n\\n # create volume\\n volume = {'instance_uuid': None,\\n 'device_name': None,\\n 'id': uuids.volume,\\n 'size': 200,\\n 'attach_status': 'detached'}\\n bdm = objects.BlockDeviceMapping(\\n **{'context': self.context,\\n 'source_type': 'volume',\\n 'destination_type': 'volume',\\n 'volume_id': uuids.volume,\\n 'instance_uuid': instance['uuid'],\\n 'device_name': '/dev/vdc'})\\n bdm.create()\\n\\n # stub out volume attach\\n def fake_volume_get(self, context, volume_id, microversion=None):\\n return volume\\n self.stub_out('nova.volume.cinder.API.get', fake_volume_get)\\n\\n def fake_volume_check_availability_zone(self, context,\\n volume_id, instance):\\n pass\\n self.stub_out('nova.volume.cinder.API.check_availability_zone',\\n fake_volume_check_availability_zone)\\n\\n def fake_get_volume_encryption_metadata(self, context, volume_id):\\n return {}\\n self.stub_out('nova.volume.cinder.API.get_volume_encryption_metadata',\\n fake_get_volume_encryption_metadata)\\n\\n orig_connection_data = {\\n 'target_discovered': True,\\n 'target_iqn': 'iqn.2010-10.org.openstack:%s.1' % uuids.volume_id,\\n 'target_portal': '127.0.0.0.1:3260',\\n 'volume_id': uuids.volume_id,\\n }\\n connection_info = {\\n 'driver_volume_type': 'iscsi',\\n 'data': orig_connection_data,\\n }\\n\\n def fake_init_conn(self, context, volume_id, session):\\n return connection_info\\n self.stub_out('nova.volume.cinder.API.initialize_connection',\\n fake_init_conn)\\n\\n def fake_attach(self, context, volume_id, instance_uuid, device_name,\\n mode='rw'):\\n volume['instance_uuid'] = instance_uuid\\n volume['device_name'] = device_name\\n self.stub_out('nova.volume.cinder.API.attach', fake_attach)\\n\\n # stub out virt driver attach\\n def fake_get_volume_connector(*args, **kwargs):\\n return {}\\n self.stub_out('nova.virt.fake.FakeDriver.get_volume_connector',\\n fake_get_volume_connector)\\n\\n def fake_attach_volume(*args, **kwargs):\\n pass\\n self.stub_out('nova.virt.fake.FakeDriver.attach_volume',\\n fake_attach_volume)\\n\\n # attach volume to instance\\n self.compute.attach_volume(self.context, instance, bdm)\\n\\n # assert volume attached correctly\\n self.assertEqual(volume['device_name'], '/dev/vdc')\\n disk_info = db.block_device_mapping_get_all_by_instance(\\n self.context, instance.uuid)\\n self.assertEqual(len(disk_info), 1)\\n for bdm in disk_info:\\n self.assertEqual(bdm['device_name'], volume['device_name'])\\n self.assertEqual(bdm['connection_info'],\\n jsonutils.dumps(connection_info))\\n\\n # begin resize\\n flavor = self.default_flavor\\n instance.task_state = task_states.RESIZE_PREP\\n instance.save()\\n self.compute.prep_resize(self.context, instance=instance,\\n flavor=flavor,\\n image={}, request_spec=request_spec,\\n filter_properties={}, node=None,\\n clean_shutdown=True, migration=None,\\n host_list=[])\\n\\n # fake out detach for prep_resize (and later terminate)\\n def fake_terminate_connection(self, context, volume, connector):\\n connection_info['data'] = None\\n self.stub_out('nova.volume.cinder.API.terminate_connection',\\n fake_terminate_connection)\\n\\n migration = objects.Migration.get_by_instance_and_status(\\n self.context.elevated(),\\n instance.uuid, 'pre-migrating')\\n self.compute.resize_instance(self.context, instance=instance,\\n migration=migration, image={},\\n # TODO(stephenfin): Why a JSON string?\\n flavor=jsonutils.to_primitive(flavor),\\n clean_shutdown=True, request_spec=request_spec)\\n\\n # assert bdm is unchanged\\n disk_info = db.block_device_mapping_get_all_by_instance(\\n self.context, instance.uuid)\\n self.assertEqual(len(disk_info), 1)\\n for bdm in disk_info:\\n self.assertEqual(bdm['device_name'], volume['device_name'])\\n cached_connection_info = jsonutils.loads(bdm['connection_info'])\\n self.assertEqual(cached_connection_info['data'],\\n orig_connection_data)\\n # but connection was terminated\\n self.assertIsNone(connection_info['data'])\\n\\n # stub out virt driver finish_migration\\n def fake(*args, **kwargs):\\n pass\\n self.stub_out('nova.virt.fake.FakeDriver.finish_migration', fake)\\n\\n instance.task_state = task_states.RESIZE_MIGRATED\\n instance.save()\\n\\n # new initialize connection\\n new_connection_data = dict(orig_connection_data)\\n new_iqn = 'iqn.2010-10.org.openstack:%s.2' % uuids.volume_id,\\n new_connection_data['target_iqn'] = new_iqn\\n\\n def fake_init_conn_with_data(self, context, volume, session):\\n connection_info['data'] = new_connection_data\\n return connection_info\\n self.stub_out('nova.volume.cinder.API.initialize_connection',\\n fake_init_conn_with_data)\\n\\n self.compute.finish_resize(self.context,\\n migration=migration,\\n disk_info={}, image={}, instance=instance,\\n request_spec=request_spec)\\n\\n # assert volume attached correctly\\n disk_info = db.block_device_mapping_get_all_by_instance(\\n self.context, instance['uuid'])\\n self.assertEqual(len(disk_info), 1)\\n for bdm in disk_info:\\n self.assertEqual(bdm['connection_info'],\\n jsonutils.dumps(connection_info))\\n\\n # stub out detach\\n def fake_detach(self, context, volume_uuid):\\n volume['device_path'] = None\\n volume['instance_uuid'] = None\\n self.stub_out('nova.volume.cinder.API.detach', fake_detach)\\n\\n # clean up\\n self.compute.terminate_instance(self.context, instance, [])\",\n \"def setupVolumes(volumes: Volumes) -> None:\\n volumesList = readProcessJson(\\n [\\\"podman\\\", \\\"volume\\\", \\\"ls\\\", \\\"--format\\\", \\\"json\\\"])\\n existingVolumes: Set[str] = set()\\n if volumesList:\\n for volume in volumesList:\\n existingVolumes.add(volume['name'])\\n for volume in volumes.values():\\n if volume.name not in existingVolumes:\\n log.info(f\\\"Creating volume {volume.name}\\\")\\n execute([\\\"podman\\\", \\\"volume\\\", \\\"create\\\", volume.name])\\n if volume.files:\\n for file in volume.files:\\n path = Path(\\\"~/.local/share/containers/storage/volumes/\\\"\\n f\\\"{volume.name}/_data/{file.name}\\\").expanduser()\\n if not path.exists():\\n log.info(f\\\"Writting {path}\\\")\\n path.write_text(file.content)\",\n \"def load_snapshot_subhalos(base_path, snap_num, subvolumes, fields=None, matches=False):\\n return load_snapshot(base_path, snap_num, subvolumes, \\\"Galprop\\\", fields, matches)\",\n \"def setup_volumes():\\n\\n fix_path()\\n\\n # Get what we want from the ZK tree\\n logical_volumes = {}\\n expected_sdvols = set()\\n f = open('/etc/zim/volumes')\\n for line in f:\\n line = line.strip()\\n if not line:\\n continue\\n sdvols = line.split()\\n mount_point = sdvols.pop(0)\\n if len(sdvols) == 1:\\n dev = sdvols[0]\\n if dev[0] == '/':\\n ln(mount_point, dev)\\n else:\\n single(mount_point, '/dev/'+dev)\\n continue\\n\\n if len(sdvols) < 1:\\n raise ValueError(line)\\n\\n if lvname(sdvols[0]):\\n lvm(mount_point, sdvols)\\n continue\\n\\n\\n # RAID10:\\n assert len(set(sdvol[:3] for sdvol in sdvols)) == 1, (\\n \\\"Multiple device prefixes\\\")\\n sdprefix = sdvols[0][:3]\\n logical_volumes[sdprefix] = LogicalVolume(\\n sdprefix, sdvols, mount_point)\\n expected_sdvols.update(sdvols)\\n\\n if logical_volumes:\\n\\n # Wait for all of our expected sd volumes to appear. (They may be\\n # attaching.)\\n for v in expected_sdvols:\\n wait_for_device('/dev/' + v)\\n\\n # The volumes may have been set up before on a previous machine.\\n # Scan for them:\\n s('mdadm --examine --scan >>/etc/mdadm.conf')\\n f = open('/etc/mdadm.conf')\\n if f.read().strip():\\n s('mdadm -A --scan')\\n f.close()\\n\\n # Read /proc/mdstat to find out about existing raid volumes:\\n mdstat = re.compile(r'md(\\\\w+) : (\\\\w+) (\\\\w+) (.+)$').match\\n mdstatsd = re.compile(r'(sd(\\\\w+))\\\\[\\\\d+\\\\](\\\\(F\\\\))?$').match\\n for line in open('/proc/mdstat'):\\n if not line.strip():\\n continue\\n m = mdstat(line)\\n if not m:\\n assert (line.startswith('Personalities') or\\n line.startswith(' ') or\\n line.startswith('unused devices')), (\\n \\\"unexpected line\\\", line\\n )\\n continue\\n mdnum, status, rtype, data = m.group(1, 2, 3, 4)\\n data = [mdstatsd(d).groups() for d in data.strip().split()]\\n\\n assert not [d for d in data if d[2]], (\\n \\\"Failed volume\\\", line\\n )\\n\\n data = [d[0] for d in data]\\n if not [d for d in data if d in expected_sdvols]:\\n # Hm, not one weore interested in.\\n print 'skipping', line\\n continue\\n\\n assert not [d for d in data if d not in expected_sdvols], (\\n \\\"Unexpected volume\\\", data\\n )\\n\\n assert status == 'active', status\\n assert rtype == 'raid10', rtype\\n\\n logical_volumes[data[0][:3]].add_md(mdnum, data)\\n\\n # Scan for logical volumes:\\n lv_pat = re.compile('Found volume group \\\"vg_(sd\\\\w+)\\\"').search\\n for line in p('vgscan'):\\n m = lv_pat(line)\\n if not m:\\n continue\\n name = m.group(1)\\n if name in logical_volumes:\\n logical_volumes[name].has_logical_volume()\\n\\n # Record the physical volums in each logical_volume so we can see\\n # if any are missing:\\n PV = re.compile(\\\"PV /dev/md(\\\\w+) +VG vg_(sd\\\\w+) \\\").search\\n for line in p(\\\"pvscan\\\"):\\n m = PV(line)\\n if not m:\\n continue\\n mdnum, vgname = m.groups()\\n logical_volumes[vgname].pvs.add(mdnum)\\n\\n # Finally, create any missing raid volumes and logical volumes\\n for lv in logical_volumes.values():\\n lv.setup()\\n\\n os.rename('/etc/zim/volumes', '/etc/zim/volumes-setup')\",\n \"def test_upload_volume_to_image(self, volume, images_steps, volumes_steps):\\n image_name = next(generate_ids('image', length=20))\\n volumes_steps.upload_volume_to_image(volume.name, image_name)\\n\\n images_steps.page_images().table_images.row(\\n name=image_name).wait_for_presence(30)\\n images_steps.delete_image(image_name)\",\n \"def perform_snapshot(context, region, installed_region='us-east-1'):\\n LOG.info('Reviewing snapshots in region %s', region)\\n\\n # fetch these, in case we need to figure out what applies to an instance\\n configurations = dynamo.list_configurations(context, installed_region)\\n LOG.debug('Fetched all possible configuration rules from DynamoDB')\\n\\n # build a list of any IDs (anywhere) that we should ignore\\n ignore_ids = utils.build_ignore_list(configurations)\\n\\n # setup some lookup tables\\n cache_data = utils.build_cache_maps(context, configurations, region, installed_region)\\n all_instances = cache_data['instance_id_to_data']\\n instance_configs = cache_data['instance_id_to_config']\\n volume_snap_recent = cache_data['volume_id_to_most_recent_snapshot_date']\\n\\n for instance_id in set(all_instances.keys()):\\n # before we go do some work\\n if timeout_check(context, 'perform_snapshot'):\\n break\\n\\n if instance_id in ignore_ids:\\n continue\\n\\n snapshot_settings = instance_configs[instance_id]\\n\\n # parse out snapshot settings\\n retention, frequency = utils.parse_snapshot_settings(snapshot_settings)\\n\\n # grab the data about this instance id, if we don't already have it\\n instance_data = all_instances[instance_id]\\n\\n ami_id = instance_data['ImageId']\\n LOG.info('Reviewing snapshots in region %s on instance %s', region, instance_id)\\n\\n for dev in instance_data.get('BlockDeviceMappings', []):\\n # before we go make a bunch more API calls\\n if timeout_check(context, 'perform_snapshot'):\\n break\\n\\n # we probably should have been using volume keys from one of the\\n # caches here, but since we're not, we're going to have to check here too\\n LOG.debug('Considering device %s', dev)\\n volume_id = dev['Ebs']['VolumeId']\\n\\n if volume_id in ignore_ids:\\n continue\\n\\n # find snapshots\\n recent = volume_snap_recent.get(volume_id)\\n now = datetime.datetime.now(dateutil.tz.tzutc())\\n\\n # snapshot due?\\n if should_perform_snapshot(frequency, now, volume_id, recent):\\n LOG.debug('Performing snapshot for %s, calculating tags', volume_id)\\n else:\\n LOG.debug('NOT Performing snapshot for %s', volume_id)\\n continue\\n\\n # perform actual snapshot and create tag: retention + now() as a Y-M-D\\n delete_on_dt = now + retention\\n delete_on = delete_on_dt.strftime('%Y-%m-%d')\\n\\n volume_data = utils.get_volume(volume_id, region=region)\\n expected_tags = utils.calculate_relevant_tags(\\n instance_data.get('Tags', None),\\n volume_data.get('Tags', None))\\n\\n utils.snapshot_and_tag(\\n instance_id,\\n ami_id,\\n volume_id,\\n delete_on,\\n region,\\n additional_tags=expected_tags)\",\n \"def test_change_volume_status(self, volume, volumes_steps):\\n volumes_steps.change_volume_status(volume.name, 'Error')\\n volumes_steps.change_volume_status(volume.name, 'Available')\",\n \"def test_delete__volume(self):\\n arglist = [\\n '--volume',\\n self.projects[0].id,\\n ]\\n verifylist = [\\n ('service', 'volume'),\\n ('project', self.projects[0].id),\\n ]\\n\\n parsed_args = self.check_parser(self.cmd, arglist, verifylist)\\n\\n result = self.cmd.take_action(parsed_args)\\n\\n self.assertIsNone(result)\\n self.projects_mock.get.assert_called_once_with(self.projects[0].id)\\n self.compute_quotas_mock.delete.assert_not_called()\\n self.volume_quotas_mock.delete.assert_called_once_with(\\n self.projects[0].id,\\n )\\n self.network_mock.delete_quota.assert_not_called()\",\n \"def test_aws_service_api_volume_delete(self):\\n pass\",\n \"def __mount_ebs_volume( self ):\\n ebs_volume_size = self.instance_tag( 'ebs_volume_size' ) or '0'\\n ebs_volume_size = int( ebs_volume_size )\\n if ebs_volume_size:\\n instance_name = self.instance_tag( 'Name' )\\n cluster_ordinal = int( self.instance_tag( 'cluster_ordinal' ) )\\n volume_name = '%s__%d' % (instance_name, cluster_ordinal)\\n volume = EC2VolumeHelper( ec2=self.ec2,\\n availability_zone=self.availability_zone,\\n name=volume_name,\\n size=ebs_volume_size,\\n volume_type=\\\"gp2\\\" )\\n # TODO: handle case where volume is already attached\\n device_ext = '/dev/sdf'\\n device = '/dev/xvdf'\\n volume.attach( self.instance_id, device_ext )\\n\\n # Wait for inode to appear and make sure its a block device\\n while True:\\n try:\\n assert stat.S_ISBLK( os.stat( device ).st_mode )\\n break\\n except OSError as e:\\n if e.errno == errno.ENOENT:\\n time.sleep( 1 )\\n else:\\n raise\\n\\n # Only format empty volumes\\n volume_label = volume_label_hash( volume_name )\\n if check_output( [ 'file', '-sL', device ] ).strip( ) == device + ': data':\\n check_call( [ 'mkfs', '-t', 'ext4', device ] )\\n check_call( [ 'e2label', device, volume_label ] )\\n else:\\n # If the volume is not empty, verify the file system label\\n actual_label = check_output( [ 'e2label', device ] ).strip( )\\n if actual_label != volume_label:\\n raise AssertionError(\\n \\\"Expected volume label '%s' (derived from '%s') but got '%s'\\\" %\\n (volume_label, volume_name, actual_label) )\\n current_mount_point = self.__mount_point( device )\\n if current_mount_point is None:\\n mkdir_p( self.persistent_dir )\\n check_call( [ 'mount', device, self.persistent_dir ] )\\n elif current_mount_point == self.persistent_dir:\\n pass\\n else:\\n raise RuntimeError(\\n \\\"Can't mount device %s on '%s' since it is already mounted on '%s'\\\" % (\\n device, self.persistent_dir, current_mount_point) )\\n else:\\n # No persistent volume is attached and the root volume is off limits, so we will need\\n # to place persistent data on the ephemeral volume.\\n self.persistent_dir = self.ephemeral_dir\",\n \"def get_volume_snapshots(\\n self,\\n references=None, # type: List[models.ReferenceType]\\n sources=None, # type: List[models.ReferenceType]\\n authorization=None, # type: str\\n x_request_id=None, # type: str\\n destroyed=None, # type: bool\\n filter=None, # type: str\\n ids=None, # type: List[str]\\n limit=None, # type: int\\n names=None, # type: List[str]\\n offset=None, # type: int\\n sort=None, # type: List[str]\\n source_ids=None, # type: List[str]\\n source_names=None, # type: List[str]\\n total_item_count=None, # type: bool\\n total_only=None, # type: bool\\n async_req=False, # type: bool\\n _return_http_data_only=False, # type: bool\\n _preload_content=True, # type: bool\\n _request_timeout=None, # type: Optional[int]\\n ):\\n # type: (...) -> models.VolumeSnapshotGetResponse\\n kwargs = dict(\\n authorization=authorization,\\n x_request_id=x_request_id,\\n destroyed=destroyed,\\n filter=filter,\\n ids=ids,\\n limit=limit,\\n names=names,\\n offset=offset,\\n sort=sort,\\n source_ids=source_ids,\\n source_names=source_names,\\n total_item_count=total_item_count,\\n total_only=total_only,\\n async_req=async_req,\\n _return_http_data_only=_return_http_data_only,\\n _preload_content=_preload_content,\\n _request_timeout=_request_timeout,\\n )\\n kwargs = {k: v for k, v in kwargs.items() if v is not None}\\n endpoint = self._volume_snapshots_api.api20_volume_snapshots_get_with_http_info\\n _process_references(references, ['ids', 'names'], kwargs)\\n _process_references(sources, ['source_ids', 'source_names'], kwargs)\\n return self._call_api(endpoint, kwargs)\",\n \"def _create_snapshot(self, name=None, metadata=None):\\n req = fakes.HTTPRequest.blank('/v3/snapshots')\\n req.environ['cinder.context'] = self.ctx\\n snap = {\\\"volume_id\\\": fake.VOLUME_ID,\\n \\\"display_name\\\": name or \\\"Volume Test Name\\\",\\n \\\"description\\\": \\\"Volume Test Desc\\\"\\n }\\n if metadata:\\n snap[\\\"metadata\\\"] = metadata\\n body = {\\\"snapshot\\\": snap}\\n self.controller.create(req, body=body)\",\n \"def ensure_volume_access_right_exists( user_email, volume_name, caps, allowed_gateways=[msconfig.GATEWAY_TYPE_UG] ):\\n client = connect_syndicate()\\n return syndicate_provisioning.ensure_volume_access_right_exists( client, user_email, volume_name, caps, allowed_gateways )\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6860214","0.68374085","0.6810308","0.6785922","0.67043364","0.66553533","0.65876997","0.65367866","0.64045566","0.6373387","0.6342591","0.62254906","0.6165685","0.60885876","0.60594773","0.6057364","0.6054742","0.6044898","0.60077125","0.6006443","0.60047895","0.60014904","0.598205","0.5961584","0.5930594","0.5924005","0.5923422","0.59167534","0.5892","0.58850485","0.58785367","0.5829636","0.5815696","0.5779358","0.5773617","0.57655936","0.57366645","0.57312965","0.57224596","0.5705593","0.57010436","0.56748587","0.56637394","0.5655298","0.56483734","0.5634459","0.56326294","0.5625975","0.5624414","0.5623352","0.5616475","0.56107676","0.56065977","0.55852294","0.5584184","0.55746704","0.55589163","0.5554904","0.55542374","0.5547106","0.55300474","0.5524513","0.5519711","0.5517537","0.5511031","0.55107087","0.5509424","0.5509399","0.55047315","0.5504444","0.5489362","0.54882413","0.54868317","0.5477654","0.54774725","0.5463879","0.5444111","0.5441999","0.5431348","0.5421221","0.54174685","0.5410124","0.5409631","0.53854966","0.5385431","0.5374542","0.53722626","0.5370488","0.5363407","0.5359491","0.5358883","0.53563553","0.53530556","0.5337984","0.5332776","0.5321546","0.5319718","0.53164667","0.53109485","0.53026396"],"string":"[\n \"0.6860214\",\n \"0.68374085\",\n \"0.6810308\",\n \"0.6785922\",\n \"0.67043364\",\n \"0.66553533\",\n \"0.65876997\",\n \"0.65367866\",\n \"0.64045566\",\n \"0.6373387\",\n \"0.6342591\",\n \"0.62254906\",\n \"0.6165685\",\n \"0.60885876\",\n \"0.60594773\",\n \"0.6057364\",\n \"0.6054742\",\n \"0.6044898\",\n \"0.60077125\",\n \"0.6006443\",\n \"0.60047895\",\n \"0.60014904\",\n \"0.598205\",\n \"0.5961584\",\n \"0.5930594\",\n \"0.5924005\",\n \"0.5923422\",\n \"0.59167534\",\n \"0.5892\",\n \"0.58850485\",\n \"0.58785367\",\n \"0.5829636\",\n \"0.5815696\",\n \"0.5779358\",\n \"0.5773617\",\n \"0.57655936\",\n \"0.57366645\",\n \"0.57312965\",\n \"0.57224596\",\n \"0.5705593\",\n \"0.57010436\",\n \"0.56748587\",\n \"0.56637394\",\n \"0.5655298\",\n \"0.56483734\",\n \"0.5634459\",\n \"0.56326294\",\n \"0.5625975\",\n \"0.5624414\",\n \"0.5623352\",\n \"0.5616475\",\n \"0.56107676\",\n \"0.56065977\",\n \"0.55852294\",\n \"0.5584184\",\n \"0.55746704\",\n \"0.55589163\",\n \"0.5554904\",\n \"0.55542374\",\n \"0.5547106\",\n \"0.55300474\",\n \"0.5524513\",\n \"0.5519711\",\n \"0.5517537\",\n \"0.5511031\",\n \"0.55107087\",\n \"0.5509424\",\n \"0.5509399\",\n \"0.55047315\",\n \"0.5504444\",\n \"0.5489362\",\n \"0.54882413\",\n \"0.54868317\",\n \"0.5477654\",\n \"0.54774725\",\n \"0.5463879\",\n \"0.5444111\",\n \"0.5441999\",\n \"0.5431348\",\n \"0.5421221\",\n \"0.54174685\",\n \"0.5410124\",\n \"0.5409631\",\n \"0.53854966\",\n \"0.5385431\",\n \"0.5374542\",\n \"0.53722626\",\n \"0.5370488\",\n \"0.5363407\",\n \"0.5359491\",\n \"0.5358883\",\n \"0.53563553\",\n \"0.53530556\",\n \"0.5337984\",\n \"0.5332776\",\n \"0.5321546\",\n \"0.5319718\",\n \"0.53164667\",\n \"0.53109485\",\n \"0.53026396\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5774927"},"document_rank":{"kind":"string","value":"34"}}},{"rowIdx":81762,"cells":{"query":{"kind":"string","value":"Create a new snapshot"},"document":{"kind":"string","value":"def _create_snapshot(connection, volume, name=''):\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", \"creating new snapshot\", {\"volume\": volume.id}))\n snapshot = volume.create_snapshot(\n description=\"automatic snapshot by ebs-snapshots\")\n if not name:\n name = '{}-snapshot'.format(volume.id)\n connection.create_tags(\n [snapshot.id], dict(Name=name, creator='ebs-snapshots'))\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", \"created snapshot successfully\", {\n \"name\": name,\n \"volume\": volume.id,\n \"snapshot\": snapshot.id\n }))\n return snapshot"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_snapshot(store, dataset, snapshot, description_fields, snapshot_changes):\n validate_snapshot_name(store, dataset, snapshot)\n validate_datalad_config(store, dataset)\n update_description(store, dataset, description_fields)\n update_changes(store, dataset, snapshot, snapshot_changes)\n save_snapshot(store, dataset, snapshot)\n return get_snapshot(store, dataset, snapshot)","def create_snapshot(self, **kwargs):\n post_body = json.dumps({'snapshot': kwargs})\n resp, body = self.post('snapshots', post_body)\n body = json.loads(body)\n self.validate_response(schema.create_snapshot, resp, body)\n return rest_client.ResponseBody(resp, body)","def create_snapshot(self, description=None):\r\n return self.connection.create_snapshot(self.id, description)","def _create_snapshot(self, name=None, metadata=None):\n req = fakes.HTTPRequest.blank('/v3/snapshots')\n req.environ['cinder.context'] = self.ctx\n snap = {\"volume_id\": fake.VOLUME_ID,\n \"display_name\": name or \"Volume Test Name\",\n \"description\": \"Volume Test Desc\"\n }\n if metadata:\n snap[\"metadata\"] = metadata\n body = {\"snapshot\": snap}\n self.controller.create(req, body=body)","def create_snapshot(self, snap_description=None):\n raise NotImplementedError()","def create_snapshot(DirectoryId=None, Name=None):\n pass","def create_snapshot(project, node, snap_name):\n data = {constants.PROJECT_PARAMETER: project,\n constants.NODE_NAME_PARAMETER: node,\n constants.SNAP_NAME_PARAMETER: snap_name}\n res = requests.put(_url + \"create_snapshot/\", data=data,\n auth=(_username, _password))\n click.echo(res.content)","def create(self):\n snap = self.resource.create_snapshot(\n Description=self._get_snapshot_description(),\n VolumeId=VOLUME_ID,\n TagSpecifications=[\n {\n 'ResourceType': 'snapshot',\n 'Tags': [\n {\n 'Key': 'CreatedBy',\n 'Value': 'AutomatedBackup{}'.format(INTERVAL_TYPE.capitalize())\n },\n ]\n },\n ],\n DryRun=DRY_RUN\n )\n self.created_id = snap['SnapshotId']","def create_snapshot(self, snapshot):\n vg_name = self.get_volume_group_name(snapshot.volume_id)\n snap_name = self.get_snap_name(snapshot.id)\n rpolicy = self.get_policy()\n try:\n LOG.debug(\"Searching volume_group: %s in K2.\", vg_name)\n vg = self.client.search(\"volume_groups\", name=vg_name).hits[0]\n LOG.debug(\"Creating a snapshot: %(snap)s from vg: %(vg)s\",\n {'snap': snap_name, 'vg': vg_name})\n self.client.new(\"snapshots\", short_name=snap_name,\n source=vg, retention_policy=rpolicy,\n is_auto_deleteable=False).save()\n except Exception as ex:\n LOG.exception(\"Creation of snapshot: %s failed.\", snap_name)\n raise KaminarioCinderDriverException(reason=ex)","def create_snapshot(self, name):\n self.get_snapshots()\n\n _snapshot = self.get_snapshot(name=name)\n if _snapshot:\n raise ValueError(\"Snapshot already created\")\n\n _url = f\"{self.connector.base_url}/projects/{self.project_id}/snapshots\"\n\n response = self.connector.http_call(\"post\", _url, json_data=dict(name=name))\n\n _snapshot = response.json()\n\n self.snapshots.append(_snapshot)\n print(f\"Created snapshot: {_snapshot['name']}\")","def snapshot(self, snapshot_id):\r\n return self.connection.create_dbsnapshot(snapshot_id, self.id)","def create_snapshot(self, snapshot):\n LOG.info(_LI('Creating snapshot: %s'), snapshot['name'])\n lcfg = self.configuration\n snap_name = self._create_snapshot_name()\n self.zfssa.create_snapshot(lcfg.zfssa_nfs_pool, lcfg.zfssa_nfs_project,\n lcfg.zfssa_nfs_share, snap_name)\n\n src_file = snap_name + '/' + snapshot['volume_name']\n\n try:\n self.zfssa.create_snapshot_of_volume_file(src_file=src_file,\n dst_file=\n snapshot['name'])\n except Exception:\n with excutils.save_and_reraise_exception():\n LOG.debug('Error thrown during snapshot: %s creation',\n snapshot['name'])\n finally:\n self.zfssa.delete_snapshot(lcfg.zfssa_nfs_pool,\n lcfg.zfssa_nfs_project,\n lcfg.zfssa_nfs_share, snap_name)","def test_create_snapshot(self, mock_ghn):\n # Now snapshot the volume and check commands\n snapshot = {'volume_name': 'volume10',\n 'volume_id': 'xxx', 'display_name': 'snap10',\n 'name': '123abc', 'volume_size': 10, 'id': '123abc',\n 'volume': {'provider_id': 'space10'}}\n ret = self.driver.create_snapshot(snapshot)\n # We must copy entier underlying storage, ~12GB, not just 10GB\n self.assertEqual(11444 * units.Mi, self.dd_count)\n self.assertEqual('1M', self.bs)\n # Check space-create command\n expected = {'redundancy': '0', 'group': 'xanadu',\n 'name': snapshot['display_name'], 'mode': '0777',\n 'user': 'kane', 'net': 'net1',\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\n 'size': '12'}\n self.assertDictMatch(expected, self.created)\n # Check the returned provider\n expected_pid = {'provider_id': 'snap10'}\n self.assertDictMatch(expected_pid, ret)","def create_snapshot(self, sName, sDescription = ''):\n\t\treturn Job(SDK.PrlVm_CreateSnapshot(self.handle, sName, sDescription)[0])","def create_snapshot(self, pool, project, share, snapshot):\n svc = self.snapshots_path % (pool, project, share)\n arg = {'name': snapshot}\n ret = self.rclient.post(svc, arg)\n if ret.status != restclient.Status.CREATED:\n exception_msg = (_('Error creating '\n 'snapshot: %(snapshot)s on '\n 'share: %(share)s to '\n 'pool: %(pool)s '\n 'project: %(project)s '\n 'return code: %(ret.status)d '\n 'message: %(ret.data)s.')\n % {'snapshot': snapshot,\n 'share': share,\n 'pool': pool,\n 'project': project,\n 'ret.status': ret.status,\n 'ret.data': ret.data})\n raise exception.ShareBackendException(msg=exception_msg)","def create_snapshot(name: str, subtitle: str, summaryImg: str = \"\", description: str = \"\", layout_params: Dict = {}):\n snapTpl = load_templates(\"snapshot\")\n\n # inject layout settings\n snapTpl[\"layout\"] = merge(snapTpl[\"layout\"], layout_params)\n\n # set name and subtitle\n snapTpl = merge(\n snapTpl,\n {\n \"id\": str(uuid.uuid4()),\n \"snapName\": name,\n \"subtitle\": subtitle,\n \"summaryImg\": summaryImg,\n \"descr\": description,\n },\n )\n\n return snapTpl","def create_snapshot(self, snap_description=None):\n log.debug(\"Initiating creation of a snapshot for volume '%s'\" % self.volume_id)\n try:\n snapshot = self.volume.create_snapshot(description=snap_description)\n log.info(\"Created snapshot {0} from volume {1} ({2}). Check the snapshot \"\n \"for status.\".format(snapshot.id, self.volume_id, self.fs))\n self._derived_snapshots.append(snapshot)\n # Add tags to the newly created snapshot\n self.app.cloud_interface.add_tag(snapshot, 'Name',\n self.app.config['cluster_name'])\n self.app.cloud_interface.add_tag(\n self.volume, 'bucketName', self.app.config['bucket_cluster'])\n self.app.cloud_interface.add_tag(self.volume, 'filesystem', self.fs.name)\n return str(snapshot.id)\n except EC2ResponseError as ex:\n log.error(\"Error creating a snapshot from volume '%s': %s\" %\n (self.volume_id, ex))\n return None","def create_snapshot(volume_name, volume_id):\n\tif cliargs.verbose:\n\t\tprint \"Will snapshot '%s' and tag it with '%s'\" % (volume_id, volume_name)\n\n\tresponse = ec2.create_snapshot(VolumeId=volume_id, Description=volume_name)\n\tif response:\n\t\tec2.create_tags(Resources=[response[\"SnapshotId\"]], Tags=[{\"Key\": \"Name\", \"Value\": volume_name}])","async def new_snapshot(self, data, full=False):\n if ATTR_NAME not in data:\n # provide a default name if none was supplied.\n data[ATTR_NAME] = datetime.now(self._hass.config.time_zone).strftime(\n \"%A, %b %d, %Y\"\n )\n\n _LOGGER.debug(\"Creating snapshot %s\", data[ATTR_NAME])\n\n command = COMMAND_SNAPSHOT_FULL if full else COMMAND_SNAPSHOT_PARTIAL\n keep_days = data.pop(ATTR_KEEP_DAYS, None)\n backup_path = data.pop(ATTR_BACKUP_PATH, None)\n\n if full:\n # performing full backup.\n exclude = data.pop(ATTR_EXCLUDE, None)\n if exclude:\n # handle exclude config.\n command = COMMAND_SNAPSHOT_PARTIAL\n\n # append addons.\n addons = await self.get_addons()\n if addons:\n excluded_addons = await self._replace_addon_names(\n exclude[ATTR_ADDONS], addons\n )\n\n data[ATTR_ADDONS] = [\n addon[\"slug\"]\n for addon in addons\n if addon[\"slug\"] not in excluded_addons\n ]\n\n # append folders.\n excluded_folders = self._replace_folder_names(exclude[ATTR_FOLDERS])\n data[ATTR_FOLDERS] = [\n folder\n for folder in DEFAULT_SNAPSHOT_FOLDERS.values()\n if folder not in excluded_folders\n ]\n\n else:\n # performing partial backup.\n # replace addon names with their appropriate slugs.\n if ATTR_ADDONS in data:\n data[ATTR_ADDONS] = await self._replace_addon_names(data[ATTR_ADDONS])\n # replace friendly folder names.\n if ATTR_FOLDERS in data:\n data[ATTR_FOLDERS] = self._replace_folder_names(data[ATTR_FOLDERS])\n\n _LOGGER.debug(\n \"New snapshot; command: %s, keep_days: %s, data: %s, timeout: %s\",\n command,\n keep_days,\n data,\n self._backup_timeout,\n )\n\n # add to pending snapshots and update sensor.\n self._pending_snapshots += 1\n if self.update_sensor_callback:\n self.update_sensor_callback()\n\n # make request to create new snapshot.\n try:\n result = await self.send_command(\n command, payload=data, timeout=self._backup_timeout\n )\n\n _LOGGER.debug(\"Snapshot create result: %s\" % result)\n\n slug = result.get(\"data\", {}).get(\"slug\")\n if slug is None:\n error = \"There may be a backup already in progress.\"\n if data.get(\"message\"):\n error = f\"{error} {data.get('message')}\"\n raise HassioAPIError(error)\n\n # snapshot creation was successful\n _LOGGER.info(\n \"Snapshot created successfully; '%s' (%s)\", data[ATTR_NAME], slug\n )\n self._hass.bus.async_fire(\n f\"{DOMAIN}.snapshot_successful\", {\"name\": data[ATTR_NAME], \"slug\": slug}\n )\n\n if keep_days is not None:\n # set snapshot expiry\n self._snapshots_expiry[slug] = datetime.now(timezone.utc) + timedelta(\n days=float(keep_days)\n )\n # write snapshot expiry to storage\n await self._snapshots_store.async_save(self._snapshots_expiry)\n\n # copy snapshot to location if specified\n if backup_path:\n await self.copy_snapshot(data[ATTR_NAME], slug, backup_path)\n\n except HassioAPIError as err:\n _LOGGER.error(\"Error during backup. %s\", err)\n self._hass.bus.async_fire(\n f\"{DOMAIN}.snapshot_failed\",\n {\"name\": data[ATTR_NAME], \"error\": str(err)},\n )\n self.last_failure = data[ATTR_NAME]\n\n # remove from pending snapshots and update sensor.\n self._pending_snapshots -= 1\n if self.update_sensor_callback:\n self.update_sensor_callback()\n\n # purging old snapshots\n if self._auto_purge:\n await self.purge_snapshots()","def snapshot(self, snapshot, keep=0):\n if keep:\n until = util.today() + datetime.timedelta(days=keep)\n snapshot = snapshot + \"-keep-until-\" + until.strftime(\"%Y%m%d\")\n if snapshot in [x.snapname for x in self.ceph.root.snapshots]:\n self.log.info(\"snapshot-exists\", snapshot=snapshot)\n return\n self.log.info(\"snapshot-create\", name=snapshot)\n with self.frozen_vm() as frozen:\n if frozen:\n self.ceph.root.snapshots.create(snapshot)\n else:\n self.log.error(\"snapshot-ignore\", reason=\"not frozen\")\n raise RuntimeError(\"VM not frozen, not making snapshot.\")","def create_snapshot( # pylint: disable=inconsistent-return-statements\n self, timeout: Optional[int] = None, metadata: Optional[Dict[str, str]] = None, **kwargs: Any\n ) -> None:\n error_map = {\n 401: ClientAuthenticationError,\n 404: ResourceNotFoundError,\n 409: ResourceExistsError,\n 304: ResourceNotModifiedError,\n }\n error_map.update(kwargs.pop(\"error_map\", {}) or {})\n\n _headers = kwargs.pop(\"headers\", {}) or {}\n _params = case_insensitive_dict(kwargs.pop(\"params\", {}) or {})\n\n restype: Literal[\"share\"] = kwargs.pop(\"restype\", _params.pop(\"restype\", \"share\"))\n comp: Literal[\"snapshot\"] = kwargs.pop(\"comp\", _params.pop(\"comp\", \"snapshot\"))\n cls: ClsType[None] = kwargs.pop(\"cls\", None)\n\n request = build_create_snapshot_request(\n url=self._config.url,\n timeout=timeout,\n metadata=metadata,\n restype=restype,\n comp=comp,\n version=self._config.version,\n template_url=self.create_snapshot.metadata[\"url\"],\n headers=_headers,\n params=_params,\n )\n request = _convert_request(request)\n request.url = self._client.format_url(request.url)\n\n _stream = False\n pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access\n request, stream=_stream, **kwargs\n )\n\n response = pipeline_response.http_response\n\n if response.status_code not in [201]:\n map_error(status_code=response.status_code, response=response, error_map=error_map)\n error = self._deserialize.failsafe_deserialize(_models.StorageError, pipeline_response)\n raise HttpResponseError(response=response, model=error)\n\n response_headers = {}\n response_headers[\"x-ms-snapshot\"] = self._deserialize(\"str\", response.headers.get(\"x-ms-snapshot\"))\n response_headers[\"ETag\"] = self._deserialize(\"str\", response.headers.get(\"ETag\"))\n response_headers[\"Last-Modified\"] = self._deserialize(\"rfc-1123\", response.headers.get(\"Last-Modified\"))\n response_headers[\"x-ms-request-id\"] = self._deserialize(\"str\", response.headers.get(\"x-ms-request-id\"))\n response_headers[\"x-ms-version\"] = self._deserialize(\"str\", response.headers.get(\"x-ms-version\"))\n response_headers[\"Date\"] = self._deserialize(\"rfc-1123\", response.headers.get(\"Date\"))\n\n if cls:\n return cls(pipeline_response, None, response_headers)","def create_snapshot(args, **_):\n\n volume_id = \\\n utils.get_external_resource_id_or_raise(\n 'create snapshot', ctx.instance)\n\n ctx.logger.info(\n 'Trying to create a snapshot of EBS volume {0}.'\n .format(volume_id))\n\n volume_object = _get_volumes_from_id(volume_id)\n\n if not args:\n snapshot_desc = \\\n unicode(datetime.datetime.now()) + \\\n ctx.instance.runtime_properties[constants.EXTERNAL_RESOURCE_ID]\n args = dict(description=snapshot_desc)\n\n try:\n new_snapshot = volume_object.create_snapshot(**args)\n except (boto.exception.EC2ResponseError,\n boto.exception.BotoServerError) as e:\n raise NonRecoverableError('{0}'.format(str(e)))\n\n ctx.logger.info(\n 'Created snapshot of EBS volume {0}.'.format(volume_id))\n\n if constants.VOLUME_SNAPSHOT_ATTRIBUTE not in \\\n ctx.instance.runtime_properties:\n ctx.instance.runtime_properties[\n constants.VOLUME_SNAPSHOT_ATTRIBUTE] = list()\n\n ctx.instance.runtime_properties[\n constants.VOLUME_SNAPSHOT_ATTRIBUTE].append(new_snapshot.id)","def create_snapshot(self, volume_id):\n response = snapshot.create_snapshot(self.url, self.verb,\n self.headers, self.version,\n volume_id)\n \n if response is not None :\n res = CreateSnapshotResponse.CreateSnapshotResponse()\n parseString(str(response.text), res)\n return res\n else :\n return None","def create_snapshot(self, volume_id, description=None):\r\n params = {'VolumeId' : volume_id}\r\n if description:\r\n params['Description'] = description[0:255]\r\n snapshot = self.get_object('CreateSnapshot', params,\r\n Snapshot, verb='POST')\r\n volume = self.get_all_volumes([volume_id])[0]\r\n volume_name = volume.tags.get('Name')\r\n if volume_name:\r\n snapshot.add_tag('Name', volume_name)\r\n return snapshot","def create_snapshot(self, context, volume_id, snapshot_id):\n\n context = context.elevated()\n snapshot_ref = self.db.snapshot_get(context, snapshot_id)\n display_name = snapshot_ref['display_name']\n display_description = snapshot_ref['display_description']\n LOG.info(_(\"snapshot %s: creating\"), snapshot_ref['id'])\n\n self._notify_about_snapshot_usage(\n context, snapshot_ref, \"create.start\")\n\n vol_ref = self.db.volume_get(context, volume_id)\n LOG.info(_(\"Cascade info: create snapshot while cascade id is:%s\"),\n vol_ref['mapping_uuid'])\n\n try:\n vol_ref = self.db.volume_get(context, volume_id)\n casecaded_volume_id = vol_ref['mapping_uuid']\n cinderClient = self._get_cinder_cascaded_user_client(context)\n bodyResponse = cinderClient.volume_snapshots.create(\n volume_id=casecaded_volume_id,\n force=False,\n name=display_name,\n description=display_description)\n\n LOG.info(_(\"Cascade info: create snapshot while response is:%s\"),\n bodyResponse._info)\n if bodyResponse._info['status'] == 'creating':\n self._heal_snapshot_mapping_cache(snapshot_id,\n bodyResponse._info['id'],\n \"add\")\n self.db.snapshot_update(\n context,\n snapshot_ref['id'],\n {'mapping_uuid': bodyResponse._info['id']})\n\n except Exception:\n with excutils.save_and_reraise_exception():\n self.db.snapshot_update(context,\n snapshot_ref['id'],\n {'status': 'error'})\n return\n\n self.db.snapshot_update(context,\n snapshot_ref['id'], {'status': 'available',\n 'progress': '100%'})\n# vol_ref = self.db.volume_get(context, volume_id)\n\n if vol_ref.bootable:\n try:\n self.db.volume_glance_metadata_copy_to_snapshot(\n context, snapshot_ref['id'], volume_id)\n except exception.CinderException as ex:\n LOG.exception(_(\"Failed updating %(snapshot_id)s\"\n \" metadata using the provided volumes\"\n \" %(volume_id)s metadata\") %\n {'volume_id': volume_id,\n 'snapshot_id': snapshot_id})\n raise exception.MetadataCopyFailure(reason=ex)\n\n LOG.info(_(\"Cascade info: snapshot %s, created successfully\"),\n snapshot_ref['id'])\n self._notify_about_snapshot_usage(context, snapshot_ref, \"create.end\")\n\n return snapshot_id","def CreateVMSnapshot(self, **kwargs):\n statusCode = 0 # process exit code\n snapshotName = None\n rewrite = True\n failIfExist = False\n\n try:\n # --- Checking parameters:\n LOGGER.debug('Initialization parameters:')\n\n if 'name' in kwargs.keys():\n snapshotName = kwargs['name']\n LOGGER.debug(' Parameter \"name\" = {}'.format(snapshotName))\n\n else:\n LOGGER.error(' Parameter \"name\" not define!')\n\n if 'rewrite' in kwargs.keys():\n if kwargs['rewrite'].lower() == 'true':\n rewrite = True\n\n else:\n rewrite = False\n\n LOGGER.debug(' Parameter \"rewrite\" = {}'.format(rewrite))\n\n if 'fail-if-exist' in kwargs.keys():\n if kwargs['fail-if-exist'].lower() == 'true':\n failIfExist = True\n\n else:\n failIfExist = False\n\n LOGGER.debug(' Parameter \"fail-if-exist\" = {}'.format(failIfExist))\n\n # --- Creating snapshot from current state:\n if snapshotName:\n snapshots = self.GetVMSnapshotsList()\n snapshotList = [snap.get_name() for snap in snapshots]\n\n if snapshotName in snapshotList:\n LOGGER.warning('Snapshot \"{}\" already exist!'.format(snapshotName))\n\n if rewrite:\n LOGGER.info('Removing exist snapshot because rewrite = True, \"fail-if-exist\" - ignored.')\n self.vmInstance.delete_named_snapshot(snapshotName)\n LOGGER.info('Old snapshot \"{}\" of virtual machine deleted.'.format(snapshotName))\n\n else:\n if failIfExist:\n LOGGER.error('Fail because fail-if-exist = True and rewrite = False.')\n statusCode = 2\n\n else:\n statusCode = None # To do nothing, see next code \"if statusCode is None:\" ...\n\n else:\n LOGGER.error('Fail because snapshot name not define!')\n statusCode = 1\n\n if statusCode == 0:\n LOGGER.info('New snapshot \"{}\" creating in progress...'.format(snapshotName))\n self.vmInstance.create_snapshot(snapshotName)\n LOGGER.info('New snapshot from current state of virtual machine created successful.')\n\n if statusCode is None:\n LOGGER.warning('To do nothing because snapshot already exist and not rewrite and not fail enabled.')\n statusCode = 0\n\n except Exception as e:\n statusCode = -1\n LOGGER.debug(e)\n LOGGER.error(traceback.format_exc())\n LOGGER.error('An error occured while creating snapshots of virtual machine \"{}\"!'.format(VM_NAME))\n\n return statusCode","def create_snapshot(volume_id, size=1, metadata=None, ctxt=None,\n **kwargs):\n metadata = metadata or {}\n snap = objects.Snapshot(ctxt or context.get_admin_context())\n snap.volume_size = size\n snap.user_id = kwargs.get('user_id', fake.USER_ID)\n snap.project_id = kwargs.get('project_id', fake.PROJECT_ID)\n snap.volume_id = volume_id\n snap.status = fields.SnapshotStatus.CREATING\n if metadata is not None:\n snap.metadata = metadata\n snap.update(kwargs)\n\n snap.create()\n return snap","def vm_snapshot_create(self, vm_moid, snapshot):\n result = DataResult()\n try:\n vm_mor = self.get_vm_mor(vm_moid)\n task_mor = vm_mor.CreateSnapshot(snapshot[\"name\"],\n snapshot[\"description\"],\n snapshot[\"memory\"],\n snapshot[\"quiesce\"])\n result.task_key = task_mor._moId\n except Exception as ex:\n LOG.exception(ex)\n result.status = False\n result.message = \"Create snapshot error: %s\" % str(ex)\n return result","def create_snapshot(\n self, volume_id, name=None, description=None,\n force_create=False, requestslib_kwargs=None):\n\n resp = self.client.create_snapshot(\n volume_id, name=name, description=description,\n force_create=force_create)\n\n return resp","def snap_create(mnode, volname, snapname, timestamp=False,\n description='', force=False):\n\n if description != '':\n description = \"description '%s'\" % description\n\n tstamp = ''\n if not timestamp:\n tstamp = \"no-timestamp\"\n\n frce = ''\n if force:\n frce = 'force'\n\n cmd = (\"gluster snapshot create %s %s %s %s %s\"\n % (snapname, volname, tstamp, description, frce))\n return g.run(mnode, cmd)","def create_volume_snapshot(self, volume, name=None, description=None,\n check=True):\n cmd = 'cinder snapshot-create'\n if name:\n cmd += ' --name ' + name\n if description is not None:\n cmd += ' --description ' + moves.shlex_quote(description)\n\n cmd += ' ' + volume.id\n\n exit_code, stdout, stderr = self.execute_command(\n cmd, timeout=config.SNAPSHOT_AVAILABLE_TIMEOUT, check=check)\n\n snapshot_table = output_parser.table(stdout)\n snapshot = {key: value for key, value in snapshot_table['values']}\n\n return snapshot","def create(self, volume_id, force=False, name=None, description=None, \n **kwargs):\n body = {'snapshot': {'volume_id': volume_id,\n 'force': force,\n 'name': name,\n 'description': description}}\n return self._post('/snapshots', body = body, **kwargs)","def snapshot(self):\n pass","def Snapshot(self,\n snapshot_name: Optional[str] = None,\n tags: Optional[Dict[str, str]] = None) -> 'AZComputeSnapshot':\n\n if not snapshot_name:\n snapshot_name = self.name + '_snapshot'\n truncate_at = 80 - 1\n snapshot_name = snapshot_name[:truncate_at]\n if not common.REGEX_SNAPSHOT_NAME.match(snapshot_name):\n raise errors.InvalidNameError(\n 'Snapshot name {0:s} does not comply with {1:s}'.format(\n snapshot_name, common.REGEX_SNAPSHOT_NAME.pattern), __name__)\n\n creation_data = {\n 'location': self.region,\n 'creation_data': {\n 'sourceResourceId': self.resource_id,\n 'create_option': models.DiskCreateOption.copy\n }\n }\n\n if tags:\n creation_data['tags'] = tags\n\n try:\n logger.info('Creating snapshot: {0:s}'.format(snapshot_name))\n request = self.compute_client.snapshots.begin_create_or_update(\n self.resource_group_name,\n snapshot_name,\n creation_data)\n while not request.done():\n sleep(5) # Wait 5 seconds before checking snapshot status again\n snapshot = request.result()\n logger.info('Snapshot {0:s} successfully created'.format(snapshot_name))\n except azure_exceptions.CloudError as exception:\n raise errors.ResourceCreationError(\n 'Could not create snapshot for disk {0:s}: {1!s}'.format(\n self.resource_id, exception), __name__) from exception\n\n return AZComputeSnapshot(self.az_account,\n snapshot.id,\n snapshot.name,\n snapshot.location,\n self)","def create(isamAppliance, comment='', check_mode=False, force=False):\n if force is True or _check(isamAppliance, comment=comment) is False:\n if check_mode is True:\n return isamAppliance.create_return_object(changed=True)\n else:\n return isamAppliance.invoke_post(\"Creating snapshot\", \"/snapshots\",\n {\n 'comment': comment\n })\n\n return isamAppliance.create_return_object()","def create_volume_from_snapshot(self, snapshot, volume, volume_db):\n self.authenticate_user()\n\n if self.configuration.vipr_emulate_snapshot == 'True':\n self.create_cloned_volume(volume, snapshot)\n return\n\n ctxt = context.get_admin_context()\n\n src_snapshot_name = None\n\n #src_snapshot_name = snapshot['display_name']\n src_vol_ref = volume_db.volume_get(ctxt, snapshot['volume_id'])\n new_volume_name = self._get_volume_name(volume)\n number_of_volumes = 1\n\n try:\n src_vol_name, src_vol_uri = self._get_vipr_volume_name(src_vol_ref, True)\n src_snapshot_name = self._get_vipr_snapshot_name(snapshot , src_vol_uri)\n\n (storageresType, storageresTypename) = self.volume_obj.get_storageAttributes(\n src_vol_name\n , None\n , src_snapshot_name)\n\n resource_id = self.volume_obj.storageResource_query(storageresType,\n src_vol_name,\n None,\n src_snapshot_name,\n self.configuration.vipr_project,\n self.configuration.vipr_tenant)\n\n self.volume_obj.clone(\n new_volume_name,\n number_of_volumes,\n resource_id,\n sync=True)\n\n except vipr_utils.SOSError as e:\n if(e.err_code == vipr_utils.SOSError.SOS_FAILURE_ERR):\n raise vipr_utils.SOSError(\n vipr_utils.SOSError.SOS_FAILURE_ERR,\n \"Snapshot \" +\n src_snapshot_name +\n \": clone failed\\n\" +\n e.err_text)\n else:\n with excutils.save_and_reraise_exception():\n LOG.exception(\n _(\"Snapshot : %s clone failed\") % src_snapshot_name)","def test_create_volume_from_snapshot(self, mock_ghn):\n ctxt = context.get_admin_context()\n extra_specs = {}\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\n snap = {'id': '1', 'name': 'volume1', 'display_name': '',\n 'volume_type_id': type_ref['id'], 'size': 10,\n 'provider_id': 'space_orig'}\n volume = {'id': '2', 'name': 'volume2', 'display_name': '',\n 'volume_type_id': type_ref['id'], 'size': 10}\n pid = self.driver.create_volume_from_snapshot(volume, snap)\n # We must copy entier underlying storage, ~12GB, not just 10GB\n self.assertEqual(11444 * units.Mi, self.dd_count)\n self.assertEqual('1M', self.bs)\n # Check space-create command\n expected = {'redundancy': '0', 'group': 'xanadu',\n 'name': 'volume2', 'mode': '0777',\n 'user': 'kane', 'net': 'net1',\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\n 'size': '12'}\n self.assertDictMatch(expected, self.created)\n # Check the returned provider\n expected_pid = {'provider_id': 'volume2'}\n self.assertDictMatch(expected_pid, pid)","def create_snapshot(self, systemId, snapshotSpecificationObject):\n self.conn.connection._check_login()\n #try:\n response = self.conn.connection._do_post(\"{}/{}{}/{}\".format(self.conn.connection._api_url, \"instances/System::\", systemId, 'action/snapshotVolumes'), json=snapshotSpecificationObject.__to_dict__())\n #except:\n # raise RuntimeError(\"create_snapshot_by_system_id() - Error communicating with ScaleIO gateway\")\n return response","def test_snapshot(self):\n # Try to create a snapshot with a wrong machine_uuid.\n status = self.proxy.snapshot.create(\n PROVIDER_ID, \"Doesn't exist\"\n )\n self.check_xmlrpc_command_result(status, has_error=True)\n\n # Try to create a snapshot with a wrong provider.\n status = self.proxy.snapshot.create(\n \"Doesn't exist\", self.machine_uuid\n )\n self.check_xmlrpc_command_result(status, has_error=True)\n\n # Create a snapshot.\n status = self.proxy.snapshot.create(\n PROVIDER_ID, self.machine_uuid\n )\n self.check_xmlrpc_command_result(status)\n\n # Try to destroy snapshots with a wrong provider.\n status = self.proxy.snapshot.destroy(\n \"Doesn't exist\", self.machine_uuid\n )\n self.check_xmlrpc_command_result(status, has_error=True)\n\n # Destroy snapshots.\n status = self.proxy.snapshot.destroy(\n PROVIDER_ID, self.machine_uuid\n )\n self.check_xmlrpc_command_result(status)","def snapshot(self, filename=None):\n if filename:\n self.command(\"snapshot %(filename)s\" % locals())\n else:\n self.command(\"snapshot\")","def snapshot(*args, constructionHistory: bool=True, endTime: Union[time, bool]=None, increment:\n Union[time, bool]=None, motionTrail: bool=False, name: Union[AnyStr, bool]=\"\",\n startTime: Union[time, bool]=None, update: Union[AnyStr, bool]=\"always\", q=True,\n query=True, e=True, edit=True, **kwargs)->Union[List[AnyStr], Any]:\n pass","def take_snapshot(instance_id, objects_created, instance_name=None,\n public=False, wait_for_available=120):\n if not instance_name:\n instance_name = instance_id\n command = 'nova image-create --show %s temp-snap-%s' % (instance_id,\n instance_name)\n snapshot = parse_output(Popen(command.split(), stdout=STDOUT, stderr=STDERR\n ).communicate()[0])\n if wait_for_available > 0:\n wait = 0\n again = False\n while wait < wait_for_available:\n time.sleep(5)\n wait += 5\n again = False\n command = 'glance image-show %s' % snapshot['id']\n status = parse_output(Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n )['status']\n if status == 'error':\n # clean up and create snapshot again\n command = 'glance image-delete %s' % snapshot['id']\n a = Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n command = 'nova image-create --show %s temp-snap-%s' % \\\n (instance_id, instance_name)\n snapshot = parse_output(Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0])\n again = True\n elif status == 'queued' or status == 'saving':\n again = True\n elif status == 'active':\n snapshot['status'] = status\n break\n if again: # loop ended due to timeout\n print 'Error snapshotting instance \\'%s\\'!' % instance_id\n print 'The following entities were created in the process:'\n print_objects_created(objects_created)\n sys.exit(-1)\n if public:\n command = 'glance image-update --visibility public %s' % snapshot['id']\n else:\n command = 'glance image-update --visibility private %s' % \\\n snapshot['id']\n snapshot = parse_output(Popen(\n command.split(), stdout=STDOUT, stderr=STDERR).communicate()[0])\n return snapshot","def create_share_from_snapshot(\r\n self,\r\n context,\r\n share,\r\n snapshot,\r\n share_server=None):\r\n LOG.debug(\"Create share from snapshot.\")\r\n raise NotImplementedError()","def snapshot(self, snapshot):\n self._context[\"snapshot\"] = snapshot","def snapshot(snapshot_type, result_q, time_delta):","def capture_snapshot(db_conn, logger):\n Snapshots.__validate(db_conn=db_conn,\n logger=logger)\n #\n db_conn.execute_proc(name='DBMS_WORKLOAD_REPOSITORY.CREATE_SNAPSHOT',\n parameters={})","def saveSnapshot(self, filename): \n\t\tpass","def take_snapshot():\n df = scrape()\n for i in df.index:\n single = df.loc[i]\n # create or get locations\n loc, created = Location.objects.get_or_create(\n name=single['Location'],\n all_stands=single['Stands'],\n coordinates=single['Coords']\n )\n # add a new snapshot\n obj = Snapshot(\n location=loc,\n avail_bikes=single['Bikes'],\n free_stands=single['Free stands'],\n timestamp=datetime.now(tz=timezone('Europe/Warsaw'))\n )\n obj.save()","def snapshot(self):\n self._client.snapshot()","def create_snapshot_metadata(self, snapshot_id, metadata):\n put_body = json.dumps({'metadata': metadata})\n url = \"snapshots/%s/metadata\" % snapshot_id\n resp, body = self.post(url, put_body)\n body = json.loads(body)\n self.validate_response(schema.create_snapshot_metadata, resp, body)\n return rest_client.ResponseBody(resp, body)","def create_share_from_snapshot(self, context, share, snapshot,\n share_server=None):\n raise NotImplementedError()","def post_create_snapshot(self, response: pubsub.Snapshot) -> pubsub.Snapshot:\n return response","def execute(self): \r\n _logger.info(\"=== Stage=snapshot = %s\" % self._config.name)\r\n _logger.info(\"++ Started at %s\" % time.strftime(\"%H:%M:%S\", time.localtime()))\r\n session = self.get_session()\r\n project = session.create(self._config.name)\r\n\r\n target_dir = os.path.normpath(os.path.join(self._config['dir'], project.name))\r\n _logger.info(\"Looking for snapshot under %s.\" % target_dir)\r\n if not self._check_version(project, target_dir):\r\n if not os.path.exists(target_dir):\r\n _logger.info(\"Creating '%s'.\" % target_dir)\r\n os.makedirs(target_dir)\r\n else:\r\n _logger.info(\"Project needs to be updated, so deleting '%s'.\" % target_dir)\r\n fileutils.rmtree(target_dir)\r\n \r\n try:\r\n _logger.info(\"Snapshotting project.\") \r\n if self.get_threads() == 1: \r\n _logger.info(project.snapshot(target_dir, True))\r\n else:\r\n _logger.info(ccm.extra.FastSnapshot(project, target_dir, self.get_threads()))\r\n \r\n # writing version file \r\n _logger.info(\"Saving project version information.\")\r\n versionfile = open(os.path.join(self._config['dir'], project.name, 'project.version'), \"w+\")\r\n versionfile.write(str(project))\r\n versionfile.close() \r\n except Exception, exc:\r\n if isinstance(exc, ccm.extra.CCMExtraException):\r\n for sexc in exc.subexceptions:\r\n _logger.info(sexc)\r\n _logger.info(\"ERROR: snapshotting %s\" % self._config.name)\r\n _logger.info(exc)\r\n raise exc\r\n else:\r\n _logger.info(\"Project snapshot is still up to date. Nothing to do.\")\r\n\r\n _logger.info(\"++ Finished at %s\" % time.strftime(\"%H:%M:%S\", time.localtime()))","def snapshot(self, name):\r\n return self.driver.create_volume_snapshot(volume=self, name=name)","def snapshot(self, instance, name):\n # TODO(imsplitbit): Need to implement vzdump\n pass","def test_06_create_snapshots_in_project(self):\n # Validate the following\n # 1. Create a project\n # 2. Add some snapshots to the project\n # 3. Verify snapshot created inside project can only be used in inside\n # the project\n\n if not self.snapshotSupported:\n self.skipTest(\"Snapshot is not supported on %s\" % self.hypervisor)\n\n self.debug(\"Deploying VM for Project: %s\" % self.project.id)\n virtual_machine_1 = VirtualMachine.create(\n self.apiclient,\n self.services[\"server\"],\n templateid=self.template.id,\n serviceofferingid=self.service_offering.id,\n projectid=self.project.id\n )\n self.cleanup.append(virtual_machine_1)\n # Verify VM state\n self.assertEqual(\n virtual_machine_1.state,\n 'Running',\n \"Check VM state is Running or not\"\n )\n\n # Get the Root disk of VM\n volumes = list_volumes(\n self.apiclient,\n projectid=self.project.id,\n type='ROOT',\n listall=True\n )\n self.assertEqual(\n isinstance(volumes, list),\n True,\n \"Check for list volume response return valid data\"\n )\n\n self.debug(\"Creating snapshot from volume: %s\" % volumes[0].id)\n # Create a snapshot from the ROOTDISK\n snapshot = Snapshot.create(self.apiclient,\n volumes[0].id,\n projectid=self.project.id\n )\n self.cleanup.append(snapshot)\n # Verify Snapshot state\n self.assertEqual(\n snapshot.state in [\n 'BackedUp',\n 'CreatedOnPrimary',\n 'Allocated'\n ],\n True,\n \"Check Snapshot state is in one of the mentioned possible states, \\\n It is currently: %s\" % snapshot.state\n )\n\n snapshots = Snapshot.list(\n self.apiclient,\n account=self.account.name,\n domainid=self.account.domainid\n )\n self.assertEqual(\n snapshots,\n None,\n \"Snapshots should not be available outside the project\"\n )\n return","def create(self, volume_id, force=False,\n name=None, description=None, metadata=None):\n\n if metadata is None:\n snapshot_metadata = {}\n else:\n snapshot_metadata = metadata\n\n # Bug #1995883: it's possible for the shell to use the user-\n # specified 3.66 do_snapshot_create function, but if the server\n # only supports < 3.66, the client will have been downgraded and\n # will use this function. In that case, the 'force' parameter will\n # be None, which means that the user didn't specify a value for it,\n # so we set it to the pre-3.66 default value of False.\n #\n # NOTE: we know this isn't a problem for current client consumers\n # because a null value for 'force' has never been allowed by the\n # Block Storage API v3, so there's no reason for anyone to directly\n # call this method passing force=None.\n if force is None:\n force = False\n\n body = {'snapshot': {'volume_id': volume_id,\n 'force': force,\n 'name': name,\n 'description': description,\n 'metadata': snapshot_metadata}}\n return self._create('/snapshots', body, 'snapshot')","def create_snapshot(self, volume_id, notes='No longer needed'):\r\n\r\n self.iscsi_svc.createSnapshot(notes, id=volume_id)","def create(self, volume_id, force=None, # noqa: F811\n name=None, description=None, metadata=None):\n\n if metadata is None:\n snapshot_metadata = {}\n else:\n snapshot_metadata = metadata\n\n body = {'snapshot': {'volume_id': volume_id,\n 'name': name,\n 'description': description,\n 'metadata': snapshot_metadata}}\n if force is not None:\n try:\n force = strutils.bool_from_string(force, strict=True)\n if not force:\n raise ValueError()\n except ValueError:\n raise ValueError(MV_3_66_FORCE_FLAG_ERROR)\n return self._create('/snapshots', body, 'snapshot')","def create_volume_from_snapshot(self, volume, snapshot):\n snap_name = self.get_snap_name(snapshot.id)\n view_name = self.get_view_name(volume.id)\n vol_name = self.get_volume_name(volume.id)\n cview = src_attach_info = dest_attach_info = None\n rpolicy = self.get_policy()\n properties = volume_utils.brick_get_connector_properties(\n self.configuration.use_multipath_for_image_xfer,\n self.configuration.enforce_multipath_for_image_xfer)\n LOG.debug(\"Searching for snapshot: %s in K2.\", snap_name)\n snap_rs = self.client.search(\"snapshots\", short_name=snap_name)\n if hasattr(snap_rs, 'hits') and snap_rs.total != 0:\n snap = snap_rs.hits[0]\n LOG.debug(\"Creating a view: %(view)s from snapshot: %(snap)s\",\n {'view': view_name, 'snap': snap_name})\n try:\n cview = self.client.new(\"snapshots\",\n short_name=view_name,\n source=snap, retention_policy=rpolicy,\n is_exposable=True).save()\n except Exception as ex:\n LOG.exception(\"Creating a view: %(view)s from snapshot: \"\n \"%(snap)s failed\", {\"view\": view_name,\n \"snap\": snap_name})\n raise KaminarioCinderDriverException(reason=ex)\n\n else:\n msg = _(\"Snapshot: %s search failed in K2.\") % snap_name\n LOG.error(msg)\n raise KaminarioCinderDriverException(reason=msg)\n\n try:\n conn = self.initialize_connection(cview, properties)\n src_attach_info = self._connect_device(conn)\n self.create_volume(volume)\n conn = self.initialize_connection(volume, properties)\n dest_attach_info = self._connect_device(conn)\n volume_utils.copy_volume(src_attach_info['device']['path'],\n dest_attach_info['device']['path'],\n snapshot.volume.size * units.Ki,\n self.configuration.volume_dd_blocksize,\n sparse=True)\n self._kaminario_disconnect_volume(src_attach_info,\n dest_attach_info)\n self.terminate_connection(volume, properties)\n self.terminate_connection(cview, properties)\n cview.delete()\n except Exception as ex:\n self._kaminario_disconnect_volume(src_attach_info,\n dest_attach_info)\n self.terminate_connection(cview, properties)\n self.terminate_connection(volume, properties)\n cview.delete()\n self.delete_volume(volume)\n LOG.exception(\"Copy to volume: %(vol)s from view: %(view)s \"\n \"failed\", {\"vol\": vol_name, \"view\": view_name})\n raise KaminarioCinderDriverException(reason=ex)","def clone_snapshot(self, pool, project, snapshot, clone, arg):\n self.verify_avail_space(pool, project, clone['id'], clone['size'])\n svc = self.clone_path % (pool, project,\n snapshot['share_id'],\n snapshot['id'])\n ret = self.rclient.put(svc, arg)\n if ret.status != restclient.Status.CREATED:\n exception_msg = (_('Error cloning '\n 'snapshot: %(snapshot)s on '\n 'share: %(share)s of '\n 'Pool: %(pool)s '\n 'project: %(project)s '\n 'return code: %(ret.status)d '\n 'message: %(ret.data)s.')\n % {'snapshot': snapshot['id'],\n 'share': snapshot['share_id'],\n 'pool': pool,\n 'project': project,\n 'ret.status': ret.status,\n 'ret.data': ret.data})\n LOG.error(exception_msg)\n raise exception.ShareBackendException(msg=exception_msg)","def database_volume_snapshot_add(volume_snapshot_obj):\n db = database_get()\n session = db.session()\n query = session.query(model.VolumeSnapshot)\n query = query.filter(model.VolumeSnapshot.uuid == volume_snapshot_obj.uuid)\n volume_snapshot = query.first()\n if not volume_snapshot:\n volume_snapshot = model.VolumeSnapshot()\n volume_snapshot.uuid = volume_snapshot_obj.uuid\n volume_snapshot.name = volume_snapshot_obj.name\n volume_snapshot.description = volume_snapshot_obj.description\n volume_snapshot.size_gb = volume_snapshot_obj.size_gb\n volume_snapshot.volume_uuid = volume_snapshot_obj.volume_uuid\n volume_snapshot.nfvi_volume_snapshot_data = \\\n json.dumps(volume_snapshot_obj.nfvi_volume_snapshot.as_dict())\n session.add(volume_snapshot)\n else:\n volume_snapshot.name = volume_snapshot_obj.name\n volume_snapshot.description = volume_snapshot_obj.description\n volume_snapshot.size_gb = volume_snapshot_obj.size_gb\n volume_snapshot.volume_uuid = volume_snapshot_obj.volume_uuid\n volume_snapshot.nfvi_volume_snapshot_data = \\\n json.dumps(volume_snapshot_obj.nfvi_volume_snapshot.as_dict())\n db.commit()","def snapshot_gen(self):\n \n # Generate snapshot\n snapshot, snapshot_param = make_snapshot.snapshot_gen(self._parent)\n # Save to ICobj\n self._parent.snapshot = snapshot\n self._parent.snapshot_param = snapshot_param","def create_zfs_snapshot(self, name, source_zv_name, zfs_type='default'):\n pname=self.poolname + '/' + source_zv_name + '@' + name\n cmdstr=['zfs','snapshot',pname]\n\n try:\n self._execute(*cmdstr,root_helper=self.r_helper,run_as_root=True) \n except putils.ProcessExecutionError as err:\n LOG.error(_('Cmd :%s') % err.cmd)\n LOG.error(_('StdOut :%s') % err.stdout)\n LOG.error(_('StdErr :%s') % err.stderr)\n raise NameError('Error:failed to create snapshot for zfs volume:%s' % source_zv_name)","def save(self, arguments):\n name = arguments['<name>']\n\n instance_name = arguments['<instance>']\n instance_name = self.activate(instance_name)\n\n vmrun = VMrun(self.vmx, user=self.user, password=self.password)\n if vmrun.snapshot(name) is None:\n puts_err(colored.red(\"Cannot take snapshot\"))\n else:\n puts_err(colored.green(\"Snapshot {} taken\".format(name)))","def test_aws_service_api_snapshots_post(self):\n pass","def createDatabase(store):\n atomicImageFile = store.newFile(*MUGSHOT_BODY_PATH_SEGMENTS)\n imageFilePath = FilePath(__file__).parent().parent().child(\n 'resources').child('square.png')\n atomicImageFile.write(imageFilePath.getContent())\n atomicImageFile.close()\n\n Mugshot(store=store,\n person=Person(store=store),\n body=atomicImageFile.finalpath,\n smallerBody=atomicImageFile.finalpath,\n type=MUGSHOT_TYPE)","def snapshot_image_on_provider(self, builder, provider, credentials, target, template, parameters):","def createNewShot(*args):\n createDir.createShot(pi.shotsFolder)","def create_and_publish_first_snapshot(distribution: str):\n snapshot = f'distribution-{VERSION}'\n run_cmd(['aptly', 'snapshot', 'create',\n snapshot, 'from', 'repo', distribution])\n run_cmd(['aptly', 'publish', 'snapshot', snapshot])","def snap(self, path=None):\n if path is None:\n path = \"/tmp\"\n else:\n path = path.rstrip(\"/\")\n day_dir = datetime.datetime.now().strftime(\"%d%m%Y\")\n hour_dir = datetime.datetime.now().strftime(\"%H%M\")\n ensure_snapshot_dir(path+\"/\"+self.cam_id+\"/\"+day_dir+\"/\"+hour_dir)\n f_path = \"{0}/{1}/{2}/{3}/{4}.jpg\".format(\n path,\n self.cam_id,\n day_dir,\n hour_dir,\n datetime.datetime.now().strftime(\"%S\"),\n )\n\n urllib.urlretrieve(\n 'http://{0}/snapshot.cgi?user={1}&pwd={2}'.format(\n self.address, \n self.user, \n self.pswd,\n ),\n f_path,\n )\n #print resp[1]['Content-disposition'].replace(\"filename=\\\"\",\"\")[:-1]","def snapshot(self):\n return self.journal.create_checkpoint()","def test_create_storage_group_snapshot_by_snap_id(self):\n snapshot_info, sg_name = self.create_sg_snapshot()\n ss_name = self.generate_name(object_type='ss')\n self.replication.create_storage_group_snapshot(\n sg_name, ss_name, ttl=1, hours=True)\n snapshot_info = self.replication.get_storage_group_snapshot_list(\n sg_name)\n snapshot_details = (\n self.replication.get_storage_group_snapshot_snap_id_list(\n sg_name, ss_name))\n self.replication.delete_storage_group_snapshot_by_snap_id(\n sg_name, ss_name, snapshot_details[0])\n self.assertIn(ss_name, snapshot_info)","def create_snapshot(self):\n # Don't create if it already exists\n if self.image_available(self.snapshot_name):\n print('Snapshot already exists')\n return\n\n self.spawn()\n\n sleep_len = 10\n # Make sure the network is up\n t = 0\n networks = None\n while not networks:\n try:\n networks = self.instances[0].networks\n except:\n # not ready yet\n pass\n print('Waited {0}s for network to be up'.format(t))\n if not networks:\n time.sleep(sleep_len)\n t += sleep_len\n self.instances[0] = self.nova.servers.get(self.instances[0].id)\n\n # make sure an ip is received that we can ssh to\n # self.instances[0].add_floating_ip('129.16.125.236')\n t = 0\n ip = None\n while not ip:\n networks = self.instances[0].networks\n for key in networks:\n if 'IPv4' in key:\n ips = networks[key]\n for i in ips:\n # change to not if we want a floating ip\n if i.startswith('192'):\n ip = i\n break\n break\n if not ip:\n time.sleep(sleep_len)\n print('Waited {0}s for ip'.format(t))\n t += sleep_len\n self.instances[0] = self.nova.servers.get(self.instances[0].id)\n\n # make sure cloud init finishes\n t = 0\n while not self._exists_remote(ip):\n print('Waited {0}s for cloud-init to finish'.format(t))\n time.sleep(sleep_len*3)\n t += sleep_len*3\n # create snapshot and make sure it gets active\n self.nova.servers.create_image(self.instances[0].id, self.snapshot_name, None)\n snapshot = self.nova.glance.find_image(self.snapshot_name)\n\n # Wait until snap\n t = 0\n status = snapshot.status\n while status != 'active':\n print('Waited {0}s for snapshot. Status is {1}'.format(t, status))\n snapshot = self.nova.glance.find_image(self.snapshot_name)\n status = snapshot.status\n time.sleep(sleep_len*3)\n t += sleep_len*3\n print('Snapshot successfully uploaded. Now terminating worker.')\n # kill created worker\n self.terminate_all()","def __take_snapshot(self):\n # Set the filename to\n # year_month_date_hour_minute_second.jpg\n time_label = datetime.datetime.now()\n filename = f\"{time_label.strftime('%Y-%m-%d_%H-%M-%S')}.jpg\"\n\n # Start the saving function in background\n save_img_back = threading.Thread(target=self.__upload,\n args=(filename,),\n daemon=True)\n save_img_back.start()","def snapshot(source, destination):\n\n processutils.execute(\n 'qemu-img convert --force-share -O qcow2 %s %s'\n % (source, destination),\n shell=True)","def test_snapshot(self):\n converter = InstructionToQobjConverter(PulseQobjInstruction, meas_level=2)\n instruction = Snapshot(name='label', snap_type='type')\n\n valid_qobj = PulseQobjInstruction(\n name='snapshot',\n t0=0,\n label='label',\n type='type'\n )\n\n self.assertEqual(converter(0, instruction), valid_qobj)","def create_volume_snapshot(volumes, source_instance, objects_created,\n wait_for_available=50):\n if type(volumes) is not list:\n volumes = [volumes]\n s = []\n for volume in volumes:\n command = 'cinder snapshot-create --force True --name %s %s' % \\\n (volume['name'], volume['id'])\n snapshot_info = parse_output(Popen(command.split(), stdout=STDOUT).communicate()[0])\n if volume['bootable'] == 'true':\n snapshot_info['bootable'] = True\n else:\n snapshot_info['bootable'] = False\n att = volume['attachments'].replace(\"'\", \"\\\"\").replace(\n \"u\\\"\", \"\\\"\").replace(\" None,\", \" \\\"None\\\",\")\n snapshot_info['device'] = get(json.loads(att), 'server_id',\n source_instance['id'])[0]['device']\n s.append(snapshot_info)\n if wait_for_available > 0:\n wait = 0\n again = False\n while wait < wait_for_available:\n time.sleep(5)\n wait += 5\n again = False\n for snapshot in s:\n command = 'cinder snapshot-show %s' % snapshot['id']\n status = parse_output(Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n )['status']\n if status == 'error':\n # clean up and take snapshot again\n command = 'cinder snapshot-delete %s' % snapshot['id']\n a = Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n command = 'cinder snapshot-create --force True %s' % \\\n snapshot['volume_id']\n snapshot_info = parse_output(Popen(command.split(),\n stdout=STDOUT, stderr=STDERR\n ).communicate()[0])\n snapshot_info['bootable'] = snapshot['bootable']\n snapshot_info['device'] = snapshot['device']\n snapshot = snapshot_info\n again = True\n break\n elif status == 'creating':\n again = True\n break\n elif status == 'available':\n snapshot['status'] = status\n pass\n if again:\n continue\n else:\n break\n if again: # Loop ended due to timeout\n print 'Error creating volume snapshot!'\n print 'The following entities were created in the process:'\n print_objects_created(objects_created)\n sys.exit(-1)\n return s","def create(self, group_id, name=None, description=None,\n user_id=None,\n project_id=None):\n\n body = {\n 'group_snapshot': {\n 'group_id': group_id,\n 'name': name,\n 'description': description,\n }\n }\n\n return self._create('/group_snapshots', body, 'group_snapshot')","def create_volume(self, snapshot_id = \"\", size = -1):\n response = volume.create_volume(self.url, self.verb,\n self.headers, self.version,\n snapshot_id, size)\n if response is not None :\n res = CreateVolumeResponse.CreateVolumeResponse()\n parseString(str(response.text), res)\n return res\n else :\n return None","def _take_snapshot(self, filename, frame):\n thumbnail_key = os.path.join(self._obj_key_prefix, \"{}.jpg\"\n .format(filename))\n drawn_image = im.draw_region(frame.image,\n self._detector.roi,\n EVENT_ALERT_COLOR_CODE,\n 0.4)\n shrunk_image = im.shrink_image(drawn_image)\n self._obj_store.save_image_obj(thumbnail_key, shrunk_image)\n return thumbnail_key","def snapshot(self, agent_memory):\n\n read_cmd = \"SELECT \"\n for r in self.TABLE_COLUMNS:\n read_cmd += r + \", \"\n read_cmd = read_cmd.strip(\", \")\n read_cmd += \" FROM \" + self.TABLE + \" WHERE uuid=?\"\n data = agent_memory._db_read_one(read_cmd, self.memid)\n if not data:\n raise (\"tried to snapshot nonexistent memory\")\n\n archive_memid = self.new(agent_memory, snapshot=True)\n new_data = list(data)\n new_data[0] = archive_memid\n\n if hasattr(self, \"ARCHIVE_TABLE\"):\n archive_table = self.ARCHIVE_TABLE\n else:\n archive_table = self.TABLE\n write_cmd = \"INSERT INTO \" + archive_table + \"(\"\n qs = \"\"\n for r in self.TABLE_COLUMNS:\n write_cmd += r + \", \"\n qs += \"?, \"\n write_cmd = write_cmd.strip(\", \")\n write_cmd += \") VALUES (\" + qs.strip(\", \") + \")\"\n agent_memory._db_write(write_cmd, *new_data)\n link_archive_to_mem(agent_memory, self.memid, archive_memid)","def test_snapshot(self):\n cmd = Snapshot(name='label', snap_type='type')\n instruction = cmd << 10\n\n qobj = PulseQobjInstruction(name='snapshot', t0=10, label='label', type='type')\n converted_instruction = self.converter(qobj)\n\n self.assertEqual(converted_instruction.timeslots, instruction.timeslots)\n self.assertEqual(converted_instruction.instructions[0][-1], cmd)","def snapshot(self, context, instance, image_id, update_task_state):\n raise NotImplementedError()","def _ensure_snapshot(connection, volume, interval, name):\n if interval not in VALID_INTERVALS:\n logging.warning(kayvee.formatLog(\"ebs-snapshots\", \"warning\", \"invalid snapshotting interval\", {\n \"volume\": volume.id,\n \"interval\": interval\n }))\n return\n\n snapshots = connection.get_all_snapshots(filters={'volume-id': volume.id})\n\n # Create a snapshot if we don't have any\n if not snapshots:\n _create_snapshot(connection, volume, name)\n return\n\n min_delta = 3600 * 24 * 365 * 10 # 10 years :)\n for snapshot in snapshots:\n timestamp = datetime.datetime.strptime(\n snapshot.start_time,\n '%Y-%m-%dT%H:%M:%S.000Z')\n delta_seconds = int(\n (datetime.datetime.utcnow() - timestamp).total_seconds())\n\n if delta_seconds < min_delta:\n min_delta = delta_seconds\n\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", 'The newest snapshot for {} is {} seconds old'.format(volume.id, min_delta)))\n\n if interval == 'hourly' and min_delta > 3600:\n _create_snapshot(connection, volume, name)\n elif interval == 'daily' and min_delta > 3600*24:\n _create_snapshot(connection, volume, name)\n elif interval == 'weekly' and min_delta > 3600*24*7:\n _create_snapshot(connection, volume, name)\n elif interval == 'monthly' and min_delta > 3600*24*30:\n _create_snapshot(connection, volume, name)\n elif interval == 'yearly' and min_delta > 3600*24*365:\n _create_snapshot(connection, volume, name)\n else:\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", \"no snapshot needed\", {\"volume\": volume.id}))","def save_snapshot(args):\n html_doc = document.Document(get_code(args.file))\n info = html_doc.save(args.message, date=args.edition, region=args.region)\n if info is None:\n print('Duplicate snapshot. No snapshot saved.')\n else:\n print('Snapshot saved for {:s} {:%B %d, %Y}. '.format(info[2].capitalize(), info[3]) +\n '{0!r:} - {1:%B} {1.day:2}, {1:%Y %l:%M:%S.%f %p}'.format(info[0], info[1]))","def snapshot(self) -> Snapshot:\n snapshot = self.open(Snapshot.type).signed\n if not isinstance(snapshot, Snapshot):\n raise RuntimeError(\"Unexpected snapshot type\")\n return snapshot","def prepare_snapshot(self, instance, activity, **kwargs):\n return activity._content_object","def take_snapshot(self):\r\n self.snapshot = self.gain, self.block, self.locked, self.bucket_num","def do_takesnapshot(self, str_arg):\n img = None\n fname = validateString(str_arg)\n try:\n # self.adbc.wake()\n printLog(self.threadName + 'taking snapshot (0,50,%d,%d) ...' %\n (self.scn_width, self.scn_height))\n img = self.adbc.takeSnapshot(reconnect=True)\n # PIL code\n img = img.crop((0, 50, self.scn_width, self.scn_height))\n img.save(fname, SNAPSHOT_IMAGE_FORMAT)\n # if self.scn_width>SNAPSHOT_WIDTH:\n # self.compressImage(fname)\n # os.remove(fname)\n # im.save(fname)\n printLog(self.threadName + 'snapshot saved as %s' % fname)\n except EnvironmentError:\n self.resultFlag = False\n if DEBUG:\n traceback.print_exc()\n finally:\n img = None","def serialize_snapshot(self, snapshot, fields=None, version=None):\n fields = fields or self.snapshot_fields\n version = version or self.snapshot_version\n serialized_snapshot = serializers.serialize(\n 'python', [snapshot], fields=fields\n )[0]\n serialized_snapshot['version'] = version\n serialized_snapshot['extra_fields'] = {}\n return serialized_snapshot","def add_snapshot(self, dest, source=None):\n raise NotImplementedYet()","def put_snapshot_object(session, key, data, snapshot=None):\n # type: (Session, Text, Any, Optional[Text]) -> None\n url_tail = \"/{}/{}/{}/{}/{}\".format(\n CoordConstsV2.RSC_NETWORKS,\n session.network,\n CoordConstsV2.RSC_SNAPSHOTS,\n session.get_snapshot(snapshot),\n CoordConstsV2.RSC_OBJECTS,\n )\n _put_stream(session, url_tail, data, {CoordConstsV2.QP_KEY: key})","def link_snapshot(argstr):\n pass","def new_shot(context):\n\n shot = context.scene.milkshake_shots.add()\n camera = bpy.data.cameras.new(\"Camera\")\n camera.display_size = 1\n camera.dof.aperture_blades = 5\n camera.dof.aperture_fstop = 4\n camera.dof.aperture_ratio = 1\n camera.dof.aperture_rotation = math.radians(10)\n camera.dof.focus_distance = 1\n camera.dof.use_dof = True\n camera.lens = 35\n camera.passepartout_alpha = 0.85\n camera.sensor_fit = 'HORIZONTAL'\n camera.sensor_height = 13.365\n camera.sensor_width = 23.76\n camera_object = bpy.data.objects.new(\"Camera\", camera)\n\n cam_collection = camera_collection(context)\n cam_collection.objects.link(camera_object)\n shot.camera = camera\n core.log(\"Created new shot and camera.\")","def _AddSnapshot(self, snapshot):\n if self._history.count(snapshot) == 0:\n self._history.append(snapshot)","def __call__(\n self,\n request: pubsub.CreateSnapshotRequest,\n *,\n retry: OptionalRetry = gapic_v1.method.DEFAULT,\n timeout: Optional[float] = None,\n metadata: Sequence[Tuple[str, str]] = (),\n ) -> pubsub.Snapshot:\n\n http_options: List[Dict[str, str]] = [\n {\n \"method\": \"put\",\n \"uri\": \"/v1/{name=projects/*/snapshots/*}\",\n \"body\": \"*\",\n },\n ]\n request, metadata = self._interceptor.pre_create_snapshot(request, metadata)\n pb_request = pubsub.CreateSnapshotRequest.pb(request)\n transcoded_request = path_template.transcode(http_options, pb_request)\n\n # Jsonify the request body\n\n body = json_format.MessageToJson(\n transcoded_request[\"body\"],\n including_default_value_fields=False,\n use_integers_for_enums=True,\n )\n uri = transcoded_request[\"uri\"]\n method = transcoded_request[\"method\"]\n\n # Jsonify the query params\n query_params = json.loads(\n json_format.MessageToJson(\n transcoded_request[\"query_params\"],\n including_default_value_fields=False,\n use_integers_for_enums=True,\n )\n )\n query_params.update(self._get_unset_required_fields(query_params))\n\n query_params[\"$alt\"] = \"json;enum-encoding=int\"\n\n # Send the request\n headers = dict(metadata)\n headers[\"Content-Type\"] = \"application/json\"\n response = getattr(self._session, method)(\n \"{host}{uri}\".format(host=self._host, uri=uri),\n timeout=timeout,\n headers=headers,\n params=rest_helpers.flatten_query_params(query_params, strict=True),\n data=body,\n )\n\n # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception\n # subclass.\n if response.status_code >= 400:\n raise core_exceptions.from_http_response(response)\n\n # Return the response\n resp = pubsub.Snapshot()\n pb_resp = pubsub.Snapshot.pb(resp)\n\n json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)\n resp = self._interceptor.post_create_snapshot(resp)\n return resp","def manage(self, volume_id, ref, name=None, description=None,\n metadata=None):\n body = {'snapshot': {'volume_id': volume_id,\n 'ref': ref,\n 'name': name,\n 'description': description,\n 'metadata': metadata\n }\n }\n return self._create('/os-snapshot-manage', body, 'snapshot')","def make_release(self, **kwargs) -> ThothRelease:\n snapshot_date = make_snapshot_date(**kwargs)\n release = ThothRelease(dag_id=self.dag_id, run_id=kwargs[\"run_id\"], snapshot_date=snapshot_date)\n return release","def restore(project, zone, instance, snapshot):\n disks = []\n description = 'Created from %s by %s' % (snapshot, getpass.getuser())\n for disk, size in get_disks(instance).items():\n gcloud(\n project,\n 'compute',\n 'disks',\n 'create',\n '--description=%s' % description,\n '--zone=%s' % zone,\n '--size=%dGB' % size,\n '--source-snapshot=%s-%s' % (disk, snapshot),\n disk,\n )\n attrs = [\n 'name=%s' % disk,\n 'device-name=%s' % disk,\n ]\n if disk == instance:\n attrs.append('boot=yes')\n disks.append(attrs)\n gcloud(\n project,\n 'compute',\n 'instances',\n 'create',\n '--description=%s' % description,\n '--zone=%s' % zone,\n '--machine-type=n1-highmem-32', # should reduce to 8\n '--scopes=%s' % ','.join(SCOPES),\n '--tag=do-not-delete,jenkins,jenkins-master',\n '--address=%s' % get_address(project, zone, instance),\n *('--disk=%s' % ','.join(a) for a in disks))"],"string":"[\n \"def create_snapshot(store, dataset, snapshot, description_fields, snapshot_changes):\\n validate_snapshot_name(store, dataset, snapshot)\\n validate_datalad_config(store, dataset)\\n update_description(store, dataset, description_fields)\\n update_changes(store, dataset, snapshot, snapshot_changes)\\n save_snapshot(store, dataset, snapshot)\\n return get_snapshot(store, dataset, snapshot)\",\n \"def create_snapshot(self, **kwargs):\\n post_body = json.dumps({'snapshot': kwargs})\\n resp, body = self.post('snapshots', post_body)\\n body = json.loads(body)\\n self.validate_response(schema.create_snapshot, resp, body)\\n return rest_client.ResponseBody(resp, body)\",\n \"def create_snapshot(self, description=None):\\r\\n return self.connection.create_snapshot(self.id, description)\",\n \"def _create_snapshot(self, name=None, metadata=None):\\n req = fakes.HTTPRequest.blank('/v3/snapshots')\\n req.environ['cinder.context'] = self.ctx\\n snap = {\\\"volume_id\\\": fake.VOLUME_ID,\\n \\\"display_name\\\": name or \\\"Volume Test Name\\\",\\n \\\"description\\\": \\\"Volume Test Desc\\\"\\n }\\n if metadata:\\n snap[\\\"metadata\\\"] = metadata\\n body = {\\\"snapshot\\\": snap}\\n self.controller.create(req, body=body)\",\n \"def create_snapshot(self, snap_description=None):\\n raise NotImplementedError()\",\n \"def create_snapshot(DirectoryId=None, Name=None):\\n pass\",\n \"def create_snapshot(project, node, snap_name):\\n data = {constants.PROJECT_PARAMETER: project,\\n constants.NODE_NAME_PARAMETER: node,\\n constants.SNAP_NAME_PARAMETER: snap_name}\\n res = requests.put(_url + \\\"create_snapshot/\\\", data=data,\\n auth=(_username, _password))\\n click.echo(res.content)\",\n \"def create(self):\\n snap = self.resource.create_snapshot(\\n Description=self._get_snapshot_description(),\\n VolumeId=VOLUME_ID,\\n TagSpecifications=[\\n {\\n 'ResourceType': 'snapshot',\\n 'Tags': [\\n {\\n 'Key': 'CreatedBy',\\n 'Value': 'AutomatedBackup{}'.format(INTERVAL_TYPE.capitalize())\\n },\\n ]\\n },\\n ],\\n DryRun=DRY_RUN\\n )\\n self.created_id = snap['SnapshotId']\",\n \"def create_snapshot(self, snapshot):\\n vg_name = self.get_volume_group_name(snapshot.volume_id)\\n snap_name = self.get_snap_name(snapshot.id)\\n rpolicy = self.get_policy()\\n try:\\n LOG.debug(\\\"Searching volume_group: %s in K2.\\\", vg_name)\\n vg = self.client.search(\\\"volume_groups\\\", name=vg_name).hits[0]\\n LOG.debug(\\\"Creating a snapshot: %(snap)s from vg: %(vg)s\\\",\\n {'snap': snap_name, 'vg': vg_name})\\n self.client.new(\\\"snapshots\\\", short_name=snap_name,\\n source=vg, retention_policy=rpolicy,\\n is_auto_deleteable=False).save()\\n except Exception as ex:\\n LOG.exception(\\\"Creation of snapshot: %s failed.\\\", snap_name)\\n raise KaminarioCinderDriverException(reason=ex)\",\n \"def create_snapshot(self, name):\\n self.get_snapshots()\\n\\n _snapshot = self.get_snapshot(name=name)\\n if _snapshot:\\n raise ValueError(\\\"Snapshot already created\\\")\\n\\n _url = f\\\"{self.connector.base_url}/projects/{self.project_id}/snapshots\\\"\\n\\n response = self.connector.http_call(\\\"post\\\", _url, json_data=dict(name=name))\\n\\n _snapshot = response.json()\\n\\n self.snapshots.append(_snapshot)\\n print(f\\\"Created snapshot: {_snapshot['name']}\\\")\",\n \"def snapshot(self, snapshot_id):\\r\\n return self.connection.create_dbsnapshot(snapshot_id, self.id)\",\n \"def create_snapshot(self, snapshot):\\n LOG.info(_LI('Creating snapshot: %s'), snapshot['name'])\\n lcfg = self.configuration\\n snap_name = self._create_snapshot_name()\\n self.zfssa.create_snapshot(lcfg.zfssa_nfs_pool, lcfg.zfssa_nfs_project,\\n lcfg.zfssa_nfs_share, snap_name)\\n\\n src_file = snap_name + '/' + snapshot['volume_name']\\n\\n try:\\n self.zfssa.create_snapshot_of_volume_file(src_file=src_file,\\n dst_file=\\n snapshot['name'])\\n except Exception:\\n with excutils.save_and_reraise_exception():\\n LOG.debug('Error thrown during snapshot: %s creation',\\n snapshot['name'])\\n finally:\\n self.zfssa.delete_snapshot(lcfg.zfssa_nfs_pool,\\n lcfg.zfssa_nfs_project,\\n lcfg.zfssa_nfs_share, snap_name)\",\n \"def test_create_snapshot(self, mock_ghn):\\n # Now snapshot the volume and check commands\\n snapshot = {'volume_name': 'volume10',\\n 'volume_id': 'xxx', 'display_name': 'snap10',\\n 'name': '123abc', 'volume_size': 10, 'id': '123abc',\\n 'volume': {'provider_id': 'space10'}}\\n ret = self.driver.create_snapshot(snapshot)\\n # We must copy entier underlying storage, ~12GB, not just 10GB\\n self.assertEqual(11444 * units.Mi, self.dd_count)\\n self.assertEqual('1M', self.bs)\\n # Check space-create command\\n expected = {'redundancy': '0', 'group': 'xanadu',\\n 'name': snapshot['display_name'], 'mode': '0777',\\n 'user': 'kane', 'net': 'net1',\\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\\n 'size': '12'}\\n self.assertDictMatch(expected, self.created)\\n # Check the returned provider\\n expected_pid = {'provider_id': 'snap10'}\\n self.assertDictMatch(expected_pid, ret)\",\n \"def create_snapshot(self, sName, sDescription = ''):\\n\\t\\treturn Job(SDK.PrlVm_CreateSnapshot(self.handle, sName, sDescription)[0])\",\n \"def create_snapshot(self, pool, project, share, snapshot):\\n svc = self.snapshots_path % (pool, project, share)\\n arg = {'name': snapshot}\\n ret = self.rclient.post(svc, arg)\\n if ret.status != restclient.Status.CREATED:\\n exception_msg = (_('Error creating '\\n 'snapshot: %(snapshot)s on '\\n 'share: %(share)s to '\\n 'pool: %(pool)s '\\n 'project: %(project)s '\\n 'return code: %(ret.status)d '\\n 'message: %(ret.data)s.')\\n % {'snapshot': snapshot,\\n 'share': share,\\n 'pool': pool,\\n 'project': project,\\n 'ret.status': ret.status,\\n 'ret.data': ret.data})\\n raise exception.ShareBackendException(msg=exception_msg)\",\n \"def create_snapshot(name: str, subtitle: str, summaryImg: str = \\\"\\\", description: str = \\\"\\\", layout_params: Dict = {}):\\n snapTpl = load_templates(\\\"snapshot\\\")\\n\\n # inject layout settings\\n snapTpl[\\\"layout\\\"] = merge(snapTpl[\\\"layout\\\"], layout_params)\\n\\n # set name and subtitle\\n snapTpl = merge(\\n snapTpl,\\n {\\n \\\"id\\\": str(uuid.uuid4()),\\n \\\"snapName\\\": name,\\n \\\"subtitle\\\": subtitle,\\n \\\"summaryImg\\\": summaryImg,\\n \\\"descr\\\": description,\\n },\\n )\\n\\n return snapTpl\",\n \"def create_snapshot(self, snap_description=None):\\n log.debug(\\\"Initiating creation of a snapshot for volume '%s'\\\" % self.volume_id)\\n try:\\n snapshot = self.volume.create_snapshot(description=snap_description)\\n log.info(\\\"Created snapshot {0} from volume {1} ({2}). Check the snapshot \\\"\\n \\\"for status.\\\".format(snapshot.id, self.volume_id, self.fs))\\n self._derived_snapshots.append(snapshot)\\n # Add tags to the newly created snapshot\\n self.app.cloud_interface.add_tag(snapshot, 'Name',\\n self.app.config['cluster_name'])\\n self.app.cloud_interface.add_tag(\\n self.volume, 'bucketName', self.app.config['bucket_cluster'])\\n self.app.cloud_interface.add_tag(self.volume, 'filesystem', self.fs.name)\\n return str(snapshot.id)\\n except EC2ResponseError as ex:\\n log.error(\\\"Error creating a snapshot from volume '%s': %s\\\" %\\n (self.volume_id, ex))\\n return None\",\n \"def create_snapshot(volume_name, volume_id):\\n\\tif cliargs.verbose:\\n\\t\\tprint \\\"Will snapshot '%s' and tag it with '%s'\\\" % (volume_id, volume_name)\\n\\n\\tresponse = ec2.create_snapshot(VolumeId=volume_id, Description=volume_name)\\n\\tif response:\\n\\t\\tec2.create_tags(Resources=[response[\\\"SnapshotId\\\"]], Tags=[{\\\"Key\\\": \\\"Name\\\", \\\"Value\\\": volume_name}])\",\n \"async def new_snapshot(self, data, full=False):\\n if ATTR_NAME not in data:\\n # provide a default name if none was supplied.\\n data[ATTR_NAME] = datetime.now(self._hass.config.time_zone).strftime(\\n \\\"%A, %b %d, %Y\\\"\\n )\\n\\n _LOGGER.debug(\\\"Creating snapshot %s\\\", data[ATTR_NAME])\\n\\n command = COMMAND_SNAPSHOT_FULL if full else COMMAND_SNAPSHOT_PARTIAL\\n keep_days = data.pop(ATTR_KEEP_DAYS, None)\\n backup_path = data.pop(ATTR_BACKUP_PATH, None)\\n\\n if full:\\n # performing full backup.\\n exclude = data.pop(ATTR_EXCLUDE, None)\\n if exclude:\\n # handle exclude config.\\n command = COMMAND_SNAPSHOT_PARTIAL\\n\\n # append addons.\\n addons = await self.get_addons()\\n if addons:\\n excluded_addons = await self._replace_addon_names(\\n exclude[ATTR_ADDONS], addons\\n )\\n\\n data[ATTR_ADDONS] = [\\n addon[\\\"slug\\\"]\\n for addon in addons\\n if addon[\\\"slug\\\"] not in excluded_addons\\n ]\\n\\n # append folders.\\n excluded_folders = self._replace_folder_names(exclude[ATTR_FOLDERS])\\n data[ATTR_FOLDERS] = [\\n folder\\n for folder in DEFAULT_SNAPSHOT_FOLDERS.values()\\n if folder not in excluded_folders\\n ]\\n\\n else:\\n # performing partial backup.\\n # replace addon names with their appropriate slugs.\\n if ATTR_ADDONS in data:\\n data[ATTR_ADDONS] = await self._replace_addon_names(data[ATTR_ADDONS])\\n # replace friendly folder names.\\n if ATTR_FOLDERS in data:\\n data[ATTR_FOLDERS] = self._replace_folder_names(data[ATTR_FOLDERS])\\n\\n _LOGGER.debug(\\n \\\"New snapshot; command: %s, keep_days: %s, data: %s, timeout: %s\\\",\\n command,\\n keep_days,\\n data,\\n self._backup_timeout,\\n )\\n\\n # add to pending snapshots and update sensor.\\n self._pending_snapshots += 1\\n if self.update_sensor_callback:\\n self.update_sensor_callback()\\n\\n # make request to create new snapshot.\\n try:\\n result = await self.send_command(\\n command, payload=data, timeout=self._backup_timeout\\n )\\n\\n _LOGGER.debug(\\\"Snapshot create result: %s\\\" % result)\\n\\n slug = result.get(\\\"data\\\", {}).get(\\\"slug\\\")\\n if slug is None:\\n error = \\\"There may be a backup already in progress.\\\"\\n if data.get(\\\"message\\\"):\\n error = f\\\"{error} {data.get('message')}\\\"\\n raise HassioAPIError(error)\\n\\n # snapshot creation was successful\\n _LOGGER.info(\\n \\\"Snapshot created successfully; '%s' (%s)\\\", data[ATTR_NAME], slug\\n )\\n self._hass.bus.async_fire(\\n f\\\"{DOMAIN}.snapshot_successful\\\", {\\\"name\\\": data[ATTR_NAME], \\\"slug\\\": slug}\\n )\\n\\n if keep_days is not None:\\n # set snapshot expiry\\n self._snapshots_expiry[slug] = datetime.now(timezone.utc) + timedelta(\\n days=float(keep_days)\\n )\\n # write snapshot expiry to storage\\n await self._snapshots_store.async_save(self._snapshots_expiry)\\n\\n # copy snapshot to location if specified\\n if backup_path:\\n await self.copy_snapshot(data[ATTR_NAME], slug, backup_path)\\n\\n except HassioAPIError as err:\\n _LOGGER.error(\\\"Error during backup. %s\\\", err)\\n self._hass.bus.async_fire(\\n f\\\"{DOMAIN}.snapshot_failed\\\",\\n {\\\"name\\\": data[ATTR_NAME], \\\"error\\\": str(err)},\\n )\\n self.last_failure = data[ATTR_NAME]\\n\\n # remove from pending snapshots and update sensor.\\n self._pending_snapshots -= 1\\n if self.update_sensor_callback:\\n self.update_sensor_callback()\\n\\n # purging old snapshots\\n if self._auto_purge:\\n await self.purge_snapshots()\",\n \"def snapshot(self, snapshot, keep=0):\\n if keep:\\n until = util.today() + datetime.timedelta(days=keep)\\n snapshot = snapshot + \\\"-keep-until-\\\" + until.strftime(\\\"%Y%m%d\\\")\\n if snapshot in [x.snapname for x in self.ceph.root.snapshots]:\\n self.log.info(\\\"snapshot-exists\\\", snapshot=snapshot)\\n return\\n self.log.info(\\\"snapshot-create\\\", name=snapshot)\\n with self.frozen_vm() as frozen:\\n if frozen:\\n self.ceph.root.snapshots.create(snapshot)\\n else:\\n self.log.error(\\\"snapshot-ignore\\\", reason=\\\"not frozen\\\")\\n raise RuntimeError(\\\"VM not frozen, not making snapshot.\\\")\",\n \"def create_snapshot( # pylint: disable=inconsistent-return-statements\\n self, timeout: Optional[int] = None, metadata: Optional[Dict[str, str]] = None, **kwargs: Any\\n ) -> None:\\n error_map = {\\n 401: ClientAuthenticationError,\\n 404: ResourceNotFoundError,\\n 409: ResourceExistsError,\\n 304: ResourceNotModifiedError,\\n }\\n error_map.update(kwargs.pop(\\\"error_map\\\", {}) or {})\\n\\n _headers = kwargs.pop(\\\"headers\\\", {}) or {}\\n _params = case_insensitive_dict(kwargs.pop(\\\"params\\\", {}) or {})\\n\\n restype: Literal[\\\"share\\\"] = kwargs.pop(\\\"restype\\\", _params.pop(\\\"restype\\\", \\\"share\\\"))\\n comp: Literal[\\\"snapshot\\\"] = kwargs.pop(\\\"comp\\\", _params.pop(\\\"comp\\\", \\\"snapshot\\\"))\\n cls: ClsType[None] = kwargs.pop(\\\"cls\\\", None)\\n\\n request = build_create_snapshot_request(\\n url=self._config.url,\\n timeout=timeout,\\n metadata=metadata,\\n restype=restype,\\n comp=comp,\\n version=self._config.version,\\n template_url=self.create_snapshot.metadata[\\\"url\\\"],\\n headers=_headers,\\n params=_params,\\n )\\n request = _convert_request(request)\\n request.url = self._client.format_url(request.url)\\n\\n _stream = False\\n pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access\\n request, stream=_stream, **kwargs\\n )\\n\\n response = pipeline_response.http_response\\n\\n if response.status_code not in [201]:\\n map_error(status_code=response.status_code, response=response, error_map=error_map)\\n error = self._deserialize.failsafe_deserialize(_models.StorageError, pipeline_response)\\n raise HttpResponseError(response=response, model=error)\\n\\n response_headers = {}\\n response_headers[\\\"x-ms-snapshot\\\"] = self._deserialize(\\\"str\\\", response.headers.get(\\\"x-ms-snapshot\\\"))\\n response_headers[\\\"ETag\\\"] = self._deserialize(\\\"str\\\", response.headers.get(\\\"ETag\\\"))\\n response_headers[\\\"Last-Modified\\\"] = self._deserialize(\\\"rfc-1123\\\", response.headers.get(\\\"Last-Modified\\\"))\\n response_headers[\\\"x-ms-request-id\\\"] = self._deserialize(\\\"str\\\", response.headers.get(\\\"x-ms-request-id\\\"))\\n response_headers[\\\"x-ms-version\\\"] = self._deserialize(\\\"str\\\", response.headers.get(\\\"x-ms-version\\\"))\\n response_headers[\\\"Date\\\"] = self._deserialize(\\\"rfc-1123\\\", response.headers.get(\\\"Date\\\"))\\n\\n if cls:\\n return cls(pipeline_response, None, response_headers)\",\n \"def create_snapshot(args, **_):\\n\\n volume_id = \\\\\\n utils.get_external_resource_id_or_raise(\\n 'create snapshot', ctx.instance)\\n\\n ctx.logger.info(\\n 'Trying to create a snapshot of EBS volume {0}.'\\n .format(volume_id))\\n\\n volume_object = _get_volumes_from_id(volume_id)\\n\\n if not args:\\n snapshot_desc = \\\\\\n unicode(datetime.datetime.now()) + \\\\\\n ctx.instance.runtime_properties[constants.EXTERNAL_RESOURCE_ID]\\n args = dict(description=snapshot_desc)\\n\\n try:\\n new_snapshot = volume_object.create_snapshot(**args)\\n except (boto.exception.EC2ResponseError,\\n boto.exception.BotoServerError) as e:\\n raise NonRecoverableError('{0}'.format(str(e)))\\n\\n ctx.logger.info(\\n 'Created snapshot of EBS volume {0}.'.format(volume_id))\\n\\n if constants.VOLUME_SNAPSHOT_ATTRIBUTE not in \\\\\\n ctx.instance.runtime_properties:\\n ctx.instance.runtime_properties[\\n constants.VOLUME_SNAPSHOT_ATTRIBUTE] = list()\\n\\n ctx.instance.runtime_properties[\\n constants.VOLUME_SNAPSHOT_ATTRIBUTE].append(new_snapshot.id)\",\n \"def create_snapshot(self, volume_id):\\n response = snapshot.create_snapshot(self.url, self.verb,\\n self.headers, self.version,\\n volume_id)\\n \\n if response is not None :\\n res = CreateSnapshotResponse.CreateSnapshotResponse()\\n parseString(str(response.text), res)\\n return res\\n else :\\n return None\",\n \"def create_snapshot(self, volume_id, description=None):\\r\\n params = {'VolumeId' : volume_id}\\r\\n if description:\\r\\n params['Description'] = description[0:255]\\r\\n snapshot = self.get_object('CreateSnapshot', params,\\r\\n Snapshot, verb='POST')\\r\\n volume = self.get_all_volumes([volume_id])[0]\\r\\n volume_name = volume.tags.get('Name')\\r\\n if volume_name:\\r\\n snapshot.add_tag('Name', volume_name)\\r\\n return snapshot\",\n \"def create_snapshot(self, context, volume_id, snapshot_id):\\n\\n context = context.elevated()\\n snapshot_ref = self.db.snapshot_get(context, snapshot_id)\\n display_name = snapshot_ref['display_name']\\n display_description = snapshot_ref['display_description']\\n LOG.info(_(\\\"snapshot %s: creating\\\"), snapshot_ref['id'])\\n\\n self._notify_about_snapshot_usage(\\n context, snapshot_ref, \\\"create.start\\\")\\n\\n vol_ref = self.db.volume_get(context, volume_id)\\n LOG.info(_(\\\"Cascade info: create snapshot while cascade id is:%s\\\"),\\n vol_ref['mapping_uuid'])\\n\\n try:\\n vol_ref = self.db.volume_get(context, volume_id)\\n casecaded_volume_id = vol_ref['mapping_uuid']\\n cinderClient = self._get_cinder_cascaded_user_client(context)\\n bodyResponse = cinderClient.volume_snapshots.create(\\n volume_id=casecaded_volume_id,\\n force=False,\\n name=display_name,\\n description=display_description)\\n\\n LOG.info(_(\\\"Cascade info: create snapshot while response is:%s\\\"),\\n bodyResponse._info)\\n if bodyResponse._info['status'] == 'creating':\\n self._heal_snapshot_mapping_cache(snapshot_id,\\n bodyResponse._info['id'],\\n \\\"add\\\")\\n self.db.snapshot_update(\\n context,\\n snapshot_ref['id'],\\n {'mapping_uuid': bodyResponse._info['id']})\\n\\n except Exception:\\n with excutils.save_and_reraise_exception():\\n self.db.snapshot_update(context,\\n snapshot_ref['id'],\\n {'status': 'error'})\\n return\\n\\n self.db.snapshot_update(context,\\n snapshot_ref['id'], {'status': 'available',\\n 'progress': '100%'})\\n# vol_ref = self.db.volume_get(context, volume_id)\\n\\n if vol_ref.bootable:\\n try:\\n self.db.volume_glance_metadata_copy_to_snapshot(\\n context, snapshot_ref['id'], volume_id)\\n except exception.CinderException as ex:\\n LOG.exception(_(\\\"Failed updating %(snapshot_id)s\\\"\\n \\\" metadata using the provided volumes\\\"\\n \\\" %(volume_id)s metadata\\\") %\\n {'volume_id': volume_id,\\n 'snapshot_id': snapshot_id})\\n raise exception.MetadataCopyFailure(reason=ex)\\n\\n LOG.info(_(\\\"Cascade info: snapshot %s, created successfully\\\"),\\n snapshot_ref['id'])\\n self._notify_about_snapshot_usage(context, snapshot_ref, \\\"create.end\\\")\\n\\n return snapshot_id\",\n \"def CreateVMSnapshot(self, **kwargs):\\n statusCode = 0 # process exit code\\n snapshotName = None\\n rewrite = True\\n failIfExist = False\\n\\n try:\\n # --- Checking parameters:\\n LOGGER.debug('Initialization parameters:')\\n\\n if 'name' in kwargs.keys():\\n snapshotName = kwargs['name']\\n LOGGER.debug(' Parameter \\\"name\\\" = {}'.format(snapshotName))\\n\\n else:\\n LOGGER.error(' Parameter \\\"name\\\" not define!')\\n\\n if 'rewrite' in kwargs.keys():\\n if kwargs['rewrite'].lower() == 'true':\\n rewrite = True\\n\\n else:\\n rewrite = False\\n\\n LOGGER.debug(' Parameter \\\"rewrite\\\" = {}'.format(rewrite))\\n\\n if 'fail-if-exist' in kwargs.keys():\\n if kwargs['fail-if-exist'].lower() == 'true':\\n failIfExist = True\\n\\n else:\\n failIfExist = False\\n\\n LOGGER.debug(' Parameter \\\"fail-if-exist\\\" = {}'.format(failIfExist))\\n\\n # --- Creating snapshot from current state:\\n if snapshotName:\\n snapshots = self.GetVMSnapshotsList()\\n snapshotList = [snap.get_name() for snap in snapshots]\\n\\n if snapshotName in snapshotList:\\n LOGGER.warning('Snapshot \\\"{}\\\" already exist!'.format(snapshotName))\\n\\n if rewrite:\\n LOGGER.info('Removing exist snapshot because rewrite = True, \\\"fail-if-exist\\\" - ignored.')\\n self.vmInstance.delete_named_snapshot(snapshotName)\\n LOGGER.info('Old snapshot \\\"{}\\\" of virtual machine deleted.'.format(snapshotName))\\n\\n else:\\n if failIfExist:\\n LOGGER.error('Fail because fail-if-exist = True and rewrite = False.')\\n statusCode = 2\\n\\n else:\\n statusCode = None # To do nothing, see next code \\\"if statusCode is None:\\\" ...\\n\\n else:\\n LOGGER.error('Fail because snapshot name not define!')\\n statusCode = 1\\n\\n if statusCode == 0:\\n LOGGER.info('New snapshot \\\"{}\\\" creating in progress...'.format(snapshotName))\\n self.vmInstance.create_snapshot(snapshotName)\\n LOGGER.info('New snapshot from current state of virtual machine created successful.')\\n\\n if statusCode is None:\\n LOGGER.warning('To do nothing because snapshot already exist and not rewrite and not fail enabled.')\\n statusCode = 0\\n\\n except Exception as e:\\n statusCode = -1\\n LOGGER.debug(e)\\n LOGGER.error(traceback.format_exc())\\n LOGGER.error('An error occured while creating snapshots of virtual machine \\\"{}\\\"!'.format(VM_NAME))\\n\\n return statusCode\",\n \"def create_snapshot(volume_id, size=1, metadata=None, ctxt=None,\\n **kwargs):\\n metadata = metadata or {}\\n snap = objects.Snapshot(ctxt or context.get_admin_context())\\n snap.volume_size = size\\n snap.user_id = kwargs.get('user_id', fake.USER_ID)\\n snap.project_id = kwargs.get('project_id', fake.PROJECT_ID)\\n snap.volume_id = volume_id\\n snap.status = fields.SnapshotStatus.CREATING\\n if metadata is not None:\\n snap.metadata = metadata\\n snap.update(kwargs)\\n\\n snap.create()\\n return snap\",\n \"def vm_snapshot_create(self, vm_moid, snapshot):\\n result = DataResult()\\n try:\\n vm_mor = self.get_vm_mor(vm_moid)\\n task_mor = vm_mor.CreateSnapshot(snapshot[\\\"name\\\"],\\n snapshot[\\\"description\\\"],\\n snapshot[\\\"memory\\\"],\\n snapshot[\\\"quiesce\\\"])\\n result.task_key = task_mor._moId\\n except Exception as ex:\\n LOG.exception(ex)\\n result.status = False\\n result.message = \\\"Create snapshot error: %s\\\" % str(ex)\\n return result\",\n \"def create_snapshot(\\n self, volume_id, name=None, description=None,\\n force_create=False, requestslib_kwargs=None):\\n\\n resp = self.client.create_snapshot(\\n volume_id, name=name, description=description,\\n force_create=force_create)\\n\\n return resp\",\n \"def snap_create(mnode, volname, snapname, timestamp=False,\\n description='', force=False):\\n\\n if description != '':\\n description = \\\"description '%s'\\\" % description\\n\\n tstamp = ''\\n if not timestamp:\\n tstamp = \\\"no-timestamp\\\"\\n\\n frce = ''\\n if force:\\n frce = 'force'\\n\\n cmd = (\\\"gluster snapshot create %s %s %s %s %s\\\"\\n % (snapname, volname, tstamp, description, frce))\\n return g.run(mnode, cmd)\",\n \"def create_volume_snapshot(self, volume, name=None, description=None,\\n check=True):\\n cmd = 'cinder snapshot-create'\\n if name:\\n cmd += ' --name ' + name\\n if description is not None:\\n cmd += ' --description ' + moves.shlex_quote(description)\\n\\n cmd += ' ' + volume.id\\n\\n exit_code, stdout, stderr = self.execute_command(\\n cmd, timeout=config.SNAPSHOT_AVAILABLE_TIMEOUT, check=check)\\n\\n snapshot_table = output_parser.table(stdout)\\n snapshot = {key: value for key, value in snapshot_table['values']}\\n\\n return snapshot\",\n \"def create(self, volume_id, force=False, name=None, description=None, \\n **kwargs):\\n body = {'snapshot': {'volume_id': volume_id,\\n 'force': force,\\n 'name': name,\\n 'description': description}}\\n return self._post('/snapshots', body = body, **kwargs)\",\n \"def snapshot(self):\\n pass\",\n \"def Snapshot(self,\\n snapshot_name: Optional[str] = None,\\n tags: Optional[Dict[str, str]] = None) -> 'AZComputeSnapshot':\\n\\n if not snapshot_name:\\n snapshot_name = self.name + '_snapshot'\\n truncate_at = 80 - 1\\n snapshot_name = snapshot_name[:truncate_at]\\n if not common.REGEX_SNAPSHOT_NAME.match(snapshot_name):\\n raise errors.InvalidNameError(\\n 'Snapshot name {0:s} does not comply with {1:s}'.format(\\n snapshot_name, common.REGEX_SNAPSHOT_NAME.pattern), __name__)\\n\\n creation_data = {\\n 'location': self.region,\\n 'creation_data': {\\n 'sourceResourceId': self.resource_id,\\n 'create_option': models.DiskCreateOption.copy\\n }\\n }\\n\\n if tags:\\n creation_data['tags'] = tags\\n\\n try:\\n logger.info('Creating snapshot: {0:s}'.format(snapshot_name))\\n request = self.compute_client.snapshots.begin_create_or_update(\\n self.resource_group_name,\\n snapshot_name,\\n creation_data)\\n while not request.done():\\n sleep(5) # Wait 5 seconds before checking snapshot status again\\n snapshot = request.result()\\n logger.info('Snapshot {0:s} successfully created'.format(snapshot_name))\\n except azure_exceptions.CloudError as exception:\\n raise errors.ResourceCreationError(\\n 'Could not create snapshot for disk {0:s}: {1!s}'.format(\\n self.resource_id, exception), __name__) from exception\\n\\n return AZComputeSnapshot(self.az_account,\\n snapshot.id,\\n snapshot.name,\\n snapshot.location,\\n self)\",\n \"def create(isamAppliance, comment='', check_mode=False, force=False):\\n if force is True or _check(isamAppliance, comment=comment) is False:\\n if check_mode is True:\\n return isamAppliance.create_return_object(changed=True)\\n else:\\n return isamAppliance.invoke_post(\\\"Creating snapshot\\\", \\\"/snapshots\\\",\\n {\\n 'comment': comment\\n })\\n\\n return isamAppliance.create_return_object()\",\n \"def create_volume_from_snapshot(self, snapshot, volume, volume_db):\\n self.authenticate_user()\\n\\n if self.configuration.vipr_emulate_snapshot == 'True':\\n self.create_cloned_volume(volume, snapshot)\\n return\\n\\n ctxt = context.get_admin_context()\\n\\n src_snapshot_name = None\\n\\n #src_snapshot_name = snapshot['display_name']\\n src_vol_ref = volume_db.volume_get(ctxt, snapshot['volume_id'])\\n new_volume_name = self._get_volume_name(volume)\\n number_of_volumes = 1\\n\\n try:\\n src_vol_name, src_vol_uri = self._get_vipr_volume_name(src_vol_ref, True)\\n src_snapshot_name = self._get_vipr_snapshot_name(snapshot , src_vol_uri)\\n\\n (storageresType, storageresTypename) = self.volume_obj.get_storageAttributes(\\n src_vol_name\\n , None\\n , src_snapshot_name)\\n\\n resource_id = self.volume_obj.storageResource_query(storageresType,\\n src_vol_name,\\n None,\\n src_snapshot_name,\\n self.configuration.vipr_project,\\n self.configuration.vipr_tenant)\\n\\n self.volume_obj.clone(\\n new_volume_name,\\n number_of_volumes,\\n resource_id,\\n sync=True)\\n\\n except vipr_utils.SOSError as e:\\n if(e.err_code == vipr_utils.SOSError.SOS_FAILURE_ERR):\\n raise vipr_utils.SOSError(\\n vipr_utils.SOSError.SOS_FAILURE_ERR,\\n \\\"Snapshot \\\" +\\n src_snapshot_name +\\n \\\": clone failed\\\\n\\\" +\\n e.err_text)\\n else:\\n with excutils.save_and_reraise_exception():\\n LOG.exception(\\n _(\\\"Snapshot : %s clone failed\\\") % src_snapshot_name)\",\n \"def test_create_volume_from_snapshot(self, mock_ghn):\\n ctxt = context.get_admin_context()\\n extra_specs = {}\\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\\n snap = {'id': '1', 'name': 'volume1', 'display_name': '',\\n 'volume_type_id': type_ref['id'], 'size': 10,\\n 'provider_id': 'space_orig'}\\n volume = {'id': '2', 'name': 'volume2', 'display_name': '',\\n 'volume_type_id': type_ref['id'], 'size': 10}\\n pid = self.driver.create_volume_from_snapshot(volume, snap)\\n # We must copy entier underlying storage, ~12GB, not just 10GB\\n self.assertEqual(11444 * units.Mi, self.dd_count)\\n self.assertEqual('1M', self.bs)\\n # Check space-create command\\n expected = {'redundancy': '0', 'group': 'xanadu',\\n 'name': 'volume2', 'mode': '0777',\\n 'user': 'kane', 'net': 'net1',\\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\\n 'size': '12'}\\n self.assertDictMatch(expected, self.created)\\n # Check the returned provider\\n expected_pid = {'provider_id': 'volume2'}\\n self.assertDictMatch(expected_pid, pid)\",\n \"def create_snapshot(self, systemId, snapshotSpecificationObject):\\n self.conn.connection._check_login()\\n #try:\\n response = self.conn.connection._do_post(\\\"{}/{}{}/{}\\\".format(self.conn.connection._api_url, \\\"instances/System::\\\", systemId, 'action/snapshotVolumes'), json=snapshotSpecificationObject.__to_dict__())\\n #except:\\n # raise RuntimeError(\\\"create_snapshot_by_system_id() - Error communicating with ScaleIO gateway\\\")\\n return response\",\n \"def test_snapshot(self):\\n # Try to create a snapshot with a wrong machine_uuid.\\n status = self.proxy.snapshot.create(\\n PROVIDER_ID, \\\"Doesn't exist\\\"\\n )\\n self.check_xmlrpc_command_result(status, has_error=True)\\n\\n # Try to create a snapshot with a wrong provider.\\n status = self.proxy.snapshot.create(\\n \\\"Doesn't exist\\\", self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status, has_error=True)\\n\\n # Create a snapshot.\\n status = self.proxy.snapshot.create(\\n PROVIDER_ID, self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status)\\n\\n # Try to destroy snapshots with a wrong provider.\\n status = self.proxy.snapshot.destroy(\\n \\\"Doesn't exist\\\", self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status, has_error=True)\\n\\n # Destroy snapshots.\\n status = self.proxy.snapshot.destroy(\\n PROVIDER_ID, self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status)\",\n \"def snapshot(self, filename=None):\\n if filename:\\n self.command(\\\"snapshot %(filename)s\\\" % locals())\\n else:\\n self.command(\\\"snapshot\\\")\",\n \"def snapshot(*args, constructionHistory: bool=True, endTime: Union[time, bool]=None, increment:\\n Union[time, bool]=None, motionTrail: bool=False, name: Union[AnyStr, bool]=\\\"\\\",\\n startTime: Union[time, bool]=None, update: Union[AnyStr, bool]=\\\"always\\\", q=True,\\n query=True, e=True, edit=True, **kwargs)->Union[List[AnyStr], Any]:\\n pass\",\n \"def take_snapshot(instance_id, objects_created, instance_name=None,\\n public=False, wait_for_available=120):\\n if not instance_name:\\n instance_name = instance_id\\n command = 'nova image-create --show %s temp-snap-%s' % (instance_id,\\n instance_name)\\n snapshot = parse_output(Popen(command.split(), stdout=STDOUT, stderr=STDERR\\n ).communicate()[0])\\n if wait_for_available > 0:\\n wait = 0\\n again = False\\n while wait < wait_for_available:\\n time.sleep(5)\\n wait += 5\\n again = False\\n command = 'glance image-show %s' % snapshot['id']\\n status = parse_output(Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n )['status']\\n if status == 'error':\\n # clean up and create snapshot again\\n command = 'glance image-delete %s' % snapshot['id']\\n a = Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n command = 'nova image-create --show %s temp-snap-%s' % \\\\\\n (instance_id, instance_name)\\n snapshot = parse_output(Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0])\\n again = True\\n elif status == 'queued' or status == 'saving':\\n again = True\\n elif status == 'active':\\n snapshot['status'] = status\\n break\\n if again: # loop ended due to timeout\\n print 'Error snapshotting instance \\\\'%s\\\\'!' % instance_id\\n print 'The following entities were created in the process:'\\n print_objects_created(objects_created)\\n sys.exit(-1)\\n if public:\\n command = 'glance image-update --visibility public %s' % snapshot['id']\\n else:\\n command = 'glance image-update --visibility private %s' % \\\\\\n snapshot['id']\\n snapshot = parse_output(Popen(\\n command.split(), stdout=STDOUT, stderr=STDERR).communicate()[0])\\n return snapshot\",\n \"def create_share_from_snapshot(\\r\\n self,\\r\\n context,\\r\\n share,\\r\\n snapshot,\\r\\n share_server=None):\\r\\n LOG.debug(\\\"Create share from snapshot.\\\")\\r\\n raise NotImplementedError()\",\n \"def snapshot(self, snapshot):\\n self._context[\\\"snapshot\\\"] = snapshot\",\n \"def snapshot(snapshot_type, result_q, time_delta):\",\n \"def capture_snapshot(db_conn, logger):\\n Snapshots.__validate(db_conn=db_conn,\\n logger=logger)\\n #\\n db_conn.execute_proc(name='DBMS_WORKLOAD_REPOSITORY.CREATE_SNAPSHOT',\\n parameters={})\",\n \"def saveSnapshot(self, filename): \\n\\t\\tpass\",\n \"def take_snapshot():\\n df = scrape()\\n for i in df.index:\\n single = df.loc[i]\\n # create or get locations\\n loc, created = Location.objects.get_or_create(\\n name=single['Location'],\\n all_stands=single['Stands'],\\n coordinates=single['Coords']\\n )\\n # add a new snapshot\\n obj = Snapshot(\\n location=loc,\\n avail_bikes=single['Bikes'],\\n free_stands=single['Free stands'],\\n timestamp=datetime.now(tz=timezone('Europe/Warsaw'))\\n )\\n obj.save()\",\n \"def snapshot(self):\\n self._client.snapshot()\",\n \"def create_snapshot_metadata(self, snapshot_id, metadata):\\n put_body = json.dumps({'metadata': metadata})\\n url = \\\"snapshots/%s/metadata\\\" % snapshot_id\\n resp, body = self.post(url, put_body)\\n body = json.loads(body)\\n self.validate_response(schema.create_snapshot_metadata, resp, body)\\n return rest_client.ResponseBody(resp, body)\",\n \"def create_share_from_snapshot(self, context, share, snapshot,\\n share_server=None):\\n raise NotImplementedError()\",\n \"def post_create_snapshot(self, response: pubsub.Snapshot) -> pubsub.Snapshot:\\n return response\",\n \"def execute(self): \\r\\n _logger.info(\\\"=== Stage=snapshot = %s\\\" % self._config.name)\\r\\n _logger.info(\\\"++ Started at %s\\\" % time.strftime(\\\"%H:%M:%S\\\", time.localtime()))\\r\\n session = self.get_session()\\r\\n project = session.create(self._config.name)\\r\\n\\r\\n target_dir = os.path.normpath(os.path.join(self._config['dir'], project.name))\\r\\n _logger.info(\\\"Looking for snapshot under %s.\\\" % target_dir)\\r\\n if not self._check_version(project, target_dir):\\r\\n if not os.path.exists(target_dir):\\r\\n _logger.info(\\\"Creating '%s'.\\\" % target_dir)\\r\\n os.makedirs(target_dir)\\r\\n else:\\r\\n _logger.info(\\\"Project needs to be updated, so deleting '%s'.\\\" % target_dir)\\r\\n fileutils.rmtree(target_dir)\\r\\n \\r\\n try:\\r\\n _logger.info(\\\"Snapshotting project.\\\") \\r\\n if self.get_threads() == 1: \\r\\n _logger.info(project.snapshot(target_dir, True))\\r\\n else:\\r\\n _logger.info(ccm.extra.FastSnapshot(project, target_dir, self.get_threads()))\\r\\n \\r\\n # writing version file \\r\\n _logger.info(\\\"Saving project version information.\\\")\\r\\n versionfile = open(os.path.join(self._config['dir'], project.name, 'project.version'), \\\"w+\\\")\\r\\n versionfile.write(str(project))\\r\\n versionfile.close() \\r\\n except Exception, exc:\\r\\n if isinstance(exc, ccm.extra.CCMExtraException):\\r\\n for sexc in exc.subexceptions:\\r\\n _logger.info(sexc)\\r\\n _logger.info(\\\"ERROR: snapshotting %s\\\" % self._config.name)\\r\\n _logger.info(exc)\\r\\n raise exc\\r\\n else:\\r\\n _logger.info(\\\"Project snapshot is still up to date. Nothing to do.\\\")\\r\\n\\r\\n _logger.info(\\\"++ Finished at %s\\\" % time.strftime(\\\"%H:%M:%S\\\", time.localtime()))\",\n \"def snapshot(self, name):\\r\\n return self.driver.create_volume_snapshot(volume=self, name=name)\",\n \"def snapshot(self, instance, name):\\n # TODO(imsplitbit): Need to implement vzdump\\n pass\",\n \"def test_06_create_snapshots_in_project(self):\\n # Validate the following\\n # 1. Create a project\\n # 2. Add some snapshots to the project\\n # 3. Verify snapshot created inside project can only be used in inside\\n # the project\\n\\n if not self.snapshotSupported:\\n self.skipTest(\\\"Snapshot is not supported on %s\\\" % self.hypervisor)\\n\\n self.debug(\\\"Deploying VM for Project: %s\\\" % self.project.id)\\n virtual_machine_1 = VirtualMachine.create(\\n self.apiclient,\\n self.services[\\\"server\\\"],\\n templateid=self.template.id,\\n serviceofferingid=self.service_offering.id,\\n projectid=self.project.id\\n )\\n self.cleanup.append(virtual_machine_1)\\n # Verify VM state\\n self.assertEqual(\\n virtual_machine_1.state,\\n 'Running',\\n \\\"Check VM state is Running or not\\\"\\n )\\n\\n # Get the Root disk of VM\\n volumes = list_volumes(\\n self.apiclient,\\n projectid=self.project.id,\\n type='ROOT',\\n listall=True\\n )\\n self.assertEqual(\\n isinstance(volumes, list),\\n True,\\n \\\"Check for list volume response return valid data\\\"\\n )\\n\\n self.debug(\\\"Creating snapshot from volume: %s\\\" % volumes[0].id)\\n # Create a snapshot from the ROOTDISK\\n snapshot = Snapshot.create(self.apiclient,\\n volumes[0].id,\\n projectid=self.project.id\\n )\\n self.cleanup.append(snapshot)\\n # Verify Snapshot state\\n self.assertEqual(\\n snapshot.state in [\\n 'BackedUp',\\n 'CreatedOnPrimary',\\n 'Allocated'\\n ],\\n True,\\n \\\"Check Snapshot state is in one of the mentioned possible states, \\\\\\n It is currently: %s\\\" % snapshot.state\\n )\\n\\n snapshots = Snapshot.list(\\n self.apiclient,\\n account=self.account.name,\\n domainid=self.account.domainid\\n )\\n self.assertEqual(\\n snapshots,\\n None,\\n \\\"Snapshots should not be available outside the project\\\"\\n )\\n return\",\n \"def create(self, volume_id, force=False,\\n name=None, description=None, metadata=None):\\n\\n if metadata is None:\\n snapshot_metadata = {}\\n else:\\n snapshot_metadata = metadata\\n\\n # Bug #1995883: it's possible for the shell to use the user-\\n # specified 3.66 do_snapshot_create function, but if the server\\n # only supports < 3.66, the client will have been downgraded and\\n # will use this function. In that case, the 'force' parameter will\\n # be None, which means that the user didn't specify a value for it,\\n # so we set it to the pre-3.66 default value of False.\\n #\\n # NOTE: we know this isn't a problem for current client consumers\\n # because a null value for 'force' has never been allowed by the\\n # Block Storage API v3, so there's no reason for anyone to directly\\n # call this method passing force=None.\\n if force is None:\\n force = False\\n\\n body = {'snapshot': {'volume_id': volume_id,\\n 'force': force,\\n 'name': name,\\n 'description': description,\\n 'metadata': snapshot_metadata}}\\n return self._create('/snapshots', body, 'snapshot')\",\n \"def create_snapshot(self, volume_id, notes='No longer needed'):\\r\\n\\r\\n self.iscsi_svc.createSnapshot(notes, id=volume_id)\",\n \"def create(self, volume_id, force=None, # noqa: F811\\n name=None, description=None, metadata=None):\\n\\n if metadata is None:\\n snapshot_metadata = {}\\n else:\\n snapshot_metadata = metadata\\n\\n body = {'snapshot': {'volume_id': volume_id,\\n 'name': name,\\n 'description': description,\\n 'metadata': snapshot_metadata}}\\n if force is not None:\\n try:\\n force = strutils.bool_from_string(force, strict=True)\\n if not force:\\n raise ValueError()\\n except ValueError:\\n raise ValueError(MV_3_66_FORCE_FLAG_ERROR)\\n return self._create('/snapshots', body, 'snapshot')\",\n \"def create_volume_from_snapshot(self, volume, snapshot):\\n snap_name = self.get_snap_name(snapshot.id)\\n view_name = self.get_view_name(volume.id)\\n vol_name = self.get_volume_name(volume.id)\\n cview = src_attach_info = dest_attach_info = None\\n rpolicy = self.get_policy()\\n properties = volume_utils.brick_get_connector_properties(\\n self.configuration.use_multipath_for_image_xfer,\\n self.configuration.enforce_multipath_for_image_xfer)\\n LOG.debug(\\\"Searching for snapshot: %s in K2.\\\", snap_name)\\n snap_rs = self.client.search(\\\"snapshots\\\", short_name=snap_name)\\n if hasattr(snap_rs, 'hits') and snap_rs.total != 0:\\n snap = snap_rs.hits[0]\\n LOG.debug(\\\"Creating a view: %(view)s from snapshot: %(snap)s\\\",\\n {'view': view_name, 'snap': snap_name})\\n try:\\n cview = self.client.new(\\\"snapshots\\\",\\n short_name=view_name,\\n source=snap, retention_policy=rpolicy,\\n is_exposable=True).save()\\n except Exception as ex:\\n LOG.exception(\\\"Creating a view: %(view)s from snapshot: \\\"\\n \\\"%(snap)s failed\\\", {\\\"view\\\": view_name,\\n \\\"snap\\\": snap_name})\\n raise KaminarioCinderDriverException(reason=ex)\\n\\n else:\\n msg = _(\\\"Snapshot: %s search failed in K2.\\\") % snap_name\\n LOG.error(msg)\\n raise KaminarioCinderDriverException(reason=msg)\\n\\n try:\\n conn = self.initialize_connection(cview, properties)\\n src_attach_info = self._connect_device(conn)\\n self.create_volume(volume)\\n conn = self.initialize_connection(volume, properties)\\n dest_attach_info = self._connect_device(conn)\\n volume_utils.copy_volume(src_attach_info['device']['path'],\\n dest_attach_info['device']['path'],\\n snapshot.volume.size * units.Ki,\\n self.configuration.volume_dd_blocksize,\\n sparse=True)\\n self._kaminario_disconnect_volume(src_attach_info,\\n dest_attach_info)\\n self.terminate_connection(volume, properties)\\n self.terminate_connection(cview, properties)\\n cview.delete()\\n except Exception as ex:\\n self._kaminario_disconnect_volume(src_attach_info,\\n dest_attach_info)\\n self.terminate_connection(cview, properties)\\n self.terminate_connection(volume, properties)\\n cview.delete()\\n self.delete_volume(volume)\\n LOG.exception(\\\"Copy to volume: %(vol)s from view: %(view)s \\\"\\n \\\"failed\\\", {\\\"vol\\\": vol_name, \\\"view\\\": view_name})\\n raise KaminarioCinderDriverException(reason=ex)\",\n \"def clone_snapshot(self, pool, project, snapshot, clone, arg):\\n self.verify_avail_space(pool, project, clone['id'], clone['size'])\\n svc = self.clone_path % (pool, project,\\n snapshot['share_id'],\\n snapshot['id'])\\n ret = self.rclient.put(svc, arg)\\n if ret.status != restclient.Status.CREATED:\\n exception_msg = (_('Error cloning '\\n 'snapshot: %(snapshot)s on '\\n 'share: %(share)s of '\\n 'Pool: %(pool)s '\\n 'project: %(project)s '\\n 'return code: %(ret.status)d '\\n 'message: %(ret.data)s.')\\n % {'snapshot': snapshot['id'],\\n 'share': snapshot['share_id'],\\n 'pool': pool,\\n 'project': project,\\n 'ret.status': ret.status,\\n 'ret.data': ret.data})\\n LOG.error(exception_msg)\\n raise exception.ShareBackendException(msg=exception_msg)\",\n \"def database_volume_snapshot_add(volume_snapshot_obj):\\n db = database_get()\\n session = db.session()\\n query = session.query(model.VolumeSnapshot)\\n query = query.filter(model.VolumeSnapshot.uuid == volume_snapshot_obj.uuid)\\n volume_snapshot = query.first()\\n if not volume_snapshot:\\n volume_snapshot = model.VolumeSnapshot()\\n volume_snapshot.uuid = volume_snapshot_obj.uuid\\n volume_snapshot.name = volume_snapshot_obj.name\\n volume_snapshot.description = volume_snapshot_obj.description\\n volume_snapshot.size_gb = volume_snapshot_obj.size_gb\\n volume_snapshot.volume_uuid = volume_snapshot_obj.volume_uuid\\n volume_snapshot.nfvi_volume_snapshot_data = \\\\\\n json.dumps(volume_snapshot_obj.nfvi_volume_snapshot.as_dict())\\n session.add(volume_snapshot)\\n else:\\n volume_snapshot.name = volume_snapshot_obj.name\\n volume_snapshot.description = volume_snapshot_obj.description\\n volume_snapshot.size_gb = volume_snapshot_obj.size_gb\\n volume_snapshot.volume_uuid = volume_snapshot_obj.volume_uuid\\n volume_snapshot.nfvi_volume_snapshot_data = \\\\\\n json.dumps(volume_snapshot_obj.nfvi_volume_snapshot.as_dict())\\n db.commit()\",\n \"def snapshot_gen(self):\\n \\n # Generate snapshot\\n snapshot, snapshot_param = make_snapshot.snapshot_gen(self._parent)\\n # Save to ICobj\\n self._parent.snapshot = snapshot\\n self._parent.snapshot_param = snapshot_param\",\n \"def create_zfs_snapshot(self, name, source_zv_name, zfs_type='default'):\\n pname=self.poolname + '/' + source_zv_name + '@' + name\\n cmdstr=['zfs','snapshot',pname]\\n\\n try:\\n self._execute(*cmdstr,root_helper=self.r_helper,run_as_root=True) \\n except putils.ProcessExecutionError as err:\\n LOG.error(_('Cmd :%s') % err.cmd)\\n LOG.error(_('StdOut :%s') % err.stdout)\\n LOG.error(_('StdErr :%s') % err.stderr)\\n raise NameError('Error:failed to create snapshot for zfs volume:%s' % source_zv_name)\",\n \"def save(self, arguments):\\n name = arguments['<name>']\\n\\n instance_name = arguments['<instance>']\\n instance_name = self.activate(instance_name)\\n\\n vmrun = VMrun(self.vmx, user=self.user, password=self.password)\\n if vmrun.snapshot(name) is None:\\n puts_err(colored.red(\\\"Cannot take snapshot\\\"))\\n else:\\n puts_err(colored.green(\\\"Snapshot {} taken\\\".format(name)))\",\n \"def test_aws_service_api_snapshots_post(self):\\n pass\",\n \"def createDatabase(store):\\n atomicImageFile = store.newFile(*MUGSHOT_BODY_PATH_SEGMENTS)\\n imageFilePath = FilePath(__file__).parent().parent().child(\\n 'resources').child('square.png')\\n atomicImageFile.write(imageFilePath.getContent())\\n atomicImageFile.close()\\n\\n Mugshot(store=store,\\n person=Person(store=store),\\n body=atomicImageFile.finalpath,\\n smallerBody=atomicImageFile.finalpath,\\n type=MUGSHOT_TYPE)\",\n \"def snapshot_image_on_provider(self, builder, provider, credentials, target, template, parameters):\",\n \"def createNewShot(*args):\\n createDir.createShot(pi.shotsFolder)\",\n \"def create_and_publish_first_snapshot(distribution: str):\\n snapshot = f'distribution-{VERSION}'\\n run_cmd(['aptly', 'snapshot', 'create',\\n snapshot, 'from', 'repo', distribution])\\n run_cmd(['aptly', 'publish', 'snapshot', snapshot])\",\n \"def snap(self, path=None):\\n if path is None:\\n path = \\\"/tmp\\\"\\n else:\\n path = path.rstrip(\\\"/\\\")\\n day_dir = datetime.datetime.now().strftime(\\\"%d%m%Y\\\")\\n hour_dir = datetime.datetime.now().strftime(\\\"%H%M\\\")\\n ensure_snapshot_dir(path+\\\"/\\\"+self.cam_id+\\\"/\\\"+day_dir+\\\"/\\\"+hour_dir)\\n f_path = \\\"{0}/{1}/{2}/{3}/{4}.jpg\\\".format(\\n path,\\n self.cam_id,\\n day_dir,\\n hour_dir,\\n datetime.datetime.now().strftime(\\\"%S\\\"),\\n )\\n\\n urllib.urlretrieve(\\n 'http://{0}/snapshot.cgi?user={1}&pwd={2}'.format(\\n self.address, \\n self.user, \\n self.pswd,\\n ),\\n f_path,\\n )\\n #print resp[1]['Content-disposition'].replace(\\\"filename=\\\\\\\"\\\",\\\"\\\")[:-1]\",\n \"def snapshot(self):\\n return self.journal.create_checkpoint()\",\n \"def test_create_storage_group_snapshot_by_snap_id(self):\\n snapshot_info, sg_name = self.create_sg_snapshot()\\n ss_name = self.generate_name(object_type='ss')\\n self.replication.create_storage_group_snapshot(\\n sg_name, ss_name, ttl=1, hours=True)\\n snapshot_info = self.replication.get_storage_group_snapshot_list(\\n sg_name)\\n snapshot_details = (\\n self.replication.get_storage_group_snapshot_snap_id_list(\\n sg_name, ss_name))\\n self.replication.delete_storage_group_snapshot_by_snap_id(\\n sg_name, ss_name, snapshot_details[0])\\n self.assertIn(ss_name, snapshot_info)\",\n \"def create_snapshot(self):\\n # Don't create if it already exists\\n if self.image_available(self.snapshot_name):\\n print('Snapshot already exists')\\n return\\n\\n self.spawn()\\n\\n sleep_len = 10\\n # Make sure the network is up\\n t = 0\\n networks = None\\n while not networks:\\n try:\\n networks = self.instances[0].networks\\n except:\\n # not ready yet\\n pass\\n print('Waited {0}s for network to be up'.format(t))\\n if not networks:\\n time.sleep(sleep_len)\\n t += sleep_len\\n self.instances[0] = self.nova.servers.get(self.instances[0].id)\\n\\n # make sure an ip is received that we can ssh to\\n # self.instances[0].add_floating_ip('129.16.125.236')\\n t = 0\\n ip = None\\n while not ip:\\n networks = self.instances[0].networks\\n for key in networks:\\n if 'IPv4' in key:\\n ips = networks[key]\\n for i in ips:\\n # change to not if we want a floating ip\\n if i.startswith('192'):\\n ip = i\\n break\\n break\\n if not ip:\\n time.sleep(sleep_len)\\n print('Waited {0}s for ip'.format(t))\\n t += sleep_len\\n self.instances[0] = self.nova.servers.get(self.instances[0].id)\\n\\n # make sure cloud init finishes\\n t = 0\\n while not self._exists_remote(ip):\\n print('Waited {0}s for cloud-init to finish'.format(t))\\n time.sleep(sleep_len*3)\\n t += sleep_len*3\\n # create snapshot and make sure it gets active\\n self.nova.servers.create_image(self.instances[0].id, self.snapshot_name, None)\\n snapshot = self.nova.glance.find_image(self.snapshot_name)\\n\\n # Wait until snap\\n t = 0\\n status = snapshot.status\\n while status != 'active':\\n print('Waited {0}s for snapshot. Status is {1}'.format(t, status))\\n snapshot = self.nova.glance.find_image(self.snapshot_name)\\n status = snapshot.status\\n time.sleep(sleep_len*3)\\n t += sleep_len*3\\n print('Snapshot successfully uploaded. Now terminating worker.')\\n # kill created worker\\n self.terminate_all()\",\n \"def __take_snapshot(self):\\n # Set the filename to\\n # year_month_date_hour_minute_second.jpg\\n time_label = datetime.datetime.now()\\n filename = f\\\"{time_label.strftime('%Y-%m-%d_%H-%M-%S')}.jpg\\\"\\n\\n # Start the saving function in background\\n save_img_back = threading.Thread(target=self.__upload,\\n args=(filename,),\\n daemon=True)\\n save_img_back.start()\",\n \"def snapshot(source, destination):\\n\\n processutils.execute(\\n 'qemu-img convert --force-share -O qcow2 %s %s'\\n % (source, destination),\\n shell=True)\",\n \"def test_snapshot(self):\\n converter = InstructionToQobjConverter(PulseQobjInstruction, meas_level=2)\\n instruction = Snapshot(name='label', snap_type='type')\\n\\n valid_qobj = PulseQobjInstruction(\\n name='snapshot',\\n t0=0,\\n label='label',\\n type='type'\\n )\\n\\n self.assertEqual(converter(0, instruction), valid_qobj)\",\n \"def create_volume_snapshot(volumes, source_instance, objects_created,\\n wait_for_available=50):\\n if type(volumes) is not list:\\n volumes = [volumes]\\n s = []\\n for volume in volumes:\\n command = 'cinder snapshot-create --force True --name %s %s' % \\\\\\n (volume['name'], volume['id'])\\n snapshot_info = parse_output(Popen(command.split(), stdout=STDOUT).communicate()[0])\\n if volume['bootable'] == 'true':\\n snapshot_info['bootable'] = True\\n else:\\n snapshot_info['bootable'] = False\\n att = volume['attachments'].replace(\\\"'\\\", \\\"\\\\\\\"\\\").replace(\\n \\\"u\\\\\\\"\\\", \\\"\\\\\\\"\\\").replace(\\\" None,\\\", \\\" \\\\\\\"None\\\\\\\",\\\")\\n snapshot_info['device'] = get(json.loads(att), 'server_id',\\n source_instance['id'])[0]['device']\\n s.append(snapshot_info)\\n if wait_for_available > 0:\\n wait = 0\\n again = False\\n while wait < wait_for_available:\\n time.sleep(5)\\n wait += 5\\n again = False\\n for snapshot in s:\\n command = 'cinder snapshot-show %s' % snapshot['id']\\n status = parse_output(Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n )['status']\\n if status == 'error':\\n # clean up and take snapshot again\\n command = 'cinder snapshot-delete %s' % snapshot['id']\\n a = Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n command = 'cinder snapshot-create --force True %s' % \\\\\\n snapshot['volume_id']\\n snapshot_info = parse_output(Popen(command.split(),\\n stdout=STDOUT, stderr=STDERR\\n ).communicate()[0])\\n snapshot_info['bootable'] = snapshot['bootable']\\n snapshot_info['device'] = snapshot['device']\\n snapshot = snapshot_info\\n again = True\\n break\\n elif status == 'creating':\\n again = True\\n break\\n elif status == 'available':\\n snapshot['status'] = status\\n pass\\n if again:\\n continue\\n else:\\n break\\n if again: # Loop ended due to timeout\\n print 'Error creating volume snapshot!'\\n print 'The following entities were created in the process:'\\n print_objects_created(objects_created)\\n sys.exit(-1)\\n return s\",\n \"def create(self, group_id, name=None, description=None,\\n user_id=None,\\n project_id=None):\\n\\n body = {\\n 'group_snapshot': {\\n 'group_id': group_id,\\n 'name': name,\\n 'description': description,\\n }\\n }\\n\\n return self._create('/group_snapshots', body, 'group_snapshot')\",\n \"def create_volume(self, snapshot_id = \\\"\\\", size = -1):\\n response = volume.create_volume(self.url, self.verb,\\n self.headers, self.version,\\n snapshot_id, size)\\n if response is not None :\\n res = CreateVolumeResponse.CreateVolumeResponse()\\n parseString(str(response.text), res)\\n return res\\n else :\\n return None\",\n \"def _take_snapshot(self, filename, frame):\\n thumbnail_key = os.path.join(self._obj_key_prefix, \\\"{}.jpg\\\"\\n .format(filename))\\n drawn_image = im.draw_region(frame.image,\\n self._detector.roi,\\n EVENT_ALERT_COLOR_CODE,\\n 0.4)\\n shrunk_image = im.shrink_image(drawn_image)\\n self._obj_store.save_image_obj(thumbnail_key, shrunk_image)\\n return thumbnail_key\",\n \"def snapshot(self, agent_memory):\\n\\n read_cmd = \\\"SELECT \\\"\\n for r in self.TABLE_COLUMNS:\\n read_cmd += r + \\\", \\\"\\n read_cmd = read_cmd.strip(\\\", \\\")\\n read_cmd += \\\" FROM \\\" + self.TABLE + \\\" WHERE uuid=?\\\"\\n data = agent_memory._db_read_one(read_cmd, self.memid)\\n if not data:\\n raise (\\\"tried to snapshot nonexistent memory\\\")\\n\\n archive_memid = self.new(agent_memory, snapshot=True)\\n new_data = list(data)\\n new_data[0] = archive_memid\\n\\n if hasattr(self, \\\"ARCHIVE_TABLE\\\"):\\n archive_table = self.ARCHIVE_TABLE\\n else:\\n archive_table = self.TABLE\\n write_cmd = \\\"INSERT INTO \\\" + archive_table + \\\"(\\\"\\n qs = \\\"\\\"\\n for r in self.TABLE_COLUMNS:\\n write_cmd += r + \\\", \\\"\\n qs += \\\"?, \\\"\\n write_cmd = write_cmd.strip(\\\", \\\")\\n write_cmd += \\\") VALUES (\\\" + qs.strip(\\\", \\\") + \\\")\\\"\\n agent_memory._db_write(write_cmd, *new_data)\\n link_archive_to_mem(agent_memory, self.memid, archive_memid)\",\n \"def test_snapshot(self):\\n cmd = Snapshot(name='label', snap_type='type')\\n instruction = cmd << 10\\n\\n qobj = PulseQobjInstruction(name='snapshot', t0=10, label='label', type='type')\\n converted_instruction = self.converter(qobj)\\n\\n self.assertEqual(converted_instruction.timeslots, instruction.timeslots)\\n self.assertEqual(converted_instruction.instructions[0][-1], cmd)\",\n \"def snapshot(self, context, instance, image_id, update_task_state):\\n raise NotImplementedError()\",\n \"def _ensure_snapshot(connection, volume, interval, name):\\n if interval not in VALID_INTERVALS:\\n logging.warning(kayvee.formatLog(\\\"ebs-snapshots\\\", \\\"warning\\\", \\\"invalid snapshotting interval\\\", {\\n \\\"volume\\\": volume.id,\\n \\\"interval\\\": interval\\n }))\\n return\\n\\n snapshots = connection.get_all_snapshots(filters={'volume-id': volume.id})\\n\\n # Create a snapshot if we don't have any\\n if not snapshots:\\n _create_snapshot(connection, volume, name)\\n return\\n\\n min_delta = 3600 * 24 * 365 * 10 # 10 years :)\\n for snapshot in snapshots:\\n timestamp = datetime.datetime.strptime(\\n snapshot.start_time,\\n '%Y-%m-%dT%H:%M:%S.000Z')\\n delta_seconds = int(\\n (datetime.datetime.utcnow() - timestamp).total_seconds())\\n\\n if delta_seconds < min_delta:\\n min_delta = delta_seconds\\n\\n logging.info(kayvee.formatLog(\\\"ebs-snapshots\\\", \\\"info\\\", 'The newest snapshot for {} is {} seconds old'.format(volume.id, min_delta)))\\n\\n if interval == 'hourly' and min_delta > 3600:\\n _create_snapshot(connection, volume, name)\\n elif interval == 'daily' and min_delta > 3600*24:\\n _create_snapshot(connection, volume, name)\\n elif interval == 'weekly' and min_delta > 3600*24*7:\\n _create_snapshot(connection, volume, name)\\n elif interval == 'monthly' and min_delta > 3600*24*30:\\n _create_snapshot(connection, volume, name)\\n elif interval == 'yearly' and min_delta > 3600*24*365:\\n _create_snapshot(connection, volume, name)\\n else:\\n logging.info(kayvee.formatLog(\\\"ebs-snapshots\\\", \\\"info\\\", \\\"no snapshot needed\\\", {\\\"volume\\\": volume.id}))\",\n \"def save_snapshot(args):\\n html_doc = document.Document(get_code(args.file))\\n info = html_doc.save(args.message, date=args.edition, region=args.region)\\n if info is None:\\n print('Duplicate snapshot. No snapshot saved.')\\n else:\\n print('Snapshot saved for {:s} {:%B %d, %Y}. '.format(info[2].capitalize(), info[3]) +\\n '{0!r:} - {1:%B} {1.day:2}, {1:%Y %l:%M:%S.%f %p}'.format(info[0], info[1]))\",\n \"def snapshot(self) -> Snapshot:\\n snapshot = self.open(Snapshot.type).signed\\n if not isinstance(snapshot, Snapshot):\\n raise RuntimeError(\\\"Unexpected snapshot type\\\")\\n return snapshot\",\n \"def prepare_snapshot(self, instance, activity, **kwargs):\\n return activity._content_object\",\n \"def take_snapshot(self):\\r\\n self.snapshot = self.gain, self.block, self.locked, self.bucket_num\",\n \"def do_takesnapshot(self, str_arg):\\n img = None\\n fname = validateString(str_arg)\\n try:\\n # self.adbc.wake()\\n printLog(self.threadName + 'taking snapshot (0,50,%d,%d) ...' %\\n (self.scn_width, self.scn_height))\\n img = self.adbc.takeSnapshot(reconnect=True)\\n # PIL code\\n img = img.crop((0, 50, self.scn_width, self.scn_height))\\n img.save(fname, SNAPSHOT_IMAGE_FORMAT)\\n # if self.scn_width>SNAPSHOT_WIDTH:\\n # self.compressImage(fname)\\n # os.remove(fname)\\n # im.save(fname)\\n printLog(self.threadName + 'snapshot saved as %s' % fname)\\n except EnvironmentError:\\n self.resultFlag = False\\n if DEBUG:\\n traceback.print_exc()\\n finally:\\n img = None\",\n \"def serialize_snapshot(self, snapshot, fields=None, version=None):\\n fields = fields or self.snapshot_fields\\n version = version or self.snapshot_version\\n serialized_snapshot = serializers.serialize(\\n 'python', [snapshot], fields=fields\\n )[0]\\n serialized_snapshot['version'] = version\\n serialized_snapshot['extra_fields'] = {}\\n return serialized_snapshot\",\n \"def add_snapshot(self, dest, source=None):\\n raise NotImplementedYet()\",\n \"def put_snapshot_object(session, key, data, snapshot=None):\\n # type: (Session, Text, Any, Optional[Text]) -> None\\n url_tail = \\\"/{}/{}/{}/{}/{}\\\".format(\\n CoordConstsV2.RSC_NETWORKS,\\n session.network,\\n CoordConstsV2.RSC_SNAPSHOTS,\\n session.get_snapshot(snapshot),\\n CoordConstsV2.RSC_OBJECTS,\\n )\\n _put_stream(session, url_tail, data, {CoordConstsV2.QP_KEY: key})\",\n \"def link_snapshot(argstr):\\n pass\",\n \"def new_shot(context):\\n\\n shot = context.scene.milkshake_shots.add()\\n camera = bpy.data.cameras.new(\\\"Camera\\\")\\n camera.display_size = 1\\n camera.dof.aperture_blades = 5\\n camera.dof.aperture_fstop = 4\\n camera.dof.aperture_ratio = 1\\n camera.dof.aperture_rotation = math.radians(10)\\n camera.dof.focus_distance = 1\\n camera.dof.use_dof = True\\n camera.lens = 35\\n camera.passepartout_alpha = 0.85\\n camera.sensor_fit = 'HORIZONTAL'\\n camera.sensor_height = 13.365\\n camera.sensor_width = 23.76\\n camera_object = bpy.data.objects.new(\\\"Camera\\\", camera)\\n\\n cam_collection = camera_collection(context)\\n cam_collection.objects.link(camera_object)\\n shot.camera = camera\\n core.log(\\\"Created new shot and camera.\\\")\",\n \"def _AddSnapshot(self, snapshot):\\n if self._history.count(snapshot) == 0:\\n self._history.append(snapshot)\",\n \"def __call__(\\n self,\\n request: pubsub.CreateSnapshotRequest,\\n *,\\n retry: OptionalRetry = gapic_v1.method.DEFAULT,\\n timeout: Optional[float] = None,\\n metadata: Sequence[Tuple[str, str]] = (),\\n ) -> pubsub.Snapshot:\\n\\n http_options: List[Dict[str, str]] = [\\n {\\n \\\"method\\\": \\\"put\\\",\\n \\\"uri\\\": \\\"/v1/{name=projects/*/snapshots/*}\\\",\\n \\\"body\\\": \\\"*\\\",\\n },\\n ]\\n request, metadata = self._interceptor.pre_create_snapshot(request, metadata)\\n pb_request = pubsub.CreateSnapshotRequest.pb(request)\\n transcoded_request = path_template.transcode(http_options, pb_request)\\n\\n # Jsonify the request body\\n\\n body = json_format.MessageToJson(\\n transcoded_request[\\\"body\\\"],\\n including_default_value_fields=False,\\n use_integers_for_enums=True,\\n )\\n uri = transcoded_request[\\\"uri\\\"]\\n method = transcoded_request[\\\"method\\\"]\\n\\n # Jsonify the query params\\n query_params = json.loads(\\n json_format.MessageToJson(\\n transcoded_request[\\\"query_params\\\"],\\n including_default_value_fields=False,\\n use_integers_for_enums=True,\\n )\\n )\\n query_params.update(self._get_unset_required_fields(query_params))\\n\\n query_params[\\\"$alt\\\"] = \\\"json;enum-encoding=int\\\"\\n\\n # Send the request\\n headers = dict(metadata)\\n headers[\\\"Content-Type\\\"] = \\\"application/json\\\"\\n response = getattr(self._session, method)(\\n \\\"{host}{uri}\\\".format(host=self._host, uri=uri),\\n timeout=timeout,\\n headers=headers,\\n params=rest_helpers.flatten_query_params(query_params, strict=True),\\n data=body,\\n )\\n\\n # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception\\n # subclass.\\n if response.status_code >= 400:\\n raise core_exceptions.from_http_response(response)\\n\\n # Return the response\\n resp = pubsub.Snapshot()\\n pb_resp = pubsub.Snapshot.pb(resp)\\n\\n json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)\\n resp = self._interceptor.post_create_snapshot(resp)\\n return resp\",\n \"def manage(self, volume_id, ref, name=None, description=None,\\n metadata=None):\\n body = {'snapshot': {'volume_id': volume_id,\\n 'ref': ref,\\n 'name': name,\\n 'description': description,\\n 'metadata': metadata\\n }\\n }\\n return self._create('/os-snapshot-manage', body, 'snapshot')\",\n \"def make_release(self, **kwargs) -> ThothRelease:\\n snapshot_date = make_snapshot_date(**kwargs)\\n release = ThothRelease(dag_id=self.dag_id, run_id=kwargs[\\\"run_id\\\"], snapshot_date=snapshot_date)\\n return release\",\n \"def restore(project, zone, instance, snapshot):\\n disks = []\\n description = 'Created from %s by %s' % (snapshot, getpass.getuser())\\n for disk, size in get_disks(instance).items():\\n gcloud(\\n project,\\n 'compute',\\n 'disks',\\n 'create',\\n '--description=%s' % description,\\n '--zone=%s' % zone,\\n '--size=%dGB' % size,\\n '--source-snapshot=%s-%s' % (disk, snapshot),\\n disk,\\n )\\n attrs = [\\n 'name=%s' % disk,\\n 'device-name=%s' % disk,\\n ]\\n if disk == instance:\\n attrs.append('boot=yes')\\n disks.append(attrs)\\n gcloud(\\n project,\\n 'compute',\\n 'instances',\\n 'create',\\n '--description=%s' % description,\\n '--zone=%s' % zone,\\n '--machine-type=n1-highmem-32', # should reduce to 8\\n '--scopes=%s' % ','.join(SCOPES),\\n '--tag=do-not-delete,jenkins,jenkins-master',\\n '--address=%s' % get_address(project, zone, instance),\\n *('--disk=%s' % ','.join(a) for a in disks))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.79396224","0.79085445","0.7880862","0.78679043","0.77699107","0.77232075","0.7571505","0.7500152","0.7409868","0.73697287","0.7301827","0.7300242","0.72600234","0.72017276","0.71182054","0.7031012","0.69631094","0.69143236","0.69007653","0.68159884","0.68020076","0.67745256","0.6772022","0.67391044","0.67329186","0.6725525","0.67015535","0.66622853","0.66602796","0.66228485","0.66221267","0.6590441","0.65338767","0.65256816","0.65238196","0.65072095","0.6487937","0.6461002","0.6446254","0.64345235","0.6432914","0.6369619","0.63647115","0.6363704","0.6360475","0.63598514","0.6350493","0.6347783","0.6329532","0.6314064","0.62832546","0.62570393","0.62439185","0.62314516","0.6222056","0.62178326","0.6213883","0.6209786","0.61810607","0.61624116","0.6149846","0.61401814","0.6138937","0.6134743","0.6130828","0.60880214","0.60842866","0.60811174","0.6077114","0.60384494","0.6025394","0.60144836","0.599502","0.5988858","0.5982416","0.596959","0.59654886","0.5906697","0.5906553","0.5903645","0.58994937","0.5895967","0.58740276","0.5873482","0.5859258","0.585525","0.5851649","0.58410114","0.5831686","0.5808456","0.5801333","0.5767185","0.57522565","0.5738319","0.57369214","0.57365334","0.5726083","0.57183725","0.57170993","0.56935275"],"string":"[\n \"0.79396224\",\n \"0.79085445\",\n \"0.7880862\",\n \"0.78679043\",\n \"0.77699107\",\n \"0.77232075\",\n \"0.7571505\",\n \"0.7500152\",\n \"0.7409868\",\n \"0.73697287\",\n \"0.7301827\",\n \"0.7300242\",\n \"0.72600234\",\n \"0.72017276\",\n \"0.71182054\",\n \"0.7031012\",\n \"0.69631094\",\n \"0.69143236\",\n \"0.69007653\",\n \"0.68159884\",\n \"0.68020076\",\n \"0.67745256\",\n \"0.6772022\",\n \"0.67391044\",\n \"0.67329186\",\n \"0.6725525\",\n \"0.67015535\",\n \"0.66622853\",\n \"0.66602796\",\n \"0.66228485\",\n \"0.66221267\",\n \"0.6590441\",\n \"0.65338767\",\n \"0.65256816\",\n \"0.65238196\",\n \"0.65072095\",\n \"0.6487937\",\n \"0.6461002\",\n \"0.6446254\",\n \"0.64345235\",\n \"0.6432914\",\n \"0.6369619\",\n \"0.63647115\",\n \"0.6363704\",\n \"0.6360475\",\n \"0.63598514\",\n \"0.6350493\",\n \"0.6347783\",\n \"0.6329532\",\n \"0.6314064\",\n \"0.62832546\",\n \"0.62570393\",\n \"0.62439185\",\n \"0.62314516\",\n \"0.6222056\",\n \"0.62178326\",\n \"0.6213883\",\n \"0.6209786\",\n \"0.61810607\",\n \"0.61624116\",\n \"0.6149846\",\n \"0.61401814\",\n \"0.6138937\",\n \"0.6134743\",\n \"0.6130828\",\n \"0.60880214\",\n \"0.60842866\",\n \"0.60811174\",\n \"0.6077114\",\n \"0.60384494\",\n \"0.6025394\",\n \"0.60144836\",\n \"0.599502\",\n \"0.5988858\",\n \"0.5982416\",\n \"0.596959\",\n \"0.59654886\",\n \"0.5906697\",\n \"0.5906553\",\n \"0.5903645\",\n \"0.58994937\",\n \"0.5895967\",\n \"0.58740276\",\n \"0.5873482\",\n \"0.5859258\",\n \"0.585525\",\n \"0.5851649\",\n \"0.58410114\",\n \"0.5831686\",\n \"0.5808456\",\n \"0.5801333\",\n \"0.5767185\",\n \"0.57522565\",\n \"0.5738319\",\n \"0.57369214\",\n \"0.57365334\",\n \"0.5726083\",\n \"0.57183725\",\n \"0.57170993\",\n \"0.56935275\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.752988"},"document_rank":{"kind":"string","value":"7"}}},{"rowIdx":81763,"cells":{"query":{"kind":"string","value":"Ensure that a given volume has an appropriate snapshot"},"document":{"kind":"string","value":"def _ensure_snapshot(connection, volume, interval, name):\n if interval not in VALID_INTERVALS:\n logging.warning(kayvee.formatLog(\"ebs-snapshots\", \"warning\", \"invalid snapshotting interval\", {\n \"volume\": volume.id,\n \"interval\": interval\n }))\n return\n\n snapshots = connection.get_all_snapshots(filters={'volume-id': volume.id})\n\n # Create a snapshot if we don't have any\n if not snapshots:\n _create_snapshot(connection, volume, name)\n return\n\n min_delta = 3600 * 24 * 365 * 10 # 10 years :)\n for snapshot in snapshots:\n timestamp = datetime.datetime.strptime(\n snapshot.start_time,\n '%Y-%m-%dT%H:%M:%S.000Z')\n delta_seconds = int(\n (datetime.datetime.utcnow() - timestamp).total_seconds())\n\n if delta_seconds < min_delta:\n min_delta = delta_seconds\n\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", 'The newest snapshot for {} is {} seconds old'.format(volume.id, min_delta)))\n\n if interval == 'hourly' and min_delta > 3600:\n _create_snapshot(connection, volume, name)\n elif interval == 'daily' and min_delta > 3600*24:\n _create_snapshot(connection, volume, name)\n elif interval == 'weekly' and min_delta > 3600*24*7:\n _create_snapshot(connection, volume, name)\n elif interval == 'monthly' and min_delta > 3600*24*30:\n _create_snapshot(connection, volume, name)\n elif interval == 'yearly' and min_delta > 3600*24*365:\n _create_snapshot(connection, volume, name)\n else:\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", \"no snapshot needed\", {\"volume\": volume.id}))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_create_volume_from_snapshot(self, mock_ghn):\n ctxt = context.get_admin_context()\n extra_specs = {}\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\n snap = {'id': '1', 'name': 'volume1', 'display_name': '',\n 'volume_type_id': type_ref['id'], 'size': 10,\n 'provider_id': 'space_orig'}\n volume = {'id': '2', 'name': 'volume2', 'display_name': '',\n 'volume_type_id': type_ref['id'], 'size': 10}\n pid = self.driver.create_volume_from_snapshot(volume, snap)\n # We must copy entier underlying storage, ~12GB, not just 10GB\n self.assertEqual(11444 * units.Mi, self.dd_count)\n self.assertEqual('1M', self.bs)\n # Check space-create command\n expected = {'redundancy': '0', 'group': 'xanadu',\n 'name': 'volume2', 'mode': '0777',\n 'user': 'kane', 'net': 'net1',\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\n 'size': '12'}\n self.assertDictMatch(expected, self.created)\n # Check the returned provider\n expected_pid = {'provider_id': 'volume2'}\n self.assertDictMatch(expected_pid, pid)","def create_volume_from_snapshot(snapshots, objects_created,\n wait_for_available=120):\n if type(snapshots) is not list:\n snapshots = [snapshots]\n v = []\n for snapshot in snapshots:\n command = 'cinder create --snapshot-id %s --name %s' % \\\n (snapshot['id'], snapshot['display_name'])\n volume_from_snapshot = parse_output(Popen(\n command.split(), stdout=STDOUT, stderr=STDERR).communicate()[0])\n volume_from_snapshot['device'] = snapshot['device']\n volume_from_snapshot['bootable'] = snapshot['bootable']\n v.append(volume_from_snapshot)\n if wait_for_available > 0:\n wait = 0\n again = False\n while wait < wait_for_available:\n time.sleep(5)\n wait += 5\n again = False\n for volume in v:\n command = 'cinder show %s' % volume['id']\n status = parse_output(Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n )['status']\n if status == 'error':\n # clean up and create volume again\n command = 'cinder delete %s' % volume['id']\n a = Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n command = 'cinder create --snapshot-id %s' % \\\n volume['snapshot_id']\n volume_info = parse_output(Popen(\n command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0])\n volume_info['bootable'] = volume['bootable']\n volume_info['device'] = volume['device']\n volume = volume_info\n again = True\n break\n elif status == 'creating':\n again = True\n break\n elif status == 'available':\n volume['status'] = status\n pass\n if again:\n continue\n else:\n break\n if again: # Loop ended due to timeout\n print 'Error creating volume from snapshot!'\n print 'The following entities were created in the process:'\n print_objects_created(objects_created)\n sys.exit(-1)\n return v","def create_volume_from_snapshot(self, snapshot, volume, volume_db):\n self.authenticate_user()\n\n if self.configuration.vipr_emulate_snapshot == 'True':\n self.create_cloned_volume(volume, snapshot)\n return\n\n ctxt = context.get_admin_context()\n\n src_snapshot_name = None\n\n #src_snapshot_name = snapshot['display_name']\n src_vol_ref = volume_db.volume_get(ctxt, snapshot['volume_id'])\n new_volume_name = self._get_volume_name(volume)\n number_of_volumes = 1\n\n try:\n src_vol_name, src_vol_uri = self._get_vipr_volume_name(src_vol_ref, True)\n src_snapshot_name = self._get_vipr_snapshot_name(snapshot , src_vol_uri)\n\n (storageresType, storageresTypename) = self.volume_obj.get_storageAttributes(\n src_vol_name\n , None\n , src_snapshot_name)\n\n resource_id = self.volume_obj.storageResource_query(storageresType,\n src_vol_name,\n None,\n src_snapshot_name,\n self.configuration.vipr_project,\n self.configuration.vipr_tenant)\n\n self.volume_obj.clone(\n new_volume_name,\n number_of_volumes,\n resource_id,\n sync=True)\n\n except vipr_utils.SOSError as e:\n if(e.err_code == vipr_utils.SOSError.SOS_FAILURE_ERR):\n raise vipr_utils.SOSError(\n vipr_utils.SOSError.SOS_FAILURE_ERR,\n \"Snapshot \" +\n src_snapshot_name +\n \": clone failed\\n\" +\n e.err_text)\n else:\n with excutils.save_and_reraise_exception():\n LOG.exception(\n _(\"Snapshot : %s clone failed\") % src_snapshot_name)","def create_volume_snapshot(self, volume, name=None, description=None,\n check=True):\n cmd = 'cinder snapshot-create'\n if name:\n cmd += ' --name ' + name\n if description is not None:\n cmd += ' --description ' + moves.shlex_quote(description)\n\n cmd += ' ' + volume.id\n\n exit_code, stdout, stderr = self.execute_command(\n cmd, timeout=config.SNAPSHOT_AVAILABLE_TIMEOUT, check=check)\n\n snapshot_table = output_parser.table(stdout)\n snapshot = {key: value for key, value in snapshot_table['values']}\n\n return snapshot","def create_volume_from_snapshot(self, volume, snapshot):\n snap_name = self.get_snap_name(snapshot.id)\n view_name = self.get_view_name(volume.id)\n vol_name = self.get_volume_name(volume.id)\n cview = src_attach_info = dest_attach_info = None\n rpolicy = self.get_policy()\n properties = volume_utils.brick_get_connector_properties(\n self.configuration.use_multipath_for_image_xfer,\n self.configuration.enforce_multipath_for_image_xfer)\n LOG.debug(\"Searching for snapshot: %s in K2.\", snap_name)\n snap_rs = self.client.search(\"snapshots\", short_name=snap_name)\n if hasattr(snap_rs, 'hits') and snap_rs.total != 0:\n snap = snap_rs.hits[0]\n LOG.debug(\"Creating a view: %(view)s from snapshot: %(snap)s\",\n {'view': view_name, 'snap': snap_name})\n try:\n cview = self.client.new(\"snapshots\",\n short_name=view_name,\n source=snap, retention_policy=rpolicy,\n is_exposable=True).save()\n except Exception as ex:\n LOG.exception(\"Creating a view: %(view)s from snapshot: \"\n \"%(snap)s failed\", {\"view\": view_name,\n \"snap\": snap_name})\n raise KaminarioCinderDriverException(reason=ex)\n\n else:\n msg = _(\"Snapshot: %s search failed in K2.\") % snap_name\n LOG.error(msg)\n raise KaminarioCinderDriverException(reason=msg)\n\n try:\n conn = self.initialize_connection(cview, properties)\n src_attach_info = self._connect_device(conn)\n self.create_volume(volume)\n conn = self.initialize_connection(volume, properties)\n dest_attach_info = self._connect_device(conn)\n volume_utils.copy_volume(src_attach_info['device']['path'],\n dest_attach_info['device']['path'],\n snapshot.volume.size * units.Ki,\n self.configuration.volume_dd_blocksize,\n sparse=True)\n self._kaminario_disconnect_volume(src_attach_info,\n dest_attach_info)\n self.terminate_connection(volume, properties)\n self.terminate_connection(cview, properties)\n cview.delete()\n except Exception as ex:\n self._kaminario_disconnect_volume(src_attach_info,\n dest_attach_info)\n self.terminate_connection(cview, properties)\n self.terminate_connection(volume, properties)\n cview.delete()\n self.delete_volume(volume)\n LOG.exception(\"Copy to volume: %(vol)s from view: %(view)s \"\n \"failed\", {\"vol\": vol_name, \"view\": view_name})\n raise KaminarioCinderDriverException(reason=ex)","def create_volume_from_snapshot(self, volume, snapshot):\n snapshotname = huawei_utils.encode_name(snapshot['id'])\n\n snapshot_id = snapshot.get('provider_location', None)\n if snapshot_id is None:\n snapshot_id = self.restclient.get_snapshotid_by_name(snapshotname)\n if snapshot_id is None:\n err_msg = (_(\n 'create_volume_from_snapshot: Snapshot %(name)s '\n 'does not exist.')\n % {'name': snapshotname})\n LOG.error(err_msg)\n raise exception.VolumeBackendAPIException(data=err_msg)\n\n lun_info = self.create_volume(volume)\n\n tgt_lun_id = lun_info['ID']\n luncopy_name = huawei_utils.encode_name(volume['id'])\n\n LOG.info(_LI(\n 'create_volume_from_snapshot: src_lun_id: %(src_lun_id)s, '\n 'tgt_lun_id: %(tgt_lun_id)s, copy_name: %(copy_name)s.'),\n {'src_lun_id': snapshot_id,\n 'tgt_lun_id': tgt_lun_id,\n 'copy_name': luncopy_name})\n\n event_type = 'LUNReadyWaitInterval'\n\n wait_interval = huawei_utils.get_wait_interval(self.xml_file_path,\n event_type)\n\n def _volume_ready():\n result = self.restclient.get_lun_info(tgt_lun_id)\n\n if (result['HEALTHSTATUS'] == constants.STATUS_HEALTH\n and result['RUNNINGSTATUS'] == constants.STATUS_VOLUME_READY):\n return True\n return False\n\n huawei_utils.wait_for_condition(self.xml_file_path,\n _volume_ready,\n wait_interval,\n wait_interval * 10)\n\n self._copy_volume(volume, luncopy_name,\n snapshot_id, tgt_lun_id)\n\n return {'ID': lun_info['ID'],\n 'lun_info': lun_info}","def create_volume_snapshot(volumes, source_instance, objects_created,\n wait_for_available=50):\n if type(volumes) is not list:\n volumes = [volumes]\n s = []\n for volume in volumes:\n command = 'cinder snapshot-create --force True --name %s %s' % \\\n (volume['name'], volume['id'])\n snapshot_info = parse_output(Popen(command.split(), stdout=STDOUT).communicate()[0])\n if volume['bootable'] == 'true':\n snapshot_info['bootable'] = True\n else:\n snapshot_info['bootable'] = False\n att = volume['attachments'].replace(\"'\", \"\\\"\").replace(\n \"u\\\"\", \"\\\"\").replace(\" None,\", \" \\\"None\\\",\")\n snapshot_info['device'] = get(json.loads(att), 'server_id',\n source_instance['id'])[0]['device']\n s.append(snapshot_info)\n if wait_for_available > 0:\n wait = 0\n again = False\n while wait < wait_for_available:\n time.sleep(5)\n wait += 5\n again = False\n for snapshot in s:\n command = 'cinder snapshot-show %s' % snapshot['id']\n status = parse_output(Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n )['status']\n if status == 'error':\n # clean up and take snapshot again\n command = 'cinder snapshot-delete %s' % snapshot['id']\n a = Popen(command.split(), stdout=STDOUT,\n stderr=STDERR).communicate()[0]\n command = 'cinder snapshot-create --force True %s' % \\\n snapshot['volume_id']\n snapshot_info = parse_output(Popen(command.split(),\n stdout=STDOUT, stderr=STDERR\n ).communicate()[0])\n snapshot_info['bootable'] = snapshot['bootable']\n snapshot_info['device'] = snapshot['device']\n snapshot = snapshot_info\n again = True\n break\n elif status == 'creating':\n again = True\n break\n elif status == 'available':\n snapshot['status'] = status\n pass\n if again:\n continue\n else:\n break\n if again: # Loop ended due to timeout\n print 'Error creating volume snapshot!'\n print 'The following entities were created in the process:'\n print_objects_created(objects_created)\n sys.exit(-1)\n return s","def migrate_volume(self, ctxt, volume, host):\n LOG.debug('Enter: migrate_volume: id=%(id)s, host=%(host)s',\n {'id': volume['id'], 'host': host})\n\n false_ret = (False, None)\n\n if volume['status'] not in ('available', 'retyping'):\n LOG.warning(\"Volume status must be 'available' or 'retyping'.\"\n \" Current volume status: %s\", volume['status'])\n return false_ret\n\n if 'capabilities' not in host:\n LOG.warning(\"Unsupported host. No capabilities found\")\n return false_ret\n\n capabilities = host['capabilities']\n ns_shares = capabilities['ns_shares']\n dst_parts = capabilities['location_info'].split(':')\n dst_host, dst_volume = dst_parts[1:]\n\n if (capabilities.get('vendor_name') != 'Nexenta' or\n dst_parts[0] != self.__class__.__name__ or\n capabilities['free_capacity_gb'] < volume['size']):\n return false_ret\n\n nms = self.share2nms[volume['provider_location']]\n ssh_bindings = nms.appliance.ssh_list_bindings()\n shares = []\n for bind in ssh_bindings:\n for share in ns_shares:\n if (share.startswith(ssh_bindings[bind][3]) and\n ns_shares[share] >= volume['size']):\n shares.append(share)\n if len(shares) == 0:\n LOG.warning(\"Remote NexentaStor appliance at %s should be \"\n \"SSH-bound.\", share)\n return false_ret\n share = sorted(shares, key=ns_shares.get, reverse=True)[0]\n snapshot = {\n 'volume_name': volume['name'],\n 'volume_id': volume['id'],\n 'name': utils.get_migrate_snapshot_name(volume)\n }\n self.create_snapshot(snapshot)\n location = volume['provider_location']\n src = '%(share)s/%(volume)s@%(snapshot)s' % {\n 'share': location.split(':')[1].split('volumes/')[1],\n 'volume': volume['name'],\n 'snapshot': snapshot['name']\n }\n dst = ':'.join([dst_host, dst_volume.split('/volumes/')[1]])\n try:\n nms.appliance.execute(self._get_zfs_send_recv_cmd(src, dst))\n except utils.NexentaException as exc:\n LOG.warning(\"Cannot send source snapshot %(src)s to \"\n \"destination %(dst)s. Reason: %(exc)s\",\n {'src': src, 'dst': dst, 'exc': exc})\n return false_ret\n finally:\n try:\n self.delete_snapshot(snapshot)\n except utils.NexentaException as exc:\n LOG.warning(\"Cannot delete temporary source snapshot \"\n \"%(src)s on NexentaStor Appliance: %(exc)s\",\n {'src': src, 'exc': exc})\n try:\n self.delete_volume(volume)\n except utils.NexentaException as exc:\n LOG.warning(\"Cannot delete source volume %(volume)s on \"\n \"NexentaStor Appliance: %(exc)s\",\n {'volume': volume['name'], 'exc': exc})\n\n dst_nms = self._get_nms_for_url(capabilities['nms_url'])\n dst_snapshot = '%s/%s@%s' % (dst_volume.split('volumes/')[1],\n volume['name'], snapshot['name'])\n try:\n dst_nms.snapshot.destroy(dst_snapshot, '')\n except utils.NexentaException as exc:\n LOG.warning(\"Cannot delete temporary destination snapshot \"\n \"%(dst)s on NexentaStor Appliance: %(exc)s\",\n {'dst': dst_snapshot, 'exc': exc})\n return True, {'provider_location': share}","def create_volume_from_snapshot(self, volume, snapshot):\n\n free_size = self._get_spdk_lvs_free_space(\n self._get_spdk_lvs_uuid(\n self._get_spdk_volume_name(snapshot.name)))\n\n if free_size < volume.size:\n raise exception.VolumeBackendAPIException(\n data=_('Not enough space to create snapshot with SPDK'))\n\n return self._create_volume(volume, snapshot)","def snapshot(self, name):\r\n return self.driver.create_volume_snapshot(volume=self, name=name)","def snapshot_volumes(self) -> bool:\n return pulumi.get(self, \"snapshot_volumes\")","def create_volume_from_snapshot(self, volume, snapshot):\n self._ensure_shares_mounted()\n\n snapshot_vol = self._get_snapshot_volume(snapshot)\n nfs_share = snapshot_vol['provider_location']\n volume['provider_location'] = nfs_share\n nms = self.share2nms[nfs_share]\n\n vol, dataset = self._get_share_datasets(nfs_share)\n snapshot_name = '%s/%s/%s@%s' % (vol, dataset, snapshot['volume_name'],\n snapshot['name'])\n folder = '%s/%s' % (dataset, volume['name'])\n nms.folder.clone(snapshot_name, '%s/%s' % (vol, folder))\n\n try:\n self._share_folder(nms, vol, folder)\n except utils.NexentaException:\n try:\n nms.folder.destroy('%s/%s' % (vol, folder), '')\n except utils.NexentaException:\n LOG.warning(\"Cannot destroy cloned folder: \"\n \"%(vol)s/%(folder)s\",\n {'vol': vol, 'folder': folder})\n raise\n\n if self._get_nfs_server_version(nfs_share) < 4:\n sub_share, mnt_path = self._get_subshare_mount_point(nfs_share,\n volume)\n self._ensure_share_mounted(sub_share, mnt_path)\n\n if (('size' in volume) and (\n volume['size'] > snapshot['volume_size'])):\n self.extend_volume(volume, volume['size'])\n\n return {'provider_location': volume['provider_location']}","def test_volume_snapshot_create_get_list_delete(self):\n volume = self.create_volume()\n self.addCleanup(self.delete_volume, volume['id'])\n\n s_name = data_utils.rand_name(self.__class__.__name__ + '-Snapshot')\n # Create snapshot\n snapshot = self.snapshots_client.create_snapshot(\n volume_id=volume['id'],\n display_name=s_name)['snapshot']\n\n def delete_snapshot(snapshot_id):\n waiters.wait_for_volume_resource_status(self.snapshots_client,\n snapshot_id,\n 'available')\n # Delete snapshot\n self.snapshots_client.delete_snapshot(snapshot_id)\n self.snapshots_client.wait_for_resource_deletion(snapshot_id)\n\n self.addCleanup(delete_snapshot, snapshot['id'])\n self.assertEqual(volume['id'], snapshot['volumeId'])\n # Get snapshot\n fetched_snapshot = self.snapshots_client.show_snapshot(\n snapshot['id'])['snapshot']\n self.assertEqual(s_name, fetched_snapshot['displayName'])\n self.assertEqual(volume['id'], fetched_snapshot['volumeId'])\n # Fetch all snapshots\n snapshots = self.snapshots_client.list_snapshots()['snapshots']\n self.assertIn(snapshot['id'], map(lambda x: x['id'], snapshots))","def test_create_snapshot(self, mock_ghn):\n # Now snapshot the volume and check commands\n snapshot = {'volume_name': 'volume10',\n 'volume_id': 'xxx', 'display_name': 'snap10',\n 'name': '123abc', 'volume_size': 10, 'id': '123abc',\n 'volume': {'provider_id': 'space10'}}\n ret = self.driver.create_snapshot(snapshot)\n # We must copy entier underlying storage, ~12GB, not just 10GB\n self.assertEqual(11444 * units.Mi, self.dd_count)\n self.assertEqual('1M', self.bs)\n # Check space-create command\n expected = {'redundancy': '0', 'group': 'xanadu',\n 'name': snapshot['display_name'], 'mode': '0777',\n 'user': 'kane', 'net': 'net1',\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\n 'size': '12'}\n self.assertDictMatch(expected, self.created)\n # Check the returned provider\n expected_pid = {'provider_id': 'snap10'}\n self.assertDictMatch(expected_pid, ret)","def test_clone_delete_snap(self):\n\n # pylint: disable=too-many-statements, too-many-locals\n # Enabling Volume options on the volume and validating\n g.log.info(\"Enabling volume options for volume %s \", self.volname)\n options = {\" features.uss\": \"enable\"}\n ret = set_volume_options(self.mnode, self.volname, options)\n self.assertTrue(ret, (\"Failed to set volume options for volume %s\"\n % self.volname))\n g.log.info(\"Successfully set volume options\"\n \"for volume %s\", self.volname)\n\n # Validate feature.uss enabled or not\n g.log.info(\"Validating feature.uss is enabled\")\n option = \"features.uss\"\n vol_option = get_volume_options(self.mnode, self.volname, option)\n self.assertEqual(vol_option['features.uss'], 'enable', \"Failed\"\n \" to validate \"\n \"volume options\")\n g.log.info(\"Successfully validated volume options\"\n \"for volume %s\", self.volname)\n\n # Creating snapshot\n g.log.info(\"Starting to Create snapshot\")\n for snap_count in range(0, 2):\n ret, _, _ = snap_create(self.mnode, self.volname,\n \"snap%s\" % snap_count)\n self.assertEqual(ret, 0, (\"Failed to create snapshot for volume %s\"\n % self.volname))\n g.log.info(\"Snapshot snap%s created successfully\"\n \"for volume %s\", snap_count, self.volname)\n\n # Activating snapshot\n g.log.info(\"Starting to Activate Snapshot\")\n for snap_count in range(0, 2):\n ret, _, _ = snap_activate(self.mnode, \"snap%s\" % snap_count)\n self.assertEqual(ret, 0, (\"Failed to Activate snapshot snap%s\"\n % snap_count))\n g.log.info(\"Snapshot snap%s activated successfully\", snap_count)\n\n # Reset volume:\n g.log.info(\"Starting to Reset Volume\")\n ret, _, _ = volume_reset(self.mnode, self.volname, force=False)\n self.assertEqual(ret, 0, (\"Failed to reset volume %s\" % self.volname))\n g.log.info(\"Reset Volume on volume %s is Successful\", self.volname)\n\n # Validate feature.uss enabled or not\n g.log.info(\"Validating feature.uss is enabled\")\n option = \"features.uss\"\n vol_option = get_volume_options(self.mnode, self.volname, option)\n self.assertEqual(vol_option['features.uss'], 'off', \"Failed\"\n \" to validate \"\n \"volume options\")\n g.log.info(\"Successfully validated volume options\"\n \"for volume %s\", self.volname)\n\n # Verify volume's all process are online\n g.log.info(\"Starting to Verify volume's all process are online\")\n ret = verify_all_process_of_volume_are_online(self.mnode, self.volname)\n self.assertTrue(ret, (\"Volume %s : All process are\"\n \"not online\" % self.volname))\n g.log.info(\"Volume %s : All process are online\", self.volname)\n\n # Creating and starting a Clone of snapshot\n g.log.info(\"Starting to Clone Snapshot\")\n for clone_count in range(0, 2):\n ret, _, _ = snap_clone(self.mnode, \"snap%s\" % clone_count,\n \"clone%s\" % clone_count)\n self.assertEqual(ret, 0, (\"Failed to clone clone%s volume\"\n % clone_count))\n g.log.info(\"clone%s volume created successfully\", clone_count)\n\n # Start Cloned volume\n g.log.info(\"starting to Validate clone volumes are started\")\n for clone_count in range(0, 2):\n ret, _, _ = volume_start(self.mnode, \"clone%s\" % clone_count)\n self.assertEqual(ret, 0, (\"Failed to start clone%s\"\n % clone_count))\n g.log.info(\"clone%s started successfully\", clone_count)\n g.log.info(\"All the clone volumes are started Successfully\")\n\n # Validate Volume start of cloned volume\n g.log.info(\"Starting to Validate Volume start\")\n for clone_count in range(0, 2):\n vol_info = get_volume_info(self.mnode, \"clone%s\" % clone_count)\n if vol_info[\"clone%s\" % clone_count]['statusStr'] != 'Started':\n raise ExecutionError(\"Failed to get volume info for clone%s\"\n % clone_count)\n g.log.info(\"Volume clone%s is in Started state\", clone_count)\n\n # Validate feature.uss enabled or not\n g.log.info(\"Validating feature.uss is enabled\")\n option = \"features.uss\"\n for clone_count in range(0, 2):\n vol_option = get_volume_options(self.mnode, \"clone%s\"\n % clone_count, option)\n self.assertEqual(vol_option['features.uss'], 'enable', \"Failed\"\n \" to validate\"\n \"volume options\")\n g.log.info(\"Successfully validated volume options\"\n \"for volume clone%s\", clone_count)\n\n # Mount both the cloned volumes\n g.log.info(\"Mounting Cloned Volumes\")\n for mount_obj in range(0, 2):\n self.mpoint = \"/mnt/clone%s\" % mount_obj\n cmd = \"mkdir -p %s\" % self.mpoint\n ret, _, _ = g.run(self.clients[0], cmd)\n self.assertEqual(ret, 0, (\"Creation of directory %s\"\n \"for mounting\"\n \"volume %s failed: Directory already\"\n \"present\"\n % (self.mpoint, \"clone%s\" % mount_obj)))\n g.log.info(\"Creation of directory %s for mounting volume %s \"\n \"success\", self.mpoint, (\"clone%s\" % mount_obj))\n ret, _, _ = mount_volume(\"clone%s\" % mount_obj, self.mount_type,\n self.mpoint, self.mnode, self.clients[0])\n self.assertEqual(ret, 0, (\"clone%s is not mounted\"\n % mount_obj))\n g.log.info(\"clone%s is mounted Successfully\", mount_obj)\n\n # Perform I/O on mount\n # Start I/O on all mounts\n g.log.info(\"Starting to Perform I/O on Mountpoint\")\n all_mounts_procs = []\n for mount_obj in range(0, 2):\n cmd = (\"cd /mnt/clone%s/; for i in {1..10};\"\n \"do touch file$i; done; cd;\") % mount_obj\n proc = g.run(self.clients[0], cmd)\n all_mounts_procs.append(proc)\n g.log.info(\"I/O on mountpoint is successful\")\n\n # create snapshot\n g.log.info(\"Starting to Create snapshot of clone volume\")\n ret0, _, _ = snap_create(self.mnode, \"clone0\", \"snap2\")\n self.assertEqual(ret0, 0, \"Failed to create the snapshot\"\n \"snap2 from clone0\")\n g.log.info(\"Snapshots snap2 created successfully from clone0\")\n ret1, _, _ = snap_create(self.mnode, \"clone1\", \"snap3\")\n self.assertEqual(ret1, 0, \"Failed to create the snapshot snap3\"\n \"from clone1\")\n g.log.info(\"Snapshots snap3 created successfully from clone1\")\n\n # Listing all Snapshots present\n g.log.info(\"Starting to list all snapshots\")\n ret, _, _ = snap_list(self.mnode)\n self.assertEqual(ret, 0, (\"Failed to list snapshots present\"))\n g.log.info(\"Snapshots successfully listed\")","def _verify_cache_volume(self, context, img_meta,\n img_service, cachevol_props):\n lcfg = self.configuration\n cache_dir = '%s/' % lcfg.zfssa_cache_directory\n cache_vol_obj = Volume()\n cache_vol_obj.provider_location = self.mount_path + '/' + cache_dir\n cache_vol_obj._name_id = cachevol_props['id']\n cachevol_name = cache_dir + cache_vol_obj.name\n\n LOG.debug('Verifying cache volume %s:', cachevol_name)\n\n try:\n cache_vol = self.zfssa.get_volume(cachevol_name)\n except exception.VolumeNotFound:\n # There is no existing cache volume, create one:\n LOG.debug('Cache volume not found. Creating one...')\n return self._create_cache_volume(context,\n img_meta,\n img_service,\n cachevol_props)\n\n # A cache volume does exist, check if it's updated:\n if ((cache_vol['updated_at'] != cachevol_props['updated_at']) or\n (cache_vol['image_id'] != cachevol_props['image_id'])):\n if cache_vol['numclones'] > 0:\n # The cache volume is updated, but has clones\n exception_msg = (_('Cannot delete '\n 'cache volume: %(cachevol_name)s. '\n 'It was updated at %(updated_at)s '\n 'and currently has %(numclones)d '\n 'volume instances.'),\n {'cachevol_name': cachevol_name,\n 'updated_at': cachevol_props['updated_at'],\n 'numclones': cache_vol['numclones']})\n LOG.error(exception_msg)\n raise exception.VolumeBackendAPIException(data=exception_msg)\n\n # The cache volume is updated, but has no clone, so we delete it\n # and re-create a new one:\n super(ZFSSANFSDriver, self).delete_volume(cache_vol_obj)\n return self._create_cache_volume(context,\n img_meta,\n img_service,\n cachevol_props)\n\n return cachevol_name","def snapshot(self, snapshot, keep=0):\n if keep:\n until = util.today() + datetime.timedelta(days=keep)\n snapshot = snapshot + \"-keep-until-\" + until.strftime(\"%Y%m%d\")\n if snapshot in [x.snapname for x in self.ceph.root.snapshots]:\n self.log.info(\"snapshot-exists\", snapshot=snapshot)\n return\n self.log.info(\"snapshot-create\", name=snapshot)\n with self.frozen_vm() as frozen:\n if frozen:\n self.ceph.root.snapshots.create(snapshot)\n else:\n self.log.error(\"snapshot-ignore\", reason=\"not frozen\")\n raise RuntimeError(\"VM not frozen, not making snapshot.\")","def test_view_volume(self, volume, volumes_steps):\n volumes_steps.view_volume(volume.name)","def get_volume_snapshots(self, volume):\n LOG.debug('get_volume_snapshot starts')\n pool_name = self.configuration.rbd_pool\n volume_name = 'volume-%s' % encodeutils.safe_encode(volume[\"id\"])\n snaps_on_vol = self._get_volume_snapshots(pool_name, volume_name)\n snapshots = list()\n if snaps_on_vol is not None:\n for snap in snaps_on_vol:\n snap_name = str(snap[\"name\"])\n item = dict()\n if snap_name.startswith(\"snapshot-\"):\n # snapshot directly created on volume.\n item[\"type\"] = \"volume_snap\"\n item[\"uuid\"] = snap_name[len('snapshot-'):]\n elif snap_name.startswith(\"volume-\") and \\\n snap_name.endswith(\".clone_snap\"):\n # snapshot used for create volume on volume.\n item[\"type\"] = \"clone_snap\"\n item[\"uuid\"] = snap_name[len(\"volume-\"):-len(\".clone_snap\")]\n elif snap_name.startswith(\"backup.\") and \".snap.\" in snap_name:\n # snapshot used for backup volume.\n item[\"type\"] = \"backup_snap\"\n item[\"uuid\"] = \\\n snap_name[len(\"backup.\"):snap_name.index(\".snap.\")]\n else:\n item[\"type\"] = \"\"\n item[\"uuid\"] = \"\"\n snapshots.append(item)\n\n LOG.debug('volume snapshots: %s', snapshots)\n LOG.debug('get_volume_snapshots finished.')\n return snapshots","def test_migrate_volume(self, volume, volumes_steps):\n old_host, _ = volumes_steps.migrate_volume(volume.name)\n volumes_steps.migrate_volume(volume.name, old_host)","def _assert_source_detached(self, volume):\n if (volume['status'] != \"available\" or\n volume['attach_status'] == fields.VolumeAttachStatus.ATTACHED):\n LOG.error(\"Volume must be detached for clone operation.\")\n raise exception.VolumeAttached(volume_id=volume['id'])","def migrate_volume(self, volume, host):\n false_ret = (False, None)\n if volume['attach_status'] == fields.VolumeAttachStatus.ATTACHED:\n return false_ret\n if 'location_info' not in host['capabilities']:\n return false_ret\n info = host['capabilities']['location_info']\n try:\n (dest_type, dest_id,\n dest_back_name, dest_owner) = info.split(':')\n except ValueError:\n return false_ret\n\n reqd_dest_type = '%sVolumeDriver' % self.vendor_name\n if not (dest_type == reqd_dest_type and\n dest_id == self.serialNumber and\n dest_owner == self.owner):\n return false_ret\n if volume['name_id']:\n source_name = self._get_vol_name(volume['name_id'])\n else:\n source_name = self._get_vol_name(volume['id'])\n # the array does not support duplicate names\n dest_name = \"m%s\" % source_name[1:]\n\n self.client_login()\n try:\n self.client.copy_volume(source_name, dest_name,\n dest_back_name, self.backend_type)\n self.client.delete_volume(source_name)\n self.client.modify_volume_name(dest_name, source_name)\n return (True, None)\n except stx_exception.RequestError as ex:\n LOG.exception(\"Error migrating volume: %s\", source_name)\n raise exception.Invalid(ex)\n finally:\n self.client_logout()","def snapshot_volumes(self) -> pulumi.Input[bool]:\n return pulumi.get(self, \"snapshot_volumes\")","def test_backup_can_use_snapshots(self):\n use_snaps = self.driver.backup_use_temp_snapshot()\n self.assertTrue(use_snaps)","def show_volume_snapshot(self, snapshot, check=True):\n cmd = 'cinder snapshot-show ' + snapshot.id\n\n exit_code, stdout, stderr = self.execute_command(\n cmd, timeout=config.SNAPSHOT_SHOW_TIMEOUT, check=check)\n\n snapshot_table = output_parser.table(stdout)\n show_result = {key: value for key, value in snapshot_table['values']}\n\n if check:\n assert_that(show_result['id'], is_(snapshot.id))\n if snapshot.name:\n assert_that(show_result['name'], is_(snapshot.name))\n if snapshot.description:\n assert_that(show_result['description'],\n is_(snapshot.description))","def create(self, filesystem=None):\n if not self.size and not self.from_snapshot_id and not self.from_archive:\n log.error('Cannot add a {0} volume without a size, snapshot ID or '\n 'archive url; aborting.'.format(self.fs))\n return False\n # If creating the volume from a snaphost, get the expected volume size\n if self.from_snapshot_id and not self.volume:\n self.snapshot = self.app.cloud_interface.get_snapshot(self.from_snapshot_id)\n if not self.snapshot:\n log.error(\"Did not retrieve Snapshot object for {0}; aborting.\"\n .format(self.from_snapshot_id))\n return False\n # We need a size to be able to create a volume, so if none\n # is specified, use snapshot size\n if not self.size:\n si = self.app.cloud_interface.get_snapshot_info(self.from_snapshot_id)\n self.size = si.get('volume_size')\n # If it does not already exist, create the volume\n if self.status == volume_status.NONE:\n log.debug(\"Creating a new volume of size '%s' in zone '%s' from \"\n \"snapshot '%s' for %s.\"\n % (self.size, self.app.cloud_interface.get_zone(),\n self.from_snapshot_id, self.fs))\n self.volume = self.app.cloud_interface.create_volume(\n self.size,\n self.app.cloud_interface.get_zone(),\n snapshot=self.from_snapshot_id)\n if self.volume:\n # When creating from a snapshot in Euca, volume.size may be None\n self.size = int(self.volume.size or 0)\n log.debug(\"Created a new volume of size '%s' from snapshot '%s' \"\n \"with ID '%s' in zone '%s' for %s.\"\n % (self.size, self.from_snapshot_id, self.volume_id,\n self.app.cloud_interface.get_zone(), self.fs))\n else:\n log.warning(\"No volume object - did not create a volume?\")\n return False\n else:\n log.debug(\"Tried to create a volume for %s but it is in state '%s' \"\n \"(volume ID: %s)\" % (self.fs, self.status, self.volume_id))\n return False\n # Add tags to newly created volumes (do this outside the inital if/else\n # to ensure the tags get assigned even if using an existing volume vs.\n # creating a new one)\n self.app.cloud_interface.add_tag(\n self.volume, 'Name', self.app.config['cluster_name'])\n self.app.cloud_interface.add_tag(\n self.volume, 'bucketName', self.app.config['bucket_cluster'])\n if self.fs:\n self.app.cloud_interface.add_tag(\n self.volume, 'filesystem', self.fs.get_full_name())\n self.app.cloud_interface.add_tag(\n self.volume, 'roles', ServiceRole.to_string(self.fs.svc_roles))\n return True","def test_delete_snapshot(self):\n ctxt = context.get_admin_context()\n extra_specs = {}\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\n snapshot = {'id': '1', 'name': 'volume1',\n 'display_name': '',\n 'volume_type_id': type_ref['id'],\n 'size': 10,\n 'provider_id': 'snap10'}\n self.driver.delete_snapshot(snapshot)\n expected = {'name': 'snap10'}\n self.assertDictMatch(expected, self.deleted)","def assert_valid_volume(wells,exception_info='invalid volume'):\n wells = ensure_list(wells)\n \n assert all([well.volume >= get_well_dead_volume(well) for well in wells]), exception_info\n assert all([well.volume <= get_well_max_volume(well) for well in wells]), exception_info","def create_snapshot(self, volume_id, notes='No longer needed'):\r\n\r\n self.iscsi_svc.createSnapshot(notes, id=volume_id)","def test_snapshot(self):\n # Try to create a snapshot with a wrong machine_uuid.\n status = self.proxy.snapshot.create(\n PROVIDER_ID, \"Doesn't exist\"\n )\n self.check_xmlrpc_command_result(status, has_error=True)\n\n # Try to create a snapshot with a wrong provider.\n status = self.proxy.snapshot.create(\n \"Doesn't exist\", self.machine_uuid\n )\n self.check_xmlrpc_command_result(status, has_error=True)\n\n # Create a snapshot.\n status = self.proxy.snapshot.create(\n PROVIDER_ID, self.machine_uuid\n )\n self.check_xmlrpc_command_result(status)\n\n # Try to destroy snapshots with a wrong provider.\n status = self.proxy.snapshot.destroy(\n \"Doesn't exist\", self.machine_uuid\n )\n self.check_xmlrpc_command_result(status, has_error=True)\n\n # Destroy snapshots.\n status = self.proxy.snapshot.destroy(\n PROVIDER_ID, self.machine_uuid\n )\n self.check_xmlrpc_command_result(status)","def test_retype_setup_fail_volume_is_available(self, mock_notify):\n elevated = context.get_admin_context()\n project_id = self.context.project_id\n\n db.volume_type_create(elevated, {'name': 'old', 'extra_specs': {}})\n old_vol_type = db.volume_type_get_by_name(elevated, 'old')\n db.volume_type_create(elevated, {'name': 'new', 'extra_specs': {}})\n new_vol_type = db.volume_type_get_by_name(elevated, 'new')\n db.quota_create(elevated, project_id, 'volumes_new', 0)\n\n volume = tests_utils.create_volume(self.context, size=1,\n host=CONF.host, status='available',\n volume_type_id=old_vol_type['id'])\n\n api = cinder.volume.api.API()\n self.assertRaises(exception.VolumeLimitExceeded, api.retype,\n self.context, volume, new_vol_type['id'])\n\n volume = db.volume_get(elevated, volume.id)\n # FIXME: restore when Bug #1803648 is figured out\n # mock_notify.assert_not_called()\n self.assertEqual('available', volume['status'])","def test_live_migration_src_check_volume_node_not_alive(self):\n\n instance_id = self._create_instance()\n i_ref = db.instance_get(self.context, instance_id)\n dic = {'instance_id': instance_id, 'size': 1}\n v_ref = db.volume_create(self.context, {'instance_id': instance_id,\n 'size': 1})\n t1 = utils.utcnow() - datetime.timedelta(1)\n dic = {'created_at': t1, 'updated_at': t1, 'binary': 'nova-volume',\n 'topic': 'volume', 'report_count': 0}\n s_ref = db.service_create(self.context, dic)\n\n self.assertRaises(exception.VolumeServiceUnavailable,\n self.scheduler.driver.schedule_live_migration,\n self.context, instance_id, i_ref['host'])\n\n db.instance_destroy(self.context, instance_id)\n db.service_destroy(self.context, s_ref['id'])\n db.volume_destroy(self.context, v_ref['id'])","def test_least_busy_host_gets_volume(self):\n volume1 = self.start_service('volume', host='host1')\n volume2 = self.start_service('volume', host='host2')\n volume_id1 = self._create_volume()\n volume1.create_volume(self.context, volume_id1)\n volume_id2 = self._create_volume()\n host = self.scheduler.driver.schedule_create_volume(self.context,\n volume_id2)\n self.assertEqual(host, 'host2')\n volume1.delete_volume(self.context, volume_id1)\n db.volume_destroy(self.context, volume_id2)\n volume1.kill()\n volume2.kill()","def test_attachment_create_volume_in_error_state(self):\n volume_params = {'status': 'available'}\n\n vref = tests_utils.create_volume(self.context, **volume_params)\n vref.status = \"error\"\n self.assertRaises(exception.InvalidVolume,\n self.volume_api.attachment_create,\n self.context,\n vref,\n fake.UUID2)","def create_snapshot(args, **_):\n\n volume_id = \\\n utils.get_external_resource_id_or_raise(\n 'create snapshot', ctx.instance)\n\n ctx.logger.info(\n 'Trying to create a snapshot of EBS volume {0}.'\n .format(volume_id))\n\n volume_object = _get_volumes_from_id(volume_id)\n\n if not args:\n snapshot_desc = \\\n unicode(datetime.datetime.now()) + \\\n ctx.instance.runtime_properties[constants.EXTERNAL_RESOURCE_ID]\n args = dict(description=snapshot_desc)\n\n try:\n new_snapshot = volume_object.create_snapshot(**args)\n except (boto.exception.EC2ResponseError,\n boto.exception.BotoServerError) as e:\n raise NonRecoverableError('{0}'.format(str(e)))\n\n ctx.logger.info(\n 'Created snapshot of EBS volume {0}.'.format(volume_id))\n\n if constants.VOLUME_SNAPSHOT_ATTRIBUTE not in \\\n ctx.instance.runtime_properties:\n ctx.instance.runtime_properties[\n constants.VOLUME_SNAPSHOT_ATTRIBUTE] = list()\n\n ctx.instance.runtime_properties[\n constants.VOLUME_SNAPSHOT_ATTRIBUTE].append(new_snapshot.id)","def ensure_volume_exists( user_email, opencloud_volume, user=None ):\n client = connect_syndicate()\n\n try:\n volume = client.read_volume( opencloud_volume.name )\n except Exception, e:\n # transport error \n logger.exception(e)\n raise e\n\n if volume is None:\n # the volume does not exist....try to create it \n vol_name = opencloud_volume.name\n vol_blocksize = opencloud_volume.blocksize\n vol_description = opencloud_volume.description\n vol_private = opencloud_volume.private\n vol_archive = opencloud_volume.archive \n vol_default_gateway_caps = opencloud_caps_to_syndicate_caps( opencloud_volume.cap_read_data, opencloud_volume.cap_write_data, opencloud_volume.cap_host_data )\n\n try:\n vol_info = client.create_volume( user_email, vol_name, vol_description, vol_blocksize,\n private=vol_private,\n archive=vol_archive,\n active=True,\n default_gateway_caps=vol_default_gateway_caps,\n store_private_key=False,\n metadata_private_key=\"MAKE_METADATA_KEY\" )\n\n except Exception, e:\n # transport error\n logger.exception(e)\n raise e\n\n else:\n # successfully created the volume!\n return vol_info\n\n else:\n \n # volume already exists. Verify its owned by this user.\n if user is None:\n try:\n user = client.read_user( volume['owner_id'] )\n except Exception, e:\n # transport error, or user doesn't exist (either is unacceptable)\n logger.exception(e)\n raise e\n\n if user is None or user['email'] != user_email:\n raise Exception(\"Volume '%s' already exists, but is NOT owned by '%s'\" % (opencloud_volume.name, user_email) )\n\n # we're good!\n return None","def resource_type(self):\n return 'volume-snapshot'","def test_aws_service_api_volume_get(self):\n pass","def test_snapshot_compatibility(microvm_factory, guest_kernel, rootfs):\n vm = microvm_factory.build(guest_kernel, rootfs)\n vm.spawn()\n vm.basic_config(\n vcpu_count=2,\n mem_size_mib=256,\n )\n\n # Add a memory balloon with stats enabled.\n vm.api.balloon.put(amount_mib=0, deflate_on_oom=True, stats_polling_interval_s=1)\n\n vm.start()\n vm.snapshot_full()","def snap_status(mnode, snapname=\"\", volname=\"\"):\n\n if snapname != \"\" and volname != \"\":\n g.log.error(\"Incorrect cmd. snap status cli accepts either \"\n \"snapname or volname\")\n return (-1, None, None)\n\n if volname != '':\n volname = \"volume %s\" % volname\n\n cmd = \"gluster snapshot status %s %s\" % (snapname, volname)\n return g.run(mnode, cmd)","def test_present_wo_existing_volumes():\n docker_create_volume = Mock(return_value=\"created\")\n docker_remove_volume = Mock(return_value=\"removed\")\n __salt__ = {\n \"docker.create_volume\": docker_create_volume,\n \"docker.remove_volume\": docker_remove_volume,\n \"docker.volumes\": Mock(return_value={\"Volumes\": None}),\n }\n with patch.dict(docker_state.__dict__, {\"__salt__\": __salt__}):\n ret = docker_state.present(\n \"volume_foo\",\n driver=\"bar\",\n force=True,\n )\n docker_create_volume.assert_called_with(\n \"volume_foo\", driver=\"bar\", driver_opts=None\n )\n assert ret == {\n \"name\": \"volume_foo\",\n \"comment\": \"\",\n \"changes\": {\"created\": \"created\"},\n \"result\": True,\n }","def _wait_until_volume_available(self, volume, maybe_in_use=False):\n ok_states = [\"creating\"] # it's ok to wait if the volume is in this\n tries = 0\n if maybe_in_use:\n ok_states.append(\"in_use\")\n logger.info(\"Volume: %s is in state: %s\", volume.name, volume.state)\n while volume.state in ok_states:\n sleep(3)\n volume = self.get_volume(volume.name)\n tries = tries + 1\n if tries > 10:\n logger.info(\"Maximum amount of tries reached..\")\n break\n if volume.state == \"notfound\":\n logger.error(\"no volume was found for: %s\", volume.name)\n break\n logger.info(\" ... %s\", volume.state)\n if volume.state != \"available\":\n # OVH uses a non-standard state of 3 to indicate an available\n # volume\n logger.info(\"Volume %s is %s (not available)\", volume.name, volume.state)\n logger.info(\n \"The volume %s is not available, but will continue anyway...\",\n volume.name,\n )\n return True","def create_snapshot(volume_name, volume_id):\n\tif cliargs.verbose:\n\t\tprint \"Will snapshot '%s' and tag it with '%s'\" % (volume_id, volume_name)\n\n\tresponse = ec2.create_snapshot(VolumeId=volume_id, Description=volume_name)\n\tif response:\n\t\tec2.create_tags(Resources=[response[\"SnapshotId\"]], Tags=[{\"Key\": \"Name\", \"Value\": volume_name}])","def test_aws_service_api_volume_patch(self):\n pass","def _create_snapshot(connection, volume, name=''):\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", \"creating new snapshot\", {\"volume\": volume.id}))\n snapshot = volume.create_snapshot(\n description=\"automatic snapshot by ebs-snapshots\")\n if not name:\n name = '{}-snapshot'.format(volume.id)\n connection.create_tags(\n [snapshot.id], dict(Name=name, creator='ebs-snapshots'))\n logging.info(kayvee.formatLog(\"ebs-snapshots\", \"info\", \"created snapshot successfully\", {\n \"name\": name,\n \"volume\": volume.id,\n \"snapshot\": snapshot.id\n }))\n return snapshot","def issnapshot_available(self, item_name):\n return False","def get_snapshots(vol_name):\n\n l = None\n try:\n cmd = 'gluster snapshot info volume %s --xml' % vol_name\n d, err = xml_parse.run_gluster_command(cmd)\n if err:\n raise Exception(err)\n if d:\n if d[\"op_status\"][\"op_ret\"] == 0:\n l, err = xml_parse.get_snapshots(d[\"root\"])\n if err:\n raise Exception(err)\n except Exception, e:\n return None, 'Error getting volume snapshots: %s' % str(e)\n else:\n return l, None","def sync_volume_record( volume ):\n \n logger.info( \"Sync Volume = %s\\n\\n\" % volume.name )\n \n principal_id = volume.owner_id.email\n config = observer_core.get_config()\n \n max_UGs = None \n max_RGs = None\n volume_principal_id = observer_core.make_volume_principal_id( principal_id, volume.name )\n\n # get the observer secret \n try:\n max_UGs = CONFIG.SYNDICATE_UG_QUOTA \n max_RGs = CONFIG.SYNDICATE_RG_QUOTA\n observer_secret = observer_core.get_syndicate_observer_secret( config.SYNDICATE_OBSERVER_SECRET )\n except Exception, e:\n traceback.print_exc()\n logger.error(\"config is missing SYNDICATE_OBSERVER_SECRET, SYNDICATE_UG_QUOTA, SYNDICATE_RG_QUOTA\")\n raise e\n \n # volume owner must exist as a Syndicate user...\n try:\n rc, user = observer_core.ensure_principal_exists( volume_principal_id, observer_secret, is_admin=False, max_UGs=max_UGs, max_RGs=max_RGs)\n assert rc == True, \"Failed to create or read volume principal '%s'\" % volume_principal_id\n except Exception, e:\n traceback.print_exc()\n logger.error(\"Failed to ensure principal '%s' exists\" % volume_principal_id )\n raise e\n\n # volume must exist \n # create or update the Volume\n try:\n new_volume = observer_core.ensure_volume_exists( volume_principal_id, volume, user=user )\n except Exception, e:\n traceback.print_exc()\n logger.error(\"Failed to ensure volume '%s' exists\" % volume.name )\n raise e\n \n # did we create the Volume?\n if new_volume is not None:\n # we're good\n pass \n \n # otherwise, just update it \n else:\n try:\n rc = observer_core.update_volume( volume )\n except Exception, e:\n traceback.print_exc()\n logger.error(\"Failed to update volume '%s', exception = %s\" % (volume.name, e.message))\n raise e\n \n return True","def _tag_volume():\n if dry:\n print('Would tag the new volume.')\n return True\n\n while True:\n # waiting for the volume to be up to tag it\n i = _fetch('vm')\n v = [x for x in i.volumes.all()]\n if len(v) == 0:\n # volumes should actually be already there once the IP is up\n time.sleep(1)\n else:\n for x in v:\n print('Tagging volume ' + x.id + '.')\n _tag_resource(x)\n break","def test_least_busy_host_gets_volume_no_queue(self):\n volume1 = service.Service('host1',\n 'nova-volume',\n 'volume',\n FLAGS.volume_manager)\n volume1.start()\n volume2 = service.Service('host2',\n 'nova-volume',\n 'volume',\n FLAGS.volume_manager)\n volume2.start()\n volume_id1 = self._create_volume()\n volume1.create_volume(self.context, volume_id1)\n volume_id2 = self._create_volume()\n host = self.scheduler.driver.schedule_create_volume(self.context,\n volume_id2)\n self.assertEqual(host, 'host2')\n volume1.delete_volume(self.context, volume_id1)\n db.volume_destroy(self.context, volume_id2)","def test_create_volume(self, mock_ghn):\n ctxt = context.get_admin_context()\n extra_specs = {}\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\n volume = {'id': '1', 'name': 'volume1',\n 'display_name': '',\n 'volume_type_id': type_ref['id'],\n 'size': 10}\n ret = self.driver.create_volume(volume)\n expected = {'redundancy': '0', 'group': 'xanadu',\n 'name': 'volume10', 'mode': '0777',\n 'user': 'kane', 'net': 'net1',\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\n 'size': '12'}\n self.assertDictMatch(expected, self.created)\n # Check the returned provider, note that provider_id is hashed\n expected_pid = {'provider_id': 'volume10'}\n self.assertDictMatch(expected_pid, ret)","def test_volume():\n structure = Material(input)\n assert (structure.volume == 90.725624999999965)","def create_volume(self, snapshot_id = \"\", size = -1):\n response = volume.create_volume(self.url, self.verb,\n self.headers, self.version,\n snapshot_id, size)\n if response is not None :\n res = CreateVolumeResponse.CreateVolumeResponse()\n parseString(str(response.text), res)\n return res\n else :\n return None","def test_csi_volumesnapshot_basic(set_random_backupstore, # NOQA\n volumesnapshotclass, # NOQA\n volumesnapshot, # NOQA\n client, # NOQA\n core_api, # NOQA\n volume_name, # NOQA\n csi_pv, # NOQA\n pvc, # NOQA\n pod_make, # NOQA\n volsnapshotclass_delete_policy, # NOQA\n backup_is_deleted): # NOQA\n\n csisnapclass = \\\n volumesnapshotclass(name=\"snapshotclass\",\n deletepolicy=volsnapshotclass_delete_policy)\n\n pod_name, pv_name, pvc_name, md5sum = \\\n prepare_pod_with_data_in_mb(client, core_api,\n csi_pv, pvc, pod_make,\n volume_name,\n data_path=\"/data/test\")\n\n # Create volumeSnapshot test\n csivolsnap = volumesnapshot(volume_name + \"-volumesnapshot\",\n \"default\",\n csisnapclass[\"metadata\"][\"name\"],\n \"persistentVolumeClaimName\",\n pvc_name)\n\n volume = client.by_id_volume(volume_name)\n\n for i in range(RETRY_COUNTS):\n snapshots = volume.snapshotList()\n if len(snapshots) == 2:\n break\n time.sleep(RETRY_INTERVAL)\n\n lh_snapshot = None\n snapshots = volume.snapshotList()\n for snapshot in snapshots:\n if snapshot[\"name\"] == \"snapshot-\" + csivolsnap[\"metadata\"][\"uid\"]:\n lh_snapshot = snapshot\n assert lh_snapshot is not None\n\n wait_for_volumesnapshot_ready(csivolsnap[\"metadata\"][\"name\"],\n csivolsnap[\"metadata\"][\"namespace\"])\n\n bv1, b = find_backup(client, volume_name, lh_snapshot[\"name\"])\n\n assert b[\"snapshotName\"] == lh_snapshot[\"name\"]\n\n restore_pvc_name = pvc[\"metadata\"][\"name\"] + \"-restore\"\n restore_pvc_size = pvc[\"spec\"][\"resources\"][\"requests\"][\"storage\"]\n\n restore_csi_volume_snapshot(core_api,\n client,\n csivolsnap,\n restore_pvc_name,\n restore_pvc_size)\n\n restore_pod = pod_make()\n restore_pod_name = restore_pod[\"metadata\"][\"name\"]\n restore_pod['spec']['volumes'] = [create_pvc_spec(restore_pvc_name)]\n\n create_and_wait_pod(core_api, restore_pod)\n restore_md5sum = \\\n get_pod_data_md5sum(core_api, restore_pod_name, path=\"/data/test\")\n assert restore_md5sum == md5sum\n\n # Delete volumeSnapshot test\n delete_volumesnapshot(csivolsnap[\"metadata\"][\"name\"], \"default\")\n\n if backup_is_deleted is False:\n find_backup(client, volume_name, b[\"snapshotName\"])\n else:\n wait_for_backup_delete(client, volume_name, b[\"name\"])","def database_volume_snapshot_delete(volume_snapshot_uuid):\n db = database_get()\n session = db.session()\n query = session.query(model.VolumeSnapshot)\n query.filter(model.VolumeSnapshot.uuid == volume_snapshot_uuid).delete()\n session.commit()","def ensure_export(self, context, volume):\n pass","def _is_booted_from_volume(self, instance, disk_mapping=None):\n return not bool(instance.get('image_ref'))","def create_snapshot(self, snapshot):\n vg_name = self.get_volume_group_name(snapshot.volume_id)\n snap_name = self.get_snap_name(snapshot.id)\n rpolicy = self.get_policy()\n try:\n LOG.debug(\"Searching volume_group: %s in K2.\", vg_name)\n vg = self.client.search(\"volume_groups\", name=vg_name).hits[0]\n LOG.debug(\"Creating a snapshot: %(snap)s from vg: %(vg)s\",\n {'snap': snap_name, 'vg': vg_name})\n self.client.new(\"snapshots\", short_name=snap_name,\n source=vg, retention_policy=rpolicy,\n is_auto_deleteable=False).save()\n except Exception as ex:\n LOG.exception(\"Creation of snapshot: %s failed.\", snap_name)\n raise KaminarioCinderDriverException(reason=ex)","def manage(self, volume_id, ref, name=None, description=None,\n metadata=None):\n body = {'snapshot': {'volume_id': volume_id,\n 'ref': ref,\n 'name': name,\n 'description': description,\n 'metadata': metadata\n }\n }\n return self._create('/os-snapshot-manage', body, 'snapshot')","def _create_snapshot(self, name=None, metadata=None):\n req = fakes.HTTPRequest.blank('/v3/snapshots')\n req.environ['cinder.context'] = self.ctx\n snap = {\"volume_id\": fake.VOLUME_ID,\n \"display_name\": name or \"Volume Test Name\",\n \"description\": \"Volume Test Desc\"\n }\n if metadata:\n snap[\"metadata\"] = metadata\n body = {\"snapshot\": snap}\n self.controller.create(req, body=body)","def test_attachment_update_volume_in_error_state(self):\n volume_params = {'status': 'available'}\n\n vref = tests_utils.create_volume(self.context, **volume_params)\n aref = self.volume_api.attachment_create(self.context,\n vref,\n fake.UUID2)\n self.assertEqual(fake.UUID2, aref.instance_uuid)\n self.assertIsNone(aref.attach_time)\n self.assertEqual('reserved', aref.attach_status)\n self.assertEqual(vref.id, aref.volume_id)\n self.assertEqual({}, aref.connection_info)\n vref.status = 'error'\n vref.save()\n connector = {'fake': 'connector',\n 'host': 'somehost'}\n self.assertRaises(exception.InvalidVolume,\n self.volume_api.attachment_update,\n self.context,\n aref,\n connector)","def create_snapshot(self, context, volume_id, snapshot_id):\n\n context = context.elevated()\n snapshot_ref = self.db.snapshot_get(context, snapshot_id)\n display_name = snapshot_ref['display_name']\n display_description = snapshot_ref['display_description']\n LOG.info(_(\"snapshot %s: creating\"), snapshot_ref['id'])\n\n self._notify_about_snapshot_usage(\n context, snapshot_ref, \"create.start\")\n\n vol_ref = self.db.volume_get(context, volume_id)\n LOG.info(_(\"Cascade info: create snapshot while cascade id is:%s\"),\n vol_ref['mapping_uuid'])\n\n try:\n vol_ref = self.db.volume_get(context, volume_id)\n casecaded_volume_id = vol_ref['mapping_uuid']\n cinderClient = self._get_cinder_cascaded_user_client(context)\n bodyResponse = cinderClient.volume_snapshots.create(\n volume_id=casecaded_volume_id,\n force=False,\n name=display_name,\n description=display_description)\n\n LOG.info(_(\"Cascade info: create snapshot while response is:%s\"),\n bodyResponse._info)\n if bodyResponse._info['status'] == 'creating':\n self._heal_snapshot_mapping_cache(snapshot_id,\n bodyResponse._info['id'],\n \"add\")\n self.db.snapshot_update(\n context,\n snapshot_ref['id'],\n {'mapping_uuid': bodyResponse._info['id']})\n\n except Exception:\n with excutils.save_and_reraise_exception():\n self.db.snapshot_update(context,\n snapshot_ref['id'],\n {'status': 'error'})\n return\n\n self.db.snapshot_update(context,\n snapshot_ref['id'], {'status': 'available',\n 'progress': '100%'})\n# vol_ref = self.db.volume_get(context, volume_id)\n\n if vol_ref.bootable:\n try:\n self.db.volume_glance_metadata_copy_to_snapshot(\n context, snapshot_ref['id'], volume_id)\n except exception.CinderException as ex:\n LOG.exception(_(\"Failed updating %(snapshot_id)s\"\n \" metadata using the provided volumes\"\n \" %(volume_id)s metadata\") %\n {'volume_id': volume_id,\n 'snapshot_id': snapshot_id})\n raise exception.MetadataCopyFailure(reason=ex)\n\n LOG.info(_(\"Cascade info: snapshot %s, created successfully\"),\n snapshot_ref['id'])\n self._notify_about_snapshot_usage(context, snapshot_ref, \"create.end\")\n\n return snapshot_id","def create_cloned_volume(self, volume, src_vref):\n # Form the snapshot structure.\n snapshot = {'id': uuid.uuid4().__str__(),\n 'volume_id': src_vref['id'],\n 'volume': src_vref}\n\n # Create snapshot.\n self.create_snapshot(snapshot)\n\n try:\n # Create volume from snapshot.\n lun_info = self.create_volume_from_snapshot(volume, snapshot)\n finally:\n try:\n # Delete snapshot.\n self.delete_snapshot(snapshot)\n except exception.VolumeBackendAPIException:\n LOG.warning(_LW(\n 'Failure deleting the snapshot %(snapshot_id)s '\n 'of volume %(volume_id)s.'),\n {'snapshot_id': snapshot['id'],\n 'volume_id': src_vref['id']},)\n\n return {'provider_location': lun_info['ID'],\n 'lun_info': lun_info}","def bootable_volume(volumes):\n for volume in volumes:\n if '/dev/vda' in volume['attachments']:\n return volume","def volume_exists(vil, vol_name):\n\n exists = False\n try:\n if not vil:\n vil, err = get_basic_volume_info_all()\n if err:\n raise Exception(err)\n if vil:\n for v in vil:\n if v[\"name\"] == vol_name:\n exists = True\n except Exception, e:\n return False, 'Error checking for volume existance : %s' % str(e)\n else:\n return exists, None","def create_snapshot(self, snap_description=None):\n log.debug(\"Initiating creation of a snapshot for volume '%s'\" % self.volume_id)\n try:\n snapshot = self.volume.create_snapshot(description=snap_description)\n log.info(\"Created snapshot {0} from volume {1} ({2}). Check the snapshot \"\n \"for status.\".format(snapshot.id, self.volume_id, self.fs))\n self._derived_snapshots.append(snapshot)\n # Add tags to the newly created snapshot\n self.app.cloud_interface.add_tag(snapshot, 'Name',\n self.app.config['cluster_name'])\n self.app.cloud_interface.add_tag(\n self.volume, 'bucketName', self.app.config['bucket_cluster'])\n self.app.cloud_interface.add_tag(self.volume, 'filesystem', self.fs.name)\n return str(snapshot.id)\n except EC2ResponseError as ex:\n log.error(\"Error creating a snapshot from volume '%s': %s\" %\n (self.volume_id, ex))\n return None","def create_snapshot(self, snapshot):\n LOG.info(_LI('Creating snapshot: %s'), snapshot['name'])\n lcfg = self.configuration\n snap_name = self._create_snapshot_name()\n self.zfssa.create_snapshot(lcfg.zfssa_nfs_pool, lcfg.zfssa_nfs_project,\n lcfg.zfssa_nfs_share, snap_name)\n\n src_file = snap_name + '/' + snapshot['volume_name']\n\n try:\n self.zfssa.create_snapshot_of_volume_file(src_file=src_file,\n dst_file=\n snapshot['name'])\n except Exception:\n with excutils.save_and_reraise_exception():\n LOG.debug('Error thrown during snapshot: %s creation',\n snapshot['name'])\n finally:\n self.zfssa.delete_snapshot(lcfg.zfssa_nfs_pool,\n lcfg.zfssa_nfs_project,\n lcfg.zfssa_nfs_share, snap_name)","def test_edit_volume(self, volume, volumes_steps):\n new_name = volume.name + ' (updated)'\n with volume.put(name=new_name):\n volumes_steps.edit_volume(volume_name=volume.name,\n new_volume_name=new_name)","def _create_volume(self):\n vol = {}\n vol['size'] = 1\n vol['availability_zone'] = 'test'\n return db.volume_create(self.context, vol)['id']","def ensure_volume_absent( volume_name ):\n\n client = connect_syndicate()\n\n # this is idempotent, and returns True even if the Volume doesn't exist\n return client.delete_volume( volume_name )","def find_recovery_on_volume(volume):\n return _find(volume, RECOVERY_ON_VOLUME_TABLE)","def __mount_ebs_volume( self ):\n ebs_volume_size = self.instance_tag( 'ebs_volume_size' ) or '0'\n ebs_volume_size = int( ebs_volume_size )\n if ebs_volume_size:\n instance_name = self.instance_tag( 'Name' )\n cluster_ordinal = int( self.instance_tag( 'cluster_ordinal' ) )\n volume_name = '%s__%d' % (instance_name, cluster_ordinal)\n volume = EC2VolumeHelper( ec2=self.ec2,\n availability_zone=self.availability_zone,\n name=volume_name,\n size=ebs_volume_size,\n volume_type=\"gp2\" )\n # TODO: handle case where volume is already attached\n device_ext = '/dev/sdf'\n device = '/dev/xvdf'\n volume.attach( self.instance_id, device_ext )\n\n # Wait for inode to appear and make sure its a block device\n while True:\n try:\n assert stat.S_ISBLK( os.stat( device ).st_mode )\n break\n except OSError as e:\n if e.errno == errno.ENOENT:\n time.sleep( 1 )\n else:\n raise\n\n # Only format empty volumes\n volume_label = volume_label_hash( volume_name )\n if check_output( [ 'file', '-sL', device ] ).strip( ) == device + ': data':\n check_call( [ 'mkfs', '-t', 'ext4', device ] )\n check_call( [ 'e2label', device, volume_label ] )\n else:\n # If the volume is not empty, verify the file system label\n actual_label = check_output( [ 'e2label', device ] ).strip( )\n if actual_label != volume_label:\n raise AssertionError(\n \"Expected volume label '%s' (derived from '%s') but got '%s'\" %\n (volume_label, volume_name, actual_label) )\n current_mount_point = self.__mount_point( device )\n if current_mount_point is None:\n mkdir_p( self.persistent_dir )\n check_call( [ 'mount', device, self.persistent_dir ] )\n elif current_mount_point == self.persistent_dir:\n pass\n else:\n raise RuntimeError(\n \"Can't mount device %s on '%s' since it is already mounted on '%s'\" % (\n device, self.persistent_dir, current_mount_point) )\n else:\n # No persistent volume is attached and the root volume is off limits, so we will need\n # to place persistent data on the ephemeral volume.\n self.persistent_dir = self.ephemeral_dir","def _volume_command(ramp, volume):\n if volume is not None:\n ramp.set_volume(float(volume))\n else:\n print ramp.volume","def test_pvresize_not_pv():\n pvdisplay = MagicMock(return_value=False)\n with patch(\"salt.modules.linux_lvm.pvdisplay\", pvdisplay):\n assert linux_lvm.pvresize(\"A\", override=False) == \"A is not a physical volume\"\n\n pvdisplay = MagicMock(return_value=False)\n with patch(\"salt.modules.linux_lvm.pvdisplay\", pvdisplay):\n assert linux_lvm.pvresize(\"A\") is True","def vol_up_and_validate(self):\n self.logger.info('Increasing volume')\n before_vol = self.dut.volume('Up', 1)\n time.sleep(2)\n after_vol = self.dut.volume('Up', 1)\n if not after_vol or not before_vol or after_vol <= before_vol:\n self.logger.error(\n 'Unable to increase the volume. Before: %s. After: %s' %\n (before_vol, after_vol))\n raise TestActsError('error increasing volume')","def test_update_volume_stats_error(self):\n self._fail_host_storage = True\n actual = self.driver.get_volume_stats(True)\n self.assertEqual('HGST', actual['vendor_name'])\n self.assertEqual('hgst', actual['storage_protocol'])\n self.assertEqual('unknown', actual['total_capacity_gb'])\n self.assertEqual('unknown', actual['free_capacity_gb'])\n self.assertEqual(0, actual['reserved_percentage'])","def test_attachment_create_creating_volume(self):\n volume_params = {'status': 'creating'}\n\n vref = tests_utils.create_volume(self.context, **volume_params)\n self.assertRaises(exception.InvalidVolume,\n self.volume_api.attachment_create,\n self.context,\n vref,\n fake.UUID1)","def cli(env, snapshot_id):\n block_manager = SoftLayer.BlockStorageManager(env.client)\n deleted = block_manager.delete_snapshot(snapshot_id)\n\n if deleted:\n click.echo('Snapshot %s deleted' % snapshot_id)","def database_volume_snapshot_add(volume_snapshot_obj):\n db = database_get()\n session = db.session()\n query = session.query(model.VolumeSnapshot)\n query = query.filter(model.VolumeSnapshot.uuid == volume_snapshot_obj.uuid)\n volume_snapshot = query.first()\n if not volume_snapshot:\n volume_snapshot = model.VolumeSnapshot()\n volume_snapshot.uuid = volume_snapshot_obj.uuid\n volume_snapshot.name = volume_snapshot_obj.name\n volume_snapshot.description = volume_snapshot_obj.description\n volume_snapshot.size_gb = volume_snapshot_obj.size_gb\n volume_snapshot.volume_uuid = volume_snapshot_obj.volume_uuid\n volume_snapshot.nfvi_volume_snapshot_data = \\\n json.dumps(volume_snapshot_obj.nfvi_volume_snapshot.as_dict())\n session.add(volume_snapshot)\n else:\n volume_snapshot.name = volume_snapshot_obj.name\n volume_snapshot.description = volume_snapshot_obj.description\n volume_snapshot.size_gb = volume_snapshot_obj.size_gb\n volume_snapshot.volume_uuid = volume_snapshot_obj.volume_uuid\n volume_snapshot.nfvi_volume_snapshot_data = \\\n json.dumps(volume_snapshot_obj.nfvi_volume_snapshot.as_dict())\n db.commit()","def load_snapshot_halos(base_path, snap_num, subvolumes, fields=None, matches=False):\n return load_snapshot(base_path, snap_num, subvolumes, \"Haloprop\", fields, matches)","def load_volume(self, volume_path, series_uid):\n if volume_path is None:\n return False, 'Volume data is None.'\n\n im = read_image(volume_path)\n\n # manage volume data in a dictionary\n self.volumes[series_uid] = im\n # init config info of this volume\n self.configs[series_uid] = {}\n self.configs[series_uid]['size'] = [512, 512, 57]\n self.configs[series_uid]['center'] = im.center()\n self.configs[series_uid]['cursor'] = im.center()\n self.configs[series_uid]['spacing'] = im.spacing() # [1, 1, 1]\n self.configs[series_uid]['zoom_factor'] = 1\n self.configs[series_uid]['win_center'] = 0\n self.configs[series_uid]['win_width'] = 2000\n self.configs[series_uid]['colormode'] = 0\n self.configs[series_uid]['alpha'] = 1\n self.configs[series_uid]['default_v'] = -1024\n self.configs[series_uid]['transverse_axis'] = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]\n self.configs[series_uid]['saggital_axis'] = [[0, 1, 0], [0, 0, -1], [1, 0, 0]]\n self.configs[series_uid]['coronal_axis'] = [[1, 0, 0], [0, 0, -1], [0, 1, 0]]\n\n # switch current volume to this volume\n self.change_volume(series_uid)\n\n self.look_at['transverse'] = im.center()\n self.look_at['coronal'] = im.center()\n self.look_at['saggital'] = im.center()\n\n return True, 'Load succeed.'","def test_create_volume_blocked(self, mock_ghn):\n ctxt = context.get_admin_context()\n extra_specs = {}\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\n volume = {'id': '1', 'name': 'volume1',\n 'display_name': '',\n 'volume_type_id': type_ref['id'],\n 'size': 10}\n self._return_blocked = 1 # Block & fail cancel => create succeeded\n ret = self.driver.create_volume(volume)\n expected = {'redundancy': '0', 'group': 'xanadu',\n 'name': 'volume10', 'mode': '0777',\n 'user': 'kane', 'net': 'net1',\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\n 'size': '12'}\n self.assertDictMatch(expected, self.created)\n # Check the returned provider\n expected_pid = {'provider_id': 'volume10'}\n self.assertDictMatch(expected_pid, ret)\n self.assertTrue(self._request_cancel)","def test_migrate_volume_driver(self):\n # Mock driver and rpc functions\n self.mock_object(self.volume.driver, 'migrate_volume',\n lambda x, y, z, new_type_id=None: (\n True, {'user_id': fake.USER_ID}))\n\n volume = tests_utils.create_volume(ctxt=self.context, size=0,\n host=CONF.host,\n migration_status='migrating')\n host_obj = {'host': 'newhost', 'capabilities': {}}\n self.volume.migrate_volume(self.context, volume, host_obj, False)\n\n # check volume properties\n volume = objects.Volume.get_by_id(context.get_admin_context(),\n volume.id)\n self.assertEqual('newhost', volume.host)\n self.assertEqual('success', volume.migration_status)","def verify_no_snapshot_reingestion(c: Composition) -> None:\n c.run(\"testdrive\", \"wait-for-snapshot.td\", \"postgres-disable-select-permission.td\")\n\n restart_mz(c)\n\n c.run(\n \"testdrive\",\n \"delete-rows-t1.td\",\n \"delete-rows-t2.td\",\n \"alter-table.td\",\n \"alter-mz.td\",\n )","def test_update_volume_stats_cached(self):\n self._fail_host_storage = True\n actual = self.driver.get_volume_stats(False)\n self.assertEqual('HGST', actual['vendor_name'])\n self.assertEqual('hgst', actual['storage_protocol'])\n self.assertEqual(90, actual['total_capacity_gb'])\n self.assertEqual(87, actual['free_capacity_gb'])\n self.assertEqual(0, actual['reserved_percentage'])","def create_cloned_volume(self, volume, src_vref):\n LOG.info('Creating clone of volume: %s', src_vref['id'])\n snapshot = {'volume_name': src_vref['name'],\n 'volume_id': src_vref['id'],\n 'volume_size': src_vref['size'],\n 'name': self._get_clone_snapshot_name(volume)}\n # We don't delete this snapshot, because this snapshot will be origin\n # of new volume. This snapshot will be automatically promoted by NMS\n # when user will delete its origin.\n self.create_snapshot(snapshot)\n try:\n return self.create_volume_from_snapshot(volume, snapshot)\n except utils.NexentaException:\n LOG.error('Volume creation failed, deleting created snapshot '\n '%(volume_name)s@%(name)s', snapshot)\n try:\n self.delete_snapshot(snapshot)\n except (utils.NexentaException, exception.SnapshotIsBusy):\n LOG.warning('Failed to delete zfs snapshot '\n '%(volume_name)s@%(name)s', snapshot)\n raise","def test_finish_resize_with_volumes(self):\n\n # create instance\n instance = self._create_fake_instance_obj()\n request_spec = objects.RequestSpec()\n\n # create volume\n volume = {'instance_uuid': None,\n 'device_name': None,\n 'id': uuids.volume,\n 'size': 200,\n 'attach_status': 'detached'}\n bdm = objects.BlockDeviceMapping(\n **{'context': self.context,\n 'source_type': 'volume',\n 'destination_type': 'volume',\n 'volume_id': uuids.volume,\n 'instance_uuid': instance['uuid'],\n 'device_name': '/dev/vdc'})\n bdm.create()\n\n # stub out volume attach\n def fake_volume_get(self, context, volume_id, microversion=None):\n return volume\n self.stub_out('nova.volume.cinder.API.get', fake_volume_get)\n\n def fake_volume_check_availability_zone(self, context,\n volume_id, instance):\n pass\n self.stub_out('nova.volume.cinder.API.check_availability_zone',\n fake_volume_check_availability_zone)\n\n def fake_get_volume_encryption_metadata(self, context, volume_id):\n return {}\n self.stub_out('nova.volume.cinder.API.get_volume_encryption_metadata',\n fake_get_volume_encryption_metadata)\n\n orig_connection_data = {\n 'target_discovered': True,\n 'target_iqn': 'iqn.2010-10.org.openstack:%s.1' % uuids.volume_id,\n 'target_portal': '127.0.0.0.1:3260',\n 'volume_id': uuids.volume_id,\n }\n connection_info = {\n 'driver_volume_type': 'iscsi',\n 'data': orig_connection_data,\n }\n\n def fake_init_conn(self, context, volume_id, session):\n return connection_info\n self.stub_out('nova.volume.cinder.API.initialize_connection',\n fake_init_conn)\n\n def fake_attach(self, context, volume_id, instance_uuid, device_name,\n mode='rw'):\n volume['instance_uuid'] = instance_uuid\n volume['device_name'] = device_name\n self.stub_out('nova.volume.cinder.API.attach', fake_attach)\n\n # stub out virt driver attach\n def fake_get_volume_connector(*args, **kwargs):\n return {}\n self.stub_out('nova.virt.fake.FakeDriver.get_volume_connector',\n fake_get_volume_connector)\n\n def fake_attach_volume(*args, **kwargs):\n pass\n self.stub_out('nova.virt.fake.FakeDriver.attach_volume',\n fake_attach_volume)\n\n # attach volume to instance\n self.compute.attach_volume(self.context, instance, bdm)\n\n # assert volume attached correctly\n self.assertEqual(volume['device_name'], '/dev/vdc')\n disk_info = db.block_device_mapping_get_all_by_instance(\n self.context, instance.uuid)\n self.assertEqual(len(disk_info), 1)\n for bdm in disk_info:\n self.assertEqual(bdm['device_name'], volume['device_name'])\n self.assertEqual(bdm['connection_info'],\n jsonutils.dumps(connection_info))\n\n # begin resize\n flavor = self.default_flavor\n instance.task_state = task_states.RESIZE_PREP\n instance.save()\n self.compute.prep_resize(self.context, instance=instance,\n flavor=flavor,\n image={}, request_spec=request_spec,\n filter_properties={}, node=None,\n clean_shutdown=True, migration=None,\n host_list=[])\n\n # fake out detach for prep_resize (and later terminate)\n def fake_terminate_connection(self, context, volume, connector):\n connection_info['data'] = None\n self.stub_out('nova.volume.cinder.API.terminate_connection',\n fake_terminate_connection)\n\n migration = objects.Migration.get_by_instance_and_status(\n self.context.elevated(),\n instance.uuid, 'pre-migrating')\n self.compute.resize_instance(self.context, instance=instance,\n migration=migration, image={},\n # TODO(stephenfin): Why a JSON string?\n flavor=jsonutils.to_primitive(flavor),\n clean_shutdown=True, request_spec=request_spec)\n\n # assert bdm is unchanged\n disk_info = db.block_device_mapping_get_all_by_instance(\n self.context, instance.uuid)\n self.assertEqual(len(disk_info), 1)\n for bdm in disk_info:\n self.assertEqual(bdm['device_name'], volume['device_name'])\n cached_connection_info = jsonutils.loads(bdm['connection_info'])\n self.assertEqual(cached_connection_info['data'],\n orig_connection_data)\n # but connection was terminated\n self.assertIsNone(connection_info['data'])\n\n # stub out virt driver finish_migration\n def fake(*args, **kwargs):\n pass\n self.stub_out('nova.virt.fake.FakeDriver.finish_migration', fake)\n\n instance.task_state = task_states.RESIZE_MIGRATED\n instance.save()\n\n # new initialize connection\n new_connection_data = dict(orig_connection_data)\n new_iqn = 'iqn.2010-10.org.openstack:%s.2' % uuids.volume_id,\n new_connection_data['target_iqn'] = new_iqn\n\n def fake_init_conn_with_data(self, context, volume, session):\n connection_info['data'] = new_connection_data\n return connection_info\n self.stub_out('nova.volume.cinder.API.initialize_connection',\n fake_init_conn_with_data)\n\n self.compute.finish_resize(self.context,\n migration=migration,\n disk_info={}, image={}, instance=instance,\n request_spec=request_spec)\n\n # assert volume attached correctly\n disk_info = db.block_device_mapping_get_all_by_instance(\n self.context, instance['uuid'])\n self.assertEqual(len(disk_info), 1)\n for bdm in disk_info:\n self.assertEqual(bdm['connection_info'],\n jsonutils.dumps(connection_info))\n\n # stub out detach\n def fake_detach(self, context, volume_uuid):\n volume['device_path'] = None\n volume['instance_uuid'] = None\n self.stub_out('nova.volume.cinder.API.detach', fake_detach)\n\n # clean up\n self.compute.terminate_instance(self.context, instance, [])","def snapcheck(self, data, pre_file=None, dev=None, local=False, folder=None):\n if pre_file is None:\n pre_file = \"snap_temp\"\n self.snap_del = True\n return self.action_api_based(\n dev, data, pre_file, \"snapcheck\", folder, local=local\n )","def test_csi_volumesnapshot_restore_existing_backup(set_random_backupstore, # NOQA\n client, # NOQA\n core_api, # NOQA\n volume_name, # NOQA\n csi_pv, # NOQA\n pvc, # NOQA\n pod_make, # NOQA\n volumesnapshotclass, # NOQA\n volumesnapshotcontent,\n volumesnapshot, # NOQA\n volsnapshotclass_delete_policy, # NOQA\n backup_is_deleted): # NOQA\n csisnapclass = \\\n volumesnapshotclass(name=\"snapshotclass\",\n deletepolicy=volsnapshotclass_delete_policy)\n\n pod_name, pv_name, pvc_name, md5sum = \\\n prepare_pod_with_data_in_mb(client, core_api,\n csi_pv, pvc, pod_make,\n volume_name,\n data_path=\"/data/test\")\n\n volume = client.by_id_volume(volume_name)\n snap = create_snapshot(client, volume_name)\n volume.snapshotBackup(name=snap.name)\n wait_for_backup_completion(client, volume_name, snap.name)\n bv, b = find_backup(client, volume_name, snap.name)\n\n csivolsnap_name = volume_name + \"-volumesnapshot\"\n csivolsnap_namespace = \"default\"\n\n volsnapcontent = \\\n volumesnapshotcontent(\"volsnapcontent\",\n csisnapclass[\"metadata\"][\"name\"],\n \"Delete\",\n \"bs://\" + volume_name + \"/\" + b.name,\n csivolsnap_name,\n csivolsnap_namespace)\n\n csivolsnap = volumesnapshot(csivolsnap_name,\n csivolsnap_namespace,\n csisnapclass[\"metadata\"][\"name\"],\n \"volumeSnapshotContentName\",\n volsnapcontent[\"metadata\"][\"name\"])\n\n restore_pvc_name = pvc[\"metadata\"][\"name\"] + \"-restore\"\n restore_pvc_size = pvc[\"spec\"][\"resources\"][\"requests\"][\"storage\"]\n\n restore_csi_volume_snapshot(core_api,\n client,\n csivolsnap,\n restore_pvc_name,\n restore_pvc_size)\n\n restore_pod = pod_make()\n restore_pod_name = restore_pod[\"metadata\"][\"name\"]\n restore_pod['spec']['volumes'] = [create_pvc_spec(restore_pvc_name)]\n\n create_and_wait_pod(core_api, restore_pod)\n restore_md5sum = \\\n get_pod_data_md5sum(core_api, restore_pod_name, path=\"/data/test\")\n\n assert restore_md5sum == md5sum\n\n # Delete volumeSnapshot test\n delete_volumesnapshot(csivolsnap[\"metadata\"][\"name\"], \"default\")\n\n if backup_is_deleted is False:\n find_backup(client, volume_name, b[\"snapshotName\"])\n else:\n wait_for_backup_delete(client, volume_name, b[\"name\"])","def creation_validation(**_):\n\n for property_key in constants.VOLUME_REQUIRED_PROPERTIES:\n utils.validate_node_property(property_key, ctx.node.properties)\n\n volume_object = _get_volumes_from_id(utils.get_resource_id())\n\n if ctx.node.properties['use_external_resource'] and not volume_object:\n raise NonRecoverableError(\n 'External resource, but the supplied '\n 'EBS volume does not exist in the account.')\n\n if not ctx.node.properties['use_external_resource'] and volume_object:\n raise NonRecoverableError(\n 'Not external resource, but the supplied '\n 'EBS volume exists in the account.')","def test_07_migrate_vm_live_with_snapshots(self):\n global vm\n # Get ROOT Volume\n vol_for_snap = list_volumes(\n self.apiclient,\n virtualmachineid=vm.id,\n listall=True)\n for vol in vol_for_snap:\n snapshot = Snapshot.create(\n self.apiclient,\n volume_id=vol.id\n )\n snapshot.validateState(\n self.apiclient,\n snapshotstate=\"backedup\",\n )\n # Migrate all volumes and VMs\n\n destinationHost, vol_list = self.helper.get_destination_pools_hosts(self.apiclient, vm, self.host)\n for v in vol_list:\n self.helper.check_storpool_volume_iops(self.spapi, v)\n vm = self.helper.migrateVm(self.apiclient, self.virtual_machine_live_migration_1, destinationHost)\n\n destinationHost, vol_list = self.helper.get_destination_pools_hosts(self.apiclient, vm, self.host)\n for v in vol_list:\n self.helper.check_storpool_volume_iops(self.spapi, v)","def migrate_volume(self, ctxt, volume_id, host, force_host_copy=False):\n return","def test_volumes_get(self):\n pass","def update_volume( opencloud_volume ):\n\n client = connect_syndicate()\n\n vol_name = opencloud_volume.name\n vol_description = opencloud_volume.description\n vol_private = opencloud_volume.private\n vol_archive = opencloud_volume.archive\n vol_default_gateway_caps = opencloud_caps_to_syndicate_caps( opencloud_volume.cap_read_data, opencloud_volume.cap_write_data, opencloud_volume.cap_host_data )\n\n try:\n rc = client.update_volume( vol_name,\n description=vol_description,\n private=vol_private,\n archive=vol_archive,\n default_gateway_caps=vol_default_gateway_caps )\n\n if not rc:\n raise Exception(\"update_volume(%s) failed!\" % vol_name )\n\n except Exception, e:\n # transort or method error \n logger.exception(e)\n return False\n\n else:\n return True","def migrate_volume(self, ctxt, volume, host, new_type=None):\n return self._migrate_volume(volume, host, new_type)","def test_aws_service_api_volume_attachment_put(self):\n pass","def manage_existing_snapshot(self, snapshot, existing_ref):\n\n old_snap_name = existing_ref['source-name']\n new_snap_name = self._get_snap_name(snapshot.id)\n LOG.info(\"Renaming existing snapshot %(old_name)s to \"\n \"%(new_name)s\", {\"old_name\": old_snap_name,\n \"new_name\": new_snap_name})\n\n self.client_login()\n try:\n self.client.modify_volume_name(old_snap_name,\n new_snap_name)\n except stx_exception.RequestError as ex:\n LOG.exception(\"Error managing existing snapshot.\")\n raise exception.Invalid(ex)\n finally:\n self.client_logout()\n\n return None","def check_volume(vol, srf_names, verbose=True):\n if verbose:\n print(\" checking volume for validity\")\n print(\" ----------------------------\")\n # check if dict\n if not isinstance(vol, dict):\n if verbose:\n print(\" vol is not of type dict\")\n return False\n # check for keys in gli dict\n in_vol_keys = set(vol)\n if in_vol_keys == VOL_KEYS:\n if verbose:\n print(\" vol keys are valid\")\n else:\n if verbose:\n print(\" vol keys are not valid!\")\n print(\" needs: \" + \" \".join(VOL_KEYS))\n print(\" found: \" + \" \".join(map(str, in_vol_keys)))\n print(\" missing: \" + \" \".join(map(str, VOL_KEYS - in_vol_keys)))\n print(\" corrupted: \" + \" \".join(map(str, in_vol_keys - VOL_KEYS)))\n return False\n # check NAME\n if (\n isinstance(vol[\"NAME\"], STRTYPE)\n and not has_whitespaces(vol[\"NAME\"])\n and len(vol[\"NAME\"]) > 0\n ):\n if verbose:\n print(\" vol['NAME'] valid\")\n print(\" NAME: '\" + vol[\"NAME\"] + \"'\")\n else:\n if verbose:\n print(\" vol['NAME'] not valid\")\n return False\n # check SURFACES\n if (\n isinstance(vol[\"SURFACES\"], list)\n and len(vol[\"SURFACES\"]) > 0\n and all(srf in srf_names for srf in vol[\"SURFACES\"])\n ):\n if verbose:\n print(\" vol['SURFACES'] valid\")\n else:\n if verbose:\n print(\" vol['SURFACES'] not valid\")\n return False\n # check TYPE\n if vol[\"TYPE\"] is None or isinstance(vol[\"TYPE\"], int):\n if verbose:\n print(\" vol['TYPE'] valid\")\n else:\n if verbose:\n print(\" vol['TYPE'] not valid\")\n return False\n # check MAT_GROUP\n if vol[\"MAT_GROUP\"] is None or isinstance(vol[\"MAT_GROUP\"], int):\n if verbose:\n print(\" vol['MAT_GROUP'] valid\")\n else:\n if verbose:\n print(\" vol['MAT_GROUP'] not valid\")\n return False\n # check LAYER\n if vol[\"LAYER\"] is None or isinstance(vol[\"LAYER\"], int):\n if verbose:\n print(\" vol['LAYER'] valid\")\n else:\n if verbose:\n print(\" vol['LAYER'] not valid\")\n return False\n # finally\n if verbose:\n print(\" ------------\")\n print(\" vol is valid\")\n print(\"\")\n return True","def test_change_volume_status(self, volume, volumes_steps):\n volumes_steps.change_volume_status(volume.name, 'Error')\n volumes_steps.change_volume_status(volume.name, 'Available')","def test_absolute_volume(self):\n\n assert self.test_shape.volume() == pytest.approx(50 * 60 * math.pi * 2 * 1000)"],"string":"[\n \"def test_create_volume_from_snapshot(self, mock_ghn):\\n ctxt = context.get_admin_context()\\n extra_specs = {}\\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\\n snap = {'id': '1', 'name': 'volume1', 'display_name': '',\\n 'volume_type_id': type_ref['id'], 'size': 10,\\n 'provider_id': 'space_orig'}\\n volume = {'id': '2', 'name': 'volume2', 'display_name': '',\\n 'volume_type_id': type_ref['id'], 'size': 10}\\n pid = self.driver.create_volume_from_snapshot(volume, snap)\\n # We must copy entier underlying storage, ~12GB, not just 10GB\\n self.assertEqual(11444 * units.Mi, self.dd_count)\\n self.assertEqual('1M', self.bs)\\n # Check space-create command\\n expected = {'redundancy': '0', 'group': 'xanadu',\\n 'name': 'volume2', 'mode': '0777',\\n 'user': 'kane', 'net': 'net1',\\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\\n 'size': '12'}\\n self.assertDictMatch(expected, self.created)\\n # Check the returned provider\\n expected_pid = {'provider_id': 'volume2'}\\n self.assertDictMatch(expected_pid, pid)\",\n \"def create_volume_from_snapshot(snapshots, objects_created,\\n wait_for_available=120):\\n if type(snapshots) is not list:\\n snapshots = [snapshots]\\n v = []\\n for snapshot in snapshots:\\n command = 'cinder create --snapshot-id %s --name %s' % \\\\\\n (snapshot['id'], snapshot['display_name'])\\n volume_from_snapshot = parse_output(Popen(\\n command.split(), stdout=STDOUT, stderr=STDERR).communicate()[0])\\n volume_from_snapshot['device'] = snapshot['device']\\n volume_from_snapshot['bootable'] = snapshot['bootable']\\n v.append(volume_from_snapshot)\\n if wait_for_available > 0:\\n wait = 0\\n again = False\\n while wait < wait_for_available:\\n time.sleep(5)\\n wait += 5\\n again = False\\n for volume in v:\\n command = 'cinder show %s' % volume['id']\\n status = parse_output(Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n )['status']\\n if status == 'error':\\n # clean up and create volume again\\n command = 'cinder delete %s' % volume['id']\\n a = Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n command = 'cinder create --snapshot-id %s' % \\\\\\n volume['snapshot_id']\\n volume_info = parse_output(Popen(\\n command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0])\\n volume_info['bootable'] = volume['bootable']\\n volume_info['device'] = volume['device']\\n volume = volume_info\\n again = True\\n break\\n elif status == 'creating':\\n again = True\\n break\\n elif status == 'available':\\n volume['status'] = status\\n pass\\n if again:\\n continue\\n else:\\n break\\n if again: # Loop ended due to timeout\\n print 'Error creating volume from snapshot!'\\n print 'The following entities were created in the process:'\\n print_objects_created(objects_created)\\n sys.exit(-1)\\n return v\",\n \"def create_volume_from_snapshot(self, snapshot, volume, volume_db):\\n self.authenticate_user()\\n\\n if self.configuration.vipr_emulate_snapshot == 'True':\\n self.create_cloned_volume(volume, snapshot)\\n return\\n\\n ctxt = context.get_admin_context()\\n\\n src_snapshot_name = None\\n\\n #src_snapshot_name = snapshot['display_name']\\n src_vol_ref = volume_db.volume_get(ctxt, snapshot['volume_id'])\\n new_volume_name = self._get_volume_name(volume)\\n number_of_volumes = 1\\n\\n try:\\n src_vol_name, src_vol_uri = self._get_vipr_volume_name(src_vol_ref, True)\\n src_snapshot_name = self._get_vipr_snapshot_name(snapshot , src_vol_uri)\\n\\n (storageresType, storageresTypename) = self.volume_obj.get_storageAttributes(\\n src_vol_name\\n , None\\n , src_snapshot_name)\\n\\n resource_id = self.volume_obj.storageResource_query(storageresType,\\n src_vol_name,\\n None,\\n src_snapshot_name,\\n self.configuration.vipr_project,\\n self.configuration.vipr_tenant)\\n\\n self.volume_obj.clone(\\n new_volume_name,\\n number_of_volumes,\\n resource_id,\\n sync=True)\\n\\n except vipr_utils.SOSError as e:\\n if(e.err_code == vipr_utils.SOSError.SOS_FAILURE_ERR):\\n raise vipr_utils.SOSError(\\n vipr_utils.SOSError.SOS_FAILURE_ERR,\\n \\\"Snapshot \\\" +\\n src_snapshot_name +\\n \\\": clone failed\\\\n\\\" +\\n e.err_text)\\n else:\\n with excutils.save_and_reraise_exception():\\n LOG.exception(\\n _(\\\"Snapshot : %s clone failed\\\") % src_snapshot_name)\",\n \"def create_volume_snapshot(self, volume, name=None, description=None,\\n check=True):\\n cmd = 'cinder snapshot-create'\\n if name:\\n cmd += ' --name ' + name\\n if description is not None:\\n cmd += ' --description ' + moves.shlex_quote(description)\\n\\n cmd += ' ' + volume.id\\n\\n exit_code, stdout, stderr = self.execute_command(\\n cmd, timeout=config.SNAPSHOT_AVAILABLE_TIMEOUT, check=check)\\n\\n snapshot_table = output_parser.table(stdout)\\n snapshot = {key: value for key, value in snapshot_table['values']}\\n\\n return snapshot\",\n \"def create_volume_from_snapshot(self, volume, snapshot):\\n snap_name = self.get_snap_name(snapshot.id)\\n view_name = self.get_view_name(volume.id)\\n vol_name = self.get_volume_name(volume.id)\\n cview = src_attach_info = dest_attach_info = None\\n rpolicy = self.get_policy()\\n properties = volume_utils.brick_get_connector_properties(\\n self.configuration.use_multipath_for_image_xfer,\\n self.configuration.enforce_multipath_for_image_xfer)\\n LOG.debug(\\\"Searching for snapshot: %s in K2.\\\", snap_name)\\n snap_rs = self.client.search(\\\"snapshots\\\", short_name=snap_name)\\n if hasattr(snap_rs, 'hits') and snap_rs.total != 0:\\n snap = snap_rs.hits[0]\\n LOG.debug(\\\"Creating a view: %(view)s from snapshot: %(snap)s\\\",\\n {'view': view_name, 'snap': snap_name})\\n try:\\n cview = self.client.new(\\\"snapshots\\\",\\n short_name=view_name,\\n source=snap, retention_policy=rpolicy,\\n is_exposable=True).save()\\n except Exception as ex:\\n LOG.exception(\\\"Creating a view: %(view)s from snapshot: \\\"\\n \\\"%(snap)s failed\\\", {\\\"view\\\": view_name,\\n \\\"snap\\\": snap_name})\\n raise KaminarioCinderDriverException(reason=ex)\\n\\n else:\\n msg = _(\\\"Snapshot: %s search failed in K2.\\\") % snap_name\\n LOG.error(msg)\\n raise KaminarioCinderDriverException(reason=msg)\\n\\n try:\\n conn = self.initialize_connection(cview, properties)\\n src_attach_info = self._connect_device(conn)\\n self.create_volume(volume)\\n conn = self.initialize_connection(volume, properties)\\n dest_attach_info = self._connect_device(conn)\\n volume_utils.copy_volume(src_attach_info['device']['path'],\\n dest_attach_info['device']['path'],\\n snapshot.volume.size * units.Ki,\\n self.configuration.volume_dd_blocksize,\\n sparse=True)\\n self._kaminario_disconnect_volume(src_attach_info,\\n dest_attach_info)\\n self.terminate_connection(volume, properties)\\n self.terminate_connection(cview, properties)\\n cview.delete()\\n except Exception as ex:\\n self._kaminario_disconnect_volume(src_attach_info,\\n dest_attach_info)\\n self.terminate_connection(cview, properties)\\n self.terminate_connection(volume, properties)\\n cview.delete()\\n self.delete_volume(volume)\\n LOG.exception(\\\"Copy to volume: %(vol)s from view: %(view)s \\\"\\n \\\"failed\\\", {\\\"vol\\\": vol_name, \\\"view\\\": view_name})\\n raise KaminarioCinderDriverException(reason=ex)\",\n \"def create_volume_from_snapshot(self, volume, snapshot):\\n snapshotname = huawei_utils.encode_name(snapshot['id'])\\n\\n snapshot_id = snapshot.get('provider_location', None)\\n if snapshot_id is None:\\n snapshot_id = self.restclient.get_snapshotid_by_name(snapshotname)\\n if snapshot_id is None:\\n err_msg = (_(\\n 'create_volume_from_snapshot: Snapshot %(name)s '\\n 'does not exist.')\\n % {'name': snapshotname})\\n LOG.error(err_msg)\\n raise exception.VolumeBackendAPIException(data=err_msg)\\n\\n lun_info = self.create_volume(volume)\\n\\n tgt_lun_id = lun_info['ID']\\n luncopy_name = huawei_utils.encode_name(volume['id'])\\n\\n LOG.info(_LI(\\n 'create_volume_from_snapshot: src_lun_id: %(src_lun_id)s, '\\n 'tgt_lun_id: %(tgt_lun_id)s, copy_name: %(copy_name)s.'),\\n {'src_lun_id': snapshot_id,\\n 'tgt_lun_id': tgt_lun_id,\\n 'copy_name': luncopy_name})\\n\\n event_type = 'LUNReadyWaitInterval'\\n\\n wait_interval = huawei_utils.get_wait_interval(self.xml_file_path,\\n event_type)\\n\\n def _volume_ready():\\n result = self.restclient.get_lun_info(tgt_lun_id)\\n\\n if (result['HEALTHSTATUS'] == constants.STATUS_HEALTH\\n and result['RUNNINGSTATUS'] == constants.STATUS_VOLUME_READY):\\n return True\\n return False\\n\\n huawei_utils.wait_for_condition(self.xml_file_path,\\n _volume_ready,\\n wait_interval,\\n wait_interval * 10)\\n\\n self._copy_volume(volume, luncopy_name,\\n snapshot_id, tgt_lun_id)\\n\\n return {'ID': lun_info['ID'],\\n 'lun_info': lun_info}\",\n \"def create_volume_snapshot(volumes, source_instance, objects_created,\\n wait_for_available=50):\\n if type(volumes) is not list:\\n volumes = [volumes]\\n s = []\\n for volume in volumes:\\n command = 'cinder snapshot-create --force True --name %s %s' % \\\\\\n (volume['name'], volume['id'])\\n snapshot_info = parse_output(Popen(command.split(), stdout=STDOUT).communicate()[0])\\n if volume['bootable'] == 'true':\\n snapshot_info['bootable'] = True\\n else:\\n snapshot_info['bootable'] = False\\n att = volume['attachments'].replace(\\\"'\\\", \\\"\\\\\\\"\\\").replace(\\n \\\"u\\\\\\\"\\\", \\\"\\\\\\\"\\\").replace(\\\" None,\\\", \\\" \\\\\\\"None\\\\\\\",\\\")\\n snapshot_info['device'] = get(json.loads(att), 'server_id',\\n source_instance['id'])[0]['device']\\n s.append(snapshot_info)\\n if wait_for_available > 0:\\n wait = 0\\n again = False\\n while wait < wait_for_available:\\n time.sleep(5)\\n wait += 5\\n again = False\\n for snapshot in s:\\n command = 'cinder snapshot-show %s' % snapshot['id']\\n status = parse_output(Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n )['status']\\n if status == 'error':\\n # clean up and take snapshot again\\n command = 'cinder snapshot-delete %s' % snapshot['id']\\n a = Popen(command.split(), stdout=STDOUT,\\n stderr=STDERR).communicate()[0]\\n command = 'cinder snapshot-create --force True %s' % \\\\\\n snapshot['volume_id']\\n snapshot_info = parse_output(Popen(command.split(),\\n stdout=STDOUT, stderr=STDERR\\n ).communicate()[0])\\n snapshot_info['bootable'] = snapshot['bootable']\\n snapshot_info['device'] = snapshot['device']\\n snapshot = snapshot_info\\n again = True\\n break\\n elif status == 'creating':\\n again = True\\n break\\n elif status == 'available':\\n snapshot['status'] = status\\n pass\\n if again:\\n continue\\n else:\\n break\\n if again: # Loop ended due to timeout\\n print 'Error creating volume snapshot!'\\n print 'The following entities were created in the process:'\\n print_objects_created(objects_created)\\n sys.exit(-1)\\n return s\",\n \"def migrate_volume(self, ctxt, volume, host):\\n LOG.debug('Enter: migrate_volume: id=%(id)s, host=%(host)s',\\n {'id': volume['id'], 'host': host})\\n\\n false_ret = (False, None)\\n\\n if volume['status'] not in ('available', 'retyping'):\\n LOG.warning(\\\"Volume status must be 'available' or 'retyping'.\\\"\\n \\\" Current volume status: %s\\\", volume['status'])\\n return false_ret\\n\\n if 'capabilities' not in host:\\n LOG.warning(\\\"Unsupported host. No capabilities found\\\")\\n return false_ret\\n\\n capabilities = host['capabilities']\\n ns_shares = capabilities['ns_shares']\\n dst_parts = capabilities['location_info'].split(':')\\n dst_host, dst_volume = dst_parts[1:]\\n\\n if (capabilities.get('vendor_name') != 'Nexenta' or\\n dst_parts[0] != self.__class__.__name__ or\\n capabilities['free_capacity_gb'] < volume['size']):\\n return false_ret\\n\\n nms = self.share2nms[volume['provider_location']]\\n ssh_bindings = nms.appliance.ssh_list_bindings()\\n shares = []\\n for bind in ssh_bindings:\\n for share in ns_shares:\\n if (share.startswith(ssh_bindings[bind][3]) and\\n ns_shares[share] >= volume['size']):\\n shares.append(share)\\n if len(shares) == 0:\\n LOG.warning(\\\"Remote NexentaStor appliance at %s should be \\\"\\n \\\"SSH-bound.\\\", share)\\n return false_ret\\n share = sorted(shares, key=ns_shares.get, reverse=True)[0]\\n snapshot = {\\n 'volume_name': volume['name'],\\n 'volume_id': volume['id'],\\n 'name': utils.get_migrate_snapshot_name(volume)\\n }\\n self.create_snapshot(snapshot)\\n location = volume['provider_location']\\n src = '%(share)s/%(volume)s@%(snapshot)s' % {\\n 'share': location.split(':')[1].split('volumes/')[1],\\n 'volume': volume['name'],\\n 'snapshot': snapshot['name']\\n }\\n dst = ':'.join([dst_host, dst_volume.split('/volumes/')[1]])\\n try:\\n nms.appliance.execute(self._get_zfs_send_recv_cmd(src, dst))\\n except utils.NexentaException as exc:\\n LOG.warning(\\\"Cannot send source snapshot %(src)s to \\\"\\n \\\"destination %(dst)s. Reason: %(exc)s\\\",\\n {'src': src, 'dst': dst, 'exc': exc})\\n return false_ret\\n finally:\\n try:\\n self.delete_snapshot(snapshot)\\n except utils.NexentaException as exc:\\n LOG.warning(\\\"Cannot delete temporary source snapshot \\\"\\n \\\"%(src)s on NexentaStor Appliance: %(exc)s\\\",\\n {'src': src, 'exc': exc})\\n try:\\n self.delete_volume(volume)\\n except utils.NexentaException as exc:\\n LOG.warning(\\\"Cannot delete source volume %(volume)s on \\\"\\n \\\"NexentaStor Appliance: %(exc)s\\\",\\n {'volume': volume['name'], 'exc': exc})\\n\\n dst_nms = self._get_nms_for_url(capabilities['nms_url'])\\n dst_snapshot = '%s/%s@%s' % (dst_volume.split('volumes/')[1],\\n volume['name'], snapshot['name'])\\n try:\\n dst_nms.snapshot.destroy(dst_snapshot, '')\\n except utils.NexentaException as exc:\\n LOG.warning(\\\"Cannot delete temporary destination snapshot \\\"\\n \\\"%(dst)s on NexentaStor Appliance: %(exc)s\\\",\\n {'dst': dst_snapshot, 'exc': exc})\\n return True, {'provider_location': share}\",\n \"def create_volume_from_snapshot(self, volume, snapshot):\\n\\n free_size = self._get_spdk_lvs_free_space(\\n self._get_spdk_lvs_uuid(\\n self._get_spdk_volume_name(snapshot.name)))\\n\\n if free_size < volume.size:\\n raise exception.VolumeBackendAPIException(\\n data=_('Not enough space to create snapshot with SPDK'))\\n\\n return self._create_volume(volume, snapshot)\",\n \"def snapshot(self, name):\\r\\n return self.driver.create_volume_snapshot(volume=self, name=name)\",\n \"def snapshot_volumes(self) -> bool:\\n return pulumi.get(self, \\\"snapshot_volumes\\\")\",\n \"def create_volume_from_snapshot(self, volume, snapshot):\\n self._ensure_shares_mounted()\\n\\n snapshot_vol = self._get_snapshot_volume(snapshot)\\n nfs_share = snapshot_vol['provider_location']\\n volume['provider_location'] = nfs_share\\n nms = self.share2nms[nfs_share]\\n\\n vol, dataset = self._get_share_datasets(nfs_share)\\n snapshot_name = '%s/%s/%s@%s' % (vol, dataset, snapshot['volume_name'],\\n snapshot['name'])\\n folder = '%s/%s' % (dataset, volume['name'])\\n nms.folder.clone(snapshot_name, '%s/%s' % (vol, folder))\\n\\n try:\\n self._share_folder(nms, vol, folder)\\n except utils.NexentaException:\\n try:\\n nms.folder.destroy('%s/%s' % (vol, folder), '')\\n except utils.NexentaException:\\n LOG.warning(\\\"Cannot destroy cloned folder: \\\"\\n \\\"%(vol)s/%(folder)s\\\",\\n {'vol': vol, 'folder': folder})\\n raise\\n\\n if self._get_nfs_server_version(nfs_share) < 4:\\n sub_share, mnt_path = self._get_subshare_mount_point(nfs_share,\\n volume)\\n self._ensure_share_mounted(sub_share, mnt_path)\\n\\n if (('size' in volume) and (\\n volume['size'] > snapshot['volume_size'])):\\n self.extend_volume(volume, volume['size'])\\n\\n return {'provider_location': volume['provider_location']}\",\n \"def test_volume_snapshot_create_get_list_delete(self):\\n volume = self.create_volume()\\n self.addCleanup(self.delete_volume, volume['id'])\\n\\n s_name = data_utils.rand_name(self.__class__.__name__ + '-Snapshot')\\n # Create snapshot\\n snapshot = self.snapshots_client.create_snapshot(\\n volume_id=volume['id'],\\n display_name=s_name)['snapshot']\\n\\n def delete_snapshot(snapshot_id):\\n waiters.wait_for_volume_resource_status(self.snapshots_client,\\n snapshot_id,\\n 'available')\\n # Delete snapshot\\n self.snapshots_client.delete_snapshot(snapshot_id)\\n self.snapshots_client.wait_for_resource_deletion(snapshot_id)\\n\\n self.addCleanup(delete_snapshot, snapshot['id'])\\n self.assertEqual(volume['id'], snapshot['volumeId'])\\n # Get snapshot\\n fetched_snapshot = self.snapshots_client.show_snapshot(\\n snapshot['id'])['snapshot']\\n self.assertEqual(s_name, fetched_snapshot['displayName'])\\n self.assertEqual(volume['id'], fetched_snapshot['volumeId'])\\n # Fetch all snapshots\\n snapshots = self.snapshots_client.list_snapshots()['snapshots']\\n self.assertIn(snapshot['id'], map(lambda x: x['id'], snapshots))\",\n \"def test_create_snapshot(self, mock_ghn):\\n # Now snapshot the volume and check commands\\n snapshot = {'volume_name': 'volume10',\\n 'volume_id': 'xxx', 'display_name': 'snap10',\\n 'name': '123abc', 'volume_size': 10, 'id': '123abc',\\n 'volume': {'provider_id': 'space10'}}\\n ret = self.driver.create_snapshot(snapshot)\\n # We must copy entier underlying storage, ~12GB, not just 10GB\\n self.assertEqual(11444 * units.Mi, self.dd_count)\\n self.assertEqual('1M', self.bs)\\n # Check space-create command\\n expected = {'redundancy': '0', 'group': 'xanadu',\\n 'name': snapshot['display_name'], 'mode': '0777',\\n 'user': 'kane', 'net': 'net1',\\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\\n 'size': '12'}\\n self.assertDictMatch(expected, self.created)\\n # Check the returned provider\\n expected_pid = {'provider_id': 'snap10'}\\n self.assertDictMatch(expected_pid, ret)\",\n \"def test_clone_delete_snap(self):\\n\\n # pylint: disable=too-many-statements, too-many-locals\\n # Enabling Volume options on the volume and validating\\n g.log.info(\\\"Enabling volume options for volume %s \\\", self.volname)\\n options = {\\\" features.uss\\\": \\\"enable\\\"}\\n ret = set_volume_options(self.mnode, self.volname, options)\\n self.assertTrue(ret, (\\\"Failed to set volume options for volume %s\\\"\\n % self.volname))\\n g.log.info(\\\"Successfully set volume options\\\"\\n \\\"for volume %s\\\", self.volname)\\n\\n # Validate feature.uss enabled or not\\n g.log.info(\\\"Validating feature.uss is enabled\\\")\\n option = \\\"features.uss\\\"\\n vol_option = get_volume_options(self.mnode, self.volname, option)\\n self.assertEqual(vol_option['features.uss'], 'enable', \\\"Failed\\\"\\n \\\" to validate \\\"\\n \\\"volume options\\\")\\n g.log.info(\\\"Successfully validated volume options\\\"\\n \\\"for volume %s\\\", self.volname)\\n\\n # Creating snapshot\\n g.log.info(\\\"Starting to Create snapshot\\\")\\n for snap_count in range(0, 2):\\n ret, _, _ = snap_create(self.mnode, self.volname,\\n \\\"snap%s\\\" % snap_count)\\n self.assertEqual(ret, 0, (\\\"Failed to create snapshot for volume %s\\\"\\n % self.volname))\\n g.log.info(\\\"Snapshot snap%s created successfully\\\"\\n \\\"for volume %s\\\", snap_count, self.volname)\\n\\n # Activating snapshot\\n g.log.info(\\\"Starting to Activate Snapshot\\\")\\n for snap_count in range(0, 2):\\n ret, _, _ = snap_activate(self.mnode, \\\"snap%s\\\" % snap_count)\\n self.assertEqual(ret, 0, (\\\"Failed to Activate snapshot snap%s\\\"\\n % snap_count))\\n g.log.info(\\\"Snapshot snap%s activated successfully\\\", snap_count)\\n\\n # Reset volume:\\n g.log.info(\\\"Starting to Reset Volume\\\")\\n ret, _, _ = volume_reset(self.mnode, self.volname, force=False)\\n self.assertEqual(ret, 0, (\\\"Failed to reset volume %s\\\" % self.volname))\\n g.log.info(\\\"Reset Volume on volume %s is Successful\\\", self.volname)\\n\\n # Validate feature.uss enabled or not\\n g.log.info(\\\"Validating feature.uss is enabled\\\")\\n option = \\\"features.uss\\\"\\n vol_option = get_volume_options(self.mnode, self.volname, option)\\n self.assertEqual(vol_option['features.uss'], 'off', \\\"Failed\\\"\\n \\\" to validate \\\"\\n \\\"volume options\\\")\\n g.log.info(\\\"Successfully validated volume options\\\"\\n \\\"for volume %s\\\", self.volname)\\n\\n # Verify volume's all process are online\\n g.log.info(\\\"Starting to Verify volume's all process are online\\\")\\n ret = verify_all_process_of_volume_are_online(self.mnode, self.volname)\\n self.assertTrue(ret, (\\\"Volume %s : All process are\\\"\\n \\\"not online\\\" % self.volname))\\n g.log.info(\\\"Volume %s : All process are online\\\", self.volname)\\n\\n # Creating and starting a Clone of snapshot\\n g.log.info(\\\"Starting to Clone Snapshot\\\")\\n for clone_count in range(0, 2):\\n ret, _, _ = snap_clone(self.mnode, \\\"snap%s\\\" % clone_count,\\n \\\"clone%s\\\" % clone_count)\\n self.assertEqual(ret, 0, (\\\"Failed to clone clone%s volume\\\"\\n % clone_count))\\n g.log.info(\\\"clone%s volume created successfully\\\", clone_count)\\n\\n # Start Cloned volume\\n g.log.info(\\\"starting to Validate clone volumes are started\\\")\\n for clone_count in range(0, 2):\\n ret, _, _ = volume_start(self.mnode, \\\"clone%s\\\" % clone_count)\\n self.assertEqual(ret, 0, (\\\"Failed to start clone%s\\\"\\n % clone_count))\\n g.log.info(\\\"clone%s started successfully\\\", clone_count)\\n g.log.info(\\\"All the clone volumes are started Successfully\\\")\\n\\n # Validate Volume start of cloned volume\\n g.log.info(\\\"Starting to Validate Volume start\\\")\\n for clone_count in range(0, 2):\\n vol_info = get_volume_info(self.mnode, \\\"clone%s\\\" % clone_count)\\n if vol_info[\\\"clone%s\\\" % clone_count]['statusStr'] != 'Started':\\n raise ExecutionError(\\\"Failed to get volume info for clone%s\\\"\\n % clone_count)\\n g.log.info(\\\"Volume clone%s is in Started state\\\", clone_count)\\n\\n # Validate feature.uss enabled or not\\n g.log.info(\\\"Validating feature.uss is enabled\\\")\\n option = \\\"features.uss\\\"\\n for clone_count in range(0, 2):\\n vol_option = get_volume_options(self.mnode, \\\"clone%s\\\"\\n % clone_count, option)\\n self.assertEqual(vol_option['features.uss'], 'enable', \\\"Failed\\\"\\n \\\" to validate\\\"\\n \\\"volume options\\\")\\n g.log.info(\\\"Successfully validated volume options\\\"\\n \\\"for volume clone%s\\\", clone_count)\\n\\n # Mount both the cloned volumes\\n g.log.info(\\\"Mounting Cloned Volumes\\\")\\n for mount_obj in range(0, 2):\\n self.mpoint = \\\"/mnt/clone%s\\\" % mount_obj\\n cmd = \\\"mkdir -p %s\\\" % self.mpoint\\n ret, _, _ = g.run(self.clients[0], cmd)\\n self.assertEqual(ret, 0, (\\\"Creation of directory %s\\\"\\n \\\"for mounting\\\"\\n \\\"volume %s failed: Directory already\\\"\\n \\\"present\\\"\\n % (self.mpoint, \\\"clone%s\\\" % mount_obj)))\\n g.log.info(\\\"Creation of directory %s for mounting volume %s \\\"\\n \\\"success\\\", self.mpoint, (\\\"clone%s\\\" % mount_obj))\\n ret, _, _ = mount_volume(\\\"clone%s\\\" % mount_obj, self.mount_type,\\n self.mpoint, self.mnode, self.clients[0])\\n self.assertEqual(ret, 0, (\\\"clone%s is not mounted\\\"\\n % mount_obj))\\n g.log.info(\\\"clone%s is mounted Successfully\\\", mount_obj)\\n\\n # Perform I/O on mount\\n # Start I/O on all mounts\\n g.log.info(\\\"Starting to Perform I/O on Mountpoint\\\")\\n all_mounts_procs = []\\n for mount_obj in range(0, 2):\\n cmd = (\\\"cd /mnt/clone%s/; for i in {1..10};\\\"\\n \\\"do touch file$i; done; cd;\\\") % mount_obj\\n proc = g.run(self.clients[0], cmd)\\n all_mounts_procs.append(proc)\\n g.log.info(\\\"I/O on mountpoint is successful\\\")\\n\\n # create snapshot\\n g.log.info(\\\"Starting to Create snapshot of clone volume\\\")\\n ret0, _, _ = snap_create(self.mnode, \\\"clone0\\\", \\\"snap2\\\")\\n self.assertEqual(ret0, 0, \\\"Failed to create the snapshot\\\"\\n \\\"snap2 from clone0\\\")\\n g.log.info(\\\"Snapshots snap2 created successfully from clone0\\\")\\n ret1, _, _ = snap_create(self.mnode, \\\"clone1\\\", \\\"snap3\\\")\\n self.assertEqual(ret1, 0, \\\"Failed to create the snapshot snap3\\\"\\n \\\"from clone1\\\")\\n g.log.info(\\\"Snapshots snap3 created successfully from clone1\\\")\\n\\n # Listing all Snapshots present\\n g.log.info(\\\"Starting to list all snapshots\\\")\\n ret, _, _ = snap_list(self.mnode)\\n self.assertEqual(ret, 0, (\\\"Failed to list snapshots present\\\"))\\n g.log.info(\\\"Snapshots successfully listed\\\")\",\n \"def _verify_cache_volume(self, context, img_meta,\\n img_service, cachevol_props):\\n lcfg = self.configuration\\n cache_dir = '%s/' % lcfg.zfssa_cache_directory\\n cache_vol_obj = Volume()\\n cache_vol_obj.provider_location = self.mount_path + '/' + cache_dir\\n cache_vol_obj._name_id = cachevol_props['id']\\n cachevol_name = cache_dir + cache_vol_obj.name\\n\\n LOG.debug('Verifying cache volume %s:', cachevol_name)\\n\\n try:\\n cache_vol = self.zfssa.get_volume(cachevol_name)\\n except exception.VolumeNotFound:\\n # There is no existing cache volume, create one:\\n LOG.debug('Cache volume not found. Creating one...')\\n return self._create_cache_volume(context,\\n img_meta,\\n img_service,\\n cachevol_props)\\n\\n # A cache volume does exist, check if it's updated:\\n if ((cache_vol['updated_at'] != cachevol_props['updated_at']) or\\n (cache_vol['image_id'] != cachevol_props['image_id'])):\\n if cache_vol['numclones'] > 0:\\n # The cache volume is updated, but has clones\\n exception_msg = (_('Cannot delete '\\n 'cache volume: %(cachevol_name)s. '\\n 'It was updated at %(updated_at)s '\\n 'and currently has %(numclones)d '\\n 'volume instances.'),\\n {'cachevol_name': cachevol_name,\\n 'updated_at': cachevol_props['updated_at'],\\n 'numclones': cache_vol['numclones']})\\n LOG.error(exception_msg)\\n raise exception.VolumeBackendAPIException(data=exception_msg)\\n\\n # The cache volume is updated, but has no clone, so we delete it\\n # and re-create a new one:\\n super(ZFSSANFSDriver, self).delete_volume(cache_vol_obj)\\n return self._create_cache_volume(context,\\n img_meta,\\n img_service,\\n cachevol_props)\\n\\n return cachevol_name\",\n \"def snapshot(self, snapshot, keep=0):\\n if keep:\\n until = util.today() + datetime.timedelta(days=keep)\\n snapshot = snapshot + \\\"-keep-until-\\\" + until.strftime(\\\"%Y%m%d\\\")\\n if snapshot in [x.snapname for x in self.ceph.root.snapshots]:\\n self.log.info(\\\"snapshot-exists\\\", snapshot=snapshot)\\n return\\n self.log.info(\\\"snapshot-create\\\", name=snapshot)\\n with self.frozen_vm() as frozen:\\n if frozen:\\n self.ceph.root.snapshots.create(snapshot)\\n else:\\n self.log.error(\\\"snapshot-ignore\\\", reason=\\\"not frozen\\\")\\n raise RuntimeError(\\\"VM not frozen, not making snapshot.\\\")\",\n \"def test_view_volume(self, volume, volumes_steps):\\n volumes_steps.view_volume(volume.name)\",\n \"def get_volume_snapshots(self, volume):\\n LOG.debug('get_volume_snapshot starts')\\n pool_name = self.configuration.rbd_pool\\n volume_name = 'volume-%s' % encodeutils.safe_encode(volume[\\\"id\\\"])\\n snaps_on_vol = self._get_volume_snapshots(pool_name, volume_name)\\n snapshots = list()\\n if snaps_on_vol is not None:\\n for snap in snaps_on_vol:\\n snap_name = str(snap[\\\"name\\\"])\\n item = dict()\\n if snap_name.startswith(\\\"snapshot-\\\"):\\n # snapshot directly created on volume.\\n item[\\\"type\\\"] = \\\"volume_snap\\\"\\n item[\\\"uuid\\\"] = snap_name[len('snapshot-'):]\\n elif snap_name.startswith(\\\"volume-\\\") and \\\\\\n snap_name.endswith(\\\".clone_snap\\\"):\\n # snapshot used for create volume on volume.\\n item[\\\"type\\\"] = \\\"clone_snap\\\"\\n item[\\\"uuid\\\"] = snap_name[len(\\\"volume-\\\"):-len(\\\".clone_snap\\\")]\\n elif snap_name.startswith(\\\"backup.\\\") and \\\".snap.\\\" in snap_name:\\n # snapshot used for backup volume.\\n item[\\\"type\\\"] = \\\"backup_snap\\\"\\n item[\\\"uuid\\\"] = \\\\\\n snap_name[len(\\\"backup.\\\"):snap_name.index(\\\".snap.\\\")]\\n else:\\n item[\\\"type\\\"] = \\\"\\\"\\n item[\\\"uuid\\\"] = \\\"\\\"\\n snapshots.append(item)\\n\\n LOG.debug('volume snapshots: %s', snapshots)\\n LOG.debug('get_volume_snapshots finished.')\\n return snapshots\",\n \"def test_migrate_volume(self, volume, volumes_steps):\\n old_host, _ = volumes_steps.migrate_volume(volume.name)\\n volumes_steps.migrate_volume(volume.name, old_host)\",\n \"def _assert_source_detached(self, volume):\\n if (volume['status'] != \\\"available\\\" or\\n volume['attach_status'] == fields.VolumeAttachStatus.ATTACHED):\\n LOG.error(\\\"Volume must be detached for clone operation.\\\")\\n raise exception.VolumeAttached(volume_id=volume['id'])\",\n \"def migrate_volume(self, volume, host):\\n false_ret = (False, None)\\n if volume['attach_status'] == fields.VolumeAttachStatus.ATTACHED:\\n return false_ret\\n if 'location_info' not in host['capabilities']:\\n return false_ret\\n info = host['capabilities']['location_info']\\n try:\\n (dest_type, dest_id,\\n dest_back_name, dest_owner) = info.split(':')\\n except ValueError:\\n return false_ret\\n\\n reqd_dest_type = '%sVolumeDriver' % self.vendor_name\\n if not (dest_type == reqd_dest_type and\\n dest_id == self.serialNumber and\\n dest_owner == self.owner):\\n return false_ret\\n if volume['name_id']:\\n source_name = self._get_vol_name(volume['name_id'])\\n else:\\n source_name = self._get_vol_name(volume['id'])\\n # the array does not support duplicate names\\n dest_name = \\\"m%s\\\" % source_name[1:]\\n\\n self.client_login()\\n try:\\n self.client.copy_volume(source_name, dest_name,\\n dest_back_name, self.backend_type)\\n self.client.delete_volume(source_name)\\n self.client.modify_volume_name(dest_name, source_name)\\n return (True, None)\\n except stx_exception.RequestError as ex:\\n LOG.exception(\\\"Error migrating volume: %s\\\", source_name)\\n raise exception.Invalid(ex)\\n finally:\\n self.client_logout()\",\n \"def snapshot_volumes(self) -> pulumi.Input[bool]:\\n return pulumi.get(self, \\\"snapshot_volumes\\\")\",\n \"def test_backup_can_use_snapshots(self):\\n use_snaps = self.driver.backup_use_temp_snapshot()\\n self.assertTrue(use_snaps)\",\n \"def show_volume_snapshot(self, snapshot, check=True):\\n cmd = 'cinder snapshot-show ' + snapshot.id\\n\\n exit_code, stdout, stderr = self.execute_command(\\n cmd, timeout=config.SNAPSHOT_SHOW_TIMEOUT, check=check)\\n\\n snapshot_table = output_parser.table(stdout)\\n show_result = {key: value for key, value in snapshot_table['values']}\\n\\n if check:\\n assert_that(show_result['id'], is_(snapshot.id))\\n if snapshot.name:\\n assert_that(show_result['name'], is_(snapshot.name))\\n if snapshot.description:\\n assert_that(show_result['description'],\\n is_(snapshot.description))\",\n \"def create(self, filesystem=None):\\n if not self.size and not self.from_snapshot_id and not self.from_archive:\\n log.error('Cannot add a {0} volume without a size, snapshot ID or '\\n 'archive url; aborting.'.format(self.fs))\\n return False\\n # If creating the volume from a snaphost, get the expected volume size\\n if self.from_snapshot_id and not self.volume:\\n self.snapshot = self.app.cloud_interface.get_snapshot(self.from_snapshot_id)\\n if not self.snapshot:\\n log.error(\\\"Did not retrieve Snapshot object for {0}; aborting.\\\"\\n .format(self.from_snapshot_id))\\n return False\\n # We need a size to be able to create a volume, so if none\\n # is specified, use snapshot size\\n if not self.size:\\n si = self.app.cloud_interface.get_snapshot_info(self.from_snapshot_id)\\n self.size = si.get('volume_size')\\n # If it does not already exist, create the volume\\n if self.status == volume_status.NONE:\\n log.debug(\\\"Creating a new volume of size '%s' in zone '%s' from \\\"\\n \\\"snapshot '%s' for %s.\\\"\\n % (self.size, self.app.cloud_interface.get_zone(),\\n self.from_snapshot_id, self.fs))\\n self.volume = self.app.cloud_interface.create_volume(\\n self.size,\\n self.app.cloud_interface.get_zone(),\\n snapshot=self.from_snapshot_id)\\n if self.volume:\\n # When creating from a snapshot in Euca, volume.size may be None\\n self.size = int(self.volume.size or 0)\\n log.debug(\\\"Created a new volume of size '%s' from snapshot '%s' \\\"\\n \\\"with ID '%s' in zone '%s' for %s.\\\"\\n % (self.size, self.from_snapshot_id, self.volume_id,\\n self.app.cloud_interface.get_zone(), self.fs))\\n else:\\n log.warning(\\\"No volume object - did not create a volume?\\\")\\n return False\\n else:\\n log.debug(\\\"Tried to create a volume for %s but it is in state '%s' \\\"\\n \\\"(volume ID: %s)\\\" % (self.fs, self.status, self.volume_id))\\n return False\\n # Add tags to newly created volumes (do this outside the inital if/else\\n # to ensure the tags get assigned even if using an existing volume vs.\\n # creating a new one)\\n self.app.cloud_interface.add_tag(\\n self.volume, 'Name', self.app.config['cluster_name'])\\n self.app.cloud_interface.add_tag(\\n self.volume, 'bucketName', self.app.config['bucket_cluster'])\\n if self.fs:\\n self.app.cloud_interface.add_tag(\\n self.volume, 'filesystem', self.fs.get_full_name())\\n self.app.cloud_interface.add_tag(\\n self.volume, 'roles', ServiceRole.to_string(self.fs.svc_roles))\\n return True\",\n \"def test_delete_snapshot(self):\\n ctxt = context.get_admin_context()\\n extra_specs = {}\\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\\n snapshot = {'id': '1', 'name': 'volume1',\\n 'display_name': '',\\n 'volume_type_id': type_ref['id'],\\n 'size': 10,\\n 'provider_id': 'snap10'}\\n self.driver.delete_snapshot(snapshot)\\n expected = {'name': 'snap10'}\\n self.assertDictMatch(expected, self.deleted)\",\n \"def assert_valid_volume(wells,exception_info='invalid volume'):\\n wells = ensure_list(wells)\\n \\n assert all([well.volume >= get_well_dead_volume(well) for well in wells]), exception_info\\n assert all([well.volume <= get_well_max_volume(well) for well in wells]), exception_info\",\n \"def create_snapshot(self, volume_id, notes='No longer needed'):\\r\\n\\r\\n self.iscsi_svc.createSnapshot(notes, id=volume_id)\",\n \"def test_snapshot(self):\\n # Try to create a snapshot with a wrong machine_uuid.\\n status = self.proxy.snapshot.create(\\n PROVIDER_ID, \\\"Doesn't exist\\\"\\n )\\n self.check_xmlrpc_command_result(status, has_error=True)\\n\\n # Try to create a snapshot with a wrong provider.\\n status = self.proxy.snapshot.create(\\n \\\"Doesn't exist\\\", self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status, has_error=True)\\n\\n # Create a snapshot.\\n status = self.proxy.snapshot.create(\\n PROVIDER_ID, self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status)\\n\\n # Try to destroy snapshots with a wrong provider.\\n status = self.proxy.snapshot.destroy(\\n \\\"Doesn't exist\\\", self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status, has_error=True)\\n\\n # Destroy snapshots.\\n status = self.proxy.snapshot.destroy(\\n PROVIDER_ID, self.machine_uuid\\n )\\n self.check_xmlrpc_command_result(status)\",\n \"def test_retype_setup_fail_volume_is_available(self, mock_notify):\\n elevated = context.get_admin_context()\\n project_id = self.context.project_id\\n\\n db.volume_type_create(elevated, {'name': 'old', 'extra_specs': {}})\\n old_vol_type = db.volume_type_get_by_name(elevated, 'old')\\n db.volume_type_create(elevated, {'name': 'new', 'extra_specs': {}})\\n new_vol_type = db.volume_type_get_by_name(elevated, 'new')\\n db.quota_create(elevated, project_id, 'volumes_new', 0)\\n\\n volume = tests_utils.create_volume(self.context, size=1,\\n host=CONF.host, status='available',\\n volume_type_id=old_vol_type['id'])\\n\\n api = cinder.volume.api.API()\\n self.assertRaises(exception.VolumeLimitExceeded, api.retype,\\n self.context, volume, new_vol_type['id'])\\n\\n volume = db.volume_get(elevated, volume.id)\\n # FIXME: restore when Bug #1803648 is figured out\\n # mock_notify.assert_not_called()\\n self.assertEqual('available', volume['status'])\",\n \"def test_live_migration_src_check_volume_node_not_alive(self):\\n\\n instance_id = self._create_instance()\\n i_ref = db.instance_get(self.context, instance_id)\\n dic = {'instance_id': instance_id, 'size': 1}\\n v_ref = db.volume_create(self.context, {'instance_id': instance_id,\\n 'size': 1})\\n t1 = utils.utcnow() - datetime.timedelta(1)\\n dic = {'created_at': t1, 'updated_at': t1, 'binary': 'nova-volume',\\n 'topic': 'volume', 'report_count': 0}\\n s_ref = db.service_create(self.context, dic)\\n\\n self.assertRaises(exception.VolumeServiceUnavailable,\\n self.scheduler.driver.schedule_live_migration,\\n self.context, instance_id, i_ref['host'])\\n\\n db.instance_destroy(self.context, instance_id)\\n db.service_destroy(self.context, s_ref['id'])\\n db.volume_destroy(self.context, v_ref['id'])\",\n \"def test_least_busy_host_gets_volume(self):\\n volume1 = self.start_service('volume', host='host1')\\n volume2 = self.start_service('volume', host='host2')\\n volume_id1 = self._create_volume()\\n volume1.create_volume(self.context, volume_id1)\\n volume_id2 = self._create_volume()\\n host = self.scheduler.driver.schedule_create_volume(self.context,\\n volume_id2)\\n self.assertEqual(host, 'host2')\\n volume1.delete_volume(self.context, volume_id1)\\n db.volume_destroy(self.context, volume_id2)\\n volume1.kill()\\n volume2.kill()\",\n \"def test_attachment_create_volume_in_error_state(self):\\n volume_params = {'status': 'available'}\\n\\n vref = tests_utils.create_volume(self.context, **volume_params)\\n vref.status = \\\"error\\\"\\n self.assertRaises(exception.InvalidVolume,\\n self.volume_api.attachment_create,\\n self.context,\\n vref,\\n fake.UUID2)\",\n \"def create_snapshot(args, **_):\\n\\n volume_id = \\\\\\n utils.get_external_resource_id_or_raise(\\n 'create snapshot', ctx.instance)\\n\\n ctx.logger.info(\\n 'Trying to create a snapshot of EBS volume {0}.'\\n .format(volume_id))\\n\\n volume_object = _get_volumes_from_id(volume_id)\\n\\n if not args:\\n snapshot_desc = \\\\\\n unicode(datetime.datetime.now()) + \\\\\\n ctx.instance.runtime_properties[constants.EXTERNAL_RESOURCE_ID]\\n args = dict(description=snapshot_desc)\\n\\n try:\\n new_snapshot = volume_object.create_snapshot(**args)\\n except (boto.exception.EC2ResponseError,\\n boto.exception.BotoServerError) as e:\\n raise NonRecoverableError('{0}'.format(str(e)))\\n\\n ctx.logger.info(\\n 'Created snapshot of EBS volume {0}.'.format(volume_id))\\n\\n if constants.VOLUME_SNAPSHOT_ATTRIBUTE not in \\\\\\n ctx.instance.runtime_properties:\\n ctx.instance.runtime_properties[\\n constants.VOLUME_SNAPSHOT_ATTRIBUTE] = list()\\n\\n ctx.instance.runtime_properties[\\n constants.VOLUME_SNAPSHOT_ATTRIBUTE].append(new_snapshot.id)\",\n \"def ensure_volume_exists( user_email, opencloud_volume, user=None ):\\n client = connect_syndicate()\\n\\n try:\\n volume = client.read_volume( opencloud_volume.name )\\n except Exception, e:\\n # transport error \\n logger.exception(e)\\n raise e\\n\\n if volume is None:\\n # the volume does not exist....try to create it \\n vol_name = opencloud_volume.name\\n vol_blocksize = opencloud_volume.blocksize\\n vol_description = opencloud_volume.description\\n vol_private = opencloud_volume.private\\n vol_archive = opencloud_volume.archive \\n vol_default_gateway_caps = opencloud_caps_to_syndicate_caps( opencloud_volume.cap_read_data, opencloud_volume.cap_write_data, opencloud_volume.cap_host_data )\\n\\n try:\\n vol_info = client.create_volume( user_email, vol_name, vol_description, vol_blocksize,\\n private=vol_private,\\n archive=vol_archive,\\n active=True,\\n default_gateway_caps=vol_default_gateway_caps,\\n store_private_key=False,\\n metadata_private_key=\\\"MAKE_METADATA_KEY\\\" )\\n\\n except Exception, e:\\n # transport error\\n logger.exception(e)\\n raise e\\n\\n else:\\n # successfully created the volume!\\n return vol_info\\n\\n else:\\n \\n # volume already exists. Verify its owned by this user.\\n if user is None:\\n try:\\n user = client.read_user( volume['owner_id'] )\\n except Exception, e:\\n # transport error, or user doesn't exist (either is unacceptable)\\n logger.exception(e)\\n raise e\\n\\n if user is None or user['email'] != user_email:\\n raise Exception(\\\"Volume '%s' already exists, but is NOT owned by '%s'\\\" % (opencloud_volume.name, user_email) )\\n\\n # we're good!\\n return None\",\n \"def resource_type(self):\\n return 'volume-snapshot'\",\n \"def test_aws_service_api_volume_get(self):\\n pass\",\n \"def test_snapshot_compatibility(microvm_factory, guest_kernel, rootfs):\\n vm = microvm_factory.build(guest_kernel, rootfs)\\n vm.spawn()\\n vm.basic_config(\\n vcpu_count=2,\\n mem_size_mib=256,\\n )\\n\\n # Add a memory balloon with stats enabled.\\n vm.api.balloon.put(amount_mib=0, deflate_on_oom=True, stats_polling_interval_s=1)\\n\\n vm.start()\\n vm.snapshot_full()\",\n \"def snap_status(mnode, snapname=\\\"\\\", volname=\\\"\\\"):\\n\\n if snapname != \\\"\\\" and volname != \\\"\\\":\\n g.log.error(\\\"Incorrect cmd. snap status cli accepts either \\\"\\n \\\"snapname or volname\\\")\\n return (-1, None, None)\\n\\n if volname != '':\\n volname = \\\"volume %s\\\" % volname\\n\\n cmd = \\\"gluster snapshot status %s %s\\\" % (snapname, volname)\\n return g.run(mnode, cmd)\",\n \"def test_present_wo_existing_volumes():\\n docker_create_volume = Mock(return_value=\\\"created\\\")\\n docker_remove_volume = Mock(return_value=\\\"removed\\\")\\n __salt__ = {\\n \\\"docker.create_volume\\\": docker_create_volume,\\n \\\"docker.remove_volume\\\": docker_remove_volume,\\n \\\"docker.volumes\\\": Mock(return_value={\\\"Volumes\\\": None}),\\n }\\n with patch.dict(docker_state.__dict__, {\\\"__salt__\\\": __salt__}):\\n ret = docker_state.present(\\n \\\"volume_foo\\\",\\n driver=\\\"bar\\\",\\n force=True,\\n )\\n docker_create_volume.assert_called_with(\\n \\\"volume_foo\\\", driver=\\\"bar\\\", driver_opts=None\\n )\\n assert ret == {\\n \\\"name\\\": \\\"volume_foo\\\",\\n \\\"comment\\\": \\\"\\\",\\n \\\"changes\\\": {\\\"created\\\": \\\"created\\\"},\\n \\\"result\\\": True,\\n }\",\n \"def _wait_until_volume_available(self, volume, maybe_in_use=False):\\n ok_states = [\\\"creating\\\"] # it's ok to wait if the volume is in this\\n tries = 0\\n if maybe_in_use:\\n ok_states.append(\\\"in_use\\\")\\n logger.info(\\\"Volume: %s is in state: %s\\\", volume.name, volume.state)\\n while volume.state in ok_states:\\n sleep(3)\\n volume = self.get_volume(volume.name)\\n tries = tries + 1\\n if tries > 10:\\n logger.info(\\\"Maximum amount of tries reached..\\\")\\n break\\n if volume.state == \\\"notfound\\\":\\n logger.error(\\\"no volume was found for: %s\\\", volume.name)\\n break\\n logger.info(\\\" ... %s\\\", volume.state)\\n if volume.state != \\\"available\\\":\\n # OVH uses a non-standard state of 3 to indicate an available\\n # volume\\n logger.info(\\\"Volume %s is %s (not available)\\\", volume.name, volume.state)\\n logger.info(\\n \\\"The volume %s is not available, but will continue anyway...\\\",\\n volume.name,\\n )\\n return True\",\n \"def create_snapshot(volume_name, volume_id):\\n\\tif cliargs.verbose:\\n\\t\\tprint \\\"Will snapshot '%s' and tag it with '%s'\\\" % (volume_id, volume_name)\\n\\n\\tresponse = ec2.create_snapshot(VolumeId=volume_id, Description=volume_name)\\n\\tif response:\\n\\t\\tec2.create_tags(Resources=[response[\\\"SnapshotId\\\"]], Tags=[{\\\"Key\\\": \\\"Name\\\", \\\"Value\\\": volume_name}])\",\n \"def test_aws_service_api_volume_patch(self):\\n pass\",\n \"def _create_snapshot(connection, volume, name=''):\\n logging.info(kayvee.formatLog(\\\"ebs-snapshots\\\", \\\"info\\\", \\\"creating new snapshot\\\", {\\\"volume\\\": volume.id}))\\n snapshot = volume.create_snapshot(\\n description=\\\"automatic snapshot by ebs-snapshots\\\")\\n if not name:\\n name = '{}-snapshot'.format(volume.id)\\n connection.create_tags(\\n [snapshot.id], dict(Name=name, creator='ebs-snapshots'))\\n logging.info(kayvee.formatLog(\\\"ebs-snapshots\\\", \\\"info\\\", \\\"created snapshot successfully\\\", {\\n \\\"name\\\": name,\\n \\\"volume\\\": volume.id,\\n \\\"snapshot\\\": snapshot.id\\n }))\\n return snapshot\",\n \"def issnapshot_available(self, item_name):\\n return False\",\n \"def get_snapshots(vol_name):\\n\\n l = None\\n try:\\n cmd = 'gluster snapshot info volume %s --xml' % vol_name\\n d, err = xml_parse.run_gluster_command(cmd)\\n if err:\\n raise Exception(err)\\n if d:\\n if d[\\\"op_status\\\"][\\\"op_ret\\\"] == 0:\\n l, err = xml_parse.get_snapshots(d[\\\"root\\\"])\\n if err:\\n raise Exception(err)\\n except Exception, e:\\n return None, 'Error getting volume snapshots: %s' % str(e)\\n else:\\n return l, None\",\n \"def sync_volume_record( volume ):\\n \\n logger.info( \\\"Sync Volume = %s\\\\n\\\\n\\\" % volume.name )\\n \\n principal_id = volume.owner_id.email\\n config = observer_core.get_config()\\n \\n max_UGs = None \\n max_RGs = None\\n volume_principal_id = observer_core.make_volume_principal_id( principal_id, volume.name )\\n\\n # get the observer secret \\n try:\\n max_UGs = CONFIG.SYNDICATE_UG_QUOTA \\n max_RGs = CONFIG.SYNDICATE_RG_QUOTA\\n observer_secret = observer_core.get_syndicate_observer_secret( config.SYNDICATE_OBSERVER_SECRET )\\n except Exception, e:\\n traceback.print_exc()\\n logger.error(\\\"config is missing SYNDICATE_OBSERVER_SECRET, SYNDICATE_UG_QUOTA, SYNDICATE_RG_QUOTA\\\")\\n raise e\\n \\n # volume owner must exist as a Syndicate user...\\n try:\\n rc, user = observer_core.ensure_principal_exists( volume_principal_id, observer_secret, is_admin=False, max_UGs=max_UGs, max_RGs=max_RGs)\\n assert rc == True, \\\"Failed to create or read volume principal '%s'\\\" % volume_principal_id\\n except Exception, e:\\n traceback.print_exc()\\n logger.error(\\\"Failed to ensure principal '%s' exists\\\" % volume_principal_id )\\n raise e\\n\\n # volume must exist \\n # create or update the Volume\\n try:\\n new_volume = observer_core.ensure_volume_exists( volume_principal_id, volume, user=user )\\n except Exception, e:\\n traceback.print_exc()\\n logger.error(\\\"Failed to ensure volume '%s' exists\\\" % volume.name )\\n raise e\\n \\n # did we create the Volume?\\n if new_volume is not None:\\n # we're good\\n pass \\n \\n # otherwise, just update it \\n else:\\n try:\\n rc = observer_core.update_volume( volume )\\n except Exception, e:\\n traceback.print_exc()\\n logger.error(\\\"Failed to update volume '%s', exception = %s\\\" % (volume.name, e.message))\\n raise e\\n \\n return True\",\n \"def _tag_volume():\\n if dry:\\n print('Would tag the new volume.')\\n return True\\n\\n while True:\\n # waiting for the volume to be up to tag it\\n i = _fetch('vm')\\n v = [x for x in i.volumes.all()]\\n if len(v) == 0:\\n # volumes should actually be already there once the IP is up\\n time.sleep(1)\\n else:\\n for x in v:\\n print('Tagging volume ' + x.id + '.')\\n _tag_resource(x)\\n break\",\n \"def test_least_busy_host_gets_volume_no_queue(self):\\n volume1 = service.Service('host1',\\n 'nova-volume',\\n 'volume',\\n FLAGS.volume_manager)\\n volume1.start()\\n volume2 = service.Service('host2',\\n 'nova-volume',\\n 'volume',\\n FLAGS.volume_manager)\\n volume2.start()\\n volume_id1 = self._create_volume()\\n volume1.create_volume(self.context, volume_id1)\\n volume_id2 = self._create_volume()\\n host = self.scheduler.driver.schedule_create_volume(self.context,\\n volume_id2)\\n self.assertEqual(host, 'host2')\\n volume1.delete_volume(self.context, volume_id1)\\n db.volume_destroy(self.context, volume_id2)\",\n \"def test_create_volume(self, mock_ghn):\\n ctxt = context.get_admin_context()\\n extra_specs = {}\\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\\n volume = {'id': '1', 'name': 'volume1',\\n 'display_name': '',\\n 'volume_type_id': type_ref['id'],\\n 'size': 10}\\n ret = self.driver.create_volume(volume)\\n expected = {'redundancy': '0', 'group': 'xanadu',\\n 'name': 'volume10', 'mode': '0777',\\n 'user': 'kane', 'net': 'net1',\\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\\n 'size': '12'}\\n self.assertDictMatch(expected, self.created)\\n # Check the returned provider, note that provider_id is hashed\\n expected_pid = {'provider_id': 'volume10'}\\n self.assertDictMatch(expected_pid, ret)\",\n \"def test_volume():\\n structure = Material(input)\\n assert (structure.volume == 90.725624999999965)\",\n \"def create_volume(self, snapshot_id = \\\"\\\", size = -1):\\n response = volume.create_volume(self.url, self.verb,\\n self.headers, self.version,\\n snapshot_id, size)\\n if response is not None :\\n res = CreateVolumeResponse.CreateVolumeResponse()\\n parseString(str(response.text), res)\\n return res\\n else :\\n return None\",\n \"def test_csi_volumesnapshot_basic(set_random_backupstore, # NOQA\\n volumesnapshotclass, # NOQA\\n volumesnapshot, # NOQA\\n client, # NOQA\\n core_api, # NOQA\\n volume_name, # NOQA\\n csi_pv, # NOQA\\n pvc, # NOQA\\n pod_make, # NOQA\\n volsnapshotclass_delete_policy, # NOQA\\n backup_is_deleted): # NOQA\\n\\n csisnapclass = \\\\\\n volumesnapshotclass(name=\\\"snapshotclass\\\",\\n deletepolicy=volsnapshotclass_delete_policy)\\n\\n pod_name, pv_name, pvc_name, md5sum = \\\\\\n prepare_pod_with_data_in_mb(client, core_api,\\n csi_pv, pvc, pod_make,\\n volume_name,\\n data_path=\\\"/data/test\\\")\\n\\n # Create volumeSnapshot test\\n csivolsnap = volumesnapshot(volume_name + \\\"-volumesnapshot\\\",\\n \\\"default\\\",\\n csisnapclass[\\\"metadata\\\"][\\\"name\\\"],\\n \\\"persistentVolumeClaimName\\\",\\n pvc_name)\\n\\n volume = client.by_id_volume(volume_name)\\n\\n for i in range(RETRY_COUNTS):\\n snapshots = volume.snapshotList()\\n if len(snapshots) == 2:\\n break\\n time.sleep(RETRY_INTERVAL)\\n\\n lh_snapshot = None\\n snapshots = volume.snapshotList()\\n for snapshot in snapshots:\\n if snapshot[\\\"name\\\"] == \\\"snapshot-\\\" + csivolsnap[\\\"metadata\\\"][\\\"uid\\\"]:\\n lh_snapshot = snapshot\\n assert lh_snapshot is not None\\n\\n wait_for_volumesnapshot_ready(csivolsnap[\\\"metadata\\\"][\\\"name\\\"],\\n csivolsnap[\\\"metadata\\\"][\\\"namespace\\\"])\\n\\n bv1, b = find_backup(client, volume_name, lh_snapshot[\\\"name\\\"])\\n\\n assert b[\\\"snapshotName\\\"] == lh_snapshot[\\\"name\\\"]\\n\\n restore_pvc_name = pvc[\\\"metadata\\\"][\\\"name\\\"] + \\\"-restore\\\"\\n restore_pvc_size = pvc[\\\"spec\\\"][\\\"resources\\\"][\\\"requests\\\"][\\\"storage\\\"]\\n\\n restore_csi_volume_snapshot(core_api,\\n client,\\n csivolsnap,\\n restore_pvc_name,\\n restore_pvc_size)\\n\\n restore_pod = pod_make()\\n restore_pod_name = restore_pod[\\\"metadata\\\"][\\\"name\\\"]\\n restore_pod['spec']['volumes'] = [create_pvc_spec(restore_pvc_name)]\\n\\n create_and_wait_pod(core_api, restore_pod)\\n restore_md5sum = \\\\\\n get_pod_data_md5sum(core_api, restore_pod_name, path=\\\"/data/test\\\")\\n assert restore_md5sum == md5sum\\n\\n # Delete volumeSnapshot test\\n delete_volumesnapshot(csivolsnap[\\\"metadata\\\"][\\\"name\\\"], \\\"default\\\")\\n\\n if backup_is_deleted is False:\\n find_backup(client, volume_name, b[\\\"snapshotName\\\"])\\n else:\\n wait_for_backup_delete(client, volume_name, b[\\\"name\\\"])\",\n \"def database_volume_snapshot_delete(volume_snapshot_uuid):\\n db = database_get()\\n session = db.session()\\n query = session.query(model.VolumeSnapshot)\\n query.filter(model.VolumeSnapshot.uuid == volume_snapshot_uuid).delete()\\n session.commit()\",\n \"def ensure_export(self, context, volume):\\n pass\",\n \"def _is_booted_from_volume(self, instance, disk_mapping=None):\\n return not bool(instance.get('image_ref'))\",\n \"def create_snapshot(self, snapshot):\\n vg_name = self.get_volume_group_name(snapshot.volume_id)\\n snap_name = self.get_snap_name(snapshot.id)\\n rpolicy = self.get_policy()\\n try:\\n LOG.debug(\\\"Searching volume_group: %s in K2.\\\", vg_name)\\n vg = self.client.search(\\\"volume_groups\\\", name=vg_name).hits[0]\\n LOG.debug(\\\"Creating a snapshot: %(snap)s from vg: %(vg)s\\\",\\n {'snap': snap_name, 'vg': vg_name})\\n self.client.new(\\\"snapshots\\\", short_name=snap_name,\\n source=vg, retention_policy=rpolicy,\\n is_auto_deleteable=False).save()\\n except Exception as ex:\\n LOG.exception(\\\"Creation of snapshot: %s failed.\\\", snap_name)\\n raise KaminarioCinderDriverException(reason=ex)\",\n \"def manage(self, volume_id, ref, name=None, description=None,\\n metadata=None):\\n body = {'snapshot': {'volume_id': volume_id,\\n 'ref': ref,\\n 'name': name,\\n 'description': description,\\n 'metadata': metadata\\n }\\n }\\n return self._create('/os-snapshot-manage', body, 'snapshot')\",\n \"def _create_snapshot(self, name=None, metadata=None):\\n req = fakes.HTTPRequest.blank('/v3/snapshots')\\n req.environ['cinder.context'] = self.ctx\\n snap = {\\\"volume_id\\\": fake.VOLUME_ID,\\n \\\"display_name\\\": name or \\\"Volume Test Name\\\",\\n \\\"description\\\": \\\"Volume Test Desc\\\"\\n }\\n if metadata:\\n snap[\\\"metadata\\\"] = metadata\\n body = {\\\"snapshot\\\": snap}\\n self.controller.create(req, body=body)\",\n \"def test_attachment_update_volume_in_error_state(self):\\n volume_params = {'status': 'available'}\\n\\n vref = tests_utils.create_volume(self.context, **volume_params)\\n aref = self.volume_api.attachment_create(self.context,\\n vref,\\n fake.UUID2)\\n self.assertEqual(fake.UUID2, aref.instance_uuid)\\n self.assertIsNone(aref.attach_time)\\n self.assertEqual('reserved', aref.attach_status)\\n self.assertEqual(vref.id, aref.volume_id)\\n self.assertEqual({}, aref.connection_info)\\n vref.status = 'error'\\n vref.save()\\n connector = {'fake': 'connector',\\n 'host': 'somehost'}\\n self.assertRaises(exception.InvalidVolume,\\n self.volume_api.attachment_update,\\n self.context,\\n aref,\\n connector)\",\n \"def create_snapshot(self, context, volume_id, snapshot_id):\\n\\n context = context.elevated()\\n snapshot_ref = self.db.snapshot_get(context, snapshot_id)\\n display_name = snapshot_ref['display_name']\\n display_description = snapshot_ref['display_description']\\n LOG.info(_(\\\"snapshot %s: creating\\\"), snapshot_ref['id'])\\n\\n self._notify_about_snapshot_usage(\\n context, snapshot_ref, \\\"create.start\\\")\\n\\n vol_ref = self.db.volume_get(context, volume_id)\\n LOG.info(_(\\\"Cascade info: create snapshot while cascade id is:%s\\\"),\\n vol_ref['mapping_uuid'])\\n\\n try:\\n vol_ref = self.db.volume_get(context, volume_id)\\n casecaded_volume_id = vol_ref['mapping_uuid']\\n cinderClient = self._get_cinder_cascaded_user_client(context)\\n bodyResponse = cinderClient.volume_snapshots.create(\\n volume_id=casecaded_volume_id,\\n force=False,\\n name=display_name,\\n description=display_description)\\n\\n LOG.info(_(\\\"Cascade info: create snapshot while response is:%s\\\"),\\n bodyResponse._info)\\n if bodyResponse._info['status'] == 'creating':\\n self._heal_snapshot_mapping_cache(snapshot_id,\\n bodyResponse._info['id'],\\n \\\"add\\\")\\n self.db.snapshot_update(\\n context,\\n snapshot_ref['id'],\\n {'mapping_uuid': bodyResponse._info['id']})\\n\\n except Exception:\\n with excutils.save_and_reraise_exception():\\n self.db.snapshot_update(context,\\n snapshot_ref['id'],\\n {'status': 'error'})\\n return\\n\\n self.db.snapshot_update(context,\\n snapshot_ref['id'], {'status': 'available',\\n 'progress': '100%'})\\n# vol_ref = self.db.volume_get(context, volume_id)\\n\\n if vol_ref.bootable:\\n try:\\n self.db.volume_glance_metadata_copy_to_snapshot(\\n context, snapshot_ref['id'], volume_id)\\n except exception.CinderException as ex:\\n LOG.exception(_(\\\"Failed updating %(snapshot_id)s\\\"\\n \\\" metadata using the provided volumes\\\"\\n \\\" %(volume_id)s metadata\\\") %\\n {'volume_id': volume_id,\\n 'snapshot_id': snapshot_id})\\n raise exception.MetadataCopyFailure(reason=ex)\\n\\n LOG.info(_(\\\"Cascade info: snapshot %s, created successfully\\\"),\\n snapshot_ref['id'])\\n self._notify_about_snapshot_usage(context, snapshot_ref, \\\"create.end\\\")\\n\\n return snapshot_id\",\n \"def create_cloned_volume(self, volume, src_vref):\\n # Form the snapshot structure.\\n snapshot = {'id': uuid.uuid4().__str__(),\\n 'volume_id': src_vref['id'],\\n 'volume': src_vref}\\n\\n # Create snapshot.\\n self.create_snapshot(snapshot)\\n\\n try:\\n # Create volume from snapshot.\\n lun_info = self.create_volume_from_snapshot(volume, snapshot)\\n finally:\\n try:\\n # Delete snapshot.\\n self.delete_snapshot(snapshot)\\n except exception.VolumeBackendAPIException:\\n LOG.warning(_LW(\\n 'Failure deleting the snapshot %(snapshot_id)s '\\n 'of volume %(volume_id)s.'),\\n {'snapshot_id': snapshot['id'],\\n 'volume_id': src_vref['id']},)\\n\\n return {'provider_location': lun_info['ID'],\\n 'lun_info': lun_info}\",\n \"def bootable_volume(volumes):\\n for volume in volumes:\\n if '/dev/vda' in volume['attachments']:\\n return volume\",\n \"def volume_exists(vil, vol_name):\\n\\n exists = False\\n try:\\n if not vil:\\n vil, err = get_basic_volume_info_all()\\n if err:\\n raise Exception(err)\\n if vil:\\n for v in vil:\\n if v[\\\"name\\\"] == vol_name:\\n exists = True\\n except Exception, e:\\n return False, 'Error checking for volume existance : %s' % str(e)\\n else:\\n return exists, None\",\n \"def create_snapshot(self, snap_description=None):\\n log.debug(\\\"Initiating creation of a snapshot for volume '%s'\\\" % self.volume_id)\\n try:\\n snapshot = self.volume.create_snapshot(description=snap_description)\\n log.info(\\\"Created snapshot {0} from volume {1} ({2}). Check the snapshot \\\"\\n \\\"for status.\\\".format(snapshot.id, self.volume_id, self.fs))\\n self._derived_snapshots.append(snapshot)\\n # Add tags to the newly created snapshot\\n self.app.cloud_interface.add_tag(snapshot, 'Name',\\n self.app.config['cluster_name'])\\n self.app.cloud_interface.add_tag(\\n self.volume, 'bucketName', self.app.config['bucket_cluster'])\\n self.app.cloud_interface.add_tag(self.volume, 'filesystem', self.fs.name)\\n return str(snapshot.id)\\n except EC2ResponseError as ex:\\n log.error(\\\"Error creating a snapshot from volume '%s': %s\\\" %\\n (self.volume_id, ex))\\n return None\",\n \"def create_snapshot(self, snapshot):\\n LOG.info(_LI('Creating snapshot: %s'), snapshot['name'])\\n lcfg = self.configuration\\n snap_name = self._create_snapshot_name()\\n self.zfssa.create_snapshot(lcfg.zfssa_nfs_pool, lcfg.zfssa_nfs_project,\\n lcfg.zfssa_nfs_share, snap_name)\\n\\n src_file = snap_name + '/' + snapshot['volume_name']\\n\\n try:\\n self.zfssa.create_snapshot_of_volume_file(src_file=src_file,\\n dst_file=\\n snapshot['name'])\\n except Exception:\\n with excutils.save_and_reraise_exception():\\n LOG.debug('Error thrown during snapshot: %s creation',\\n snapshot['name'])\\n finally:\\n self.zfssa.delete_snapshot(lcfg.zfssa_nfs_pool,\\n lcfg.zfssa_nfs_project,\\n lcfg.zfssa_nfs_share, snap_name)\",\n \"def test_edit_volume(self, volume, volumes_steps):\\n new_name = volume.name + ' (updated)'\\n with volume.put(name=new_name):\\n volumes_steps.edit_volume(volume_name=volume.name,\\n new_volume_name=new_name)\",\n \"def _create_volume(self):\\n vol = {}\\n vol['size'] = 1\\n vol['availability_zone'] = 'test'\\n return db.volume_create(self.context, vol)['id']\",\n \"def ensure_volume_absent( volume_name ):\\n\\n client = connect_syndicate()\\n\\n # this is idempotent, and returns True even if the Volume doesn't exist\\n return client.delete_volume( volume_name )\",\n \"def find_recovery_on_volume(volume):\\n return _find(volume, RECOVERY_ON_VOLUME_TABLE)\",\n \"def __mount_ebs_volume( self ):\\n ebs_volume_size = self.instance_tag( 'ebs_volume_size' ) or '0'\\n ebs_volume_size = int( ebs_volume_size )\\n if ebs_volume_size:\\n instance_name = self.instance_tag( 'Name' )\\n cluster_ordinal = int( self.instance_tag( 'cluster_ordinal' ) )\\n volume_name = '%s__%d' % (instance_name, cluster_ordinal)\\n volume = EC2VolumeHelper( ec2=self.ec2,\\n availability_zone=self.availability_zone,\\n name=volume_name,\\n size=ebs_volume_size,\\n volume_type=\\\"gp2\\\" )\\n # TODO: handle case where volume is already attached\\n device_ext = '/dev/sdf'\\n device = '/dev/xvdf'\\n volume.attach( self.instance_id, device_ext )\\n\\n # Wait for inode to appear and make sure its a block device\\n while True:\\n try:\\n assert stat.S_ISBLK( os.stat( device ).st_mode )\\n break\\n except OSError as e:\\n if e.errno == errno.ENOENT:\\n time.sleep( 1 )\\n else:\\n raise\\n\\n # Only format empty volumes\\n volume_label = volume_label_hash( volume_name )\\n if check_output( [ 'file', '-sL', device ] ).strip( ) == device + ': data':\\n check_call( [ 'mkfs', '-t', 'ext4', device ] )\\n check_call( [ 'e2label', device, volume_label ] )\\n else:\\n # If the volume is not empty, verify the file system label\\n actual_label = check_output( [ 'e2label', device ] ).strip( )\\n if actual_label != volume_label:\\n raise AssertionError(\\n \\\"Expected volume label '%s' (derived from '%s') but got '%s'\\\" %\\n (volume_label, volume_name, actual_label) )\\n current_mount_point = self.__mount_point( device )\\n if current_mount_point is None:\\n mkdir_p( self.persistent_dir )\\n check_call( [ 'mount', device, self.persistent_dir ] )\\n elif current_mount_point == self.persistent_dir:\\n pass\\n else:\\n raise RuntimeError(\\n \\\"Can't mount device %s on '%s' since it is already mounted on '%s'\\\" % (\\n device, self.persistent_dir, current_mount_point) )\\n else:\\n # No persistent volume is attached and the root volume is off limits, so we will need\\n # to place persistent data on the ephemeral volume.\\n self.persistent_dir = self.ephemeral_dir\",\n \"def _volume_command(ramp, volume):\\n if volume is not None:\\n ramp.set_volume(float(volume))\\n else:\\n print ramp.volume\",\n \"def test_pvresize_not_pv():\\n pvdisplay = MagicMock(return_value=False)\\n with patch(\\\"salt.modules.linux_lvm.pvdisplay\\\", pvdisplay):\\n assert linux_lvm.pvresize(\\\"A\\\", override=False) == \\\"A is not a physical volume\\\"\\n\\n pvdisplay = MagicMock(return_value=False)\\n with patch(\\\"salt.modules.linux_lvm.pvdisplay\\\", pvdisplay):\\n assert linux_lvm.pvresize(\\\"A\\\") is True\",\n \"def vol_up_and_validate(self):\\n self.logger.info('Increasing volume')\\n before_vol = self.dut.volume('Up', 1)\\n time.sleep(2)\\n after_vol = self.dut.volume('Up', 1)\\n if not after_vol or not before_vol or after_vol <= before_vol:\\n self.logger.error(\\n 'Unable to increase the volume. Before: %s. After: %s' %\\n (before_vol, after_vol))\\n raise TestActsError('error increasing volume')\",\n \"def test_update_volume_stats_error(self):\\n self._fail_host_storage = True\\n actual = self.driver.get_volume_stats(True)\\n self.assertEqual('HGST', actual['vendor_name'])\\n self.assertEqual('hgst', actual['storage_protocol'])\\n self.assertEqual('unknown', actual['total_capacity_gb'])\\n self.assertEqual('unknown', actual['free_capacity_gb'])\\n self.assertEqual(0, actual['reserved_percentage'])\",\n \"def test_attachment_create_creating_volume(self):\\n volume_params = {'status': 'creating'}\\n\\n vref = tests_utils.create_volume(self.context, **volume_params)\\n self.assertRaises(exception.InvalidVolume,\\n self.volume_api.attachment_create,\\n self.context,\\n vref,\\n fake.UUID1)\",\n \"def cli(env, snapshot_id):\\n block_manager = SoftLayer.BlockStorageManager(env.client)\\n deleted = block_manager.delete_snapshot(snapshot_id)\\n\\n if deleted:\\n click.echo('Snapshot %s deleted' % snapshot_id)\",\n \"def database_volume_snapshot_add(volume_snapshot_obj):\\n db = database_get()\\n session = db.session()\\n query = session.query(model.VolumeSnapshot)\\n query = query.filter(model.VolumeSnapshot.uuid == volume_snapshot_obj.uuid)\\n volume_snapshot = query.first()\\n if not volume_snapshot:\\n volume_snapshot = model.VolumeSnapshot()\\n volume_snapshot.uuid = volume_snapshot_obj.uuid\\n volume_snapshot.name = volume_snapshot_obj.name\\n volume_snapshot.description = volume_snapshot_obj.description\\n volume_snapshot.size_gb = volume_snapshot_obj.size_gb\\n volume_snapshot.volume_uuid = volume_snapshot_obj.volume_uuid\\n volume_snapshot.nfvi_volume_snapshot_data = \\\\\\n json.dumps(volume_snapshot_obj.nfvi_volume_snapshot.as_dict())\\n session.add(volume_snapshot)\\n else:\\n volume_snapshot.name = volume_snapshot_obj.name\\n volume_snapshot.description = volume_snapshot_obj.description\\n volume_snapshot.size_gb = volume_snapshot_obj.size_gb\\n volume_snapshot.volume_uuid = volume_snapshot_obj.volume_uuid\\n volume_snapshot.nfvi_volume_snapshot_data = \\\\\\n json.dumps(volume_snapshot_obj.nfvi_volume_snapshot.as_dict())\\n db.commit()\",\n \"def load_snapshot_halos(base_path, snap_num, subvolumes, fields=None, matches=False):\\n return load_snapshot(base_path, snap_num, subvolumes, \\\"Haloprop\\\", fields, matches)\",\n \"def load_volume(self, volume_path, series_uid):\\n if volume_path is None:\\n return False, 'Volume data is None.'\\n\\n im = read_image(volume_path)\\n\\n # manage volume data in a dictionary\\n self.volumes[series_uid] = im\\n # init config info of this volume\\n self.configs[series_uid] = {}\\n self.configs[series_uid]['size'] = [512, 512, 57]\\n self.configs[series_uid]['center'] = im.center()\\n self.configs[series_uid]['cursor'] = im.center()\\n self.configs[series_uid]['spacing'] = im.spacing() # [1, 1, 1]\\n self.configs[series_uid]['zoom_factor'] = 1\\n self.configs[series_uid]['win_center'] = 0\\n self.configs[series_uid]['win_width'] = 2000\\n self.configs[series_uid]['colormode'] = 0\\n self.configs[series_uid]['alpha'] = 1\\n self.configs[series_uid]['default_v'] = -1024\\n self.configs[series_uid]['transverse_axis'] = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]\\n self.configs[series_uid]['saggital_axis'] = [[0, 1, 0], [0, 0, -1], [1, 0, 0]]\\n self.configs[series_uid]['coronal_axis'] = [[1, 0, 0], [0, 0, -1], [0, 1, 0]]\\n\\n # switch current volume to this volume\\n self.change_volume(series_uid)\\n\\n self.look_at['transverse'] = im.center()\\n self.look_at['coronal'] = im.center()\\n self.look_at['saggital'] = im.center()\\n\\n return True, 'Load succeed.'\",\n \"def test_create_volume_blocked(self, mock_ghn):\\n ctxt = context.get_admin_context()\\n extra_specs = {}\\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\\n volume = {'id': '1', 'name': 'volume1',\\n 'display_name': '',\\n 'volume_type_id': type_ref['id'],\\n 'size': 10}\\n self._return_blocked = 1 # Block & fail cancel => create succeeded\\n ret = self.driver.create_volume(volume)\\n expected = {'redundancy': '0', 'group': 'xanadu',\\n 'name': 'volume10', 'mode': '0777',\\n 'user': 'kane', 'net': 'net1',\\n 'storageserver': 'stor1:gbd0,stor2:gbd0,',\\n 'size': '12'}\\n self.assertDictMatch(expected, self.created)\\n # Check the returned provider\\n expected_pid = {'provider_id': 'volume10'}\\n self.assertDictMatch(expected_pid, ret)\\n self.assertTrue(self._request_cancel)\",\n \"def test_migrate_volume_driver(self):\\n # Mock driver and rpc functions\\n self.mock_object(self.volume.driver, 'migrate_volume',\\n lambda x, y, z, new_type_id=None: (\\n True, {'user_id': fake.USER_ID}))\\n\\n volume = tests_utils.create_volume(ctxt=self.context, size=0,\\n host=CONF.host,\\n migration_status='migrating')\\n host_obj = {'host': 'newhost', 'capabilities': {}}\\n self.volume.migrate_volume(self.context, volume, host_obj, False)\\n\\n # check volume properties\\n volume = objects.Volume.get_by_id(context.get_admin_context(),\\n volume.id)\\n self.assertEqual('newhost', volume.host)\\n self.assertEqual('success', volume.migration_status)\",\n \"def verify_no_snapshot_reingestion(c: Composition) -> None:\\n c.run(\\\"testdrive\\\", \\\"wait-for-snapshot.td\\\", \\\"postgres-disable-select-permission.td\\\")\\n\\n restart_mz(c)\\n\\n c.run(\\n \\\"testdrive\\\",\\n \\\"delete-rows-t1.td\\\",\\n \\\"delete-rows-t2.td\\\",\\n \\\"alter-table.td\\\",\\n \\\"alter-mz.td\\\",\\n )\",\n \"def test_update_volume_stats_cached(self):\\n self._fail_host_storage = True\\n actual = self.driver.get_volume_stats(False)\\n self.assertEqual('HGST', actual['vendor_name'])\\n self.assertEqual('hgst', actual['storage_protocol'])\\n self.assertEqual(90, actual['total_capacity_gb'])\\n self.assertEqual(87, actual['free_capacity_gb'])\\n self.assertEqual(0, actual['reserved_percentage'])\",\n \"def create_cloned_volume(self, volume, src_vref):\\n LOG.info('Creating clone of volume: %s', src_vref['id'])\\n snapshot = {'volume_name': src_vref['name'],\\n 'volume_id': src_vref['id'],\\n 'volume_size': src_vref['size'],\\n 'name': self._get_clone_snapshot_name(volume)}\\n # We don't delete this snapshot, because this snapshot will be origin\\n # of new volume. This snapshot will be automatically promoted by NMS\\n # when user will delete its origin.\\n self.create_snapshot(snapshot)\\n try:\\n return self.create_volume_from_snapshot(volume, snapshot)\\n except utils.NexentaException:\\n LOG.error('Volume creation failed, deleting created snapshot '\\n '%(volume_name)s@%(name)s', snapshot)\\n try:\\n self.delete_snapshot(snapshot)\\n except (utils.NexentaException, exception.SnapshotIsBusy):\\n LOG.warning('Failed to delete zfs snapshot '\\n '%(volume_name)s@%(name)s', snapshot)\\n raise\",\n \"def test_finish_resize_with_volumes(self):\\n\\n # create instance\\n instance = self._create_fake_instance_obj()\\n request_spec = objects.RequestSpec()\\n\\n # create volume\\n volume = {'instance_uuid': None,\\n 'device_name': None,\\n 'id': uuids.volume,\\n 'size': 200,\\n 'attach_status': 'detached'}\\n bdm = objects.BlockDeviceMapping(\\n **{'context': self.context,\\n 'source_type': 'volume',\\n 'destination_type': 'volume',\\n 'volume_id': uuids.volume,\\n 'instance_uuid': instance['uuid'],\\n 'device_name': '/dev/vdc'})\\n bdm.create()\\n\\n # stub out volume attach\\n def fake_volume_get(self, context, volume_id, microversion=None):\\n return volume\\n self.stub_out('nova.volume.cinder.API.get', fake_volume_get)\\n\\n def fake_volume_check_availability_zone(self, context,\\n volume_id, instance):\\n pass\\n self.stub_out('nova.volume.cinder.API.check_availability_zone',\\n fake_volume_check_availability_zone)\\n\\n def fake_get_volume_encryption_metadata(self, context, volume_id):\\n return {}\\n self.stub_out('nova.volume.cinder.API.get_volume_encryption_metadata',\\n fake_get_volume_encryption_metadata)\\n\\n orig_connection_data = {\\n 'target_discovered': True,\\n 'target_iqn': 'iqn.2010-10.org.openstack:%s.1' % uuids.volume_id,\\n 'target_portal': '127.0.0.0.1:3260',\\n 'volume_id': uuids.volume_id,\\n }\\n connection_info = {\\n 'driver_volume_type': 'iscsi',\\n 'data': orig_connection_data,\\n }\\n\\n def fake_init_conn(self, context, volume_id, session):\\n return connection_info\\n self.stub_out('nova.volume.cinder.API.initialize_connection',\\n fake_init_conn)\\n\\n def fake_attach(self, context, volume_id, instance_uuid, device_name,\\n mode='rw'):\\n volume['instance_uuid'] = instance_uuid\\n volume['device_name'] = device_name\\n self.stub_out('nova.volume.cinder.API.attach', fake_attach)\\n\\n # stub out virt driver attach\\n def fake_get_volume_connector(*args, **kwargs):\\n return {}\\n self.stub_out('nova.virt.fake.FakeDriver.get_volume_connector',\\n fake_get_volume_connector)\\n\\n def fake_attach_volume(*args, **kwargs):\\n pass\\n self.stub_out('nova.virt.fake.FakeDriver.attach_volume',\\n fake_attach_volume)\\n\\n # attach volume to instance\\n self.compute.attach_volume(self.context, instance, bdm)\\n\\n # assert volume attached correctly\\n self.assertEqual(volume['device_name'], '/dev/vdc')\\n disk_info = db.block_device_mapping_get_all_by_instance(\\n self.context, instance.uuid)\\n self.assertEqual(len(disk_info), 1)\\n for bdm in disk_info:\\n self.assertEqual(bdm['device_name'], volume['device_name'])\\n self.assertEqual(bdm['connection_info'],\\n jsonutils.dumps(connection_info))\\n\\n # begin resize\\n flavor = self.default_flavor\\n instance.task_state = task_states.RESIZE_PREP\\n instance.save()\\n self.compute.prep_resize(self.context, instance=instance,\\n flavor=flavor,\\n image={}, request_spec=request_spec,\\n filter_properties={}, node=None,\\n clean_shutdown=True, migration=None,\\n host_list=[])\\n\\n # fake out detach for prep_resize (and later terminate)\\n def fake_terminate_connection(self, context, volume, connector):\\n connection_info['data'] = None\\n self.stub_out('nova.volume.cinder.API.terminate_connection',\\n fake_terminate_connection)\\n\\n migration = objects.Migration.get_by_instance_and_status(\\n self.context.elevated(),\\n instance.uuid, 'pre-migrating')\\n self.compute.resize_instance(self.context, instance=instance,\\n migration=migration, image={},\\n # TODO(stephenfin): Why a JSON string?\\n flavor=jsonutils.to_primitive(flavor),\\n clean_shutdown=True, request_spec=request_spec)\\n\\n # assert bdm is unchanged\\n disk_info = db.block_device_mapping_get_all_by_instance(\\n self.context, instance.uuid)\\n self.assertEqual(len(disk_info), 1)\\n for bdm in disk_info:\\n self.assertEqual(bdm['device_name'], volume['device_name'])\\n cached_connection_info = jsonutils.loads(bdm['connection_info'])\\n self.assertEqual(cached_connection_info['data'],\\n orig_connection_data)\\n # but connection was terminated\\n self.assertIsNone(connection_info['data'])\\n\\n # stub out virt driver finish_migration\\n def fake(*args, **kwargs):\\n pass\\n self.stub_out('nova.virt.fake.FakeDriver.finish_migration', fake)\\n\\n instance.task_state = task_states.RESIZE_MIGRATED\\n instance.save()\\n\\n # new initialize connection\\n new_connection_data = dict(orig_connection_data)\\n new_iqn = 'iqn.2010-10.org.openstack:%s.2' % uuids.volume_id,\\n new_connection_data['target_iqn'] = new_iqn\\n\\n def fake_init_conn_with_data(self, context, volume, session):\\n connection_info['data'] = new_connection_data\\n return connection_info\\n self.stub_out('nova.volume.cinder.API.initialize_connection',\\n fake_init_conn_with_data)\\n\\n self.compute.finish_resize(self.context,\\n migration=migration,\\n disk_info={}, image={}, instance=instance,\\n request_spec=request_spec)\\n\\n # assert volume attached correctly\\n disk_info = db.block_device_mapping_get_all_by_instance(\\n self.context, instance['uuid'])\\n self.assertEqual(len(disk_info), 1)\\n for bdm in disk_info:\\n self.assertEqual(bdm['connection_info'],\\n jsonutils.dumps(connection_info))\\n\\n # stub out detach\\n def fake_detach(self, context, volume_uuid):\\n volume['device_path'] = None\\n volume['instance_uuid'] = None\\n self.stub_out('nova.volume.cinder.API.detach', fake_detach)\\n\\n # clean up\\n self.compute.terminate_instance(self.context, instance, [])\",\n \"def snapcheck(self, data, pre_file=None, dev=None, local=False, folder=None):\\n if pre_file is None:\\n pre_file = \\\"snap_temp\\\"\\n self.snap_del = True\\n return self.action_api_based(\\n dev, data, pre_file, \\\"snapcheck\\\", folder, local=local\\n )\",\n \"def test_csi_volumesnapshot_restore_existing_backup(set_random_backupstore, # NOQA\\n client, # NOQA\\n core_api, # NOQA\\n volume_name, # NOQA\\n csi_pv, # NOQA\\n pvc, # NOQA\\n pod_make, # NOQA\\n volumesnapshotclass, # NOQA\\n volumesnapshotcontent,\\n volumesnapshot, # NOQA\\n volsnapshotclass_delete_policy, # NOQA\\n backup_is_deleted): # NOQA\\n csisnapclass = \\\\\\n volumesnapshotclass(name=\\\"snapshotclass\\\",\\n deletepolicy=volsnapshotclass_delete_policy)\\n\\n pod_name, pv_name, pvc_name, md5sum = \\\\\\n prepare_pod_with_data_in_mb(client, core_api,\\n csi_pv, pvc, pod_make,\\n volume_name,\\n data_path=\\\"/data/test\\\")\\n\\n volume = client.by_id_volume(volume_name)\\n snap = create_snapshot(client, volume_name)\\n volume.snapshotBackup(name=snap.name)\\n wait_for_backup_completion(client, volume_name, snap.name)\\n bv, b = find_backup(client, volume_name, snap.name)\\n\\n csivolsnap_name = volume_name + \\\"-volumesnapshot\\\"\\n csivolsnap_namespace = \\\"default\\\"\\n\\n volsnapcontent = \\\\\\n volumesnapshotcontent(\\\"volsnapcontent\\\",\\n csisnapclass[\\\"metadata\\\"][\\\"name\\\"],\\n \\\"Delete\\\",\\n \\\"bs://\\\" + volume_name + \\\"/\\\" + b.name,\\n csivolsnap_name,\\n csivolsnap_namespace)\\n\\n csivolsnap = volumesnapshot(csivolsnap_name,\\n csivolsnap_namespace,\\n csisnapclass[\\\"metadata\\\"][\\\"name\\\"],\\n \\\"volumeSnapshotContentName\\\",\\n volsnapcontent[\\\"metadata\\\"][\\\"name\\\"])\\n\\n restore_pvc_name = pvc[\\\"metadata\\\"][\\\"name\\\"] + \\\"-restore\\\"\\n restore_pvc_size = pvc[\\\"spec\\\"][\\\"resources\\\"][\\\"requests\\\"][\\\"storage\\\"]\\n\\n restore_csi_volume_snapshot(core_api,\\n client,\\n csivolsnap,\\n restore_pvc_name,\\n restore_pvc_size)\\n\\n restore_pod = pod_make()\\n restore_pod_name = restore_pod[\\\"metadata\\\"][\\\"name\\\"]\\n restore_pod['spec']['volumes'] = [create_pvc_spec(restore_pvc_name)]\\n\\n create_and_wait_pod(core_api, restore_pod)\\n restore_md5sum = \\\\\\n get_pod_data_md5sum(core_api, restore_pod_name, path=\\\"/data/test\\\")\\n\\n assert restore_md5sum == md5sum\\n\\n # Delete volumeSnapshot test\\n delete_volumesnapshot(csivolsnap[\\\"metadata\\\"][\\\"name\\\"], \\\"default\\\")\\n\\n if backup_is_deleted is False:\\n find_backup(client, volume_name, b[\\\"snapshotName\\\"])\\n else:\\n wait_for_backup_delete(client, volume_name, b[\\\"name\\\"])\",\n \"def creation_validation(**_):\\n\\n for property_key in constants.VOLUME_REQUIRED_PROPERTIES:\\n utils.validate_node_property(property_key, ctx.node.properties)\\n\\n volume_object = _get_volumes_from_id(utils.get_resource_id())\\n\\n if ctx.node.properties['use_external_resource'] and not volume_object:\\n raise NonRecoverableError(\\n 'External resource, but the supplied '\\n 'EBS volume does not exist in the account.')\\n\\n if not ctx.node.properties['use_external_resource'] and volume_object:\\n raise NonRecoverableError(\\n 'Not external resource, but the supplied '\\n 'EBS volume exists in the account.')\",\n \"def test_07_migrate_vm_live_with_snapshots(self):\\n global vm\\n # Get ROOT Volume\\n vol_for_snap = list_volumes(\\n self.apiclient,\\n virtualmachineid=vm.id,\\n listall=True)\\n for vol in vol_for_snap:\\n snapshot = Snapshot.create(\\n self.apiclient,\\n volume_id=vol.id\\n )\\n snapshot.validateState(\\n self.apiclient,\\n snapshotstate=\\\"backedup\\\",\\n )\\n # Migrate all volumes and VMs\\n\\n destinationHost, vol_list = self.helper.get_destination_pools_hosts(self.apiclient, vm, self.host)\\n for v in vol_list:\\n self.helper.check_storpool_volume_iops(self.spapi, v)\\n vm = self.helper.migrateVm(self.apiclient, self.virtual_machine_live_migration_1, destinationHost)\\n\\n destinationHost, vol_list = self.helper.get_destination_pools_hosts(self.apiclient, vm, self.host)\\n for v in vol_list:\\n self.helper.check_storpool_volume_iops(self.spapi, v)\",\n \"def migrate_volume(self, ctxt, volume_id, host, force_host_copy=False):\\n return\",\n \"def test_volumes_get(self):\\n pass\",\n \"def update_volume( opencloud_volume ):\\n\\n client = connect_syndicate()\\n\\n vol_name = opencloud_volume.name\\n vol_description = opencloud_volume.description\\n vol_private = opencloud_volume.private\\n vol_archive = opencloud_volume.archive\\n vol_default_gateway_caps = opencloud_caps_to_syndicate_caps( opencloud_volume.cap_read_data, opencloud_volume.cap_write_data, opencloud_volume.cap_host_data )\\n\\n try:\\n rc = client.update_volume( vol_name,\\n description=vol_description,\\n private=vol_private,\\n archive=vol_archive,\\n default_gateway_caps=vol_default_gateway_caps )\\n\\n if not rc:\\n raise Exception(\\\"update_volume(%s) failed!\\\" % vol_name )\\n\\n except Exception, e:\\n # transort or method error \\n logger.exception(e)\\n return False\\n\\n else:\\n return True\",\n \"def migrate_volume(self, ctxt, volume, host, new_type=None):\\n return self._migrate_volume(volume, host, new_type)\",\n \"def test_aws_service_api_volume_attachment_put(self):\\n pass\",\n \"def manage_existing_snapshot(self, snapshot, existing_ref):\\n\\n old_snap_name = existing_ref['source-name']\\n new_snap_name = self._get_snap_name(snapshot.id)\\n LOG.info(\\\"Renaming existing snapshot %(old_name)s to \\\"\\n \\\"%(new_name)s\\\", {\\\"old_name\\\": old_snap_name,\\n \\\"new_name\\\": new_snap_name})\\n\\n self.client_login()\\n try:\\n self.client.modify_volume_name(old_snap_name,\\n new_snap_name)\\n except stx_exception.RequestError as ex:\\n LOG.exception(\\\"Error managing existing snapshot.\\\")\\n raise exception.Invalid(ex)\\n finally:\\n self.client_logout()\\n\\n return None\",\n \"def check_volume(vol, srf_names, verbose=True):\\n if verbose:\\n print(\\\" checking volume for validity\\\")\\n print(\\\" ----------------------------\\\")\\n # check if dict\\n if not isinstance(vol, dict):\\n if verbose:\\n print(\\\" vol is not of type dict\\\")\\n return False\\n # check for keys in gli dict\\n in_vol_keys = set(vol)\\n if in_vol_keys == VOL_KEYS:\\n if verbose:\\n print(\\\" vol keys are valid\\\")\\n else:\\n if verbose:\\n print(\\\" vol keys are not valid!\\\")\\n print(\\\" needs: \\\" + \\\" \\\".join(VOL_KEYS))\\n print(\\\" found: \\\" + \\\" \\\".join(map(str, in_vol_keys)))\\n print(\\\" missing: \\\" + \\\" \\\".join(map(str, VOL_KEYS - in_vol_keys)))\\n print(\\\" corrupted: \\\" + \\\" \\\".join(map(str, in_vol_keys - VOL_KEYS)))\\n return False\\n # check NAME\\n if (\\n isinstance(vol[\\\"NAME\\\"], STRTYPE)\\n and not has_whitespaces(vol[\\\"NAME\\\"])\\n and len(vol[\\\"NAME\\\"]) > 0\\n ):\\n if verbose:\\n print(\\\" vol['NAME'] valid\\\")\\n print(\\\" NAME: '\\\" + vol[\\\"NAME\\\"] + \\\"'\\\")\\n else:\\n if verbose:\\n print(\\\" vol['NAME'] not valid\\\")\\n return False\\n # check SURFACES\\n if (\\n isinstance(vol[\\\"SURFACES\\\"], list)\\n and len(vol[\\\"SURFACES\\\"]) > 0\\n and all(srf in srf_names for srf in vol[\\\"SURFACES\\\"])\\n ):\\n if verbose:\\n print(\\\" vol['SURFACES'] valid\\\")\\n else:\\n if verbose:\\n print(\\\" vol['SURFACES'] not valid\\\")\\n return False\\n # check TYPE\\n if vol[\\\"TYPE\\\"] is None or isinstance(vol[\\\"TYPE\\\"], int):\\n if verbose:\\n print(\\\" vol['TYPE'] valid\\\")\\n else:\\n if verbose:\\n print(\\\" vol['TYPE'] not valid\\\")\\n return False\\n # check MAT_GROUP\\n if vol[\\\"MAT_GROUP\\\"] is None or isinstance(vol[\\\"MAT_GROUP\\\"], int):\\n if verbose:\\n print(\\\" vol['MAT_GROUP'] valid\\\")\\n else:\\n if verbose:\\n print(\\\" vol['MAT_GROUP'] not valid\\\")\\n return False\\n # check LAYER\\n if vol[\\\"LAYER\\\"] is None or isinstance(vol[\\\"LAYER\\\"], int):\\n if verbose:\\n print(\\\" vol['LAYER'] valid\\\")\\n else:\\n if verbose:\\n print(\\\" vol['LAYER'] not valid\\\")\\n return False\\n # finally\\n if verbose:\\n print(\\\" ------------\\\")\\n print(\\\" vol is valid\\\")\\n print(\\\"\\\")\\n return True\",\n \"def test_change_volume_status(self, volume, volumes_steps):\\n volumes_steps.change_volume_status(volume.name, 'Error')\\n volumes_steps.change_volume_status(volume.name, 'Available')\",\n \"def test_absolute_volume(self):\\n\\n assert self.test_shape.volume() == pytest.approx(50 * 60 * math.pi * 2 * 1000)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.72817236","0.68085235","0.6774093","0.67722756","0.67518574","0.66919476","0.66683424","0.66099256","0.6593119","0.6561201","0.64276564","0.64078516","0.64017785","0.63788575","0.63636637","0.6321371","0.62975985","0.62808114","0.6255119","0.62545985","0.624078","0.6208396","0.6205359","0.61692315","0.61349237","0.61243236","0.60962516","0.60812366","0.6075888","0.60354286","0.60068023","0.6001154","0.5987496","0.5985551","0.59716","0.59467435","0.5920929","0.59184635","0.59168786","0.5907889","0.58900654","0.5878496","0.58648455","0.5862296","0.58516186","0.5835566","0.5827114","0.5822892","0.5820384","0.5812561","0.5803726","0.57922274","0.57739615","0.575548","0.5750399","0.5744503","0.57391334","0.57220304","0.57087123","0.5693878","0.56638074","0.5661062","0.56378406","0.56362015","0.56302965","0.5629835","0.5627713","0.5619122","0.5612684","0.5596079","0.5582384","0.5576846","0.55742097","0.55638933","0.55614763","0.55566055","0.55560887","0.55554456","0.5547882","0.5544607","0.55423754","0.55363446","0.5533889","0.5523204","0.55230457","0.5515317","0.55137175","0.55091125","0.5507382","0.5504859","0.5504477","0.5489282","0.5486404","0.54848385","0.54795855","0.5476927","0.5473603","0.54712784","0.54697126","0.54679656"],"string":"[\n \"0.72817236\",\n \"0.68085235\",\n \"0.6774093\",\n \"0.67722756\",\n \"0.67518574\",\n \"0.66919476\",\n \"0.66683424\",\n \"0.66099256\",\n \"0.6593119\",\n \"0.6561201\",\n \"0.64276564\",\n \"0.64078516\",\n \"0.64017785\",\n \"0.63788575\",\n \"0.63636637\",\n \"0.6321371\",\n \"0.62975985\",\n \"0.62808114\",\n \"0.6255119\",\n \"0.62545985\",\n \"0.624078\",\n \"0.6208396\",\n \"0.6205359\",\n \"0.61692315\",\n \"0.61349237\",\n \"0.61243236\",\n \"0.60962516\",\n \"0.60812366\",\n \"0.6075888\",\n \"0.60354286\",\n \"0.60068023\",\n \"0.6001154\",\n \"0.5987496\",\n \"0.5985551\",\n \"0.59716\",\n \"0.59467435\",\n \"0.5920929\",\n \"0.59184635\",\n \"0.59168786\",\n \"0.5907889\",\n \"0.58900654\",\n \"0.5878496\",\n \"0.58648455\",\n \"0.5862296\",\n \"0.58516186\",\n \"0.5835566\",\n \"0.5827114\",\n \"0.5822892\",\n \"0.5820384\",\n \"0.5812561\",\n \"0.5803726\",\n \"0.57922274\",\n \"0.57739615\",\n \"0.575548\",\n \"0.5750399\",\n \"0.5744503\",\n \"0.57391334\",\n \"0.57220304\",\n \"0.57087123\",\n \"0.5693878\",\n \"0.56638074\",\n \"0.5661062\",\n \"0.56378406\",\n \"0.56362015\",\n \"0.56302965\",\n \"0.5629835\",\n \"0.5627713\",\n \"0.5619122\",\n \"0.5612684\",\n \"0.5596079\",\n \"0.5582384\",\n \"0.5576846\",\n \"0.55742097\",\n \"0.55638933\",\n \"0.55614763\",\n \"0.55566055\",\n \"0.55560887\",\n \"0.55554456\",\n \"0.5547882\",\n \"0.5544607\",\n \"0.55423754\",\n \"0.55363446\",\n \"0.5533889\",\n \"0.5523204\",\n \"0.55230457\",\n \"0.5515317\",\n \"0.55137175\",\n \"0.55091125\",\n \"0.5507382\",\n \"0.5504859\",\n \"0.5504477\",\n \"0.5489282\",\n \"0.5486404\",\n \"0.54848385\",\n \"0.54795855\",\n \"0.5476927\",\n \"0.5473603\",\n \"0.54712784\",\n \"0.54697126\",\n \"0.54679656\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6775116"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81764,"cells":{"query":{"kind":"string","value":"Get the custom argument names and their defaults for this callbacks object."},"document":{"kind":"string","value":"def args_map_custom(cls) -> dict:\n args = {}\n args.update(cls.args_map_export())\n args.update({\"json_flat\": False})\n return args"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_defaults(self):\n default_dict = {}\n args, varargs, keyword, defaults = inspect.getargspec(self.exec_obj)\n if defaults:\n default_dict = dict(zip(args[-len(defaults):], defaults))\n return default_dict","def _default_arguments(self, obj):\n \n if not (inspect.isfunction(obj) or inspect.ismethod(obj)):\n # for classes, check for __init__,__new__\n if inspect.isclass(obj):\n obj = (getattr(obj,'__init__',None) or\n getattr(obj,'__new__',None))\n # for all others, check if they are __call__able\n elif hasattr(obj, '__call__'):\n obj = obj.__call__\n # XXX: is there a way to handle the builtins ?\n try:\n args,_,_1,defaults = inspect.getargspec(obj)\n if defaults:\n return args[-len(defaults):]\n except TypeError: pass\n return []","def _get_init_args(self):\n\n return dict(enum=self.enum, dflt=self._defname,\n base=self.base, shape=self.shape)","def names(self):\n result = []\n result.extend(self.positional_arguments)\n if self.arbitary_positional_arguments is not None:\n result.append(self.arbitary_positional_arguments)\n if self.arbitary_keyword_arguments is not None:\n result.append(self.arbitary_keyword_arguments)\n result.extend(self.keyword_arguments)\n return result","def arg_names(self):\n return self._arg_names","def arg_names(self):\n return self._arg_names","def get_xx_args_dict(self):\n return self.__xx_args","def get_additional_hook_arguments(\n self,\n path_manager: PathManager,\n extra_arguments: Optional[Dict[str, str]] = None,\n ) -> List[str]:","def get_mandatory_arguments(self):\n args, varargs, keyword, defaults = inspect.getargspec(self.exec_obj)\n\n if defaults is not None:\n args = args[:-len(defaults)]\n\n if args.count('self') > 0:\n args.remove('self')\n return args","def _invocation_params(self) -> Dict[str, Any]:\n return self._default_params","def _make_args(self, args, defaults=[], vararg=None, kwonlyargs=[],\n kw_defaults=[], kwarg=None):\n # On Python 2 convert vararg and kwarg to raw name, raise error using\n # lineno stored on the node and lexer from self.\n # On Python 3.3 extract name and annotation\n # After should be straight forward\n raise NotImplementedError()","def _get_param_names(self):\r\n return sorted([p\r\n for p in self.__dict__\r\n if p != 'additional_args'])","def get_kwargs():\n\treturn get_kwargs_raw(sys.argv)","def get_x_args_dict(self):\n return self.__x_args","def __getinitargs__(self):\n\n return (self.name, self.value)","def get_arguments(callable, exclude):\n info = arginfo(callable)\n defaults = info.defaults or []\n defaults = [None] * (len(info.args) - len(defaults)) + list(defaults)\n return {name: default for (name, default) in zip(info.args, defaults)\n if name not in exclude}","def args(self) -> tuple[Basic, ...]:\n return self._args","def getPositionalArgs():","def _get_init_args(self):\n signature = inspect.signature(self.__init__)\n parameters = signature.parameters\n args = [arg for arg, p in parameters.items()\n if p.kind is p.POSITIONAL_OR_KEYWORD]\n\n return {arg: getattr(self, arg) for arg in args if arg != 'self'}","def getargspec(self,obj):\n\n if inspect.isfunction(obj):\n func_obj = obj\n elif inspect.ismethod(obj):\n func_obj = obj.im_func\n else:\n raise TypeError, 'arg is not a Python function'\n args, varargs, varkw = inspect.getargs(func_obj.func_code)\n return args, varargs, varkw, func_obj.func_defaults","def get_args(self):\r\n return self.args","def _get_param_names(self):\n temp_params = {'function': self.function, 'target': self.target}\n\n temp_params.update(self.kwargs)\n\n return temp_params","def get_parameters(self):\n params = {}\n for p in self.DEFAULT_VALUES.keys():\n params[p] = getattr(self, p)\n return params","def pykwarg(self):\n return self._pykwarg","def get_init_arguments_and_types(cls) -> List[Tuple[str, Tuple, Any]]:\n trainer_default_params = inspect.signature(cls).parameters\n name_type_default = []\n for arg in trainer_default_params:\n arg_type = trainer_default_params[arg].annotation\n arg_default = trainer_default_params[arg].default\n try:\n arg_types = tuple(arg_type.__args__)\n except AttributeError:\n arg_types = (arg_type,)\n\n name_type_default.append((arg, arg_types, arg_default))\n\n return name_type_default","def getRequiredArguments(self):\n if self._initValue.needsArgument:\n return [self._initValue.getArgument()]\n else:\n return []","def SaveCustomDefaults(self, *args, **kwargs):\n # type: (*Any, **Any) -> None\n payload = { \"Arg1\": self }\n for i in range(len(args)): payload['Arg%s' % (i + 2)] = args[i]\n for item in kwargs.items(): payload[item[0]] = item[1]\n return self._execute('saveCustomDefaults', payload=payload, response_object=None)","def __get_arguments(args=None, logger=None, stats=None):\n\n if not args:\n parser = get_parser()\n add_boto_cli_arguments(parser)\n # Parse only the known arguments added by add_boto_cli_arguments().\n # We only need those arguments to create Boto object, nothing else.\n # parse_known_args() return (Namespace, list of unknown arguments),\n # we only care about the Namespace object here.\n args = parser.parse_known_args()[0]\n\n if not logger:\n logger = get_logger(name=NAME)\n\n if not stats:\n stats = get_stats(prefix=NAME)\n\n return {\n 'log_level': getattr(args, 'boto_log_level', DEFAULT['log_level']()),\n 'access_key': getattr(args, 'boto_access_key', DEFAULT['access_key']()),\n 'secret_key': getattr(args, 'boto_secret_key', DEFAULT['secret_key']()),\n 'region': getattr(args, 'boto_region', DEFAULT['region']()),\n 'logger': logger,\n 'stats': stats,\n }","def get(self):\n return self.args, self.kwargs","def args(cls):\n try:\n args = getfullargspec(cls.__init__)\n except TypeError:\n return []\n return args[0]","def parameters(self) -> Dict[str, Any]:\n return self.data[\"args\"].get(\"parameters\", {})","def args(self):\n\t\tret = []\n\t\tfor argname in self._arg_names:\n\t\t\tret += [self._args[argname]]\n\t\treturn ret","def args(self) -> List[str]:\n return self.__args","def get_all_arguments(self):\n args, varargs, keyword, defaults = inspect.getargspec(self.exec_obj)\n if args.count('self') > 0:\n args.remove('self')\n return args","def func_args(self) -> str:\n\n return self.call_data[10:]","def extra_args(self):\n return []","def base_arguments(self):\n raise NotImplementedError()","def get_default_args(func):\n signature = inspect.signature(func)\n return {\n k: v.default\n for k, v in signature.parameters.items()\n if v.default is not inspect.Parameter.empty\n }","def argnames(self):\n if self.get_key is None:\n return set()\n return set(self.get_key.names)","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def args(self) -> Optional[Sequence[str]]:\n return pulumi.get(self, \"args\")","def get_helper_c_code_args(self):\r\n return Subtensor.default_helper_c_code_args()","def _get_function_defaults(func: FunctionType) -> dict[str, Any]:\n # extracted bit from inspect.signature... ~20x faster\n pos_count = func.__code__.co_argcount\n arg_names = func.__code__.co_varnames\n\n defaults = func.__defaults__ or ()\n\n non_default_count = pos_count - len(defaults)\n positional_args = arg_names[:pos_count]\n\n output = {\n name: defaults[offset]\n for offset, name in enumerate(positional_args[non_default_count:])\n }\n if func.__kwdefaults__:\n output.update(func.__kwdefaults__)\n return output","def argdict(self):\n return dict((arg.name, val) for arg, val in zip(self.sig, self))","def get_json_argument_list():\n list_of_arguments_to_get = [\"finish_time\", \"segmentation_training_samples\", \"patch_count_per_image\", \"learning_rate\", \"batch_k\",\n \"batch_p\", \"flip_augment\", \"standardize\", \"margin\", \"metric\"]\n\n return list_of_arguments_to_get","def as_kwargs(self) -> Dict[str, Any]:\n ret = {}\n for arg in self.args.values():\n ret[arg.name] = arg.value\n return ret","def get_default_args(**kw):\n default_args_log = {\n \"output_file\": \"POLY.c\",\n \"function_name\": \"POLY\",\n \"precision\": ML_Binary64,\n \"target\": GenericProcessor.get_target_instance(),\n \"function\": None,\n \"interval\": None,\n \"epsilon\": None\n }\n default_args_log.update(kw)\n return DefaultArgTemplate(**default_args_log)","def args(self):\n return self._parse_args","def inspect_args_func(frame):\n args, _, _, values = inspect.getargvalues(frame)\n return {key: values[key] for key in args if key != 'self'}","def argument_list(self):\n answer = self._call('argument_list')\n return answer.names","def preprocess_arguments(self, *args, **kwargs):\n return (args, kwargs)","def get_custom_hook_names():\n return list(_CUSTOM_HOOKS)","def defaultargs(options):\n config = {}\n for longname, default, _ in options:\n config[longname] = default\n return config","def init_json_args(cls):\n defaults = cls._base_json_args()\n\n if cls.__json_args__ is None:\n cls.__json_args__ = defaults\n else:\n cls.__json_args__ = mapping_extend(defaults, cls.__json_args__)","def args(self):\n return self._args","def args(self):\n return self._args","def args(self):\n return self._args","def args(self) -> Optional[str]:\n return pulumi.get(self, \"args\")","def getcallback(cls, cmd, arg):\n return [dict({'cmd': cmd, 'arg': arg, 'ret': None})]","def _params(self, **kwargs):\n defaults = {'display_name': 'Test User',\n 'locale': 'en-us',\n 'country': 'us'}\n defaults.update(kwargs)\n\n return defaults","def _get_reproducing_arguments(self):\n reproducing_arguments = {\n 'include': self.include,\n 'exclude': self.exclude,\n 'copy': self.copy,\n }\n args_names = {name: getattr(self, name) for name in self.args_names}\n reproducing_arguments.update(args_names)\n return reproducing_arguments","def gen_args(self, obj, pa_names = False):\n\n pal, kwal = get_class_total_args(type(obj))\n\n try:\n get_val = type(obj).__get_init_arg_val__\n except AttributeError:\n get_val = getattr\n\n for pa in pal:\n v = get_val(obj, pa)\n self.gen_field((pa + \" = \") if pa_names else \"\")\n self.pprint(v)\n\n for kwa, default in kwal.items():\n try:\n v = get_val(obj, kwa)\n except AttributeError:\n # If value cannot be obtained, skip the argument generation\n continue\n\n # generate only arguments with non-default values\n if (v is default) or (v == default):\n continue\n\n self.gen_field(kwa + \" = \")\n self.pprint(v)","def get_mandatory_args(self):\n raise NotImplementedError(\"ICallable.get_mandatory_args\")","def __loadDefaultArgs(self):\n mod = self.__class__.__name__.lower()\n logger.debug(\"Loading default args for module: %s\" % mod)\n\n default_args = conf.get(\"modules.%s\" % mod, None)\n if not default_args:\n return\n for k, v in default_args.iteritems():\n logger.debug(\"Setting default %s arg: %s=%s\" % (mod, k, v))\n self.setArg(k, v)","def parameter_names(self) -> List[str]:","def getArgs(func):\n # exclude the defaults at the end (hence the [:-1])\n args = list(utils.flatten(inspect.getargspec(func)[:-1]))\n return set(args).difference(set([None]))","def parse_known_args(self):\n args, other_args = self.parser.parse_known_args()\n args = self.__process_args__(args)\n return args, other_args","def get_additional_arguments(obj):\n args = ''\n\n try:\n # If the object has arguments parse them to a string and replace the values from the lookup table\n if obj.args:\n # Parse the list to a string\n args = ' '.join(obj.args)\n\n # Replace the items in the string with entries from the lookup table\n for k, v in config.lookup_table:\n args = args.replace(k, v)\n\n # Reset the args in the object to reset its state\n obj.args = None\n except AttributeError:\n # No additional args present so we can just skip the parsing\n pass\n\n return args","def get_partial_arguments(self):\n return (), {}","def get_cli_arguments(self):\n pass","def args(self):\n if not self.arg_names:\n return []\n modes = self.arg_modes or [\"i\"] * len(self.arg_names)\n args = [\n (name, typ)\n for name, typ, mode in zip(self.arg_names, self.arg_types, modes)\n if mode in (\"i\", \"b\", \"v\") # IN, INOUT, VARIADIC\n ]\n\n def arg(name, typ, num):\n num_args = len(args)\n num_defaults = len(self.arg_defaults)\n has_default = num + num_defaults >= num_args\n default = (\n self.arg_defaults[num - num_args + num_defaults]\n if has_default\n else None\n )\n return ColumnMetadata(name, typ, [], default, has_default)\n\n return [arg(name, typ, num) for num, (name, typ) in enumerate(args)]","def _getArg(self,synonyms,args,default=None):\n value = None\n if (type(synonyms) != type([])):\n synonyms = Utilities.splitString(synonyms)\n #endIf\n\n for name in synonyms:\n value = args.get(name)\n if (value != None):\n break\n #endIf\n #endFor\n\n if (value == None and default != None):\n value = default\n #endIf\n\n return value","def get_arguments(self):\n args = self.parser.parse_args()\n config = None\n with open(args.config_file, \"r\") as f:\n config = json.load(f)\n\n if \"collections\" in config:\n if len(config[\"collections\"]) > 0:\n collection = config[\"collections\"][0]\n if \"collection_name\" in collection:\n self.collection_name = collection[\"collection_name\"]\n else:\n raise AttributeError(\n \"'collection_name' not present in 'collections'!\"\n )\n self.slack_channel = collection[\"slack_channel\"]\n else:\n raise AttributeError(\n \"No 'collections' details found in config_file!\"\n )\n else:\n raise AttributeError(\"'collections' not present in config_file!\")\n\n if \"postman_api_key\" in config:\n self.postman_api_key = config[\"postman_api_key\"]\n else:\n raise AttributeError(\n \"'postman_api_key' not present in config_file!\"\n )\n\n if \"trigger_interval\" in config:\n self.trigger_interval = config[\"trigger_interval\"]\n\n if \"slack_token\" in config:\n self.slack_token = config[\"slack_token\"]\n else:\n raise AttributeError(\"'slack_token' not present in config_file!\")\n\n return (\n self.collection_name,\n self.postman_api_key,\n self.trigger_interval,\n self.slack_channel,\n self.slack_token,\n )","def get_python_function_arguments(f):\n # Note that we only return non-optional arguments (we assume that any optional args are not specified).\n # This allows to, e.g., accept max(a, b, *more, name='') as a binary function\n param_specs = inspect.getfullargspec(f)\n annotations = param_specs.annotations\n arg_names = param_specs.args\n defaults = param_specs.defaults # \"if this tuple has n elements, they correspond to the last n elements listed\n # in args\"\n if defaults:\n arg_names = arg_names[:-len(defaults)]\n return (arg_names, annotations)","def get_default_args(**kw):\n default_args_exp = {\n \"output_file\": \"ml_demo.c\",\n \"function_name\": \"ml_demo\",\n \"precision\": ML_Binary32,\n \"accuracy\": ML_Faithful,\n \"target\": GenericProcessor.get_target_instance()\n }\n default_args_exp.update(kw)\n return DefaultArgTemplate(**default_args_exp)","def punkte(self):\n return self.args","def _get_args(self) -> str:\n args = \"\"\n\n for config_key, config_option in self.config_options.items():\n if config_key in self.special_args:\n get_args_func = self.special_args[config_key]\n args += get_args_func(config_option)\n elif config_key in self.ignore_args:\n continue\n else:\n args += self._get_normal_args(config_key, config_option)\n\n return args.strip()","def get_kwd_args(func):\n try:\n sig = inspect.signature(func)\n except AttributeError:\n args, _, _, defaults = inspect.getargspec(func)\n if defaults:\n kwonlyargs = args[-len(defaults):]\n else:\n kwonlyargs = []\n else:\n kwonlyargs = {p.name:p.default for p in sig.parameters.values()\n if p.default is not p.empty}\n\n return kwonlyargs","def get_argdefaults(factory, num_skipped=0):\n args, defaults = _getargspec(factory)\n\n if defaults is not None:\n num_without_defaults = len(args) - len(defaults)\n default_values = (NO_DEFAULT,) * num_without_defaults + defaults\n else:\n default_values = (NO_DEFAULT,) * len(args)\n\n return dict(zip(args, default_values)[num_skipped:])","def test_kw_args_with_defaults():\n assert arguments.fun_opt_kw_params() == ('blue', 'red', 'yellow', 'orange')","def getArguments(self, optional=False):\n if not rospy.has_param(self.namespace):\n if not optional:\n raise KeyError('Could not retrieve any arguments. There is nothing on the parameter server for this namespace: ' + self.namespace)\n return {}\n arguments = rospy.get_param(self.namespace)\n missingArguments = []\n for argument in self.listOfArgumentNames:\n if argument not in arguments:\n missingArguments.append(argument)\n if not optional and len(missingArguments) > 0:\n rospy.logerr('Could not retrieve all arguments for %s from parameter server. ' +\n 'Missing arguments are: %l') % (self.namespace, missingArguments)\n raise KeyError('The arguments %l are missing.') % missingArguments\n return arguments","def _get_args(self):\n return (self.http_status, self.code, self.message)"],"string":"[\n \"def get_defaults(self):\\n default_dict = {}\\n args, varargs, keyword, defaults = inspect.getargspec(self.exec_obj)\\n if defaults:\\n default_dict = dict(zip(args[-len(defaults):], defaults))\\n return default_dict\",\n \"def _default_arguments(self, obj):\\n \\n if not (inspect.isfunction(obj) or inspect.ismethod(obj)):\\n # for classes, check for __init__,__new__\\n if inspect.isclass(obj):\\n obj = (getattr(obj,'__init__',None) or\\n getattr(obj,'__new__',None))\\n # for all others, check if they are __call__able\\n elif hasattr(obj, '__call__'):\\n obj = obj.__call__\\n # XXX: is there a way to handle the builtins ?\\n try:\\n args,_,_1,defaults = inspect.getargspec(obj)\\n if defaults:\\n return args[-len(defaults):]\\n except TypeError: pass\\n return []\",\n \"def _get_init_args(self):\\n\\n return dict(enum=self.enum, dflt=self._defname,\\n base=self.base, shape=self.shape)\",\n \"def names(self):\\n result = []\\n result.extend(self.positional_arguments)\\n if self.arbitary_positional_arguments is not None:\\n result.append(self.arbitary_positional_arguments)\\n if self.arbitary_keyword_arguments is not None:\\n result.append(self.arbitary_keyword_arguments)\\n result.extend(self.keyword_arguments)\\n return result\",\n \"def arg_names(self):\\n return self._arg_names\",\n \"def arg_names(self):\\n return self._arg_names\",\n \"def get_xx_args_dict(self):\\n return self.__xx_args\",\n \"def get_additional_hook_arguments(\\n self,\\n path_manager: PathManager,\\n extra_arguments: Optional[Dict[str, str]] = None,\\n ) -> List[str]:\",\n \"def get_mandatory_arguments(self):\\n args, varargs, keyword, defaults = inspect.getargspec(self.exec_obj)\\n\\n if defaults is not None:\\n args = args[:-len(defaults)]\\n\\n if args.count('self') > 0:\\n args.remove('self')\\n return args\",\n \"def _invocation_params(self) -> Dict[str, Any]:\\n return self._default_params\",\n \"def _make_args(self, args, defaults=[], vararg=None, kwonlyargs=[],\\n kw_defaults=[], kwarg=None):\\n # On Python 2 convert vararg and kwarg to raw name, raise error using\\n # lineno stored on the node and lexer from self.\\n # On Python 3.3 extract name and annotation\\n # After should be straight forward\\n raise NotImplementedError()\",\n \"def _get_param_names(self):\\r\\n return sorted([p\\r\\n for p in self.__dict__\\r\\n if p != 'additional_args'])\",\n \"def get_kwargs():\\n\\treturn get_kwargs_raw(sys.argv)\",\n \"def get_x_args_dict(self):\\n return self.__x_args\",\n \"def __getinitargs__(self):\\n\\n return (self.name, self.value)\",\n \"def get_arguments(callable, exclude):\\n info = arginfo(callable)\\n defaults = info.defaults or []\\n defaults = [None] * (len(info.args) - len(defaults)) + list(defaults)\\n return {name: default for (name, default) in zip(info.args, defaults)\\n if name not in exclude}\",\n \"def args(self) -> tuple[Basic, ...]:\\n return self._args\",\n \"def getPositionalArgs():\",\n \"def _get_init_args(self):\\n signature = inspect.signature(self.__init__)\\n parameters = signature.parameters\\n args = [arg for arg, p in parameters.items()\\n if p.kind is p.POSITIONAL_OR_KEYWORD]\\n\\n return {arg: getattr(self, arg) for arg in args if arg != 'self'}\",\n \"def getargspec(self,obj):\\n\\n if inspect.isfunction(obj):\\n func_obj = obj\\n elif inspect.ismethod(obj):\\n func_obj = obj.im_func\\n else:\\n raise TypeError, 'arg is not a Python function'\\n args, varargs, varkw = inspect.getargs(func_obj.func_code)\\n return args, varargs, varkw, func_obj.func_defaults\",\n \"def get_args(self):\\r\\n return self.args\",\n \"def _get_param_names(self):\\n temp_params = {'function': self.function, 'target': self.target}\\n\\n temp_params.update(self.kwargs)\\n\\n return temp_params\",\n \"def get_parameters(self):\\n params = {}\\n for p in self.DEFAULT_VALUES.keys():\\n params[p] = getattr(self, p)\\n return params\",\n \"def pykwarg(self):\\n return self._pykwarg\",\n \"def get_init_arguments_and_types(cls) -> List[Tuple[str, Tuple, Any]]:\\n trainer_default_params = inspect.signature(cls).parameters\\n name_type_default = []\\n for arg in trainer_default_params:\\n arg_type = trainer_default_params[arg].annotation\\n arg_default = trainer_default_params[arg].default\\n try:\\n arg_types = tuple(arg_type.__args__)\\n except AttributeError:\\n arg_types = (arg_type,)\\n\\n name_type_default.append((arg, arg_types, arg_default))\\n\\n return name_type_default\",\n \"def getRequiredArguments(self):\\n if self._initValue.needsArgument:\\n return [self._initValue.getArgument()]\\n else:\\n return []\",\n \"def SaveCustomDefaults(self, *args, **kwargs):\\n # type: (*Any, **Any) -> None\\n payload = { \\\"Arg1\\\": self }\\n for i in range(len(args)): payload['Arg%s' % (i + 2)] = args[i]\\n for item in kwargs.items(): payload[item[0]] = item[1]\\n return self._execute('saveCustomDefaults', payload=payload, response_object=None)\",\n \"def __get_arguments(args=None, logger=None, stats=None):\\n\\n if not args:\\n parser = get_parser()\\n add_boto_cli_arguments(parser)\\n # Parse only the known arguments added by add_boto_cli_arguments().\\n # We only need those arguments to create Boto object, nothing else.\\n # parse_known_args() return (Namespace, list of unknown arguments),\\n # we only care about the Namespace object here.\\n args = parser.parse_known_args()[0]\\n\\n if not logger:\\n logger = get_logger(name=NAME)\\n\\n if not stats:\\n stats = get_stats(prefix=NAME)\\n\\n return {\\n 'log_level': getattr(args, 'boto_log_level', DEFAULT['log_level']()),\\n 'access_key': getattr(args, 'boto_access_key', DEFAULT['access_key']()),\\n 'secret_key': getattr(args, 'boto_secret_key', DEFAULT['secret_key']()),\\n 'region': getattr(args, 'boto_region', DEFAULT['region']()),\\n 'logger': logger,\\n 'stats': stats,\\n }\",\n \"def get(self):\\n return self.args, self.kwargs\",\n \"def args(cls):\\n try:\\n args = getfullargspec(cls.__init__)\\n except TypeError:\\n return []\\n return args[0]\",\n \"def parameters(self) -> Dict[str, Any]:\\n return self.data[\\\"args\\\"].get(\\\"parameters\\\", {})\",\n \"def args(self):\\n\\t\\tret = []\\n\\t\\tfor argname in self._arg_names:\\n\\t\\t\\tret += [self._args[argname]]\\n\\t\\treturn ret\",\n \"def args(self) -> List[str]:\\n return self.__args\",\n \"def get_all_arguments(self):\\n args, varargs, keyword, defaults = inspect.getargspec(self.exec_obj)\\n if args.count('self') > 0:\\n args.remove('self')\\n return args\",\n \"def func_args(self) -> str:\\n\\n return self.call_data[10:]\",\n \"def extra_args(self):\\n return []\",\n \"def base_arguments(self):\\n raise NotImplementedError()\",\n \"def get_default_args(func):\\n signature = inspect.signature(func)\\n return {\\n k: v.default\\n for k, v in signature.parameters.items()\\n if v.default is not inspect.Parameter.empty\\n }\",\n \"def argnames(self):\\n if self.get_key is None:\\n return set()\\n return set(self.get_key.names)\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def args(self) -> Optional[Sequence[str]]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def get_helper_c_code_args(self):\\r\\n return Subtensor.default_helper_c_code_args()\",\n \"def _get_function_defaults(func: FunctionType) -> dict[str, Any]:\\n # extracted bit from inspect.signature... ~20x faster\\n pos_count = func.__code__.co_argcount\\n arg_names = func.__code__.co_varnames\\n\\n defaults = func.__defaults__ or ()\\n\\n non_default_count = pos_count - len(defaults)\\n positional_args = arg_names[:pos_count]\\n\\n output = {\\n name: defaults[offset]\\n for offset, name in enumerate(positional_args[non_default_count:])\\n }\\n if func.__kwdefaults__:\\n output.update(func.__kwdefaults__)\\n return output\",\n \"def argdict(self):\\n return dict((arg.name, val) for arg, val in zip(self.sig, self))\",\n \"def get_json_argument_list():\\n list_of_arguments_to_get = [\\\"finish_time\\\", \\\"segmentation_training_samples\\\", \\\"patch_count_per_image\\\", \\\"learning_rate\\\", \\\"batch_k\\\",\\n \\\"batch_p\\\", \\\"flip_augment\\\", \\\"standardize\\\", \\\"margin\\\", \\\"metric\\\"]\\n\\n return list_of_arguments_to_get\",\n \"def as_kwargs(self) -> Dict[str, Any]:\\n ret = {}\\n for arg in self.args.values():\\n ret[arg.name] = arg.value\\n return ret\",\n \"def get_default_args(**kw):\\n default_args_log = {\\n \\\"output_file\\\": \\\"POLY.c\\\",\\n \\\"function_name\\\": \\\"POLY\\\",\\n \\\"precision\\\": ML_Binary64,\\n \\\"target\\\": GenericProcessor.get_target_instance(),\\n \\\"function\\\": None,\\n \\\"interval\\\": None,\\n \\\"epsilon\\\": None\\n }\\n default_args_log.update(kw)\\n return DefaultArgTemplate(**default_args_log)\",\n \"def args(self):\\n return self._parse_args\",\n \"def inspect_args_func(frame):\\n args, _, _, values = inspect.getargvalues(frame)\\n return {key: values[key] for key in args if key != 'self'}\",\n \"def argument_list(self):\\n answer = self._call('argument_list')\\n return answer.names\",\n \"def preprocess_arguments(self, *args, **kwargs):\\n return (args, kwargs)\",\n \"def get_custom_hook_names():\\n return list(_CUSTOM_HOOKS)\",\n \"def defaultargs(options):\\n config = {}\\n for longname, default, _ in options:\\n config[longname] = default\\n return config\",\n \"def init_json_args(cls):\\n defaults = cls._base_json_args()\\n\\n if cls.__json_args__ is None:\\n cls.__json_args__ = defaults\\n else:\\n cls.__json_args__ = mapping_extend(defaults, cls.__json_args__)\",\n \"def args(self):\\n return self._args\",\n \"def args(self):\\n return self._args\",\n \"def args(self):\\n return self._args\",\n \"def args(self) -> Optional[str]:\\n return pulumi.get(self, \\\"args\\\")\",\n \"def getcallback(cls, cmd, arg):\\n return [dict({'cmd': cmd, 'arg': arg, 'ret': None})]\",\n \"def _params(self, **kwargs):\\n defaults = {'display_name': 'Test User',\\n 'locale': 'en-us',\\n 'country': 'us'}\\n defaults.update(kwargs)\\n\\n return defaults\",\n \"def _get_reproducing_arguments(self):\\n reproducing_arguments = {\\n 'include': self.include,\\n 'exclude': self.exclude,\\n 'copy': self.copy,\\n }\\n args_names = {name: getattr(self, name) for name in self.args_names}\\n reproducing_arguments.update(args_names)\\n return reproducing_arguments\",\n \"def gen_args(self, obj, pa_names = False):\\n\\n pal, kwal = get_class_total_args(type(obj))\\n\\n try:\\n get_val = type(obj).__get_init_arg_val__\\n except AttributeError:\\n get_val = getattr\\n\\n for pa in pal:\\n v = get_val(obj, pa)\\n self.gen_field((pa + \\\" = \\\") if pa_names else \\\"\\\")\\n self.pprint(v)\\n\\n for kwa, default in kwal.items():\\n try:\\n v = get_val(obj, kwa)\\n except AttributeError:\\n # If value cannot be obtained, skip the argument generation\\n continue\\n\\n # generate only arguments with non-default values\\n if (v is default) or (v == default):\\n continue\\n\\n self.gen_field(kwa + \\\" = \\\")\\n self.pprint(v)\",\n \"def get_mandatory_args(self):\\n raise NotImplementedError(\\\"ICallable.get_mandatory_args\\\")\",\n \"def __loadDefaultArgs(self):\\n mod = self.__class__.__name__.lower()\\n logger.debug(\\\"Loading default args for module: %s\\\" % mod)\\n\\n default_args = conf.get(\\\"modules.%s\\\" % mod, None)\\n if not default_args:\\n return\\n for k, v in default_args.iteritems():\\n logger.debug(\\\"Setting default %s arg: %s=%s\\\" % (mod, k, v))\\n self.setArg(k, v)\",\n \"def parameter_names(self) -> List[str]:\",\n \"def getArgs(func):\\n # exclude the defaults at the end (hence the [:-1])\\n args = list(utils.flatten(inspect.getargspec(func)[:-1]))\\n return set(args).difference(set([None]))\",\n \"def parse_known_args(self):\\n args, other_args = self.parser.parse_known_args()\\n args = self.__process_args__(args)\\n return args, other_args\",\n \"def get_additional_arguments(obj):\\n args = ''\\n\\n try:\\n # If the object has arguments parse them to a string and replace the values from the lookup table\\n if obj.args:\\n # Parse the list to a string\\n args = ' '.join(obj.args)\\n\\n # Replace the items in the string with entries from the lookup table\\n for k, v in config.lookup_table:\\n args = args.replace(k, v)\\n\\n # Reset the args in the object to reset its state\\n obj.args = None\\n except AttributeError:\\n # No additional args present so we can just skip the parsing\\n pass\\n\\n return args\",\n \"def get_partial_arguments(self):\\n return (), {}\",\n \"def get_cli_arguments(self):\\n pass\",\n \"def args(self):\\n if not self.arg_names:\\n return []\\n modes = self.arg_modes or [\\\"i\\\"] * len(self.arg_names)\\n args = [\\n (name, typ)\\n for name, typ, mode in zip(self.arg_names, self.arg_types, modes)\\n if mode in (\\\"i\\\", \\\"b\\\", \\\"v\\\") # IN, INOUT, VARIADIC\\n ]\\n\\n def arg(name, typ, num):\\n num_args = len(args)\\n num_defaults = len(self.arg_defaults)\\n has_default = num + num_defaults >= num_args\\n default = (\\n self.arg_defaults[num - num_args + num_defaults]\\n if has_default\\n else None\\n )\\n return ColumnMetadata(name, typ, [], default, has_default)\\n\\n return [arg(name, typ, num) for num, (name, typ) in enumerate(args)]\",\n \"def _getArg(self,synonyms,args,default=None):\\n value = None\\n if (type(synonyms) != type([])):\\n synonyms = Utilities.splitString(synonyms)\\n #endIf\\n\\n for name in synonyms:\\n value = args.get(name)\\n if (value != None):\\n break\\n #endIf\\n #endFor\\n\\n if (value == None and default != None):\\n value = default\\n #endIf\\n\\n return value\",\n \"def get_arguments(self):\\n args = self.parser.parse_args()\\n config = None\\n with open(args.config_file, \\\"r\\\") as f:\\n config = json.load(f)\\n\\n if \\\"collections\\\" in config:\\n if len(config[\\\"collections\\\"]) > 0:\\n collection = config[\\\"collections\\\"][0]\\n if \\\"collection_name\\\" in collection:\\n self.collection_name = collection[\\\"collection_name\\\"]\\n else:\\n raise AttributeError(\\n \\\"'collection_name' not present in 'collections'!\\\"\\n )\\n self.slack_channel = collection[\\\"slack_channel\\\"]\\n else:\\n raise AttributeError(\\n \\\"No 'collections' details found in config_file!\\\"\\n )\\n else:\\n raise AttributeError(\\\"'collections' not present in config_file!\\\")\\n\\n if \\\"postman_api_key\\\" in config:\\n self.postman_api_key = config[\\\"postman_api_key\\\"]\\n else:\\n raise AttributeError(\\n \\\"'postman_api_key' not present in config_file!\\\"\\n )\\n\\n if \\\"trigger_interval\\\" in config:\\n self.trigger_interval = config[\\\"trigger_interval\\\"]\\n\\n if \\\"slack_token\\\" in config:\\n self.slack_token = config[\\\"slack_token\\\"]\\n else:\\n raise AttributeError(\\\"'slack_token' not present in config_file!\\\")\\n\\n return (\\n self.collection_name,\\n self.postman_api_key,\\n self.trigger_interval,\\n self.slack_channel,\\n self.slack_token,\\n )\",\n \"def get_python_function_arguments(f):\\n # Note that we only return non-optional arguments (we assume that any optional args are not specified).\\n # This allows to, e.g., accept max(a, b, *more, name='') as a binary function\\n param_specs = inspect.getfullargspec(f)\\n annotations = param_specs.annotations\\n arg_names = param_specs.args\\n defaults = param_specs.defaults # \\\"if this tuple has n elements, they correspond to the last n elements listed\\n # in args\\\"\\n if defaults:\\n arg_names = arg_names[:-len(defaults)]\\n return (arg_names, annotations)\",\n \"def get_default_args(**kw):\\n default_args_exp = {\\n \\\"output_file\\\": \\\"ml_demo.c\\\",\\n \\\"function_name\\\": \\\"ml_demo\\\",\\n \\\"precision\\\": ML_Binary32,\\n \\\"accuracy\\\": ML_Faithful,\\n \\\"target\\\": GenericProcessor.get_target_instance()\\n }\\n default_args_exp.update(kw)\\n return DefaultArgTemplate(**default_args_exp)\",\n \"def punkte(self):\\n return self.args\",\n \"def _get_args(self) -> str:\\n args = \\\"\\\"\\n\\n for config_key, config_option in self.config_options.items():\\n if config_key in self.special_args:\\n get_args_func = self.special_args[config_key]\\n args += get_args_func(config_option)\\n elif config_key in self.ignore_args:\\n continue\\n else:\\n args += self._get_normal_args(config_key, config_option)\\n\\n return args.strip()\",\n \"def get_kwd_args(func):\\n try:\\n sig = inspect.signature(func)\\n except AttributeError:\\n args, _, _, defaults = inspect.getargspec(func)\\n if defaults:\\n kwonlyargs = args[-len(defaults):]\\n else:\\n kwonlyargs = []\\n else:\\n kwonlyargs = {p.name:p.default for p in sig.parameters.values()\\n if p.default is not p.empty}\\n\\n return kwonlyargs\",\n \"def get_argdefaults(factory, num_skipped=0):\\n args, defaults = _getargspec(factory)\\n\\n if defaults is not None:\\n num_without_defaults = len(args) - len(defaults)\\n default_values = (NO_DEFAULT,) * num_without_defaults + defaults\\n else:\\n default_values = (NO_DEFAULT,) * len(args)\\n\\n return dict(zip(args, default_values)[num_skipped:])\",\n \"def test_kw_args_with_defaults():\\n assert arguments.fun_opt_kw_params() == ('blue', 'red', 'yellow', 'orange')\",\n \"def getArguments(self, optional=False):\\n if not rospy.has_param(self.namespace):\\n if not optional:\\n raise KeyError('Could not retrieve any arguments. There is nothing on the parameter server for this namespace: ' + self.namespace)\\n return {}\\n arguments = rospy.get_param(self.namespace)\\n missingArguments = []\\n for argument in self.listOfArgumentNames:\\n if argument not in arguments:\\n missingArguments.append(argument)\\n if not optional and len(missingArguments) > 0:\\n rospy.logerr('Could not retrieve all arguments for %s from parameter server. ' +\\n 'Missing arguments are: %l') % (self.namespace, missingArguments)\\n raise KeyError('The arguments %l are missing.') % missingArguments\\n return arguments\",\n \"def _get_args(self):\\n return (self.http_status, self.code, self.message)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.61624855","0.6132843","0.6095295","0.60910934","0.6068363","0.6068363","0.6029796","0.5978995","0.5969861","0.5933815","0.5930009","0.5890643","0.58816427","0.5855672","0.5841174","0.5833141","0.58139366","0.5811528","0.58108425","0.57942617","0.5759906","0.574093","0.5724381","0.57240814","0.5708885","0.57033944","0.569451","0.56876594","0.56806195","0.56578517","0.56509435","0.5638644","0.56337285","0.56226283","0.5622055","0.56212693","0.5621124","0.56011504","0.55950123","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.5591319","0.55836535","0.5570087","0.55497205","0.5541906","0.55412424","0.55382764","0.5537457","0.55368066","0.54960066","0.5494859","0.5482649","0.54701275","0.5469952","0.5458587","0.5458587","0.5458587","0.54473567","0.5443477","0.54401416","0.54381716","0.54320353","0.5430803","0.54080415","0.5402717","0.5402199","0.539736","0.53939","0.5381828","0.5377533","0.537507","0.5372351","0.5370225","0.5362713","0.53580993","0.5349423","0.53488266","0.53479","0.53363323","0.5332981","0.5325768","0.5324416"],"string":"[\n \"0.61624855\",\n \"0.6132843\",\n \"0.6095295\",\n \"0.60910934\",\n \"0.6068363\",\n \"0.6068363\",\n \"0.6029796\",\n \"0.5978995\",\n \"0.5969861\",\n \"0.5933815\",\n \"0.5930009\",\n \"0.5890643\",\n \"0.58816427\",\n \"0.5855672\",\n \"0.5841174\",\n \"0.5833141\",\n \"0.58139366\",\n \"0.5811528\",\n \"0.58108425\",\n \"0.57942617\",\n \"0.5759906\",\n \"0.574093\",\n \"0.5724381\",\n \"0.57240814\",\n \"0.5708885\",\n \"0.57033944\",\n \"0.569451\",\n \"0.56876594\",\n \"0.56806195\",\n \"0.56578517\",\n \"0.56509435\",\n \"0.5638644\",\n \"0.56337285\",\n \"0.56226283\",\n \"0.5622055\",\n \"0.56212693\",\n \"0.5621124\",\n \"0.56011504\",\n \"0.55950123\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.5591319\",\n \"0.55836535\",\n \"0.5570087\",\n \"0.55497205\",\n \"0.5541906\",\n \"0.55412424\",\n \"0.55382764\",\n \"0.5537457\",\n \"0.55368066\",\n \"0.54960066\",\n \"0.5494859\",\n \"0.5482649\",\n \"0.54701275\",\n \"0.5469952\",\n \"0.5458587\",\n \"0.5458587\",\n \"0.5458587\",\n \"0.54473567\",\n \"0.5443477\",\n \"0.54401416\",\n \"0.54381716\",\n \"0.54320353\",\n \"0.5430803\",\n \"0.54080415\",\n \"0.5402717\",\n \"0.5402199\",\n \"0.539736\",\n \"0.53939\",\n \"0.5381828\",\n \"0.5377533\",\n \"0.537507\",\n \"0.5372351\",\n \"0.5370225\",\n \"0.5362713\",\n \"0.53580993\",\n \"0.5349423\",\n \"0.53488266\",\n \"0.53479\",\n \"0.53363323\",\n \"0.5332981\",\n \"0.5325768\",\n \"0.5324416\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5322465"},"document_rank":{"kind":"string","value":"100"}}},{"rowIdx":81765,"cells":{"query":{"kind":"string","value":"Start this callbacks object."},"document":{"kind":"string","value":"def start(self, **kwargs):\n super(Json, self).start(**kwargs)\n flat = self.get_arg_value(\"json_flat\")\n\n self._first_row = True\n self.open_fd()\n begin = \"\" if flat else \"[\"\n self._fd.write(begin)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def Start(self) :\n\t\t...","def start(self):\n if self._start_event is None:\n _call_spawn_callbacks(self)\n hub = get_my_hub(self) # pylint:disable=undefined-variable\n self._start_event = hub.loop.run_callback(self.switch)","def on_init_start(self):\n for callback in self.callbacks:\n callback.on_init_start(self)","def start(self):\n if self._callable:\n self._is_running = True\n self._run_client()","def call_start_cbs(self):\n try:\n for (cb,args) in self._start_cbs:\n cb(self.userdata, self.get_initial_states(), *args)\n except:\n smach.logerr(\"Could not execute start callback: \"+traceback.format_exc())","def start(cls):\n\n cls._set_mode_running()\n TimeDisplay.start_time()\n for callback in cls.start_callback:\n callback()","def start(self, **kwargs):\n pass","def start(self, **kwargs):\n pass","def run(self):\n self.started()","def start(self):\r\n pass","def start(self):\n self._listener.start()","def start(self):\n pass","def start(self):\n pass","def start(self):\n pass","def start(self):\n pass","def start(self):\n pass","def start(self):\n pass","def start(self):\n pass","def start(self):\n pass","def start (self):\n pass","def start (self):\n pass","def start(self) -> None:\n ...","def start(self) -> None:\n ...","def start(self):\n assert(self._cbs is not None)\n self._as.start() # start the server","def start(self):\n\n # Start listening for records\n self._run_loop(True)\n # There might still be records in the queue.\n self._run_loop(False)","def start(self):\n ...","def start(self):\n self.listener.start()\n # No need to start broadcaster, it just sends when necessary","def start(self):\n if self._started:\n return\n\n self._register()\n self._started = True","def start(self) -> None:","def start(self) -> None:","def _start(self):\n pass","def start(self):\n raise NotImplementedError","def start(self):\n raise NotImplementedError","def start(self):\n raise NotImplementedError","def start(self):\n self.reset()\n self.on_start()","def start(self):\r\n if self._ready:\r\n return\r\n\r\n self._start()\r\n self._ready = True","def activate(self):\n self.start()","def start(self):\n raise NotImplementedError()","def start(self):\n raise NotImplementedError()","def start(self):\n raise NotImplementedError()","def start(self):\n raise NotImplementedError()","def start(self) -> None:\n start_thread(super().start, self.__class__.__name__)","async def start(self):","async def start(self):","def start(self) -> None:\n cb = self._callback\n if cb is not None:\n self._callback = None\n propagate(from_=ensure_future(cb()), to=self._future)","def started(self):","def init(self):\n\t\tsp_addcallback(self.sp_callback)\n\t\tself.downloader.start()","def on_start(self):\n pass","def on_start(self):\n pass","def on_start(self):\n pass","def on_start(self):\n pass","def on_start(self):\n pass","def on_start(self):\n pass","def on_start(self):\n pass","def on_start(self):\n pass","def _start(self):","def start():","def start():","def start():","def start():","def start(self) -> None:\n self.observer.start()","def run(self):\n self.initialize()\n\n # run the start callback\n tools.run_callback(\"start\", {'request': self._request})\n\n data = self._request.getData()\n pyhttp = self._request.getHttp()\n config = self._request.getConfiguration()\n\n # allow anyone else to handle the request at this point\n handled = tools.run_callback(\"handle\", \n {'request': self._request},\n mappingfunc=lambda x,y:x,\n donefunc=lambda x:x)\n\n if not handled == 1:\n blosxom_handler(self._request)\n\n # do end callback\n tools.run_callback(\"end\", {'request': self._request})","def start( self ):\n\n self.service()","def start(self):\n self.observer.start()","def init(self):\n self.dispatcher.start()\n self.replyer.start()","def start(self):\n self._is_waiting = False","async def start(self) -> None:","def start(self):\n self.ioloop.add_callback(self.get_data)\n logging.info(\"[DataSource] Started\")","def run(self):\n ioloop.IOLoop.current().start()","def on_start(self):\n self.init()","def start(self):\n self.sender.start()\n self.receiver.start()","def start(self):\n self.sender.start()\n self.receiver.start()","def start(self):\n self.stream.start()\n self.running = True\n self.update()","def start(self):\n\t\tself.stream.start_stream()","def run(self):\n self.loop.spawn_callback(self.main)\n self.loop.start()\n if self.exc_info:\n six.reraise(*self.exc_info)","def on_start(self):\n self.run_in_background(self.__run_client)","def connect(self):\n self.start()","def start(self):\n self.p.start()","def start(self):\n with self._lock:\n if not self.started():\n self._started = None\n getattr(self.factory, 'start_' + self.class_name())(self)","def start(self) -> None:\n self._stream.start()","def start(self):\n gevent.spawn(self.run)","def on_test_start(self):\n for callback in self.callbacks:\n callback.on_test_start(self, self.get_model())","def start(self):\n super().start()\n loop = IOLoop.current()\n # Collect and send all IOPub messages, for all time\n # TODO: Check errors from this loop and restart as needed (or shut down the kernel)\n loop.add_callback(self.relay_iopub_messages)","def start(self) -> None:\n\n self.bus.subscribe(\"server:ready\", self.setup)\n self.bus.subscribe(\"bookmarks:find:id\", self.find_id)\n self.bus.subscribe(\"bookmarks:find:url\", self.find_url)\n self.bus.subscribe(\"bookmarks:add\", self.add)\n self.bus.subscribe(\"bookmarks:add:fulltext\", self.add_full_text)\n self.bus.subscribe(\"bookmarks:domaincount\", self.domain_count)\n self.bus.subscribe(\"bookmarks:search\", self.search)\n self.bus.subscribe(\"bookmarks:prune\", self.prune)\n self.bus.subscribe(\"bookmarks:recent\", self.recent)\n self.bus.subscribe(\"bookmarks:tags:all\", self.all_tags)\n self.bus.subscribe(\"bookmarks:remove\", self.remove)\n self.bus.subscribe(\"bookmarks:repair\", self.repair)","def on_start(self):","def on_start(self):","def start(self):\n\n self._task.start()","def start(self):\n self.parent.start(auto_terminate=False)\n self.started = True","def start(self):\n if self.__running:\n raise RuntimeError('already started')\n self.__hook_thread = threading.Thread(target=self.__run_hook, args=(self.__build_runner(),))\n self.__running = True\n self.__hook_thread.start()","def runCallback(self, callback=\"help\"):\n self.initialize()\n\n # run the start callback\n tools.run_callback(\"start\", {'request': self._request})\n\n config = self._request.getConfig()\n data = self._request.getData()\n\n # invoke all callbacks for the 'callback'\n handled = tools.run_callback(callback,\n {'request': self._request},\n mappingfunc=lambda x,y:x,\n donefunc=lambda x:x)\n\n # do end callback\n tools.run_callback(\"end\", {'request': request})","def connect(\n cls,\n on_start=None,\n on_resume=None,\n on_pause=None,\n on_stop=None,\n on_save=None,\n on_reset=None,\n ):\n if on_start and on_start not in cls.start_callback:\n cls.start_callback.append(on_start)\n\n if on_resume and on_resume not in cls.resume_callback:\n cls.resume_callback.append(on_resume)\n\n if on_pause and on_pause not in cls.pause_callback:\n cls.pause_callback.append(on_pause)\n\n if on_stop and on_stop not in cls.stop_callback:\n cls.stop_callback.append(on_stop)\n\n if on_save and on_save not in cls.save_callback:\n cls.save_callback.append(on_save)\n\n if on_reset and on_reset not in cls.reset_callback:\n cls.reset_callback.append(on_reset)","def start(self):\n self._setup_thread()\n self.thread.start()","def start(self):\n if not self.periodic._running:\n self.periodic.start()\n else:\n raise Exception('PeriodicCallback already running.')","def on_start(self, ctx):\n pass","def start(self):\n self.watcher.start()\n self._asyncio_loop.run_forever()","def start(self):\n self._closing_checks = {}\n self._refresh_closing_checks()\n self._bind_observers()","def on_train_start(self):\n for callback in self.callbacks:\n callback.on_train_start(self, self.get_model())","def on_batch_start(self):\n for callback in self.callbacks:\n callback.on_batch_start(self, self.get_model())","def start(self) -> None:\n self.__enter__()","async def on_start(self):","def start(self):\n self._thread.start()"],"string":"[\n \"def Start(self) :\\n\\t\\t...\",\n \"def start(self):\\n if self._start_event is None:\\n _call_spawn_callbacks(self)\\n hub = get_my_hub(self) # pylint:disable=undefined-variable\\n self._start_event = hub.loop.run_callback(self.switch)\",\n \"def on_init_start(self):\\n for callback in self.callbacks:\\n callback.on_init_start(self)\",\n \"def start(self):\\n if self._callable:\\n self._is_running = True\\n self._run_client()\",\n \"def call_start_cbs(self):\\n try:\\n for (cb,args) in self._start_cbs:\\n cb(self.userdata, self.get_initial_states(), *args)\\n except:\\n smach.logerr(\\\"Could not execute start callback: \\\"+traceback.format_exc())\",\n \"def start(cls):\\n\\n cls._set_mode_running()\\n TimeDisplay.start_time()\\n for callback in cls.start_callback:\\n callback()\",\n \"def start(self, **kwargs):\\n pass\",\n \"def start(self, **kwargs):\\n pass\",\n \"def run(self):\\n self.started()\",\n \"def start(self):\\r\\n pass\",\n \"def start(self):\\n self._listener.start()\",\n \"def start(self):\\n pass\",\n \"def start(self):\\n pass\",\n \"def start(self):\\n pass\",\n \"def start(self):\\n pass\",\n \"def start(self):\\n pass\",\n \"def start(self):\\n pass\",\n \"def start(self):\\n pass\",\n \"def start(self):\\n pass\",\n \"def start (self):\\n pass\",\n \"def start (self):\\n pass\",\n \"def start(self) -> None:\\n ...\",\n \"def start(self) -> None:\\n ...\",\n \"def start(self):\\n assert(self._cbs is not None)\\n self._as.start() # start the server\",\n \"def start(self):\\n\\n # Start listening for records\\n self._run_loop(True)\\n # There might still be records in the queue.\\n self._run_loop(False)\",\n \"def start(self):\\n ...\",\n \"def start(self):\\n self.listener.start()\\n # No need to start broadcaster, it just sends when necessary\",\n \"def start(self):\\n if self._started:\\n return\\n\\n self._register()\\n self._started = True\",\n \"def start(self) -> None:\",\n \"def start(self) -> None:\",\n \"def _start(self):\\n pass\",\n \"def start(self):\\n raise NotImplementedError\",\n \"def start(self):\\n raise NotImplementedError\",\n \"def start(self):\\n raise NotImplementedError\",\n \"def start(self):\\n self.reset()\\n self.on_start()\",\n \"def start(self):\\r\\n if self._ready:\\r\\n return\\r\\n\\r\\n self._start()\\r\\n self._ready = True\",\n \"def activate(self):\\n self.start()\",\n \"def start(self):\\n raise NotImplementedError()\",\n \"def start(self):\\n raise NotImplementedError()\",\n \"def start(self):\\n raise NotImplementedError()\",\n \"def start(self):\\n raise NotImplementedError()\",\n \"def start(self) -> None:\\n start_thread(super().start, self.__class__.__name__)\",\n \"async def start(self):\",\n \"async def start(self):\",\n \"def start(self) -> None:\\n cb = self._callback\\n if cb is not None:\\n self._callback = None\\n propagate(from_=ensure_future(cb()), to=self._future)\",\n \"def started(self):\",\n \"def init(self):\\n\\t\\tsp_addcallback(self.sp_callback)\\n\\t\\tself.downloader.start()\",\n \"def on_start(self):\\n pass\",\n \"def on_start(self):\\n pass\",\n \"def on_start(self):\\n pass\",\n \"def on_start(self):\\n pass\",\n \"def on_start(self):\\n pass\",\n \"def on_start(self):\\n pass\",\n \"def on_start(self):\\n pass\",\n \"def on_start(self):\\n pass\",\n \"def _start(self):\",\n \"def start():\",\n \"def start():\",\n \"def start():\",\n \"def start():\",\n \"def start(self) -> None:\\n self.observer.start()\",\n \"def run(self):\\n self.initialize()\\n\\n # run the start callback\\n tools.run_callback(\\\"start\\\", {'request': self._request})\\n\\n data = self._request.getData()\\n pyhttp = self._request.getHttp()\\n config = self._request.getConfiguration()\\n\\n # allow anyone else to handle the request at this point\\n handled = tools.run_callback(\\\"handle\\\", \\n {'request': self._request},\\n mappingfunc=lambda x,y:x,\\n donefunc=lambda x:x)\\n\\n if not handled == 1:\\n blosxom_handler(self._request)\\n\\n # do end callback\\n tools.run_callback(\\\"end\\\", {'request': self._request})\",\n \"def start( self ):\\n\\n self.service()\",\n \"def start(self):\\n self.observer.start()\",\n \"def init(self):\\n self.dispatcher.start()\\n self.replyer.start()\",\n \"def start(self):\\n self._is_waiting = False\",\n \"async def start(self) -> None:\",\n \"def start(self):\\n self.ioloop.add_callback(self.get_data)\\n logging.info(\\\"[DataSource] Started\\\")\",\n \"def run(self):\\n ioloop.IOLoop.current().start()\",\n \"def on_start(self):\\n self.init()\",\n \"def start(self):\\n self.sender.start()\\n self.receiver.start()\",\n \"def start(self):\\n self.sender.start()\\n self.receiver.start()\",\n \"def start(self):\\n self.stream.start()\\n self.running = True\\n self.update()\",\n \"def start(self):\\n\\t\\tself.stream.start_stream()\",\n \"def run(self):\\n self.loop.spawn_callback(self.main)\\n self.loop.start()\\n if self.exc_info:\\n six.reraise(*self.exc_info)\",\n \"def on_start(self):\\n self.run_in_background(self.__run_client)\",\n \"def connect(self):\\n self.start()\",\n \"def start(self):\\n self.p.start()\",\n \"def start(self):\\n with self._lock:\\n if not self.started():\\n self._started = None\\n getattr(self.factory, 'start_' + self.class_name())(self)\",\n \"def start(self) -> None:\\n self._stream.start()\",\n \"def start(self):\\n gevent.spawn(self.run)\",\n \"def on_test_start(self):\\n for callback in self.callbacks:\\n callback.on_test_start(self, self.get_model())\",\n \"def start(self):\\n super().start()\\n loop = IOLoop.current()\\n # Collect and send all IOPub messages, for all time\\n # TODO: Check errors from this loop and restart as needed (or shut down the kernel)\\n loop.add_callback(self.relay_iopub_messages)\",\n \"def start(self) -> None:\\n\\n self.bus.subscribe(\\\"server:ready\\\", self.setup)\\n self.bus.subscribe(\\\"bookmarks:find:id\\\", self.find_id)\\n self.bus.subscribe(\\\"bookmarks:find:url\\\", self.find_url)\\n self.bus.subscribe(\\\"bookmarks:add\\\", self.add)\\n self.bus.subscribe(\\\"bookmarks:add:fulltext\\\", self.add_full_text)\\n self.bus.subscribe(\\\"bookmarks:domaincount\\\", self.domain_count)\\n self.bus.subscribe(\\\"bookmarks:search\\\", self.search)\\n self.bus.subscribe(\\\"bookmarks:prune\\\", self.prune)\\n self.bus.subscribe(\\\"bookmarks:recent\\\", self.recent)\\n self.bus.subscribe(\\\"bookmarks:tags:all\\\", self.all_tags)\\n self.bus.subscribe(\\\"bookmarks:remove\\\", self.remove)\\n self.bus.subscribe(\\\"bookmarks:repair\\\", self.repair)\",\n \"def on_start(self):\",\n \"def on_start(self):\",\n \"def start(self):\\n\\n self._task.start()\",\n \"def start(self):\\n self.parent.start(auto_terminate=False)\\n self.started = True\",\n \"def start(self):\\n if self.__running:\\n raise RuntimeError('already started')\\n self.__hook_thread = threading.Thread(target=self.__run_hook, args=(self.__build_runner(),))\\n self.__running = True\\n self.__hook_thread.start()\",\n \"def runCallback(self, callback=\\\"help\\\"):\\n self.initialize()\\n\\n # run the start callback\\n tools.run_callback(\\\"start\\\", {'request': self._request})\\n\\n config = self._request.getConfig()\\n data = self._request.getData()\\n\\n # invoke all callbacks for the 'callback'\\n handled = tools.run_callback(callback,\\n {'request': self._request},\\n mappingfunc=lambda x,y:x,\\n donefunc=lambda x:x)\\n\\n # do end callback\\n tools.run_callback(\\\"end\\\", {'request': request})\",\n \"def connect(\\n cls,\\n on_start=None,\\n on_resume=None,\\n on_pause=None,\\n on_stop=None,\\n on_save=None,\\n on_reset=None,\\n ):\\n if on_start and on_start not in cls.start_callback:\\n cls.start_callback.append(on_start)\\n\\n if on_resume and on_resume not in cls.resume_callback:\\n cls.resume_callback.append(on_resume)\\n\\n if on_pause and on_pause not in cls.pause_callback:\\n cls.pause_callback.append(on_pause)\\n\\n if on_stop and on_stop not in cls.stop_callback:\\n cls.stop_callback.append(on_stop)\\n\\n if on_save and on_save not in cls.save_callback:\\n cls.save_callback.append(on_save)\\n\\n if on_reset and on_reset not in cls.reset_callback:\\n cls.reset_callback.append(on_reset)\",\n \"def start(self):\\n self._setup_thread()\\n self.thread.start()\",\n \"def start(self):\\n if not self.periodic._running:\\n self.periodic.start()\\n else:\\n raise Exception('PeriodicCallback already running.')\",\n \"def on_start(self, ctx):\\n pass\",\n \"def start(self):\\n self.watcher.start()\\n self._asyncio_loop.run_forever()\",\n \"def start(self):\\n self._closing_checks = {}\\n self._refresh_closing_checks()\\n self._bind_observers()\",\n \"def on_train_start(self):\\n for callback in self.callbacks:\\n callback.on_train_start(self, self.get_model())\",\n \"def on_batch_start(self):\\n for callback in self.callbacks:\\n callback.on_batch_start(self, self.get_model())\",\n \"def start(self) -> None:\\n self.__enter__()\",\n \"async def on_start(self):\",\n \"def start(self):\\n self._thread.start()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7341116","0.72688156","0.72455454","0.72304714","0.7201714","0.71944135","0.7172131","0.7172131","0.7169214","0.7162993","0.71609396","0.7144856","0.7144856","0.7144856","0.7144856","0.7144856","0.7144856","0.7144856","0.7144856","0.7108717","0.7108717","0.70965916","0.70965916","0.7095892","0.7054989","0.7040714","0.70346373","0.701287","0.70057","0.70057","0.69840544","0.6983677","0.6983677","0.6983677","0.6983024","0.6932758","0.68972","0.68613577","0.68613577","0.68613577","0.68613577","0.6860318","0.68409616","0.68409616","0.68317664","0.68277335","0.67829895","0.6775856","0.6775856","0.6775856","0.6775856","0.6775856","0.6775856","0.6775856","0.6775856","0.67728764","0.6767403","0.6767403","0.6767403","0.6767403","0.67590046","0.6758911","0.675861","0.67425865","0.67377186","0.6724084","0.6714583","0.66870576","0.66868794","0.66539836","0.664426","0.664426","0.6631146","0.6628526","0.66157585","0.6609603","0.6605695","0.660433","0.65933555","0.65920436","0.6585164","0.6566071","0.6546121","0.65352273","0.6510521","0.6510521","0.64802635","0.64680576","0.6467664","0.6467005","0.646488","0.6452512","0.6449389","0.6447669","0.64461666","0.64418525","0.6437034","0.64311373","0.6423422","0.6421002","0.64193636"],"string":"[\n \"0.7341116\",\n \"0.72688156\",\n \"0.72455454\",\n \"0.72304714\",\n \"0.7201714\",\n \"0.71944135\",\n \"0.7172131\",\n \"0.7172131\",\n \"0.7169214\",\n \"0.7162993\",\n \"0.71609396\",\n \"0.7144856\",\n \"0.7144856\",\n \"0.7144856\",\n \"0.7144856\",\n \"0.7144856\",\n \"0.7144856\",\n \"0.7144856\",\n \"0.7144856\",\n \"0.7108717\",\n \"0.7108717\",\n \"0.70965916\",\n \"0.70965916\",\n \"0.7095892\",\n \"0.7054989\",\n \"0.7040714\",\n \"0.70346373\",\n \"0.701287\",\n \"0.70057\",\n \"0.70057\",\n \"0.69840544\",\n \"0.6983677\",\n \"0.6983677\",\n \"0.6983677\",\n \"0.6983024\",\n \"0.6932758\",\n \"0.68972\",\n \"0.68613577\",\n \"0.68613577\",\n \"0.68613577\",\n \"0.68613577\",\n \"0.6860318\",\n \"0.68409616\",\n \"0.68409616\",\n \"0.68317664\",\n \"0.68277335\",\n \"0.67829895\",\n \"0.6775856\",\n \"0.6775856\",\n \"0.6775856\",\n \"0.6775856\",\n \"0.6775856\",\n \"0.6775856\",\n \"0.6775856\",\n \"0.6775856\",\n \"0.67728764\",\n \"0.6767403\",\n \"0.6767403\",\n \"0.6767403\",\n \"0.6767403\",\n \"0.67590046\",\n \"0.6758911\",\n \"0.675861\",\n \"0.67425865\",\n \"0.67377186\",\n \"0.6724084\",\n \"0.6714583\",\n \"0.66870576\",\n \"0.66868794\",\n \"0.66539836\",\n \"0.664426\",\n \"0.664426\",\n \"0.6631146\",\n \"0.6628526\",\n \"0.66157585\",\n \"0.6609603\",\n \"0.6605695\",\n \"0.660433\",\n \"0.65933555\",\n \"0.65920436\",\n \"0.6585164\",\n \"0.6566071\",\n \"0.6546121\",\n \"0.65352273\",\n \"0.6510521\",\n \"0.6510521\",\n \"0.64802635\",\n \"0.64680576\",\n \"0.6467664\",\n \"0.6467005\",\n \"0.646488\",\n \"0.6452512\",\n \"0.6449389\",\n \"0.6447669\",\n \"0.64461666\",\n \"0.64418525\",\n \"0.6437034\",\n \"0.64311373\",\n \"0.6423422\",\n \"0.6421002\",\n \"0.64193636\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":81766,"cells":{"query":{"kind":"string","value":"Stop this callbacks object."},"document":{"kind":"string","value":"def stop(self, **kwargs):\n super(Json, self).stop(**kwargs)\n flat = self.get_arg_value(\"json_flat\")\n\n self.do_export_schema()\n end = \"\" if flat else \"\\n]\"\n self._fd.write(end)\n self.close_fd()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def stop(self):\n callbacks_to_invoke = None\n self.__condition.acquire()\n if self.__is_running:\n callbacks_to_invoke = self.__on_stop_callbacks\n self.__on_stop_callbacks = []\n self.__is_running = False\n self.__condition.notifyAll()\n self.__condition.release()\n\n # Invoke the stopped callbacks.\n if callbacks_to_invoke is not None:\n for callback in callbacks_to_invoke:\n callback()","def stop(self):\n self.on_stop()","def stop(self):\r\n pass","def stop(self) -> None:\n pass","def stop(self):\n pass","def stop(self):\n pass","def stop(self):\n pass","def stop(self):\n pass","def stop(self):\n pass","def stop(self):\n pass","def stop(self):\n pass","def stop(self):\n pass","def stop(self):\n pass","def stop(self):\n pass","def stop(self):\n pass","def stop (self):\n pass","def stop (self):\n pass","def Stop(self) :\n\t\t...","def stop(self) -> None:\n ...","def stop(self):\n self._listener.stop()","def stop(self):\n self._stop_signal = True","def stop(self):\n self._stop_event.set()","def stop(self):\n self._stop_event.set()","def stop(self):\n self.io_loop.add_callback(self.io_loop.stop)","def stop(self) -> None:\n raise NotImplementedError(\"Base method not implemented\")","def stop(self):\n raise NotImplementedError","def stop(self):\n raise NotImplementedError","def stop(self) -> None:","def stop(self) -> None:","def stop(self):\n self.api.stop()","def stop(self):\r\n self._stop.set()","def stop(self):\n\n self._stop.set()","def stop(self):\n with self.stop_lock:\n self._stop_event.set()","def stop(self) :\n raise NotImplementedError(\"stop not implemented\")","def stop(self):\n if self._running:\n self._running = False\n self._call.stop()","def stop(self, timeout=2.0):\n self._callback.stop(timeout=timeout)\n \n cleanup_members()\n cleanup_singletons()","def stop(self):\n self._stop_flag = True","def stop(self) -> None:\n raise NotImplementedError()","def stop(self) -> None:\n raise NotImplementedError()","def stop(self):","def stop(self):","def stop(self):\n\t\tpass","def stop(self):\n self._stop.set()","def stop(self):\r\n raise NotImplementedError('method stop() is not implemented')","def stop(self):\n return","def stop(self):\n self.stopped = True","def stop(self):\n self.stopped = True","def stop(self):\n\n self.stop_thread = True","def stop(self):\n self.__running = False","def stop(self):\n self._stop = True\n self.wake_up()","def stop(self):\n self._running = False","def stop(self):\n self._running = False","def stop(self):\n raise NotImplementedError()","def stop(self):\n raise NotImplementedError()","def stop(self):\r\n self.stopped = True","def stop(self, **kwargs):\n self.turn_off()","def stop(self):\n with self.stop_event_lock:\n self.stop_event.set()\n self.clean_up()","def stop(self):\n self.send_stop()\n self.join()","def stop(self):\n self.stop_event.set()","def stop(self):\n self.stop_event.set()","def stop(self) -> None:\n self._running = False","def _stop(self) -> None:\n self._stopped.set()","def stop(self):\n self.unhook()","def stop(self):\n\n self.keep_running = False","def stop(self):\n self._stop_event.set()\n super().stop()","def stop(self):\n self._transport = None\n self._cleanup()\n self._disconnected_callback = None","def stop(self):\n\n self.active = False","def stop(self):\n self.running = False","def stop(self):\n self.running = False","def stop(self):\n self.running = False","def stop(self):\n self.running = False","def stop(self):\n self.running = False","def _stop(self):","def stop(self):\n with self._lock:\n if not self.stopped():\n self._started = None\n getattr(self.factory, 'stop_' + self.class_name())(self)","def stop(self):\n with self._state_change:\n if not self._running:\n return\n\n self._running = False\n\n for queue in (self.callback_queue,):\n queue.put(_STOP)\n\n while self._workers:\n worker = self._workers.pop()\n worker.join()\n\n # Clear the queues\n self.callback_queue = self.queue_impl() # pragma: nocover\n\n python2atexit.unregister(self.stop)","def stop(self):\r\n self.running = False","def stop(self):\r\n self.running = False","def stop(self):\n self.stream.stop()\n self.running = False","async def stop(self):","def foreceStop(self):\n self.__success = False\n self.stop()","def stop(self):\n self._stop_event.set()","def cancel(self):\n self.stop()\n self.make_callback('canceled')","def stop(self):\n self._Thread__stop()","def stop(self):\n GameEngine().stop()\n self.on_stop()","def stop(self):\n raise NotImplementedError(\"(%s).stop\" % self)","def stop(self):\n\n self.detach()\n self._pi.stop()\n self._stopped = True","def stop(self):\n self.listener.stop()\n self.broadcaster.stop()","def stop(self):\n super().stop()","def stop(self) -> None:\n self._stream.stop()","def stop(self):\n self.disconnect()","def stop(self):\n self.disconnect()","def stop():","def stop():","def stop():","def stop():","def stop(self) -> None:\n self._stream.stop()","def stop() -> None:","def stop(self):\n self._alive = False","def stop(self):\n self.stopped = True\n # FIXME?: Why is this not doing anything? Shouldn't it be calling into the player API?","def deactivate(self) -> None:\n return self.stop()","def _stop(self):\n self._pi.stop()"],"string":"[\n \"def stop(self):\\n callbacks_to_invoke = None\\n self.__condition.acquire()\\n if self.__is_running:\\n callbacks_to_invoke = self.__on_stop_callbacks\\n self.__on_stop_callbacks = []\\n self.__is_running = False\\n self.__condition.notifyAll()\\n self.__condition.release()\\n\\n # Invoke the stopped callbacks.\\n if callbacks_to_invoke is not None:\\n for callback in callbacks_to_invoke:\\n callback()\",\n \"def stop(self):\\n self.on_stop()\",\n \"def stop(self):\\r\\n pass\",\n \"def stop(self) -> None:\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop(self):\\n pass\",\n \"def stop (self):\\n pass\",\n \"def stop (self):\\n pass\",\n \"def Stop(self) :\\n\\t\\t...\",\n \"def stop(self) -> None:\\n ...\",\n \"def stop(self):\\n self._listener.stop()\",\n \"def stop(self):\\n self._stop_signal = True\",\n \"def stop(self):\\n self._stop_event.set()\",\n \"def stop(self):\\n self._stop_event.set()\",\n \"def stop(self):\\n self.io_loop.add_callback(self.io_loop.stop)\",\n \"def stop(self) -> None:\\n raise NotImplementedError(\\\"Base method not implemented\\\")\",\n \"def stop(self):\\n raise NotImplementedError\",\n \"def stop(self):\\n raise NotImplementedError\",\n \"def stop(self) -> None:\",\n \"def stop(self) -> None:\",\n \"def stop(self):\\n self.api.stop()\",\n \"def stop(self):\\r\\n self._stop.set()\",\n \"def stop(self):\\n\\n self._stop.set()\",\n \"def stop(self):\\n with self.stop_lock:\\n self._stop_event.set()\",\n \"def stop(self) :\\n raise NotImplementedError(\\\"stop not implemented\\\")\",\n \"def stop(self):\\n if self._running:\\n self._running = False\\n self._call.stop()\",\n \"def stop(self, timeout=2.0):\\n self._callback.stop(timeout=timeout)\\n \\n cleanup_members()\\n cleanup_singletons()\",\n \"def stop(self):\\n self._stop_flag = True\",\n \"def stop(self) -> None:\\n raise NotImplementedError()\",\n \"def stop(self) -> None:\\n raise NotImplementedError()\",\n \"def stop(self):\",\n \"def stop(self):\",\n \"def stop(self):\\n\\t\\tpass\",\n \"def stop(self):\\n self._stop.set()\",\n \"def stop(self):\\r\\n raise NotImplementedError('method stop() is not implemented')\",\n \"def stop(self):\\n return\",\n \"def stop(self):\\n self.stopped = True\",\n \"def stop(self):\\n self.stopped = True\",\n \"def stop(self):\\n\\n self.stop_thread = True\",\n \"def stop(self):\\n self.__running = False\",\n \"def stop(self):\\n self._stop = True\\n self.wake_up()\",\n \"def stop(self):\\n self._running = False\",\n \"def stop(self):\\n self._running = False\",\n \"def stop(self):\\n raise NotImplementedError()\",\n \"def stop(self):\\n raise NotImplementedError()\",\n \"def stop(self):\\r\\n self.stopped = True\",\n \"def stop(self, **kwargs):\\n self.turn_off()\",\n \"def stop(self):\\n with self.stop_event_lock:\\n self.stop_event.set()\\n self.clean_up()\",\n \"def stop(self):\\n self.send_stop()\\n self.join()\",\n \"def stop(self):\\n self.stop_event.set()\",\n \"def stop(self):\\n self.stop_event.set()\",\n \"def stop(self) -> None:\\n self._running = False\",\n \"def _stop(self) -> None:\\n self._stopped.set()\",\n \"def stop(self):\\n self.unhook()\",\n \"def stop(self):\\n\\n self.keep_running = False\",\n \"def stop(self):\\n self._stop_event.set()\\n super().stop()\",\n \"def stop(self):\\n self._transport = None\\n self._cleanup()\\n self._disconnected_callback = None\",\n \"def stop(self):\\n\\n self.active = False\",\n \"def stop(self):\\n self.running = False\",\n \"def stop(self):\\n self.running = False\",\n \"def stop(self):\\n self.running = False\",\n \"def stop(self):\\n self.running = False\",\n \"def stop(self):\\n self.running = False\",\n \"def _stop(self):\",\n \"def stop(self):\\n with self._lock:\\n if not self.stopped():\\n self._started = None\\n getattr(self.factory, 'stop_' + self.class_name())(self)\",\n \"def stop(self):\\n with self._state_change:\\n if not self._running:\\n return\\n\\n self._running = False\\n\\n for queue in (self.callback_queue,):\\n queue.put(_STOP)\\n\\n while self._workers:\\n worker = self._workers.pop()\\n worker.join()\\n\\n # Clear the queues\\n self.callback_queue = self.queue_impl() # pragma: nocover\\n\\n python2atexit.unregister(self.stop)\",\n \"def stop(self):\\r\\n self.running = False\",\n \"def stop(self):\\r\\n self.running = False\",\n \"def stop(self):\\n self.stream.stop()\\n self.running = False\",\n \"async def stop(self):\",\n \"def foreceStop(self):\\n self.__success = False\\n self.stop()\",\n \"def stop(self):\\n self._stop_event.set()\",\n \"def cancel(self):\\n self.stop()\\n self.make_callback('canceled')\",\n \"def stop(self):\\n self._Thread__stop()\",\n \"def stop(self):\\n GameEngine().stop()\\n self.on_stop()\",\n \"def stop(self):\\n raise NotImplementedError(\\\"(%s).stop\\\" % self)\",\n \"def stop(self):\\n\\n self.detach()\\n self._pi.stop()\\n self._stopped = True\",\n \"def stop(self):\\n self.listener.stop()\\n self.broadcaster.stop()\",\n \"def stop(self):\\n super().stop()\",\n \"def stop(self) -> None:\\n self._stream.stop()\",\n \"def stop(self):\\n self.disconnect()\",\n \"def stop(self):\\n self.disconnect()\",\n \"def stop():\",\n \"def stop():\",\n \"def stop():\",\n \"def stop():\",\n \"def stop(self) -> None:\\n self._stream.stop()\",\n \"def stop() -> None:\",\n \"def stop(self):\\n self._alive = False\",\n \"def stop(self):\\n self.stopped = True\\n # FIXME?: Why is this not doing anything? Shouldn't it be calling into the player API?\",\n \"def deactivate(self) -> None:\\n return self.stop()\",\n \"def _stop(self):\\n self._pi.stop()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7963989","0.7829633","0.77804077","0.77698517","0.7754477","0.7754477","0.7754477","0.7754477","0.7754477","0.7754477","0.7754477","0.7754477","0.7754477","0.7754477","0.7754477","0.7751761","0.7751761","0.7730036","0.7728273","0.7700817","0.7687963","0.7680435","0.7680435","0.76785123","0.76687133","0.7668131","0.7668131","0.7665994","0.7665994","0.76621425","0.7656757","0.76567096","0.76559263","0.7655563","0.7646723","0.76372266","0.7636085","0.7630554","0.7630554","0.76266795","0.76266795","0.7625087","0.7624832","0.7600787","0.75944144","0.7580159","0.7580159","0.7569561","0.7568995","0.7564821","0.75627506","0.75627506","0.7556622","0.7556622","0.75386107","0.7529622","0.7523741","0.7517503","0.75047797","0.75047797","0.74788517","0.7476014","0.7475191","0.746719","0.74616754","0.7448096","0.74424297","0.74368197","0.74368197","0.74368197","0.74368197","0.74368197","0.74292606","0.7426413","0.74214303","0.741992","0.741992","0.7418964","0.74126273","0.7412129","0.7411126","0.7410239","0.7402278","0.739044","0.7379645","0.7369778","0.73651576","0.7363647","0.7347057","0.73453104","0.73453104","0.7335638","0.7335638","0.7335638","0.7335638","0.73329085","0.7316478","0.7305836","0.73036456","0.72973037","0.7294563"],"string":"[\n \"0.7963989\",\n \"0.7829633\",\n \"0.77804077\",\n \"0.77698517\",\n \"0.7754477\",\n \"0.7754477\",\n \"0.7754477\",\n \"0.7754477\",\n \"0.7754477\",\n \"0.7754477\",\n \"0.7754477\",\n \"0.7754477\",\n \"0.7754477\",\n \"0.7754477\",\n \"0.7754477\",\n \"0.7751761\",\n \"0.7751761\",\n \"0.7730036\",\n \"0.7728273\",\n \"0.7700817\",\n \"0.7687963\",\n \"0.7680435\",\n \"0.7680435\",\n \"0.76785123\",\n \"0.76687133\",\n \"0.7668131\",\n \"0.7668131\",\n \"0.7665994\",\n \"0.7665994\",\n \"0.76621425\",\n \"0.7656757\",\n \"0.76567096\",\n \"0.76559263\",\n \"0.7655563\",\n \"0.7646723\",\n \"0.76372266\",\n \"0.7636085\",\n \"0.7630554\",\n \"0.7630554\",\n \"0.76266795\",\n \"0.76266795\",\n \"0.7625087\",\n \"0.7624832\",\n \"0.7600787\",\n \"0.75944144\",\n \"0.7580159\",\n \"0.7580159\",\n \"0.7569561\",\n \"0.7568995\",\n \"0.7564821\",\n \"0.75627506\",\n \"0.75627506\",\n \"0.7556622\",\n \"0.7556622\",\n \"0.75386107\",\n \"0.7529622\",\n \"0.7523741\",\n \"0.7517503\",\n \"0.75047797\",\n \"0.75047797\",\n \"0.74788517\",\n \"0.7476014\",\n \"0.7475191\",\n \"0.746719\",\n \"0.74616754\",\n \"0.7448096\",\n \"0.74424297\",\n \"0.74368197\",\n \"0.74368197\",\n \"0.74368197\",\n \"0.74368197\",\n \"0.74368197\",\n \"0.74292606\",\n \"0.7426413\",\n \"0.74214303\",\n \"0.741992\",\n \"0.741992\",\n \"0.7418964\",\n \"0.74126273\",\n \"0.7412129\",\n \"0.7411126\",\n \"0.7410239\",\n \"0.7402278\",\n \"0.739044\",\n \"0.7379645\",\n \"0.7369778\",\n \"0.73651576\",\n \"0.7363647\",\n \"0.7347057\",\n \"0.73453104\",\n \"0.73453104\",\n \"0.7335638\",\n \"0.7335638\",\n \"0.7335638\",\n \"0.7335638\",\n \"0.73329085\",\n \"0.7316478\",\n \"0.7305836\",\n \"0.73036456\",\n \"0.72973037\",\n \"0.7294563\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":81767,"cells":{"query":{"kind":"string","value":"Process the callbacks for current row."},"document":{"kind":"string","value":"def process_row(self, row: Union[List[dict], dict]) -> List[dict]:\n rows = listify(row)\n rows = self.do_pre_row(rows=rows)\n row_return = [{\"internal_axon_id\": row[\"internal_axon_id\"]} for row in rows]\n rows = self.do_row(rows=rows)\n self.write_rows(rows=rows)\n del rows, row\n return row_return"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def set_row_callback(self, row_idx, callback):\n self.row_config[row_idx]['callback'] = callback","def handleRowDataChange(self, changedItem ):\n with Tracer(traceLogger):\n # Figure out which row this widget is in\n row = changedItem.row()\n column = changedItem.column()\n\n # Can't update until the row is fully initialized\n needUpdate = True\n needUpdate &= column == Column.Name or column == Column.InternalID\n needUpdate &= self.fileInfoTableWidget.item(row, Column.Name) != None\n needUpdate &= self.fileInfoTableWidget.cellWidget(row, Column.InternalID) != None\n needUpdate &= self.fileInfoTableWidget.cellWidget(row, column) is not None\n\n if needUpdate:\n self.updateFilePath(row)","def execute_callbacks(query, result):\n for func in self.callbacks:\n func(query, result)","def on_batch_end(self):\n for callback in self.callbacks:\n callback.on_batch_end(self, self.get_model())","def perform_callback(self, *args, **kwargs):\n pass","def data_callback_modify(self, c, e, callback):\n if e:\n raise e\n\n if c.description:\n row = c.fetchone()\n callback(row[0])\n else:\n callback(None)","def callback_tablechanged(table_data):\n return {\n \"data\": [\n {\"x\": [row[\"x0\"], row[\"x1\"]], \"y\": [row[\"y0\"], row[\"y1\"]], \"type\": \"line\"}\n for row in table_data\n ]\n }","def process_data_callback(self, res):\n self.current_in_progress -= 1","def __process_table_event(self, item):\n if item is not None:\n if isinstance(item, TableEvent) \\\n and item.table_event_type == TableEventType.INSERT \\\n and item.records is not None \\\n and len(item.records) > 0:\n for index, message in enumerate(item.records):\n print(message)\n elif isinstance(item, TableEvent) \\\n and (item.table_event_type in [TableEventType.DELETE, TableEventType.UPDATE]) \\\n and item.count is not None \\\n and item.count > 0:\n if item.table_event_type == TableEventType.DELETE:\n print(\"Records deleted = %s\" % item.count)\n else:\n print(\"Records updated = %s\" % item.count)","def table_callback(table, data, event, column=False):\n if column:\n table.object = data.loc[event.new]\n else:\n table.object = data.loc[event.new:event.new]","def component_callbacks(self, app):\n @app.callback(\n Output('main_table', 'selected_rows' + self.title),\n Input('Mygraph-normal-plot', 'selectedData'))\n def display_selected_data(graphPoints):\n \"\"\"\n Display the selected data i the table.\n :param graphPoints: Data that is currently displayed\n :return: Table\n \"\"\"\n points_selected = []\n if graphPoints is not None:\n print(graphPoints)\n for point in graphPoints['points']:\n points_selected.append(point['customdata'][0])\n return points_selected","def on_batch_start(self):\n for callback in self.callbacks:\n callback.on_batch_start(self, self.get_model())","def _forward_cb(self, *args, **kwargs):\n for callback_function in self.changeCallbacks:\n callback_function(*args, **kwargs)","def _trigger_callback(self, *args, **kwargs):\n for callback_function in self.changeCallbacks:\n callback_function(self, *args, **kwargs)","def tbl_images_cell_changed_callback(self, row: int, col: int):\n editable_cols = {\n 'filename': 1,\n 'description': 4\n }\n\n if col not in editable_cols.values():\n return\n\n image_id = self.tbl_images.item(row, 0).text()\n filename = self.tbl_images.item(row, 1).text()\n description = self.tbl_images.item(row, 4).text()\n\n if col == editable_cols['filename']:\n ret = api.edit_filename(image_id, filename, self.user_hash)\n if ret.get('success') is False:\n self.show_error(ret['error_msg'])\n\n elif col == editable_cols['description']:\n ret = api.edit_description(image_id, description, self.user_hash)\n if ret.get('success') is False:\n self.show_error(ret['error_msg'])","def callback(self):\n pass # pragma: no cover","def __call__(self, connection, table, buffer, context, row, engine):\n\n buffer.put(row)\n\n yield from self.commit(table, connection, buffer)","def execute(self):\n\t\tfor callback in self:\n\t\t\tcallback()","def create_row_processor(self, context, path, reduced_path, mapper, \n row, adapter):\n\n return None, None, None","def add_common_callbacks(self):\n app = self.app\n\n @app.callback(\n [\n Output(\"column_title\", \"children\"),\n Output(\"column_type\", \"children\"),\n ],\n [\n Input(\"input_column\", \"value\"),\n ],\n )\n def update_column_title(col):\n \"\"\"Update the content title.\"\"\"\n col_type = self.features_bucket_mapping_.get(col).type\n return [f\"Feature '{col}'\"], [col_type]\n\n @app.callback(\n [Output(\"code_export\", \"content\")],\n [Input(\"input_map\", \"value\")],\n )\n def update_code_export(input_map):\n return [f\"UserInputBucketer({self.features_bucket_mapping_.as_dict()})\"]","def _apply_func(data, func, num_rows, base_row_index=0, increment=False):\n row = list(data[base_row_index])\n curr_index = base_row_index\n for _ in range(num_rows):\n data.append(func(row))\n if increment:\n curr_index += 1\n row = list(data[curr_index])\n return data","def create_row_processor(self, context, path, reduced_path, \n mapper, row, adapter):\n return None, None, None","def cell_change_current(self):\n\n # Add exception handling for case when new row is added to unmodified file to avoid crash\n try:\n if self.check_cell_change:\n row = self.csv_data_table.currentRow()\n col = self.csv_data_table.currentColumn()\n value = self.csv_data_table.item(row, col).text()\n\n self.set_bottom_toolbar_info()\n\n except:\n pass\n finally:\n # Set the flag to changes in current file state\n if self.check_cell_change:\n self.file_changed = True\n self.set_save_enabled(True)","def _during_execute(self, db):\n pass","def table_edit_callback(data, data_previous):\n # Determine where the change occurred\n diff = diff_dashtable(data, data_previous)\n\n for d in diff:\n r_changed = d['index']\n c_changed = d['column_name']\n print(f\"Caught a change in the table at {r_changed} {c_changed}!\")\n\n # # If the column is empty it won't be in the dict. Use .get to handle this with empty string as default\n # data[r_changed][CHANGED_COLUMN] = f\"{data[r_changed].get(CHANGED_COLUMN, '')} {CHANGED_PAD_START}{c_changed}{CHANGED_PAD_END}\"\n return data","def call_transition_cbs(self):\n try:\n for (cb,args) in self._transition_cbs:\n cb(self.userdata, self.get_active_states(), *args)\n except:\n smach.logerr(\"Could not execute transition callback: \"+traceback.format_exc())","def Echocallback(self, Frame_data):","def handle(self, message):\n for callback in self.callbacks:\n callback(message['data'])","def process_record(self, record):\n raise NotImplementedError('Process record needs to be customized')","def process(self, row):\n #print (row)\n \n key = conf[\"equipment_id\"]\n \n result = \"test start\" \n result = \"test end\" \n \n data = 1 ## 1\n \n self.db.save(key, result, data)","def do_callback(self, sensor):\n if sensor in self._callbacks:\n for callback in self._callbacks[sensor]:\n try:\n callback(None)\n except Exception as e:\n self.stick.logger.error(\n \"Error while executing all callback : %s\",\n e,\n )","def on_result(self, callback):\n self.result_callback = callback","def __call__(self,row):\n filterType = row.pop(0)\n if filterType: #i.e. not none and >0\n result = self.dispatch[filterType](row,self.prev)\n self.prev = result\n return result\n else:\n self.prev = row\n return self.prev","def __clb_handler(self, update, context):\n trigger = update.callback_query.data\n self.__handler(context, update, trigger)","def _add_callback_processing(self):\n pass","def process_data(self, data):\n parsed = json.loads(data)\n current = parsed[\"current\"]\n future = parsed[\"hourly\"]\n current_res = self.get_columns(current)\n self.database_conn(\"current\", -1, current_res)\n for hour, data in enumerate(future):\n current_res = self.get_columns(data)\n self.database_conn(\"current\", hour, current_res)","def process_row(row, row_num, column_map, num_required_columns, additional_isbn_columns,\n doab_analysis, doaj_analysis, no_crossref_lookup=False, no_pubmed_lookup=False,\n no_doaj_lookup=False, no_title_lookup=False, round_monetary=False,\n offsetting_mode=None, orig_file_path=None, crossref_max_retries=3):\n if len(row) != num_required_columns:\n msg = \"Line %s: \" + MESSAGES[\"num_columns\"]\n logging.error(msg, row_num, len(row), num_required_columns)\n return row\n\n empty_row = True\n for elem in row:\n if has_value(elem):\n empty_row = False\n break\n else:\n msg = \"Line %s: \" + MESSAGES[\"empty_row\"]\n logging.warning(msg, row_num)\n\n current_row = {}\n record_type = None\n\n # Copy content of identified columns and apply special processing rules\n for csv_column in column_map.values():\n index, column_type = csv_column.index, csv_column.column_type\n if empty_row:\n current_row[column_type] = \"\"\n continue\n if column_type == \"euro\" and index is not None:\n current_row[\"euro\"] = _process_euro_value(row[index], round_monetary, row_num, index, offsetting_mode)\n elif column_type == \"period\" and index is not None:\n current_row[\"period\"] = _process_period_value(row[index], row_num)\n elif column_type == \"is_hybrid\" and index is not None:\n current_row[\"is_hybrid\"] = _process_hybrid_status(row[index], row_num)\n elif column_type == \"institution\" and index is not None:\n current_row[\"institution\"] = _process_institution_value(row[index], row_num, orig_file_path, offsetting_mode)\n else:\n if index is not None and len(row[index]) > 0:\n current_row[column_type] = row[index]\n else:\n current_row[column_type] = \"NA\"\n\n doi = current_row[\"doi\"]\n if not has_value(doi) and not empty_row:\n msg = (\"Line %s: No DOI found\")\n logging.info(msg, row_num)\n current_row[\"indexed_in_crossref\"] = \"FALSE\"\n # lookup ISBNs in crossref\n additional_isbns = [row[i] for i in additional_isbn_columns]\n found_doi, r_type = _isbn_lookup(current_row, row_num, additional_isbns, doab_analysis.isbn_handling)\n if r_type is not None:\n record_type = r_type\n if found_doi is not None:\n # integrate DOI into row and restart\n logging.info(\"New DOI integrated, restarting enrichment for current line.\")\n index = column_map[\"doi\"].index\n row[index] = found_doi\n return process_row(row, row_num, column_map, num_required_columns, additional_isbn_columns,\n doab_analysis, doaj_analysis, no_crossref_lookup, no_pubmed_lookup,\n no_doaj_lookup, no_title_lookup, round_monetary, offsetting_mode, orig_file_path)\n # lookup the book title in Crossref\n lookup_title = current_row[\"book_title\"]\n if has_value(lookup_title):\n msg = (\"Line %s: Trying to look up the book title ('%s') in Crossref...\")\n logging.info(msg, row_num, lookup_title)\n book_doi = title_lookup(lookup_title, [\"book\", \"monograph\", \"reference-book\"])\n if book_doi:\n logging.info(\"New DOI integrated, restarting enrichment for current line.\")\n index = column_map[\"doi\"].index\n row[index] = book_doi\n return process_row(row, row_num, column_map, num_required_columns, additional_isbn_columns,\n doab_analysis, doaj_analysis, no_crossref_lookup, no_pubmed_lookup,\n no_doaj_lookup, no_title_lookup, round_monetary, offsetting_mode, orig_file_path)\n if has_value(doi):\n # Normalise DOI\n norm_doi = get_normalised_DOI(doi)\n if norm_doi is not None and norm_doi != doi:\n current_row[\"doi\"] = norm_doi\n msg = MESSAGES[\"doi_norm\"].format(doi, norm_doi)\n logging.info(msg)\n doi = norm_doi\n # include crossref metadata\n if not no_crossref_lookup:\n crossref_result = get_metadata_from_crossref(doi)\n retries = 0\n while not crossref_result[\"success\"] and crossref_result[\"error_msg\"].startswith(\"HTTPError: 504\"):\n if retries >= crossref_max_retries:\n break\n # retry on gateway timeouts, crossref API is quite busy sometimes\n msg = \"%s, retrying...\"\n logging.warning(msg, crossref_result[\"error_msg\"])\n retries += 1\n crossref_result = get_metadata_from_crossref(doi)\n if not crossref_result[\"success\"]:\n exc = crossref_result[\"exception\"]\n # check if a preprint lookup is possible\n if not no_title_lookup and type(exc) == UnsupportedDoiTypeError and exc.doi_type == \"posted-content\":\n msg = (\"Line %s: Found a DOI with type 'posted_content' (%s). This might \" +\n \"be a case of a preprint DOI, trying to find the final version of the article...\")\n logging.info(msg, row_num, doi)\n if not exc.crossref_title:\n msg = \"Line %s: Preprint lookup failed, no title could be extracted.\"\n logging.warning(msg, row_num)\n else:\n article_doi = title_lookup(exc.crossref_title, [\"journal-article\"])\n if article_doi:\n logging.info(\"New DOI integrated, restarting enrichment for current line...\")\n index = column_map[\"doi\"].index\n row[index] = article_doi\n return process_row(row, row_num, column_map, num_required_columns, additional_isbn_columns,\n doab_analysis, doaj_analysis, no_crossref_lookup, no_pubmed_lookup,\n no_doaj_lookup, no_title_lookup, round_monetary, offsetting_mode, orig_file_path)\n if crossref_result[\"success\"]:\n data = crossref_result[\"data\"]\n record_type = data.pop(\"doi_type\")\n logging.info(\"Crossref: DOI resolved: \" + doi + \" [\" + record_type + \"]\")\n current_row[\"indexed_in_crossref\"] = \"TRUE\"\n for key, value in data.items():\n new_value = _process_crossref_results(current_row, row_num, key, value)\n old_value = current_row[key]\n current_row[key] = column_map[key].check_overwrite(old_value, new_value)\n else:\n msg = \"Line %s: Crossref: Error while trying to resolve DOI %s: %s\"\n logging.error(msg, row_num, doi, crossref_result[\"error_msg\"])\n current_row[\"indexed_in_crossref\"] = \"FALSE\"\n # lookup ISBNs in crossref and try to find a correct DOI\n additional_isbns = [row[i] for i in additional_isbn_columns]\n found_doi, r_type = _isbn_lookup(current_row, row_num, additional_isbns, doab_analysis.isbn_handling)\n if r_type is not None:\n record_type = r_type\n if found_doi is not None:\n # integrate DOI into row and restart\n logging.info(\"New DOI integrated, restarting enrichment for current line.\")\n index = column_map[\"doi\"].index\n row[index] = found_doi\n return process_row(row, row_num, column_map, num_required_columns, additional_isbn_columns,\n doab_analysis, doaj_analysis, no_crossref_lookup, no_pubmed_lookup,\n no_doaj_lookup, no_title_lookup, round_monetary, offsetting_mode, orig_file_path)\n # include pubmed metadata\n if not no_pubmed_lookup and record_type == \"journal-article\":\n pubmed_result = get_metadata_from_pubmed(doi)\n if pubmed_result[\"success\"]:\n logging.info(\"Pubmed: DOI resolved: \" + doi)\n data = pubmed_result[\"data\"]\n for key, value in data.items():\n if value is not None:\n new_value = value\n else:\n new_value = \"NA\"\n msg = \"WARNING: Element %s not found in in response for doi %s.\"\n logging.debug(msg, key, doi)\n old_value = current_row[key]\n current_row[key] = column_map[key].check_overwrite(old_value, new_value)\n else:\n msg = \"Line %s: Pubmed: Error while trying to resolve DOI %s: %s\"\n logging.error(msg, row_num, doi, pubmed_result[\"error_msg\"])\n\n # lookup in DOAJ. try the EISSN first, then ISSN and finally print ISSN\n if not no_doaj_lookup and not empty_row:\n issns = []\n new_value = \"NA\"\n if current_row[\"issn_electronic\"] != \"NA\":\n issns.append(current_row[\"issn_electronic\"])\n if current_row[\"issn\"] != \"NA\":\n issns.append(current_row[\"issn\"])\n if current_row[\"issn_print\"] != \"NA\":\n issns.append(current_row[\"issn_print\"])\n for issn in issns:\n lookup_result = doaj_analysis.lookup(issn)\n if lookup_result:\n msg = \"DOAJ: Journal ISSN (%s) found in DOAJ offline copy ('%s').\"\n logging.info(msg, issn, lookup_result)\n new_value = \"TRUE\"\n break\n else:\n msg = \"DOAJ: Journal ISSN (%s) not found in DOAJ offline copy.\"\n new_value = \"FALSE\"\n logging.info(msg, issn)\n old_value = current_row[\"doaj\"]\n current_row[\"doaj\"] = column_map[\"doaj\"].check_overwrite(old_value, new_value)\n if record_type != \"journal-article\" and not empty_row:\n collected_isbns = []\n for isbn_field in [\"isbn\", \"isbn_print\", \"isbn_electronic\"]:\n # test and split all ISBNs\n current_row[isbn_field] = _process_isbn(row_num, current_row[isbn_field], doab_analysis.isbn_handling)\n if has_value(current_row[isbn_field]):\n collected_isbns.append(current_row[isbn_field])\n additional_isbns = [row[i] for i in additional_isbn_columns]\n for isbn in additional_isbns:\n result = _process_isbn(row_num, isbn, doab_analysis.isbn_handling)\n if has_value(result):\n collected_isbns.append(result)\n if len(collected_isbns) == 0:\n logging.info(\"No ISBN found, skipping DOAB lookup.\")\n current_row[\"doab\"] = \"NA\"\n else:\n record_type = \"book\"\n logging.info(\"Trying a DOAB lookup with the following values: \" + str(collected_isbns))\n for isbn in collected_isbns:\n doab_result = doab_analysis.lookup(isbn)\n if doab_result is not None:\n current_row[\"doab\"] = \"TRUE\"\n msg = 'DOAB: ISBN %s found in normalized DOAB (%s, \"%s\")'\n logging.info(msg, isbn, doab_result[\"publisher\"], doab_result[\"book_title\"])\n if current_row[\"indexed_in_crossref\"] == \"TRUE\":\n msg = \"Book already found in Crossref via DOI, those results take precedence\"\n logging.info(msg)\n else:\n for key in doab_result:\n current_row[key] = doab_result[key]\n if not has_value(current_row[\"isbn\"]):\n current_row[\"isbn\"] = isbn\n break\n else:\n current_row[\"doab\"] = \"FALSE\"\n msg = \"DOAB: None of the ISBNs found in DOAB\"\n logging.info(msg)\n if offsetting_mode:\n current_row[\"agreement\"] = offsetting_mode\n record_type = \"journal-article_transagree\"\n\n if record_type is None:\n msg = \"Line %s: Could not identify record type, using default schema 'journal-article'\"\n logging.warning(msg, row_num)\n record_type = \"journal-article\"\n\n result = []\n for field in COLUMN_SCHEMAS[record_type]:\n result.append(current_row[field])\n\n return (record_type, result)","def on_update_seatable(data, index, *args):\n row = convert_row(metadata, data)\n print(row)","def run_bulk_process(\n row_handler, rows, progress_label=None, stats=None, raise_global_error=True\n):\n processor = _create_bulk_processor(\n row_handler,\n rows,\n progress_label,\n stats=stats,\n raise_global_error=raise_global_error,\n )\n return processor.run()","def process_steps(self, df, **kwargs):\n pass","def on_tab_records_currentChanged(self, index):\n # TODO: not implemented yet\n raise NotImplementedError","def feedDataRow(self, row, **kwargs): \n\n self.nullify()\n \n #avoid automatic call to \"read\" after _objectid changes \n self._feed = True\n self._objectid = row['objectid']\n self._feed = False\n \n self._original_values.clear()\n for cn in row:\n if cn in self._extra_sql_columns:\n self.__dict__[cn] = row[cn]\n if cn not in self._table: continue\n field = self._table[cn]\n decoded = field.val_sql2py ( row[cn] )\n self.__dict__[cn] = decoded\n self._original_values[cn] = decoded\n \n #if _astxt was not provided with the data, _reprfunc is not set,\n #get the text from database\n if '_astxt' in row:\n self._astxt = row['_astxt']\n elif self._reprfunc:\n self._astxt = self._reprfunc (self)\n else: \n self._astxt = self.TextCache[self._objectid] or \"(none)\"\n \n if self._resolve_child_ref:\n for child_handle in self._child_referencelist:\n t, f = self._table.reference_child_hash[child_handle] \n self._child_referencelist[child_handle].filter = f.name + \" = '\" + str(row['objectid']) + \"'\"\n self._child_referencelist[child_handle].reload()\n \n self._hasdata = True\n self._isnew = False\n self._ismodified = False\n self._modified_values.clear()","def on_button_group(self, row_index: int):\n\n def _callback(attr, old, new):\n # Note: bokeh.core.PropertyList can not be deep copied\n # it RuntimeErrors, cast as list instead\n active = list(new)\n self.notify(on_button_group(row_index, active))\n\n return _callback","def run(self, row, **kwargs):\n self.source = row\n kwargs['output'] = self.__graph__()\n super(CSVRowProcessor, self).run(**kwargs)\n return kwargs['output']","def update_row_flag_status(self, index: qtc.QModelIndex):\n row = index.row()\n self.dataChanged.emit(self.index(row, 0), self.index(row, 0), [qtc.Qt.ForegroundRole])","def places_process_rows(self):\n\n for index in range(len(self.table)):\n row_rdf = self.places_map_row_to_rdf(self.table.iloc[index])\n if row_rdf is not None:\n self.data += row_rdf","def parse_row(self, response, row):\n raise NotImplementedError","def _do_change_row(self, treeview):\n _return = False\n\n self.treeview.handler_block(self._lst_handler_id[0])\n\n (_model, _row) = treeview.get_selection().get_selected()\n try:\n _level = _model.get_value(_row, 11)\n except TypeError:\n _level = None\n\n _columns = treeview.get_columns()\n\n # Change the column headings depending on what is being selected.\n if _level == 'mission':\n _headings = [\n _(u\"Mission ID\"),\n _(u\"Description\"),\n _(u\"Units\"),\n _(u\"Start Time\"),\n _(u\"End Time\"),\n _(u\"\"),\n _(u\"\"),\n _(u\"\")\n ]\n elif _level == 'phase':\n _headings = [\n _(u\"Phase ID\"),\n _(u\" Code\\t\\tDescription\"),\n _(u\"Units\"),\n _(u\"Start Time\"),\n _(u\"End Time\"),\n _(u\"\"),\n _(u\"\"),\n _(u\"\")\n ]\n elif _level == 'environment':\n _headings = [\n _(u\"Environment ID\"),\n _(u\"Condition\"),\n _(u\"Units\"),\n _(u\"Minimum Value\"),\n _(u\"Maximum Value\"),\n _(u\"Mean Value\"),\n _(u\"Variance\"),\n _(u\"\")\n ]\n else:\n _headings = []\n\n i = 0\n for _heading in _headings:\n _label = gtk.Label()\n _label.set_line_wrap(True)\n _label.set_alignment(xalign=0.5, yalign=0.5)\n _label.set_justify(gtk.JUSTIFY_CENTER)\n _label.set_markup(\"<span weight='bold'>\" + _heading + \"</span>\")\n _label.set_use_markup(True)\n _label.show_all()\n _columns[i].set_widget(_label)\n\n i += 1\n\n self.treeview.handler_unblock(self._lst_handler_id[0])\n\n return _return","def iter_rows_raw(self, *args):\n\n for row in super().iter_rows_raw(*args):\n row[0] = row[1] # sequential catalog index not right in this case; overwrite to match finder id\n yield row","def apply(self, df_events):\n pass","def update_row(self):\n self.current_row = self.next_row\n self.next_row = self.get_row()","def process_row(self, table, row):\n for index, column in enumerate(table.columns):\n hash_key = hash(frozenset(column.items()))\n column_type = self.column_types[hash_key] if hash_key in self.column_types else self.column_type(column)\n if row[index] == None and ('timestamp' not in column_type or not column['default']):\n row[index] = '\\N'\n elif row[index] == None and column['default']:\n if self.tz:\n row[index] = '1970-01-01T00:00:00.000000' + self.tz_offset\n else:\n row[index] = '1970-01-01 00:00:00'\n elif 'bit' in column_type:\n row[index] = bin(ord(row[index]))[2:]\n elif isinstance(row[index], (str, unicode, basestring)):\n if column_type == 'bytea':\n row[index] = Binary(row[index]).getquoted()[1:-8] if row[index] else row[index]\n elif 'text[' in column_type:\n row[index] = '{%s}' % ','.join('\"%s\"' % v.replace('\"', r'\\\"') for v in row[index].split(','))\n else:\n row[index] = row[index].replace('\\\\', r'\\\\').replace('\\n', r'\\n').replace(\n '\\t', r'\\t').replace('\\r', r'\\r').replace('\\0', '')\n elif column_type == 'boolean':\n # We got here because you used a tinyint(1), if you didn't want a bool, don't use that type\n row[index] = 't' if row[index] not in (None, 0) else 'f' if row[index] == 0 else row[index]\n elif isinstance(row[index], (date, datetime)):\n if isinstance(row[index], datetime) and self.tz:\n try:\n if row[index].tzinfo:\n row[index] = row[index].astimezone(self.tz).isoformat()\n else:\n row[index] = datetime(*row[index].timetuple()[:6], tzinfo=self.tz).isoformat()\n except Exception as e:\n print e.message\n else:\n row[index] = row[index].isoformat()\n elif isinstance(row[index], timedelta):\n row[index] = datetime.utcfromtimestamp(_get_total_seconds(row[index])).time().isoformat()\n else:\n row[index] = AsIs(row[index]).getquoted()","def inserted_callback(p_queue=None, p_columns=None, p_row=None, p_key=None):\n\n if not isinstance(p_queue, multiprocessing.managers.BaseProxy):\n raise custom_exceptions.InvalidParameterTypeException('\"p_queue\" parameter must be a \"multiprocessing.managers.BaseProxy\" instance.', p_queue)\n\n if not isinstance(p_columns, list):\n raise custom_exceptions.InvalidParameterTypeException('\"p_columns\" parameter must be a \"list\" instance.', p_columns)\n\n if not isinstance(p_row, list):\n raise custom_exceptions.InvalidParameterTypeException('\"p_row\" parameter must be a \"list\" instance.', p_row)\n\n if not isinstance(p_key, list):\n raise custom_exceptions.InvalidParameterTypeException('\"p_key\" parameter must be a \"list\" instance.', p_key)\n\n p_queue.put({\n 'type': 'tables',\n 'row': {\n 'schema_name': p_row['table_schema'],\n 'table_name': p_row['table_name'],\n 'status': 'INSERTED',\n 'sql': inspect.cleandoc(doc=p_row['create_table_ddl'])\n }\n })","def run_callbacks(self, **kwargs):\n for callback in self.CALLBACKS:\n getattr(self, callback)(**kwargs)","def processRow(self, row=None, pdata=None):\n\t\tcol_name2index = getattr(pdata, 'col_name2index', None)\n\t\txValue2yValueLs = getattr(pdata, 'xValue2yValueLs', None)\n\t\ty_ls = getattr(pdata, 'y_ls', None)\n\t\tif col_name2index and xValue2yValueLs is not None:\n\t\t\tif self.whichColumnHeader:\n\t\t\t\twhichColumn = col_name2index.get(self.whichColumnHeader, None)\n\t\t\telse:\n\t\t\t\twhichColumn = self.whichColumn\n\t\t\tx_index = col_name2index.get(self.xColumnHeader, None)\n\t\t\t\n\t\t\txValue = float(row[x_index])\n\t\t\txValue = self.processValue(xValue, processType=self.logX)\n\t\t\tyValue = float(row[whichColumn])\n\t\t\tyValue = self.processValue(yValue, processType=self.logY)\n\t\t\tif xValue not in xValue2yValueLs:\n\t\t\t\txValue2yValueLs[xValue] = []\n\t\t\txValue2yValueLs[xValue].append(yValue)\n\t\t\ty_ls.append(yValue)","def cell_entered(self, row: int, _):\n self.selectRow(row)","def iter_rows(self, *args):\n\n raw_args = []\n for arg in args:\n if arg in self._column_translations:\n raw_args+=self._column_translations[arg].inputs()\n else:\n raw_args.append(arg)\n for raw_values in self.iter_rows_raw(*raw_args):\n values = [raw_values[0], raw_values[1]]\n for arg in args:\n if arg in self._column_translations:\n values.append(self._column_translations[arg](raw_args, raw_values[2:]))\n else:\n values.append(raw_values[2:][raw_args.index(arg)])\n yield values","def on_train_batch_end(self, outputs, batch, batch_idx, dataloader_idx):\n for callback in self.callbacks:\n callback.on_train_batch_end(self, self.get_model(), outputs, batch, batch_idx, dataloader_idx)","def handleTableSelectionChange(self):\n self.selectEntireRow()\n self.showSelectedDataset()","def _on_bob(self) -> None:\n self.row_generator.set_bob()","def handle_record(self, record):\n raise NotImplementedError","def __clb_handler(self, bot, update):\n trigger = update.callback_query.data\n self.__handler(bot, update, trigger)","def on_row_activated(self, widget, path, view_column):\n self.launch_layout()","def ExecuteCallback(self):\n return _gmat_py.GmatBase_ExecuteCallback(self)","def _process_data(self):\r\n # Rename columns to match final feature class\r\n self._rename_columns()\r\n # Add point ID column\r\n self._add_pointid()\r\n # Sort rows by transect id and timestamp\r\n self._sort_rows()\r\n # Fill Null records with a value\r\n self._fill_nulls()\r\n # Set site_code to lower case\r\n self._lower_site_code()\r\n # Create survey_id\r\n self._calc_survey_id()\r\n # Calculate nativesg column if at least one of the veg columns is a Native seagrass type\r\n if set(self.veg_columns).intersection(set(NATIVESG_CODES)) > 0:\r\n self.nativesg_columns = list(set(self.veg_columns).intersection(set(NATIVESG_CODES)))\r\n self._calc_nativesg()\r\n #\r","def process_data(self, excel_file, output_title):\n df = read_excel(excel_file)\n labels = df.columns.values.tolist()\n title = f\"{labels[1]} vs {labels[0]}\"\n data = []\n for label in labels:\n data.append(df[label].values.tolist())\n\n for callback in self.callbacks:\n callback(title, data, labels, output_title)","def validate(self, row):\n raise NotImplementedError","def map_transfer_to_row(self, transfer):\n pass","def table_data_update_dispatcher(data_timestamp, active_cell, data, data_previous):\n # Escape if we have no data. This might not be intention if app's data is empty?\n if data is None and data_previous is None:\n return dash.no_update\n\n ctx = dash.callback_context\n if ctx.triggered[0][\"prop_id\"] == \"table.data_timestamp\":\n return table_edit_callback(data, data_previous), data_timestamp\n elif ctx.triggered[0][\"prop_id\"] == \"table.active_cell\":\n return table_on_click_via_active_cell(active_cell, data), data_timestamp\n else:\n # During app boot (?) the callback fires without normal trigger events, which can slip down here. Can't end\n # without a return because that will set table.data == None in perpetuity\n return dash.no_update","def processEscrows(self):\n\n try:\n self.processOutOfOrders()\n self.processPartials()\n self.processDuplicitous()\n self.processUnverifieds()\n self.processTransUnverifieds()\n\n except Exception as ex: # log diagnostics errors etc\n if logger.isEnabledFor(logging.DEBUG):\n logger.exception(\"Kevery escrow process error: %s\\n\", ex.args[0])\n else:\n logger.error(\"Kevery escrow process error: %s\\n\", ex.args[0])","def handle_callback_query(bot, update, session, user):\n query = update.callback_query\n data = query.data\n\n # Extract the callback type, task id\n [callback_type, payload, action] = data.split(':')\n callback_type = int(callback_type)\n action = int(action)\n\n chat = session.query(Chat).get(query.message.chat.id)\n tg_chat = query.message.chat\n\n # Handle task vote ban callbacks\n if CallbackType(callback_type).name == 'task_vote_ban':\n task = session.query(Task).get(payload)\n if CallbackResult(action).name == 'ban':\n task.sticker_set.banned = True\n call_tg_func(query, 'answer', args=['Set banned'])\n else:\n task.sticker_set.banned = False\n call_tg_func(query, 'answer', args=['Set unbanned'])\n\n if not task.reviewed:\n task.reviewed = True\n process_task(session, tg_chat, chat)\n\n # Handle task vote ban callbacks\n if CallbackType(callback_type).name == 'task_vote_nsfw':\n task = session.query(Task).get(payload)\n if CallbackResult(action).name == 'ban':\n task.sticker_set.nsfw = True\n call_tg_func(query, 'answer', args=['Set tagged as nsfw'])\n else:\n task.sticker_set.nsfw = False\n call_tg_func(query, 'answer', args=['Set no longer tagged as nsfw'])\n\n if not task.reviewed:\n task.reviewed = True\n process_task(session, tg_chat, chat)\n\n # Handle task user ban callbacks\n elif CallbackType(callback_type).name == 'task_user_revert':\n task = session.query(Task).get(payload)\n if CallbackResult(action).name == 'revert':\n task.user.banned = True\n call_tg_func(query, 'answer', args=['User banned and changes reverted'])\n revert_user_changes(session, task.user)\n\n if not task.reviewed:\n task.reviewed = True\n process_task(session, tg_chat, chat)\n\n # Handle the \"Skip this sticker\" button\n elif CallbackType(callback_type).name == 'ban_set':\n sticker_set = session.query(StickerSet).get(payload)\n if CallbackResult(action).name == 'ban':\n sticker_set.banned = True\n elif CallbackResult(action).name == 'ok':\n sticker_set.banned = False\n\n keyboard = get_nsfw_ban_keyboard(sticker_set)\n call_tg_func(query.message, 'edit_reply_markup',\n kwargs={'reply_markup': keyboard})\n\n elif CallbackType(callback_type).name == 'nsfw_set':\n sticker_set = session.query(StickerSet).get(payload)\n if CallbackResult(action).name == 'ban':\n sticker_set.nsfw = True\n elif CallbackResult(action).name == 'ok':\n sticker_set.nsfw = False\n\n keyboard = get_nsfw_ban_keyboard(sticker_set)\n call_tg_func(query.message, 'edit_reply_markup',\n kwargs={'reply_markup': keyboard})\n\n # Handle the \"Skip this sticker\" button\n elif CallbackType(callback_type).name == 'next':\n handle_next(session, chat, tg_chat)\n\n # Handle the \"Stop tagging\" button\n elif CallbackType(callback_type).name == 'cancel':\n call_tg_func(query, 'answer', args=['All active commands have been canceled'])\n call_tg_func(tg_chat, 'send_message', ['All running commands are canceled'],\n {'reply_markup': main_keyboard})\n chat.cancel()\n\n # Handle \"Fix this sticker's tags\"\n elif CallbackType(callback_type).name == 'edit_sticker':\n sticker = session.query(Sticker).get(payload)\n chat.current_sticker = sticker\n if not chat.full_sticker_set and not chat.tagging_random_sticker:\n chat.fix_single_sticker = True\n send_tag_messages(chat, tg_chat)\n\n elif CallbackType(callback_type).name == 'tag_set':\n initialize_set_tagging(bot, tg_chat, session, payload, chat, user)\n\n return","def processRow(self, row):\n\t\tif self.delim is not None:\n\t\t\trowArr = row.split(self.delim)\n\t\t\tmsg = \"row does not have expected number of columns found \" + str(len(rowArr)) + \" expected \" + str(self.rowSize)\n\t\t\tassert len(rowArr) == self.rowSize, msg\n\t\telse:\n\t\t\trowArr = row\n\t\t\t\n\t\tnewRowArr = []\n\t\tfor i in range(len(rowArr)):\n\t\t\tcurVal = rowArr[i]\n\t\t\tif (i in self.catValues):\n\t\t\t\tvalues = self.catValues[i]\n\t\t\t\tfor val in values:\n\t\t\t\t\tif val == curVal:\n\t\t\t\t\t\tnewVal = self.trueVal\n\t\t\t\t\telse:\n\t\t\t\t\t\tnewVal = self.falseVal\n\t\t\t\t\tnewRowArr.append(newVal)\n\t\t\telse:\n\t\t\t\tnewRowArr.append(curVal)\n\t\tassert len(newRowArr) == self.newRowSize, \"invalid new row size \" + str(len(newRowArr)) + \" expected \" + str(self.newRowSize)\n\t\tencRow = self.delim.join(newRowArr) if self.delim is not None else newRowArr\n\t\treturn encRow","def OutputTestRecord(self, test_record):\n for output_cb in self.output_callbacks:\n output_cb(test_record)","def _step_callback_gen(self):\n\n with open(self.output_filename, 'wb') as f: # Note: need to use wb since windows\n w = csv.writer(f, lineterminator=os.linesep) # Also lineterminator=os.linesep for cross platform compatibility\n\n while True:\n sensor, step_samples = (yield) # Wait for step_callback to send us the a sample\n\n if not self._headers_written: \n w.writerow(sensor.get_csv_headers())\n self._headers_written = True\n \n if self.sim.data_logging_enabled(self, sensor):\n for sample in step_samples:\n w.writerow(list(sample)) # Note: each sample is assumed to be a namedtuple of some sort","def csv_handle(self,instance):\n table_origin = self.csv_dataframe\n in_column_num = len(self.column_names) \n in_column_name = self.column_names\n in_column_type = self.column_types\n\n instance.column_num = instance.tables[0].column_num = in_column_num\n for i in range(instance.column_num):\n instance.tables[0].names.append(in_column_name[i])\n instance.tables[0].types.append(Type.getType(in_column_type[i].lower())) #getType is a static method\n instance.tables[0].origins = [i for i in range(instance.tables[0].column_num)]\n \n instance.tuple_num = instance.tables[0].tuple_num = table_origin.shape[0] # the number of rows\n for i in range(instance.tables[0].column_num):\n if instance.tables[0].types[i] == 3: #if there is date type column in csv,convert into datetime format\n col_name = table_origin.columns[i]\n col_type = self.column_types[i]\n self.csv_handle_changedate(col_name,col_type)\n \n #change table column name with table_info column_names (for date type columns)\n for i in range(len(table_origin.columns)):\n table_origin.rename(columns={ table_origin.columns[i] : in_column_name[i] }, inplace=True) \n instance.tables[0].D = table_origin.values.tolist() #dataframe to list type and feed to D(where to store all the table info )\n return instance","def redraw_row(cls, row):\n # TODO: Draw blocks in row","def _callback_combo_cell(self, cell, path, row, position, treemodel):\r\n\r\n _model = cell.get_property('model')\r\n _text = _model.get_value(row, 0)\r\n _index = _model.get_value(row, 1)\r\n\r\n _row = treemodel.get_iter(path)\r\n\r\n _position = treemodel.get_value(_row, 0)\r\n self._file_index[_position] = _index\r\n\r\n treemodel.set_value(_row, position, _text)\r\n\r\n return False","def _callback(self, data: list):\n self.data = data","def add_row(self, row):\n ...","def job_execute(self, row):\n job_id = self.jobsTableWidget.item(row, 0).text()\n self.connection.job_start(job_id)\n self.refresh_jobs()","def _callbackFunc(self, event: tk.Event) -> None:\n el_number = self.choose_import.current()\n if el_number == 0:\n self._print_folder_import()\n elif el_number == 1:\n self._print_camera_import()\n elif el_number == 2:\n self._print_webpage_import()\n elif el_number == 3:\n self._print_video_import()","def process_loading_file(self):\n column_headers = []\n column_headers_all = []\n\n # Open the file once to get idea of the total rowcount to display progress\n with open(self.csv_file_path[0], newline='') as csv_file:\n self.progress_max.emit(len(csv_file.readlines()) - 2)\n\n with open(self.csv_file_path[0], newline='') as csv_file:\n\n self.csv_data_table.setRowCount(0)\n self.csv_data_table.setColumnCount(0)\n\n csv_file_read = csv.reader(csv_file, delimiter=',', quotechar='|')\n\n # Fetch the column headers and move the iterator to actual data\n column_headers = next(csv_file_read)\n\n # Reflect back the changes in the reference to the column headers\n for header in column_headers:\n self.column_headers.append(header)\n # A backup to keep a list of all the headers to toogle their view later\n self.column_headers_all.append(header)\n\n # TODO: Increase the reading speed by decreasing load on actual table population\n\n # self.csv_data_table.hide()\n\n for row_data in csv_file_read:\n\n self.relay.emit(self.csv_data_table.rowCount())\n # self.relay.emit(self.x)\n # self.x = self.x + 1\n row = self.csv_data_table.rowCount()\n self.csv_data_table.insertRow(row)\n self.csv_data_table.setColumnCount(len(row_data))\n for column, stuff in enumerate(row_data):\n item = QTableWidgetItem(stuff)\n self.csv_data_table.setItem(row, column, item)\n\n self.csv_data_table.setHorizontalHeaderLabels(self.column_headers)\n\n # Set WordWrap to True to make the cells change height according to content\n # Currently set it to false as it looks very decent and makes cell size uniform throughout\n self.csv_data_table.setWordWrap(False)\n # Uncomment below line to stretch to fill the column width according to content\n # self.csv_data_table.resizeColumnsToContents()\n self.csv_data_table.resizeRowsToContents()\n\n # Update the bottom toolbar to reflect changes\n self.update_bottom_toolbar.emit()\n self.finished.emit()","def _call_followers(self, event):\n context = self.get_context(event)\n if context is not None:\n for callback in self.followers.get(context, []):\n callback(event)","def set_update_callbacks(self, update_tr_pos_callback, update_view_model_callback) -> None:\n\n self.update_tr_position = update_tr_pos_callback\n self.update_view_model = update_view_model_callback","def _apply_all(self, callback: Optional[Callable] = None) -> None:\n while self:\n op = self.apply()\n if callback:\n callback(op)","def cb(xk):\n self.iteration += 1\n t_current = time.time()\n t_elapsed = t_current - self.t_store\n self.t_store = t_current\n \n self.of_list.append(self.of_last)\n self.params = xk\n self._disp(t_elapsed)\n\n # Call the custom callback function if any\n if callback is not None:\n callback(self)","def process_data(cur, conn, filepath, func):\n # get all files matching extension from directory\n all_files = []\n for root, dirs, files in os.walk(filepath):\n files = glob.glob(os.path.join(root,'*.json'))\n for f in files :\n all_files.append(os.path.abspath(f))\n\n # get total number of files found\n num_files = len(all_files)\n print('{} files found in {}'.format(num_files, filepath))\n\n # iterate over files and process\n for i, datafile in enumerate(all_files, 1):\n func(cur, datafile)\n conn.commit()\n print('{}/{} files processed.'.format(i, num_files))","def process_data(cur, conn, filepath, func):\n # get all files matching extension from directory\n all_files = []\n for root, dirs, files in os.walk(filepath):\n files = glob.glob(os.path.join(root,'*.json'))\n for f in files :\n all_files.append(os.path.abspath(f))\n\n # get total number of files found\n num_files = len(all_files)\n print('{} files found in {}'.format(num_files, filepath))\n\n # iterate over files and process\n for i, datafile in enumerate(all_files, 1):\n func(cur, datafile)\n conn.commit()\n print('{}/{} files processed.'.format(i, num_files))","def on_validation_batch_start(self, batch, batch_idx, dataloader_idx):\n for callback in self.callbacks:\n callback.on_validation_batch_start(self, self.get_model(), batch, batch_idx, dataloader_idx)","def _run_callbacks(cls, cb_method, *args):\n global CALLBACKS\n for c in CALLBACKS:\n attr = getattr(c, cb_method)\n attr(*args)","def process_data(cur, conn, filepath, func):\n # get all files matching extension from directory\n all_files = []\n for root, dirs, files in os.walk(filepath):\n files = glob.glob(os.path.join(root,'*.json'))\n for f in files :\n all_files.append(os.path.abspath(f))\n\n num_files = len(all_files)\n print('{} files found in {}'.format(num_files, filepath))\n\n for i, datafile in enumerate(all_files, 1):\n func(cur, datafile)\n conn.commit()\n print('{}/{} files processed.'.format(i, num_files))","def process_data(cur, conn, filepath, func):\n # get all files matching extension from directory\n all_files = []\n for root, dirs, files in os.walk(filepath):\n files = glob.glob(os.path.join(root, '*.json'))\n for file in files:\n all_files.append(os.path.abspath(file))\n\n # get total number of files found\n num_files = len(all_files)\n print('{} files found in {}'.format(num_files, filepath))\n\n # iterate over files and process\n for i, datafile in enumerate(all_files, 1):\n func(cur, datafile)\n conn.commit()\n print('{}/{} files processed.'.format(i, num_files))","def update_data(self, **kwargs):\n self.source_data = self.get_dict()\n for c in self.callbacks[\"update_data\"]:\n c()","def process_data(cur, conn, filepath, func):\n # get all files matching extension from directory\n all_files = []\n for root, dirs, files in os.walk(filepath):\n files = glob.glob(os.path.join(root, '*.json'))\n for f in files:\n all_files.append(os.path.abspath(f))\n\n # get total number of files found\n num_files = len(all_files)\n print('{} files found in {}'.format(num_files, filepath))\n\n # iterate over files and process\n for i, datafile in enumerate(all_files, 1):\n func(cur, datafile)\n conn.commit()\n print('{}/{} files processed.'.format(i, num_files))","def callback(self, *args):\n raise NotImplementedError()","def _data_updated_callback(self, attr, old, new):\n pass","def process_data(cur, conn, filepath, func):\n \n # get all files matching extension from directory\n all_files = []\n for root, dirs, files in os.walk(filepath):\n files = glob.glob(os.path.join(root,'*.json'))\n for f in files:\n all_files.append(os.path.abspath(f))\n \n # get total number of files found\n num_files = len(all_files)\n print('{} files found in {}'.format(num_files, filepath))\n \n # iterate over files and process\n for i, datafile in enumerate(all_files, 1):\n func(cur, datafile)\n conn.commit()\n print('{}/{} files processed.'.format(i, num_files))","def process_data(cur, conn, filepath, func):\n\n # get all files matching extension from directory\n all_files = []\n for root, dirs, files in os.walk(filepath):\n files = glob.glob(os.path.join(root, '*.json'))\n for f in files:\n all_files.append(os.path.abspath(f))\n\n # get total number of files found\n num_files = len(all_files)\n print('{} files found in {}'.format(num_files, filepath))\n\n # iterate over files and process\n for i, datafile in enumerate(all_files, 1):\n func(cur, datafile)\n conn.commit()\n print('{}/{} files processed.'.format(i, num_files))","def edit_current_cell(self):\n cells = self.csv_data_table.selectionModel().selectedIndexes()\n if len(cells) == 1:\n for cell in sorted(cells):\n r = cell.row()\n c = cell.column()\n self.csv_data_table.editItem(self.csv_data_table.item(r, c))","def on_tableWidget_Trade_Args_cellClicked(self, row, column):\n # TODO: not implemented yet\n raise NotImplementedError"],"string":"[\n \"def set_row_callback(self, row_idx, callback):\\n self.row_config[row_idx]['callback'] = callback\",\n \"def handleRowDataChange(self, changedItem ):\\n with Tracer(traceLogger):\\n # Figure out which row this widget is in\\n row = changedItem.row()\\n column = changedItem.column()\\n\\n # Can't update until the row is fully initialized\\n needUpdate = True\\n needUpdate &= column == Column.Name or column == Column.InternalID\\n needUpdate &= self.fileInfoTableWidget.item(row, Column.Name) != None\\n needUpdate &= self.fileInfoTableWidget.cellWidget(row, Column.InternalID) != None\\n needUpdate &= self.fileInfoTableWidget.cellWidget(row, column) is not None\\n\\n if needUpdate:\\n self.updateFilePath(row)\",\n \"def execute_callbacks(query, result):\\n for func in self.callbacks:\\n func(query, result)\",\n \"def on_batch_end(self):\\n for callback in self.callbacks:\\n callback.on_batch_end(self, self.get_model())\",\n \"def perform_callback(self, *args, **kwargs):\\n pass\",\n \"def data_callback_modify(self, c, e, callback):\\n if e:\\n raise e\\n\\n if c.description:\\n row = c.fetchone()\\n callback(row[0])\\n else:\\n callback(None)\",\n \"def callback_tablechanged(table_data):\\n return {\\n \\\"data\\\": [\\n {\\\"x\\\": [row[\\\"x0\\\"], row[\\\"x1\\\"]], \\\"y\\\": [row[\\\"y0\\\"], row[\\\"y1\\\"]], \\\"type\\\": \\\"line\\\"}\\n for row in table_data\\n ]\\n }\",\n \"def process_data_callback(self, res):\\n self.current_in_progress -= 1\",\n \"def __process_table_event(self, item):\\n if item is not None:\\n if isinstance(item, TableEvent) \\\\\\n and item.table_event_type == TableEventType.INSERT \\\\\\n and item.records is not None \\\\\\n and len(item.records) > 0:\\n for index, message in enumerate(item.records):\\n print(message)\\n elif isinstance(item, TableEvent) \\\\\\n and (item.table_event_type in [TableEventType.DELETE, TableEventType.UPDATE]) \\\\\\n and item.count is not None \\\\\\n and item.count > 0:\\n if item.table_event_type == TableEventType.DELETE:\\n print(\\\"Records deleted = %s\\\" % item.count)\\n else:\\n print(\\\"Records updated = %s\\\" % item.count)\",\n \"def table_callback(table, data, event, column=False):\\n if column:\\n table.object = data.loc[event.new]\\n else:\\n table.object = data.loc[event.new:event.new]\",\n \"def component_callbacks(self, app):\\n @app.callback(\\n Output('main_table', 'selected_rows' + self.title),\\n Input('Mygraph-normal-plot', 'selectedData'))\\n def display_selected_data(graphPoints):\\n \\\"\\\"\\\"\\n Display the selected data i the table.\\n :param graphPoints: Data that is currently displayed\\n :return: Table\\n \\\"\\\"\\\"\\n points_selected = []\\n if graphPoints is not None:\\n print(graphPoints)\\n for point in graphPoints['points']:\\n points_selected.append(point['customdata'][0])\\n return points_selected\",\n \"def on_batch_start(self):\\n for callback in self.callbacks:\\n callback.on_batch_start(self, self.get_model())\",\n \"def _forward_cb(self, *args, **kwargs):\\n for callback_function in self.changeCallbacks:\\n callback_function(*args, **kwargs)\",\n \"def _trigger_callback(self, *args, **kwargs):\\n for callback_function in self.changeCallbacks:\\n callback_function(self, *args, **kwargs)\",\n \"def tbl_images_cell_changed_callback(self, row: int, col: int):\\n editable_cols = {\\n 'filename': 1,\\n 'description': 4\\n }\\n\\n if col not in editable_cols.values():\\n return\\n\\n image_id = self.tbl_images.item(row, 0).text()\\n filename = self.tbl_images.item(row, 1).text()\\n description = self.tbl_images.item(row, 4).text()\\n\\n if col == editable_cols['filename']:\\n ret = api.edit_filename(image_id, filename, self.user_hash)\\n if ret.get('success') is False:\\n self.show_error(ret['error_msg'])\\n\\n elif col == editable_cols['description']:\\n ret = api.edit_description(image_id, description, self.user_hash)\\n if ret.get('success') is False:\\n self.show_error(ret['error_msg'])\",\n \"def callback(self):\\n pass # pragma: no cover\",\n \"def __call__(self, connection, table, buffer, context, row, engine):\\n\\n buffer.put(row)\\n\\n yield from self.commit(table, connection, buffer)\",\n \"def execute(self):\\n\\t\\tfor callback in self:\\n\\t\\t\\tcallback()\",\n \"def create_row_processor(self, context, path, reduced_path, mapper, \\n row, adapter):\\n\\n return None, None, None\",\n \"def add_common_callbacks(self):\\n app = self.app\\n\\n @app.callback(\\n [\\n Output(\\\"column_title\\\", \\\"children\\\"),\\n Output(\\\"column_type\\\", \\\"children\\\"),\\n ],\\n [\\n Input(\\\"input_column\\\", \\\"value\\\"),\\n ],\\n )\\n def update_column_title(col):\\n \\\"\\\"\\\"Update the content title.\\\"\\\"\\\"\\n col_type = self.features_bucket_mapping_.get(col).type\\n return [f\\\"Feature '{col}'\\\"], [col_type]\\n\\n @app.callback(\\n [Output(\\\"code_export\\\", \\\"content\\\")],\\n [Input(\\\"input_map\\\", \\\"value\\\")],\\n )\\n def update_code_export(input_map):\\n return [f\\\"UserInputBucketer({self.features_bucket_mapping_.as_dict()})\\\"]\",\n \"def _apply_func(data, func, num_rows, base_row_index=0, increment=False):\\n row = list(data[base_row_index])\\n curr_index = base_row_index\\n for _ in range(num_rows):\\n data.append(func(row))\\n if increment:\\n curr_index += 1\\n row = list(data[curr_index])\\n return data\",\n \"def create_row_processor(self, context, path, reduced_path, \\n mapper, row, adapter):\\n return None, None, None\",\n \"def cell_change_current(self):\\n\\n # Add exception handling for case when new row is added to unmodified file to avoid crash\\n try:\\n if self.check_cell_change:\\n row = self.csv_data_table.currentRow()\\n col = self.csv_data_table.currentColumn()\\n value = self.csv_data_table.item(row, col).text()\\n\\n self.set_bottom_toolbar_info()\\n\\n except:\\n pass\\n finally:\\n # Set the flag to changes in current file state\\n if self.check_cell_change:\\n self.file_changed = True\\n self.set_save_enabled(True)\",\n \"def _during_execute(self, db):\\n pass\",\n \"def table_edit_callback(data, data_previous):\\n # Determine where the change occurred\\n diff = diff_dashtable(data, data_previous)\\n\\n for d in diff:\\n r_changed = d['index']\\n c_changed = d['column_name']\\n print(f\\\"Caught a change in the table at {r_changed} {c_changed}!\\\")\\n\\n # # If the column is empty it won't be in the dict. Use .get to handle this with empty string as default\\n # data[r_changed][CHANGED_COLUMN] = f\\\"{data[r_changed].get(CHANGED_COLUMN, '')} {CHANGED_PAD_START}{c_changed}{CHANGED_PAD_END}\\\"\\n return data\",\n \"def call_transition_cbs(self):\\n try:\\n for (cb,args) in self._transition_cbs:\\n cb(self.userdata, self.get_active_states(), *args)\\n except:\\n smach.logerr(\\\"Could not execute transition callback: \\\"+traceback.format_exc())\",\n \"def Echocallback(self, Frame_data):\",\n \"def handle(self, message):\\n for callback in self.callbacks:\\n callback(message['data'])\",\n \"def process_record(self, record):\\n raise NotImplementedError('Process record needs to be customized')\",\n \"def process(self, row):\\n #print (row)\\n \\n key = conf[\\\"equipment_id\\\"]\\n \\n result = \\\"test start\\\" \\n result = \\\"test end\\\" \\n \\n data = 1 ## 1\\n \\n self.db.save(key, result, data)\",\n \"def do_callback(self, sensor):\\n if sensor in self._callbacks:\\n for callback in self._callbacks[sensor]:\\n try:\\n callback(None)\\n except Exception as e:\\n self.stick.logger.error(\\n \\\"Error while executing all callback : %s\\\",\\n e,\\n )\",\n \"def on_result(self, callback):\\n self.result_callback = callback\",\n \"def __call__(self,row):\\n filterType = row.pop(0)\\n if filterType: #i.e. not none and >0\\n result = self.dispatch[filterType](row,self.prev)\\n self.prev = result\\n return result\\n else:\\n self.prev = row\\n return self.prev\",\n \"def __clb_handler(self, update, context):\\n trigger = update.callback_query.data\\n self.__handler(context, update, trigger)\",\n \"def _add_callback_processing(self):\\n pass\",\n \"def process_data(self, data):\\n parsed = json.loads(data)\\n current = parsed[\\\"current\\\"]\\n future = parsed[\\\"hourly\\\"]\\n current_res = self.get_columns(current)\\n self.database_conn(\\\"current\\\", -1, current_res)\\n for hour, data in enumerate(future):\\n current_res = self.get_columns(data)\\n self.database_conn(\\\"current\\\", hour, current_res)\",\n \"def process_row(row, row_num, column_map, num_required_columns, additional_isbn_columns,\\n doab_analysis, doaj_analysis, no_crossref_lookup=False, no_pubmed_lookup=False,\\n no_doaj_lookup=False, no_title_lookup=False, round_monetary=False,\\n offsetting_mode=None, orig_file_path=None, crossref_max_retries=3):\\n if len(row) != num_required_columns:\\n msg = \\\"Line %s: \\\" + MESSAGES[\\\"num_columns\\\"]\\n logging.error(msg, row_num, len(row), num_required_columns)\\n return row\\n\\n empty_row = True\\n for elem in row:\\n if has_value(elem):\\n empty_row = False\\n break\\n else:\\n msg = \\\"Line %s: \\\" + MESSAGES[\\\"empty_row\\\"]\\n logging.warning(msg, row_num)\\n\\n current_row = {}\\n record_type = None\\n\\n # Copy content of identified columns and apply special processing rules\\n for csv_column in column_map.values():\\n index, column_type = csv_column.index, csv_column.column_type\\n if empty_row:\\n current_row[column_type] = \\\"\\\"\\n continue\\n if column_type == \\\"euro\\\" and index is not None:\\n current_row[\\\"euro\\\"] = _process_euro_value(row[index], round_monetary, row_num, index, offsetting_mode)\\n elif column_type == \\\"period\\\" and index is not None:\\n current_row[\\\"period\\\"] = _process_period_value(row[index], row_num)\\n elif column_type == \\\"is_hybrid\\\" and index is not None:\\n current_row[\\\"is_hybrid\\\"] = _process_hybrid_status(row[index], row_num)\\n elif column_type == \\\"institution\\\" and index is not None:\\n current_row[\\\"institution\\\"] = _process_institution_value(row[index], row_num, orig_file_path, offsetting_mode)\\n else:\\n if index is not None and len(row[index]) > 0:\\n current_row[column_type] = row[index]\\n else:\\n current_row[column_type] = \\\"NA\\\"\\n\\n doi = current_row[\\\"doi\\\"]\\n if not has_value(doi) and not empty_row:\\n msg = (\\\"Line %s: No DOI found\\\")\\n logging.info(msg, row_num)\\n current_row[\\\"indexed_in_crossref\\\"] = \\\"FALSE\\\"\\n # lookup ISBNs in crossref\\n additional_isbns = [row[i] for i in additional_isbn_columns]\\n found_doi, r_type = _isbn_lookup(current_row, row_num, additional_isbns, doab_analysis.isbn_handling)\\n if r_type is not None:\\n record_type = r_type\\n if found_doi is not None:\\n # integrate DOI into row and restart\\n logging.info(\\\"New DOI integrated, restarting enrichment for current line.\\\")\\n index = column_map[\\\"doi\\\"].index\\n row[index] = found_doi\\n return process_row(row, row_num, column_map, num_required_columns, additional_isbn_columns,\\n doab_analysis, doaj_analysis, no_crossref_lookup, no_pubmed_lookup,\\n no_doaj_lookup, no_title_lookup, round_monetary, offsetting_mode, orig_file_path)\\n # lookup the book title in Crossref\\n lookup_title = current_row[\\\"book_title\\\"]\\n if has_value(lookup_title):\\n msg = (\\\"Line %s: Trying to look up the book title ('%s') in Crossref...\\\")\\n logging.info(msg, row_num, lookup_title)\\n book_doi = title_lookup(lookup_title, [\\\"book\\\", \\\"monograph\\\", \\\"reference-book\\\"])\\n if book_doi:\\n logging.info(\\\"New DOI integrated, restarting enrichment for current line.\\\")\\n index = column_map[\\\"doi\\\"].index\\n row[index] = book_doi\\n return process_row(row, row_num, column_map, num_required_columns, additional_isbn_columns,\\n doab_analysis, doaj_analysis, no_crossref_lookup, no_pubmed_lookup,\\n no_doaj_lookup, no_title_lookup, round_monetary, offsetting_mode, orig_file_path)\\n if has_value(doi):\\n # Normalise DOI\\n norm_doi = get_normalised_DOI(doi)\\n if norm_doi is not None and norm_doi != doi:\\n current_row[\\\"doi\\\"] = norm_doi\\n msg = MESSAGES[\\\"doi_norm\\\"].format(doi, norm_doi)\\n logging.info(msg)\\n doi = norm_doi\\n # include crossref metadata\\n if not no_crossref_lookup:\\n crossref_result = get_metadata_from_crossref(doi)\\n retries = 0\\n while not crossref_result[\\\"success\\\"] and crossref_result[\\\"error_msg\\\"].startswith(\\\"HTTPError: 504\\\"):\\n if retries >= crossref_max_retries:\\n break\\n # retry on gateway timeouts, crossref API is quite busy sometimes\\n msg = \\\"%s, retrying...\\\"\\n logging.warning(msg, crossref_result[\\\"error_msg\\\"])\\n retries += 1\\n crossref_result = get_metadata_from_crossref(doi)\\n if not crossref_result[\\\"success\\\"]:\\n exc = crossref_result[\\\"exception\\\"]\\n # check if a preprint lookup is possible\\n if not no_title_lookup and type(exc) == UnsupportedDoiTypeError and exc.doi_type == \\\"posted-content\\\":\\n msg = (\\\"Line %s: Found a DOI with type 'posted_content' (%s). This might \\\" +\\n \\\"be a case of a preprint DOI, trying to find the final version of the article...\\\")\\n logging.info(msg, row_num, doi)\\n if not exc.crossref_title:\\n msg = \\\"Line %s: Preprint lookup failed, no title could be extracted.\\\"\\n logging.warning(msg, row_num)\\n else:\\n article_doi = title_lookup(exc.crossref_title, [\\\"journal-article\\\"])\\n if article_doi:\\n logging.info(\\\"New DOI integrated, restarting enrichment for current line...\\\")\\n index = column_map[\\\"doi\\\"].index\\n row[index] = article_doi\\n return process_row(row, row_num, column_map, num_required_columns, additional_isbn_columns,\\n doab_analysis, doaj_analysis, no_crossref_lookup, no_pubmed_lookup,\\n no_doaj_lookup, no_title_lookup, round_monetary, offsetting_mode, orig_file_path)\\n if crossref_result[\\\"success\\\"]:\\n data = crossref_result[\\\"data\\\"]\\n record_type = data.pop(\\\"doi_type\\\")\\n logging.info(\\\"Crossref: DOI resolved: \\\" + doi + \\\" [\\\" + record_type + \\\"]\\\")\\n current_row[\\\"indexed_in_crossref\\\"] = \\\"TRUE\\\"\\n for key, value in data.items():\\n new_value = _process_crossref_results(current_row, row_num, key, value)\\n old_value = current_row[key]\\n current_row[key] = column_map[key].check_overwrite(old_value, new_value)\\n else:\\n msg = \\\"Line %s: Crossref: Error while trying to resolve DOI %s: %s\\\"\\n logging.error(msg, row_num, doi, crossref_result[\\\"error_msg\\\"])\\n current_row[\\\"indexed_in_crossref\\\"] = \\\"FALSE\\\"\\n # lookup ISBNs in crossref and try to find a correct DOI\\n additional_isbns = [row[i] for i in additional_isbn_columns]\\n found_doi, r_type = _isbn_lookup(current_row, row_num, additional_isbns, doab_analysis.isbn_handling)\\n if r_type is not None:\\n record_type = r_type\\n if found_doi is not None:\\n # integrate DOI into row and restart\\n logging.info(\\\"New DOI integrated, restarting enrichment for current line.\\\")\\n index = column_map[\\\"doi\\\"].index\\n row[index] = found_doi\\n return process_row(row, row_num, column_map, num_required_columns, additional_isbn_columns,\\n doab_analysis, doaj_analysis, no_crossref_lookup, no_pubmed_lookup,\\n no_doaj_lookup, no_title_lookup, round_monetary, offsetting_mode, orig_file_path)\\n # include pubmed metadata\\n if not no_pubmed_lookup and record_type == \\\"journal-article\\\":\\n pubmed_result = get_metadata_from_pubmed(doi)\\n if pubmed_result[\\\"success\\\"]:\\n logging.info(\\\"Pubmed: DOI resolved: \\\" + doi)\\n data = pubmed_result[\\\"data\\\"]\\n for key, value in data.items():\\n if value is not None:\\n new_value = value\\n else:\\n new_value = \\\"NA\\\"\\n msg = \\\"WARNING: Element %s not found in in response for doi %s.\\\"\\n logging.debug(msg, key, doi)\\n old_value = current_row[key]\\n current_row[key] = column_map[key].check_overwrite(old_value, new_value)\\n else:\\n msg = \\\"Line %s: Pubmed: Error while trying to resolve DOI %s: %s\\\"\\n logging.error(msg, row_num, doi, pubmed_result[\\\"error_msg\\\"])\\n\\n # lookup in DOAJ. try the EISSN first, then ISSN and finally print ISSN\\n if not no_doaj_lookup and not empty_row:\\n issns = []\\n new_value = \\\"NA\\\"\\n if current_row[\\\"issn_electronic\\\"] != \\\"NA\\\":\\n issns.append(current_row[\\\"issn_electronic\\\"])\\n if current_row[\\\"issn\\\"] != \\\"NA\\\":\\n issns.append(current_row[\\\"issn\\\"])\\n if current_row[\\\"issn_print\\\"] != \\\"NA\\\":\\n issns.append(current_row[\\\"issn_print\\\"])\\n for issn in issns:\\n lookup_result = doaj_analysis.lookup(issn)\\n if lookup_result:\\n msg = \\\"DOAJ: Journal ISSN (%s) found in DOAJ offline copy ('%s').\\\"\\n logging.info(msg, issn, lookup_result)\\n new_value = \\\"TRUE\\\"\\n break\\n else:\\n msg = \\\"DOAJ: Journal ISSN (%s) not found in DOAJ offline copy.\\\"\\n new_value = \\\"FALSE\\\"\\n logging.info(msg, issn)\\n old_value = current_row[\\\"doaj\\\"]\\n current_row[\\\"doaj\\\"] = column_map[\\\"doaj\\\"].check_overwrite(old_value, new_value)\\n if record_type != \\\"journal-article\\\" and not empty_row:\\n collected_isbns = []\\n for isbn_field in [\\\"isbn\\\", \\\"isbn_print\\\", \\\"isbn_electronic\\\"]:\\n # test and split all ISBNs\\n current_row[isbn_field] = _process_isbn(row_num, current_row[isbn_field], doab_analysis.isbn_handling)\\n if has_value(current_row[isbn_field]):\\n collected_isbns.append(current_row[isbn_field])\\n additional_isbns = [row[i] for i in additional_isbn_columns]\\n for isbn in additional_isbns:\\n result = _process_isbn(row_num, isbn, doab_analysis.isbn_handling)\\n if has_value(result):\\n collected_isbns.append(result)\\n if len(collected_isbns) == 0:\\n logging.info(\\\"No ISBN found, skipping DOAB lookup.\\\")\\n current_row[\\\"doab\\\"] = \\\"NA\\\"\\n else:\\n record_type = \\\"book\\\"\\n logging.info(\\\"Trying a DOAB lookup with the following values: \\\" + str(collected_isbns))\\n for isbn in collected_isbns:\\n doab_result = doab_analysis.lookup(isbn)\\n if doab_result is not None:\\n current_row[\\\"doab\\\"] = \\\"TRUE\\\"\\n msg = 'DOAB: ISBN %s found in normalized DOAB (%s, \\\"%s\\\")'\\n logging.info(msg, isbn, doab_result[\\\"publisher\\\"], doab_result[\\\"book_title\\\"])\\n if current_row[\\\"indexed_in_crossref\\\"] == \\\"TRUE\\\":\\n msg = \\\"Book already found in Crossref via DOI, those results take precedence\\\"\\n logging.info(msg)\\n else:\\n for key in doab_result:\\n current_row[key] = doab_result[key]\\n if not has_value(current_row[\\\"isbn\\\"]):\\n current_row[\\\"isbn\\\"] = isbn\\n break\\n else:\\n current_row[\\\"doab\\\"] = \\\"FALSE\\\"\\n msg = \\\"DOAB: None of the ISBNs found in DOAB\\\"\\n logging.info(msg)\\n if offsetting_mode:\\n current_row[\\\"agreement\\\"] = offsetting_mode\\n record_type = \\\"journal-article_transagree\\\"\\n\\n if record_type is None:\\n msg = \\\"Line %s: Could not identify record type, using default schema 'journal-article'\\\"\\n logging.warning(msg, row_num)\\n record_type = \\\"journal-article\\\"\\n\\n result = []\\n for field in COLUMN_SCHEMAS[record_type]:\\n result.append(current_row[field])\\n\\n return (record_type, result)\",\n \"def on_update_seatable(data, index, *args):\\n row = convert_row(metadata, data)\\n print(row)\",\n \"def run_bulk_process(\\n row_handler, rows, progress_label=None, stats=None, raise_global_error=True\\n):\\n processor = _create_bulk_processor(\\n row_handler,\\n rows,\\n progress_label,\\n stats=stats,\\n raise_global_error=raise_global_error,\\n )\\n return processor.run()\",\n \"def process_steps(self, df, **kwargs):\\n pass\",\n \"def on_tab_records_currentChanged(self, index):\\n # TODO: not implemented yet\\n raise NotImplementedError\",\n \"def feedDataRow(self, row, **kwargs): \\n\\n self.nullify()\\n \\n #avoid automatic call to \\\"read\\\" after _objectid changes \\n self._feed = True\\n self._objectid = row['objectid']\\n self._feed = False\\n \\n self._original_values.clear()\\n for cn in row:\\n if cn in self._extra_sql_columns:\\n self.__dict__[cn] = row[cn]\\n if cn not in self._table: continue\\n field = self._table[cn]\\n decoded = field.val_sql2py ( row[cn] )\\n self.__dict__[cn] = decoded\\n self._original_values[cn] = decoded\\n \\n #if _astxt was not provided with the data, _reprfunc is not set,\\n #get the text from database\\n if '_astxt' in row:\\n self._astxt = row['_astxt']\\n elif self._reprfunc:\\n self._astxt = self._reprfunc (self)\\n else: \\n self._astxt = self.TextCache[self._objectid] or \\\"(none)\\\"\\n \\n if self._resolve_child_ref:\\n for child_handle in self._child_referencelist:\\n t, f = self._table.reference_child_hash[child_handle] \\n self._child_referencelist[child_handle].filter = f.name + \\\" = '\\\" + str(row['objectid']) + \\\"'\\\"\\n self._child_referencelist[child_handle].reload()\\n \\n self._hasdata = True\\n self._isnew = False\\n self._ismodified = False\\n self._modified_values.clear()\",\n \"def on_button_group(self, row_index: int):\\n\\n def _callback(attr, old, new):\\n # Note: bokeh.core.PropertyList can not be deep copied\\n # it RuntimeErrors, cast as list instead\\n active = list(new)\\n self.notify(on_button_group(row_index, active))\\n\\n return _callback\",\n \"def run(self, row, **kwargs):\\n self.source = row\\n kwargs['output'] = self.__graph__()\\n super(CSVRowProcessor, self).run(**kwargs)\\n return kwargs['output']\",\n \"def update_row_flag_status(self, index: qtc.QModelIndex):\\n row = index.row()\\n self.dataChanged.emit(self.index(row, 0), self.index(row, 0), [qtc.Qt.ForegroundRole])\",\n \"def places_process_rows(self):\\n\\n for index in range(len(self.table)):\\n row_rdf = self.places_map_row_to_rdf(self.table.iloc[index])\\n if row_rdf is not None:\\n self.data += row_rdf\",\n \"def parse_row(self, response, row):\\n raise NotImplementedError\",\n \"def _do_change_row(self, treeview):\\n _return = False\\n\\n self.treeview.handler_block(self._lst_handler_id[0])\\n\\n (_model, _row) = treeview.get_selection().get_selected()\\n try:\\n _level = _model.get_value(_row, 11)\\n except TypeError:\\n _level = None\\n\\n _columns = treeview.get_columns()\\n\\n # Change the column headings depending on what is being selected.\\n if _level == 'mission':\\n _headings = [\\n _(u\\\"Mission ID\\\"),\\n _(u\\\"Description\\\"),\\n _(u\\\"Units\\\"),\\n _(u\\\"Start Time\\\"),\\n _(u\\\"End Time\\\"),\\n _(u\\\"\\\"),\\n _(u\\\"\\\"),\\n _(u\\\"\\\")\\n ]\\n elif _level == 'phase':\\n _headings = [\\n _(u\\\"Phase ID\\\"),\\n _(u\\\" Code\\\\t\\\\tDescription\\\"),\\n _(u\\\"Units\\\"),\\n _(u\\\"Start Time\\\"),\\n _(u\\\"End Time\\\"),\\n _(u\\\"\\\"),\\n _(u\\\"\\\"),\\n _(u\\\"\\\")\\n ]\\n elif _level == 'environment':\\n _headings = [\\n _(u\\\"Environment ID\\\"),\\n _(u\\\"Condition\\\"),\\n _(u\\\"Units\\\"),\\n _(u\\\"Minimum Value\\\"),\\n _(u\\\"Maximum Value\\\"),\\n _(u\\\"Mean Value\\\"),\\n _(u\\\"Variance\\\"),\\n _(u\\\"\\\")\\n ]\\n else:\\n _headings = []\\n\\n i = 0\\n for _heading in _headings:\\n _label = gtk.Label()\\n _label.set_line_wrap(True)\\n _label.set_alignment(xalign=0.5, yalign=0.5)\\n _label.set_justify(gtk.JUSTIFY_CENTER)\\n _label.set_markup(\\\"<span weight='bold'>\\\" + _heading + \\\"</span>\\\")\\n _label.set_use_markup(True)\\n _label.show_all()\\n _columns[i].set_widget(_label)\\n\\n i += 1\\n\\n self.treeview.handler_unblock(self._lst_handler_id[0])\\n\\n return _return\",\n \"def iter_rows_raw(self, *args):\\n\\n for row in super().iter_rows_raw(*args):\\n row[0] = row[1] # sequential catalog index not right in this case; overwrite to match finder id\\n yield row\",\n \"def apply(self, df_events):\\n pass\",\n \"def update_row(self):\\n self.current_row = self.next_row\\n self.next_row = self.get_row()\",\n \"def process_row(self, table, row):\\n for index, column in enumerate(table.columns):\\n hash_key = hash(frozenset(column.items()))\\n column_type = self.column_types[hash_key] if hash_key in self.column_types else self.column_type(column)\\n if row[index] == None and ('timestamp' not in column_type or not column['default']):\\n row[index] = '\\\\N'\\n elif row[index] == None and column['default']:\\n if self.tz:\\n row[index] = '1970-01-01T00:00:00.000000' + self.tz_offset\\n else:\\n row[index] = '1970-01-01 00:00:00'\\n elif 'bit' in column_type:\\n row[index] = bin(ord(row[index]))[2:]\\n elif isinstance(row[index], (str, unicode, basestring)):\\n if column_type == 'bytea':\\n row[index] = Binary(row[index]).getquoted()[1:-8] if row[index] else row[index]\\n elif 'text[' in column_type:\\n row[index] = '{%s}' % ','.join('\\\"%s\\\"' % v.replace('\\\"', r'\\\\\\\"') for v in row[index].split(','))\\n else:\\n row[index] = row[index].replace('\\\\\\\\', r'\\\\\\\\').replace('\\\\n', r'\\\\n').replace(\\n '\\\\t', r'\\\\t').replace('\\\\r', r'\\\\r').replace('\\\\0', '')\\n elif column_type == 'boolean':\\n # We got here because you used a tinyint(1), if you didn't want a bool, don't use that type\\n row[index] = 't' if row[index] not in (None, 0) else 'f' if row[index] == 0 else row[index]\\n elif isinstance(row[index], (date, datetime)):\\n if isinstance(row[index], datetime) and self.tz:\\n try:\\n if row[index].tzinfo:\\n row[index] = row[index].astimezone(self.tz).isoformat()\\n else:\\n row[index] = datetime(*row[index].timetuple()[:6], tzinfo=self.tz).isoformat()\\n except Exception as e:\\n print e.message\\n else:\\n row[index] = row[index].isoformat()\\n elif isinstance(row[index], timedelta):\\n row[index] = datetime.utcfromtimestamp(_get_total_seconds(row[index])).time().isoformat()\\n else:\\n row[index] = AsIs(row[index]).getquoted()\",\n \"def inserted_callback(p_queue=None, p_columns=None, p_row=None, p_key=None):\\n\\n if not isinstance(p_queue, multiprocessing.managers.BaseProxy):\\n raise custom_exceptions.InvalidParameterTypeException('\\\"p_queue\\\" parameter must be a \\\"multiprocessing.managers.BaseProxy\\\" instance.', p_queue)\\n\\n if not isinstance(p_columns, list):\\n raise custom_exceptions.InvalidParameterTypeException('\\\"p_columns\\\" parameter must be a \\\"list\\\" instance.', p_columns)\\n\\n if not isinstance(p_row, list):\\n raise custom_exceptions.InvalidParameterTypeException('\\\"p_row\\\" parameter must be a \\\"list\\\" instance.', p_row)\\n\\n if not isinstance(p_key, list):\\n raise custom_exceptions.InvalidParameterTypeException('\\\"p_key\\\" parameter must be a \\\"list\\\" instance.', p_key)\\n\\n p_queue.put({\\n 'type': 'tables',\\n 'row': {\\n 'schema_name': p_row['table_schema'],\\n 'table_name': p_row['table_name'],\\n 'status': 'INSERTED',\\n 'sql': inspect.cleandoc(doc=p_row['create_table_ddl'])\\n }\\n })\",\n \"def run_callbacks(self, **kwargs):\\n for callback in self.CALLBACKS:\\n getattr(self, callback)(**kwargs)\",\n \"def processRow(self, row=None, pdata=None):\\n\\t\\tcol_name2index = getattr(pdata, 'col_name2index', None)\\n\\t\\txValue2yValueLs = getattr(pdata, 'xValue2yValueLs', None)\\n\\t\\ty_ls = getattr(pdata, 'y_ls', None)\\n\\t\\tif col_name2index and xValue2yValueLs is not None:\\n\\t\\t\\tif self.whichColumnHeader:\\n\\t\\t\\t\\twhichColumn = col_name2index.get(self.whichColumnHeader, None)\\n\\t\\t\\telse:\\n\\t\\t\\t\\twhichColumn = self.whichColumn\\n\\t\\t\\tx_index = col_name2index.get(self.xColumnHeader, None)\\n\\t\\t\\t\\n\\t\\t\\txValue = float(row[x_index])\\n\\t\\t\\txValue = self.processValue(xValue, processType=self.logX)\\n\\t\\t\\tyValue = float(row[whichColumn])\\n\\t\\t\\tyValue = self.processValue(yValue, processType=self.logY)\\n\\t\\t\\tif xValue not in xValue2yValueLs:\\n\\t\\t\\t\\txValue2yValueLs[xValue] = []\\n\\t\\t\\txValue2yValueLs[xValue].append(yValue)\\n\\t\\t\\ty_ls.append(yValue)\",\n \"def cell_entered(self, row: int, _):\\n self.selectRow(row)\",\n \"def iter_rows(self, *args):\\n\\n raw_args = []\\n for arg in args:\\n if arg in self._column_translations:\\n raw_args+=self._column_translations[arg].inputs()\\n else:\\n raw_args.append(arg)\\n for raw_values in self.iter_rows_raw(*raw_args):\\n values = [raw_values[0], raw_values[1]]\\n for arg in args:\\n if arg in self._column_translations:\\n values.append(self._column_translations[arg](raw_args, raw_values[2:]))\\n else:\\n values.append(raw_values[2:][raw_args.index(arg)])\\n yield values\",\n \"def on_train_batch_end(self, outputs, batch, batch_idx, dataloader_idx):\\n for callback in self.callbacks:\\n callback.on_train_batch_end(self, self.get_model(), outputs, batch, batch_idx, dataloader_idx)\",\n \"def handleTableSelectionChange(self):\\n self.selectEntireRow()\\n self.showSelectedDataset()\",\n \"def _on_bob(self) -> None:\\n self.row_generator.set_bob()\",\n \"def handle_record(self, record):\\n raise NotImplementedError\",\n \"def __clb_handler(self, bot, update):\\n trigger = update.callback_query.data\\n self.__handler(bot, update, trigger)\",\n \"def on_row_activated(self, widget, path, view_column):\\n self.launch_layout()\",\n \"def ExecuteCallback(self):\\n return _gmat_py.GmatBase_ExecuteCallback(self)\",\n \"def _process_data(self):\\r\\n # Rename columns to match final feature class\\r\\n self._rename_columns()\\r\\n # Add point ID column\\r\\n self._add_pointid()\\r\\n # Sort rows by transect id and timestamp\\r\\n self._sort_rows()\\r\\n # Fill Null records with a value\\r\\n self._fill_nulls()\\r\\n # Set site_code to lower case\\r\\n self._lower_site_code()\\r\\n # Create survey_id\\r\\n self._calc_survey_id()\\r\\n # Calculate nativesg column if at least one of the veg columns is a Native seagrass type\\r\\n if set(self.veg_columns).intersection(set(NATIVESG_CODES)) > 0:\\r\\n self.nativesg_columns = list(set(self.veg_columns).intersection(set(NATIVESG_CODES)))\\r\\n self._calc_nativesg()\\r\\n #\\r\",\n \"def process_data(self, excel_file, output_title):\\n df = read_excel(excel_file)\\n labels = df.columns.values.tolist()\\n title = f\\\"{labels[1]} vs {labels[0]}\\\"\\n data = []\\n for label in labels:\\n data.append(df[label].values.tolist())\\n\\n for callback in self.callbacks:\\n callback(title, data, labels, output_title)\",\n \"def validate(self, row):\\n raise NotImplementedError\",\n \"def map_transfer_to_row(self, transfer):\\n pass\",\n \"def table_data_update_dispatcher(data_timestamp, active_cell, data, data_previous):\\n # Escape if we have no data. This might not be intention if app's data is empty?\\n if data is None and data_previous is None:\\n return dash.no_update\\n\\n ctx = dash.callback_context\\n if ctx.triggered[0][\\\"prop_id\\\"] == \\\"table.data_timestamp\\\":\\n return table_edit_callback(data, data_previous), data_timestamp\\n elif ctx.triggered[0][\\\"prop_id\\\"] == \\\"table.active_cell\\\":\\n return table_on_click_via_active_cell(active_cell, data), data_timestamp\\n else:\\n # During app boot (?) the callback fires without normal trigger events, which can slip down here. Can't end\\n # without a return because that will set table.data == None in perpetuity\\n return dash.no_update\",\n \"def processEscrows(self):\\n\\n try:\\n self.processOutOfOrders()\\n self.processPartials()\\n self.processDuplicitous()\\n self.processUnverifieds()\\n self.processTransUnverifieds()\\n\\n except Exception as ex: # log diagnostics errors etc\\n if logger.isEnabledFor(logging.DEBUG):\\n logger.exception(\\\"Kevery escrow process error: %s\\\\n\\\", ex.args[0])\\n else:\\n logger.error(\\\"Kevery escrow process error: %s\\\\n\\\", ex.args[0])\",\n \"def handle_callback_query(bot, update, session, user):\\n query = update.callback_query\\n data = query.data\\n\\n # Extract the callback type, task id\\n [callback_type, payload, action] = data.split(':')\\n callback_type = int(callback_type)\\n action = int(action)\\n\\n chat = session.query(Chat).get(query.message.chat.id)\\n tg_chat = query.message.chat\\n\\n # Handle task vote ban callbacks\\n if CallbackType(callback_type).name == 'task_vote_ban':\\n task = session.query(Task).get(payload)\\n if CallbackResult(action).name == 'ban':\\n task.sticker_set.banned = True\\n call_tg_func(query, 'answer', args=['Set banned'])\\n else:\\n task.sticker_set.banned = False\\n call_tg_func(query, 'answer', args=['Set unbanned'])\\n\\n if not task.reviewed:\\n task.reviewed = True\\n process_task(session, tg_chat, chat)\\n\\n # Handle task vote ban callbacks\\n if CallbackType(callback_type).name == 'task_vote_nsfw':\\n task = session.query(Task).get(payload)\\n if CallbackResult(action).name == 'ban':\\n task.sticker_set.nsfw = True\\n call_tg_func(query, 'answer', args=['Set tagged as nsfw'])\\n else:\\n task.sticker_set.nsfw = False\\n call_tg_func(query, 'answer', args=['Set no longer tagged as nsfw'])\\n\\n if not task.reviewed:\\n task.reviewed = True\\n process_task(session, tg_chat, chat)\\n\\n # Handle task user ban callbacks\\n elif CallbackType(callback_type).name == 'task_user_revert':\\n task = session.query(Task).get(payload)\\n if CallbackResult(action).name == 'revert':\\n task.user.banned = True\\n call_tg_func(query, 'answer', args=['User banned and changes reverted'])\\n revert_user_changes(session, task.user)\\n\\n if not task.reviewed:\\n task.reviewed = True\\n process_task(session, tg_chat, chat)\\n\\n # Handle the \\\"Skip this sticker\\\" button\\n elif CallbackType(callback_type).name == 'ban_set':\\n sticker_set = session.query(StickerSet).get(payload)\\n if CallbackResult(action).name == 'ban':\\n sticker_set.banned = True\\n elif CallbackResult(action).name == 'ok':\\n sticker_set.banned = False\\n\\n keyboard = get_nsfw_ban_keyboard(sticker_set)\\n call_tg_func(query.message, 'edit_reply_markup',\\n kwargs={'reply_markup': keyboard})\\n\\n elif CallbackType(callback_type).name == 'nsfw_set':\\n sticker_set = session.query(StickerSet).get(payload)\\n if CallbackResult(action).name == 'ban':\\n sticker_set.nsfw = True\\n elif CallbackResult(action).name == 'ok':\\n sticker_set.nsfw = False\\n\\n keyboard = get_nsfw_ban_keyboard(sticker_set)\\n call_tg_func(query.message, 'edit_reply_markup',\\n kwargs={'reply_markup': keyboard})\\n\\n # Handle the \\\"Skip this sticker\\\" button\\n elif CallbackType(callback_type).name == 'next':\\n handle_next(session, chat, tg_chat)\\n\\n # Handle the \\\"Stop tagging\\\" button\\n elif CallbackType(callback_type).name == 'cancel':\\n call_tg_func(query, 'answer', args=['All active commands have been canceled'])\\n call_tg_func(tg_chat, 'send_message', ['All running commands are canceled'],\\n {'reply_markup': main_keyboard})\\n chat.cancel()\\n\\n # Handle \\\"Fix this sticker's tags\\\"\\n elif CallbackType(callback_type).name == 'edit_sticker':\\n sticker = session.query(Sticker).get(payload)\\n chat.current_sticker = sticker\\n if not chat.full_sticker_set and not chat.tagging_random_sticker:\\n chat.fix_single_sticker = True\\n send_tag_messages(chat, tg_chat)\\n\\n elif CallbackType(callback_type).name == 'tag_set':\\n initialize_set_tagging(bot, tg_chat, session, payload, chat, user)\\n\\n return\",\n \"def processRow(self, row):\\n\\t\\tif self.delim is not None:\\n\\t\\t\\trowArr = row.split(self.delim)\\n\\t\\t\\tmsg = \\\"row does not have expected number of columns found \\\" + str(len(rowArr)) + \\\" expected \\\" + str(self.rowSize)\\n\\t\\t\\tassert len(rowArr) == self.rowSize, msg\\n\\t\\telse:\\n\\t\\t\\trowArr = row\\n\\t\\t\\t\\n\\t\\tnewRowArr = []\\n\\t\\tfor i in range(len(rowArr)):\\n\\t\\t\\tcurVal = rowArr[i]\\n\\t\\t\\tif (i in self.catValues):\\n\\t\\t\\t\\tvalues = self.catValues[i]\\n\\t\\t\\t\\tfor val in values:\\n\\t\\t\\t\\t\\tif val == curVal:\\n\\t\\t\\t\\t\\t\\tnewVal = self.trueVal\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\tnewVal = self.falseVal\\n\\t\\t\\t\\t\\tnewRowArr.append(newVal)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tnewRowArr.append(curVal)\\n\\t\\tassert len(newRowArr) == self.newRowSize, \\\"invalid new row size \\\" + str(len(newRowArr)) + \\\" expected \\\" + str(self.newRowSize)\\n\\t\\tencRow = self.delim.join(newRowArr) if self.delim is not None else newRowArr\\n\\t\\treturn encRow\",\n \"def OutputTestRecord(self, test_record):\\n for output_cb in self.output_callbacks:\\n output_cb(test_record)\",\n \"def _step_callback_gen(self):\\n\\n with open(self.output_filename, 'wb') as f: # Note: need to use wb since windows\\n w = csv.writer(f, lineterminator=os.linesep) # Also lineterminator=os.linesep for cross platform compatibility\\n\\n while True:\\n sensor, step_samples = (yield) # Wait for step_callback to send us the a sample\\n\\n if not self._headers_written: \\n w.writerow(sensor.get_csv_headers())\\n self._headers_written = True\\n \\n if self.sim.data_logging_enabled(self, sensor):\\n for sample in step_samples:\\n w.writerow(list(sample)) # Note: each sample is assumed to be a namedtuple of some sort\",\n \"def csv_handle(self,instance):\\n table_origin = self.csv_dataframe\\n in_column_num = len(self.column_names) \\n in_column_name = self.column_names\\n in_column_type = self.column_types\\n\\n instance.column_num = instance.tables[0].column_num = in_column_num\\n for i in range(instance.column_num):\\n instance.tables[0].names.append(in_column_name[i])\\n instance.tables[0].types.append(Type.getType(in_column_type[i].lower())) #getType is a static method\\n instance.tables[0].origins = [i for i in range(instance.tables[0].column_num)]\\n \\n instance.tuple_num = instance.tables[0].tuple_num = table_origin.shape[0] # the number of rows\\n for i in range(instance.tables[0].column_num):\\n if instance.tables[0].types[i] == 3: #if there is date type column in csv,convert into datetime format\\n col_name = table_origin.columns[i]\\n col_type = self.column_types[i]\\n self.csv_handle_changedate(col_name,col_type)\\n \\n #change table column name with table_info column_names (for date type columns)\\n for i in range(len(table_origin.columns)):\\n table_origin.rename(columns={ table_origin.columns[i] : in_column_name[i] }, inplace=True) \\n instance.tables[0].D = table_origin.values.tolist() #dataframe to list type and feed to D(where to store all the table info )\\n return instance\",\n \"def redraw_row(cls, row):\\n # TODO: Draw blocks in row\",\n \"def _callback_combo_cell(self, cell, path, row, position, treemodel):\\r\\n\\r\\n _model = cell.get_property('model')\\r\\n _text = _model.get_value(row, 0)\\r\\n _index = _model.get_value(row, 1)\\r\\n\\r\\n _row = treemodel.get_iter(path)\\r\\n\\r\\n _position = treemodel.get_value(_row, 0)\\r\\n self._file_index[_position] = _index\\r\\n\\r\\n treemodel.set_value(_row, position, _text)\\r\\n\\r\\n return False\",\n \"def _callback(self, data: list):\\n self.data = data\",\n \"def add_row(self, row):\\n ...\",\n \"def job_execute(self, row):\\n job_id = self.jobsTableWidget.item(row, 0).text()\\n self.connection.job_start(job_id)\\n self.refresh_jobs()\",\n \"def _callbackFunc(self, event: tk.Event) -> None:\\n el_number = self.choose_import.current()\\n if el_number == 0:\\n self._print_folder_import()\\n elif el_number == 1:\\n self._print_camera_import()\\n elif el_number == 2:\\n self._print_webpage_import()\\n elif el_number == 3:\\n self._print_video_import()\",\n \"def process_loading_file(self):\\n column_headers = []\\n column_headers_all = []\\n\\n # Open the file once to get idea of the total rowcount to display progress\\n with open(self.csv_file_path[0], newline='') as csv_file:\\n self.progress_max.emit(len(csv_file.readlines()) - 2)\\n\\n with open(self.csv_file_path[0], newline='') as csv_file:\\n\\n self.csv_data_table.setRowCount(0)\\n self.csv_data_table.setColumnCount(0)\\n\\n csv_file_read = csv.reader(csv_file, delimiter=',', quotechar='|')\\n\\n # Fetch the column headers and move the iterator to actual data\\n column_headers = next(csv_file_read)\\n\\n # Reflect back the changes in the reference to the column headers\\n for header in column_headers:\\n self.column_headers.append(header)\\n # A backup to keep a list of all the headers to toogle their view later\\n self.column_headers_all.append(header)\\n\\n # TODO: Increase the reading speed by decreasing load on actual table population\\n\\n # self.csv_data_table.hide()\\n\\n for row_data in csv_file_read:\\n\\n self.relay.emit(self.csv_data_table.rowCount())\\n # self.relay.emit(self.x)\\n # self.x = self.x + 1\\n row = self.csv_data_table.rowCount()\\n self.csv_data_table.insertRow(row)\\n self.csv_data_table.setColumnCount(len(row_data))\\n for column, stuff in enumerate(row_data):\\n item = QTableWidgetItem(stuff)\\n self.csv_data_table.setItem(row, column, item)\\n\\n self.csv_data_table.setHorizontalHeaderLabels(self.column_headers)\\n\\n # Set WordWrap to True to make the cells change height according to content\\n # Currently set it to false as it looks very decent and makes cell size uniform throughout\\n self.csv_data_table.setWordWrap(False)\\n # Uncomment below line to stretch to fill the column width according to content\\n # self.csv_data_table.resizeColumnsToContents()\\n self.csv_data_table.resizeRowsToContents()\\n\\n # Update the bottom toolbar to reflect changes\\n self.update_bottom_toolbar.emit()\\n self.finished.emit()\",\n \"def _call_followers(self, event):\\n context = self.get_context(event)\\n if context is not None:\\n for callback in self.followers.get(context, []):\\n callback(event)\",\n \"def set_update_callbacks(self, update_tr_pos_callback, update_view_model_callback) -> None:\\n\\n self.update_tr_position = update_tr_pos_callback\\n self.update_view_model = update_view_model_callback\",\n \"def _apply_all(self, callback: Optional[Callable] = None) -> None:\\n while self:\\n op = self.apply()\\n if callback:\\n callback(op)\",\n \"def cb(xk):\\n self.iteration += 1\\n t_current = time.time()\\n t_elapsed = t_current - self.t_store\\n self.t_store = t_current\\n \\n self.of_list.append(self.of_last)\\n self.params = xk\\n self._disp(t_elapsed)\\n\\n # Call the custom callback function if any\\n if callback is not None:\\n callback(self)\",\n \"def process_data(cur, conn, filepath, func):\\n # get all files matching extension from directory\\n all_files = []\\n for root, dirs, files in os.walk(filepath):\\n files = glob.glob(os.path.join(root,'*.json'))\\n for f in files :\\n all_files.append(os.path.abspath(f))\\n\\n # get total number of files found\\n num_files = len(all_files)\\n print('{} files found in {}'.format(num_files, filepath))\\n\\n # iterate over files and process\\n for i, datafile in enumerate(all_files, 1):\\n func(cur, datafile)\\n conn.commit()\\n print('{}/{} files processed.'.format(i, num_files))\",\n \"def process_data(cur, conn, filepath, func):\\n # get all files matching extension from directory\\n all_files = []\\n for root, dirs, files in os.walk(filepath):\\n files = glob.glob(os.path.join(root,'*.json'))\\n for f in files :\\n all_files.append(os.path.abspath(f))\\n\\n # get total number of files found\\n num_files = len(all_files)\\n print('{} files found in {}'.format(num_files, filepath))\\n\\n # iterate over files and process\\n for i, datafile in enumerate(all_files, 1):\\n func(cur, datafile)\\n conn.commit()\\n print('{}/{} files processed.'.format(i, num_files))\",\n \"def on_validation_batch_start(self, batch, batch_idx, dataloader_idx):\\n for callback in self.callbacks:\\n callback.on_validation_batch_start(self, self.get_model(), batch, batch_idx, dataloader_idx)\",\n \"def _run_callbacks(cls, cb_method, *args):\\n global CALLBACKS\\n for c in CALLBACKS:\\n attr = getattr(c, cb_method)\\n attr(*args)\",\n \"def process_data(cur, conn, filepath, func):\\n # get all files matching extension from directory\\n all_files = []\\n for root, dirs, files in os.walk(filepath):\\n files = glob.glob(os.path.join(root,'*.json'))\\n for f in files :\\n all_files.append(os.path.abspath(f))\\n\\n num_files = len(all_files)\\n print('{} files found in {}'.format(num_files, filepath))\\n\\n for i, datafile in enumerate(all_files, 1):\\n func(cur, datafile)\\n conn.commit()\\n print('{}/{} files processed.'.format(i, num_files))\",\n \"def process_data(cur, conn, filepath, func):\\n # get all files matching extension from directory\\n all_files = []\\n for root, dirs, files in os.walk(filepath):\\n files = glob.glob(os.path.join(root, '*.json'))\\n for file in files:\\n all_files.append(os.path.abspath(file))\\n\\n # get total number of files found\\n num_files = len(all_files)\\n print('{} files found in {}'.format(num_files, filepath))\\n\\n # iterate over files and process\\n for i, datafile in enumerate(all_files, 1):\\n func(cur, datafile)\\n conn.commit()\\n print('{}/{} files processed.'.format(i, num_files))\",\n \"def update_data(self, **kwargs):\\n self.source_data = self.get_dict()\\n for c in self.callbacks[\\\"update_data\\\"]:\\n c()\",\n \"def process_data(cur, conn, filepath, func):\\n # get all files matching extension from directory\\n all_files = []\\n for root, dirs, files in os.walk(filepath):\\n files = glob.glob(os.path.join(root, '*.json'))\\n for f in files:\\n all_files.append(os.path.abspath(f))\\n\\n # get total number of files found\\n num_files = len(all_files)\\n print('{} files found in {}'.format(num_files, filepath))\\n\\n # iterate over files and process\\n for i, datafile in enumerate(all_files, 1):\\n func(cur, datafile)\\n conn.commit()\\n print('{}/{} files processed.'.format(i, num_files))\",\n \"def callback(self, *args):\\n raise NotImplementedError()\",\n \"def _data_updated_callback(self, attr, old, new):\\n pass\",\n \"def process_data(cur, conn, filepath, func):\\n \\n # get all files matching extension from directory\\n all_files = []\\n for root, dirs, files in os.walk(filepath):\\n files = glob.glob(os.path.join(root,'*.json'))\\n for f in files:\\n all_files.append(os.path.abspath(f))\\n \\n # get total number of files found\\n num_files = len(all_files)\\n print('{} files found in {}'.format(num_files, filepath))\\n \\n # iterate over files and process\\n for i, datafile in enumerate(all_files, 1):\\n func(cur, datafile)\\n conn.commit()\\n print('{}/{} files processed.'.format(i, num_files))\",\n \"def process_data(cur, conn, filepath, func):\\n\\n # get all files matching extension from directory\\n all_files = []\\n for root, dirs, files in os.walk(filepath):\\n files = glob.glob(os.path.join(root, '*.json'))\\n for f in files:\\n all_files.append(os.path.abspath(f))\\n\\n # get total number of files found\\n num_files = len(all_files)\\n print('{} files found in {}'.format(num_files, filepath))\\n\\n # iterate over files and process\\n for i, datafile in enumerate(all_files, 1):\\n func(cur, datafile)\\n conn.commit()\\n print('{}/{} files processed.'.format(i, num_files))\",\n \"def edit_current_cell(self):\\n cells = self.csv_data_table.selectionModel().selectedIndexes()\\n if len(cells) == 1:\\n for cell in sorted(cells):\\n r = cell.row()\\n c = cell.column()\\n self.csv_data_table.editItem(self.csv_data_table.item(r, c))\",\n \"def on_tableWidget_Trade_Args_cellClicked(self, row, column):\\n # TODO: not implemented yet\\n raise NotImplementedError\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6472857","0.5750757","0.5650037","0.5516797","0.5459125","0.54315567","0.542719","0.5388466","0.5336627","0.53299576","0.5304679","0.52980345","0.52818644","0.52797127","0.5246277","0.5232472","0.52007216","0.5188484","0.5181919","0.5174036","0.5146636","0.5142773","0.512924","0.5119605","0.51102847","0.50976866","0.50848013","0.50746673","0.5039749","0.5035337","0.50214773","0.5006417","0.49807134","0.49771914","0.49670306","0.49295518","0.4926534","0.49199817","0.49171782","0.49151823","0.4908545","0.4901406","0.48876593","0.48852453","0.48711237","0.48629707","0.4861078","0.48476452","0.48425475","0.4836251","0.4833537","0.48292664","0.48272035","0.48270997","0.4824705","0.479232","0.4789255","0.4786484","0.47855487","0.47851005","0.4779864","0.47580424","0.4754054","0.4753803","0.47536433","0.47504663","0.47429112","0.47389635","0.4735756","0.47346902","0.4733986","0.4729851","0.4726891","0.47196308","0.47195357","0.4715567","0.47109652","0.4703375","0.46925768","0.46830717","0.46811545","0.46800348","0.46758896","0.46745157","0.4673177","0.46718472","0.46654335","0.46654335","0.46594226","0.46572414","0.46516943","0.46477503","0.46423712","0.46410853","0.464019","0.4636283","0.4635786","0.46235895","0.4621471","0.4612817"],"string":"[\n \"0.6472857\",\n \"0.5750757\",\n \"0.5650037\",\n \"0.5516797\",\n \"0.5459125\",\n \"0.54315567\",\n \"0.542719\",\n \"0.5388466\",\n \"0.5336627\",\n \"0.53299576\",\n \"0.5304679\",\n \"0.52980345\",\n \"0.52818644\",\n \"0.52797127\",\n \"0.5246277\",\n \"0.5232472\",\n \"0.52007216\",\n \"0.5188484\",\n \"0.5181919\",\n \"0.5174036\",\n \"0.5146636\",\n \"0.5142773\",\n \"0.512924\",\n \"0.5119605\",\n \"0.51102847\",\n \"0.50976866\",\n \"0.50848013\",\n \"0.50746673\",\n \"0.5039749\",\n \"0.5035337\",\n \"0.50214773\",\n \"0.5006417\",\n \"0.49807134\",\n \"0.49771914\",\n \"0.49670306\",\n \"0.49295518\",\n \"0.4926534\",\n \"0.49199817\",\n \"0.49171782\",\n \"0.49151823\",\n \"0.4908545\",\n \"0.4901406\",\n \"0.48876593\",\n \"0.48852453\",\n \"0.48711237\",\n \"0.48629707\",\n \"0.4861078\",\n \"0.48476452\",\n \"0.48425475\",\n \"0.4836251\",\n \"0.4833537\",\n \"0.48292664\",\n \"0.48272035\",\n \"0.48270997\",\n \"0.4824705\",\n \"0.479232\",\n \"0.4789255\",\n \"0.4786484\",\n \"0.47855487\",\n \"0.47851005\",\n \"0.4779864\",\n \"0.47580424\",\n \"0.4754054\",\n \"0.4753803\",\n \"0.47536433\",\n \"0.47504663\",\n \"0.47429112\",\n \"0.47389635\",\n \"0.4735756\",\n \"0.47346902\",\n \"0.4733986\",\n \"0.4729851\",\n \"0.4726891\",\n \"0.47196308\",\n \"0.47195357\",\n \"0.4715567\",\n \"0.47109652\",\n \"0.4703375\",\n \"0.46925768\",\n \"0.46830717\",\n \"0.46811545\",\n \"0.46800348\",\n \"0.46758896\",\n \"0.46745157\",\n \"0.4673177\",\n \"0.46718472\",\n \"0.46654335\",\n \"0.46654335\",\n \"0.46594226\",\n \"0.46572414\",\n \"0.46516943\",\n \"0.46477503\",\n \"0.46423712\",\n \"0.46410853\",\n \"0.464019\",\n \"0.4636283\",\n \"0.4635786\",\n \"0.46235895\",\n \"0.4621471\",\n \"0.4612817\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.4780201"},"document_rank":{"kind":"string","value":"60"}}},{"rowIdx":81768,"cells":{"query":{"kind":"string","value":"Write rows to the file descriptor."},"document":{"kind":"string","value":"def write_rows(self, rows: Union[List[dict], dict]):\n rows = listify(rows)\n flat = self.get_arg_value(\"json_flat\")\n\n indent = None if flat else 2\n prefix = \" \" * indent if indent else \"\"\n\n for row in rows:\n if self._first_row:\n pre = \"\" if flat else \"\\n\"\n else:\n pre = \"\\n\" if flat else \",\\n\"\n\n self._first_row = False\n self._fd.write(pre)\n\n value = json.dumps(row, indent=indent)\n value = textwrap.indent(value, prefix=prefix) if indent else value\n self._fd.write(value)\n del value, row"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def write(self, row):\n bytes = struct.pack(self.pack_format, *row)\n self.f.write(bytes)","def store_rows(self, course_id, filename, rows):\r\n output_buffer = StringIO()\r\n csv.writer(output_buffer).writerows(rows)\r\n self.store(course_id, filename, output_buffer)","def writelines(self, lines):\n for line in lines:\n self.write(line)","def __closeRow(fd):\n\n print(\" </tr>\", file=fd)","def _write_rows(self):\n try:\n xf = self._writer.xf.send(True)\n except StopIteration:\n self._already_saved()\n\n with xf.element(\"sheetData\"):\n row_idx = 1\n try:\n while True:\n row = (yield)\n row = self._values_to_row(row, row_idx)\n self._writer.write_row(xf, row, row_idx)\n row_idx += 1\n except GeneratorExit:\n pass\n\n self._writer.xf.send(None)","def write(self, row):\n self.append_rows.append(tuple(row))","def feed_rows(self, rows):\n self.write(self.ASCII_ESC, 'J', rows)\n self.timeout_set(rows * self._dot_feed_time)\n self._prev_byte = '\\n'\n self._column = 0","def _write(self):\n # Reload\n with portalocker.Lock(self.filename, 'w') as fh:\n self.data.to_csv(fh, index=False)\n fh.flush()\n os.fsync(fh.fileno())","def store_rows(self, course_id, filename, rows):\r\n output_buffer = StringIO()\r\n gzip_file = GzipFile(fileobj=output_buffer, mode=\"wb\")\r\n csv.writer(gzip_file).writerows(rows)\r\n gzip_file.close()\r\n\r\n self.store(course_id, filename, output_buffer)","def writelines(self, seq):\n for line in seq:\n self.write(line)","def writeData(self, lines, fpath):\n with open(fpath, 'w') as f:\n for line in lines:\n print(line, file=f)","def write_row(self, data):\n raise NotImplementedError()","def write (self, path):\n\t\ts=[]; add=s.append\n\t\tadd ('\\t'.join (self.schema))\n\t\tfor record in self.data:\n\t\t\tadd (record.asTabDelimitedRecord())\n\t\t\n\t\t# f = open (path, 'w')\n\t\tf = codecs.open(path, 'w', 'utf-8')\n\t\tf.write (self.linesep.join (s))\n\t\tf.close()\n\t\tprint (\"data written to \" + path)","def serialise(rows: Iterable[Dict], path: pathlib.Path, **kwargs):\n\n fieldnames = settings.OUTPUT_HEADERS\n\n LOGGER.info(\"Writing CSV with headers: %s\", fieldnames)\n\n with path.open('w', newline='') as file:\n writer = csv.DictWriter(file, fieldnames=fieldnames, dialect=UrbanDialect, **kwargs)\n\n row_count = 0\n for row in rows:\n writer.writerow(row)\n\n row_count += 1\n\n if row_count:\n LOGGER.info(\"Wrote %s rows to '%s'\", row_count, file.name)\n else:\n path.unlink()\n LOGGER.info(\"Deleted '%s'\", file.name)","def putRow(self, idx, row):\n if idx >= self.N:\n raise IndexError(\"Attempting to write index %s, raw store only has %d rows\"%(\n idx, self.N))\n if len(row) != len(self.dtypes):\n raise ValueError(\n \"data value only has %s entries, \"\n \"raw store has %s columns\"%(\n len(row), len(self.dtypes)))\n\n # checks row datatypes\n try:\n v = [dtype(v) for dtype,v in zip(self.dtypes, row)]\n except TypeError as e:\n # we might have None's here\n message = [str(e)]\n for i,(dtype,v) in enumerate(zip(self.dtypes, row)):\n try: dtype(v)\n except:\n message.append(\"\\tFor column %r can't convert %r to %s\"%(\n self.colnames[i],\n v,\n dtype))\n raise TypeError(\"\\n\".join(message))\n \n offset = idx * self.rowbytes\n self.f.seek(offset,0)\n try:\n bytes = struct.pack(self.pack_format, *[convert_string(x) for x in row])\n except struct.error:\n logging.exception(\"Can't write row %r\\ntypes: %r\\nformat: %r\",\n row,\n self.dtypes,\n self.pack_format)\n raise\n try:\n self.f.write(bytes)\n except Exception as e:\n logging.error(\"Attempting to write to offset: %s\", offset)\n logging.error(\"Rowsize: %s\", self.rowbytes)\n logging.error(\"Row: %s\", idx)\n logging.error(\"Max Row: %s\", self.N)\n logging.error(\"Filesize is %s\",\n os.path.getsize(self.fname))\n raise","def write(self, row: Optional[Any] = None):\n self.fout.write('{}\\n'.format(json.dumps(row, cls=self.encoder)))","def write(self):\n self.log('Writing {0}'.format(self.filename))\n with open(self.filename, 'w') as handle:\n for this_line in self.contents:\n handle.write(this_line+self.linesep)\n self.changed = False\n return True","def WriteOutput(self, rows, fileName, access='wb'):\n \n outputFile = open(fileName, access)\n try: \n outputFile.write(self.GetBanner())\n csv.writer(outputFile, dialect='excel-tab').writerows(rows)\n print 'Wrote secondary output to: %s' %(fileName) \n except IOError:\n print 'Error writing output to: %s' %(fileName) \n finally:\n outputFile.close()","def write_entries(self, entries):\n for entry in entries:\n self.write(entry)","def __openRow(fd):\n\n print(\" <tr>\", file=fd)","def writerow(self, row):\n data = []\n basestring_type = six.string_types[0]\n for value in row:\n if not isinstance(value, basestring_type):\n value = '%s' % (value,)\n data.append(value.encode('utf-8'))\n self.writer.writerow(data)\n data = self.queue.getvalue()\n data = data.decode('utf-8')\n self.stream.write(data)\n self.queue.truncate(0)","def writelines(self, iterable):\n for line in iterable:\n self._barf_if_closed()\n self.write(line)","def write(self, path):\n\n lines = [t._to_fam_file_line() for t in self._trios]\n\n with Env.fs().open(path, mode=\"w\") as file:\n for line in lines:\n file.write(line + \"\\n\")","def write(self, fd, ext_file_action=ExtFileAction.copy_relative_paths):\n # never write an empty block\n is_empty = self.is_empty()\n if (\n is_empty\n and self.structure.name.lower() != \"exchanges\"\n and self.structure.name.lower() != \"options\"\n and self.structure.name.lower() != \"sources\"\n and self.structure.name.lower() != \"stressperioddata\"\n ):\n return\n if self.structure.repeating():\n repeating_datasets = self._find_repeating_datasets()\n for repeating_dataset in repeating_datasets:\n # resolve any missing block headers\n self._add_missing_block_headers(repeating_dataset)\n for block_header in sorted(self.block_headers):\n # write block\n self._write_block(fd, block_header, ext_file_action)\n else:\n self._write_block(fd, self.block_headers[0], ext_file_action)","def write_report_row(self, row):\n if self._report_filename:\n try:\n f = open(self._report_filename, \"at\")\n f.write(\",\".join([str(v) for v in row]) + \"\\n\")\n except Exception as e:\n error_logger.error(repr(e))\n finally:\n f.close()","def write(self, line):\n for stream in self.streams:\n stream.write(line)","def write(self): \n # Open csv file\n with open(self.file_name, 'w', newline='') as file:\n self._writer = csv.writer(file)\n \n # Write header rows\n# self.write_sim_header_data(self.trace.sim.get_data())\n \n # Write trace table\n self._writer.writerow(['Record #', 'Rep', 'Time',\n 'Priority', 'Record Type', 'Name'])\n for trace_record in self.trace._record_list:\n self._writer.writerow(trace_record.get_row())\n file.close()","def save_to_file(self, file_path):\n if file_path:\n f = open(file_path, 'w')\n for row in range(self.rows):\n f.write(''.join(self.data[row]) + '\\n')\n f.close()","def save_to_file(self, file_path):\n if file_path:\n f = open(file_path, 'w')\n for row in range(self.rows):\n f.write(''.join(self.data[row]) + '\\n')\n f.close()","def writelines(self, iterable):\n for line in iterable:\n for stream in self.streams:\n stream.write(line)","def write_to(channel, lines):\n for s in lines:\n channel.write(s)\n channel.write('\\n')","def writeRow(self, row, data, offset=0):\n for d in data:\n if offset > self.__width: break\n self._c[row + offset*self.__height] = d\n offset += 1","def write(self, fd):\n if self.__tag:\n fd.write(self.__tag)\n for ii in self.__content:\n fd.write(ii)","def write(self, batch):\n cursor = connection.cursor()\n while batch:\n values = [\n \"(%s, %s)\" % (\n psycopg2.Binary(k),\n psycopg2.Binary(v)\n ) for k, v in batch[:self.BATCH_SIZE]]\n sql = \"INSERT INTO %s(k,v) VALUES %s\" % (self.table, \",\".join(values))\n batch = batch[self.BATCH_SIZE:]\n cursor.execute(sql)\n cursor.execute(\"COMMIT\")","def save(self, close=True):\n rows = []\n # find out how many rows we're going to need to write\n max_rows = 0\n for _, cont in self.data:\n if len(cont) > max_rows:\n max_rows = len(cont)\n max_rows += 1 # add the header row\n\n for i in range(0, max_rows):\n row = []\n for (col_name, col_contents) in self.data:\n col_data = [col_name] + col_contents\n if len(col_data) > i:\n row.append(col_data[i])\n else:\n row.append(\"\")\n rows.insert(i, row)\n\n # Remove current contents of file\n self.file_object.seek(0)\n self.file_object.truncate()\n\n # Write new CSV data\n writer = UnicodeWriter(self.file_object, encoding=self.output_encoding)\n writer.writerows(rows)\n\n if close:\n self.file_object.close()","def write_to_file(self, file):\n f = open(file, \"w+\")\n for row in self.value:\n line = \" \".join(str(el) for el in row) + \"\\n\"\n f.write(line)\n\n f.close()","def save_csv(filename, rows):\n with open(filename, 'w', newline='', encoding='utf-8') as f:\n writer = csv.writer(f)\n writer.writerow([\n 'title', 'runtime', 'genre(s)', 'director(s)', 'writer(s)',\n 'actor(s)', 'rating(s)', 'number of rating(s)'\n ])\n\n writer.writerows(rows)","def _write_shard(filename, dataset, indices):\n with tf.python_io.TFRecordWriter(filename) as writer:\n for j in indices:\n writer.write(dataset[j])","def write_csv(path, lines, headers):\n print \"Opening %s for score output\" % base_name(path)\n\n try:\n f = open(path, 'wb')\n writer = csv.writer(f)\n writer.writerow(headers)\n writer.writerows(lines)\n except IOError:\n print \"Cannot open %s\" % path\n else:\n print \"Scores successfully written to %s\" % path\n f.close()","def __do_write(filestream, seq, header=None):\n if header is not None:\n filestream.write(header + '\\n') # double check newlines\n try:\n for line in chunks(seq, 70):\n filestream.write(line + '\\n')\n except Exception as e:\n print(e)","def _write_shard(filename, dataset, indices):\n with tf.io.TFRecordWriter(filename) as writer:\n for j in indices:\n writer.write(dataset[j])","def write_archive_row(self, row: ArchiveRow):\n raise NotImplementedError() # pragma: no cover","def _file_writer(self, lines, filename):\n if self.MockRun:\n return\n\n if self.Verbose:\n print \"Writing file %s\" % filename\n\n updated_file = open(filename, 'w')\n updated_file.write(''.join(lines))\n updated_file.close()","def writeToCon(self, line):\r\n if not self.connected:\r\n raise UserError(errors['NotConnectedYet'])\r\n else:\r\n self.con.write(self.normalise(line) + '\\n')","def writefile(file, fvs, sequence, cvs = None):\r\n if cvs is not None: assert fvs.shape[0] == cvs.shape[0]\r\n for thread in sequence:\r\n for i in thread:\r\n if cvs is not None:\r\n one_line = CRFFileWriter.instance(fvs[i], cvs[i])\r\n else:\r\n one_line = CRFFileWriter.instance(fvs[i])\r\n file.write(one_line)\r\n file.write('\\n')","def _close_writable(self):\n for future in as_completed(self._write_futures):\n future.result()","async def writelines(self, lines):\n # first check if the file is binary or not\n if 'b' in self._mode:\n raise APIException(\n \"writelines on a binary file is not permitted: {}\".format(\n self._uri)\n )\n # write all but the last line with a line break\n for l in lines:\n await self.write((l+\"\\n\").encode('utf-8'))\n return True","def to_csv_file_obj(self, rows):\n output = StringIO.StringIO()\n writer = csv.writer(output)\n writer.writerows(rows)\n return output","def write_csv(self, filename, cutoff=2):\n f = csv.writer(open(filename, 'wb'))\n for row in self.rows(cutoff=cutoff):\n f.writerow(row)","def writerow(self, outdict):\r\n row = []\r\n for field in FatWriter.FIELDS:\r\n col = outdict.get(field, '')\r\n col = col.replace('\\t', ' ')\r\n col = col.replace('\\n', '\\\\n')\r\n row.append(col)\r\n self.outfile.write('\\t'.join(row) + '\\n')","def xlsx_write_rows(filename, rows):\n workbook = xlsxwriter.Workbook(filename)\n worksheet = workbook.add_worksheet()\n # Write values\n nrows = 0\n for i, row in enumerate(rows):\n for j, val in enumerate(row):\n worksheet.write(i, j, val)\n nrows += 1\n # Cleanup\n workbook.close()\n return nrows","def writerows(self, row):\n if not self.resolved:\n self._resolve_writer()\n\n if isinstance(self.resolved, ReaderType):\n raise AttributeError('Object CSV has no attribute writerows')\n self._resolve_writer()\n self.resolved.writerows(row)","def writerow(self, data):\n self.get_csv_writer().writerow(data)","def _write_stream(self):\n enrich_df = self._process_stream()\n df_writer = enrich_df \\\n .writeStream \\\n .queryName(\"Agro Data Writer\") \\\n .foreachBatch(db_utils.foreach_batch_function) \\\n .option(\"checkpointLocation\", \"chk-point-dir\") \\\n .trigger(processingTime=\"1 minute\") \\\n .start()\n\n df_writer.awaitTermination()","def write(self, path):\n # if file doesn't already exist, write column names in a header\n if not os.path.exists(path):\n with open(path, 'a+') as f:\n f.write('# {}# time,status,dphi,umolar,mbar,airSat,tempSample,tempCase,signalIntensity,ambientLight,pressure,humidity,resistorTemp,percentO2\\n'.format(self.label))\n # generate out_str\n if isinstance(self.last_read[0], list):\n out_str = ''\n for r in self.last_read:\n out_str += fmt(r, 1, ',') + '\\n'\n else:\n out_str = fmt(self.last_read, 1, ',') + '\\n'\n # write and save data\n self.write_str = out_str\n with open(path, 'a+') as f:\n f.write(out_str)\n return","def write_to(self, fname, **kwargs):\n data = self.to_Table()\n data.write(fname, **kwargs)","def __multi_append_row(self, data, path):\n #Write the row to the data page file ('a' positions the stream at the end of the file).\n temp_current_row = self.current_row\n with open(path, 'a') as f:\n f.write(data)\n #if self.__check_write_success_insert(new_data, path):\n # return True\n #else:\n # print('Data was corrupted at row: ' + temp_current_row)\n # return False\n return True","def writerow(self, row):\n if not self.resolved:\n self._resolve_writer()\n\n if isinstance(self.resolved, ReaderType):\n raise AttributeError('Object CSV has no attribute writerow')\n\n self.resolved.writerow(row)","def write(self, stream, root, order):\n need_newline = False\n for row in root:\n if need_newline:\n stream.write('\\n')\n need_newline = True\n if isinstance(row, list):\n stream.write('\\n'.join(row) + '\\n')\n else:\n for column in order:\n stream.write(row[column] + '\\n')","def _write(fdesc, data):\n while data:\n count = os.write(fdesc, data)\n data = data[count:]","def flush(self):\n self._write()","def log_readouts(self, rs):\n for r in rs: self.log_readout(*r)\n if len(rs): self.writeconn.commit()","def write_csv(self, file):\n # Write header row\n file.write('Timestamp,MessageType,Queue,Price,Volume,OrderID\\n')\n # Write content\n for x in self.records:\n row = (str(x[0]) + ',' + x[1][\"MessageType\"] + ',' +\n x[1][\"Queue\"] + ',' + str(x[1][\"Price\"]) + ',' +\n str(x[1][\"Volume\"]) + ',' + str(x[1][\"OrderID\"]) + '\\n')\n file.write(row)","def write_record(self, *items):\n items = tuple(np.asarray(item) for item in items)\n total_size = sum(item.nbytes for item in items)\n\n nb = np.array([total_size], dtype=self._header_dtype)\n\n nb.tofile(self._fp)\n for item in items:\n item.tofile(self._fp)\n nb.tofile(self._fp)","def write(l, path, columns):\n \n file = open(path, 'w', newline = '', encoding = 'utf-8')\n writer = csv.writer(file, delimiter = '\\t', quotechar = '', quoting = csv.QUOTE_NONE)\n row = []\n for col in columns:\n row.append(col)\n writer.writerow(row)\n for entry in l:\n row = []\n for col in columns:\n row.append(entry[col])\n writer.writerow(row)\n file.close()","def write_csv(outputfile, delimiter, newline, qchar, encoding, header, rows):\n with open(outputfile, 'w', newline=newline, encoding=encoding) as csvfile:\n writer = csv.writer(csvfile, delimiter=delimiter,\n quotechar=qchar, quoting=csv.QUOTE_MINIMAL)\n writer.writerow(header)\n for row in rows:\n writer.writerow(row)","def write_lines(list_of_lines, file):\r\n for i in range(0, len(list_of_lines)):\r\n file.write(list_of_lines[i] + b\"\\n\")","def write_csv_file(filepath, fieldnames, rows):\n headers = [{'label': field} for field in fieldnames]\n with open(filepath, 'w') as f_buf:\n outfile = CsvWriter()\n outfile.set_headers(headers)\n outfile._datas = rows\n outfile.render(f_buf)","def save_entries(self):\n with open(self.file_name, \"w\") as file:\n file.write('date,name,minutes,note\\n')\n for entry in self.entries:\n writer = csv.writer(file)\n writer.writerow([entry.date, entry.name, entry.minutes, entry.note])","def index_rows(self, corpus, source, *rows):\n # Pickle database rows.\n self._pickle_rows(corpus, source, rows)\n\n # Write text content.\n for row in rows:\n if getattr(row, '_text', None):\n self._write_text(row)\n self._write_tokens(row)","def _batch_write(self):\n if self.to_put:\n db.put(self.to_put)\n self.to_put = []\n if self.to_delete:\n db.delete(self.to_delete)\n self.to_delete = []","def write(self):\n pass","def write(self):\n pass","def send_to_kafka(rows):\n producer = connect_kafka_producer()\n for row in rows:\n print(row.asDict())\n producer.send(TOPIC_NAME, value=row.asDict())\n producer.flush()","def _write(self, data):\n self._writer.write(data)","def write(self, fh):\n # Skip over the file header for now, we'll fill it out later\n fh.seek(self.IDX_TABLE_ADDR, 0)\n\n idx_table_entry_count = len(self.entries)\n\n # Generate and write the index table\n for idx, res in enumerate(self.entries):\n typ, num1, num2, num3, num4 = b\"\\0\\0\\0\\0\", 0x0, 0x0, 0x0, 0x8\n if res is not None:\n typ, num1, num2, num3, num4 = res.get_header()\n fh.write(struct.pack(\"=4s4x2I2xBB\", typ, num1, num2, num3, num4))\n\n off_table_offset = fh.tell() - self.IDX_TABLE_ADDR\n off_table_entry_count = len([i for i in self.entries if i is not None])\n # ???: An unknown pointer into the middle of the index table. Modifying it causes the game to crash on boot. The value is exactly 0x800 bytes (1 BLOCK_SIZE) less than the start of the offset table.\n unk = 0x1C4B4\n\n fh.write(struct.pack(\"=4x2I\", off_table_entry_count, unk))\n\n next_empty_addr = self.NEXT_BLOCK_ADDR(\n fh.tell() + struct.calcsize(\"=2I\") * off_table_entry_count\n )\n data_start_block = self.ADDR_NUM_BLOCK(next_empty_addr)\n\n # Generate and write the offset table & its targets\n\n for idx, res in enumerate(self.entries):\n if res is None:\n continue\n fh.write(struct.pack(\"=2I\", idx, self.ADDR_NUM_BLOCK(next_empty_addr)))\n off = fh.tell()\n\n # Write resource\n fh.seek(next_empty_addr, 0)\n res.fw.seek(0x0)\n fh.write(res.fw.read())\n next_empty_addr = self.NEXT_BLOCK_ADDR(fh.tell())\n\n # Pad to next block\n fh.write(b\"\\0\" * (next_empty_addr - fh.tell()))\n\n fh.seek(off)\n\n # Write the file header\n # ???: All these constants are unknown\n fh.seek(0x0, 0)\n fh.write(\n struct.pack(\n \"=10I\",\n 0xA,\n data_start_block,\n 0x1,\n 0x0,\n idx_table_entry_count,\n off_table_offset,\n 0x1,\n 0x0,\n 0x0,\n 0x276F4, # ???: Doesn't affect game boot\n )\n )","def _writeRecord(self, path, name, data):\n file_path = os.path.join(path, name)\n with open(file_path, 'w') as f:\n for item in data:\n f.write(str(item)+'\\t')\n f.write('\\n')","def write_data():","def write(self):\n\t\traise NotImplementedError('%s: No write function implemented!' % self.name)","def write(self, content):\n for f in self.files:\n f.write(content)\n f.flush() # Want this content is displayed immediately on file","def write_to_sheet(self):\n for i, row in enumerate(self.ws[self.range_name]):\n if isinstance(self.data[i], tuple):\n self.data[i] = list(self.data[i])\n for j, cell in enumerate(row):\n cell.value = self.data[i][j]","def _export_disp_rowset(self, name: str, membr: str, f: IO[str], ind: str, size: int) -> None:\n assert self._disp_verts is not None\n f.write(f'{ind}\\t\\t{name}\\n{ind}\\t\\t{{\\n')\n rows = [\n str(getattr(vert, membr))\n for vert in self._disp_verts\n ]\n for y in range(size):\n f.write(f'{ind}\\t\\t\"row{y}\" \"{\" \".join(rows[size * y:size * (y+1)])}\"\\n')\n f.write(f'{ind}\\t\\t}}\\n')","def Write(self):\n table_data = self._TABLE.build(self._offsets)\n self._zip_file.writestr(self._stream_name, table_data)","def write(self, args):\n\t\tnewcsvfile = self.filename[:len(self.filename)-4] + \"NEW.csv\" #clever naming MIGHT NEED TO CHANGE THIS LATER/OVERWRITE OLD FILE?\n\t\twith open(newcsvfile, 'wb') as f:\n\t\t\twriter = csv.writer(f)\n\t\t\twriter.writerows(self.all_likes)","def write(self):\n raise NotImplementedError","def write(self):","def write(self):","def Write(self):\n table_data = self._TABLE.build(self._timestamps)\n self._zip_file.writestr(self._stream_name, table_data)","def row(self, rdata):\n self = self\n file = open(\"imdb_output.txt\", \"a\")\n file.write(str(\"\\t\".join(rdata)) + \"\\n\")","def write(self, data: np.ndarray) -> None:\n assert data.ndim == 1\n all_data = np.hstack((self.res, data))\n nrows = len(all_data) // self.width\n if nrows > 0:\n d = all_data[0: nrows * self.width].reshape(nrows, self.width)\n w = Window(0, self.rows_written, d.shape[1], d.shape[0])\n self.f.write(d, 1, window=w)\n self.rows_written += nrows\n self.res = all_data[nrows * self.width:]\n else:\n self.res = all_data","def write(self, recs, out_handle):\n self._write_header(out_handle)\n for rec in recs:\n self._write_annotations(rec.annotations, rec.id, out_handle)\n for sf in rec.features:\n self._write_feature(sf, rec.id, out_handle)","def write_all(self):\r\n pass","def append_rows(self, rows):\n for row in rows:\n self.append_row(row)","def _write(self, line):\n data = (line + TERMINATOR).encode()\n self._transport.write(data)\n log.debug(f'{self} >> {line!r}')","def write(self, fname):\n pass","def _write_to_file(self):\n with open(self.filename + \".ir\", \"w+\") as file:\n file.writelines(\n [\"\\n\" + l if p != 0 else l for p, l in enumerate(self.lines)]\n )","def write_to_csv(self, data):\n with open(\"out.csv\", \"w\", newline=\"\") as f:\n writer = csv.writer(f)\n writer.writerow(self.column_names)\n writer.writerows(data)\n print(\" Updated succesfully \")","def write(self, out):","def write_to_csv(list_of_rows, file_name):\n with open(file_name, 'w') as f:\n writer = csv.writer(f)\n for row in list_of_rows:\n if None in row:\n continue\n writer.writerow(row)\n \n f.close()","def write(data):"],"string":"[\n \"def write(self, row):\\n bytes = struct.pack(self.pack_format, *row)\\n self.f.write(bytes)\",\n \"def store_rows(self, course_id, filename, rows):\\r\\n output_buffer = StringIO()\\r\\n csv.writer(output_buffer).writerows(rows)\\r\\n self.store(course_id, filename, output_buffer)\",\n \"def writelines(self, lines):\\n for line in lines:\\n self.write(line)\",\n \"def __closeRow(fd):\\n\\n print(\\\" </tr>\\\", file=fd)\",\n \"def _write_rows(self):\\n try:\\n xf = self._writer.xf.send(True)\\n except StopIteration:\\n self._already_saved()\\n\\n with xf.element(\\\"sheetData\\\"):\\n row_idx = 1\\n try:\\n while True:\\n row = (yield)\\n row = self._values_to_row(row, row_idx)\\n self._writer.write_row(xf, row, row_idx)\\n row_idx += 1\\n except GeneratorExit:\\n pass\\n\\n self._writer.xf.send(None)\",\n \"def write(self, row):\\n self.append_rows.append(tuple(row))\",\n \"def feed_rows(self, rows):\\n self.write(self.ASCII_ESC, 'J', rows)\\n self.timeout_set(rows * self._dot_feed_time)\\n self._prev_byte = '\\\\n'\\n self._column = 0\",\n \"def _write(self):\\n # Reload\\n with portalocker.Lock(self.filename, 'w') as fh:\\n self.data.to_csv(fh, index=False)\\n fh.flush()\\n os.fsync(fh.fileno())\",\n \"def store_rows(self, course_id, filename, rows):\\r\\n output_buffer = StringIO()\\r\\n gzip_file = GzipFile(fileobj=output_buffer, mode=\\\"wb\\\")\\r\\n csv.writer(gzip_file).writerows(rows)\\r\\n gzip_file.close()\\r\\n\\r\\n self.store(course_id, filename, output_buffer)\",\n \"def writelines(self, seq):\\n for line in seq:\\n self.write(line)\",\n \"def writeData(self, lines, fpath):\\n with open(fpath, 'w') as f:\\n for line in lines:\\n print(line, file=f)\",\n \"def write_row(self, data):\\n raise NotImplementedError()\",\n \"def write (self, path):\\n\\t\\ts=[]; add=s.append\\n\\t\\tadd ('\\\\t'.join (self.schema))\\n\\t\\tfor record in self.data:\\n\\t\\t\\tadd (record.asTabDelimitedRecord())\\n\\t\\t\\n\\t\\t# f = open (path, 'w')\\n\\t\\tf = codecs.open(path, 'w', 'utf-8')\\n\\t\\tf.write (self.linesep.join (s))\\n\\t\\tf.close()\\n\\t\\tprint (\\\"data written to \\\" + path)\",\n \"def serialise(rows: Iterable[Dict], path: pathlib.Path, **kwargs):\\n\\n fieldnames = settings.OUTPUT_HEADERS\\n\\n LOGGER.info(\\\"Writing CSV with headers: %s\\\", fieldnames)\\n\\n with path.open('w', newline='') as file:\\n writer = csv.DictWriter(file, fieldnames=fieldnames, dialect=UrbanDialect, **kwargs)\\n\\n row_count = 0\\n for row in rows:\\n writer.writerow(row)\\n\\n row_count += 1\\n\\n if row_count:\\n LOGGER.info(\\\"Wrote %s rows to '%s'\\\", row_count, file.name)\\n else:\\n path.unlink()\\n LOGGER.info(\\\"Deleted '%s'\\\", file.name)\",\n \"def putRow(self, idx, row):\\n if idx >= self.N:\\n raise IndexError(\\\"Attempting to write index %s, raw store only has %d rows\\\"%(\\n idx, self.N))\\n if len(row) != len(self.dtypes):\\n raise ValueError(\\n \\\"data value only has %s entries, \\\"\\n \\\"raw store has %s columns\\\"%(\\n len(row), len(self.dtypes)))\\n\\n # checks row datatypes\\n try:\\n v = [dtype(v) for dtype,v in zip(self.dtypes, row)]\\n except TypeError as e:\\n # we might have None's here\\n message = [str(e)]\\n for i,(dtype,v) in enumerate(zip(self.dtypes, row)):\\n try: dtype(v)\\n except:\\n message.append(\\\"\\\\tFor column %r can't convert %r to %s\\\"%(\\n self.colnames[i],\\n v,\\n dtype))\\n raise TypeError(\\\"\\\\n\\\".join(message))\\n \\n offset = idx * self.rowbytes\\n self.f.seek(offset,0)\\n try:\\n bytes = struct.pack(self.pack_format, *[convert_string(x) for x in row])\\n except struct.error:\\n logging.exception(\\\"Can't write row %r\\\\ntypes: %r\\\\nformat: %r\\\",\\n row,\\n self.dtypes,\\n self.pack_format)\\n raise\\n try:\\n self.f.write(bytes)\\n except Exception as e:\\n logging.error(\\\"Attempting to write to offset: %s\\\", offset)\\n logging.error(\\\"Rowsize: %s\\\", self.rowbytes)\\n logging.error(\\\"Row: %s\\\", idx)\\n logging.error(\\\"Max Row: %s\\\", self.N)\\n logging.error(\\\"Filesize is %s\\\",\\n os.path.getsize(self.fname))\\n raise\",\n \"def write(self, row: Optional[Any] = None):\\n self.fout.write('{}\\\\n'.format(json.dumps(row, cls=self.encoder)))\",\n \"def write(self):\\n self.log('Writing {0}'.format(self.filename))\\n with open(self.filename, 'w') as handle:\\n for this_line in self.contents:\\n handle.write(this_line+self.linesep)\\n self.changed = False\\n return True\",\n \"def WriteOutput(self, rows, fileName, access='wb'):\\n \\n outputFile = open(fileName, access)\\n try: \\n outputFile.write(self.GetBanner())\\n csv.writer(outputFile, dialect='excel-tab').writerows(rows)\\n print 'Wrote secondary output to: %s' %(fileName) \\n except IOError:\\n print 'Error writing output to: %s' %(fileName) \\n finally:\\n outputFile.close()\",\n \"def write_entries(self, entries):\\n for entry in entries:\\n self.write(entry)\",\n \"def __openRow(fd):\\n\\n print(\\\" <tr>\\\", file=fd)\",\n \"def writerow(self, row):\\n data = []\\n basestring_type = six.string_types[0]\\n for value in row:\\n if not isinstance(value, basestring_type):\\n value = '%s' % (value,)\\n data.append(value.encode('utf-8'))\\n self.writer.writerow(data)\\n data = self.queue.getvalue()\\n data = data.decode('utf-8')\\n self.stream.write(data)\\n self.queue.truncate(0)\",\n \"def writelines(self, iterable):\\n for line in iterable:\\n self._barf_if_closed()\\n self.write(line)\",\n \"def write(self, path):\\n\\n lines = [t._to_fam_file_line() for t in self._trios]\\n\\n with Env.fs().open(path, mode=\\\"w\\\") as file:\\n for line in lines:\\n file.write(line + \\\"\\\\n\\\")\",\n \"def write(self, fd, ext_file_action=ExtFileAction.copy_relative_paths):\\n # never write an empty block\\n is_empty = self.is_empty()\\n if (\\n is_empty\\n and self.structure.name.lower() != \\\"exchanges\\\"\\n and self.structure.name.lower() != \\\"options\\\"\\n and self.structure.name.lower() != \\\"sources\\\"\\n and self.structure.name.lower() != \\\"stressperioddata\\\"\\n ):\\n return\\n if self.structure.repeating():\\n repeating_datasets = self._find_repeating_datasets()\\n for repeating_dataset in repeating_datasets:\\n # resolve any missing block headers\\n self._add_missing_block_headers(repeating_dataset)\\n for block_header in sorted(self.block_headers):\\n # write block\\n self._write_block(fd, block_header, ext_file_action)\\n else:\\n self._write_block(fd, self.block_headers[0], ext_file_action)\",\n \"def write_report_row(self, row):\\n if self._report_filename:\\n try:\\n f = open(self._report_filename, \\\"at\\\")\\n f.write(\\\",\\\".join([str(v) for v in row]) + \\\"\\\\n\\\")\\n except Exception as e:\\n error_logger.error(repr(e))\\n finally:\\n f.close()\",\n \"def write(self, line):\\n for stream in self.streams:\\n stream.write(line)\",\n \"def write(self): \\n # Open csv file\\n with open(self.file_name, 'w', newline='') as file:\\n self._writer = csv.writer(file)\\n \\n # Write header rows\\n# self.write_sim_header_data(self.trace.sim.get_data())\\n \\n # Write trace table\\n self._writer.writerow(['Record #', 'Rep', 'Time',\\n 'Priority', 'Record Type', 'Name'])\\n for trace_record in self.trace._record_list:\\n self._writer.writerow(trace_record.get_row())\\n file.close()\",\n \"def save_to_file(self, file_path):\\n if file_path:\\n f = open(file_path, 'w')\\n for row in range(self.rows):\\n f.write(''.join(self.data[row]) + '\\\\n')\\n f.close()\",\n \"def save_to_file(self, file_path):\\n if file_path:\\n f = open(file_path, 'w')\\n for row in range(self.rows):\\n f.write(''.join(self.data[row]) + '\\\\n')\\n f.close()\",\n \"def writelines(self, iterable):\\n for line in iterable:\\n for stream in self.streams:\\n stream.write(line)\",\n \"def write_to(channel, lines):\\n for s in lines:\\n channel.write(s)\\n channel.write('\\\\n')\",\n \"def writeRow(self, row, data, offset=0):\\n for d in data:\\n if offset > self.__width: break\\n self._c[row + offset*self.__height] = d\\n offset += 1\",\n \"def write(self, fd):\\n if self.__tag:\\n fd.write(self.__tag)\\n for ii in self.__content:\\n fd.write(ii)\",\n \"def write(self, batch):\\n cursor = connection.cursor()\\n while batch:\\n values = [\\n \\\"(%s, %s)\\\" % (\\n psycopg2.Binary(k),\\n psycopg2.Binary(v)\\n ) for k, v in batch[:self.BATCH_SIZE]]\\n sql = \\\"INSERT INTO %s(k,v) VALUES %s\\\" % (self.table, \\\",\\\".join(values))\\n batch = batch[self.BATCH_SIZE:]\\n cursor.execute(sql)\\n cursor.execute(\\\"COMMIT\\\")\",\n \"def save(self, close=True):\\n rows = []\\n # find out how many rows we're going to need to write\\n max_rows = 0\\n for _, cont in self.data:\\n if len(cont) > max_rows:\\n max_rows = len(cont)\\n max_rows += 1 # add the header row\\n\\n for i in range(0, max_rows):\\n row = []\\n for (col_name, col_contents) in self.data:\\n col_data = [col_name] + col_contents\\n if len(col_data) > i:\\n row.append(col_data[i])\\n else:\\n row.append(\\\"\\\")\\n rows.insert(i, row)\\n\\n # Remove current contents of file\\n self.file_object.seek(0)\\n self.file_object.truncate()\\n\\n # Write new CSV data\\n writer = UnicodeWriter(self.file_object, encoding=self.output_encoding)\\n writer.writerows(rows)\\n\\n if close:\\n self.file_object.close()\",\n \"def write_to_file(self, file):\\n f = open(file, \\\"w+\\\")\\n for row in self.value:\\n line = \\\" \\\".join(str(el) for el in row) + \\\"\\\\n\\\"\\n f.write(line)\\n\\n f.close()\",\n \"def save_csv(filename, rows):\\n with open(filename, 'w', newline='', encoding='utf-8') as f:\\n writer = csv.writer(f)\\n writer.writerow([\\n 'title', 'runtime', 'genre(s)', 'director(s)', 'writer(s)',\\n 'actor(s)', 'rating(s)', 'number of rating(s)'\\n ])\\n\\n writer.writerows(rows)\",\n \"def _write_shard(filename, dataset, indices):\\n with tf.python_io.TFRecordWriter(filename) as writer:\\n for j in indices:\\n writer.write(dataset[j])\",\n \"def write_csv(path, lines, headers):\\n print \\\"Opening %s for score output\\\" % base_name(path)\\n\\n try:\\n f = open(path, 'wb')\\n writer = csv.writer(f)\\n writer.writerow(headers)\\n writer.writerows(lines)\\n except IOError:\\n print \\\"Cannot open %s\\\" % path\\n else:\\n print \\\"Scores successfully written to %s\\\" % path\\n f.close()\",\n \"def __do_write(filestream, seq, header=None):\\n if header is not None:\\n filestream.write(header + '\\\\n') # double check newlines\\n try:\\n for line in chunks(seq, 70):\\n filestream.write(line + '\\\\n')\\n except Exception as e:\\n print(e)\",\n \"def _write_shard(filename, dataset, indices):\\n with tf.io.TFRecordWriter(filename) as writer:\\n for j in indices:\\n writer.write(dataset[j])\",\n \"def write_archive_row(self, row: ArchiveRow):\\n raise NotImplementedError() # pragma: no cover\",\n \"def _file_writer(self, lines, filename):\\n if self.MockRun:\\n return\\n\\n if self.Verbose:\\n print \\\"Writing file %s\\\" % filename\\n\\n updated_file = open(filename, 'w')\\n updated_file.write(''.join(lines))\\n updated_file.close()\",\n \"def writeToCon(self, line):\\r\\n if not self.connected:\\r\\n raise UserError(errors['NotConnectedYet'])\\r\\n else:\\r\\n self.con.write(self.normalise(line) + '\\\\n')\",\n \"def writefile(file, fvs, sequence, cvs = None):\\r\\n if cvs is not None: assert fvs.shape[0] == cvs.shape[0]\\r\\n for thread in sequence:\\r\\n for i in thread:\\r\\n if cvs is not None:\\r\\n one_line = CRFFileWriter.instance(fvs[i], cvs[i])\\r\\n else:\\r\\n one_line = CRFFileWriter.instance(fvs[i])\\r\\n file.write(one_line)\\r\\n file.write('\\\\n')\",\n \"def _close_writable(self):\\n for future in as_completed(self._write_futures):\\n future.result()\",\n \"async def writelines(self, lines):\\n # first check if the file is binary or not\\n if 'b' in self._mode:\\n raise APIException(\\n \\\"writelines on a binary file is not permitted: {}\\\".format(\\n self._uri)\\n )\\n # write all but the last line with a line break\\n for l in lines:\\n await self.write((l+\\\"\\\\n\\\").encode('utf-8'))\\n return True\",\n \"def to_csv_file_obj(self, rows):\\n output = StringIO.StringIO()\\n writer = csv.writer(output)\\n writer.writerows(rows)\\n return output\",\n \"def write_csv(self, filename, cutoff=2):\\n f = csv.writer(open(filename, 'wb'))\\n for row in self.rows(cutoff=cutoff):\\n f.writerow(row)\",\n \"def writerow(self, outdict):\\r\\n row = []\\r\\n for field in FatWriter.FIELDS:\\r\\n col = outdict.get(field, '')\\r\\n col = col.replace('\\\\t', ' ')\\r\\n col = col.replace('\\\\n', '\\\\\\\\n')\\r\\n row.append(col)\\r\\n self.outfile.write('\\\\t'.join(row) + '\\\\n')\",\n \"def xlsx_write_rows(filename, rows):\\n workbook = xlsxwriter.Workbook(filename)\\n worksheet = workbook.add_worksheet()\\n # Write values\\n nrows = 0\\n for i, row in enumerate(rows):\\n for j, val in enumerate(row):\\n worksheet.write(i, j, val)\\n nrows += 1\\n # Cleanup\\n workbook.close()\\n return nrows\",\n \"def writerows(self, row):\\n if not self.resolved:\\n self._resolve_writer()\\n\\n if isinstance(self.resolved, ReaderType):\\n raise AttributeError('Object CSV has no attribute writerows')\\n self._resolve_writer()\\n self.resolved.writerows(row)\",\n \"def writerow(self, data):\\n self.get_csv_writer().writerow(data)\",\n \"def _write_stream(self):\\n enrich_df = self._process_stream()\\n df_writer = enrich_df \\\\\\n .writeStream \\\\\\n .queryName(\\\"Agro Data Writer\\\") \\\\\\n .foreachBatch(db_utils.foreach_batch_function) \\\\\\n .option(\\\"checkpointLocation\\\", \\\"chk-point-dir\\\") \\\\\\n .trigger(processingTime=\\\"1 minute\\\") \\\\\\n .start()\\n\\n df_writer.awaitTermination()\",\n \"def write(self, path):\\n # if file doesn't already exist, write column names in a header\\n if not os.path.exists(path):\\n with open(path, 'a+') as f:\\n f.write('# {}# time,status,dphi,umolar,mbar,airSat,tempSample,tempCase,signalIntensity,ambientLight,pressure,humidity,resistorTemp,percentO2\\\\n'.format(self.label))\\n # generate out_str\\n if isinstance(self.last_read[0], list):\\n out_str = ''\\n for r in self.last_read:\\n out_str += fmt(r, 1, ',') + '\\\\n'\\n else:\\n out_str = fmt(self.last_read, 1, ',') + '\\\\n'\\n # write and save data\\n self.write_str = out_str\\n with open(path, 'a+') as f:\\n f.write(out_str)\\n return\",\n \"def write_to(self, fname, **kwargs):\\n data = self.to_Table()\\n data.write(fname, **kwargs)\",\n \"def __multi_append_row(self, data, path):\\n #Write the row to the data page file ('a' positions the stream at the end of the file).\\n temp_current_row = self.current_row\\n with open(path, 'a') as f:\\n f.write(data)\\n #if self.__check_write_success_insert(new_data, path):\\n # return True\\n #else:\\n # print('Data was corrupted at row: ' + temp_current_row)\\n # return False\\n return True\",\n \"def writerow(self, row):\\n if not self.resolved:\\n self._resolve_writer()\\n\\n if isinstance(self.resolved, ReaderType):\\n raise AttributeError('Object CSV has no attribute writerow')\\n\\n self.resolved.writerow(row)\",\n \"def write(self, stream, root, order):\\n need_newline = False\\n for row in root:\\n if need_newline:\\n stream.write('\\\\n')\\n need_newline = True\\n if isinstance(row, list):\\n stream.write('\\\\n'.join(row) + '\\\\n')\\n else:\\n for column in order:\\n stream.write(row[column] + '\\\\n')\",\n \"def _write(fdesc, data):\\n while data:\\n count = os.write(fdesc, data)\\n data = data[count:]\",\n \"def flush(self):\\n self._write()\",\n \"def log_readouts(self, rs):\\n for r in rs: self.log_readout(*r)\\n if len(rs): self.writeconn.commit()\",\n \"def write_csv(self, file):\\n # Write header row\\n file.write('Timestamp,MessageType,Queue,Price,Volume,OrderID\\\\n')\\n # Write content\\n for x in self.records:\\n row = (str(x[0]) + ',' + x[1][\\\"MessageType\\\"] + ',' +\\n x[1][\\\"Queue\\\"] + ',' + str(x[1][\\\"Price\\\"]) + ',' +\\n str(x[1][\\\"Volume\\\"]) + ',' + str(x[1][\\\"OrderID\\\"]) + '\\\\n')\\n file.write(row)\",\n \"def write_record(self, *items):\\n items = tuple(np.asarray(item) for item in items)\\n total_size = sum(item.nbytes for item in items)\\n\\n nb = np.array([total_size], dtype=self._header_dtype)\\n\\n nb.tofile(self._fp)\\n for item in items:\\n item.tofile(self._fp)\\n nb.tofile(self._fp)\",\n \"def write(l, path, columns):\\n \\n file = open(path, 'w', newline = '', encoding = 'utf-8')\\n writer = csv.writer(file, delimiter = '\\\\t', quotechar = '', quoting = csv.QUOTE_NONE)\\n row = []\\n for col in columns:\\n row.append(col)\\n writer.writerow(row)\\n for entry in l:\\n row = []\\n for col in columns:\\n row.append(entry[col])\\n writer.writerow(row)\\n file.close()\",\n \"def write_csv(outputfile, delimiter, newline, qchar, encoding, header, rows):\\n with open(outputfile, 'w', newline=newline, encoding=encoding) as csvfile:\\n writer = csv.writer(csvfile, delimiter=delimiter,\\n quotechar=qchar, quoting=csv.QUOTE_MINIMAL)\\n writer.writerow(header)\\n for row in rows:\\n writer.writerow(row)\",\n \"def write_lines(list_of_lines, file):\\r\\n for i in range(0, len(list_of_lines)):\\r\\n file.write(list_of_lines[i] + b\\\"\\\\n\\\")\",\n \"def write_csv_file(filepath, fieldnames, rows):\\n headers = [{'label': field} for field in fieldnames]\\n with open(filepath, 'w') as f_buf:\\n outfile = CsvWriter()\\n outfile.set_headers(headers)\\n outfile._datas = rows\\n outfile.render(f_buf)\",\n \"def save_entries(self):\\n with open(self.file_name, \\\"w\\\") as file:\\n file.write('date,name,minutes,note\\\\n')\\n for entry in self.entries:\\n writer = csv.writer(file)\\n writer.writerow([entry.date, entry.name, entry.minutes, entry.note])\",\n \"def index_rows(self, corpus, source, *rows):\\n # Pickle database rows.\\n self._pickle_rows(corpus, source, rows)\\n\\n # Write text content.\\n for row in rows:\\n if getattr(row, '_text', None):\\n self._write_text(row)\\n self._write_tokens(row)\",\n \"def _batch_write(self):\\n if self.to_put:\\n db.put(self.to_put)\\n self.to_put = []\\n if self.to_delete:\\n db.delete(self.to_delete)\\n self.to_delete = []\",\n \"def write(self):\\n pass\",\n \"def write(self):\\n pass\",\n \"def send_to_kafka(rows):\\n producer = connect_kafka_producer()\\n for row in rows:\\n print(row.asDict())\\n producer.send(TOPIC_NAME, value=row.asDict())\\n producer.flush()\",\n \"def _write(self, data):\\n self._writer.write(data)\",\n \"def write(self, fh):\\n # Skip over the file header for now, we'll fill it out later\\n fh.seek(self.IDX_TABLE_ADDR, 0)\\n\\n idx_table_entry_count = len(self.entries)\\n\\n # Generate and write the index table\\n for idx, res in enumerate(self.entries):\\n typ, num1, num2, num3, num4 = b\\\"\\\\0\\\\0\\\\0\\\\0\\\", 0x0, 0x0, 0x0, 0x8\\n if res is not None:\\n typ, num1, num2, num3, num4 = res.get_header()\\n fh.write(struct.pack(\\\"=4s4x2I2xBB\\\", typ, num1, num2, num3, num4))\\n\\n off_table_offset = fh.tell() - self.IDX_TABLE_ADDR\\n off_table_entry_count = len([i for i in self.entries if i is not None])\\n # ???: An unknown pointer into the middle of the index table. Modifying it causes the game to crash on boot. The value is exactly 0x800 bytes (1 BLOCK_SIZE) less than the start of the offset table.\\n unk = 0x1C4B4\\n\\n fh.write(struct.pack(\\\"=4x2I\\\", off_table_entry_count, unk))\\n\\n next_empty_addr = self.NEXT_BLOCK_ADDR(\\n fh.tell() + struct.calcsize(\\\"=2I\\\") * off_table_entry_count\\n )\\n data_start_block = self.ADDR_NUM_BLOCK(next_empty_addr)\\n\\n # Generate and write the offset table & its targets\\n\\n for idx, res in enumerate(self.entries):\\n if res is None:\\n continue\\n fh.write(struct.pack(\\\"=2I\\\", idx, self.ADDR_NUM_BLOCK(next_empty_addr)))\\n off = fh.tell()\\n\\n # Write resource\\n fh.seek(next_empty_addr, 0)\\n res.fw.seek(0x0)\\n fh.write(res.fw.read())\\n next_empty_addr = self.NEXT_BLOCK_ADDR(fh.tell())\\n\\n # Pad to next block\\n fh.write(b\\\"\\\\0\\\" * (next_empty_addr - fh.tell()))\\n\\n fh.seek(off)\\n\\n # Write the file header\\n # ???: All these constants are unknown\\n fh.seek(0x0, 0)\\n fh.write(\\n struct.pack(\\n \\\"=10I\\\",\\n 0xA,\\n data_start_block,\\n 0x1,\\n 0x0,\\n idx_table_entry_count,\\n off_table_offset,\\n 0x1,\\n 0x0,\\n 0x0,\\n 0x276F4, # ???: Doesn't affect game boot\\n )\\n )\",\n \"def _writeRecord(self, path, name, data):\\n file_path = os.path.join(path, name)\\n with open(file_path, 'w') as f:\\n for item in data:\\n f.write(str(item)+'\\\\t')\\n f.write('\\\\n')\",\n \"def write_data():\",\n \"def write(self):\\n\\t\\traise NotImplementedError('%s: No write function implemented!' % self.name)\",\n \"def write(self, content):\\n for f in self.files:\\n f.write(content)\\n f.flush() # Want this content is displayed immediately on file\",\n \"def write_to_sheet(self):\\n for i, row in enumerate(self.ws[self.range_name]):\\n if isinstance(self.data[i], tuple):\\n self.data[i] = list(self.data[i])\\n for j, cell in enumerate(row):\\n cell.value = self.data[i][j]\",\n \"def _export_disp_rowset(self, name: str, membr: str, f: IO[str], ind: str, size: int) -> None:\\n assert self._disp_verts is not None\\n f.write(f'{ind}\\\\t\\\\t{name}\\\\n{ind}\\\\t\\\\t{{\\\\n')\\n rows = [\\n str(getattr(vert, membr))\\n for vert in self._disp_verts\\n ]\\n for y in range(size):\\n f.write(f'{ind}\\\\t\\\\t\\\"row{y}\\\" \\\"{\\\" \\\".join(rows[size * y:size * (y+1)])}\\\"\\\\n')\\n f.write(f'{ind}\\\\t\\\\t}}\\\\n')\",\n \"def Write(self):\\n table_data = self._TABLE.build(self._offsets)\\n self._zip_file.writestr(self._stream_name, table_data)\",\n \"def write(self, args):\\n\\t\\tnewcsvfile = self.filename[:len(self.filename)-4] + \\\"NEW.csv\\\" #clever naming MIGHT NEED TO CHANGE THIS LATER/OVERWRITE OLD FILE?\\n\\t\\twith open(newcsvfile, 'wb') as f:\\n\\t\\t\\twriter = csv.writer(f)\\n\\t\\t\\twriter.writerows(self.all_likes)\",\n \"def write(self):\\n raise NotImplementedError\",\n \"def write(self):\",\n \"def write(self):\",\n \"def Write(self):\\n table_data = self._TABLE.build(self._timestamps)\\n self._zip_file.writestr(self._stream_name, table_data)\",\n \"def row(self, rdata):\\n self = self\\n file = open(\\\"imdb_output.txt\\\", \\\"a\\\")\\n file.write(str(\\\"\\\\t\\\".join(rdata)) + \\\"\\\\n\\\")\",\n \"def write(self, data: np.ndarray) -> None:\\n assert data.ndim == 1\\n all_data = np.hstack((self.res, data))\\n nrows = len(all_data) // self.width\\n if nrows > 0:\\n d = all_data[0: nrows * self.width].reshape(nrows, self.width)\\n w = Window(0, self.rows_written, d.shape[1], d.shape[0])\\n self.f.write(d, 1, window=w)\\n self.rows_written += nrows\\n self.res = all_data[nrows * self.width:]\\n else:\\n self.res = all_data\",\n \"def write(self, recs, out_handle):\\n self._write_header(out_handle)\\n for rec in recs:\\n self._write_annotations(rec.annotations, rec.id, out_handle)\\n for sf in rec.features:\\n self._write_feature(sf, rec.id, out_handle)\",\n \"def write_all(self):\\r\\n pass\",\n \"def append_rows(self, rows):\\n for row in rows:\\n self.append_row(row)\",\n \"def _write(self, line):\\n data = (line + TERMINATOR).encode()\\n self._transport.write(data)\\n log.debug(f'{self} >> {line!r}')\",\n \"def write(self, fname):\\n pass\",\n \"def _write_to_file(self):\\n with open(self.filename + \\\".ir\\\", \\\"w+\\\") as file:\\n file.writelines(\\n [\\\"\\\\n\\\" + l if p != 0 else l for p, l in enumerate(self.lines)]\\n )\",\n \"def write_to_csv(self, data):\\n with open(\\\"out.csv\\\", \\\"w\\\", newline=\\\"\\\") as f:\\n writer = csv.writer(f)\\n writer.writerow(self.column_names)\\n writer.writerows(data)\\n print(\\\" Updated succesfully \\\")\",\n \"def write(self, out):\",\n \"def write_to_csv(list_of_rows, file_name):\\n with open(file_name, 'w') as f:\\n writer = csv.writer(f)\\n for row in list_of_rows:\\n if None in row:\\n continue\\n writer.writerow(row)\\n \\n f.close()\",\n \"def write(data):\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.65288514","0.64927477","0.63778","0.63315696","0.63270783","0.6293423","0.6291826","0.62790984","0.6272529","0.6243658","0.62395215","0.6211141","0.61144894","0.6026084","0.60218585","0.59980494","0.5994269","0.5977457","0.5938158","0.5935091","0.59253085","0.58952105","0.5842943","0.5805881","0.58012694","0.5720609","0.57115096","0.56935287","0.56935287","0.5681466","0.568035","0.566977","0.5639393","0.5618521","0.56130594","0.55974936","0.55697477","0.55691904","0.55546004","0.5545012","0.5544475","0.5535364","0.5504963","0.55032516","0.54654","0.5465205","0.54613465","0.5457447","0.54548275","0.5451015","0.5434238","0.54266626","0.5395559","0.5392253","0.53886604","0.5387442","0.5378677","0.5371706","0.5353693","0.53358793","0.53168917","0.53160006","0.531489","0.5312576","0.5292518","0.5291451","0.52848756","0.5273954","0.52738976","0.52735513","0.5270939","0.5267135","0.5267135","0.52497816","0.5247101","0.5237295","0.5235206","0.52321106","0.5228665","0.5227004","0.52228975","0.52213144","0.52145904","0.521093","0.5210831","0.5206217","0.5206217","0.52055657","0.52055633","0.520357","0.520006","0.51950824","0.5181281","0.517789","0.51765126","0.5173713","0.51629084","0.5154249","0.51487297","0.5148697"],"string":"[\n \"0.65288514\",\n \"0.64927477\",\n \"0.63778\",\n \"0.63315696\",\n \"0.63270783\",\n \"0.6293423\",\n \"0.6291826\",\n \"0.62790984\",\n \"0.6272529\",\n \"0.6243658\",\n \"0.62395215\",\n \"0.6211141\",\n \"0.61144894\",\n \"0.6026084\",\n \"0.60218585\",\n \"0.59980494\",\n \"0.5994269\",\n \"0.5977457\",\n \"0.5938158\",\n \"0.5935091\",\n \"0.59253085\",\n \"0.58952105\",\n \"0.5842943\",\n \"0.5805881\",\n \"0.58012694\",\n \"0.5720609\",\n \"0.57115096\",\n \"0.56935287\",\n \"0.56935287\",\n \"0.5681466\",\n \"0.568035\",\n \"0.566977\",\n \"0.5639393\",\n \"0.5618521\",\n \"0.56130594\",\n \"0.55974936\",\n \"0.55697477\",\n \"0.55691904\",\n \"0.55546004\",\n \"0.5545012\",\n \"0.5544475\",\n \"0.5535364\",\n \"0.5504963\",\n \"0.55032516\",\n \"0.54654\",\n \"0.5465205\",\n \"0.54613465\",\n \"0.5457447\",\n \"0.54548275\",\n \"0.5451015\",\n \"0.5434238\",\n \"0.54266626\",\n \"0.5395559\",\n \"0.5392253\",\n \"0.53886604\",\n \"0.5387442\",\n \"0.5378677\",\n \"0.5371706\",\n \"0.5353693\",\n \"0.53358793\",\n \"0.53168917\",\n \"0.53160006\",\n \"0.531489\",\n \"0.5312576\",\n \"0.5292518\",\n \"0.5291451\",\n \"0.52848756\",\n \"0.5273954\",\n \"0.52738976\",\n \"0.52735513\",\n \"0.5270939\",\n \"0.5267135\",\n \"0.5267135\",\n \"0.52497816\",\n \"0.5247101\",\n \"0.5237295\",\n \"0.5235206\",\n \"0.52321106\",\n \"0.5228665\",\n \"0.5227004\",\n \"0.52228975\",\n \"0.52213144\",\n \"0.52145904\",\n \"0.521093\",\n \"0.5210831\",\n \"0.5206217\",\n \"0.5206217\",\n \"0.52055657\",\n \"0.52055633\",\n \"0.520357\",\n \"0.520006\",\n \"0.51950824\",\n \"0.5181281\",\n \"0.517789\",\n \"0.51765126\",\n \"0.5173713\",\n \"0.51629084\",\n \"0.5154249\",\n \"0.51487297\",\n \"0.5148697\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5914556"},"document_rank":{"kind":"string","value":"21"}}},{"rowIdx":81769,"cells":{"query":{"kind":"string","value":"Add schema rows to the output."},"document":{"kind":"string","value":"def do_export_schema(self):\n export_schema = self.get_arg_value(\"export_schema\")\n\n if export_schema:\n row = {\"schemas\": self.final_schemas}\n self.write_rows(rows=row)\n del row"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def add_rows(self):\n for row in self.rows:\n self.table.add_row(row)","def append_row(self):\r\n values = []\r\n vals_to_insert = ''\r\n\r\n for key in Output.COLUMNS:\r\n values.append(str(self[key]))\r\n\r\n # Replace any Quotes in parsed record with double quotes\r\n for i in values:\r\n vals_to_insert += i.replace('\"', '\"\"') + '\",\"'\r\n\r\n vals_to_insert = '\"' + vals_to_insert[:-3] + '\"'\r\n insert_sqlite_db(vals_to_insert)","def append_rows(self, rows):\n for row in rows:\n self.append_row(row)","def write (self, path):\n\t\ts=[]; add=s.append\n\t\tadd ('\\t'.join (self.schema))\n\t\tfor record in self.data:\n\t\t\tadd (record.asTabDelimitedRecord())\n\t\t\n\t\t# f = open (path, 'w')\n\t\tf = codecs.open(path, 'w', 'utf-8')\n\t\tf.write (self.linesep.join (s))\n\t\tf.close()\n\t\tprint (\"data written to \" + path)","def _add_rows(self, writer_name, list_of_dictionaries):\n assert(isinstance(list_of_dictionaries, list))\n self._writers[writer_name].writerows(list_of_dictionaries)","def create_schema(self, schema, *, debug=False):\n c = self.conn.cursor()\n for line in schema.split(\";\"):\n line = line.strip()\n if len(line)>0:\n if self.debug or debug:\n print(f\"{line};\", file=sys.stderr)\n try:\n c.execute(line)\n except (sqlite3.Error, pymysql.MySQLError) as e:\n print(\"SQL:\", line, file=sys.stderr)\n print(\"Error:\", e, file=sys.stderr)\n exit(1)","def _add_row(self, w2):\n done = []\n row = {}\n while len(done) != len(self.columns):\n for col in self.columns:\n if col in done:\n continue\n\n ok = self._add_item(w2, col, row)\n if ok:\n done.append(col)\n\n self.rows.append(row)","def newrow(self):\n maxlen = 0\n for colbuf in self.colbufs:\n maxlen = max(maxlen, len(colbuf))\n\n for i in range(maxlen):\n first = True\n for colbuf in self.colbufs:\n if first:\n first = False\n else:\n sys.stdout.write(self.sepstr)\n if i < len(colbuf):\n sys.stdout.write(colbuf[i])\n else:\n sys.stdout.write(\" \"*self.colwidth)\n sys.stdout.write(\"\\n\")\n\n self.colbufs = []\n for i in range(self.ncolumns):\n self.colbufs.append([])","def append_row(self, row_dict):\n \n for k,v in row_dict.items():\n \n if(k not in self.table):\n # Heading does not exist yet. Fill in blanks for past items\n self.table[k] = [\"\"] * self.rowcount\n \n # clean up value\n v = v.strip()\n # try converting string to a number\n try:\n v = ast.literal_eval(v)\n except:\n pass\n \n self.table[k].append(v)\n \n self.rowcount = self.rowcount + 1\n \n # Even out any columns in DB that were not filled\n for hdr in self.table:\n if(len(self.table[hdr]) < self.rowcount):\n self.table[hdr].append(None)","def add_rows(self, rows) :\n\n converted = [self._convert_row(row) for row in rows]\n self._bulk_add_rows(converted)\n self.version += 1","def _populate_output(self):\n self._store_atomic_queries_table()\n self._store_composite_queries_table()","def __init__(self, schema_row):\n self.schema = []\n for field in schema_row['fields']:\n self.schema.append(field['type'])","def _create_schema(self):\n self._conn.executescript(self._db_schema)","def merge_schema(self, schema):\n for _, attr_schema in schema.iter_attributes():\n self.merge_attribute_schema(attr_schema)","def generate_table(self, rows):\n ...","def print_dataset_schema(outputs, name, columns):\n outputs.stdout.append(TextOutput(name + ' ('))\n for i in range(len(columns)):\n text = ' ' + str(columns[i])\n if i != len(columns) - 1:\n text += ','\n outputs.stdout.append(TextOutput(text))\n outputs.stdout.append(TextOutput(')'))","def _write_rows(self):\n try:\n xf = self._writer.xf.send(True)\n except StopIteration:\n self._already_saved()\n\n with xf.element(\"sheetData\"):\n row_idx = 1\n try:\n while True:\n row = (yield)\n row = self._values_to_row(row, row_idx)\n self._writer.write_row(xf, row, row_idx)\n row_idx += 1\n except GeneratorExit:\n pass\n\n self._writer.xf.send(None)","def _schema_write(self, table: TableSchema) -> None:\n with open(self.schemas / (table['name'] + '.json'), 'w') as f:\n json.dump(table, f, indent=True)","def _prepare_schema(self):\n schema = DaskSchema(self.schema_name)\n\n if not self.tables:\n logger.warning(\"No tables are registered.\")\n\n for name, dc in self.tables.items():\n table = DaskTable(name)\n df = dc.df\n logger.debug(\n f\"Adding table '{name}' to schema with columns: {list(df.columns)}\"\n )\n for column in df.columns:\n data_type = df[column].dtype\n sql_data_type = python_to_sql_type(data_type)\n\n table.addColumn(column, sql_data_type)\n\n schema.addTable(table)\n\n if not self.functions:\n logger.debug(\"No custom functions defined.\")\n\n for function_description in self.function_list:\n name = function_description.name\n sql_return_type = python_to_sql_type(function_description.return_type)\n if function_description.aggregation:\n logger.debug(f\"Adding function '{name}' to schema as aggregation.\")\n dask_function = DaskAggregateFunction(name, sql_return_type)\n else:\n logger.debug(f\"Adding function '{name}' to schema as scalar function.\")\n dask_function = DaskScalarFunction(name, sql_return_type)\n\n dask_function = self._add_parameters_from_description(\n function_description, dask_function\n )\n\n schema.addFunction(dask_function)\n\n return schema","def add_duplicate_schema(csv: pd.DataFrame, state: Random, verbose:bool) -> pd.DataFrame:\n schema_number = state.randint(0, max(1, len(csv)//2))\n for _ in tqdm(range(schema_number), desc=\"Adding duplicated schemas\", disable=not verbose):\n csv = add_row(csv, csv.columns, state=state)\n return csv","def add_all_lines(conn, table_values):\n\n column_list = table_values[0]\n column_row = \",\".join(column_list)\n qmark = \"?\"\n col_count = len(column_list)\n for cols in range(1, col_count):\n qmark += \", ?\"\n cols = cols\n\n cur = conn.cursor()\n cur.execute(\"DROP TABLE IF EXISTS ayasdi_table;\")\n cur.execute(\"CREATE TABLE ayasdi_table (\" + column_row + \");\")\n cur.executemany(\\\n \"INSERT INTO ayasdi_table (\" + column_row + \") VALUES (\" + qmark + \");\", \\\n table_values)","def add_row(self, shape, attributes=[]):\n if isinstance(shape, shapefile.shapefile._Shape):\n self.shapes.append(shape)\n self.__shapeHolder._shapes.append(shape)\n else:\n if self.shapeType in (1, 8, 11, 21, 25, 31):\n self.__shapeHolder.point(*shape)\n elif self.shapeType in (3, 13, 23):\n addShp = self.__shapeHolder.line(shape)\n else:\n self.__shapeHolder.poly(shape)\n\n self.shapes.append(self.__shapeHolder.shapes()[-1])\n self.records.append(self.addDefaults(attributes))\n self.__isBuilt = False","def schema(self):\n pass","def add_row(self, row):\n ...","def add_row(self, shape, attributes):\n if isinstance(shape, shapefile.shapefile._Shape):\n self.w._shapes.append(shape)\n else:\n if self.shapeType in (1, 8, 11, 21, 25, 31):\n self.w.point(*shape)\n elif self.shapeType in (3, 13, 23):\n self.w.line(shape)\n else:\n self.w.poly(shape)\n self.w.record(*attributes)","def _generate_rows(self):\n logger.debug(\"Generating pre-genealogical coherence data for %s\", self.w1)\n if not self.rows:\n for w2 in self.all_mss:\n if self.w1 == w2:\n continue\n self._add_row(w2)\n\n self._sort()\n logger.debug(\"Generated pre-genealogical coherence data for %s\", self.w1)","def write_row(self, shape, attributes=[]):\n if isinstance(shape, shapefile.shapefile._Shape):\n self.w._shapes.append(shape)\n else:\n if self.w.shapeType in (1, 8, 11, 21, 25, 31):\n self.w.w.point(*shape)\n elif self.w.shapeType in (3, 13, 23):\n self.w.line(shape)\n else:\n self.w.poly(shape)\n self.w.record(*self.addDefaults(attributes))","def _add_table_schema(table_desc, table_name, schema):\n table_desc['TableName'] = table_name\n table_desc['AttributeDefinitions'] = [{\n 'AttributeName': item['name'],\n 'AttributeType': DynamoStubber._encode_type(item['type'])\n } for item in schema]\n table_desc['KeySchema'] = [{\n 'AttributeName': item['name'],\n 'KeyType': item['key_type']\n } for item in schema]","def schema(self):","def add_row(self, row):\n \n new_row = pd.DataFrame(data=[row], columns = self.table.columns) \n self.table = self.table.append(new_row, ignore_index=True)","def build_schema(self):\n field_defs = []\n fields = []\n point_rows = []\n line_rows = []\n polygon_rows = []\n for i in self.json_in['features']: # first iterate through it all and get all the fields\n props = i.get('properties')\n\n for k, v in props.items():\n if k not in fields:\n fields.append(k)\n\n for i in self.json_in['features']: # now fill in any props that any features are missing, and sort them all\n geom = i['geometry']\n props = i['properties']\n for f in fields:\n if f not in props.keys():\n props[f] = ''\n props = OrderedDict(sorted(props.items()))\n\n for k, v in props.items():\n schema_row = [k, \"TEXT\", k.replace('_', ' '), 256]\n if schema_row not in field_defs:\n field_defs.append(schema_row)\n row = [str(v) for k, v in sorted(props.items())] # coerce everything to str cause this stuff is a mess\n parsed_geom = GeoJSONUtils.parse_geometry(geom)\n geotype = parsed_geom['type']\n egeom = parsed_geom['esri_geom']\n\n if geotype == \"POINT\":\n row.insert(0, egeom)\n print(row)\n point_rows.append(row)\n elif geotype == \"POLYLINE\":\n row.insert(0, egeom)\n print(row)\n line_rows.append(row)\n else:\n row.insert(0, egeom)\n print(row)\n polygon_rows.append(row)\n\n return {\n \"fields\": fields,\n \"field_defs\": field_defs,\n \"rows\": [point_rows, line_rows, polygon_rows]\n }","def add_schema(self, schema, db):\n self._dbs[schema.typename] = db\n return None","def appendRow(self, contents = None):\n\n\t\t\t\t#Find the last row\n\t\t\t\trow = len(tuple(self.thing.iter_rows())) + 1\n\n\t\t\t\t#Write to cells\n\t\t\t\tif ((contents != None) and (len(contents) != 0)):\n\t\t\t\t\tfor column, item in enumerate(contents):\n\t\t\t\t\t\tself.setCell(row, column + 1, item)\n\t\t\t\telse:\n\t\t\t\t\tself.setCell(row, 1, \" \")","def add_row(self, *column_data):\n if not self.col_widths:\n self.col_widths = [len(data) for data in column_data]\n row = \"| \"\n row += \" | \".join(f\"{data:{w}}\"\n for (data, w) in zip(column_data, self.col_widths))\n row += \" |\\n\"\n self.result += row","def _store_rows(self):\n\n for value in self.values:\n self.counters.append(value['counter'])\n self.timestamps.append(value['timestamp'])\n self.acceleration.append(value['acceleration'])","def WriteBody( self ):\n\n self.ParseHeader( sys.stdin.readline() )\n\n self.CreateTable()\n\n num_lines = 0\n\n total_lines = 0\n sys.stderr.write(\"parsing..\")\n \n while 1:\n line = sys.stdin.readline()\n \n if not line: break\n if line[0] == \"#\": continue\n if line[0:2] == \"//\": break\n \n if not (total_lines % 100) and total_lines > 0:\n sys.stderr.write( \".%i..\" % total_lines)\n print self.table \n self.table.body = []\n\n total_lines = total_lines + 1\n\n (columns) = string.split( line[:-1], \"\\t\" )\n \n if not columns:\n break\n\n if self.mUseIndex:\n col_string = [str(total_lines),] + self.ParseColumns( columns )\n else:\n col_string = self.ParseColumns( columns )\n \n self.table.body.append( col_string ) \n \n print self.table\n \n sys.stderr.write(\"done\\n\")","def schema(self):\n raise NotImplementedError","def append(self,output):\n\n if self.log_init is False or self.reprint_header:\n # Insert our new headers in reverse order\n line = self.separator.join(output['HEADER'])\n self.outfd.write(line)\n self.log_init = True\n self.outfd.write(\"\\n\")\n \n for row in output['DATA']:\n \n # Convert everything to a string\n row = [str(i) for i in row]\n line = self.separator.join(row)\n self.outfd.write(line)\n self.outfd.write(\"\\n\")\n \n self.outfd.flush()","def start_table(self):\n self.col_widths = []\n self.result = \"\"","def __append_rows_to_partition(self,partition_dt,rows):\n\n ts_data = self.__fetch_or_create_partition_table(partition_dt)\n ts_data.append(rows)","def _rebuild(self):\n for shape, record in iter(self):\n self.write_row(shape, record)\n self.__isBuilt = True","def formatSchema(self):\n schema = json.loads(self.schemaSource)\n stack = [schema]\n # Strip out all the docs\n while len(stack) > 0:\n elm = stack.pop()\n if \"doc\" in elm:\n elm[\"doc\"] = \"\"\n for value in elm.values():\n if isinstance(value, dict):\n stack.append(value)\n elif isinstance(value, list):\n for dic in value:\n if isinstance(dic, dict):\n stack.append(dic)\n jsonData = json.dumps(schema)\n output = \"\\n\".join(textwrap.wrap(jsonData)) + \"\\n\"\n return output","def initialize_schema(self, dry_run=False):\n if not dry_run:\n self.flush()","def write_rows(self, rows: Union[List[dict], dict]):\n rows = listify(rows)\n flat = self.get_arg_value(\"json_flat\")\n\n indent = None if flat else 2\n prefix = \" \" * indent if indent else \"\"\n\n for row in rows:\n if self._first_row:\n pre = \"\" if flat else \"\\n\"\n else:\n pre = \"\\n\" if flat else \",\\n\"\n\n self._first_row = False\n self._fd.write(pre)\n\n value = json.dumps(row, indent=indent)\n value = textwrap.indent(value, prefix=prefix) if indent else value\n self._fd.write(value)\n del value, row","def insert_rows(rows: Iterable[Row],\n name: str,\n fields: List[Tuple[str, str]],\n ws: str = \"memory\",\n spatial_reference: int = 3857,\n shape_type: str = \"POLYGON\",\n shape_format: str = \"WKB\") -> None:\n cols = [f\"Shape@{shape_format}\"]\n with _insert_cursor(cols, name, fields, ws, spatial_reference, shape_type) as cursor:\n for row in rows:\n cursor.insertRow(row)","def write(self, row):\n self.append_rows.append(tuple(row))","def handle_output(all_rows, opts):\n for dev, rows in all_rows.iteritems():\n\n if opts.csv:\n writer = csv.writer(sys.stdout)\n for row in rows:\n writer.writerow([dev] + row)\n elif opts.dotty:\n continue\n elif opts.sqldb:\n write_sqldb(opts.sqldb, dev, rows)\n else:\n print 'DEVICE: {}'.format(dev)\n print_table(rows)","def showSchema (self):\n\t\ts=[];add=s.append\n\t\tfor i in range(len(self.schema)):\n\t\t\tadd (\"%d. %s\" % (i+1, self.schema[i]))\n\t\treturn join (s, '\\n')","def add_row(self, values):\n if len(values) != len(self.column_names):\n raise ValueError(\n 'Number of values does not match number of columns'\n )\n\n self.rows.append(values)","def add_row(self, *column_data):\n row = \"<tr>\"\n row += \" \".join(f\"<td>{header}</td>\" for header in column_data)\n row += \"</tr>\\n\"\n self.result += row","def schema(self):\n attrs = self.attrs.copy()\n parts = ['CREATE', 'TABLE', self.name, '(%s,' % self.hash_key.schema]\n del attrs[self.hash_key.name]\n if self.range_key:\n parts.append(self.range_key.schema + ',')\n del attrs[self.range_key.name]\n if attrs:\n attr_def = ', '.join([attr.schema for attr in six.itervalues(attrs)])\n parts.append(attr_def + ',')\n\n parts.append(\"THROUGHPUT (%d, %d))\" % (self.read_throughput,\n self.write_throughput))\n parts.extend([g.schema for g in six.itervalues(self.global_indexes)])\n return ' '.join(parts) + ';'","def add_row(self, row):\r\n self.rows.append(row)","def describe(self):\n print('Schema Changes\\n==============')\n self.schema().describe()\n print('\\nData Changes\\n============')\n self.rows().describe()","def __format_results__(self, result_rows):\n for row in result_rows:\n self.return_dict['results']['items'].append(row)","def addEntryToTable(self):\n self.table_view.table_model.insertRows(0, 1)","def MaterializeData(self, output_path):\n output_file_name = os.path.join(output_path, self.file_name)\n\n if self.verbose:\n print 'Writing file: %s' % output_file_name\n\n csv_output_file = open(output_file_name, 'wb')\n csv_writer = csv.writer(csv_output_file)\n\n for row in self.table_data:\n csv_writer.writerow(row)\n\n csv_output_file.close()","def install(cls):\n return cls.interface.set_table(cls.schema)","def writerow(self, outdict):\r\n row = []\r\n for field in FatWriter.FIELDS:\r\n col = outdict.get(field, '')\r\n col = col.replace('\\t', ' ')\r\n col = col.replace('\\n', '\\\\n')\r\n row.append(col)\r\n self.outfile.write('\\t'.join(row) + '\\n')","def add_column(self, schema):\n self[schema.name] = schema.copy()","def place_types_process_rows(self):\n\n for index in range(len(self.table)):\n row_rdf = self.place_types_map_row_to_rdf(self.table.iloc[index])\n if row_rdf is not None:\n self.data += row_rdf","def append_row(self, row=None):\n self.set_row(self.size, row)","def export(self, out=sys.stdout):\n\n tablemodel = None\n for x in self.tables:\n if x.name == self.config.table:\n tablemodel = x\n \n if tablemodel is None:\n return\n \n # output the header\n tableinstance = tablemodel(self.dbpath)\n fieldnames = list(tableinstance.fieldnames()) \n out.write(\"\\t\".join(fieldnames) + \"\\n\") \n # output the table contents\n generator = DBGenerator(tablemodel(self.dbpath))\n for row in generator.next():\n temp = [str(row[_]) for _ in fieldnames]\n out.write(\"\\t\".join(temp) + \"\\n\")","def add(self, *args):\n if (len(args) == 1) and type(args[0]) in [list, tuple]:\n row = args[0]\n else:\n row = args\n if self.headings:\n assert len(row) == len(self.headings), 'Expected {} columns but got {}'.format(len(self.headings), len(row))\n self.root.append({name: str(row[pos]) for (pos, name) in enumerate(self.headings)})\n else:\n self.root.append([col for col in row])","def populateTable(self):\n\n output_list = self.output_ports.split(', ')\n\n for i in output_list:\n values = i.split('-')\n nextHopPort = values[0]\n linkCost = values[1]\n destId = values[2]\n learnedFrom = 0 # As it was learned from ConfigFile\n row = routing_row.RoutingRow(nextHopPort, destId, linkCost, destId, learnedFrom)\n self.addToRoutingTable(row)","def Result(row, schema):\r\n return dict(zip(schema.fields(), row))","def add_row(self, row_id):","async def upgradeSchema(self) -> None:","def to_python(self):\r\n # Adding rows\r\n items = []\r\n for row in self.rows:\r\n formatted_row = [_format_python_value(v) for v in row]\r\n items.append(dict(zip(self.columns, formatted_row)))\r\n return items","def create_schema(self, schema: str):\n return","def generate_sql_schema(self, schema, schema_name, psql_tables_path):\n psql_tables = open(psql_tables_path, 'w')\n psql_tables.write(\"SET client_min_messages TO WARNING;\\n\")\n psql_tables.write(\"DROP SCHEMA IF EXISTS %s CASCADE;\\n\" % schema_name)\n psql_tables.write(\"CREATE SCHEMA IF NOT EXISTS %s;\\n\" % schema_name)\n psql_tables.write(\"SET SCHEMA '%s';\\n\" % schema_name)\n psql_tables.write(\"CREATE EXTENSION \\\"unaccent\\\";\\n\\n\")\n\n for table_name, table_attr in schema['tables'].iteritems():\n psql_tables.write(\"\\n-- CREATE TABLE %s \\n %s \\n %s \\n\" % (\n table_attr['name'], self._get_sql_drop_table(table_attr),\n self._get_sql_create_table(table_attr)\n ))\n\n psql_tables.close()","def row(self, rdata):\n self = self\n file = open(\"imdb_output.txt\", \"a\")\n file.write(str(\"\\t\".join(rdata)) + \"\\n\")","def _get_rows(self):\n rows = []\n for row in self.plate_meta['rows']:\n rows.append(row['name'])\n self.rows = rows","def get_table_rows(self, conn):\n raise NotImplementedError(\"Please implement this method\")","def rows(self):\n for station in self.stations:\n yield {'Station': station.as_row()}","def append_row(self, values):\n self.range(self._op.max_row + 1, 1, len(values)).values = values","def _build_rows_struct(self):\n struct = []\n # Step 1 - See docstring for details\n for row in itertools.izip_longest(*self.columns, fillvalue=(\"\",)):\n # Step 2\n row_list = [dict(itertools.izip((\"v\",\"f\",\"p\"), item))\n for item in row]\n # Step 3\n struct.append({\n \"c\": row_list\n })\n return struct","def append(self, *data):\n super(TextDataWriter, self).append(*data)\n dline = []\n for c, d in zip(self.column_descriptions, data):\n if is_sequence(d):\n for x in d:\n dline.append(c.format(x))\n else:\n dline.append(c.format(d))\n self.fo.write(self.separator.join(dline))\n self.fo.write('\\n')","def make_tables(self):\n for t in self.tables:\n self.add_table(groupname=t['groupname'],\n tablename=t['tablename'],\n description=t['description'],\n tabletitle=t['tabletitle'])","def as_rows(self, rows: Iterable):\n try:\n out = self.from_rows(rows, columns=self.data.columns, meta_dict=self.meta)\n except AssertionError as exc:\n columns = self.data.columns.tolist()\n firstrow = next(iter(rows))\n raise RuntimeError(\n f\"Passed {len(columns)} columns {columns!r}, but \"\n f\"{len(firstrow)} elements in first row: {firstrow}\"\n ) from exc\n return out","def __new_tables_statement(self):\n new_tables = self.__new_tables()\n for table in new_tables:\n with open('./update/create_tables.sql', 'a') as f:\n create_statement = self.source.query_create_table_statement(table.name)\n f.write(create_statement)\n f.write('\\n')","def write_row(self, data):\n raise NotImplementedError()","def append_table(self, table):\n if not table:\n return\n\n indexes = []\n for idx in table.index:\n index = self.size + idx\n indexes.append(index)\n\n self.set(indexes=indexes, columns=table.columns, values=table.data)","def schemaDump(self, output):\n libxml2mod.xmlSchemaDump(output, self._o)","def create_all_tables(self):\n pass","def append_table(lines, table):\n tabulate(table)\n for row in table:\n lines.append('|' + '|'.join(row).rstrip() + '\\n')","def output_columns(self) -> List[str]:","def set_schema(self, schema, set_num_columns=True):\n update_dict = {self.SCHEMA: schema}\n\n if set_num_columns:\n update_dict.update({self.NUM_COLUMNS: len(schema.keys())})\n\n self.update(update_dict)","def schema() -> None:\n pass","def dump(self):\n # This is pretty, but we could just return the ddl_string\n outputs = [\"Table : %s\\n\" % self.name]\n # We show the columns in sequence order, using DSU\n # DSU = Decorate, Sort, Undecorate - a.k.a Schwartzian transform\n deco_cols = [ (x['sequence'], x) for x in list(self.columns.values()) ]\n deco_cols.sort()\n cols = [ col for seq, col in deco_cols ]\n for column in cols:\n outputs.append(\" %-30s\" % column['name'])\n if 'length' in column and column['length'] != None:\n if 'precision' in column and column['precision'] != None:\n # This column is a numeric data type\n column_defn = column['type']+self.__class__.calc_precision(column['type'], column['length'], column['precision'], column['scale'])\n else:\n # This column is a text data type\n column_defn = '%s(%d)' % (column['type'], column['length'])\n else:\n # This column is a simple data type such as date or boolean\n column_defn = column['type']\n outputs.append(\" %-15s \" % column_defn)\n if not column['nullable']:\n outputs.append(\" NOT NULL\")\n if 'special' in column:\n # Special case for e.g. 'enum' in MySQL\n outputs.append(' %s' % column['special'])\n outputs.append(\"\\n\")\n # Constraints please\n if len(self.constraints) != 0:\n outputs.append(\" Constraints;\\n\")\n for constraint_name, constraint in list(self.constraints.items()):\n outputs.append(\" %s, \" % constraint_name)\n outputs.append(\"%s \" % (constraint['type']))\n if 'columns' in constraint:\n outputs.append(\": \")\n outputs.append(', '.join(constraint['columns']))\n outputs.append(\"\\n\")\n # Indexes\n if len(self.indexes) > 0:\n outputs.append(\" Indexes:\\n\")\n for index_name, index in list(self.indexes.items()):\n outputs.append(\" %s, \" % index_name)\n outputs.append(\"%s\\n\" % index['type'])\n # Don't check number of columns because there must be at least 1\n outputs.append(\" Columns: \")\n outputs.append(\", \".join(index['columns']))\n outputs.append(\"\\n\")\n # LOG.debug(\"Table Dump output: \" + \"\".join(outputs))\n return \"\".join(outputs)","def outtype(self, intypes):\n rowtype = {\n 'fieldnames': [ 'f%d' % (i+1) for i in range(0, len(intypes)) ],\n 'fieldtypes': dict([ ('f%d' % (i+1), intypes[i].flatten() )\n for i in range(0, len(intypes)) ])\n }\n return RowType(rowtype, 'dynamically created row type')","def _configure_csv_file(self, file_handle, schema):\n csv_writer = csv.writer(file_handle, delimiter=self.field_delimiter)\n csv_writer.writerow(schema)\n return csv_writer","def setup_schema(self):\n models.Base.metadata.create_all(self.session.bind)","def schema(self, schema):\n\n self._schema = schema","def schema(self, schema):\n\n self._schema = schema","def schema(self, schema):\n\n self._schema = schema","def schema(self, schema):\n self._schema = schema","def add_table(self, schema, query=None, create=True):\n if not constants.NAME_RX.match(schema[\"name\"]):\n raise ValueError(\"invalid table name\")\n if utils.name_in_nocase(schema[\"name\"], self.db[\"tables\"]):\n raise ValueError(\"name is already in use for a table\")\n if utils.name_in_nocase(schema[\"name\"], self.db[\"views\"]):\n raise ValueError(\"name is already in use for a view\")\n if query:\n sql = dbshare.query.get_sql_statement(query)\n sql = 'CREATE TABLE \"%s\" AS %s' % (schema[\"name\"], sql)\n utils.execute_timeout(self.dbcnx, sql)\n if not schema.get(\"description\"):\n schema[\"description\"] = sql\n sql = 'PRAGMA table_info(\"%s\")' % schema[\"name\"]\n schema[\"columns\"] = []\n for row in self.dbcnx.execute(sql):\n column = {\"name\": row[1]}\n if row[2] == \"INT\":\n column[\"type\"] = constants.INTEGER\n else:\n column[\"type\"] = row[2]\n schema[\"columns\"].append(column)\n elif create:\n sql = get_sql_create_table(schema)\n self.dbcnx.execute(sql)\n with self.dbcnx:\n sql = f\"INSERT INTO {constants.TABLES} (name,schema) VALUES (?,?)\"\n self.dbcnx.execute(sql, (schema[\"name\"], json.dumps(schema)))\n self.update_table(schema)\n self.db[\"tables\"][schema[\"name\"]] = schema","def add_to_table(self):\n if len(self.result) == 0:\n self.result = {self.title: [self.accuracy, self.f1, self.precision]}\n self.result = pd.DataFrame(self.result, index=['Accuracy', 'F-score', 'Precision'])\n return self.result\n else:\n conact = {self.title: [self.accuracy, self.f1, self.precision]}\n conact = pd.DataFrame(conact, index=['Accuracy', 'F-score', 'Precision'])\n self.result = pd.concat([self.result, conact], axis=1)\n return self.result","def start_table(self):\n self.result = \"<table>\\n\"","def addRow(self, data):\n self.jobRow.appendRow(self.createRowData(data))"],"string":"[\n \"def add_rows(self):\\n for row in self.rows:\\n self.table.add_row(row)\",\n \"def append_row(self):\\r\\n values = []\\r\\n vals_to_insert = ''\\r\\n\\r\\n for key in Output.COLUMNS:\\r\\n values.append(str(self[key]))\\r\\n\\r\\n # Replace any Quotes in parsed record with double quotes\\r\\n for i in values:\\r\\n vals_to_insert += i.replace('\\\"', '\\\"\\\"') + '\\\",\\\"'\\r\\n\\r\\n vals_to_insert = '\\\"' + vals_to_insert[:-3] + '\\\"'\\r\\n insert_sqlite_db(vals_to_insert)\",\n \"def append_rows(self, rows):\\n for row in rows:\\n self.append_row(row)\",\n \"def write (self, path):\\n\\t\\ts=[]; add=s.append\\n\\t\\tadd ('\\\\t'.join (self.schema))\\n\\t\\tfor record in self.data:\\n\\t\\t\\tadd (record.asTabDelimitedRecord())\\n\\t\\t\\n\\t\\t# f = open (path, 'w')\\n\\t\\tf = codecs.open(path, 'w', 'utf-8')\\n\\t\\tf.write (self.linesep.join (s))\\n\\t\\tf.close()\\n\\t\\tprint (\\\"data written to \\\" + path)\",\n \"def _add_rows(self, writer_name, list_of_dictionaries):\\n assert(isinstance(list_of_dictionaries, list))\\n self._writers[writer_name].writerows(list_of_dictionaries)\",\n \"def create_schema(self, schema, *, debug=False):\\n c = self.conn.cursor()\\n for line in schema.split(\\\";\\\"):\\n line = line.strip()\\n if len(line)>0:\\n if self.debug or debug:\\n print(f\\\"{line};\\\", file=sys.stderr)\\n try:\\n c.execute(line)\\n except (sqlite3.Error, pymysql.MySQLError) as e:\\n print(\\\"SQL:\\\", line, file=sys.stderr)\\n print(\\\"Error:\\\", e, file=sys.stderr)\\n exit(1)\",\n \"def _add_row(self, w2):\\n done = []\\n row = {}\\n while len(done) != len(self.columns):\\n for col in self.columns:\\n if col in done:\\n continue\\n\\n ok = self._add_item(w2, col, row)\\n if ok:\\n done.append(col)\\n\\n self.rows.append(row)\",\n \"def newrow(self):\\n maxlen = 0\\n for colbuf in self.colbufs:\\n maxlen = max(maxlen, len(colbuf))\\n\\n for i in range(maxlen):\\n first = True\\n for colbuf in self.colbufs:\\n if first:\\n first = False\\n else:\\n sys.stdout.write(self.sepstr)\\n if i < len(colbuf):\\n sys.stdout.write(colbuf[i])\\n else:\\n sys.stdout.write(\\\" \\\"*self.colwidth)\\n sys.stdout.write(\\\"\\\\n\\\")\\n\\n self.colbufs = []\\n for i in range(self.ncolumns):\\n self.colbufs.append([])\",\n \"def append_row(self, row_dict):\\n \\n for k,v in row_dict.items():\\n \\n if(k not in self.table):\\n # Heading does not exist yet. Fill in blanks for past items\\n self.table[k] = [\\\"\\\"] * self.rowcount\\n \\n # clean up value\\n v = v.strip()\\n # try converting string to a number\\n try:\\n v = ast.literal_eval(v)\\n except:\\n pass\\n \\n self.table[k].append(v)\\n \\n self.rowcount = self.rowcount + 1\\n \\n # Even out any columns in DB that were not filled\\n for hdr in self.table:\\n if(len(self.table[hdr]) < self.rowcount):\\n self.table[hdr].append(None)\",\n \"def add_rows(self, rows) :\\n\\n converted = [self._convert_row(row) for row in rows]\\n self._bulk_add_rows(converted)\\n self.version += 1\",\n \"def _populate_output(self):\\n self._store_atomic_queries_table()\\n self._store_composite_queries_table()\",\n \"def __init__(self, schema_row):\\n self.schema = []\\n for field in schema_row['fields']:\\n self.schema.append(field['type'])\",\n \"def _create_schema(self):\\n self._conn.executescript(self._db_schema)\",\n \"def merge_schema(self, schema):\\n for _, attr_schema in schema.iter_attributes():\\n self.merge_attribute_schema(attr_schema)\",\n \"def generate_table(self, rows):\\n ...\",\n \"def print_dataset_schema(outputs, name, columns):\\n outputs.stdout.append(TextOutput(name + ' ('))\\n for i in range(len(columns)):\\n text = ' ' + str(columns[i])\\n if i != len(columns) - 1:\\n text += ','\\n outputs.stdout.append(TextOutput(text))\\n outputs.stdout.append(TextOutput(')'))\",\n \"def _write_rows(self):\\n try:\\n xf = self._writer.xf.send(True)\\n except StopIteration:\\n self._already_saved()\\n\\n with xf.element(\\\"sheetData\\\"):\\n row_idx = 1\\n try:\\n while True:\\n row = (yield)\\n row = self._values_to_row(row, row_idx)\\n self._writer.write_row(xf, row, row_idx)\\n row_idx += 1\\n except GeneratorExit:\\n pass\\n\\n self._writer.xf.send(None)\",\n \"def _schema_write(self, table: TableSchema) -> None:\\n with open(self.schemas / (table['name'] + '.json'), 'w') as f:\\n json.dump(table, f, indent=True)\",\n \"def _prepare_schema(self):\\n schema = DaskSchema(self.schema_name)\\n\\n if not self.tables:\\n logger.warning(\\\"No tables are registered.\\\")\\n\\n for name, dc in self.tables.items():\\n table = DaskTable(name)\\n df = dc.df\\n logger.debug(\\n f\\\"Adding table '{name}' to schema with columns: {list(df.columns)}\\\"\\n )\\n for column in df.columns:\\n data_type = df[column].dtype\\n sql_data_type = python_to_sql_type(data_type)\\n\\n table.addColumn(column, sql_data_type)\\n\\n schema.addTable(table)\\n\\n if not self.functions:\\n logger.debug(\\\"No custom functions defined.\\\")\\n\\n for function_description in self.function_list:\\n name = function_description.name\\n sql_return_type = python_to_sql_type(function_description.return_type)\\n if function_description.aggregation:\\n logger.debug(f\\\"Adding function '{name}' to schema as aggregation.\\\")\\n dask_function = DaskAggregateFunction(name, sql_return_type)\\n else:\\n logger.debug(f\\\"Adding function '{name}' to schema as scalar function.\\\")\\n dask_function = DaskScalarFunction(name, sql_return_type)\\n\\n dask_function = self._add_parameters_from_description(\\n function_description, dask_function\\n )\\n\\n schema.addFunction(dask_function)\\n\\n return schema\",\n \"def add_duplicate_schema(csv: pd.DataFrame, state: Random, verbose:bool) -> pd.DataFrame:\\n schema_number = state.randint(0, max(1, len(csv)//2))\\n for _ in tqdm(range(schema_number), desc=\\\"Adding duplicated schemas\\\", disable=not verbose):\\n csv = add_row(csv, csv.columns, state=state)\\n return csv\",\n \"def add_all_lines(conn, table_values):\\n\\n column_list = table_values[0]\\n column_row = \\\",\\\".join(column_list)\\n qmark = \\\"?\\\"\\n col_count = len(column_list)\\n for cols in range(1, col_count):\\n qmark += \\\", ?\\\"\\n cols = cols\\n\\n cur = conn.cursor()\\n cur.execute(\\\"DROP TABLE IF EXISTS ayasdi_table;\\\")\\n cur.execute(\\\"CREATE TABLE ayasdi_table (\\\" + column_row + \\\");\\\")\\n cur.executemany(\\\\\\n \\\"INSERT INTO ayasdi_table (\\\" + column_row + \\\") VALUES (\\\" + qmark + \\\");\\\", \\\\\\n table_values)\",\n \"def add_row(self, shape, attributes=[]):\\n if isinstance(shape, shapefile.shapefile._Shape):\\n self.shapes.append(shape)\\n self.__shapeHolder._shapes.append(shape)\\n else:\\n if self.shapeType in (1, 8, 11, 21, 25, 31):\\n self.__shapeHolder.point(*shape)\\n elif self.shapeType in (3, 13, 23):\\n addShp = self.__shapeHolder.line(shape)\\n else:\\n self.__shapeHolder.poly(shape)\\n\\n self.shapes.append(self.__shapeHolder.shapes()[-1])\\n self.records.append(self.addDefaults(attributes))\\n self.__isBuilt = False\",\n \"def schema(self):\\n pass\",\n \"def add_row(self, row):\\n ...\",\n \"def add_row(self, shape, attributes):\\n if isinstance(shape, shapefile.shapefile._Shape):\\n self.w._shapes.append(shape)\\n else:\\n if self.shapeType in (1, 8, 11, 21, 25, 31):\\n self.w.point(*shape)\\n elif self.shapeType in (3, 13, 23):\\n self.w.line(shape)\\n else:\\n self.w.poly(shape)\\n self.w.record(*attributes)\",\n \"def _generate_rows(self):\\n logger.debug(\\\"Generating pre-genealogical coherence data for %s\\\", self.w1)\\n if not self.rows:\\n for w2 in self.all_mss:\\n if self.w1 == w2:\\n continue\\n self._add_row(w2)\\n\\n self._sort()\\n logger.debug(\\\"Generated pre-genealogical coherence data for %s\\\", self.w1)\",\n \"def write_row(self, shape, attributes=[]):\\n if isinstance(shape, shapefile.shapefile._Shape):\\n self.w._shapes.append(shape)\\n else:\\n if self.w.shapeType in (1, 8, 11, 21, 25, 31):\\n self.w.w.point(*shape)\\n elif self.w.shapeType in (3, 13, 23):\\n self.w.line(shape)\\n else:\\n self.w.poly(shape)\\n self.w.record(*self.addDefaults(attributes))\",\n \"def _add_table_schema(table_desc, table_name, schema):\\n table_desc['TableName'] = table_name\\n table_desc['AttributeDefinitions'] = [{\\n 'AttributeName': item['name'],\\n 'AttributeType': DynamoStubber._encode_type(item['type'])\\n } for item in schema]\\n table_desc['KeySchema'] = [{\\n 'AttributeName': item['name'],\\n 'KeyType': item['key_type']\\n } for item in schema]\",\n \"def schema(self):\",\n \"def add_row(self, row):\\n \\n new_row = pd.DataFrame(data=[row], columns = self.table.columns) \\n self.table = self.table.append(new_row, ignore_index=True)\",\n \"def build_schema(self):\\n field_defs = []\\n fields = []\\n point_rows = []\\n line_rows = []\\n polygon_rows = []\\n for i in self.json_in['features']: # first iterate through it all and get all the fields\\n props = i.get('properties')\\n\\n for k, v in props.items():\\n if k not in fields:\\n fields.append(k)\\n\\n for i in self.json_in['features']: # now fill in any props that any features are missing, and sort them all\\n geom = i['geometry']\\n props = i['properties']\\n for f in fields:\\n if f not in props.keys():\\n props[f] = ''\\n props = OrderedDict(sorted(props.items()))\\n\\n for k, v in props.items():\\n schema_row = [k, \\\"TEXT\\\", k.replace('_', ' '), 256]\\n if schema_row not in field_defs:\\n field_defs.append(schema_row)\\n row = [str(v) for k, v in sorted(props.items())] # coerce everything to str cause this stuff is a mess\\n parsed_geom = GeoJSONUtils.parse_geometry(geom)\\n geotype = parsed_geom['type']\\n egeom = parsed_geom['esri_geom']\\n\\n if geotype == \\\"POINT\\\":\\n row.insert(0, egeom)\\n print(row)\\n point_rows.append(row)\\n elif geotype == \\\"POLYLINE\\\":\\n row.insert(0, egeom)\\n print(row)\\n line_rows.append(row)\\n else:\\n row.insert(0, egeom)\\n print(row)\\n polygon_rows.append(row)\\n\\n return {\\n \\\"fields\\\": fields,\\n \\\"field_defs\\\": field_defs,\\n \\\"rows\\\": [point_rows, line_rows, polygon_rows]\\n }\",\n \"def add_schema(self, schema, db):\\n self._dbs[schema.typename] = db\\n return None\",\n \"def appendRow(self, contents = None):\\n\\n\\t\\t\\t\\t#Find the last row\\n\\t\\t\\t\\trow = len(tuple(self.thing.iter_rows())) + 1\\n\\n\\t\\t\\t\\t#Write to cells\\n\\t\\t\\t\\tif ((contents != None) and (len(contents) != 0)):\\n\\t\\t\\t\\t\\tfor column, item in enumerate(contents):\\n\\t\\t\\t\\t\\t\\tself.setCell(row, column + 1, item)\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tself.setCell(row, 1, \\\" \\\")\",\n \"def add_row(self, *column_data):\\n if not self.col_widths:\\n self.col_widths = [len(data) for data in column_data]\\n row = \\\"| \\\"\\n row += \\\" | \\\".join(f\\\"{data:{w}}\\\"\\n for (data, w) in zip(column_data, self.col_widths))\\n row += \\\" |\\\\n\\\"\\n self.result += row\",\n \"def _store_rows(self):\\n\\n for value in self.values:\\n self.counters.append(value['counter'])\\n self.timestamps.append(value['timestamp'])\\n self.acceleration.append(value['acceleration'])\",\n \"def WriteBody( self ):\\n\\n self.ParseHeader( sys.stdin.readline() )\\n\\n self.CreateTable()\\n\\n num_lines = 0\\n\\n total_lines = 0\\n sys.stderr.write(\\\"parsing..\\\")\\n \\n while 1:\\n line = sys.stdin.readline()\\n \\n if not line: break\\n if line[0] == \\\"#\\\": continue\\n if line[0:2] == \\\"//\\\": break\\n \\n if not (total_lines % 100) and total_lines > 0:\\n sys.stderr.write( \\\".%i..\\\" % total_lines)\\n print self.table \\n self.table.body = []\\n\\n total_lines = total_lines + 1\\n\\n (columns) = string.split( line[:-1], \\\"\\\\t\\\" )\\n \\n if not columns:\\n break\\n\\n if self.mUseIndex:\\n col_string = [str(total_lines),] + self.ParseColumns( columns )\\n else:\\n col_string = self.ParseColumns( columns )\\n \\n self.table.body.append( col_string ) \\n \\n print self.table\\n \\n sys.stderr.write(\\\"done\\\\n\\\")\",\n \"def schema(self):\\n raise NotImplementedError\",\n \"def append(self,output):\\n\\n if self.log_init is False or self.reprint_header:\\n # Insert our new headers in reverse order\\n line = self.separator.join(output['HEADER'])\\n self.outfd.write(line)\\n self.log_init = True\\n self.outfd.write(\\\"\\\\n\\\")\\n \\n for row in output['DATA']:\\n \\n # Convert everything to a string\\n row = [str(i) for i in row]\\n line = self.separator.join(row)\\n self.outfd.write(line)\\n self.outfd.write(\\\"\\\\n\\\")\\n \\n self.outfd.flush()\",\n \"def start_table(self):\\n self.col_widths = []\\n self.result = \\\"\\\"\",\n \"def __append_rows_to_partition(self,partition_dt,rows):\\n\\n ts_data = self.__fetch_or_create_partition_table(partition_dt)\\n ts_data.append(rows)\",\n \"def _rebuild(self):\\n for shape, record in iter(self):\\n self.write_row(shape, record)\\n self.__isBuilt = True\",\n \"def formatSchema(self):\\n schema = json.loads(self.schemaSource)\\n stack = [schema]\\n # Strip out all the docs\\n while len(stack) > 0:\\n elm = stack.pop()\\n if \\\"doc\\\" in elm:\\n elm[\\\"doc\\\"] = \\\"\\\"\\n for value in elm.values():\\n if isinstance(value, dict):\\n stack.append(value)\\n elif isinstance(value, list):\\n for dic in value:\\n if isinstance(dic, dict):\\n stack.append(dic)\\n jsonData = json.dumps(schema)\\n output = \\\"\\\\n\\\".join(textwrap.wrap(jsonData)) + \\\"\\\\n\\\"\\n return output\",\n \"def initialize_schema(self, dry_run=False):\\n if not dry_run:\\n self.flush()\",\n \"def write_rows(self, rows: Union[List[dict], dict]):\\n rows = listify(rows)\\n flat = self.get_arg_value(\\\"json_flat\\\")\\n\\n indent = None if flat else 2\\n prefix = \\\" \\\" * indent if indent else \\\"\\\"\\n\\n for row in rows:\\n if self._first_row:\\n pre = \\\"\\\" if flat else \\\"\\\\n\\\"\\n else:\\n pre = \\\"\\\\n\\\" if flat else \\\",\\\\n\\\"\\n\\n self._first_row = False\\n self._fd.write(pre)\\n\\n value = json.dumps(row, indent=indent)\\n value = textwrap.indent(value, prefix=prefix) if indent else value\\n self._fd.write(value)\\n del value, row\",\n \"def insert_rows(rows: Iterable[Row],\\n name: str,\\n fields: List[Tuple[str, str]],\\n ws: str = \\\"memory\\\",\\n spatial_reference: int = 3857,\\n shape_type: str = \\\"POLYGON\\\",\\n shape_format: str = \\\"WKB\\\") -> None:\\n cols = [f\\\"Shape@{shape_format}\\\"]\\n with _insert_cursor(cols, name, fields, ws, spatial_reference, shape_type) as cursor:\\n for row in rows:\\n cursor.insertRow(row)\",\n \"def write(self, row):\\n self.append_rows.append(tuple(row))\",\n \"def handle_output(all_rows, opts):\\n for dev, rows in all_rows.iteritems():\\n\\n if opts.csv:\\n writer = csv.writer(sys.stdout)\\n for row in rows:\\n writer.writerow([dev] + row)\\n elif opts.dotty:\\n continue\\n elif opts.sqldb:\\n write_sqldb(opts.sqldb, dev, rows)\\n else:\\n print 'DEVICE: {}'.format(dev)\\n print_table(rows)\",\n \"def showSchema (self):\\n\\t\\ts=[];add=s.append\\n\\t\\tfor i in range(len(self.schema)):\\n\\t\\t\\tadd (\\\"%d. %s\\\" % (i+1, self.schema[i]))\\n\\t\\treturn join (s, '\\\\n')\",\n \"def add_row(self, values):\\n if len(values) != len(self.column_names):\\n raise ValueError(\\n 'Number of values does not match number of columns'\\n )\\n\\n self.rows.append(values)\",\n \"def add_row(self, *column_data):\\n row = \\\"<tr>\\\"\\n row += \\\" \\\".join(f\\\"<td>{header}</td>\\\" for header in column_data)\\n row += \\\"</tr>\\\\n\\\"\\n self.result += row\",\n \"def schema(self):\\n attrs = self.attrs.copy()\\n parts = ['CREATE', 'TABLE', self.name, '(%s,' % self.hash_key.schema]\\n del attrs[self.hash_key.name]\\n if self.range_key:\\n parts.append(self.range_key.schema + ',')\\n del attrs[self.range_key.name]\\n if attrs:\\n attr_def = ', '.join([attr.schema for attr in six.itervalues(attrs)])\\n parts.append(attr_def + ',')\\n\\n parts.append(\\\"THROUGHPUT (%d, %d))\\\" % (self.read_throughput,\\n self.write_throughput))\\n parts.extend([g.schema for g in six.itervalues(self.global_indexes)])\\n return ' '.join(parts) + ';'\",\n \"def add_row(self, row):\\r\\n self.rows.append(row)\",\n \"def describe(self):\\n print('Schema Changes\\\\n==============')\\n self.schema().describe()\\n print('\\\\nData Changes\\\\n============')\\n self.rows().describe()\",\n \"def __format_results__(self, result_rows):\\n for row in result_rows:\\n self.return_dict['results']['items'].append(row)\",\n \"def addEntryToTable(self):\\n self.table_view.table_model.insertRows(0, 1)\",\n \"def MaterializeData(self, output_path):\\n output_file_name = os.path.join(output_path, self.file_name)\\n\\n if self.verbose:\\n print 'Writing file: %s' % output_file_name\\n\\n csv_output_file = open(output_file_name, 'wb')\\n csv_writer = csv.writer(csv_output_file)\\n\\n for row in self.table_data:\\n csv_writer.writerow(row)\\n\\n csv_output_file.close()\",\n \"def install(cls):\\n return cls.interface.set_table(cls.schema)\",\n \"def writerow(self, outdict):\\r\\n row = []\\r\\n for field in FatWriter.FIELDS:\\r\\n col = outdict.get(field, '')\\r\\n col = col.replace('\\\\t', ' ')\\r\\n col = col.replace('\\\\n', '\\\\\\\\n')\\r\\n row.append(col)\\r\\n self.outfile.write('\\\\t'.join(row) + '\\\\n')\",\n \"def add_column(self, schema):\\n self[schema.name] = schema.copy()\",\n \"def place_types_process_rows(self):\\n\\n for index in range(len(self.table)):\\n row_rdf = self.place_types_map_row_to_rdf(self.table.iloc[index])\\n if row_rdf is not None:\\n self.data += row_rdf\",\n \"def append_row(self, row=None):\\n self.set_row(self.size, row)\",\n \"def export(self, out=sys.stdout):\\n\\n tablemodel = None\\n for x in self.tables:\\n if x.name == self.config.table:\\n tablemodel = x\\n \\n if tablemodel is None:\\n return\\n \\n # output the header\\n tableinstance = tablemodel(self.dbpath)\\n fieldnames = list(tableinstance.fieldnames()) \\n out.write(\\\"\\\\t\\\".join(fieldnames) + \\\"\\\\n\\\") \\n # output the table contents\\n generator = DBGenerator(tablemodel(self.dbpath))\\n for row in generator.next():\\n temp = [str(row[_]) for _ in fieldnames]\\n out.write(\\\"\\\\t\\\".join(temp) + \\\"\\\\n\\\")\",\n \"def add(self, *args):\\n if (len(args) == 1) and type(args[0]) in [list, tuple]:\\n row = args[0]\\n else:\\n row = args\\n if self.headings:\\n assert len(row) == len(self.headings), 'Expected {} columns but got {}'.format(len(self.headings), len(row))\\n self.root.append({name: str(row[pos]) for (pos, name) in enumerate(self.headings)})\\n else:\\n self.root.append([col for col in row])\",\n \"def populateTable(self):\\n\\n output_list = self.output_ports.split(', ')\\n\\n for i in output_list:\\n values = i.split('-')\\n nextHopPort = values[0]\\n linkCost = values[1]\\n destId = values[2]\\n learnedFrom = 0 # As it was learned from ConfigFile\\n row = routing_row.RoutingRow(nextHopPort, destId, linkCost, destId, learnedFrom)\\n self.addToRoutingTable(row)\",\n \"def Result(row, schema):\\r\\n return dict(zip(schema.fields(), row))\",\n \"def add_row(self, row_id):\",\n \"async def upgradeSchema(self) -> None:\",\n \"def to_python(self):\\r\\n # Adding rows\\r\\n items = []\\r\\n for row in self.rows:\\r\\n formatted_row = [_format_python_value(v) for v in row]\\r\\n items.append(dict(zip(self.columns, formatted_row)))\\r\\n return items\",\n \"def create_schema(self, schema: str):\\n return\",\n \"def generate_sql_schema(self, schema, schema_name, psql_tables_path):\\n psql_tables = open(psql_tables_path, 'w')\\n psql_tables.write(\\\"SET client_min_messages TO WARNING;\\\\n\\\")\\n psql_tables.write(\\\"DROP SCHEMA IF EXISTS %s CASCADE;\\\\n\\\" % schema_name)\\n psql_tables.write(\\\"CREATE SCHEMA IF NOT EXISTS %s;\\\\n\\\" % schema_name)\\n psql_tables.write(\\\"SET SCHEMA '%s';\\\\n\\\" % schema_name)\\n psql_tables.write(\\\"CREATE EXTENSION \\\\\\\"unaccent\\\\\\\";\\\\n\\\\n\\\")\\n\\n for table_name, table_attr in schema['tables'].iteritems():\\n psql_tables.write(\\\"\\\\n-- CREATE TABLE %s \\\\n %s \\\\n %s \\\\n\\\" % (\\n table_attr['name'], self._get_sql_drop_table(table_attr),\\n self._get_sql_create_table(table_attr)\\n ))\\n\\n psql_tables.close()\",\n \"def row(self, rdata):\\n self = self\\n file = open(\\\"imdb_output.txt\\\", \\\"a\\\")\\n file.write(str(\\\"\\\\t\\\".join(rdata)) + \\\"\\\\n\\\")\",\n \"def _get_rows(self):\\n rows = []\\n for row in self.plate_meta['rows']:\\n rows.append(row['name'])\\n self.rows = rows\",\n \"def get_table_rows(self, conn):\\n raise NotImplementedError(\\\"Please implement this method\\\")\",\n \"def rows(self):\\n for station in self.stations:\\n yield {'Station': station.as_row()}\",\n \"def append_row(self, values):\\n self.range(self._op.max_row + 1, 1, len(values)).values = values\",\n \"def _build_rows_struct(self):\\n struct = []\\n # Step 1 - See docstring for details\\n for row in itertools.izip_longest(*self.columns, fillvalue=(\\\"\\\",)):\\n # Step 2\\n row_list = [dict(itertools.izip((\\\"v\\\",\\\"f\\\",\\\"p\\\"), item))\\n for item in row]\\n # Step 3\\n struct.append({\\n \\\"c\\\": row_list\\n })\\n return struct\",\n \"def append(self, *data):\\n super(TextDataWriter, self).append(*data)\\n dline = []\\n for c, d in zip(self.column_descriptions, data):\\n if is_sequence(d):\\n for x in d:\\n dline.append(c.format(x))\\n else:\\n dline.append(c.format(d))\\n self.fo.write(self.separator.join(dline))\\n self.fo.write('\\\\n')\",\n \"def make_tables(self):\\n for t in self.tables:\\n self.add_table(groupname=t['groupname'],\\n tablename=t['tablename'],\\n description=t['description'],\\n tabletitle=t['tabletitle'])\",\n \"def as_rows(self, rows: Iterable):\\n try:\\n out = self.from_rows(rows, columns=self.data.columns, meta_dict=self.meta)\\n except AssertionError as exc:\\n columns = self.data.columns.tolist()\\n firstrow = next(iter(rows))\\n raise RuntimeError(\\n f\\\"Passed {len(columns)} columns {columns!r}, but \\\"\\n f\\\"{len(firstrow)} elements in first row: {firstrow}\\\"\\n ) from exc\\n return out\",\n \"def __new_tables_statement(self):\\n new_tables = self.__new_tables()\\n for table in new_tables:\\n with open('./update/create_tables.sql', 'a') as f:\\n create_statement = self.source.query_create_table_statement(table.name)\\n f.write(create_statement)\\n f.write('\\\\n')\",\n \"def write_row(self, data):\\n raise NotImplementedError()\",\n \"def append_table(self, table):\\n if not table:\\n return\\n\\n indexes = []\\n for idx in table.index:\\n index = self.size + idx\\n indexes.append(index)\\n\\n self.set(indexes=indexes, columns=table.columns, values=table.data)\",\n \"def schemaDump(self, output):\\n libxml2mod.xmlSchemaDump(output, self._o)\",\n \"def create_all_tables(self):\\n pass\",\n \"def append_table(lines, table):\\n tabulate(table)\\n for row in table:\\n lines.append('|' + '|'.join(row).rstrip() + '\\\\n')\",\n \"def output_columns(self) -> List[str]:\",\n \"def set_schema(self, schema, set_num_columns=True):\\n update_dict = {self.SCHEMA: schema}\\n\\n if set_num_columns:\\n update_dict.update({self.NUM_COLUMNS: len(schema.keys())})\\n\\n self.update(update_dict)\",\n \"def schema() -> None:\\n pass\",\n \"def dump(self):\\n # This is pretty, but we could just return the ddl_string\\n outputs = [\\\"Table : %s\\\\n\\\" % self.name]\\n # We show the columns in sequence order, using DSU\\n # DSU = Decorate, Sort, Undecorate - a.k.a Schwartzian transform\\n deco_cols = [ (x['sequence'], x) for x in list(self.columns.values()) ]\\n deco_cols.sort()\\n cols = [ col for seq, col in deco_cols ]\\n for column in cols:\\n outputs.append(\\\" %-30s\\\" % column['name'])\\n if 'length' in column and column['length'] != None:\\n if 'precision' in column and column['precision'] != None:\\n # This column is a numeric data type\\n column_defn = column['type']+self.__class__.calc_precision(column['type'], column['length'], column['precision'], column['scale'])\\n else:\\n # This column is a text data type\\n column_defn = '%s(%d)' % (column['type'], column['length'])\\n else:\\n # This column is a simple data type such as date or boolean\\n column_defn = column['type']\\n outputs.append(\\\" %-15s \\\" % column_defn)\\n if not column['nullable']:\\n outputs.append(\\\" NOT NULL\\\")\\n if 'special' in column:\\n # Special case for e.g. 'enum' in MySQL\\n outputs.append(' %s' % column['special'])\\n outputs.append(\\\"\\\\n\\\")\\n # Constraints please\\n if len(self.constraints) != 0:\\n outputs.append(\\\" Constraints;\\\\n\\\")\\n for constraint_name, constraint in list(self.constraints.items()):\\n outputs.append(\\\" %s, \\\" % constraint_name)\\n outputs.append(\\\"%s \\\" % (constraint['type']))\\n if 'columns' in constraint:\\n outputs.append(\\\": \\\")\\n outputs.append(', '.join(constraint['columns']))\\n outputs.append(\\\"\\\\n\\\")\\n # Indexes\\n if len(self.indexes) > 0:\\n outputs.append(\\\" Indexes:\\\\n\\\")\\n for index_name, index in list(self.indexes.items()):\\n outputs.append(\\\" %s, \\\" % index_name)\\n outputs.append(\\\"%s\\\\n\\\" % index['type'])\\n # Don't check number of columns because there must be at least 1\\n outputs.append(\\\" Columns: \\\")\\n outputs.append(\\\", \\\".join(index['columns']))\\n outputs.append(\\\"\\\\n\\\")\\n # LOG.debug(\\\"Table Dump output: \\\" + \\\"\\\".join(outputs))\\n return \\\"\\\".join(outputs)\",\n \"def outtype(self, intypes):\\n rowtype = {\\n 'fieldnames': [ 'f%d' % (i+1) for i in range(0, len(intypes)) ],\\n 'fieldtypes': dict([ ('f%d' % (i+1), intypes[i].flatten() )\\n for i in range(0, len(intypes)) ])\\n }\\n return RowType(rowtype, 'dynamically created row type')\",\n \"def _configure_csv_file(self, file_handle, schema):\\n csv_writer = csv.writer(file_handle, delimiter=self.field_delimiter)\\n csv_writer.writerow(schema)\\n return csv_writer\",\n \"def setup_schema(self):\\n models.Base.metadata.create_all(self.session.bind)\",\n \"def schema(self, schema):\\n\\n self._schema = schema\",\n \"def schema(self, schema):\\n\\n self._schema = schema\",\n \"def schema(self, schema):\\n\\n self._schema = schema\",\n \"def schema(self, schema):\\n self._schema = schema\",\n \"def add_table(self, schema, query=None, create=True):\\n if not constants.NAME_RX.match(schema[\\\"name\\\"]):\\n raise ValueError(\\\"invalid table name\\\")\\n if utils.name_in_nocase(schema[\\\"name\\\"], self.db[\\\"tables\\\"]):\\n raise ValueError(\\\"name is already in use for a table\\\")\\n if utils.name_in_nocase(schema[\\\"name\\\"], self.db[\\\"views\\\"]):\\n raise ValueError(\\\"name is already in use for a view\\\")\\n if query:\\n sql = dbshare.query.get_sql_statement(query)\\n sql = 'CREATE TABLE \\\"%s\\\" AS %s' % (schema[\\\"name\\\"], sql)\\n utils.execute_timeout(self.dbcnx, sql)\\n if not schema.get(\\\"description\\\"):\\n schema[\\\"description\\\"] = sql\\n sql = 'PRAGMA table_info(\\\"%s\\\")' % schema[\\\"name\\\"]\\n schema[\\\"columns\\\"] = []\\n for row in self.dbcnx.execute(sql):\\n column = {\\\"name\\\": row[1]}\\n if row[2] == \\\"INT\\\":\\n column[\\\"type\\\"] = constants.INTEGER\\n else:\\n column[\\\"type\\\"] = row[2]\\n schema[\\\"columns\\\"].append(column)\\n elif create:\\n sql = get_sql_create_table(schema)\\n self.dbcnx.execute(sql)\\n with self.dbcnx:\\n sql = f\\\"INSERT INTO {constants.TABLES} (name,schema) VALUES (?,?)\\\"\\n self.dbcnx.execute(sql, (schema[\\\"name\\\"], json.dumps(schema)))\\n self.update_table(schema)\\n self.db[\\\"tables\\\"][schema[\\\"name\\\"]] = schema\",\n \"def add_to_table(self):\\n if len(self.result) == 0:\\n self.result = {self.title: [self.accuracy, self.f1, self.precision]}\\n self.result = pd.DataFrame(self.result, index=['Accuracy', 'F-score', 'Precision'])\\n return self.result\\n else:\\n conact = {self.title: [self.accuracy, self.f1, self.precision]}\\n conact = pd.DataFrame(conact, index=['Accuracy', 'F-score', 'Precision'])\\n self.result = pd.concat([self.result, conact], axis=1)\\n return self.result\",\n \"def start_table(self):\\n self.result = \\\"<table>\\\\n\\\"\",\n \"def addRow(self, data):\\n self.jobRow.appendRow(self.createRowData(data))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67264223","0.6197562","0.61581135","0.5907348","0.59029365","0.5833993","0.58154505","0.57763284","0.57446873","0.5742718","0.56974214","0.56769365","0.56498146","0.5647206","0.5645583","0.56280947","0.5627587","0.56085706","0.553828","0.5537964","0.5532495","0.5521361","0.55079097","0.55072314","0.54977864","0.54970425","0.5491578","0.5489","0.5486442","0.5480991","0.547911","0.54627633","0.544999","0.54012287","0.5371617","0.5365135","0.53592545","0.5320041","0.52963763","0.5296364","0.5292108","0.5281949","0.527919","0.5272635","0.5272232","0.5270707","0.5252956","0.5252288","0.5232807","0.52097","0.5202329","0.5188623","0.51767904","0.517582","0.5162146","0.51452667","0.51410574","0.51408684","0.51361936","0.51280516","0.5103689","0.5095706","0.50808865","0.5067307","0.505202","0.5049465","0.5045839","0.5041272","0.5038178","0.5036517","0.503614","0.5033414","0.5030162","0.5022383","0.5014356","0.50086886","0.5006047","0.4993267","0.49824327","0.49805173","0.49804398","0.49767953","0.49749678","0.4969422","0.4969108","0.49540597","0.49537006","0.49536923","0.49502283","0.49462667","0.49422652","0.4938555","0.49380767","0.49380767","0.49380767","0.49229282","0.4922596","0.4920608","0.49175918","0.49175856"],"string":"[\n \"0.67264223\",\n \"0.6197562\",\n \"0.61581135\",\n \"0.5907348\",\n \"0.59029365\",\n \"0.5833993\",\n \"0.58154505\",\n \"0.57763284\",\n \"0.57446873\",\n \"0.5742718\",\n \"0.56974214\",\n \"0.56769365\",\n \"0.56498146\",\n \"0.5647206\",\n \"0.5645583\",\n \"0.56280947\",\n \"0.5627587\",\n \"0.56085706\",\n \"0.553828\",\n \"0.5537964\",\n \"0.5532495\",\n \"0.5521361\",\n \"0.55079097\",\n \"0.55072314\",\n \"0.54977864\",\n \"0.54970425\",\n \"0.5491578\",\n \"0.5489\",\n \"0.5486442\",\n \"0.5480991\",\n \"0.547911\",\n \"0.54627633\",\n \"0.544999\",\n \"0.54012287\",\n \"0.5371617\",\n \"0.5365135\",\n \"0.53592545\",\n \"0.5320041\",\n \"0.52963763\",\n \"0.5296364\",\n \"0.5292108\",\n \"0.5281949\",\n \"0.527919\",\n \"0.5272635\",\n \"0.5272232\",\n \"0.5270707\",\n \"0.5252956\",\n \"0.5252288\",\n \"0.5232807\",\n \"0.52097\",\n \"0.5202329\",\n \"0.5188623\",\n \"0.51767904\",\n \"0.517582\",\n \"0.5162146\",\n \"0.51452667\",\n \"0.51410574\",\n \"0.51408684\",\n \"0.51361936\",\n \"0.51280516\",\n \"0.5103689\",\n \"0.5095706\",\n \"0.50808865\",\n \"0.5067307\",\n \"0.505202\",\n \"0.5049465\",\n \"0.5045839\",\n \"0.5041272\",\n \"0.5038178\",\n \"0.5036517\",\n \"0.503614\",\n \"0.5033414\",\n \"0.5030162\",\n \"0.5022383\",\n \"0.5014356\",\n \"0.50086886\",\n \"0.5006047\",\n \"0.4993267\",\n \"0.49824327\",\n \"0.49805173\",\n \"0.49804398\",\n \"0.49767953\",\n \"0.49749678\",\n \"0.4969422\",\n \"0.4969108\",\n \"0.49540597\",\n \"0.49537006\",\n \"0.49536923\",\n \"0.49502283\",\n \"0.49462667\",\n \"0.49422652\",\n \"0.4938555\",\n \"0.49380767\",\n \"0.49380767\",\n \"0.49380767\",\n \"0.49229282\",\n \"0.4922596\",\n \"0.4920608\",\n \"0.49175918\",\n \"0.49175856\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.65681523"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81770,"cells":{"query":{"kind":"string","value":"Return all the buffered objects, in the correct order as well as their index"},"document":{"kind":"string","value":"def items(self):\n ix_obj = list(self.d_buffer.keys())\n ix_obj.sort()\n l_obj = [self.d_buffer[ix] for ix in ix_obj]\n\n return ix_obj, l_obj"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get(self):\n assert self.ptr == self.max_size\n self.ptr, self.path_start_idx = 0, 0\n return [self.obs_buf, self.act_buf, self.adv_buf, self.ret_buf, self.val_buf]","def BufferList(self) -> _n_2_t_0[_n_0_t_11[_n_0_t_6]]:","def __getitem__(self, index):\n return self.buffer[index]","def _readIdxBuf(self):\n base = self.fres.bufferSection['buf_offs']\n self.idx_buf = self.fres.read(self.idx_fmt,\n pos = self.header['face_offs'] + base,\n count = self.header['idx_cnt'])\n\n for i in range(self.header['idx_cnt']):\n self.idx_buf[i] += self.header['visibility_group']","def get_batch(self):\n result = self.buffer_.get()\n self._async_next()\n return result","def get_batch(self):\n result = self.buffer_.get()\n self._async_next()\n return result","def _buffer_all(self):\n self._buffer()","def getAll(self):\n return self.dataBuffer","def cbuffers(self):\r\n self._core.sym.assert_have_symbols()\r\n\r\n cbuffer_name_key = \"cbuffer_struc$\"\r\n cbuffer_name_key_len = len(cbuffer_name_key)\r\n cbuffers = self._core.sym.varfind(cbuffer_name_key)\r\n cbuffers.sort()\r\n\r\n print \" \" * 30 + \"C-Buffer Size Read Addr Write Addr Start Space Data\"\r\n\r\n # The results from varfind are unfortunately tuples -- one simply has to know the correct indices.\r\n for (struct_name, size_in_addressable_units, struct_address) in cbuffers:\r\n # Order of fields in the structure: size, read pointer, write pointer.\r\n (sz, rd, wr) = self._read_var_with_size_check(struct_address, size_in_addressable_units)\r\n\r\n struct_name = struct_name[:-cbuffer_name_key_len]\r\n print \"%38s\" % struct_name,\r\n\r\n if sz != 0:\r\n # Find start address of the buffer\r\n mask = int(2**math.ceil(math.log(sz, 2)) - 1)\r\n start_addr = rd - (rd & mask)\r\n if start_addr != (wr - (wr & mask)):\r\n print '\\n\\n** Warning the start address calculated from the read',\r\n print 'and write pointers is different! **'\r\n\r\n amount_space = rd - wr\r\n if amount_space <= 0:\r\n amount_space += sz\r\n amount_space -= 1\r\n amount_data = wr - rd\r\n if amount_data < 0:\r\n amount_data += sz\r\n\r\n print ' %4d 0x%06x 0x%06x 0x%06x %4d %4d' % \\\r\n (sz, rd, wr, start_addr, amount_space, amount_data)\r\n else:\r\n print \"size=0\"","def items(self):\n out = []\n for y,x in self.coords(False):\n out.append(self.retrieve(y, x))\n return out","def test_benchmark_BufferedGraphReader_in_order(\n benchmark, db_10000: graph_tuple_database.Database, buffer_size_mb: int,\n):\n benchmark(\n list,\n reader.BufferedGraphReader(\n db_10000,\n buffer_size_mb=buffer_size_mb,\n order=reader.BufferedGraphReaderOrder.IN_ORDER,\n ),\n )","def object_block(data, pos, player_number, index):\n objects = []\n offset = None\n while True:\n if not offset:\n match = REGEXES[player_number].search(data, pos)\n end = data.find(BLOCK_END, pos) - pos + len(BLOCK_END)\n if match is None:\n break\n offset = match.start() - pos\n while end + 8 < offset:\n end += data.find(BLOCK_END, pos + end) - (pos + end) + len(BLOCK_END)\n if end + 8 == offset:\n break\n pos += offset\n # Speed optimization: Skip specified fixed-length objects.\n test = data[pos:pos + 4]\n for fingerprint, offset in SKIP_OBJECTS:\n if test == fingerprint:\n break\n else:\n objects.append(dict(parse_object(data, pos), index=index))\n offset = None\n pos += 31\n return objects, pos + end","def get_all(self):\r\n if self.filled_rows < self.rows:\r\n return np.roll(self._data, -(self.curr_pos + self.rows - self.filled_rows),\r\n axis=0)[:self.filled_rows,:]\r\n else:\r\n # The buffer has fewer lines in this case\r\n return np.roll(self._data, -self.curr_pos,\r\n axis=0)","def _get_buffer(self):\n return memoryview(self._write_buffer)[: self._buffer_seek]","def alltoall_recvbuffer(\n self, obj: torch.Tensor\n ) -> List[Union[MPI.memory, Tuple[int, int], MPI.Datatype]]:\n mpi_type, _ = self.__mpi_type_mappings[obj.dtype], torch.numel(obj)\n\n nproc = self.size\n shape = obj.shape[1:]\n strides = [1] * len(shape)\n strides[0] = obj.stride()[-1]\n strides = strides[::-1]\n offsets = [obj.element_size() * stride for stride in obj.stride()[:-1]]\n\n # Step 1: Wrap along axes > 0 (all axes except recv_axis)\n for i in range(len(shape) - 1, -1, -1):\n mpi_type = mpi_type.Create_vector(shape[i], 1, strides[i]).Create_resized(0, offsets[i])\n mpi_type.Commit()\n\n # Step 2: Receive blocks along the recv axis\n # Prepare recvcount, senddispls and sendtypes for alltoallw\n recvcount = np.full((nproc,), obj.shape[0] // nproc)\n recvcount[: obj.shape[0] % nproc] += 1\n # size/extent of mpitype = offsets[0]\n tmp_displs = [0] * nproc\n tmp_displs[1:] = np.cumsum(recvcount[:-1])\n recvdispls = [offsets[0] * d for d in tmp_displs]\n recvtypes = [mpi_type] * nproc\n\n return self.as_mpi_memory(obj), (recvcount, recvdispls), recvtypes","def worker(self):\n while True:\n item,index = self.inbound.get()\n if index is None:\n self.buffer.append(item)\n self.index.value = self.index.value + 1 #index of next item for buffer\n if len(self.buffer)>self.size:\n del self.buffer[0]\n self.newitem.put(None)\n else:\n self.buffer[len(self.buffer)+(index - self.index.value)] = item","def getBufferChildren(self, buffertop):\n children = [v for k, v in self.GS_arcs if k == buffertop]\n return children","def spit(self):\n idxs = np.arange(self.total_tuples)\n return [self.recurse_index_state(copy.deepcopy(self.state_buffer), idxs), self.recurse_index_state(copy.deepcopy(self.state2_buffer), idxs), self.action_buffer[idxs], self.adv_buffer[idxs], \n self.rtg_buffer[idxs], self.logp_buffer[idxs], self.valid_actions_buffer[idxs], self.rew_buffer[idxs], self.done_buffer[idxs]]","def index(self):\n return copy.deepcopy(self._innercontainer)","def __iter__(self):\n buff = self.__buffer\n buff_size = self.__buffer_size\n\n # Create iterators\n readers = [iter(x) for x in self.__readers]\n\n # Keep a dict to store the bars that weren't yielded, and on the\n # next iteration, replace the yielded bar with one from the reader that\n # bar came from.\n bars = {i: next(x, None) for i, x in enumerate(readers)}\n\n # Remove any Nones\n bars = {k: v for k, v in bars.items() if v is not None}\n\n # On each iteration, yield the earliest bar.\n while bars:\n # Get bar with smallest timestamp and yield it\n min_index, bar = min(bars.items(), key=lambda x: x[1][\"timestamp\"])\n bar_obj = Bar(**bar)\n self.__length += 1\n if buff is not None:\n buff.append(bar_obj)\n if len(buff) > buff_size:\n buff.pop(0)\n yield bar_obj\n\n # Get the next bar and replace the yielded bar with it.\n # If there are no more bars in that reader, remove the\n # iterator and close the reader.\n next_bar = next(readers[min_index], None)\n if next_bar is None:\n del bars[min_index]\n readers[min_index].close()\n else:\n bars[min_index] = next_bar","def get_downstream_objects(obj):\n # gcl = gc.get_objects()\n olist = []\n seen = {}\n # Just in case:\n # seen[id(gcl)] = None\n seen[id(olist)] = None\n seen[id(seen)] = None\n # _getr does the real work.\n _getr([obj], olist, seen)\n return olist","def getAllAndClearBuffer(self):\n data = self.dataBuffer\n\n self.dataBuffer = []\n self.timestamps = []\n\n return data","def get_merged_buffers(ptr):\n\n\thdata = weechat.hdata_get(\"buffer\")\n\tbuffers = weechat.hdata_get_list(hdata, \"gui_buffers\")\n\tbuffer = weechat.hdata_search(hdata, buffers, \"${buffer.number} == %i\" % weechat.hdata_integer(hdata, ptr, \"number\"), 1)\n\tnbuffer = weechat.hdata_move(hdata, buffer, 1)\n\n\tret = []\n\twhile buffer:\n\t\tret.append(weechat.hdata_string(hdata, buffer, \"full_name\"))\n\n\t\tif (weechat.hdata_integer(hdata, buffer, \"number\") == weechat.hdata_integer(hdata, nbuffer, \"number\")):\n\t\t\tbuffer = nbuffer\n\t\t\tnbuffer = weechat.hdata_move(hdata, nbuffer, 1)\n\t\telse:\n\t\t\tbuffer = None\n\n\treturn ret","def create_buffers(self):","def GetMainBuffer(self):\n tmp = self.buffers[0]\n self.buffers[0] = []\n return tmp","def read_buffer(self):\n data = []\n\n # loop until the buffer was completely read out\n while True:\n new = [float(n) for n in self.read(\":FETC:ARR? MAX\").split(\",\") if n]\n data += new\n\n if len(new) < self.batch_size:\n break\n\n return data","def index(self):\n return list(self._innercontainer)","def get_all_objects():\n gc.collect()\n gcl = gc.get_objects()\n olist = []\n seen = {}\n # Just in case:\n seen[id(gcl)] = None\n seen[id(olist)] = None\n seen[id(seen)] = None\n # _getr does the real work.\n _getr(gcl, olist, seen)\n return olist","def RefBuffer(self):\n return self.buffers[self.buffergrade]","def get_items_to_index(self):\n\t\treturn []","def __call__(self):\n self._count += 1\n return []","def as_buffer(\n cls,\n obj: torch.Tensor,\n counts: Tuple[int] = None,\n displs: Tuple[int] = None,\n is_contiguous: Optional[bool] = None,\n ) -> List[Union[MPI.memory, Tuple[int, int], MPI.Datatype]]:\n squ = False\n if not obj.is_contiguous() and obj.ndim == 1:\n # this makes the math work below this function.\n obj.unsqueeze_(-1)\n squ = True\n\n mpi_type, elements = cls.mpi_type_and_elements_of(obj, counts, displs, is_contiguous)\n mpi_mem = cls.as_mpi_memory(obj)\n if squ:\n # the squeeze happens in the mpi_type_and_elements_of function in the case of a\n # non-contiguous 1D tensor. Squeezing it puts the memory back to where it should be\n obj.squeeze_(-1)\n return [mpi_mem, elements, mpi_type]","def hbObjects(self):\r\n return self.__hbObjs","def fetch(self, n: int) -> t.List[Record]:\n self._buffer(n)\n return [\n self._record_buffer.popleft()\n for _ in range(min(n, len(self._record_buffer)))\n ]","def create_buffer(self, cursor, n):\n buffer = []\n for c in cursor:\n buffer.append(c)\n if len(buffer) >= n:\n yield buffer\n buffer = []\n yield buffer","def get_data(queue, item_count):\n return [loads(queue.get()) for _ in range(item_count)]","def _next(self):\n i = 0\n while i < self.size:\n yield self.data[i]\n i += 1","def next(self) -> List[object]:\n ...","def Buffer(self) -> _n_0_t_7[_n_0_t_6]:","def Buffer(self) -> _n_0_t_7[_n_0_t_6]:","def Buffer(self) -> _n_0_t_7[_n_0_t_6]:","def getBufferedData(self):\n if not self.ringBuffer: # first time when buffer is empty\n return np.zeros((1, self.windowLength, self.sensorChannels)) \n return np.array(self.ringBuffer)","def get_from_head(self, total_count = 1) -> list:\n return self.queue.get_all(total_count)","def _read(self):\n return np.copy(self.memory[self.head_pos])","def list(self):\n return self.cell.objects+self.cell.tempObjects","def get_all_objects():\n gcl = gc.get_objects()\n olist = []\n seen = {}\n # Just in case:\n seen[id(gcl)] = None\n seen[id(olist)] = None\n seen[id(seen)] = None\n # _getr does the real work.\n _getr(gcl, olist, seen)\n return olist","def get_buffer(self):\n \n # Get sources for documents which are in elasticsearch\n # and they are not in local buffer\n if self.doc_to_get: self.update_sources()\n \n ES_buffer = deepcopy(self.action_buffer)\n self.action_buffer = []\n self.sources = {}\n return ES_buffer","def forward(self):\n blobs = self._get_next_minibatch()\n return blobs","def enumerate(self):\n # go through the container and tile in sync\n for index, value in zip(self.tile, self.data):\n # hand the {index} and the corresponding value to the caller\n yield index, value\n # all done\n return","def reindex_graphics(self):\n for obj in self.context.static_objects:\n self.canvas.children.remove(obj.widget.canvas)\n # fill _objects_z_index\n _objects_z_index = {}\n for obj in self.context.static_objects:\n y = obj.widget.pos[1]\n if not y in _objects_z_index:\n _objects_z_index[y] = []\n _objects_z_index[y].append(obj)\n _keys = _objects_z_index.keys()\n _keys.sort()\n _keys.reverse()\n for k in _keys:\n objs = _objects_z_index[k]\n for obj in objs:\n self.canvas.add(obj.widget.canvas)","def _get_obs(self):\n pos = []\n z = []\n for i in range(params['memory_size']):\n if self._step - i * params['memory_size'] > 1:\n pos.append(self._track_item['joint_pos'][self._step - i * params['memory_size'] - 1].copy())\n z.append(self._track_item['z'][self._step - i * params['memory_size'] - 1].copy())\n else:\n pos.append(self._track_item['joint_pos'][0].copy())\n if len(self._track_item['z']) < 1:\n z.append(self.z.copy())\n else:\n z.append(self._track_item['z'][0].copy())\n out = pos\n if params['observation_version'] == 1:\n out += z\n ob = {\n 'observation' : np.concatenate(out, -1),\n 'desired_goal' : self.desired_goal.copy(),\n 'achieved_goal' : self.achieved_goal.copy(),\n 'z' : self.z.copy()\n }\n return ob","def all(self):\n if self._writer._buffer == deque([]):\n raise RuntimeError(\"Writer buffer is empty.\")\n # Read first file to get structure\n data0 = self._writer._buffer[0]\n return self._expand(data0)","def __iter__(self):\n try:\n self._load(False)\n except KeyError:\n return iter([])\n\n return self._iter(self.head - self.count, self.count)","def _tobuffer(self, object_):\n\n raise NotImplementedError","def __getitem__(self, idx):\n return self.batches[idx]","def _bucketing(self):\n bucket = []\n if self.bucket_size_init > 0:\n _bucket_size = self.bucket_size_init\n else:\n _bucket_size = self.bucket_size\n for ex in self.mixer:\n bucket.append(ex)\n if len(bucket) == _bucket_size:\n yield self._tuple_to_json_with_tokIDs(bucket)\n bucket = []\n if _bucket_size < self.bucket_size:\n _bucket_size += self.bucket_size_increment\n else:\n _bucket_size = self.bucket_size\n if bucket:\n yield self._tuple_to_json_with_tokIDs(bucket)","def objects(self):\n\t\treturn self._objects","def fetch(self, messages, uid):\n return list(zip(range(1, len(self.msgObjs) + 1), self.msgObjs))","def get_all_objects():\n gcl = gc.get_objects()\n olist = []\n seen = {}\n # Just in case:\n seen[id(gcl)] = None\n seen[id(olist)] = None\n seen[id(seen)] = None\n # _getr does the real work.\n _getr(gcl, olist, seen)\n return olist","def pull_buffer(self, last_shared_index):\n buffer = []\n explicit_buffer = []\n\n # report_implicit_count = 0\n # report_last_shared_time = self.ledger[last_shared_index][\"time\"]\n # report_now_last_shared_time = rospy.get_rostime()\n # report_duration = report_now_last_shared_time - report_last_shared_time\n\n meas_dict = self._get_shareable_meas_dict(last_shared_index)\n print(\"PULLING BUFFER: current index {}\".format(len(self.ledger)))\n for msg_id in meas_dict:\n times = meas_dict[msg_id][\"times\"] # Should be sorted\n explicit = meas_dict[msg_id][\"explicit\"]\n bursts = self._get_bursts(times)\n # print(\"Delta: {} | Msg id: {} | Num Explicit: {}\".format(self.delta_multiplier, msg_id, len(explicit)))\n # print(\"size(times): {}\".format(len(times)))\n # print(\"size(explicit): {}\".format(len(explicit)))\n # print(\"bursts: {}\".format(bursts))\n\n if len(bursts) > 1:\n print(\"ERROR MULTIPLE BURSTS DETECTED\")\n print(bursts)\n\n b = bursts[-1] # Only use last burst\n b_numpy = np.array(b)\n start_time = b[0]\n # print(\"Constructing msg: {}\".format(msg_id))\n if len(b) > 1:\n cumdiff = b_numpy[1:] - b_numpy[:-1] # Get the adjacent difference\n latencies = [lat.to_sec() for lat in cumdiff]\n mean_lat = np.mean(latencies)\n # print(\"Avg latency: {}\".format(mean_lat))\n else:\n mean_lat = 0\n # print(\"Num msgs: {}\".format(len(b)))\n burst_msg = self._make_burst_msg(msg_id, len(b), start_time, mean_lat)\n buffer.append( burst_msg )\n explicit_buffer.extend( explicit )\n # report_implicit_count += (len(b) - len(explicit))\n \n meas_sort = lambda x : x.stamp\n explicit_buffer.sort(key=meas_sort, reverse=True)\n buffer.extend(explicit_buffer)\n\n # REPORT\n # print(\"******* BUFFER SHARING REPORT FOR {} w/ Delta {}*******\".format(self.my_name, self.delta_multiplier))\n # print(\"Last shared time: {}\".format(report_last_shared_time.to_sec()))\n # print(\"Sharing duration: {}\".format(report_duration.to_sec()))\n # print(\"Sharing time now: {}\".format(report_now_last_shared_time.to_sec()))\n # print(\"Implicit cnt: {}\".format(report_implicit_count))\n # print(\"Explicit cnt: {}\".format(len(explicit_buffer)))\n\n return buffer # Delta-Tiering\n # return explicit_buffer # N-most recent","def search_buffer(self):\n id1 = list(self.f.read_ui8(2))\n search_cnt = 0\n fd = self.f\n if self._debug_level > 3:\n print(' -->In search_buffer...')\n while (search_cnt < self._search_num and\n ((id1[0] != 127 or id1[1] != 127) or\n not self.checkheader())):\n search_cnt += 1\n nextbyte = fd.read_ui8(1)\n id1[1] = id1[0]\n id1[0] = nextbyte\n if search_cnt == self._search_num:\n raise Exception(\n 'Searched {} entries... Bad data encountered. -> {}'\n .format(search_cnt, id1))\n elif search_cnt > 0:\n if self._debug_level > 0:\n print(' WARNING: Searched {} bytes to find next '\n 'valid ensemble start [{:x}, {:x}]'.format(search_cnt,\n *id1))","def iter(self):\n return []","def GetItemsFromIterablesCached(self):\n items = []\n assert len(self.state_id) == len(self.iterables)\n for iter_num, iter_counter in enumerate(self.state_id):\n item = self.history_items[iter_num].get(iter_counter+1, \"unexplored\")\n if item == \"unexplored\":\n try:\n item = self.iterables[iter_num].next()\n except StopIteration:\n item = None\n self.history_items[iter_num][iter_counter+1] = item\n items.append(item)\n return items","def __iter__(self,):\n self.f.seek(self.pos)\n data = self.f.read(BUFFER_SZ)\n while data:\n while self.dataptr < len(data):\n self.dataptr += 1\n yield data[self.dataptr - 1]\n\n self.pos = self.f.tell()\n self.dataptr = 0\n data = self.f.read(BUFFER_SZ)","def objects(self):","def get_all(self, start_at, limit, order=None):\n result = []\n objects = []\n if limit == 0:\n objects = self.items[start_at:]\n else:\n objects = self.items[start_at:(start_at + limit)]\n for item in objects:\n result.append(FileDict(item))\n return result","def _elements(self):\n return list(islice(self.generate(), None))","def getContents(self):\r\n cont=[]\r\n for i in range (len(self._indices)):\r\n cont.append(self._dataset.getPoint(self._indices[i]))\r\n return cont","def get_buffer(self, i):\n\n if i not in range(1, self.NUM_BUFFERS + 1):\n raise IndexError(\"Error: Could not get buffer %d. Must be \"\n \"between 1 and 9\" % i)\n return self.m_param[i]","def next_object(self):\n if not self._buffer_size():\n return None\n return next(self.delegate)","def buffers_with_matches(self):\n _set = set(self.misc.buffers()) & set(self.matches.keys())\n _set.add(self.curr_buf.number)\n return list(_set)","def get_data(self):\n idxs = self.get_indexes(self._start, self._length, self.maxsize)\n return self._data[idxs].copy()","def sort_objects_from_viewworld(self, viewworld):\n opaque_objects = []\n transparent_objects = []\n centers = []\n for guid in self.objects:\n obj = self.objects[guid]\n if isinstance(obj, BufferObject):\n if obj.opacity * self.opacity < 1 and obj.bounding_box_center is not None:\n transparent_objects.append(obj)\n centers.append(transform_points_numpy([obj.bounding_box_center], obj.matrix)[0])\n else:\n opaque_objects.append(obj)\n if transparent_objects:\n centers = transform_points_numpy(centers, viewworld)\n transparent_objects = sorted(zip(transparent_objects, centers), key=lambda pair: pair[1][2])\n transparent_objects, _ = zip(*transparent_objects)\n return opaque_objects + list(transparent_objects)","def index_object(idxs=None):","def __init__(self,size=10):\n \n self.inbound = Queue() #an internal queue to manage the class properly in a thread safe manner.\n self.index = Value('i',0) #index of next item to be added.\n self.manager = Manager()\n \n self.buffer = self.manager.list() #the buffer we will store things in.\n self.size = size #the maximum size of the buffer\n self.newitem = Queue() #a blocking event to control the pop method\n t = threading.Thread(target=self.worker) #the worker that will run when items are added.\n t.start() #start the worker\n self.newitemindex = 0 #index of items to pop","def _refresh_buffers(self) -> None:","def getChunks():","def __iter__(self):\n cursor = 0\n while cursor < len(self):\n yield self._items[cursor]\n cursor += 1","def read(self,getindex):\n if getindex<0:\n #print(\"Indicies are non-negative\")\n return None\n try:\n bufinx = len(self.buffer)+(getindex - self.index.value)\n if bufinx<0:\n #print(\"This item has been deleted, try increasing the queue size\")\n return None\n return self.buffer[bufinx]\n except IndexError:\n #print(\"This item doesn't exist yet\")\n return None","def get_last(self, count):\n result = self.items[-count:]\n # Reverse the count\n objects = []\n result.reverse()\n for item in result:\n objects.append(FileDict(item))\n return objects","def positions(self):\n return self.preorder() # return entire preorder iteration","def objects(self):\n _, c = self.get_column(0)\n size = len(c)\n headers = self.headers()\n for i in range(size):\n obj = {}\n for h in headers:\n _, col = self.get_column(h)\n val = col[i]\n obj[h] = val\n yield obj","def bufferView( self ):\n if not self.buffer:\n raise AttributeError( 'No buffer currently' )\n buffer = self.buffer.buffer\n # okay, now slice-and-dice it...\n # TODO: watch for cases where the buffer is something \n # other than the native-size? Shouldn't be possible given \n # the typed nature of the buffer property.\n if self.bufferKey:\n # pull out just the first items (this property) from the \n # buffer, will *likely* want to collapse with .view() as well...\n return buffer[self.bufferKey][:,0].view( '%sf'%( self.size,))\n shape = buffer.shape\n offset = self.offset//buffer.itemsize\n stride = self.stride//buffer.itemsize\n # okay, are we a multi-dimensional buffer?\n if len(shape) == 2:\n if stride%shape[-1]:\n # is not evenly divisble...\n raise ValueError( \n \"\"\"Stride %s is not evenly divisible into matrix shape %s\"\"\"%(\n stride, shape\n ) \n )\n else:\n step = stride//shape[-1]\n # TODO: support higher-order shapes\n if step > 1:\n return buffer[::step,offset:offset+self.size]\n else:\n return buffer[:,offset:offset+self.size]\n elif len(shape) == 1:\n # we're a ravelled array...\n buffer = reshape( buffer, (-1,stride))\n return buffer[:,offset:offset+self.size]\n else:\n raise NotImplemented( \n \"\"\"Haven't implemented view support for N dimensional arrays\"\"\"\n )","def __getitem__(self, index):\r\n\r\n # Generate indexes of the batch\r\n indexes = self.indexes[index * self.batch_size:(index + 1) * self.batch_size]\r\n\r\n # Find list of IDs\r\n list_ids_temp = [self.list_IDs[k] for k in indexes]\r\n\r\n # Calls function to load batch of data into memory\r\n X, y = self.__data_generation(list_ids_temp)\r\n\r\n return X, y","def merge(self, bufr, x=0.0, y=0.0, z=0.0,\r\n rx=0.0, ry=0.0, rz=0.0,\r\n sx=1.0, sy=1.0, sz=1.0):\r\n if not isinstance(bufr, list) and not isinstance(bufr, tuple):\r\n buflist = [[bufr, x, y, z, rx, ry, rz, sx, sy, sz]]\r\n else:\r\n buflist = bufr\r\n\r\n for b in buflist:\r\n if not(type(b[0]) is Buffer):\r\n bufr = b[0].buf[0]\r\n else:\r\n bufr = b[0]\r\n\r\n #assert shape.ttype == GL_TRIANGLES # this is always true of Buffer objects\r\n assert len(bufr.vertices) == len(bufr.normals)\r\n\r\n if VERBOSE:\r\n print(\"Merging\", bufr.name)\r\n\r\n original_vertex_count = len(self.vertices)\r\n\r\n for v in range(0, len(bufr.vertices)):\r\n # Scale, offset and store vertices\r\n vx, vy, vz = rotate_vec(b[4], b[5], b[6], bufr.vertices[v])\r\n self.vertices.append((vx * b[7] + b[1], vy * b[8] + b[2], vz * b[9] + b[3]))\r\n\r\n # Rotate normals\r\n self.normals.append(rotate_vec(b[4], b[5], b[6], bufr.normals[v]))\r\n\r\n self.tex_coords.extend(bufr.tex_coords)\r\n\r\n ctypes.restype = ctypes.c_short # TODO: remove this side-effect.\r\n indices = [(i[0] + original_vertex_count, i[1] + original_vertex_count,\r\n i[2] + original_vertex_count) for i in bufr.indices]\r\n self.indices.extend(indices)\r\n\r\n self.buf = []\r\n self.buf.append(Buffer(self, self.vertices, self.tex_coords, self.indices, self.normals))","def __getitem__(self, index):\n # Generate indexes of the batch\n folder_id, file_id, el_id = self.index_to_ids(index)\n folder_id = self.idx_folder[folder_id]\n file_id = self.idx_file[file_id]\n el_ids = self.idx_el[el_id*self.batch_size + np.arange(self.batch_size)]\n self.current_b = el_ids\n return self.__data_generation(folder_id, file_id, el_ids)","def __getitem__(self, index):\n # Generate indexes of the batch\n folder_id, file_id, el_id = self.index_to_ids(index)\n folder_id = self.idx_folder[folder_id]\n file_id = self.idx_file[file_id]\n el_ids = self.idx_el[el_id*self.batch_size + np.arange(self.batch_size)]\n self.current_b = el_ids\n return self.__data_generation(folder_id, file_id, el_ids)","def __getitem__(self, i):\n\t\treturn self._blocks[i]","def buffered_read(file_object, chunk_size=1024):\n while True:\n data = file_object.read(chunk_size)\n if not data:\n break\n yield data","def peek(\n self,\n count: int = 1,\n ) -> List[T]:\n buffer = self._buffer\n buffer_len = len(buffer)\n\n if count > buffer_len:\n buffer.extend(islice(self._iterator, count - buffer_len))\n\n return list(islice(buffer, count))","def __getitem__(self, idx):\n assert isinstance(\n idx, (int, slice)), \"Index Could be an integer or a slice\"\n\n if isinstance(idx, int) and idx < 0:\n for cur_index in range(-idx):\n obj, pos = self.__get_json_from_end()\n if -cur_index - 1 == idx:\n return json.loads(obj, encoding=\"utf-8\")\n raise IndexError\n\n if isinstance(idx, slice):\n to_extract = (elm for elm in gen_increasing_slice(idx))\n else:\n to_extract = [idx]\n\n results = []\n\n for target_idx in to_extract:\n self.__descriptor.seek(0, 0)\n cur_idx = 0\n\n checkpoint = self.__get_checkpoint(target_idx)\n if checkpoint != False:\n self.__descriptor.seek(checkpoint[1])\n cur_idx = checkpoint[0]\n self.__last_index = checkpoint[0]\n self.__last_index_pos = checkpoint[1]\n\n if self.__last_index > cur_idx and target_idx > self.__last_index:\n self.__descriptor.seek(self.__last_index_pos)\n cur_idx = self.__last_index\n\n for obj, start in iter(lambda: self.__get_json(), (None, -1)):\n last_obj = obj\n self.__last_index_pos = start\n self.__last_index = cur_idx\n\n if cur_idx == target_idx:\n results.append(json.loads(last_obj, encoding=\"utf-8\"))\n break\n\n cur_idx += 1\n\n if isinstance(idx, slice):\n if idx.start is not None and idx.stop is not None and idx.start > idx.stop:\n return list(reversed(results))\n return results\n else:\n return results.pop(0)","def enumerate(self):\r\n return enumerate(self, 1)","def unbucketed_next(self):\n # Initialize batch containers\n label_batch = list()\n enc_input_batch = list()\n dec_input_batch = list()\n # Fill individual batches by iterating over the entire data source\n if self.sent_id < self.get_length():\n while len(enc_input_batch) < self.opt.batch_size:\n try:\n indexed_sent = self.data[self.sent_id]\n label_item = indexed_sent[1:]\n enc_input_item = indexed_sent[1:]\n # Reverse the input to the encoder, see arxiv.org/pdf/1703.03906.pdf\n enc_input_item.reverse()\n dec_input_item = indexed_sent[:-1]\n label_batch.append(label_item)\n enc_input_batch.append(enc_input_item)\n dec_input_batch.append(dec_input_item)\n self.sent_id += 1\n except IndexError:\n break\n else:\n raise IndexError\n return label_batch, enc_input_batch, dec_input_batch","def objects(self):\r\n return self._objects","def __pos__(self):\n ret = copy.deepcopy(self)\n for row in ret:\n if __debug__:\n assert hasattr(row, '__iter__'), repr(row) + \" | \" + repr(ret)\n assert len(row) <= len(ret.header), 'header needs to be larger or equal to all! ({},{})'.\\\n format(row, ret.header)\n for i in range(len(ret.header) - len(row)):\n row.append(None)\n return ret","def retrieve(self, indices):\n obses_t, actions, rewards, obses_tp1, dones = [], [], [], [], []\n for i in indices:\n if i == 0:\n i = 1\n data = self._storage[i]\n obs_t, action, reward, obs_tp1, done = data\n obses_t.append(np.array(obs_t, copy=False))\n actions.append(np.array(action, copy=False))\n rewards.append(reward)\n obses_tp1.append(np.array(obs_tp1, copy=False))\n dones.append(done)\n return np.array(obses_t), np.array(actions), np.array(rewards), np.array(obses_tp1), np.array(dones)","def __iter__(self):\n\n # collector will fetch chunksize array for each 'get' call\n collector = FIFOArray(self.chunksize, self.axis)\n\n # make tmp array to hold generated subarrs\n tmp = []\n tmp_size = 0\n for subarr in self.data(**self.kwargs):\n\n tmp.append(subarr)\n tmp_size += subarr.shape[self.axis]\n\n # if tmp exceeds chunksize put in collector\n if tmp_size >= self.chunksize:\n arr = np.concatenate(tmp, axis=self.axis)\n collector.put(arr)\n\n # fetch chunksize till not full\n while collector.full():\n yield collector.get()\n\n # place leftover back into tmp and empty collector\n tmp = [collector.queue]\n tmp_size = collector.qsize()\n collector.queue = np.array([])\n\n else:\n\n # append to tmp again\n continue\n\n # else runs after normal loop exit -- required here\n else: #pylint: disable=useless-else-on-loop\n\n # yield whatever is left in tmp (its below chunksize)\n remaining = np.concatenate(tmp, axis=self.axis)\n if remaining.size > 0:\n yield remaining","def sort_chunks(self):\n\n first = True\n\n all_chunks = dict(self.dirty_chunk_cache)\n all_chunks.update(self.chunk_cache)\n self.chunk_cache.clear()\n self.dirty_chunk_cache.clear()\n for coords, chunk in all_chunks.iteritems():\n if chunk.dirty:\n if first:\n first = False\n self.save_chunk(chunk)\n self.chunk_cache[coords] = chunk\n else:\n self.dirty_chunk_cache[coords] = chunk\n else:\n self.chunk_cache[coords] = chunk","def __iter__(self):\n n = self.head\n for _ in range(len(self)):\n if n == self.capacity:\n n = 0\n yield self.lst[n]\n n += 1","def _filesync_read_buffered(self, size, adb_info, filesync_info):\n # Ensure recv buffer has enough data.\n while len(filesync_info.recv_buffer) < size:\n _, data = self._read_until([constants.WRTE], adb_info)\n filesync_info.recv_buffer += data\n\n result = filesync_info.recv_buffer[:size]\n filesync_info.recv_buffer = filesync_info.recv_buffer[size:]\n return result"],"string":"[\n \"def get(self):\\n assert self.ptr == self.max_size\\n self.ptr, self.path_start_idx = 0, 0\\n return [self.obs_buf, self.act_buf, self.adv_buf, self.ret_buf, self.val_buf]\",\n \"def BufferList(self) -> _n_2_t_0[_n_0_t_11[_n_0_t_6]]:\",\n \"def __getitem__(self, index):\\n return self.buffer[index]\",\n \"def _readIdxBuf(self):\\n base = self.fres.bufferSection['buf_offs']\\n self.idx_buf = self.fres.read(self.idx_fmt,\\n pos = self.header['face_offs'] + base,\\n count = self.header['idx_cnt'])\\n\\n for i in range(self.header['idx_cnt']):\\n self.idx_buf[i] += self.header['visibility_group']\",\n \"def get_batch(self):\\n result = self.buffer_.get()\\n self._async_next()\\n return result\",\n \"def get_batch(self):\\n result = self.buffer_.get()\\n self._async_next()\\n return result\",\n \"def _buffer_all(self):\\n self._buffer()\",\n \"def getAll(self):\\n return self.dataBuffer\",\n \"def cbuffers(self):\\r\\n self._core.sym.assert_have_symbols()\\r\\n\\r\\n cbuffer_name_key = \\\"cbuffer_struc$\\\"\\r\\n cbuffer_name_key_len = len(cbuffer_name_key)\\r\\n cbuffers = self._core.sym.varfind(cbuffer_name_key)\\r\\n cbuffers.sort()\\r\\n\\r\\n print \\\" \\\" * 30 + \\\"C-Buffer Size Read Addr Write Addr Start Space Data\\\"\\r\\n\\r\\n # The results from varfind are unfortunately tuples -- one simply has to know the correct indices.\\r\\n for (struct_name, size_in_addressable_units, struct_address) in cbuffers:\\r\\n # Order of fields in the structure: size, read pointer, write pointer.\\r\\n (sz, rd, wr) = self._read_var_with_size_check(struct_address, size_in_addressable_units)\\r\\n\\r\\n struct_name = struct_name[:-cbuffer_name_key_len]\\r\\n print \\\"%38s\\\" % struct_name,\\r\\n\\r\\n if sz != 0:\\r\\n # Find start address of the buffer\\r\\n mask = int(2**math.ceil(math.log(sz, 2)) - 1)\\r\\n start_addr = rd - (rd & mask)\\r\\n if start_addr != (wr - (wr & mask)):\\r\\n print '\\\\n\\\\n** Warning the start address calculated from the read',\\r\\n print 'and write pointers is different! **'\\r\\n\\r\\n amount_space = rd - wr\\r\\n if amount_space <= 0:\\r\\n amount_space += sz\\r\\n amount_space -= 1\\r\\n amount_data = wr - rd\\r\\n if amount_data < 0:\\r\\n amount_data += sz\\r\\n\\r\\n print ' %4d 0x%06x 0x%06x 0x%06x %4d %4d' % \\\\\\r\\n (sz, rd, wr, start_addr, amount_space, amount_data)\\r\\n else:\\r\\n print \\\"size=0\\\"\",\n \"def items(self):\\n out = []\\n for y,x in self.coords(False):\\n out.append(self.retrieve(y, x))\\n return out\",\n \"def test_benchmark_BufferedGraphReader_in_order(\\n benchmark, db_10000: graph_tuple_database.Database, buffer_size_mb: int,\\n):\\n benchmark(\\n list,\\n reader.BufferedGraphReader(\\n db_10000,\\n buffer_size_mb=buffer_size_mb,\\n order=reader.BufferedGraphReaderOrder.IN_ORDER,\\n ),\\n )\",\n \"def object_block(data, pos, player_number, index):\\n objects = []\\n offset = None\\n while True:\\n if not offset:\\n match = REGEXES[player_number].search(data, pos)\\n end = data.find(BLOCK_END, pos) - pos + len(BLOCK_END)\\n if match is None:\\n break\\n offset = match.start() - pos\\n while end + 8 < offset:\\n end += data.find(BLOCK_END, pos + end) - (pos + end) + len(BLOCK_END)\\n if end + 8 == offset:\\n break\\n pos += offset\\n # Speed optimization: Skip specified fixed-length objects.\\n test = data[pos:pos + 4]\\n for fingerprint, offset in SKIP_OBJECTS:\\n if test == fingerprint:\\n break\\n else:\\n objects.append(dict(parse_object(data, pos), index=index))\\n offset = None\\n pos += 31\\n return objects, pos + end\",\n \"def get_all(self):\\r\\n if self.filled_rows < self.rows:\\r\\n return np.roll(self._data, -(self.curr_pos + self.rows - self.filled_rows),\\r\\n axis=0)[:self.filled_rows,:]\\r\\n else:\\r\\n # The buffer has fewer lines in this case\\r\\n return np.roll(self._data, -self.curr_pos,\\r\\n axis=0)\",\n \"def _get_buffer(self):\\n return memoryview(self._write_buffer)[: self._buffer_seek]\",\n \"def alltoall_recvbuffer(\\n self, obj: torch.Tensor\\n ) -> List[Union[MPI.memory, Tuple[int, int], MPI.Datatype]]:\\n mpi_type, _ = self.__mpi_type_mappings[obj.dtype], torch.numel(obj)\\n\\n nproc = self.size\\n shape = obj.shape[1:]\\n strides = [1] * len(shape)\\n strides[0] = obj.stride()[-1]\\n strides = strides[::-1]\\n offsets = [obj.element_size() * stride for stride in obj.stride()[:-1]]\\n\\n # Step 1: Wrap along axes > 0 (all axes except recv_axis)\\n for i in range(len(shape) - 1, -1, -1):\\n mpi_type = mpi_type.Create_vector(shape[i], 1, strides[i]).Create_resized(0, offsets[i])\\n mpi_type.Commit()\\n\\n # Step 2: Receive blocks along the recv axis\\n # Prepare recvcount, senddispls and sendtypes for alltoallw\\n recvcount = np.full((nproc,), obj.shape[0] // nproc)\\n recvcount[: obj.shape[0] % nproc] += 1\\n # size/extent of mpitype = offsets[0]\\n tmp_displs = [0] * nproc\\n tmp_displs[1:] = np.cumsum(recvcount[:-1])\\n recvdispls = [offsets[0] * d for d in tmp_displs]\\n recvtypes = [mpi_type] * nproc\\n\\n return self.as_mpi_memory(obj), (recvcount, recvdispls), recvtypes\",\n \"def worker(self):\\n while True:\\n item,index = self.inbound.get()\\n if index is None:\\n self.buffer.append(item)\\n self.index.value = self.index.value + 1 #index of next item for buffer\\n if len(self.buffer)>self.size:\\n del self.buffer[0]\\n self.newitem.put(None)\\n else:\\n self.buffer[len(self.buffer)+(index - self.index.value)] = item\",\n \"def getBufferChildren(self, buffertop):\\n children = [v for k, v in self.GS_arcs if k == buffertop]\\n return children\",\n \"def spit(self):\\n idxs = np.arange(self.total_tuples)\\n return [self.recurse_index_state(copy.deepcopy(self.state_buffer), idxs), self.recurse_index_state(copy.deepcopy(self.state2_buffer), idxs), self.action_buffer[idxs], self.adv_buffer[idxs], \\n self.rtg_buffer[idxs], self.logp_buffer[idxs], self.valid_actions_buffer[idxs], self.rew_buffer[idxs], self.done_buffer[idxs]]\",\n \"def index(self):\\n return copy.deepcopy(self._innercontainer)\",\n \"def __iter__(self):\\n buff = self.__buffer\\n buff_size = self.__buffer_size\\n\\n # Create iterators\\n readers = [iter(x) for x in self.__readers]\\n\\n # Keep a dict to store the bars that weren't yielded, and on the\\n # next iteration, replace the yielded bar with one from the reader that\\n # bar came from.\\n bars = {i: next(x, None) for i, x in enumerate(readers)}\\n\\n # Remove any Nones\\n bars = {k: v for k, v in bars.items() if v is not None}\\n\\n # On each iteration, yield the earliest bar.\\n while bars:\\n # Get bar with smallest timestamp and yield it\\n min_index, bar = min(bars.items(), key=lambda x: x[1][\\\"timestamp\\\"])\\n bar_obj = Bar(**bar)\\n self.__length += 1\\n if buff is not None:\\n buff.append(bar_obj)\\n if len(buff) > buff_size:\\n buff.pop(0)\\n yield bar_obj\\n\\n # Get the next bar and replace the yielded bar with it.\\n # If there are no more bars in that reader, remove the\\n # iterator and close the reader.\\n next_bar = next(readers[min_index], None)\\n if next_bar is None:\\n del bars[min_index]\\n readers[min_index].close()\\n else:\\n bars[min_index] = next_bar\",\n \"def get_downstream_objects(obj):\\n # gcl = gc.get_objects()\\n olist = []\\n seen = {}\\n # Just in case:\\n # seen[id(gcl)] = None\\n seen[id(olist)] = None\\n seen[id(seen)] = None\\n # _getr does the real work.\\n _getr([obj], olist, seen)\\n return olist\",\n \"def getAllAndClearBuffer(self):\\n data = self.dataBuffer\\n\\n self.dataBuffer = []\\n self.timestamps = []\\n\\n return data\",\n \"def get_merged_buffers(ptr):\\n\\n\\thdata = weechat.hdata_get(\\\"buffer\\\")\\n\\tbuffers = weechat.hdata_get_list(hdata, \\\"gui_buffers\\\")\\n\\tbuffer = weechat.hdata_search(hdata, buffers, \\\"${buffer.number} == %i\\\" % weechat.hdata_integer(hdata, ptr, \\\"number\\\"), 1)\\n\\tnbuffer = weechat.hdata_move(hdata, buffer, 1)\\n\\n\\tret = []\\n\\twhile buffer:\\n\\t\\tret.append(weechat.hdata_string(hdata, buffer, \\\"full_name\\\"))\\n\\n\\t\\tif (weechat.hdata_integer(hdata, buffer, \\\"number\\\") == weechat.hdata_integer(hdata, nbuffer, \\\"number\\\")):\\n\\t\\t\\tbuffer = nbuffer\\n\\t\\t\\tnbuffer = weechat.hdata_move(hdata, nbuffer, 1)\\n\\t\\telse:\\n\\t\\t\\tbuffer = None\\n\\n\\treturn ret\",\n \"def create_buffers(self):\",\n \"def GetMainBuffer(self):\\n tmp = self.buffers[0]\\n self.buffers[0] = []\\n return tmp\",\n \"def read_buffer(self):\\n data = []\\n\\n # loop until the buffer was completely read out\\n while True:\\n new = [float(n) for n in self.read(\\\":FETC:ARR? MAX\\\").split(\\\",\\\") if n]\\n data += new\\n\\n if len(new) < self.batch_size:\\n break\\n\\n return data\",\n \"def index(self):\\n return list(self._innercontainer)\",\n \"def get_all_objects():\\n gc.collect()\\n gcl = gc.get_objects()\\n olist = []\\n seen = {}\\n # Just in case:\\n seen[id(gcl)] = None\\n seen[id(olist)] = None\\n seen[id(seen)] = None\\n # _getr does the real work.\\n _getr(gcl, olist, seen)\\n return olist\",\n \"def RefBuffer(self):\\n return self.buffers[self.buffergrade]\",\n \"def get_items_to_index(self):\\n\\t\\treturn []\",\n \"def __call__(self):\\n self._count += 1\\n return []\",\n \"def as_buffer(\\n cls,\\n obj: torch.Tensor,\\n counts: Tuple[int] = None,\\n displs: Tuple[int] = None,\\n is_contiguous: Optional[bool] = None,\\n ) -> List[Union[MPI.memory, Tuple[int, int], MPI.Datatype]]:\\n squ = False\\n if not obj.is_contiguous() and obj.ndim == 1:\\n # this makes the math work below this function.\\n obj.unsqueeze_(-1)\\n squ = True\\n\\n mpi_type, elements = cls.mpi_type_and_elements_of(obj, counts, displs, is_contiguous)\\n mpi_mem = cls.as_mpi_memory(obj)\\n if squ:\\n # the squeeze happens in the mpi_type_and_elements_of function in the case of a\\n # non-contiguous 1D tensor. Squeezing it puts the memory back to where it should be\\n obj.squeeze_(-1)\\n return [mpi_mem, elements, mpi_type]\",\n \"def hbObjects(self):\\r\\n return self.__hbObjs\",\n \"def fetch(self, n: int) -> t.List[Record]:\\n self._buffer(n)\\n return [\\n self._record_buffer.popleft()\\n for _ in range(min(n, len(self._record_buffer)))\\n ]\",\n \"def create_buffer(self, cursor, n):\\n buffer = []\\n for c in cursor:\\n buffer.append(c)\\n if len(buffer) >= n:\\n yield buffer\\n buffer = []\\n yield buffer\",\n \"def get_data(queue, item_count):\\n return [loads(queue.get()) for _ in range(item_count)]\",\n \"def _next(self):\\n i = 0\\n while i < self.size:\\n yield self.data[i]\\n i += 1\",\n \"def next(self) -> List[object]:\\n ...\",\n \"def Buffer(self) -> _n_0_t_7[_n_0_t_6]:\",\n \"def Buffer(self) -> _n_0_t_7[_n_0_t_6]:\",\n \"def Buffer(self) -> _n_0_t_7[_n_0_t_6]:\",\n \"def getBufferedData(self):\\n if not self.ringBuffer: # first time when buffer is empty\\n return np.zeros((1, self.windowLength, self.sensorChannels)) \\n return np.array(self.ringBuffer)\",\n \"def get_from_head(self, total_count = 1) -> list:\\n return self.queue.get_all(total_count)\",\n \"def _read(self):\\n return np.copy(self.memory[self.head_pos])\",\n \"def list(self):\\n return self.cell.objects+self.cell.tempObjects\",\n \"def get_all_objects():\\n gcl = gc.get_objects()\\n olist = []\\n seen = {}\\n # Just in case:\\n seen[id(gcl)] = None\\n seen[id(olist)] = None\\n seen[id(seen)] = None\\n # _getr does the real work.\\n _getr(gcl, olist, seen)\\n return olist\",\n \"def get_buffer(self):\\n \\n # Get sources for documents which are in elasticsearch\\n # and they are not in local buffer\\n if self.doc_to_get: self.update_sources()\\n \\n ES_buffer = deepcopy(self.action_buffer)\\n self.action_buffer = []\\n self.sources = {}\\n return ES_buffer\",\n \"def forward(self):\\n blobs = self._get_next_minibatch()\\n return blobs\",\n \"def enumerate(self):\\n # go through the container and tile in sync\\n for index, value in zip(self.tile, self.data):\\n # hand the {index} and the corresponding value to the caller\\n yield index, value\\n # all done\\n return\",\n \"def reindex_graphics(self):\\n for obj in self.context.static_objects:\\n self.canvas.children.remove(obj.widget.canvas)\\n # fill _objects_z_index\\n _objects_z_index = {}\\n for obj in self.context.static_objects:\\n y = obj.widget.pos[1]\\n if not y in _objects_z_index:\\n _objects_z_index[y] = []\\n _objects_z_index[y].append(obj)\\n _keys = _objects_z_index.keys()\\n _keys.sort()\\n _keys.reverse()\\n for k in _keys:\\n objs = _objects_z_index[k]\\n for obj in objs:\\n self.canvas.add(obj.widget.canvas)\",\n \"def _get_obs(self):\\n pos = []\\n z = []\\n for i in range(params['memory_size']):\\n if self._step - i * params['memory_size'] > 1:\\n pos.append(self._track_item['joint_pos'][self._step - i * params['memory_size'] - 1].copy())\\n z.append(self._track_item['z'][self._step - i * params['memory_size'] - 1].copy())\\n else:\\n pos.append(self._track_item['joint_pos'][0].copy())\\n if len(self._track_item['z']) < 1:\\n z.append(self.z.copy())\\n else:\\n z.append(self._track_item['z'][0].copy())\\n out = pos\\n if params['observation_version'] == 1:\\n out += z\\n ob = {\\n 'observation' : np.concatenate(out, -1),\\n 'desired_goal' : self.desired_goal.copy(),\\n 'achieved_goal' : self.achieved_goal.copy(),\\n 'z' : self.z.copy()\\n }\\n return ob\",\n \"def all(self):\\n if self._writer._buffer == deque([]):\\n raise RuntimeError(\\\"Writer buffer is empty.\\\")\\n # Read first file to get structure\\n data0 = self._writer._buffer[0]\\n return self._expand(data0)\",\n \"def __iter__(self):\\n try:\\n self._load(False)\\n except KeyError:\\n return iter([])\\n\\n return self._iter(self.head - self.count, self.count)\",\n \"def _tobuffer(self, object_):\\n\\n raise NotImplementedError\",\n \"def __getitem__(self, idx):\\n return self.batches[idx]\",\n \"def _bucketing(self):\\n bucket = []\\n if self.bucket_size_init > 0:\\n _bucket_size = self.bucket_size_init\\n else:\\n _bucket_size = self.bucket_size\\n for ex in self.mixer:\\n bucket.append(ex)\\n if len(bucket) == _bucket_size:\\n yield self._tuple_to_json_with_tokIDs(bucket)\\n bucket = []\\n if _bucket_size < self.bucket_size:\\n _bucket_size += self.bucket_size_increment\\n else:\\n _bucket_size = self.bucket_size\\n if bucket:\\n yield self._tuple_to_json_with_tokIDs(bucket)\",\n \"def objects(self):\\n\\t\\treturn self._objects\",\n \"def fetch(self, messages, uid):\\n return list(zip(range(1, len(self.msgObjs) + 1), self.msgObjs))\",\n \"def get_all_objects():\\n gcl = gc.get_objects()\\n olist = []\\n seen = {}\\n # Just in case:\\n seen[id(gcl)] = None\\n seen[id(olist)] = None\\n seen[id(seen)] = None\\n # _getr does the real work.\\n _getr(gcl, olist, seen)\\n return olist\",\n \"def pull_buffer(self, last_shared_index):\\n buffer = []\\n explicit_buffer = []\\n\\n # report_implicit_count = 0\\n # report_last_shared_time = self.ledger[last_shared_index][\\\"time\\\"]\\n # report_now_last_shared_time = rospy.get_rostime()\\n # report_duration = report_now_last_shared_time - report_last_shared_time\\n\\n meas_dict = self._get_shareable_meas_dict(last_shared_index)\\n print(\\\"PULLING BUFFER: current index {}\\\".format(len(self.ledger)))\\n for msg_id in meas_dict:\\n times = meas_dict[msg_id][\\\"times\\\"] # Should be sorted\\n explicit = meas_dict[msg_id][\\\"explicit\\\"]\\n bursts = self._get_bursts(times)\\n # print(\\\"Delta: {} | Msg id: {} | Num Explicit: {}\\\".format(self.delta_multiplier, msg_id, len(explicit)))\\n # print(\\\"size(times): {}\\\".format(len(times)))\\n # print(\\\"size(explicit): {}\\\".format(len(explicit)))\\n # print(\\\"bursts: {}\\\".format(bursts))\\n\\n if len(bursts) > 1:\\n print(\\\"ERROR MULTIPLE BURSTS DETECTED\\\")\\n print(bursts)\\n\\n b = bursts[-1] # Only use last burst\\n b_numpy = np.array(b)\\n start_time = b[0]\\n # print(\\\"Constructing msg: {}\\\".format(msg_id))\\n if len(b) > 1:\\n cumdiff = b_numpy[1:] - b_numpy[:-1] # Get the adjacent difference\\n latencies = [lat.to_sec() for lat in cumdiff]\\n mean_lat = np.mean(latencies)\\n # print(\\\"Avg latency: {}\\\".format(mean_lat))\\n else:\\n mean_lat = 0\\n # print(\\\"Num msgs: {}\\\".format(len(b)))\\n burst_msg = self._make_burst_msg(msg_id, len(b), start_time, mean_lat)\\n buffer.append( burst_msg )\\n explicit_buffer.extend( explicit )\\n # report_implicit_count += (len(b) - len(explicit))\\n \\n meas_sort = lambda x : x.stamp\\n explicit_buffer.sort(key=meas_sort, reverse=True)\\n buffer.extend(explicit_buffer)\\n\\n # REPORT\\n # print(\\\"******* BUFFER SHARING REPORT FOR {} w/ Delta {}*******\\\".format(self.my_name, self.delta_multiplier))\\n # print(\\\"Last shared time: {}\\\".format(report_last_shared_time.to_sec()))\\n # print(\\\"Sharing duration: {}\\\".format(report_duration.to_sec()))\\n # print(\\\"Sharing time now: {}\\\".format(report_now_last_shared_time.to_sec()))\\n # print(\\\"Implicit cnt: {}\\\".format(report_implicit_count))\\n # print(\\\"Explicit cnt: {}\\\".format(len(explicit_buffer)))\\n\\n return buffer # Delta-Tiering\\n # return explicit_buffer # N-most recent\",\n \"def search_buffer(self):\\n id1 = list(self.f.read_ui8(2))\\n search_cnt = 0\\n fd = self.f\\n if self._debug_level > 3:\\n print(' -->In search_buffer...')\\n while (search_cnt < self._search_num and\\n ((id1[0] != 127 or id1[1] != 127) or\\n not self.checkheader())):\\n search_cnt += 1\\n nextbyte = fd.read_ui8(1)\\n id1[1] = id1[0]\\n id1[0] = nextbyte\\n if search_cnt == self._search_num:\\n raise Exception(\\n 'Searched {} entries... Bad data encountered. -> {}'\\n .format(search_cnt, id1))\\n elif search_cnt > 0:\\n if self._debug_level > 0:\\n print(' WARNING: Searched {} bytes to find next '\\n 'valid ensemble start [{:x}, {:x}]'.format(search_cnt,\\n *id1))\",\n \"def iter(self):\\n return []\",\n \"def GetItemsFromIterablesCached(self):\\n items = []\\n assert len(self.state_id) == len(self.iterables)\\n for iter_num, iter_counter in enumerate(self.state_id):\\n item = self.history_items[iter_num].get(iter_counter+1, \\\"unexplored\\\")\\n if item == \\\"unexplored\\\":\\n try:\\n item = self.iterables[iter_num].next()\\n except StopIteration:\\n item = None\\n self.history_items[iter_num][iter_counter+1] = item\\n items.append(item)\\n return items\",\n \"def __iter__(self,):\\n self.f.seek(self.pos)\\n data = self.f.read(BUFFER_SZ)\\n while data:\\n while self.dataptr < len(data):\\n self.dataptr += 1\\n yield data[self.dataptr - 1]\\n\\n self.pos = self.f.tell()\\n self.dataptr = 0\\n data = self.f.read(BUFFER_SZ)\",\n \"def objects(self):\",\n \"def get_all(self, start_at, limit, order=None):\\n result = []\\n objects = []\\n if limit == 0:\\n objects = self.items[start_at:]\\n else:\\n objects = self.items[start_at:(start_at + limit)]\\n for item in objects:\\n result.append(FileDict(item))\\n return result\",\n \"def _elements(self):\\n return list(islice(self.generate(), None))\",\n \"def getContents(self):\\r\\n cont=[]\\r\\n for i in range (len(self._indices)):\\r\\n cont.append(self._dataset.getPoint(self._indices[i]))\\r\\n return cont\",\n \"def get_buffer(self, i):\\n\\n if i not in range(1, self.NUM_BUFFERS + 1):\\n raise IndexError(\\\"Error: Could not get buffer %d. Must be \\\"\\n \\\"between 1 and 9\\\" % i)\\n return self.m_param[i]\",\n \"def next_object(self):\\n if not self._buffer_size():\\n return None\\n return next(self.delegate)\",\n \"def buffers_with_matches(self):\\n _set = set(self.misc.buffers()) & set(self.matches.keys())\\n _set.add(self.curr_buf.number)\\n return list(_set)\",\n \"def get_data(self):\\n idxs = self.get_indexes(self._start, self._length, self.maxsize)\\n return self._data[idxs].copy()\",\n \"def sort_objects_from_viewworld(self, viewworld):\\n opaque_objects = []\\n transparent_objects = []\\n centers = []\\n for guid in self.objects:\\n obj = self.objects[guid]\\n if isinstance(obj, BufferObject):\\n if obj.opacity * self.opacity < 1 and obj.bounding_box_center is not None:\\n transparent_objects.append(obj)\\n centers.append(transform_points_numpy([obj.bounding_box_center], obj.matrix)[0])\\n else:\\n opaque_objects.append(obj)\\n if transparent_objects:\\n centers = transform_points_numpy(centers, viewworld)\\n transparent_objects = sorted(zip(transparent_objects, centers), key=lambda pair: pair[1][2])\\n transparent_objects, _ = zip(*transparent_objects)\\n return opaque_objects + list(transparent_objects)\",\n \"def index_object(idxs=None):\",\n \"def __init__(self,size=10):\\n \\n self.inbound = Queue() #an internal queue to manage the class properly in a thread safe manner.\\n self.index = Value('i',0) #index of next item to be added.\\n self.manager = Manager()\\n \\n self.buffer = self.manager.list() #the buffer we will store things in.\\n self.size = size #the maximum size of the buffer\\n self.newitem = Queue() #a blocking event to control the pop method\\n t = threading.Thread(target=self.worker) #the worker that will run when items are added.\\n t.start() #start the worker\\n self.newitemindex = 0 #index of items to pop\",\n \"def _refresh_buffers(self) -> None:\",\n \"def getChunks():\",\n \"def __iter__(self):\\n cursor = 0\\n while cursor < len(self):\\n yield self._items[cursor]\\n cursor += 1\",\n \"def read(self,getindex):\\n if getindex<0:\\n #print(\\\"Indicies are non-negative\\\")\\n return None\\n try:\\n bufinx = len(self.buffer)+(getindex - self.index.value)\\n if bufinx<0:\\n #print(\\\"This item has been deleted, try increasing the queue size\\\")\\n return None\\n return self.buffer[bufinx]\\n except IndexError:\\n #print(\\\"This item doesn't exist yet\\\")\\n return None\",\n \"def get_last(self, count):\\n result = self.items[-count:]\\n # Reverse the count\\n objects = []\\n result.reverse()\\n for item in result:\\n objects.append(FileDict(item))\\n return objects\",\n \"def positions(self):\\n return self.preorder() # return entire preorder iteration\",\n \"def objects(self):\\n _, c = self.get_column(0)\\n size = len(c)\\n headers = self.headers()\\n for i in range(size):\\n obj = {}\\n for h in headers:\\n _, col = self.get_column(h)\\n val = col[i]\\n obj[h] = val\\n yield obj\",\n \"def bufferView( self ):\\n if not self.buffer:\\n raise AttributeError( 'No buffer currently' )\\n buffer = self.buffer.buffer\\n # okay, now slice-and-dice it...\\n # TODO: watch for cases where the buffer is something \\n # other than the native-size? Shouldn't be possible given \\n # the typed nature of the buffer property.\\n if self.bufferKey:\\n # pull out just the first items (this property) from the \\n # buffer, will *likely* want to collapse with .view() as well...\\n return buffer[self.bufferKey][:,0].view( '%sf'%( self.size,))\\n shape = buffer.shape\\n offset = self.offset//buffer.itemsize\\n stride = self.stride//buffer.itemsize\\n # okay, are we a multi-dimensional buffer?\\n if len(shape) == 2:\\n if stride%shape[-1]:\\n # is not evenly divisble...\\n raise ValueError( \\n \\\"\\\"\\\"Stride %s is not evenly divisible into matrix shape %s\\\"\\\"\\\"%(\\n stride, shape\\n ) \\n )\\n else:\\n step = stride//shape[-1]\\n # TODO: support higher-order shapes\\n if step > 1:\\n return buffer[::step,offset:offset+self.size]\\n else:\\n return buffer[:,offset:offset+self.size]\\n elif len(shape) == 1:\\n # we're a ravelled array...\\n buffer = reshape( buffer, (-1,stride))\\n return buffer[:,offset:offset+self.size]\\n else:\\n raise NotImplemented( \\n \\\"\\\"\\\"Haven't implemented view support for N dimensional arrays\\\"\\\"\\\"\\n )\",\n \"def __getitem__(self, index):\\r\\n\\r\\n # Generate indexes of the batch\\r\\n indexes = self.indexes[index * self.batch_size:(index + 1) * self.batch_size]\\r\\n\\r\\n # Find list of IDs\\r\\n list_ids_temp = [self.list_IDs[k] for k in indexes]\\r\\n\\r\\n # Calls function to load batch of data into memory\\r\\n X, y = self.__data_generation(list_ids_temp)\\r\\n\\r\\n return X, y\",\n \"def merge(self, bufr, x=0.0, y=0.0, z=0.0,\\r\\n rx=0.0, ry=0.0, rz=0.0,\\r\\n sx=1.0, sy=1.0, sz=1.0):\\r\\n if not isinstance(bufr, list) and not isinstance(bufr, tuple):\\r\\n buflist = [[bufr, x, y, z, rx, ry, rz, sx, sy, sz]]\\r\\n else:\\r\\n buflist = bufr\\r\\n\\r\\n for b in buflist:\\r\\n if not(type(b[0]) is Buffer):\\r\\n bufr = b[0].buf[0]\\r\\n else:\\r\\n bufr = b[0]\\r\\n\\r\\n #assert shape.ttype == GL_TRIANGLES # this is always true of Buffer objects\\r\\n assert len(bufr.vertices) == len(bufr.normals)\\r\\n\\r\\n if VERBOSE:\\r\\n print(\\\"Merging\\\", bufr.name)\\r\\n\\r\\n original_vertex_count = len(self.vertices)\\r\\n\\r\\n for v in range(0, len(bufr.vertices)):\\r\\n # Scale, offset and store vertices\\r\\n vx, vy, vz = rotate_vec(b[4], b[5], b[6], bufr.vertices[v])\\r\\n self.vertices.append((vx * b[7] + b[1], vy * b[8] + b[2], vz * b[9] + b[3]))\\r\\n\\r\\n # Rotate normals\\r\\n self.normals.append(rotate_vec(b[4], b[5], b[6], bufr.normals[v]))\\r\\n\\r\\n self.tex_coords.extend(bufr.tex_coords)\\r\\n\\r\\n ctypes.restype = ctypes.c_short # TODO: remove this side-effect.\\r\\n indices = [(i[0] + original_vertex_count, i[1] + original_vertex_count,\\r\\n i[2] + original_vertex_count) for i in bufr.indices]\\r\\n self.indices.extend(indices)\\r\\n\\r\\n self.buf = []\\r\\n self.buf.append(Buffer(self, self.vertices, self.tex_coords, self.indices, self.normals))\",\n \"def __getitem__(self, index):\\n # Generate indexes of the batch\\n folder_id, file_id, el_id = self.index_to_ids(index)\\n folder_id = self.idx_folder[folder_id]\\n file_id = self.idx_file[file_id]\\n el_ids = self.idx_el[el_id*self.batch_size + np.arange(self.batch_size)]\\n self.current_b = el_ids\\n return self.__data_generation(folder_id, file_id, el_ids)\",\n \"def __getitem__(self, index):\\n # Generate indexes of the batch\\n folder_id, file_id, el_id = self.index_to_ids(index)\\n folder_id = self.idx_folder[folder_id]\\n file_id = self.idx_file[file_id]\\n el_ids = self.idx_el[el_id*self.batch_size + np.arange(self.batch_size)]\\n self.current_b = el_ids\\n return self.__data_generation(folder_id, file_id, el_ids)\",\n \"def __getitem__(self, i):\\n\\t\\treturn self._blocks[i]\",\n \"def buffered_read(file_object, chunk_size=1024):\\n while True:\\n data = file_object.read(chunk_size)\\n if not data:\\n break\\n yield data\",\n \"def peek(\\n self,\\n count: int = 1,\\n ) -> List[T]:\\n buffer = self._buffer\\n buffer_len = len(buffer)\\n\\n if count > buffer_len:\\n buffer.extend(islice(self._iterator, count - buffer_len))\\n\\n return list(islice(buffer, count))\",\n \"def __getitem__(self, idx):\\n assert isinstance(\\n idx, (int, slice)), \\\"Index Could be an integer or a slice\\\"\\n\\n if isinstance(idx, int) and idx < 0:\\n for cur_index in range(-idx):\\n obj, pos = self.__get_json_from_end()\\n if -cur_index - 1 == idx:\\n return json.loads(obj, encoding=\\\"utf-8\\\")\\n raise IndexError\\n\\n if isinstance(idx, slice):\\n to_extract = (elm for elm in gen_increasing_slice(idx))\\n else:\\n to_extract = [idx]\\n\\n results = []\\n\\n for target_idx in to_extract:\\n self.__descriptor.seek(0, 0)\\n cur_idx = 0\\n\\n checkpoint = self.__get_checkpoint(target_idx)\\n if checkpoint != False:\\n self.__descriptor.seek(checkpoint[1])\\n cur_idx = checkpoint[0]\\n self.__last_index = checkpoint[0]\\n self.__last_index_pos = checkpoint[1]\\n\\n if self.__last_index > cur_idx and target_idx > self.__last_index:\\n self.__descriptor.seek(self.__last_index_pos)\\n cur_idx = self.__last_index\\n\\n for obj, start in iter(lambda: self.__get_json(), (None, -1)):\\n last_obj = obj\\n self.__last_index_pos = start\\n self.__last_index = cur_idx\\n\\n if cur_idx == target_idx:\\n results.append(json.loads(last_obj, encoding=\\\"utf-8\\\"))\\n break\\n\\n cur_idx += 1\\n\\n if isinstance(idx, slice):\\n if idx.start is not None and idx.stop is not None and idx.start > idx.stop:\\n return list(reversed(results))\\n return results\\n else:\\n return results.pop(0)\",\n \"def enumerate(self):\\r\\n return enumerate(self, 1)\",\n \"def unbucketed_next(self):\\n # Initialize batch containers\\n label_batch = list()\\n enc_input_batch = list()\\n dec_input_batch = list()\\n # Fill individual batches by iterating over the entire data source\\n if self.sent_id < self.get_length():\\n while len(enc_input_batch) < self.opt.batch_size:\\n try:\\n indexed_sent = self.data[self.sent_id]\\n label_item = indexed_sent[1:]\\n enc_input_item = indexed_sent[1:]\\n # Reverse the input to the encoder, see arxiv.org/pdf/1703.03906.pdf\\n enc_input_item.reverse()\\n dec_input_item = indexed_sent[:-1]\\n label_batch.append(label_item)\\n enc_input_batch.append(enc_input_item)\\n dec_input_batch.append(dec_input_item)\\n self.sent_id += 1\\n except IndexError:\\n break\\n else:\\n raise IndexError\\n return label_batch, enc_input_batch, dec_input_batch\",\n \"def objects(self):\\r\\n return self._objects\",\n \"def __pos__(self):\\n ret = copy.deepcopy(self)\\n for row in ret:\\n if __debug__:\\n assert hasattr(row, '__iter__'), repr(row) + \\\" | \\\" + repr(ret)\\n assert len(row) <= len(ret.header), 'header needs to be larger or equal to all! ({},{})'.\\\\\\n format(row, ret.header)\\n for i in range(len(ret.header) - len(row)):\\n row.append(None)\\n return ret\",\n \"def retrieve(self, indices):\\n obses_t, actions, rewards, obses_tp1, dones = [], [], [], [], []\\n for i in indices:\\n if i == 0:\\n i = 1\\n data = self._storage[i]\\n obs_t, action, reward, obs_tp1, done = data\\n obses_t.append(np.array(obs_t, copy=False))\\n actions.append(np.array(action, copy=False))\\n rewards.append(reward)\\n obses_tp1.append(np.array(obs_tp1, copy=False))\\n dones.append(done)\\n return np.array(obses_t), np.array(actions), np.array(rewards), np.array(obses_tp1), np.array(dones)\",\n \"def __iter__(self):\\n\\n # collector will fetch chunksize array for each 'get' call\\n collector = FIFOArray(self.chunksize, self.axis)\\n\\n # make tmp array to hold generated subarrs\\n tmp = []\\n tmp_size = 0\\n for subarr in self.data(**self.kwargs):\\n\\n tmp.append(subarr)\\n tmp_size += subarr.shape[self.axis]\\n\\n # if tmp exceeds chunksize put in collector\\n if tmp_size >= self.chunksize:\\n arr = np.concatenate(tmp, axis=self.axis)\\n collector.put(arr)\\n\\n # fetch chunksize till not full\\n while collector.full():\\n yield collector.get()\\n\\n # place leftover back into tmp and empty collector\\n tmp = [collector.queue]\\n tmp_size = collector.qsize()\\n collector.queue = np.array([])\\n\\n else:\\n\\n # append to tmp again\\n continue\\n\\n # else runs after normal loop exit -- required here\\n else: #pylint: disable=useless-else-on-loop\\n\\n # yield whatever is left in tmp (its below chunksize)\\n remaining = np.concatenate(tmp, axis=self.axis)\\n if remaining.size > 0:\\n yield remaining\",\n \"def sort_chunks(self):\\n\\n first = True\\n\\n all_chunks = dict(self.dirty_chunk_cache)\\n all_chunks.update(self.chunk_cache)\\n self.chunk_cache.clear()\\n self.dirty_chunk_cache.clear()\\n for coords, chunk in all_chunks.iteritems():\\n if chunk.dirty:\\n if first:\\n first = False\\n self.save_chunk(chunk)\\n self.chunk_cache[coords] = chunk\\n else:\\n self.dirty_chunk_cache[coords] = chunk\\n else:\\n self.chunk_cache[coords] = chunk\",\n \"def __iter__(self):\\n n = self.head\\n for _ in range(len(self)):\\n if n == self.capacity:\\n n = 0\\n yield self.lst[n]\\n n += 1\",\n \"def _filesync_read_buffered(self, size, adb_info, filesync_info):\\n # Ensure recv buffer has enough data.\\n while len(filesync_info.recv_buffer) < size:\\n _, data = self._read_until([constants.WRTE], adb_info)\\n filesync_info.recv_buffer += data\\n\\n result = filesync_info.recv_buffer[:size]\\n filesync_info.recv_buffer = filesync_info.recv_buffer[size:]\\n return result\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.60331285","0.600125","0.59499425","0.5791308","0.57847834","0.57847834","0.57508755","0.5720811","0.56735605","0.5663488","0.56373197","0.5627264","0.5612106","0.5609416","0.5598592","0.5567743","0.55047196","0.5464387","0.544293","0.54306895","0.5413052","0.54127294","0.5410669","0.5402021","0.5389263","0.5387667","0.53841555","0.5373835","0.53723687","0.5366374","0.535851","0.5345086","0.53435886","0.5333569","0.53243005","0.53233314","0.5313376","0.5310109","0.53046757","0.53046757","0.53046757","0.53041637","0.5303626","0.53007805","0.5296886","0.5291884","0.5283068","0.5270519","0.5265049","0.52608305","0.525184","0.5247983","0.5247543","0.5238691","0.52373254","0.52353776","0.5232215","0.5226477","0.5222456","0.52083707","0.5168485","0.5168469","0.5160044","0.51588356","0.51466054","0.51441765","0.51360637","0.5134846","0.5131984","0.5129769","0.51296264","0.51275057","0.51258206","0.5125283","0.5119986","0.5106612","0.5105106","0.5091015","0.5090591","0.50902915","0.50867945","0.50853884","0.5084947","0.5074204","0.5073617","0.506811","0.506811","0.5067599","0.5063117","0.5054636","0.50540596","0.50495595","0.5047705","0.504732","0.5046987","0.50437766","0.5038624","0.50367427","0.5028752","0.50250345"],"string":"[\n \"0.60331285\",\n \"0.600125\",\n \"0.59499425\",\n \"0.5791308\",\n \"0.57847834\",\n \"0.57847834\",\n \"0.57508755\",\n \"0.5720811\",\n \"0.56735605\",\n \"0.5663488\",\n \"0.56373197\",\n \"0.5627264\",\n \"0.5612106\",\n \"0.5609416\",\n \"0.5598592\",\n \"0.5567743\",\n \"0.55047196\",\n \"0.5464387\",\n \"0.544293\",\n \"0.54306895\",\n \"0.5413052\",\n \"0.54127294\",\n \"0.5410669\",\n \"0.5402021\",\n \"0.5389263\",\n \"0.5387667\",\n \"0.53841555\",\n \"0.5373835\",\n \"0.53723687\",\n \"0.5366374\",\n \"0.535851\",\n \"0.5345086\",\n \"0.53435886\",\n \"0.5333569\",\n \"0.53243005\",\n \"0.53233314\",\n \"0.5313376\",\n \"0.5310109\",\n \"0.53046757\",\n \"0.53046757\",\n \"0.53046757\",\n \"0.53041637\",\n \"0.5303626\",\n \"0.53007805\",\n \"0.5296886\",\n \"0.5291884\",\n \"0.5283068\",\n \"0.5270519\",\n \"0.5265049\",\n \"0.52608305\",\n \"0.525184\",\n \"0.5247983\",\n \"0.5247543\",\n \"0.5238691\",\n \"0.52373254\",\n \"0.52353776\",\n \"0.5232215\",\n \"0.5226477\",\n \"0.5222456\",\n \"0.52083707\",\n \"0.5168485\",\n \"0.5168469\",\n \"0.5160044\",\n \"0.51588356\",\n \"0.51466054\",\n \"0.51441765\",\n \"0.51360637\",\n \"0.5134846\",\n \"0.5131984\",\n \"0.5129769\",\n \"0.51296264\",\n \"0.51275057\",\n \"0.51258206\",\n \"0.5125283\",\n \"0.5119986\",\n \"0.5106612\",\n \"0.5105106\",\n \"0.5091015\",\n \"0.5090591\",\n \"0.50902915\",\n \"0.50867945\",\n \"0.50853884\",\n \"0.5084947\",\n \"0.5074204\",\n \"0.5073617\",\n \"0.506811\",\n \"0.506811\",\n \"0.5067599\",\n \"0.5063117\",\n \"0.5054636\",\n \"0.50540596\",\n \"0.50495595\",\n \"0.5047705\",\n \"0.504732\",\n \"0.5046987\",\n \"0.50437766\",\n \"0.5038624\",\n \"0.50367427\",\n \"0.5028752\",\n \"0.50250345\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.66548544"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81771,"cells":{"query":{"kind":"string","value":"Add one particular item, with a specific index to the buffer If the item is already buffered do not add it again Argument"},"document":{"kind":"string","value":"def add_item(self, item, index):\n if index in self.d_buffer.keys():\n return True\n elif len(self) < self._size:\n self.d_buffer.update({index: item})\n return True\n else:\n return False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def add(self, item):\r\n if len(self.buff)==self.size: self.buff.pop(0)\r\n self.buff.append(item)","def add_next(self, item, index):\n if index in self.d_buffer.keys():\n return\n if len(self) == self.size:\n self.pop_first()\n self.add_item(item, index)","def __setitem__(self, index, value):\n self.buffer[index] = value","def add_prev(self, item, index):\n if index in self.d_buffer.keys():\n return\n if len(self) == self._size:\n self.pop_last()\n self.add_item(item, index)","def _add_buffer(self, p_buffer_element:PyTorchIOElement):\r\n\r\n self._buffer.add_element(p_buffer_element)","def worker(self):\n while True:\n item,index = self.inbound.get()\n if index is None:\n self.buffer.append(item)\n self.index.value = self.index.value + 1 #index of next item for buffer\n if len(self.buffer)>self.size:\n del self.buffer[0]\n self.newitem.put(None)\n else:\n self.buffer[len(self.buffer)+(index - self.index.value)] = item","def delayed_buffer_item(self, buffer_item, buffer_item_len, item):\n item_copy = copy.copy(item)\n if buffer_item is None:\n buffer_item = buffer_item_len * [item_copy]\n else:\n buffer_item.append(item_copy)\n item_cur = copy.copy(buffer_item.pop(0))\n\n return buffer_item, item_cur","def _add(self, sample):#obs_t, action, reward, obs_tp1, done):\n\n if self._next_idx >= len(self._buffer): #appends data if max capacity not reached yet\n self._buffer.append(sample)\n else:\n self._buffer[self._next_idx] = sample #drops old entry and appends new data if max capacity\n self._next_idx = (self._next_idx + 1) % self._capacity","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][3] for b in buffer.memory] # images\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[1][1] for b in buffer.memory] # gears\n d8 = [b[1][2] for b in buffer.memory] # rpms\n d9 = [b[3] for b in buffer.memory] # terminated\n d10 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n self.data[9] += d9\n self.data[10] += d10\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n self.data.append(d9)\n self.data.append(d10)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n self.data[9] = self.data[9][to_trim:]\n self.data[10] = self.data[10][to_trim:]\n\n return self","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][2] for b in buffer.memory] # lidar\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[1][1] for b in buffer.memory] # progress\n d8 = [b[3] for b in buffer.memory] # terminated\n d9 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n self.data[9] += d9\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n self.data.append(d9)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n self.data[9] = self.data[9][to_trim:]\n\n return self","def add_item(self, item: _T) -> None:\n if item not in self.item_to_index:\n self.item_to_index[item] = len(self.index_to_item)\n self.index_to_item.append(item)","def append(self, item):\n if self.full or self.pre_allocated:\n # overwrite\n self.data[self.cur] = item\n else:\n self.data.append(item)\n if not self.full:\n self.full = self.cur == self.max - 1\n self.cur = (self.cur + 1) % self.max","def addToBuffer(self, request):\n raise NotImplementedError","def add_item(self, item):\n self.items.append(item)\n self.length += 1","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][1] for b in buffer.memory] # lidar\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes (terminated or truncated)\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[3] for b in buffer.memory] # terminated\n d8 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n\n return self","def put(self,item,index=None):\n self.inbound.put((item,index))","def add(self, item):\n self.num_item += 1\n indexs = self.__get_indexs(item)\n for index in indexs:\n self.filter_bitarray[index] = True","def enqueue(self, item):\n # double size of array if necessary and recopy to front of array\n if self._N == len(self._q):\n self._resize(2*len(self._q)) # double size of array if necessary\n self._q[self._last] = item # add item\n self._last += 1\n if self._last == len(self._q):\n self._last = 0 # wrap-around\n self._N += 1","def set_buffer(self, i, data, append = False):\n if i not in range(1, self.NUM_BUFFERS + 1):\n raise IndexError(\"Error: Could not set buffer %d. Must be \"\n \"between 1 and 9\" % i)\n if type(data) == types.UnicodeType:\n data = data.encode('ascii', 'xmlcharrefreplace')\n if append:\n self.logger.debug(\"set_buffer(%d), appending: %s\" % (i,data))\n self.m_param[i] += data\n else:\n self.logger.debug(\"set_buffer(%d): %s\" % (i,data))\n self.m_param[i] = data\n return","def add_item(self, item):\n if self.head is None:\n # if not self.array:\n self.head = 0\n self.array = [item]\n else:\n # insert item\n self.array.insert(self.head, item)\n\n # reassign head\n self.head += 1","def add(self, item):\n if self.has_item(item):\n return\n\n self.cache.append(item)\n\n if self.size() > self.max_size:\n self.cache.popleft()","def __getitem__(self, index):\n return self.buffer[index]","def _append(self, key):\n \"\"\" Returns: The index at which the new value is appended \"\"\"\n if len(self.queue) > self.size:# There is still space left in queue\n self.queue[self.size] = key\n # No space left in queue\n self.queue.append(key)\n atIndex = self.size\n self.size += 1\n return atIndex","def add_item(self, item):\n self.items.append(item)\n self.item_count += 1\n self.max_length = max(self.max_length, len(item.samples))","def append(self, x):\n if self.buffer[self.end]:\n if self.start <= self.end:\n self.buffer = (self.buffer[self.start:self.end]\n + [x]\n + [None]*(self.size - 1))\n else:\n self.buffer = ([(item for item\n in (self.buffer[self.start:]\n + self.buffer[:self.end])\n if item is not None)]\n + [x]\n + [None]*(self.size - 1))\n self.start = 0\n self.end = len(self.buffer) - self.size + 1\n else:\n self.buffer[self.end] = x\n self.end = (self.end + 1) % len(self.buffer)","def append ( self , item ) :\n self.cond.acquire()\n try:\n if self.closed :\n raise Exception( \"Trying to append to a closed queue\" )\n else :\n self.weight += int( item['size'] )\n self.push( item )\n self.cond.notify()\n finally:\n self.cond.release()","def add_to_buffer(self, values):\n self._buffer.extend(values)","def enqueue(self, item):\n\t\tself.items.insert(0, item)","def put(self, item): \n if len(self.contents) < self.max_size:\n self.contents.append(item)\n elif len(self.contents) >= self.max_size:\n print \"Backpack Full.\"","def enqueue(self, item):\n self.items.insert(0, item)","def enqueue(self, item):\n self.items.insert(0, item)","def fillBuffer():\n buff[bufferCounter].next = dataIn","def add_to_group(self,item):\n self.items.append(item)\n self.n += 1","def add_chunk(self, chunk):\n self.chunkbuffer.appendleft(chunk)","def add_to_buffer(self, packet):\n # If the buffer is currently empty, the we should send the next packet\n # (i.e. this packet) as soon as it finishes transmitting (which will take\n # time + sizeofpacket/transmissionrate)\n if (len(self.buffer) == 0):\n self.next_packet_send_time = globals.systime + (packet.get_size()/self.rate)\n\n # Checks that there is room to add the packet to the buffer\n if (packet.get_size() + self.buffersize <= self.buffercapacity):\n self.buffersize = self.buffersize + packet.get_size()\n self.buffer.append(packet)\n # if there isn't room in the buffer, we return 0 to indicate that the\n # packet was dropped.\n else:\n return 0\n\n # returns the size of the packet that was succesfully added to the\n # buffer.\n return packet.get_size()","def take_item(self, item):\r\n if len(self.items) <= 2:\r\n self.items.append(item)\r\n if self.got_both():\r\n self.working = True","def __init__(self,size=10):\n \n self.inbound = Queue() #an internal queue to manage the class properly in a thread safe manner.\n self.index = Value('i',0) #index of next item to be added.\n self.manager = Manager()\n \n self.buffer = self.manager.list() #the buffer we will store things in.\n self.size = size #the maximum size of the buffer\n self.newitem = Queue() #a blocking event to control the pop method\n t = threading.Thread(target=self.worker) #the worker that will run when items are added.\n t.start() #start the worker\n self.newitemindex = 0 #index of items to pop","def add(\n self,\n state: np.ndarray,\n action: np.ndarray,\n reward: np.float64,\n next_state: np.ndarray,\n done: float,\n ):\n data = (state, action, reward, next_state, done)\n\n if len(self.buffer) == self.buffer_size:\n self.buffer[self.idx] = data\n self.idx = (self.idx + 1) % self.buffer_size\n else:\n self.buffer.append(data)","def enqueue(self, item):\n self.queue.append(item)","def enqueue(self, item):\n self.queue.append(item)","def insert(self, index: int, item: Any) -> None:\n self.contents.insert(index, item)\n return","def add_first(self, data):\n self.deque.insert(0, data)","def add(self, result, next_item):\n self.test += 1\n\n if next_item in result[:self.length].index:\n self.hit += 1","def add(self, item):\n\n if item not in self:\n self._index_map[item] = len(self._list)\n self._list.append(item)","def enqueue(self, item):\n self.__queue.insert(0, item)","def remember(self, item):\n self.memory.append(item)","def _buffer_to(self, amount):\n if amount > self.lookahead:\n raise Exception(\n 'Cannot extend buffer to {}: '\n 'beyond buffer lookahead {}'.format(\n amount, self.lookahead\n )\n )\n while len(self.buffer) < amount:\n try:\n self.buffer.appendleft(next(self.stream))\n except StopIteration:\n break","def add(self, experience: []):\n if len(self.buffer) + len(experience) >= self.buffer_size:\n self.buffer[0:1] = []\n self.buffer.append(experience)","def append(self, item):\n\n # resize array to 2*capacity if max capacity reached\n if self.count == self.capacity:\n self._resize(2 * self.capacity)\n\n # Append the item at the end of array\n self.the_array[self.count] = item\n self.count += 1","def enqueue(self, item):\n self.list.append(item)","def append(self, observation, action, reward, next_observation, done):\n self.buffer.append([observation, action, reward, next_observation, done])","def insert(self, index, item):\n # type: (int, Any) -> None\n return list.insert(self, index, self.ref(item))","def _add_cached_chunk(self, offset, data):\n if (\n self._cached_chunk_position + len(self._cached_chunk) == offset\n and len(self._cached_chunk) + len(data) < _MAX_CACHED_CHUNK_SIZE\n ):\n # add to existing cache\n self._cached_chunk += data\n else:\n self._cached_chunk = data\n self._cached_chunk_position = offset","def observation(self, observation):\n \n # push backward all observations\n self.buffer[:-1] = self.buffer[1:]\n\n # add last observation to the end (similar to adding an item to a queue)\n self.buffer[-1] = observation\n \n return self.buffer","def add(self, data):\n self.databuffer.append(data)\n if len(self.databuffer) > self.buffersize:\n self._flush()","def push(self, item):\n self.list.prepend(item)","def put(self, item: Any):\n has_item = True\n with self._lock:\n if item not in self._items:\n self._items.add(item)\n has_item = False\n if not has_item:\n self._queue.put(item)","def _add_to_buffer(self, data):\n for byte in data:\n self.next_fn(byte) \n self._parse_cmds()","def push(self, item):\n if len(self._data) == self.MAX_SIZE:\n # full we have to pop the oldest item (head)\n self._data.pop(0)\n self._data.append(item)","def send(self, item):\n self.input_queue.put(item)","def add(self, element):\n\n if self.style == 'FIFO': # If FIFO, append element to end of list\n self.queue.append(element)\n\n elif self.style == 'LIFO': # If LIFO, append element to front of list\n self.queue.insert(0, element)","def __setitem__(self, i: int, item: Any) -> None:\n if i < 0:\n i = self._length + i\n\n curr = self._first\n index_so_far = 0\n\n while curr is not None:\n if index_so_far == i:\n curr.item = item\n break\n index_so_far += 1\n curr = curr.next\n if curr is None:\n raise IndexError","def add(self, result, next_item):\n self.test += self.length\n self.hit += len(set(next_item) & set(result[:self.length].index))","def push(self, Item):\n self.data_container.insert(0, Item)","def add_item (self, item):\n new_item = CacheItem (item)\n cached = self.cache.get(hash(item))\n if cached is None:\n self.evict_or_add (new_item)\n cached.hits += 1","def insert(self, item: T, index: int) -> None:\n pass","def enqueue(self, item):\n\n self._data.append(item)","def add_to_bag(self, item):\n self._bag.append(item)","def add(self, item):","def __setitem__(self, index, item):\n # TODO: complete this function!\n if index >= self.__len__():\n raise IndexError\n else:\n if index == 0:\n self._first = item\n else:\n self._rest.__setitem__(index-1, item)","def _add_item_by_item(self, item):\n self.item_list[item.call_number] = item","def put(self, key, item):\n if key or item:\n self.cache_data[key] = item\n if len(self.cache_data) > BaseCaching.MAX_ITEMS:\n print(\"DISCARD: {}\".format(self.last))\n del self.cache_data[self.last]\n self.last = key","def add_item(items, coder, tag, start, n):\n if start is not None:\n # close opened items\n add_zero_item(items, coder, tag, start) # default tag\n items[tag][coder].append(item(b=start, l=n-start, v=1)) # found tag","def put(self, key, item):\n if key and item:\n if key in self.cache_data.keys():\n self.cache_data[key] = item\n self.stack.append(key)\n else:\n if len(self.cache_data.keys()) < self.MAX_ITEMS:\n self.cache_data[key] = item\n self.stack.append(key)\n elif len(self.cache_data.keys()) == self.MAX_ITEMS:\n k = self.stack.pop(-1)\n self.cache_data.pop(k)\n print(\"DISCARD: {}\".format(k))\n self.cache_data[key] = item\n self.stack.append(key)","def __setitem__(self, index, newItem):\r\n #if index < 0 or index >= self.size():\r\n # raise IndexError(\"Array index out of bounds\")\r\n self._items[index] = newItem","def push(self, value):\n # Add value, then increment pointer (and size if necessary)\n self.buf[self.ptr] = np.array(value)\n self.ptr = (self.ptr + 1) % self.length\n if self._size < self.length:\n self._size += 1","def add(self, result, next_item):\n res = result[:self.length]\n\n self.test += 1\n\n if next_item in res.index:\n rank = res.index.get_loc(next_item) + 1\n self.pos += (1.0 / rank)","def push(self, item):\n self._tail_iters.append(iter([item]))","def _put(self, item, queue):","def put(self, obj):\r\n self.staging_buffer.append(obj)\r\n\r\n if self.is_full():\r\n self._flush()","def push(self, item):\n\t\tself.top+=1;\n\t\tself.arr.insert(self.top, item);","def add(self, obs_t, action, reward, obs_tp1, done):\n self.count += 1\n data = (obs_t, action, reward, obs_tp1, done)\n popped_data = self.buffers[0].add(*data)\n \n for i in range(1, self.num_buffers):\n #print(\"buffer \", i)\n #print(\"popped: \", popped_data)\n if popped_data == None:\n break\n if random.uniform(0, 1) < self.beta:\n popped_data = self.buffers[i].add(*popped_data)\n elif self.no_waste:\n self.overflow_buffer.appendleft(popped_data)\n break\n else:\n break\n if self.no_waste and (self.count > self._maxsize) and (len(self.overflow_buffer) != 0):\n self.overflow_buffer.pop()","def enqueue(self, item):\n\n self.__items__.append(item)","def push(self,item):\n self.items.append(item)","def insert(self, index, newItem):\r\n if self.size() == len(self):\r\n self.grow()\r\n if index >= self.size():\r\n self._items[self.size()] = newItem\r\n else:\r\n index = max(index, 0)\r\n # Shift items down by one position\r\n for i in range(self.size(), index, -1):\r\n self._items[i] = self._items[i - 1]\r\n\r\n # Add new item and increment logical size\r\n self._items[index] = newItem\r\n self._logicalSize += 1","def enqueue(self, item):\n self._queue.append(item)","def next_buffer(self):\n selected_window = self.selected_window()\n selected_window.set_buffer(self._find_next_buffer(selected_window.buffer()))","def get_new_item(self, index):\n if index not in self.d_buffer.keys():\n if 0 <= index < self.n_im:\n return self.stack[index]\n # Does not raise an error in case of wrong index for easier\n # handling upstream\n else:\n return None\n else:\n return self.d_buffer[index]","def append(self, experience):\n self.buffer.append(experience)\n self.number += 1","def pop_item(self, index):\n ix, obj = self.items\n if index < len(ix):\n self.d_buffer.pop(ix[index])\n else:\n raise IndexError('Buffer does not have {0} elements'.format(index))","def push(self, item):\n pass","def add(self, result, next_item):\n self.test += len(set(next_item))\n self.hit += len(set(next_item) & set(result[:self.length].index))","def push(self, item) -> None:\n self.items.append(item)","def push(self, item):\n\t\tself.items.append(item)","def insert(self, item):\r\n self.fetch()\r\n t = self.make_item_tuple(item)\r\n changed = False\r\n if t not in self.data:\r\n self.data.insert(0, t)\r\n changed = True\r\n\r\n if changed:\r\n query_cache.set(self.iden, self.data[:precompute_limit])","def insert(self, index, item):\n\n # Check if -len(self) <= index <= len(self)\n valid_index = (index <= len(self)) and (index >= -len(self))\n\n try:\n if not valid_index:\n raise IndexError\n\n if self.count == self.capacity:\n self._resize(2 * self.capacity)\n\n # Index '-1' for last item, '-len(self)' for first item\n if index < 0:\n index = index + len(self)\n\n # Move every item after the 'index' to the right\n for i in range(self.count, index - 1, -1):\n self.the_array[i] = self.the_array[i - 1]\n\n # Insert the 'item' at 'index'\n self.the_array[index] = item\n self.count += 1\n\n return True\n\n except IndexError:\n print(\"Index must be in between -len(self) to len(self).\")\n return False","def add_item ( self, offset ):\n list, index = self.get_info()\n index += offset \n item_trait = self.factory.trait_handler.item_trait\n value = item_trait.default_value()[1]\n self.value = list[:index] + [ value ] + list[index:]","def _set_item(self, index, item):\r\n switched_item = self._items[index]\r\n if switched_item:\r\n switched_item.on_taken_from_bag(self)\r\n self.set_switched_item(switched_item)\r\n if item:\r\n item.on_put_into_bag(self)\r\n self._items[index] = item","def push(self, item):\n self.items.append(item)","def push(self, item):\n self.items.append(item)"],"string":"[\n \"def add(self, item):\\r\\n if len(self.buff)==self.size: self.buff.pop(0)\\r\\n self.buff.append(item)\",\n \"def add_next(self, item, index):\\n if index in self.d_buffer.keys():\\n return\\n if len(self) == self.size:\\n self.pop_first()\\n self.add_item(item, index)\",\n \"def __setitem__(self, index, value):\\n self.buffer[index] = value\",\n \"def add_prev(self, item, index):\\n if index in self.d_buffer.keys():\\n return\\n if len(self) == self._size:\\n self.pop_last()\\n self.add_item(item, index)\",\n \"def _add_buffer(self, p_buffer_element:PyTorchIOElement):\\r\\n\\r\\n self._buffer.add_element(p_buffer_element)\",\n \"def worker(self):\\n while True:\\n item,index = self.inbound.get()\\n if index is None:\\n self.buffer.append(item)\\n self.index.value = self.index.value + 1 #index of next item for buffer\\n if len(self.buffer)>self.size:\\n del self.buffer[0]\\n self.newitem.put(None)\\n else:\\n self.buffer[len(self.buffer)+(index - self.index.value)] = item\",\n \"def delayed_buffer_item(self, buffer_item, buffer_item_len, item):\\n item_copy = copy.copy(item)\\n if buffer_item is None:\\n buffer_item = buffer_item_len * [item_copy]\\n else:\\n buffer_item.append(item_copy)\\n item_cur = copy.copy(buffer_item.pop(0))\\n\\n return buffer_item, item_cur\",\n \"def _add(self, sample):#obs_t, action, reward, obs_tp1, done):\\n\\n if self._next_idx >= len(self._buffer): #appends data if max capacity not reached yet\\n self._buffer.append(sample)\\n else:\\n self._buffer[self._next_idx] = sample #drops old entry and appends new data if max capacity\\n self._next_idx = (self._next_idx + 1) % self._capacity\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][3] for b in buffer.memory] # images\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[1][1] for b in buffer.memory] # gears\\n d8 = [b[1][2] for b in buffer.memory] # rpms\\n d9 = [b[3] for b in buffer.memory] # terminated\\n d10 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n self.data[9] += d9\\n self.data[10] += d10\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n self.data.append(d9)\\n self.data.append(d10)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n self.data[9] = self.data[9][to_trim:]\\n self.data[10] = self.data[10][to_trim:]\\n\\n return self\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][2] for b in buffer.memory] # lidar\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[1][1] for b in buffer.memory] # progress\\n d8 = [b[3] for b in buffer.memory] # terminated\\n d9 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n self.data[9] += d9\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n self.data.append(d9)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n self.data[9] = self.data[9][to_trim:]\\n\\n return self\",\n \"def add_item(self, item: _T) -> None:\\n if item not in self.item_to_index:\\n self.item_to_index[item] = len(self.index_to_item)\\n self.index_to_item.append(item)\",\n \"def append(self, item):\\n if self.full or self.pre_allocated:\\n # overwrite\\n self.data[self.cur] = item\\n else:\\n self.data.append(item)\\n if not self.full:\\n self.full = self.cur == self.max - 1\\n self.cur = (self.cur + 1) % self.max\",\n \"def addToBuffer(self, request):\\n raise NotImplementedError\",\n \"def add_item(self, item):\\n self.items.append(item)\\n self.length += 1\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][1] for b in buffer.memory] # lidar\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes (terminated or truncated)\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[3] for b in buffer.memory] # terminated\\n d8 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n\\n return self\",\n \"def put(self,item,index=None):\\n self.inbound.put((item,index))\",\n \"def add(self, item):\\n self.num_item += 1\\n indexs = self.__get_indexs(item)\\n for index in indexs:\\n self.filter_bitarray[index] = True\",\n \"def enqueue(self, item):\\n # double size of array if necessary and recopy to front of array\\n if self._N == len(self._q):\\n self._resize(2*len(self._q)) # double size of array if necessary\\n self._q[self._last] = item # add item\\n self._last += 1\\n if self._last == len(self._q):\\n self._last = 0 # wrap-around\\n self._N += 1\",\n \"def set_buffer(self, i, data, append = False):\\n if i not in range(1, self.NUM_BUFFERS + 1):\\n raise IndexError(\\\"Error: Could not set buffer %d. Must be \\\"\\n \\\"between 1 and 9\\\" % i)\\n if type(data) == types.UnicodeType:\\n data = data.encode('ascii', 'xmlcharrefreplace')\\n if append:\\n self.logger.debug(\\\"set_buffer(%d), appending: %s\\\" % (i,data))\\n self.m_param[i] += data\\n else:\\n self.logger.debug(\\\"set_buffer(%d): %s\\\" % (i,data))\\n self.m_param[i] = data\\n return\",\n \"def add_item(self, item):\\n if self.head is None:\\n # if not self.array:\\n self.head = 0\\n self.array = [item]\\n else:\\n # insert item\\n self.array.insert(self.head, item)\\n\\n # reassign head\\n self.head += 1\",\n \"def add(self, item):\\n if self.has_item(item):\\n return\\n\\n self.cache.append(item)\\n\\n if self.size() > self.max_size:\\n self.cache.popleft()\",\n \"def __getitem__(self, index):\\n return self.buffer[index]\",\n \"def _append(self, key):\\n \\\"\\\"\\\" Returns: The index at which the new value is appended \\\"\\\"\\\"\\n if len(self.queue) > self.size:# There is still space left in queue\\n self.queue[self.size] = key\\n # No space left in queue\\n self.queue.append(key)\\n atIndex = self.size\\n self.size += 1\\n return atIndex\",\n \"def add_item(self, item):\\n self.items.append(item)\\n self.item_count += 1\\n self.max_length = max(self.max_length, len(item.samples))\",\n \"def append(self, x):\\n if self.buffer[self.end]:\\n if self.start <= self.end:\\n self.buffer = (self.buffer[self.start:self.end]\\n + [x]\\n + [None]*(self.size - 1))\\n else:\\n self.buffer = ([(item for item\\n in (self.buffer[self.start:]\\n + self.buffer[:self.end])\\n if item is not None)]\\n + [x]\\n + [None]*(self.size - 1))\\n self.start = 0\\n self.end = len(self.buffer) - self.size + 1\\n else:\\n self.buffer[self.end] = x\\n self.end = (self.end + 1) % len(self.buffer)\",\n \"def append ( self , item ) :\\n self.cond.acquire()\\n try:\\n if self.closed :\\n raise Exception( \\\"Trying to append to a closed queue\\\" )\\n else :\\n self.weight += int( item['size'] )\\n self.push( item )\\n self.cond.notify()\\n finally:\\n self.cond.release()\",\n \"def add_to_buffer(self, values):\\n self._buffer.extend(values)\",\n \"def enqueue(self, item):\\n\\t\\tself.items.insert(0, item)\",\n \"def put(self, item): \\n if len(self.contents) < self.max_size:\\n self.contents.append(item)\\n elif len(self.contents) >= self.max_size:\\n print \\\"Backpack Full.\\\"\",\n \"def enqueue(self, item):\\n self.items.insert(0, item)\",\n \"def enqueue(self, item):\\n self.items.insert(0, item)\",\n \"def fillBuffer():\\n buff[bufferCounter].next = dataIn\",\n \"def add_to_group(self,item):\\n self.items.append(item)\\n self.n += 1\",\n \"def add_chunk(self, chunk):\\n self.chunkbuffer.appendleft(chunk)\",\n \"def add_to_buffer(self, packet):\\n # If the buffer is currently empty, the we should send the next packet\\n # (i.e. this packet) as soon as it finishes transmitting (which will take\\n # time + sizeofpacket/transmissionrate)\\n if (len(self.buffer) == 0):\\n self.next_packet_send_time = globals.systime + (packet.get_size()/self.rate)\\n\\n # Checks that there is room to add the packet to the buffer\\n if (packet.get_size() + self.buffersize <= self.buffercapacity):\\n self.buffersize = self.buffersize + packet.get_size()\\n self.buffer.append(packet)\\n # if there isn't room in the buffer, we return 0 to indicate that the\\n # packet was dropped.\\n else:\\n return 0\\n\\n # returns the size of the packet that was succesfully added to the\\n # buffer.\\n return packet.get_size()\",\n \"def take_item(self, item):\\r\\n if len(self.items) <= 2:\\r\\n self.items.append(item)\\r\\n if self.got_both():\\r\\n self.working = True\",\n \"def __init__(self,size=10):\\n \\n self.inbound = Queue() #an internal queue to manage the class properly in a thread safe manner.\\n self.index = Value('i',0) #index of next item to be added.\\n self.manager = Manager()\\n \\n self.buffer = self.manager.list() #the buffer we will store things in.\\n self.size = size #the maximum size of the buffer\\n self.newitem = Queue() #a blocking event to control the pop method\\n t = threading.Thread(target=self.worker) #the worker that will run when items are added.\\n t.start() #start the worker\\n self.newitemindex = 0 #index of items to pop\",\n \"def add(\\n self,\\n state: np.ndarray,\\n action: np.ndarray,\\n reward: np.float64,\\n next_state: np.ndarray,\\n done: float,\\n ):\\n data = (state, action, reward, next_state, done)\\n\\n if len(self.buffer) == self.buffer_size:\\n self.buffer[self.idx] = data\\n self.idx = (self.idx + 1) % self.buffer_size\\n else:\\n self.buffer.append(data)\",\n \"def enqueue(self, item):\\n self.queue.append(item)\",\n \"def enqueue(self, item):\\n self.queue.append(item)\",\n \"def insert(self, index: int, item: Any) -> None:\\n self.contents.insert(index, item)\\n return\",\n \"def add_first(self, data):\\n self.deque.insert(0, data)\",\n \"def add(self, result, next_item):\\n self.test += 1\\n\\n if next_item in result[:self.length].index:\\n self.hit += 1\",\n \"def add(self, item):\\n\\n if item not in self:\\n self._index_map[item] = len(self._list)\\n self._list.append(item)\",\n \"def enqueue(self, item):\\n self.__queue.insert(0, item)\",\n \"def remember(self, item):\\n self.memory.append(item)\",\n \"def _buffer_to(self, amount):\\n if amount > self.lookahead:\\n raise Exception(\\n 'Cannot extend buffer to {}: '\\n 'beyond buffer lookahead {}'.format(\\n amount, self.lookahead\\n )\\n )\\n while len(self.buffer) < amount:\\n try:\\n self.buffer.appendleft(next(self.stream))\\n except StopIteration:\\n break\",\n \"def add(self, experience: []):\\n if len(self.buffer) + len(experience) >= self.buffer_size:\\n self.buffer[0:1] = []\\n self.buffer.append(experience)\",\n \"def append(self, item):\\n\\n # resize array to 2*capacity if max capacity reached\\n if self.count == self.capacity:\\n self._resize(2 * self.capacity)\\n\\n # Append the item at the end of array\\n self.the_array[self.count] = item\\n self.count += 1\",\n \"def enqueue(self, item):\\n self.list.append(item)\",\n \"def append(self, observation, action, reward, next_observation, done):\\n self.buffer.append([observation, action, reward, next_observation, done])\",\n \"def insert(self, index, item):\\n # type: (int, Any) -> None\\n return list.insert(self, index, self.ref(item))\",\n \"def _add_cached_chunk(self, offset, data):\\n if (\\n self._cached_chunk_position + len(self._cached_chunk) == offset\\n and len(self._cached_chunk) + len(data) < _MAX_CACHED_CHUNK_SIZE\\n ):\\n # add to existing cache\\n self._cached_chunk += data\\n else:\\n self._cached_chunk = data\\n self._cached_chunk_position = offset\",\n \"def observation(self, observation):\\n \\n # push backward all observations\\n self.buffer[:-1] = self.buffer[1:]\\n\\n # add last observation to the end (similar to adding an item to a queue)\\n self.buffer[-1] = observation\\n \\n return self.buffer\",\n \"def add(self, data):\\n self.databuffer.append(data)\\n if len(self.databuffer) > self.buffersize:\\n self._flush()\",\n \"def push(self, item):\\n self.list.prepend(item)\",\n \"def put(self, item: Any):\\n has_item = True\\n with self._lock:\\n if item not in self._items:\\n self._items.add(item)\\n has_item = False\\n if not has_item:\\n self._queue.put(item)\",\n \"def _add_to_buffer(self, data):\\n for byte in data:\\n self.next_fn(byte) \\n self._parse_cmds()\",\n \"def push(self, item):\\n if len(self._data) == self.MAX_SIZE:\\n # full we have to pop the oldest item (head)\\n self._data.pop(0)\\n self._data.append(item)\",\n \"def send(self, item):\\n self.input_queue.put(item)\",\n \"def add(self, element):\\n\\n if self.style == 'FIFO': # If FIFO, append element to end of list\\n self.queue.append(element)\\n\\n elif self.style == 'LIFO': # If LIFO, append element to front of list\\n self.queue.insert(0, element)\",\n \"def __setitem__(self, i: int, item: Any) -> None:\\n if i < 0:\\n i = self._length + i\\n\\n curr = self._first\\n index_so_far = 0\\n\\n while curr is not None:\\n if index_so_far == i:\\n curr.item = item\\n break\\n index_so_far += 1\\n curr = curr.next\\n if curr is None:\\n raise IndexError\",\n \"def add(self, result, next_item):\\n self.test += self.length\\n self.hit += len(set(next_item) & set(result[:self.length].index))\",\n \"def push(self, Item):\\n self.data_container.insert(0, Item)\",\n \"def add_item (self, item):\\n new_item = CacheItem (item)\\n cached = self.cache.get(hash(item))\\n if cached is None:\\n self.evict_or_add (new_item)\\n cached.hits += 1\",\n \"def insert(self, item: T, index: int) -> None:\\n pass\",\n \"def enqueue(self, item):\\n\\n self._data.append(item)\",\n \"def add_to_bag(self, item):\\n self._bag.append(item)\",\n \"def add(self, item):\",\n \"def __setitem__(self, index, item):\\n # TODO: complete this function!\\n if index >= self.__len__():\\n raise IndexError\\n else:\\n if index == 0:\\n self._first = item\\n else:\\n self._rest.__setitem__(index-1, item)\",\n \"def _add_item_by_item(self, item):\\n self.item_list[item.call_number] = item\",\n \"def put(self, key, item):\\n if key or item:\\n self.cache_data[key] = item\\n if len(self.cache_data) > BaseCaching.MAX_ITEMS:\\n print(\\\"DISCARD: {}\\\".format(self.last))\\n del self.cache_data[self.last]\\n self.last = key\",\n \"def add_item(items, coder, tag, start, n):\\n if start is not None:\\n # close opened items\\n add_zero_item(items, coder, tag, start) # default tag\\n items[tag][coder].append(item(b=start, l=n-start, v=1)) # found tag\",\n \"def put(self, key, item):\\n if key and item:\\n if key in self.cache_data.keys():\\n self.cache_data[key] = item\\n self.stack.append(key)\\n else:\\n if len(self.cache_data.keys()) < self.MAX_ITEMS:\\n self.cache_data[key] = item\\n self.stack.append(key)\\n elif len(self.cache_data.keys()) == self.MAX_ITEMS:\\n k = self.stack.pop(-1)\\n self.cache_data.pop(k)\\n print(\\\"DISCARD: {}\\\".format(k))\\n self.cache_data[key] = item\\n self.stack.append(key)\",\n \"def __setitem__(self, index, newItem):\\r\\n #if index < 0 or index >= self.size():\\r\\n # raise IndexError(\\\"Array index out of bounds\\\")\\r\\n self._items[index] = newItem\",\n \"def push(self, value):\\n # Add value, then increment pointer (and size if necessary)\\n self.buf[self.ptr] = np.array(value)\\n self.ptr = (self.ptr + 1) % self.length\\n if self._size < self.length:\\n self._size += 1\",\n \"def add(self, result, next_item):\\n res = result[:self.length]\\n\\n self.test += 1\\n\\n if next_item in res.index:\\n rank = res.index.get_loc(next_item) + 1\\n self.pos += (1.0 / rank)\",\n \"def push(self, item):\\n self._tail_iters.append(iter([item]))\",\n \"def _put(self, item, queue):\",\n \"def put(self, obj):\\r\\n self.staging_buffer.append(obj)\\r\\n\\r\\n if self.is_full():\\r\\n self._flush()\",\n \"def push(self, item):\\n\\t\\tself.top+=1;\\n\\t\\tself.arr.insert(self.top, item);\",\n \"def add(self, obs_t, action, reward, obs_tp1, done):\\n self.count += 1\\n data = (obs_t, action, reward, obs_tp1, done)\\n popped_data = self.buffers[0].add(*data)\\n \\n for i in range(1, self.num_buffers):\\n #print(\\\"buffer \\\", i)\\n #print(\\\"popped: \\\", popped_data)\\n if popped_data == None:\\n break\\n if random.uniform(0, 1) < self.beta:\\n popped_data = self.buffers[i].add(*popped_data)\\n elif self.no_waste:\\n self.overflow_buffer.appendleft(popped_data)\\n break\\n else:\\n break\\n if self.no_waste and (self.count > self._maxsize) and (len(self.overflow_buffer) != 0):\\n self.overflow_buffer.pop()\",\n \"def enqueue(self, item):\\n\\n self.__items__.append(item)\",\n \"def push(self,item):\\n self.items.append(item)\",\n \"def insert(self, index, newItem):\\r\\n if self.size() == len(self):\\r\\n self.grow()\\r\\n if index >= self.size():\\r\\n self._items[self.size()] = newItem\\r\\n else:\\r\\n index = max(index, 0)\\r\\n # Shift items down by one position\\r\\n for i in range(self.size(), index, -1):\\r\\n self._items[i] = self._items[i - 1]\\r\\n\\r\\n # Add new item and increment logical size\\r\\n self._items[index] = newItem\\r\\n self._logicalSize += 1\",\n \"def enqueue(self, item):\\n self._queue.append(item)\",\n \"def next_buffer(self):\\n selected_window = self.selected_window()\\n selected_window.set_buffer(self._find_next_buffer(selected_window.buffer()))\",\n \"def get_new_item(self, index):\\n if index not in self.d_buffer.keys():\\n if 0 <= index < self.n_im:\\n return self.stack[index]\\n # Does not raise an error in case of wrong index for easier\\n # handling upstream\\n else:\\n return None\\n else:\\n return self.d_buffer[index]\",\n \"def append(self, experience):\\n self.buffer.append(experience)\\n self.number += 1\",\n \"def pop_item(self, index):\\n ix, obj = self.items\\n if index < len(ix):\\n self.d_buffer.pop(ix[index])\\n else:\\n raise IndexError('Buffer does not have {0} elements'.format(index))\",\n \"def push(self, item):\\n pass\",\n \"def add(self, result, next_item):\\n self.test += len(set(next_item))\\n self.hit += len(set(next_item) & set(result[:self.length].index))\",\n \"def push(self, item) -> None:\\n self.items.append(item)\",\n \"def push(self, item):\\n\\t\\tself.items.append(item)\",\n \"def insert(self, item):\\r\\n self.fetch()\\r\\n t = self.make_item_tuple(item)\\r\\n changed = False\\r\\n if t not in self.data:\\r\\n self.data.insert(0, t)\\r\\n changed = True\\r\\n\\r\\n if changed:\\r\\n query_cache.set(self.iden, self.data[:precompute_limit])\",\n \"def insert(self, index, item):\\n\\n # Check if -len(self) <= index <= len(self)\\n valid_index = (index <= len(self)) and (index >= -len(self))\\n\\n try:\\n if not valid_index:\\n raise IndexError\\n\\n if self.count == self.capacity:\\n self._resize(2 * self.capacity)\\n\\n # Index '-1' for last item, '-len(self)' for first item\\n if index < 0:\\n index = index + len(self)\\n\\n # Move every item after the 'index' to the right\\n for i in range(self.count, index - 1, -1):\\n self.the_array[i] = self.the_array[i - 1]\\n\\n # Insert the 'item' at 'index'\\n self.the_array[index] = item\\n self.count += 1\\n\\n return True\\n\\n except IndexError:\\n print(\\\"Index must be in between -len(self) to len(self).\\\")\\n return False\",\n \"def add_item ( self, offset ):\\n list, index = self.get_info()\\n index += offset \\n item_trait = self.factory.trait_handler.item_trait\\n value = item_trait.default_value()[1]\\n self.value = list[:index] + [ value ] + list[index:]\",\n \"def _set_item(self, index, item):\\r\\n switched_item = self._items[index]\\r\\n if switched_item:\\r\\n switched_item.on_taken_from_bag(self)\\r\\n self.set_switched_item(switched_item)\\r\\n if item:\\r\\n item.on_put_into_bag(self)\\r\\n self._items[index] = item\",\n \"def push(self, item):\\n self.items.append(item)\",\n \"def push(self, item):\\n self.items.append(item)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.76870745","0.76835316","0.7008656","0.68846583","0.6850312","0.6849075","0.67566377","0.67298174","0.6627526","0.6571266","0.6514428","0.64295965","0.6416794","0.6378212","0.6364589","0.6336134","0.63103914","0.6234741","0.623079","0.6226195","0.61191016","0.60894626","0.6081906","0.60785246","0.60677385","0.6066206","0.6042715","0.60399246","0.6020756","0.60067064","0.60067064","0.60045433","0.5992261","0.5988058","0.59509367","0.59050256","0.5894219","0.58922505","0.586908","0.586908","0.5868133","0.5865265","0.5858001","0.5851531","0.58486927","0.5848505","0.5838486","0.5838134","0.5835788","0.58357304","0.5828103","0.58237135","0.58204204","0.5817524","0.5810202","0.58087397","0.57842684","0.578243","0.57722735","0.577124","0.57650906","0.57639074","0.57554173","0.57545406","0.5745884","0.57441455","0.5743173","0.5731957","0.57238984","0.5713309","0.57120365","0.570956","0.57042307","0.57025135","0.569898","0.56944895","0.5691577","0.56914663","0.5689059","0.56883466","0.5682847","0.5679602","0.5678219","0.5678098","0.56774837","0.56731117","0.5667846","0.56662005","0.5664085","0.56585896","0.56548643","0.56438845","0.5641414","0.5636774","0.56209415","0.5619491","0.5618638","0.5615931","0.5611011","0.5611011"],"string":"[\n \"0.76870745\",\n \"0.76835316\",\n \"0.7008656\",\n \"0.68846583\",\n \"0.6850312\",\n \"0.6849075\",\n \"0.67566377\",\n \"0.67298174\",\n \"0.6627526\",\n \"0.6571266\",\n \"0.6514428\",\n \"0.64295965\",\n \"0.6416794\",\n \"0.6378212\",\n \"0.6364589\",\n \"0.6336134\",\n \"0.63103914\",\n \"0.6234741\",\n \"0.623079\",\n \"0.6226195\",\n \"0.61191016\",\n \"0.60894626\",\n \"0.6081906\",\n \"0.60785246\",\n \"0.60677385\",\n \"0.6066206\",\n \"0.6042715\",\n \"0.60399246\",\n \"0.6020756\",\n \"0.60067064\",\n \"0.60067064\",\n \"0.60045433\",\n \"0.5992261\",\n \"0.5988058\",\n \"0.59509367\",\n \"0.59050256\",\n \"0.5894219\",\n \"0.58922505\",\n \"0.586908\",\n \"0.586908\",\n \"0.5868133\",\n \"0.5865265\",\n \"0.5858001\",\n \"0.5851531\",\n \"0.58486927\",\n \"0.5848505\",\n \"0.5838486\",\n \"0.5838134\",\n \"0.5835788\",\n \"0.58357304\",\n \"0.5828103\",\n \"0.58237135\",\n \"0.58204204\",\n \"0.5817524\",\n \"0.5810202\",\n \"0.58087397\",\n \"0.57842684\",\n \"0.578243\",\n \"0.57722735\",\n \"0.577124\",\n \"0.57650906\",\n \"0.57639074\",\n \"0.57554173\",\n \"0.57545406\",\n \"0.5745884\",\n \"0.57441455\",\n \"0.5743173\",\n \"0.5731957\",\n \"0.57238984\",\n \"0.5713309\",\n \"0.57120365\",\n \"0.570956\",\n \"0.57042307\",\n \"0.57025135\",\n \"0.569898\",\n \"0.56944895\",\n \"0.5691577\",\n \"0.56914663\",\n \"0.5689059\",\n \"0.56883466\",\n \"0.5682847\",\n \"0.5679602\",\n \"0.5678219\",\n \"0.5678098\",\n \"0.56774837\",\n \"0.56731117\",\n \"0.5667846\",\n \"0.56662005\",\n \"0.5664085\",\n \"0.56585896\",\n \"0.56548643\",\n \"0.56438845\",\n \"0.5641414\",\n \"0.5636774\",\n \"0.56209415\",\n \"0.5619491\",\n \"0.5618638\",\n \"0.5615931\",\n \"0.5611011\",\n \"0.5611011\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7550045"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81772,"cells":{"query":{"kind":"string","value":"Remove one particular item from the buffer"},"document":{"kind":"string","value":"def pop_item(self, index):\n ix, obj = self.items\n if index < len(ix):\n self.d_buffer.pop(ix[index])\n else:\n raise IndexError('Buffer does not have {0} elements'.format(index))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def take(self, item): \n self.contents.remove(item)","def __delitem__(self, where):\n with self._lock:\n self._current_bytes -= self._data[where]\n del self._data[where]\n self._order.remove(where)","def remove(self, item: T) -> None:\n index = self.index(item)\n self.delete_at_index(index)","def remove(self, item: T) -> None:\n index = self.index(item)\n self.delete_at_index(index)","def remove_item(self, idx_of_item):\n del self.items[idx_of_item]","def remove(self, item):\n try:\n entry = self.set.pop(item)\n entry[-1] = self.REMOVED\n except KeyError:\n print(\"Can't remove a non-existing item\")","def remove(self, item) -> None:\n entry = self.entry_finder.pop(item)\n entry[-1][0] = None","def removeItem(*args):","def removeItem(*args):","def discard(self, item):\n try:\n self._del(item)\n except KeyError:\n pass","def remove(self, item):\n # type: (Any) -> None\n return list.remove(self, self.ref(item))","def discard(self, item):\n try:\n counter = self._get(item) - 1\n except KeyError:\n return\n\n if counter <= 0:\n self._del(item)\n else:\n self._set(item, counter)","def remove():","def remove(self, item):\n del self._dict[item]","def remove (self, item):\n pass","def __delitem__(self, idx):\n self.pop(idx)","def remove(self, index):\n item = self._items.pop(index)\n if item in self._data:\n data = self._data.pop(item)\n else:\n data = None\n return item, data","def delete(self):\n first = self.data[0]\n self.data.pop(0)\n self.size = self.size - 1\n return first","def remove(self, item):\n\t\tif self.len == 0:\n\t\t\traise ValueError(\"Lista vacia\")\n\t\tif self.prim.dato == item:\n\t\t\tself.borrar_primero()\n\t\t\treturn\n\t\tanterior = self.prim\n\t\tactual = anterior.prox\n\t\twhile actual and actual.dato != item:\n\t\t\tanterior = anterior.prox\n\t\t\tactual = actual.prox\n\t\tif not actual:\n\t\t\traise ValueError(\"Elemento no encontrado\")\n\t\tanterior.prox = actual.prox\n\t\tself.len -= 1","def __delitem__(self, index):\n del self.chromosome_list[index]","def item_remove(self, item):\n\t\treturn self._modify_object(item=item, new_item=\"\")","def pop(self):\r\n return self.buff.pop(-1)","def discard(self, item):\n try:\n self._data.remove(item)\n except ValueError:\n pass\n else:\n self.__log__.append(SetDiscard(value=item))","def __delitem__(self, index: Any) -> None:\n del self.contents[index]\n return","def remove(self, item):\n\n if item in self:\n item_index = self._index_map[item]\n last_item = self._list[-1]\n\n # Swap in the item from the end of the list\n self._list[item_index] = last_item\n self._list.pop()\n\n self._index_map[last_item] = item_index","def remove(self, key):","def delete(self, item):\r\n self.fetch()\r\n t = self.make_item_tuple(item)\r\n changed = False\r\n while t in self.data:\r\n self.data.remove(t)\r\n changed = True\r\n \r\n if changed:\r\n query_cache.set(self.iden, self.data)","def remove(self, index):\n if index < 0 or index >= len(self):\n raise AttributeError(\"i must be >= 0 and < size of queue\")\n if index == 0:\n oldItem = self._front.data\n self._front = self._front.next\n else:\n probe = self._front\n while index > 1:\n probe = probe.next\n index -= 1\n oldItem = probe.next.data\n probe.next = probe.next.next\n self._size -= 1\n if self.isEmpty():\n self._rear = None\n return oldItem","def remove(self, index):\n self.data.pop(index)","def remove(self, item):\n # self._probeCount = 0\n self._homeIndex = abs(self._hash(item)) % len(self._table)\n distance = 1\n index = self._homeIndex\n\n while (self._table[index] != HashTable.EMPTY or \\\n self._table[index] == HashTable.DELETED) and \\\n self._table[index] != item:\n\n if self._liner:\n increment = index + 1\n else:\n increment = self._homeIndex + distance ** 2\n distance += 1\n index = increment % len(self._table)\n self._probeCount += 1\n\n if self._table[index] == item:\n self._table[index] = HashTable.DELETED\n self._actualIndex = index\n self._size -= 1\n return index\n else:\n self._actualIndex = -1\n return -1","def popitem(self):\n pass","def pop(self):\n value = self.buffer[self.end - 1]\n self.buffer[self.end - 1] = None\n self.end = (self.end - 1) % len(self.buffer)\n return value","def delete(self) -> None:\n if not self.buffer or self.index == len(self.buffer):\n return\n\n self.buffer.delete(self.index)\n\n if 0 < self.index > self.buffer.end:\n self.index = self.buffer.end","def __delitem__(self, key):\n self.f_remove(key)","def remove(self, key: int) -> None:\n idx = key % self.size\n if self.mp[idx]:\n for i in range(len(self.mp[idx])):\n if self.mp[idx][i][0] == key:\n #self.mp[idx].pop(i)\n del self.mp[idx][i]\n break","def pop(self):\n data = self.buffer.getvalue()\n self.buffer.seek(0)\n self.buffer.truncate()\n return data","def remove(self, index):\n self._checkIndex(index)\n self._updateOwner(index, register=False)\n discard = self._items.pop(index)","def popitem(self):\n return self.pop(0)","def remove(self, key):\r\n for i in range(len(self.lis)):\r\n if self.lis[i][0] == key:\r\n self.lis.pop(i)\r\n break","def remove(self, element: int) -> None:\n self._used.remove(element)\n if element < self.search_pos:\n self.search_pos = element","def remove(self, item: Item) -> None:\n raise NotImplementedError(\"remove\")","def remove_item(self, item_id):\n\t\tself.todolist.remove(item_id) \n\t\tstore = self.store\n\t\tfor row in store:\n\t\t\tif row[0] == item_id:\n\t\t\t\tstore.remove(row.iter)\n\t\t\t\tbreak","def __delitem__(self, ngram):\n self.pop(ngram)","def remove(*, item : Any, list : Union[List[Any], ConduitVariable]) -> None:\n list.remove(item)","def remove(self, key: int | str):\n self.__delitem__(key)","def __delitem__(self, key):\r\n key = self.key(key)\r\n if key in self.data_with_same_key:\r\n if len(self.data_with_same_key[key]) == 1:\r\n self.data[key] = self.data_with_same_key.pop(key)[0]\r\n else:\r\n self.data[key] = self.data_with_same_key[key].pop(-1)\r\n else:\r\n del self.data[key]","def delete_first(self):\n self.deque.pop(0)","def remove_entry(self, pos: int) -> None:\n del self.entries[pos]","def remove(self, x):\n del self[self.index(x)]","def remove(self, item):\n index = self.get_all().index(item)\n removed_item = self._items.pop(item)\n previous_item, next_item = removed_item[1]\n if item == self._first:\n self._first = next_item\n if next_item:\n self._items[next_item][1][0] = None\n elif item == self._last:\n self._last = previous_item\n if previous_item:\n self._items[previous_item][1][1] = None\n else:\n if previous_item:\n self._items[previous_item][1][1] = next_item\n if next_item:\n self._items[next_item][1][0] = previous_item\n return index","def __delitem__(self, key):\n del self.list[key]","def remove_item(self, item):\n node = self.find(item)\n if node:\n self.delete(node)\n return node.item\n else:\n return None","def remove(self, value): # real signature unknown; restored from __doc__\n pass","def delete_item ( self ):\n list, index = self.get_info()\n self.value = list[:index] + list[index+1:]","def __delitem__(self, idx):\n # note that this may result in an empty HSP object, which should be\n # invalid\n del self._items[idx]","def remove(self):","def __delitem__(self, tid: int):\n del self._cache[tid]","def remove(self, e):\n p = self._find_position(e) # try to locate existing element\n if p is not None:\n self._data.delete(p) # delete if found","def remove_a_specific_item(self, index):\n\n current = self.head\n previous = None\n for i in range(index):\n previous = current\n current = current.next\n if previous is None: self.head = current.next\n else: previous.next = current.next\n self.size -= 1","def remove(self, item):\n \n previous = None\n current = self.head\n \n while current is not None:\n \n if current.get_data() == item:\n # If the item to be removed is the first item\n if previous is None:\n self.head = current.get_next()\n else:\n previous.set_next(current.get_next())\n return\n \n else:\n previous = current\n current = current.get_next()","def remove(self, item: Any) -> None:\n curr = self._first\n\n if not curr:\n raise ValueError\n\n elif curr.item == item:\n self._first = self._first.next\n self._length -= 1\n\n else:\n while curr is not None:\n if curr.next and curr.next.item == item:\n curr.next = curr.next.next\n self._length -= 1\n return\n curr = curr.next\n raise ValueError","def del_item(self, item):\n index = self.board[item.pos[0]][item.pos[1]].index(item)\n del self.board[item.pos[0]][item.pos[1]][index]","def popitem(self):\n all_items = self.items()\n removed_item = random.choice(all_items)\n self[removed_item[0]] = None\n return removed_item","def popitem(self): # real signature unknown; restored from __doc__\n pass","def discard(self, element: int) -> None:\n self._used.discard(element)\n if element < self.search_pos:\n self.search_pos = element","def remove(self, item):\n try:\n self._data.remove(item)\n except ValueError as exc:\n raise KeyError from exc\n else:\n self.__log__.append(SetRemove(value=item))","def remove(self, x) -> None:\n pass","def remove(self, key: int) -> None:\n chain, idx = self._search(key)\n if idx is not None:\n chain.pop(idx)","def remove():\n pass","def remove(self, key):\n self.arr[key] = -1","def remove(self):\n return self.queue.popleft()","def __delitem__(self, key):\n del self._data[key]","def __delitem__(self, key: Hashable) -> None:\n del self.contents[key]\n return","def __delitem__(self, key: Union[Any, int]) -> None:\n if isinstance(key, int):\n del self.contents[key]\n else:\n self.contents = [c for c in self.contents \n if denovo.unit.get_name(c) != key]\n return","def remove(self, value):\n found = False\n for i in range(len(self.data)):\n if self.data[i] != value:\n pass\n else:\n found = True\n self.__delitem__(i)\n break\n if not found:\n raise ValueError","def pop_from_deque(self):","def delete(self, rgx):\n newbuf = [l for l in self.buffer if not re.search(rgx, l)]\n rval = [l for l in self.buffer if re.search(rgx, l)]\n self.buffer = newbuf\n return rval","def remove(self, item):\n item_found = False\n\n try:\n # Traverse through the array to look for the 'item'\n for i in range(len(self)):\n if self.the_array[i] == item:\n # Move every item after the 'item' found to left in order\n # to remove the 'item'\n for j in range(i, self.count - 1):\n self.the_array[j] = self.the_array[j + 1]\n self.count -= 1\n item_found = True\n\n if (self.capacity // 2 >= self.BASE_SIZE) and (self.count < self.capacity / 8):\n self._resize(self.capacity // 2)\n break\n\n if not item_found:\n raise ValueError\n\n except ValueError:\n print(\"Item not found in list.\")\n\n return item_found","def __delitem__(self, key: tuple):\n s, a = key\n del self.store[s][a]","def remove(self):\n if len(self.line) == 0:\n raise ValueError, \"No more elements in the queue to remove.\"\n\n frontOfLine = self.line[-1]\n self.line = self.line[:-1]\n return frontOfLine","def __delitem__(self, key):\n pass","def __delitem__(self, key):\n pass","def remove_one(self):\n item = self.expiry.pop(0)\n if item.updated:\n self.new_expiry.append(item)\n return\n del self.index[item.target]\n return","def remove(self, key: int) -> None:\n index = key % 10000\n previous = self.array[index]\n current = previous.next\n while current:\n if current.key == key:\n previous.next = current.next\n break\n previous = previous.next\n current = current.next","def remove(self, key):\n \n # If there used to be a key, there must exist an old value blob somewhere in the database. It should be deallocated after a successful commit to disk.\n if key in self.keys:\n if self.keys[key] is not None:\n punchat,punchlen = self.keys[key]\n self.awaitingpunch.append((punchat, punchlen))\n\n self.keys.pop(key, None)\n self.buffered.pop(key, None)\n self.cache.pop(key, None)\n\n if self.autocommit:\n commit()","def remove(self, p_int, p_int_1=None): # real signature unknown; restored from __doc__ with multiple overloads\n pass","def __delitem__(self, key):\n self.delete(key)","def __delitem__(self, key):\n self.delete(key)","def popitem(self):\n pass","def remove(self, value):\n pass","def __delitem__(self,key):\n if key in self.changed: self.changed.remove(key)\n if key not in self.deleted: self.deleted.append(key)\n del self.data[key]","def __delitem__(self, userid):\r\n self.removePlayer(userid)","def remove_item(self,itm):\n inv = self.get_inventory()\n s = str(itm)\n if s in inv:\n if inv[s] > 1:\n inv[s] -= 1\n else:\n del inv[s]\n self.put_inventory(inv)","def __delitem__(self, index):\n # delete the column\n del self._data[index]\n\n # adjust the number of columns\n self._nrows -= 1","def __delitem__(self, key):\n del self.elements[key]","def delete_item(self, key):\n deleted_slot = self.count_hash(key, len(self.slots))\n\n if self.slots[deleted_slot] == key:\n self.slots[deleted_slot] = None\n self.data[deleted_slot] = None\n elif isinstance(self.slots[deleted_slot], tuple):\n index_tuple = (self.slots[deleted_slot].index(key))\n list_slot = list(self.slots[deleted_slot])\n list_data = list(self.data[deleted_slot])\n list_slot.pop(index_tuple)\n list_data.pop(index_tuple)\n self.slots[deleted_slot] = tuple(list_slot)\n self.data[deleted_slot] = tuple(list_data)","def pop(self):","def pop(self):","def __delitem__(self, key):\n del self._get_storage()[key]","def remove_item(self, item: tuple) -> None:\n self._antecedent.remove(item)\n self._is_updated = False"],"string":"[\n \"def take(self, item): \\n self.contents.remove(item)\",\n \"def __delitem__(self, where):\\n with self._lock:\\n self._current_bytes -= self._data[where]\\n del self._data[where]\\n self._order.remove(where)\",\n \"def remove(self, item: T) -> None:\\n index = self.index(item)\\n self.delete_at_index(index)\",\n \"def remove(self, item: T) -> None:\\n index = self.index(item)\\n self.delete_at_index(index)\",\n \"def remove_item(self, idx_of_item):\\n del self.items[idx_of_item]\",\n \"def remove(self, item):\\n try:\\n entry = self.set.pop(item)\\n entry[-1] = self.REMOVED\\n except KeyError:\\n print(\\\"Can't remove a non-existing item\\\")\",\n \"def remove(self, item) -> None:\\n entry = self.entry_finder.pop(item)\\n entry[-1][0] = None\",\n \"def removeItem(*args):\",\n \"def removeItem(*args):\",\n \"def discard(self, item):\\n try:\\n self._del(item)\\n except KeyError:\\n pass\",\n \"def remove(self, item):\\n # type: (Any) -> None\\n return list.remove(self, self.ref(item))\",\n \"def discard(self, item):\\n try:\\n counter = self._get(item) - 1\\n except KeyError:\\n return\\n\\n if counter <= 0:\\n self._del(item)\\n else:\\n self._set(item, counter)\",\n \"def remove():\",\n \"def remove(self, item):\\n del self._dict[item]\",\n \"def remove (self, item):\\n pass\",\n \"def __delitem__(self, idx):\\n self.pop(idx)\",\n \"def remove(self, index):\\n item = self._items.pop(index)\\n if item in self._data:\\n data = self._data.pop(item)\\n else:\\n data = None\\n return item, data\",\n \"def delete(self):\\n first = self.data[0]\\n self.data.pop(0)\\n self.size = self.size - 1\\n return first\",\n \"def remove(self, item):\\n\\t\\tif self.len == 0:\\n\\t\\t\\traise ValueError(\\\"Lista vacia\\\")\\n\\t\\tif self.prim.dato == item:\\n\\t\\t\\tself.borrar_primero()\\n\\t\\t\\treturn\\n\\t\\tanterior = self.prim\\n\\t\\tactual = anterior.prox\\n\\t\\twhile actual and actual.dato != item:\\n\\t\\t\\tanterior = anterior.prox\\n\\t\\t\\tactual = actual.prox\\n\\t\\tif not actual:\\n\\t\\t\\traise ValueError(\\\"Elemento no encontrado\\\")\\n\\t\\tanterior.prox = actual.prox\\n\\t\\tself.len -= 1\",\n \"def __delitem__(self, index):\\n del self.chromosome_list[index]\",\n \"def item_remove(self, item):\\n\\t\\treturn self._modify_object(item=item, new_item=\\\"\\\")\",\n \"def pop(self):\\r\\n return self.buff.pop(-1)\",\n \"def discard(self, item):\\n try:\\n self._data.remove(item)\\n except ValueError:\\n pass\\n else:\\n self.__log__.append(SetDiscard(value=item))\",\n \"def __delitem__(self, index: Any) -> None:\\n del self.contents[index]\\n return\",\n \"def remove(self, item):\\n\\n if item in self:\\n item_index = self._index_map[item]\\n last_item = self._list[-1]\\n\\n # Swap in the item from the end of the list\\n self._list[item_index] = last_item\\n self._list.pop()\\n\\n self._index_map[last_item] = item_index\",\n \"def remove(self, key):\",\n \"def delete(self, item):\\r\\n self.fetch()\\r\\n t = self.make_item_tuple(item)\\r\\n changed = False\\r\\n while t in self.data:\\r\\n self.data.remove(t)\\r\\n changed = True\\r\\n \\r\\n if changed:\\r\\n query_cache.set(self.iden, self.data)\",\n \"def remove(self, index):\\n if index < 0 or index >= len(self):\\n raise AttributeError(\\\"i must be >= 0 and < size of queue\\\")\\n if index == 0:\\n oldItem = self._front.data\\n self._front = self._front.next\\n else:\\n probe = self._front\\n while index > 1:\\n probe = probe.next\\n index -= 1\\n oldItem = probe.next.data\\n probe.next = probe.next.next\\n self._size -= 1\\n if self.isEmpty():\\n self._rear = None\\n return oldItem\",\n \"def remove(self, index):\\n self.data.pop(index)\",\n \"def remove(self, item):\\n # self._probeCount = 0\\n self._homeIndex = abs(self._hash(item)) % len(self._table)\\n distance = 1\\n index = self._homeIndex\\n\\n while (self._table[index] != HashTable.EMPTY or \\\\\\n self._table[index] == HashTable.DELETED) and \\\\\\n self._table[index] != item:\\n\\n if self._liner:\\n increment = index + 1\\n else:\\n increment = self._homeIndex + distance ** 2\\n distance += 1\\n index = increment % len(self._table)\\n self._probeCount += 1\\n\\n if self._table[index] == item:\\n self._table[index] = HashTable.DELETED\\n self._actualIndex = index\\n self._size -= 1\\n return index\\n else:\\n self._actualIndex = -1\\n return -1\",\n \"def popitem(self):\\n pass\",\n \"def pop(self):\\n value = self.buffer[self.end - 1]\\n self.buffer[self.end - 1] = None\\n self.end = (self.end - 1) % len(self.buffer)\\n return value\",\n \"def delete(self) -> None:\\n if not self.buffer or self.index == len(self.buffer):\\n return\\n\\n self.buffer.delete(self.index)\\n\\n if 0 < self.index > self.buffer.end:\\n self.index = self.buffer.end\",\n \"def __delitem__(self, key):\\n self.f_remove(key)\",\n \"def remove(self, key: int) -> None:\\n idx = key % self.size\\n if self.mp[idx]:\\n for i in range(len(self.mp[idx])):\\n if self.mp[idx][i][0] == key:\\n #self.mp[idx].pop(i)\\n del self.mp[idx][i]\\n break\",\n \"def pop(self):\\n data = self.buffer.getvalue()\\n self.buffer.seek(0)\\n self.buffer.truncate()\\n return data\",\n \"def remove(self, index):\\n self._checkIndex(index)\\n self._updateOwner(index, register=False)\\n discard = self._items.pop(index)\",\n \"def popitem(self):\\n return self.pop(0)\",\n \"def remove(self, key):\\r\\n for i in range(len(self.lis)):\\r\\n if self.lis[i][0] == key:\\r\\n self.lis.pop(i)\\r\\n break\",\n \"def remove(self, element: int) -> None:\\n self._used.remove(element)\\n if element < self.search_pos:\\n self.search_pos = element\",\n \"def remove(self, item: Item) -> None:\\n raise NotImplementedError(\\\"remove\\\")\",\n \"def remove_item(self, item_id):\\n\\t\\tself.todolist.remove(item_id) \\n\\t\\tstore = self.store\\n\\t\\tfor row in store:\\n\\t\\t\\tif row[0] == item_id:\\n\\t\\t\\t\\tstore.remove(row.iter)\\n\\t\\t\\t\\tbreak\",\n \"def __delitem__(self, ngram):\\n self.pop(ngram)\",\n \"def remove(*, item : Any, list : Union[List[Any], ConduitVariable]) -> None:\\n list.remove(item)\",\n \"def remove(self, key: int | str):\\n self.__delitem__(key)\",\n \"def __delitem__(self, key):\\r\\n key = self.key(key)\\r\\n if key in self.data_with_same_key:\\r\\n if len(self.data_with_same_key[key]) == 1:\\r\\n self.data[key] = self.data_with_same_key.pop(key)[0]\\r\\n else:\\r\\n self.data[key] = self.data_with_same_key[key].pop(-1)\\r\\n else:\\r\\n del self.data[key]\",\n \"def delete_first(self):\\n self.deque.pop(0)\",\n \"def remove_entry(self, pos: int) -> None:\\n del self.entries[pos]\",\n \"def remove(self, x):\\n del self[self.index(x)]\",\n \"def remove(self, item):\\n index = self.get_all().index(item)\\n removed_item = self._items.pop(item)\\n previous_item, next_item = removed_item[1]\\n if item == self._first:\\n self._first = next_item\\n if next_item:\\n self._items[next_item][1][0] = None\\n elif item == self._last:\\n self._last = previous_item\\n if previous_item:\\n self._items[previous_item][1][1] = None\\n else:\\n if previous_item:\\n self._items[previous_item][1][1] = next_item\\n if next_item:\\n self._items[next_item][1][0] = previous_item\\n return index\",\n \"def __delitem__(self, key):\\n del self.list[key]\",\n \"def remove_item(self, item):\\n node = self.find(item)\\n if node:\\n self.delete(node)\\n return node.item\\n else:\\n return None\",\n \"def remove(self, value): # real signature unknown; restored from __doc__\\n pass\",\n \"def delete_item ( self ):\\n list, index = self.get_info()\\n self.value = list[:index] + list[index+1:]\",\n \"def __delitem__(self, idx):\\n # note that this may result in an empty HSP object, which should be\\n # invalid\\n del self._items[idx]\",\n \"def remove(self):\",\n \"def __delitem__(self, tid: int):\\n del self._cache[tid]\",\n \"def remove(self, e):\\n p = self._find_position(e) # try to locate existing element\\n if p is not None:\\n self._data.delete(p) # delete if found\",\n \"def remove_a_specific_item(self, index):\\n\\n current = self.head\\n previous = None\\n for i in range(index):\\n previous = current\\n current = current.next\\n if previous is None: self.head = current.next\\n else: previous.next = current.next\\n self.size -= 1\",\n \"def remove(self, item):\\n \\n previous = None\\n current = self.head\\n \\n while current is not None:\\n \\n if current.get_data() == item:\\n # If the item to be removed is the first item\\n if previous is None:\\n self.head = current.get_next()\\n else:\\n previous.set_next(current.get_next())\\n return\\n \\n else:\\n previous = current\\n current = current.get_next()\",\n \"def remove(self, item: Any) -> None:\\n curr = self._first\\n\\n if not curr:\\n raise ValueError\\n\\n elif curr.item == item:\\n self._first = self._first.next\\n self._length -= 1\\n\\n else:\\n while curr is not None:\\n if curr.next and curr.next.item == item:\\n curr.next = curr.next.next\\n self._length -= 1\\n return\\n curr = curr.next\\n raise ValueError\",\n \"def del_item(self, item):\\n index = self.board[item.pos[0]][item.pos[1]].index(item)\\n del self.board[item.pos[0]][item.pos[1]][index]\",\n \"def popitem(self):\\n all_items = self.items()\\n removed_item = random.choice(all_items)\\n self[removed_item[0]] = None\\n return removed_item\",\n \"def popitem(self): # real signature unknown; restored from __doc__\\n pass\",\n \"def discard(self, element: int) -> None:\\n self._used.discard(element)\\n if element < self.search_pos:\\n self.search_pos = element\",\n \"def remove(self, item):\\n try:\\n self._data.remove(item)\\n except ValueError as exc:\\n raise KeyError from exc\\n else:\\n self.__log__.append(SetRemove(value=item))\",\n \"def remove(self, x) -> None:\\n pass\",\n \"def remove(self, key: int) -> None:\\n chain, idx = self._search(key)\\n if idx is not None:\\n chain.pop(idx)\",\n \"def remove():\\n pass\",\n \"def remove(self, key):\\n self.arr[key] = -1\",\n \"def remove(self):\\n return self.queue.popleft()\",\n \"def __delitem__(self, key):\\n del self._data[key]\",\n \"def __delitem__(self, key: Hashable) -> None:\\n del self.contents[key]\\n return\",\n \"def __delitem__(self, key: Union[Any, int]) -> None:\\n if isinstance(key, int):\\n del self.contents[key]\\n else:\\n self.contents = [c for c in self.contents \\n if denovo.unit.get_name(c) != key]\\n return\",\n \"def remove(self, value):\\n found = False\\n for i in range(len(self.data)):\\n if self.data[i] != value:\\n pass\\n else:\\n found = True\\n self.__delitem__(i)\\n break\\n if not found:\\n raise ValueError\",\n \"def pop_from_deque(self):\",\n \"def delete(self, rgx):\\n newbuf = [l for l in self.buffer if not re.search(rgx, l)]\\n rval = [l for l in self.buffer if re.search(rgx, l)]\\n self.buffer = newbuf\\n return rval\",\n \"def remove(self, item):\\n item_found = False\\n\\n try:\\n # Traverse through the array to look for the 'item'\\n for i in range(len(self)):\\n if self.the_array[i] == item:\\n # Move every item after the 'item' found to left in order\\n # to remove the 'item'\\n for j in range(i, self.count - 1):\\n self.the_array[j] = self.the_array[j + 1]\\n self.count -= 1\\n item_found = True\\n\\n if (self.capacity // 2 >= self.BASE_SIZE) and (self.count < self.capacity / 8):\\n self._resize(self.capacity // 2)\\n break\\n\\n if not item_found:\\n raise ValueError\\n\\n except ValueError:\\n print(\\\"Item not found in list.\\\")\\n\\n return item_found\",\n \"def __delitem__(self, key: tuple):\\n s, a = key\\n del self.store[s][a]\",\n \"def remove(self):\\n if len(self.line) == 0:\\n raise ValueError, \\\"No more elements in the queue to remove.\\\"\\n\\n frontOfLine = self.line[-1]\\n self.line = self.line[:-1]\\n return frontOfLine\",\n \"def __delitem__(self, key):\\n pass\",\n \"def __delitem__(self, key):\\n pass\",\n \"def remove_one(self):\\n item = self.expiry.pop(0)\\n if item.updated:\\n self.new_expiry.append(item)\\n return\\n del self.index[item.target]\\n return\",\n \"def remove(self, key: int) -> None:\\n index = key % 10000\\n previous = self.array[index]\\n current = previous.next\\n while current:\\n if current.key == key:\\n previous.next = current.next\\n break\\n previous = previous.next\\n current = current.next\",\n \"def remove(self, key):\\n \\n # If there used to be a key, there must exist an old value blob somewhere in the database. It should be deallocated after a successful commit to disk.\\n if key in self.keys:\\n if self.keys[key] is not None:\\n punchat,punchlen = self.keys[key]\\n self.awaitingpunch.append((punchat, punchlen))\\n\\n self.keys.pop(key, None)\\n self.buffered.pop(key, None)\\n self.cache.pop(key, None)\\n\\n if self.autocommit:\\n commit()\",\n \"def remove(self, p_int, p_int_1=None): # real signature unknown; restored from __doc__ with multiple overloads\\n pass\",\n \"def __delitem__(self, key):\\n self.delete(key)\",\n \"def __delitem__(self, key):\\n self.delete(key)\",\n \"def popitem(self):\\n pass\",\n \"def remove(self, value):\\n pass\",\n \"def __delitem__(self,key):\\n if key in self.changed: self.changed.remove(key)\\n if key not in self.deleted: self.deleted.append(key)\\n del self.data[key]\",\n \"def __delitem__(self, userid):\\r\\n self.removePlayer(userid)\",\n \"def remove_item(self,itm):\\n inv = self.get_inventory()\\n s = str(itm)\\n if s in inv:\\n if inv[s] > 1:\\n inv[s] -= 1\\n else:\\n del inv[s]\\n self.put_inventory(inv)\",\n \"def __delitem__(self, index):\\n # delete the column\\n del self._data[index]\\n\\n # adjust the number of columns\\n self._nrows -= 1\",\n \"def __delitem__(self, key):\\n del self.elements[key]\",\n \"def delete_item(self, key):\\n deleted_slot = self.count_hash(key, len(self.slots))\\n\\n if self.slots[deleted_slot] == key:\\n self.slots[deleted_slot] = None\\n self.data[deleted_slot] = None\\n elif isinstance(self.slots[deleted_slot], tuple):\\n index_tuple = (self.slots[deleted_slot].index(key))\\n list_slot = list(self.slots[deleted_slot])\\n list_data = list(self.data[deleted_slot])\\n list_slot.pop(index_tuple)\\n list_data.pop(index_tuple)\\n self.slots[deleted_slot] = tuple(list_slot)\\n self.data[deleted_slot] = tuple(list_data)\",\n \"def pop(self):\",\n \"def pop(self):\",\n \"def __delitem__(self, key):\\n del self._get_storage()[key]\",\n \"def remove_item(self, item: tuple) -> None:\\n self._antecedent.remove(item)\\n self._is_updated = False\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7478718","0.7395259","0.70754623","0.70754623","0.70691514","0.7067231","0.6973058","0.6886449","0.6886449","0.68595606","0.6845985","0.6819009","0.67979664","0.6790535","0.6789824","0.6737365","0.6720759","0.67044306","0.66581875","0.66425633","0.66389936","0.65886813","0.65699935","0.6560922","0.65422744","0.652208","0.6516925","0.6510133","0.6497852","0.64795005","0.6474609","0.6470152","0.64559567","0.6454891","0.64474857","0.64423627","0.6424373","0.64109755","0.6398717","0.63949156","0.63716304","0.6369647","0.6366219","0.63544714","0.6343893","0.6337438","0.63363063","0.63351583","0.63309795","0.6328636","0.6327127","0.6309966","0.6309218","0.6297342","0.6294882","0.62944484","0.6293658","0.62843835","0.62771124","0.6272826","0.6272531","0.6264139","0.6259828","0.6259627","0.6255532","0.6255259","0.6247992","0.6236711","0.62336177","0.6231454","0.6228204","0.6227258","0.6221064","0.6220776","0.62093925","0.620876","0.6206738","0.6197622","0.6197462","0.61965245","0.61882997","0.61882997","0.61752","0.61645347","0.61643994","0.61579764","0.6156186","0.6156186","0.6152468","0.614103","0.6140467","0.6140391","0.6139622","0.6128827","0.6127875","0.6125717","0.6117398","0.6117398","0.61163956","0.61123973"],"string":"[\n \"0.7478718\",\n \"0.7395259\",\n \"0.70754623\",\n \"0.70754623\",\n \"0.70691514\",\n \"0.7067231\",\n \"0.6973058\",\n \"0.6886449\",\n \"0.6886449\",\n \"0.68595606\",\n \"0.6845985\",\n \"0.6819009\",\n \"0.67979664\",\n \"0.6790535\",\n \"0.6789824\",\n \"0.6737365\",\n \"0.6720759\",\n \"0.67044306\",\n \"0.66581875\",\n \"0.66425633\",\n \"0.66389936\",\n \"0.65886813\",\n \"0.65699935\",\n \"0.6560922\",\n \"0.65422744\",\n \"0.652208\",\n \"0.6516925\",\n \"0.6510133\",\n \"0.6497852\",\n \"0.64795005\",\n \"0.6474609\",\n \"0.6470152\",\n \"0.64559567\",\n \"0.6454891\",\n \"0.64474857\",\n \"0.64423627\",\n \"0.6424373\",\n \"0.64109755\",\n \"0.6398717\",\n \"0.63949156\",\n \"0.63716304\",\n \"0.6369647\",\n \"0.6366219\",\n \"0.63544714\",\n \"0.6343893\",\n \"0.6337438\",\n \"0.63363063\",\n \"0.63351583\",\n \"0.63309795\",\n \"0.6328636\",\n \"0.6327127\",\n \"0.6309966\",\n \"0.6309218\",\n \"0.6297342\",\n \"0.6294882\",\n \"0.62944484\",\n \"0.6293658\",\n \"0.62843835\",\n \"0.62771124\",\n \"0.6272826\",\n \"0.6272531\",\n \"0.6264139\",\n \"0.6259828\",\n \"0.6259627\",\n \"0.6255532\",\n \"0.6255259\",\n \"0.6247992\",\n \"0.6236711\",\n \"0.62336177\",\n \"0.6231454\",\n \"0.6228204\",\n \"0.6227258\",\n \"0.6221064\",\n \"0.6220776\",\n \"0.62093925\",\n \"0.620876\",\n \"0.6206738\",\n \"0.6197622\",\n \"0.6197462\",\n \"0.61965245\",\n \"0.61882997\",\n \"0.61882997\",\n \"0.61752\",\n \"0.61645347\",\n \"0.61643994\",\n \"0.61579764\",\n \"0.6156186\",\n \"0.6156186\",\n \"0.6152468\",\n \"0.614103\",\n \"0.6140467\",\n \"0.6140391\",\n \"0.6139622\",\n \"0.6128827\",\n \"0.6127875\",\n \"0.6125717\",\n \"0.6117398\",\n \"0.6117398\",\n \"0.61163956\",\n \"0.61123973\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7550008"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81773,"cells":{"query":{"kind":"string","value":"Remove the first item in the buffer"},"document":{"kind":"string","value":"def pop_first(self):\n self.pop_item(0)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def delete_first(self):\n self.deque.pop(0)","def delete(self):\n first = self.data[0]\n self.data.pop(0)\n self.size = self.size - 1\n return first","def pop_item(self, index):\n ix, obj = self.items\n if index < len(ix):\n self.d_buffer.pop(ix[index])\n else:\n raise IndexError('Buffer does not have {0} elements'.format(index))","def pop(self):\n value = self.buffer[self.end - 1]\n self.buffer[self.end - 1] = None\n self.end = (self.end - 1) % len(self.buffer)\n return value","def remove_first(self):\n if self.is_empty(): raise RuntimeError(\"Empty list\")\n\n data = self.head.data\n self.head = self.head.nxt\n self.size -= 1\n\n if self.is_empty(): self.tail = None\n else: self.head.prev = None\n\n return data","def pop(self):\n data = self.buffer.getvalue()\n self.buffer.seek(0)\n self.buffer.truncate()\n return data","def remove_first(self):\n if self.is_empty():\n raise IndexError\n else:\n self._first = self._rest._first\n if self._rest.is_empty():\n self._rest = None\n else:\n self._rest = self._rest._rest","def __remove_first(self):\n if self.__head is not None:\n self.__length -= 1\n self.__head = self.__head.next()\n if self.__length == 0: # when there are no more elements in the list,\n self.__last = None # remove the pointer to the last element","def _pop_first(self) -> Any:\n if self.is_empty():\n raise IndexError\n return self.pop(0)","def pop(self):\r\n return self.buff.pop(-1)","def remove(self):\r\n if self.first() is not None:\r\n self.dec_size()\r\n self.set_first(self.first().next())\r\n if self.size() == 0: # when there are no more elements in the list,\r\n self.__last = None # remove the pointer to the last element\r","def delete_first(self):\n if self.n == 0:\n return None\n first = self.A[1]\n self.n -= 1\n last = self.A.pop()\n if self.n > 0:\n self.A[1] = last\n self.pos[last[0]] = 1\n self.combine(1)\n return first[0]","def take(self, item): \n self.contents.remove(item)","def remove_front(self):\n\n if self.items:\n return self.items.pop(0)\n return None","def popleft(self):\n value = self.buffer[self.start]\n self.buffer[self.start] = None\n self.start = (self.start + 1) % len(self.buffer)\n return value","def delete(self) -> None:\n if not self.buffer or self.index == len(self.buffer):\n return\n\n self.buffer.delete(self.index)\n\n if 0 < self.index > self.buffer.end:\n self.index = self.buffer.end","def popitem(self):\n return self.pop(0)","def delete_first(self):\n if self.is_empty():\n raise Empty(\"List is empty\")\n return self._delete_node(self._header._next)","def pop(self):\n if len(self) == 0:\n if self.none_for_empty:\n return None\n raise ValueError(\"Buffer is empty\")\n pt = self.buf[self.front]\n if self.rear == self.front:\n self.rear = None\n else:\n self.front = self.length - 1 if self.front == 0 else self.front - 1\n return pt","def remove(self):\n if len(self.line) == 0:\n raise ValueError, \"No more elements in the queue to remove.\"\n\n frontOfLine = self.line[-1]\n self.line = self.line[:-1]\n return frontOfLine","def remove_buffered_packets(self):\n seq = self.next_seq\n while True:\n p = self.buffer.pop(seq, None)\n if p is None:\n break\n else:\n seq += len(p.data)\n yield p","def pop_from_deque(self):","def test_removing_the_first_val_in_deque(filled_deque):\n assert filled_deque.popleft() == 4","def delete_first(self):\n if self.is_empty():\n raise Empty('list is empty')\n answer = self._head._element\n self._head = self._head._next\n self._size -= 1\n if self.is_empty(): # special case as deque is empty\n self._tail = None # removed head had been the tail\n else:\n self._head._prev = None\n return answer","def _primerElem(l):\n return l[0]","def removeFirst(self):\n if self.__nelems == 0:\n raise BaseException('Empty List')\n\n temp = self.__head\n if self.__nelems == 1:\n self.__head = self.__tail = None\n\n else:\n self.__head = temp.getNext()\n temp.setNext(None)\n\n self.__nelems -= 1\n\n return temp.getData()","def pop_rear(self):\n if len(self) == 0:\n if self.none_for_empty:\n return None\n raise ValueError(\"Buffer is empty\")\n pt = self.buf[self.rear]\n if self.rear == self.front:\n self.rear = None\n else:\n self.rear = (self.rear + 1) % self.length\n return pt","def pop(self):\n return self.remove(0)","def delete_first(self):\n if self._size == 0:\n raise Empty('Dequeue is empty')\n return self._delete_node(self._head._next)","def _clean_first_key_from_registry(self):\n # only clean the first entry from the list\n to_clean = self._buffered_backend_keys[0]\n for registry_key in list(self.chunks_registry.keys()):\n if to_clean in registry_key:\n del self.chunks_registry[registry_key]\n del self._buffered_backend_keys[0]","def delete_last(self):\n self.deque.pop()","def pop(self):\n return super().remove_item_from_front()","def pop(self):\n while self.number > self.maxlength:\n self.buffer.popleft()\n self.number -= 1","def drop_first(count):\n def _drop_first(iterable):\n g = (x for x in range(1, count + 1))\n return dropwhile(\n lambda i: unless(StopIteration, lambda: next(g))(), iterable)\n return pipe | set_name('drop_first(%s)' % count, _drop_first)","def pop(self):\n return self.ll.delete_first()","def chop(x):\n del x[0]\n l = len(x)\n del x[l-1]","def remove_rear(self):\n\n if self.items:\n return self.items.pop()\n return None","def next(self):\n # type: () -> T\n if len(self.buffer) == 0:\n raise StopIteration\n self.prev = self.buffer.pop()\n self._buffer_to(self.lookahead)\n return self.prev","def remove_first(self):\n if self.is_empty():\n raise self.NoSuchNodeException()\n\n tmp_val = self.head.data\n self.head = self.head.next_node\n self.list_size -= 1\n return tmp_val","def remove(self, index):\n if index < 0 or index >= len(self):\n raise AttributeError(\"i must be >= 0 and < size of queue\")\n if index == 0:\n oldItem = self._front.data\n self._front = self._front.next\n else:\n probe = self._front\n while index > 1:\n probe = probe.next\n index -= 1\n oldItem = probe.next.data\n probe.next = probe.next.next\n self._size -= 1\n if self.isEmpty():\n self._rear = None\n return oldItem","def remove_first(self):\n # return None if there are no Nodes\n if self.head is None:\n return None\n # save and disconect the first Node from the list\n # and set the head to the next Node\n removed = self.head\n self.head = self.head.next\n removed.next = None\n # set the tail as None if list got empty\n if self.head is None:\n self.tail = None\n # remove the skip back pointer from the second Node if needed\n elif self.head.next is not None:\n self.head.next.skip_back = None\n \n return removed.data","def removeFront(self):\n if self._size == 0:\n raise AttributeError(\"Cannot removeFront from an empty Deque\")\n \n temp = self._front\n self._front = self._front.getPrevious()\n if self._size == 1:\n # removing only item which is the rear as well as the front item\n self._rear = None\n else:\n self._front.setNext(None)\n self._size -= 1\n \n return temp.getData()","def delete_first(self):\n if self.is_empty():\n raise Empty('list is empty')\n return self._delete_node(self._head._next)","def removeFromFront(self):\n if self.size <= 0:\n raise IndexError(\"the array is empty\")\n self._shrinkCheck()\n super().removeFromFront()","def pop(self):\n if len(self._data) == 0:\n return None\n else:\n return self._data.pop(0)","def dequeue(self):\n\n item = self.__items__.pop(0)\n return item","def array_pop(item):\n return item.pop()","def dequeue(self):\n\n return self._data.pop(0)","def remove(self, index):\n item = self._items.pop(index)\n if item in self._data:\n data = self._data.pop(item)\n else:\n data = None\n return item, data","def clear_buffer(self):\n for i, value in enumerate(self.buffer):\n self.buffer[i] = 0","def popitem(self):\n pass","def __delitem__(self, where):\n with self._lock:\n self._current_bytes -= self._data[where]\n del self._data[where]\n self._order.remove(where)","def __next__(self) -> T:\n buffer = self._buffer\n\n if buffer:\n return buffer.popleft()\n else:\n return next(self._iterator)","def remove(self):\n return self.queue.popleft()","def pop_message(self):\n app_process = sqlite3.connect('app_process::memory:', check_same_thread=False)\n app_process_cursor = app_process.cursor()\n app_process_cursor.execute(\"SELECT * FROM message_queue WHERE tstamp==(:first)\", {\"first\":self.mq_first}) \n item = app_process_cursor.fetchone()\n if item == None:\n return\n app_process_cursor.execute(\"DELETE FROM message_queue WHERE tstamp==(:first)\", {\"first\":self.mq_first})\n self.mq_first = item[4] #now sets first to next item pointed to\n app_process.commit()\n app_process.close()\n return item","def remove(self, index):\n self.data.pop(index)","def dequeue(self) -> object:\n return self._data.pop(0)","def dequeue(self) -> object:\n return self._data.pop(0)","def pop(self):\r\n\r\n if not self.is_empty():\r\n\r\n half_cap = self._capacity // 2\r\n item = self._data[self._size-1]\r\n self._data[self._size-1] = 0\r\n self._size -= 1\r\n\r\n if self._size <= half_cap:\r\n if half_cap != 0:\r\n\r\n self.shrink()\r\n\r\n return item\r\n\r\n else:\r\n pass","def remove(self) -> T:\n if self.is_empty():\n raise EmptyStackError\n else:\n self._size -= 1\n return self._items.pop()","def remove_one(self):\n item = self.expiry.pop(0)\n if item.updated:\n self.new_expiry.append(item)\n return\n del self.index[item.target]\n return","def remove_last_item_from_stack(self):\n if self.length > 0:\n return self.container.pop()\n else:\n return None","def pop(self) -> int:\r\n return self.items.pop(0)","def remove(self, item) -> None:\n entry = self.entry_finder.pop(item)\n entry[-1][0] = None","def remove(self, index):\n if index >= len(self):\n raise IndexError\n else:\n if index == 0:\n self.remove_first()\n else:\n self._rest.remove(index-1)","def pop(self):","def pop(self):","def backspace(self) -> None:\n if self.index:\n self.buffer.delete(self.index - 1)\n self.index -= 1","def __delitem__(self, idx):\n self.pop(idx)","def unshift(self, chunk):\n if chunk:\n self._pos -= len(chunk)\n self._unconsumed.append(chunk)","def remove():","def pop():","def remove(self, key):\r\n for i in range(len(self.lis)):\r\n if self.lis[i][0] == key:\r\n self.lis.pop(i)\r\n break","def pop_last(self):\n self.pop_item(-1)","def pop(self):\n b = self.a[-1]\n del self.a[-1]\n return b","def remove_first(lst, elem):\n \"*** YOUR CODE HERE ***\"\n if len(lst) <= 0:\n return []\n if lst[0] == elem:\n return lst[1:]\n return lst[:1] + remove_first(lst[1:], elem)","def remove(self, item: Any) -> None:\n curr = self._first\n\n if not curr:\n raise ValueError\n\n elif curr.item == item:\n self._first = self._first.next\n self._length -= 1\n\n else:\n while curr is not None:\n if curr.next and curr.next.item == item:\n curr.next = curr.next.next\n self._length -= 1\n return\n curr = curr.next\n raise ValueError","def remove(self, key: int) -> None:\n idx = key % self.size\n if self.mp[idx]:\n for i in range(len(self.mp[idx])):\n if self.mp[idx][i][0] == key:\n #self.mp[idx].pop(i)\n del self.mp[idx][i]\n break","def remove_min(self):\r\n # Should raise an exception of size is 0...\r\n if self._size == 0: raise KeyError # Can't remove from an empty heap\r\n result = self._data[0] # remember the smallest\r\n self._data[0] = None # None is so we don't have a reference.\r\n self._size -= 1 # don't forget we have one less\r\n # bring the last to the front and stick the None at the end\r\n self.swap(0, self._size)\r\n # and let the item inserted at the front \"drift down\"\r\n self.down_heap(0)\r\n return result # finally return what was the minimum\r","def discard(self, element: int) -> None:\n self._used.discard(element)\n if element < self.search_pos:\n self.search_pos = element","def remove_front(self):\n\n if self.front.next is None:\n temp = self.front\n self.front = None\n return temp.data\n\n temp = self.front\n self.front = self.front.next\n return temp.data","def pop(self, index=None, last=True):\n if index == None:\n return super().pop(last)\n else:\n ret = self[index]\n self.remove(ret)\n return ret","def remove(self, item):\n \n previous = None\n current = self.head\n \n while current is not None:\n \n if current.get_data() == item:\n # If the item to be removed is the first item\n if previous is None:\n self.head = current.get_next()\n else:\n previous.set_next(current.get_next())\n return\n \n else:\n previous = current\n current = current.get_next()","def port_buffer_drop():","def delete_at_beginning(self) -> None:\n current = self.head\n if current is None:\n return None\n else:\n self.head = self.head.get_next_node()\n self.head.set_previous_node(None)\n temp = current.get_data()\n del current\n self._decrease_length()\n return temp","def dequeue(self): # total O(1)\n topItem = self._queue[self._start] #O(1)\n self._queue[self._start] = None #O(1)\n self._start = (self._start+1)% self._capacity #O(1)\n self._size -= 1 #O(1)\n return topItem #O(1)","def delete(self, rgx):\n newbuf = [l for l in self.buffer if not re.search(rgx, l)]\n rval = [l for l in self.buffer if re.search(rgx, l)]\n self.buffer = newbuf\n return rval","def pop(self):\n if self._size > 0:\n elem = self.first.data\n self.first = self.first.next\n self._size = self._size - 1\n return elem\n \n raise IndexError('The queue is empty! ')","def __delitem__(self, index: Any) -> None:\n del self.contents[index]\n return","def pop(self):\r\n return self.queue.pop(0)","def dequeue(self):\n\t\treturn self.items.pop()","def GetMainBuffer(self):\n tmp = self.buffers[0]\n self.buffers[0] = []\n return tmp","def discard(self, item):\n try:\n counter = self._get(item) - 1\n except KeyError:\n return\n\n if counter <= 0:\n self._del(item)\n else:\n self._set(item, counter)","def remove(self, key):\n index = int((keyIndex(key) & (self.BUCKET_SIZE - 1)))\n inner = self.keys[index]\n if inner == None:\n return None\n i = 0\n while len(inner):\n if inner[i] == self.EMPTY_KEY:\n break\n if inner[i] == key:\n value = self.values[index][i]\n while len(inner):\n if inner[i] == self.EMPTY_KEY:\n break\n inner[i - 1] = inner[i]\n self.values[index][i - 1] = self.values[index][i]\n i += 1\n inner[i - 1] = self.EMPTY_KEY\n self.values[index][i - 1] = None\n self.size -= 1\n self.modCount += 1\n return value\n i += 1\n return None","def remove(self, key: int) -> None:\n index = key % 10000\n previous = self.array[index]\n current = previous.next\n while current:\n if current.key == key:\n previous.next = current.next\n break\n previous = previous.next\n current = current.next","def pop(self):\n if self.items:\n return self.items.pop()\n return None","def _discard_excess_bytes(self):\n discard_len = min(self._discard, len(self._buffer))\n del self._buffer[:discard_len]\n self._discard -= discard_len","def dequeue(self):\n if len(self) == 1:\n self.tail = None\n return self.pop()","def popitem(self): # real signature unknown; restored from __doc__\n pass","def dequeue(self):\n return self.items.pop()"],"string":"[\n \"def delete_first(self):\\n self.deque.pop(0)\",\n \"def delete(self):\\n first = self.data[0]\\n self.data.pop(0)\\n self.size = self.size - 1\\n return first\",\n \"def pop_item(self, index):\\n ix, obj = self.items\\n if index < len(ix):\\n self.d_buffer.pop(ix[index])\\n else:\\n raise IndexError('Buffer does not have {0} elements'.format(index))\",\n \"def pop(self):\\n value = self.buffer[self.end - 1]\\n self.buffer[self.end - 1] = None\\n self.end = (self.end - 1) % len(self.buffer)\\n return value\",\n \"def remove_first(self):\\n if self.is_empty(): raise RuntimeError(\\\"Empty list\\\")\\n\\n data = self.head.data\\n self.head = self.head.nxt\\n self.size -= 1\\n\\n if self.is_empty(): self.tail = None\\n else: self.head.prev = None\\n\\n return data\",\n \"def pop(self):\\n data = self.buffer.getvalue()\\n self.buffer.seek(0)\\n self.buffer.truncate()\\n return data\",\n \"def remove_first(self):\\n if self.is_empty():\\n raise IndexError\\n else:\\n self._first = self._rest._first\\n if self._rest.is_empty():\\n self._rest = None\\n else:\\n self._rest = self._rest._rest\",\n \"def __remove_first(self):\\n if self.__head is not None:\\n self.__length -= 1\\n self.__head = self.__head.next()\\n if self.__length == 0: # when there are no more elements in the list,\\n self.__last = None # remove the pointer to the last element\",\n \"def _pop_first(self) -> Any:\\n if self.is_empty():\\n raise IndexError\\n return self.pop(0)\",\n \"def pop(self):\\r\\n return self.buff.pop(-1)\",\n \"def remove(self):\\r\\n if self.first() is not None:\\r\\n self.dec_size()\\r\\n self.set_first(self.first().next())\\r\\n if self.size() == 0: # when there are no more elements in the list,\\r\\n self.__last = None # remove the pointer to the last element\\r\",\n \"def delete_first(self):\\n if self.n == 0:\\n return None\\n first = self.A[1]\\n self.n -= 1\\n last = self.A.pop()\\n if self.n > 0:\\n self.A[1] = last\\n self.pos[last[0]] = 1\\n self.combine(1)\\n return first[0]\",\n \"def take(self, item): \\n self.contents.remove(item)\",\n \"def remove_front(self):\\n\\n if self.items:\\n return self.items.pop(0)\\n return None\",\n \"def popleft(self):\\n value = self.buffer[self.start]\\n self.buffer[self.start] = None\\n self.start = (self.start + 1) % len(self.buffer)\\n return value\",\n \"def delete(self) -> None:\\n if not self.buffer or self.index == len(self.buffer):\\n return\\n\\n self.buffer.delete(self.index)\\n\\n if 0 < self.index > self.buffer.end:\\n self.index = self.buffer.end\",\n \"def popitem(self):\\n return self.pop(0)\",\n \"def delete_first(self):\\n if self.is_empty():\\n raise Empty(\\\"List is empty\\\")\\n return self._delete_node(self._header._next)\",\n \"def pop(self):\\n if len(self) == 0:\\n if self.none_for_empty:\\n return None\\n raise ValueError(\\\"Buffer is empty\\\")\\n pt = self.buf[self.front]\\n if self.rear == self.front:\\n self.rear = None\\n else:\\n self.front = self.length - 1 if self.front == 0 else self.front - 1\\n return pt\",\n \"def remove(self):\\n if len(self.line) == 0:\\n raise ValueError, \\\"No more elements in the queue to remove.\\\"\\n\\n frontOfLine = self.line[-1]\\n self.line = self.line[:-1]\\n return frontOfLine\",\n \"def remove_buffered_packets(self):\\n seq = self.next_seq\\n while True:\\n p = self.buffer.pop(seq, None)\\n if p is None:\\n break\\n else:\\n seq += len(p.data)\\n yield p\",\n \"def pop_from_deque(self):\",\n \"def test_removing_the_first_val_in_deque(filled_deque):\\n assert filled_deque.popleft() == 4\",\n \"def delete_first(self):\\n if self.is_empty():\\n raise Empty('list is empty')\\n answer = self._head._element\\n self._head = self._head._next\\n self._size -= 1\\n if self.is_empty(): # special case as deque is empty\\n self._tail = None # removed head had been the tail\\n else:\\n self._head._prev = None\\n return answer\",\n \"def _primerElem(l):\\n return l[0]\",\n \"def removeFirst(self):\\n if self.__nelems == 0:\\n raise BaseException('Empty List')\\n\\n temp = self.__head\\n if self.__nelems == 1:\\n self.__head = self.__tail = None\\n\\n else:\\n self.__head = temp.getNext()\\n temp.setNext(None)\\n\\n self.__nelems -= 1\\n\\n return temp.getData()\",\n \"def pop_rear(self):\\n if len(self) == 0:\\n if self.none_for_empty:\\n return None\\n raise ValueError(\\\"Buffer is empty\\\")\\n pt = self.buf[self.rear]\\n if self.rear == self.front:\\n self.rear = None\\n else:\\n self.rear = (self.rear + 1) % self.length\\n return pt\",\n \"def pop(self):\\n return self.remove(0)\",\n \"def delete_first(self):\\n if self._size == 0:\\n raise Empty('Dequeue is empty')\\n return self._delete_node(self._head._next)\",\n \"def _clean_first_key_from_registry(self):\\n # only clean the first entry from the list\\n to_clean = self._buffered_backend_keys[0]\\n for registry_key in list(self.chunks_registry.keys()):\\n if to_clean in registry_key:\\n del self.chunks_registry[registry_key]\\n del self._buffered_backend_keys[0]\",\n \"def delete_last(self):\\n self.deque.pop()\",\n \"def pop(self):\\n return super().remove_item_from_front()\",\n \"def pop(self):\\n while self.number > self.maxlength:\\n self.buffer.popleft()\\n self.number -= 1\",\n \"def drop_first(count):\\n def _drop_first(iterable):\\n g = (x for x in range(1, count + 1))\\n return dropwhile(\\n lambda i: unless(StopIteration, lambda: next(g))(), iterable)\\n return pipe | set_name('drop_first(%s)' % count, _drop_first)\",\n \"def pop(self):\\n return self.ll.delete_first()\",\n \"def chop(x):\\n del x[0]\\n l = len(x)\\n del x[l-1]\",\n \"def remove_rear(self):\\n\\n if self.items:\\n return self.items.pop()\\n return None\",\n \"def next(self):\\n # type: () -> T\\n if len(self.buffer) == 0:\\n raise StopIteration\\n self.prev = self.buffer.pop()\\n self._buffer_to(self.lookahead)\\n return self.prev\",\n \"def remove_first(self):\\n if self.is_empty():\\n raise self.NoSuchNodeException()\\n\\n tmp_val = self.head.data\\n self.head = self.head.next_node\\n self.list_size -= 1\\n return tmp_val\",\n \"def remove(self, index):\\n if index < 0 or index >= len(self):\\n raise AttributeError(\\\"i must be >= 0 and < size of queue\\\")\\n if index == 0:\\n oldItem = self._front.data\\n self._front = self._front.next\\n else:\\n probe = self._front\\n while index > 1:\\n probe = probe.next\\n index -= 1\\n oldItem = probe.next.data\\n probe.next = probe.next.next\\n self._size -= 1\\n if self.isEmpty():\\n self._rear = None\\n return oldItem\",\n \"def remove_first(self):\\n # return None if there are no Nodes\\n if self.head is None:\\n return None\\n # save and disconect the first Node from the list\\n # and set the head to the next Node\\n removed = self.head\\n self.head = self.head.next\\n removed.next = None\\n # set the tail as None if list got empty\\n if self.head is None:\\n self.tail = None\\n # remove the skip back pointer from the second Node if needed\\n elif self.head.next is not None:\\n self.head.next.skip_back = None\\n \\n return removed.data\",\n \"def removeFront(self):\\n if self._size == 0:\\n raise AttributeError(\\\"Cannot removeFront from an empty Deque\\\")\\n \\n temp = self._front\\n self._front = self._front.getPrevious()\\n if self._size == 1:\\n # removing only item which is the rear as well as the front item\\n self._rear = None\\n else:\\n self._front.setNext(None)\\n self._size -= 1\\n \\n return temp.getData()\",\n \"def delete_first(self):\\n if self.is_empty():\\n raise Empty('list is empty')\\n return self._delete_node(self._head._next)\",\n \"def removeFromFront(self):\\n if self.size <= 0:\\n raise IndexError(\\\"the array is empty\\\")\\n self._shrinkCheck()\\n super().removeFromFront()\",\n \"def pop(self):\\n if len(self._data) == 0:\\n return None\\n else:\\n return self._data.pop(0)\",\n \"def dequeue(self):\\n\\n item = self.__items__.pop(0)\\n return item\",\n \"def array_pop(item):\\n return item.pop()\",\n \"def dequeue(self):\\n\\n return self._data.pop(0)\",\n \"def remove(self, index):\\n item = self._items.pop(index)\\n if item in self._data:\\n data = self._data.pop(item)\\n else:\\n data = None\\n return item, data\",\n \"def clear_buffer(self):\\n for i, value in enumerate(self.buffer):\\n self.buffer[i] = 0\",\n \"def popitem(self):\\n pass\",\n \"def __delitem__(self, where):\\n with self._lock:\\n self._current_bytes -= self._data[where]\\n del self._data[where]\\n self._order.remove(where)\",\n \"def __next__(self) -> T:\\n buffer = self._buffer\\n\\n if buffer:\\n return buffer.popleft()\\n else:\\n return next(self._iterator)\",\n \"def remove(self):\\n return self.queue.popleft()\",\n \"def pop_message(self):\\n app_process = sqlite3.connect('app_process::memory:', check_same_thread=False)\\n app_process_cursor = app_process.cursor()\\n app_process_cursor.execute(\\\"SELECT * FROM message_queue WHERE tstamp==(:first)\\\", {\\\"first\\\":self.mq_first}) \\n item = app_process_cursor.fetchone()\\n if item == None:\\n return\\n app_process_cursor.execute(\\\"DELETE FROM message_queue WHERE tstamp==(:first)\\\", {\\\"first\\\":self.mq_first})\\n self.mq_first = item[4] #now sets first to next item pointed to\\n app_process.commit()\\n app_process.close()\\n return item\",\n \"def remove(self, index):\\n self.data.pop(index)\",\n \"def dequeue(self) -> object:\\n return self._data.pop(0)\",\n \"def dequeue(self) -> object:\\n return self._data.pop(0)\",\n \"def pop(self):\\r\\n\\r\\n if not self.is_empty():\\r\\n\\r\\n half_cap = self._capacity // 2\\r\\n item = self._data[self._size-1]\\r\\n self._data[self._size-1] = 0\\r\\n self._size -= 1\\r\\n\\r\\n if self._size <= half_cap:\\r\\n if half_cap != 0:\\r\\n\\r\\n self.shrink()\\r\\n\\r\\n return item\\r\\n\\r\\n else:\\r\\n pass\",\n \"def remove(self) -> T:\\n if self.is_empty():\\n raise EmptyStackError\\n else:\\n self._size -= 1\\n return self._items.pop()\",\n \"def remove_one(self):\\n item = self.expiry.pop(0)\\n if item.updated:\\n self.new_expiry.append(item)\\n return\\n del self.index[item.target]\\n return\",\n \"def remove_last_item_from_stack(self):\\n if self.length > 0:\\n return self.container.pop()\\n else:\\n return None\",\n \"def pop(self) -> int:\\r\\n return self.items.pop(0)\",\n \"def remove(self, item) -> None:\\n entry = self.entry_finder.pop(item)\\n entry[-1][0] = None\",\n \"def remove(self, index):\\n if index >= len(self):\\n raise IndexError\\n else:\\n if index == 0:\\n self.remove_first()\\n else:\\n self._rest.remove(index-1)\",\n \"def pop(self):\",\n \"def pop(self):\",\n \"def backspace(self) -> None:\\n if self.index:\\n self.buffer.delete(self.index - 1)\\n self.index -= 1\",\n \"def __delitem__(self, idx):\\n self.pop(idx)\",\n \"def unshift(self, chunk):\\n if chunk:\\n self._pos -= len(chunk)\\n self._unconsumed.append(chunk)\",\n \"def remove():\",\n \"def pop():\",\n \"def remove(self, key):\\r\\n for i in range(len(self.lis)):\\r\\n if self.lis[i][0] == key:\\r\\n self.lis.pop(i)\\r\\n break\",\n \"def pop_last(self):\\n self.pop_item(-1)\",\n \"def pop(self):\\n b = self.a[-1]\\n del self.a[-1]\\n return b\",\n \"def remove_first(lst, elem):\\n \\\"*** YOUR CODE HERE ***\\\"\\n if len(lst) <= 0:\\n return []\\n if lst[0] == elem:\\n return lst[1:]\\n return lst[:1] + remove_first(lst[1:], elem)\",\n \"def remove(self, item: Any) -> None:\\n curr = self._first\\n\\n if not curr:\\n raise ValueError\\n\\n elif curr.item == item:\\n self._first = self._first.next\\n self._length -= 1\\n\\n else:\\n while curr is not None:\\n if curr.next and curr.next.item == item:\\n curr.next = curr.next.next\\n self._length -= 1\\n return\\n curr = curr.next\\n raise ValueError\",\n \"def remove(self, key: int) -> None:\\n idx = key % self.size\\n if self.mp[idx]:\\n for i in range(len(self.mp[idx])):\\n if self.mp[idx][i][0] == key:\\n #self.mp[idx].pop(i)\\n del self.mp[idx][i]\\n break\",\n \"def remove_min(self):\\r\\n # Should raise an exception of size is 0...\\r\\n if self._size == 0: raise KeyError # Can't remove from an empty heap\\r\\n result = self._data[0] # remember the smallest\\r\\n self._data[0] = None # None is so we don't have a reference.\\r\\n self._size -= 1 # don't forget we have one less\\r\\n # bring the last to the front and stick the None at the end\\r\\n self.swap(0, self._size)\\r\\n # and let the item inserted at the front \\\"drift down\\\"\\r\\n self.down_heap(0)\\r\\n return result # finally return what was the minimum\\r\",\n \"def discard(self, element: int) -> None:\\n self._used.discard(element)\\n if element < self.search_pos:\\n self.search_pos = element\",\n \"def remove_front(self):\\n\\n if self.front.next is None:\\n temp = self.front\\n self.front = None\\n return temp.data\\n\\n temp = self.front\\n self.front = self.front.next\\n return temp.data\",\n \"def pop(self, index=None, last=True):\\n if index == None:\\n return super().pop(last)\\n else:\\n ret = self[index]\\n self.remove(ret)\\n return ret\",\n \"def remove(self, item):\\n \\n previous = None\\n current = self.head\\n \\n while current is not None:\\n \\n if current.get_data() == item:\\n # If the item to be removed is the first item\\n if previous is None:\\n self.head = current.get_next()\\n else:\\n previous.set_next(current.get_next())\\n return\\n \\n else:\\n previous = current\\n current = current.get_next()\",\n \"def port_buffer_drop():\",\n \"def delete_at_beginning(self) -> None:\\n current = self.head\\n if current is None:\\n return None\\n else:\\n self.head = self.head.get_next_node()\\n self.head.set_previous_node(None)\\n temp = current.get_data()\\n del current\\n self._decrease_length()\\n return temp\",\n \"def dequeue(self): # total O(1)\\n topItem = self._queue[self._start] #O(1)\\n self._queue[self._start] = None #O(1)\\n self._start = (self._start+1)% self._capacity #O(1)\\n self._size -= 1 #O(1)\\n return topItem #O(1)\",\n \"def delete(self, rgx):\\n newbuf = [l for l in self.buffer if not re.search(rgx, l)]\\n rval = [l for l in self.buffer if re.search(rgx, l)]\\n self.buffer = newbuf\\n return rval\",\n \"def pop(self):\\n if self._size > 0:\\n elem = self.first.data\\n self.first = self.first.next\\n self._size = self._size - 1\\n return elem\\n \\n raise IndexError('The queue is empty! ')\",\n \"def __delitem__(self, index: Any) -> None:\\n del self.contents[index]\\n return\",\n \"def pop(self):\\r\\n return self.queue.pop(0)\",\n \"def dequeue(self):\\n\\t\\treturn self.items.pop()\",\n \"def GetMainBuffer(self):\\n tmp = self.buffers[0]\\n self.buffers[0] = []\\n return tmp\",\n \"def discard(self, item):\\n try:\\n counter = self._get(item) - 1\\n except KeyError:\\n return\\n\\n if counter <= 0:\\n self._del(item)\\n else:\\n self._set(item, counter)\",\n \"def remove(self, key):\\n index = int((keyIndex(key) & (self.BUCKET_SIZE - 1)))\\n inner = self.keys[index]\\n if inner == None:\\n return None\\n i = 0\\n while len(inner):\\n if inner[i] == self.EMPTY_KEY:\\n break\\n if inner[i] == key:\\n value = self.values[index][i]\\n while len(inner):\\n if inner[i] == self.EMPTY_KEY:\\n break\\n inner[i - 1] = inner[i]\\n self.values[index][i - 1] = self.values[index][i]\\n i += 1\\n inner[i - 1] = self.EMPTY_KEY\\n self.values[index][i - 1] = None\\n self.size -= 1\\n self.modCount += 1\\n return value\\n i += 1\\n return None\",\n \"def remove(self, key: int) -> None:\\n index = key % 10000\\n previous = self.array[index]\\n current = previous.next\\n while current:\\n if current.key == key:\\n previous.next = current.next\\n break\\n previous = previous.next\\n current = current.next\",\n \"def pop(self):\\n if self.items:\\n return self.items.pop()\\n return None\",\n \"def _discard_excess_bytes(self):\\n discard_len = min(self._discard, len(self._buffer))\\n del self._buffer[:discard_len]\\n self._discard -= discard_len\",\n \"def dequeue(self):\\n if len(self) == 1:\\n self.tail = None\\n return self.pop()\",\n \"def popitem(self): # real signature unknown; restored from __doc__\\n pass\",\n \"def dequeue(self):\\n return self.items.pop()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.77843237","0.7342911","0.71000373","0.68947244","0.688018","0.68741614","0.6867453","0.6845434","0.6821856","0.6749494","0.66855025","0.66670585","0.66445595","0.661845","0.66004205","0.6579086","0.65492535","0.6534603","0.6392726","0.6383168","0.63651276","0.63288","0.6292754","0.62894005","0.62093323","0.6187035","0.618469","0.6183913","0.6157145","0.6156994","0.61107856","0.6096641","0.60917866","0.6090366","0.609017","0.6086837","0.6071513","0.60130167","0.6012786","0.6007076","0.59688675","0.5956038","0.5955162","0.5949962","0.59260553","0.59171724","0.591265","0.5905925","0.5894432","0.5894282","0.58822113","0.5880766","0.5874641","0.5871477","0.5867921","0.58626544","0.58585227","0.58585227","0.58416283","0.5820104","0.58141565","0.5808659","0.5803741","0.5788276","0.57881916","0.57853925","0.57853925","0.5781582","0.5777663","0.5773583","0.5772261","0.5767563","0.57637864","0.57614833","0.5759961","0.57564527","0.5753757","0.57519466","0.573685","0.57319105","0.5730615","0.57302463","0.5722657","0.5716078","0.570869","0.5701098","0.56923276","0.5690993","0.5687772","0.56820244","0.56808233","0.5678121","0.5672656","0.5668109","0.56657386","0.566417","0.5660901","0.56581306","0.56565034","0.5655076"],"string":"[\n \"0.77843237\",\n \"0.7342911\",\n \"0.71000373\",\n \"0.68947244\",\n \"0.688018\",\n \"0.68741614\",\n \"0.6867453\",\n \"0.6845434\",\n \"0.6821856\",\n \"0.6749494\",\n \"0.66855025\",\n \"0.66670585\",\n \"0.66445595\",\n \"0.661845\",\n \"0.66004205\",\n \"0.6579086\",\n \"0.65492535\",\n \"0.6534603\",\n \"0.6392726\",\n \"0.6383168\",\n \"0.63651276\",\n \"0.63288\",\n \"0.6292754\",\n \"0.62894005\",\n \"0.62093323\",\n \"0.6187035\",\n \"0.618469\",\n \"0.6183913\",\n \"0.6157145\",\n \"0.6156994\",\n \"0.61107856\",\n \"0.6096641\",\n \"0.60917866\",\n \"0.6090366\",\n \"0.609017\",\n \"0.6086837\",\n \"0.6071513\",\n \"0.60130167\",\n \"0.6012786\",\n \"0.6007076\",\n \"0.59688675\",\n \"0.5956038\",\n \"0.5955162\",\n \"0.5949962\",\n \"0.59260553\",\n \"0.59171724\",\n \"0.591265\",\n \"0.5905925\",\n \"0.5894432\",\n \"0.5894282\",\n \"0.58822113\",\n \"0.5880766\",\n \"0.5874641\",\n \"0.5871477\",\n \"0.5867921\",\n \"0.58626544\",\n \"0.58585227\",\n \"0.58585227\",\n \"0.58416283\",\n \"0.5820104\",\n \"0.58141565\",\n \"0.5808659\",\n \"0.5803741\",\n \"0.5788276\",\n \"0.57881916\",\n \"0.57853925\",\n \"0.57853925\",\n \"0.5781582\",\n \"0.5777663\",\n \"0.5773583\",\n \"0.5772261\",\n \"0.5767563\",\n \"0.57637864\",\n \"0.57614833\",\n \"0.5759961\",\n \"0.57564527\",\n \"0.5753757\",\n \"0.57519466\",\n \"0.573685\",\n \"0.57319105\",\n \"0.5730615\",\n \"0.57302463\",\n \"0.5722657\",\n \"0.5716078\",\n \"0.570869\",\n \"0.5701098\",\n \"0.56923276\",\n \"0.5690993\",\n \"0.5687772\",\n \"0.56820244\",\n \"0.56808233\",\n \"0.5678121\",\n \"0.5672656\",\n \"0.5668109\",\n \"0.56657386\",\n \"0.566417\",\n \"0.5660901\",\n \"0.56581306\",\n \"0.56565034\",\n \"0.5655076\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.73949045"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81774,"cells":{"query":{"kind":"string","value":"Remove the last item in the buffer"},"document":{"kind":"string","value":"def pop_last(self):\n self.pop_item(-1)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def delete_last(self):\n self.deque.pop()","def pop(self):\n value = self.buffer[self.end - 1]\n self.buffer[self.end - 1] = None\n self.end = (self.end - 1) % len(self.buffer)\n return value","def pop(self):\n data = self.buffer.getvalue()\n self.buffer.seek(0)\n self.buffer.truncate()\n return data","def pop(self):\r\n return self.buff.pop(-1)","def pop(self):\n while self.number > self.maxlength:\n self.buffer.popleft()\n self.number -= 1","def pop_item(self, index):\n ix, obj = self.items\n if index < len(ix):\n self.d_buffer.pop(ix[index])\n else:\n raise IndexError('Buffer does not have {0} elements'.format(index))","def remove_last_item_from_stack(self):\n if self.length > 0:\n return self.container.pop()\n else:\n return None","def remove_last_item(mylist):\n # This modifies mylist\n mylist.pop(-1)","def pop_from_deque(self):","def delete_first(self):\n self.deque.pop(0)","def delete(self):\n first = self.data[0]\n self.data.pop(0)\n self.size = self.size - 1\n return first","def remove(self):\n if len(self.line) == 0:\n raise ValueError, \"No more elements in the queue to remove.\"\n\n frontOfLine = self.line[-1]\n self.line = self.line[:-1]\n return frontOfLine","def delete(self) -> None:\n if not self.buffer or self.index == len(self.buffer):\n return\n\n self.buffer.delete(self.index)\n\n if 0 < self.index > self.buffer.end:\n self.index = self.buffer.end","def remove(self):\r\n if self.first() is not None:\r\n self.dec_size()\r\n self.set_first(self.first().next())\r\n if self.size() == 0: # when there are no more elements in the list,\r\n self.__last = None # remove the pointer to the last element\r","def popitem(self):\n return self.pop(0)","def pop_rear(self):\n if len(self) == 0:\n if self.none_for_empty:\n return None\n raise ValueError(\"Buffer is empty\")\n pt = self.buf[self.rear]\n if self.rear == self.front:\n self.rear = None\n else:\n self.rear = (self.rear + 1) % self.length\n return pt","def pop(self):\n if len(self) == 0:\n if self.none_for_empty:\n return None\n raise ValueError(\"Buffer is empty\")\n pt = self.buf[self.front]\n if self.rear == self.front:\n self.rear = None\n else:\n self.front = self.length - 1 if self.front == 0 else self.front - 1\n return pt","def _remove_old_items(self):\n if self.size_limit is not None:\n while len(self) > self.size_limit:\n self.popitem(last=False)","def backspace(self) -> None:\n if self.index:\n self.buffer.delete(self.index - 1)\n self.index -= 1","def remove_last(data):\n for sublist in data:\n del sublist[-1]\n\n return data","async def remove_last_element(message: types.Message):\n commands.remove_last(message.chat.id)\n await message.answer('Done 👌')","def remove_buffered_packets(self):\n seq = self.next_seq\n while True:\n p = self.buffer.pop(seq, None)\n if p is None:\n break\n else:\n seq += len(p.data)\n yield p","def remove_rear(self):\n\n if self.items:\n return self.items.pop()\n return None","def removeLast(self):\n # primeiro verifico se a lista está vazia\n if self.head is None:\n print(\"Erro: a lista está vazia.\")\n # se a lista não estiver vazia\n # armazenamos o valor do primeiro \"nó\"\n else:\n valor_ultimo_no = self.tail.valor\n if self.head is self.tail: # se True: a lista tem apenas \"1 item\"\n self.head = self.tail = None\n else: # se a lista tiver mais de \"1 item\"\n no_atual = self.head\n while no_atual.proximo_no is not self.tail:\n no_atual = no_atual.proximo_no\n no_atual.proximo_no = None\n self.tail = no_atual\n print(\"Removendo último item: [ {} ]\".format(valor_ultimo_no))\n self.size -= 1\n return valor_ultimo_no","def pop_first(self):\n self.pop_item(0)","def pop(self, index=None, last=True):\n if index == None:\n return super().pop(last)\n else:\n ret = self[index]\n self.remove(ret)\n return ret","def getLast(self):\n return self.dataBuffer[len(self.dataBuffer) - 1]","def test_removing_the_last_val_in_deque(filled_deque):\n assert filled_deque.pop() == 1","def pop(self):\n b = self.a[-1]\n del self.a[-1]\n return b","def popitem(self):\n pass","def delete_last(self):\n if self.is_empty():\n raise Empty('list is empty')\n answer = self._tail._element\n self._tail = self._tail._prev\n self._size -= 1\n if self.is_empty(): # special case as deque is empty\n self._head = None # removed tail had been the head\n else:\n self._tail._next = None\n return answer","def last_item(self):\n return self.container[self.length-1]","def pop(self):","def pop(self):","def pop(self):\n return self.remove(0)","def take(self, item): \n self.contents.remove(item)","def delete_last(self):\n if self.is_empty():\n raise Empty(\"List is empty\")\n return self._delete_node(self.trailer._prev)","def popleft(self):\n value = self.buffer[self.start]\n self.buffer[self.start] = None\n self.start = (self.start + 1) % len(self.buffer)\n return value","def pop():","def pop_current_line(self):\n self.current_line.pop()","def delete_last(self):\n if self._size == 0:\n raise Empty('Dequeue is empty')\n return self._delete_node(self._tail._prev)","def pop(self):\n return self.ll.delete_first()","def butlast(mylist):\n # This returns a copy of mylist\n return mylist[:-1]","def AdvanceQueue(self):\r\n self.data.pop(0)\r\n return","def dequeue(self):\n\n return self._data.pop(0)","def pop(self):\r\n\r\n if not self.is_empty():\r\n\r\n half_cap = self._capacity // 2\r\n item = self._data[self._size-1]\r\n self._data[self._size-1] = 0\r\n self._size -= 1\r\n\r\n if self._size <= half_cap:\r\n if half_cap != 0:\r\n\r\n self.shrink()\r\n\r\n return item\r\n\r\n else:\r\n pass","def dequeue(self) -> object:\n return self._data.pop(0)","def dequeue(self) -> object:\n return self._data.pop(0)","def dequeue(self):\n\t\treturn self.items.pop()","def remove_last(self):\n if self.is_empty():\n raise self.NoSuchNodeException()\n\n tail = self.getNode(self.list_size - 1)\n tail_data = tail.data\n\n if self.list_size == 1:\n self.head = None\n else:\n before_tail = self.getNode(self.list_size - 2)\n before_tail.next_node = None\n\n self.list_size -= 1\n\n return tail_data","def dequeue(self):\n\n item = self.__items__.pop(0)\n return item","def dequeue(self):\n return self.items.pop()","def dequeue(self):\n return self.items.pop()","def last(iterable):\n d = deque(iterable, maxlen=1)\n try:\n return d.pop()\n except IndexError:\n raise ValueError(\"Cannot return last item from empty iterable {!r}\".format(iterable))","def Rear(self):\n return -1 if self.isEmpty() else self.__buffer[(self.__start+self.__size-1) % len(self.__buffer)]","def remove(self):\n return self.queue.popleft()","def pop(self):\n pass","def pop(self):\n pass","def keep_last_lines(self, num_lines):\n self.data = self.data[-num_lines:]","def dequeue(self):\n if len(self) == 1:\n self.tail = None\n return self.pop()","def remove(self) -> T:\n if self.is_empty():\n raise EmptyStackError\n else:\n self._size -= 1\n return self._items.pop()","def array_pop(item):\n return item.pop()","def pop(self): ##################### <-\n value = self.lst[-1]\n self.lst = self.lst[:-1]\n return value","def next(self):\n # type: () -> T\n if len(self.buffer) == 0:\n raise StopIteration\n self.prev = self.buffer.pop()\n self._buffer_to(self.lookahead)\n return self.prev","def last(self):\n return self.deque[-1]","def pop(self):\n return super().remove_item_from_front()","def popBuffer(self):\n return self.ecg_buffer.get()","def pop(self):\n size = self._list.size()\n if size == 0:\n return None\n data = self._list.tail.data\n self._list.removeIndex(size-1)\n return data","def __remove_first(self):\n if self.__head is not None:\n self.__length -= 1\n self.__head = self.__head.next()\n if self.__length == 0: # when there are no more elements in the list,\n self.__last = None # remove the pointer to the last element","def remove_last(self):\n # return None if no Node to remove\n if self.tail is None:\n return None\n # save the tail\n removed = self.tail\n # set the new tail\n if self.tail != self.head:\n if self.tail.skip_back is None:\n self.tail = self.head\n else:\n self.tail = self.tail.skip_back.next\n self.tail.next = None\n else:\n self.tail = self.head = None\n\n return removed.data","def pop(self):\n if self._pushed:\n rv = self._pushed.pop()\n else:\n rv = self._generator.next()\n self.last = rv\n return rv","def delete_last_record():\n\tnewRcrds = list()\n\twith jsonlines.open('tempRecords.jsonl', mode='r') as readerOp:\n\t\tfor obj in readerOp:\n\t\t\tnewRcrds.append(obj)\n\twith jsonlines.open('tempRecords.jsonl', mode='w') as writerOp:\n\t\tif len(newRcrds) != 1:\n\t\t\t# checking if the record being removed is the last record which has file names.\n\t\t\tfor obji in newRcrds[:len(newRcrds)-1]:\n\t\t\t\twriterOp.write(obji)\n\t\telse:\n\t\t\t# if its the last record then do not delet it, as it is required for annotation data\n\t\t\tfor obji in newRcrds[:len(newRcrds)]:\n\t\t\t\twriterOp.write(obji)","def popleft(self, timeout=None):\n item = super(ExclusiveQueue, self).popleft(timeout)\n try:\n self.remove(item)\n except ValueError:\n pass\n return item","def pop(self):\n\t\treturn self.items.pop()","def pop(self):\r\n return self.list.pop()","def popitem(self): # real signature unknown; restored from __doc__\n pass","def pop(self):\n popped = self.__list[-1]\n self.__list = self.__list[:-1]\n return popped","def pop(self):\r\n return self.queue.pop(0)","def pop(self, timeout=None):\n item = super(ExclusiveQueue, self).pop(timeout)\n try:\n self.remove(item)\n except ValueError:\n pass\n return item","def pop(self):\n if len(self._data) == 0:\n return None\n else:\n return self._data.pop(0)","def dequeue(self):\n if self.items:\n return self.items.pop()\n return None","def remove_first(self):\n if self.is_empty(): raise RuntimeError(\"Empty list\")\n\n data = self.head.data\n self.head = self.head.nxt\n self.size -= 1\n\n if self.is_empty(): self.tail = None\n else: self.head.prev = None\n\n return data","def popitem(self):\n pass","def pop(self) -> object:\n return self.data.pop()","def chop(x):\n del x[0]\n l = len(x)\n del x[l-1]","def removeFromBack(self):\n if self.size <= 0:\n raise IndexError(\"the array is empty\")\n self._shrinkCheck()\n super().removeFromBack()","def pop_message(self):\n app_process = sqlite3.connect('app_process::memory:', check_same_thread=False)\n app_process_cursor = app_process.cursor()\n app_process_cursor.execute(\"SELECT * FROM message_queue WHERE tstamp==(:first)\", {\"first\":self.mq_first}) \n item = app_process_cursor.fetchone()\n if item == None:\n return\n app_process_cursor.execute(\"DELETE FROM message_queue WHERE tstamp==(:first)\", {\"first\":self.mq_first})\n self.mq_first = item[4] #now sets first to next item pointed to\n app_process.commit()\n app_process.close()\n return item","def pop(self):\n self.list.pop()","def popLast(self):\n if self.last != None:\n filename = self.last.filename\n self.deleteLast()\n return filename\n else:\n return None","def pop_write(self):\n ...","def pop(self):\n if self.items:\n return self.items.pop()\n return None","def purge_buffer(self):\n self._buf = b''","def pop(self):\n self.data[0], self.data[-1] = self.data[-1], self.data[0]\n result = self.data.pop()\n self.heapify_down(0)\n return result","def deQueue(self):\n if self.isEmpty():\n return False\n self.__start = (self.__start+1) % len(self.__buffer)\n self.__size -= 1\n return True","def pop(self):\r\n removed = self.__memory.pop()\r\n return removed","def pop(self) -> int:\r\n return self.items.pop(0)","def pop(self):\n self._a_to_b()\n r = self.b[-1]\n self.b.pop()\n return r","def _drop_old_data(self, current_time):\n for k in self._buf.keys():\n timelimit = current_time - self._lifetime\n if (k < timelimit):\n del self._buf[k]","def pop(self):\n return self.arr.pop()","def pop(self):\n assert len(self.paths) > 1\n self.time -= self.paths[-1].time\n return self.paths.pop()"],"string":"[\n \"def delete_last(self):\\n self.deque.pop()\",\n \"def pop(self):\\n value = self.buffer[self.end - 1]\\n self.buffer[self.end - 1] = None\\n self.end = (self.end - 1) % len(self.buffer)\\n return value\",\n \"def pop(self):\\n data = self.buffer.getvalue()\\n self.buffer.seek(0)\\n self.buffer.truncate()\\n return data\",\n \"def pop(self):\\r\\n return self.buff.pop(-1)\",\n \"def pop(self):\\n while self.number > self.maxlength:\\n self.buffer.popleft()\\n self.number -= 1\",\n \"def pop_item(self, index):\\n ix, obj = self.items\\n if index < len(ix):\\n self.d_buffer.pop(ix[index])\\n else:\\n raise IndexError('Buffer does not have {0} elements'.format(index))\",\n \"def remove_last_item_from_stack(self):\\n if self.length > 0:\\n return self.container.pop()\\n else:\\n return None\",\n \"def remove_last_item(mylist):\\n # This modifies mylist\\n mylist.pop(-1)\",\n \"def pop_from_deque(self):\",\n \"def delete_first(self):\\n self.deque.pop(0)\",\n \"def delete(self):\\n first = self.data[0]\\n self.data.pop(0)\\n self.size = self.size - 1\\n return first\",\n \"def remove(self):\\n if len(self.line) == 0:\\n raise ValueError, \\\"No more elements in the queue to remove.\\\"\\n\\n frontOfLine = self.line[-1]\\n self.line = self.line[:-1]\\n return frontOfLine\",\n \"def delete(self) -> None:\\n if not self.buffer or self.index == len(self.buffer):\\n return\\n\\n self.buffer.delete(self.index)\\n\\n if 0 < self.index > self.buffer.end:\\n self.index = self.buffer.end\",\n \"def remove(self):\\r\\n if self.first() is not None:\\r\\n self.dec_size()\\r\\n self.set_first(self.first().next())\\r\\n if self.size() == 0: # when there are no more elements in the list,\\r\\n self.__last = None # remove the pointer to the last element\\r\",\n \"def popitem(self):\\n return self.pop(0)\",\n \"def pop_rear(self):\\n if len(self) == 0:\\n if self.none_for_empty:\\n return None\\n raise ValueError(\\\"Buffer is empty\\\")\\n pt = self.buf[self.rear]\\n if self.rear == self.front:\\n self.rear = None\\n else:\\n self.rear = (self.rear + 1) % self.length\\n return pt\",\n \"def pop(self):\\n if len(self) == 0:\\n if self.none_for_empty:\\n return None\\n raise ValueError(\\\"Buffer is empty\\\")\\n pt = self.buf[self.front]\\n if self.rear == self.front:\\n self.rear = None\\n else:\\n self.front = self.length - 1 if self.front == 0 else self.front - 1\\n return pt\",\n \"def _remove_old_items(self):\\n if self.size_limit is not None:\\n while len(self) > self.size_limit:\\n self.popitem(last=False)\",\n \"def backspace(self) -> None:\\n if self.index:\\n self.buffer.delete(self.index - 1)\\n self.index -= 1\",\n \"def remove_last(data):\\n for sublist in data:\\n del sublist[-1]\\n\\n return data\",\n \"async def remove_last_element(message: types.Message):\\n commands.remove_last(message.chat.id)\\n await message.answer('Done 👌')\",\n \"def remove_buffered_packets(self):\\n seq = self.next_seq\\n while True:\\n p = self.buffer.pop(seq, None)\\n if p is None:\\n break\\n else:\\n seq += len(p.data)\\n yield p\",\n \"def remove_rear(self):\\n\\n if self.items:\\n return self.items.pop()\\n return None\",\n \"def removeLast(self):\\n # primeiro verifico se a lista está vazia\\n if self.head is None:\\n print(\\\"Erro: a lista está vazia.\\\")\\n # se a lista não estiver vazia\\n # armazenamos o valor do primeiro \\\"nó\\\"\\n else:\\n valor_ultimo_no = self.tail.valor\\n if self.head is self.tail: # se True: a lista tem apenas \\\"1 item\\\"\\n self.head = self.tail = None\\n else: # se a lista tiver mais de \\\"1 item\\\"\\n no_atual = self.head\\n while no_atual.proximo_no is not self.tail:\\n no_atual = no_atual.proximo_no\\n no_atual.proximo_no = None\\n self.tail = no_atual\\n print(\\\"Removendo último item: [ {} ]\\\".format(valor_ultimo_no))\\n self.size -= 1\\n return valor_ultimo_no\",\n \"def pop_first(self):\\n self.pop_item(0)\",\n \"def pop(self, index=None, last=True):\\n if index == None:\\n return super().pop(last)\\n else:\\n ret = self[index]\\n self.remove(ret)\\n return ret\",\n \"def getLast(self):\\n return self.dataBuffer[len(self.dataBuffer) - 1]\",\n \"def test_removing_the_last_val_in_deque(filled_deque):\\n assert filled_deque.pop() == 1\",\n \"def pop(self):\\n b = self.a[-1]\\n del self.a[-1]\\n return b\",\n \"def popitem(self):\\n pass\",\n \"def delete_last(self):\\n if self.is_empty():\\n raise Empty('list is empty')\\n answer = self._tail._element\\n self._tail = self._tail._prev\\n self._size -= 1\\n if self.is_empty(): # special case as deque is empty\\n self._head = None # removed tail had been the head\\n else:\\n self._tail._next = None\\n return answer\",\n \"def last_item(self):\\n return self.container[self.length-1]\",\n \"def pop(self):\",\n \"def pop(self):\",\n \"def pop(self):\\n return self.remove(0)\",\n \"def take(self, item): \\n self.contents.remove(item)\",\n \"def delete_last(self):\\n if self.is_empty():\\n raise Empty(\\\"List is empty\\\")\\n return self._delete_node(self.trailer._prev)\",\n \"def popleft(self):\\n value = self.buffer[self.start]\\n self.buffer[self.start] = None\\n self.start = (self.start + 1) % len(self.buffer)\\n return value\",\n \"def pop():\",\n \"def pop_current_line(self):\\n self.current_line.pop()\",\n \"def delete_last(self):\\n if self._size == 0:\\n raise Empty('Dequeue is empty')\\n return self._delete_node(self._tail._prev)\",\n \"def pop(self):\\n return self.ll.delete_first()\",\n \"def butlast(mylist):\\n # This returns a copy of mylist\\n return mylist[:-1]\",\n \"def AdvanceQueue(self):\\r\\n self.data.pop(0)\\r\\n return\",\n \"def dequeue(self):\\n\\n return self._data.pop(0)\",\n \"def pop(self):\\r\\n\\r\\n if not self.is_empty():\\r\\n\\r\\n half_cap = self._capacity // 2\\r\\n item = self._data[self._size-1]\\r\\n self._data[self._size-1] = 0\\r\\n self._size -= 1\\r\\n\\r\\n if self._size <= half_cap:\\r\\n if half_cap != 0:\\r\\n\\r\\n self.shrink()\\r\\n\\r\\n return item\\r\\n\\r\\n else:\\r\\n pass\",\n \"def dequeue(self) -> object:\\n return self._data.pop(0)\",\n \"def dequeue(self) -> object:\\n return self._data.pop(0)\",\n \"def dequeue(self):\\n\\t\\treturn self.items.pop()\",\n \"def remove_last(self):\\n if self.is_empty():\\n raise self.NoSuchNodeException()\\n\\n tail = self.getNode(self.list_size - 1)\\n tail_data = tail.data\\n\\n if self.list_size == 1:\\n self.head = None\\n else:\\n before_tail = self.getNode(self.list_size - 2)\\n before_tail.next_node = None\\n\\n self.list_size -= 1\\n\\n return tail_data\",\n \"def dequeue(self):\\n\\n item = self.__items__.pop(0)\\n return item\",\n \"def dequeue(self):\\n return self.items.pop()\",\n \"def dequeue(self):\\n return self.items.pop()\",\n \"def last(iterable):\\n d = deque(iterable, maxlen=1)\\n try:\\n return d.pop()\\n except IndexError:\\n raise ValueError(\\\"Cannot return last item from empty iterable {!r}\\\".format(iterable))\",\n \"def Rear(self):\\n return -1 if self.isEmpty() else self.__buffer[(self.__start+self.__size-1) % len(self.__buffer)]\",\n \"def remove(self):\\n return self.queue.popleft()\",\n \"def pop(self):\\n pass\",\n \"def pop(self):\\n pass\",\n \"def keep_last_lines(self, num_lines):\\n self.data = self.data[-num_lines:]\",\n \"def dequeue(self):\\n if len(self) == 1:\\n self.tail = None\\n return self.pop()\",\n \"def remove(self) -> T:\\n if self.is_empty():\\n raise EmptyStackError\\n else:\\n self._size -= 1\\n return self._items.pop()\",\n \"def array_pop(item):\\n return item.pop()\",\n \"def pop(self): ##################### <-\\n value = self.lst[-1]\\n self.lst = self.lst[:-1]\\n return value\",\n \"def next(self):\\n # type: () -> T\\n if len(self.buffer) == 0:\\n raise StopIteration\\n self.prev = self.buffer.pop()\\n self._buffer_to(self.lookahead)\\n return self.prev\",\n \"def last(self):\\n return self.deque[-1]\",\n \"def pop(self):\\n return super().remove_item_from_front()\",\n \"def popBuffer(self):\\n return self.ecg_buffer.get()\",\n \"def pop(self):\\n size = self._list.size()\\n if size == 0:\\n return None\\n data = self._list.tail.data\\n self._list.removeIndex(size-1)\\n return data\",\n \"def __remove_first(self):\\n if self.__head is not None:\\n self.__length -= 1\\n self.__head = self.__head.next()\\n if self.__length == 0: # when there are no more elements in the list,\\n self.__last = None # remove the pointer to the last element\",\n \"def remove_last(self):\\n # return None if no Node to remove\\n if self.tail is None:\\n return None\\n # save the tail\\n removed = self.tail\\n # set the new tail\\n if self.tail != self.head:\\n if self.tail.skip_back is None:\\n self.tail = self.head\\n else:\\n self.tail = self.tail.skip_back.next\\n self.tail.next = None\\n else:\\n self.tail = self.head = None\\n\\n return removed.data\",\n \"def pop(self):\\n if self._pushed:\\n rv = self._pushed.pop()\\n else:\\n rv = self._generator.next()\\n self.last = rv\\n return rv\",\n \"def delete_last_record():\\n\\tnewRcrds = list()\\n\\twith jsonlines.open('tempRecords.jsonl', mode='r') as readerOp:\\n\\t\\tfor obj in readerOp:\\n\\t\\t\\tnewRcrds.append(obj)\\n\\twith jsonlines.open('tempRecords.jsonl', mode='w') as writerOp:\\n\\t\\tif len(newRcrds) != 1:\\n\\t\\t\\t# checking if the record being removed is the last record which has file names.\\n\\t\\t\\tfor obji in newRcrds[:len(newRcrds)-1]:\\n\\t\\t\\t\\twriterOp.write(obji)\\n\\t\\telse:\\n\\t\\t\\t# if its the last record then do not delet it, as it is required for annotation data\\n\\t\\t\\tfor obji in newRcrds[:len(newRcrds)]:\\n\\t\\t\\t\\twriterOp.write(obji)\",\n \"def popleft(self, timeout=None):\\n item = super(ExclusiveQueue, self).popleft(timeout)\\n try:\\n self.remove(item)\\n except ValueError:\\n pass\\n return item\",\n \"def pop(self):\\n\\t\\treturn self.items.pop()\",\n \"def pop(self):\\r\\n return self.list.pop()\",\n \"def popitem(self): # real signature unknown; restored from __doc__\\n pass\",\n \"def pop(self):\\n popped = self.__list[-1]\\n self.__list = self.__list[:-1]\\n return popped\",\n \"def pop(self):\\r\\n return self.queue.pop(0)\",\n \"def pop(self, timeout=None):\\n item = super(ExclusiveQueue, self).pop(timeout)\\n try:\\n self.remove(item)\\n except ValueError:\\n pass\\n return item\",\n \"def pop(self):\\n if len(self._data) == 0:\\n return None\\n else:\\n return self._data.pop(0)\",\n \"def dequeue(self):\\n if self.items:\\n return self.items.pop()\\n return None\",\n \"def remove_first(self):\\n if self.is_empty(): raise RuntimeError(\\\"Empty list\\\")\\n\\n data = self.head.data\\n self.head = self.head.nxt\\n self.size -= 1\\n\\n if self.is_empty(): self.tail = None\\n else: self.head.prev = None\\n\\n return data\",\n \"def popitem(self):\\n pass\",\n \"def pop(self) -> object:\\n return self.data.pop()\",\n \"def chop(x):\\n del x[0]\\n l = len(x)\\n del x[l-1]\",\n \"def removeFromBack(self):\\n if self.size <= 0:\\n raise IndexError(\\\"the array is empty\\\")\\n self._shrinkCheck()\\n super().removeFromBack()\",\n \"def pop_message(self):\\n app_process = sqlite3.connect('app_process::memory:', check_same_thread=False)\\n app_process_cursor = app_process.cursor()\\n app_process_cursor.execute(\\\"SELECT * FROM message_queue WHERE tstamp==(:first)\\\", {\\\"first\\\":self.mq_first}) \\n item = app_process_cursor.fetchone()\\n if item == None:\\n return\\n app_process_cursor.execute(\\\"DELETE FROM message_queue WHERE tstamp==(:first)\\\", {\\\"first\\\":self.mq_first})\\n self.mq_first = item[4] #now sets first to next item pointed to\\n app_process.commit()\\n app_process.close()\\n return item\",\n \"def pop(self):\\n self.list.pop()\",\n \"def popLast(self):\\n if self.last != None:\\n filename = self.last.filename\\n self.deleteLast()\\n return filename\\n else:\\n return None\",\n \"def pop_write(self):\\n ...\",\n \"def pop(self):\\n if self.items:\\n return self.items.pop()\\n return None\",\n \"def purge_buffer(self):\\n self._buf = b''\",\n \"def pop(self):\\n self.data[0], self.data[-1] = self.data[-1], self.data[0]\\n result = self.data.pop()\\n self.heapify_down(0)\\n return result\",\n \"def deQueue(self):\\n if self.isEmpty():\\n return False\\n self.__start = (self.__start+1) % len(self.__buffer)\\n self.__size -= 1\\n return True\",\n \"def pop(self):\\r\\n removed = self.__memory.pop()\\r\\n return removed\",\n \"def pop(self) -> int:\\r\\n return self.items.pop(0)\",\n \"def pop(self):\\n self._a_to_b()\\n r = self.b[-1]\\n self.b.pop()\\n return r\",\n \"def _drop_old_data(self, current_time):\\n for k in self._buf.keys():\\n timelimit = current_time - self._lifetime\\n if (k < timelimit):\\n del self._buf[k]\",\n \"def pop(self):\\n return self.arr.pop()\",\n \"def pop(self):\\n assert len(self.paths) > 1\\n self.time -= self.paths[-1].time\\n return self.paths.pop()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7669612","0.7375816","0.73687816","0.7366045","0.71360344","0.70445234","0.6985398","0.6823437","0.6730714","0.6690923","0.66654307","0.6621386","0.6602832","0.659624","0.6571084","0.6533281","0.65202886","0.6503479","0.64959717","0.64928275","0.6475953","0.64373326","0.6399829","0.63817483","0.6367661","0.63445324","0.6342977","0.63148236","0.6312065","0.63067067","0.63011885","0.6296674","0.625871","0.625871","0.62491775","0.6235812","0.6219352","0.62145776","0.62017876","0.61753434","0.61716896","0.61536014","0.61511165","0.6148118","0.6145812","0.61357385","0.61299473","0.61299473","0.612323","0.6120327","0.6117158","0.6116158","0.6116158","0.61112505","0.61034656","0.60965616","0.6084844","0.6084844","0.6076779","0.60624343","0.60587335","0.6044092","0.60432714","0.60381967","0.603146","0.6029859","0.6029023","0.602849","0.6021721","0.6020094","0.60163176","0.5975233","0.5974293","0.5969484","0.59650594","0.59622824","0.5956886","0.5952036","0.59515077","0.5944397","0.59344035","0.5933182","0.5932897","0.59298855","0.5929603","0.59138656","0.59067833","0.59049886","0.5900247","0.58958083","0.58915913","0.58910996","0.58907175","0.58902377","0.58900887","0.5887311","0.58865225","0.58852106","0.5882143","0.5880261"],"string":"[\n \"0.7669612\",\n \"0.7375816\",\n \"0.73687816\",\n \"0.7366045\",\n \"0.71360344\",\n \"0.70445234\",\n \"0.6985398\",\n \"0.6823437\",\n \"0.6730714\",\n \"0.6690923\",\n \"0.66654307\",\n \"0.6621386\",\n \"0.6602832\",\n \"0.659624\",\n \"0.6571084\",\n \"0.6533281\",\n \"0.65202886\",\n \"0.6503479\",\n \"0.64959717\",\n \"0.64928275\",\n \"0.6475953\",\n \"0.64373326\",\n \"0.6399829\",\n \"0.63817483\",\n \"0.6367661\",\n \"0.63445324\",\n \"0.6342977\",\n \"0.63148236\",\n \"0.6312065\",\n \"0.63067067\",\n \"0.63011885\",\n \"0.6296674\",\n \"0.625871\",\n \"0.625871\",\n \"0.62491775\",\n \"0.6235812\",\n \"0.6219352\",\n \"0.62145776\",\n \"0.62017876\",\n \"0.61753434\",\n \"0.61716896\",\n \"0.61536014\",\n \"0.61511165\",\n \"0.6148118\",\n \"0.6145812\",\n \"0.61357385\",\n \"0.61299473\",\n \"0.61299473\",\n \"0.612323\",\n \"0.6120327\",\n \"0.6117158\",\n \"0.6116158\",\n \"0.6116158\",\n \"0.61112505\",\n \"0.61034656\",\n \"0.60965616\",\n \"0.6084844\",\n \"0.6084844\",\n \"0.6076779\",\n \"0.60624343\",\n \"0.60587335\",\n \"0.6044092\",\n \"0.60432714\",\n \"0.60381967\",\n \"0.603146\",\n \"0.6029859\",\n \"0.6029023\",\n \"0.602849\",\n \"0.6021721\",\n \"0.6020094\",\n \"0.60163176\",\n \"0.5975233\",\n \"0.5974293\",\n \"0.5969484\",\n \"0.59650594\",\n \"0.59622824\",\n \"0.5956886\",\n \"0.5952036\",\n \"0.59515077\",\n \"0.5944397\",\n \"0.59344035\",\n \"0.5933182\",\n \"0.5932897\",\n \"0.59298855\",\n \"0.5929603\",\n \"0.59138656\",\n \"0.59067833\",\n \"0.59049886\",\n \"0.5900247\",\n \"0.58958083\",\n \"0.58915913\",\n \"0.58910996\",\n \"0.58907175\",\n \"0.58902377\",\n \"0.58900887\",\n \"0.5887311\",\n \"0.58865225\",\n \"0.58852106\",\n \"0.5882143\",\n \"0.5880261\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7435102"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81775,"cells":{"query":{"kind":"string","value":"Add a new item at the end of the buffer and drop one item if necessary (from the beginning)"},"document":{"kind":"string","value":"def add_next(self, item, index):\n if index in self.d_buffer.keys():\n return\n if len(self) == self.size:\n self.pop_first()\n self.add_item(item, index)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def add(self, item):\r\n if len(self.buff)==self.size: self.buff.pop(0)\r\n self.buff.append(item)","def delayed_buffer_item(self, buffer_item, buffer_item_len, item):\n item_copy = copy.copy(item)\n if buffer_item is None:\n buffer_item = buffer_item_len * [item_copy]\n else:\n buffer_item.append(item_copy)\n item_cur = copy.copy(buffer_item.pop(0))\n\n return buffer_item, item_cur","def append(self, item):\n if self.full or self.pre_allocated:\n # overwrite\n self.data[self.cur] = item\n else:\n self.data.append(item)\n if not self.full:\n self.full = self.cur == self.max - 1\n self.cur = (self.cur + 1) % self.max","def add_prev(self, item, index):\n if index in self.d_buffer.keys():\n return\n if len(self) == self._size:\n self.pop_last()\n self.add_item(item, index)","def add_item(self, item, index):\n if index in self.d_buffer.keys():\n return True\n elif len(self) < self._size:\n self.d_buffer.update({index: item})\n return True\n else:\n return False","def worker(self):\n while True:\n item,index = self.inbound.get()\n if index is None:\n self.buffer.append(item)\n self.index.value = self.index.value + 1 #index of next item for buffer\n if len(self.buffer)>self.size:\n del self.buffer[0]\n self.newitem.put(None)\n else:\n self.buffer[len(self.buffer)+(index - self.index.value)] = item","def put(self, item): \n if len(self.contents) < self.max_size:\n self.contents.append(item)\n elif len(self.contents) >= self.max_size:\n print \"Backpack Full.\"","def take_item(self, item):\r\n if len(self.items) <= 2:\r\n self.items.append(item)\r\n if self.got_both():\r\n self.working = True","def push(self, item):\n if len(self._data) == self.MAX_SIZE:\n # full we have to pop the oldest item (head)\n self._data.pop(0)\n self._data.append(item)","def _add(self, sample):#obs_t, action, reward, obs_tp1, done):\n\n if self._next_idx >= len(self._buffer): #appends data if max capacity not reached yet\n self._buffer.append(sample)\n else:\n self._buffer[self._next_idx] = sample #drops old entry and appends new data if max capacity\n self._next_idx = (self._next_idx + 1) % self._capacity","def append(self, x):\n if self.buffer[self.end]:\n if self.start <= self.end:\n self.buffer = (self.buffer[self.start:self.end]\n + [x]\n + [None]*(self.size - 1))\n else:\n self.buffer = ([(item for item\n in (self.buffer[self.start:]\n + self.buffer[:self.end])\n if item is not None)]\n + [x]\n + [None]*(self.size - 1))\n self.start = 0\n self.end = len(self.buffer) - self.size + 1\n else:\n self.buffer[self.end] = x\n self.end = (self.end + 1) % len(self.buffer)","def push(self, item):\n self.list.prepend(item)","def append(self, state):\n self._buffer[:-1] = self._buffer[1:]\n self._buffer[-1] = state","def add_item(self, item):\n self.items.append(item)\n self.length += 1","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][1] for b in buffer.memory] # lidar\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes (terminated or truncated)\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[3] for b in buffer.memory] # terminated\n d8 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n\n return self","def enqueue(self, item):\n\t\tself.items.insert(0, item)","def add_last(self, data):\n self.deque.append(data)","def _push_from_buffer(self):\r\n if len(self.buffer) > 0:\r\n if time.time() - self.last_sent_time > 5:\r\n try:\r\n message = self.buffer.pop(0)\r\n self._send_now(message)\r\n finally:\r\n self.last_sent_time = time.time()","def enqueue_rear(self, item):\n self._items.append(item)","def enqueue(self, item):\n self.items.insert(0, item)","def enqueue(self, item):\n self.items.insert(0, item)","def _buffer_to(self, amount):\n if amount > self.lookahead:\n raise Exception(\n 'Cannot extend buffer to {}: '\n 'beyond buffer lookahead {}'.format(\n amount, self.lookahead\n )\n )\n while len(self.buffer) < amount:\n try:\n self.buffer.appendleft(next(self.stream))\n except StopIteration:\n break","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][2] for b in buffer.memory] # lidar\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[1][1] for b in buffer.memory] # progress\n d8 = [b[3] for b in buffer.memory] # terminated\n d9 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n self.data[9] += d9\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n self.data.append(d9)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n self.data[9] = self.data[9][to_trim:]\n\n return self","def add_first(self, data):\n self.deque.insert(0, data)","def insert(self, item):\r\n if not self.is_full():\r\n for i in range(1,len(self.items)):\r\n if self.items[i] is None:\r\n self.items[i] = item\r\n self.size += 1\r\n self.perc_up(i)\r\n return True\r\n return False","def observation(self, observation):\n \n # push backward all observations\n self.buffer[:-1] = self.buffer[1:]\n\n # add last observation to the end (similar to adding an item to a queue)\n self.buffer[-1] = observation\n \n return self.buffer","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][3] for b in buffer.memory] # images\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[1][1] for b in buffer.memory] # gears\n d8 = [b[1][2] for b in buffer.memory] # rpms\n d9 = [b[3] for b in buffer.memory] # terminated\n d10 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n self.data[9] += d9\n self.data[10] += d10\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n self.data.append(d9)\n self.data.append(d10)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n self.data[9] = self.data[9][to_trim:]\n self.data[10] = self.data[10][to_trim:]\n\n return self","def insertBack(self, item):\n self.sentinel.prev.insertAfter(item)\n self.N += 1","def unshift(self, chunk):\n if chunk:\n self._pos -= len(chunk)\n self._unconsumed.append(chunk)","def push(self, item):\n self._tail_iters.append(iter([item]))","def pop_item(self, index):\n ix, obj = self.items\n if index < len(ix):\n self.d_buffer.pop(ix[index])\n else:\n raise IndexError('Buffer does not have {0} elements'.format(index))","def push(self, item):\n super().add_item_to_front(item)","def add(self, data):\n self.databuffer.append(data)\n if len(self.databuffer) > self.buffersize:\n self._flush()","def evict_or_add (self, item):","def add_chunk(self, chunk):\n self.chunkbuffer.appendleft(chunk)","def enqueue(self, item):\n # double size of array if necessary and recopy to front of array\n if self._N == len(self._q):\n self._resize(2*len(self._q)) # double size of array if necessary\n self._q[self._last] = item # add item\n self._last += 1\n if self._last == len(self._q):\n self._last = 0 # wrap-around\n self._N += 1","def append ( self , item ) :\n self.cond.acquire()\n try:\n if self.closed :\n raise Exception( \"Trying to append to a closed queue\" )\n else :\n self.weight += int( item['size'] )\n self.push( item )\n self.cond.notify()\n finally:\n self.cond.release()","def push(self, item):\n if item not in self._items:\n self._items.append(item)","def prepend(self, item: Any):\n self.insert(0, item)","def add_item(self, item: _T) -> None:\n if item not in self.item_to_index:\n self.item_to_index[item] = len(self.index_to_item)\n self.index_to_item.append(item)","def push(self, item):\n self.linked_list.prepend(item)","def add_item(self, item):\n if self.head is None:\n # if not self.array:\n self.head = 0\n self.array = [item]\n else:\n # insert item\n self.array.insert(self.head, item)\n\n # reassign head\n self.head += 1","def add_to_buffer(self, packet):\n # If the buffer is currently empty, the we should send the next packet\n # (i.e. this packet) as soon as it finishes transmitting (which will take\n # time + sizeofpacket/transmissionrate)\n if (len(self.buffer) == 0):\n self.next_packet_send_time = globals.systime + (packet.get_size()/self.rate)\n\n # Checks that there is room to add the packet to the buffer\n if (packet.get_size() + self.buffersize <= self.buffercapacity):\n self.buffersize = self.buffersize + packet.get_size()\n self.buffer.append(packet)\n # if there isn't room in the buffer, we return 0 to indicate that the\n # packet was dropped.\n else:\n return 0\n\n # returns the size of the packet that was succesfully added to the\n # buffer.\n return packet.get_size()","def push(self, Item):\n self.data_container.insert(0, Item)","def add(self, item):\n if self.has_item(item):\n return\n\n self.cache.append(item)\n\n if self.size() > self.max_size:\n self.cache.popleft()","def take(self, item): \n self.contents.remove(item)","def add_to_group(self,item):\n self.items.append(item)\n self.n += 1","def push(self, item) -> None:\n self.items.append(item)","def add_item(self, item):\n self.items.append(item)\n self.item_count += 1\n self.max_length = max(self.max_length, len(item.samples))","def append(self, item):\n\n # resize array to 2*capacity if max capacity reached\n if self.count == self.capacity:\n self._resize(2 * self.capacity)\n\n # Append the item at the end of array\n self.the_array[self.count] = item\n self.count += 1","def add(self, item):\n self._set(item, None)","def add(self, data):\n wasquiet = True if (self.tail == self.curr) else False\n\n # Assert the queue is clean\n qtail = self.base + \".\" + str(self.tail)\n print \"creating %s\" % qtail\n assert not os.path.exists(qtail)\n qt = open(qtail, \"w\")\n qt.write(data)\n qt.close()\n\n # Where does the next item go\n self.tail += 1\n self._settail(self.tail)\n\n return wasquiet","def push(self, new_item):\n self.items.append(new_item)","def __setitem__(self, index, value):\n self.buffer[index] = value","def push(self, item):\n if hasattr(item, \"__iter__\"):\n self.items.extend(item)\n else:\n self.items.append(item)","def append(self, item: T) -> None:\n self.insert(item)","def append(self, item):\n self.update([item])","def push(self):\n i = 0\n for ele in self.buffer:\n index = ele.find('\\n')\n if index != -1:\n self.publish(''.join(self.buffer[:i]+[self.buffer[i][:index]]))\n del self.buffer[:i]\n self.buffer[0] = self.buffer[0][index+1:]\n return True\n i += 1","def add(self, item: T) -> None:\n self._queue.append(item)\n if not self.is_empty():\n self._queue.sort(reverse=True)","def appendleft(self, x):\n entry = (self.start - 1) % len(self.buffer)\n if self.buffer[entry]:\n if self.start <= self.end:\n self.buffer = ([x]\n + self.buffer[self.start:self.end]\n + [None]*(self.size - 1))\n else:\n self.buffer = ([x]\n + [(item for item\n in (self.buffer[self.start:]\n + self.buffer[:self.end])\n if item is not None)]\n + [None]*(self.size - 1))\n self.start = 0\n self.end = len(self.buffer) - self.size + 1\n else:\n self.buffer[entry] = x\n self.start = entry","def push(self, item):\n pass","def insertFront(self, item):\n self.sentinel.insertAfter(item)\n self.N += 1","def push(self, item) -> None:\n self._items.append(item)","def push(self,item):\n self.items.append(item)","def push(self, item):\n self._data.append(item)","def push(self, item):\n\t\tself.top+=1;\n\t\tself.arr.insert(self.top, item);","def push(self, item):\n\t\tself.items.append(item)","def remember(self, item):\n self.memory.append(item)","def add_rear(self, item):\n\n self.items.append(item)","def push(self, item):\n self.items.append(item)","def push(self, item):\n self.items.append(item)","def push(self, item):\n self.items.append(item)","def push(self, item):\n self.items.append(item)","def push(self, item):\n self.items.append(item)","def consume(self):\n rest = self._buf.read()\n self._buf.seek(0, 0)\n self._buf.truncate(0)\n self._len = 0\n self.append(rest)","def put(self, key, item):\n if key or item:\n self.cache_data[key] = item\n if len(self.cache_data) > BaseCaching.MAX_ITEMS:\n print(\"DISCARD: {}\".format(self.last))\n del self.cache_data[self.last]\n self.last = key","def right_enqueue(self, item):\n item_to_add = Node(item)\n item_to_add.set_prev(self.tail)\n\n # if the deque is empty, the new item is the head\n if not self.head:\n self.head = item_to_add\n else:\n # connect the old tail to the new tail\n self.tail.set_next(item_to_add)\n\n self.tail = item_to_add\n self.size += 1","def grow(self):\n \n self.body.append(self.body[-1])","def add_to_buffer(self, values):\n self._buffer.extend(values)","def enqueue_front(self, item):\n self._items.insert(0, item)","def push(self, item: Any) -> None:\n self._data.append(item)","def append_bytes(self, data):\n\n if self.index != 7:\n self.buf.append(self.byte)\n self.byte = 0\n self.index = 7\n\n self.buf.extend(data)","def _check_buffer(self):\n count = 0\n for packet in self.remove_buffered_packets():\n self._append_packet(packet)\n count += 1\n\n if count > 0:\n logging.debug('Removed %i items from the buffer, %i left.' % (count, len(self.buffer)))","def enqueue(self, item):\n self.__queue.insert(0, item)","def push(self, item: Any) -> None:\n self._items.append(item)","def append(self, value):\n if len(self.data) >= n:\n self.data.pop(0)\n self.data.append(value)","def offer(self, value):\n if self.isFull():\n raise Exception(\"Queue too small!\")\n \n self.data[self.end] = value\n self.end += 1\n self.qSize += 1\n self.end = self.end % len(self.data)","def add_front(self, item):\n\n self.items.insert(0, item)","def put_nowait(self, item):\r\n if self.full():\r\n raise QueueFull\r\n self._put(item)\r\n self._unfinished_tasks += 1\r\n self._finished.clear()\r\n self._wakeup_next(self._getters)","def next(self,item):\n if not self.clist or len(self.clist)<self.maxsize:\n self.clist.append(item)\n self.wsize = len(self.clist)\n else:\n self.clist.popleft()\n if len(self.clist) > self.maxsize:\n print('Something fishy with size')\n else:\n self.clist.append(item)\n self.wsize = len(self.clist)","def push(self, item):\n self._items.append(item)","def add_item(self, command, screen_output, scroll_position):\n if self._pointer + 1 < len(self._items):\n self._items = self._items[:self._pointer + 1]\n self._items.append(\n NavigationHistoryItem(command, screen_output, scroll_position))\n if len(self._items) > self._capacity:\n self._items = self._items[-self._capacity:]\n self._pointer = len(self._items) - 1","def addToBuffer(self, request):\n raise NotImplementedError","def add_to_bag(self, item):\n self._bag.append(item)","def push(self, node):\n try:\n self._load(True)\n\n # Stow the new node at our head and increment it\n self.db[self.head] = node\n self.head = self.head + 1\n if self.head >= self.size:\n self.head -= self.size\n self.db['head'] = self.head\n\n # If we haven't just also pushed out an old item,\n # increment the count of items in our db.\n if self.count < self.size:\n self.count += 1\n self.db['count'] = self.count\n except KeyError:\n # HACK\n self.clear()","def write(self, data):\n self.buffer.append(data)\n while self.push():\n pass","def put(self, key, item):\n if key and item:\n if key in self.cache_data.keys():\n self.cache_data[key] = item\n self.stack.append(key)\n else:\n if len(self.cache_data.keys()) < self.MAX_ITEMS:\n self.cache_data[key] = item\n self.stack.append(key)\n elif len(self.cache_data.keys()) == self.MAX_ITEMS:\n k = self.stack.pop(-1)\n self.cache_data.pop(k)\n print(\"DISCARD: {}\".format(k))\n self.cache_data[key] = item\n self.stack.append(key)","def _append(self, key):\n \"\"\" Returns: The index at which the new value is appended \"\"\"\n if len(self.queue) > self.size:# There is still space left in queue\n self.queue[self.size] = key\n # No space left in queue\n self.queue.append(key)\n atIndex = self.size\n self.size += 1\n return atIndex","def push(self, e):\n # if reach the maxlen size\n if self._size == self._maxlen:\n self._front = (self._front + 1) % len(self._data)\n avail = (self._front + self._size - 1) % len(self._data)\n self._data[avail] = e\n return\n # not reach the maxlen size\n if self._size == len(self._data):\n self._resize(2 * self._size)\n avail = (self._front + self._size) % len(self._data)\n self._data[avail] = e\n self._size += 1","def add(self, obs_t, action, reward, obs_tp1, done):\n self.count += 1\n data = (obs_t, action, reward, obs_tp1, done)\n popped_data = self.buffers[0].add(*data)\n \n for i in range(1, self.num_buffers):\n #print(\"buffer \", i)\n #print(\"popped: \", popped_data)\n if popped_data == None:\n break\n if random.uniform(0, 1) < self.beta:\n popped_data = self.buffers[i].add(*popped_data)\n elif self.no_waste:\n self.overflow_buffer.appendleft(popped_data)\n break\n else:\n break\n if self.no_waste and (self.count > self._maxsize) and (len(self.overflow_buffer) != 0):\n self.overflow_buffer.pop()"],"string":"[\n \"def add(self, item):\\r\\n if len(self.buff)==self.size: self.buff.pop(0)\\r\\n self.buff.append(item)\",\n \"def delayed_buffer_item(self, buffer_item, buffer_item_len, item):\\n item_copy = copy.copy(item)\\n if buffer_item is None:\\n buffer_item = buffer_item_len * [item_copy]\\n else:\\n buffer_item.append(item_copy)\\n item_cur = copy.copy(buffer_item.pop(0))\\n\\n return buffer_item, item_cur\",\n \"def append(self, item):\\n if self.full or self.pre_allocated:\\n # overwrite\\n self.data[self.cur] = item\\n else:\\n self.data.append(item)\\n if not self.full:\\n self.full = self.cur == self.max - 1\\n self.cur = (self.cur + 1) % self.max\",\n \"def add_prev(self, item, index):\\n if index in self.d_buffer.keys():\\n return\\n if len(self) == self._size:\\n self.pop_last()\\n self.add_item(item, index)\",\n \"def add_item(self, item, index):\\n if index in self.d_buffer.keys():\\n return True\\n elif len(self) < self._size:\\n self.d_buffer.update({index: item})\\n return True\\n else:\\n return False\",\n \"def worker(self):\\n while True:\\n item,index = self.inbound.get()\\n if index is None:\\n self.buffer.append(item)\\n self.index.value = self.index.value + 1 #index of next item for buffer\\n if len(self.buffer)>self.size:\\n del self.buffer[0]\\n self.newitem.put(None)\\n else:\\n self.buffer[len(self.buffer)+(index - self.index.value)] = item\",\n \"def put(self, item): \\n if len(self.contents) < self.max_size:\\n self.contents.append(item)\\n elif len(self.contents) >= self.max_size:\\n print \\\"Backpack Full.\\\"\",\n \"def take_item(self, item):\\r\\n if len(self.items) <= 2:\\r\\n self.items.append(item)\\r\\n if self.got_both():\\r\\n self.working = True\",\n \"def push(self, item):\\n if len(self._data) == self.MAX_SIZE:\\n # full we have to pop the oldest item (head)\\n self._data.pop(0)\\n self._data.append(item)\",\n \"def _add(self, sample):#obs_t, action, reward, obs_tp1, done):\\n\\n if self._next_idx >= len(self._buffer): #appends data if max capacity not reached yet\\n self._buffer.append(sample)\\n else:\\n self._buffer[self._next_idx] = sample #drops old entry and appends new data if max capacity\\n self._next_idx = (self._next_idx + 1) % self._capacity\",\n \"def append(self, x):\\n if self.buffer[self.end]:\\n if self.start <= self.end:\\n self.buffer = (self.buffer[self.start:self.end]\\n + [x]\\n + [None]*(self.size - 1))\\n else:\\n self.buffer = ([(item for item\\n in (self.buffer[self.start:]\\n + self.buffer[:self.end])\\n if item is not None)]\\n + [x]\\n + [None]*(self.size - 1))\\n self.start = 0\\n self.end = len(self.buffer) - self.size + 1\\n else:\\n self.buffer[self.end] = x\\n self.end = (self.end + 1) % len(self.buffer)\",\n \"def push(self, item):\\n self.list.prepend(item)\",\n \"def append(self, state):\\n self._buffer[:-1] = self._buffer[1:]\\n self._buffer[-1] = state\",\n \"def add_item(self, item):\\n self.items.append(item)\\n self.length += 1\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][1] for b in buffer.memory] # lidar\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes (terminated or truncated)\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[3] for b in buffer.memory] # terminated\\n d8 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n\\n return self\",\n \"def enqueue(self, item):\\n\\t\\tself.items.insert(0, item)\",\n \"def add_last(self, data):\\n self.deque.append(data)\",\n \"def _push_from_buffer(self):\\r\\n if len(self.buffer) > 0:\\r\\n if time.time() - self.last_sent_time > 5:\\r\\n try:\\r\\n message = self.buffer.pop(0)\\r\\n self._send_now(message)\\r\\n finally:\\r\\n self.last_sent_time = time.time()\",\n \"def enqueue_rear(self, item):\\n self._items.append(item)\",\n \"def enqueue(self, item):\\n self.items.insert(0, item)\",\n \"def enqueue(self, item):\\n self.items.insert(0, item)\",\n \"def _buffer_to(self, amount):\\n if amount > self.lookahead:\\n raise Exception(\\n 'Cannot extend buffer to {}: '\\n 'beyond buffer lookahead {}'.format(\\n amount, self.lookahead\\n )\\n )\\n while len(self.buffer) < amount:\\n try:\\n self.buffer.appendleft(next(self.stream))\\n except StopIteration:\\n break\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][2] for b in buffer.memory] # lidar\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[1][1] for b in buffer.memory] # progress\\n d8 = [b[3] for b in buffer.memory] # terminated\\n d9 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n self.data[9] += d9\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n self.data.append(d9)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n self.data[9] = self.data[9][to_trim:]\\n\\n return self\",\n \"def add_first(self, data):\\n self.deque.insert(0, data)\",\n \"def insert(self, item):\\r\\n if not self.is_full():\\r\\n for i in range(1,len(self.items)):\\r\\n if self.items[i] is None:\\r\\n self.items[i] = item\\r\\n self.size += 1\\r\\n self.perc_up(i)\\r\\n return True\\r\\n return False\",\n \"def observation(self, observation):\\n \\n # push backward all observations\\n self.buffer[:-1] = self.buffer[1:]\\n\\n # add last observation to the end (similar to adding an item to a queue)\\n self.buffer[-1] = observation\\n \\n return self.buffer\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][3] for b in buffer.memory] # images\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[1][1] for b in buffer.memory] # gears\\n d8 = [b[1][2] for b in buffer.memory] # rpms\\n d9 = [b[3] for b in buffer.memory] # terminated\\n d10 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n self.data[9] += d9\\n self.data[10] += d10\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n self.data.append(d9)\\n self.data.append(d10)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n self.data[9] = self.data[9][to_trim:]\\n self.data[10] = self.data[10][to_trim:]\\n\\n return self\",\n \"def insertBack(self, item):\\n self.sentinel.prev.insertAfter(item)\\n self.N += 1\",\n \"def unshift(self, chunk):\\n if chunk:\\n self._pos -= len(chunk)\\n self._unconsumed.append(chunk)\",\n \"def push(self, item):\\n self._tail_iters.append(iter([item]))\",\n \"def pop_item(self, index):\\n ix, obj = self.items\\n if index < len(ix):\\n self.d_buffer.pop(ix[index])\\n else:\\n raise IndexError('Buffer does not have {0} elements'.format(index))\",\n \"def push(self, item):\\n super().add_item_to_front(item)\",\n \"def add(self, data):\\n self.databuffer.append(data)\\n if len(self.databuffer) > self.buffersize:\\n self._flush()\",\n \"def evict_or_add (self, item):\",\n \"def add_chunk(self, chunk):\\n self.chunkbuffer.appendleft(chunk)\",\n \"def enqueue(self, item):\\n # double size of array if necessary and recopy to front of array\\n if self._N == len(self._q):\\n self._resize(2*len(self._q)) # double size of array if necessary\\n self._q[self._last] = item # add item\\n self._last += 1\\n if self._last == len(self._q):\\n self._last = 0 # wrap-around\\n self._N += 1\",\n \"def append ( self , item ) :\\n self.cond.acquire()\\n try:\\n if self.closed :\\n raise Exception( \\\"Trying to append to a closed queue\\\" )\\n else :\\n self.weight += int( item['size'] )\\n self.push( item )\\n self.cond.notify()\\n finally:\\n self.cond.release()\",\n \"def push(self, item):\\n if item not in self._items:\\n self._items.append(item)\",\n \"def prepend(self, item: Any):\\n self.insert(0, item)\",\n \"def add_item(self, item: _T) -> None:\\n if item not in self.item_to_index:\\n self.item_to_index[item] = len(self.index_to_item)\\n self.index_to_item.append(item)\",\n \"def push(self, item):\\n self.linked_list.prepend(item)\",\n \"def add_item(self, item):\\n if self.head is None:\\n # if not self.array:\\n self.head = 0\\n self.array = [item]\\n else:\\n # insert item\\n self.array.insert(self.head, item)\\n\\n # reassign head\\n self.head += 1\",\n \"def add_to_buffer(self, packet):\\n # If the buffer is currently empty, the we should send the next packet\\n # (i.e. this packet) as soon as it finishes transmitting (which will take\\n # time + sizeofpacket/transmissionrate)\\n if (len(self.buffer) == 0):\\n self.next_packet_send_time = globals.systime + (packet.get_size()/self.rate)\\n\\n # Checks that there is room to add the packet to the buffer\\n if (packet.get_size() + self.buffersize <= self.buffercapacity):\\n self.buffersize = self.buffersize + packet.get_size()\\n self.buffer.append(packet)\\n # if there isn't room in the buffer, we return 0 to indicate that the\\n # packet was dropped.\\n else:\\n return 0\\n\\n # returns the size of the packet that was succesfully added to the\\n # buffer.\\n return packet.get_size()\",\n \"def push(self, Item):\\n self.data_container.insert(0, Item)\",\n \"def add(self, item):\\n if self.has_item(item):\\n return\\n\\n self.cache.append(item)\\n\\n if self.size() > self.max_size:\\n self.cache.popleft()\",\n \"def take(self, item): \\n self.contents.remove(item)\",\n \"def add_to_group(self,item):\\n self.items.append(item)\\n self.n += 1\",\n \"def push(self, item) -> None:\\n self.items.append(item)\",\n \"def add_item(self, item):\\n self.items.append(item)\\n self.item_count += 1\\n self.max_length = max(self.max_length, len(item.samples))\",\n \"def append(self, item):\\n\\n # resize array to 2*capacity if max capacity reached\\n if self.count == self.capacity:\\n self._resize(2 * self.capacity)\\n\\n # Append the item at the end of array\\n self.the_array[self.count] = item\\n self.count += 1\",\n \"def add(self, item):\\n self._set(item, None)\",\n \"def add(self, data):\\n wasquiet = True if (self.tail == self.curr) else False\\n\\n # Assert the queue is clean\\n qtail = self.base + \\\".\\\" + str(self.tail)\\n print \\\"creating %s\\\" % qtail\\n assert not os.path.exists(qtail)\\n qt = open(qtail, \\\"w\\\")\\n qt.write(data)\\n qt.close()\\n\\n # Where does the next item go\\n self.tail += 1\\n self._settail(self.tail)\\n\\n return wasquiet\",\n \"def push(self, new_item):\\n self.items.append(new_item)\",\n \"def __setitem__(self, index, value):\\n self.buffer[index] = value\",\n \"def push(self, item):\\n if hasattr(item, \\\"__iter__\\\"):\\n self.items.extend(item)\\n else:\\n self.items.append(item)\",\n \"def append(self, item: T) -> None:\\n self.insert(item)\",\n \"def append(self, item):\\n self.update([item])\",\n \"def push(self):\\n i = 0\\n for ele in self.buffer:\\n index = ele.find('\\\\n')\\n if index != -1:\\n self.publish(''.join(self.buffer[:i]+[self.buffer[i][:index]]))\\n del self.buffer[:i]\\n self.buffer[0] = self.buffer[0][index+1:]\\n return True\\n i += 1\",\n \"def add(self, item: T) -> None:\\n self._queue.append(item)\\n if not self.is_empty():\\n self._queue.sort(reverse=True)\",\n \"def appendleft(self, x):\\n entry = (self.start - 1) % len(self.buffer)\\n if self.buffer[entry]:\\n if self.start <= self.end:\\n self.buffer = ([x]\\n + self.buffer[self.start:self.end]\\n + [None]*(self.size - 1))\\n else:\\n self.buffer = ([x]\\n + [(item for item\\n in (self.buffer[self.start:]\\n + self.buffer[:self.end])\\n if item is not None)]\\n + [None]*(self.size - 1))\\n self.start = 0\\n self.end = len(self.buffer) - self.size + 1\\n else:\\n self.buffer[entry] = x\\n self.start = entry\",\n \"def push(self, item):\\n pass\",\n \"def insertFront(self, item):\\n self.sentinel.insertAfter(item)\\n self.N += 1\",\n \"def push(self, item) -> None:\\n self._items.append(item)\",\n \"def push(self,item):\\n self.items.append(item)\",\n \"def push(self, item):\\n self._data.append(item)\",\n \"def push(self, item):\\n\\t\\tself.top+=1;\\n\\t\\tself.arr.insert(self.top, item);\",\n \"def push(self, item):\\n\\t\\tself.items.append(item)\",\n \"def remember(self, item):\\n self.memory.append(item)\",\n \"def add_rear(self, item):\\n\\n self.items.append(item)\",\n \"def push(self, item):\\n self.items.append(item)\",\n \"def push(self, item):\\n self.items.append(item)\",\n \"def push(self, item):\\n self.items.append(item)\",\n \"def push(self, item):\\n self.items.append(item)\",\n \"def push(self, item):\\n self.items.append(item)\",\n \"def consume(self):\\n rest = self._buf.read()\\n self._buf.seek(0, 0)\\n self._buf.truncate(0)\\n self._len = 0\\n self.append(rest)\",\n \"def put(self, key, item):\\n if key or item:\\n self.cache_data[key] = item\\n if len(self.cache_data) > BaseCaching.MAX_ITEMS:\\n print(\\\"DISCARD: {}\\\".format(self.last))\\n del self.cache_data[self.last]\\n self.last = key\",\n \"def right_enqueue(self, item):\\n item_to_add = Node(item)\\n item_to_add.set_prev(self.tail)\\n\\n # if the deque is empty, the new item is the head\\n if not self.head:\\n self.head = item_to_add\\n else:\\n # connect the old tail to the new tail\\n self.tail.set_next(item_to_add)\\n\\n self.tail = item_to_add\\n self.size += 1\",\n \"def grow(self):\\n \\n self.body.append(self.body[-1])\",\n \"def add_to_buffer(self, values):\\n self._buffer.extend(values)\",\n \"def enqueue_front(self, item):\\n self._items.insert(0, item)\",\n \"def push(self, item: Any) -> None:\\n self._data.append(item)\",\n \"def append_bytes(self, data):\\n\\n if self.index != 7:\\n self.buf.append(self.byte)\\n self.byte = 0\\n self.index = 7\\n\\n self.buf.extend(data)\",\n \"def _check_buffer(self):\\n count = 0\\n for packet in self.remove_buffered_packets():\\n self._append_packet(packet)\\n count += 1\\n\\n if count > 0:\\n logging.debug('Removed %i items from the buffer, %i left.' % (count, len(self.buffer)))\",\n \"def enqueue(self, item):\\n self.__queue.insert(0, item)\",\n \"def push(self, item: Any) -> None:\\n self._items.append(item)\",\n \"def append(self, value):\\n if len(self.data) >= n:\\n self.data.pop(0)\\n self.data.append(value)\",\n \"def offer(self, value):\\n if self.isFull():\\n raise Exception(\\\"Queue too small!\\\")\\n \\n self.data[self.end] = value\\n self.end += 1\\n self.qSize += 1\\n self.end = self.end % len(self.data)\",\n \"def add_front(self, item):\\n\\n self.items.insert(0, item)\",\n \"def put_nowait(self, item):\\r\\n if self.full():\\r\\n raise QueueFull\\r\\n self._put(item)\\r\\n self._unfinished_tasks += 1\\r\\n self._finished.clear()\\r\\n self._wakeup_next(self._getters)\",\n \"def next(self,item):\\n if not self.clist or len(self.clist)<self.maxsize:\\n self.clist.append(item)\\n self.wsize = len(self.clist)\\n else:\\n self.clist.popleft()\\n if len(self.clist) > self.maxsize:\\n print('Something fishy with size')\\n else:\\n self.clist.append(item)\\n self.wsize = len(self.clist)\",\n \"def push(self, item):\\n self._items.append(item)\",\n \"def add_item(self, command, screen_output, scroll_position):\\n if self._pointer + 1 < len(self._items):\\n self._items = self._items[:self._pointer + 1]\\n self._items.append(\\n NavigationHistoryItem(command, screen_output, scroll_position))\\n if len(self._items) > self._capacity:\\n self._items = self._items[-self._capacity:]\\n self._pointer = len(self._items) - 1\",\n \"def addToBuffer(self, request):\\n raise NotImplementedError\",\n \"def add_to_bag(self, item):\\n self._bag.append(item)\",\n \"def push(self, node):\\n try:\\n self._load(True)\\n\\n # Stow the new node at our head and increment it\\n self.db[self.head] = node\\n self.head = self.head + 1\\n if self.head >= self.size:\\n self.head -= self.size\\n self.db['head'] = self.head\\n\\n # If we haven't just also pushed out an old item,\\n # increment the count of items in our db.\\n if self.count < self.size:\\n self.count += 1\\n self.db['count'] = self.count\\n except KeyError:\\n # HACK\\n self.clear()\",\n \"def write(self, data):\\n self.buffer.append(data)\\n while self.push():\\n pass\",\n \"def put(self, key, item):\\n if key and item:\\n if key in self.cache_data.keys():\\n self.cache_data[key] = item\\n self.stack.append(key)\\n else:\\n if len(self.cache_data.keys()) < self.MAX_ITEMS:\\n self.cache_data[key] = item\\n self.stack.append(key)\\n elif len(self.cache_data.keys()) == self.MAX_ITEMS:\\n k = self.stack.pop(-1)\\n self.cache_data.pop(k)\\n print(\\\"DISCARD: {}\\\".format(k))\\n self.cache_data[key] = item\\n self.stack.append(key)\",\n \"def _append(self, key):\\n \\\"\\\"\\\" Returns: The index at which the new value is appended \\\"\\\"\\\"\\n if len(self.queue) > self.size:# There is still space left in queue\\n self.queue[self.size] = key\\n # No space left in queue\\n self.queue.append(key)\\n atIndex = self.size\\n self.size += 1\\n return atIndex\",\n \"def push(self, e):\\n # if reach the maxlen size\\n if self._size == self._maxlen:\\n self._front = (self._front + 1) % len(self._data)\\n avail = (self._front + self._size - 1) % len(self._data)\\n self._data[avail] = e\\n return\\n # not reach the maxlen size\\n if self._size == len(self._data):\\n self._resize(2 * self._size)\\n avail = (self._front + self._size) % len(self._data)\\n self._data[avail] = e\\n self._size += 1\",\n \"def add(self, obs_t, action, reward, obs_tp1, done):\\n self.count += 1\\n data = (obs_t, action, reward, obs_tp1, done)\\n popped_data = self.buffers[0].add(*data)\\n \\n for i in range(1, self.num_buffers):\\n #print(\\\"buffer \\\", i)\\n #print(\\\"popped: \\\", popped_data)\\n if popped_data == None:\\n break\\n if random.uniform(0, 1) < self.beta:\\n popped_data = self.buffers[i].add(*popped_data)\\n elif self.no_waste:\\n self.overflow_buffer.appendleft(popped_data)\\n break\\n else:\\n break\\n if self.no_waste and (self.count > self._maxsize) and (len(self.overflow_buffer) != 0):\\n self.overflow_buffer.pop()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.781679","0.69368887","0.69074106","0.6848678","0.6844897","0.6722651","0.6693831","0.6517391","0.65031815","0.64660585","0.64001614","0.6381809","0.6352038","0.628194","0.6240794","0.6232624","0.62238234","0.62209296","0.62180114","0.62095904","0.62095904","0.6202612","0.61786526","0.617738","0.6170513","0.61614484","0.6149487","0.61281854","0.61150044","0.61130214","0.61104965","0.61082685","0.6097892","0.6096165","0.60808325","0.6074158","0.6049388","0.60490966","0.60291743","0.60242844","0.6023949","0.6005045","0.60009784","0.5994859","0.598559","0.5978995","0.59634864","0.5925478","0.5923105","0.5916884","0.5910272","0.59087795","0.58901006","0.5883241","0.58821815","0.58817196","0.58799505","0.587949","0.58788484","0.5876855","0.5869342","0.58644193","0.5858092","0.5846255","0.58454084","0.5839577","0.5833155","0.58296555","0.58241004","0.5818789","0.5818789","0.5818789","0.5818789","0.5818789","0.5806762","0.58063024","0.580225","0.5779321","0.57615143","0.5756753","0.5756131","0.5751817","0.5743197","0.57381374","0.5734842","0.5727885","0.5726748","0.572316","0.57217336","0.57209593","0.5712884","0.5709467","0.5709223","0.5706993","0.57002157","0.5699038","0.5697561","0.5685361","0.5685327","0.5681605"],"string":"[\n \"0.781679\",\n \"0.69368887\",\n \"0.69074106\",\n \"0.6848678\",\n \"0.6844897\",\n \"0.6722651\",\n \"0.6693831\",\n \"0.6517391\",\n \"0.65031815\",\n \"0.64660585\",\n \"0.64001614\",\n \"0.6381809\",\n \"0.6352038\",\n \"0.628194\",\n \"0.6240794\",\n \"0.6232624\",\n \"0.62238234\",\n \"0.62209296\",\n \"0.62180114\",\n \"0.62095904\",\n \"0.62095904\",\n \"0.6202612\",\n \"0.61786526\",\n \"0.617738\",\n \"0.6170513\",\n \"0.61614484\",\n \"0.6149487\",\n \"0.61281854\",\n \"0.61150044\",\n \"0.61130214\",\n \"0.61104965\",\n \"0.61082685\",\n \"0.6097892\",\n \"0.6096165\",\n \"0.60808325\",\n \"0.6074158\",\n \"0.6049388\",\n \"0.60490966\",\n \"0.60291743\",\n \"0.60242844\",\n \"0.6023949\",\n \"0.6005045\",\n \"0.60009784\",\n \"0.5994859\",\n \"0.598559\",\n \"0.5978995\",\n \"0.59634864\",\n \"0.5925478\",\n \"0.5923105\",\n \"0.5916884\",\n \"0.5910272\",\n \"0.59087795\",\n \"0.58901006\",\n \"0.5883241\",\n \"0.58821815\",\n \"0.58817196\",\n \"0.58799505\",\n \"0.587949\",\n \"0.58788484\",\n \"0.5876855\",\n \"0.5869342\",\n \"0.58644193\",\n \"0.5858092\",\n \"0.5846255\",\n \"0.58454084\",\n \"0.5839577\",\n \"0.5833155\",\n \"0.58296555\",\n \"0.58241004\",\n \"0.5818789\",\n \"0.5818789\",\n \"0.5818789\",\n \"0.5818789\",\n \"0.5818789\",\n \"0.5806762\",\n \"0.58063024\",\n \"0.580225\",\n \"0.5779321\",\n \"0.57615143\",\n \"0.5756753\",\n \"0.5756131\",\n \"0.5751817\",\n \"0.5743197\",\n \"0.57381374\",\n \"0.5734842\",\n \"0.5727885\",\n \"0.5726748\",\n \"0.572316\",\n \"0.57217336\",\n \"0.57209593\",\n \"0.5712884\",\n \"0.5709467\",\n \"0.5709223\",\n \"0.5706993\",\n \"0.57002157\",\n \"0.5699038\",\n \"0.5697561\",\n \"0.5685361\",\n \"0.5685327\",\n \"0.5681605\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7406223"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":81776,"cells":{"query":{"kind":"string","value":"Add a new item at the beginning of the buffer and drop one item if necessary (from the end)"},"document":{"kind":"string","value":"def add_prev(self, item, index):\n if index in self.d_buffer.keys():\n return\n if len(self) == self._size:\n self.pop_last()\n self.add_item(item, index)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def add(self, item):\r\n if len(self.buff)==self.size: self.buff.pop(0)\r\n self.buff.append(item)","def add_next(self, item, index):\n if index in self.d_buffer.keys():\n return\n if len(self) == self.size:\n self.pop_first()\n self.add_item(item, index)","def delayed_buffer_item(self, buffer_item, buffer_item_len, item):\n item_copy = copy.copy(item)\n if buffer_item is None:\n buffer_item = buffer_item_len * [item_copy]\n else:\n buffer_item.append(item_copy)\n item_cur = copy.copy(buffer_item.pop(0))\n\n return buffer_item, item_cur","def worker(self):\n while True:\n item,index = self.inbound.get()\n if index is None:\n self.buffer.append(item)\n self.index.value = self.index.value + 1 #index of next item for buffer\n if len(self.buffer)>self.size:\n del self.buffer[0]\n self.newitem.put(None)\n else:\n self.buffer[len(self.buffer)+(index - self.index.value)] = item","def prepend(self, item: Any):\n self.insert(0, item)","def add_first(self, data):\n self.deque.insert(0, data)","def unshift(self, chunk):\n if chunk:\n self._pos -= len(chunk)\n self._unconsumed.append(chunk)","def append(self, item):\n if self.full or self.pre_allocated:\n # overwrite\n self.data[self.cur] = item\n else:\n self.data.append(item)\n if not self.full:\n self.full = self.cur == self.max - 1\n self.cur = (self.cur + 1) % self.max","def push(self, item):\n self.list.prepend(item)","def add_item(self, item, index):\n if index in self.d_buffer.keys():\n return True\n elif len(self) < self._size:\n self.d_buffer.update({index: item})\n return True\n else:\n return False","def insertFront(self, item):\n self.sentinel.insertAfter(item)\n self.N += 1","def take_item(self, item):\r\n if len(self.items) <= 2:\r\n self.items.append(item)\r\n if self.got_both():\r\n self.working = True","def enqueue(self, item):\n\t\tself.items.insert(0, item)","def appendleft(self, x):\n entry = (self.start - 1) % len(self.buffer)\n if self.buffer[entry]:\n if self.start <= self.end:\n self.buffer = ([x]\n + self.buffer[self.start:self.end]\n + [None]*(self.size - 1))\n else:\n self.buffer = ([x]\n + [(item for item\n in (self.buffer[self.start:]\n + self.buffer[:self.end])\n if item is not None)]\n + [None]*(self.size - 1))\n self.start = 0\n self.end = len(self.buffer) - self.size + 1\n else:\n self.buffer[entry] = x\n self.start = entry","def enqueue(self, item):\n self.items.insert(0, item)","def enqueue(self, item):\n self.items.insert(0, item)","def push(self, item):\n if len(self._data) == self.MAX_SIZE:\n # full we have to pop the oldest item (head)\n self._data.pop(0)\n self._data.append(item)","def put(self, item): \n if len(self.contents) < self.max_size:\n self.contents.append(item)\n elif len(self.contents) >= self.max_size:\n print \"Backpack Full.\"","def _add(self, sample):#obs_t, action, reward, obs_tp1, done):\n\n if self._next_idx >= len(self._buffer): #appends data if max capacity not reached yet\n self._buffer.append(sample)\n else:\n self._buffer[self._next_idx] = sample #drops old entry and appends new data if max capacity\n self._next_idx = (self._next_idx + 1) % self._capacity","def enqueue_front(self, item):\n self._items.insert(0, item)","def add_front(self, item):\n\n self.items.insert(0, item)","def push(self, item):\n super().add_item_to_front(item)","def insertBack(self, item):\n self.sentinel.prev.insertAfter(item)\n self.N += 1","def _push_from_buffer(self):\r\n if len(self.buffer) > 0:\r\n if time.time() - self.last_sent_time > 5:\r\n try:\r\n message = self.buffer.pop(0)\r\n self._send_now(message)\r\n finally:\r\n self.last_sent_time = time.time()","def insert(self, item):\r\n if not self.is_full():\r\n for i in range(1,len(self.items)):\r\n if self.items[i] is None:\r\n self.items[i] = item\r\n self.size += 1\r\n self.perc_up(i)\r\n return True\r\n return False","def push(self, item):\n self.linked_list.prepend(item)","def pop_item(self, index):\n ix, obj = self.items\n if index < len(ix):\n self.d_buffer.pop(ix[index])\n else:\n raise IndexError('Buffer does not have {0} elements'.format(index))","def append(self, x):\n if self.buffer[self.end]:\n if self.start <= self.end:\n self.buffer = (self.buffer[self.start:self.end]\n + [x]\n + [None]*(self.size - 1))\n else:\n self.buffer = ([(item for item\n in (self.buffer[self.start:]\n + self.buffer[:self.end])\n if item is not None)]\n + [x]\n + [None]*(self.size - 1))\n self.start = 0\n self.end = len(self.buffer) - self.size + 1\n else:\n self.buffer[self.end] = x\n self.end = (self.end + 1) % len(self.buffer)","def _buffer_to(self, amount):\n if amount > self.lookahead:\n raise Exception(\n 'Cannot extend buffer to {}: '\n 'beyond buffer lookahead {}'.format(\n amount, self.lookahead\n )\n )\n while len(self.buffer) < amount:\n try:\n self.buffer.appendleft(next(self.stream))\n except StopIteration:\n break","def take(self, item): \n self.contents.remove(item)","def observation(self, observation):\n \n # push backward all observations\n self.buffer[:-1] = self.buffer[1:]\n\n # add last observation to the end (similar to adding an item to a queue)\n self.buffer[-1] = observation\n \n return self.buffer","def enqueue_rear(self, item):\n self._items.append(item)","def evict_or_add (self, item):","def enqueue(self, item):\n # double size of array if necessary and recopy to front of array\n if self._N == len(self._q):\n self._resize(2*len(self._q)) # double size of array if necessary\n self._q[self._last] = item # add item\n self._last += 1\n if self._last == len(self._q):\n self._last = 0 # wrap-around\n self._N += 1","def _insert_first(self, item: Any) -> None:\n if self.is_empty():\n raise IndexError\n return self.insert(0, item)","def append(self, state):\n self._buffer[:-1] = self._buffer[1:]\n self._buffer[-1] = state","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][1] for b in buffer.memory] # lidar\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes (terminated or truncated)\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[3] for b in buffer.memory] # terminated\n d8 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n\n return self","def add_item(self, item):\n self.items.append(item)\n self.length += 1","def add_item(self, item):\n if self.head is None:\n # if not self.array:\n self.head = 0\n self.array = [item]\n else:\n # insert item\n self.array.insert(self.head, item)\n\n # reassign head\n self.head += 1","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][2] for b in buffer.memory] # lidar\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[1][1] for b in buffer.memory] # progress\n d8 = [b[3] for b in buffer.memory] # terminated\n d9 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n self.data[9] += d9\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n self.data.append(d9)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n self.data[9] = self.data[9][to_trim:]\n\n return self","def add_chunk(self, chunk):\n self.chunkbuffer.appendleft(chunk)","def push(self, Item):\n self.data_container.insert(0, Item)","def append_buffer(self, buffer):\n\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\n\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\n d1 = [b[0] for b in buffer.memory] # actions\n d2 = [b[1][0] for b in buffer.memory] # speeds\n d3 = [b[1][3] for b in buffer.memory] # images\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\n d5 = [b[2] for b in buffer.memory] # rewards\n d6 = [b[5] for b in buffer.memory] # infos\n d7 = [b[1][1] for b in buffer.memory] # gears\n d8 = [b[1][2] for b in buffer.memory] # rpms\n d9 = [b[3] for b in buffer.memory] # terminated\n d10 = [b[4] for b in buffer.memory] # truncated\n\n if self.__len__() > 0:\n self.data[0] += d0\n self.data[1] += d1\n self.data[2] += d2\n self.data[3] += d3\n self.data[4] += d4\n self.data[5] += d5\n self.data[6] += d6\n self.data[7] += d7\n self.data[8] += d8\n self.data[9] += d9\n self.data[10] += d10\n else:\n self.data.append(d0)\n self.data.append(d1)\n self.data.append(d2)\n self.data.append(d3)\n self.data.append(d4)\n self.data.append(d5)\n self.data.append(d6)\n self.data.append(d7)\n self.data.append(d8)\n self.data.append(d9)\n self.data.append(d10)\n\n to_trim = self.__len__() - self.memory_size\n if to_trim > 0:\n self.data[0] = self.data[0][to_trim:]\n self.data[1] = self.data[1][to_trim:]\n self.data[2] = self.data[2][to_trim:]\n self.data[3] = self.data[3][to_trim:]\n self.data[4] = self.data[4][to_trim:]\n self.data[5] = self.data[5][to_trim:]\n self.data[6] = self.data[6][to_trim:]\n self.data[7] = self.data[7][to_trim:]\n self.data[8] = self.data[8][to_trim:]\n self.data[9] = self.data[9][to_trim:]\n self.data[10] = self.data[10][to_trim:]\n\n return self","def __setitem__(self, index, value):\n self.buffer[index] = value","def add_item(self, item: _T) -> None:\n if item not in self.item_to_index:\n self.item_to_index[item] = len(self.index_to_item)\n self.index_to_item.append(item)","def enqueue(self, item):\n self.__queue.insert(0, item)","def add(self, item):\n self._set(item, None)","def push(self, item):\n if item not in self._items:\n self._items.append(item)","def consume(self):\n rest = self._buf.read()\n self._buf.seek(0, 0)\n self._buf.truncate(0)\n self._len = 0\n self.append(rest)","def cbuf_push_left(buf, val):\n return buf.at[1:].set(buf[:-1]).at[0].set(val)","def add_to_buffer(self, packet):\n # If the buffer is currently empty, the we should send the next packet\n # (i.e. this packet) as soon as it finishes transmitting (which will take\n # time + sizeofpacket/transmissionrate)\n if (len(self.buffer) == 0):\n self.next_packet_send_time = globals.systime + (packet.get_size()/self.rate)\n\n # Checks that there is room to add the packet to the buffer\n if (packet.get_size() + self.buffersize <= self.buffercapacity):\n self.buffersize = self.buffersize + packet.get_size()\n self.buffer.append(packet)\n # if there isn't room in the buffer, we return 0 to indicate that the\n # packet was dropped.\n else:\n return 0\n\n # returns the size of the packet that was succesfully added to the\n # buffer.\n return packet.get_size()","def push(self, item):\n self._tail_iters.append(iter([item]))","def add_last(self, data):\n self.deque.append(data)","def remember(self, item):\n self.memory.append(item)","def push(self, item):\n\t\tself.top+=1;\n\t\tself.arr.insert(self.top, item);","def fillBuffer():\n buff[bufferCounter].next = dataIn","def insert(self, value):\n current_timestamp = time.time()\n self.timestamps.append(current_timestamp)\n self.dataBuffer.append(value)\n if (self.timestamps[0] < (current_timestamp - self.seconds_back)):\n self.dataBuffer.pop(0)\n self.timestamps.pop(0)","def insert(self, item):\r\n self.fetch()\r\n t = self.make_item_tuple(item)\r\n changed = False\r\n if t not in self.data:\r\n self.data.insert(0, t)\r\n changed = True\r\n\r\n if changed:\r\n query_cache.set(self.iden, self.data[:precompute_limit])","def delete(self) -> None:\n if not self.buffer or self.index == len(self.buffer):\n return\n\n self.buffer.delete(self.index)\n\n if 0 < self.index > self.buffer.end:\n self.index = self.buffer.end","def _move_item(self, src, dst):\n \"Does nothing\"","def push(self):\n i = 0\n for ele in self.buffer:\n index = ele.find('\\n')\n if index != -1:\n self.publish(''.join(self.buffer[:i]+[self.buffer[i][:index]]))\n del self.buffer[:i]\n self.buffer[0] = self.buffer[0][index+1:]\n return True\n i += 1","def add(self, item):\n if self.has_item(item):\n return\n\n self.cache.append(item)\n\n if self.size() > self.max_size:\n self.cache.popleft()","def insert_first(self, item):\n if self.is_empty():\n self._first = item\n self._rest = LinkedListRec([None])\n else:\n new_list = LinkedListRec([self._first])\n new_list._rest = self._rest\n self._first = item\n self._rest = new_list","def put(self, key, item):\n if key or item:\n self.cache_data[key] = item\n if len(self.cache_data) > BaseCaching.MAX_ITEMS:\n print(\"DISCARD: {}\".format(self.last))\n del self.cache_data[self.last]\n self.last = key","def add(self, data):\n self.databuffer.append(data)\n if len(self.databuffer) > self.buffersize:\n self._flush()","def __init__(self,size=10):\n \n self.inbound = Queue() #an internal queue to manage the class properly in a thread safe manner.\n self.index = Value('i',0) #index of next item to be added.\n self.manager = Manager()\n \n self.buffer = self.manager.list() #the buffer we will store things in.\n self.size = size #the maximum size of the buffer\n self.newitem = Queue() #a blocking event to control the pop method\n t = threading.Thread(target=self.worker) #the worker that will run when items are added.\n t.start() #start the worker\n self.newitemindex = 0 #index of items to pop","def insert(self, item):\n self.heaplist.append(item)\n self.currentsize += 1\n self.shift_item_up(self.currentsize)","def right_enqueue(self, item):\n item_to_add = Node(item)\n item_to_add.set_prev(self.tail)\n\n # if the deque is empty, the new item is the head\n if not self.head:\n self.head = item_to_add\n else:\n # connect the old tail to the new tail\n self.tail.set_next(item_to_add)\n\n self.tail = item_to_add\n self.size += 1","def push(self, node):\n try:\n self._load(True)\n\n # Stow the new node at our head and increment it\n self.db[self.head] = node\n self.head = self.head + 1\n if self.head >= self.size:\n self.head -= self.size\n self.db['head'] = self.head\n\n # If we haven't just also pushed out an old item,\n # increment the count of items in our db.\n if self.count < self.size:\n self.count += 1\n self.db['count'] = self.count\n except KeyError:\n # HACK\n self.clear()","def replace_buffer(new_data, offset, datatype):\n offset = offset - 1\n\n if offset < 0:\n # If our buffer was a zero buffer, we don't need to bother changing.\n return\n\n global buffer\n buffer_size = len(new_data.flatten()) * dtype_size(datatype)\n (buffer_size, new_data) = align(buffer_size, new_data)\n\n # print(offset)\n buffer[offset] = new_data","def __setitem__(self, index, item):\n # TODO: complete this function!\n if index >= self.__len__():\n raise IndexError\n else:\n if index == 0:\n self._first = item\n else:\n self._rest.__setitem__(index-1, item)","def add_before ( self ):\n self.add_item( 0 )","def push(self, item):\n if hasattr(item, \"__iter__\"):\n self.items.extend(item)\n else:\n self.items.append(item)","def push(self, item) -> None:\n self.items.append(item)","def add_to_group(self,item):\n self.items.append(item)\n self.n += 1","def offer(self, value):\n if self.isFull():\n raise Exception(\"Queue too small!\")\n \n self.data[self.end] = value\n self.end += 1\n self.qSize += 1\n self.end = self.end % len(self.data)","def put(self, key, item):\n if key is None or item is None:\n return\n if key in self.key_tracker.keys():\n self.key_tracker.pop(key)\n if len(self.key_tracker) >= BaseCaching.MAX_ITEMS:\n x = self.most_recent_use_key()\n print(\"DISCARD: {}\".format(x))\n self.key_tracker.pop(x)\n self.cache_data.pop(x)\n self.cache_data.update({key: item})\n self.key_tracker.update({key: self.count})\n self.count += 1","def enqueue(self, item):\n self.list.append(item)","def put_nowait(self, item):\r\n if self.full():\r\n raise QueueFull\r\n self._put(item)\r\n self._unfinished_tasks += 1\r\n self._finished.clear()\r\n self._wakeup_next(self._getters)","def push(self, item):\n pass","def append(self, item: T) -> None:\n self.insert(item)","def add(self, item: T) -> None:\n self._queue.append(item)\n if not self.is_empty():\n self._queue.sort(reverse=True)","def push(self,item):\n self.items.append(item)","def push(self, item):\n self._cursor_stack.append(item)","def insert(self, index, newItem):\r\n if self.size() == len(self):\r\n self.grow()\r\n if index >= self.size():\r\n self._items[self.size()] = newItem\r\n else:\r\n index = max(index, 0)\r\n # Shift items down by one position\r\n for i in range(self.size(), index, -1):\r\n self._items[i] = self._items[i - 1]\r\n\r\n # Add new item and increment logical size\r\n self._items[index] = newItem\r\n self._logicalSize += 1","def push(self, new_item):\n self.items.append(new_item)","def enqueue(self, item):\n old_last = self.last\n self.last = self.Node(item)\n\n if self.is_empty():\n self.first = self.last\n else:\n old_last.next_node = self.last\n\n self.N += 1","def put(self, key, item):\n if key and item:\n if key in self.cache_data.keys():\n self.cache_data[key] = item\n self.stack.append(key)\n else:\n if len(self.cache_data.keys()) < self.MAX_ITEMS:\n self.cache_data[key] = item\n self.stack.append(key)\n elif len(self.cache_data.keys()) == self.MAX_ITEMS:\n k = self.stack.pop(-1)\n self.cache_data.pop(k)\n print(\"DISCARD: {}\".format(k))\n self.cache_data[key] = item\n self.stack.append(key)","def add_zero_item(items, coder, tag, start):\n if items[tag][coder]:\n it = items[tag][coder][-1]\n zero_start = it.b + it.l\n else:\n zero_start = 0\n if start - zero_start:\n items[tag][coder].append(item(b=zero_start, l=start - zero_start, v=0))","def add_item(self, item):\n self.items.append(item)\n self.item_count += 1\n self.max_length = max(self.max_length, len(item.samples))","def push(self, item):\n\t\tself.items.append(item)","def push(self, item) -> None:\n self._items.append(item)","def add_item(self, command, screen_output, scroll_position):\n if self._pointer + 1 < len(self._items):\n self._items = self._items[:self._pointer + 1]\n self._items.append(\n NavigationHistoryItem(command, screen_output, scroll_position))\n if len(self._items) > self._capacity:\n self._items = self._items[-self._capacity:]\n self._pointer = len(self._items) - 1","def addToBuffer(self, request):\n raise NotImplementedError","def pop(self):\n self.newitem.get() #blocks until an item is added, using a queue for this to ensure that only one worker is triggered.\n #if self.newitemindex+1==self.index: self.newitem.clear()\n index = self.newitemindex\n item = self.read(index)\n self.newitemindex += 1\n \n return index, item","def pop(self):\n value = self.buffer[self.end - 1]\n self.buffer[self.end - 1] = None\n self.end = (self.end - 1) % len(self.buffer)\n return value","def next(self,item):\n if not self.clist or len(self.clist)<self.maxsize:\n self.clist.append(item)\n self.wsize = len(self.clist)\n else:\n self.clist.popleft()\n if len(self.clist) > self.maxsize:\n print('Something fishy with size')\n else:\n self.clist.append(item)\n self.wsize = len(self.clist)","def grow(self):\n \n self.body.append(self.body[-1])","def _append(self, key):\n \"\"\" Returns: The index at which the new value is appended \"\"\"\n if len(self.queue) > self.size:# There is still space left in queue\n self.queue[self.size] = key\n # No space left in queue\n self.queue.append(key)\n atIndex = self.size\n self.size += 1\n return atIndex","def insert(self, index, item):\n\n # Check if -len(self) <= index <= len(self)\n valid_index = (index <= len(self)) and (index >= -len(self))\n\n try:\n if not valid_index:\n raise IndexError\n\n if self.count == self.capacity:\n self._resize(2 * self.capacity)\n\n # Index '-1' for last item, '-len(self)' for first item\n if index < 0:\n index = index + len(self)\n\n # Move every item after the 'index' to the right\n for i in range(self.count, index - 1, -1):\n self.the_array[i] = self.the_array[i - 1]\n\n # Insert the 'item' at 'index'\n self.the_array[index] = item\n self.count += 1\n\n return True\n\n except IndexError:\n print(\"Index must be in between -len(self) to len(self).\")\n return False"],"string":"[\n \"def add(self, item):\\r\\n if len(self.buff)==self.size: self.buff.pop(0)\\r\\n self.buff.append(item)\",\n \"def add_next(self, item, index):\\n if index in self.d_buffer.keys():\\n return\\n if len(self) == self.size:\\n self.pop_first()\\n self.add_item(item, index)\",\n \"def delayed_buffer_item(self, buffer_item, buffer_item_len, item):\\n item_copy = copy.copy(item)\\n if buffer_item is None:\\n buffer_item = buffer_item_len * [item_copy]\\n else:\\n buffer_item.append(item_copy)\\n item_cur = copy.copy(buffer_item.pop(0))\\n\\n return buffer_item, item_cur\",\n \"def worker(self):\\n while True:\\n item,index = self.inbound.get()\\n if index is None:\\n self.buffer.append(item)\\n self.index.value = self.index.value + 1 #index of next item for buffer\\n if len(self.buffer)>self.size:\\n del self.buffer[0]\\n self.newitem.put(None)\\n else:\\n self.buffer[len(self.buffer)+(index - self.index.value)] = item\",\n \"def prepend(self, item: Any):\\n self.insert(0, item)\",\n \"def add_first(self, data):\\n self.deque.insert(0, data)\",\n \"def unshift(self, chunk):\\n if chunk:\\n self._pos -= len(chunk)\\n self._unconsumed.append(chunk)\",\n \"def append(self, item):\\n if self.full or self.pre_allocated:\\n # overwrite\\n self.data[self.cur] = item\\n else:\\n self.data.append(item)\\n if not self.full:\\n self.full = self.cur == self.max - 1\\n self.cur = (self.cur + 1) % self.max\",\n \"def push(self, item):\\n self.list.prepend(item)\",\n \"def add_item(self, item, index):\\n if index in self.d_buffer.keys():\\n return True\\n elif len(self) < self._size:\\n self.d_buffer.update({index: item})\\n return True\\n else:\\n return False\",\n \"def insertFront(self, item):\\n self.sentinel.insertAfter(item)\\n self.N += 1\",\n \"def take_item(self, item):\\r\\n if len(self.items) <= 2:\\r\\n self.items.append(item)\\r\\n if self.got_both():\\r\\n self.working = True\",\n \"def enqueue(self, item):\\n\\t\\tself.items.insert(0, item)\",\n \"def appendleft(self, x):\\n entry = (self.start - 1) % len(self.buffer)\\n if self.buffer[entry]:\\n if self.start <= self.end:\\n self.buffer = ([x]\\n + self.buffer[self.start:self.end]\\n + [None]*(self.size - 1))\\n else:\\n self.buffer = ([x]\\n + [(item for item\\n in (self.buffer[self.start:]\\n + self.buffer[:self.end])\\n if item is not None)]\\n + [None]*(self.size - 1))\\n self.start = 0\\n self.end = len(self.buffer) - self.size + 1\\n else:\\n self.buffer[entry] = x\\n self.start = entry\",\n \"def enqueue(self, item):\\n self.items.insert(0, item)\",\n \"def enqueue(self, item):\\n self.items.insert(0, item)\",\n \"def push(self, item):\\n if len(self._data) == self.MAX_SIZE:\\n # full we have to pop the oldest item (head)\\n self._data.pop(0)\\n self._data.append(item)\",\n \"def put(self, item): \\n if len(self.contents) < self.max_size:\\n self.contents.append(item)\\n elif len(self.contents) >= self.max_size:\\n print \\\"Backpack Full.\\\"\",\n \"def _add(self, sample):#obs_t, action, reward, obs_tp1, done):\\n\\n if self._next_idx >= len(self._buffer): #appends data if max capacity not reached yet\\n self._buffer.append(sample)\\n else:\\n self._buffer[self._next_idx] = sample #drops old entry and appends new data if max capacity\\n self._next_idx = (self._next_idx + 1) % self._capacity\",\n \"def enqueue_front(self, item):\\n self._items.insert(0, item)\",\n \"def add_front(self, item):\\n\\n self.items.insert(0, item)\",\n \"def push(self, item):\\n super().add_item_to_front(item)\",\n \"def insertBack(self, item):\\n self.sentinel.prev.insertAfter(item)\\n self.N += 1\",\n \"def _push_from_buffer(self):\\r\\n if len(self.buffer) > 0:\\r\\n if time.time() - self.last_sent_time > 5:\\r\\n try:\\r\\n message = self.buffer.pop(0)\\r\\n self._send_now(message)\\r\\n finally:\\r\\n self.last_sent_time = time.time()\",\n \"def insert(self, item):\\r\\n if not self.is_full():\\r\\n for i in range(1,len(self.items)):\\r\\n if self.items[i] is None:\\r\\n self.items[i] = item\\r\\n self.size += 1\\r\\n self.perc_up(i)\\r\\n return True\\r\\n return False\",\n \"def push(self, item):\\n self.linked_list.prepend(item)\",\n \"def pop_item(self, index):\\n ix, obj = self.items\\n if index < len(ix):\\n self.d_buffer.pop(ix[index])\\n else:\\n raise IndexError('Buffer does not have {0} elements'.format(index))\",\n \"def append(self, x):\\n if self.buffer[self.end]:\\n if self.start <= self.end:\\n self.buffer = (self.buffer[self.start:self.end]\\n + [x]\\n + [None]*(self.size - 1))\\n else:\\n self.buffer = ([(item for item\\n in (self.buffer[self.start:]\\n + self.buffer[:self.end])\\n if item is not None)]\\n + [x]\\n + [None]*(self.size - 1))\\n self.start = 0\\n self.end = len(self.buffer) - self.size + 1\\n else:\\n self.buffer[self.end] = x\\n self.end = (self.end + 1) % len(self.buffer)\",\n \"def _buffer_to(self, amount):\\n if amount > self.lookahead:\\n raise Exception(\\n 'Cannot extend buffer to {}: '\\n 'beyond buffer lookahead {}'.format(\\n amount, self.lookahead\\n )\\n )\\n while len(self.buffer) < amount:\\n try:\\n self.buffer.appendleft(next(self.stream))\\n except StopIteration:\\n break\",\n \"def take(self, item): \\n self.contents.remove(item)\",\n \"def observation(self, observation):\\n \\n # push backward all observations\\n self.buffer[:-1] = self.buffer[1:]\\n\\n # add last observation to the end (similar to adding an item to a queue)\\n self.buffer[-1] = observation\\n \\n return self.buffer\",\n \"def enqueue_rear(self, item):\\n self._items.append(item)\",\n \"def evict_or_add (self, item):\",\n \"def enqueue(self, item):\\n # double size of array if necessary and recopy to front of array\\n if self._N == len(self._q):\\n self._resize(2*len(self._q)) # double size of array if necessary\\n self._q[self._last] = item # add item\\n self._last += 1\\n if self._last == len(self._q):\\n self._last = 0 # wrap-around\\n self._N += 1\",\n \"def _insert_first(self, item: Any) -> None:\\n if self.is_empty():\\n raise IndexError\\n return self.insert(0, item)\",\n \"def append(self, state):\\n self._buffer[:-1] = self._buffer[1:]\\n self._buffer[-1] = state\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][1] for b in buffer.memory] # lidar\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes (terminated or truncated)\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[3] for b in buffer.memory] # terminated\\n d8 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n\\n return self\",\n \"def add_item(self, item):\\n self.items.append(item)\\n self.length += 1\",\n \"def add_item(self, item):\\n if self.head is None:\\n # if not self.array:\\n self.head = 0\\n self.array = [item]\\n else:\\n # insert item\\n self.array.insert(self.head, item)\\n\\n # reassign head\\n self.head += 1\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][2] for b in buffer.memory] # lidar\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[1][1] for b in buffer.memory] # progress\\n d8 = [b[3] for b in buffer.memory] # terminated\\n d9 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n self.data[9] += d9\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n self.data.append(d9)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n self.data[9] = self.data[9][to_trim:]\\n\\n return self\",\n \"def add_chunk(self, chunk):\\n self.chunkbuffer.appendleft(chunk)\",\n \"def push(self, Item):\\n self.data_container.insert(0, Item)\",\n \"def append_buffer(self, buffer):\\n\\n first_data_idx = self.data[0][-1] + 1 if self.__len__() > 0 else 0\\n\\n d0 = [first_data_idx + i for i, _ in enumerate(buffer.memory)] # indexes\\n d1 = [b[0] for b in buffer.memory] # actions\\n d2 = [b[1][0] for b in buffer.memory] # speeds\\n d3 = [b[1][3] for b in buffer.memory] # images\\n d4 = [b[3] or b[4] for b in buffer.memory] # eoes\\n d5 = [b[2] for b in buffer.memory] # rewards\\n d6 = [b[5] for b in buffer.memory] # infos\\n d7 = [b[1][1] for b in buffer.memory] # gears\\n d8 = [b[1][2] for b in buffer.memory] # rpms\\n d9 = [b[3] for b in buffer.memory] # terminated\\n d10 = [b[4] for b in buffer.memory] # truncated\\n\\n if self.__len__() > 0:\\n self.data[0] += d0\\n self.data[1] += d1\\n self.data[2] += d2\\n self.data[3] += d3\\n self.data[4] += d4\\n self.data[5] += d5\\n self.data[6] += d6\\n self.data[7] += d7\\n self.data[8] += d8\\n self.data[9] += d9\\n self.data[10] += d10\\n else:\\n self.data.append(d0)\\n self.data.append(d1)\\n self.data.append(d2)\\n self.data.append(d3)\\n self.data.append(d4)\\n self.data.append(d5)\\n self.data.append(d6)\\n self.data.append(d7)\\n self.data.append(d8)\\n self.data.append(d9)\\n self.data.append(d10)\\n\\n to_trim = self.__len__() - self.memory_size\\n if to_trim > 0:\\n self.data[0] = self.data[0][to_trim:]\\n self.data[1] = self.data[1][to_trim:]\\n self.data[2] = self.data[2][to_trim:]\\n self.data[3] = self.data[3][to_trim:]\\n self.data[4] = self.data[4][to_trim:]\\n self.data[5] = self.data[5][to_trim:]\\n self.data[6] = self.data[6][to_trim:]\\n self.data[7] = self.data[7][to_trim:]\\n self.data[8] = self.data[8][to_trim:]\\n self.data[9] = self.data[9][to_trim:]\\n self.data[10] = self.data[10][to_trim:]\\n\\n return self\",\n \"def __setitem__(self, index, value):\\n self.buffer[index] = value\",\n \"def add_item(self, item: _T) -> None:\\n if item not in self.item_to_index:\\n self.item_to_index[item] = len(self.index_to_item)\\n self.index_to_item.append(item)\",\n \"def enqueue(self, item):\\n self.__queue.insert(0, item)\",\n \"def add(self, item):\\n self._set(item, None)\",\n \"def push(self, item):\\n if item not in self._items:\\n self._items.append(item)\",\n \"def consume(self):\\n rest = self._buf.read()\\n self._buf.seek(0, 0)\\n self._buf.truncate(0)\\n self._len = 0\\n self.append(rest)\",\n \"def cbuf_push_left(buf, val):\\n return buf.at[1:].set(buf[:-1]).at[0].set(val)\",\n \"def add_to_buffer(self, packet):\\n # If the buffer is currently empty, the we should send the next packet\\n # (i.e. this packet) as soon as it finishes transmitting (which will take\\n # time + sizeofpacket/transmissionrate)\\n if (len(self.buffer) == 0):\\n self.next_packet_send_time = globals.systime + (packet.get_size()/self.rate)\\n\\n # Checks that there is room to add the packet to the buffer\\n if (packet.get_size() + self.buffersize <= self.buffercapacity):\\n self.buffersize = self.buffersize + packet.get_size()\\n self.buffer.append(packet)\\n # if there isn't room in the buffer, we return 0 to indicate that the\\n # packet was dropped.\\n else:\\n return 0\\n\\n # returns the size of the packet that was succesfully added to the\\n # buffer.\\n return packet.get_size()\",\n \"def push(self, item):\\n self._tail_iters.append(iter([item]))\",\n \"def add_last(self, data):\\n self.deque.append(data)\",\n \"def remember(self, item):\\n self.memory.append(item)\",\n \"def push(self, item):\\n\\t\\tself.top+=1;\\n\\t\\tself.arr.insert(self.top, item);\",\n \"def fillBuffer():\\n buff[bufferCounter].next = dataIn\",\n \"def insert(self, value):\\n current_timestamp = time.time()\\n self.timestamps.append(current_timestamp)\\n self.dataBuffer.append(value)\\n if (self.timestamps[0] < (current_timestamp - self.seconds_back)):\\n self.dataBuffer.pop(0)\\n self.timestamps.pop(0)\",\n \"def insert(self, item):\\r\\n self.fetch()\\r\\n t = self.make_item_tuple(item)\\r\\n changed = False\\r\\n if t not in self.data:\\r\\n self.data.insert(0, t)\\r\\n changed = True\\r\\n\\r\\n if changed:\\r\\n query_cache.set(self.iden, self.data[:precompute_limit])\",\n \"def delete(self) -> None:\\n if not self.buffer or self.index == len(self.buffer):\\n return\\n\\n self.buffer.delete(self.index)\\n\\n if 0 < self.index > self.buffer.end:\\n self.index = self.buffer.end\",\n \"def _move_item(self, src, dst):\\n \\\"Does nothing\\\"\",\n \"def push(self):\\n i = 0\\n for ele in self.buffer:\\n index = ele.find('\\\\n')\\n if index != -1:\\n self.publish(''.join(self.buffer[:i]+[self.buffer[i][:index]]))\\n del self.buffer[:i]\\n self.buffer[0] = self.buffer[0][index+1:]\\n return True\\n i += 1\",\n \"def add(self, item):\\n if self.has_item(item):\\n return\\n\\n self.cache.append(item)\\n\\n if self.size() > self.max_size:\\n self.cache.popleft()\",\n \"def insert_first(self, item):\\n if self.is_empty():\\n self._first = item\\n self._rest = LinkedListRec([None])\\n else:\\n new_list = LinkedListRec([self._first])\\n new_list._rest = self._rest\\n self._first = item\\n self._rest = new_list\",\n \"def put(self, key, item):\\n if key or item:\\n self.cache_data[key] = item\\n if len(self.cache_data) > BaseCaching.MAX_ITEMS:\\n print(\\\"DISCARD: {}\\\".format(self.last))\\n del self.cache_data[self.last]\\n self.last = key\",\n \"def add(self, data):\\n self.databuffer.append(data)\\n if len(self.databuffer) > self.buffersize:\\n self._flush()\",\n \"def __init__(self,size=10):\\n \\n self.inbound = Queue() #an internal queue to manage the class properly in a thread safe manner.\\n self.index = Value('i',0) #index of next item to be added.\\n self.manager = Manager()\\n \\n self.buffer = self.manager.list() #the buffer we will store things in.\\n self.size = size #the maximum size of the buffer\\n self.newitem = Queue() #a blocking event to control the pop method\\n t = threading.Thread(target=self.worker) #the worker that will run when items are added.\\n t.start() #start the worker\\n self.newitemindex = 0 #index of items to pop\",\n \"def insert(self, item):\\n self.heaplist.append(item)\\n self.currentsize += 1\\n self.shift_item_up(self.currentsize)\",\n \"def right_enqueue(self, item):\\n item_to_add = Node(item)\\n item_to_add.set_prev(self.tail)\\n\\n # if the deque is empty, the new item is the head\\n if not self.head:\\n self.head = item_to_add\\n else:\\n # connect the old tail to the new tail\\n self.tail.set_next(item_to_add)\\n\\n self.tail = item_to_add\\n self.size += 1\",\n \"def push(self, node):\\n try:\\n self._load(True)\\n\\n # Stow the new node at our head and increment it\\n self.db[self.head] = node\\n self.head = self.head + 1\\n if self.head >= self.size:\\n self.head -= self.size\\n self.db['head'] = self.head\\n\\n # If we haven't just also pushed out an old item,\\n # increment the count of items in our db.\\n if self.count < self.size:\\n self.count += 1\\n self.db['count'] = self.count\\n except KeyError:\\n # HACK\\n self.clear()\",\n \"def replace_buffer(new_data, offset, datatype):\\n offset = offset - 1\\n\\n if offset < 0:\\n # If our buffer was a zero buffer, we don't need to bother changing.\\n return\\n\\n global buffer\\n buffer_size = len(new_data.flatten()) * dtype_size(datatype)\\n (buffer_size, new_data) = align(buffer_size, new_data)\\n\\n # print(offset)\\n buffer[offset] = new_data\",\n \"def __setitem__(self, index, item):\\n # TODO: complete this function!\\n if index >= self.__len__():\\n raise IndexError\\n else:\\n if index == 0:\\n self._first = item\\n else:\\n self._rest.__setitem__(index-1, item)\",\n \"def add_before ( self ):\\n self.add_item( 0 )\",\n \"def push(self, item):\\n if hasattr(item, \\\"__iter__\\\"):\\n self.items.extend(item)\\n else:\\n self.items.append(item)\",\n \"def push(self, item) -> None:\\n self.items.append(item)\",\n \"def add_to_group(self,item):\\n self.items.append(item)\\n self.n += 1\",\n \"def offer(self, value):\\n if self.isFull():\\n raise Exception(\\\"Queue too small!\\\")\\n \\n self.data[self.end] = value\\n self.end += 1\\n self.qSize += 1\\n self.end = self.end % len(self.data)\",\n \"def put(self, key, item):\\n if key is None or item is None:\\n return\\n if key in self.key_tracker.keys():\\n self.key_tracker.pop(key)\\n if len(self.key_tracker) >= BaseCaching.MAX_ITEMS:\\n x = self.most_recent_use_key()\\n print(\\\"DISCARD: {}\\\".format(x))\\n self.key_tracker.pop(x)\\n self.cache_data.pop(x)\\n self.cache_data.update({key: item})\\n self.key_tracker.update({key: self.count})\\n self.count += 1\",\n \"def enqueue(self, item):\\n self.list.append(item)\",\n \"def put_nowait(self, item):\\r\\n if self.full():\\r\\n raise QueueFull\\r\\n self._put(item)\\r\\n self._unfinished_tasks += 1\\r\\n self._finished.clear()\\r\\n self._wakeup_next(self._getters)\",\n \"def push(self, item):\\n pass\",\n \"def append(self, item: T) -> None:\\n self.insert(item)\",\n \"def add(self, item: T) -> None:\\n self._queue.append(item)\\n if not self.is_empty():\\n self._queue.sort(reverse=True)\",\n \"def push(self,item):\\n self.items.append(item)\",\n \"def push(self, item):\\n self._cursor_stack.append(item)\",\n \"def insert(self, index, newItem):\\r\\n if self.size() == len(self):\\r\\n self.grow()\\r\\n if index >= self.size():\\r\\n self._items[self.size()] = newItem\\r\\n else:\\r\\n index = max(index, 0)\\r\\n # Shift items down by one position\\r\\n for i in range(self.size(), index, -1):\\r\\n self._items[i] = self._items[i - 1]\\r\\n\\r\\n # Add new item and increment logical size\\r\\n self._items[index] = newItem\\r\\n self._logicalSize += 1\",\n \"def push(self, new_item):\\n self.items.append(new_item)\",\n \"def enqueue(self, item):\\n old_last = self.last\\n self.last = self.Node(item)\\n\\n if self.is_empty():\\n self.first = self.last\\n else:\\n old_last.next_node = self.last\\n\\n self.N += 1\",\n \"def put(self, key, item):\\n if key and item:\\n if key in self.cache_data.keys():\\n self.cache_data[key] = item\\n self.stack.append(key)\\n else:\\n if len(self.cache_data.keys()) < self.MAX_ITEMS:\\n self.cache_data[key] = item\\n self.stack.append(key)\\n elif len(self.cache_data.keys()) == self.MAX_ITEMS:\\n k = self.stack.pop(-1)\\n self.cache_data.pop(k)\\n print(\\\"DISCARD: {}\\\".format(k))\\n self.cache_data[key] = item\\n self.stack.append(key)\",\n \"def add_zero_item(items, coder, tag, start):\\n if items[tag][coder]:\\n it = items[tag][coder][-1]\\n zero_start = it.b + it.l\\n else:\\n zero_start = 0\\n if start - zero_start:\\n items[tag][coder].append(item(b=zero_start, l=start - zero_start, v=0))\",\n \"def add_item(self, item):\\n self.items.append(item)\\n self.item_count += 1\\n self.max_length = max(self.max_length, len(item.samples))\",\n \"def push(self, item):\\n\\t\\tself.items.append(item)\",\n \"def push(self, item) -> None:\\n self._items.append(item)\",\n \"def add_item(self, command, screen_output, scroll_position):\\n if self._pointer + 1 < len(self._items):\\n self._items = self._items[:self._pointer + 1]\\n self._items.append(\\n NavigationHistoryItem(command, screen_output, scroll_position))\\n if len(self._items) > self._capacity:\\n self._items = self._items[-self._capacity:]\\n self._pointer = len(self._items) - 1\",\n \"def addToBuffer(self, request):\\n raise NotImplementedError\",\n \"def pop(self):\\n self.newitem.get() #blocks until an item is added, using a queue for this to ensure that only one worker is triggered.\\n #if self.newitemindex+1==self.index: self.newitem.clear()\\n index = self.newitemindex\\n item = self.read(index)\\n self.newitemindex += 1\\n \\n return index, item\",\n \"def pop(self):\\n value = self.buffer[self.end - 1]\\n self.buffer[self.end - 1] = None\\n self.end = (self.end - 1) % len(self.buffer)\\n return value\",\n \"def next(self,item):\\n if not self.clist or len(self.clist)<self.maxsize:\\n self.clist.append(item)\\n self.wsize = len(self.clist)\\n else:\\n self.clist.popleft()\\n if len(self.clist) > self.maxsize:\\n print('Something fishy with size')\\n else:\\n self.clist.append(item)\\n self.wsize = len(self.clist)\",\n \"def grow(self):\\n \\n self.body.append(self.body[-1])\",\n \"def _append(self, key):\\n \\\"\\\"\\\" Returns: The index at which the new value is appended \\\"\\\"\\\"\\n if len(self.queue) > self.size:# There is still space left in queue\\n self.queue[self.size] = key\\n # No space left in queue\\n self.queue.append(key)\\n atIndex = self.size\\n self.size += 1\\n return atIndex\",\n \"def insert(self, index, item):\\n\\n # Check if -len(self) <= index <= len(self)\\n valid_index = (index <= len(self)) and (index >= -len(self))\\n\\n try:\\n if not valid_index:\\n raise IndexError\\n\\n if self.count == self.capacity:\\n self._resize(2 * self.capacity)\\n\\n # Index '-1' for last item, '-len(self)' for first item\\n if index < 0:\\n index = index + len(self)\\n\\n # Move every item after the 'index' to the right\\n for i in range(self.count, index - 1, -1):\\n self.the_array[i] = self.the_array[i - 1]\\n\\n # Insert the 'item' at 'index'\\n self.the_array[index] = item\\n self.count += 1\\n\\n return True\\n\\n except IndexError:\\n print(\\\"Index must be in between -len(self) to len(self).\\\")\\n return False\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7400422","0.71560556","0.69278336","0.6553957","0.6530426","0.6513943","0.6506356","0.6479094","0.64768803","0.6469337","0.63909703","0.62929386","0.6251014","0.624164","0.6228138","0.6228138","0.6215412","0.6198763","0.61914164","0.6188572","0.6176583","0.61553514","0.6154079","0.61493236","0.60819244","0.60816175","0.60788494","0.6065721","0.6060843","0.60539967","0.60517895","0.5997814","0.59828335","0.59734493","0.5955009","0.59472823","0.591495","0.5865264","0.585279","0.5833054","0.5810502","0.57778645","0.5774953","0.57607275","0.5745194","0.57230365","0.5711197","0.5694736","0.56868976","0.5651381","0.5649587","0.5648505","0.56395334","0.56346655","0.5630337","0.5620397","0.5613321","0.5599573","0.5589485","0.5588547","0.558578","0.5578537","0.55598927","0.55431825","0.5540256","0.5534708","0.5530294","0.55298567","0.5527066","0.5518063","0.55153275","0.55017","0.55000407","0.54901177","0.5489168","0.5482013","0.5479803","0.547756","0.54763156","0.5475207","0.5470067","0.5461806","0.54491997","0.5443787","0.54432714","0.54397064","0.54347205","0.5431498","0.54270446","0.54251707","0.54246","0.5422826","0.54222435","0.54176223","0.5417578","0.54172045","0.5414869","0.5411325","0.54112726","0.54052407"],"string":"[\n \"0.7400422\",\n \"0.71560556\",\n \"0.69278336\",\n \"0.6553957\",\n \"0.6530426\",\n \"0.6513943\",\n \"0.6506356\",\n \"0.6479094\",\n \"0.64768803\",\n \"0.6469337\",\n \"0.63909703\",\n \"0.62929386\",\n \"0.6251014\",\n \"0.624164\",\n \"0.6228138\",\n \"0.6228138\",\n \"0.6215412\",\n \"0.6198763\",\n \"0.61914164\",\n \"0.6188572\",\n \"0.6176583\",\n \"0.61553514\",\n \"0.6154079\",\n \"0.61493236\",\n \"0.60819244\",\n \"0.60816175\",\n \"0.60788494\",\n \"0.6065721\",\n \"0.6060843\",\n \"0.60539967\",\n \"0.60517895\",\n \"0.5997814\",\n \"0.59828335\",\n \"0.59734493\",\n \"0.5955009\",\n \"0.59472823\",\n \"0.591495\",\n \"0.5865264\",\n \"0.585279\",\n \"0.5833054\",\n \"0.5810502\",\n \"0.57778645\",\n \"0.5774953\",\n \"0.57607275\",\n \"0.5745194\",\n \"0.57230365\",\n \"0.5711197\",\n \"0.5694736\",\n \"0.56868976\",\n \"0.5651381\",\n \"0.5649587\",\n \"0.5648505\",\n \"0.56395334\",\n \"0.56346655\",\n \"0.5630337\",\n \"0.5620397\",\n \"0.5613321\",\n \"0.5599573\",\n \"0.5589485\",\n \"0.5588547\",\n \"0.558578\",\n \"0.5578537\",\n \"0.55598927\",\n \"0.55431825\",\n \"0.5540256\",\n \"0.5534708\",\n \"0.5530294\",\n \"0.55298567\",\n \"0.5527066\",\n \"0.5518063\",\n \"0.55153275\",\n \"0.55017\",\n \"0.55000407\",\n \"0.54901177\",\n \"0.5489168\",\n \"0.5482013\",\n \"0.5479803\",\n \"0.547756\",\n \"0.54763156\",\n \"0.5475207\",\n \"0.5470067\",\n \"0.5461806\",\n \"0.54491997\",\n \"0.5443787\",\n \"0.54432714\",\n \"0.54397064\",\n \"0.54347205\",\n \"0.5431498\",\n \"0.54270446\",\n \"0.54251707\",\n \"0.54246\",\n \"0.5422826\",\n \"0.54222435\",\n \"0.54176223\",\n \"0.5417578\",\n \"0.54172045\",\n \"0.5414869\",\n \"0.5411325\",\n \"0.54112726\",\n \"0.54052407\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.70878935"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81777,"cells":{"query":{"kind":"string","value":"In response to a signal, stops filling the buffer Argument signum frame"},"document":{"kind":"string","value":"def stop_filling(self, signum, frame):\n self._filling = False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def handler(signum, frame):\n m.signal()","def signal_handler(self, signum, frame):\n self._running = False","def signal_kernel(self, signum: int):","def signal_kernel(self, signum):\n pass","def sigterm(signum, frame):\n loop.stop()","def signal(self, args):\n pass","def __signalHandler(self, signalNumber, frame):\n self._loop = False","def handler(signum, frame):\n logging.warning(\"Got a {} signal. Doing nothing\".format(signum))","def signal_handler(signal, frame):\n Clear()\n exit(0)","def _signal_handler(signum, frame):\n res_mgr()\n sys.exit(0)","def handler(signum, frame):\n print(\"Signal handler called with signal %i\" % signum)\n sys.exit(-1)","def signal_handler(self, signal_number, frame):\n sys.exit(0)","def signal(self):\n pass","def requeueHandler(self, signum, frame):\n args = self.args\n print('Signal received', signum, time.time(), flush=True)\n self.SIGNAL_RECEIVED = True\n\n if os.path.isfile(self.HALT_filename):\n print('Job is done, exiting', flush=True)\n exit(0)","def handler(signum, frame):\n global keep_running\n keep_running = False","def handler(signum, frame):\n global keep_running\n keep_running = False","def signal_handler(signal, frame):\n print()\n endProgram(0)","def signal_handler(sig, frame):\n raise ExitException()","def empty_signal(self, *args, **kwargs):\n pass","def signal_handler(signum, frame):\n sys.exit(0)","def signal_handler(self, signum, frame):\n if signum == signal.SIGINT:\n self.terminate = True\n elif signum == signal.SIGALRM:\n self.button_handler(self.BUTTON_PIN)","def handler_sighup(signum, frame):\n global done, pipe\n\n try:\n pipe.flush()\n pipe.close()\n except:\n pass\n pipe = None\n done = True","def interrupt_handler(self, signo, frame):\n log.debug(\"interrupting run\")\n self._keep_running = False","def signal_handler(signal_received, frame):\n\n sys.stdout.write('\\n')\n sys.exit(0)","def _handle_term_signal(self, sig: int, frame: FrameType) -> None:\n del sig, frame # Unused.\n raise SystemExit()","def handle_sigint(self, signum, frame):\n self.finish()\n self.original_handler(signum, frame)","def fancy_handler(signum: int, frame: Any, spinner: Yaspin) -> None: # pylint: disable=unused-argument\n spinner.red.fail(\"✘\")\n spinner.stop()\n sys.exit(0)","def stop(self, signum=None, frame=None):\n self.__logger.warning(\"Caught signal, exiting\")\n self._running = False","def stop(self, signal):\n pass","def stop(self, signal):\n pass","def signal_handler(sig_num, frame):\n global exit_flag\n logger.warn('Signal Recieved: {}'.format(str(sig_num)))\n if sig_num:\n exit_flag = True","def signal_handler(signal, frame):\n sys.exit(0)","def signal_handler(signal, frame):\n sys.exit(0)","def signal_handler(signal, frame):\n sys.exit(0)","def dummyF(self, arg, signal, sender):\n \n if self.isDead == True:\n return\n \n \n #print \"DUMMY\"\n if self.aborting:\n self.aborting = False\n self.isActive = False\n self.__orderQueue.popleft()\n del self.slaveTalk\n self.slaveTalk = None\n# self.__orderQueue.popleft()\n try:\n self.releaseLock()\n except:\n pass\n #print \"No lock, actually.\" \n dispatcher.send('SLAVE_PARSE_QUEUE', self, '')","def signalReceived (self, signal): \n raise NotImplementedError(\"Lack of signalReceived method\")","def signal_oi(self):\n pass","def _signal_handler(*args):\n self._user_exit = True","def abort_ber_meas(self):\r\r\n loggerCmw = logging.getLogger('abort_ber_meas')\r\r\n self.write('ABORt:WCDMa:SIGN:BER')\r\r\n loggerCmw.info(\"Aborting BER measurements\")\r\r\n time.sleep(1)","def signal_handler(signal, frame):\n print(chr(27) + \"[2J\")\n sys.exit(0)","def signal_handler(sig, frame):\n sys.exit(0)","def timeout(signum, frame):\n global stopping_timeout\n print(\"Received signal: {!s} frame: {!s}\".format(signum, frame))\n # mutating a mutable object doesn't require changing what the variable name points to\n # Python2/3 compat (ugly) workaround\n stopping_timeout[0] = True","def handle_sigterm(signum, frame):\n raise TermException","def receive_signal(signal_number, frame):\n\n global read_loop\n\n print('Received signal: ', signal_number)\n read_loop = False","def abort_signal(self, signal, frame):\r\n\r\n print \"\\nMANUAL TERMINATION: Stopping all threads...\"\r\n self.stop(True)\r\n sys.exit(0)","def signal(sig, action): # real signature unknown; restored from __doc__\n pass","def siginterrupt(sig, flag): # real signature unknown; restored from __doc__\n pass","def _sigterm_handler(signum: int, _frame: FrameType) -> None:\n sys.exit('from sigterm handler')","def handler(signum, frame, spinner):\n spinner.fail()\n spinner.stop()","def signal_process( Qin, source, stop_flag, log, pos_ref, FIX_1BIT_ERRORS=False ):\n\n\trow_size = 16 + 112*2 #240 bits\n\t\n\twhile( not stop_flag.is_set() ):\n\t\tcurr_time = time.strftime('%d/%b/%Y %H:%M:%S', time.localtime())\n\t\t\n\t\t# Get streaming chunk from sdr_read thread\n\t\ty = Qin.get();\n\t\t\t\n\t\tpacket_diff = len(packets)\n\t\tidx_preamble, noise_floor = asp.detectPreamble(y)\t\t\n\t\tfor n in idx_preamble:\n\t\t\tsignal = abs(y[int(n) : int(n) + row_size])\n\t\t\tmsg = asp.decode_ADSB( signal, FIX_1BIT_ERRORS )\n\t\t\tif msg != None:\n\t\t\t\tsnr = asp.SNR(signal, noise_floor)\n\t\t\t\tpkt = ao.Packet(msg, time.time(), snr)\n\t\t\t\tpackets.append( pkt )\n\t\t\t\tprint( '!' , end='', flush=True )\n\t\t\t\t\n\t\t\t\tif len(packets) > PACKET_BUFF_SIZE:\n\t\t\t\t\tpackets.pop(0)\n\t\t\t\t\n\t\t\t\tif log != None:\n\t\t\t\t\ttry:\n\t\t\t\t\t\twith open(log, 'a') as f:\n\t\t\t\t\t\t\tf.write(f\"[{curr_time}] {msg}\\n\")\n\t\t\t\t\texcept:\n\t\t\t\t\t\tprint(f\"Error writing to {log}!\")\n\t\t\t\t\n\t\t\t\tif pkt.icao in planes:\n\t\t\t\t\tplanes[pkt.icao].process_packet( pkt )\n\t\t\t\telif pkt.icao != None:\n\t\t\t\t\tplanes[pkt.icao] = ao.Plane( pkt, pos_ref )\n\t\t\n\t\tif packet_diff == len(packets):\n\t\t\t# packets.append(f\"[{curr_time}] None received...\")\n\t\t\tprint( '.' , end='', flush=True )\n\t\t\n\t\t# Remove excess objects\n\t\tto_delete = []\n\t\tfor p in planes.keys():\n\t\t\tif (time.time() - planes[p].last_update) >= TTL:\n\t\t\t\tto_delete.append(p)\n\t\t\n\t\tfor p in to_delete:\n\t\t\tplanes.pop(p)\n\t\t\n\t\tQin.queue.clear()","def signal(self):\n self.mainloop().signal()","def signal_handler(self, signal, frame):\n logger.info('CTRL+C pressed')\n self.trigger_stop()","def _termination_handler(self, signum, frame):\n print '[i] Shutting down...'\n self.sensor.close()\n sys.exit(1)","def process_signal(self, src, tag, value):\n pass","def __streamHandler__(signum, frame):\n raise Exception(\"end of time\")","def sigint_handler(signal, frame):\n rclpy.shutdown()\n if prev_sigint_handler is not None:\n prev_sigint_handler(signal)","def shutdownSignal(signum, frame):\n LOG.warning(\"shutting down, got signal %d\", signum)\n shutdown()","def port_buffer_drop():","def signal_handler(signum, frame):\n main.CLOSE = True","def gracefulexit(signalnumber, frame):\n\t\n\tsys.exit(0) # resources will be closed on their corresponding finally blocks","def signal_handler(signum, frame):\n monitor.stop()\n sys.exit(0)","def found_terminator(self):\n self.signal_filter.send((self, \"\".join(self.buffer)))\n del(self.buffer[:])","def signal_handler(signal_number, stack_frame):\n if signal_number in [signal.SIGTERM, signal.SIGINT]:\n terminate_surveillance()","def signal_handler(self, signal, frame):\n logger.error(\"Received Signal to Terminate\")\n self.set_lcd_brightness(self.DIM_SHUT)\n ui.runui = False\n # sys.exit(0)","def termHandler(self, signum, frame):\n print(\"SIGTERM caught and ignored\", flush=True)","def _fill_buffer(self, in_data, *args, **kwargs):\r\n self._buff.put(in_data)\r\n return None, pyaudio.paContinue","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def stop_emission(self, detailed_signal): # reliably restored by inspect\n pass","def signal_handler(self, signum):\n raise Exception(\"Caught signal {0}\".format(signum))","def _sigint(self, signal, frame):\n self.disconnect = True\n if self.cardinal:\n self.cardinal.quit('Received SIGINT.')","def abort() -> NoReturn:\n raise AbortSignal","def default_handler(signum: int, frame: Any, spinner: Yaspin) -> None: # pylint: disable=unused-argument\n spinner.fail()\n spinner.stop()\n sys.exit(0)","def exit_from_signals(self, signal_num, frame):\n detail = 'signal {}'.format(signal_num)\n self.exit(detail)","def sendSignal (self, signal) :\n\n data = streamModule.WriteBuffer()\n\n data.writeStruct('B', signal)\n\n return self.sendCommand(\"CMD_IN_DO_KILL\", data.getvalue()).addCallback(self._sendSignal_result)","def SendEndScanSignal(self):\n pass","def signal_handler(self, signal, frame):\r\n print 'You pressed Ctrl+C!'\r\n sys.exit(0)","def fit(self, signal):\n self.signal = signal","def signal_rsi(self):\n pass","def _HandleStopSignal(self, sig, frame):\n del frame # Unused.\n logging.info('Received signal %d', sig)\n if self.stopping:\n reactor.callLater(3, reactor.stop)\n return\n\n logging.info('Stop umpired...')\n self.Stop()","def send_blocking_signal(self, compression=True):\n while not self._stop_receive.is_set():\n if len(self._send_queue) > 0:\n super(MastermindClientUDP, self).send(JSONSerializer.serialize(self._send_queue.pop()), compression)\n else:\n super(MastermindClientUDP, self).send(JSONSerializer.serialize(DummyEvent()), compression)\n time.sleep(1)","def _fill_buffer(self, in_data, *args, **kwargs):\n self._buff.put(in_data)\n return None, pyaudio.paContinue","def sig_exit_gracefully(cursignal, frame):\n print(\"Exiting in a Graceful way sig=\", cursignal, frame)\n traceback.print_exc(file=sys.stdout)\n #for c in mac_targets.values():\n # try:\n # c.set_var(0)\n # except Exception, x:\n # print \"Exception:\", x\n sys.stdout.flush()\n sys.stderr.flush()\n sys.exit(0)","def _exit_gracefully(self, signum, frame):\n self.log.info(\"Exiting gracefully upon receiving signal %s\", signum)\n self.log.debug(\"Current Stacktrace is: %s\", \"\\n\".join(map(str, inspect.stack())))\n self.terminate()\n self.end()\n self.log.debug(\"Finished terminating DAG processors.\")\n sys.exit(os.EX_OK)","def signal_qual(self):\n sig = None\n while sig is None:\n sig = self.acquire_signal_quality()\n time.sleep(0.5)\n return sig","def _signal_handler(signalnum: int, _: Any) -> None:\n logger.info('Received signal: {0}', signal.Signals(signalnum).name)\n # safely close video stream & writer\n stream.stop()\n writer.close()\n sys.exit(0)"],"string":"[\n \"def handler(signum, frame):\\n m.signal()\",\n \"def signal_handler(self, signum, frame):\\n self._running = False\",\n \"def signal_kernel(self, signum: int):\",\n \"def signal_kernel(self, signum):\\n pass\",\n \"def sigterm(signum, frame):\\n loop.stop()\",\n \"def signal(self, args):\\n pass\",\n \"def __signalHandler(self, signalNumber, frame):\\n self._loop = False\",\n \"def handler(signum, frame):\\n logging.warning(\\\"Got a {} signal. Doing nothing\\\".format(signum))\",\n \"def signal_handler(signal, frame):\\n Clear()\\n exit(0)\",\n \"def _signal_handler(signum, frame):\\n res_mgr()\\n sys.exit(0)\",\n \"def handler(signum, frame):\\n print(\\\"Signal handler called with signal %i\\\" % signum)\\n sys.exit(-1)\",\n \"def signal_handler(self, signal_number, frame):\\n sys.exit(0)\",\n \"def signal(self):\\n pass\",\n \"def requeueHandler(self, signum, frame):\\n args = self.args\\n print('Signal received', signum, time.time(), flush=True)\\n self.SIGNAL_RECEIVED = True\\n\\n if os.path.isfile(self.HALT_filename):\\n print('Job is done, exiting', flush=True)\\n exit(0)\",\n \"def handler(signum, frame):\\n global keep_running\\n keep_running = False\",\n \"def handler(signum, frame):\\n global keep_running\\n keep_running = False\",\n \"def signal_handler(signal, frame):\\n print()\\n endProgram(0)\",\n \"def signal_handler(sig, frame):\\n raise ExitException()\",\n \"def empty_signal(self, *args, **kwargs):\\n pass\",\n \"def signal_handler(signum, frame):\\n sys.exit(0)\",\n \"def signal_handler(self, signum, frame):\\n if signum == signal.SIGINT:\\n self.terminate = True\\n elif signum == signal.SIGALRM:\\n self.button_handler(self.BUTTON_PIN)\",\n \"def handler_sighup(signum, frame):\\n global done, pipe\\n\\n try:\\n pipe.flush()\\n pipe.close()\\n except:\\n pass\\n pipe = None\\n done = True\",\n \"def interrupt_handler(self, signo, frame):\\n log.debug(\\\"interrupting run\\\")\\n self._keep_running = False\",\n \"def signal_handler(signal_received, frame):\\n\\n sys.stdout.write('\\\\n')\\n sys.exit(0)\",\n \"def _handle_term_signal(self, sig: int, frame: FrameType) -> None:\\n del sig, frame # Unused.\\n raise SystemExit()\",\n \"def handle_sigint(self, signum, frame):\\n self.finish()\\n self.original_handler(signum, frame)\",\n \"def fancy_handler(signum: int, frame: Any, spinner: Yaspin) -> None: # pylint: disable=unused-argument\\n spinner.red.fail(\\\"✘\\\")\\n spinner.stop()\\n sys.exit(0)\",\n \"def stop(self, signum=None, frame=None):\\n self.__logger.warning(\\\"Caught signal, exiting\\\")\\n self._running = False\",\n \"def stop(self, signal):\\n pass\",\n \"def stop(self, signal):\\n pass\",\n \"def signal_handler(sig_num, frame):\\n global exit_flag\\n logger.warn('Signal Recieved: {}'.format(str(sig_num)))\\n if sig_num:\\n exit_flag = True\",\n \"def signal_handler(signal, frame):\\n sys.exit(0)\",\n \"def signal_handler(signal, frame):\\n sys.exit(0)\",\n \"def signal_handler(signal, frame):\\n sys.exit(0)\",\n \"def dummyF(self, arg, signal, sender):\\n \\n if self.isDead == True:\\n return\\n \\n \\n #print \\\"DUMMY\\\"\\n if self.aborting:\\n self.aborting = False\\n self.isActive = False\\n self.__orderQueue.popleft()\\n del self.slaveTalk\\n self.slaveTalk = None\\n# self.__orderQueue.popleft()\\n try:\\n self.releaseLock()\\n except:\\n pass\\n #print \\\"No lock, actually.\\\" \\n dispatcher.send('SLAVE_PARSE_QUEUE', self, '')\",\n \"def signalReceived (self, signal): \\n raise NotImplementedError(\\\"Lack of signalReceived method\\\")\",\n \"def signal_oi(self):\\n pass\",\n \"def _signal_handler(*args):\\n self._user_exit = True\",\n \"def abort_ber_meas(self):\\r\\r\\n loggerCmw = logging.getLogger('abort_ber_meas')\\r\\r\\n self.write('ABORt:WCDMa:SIGN:BER')\\r\\r\\n loggerCmw.info(\\\"Aborting BER measurements\\\")\\r\\r\\n time.sleep(1)\",\n \"def signal_handler(signal, frame):\\n print(chr(27) + \\\"[2J\\\")\\n sys.exit(0)\",\n \"def signal_handler(sig, frame):\\n sys.exit(0)\",\n \"def timeout(signum, frame):\\n global stopping_timeout\\n print(\\\"Received signal: {!s} frame: {!s}\\\".format(signum, frame))\\n # mutating a mutable object doesn't require changing what the variable name points to\\n # Python2/3 compat (ugly) workaround\\n stopping_timeout[0] = True\",\n \"def handle_sigterm(signum, frame):\\n raise TermException\",\n \"def receive_signal(signal_number, frame):\\n\\n global read_loop\\n\\n print('Received signal: ', signal_number)\\n read_loop = False\",\n \"def abort_signal(self, signal, frame):\\r\\n\\r\\n print \\\"\\\\nMANUAL TERMINATION: Stopping all threads...\\\"\\r\\n self.stop(True)\\r\\n sys.exit(0)\",\n \"def signal(sig, action): # real signature unknown; restored from __doc__\\n pass\",\n \"def siginterrupt(sig, flag): # real signature unknown; restored from __doc__\\n pass\",\n \"def _sigterm_handler(signum: int, _frame: FrameType) -> None:\\n sys.exit('from sigterm handler')\",\n \"def handler(signum, frame, spinner):\\n spinner.fail()\\n spinner.stop()\",\n \"def signal_process( Qin, source, stop_flag, log, pos_ref, FIX_1BIT_ERRORS=False ):\\n\\n\\trow_size = 16 + 112*2 #240 bits\\n\\t\\n\\twhile( not stop_flag.is_set() ):\\n\\t\\tcurr_time = time.strftime('%d/%b/%Y %H:%M:%S', time.localtime())\\n\\t\\t\\n\\t\\t# Get streaming chunk from sdr_read thread\\n\\t\\ty = Qin.get();\\n\\t\\t\\t\\n\\t\\tpacket_diff = len(packets)\\n\\t\\tidx_preamble, noise_floor = asp.detectPreamble(y)\\t\\t\\n\\t\\tfor n in idx_preamble:\\n\\t\\t\\tsignal = abs(y[int(n) : int(n) + row_size])\\n\\t\\t\\tmsg = asp.decode_ADSB( signal, FIX_1BIT_ERRORS )\\n\\t\\t\\tif msg != None:\\n\\t\\t\\t\\tsnr = asp.SNR(signal, noise_floor)\\n\\t\\t\\t\\tpkt = ao.Packet(msg, time.time(), snr)\\n\\t\\t\\t\\tpackets.append( pkt )\\n\\t\\t\\t\\tprint( '!' , end='', flush=True )\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif len(packets) > PACKET_BUFF_SIZE:\\n\\t\\t\\t\\t\\tpackets.pop(0)\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif log != None:\\n\\t\\t\\t\\t\\ttry:\\n\\t\\t\\t\\t\\t\\twith open(log, 'a') as f:\\n\\t\\t\\t\\t\\t\\t\\tf.write(f\\\"[{curr_time}] {msg}\\\\n\\\")\\n\\t\\t\\t\\t\\texcept:\\n\\t\\t\\t\\t\\t\\tprint(f\\\"Error writing to {log}!\\\")\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif pkt.icao in planes:\\n\\t\\t\\t\\t\\tplanes[pkt.icao].process_packet( pkt )\\n\\t\\t\\t\\telif pkt.icao != None:\\n\\t\\t\\t\\t\\tplanes[pkt.icao] = ao.Plane( pkt, pos_ref )\\n\\t\\t\\n\\t\\tif packet_diff == len(packets):\\n\\t\\t\\t# packets.append(f\\\"[{curr_time}] None received...\\\")\\n\\t\\t\\tprint( '.' , end='', flush=True )\\n\\t\\t\\n\\t\\t# Remove excess objects\\n\\t\\tto_delete = []\\n\\t\\tfor p in planes.keys():\\n\\t\\t\\tif (time.time() - planes[p].last_update) >= TTL:\\n\\t\\t\\t\\tto_delete.append(p)\\n\\t\\t\\n\\t\\tfor p in to_delete:\\n\\t\\t\\tplanes.pop(p)\\n\\t\\t\\n\\t\\tQin.queue.clear()\",\n \"def signal(self):\\n self.mainloop().signal()\",\n \"def signal_handler(self, signal, frame):\\n logger.info('CTRL+C pressed')\\n self.trigger_stop()\",\n \"def _termination_handler(self, signum, frame):\\n print '[i] Shutting down...'\\n self.sensor.close()\\n sys.exit(1)\",\n \"def process_signal(self, src, tag, value):\\n pass\",\n \"def __streamHandler__(signum, frame):\\n raise Exception(\\\"end of time\\\")\",\n \"def sigint_handler(signal, frame):\\n rclpy.shutdown()\\n if prev_sigint_handler is not None:\\n prev_sigint_handler(signal)\",\n \"def shutdownSignal(signum, frame):\\n LOG.warning(\\\"shutting down, got signal %d\\\", signum)\\n shutdown()\",\n \"def port_buffer_drop():\",\n \"def signal_handler(signum, frame):\\n main.CLOSE = True\",\n \"def gracefulexit(signalnumber, frame):\\n\\t\\n\\tsys.exit(0) # resources will be closed on their corresponding finally blocks\",\n \"def signal_handler(signum, frame):\\n monitor.stop()\\n sys.exit(0)\",\n \"def found_terminator(self):\\n self.signal_filter.send((self, \\\"\\\".join(self.buffer)))\\n del(self.buffer[:])\",\n \"def signal_handler(signal_number, stack_frame):\\n if signal_number in [signal.SIGTERM, signal.SIGINT]:\\n terminate_surveillance()\",\n \"def signal_handler(self, signal, frame):\\n logger.error(\\\"Received Signal to Terminate\\\")\\n self.set_lcd_brightness(self.DIM_SHUT)\\n ui.runui = False\\n # sys.exit(0)\",\n \"def termHandler(self, signum, frame):\\n print(\\\"SIGTERM caught and ignored\\\", flush=True)\",\n \"def _fill_buffer(self, in_data, *args, **kwargs):\\r\\n self._buff.put(in_data)\\r\\n return None, pyaudio.paContinue\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def stop_emission(self, detailed_signal): # reliably restored by inspect\\n pass\",\n \"def signal_handler(self, signum):\\n raise Exception(\\\"Caught signal {0}\\\".format(signum))\",\n \"def _sigint(self, signal, frame):\\n self.disconnect = True\\n if self.cardinal:\\n self.cardinal.quit('Received SIGINT.')\",\n \"def abort() -> NoReturn:\\n raise AbortSignal\",\n \"def default_handler(signum: int, frame: Any, spinner: Yaspin) -> None: # pylint: disable=unused-argument\\n spinner.fail()\\n spinner.stop()\\n sys.exit(0)\",\n \"def exit_from_signals(self, signal_num, frame):\\n detail = 'signal {}'.format(signal_num)\\n self.exit(detail)\",\n \"def sendSignal (self, signal) :\\n\\n data = streamModule.WriteBuffer()\\n\\n data.writeStruct('B', signal)\\n\\n return self.sendCommand(\\\"CMD_IN_DO_KILL\\\", data.getvalue()).addCallback(self._sendSignal_result)\",\n \"def SendEndScanSignal(self):\\n pass\",\n \"def signal_handler(self, signal, frame):\\r\\n print 'You pressed Ctrl+C!'\\r\\n sys.exit(0)\",\n \"def fit(self, signal):\\n self.signal = signal\",\n \"def signal_rsi(self):\\n pass\",\n \"def _HandleStopSignal(self, sig, frame):\\n del frame # Unused.\\n logging.info('Received signal %d', sig)\\n if self.stopping:\\n reactor.callLater(3, reactor.stop)\\n return\\n\\n logging.info('Stop umpired...')\\n self.Stop()\",\n \"def send_blocking_signal(self, compression=True):\\n while not self._stop_receive.is_set():\\n if len(self._send_queue) > 0:\\n super(MastermindClientUDP, self).send(JSONSerializer.serialize(self._send_queue.pop()), compression)\\n else:\\n super(MastermindClientUDP, self).send(JSONSerializer.serialize(DummyEvent()), compression)\\n time.sleep(1)\",\n \"def _fill_buffer(self, in_data, *args, **kwargs):\\n self._buff.put(in_data)\\n return None, pyaudio.paContinue\",\n \"def sig_exit_gracefully(cursignal, frame):\\n print(\\\"Exiting in a Graceful way sig=\\\", cursignal, frame)\\n traceback.print_exc(file=sys.stdout)\\n #for c in mac_targets.values():\\n # try:\\n # c.set_var(0)\\n # except Exception, x:\\n # print \\\"Exception:\\\", x\\n sys.stdout.flush()\\n sys.stderr.flush()\\n sys.exit(0)\",\n \"def _exit_gracefully(self, signum, frame):\\n self.log.info(\\\"Exiting gracefully upon receiving signal %s\\\", signum)\\n self.log.debug(\\\"Current Stacktrace is: %s\\\", \\\"\\\\n\\\".join(map(str, inspect.stack())))\\n self.terminate()\\n self.end()\\n self.log.debug(\\\"Finished terminating DAG processors.\\\")\\n sys.exit(os.EX_OK)\",\n \"def signal_qual(self):\\n sig = None\\n while sig is None:\\n sig = self.acquire_signal_quality()\\n time.sleep(0.5)\\n return sig\",\n \"def _signal_handler(signalnum: int, _: Any) -> None:\\n logger.info('Received signal: {0}', signal.Signals(signalnum).name)\\n # safely close video stream & writer\\n stream.stop()\\n writer.close()\\n sys.exit(0)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.71383697","0.6638584","0.66365296","0.65838414","0.65606594","0.651072","0.6385658","0.633539","0.6274212","0.62507004","0.61414415","0.6116271","0.6104604","0.60822886","0.60652584","0.60652584","0.60072625","0.59255743","0.5915507","0.58945","0.5891752","0.5827557","0.5786341","0.57825404","0.57784635","0.57713944","0.5731047","0.5704328","0.5700055","0.5700055","0.5684294","0.5684245","0.5684245","0.5684245","0.5681513","0.5659023","0.5654541","0.5651016","0.56509113","0.562946","0.56250256","0.56242186","0.5609461","0.56011003","0.55619043","0.55517656","0.55393755","0.5537945","0.55302936","0.55160606","0.5499553","0.549303","0.5486107","0.5480169","0.5473693","0.54673797","0.5451099","0.54506856","0.5442912","0.54371536","0.5432264","0.54267126","0.5422862","0.53968","0.53944856","0.53928995","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5381414","0.5372399","0.5369964","0.536529","0.53566074","0.5349784","0.5349107","0.534326","0.5321784","0.53179324","0.5317548","0.5309512","0.5308308","0.5278951","0.5267607","0.52655506","0.52564657","0.5248345"],"string":"[\n \"0.71383697\",\n \"0.6638584\",\n \"0.66365296\",\n \"0.65838414\",\n \"0.65606594\",\n \"0.651072\",\n \"0.6385658\",\n \"0.633539\",\n \"0.6274212\",\n \"0.62507004\",\n \"0.61414415\",\n \"0.6116271\",\n \"0.6104604\",\n \"0.60822886\",\n \"0.60652584\",\n \"0.60652584\",\n \"0.60072625\",\n \"0.59255743\",\n \"0.5915507\",\n \"0.58945\",\n \"0.5891752\",\n \"0.5827557\",\n \"0.5786341\",\n \"0.57825404\",\n \"0.57784635\",\n \"0.57713944\",\n \"0.5731047\",\n \"0.5704328\",\n \"0.5700055\",\n \"0.5700055\",\n \"0.5684294\",\n \"0.5684245\",\n \"0.5684245\",\n \"0.5684245\",\n \"0.5681513\",\n \"0.5659023\",\n \"0.5654541\",\n \"0.5651016\",\n \"0.56509113\",\n \"0.562946\",\n \"0.56250256\",\n \"0.56242186\",\n \"0.5609461\",\n \"0.56011003\",\n \"0.55619043\",\n \"0.55517656\",\n \"0.55393755\",\n \"0.5537945\",\n \"0.55302936\",\n \"0.55160606\",\n \"0.5499553\",\n \"0.549303\",\n \"0.5486107\",\n \"0.5480169\",\n \"0.5473693\",\n \"0.54673797\",\n \"0.5451099\",\n \"0.54506856\",\n \"0.5442912\",\n \"0.54371536\",\n \"0.5432264\",\n \"0.54267126\",\n \"0.5422862\",\n \"0.53968\",\n \"0.53944856\",\n \"0.53928995\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5381414\",\n \"0.5372399\",\n \"0.5369964\",\n \"0.536529\",\n \"0.53566074\",\n \"0.5349784\",\n \"0.5349107\",\n \"0.534326\",\n \"0.5321784\",\n \"0.53179324\",\n \"0.5317548\",\n \"0.5309512\",\n \"0.5308308\",\n \"0.5278951\",\n \"0.5267607\",\n \"0.52655506\",\n \"0.52564657\",\n \"0.5248345\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6557572"},"document_rank":{"kind":"string","value":"5"}}},{"rowIdx":81778,"cells":{"query":{"kind":"string","value":"Get a new picture to put in the buffer"},"document":{"kind":"string","value":"def get_new_item(self, index):\n if index not in self.d_buffer.keys():\n if 0 <= index < self.n_im:\n return self.stack[index]\n # Does not raise an error in case of wrong index for easier\n # handling upstream\n else:\n return None\n else:\n return self.d_buffer[index]"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def take_pic(self):\n \n try:\n if os.path.isfile(self.pics_path):\n os.remove(self.pics_path)\n self.camera.capture(self.pics_path, use_video_port=True)\n except:\n print(\"Error when recording image\")\n exit()\n \n try:\n image = open(self.pics_path, 'rb')\n img_bytes = image.read()\n size = len(img_bytes)\n self.img_buffer.append((size, img_bytes))\n image.close()\n except:\n print(\"Error when opening image\")\n exit()","def get_image():\n\n # Access the global variable and activate the saving for the last camera's\n # frame\n global _save_image\n _save_image = True","def get_new_image(self):\n return self.vid_mem_reader.get_latest_image()[0]","def get_new_image(self):\n img = self.vid_mem_reader.get_latest_image()\n if not img: \n return None\n img = img[0]\n return convert_16to8(img)","def getimage(self):","def grab_image(self):\n _, camera_image = self.camera.read()\n with self.lock:\n self.image = camera_image","def getPNGBuffer():\n buf, n = dislin.rbfpng(0)\n buf, n = dislin.rbfpng(n)\n return buf","def get_latest_valid_picture(self):\n return self.buffer[self.buffer_index]","def _buffer_vision(self):\n\n # start with no new data\n self.new_frame = False\n\n # run forever, trying to grab the latest image\n if (self.vision_running):\n # generate a temporary file, gets deleted after usage automatically\n #self.file = tempfile.NamedTemporaryFile(dir=self.imagePath)\n self.file = join(self.imagePath, \"visionStream.jpg\")\n #self.file = tempfile.SpooledTemporaryFile(max_size=32768)\n # save the current picture from the stream\n self.player.video_take_snapshot(0, self.file, 0, 0)\n # read the picture into opencv\n img = cv2.imread(self.file)\n\n # sometimes cv2 returns a None object so skip putting those in the array\n if (img is not None):\n # got a new image, save it to the buffer directly\n self.buffer_index += 1\n self.buffer_index %= self.buffer_size\n #print video_frame\n self.buffer[self.buffer_index] = img\n self.new_frame = True","def get_image(self):\n self.flush_buffer()\n _, frame = self.cam.read()\n shift_frame = self.perspective_shift(frame)\n #shift_frame = None\n return frame, shift_frame","def get_image(self):\n self.drawer.flush()\n return self.img","def img_cb(self, image):\n self.last_img = image\n self.is_new_img = True","def new_image(x, y, out, data):\n img = Image.new('RGB', (x, y))\n img.putdata(data)\n img.save(out)","def get_picture(self, name=None, use_timestamp=True):\n self._get_filepath(name, use_timestamp)\n self._initialize()\n LOG.info(\"Taking picture: %s\" % self.fname)\n self.cam.capture(self.fname)\n self.close()","def grabRawFrame(self):\r\n \r\n self.surface = self.capture.get_image(self.surface)\r\n width, height = self.surface.get_size()\r\n return pygame.image.tostring(self.surface, 'RGB'), width, height, 1","def getImage(cam):\n\n return cam.getImage()","def get_image(self, image):\n self.original_image = image\n self.prepare_images()","def newimage(self, infile):\n return _image.image_newimage(self, infile)","def image(self, where):\n cook = cookie()\n I = Image(cook, self)\n self.call('image', cook, where)\n print(\"IMAGE\", where)\n return I","def take_picture(self):\n self.drone.take_picture()","def take_picture(self):\n self.drone.take_picture()","def __next__(self):\n while True:\n self.stream_bytes += self.stream_conn.read(1024)\n first = bytearray(self.stream_bytes).find(b'\\xff\\xd8')\n last = bytearray(self.stream_bytes).find(b'\\xff\\xd9')\n if first != -1 and last != -1:\n jpg = self.stream_bytes[first:last + 2]\n self.stream_bytes = self.stream_bytes[last + 2:]\n image = cv2.imdecode(np.fromstring(jpg, dtype=np.uint8), 0)\n self.total_frame += 1\n return image","def NextFrame(self, event):\n buffer = self.GetDataBuffer()\n if buffer is not None:\n # Update bitmap widget with new image frame:\n self.bitmap.CopyFromBuffer(buffer)\n # Refresh panel to draw image into bitmap:\n self.Refresh()\n pass","def get_image(self, frame):\n msec = frame * config.MS_PER_FRAME\n frame = msec // 250\n return self.frames[frame % self.num_frames]","def image_cb(self, msg):\n self.has_image = True\n self.camera_image = msg","def get_image(self, frame):\n rect = pygame.Rect(0, 0, self.width, self.height)\n msec = frame * config.MS_PER_FRAME\n frame = msec // 100\n rect.y = self.height - (frame % self.height)\n return self.double.subsurface(rect)","async def grab(self):\r\n # TODO probe the system for optimal size\r\n await self.configure_acquisition(100, continuous=True)\r\n\r\n self.start_acquisition()\r\n with trio.CancelScope():\r\n while True:\r\n yield await self.get_image(mode=BufferRetrieveMode.Latest, copy=False)\r\n self.stop_acquisition()\r\n\r\n await self.unconfigure_acquisition()","def getPic(self):\n if self.sync==False:\n self._drawOnCanvas()\n return self.canvas","def snapshot(self, components=4):\n fbo = self.fbo\n data = fbo.read(components=3)\n from PIL import Image\n return Image.frombytes('RGB', fbo.size, data).transpose(Image.FLIP_TOP_BOTTOM)","def CopyToBuffer(*args, **kwargs):\n return _gdi_.Bitmap_CopyToBuffer(*args, **kwargs)","def update_image(self):\n self.image = Image.fromarray(self.img)","def camera_cb(self, msg):\n #rospy.loginfo(\"Received new image\")\n\n try:\n image = self.bridge.imgmsg_to_cv2(msg, \"bgr8\")\n except CvBridgeError as e:\n rospy.logerr(e)\n return\n\n self.image = cv2.flip(image, -1)","def newImage(self, new_image):\n if not self.mfitter.isInitialized():\n self.mfitter.initializeC(new_image)\n self.mfitter.newImage(new_image)","def save_to_buffer(self) -> io.BytesIO:\n image = get_screenshot_as_png(self._layout)\n buffer = io.BytesIO()\n image.save(buffer, \"png\")\n return buffer","def get_image(self) -> Image.Image:\n raw_buffer_data = self.get_raw_frame_buffer_object_data()\n image = Image.frombytes(\n \"RGBA\",\n self.get_pixel_shape(),\n raw_buffer_data,\n \"raw\",\n \"RGBA\",\n 0,\n -1,\n )\n return image","def test_handle_new_picture():\n import os\n from .views.default import handle_new_picture\n here = os.path.abspath(os.path.dirname(__file__))\n path = os.path.join(here, 'scripts/img_questions/how.jpg')\n with open(path, 'rb') as ouput_file:\n new_picture = handle_new_picture(\"name\", ouput_file)\n assert isinstance(new_picture, bytes)","def get_current_pic(self):\n # Change the picture\n if clock() > self.next_frame:\n if self.exploding:\n if self.frame_num < self.num_of_explosion_frames:\n self.frame_num += 1\n else:\n self.away = True\n else:\n # Chose animation direction by the asteroid's horizontal direction\n self.frame_num += int(copysign(1, self.speed[0]+self.acceleration[0]))\n if self.frame_num >= self.num_of_images:\n self.frame_num = 0\n elif self.frame_num < 0:\n self.frame_num = self.num_of_images - 1\n self.next_frame = clock() + self.frame_time\n return self.current_image_set[self.frame_num]","def get_image(self):\n glReadBuffer(GL_FRONT)\n glReadPixels(0, 0, self.__width, self.__height, GL_RGBA, GL_FLOAT,\n self.__output_image)\n return self.__output_image","def acquire_image():\n import Image\n w,h = image_size()\n image = Image.new('RGB',(w,h))\n global image_data # for debugging\n image_data = eval(subprocess(\"print repr(camera_acquire_image().tostring())\"))\n log(\"acquire_image: got %d bytes of image data from subprocess\" % len(image_data))\n if len(image_data) != w*h*3:\n log(\"acquire_image: expecting %d, got %d bytes of image data\" %\n (w*h*3,len(image_data)))\n if len(image_data) == w*h*3: image.fromstring(image_data)\n else: log(\"acquire_image: image data corrupted, substituting blank image\")\n return image","def _image(self):\n print(\"imaging\")\n self.images.append(self.device_control.image())\n yield","def image_cb(self, msg): # incoming image\n self.has_image = True\n self.camera_image = msg","def figure_buffer(self, fig, dpi=180):\n buf = io.BytesIO()\n fig.savefig(buf, format=\"png\", dpi=dpi)\n buf.seek(0)\n img_arr = np.frombuffer(buf.getvalue(), dtype=np.uint8)\n buf.close()\n img = cv2.imdecode(img_arr, 1)\n img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n return img","def GetImageMem(self):\r\n CALL('GetImageMem',self,byref(self.image))","def next(self):\n if self.currentframe < (self.nframes - 1) and self.nframes > 1:\n return self.getframe(self.currentframe + 1)\n else:\n newobj = pixiimage()\n newobj.read(next_filename(\n self.sequencefilename))\n return newobj","def grabFrame(self):\r\n \r\n data, w, h, orientation = self.grabRawFrame()\r\n return Image.fromstring(\"RGB\", (w, h), data, \"raw\", \"BGR\", 0, orientation)","def newAvatarImage(self, imgPath, imgName): \n img = ocempgui.draw.Image.load_image(imgPath)\n if not self.images[imgName]: \n imgOcemp = guiobjects.OcempImageMapTransparent(img)\n imgOcemp.topleft = 528, 114\n self.window.add_child(imgOcemp)\n self.images[imgName] = imgOcemp\n else:\n self.images[imgName].picture = img","def image_cb(self, msg):\n self.has_image = True\n self.camera_image = msg\n self.get_light_state()","def make_image(self, mode=\"L\") -> Image:\r\n return Image.fromarray(self.fb, mode=\"L\")","def get_next_image(self):\n raise NotImplementedError","def OnNewImage(self, event):\r\n #print sys._getframe().f_code.co_name\r\n\r\n self.eventLock = event.eventLock\r\n\r\n if not self.pause:\r\n self.UpdateImage(event.img)\r\n self.ReleaseEventLock()\r\n if event.oldImageLock:\r\n if event.oldImageLock.locked():\r\n event.oldImageLock.release()","def imgCopy(img):\n return sitk.Image(img)","def _BitmapFromBuffer(*args, **kwargs):\n return _gdi_._BitmapFromBuffer(*args, **kwargs)","def get_image():\n\n url = 'http://skyview.gsfc.nasa.gov/cgi-bin/images'\n params = dict(Position='%s,%s' % (source['ra'], source['dec']),\n Survey=source['survey'].val,\n Return='GIF')\n response = requests.get(url, params=params, stream=True)\n with open(files['image.gif'].rel, 'wb') as out_file:\n shutil.copyfileobj(response.raw, out_file)","def raw_image_callback(self, msg):\n if self.pictures_to_take and not self.detection_to_receive:\n self.pictures_to_take -= 1\n # so let's analyse it here and then delete the subscription\n rows = msg.height\n step = msg.step\n cols = msg.width\n dim = int(step / cols)\n pixels = msg.data # of size (steps, nrows)\n # save the image (later we will need to analyse it)\n vision_utils.save_picture(pixels, rows, cols, dim, self.name, FOLDER)","def work_on_the_picture(self) -> None:\n self.folder_create(self.folder_config)\n value_image_used = os.path.join(self.folder_config, entrance_bot_img_name)\n if os.path.exists(value_image_used) and os.path.isfile(value_image_used):\n return value_image_used\n a = TelegramManager()\n try:\n value_img = self.produce_request(entrance_bot_img_link)\n if value_img.status_code == 200:\n with open(value_image_used, 'wb') as new_picture:\n for chunk in value_img:\n new_picture.write(chunk)\n return value_image_used\n a.proceed_message_values('Unfortunatelly, your link to the image is not working.')\n except Exception as e:\n a.proceed_message_values(f'We faced problem with the getting requests. Mistake: {e}')\n return ''","def copy(img):\n\treturn img.copy()","def camera_acquire_image():\n from time import time\n from PIL import Image # Python Imaging Library\n \n camera = GigE_camera(parameter(\"camera.IP_addr\"),use_multicast=use_multicast)\n camera.last_timestamp = 0\n\n camera.start() \n t = time()\n while not camera.has_image or camera.timestamp == 0:\n if time()-t > 2.0 and not \"started\" in camera.state:\n log (\"camera_acquire_image: image unreadable (%s)\" % camera.state); break\n if time()-t > 5.0:\n log (\"camera_acquire_image: image acquistion timed out (%s)\" % camera.state); break\n sleep(0.1)\n\n camera.stop()\n\n debug(\"get_image: read image with %dx%d pixels, %d bytes\" %\n (camera.width,camera.height,len(camera.rgb_data)))\n image = Image.new('RGB',(camera.width,camera.height))\n image.fromstring(camera.rgb_data)\n image = rotated_image(image)\n return image","def _save_buffer(self):\n img_data = renderer.fbuffer.read(mode='color', alpha=False)\n img = Image.fromarray(img_data)\n img.save(self._save_fname)\n self._save_flag = False","def image_cb(self, msg):\n self.has_image = True\n self.camera_image_msg = msg","def get_tkimage(self):\n self.drawer.flush()\n return PIL.ImageTk.PhotoImage(self.img)","def getImage(self, filename, size=(1920, 1080)):\n post_name.put(filename)\n Proxy = serve.JSProxy(self.send, \"window.viewer.getImage\")\n return Proxy(size[0], size[1], \"mixer.html\")","def update_img(self):\n img_old = self.img\n #Ensure at least one image has been captured\n attempts = 0\n while img_old == None:\n print(\"Wating to capture first image...\")\n time.sleep(1)\n img_old = self.img\n attempts = attempts + 1\n if attempts == 10:\n raise Exception('No images captured after 10 attempts, aborting.')\n img_new = img_old\n #wait until new image is captured\n print('Waiting for new image...')\n while np.all(img_old == img_new):\n img_new = self.img\n print('New image acquired.')\n \n return img_new","def __get_img(self):\n # Read camera image\n while True:\n # Wait for prediction\n if not self.__predict_start:\n continue\n\n # Get current frame and\n # check for success\n success, self.__img = self.__cap.read()\n if not success:\n continue\n\n self.__img = cv2.resize(self.__img, (self.__size[0], self.__size[1]))","def retrieve(self, clone: bool = False, *args, **kwargs) -> np.ndarray:\n if not self._frame_in_buffer:\n _, img = super(Camera, self).retrieve(*args, **kwargs)\n self._frame_buffer = cv.remap(img, *self.undistort_rectify_map, cv.INTER_LINEAR)\n self._frame_in_buffer = True\n\n if clone:\n return self._frame_buffer.copy()\n\n return self._frame_buffer","def screenshot_base(self, previous):\n\tif self.internal.device.google_experience or not getattr(\n\t\t\tself.internal.settings, 'LV_USE_FRAMEBUFFER_COMMAND', False):\n\t\treturn previous(self)\n\n\treturn BytesIO(binascii.a2b_hex(''.join(\n\t\t\tself.internal.transport.view_server_query('FRAMEBUFFER\\n',\n\t\t\t\t\t2*self.internal.settings.INTERNAL_VIEW_SERVER_QUERY_DEFAULT_TIMEOUT))))","def read(self):\n\n # Obtém frame da câmera.\n status , frame = super().read()\n\n if not status: return\n\n # Obtém a imagem.\n frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n frame = Image.fromarray(frame)\n \n # Se a opção de efeito espelho estiver ativa, a imagem será invertida.\n if self.__mirror:\n frame = frame.transpose(Image.FLIP_LEFT_RIGHT)\n \n return ImageTk.PhotoImage(frame) , frame.size","def capture_image(self):\n ext = self.image_save_type.lower()\n\n if self.calibrating:\n print('calibrating')\n\n if ext == 'fits':\n self.save_fits()\n self._image_counter += 1\n else:\n img = self.original_image\n path = os.path.join(self.home, 'data')\n name = \"camtrak_frame_{}.png\".format(self._image_counter) \n fn = os.path.join(path, name)\n cv2.imwrite(fn, img)\n\n QtWidgets.QApplication.beep()\n self.statusBar().showMessage(f'Saved image to {fn}')\n self._image_counter += 1","def get_image(self):\n return self.camera.getImage()","async def snap(self, out=None):\r\n # NOTE ring buffer requires minimally of 2 frames\r\n await self.configure_acquisition(1)\r\n\r\n self.start_acquisition()\r\n out = await self.get_image(out=out)\r\n self.stop_acquisition()\r\n\r\n await self.unconfigure_acquisition()\r\n\r\n return out","def get_image(url, path):\n r = requests.get(url, stream=True)\n if r.status_code == 200:\n with open(path, 'wb') as f:\n r.raw.decode_content = True\n shutil.copyfileobj(r.raw, f)\n print(\"[>] get\", url, \">>\", path)\n f.close()","def LoadPicture(filename):\n return Bitmap(filename)","def gen(camera):\n \n while True:\n \n \n \n frame = camera.get_frame()\n \n yield (b'--frame\\r\\n'\n b'Content-Type: image/jpeg\\r\\n\\r\\n' + frame + b'\\r\\n')","def read(self):\n with self.lock:\n return self.image","def newimagefromfits(self, *args, **kwargs):\n return _image.image_newimagefromfits(self, *args, **kwargs)","def buffer(self) -> np.ndarray:\n return np.array(self._image_data, copy=False)","def gen(camera):\n #time.sleep(3)\n while True:\n frame = camera.get_frame()\n yield (b'--frame\\r\\n'\n b'Content-Type: image/jpeg\\r\\n\\r\\n' + frame + b'\\r\\n')","def take_snapshot(self, path, file_name):\n pipelie_state = self.player.get_state(1)\n p_state = pipelie_state.state\n if p_state not in (Gst.State.PLAYING, Gst.State.PAUSED):\n print(\"Stream is not ready\")\n else:\n try:\n sink = self.player.get_by_name('sink')\n sample = GstBase.BaseSink.get_last_sample(sink)\n image_buffer = Gst.Sample.get_buffer(sample)\n buffer_map = Gst.Buffer.map(image_buffer, Gst.MapFlags.READ)\n image_binary_data = bytearray(buffer_map.info.data)\n utils.store_image(image_binary_data, path, file_name + \".jpeg\")\n except:\n print(\"Capturing image failed.\")","def take_picture():\n\n #This reads the data from the webcam\n ret, frame = vid.read() \n \n #This writes the image to the unknown directory\n cv2.imwrite('/Users/srikarkarra/Downloads/Important Stuff/Coding/facial_rec/unknown/unknown.jpg', frame)","def convertFrame(self):\r\n try:\r\n height, width = self.currentFrame.shape[:2]\r\n img = QtGui.QImage(self.currentFrame,\r\n width,\r\n height,\r\n QtGui.QImage.Format_RGB888)\r\n img = QtGui.QPixmap.fromImage(img)\r\n self.previousFrame = self.currentFrame\r\n return img\r\n except:\r\n return None","def CopyImageMem(self):\r\n r = CALL(\"CopyImageMem\",self,self.image,self.id,self.data.ctypes.data)\r\n return self.CheckForSuccessError(r)","def get_image(self):\r\n try:\r\n\r\n message = self.communicator.get_dec_message(self.client_socket)\r\n output = StringIO.StringIO(message)\r\n image = pygame.image.load(output)\r\n return image\r\n\r\n except pygame.error:\r\n return None\r\n except socket.error:\r\n self.close_connection()","def get_current_image(self):\n raise NotImplementedError","def take_still(self):\n\n while(1):\n if self.take:\n self.make = False\n img = self.shot\n self.make = True\n break\n return img","def send_picture (infile, dev, counter = None):\n #print(\"sendpicture:\", infile, \"counter=\", counter)\n \n try:\n image = Image.open(infile)\n except IOError as (errno, msg):\n # prepare error pic and send\n wimage = Image.new(\"RGB\",(800,480), \"Red\")\n draw = ImageDraw.Draw(wimage)\n draw.text((2 , 10 ), \"Error\", font=pfont['big'], fill=\"Black\")\n draw.text((10 , 200 ), str(msg) +\":\" , font=pfont['small'], fill=\"black\")\n draw.text((10 , 240 ), infile, font=pfont['small'], fill=\"Black\")\n \n output = StringIO.StringIO()\n wimage.save(output, \"JPEG\", quality=95)\n pic = output.getvalue()\n output.close()\n #vprint(\"len(pic) =\", len(pic), \"chunks of 16384:\",len(pic)/16384.,\"q=\",90)\n write_jpg2frame(dev, pic)\n\n return 2\n\n vprint(\"\\nimage as original is :\",image.format, image.size, image.mode, infile)\n #vprint( time.strftime(\"%d.%m.%Y %H:%M\"))\n \n # convert from Palette mode (e.g GIF) to RGB mode\n if image.mode == \"P\":\n image = image.convert(\"RGB\")\n vprint(\"\\nimage after conversion from P to RGB is :\",image.format, image.size, image.mode, infile)\n \n w = image.size[0]\n h = image.size[1]\n wh = float(w) / float(h)\n if wh < 1 : \n vprint(\"Tall format, adjust\")\n simage = image.resize((int(480. * wh ),480)) \n image = Image.new(\"RGB\",(800,480), \"black\")\n image.paste(simage, (400 - simage.size[0]/2,0))\n \n if image.size != (800,480): \n w = image.size[0]\n h = image.size[1]\n wh = float(w) / float(h)\n \n r = 800./480.\n #vprint(\"image w/h:\", wh, \"(frame 800/480=\",r))\n \n # crop the image to match the aspect ratio of the frame to avoid distortion of the picture\n # unless there is only a less than 5% difference\n if (wh > r * 1.05 or wh < r * 0.95): \n w_crop = w \n h_crop = w_crop / r \n \n if h_crop <= h:\n h_delta_top = int((h - h_crop) / 4)\n h_delta_bottom = int((h - h_crop) * 3 / 4) \n w_delta = int((w - w_crop) / 2)\n image = image.crop((0 + w_delta, 0 + h_delta_top, w - w_delta, h - h_delta_bottom)) \n \n vprint(\"image after cropping: \", image.format, image.size, image.mode)\n else:\n vprint(\"image was NOT cropped\") \n\n # image MUST be resized EXACTLY to 800x480 to fit on the photoframe, \n # otherwise gibberish or nothing appears on frame\n image = image.resize((800,480))\n \n vprint(\"image after resizing: \", image.format, image.size, image.mode)\n\n else:\n vprint(\"image NOT resized and NOT cropped\")\n \n pname = os.path.basename(infile) # current picture name\n pfolder = os.path.dirname(infile).rpartition('/')[2] # current picture folder\n pname_width, pname_height = pfont['small'].getsize(pname) # size of picture name \n #vprint(\"text_width, text_height\",text_width, text_height)\n\n # add text to picture \n draw = ImageDraw.Draw(image)\n draw.text((800 - pname_width - 2, pname_height - 20 ), pname, font=pfont['small'], fill=\"blue\") # pic name\n draw.text((2, pname_height - 20 ), pfolder, font=pfont['small'], fill=\"blue\") # pic directory\n draw.text((380, 305), time.strftime(\"%H:%M\"), font=pfont['time'], fill=\"gold\") # current time\n if counter != None : \n draw.text((30, 20), \"#\"+str(counter + 1), font=pfont['medium'], fill=\"yellow\") # counter\n \n q = 94 \n # one slide could not be transferred with q=95??? at 94, 93 it worked, and also at 96, 97, 98, 99\n # ??? why not at 95\n # pic is 2009-07%20Norwegen/imgp1785-m2.jpg\n limit = 23\n\n nl = \"\\n\" # to make a NewLine in the log file when the first new quality needs to be recalculated\n flag = False\n #f = open('bigfile', 'w')\n\n while True:\n output = StringIO.StringIO()\n try:\n image.save(output, \"JPEG\", quality=q)\n except IOError as errno:\n print \"=======================================IOERROR in Image.save:\", errno\n nimage = image.convert(\"RGB\") \n nimage.save(output, \"JPEG\", quality=q)\n #sys.exit()\n\n pic = output.getvalue()\n output.close()\n\n vprint(\"len(pic) =\", len(pic), \"chunks of 16384:\",len(pic)/16384.,\"q=\",q)\n \n # in some 4000 photos, only 3 required a quality of 95 to stay under 23 chunks of 16384\n # none required a quality of 94 or less\n # 22 required 96\n # 124 required 97\n # ~700 required 98\n # so about 3000 could do with 99 \n # when the limit was 24, it failed with a USBError('Operation timed out',) error after a few pictures!\n # conclusion: use limit of 23, and quality of 95, but still check for len of picture!\n \n # Test for length and write log\n if len(pic) > (16384 * limit) :\n flag = True\n vprint(nl + \" limit=\" + str(limit) + \" (\" + str(16384 * limit) +\"), \" + infile + \", q=\" + str(q) + \", len(pic)=\" + str(len(pic)) + \"\\n\", forceprint = True)\n else:\n if flag:\n vprint(\"OK \" + \"limit=\" + str(limit) + \" (\" + str(16384 * limit) +\"), \" + infile + \", q=\" + str(q) + \", len(pic)=\" + str(len(pic)) + \"\\n\", forceprint = True)\n break\n\n q -= 1\n nl = \"\" # reset new line\n \n write_jpg2frame(dev, pic)\n \n return 0","def capture(self):\n log.info('Image: %d' % self.idx)\n img = cv.imread(self.files[self.idx])\n self.idx = (self.idx + 1) % len(self.files)\n\n img = cv.cvtColor(img, cv.COLOR_BGR2RGB)\n return img","def get_image(self, frame):\n self.surface.fill((0, 0, 0, 0))\n for sprite in self.sprites:\n self.surface.blit(sprite.get_image(frame), (0, 0))\n return self.surface","def convertFrame(self):\n try:\n height,width=self.currentFrame.shape[:2]\n img=QtGui.QImage(self.currentFrame,\n width,\n height,\n QtGui.QImage.Format_RGB888)\n img=QtGui.QPixmap.fromImage(img)\n self.previousFrame = self.currentFrame\n return img\n except:\n return None","def draw(self, frame):\n frame[OFS:OFS+self.image.shape[0], OFS:OFS+self.image.shape[1]] = self.image","def create_full_pic(self):\n self.create_half_pic()\n mirror_update(self.flag)","def get_image(self, size, mode='normal', state='on'):\n raise NotImplementedError","def pic(update, context):\n chars = '01234567890ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghiklmnopqrstuvwxyz'\n length = 5\n\n while True:\n img_code = choices(chars, k=length)\n address = 'https://i.imgur.com/' + \"\".join(img_code) + '.jpg'\n img = Image.open(BytesIO(get(address).content))\n\n if img.size[0] != 161:\n break\n\n update.message.reply_photo(\n photo=address,\n )","def GET(self, url):\n try:\n f = open(url, 'r')\n image = f.read()\n f.close()\n except:\n\n db_module.resave_img(url[5:])\n\n f = open(url, 'r')\n image = f.read()\n f.close()\n\n return image","def getNextImage(self):\n self._images = self._api.updateImageNames()\n \n # Get index from local txt file. \n # This ensures that the image queue does not reset if the Pola restarts.\n try: \n f = open(\"memoryIndex.txt\", 'r')\n self._currentIndex = int((f.read()))\n f.close()\n except: \n self._currentIndex = -1\n \n self._currentIndex = (self._currentIndex + 1) % len(self._images)\n \n f = open(\"memoryIndex.txt\", 'w')\n f.write(str(self._currentIndex))\n f.close()\n \n \n # If there is an internet connection, go online. If not, get the \"no wifi error\"- image queue\n try:\n urllib.request.urlopen('http://torabodin.com/')\n try: \n imageName = self._api.downloadImage(self._currentIndex)\n print(1, imageName)\n self._image= self.loadImage(imageName, True)\n print (self._image)\n \n except: \n self._image = self.getNextImage()\n \n except:\n self._image = self.loadImage(None, False)\n \n \n return self._image","def new_image_callback(self, new_image_msg):\n self.process_new_frame(\n self.cv_bridge.imgmsg_to_cv2(\n new_image_msg,\n desired_encoding=\"bgr8\"\n )\n )","def get_image(self):\n image = Image.new('1', (8, 16))\n draw = ImageDraw.Draw(image)\n for x in xrange(8):\n for y in xrange(16):\n draw.point((x,y),self.get_pixel(x, y))\n return image","async def get_image(self):\n\n # generating\n fixed_latent = torch.randn(1, 512, 1, 1, device=self.device)\n\n with torch.no_grad():\n # passing through\n fake_images = self.model(fixed_latent)\n # saving\n save_image(fake_images, f'models/FaceGAN_dir/faces/fake.jpg')","def draw(self):\n return ImageDraw.Draw(self.buffer)","def nextPicture(self):\n\t\tif self.currentPicture == self.totalPictures-1:\n\t\t\tself.currentPicture = 0\n\t\telse:\n\t\t\tself.currentPicture += 1\n\t\tself.loadImage(self.picPaths[self.currentPicture])","def capture_to_buf(self, selector=None):\n\n images = self.capture(selector)\n result = []\n\n for image in images:\n ba = QByteArray()\n buf = QBuffer(ba)\n buf.open(QIODevice.ReadWrite)\n image.save(buf, 'jpg')\n stream = StringIO(str(buf.buffer()))\n result.append(stream)\n\n return result","def image(self, img):\n # determine our effective width/height, taking rotation into account\n width = self.width\n height = self.height\n if self.rotation in (1, 3):\n width, height = height, width\n\n if isinstance(self.format, (RGB565Format, RGB888Format)) and img.mode != \"RGB\":\n raise ValueError(\"Image must be in mode RGB.\")\n if isinstance(self.format, (MHMSBFormat, MVLSBFormat)) and img.mode != \"1\":\n raise ValueError(\"Image must be in mode 1.\")\n\n imwidth, imheight = img.size\n if imwidth != width or imheight != height:\n raise ValueError(\n f\"Image must be same dimensions as display ({width}x{height}).\"\n )\n # Grab all the pixels from the image, faster than getpixel.\n pixels = img.load()\n # Clear buffer\n for i in range(len(self.buf)): # pylint: disable=consider-using-enumerate\n self.buf[i] = 0\n # Iterate through the pixels\n for x in range(width): # yes this double loop is slow,\n for y in range(height): # but these displays are small!\n if img.mode == \"RGB\":\n self.pixel(x, y, pixels[(x, y)])\n elif pixels[(x, y)]:\n self.pixel(x, y, 1) # only write if pixel is true","def CopyFromBuffer(*args, **kwargs):\n return _gdi_.Bitmap_CopyFromBuffer(*args, **kwargs)"],"string":"[\n \"def take_pic(self):\\n \\n try:\\n if os.path.isfile(self.pics_path):\\n os.remove(self.pics_path)\\n self.camera.capture(self.pics_path, use_video_port=True)\\n except:\\n print(\\\"Error when recording image\\\")\\n exit()\\n \\n try:\\n image = open(self.pics_path, 'rb')\\n img_bytes = image.read()\\n size = len(img_bytes)\\n self.img_buffer.append((size, img_bytes))\\n image.close()\\n except:\\n print(\\\"Error when opening image\\\")\\n exit()\",\n \"def get_image():\\n\\n # Access the global variable and activate the saving for the last camera's\\n # frame\\n global _save_image\\n _save_image = True\",\n \"def get_new_image(self):\\n return self.vid_mem_reader.get_latest_image()[0]\",\n \"def get_new_image(self):\\n img = self.vid_mem_reader.get_latest_image()\\n if not img: \\n return None\\n img = img[0]\\n return convert_16to8(img)\",\n \"def getimage(self):\",\n \"def grab_image(self):\\n _, camera_image = self.camera.read()\\n with self.lock:\\n self.image = camera_image\",\n \"def getPNGBuffer():\\n buf, n = dislin.rbfpng(0)\\n buf, n = dislin.rbfpng(n)\\n return buf\",\n \"def get_latest_valid_picture(self):\\n return self.buffer[self.buffer_index]\",\n \"def _buffer_vision(self):\\n\\n # start with no new data\\n self.new_frame = False\\n\\n # run forever, trying to grab the latest image\\n if (self.vision_running):\\n # generate a temporary file, gets deleted after usage automatically\\n #self.file = tempfile.NamedTemporaryFile(dir=self.imagePath)\\n self.file = join(self.imagePath, \\\"visionStream.jpg\\\")\\n #self.file = tempfile.SpooledTemporaryFile(max_size=32768)\\n # save the current picture from the stream\\n self.player.video_take_snapshot(0, self.file, 0, 0)\\n # read the picture into opencv\\n img = cv2.imread(self.file)\\n\\n # sometimes cv2 returns a None object so skip putting those in the array\\n if (img is not None):\\n # got a new image, save it to the buffer directly\\n self.buffer_index += 1\\n self.buffer_index %= self.buffer_size\\n #print video_frame\\n self.buffer[self.buffer_index] = img\\n self.new_frame = True\",\n \"def get_image(self):\\n self.flush_buffer()\\n _, frame = self.cam.read()\\n shift_frame = self.perspective_shift(frame)\\n #shift_frame = None\\n return frame, shift_frame\",\n \"def get_image(self):\\n self.drawer.flush()\\n return self.img\",\n \"def img_cb(self, image):\\n self.last_img = image\\n self.is_new_img = True\",\n \"def new_image(x, y, out, data):\\n img = Image.new('RGB', (x, y))\\n img.putdata(data)\\n img.save(out)\",\n \"def get_picture(self, name=None, use_timestamp=True):\\n self._get_filepath(name, use_timestamp)\\n self._initialize()\\n LOG.info(\\\"Taking picture: %s\\\" % self.fname)\\n self.cam.capture(self.fname)\\n self.close()\",\n \"def grabRawFrame(self):\\r\\n \\r\\n self.surface = self.capture.get_image(self.surface)\\r\\n width, height = self.surface.get_size()\\r\\n return pygame.image.tostring(self.surface, 'RGB'), width, height, 1\",\n \"def getImage(cam):\\n\\n return cam.getImage()\",\n \"def get_image(self, image):\\n self.original_image = image\\n self.prepare_images()\",\n \"def newimage(self, infile):\\n return _image.image_newimage(self, infile)\",\n \"def image(self, where):\\n cook = cookie()\\n I = Image(cook, self)\\n self.call('image', cook, where)\\n print(\\\"IMAGE\\\", where)\\n return I\",\n \"def take_picture(self):\\n self.drone.take_picture()\",\n \"def take_picture(self):\\n self.drone.take_picture()\",\n \"def __next__(self):\\n while True:\\n self.stream_bytes += self.stream_conn.read(1024)\\n first = bytearray(self.stream_bytes).find(b'\\\\xff\\\\xd8')\\n last = bytearray(self.stream_bytes).find(b'\\\\xff\\\\xd9')\\n if first != -1 and last != -1:\\n jpg = self.stream_bytes[first:last + 2]\\n self.stream_bytes = self.stream_bytes[last + 2:]\\n image = cv2.imdecode(np.fromstring(jpg, dtype=np.uint8), 0)\\n self.total_frame += 1\\n return image\",\n \"def NextFrame(self, event):\\n buffer = self.GetDataBuffer()\\n if buffer is not None:\\n # Update bitmap widget with new image frame:\\n self.bitmap.CopyFromBuffer(buffer)\\n # Refresh panel to draw image into bitmap:\\n self.Refresh()\\n pass\",\n \"def get_image(self, frame):\\n msec = frame * config.MS_PER_FRAME\\n frame = msec // 250\\n return self.frames[frame % self.num_frames]\",\n \"def image_cb(self, msg):\\n self.has_image = True\\n self.camera_image = msg\",\n \"def get_image(self, frame):\\n rect = pygame.Rect(0, 0, self.width, self.height)\\n msec = frame * config.MS_PER_FRAME\\n frame = msec // 100\\n rect.y = self.height - (frame % self.height)\\n return self.double.subsurface(rect)\",\n \"async def grab(self):\\r\\n # TODO probe the system for optimal size\\r\\n await self.configure_acquisition(100, continuous=True)\\r\\n\\r\\n self.start_acquisition()\\r\\n with trio.CancelScope():\\r\\n while True:\\r\\n yield await self.get_image(mode=BufferRetrieveMode.Latest, copy=False)\\r\\n self.stop_acquisition()\\r\\n\\r\\n await self.unconfigure_acquisition()\",\n \"def getPic(self):\\n if self.sync==False:\\n self._drawOnCanvas()\\n return self.canvas\",\n \"def snapshot(self, components=4):\\n fbo = self.fbo\\n data = fbo.read(components=3)\\n from PIL import Image\\n return Image.frombytes('RGB', fbo.size, data).transpose(Image.FLIP_TOP_BOTTOM)\",\n \"def CopyToBuffer(*args, **kwargs):\\n return _gdi_.Bitmap_CopyToBuffer(*args, **kwargs)\",\n \"def update_image(self):\\n self.image = Image.fromarray(self.img)\",\n \"def camera_cb(self, msg):\\n #rospy.loginfo(\\\"Received new image\\\")\\n\\n try:\\n image = self.bridge.imgmsg_to_cv2(msg, \\\"bgr8\\\")\\n except CvBridgeError as e:\\n rospy.logerr(e)\\n return\\n\\n self.image = cv2.flip(image, -1)\",\n \"def newImage(self, new_image):\\n if not self.mfitter.isInitialized():\\n self.mfitter.initializeC(new_image)\\n self.mfitter.newImage(new_image)\",\n \"def save_to_buffer(self) -> io.BytesIO:\\n image = get_screenshot_as_png(self._layout)\\n buffer = io.BytesIO()\\n image.save(buffer, \\\"png\\\")\\n return buffer\",\n \"def get_image(self) -> Image.Image:\\n raw_buffer_data = self.get_raw_frame_buffer_object_data()\\n image = Image.frombytes(\\n \\\"RGBA\\\",\\n self.get_pixel_shape(),\\n raw_buffer_data,\\n \\\"raw\\\",\\n \\\"RGBA\\\",\\n 0,\\n -1,\\n )\\n return image\",\n \"def test_handle_new_picture():\\n import os\\n from .views.default import handle_new_picture\\n here = os.path.abspath(os.path.dirname(__file__))\\n path = os.path.join(here, 'scripts/img_questions/how.jpg')\\n with open(path, 'rb') as ouput_file:\\n new_picture = handle_new_picture(\\\"name\\\", ouput_file)\\n assert isinstance(new_picture, bytes)\",\n \"def get_current_pic(self):\\n # Change the picture\\n if clock() > self.next_frame:\\n if self.exploding:\\n if self.frame_num < self.num_of_explosion_frames:\\n self.frame_num += 1\\n else:\\n self.away = True\\n else:\\n # Chose animation direction by the asteroid's horizontal direction\\n self.frame_num += int(copysign(1, self.speed[0]+self.acceleration[0]))\\n if self.frame_num >= self.num_of_images:\\n self.frame_num = 0\\n elif self.frame_num < 0:\\n self.frame_num = self.num_of_images - 1\\n self.next_frame = clock() + self.frame_time\\n return self.current_image_set[self.frame_num]\",\n \"def get_image(self):\\n glReadBuffer(GL_FRONT)\\n glReadPixels(0, 0, self.__width, self.__height, GL_RGBA, GL_FLOAT,\\n self.__output_image)\\n return self.__output_image\",\n \"def acquire_image():\\n import Image\\n w,h = image_size()\\n image = Image.new('RGB',(w,h))\\n global image_data # for debugging\\n image_data = eval(subprocess(\\\"print repr(camera_acquire_image().tostring())\\\"))\\n log(\\\"acquire_image: got %d bytes of image data from subprocess\\\" % len(image_data))\\n if len(image_data) != w*h*3:\\n log(\\\"acquire_image: expecting %d, got %d bytes of image data\\\" %\\n (w*h*3,len(image_data)))\\n if len(image_data) == w*h*3: image.fromstring(image_data)\\n else: log(\\\"acquire_image: image data corrupted, substituting blank image\\\")\\n return image\",\n \"def _image(self):\\n print(\\\"imaging\\\")\\n self.images.append(self.device_control.image())\\n yield\",\n \"def image_cb(self, msg): # incoming image\\n self.has_image = True\\n self.camera_image = msg\",\n \"def figure_buffer(self, fig, dpi=180):\\n buf = io.BytesIO()\\n fig.savefig(buf, format=\\\"png\\\", dpi=dpi)\\n buf.seek(0)\\n img_arr = np.frombuffer(buf.getvalue(), dtype=np.uint8)\\n buf.close()\\n img = cv2.imdecode(img_arr, 1)\\n img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\\n return img\",\n \"def GetImageMem(self):\\r\\n CALL('GetImageMem',self,byref(self.image))\",\n \"def next(self):\\n if self.currentframe < (self.nframes - 1) and self.nframes > 1:\\n return self.getframe(self.currentframe + 1)\\n else:\\n newobj = pixiimage()\\n newobj.read(next_filename(\\n self.sequencefilename))\\n return newobj\",\n \"def grabFrame(self):\\r\\n \\r\\n data, w, h, orientation = self.grabRawFrame()\\r\\n return Image.fromstring(\\\"RGB\\\", (w, h), data, \\\"raw\\\", \\\"BGR\\\", 0, orientation)\",\n \"def newAvatarImage(self, imgPath, imgName): \\n img = ocempgui.draw.Image.load_image(imgPath)\\n if not self.images[imgName]: \\n imgOcemp = guiobjects.OcempImageMapTransparent(img)\\n imgOcemp.topleft = 528, 114\\n self.window.add_child(imgOcemp)\\n self.images[imgName] = imgOcemp\\n else:\\n self.images[imgName].picture = img\",\n \"def image_cb(self, msg):\\n self.has_image = True\\n self.camera_image = msg\\n self.get_light_state()\",\n \"def make_image(self, mode=\\\"L\\\") -> Image:\\r\\n return Image.fromarray(self.fb, mode=\\\"L\\\")\",\n \"def get_next_image(self):\\n raise NotImplementedError\",\n \"def OnNewImage(self, event):\\r\\n #print sys._getframe().f_code.co_name\\r\\n\\r\\n self.eventLock = event.eventLock\\r\\n\\r\\n if not self.pause:\\r\\n self.UpdateImage(event.img)\\r\\n self.ReleaseEventLock()\\r\\n if event.oldImageLock:\\r\\n if event.oldImageLock.locked():\\r\\n event.oldImageLock.release()\",\n \"def imgCopy(img):\\n return sitk.Image(img)\",\n \"def _BitmapFromBuffer(*args, **kwargs):\\n return _gdi_._BitmapFromBuffer(*args, **kwargs)\",\n \"def get_image():\\n\\n url = 'http://skyview.gsfc.nasa.gov/cgi-bin/images'\\n params = dict(Position='%s,%s' % (source['ra'], source['dec']),\\n Survey=source['survey'].val,\\n Return='GIF')\\n response = requests.get(url, params=params, stream=True)\\n with open(files['image.gif'].rel, 'wb') as out_file:\\n shutil.copyfileobj(response.raw, out_file)\",\n \"def raw_image_callback(self, msg):\\n if self.pictures_to_take and not self.detection_to_receive:\\n self.pictures_to_take -= 1\\n # so let's analyse it here and then delete the subscription\\n rows = msg.height\\n step = msg.step\\n cols = msg.width\\n dim = int(step / cols)\\n pixels = msg.data # of size (steps, nrows)\\n # save the image (later we will need to analyse it)\\n vision_utils.save_picture(pixels, rows, cols, dim, self.name, FOLDER)\",\n \"def work_on_the_picture(self) -> None:\\n self.folder_create(self.folder_config)\\n value_image_used = os.path.join(self.folder_config, entrance_bot_img_name)\\n if os.path.exists(value_image_used) and os.path.isfile(value_image_used):\\n return value_image_used\\n a = TelegramManager()\\n try:\\n value_img = self.produce_request(entrance_bot_img_link)\\n if value_img.status_code == 200:\\n with open(value_image_used, 'wb') as new_picture:\\n for chunk in value_img:\\n new_picture.write(chunk)\\n return value_image_used\\n a.proceed_message_values('Unfortunatelly, your link to the image is not working.')\\n except Exception as e:\\n a.proceed_message_values(f'We faced problem with the getting requests. Mistake: {e}')\\n return ''\",\n \"def copy(img):\\n\\treturn img.copy()\",\n \"def camera_acquire_image():\\n from time import time\\n from PIL import Image # Python Imaging Library\\n \\n camera = GigE_camera(parameter(\\\"camera.IP_addr\\\"),use_multicast=use_multicast)\\n camera.last_timestamp = 0\\n\\n camera.start() \\n t = time()\\n while not camera.has_image or camera.timestamp == 0:\\n if time()-t > 2.0 and not \\\"started\\\" in camera.state:\\n log (\\\"camera_acquire_image: image unreadable (%s)\\\" % camera.state); break\\n if time()-t > 5.0:\\n log (\\\"camera_acquire_image: image acquistion timed out (%s)\\\" % camera.state); break\\n sleep(0.1)\\n\\n camera.stop()\\n\\n debug(\\\"get_image: read image with %dx%d pixels, %d bytes\\\" %\\n (camera.width,camera.height,len(camera.rgb_data)))\\n image = Image.new('RGB',(camera.width,camera.height))\\n image.fromstring(camera.rgb_data)\\n image = rotated_image(image)\\n return image\",\n \"def _save_buffer(self):\\n img_data = renderer.fbuffer.read(mode='color', alpha=False)\\n img = Image.fromarray(img_data)\\n img.save(self._save_fname)\\n self._save_flag = False\",\n \"def image_cb(self, msg):\\n self.has_image = True\\n self.camera_image_msg = msg\",\n \"def get_tkimage(self):\\n self.drawer.flush()\\n return PIL.ImageTk.PhotoImage(self.img)\",\n \"def getImage(self, filename, size=(1920, 1080)):\\n post_name.put(filename)\\n Proxy = serve.JSProxy(self.send, \\\"window.viewer.getImage\\\")\\n return Proxy(size[0], size[1], \\\"mixer.html\\\")\",\n \"def update_img(self):\\n img_old = self.img\\n #Ensure at least one image has been captured\\n attempts = 0\\n while img_old == None:\\n print(\\\"Wating to capture first image...\\\")\\n time.sleep(1)\\n img_old = self.img\\n attempts = attempts + 1\\n if attempts == 10:\\n raise Exception('No images captured after 10 attempts, aborting.')\\n img_new = img_old\\n #wait until new image is captured\\n print('Waiting for new image...')\\n while np.all(img_old == img_new):\\n img_new = self.img\\n print('New image acquired.')\\n \\n return img_new\",\n \"def __get_img(self):\\n # Read camera image\\n while True:\\n # Wait for prediction\\n if not self.__predict_start:\\n continue\\n\\n # Get current frame and\\n # check for success\\n success, self.__img = self.__cap.read()\\n if not success:\\n continue\\n\\n self.__img = cv2.resize(self.__img, (self.__size[0], self.__size[1]))\",\n \"def retrieve(self, clone: bool = False, *args, **kwargs) -> np.ndarray:\\n if not self._frame_in_buffer:\\n _, img = super(Camera, self).retrieve(*args, **kwargs)\\n self._frame_buffer = cv.remap(img, *self.undistort_rectify_map, cv.INTER_LINEAR)\\n self._frame_in_buffer = True\\n\\n if clone:\\n return self._frame_buffer.copy()\\n\\n return self._frame_buffer\",\n \"def screenshot_base(self, previous):\\n\\tif self.internal.device.google_experience or not getattr(\\n\\t\\t\\tself.internal.settings, 'LV_USE_FRAMEBUFFER_COMMAND', False):\\n\\t\\treturn previous(self)\\n\\n\\treturn BytesIO(binascii.a2b_hex(''.join(\\n\\t\\t\\tself.internal.transport.view_server_query('FRAMEBUFFER\\\\n',\\n\\t\\t\\t\\t\\t2*self.internal.settings.INTERNAL_VIEW_SERVER_QUERY_DEFAULT_TIMEOUT))))\",\n \"def read(self):\\n\\n # Obtém frame da câmera.\\n status , frame = super().read()\\n\\n if not status: return\\n\\n # Obtém a imagem.\\n frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\\n frame = Image.fromarray(frame)\\n \\n # Se a opção de efeito espelho estiver ativa, a imagem será invertida.\\n if self.__mirror:\\n frame = frame.transpose(Image.FLIP_LEFT_RIGHT)\\n \\n return ImageTk.PhotoImage(frame) , frame.size\",\n \"def capture_image(self):\\n ext = self.image_save_type.lower()\\n\\n if self.calibrating:\\n print('calibrating')\\n\\n if ext == 'fits':\\n self.save_fits()\\n self._image_counter += 1\\n else:\\n img = self.original_image\\n path = os.path.join(self.home, 'data')\\n name = \\\"camtrak_frame_{}.png\\\".format(self._image_counter) \\n fn = os.path.join(path, name)\\n cv2.imwrite(fn, img)\\n\\n QtWidgets.QApplication.beep()\\n self.statusBar().showMessage(f'Saved image to {fn}')\\n self._image_counter += 1\",\n \"def get_image(self):\\n return self.camera.getImage()\",\n \"async def snap(self, out=None):\\r\\n # NOTE ring buffer requires minimally of 2 frames\\r\\n await self.configure_acquisition(1)\\r\\n\\r\\n self.start_acquisition()\\r\\n out = await self.get_image(out=out)\\r\\n self.stop_acquisition()\\r\\n\\r\\n await self.unconfigure_acquisition()\\r\\n\\r\\n return out\",\n \"def get_image(url, path):\\n r = requests.get(url, stream=True)\\n if r.status_code == 200:\\n with open(path, 'wb') as f:\\n r.raw.decode_content = True\\n shutil.copyfileobj(r.raw, f)\\n print(\\\"[>] get\\\", url, \\\">>\\\", path)\\n f.close()\",\n \"def LoadPicture(filename):\\n return Bitmap(filename)\",\n \"def gen(camera):\\n \\n while True:\\n \\n \\n \\n frame = camera.get_frame()\\n \\n yield (b'--frame\\\\r\\\\n'\\n b'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' + frame + b'\\\\r\\\\n')\",\n \"def read(self):\\n with self.lock:\\n return self.image\",\n \"def newimagefromfits(self, *args, **kwargs):\\n return _image.image_newimagefromfits(self, *args, **kwargs)\",\n \"def buffer(self) -> np.ndarray:\\n return np.array(self._image_data, copy=False)\",\n \"def gen(camera):\\n #time.sleep(3)\\n while True:\\n frame = camera.get_frame()\\n yield (b'--frame\\\\r\\\\n'\\n b'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' + frame + b'\\\\r\\\\n')\",\n \"def take_snapshot(self, path, file_name):\\n pipelie_state = self.player.get_state(1)\\n p_state = pipelie_state.state\\n if p_state not in (Gst.State.PLAYING, Gst.State.PAUSED):\\n print(\\\"Stream is not ready\\\")\\n else:\\n try:\\n sink = self.player.get_by_name('sink')\\n sample = GstBase.BaseSink.get_last_sample(sink)\\n image_buffer = Gst.Sample.get_buffer(sample)\\n buffer_map = Gst.Buffer.map(image_buffer, Gst.MapFlags.READ)\\n image_binary_data = bytearray(buffer_map.info.data)\\n utils.store_image(image_binary_data, path, file_name + \\\".jpeg\\\")\\n except:\\n print(\\\"Capturing image failed.\\\")\",\n \"def take_picture():\\n\\n #This reads the data from the webcam\\n ret, frame = vid.read() \\n \\n #This writes the image to the unknown directory\\n cv2.imwrite('/Users/srikarkarra/Downloads/Important Stuff/Coding/facial_rec/unknown/unknown.jpg', frame)\",\n \"def convertFrame(self):\\r\\n try:\\r\\n height, width = self.currentFrame.shape[:2]\\r\\n img = QtGui.QImage(self.currentFrame,\\r\\n width,\\r\\n height,\\r\\n QtGui.QImage.Format_RGB888)\\r\\n img = QtGui.QPixmap.fromImage(img)\\r\\n self.previousFrame = self.currentFrame\\r\\n return img\\r\\n except:\\r\\n return None\",\n \"def CopyImageMem(self):\\r\\n r = CALL(\\\"CopyImageMem\\\",self,self.image,self.id,self.data.ctypes.data)\\r\\n return self.CheckForSuccessError(r)\",\n \"def get_image(self):\\r\\n try:\\r\\n\\r\\n message = self.communicator.get_dec_message(self.client_socket)\\r\\n output = StringIO.StringIO(message)\\r\\n image = pygame.image.load(output)\\r\\n return image\\r\\n\\r\\n except pygame.error:\\r\\n return None\\r\\n except socket.error:\\r\\n self.close_connection()\",\n \"def get_current_image(self):\\n raise NotImplementedError\",\n \"def take_still(self):\\n\\n while(1):\\n if self.take:\\n self.make = False\\n img = self.shot\\n self.make = True\\n break\\n return img\",\n \"def send_picture (infile, dev, counter = None):\\n #print(\\\"sendpicture:\\\", infile, \\\"counter=\\\", counter)\\n \\n try:\\n image = Image.open(infile)\\n except IOError as (errno, msg):\\n # prepare error pic and send\\n wimage = Image.new(\\\"RGB\\\",(800,480), \\\"Red\\\")\\n draw = ImageDraw.Draw(wimage)\\n draw.text((2 , 10 ), \\\"Error\\\", font=pfont['big'], fill=\\\"Black\\\")\\n draw.text((10 , 200 ), str(msg) +\\\":\\\" , font=pfont['small'], fill=\\\"black\\\")\\n draw.text((10 , 240 ), infile, font=pfont['small'], fill=\\\"Black\\\")\\n \\n output = StringIO.StringIO()\\n wimage.save(output, \\\"JPEG\\\", quality=95)\\n pic = output.getvalue()\\n output.close()\\n #vprint(\\\"len(pic) =\\\", len(pic), \\\"chunks of 16384:\\\",len(pic)/16384.,\\\"q=\\\",90)\\n write_jpg2frame(dev, pic)\\n\\n return 2\\n\\n vprint(\\\"\\\\nimage as original is :\\\",image.format, image.size, image.mode, infile)\\n #vprint( time.strftime(\\\"%d.%m.%Y %H:%M\\\"))\\n \\n # convert from Palette mode (e.g GIF) to RGB mode\\n if image.mode == \\\"P\\\":\\n image = image.convert(\\\"RGB\\\")\\n vprint(\\\"\\\\nimage after conversion from P to RGB is :\\\",image.format, image.size, image.mode, infile)\\n \\n w = image.size[0]\\n h = image.size[1]\\n wh = float(w) / float(h)\\n if wh < 1 : \\n vprint(\\\"Tall format, adjust\\\")\\n simage = image.resize((int(480. * wh ),480)) \\n image = Image.new(\\\"RGB\\\",(800,480), \\\"black\\\")\\n image.paste(simage, (400 - simage.size[0]/2,0))\\n \\n if image.size != (800,480): \\n w = image.size[0]\\n h = image.size[1]\\n wh = float(w) / float(h)\\n \\n r = 800./480.\\n #vprint(\\\"image w/h:\\\", wh, \\\"(frame 800/480=\\\",r))\\n \\n # crop the image to match the aspect ratio of the frame to avoid distortion of the picture\\n # unless there is only a less than 5% difference\\n if (wh > r * 1.05 or wh < r * 0.95): \\n w_crop = w \\n h_crop = w_crop / r \\n \\n if h_crop <= h:\\n h_delta_top = int((h - h_crop) / 4)\\n h_delta_bottom = int((h - h_crop) * 3 / 4) \\n w_delta = int((w - w_crop) / 2)\\n image = image.crop((0 + w_delta, 0 + h_delta_top, w - w_delta, h - h_delta_bottom)) \\n \\n vprint(\\\"image after cropping: \\\", image.format, image.size, image.mode)\\n else:\\n vprint(\\\"image was NOT cropped\\\") \\n\\n # image MUST be resized EXACTLY to 800x480 to fit on the photoframe, \\n # otherwise gibberish or nothing appears on frame\\n image = image.resize((800,480))\\n \\n vprint(\\\"image after resizing: \\\", image.format, image.size, image.mode)\\n\\n else:\\n vprint(\\\"image NOT resized and NOT cropped\\\")\\n \\n pname = os.path.basename(infile) # current picture name\\n pfolder = os.path.dirname(infile).rpartition('/')[2] # current picture folder\\n pname_width, pname_height = pfont['small'].getsize(pname) # size of picture name \\n #vprint(\\\"text_width, text_height\\\",text_width, text_height)\\n\\n # add text to picture \\n draw = ImageDraw.Draw(image)\\n draw.text((800 - pname_width - 2, pname_height - 20 ), pname, font=pfont['small'], fill=\\\"blue\\\") # pic name\\n draw.text((2, pname_height - 20 ), pfolder, font=pfont['small'], fill=\\\"blue\\\") # pic directory\\n draw.text((380, 305), time.strftime(\\\"%H:%M\\\"), font=pfont['time'], fill=\\\"gold\\\") # current time\\n if counter != None : \\n draw.text((30, 20), \\\"#\\\"+str(counter + 1), font=pfont['medium'], fill=\\\"yellow\\\") # counter\\n \\n q = 94 \\n # one slide could not be transferred with q=95??? at 94, 93 it worked, and also at 96, 97, 98, 99\\n # ??? why not at 95\\n # pic is 2009-07%20Norwegen/imgp1785-m2.jpg\\n limit = 23\\n\\n nl = \\\"\\\\n\\\" # to make a NewLine in the log file when the first new quality needs to be recalculated\\n flag = False\\n #f = open('bigfile', 'w')\\n\\n while True:\\n output = StringIO.StringIO()\\n try:\\n image.save(output, \\\"JPEG\\\", quality=q)\\n except IOError as errno:\\n print \\\"=======================================IOERROR in Image.save:\\\", errno\\n nimage = image.convert(\\\"RGB\\\") \\n nimage.save(output, \\\"JPEG\\\", quality=q)\\n #sys.exit()\\n\\n pic = output.getvalue()\\n output.close()\\n\\n vprint(\\\"len(pic) =\\\", len(pic), \\\"chunks of 16384:\\\",len(pic)/16384.,\\\"q=\\\",q)\\n \\n # in some 4000 photos, only 3 required a quality of 95 to stay under 23 chunks of 16384\\n # none required a quality of 94 or less\\n # 22 required 96\\n # 124 required 97\\n # ~700 required 98\\n # so about 3000 could do with 99 \\n # when the limit was 24, it failed with a USBError('Operation timed out',) error after a few pictures!\\n # conclusion: use limit of 23, and quality of 95, but still check for len of picture!\\n \\n # Test for length and write log\\n if len(pic) > (16384 * limit) :\\n flag = True\\n vprint(nl + \\\" limit=\\\" + str(limit) + \\\" (\\\" + str(16384 * limit) +\\\"), \\\" + infile + \\\", q=\\\" + str(q) + \\\", len(pic)=\\\" + str(len(pic)) + \\\"\\\\n\\\", forceprint = True)\\n else:\\n if flag:\\n vprint(\\\"OK \\\" + \\\"limit=\\\" + str(limit) + \\\" (\\\" + str(16384 * limit) +\\\"), \\\" + infile + \\\", q=\\\" + str(q) + \\\", len(pic)=\\\" + str(len(pic)) + \\\"\\\\n\\\", forceprint = True)\\n break\\n\\n q -= 1\\n nl = \\\"\\\" # reset new line\\n \\n write_jpg2frame(dev, pic)\\n \\n return 0\",\n \"def capture(self):\\n log.info('Image: %d' % self.idx)\\n img = cv.imread(self.files[self.idx])\\n self.idx = (self.idx + 1) % len(self.files)\\n\\n img = cv.cvtColor(img, cv.COLOR_BGR2RGB)\\n return img\",\n \"def get_image(self, frame):\\n self.surface.fill((0, 0, 0, 0))\\n for sprite in self.sprites:\\n self.surface.blit(sprite.get_image(frame), (0, 0))\\n return self.surface\",\n \"def convertFrame(self):\\n try:\\n height,width=self.currentFrame.shape[:2]\\n img=QtGui.QImage(self.currentFrame,\\n width,\\n height,\\n QtGui.QImage.Format_RGB888)\\n img=QtGui.QPixmap.fromImage(img)\\n self.previousFrame = self.currentFrame\\n return img\\n except:\\n return None\",\n \"def draw(self, frame):\\n frame[OFS:OFS+self.image.shape[0], OFS:OFS+self.image.shape[1]] = self.image\",\n \"def create_full_pic(self):\\n self.create_half_pic()\\n mirror_update(self.flag)\",\n \"def get_image(self, size, mode='normal', state='on'):\\n raise NotImplementedError\",\n \"def pic(update, context):\\n chars = '01234567890ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghiklmnopqrstuvwxyz'\\n length = 5\\n\\n while True:\\n img_code = choices(chars, k=length)\\n address = 'https://i.imgur.com/' + \\\"\\\".join(img_code) + '.jpg'\\n img = Image.open(BytesIO(get(address).content))\\n\\n if img.size[0] != 161:\\n break\\n\\n update.message.reply_photo(\\n photo=address,\\n )\",\n \"def GET(self, url):\\n try:\\n f = open(url, 'r')\\n image = f.read()\\n f.close()\\n except:\\n\\n db_module.resave_img(url[5:])\\n\\n f = open(url, 'r')\\n image = f.read()\\n f.close()\\n\\n return image\",\n \"def getNextImage(self):\\n self._images = self._api.updateImageNames()\\n \\n # Get index from local txt file. \\n # This ensures that the image queue does not reset if the Pola restarts.\\n try: \\n f = open(\\\"memoryIndex.txt\\\", 'r')\\n self._currentIndex = int((f.read()))\\n f.close()\\n except: \\n self._currentIndex = -1\\n \\n self._currentIndex = (self._currentIndex + 1) % len(self._images)\\n \\n f = open(\\\"memoryIndex.txt\\\", 'w')\\n f.write(str(self._currentIndex))\\n f.close()\\n \\n \\n # If there is an internet connection, go online. If not, get the \\\"no wifi error\\\"- image queue\\n try:\\n urllib.request.urlopen('http://torabodin.com/')\\n try: \\n imageName = self._api.downloadImage(self._currentIndex)\\n print(1, imageName)\\n self._image= self.loadImage(imageName, True)\\n print (self._image)\\n \\n except: \\n self._image = self.getNextImage()\\n \\n except:\\n self._image = self.loadImage(None, False)\\n \\n \\n return self._image\",\n \"def new_image_callback(self, new_image_msg):\\n self.process_new_frame(\\n self.cv_bridge.imgmsg_to_cv2(\\n new_image_msg,\\n desired_encoding=\\\"bgr8\\\"\\n )\\n )\",\n \"def get_image(self):\\n image = Image.new('1', (8, 16))\\n draw = ImageDraw.Draw(image)\\n for x in xrange(8):\\n for y in xrange(16):\\n draw.point((x,y),self.get_pixel(x, y))\\n return image\",\n \"async def get_image(self):\\n\\n # generating\\n fixed_latent = torch.randn(1, 512, 1, 1, device=self.device)\\n\\n with torch.no_grad():\\n # passing through\\n fake_images = self.model(fixed_latent)\\n # saving\\n save_image(fake_images, f'models/FaceGAN_dir/faces/fake.jpg')\",\n \"def draw(self):\\n return ImageDraw.Draw(self.buffer)\",\n \"def nextPicture(self):\\n\\t\\tif self.currentPicture == self.totalPictures-1:\\n\\t\\t\\tself.currentPicture = 0\\n\\t\\telse:\\n\\t\\t\\tself.currentPicture += 1\\n\\t\\tself.loadImage(self.picPaths[self.currentPicture])\",\n \"def capture_to_buf(self, selector=None):\\n\\n images = self.capture(selector)\\n result = []\\n\\n for image in images:\\n ba = QByteArray()\\n buf = QBuffer(ba)\\n buf.open(QIODevice.ReadWrite)\\n image.save(buf, 'jpg')\\n stream = StringIO(str(buf.buffer()))\\n result.append(stream)\\n\\n return result\",\n \"def image(self, img):\\n # determine our effective width/height, taking rotation into account\\n width = self.width\\n height = self.height\\n if self.rotation in (1, 3):\\n width, height = height, width\\n\\n if isinstance(self.format, (RGB565Format, RGB888Format)) and img.mode != \\\"RGB\\\":\\n raise ValueError(\\\"Image must be in mode RGB.\\\")\\n if isinstance(self.format, (MHMSBFormat, MVLSBFormat)) and img.mode != \\\"1\\\":\\n raise ValueError(\\\"Image must be in mode 1.\\\")\\n\\n imwidth, imheight = img.size\\n if imwidth != width or imheight != height:\\n raise ValueError(\\n f\\\"Image must be same dimensions as display ({width}x{height}).\\\"\\n )\\n # Grab all the pixels from the image, faster than getpixel.\\n pixels = img.load()\\n # Clear buffer\\n for i in range(len(self.buf)): # pylint: disable=consider-using-enumerate\\n self.buf[i] = 0\\n # Iterate through the pixels\\n for x in range(width): # yes this double loop is slow,\\n for y in range(height): # but these displays are small!\\n if img.mode == \\\"RGB\\\":\\n self.pixel(x, y, pixels[(x, y)])\\n elif pixels[(x, y)]:\\n self.pixel(x, y, 1) # only write if pixel is true\",\n \"def CopyFromBuffer(*args, **kwargs):\\n return _gdi_.Bitmap_CopyFromBuffer(*args, **kwargs)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67637736","0.66389644","0.6545607","0.649641","0.64811593","0.6454082","0.64298207","0.63318187","0.63116366","0.6224079","0.6165722","0.6156108","0.61227834","0.60747534","0.6073141","0.60558736","0.5991578","0.5963383","0.593771","0.5916153","0.5916153","0.5914926","0.58988667","0.58926207","0.5876393","0.5874509","0.58456385","0.5836193","0.58329076","0.5811635","0.5809651","0.5807474","0.5806552","0.57986975","0.5793285","0.57852155","0.57763207","0.57656336","0.5757944","0.57575136","0.574245","0.5738522","0.5737816","0.57357633","0.5732268","0.5730467","0.57246304","0.57240343","0.572242","0.57152134","0.5688941","0.5685832","0.568563","0.56836283","0.56711507","0.5669633","0.5663809","0.5659465","0.5651954","0.5645256","0.5642618","0.5625471","0.56244004","0.5623065","0.5619582","0.56182945","0.5612992","0.5602252","0.5601519","0.5595656","0.55912215","0.55864877","0.5582962","0.5581769","0.5570695","0.5563532","0.5559397","0.5552585","0.5551238","0.5550157","0.55499506","0.5548695","0.5543411","0.5536755","0.5535729","0.55291474","0.5528968","0.5526841","0.5520532","0.5516574","0.5511746","0.55111676","0.5506834","0.5502303","0.5498739","0.549759","0.5494595","0.5491081","0.5490815","0.5489927","0.5489602"],"string":"[\n \"0.67637736\",\n \"0.66389644\",\n \"0.6545607\",\n \"0.649641\",\n \"0.64811593\",\n \"0.6454082\",\n \"0.64298207\",\n \"0.63318187\",\n \"0.63116366\",\n \"0.6224079\",\n \"0.6165722\",\n \"0.6156108\",\n \"0.61227834\",\n \"0.60747534\",\n \"0.6073141\",\n \"0.60558736\",\n \"0.5991578\",\n \"0.5963383\",\n \"0.593771\",\n \"0.5916153\",\n \"0.5916153\",\n \"0.5914926\",\n \"0.58988667\",\n \"0.58926207\",\n \"0.5876393\",\n \"0.5874509\",\n \"0.58456385\",\n \"0.5836193\",\n \"0.58329076\",\n \"0.5811635\",\n \"0.5809651\",\n \"0.5807474\",\n \"0.5806552\",\n \"0.57986975\",\n \"0.5793285\",\n \"0.57852155\",\n \"0.57763207\",\n \"0.57656336\",\n \"0.5757944\",\n \"0.57575136\",\n \"0.574245\",\n \"0.5738522\",\n \"0.5737816\",\n \"0.57357633\",\n \"0.5732268\",\n \"0.5730467\",\n \"0.57246304\",\n \"0.57240343\",\n \"0.572242\",\n \"0.57152134\",\n \"0.5688941\",\n \"0.5685832\",\n \"0.568563\",\n \"0.56836283\",\n \"0.56711507\",\n \"0.5669633\",\n \"0.5663809\",\n \"0.5659465\",\n \"0.5651954\",\n \"0.5645256\",\n \"0.5642618\",\n \"0.5625471\",\n \"0.56244004\",\n \"0.5623065\",\n \"0.5619582\",\n \"0.56182945\",\n \"0.5612992\",\n \"0.5602252\",\n \"0.5601519\",\n \"0.5595656\",\n \"0.55912215\",\n \"0.55864877\",\n \"0.5582962\",\n \"0.5581769\",\n \"0.5570695\",\n \"0.5563532\",\n \"0.5559397\",\n \"0.5552585\",\n \"0.5551238\",\n \"0.5550157\",\n \"0.55499506\",\n \"0.5548695\",\n \"0.5543411\",\n \"0.5536755\",\n \"0.5535729\",\n \"0.55291474\",\n \"0.5528968\",\n \"0.5526841\",\n \"0.5520532\",\n \"0.5516574\",\n \"0.5511746\",\n \"0.55111676\",\n \"0.5506834\",\n \"0.5502303\",\n \"0.5498739\",\n \"0.549759\",\n \"0.5494595\",\n \"0.5491081\",\n \"0.5490815\",\n \"0.5489927\",\n \"0.5489602\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":81779,"cells":{"query":{"kind":"string","value":"Returns a dictionary which maps subfolder > example > source wavs list. Returns a hierarchical dict of relative source file paths when given a folder produced by scaper."},"document":{"kind":"string","value":"def make_example_dict_from_folder(\n folder_sources, subset='all', ss_regex=re.compile(r'example.*_sources'),\n pattern='_sources', subfolder_events=('background', 'foreground')):\n if subset == 'all':\n subfolders = ['train', 'validation', 'eval']\n else:\n subfolders = [subset]\n sources_for_mix = {}\n for subfolder in subfolders:\n sources_for_mix[subfolder] = {}\n src_sub = os.path.join(folder_sources, subfolder)\n if os.path.isdir(src_sub):\n src_entries = os.listdir(src_sub)\n src_selected = sorted(list(filter(ss_regex.search, src_entries)))\n for src_example in src_selected:\n src_example_base = src_example.rstrip(pattern)\n src_example_wav = src_example_base + '.wav'\n if not os.path.isfile(os.path.join(src_sub, src_example_wav)):\n raise ValueError('In {}, no mixed file {} but there is a folder '\n 'of sources {}'.format(\n subfolder, src_example_wav, src_example))\n src_example_rel = os.path.join(subfolder, src_example_wav)\n sources_for_mix[subfolder][src_example_rel] = []\n if subfolder_events is not None:\n for ex_sub in subfolder_events:\n src_wav_dir = os.path.join(src_sub, src_example, ex_sub)\n if os.path.isdir(src_wav_dir):\n src_wavs = sorted(list(filter(re.compile(r'.*\\.wav').search,\n os.listdir(src_wav_dir))))\n for src_wav in src_wavs:\n src_wav_f = os.path.join(src_wav_dir, src_wav)\n src_wav_f_rel = os.path.relpath(src_wav_f, folder_sources)\n sources_for_mix[subfolder][src_example_rel].append(\n src_wav_f_rel)\n else:\n src_wav_dir = os.path.join(src_sub, src_example)\n if os.path.isdir(src_wav_dir):\n src_wavs = sorted(list(filter(re.compile(r'.*\\.wav').search,\n os.listdir(src_wav_dir))))\n for src_wav in src_wavs:\n src_wav_f = os.path.join(src_wav_dir, src_wav)\n src_wav_f_rel = os.path.relpath(src_wav_f, folder_sources)\n sources_for_mix[subfolder][src_example_rel].append(src_wav_f_rel)\n return sources_for_mix"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def extract_folder_file_structure() -> Dict[str, List[str]]:\n folders_and_files = {}\n for path_to_folder in glob.glob(f\"{ZULIPTERMINAL}/**/\", recursive=True):\n complete_directory_path = Path(path_to_folder)\n if complete_directory_path.name in FOLDERS_TO_EXCLUDE:\n continue\n relative_directory_path = complete_directory_path.relative_to(ROOT_DIRECTORY)\n if str(relative_directory_path) not in DESC_FOR_NO_FILE_FOLDERS:\n files_in_directory = [\n file.name\n for file in complete_directory_path.glob(\"*.py\")\n if file.name != \"__init__.py\"\n ]\n folders_and_files[str(relative_directory_path)] = files_in_directory\n return folders_and_files","def _walk_dirs(self):\n for project_name in self.new_source_paths.keys():\n # print \"-------- Now mapping ---- \" + project_name\n search_path = self.root + project_name + '\\\\Data'\n for dirpath, subdirs, files in os.walk(search_path):\n for file in files:\n self.new_source_paths[project_name][file] = dirpath\n # print \"------------ Finished mapping ------- \" + project_name\n return self.new_source_paths","def make_example_list_from_folder(\n folder_sources, subset='all', ss_regex=re.compile(r'example.*_sources'),\n pattern='_sources', subfolder_events=('background', 'foreground')):\n example_dict = make_example_dict_from_folder(\n folder_sources, subset=subset, ss_regex=ss_regex, pattern=pattern,\n subfolder_events=subfolder_events)\n example_list = []\n for subset in example_dict:\n for example in example_dict[subset]:\n example_list.append('\\t'.join([example] + example_dict[subset][example]))\n return example_list","def incoming_paths(root_dir, parent_dir):\n return {\n 'F1' : os.path.join(root_dir, \"F1\"),\n 'F' : os.path.join(parent_dir, \"F\"),\n 'F2' : os.path.join(parent_dir, \"F2-in\"),\n 'D1' : os.path.join(root_dir, \"D1\"),\n 'D' : os.path.join(parent_dir, \"D\"),\n 'D2' : os.path.join(parent_dir, \"D2-in\"),\n }","def parse_folder(self, path):\n\n for filename in os.listdir(path):\n self.parse_file(os.path.join(path, filename), filename)\n return self.country_dict, self.hre_dict, self.name_dict","def get_paths(input_folder):\n list_files = []\n conll_folder = glob.glob(input_folder + '/*.json')\n \n for filename in conll_folder:\n list_files.append(filename)\n\n return list_files","def get_all_paths(why = 'train'):\r\n if why == 'train':\r\n parent_folder = train_parent_folder\r\n if why == 'test':\r\n parent_folder = test_test_folder\r\n sub_folders = glob.glob(parent_folder) # Directories of all languages\r\n image_paths = [glob.glob(sub_folder + '\\*') for sub_folder in sub_folders] # Directories of all characters\r\n image_paths = sum(image_paths, []) # Flatten out the 2D list to a 1D list \r\n return image_paths","def map_audio(self): \n for root, dirs, files in os.walk(self.dir):\n for name in files:\n if (name.split(\".\")[-1].lower() == 'm4a' or \\\n name.split(\".\")[-1].lower() == 'mp3'):\n \n cur_path = \"{0}/{1}\".format(root, name)\n cur_file = auto.File(cur_path)\n \n artist = cur_file.artist.lower().strip()\n album = cur_file.album.lower().strip()\n title = cur_file.title.lower().strip()\n bitrate = cur_file.bitrate\n \n if not artist in self.audio_dict:\n self.audio_dict[artist] = {}\n \n if not album in self.audio_dict[artist]:\n self.audio_dict[artist][album] = {}\n \n title_key = title\n for in_album_title in self.audio_dict[artist][album]:\n if sm(None, title, in_album_title).ratio() > 0.9:\n title_key = in_album_title\n \n if not title_key in \\\n self.audio_dict[artist][album]:\n self.audio_dict[artist][album][title_key] = []\n \n self.audio_dict[artist][album][title_key].append({\n 'path': cur_path,\n 'bitrate': bitrate,\n 'file_name': name\n })\n \n return self","def parse_paths():\r\n sources = get_source_paths()\r\n results = collections.defaultdict(list)\r\n for root_dir in sources:\r\n\r\n for script_type, dirs in walkdirs(root_dir).iteritems():\r\n\r\n for d in dirs:\r\n logger.debug(d)\r\n\r\n # Add paths to environments\r\n if os.path.basename(d).lower().startswith(ICONS):\r\n results['XBMLANGPATH'].append(d)\r\n os.environ['XBMLANGPATH'] += os.pathsep + d\r\n\r\n if script_type == 'mel':\r\n results['MAYA_SCRIPT_PATH'].append(d)\r\n os.environ['MAYA_SCRIPT_PATH'] += os.pathsep + d\r\n else:\r\n results['PYTHONPATH'].append(d)\r\n site.addsitedir(d)\r\n return results","def read_base_folder(base_path: str) -> dict:\n\tfour_x_images: dict = {}\n\tfor file in listdir(four_x_file_path):\n\t\tfile_extension = os.path.splitext(file)[1]\n\t\tif file_extension in image_extensions:\n\t\t\tfour_x_images[file] = join(base_path, file)\n\treturn four_x_images","def getpaths_fromdir(input_prefix_, directory_):\n path = os.path.join(input_prefix_, \"%s*\" % directory_, \"*\")\n return [tuple([directory_, path])]","def get_file_paths():\n audio_folder = MY_DIR + '/assets'\n\n audio_addy_list = []\n for file in os.scandir(audio_folder):\n audio_addy_list.append(file.path)\n\n return audio_addy_list","def list_files_in_directory(self):\n lesson_file_dict = dict()\n lesson_file_dict[\"files\"] = []\n\n directory_list = listdir(self.sub_dir)\n for directory in directory_list:\n if isfile(join(self.sub_dir, directory)):\n lesson_file_dict[\"files\"].append(directory)\n\n return lesson_file_dict","def prep_files(app):\n smali_paths = []\n start = time.time()\n \n for root, dirs, files in os.walk(app, topdown=False):\n for name in files:\n if name[-6:] == \".smali\":\n smali_paths.append(str(os.path.join(root, name)))\n \n return smali_paths","def samples_path():\n dir = os.path.dirname(os.path.abspath(__file__))\n samples = os.path.join(dir, 'samples')\n return samples","def get_data(folder_name):\n train_data = {}\n for study_id, study_path in sorted(get_studies(folder_name)):\n train_data[study_id] = get_slices(study_id, study_path)\n return train_data","def _get_project_names(self):\n for folder in os.listdir(self.root):\n if folder[0].isdigit():\n try:\n self.new_source_paths[folder]\n pass\n except:\n self.new_source_paths[folder] = {}\n return self.new_source_paths","def load_data(self):\r\n if not os.path.exists(self.origin_dir):\r\n raise ValueError(f\"Folder {self.origin_dir} not exists!\")\r\n\r\n # loop folders\r\n listglobs = glob.glob(os.path.join(self.origin_dir)+r\"[0-9]*\")\r\n count = 0\r\n temp = []\r\n for x in listglobs:\r\n\r\n # step1, get speaker id md5\r\n user_id = x.rsplit(\"\\\\\")[-1]\r\n speaker_id = hashlib.md5(user_id.encode(\"utf-8\")).hexdigest()\r\n self.wav_desc[\"speaker_id\"] = speaker_id\r\n print(\"1=>\", x)\r\n\r\n for k in [\"你好小顺\", \"小顺小顺\"]:\r\n paths = os.path.join(x, k)\r\n print(\"2=>\", paths)\r\n # step2, parse speaker info\r\n with open(os.path.join(paths, \"spearker_info.txt\"), 'r', encoding=\"utf-8\") as f:\r\n line = f.readline()\r\n arrs = line.strip().split(\"\\\\t\")\r\n if len(arrs) != 3:\r\n raise ValueError(\"Required three field in speaker_info<id>\\t<gender>\\t<age>\")\r\n self.wav_desc[\"gender\"] = arrs[1].strip(\"<\").rstrip(\">\")\r\n self.wav_desc[\"age\"] = arrs[-1].strip(\"<\").rstrip(\">\")\r\n\r\n # step3, parse wav detailed information\r\n # key: wav_id, value: info_list, [keyword, noise_type, distance, speed,user_id, equipment]\r\n wav_infos_dict = {}\r\n with open(os.path.join(paths, \"wav_desc.txt\"), \"r\", encoding=\"utf-8\") as f:\r\n for line in f.readlines():\r\n arrs = line.strip().split(\"\\\\t\")\r\n wav_infos_dict[arrs[0].strip(\"<\").rstrip(\">\")] = [x.strip(\"<\").rstrip(\">\") for\r\n x in arrs[1:]]\r\n\r\n print(f\"Parse wav info finished find {len(wav_infos_dict)} infos.\")\r\n\r\n # Step4, audio with background noise and without nose, which was back_wav and wav_data folder\r\n for wav_folder in [\"back_wav\", \"wav_data\"]:\r\n audio_lists = glob.glob(os.path.join(paths + f\"\\\\{wav_folder}\", \"*.wav\"))\r\n for xa in audio_lists:\r\n # copy data to\r\n wav_id, user_id = get_wav_name(xa)\r\n # print(wav_id, user_id)\r\n # create md5 id\r\n utt_id = hashlib.md5(xa.encode(\"utf-8\")).hexdigest()\r\n # speaker_id = hashlib.md5(user_id.encode(\"utf-8\")).hexdigest()\r\n # print(utt_id, speaker_id)\r\n # collect all info for an audio\r\n self.wav_desc[\"utt_id\"] = utt_id\r\n infos = wav_infos_dict[wav_id]\r\n if len(infos) != 6:\r\n print(\"==>\", infos)\r\n self.wav_desc[\"keyword_id\"] = self.keywords_dict[infos[0]]\r\n self.wav_desc[\"noise_type\"] = infos[1]\r\n self.wav_desc[\"distance\"] = infos[2]\r\n self.wav_desc[\"record_speed\"] = infos[3]\r\n self.wav_desc[\"speaker_id\"] = speaker_id\r\n self.wav_desc[\"record_equipment\"] = infos[5]\r\n\r\n # record wav information\r\n t_infos = copy.deepcopy(self.wav_desc)\r\n self.all_wavs.append(t_infos)\r\n count += 1\r\n temp.append(utt_id)\r\n\r\n # copy data to resource folder\r\n dest = shutil.copy2(xa, os.path.join(self.dest_dir, f\"audios/{utt_id}.wav\"))\r\n set_index = which_set(dest, 20, 30)\r\n self.data_index[set_index].append(t_infos)\r\n\r\n # write wav information into json file\r\n with open(os.path.join(self.dest_dir, \"resources/wav_desc.json\"), \"w\", encoding=\"utf-8\") as f:\r\n json.dump(self.all_wavs, f, ensure_ascii=False, indent=True)\r\n print(f\"total wavs:{count}, total ids:{len(temp)}\")\r\n for set_index in self.data_index.keys():\r\n with open(os.path.join(self.dest_dir, f\"resources/p_{set_index}.json\"), \"w\", encoding=\"utf-8\") as f:\r\n json.dump(self.data_index[set_index], f, ensure_ascii=False, indent=True)\r\n print(f\"Collect {set_index} data total {len(self.data_index[set_index])} samples.\")","def filelist(folder):\n file_dict={}\n folderlist = glob.glob(os.getcwd()+\"/\"+folder+\"/*\")\n for i in tqdm(folderlist):\n filelist = glob.glob(i+\"/*\")\n filename = i.rsplit(\"/\")[-1]\n file_dict[filename]= filelist\n\n return file_dict","def voicesPathsCollector(source_dir, gender_ids):\r\n # The list containing the IDs of the speakers which are the folder names\r\n person_ids_list = gender_ids\r\n\r\n # An empty list which it will contains voices paths which are in the section folders\r\n voices_paths_list = []\r\n\r\n # Iterating over a person speaker ids\r\n for person_id_idx in range(len(person_ids_list)):\r\n # Speaker path containing the chapter's directories\r\n speaker_path = Path.cwd().joinpath(source_dir, person_ids_list[person_id_idx])\r\n # The list containing the IDs of the sections by the current speaker which are the folder names\r\n sections_ids_list = os.listdir(speaker_path)\r\n\r\n # Iterating over a sections ids by the current speaker\r\n for sec_id_idx in range(len(sections_ids_list)):\r\n # Section path containing files\r\n section_path = Path.cwd().joinpath(speaker_path,sections_ids_list[sec_id_idx])\r\n # Iterating over files which are existing in section's folders\r\n for file in os.listdir(section_path):\r\n # Choose files with .flac extension\r\n if file.endswith(\".flac\"):\r\n\r\n voice_path = Path.cwd().joinpath(section_path, file)\r\n voices_paths_list.append(voice_path)\r\n\r\n return voices_paths_list","def getSourcePaths(self, makeGlyphs=True, makeKerning=True, makeInfo=True):\n paths = []\n for name in self.sources.keys():\n paths.append(self.sources[name][0].path)\n return paths","def get_paths_list_from_folder(folder):\n names = os.listdir(folder)\n relative_paths = [os.path.join(folder, image_name) for image_name in names]\n return relative_paths","def _get_sourceFolders(self, dom):\n return self._get_new_module_root_manager(dom).getElementsByTagName('sourceFolder')","def get_filepaths(extract_dir):\n\n index = []\n labels = []\n _extract_dir = os.path.join(extract_dir, 'UCF-101')\n for folder in os.listdir(_extract_dir):\n labels.append(folder)\n folderpath = os.path.join(_extract_dir, folder)\n\n if not os.path.isdir(folderpath):\n continue\n\n for filename in os.listdir(folderpath):\n if 'avi' not in filename:\n continue\n\n if filename[0] == '.':\n continue\n\n filepath = os.path.join(folderpath, filename)\n\n if os.path.exists(filepath):\n index.append(filepath)\n else:\n print(filepath)\n return index, labels","def get_samples_file(foldername, filter=None):\n samples = []\n for file in os.listdir(foldername):\n if filter and file.find(filter) == -1:\n continue\n for sample in sfile(foldername + '/' + file, None).get_samples():\n samples.append(sample)\n return samples","def read_process_labelled(src_dir, window=0.2, overlap=0.5, debug=True):\n\n arr_features = []\n\n # Read files from the folders\n for x, _ in GENRES.items():\n folder = src_dir + x\n \n for root, subdirs, files in os.walk(folder):\n for file in files:\n # Read the audio file\n file_name = folder + \"/\" + file\n signal, sr = librosa.load(file_name)\n signal = signal[:660000]\n \n # Debug process\n if debug:\n print(f\"Reading file: {file_name}\")\n \n # Split songs:\n samples = split_songs(signal, window, overlap)\n\n # Append the result to the data structure\n for s in samples:\n features = get_features(s, sr)\n features['genre'] = GENRES[x]\n arr_features.append(features)\n\n return arr_features","def get_realization_paths(rootdir, folder_prefix): #{{{\n fnames = []\n for root, dirs, files in os.walk(rootdir):\n if(root=='.'):\n dirs.sort()\n for adir in dirs:\n if(adir.startswith(folder_prefix)):\n fnames.append(rootdir + '/' + adir)\n\n return fnames #}}}","def read_from_folder(folder):\n\n raw_dict = dict()\n\n for file in os.listdir(folder):\n raw = read_raw_from_file(os.path.join(folder, file))\n raw_dict[file] = raw\n\n return raw_dict","def sources_relative_to_buildroot(self):\r\n for src in self.sources:\r\n yield os.path.join(self.target_base, src)","def agg_paths(dataset_root_dir):\n root_dir_p = Path(dataset_root_dir)\n experiment_dirs = sorted([e for e in root_dir_p.iterdir()])\n \n left_paths=[]\n right_paths=[]\n occl_paths=[]\n disparity_paths=[]\n depth_paths=[] \n calib_paths=[]\n sample_name=[]\n\n for experiment in experiment_dirs:\n modality_gt_dirs = sorted([gt_dir for gt_dir in experiment.iterdir() if 'Ground_truth' in gt_dir.name])\n for modality_gt_dir in modality_gt_dirs:\n occl_paths.extend(sorted([p.resolve()\n for p in (modality_gt_dir/'OcclusionL').iterdir()]))\n disparity_paths.extend(sorted([p.resolve()\n for p in (modality_gt_dir/'Disparity').iterdir()]))\n depth_paths.extend(sorted([p.resolve()\n for p in (modality_gt_dir/'DepthL').iterdir()]))\n \n \n left_paths.extend(sorted([(experiment/'Left_rectified'/p.name).resolve()\n for p in (modality_gt_dir/'OcclusionL').iterdir()]))\n right_paths.extend(sorted([(experiment/'Right_rectified'/p.name).resolve()\n for p in (modality_gt_dir/'OcclusionL').iterdir()]))\n calib_paths.extend(sorted([(experiment/'Rectified_calibration'/(p.stem+'.json')).resolve()\n for p in (modality_gt_dir/'OcclusionL').iterdir()]))\n sample_name.extend(sorted([(p.parents[2]).name+' - ' + (p.parents[1]).name.split('_')[-1]+ ' - '+p.stem for p in (modality_gt_dir/'Disparity').iterdir()])) \n return {'left': left_paths,\n 'right': right_paths,\n 'occ': occl_paths,\n 'disparity': disparity_paths,\n 'depth': depth_paths,\n 'calib': calib_paths,\n 'name': sample_name}","def get_folders_content(path):\n folder_contents = {}\n for folder_name, folder in zip(json_names, experiment_folders(path)):\n if not folder.exists():\n raise RuntimeError(\n f\"The {folder_name} folder doesn' exist in the\" \" specified path\"\n )\n\n folder_contents[folder_name] = folder.glob(\"*\")\n return folder_contents","def extract_embeddings_recursive_from_dir(self, dir_from: PathLike, dir_to: PathLike) -> PathLike:\n pass","def target_folders(metadata, analysistype):\n # Initialise variables\n targetfolders = set()\n targetfiles = list()\n records = dict()\n for sample in metadata:\n if sample[analysistype].combinedtargets != 'NA':\n targetfolders.add(sample[analysistype].targetpath)\n for targetdir in targetfolders:\n # Find all the .fasta files in each target folder\n targetfiles = glob(os.path.join(targetdir, '*.fasta'))\n for targetfile in targetfiles:\n # Read the sequences from the target file to a dictionary\n records[targetfile] = SeqIO.to_dict(SeqIO.parse(targetfile, 'fasta'))\n return targetfolders, targetfiles, records","def get_all_file_paths_labels(data_root: str) -> list:\n\n speaker_dirs = os.listdir(data_root)\n all_files = []\n i = 0\n for d in speaker_dirs:\n files = glob.iglob(data_root + '/' + d + '/**/*.wav', recursive=True)\n files = [[f, i] for f in files]\n all_files += files\n i += 1\n all_files = sorted(all_files, key=lambda x:x[0], reverse=False)\n\n return all_files","def parse(cls, raw_folder: str) -> Dict[str, Any]:\n folder_path = os.path.abspath(raw_folder)\n data = dict()\n files = os.listdir(folder_path)\n for file in files:\n if is_ignored(file):\n continue\n try:\n file = os.path.join(raw_folder, file)\n datum = cls.process_file(file)\n except FileNotCompatible:\n continue\n\n _, kwrd = os.path.split(file)\n kwrd = os.path.splitext(kwrd)[0]\n data[kwrd] = datum\n\n return data","def get_dir_files(self, recursive=False):\n logging.info('Enumerating files under the source path (recursive=%s) ...', recursive)\n files = {}\n if not recursive:\n files[self.path_source] = [\n f for f in os.listdir(self.path_source) if os.path.isfile(os.path.join(self.path_source, f))\n ]\n else:\n for current_dir, sub_dirs, dir_files in os.walk(self.path_source):\n files[os.path.join(self.path_source, current_dir)] = [f for f in dir_files]\n\n return files","def get_training_data_directories():\n\n\tmapping = dict()\n\tmapping[ASCause.apsp] = directories.training_cause_apsp\n\tmapping[ASCause.bl] = directories.training_cause_bl\n\tmapping[ASCause.ce] = directories.training_cause_ce\n\tmapping[ASCause.dfl] = directories.training_cause_dfl\n\tmapping[ASCause.lrssi] = directories.training_cause_lrssi\n\tmapping[ASCause.pscan_assoc] = directories.training_cause_pscan_assoc\n\tmapping[ASCause.pscan_unassoc] = directories.training_cause_pscan_unassoc\n\tmapping[ASCause.pwr_state] = directories.training_cause_pwr_state\n\treturn mapping","def relative_to_buildroot(self):\n return [os.path.join(self.rel_path, source) for source in self.source_paths]","def sources_under(self, base_dir):\n if '*' in base_dir or '?' in base_dir or '[' in base_dir:\n for d in sorted(fnmatch.filter(self.keys(), base_dir)):\n yield self[d]\n else:\n base_dir_sep = base_dir + os.sep\n for d, s in sorted(self.items()):\n if d == base_dir or d.startswith(base_dir_sep):\n yield s","def examples_paths():\n data_dir = utils.get_data_filename(os.path.join('tests', 'data'))\n p_xylene_dir = os.path.join(data_dir, 'p-xylene-implicit')\n p_xylene_gro_dir = os.path.join(data_dir, 'p-xylene-gromacs-example')\n ben_tol_dir = os.path.join(data_dir, 'benzene-toluene-explicit')\n abl_imatinib_dir = os.path.join(data_dir, 'abl-imatinib-explicit')\n tol_dir = os.path.join(data_dir, 'toluene-explicit')\n benz_tol_dir = os.path.join(data_dir, 'benzene-toluene-standard-state')\n\n paths = dict()\n paths['lysozyme'] = os.path.join(p_xylene_dir, '181L-pdbfixer.pdb')\n paths['p-xylene'] = os.path.join(p_xylene_dir, 'p-xylene.mol2')\n paths['benzene'] = os.path.join(ben_tol_dir, 'benzene.tripos.mol2')\n paths['toluene'] = os.path.join(ben_tol_dir, 'toluene.tripos.mol2')\n paths['abl'] = os.path.join(abl_imatinib_dir, '2HYY-pdbfixer.pdb')\n paths['imatinib'] = os.path.join(abl_imatinib_dir, 'STI02.mol2')\n paths['bentol-complex'] = [os.path.join(ben_tol_dir, 'complex.prmtop'),\n os.path.join(ben_tol_dir, 'complex.inpcrd')]\n paths['bentol-solvent'] = [os.path.join(ben_tol_dir, 'solvent.prmtop'),\n os.path.join(ben_tol_dir, 'solvent.inpcrd')]\n paths['pxylene-complex'] = [os.path.join(p_xylene_gro_dir, 'complex.top'),\n os.path.join(p_xylene_gro_dir, 'complex.gro')]\n paths['pxylene-solvent'] = [os.path.join(p_xylene_gro_dir, 'solvent.top'),\n os.path.join(p_xylene_gro_dir, 'solvent.gro')]\n paths['pxylene-gro-include'] = os.path.join(p_xylene_gro_dir, 'top')\n paths['toluene-solvent'] = [os.path.join(tol_dir, 'solvent.pdb'),\n os.path.join(tol_dir, 'solvent.xml')]\n paths['toluene-vacuum'] = [os.path.join(tol_dir, 'vacuum.pdb'),\n os.path.join(tol_dir, 'vacuum.xml')]\n paths['benzene-toluene-boxless'] = [os.path.join(benz_tol_dir, 'standard_state_complex_boxless.inpcrd'),\n os.path.join(benz_tol_dir, 'standard_state_complex.prmtop')]\n paths['benzene-toluene-nan'] = [os.path.join(benz_tol_dir, 'standard_state_complex_nan.inpcrd'),\n os.path.join(benz_tol_dir, 'standard_state_complex.prmtop')]\n return paths","def create_sample_dictionary(sample_path):\n sample_dict = {'_'.join(sample_path.split('/')[-1].split('.')[0].split('_')[:-1]) : sc.read(sample_path)}\n return sample_dict","def get_pathes(self) -> Dict[str, str]:\n\n pathes: Dict[str, str] = {}\n\n for path in self.files:\n name = path.split(\"/\")[-1].split(\".\")[0]\n pathes[name] = os.path.join(self.home_folder, path)\n return pathes","def map_files(key):\n \n datadir=os.path.join(os.path.dirname(__file__),'ncnr_sample_data')\n filedict={'empty_1m':os.path.join(datadir,'SILIC001.SA3_SRK_S101'),\n 'empty_4m':os.path.join(datadir,'SILIC002.SA3_SRK_S102'),\n 'empty_cell_1m':os.path.join(datadir,'SILIC003.SA3_SRK_S103'),\n 'blocked_1m':os.path.join(datadir,'SILIC004.SA3_SRK_S104'),\n 'trans_empty_cell_4m':os.path.join(datadir,'SILIC005.SA3_SRK_S105'),\n 'trans_sample_4m':os.path.join(datadir,'SILIC006.SA3_SRK_S106'),\n 'blocked_4m':os.path.join(datadir,'SILIC007.SA3_SRK_S107'),\n 'empty_cell_4m':os.path.join(datadir,'SILIC008.SA3_SRK_S108'),\n 'sample_1m':os.path.join(datadir,'SILIC009.SA3_SRK_S109'),\n 'sample_4m':os.path.join(datadir,'SILIC010.SA3_SRK_S110'),\n 'mask':os.path.join(datadir,'DEFAULT.MASK'),\n 'div':os.path.join(datadir,'PLEX_2NOV2007_NG3.DIV'),\n }\n return filedict[key]","def _getSoundsFromDirectory(self, directoryPath):\n files = [f for f in listdir(directoryPath)\n if isfile(join(directoryPath, f))]\n for filePath in files:\n self._soundsDictionary[filePath] = FMOD.FMOD.loadSound(\n self._formatPath(directoryPath, filePath))","def get_all(folder, filter_funs = []) :\n\n def apply_funs(x, funs) :\n \"\"\"Applies the filter functions.\"\"\"\n res = True\n for f in funs :\n res = f(x)\n if not res :\n break\n return res\n \n final = {}\n files = listdir(folder)\n print(\"Loading Spectras\")\n for f in files :\n try :\n spectra = Spectra(folder + \"/\" + f)\n print(\".\", end=\"\")\n except:\n continue\n if spectra == None :\n continue\n if not apply_funs(spectra, filter_funs) :\n continue\n pot_spectra = final.get(spectra.database_id, None)\n if not pot_spectra :\n final[spectra.database_id] = [deepcopy(spectra)]\n else :\n pot_spectra.append(deepcopy(spectra))\n return final","def get_folder_filenames(path):\n result = {}\n for parent, dirnames, filenames in os.walk(path):\n if not dirnames:\n result[os.path.split(parent)[-1]] = filenames\n return result","def collect_files(path, audio_files):\n\n for entry in os.scandir(path):\n if entry.is_dir():\n collect_files(entry.path, audio_files)\n if entry.is_file() and (entry.path.endswith(\".flac\") or entry.path.endswith(\".wav\")):\n audio_files.append(entry.path)","def prepare_src_folder(self, src_folder: str) -> None:","def get_midi_paths(root):\n\treturn [os.path.join(dirpath, filename) \n\t\t\tfor dirpath, _, filenames in os.walk(root) \n\t\t\tfor filename in filenames \n\t\t\tif filename.endswith(\".mid\")]","def demo_paths(self):\n base_path = os.path.join(self.module.__path__[0], 'demo')\n paths = []\n if os.path.isdir(base_path):\n for item in os.listdir(base_path):\n # TODO: support examples which is not auto-loaded\n if not os.path.isdir(os.path.join(base_path, 'examples')):\n paths.append(os.path.join(base_path, item))\n return paths","def walkdirs(root):\r\n scriptype_paths = collections.defaultdict(set)\r\n for root, subdirs, files in os.walk(root):\r\n\r\n # Filter subdirs\r\n tmpdir = []\r\n for i in subdirs:\r\n if i.startswith(EXCLUDE_PATTERNS):\r\n continue\r\n if '__init__.py' in os.listdir(os.path.join(root, i)):\r\n scriptype_paths['python'].add(root)\r\n continue\r\n tmpdir.append(i)\r\n subdirs[:] = tmpdir\r\n\r\n # If files with extension exists add to right source type.\r\n if ext_exists('.py', files):\r\n scriptype_paths['python'].add(root)\r\n if ext_exists('.mel', files):\r\n scriptype_paths['mel'].add(root)\r\n return scriptype_paths","def get_wavs_dict_list(test_dir):\n # Find all clean files and make an {id: filepath} dictionary\n clean_wavs = glob.glob(os.path.join(test_dir, \"clean/*.wav\"))\n clean_dic = make_wav_id_dict(clean_wavs)\n # Same for noisy files\n noisy_wavs = glob.glob(os.path.join(test_dir, \"noisy/*.wav\"))\n noisy_dic = make_wav_id_dict(noisy_wavs)\n assert clean_dic.keys() == noisy_dic.keys()\n # Combine both dictionaries\n dict_list = [dict(clean=clean_dic[k], noisy=noisy_dic[k], id=k) for k in clean_dic.keys()]\n return dict_list","def _collect_reads(self, wildcards, _library_name, prefix):\n folder_name = get_ngs_library_folder_name(self.parent.sheets, wildcards.library_name)\n pattern_set_keys = (\"right\",) if prefix.startswith(\"right-\") else (\"left\",)\n seen = []\n for _, path_infix, filename in self.path_gen.run(folder_name, pattern_set_keys):\n path = os.path.join(self.base_path_in, path_infix, filename).format(**wildcards)\n if path in seen:\n print(\"WARNING: ignoring path seen before %s\" % path, file=sys.stderr)\n else:\n seen.append(path)\n yield path","def get_filepaths(directory):\n file_paths = [] # List which will store all of the full filepaths.\n\n # Walk the tree.\n\n for root, directories, files in os.walk(directory):\n\n for filename in files:\n if filename.endswith('.wav'):\n # Join the two strings in order to form the full filepath.\n filepath = os.path.join(root, filename)\n file_paths.append(filepath) # Add it to the list.\n # pdb.set_trace()\n file_paths.sort()\n return file_paths","def get_all_files(samples, directory, suffix=\"\", nested=False):\n files = []\n if type(directory) == list:\n directory = directory[0]\n for sample in samples:\n for unit in samples[sample].keys():\n if nested:\n d = \"{}/{}_{}\".format(directory, sample, unit)\n else:\n d = \"{}\".format(directory)\n if is_pe(samples[sample][unit]):\n files.append(d+\"/{}_{}_pe{}\".format(sample, unit, suffix))\n else:\n files.append(d+\"/{}_{}_se{}\".format(sample, unit, suffix))\n return files","def get_all_img_paths(path_to_folder):\n all_subfolders = glob.glob(path_to_folder + '*')\n all_paths = []\n for folder in all_subfolders:\n all_paths.extend(glob.glob(folder + '/*'))\n # get relative paths\n common_prefix = path_to_folder\n relative_paths = [os.path.relpath(path, common_prefix) for path in all_paths]\n return relative_paths","def process_folder(root, path=\"\"):\n myDict = {}\n if path:\n if root.cd(path):\n for key in ROOT.gDirectory.GetListOfKeys():\n filterKey(root, key, path, myDict, \"__List\")\n else:\n for key in ROOT.gDirectory.GetListOfKeys():\n mypath = ROOT.gDirectory.GetPathStatic()\n filterKey(root, key, mypath, myDict, \"\")\n ROOT.gDirectory.cd(mypath)\n return myDict","def load_slurm_folder(p):\n filter_function = lambda f: True if \".out\" in f else False\n slurm_dict = {\"runs\": []}\n for f in filter(filter_function, os.listdir(p)):\n slurm_dict[\"runs\"].append(load_slurm_data(os.path.join(p, f)))\n exit(\"Success!\")","def _resolvePathPatterns(self, sources, source):\n kept = []\n pattern = re.compile(source['pathPattern'])\n basedir = self._basePath / source['path']\n if (self._basePath.name == Path(self._largeImagePath).name and\n (self._basePath.parent / source['path']).is_dir()):\n basedir = self._basePath.parent / source['path']\n basedir = basedir.resolve()\n for entry in basedir.iterdir():\n match = pattern.search(entry.name)\n if match:\n if entry.is_file():\n kept.append((entry.name, entry, match))\n elif entry.is_dir() and (entry / entry.name).is_file():\n kept.append((entry.name, entry / entry.name, match))\n for idx, (_, entry, match) in enumerate(sorted(kept)):\n subsource = copy.deepcopy(source)\n # Use named match groups to augment source values.\n for k, v in match.groupdict().items():\n if v.isdigit():\n v = int(v)\n if k.endswith('1'):\n v -= 1\n if '.' in k:\n subsource.setdefault(k.split('.', 1)[0], {})[k.split('.', 1)[1]] = v\n else:\n subsource[k] = v\n subsource['path'] = entry\n for axis in self._axesList:\n stepKey = '%sStep' % axis\n valuesKey = '%sValues' % axis\n if stepKey in source:\n if axis in source or valuesKey not in source:\n subsource[axis] = subsource.get(axis, 0) + idx * source[stepKey]\n else:\n subsource[valuesKey] = [\n val + idx * source[stepKey] for val in subsource[valuesKey]]\n del subsource['pathPattern']\n sources.append(subsource)","def extract_from_dir(self, data_dir):\n data_paths = []\n for(dirpath, dirnames, filenames) in os.walk(data_dir):\n for file in filenames:\n # Make sure that we don't get garbage files\n file_type = file.split('.')\n if len(file_type) == 1 or (file_type[1] not in ['wav', 'txt']):\n continue\n\n data_paths.append(os.path.join(dirpath, file))\n\n return data_paths","def src_dir(path=None, base=None, subdir=None, max_levels=100):\n path = path or _get_caller_path()\n return _data_science_dir(\n path=path, dirname='src', base=base,\n subdir=subdir, max_levels=max_levels)","def _load_files(self):\n files = {}\n for fn_ in self.opts[\"src\"]:\n if os.path.isfile(fn_):\n files.update(self._file_dict(fn_))\n elif os.path.isdir(fn_):\n salt.utils.stringutils.print_cli(\n \"{} is a directory, only files are supported \"\n 'in non-chunked mode. Use \"--chunked\" command '\n \"line argument.\".format(fn_)\n )\n sys.exit(1)\n return files","def get_sample(self, path, prefix) -> List:\n pass","def _get_script_paths_from_folders_node(self) -> typing.Generator:\r\n for folder_node in filter(is_folder_node, self.folders_node):\r\n self.try_fix_namespace_path(folder_node)\r\n\r\n attr_no_recurse: bool = folder_node.get(XmlAttributeName.NO_RECURSE) == 'True'\r\n\r\n folder_path: str = folder_node.text\r\n\r\n # handle . and .. in path\r\n if folder_path == os.pardir or startswith(folder_path, os.pardir):\r\n folder_path = folder_path.replace(os.pardir, os.path.normpath(os.path.join(self.project_path, os.pardir)), 1)\r\n yield from PathHelper.find_script_paths_from_folder(folder_path,\r\n no_recurse=attr_no_recurse)\r\n continue\r\n\r\n if folder_path == os.curdir or startswith(folder_path, os.curdir):\r\n folder_path = folder_path.replace(os.curdir, self.project_path, 1)\r\n yield from PathHelper.find_script_paths_from_folder(folder_path,\r\n no_recurse=attr_no_recurse)\r\n continue\r\n\r\n if startswith(folder_path, self.remote_schemas, ignorecase=True):\r\n local_path = self._get_remote_path(folder_node)\r\n PapyrusProject.log.info(f'Adding import path from remote: \"{local_path}\"...')\r\n self.import_paths.insert(0, local_path)\r\n PapyrusProject.log.info(f'Adding folder path from remote: \"{local_path}\"...')\r\n yield from PathHelper.find_script_paths_from_folder(local_path,\r\n no_recurse=attr_no_recurse)\r\n continue\r\n\r\n folder_path = os.path.normpath(folder_path)\r\n\r\n # try to add absolute path\r\n if os.path.isabs(folder_path) and os.path.isdir(folder_path):\r\n yield from PathHelper.find_script_paths_from_folder(folder_path,\r\n no_recurse=attr_no_recurse)\r\n continue\r\n\r\n # try to add project-relative folder path\r\n test_path = os.path.join(self.project_path, folder_path)\r\n if os.path.isdir(test_path):\r\n # count scripts to avoid issue where an errant `test_path` may exist and contain no sources\r\n # this can be a problem if that folder contains sources but user error is hard to fix\r\n test_passed = False\r\n\r\n user_flags = wcmatch.RECURSIVE if not attr_no_recurse else 0x0\r\n matcher = wcmatch.WcMatch(test_path, '*.psc', flags=wcmatch.IGNORECASE | user_flags)\r\n for _ in matcher.imatch():\r\n test_passed = True\r\n break\r\n\r\n if test_passed:\r\n yield from PathHelper.find_script_paths_from_folder(test_path,\r\n no_recurse=attr_no_recurse,\r\n matcher=matcher)\r\n continue\r\n\r\n # try to add import-relative folder path\r\n for import_path in self.import_paths:\r\n test_path = os.path.join(import_path, folder_path)\r\n if os.path.isdir(test_path):\r\n yield from PathHelper.find_script_paths_from_folder(test_path,\r\n no_recurse=attr_no_recurse)","def from_folder(self, folder, include=None, exclude=None):\n\n self.folder = folder\n self.include = include\n self.exclude = exclude\n\n filepaths = []\n\n # crawl files in subfolders \n for root, dirs, files in os.walk(self.folder):\n for file in files:\n filepath = os.path.join(root, file)\n \n add_filepath = True\n if self.include is not None:\n add_filepath = any((_inc in filepath\n for _inc in self.include))\n if add_filepath:\n if self.exclude is not None:\n add_filepath = all((_exc not in filepath\n for _exc in self.exclude))\n\n if add_filepath:\n #append the file name to the list of paths\n filepaths.append(filepath)\n\n self._obj['filepath'] = filepaths\n \n return self","def discover_examples():\n root = './examples'\n for filename in os.listdir(root):\n if os.path.splitext(filename)[1] == '.py':\n yield os.path.join(root, filename)","def load_transcriptions_and_paths(dirs):\n all_transcriptions = load_and_normalize_transcriptions(dirs)\n\n sections = cut_into_sections_and_normalize_times(all_transcriptions)\n\n audio_paths = [ospj(dirs[\"data_in_dir\"], \"fgad\", \"fg_ad_seg\" + str(i)) for i in range(8)]\n\n return zip(sections, audio_paths)","def features_from_folder(label_folder, audio_folder, output_folder):\n print('Listing label files from folder.')\n #scan labels folder\n labels_list = os.listdir(label_folder)\n label_files = []\n for filename in labels_list:\n #get its extension\n file_extension = filename.split('.')[-1]\n if file_extension != 'txt':\n continue\n #save to without its extension\n label_files.append(filename[:-4])\n\n print('Listing audio files from folder.')\n #scan audio folder\n audios_list = os.listdir(audio_folder)\n audio_files = []\n for filename in audios_list:\n #get its extension\n file_extension = filename.split('.')[-1]\n if file_extension != 'wav':\n continue\n #save to without its extension\n audio_files.append(filename[:-4])\n\n print('Removing files without matches')\n #use only the files with matching audio/label\n files_to_process = []\n for label_file in label_files:\n if label_file in audio_files:\n files_to_process.append(label_file)\n\n print('Processing each file...')\n i = 1\n class_count = {}\n total_f = len(files_to_process)\n #for each file\n for processing in files_to_process:\n print('File', str(i) + '/' + str(total_f))\n i += 1\n\n #\n label_file = os.path.join(label_folder, processing + \".txt\")\n audio_file = os.path.join(audio_folder, processing + \".wav\")\n\n #get the segments from the corresponding label file\n segments = get_segments(label_file)\n\n #\n total_s = len(segments)\n j = 1\n #for each segment\n for segment in segments:\n print('\\tSegment', str(j) + '/' + str(total_s), segment['class'])\n j += 1\n\n if class_count.get(segment['class']) is None:\n class_count[segment['class']] = 1\n else:\n class_count[segment['class']] += 1\n output_filename = segment['class']\n output_filename += '-' + format(class_count[segment['class']], '04d')\n output_filename = os.path.join(output_folder, output_filename)\n\n #get its features\n segment_features = features_from_label(audio_file, segment)\n\n #save it to a file\n fe.write_as_bin(output_filename, segment_features)","def read_dir(self, path, process_zone, prefix=\"\"):\n\n zones = {}\n for entry in os.listdir(path):\n fullpath = os.path.join(path, entry)\n if os.path.isdir(fullpath):\n zones.update(self.read_dir(fullpath, process_zone, os.path.join(prefix, entry)))\n elif prefix != \"\":\n filename = os.path.join(prefix, entry)\n zones[filename[:-4]] = process_zone(filename)\n return zones","def parse_folder(self, path):\n\n for filename in os.listdir(path):\n self.parse_file(os.path.join(path, filename), filename)\n return self.relations","def path_generator(initial_root):\n for root, dirs, files in os.walk(initial_root):\n paths = [os.path.join(root, name) for name in files]\n return paths","def _get_result_paths(self, data):\r\n\r\n result = {}\r\n\r\n inp_file_name = str(self.Parameters['--query_NAST'].Value)\r\n inp_file_name = inp_file_name.rstrip('\"')\r\n inp_file_name = inp_file_name.lstrip('\"')\r\n\r\n exec_dir = self.Parameters['--exec_dir']\r\n if exec_dir.isOn():\r\n exec_dir = str(exec_dir.Value)\r\n exec_dir = exec_dir.lstrip('\"')\r\n exec_dir = exec_dir.rstrip('\"')\r\n\r\n if inp_file_name[0] == '/':\r\n # path is already absolute\r\n pass\r\n else:\r\n inp_file_name = exec_dir + \"/\" + inp_file_name\r\n\r\n if not exists(inp_file_name + \".CPS.CPC\"):\r\n raise ApplicationError(\"Calling ChimeraSlayer failed.\")\r\n\r\n result['CPS'] = ResultPath(Path=inp_file_name + \".CPS.CPC\",\r\n IsWritten=True)\r\n return result","def get_sar_paths(directory_path: str) -> list:\n dataset_path = Path(directory_path)\n\n path_generator = dataset_path.rglob('*.tif')\n paths = sorted([path for path in path_generator if path.is_file()])\n return [sar_set(*g) for k, g in groupby(paths, key=lambda path: re.match(TYPE_REGEX, path.name)[2])]","def find_wavs(directory, pattern='**/*.wav'):\n return glob(os.path.join(directory, pattern), recursive=True)","def get_filenames(self, root_folder):\n t_images = []\n t_labels = []\n v_images = []\n v_labels = []\n if not os.path.isfile('filenames.p'):\n for dirName, subdirList, fileList in os.walk(root_folder):\n print('Collecting ' + dirName)\n files = [fname for fname in fileList]\n if len(files) > 0:\n if 'Depth' in dirName:\n if any(subj in dirName for subj in self.val_subjects):\n v_labels.extend([os.path.join(dirName, fname) for fname in fileList])\n else:\n t_labels.extend([os.path.join(dirName, fname) for fname in fileList])\n elif 'Color' in dirName:\n if any(subj in dirName for subj in self.val_subjects):\n v_images.extend([os.path.join(dirName, fname) for fname in fileList])\n else:\n t_images.extend([os.path.join(dirName, fname) for fname in fileList])\n pickle.dump([sorted(t_images), sorted(t_labels), sorted(v_images), sorted(v_labels)], open('filenames.p', 'wb'))\n return sorted(t_images), sorted(t_labels), sorted(v_images), sorted(v_labels)\n else:\n return pickle.load(open('filenames.p', 'rb'))","def to_sources(todos):\n for subtodos in todos.iter_sourced():\n to_path(subtodos, subtodos.get_source())","def _get_file_paths(self):\n return [os.path.join(self.path, self.mode, 'waveforms', file_name + '.npy') for file_name in self.file_names]","def parse_folder(self, path):\n\n data = []\n for filename in os.listdir(path):\n data.append(self.parse_file(os.path.join(path, filename), filename))\n return data","def _load_paths(self):\n ts_paths_map = {}\n for path in Path(self.datadir).rglob(\"roas.*.json.gz\"):\n path = str(path)\n ts = int(path.split(\"/\")[-1].split(\".\")[2])\n ts_paths_map[ts] = path\n return ts_paths_map","def get_datapaths(input_dir):\n image_paths = []\n assert os.path.isdir(input_dir), f\"{input_dir} is not existed\"\n\n for root, _, names in os.walk(input_dir):\n for name in names:\n path = os.path.join(root, name)\n image_paths.append(path)\n return image_paths","def _get_psc_paths(self) -> dict:\r\n object_names: dict = {}\r\n\r\n def add_object_name(p: str) -> None:\r\n object_names[p if not os.path.isabs(p) else self._calculate_object_name(p)] = p\r\n\r\n # try to populate paths with scripts from Folders and Scripts nodes\r\n if self.folders_node is not None:\r\n for path in self._get_script_paths_from_folders_node():\r\n add_object_name(path)\r\n\r\n if self.scripts_node is not None:\r\n for path in self._get_script_paths_from_scripts_node():\r\n add_object_name(path)\r\n\r\n # convert user paths to absolute paths\r\n for object_name, script_path in object_names.items():\r\n # ignore existing absolute paths\r\n if os.path.isabs(script_path) and os.path.isfile(script_path):\r\n continue\r\n\r\n # try to add existing project-relative paths\r\n test_path = os.path.join(self.project_path, script_path)\r\n if os.path.isfile(test_path):\r\n object_names[object_name] = test_path\r\n continue\r\n\r\n # try to add existing import-relative paths\r\n for import_path in self.import_paths:\r\n if not os.path.isabs(import_path):\r\n import_path = os.path.join(self.project_path, import_path)\r\n\r\n test_path = os.path.join(import_path, script_path)\r\n if os.path.isfile(test_path):\r\n object_names[object_name] = test_path\r\n break\r\n\r\n PapyrusProject.log.info(f'{len(object_names)} unique script paths resolved to absolute paths.')\r\n\r\n return object_names","def samples_in_trial(self, trial_folder):\n files = listdir(join(trial_folder, 'Background'))\n img_files = [x for x in files if x.split(\n '.')[-1] in ('tif', 'jpg', 'png')]\n sample_name_list = [x.split('.')[1] for x in img_files]\n return sample_name_list # like ['12B',]","def scan(root: str, config: dict) -> dict:\n\n extensions = config['extensions']\n exceptions = config['exceptions']\n\n # get list of directories, with their contents (files and sub-directories)\n dirs_by_path = {\n get_path_from_common_root(dir_path, root): (\n dir_path,\n dir_names,\n [name for name in file_names if is_valid_file_name(name, config)]\n )\n for dir_path, dir_names, file_names in os.walk(root)\n }\n\n dirs_by_path = {key: value for key, value in dirs_by_path.items() if value[1] or value[2]}\n\n # get list of file paths\n file_path_list = [\n (file_dir, file_name)\n for file_dir, _, file_names in dirs_by_path.values()\n for file_name in file_names\n ]\n\n files_by_path = {}\n # todo: put below loop contents into function, used in above list comprehension\n for file_dir, file_name_with_extension in file_path_list:\n # todo: remove code file definition from here to allow this to be reused for non-code related files\n # todo: refactor to use inheritable File class instead of named tuple, to be reused for non-code files\n\n if file_name_with_extension in exceptions:\n continue\n\n file = CodeFile(\n imports=[],\n exports=[],\n local_params=[],\n blocks=[],\n dir=file_dir,\n name=file_name_with_extension.rsplit('.', 1)[0],\n extension=file_name_with_extension.rsplit('.', 1)[1]\n )\n\n parse_file(file, config)\n file_no_dupes = remove_duplicate_entries(file)\n\n dir_key = get_path_from_common_root(file_dir, root)\n if dir_key not in files_by_path:\n files_by_path[dir_key] = []\n\n files_by_path[dir_key].append(file_no_dupes)\n\n return {'dirs_by_path': dirs_by_path, 'files_by_path': files_by_path,\n 'starting_point': get_path_from_common_root(root, root)}","def _output_paths(outputs: Dict[str, str]) -> Dict[str, Path]:\n out_paths = dict()\n for name in outputs:\n target_dir = _BASE_PATH / name\n target_dir.mkdir()\n out_paths[name] = target_dir / 'data.json'\n return out_paths","def my_get_paths_to_wavs(self, path):\n if self.label_type == 'original':\n # Just get all files\n return get_paths_to_wavs(path)\n elif self.label_type == 'four':\n # Filter out emotions Excitement and Frustration, leaving only\n # anger, happiness, neutral, sadness.\n new_paths_to_wavs = []\n paths_to_wavs, path_to_noise = get_paths_to_wavs(path)\n for file in paths_to_wavs:\n file_name = os.path.split(file)[1]\n emotion_label = self.get_emotion_label(file_name)\n if emotion_label in ('ang', 'hap', 'neu', 'sad'):\n new_paths_to_wavs.append(file)\n return new_paths_to_wavs, path_to_noise\n else:\n raise ValueError('Unknown label type! Should be either \"original\" for all samples, or \"four\" for anger, '\n 'happiness, neutral, sadness')","def collect_project_source_files():\n source_files = glob.glob(PROJECT_SOURCE_FILES_FOLDER + '/**/*.py', recursive=True)\n # Insert root main.py at the beginning.\n source_files.insert(0, os.path.join(PROJECT_ROOT_FOLDER, 'main.py'))\n return list(map(lambda path: posixpath.join(*path.split('\\\\')), source_files))","def getImmediateSubdirectories(dir):","def parse_animation_path(path, verbose=True):\n output = {}\n\n # Iterate through all possible paths\n for folder_path in os.listdir(path):\n animation_dict = {'transition': [], 'idle': [], 'transition_playback': [], 'idle_playback': [], 'animation_name': \"\"}\n animation_path = path + \"/\" + folder_path\n\n # And only proceed if the animation path is valid\n if is_valid_animation(animation_path, verbose):\n for sub_animation in [\"transition\", \"idle\"]:\n try:\n sub_animation_path = animation_path + \"/\" + sub_animation + \"/\"\n animation_dict['animation_name'] = animation_path\n\n filenames = os.listdir(sub_animation_path)\n frames = [sub_animation_path + frame for frame in filenames if is_image_file(frame)]\n frames.sort()\n animation_dict[sub_animation] = frames\n\n if \"frames\" in filenames:\n with open(sub_animation_path + \"/frames\", \"r\") as f:\n animation_dict[sub_animation + \"_playback\"] = generate_playback_list(f.read())\n except Exception as e:\n print(\"parse_animation_path():\", e)\n\n output[folder_path] = animation_dict\n\n return output","def get_data_file_paths(input_folder: str, data_file_prefix: str = \"\",\n data_file_postfix: str = \".nc\") -> list:\n data_file_paths = list()\n # we look at all subfolders, whatever they are named\n subfolders = get_files(input_folder, keep_path=True, order_numerical=True)\n for subfolder in subfolders:\n data_files = get_files(subfolder, prefix=data_file_prefix,\n postfix=data_file_postfix, keep_path=True,\n order_numerical=True)\n data_file_paths += data_files\n return data_file_paths","def getFilePaths(directory):\r\n\tfor folder, subs, files in os.walk(directory):\r\n\t\tfor filename in files:\r\n\t\t\tyield os.path.join(folder, filename)","def folder(fpath):\n file_paths = glob.glob(fpath + '/*.dat')\n return list(file_paths)","def source_paths(self):\n paths = self.config.get('static_dirs')\n if paths:\n return paths\n return [self.config.get('static_dir')]","def setupSampleDirectories(self):\n self.allSamplesDir = \"%s/%s_all-samples\" % (os.getcwd(),\n self.project2Id)\n if not os.path.exists(self.allSamplesDir):\n os.mkdir(self.allSamplesDir)\n for sampleId,iSample in self.dSamples.items():\n dirSample = \"%s/%s\" % (self.allSamplesDir, sampleId)\n iSample.dir = dirSample\n if not os.path.exists(dirSample):\n os.mkdir(dirSample)\n if self.verbose > 0:\n msg = \"sample directories: %s\" % self.allSamplesDir\n print(msg); sys.stdout.flush()","def _get_files(self):\n # pylint: disable=unused-variable\n for dirpath, __, filenames in os.walk(self.start_location):\n for file_ in filenames:\n if file_.endswith('.py'):\n yield \"{0}{1}\".format(dirpath, file_)","def paired_paths_from_folder(folders, keys, filename_tmpl):\n assert len(folders) == 2, (\n 'The len of folders should be 2 with [input_folder, gt_folder]. '\n f'But got {len(folders)}')\n assert len(keys) == 2, (\n 'The len of keys should be 2 with [input_key, gt_key]. '\n f'But got {len(keys)}')\n input_folder, gt_folder = folders\n input_key, gt_key = keys\n\n input_paths = list(scandir(input_folder))\n gt_paths = list(scandir(gt_folder))\n assert len(input_paths) == len(gt_paths), (\n f'{input_key} and {gt_key} datasets have different number of images: '\n f'{len(input_paths)}, {len(gt_paths)}.')\n paths = []\n for gt_path in gt_paths:\n basename, ext = os.path.splitext(os.path.basename(gt_path))\n input_name = f'{filename_tmpl.format(basename)}{ext}'\n input_path = os.path.join(input_folder, input_name)\n assert input_name in input_paths, (f'{input_name} is not in '\n f'{input_key}_paths.')\n gt_path = os.path.join(gt_folder, gt_path)\n paths.append(\n dict([(f'{input_key}_path', input_path),\n (f'{gt_key}_path', gt_path)]))\n return paths","def GetSongFilenames():\n\n\t## Loop through each directory\n\tsong_files = []\n\tfor root, dirs, fnames in os.walk(\"_data\\\\fma_small\\\\\"):\n\t\t\n\t\t## Skip the first level\n\t\tif root == \"_data\\\\fma_small\\\\\":\n\t\t\tcontinue\n\n\t\t## Otherwise collect the files, appending\n\t\t## the root path.\n\t\tsong_files += [root+\"\\\\\"+f for f in fnames]\n\n\treturn song_files","def find_tryouts(data_dir, prefix):\n filenames = os.listdir(data_dir)\n return sorted(list(map(lambda d: os.path.join(data_dir, d), filter(lambda s: s.startswith(prefix), filenames))))","def filepaths(self, langs) -> Generator[str, None, None]:\n for pv in self.projects(langs):\n yield from pv.filepaths()","def dir_resolution(self, src_path, frag_length=128):\n src_path = os.path.join(self.root_path, src_path)\n files = os.listdir(src_path)\n\n MFCCs = None\n labels = None\n cnt = 1\n total_num = len(files)\n for wav in files:\n wav_path = os.path.join(src_path, wav)\n MFCCs_each, labels_each = self.features_and_labels(wav_path, frag_length)\n if MFCCs is not None:\n MFCCs = torch.cat((MFCCs, MFCCs_each))\n labels = torch.cat((labels, labels_each))\n else:\n MFCCs, labels = MFCCs_each, labels_each\n\n if cnt % 1000 == 0:\n print('{} data pieces have been loaded in and {} are left'.format(cnt, total_num-cnt))\n cnt += 1\n\n np.save(self.feature_file, MFCCs.numpy()) \n np.save(self.label_file, labels.numpy())\n print('Loading into files finished!')","def get_paths(input_folder: str) -> list[str]:\n\n return [f for f in os.listdir(input_folder) if f[-4:] == '.txt' and f[:3] != 'top']"],"string":"[\n \"def extract_folder_file_structure() -> Dict[str, List[str]]:\\n folders_and_files = {}\\n for path_to_folder in glob.glob(f\\\"{ZULIPTERMINAL}/**/\\\", recursive=True):\\n complete_directory_path = Path(path_to_folder)\\n if complete_directory_path.name in FOLDERS_TO_EXCLUDE:\\n continue\\n relative_directory_path = complete_directory_path.relative_to(ROOT_DIRECTORY)\\n if str(relative_directory_path) not in DESC_FOR_NO_FILE_FOLDERS:\\n files_in_directory = [\\n file.name\\n for file in complete_directory_path.glob(\\\"*.py\\\")\\n if file.name != \\\"__init__.py\\\"\\n ]\\n folders_and_files[str(relative_directory_path)] = files_in_directory\\n return folders_and_files\",\n \"def _walk_dirs(self):\\n for project_name in self.new_source_paths.keys():\\n # print \\\"-------- Now mapping ---- \\\" + project_name\\n search_path = self.root + project_name + '\\\\\\\\Data'\\n for dirpath, subdirs, files in os.walk(search_path):\\n for file in files:\\n self.new_source_paths[project_name][file] = dirpath\\n # print \\\"------------ Finished mapping ------- \\\" + project_name\\n return self.new_source_paths\",\n \"def make_example_list_from_folder(\\n folder_sources, subset='all', ss_regex=re.compile(r'example.*_sources'),\\n pattern='_sources', subfolder_events=('background', 'foreground')):\\n example_dict = make_example_dict_from_folder(\\n folder_sources, subset=subset, ss_regex=ss_regex, pattern=pattern,\\n subfolder_events=subfolder_events)\\n example_list = []\\n for subset in example_dict:\\n for example in example_dict[subset]:\\n example_list.append('\\\\t'.join([example] + example_dict[subset][example]))\\n return example_list\",\n \"def incoming_paths(root_dir, parent_dir):\\n return {\\n 'F1' : os.path.join(root_dir, \\\"F1\\\"),\\n 'F' : os.path.join(parent_dir, \\\"F\\\"),\\n 'F2' : os.path.join(parent_dir, \\\"F2-in\\\"),\\n 'D1' : os.path.join(root_dir, \\\"D1\\\"),\\n 'D' : os.path.join(parent_dir, \\\"D\\\"),\\n 'D2' : os.path.join(parent_dir, \\\"D2-in\\\"),\\n }\",\n \"def parse_folder(self, path):\\n\\n for filename in os.listdir(path):\\n self.parse_file(os.path.join(path, filename), filename)\\n return self.country_dict, self.hre_dict, self.name_dict\",\n \"def get_paths(input_folder):\\n list_files = []\\n conll_folder = glob.glob(input_folder + '/*.json')\\n \\n for filename in conll_folder:\\n list_files.append(filename)\\n\\n return list_files\",\n \"def get_all_paths(why = 'train'):\\r\\n if why == 'train':\\r\\n parent_folder = train_parent_folder\\r\\n if why == 'test':\\r\\n parent_folder = test_test_folder\\r\\n sub_folders = glob.glob(parent_folder) # Directories of all languages\\r\\n image_paths = [glob.glob(sub_folder + '\\\\*') for sub_folder in sub_folders] # Directories of all characters\\r\\n image_paths = sum(image_paths, []) # Flatten out the 2D list to a 1D list \\r\\n return image_paths\",\n \"def map_audio(self): \\n for root, dirs, files in os.walk(self.dir):\\n for name in files:\\n if (name.split(\\\".\\\")[-1].lower() == 'm4a' or \\\\\\n name.split(\\\".\\\")[-1].lower() == 'mp3'):\\n \\n cur_path = \\\"{0}/{1}\\\".format(root, name)\\n cur_file = auto.File(cur_path)\\n \\n artist = cur_file.artist.lower().strip()\\n album = cur_file.album.lower().strip()\\n title = cur_file.title.lower().strip()\\n bitrate = cur_file.bitrate\\n \\n if not artist in self.audio_dict:\\n self.audio_dict[artist] = {}\\n \\n if not album in self.audio_dict[artist]:\\n self.audio_dict[artist][album] = {}\\n \\n title_key = title\\n for in_album_title in self.audio_dict[artist][album]:\\n if sm(None, title, in_album_title).ratio() > 0.9:\\n title_key = in_album_title\\n \\n if not title_key in \\\\\\n self.audio_dict[artist][album]:\\n self.audio_dict[artist][album][title_key] = []\\n \\n self.audio_dict[artist][album][title_key].append({\\n 'path': cur_path,\\n 'bitrate': bitrate,\\n 'file_name': name\\n })\\n \\n return self\",\n \"def parse_paths():\\r\\n sources = get_source_paths()\\r\\n results = collections.defaultdict(list)\\r\\n for root_dir in sources:\\r\\n\\r\\n for script_type, dirs in walkdirs(root_dir).iteritems():\\r\\n\\r\\n for d in dirs:\\r\\n logger.debug(d)\\r\\n\\r\\n # Add paths to environments\\r\\n if os.path.basename(d).lower().startswith(ICONS):\\r\\n results['XBMLANGPATH'].append(d)\\r\\n os.environ['XBMLANGPATH'] += os.pathsep + d\\r\\n\\r\\n if script_type == 'mel':\\r\\n results['MAYA_SCRIPT_PATH'].append(d)\\r\\n os.environ['MAYA_SCRIPT_PATH'] += os.pathsep + d\\r\\n else:\\r\\n results['PYTHONPATH'].append(d)\\r\\n site.addsitedir(d)\\r\\n return results\",\n \"def read_base_folder(base_path: str) -> dict:\\n\\tfour_x_images: dict = {}\\n\\tfor file in listdir(four_x_file_path):\\n\\t\\tfile_extension = os.path.splitext(file)[1]\\n\\t\\tif file_extension in image_extensions:\\n\\t\\t\\tfour_x_images[file] = join(base_path, file)\\n\\treturn four_x_images\",\n \"def getpaths_fromdir(input_prefix_, directory_):\\n path = os.path.join(input_prefix_, \\\"%s*\\\" % directory_, \\\"*\\\")\\n return [tuple([directory_, path])]\",\n \"def get_file_paths():\\n audio_folder = MY_DIR + '/assets'\\n\\n audio_addy_list = []\\n for file in os.scandir(audio_folder):\\n audio_addy_list.append(file.path)\\n\\n return audio_addy_list\",\n \"def list_files_in_directory(self):\\n lesson_file_dict = dict()\\n lesson_file_dict[\\\"files\\\"] = []\\n\\n directory_list = listdir(self.sub_dir)\\n for directory in directory_list:\\n if isfile(join(self.sub_dir, directory)):\\n lesson_file_dict[\\\"files\\\"].append(directory)\\n\\n return lesson_file_dict\",\n \"def prep_files(app):\\n smali_paths = []\\n start = time.time()\\n \\n for root, dirs, files in os.walk(app, topdown=False):\\n for name in files:\\n if name[-6:] == \\\".smali\\\":\\n smali_paths.append(str(os.path.join(root, name)))\\n \\n return smali_paths\",\n \"def samples_path():\\n dir = os.path.dirname(os.path.abspath(__file__))\\n samples = os.path.join(dir, 'samples')\\n return samples\",\n \"def get_data(folder_name):\\n train_data = {}\\n for study_id, study_path in sorted(get_studies(folder_name)):\\n train_data[study_id] = get_slices(study_id, study_path)\\n return train_data\",\n \"def _get_project_names(self):\\n for folder in os.listdir(self.root):\\n if folder[0].isdigit():\\n try:\\n self.new_source_paths[folder]\\n pass\\n except:\\n self.new_source_paths[folder] = {}\\n return self.new_source_paths\",\n \"def load_data(self):\\r\\n if not os.path.exists(self.origin_dir):\\r\\n raise ValueError(f\\\"Folder {self.origin_dir} not exists!\\\")\\r\\n\\r\\n # loop folders\\r\\n listglobs = glob.glob(os.path.join(self.origin_dir)+r\\\"[0-9]*\\\")\\r\\n count = 0\\r\\n temp = []\\r\\n for x in listglobs:\\r\\n\\r\\n # step1, get speaker id md5\\r\\n user_id = x.rsplit(\\\"\\\\\\\\\\\")[-1]\\r\\n speaker_id = hashlib.md5(user_id.encode(\\\"utf-8\\\")).hexdigest()\\r\\n self.wav_desc[\\\"speaker_id\\\"] = speaker_id\\r\\n print(\\\"1=>\\\", x)\\r\\n\\r\\n for k in [\\\"你好小顺\\\", \\\"小顺小顺\\\"]:\\r\\n paths = os.path.join(x, k)\\r\\n print(\\\"2=>\\\", paths)\\r\\n # step2, parse speaker info\\r\\n with open(os.path.join(paths, \\\"spearker_info.txt\\\"), 'r', encoding=\\\"utf-8\\\") as f:\\r\\n line = f.readline()\\r\\n arrs = line.strip().split(\\\"\\\\\\\\t\\\")\\r\\n if len(arrs) != 3:\\r\\n raise ValueError(\\\"Required three field in speaker_info<id>\\\\t<gender>\\\\t<age>\\\")\\r\\n self.wav_desc[\\\"gender\\\"] = arrs[1].strip(\\\"<\\\").rstrip(\\\">\\\")\\r\\n self.wav_desc[\\\"age\\\"] = arrs[-1].strip(\\\"<\\\").rstrip(\\\">\\\")\\r\\n\\r\\n # step3, parse wav detailed information\\r\\n # key: wav_id, value: info_list, [keyword, noise_type, distance, speed,user_id, equipment]\\r\\n wav_infos_dict = {}\\r\\n with open(os.path.join(paths, \\\"wav_desc.txt\\\"), \\\"r\\\", encoding=\\\"utf-8\\\") as f:\\r\\n for line in f.readlines():\\r\\n arrs = line.strip().split(\\\"\\\\\\\\t\\\")\\r\\n wav_infos_dict[arrs[0].strip(\\\"<\\\").rstrip(\\\">\\\")] = [x.strip(\\\"<\\\").rstrip(\\\">\\\") for\\r\\n x in arrs[1:]]\\r\\n\\r\\n print(f\\\"Parse wav info finished find {len(wav_infos_dict)} infos.\\\")\\r\\n\\r\\n # Step4, audio with background noise and without nose, which was back_wav and wav_data folder\\r\\n for wav_folder in [\\\"back_wav\\\", \\\"wav_data\\\"]:\\r\\n audio_lists = glob.glob(os.path.join(paths + f\\\"\\\\\\\\{wav_folder}\\\", \\\"*.wav\\\"))\\r\\n for xa in audio_lists:\\r\\n # copy data to\\r\\n wav_id, user_id = get_wav_name(xa)\\r\\n # print(wav_id, user_id)\\r\\n # create md5 id\\r\\n utt_id = hashlib.md5(xa.encode(\\\"utf-8\\\")).hexdigest()\\r\\n # speaker_id = hashlib.md5(user_id.encode(\\\"utf-8\\\")).hexdigest()\\r\\n # print(utt_id, speaker_id)\\r\\n # collect all info for an audio\\r\\n self.wav_desc[\\\"utt_id\\\"] = utt_id\\r\\n infos = wav_infos_dict[wav_id]\\r\\n if len(infos) != 6:\\r\\n print(\\\"==>\\\", infos)\\r\\n self.wav_desc[\\\"keyword_id\\\"] = self.keywords_dict[infos[0]]\\r\\n self.wav_desc[\\\"noise_type\\\"] = infos[1]\\r\\n self.wav_desc[\\\"distance\\\"] = infos[2]\\r\\n self.wav_desc[\\\"record_speed\\\"] = infos[3]\\r\\n self.wav_desc[\\\"speaker_id\\\"] = speaker_id\\r\\n self.wav_desc[\\\"record_equipment\\\"] = infos[5]\\r\\n\\r\\n # record wav information\\r\\n t_infos = copy.deepcopy(self.wav_desc)\\r\\n self.all_wavs.append(t_infos)\\r\\n count += 1\\r\\n temp.append(utt_id)\\r\\n\\r\\n # copy data to resource folder\\r\\n dest = shutil.copy2(xa, os.path.join(self.dest_dir, f\\\"audios/{utt_id}.wav\\\"))\\r\\n set_index = which_set(dest, 20, 30)\\r\\n self.data_index[set_index].append(t_infos)\\r\\n\\r\\n # write wav information into json file\\r\\n with open(os.path.join(self.dest_dir, \\\"resources/wav_desc.json\\\"), \\\"w\\\", encoding=\\\"utf-8\\\") as f:\\r\\n json.dump(self.all_wavs, f, ensure_ascii=False, indent=True)\\r\\n print(f\\\"total wavs:{count}, total ids:{len(temp)}\\\")\\r\\n for set_index in self.data_index.keys():\\r\\n with open(os.path.join(self.dest_dir, f\\\"resources/p_{set_index}.json\\\"), \\\"w\\\", encoding=\\\"utf-8\\\") as f:\\r\\n json.dump(self.data_index[set_index], f, ensure_ascii=False, indent=True)\\r\\n print(f\\\"Collect {set_index} data total {len(self.data_index[set_index])} samples.\\\")\",\n \"def filelist(folder):\\n file_dict={}\\n folderlist = glob.glob(os.getcwd()+\\\"/\\\"+folder+\\\"/*\\\")\\n for i in tqdm(folderlist):\\n filelist = glob.glob(i+\\\"/*\\\")\\n filename = i.rsplit(\\\"/\\\")[-1]\\n file_dict[filename]= filelist\\n\\n return file_dict\",\n \"def voicesPathsCollector(source_dir, gender_ids):\\r\\n # The list containing the IDs of the speakers which are the folder names\\r\\n person_ids_list = gender_ids\\r\\n\\r\\n # An empty list which it will contains voices paths which are in the section folders\\r\\n voices_paths_list = []\\r\\n\\r\\n # Iterating over a person speaker ids\\r\\n for person_id_idx in range(len(person_ids_list)):\\r\\n # Speaker path containing the chapter's directories\\r\\n speaker_path = Path.cwd().joinpath(source_dir, person_ids_list[person_id_idx])\\r\\n # The list containing the IDs of the sections by the current speaker which are the folder names\\r\\n sections_ids_list = os.listdir(speaker_path)\\r\\n\\r\\n # Iterating over a sections ids by the current speaker\\r\\n for sec_id_idx in range(len(sections_ids_list)):\\r\\n # Section path containing files\\r\\n section_path = Path.cwd().joinpath(speaker_path,sections_ids_list[sec_id_idx])\\r\\n # Iterating over files which are existing in section's folders\\r\\n for file in os.listdir(section_path):\\r\\n # Choose files with .flac extension\\r\\n if file.endswith(\\\".flac\\\"):\\r\\n\\r\\n voice_path = Path.cwd().joinpath(section_path, file)\\r\\n voices_paths_list.append(voice_path)\\r\\n\\r\\n return voices_paths_list\",\n \"def getSourcePaths(self, makeGlyphs=True, makeKerning=True, makeInfo=True):\\n paths = []\\n for name in self.sources.keys():\\n paths.append(self.sources[name][0].path)\\n return paths\",\n \"def get_paths_list_from_folder(folder):\\n names = os.listdir(folder)\\n relative_paths = [os.path.join(folder, image_name) for image_name in names]\\n return relative_paths\",\n \"def _get_sourceFolders(self, dom):\\n return self._get_new_module_root_manager(dom).getElementsByTagName('sourceFolder')\",\n \"def get_filepaths(extract_dir):\\n\\n index = []\\n labels = []\\n _extract_dir = os.path.join(extract_dir, 'UCF-101')\\n for folder in os.listdir(_extract_dir):\\n labels.append(folder)\\n folderpath = os.path.join(_extract_dir, folder)\\n\\n if not os.path.isdir(folderpath):\\n continue\\n\\n for filename in os.listdir(folderpath):\\n if 'avi' not in filename:\\n continue\\n\\n if filename[0] == '.':\\n continue\\n\\n filepath = os.path.join(folderpath, filename)\\n\\n if os.path.exists(filepath):\\n index.append(filepath)\\n else:\\n print(filepath)\\n return index, labels\",\n \"def get_samples_file(foldername, filter=None):\\n samples = []\\n for file in os.listdir(foldername):\\n if filter and file.find(filter) == -1:\\n continue\\n for sample in sfile(foldername + '/' + file, None).get_samples():\\n samples.append(sample)\\n return samples\",\n \"def read_process_labelled(src_dir, window=0.2, overlap=0.5, debug=True):\\n\\n arr_features = []\\n\\n # Read files from the folders\\n for x, _ in GENRES.items():\\n folder = src_dir + x\\n \\n for root, subdirs, files in os.walk(folder):\\n for file in files:\\n # Read the audio file\\n file_name = folder + \\\"/\\\" + file\\n signal, sr = librosa.load(file_name)\\n signal = signal[:660000]\\n \\n # Debug process\\n if debug:\\n print(f\\\"Reading file: {file_name}\\\")\\n \\n # Split songs:\\n samples = split_songs(signal, window, overlap)\\n\\n # Append the result to the data structure\\n for s in samples:\\n features = get_features(s, sr)\\n features['genre'] = GENRES[x]\\n arr_features.append(features)\\n\\n return arr_features\",\n \"def get_realization_paths(rootdir, folder_prefix): #{{{\\n fnames = []\\n for root, dirs, files in os.walk(rootdir):\\n if(root=='.'):\\n dirs.sort()\\n for adir in dirs:\\n if(adir.startswith(folder_prefix)):\\n fnames.append(rootdir + '/' + adir)\\n\\n return fnames #}}}\",\n \"def read_from_folder(folder):\\n\\n raw_dict = dict()\\n\\n for file in os.listdir(folder):\\n raw = read_raw_from_file(os.path.join(folder, file))\\n raw_dict[file] = raw\\n\\n return raw_dict\",\n \"def sources_relative_to_buildroot(self):\\r\\n for src in self.sources:\\r\\n yield os.path.join(self.target_base, src)\",\n \"def agg_paths(dataset_root_dir):\\n root_dir_p = Path(dataset_root_dir)\\n experiment_dirs = sorted([e for e in root_dir_p.iterdir()])\\n \\n left_paths=[]\\n right_paths=[]\\n occl_paths=[]\\n disparity_paths=[]\\n depth_paths=[] \\n calib_paths=[]\\n sample_name=[]\\n\\n for experiment in experiment_dirs:\\n modality_gt_dirs = sorted([gt_dir for gt_dir in experiment.iterdir() if 'Ground_truth' in gt_dir.name])\\n for modality_gt_dir in modality_gt_dirs:\\n occl_paths.extend(sorted([p.resolve()\\n for p in (modality_gt_dir/'OcclusionL').iterdir()]))\\n disparity_paths.extend(sorted([p.resolve()\\n for p in (modality_gt_dir/'Disparity').iterdir()]))\\n depth_paths.extend(sorted([p.resolve()\\n for p in (modality_gt_dir/'DepthL').iterdir()]))\\n \\n \\n left_paths.extend(sorted([(experiment/'Left_rectified'/p.name).resolve()\\n for p in (modality_gt_dir/'OcclusionL').iterdir()]))\\n right_paths.extend(sorted([(experiment/'Right_rectified'/p.name).resolve()\\n for p in (modality_gt_dir/'OcclusionL').iterdir()]))\\n calib_paths.extend(sorted([(experiment/'Rectified_calibration'/(p.stem+'.json')).resolve()\\n for p in (modality_gt_dir/'OcclusionL').iterdir()]))\\n sample_name.extend(sorted([(p.parents[2]).name+' - ' + (p.parents[1]).name.split('_')[-1]+ ' - '+p.stem for p in (modality_gt_dir/'Disparity').iterdir()])) \\n return {'left': left_paths,\\n 'right': right_paths,\\n 'occ': occl_paths,\\n 'disparity': disparity_paths,\\n 'depth': depth_paths,\\n 'calib': calib_paths,\\n 'name': sample_name}\",\n \"def get_folders_content(path):\\n folder_contents = {}\\n for folder_name, folder in zip(json_names, experiment_folders(path)):\\n if not folder.exists():\\n raise RuntimeError(\\n f\\\"The {folder_name} folder doesn' exist in the\\\" \\\" specified path\\\"\\n )\\n\\n folder_contents[folder_name] = folder.glob(\\\"*\\\")\\n return folder_contents\",\n \"def extract_embeddings_recursive_from_dir(self, dir_from: PathLike, dir_to: PathLike) -> PathLike:\\n pass\",\n \"def target_folders(metadata, analysistype):\\n # Initialise variables\\n targetfolders = set()\\n targetfiles = list()\\n records = dict()\\n for sample in metadata:\\n if sample[analysistype].combinedtargets != 'NA':\\n targetfolders.add(sample[analysistype].targetpath)\\n for targetdir in targetfolders:\\n # Find all the .fasta files in each target folder\\n targetfiles = glob(os.path.join(targetdir, '*.fasta'))\\n for targetfile in targetfiles:\\n # Read the sequences from the target file to a dictionary\\n records[targetfile] = SeqIO.to_dict(SeqIO.parse(targetfile, 'fasta'))\\n return targetfolders, targetfiles, records\",\n \"def get_all_file_paths_labels(data_root: str) -> list:\\n\\n speaker_dirs = os.listdir(data_root)\\n all_files = []\\n i = 0\\n for d in speaker_dirs:\\n files = glob.iglob(data_root + '/' + d + '/**/*.wav', recursive=True)\\n files = [[f, i] for f in files]\\n all_files += files\\n i += 1\\n all_files = sorted(all_files, key=lambda x:x[0], reverse=False)\\n\\n return all_files\",\n \"def parse(cls, raw_folder: str) -> Dict[str, Any]:\\n folder_path = os.path.abspath(raw_folder)\\n data = dict()\\n files = os.listdir(folder_path)\\n for file in files:\\n if is_ignored(file):\\n continue\\n try:\\n file = os.path.join(raw_folder, file)\\n datum = cls.process_file(file)\\n except FileNotCompatible:\\n continue\\n\\n _, kwrd = os.path.split(file)\\n kwrd = os.path.splitext(kwrd)[0]\\n data[kwrd] = datum\\n\\n return data\",\n \"def get_dir_files(self, recursive=False):\\n logging.info('Enumerating files under the source path (recursive=%s) ...', recursive)\\n files = {}\\n if not recursive:\\n files[self.path_source] = [\\n f for f in os.listdir(self.path_source) if os.path.isfile(os.path.join(self.path_source, f))\\n ]\\n else:\\n for current_dir, sub_dirs, dir_files in os.walk(self.path_source):\\n files[os.path.join(self.path_source, current_dir)] = [f for f in dir_files]\\n\\n return files\",\n \"def get_training_data_directories():\\n\\n\\tmapping = dict()\\n\\tmapping[ASCause.apsp] = directories.training_cause_apsp\\n\\tmapping[ASCause.bl] = directories.training_cause_bl\\n\\tmapping[ASCause.ce] = directories.training_cause_ce\\n\\tmapping[ASCause.dfl] = directories.training_cause_dfl\\n\\tmapping[ASCause.lrssi] = directories.training_cause_lrssi\\n\\tmapping[ASCause.pscan_assoc] = directories.training_cause_pscan_assoc\\n\\tmapping[ASCause.pscan_unassoc] = directories.training_cause_pscan_unassoc\\n\\tmapping[ASCause.pwr_state] = directories.training_cause_pwr_state\\n\\treturn mapping\",\n \"def relative_to_buildroot(self):\\n return [os.path.join(self.rel_path, source) for source in self.source_paths]\",\n \"def sources_under(self, base_dir):\\n if '*' in base_dir or '?' in base_dir or '[' in base_dir:\\n for d in sorted(fnmatch.filter(self.keys(), base_dir)):\\n yield self[d]\\n else:\\n base_dir_sep = base_dir + os.sep\\n for d, s in sorted(self.items()):\\n if d == base_dir or d.startswith(base_dir_sep):\\n yield s\",\n \"def examples_paths():\\n data_dir = utils.get_data_filename(os.path.join('tests', 'data'))\\n p_xylene_dir = os.path.join(data_dir, 'p-xylene-implicit')\\n p_xylene_gro_dir = os.path.join(data_dir, 'p-xylene-gromacs-example')\\n ben_tol_dir = os.path.join(data_dir, 'benzene-toluene-explicit')\\n abl_imatinib_dir = os.path.join(data_dir, 'abl-imatinib-explicit')\\n tol_dir = os.path.join(data_dir, 'toluene-explicit')\\n benz_tol_dir = os.path.join(data_dir, 'benzene-toluene-standard-state')\\n\\n paths = dict()\\n paths['lysozyme'] = os.path.join(p_xylene_dir, '181L-pdbfixer.pdb')\\n paths['p-xylene'] = os.path.join(p_xylene_dir, 'p-xylene.mol2')\\n paths['benzene'] = os.path.join(ben_tol_dir, 'benzene.tripos.mol2')\\n paths['toluene'] = os.path.join(ben_tol_dir, 'toluene.tripos.mol2')\\n paths['abl'] = os.path.join(abl_imatinib_dir, '2HYY-pdbfixer.pdb')\\n paths['imatinib'] = os.path.join(abl_imatinib_dir, 'STI02.mol2')\\n paths['bentol-complex'] = [os.path.join(ben_tol_dir, 'complex.prmtop'),\\n os.path.join(ben_tol_dir, 'complex.inpcrd')]\\n paths['bentol-solvent'] = [os.path.join(ben_tol_dir, 'solvent.prmtop'),\\n os.path.join(ben_tol_dir, 'solvent.inpcrd')]\\n paths['pxylene-complex'] = [os.path.join(p_xylene_gro_dir, 'complex.top'),\\n os.path.join(p_xylene_gro_dir, 'complex.gro')]\\n paths['pxylene-solvent'] = [os.path.join(p_xylene_gro_dir, 'solvent.top'),\\n os.path.join(p_xylene_gro_dir, 'solvent.gro')]\\n paths['pxylene-gro-include'] = os.path.join(p_xylene_gro_dir, 'top')\\n paths['toluene-solvent'] = [os.path.join(tol_dir, 'solvent.pdb'),\\n os.path.join(tol_dir, 'solvent.xml')]\\n paths['toluene-vacuum'] = [os.path.join(tol_dir, 'vacuum.pdb'),\\n os.path.join(tol_dir, 'vacuum.xml')]\\n paths['benzene-toluene-boxless'] = [os.path.join(benz_tol_dir, 'standard_state_complex_boxless.inpcrd'),\\n os.path.join(benz_tol_dir, 'standard_state_complex.prmtop')]\\n paths['benzene-toluene-nan'] = [os.path.join(benz_tol_dir, 'standard_state_complex_nan.inpcrd'),\\n os.path.join(benz_tol_dir, 'standard_state_complex.prmtop')]\\n return paths\",\n \"def create_sample_dictionary(sample_path):\\n sample_dict = {'_'.join(sample_path.split('/')[-1].split('.')[0].split('_')[:-1]) : sc.read(sample_path)}\\n return sample_dict\",\n \"def get_pathes(self) -> Dict[str, str]:\\n\\n pathes: Dict[str, str] = {}\\n\\n for path in self.files:\\n name = path.split(\\\"/\\\")[-1].split(\\\".\\\")[0]\\n pathes[name] = os.path.join(self.home_folder, path)\\n return pathes\",\n \"def map_files(key):\\n \\n datadir=os.path.join(os.path.dirname(__file__),'ncnr_sample_data')\\n filedict={'empty_1m':os.path.join(datadir,'SILIC001.SA3_SRK_S101'),\\n 'empty_4m':os.path.join(datadir,'SILIC002.SA3_SRK_S102'),\\n 'empty_cell_1m':os.path.join(datadir,'SILIC003.SA3_SRK_S103'),\\n 'blocked_1m':os.path.join(datadir,'SILIC004.SA3_SRK_S104'),\\n 'trans_empty_cell_4m':os.path.join(datadir,'SILIC005.SA3_SRK_S105'),\\n 'trans_sample_4m':os.path.join(datadir,'SILIC006.SA3_SRK_S106'),\\n 'blocked_4m':os.path.join(datadir,'SILIC007.SA3_SRK_S107'),\\n 'empty_cell_4m':os.path.join(datadir,'SILIC008.SA3_SRK_S108'),\\n 'sample_1m':os.path.join(datadir,'SILIC009.SA3_SRK_S109'),\\n 'sample_4m':os.path.join(datadir,'SILIC010.SA3_SRK_S110'),\\n 'mask':os.path.join(datadir,'DEFAULT.MASK'),\\n 'div':os.path.join(datadir,'PLEX_2NOV2007_NG3.DIV'),\\n }\\n return filedict[key]\",\n \"def _getSoundsFromDirectory(self, directoryPath):\\n files = [f for f in listdir(directoryPath)\\n if isfile(join(directoryPath, f))]\\n for filePath in files:\\n self._soundsDictionary[filePath] = FMOD.FMOD.loadSound(\\n self._formatPath(directoryPath, filePath))\",\n \"def get_all(folder, filter_funs = []) :\\n\\n def apply_funs(x, funs) :\\n \\\"\\\"\\\"Applies the filter functions.\\\"\\\"\\\"\\n res = True\\n for f in funs :\\n res = f(x)\\n if not res :\\n break\\n return res\\n \\n final = {}\\n files = listdir(folder)\\n print(\\\"Loading Spectras\\\")\\n for f in files :\\n try :\\n spectra = Spectra(folder + \\\"/\\\" + f)\\n print(\\\".\\\", end=\\\"\\\")\\n except:\\n continue\\n if spectra == None :\\n continue\\n if not apply_funs(spectra, filter_funs) :\\n continue\\n pot_spectra = final.get(spectra.database_id, None)\\n if not pot_spectra :\\n final[spectra.database_id] = [deepcopy(spectra)]\\n else :\\n pot_spectra.append(deepcopy(spectra))\\n return final\",\n \"def get_folder_filenames(path):\\n result = {}\\n for parent, dirnames, filenames in os.walk(path):\\n if not dirnames:\\n result[os.path.split(parent)[-1]] = filenames\\n return result\",\n \"def collect_files(path, audio_files):\\n\\n for entry in os.scandir(path):\\n if entry.is_dir():\\n collect_files(entry.path, audio_files)\\n if entry.is_file() and (entry.path.endswith(\\\".flac\\\") or entry.path.endswith(\\\".wav\\\")):\\n audio_files.append(entry.path)\",\n \"def prepare_src_folder(self, src_folder: str) -> None:\",\n \"def get_midi_paths(root):\\n\\treturn [os.path.join(dirpath, filename) \\n\\t\\t\\tfor dirpath, _, filenames in os.walk(root) \\n\\t\\t\\tfor filename in filenames \\n\\t\\t\\tif filename.endswith(\\\".mid\\\")]\",\n \"def demo_paths(self):\\n base_path = os.path.join(self.module.__path__[0], 'demo')\\n paths = []\\n if os.path.isdir(base_path):\\n for item in os.listdir(base_path):\\n # TODO: support examples which is not auto-loaded\\n if not os.path.isdir(os.path.join(base_path, 'examples')):\\n paths.append(os.path.join(base_path, item))\\n return paths\",\n \"def walkdirs(root):\\r\\n scriptype_paths = collections.defaultdict(set)\\r\\n for root, subdirs, files in os.walk(root):\\r\\n\\r\\n # Filter subdirs\\r\\n tmpdir = []\\r\\n for i in subdirs:\\r\\n if i.startswith(EXCLUDE_PATTERNS):\\r\\n continue\\r\\n if '__init__.py' in os.listdir(os.path.join(root, i)):\\r\\n scriptype_paths['python'].add(root)\\r\\n continue\\r\\n tmpdir.append(i)\\r\\n subdirs[:] = tmpdir\\r\\n\\r\\n # If files with extension exists add to right source type.\\r\\n if ext_exists('.py', files):\\r\\n scriptype_paths['python'].add(root)\\r\\n if ext_exists('.mel', files):\\r\\n scriptype_paths['mel'].add(root)\\r\\n return scriptype_paths\",\n \"def get_wavs_dict_list(test_dir):\\n # Find all clean files and make an {id: filepath} dictionary\\n clean_wavs = glob.glob(os.path.join(test_dir, \\\"clean/*.wav\\\"))\\n clean_dic = make_wav_id_dict(clean_wavs)\\n # Same for noisy files\\n noisy_wavs = glob.glob(os.path.join(test_dir, \\\"noisy/*.wav\\\"))\\n noisy_dic = make_wav_id_dict(noisy_wavs)\\n assert clean_dic.keys() == noisy_dic.keys()\\n # Combine both dictionaries\\n dict_list = [dict(clean=clean_dic[k], noisy=noisy_dic[k], id=k) for k in clean_dic.keys()]\\n return dict_list\",\n \"def _collect_reads(self, wildcards, _library_name, prefix):\\n folder_name = get_ngs_library_folder_name(self.parent.sheets, wildcards.library_name)\\n pattern_set_keys = (\\\"right\\\",) if prefix.startswith(\\\"right-\\\") else (\\\"left\\\",)\\n seen = []\\n for _, path_infix, filename in self.path_gen.run(folder_name, pattern_set_keys):\\n path = os.path.join(self.base_path_in, path_infix, filename).format(**wildcards)\\n if path in seen:\\n print(\\\"WARNING: ignoring path seen before %s\\\" % path, file=sys.stderr)\\n else:\\n seen.append(path)\\n yield path\",\n \"def get_filepaths(directory):\\n file_paths = [] # List which will store all of the full filepaths.\\n\\n # Walk the tree.\\n\\n for root, directories, files in os.walk(directory):\\n\\n for filename in files:\\n if filename.endswith('.wav'):\\n # Join the two strings in order to form the full filepath.\\n filepath = os.path.join(root, filename)\\n file_paths.append(filepath) # Add it to the list.\\n # pdb.set_trace()\\n file_paths.sort()\\n return file_paths\",\n \"def get_all_files(samples, directory, suffix=\\\"\\\", nested=False):\\n files = []\\n if type(directory) == list:\\n directory = directory[0]\\n for sample in samples:\\n for unit in samples[sample].keys():\\n if nested:\\n d = \\\"{}/{}_{}\\\".format(directory, sample, unit)\\n else:\\n d = \\\"{}\\\".format(directory)\\n if is_pe(samples[sample][unit]):\\n files.append(d+\\\"/{}_{}_pe{}\\\".format(sample, unit, suffix))\\n else:\\n files.append(d+\\\"/{}_{}_se{}\\\".format(sample, unit, suffix))\\n return files\",\n \"def get_all_img_paths(path_to_folder):\\n all_subfolders = glob.glob(path_to_folder + '*')\\n all_paths = []\\n for folder in all_subfolders:\\n all_paths.extend(glob.glob(folder + '/*'))\\n # get relative paths\\n common_prefix = path_to_folder\\n relative_paths = [os.path.relpath(path, common_prefix) for path in all_paths]\\n return relative_paths\",\n \"def process_folder(root, path=\\\"\\\"):\\n myDict = {}\\n if path:\\n if root.cd(path):\\n for key in ROOT.gDirectory.GetListOfKeys():\\n filterKey(root, key, path, myDict, \\\"__List\\\")\\n else:\\n for key in ROOT.gDirectory.GetListOfKeys():\\n mypath = ROOT.gDirectory.GetPathStatic()\\n filterKey(root, key, mypath, myDict, \\\"\\\")\\n ROOT.gDirectory.cd(mypath)\\n return myDict\",\n \"def load_slurm_folder(p):\\n filter_function = lambda f: True if \\\".out\\\" in f else False\\n slurm_dict = {\\\"runs\\\": []}\\n for f in filter(filter_function, os.listdir(p)):\\n slurm_dict[\\\"runs\\\"].append(load_slurm_data(os.path.join(p, f)))\\n exit(\\\"Success!\\\")\",\n \"def _resolvePathPatterns(self, sources, source):\\n kept = []\\n pattern = re.compile(source['pathPattern'])\\n basedir = self._basePath / source['path']\\n if (self._basePath.name == Path(self._largeImagePath).name and\\n (self._basePath.parent / source['path']).is_dir()):\\n basedir = self._basePath.parent / source['path']\\n basedir = basedir.resolve()\\n for entry in basedir.iterdir():\\n match = pattern.search(entry.name)\\n if match:\\n if entry.is_file():\\n kept.append((entry.name, entry, match))\\n elif entry.is_dir() and (entry / entry.name).is_file():\\n kept.append((entry.name, entry / entry.name, match))\\n for idx, (_, entry, match) in enumerate(sorted(kept)):\\n subsource = copy.deepcopy(source)\\n # Use named match groups to augment source values.\\n for k, v in match.groupdict().items():\\n if v.isdigit():\\n v = int(v)\\n if k.endswith('1'):\\n v -= 1\\n if '.' in k:\\n subsource.setdefault(k.split('.', 1)[0], {})[k.split('.', 1)[1]] = v\\n else:\\n subsource[k] = v\\n subsource['path'] = entry\\n for axis in self._axesList:\\n stepKey = '%sStep' % axis\\n valuesKey = '%sValues' % axis\\n if stepKey in source:\\n if axis in source or valuesKey not in source:\\n subsource[axis] = subsource.get(axis, 0) + idx * source[stepKey]\\n else:\\n subsource[valuesKey] = [\\n val + idx * source[stepKey] for val in subsource[valuesKey]]\\n del subsource['pathPattern']\\n sources.append(subsource)\",\n \"def extract_from_dir(self, data_dir):\\n data_paths = []\\n for(dirpath, dirnames, filenames) in os.walk(data_dir):\\n for file in filenames:\\n # Make sure that we don't get garbage files\\n file_type = file.split('.')\\n if len(file_type) == 1 or (file_type[1] not in ['wav', 'txt']):\\n continue\\n\\n data_paths.append(os.path.join(dirpath, file))\\n\\n return data_paths\",\n \"def src_dir(path=None, base=None, subdir=None, max_levels=100):\\n path = path or _get_caller_path()\\n return _data_science_dir(\\n path=path, dirname='src', base=base,\\n subdir=subdir, max_levels=max_levels)\",\n \"def _load_files(self):\\n files = {}\\n for fn_ in self.opts[\\\"src\\\"]:\\n if os.path.isfile(fn_):\\n files.update(self._file_dict(fn_))\\n elif os.path.isdir(fn_):\\n salt.utils.stringutils.print_cli(\\n \\\"{} is a directory, only files are supported \\\"\\n 'in non-chunked mode. Use \\\"--chunked\\\" command '\\n \\\"line argument.\\\".format(fn_)\\n )\\n sys.exit(1)\\n return files\",\n \"def get_sample(self, path, prefix) -> List:\\n pass\",\n \"def _get_script_paths_from_folders_node(self) -> typing.Generator:\\r\\n for folder_node in filter(is_folder_node, self.folders_node):\\r\\n self.try_fix_namespace_path(folder_node)\\r\\n\\r\\n attr_no_recurse: bool = folder_node.get(XmlAttributeName.NO_RECURSE) == 'True'\\r\\n\\r\\n folder_path: str = folder_node.text\\r\\n\\r\\n # handle . and .. in path\\r\\n if folder_path == os.pardir or startswith(folder_path, os.pardir):\\r\\n folder_path = folder_path.replace(os.pardir, os.path.normpath(os.path.join(self.project_path, os.pardir)), 1)\\r\\n yield from PathHelper.find_script_paths_from_folder(folder_path,\\r\\n no_recurse=attr_no_recurse)\\r\\n continue\\r\\n\\r\\n if folder_path == os.curdir or startswith(folder_path, os.curdir):\\r\\n folder_path = folder_path.replace(os.curdir, self.project_path, 1)\\r\\n yield from PathHelper.find_script_paths_from_folder(folder_path,\\r\\n no_recurse=attr_no_recurse)\\r\\n continue\\r\\n\\r\\n if startswith(folder_path, self.remote_schemas, ignorecase=True):\\r\\n local_path = self._get_remote_path(folder_node)\\r\\n PapyrusProject.log.info(f'Adding import path from remote: \\\"{local_path}\\\"...')\\r\\n self.import_paths.insert(0, local_path)\\r\\n PapyrusProject.log.info(f'Adding folder path from remote: \\\"{local_path}\\\"...')\\r\\n yield from PathHelper.find_script_paths_from_folder(local_path,\\r\\n no_recurse=attr_no_recurse)\\r\\n continue\\r\\n\\r\\n folder_path = os.path.normpath(folder_path)\\r\\n\\r\\n # try to add absolute path\\r\\n if os.path.isabs(folder_path) and os.path.isdir(folder_path):\\r\\n yield from PathHelper.find_script_paths_from_folder(folder_path,\\r\\n no_recurse=attr_no_recurse)\\r\\n continue\\r\\n\\r\\n # try to add project-relative folder path\\r\\n test_path = os.path.join(self.project_path, folder_path)\\r\\n if os.path.isdir(test_path):\\r\\n # count scripts to avoid issue where an errant `test_path` may exist and contain no sources\\r\\n # this can be a problem if that folder contains sources but user error is hard to fix\\r\\n test_passed = False\\r\\n\\r\\n user_flags = wcmatch.RECURSIVE if not attr_no_recurse else 0x0\\r\\n matcher = wcmatch.WcMatch(test_path, '*.psc', flags=wcmatch.IGNORECASE | user_flags)\\r\\n for _ in matcher.imatch():\\r\\n test_passed = True\\r\\n break\\r\\n\\r\\n if test_passed:\\r\\n yield from PathHelper.find_script_paths_from_folder(test_path,\\r\\n no_recurse=attr_no_recurse,\\r\\n matcher=matcher)\\r\\n continue\\r\\n\\r\\n # try to add import-relative folder path\\r\\n for import_path in self.import_paths:\\r\\n test_path = os.path.join(import_path, folder_path)\\r\\n if os.path.isdir(test_path):\\r\\n yield from PathHelper.find_script_paths_from_folder(test_path,\\r\\n no_recurse=attr_no_recurse)\",\n \"def from_folder(self, folder, include=None, exclude=None):\\n\\n self.folder = folder\\n self.include = include\\n self.exclude = exclude\\n\\n filepaths = []\\n\\n # crawl files in subfolders \\n for root, dirs, files in os.walk(self.folder):\\n for file in files:\\n filepath = os.path.join(root, file)\\n \\n add_filepath = True\\n if self.include is not None:\\n add_filepath = any((_inc in filepath\\n for _inc in self.include))\\n if add_filepath:\\n if self.exclude is not None:\\n add_filepath = all((_exc not in filepath\\n for _exc in self.exclude))\\n\\n if add_filepath:\\n #append the file name to the list of paths\\n filepaths.append(filepath)\\n\\n self._obj['filepath'] = filepaths\\n \\n return self\",\n \"def discover_examples():\\n root = './examples'\\n for filename in os.listdir(root):\\n if os.path.splitext(filename)[1] == '.py':\\n yield os.path.join(root, filename)\",\n \"def load_transcriptions_and_paths(dirs):\\n all_transcriptions = load_and_normalize_transcriptions(dirs)\\n\\n sections = cut_into_sections_and_normalize_times(all_transcriptions)\\n\\n audio_paths = [ospj(dirs[\\\"data_in_dir\\\"], \\\"fgad\\\", \\\"fg_ad_seg\\\" + str(i)) for i in range(8)]\\n\\n return zip(sections, audio_paths)\",\n \"def features_from_folder(label_folder, audio_folder, output_folder):\\n print('Listing label files from folder.')\\n #scan labels folder\\n labels_list = os.listdir(label_folder)\\n label_files = []\\n for filename in labels_list:\\n #get its extension\\n file_extension = filename.split('.')[-1]\\n if file_extension != 'txt':\\n continue\\n #save to without its extension\\n label_files.append(filename[:-4])\\n\\n print('Listing audio files from folder.')\\n #scan audio folder\\n audios_list = os.listdir(audio_folder)\\n audio_files = []\\n for filename in audios_list:\\n #get its extension\\n file_extension = filename.split('.')[-1]\\n if file_extension != 'wav':\\n continue\\n #save to without its extension\\n audio_files.append(filename[:-4])\\n\\n print('Removing files without matches')\\n #use only the files with matching audio/label\\n files_to_process = []\\n for label_file in label_files:\\n if label_file in audio_files:\\n files_to_process.append(label_file)\\n\\n print('Processing each file...')\\n i = 1\\n class_count = {}\\n total_f = len(files_to_process)\\n #for each file\\n for processing in files_to_process:\\n print('File', str(i) + '/' + str(total_f))\\n i += 1\\n\\n #\\n label_file = os.path.join(label_folder, processing + \\\".txt\\\")\\n audio_file = os.path.join(audio_folder, processing + \\\".wav\\\")\\n\\n #get the segments from the corresponding label file\\n segments = get_segments(label_file)\\n\\n #\\n total_s = len(segments)\\n j = 1\\n #for each segment\\n for segment in segments:\\n print('\\\\tSegment', str(j) + '/' + str(total_s), segment['class'])\\n j += 1\\n\\n if class_count.get(segment['class']) is None:\\n class_count[segment['class']] = 1\\n else:\\n class_count[segment['class']] += 1\\n output_filename = segment['class']\\n output_filename += '-' + format(class_count[segment['class']], '04d')\\n output_filename = os.path.join(output_folder, output_filename)\\n\\n #get its features\\n segment_features = features_from_label(audio_file, segment)\\n\\n #save it to a file\\n fe.write_as_bin(output_filename, segment_features)\",\n \"def read_dir(self, path, process_zone, prefix=\\\"\\\"):\\n\\n zones = {}\\n for entry in os.listdir(path):\\n fullpath = os.path.join(path, entry)\\n if os.path.isdir(fullpath):\\n zones.update(self.read_dir(fullpath, process_zone, os.path.join(prefix, entry)))\\n elif prefix != \\\"\\\":\\n filename = os.path.join(prefix, entry)\\n zones[filename[:-4]] = process_zone(filename)\\n return zones\",\n \"def parse_folder(self, path):\\n\\n for filename in os.listdir(path):\\n self.parse_file(os.path.join(path, filename), filename)\\n return self.relations\",\n \"def path_generator(initial_root):\\n for root, dirs, files in os.walk(initial_root):\\n paths = [os.path.join(root, name) for name in files]\\n return paths\",\n \"def _get_result_paths(self, data):\\r\\n\\r\\n result = {}\\r\\n\\r\\n inp_file_name = str(self.Parameters['--query_NAST'].Value)\\r\\n inp_file_name = inp_file_name.rstrip('\\\"')\\r\\n inp_file_name = inp_file_name.lstrip('\\\"')\\r\\n\\r\\n exec_dir = self.Parameters['--exec_dir']\\r\\n if exec_dir.isOn():\\r\\n exec_dir = str(exec_dir.Value)\\r\\n exec_dir = exec_dir.lstrip('\\\"')\\r\\n exec_dir = exec_dir.rstrip('\\\"')\\r\\n\\r\\n if inp_file_name[0] == '/':\\r\\n # path is already absolute\\r\\n pass\\r\\n else:\\r\\n inp_file_name = exec_dir + \\\"/\\\" + inp_file_name\\r\\n\\r\\n if not exists(inp_file_name + \\\".CPS.CPC\\\"):\\r\\n raise ApplicationError(\\\"Calling ChimeraSlayer failed.\\\")\\r\\n\\r\\n result['CPS'] = ResultPath(Path=inp_file_name + \\\".CPS.CPC\\\",\\r\\n IsWritten=True)\\r\\n return result\",\n \"def get_sar_paths(directory_path: str) -> list:\\n dataset_path = Path(directory_path)\\n\\n path_generator = dataset_path.rglob('*.tif')\\n paths = sorted([path for path in path_generator if path.is_file()])\\n return [sar_set(*g) for k, g in groupby(paths, key=lambda path: re.match(TYPE_REGEX, path.name)[2])]\",\n \"def find_wavs(directory, pattern='**/*.wav'):\\n return glob(os.path.join(directory, pattern), recursive=True)\",\n \"def get_filenames(self, root_folder):\\n t_images = []\\n t_labels = []\\n v_images = []\\n v_labels = []\\n if not os.path.isfile('filenames.p'):\\n for dirName, subdirList, fileList in os.walk(root_folder):\\n print('Collecting ' + dirName)\\n files = [fname for fname in fileList]\\n if len(files) > 0:\\n if 'Depth' in dirName:\\n if any(subj in dirName for subj in self.val_subjects):\\n v_labels.extend([os.path.join(dirName, fname) for fname in fileList])\\n else:\\n t_labels.extend([os.path.join(dirName, fname) for fname in fileList])\\n elif 'Color' in dirName:\\n if any(subj in dirName for subj in self.val_subjects):\\n v_images.extend([os.path.join(dirName, fname) for fname in fileList])\\n else:\\n t_images.extend([os.path.join(dirName, fname) for fname in fileList])\\n pickle.dump([sorted(t_images), sorted(t_labels), sorted(v_images), sorted(v_labels)], open('filenames.p', 'wb'))\\n return sorted(t_images), sorted(t_labels), sorted(v_images), sorted(v_labels)\\n else:\\n return pickle.load(open('filenames.p', 'rb'))\",\n \"def to_sources(todos):\\n for subtodos in todos.iter_sourced():\\n to_path(subtodos, subtodos.get_source())\",\n \"def _get_file_paths(self):\\n return [os.path.join(self.path, self.mode, 'waveforms', file_name + '.npy') for file_name in self.file_names]\",\n \"def parse_folder(self, path):\\n\\n data = []\\n for filename in os.listdir(path):\\n data.append(self.parse_file(os.path.join(path, filename), filename))\\n return data\",\n \"def _load_paths(self):\\n ts_paths_map = {}\\n for path in Path(self.datadir).rglob(\\\"roas.*.json.gz\\\"):\\n path = str(path)\\n ts = int(path.split(\\\"/\\\")[-1].split(\\\".\\\")[2])\\n ts_paths_map[ts] = path\\n return ts_paths_map\",\n \"def get_datapaths(input_dir):\\n image_paths = []\\n assert os.path.isdir(input_dir), f\\\"{input_dir} is not existed\\\"\\n\\n for root, _, names in os.walk(input_dir):\\n for name in names:\\n path = os.path.join(root, name)\\n image_paths.append(path)\\n return image_paths\",\n \"def _get_psc_paths(self) -> dict:\\r\\n object_names: dict = {}\\r\\n\\r\\n def add_object_name(p: str) -> None:\\r\\n object_names[p if not os.path.isabs(p) else self._calculate_object_name(p)] = p\\r\\n\\r\\n # try to populate paths with scripts from Folders and Scripts nodes\\r\\n if self.folders_node is not None:\\r\\n for path in self._get_script_paths_from_folders_node():\\r\\n add_object_name(path)\\r\\n\\r\\n if self.scripts_node is not None:\\r\\n for path in self._get_script_paths_from_scripts_node():\\r\\n add_object_name(path)\\r\\n\\r\\n # convert user paths to absolute paths\\r\\n for object_name, script_path in object_names.items():\\r\\n # ignore existing absolute paths\\r\\n if os.path.isabs(script_path) and os.path.isfile(script_path):\\r\\n continue\\r\\n\\r\\n # try to add existing project-relative paths\\r\\n test_path = os.path.join(self.project_path, script_path)\\r\\n if os.path.isfile(test_path):\\r\\n object_names[object_name] = test_path\\r\\n continue\\r\\n\\r\\n # try to add existing import-relative paths\\r\\n for import_path in self.import_paths:\\r\\n if not os.path.isabs(import_path):\\r\\n import_path = os.path.join(self.project_path, import_path)\\r\\n\\r\\n test_path = os.path.join(import_path, script_path)\\r\\n if os.path.isfile(test_path):\\r\\n object_names[object_name] = test_path\\r\\n break\\r\\n\\r\\n PapyrusProject.log.info(f'{len(object_names)} unique script paths resolved to absolute paths.')\\r\\n\\r\\n return object_names\",\n \"def samples_in_trial(self, trial_folder):\\n files = listdir(join(trial_folder, 'Background'))\\n img_files = [x for x in files if x.split(\\n '.')[-1] in ('tif', 'jpg', 'png')]\\n sample_name_list = [x.split('.')[1] for x in img_files]\\n return sample_name_list # like ['12B',]\",\n \"def scan(root: str, config: dict) -> dict:\\n\\n extensions = config['extensions']\\n exceptions = config['exceptions']\\n\\n # get list of directories, with their contents (files and sub-directories)\\n dirs_by_path = {\\n get_path_from_common_root(dir_path, root): (\\n dir_path,\\n dir_names,\\n [name for name in file_names if is_valid_file_name(name, config)]\\n )\\n for dir_path, dir_names, file_names in os.walk(root)\\n }\\n\\n dirs_by_path = {key: value for key, value in dirs_by_path.items() if value[1] or value[2]}\\n\\n # get list of file paths\\n file_path_list = [\\n (file_dir, file_name)\\n for file_dir, _, file_names in dirs_by_path.values()\\n for file_name in file_names\\n ]\\n\\n files_by_path = {}\\n # todo: put below loop contents into function, used in above list comprehension\\n for file_dir, file_name_with_extension in file_path_list:\\n # todo: remove code file definition from here to allow this to be reused for non-code related files\\n # todo: refactor to use inheritable File class instead of named tuple, to be reused for non-code files\\n\\n if file_name_with_extension in exceptions:\\n continue\\n\\n file = CodeFile(\\n imports=[],\\n exports=[],\\n local_params=[],\\n blocks=[],\\n dir=file_dir,\\n name=file_name_with_extension.rsplit('.', 1)[0],\\n extension=file_name_with_extension.rsplit('.', 1)[1]\\n )\\n\\n parse_file(file, config)\\n file_no_dupes = remove_duplicate_entries(file)\\n\\n dir_key = get_path_from_common_root(file_dir, root)\\n if dir_key not in files_by_path:\\n files_by_path[dir_key] = []\\n\\n files_by_path[dir_key].append(file_no_dupes)\\n\\n return {'dirs_by_path': dirs_by_path, 'files_by_path': files_by_path,\\n 'starting_point': get_path_from_common_root(root, root)}\",\n \"def _output_paths(outputs: Dict[str, str]) -> Dict[str, Path]:\\n out_paths = dict()\\n for name in outputs:\\n target_dir = _BASE_PATH / name\\n target_dir.mkdir()\\n out_paths[name] = target_dir / 'data.json'\\n return out_paths\",\n \"def my_get_paths_to_wavs(self, path):\\n if self.label_type == 'original':\\n # Just get all files\\n return get_paths_to_wavs(path)\\n elif self.label_type == 'four':\\n # Filter out emotions Excitement and Frustration, leaving only\\n # anger, happiness, neutral, sadness.\\n new_paths_to_wavs = []\\n paths_to_wavs, path_to_noise = get_paths_to_wavs(path)\\n for file in paths_to_wavs:\\n file_name = os.path.split(file)[1]\\n emotion_label = self.get_emotion_label(file_name)\\n if emotion_label in ('ang', 'hap', 'neu', 'sad'):\\n new_paths_to_wavs.append(file)\\n return new_paths_to_wavs, path_to_noise\\n else:\\n raise ValueError('Unknown label type! Should be either \\\"original\\\" for all samples, or \\\"four\\\" for anger, '\\n 'happiness, neutral, sadness')\",\n \"def collect_project_source_files():\\n source_files = glob.glob(PROJECT_SOURCE_FILES_FOLDER + '/**/*.py', recursive=True)\\n # Insert root main.py at the beginning.\\n source_files.insert(0, os.path.join(PROJECT_ROOT_FOLDER, 'main.py'))\\n return list(map(lambda path: posixpath.join(*path.split('\\\\\\\\')), source_files))\",\n \"def getImmediateSubdirectories(dir):\",\n \"def parse_animation_path(path, verbose=True):\\n output = {}\\n\\n # Iterate through all possible paths\\n for folder_path in os.listdir(path):\\n animation_dict = {'transition': [], 'idle': [], 'transition_playback': [], 'idle_playback': [], 'animation_name': \\\"\\\"}\\n animation_path = path + \\\"/\\\" + folder_path\\n\\n # And only proceed if the animation path is valid\\n if is_valid_animation(animation_path, verbose):\\n for sub_animation in [\\\"transition\\\", \\\"idle\\\"]:\\n try:\\n sub_animation_path = animation_path + \\\"/\\\" + sub_animation + \\\"/\\\"\\n animation_dict['animation_name'] = animation_path\\n\\n filenames = os.listdir(sub_animation_path)\\n frames = [sub_animation_path + frame for frame in filenames if is_image_file(frame)]\\n frames.sort()\\n animation_dict[sub_animation] = frames\\n\\n if \\\"frames\\\" in filenames:\\n with open(sub_animation_path + \\\"/frames\\\", \\\"r\\\") as f:\\n animation_dict[sub_animation + \\\"_playback\\\"] = generate_playback_list(f.read())\\n except Exception as e:\\n print(\\\"parse_animation_path():\\\", e)\\n\\n output[folder_path] = animation_dict\\n\\n return output\",\n \"def get_data_file_paths(input_folder: str, data_file_prefix: str = \\\"\\\",\\n data_file_postfix: str = \\\".nc\\\") -> list:\\n data_file_paths = list()\\n # we look at all subfolders, whatever they are named\\n subfolders = get_files(input_folder, keep_path=True, order_numerical=True)\\n for subfolder in subfolders:\\n data_files = get_files(subfolder, prefix=data_file_prefix,\\n postfix=data_file_postfix, keep_path=True,\\n order_numerical=True)\\n data_file_paths += data_files\\n return data_file_paths\",\n \"def getFilePaths(directory):\\r\\n\\tfor folder, subs, files in os.walk(directory):\\r\\n\\t\\tfor filename in files:\\r\\n\\t\\t\\tyield os.path.join(folder, filename)\",\n \"def folder(fpath):\\n file_paths = glob.glob(fpath + '/*.dat')\\n return list(file_paths)\",\n \"def source_paths(self):\\n paths = self.config.get('static_dirs')\\n if paths:\\n return paths\\n return [self.config.get('static_dir')]\",\n \"def setupSampleDirectories(self):\\n self.allSamplesDir = \\\"%s/%s_all-samples\\\" % (os.getcwd(),\\n self.project2Id)\\n if not os.path.exists(self.allSamplesDir):\\n os.mkdir(self.allSamplesDir)\\n for sampleId,iSample in self.dSamples.items():\\n dirSample = \\\"%s/%s\\\" % (self.allSamplesDir, sampleId)\\n iSample.dir = dirSample\\n if not os.path.exists(dirSample):\\n os.mkdir(dirSample)\\n if self.verbose > 0:\\n msg = \\\"sample directories: %s\\\" % self.allSamplesDir\\n print(msg); sys.stdout.flush()\",\n \"def _get_files(self):\\n # pylint: disable=unused-variable\\n for dirpath, __, filenames in os.walk(self.start_location):\\n for file_ in filenames:\\n if file_.endswith('.py'):\\n yield \\\"{0}{1}\\\".format(dirpath, file_)\",\n \"def paired_paths_from_folder(folders, keys, filename_tmpl):\\n assert len(folders) == 2, (\\n 'The len of folders should be 2 with [input_folder, gt_folder]. '\\n f'But got {len(folders)}')\\n assert len(keys) == 2, (\\n 'The len of keys should be 2 with [input_key, gt_key]. '\\n f'But got {len(keys)}')\\n input_folder, gt_folder = folders\\n input_key, gt_key = keys\\n\\n input_paths = list(scandir(input_folder))\\n gt_paths = list(scandir(gt_folder))\\n assert len(input_paths) == len(gt_paths), (\\n f'{input_key} and {gt_key} datasets have different number of images: '\\n f'{len(input_paths)}, {len(gt_paths)}.')\\n paths = []\\n for gt_path in gt_paths:\\n basename, ext = os.path.splitext(os.path.basename(gt_path))\\n input_name = f'{filename_tmpl.format(basename)}{ext}'\\n input_path = os.path.join(input_folder, input_name)\\n assert input_name in input_paths, (f'{input_name} is not in '\\n f'{input_key}_paths.')\\n gt_path = os.path.join(gt_folder, gt_path)\\n paths.append(\\n dict([(f'{input_key}_path', input_path),\\n (f'{gt_key}_path', gt_path)]))\\n return paths\",\n \"def GetSongFilenames():\\n\\n\\t## Loop through each directory\\n\\tsong_files = []\\n\\tfor root, dirs, fnames in os.walk(\\\"_data\\\\\\\\fma_small\\\\\\\\\\\"):\\n\\t\\t\\n\\t\\t## Skip the first level\\n\\t\\tif root == \\\"_data\\\\\\\\fma_small\\\\\\\\\\\":\\n\\t\\t\\tcontinue\\n\\n\\t\\t## Otherwise collect the files, appending\\n\\t\\t## the root path.\\n\\t\\tsong_files += [root+\\\"\\\\\\\\\\\"+f for f in fnames]\\n\\n\\treturn song_files\",\n \"def find_tryouts(data_dir, prefix):\\n filenames = os.listdir(data_dir)\\n return sorted(list(map(lambda d: os.path.join(data_dir, d), filter(lambda s: s.startswith(prefix), filenames))))\",\n \"def filepaths(self, langs) -> Generator[str, None, None]:\\n for pv in self.projects(langs):\\n yield from pv.filepaths()\",\n \"def dir_resolution(self, src_path, frag_length=128):\\n src_path = os.path.join(self.root_path, src_path)\\n files = os.listdir(src_path)\\n\\n MFCCs = None\\n labels = None\\n cnt = 1\\n total_num = len(files)\\n for wav in files:\\n wav_path = os.path.join(src_path, wav)\\n MFCCs_each, labels_each = self.features_and_labels(wav_path, frag_length)\\n if MFCCs is not None:\\n MFCCs = torch.cat((MFCCs, MFCCs_each))\\n labels = torch.cat((labels, labels_each))\\n else:\\n MFCCs, labels = MFCCs_each, labels_each\\n\\n if cnt % 1000 == 0:\\n print('{} data pieces have been loaded in and {} are left'.format(cnt, total_num-cnt))\\n cnt += 1\\n\\n np.save(self.feature_file, MFCCs.numpy()) \\n np.save(self.label_file, labels.numpy())\\n print('Loading into files finished!')\",\n \"def get_paths(input_folder: str) -> list[str]:\\n\\n return [f for f in os.listdir(input_folder) if f[-4:] == '.txt' and f[:3] != 'top']\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6020198","0.6010303","0.5987424","0.59563166","0.59123486","0.58793145","0.581208","0.5806299","0.5796214","0.57869065","0.5786168","0.5785967","0.57851917","0.5748538","0.56930906","0.5687381","0.5681763","0.5676166","0.56466466","0.5594708","0.55859464","0.5576922","0.5553613","0.5552828","0.55518466","0.5535267","0.55350864","0.55335754","0.5532481","0.5531675","0.5487301","0.5442267","0.5440037","0.542004","0.5400144","0.54000413","0.5383955","0.536843","0.5358817","0.5353108","0.5344429","0.5334882","0.53334355","0.53278416","0.531999","0.5318824","0.53175104","0.5314936","0.53118014","0.53091437","0.53047657","0.5299137","0.52942127","0.5284672","0.5283408","0.52813315","0.528112","0.5270331","0.52688754","0.5260531","0.52550983","0.52550626","0.52378464","0.5236113","0.52317625","0.52251744","0.5216114","0.5209744","0.52079964","0.5195843","0.5192494","0.5185826","0.5182831","0.518087","0.5178268","0.51768","0.51737535","0.5168817","0.5168707","0.5154232","0.51525235","0.5152402","0.5150604","0.514387","0.513876","0.5138356","0.5136575","0.51339906","0.5124657","0.5117723","0.5116192","0.5115421","0.5115093","0.51142097","0.51124716","0.51111275","0.5099846","0.5099774","0.5093527","0.509145"],"string":"[\n \"0.6020198\",\n \"0.6010303\",\n \"0.5987424\",\n \"0.59563166\",\n \"0.59123486\",\n \"0.58793145\",\n \"0.581208\",\n \"0.5806299\",\n \"0.5796214\",\n \"0.57869065\",\n \"0.5786168\",\n \"0.5785967\",\n \"0.57851917\",\n \"0.5748538\",\n \"0.56930906\",\n \"0.5687381\",\n \"0.5681763\",\n \"0.5676166\",\n \"0.56466466\",\n \"0.5594708\",\n \"0.55859464\",\n \"0.5576922\",\n \"0.5553613\",\n \"0.5552828\",\n \"0.55518466\",\n \"0.5535267\",\n \"0.55350864\",\n \"0.55335754\",\n \"0.5532481\",\n \"0.5531675\",\n \"0.5487301\",\n \"0.5442267\",\n \"0.5440037\",\n \"0.542004\",\n \"0.5400144\",\n \"0.54000413\",\n \"0.5383955\",\n \"0.536843\",\n \"0.5358817\",\n \"0.5353108\",\n \"0.5344429\",\n \"0.5334882\",\n \"0.53334355\",\n \"0.53278416\",\n \"0.531999\",\n \"0.5318824\",\n \"0.53175104\",\n \"0.5314936\",\n \"0.53118014\",\n \"0.53091437\",\n \"0.53047657\",\n \"0.5299137\",\n \"0.52942127\",\n \"0.5284672\",\n \"0.5283408\",\n \"0.52813315\",\n \"0.528112\",\n \"0.5270331\",\n \"0.52688754\",\n \"0.5260531\",\n \"0.52550983\",\n \"0.52550626\",\n \"0.52378464\",\n \"0.5236113\",\n \"0.52317625\",\n \"0.52251744\",\n \"0.5216114\",\n \"0.5209744\",\n \"0.52079964\",\n \"0.5195843\",\n \"0.5192494\",\n \"0.5185826\",\n \"0.5182831\",\n \"0.518087\",\n \"0.5178268\",\n \"0.51768\",\n \"0.51737535\",\n \"0.5168817\",\n \"0.5168707\",\n \"0.5154232\",\n \"0.51525235\",\n \"0.5152402\",\n \"0.5150604\",\n \"0.514387\",\n \"0.513876\",\n \"0.5138356\",\n \"0.5136575\",\n \"0.51339906\",\n \"0.5124657\",\n \"0.5117723\",\n \"0.5116192\",\n \"0.5115421\",\n \"0.5115093\",\n \"0.51142097\",\n \"0.51124716\",\n \"0.51111275\",\n \"0.5099846\",\n \"0.5099774\",\n \"0.5093527\",\n \"0.509145\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7107858"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81780,"cells":{"query":{"kind":"string","value":"Makes a tab separated list of examples from a top folder."},"document":{"kind":"string","value":"def make_example_list_from_folder(\n folder_sources, subset='all', ss_regex=re.compile(r'example.*_sources'),\n pattern='_sources', subfolder_events=('background', 'foreground')):\n example_dict = make_example_dict_from_folder(\n folder_sources, subset=subset, ss_regex=ss_regex, pattern=pattern,\n subfolder_events=subfolder_events)\n example_list = []\n for subset in example_dict:\n for example in example_dict[subset]:\n example_list.append('\\t'.join([example] + example_dict[subset][example]))\n return example_list"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def generate_test_list(tdir):\n\n # Skip this if it already exists\n if os.path.exists(os.path.join(tdir.name, \"kstest-list\")):\n return\n\n kstest_log = os.path.join(tdir.name, \"kstest.log\")\n with open(kstest_log) as f:\n for line in f.readlines():\n if not line.startswith(\"Running tests: \"):\n continue\n\n tests = [os.path.basename(os.path.splitext(s)[0]) for s in line[15:].split()]\n with open(os.path.join(tdir.name, \"kstest-list\"), \"wt\") as klf:\n for t in tests:\n print(t, file=klf)\n break","def list(ctx):\n handler = ValidateCommandHandler(ctx.obj['qa_dir'])\n if handler.validate():\n handler = ListCommandHandler(ctx.obj['qa_dir'])\n handler.show_test_case_tree()\n else:\n exit(1)","def test_examples():\n tests = [d for d in listdir(ex) if path.isdir(path.join(ex, d))]\n for d in tests:\n yield check_examples, d","def _generate_examples(self, folders, split):\n raise NotImplementedError(\"TODO\")","def tabulate_tribes():\n tribes = {}\n for tribe in os.listdir('tribes'):\n tribes[tribe[:-3].title()] = 'tribes/' + tribe[:-3]\n table = tabulate(list(sorted(tribes)))\n for tribe in tribes:\n table = table.replace(tribe, f'[{tribe}]({tribes[tribe]})')\n return table","def _generate_examples(self, filepath):\n\n key = 1\n with tf.io.gfile.GFile(filepath, \"r\") as f:\n tokens = []\n tags = []\n langs = []\n for line in f:\n line = line.rstrip()\n # pylint: disable=g-explicit-bool-comparison\n if line.startswith(\"-DOCSTART-\") or line == \"\":\n if tokens:\n spans = get_spans(tokens, tags)\n yield key, {\n \"tokens\": tokens,\n \"tags\": tags,\n \"langs\": langs,\n \"spans\": spans\n }\n key += 1\n tokens = []\n tags = []\n langs = []\n else:\n # wikiann data is tab separated\n fields = line.split(\"\\t\")\n # strip out language prefix\n langs.append(fields[0].split(\":\")[0])\n tokens.append(\":\".join(fields[0].split(\":\")[1:]))\n if len(fields) > 1:\n tags.append(fields[-1])\n else:\n # examples have no label in test set\n tags.append(\"O\")\n if tokens:\n spans = get_spans(tokens, tags)\n yield key, {\n \"tokens\": tokens,\n \"tags\": tags,\n \"langs\": langs,\n \"spans\": spans\n }","def workbench_scenarios():\n return [\n (\"filethumbs\",\n \"\"\"\\\n <vertical_demo>\n <filethumbs/>\n <filethumbs/>\n <filethumbs/>\n </vertical_demo>\n \"\"\")\n ]","def get_test_examples(self, data_dir):\n raise NotImplementedError()","def get_test_examples(self, data_dir):\n raise NotImplementedError()","def get_tests():\n\tret = []\n\tfor walk_tuple in os.walk(webnotes.defs.modules_path):\n\t\tfor test_file in filter(lambda x: x.startswith('test') and x.endswith('.py'), walk_tuple[2]):\n\t\t\tdir_path = os.path.relpath(walk_tuple[0], webnotes.defs.modules_path)\n\t\t\tif dir_path=='.':\n\t\t\t\tret.append(test_file[:-3])\n\t\t\telse:\n\t\t\t\tret.append(dir_path.replace('/', '.') + '.' + test_file[:-3])\t\t\t\n\treturn ret","def test_tabify(self):\n before_b = \"\"\"\\\n first line\n line 1\n line a\n line b\n line c\n last line\n \"\"\"\n after_b = \"\"\"\\\n first line\n line 1\n \tline a\n \t\tline b\n line c\n last line\n \"\"\"\n self.run_test(\n before_b=before_b,\n after_b=after_b,\n before_sel=(\"1.0\", \"7.0\"),\n after_sel=(\"7.0\", \"7.0\"),\n command_name=\"tabify\",\n )","def _generate_examples(self, files):\n idx = 0\n for filename in files:\n with open(filename) as file:\n for line in file:\n yield idx, {\"text\": line}\n idx += 1","def test_get_result_top_dirs(self):\n pass","def make_toc(c: Cmdr, kind: str, root: Position) -> str:\n\n def cell_type(p: Position) -> str:\n language = g.getLanguageAtPosition(c, p)\n return 'markdown' if language in ('jupyter', 'markdown') else 'python'\n\n def clean_headline(s: str) -> str:\n # Surprisingly tricky. This could remove too much, but better to be safe.\n aList = [ch for ch in s if ch in '-: ' or ch.isalnum()]\n return ''.join(aList).rstrip('-').strip()\n\n result: list[str] = []\n stack: list[int] = []\n for p in root.subtree():\n if cell_type(p) == 'markdown':\n level = p.level() - root.level()\n if len(stack) < level:\n stack.append(1)\n else:\n stack = stack[:level]\n n = stack[-1]\n stack[-1] = n + 1\n # Use bullets\n title = clean_headline(p.h)\n url = clean_headline(p.h.replace(' ', '-'))\n if kind == 'markdown':\n url = url.lower()\n line = f\"{' ' * 4 * (level - 1)}- [{title}](#{url})\\n\"\n result.append(line)\n if result:\n result.append('\\n')\n return ''.join(result)","def _create_examples(self, data_dir, set_type):\n\t\texamples = []\n\t\tinput_file_data = os.path.join(data_dir, \"data.tsv\")\n\t\twith open(input_file_data, \"r\", encoding=\"utf-8-sig\") as f:\n\t\t\tfor i, inp in enumerate(f):\n\t\t\t\tinps = inp.split('\\t') \n\t\t\t\tguid = \"%s-%s\" % (set_type, i)\n\t\t\t\ttext_inp = inps[1].strip()\n\t\t\t\ttext_out = inps[2].strip()\n\t\t\t\texamples.append(InputExample(guid=guid, text_inp=text_inp, text_out=text_out))\n\t\t\t\t\n\t\t\t# Sort these out before returning\n\t\t\texamples = sorted(examples, key=sort_inp_len)\n\t\t\treturn examples","def get_test_examples(self, data_dir):\n \n raise NotImplementedError()","def zio_test_help():\n print(\"zio-ut [TESTS]\")\n print(\"\")\n print(\"[TESTS]: list of tests to perform. It can be the name of a specific test, or the name of a module of tests\")\n print(\" In alternative, you che use the test code:\")\n print(\"Code test case\")\n print(\"- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - \")\n i = 0\n for t in test_list:\n print(str(i) + \" \" + t)\n i = i + 1","def run_tests():\r\n p = Parser(b\"0About prices\\tPrices/aboutus\\tserver.example.com\\t70\\r\\n\".decode(\"ascii\"))\r\n print(p._parse_dir())","def dir_dataset():\n return TabularDataset.from_path('tests/data/dummy_tabular', sep=',')","def master_test_suite( pkg_mod_iter ):\n master_suite= unittest.TestSuite()\n for package, module_iter in pkg_mod_iter:\n for filename, module in module_iter:\n print( package+\".\"+module )\n suite= doctest.DocTestSuite( package+\".\"+module )\n print( \" \", suite )\n master_suite.addTests( suite )\n runner= unittest.TextTestRunner( verbosity=1 )\n runner.run( master_suite )","def get_test_examples(self, data_dir):\n raise NotImplementedError()","def get_test_examples(self, data_dir):\n raise NotImplementedError()","def get_test_examples(self, data_dir):\n raise NotImplementedError()","def get_test_examples(self, data_dir):\n raise NotImplementedError()","def get_test_examples(self, data_dir):\n raise NotImplementedError()","def test_file_shizz(topic_path):\n\tL = [[1,2,3],[4,5,6]]\n\tprint(open(topic_path+'/D/'+str(L[1][0])+'.txt'))","def get_examples():\n # Get the tjson test cases from a url.\n examples = urlopen(TJSON_EXAMPLES_URL).read()\n\n # Strip comments from the lines.\n examples = re.sub(r\"^#.*\\n?\", \"\", examples.decode(), flags=re.MULTILINE)\n\n # Split a group of examples.\n delimiter = re.escape(EXAMPLES_DELIMITER)\n example_re = re.compile(delimiter + r'(.*?)' + delimiter, re.S)\n split = re.findall(example_re, examples)\n\n # Create the `Example` named tuples.\n return [\n parse_example(example)\n for example in split]","def get_test_examples(self, data_path):\r\n return self.create_examples(self.read_data(data_path), 'test')","def main():\n\n parser = argparse.ArgumentParser()\n parser.add_argument(\"folder\")\n args = parser.parse_args()\n \n print(\"\")\n print(\"Smart Listing:\", args.folder.replace(\"/\", \" >\"))\n print(\"\")\n for seq, frange in parsefilenames(os.listdir(args.folder)):\n print(len(frange), seq, frange)","def ConstrTest():\n with open(path.join(MAIN_PATH, TEST)) as f:\n for line in f:\n line = line.strip().split(\"\\t\")\n src, dest = line[1:]\n features = Features(src, dest)\n test_instances.append(features)","def test_suite():\n suite = unittest.TestSuite()\n suite.addTests(\n [\n layered(\n doctest.DocFileSuite(\"behaviors.rst\"),\n layer=testing.TEXT_INTEXER_INTEGRATION_TESTING,\n ),\n ]\n )\n return suite","def test_toc(self):\n with sphinx_build('pyexample'):\n with open('_build/text/docfx_yaml/toc.yml') as yml_file:\n data = yaml.safe_load(yml_file)\n for item in data:\n if 'items' in item:\n self.assertEqual(\n item['items'][0]['name'],\n 'example.enum_type.EnumFoo'\n )\n break","def test_suite():\n test_loader = unittest.TestLoader()\n # Read in unit tests\n test_suite = test_loader.discover('tests')\n\n # Read in doctests from README\n test_suite.addTests(doctest.DocFileSuite('README.md',\n optionflags=doctest.ELLIPSIS))\n return test_suite","def discover_examples():\n root = './examples'\n for filename in os.listdir(root):\n if os.path.splitext(filename)[1] == '.py':\n yield os.path.join(root, filename)","def fmt_folder(folder):\n result = []\n\n folder_dir = localizer_config.get_src_path(folder)\n if not os.path.isdir(folder_dir):\n localizer_log.error(\"folder \" + folder + ' not exist. Abort.')\n\n experiments = [x for x in os.listdir(folder_dir)\n if os.path.isdir(os.path.join(folder_dir, x))]\n\n list_size = len(kpi_info.kpi_list)\n import util.runtime as runtime\n for exp_name in experiments:\n exp = runtime.find_exp_by_name(exp_name)\n if not exp:\n localizer_log.warning(\"Experiment {exp} not found\"\n .format(exp=exp_name))\n continue\n exp_dir = os.path.join(folder_dir, exp_name)\n files = [x for x in os.listdir(exp_dir) if x.endswith('.txt')]\n timeset = [int(filename.strip().replace('.txt', ''))\n for filename in files]\n\n for t in sorted(timeset):\n lst = [0 for i in range(list_size)]\n with open(os.path.join(exp_dir, str(t) + '.txt')) as f:\n for l in f:\n idx = kpi_info.get_index(l.strip())\n lst[idx] = 1\n result.append(PredData(exp, str(t), lst))\n\n return result","def create_file_overview_doc() -> None:\n folder_file_docstring = generate_folder_file_docstrings_dict()\n\n table_markdown = []\n for folder in folder_file_docstring:\n dictionary_of_files = folder_file_docstring[folder]\n\n folder_text = folder\n for file in sorted(dictionary_of_files):\n new_row = f\"| {folder_text:{COLUMN_WIDTHS[0]}}| {file:{COLUMN_WIDTHS[1]}}| {folder_file_docstring[folder][file]:{COLUMN_WIDTHS[2]}}|\\n\"\n table_markdown.append(new_row)\n folder_text = \" \"\n\n # adding blank row at the end of every folder\n table_markdown.append(BLANK_ROW)\n\n # Folders that do not contain any files with docstrings are added separately to the file-overview\n for folder_name in sorted(DESC_FOR_NO_FILE_FOLDERS):\n new_row = f\"| {folder_name:{COLUMN_WIDTHS[0]}}| {SPACEBAR:{COLUMN_WIDTHS[1]}}| {DESC_FOR_NO_FILE_FOLDERS[folder_name]:{COLUMN_WIDTHS[2]}}|\\n\"\n table_markdown.extend([new_row, BLANK_ROW])\n\n with open(DEVELOPER_DOC_PATH, \"r\") as dev_file:\n doc_data = dev_file.readlines()\n\n doc_data[TABLE_OFFSET - 1 :] = table_markdown[:-1]\n updated_data = \"\".join(doc_data)\n\n with open(DEVELOPER_DOC_PATH, \"w\") as dev_file:\n dev_file.write(updated_data)","def tab(self):\n\n extension = ['.zip', '.tar.gz', '.rar', '.7z']\n return ['compress ' + os.path.basename(self.fm.thisdir.path) + ext for ext in extension]","def test(self, absList, modelFilename, fold=None):\n raise NotImplementedError(\"Need to implement test()\")","def list_tests(arn=None, nextToken=None):\n pass","def printReftestList():\n print(\"Generating reftestList.js...\", end=\"\")\n\n suite = reftest.reftestSuite()\n fp = file(MATHJAX_WEB_PATH + \"reftestList.js\", \"w\")\n stdout = sys.stdout\n sys.stdout = fp\n print(\"// \" + WARNING_GENERATED_FILE)\n print(\"/**\")\n print(\" * @file reftestList.js\")\n print(\" * @brief array representing the test suite.\")\n print(\" *\")\n print(\" * This file is generated by runTestsuite.py -p\")\n print(\" *\")\n print(\" * @var Array gTestSuite\")\n print(\" * An array representing the file hierarchy of the test suite\")\n print(\" */\")\n print(\"var gTestSuite = [\\\"testsuite/\\\"\", end=\"\")\n suite.addReftests(\"printList\",\n MATHJAX_TESTSUITE_PATH, \"reftest.list\", -1)\n print(\"]\")\n sys.stdout = stdout\n fp.close()\n\n print(\"done\")","def get_dev_examples(self, data_dir):\r\n raise NotImplementedError()","def tabular_data(self):\n path = CFG.GRAPHS_DIR\n chdir(path)\n\n if self.experiment_count == 1:\n f = open(self.tablefile, 'w')\n f.write(self.print_border_line())\n f.write(self.table_header())\n f.write(self.print_border_line())\n f.write(self.pretty_string(\"Functions\"))\n f.write(self.pretty_string(\"Batch Size\"))\n f.write(self.pretty_string(\"Training (%)\"))\n f.write(self.pretty_string(\"Testing (%)\", True))\n f.write('\\n')\n f.write(self.print_border_line())\n f.close()\n\n f = open(self.tablefile, 'a')\n f.write(self.pretty_string(self.function_name))\n f.write(self.pretty_string(str(self.batch_size)))\n f.write(self.pretty_string(self.tr_mean_str))\n f.write(self.pretty_string(self.test_mean_str, True))\n f.write('\\n')\n f.close()","def generate_test_list(self, **kwargs):\n LOGGER.debug(\"Generating test case list...\")\n self.backup_tempest_config(self.conf_file, '/etc')\n if kwargs.get('mode') == 'custom':\n if os.path.isfile(self.tempest_custom):\n shutil.copyfile(\n self.tempest_custom, self.list)\n else:\n raise Exception(\n f\"Tempest test list file {self.tempest_custom} NOT found.\")\n else:\n testr_mode = kwargs.get(\n 'mode', r'^tempest\\.(api|scenario).*\\[.*\\bsmoke\\b.*\\]$')\n cmd = (f\"(cd {self.verifier_repo_dir}; \"\n f\"stestr list '{testr_mode}' > {self.list} 2>/dev/null)\")\n output = subprocess.check_output(cmd, shell=True)\n LOGGER.info(\"%s\\n%s\", cmd, output.decode(\"utf-8\"))\n os.remove('/etc/tempest.conf')","def KittiTestDataset(test_root_path):\n \n names = os.listdir(test_root_path)\n dataset = [[os.path.join(test_root_path, name)] for name in names]\n \n return dataset","def _create_test_module_heading(nbdir):\n heading = 'import os\\n'\\\n 'import sys\\n'\\\n 'import test_func as tf\\n\\n'\\\n '#make projectdir accessible inside this script\\n'\\\n 'tst_dir = os.path.dirname(os.path.realpath(__file__))\\n'\\\n f'nb_dir = os.path.join(tst_dir, \"..\", *{os.path.split(nbdir)})\\n' # noqa E501\n\n return heading","def run_test_suite( pkg_mod_iter ):\n for package, module_iter in pkg_mod_iter:\n print( package )\n print( \"=\"*len(package ) )\n print()\n for filename, module in module_iter:\n suite= doctest.DocTestSuite( package+\".\"+module )\n runner= unittest.TextTestRunner( verbosity=1 )\n runner.run( suite )","def get_dev_examples(self, data_dir):\n raise NotImplementedError()","def get_dev_examples(self, data_dir):\n raise NotImplementedError()","def test(self, absList, modelfilename, fold=None):\n raise NotImplementedError(\"Need to implement test()\")","def example(*paths):\n\n return normpath(join(dirname(__file__), '..', 'examples', *paths))","def workbench_scenarios(): \n return [\n (\"TermsXBlock\",\n \"\"\"<terms/>\n \"\"\"),\n (\"Multiple TermsXBlock\",\n \"\"\"<vertical_demo>\n <terms/>\n <terms/>\n <terms/>\n </vertical_demo>\n \"\"\"),\n ]","def test_add_tab_to_lines(self):\n before_b = \"\"\"\\\n first line\n line 1\n line a\n line b\n line c\n last line\n \"\"\"\n after_b = \"\"\"\\\n first line\n line 1\n line a\n line b\n line c\n last line\n \"\"\"\n self.run_test(\n before_b=before_b,\n after_b=after_b,\n before_sel=(\"2.0\", \"5.6\"),\n after_sel=(\"2.0\", \"5.10\"),\n command_name=\"add-tab-to-lines\",\n )","def list(args):\n experiments = sorted(os.listdir('./litmus'))\n print_color(\"Available Litmus Chaos Experiments:\\n\\n\")\n if (f\"{args.platform}\" == \"GKE\"):\n i = 1\n for experiment_file in experiments:\n print_color(f\"\\t{i}. {experiment_file.replace('.yaml', '')}\")\n i += 1\n\n if (f\"{args.platform}\" == \"kind\"):\n kind_supported = [\"pod-delete\",\"container-kill\",\"node-cpu-hog\",\"node-memory-hog\"]\n i = 0\n for i in range(0, len(kind_supported)):\n print_color(f\"\\t{i+1}. {kind_supported[i]}\")\n i += 1\n\n if (f\"{args.platform}\" == \"EKS\"):\n i = 1\n for experiment_file in experiments:\n print_color(f\"\\t{i}. {experiment_file.replace('.yaml', '')}\")\n i += 1","def test_suite():\n tests = [doctest.DocFileSuite(file,\n optionflags=doctest.ELLIPSIS) for file in docfiles]\n return unittest.TestSuite(tests)","def main(argv):\n\n opts = docopt.docopt(__doc__, version='ftree 0.1')\n\n dirs = opts['<dir>'] or ['.']\n for d in dirs:\n #print d\n print ListTree(d)\n\n return 0","def test_examples():\n argv = [\"py.test\", \"-examples\"]\n assert get_sargs(argv) is None","def _create_examples(self, lines: List[str], mode: Split):\n # id,title,content,label\n test_mode = mode == Split.test\n title_index = 1\n content_index = 2\n examples = []\n for (i, line) in enumerate(lines):\n if i == 0:\n continue\n guid = \"%s-%s\" % (mode.value, line[0])\n try:\n text_a = line[title_index]\n text_b = line[content_index]\n if test_mode:\n label = None\n else:\n label = line[3]\n except IndexError:\n continue\n examples.append(InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))\n return examples","def newTestSuite (self):\n self.newTab( extension = TestSuite.TYPE, repoDest=UCI.REPO_UNDEFINED )","def _create_examples(self, lines: List[str], mode: Split):\n examples = []\n text_index = 1 if mode == Split.test else 0\n for (i, line) in enumerate(lines):\n if i == 0:\n continue\n guid = \"%s-%s\" % (mode.value, i)\n text_a = line[text_index]\n if len(line) > text_index + 1:\n label = line[text_index + 1]\n else:\n label = None\n examples.append(InputExample(guid=guid, text_a=text_a, text_b=None, label=label))\n return examples","def tab_runs(env):\n return [TAB_ARGS]","def _get_tests(cls, suite: dict):\n suite_file_name = \"{}.py\".format(str(suite[\"id\"]).replace('.', os.path.sep))\n with open(suite_file_name) as f:\n file_contents = f.read()\n module = ast.parse(file_contents)\n functions = [node for node in module.body if isinstance(node, ast.FunctionDef)]\n docs = [ast.get_docstring(f) for f in functions if f.name.startswith(cls.TEST_PREFIX)]\n return docs","def describe_tests(remit, sourcelist):\n print('* run tests with \"%s\"' % remit)\n print('* tests to run: ')\n for line in pretty_list(sourcelist, 7):\n print(' ' + line)\n print('* writers to test: ')\n for line in pretty_list(spec.TEST['writer'], 7):\n print(' ' + line)\n print('* options to test: ')\n for line in pretty_list(spec.TEST['pandoc_options'], 7):\n print(' ' + line)\n print('* blacklisted: ')\n for config in spec.BLACKLIST:\n command = make_command(remit=remit,\n source='TEST',\n writer=config['writer'],\n pandoc_options=config['pandoc_options'],\n extension=config['extension'])\n print(' ' + ' '.join(command))\n print(' (' + config['comment'] + ')')","def experiment_list_table_format(result):\n table = []\n for item in result:\n table.append(experiment_show_table_format(item))\n return table","def newTestTxt(self):\n self.newTab( extension = TestTxt.TYPE, repoDest=UCI.REPO_UNDEFINED )","def workbench_scenarios():\n return [\n (\"SummaryXBlock\",\n \"\"\"<summary/>\n \"\"\"),\n (\"Multiple SummaryXBlock\",\n \"\"\"<vertical_demo>\n <summary/>\n <summary/>\n <summary/>\n </vertical_demo>\n \"\"\"),\n ]","def test_get_result_top_dir(self):\n pass","def create_robot_tests(fout):\n processed = {} # dict to avoid circular imports\n\n def get_all_keywords(resource):\n \"\"\"\n Helper function to recursively get keywords from resource files\n \"\"\"\n keywords = []\n resource.populate()\n for res in [i for i in resource.imports.data if isinstance(i, robot.parsing.settings.Resource)]:\n keyword_file = os.path.abspath('{}/{}'.format(res.directory, res.name))\n if keyword_file not in processed:\n res_obj = ResourceFile(keyword_file)\n processed[keyword_file] = res_obj\n keywords += get_all_keywords(res_obj)\n for keyword in resource.keywords:\n print(keyword.name)\n keywords.append(tuple((keyword.source, keyword.name, keyword.args.value if keyword.args.value else [])))\n return keywords\n\n fusion_api_resource = ResourceFile(MAIN_RESOURCE_FILE)\n for keyword in get_all_keywords(fusion_api_resource):\n fout.write('Test {}\\n'.format(keyword[1]))\n fout.write(' [Documentation] {}\\n'.format(keyword[0]))\n fout.write(' {} '.format(keyword[1]))\n for arg in keyword[2]:\n if '=' in arg:\n fout.write(' {} '.format(arg.split('=')[-1]))\n else:\n if arg.startswith('&'):\n fout.write(' testk=testv ')\n else:\n fout.write(' test ')\n fout.write('\\n\\n')","def _test_examples(self):\n checks = [\n (\n \"ex5_line-of-sight_solution\",\n [r\"RAJA sequential\", r\"RAJA OpenMP\", r\"result -- PASS\"],\n ),\n (\n \"ex6_stencil-offset-layout_solution\",\n [r\"RAJA Views \\(permuted\\)\", r\"result -- PASS\"],\n ),\n (\n \"ex8_tiled-matrix-transpose_solution\",\n [r\"parallel top inner loop\", r\"collapsed inner loops\", r\"result -- PASS\"],\n ),\n (\"kernel-dynamic-tile\", [r\"Running index\", r\"(24,24)\"]),\n (\"plugin-example\", [r\"Launching host kernel for the 10 time\"]),\n (\"tut_batched-matrix-multiply\", [r\"result -- PASS\"]),\n (\"wave-eqn\", [r\"Max Error = 2\", r\"Evolved solution to time\"]),\n ]\n for exe, expected in checks:\n reason = \"test: checking output of {0} for {1}\".format(exe, expected)\n self.run_test(\n exe,\n [],\n expected,\n installed=False,\n purpose=reason,\n skip_missing=True,\n work_dir=self._extra_tests_path,\n )","def tubs_from_filelist(file_list, verbose=False):\n tub_dirs = preprocessFileList(file_list)\n tubs = []\n count = 0\n root_path = Path(\"data\")\n for item in tub_dirs:\n if Path(item).is_dir():\n try:\n t = Tub(str(item),read_only=True)\n except FileNotFoundError as ex:\n continue\n except ValueError as ex:\n # In case the catalog file is empty\n continue\n tubs.append(t)\n count += len(t)\n if verbose:\n print( f\"Loaded {count} records.\" )\n\n return tubs","def test_get_result_top_files(self):\n pass","def alltests(opts):\n \n print \"API Root: %s\" % options.apiroot\n print \"Token: %s\" % options.token\n print \"Output dir: %s\" % options.output\n print \"Running %d%% of tests\" % options.percent\n print\n \n # need to use DEPT-001, not ID#\n coursehistory_tests = [\n # basic tests:\n \"cis-120\", \"math-114\", \"engl-101\", \"econ-001\",\n # miscellaneously somewhat problematic:\n \"engl-016\", \"law-205\", \"hpr-612\", \"rels-414\", \"nurs-322\",\n \"writ-030\", \"be-310\", \"psci-010\", \"psci-136\",\n # crosslistings:\n \"engl-135\", \"writ-135\", \"fnar-264\", \"cogs-001\", \"russ-048\", \"hist-048\",\n # no reviews?:\n \"afam-271\", \"ames-071\", \"slav-532\", \"afam-285\", \"prtg-213\", \"slav-533\",\n # errors:\n \"99999\", \"moo\",\n ]\n\n instructor_tests = [\n # basic tests:\n \"403\", \"631\", \"1883\", \"2217-FERNANDO-C--PEREIRA\", \"1602-BENJAMIN-PIERCE\",\n # crosslistings:\n \"1034-LYLE-H-UNGAR\", \"2709-DAVID-P--COMBERG\",\n # miscellaneously somewhat problematic:\n \"1040-DAVID-FOX\", \"4268-BART-GERARD-C-DE-JONGHE\",\n # the instructors w/ the most sections\n \"1883\", \"1619\", \"2869\", \"942\", \"1644\", \"541\", \"767\", \"434\",\n # concerned citizens:\n \"1759-MAX-C--CAVITCH\", \"2824-TIMOTHY-CORRIGAN\",\n \"1763-EMILY-R-STEINER\", \"1624-VALERIE-ROSS\",\n # no reviews?:\n \"416-LUDO-ROCHER\", \"715-ELIZABETH-ANN-POLLARD\", \"1094-MARIA-A-COWLES\",\n \"1500-ANDREW-GALLIA\", \"1888-RUSSELL-DILEO\",\n \"1450-SORMANE-PEREIRA-GOMES\", \"2188-HUI-YI-CHEN\", \"1165-DOMENIC-VITIELLO\",\n \"2359-CLAUDIA-CANCINO\", \"2737-SHEN-WANG\", \"3229-BERLE-WHITBY\",\n # errors:\n \"99999\", \"moo\",\n ]\n\n dept_tests = [\n #fast\n \"CSE\", \"LAW\", \"ANAT\", \"KORN\", \"LATN\", \"COGS\", \"MSCI\", \"GAS\",\n #medium\n \"CIS\", \"MATH\", \"FNAR\", \"ACCT\", \"FNCE\", \"BE\", \"MUSC\", \"OPIM\",\n #slow\n #\"SPAN\", \"NURS\", \"ENGL\",\n #error\n \"EROR\"]\n\n index_tests = [\"\", \"instructors\", \"coursehistories\", \"depts\",\n \"semesters\", \"semesters/2010c\"]\n\n course_tests = [] # filled in by coursehistory_tests\n\n for t in fraclist(index_tests, options.percent):\n test(opts, t)\n \n for t in fraclist(coursehistory_tests, options.percent):\n obj = test(opts, \"coursehistories/%s\" % t)\n test(opts, \"coursehistories/%s/reviews\" % t)\n\n # now \"find\" some courses\n course_tests.append(\"2010c-%s\" % t)\n try:\n courseid = sorted(obj[\"result\"][\"courses\"])[0][\"id\"]\n course_tests.append(courseid)\n except (TypeError, KeyError, IndexError):\n pass\n \n for t in course_tests: # don't fraclist an autogenerated list\n # Some of the autogenerated courses don't exist, so ignore errors.\n root_success = test(opts, \"courses/%s\" % t, lderror_ok=True)\n if root_success:\n # Course exists, don't expect errors.\n test(opts, \"courses/%s/reviews\" % t)\n test(opts, \"courses/%s/coursehistories/\" % t)\n test(opts, \"courses/%s/sections\" % t)\n \n if test(opts, \"courses/%s/sections/001\" % t, lderror_ok=True):\n test(opts, \"courses/%s/sections/001/reviews\" % t) \n if '-' in str(t): # if we have a yyyys-dept-num test\n test(opts, \"sections/%s-001\" % t)\n # not tested: sections/001/reviews/instructor-id\n test(opts, \"courses/%s/sections/401\" % t, lderror_ok=True)\n \n for t in fraclist(instructor_tests, options.percent):\n test(opts, \"instructors/%s\" % t)\n test(opts, \"instructors/%s/sections\" % t)\n test(opts, \"instructors/%s/reviews\" % t)\n \n for t in fraclist(dept_tests, options.percent):\n test(opts, \"depts/%s\" % t)\n test(opts, \"depts/%s/reviews\" % t)\n test(opts, \"semesters/2010c/%s\" % t)","def get_dev_examples(self, data_dir):\n\t\traise NotImplementedError()","def test_suite():\n return doctest.DocFileSuite(\n '../README.rst',\n 'server.rst',\n 'client.rst',\n optionflags=doctest.ELLIPSIS | doctest.NORMALIZE_WHITESPACE)","def make_tables(self):\n for t in self.tables:\n self.add_table(groupname=t['groupname'],\n tablename=t['tablename'],\n description=t['description'],\n tabletitle=t['tabletitle'])","def get_dev_examples(self, data_dir):\r\n raise NotImplementedError()","def get_dev_examples(self, data_dir):\r\n raise NotImplementedError()","def get_dev_examples(self, data_dir):\r\n raise NotImplementedError()","def get_dev_examples(self, data_dir):\r\n raise NotImplementedError()","def get_dev_examples(self, data_dir):\r\n raise NotImplementedError()","def get_dev_examples(self, data_dir):\r\n raise NotImplementedError()","def list_tables(option, opt, value, parser):\n print \"CCP Data Dump Table List\"\n print \"------------------------\"\n for table in util.IMPORT_LIST:\n print \"%s\" % table.__name__.replace('Importer_', '')\n print \"-- %d tables --\" % len(util.IMPORT_LIST)\n # The -l argument is just used for listing, proceed no further.\n exit_with_succ()","def _create_examples(self, df, mode):\n idx_tr, idx_te = next(ShuffleSplit(test_size=0.3, random_state=1234).split(df.title, df.totalViews))\n\n examples = []\n\n iterind = idx_tr if mode == \"train\" else idx_te\n\n for i in iterind:\n examples.append(\n InputExample(guid=i, text_a=df.title.values[i], label=df.totalViews.values[i]))\n\n return examples","def load_tests(loader, tests, ignore):\n tests.addTests(doctest.DocTestSuite(l))\n return tests","def _display_examples(self):\n\n print(self._usage)\n print(self._examples)","def demonstration_examples(kind):\n\n DIR = './data/demos/'\n RNN_DEMO = \"-demo_rnn_examples\"\n EXT = '.pkl'\n\n if kind == 'rnn':\n return pd.read_pickle(DIR+RNN_DEMO+EXT)","def node_setup_files_list_table_format(result):\n table = []\n for item in result:\n row = OrderedDict()\n row['Name'] = item['name']\n row['Is directory'] = 'yes' if item['is_directory'] else 'no'\n row['Size'] = '' if item['size'] is None else (item['size'] or '0')\n table.append(row)\n return table","def pretty_runlist(runlist):\n if not runlist:\n return [' empty']\n output = list()\n current_kind = str()\n for i, entry in enumerate(runlist):\n if current_kind != entry['kind']:\n output.append(entry['kind'] + ':')\n current_kind = entry['kind']\n path = entry['command']\n basename = os.path.splitext(os.path.basename(path))[0]\n line = ' %d %s' % (i+1, basename)\n line = line.ljust(20)\n line += '\"%s\"' % pretty_path(path)\n output.append(line)\n return output","def vocab_tables(source_file, tags_file):\n pass","def load_demos():\n for index in range(len(feconf.DEMO_EXPLORATIONS)):\n load_demo(str(index))","def test_text_classifier_add_testing_samples(self):\n pass","def test_suite():\n testSuite = unittest.TestSuite()\n testSuite.addTest(test_h5fs(\"test_mode\"))\n testSuite.addTest(test_h5fs(\"test_path_splitting\"))\n testSuite.addTest(test_h5fs(\"test_link_mixing\"))\n return testSuite","def testsuite():\n \n tests = unittest.TestSuite()\n\n parse_tests = unittest.makeSuite(ParseTestCase, 'test')\n tests = unittest.TestSuite( (tests, parse_tests) )\n\n return tests","def test_tabs():\n for _, modname, ispkg in walk_packages(mne.__path__, prefix=\"mne.\"):\n # because we don't import e.g. mne.tests w/mne\n if not ispkg and modname not in tab_ignores:\n try:\n mod = importlib.import_module(modname)\n except Exception: # e.g., mne.export not having pybv\n continue\n source = inspect.getsource(mod)\n assert \"\\t\" not in source, (\n '\"%s\" has tabs, please remove them '\n \"or add it to the ignore list\" % modname\n )","def test_pep8_conformance_example(self):\n\n print(\"\\r\\n\")\n\n # Get the path to current directory\n path = os.path.dirname(os.path.realpath(__file__))\n path += \"/../docs/examples/\"\n\n # Find all the examples files\n file_paths = []\n for root, dirnames, filenames in os.walk(path):\n for file_path in fnmatch.filter(filenames, '*.py'):\n file_paths.append(os.path.join(root, file_path))\n\n for path in file_paths:\n self.run_check(path)","def load_tests(loader, tests, ignore):\n tests.addTests(doctest.DocTestSuite(Descriptors, optionflags=doctest.ELLIPSIS))\n return tests","def test_main(self):\n dummy_folder = TestOspaListDir.get_dummy_folder()\n result = listdir(dummy_folder,\n full_path=True,\n only_files=False,\n )\n need_result = ['memes',\n 'txt_files',\n 'antigravity.png',\n 'egg.png',\n 'empty.txt',\n 'holy_grenade.png',\n 'spam.jpg',\n ]\n need_result = [os.path.join(dummy_folder, x) for x in need_result]\n self.assertEqual(sorted(need_result), sorted(result))\n\n result = listdir(dummy_folder,\n full_path=False,\n only_files=False,\n )\n need_result = ['memes',\n 'txt_files',\n 'antigravity.png',\n 'egg.png',\n 'empty.txt',\n 'holy_grenade.png',\n 'spam.jpg',\n ]\n\n self.assertEqual(sorted(need_result), sorted(result))\n\n result = listdir(dummy_folder,\n full_path=True,\n only_files=True,\n )\n need_result = ['antigravity.png',\n 'egg.png',\n 'empty.txt',\n 'holy_grenade.png',\n 'spam.jpg',\n ]\n need_result = [os.path.join(dummy_folder, x) for x in need_result]\n self.assertEqual(sorted(need_result), sorted(result))\n self.assertEqual(sorted(os.listdir('.')), sorted(listdir(path='.', full_path=False)))","def workbench_scenarios():\n return [\n (\"Markdown\",\n \"\"\"<markdowna />\n \"\"\")\n ]","def test_current_file(self) -> Generator[int, None, None]:\n setting: ShowCaptionsTabSetting = ShowCaptionsTabSetting(\n self.settings,\n sublime.active_window()\n )\n\n dir: str = path.dirname(__file__)\n\n foo_fixture: str = path.normpath(\n path.join(dir, \"./fixtures/foo.txt\")\n )\n bar_fixture: str = path.normpath(\n path.join(dir, \"./fixtures/bar.txt\")\n )\n\n foo_view: sublime.View = sublime.active_window().open_file(foo_fixture)\n bar_view: sublime.View = sublime.active_window().open_file(bar_fixture)\n\n data_set: Tuple[Tuple[List[Tab], List[List[str]], sublime.View], ...]\n\n data_set = (\n ([Tab(foo_view), Tab(bar_view)], [['Current File'], []], foo_view),\n ([Tab(foo_view), Tab(bar_view)], [[], ['Current File']], bar_view),\n )\n\n yield 100\n\n for (tabs, captions, view) in data_set:\n with self.subTest(tabs=tabs, captions=view, view=view):\n view.window().focus_view(view)\n self.assertTrue(setting.is_enabled())\n self.assertListEqual(tabs, setting.apply(tabs))\n actual = []\n for tab in tabs:\n actual.append(tab.get_captions())\n self.assertListEqual(captions, actual)","def autogen_dataset_dir_with_test():\n return TabularDataset.autogen('tests/data/dummy_tabular',\n test_path='tests/data/dummy_tabular_test',\n seed=42,\n sep=',')","def tests_generator(self):\n cb_bin = os.path.join(bin_path, 'compilebench')\n cmd_list = [\n (\"Initial Create/Compile/Read Compiled Tree\", \"{0} -D {1} -i 10 --makej -s {2}\"),\n ]\n\n tests = []\n for idx, (desc, cmd) in enumerate(cmd_list):\n test_name = \"compile_bench_{0}_{1}\".format(idx + 1, to_safe_name(desc))\n test = TestProfile(\n name=test_name,\n desc=desc,\n test_path=self.test_path,\n bin_path=bin_path,\n command=cmd.format(cb_bin, self.test_path, bin_path))\n tests.append(test)\n return tests"],"string":"[\n \"def generate_test_list(tdir):\\n\\n # Skip this if it already exists\\n if os.path.exists(os.path.join(tdir.name, \\\"kstest-list\\\")):\\n return\\n\\n kstest_log = os.path.join(tdir.name, \\\"kstest.log\\\")\\n with open(kstest_log) as f:\\n for line in f.readlines():\\n if not line.startswith(\\\"Running tests: \\\"):\\n continue\\n\\n tests = [os.path.basename(os.path.splitext(s)[0]) for s in line[15:].split()]\\n with open(os.path.join(tdir.name, \\\"kstest-list\\\"), \\\"wt\\\") as klf:\\n for t in tests:\\n print(t, file=klf)\\n break\",\n \"def list(ctx):\\n handler = ValidateCommandHandler(ctx.obj['qa_dir'])\\n if handler.validate():\\n handler = ListCommandHandler(ctx.obj['qa_dir'])\\n handler.show_test_case_tree()\\n else:\\n exit(1)\",\n \"def test_examples():\\n tests = [d for d in listdir(ex) if path.isdir(path.join(ex, d))]\\n for d in tests:\\n yield check_examples, d\",\n \"def _generate_examples(self, folders, split):\\n raise NotImplementedError(\\\"TODO\\\")\",\n \"def tabulate_tribes():\\n tribes = {}\\n for tribe in os.listdir('tribes'):\\n tribes[tribe[:-3].title()] = 'tribes/' + tribe[:-3]\\n table = tabulate(list(sorted(tribes)))\\n for tribe in tribes:\\n table = table.replace(tribe, f'[{tribe}]({tribes[tribe]})')\\n return table\",\n \"def _generate_examples(self, filepath):\\n\\n key = 1\\n with tf.io.gfile.GFile(filepath, \\\"r\\\") as f:\\n tokens = []\\n tags = []\\n langs = []\\n for line in f:\\n line = line.rstrip()\\n # pylint: disable=g-explicit-bool-comparison\\n if line.startswith(\\\"-DOCSTART-\\\") or line == \\\"\\\":\\n if tokens:\\n spans = get_spans(tokens, tags)\\n yield key, {\\n \\\"tokens\\\": tokens,\\n \\\"tags\\\": tags,\\n \\\"langs\\\": langs,\\n \\\"spans\\\": spans\\n }\\n key += 1\\n tokens = []\\n tags = []\\n langs = []\\n else:\\n # wikiann data is tab separated\\n fields = line.split(\\\"\\\\t\\\")\\n # strip out language prefix\\n langs.append(fields[0].split(\\\":\\\")[0])\\n tokens.append(\\\":\\\".join(fields[0].split(\\\":\\\")[1:]))\\n if len(fields) > 1:\\n tags.append(fields[-1])\\n else:\\n # examples have no label in test set\\n tags.append(\\\"O\\\")\\n if tokens:\\n spans = get_spans(tokens, tags)\\n yield key, {\\n \\\"tokens\\\": tokens,\\n \\\"tags\\\": tags,\\n \\\"langs\\\": langs,\\n \\\"spans\\\": spans\\n }\",\n \"def workbench_scenarios():\\n return [\\n (\\\"filethumbs\\\",\\n \\\"\\\"\\\"\\\\\\n <vertical_demo>\\n <filethumbs/>\\n <filethumbs/>\\n <filethumbs/>\\n </vertical_demo>\\n \\\"\\\"\\\")\\n ]\",\n \"def get_test_examples(self, data_dir):\\n raise NotImplementedError()\",\n \"def get_test_examples(self, data_dir):\\n raise NotImplementedError()\",\n \"def get_tests():\\n\\tret = []\\n\\tfor walk_tuple in os.walk(webnotes.defs.modules_path):\\n\\t\\tfor test_file in filter(lambda x: x.startswith('test') and x.endswith('.py'), walk_tuple[2]):\\n\\t\\t\\tdir_path = os.path.relpath(walk_tuple[0], webnotes.defs.modules_path)\\n\\t\\t\\tif dir_path=='.':\\n\\t\\t\\t\\tret.append(test_file[:-3])\\n\\t\\t\\telse:\\n\\t\\t\\t\\tret.append(dir_path.replace('/', '.') + '.' + test_file[:-3])\\t\\t\\t\\n\\treturn ret\",\n \"def test_tabify(self):\\n before_b = \\\"\\\"\\\"\\\\\\n first line\\n line 1\\n line a\\n line b\\n line c\\n last line\\n \\\"\\\"\\\"\\n after_b = \\\"\\\"\\\"\\\\\\n first line\\n line 1\\n \\tline a\\n \\t\\tline b\\n line c\\n last line\\n \\\"\\\"\\\"\\n self.run_test(\\n before_b=before_b,\\n after_b=after_b,\\n before_sel=(\\\"1.0\\\", \\\"7.0\\\"),\\n after_sel=(\\\"7.0\\\", \\\"7.0\\\"),\\n command_name=\\\"tabify\\\",\\n )\",\n \"def _generate_examples(self, files):\\n idx = 0\\n for filename in files:\\n with open(filename) as file:\\n for line in file:\\n yield idx, {\\\"text\\\": line}\\n idx += 1\",\n \"def test_get_result_top_dirs(self):\\n pass\",\n \"def make_toc(c: Cmdr, kind: str, root: Position) -> str:\\n\\n def cell_type(p: Position) -> str:\\n language = g.getLanguageAtPosition(c, p)\\n return 'markdown' if language in ('jupyter', 'markdown') else 'python'\\n\\n def clean_headline(s: str) -> str:\\n # Surprisingly tricky. This could remove too much, but better to be safe.\\n aList = [ch for ch in s if ch in '-: ' or ch.isalnum()]\\n return ''.join(aList).rstrip('-').strip()\\n\\n result: list[str] = []\\n stack: list[int] = []\\n for p in root.subtree():\\n if cell_type(p) == 'markdown':\\n level = p.level() - root.level()\\n if len(stack) < level:\\n stack.append(1)\\n else:\\n stack = stack[:level]\\n n = stack[-1]\\n stack[-1] = n + 1\\n # Use bullets\\n title = clean_headline(p.h)\\n url = clean_headline(p.h.replace(' ', '-'))\\n if kind == 'markdown':\\n url = url.lower()\\n line = f\\\"{' ' * 4 * (level - 1)}- [{title}](#{url})\\\\n\\\"\\n result.append(line)\\n if result:\\n result.append('\\\\n')\\n return ''.join(result)\",\n \"def _create_examples(self, data_dir, set_type):\\n\\t\\texamples = []\\n\\t\\tinput_file_data = os.path.join(data_dir, \\\"data.tsv\\\")\\n\\t\\twith open(input_file_data, \\\"r\\\", encoding=\\\"utf-8-sig\\\") as f:\\n\\t\\t\\tfor i, inp in enumerate(f):\\n\\t\\t\\t\\tinps = inp.split('\\\\t') \\n\\t\\t\\t\\tguid = \\\"%s-%s\\\" % (set_type, i)\\n\\t\\t\\t\\ttext_inp = inps[1].strip()\\n\\t\\t\\t\\ttext_out = inps[2].strip()\\n\\t\\t\\t\\texamples.append(InputExample(guid=guid, text_inp=text_inp, text_out=text_out))\\n\\t\\t\\t\\t\\n\\t\\t\\t# Sort these out before returning\\n\\t\\t\\texamples = sorted(examples, key=sort_inp_len)\\n\\t\\t\\treturn examples\",\n \"def get_test_examples(self, data_dir):\\n \\n raise NotImplementedError()\",\n \"def zio_test_help():\\n print(\\\"zio-ut [TESTS]\\\")\\n print(\\\"\\\")\\n print(\\\"[TESTS]: list of tests to perform. It can be the name of a specific test, or the name of a module of tests\\\")\\n print(\\\" In alternative, you che use the test code:\\\")\\n print(\\\"Code test case\\\")\\n print(\\\"- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - \\\")\\n i = 0\\n for t in test_list:\\n print(str(i) + \\\" \\\" + t)\\n i = i + 1\",\n \"def run_tests():\\r\\n p = Parser(b\\\"0About prices\\\\tPrices/aboutus\\\\tserver.example.com\\\\t70\\\\r\\\\n\\\".decode(\\\"ascii\\\"))\\r\\n print(p._parse_dir())\",\n \"def dir_dataset():\\n return TabularDataset.from_path('tests/data/dummy_tabular', sep=',')\",\n \"def master_test_suite( pkg_mod_iter ):\\n master_suite= unittest.TestSuite()\\n for package, module_iter in pkg_mod_iter:\\n for filename, module in module_iter:\\n print( package+\\\".\\\"+module )\\n suite= doctest.DocTestSuite( package+\\\".\\\"+module )\\n print( \\\" \\\", suite )\\n master_suite.addTests( suite )\\n runner= unittest.TextTestRunner( verbosity=1 )\\n runner.run( master_suite )\",\n \"def get_test_examples(self, data_dir):\\n raise NotImplementedError()\",\n \"def get_test_examples(self, data_dir):\\n raise NotImplementedError()\",\n \"def get_test_examples(self, data_dir):\\n raise NotImplementedError()\",\n \"def get_test_examples(self, data_dir):\\n raise NotImplementedError()\",\n \"def get_test_examples(self, data_dir):\\n raise NotImplementedError()\",\n \"def test_file_shizz(topic_path):\\n\\tL = [[1,2,3],[4,5,6]]\\n\\tprint(open(topic_path+'/D/'+str(L[1][0])+'.txt'))\",\n \"def get_examples():\\n # Get the tjson test cases from a url.\\n examples = urlopen(TJSON_EXAMPLES_URL).read()\\n\\n # Strip comments from the lines.\\n examples = re.sub(r\\\"^#.*\\\\n?\\\", \\\"\\\", examples.decode(), flags=re.MULTILINE)\\n\\n # Split a group of examples.\\n delimiter = re.escape(EXAMPLES_DELIMITER)\\n example_re = re.compile(delimiter + r'(.*?)' + delimiter, re.S)\\n split = re.findall(example_re, examples)\\n\\n # Create the `Example` named tuples.\\n return [\\n parse_example(example)\\n for example in split]\",\n \"def get_test_examples(self, data_path):\\r\\n return self.create_examples(self.read_data(data_path), 'test')\",\n \"def main():\\n\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"folder\\\")\\n args = parser.parse_args()\\n \\n print(\\\"\\\")\\n print(\\\"Smart Listing:\\\", args.folder.replace(\\\"/\\\", \\\" >\\\"))\\n print(\\\"\\\")\\n for seq, frange in parsefilenames(os.listdir(args.folder)):\\n print(len(frange), seq, frange)\",\n \"def ConstrTest():\\n with open(path.join(MAIN_PATH, TEST)) as f:\\n for line in f:\\n line = line.strip().split(\\\"\\\\t\\\")\\n src, dest = line[1:]\\n features = Features(src, dest)\\n test_instances.append(features)\",\n \"def test_suite():\\n suite = unittest.TestSuite()\\n suite.addTests(\\n [\\n layered(\\n doctest.DocFileSuite(\\\"behaviors.rst\\\"),\\n layer=testing.TEXT_INTEXER_INTEGRATION_TESTING,\\n ),\\n ]\\n )\\n return suite\",\n \"def test_toc(self):\\n with sphinx_build('pyexample'):\\n with open('_build/text/docfx_yaml/toc.yml') as yml_file:\\n data = yaml.safe_load(yml_file)\\n for item in data:\\n if 'items' in item:\\n self.assertEqual(\\n item['items'][0]['name'],\\n 'example.enum_type.EnumFoo'\\n )\\n break\",\n \"def test_suite():\\n test_loader = unittest.TestLoader()\\n # Read in unit tests\\n test_suite = test_loader.discover('tests')\\n\\n # Read in doctests from README\\n test_suite.addTests(doctest.DocFileSuite('README.md',\\n optionflags=doctest.ELLIPSIS))\\n return test_suite\",\n \"def discover_examples():\\n root = './examples'\\n for filename in os.listdir(root):\\n if os.path.splitext(filename)[1] == '.py':\\n yield os.path.join(root, filename)\",\n \"def fmt_folder(folder):\\n result = []\\n\\n folder_dir = localizer_config.get_src_path(folder)\\n if not os.path.isdir(folder_dir):\\n localizer_log.error(\\\"folder \\\" + folder + ' not exist. Abort.')\\n\\n experiments = [x for x in os.listdir(folder_dir)\\n if os.path.isdir(os.path.join(folder_dir, x))]\\n\\n list_size = len(kpi_info.kpi_list)\\n import util.runtime as runtime\\n for exp_name in experiments:\\n exp = runtime.find_exp_by_name(exp_name)\\n if not exp:\\n localizer_log.warning(\\\"Experiment {exp} not found\\\"\\n .format(exp=exp_name))\\n continue\\n exp_dir = os.path.join(folder_dir, exp_name)\\n files = [x for x in os.listdir(exp_dir) if x.endswith('.txt')]\\n timeset = [int(filename.strip().replace('.txt', ''))\\n for filename in files]\\n\\n for t in sorted(timeset):\\n lst = [0 for i in range(list_size)]\\n with open(os.path.join(exp_dir, str(t) + '.txt')) as f:\\n for l in f:\\n idx = kpi_info.get_index(l.strip())\\n lst[idx] = 1\\n result.append(PredData(exp, str(t), lst))\\n\\n return result\",\n \"def create_file_overview_doc() -> None:\\n folder_file_docstring = generate_folder_file_docstrings_dict()\\n\\n table_markdown = []\\n for folder in folder_file_docstring:\\n dictionary_of_files = folder_file_docstring[folder]\\n\\n folder_text = folder\\n for file in sorted(dictionary_of_files):\\n new_row = f\\\"| {folder_text:{COLUMN_WIDTHS[0]}}| {file:{COLUMN_WIDTHS[1]}}| {folder_file_docstring[folder][file]:{COLUMN_WIDTHS[2]}}|\\\\n\\\"\\n table_markdown.append(new_row)\\n folder_text = \\\" \\\"\\n\\n # adding blank row at the end of every folder\\n table_markdown.append(BLANK_ROW)\\n\\n # Folders that do not contain any files with docstrings are added separately to the file-overview\\n for folder_name in sorted(DESC_FOR_NO_FILE_FOLDERS):\\n new_row = f\\\"| {folder_name:{COLUMN_WIDTHS[0]}}| {SPACEBAR:{COLUMN_WIDTHS[1]}}| {DESC_FOR_NO_FILE_FOLDERS[folder_name]:{COLUMN_WIDTHS[2]}}|\\\\n\\\"\\n table_markdown.extend([new_row, BLANK_ROW])\\n\\n with open(DEVELOPER_DOC_PATH, \\\"r\\\") as dev_file:\\n doc_data = dev_file.readlines()\\n\\n doc_data[TABLE_OFFSET - 1 :] = table_markdown[:-1]\\n updated_data = \\\"\\\".join(doc_data)\\n\\n with open(DEVELOPER_DOC_PATH, \\\"w\\\") as dev_file:\\n dev_file.write(updated_data)\",\n \"def tab(self):\\n\\n extension = ['.zip', '.tar.gz', '.rar', '.7z']\\n return ['compress ' + os.path.basename(self.fm.thisdir.path) + ext for ext in extension]\",\n \"def test(self, absList, modelFilename, fold=None):\\n raise NotImplementedError(\\\"Need to implement test()\\\")\",\n \"def list_tests(arn=None, nextToken=None):\\n pass\",\n \"def printReftestList():\\n print(\\\"Generating reftestList.js...\\\", end=\\\"\\\")\\n\\n suite = reftest.reftestSuite()\\n fp = file(MATHJAX_WEB_PATH + \\\"reftestList.js\\\", \\\"w\\\")\\n stdout = sys.stdout\\n sys.stdout = fp\\n print(\\\"// \\\" + WARNING_GENERATED_FILE)\\n print(\\\"/**\\\")\\n print(\\\" * @file reftestList.js\\\")\\n print(\\\" * @brief array representing the test suite.\\\")\\n print(\\\" *\\\")\\n print(\\\" * This file is generated by runTestsuite.py -p\\\")\\n print(\\\" *\\\")\\n print(\\\" * @var Array gTestSuite\\\")\\n print(\\\" * An array representing the file hierarchy of the test suite\\\")\\n print(\\\" */\\\")\\n print(\\\"var gTestSuite = [\\\\\\\"testsuite/\\\\\\\"\\\", end=\\\"\\\")\\n suite.addReftests(\\\"printList\\\",\\n MATHJAX_TESTSUITE_PATH, \\\"reftest.list\\\", -1)\\n print(\\\"]\\\")\\n sys.stdout = stdout\\n fp.close()\\n\\n print(\\\"done\\\")\",\n \"def get_dev_examples(self, data_dir):\\r\\n raise NotImplementedError()\",\n \"def tabular_data(self):\\n path = CFG.GRAPHS_DIR\\n chdir(path)\\n\\n if self.experiment_count == 1:\\n f = open(self.tablefile, 'w')\\n f.write(self.print_border_line())\\n f.write(self.table_header())\\n f.write(self.print_border_line())\\n f.write(self.pretty_string(\\\"Functions\\\"))\\n f.write(self.pretty_string(\\\"Batch Size\\\"))\\n f.write(self.pretty_string(\\\"Training (%)\\\"))\\n f.write(self.pretty_string(\\\"Testing (%)\\\", True))\\n f.write('\\\\n')\\n f.write(self.print_border_line())\\n f.close()\\n\\n f = open(self.tablefile, 'a')\\n f.write(self.pretty_string(self.function_name))\\n f.write(self.pretty_string(str(self.batch_size)))\\n f.write(self.pretty_string(self.tr_mean_str))\\n f.write(self.pretty_string(self.test_mean_str, True))\\n f.write('\\\\n')\\n f.close()\",\n \"def generate_test_list(self, **kwargs):\\n LOGGER.debug(\\\"Generating test case list...\\\")\\n self.backup_tempest_config(self.conf_file, '/etc')\\n if kwargs.get('mode') == 'custom':\\n if os.path.isfile(self.tempest_custom):\\n shutil.copyfile(\\n self.tempest_custom, self.list)\\n else:\\n raise Exception(\\n f\\\"Tempest test list file {self.tempest_custom} NOT found.\\\")\\n else:\\n testr_mode = kwargs.get(\\n 'mode', r'^tempest\\\\.(api|scenario).*\\\\[.*\\\\bsmoke\\\\b.*\\\\]$')\\n cmd = (f\\\"(cd {self.verifier_repo_dir}; \\\"\\n f\\\"stestr list '{testr_mode}' > {self.list} 2>/dev/null)\\\")\\n output = subprocess.check_output(cmd, shell=True)\\n LOGGER.info(\\\"%s\\\\n%s\\\", cmd, output.decode(\\\"utf-8\\\"))\\n os.remove('/etc/tempest.conf')\",\n \"def KittiTestDataset(test_root_path):\\n \\n names = os.listdir(test_root_path)\\n dataset = [[os.path.join(test_root_path, name)] for name in names]\\n \\n return dataset\",\n \"def _create_test_module_heading(nbdir):\\n heading = 'import os\\\\n'\\\\\\n 'import sys\\\\n'\\\\\\n 'import test_func as tf\\\\n\\\\n'\\\\\\n '#make projectdir accessible inside this script\\\\n'\\\\\\n 'tst_dir = os.path.dirname(os.path.realpath(__file__))\\\\n'\\\\\\n f'nb_dir = os.path.join(tst_dir, \\\"..\\\", *{os.path.split(nbdir)})\\\\n' # noqa E501\\n\\n return heading\",\n \"def run_test_suite( pkg_mod_iter ):\\n for package, module_iter in pkg_mod_iter:\\n print( package )\\n print( \\\"=\\\"*len(package ) )\\n print()\\n for filename, module in module_iter:\\n suite= doctest.DocTestSuite( package+\\\".\\\"+module )\\n runner= unittest.TextTestRunner( verbosity=1 )\\n runner.run( suite )\",\n \"def get_dev_examples(self, data_dir):\\n raise NotImplementedError()\",\n \"def get_dev_examples(self, data_dir):\\n raise NotImplementedError()\",\n \"def test(self, absList, modelfilename, fold=None):\\n raise NotImplementedError(\\\"Need to implement test()\\\")\",\n \"def example(*paths):\\n\\n return normpath(join(dirname(__file__), '..', 'examples', *paths))\",\n \"def workbench_scenarios(): \\n return [\\n (\\\"TermsXBlock\\\",\\n \\\"\\\"\\\"<terms/>\\n \\\"\\\"\\\"),\\n (\\\"Multiple TermsXBlock\\\",\\n \\\"\\\"\\\"<vertical_demo>\\n <terms/>\\n <terms/>\\n <terms/>\\n </vertical_demo>\\n \\\"\\\"\\\"),\\n ]\",\n \"def test_add_tab_to_lines(self):\\n before_b = \\\"\\\"\\\"\\\\\\n first line\\n line 1\\n line a\\n line b\\n line c\\n last line\\n \\\"\\\"\\\"\\n after_b = \\\"\\\"\\\"\\\\\\n first line\\n line 1\\n line a\\n line b\\n line c\\n last line\\n \\\"\\\"\\\"\\n self.run_test(\\n before_b=before_b,\\n after_b=after_b,\\n before_sel=(\\\"2.0\\\", \\\"5.6\\\"),\\n after_sel=(\\\"2.0\\\", \\\"5.10\\\"),\\n command_name=\\\"add-tab-to-lines\\\",\\n )\",\n \"def list(args):\\n experiments = sorted(os.listdir('./litmus'))\\n print_color(\\\"Available Litmus Chaos Experiments:\\\\n\\\\n\\\")\\n if (f\\\"{args.platform}\\\" == \\\"GKE\\\"):\\n i = 1\\n for experiment_file in experiments:\\n print_color(f\\\"\\\\t{i}. {experiment_file.replace('.yaml', '')}\\\")\\n i += 1\\n\\n if (f\\\"{args.platform}\\\" == \\\"kind\\\"):\\n kind_supported = [\\\"pod-delete\\\",\\\"container-kill\\\",\\\"node-cpu-hog\\\",\\\"node-memory-hog\\\"]\\n i = 0\\n for i in range(0, len(kind_supported)):\\n print_color(f\\\"\\\\t{i+1}. {kind_supported[i]}\\\")\\n i += 1\\n\\n if (f\\\"{args.platform}\\\" == \\\"EKS\\\"):\\n i = 1\\n for experiment_file in experiments:\\n print_color(f\\\"\\\\t{i}. {experiment_file.replace('.yaml', '')}\\\")\\n i += 1\",\n \"def test_suite():\\n tests = [doctest.DocFileSuite(file,\\n optionflags=doctest.ELLIPSIS) for file in docfiles]\\n return unittest.TestSuite(tests)\",\n \"def main(argv):\\n\\n opts = docopt.docopt(__doc__, version='ftree 0.1')\\n\\n dirs = opts['<dir>'] or ['.']\\n for d in dirs:\\n #print d\\n print ListTree(d)\\n\\n return 0\",\n \"def test_examples():\\n argv = [\\\"py.test\\\", \\\"-examples\\\"]\\n assert get_sargs(argv) is None\",\n \"def _create_examples(self, lines: List[str], mode: Split):\\n # id,title,content,label\\n test_mode = mode == Split.test\\n title_index = 1\\n content_index = 2\\n examples = []\\n for (i, line) in enumerate(lines):\\n if i == 0:\\n continue\\n guid = \\\"%s-%s\\\" % (mode.value, line[0])\\n try:\\n text_a = line[title_index]\\n text_b = line[content_index]\\n if test_mode:\\n label = None\\n else:\\n label = line[3]\\n except IndexError:\\n continue\\n examples.append(InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))\\n return examples\",\n \"def newTestSuite (self):\\n self.newTab( extension = TestSuite.TYPE, repoDest=UCI.REPO_UNDEFINED )\",\n \"def _create_examples(self, lines: List[str], mode: Split):\\n examples = []\\n text_index = 1 if mode == Split.test else 0\\n for (i, line) in enumerate(lines):\\n if i == 0:\\n continue\\n guid = \\\"%s-%s\\\" % (mode.value, i)\\n text_a = line[text_index]\\n if len(line) > text_index + 1:\\n label = line[text_index + 1]\\n else:\\n label = None\\n examples.append(InputExample(guid=guid, text_a=text_a, text_b=None, label=label))\\n return examples\",\n \"def tab_runs(env):\\n return [TAB_ARGS]\",\n \"def _get_tests(cls, suite: dict):\\n suite_file_name = \\\"{}.py\\\".format(str(suite[\\\"id\\\"]).replace('.', os.path.sep))\\n with open(suite_file_name) as f:\\n file_contents = f.read()\\n module = ast.parse(file_contents)\\n functions = [node for node in module.body if isinstance(node, ast.FunctionDef)]\\n docs = [ast.get_docstring(f) for f in functions if f.name.startswith(cls.TEST_PREFIX)]\\n return docs\",\n \"def describe_tests(remit, sourcelist):\\n print('* run tests with \\\"%s\\\"' % remit)\\n print('* tests to run: ')\\n for line in pretty_list(sourcelist, 7):\\n print(' ' + line)\\n print('* writers to test: ')\\n for line in pretty_list(spec.TEST['writer'], 7):\\n print(' ' + line)\\n print('* options to test: ')\\n for line in pretty_list(spec.TEST['pandoc_options'], 7):\\n print(' ' + line)\\n print('* blacklisted: ')\\n for config in spec.BLACKLIST:\\n command = make_command(remit=remit,\\n source='TEST',\\n writer=config['writer'],\\n pandoc_options=config['pandoc_options'],\\n extension=config['extension'])\\n print(' ' + ' '.join(command))\\n print(' (' + config['comment'] + ')')\",\n \"def experiment_list_table_format(result):\\n table = []\\n for item in result:\\n table.append(experiment_show_table_format(item))\\n return table\",\n \"def newTestTxt(self):\\n self.newTab( extension = TestTxt.TYPE, repoDest=UCI.REPO_UNDEFINED )\",\n \"def workbench_scenarios():\\n return [\\n (\\\"SummaryXBlock\\\",\\n \\\"\\\"\\\"<summary/>\\n \\\"\\\"\\\"),\\n (\\\"Multiple SummaryXBlock\\\",\\n \\\"\\\"\\\"<vertical_demo>\\n <summary/>\\n <summary/>\\n <summary/>\\n </vertical_demo>\\n \\\"\\\"\\\"),\\n ]\",\n \"def test_get_result_top_dir(self):\\n pass\",\n \"def create_robot_tests(fout):\\n processed = {} # dict to avoid circular imports\\n\\n def get_all_keywords(resource):\\n \\\"\\\"\\\"\\n Helper function to recursively get keywords from resource files\\n \\\"\\\"\\\"\\n keywords = []\\n resource.populate()\\n for res in [i for i in resource.imports.data if isinstance(i, robot.parsing.settings.Resource)]:\\n keyword_file = os.path.abspath('{}/{}'.format(res.directory, res.name))\\n if keyword_file not in processed:\\n res_obj = ResourceFile(keyword_file)\\n processed[keyword_file] = res_obj\\n keywords += get_all_keywords(res_obj)\\n for keyword in resource.keywords:\\n print(keyword.name)\\n keywords.append(tuple((keyword.source, keyword.name, keyword.args.value if keyword.args.value else [])))\\n return keywords\\n\\n fusion_api_resource = ResourceFile(MAIN_RESOURCE_FILE)\\n for keyword in get_all_keywords(fusion_api_resource):\\n fout.write('Test {}\\\\n'.format(keyword[1]))\\n fout.write(' [Documentation] {}\\\\n'.format(keyword[0]))\\n fout.write(' {} '.format(keyword[1]))\\n for arg in keyword[2]:\\n if '=' in arg:\\n fout.write(' {} '.format(arg.split('=')[-1]))\\n else:\\n if arg.startswith('&'):\\n fout.write(' testk=testv ')\\n else:\\n fout.write(' test ')\\n fout.write('\\\\n\\\\n')\",\n \"def _test_examples(self):\\n checks = [\\n (\\n \\\"ex5_line-of-sight_solution\\\",\\n [r\\\"RAJA sequential\\\", r\\\"RAJA OpenMP\\\", r\\\"result -- PASS\\\"],\\n ),\\n (\\n \\\"ex6_stencil-offset-layout_solution\\\",\\n [r\\\"RAJA Views \\\\(permuted\\\\)\\\", r\\\"result -- PASS\\\"],\\n ),\\n (\\n \\\"ex8_tiled-matrix-transpose_solution\\\",\\n [r\\\"parallel top inner loop\\\", r\\\"collapsed inner loops\\\", r\\\"result -- PASS\\\"],\\n ),\\n (\\\"kernel-dynamic-tile\\\", [r\\\"Running index\\\", r\\\"(24,24)\\\"]),\\n (\\\"plugin-example\\\", [r\\\"Launching host kernel for the 10 time\\\"]),\\n (\\\"tut_batched-matrix-multiply\\\", [r\\\"result -- PASS\\\"]),\\n (\\\"wave-eqn\\\", [r\\\"Max Error = 2\\\", r\\\"Evolved solution to time\\\"]),\\n ]\\n for exe, expected in checks:\\n reason = \\\"test: checking output of {0} for {1}\\\".format(exe, expected)\\n self.run_test(\\n exe,\\n [],\\n expected,\\n installed=False,\\n purpose=reason,\\n skip_missing=True,\\n work_dir=self._extra_tests_path,\\n )\",\n \"def tubs_from_filelist(file_list, verbose=False):\\n tub_dirs = preprocessFileList(file_list)\\n tubs = []\\n count = 0\\n root_path = Path(\\\"data\\\")\\n for item in tub_dirs:\\n if Path(item).is_dir():\\n try:\\n t = Tub(str(item),read_only=True)\\n except FileNotFoundError as ex:\\n continue\\n except ValueError as ex:\\n # In case the catalog file is empty\\n continue\\n tubs.append(t)\\n count += len(t)\\n if verbose:\\n print( f\\\"Loaded {count} records.\\\" )\\n\\n return tubs\",\n \"def test_get_result_top_files(self):\\n pass\",\n \"def alltests(opts):\\n \\n print \\\"API Root: %s\\\" % options.apiroot\\n print \\\"Token: %s\\\" % options.token\\n print \\\"Output dir: %s\\\" % options.output\\n print \\\"Running %d%% of tests\\\" % options.percent\\n print\\n \\n # need to use DEPT-001, not ID#\\n coursehistory_tests = [\\n # basic tests:\\n \\\"cis-120\\\", \\\"math-114\\\", \\\"engl-101\\\", \\\"econ-001\\\",\\n # miscellaneously somewhat problematic:\\n \\\"engl-016\\\", \\\"law-205\\\", \\\"hpr-612\\\", \\\"rels-414\\\", \\\"nurs-322\\\",\\n \\\"writ-030\\\", \\\"be-310\\\", \\\"psci-010\\\", \\\"psci-136\\\",\\n # crosslistings:\\n \\\"engl-135\\\", \\\"writ-135\\\", \\\"fnar-264\\\", \\\"cogs-001\\\", \\\"russ-048\\\", \\\"hist-048\\\",\\n # no reviews?:\\n \\\"afam-271\\\", \\\"ames-071\\\", \\\"slav-532\\\", \\\"afam-285\\\", \\\"prtg-213\\\", \\\"slav-533\\\",\\n # errors:\\n \\\"99999\\\", \\\"moo\\\",\\n ]\\n\\n instructor_tests = [\\n # basic tests:\\n \\\"403\\\", \\\"631\\\", \\\"1883\\\", \\\"2217-FERNANDO-C--PEREIRA\\\", \\\"1602-BENJAMIN-PIERCE\\\",\\n # crosslistings:\\n \\\"1034-LYLE-H-UNGAR\\\", \\\"2709-DAVID-P--COMBERG\\\",\\n # miscellaneously somewhat problematic:\\n \\\"1040-DAVID-FOX\\\", \\\"4268-BART-GERARD-C-DE-JONGHE\\\",\\n # the instructors w/ the most sections\\n \\\"1883\\\", \\\"1619\\\", \\\"2869\\\", \\\"942\\\", \\\"1644\\\", \\\"541\\\", \\\"767\\\", \\\"434\\\",\\n # concerned citizens:\\n \\\"1759-MAX-C--CAVITCH\\\", \\\"2824-TIMOTHY-CORRIGAN\\\",\\n \\\"1763-EMILY-R-STEINER\\\", \\\"1624-VALERIE-ROSS\\\",\\n # no reviews?:\\n \\\"416-LUDO-ROCHER\\\", \\\"715-ELIZABETH-ANN-POLLARD\\\", \\\"1094-MARIA-A-COWLES\\\",\\n \\\"1500-ANDREW-GALLIA\\\", \\\"1888-RUSSELL-DILEO\\\",\\n \\\"1450-SORMANE-PEREIRA-GOMES\\\", \\\"2188-HUI-YI-CHEN\\\", \\\"1165-DOMENIC-VITIELLO\\\",\\n \\\"2359-CLAUDIA-CANCINO\\\", \\\"2737-SHEN-WANG\\\", \\\"3229-BERLE-WHITBY\\\",\\n # errors:\\n \\\"99999\\\", \\\"moo\\\",\\n ]\\n\\n dept_tests = [\\n #fast\\n \\\"CSE\\\", \\\"LAW\\\", \\\"ANAT\\\", \\\"KORN\\\", \\\"LATN\\\", \\\"COGS\\\", \\\"MSCI\\\", \\\"GAS\\\",\\n #medium\\n \\\"CIS\\\", \\\"MATH\\\", \\\"FNAR\\\", \\\"ACCT\\\", \\\"FNCE\\\", \\\"BE\\\", \\\"MUSC\\\", \\\"OPIM\\\",\\n #slow\\n #\\\"SPAN\\\", \\\"NURS\\\", \\\"ENGL\\\",\\n #error\\n \\\"EROR\\\"]\\n\\n index_tests = [\\\"\\\", \\\"instructors\\\", \\\"coursehistories\\\", \\\"depts\\\",\\n \\\"semesters\\\", \\\"semesters/2010c\\\"]\\n\\n course_tests = [] # filled in by coursehistory_tests\\n\\n for t in fraclist(index_tests, options.percent):\\n test(opts, t)\\n \\n for t in fraclist(coursehistory_tests, options.percent):\\n obj = test(opts, \\\"coursehistories/%s\\\" % t)\\n test(opts, \\\"coursehistories/%s/reviews\\\" % t)\\n\\n # now \\\"find\\\" some courses\\n course_tests.append(\\\"2010c-%s\\\" % t)\\n try:\\n courseid = sorted(obj[\\\"result\\\"][\\\"courses\\\"])[0][\\\"id\\\"]\\n course_tests.append(courseid)\\n except (TypeError, KeyError, IndexError):\\n pass\\n \\n for t in course_tests: # don't fraclist an autogenerated list\\n # Some of the autogenerated courses don't exist, so ignore errors.\\n root_success = test(opts, \\\"courses/%s\\\" % t, lderror_ok=True)\\n if root_success:\\n # Course exists, don't expect errors.\\n test(opts, \\\"courses/%s/reviews\\\" % t)\\n test(opts, \\\"courses/%s/coursehistories/\\\" % t)\\n test(opts, \\\"courses/%s/sections\\\" % t)\\n \\n if test(opts, \\\"courses/%s/sections/001\\\" % t, lderror_ok=True):\\n test(opts, \\\"courses/%s/sections/001/reviews\\\" % t) \\n if '-' in str(t): # if we have a yyyys-dept-num test\\n test(opts, \\\"sections/%s-001\\\" % t)\\n # not tested: sections/001/reviews/instructor-id\\n test(opts, \\\"courses/%s/sections/401\\\" % t, lderror_ok=True)\\n \\n for t in fraclist(instructor_tests, options.percent):\\n test(opts, \\\"instructors/%s\\\" % t)\\n test(opts, \\\"instructors/%s/sections\\\" % t)\\n test(opts, \\\"instructors/%s/reviews\\\" % t)\\n \\n for t in fraclist(dept_tests, options.percent):\\n test(opts, \\\"depts/%s\\\" % t)\\n test(opts, \\\"depts/%s/reviews\\\" % t)\\n test(opts, \\\"semesters/2010c/%s\\\" % t)\",\n \"def get_dev_examples(self, data_dir):\\n\\t\\traise NotImplementedError()\",\n \"def test_suite():\\n return doctest.DocFileSuite(\\n '../README.rst',\\n 'server.rst',\\n 'client.rst',\\n optionflags=doctest.ELLIPSIS | doctest.NORMALIZE_WHITESPACE)\",\n \"def make_tables(self):\\n for t in self.tables:\\n self.add_table(groupname=t['groupname'],\\n tablename=t['tablename'],\\n description=t['description'],\\n tabletitle=t['tabletitle'])\",\n \"def get_dev_examples(self, data_dir):\\r\\n raise NotImplementedError()\",\n \"def get_dev_examples(self, data_dir):\\r\\n raise NotImplementedError()\",\n \"def get_dev_examples(self, data_dir):\\r\\n raise NotImplementedError()\",\n \"def get_dev_examples(self, data_dir):\\r\\n raise NotImplementedError()\",\n \"def get_dev_examples(self, data_dir):\\r\\n raise NotImplementedError()\",\n \"def get_dev_examples(self, data_dir):\\r\\n raise NotImplementedError()\",\n \"def list_tables(option, opt, value, parser):\\n print \\\"CCP Data Dump Table List\\\"\\n print \\\"------------------------\\\"\\n for table in util.IMPORT_LIST:\\n print \\\"%s\\\" % table.__name__.replace('Importer_', '')\\n print \\\"-- %d tables --\\\" % len(util.IMPORT_LIST)\\n # The -l argument is just used for listing, proceed no further.\\n exit_with_succ()\",\n \"def _create_examples(self, df, mode):\\n idx_tr, idx_te = next(ShuffleSplit(test_size=0.3, random_state=1234).split(df.title, df.totalViews))\\n\\n examples = []\\n\\n iterind = idx_tr if mode == \\\"train\\\" else idx_te\\n\\n for i in iterind:\\n examples.append(\\n InputExample(guid=i, text_a=df.title.values[i], label=df.totalViews.values[i]))\\n\\n return examples\",\n \"def load_tests(loader, tests, ignore):\\n tests.addTests(doctest.DocTestSuite(l))\\n return tests\",\n \"def _display_examples(self):\\n\\n print(self._usage)\\n print(self._examples)\",\n \"def demonstration_examples(kind):\\n\\n DIR = './data/demos/'\\n RNN_DEMO = \\\"-demo_rnn_examples\\\"\\n EXT = '.pkl'\\n\\n if kind == 'rnn':\\n return pd.read_pickle(DIR+RNN_DEMO+EXT)\",\n \"def node_setup_files_list_table_format(result):\\n table = []\\n for item in result:\\n row = OrderedDict()\\n row['Name'] = item['name']\\n row['Is directory'] = 'yes' if item['is_directory'] else 'no'\\n row['Size'] = '' if item['size'] is None else (item['size'] or '0')\\n table.append(row)\\n return table\",\n \"def pretty_runlist(runlist):\\n if not runlist:\\n return [' empty']\\n output = list()\\n current_kind = str()\\n for i, entry in enumerate(runlist):\\n if current_kind != entry['kind']:\\n output.append(entry['kind'] + ':')\\n current_kind = entry['kind']\\n path = entry['command']\\n basename = os.path.splitext(os.path.basename(path))[0]\\n line = ' %d %s' % (i+1, basename)\\n line = line.ljust(20)\\n line += '\\\"%s\\\"' % pretty_path(path)\\n output.append(line)\\n return output\",\n \"def vocab_tables(source_file, tags_file):\\n pass\",\n \"def load_demos():\\n for index in range(len(feconf.DEMO_EXPLORATIONS)):\\n load_demo(str(index))\",\n \"def test_text_classifier_add_testing_samples(self):\\n pass\",\n \"def test_suite():\\n testSuite = unittest.TestSuite()\\n testSuite.addTest(test_h5fs(\\\"test_mode\\\"))\\n testSuite.addTest(test_h5fs(\\\"test_path_splitting\\\"))\\n testSuite.addTest(test_h5fs(\\\"test_link_mixing\\\"))\\n return testSuite\",\n \"def testsuite():\\n \\n tests = unittest.TestSuite()\\n\\n parse_tests = unittest.makeSuite(ParseTestCase, 'test')\\n tests = unittest.TestSuite( (tests, parse_tests) )\\n\\n return tests\",\n \"def test_tabs():\\n for _, modname, ispkg in walk_packages(mne.__path__, prefix=\\\"mne.\\\"):\\n # because we don't import e.g. mne.tests w/mne\\n if not ispkg and modname not in tab_ignores:\\n try:\\n mod = importlib.import_module(modname)\\n except Exception: # e.g., mne.export not having pybv\\n continue\\n source = inspect.getsource(mod)\\n assert \\\"\\\\t\\\" not in source, (\\n '\\\"%s\\\" has tabs, please remove them '\\n \\\"or add it to the ignore list\\\" % modname\\n )\",\n \"def test_pep8_conformance_example(self):\\n\\n print(\\\"\\\\r\\\\n\\\")\\n\\n # Get the path to current directory\\n path = os.path.dirname(os.path.realpath(__file__))\\n path += \\\"/../docs/examples/\\\"\\n\\n # Find all the examples files\\n file_paths = []\\n for root, dirnames, filenames in os.walk(path):\\n for file_path in fnmatch.filter(filenames, '*.py'):\\n file_paths.append(os.path.join(root, file_path))\\n\\n for path in file_paths:\\n self.run_check(path)\",\n \"def load_tests(loader, tests, ignore):\\n tests.addTests(doctest.DocTestSuite(Descriptors, optionflags=doctest.ELLIPSIS))\\n return tests\",\n \"def test_main(self):\\n dummy_folder = TestOspaListDir.get_dummy_folder()\\n result = listdir(dummy_folder,\\n full_path=True,\\n only_files=False,\\n )\\n need_result = ['memes',\\n 'txt_files',\\n 'antigravity.png',\\n 'egg.png',\\n 'empty.txt',\\n 'holy_grenade.png',\\n 'spam.jpg',\\n ]\\n need_result = [os.path.join(dummy_folder, x) for x in need_result]\\n self.assertEqual(sorted(need_result), sorted(result))\\n\\n result = listdir(dummy_folder,\\n full_path=False,\\n only_files=False,\\n )\\n need_result = ['memes',\\n 'txt_files',\\n 'antigravity.png',\\n 'egg.png',\\n 'empty.txt',\\n 'holy_grenade.png',\\n 'spam.jpg',\\n ]\\n\\n self.assertEqual(sorted(need_result), sorted(result))\\n\\n result = listdir(dummy_folder,\\n full_path=True,\\n only_files=True,\\n )\\n need_result = ['antigravity.png',\\n 'egg.png',\\n 'empty.txt',\\n 'holy_grenade.png',\\n 'spam.jpg',\\n ]\\n need_result = [os.path.join(dummy_folder, x) for x in need_result]\\n self.assertEqual(sorted(need_result), sorted(result))\\n self.assertEqual(sorted(os.listdir('.')), sorted(listdir(path='.', full_path=False)))\",\n \"def workbench_scenarios():\\n return [\\n (\\\"Markdown\\\",\\n \\\"\\\"\\\"<markdowna />\\n \\\"\\\"\\\")\\n ]\",\n \"def test_current_file(self) -> Generator[int, None, None]:\\n setting: ShowCaptionsTabSetting = ShowCaptionsTabSetting(\\n self.settings,\\n sublime.active_window()\\n )\\n\\n dir: str = path.dirname(__file__)\\n\\n foo_fixture: str = path.normpath(\\n path.join(dir, \\\"./fixtures/foo.txt\\\")\\n )\\n bar_fixture: str = path.normpath(\\n path.join(dir, \\\"./fixtures/bar.txt\\\")\\n )\\n\\n foo_view: sublime.View = sublime.active_window().open_file(foo_fixture)\\n bar_view: sublime.View = sublime.active_window().open_file(bar_fixture)\\n\\n data_set: Tuple[Tuple[List[Tab], List[List[str]], sublime.View], ...]\\n\\n data_set = (\\n ([Tab(foo_view), Tab(bar_view)], [['Current File'], []], foo_view),\\n ([Tab(foo_view), Tab(bar_view)], [[], ['Current File']], bar_view),\\n )\\n\\n yield 100\\n\\n for (tabs, captions, view) in data_set:\\n with self.subTest(tabs=tabs, captions=view, view=view):\\n view.window().focus_view(view)\\n self.assertTrue(setting.is_enabled())\\n self.assertListEqual(tabs, setting.apply(tabs))\\n actual = []\\n for tab in tabs:\\n actual.append(tab.get_captions())\\n self.assertListEqual(captions, actual)\",\n \"def autogen_dataset_dir_with_test():\\n return TabularDataset.autogen('tests/data/dummy_tabular',\\n test_path='tests/data/dummy_tabular_test',\\n seed=42,\\n sep=',')\",\n \"def tests_generator(self):\\n cb_bin = os.path.join(bin_path, 'compilebench')\\n cmd_list = [\\n (\\\"Initial Create/Compile/Read Compiled Tree\\\", \\\"{0} -D {1} -i 10 --makej -s {2}\\\"),\\n ]\\n\\n tests = []\\n for idx, (desc, cmd) in enumerate(cmd_list):\\n test_name = \\\"compile_bench_{0}_{1}\\\".format(idx + 1, to_safe_name(desc))\\n test = TestProfile(\\n name=test_name,\\n desc=desc,\\n test_path=self.test_path,\\n bin_path=bin_path,\\n command=cmd.format(cb_bin, self.test_path, bin_path))\\n tests.append(test)\\n return tests\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6358621","0.60888994","0.60677725","0.585937","0.5713878","0.5649388","0.5635742","0.5621542","0.5621542","0.55692166","0.55307424","0.54785776","0.54528546","0.54419327","0.54034835","0.5394622","0.53802747","0.53779495","0.53719294","0.53674066","0.5364855","0.5364855","0.5364855","0.5364855","0.5364855","0.53438103","0.532746","0.5298199","0.52813596","0.52664036","0.5250641","0.5248375","0.5245483","0.52443355","0.5240539","0.5230724","0.5217161","0.5206686","0.51946247","0.5192523","0.5192251","0.5189571","0.5186237","0.517546","0.5170684","0.516156","0.515985","0.515985","0.5157838","0.5151255","0.51434046","0.5134407","0.5118642","0.5115129","0.5106113","0.5100993","0.509801","0.5097887","0.5092617","0.508802","0.50675404","0.50671554","0.50634664","0.50588834","0.50565547","0.5048167","0.50405824","0.50297695","0.50272775","0.5023436","0.50195396","0.50183165","0.50077695","0.4997858","0.49913833","0.49913833","0.49913833","0.49913833","0.49913833","0.49913833","0.49903443","0.49883974","0.49835163","0.49801716","0.4977524","0.49752986","0.4972449","0.49681553","0.49613693","0.49607417","0.4955973","0.49503455","0.4947502","0.49466732","0.49460635","0.49397483","0.49393293","0.49337736","0.493337","0.49315166"],"string":"[\n \"0.6358621\",\n \"0.60888994\",\n \"0.60677725\",\n \"0.585937\",\n \"0.5713878\",\n \"0.5649388\",\n \"0.5635742\",\n \"0.5621542\",\n \"0.5621542\",\n \"0.55692166\",\n \"0.55307424\",\n \"0.54785776\",\n \"0.54528546\",\n \"0.54419327\",\n \"0.54034835\",\n \"0.5394622\",\n \"0.53802747\",\n \"0.53779495\",\n \"0.53719294\",\n \"0.53674066\",\n \"0.5364855\",\n \"0.5364855\",\n \"0.5364855\",\n \"0.5364855\",\n \"0.5364855\",\n \"0.53438103\",\n \"0.532746\",\n \"0.5298199\",\n \"0.52813596\",\n \"0.52664036\",\n \"0.5250641\",\n \"0.5248375\",\n \"0.5245483\",\n \"0.52443355\",\n \"0.5240539\",\n \"0.5230724\",\n \"0.5217161\",\n \"0.5206686\",\n \"0.51946247\",\n \"0.5192523\",\n \"0.5192251\",\n \"0.5189571\",\n \"0.5186237\",\n \"0.517546\",\n \"0.5170684\",\n \"0.516156\",\n \"0.515985\",\n \"0.515985\",\n \"0.5157838\",\n \"0.5151255\",\n \"0.51434046\",\n \"0.5134407\",\n \"0.5118642\",\n \"0.5115129\",\n \"0.5106113\",\n \"0.5100993\",\n \"0.509801\",\n \"0.5097887\",\n \"0.5092617\",\n \"0.508802\",\n \"0.50675404\",\n \"0.50671554\",\n \"0.50634664\",\n \"0.50588834\",\n \"0.50565547\",\n \"0.5048167\",\n \"0.50405824\",\n \"0.50297695\",\n \"0.50272775\",\n \"0.5023436\",\n \"0.50195396\",\n \"0.50183165\",\n \"0.50077695\",\n \"0.4997858\",\n \"0.49913833\",\n \"0.49913833\",\n \"0.49913833\",\n \"0.49913833\",\n \"0.49913833\",\n \"0.49913833\",\n \"0.49903443\",\n \"0.49883974\",\n \"0.49835163\",\n \"0.49801716\",\n \"0.4977524\",\n \"0.49752986\",\n \"0.4972449\",\n \"0.49681553\",\n \"0.49613693\",\n \"0.49607417\",\n \"0.4955973\",\n \"0.49503455\",\n \"0.4947502\",\n \"0.49466732\",\n \"0.49460635\",\n \"0.49397483\",\n \"0.49393293\",\n \"0.49337736\",\n \"0.493337\",\n \"0.49315166\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.50884354"},"document_rank":{"kind":"string","value":"59"}}},{"rowIdx":81781,"cells":{"query":{"kind":"string","value":"Checks and possibly corrects a scaper produced example."},"document":{"kind":"string","value":"def check_and_correct_example(example, root_dir,\n check_length, fix_length,\n check_mix, fix_mix,\n sample_rate=16000, duration=10.0,\n chat=False):\n # Earlier versions of scaper had a tendency to make mistakes every\n # once in a while.\n # This has most likely been fixed in the latest scaper release, at least\n # for the parameter settings we are using, but this test and correction\n # can serve to catch failures that may be introduced by using the wrong\n # scaper version, or by using parameters in scaper that do not maintain\n # mixture consistency. For example, at the time of this coding,\n # using scaper reverb breaks mixture consistency.\n\n # Enforce dependencies between flags.\n if fix_mix:\n check_mix = True\n if check_mix:\n fix_length = True\n if fix_length:\n check_length = True\n\n length_problem = 0\n fixed_length = 0\n mix_problem = 0\n fixed_mix = 0\n\n files = example.split('\\t')\n mixfile = files[0]\n if chat:\n print('Checking {}'.format(mixfile))\n components = files[1:]\n\n def resize_audio(audio, length):\n in_length = audio.shape[0]\n new_audio = np.zeros((length, audio.shape[1]), dtype=audio.dtype)\n new_audio[0:min(length, in_length), :] = \\\n audio[0:min(length, in_length), :]\n return new_audio\n\n expected_samples = int(duration * sample_rate)\n\n if check_length:\n\n for myfile in files:\n file_abs = os.path.join(root_dir, myfile)\n file_info = sf.info(file_abs)\n num_samples = int(file_info.duration * file_info.samplerate)\n\n if num_samples != expected_samples:\n length_problem += 1\n print('Warning: scaper output on {:s} is {:d} samples; '\n 'expected {:d}'.format(file_abs, num_samples, expected_samples))\n\n audio, _ = read_wav(file_abs, always_2d=True)\n num_samples, num_channels = audio.shape\n audio = resize_audio(audio, expected_samples)\n\n if fix_length:\n # rewrite corrected source\n print('Adjusting length of {:s}'.format(file_abs))\n write_wav(file_abs, audio, sample_rate, subtype=file_info.subtype)\n fixed_length += 1\n\n def check_mixture(mixed_data, remixed_data, mixfile):\n if not np.allclose(mixed_data, remixed_data, rtol=1e-4, atol=1e-5):\n mixed_norm = np.linalg.norm(mixed_data)\n err_norm = np.linalg.norm(mixed_data - remixed_data)\n normalized_err = err_norm / mixed_norm\n print('WARNING: Mismatched mixed data found {}. '\n 'Normalized error {}, mixed signal norm {}'.format(\n mixfile, normalized_err, mixed_norm))\n return False\n return True\n\n if check_mix:\n mixfile_abs = os.path.join(root_dir, mixfile)\n mix_info = sf.info(mixfile_abs)\n mixture, _ = read_wav(mixfile_abs, always_2d=True)\n num_samples, num_channels = mixture.shape\n\n source_sum = np.zeros((expected_samples, num_channels),\n dtype=mixture.dtype)\n for srcfile in components:\n srcfile_abs = os.path.join(root_dir, srcfile)\n source, _ = read_wav(srcfile_abs, always_2d=True)\n # sum up sources\n source_sum += source\n\n if not check_mixture(mixture, source_sum, mixfile):\n mix_problem += 1\n if fix_mix:\n print('Rewriting corrected mixture file {}.'.format(mixfile_abs))\n # write new mixture\n # note we are not doing anything about clipping here,\n # so if mismatch is due to clipping it will clip again on writing.\n mixture = source_sum\n write_wav(mixfile_abs, mixture, sample_rate, subtype=mix_info.subtype)\n fixed_mix += 1\n return length_problem, fixed_length, mix_problem, fixed_mix"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_is_gene_continuously_amplified_wrong_input(self):\n self.assertEqual(\"Wrong input data\", is_gene_continuously_amplified(13))","def run_sample_checks(sub: Submission, logger):\n\n samples = sub.sample\n factors = [f.value for f in sub.study.experimental_factor]\n organisms = set()\n units = set()\n characteristics = []\n codes = []\n\n if not samples:\n logger.error(\"Experiment has no samples. At least one expected.\")\n codes.append(\"SAMP-E01\")\n return codes\n for s in samples:\n # Sample must have a name\n if not s.alias:\n logger.error(\"Sample found with no name. Not checking it further.\")\n codes.append(\"SAMP-E02\")\n continue\n # Sample must have organism/taxon annotation\n if not s.taxon:\n logger.error(\"Sample \\\"{}\\\" has no organism specified.\".format(s.alias))\n codes.append(\"SAMP-E03\")\n else:\n organisms.add(s.taxon)\n # Collecting units and categories\n for a, a_attr in s.attributes.items():\n if a_attr.unit and a_attr.unit.value:\n if a_attr.unit.value not in units:\n units.add(a_attr.unit.value)\n if a not in characteristics:\n characteristics.append(a)\n\n # Check organism name is in taxonomy\n for o in organisms:\n taxon_id = converter_utils.get_taxon(o)\n logger.debug(\"Found taxon ID: {}\".format(taxon_id))\n if not isinstance(taxon_id, int):\n logger.error(\"Organism \\\"{}\\\" was not found in NCBI taxonomy.\".format(o))\n codes.append(\"SAMP-E08\")\n\n # Check units\n unit_term = ontology_term(\"unit\")\n allowed_units = get_term_descendants(unit_term[\"ontology\"], unit_term[\"uri\"], logger)\n for unit_label in units:\n if unit_label not in allowed_units:\n logger.error(\"Unit \\\"{}\\\" is not from approved list (EFO term).\".format(unit_label))\n codes.append(\"SAMP-E04\")\n\n # Check that factors defined in study are found in sample attributes\n undefined_factors = [f for f in factors if f not in characteristics]\n if len(undefined_factors) > 0:\n logger.error(\"The following factors are declared but not annotated: {}\".format(\", \".join(undefined_factors)))\n codes.append(\"SAMP-E05\")\n\n # Check that factor values vary\n unique_factor_values = {}\n for f in factors:\n if f not in undefined_factors:\n # Get all values for a given factor\n factor_values = [s.attributes[f].value.rstrip() for s in samples]\n # Filter duplicated values to get the number of unique entries\n unique_factor_values[f.lower()] = converter_utils.remove_duplicates(factor_values)\n non_factors = [f_name for f_name, values in unique_factor_values.items() if len(values) < 2]\n good_factors = [f_name for f_name, values in unique_factor_values.items() if len(values) > 1]\n # Go through factors and check for special cases that are exempt from the rule\n for f in non_factors:\n # Special case dose\n if f == \"dose\":\n # Error if both dose + compound/irradiade do not vary\n if \"compound\" in non_factors or \"irradiate\" in non_factors:\n logger.error(\"For factor values including dose, at least one must vary.\")\n codes.append(\"SAMP-E07\")\n # Allow dose to not vary if compound/irradiate do\n elif \"compound\" in good_factors or \"irradiate\" in good_factors:\n continue\n # For compound/irradiate, we already check this above. Need to skip here to suppress second error message\n elif f == \"compound\" and \"dose\" in non_factors:\n continue\n elif f == \"irradiate\" and \"dose\" in non_factors:\n continue\n # Special case immunoprecipitate\n elif f == \"immunoprecipitate\":\n logger.info(\"Found factor \\\"immunoprecipitate\\\". This doesn't need to vary.\")\n else:\n logger.error(\"Factor value \\\"{}\\\" does not vary.\".format(f))\n codes.append(\"SAMP-E06\")\n\n return codes","def test_hardcoded_example(self):\n expected_accuracy = dict(num_recall=2, uniq_recall=2, num_precision=3, uniq_precision=2)\n self._run_and_validate(self.detections, self.ground_truths, expected_accuracy)","def test_no_specification_error():\n try:\n bad_arm = survey.get_spiral_slice()\n except SyntaxError:\n assert True\n else:\n assert False","def test_proper(self):\n\n self.assertTrue(self.cs.isProper)\n self.assertFalse(self.cs.isDegenerate)","def test__validate_topic__2():\n for input_value in (\n 12.6,\n ):\n with vampytest.assert_raises(TypeError):\n validate_topic(input_value)","def try_accept_the_example(self, denoising_sample, denoising_label):\n assert isinstance(denoising_sample, np.ndarray)\n assert isinstance(denoising_label, int) or isinstance(denoising_label, np.int64)\n # assert self.input.shape == denoising_sample.shape\n\n ok = self._is_successful(denoising_label)\n if ok:\n self.__denoising_sample = denoising_sample\n self.denoising_label = denoising_label\n else:\n self.__bad_denoising_example = denoising_sample\n\n return ok","def _checkSample(self):\n Sampler._checkSample(self)\n # make sure the prefix is registered for tracking\n # but if there's no identifying information, skip this check\n if self._registeredIdentifiers:\n prefix = self.inputInfo['prefix']\n if not prefix in self._prefixToIdentifiers:\n self.raiseAnError(RuntimeError, f'Prefix \"{prefix}\" has not been tracked in adaptive sampling!')","def test_kyc_post_legal(self):\n pass","def test_validate_input_good_input(self):\r\n _validate_input(self.dist_matrix_header, self.dist_matrix,\r\n self.mapping_header, self.mapping, \"Treatment\")","def test_validate_answer(self):\r\n sample_dict = {'x': (1, 2)}\r\n problem = self.build_problem(\r\n sample_dict=sample_dict,\r\n num_samples=10,\r\n tolerance=\"1%\",\r\n answer=\"x\"\r\n )\r\n self.assertTrue(problem.responders.values()[0].validate_answer('14*x'))\r\n self.assertFalse(problem.responders.values()[0].validate_answer('3*y+2*x'))","def test_interpret_error(self):\r\n two_choice_two_input = self._make_problem(\r\n [\r\n (\"true\", {\"answer\": \"123\", \"tolerance\": \"1\"}),\r\n (\"false\", {})\r\n ],\r\n \"checkboxtextgroup\"\r\n )\r\n\r\n with self.assertRaisesRegexp(StudentInputError, \"Could not interpret\"):\r\n # Test that error is raised for input in selected correct choice.\r\n self.assert_grade(\r\n two_choice_two_input,\r\n self._make_answer_dict([(True, [\"Platypus\"])]),\r\n \"correct\"\r\n )\r\n\r\n with self.assertRaisesRegexp(StudentInputError, \"Could not interpret\"):\r\n # Test that error is raised for input in selected incorrect choice.\r\n self.assert_grade(\r\n two_choice_two_input,\r\n self._make_answer_dict([(True, [\"1\"]), (True, [\"Platypus\"])]),\r\n \"correct\"\r\n )","def test_stochatreat_input_invalid_probs(correct_params):\n probs_not_sum_to_one = [0.1, 0.2]\n with pytest.raises(Exception):\n stochatreat(\n data=correct_params[\"data\"],\n block_cols=[\"block\"],\n treats=correct_params[\"treat\"],\n idx_col=correct_params[\"idx_col\"],\n probs=probs_not_sum_to_one,\n )","def test_kyc_get_validation_legal(self):\n pass","def testProtractedPostApplicationSanityChecks(self):\n self.assertLess(self.c.get_species_richness(1), self.c.get_species_richness(3))\n self.assertLess(self.c.get_species_richness(2), self.c.get_species_richness(4))\n self.assertLess(self.c.get_species_richness(5), self.c.get_species_richness(3))\n self.assertLess(self.c.get_species_richness(6), self.c.get_species_richness(4))\n self.assertEqual(4, self.c.get_species_richness(1))\n self.assertEqual(4, self.c.get_species_richness(2))\n self.assertEqual(7, self.c.get_species_richness(3))\n self.assertEqual(7, self.c.get_species_richness(4))\n self.assertEqual(4, self.c.get_species_richness(5))\n self.assertEqual(4, self.c.get_species_richness(6))\n self.assertEqual(21, self.c.get_species_richness(7))\n self.assertEqual(38, self.c.get_species_richness(8))","def testProtractedPostApplicationSanityChecks(self):\n self.assertLess(self.c.get_species_richness(1), self.c.get_species_richness(3))\n self.assertLess(self.c.get_species_richness(2), self.c.get_species_richness(4))\n self.assertLess(self.c.get_species_richness(5), self.c.get_species_richness(3))\n self.assertLess(self.c.get_species_richness(6), self.c.get_species_richness(4))\n self.assertEqual(4, self.c.get_species_richness(1))\n self.assertEqual(4, self.c.get_species_richness(2))\n self.assertEqual(7, self.c.get_species_richness(3))\n self.assertEqual(7, self.c.get_species_richness(4))\n self.assertEqual(4, self.c.get_species_richness(5))\n self.assertEqual(4, self.c.get_species_richness(6))\n self.assertEqual(21, self.c.get_species_richness(7))\n self.assertEqual(38, self.c.get_species_richness(8))","def testProtractedPostApplicationSanityChecks(self):\n self.assertLess(self.c.get_species_richness(1), self.c.get_species_richness(3))\n self.assertLess(self.c.get_species_richness(2), self.c.get_species_richness(4))\n self.assertLess(self.c.get_species_richness(5), self.c.get_species_richness(3))\n self.assertLess(self.c.get_species_richness(6), self.c.get_species_richness(4))\n self.assertEqual(4, self.c.get_species_richness(1))\n self.assertEqual(4, self.c.get_species_richness(2))\n self.assertEqual(7, self.c.get_species_richness(3))\n self.assertEqual(7, self.c.get_species_richness(4))\n self.assertEqual(4, self.c.get_species_richness(5))\n self.assertEqual(4, self.c.get_species_richness(6))\n self.assertEqual(21, self.c.get_species_richness(7))\n self.assertEqual(38, self.c.get_species_richness(8))","def test_05_valid_stroke(self):\n stroke_record = SwimRecord(stroke='doggie paddle')\n try:\n stroke_record.full_clean()\n except ValidationError as e:\n self.assertTrue(\"doggie paddle is not a valid stroke\" in e.message_dict['stroke'])","def validate_answer(self, answer):\r\n var_dict_list = self.randomize_variables(self.samples)\r\n try:\r\n self.tupleize_answers(answer, var_dict_list)\r\n return True\r\n except StudentInputError:\r\n return False","def test_contentious_prescription_no_rationale(self):\n url = reverse('admin:prescription_prescription_add')\n data = {\n 'name': 'Test',\n 'planned_season': 1,\n 'planned_year': 2013,\n 'region': 1,\n 'district': 1,\n 'location': 'Test location',\n 'perimeter': 20,\n 'area': 100,\n 'purposes': [1],\n 'remote_sensing_priority': 4,\n 'priority': 2,\n 'contentious': True,\n }\n response = self.client.post(url, data)\n self.assertEqual(response.status_code, 200)\n self.assertEqual(Prescription.objects.count(), 0)\n form = response.context['adminform'].form\n self.assertEqual(form.errors, {\n 'contentious_rationale': ['A contentious burn requires a '\n 'contentious rationale.']\n })","def test_validation_wrong_systems():\n data_paths = examples_paths()\n exp_builder = ExperimentBuilder()\n basic_script = \"\"\"\n ---\n molecules:\n rec: {{filepath: {0}, leap: {{parameters: oldff/leaprc.ff14SB}}}}\n rec_region: {{filepath: {0}, regions: {{a_region: 'some string'}}, leap: {{parameters: oldff/leaprc.ff14SB}}}}\n lig: {{name: lig, leap: {{parameters: leaprc.gaff}}}}\n lig_region: {{name: lig, regions: {{a_region: 'some string'}}, leap: {{parameters: leaprc.gaff}}}}\n solvents:\n solv: {{nonbonded_method: NoCutoff}}\n solv2: {{nonbonded_method: NoCutoff, implicit_solvent: OBC2}}\n solv3: {{nonbonded_method: PME, clearance: 10*angstroms}}\n solv4: {{nonbonded_method: PME}}\n \"\"\".format(data_paths['lysozyme'])\n basic_script = yaml.load(textwrap.dedent(basic_script), Loader=yaml.FullLoader)\n\n # Each test case is a pair (regexp_error, system_description).\n systems = [\n (\"'solvent' is required\",\n {'receptor': 'rec', 'ligand': 'lig'}),\n\n (\"regions\\(s\\) clashing\",\n {'receptor': 'rec_region', 'ligand': 'lig_region', 'solvent': 'solv'}),\n\n (\"ligand:\\n- must be of string type\",\n {'receptor': 'rec', 'ligand': 1, 'solvent': 'solv'}),\n\n (\"solvent:\\n- must be of string type\",\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': ['solv', 'solv']}),\n\n (\"unallowed value unknown\",\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'unknown'}),\n\n (\"solv4 does not specify clearance\",\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'solv4',\n 'leap': {'parameters': ['leaprc.gaff', 'leaprc.ff14SB']}}),\n\n (\"parameters:\\n- unknown field\",\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'solv3',\n 'parameters': 'leaprc.ff14SB'}),\n\n (\"phase1_path:\\n- must be of list type\",\n {'phase1_path': data_paths['bentol-complex'][0],\n 'phase2_path': data_paths['bentol-solvent'],\n 'ligand_dsl': 'resname BEN', 'solvent': 'solv'}),\n\n (\"File path nonexistingpath.prmtop does not exist.\",\n {'phase1_path': ['nonexistingpath.prmtop', 'nonexistingpath.inpcrd'],\n 'phase2_path': data_paths['bentol-solvent'],\n 'ligand_dsl': 'resname BEN', 'solvent': 'solv'}),\n\n (\"ligand_dsl:\\n- must be of string type\",\n {'phase1_path': data_paths['bentol-complex'],\n 'phase2_path': data_paths['bentol-solvent'],\n 'ligand_dsl': 3.4, 'solvent': 'solv'}),\n\n (\"unallowed value unknown\",\n {'phase1_path': data_paths['bentol-complex'],\n 'phase2_path': data_paths['bentol-solvent'],\n 'ligand_dsl': 'resname BEN', 'solvent1': 'unknown',\n 'solvent2': 'solv2'}),\n\n (\"unallowed value cantbespecified\",\n {'phase1_path': data_paths['toluene-solvent'],\n 'phase2_path': data_paths['toluene-vacuum'],\n 'ligand_dsl': 'resname TOL', 'solvent': 'cantbespecified'}),\n\n (\"field 'ligand' is required\",\n {'receptor': 'rec', 'solute': 'lig', 'solvent1': 'solv', 'solvent2': 'solv'}),\n\n (\"''ligand'' must not be present with ''solute''\",\n {'ligand': 'lig', 'solute': 'lig', 'solvent1': 'solv', 'solvent2': 'solv'}),\n\n (\"leap:\\n- must be of dict type\",\n {'solute': 'lig', 'solvent1': 'solv', 'solvent2': 'solv', 'leap': 'leaprc.gaff'})\n ]\n for regexp, system in systems:\n modified_script = basic_script.copy()\n modified_script['systems'] = {'sys': system}\n yield assert_raises_regexp, YamlParseError, regexp, exp_builder.parse, modified_script","def test_incorrect_creation_1(input_data, exact):\n with pytest.raises(ValueError):\n TaxCalcIO(input_data=input_data,\n tax_year=2013,\n reform=None,\n assump=None,\n growdiff_response=None,\n aging_input_data=False,\n exact_calculations=exact)","def validate_sample_and_seq_exp(program_id, donor_id, analysis_objs):\n sample_fields = {\n 'submitterSampleId': 'samples.submitterSampleId',\n 'sampleType': 'samples.sampleType',\n 'matchedNormalSubmitterSampleId': 'samples.matchedNormalSubmitterSampleId',\n 'specimenId': 'samples.specimen.specimenId',\n 'specimenType': 'samples.specimen.specimenType',\n 'tumourNormalDesignation': 'samples.specimen.tumourNormalDesignation',\n 'specimenTissueSource': 'samples.specimen.specimenTissueSource',\n 'donorId': 'samples.donor.donorId',\n 'gender': 'samples.donor.gender',\n 'studyId': 'studyId'\n }\n\n # gather sample information from all analysis objects\n sample_info = dict()\n for a in analysis_objs:\n analysisId = a['analysisId']\n sampleId = a['samples'][0]['sampleId']\n if sampleId not in sample_info:\n sample_info[sampleId] = {\n 'sampleId': sampleId,\n 'analysisId': [],\n 'sequencing_experiment': {}\n }\n\n sample_info[sampleId]['analysisId'].append(analysisId)\n\n for field in sample_fields:\n if field not in sample_info[sampleId]:\n sample_info[sampleId][field] = dict()\n\n source_path = sample_fields[field].split('.')\n if len(source_path) == 1:\n source_value_str = str(a[source_path[0]])\n elif source_path[0] == 'samples':\n if len(source_path) == 2:\n source_value_str = str(a['samples'][0][source_path[1]])\n elif len(source_path) == 3:\n source_value_str = str(a['samples'][0][source_path[1]][source_path[2]])\n else:\n assert False # not supposed to reach here\n else:\n assert False # not supposed to reach here\n\n if source_value_str not in sample_info[sampleId][field]:\n sample_info[sampleId][field][source_value_str] = []\n\n sample_info[sampleId][field][source_value_str].append(analysisId)\n\n # add sequencing_experiment\n if a.get('analysisType', {}).get('name') in ('sequencing_experiment', 'rna_sequencing_experiment'):\n strategy = a['experiment']['experimental_strategy']\n matchedNormalSubmitterSampleId = a['samples'][0]['matchedNormalSubmitterSampleId']\n\n if strategy not in sample_info[sampleId]['sequencing_experiment']:\n sample_info[sampleId]['sequencing_experiment'][strategy] = {\n 'sequencing_experiment_analysis_id': [analysisId],\n 'matchedNormalSubmitterSampleId': [matchedNormalSubmitterSampleId]\n }\n else:\n sample_info[sampleId]['sequencing_experiment'][strategy]['sequencing_experiment_analysis_id'].append(analysisId)\n sample_info[sampleId]['sequencing_experiment'][strategy]['matchedNormalSubmitterSampleId'].append(matchedNormalSubmitterSampleId)\n\n # print(json.dumps({'donor_id': donor_id}))\n # print(json.dumps(sample_info))\n\n samples, issues = value_discrepancy_check(sample_info, sample_fields)\n # print(json.dumps(samples))\n # print(json.dumps(issues))\n\n submitterSampleId2SampleId = mapping_sumbitter_sample_id_to_sample_id(samples)\n # print(json.dumps(submitterSampleId2SampleId))\n\n # figure out tumour-normal pairs\n tumour_normal_pairs, tumour_not_paired, normal_not_paired, normal_paired, issues = resolve_tumour_normal_pairs(samples, submitterSampleId2SampleId)\n # print(json.dumps(tumour_normal_pairs))\n # print(json.dumps(normal_paired))\n # print(json.dumps(tumour_not_paired))\n # print(json.dumps(normal_not_paired))\n # print(json.dumps(issues))","def reason(self, example):\n raise NotImplementedError()","def test_buoy_format1():\n with pytest.raises(AssertionError) as err_info:\n Check_BuoyDC.check_buoy_format(buoy_format_fail_1)\n assert str(err_info.value) == 'Input formatted incorrectly, see instructions'","def test_sanity(self) -> None:\n if self.report.headlines:\n return\n\n if self.report.document.paragraphs:\n self.add_error(\n \"Rubrikerna i dokumentet är felformaterade eller saknas. \"\n \"Rubrikerna ska vara skrivna i versaler och ha samma \"\n \"typsnitt, stil och storlek som brödtexten. \"\n \"Rubriker avslutas med radbrytning.\"\n )\n\n if not self.report.document.paragraphs:\n self.add_error(\"Ditt dokument är antigen tomt eller i fel format.\")","def test_update_study_missing(self):\n study_spec = sample_study_spec()\n with self.assertRaises(ValueError):\n self.storage.update_study(study_spec)","def test_strain_redefined(generate_strain_redefined):\n fname = generate_strain_redefined\n try:\n process_files([fname])\n raise Exception('The redefined strain data and lack of stress data was not caught')\n except IOError:\n pass","def test_single_specifier_needed(self):\n template = '{0} one too many {1}'\n value_count = 1\n msg = ('The formatter should only contain one '\n '\"{}\" specifier for the source field.')\n with six.assertRaisesRegex(self, ValidationError, msg):\n validate_str_substitution(template, value_count)","def test__validate_title__1():\n for input_value in (\n 12.6,\n ):\n with vampytest.assert_raises(TypeError):\n validate_title(input_value)","def test_wrong_input(self):\n\n test_float = 2954.02\n test_list = [\"anagram\", \"gramana\"]\n with pytest.raises(AttributeError) as exc_info:\n is_anagram(test_float, test_list)\n expected_error_msg = \"Words must be strings!\"\n assert exc_info.match(expected_error_msg)","def assert_goodness(self):\n if self._setted:\n self.assert_stored_iss()\n self.assert_stored_ks()\n ## Check idxs\n self.assert_stored_idxs()\n ## Check sp_relative_pos\n self.assert_stored_sp_rel_pos()","def test_for_unknown_chemical():\n try:\n verify_atomic_weight_for_substance(\",.!\", 1.0)\n except periodic_table.InvalidFormula as e:\n return\n\n raise AssertionError(\"test_for_unknown_chemical() didn't fail\")","def test_validation_wrong_samplers():\n # Each test case is a pair (regexp_error, sampler_description).\n samplers = [\n (\"locality must be an int\",\n {'type': 'MultiStateSampler', 'locality': 3.0}),\n (\"unallowed value unknown\",\n {'type': 'ReplicaExchangeSampler', 'mcmc_moves': 'unknown'}),\n (\"Could not find class NonExistentSampler\",\n {'type': 'NonExistentSampler'}),\n (\"found unknown parameter\",\n {'type': 'ReplicaExchangeSampler', 'unknown_kwarg': 5}),\n ]\n exp_builder = ExperimentBuilder(get_template_script())\n for regexp, sampler in samplers:\n script = {'samplers': {'sampler1': sampler}}\n yield assert_raises_regexp, YamlParseError, regexp, exp_builder._validate_samplers, script","def testProtractedNSESanityChecks(self):\n self.assertGreater(self.c3.get_species_richness(1), self.c2.get_species_richness(1))\n self.assertLess(self.c4.get_species_richness(1), self.c3.get_species_richness(1))","def test_error_basis_state_format(self, basis_state, wires):\n\n with pytest.raises(ValueError, match=\"'basis_state' must only contain\"):\n BasisStatePreparation(basis_state, wires)","def test_generating(resp):\n errors = []\n if not check_int(resp[\"tightness\"]):\n errors.append(\"Invalid type for Itinerary response's 'tightness' field.\")\n\n if not isinstance(resp, bool):\n errors.append(\"Invalid type for Itinerary response's 'start_from_airport' field.\")","def violated(self) -> bool:\n ...","def test_incorrect_creation_2(rawinputfile, reformfile0, year, ref, asm, gdr):\n # pylint: disable=too-many-arguments\n if ref == 'reformfile0':\n reform = reformfile0.name\n else:\n reform = ref\n with pytest.raises(ValueError):\n TaxCalcIO(\n input_data=rawinputfile.name,\n tax_year=year,\n reform=reform,\n assump=asm,\n growdiff_response=gdr,\n aging_input_data=False,\n exact_calculations=False)","def test_constructed_is_small(self):\n self.assertTrue(all(elt<10 for elt in goodwinsheaf.checkradii()))#check all entries have small radii","def sanity_check(self):\n pass","def test_invalid_format(self):\n input_file = self.copy_and_mark_for_cleanup(\"Medline/pubmed_result1.txt\")\n\n cline = XXmotifCommandline(outdir=self.out_dir, seqfile=input_file)\n\n try:\n stdout, stderr = cline()\n except ApplicationError as err:\n self.assertEqual(err.returncode, 255)\n else:\n self.fail(f\"Should have failed, returned:\\n{stdout}\\n{stderr}\")","def test_X_normalization_not_raw(self):\n\n # Assign a real value to X while X_normalization is 'none'\n del self.validator.adata.raw\n self.validator.adata.uns[\"X_normalization\"] = \"none\"\n self.validator.validate_adata()\n print(\"FOO\", self.validator.warnings)\n self.assertEqual(\n self.validator.warnings,\n [\n \"WARNING: uns['X_normalization'] is 'none', there is no 'raw.X' and 'X' doesn't appear \"\n \"to have raw counts (integers)\"\n ],\n )","def test_non_integral_validation(self):","def test_non_integral_validation(self):","def sanity_check(self):\n return True","def test_stochatreat_input_invalid_size(correct_params):\n size_bigger_than_sampling_universe_size = 101\n with pytest.raises(ValueError):\n stochatreat(\n data=correct_params[\"data\"],\n block_cols=[\"block\"],\n treats=correct_params[\"treat\"],\n idx_col=correct_params[\"idx_col\"],\n probs=correct_params[\"probs\"],\n size=size_bigger_than_sampling_universe_size,\n )","def check():","def is_example(self, is_example):\n self._is_example = is_example","def test_issn_incorrect_length(self):\n issns = ['0307-15', '0307-15789', '03071758', '0307175']\n for num in issns:\n with self.subTest(num=num):\n with self.assertRaisesRegex(ValueError, num):\n star_barcode.construct_postscript(\n issn=num,\n bwipp_location=self.bwipp,\n sequence=21,\n week=46,\n header_line=''\n )","def test_is_AKs_preHandSimple_correct(self):\n self.assertEqual(self.hand.getPreHandSimple(), 'AKs')","def test_create_unexpected_problem(self):\n pass","def _check_validity(self):\n pass","def do_checks(self):\n # ## get valid experiment variables\n all_subexperiments = [1, 2, 3]\n all_plates = list(range(1, 19))\n all_cell_ids = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I']\n all_samples = list(self.experiment.design['Sample'])\n all_genes = self.experiment.subexperiments[1].plates[1].samples[all_samples[0]].genes\n all_replicates = list(range(1, 7))\n all_time = [0.5, 1.0, 2.0, 3.0, 4.0, 8.0, 12.0, 24.0, 48.0, 72.0, 96.0]\n\n if self.time is None:\n if self.treatment is 'Baseline':\n self.time = [0.0, 96.0]\n else:\n self.time = all_time\n\n if self.cell_id is None:\n self.cell_id = all_cell_ids\n\n if self.gene is None:\n self.gene = all_genes\n\n if self.replicate is None:\n self.replicate = all_replicates\n\n if self.treatment is None:\n raise ValueError('treatment cannot be None. Specify one of \"TGFb\", \"Control\", \"Baseline\"')\n\n if not isinstance(self.treatment, str):\n raise ValueError('treatment must be a string. Got \"{}\" a \"{}\"'.format(\n self.treatment, type(self.treatment)\n ))\n\n if not isinstance(self.normed, bool):\n raise ValueError('normed argument should be boolean. Got \"{}\"'.format(\n type(self.normed)\n ))\n\n if not isinstance(self.time, list):\n self.time = [self.time]\n\n for time_point in self.time:\n if time_point not in sorted(list(set(self.data.columns.get_level_values(1)))):\n raise ValueError('\"{}\" is invalid time point. Valid time '\n 'points are: {}'.format(\n time_point, list(self.data.columns))\n )","def check(self, version=None):\n \n if version is None:\n print(\"assuming Stata version 13\")\n version = 13\n if version not in (11, 12, 13):\n raise ValueError(\"allowed versions are 11 through 13\")\n \n width = self.width\n nvar = self._nvar\n nobs = self._nobs\n \n chrdict = self._chrdict\n \n char_len = max([0] + [len(char) for evar, evardict in chrdict.items()\n for char in evardict.values()])\n num_val_encodings = max([0] + [len(mapping) \n for mapping in self._vallabs.values()])\n max_note_size = max([0] + [len(note) for d in chrdict.values()\n for name, note in d.items()\n if re.match(r'^note[0-9]+$', name)])\n max_num_notes = max([0] + [len([1 for name,note in d.items() \n if re.match(r'^note[0-9]+$', name)])\n for d in chrdict.values()])\n \n if '_dta' in chrdict and '_lang_list' in chrdict['_dta']:\n n_label_langs = len(chrdict['_dta'][\"_lang_list\"].split())\n else:\n n_label_langs = 0\n \n small_good = medium_good = large_good = True\n general_good = format_good = True\n \n print(\"\\nformat problems\")\n if self._ds_format == 117 and version <= 12:\n format_good = False\n print(\" format 117 cannot be opened by Stata version \" + \n str(version))\n if version < 12 and any(TB_FMT_RE.match(fmt) for fmt in self._fmtlist):\n format_good = False\n print(\" Stata version \" + str(version) + \n \" cannot understand tb format\")\n if format_good:\n print(\" none\")\n \n print(\"\\ngeneral size problems\")\n if len(self._data_label) > 80:\n general_good = False\n print(\" data label length > 80\")\n if any(len(name) > 32 for name in self._varlist):\n general_good = False\n print(\" variable name length > 32\")\n if any(len(v) > 80 for v in self._vlblist):\n general_good = False\n print(\" variable label length > 80\")\n if any(len(name) > 32 for name in self._vallabs.keys()):\n general_good = False\n print(\" value label name length > 32\")\n if any(len(valstr) > 32000 \n for mapping in self._vallabs.values()\n for valstr in mapping.values()):\n general_good = False\n print(\" value label string length > 32,000\")\n if max_num_notes > 10000:\n # limit here is set at 10000, assuming one of the notes is 'note0'\n general_good = False\n print(\" number of notes for single variable or _dta > 9,999\")\n if n_label_langs > 100:\n general_good = False\n print(\" number of label languages > 100\")\n if general_good:\n print(\" none\")\n\n print(\"\\nStata small problems\")\n if width > 800:\n small_good = False\n print(\" data set width > 800\")\n if nvar > 99:\n small_good = False\n print(\" numbar of variables > 99\")\n if nobs > 1200:\n small_good = False\n print(\" number of observations > 1,200\")\n if num_val_encodings > 1000:\n small_good = False\n print(\" number of encodings within single value label > 1,000\")\n if version == 13:\n if max_note_size > 13400:\n small_good = False\n print(\" note size > 13,400\")\n if char_len > 13400:\n small_good = False\n print(\" char length > 13,400\")\n else:\n if max_note_size > 8681:\n small_good = False\n print(\" note size > 8,681\")\n if char_len > 8681:\n small_good = False\n print(\" char length > 8,681\")\n if small_good:\n print(\" none\")\n\n print(\"\\nStata IC problems\")\n if width > 24564:\n medium_good = False\n print(\" data set width > 24,564\")\n if nvar > 2047:\n medium_good = False\n print(\" numbar of variables > 2,047\")\n if nobs > 2147483647:\n medium_good = False\n print(\" number of observations > 2,147,483,647\")\n if num_val_encodings > 65536:\n medium_good = False\n print(\" number of encodings within single value label > 65,536\")\n if max_note_size > 67784:\n medium_good = False\n print(\" note size > 67,784\")\n if char_len > 67784:\n medium_good = False\n print(\" char length > 67,784\")\n if medium_good:\n print(\" none\")\n\n print(\"\\nStata MP & SE problems\")\n if width > 393192:\n large_good = False\n print(\" data set width > 393,192\")\n if nvar > 32767:\n large_good = False\n print(\" numbar of variables > 32,767\")\n if nobs > 2147483647:\n large_good = False\n print(\" number of observations > 2,147,483,647\")\n if num_val_encodings > 65536:\n large_good = False\n print(\" number of encodings within single value label > 65,536\")\n if max_note_size > 67784:\n large_good = False\n print(\" note size > 67,784\")\n if char_len > 67784:\n large_good = False\n print(\" char length > 67,784\")\n if large_good:\n print(\" none\")","def test_disallowedsubst00106m1_positive(mode, save_output, output_format):\n assert_bindings(\n schema=\"sunData/ElemDecl/disallowedSubst/disallowedSubst00106m/disallowedSubst00106m1.xsd\",\n instance=\"sunData/ElemDecl/disallowedSubst/disallowedSubst00106m/disallowedSubst00106m1_p.xml\",\n class_name=\"Root\",\n version=\"1.1\",\n mode=mode,\n save_output=save_output,\n output_format=output_format,\n structure_style=\"filenames\",\n )","def test_track_shape_error():\n track = np.random.randn(50,1)\n try:\n bad_arm = survey.get_spiral_slice(track = track)\n except TypeError:\n assert True\n else:\n assert False","def test_case_assumptions(self):\n self.assertTrue(\n self.existing_map_id in self.example_map.feedline_map_lookup,\n msg=f'Expects {self.existing_map_id} to be in example map keys ({list(self.example_map.feedline_map_lookup.keys())}).'\n )\n feedline_map: FeedlineMap = self.example_map.feedline_map_lookup[self.existing_map_id]\n self.assertTrue(\n self.existing_feedline_nr in feedline_map.bitmap_lookup,\n msg=f'Expects {self.existing_feedline_nr} to be in example map keys ({list(feedline_map.bitmap_lookup.keys())}).'\n )\n self.assertFalse(\n self.not_existing_map_id in self.example_map.feedline_map_lookup,\n msg=f'Expects {self.existing_map_id} NOT to be in example map keys ({list(self.example_map.feedline_map_lookup.keys())}).'\n )\n self.assertFalse(\n self.not_existing_feedline_nr in feedline_map.bitmap_lookup,\n msg=f'Expects {self.not_existing_feedline_nr} NOT to be in example map keys ({list(feedline_map.bitmap_lookup.keys())}).'\n )","def test_example(self, example_dataset, expected_result):\n\n transformer = PreprocessFeatures()\n result = transformer.fit_transform(example_dataset)\n\n assert (result == expected_result).all()","def check_validity(self):","def test_mult_specifiers_missing(self):\n template = '{0} too few {1}'\n value_count = 3\n msg = ('The formatter contains too few \"{}\" '\n 'specifiers for the number of source fields.')\n with six.assertRaisesRegex(self, ValidationError, msg):\n validate_str_substitution(template, value_count)","def test_buoy_format2():\n with pytest.raises(AssertionError) as err_info:\n Check_BuoyDC.check_buoy_format(buoy_format_fail_2)\n assert str(err_info.value) == 'Input length incorrect, see instructions'","def test_check_distribution1():\n with pytest.raises(AssertionError) as err_info:\n Check_BuoyDC.check_distribution(distribution_fail_1)\n assert str(err_info.value) == 'distribution type input not within range of index'","def test_disallowedsubst00401m1_positive(mode, save_output, output_format):\n assert_bindings(\n schema=\"sunData/ElemDecl/disallowedSubst/disallowedSubst00401m/disallowedSubst00401m1.xsd\",\n instance=\"sunData/ElemDecl/disallowedSubst/disallowedSubst00401m/disallowedSubst00401m1_p.xml\",\n class_name=\"Root\",\n version=\"1.1\",\n mode=mode,\n save_output=save_output,\n output_format=output_format,\n structure_style=\"filenames\",\n )","def test_kyc_post_legal_share_holder(self):\n pass","def input_sample_check(conc, shear, idx):\n path = '../'\n file = '/expDataFiles.csv'\n\n os.path.isfile(path + file)\n exp = pd.read_csv(path+file, index_col='index')\n\n shear_raw = exp.loc[idx, 'shear']\n sample_raw = exp.loc[idx, 'sample']\n\n # for idx, char in enumerate(shear_raw):\n # if char != ' ':\n # continue\n # else:\n # shearIdx = idx\n # # print(char)\n # break\n #\n # for idx, char in enumerate(sample_raw):\n # if char != 'w':\n # continue\n # else:\n # sampleIdx = idx\n # # print(char)\n # break\n\n # print(shearIdx)\n # x = shear_raw[0:shearIdx]\n # y = sample_raw[0:sampleIdx]\n x = str(int(shear_raw))\n y = str(int(sample_raw))\n print(x, y)\n if conc != y or shear != x:\n raise Exception('Conc or shear mismatch')\n else:\n print('Sample input matches')\n\n return","def test_validate_input_rejection(self):\n with nose.assert_raises(exceptions.RejectionError):\n self.dtm1.validate_input('000011')","def test_illegal_input(self):\n cs = ConfigurationSpace()\n cs.add_hyperparameter(UniformFloatHyperparameter('test', 1, 10, 5))\n scen = Scenario({'run_obj': 'quality', 'cs': cs})\n stats = Stats(scen)\n # Recorded runs but no incumbent.\n stats.ta_runs = 10\n smac = SMAC(scen, stats=stats, rng=np.random.RandomState(42))\n self.output_dirs.append(scen.output_dir)\n self.assertRaises(ValueError, smac.optimize)\n # Incumbent but no recoreded runs.\n incumbent = cs.get_default_configuration()\n smac = SMAC(scen, restore_incumbent=incumbent,\n rng=np.random.RandomState(42))\n self.assertRaises(ValueError, smac.optimize)","def test_init_unknown_error(self):\n with self.assertRaises(QiitaDBUnknownIDError):\n PrepSample('Not_a_Sample', self.prep_template)","def test_correct_barcode_no_error_correction(self):\r\n barcode = \"GGAGACAAGGGT\"\r\n barcode_to_sample_id = {\r\n \"GGAGACAAGGGA\": \"s1\",\r\n \"ACACCTGGTGAT\": \"s2\"}\r\n correction_fn = None\r\n\r\n actual = correct_barcode(barcode, barcode_to_sample_id, correction_fn)\r\n expected = (0, barcode, False, None)\r\n self.assertEqual(actual, expected)\r\n\r\n # barcode contains N\r\n barcode = \"CCAGTGTANGCA\"\r\n actual = correct_barcode(barcode, barcode_to_sample_id, correction_fn)\r\n expected = (0, \"CCAGTGTANGCA\", False, None)\r\n self.assertEqual(actual, expected)","def is_valid_sample(self, gazepos):\n\t\t\n\t\t# return False if a sample is invalid\n\t\tif gazepos == (None,None) or gazepos == (-1,-1):\n\t\t\treturn False\n\t\t\n\t\t# in any other case, the sample is valid\n\t\treturn True","def _expected_inputs():\n return 1","def testBadFormatISBNAgain(self): \n val = format_isbn(\"12345678\")\n self.assertFalse(val)","def test_addSample(self):\r\n self.res1.addSample('S1', 42)\r\n self.assertEqual(self.res1.getSampleCount(), 1)\r\n self.assertEqual(self.res1.getReferenceIndividualCount('S1'), 42)\r\n\r\n with self.assertRaises(ValueError):\r\n self.res1.addSample('S1', 45)","def test_plot_ess_no_sample_stats(models):\n idata = models.model_1\n with pytest.raises(ValueError, match=\"must contain sample_stats\"):\n plot_ess(idata.posterior, rug=True)","def test_score_garbage(test_input, expected):\n score = sp.score_garbage(test_input)\n assert score == expected","def test_stochatreat_input_more_treats_than_probs(correct_params):\n treat_too_large = 3\n with pytest.raises(Exception):\n stochatreat(\n data=correct_params[\"data\"],\n block_cols=[\"block\"],\n treats=treat_too_large,\n idx_col=correct_params[\"idx_col\"],\n probs=correct_params[\"probs\"],\n )","def test_final_strongly_recommended(self):\n\n # move raw to X amd: i.e. there is no final\n self.validator.adata.X = self.validator.adata.raw.X\n del self.validator.adata.raw\n self.validator.adata.uns[\"X_normalization\"] = \"none\"\n self.validator.validate_adata()\n self.assertEqual(\n self.validator.warnings,\n [\n \"WARNING: Only raw data was found, i.e. there is no 'raw.X' and 'uns['X_normalization']' is 'none'. \"\n \"It is STRONGLY RECOMMENDED that 'final' (normalized) data is provided.\"\n ],\n )","def _validate_sample(instance: typing.Dict[str, typing.Any], schema: typing.Dict[str, typing.Any], path: typing.List[str]) -> None:\n if not isinstance(instance, dict):\n raise ValidationError('instance must be dict', path)\n valid_keys = {'_type', 'object_id'}\n required_keys = valid_keys\n schema_keys = set(instance.keys())\n invalid_keys = schema_keys - valid_keys - opt_federation_keys\n if invalid_keys:\n raise ValidationError('unexpected keys in schema: {}'.format(invalid_keys), path)\n missing_keys = required_keys - schema_keys\n if missing_keys:\n raise ValidationError('missing keys in schema: {}'.format(missing_keys), path)\n if instance['_type'] != 'sample':\n raise ValidationError('expected _type \"sample\"', path)\n if not isinstance(instance['object_id'], int):\n raise ValidationError('object_id must be int', path)\n if 'component_uuid' in instance and instance['component_uuid'] != flask.current_app.config['FEDERATION_UUID']:\n pass\n else:\n try:\n sample = objects.get_object(object_id=instance['object_id'])\n except ObjectDoesNotExistError:\n raise ValidationError('object does not exist', path)\n if sample.action_id is None:\n raise ValidationError('object must be sample', path)\n action = actions.get_action(sample.action_id)\n if action.type is None:\n raise ValidationError('object must be sample', path)\n if action.type_id != ActionType.SAMPLE_CREATION and action.type.fed_id != ActionType.SAMPLE_CREATION:\n raise ValidationError('object must be sample', path)","def test_disallowedsubst00301m1_positive(mode, save_output, output_format):\n assert_bindings(\n schema=\"sunData/ElemDecl/disallowedSubst/disallowedSubst00301m/disallowedSubst00301m1.xsd\",\n instance=\"sunData/ElemDecl/disallowedSubst/disallowedSubst00301m/disallowedSubst00301m1_p.xml\",\n class_name=\"Root\",\n version=\"1.1\",\n mode=mode,\n save_output=save_output,\n output_format=output_format,\n structure_style=\"filenames\",\n )","def test_grounded_modified_enzyme():\n mek_s202 = Agent('MEK1', mods=[ModCondition('phosphorylation', 'S', '202')],\n db_refs={'HGNC': '6840'})\n mek_phos = Agent('MEK1', mods=[ModCondition('phosphorylation', None, None)],\n db_refs={'HGNC': '6840'})\n erk = Agent('ERK2', db_refs={'HGNC': '6871'})\n stmt_to_model = Phosphorylation(mek_s202, erk, None, None)\n stmt_to_check = Phosphorylation(mek_phos, erk, None, None)\n pa = PysbAssembler()\n pa.add_statements([stmt_to_model])\n pa.make_model(policies='one_step')\n mc = ModelChecker(pa.model, [stmt_to_check])\n results = mc.check_model()\n assert len(results) == 1\n assert results[0][0] == stmt_to_check\n assert results[0][1].paths == \\\n [[('MEK1_phosphoS202_phosphorylation_ERK2_phospho', 1),\n ('ERK2_phospho_p_obs', 1)]]","def experiment3():\n raise FAKE_ERROR","def testNSESanityChecks(self):\n self.assertEqual(100, self.c.get_species_richness())\n self.assertEqual(67, self.c2.get_species_richness())","def _check_student_inputs(self, numtolerance_inputs):\r\n _ = self.capa_system.i18n.ugettext\r\n inputs_correct = True\r\n for answer_name, answer_value in numtolerance_inputs.iteritems():\r\n # If `self.corrrect_inputs` does not contain an entry for\r\n # `answer_name`, this means that answer_name is a decoy\r\n # input's value, and validation of its numericality is the\r\n # only thing of interest from the later call to\r\n # `compare_with_tolerance`.\r\n params = self.correct_inputs.get(answer_name, {'answer': 0})\r\n\r\n correct_ans = params['answer']\r\n # Set the tolerance to '0' if it was not specified in the xml\r\n tolerance = params.get('tolerance', default_tolerance)\r\n # Make sure that the staff answer is a valid number\r\n try:\r\n correct_ans = complex(correct_ans)\r\n except ValueError:\r\n log.debug(\r\n \"Content error--answer '%s' is not a valid complex number\",\r\n correct_ans\r\n )\r\n raise StudentInputError(\r\n _(\"The Staff answer could not be interpreted as a number.\")\r\n )\r\n # Compare the student answer to the staff answer/ or to 0\r\n # if all that is important is verifying numericality\r\n try:\r\n partial_correct = compare_with_tolerance(\r\n evaluator({}, {}, answer_value),\r\n correct_ans,\r\n tolerance\r\n )\r\n except:\r\n # Use the traceback-preserving version of re-raising with a\r\n # different type\r\n __, __, trace = sys.exc_info()\r\n msg = _(\"Could not interpret '{given_answer}' as a number.\").format(\r\n given_answer=cgi.escape(answer_value)\r\n )\r\n msg += \" ({0})\".format(trace)\r\n raise StudentInputError(msg)\r\n\r\n # Ignore the results of the comparisons which were just for\r\n # Numerical Validation.\r\n if answer_name in self.correct_inputs and not partial_correct:\r\n # If any input is not correct, set the return value to False\r\n inputs_correct = False\r\n return inputs_correct","def test_validation_correct_systems():\n data_paths = examples_paths()\n exp_builder = ExperimentBuilder()\n basic_script = \"\"\"\n ---\n molecules:\n rec: {{filepath: {0}, leap: {{parameters: leaprc.ff14SB}}}}\n rec_reg: {{filepath: {0}, regions: {{receptregion: 'some dsl'}}, leap: {{parameters: leaprc.ff14SB}}}}\n lig: {{name: lig, leap: {{parameters: leaprc.gaff}}}}\n lig_reg: {{name: lig, regions: {{ligregion: [143, 123]}}, leap: {{parameters: leaprc.gaff}}}}\n solvents:\n solv: {{nonbonded_method: NoCutoff}}\n solv2: {{nonbonded_method: NoCutoff, implicit_solvent: OBC2}}\n solv3: {{nonbonded_method: PME, clearance: 10*angstroms}}\n solv4: {{nonbonded_method: PME}}\n \"\"\".format(data_paths['lysozyme'])\n basic_script = yaml.load(textwrap.dedent(basic_script), Loader=yaml.FullLoader)\n\n systems = [\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'solv'},\n {'receptor': 'rec_reg', 'ligand': 'lig_reg', 'solvent': 'solv'},\n {'receptor': 'rec_reg', 'ligand': 'lig', 'solvent': 'solv'},\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'solv', 'pack': True},\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'solv3',\n 'leap': {'parameters': ['leaprc.gaff', 'leaprc.ff14SB']}},\n\n {'phase1_path': data_paths['bentol-complex'],\n 'phase2_path': data_paths['bentol-solvent'],\n 'ligand_dsl': 'resname BEN', 'solvent': 'solv'},\n {'phase1_path': data_paths['bentol-complex'],\n 'phase2_path': data_paths['bentol-solvent'],\n 'ligand_dsl': 'resname BEN', 'solvent': 'solv4'},\n {'phase1_path': data_paths['bentol-complex'],\n 'phase2_path': data_paths['bentol-solvent'],\n 'ligand_dsl': 'resname BEN', 'solvent1': 'solv3',\n 'solvent2': 'solv2'},\n\n {'phase1_path': data_paths['pxylene-complex'],\n 'phase2_path': data_paths['pxylene-solvent'],\n 'ligand_dsl': 'resname p-xylene', 'solvent': 'solv',\n 'gromacs_include_dir': data_paths['pxylene-gro-include']},\n {'phase1_path': data_paths['pxylene-complex'],\n 'phase2_path': data_paths['pxylene-solvent'],\n 'ligand_dsl': 'resname p-xylene', 'solvent': 'solv'},\n\n {'phase1_path': data_paths['toluene-solvent'],\n 'phase2_path': data_paths['toluene-vacuum'],\n 'ligand_dsl': 'resname TOL'},\n {'phase1_path': data_paths['toluene-solvent'],\n 'phase2_path': data_paths['toluene-vacuum'],\n 'ligand_dsl': 'resname TOL', 'solvent_dsl': 'not resname TOL'},\n\n {'solute': 'lig', 'solvent1': 'solv', 'solvent2': 'solv'},\n {'solute': 'lig_reg', 'solvent1': 'solv', 'solvent2': 'solv'},\n {'solute': 'lig', 'solvent1': 'solv', 'solvent2': 'solv',\n 'leap': {'parameters': 'leaprc.gaff'}}\n ]\n for system in systems:\n modified_script = basic_script.copy()\n modified_script['systems'] = {'sys': system}\n yield exp_builder.parse, modified_script","def test_compute_correlation_paired_incompatible_samples(self):\r\n self.assertRaises(ValueError, _compute_correlation,\r\n self.taxa_summary1, self.taxa_summary3, 'paired',\r\n 'spearman', 'high', 9, 0.22222)","def test_non_numberic_validation(self):","def test_non_numberic_validation(self):","def test_sanitization_function(self):\n for (broken, clean) in self.needSanitization:\n self.assertEquals(clean, sanitizeFeedback(broken))\n\n for test in self.noSanitizingNeeded:\n self.assertEquals(test, sanitizeFeedback(test))","def test_validate_input_valid(self):\n final_config = self.dtm1.validate_input('00001111')\n nose.assert_equal(final_config[0], 'q4')\n nose.assert_equal(str(final_config[1]), 'TMTape(\\'xxxxyyyy.\\')')","def test_disallowedsubst00501m1_positive(mode, save_output, output_format):\n assert_bindings(\n schema=\"sunData/ElemDecl/disallowedSubst/disallowedSubst00501m/disallowedSubst00501m1.xsd\",\n instance=\"sunData/ElemDecl/disallowedSubst/disallowedSubst00501m/disallowedSubst00501m1_p.xml\",\n class_name=\"Root\",\n version=\"1.1\",\n mode=mode,\n save_output=save_output,\n output_format=output_format,\n structure_style=\"filenames\",\n )","def test_disallowedsubst00102m1_positive(mode, save_output, output_format):\n assert_bindings(\n schema=\"sunData/ElemDecl/disallowedSubst/disallowedSubst00102m/disallowedSubst00102m1.xsd\",\n instance=\"sunData/ElemDecl/disallowedSubst/disallowedSubst00102m/disallowedSubst00102m1_p.xml\",\n class_name=\"Root\",\n version=\"1.1\",\n mode=mode,\n save_output=save_output,\n output_format=output_format,\n structure_style=\"filenames\",\n )","def test_incorrect_prediction_key(self):\n self._config['Prediction key'] = 'wrong_key'\n with self.assertRaisesRegex(ValueError, 'Invalid prediction key'):\n self._gen.generate(\n example=self._example,\n model=self._model,\n dataset=self._dataset,\n config=self._config)","def test_show_correctness_default(self):\n assert ShowCorrectness.correctness_available()","def test_properlyAveraged(self):\n r0 = self.singleReader\n r1 = DetectorReader(DET_FILES['bwr1'])\n r1.read()\n for detName in self.sampler.detectors:\n expectedTallies, expectedErrors = (_getExpectedAverages(\n r0.detectors[detName], r1.detectors[detName]))\n uniq = self.sampler.detectors[detName]\n assert_allclose(uniq.tallies, expectedTallies, err_msg='tallies',\n **TOLERANCES['tallies'])\n assert_allclose(uniq.errors, expectedErrors, err_msg='errrors',\n **TOLERANCES['errors'])","def test_required(self):\n \n from pystarlab.starlab import Makeplummer\n self.assertRaises(ValueError, Makeplummer)\n self.assertRaises(ValueError, Makeplummer, n=500)\n \n # this will fail if it raises any exceptions\n plummer_nonfailing = Makeplummer(n=500, s=12345)","def check_prize(correct_num):","def test_required(self):\n \n from pystarlab.starlab import Makeking\n self.assertRaises(ValueError, Makeking)\n \n self.assertRaises(ValueError, Makeking, n=500)\n \n self.assertRaises(ValueError, Makeking, w=1.4)\n \n # this will fail if it raises any exceptions\n king_nonfailing = Makeking(n=500, w=1.4, s=12345678)","def test_for_arbitrarily_complicated_substance():\n verify_atomic_weight_for_substance(\"Al4O2H2\", 141.94015428)","def test_single_specifier_missing(self):\n template = 'missing'\n value_count = 1\n msg = 'The formatter should contain one \"{}\" specifier.'\n with six.assertRaisesRegex(self, ValidationError, msg):\n validate_str_substitution(template, value_count)"],"string":"[\n \"def test_is_gene_continuously_amplified_wrong_input(self):\\n self.assertEqual(\\\"Wrong input data\\\", is_gene_continuously_amplified(13))\",\n \"def run_sample_checks(sub: Submission, logger):\\n\\n samples = sub.sample\\n factors = [f.value for f in sub.study.experimental_factor]\\n organisms = set()\\n units = set()\\n characteristics = []\\n codes = []\\n\\n if not samples:\\n logger.error(\\\"Experiment has no samples. At least one expected.\\\")\\n codes.append(\\\"SAMP-E01\\\")\\n return codes\\n for s in samples:\\n # Sample must have a name\\n if not s.alias:\\n logger.error(\\\"Sample found with no name. Not checking it further.\\\")\\n codes.append(\\\"SAMP-E02\\\")\\n continue\\n # Sample must have organism/taxon annotation\\n if not s.taxon:\\n logger.error(\\\"Sample \\\\\\\"{}\\\\\\\" has no organism specified.\\\".format(s.alias))\\n codes.append(\\\"SAMP-E03\\\")\\n else:\\n organisms.add(s.taxon)\\n # Collecting units and categories\\n for a, a_attr in s.attributes.items():\\n if a_attr.unit and a_attr.unit.value:\\n if a_attr.unit.value not in units:\\n units.add(a_attr.unit.value)\\n if a not in characteristics:\\n characteristics.append(a)\\n\\n # Check organism name is in taxonomy\\n for o in organisms:\\n taxon_id = converter_utils.get_taxon(o)\\n logger.debug(\\\"Found taxon ID: {}\\\".format(taxon_id))\\n if not isinstance(taxon_id, int):\\n logger.error(\\\"Organism \\\\\\\"{}\\\\\\\" was not found in NCBI taxonomy.\\\".format(o))\\n codes.append(\\\"SAMP-E08\\\")\\n\\n # Check units\\n unit_term = ontology_term(\\\"unit\\\")\\n allowed_units = get_term_descendants(unit_term[\\\"ontology\\\"], unit_term[\\\"uri\\\"], logger)\\n for unit_label in units:\\n if unit_label not in allowed_units:\\n logger.error(\\\"Unit \\\\\\\"{}\\\\\\\" is not from approved list (EFO term).\\\".format(unit_label))\\n codes.append(\\\"SAMP-E04\\\")\\n\\n # Check that factors defined in study are found in sample attributes\\n undefined_factors = [f for f in factors if f not in characteristics]\\n if len(undefined_factors) > 0:\\n logger.error(\\\"The following factors are declared but not annotated: {}\\\".format(\\\", \\\".join(undefined_factors)))\\n codes.append(\\\"SAMP-E05\\\")\\n\\n # Check that factor values vary\\n unique_factor_values = {}\\n for f in factors:\\n if f not in undefined_factors:\\n # Get all values for a given factor\\n factor_values = [s.attributes[f].value.rstrip() for s in samples]\\n # Filter duplicated values to get the number of unique entries\\n unique_factor_values[f.lower()] = converter_utils.remove_duplicates(factor_values)\\n non_factors = [f_name for f_name, values in unique_factor_values.items() if len(values) < 2]\\n good_factors = [f_name for f_name, values in unique_factor_values.items() if len(values) > 1]\\n # Go through factors and check for special cases that are exempt from the rule\\n for f in non_factors:\\n # Special case dose\\n if f == \\\"dose\\\":\\n # Error if both dose + compound/irradiade do not vary\\n if \\\"compound\\\" in non_factors or \\\"irradiate\\\" in non_factors:\\n logger.error(\\\"For factor values including dose, at least one must vary.\\\")\\n codes.append(\\\"SAMP-E07\\\")\\n # Allow dose to not vary if compound/irradiate do\\n elif \\\"compound\\\" in good_factors or \\\"irradiate\\\" in good_factors:\\n continue\\n # For compound/irradiate, we already check this above. Need to skip here to suppress second error message\\n elif f == \\\"compound\\\" and \\\"dose\\\" in non_factors:\\n continue\\n elif f == \\\"irradiate\\\" and \\\"dose\\\" in non_factors:\\n continue\\n # Special case immunoprecipitate\\n elif f == \\\"immunoprecipitate\\\":\\n logger.info(\\\"Found factor \\\\\\\"immunoprecipitate\\\\\\\". This doesn't need to vary.\\\")\\n else:\\n logger.error(\\\"Factor value \\\\\\\"{}\\\\\\\" does not vary.\\\".format(f))\\n codes.append(\\\"SAMP-E06\\\")\\n\\n return codes\",\n \"def test_hardcoded_example(self):\\n expected_accuracy = dict(num_recall=2, uniq_recall=2, num_precision=3, uniq_precision=2)\\n self._run_and_validate(self.detections, self.ground_truths, expected_accuracy)\",\n \"def test_no_specification_error():\\n try:\\n bad_arm = survey.get_spiral_slice()\\n except SyntaxError:\\n assert True\\n else:\\n assert False\",\n \"def test_proper(self):\\n\\n self.assertTrue(self.cs.isProper)\\n self.assertFalse(self.cs.isDegenerate)\",\n \"def test__validate_topic__2():\\n for input_value in (\\n 12.6,\\n ):\\n with vampytest.assert_raises(TypeError):\\n validate_topic(input_value)\",\n \"def try_accept_the_example(self, denoising_sample, denoising_label):\\n assert isinstance(denoising_sample, np.ndarray)\\n assert isinstance(denoising_label, int) or isinstance(denoising_label, np.int64)\\n # assert self.input.shape == denoising_sample.shape\\n\\n ok = self._is_successful(denoising_label)\\n if ok:\\n self.__denoising_sample = denoising_sample\\n self.denoising_label = denoising_label\\n else:\\n self.__bad_denoising_example = denoising_sample\\n\\n return ok\",\n \"def _checkSample(self):\\n Sampler._checkSample(self)\\n # make sure the prefix is registered for tracking\\n # but if there's no identifying information, skip this check\\n if self._registeredIdentifiers:\\n prefix = self.inputInfo['prefix']\\n if not prefix in self._prefixToIdentifiers:\\n self.raiseAnError(RuntimeError, f'Prefix \\\"{prefix}\\\" has not been tracked in adaptive sampling!')\",\n \"def test_kyc_post_legal(self):\\n pass\",\n \"def test_validate_input_good_input(self):\\r\\n _validate_input(self.dist_matrix_header, self.dist_matrix,\\r\\n self.mapping_header, self.mapping, \\\"Treatment\\\")\",\n \"def test_validate_answer(self):\\r\\n sample_dict = {'x': (1, 2)}\\r\\n problem = self.build_problem(\\r\\n sample_dict=sample_dict,\\r\\n num_samples=10,\\r\\n tolerance=\\\"1%\\\",\\r\\n answer=\\\"x\\\"\\r\\n )\\r\\n self.assertTrue(problem.responders.values()[0].validate_answer('14*x'))\\r\\n self.assertFalse(problem.responders.values()[0].validate_answer('3*y+2*x'))\",\n \"def test_interpret_error(self):\\r\\n two_choice_two_input = self._make_problem(\\r\\n [\\r\\n (\\\"true\\\", {\\\"answer\\\": \\\"123\\\", \\\"tolerance\\\": \\\"1\\\"}),\\r\\n (\\\"false\\\", {})\\r\\n ],\\r\\n \\\"checkboxtextgroup\\\"\\r\\n )\\r\\n\\r\\n with self.assertRaisesRegexp(StudentInputError, \\\"Could not interpret\\\"):\\r\\n # Test that error is raised for input in selected correct choice.\\r\\n self.assert_grade(\\r\\n two_choice_two_input,\\r\\n self._make_answer_dict([(True, [\\\"Platypus\\\"])]),\\r\\n \\\"correct\\\"\\r\\n )\\r\\n\\r\\n with self.assertRaisesRegexp(StudentInputError, \\\"Could not interpret\\\"):\\r\\n # Test that error is raised for input in selected incorrect choice.\\r\\n self.assert_grade(\\r\\n two_choice_two_input,\\r\\n self._make_answer_dict([(True, [\\\"1\\\"]), (True, [\\\"Platypus\\\"])]),\\r\\n \\\"correct\\\"\\r\\n )\",\n \"def test_stochatreat_input_invalid_probs(correct_params):\\n probs_not_sum_to_one = [0.1, 0.2]\\n with pytest.raises(Exception):\\n stochatreat(\\n data=correct_params[\\\"data\\\"],\\n block_cols=[\\\"block\\\"],\\n treats=correct_params[\\\"treat\\\"],\\n idx_col=correct_params[\\\"idx_col\\\"],\\n probs=probs_not_sum_to_one,\\n )\",\n \"def test_kyc_get_validation_legal(self):\\n pass\",\n \"def testProtractedPostApplicationSanityChecks(self):\\n self.assertLess(self.c.get_species_richness(1), self.c.get_species_richness(3))\\n self.assertLess(self.c.get_species_richness(2), self.c.get_species_richness(4))\\n self.assertLess(self.c.get_species_richness(5), self.c.get_species_richness(3))\\n self.assertLess(self.c.get_species_richness(6), self.c.get_species_richness(4))\\n self.assertEqual(4, self.c.get_species_richness(1))\\n self.assertEqual(4, self.c.get_species_richness(2))\\n self.assertEqual(7, self.c.get_species_richness(3))\\n self.assertEqual(7, self.c.get_species_richness(4))\\n self.assertEqual(4, self.c.get_species_richness(5))\\n self.assertEqual(4, self.c.get_species_richness(6))\\n self.assertEqual(21, self.c.get_species_richness(7))\\n self.assertEqual(38, self.c.get_species_richness(8))\",\n \"def testProtractedPostApplicationSanityChecks(self):\\n self.assertLess(self.c.get_species_richness(1), self.c.get_species_richness(3))\\n self.assertLess(self.c.get_species_richness(2), self.c.get_species_richness(4))\\n self.assertLess(self.c.get_species_richness(5), self.c.get_species_richness(3))\\n self.assertLess(self.c.get_species_richness(6), self.c.get_species_richness(4))\\n self.assertEqual(4, self.c.get_species_richness(1))\\n self.assertEqual(4, self.c.get_species_richness(2))\\n self.assertEqual(7, self.c.get_species_richness(3))\\n self.assertEqual(7, self.c.get_species_richness(4))\\n self.assertEqual(4, self.c.get_species_richness(5))\\n self.assertEqual(4, self.c.get_species_richness(6))\\n self.assertEqual(21, self.c.get_species_richness(7))\\n self.assertEqual(38, self.c.get_species_richness(8))\",\n \"def testProtractedPostApplicationSanityChecks(self):\\n self.assertLess(self.c.get_species_richness(1), self.c.get_species_richness(3))\\n self.assertLess(self.c.get_species_richness(2), self.c.get_species_richness(4))\\n self.assertLess(self.c.get_species_richness(5), self.c.get_species_richness(3))\\n self.assertLess(self.c.get_species_richness(6), self.c.get_species_richness(4))\\n self.assertEqual(4, self.c.get_species_richness(1))\\n self.assertEqual(4, self.c.get_species_richness(2))\\n self.assertEqual(7, self.c.get_species_richness(3))\\n self.assertEqual(7, self.c.get_species_richness(4))\\n self.assertEqual(4, self.c.get_species_richness(5))\\n self.assertEqual(4, self.c.get_species_richness(6))\\n self.assertEqual(21, self.c.get_species_richness(7))\\n self.assertEqual(38, self.c.get_species_richness(8))\",\n \"def test_05_valid_stroke(self):\\n stroke_record = SwimRecord(stroke='doggie paddle')\\n try:\\n stroke_record.full_clean()\\n except ValidationError as e:\\n self.assertTrue(\\\"doggie paddle is not a valid stroke\\\" in e.message_dict['stroke'])\",\n \"def validate_answer(self, answer):\\r\\n var_dict_list = self.randomize_variables(self.samples)\\r\\n try:\\r\\n self.tupleize_answers(answer, var_dict_list)\\r\\n return True\\r\\n except StudentInputError:\\r\\n return False\",\n \"def test_contentious_prescription_no_rationale(self):\\n url = reverse('admin:prescription_prescription_add')\\n data = {\\n 'name': 'Test',\\n 'planned_season': 1,\\n 'planned_year': 2013,\\n 'region': 1,\\n 'district': 1,\\n 'location': 'Test location',\\n 'perimeter': 20,\\n 'area': 100,\\n 'purposes': [1],\\n 'remote_sensing_priority': 4,\\n 'priority': 2,\\n 'contentious': True,\\n }\\n response = self.client.post(url, data)\\n self.assertEqual(response.status_code, 200)\\n self.assertEqual(Prescription.objects.count(), 0)\\n form = response.context['adminform'].form\\n self.assertEqual(form.errors, {\\n 'contentious_rationale': ['A contentious burn requires a '\\n 'contentious rationale.']\\n })\",\n \"def test_validation_wrong_systems():\\n data_paths = examples_paths()\\n exp_builder = ExperimentBuilder()\\n basic_script = \\\"\\\"\\\"\\n ---\\n molecules:\\n rec: {{filepath: {0}, leap: {{parameters: oldff/leaprc.ff14SB}}}}\\n rec_region: {{filepath: {0}, regions: {{a_region: 'some string'}}, leap: {{parameters: oldff/leaprc.ff14SB}}}}\\n lig: {{name: lig, leap: {{parameters: leaprc.gaff}}}}\\n lig_region: {{name: lig, regions: {{a_region: 'some string'}}, leap: {{parameters: leaprc.gaff}}}}\\n solvents:\\n solv: {{nonbonded_method: NoCutoff}}\\n solv2: {{nonbonded_method: NoCutoff, implicit_solvent: OBC2}}\\n solv3: {{nonbonded_method: PME, clearance: 10*angstroms}}\\n solv4: {{nonbonded_method: PME}}\\n \\\"\\\"\\\".format(data_paths['lysozyme'])\\n basic_script = yaml.load(textwrap.dedent(basic_script), Loader=yaml.FullLoader)\\n\\n # Each test case is a pair (regexp_error, system_description).\\n systems = [\\n (\\\"'solvent' is required\\\",\\n {'receptor': 'rec', 'ligand': 'lig'}),\\n\\n (\\\"regions\\\\(s\\\\) clashing\\\",\\n {'receptor': 'rec_region', 'ligand': 'lig_region', 'solvent': 'solv'}),\\n\\n (\\\"ligand:\\\\n- must be of string type\\\",\\n {'receptor': 'rec', 'ligand': 1, 'solvent': 'solv'}),\\n\\n (\\\"solvent:\\\\n- must be of string type\\\",\\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': ['solv', 'solv']}),\\n\\n (\\\"unallowed value unknown\\\",\\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'unknown'}),\\n\\n (\\\"solv4 does not specify clearance\\\",\\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'solv4',\\n 'leap': {'parameters': ['leaprc.gaff', 'leaprc.ff14SB']}}),\\n\\n (\\\"parameters:\\\\n- unknown field\\\",\\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'solv3',\\n 'parameters': 'leaprc.ff14SB'}),\\n\\n (\\\"phase1_path:\\\\n- must be of list type\\\",\\n {'phase1_path': data_paths['bentol-complex'][0],\\n 'phase2_path': data_paths['bentol-solvent'],\\n 'ligand_dsl': 'resname BEN', 'solvent': 'solv'}),\\n\\n (\\\"File path nonexistingpath.prmtop does not exist.\\\",\\n {'phase1_path': ['nonexistingpath.prmtop', 'nonexistingpath.inpcrd'],\\n 'phase2_path': data_paths['bentol-solvent'],\\n 'ligand_dsl': 'resname BEN', 'solvent': 'solv'}),\\n\\n (\\\"ligand_dsl:\\\\n- must be of string type\\\",\\n {'phase1_path': data_paths['bentol-complex'],\\n 'phase2_path': data_paths['bentol-solvent'],\\n 'ligand_dsl': 3.4, 'solvent': 'solv'}),\\n\\n (\\\"unallowed value unknown\\\",\\n {'phase1_path': data_paths['bentol-complex'],\\n 'phase2_path': data_paths['bentol-solvent'],\\n 'ligand_dsl': 'resname BEN', 'solvent1': 'unknown',\\n 'solvent2': 'solv2'}),\\n\\n (\\\"unallowed value cantbespecified\\\",\\n {'phase1_path': data_paths['toluene-solvent'],\\n 'phase2_path': data_paths['toluene-vacuum'],\\n 'ligand_dsl': 'resname TOL', 'solvent': 'cantbespecified'}),\\n\\n (\\\"field 'ligand' is required\\\",\\n {'receptor': 'rec', 'solute': 'lig', 'solvent1': 'solv', 'solvent2': 'solv'}),\\n\\n (\\\"''ligand'' must not be present with ''solute''\\\",\\n {'ligand': 'lig', 'solute': 'lig', 'solvent1': 'solv', 'solvent2': 'solv'}),\\n\\n (\\\"leap:\\\\n- must be of dict type\\\",\\n {'solute': 'lig', 'solvent1': 'solv', 'solvent2': 'solv', 'leap': 'leaprc.gaff'})\\n ]\\n for regexp, system in systems:\\n modified_script = basic_script.copy()\\n modified_script['systems'] = {'sys': system}\\n yield assert_raises_regexp, YamlParseError, regexp, exp_builder.parse, modified_script\",\n \"def test_incorrect_creation_1(input_data, exact):\\n with pytest.raises(ValueError):\\n TaxCalcIO(input_data=input_data,\\n tax_year=2013,\\n reform=None,\\n assump=None,\\n growdiff_response=None,\\n aging_input_data=False,\\n exact_calculations=exact)\",\n \"def validate_sample_and_seq_exp(program_id, donor_id, analysis_objs):\\n sample_fields = {\\n 'submitterSampleId': 'samples.submitterSampleId',\\n 'sampleType': 'samples.sampleType',\\n 'matchedNormalSubmitterSampleId': 'samples.matchedNormalSubmitterSampleId',\\n 'specimenId': 'samples.specimen.specimenId',\\n 'specimenType': 'samples.specimen.specimenType',\\n 'tumourNormalDesignation': 'samples.specimen.tumourNormalDesignation',\\n 'specimenTissueSource': 'samples.specimen.specimenTissueSource',\\n 'donorId': 'samples.donor.donorId',\\n 'gender': 'samples.donor.gender',\\n 'studyId': 'studyId'\\n }\\n\\n # gather sample information from all analysis objects\\n sample_info = dict()\\n for a in analysis_objs:\\n analysisId = a['analysisId']\\n sampleId = a['samples'][0]['sampleId']\\n if sampleId not in sample_info:\\n sample_info[sampleId] = {\\n 'sampleId': sampleId,\\n 'analysisId': [],\\n 'sequencing_experiment': {}\\n }\\n\\n sample_info[sampleId]['analysisId'].append(analysisId)\\n\\n for field in sample_fields:\\n if field not in sample_info[sampleId]:\\n sample_info[sampleId][field] = dict()\\n\\n source_path = sample_fields[field].split('.')\\n if len(source_path) == 1:\\n source_value_str = str(a[source_path[0]])\\n elif source_path[0] == 'samples':\\n if len(source_path) == 2:\\n source_value_str = str(a['samples'][0][source_path[1]])\\n elif len(source_path) == 3:\\n source_value_str = str(a['samples'][0][source_path[1]][source_path[2]])\\n else:\\n assert False # not supposed to reach here\\n else:\\n assert False # not supposed to reach here\\n\\n if source_value_str not in sample_info[sampleId][field]:\\n sample_info[sampleId][field][source_value_str] = []\\n\\n sample_info[sampleId][field][source_value_str].append(analysisId)\\n\\n # add sequencing_experiment\\n if a.get('analysisType', {}).get('name') in ('sequencing_experiment', 'rna_sequencing_experiment'):\\n strategy = a['experiment']['experimental_strategy']\\n matchedNormalSubmitterSampleId = a['samples'][0]['matchedNormalSubmitterSampleId']\\n\\n if strategy not in sample_info[sampleId]['sequencing_experiment']:\\n sample_info[sampleId]['sequencing_experiment'][strategy] = {\\n 'sequencing_experiment_analysis_id': [analysisId],\\n 'matchedNormalSubmitterSampleId': [matchedNormalSubmitterSampleId]\\n }\\n else:\\n sample_info[sampleId]['sequencing_experiment'][strategy]['sequencing_experiment_analysis_id'].append(analysisId)\\n sample_info[sampleId]['sequencing_experiment'][strategy]['matchedNormalSubmitterSampleId'].append(matchedNormalSubmitterSampleId)\\n\\n # print(json.dumps({'donor_id': donor_id}))\\n # print(json.dumps(sample_info))\\n\\n samples, issues = value_discrepancy_check(sample_info, sample_fields)\\n # print(json.dumps(samples))\\n # print(json.dumps(issues))\\n\\n submitterSampleId2SampleId = mapping_sumbitter_sample_id_to_sample_id(samples)\\n # print(json.dumps(submitterSampleId2SampleId))\\n\\n # figure out tumour-normal pairs\\n tumour_normal_pairs, tumour_not_paired, normal_not_paired, normal_paired, issues = resolve_tumour_normal_pairs(samples, submitterSampleId2SampleId)\\n # print(json.dumps(tumour_normal_pairs))\\n # print(json.dumps(normal_paired))\\n # print(json.dumps(tumour_not_paired))\\n # print(json.dumps(normal_not_paired))\\n # print(json.dumps(issues))\",\n \"def reason(self, example):\\n raise NotImplementedError()\",\n \"def test_buoy_format1():\\n with pytest.raises(AssertionError) as err_info:\\n Check_BuoyDC.check_buoy_format(buoy_format_fail_1)\\n assert str(err_info.value) == 'Input formatted incorrectly, see instructions'\",\n \"def test_sanity(self) -> None:\\n if self.report.headlines:\\n return\\n\\n if self.report.document.paragraphs:\\n self.add_error(\\n \\\"Rubrikerna i dokumentet är felformaterade eller saknas. \\\"\\n \\\"Rubrikerna ska vara skrivna i versaler och ha samma \\\"\\n \\\"typsnitt, stil och storlek som brödtexten. \\\"\\n \\\"Rubriker avslutas med radbrytning.\\\"\\n )\\n\\n if not self.report.document.paragraphs:\\n self.add_error(\\\"Ditt dokument är antigen tomt eller i fel format.\\\")\",\n \"def test_update_study_missing(self):\\n study_spec = sample_study_spec()\\n with self.assertRaises(ValueError):\\n self.storage.update_study(study_spec)\",\n \"def test_strain_redefined(generate_strain_redefined):\\n fname = generate_strain_redefined\\n try:\\n process_files([fname])\\n raise Exception('The redefined strain data and lack of stress data was not caught')\\n except IOError:\\n pass\",\n \"def test_single_specifier_needed(self):\\n template = '{0} one too many {1}'\\n value_count = 1\\n msg = ('The formatter should only contain one '\\n '\\\"{}\\\" specifier for the source field.')\\n with six.assertRaisesRegex(self, ValidationError, msg):\\n validate_str_substitution(template, value_count)\",\n \"def test__validate_title__1():\\n for input_value in (\\n 12.6,\\n ):\\n with vampytest.assert_raises(TypeError):\\n validate_title(input_value)\",\n \"def test_wrong_input(self):\\n\\n test_float = 2954.02\\n test_list = [\\\"anagram\\\", \\\"gramana\\\"]\\n with pytest.raises(AttributeError) as exc_info:\\n is_anagram(test_float, test_list)\\n expected_error_msg = \\\"Words must be strings!\\\"\\n assert exc_info.match(expected_error_msg)\",\n \"def assert_goodness(self):\\n if self._setted:\\n self.assert_stored_iss()\\n self.assert_stored_ks()\\n ## Check idxs\\n self.assert_stored_idxs()\\n ## Check sp_relative_pos\\n self.assert_stored_sp_rel_pos()\",\n \"def test_for_unknown_chemical():\\n try:\\n verify_atomic_weight_for_substance(\\\",.!\\\", 1.0)\\n except periodic_table.InvalidFormula as e:\\n return\\n\\n raise AssertionError(\\\"test_for_unknown_chemical() didn't fail\\\")\",\n \"def test_validation_wrong_samplers():\\n # Each test case is a pair (regexp_error, sampler_description).\\n samplers = [\\n (\\\"locality must be an int\\\",\\n {'type': 'MultiStateSampler', 'locality': 3.0}),\\n (\\\"unallowed value unknown\\\",\\n {'type': 'ReplicaExchangeSampler', 'mcmc_moves': 'unknown'}),\\n (\\\"Could not find class NonExistentSampler\\\",\\n {'type': 'NonExistentSampler'}),\\n (\\\"found unknown parameter\\\",\\n {'type': 'ReplicaExchangeSampler', 'unknown_kwarg': 5}),\\n ]\\n exp_builder = ExperimentBuilder(get_template_script())\\n for regexp, sampler in samplers:\\n script = {'samplers': {'sampler1': sampler}}\\n yield assert_raises_regexp, YamlParseError, regexp, exp_builder._validate_samplers, script\",\n \"def testProtractedNSESanityChecks(self):\\n self.assertGreater(self.c3.get_species_richness(1), self.c2.get_species_richness(1))\\n self.assertLess(self.c4.get_species_richness(1), self.c3.get_species_richness(1))\",\n \"def test_error_basis_state_format(self, basis_state, wires):\\n\\n with pytest.raises(ValueError, match=\\\"'basis_state' must only contain\\\"):\\n BasisStatePreparation(basis_state, wires)\",\n \"def test_generating(resp):\\n errors = []\\n if not check_int(resp[\\\"tightness\\\"]):\\n errors.append(\\\"Invalid type for Itinerary response's 'tightness' field.\\\")\\n\\n if not isinstance(resp, bool):\\n errors.append(\\\"Invalid type for Itinerary response's 'start_from_airport' field.\\\")\",\n \"def violated(self) -> bool:\\n ...\",\n \"def test_incorrect_creation_2(rawinputfile, reformfile0, year, ref, asm, gdr):\\n # pylint: disable=too-many-arguments\\n if ref == 'reformfile0':\\n reform = reformfile0.name\\n else:\\n reform = ref\\n with pytest.raises(ValueError):\\n TaxCalcIO(\\n input_data=rawinputfile.name,\\n tax_year=year,\\n reform=reform,\\n assump=asm,\\n growdiff_response=gdr,\\n aging_input_data=False,\\n exact_calculations=False)\",\n \"def test_constructed_is_small(self):\\n self.assertTrue(all(elt<10 for elt in goodwinsheaf.checkradii()))#check all entries have small radii\",\n \"def sanity_check(self):\\n pass\",\n \"def test_invalid_format(self):\\n input_file = self.copy_and_mark_for_cleanup(\\\"Medline/pubmed_result1.txt\\\")\\n\\n cline = XXmotifCommandline(outdir=self.out_dir, seqfile=input_file)\\n\\n try:\\n stdout, stderr = cline()\\n except ApplicationError as err:\\n self.assertEqual(err.returncode, 255)\\n else:\\n self.fail(f\\\"Should have failed, returned:\\\\n{stdout}\\\\n{stderr}\\\")\",\n \"def test_X_normalization_not_raw(self):\\n\\n # Assign a real value to X while X_normalization is 'none'\\n del self.validator.adata.raw\\n self.validator.adata.uns[\\\"X_normalization\\\"] = \\\"none\\\"\\n self.validator.validate_adata()\\n print(\\\"FOO\\\", self.validator.warnings)\\n self.assertEqual(\\n self.validator.warnings,\\n [\\n \\\"WARNING: uns['X_normalization'] is 'none', there is no 'raw.X' and 'X' doesn't appear \\\"\\n \\\"to have raw counts (integers)\\\"\\n ],\\n )\",\n \"def test_non_integral_validation(self):\",\n \"def test_non_integral_validation(self):\",\n \"def sanity_check(self):\\n return True\",\n \"def test_stochatreat_input_invalid_size(correct_params):\\n size_bigger_than_sampling_universe_size = 101\\n with pytest.raises(ValueError):\\n stochatreat(\\n data=correct_params[\\\"data\\\"],\\n block_cols=[\\\"block\\\"],\\n treats=correct_params[\\\"treat\\\"],\\n idx_col=correct_params[\\\"idx_col\\\"],\\n probs=correct_params[\\\"probs\\\"],\\n size=size_bigger_than_sampling_universe_size,\\n )\",\n \"def check():\",\n \"def is_example(self, is_example):\\n self._is_example = is_example\",\n \"def test_issn_incorrect_length(self):\\n issns = ['0307-15', '0307-15789', '03071758', '0307175']\\n for num in issns:\\n with self.subTest(num=num):\\n with self.assertRaisesRegex(ValueError, num):\\n star_barcode.construct_postscript(\\n issn=num,\\n bwipp_location=self.bwipp,\\n sequence=21,\\n week=46,\\n header_line=''\\n )\",\n \"def test_is_AKs_preHandSimple_correct(self):\\n self.assertEqual(self.hand.getPreHandSimple(), 'AKs')\",\n \"def test_create_unexpected_problem(self):\\n pass\",\n \"def _check_validity(self):\\n pass\",\n \"def do_checks(self):\\n # ## get valid experiment variables\\n all_subexperiments = [1, 2, 3]\\n all_plates = list(range(1, 19))\\n all_cell_ids = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I']\\n all_samples = list(self.experiment.design['Sample'])\\n all_genes = self.experiment.subexperiments[1].plates[1].samples[all_samples[0]].genes\\n all_replicates = list(range(1, 7))\\n all_time = [0.5, 1.0, 2.0, 3.0, 4.0, 8.0, 12.0, 24.0, 48.0, 72.0, 96.0]\\n\\n if self.time is None:\\n if self.treatment is 'Baseline':\\n self.time = [0.0, 96.0]\\n else:\\n self.time = all_time\\n\\n if self.cell_id is None:\\n self.cell_id = all_cell_ids\\n\\n if self.gene is None:\\n self.gene = all_genes\\n\\n if self.replicate is None:\\n self.replicate = all_replicates\\n\\n if self.treatment is None:\\n raise ValueError('treatment cannot be None. Specify one of \\\"TGFb\\\", \\\"Control\\\", \\\"Baseline\\\"')\\n\\n if not isinstance(self.treatment, str):\\n raise ValueError('treatment must be a string. Got \\\"{}\\\" a \\\"{}\\\"'.format(\\n self.treatment, type(self.treatment)\\n ))\\n\\n if not isinstance(self.normed, bool):\\n raise ValueError('normed argument should be boolean. Got \\\"{}\\\"'.format(\\n type(self.normed)\\n ))\\n\\n if not isinstance(self.time, list):\\n self.time = [self.time]\\n\\n for time_point in self.time:\\n if time_point not in sorted(list(set(self.data.columns.get_level_values(1)))):\\n raise ValueError('\\\"{}\\\" is invalid time point. Valid time '\\n 'points are: {}'.format(\\n time_point, list(self.data.columns))\\n )\",\n \"def check(self, version=None):\\n \\n if version is None:\\n print(\\\"assuming Stata version 13\\\")\\n version = 13\\n if version not in (11, 12, 13):\\n raise ValueError(\\\"allowed versions are 11 through 13\\\")\\n \\n width = self.width\\n nvar = self._nvar\\n nobs = self._nobs\\n \\n chrdict = self._chrdict\\n \\n char_len = max([0] + [len(char) for evar, evardict in chrdict.items()\\n for char in evardict.values()])\\n num_val_encodings = max([0] + [len(mapping) \\n for mapping in self._vallabs.values()])\\n max_note_size = max([0] + [len(note) for d in chrdict.values()\\n for name, note in d.items()\\n if re.match(r'^note[0-9]+$', name)])\\n max_num_notes = max([0] + [len([1 for name,note in d.items() \\n if re.match(r'^note[0-9]+$', name)])\\n for d in chrdict.values()])\\n \\n if '_dta' in chrdict and '_lang_list' in chrdict['_dta']:\\n n_label_langs = len(chrdict['_dta'][\\\"_lang_list\\\"].split())\\n else:\\n n_label_langs = 0\\n \\n small_good = medium_good = large_good = True\\n general_good = format_good = True\\n \\n print(\\\"\\\\nformat problems\\\")\\n if self._ds_format == 117 and version <= 12:\\n format_good = False\\n print(\\\" format 117 cannot be opened by Stata version \\\" + \\n str(version))\\n if version < 12 and any(TB_FMT_RE.match(fmt) for fmt in self._fmtlist):\\n format_good = False\\n print(\\\" Stata version \\\" + str(version) + \\n \\\" cannot understand tb format\\\")\\n if format_good:\\n print(\\\" none\\\")\\n \\n print(\\\"\\\\ngeneral size problems\\\")\\n if len(self._data_label) > 80:\\n general_good = False\\n print(\\\" data label length > 80\\\")\\n if any(len(name) > 32 for name in self._varlist):\\n general_good = False\\n print(\\\" variable name length > 32\\\")\\n if any(len(v) > 80 for v in self._vlblist):\\n general_good = False\\n print(\\\" variable label length > 80\\\")\\n if any(len(name) > 32 for name in self._vallabs.keys()):\\n general_good = False\\n print(\\\" value label name length > 32\\\")\\n if any(len(valstr) > 32000 \\n for mapping in self._vallabs.values()\\n for valstr in mapping.values()):\\n general_good = False\\n print(\\\" value label string length > 32,000\\\")\\n if max_num_notes > 10000:\\n # limit here is set at 10000, assuming one of the notes is 'note0'\\n general_good = False\\n print(\\\" number of notes for single variable or _dta > 9,999\\\")\\n if n_label_langs > 100:\\n general_good = False\\n print(\\\" number of label languages > 100\\\")\\n if general_good:\\n print(\\\" none\\\")\\n\\n print(\\\"\\\\nStata small problems\\\")\\n if width > 800:\\n small_good = False\\n print(\\\" data set width > 800\\\")\\n if nvar > 99:\\n small_good = False\\n print(\\\" numbar of variables > 99\\\")\\n if nobs > 1200:\\n small_good = False\\n print(\\\" number of observations > 1,200\\\")\\n if num_val_encodings > 1000:\\n small_good = False\\n print(\\\" number of encodings within single value label > 1,000\\\")\\n if version == 13:\\n if max_note_size > 13400:\\n small_good = False\\n print(\\\" note size > 13,400\\\")\\n if char_len > 13400:\\n small_good = False\\n print(\\\" char length > 13,400\\\")\\n else:\\n if max_note_size > 8681:\\n small_good = False\\n print(\\\" note size > 8,681\\\")\\n if char_len > 8681:\\n small_good = False\\n print(\\\" char length > 8,681\\\")\\n if small_good:\\n print(\\\" none\\\")\\n\\n print(\\\"\\\\nStata IC problems\\\")\\n if width > 24564:\\n medium_good = False\\n print(\\\" data set width > 24,564\\\")\\n if nvar > 2047:\\n medium_good = False\\n print(\\\" numbar of variables > 2,047\\\")\\n if nobs > 2147483647:\\n medium_good = False\\n print(\\\" number of observations > 2,147,483,647\\\")\\n if num_val_encodings > 65536:\\n medium_good = False\\n print(\\\" number of encodings within single value label > 65,536\\\")\\n if max_note_size > 67784:\\n medium_good = False\\n print(\\\" note size > 67,784\\\")\\n if char_len > 67784:\\n medium_good = False\\n print(\\\" char length > 67,784\\\")\\n if medium_good:\\n print(\\\" none\\\")\\n\\n print(\\\"\\\\nStata MP & SE problems\\\")\\n if width > 393192:\\n large_good = False\\n print(\\\" data set width > 393,192\\\")\\n if nvar > 32767:\\n large_good = False\\n print(\\\" numbar of variables > 32,767\\\")\\n if nobs > 2147483647:\\n large_good = False\\n print(\\\" number of observations > 2,147,483,647\\\")\\n if num_val_encodings > 65536:\\n large_good = False\\n print(\\\" number of encodings within single value label > 65,536\\\")\\n if max_note_size > 67784:\\n large_good = False\\n print(\\\" note size > 67,784\\\")\\n if char_len > 67784:\\n large_good = False\\n print(\\\" char length > 67,784\\\")\\n if large_good:\\n print(\\\" none\\\")\",\n \"def test_disallowedsubst00106m1_positive(mode, save_output, output_format):\\n assert_bindings(\\n schema=\\\"sunData/ElemDecl/disallowedSubst/disallowedSubst00106m/disallowedSubst00106m1.xsd\\\",\\n instance=\\\"sunData/ElemDecl/disallowedSubst/disallowedSubst00106m/disallowedSubst00106m1_p.xml\\\",\\n class_name=\\\"Root\\\",\\n version=\\\"1.1\\\",\\n mode=mode,\\n save_output=save_output,\\n output_format=output_format,\\n structure_style=\\\"filenames\\\",\\n )\",\n \"def test_track_shape_error():\\n track = np.random.randn(50,1)\\n try:\\n bad_arm = survey.get_spiral_slice(track = track)\\n except TypeError:\\n assert True\\n else:\\n assert False\",\n \"def test_case_assumptions(self):\\n self.assertTrue(\\n self.existing_map_id in self.example_map.feedline_map_lookup,\\n msg=f'Expects {self.existing_map_id} to be in example map keys ({list(self.example_map.feedline_map_lookup.keys())}).'\\n )\\n feedline_map: FeedlineMap = self.example_map.feedline_map_lookup[self.existing_map_id]\\n self.assertTrue(\\n self.existing_feedline_nr in feedline_map.bitmap_lookup,\\n msg=f'Expects {self.existing_feedline_nr} to be in example map keys ({list(feedline_map.bitmap_lookup.keys())}).'\\n )\\n self.assertFalse(\\n self.not_existing_map_id in self.example_map.feedline_map_lookup,\\n msg=f'Expects {self.existing_map_id} NOT to be in example map keys ({list(self.example_map.feedline_map_lookup.keys())}).'\\n )\\n self.assertFalse(\\n self.not_existing_feedline_nr in feedline_map.bitmap_lookup,\\n msg=f'Expects {self.not_existing_feedline_nr} NOT to be in example map keys ({list(feedline_map.bitmap_lookup.keys())}).'\\n )\",\n \"def test_example(self, example_dataset, expected_result):\\n\\n transformer = PreprocessFeatures()\\n result = transformer.fit_transform(example_dataset)\\n\\n assert (result == expected_result).all()\",\n \"def check_validity(self):\",\n \"def test_mult_specifiers_missing(self):\\n template = '{0} too few {1}'\\n value_count = 3\\n msg = ('The formatter contains too few \\\"{}\\\" '\\n 'specifiers for the number of source fields.')\\n with six.assertRaisesRegex(self, ValidationError, msg):\\n validate_str_substitution(template, value_count)\",\n \"def test_buoy_format2():\\n with pytest.raises(AssertionError) as err_info:\\n Check_BuoyDC.check_buoy_format(buoy_format_fail_2)\\n assert str(err_info.value) == 'Input length incorrect, see instructions'\",\n \"def test_check_distribution1():\\n with pytest.raises(AssertionError) as err_info:\\n Check_BuoyDC.check_distribution(distribution_fail_1)\\n assert str(err_info.value) == 'distribution type input not within range of index'\",\n \"def test_disallowedsubst00401m1_positive(mode, save_output, output_format):\\n assert_bindings(\\n schema=\\\"sunData/ElemDecl/disallowedSubst/disallowedSubst00401m/disallowedSubst00401m1.xsd\\\",\\n instance=\\\"sunData/ElemDecl/disallowedSubst/disallowedSubst00401m/disallowedSubst00401m1_p.xml\\\",\\n class_name=\\\"Root\\\",\\n version=\\\"1.1\\\",\\n mode=mode,\\n save_output=save_output,\\n output_format=output_format,\\n structure_style=\\\"filenames\\\",\\n )\",\n \"def test_kyc_post_legal_share_holder(self):\\n pass\",\n \"def input_sample_check(conc, shear, idx):\\n path = '../'\\n file = '/expDataFiles.csv'\\n\\n os.path.isfile(path + file)\\n exp = pd.read_csv(path+file, index_col='index')\\n\\n shear_raw = exp.loc[idx, 'shear']\\n sample_raw = exp.loc[idx, 'sample']\\n\\n # for idx, char in enumerate(shear_raw):\\n # if char != ' ':\\n # continue\\n # else:\\n # shearIdx = idx\\n # # print(char)\\n # break\\n #\\n # for idx, char in enumerate(sample_raw):\\n # if char != 'w':\\n # continue\\n # else:\\n # sampleIdx = idx\\n # # print(char)\\n # break\\n\\n # print(shearIdx)\\n # x = shear_raw[0:shearIdx]\\n # y = sample_raw[0:sampleIdx]\\n x = str(int(shear_raw))\\n y = str(int(sample_raw))\\n print(x, y)\\n if conc != y or shear != x:\\n raise Exception('Conc or shear mismatch')\\n else:\\n print('Sample input matches')\\n\\n return\",\n \"def test_validate_input_rejection(self):\\n with nose.assert_raises(exceptions.RejectionError):\\n self.dtm1.validate_input('000011')\",\n \"def test_illegal_input(self):\\n cs = ConfigurationSpace()\\n cs.add_hyperparameter(UniformFloatHyperparameter('test', 1, 10, 5))\\n scen = Scenario({'run_obj': 'quality', 'cs': cs})\\n stats = Stats(scen)\\n # Recorded runs but no incumbent.\\n stats.ta_runs = 10\\n smac = SMAC(scen, stats=stats, rng=np.random.RandomState(42))\\n self.output_dirs.append(scen.output_dir)\\n self.assertRaises(ValueError, smac.optimize)\\n # Incumbent but no recoreded runs.\\n incumbent = cs.get_default_configuration()\\n smac = SMAC(scen, restore_incumbent=incumbent,\\n rng=np.random.RandomState(42))\\n self.assertRaises(ValueError, smac.optimize)\",\n \"def test_init_unknown_error(self):\\n with self.assertRaises(QiitaDBUnknownIDError):\\n PrepSample('Not_a_Sample', self.prep_template)\",\n \"def test_correct_barcode_no_error_correction(self):\\r\\n barcode = \\\"GGAGACAAGGGT\\\"\\r\\n barcode_to_sample_id = {\\r\\n \\\"GGAGACAAGGGA\\\": \\\"s1\\\",\\r\\n \\\"ACACCTGGTGAT\\\": \\\"s2\\\"}\\r\\n correction_fn = None\\r\\n\\r\\n actual = correct_barcode(barcode, barcode_to_sample_id, correction_fn)\\r\\n expected = (0, barcode, False, None)\\r\\n self.assertEqual(actual, expected)\\r\\n\\r\\n # barcode contains N\\r\\n barcode = \\\"CCAGTGTANGCA\\\"\\r\\n actual = correct_barcode(barcode, barcode_to_sample_id, correction_fn)\\r\\n expected = (0, \\\"CCAGTGTANGCA\\\", False, None)\\r\\n self.assertEqual(actual, expected)\",\n \"def is_valid_sample(self, gazepos):\\n\\t\\t\\n\\t\\t# return False if a sample is invalid\\n\\t\\tif gazepos == (None,None) or gazepos == (-1,-1):\\n\\t\\t\\treturn False\\n\\t\\t\\n\\t\\t# in any other case, the sample is valid\\n\\t\\treturn True\",\n \"def _expected_inputs():\\n return 1\",\n \"def testBadFormatISBNAgain(self): \\n val = format_isbn(\\\"12345678\\\")\\n self.assertFalse(val)\",\n \"def test_addSample(self):\\r\\n self.res1.addSample('S1', 42)\\r\\n self.assertEqual(self.res1.getSampleCount(), 1)\\r\\n self.assertEqual(self.res1.getReferenceIndividualCount('S1'), 42)\\r\\n\\r\\n with self.assertRaises(ValueError):\\r\\n self.res1.addSample('S1', 45)\",\n \"def test_plot_ess_no_sample_stats(models):\\n idata = models.model_1\\n with pytest.raises(ValueError, match=\\\"must contain sample_stats\\\"):\\n plot_ess(idata.posterior, rug=True)\",\n \"def test_score_garbage(test_input, expected):\\n score = sp.score_garbage(test_input)\\n assert score == expected\",\n \"def test_stochatreat_input_more_treats_than_probs(correct_params):\\n treat_too_large = 3\\n with pytest.raises(Exception):\\n stochatreat(\\n data=correct_params[\\\"data\\\"],\\n block_cols=[\\\"block\\\"],\\n treats=treat_too_large,\\n idx_col=correct_params[\\\"idx_col\\\"],\\n probs=correct_params[\\\"probs\\\"],\\n )\",\n \"def test_final_strongly_recommended(self):\\n\\n # move raw to X amd: i.e. there is no final\\n self.validator.adata.X = self.validator.adata.raw.X\\n del self.validator.adata.raw\\n self.validator.adata.uns[\\\"X_normalization\\\"] = \\\"none\\\"\\n self.validator.validate_adata()\\n self.assertEqual(\\n self.validator.warnings,\\n [\\n \\\"WARNING: Only raw data was found, i.e. there is no 'raw.X' and 'uns['X_normalization']' is 'none'. \\\"\\n \\\"It is STRONGLY RECOMMENDED that 'final' (normalized) data is provided.\\\"\\n ],\\n )\",\n \"def _validate_sample(instance: typing.Dict[str, typing.Any], schema: typing.Dict[str, typing.Any], path: typing.List[str]) -> None:\\n if not isinstance(instance, dict):\\n raise ValidationError('instance must be dict', path)\\n valid_keys = {'_type', 'object_id'}\\n required_keys = valid_keys\\n schema_keys = set(instance.keys())\\n invalid_keys = schema_keys - valid_keys - opt_federation_keys\\n if invalid_keys:\\n raise ValidationError('unexpected keys in schema: {}'.format(invalid_keys), path)\\n missing_keys = required_keys - schema_keys\\n if missing_keys:\\n raise ValidationError('missing keys in schema: {}'.format(missing_keys), path)\\n if instance['_type'] != 'sample':\\n raise ValidationError('expected _type \\\"sample\\\"', path)\\n if not isinstance(instance['object_id'], int):\\n raise ValidationError('object_id must be int', path)\\n if 'component_uuid' in instance and instance['component_uuid'] != flask.current_app.config['FEDERATION_UUID']:\\n pass\\n else:\\n try:\\n sample = objects.get_object(object_id=instance['object_id'])\\n except ObjectDoesNotExistError:\\n raise ValidationError('object does not exist', path)\\n if sample.action_id is None:\\n raise ValidationError('object must be sample', path)\\n action = actions.get_action(sample.action_id)\\n if action.type is None:\\n raise ValidationError('object must be sample', path)\\n if action.type_id != ActionType.SAMPLE_CREATION and action.type.fed_id != ActionType.SAMPLE_CREATION:\\n raise ValidationError('object must be sample', path)\",\n \"def test_disallowedsubst00301m1_positive(mode, save_output, output_format):\\n assert_bindings(\\n schema=\\\"sunData/ElemDecl/disallowedSubst/disallowedSubst00301m/disallowedSubst00301m1.xsd\\\",\\n instance=\\\"sunData/ElemDecl/disallowedSubst/disallowedSubst00301m/disallowedSubst00301m1_p.xml\\\",\\n class_name=\\\"Root\\\",\\n version=\\\"1.1\\\",\\n mode=mode,\\n save_output=save_output,\\n output_format=output_format,\\n structure_style=\\\"filenames\\\",\\n )\",\n \"def test_grounded_modified_enzyme():\\n mek_s202 = Agent('MEK1', mods=[ModCondition('phosphorylation', 'S', '202')],\\n db_refs={'HGNC': '6840'})\\n mek_phos = Agent('MEK1', mods=[ModCondition('phosphorylation', None, None)],\\n db_refs={'HGNC': '6840'})\\n erk = Agent('ERK2', db_refs={'HGNC': '6871'})\\n stmt_to_model = Phosphorylation(mek_s202, erk, None, None)\\n stmt_to_check = Phosphorylation(mek_phos, erk, None, None)\\n pa = PysbAssembler()\\n pa.add_statements([stmt_to_model])\\n pa.make_model(policies='one_step')\\n mc = ModelChecker(pa.model, [stmt_to_check])\\n results = mc.check_model()\\n assert len(results) == 1\\n assert results[0][0] == stmt_to_check\\n assert results[0][1].paths == \\\\\\n [[('MEK1_phosphoS202_phosphorylation_ERK2_phospho', 1),\\n ('ERK2_phospho_p_obs', 1)]]\",\n \"def experiment3():\\n raise FAKE_ERROR\",\n \"def testNSESanityChecks(self):\\n self.assertEqual(100, self.c.get_species_richness())\\n self.assertEqual(67, self.c2.get_species_richness())\",\n \"def _check_student_inputs(self, numtolerance_inputs):\\r\\n _ = self.capa_system.i18n.ugettext\\r\\n inputs_correct = True\\r\\n for answer_name, answer_value in numtolerance_inputs.iteritems():\\r\\n # If `self.corrrect_inputs` does not contain an entry for\\r\\n # `answer_name`, this means that answer_name is a decoy\\r\\n # input's value, and validation of its numericality is the\\r\\n # only thing of interest from the later call to\\r\\n # `compare_with_tolerance`.\\r\\n params = self.correct_inputs.get(answer_name, {'answer': 0})\\r\\n\\r\\n correct_ans = params['answer']\\r\\n # Set the tolerance to '0' if it was not specified in the xml\\r\\n tolerance = params.get('tolerance', default_tolerance)\\r\\n # Make sure that the staff answer is a valid number\\r\\n try:\\r\\n correct_ans = complex(correct_ans)\\r\\n except ValueError:\\r\\n log.debug(\\r\\n \\\"Content error--answer '%s' is not a valid complex number\\\",\\r\\n correct_ans\\r\\n )\\r\\n raise StudentInputError(\\r\\n _(\\\"The Staff answer could not be interpreted as a number.\\\")\\r\\n )\\r\\n # Compare the student answer to the staff answer/ or to 0\\r\\n # if all that is important is verifying numericality\\r\\n try:\\r\\n partial_correct = compare_with_tolerance(\\r\\n evaluator({}, {}, answer_value),\\r\\n correct_ans,\\r\\n tolerance\\r\\n )\\r\\n except:\\r\\n # Use the traceback-preserving version of re-raising with a\\r\\n # different type\\r\\n __, __, trace = sys.exc_info()\\r\\n msg = _(\\\"Could not interpret '{given_answer}' as a number.\\\").format(\\r\\n given_answer=cgi.escape(answer_value)\\r\\n )\\r\\n msg += \\\" ({0})\\\".format(trace)\\r\\n raise StudentInputError(msg)\\r\\n\\r\\n # Ignore the results of the comparisons which were just for\\r\\n # Numerical Validation.\\r\\n if answer_name in self.correct_inputs and not partial_correct:\\r\\n # If any input is not correct, set the return value to False\\r\\n inputs_correct = False\\r\\n return inputs_correct\",\n \"def test_validation_correct_systems():\\n data_paths = examples_paths()\\n exp_builder = ExperimentBuilder()\\n basic_script = \\\"\\\"\\\"\\n ---\\n molecules:\\n rec: {{filepath: {0}, leap: {{parameters: leaprc.ff14SB}}}}\\n rec_reg: {{filepath: {0}, regions: {{receptregion: 'some dsl'}}, leap: {{parameters: leaprc.ff14SB}}}}\\n lig: {{name: lig, leap: {{parameters: leaprc.gaff}}}}\\n lig_reg: {{name: lig, regions: {{ligregion: [143, 123]}}, leap: {{parameters: leaprc.gaff}}}}\\n solvents:\\n solv: {{nonbonded_method: NoCutoff}}\\n solv2: {{nonbonded_method: NoCutoff, implicit_solvent: OBC2}}\\n solv3: {{nonbonded_method: PME, clearance: 10*angstroms}}\\n solv4: {{nonbonded_method: PME}}\\n \\\"\\\"\\\".format(data_paths['lysozyme'])\\n basic_script = yaml.load(textwrap.dedent(basic_script), Loader=yaml.FullLoader)\\n\\n systems = [\\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'solv'},\\n {'receptor': 'rec_reg', 'ligand': 'lig_reg', 'solvent': 'solv'},\\n {'receptor': 'rec_reg', 'ligand': 'lig', 'solvent': 'solv'},\\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'solv', 'pack': True},\\n {'receptor': 'rec', 'ligand': 'lig', 'solvent': 'solv3',\\n 'leap': {'parameters': ['leaprc.gaff', 'leaprc.ff14SB']}},\\n\\n {'phase1_path': data_paths['bentol-complex'],\\n 'phase2_path': data_paths['bentol-solvent'],\\n 'ligand_dsl': 'resname BEN', 'solvent': 'solv'},\\n {'phase1_path': data_paths['bentol-complex'],\\n 'phase2_path': data_paths['bentol-solvent'],\\n 'ligand_dsl': 'resname BEN', 'solvent': 'solv4'},\\n {'phase1_path': data_paths['bentol-complex'],\\n 'phase2_path': data_paths['bentol-solvent'],\\n 'ligand_dsl': 'resname BEN', 'solvent1': 'solv3',\\n 'solvent2': 'solv2'},\\n\\n {'phase1_path': data_paths['pxylene-complex'],\\n 'phase2_path': data_paths['pxylene-solvent'],\\n 'ligand_dsl': 'resname p-xylene', 'solvent': 'solv',\\n 'gromacs_include_dir': data_paths['pxylene-gro-include']},\\n {'phase1_path': data_paths['pxylene-complex'],\\n 'phase2_path': data_paths['pxylene-solvent'],\\n 'ligand_dsl': 'resname p-xylene', 'solvent': 'solv'},\\n\\n {'phase1_path': data_paths['toluene-solvent'],\\n 'phase2_path': data_paths['toluene-vacuum'],\\n 'ligand_dsl': 'resname TOL'},\\n {'phase1_path': data_paths['toluene-solvent'],\\n 'phase2_path': data_paths['toluene-vacuum'],\\n 'ligand_dsl': 'resname TOL', 'solvent_dsl': 'not resname TOL'},\\n\\n {'solute': 'lig', 'solvent1': 'solv', 'solvent2': 'solv'},\\n {'solute': 'lig_reg', 'solvent1': 'solv', 'solvent2': 'solv'},\\n {'solute': 'lig', 'solvent1': 'solv', 'solvent2': 'solv',\\n 'leap': {'parameters': 'leaprc.gaff'}}\\n ]\\n for system in systems:\\n modified_script = basic_script.copy()\\n modified_script['systems'] = {'sys': system}\\n yield exp_builder.parse, modified_script\",\n \"def test_compute_correlation_paired_incompatible_samples(self):\\r\\n self.assertRaises(ValueError, _compute_correlation,\\r\\n self.taxa_summary1, self.taxa_summary3, 'paired',\\r\\n 'spearman', 'high', 9, 0.22222)\",\n \"def test_non_numberic_validation(self):\",\n \"def test_non_numberic_validation(self):\",\n \"def test_sanitization_function(self):\\n for (broken, clean) in self.needSanitization:\\n self.assertEquals(clean, sanitizeFeedback(broken))\\n\\n for test in self.noSanitizingNeeded:\\n self.assertEquals(test, sanitizeFeedback(test))\",\n \"def test_validate_input_valid(self):\\n final_config = self.dtm1.validate_input('00001111')\\n nose.assert_equal(final_config[0], 'q4')\\n nose.assert_equal(str(final_config[1]), 'TMTape(\\\\'xxxxyyyy.\\\\')')\",\n \"def test_disallowedsubst00501m1_positive(mode, save_output, output_format):\\n assert_bindings(\\n schema=\\\"sunData/ElemDecl/disallowedSubst/disallowedSubst00501m/disallowedSubst00501m1.xsd\\\",\\n instance=\\\"sunData/ElemDecl/disallowedSubst/disallowedSubst00501m/disallowedSubst00501m1_p.xml\\\",\\n class_name=\\\"Root\\\",\\n version=\\\"1.1\\\",\\n mode=mode,\\n save_output=save_output,\\n output_format=output_format,\\n structure_style=\\\"filenames\\\",\\n )\",\n \"def test_disallowedsubst00102m1_positive(mode, save_output, output_format):\\n assert_bindings(\\n schema=\\\"sunData/ElemDecl/disallowedSubst/disallowedSubst00102m/disallowedSubst00102m1.xsd\\\",\\n instance=\\\"sunData/ElemDecl/disallowedSubst/disallowedSubst00102m/disallowedSubst00102m1_p.xml\\\",\\n class_name=\\\"Root\\\",\\n version=\\\"1.1\\\",\\n mode=mode,\\n save_output=save_output,\\n output_format=output_format,\\n structure_style=\\\"filenames\\\",\\n )\",\n \"def test_incorrect_prediction_key(self):\\n self._config['Prediction key'] = 'wrong_key'\\n with self.assertRaisesRegex(ValueError, 'Invalid prediction key'):\\n self._gen.generate(\\n example=self._example,\\n model=self._model,\\n dataset=self._dataset,\\n config=self._config)\",\n \"def test_show_correctness_default(self):\\n assert ShowCorrectness.correctness_available()\",\n \"def test_properlyAveraged(self):\\n r0 = self.singleReader\\n r1 = DetectorReader(DET_FILES['bwr1'])\\n r1.read()\\n for detName in self.sampler.detectors:\\n expectedTallies, expectedErrors = (_getExpectedAverages(\\n r0.detectors[detName], r1.detectors[detName]))\\n uniq = self.sampler.detectors[detName]\\n assert_allclose(uniq.tallies, expectedTallies, err_msg='tallies',\\n **TOLERANCES['tallies'])\\n assert_allclose(uniq.errors, expectedErrors, err_msg='errrors',\\n **TOLERANCES['errors'])\",\n \"def test_required(self):\\n \\n from pystarlab.starlab import Makeplummer\\n self.assertRaises(ValueError, Makeplummer)\\n self.assertRaises(ValueError, Makeplummer, n=500)\\n \\n # this will fail if it raises any exceptions\\n plummer_nonfailing = Makeplummer(n=500, s=12345)\",\n \"def check_prize(correct_num):\",\n \"def test_required(self):\\n \\n from pystarlab.starlab import Makeking\\n self.assertRaises(ValueError, Makeking)\\n \\n self.assertRaises(ValueError, Makeking, n=500)\\n \\n self.assertRaises(ValueError, Makeking, w=1.4)\\n \\n # this will fail if it raises any exceptions\\n king_nonfailing = Makeking(n=500, w=1.4, s=12345678)\",\n \"def test_for_arbitrarily_complicated_substance():\\n verify_atomic_weight_for_substance(\\\"Al4O2H2\\\", 141.94015428)\",\n \"def test_single_specifier_missing(self):\\n template = 'missing'\\n value_count = 1\\n msg = 'The formatter should contain one \\\"{}\\\" specifier.'\\n with six.assertRaisesRegex(self, ValidationError, msg):\\n validate_str_substitution(template, value_count)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.58382","0.5788629","0.57696885","0.57351416","0.5699103","0.56888586","0.5672273","0.5641919","0.5641791","0.5625378","0.5616322","0.55867195","0.55762357","0.5548231","0.55378455","0.55378455","0.55378455","0.55340374","0.5527008","0.5521629","0.55169755","0.5516228","0.5507241","0.55061895","0.550358","0.54982424","0.5484642","0.54682696","0.5459543","0.5458472","0.5457005","0.5452573","0.5446864","0.54465824","0.54442304","0.54439276","0.54345244","0.5430259","0.5385401","0.5383901","0.53740036","0.5373084","0.536214","0.53526014","0.53526014","0.5352597","0.5346256","0.5340682","0.5329877","0.532047","0.5319081","0.53132457","0.53111273","0.5308348","0.5305015","0.5302568","0.5302051","0.53007966","0.5298998","0.52980345","0.52975655","0.5294036","0.5292523","0.5287518","0.52871954","0.5278112","0.52769244","0.5273821","0.5272924","0.52728474","0.5267617","0.5264033","0.5253439","0.5251127","0.5248353","0.5248211","0.52421445","0.5241545","0.52409625","0.5239124","0.52288353","0.5221644","0.5219989","0.5218302","0.52165955","0.52149737","0.5207278","0.5207278","0.52063394","0.5205841","0.52050084","0.5203725","0.5201692","0.51984364","0.51924276","0.51915604","0.51898605","0.51888996","0.5186851","0.5169978"],"string":"[\n \"0.58382\",\n \"0.5788629\",\n \"0.57696885\",\n \"0.57351416\",\n \"0.5699103\",\n \"0.56888586\",\n \"0.5672273\",\n \"0.5641919\",\n \"0.5641791\",\n \"0.5625378\",\n \"0.5616322\",\n \"0.55867195\",\n \"0.55762357\",\n \"0.5548231\",\n \"0.55378455\",\n \"0.55378455\",\n \"0.55378455\",\n \"0.55340374\",\n \"0.5527008\",\n \"0.5521629\",\n \"0.55169755\",\n \"0.5516228\",\n \"0.5507241\",\n \"0.55061895\",\n \"0.550358\",\n \"0.54982424\",\n \"0.5484642\",\n \"0.54682696\",\n \"0.5459543\",\n \"0.5458472\",\n \"0.5457005\",\n \"0.5452573\",\n \"0.5446864\",\n \"0.54465824\",\n \"0.54442304\",\n \"0.54439276\",\n \"0.54345244\",\n \"0.5430259\",\n \"0.5385401\",\n \"0.5383901\",\n \"0.53740036\",\n \"0.5373084\",\n \"0.536214\",\n \"0.53526014\",\n \"0.53526014\",\n \"0.5352597\",\n \"0.5346256\",\n \"0.5340682\",\n \"0.5329877\",\n \"0.532047\",\n \"0.5319081\",\n \"0.53132457\",\n \"0.53111273\",\n \"0.5308348\",\n \"0.5305015\",\n \"0.5302568\",\n \"0.5302051\",\n \"0.53007966\",\n \"0.5298998\",\n \"0.52980345\",\n \"0.52975655\",\n \"0.5294036\",\n \"0.5292523\",\n \"0.5287518\",\n \"0.52871954\",\n \"0.5278112\",\n \"0.52769244\",\n \"0.5273821\",\n \"0.5272924\",\n \"0.52728474\",\n \"0.5267617\",\n \"0.5264033\",\n \"0.5253439\",\n \"0.5251127\",\n \"0.5248353\",\n \"0.5248211\",\n \"0.52421445\",\n \"0.5241545\",\n \"0.52409625\",\n \"0.5239124\",\n \"0.52288353\",\n \"0.5221644\",\n \"0.5219989\",\n \"0.5218302\",\n \"0.52165955\",\n \"0.52149737\",\n \"0.5207278\",\n \"0.5207278\",\n \"0.52063394\",\n \"0.5205841\",\n \"0.52050084\",\n \"0.5203725\",\n \"0.5201692\",\n \"0.51984364\",\n \"0.51924276\",\n \"0.51915604\",\n \"0.51898605\",\n \"0.51888996\",\n \"0.5186851\",\n \"0.5169978\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.64715683"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81782,"cells":{"query":{"kind":"string","value":"Test that searching for part of the beer name and mfg name works"},"document":{"kind":"string","value":"def test_compound_match(self):\n query_string = f'{self.beer.name[:10]}+{self.beer.manufacturer.name[:5]}'\n tap = TapFactory(beer=self.beer)\n response = self.client.get(\n f'{self.url}?search={query_string.upper()}',\n )\n eq_(response.status_code, 200)\n eq_(len(response.data['results']), 1, response.data)\n eq_(response.data['results'][0]['name'], self.beer.name, response.data)\n eq_(\n response.data['results'][0]['venues'][0]['id'],\n tap.venue.id,\n response.data,\n )\n eq_(len(response.data['results'][0]['venues']), 1, response.data)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_search_checkname(self):\n self.assertEquals(self.t['Scrubs'].search('my first')[0]['episodename'], 'My First Day')\n self.assertEquals(self.t['My Name Is Earl'].search('Faked His Own Death')[0]['episodename'], 'Faked His Own Death')","def test_name(self):\n\n self.check_search(\n dict(name=u'flamethrower'),\n [u'Flamethrower'],\n 'searching by name',\n exact=True,\n )\n\n self.check_search(\n dict(name=u'durp'),\n [],\n 'searching for a nonexistent name',\n exact=True,\n )\n\n self.check_search(\n dict(name=u'quICk AttACk'),\n [u'Quick Attack'],\n 'case is ignored',\n exact=True,\n )\n\n self.check_search(\n dict(name=u'thunder'),\n [ u'Thunder', u'Thunderbolt', u'Thunder Wave',\n u'ThunderShock', u'ThunderPunch', u'Thunder Fang'],\n 'no wildcards is treated as substring',\n exact=True,\n )\n self.check_search(\n dict(name=u'*under'),\n [u'Thunder'], # not ThunderShock, etc.!\n 'splat wildcard works and is not used as substring',\n exact=True,\n )\n self.check_search(\n dict(name=u'b?te'),\n [u'Bite'], # not Bug Bite!\n 'question wildcard works and is not used as substring',\n exact=True,\n )","def test_name_search(self):\n # A name in the database\n search_string = \"Umut\"\n # Search For Umut\n resp = SearchTest.client.get('/api/search/',{\"token\":SearchTest.valid_token,\"search_string\":search_string})\n search_result = json.loads(resp.content)\n # Check the name field of the result\n self.assertEqual(search_string,search_result[0]['name'],\"It doesn't return the user with the name {}\".format(search_string))","def test_name_autocomplete_match(self):\n\n # Given\n user = self.basic_user()\n user.save()\n self.client.force_login(user, backend=None)\n\n partnership_1 = self.basic_partnership()\n partnership_1.save()\n\n partnership_2 = self.basic_partnership()\n partnership_2.name = \"bla\"\n partnership_2.save()\n\n # When\n response = self.client.get('/partnership_autocomplete/?term=exa', follow=True)\n\n # Then\n self.assertContains(response, partnership_1.name, count=1)","def test_legal_names(self):\n prods = generate_products()\n for obj in prods:\n self.assertRegexpMatches(\n '(\\w{2,10} \\w{0,12}|\\?{0,3}){1}', obj.name)","def test_first_last_middle_name(self):\n\t\tformatted_name = get_formatted_name('Wolfgang','mozart','amadues')\n\t\tself.assertEqual(formatted_name,'Wolfgang Amadues Mozart')","def test_name_returner(self):\n test = self.data.name_returner()\n self.assertIn(('Trevor', 'Harvey'), test)\n self.assertIn(('Nik', 'Silver'), test)","def test_names():\n first = get_name(\"As\")\n assert first == \"Arsenic\"\n\n second = get_name(\"Be\")\n assert second == \"Beryllium\"\n\n third = get_name(\"Li\")\n assert third == \"Lithium\"","def test_search_show(self):\n self.assertEquals(\n len(self.t['life on mars'].search('the', key='episodename')),\n 10\n )","def test_three(self):\n name = get_formatted_name('david', 'malan', 'j')\n self.assertEqual(name, 'David J Malan')","def test_get_by_name1(self):\n pass","def test_legal_names(self):\n test_list = generate_products()\n names_list = []\n for i in test_list:\n names_list.append(i[0])\n for name in names_list:\n nameparts = name.split()\n self.assertEqual(len(nameparts), 2,\n msg=\"missing noun, space, or adj\")\n the_adj = nameparts[0]\n self.assertIn(the_adj, ADJECTIVES, msg='Bad Adj')\n the_noun = nameparts[1]\n self.assertIn(the_noun, NOUNS, msg='Bad Noun')","def test_legal_names(self):\n names = [prod.name for prod in generate_products()]\n sep = [(name.split()[0], name.split()[1]) for name in names]\n for name in sep:\n self.assertIn(name[0], ADJS)\n self.assertIn(name[1], NOUNS)","def test_search_with_space(self):\n # Create a group to test searching for groups\n Group.objects.create(name='spam', auto_complete=True)\n Group.objects.create(name='jam', auto_complete=True)\n Group.objects.create(name='bread', auto_complete=True)\n\n url = reverse('search')\n response = self.mozillian_client.get(url, {'q': 'am'})\n\n eq_(response.status_code, 200)\n\n queryset = response.context['people'].object_list\n for up in [self.mozillian.userprofile, self.mozillian2.userprofile]:\n self.assertTrue(up in queryset)\n\n # Assert appropriate group names are found in the document\n self.assertContains(response, 'spam')\n self.assertContains(response, 'jam')\n self.assertNotContains(response, 'bread')","def test_search_in_name(self, es_with_collector, name_term, matched_company_name):\n CompanyFactory(\n name='whiskers and tabby',\n trading_names=['Maine Coon', 'Egyptian Mau'],\n )\n CompanyFactory(\n name='1a',\n trading_names=['3a', '4a'],\n )\n es_with_collector.flush_and_refresh()\n\n url = reverse('api-v3:search:basic')\n response = self.api_client.get(\n url,\n data={\n 'term': name_term,\n 'entity': 'company',\n },\n )\n\n match = Company.objects.filter(name=matched_company_name).first()\n if match:\n assert response.data['count'] == 1\n assert len(response.data['results']) == 1\n assert response.data['results'][0]['id'] == str(match.id)\n assert [{'count': 1, 'entity': 'company'}] == response.data['aggregations']\n else:\n assert response.data['count'] == 0\n assert len(response.data['results']) == 0","def test_first_last_middle_name(self):\n formatted_name = get_formatted_name('wolfgang', 'mozart', 'amadeus')\n self.assertEqual(formatted_name, 'Wolfgang Amadeus Mozart')","def test_first_last_middle_name(self):\n formatted_name = get_formatted_name('wolfgang', 'mozart', 'amadeus')\n self.assertEqual(formatted_name, 'Wolfgang Amadeus Mozart')","def test_first_last_name(self):\n formatted_name = get_formatted_name('jimi', 'hendrix')\n self.assertEqual(formatted_name, 'Jimi Hendrix')","def test_first_last(self):\n\n full_name = get_full_name(\"pony\", \"cat\")\n self.assertEqual(full_name, \"Pony Cat\")\n\n full_name = get_full_name(\"goat\", \"cat\")\n self.assertEqual(full_name, \"Goat Cat\")","def test_first_name(self) :\n\t\tformatted_name = get_formatted_name('janis','joplin')\n\t\tself.assertEqual(formatted_name,'Janis Joplin')","def test_first_last_middle(self):\n\n full_name = get_full_name(\"pony\", \"cat\", \"sweetie\")\n self.assertEqual(full_name, \"Pony Sweetie Cat\")\n\n full_name = get_full_name(\"goat\", \"cat\", \"studman\")\n self.assertEqual(full_name, \"Goat Studman Cat\")","def test_get_by_name2(self):\n pass","def exact_name_check(name_to_test, parts):\n\n if parts is None:\n return 0\n\n if type(name_to_test) is not str:\n return 0\n\n\n for p in sorted(parts, key=len, reverse=True):\n name_to_test = name_to_test.replace(p, '', 1)\n if name_to_test == '':\n return 1\n return 0","def test_first_last_middle_name(self):\n formatted_name = get_formatted_name('marie', 'curie', 'francis')\n self.assertEqual(formatted_name, 'Marie Francis Curie')","def test_author_many_lastnames(self):\n inv_search = 'author:\"alvarez gaume, j* r* r*\"'\n spi_search = 'find a alvarez gaume, j r r'\n self._compare_searches(inv_search, spi_search)","def test_first_last(self):\r\n full_name = get_full_name('janis','joplin')\r\n # expected value\r\n self.assertEqual(full_name,'Janis Joplin')","def search(self, word):","def test_job_title(self):\n inv_search = 'title:engineer not title:programmer'\n spi_search = 'find job engineer not position programmer'\n self._compare_searches(inv_search, spi_search)","def test_legal_names(self):\n adjectives = ['Awesome', 'Shiny', 'Impressive', 'Portable', 'Improved']\n nouns = ['Anvil', 'Catapult' 'Disguise' 'Mousetrap', '???']\n products = acme_report.generate_products()\n for prod in range(len(products)):\n prod_name = products[prod].name\n name_split = prod_name.split()\n self.assertIn(name_split[0], adjectives)\n self.assertIn(name_split[1], nouns)","def test_05_get_person_by_name(self):\n p1 = Person.query.first()\n p1_data = p1.wrap()\n p1_f_name = p1_data[\"first_name\"]\n # find by first name only\n # get part of name and search\n q_string = \"?first_name={}\".format(p1_f_name[:3]) # TODO - verify the length\n rv = self.app.get('persons', query_string=q_string)\n data = json.loads(rv.data)\n self.assertEqual(data[\"count\"], 1)\n\n # find by first name and last name\n p1_l_name = p1_data[\"last_name\"]\n q_string = \"?first_name={}&last_name={}\".format(p1_f_name[:3], p1_l_name)\n rv = self.app.get('persons', query_string=q_string)\n data = json.loads(rv.data)\n self.assertEqual(data[\"count\"], 1)\n\n # find by first name and non-existing last name\n q_string = \"?first_name={}&last_name={}\".format(p1_f_name[:3], \"iAmNotThere\")\n rv = self.app.get('persons', query_string=q_string)\n data = json.loads(rv.data)\n self.assertEqual(data[\"count\"], 0)","def test_first_last_name(self):\n formatted_name = get_formatted_name('david', 'Malan')\n self.assertEqual(formatted_name, 'David Malan')","def test_legal_names(self):\r\n prod = generate_products()\r\n ADJECTIVES = ['Awesome', 'Shiny', 'Impressive', 'Portable', 'Improved']\r\n NOUNS = ['Anvil', 'Catapult', 'Disguise', 'Mousetrap', '???']\r\n for product in prod:\r\n self.assertIn(product.name.split(\" \")[0], ADJECTIVES)\r\n self.assertIn(product.name.split(\" \")[1], NOUNS)","def test_first_last_name(self):\n formatted_name = get_formatted_name('janis', 'joplin')\n self.assertEqual(formatted_name, 'Janis Joplin')","def test_first_last_name(self):\n formatted_name = get_formatted_name('janis', 'joplin')\n self.assertEqual(formatted_name, 'Janis Joplin')","def test_first_last_name(self):\n\t\tformatted_name = get_formatted_name('janos', 'jk')\n\t\tself.assertEqual(formatted_name, 'Janos Jk')","def test_first_last_middle_name(self):\n formatted_name = get_formatted_name('john', 'smith', 'billy')\n self.assertEqual(formatted_name, 'John Billy Smith')","def test_full_name(self):\n self.assertEqual(self.john.full_name, \"John Doe\")\n self.assertEqual(self.solar.full_name, \"Nathan Graule\")","def substring_match(recipe, word):\n if names_only:\n line = recipe.name\n else:\n line = str(recipe)\n\n if not case:\n word = word.lower()\n line = line.lower()\n\n return line.find(word) != -1","def test_super_short_author_name(self):\n spi_search = \"fin a er and cn cms\"\n inv_search = \"author:er collaboration:cms\"\n self._compare_searches(inv_search, spi_search)","def test_semantic_search(self):\n # A name in the database\n search_string = \"football\"\n # Search For Umut\n resp = SearchTest.client.get('/api/search/',{\"token\":SearchTest.valid_token,\"search_string\":search_string})\n search_result = json.loads(resp.content)\n # Umut must be in the results because basketball and football are semanticly related\n self.assertEqual(\"Umut\",search_result[0]['name'],\"Semantic Search functionality doesn't work.\")","def test_legal_names(self):\n product_list = generate_products()\n for prod in product_list:\n noun = prod.name.split(\" \")[1]\n adjective = prod.name.split(\" \")[0]\n self.assertIn(noun, NOUNS)\n self.assertIn(adjective, ADJECTIVES)","def match_specific_name(name: str, specific_names: list) -> str:\n c = clean_specific_name(name)\n if c == \"\":\n return c\n else:\n y = \"\"\n for x in specific_names:\n matchlist = x.variations.split(\";\")\n if c in matchlist:\n y = x.name\n return y","def test_name_field(self):\n field = self.record.find('field[@name=\\'name\\']')\n self.assertEqual(field.text, 'GUH-ADT', 'Incorrect Name Field')","def test_legal_names(self):\n products = generate_products()\n\n for product in products:\n names = product.name.split(\" \")\n self.assertIn(names[0], ADJECTIVES)\n self.assertIn(names[1], NOUNS)","def test_first_last_name(self):\n formatted_name = get_formatted_name('janis', 'joplin')\n # Asserting that formatted_name equals 'Janis Joplin'\n self.assertEqual(formatted_name, 'Janis Joplin')","def __find_string_in_response(self, fullResponse, searchFor):\n check = True\n rawResponse = fullResponse;\n if \"result\" not in rawResponse.text:\n check = False\n else:\n responseJSON = rawResponse.json()\n length_responseJSON = len(responseJSON[\"result\"])\n for i in range(0,length_responseJSON,1):\n check = searchFor in responseJSON[\"result\"][i][\"first_name\"]\n if check == False:\n return check\n return check","def test_title(names):","def test_reformatted_full_name():\n assert reformatted_full_name(\"\") == \"\"\n assert reformatted_full_name(\"George\") == \"george\"\n assert reformatted_full_name(\"X Y Z A B\") == \"x b\"","def test_name_test_queries(self):\n url = self.get_url()\n for query in TEST_NAME_QUERIES:\n response = self.client.get(url, {'q': query})\n returned_pks = get_autocomplete_view_ids(response)\n expected_matches = TEST_NAME_QUERIES[query]\n # Make sure number of matches is as expected.\n self.assertEqual(len(returned_pks), len(expected_matches))\n # Make sure the matches that are found are the ones expected.\n for expected_name in expected_matches:\n # This filter should only have one result, but I want to make sure.\n name_qs = models.HarmonizedTrait.objects.filter(i_trait_name__regex=r'^{}$'.format(expected_name))\n self.assertEqual(name_qs.count(), 1)\n expected_pk = name_qs.first().pk\n self.assertIn(expected_pk, returned_pks,\n msg=\"Could not find expected trait name {} with query '{}'\".format(expected_name, query))","def test_short_full_name(self):\n self.assertEqual(self.john.full_name_short, \"J. Doe\")\n self.assertEqual(self.solar.full_name_short, \"N. Graule\")","def find_names(s):\n \"*** YOUR CODE HERE ***\"","def test_bnd_mate_name():\n\n mate = bnd_mate_name(ALT, \"2\")\n assert mate == \"17\"","def test_author_full_initial(self):\n inv_search = 'author:\"klebanov, ig* r*\" or exactauthor:\"klebanov, i r\"'\n spi_search = \"find a klebanov, ig.r.\"\n self._compare_searches(inv_search, spi_search)","def test_legal_names(self):\n names = [i[0] for i in generate_products()]\n\n for n in names:\n name = str(n).split()\n name1 = name[0]\n name2 = name[1]\n self.assertIn(name1, ADJECTIVES)\n self.assertIn(name2, NOUNS)","def test_name_matching(string, matches: bool):\n assert (re.fullmatch(pattern, string) is not None) == matches","def test_find_word(self):\n self.assertEqual(find_word('GREEN'), [(1, 1), (1, 1), (0, 9)])\n self.assertEqual(find_word('ABSENT'), [])\n self.assertEqual(find_word('PW'), [(1, 7), (3, 7), (0, 8)])","def test_special_characters_business_name(self):\n user = \"chairman\"\n msg = self.business_item_class.create_business(\"Ma@en_deleo\", user, \"soft*%ware\", \"nairo@&\")\n print(msg)\n self.assertEqual(msg, {\"message\":\"Business name should not contain special characters\"})","def test_regex_query_shortcuts(self):\n person = self.Person(name=\"Guido van Rossum\")\n person.save()\n\n # Test contains\n obj = self.Person.objects(name__contains=\"van\").first()\n assert obj == person\n obj = self.Person.objects(name__contains=\"Van\").first()\n assert obj is None\n\n # Test icontains\n obj = self.Person.objects(name__icontains=\"Van\").first()\n assert obj == person\n\n # Test startswith\n obj = self.Person.objects(name__startswith=\"Guido\").first()\n assert obj == person\n obj = self.Person.objects(name__startswith=\"guido\").first()\n assert obj is None\n\n # Test istartswith\n obj = self.Person.objects(name__istartswith=\"guido\").first()\n assert obj == person\n\n # Test endswith\n obj = self.Person.objects(name__endswith=\"Rossum\").first()\n assert obj == person\n obj = self.Person.objects(name__endswith=\"rossuM\").first()\n assert obj is None\n\n # Test iendswith\n obj = self.Person.objects(name__iendswith=\"rossuM\").first()\n assert obj == person\n\n # Test exact\n obj = self.Person.objects(name__exact=\"Guido van Rossum\").first()\n assert obj == person\n obj = self.Person.objects(name__exact=\"Guido van rossum\").first()\n assert obj is None\n obj = self.Person.objects(name__exact=\"Guido van Rossu\").first()\n assert obj is None\n\n # Test iexact\n obj = self.Person.objects(name__iexact=\"gUIDO VAN rOSSUM\").first()\n assert obj == person\n obj = self.Person.objects(name__iexact=\"gUIDO VAN rOSSU\").first()\n assert obj is None\n\n # Test wholeword\n obj = self.Person.objects(name__wholeword=\"Guido\").first()\n assert obj == person\n obj = self.Person.objects(name__wholeword=\"rossum\").first()\n assert obj is None\n obj = self.Person.objects(name__wholeword=\"Rossu\").first()\n assert obj is None\n\n # Test iwholeword\n obj = self.Person.objects(name__iwholeword=\"rOSSUM\").first()\n assert obj == person\n obj = self.Person.objects(name__iwholeword=\"rOSSU\").first()\n assert obj is None\n\n # Test regex\n obj = self.Person.objects(name__regex=\"^[Guido].*[Rossum]$\").first()\n assert obj == person\n obj = self.Person.objects(name__regex=\"^[guido].*[rossum]$\").first()\n assert obj is None\n obj = self.Person.objects(name__regex=\"^[uido].*[Rossum]$\").first()\n assert obj is None\n\n # Test iregex\n obj = self.Person.objects(name__iregex=\"^[guido].*[rossum]$\").first()\n assert obj == person\n obj = self.Person.objects(name__iregex=\"^[Uido].*[Rossum]$\").first()\n assert obj is None\n\n # Test unsafe expressions\n person = self.Person(name=\"Guido van Rossum [.'Geek']\")\n person.save()\n\n obj = self.Person.objects(name__icontains=\"[.'Geek\").first()\n assert obj == person","def test_author_many_initials(self):\n inv_search = 'author:\"bach, p* d* q*\"'\n spi_search = 'find a p d q bach'\n self._compare_searches(inv_search, spi_search)","def test_name_autocomplete_not_match(self):\n\n # Given\n\n user = self.basic_user()\n user.save()\n self.client.force_login(user, backend=None)\n\n partnership = self.basic_partnership()\n partnership.save()\n\n self.client.force_login(user, backend=None)\n\n # When\n response = self.client.get('/partnership_autocomplete/?term=test', follow=True)\n\n # Then\n self.assertNotContains(response, partnership.name)","def test_name_test_queries(self):\n url = self.get_url()\n for query in self.TEST_NAME_QUERIES.keys():\n response = self.client.get(url, {'q': query})\n returned_pks = get_autocomplete_view_ids(response)\n expected_matches = self.TEST_NAME_QUERIES[query]\n self.assertEqual(len(returned_pks), len(expected_matches),\n msg='Did not find correct number of matches for query {}'.format(query))\n # Make sure the matches found are those that are expected.\n for expected_name in expected_matches:\n name_queryset = models.Study.objects.filter(i_study_name__iregex=r'^{}$'.format(expected_name))\n self.assertEqual(name_queryset.count(), 1)\n expected_pk = name_queryset.first().pk\n self.assertIn(expected_pk, returned_pks,\n msg='Could not find expected study name {} with query {}'.format(expected_name, query))","def test_quotes(self):\n inv_search = \"title:'compton scattering' and author:mele\"\n spi_search = \"find t 'compton scattering' and a mele\"\n self._compare_searches(inv_search, spi_search)","def test_double_word_coombe_martin(self):\n result = location.lookup_location('Combe Martin GB')\n\n self.assertEqual(result['country'], 'GB')","def test_name(name):\n # To work with the name, we remove the address and then\n # split it by its blanks\n name = name.split(\",\")[0]\n name = name.split()\n # First, we check whether the fictional person is a doctor or not\n doctor = 0\n if \"Dr.\" in name:\n doctor = 1\n\n # We save the results in a list\n result = [doctor]\n # Next we look at whether the person has a double first name\n if \"-\" in name[-2]:\n result.append(1)\n else:\n result.append(0)\n\n # Next we check if the person hat a double last name.\n if \"-\" in name[-1]:\n result.append(1)\n else:\n result.append(0)\n\n # Next we check whether the person is male or female.\n first_name = name[-2]\n if result[1] == 1:\n first_name = (first_name.split(\"-\"))[-2]\n if (first_name in names.woman and \"Herr\" not in name) or \"Frau\" in name:\n result.append(\"female\")\n elif (first_name in names.man and \"Frau\" not in name) or \"Herr\" in name:\n result.append(\"male\")\n return result","def test_refersto_author_multi_name(self):\n inv_search = 'author:ellis refersto:author:\"parke, s. j.\"'\n spi_search = 'find a ellis and refersto author \"parke, s. j.\"'\n self._compare_searches(inv_search, spi_search)","def test_bad_name(self):\n\n request = service.get_request('GET', {u'taxon': u'Nosuchtaxonia'})\n x = self.start_request_tests(request)\n m = x.json().get(u'message')\n self.assertTrue(x.status_code >= 200)\n self.assertTrue('No Taxon matched\" in \"%s\"' % m)","def test_first_equal(self):\n self.assertEqual(heaviest_word(\"man i need a taxi up to ubud\"), \"taxi\")","def test_find_first_author(self):\n inv_search = 'firstauthor:ellis'\n spi_search = 'find fa ellis'\n self._compare_searches(inv_search, spi_search)","def test_email_search(self):\n # A name in the database\n search_string = \"umut@gmail.com\"\n # Search For Umut\n resp = SearchTest.client.get('/api/search/',{\"token\":SearchTest.valid_token,\"search_string\":search_string})\n search_result = json.loads(resp.content)\n # Check the e_mail field of the result\n self.assertEqual(search_string,search_result[0]['e_mail'],\"It doesn't return the user with the email {}\".format(search_string))","def test_search_regex(self):\n # search via regex emails.\n test = self.data.search(regex='[-\\w\\d.+]+@[-\\w\\d.]+', all_names=True) # noqa\n # taking out the self.assertIn until I figure out the order of the\n # tests. See test_zeditor() for more information.\n\n # self.assertIn('random@mail.com', test[0].title)\n\n # search via regex phone numbers.\n test_2 = self.data.search(regex='\\(?\\d{3}\\)?-?\\s?\\d{3}-\\d{4}',\n all_names=True)\n self.assertIn('(555) 555-3425', test_2[0].notes)","def test_author_full_first(self):\n invenio_search = 'author:\"ellis, john*\" or exactauthor:\"ellis, j *\" or exactauthor:\"ellis, j\" or exactauthor:\"ellis, jo\" or exactauthor:\"ellis, joh\" or author:\"ellis, john, *\"'\n spires_search = 'find a ellis, john'\n self._compare_searches(invenio_search, spires_search)","def test_refersto_author_multi_name_no_quotes(self):\n inv_search = 'author:ellis refersto:(author:\"parke, sj*\" or exactauthor:\"parke, s *\" or exactauthor:\"parke, s\" or author:\"parke, sj, *\")'\n spi_search = \"find a ellis and refersto author parke, sj\"\n self._compare_searches(inv_search, spi_search)","def test_matches_both_exist_and_match(self):\n eq_(None,grepit(\"foobar\",[\"oo\"],[\"fo\"]))","def test__check_invalid_nickname__valid_name(self):\n self.assertEqual(\n first=trainercode.format_trainer_code(\"111122223333\"),\n second=\"1111 2222 3333\"\n )","def testTitleTemplateFindNames(self):\n\n\t\ttests = {\n\t\t\t'${abc.def.1}-$abc-${123}': {\n\t\t\t\t'abc.def.1': ['abc', 'def', 1],\n\t\t\t\t'123': [123]\n\t\t\t},\n\t\t\t'${abc..def} $$ ${qwe}': {'qwe': ['qwe']}\n\t\t}\n\n\t\tfor test in tests:\n\t\t\tt = TitleTemplate(test)\n\t\t\tself.assertEqual(t.getFieldNames(), tests[test])","def test_guess_nutrition_by_dish_name(self):\n pass","def test_syntax_converter_expand_search_patterns_alone(self):\n spi_search = \"find t bob sam\"\n inv_search = \"title:bob and title:sam\"\n self._compare_searches(inv_search, spi_search)","def test_legal_names(self):\r\n products = generate_products()\r\n for product in products:\r\n test_adjective, test_noun = product.name.split(\"_\")\r\n self.assertIn(test_adjective, ADJECTIVES)\r\n self.assertIn(test_noun, NOUNS)","def test_field_code(self):\n inv_search = \"subject:p\"\n spi_search = \"f f p\"\n self._compare_searches(inv_search, spi_search)","def test_ms_artist_search(helpers):\n common_tests(\n MSArtist,\n MS_ARTIST_SEARCH_XML,\n MS_ARTIST_SEARCH_DICT,\n \"00020064artistsearch:Fritjof\",\n helpers,\n )","def test_titles_do_not_match(self):\r\n gm_title = 'Zhao Hua'\r\n sp_title = 'MMXXX (ft Moor Mother)'\r\n self.assertFalse(gmspotify.titles_match(gm_title, sp_title))","def test_name_test_queries(self):\n url = self.get_url()\n for query in TEST_NAME_QUERIES:\n response = self.client.get(url, {'q': query})\n returned_pks = get_autocomplete_view_ids(response)\n expected_matches = TEST_NAME_QUERIES[query]\n # Make sure number of matches is as expected.\n self.assertEqual(len(returned_pks), len(expected_matches))\n # Make sure the matches that are found are the ones expected.\n for expected_name in expected_matches:\n # This filter should only have one result, but I want to make sure.\n name_queryset = models.SourceTrait.objects.filter(i_trait_name__regex=r'^{}$'.format(expected_name))\n self.assertEqual(name_queryset.count(), 1)\n expected_pk = name_queryset.first().pk\n self.assertIn(expected_pk, returned_pks,\n msg=\"Could not find expected trait name {} with query '{}'\".format(expected_name, query))","def test_name_test_queries(self):\n url = self.get_url()\n for query in TEST_NAME_QUERIES:\n response = self.client.get(url, {'q': query})\n returned_pks = get_autocomplete_view_ids(response)\n expected_matches = TEST_NAME_QUERIES[query]\n # Make sure number of matches is as expected.\n self.assertEqual(len(returned_pks), len(expected_matches))\n # Make sure the matches that are found are the ones expected.\n for expected_name in expected_matches:\n # This filter should only have one result, but I want to make sure.\n name_queryset = models.SourceTrait.objects.filter(i_trait_name__regex=r'^{}$'.format(expected_name))\n self.assertEqual(name_queryset.count(), 1)\n expected_pk = name_queryset.first().pk\n self.assertIn(expected_pk, returned_pks,\n msg=\"Could not find expected trait name {} with query '{}'\".format(expected_name, query))","def test_name_test_queries(self):\n url = self.get_url()\n for query in TEST_NAME_QUERIES:\n response = self.client.get(url, {'q': query})\n returned_pks = get_autocomplete_view_ids(response)\n expected_matches = TEST_NAME_QUERIES[query]\n # Make sure number of matches is as expected.\n self.assertEqual(len(returned_pks), len(expected_matches))\n # Make sure the matches that are found are the ones expected.\n for expected_name in expected_matches:\n # This filter should only have one result, but I want to make sure.\n name_queryset = models.SourceTrait.objects.filter(i_trait_name__regex=r'^{}$'.format(expected_name))\n self.assertEqual(name_queryset.count(), 1)\n expected_pk = name_queryset.first().pk\n self.assertIn(expected_pk, returned_pks,\n msg=\"Could not find expected trait name {} with query '{}'\".format(expected_name, query))","def test_search(self):\n\n with self.client as c:\n response = c.get(\"/users?q=al\")\n data = str(response.data)\n\n self.assertIn(\"@alice\", data)\n self.assertIn(\"@alvin\", data)\n\n self.assertNotIn(\"@bob\", data)\n self.assertNotIn(\"@carl\", data)","def test_absorbs_naked_author_search(self):\n invenio_search = \"author:ellis\"\n spi_search = \"author ellis\"\n self._compare_searches(invenio_search, spi_search)","def testMclCreatorSearch(self):\n driver = self.driver\n #finds the Creator filed and selects the option 'shinichi Aizawa'(string:4811539), tabs out of the field then clicks the Search button\n Select(driver.find_element(By.ID, \"creator\")).select_by_value('string:4811539')\n time.sleep(2)\n actions = ActionChains(driver) \n actions.send_keys(Keys.TAB)\n actions.perform()\n time.sleep(2)\n driver.find_element(By.ID, 'searchButton').click()\n time.sleep(2)\n #find the search results table\n results_table = self.driver.find_element(By.ID, \"resultsTable\")\n table = Table(results_table)\n #Iterate and print the search results headers\n cell1 = table.get_row_cells(0)\n symbol1 = iterate.getTextAsList(cell1)\n print(symbol1)\n #Assert the correct mutant cell line is returned\n self.assertEqual(symbol1, ['PAT-12'])","def test_get_filter_results_name_includes(self):\r\n\r\n data_file = open('data.txt', 'r')\r\n twitter_dict = tf.process_data(data_file)\r\n data_file.close()\r\n\r\n actual = tf.get_filter_results(twitter_dict, ['tomCruise', \\\r\n 'PerezHilton'], {'name_includes': 'tomCruise'})\r\n expected = ['tomCruise']\r\n self.assertEqual(actual, expected)","def test_spires_syntax_trailing_colon(self):\n spi_search = \"find a watanabe:\"\n invenio_search = \"author:watanabe:\"\n self._compare_searches(invenio_search, spi_search)","def lookup(name, phonebook):\n\n phonebook_data = read_phonebook(phonebook)\n\n match = False\n for entry_name in phonebook_data:\n if name.lower() in entry_name.lower():\n match = True\n print entry_name, phonebook_data[entry_name]\n\n if not match:\n print \"No matches found.\"","def test_name(self, parse_input):\n bb = parse_input(\"name testname\\nversion 1.0\")\n assert bb.name == \"testname\"","def name_search(self, search):\n if isinstance(search, str):\n name_re = re.compile(search)\n else:\n name_re = search\n matches = [\n entry\n for entry in self\n if entry is not None and name_re.search(entry.name)\n ]\n return matches","def test_search(self):\n pass","def test_search(self):\n pass","def test_search(self):\n pass","def test_syntax_converter_expand_search_patterns_conjoined(self):\n spi_search = \"find t bob and sam\"\n inv_search = \"title:bob and title:sam\"\n self._compare_searches(inv_search, spi_search)","def test_search_len(self):\n self.assertEquals(len(self.t['My Name Is Earl'].search('Faked His Own Death')), 1)","def test_search_key_phrase(self):\n # search via key phrase.\n test = self.data.search(key_phrase='testing entries.', all_names=True)\n self.assertIn('testing entries.', test[0].notes)","def test_check_name_is_3_parts():\n check_name_length()","def test_search_employee_text_finds_matching_employees(self):\n # add some employees to the database\n test_pattern = 'foo'\n test_employees = [\n {'id': 1, 'name': \"Test Employee 1 foo\"},\n {'id': 2, 'name': \"Test Employee 2 foo\"},\n {'id': 3, 'name': \"Test Employee 3 bar\"},\n ]\n for employee in test_employees:\n e = db_manager.Employee.get_or_create(name=employee['name'])\n db_manager.LogEntry.create(\n employee=e[0],\n date=datetime.date(2018, 1, 2),\n task_name='Test task {}'.format(employee['id']),\n duration=employee['id'],\n notes='Note')\n\n title = \"FIND EMPLOYEE NAME USING TEXT STRING\" + \"\\n\"\n subtitle = \"Enter the text string to search on\" + \"\\n\"\n employee_rows = \"\"\n for employee in test_employees:\n if test_pattern in employee['name']:\n employee_rows += \"{}) {}\\n\".format(employee['id'],\n employee['name'])\n\n expected_output = (title +\n subtitle +\n employee_rows)\n\n # Create a StringIO object to be a capture object\n captured_output = io.StringIO()\n # point stdout at the capture object\n sys.stdout = captured_output\n # Do anything that's going to have a print statement\n # (these will be accumulated in the captured_output object)\n example_input = [test_pattern, '1']\n with patch('builtins.input', side_effect=example_input):\n self.menu.search_employee_text()\n\n # Revert stdout (captured_output still holds the captured items)\n sys.stdout = sys.__stdout__\n # Do any other test code (e.g., asserts)\n self.assertEqual(expected_output, captured_output.getvalue())"],"string":"[\n \"def test_search_checkname(self):\\n self.assertEquals(self.t['Scrubs'].search('my first')[0]['episodename'], 'My First Day')\\n self.assertEquals(self.t['My Name Is Earl'].search('Faked His Own Death')[0]['episodename'], 'Faked His Own Death')\",\n \"def test_name(self):\\n\\n self.check_search(\\n dict(name=u'flamethrower'),\\n [u'Flamethrower'],\\n 'searching by name',\\n exact=True,\\n )\\n\\n self.check_search(\\n dict(name=u'durp'),\\n [],\\n 'searching for a nonexistent name',\\n exact=True,\\n )\\n\\n self.check_search(\\n dict(name=u'quICk AttACk'),\\n [u'Quick Attack'],\\n 'case is ignored',\\n exact=True,\\n )\\n\\n self.check_search(\\n dict(name=u'thunder'),\\n [ u'Thunder', u'Thunderbolt', u'Thunder Wave',\\n u'ThunderShock', u'ThunderPunch', u'Thunder Fang'],\\n 'no wildcards is treated as substring',\\n exact=True,\\n )\\n self.check_search(\\n dict(name=u'*under'),\\n [u'Thunder'], # not ThunderShock, etc.!\\n 'splat wildcard works and is not used as substring',\\n exact=True,\\n )\\n self.check_search(\\n dict(name=u'b?te'),\\n [u'Bite'], # not Bug Bite!\\n 'question wildcard works and is not used as substring',\\n exact=True,\\n )\",\n \"def test_name_search(self):\\n # A name in the database\\n search_string = \\\"Umut\\\"\\n # Search For Umut\\n resp = SearchTest.client.get('/api/search/',{\\\"token\\\":SearchTest.valid_token,\\\"search_string\\\":search_string})\\n search_result = json.loads(resp.content)\\n # Check the name field of the result\\n self.assertEqual(search_string,search_result[0]['name'],\\\"It doesn't return the user with the name {}\\\".format(search_string))\",\n \"def test_name_autocomplete_match(self):\\n\\n # Given\\n user = self.basic_user()\\n user.save()\\n self.client.force_login(user, backend=None)\\n\\n partnership_1 = self.basic_partnership()\\n partnership_1.save()\\n\\n partnership_2 = self.basic_partnership()\\n partnership_2.name = \\\"bla\\\"\\n partnership_2.save()\\n\\n # When\\n response = self.client.get('/partnership_autocomplete/?term=exa', follow=True)\\n\\n # Then\\n self.assertContains(response, partnership_1.name, count=1)\",\n \"def test_legal_names(self):\\n prods = generate_products()\\n for obj in prods:\\n self.assertRegexpMatches(\\n '(\\\\w{2,10} \\\\w{0,12}|\\\\?{0,3}){1}', obj.name)\",\n \"def test_first_last_middle_name(self):\\n\\t\\tformatted_name = get_formatted_name('Wolfgang','mozart','amadues')\\n\\t\\tself.assertEqual(formatted_name,'Wolfgang Amadues Mozart')\",\n \"def test_name_returner(self):\\n test = self.data.name_returner()\\n self.assertIn(('Trevor', 'Harvey'), test)\\n self.assertIn(('Nik', 'Silver'), test)\",\n \"def test_names():\\n first = get_name(\\\"As\\\")\\n assert first == \\\"Arsenic\\\"\\n\\n second = get_name(\\\"Be\\\")\\n assert second == \\\"Beryllium\\\"\\n\\n third = get_name(\\\"Li\\\")\\n assert third == \\\"Lithium\\\"\",\n \"def test_search_show(self):\\n self.assertEquals(\\n len(self.t['life on mars'].search('the', key='episodename')),\\n 10\\n )\",\n \"def test_three(self):\\n name = get_formatted_name('david', 'malan', 'j')\\n self.assertEqual(name, 'David J Malan')\",\n \"def test_get_by_name1(self):\\n pass\",\n \"def test_legal_names(self):\\n test_list = generate_products()\\n names_list = []\\n for i in test_list:\\n names_list.append(i[0])\\n for name in names_list:\\n nameparts = name.split()\\n self.assertEqual(len(nameparts), 2,\\n msg=\\\"missing noun, space, or adj\\\")\\n the_adj = nameparts[0]\\n self.assertIn(the_adj, ADJECTIVES, msg='Bad Adj')\\n the_noun = nameparts[1]\\n self.assertIn(the_noun, NOUNS, msg='Bad Noun')\",\n \"def test_legal_names(self):\\n names = [prod.name for prod in generate_products()]\\n sep = [(name.split()[0], name.split()[1]) for name in names]\\n for name in sep:\\n self.assertIn(name[0], ADJS)\\n self.assertIn(name[1], NOUNS)\",\n \"def test_search_with_space(self):\\n # Create a group to test searching for groups\\n Group.objects.create(name='spam', auto_complete=True)\\n Group.objects.create(name='jam', auto_complete=True)\\n Group.objects.create(name='bread', auto_complete=True)\\n\\n url = reverse('search')\\n response = self.mozillian_client.get(url, {'q': 'am'})\\n\\n eq_(response.status_code, 200)\\n\\n queryset = response.context['people'].object_list\\n for up in [self.mozillian.userprofile, self.mozillian2.userprofile]:\\n self.assertTrue(up in queryset)\\n\\n # Assert appropriate group names are found in the document\\n self.assertContains(response, 'spam')\\n self.assertContains(response, 'jam')\\n self.assertNotContains(response, 'bread')\",\n \"def test_search_in_name(self, es_with_collector, name_term, matched_company_name):\\n CompanyFactory(\\n name='whiskers and tabby',\\n trading_names=['Maine Coon', 'Egyptian Mau'],\\n )\\n CompanyFactory(\\n name='1a',\\n trading_names=['3a', '4a'],\\n )\\n es_with_collector.flush_and_refresh()\\n\\n url = reverse('api-v3:search:basic')\\n response = self.api_client.get(\\n url,\\n data={\\n 'term': name_term,\\n 'entity': 'company',\\n },\\n )\\n\\n match = Company.objects.filter(name=matched_company_name).first()\\n if match:\\n assert response.data['count'] == 1\\n assert len(response.data['results']) == 1\\n assert response.data['results'][0]['id'] == str(match.id)\\n assert [{'count': 1, 'entity': 'company'}] == response.data['aggregations']\\n else:\\n assert response.data['count'] == 0\\n assert len(response.data['results']) == 0\",\n \"def test_first_last_middle_name(self):\\n formatted_name = get_formatted_name('wolfgang', 'mozart', 'amadeus')\\n self.assertEqual(formatted_name, 'Wolfgang Amadeus Mozart')\",\n \"def test_first_last_middle_name(self):\\n formatted_name = get_formatted_name('wolfgang', 'mozart', 'amadeus')\\n self.assertEqual(formatted_name, 'Wolfgang Amadeus Mozart')\",\n \"def test_first_last_name(self):\\n formatted_name = get_formatted_name('jimi', 'hendrix')\\n self.assertEqual(formatted_name, 'Jimi Hendrix')\",\n \"def test_first_last(self):\\n\\n full_name = get_full_name(\\\"pony\\\", \\\"cat\\\")\\n self.assertEqual(full_name, \\\"Pony Cat\\\")\\n\\n full_name = get_full_name(\\\"goat\\\", \\\"cat\\\")\\n self.assertEqual(full_name, \\\"Goat Cat\\\")\",\n \"def test_first_name(self) :\\n\\t\\tformatted_name = get_formatted_name('janis','joplin')\\n\\t\\tself.assertEqual(formatted_name,'Janis Joplin')\",\n \"def test_first_last_middle(self):\\n\\n full_name = get_full_name(\\\"pony\\\", \\\"cat\\\", \\\"sweetie\\\")\\n self.assertEqual(full_name, \\\"Pony Sweetie Cat\\\")\\n\\n full_name = get_full_name(\\\"goat\\\", \\\"cat\\\", \\\"studman\\\")\\n self.assertEqual(full_name, \\\"Goat Studman Cat\\\")\",\n \"def test_get_by_name2(self):\\n pass\",\n \"def exact_name_check(name_to_test, parts):\\n\\n if parts is None:\\n return 0\\n\\n if type(name_to_test) is not str:\\n return 0\\n\\n\\n for p in sorted(parts, key=len, reverse=True):\\n name_to_test = name_to_test.replace(p, '', 1)\\n if name_to_test == '':\\n return 1\\n return 0\",\n \"def test_first_last_middle_name(self):\\n formatted_name = get_formatted_name('marie', 'curie', 'francis')\\n self.assertEqual(formatted_name, 'Marie Francis Curie')\",\n \"def test_author_many_lastnames(self):\\n inv_search = 'author:\\\"alvarez gaume, j* r* r*\\\"'\\n spi_search = 'find a alvarez gaume, j r r'\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_first_last(self):\\r\\n full_name = get_full_name('janis','joplin')\\r\\n # expected value\\r\\n self.assertEqual(full_name,'Janis Joplin')\",\n \"def search(self, word):\",\n \"def test_job_title(self):\\n inv_search = 'title:engineer not title:programmer'\\n spi_search = 'find job engineer not position programmer'\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_legal_names(self):\\n adjectives = ['Awesome', 'Shiny', 'Impressive', 'Portable', 'Improved']\\n nouns = ['Anvil', 'Catapult' 'Disguise' 'Mousetrap', '???']\\n products = acme_report.generate_products()\\n for prod in range(len(products)):\\n prod_name = products[prod].name\\n name_split = prod_name.split()\\n self.assertIn(name_split[0], adjectives)\\n self.assertIn(name_split[1], nouns)\",\n \"def test_05_get_person_by_name(self):\\n p1 = Person.query.first()\\n p1_data = p1.wrap()\\n p1_f_name = p1_data[\\\"first_name\\\"]\\n # find by first name only\\n # get part of name and search\\n q_string = \\\"?first_name={}\\\".format(p1_f_name[:3]) # TODO - verify the length\\n rv = self.app.get('persons', query_string=q_string)\\n data = json.loads(rv.data)\\n self.assertEqual(data[\\\"count\\\"], 1)\\n\\n # find by first name and last name\\n p1_l_name = p1_data[\\\"last_name\\\"]\\n q_string = \\\"?first_name={}&last_name={}\\\".format(p1_f_name[:3], p1_l_name)\\n rv = self.app.get('persons', query_string=q_string)\\n data = json.loads(rv.data)\\n self.assertEqual(data[\\\"count\\\"], 1)\\n\\n # find by first name and non-existing last name\\n q_string = \\\"?first_name={}&last_name={}\\\".format(p1_f_name[:3], \\\"iAmNotThere\\\")\\n rv = self.app.get('persons', query_string=q_string)\\n data = json.loads(rv.data)\\n self.assertEqual(data[\\\"count\\\"], 0)\",\n \"def test_first_last_name(self):\\n formatted_name = get_formatted_name('david', 'Malan')\\n self.assertEqual(formatted_name, 'David Malan')\",\n \"def test_legal_names(self):\\r\\n prod = generate_products()\\r\\n ADJECTIVES = ['Awesome', 'Shiny', 'Impressive', 'Portable', 'Improved']\\r\\n NOUNS = ['Anvil', 'Catapult', 'Disguise', 'Mousetrap', '???']\\r\\n for product in prod:\\r\\n self.assertIn(product.name.split(\\\" \\\")[0], ADJECTIVES)\\r\\n self.assertIn(product.name.split(\\\" \\\")[1], NOUNS)\",\n \"def test_first_last_name(self):\\n formatted_name = get_formatted_name('janis', 'joplin')\\n self.assertEqual(formatted_name, 'Janis Joplin')\",\n \"def test_first_last_name(self):\\n formatted_name = get_formatted_name('janis', 'joplin')\\n self.assertEqual(formatted_name, 'Janis Joplin')\",\n \"def test_first_last_name(self):\\n\\t\\tformatted_name = get_formatted_name('janos', 'jk')\\n\\t\\tself.assertEqual(formatted_name, 'Janos Jk')\",\n \"def test_first_last_middle_name(self):\\n formatted_name = get_formatted_name('john', 'smith', 'billy')\\n self.assertEqual(formatted_name, 'John Billy Smith')\",\n \"def test_full_name(self):\\n self.assertEqual(self.john.full_name, \\\"John Doe\\\")\\n self.assertEqual(self.solar.full_name, \\\"Nathan Graule\\\")\",\n \"def substring_match(recipe, word):\\n if names_only:\\n line = recipe.name\\n else:\\n line = str(recipe)\\n\\n if not case:\\n word = word.lower()\\n line = line.lower()\\n\\n return line.find(word) != -1\",\n \"def test_super_short_author_name(self):\\n spi_search = \\\"fin a er and cn cms\\\"\\n inv_search = \\\"author:er collaboration:cms\\\"\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_semantic_search(self):\\n # A name in the database\\n search_string = \\\"football\\\"\\n # Search For Umut\\n resp = SearchTest.client.get('/api/search/',{\\\"token\\\":SearchTest.valid_token,\\\"search_string\\\":search_string})\\n search_result = json.loads(resp.content)\\n # Umut must be in the results because basketball and football are semanticly related\\n self.assertEqual(\\\"Umut\\\",search_result[0]['name'],\\\"Semantic Search functionality doesn't work.\\\")\",\n \"def test_legal_names(self):\\n product_list = generate_products()\\n for prod in product_list:\\n noun = prod.name.split(\\\" \\\")[1]\\n adjective = prod.name.split(\\\" \\\")[0]\\n self.assertIn(noun, NOUNS)\\n self.assertIn(adjective, ADJECTIVES)\",\n \"def match_specific_name(name: str, specific_names: list) -> str:\\n c = clean_specific_name(name)\\n if c == \\\"\\\":\\n return c\\n else:\\n y = \\\"\\\"\\n for x in specific_names:\\n matchlist = x.variations.split(\\\";\\\")\\n if c in matchlist:\\n y = x.name\\n return y\",\n \"def test_name_field(self):\\n field = self.record.find('field[@name=\\\\'name\\\\']')\\n self.assertEqual(field.text, 'GUH-ADT', 'Incorrect Name Field')\",\n \"def test_legal_names(self):\\n products = generate_products()\\n\\n for product in products:\\n names = product.name.split(\\\" \\\")\\n self.assertIn(names[0], ADJECTIVES)\\n self.assertIn(names[1], NOUNS)\",\n \"def test_first_last_name(self):\\n formatted_name = get_formatted_name('janis', 'joplin')\\n # Asserting that formatted_name equals 'Janis Joplin'\\n self.assertEqual(formatted_name, 'Janis Joplin')\",\n \"def __find_string_in_response(self, fullResponse, searchFor):\\n check = True\\n rawResponse = fullResponse;\\n if \\\"result\\\" not in rawResponse.text:\\n check = False\\n else:\\n responseJSON = rawResponse.json()\\n length_responseJSON = len(responseJSON[\\\"result\\\"])\\n for i in range(0,length_responseJSON,1):\\n check = searchFor in responseJSON[\\\"result\\\"][i][\\\"first_name\\\"]\\n if check == False:\\n return check\\n return check\",\n \"def test_title(names):\",\n \"def test_reformatted_full_name():\\n assert reformatted_full_name(\\\"\\\") == \\\"\\\"\\n assert reformatted_full_name(\\\"George\\\") == \\\"george\\\"\\n assert reformatted_full_name(\\\"X Y Z A B\\\") == \\\"x b\\\"\",\n \"def test_name_test_queries(self):\\n url = self.get_url()\\n for query in TEST_NAME_QUERIES:\\n response = self.client.get(url, {'q': query})\\n returned_pks = get_autocomplete_view_ids(response)\\n expected_matches = TEST_NAME_QUERIES[query]\\n # Make sure number of matches is as expected.\\n self.assertEqual(len(returned_pks), len(expected_matches))\\n # Make sure the matches that are found are the ones expected.\\n for expected_name in expected_matches:\\n # This filter should only have one result, but I want to make sure.\\n name_qs = models.HarmonizedTrait.objects.filter(i_trait_name__regex=r'^{}$'.format(expected_name))\\n self.assertEqual(name_qs.count(), 1)\\n expected_pk = name_qs.first().pk\\n self.assertIn(expected_pk, returned_pks,\\n msg=\\\"Could not find expected trait name {} with query '{}'\\\".format(expected_name, query))\",\n \"def test_short_full_name(self):\\n self.assertEqual(self.john.full_name_short, \\\"J. Doe\\\")\\n self.assertEqual(self.solar.full_name_short, \\\"N. Graule\\\")\",\n \"def find_names(s):\\n \\\"*** YOUR CODE HERE ***\\\"\",\n \"def test_bnd_mate_name():\\n\\n mate = bnd_mate_name(ALT, \\\"2\\\")\\n assert mate == \\\"17\\\"\",\n \"def test_author_full_initial(self):\\n inv_search = 'author:\\\"klebanov, ig* r*\\\" or exactauthor:\\\"klebanov, i r\\\"'\\n spi_search = \\\"find a klebanov, ig.r.\\\"\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_legal_names(self):\\n names = [i[0] for i in generate_products()]\\n\\n for n in names:\\n name = str(n).split()\\n name1 = name[0]\\n name2 = name[1]\\n self.assertIn(name1, ADJECTIVES)\\n self.assertIn(name2, NOUNS)\",\n \"def test_name_matching(string, matches: bool):\\n assert (re.fullmatch(pattern, string) is not None) == matches\",\n \"def test_find_word(self):\\n self.assertEqual(find_word('GREEN'), [(1, 1), (1, 1), (0, 9)])\\n self.assertEqual(find_word('ABSENT'), [])\\n self.assertEqual(find_word('PW'), [(1, 7), (3, 7), (0, 8)])\",\n \"def test_special_characters_business_name(self):\\n user = \\\"chairman\\\"\\n msg = self.business_item_class.create_business(\\\"Ma@en_deleo\\\", user, \\\"soft*%ware\\\", \\\"nairo@&\\\")\\n print(msg)\\n self.assertEqual(msg, {\\\"message\\\":\\\"Business name should not contain special characters\\\"})\",\n \"def test_regex_query_shortcuts(self):\\n person = self.Person(name=\\\"Guido van Rossum\\\")\\n person.save()\\n\\n # Test contains\\n obj = self.Person.objects(name__contains=\\\"van\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__contains=\\\"Van\\\").first()\\n assert obj is None\\n\\n # Test icontains\\n obj = self.Person.objects(name__icontains=\\\"Van\\\").first()\\n assert obj == person\\n\\n # Test startswith\\n obj = self.Person.objects(name__startswith=\\\"Guido\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__startswith=\\\"guido\\\").first()\\n assert obj is None\\n\\n # Test istartswith\\n obj = self.Person.objects(name__istartswith=\\\"guido\\\").first()\\n assert obj == person\\n\\n # Test endswith\\n obj = self.Person.objects(name__endswith=\\\"Rossum\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__endswith=\\\"rossuM\\\").first()\\n assert obj is None\\n\\n # Test iendswith\\n obj = self.Person.objects(name__iendswith=\\\"rossuM\\\").first()\\n assert obj == person\\n\\n # Test exact\\n obj = self.Person.objects(name__exact=\\\"Guido van Rossum\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__exact=\\\"Guido van rossum\\\").first()\\n assert obj is None\\n obj = self.Person.objects(name__exact=\\\"Guido van Rossu\\\").first()\\n assert obj is None\\n\\n # Test iexact\\n obj = self.Person.objects(name__iexact=\\\"gUIDO VAN rOSSUM\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__iexact=\\\"gUIDO VAN rOSSU\\\").first()\\n assert obj is None\\n\\n # Test wholeword\\n obj = self.Person.objects(name__wholeword=\\\"Guido\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__wholeword=\\\"rossum\\\").first()\\n assert obj is None\\n obj = self.Person.objects(name__wholeword=\\\"Rossu\\\").first()\\n assert obj is None\\n\\n # Test iwholeword\\n obj = self.Person.objects(name__iwholeword=\\\"rOSSUM\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__iwholeword=\\\"rOSSU\\\").first()\\n assert obj is None\\n\\n # Test regex\\n obj = self.Person.objects(name__regex=\\\"^[Guido].*[Rossum]$\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__regex=\\\"^[guido].*[rossum]$\\\").first()\\n assert obj is None\\n obj = self.Person.objects(name__regex=\\\"^[uido].*[Rossum]$\\\").first()\\n assert obj is None\\n\\n # Test iregex\\n obj = self.Person.objects(name__iregex=\\\"^[guido].*[rossum]$\\\").first()\\n assert obj == person\\n obj = self.Person.objects(name__iregex=\\\"^[Uido].*[Rossum]$\\\").first()\\n assert obj is None\\n\\n # Test unsafe expressions\\n person = self.Person(name=\\\"Guido van Rossum [.'Geek']\\\")\\n person.save()\\n\\n obj = self.Person.objects(name__icontains=\\\"[.'Geek\\\").first()\\n assert obj == person\",\n \"def test_author_many_initials(self):\\n inv_search = 'author:\\\"bach, p* d* q*\\\"'\\n spi_search = 'find a p d q bach'\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_name_autocomplete_not_match(self):\\n\\n # Given\\n\\n user = self.basic_user()\\n user.save()\\n self.client.force_login(user, backend=None)\\n\\n partnership = self.basic_partnership()\\n partnership.save()\\n\\n self.client.force_login(user, backend=None)\\n\\n # When\\n response = self.client.get('/partnership_autocomplete/?term=test', follow=True)\\n\\n # Then\\n self.assertNotContains(response, partnership.name)\",\n \"def test_name_test_queries(self):\\n url = self.get_url()\\n for query in self.TEST_NAME_QUERIES.keys():\\n response = self.client.get(url, {'q': query})\\n returned_pks = get_autocomplete_view_ids(response)\\n expected_matches = self.TEST_NAME_QUERIES[query]\\n self.assertEqual(len(returned_pks), len(expected_matches),\\n msg='Did not find correct number of matches for query {}'.format(query))\\n # Make sure the matches found are those that are expected.\\n for expected_name in expected_matches:\\n name_queryset = models.Study.objects.filter(i_study_name__iregex=r'^{}$'.format(expected_name))\\n self.assertEqual(name_queryset.count(), 1)\\n expected_pk = name_queryset.first().pk\\n self.assertIn(expected_pk, returned_pks,\\n msg='Could not find expected study name {} with query {}'.format(expected_name, query))\",\n \"def test_quotes(self):\\n inv_search = \\\"title:'compton scattering' and author:mele\\\"\\n spi_search = \\\"find t 'compton scattering' and a mele\\\"\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_double_word_coombe_martin(self):\\n result = location.lookup_location('Combe Martin GB')\\n\\n self.assertEqual(result['country'], 'GB')\",\n \"def test_name(name):\\n # To work with the name, we remove the address and then\\n # split it by its blanks\\n name = name.split(\\\",\\\")[0]\\n name = name.split()\\n # First, we check whether the fictional person is a doctor or not\\n doctor = 0\\n if \\\"Dr.\\\" in name:\\n doctor = 1\\n\\n # We save the results in a list\\n result = [doctor]\\n # Next we look at whether the person has a double first name\\n if \\\"-\\\" in name[-2]:\\n result.append(1)\\n else:\\n result.append(0)\\n\\n # Next we check if the person hat a double last name.\\n if \\\"-\\\" in name[-1]:\\n result.append(1)\\n else:\\n result.append(0)\\n\\n # Next we check whether the person is male or female.\\n first_name = name[-2]\\n if result[1] == 1:\\n first_name = (first_name.split(\\\"-\\\"))[-2]\\n if (first_name in names.woman and \\\"Herr\\\" not in name) or \\\"Frau\\\" in name:\\n result.append(\\\"female\\\")\\n elif (first_name in names.man and \\\"Frau\\\" not in name) or \\\"Herr\\\" in name:\\n result.append(\\\"male\\\")\\n return result\",\n \"def test_refersto_author_multi_name(self):\\n inv_search = 'author:ellis refersto:author:\\\"parke, s. j.\\\"'\\n spi_search = 'find a ellis and refersto author \\\"parke, s. j.\\\"'\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_bad_name(self):\\n\\n request = service.get_request('GET', {u'taxon': u'Nosuchtaxonia'})\\n x = self.start_request_tests(request)\\n m = x.json().get(u'message')\\n self.assertTrue(x.status_code >= 200)\\n self.assertTrue('No Taxon matched\\\" in \\\"%s\\\"' % m)\",\n \"def test_first_equal(self):\\n self.assertEqual(heaviest_word(\\\"man i need a taxi up to ubud\\\"), \\\"taxi\\\")\",\n \"def test_find_first_author(self):\\n inv_search = 'firstauthor:ellis'\\n spi_search = 'find fa ellis'\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_email_search(self):\\n # A name in the database\\n search_string = \\\"umut@gmail.com\\\"\\n # Search For Umut\\n resp = SearchTest.client.get('/api/search/',{\\\"token\\\":SearchTest.valid_token,\\\"search_string\\\":search_string})\\n search_result = json.loads(resp.content)\\n # Check the e_mail field of the result\\n self.assertEqual(search_string,search_result[0]['e_mail'],\\\"It doesn't return the user with the email {}\\\".format(search_string))\",\n \"def test_search_regex(self):\\n # search via regex emails.\\n test = self.data.search(regex='[-\\\\w\\\\d.+]+@[-\\\\w\\\\d.]+', all_names=True) # noqa\\n # taking out the self.assertIn until I figure out the order of the\\n # tests. See test_zeditor() for more information.\\n\\n # self.assertIn('random@mail.com', test[0].title)\\n\\n # search via regex phone numbers.\\n test_2 = self.data.search(regex='\\\\(?\\\\d{3}\\\\)?-?\\\\s?\\\\d{3}-\\\\d{4}',\\n all_names=True)\\n self.assertIn('(555) 555-3425', test_2[0].notes)\",\n \"def test_author_full_first(self):\\n invenio_search = 'author:\\\"ellis, john*\\\" or exactauthor:\\\"ellis, j *\\\" or exactauthor:\\\"ellis, j\\\" or exactauthor:\\\"ellis, jo\\\" or exactauthor:\\\"ellis, joh\\\" or author:\\\"ellis, john, *\\\"'\\n spires_search = 'find a ellis, john'\\n self._compare_searches(invenio_search, spires_search)\",\n \"def test_refersto_author_multi_name_no_quotes(self):\\n inv_search = 'author:ellis refersto:(author:\\\"parke, sj*\\\" or exactauthor:\\\"parke, s *\\\" or exactauthor:\\\"parke, s\\\" or author:\\\"parke, sj, *\\\")'\\n spi_search = \\\"find a ellis and refersto author parke, sj\\\"\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_matches_both_exist_and_match(self):\\n eq_(None,grepit(\\\"foobar\\\",[\\\"oo\\\"],[\\\"fo\\\"]))\",\n \"def test__check_invalid_nickname__valid_name(self):\\n self.assertEqual(\\n first=trainercode.format_trainer_code(\\\"111122223333\\\"),\\n second=\\\"1111 2222 3333\\\"\\n )\",\n \"def testTitleTemplateFindNames(self):\\n\\n\\t\\ttests = {\\n\\t\\t\\t'${abc.def.1}-$abc-${123}': {\\n\\t\\t\\t\\t'abc.def.1': ['abc', 'def', 1],\\n\\t\\t\\t\\t'123': [123]\\n\\t\\t\\t},\\n\\t\\t\\t'${abc..def} $$ ${qwe}': {'qwe': ['qwe']}\\n\\t\\t}\\n\\n\\t\\tfor test in tests:\\n\\t\\t\\tt = TitleTemplate(test)\\n\\t\\t\\tself.assertEqual(t.getFieldNames(), tests[test])\",\n \"def test_guess_nutrition_by_dish_name(self):\\n pass\",\n \"def test_syntax_converter_expand_search_patterns_alone(self):\\n spi_search = \\\"find t bob sam\\\"\\n inv_search = \\\"title:bob and title:sam\\\"\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_legal_names(self):\\r\\n products = generate_products()\\r\\n for product in products:\\r\\n test_adjective, test_noun = product.name.split(\\\"_\\\")\\r\\n self.assertIn(test_adjective, ADJECTIVES)\\r\\n self.assertIn(test_noun, NOUNS)\",\n \"def test_field_code(self):\\n inv_search = \\\"subject:p\\\"\\n spi_search = \\\"f f p\\\"\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_ms_artist_search(helpers):\\n common_tests(\\n MSArtist,\\n MS_ARTIST_SEARCH_XML,\\n MS_ARTIST_SEARCH_DICT,\\n \\\"00020064artistsearch:Fritjof\\\",\\n helpers,\\n )\",\n \"def test_titles_do_not_match(self):\\r\\n gm_title = 'Zhao Hua'\\r\\n sp_title = 'MMXXX (ft Moor Mother)'\\r\\n self.assertFalse(gmspotify.titles_match(gm_title, sp_title))\",\n \"def test_name_test_queries(self):\\n url = self.get_url()\\n for query in TEST_NAME_QUERIES:\\n response = self.client.get(url, {'q': query})\\n returned_pks = get_autocomplete_view_ids(response)\\n expected_matches = TEST_NAME_QUERIES[query]\\n # Make sure number of matches is as expected.\\n self.assertEqual(len(returned_pks), len(expected_matches))\\n # Make sure the matches that are found are the ones expected.\\n for expected_name in expected_matches:\\n # This filter should only have one result, but I want to make sure.\\n name_queryset = models.SourceTrait.objects.filter(i_trait_name__regex=r'^{}$'.format(expected_name))\\n self.assertEqual(name_queryset.count(), 1)\\n expected_pk = name_queryset.first().pk\\n self.assertIn(expected_pk, returned_pks,\\n msg=\\\"Could not find expected trait name {} with query '{}'\\\".format(expected_name, query))\",\n \"def test_name_test_queries(self):\\n url = self.get_url()\\n for query in TEST_NAME_QUERIES:\\n response = self.client.get(url, {'q': query})\\n returned_pks = get_autocomplete_view_ids(response)\\n expected_matches = TEST_NAME_QUERIES[query]\\n # Make sure number of matches is as expected.\\n self.assertEqual(len(returned_pks), len(expected_matches))\\n # Make sure the matches that are found are the ones expected.\\n for expected_name in expected_matches:\\n # This filter should only have one result, but I want to make sure.\\n name_queryset = models.SourceTrait.objects.filter(i_trait_name__regex=r'^{}$'.format(expected_name))\\n self.assertEqual(name_queryset.count(), 1)\\n expected_pk = name_queryset.first().pk\\n self.assertIn(expected_pk, returned_pks,\\n msg=\\\"Could not find expected trait name {} with query '{}'\\\".format(expected_name, query))\",\n \"def test_name_test_queries(self):\\n url = self.get_url()\\n for query in TEST_NAME_QUERIES:\\n response = self.client.get(url, {'q': query})\\n returned_pks = get_autocomplete_view_ids(response)\\n expected_matches = TEST_NAME_QUERIES[query]\\n # Make sure number of matches is as expected.\\n self.assertEqual(len(returned_pks), len(expected_matches))\\n # Make sure the matches that are found are the ones expected.\\n for expected_name in expected_matches:\\n # This filter should only have one result, but I want to make sure.\\n name_queryset = models.SourceTrait.objects.filter(i_trait_name__regex=r'^{}$'.format(expected_name))\\n self.assertEqual(name_queryset.count(), 1)\\n expected_pk = name_queryset.first().pk\\n self.assertIn(expected_pk, returned_pks,\\n msg=\\\"Could not find expected trait name {} with query '{}'\\\".format(expected_name, query))\",\n \"def test_search(self):\\n\\n with self.client as c:\\n response = c.get(\\\"/users?q=al\\\")\\n data = str(response.data)\\n\\n self.assertIn(\\\"@alice\\\", data)\\n self.assertIn(\\\"@alvin\\\", data)\\n\\n self.assertNotIn(\\\"@bob\\\", data)\\n self.assertNotIn(\\\"@carl\\\", data)\",\n \"def test_absorbs_naked_author_search(self):\\n invenio_search = \\\"author:ellis\\\"\\n spi_search = \\\"author ellis\\\"\\n self._compare_searches(invenio_search, spi_search)\",\n \"def testMclCreatorSearch(self):\\n driver = self.driver\\n #finds the Creator filed and selects the option 'shinichi Aizawa'(string:4811539), tabs out of the field then clicks the Search button\\n Select(driver.find_element(By.ID, \\\"creator\\\")).select_by_value('string:4811539')\\n time.sleep(2)\\n actions = ActionChains(driver) \\n actions.send_keys(Keys.TAB)\\n actions.perform()\\n time.sleep(2)\\n driver.find_element(By.ID, 'searchButton').click()\\n time.sleep(2)\\n #find the search results table\\n results_table = self.driver.find_element(By.ID, \\\"resultsTable\\\")\\n table = Table(results_table)\\n #Iterate and print the search results headers\\n cell1 = table.get_row_cells(0)\\n symbol1 = iterate.getTextAsList(cell1)\\n print(symbol1)\\n #Assert the correct mutant cell line is returned\\n self.assertEqual(symbol1, ['PAT-12'])\",\n \"def test_get_filter_results_name_includes(self):\\r\\n\\r\\n data_file = open('data.txt', 'r')\\r\\n twitter_dict = tf.process_data(data_file)\\r\\n data_file.close()\\r\\n\\r\\n actual = tf.get_filter_results(twitter_dict, ['tomCruise', \\\\\\r\\n 'PerezHilton'], {'name_includes': 'tomCruise'})\\r\\n expected = ['tomCruise']\\r\\n self.assertEqual(actual, expected)\",\n \"def test_spires_syntax_trailing_colon(self):\\n spi_search = \\\"find a watanabe:\\\"\\n invenio_search = \\\"author:watanabe:\\\"\\n self._compare_searches(invenio_search, spi_search)\",\n \"def lookup(name, phonebook):\\n\\n phonebook_data = read_phonebook(phonebook)\\n\\n match = False\\n for entry_name in phonebook_data:\\n if name.lower() in entry_name.lower():\\n match = True\\n print entry_name, phonebook_data[entry_name]\\n\\n if not match:\\n print \\\"No matches found.\\\"\",\n \"def test_name(self, parse_input):\\n bb = parse_input(\\\"name testname\\\\nversion 1.0\\\")\\n assert bb.name == \\\"testname\\\"\",\n \"def name_search(self, search):\\n if isinstance(search, str):\\n name_re = re.compile(search)\\n else:\\n name_re = search\\n matches = [\\n entry\\n for entry in self\\n if entry is not None and name_re.search(entry.name)\\n ]\\n return matches\",\n \"def test_search(self):\\n pass\",\n \"def test_search(self):\\n pass\",\n \"def test_search(self):\\n pass\",\n \"def test_syntax_converter_expand_search_patterns_conjoined(self):\\n spi_search = \\\"find t bob and sam\\\"\\n inv_search = \\\"title:bob and title:sam\\\"\\n self._compare_searches(inv_search, spi_search)\",\n \"def test_search_len(self):\\n self.assertEquals(len(self.t['My Name Is Earl'].search('Faked His Own Death')), 1)\",\n \"def test_search_key_phrase(self):\\n # search via key phrase.\\n test = self.data.search(key_phrase='testing entries.', all_names=True)\\n self.assertIn('testing entries.', test[0].notes)\",\n \"def test_check_name_is_3_parts():\\n check_name_length()\",\n \"def test_search_employee_text_finds_matching_employees(self):\\n # add some employees to the database\\n test_pattern = 'foo'\\n test_employees = [\\n {'id': 1, 'name': \\\"Test Employee 1 foo\\\"},\\n {'id': 2, 'name': \\\"Test Employee 2 foo\\\"},\\n {'id': 3, 'name': \\\"Test Employee 3 bar\\\"},\\n ]\\n for employee in test_employees:\\n e = db_manager.Employee.get_or_create(name=employee['name'])\\n db_manager.LogEntry.create(\\n employee=e[0],\\n date=datetime.date(2018, 1, 2),\\n task_name='Test task {}'.format(employee['id']),\\n duration=employee['id'],\\n notes='Note')\\n\\n title = \\\"FIND EMPLOYEE NAME USING TEXT STRING\\\" + \\\"\\\\n\\\"\\n subtitle = \\\"Enter the text string to search on\\\" + \\\"\\\\n\\\"\\n employee_rows = \\\"\\\"\\n for employee in test_employees:\\n if test_pattern in employee['name']:\\n employee_rows += \\\"{}) {}\\\\n\\\".format(employee['id'],\\n employee['name'])\\n\\n expected_output = (title +\\n subtitle +\\n employee_rows)\\n\\n # Create a StringIO object to be a capture object\\n captured_output = io.StringIO()\\n # point stdout at the capture object\\n sys.stdout = captured_output\\n # Do anything that's going to have a print statement\\n # (these will be accumulated in the captured_output object)\\n example_input = [test_pattern, '1']\\n with patch('builtins.input', side_effect=example_input):\\n self.menu.search_employee_text()\\n\\n # Revert stdout (captured_output still holds the captured items)\\n sys.stdout = sys.__stdout__\\n # Do any other test code (e.g., asserts)\\n self.assertEqual(expected_output, captured_output.getvalue())\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.78682476","0.7367077","0.69262975","0.6646887","0.6576953","0.64594865","0.6428426","0.64177704","0.6337653","0.6327376","0.6301725","0.62890095","0.6284056","0.6256203","0.6250491","0.6238765","0.6238765","0.6227155","0.62223715","0.62219703","0.6218141","0.62176156","0.6172505","0.6163503","0.6160127","0.6146927","0.6144219","0.61424476","0.61296964","0.611661","0.61141366","0.60435635","0.6034318","0.6034318","0.6031391","0.6029205","0.6019738","0.601359","0.60085297","0.6006954","0.60005826","0.59991103","0.59871554","0.59732944","0.59588337","0.595754","0.5944388","0.593733","0.5936845","0.5934464","0.5929737","0.5916993","0.5915209","0.59002864","0.5864303","0.58496773","0.5841885","0.5840474","0.5836748","0.58326024","0.5805384","0.58016616","0.5799069","0.5797012","0.57813126","0.57808965","0.57753325","0.57752764","0.57647204","0.57424796","0.57402253","0.57393813","0.5734161","0.57206285","0.5718263","0.57068765","0.57003707","0.5700103","0.56907296","0.5688126","0.56862175","0.56821555","0.56821555","0.56821555","0.5673114","0.5670447","0.5670288","0.5664592","0.5661757","0.5661649","0.5659296","0.56592554","0.5656914","0.5656914","0.5656914","0.5654948","0.5654578","0.56479484","0.564162","0.5640443"],"string":"[\n \"0.78682476\",\n \"0.7367077\",\n \"0.69262975\",\n \"0.6646887\",\n \"0.6576953\",\n \"0.64594865\",\n \"0.6428426\",\n \"0.64177704\",\n \"0.6337653\",\n \"0.6327376\",\n \"0.6301725\",\n \"0.62890095\",\n \"0.6284056\",\n \"0.6256203\",\n \"0.6250491\",\n \"0.6238765\",\n \"0.6238765\",\n \"0.6227155\",\n \"0.62223715\",\n \"0.62219703\",\n \"0.6218141\",\n \"0.62176156\",\n \"0.6172505\",\n \"0.6163503\",\n \"0.6160127\",\n \"0.6146927\",\n \"0.6144219\",\n \"0.61424476\",\n \"0.61296964\",\n \"0.611661\",\n \"0.61141366\",\n \"0.60435635\",\n \"0.6034318\",\n \"0.6034318\",\n \"0.6031391\",\n \"0.6029205\",\n \"0.6019738\",\n \"0.601359\",\n \"0.60085297\",\n \"0.6006954\",\n \"0.60005826\",\n \"0.59991103\",\n \"0.59871554\",\n \"0.59732944\",\n \"0.59588337\",\n \"0.595754\",\n \"0.5944388\",\n \"0.593733\",\n \"0.5936845\",\n \"0.5934464\",\n \"0.5929737\",\n \"0.5916993\",\n \"0.5915209\",\n \"0.59002864\",\n \"0.5864303\",\n \"0.58496773\",\n \"0.5841885\",\n \"0.5840474\",\n \"0.5836748\",\n \"0.58326024\",\n \"0.5805384\",\n \"0.58016616\",\n \"0.5799069\",\n \"0.5797012\",\n \"0.57813126\",\n \"0.57808965\",\n \"0.57753325\",\n \"0.57752764\",\n \"0.57647204\",\n \"0.57424796\",\n \"0.57402253\",\n \"0.57393813\",\n \"0.5734161\",\n \"0.57206285\",\n \"0.5718263\",\n \"0.57068765\",\n \"0.57003707\",\n \"0.5700103\",\n \"0.56907296\",\n \"0.5688126\",\n \"0.56862175\",\n \"0.56821555\",\n \"0.56821555\",\n \"0.56821555\",\n \"0.5673114\",\n \"0.5670447\",\n \"0.5670288\",\n \"0.5664592\",\n \"0.5661757\",\n \"0.5661649\",\n \"0.5659296\",\n \"0.56592554\",\n \"0.5656914\",\n \"0.5656914\",\n \"0.5656914\",\n \"0.5654948\",\n \"0.5654578\",\n \"0.56479484\",\n \"0.564162\",\n \"0.5640443\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5681"},"document_rank":{"kind":"string","value":"84"}}},{"rowIdx":81783,"cells":{"query":{"kind":"string","value":"Wrapper for dot product operation, in order to be compatible with both Theano and Tensorflow"},"document":{"kind":"string","value":"def dot_product(x, kernel):\n if K.backend() == 'tensorflow':\n # todo: check that this is correct\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\n else:\n return K.dot(x, kernel)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def dot_prod(t1: torch.Tensor, t2: torch.Tensor, verbose: bool = False):\n assert t1.size() == t2.size(), \"Sizes for dot-product must match\"\n return mo.dot_prod(t1, t2, verbose)","def _dot(a, b):\n return np.einsum('ijk,ikl->ijl', a, b)","def dot(a, b):\r\n a, b = as_tensor_variable(a), as_tensor_variable(b)\r\n\r\n if a.ndim == 0 or b.ndim == 0:\r\n return a * b\r\n elif a.ndim > 2 or b.ndim > 2:\r\n return tensordot(a, b, [[a.ndim - 1], [numpy.maximum(0, b.ndim - 2)]])\r\n else:\r\n return _dot(a, b)","def dot_product(v1, v2):\n return v1[0] * v2[0] + v1[1] * v2[1]","def dot_product(v1, v2):\n return v1[0]*v2[0] + v1[1]*v2[1] + v1[2]*v2[2]","def dot_product(x, kernel):\n if K.backend() == 'tensorflow':\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\n else:\n return K.dot(x, kernel)","def dot_product(x, kernel):\n if K.backend() == 'tensorflow':\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\n else:\n return K.dot(x, kernel)","def dot_product(x, kernel):\n if K.backend() == 'tensorflow':\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\n else:\n return K.dot(x, kernel)","def dot_product(x, kernel):\n if K.backend() == 'tensorflow':\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\n else:\n return K.dot(x, kernel)","def dot_product(x, kernel):\r\n if K.backend() == 'tensorflow':\r\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\r\n else:\r\n return K.dot(x, kernel)","def dotproduct(v1, v2):\n\treturn sum(imap(operator.mul, v1, v2))","def dot_product(x, kernel):\n if K.backend() == 'tensorflow':\n # K.expand_dims 默认axis=-1\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\n else:\n return K.dot(x, kernel)","def dotproduct(x, y):\n return sum(imap(operator.mul, x, y))","def dotProduct(v1, v2):\n return sum((a * b) for a, b in zip(v1, v2))","def dot_product(a,b):\n return sum(pairwise_mult(a,b))","def matrix_dot(*args):\r\n rval = args[0]\r\n for a in args[1:]:\r\n rval = theano.tensor.dot(rval, a)\r\n return rval","def _layerwise_dot_product(x_s, y_s):\n return [torch.sum(x * y).item() for x, y in zip(x_s, y_s)]","def dot_product(x, kernel):\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)","def dotproduct(vec1, vec2, sum=sum, map=map, mul=mul):\n return sum(map(mul, vec1, vec2))","def dot_product(vec_1:tuple, vec_2:tuple)->float:\n return vec_1[0] * vec_2[0] + vec_1[1] * vec_2[1]","def dot_product(vector1, vector2):\n return [reduce_by_multiplication(pair) for pair in zip(vector1, vector2)]","def dot_product(a, b):\n a1, a2, a3 = a\n b1, b2, b3 = b\n return a1 * b1 + a2 * b2 + a3 * b3","def dot_product(vector1, vector2):\n out = None\n ### YOUR CODE HERE\n pass\n ### END YOUR CODE\n\n return out","def dotproduct(vec1, vec2):\n return sum((a*b) for a, b in zip(vec1, vec2))","def dotproduct(vec1, vec2):\n import operator\n return sum(map(operator.mul, vec1, vec2))","def dot_product(v,w):\n return v[0] * w[0] + v[1] * w[1]","def dot(a, b):\n return np.vdot(a.arr,b.arr)","def dot(input, other, allow_tf32=True, out_dtype=float32, _builder=None):\n allow_tf32 = _constexpr_to_value(allow_tf32)\n out_dtype = _constexpr_to_value(out_dtype)\n return semantic.dot(input, other, allow_tf32, out_dtype, _builder)","def dot(a, b):\n return a[0]*b[0] + a[1]*b[1] + a[2]*b[2]","def dot_product(vector1, vector2):\n out = None\n ### YOUR CODE HERE\n out=np.dot(vector1,vector2)\n ### END YOUR CODE\n\n return out","def dot(x, y):\n if isinstance(x, tf.SparseTensor) and isinstance(y, tf.SparseTensor):\n res = tf.sparse_tensor_dense_matmul(x, y)\n else:\n res = tf.matmul(x,y)\n return res","def dotproduct(first, other):\n if isinstance(first,FreeCAD.Vector) and isinstance(other,FreeCAD.Vector):\n return (first.x*other.x + first.y*other.y + first.z*other.z)","def dot(a,b):\n return a[0]*b[0]+a[1]*b[1]+a[2]*b[2]","def _mul(*args):\n\treturn functools.reduce(numpy.dot, args)","def dotProduct(v1, v2):\n n1 = normalize(v1)\n n2 = normalize(v2)\n return n1[0] * n2[0] + n1[1] * n2[1] + n1[2] * n2[2]","def vec_dot(x, y):\r\n return sum(a * b for a, b in zip(x, y))","def dot(x,y,sparse=False):\n if sparse:\n res = tf.sparse_tensor_dense_matmul(x, y)\n else:\n res = tf.matmul(x, y)\n return res","def convert_dot(g, op, block):\n\n # x, y should be 1D or 2D tensor\n # when it's 2D tensor, the first dimension means batch dimension\n x = g.get_node(op.input(\"X\")[0])\n y = g.get_node(op.input(\"Y\")[0])\n\n out = _op.sum(_op.multiply(x, y), axis=[-1], keepdims=True)\n g.add_node(op.output(\"Out\")[0], out)","def dot(x, y, sparse=False):\n if sparse:\n res = tf.sparse_tensor_dense_matmul(x, y)\n else:\n res = tf.matmul(x, y)\n return res","def dot_product(v, w):\n return sum(v_i * w_i for v_i, w_i in zip(v, w))","def _dot(self, s1, s2, tf_embs):\n mat1 = tf.gather(tf_embs, s1)\n mat2 = tf.gather(tf_embs, s2)\n return tf.matmul(mat1, tf.transpose(mat2))","def _tensor_batch_dot(t1: Tensor, t2: Tensor) -> Tensor:\n\n msg = (\n \"Please ensure each batch member has the same feature dimension. \"\n f\"First input has {torch.numel(t1) / t1.shape[0]} features, and \"\n f\"second input has {torch.numel(t2) / t2.shape[0]} features.\"\n )\n assert torch.numel(t1) / t1.shape[0] == torch.numel(t2) / t2.shape[0], msg\n\n return torch.mm(\n t1.view(t1.shape[0], -1),\n t2.view(t2.shape[0], -1).T,\n )","def dot(a, b):\n return sum([a[i]*b[i] for i in range(2)])","def dot(p1, p2):\n return p1[0] * p2[0] + p1[1] * p2[1]","def dot(x, y):\n if ndim(x) is not None and (ndim(x) > 2 or ndim(y) > 2):\n x_shape = []\n for i, s in zip(x.get_shape().as_list(), tf.unstack(tf.shape(x))):\n if i is not None:\n x_shape.append(i)\n else:\n x_shape.append(s)\n x_shape = tuple(x_shape)\n y_shape = []\n for i, s in zip(y.get_shape().as_list(), tf.unstack(tf.shape(y))):\n if i is not None:\n y_shape.append(i)\n else:\n y_shape.append(s)\n y_shape = tuple(y_shape)\n y_permute_dim = list(range(ndim(y)))\n y_permute_dim = [y_permute_dim.pop(-2)] + y_permute_dim\n xt = tf.reshape(x, [-1, x_shape[-1]])\n yt = tf.reshape(tf.transpose(y, perm=y_permute_dim), [y_shape[-2], -1])\n return tf.reshape(tf.matmul(xt, yt),\n x_shape[:-1] + y_shape[:-2] + y_shape[-1:])\n if isinstance(x, tf.SparseTensor):\n out = tf.sparse_tensor_dense_matmul(x, y)\n else:\n out = tf.matmul(x, y)\n return out","def vec_dot(v1,v2):\r\n \r\n return np.dot(v1,v2)","def naive_vector_dot(x, y):\n assert len(x.shape) == 1\n assert len(y.shape) == 1\n assert x.shape[0] == y.shape[0]\n\n z = 0\n for i in range(x.shape[0]):\n z += x[i] * y[i]\n return z","def vdot(x, v, pub):\n x_flatten = x.flatten()\n v_flatten = v.flatten()\n mul_res = paillier_gpu.mul_impl(v_flatten, x_flatten)\n\n return paillier_gpu.sum_impl(mul_res)","def dot(a, b):\n if issparse(a) or issparse(b):\n return dot_sparse(a, b)\n try:\n return a.dot(b)\n except AttributeError:\n return a @ b","def dot_product(v1, v2):\n #print(v1, v2)\n sum = 0\n\n for i in range(len(v1)):\n #print(v1[i], v2[i])\n sum += v1[i] * v2[i]\n return sum","def TensorDot(self, axes):\r\n return lambda a, b: tensordot(a, b, axes)","def dot_product(a, b):\n dp = 0.0\n for i, j in zip(a, b):\n dp += i * j\n return dp","def dot(x, y):\r\n if K.ndim(x) is not None and (K.ndim(x) > 2 or K.ndim(y) > 2):\r\n x_shape = []\r\n for i, s in zip(x.get_shape().as_list(), tf.unstack(tf.shape(x))):\r\n if i is not None:\r\n x_shape.append(i)\r\n else:\r\n x_shape.append(s)\r\n x_shape = tuple(x_shape)\r\n y_shape = []\r\n for i, s in zip(y.get_shape().as_list(), tf.unstack(tf.shape(y))):\r\n if i is not None:\r\n y_shape.append(i)\r\n else:\r\n y_shape.append(s)\r\n y_shape = tuple(y_shape)\r\n y_permute_dim = list(range(K.ndim(y)))\r\n y_permute_dim = [y_permute_dim.pop(-2)] + y_permute_dim\r\n xt = tf.reshape(x, [-1, x_shape[-1]])\r\n yt = tf.reshape(tf.transpose(y, perm=y_permute_dim), [y_shape[-2], -1])\r\n return tf.reshape(tf.matmul(xt, yt),\r\n x_shape[:-1] + y_shape[:-2] + y_shape[-1:])\r\n if isinstance(x, tf.SparseTensor):\r\n out = tf.sparse_tensor_dense_matmul(x, y)\r\n else:\r\n out = tf.matmul(x, y)\r\n return out","def dot(x,y):\n\treturn sum([xi*yi for (xi,yi) in zip(x,y)])","def dot(a, b):\n\n if len(a) != len(b):\n raise Exception(\"Input vectors must be of same length, not %d and %d\" % (len(a), len(b)))\n\n return float(sum([a[i] * b[i] for i in range(len(a))]))","def _dot_product_attention_inner_relative(x, y, z, transpose):\n batch_size, heads, length, _ = x.size()\n\n # xy_matmul is [batch_size, heads, length, length or depth]\n xy_matmul = torch.matmul(x, y if not transpose else y.transpose(-2, -1))\n # x_t is [length, batch_size, heads, length or depth]\n x_t = x.permute(2, 0, 1, 3)\n # x_t_r is [length, batch_size * heads, length or depth]\n x_t_r = x_t.view(length, batch_size * heads, -1)\n # x_tz_matmul is [length, batch_size * heads, length or depth]\n x_tz_matmul = torch.matmul(x_t_r, z if not transpose else z.transpose(-2, -1))\n # x_tz_matmul_r is [length, batch_size, heads, length or depth]\n x_tz_matmul_r = x_tz_matmul.view(length, batch_size, heads, -1)\n # x_tz_matmul_r_t is [batch_size, heads, length, length or depth]\n x_tz_matmul_r_t = x_tz_matmul_r.permute(1, 2, 0, 3)\n\n return xy_matmul + x_tz_matmul_r_t","def _call_dot(vecObj, vec2):\n res = vecObj.dot(vec2)\n return res","def __mul__(self, othertr):\n res = self.dot(othertr)\n return res","def dot(vector1, vector2):\n return sum(a1 * a2 for a1, a2 in zip(vector1, vector2))","def vector_dot(x, y):\n\n if(len(x) != len(y)):\n raise ValueError(\"vector lengths differ\")\n else:\n # return x1*y1+x2*y2+...xn*yn\n return sum([x[i] * y[i] for i in range(len(x))])","def dot( v1, v2 ):\n return sum( x*y for x,y in izip(v1,v2) )","def _parameter_dot_product(x: JaxComplexArray, y: JaxComplexArray, n_axes: int) -> JaxRealArray:\n axes = tuple(range(-n_axes, 0))\n return jnp.sum(x * y, axis=axes).real","def _mdot_r(a, b):\r\n if type(a) == types.TupleType:\r\n if len(a) > 1:\r\n a = mdot(*a)\r\n else:\r\n a = a[0]\r\n if type(b) == types.TupleType:\r\n if len(b) > 1:\r\n b = mdot(*b)\r\n else:\r\n b = b[0]\r\n return np.dot(a, b)","def vdot(a, b):\n return np.vdot(a.ravel(), b.ravel())","def dot_product(a, b):\n if len(a) != len(b):\n raise ValueError('Arrays are of different lengths')\n else:\n return [a[i] * b[i] for i in range(len(a))]","def dotProduct(vectorA, vectorB):\r\n product =0\r\n for i in range(len(vectorA)):\r\n product += eval(vectorA[i])*eval(vectorB[i])\r\n return product","def dot(x, y):\n res = x[0] * y[0]\n for a, b in zip(x, y):\n res += a * b\n return res","def dot(self, vec):\n if not isinstance(vec, self.__class__):\n raise TypeError('Dot product operand must be a VectorArray')\n if self.nV != 1 and vec.nV != 1 and self.nV != vec.nV:\n raise ValueError('Dot product operands must have the same '\n 'number of elements.')\n return np.sum((getattr(self, d)*getattr(vec, d) for d in self.dims), 1)","def vector_dot(v1,v2):\n return (v1.x * v2.x) + (v1.y * v2.y) + (v1.z * v2.z)","def dot_product(first_vector, second_vector):\n first_unpacker = VectorUnpacker(first_vector)\n second_unpacker = VectorUnpacker(second_vector)\n if first_unpacker.unpacked_vector_length != second_unpacker.unpacked_vector_length:\n raise ApplicationError(\"Unpacked vector sizes are unequal\")\n\n # looks better than a 'map' one-liner to me\n value = 0\n for piece in zip(first_unpacker(), second_unpacker()):\n value += piece[0] * piece[1]\n\n return value","def dot(pepx1, pepx2):\n\n Ls = pepx1.shape\n assert pepx2.shape==Ls, '[dot]: sizes of pepx1 and pepx2 are not equal'\n new_pepx = np.empty(Ls, dtype=np.object)\n new_lams = np.empty(pepx1.lambdas.shape, dtype=np.object)\n\n # if np.all([ pepx1[i].ndim==3 and pepx2[i].ndim==3 for i in np.ndenumerate(pepx1) ]):\n # return peps_dot(pepx1,pepx2)\n # else:\n for idx in np.ndindex(Ls):\n len_dp1 = len(pepx1.phys_bonds[idx])\n len_dp2 = len(pepx2.phys_bonds[idx])\n ax1 = [0,2,4,6] + range(8, 8+len_dp1)\n ax2 = [1,3,5,7] + range(8+len_dp1-1,8+len_dp1+len_dp2-1)\n ax2[-len_dp2] = ax1[-1] # contract vertical bonds (mpx1 down with mpx2 up)\n new_site = np.einsum(pepx1[idx],ax1,pepx2[idx],ax2)\n new_pepx[idx] = tf.reshape(new_site,'ii,ii,ii,ii,...',group_ellipsis=False)\n\n i,j = idx\n for xx in range(new_lams.shape[2]):\n new_lams[i,j,xx] = np.outer(pepx1.lambdas[i,j,xx], pepx2.lambdas[i,j,xx]).reshape(-1)\n # print new_lams[i,j,xx].shape\n\n return PEPX_GL(new_pepx,new_lams) #,pepx1.phys_bonds)","def convert_dot(node, **kwargs):\n name, input_nodes, attrs = get_inputs(node, kwargs)\n input_node_a = input_nodes[0]\n input_node_b = input_nodes[1]\n\n trans_a_node = None\n trans_b_node = None\n\n trans_a = get_boolean_attribute_value(attrs, \"transpose_a\")\n trans_b = get_boolean_attribute_value(attrs, \"transpose_b\")\n\n op_name = \"transpose\" + str(kwargs[\"idx\"])\n\n if trans_a:\n input_node_a = op_name + \"_a\"\n trans_a_node, = create_helper_trans_node(input_nodes[0], input_node_a)\n if trans_b:\n input_node_b = op_name + \"_b\"\n trans_b_node, = create_helper_trans_node(input_nodes[1], input_node_b)\n\n matmul_node = onnx.helper.make_node(\n 'MatMul',\n inputs=[input_node_a, input_node_b],\n outputs=[name],\n name=name\n )\n\n if not trans_a and not trans_b:\n return [matmul_node]\n elif trans_a and not trans_b:\n return [trans_a_node, matmul_node]\n elif trans_b and not trans_a:\n return [trans_b_node, matmul_node]\n else:\n return [trans_a_node, trans_b_node, matmul_node]","def compound_dot(self, A, B, C, alpha=1.0, beta=0.0, relu=False, bsum=None):\n\n # checking type and shape\n assert A.dtype == B.dtype == C.dtype\n assert A.shape[0] == C.shape[0]\n assert B.shape[1] == C.shape[1]\n assert A.shape[1] == B.shape[0]\n\n # cleaner implementation, shall be equivalent to the one below\n # if relu:\n # C[:] = self.log(1. + self.exp(alpha * self.dot(A, B))) + beta * C\n # else:\n # C[:] = alpha * self.dot(A, B) + beta * C\n\n if beta == 0:\n if C._tensor.flags['C_CONTIGUOUS'] is not True:\n tmp = np.empty(C.shape, dtype=C.dtype)\n math_cpu.blas_dot(A._tensor, B._tensor, tmp)\n C._tensor[:] = tmp.copy()\n else:\n math_cpu.blas_dot(A._tensor, B._tensor, C._tensor)\n if relu:\n self.Relu(C._tensor, C._tensor)\n else:\n # mfma: change np.multiply to mul\n if beta != 1:\n np.multiply(C._tensor, beta, C._tensor)\n tmp = np.empty(C.shape, dtype=C.dtype)\n np.dot(A._tensor, B._tensor, tmp)\n # mfma: change np.multiply to mul\n if alpha != 1:\n np.multiply(tmp, alpha, tmp)\n if relu:\n self.Relu(tmp, tmp)\n np.add(C._tensor, tmp, C._tensor)\n if bsum is not None:\n bsum[:] = self.sum(C, 1)\n\n return C","def dot(self, vec):\n if not isinstance(vec, self.__class__):\n raise TypeError('Dot product operand must be a vector')\n return np.dot(self, vec)","def mdot(*args):\n r = args[0]\n for a in args[1:]:\n r = N.dot(r,a)\n return r","def dot(v,w):\r\n return sum(v_i * w_i\r\n for v_i, w_i in zip(v, w))","def dot_product(tensor_nd, tensor_2d):\n # Get shape and replace unknown shapes (None) with -1\n shape_nd = tensor_nd.get_shape().as_list()\n shape_nd = [s if isinstance(s, int) else -1 for s in shape_nd]\n shape_2d = tensor_2d.get_shape().as_list()\n if len(shape_2d) > 2:\n raise ValueError(\"tensor_2d must be a 1D or 2D tensor\")\n \n if len(shape_2d) == 1:\n tensor_2d = tf.expand_dims(tensor_2d, 0)\n if len(shape_nd) == 1:\n shape_nd = tf.expand_dims(shape_nd, 0)\n \n if len(shape_nd) > 2:\n # collapse axes except for ones to multiply and perform matmul\n dot_prod = tf.matmul(tf.reshape(tensor_nd, [-1, shape_nd[-1]]), tensor_2d)\n # reshape to correct dimensions\n dot_prod = tf.reshape(dot_prod, shape_nd[:-1] + shape_2d[-1:])\n elif len(shape_nd) == 2:\n dot_prod = tf.matmul(tensor_nd, tensor_2d)\n else:\n dot_prod = tf.matmul(tf.expand_dims(tensor_nd, 0), tensor_2d)\n \n return dot_prod","def dot_vectors(u, v):\n return u[0] * v[0] + u[1] * v[1] + u[2] * v[2]","def dot(self, other):\n\n Vector = sympy.vector.Vector\n if isinstance(other, BasisDependentZero):\n return Vector.zero\n elif isinstance(other, Vector):\n outvec = Vector.zero\n for k, v in self.components.items():\n vect_dot = k.args[1].dot(other)\n outvec += vect_dot * v * k.args[0]\n return outvec\n elif isinstance(other, Dyadic):\n outdyad = Dyadic.zero\n for k1, v1 in self.components.items():\n for k2, v2 in other.components.items():\n vect_dot = k1.args[1].dot(k2.args[0])\n outer_product = k1.args[0].outer(k2.args[1])\n outdyad += vect_dot * v1 * v2 * outer_product\n return outdyad\n else:\n raise TypeError(\"Inner product is not defined for \" +\n str(type(other)) + \" and Dyadics.\")","def dot(vector01,vector02):\r\n result = 0\r\n # creates the initial value for the result of the dot product\r\n for z in range(len(vector01)):\r\n # for loop which continues as long as there are more values left in the vector \r\n result += vector01[z]*vector02[z]\r\n # the new result is found to be the corresponding values in each vector multiplied and then added together \r\n return result","def dot4(a,b):\n return a[0]*b[0]+a[1]*b[1]+a[2]*b[2]+a[3]*b[3]","def outer_product(x):\n return keras.backend.batch_dot(\n x[0]\n , x[1]\n , axes=[1,1]\n ) / x[0].get_shape().as_list()[1]","def __mul__(self, other): \n if isinstance(other, Iterable):\n # dot product\n return self.x * other[0] + self.y * other[1]\n else:\n # scalar product\n return Vector(self.x * other, self.y * other)","def test_dot_different_sizes():\n dot(Vector(1.0), Vector(2.0, 3.0))","def rdot(a, b): # pragma: no cover\n a, b = a.reshape((1, -1)), b.reshape((-1, 1))\n return (a @ b).item()","def dot_prod(u,v):\n each_product = []\n for i in range(len(u)):\n each_product.append(u[i] * v[i])\n return sum(each_product)","def trace_dot(a, b):\r\n return np.sum(a * b)","def dot(v,w):\n return sum(v_i * w_i for v_i,w_i in zip(v,w))","def dot(v, w):\n return sum(v_i * w_i for v_i, w_i in zip(v, w))","def dot(v, w):\n return sum(v_i * w_i for v_i, w_i in zip(v, w))","def dot(v, w):\n return sum(v_i * w_i for v_i, w_i in zip(v, w))","def dot(v, w):\n return sum(v_i * w_i for v_i, w_i in zip(v, w))","def dot(v, w):\n return sum(v_i * w_i for v_i, w_i in zip(v, w))","def mdot(*args):\n import numpy as np\n import sympy\n import operator\n from functools import reduce\n is_numpy = lambda x: isinstance(x, np.ndarray)\n is_sympy = lambda x: isinstance(x, (sympy.Matrix, sympy.ImmutableMatrix))\n\n if is_numpy(args[0]):\n if not all(map(is_numpy, args)):\n raise TypeError(set(map(type, args)))\n return reduce(np.dot, args)\n\n elif is_sympy(args[0]):\n if not all(map(is_sympy, args)):\n raise TypeError(set(map(type, args)))\n return reduce(operator.mul, args)\n\n else:\n raise TypeError(type(args[0]))","def _listdot(d1, d2):\n return [np.dot(x[0].T, x[1]) for x in zip(d1, d2)]","def batch_dot(x, y, axes=None):\n if isinstance(axes, int):\n axes = (axes, axes)\n x_ndim = ndim(x)\n y_ndim = ndim(y)\n if x_ndim > y_ndim:\n diff = x_ndim - y_ndim\n y = tf.reshape(y, tf.concat([tf.shape(y), [1] * (diff)], axis=0))\n elif y_ndim > x_ndim:\n diff = y_ndim - x_ndim\n x = tf.reshape(x, tf.concat([tf.shape(x), [1] * (diff)], axis=0))\n else:\n diff = 0\n if ndim(x) == 2 and ndim(y) == 2:\n if axes[0] == axes[1]:\n out = tf.reduce_sum(tf.multiply(x, y), axes[0])\n else:\n out = tf.reduce_sum(tf.multiply(\n tf.transpose(x, [1, 0]), y), axes[1])\n else:\n if axes is not None:\n adj_x = None if axes[0] == ndim(x) - 1 else True\n adj_y = True if axes[1] == ndim(y) - 1 else None\n else:\n adj_x = None\n adj_y = None\n out = tf.matmul(x, y, adjoint_a=adj_x, adjoint_b=adj_y)\n if diff:\n if x_ndim > y_ndim:\n idx = x_ndim + y_ndim - 3\n else:\n idx = x_ndim - 1\n out = tf.squeeze(out, list(range(idx, idx + diff)))\n if ndim(out) == 1:\n out = tf.expand_dims(out, 1)\n return out","def dot(left, right):\n if sp.sparse.issparse(right) or sp.sparse.issparse(left):\n result = left*right\n else:\n result = left.dot(right)\n return result","def dot(v,w):\n return sum(v_i * w_i\n for v_i, w_i in zip(v,w))","def dot(v, w):\n return sum(v_i * w_i\n for v_i, w_i in zip(v, w))","def batch_dot(x, y, axes=None):\r\n if isinstance(axes, int):\r\n axes = (axes, axes)\r\n x_ndim = K.ndim(x)\r\n y_ndim = K.ndim(y)\r\n if x_ndim > y_ndim:\r\n diff = x_ndim - y_ndim\r\n y = tf.reshape(y, tf.concat([tf.shape(y), [1] * (diff)], axis=0))\r\n elif y_ndim > x_ndim:\r\n diff = y_ndim - x_ndim\r\n x = tf.reshape(x, tf.concat([tf.shape(x), [1] * (diff)], axis=0))\r\n else:\r\n diff = 0\r\n if K.ndim(x) == 2 and K.ndim(y) == 2:\r\n if axes[0] == axes[1]:\r\n out = tf.reduce_sum(tf.multiply(x, y), axes[0])\r\n else:\r\n out = tf.reduce_sum(tf.multiply(\r\n tf.transpose(x, [1, 0]), y), axes[1])\r\n else:\r\n if axes is not None:\r\n adj_x = None if axes[0] == K.ndim(x) - 1 else True\r\n adj_y = True if axes[1] == K.ndim(y) - 1 else None\r\n else:\r\n adj_x = None\r\n adj_y = None\r\n out = tf.matmul(x, y, adjoint_a=adj_x, adjoint_b=adj_y)\r\n if diff:\r\n if x_ndim > y_ndim:\r\n idx = x_ndim + y_ndim - 3\r\n else:\r\n idx = x_ndim - 1\r\n out = tf.squeeze(out, list(range(idx, idx + diff)))\r\n if K.ndim(out) == 1:\r\n out = tf.expand_dims(out, 1)\r\n return out"],"string":"[\n \"def dot_prod(t1: torch.Tensor, t2: torch.Tensor, verbose: bool = False):\\n assert t1.size() == t2.size(), \\\"Sizes for dot-product must match\\\"\\n return mo.dot_prod(t1, t2, verbose)\",\n \"def _dot(a, b):\\n return np.einsum('ijk,ikl->ijl', a, b)\",\n \"def dot(a, b):\\r\\n a, b = as_tensor_variable(a), as_tensor_variable(b)\\r\\n\\r\\n if a.ndim == 0 or b.ndim == 0:\\r\\n return a * b\\r\\n elif a.ndim > 2 or b.ndim > 2:\\r\\n return tensordot(a, b, [[a.ndim - 1], [numpy.maximum(0, b.ndim - 2)]])\\r\\n else:\\r\\n return _dot(a, b)\",\n \"def dot_product(v1, v2):\\n return v1[0] * v2[0] + v1[1] * v2[1]\",\n \"def dot_product(v1, v2):\\n return v1[0]*v2[0] + v1[1]*v2[1] + v1[2]*v2[2]\",\n \"def dot_product(x, kernel):\\n if K.backend() == 'tensorflow':\\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\\n else:\\n return K.dot(x, kernel)\",\n \"def dot_product(x, kernel):\\n if K.backend() == 'tensorflow':\\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\\n else:\\n return K.dot(x, kernel)\",\n \"def dot_product(x, kernel):\\n if K.backend() == 'tensorflow':\\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\\n else:\\n return K.dot(x, kernel)\",\n \"def dot_product(x, kernel):\\n if K.backend() == 'tensorflow':\\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\\n else:\\n return K.dot(x, kernel)\",\n \"def dot_product(x, kernel):\\r\\n if K.backend() == 'tensorflow':\\r\\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\\r\\n else:\\r\\n return K.dot(x, kernel)\",\n \"def dotproduct(v1, v2):\\n\\treturn sum(imap(operator.mul, v1, v2))\",\n \"def dot_product(x, kernel):\\n if K.backend() == 'tensorflow':\\n # K.expand_dims 默认axis=-1\\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\\n else:\\n return K.dot(x, kernel)\",\n \"def dotproduct(x, y):\\n return sum(imap(operator.mul, x, y))\",\n \"def dotProduct(v1, v2):\\n return sum((a * b) for a, b in zip(v1, v2))\",\n \"def dot_product(a,b):\\n return sum(pairwise_mult(a,b))\",\n \"def matrix_dot(*args):\\r\\n rval = args[0]\\r\\n for a in args[1:]:\\r\\n rval = theano.tensor.dot(rval, a)\\r\\n return rval\",\n \"def _layerwise_dot_product(x_s, y_s):\\n return [torch.sum(x * y).item() for x, y in zip(x_s, y_s)]\",\n \"def dot_product(x, kernel):\\n return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)\",\n \"def dotproduct(vec1, vec2, sum=sum, map=map, mul=mul):\\n return sum(map(mul, vec1, vec2))\",\n \"def dot_product(vec_1:tuple, vec_2:tuple)->float:\\n return vec_1[0] * vec_2[0] + vec_1[1] * vec_2[1]\",\n \"def dot_product(vector1, vector2):\\n return [reduce_by_multiplication(pair) for pair in zip(vector1, vector2)]\",\n \"def dot_product(a, b):\\n a1, a2, a3 = a\\n b1, b2, b3 = b\\n return a1 * b1 + a2 * b2 + a3 * b3\",\n \"def dot_product(vector1, vector2):\\n out = None\\n ### YOUR CODE HERE\\n pass\\n ### END YOUR CODE\\n\\n return out\",\n \"def dotproduct(vec1, vec2):\\n return sum((a*b) for a, b in zip(vec1, vec2))\",\n \"def dotproduct(vec1, vec2):\\n import operator\\n return sum(map(operator.mul, vec1, vec2))\",\n \"def dot_product(v,w):\\n return v[0] * w[0] + v[1] * w[1]\",\n \"def dot(a, b):\\n return np.vdot(a.arr,b.arr)\",\n \"def dot(input, other, allow_tf32=True, out_dtype=float32, _builder=None):\\n allow_tf32 = _constexpr_to_value(allow_tf32)\\n out_dtype = _constexpr_to_value(out_dtype)\\n return semantic.dot(input, other, allow_tf32, out_dtype, _builder)\",\n \"def dot(a, b):\\n return a[0]*b[0] + a[1]*b[1] + a[2]*b[2]\",\n \"def dot_product(vector1, vector2):\\n out = None\\n ### YOUR CODE HERE\\n out=np.dot(vector1,vector2)\\n ### END YOUR CODE\\n\\n return out\",\n \"def dot(x, y):\\n if isinstance(x, tf.SparseTensor) and isinstance(y, tf.SparseTensor):\\n res = tf.sparse_tensor_dense_matmul(x, y)\\n else:\\n res = tf.matmul(x,y)\\n return res\",\n \"def dotproduct(first, other):\\n if isinstance(first,FreeCAD.Vector) and isinstance(other,FreeCAD.Vector):\\n return (first.x*other.x + first.y*other.y + first.z*other.z)\",\n \"def dot(a,b):\\n return a[0]*b[0]+a[1]*b[1]+a[2]*b[2]\",\n \"def _mul(*args):\\n\\treturn functools.reduce(numpy.dot, args)\",\n \"def dotProduct(v1, v2):\\n n1 = normalize(v1)\\n n2 = normalize(v2)\\n return n1[0] * n2[0] + n1[1] * n2[1] + n1[2] * n2[2]\",\n \"def vec_dot(x, y):\\r\\n return sum(a * b for a, b in zip(x, y))\",\n \"def dot(x,y,sparse=False):\\n if sparse:\\n res = tf.sparse_tensor_dense_matmul(x, y)\\n else:\\n res = tf.matmul(x, y)\\n return res\",\n \"def convert_dot(g, op, block):\\n\\n # x, y should be 1D or 2D tensor\\n # when it's 2D tensor, the first dimension means batch dimension\\n x = g.get_node(op.input(\\\"X\\\")[0])\\n y = g.get_node(op.input(\\\"Y\\\")[0])\\n\\n out = _op.sum(_op.multiply(x, y), axis=[-1], keepdims=True)\\n g.add_node(op.output(\\\"Out\\\")[0], out)\",\n \"def dot(x, y, sparse=False):\\n if sparse:\\n res = tf.sparse_tensor_dense_matmul(x, y)\\n else:\\n res = tf.matmul(x, y)\\n return res\",\n \"def dot_product(v, w):\\n return sum(v_i * w_i for v_i, w_i in zip(v, w))\",\n \"def _dot(self, s1, s2, tf_embs):\\n mat1 = tf.gather(tf_embs, s1)\\n mat2 = tf.gather(tf_embs, s2)\\n return tf.matmul(mat1, tf.transpose(mat2))\",\n \"def _tensor_batch_dot(t1: Tensor, t2: Tensor) -> Tensor:\\n\\n msg = (\\n \\\"Please ensure each batch member has the same feature dimension. \\\"\\n f\\\"First input has {torch.numel(t1) / t1.shape[0]} features, and \\\"\\n f\\\"second input has {torch.numel(t2) / t2.shape[0]} features.\\\"\\n )\\n assert torch.numel(t1) / t1.shape[0] == torch.numel(t2) / t2.shape[0], msg\\n\\n return torch.mm(\\n t1.view(t1.shape[0], -1),\\n t2.view(t2.shape[0], -1).T,\\n )\",\n \"def dot(a, b):\\n return sum([a[i]*b[i] for i in range(2)])\",\n \"def dot(p1, p2):\\n return p1[0] * p2[0] + p1[1] * p2[1]\",\n \"def dot(x, y):\\n if ndim(x) is not None and (ndim(x) > 2 or ndim(y) > 2):\\n x_shape = []\\n for i, s in zip(x.get_shape().as_list(), tf.unstack(tf.shape(x))):\\n if i is not None:\\n x_shape.append(i)\\n else:\\n x_shape.append(s)\\n x_shape = tuple(x_shape)\\n y_shape = []\\n for i, s in zip(y.get_shape().as_list(), tf.unstack(tf.shape(y))):\\n if i is not None:\\n y_shape.append(i)\\n else:\\n y_shape.append(s)\\n y_shape = tuple(y_shape)\\n y_permute_dim = list(range(ndim(y)))\\n y_permute_dim = [y_permute_dim.pop(-2)] + y_permute_dim\\n xt = tf.reshape(x, [-1, x_shape[-1]])\\n yt = tf.reshape(tf.transpose(y, perm=y_permute_dim), [y_shape[-2], -1])\\n return tf.reshape(tf.matmul(xt, yt),\\n x_shape[:-1] + y_shape[:-2] + y_shape[-1:])\\n if isinstance(x, tf.SparseTensor):\\n out = tf.sparse_tensor_dense_matmul(x, y)\\n else:\\n out = tf.matmul(x, y)\\n return out\",\n \"def vec_dot(v1,v2):\\r\\n \\r\\n return np.dot(v1,v2)\",\n \"def naive_vector_dot(x, y):\\n assert len(x.shape) == 1\\n assert len(y.shape) == 1\\n assert x.shape[0] == y.shape[0]\\n\\n z = 0\\n for i in range(x.shape[0]):\\n z += x[i] * y[i]\\n return z\",\n \"def vdot(x, v, pub):\\n x_flatten = x.flatten()\\n v_flatten = v.flatten()\\n mul_res = paillier_gpu.mul_impl(v_flatten, x_flatten)\\n\\n return paillier_gpu.sum_impl(mul_res)\",\n \"def dot(a, b):\\n if issparse(a) or issparse(b):\\n return dot_sparse(a, b)\\n try:\\n return a.dot(b)\\n except AttributeError:\\n return a @ b\",\n \"def dot_product(v1, v2):\\n #print(v1, v2)\\n sum = 0\\n\\n for i in range(len(v1)):\\n #print(v1[i], v2[i])\\n sum += v1[i] * v2[i]\\n return sum\",\n \"def TensorDot(self, axes):\\r\\n return lambda a, b: tensordot(a, b, axes)\",\n \"def dot_product(a, b):\\n dp = 0.0\\n for i, j in zip(a, b):\\n dp += i * j\\n return dp\",\n \"def dot(x, y):\\r\\n if K.ndim(x) is not None and (K.ndim(x) > 2 or K.ndim(y) > 2):\\r\\n x_shape = []\\r\\n for i, s in zip(x.get_shape().as_list(), tf.unstack(tf.shape(x))):\\r\\n if i is not None:\\r\\n x_shape.append(i)\\r\\n else:\\r\\n x_shape.append(s)\\r\\n x_shape = tuple(x_shape)\\r\\n y_shape = []\\r\\n for i, s in zip(y.get_shape().as_list(), tf.unstack(tf.shape(y))):\\r\\n if i is not None:\\r\\n y_shape.append(i)\\r\\n else:\\r\\n y_shape.append(s)\\r\\n y_shape = tuple(y_shape)\\r\\n y_permute_dim = list(range(K.ndim(y)))\\r\\n y_permute_dim = [y_permute_dim.pop(-2)] + y_permute_dim\\r\\n xt = tf.reshape(x, [-1, x_shape[-1]])\\r\\n yt = tf.reshape(tf.transpose(y, perm=y_permute_dim), [y_shape[-2], -1])\\r\\n return tf.reshape(tf.matmul(xt, yt),\\r\\n x_shape[:-1] + y_shape[:-2] + y_shape[-1:])\\r\\n if isinstance(x, tf.SparseTensor):\\r\\n out = tf.sparse_tensor_dense_matmul(x, y)\\r\\n else:\\r\\n out = tf.matmul(x, y)\\r\\n return out\",\n \"def dot(x,y):\\n\\treturn sum([xi*yi for (xi,yi) in zip(x,y)])\",\n \"def dot(a, b):\\n\\n if len(a) != len(b):\\n raise Exception(\\\"Input vectors must be of same length, not %d and %d\\\" % (len(a), len(b)))\\n\\n return float(sum([a[i] * b[i] for i in range(len(a))]))\",\n \"def _dot_product_attention_inner_relative(x, y, z, transpose):\\n batch_size, heads, length, _ = x.size()\\n\\n # xy_matmul is [batch_size, heads, length, length or depth]\\n xy_matmul = torch.matmul(x, y if not transpose else y.transpose(-2, -1))\\n # x_t is [length, batch_size, heads, length or depth]\\n x_t = x.permute(2, 0, 1, 3)\\n # x_t_r is [length, batch_size * heads, length or depth]\\n x_t_r = x_t.view(length, batch_size * heads, -1)\\n # x_tz_matmul is [length, batch_size * heads, length or depth]\\n x_tz_matmul = torch.matmul(x_t_r, z if not transpose else z.transpose(-2, -1))\\n # x_tz_matmul_r is [length, batch_size, heads, length or depth]\\n x_tz_matmul_r = x_tz_matmul.view(length, batch_size, heads, -1)\\n # x_tz_matmul_r_t is [batch_size, heads, length, length or depth]\\n x_tz_matmul_r_t = x_tz_matmul_r.permute(1, 2, 0, 3)\\n\\n return xy_matmul + x_tz_matmul_r_t\",\n \"def _call_dot(vecObj, vec2):\\n res = vecObj.dot(vec2)\\n return res\",\n \"def __mul__(self, othertr):\\n res = self.dot(othertr)\\n return res\",\n \"def dot(vector1, vector2):\\n return sum(a1 * a2 for a1, a2 in zip(vector1, vector2))\",\n \"def vector_dot(x, y):\\n\\n if(len(x) != len(y)):\\n raise ValueError(\\\"vector lengths differ\\\")\\n else:\\n # return x1*y1+x2*y2+...xn*yn\\n return sum([x[i] * y[i] for i in range(len(x))])\",\n \"def dot( v1, v2 ):\\n return sum( x*y for x,y in izip(v1,v2) )\",\n \"def _parameter_dot_product(x: JaxComplexArray, y: JaxComplexArray, n_axes: int) -> JaxRealArray:\\n axes = tuple(range(-n_axes, 0))\\n return jnp.sum(x * y, axis=axes).real\",\n \"def _mdot_r(a, b):\\r\\n if type(a) == types.TupleType:\\r\\n if len(a) > 1:\\r\\n a = mdot(*a)\\r\\n else:\\r\\n a = a[0]\\r\\n if type(b) == types.TupleType:\\r\\n if len(b) > 1:\\r\\n b = mdot(*b)\\r\\n else:\\r\\n b = b[0]\\r\\n return np.dot(a, b)\",\n \"def vdot(a, b):\\n return np.vdot(a.ravel(), b.ravel())\",\n \"def dot_product(a, b):\\n if len(a) != len(b):\\n raise ValueError('Arrays are of different lengths')\\n else:\\n return [a[i] * b[i] for i in range(len(a))]\",\n \"def dotProduct(vectorA, vectorB):\\r\\n product =0\\r\\n for i in range(len(vectorA)):\\r\\n product += eval(vectorA[i])*eval(vectorB[i])\\r\\n return product\",\n \"def dot(x, y):\\n res = x[0] * y[0]\\n for a, b in zip(x, y):\\n res += a * b\\n return res\",\n \"def dot(self, vec):\\n if not isinstance(vec, self.__class__):\\n raise TypeError('Dot product operand must be a VectorArray')\\n if self.nV != 1 and vec.nV != 1 and self.nV != vec.nV:\\n raise ValueError('Dot product operands must have the same '\\n 'number of elements.')\\n return np.sum((getattr(self, d)*getattr(vec, d) for d in self.dims), 1)\",\n \"def vector_dot(v1,v2):\\n return (v1.x * v2.x) + (v1.y * v2.y) + (v1.z * v2.z)\",\n \"def dot_product(first_vector, second_vector):\\n first_unpacker = VectorUnpacker(first_vector)\\n second_unpacker = VectorUnpacker(second_vector)\\n if first_unpacker.unpacked_vector_length != second_unpacker.unpacked_vector_length:\\n raise ApplicationError(\\\"Unpacked vector sizes are unequal\\\")\\n\\n # looks better than a 'map' one-liner to me\\n value = 0\\n for piece in zip(first_unpacker(), second_unpacker()):\\n value += piece[0] * piece[1]\\n\\n return value\",\n \"def dot(pepx1, pepx2):\\n\\n Ls = pepx1.shape\\n assert pepx2.shape==Ls, '[dot]: sizes of pepx1 and pepx2 are not equal'\\n new_pepx = np.empty(Ls, dtype=np.object)\\n new_lams = np.empty(pepx1.lambdas.shape, dtype=np.object)\\n\\n # if np.all([ pepx1[i].ndim==3 and pepx2[i].ndim==3 for i in np.ndenumerate(pepx1) ]):\\n # return peps_dot(pepx1,pepx2)\\n # else:\\n for idx in np.ndindex(Ls):\\n len_dp1 = len(pepx1.phys_bonds[idx])\\n len_dp2 = len(pepx2.phys_bonds[idx])\\n ax1 = [0,2,4,6] + range(8, 8+len_dp1)\\n ax2 = [1,3,5,7] + range(8+len_dp1-1,8+len_dp1+len_dp2-1)\\n ax2[-len_dp2] = ax1[-1] # contract vertical bonds (mpx1 down with mpx2 up)\\n new_site = np.einsum(pepx1[idx],ax1,pepx2[idx],ax2)\\n new_pepx[idx] = tf.reshape(new_site,'ii,ii,ii,ii,...',group_ellipsis=False)\\n\\n i,j = idx\\n for xx in range(new_lams.shape[2]):\\n new_lams[i,j,xx] = np.outer(pepx1.lambdas[i,j,xx], pepx2.lambdas[i,j,xx]).reshape(-1)\\n # print new_lams[i,j,xx].shape\\n\\n return PEPX_GL(new_pepx,new_lams) #,pepx1.phys_bonds)\",\n \"def convert_dot(node, **kwargs):\\n name, input_nodes, attrs = get_inputs(node, kwargs)\\n input_node_a = input_nodes[0]\\n input_node_b = input_nodes[1]\\n\\n trans_a_node = None\\n trans_b_node = None\\n\\n trans_a = get_boolean_attribute_value(attrs, \\\"transpose_a\\\")\\n trans_b = get_boolean_attribute_value(attrs, \\\"transpose_b\\\")\\n\\n op_name = \\\"transpose\\\" + str(kwargs[\\\"idx\\\"])\\n\\n if trans_a:\\n input_node_a = op_name + \\\"_a\\\"\\n trans_a_node, = create_helper_trans_node(input_nodes[0], input_node_a)\\n if trans_b:\\n input_node_b = op_name + \\\"_b\\\"\\n trans_b_node, = create_helper_trans_node(input_nodes[1], input_node_b)\\n\\n matmul_node = onnx.helper.make_node(\\n 'MatMul',\\n inputs=[input_node_a, input_node_b],\\n outputs=[name],\\n name=name\\n )\\n\\n if not trans_a and not trans_b:\\n return [matmul_node]\\n elif trans_a and not trans_b:\\n return [trans_a_node, matmul_node]\\n elif trans_b and not trans_a:\\n return [trans_b_node, matmul_node]\\n else:\\n return [trans_a_node, trans_b_node, matmul_node]\",\n \"def compound_dot(self, A, B, C, alpha=1.0, beta=0.0, relu=False, bsum=None):\\n\\n # checking type and shape\\n assert A.dtype == B.dtype == C.dtype\\n assert A.shape[0] == C.shape[0]\\n assert B.shape[1] == C.shape[1]\\n assert A.shape[1] == B.shape[0]\\n\\n # cleaner implementation, shall be equivalent to the one below\\n # if relu:\\n # C[:] = self.log(1. + self.exp(alpha * self.dot(A, B))) + beta * C\\n # else:\\n # C[:] = alpha * self.dot(A, B) + beta * C\\n\\n if beta == 0:\\n if C._tensor.flags['C_CONTIGUOUS'] is not True:\\n tmp = np.empty(C.shape, dtype=C.dtype)\\n math_cpu.blas_dot(A._tensor, B._tensor, tmp)\\n C._tensor[:] = tmp.copy()\\n else:\\n math_cpu.blas_dot(A._tensor, B._tensor, C._tensor)\\n if relu:\\n self.Relu(C._tensor, C._tensor)\\n else:\\n # mfma: change np.multiply to mul\\n if beta != 1:\\n np.multiply(C._tensor, beta, C._tensor)\\n tmp = np.empty(C.shape, dtype=C.dtype)\\n np.dot(A._tensor, B._tensor, tmp)\\n # mfma: change np.multiply to mul\\n if alpha != 1:\\n np.multiply(tmp, alpha, tmp)\\n if relu:\\n self.Relu(tmp, tmp)\\n np.add(C._tensor, tmp, C._tensor)\\n if bsum is not None:\\n bsum[:] = self.sum(C, 1)\\n\\n return C\",\n \"def dot(self, vec):\\n if not isinstance(vec, self.__class__):\\n raise TypeError('Dot product operand must be a vector')\\n return np.dot(self, vec)\",\n \"def mdot(*args):\\n r = args[0]\\n for a in args[1:]:\\n r = N.dot(r,a)\\n return r\",\n \"def dot(v,w):\\r\\n return sum(v_i * w_i\\r\\n for v_i, w_i in zip(v, w))\",\n \"def dot_product(tensor_nd, tensor_2d):\\n # Get shape and replace unknown shapes (None) with -1\\n shape_nd = tensor_nd.get_shape().as_list()\\n shape_nd = [s if isinstance(s, int) else -1 for s in shape_nd]\\n shape_2d = tensor_2d.get_shape().as_list()\\n if len(shape_2d) > 2:\\n raise ValueError(\\\"tensor_2d must be a 1D or 2D tensor\\\")\\n \\n if len(shape_2d) == 1:\\n tensor_2d = tf.expand_dims(tensor_2d, 0)\\n if len(shape_nd) == 1:\\n shape_nd = tf.expand_dims(shape_nd, 0)\\n \\n if len(shape_nd) > 2:\\n # collapse axes except for ones to multiply and perform matmul\\n dot_prod = tf.matmul(tf.reshape(tensor_nd, [-1, shape_nd[-1]]), tensor_2d)\\n # reshape to correct dimensions\\n dot_prod = tf.reshape(dot_prod, shape_nd[:-1] + shape_2d[-1:])\\n elif len(shape_nd) == 2:\\n dot_prod = tf.matmul(tensor_nd, tensor_2d)\\n else:\\n dot_prod = tf.matmul(tf.expand_dims(tensor_nd, 0), tensor_2d)\\n \\n return dot_prod\",\n \"def dot_vectors(u, v):\\n return u[0] * v[0] + u[1] * v[1] + u[2] * v[2]\",\n \"def dot(self, other):\\n\\n Vector = sympy.vector.Vector\\n if isinstance(other, BasisDependentZero):\\n return Vector.zero\\n elif isinstance(other, Vector):\\n outvec = Vector.zero\\n for k, v in self.components.items():\\n vect_dot = k.args[1].dot(other)\\n outvec += vect_dot * v * k.args[0]\\n return outvec\\n elif isinstance(other, Dyadic):\\n outdyad = Dyadic.zero\\n for k1, v1 in self.components.items():\\n for k2, v2 in other.components.items():\\n vect_dot = k1.args[1].dot(k2.args[0])\\n outer_product = k1.args[0].outer(k2.args[1])\\n outdyad += vect_dot * v1 * v2 * outer_product\\n return outdyad\\n else:\\n raise TypeError(\\\"Inner product is not defined for \\\" +\\n str(type(other)) + \\\" and Dyadics.\\\")\",\n \"def dot(vector01,vector02):\\r\\n result = 0\\r\\n # creates the initial value for the result of the dot product\\r\\n for z in range(len(vector01)):\\r\\n # for loop which continues as long as there are more values left in the vector \\r\\n result += vector01[z]*vector02[z]\\r\\n # the new result is found to be the corresponding values in each vector multiplied and then added together \\r\\n return result\",\n \"def dot4(a,b):\\n return a[0]*b[0]+a[1]*b[1]+a[2]*b[2]+a[3]*b[3]\",\n \"def outer_product(x):\\n return keras.backend.batch_dot(\\n x[0]\\n , x[1]\\n , axes=[1,1]\\n ) / x[0].get_shape().as_list()[1]\",\n \"def __mul__(self, other): \\n if isinstance(other, Iterable):\\n # dot product\\n return self.x * other[0] + self.y * other[1]\\n else:\\n # scalar product\\n return Vector(self.x * other, self.y * other)\",\n \"def test_dot_different_sizes():\\n dot(Vector(1.0), Vector(2.0, 3.0))\",\n \"def rdot(a, b): # pragma: no cover\\n a, b = a.reshape((1, -1)), b.reshape((-1, 1))\\n return (a @ b).item()\",\n \"def dot_prod(u,v):\\n each_product = []\\n for i in range(len(u)):\\n each_product.append(u[i] * v[i])\\n return sum(each_product)\",\n \"def trace_dot(a, b):\\r\\n return np.sum(a * b)\",\n \"def dot(v,w):\\n return sum(v_i * w_i for v_i,w_i in zip(v,w))\",\n \"def dot(v, w):\\n return sum(v_i * w_i for v_i, w_i in zip(v, w))\",\n \"def dot(v, w):\\n return sum(v_i * w_i for v_i, w_i in zip(v, w))\",\n \"def dot(v, w):\\n return sum(v_i * w_i for v_i, w_i in zip(v, w))\",\n \"def dot(v, w):\\n return sum(v_i * w_i for v_i, w_i in zip(v, w))\",\n \"def dot(v, w):\\n return sum(v_i * w_i for v_i, w_i in zip(v, w))\",\n \"def mdot(*args):\\n import numpy as np\\n import sympy\\n import operator\\n from functools import reduce\\n is_numpy = lambda x: isinstance(x, np.ndarray)\\n is_sympy = lambda x: isinstance(x, (sympy.Matrix, sympy.ImmutableMatrix))\\n\\n if is_numpy(args[0]):\\n if not all(map(is_numpy, args)):\\n raise TypeError(set(map(type, args)))\\n return reduce(np.dot, args)\\n\\n elif is_sympy(args[0]):\\n if not all(map(is_sympy, args)):\\n raise TypeError(set(map(type, args)))\\n return reduce(operator.mul, args)\\n\\n else:\\n raise TypeError(type(args[0]))\",\n \"def _listdot(d1, d2):\\n return [np.dot(x[0].T, x[1]) for x in zip(d1, d2)]\",\n \"def batch_dot(x, y, axes=None):\\n if isinstance(axes, int):\\n axes = (axes, axes)\\n x_ndim = ndim(x)\\n y_ndim = ndim(y)\\n if x_ndim > y_ndim:\\n diff = x_ndim - y_ndim\\n y = tf.reshape(y, tf.concat([tf.shape(y), [1] * (diff)], axis=0))\\n elif y_ndim > x_ndim:\\n diff = y_ndim - x_ndim\\n x = tf.reshape(x, tf.concat([tf.shape(x), [1] * (diff)], axis=0))\\n else:\\n diff = 0\\n if ndim(x) == 2 and ndim(y) == 2:\\n if axes[0] == axes[1]:\\n out = tf.reduce_sum(tf.multiply(x, y), axes[0])\\n else:\\n out = tf.reduce_sum(tf.multiply(\\n tf.transpose(x, [1, 0]), y), axes[1])\\n else:\\n if axes is not None:\\n adj_x = None if axes[0] == ndim(x) - 1 else True\\n adj_y = True if axes[1] == ndim(y) - 1 else None\\n else:\\n adj_x = None\\n adj_y = None\\n out = tf.matmul(x, y, adjoint_a=adj_x, adjoint_b=adj_y)\\n if diff:\\n if x_ndim > y_ndim:\\n idx = x_ndim + y_ndim - 3\\n else:\\n idx = x_ndim - 1\\n out = tf.squeeze(out, list(range(idx, idx + diff)))\\n if ndim(out) == 1:\\n out = tf.expand_dims(out, 1)\\n return out\",\n \"def dot(left, right):\\n if sp.sparse.issparse(right) or sp.sparse.issparse(left):\\n result = left*right\\n else:\\n result = left.dot(right)\\n return result\",\n \"def dot(v,w):\\n return sum(v_i * w_i\\n for v_i, w_i in zip(v,w))\",\n \"def dot(v, w):\\n return sum(v_i * w_i\\n for v_i, w_i in zip(v, w))\",\n \"def batch_dot(x, y, axes=None):\\r\\n if isinstance(axes, int):\\r\\n axes = (axes, axes)\\r\\n x_ndim = K.ndim(x)\\r\\n y_ndim = K.ndim(y)\\r\\n if x_ndim > y_ndim:\\r\\n diff = x_ndim - y_ndim\\r\\n y = tf.reshape(y, tf.concat([tf.shape(y), [1] * (diff)], axis=0))\\r\\n elif y_ndim > x_ndim:\\r\\n diff = y_ndim - x_ndim\\r\\n x = tf.reshape(x, tf.concat([tf.shape(x), [1] * (diff)], axis=0))\\r\\n else:\\r\\n diff = 0\\r\\n if K.ndim(x) == 2 and K.ndim(y) == 2:\\r\\n if axes[0] == axes[1]:\\r\\n out = tf.reduce_sum(tf.multiply(x, y), axes[0])\\r\\n else:\\r\\n out = tf.reduce_sum(tf.multiply(\\r\\n tf.transpose(x, [1, 0]), y), axes[1])\\r\\n else:\\r\\n if axes is not None:\\r\\n adj_x = None if axes[0] == K.ndim(x) - 1 else True\\r\\n adj_y = True if axes[1] == K.ndim(y) - 1 else None\\r\\n else:\\r\\n adj_x = None\\r\\n adj_y = None\\r\\n out = tf.matmul(x, y, adjoint_a=adj_x, adjoint_b=adj_y)\\r\\n if diff:\\r\\n if x_ndim > y_ndim:\\r\\n idx = x_ndim + y_ndim - 3\\r\\n else:\\r\\n idx = x_ndim - 1\\r\\n out = tf.squeeze(out, list(range(idx, idx + diff)))\\r\\n if K.ndim(out) == 1:\\r\\n out = tf.expand_dims(out, 1)\\r\\n return out\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7651723","0.76122725","0.75896275","0.75178","0.74978065","0.74902385","0.74902385","0.74902385","0.74902385","0.7466889","0.74378735","0.7429341","0.7418364","0.73810273","0.7376632","0.7343613","0.7331493","0.73104995","0.7309816","0.72749436","0.727089","0.7263545","0.7240149","0.72044","0.7199408","0.71944374","0.71932536","0.7177918","0.7156706","0.71553546","0.7136505","0.7128171","0.7109221","0.7108442","0.7096206","0.7046016","0.70341146","0.7022157","0.69888645","0.69772124","0.69640505","0.6961708","0.69530493","0.69481087","0.69216186","0.6920953","0.6886735","0.6885818","0.6851303","0.6838759","0.68342364","0.6825409","0.6819291","0.68099725","0.67929435","0.679264","0.6774491","0.6772367","0.67666185","0.6762248","0.6748303","0.6738692","0.67251974","0.6720701","0.67147034","0.671304","0.6710624","0.66991067","0.669852","0.6683376","0.6673163","0.6661936","0.6657343","0.66473526","0.6633566","0.6610409","0.6609478","0.6606761","0.6606187","0.6589745","0.6589658","0.6583372","0.658224","0.65819347","0.65805817","0.6575263","0.6558872","0.6553317","0.65523064","0.65523064","0.65523064","0.65523064","0.65523064","0.65470576","0.65454245","0.65409184","0.6535372","0.65296793","0.6525566","0.6499642"],"string":"[\n \"0.7651723\",\n \"0.76122725\",\n \"0.75896275\",\n \"0.75178\",\n \"0.74978065\",\n \"0.74902385\",\n \"0.74902385\",\n \"0.74902385\",\n \"0.74902385\",\n \"0.7466889\",\n \"0.74378735\",\n \"0.7429341\",\n \"0.7418364\",\n \"0.73810273\",\n \"0.7376632\",\n \"0.7343613\",\n \"0.7331493\",\n \"0.73104995\",\n \"0.7309816\",\n \"0.72749436\",\n \"0.727089\",\n \"0.7263545\",\n \"0.7240149\",\n \"0.72044\",\n \"0.7199408\",\n \"0.71944374\",\n \"0.71932536\",\n \"0.7177918\",\n \"0.7156706\",\n \"0.71553546\",\n \"0.7136505\",\n \"0.7128171\",\n \"0.7109221\",\n \"0.7108442\",\n \"0.7096206\",\n \"0.7046016\",\n \"0.70341146\",\n \"0.7022157\",\n \"0.69888645\",\n \"0.69772124\",\n \"0.69640505\",\n \"0.6961708\",\n \"0.69530493\",\n \"0.69481087\",\n \"0.69216186\",\n \"0.6920953\",\n \"0.6886735\",\n \"0.6885818\",\n \"0.6851303\",\n \"0.6838759\",\n \"0.68342364\",\n \"0.6825409\",\n \"0.6819291\",\n \"0.68099725\",\n \"0.67929435\",\n \"0.679264\",\n \"0.6774491\",\n \"0.6772367\",\n \"0.67666185\",\n \"0.6762248\",\n \"0.6748303\",\n \"0.6738692\",\n \"0.67251974\",\n \"0.6720701\",\n \"0.67147034\",\n \"0.671304\",\n \"0.6710624\",\n \"0.66991067\",\n \"0.669852\",\n \"0.6683376\",\n \"0.6673163\",\n \"0.6661936\",\n \"0.6657343\",\n \"0.66473526\",\n \"0.6633566\",\n \"0.6610409\",\n \"0.6609478\",\n \"0.6606761\",\n \"0.6606187\",\n \"0.6589745\",\n \"0.6589658\",\n \"0.6583372\",\n \"0.658224\",\n \"0.65819347\",\n \"0.65805817\",\n \"0.6575263\",\n \"0.6558872\",\n \"0.6553317\",\n \"0.65523064\",\n \"0.65523064\",\n \"0.65523064\",\n \"0.65523064\",\n \"0.65523064\",\n \"0.65470576\",\n \"0.65454245\",\n \"0.65409184\",\n \"0.6535372\",\n \"0.65296793\",\n \"0.6525566\",\n \"0.6499642\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7535402"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":81784,"cells":{"query":{"kind":"string","value":"Keras Layer that implements an Attention mechanism for temporal data. Supports Masking."},"document":{"kind":"string","value":"def __init__(self,\n W_regularizer=None, b_regularizer=None,\n W_constraint=None, b_constraint=None,\n bias=True,\n return_attention=False,\n **kwargs):\n self.supports_masking = True\n self.return_attention = return_attention\n self.init = initializers.get('glorot_uniform')\n\n self.W_regularizer = regularizers.get(W_regularizer)\n self.b_regularizer = regularizers.get(b_regularizer)\n\n self.W_constraint = constraints.get(W_constraint)\n self.b_constraint = constraints.get(b_constraint)\n\n self.bias = bias\n super(Attention, self).__init__(**kwargs)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _Attention(self, name, is_causal=True):\n p = self.params\n tr_atten_p = TransformerAttentionLayer.Params().Set(\n name='transformer_atten',\n input_dim=p.model_dim,\n hidden_dim=p.attention_hidden_dim or p.model_dim,\n is_masked=is_causal,\n num_heads=p.num_heads,\n residual_dropout_prob=p.residual_dropout_prob,\n atten_dropout_prob=p.atten_dropout_prob,\n fprop_dtype=p.fprop_dtype,\n add_unnormalized_input=p.selfatten_add_unnormalized_input,\n )\n tr_atten_p.atten_tpl.use_bias = p.use_bias\n tr_atten_p.atten_tpl.enable_value_proj = p.selfatten_enable_value_proj\n tr_atten_p.atten_tpl.enable_query_scale = p.enable_query_scale\n tr_atten_p.atten_tpl.enable_per_dim_scale = p.enable_per_dim_scale\n tr_atten_p.atten_tpl.device_mesh = p.device_mesh\n tr_atten_p.atten_tpl.weight_split_dims_mapping = (\n p.weight_split_dims_mapping.dnh)\n tr_atten_p.atten_tpl.activation_split_dims_mapping.blnh = (\n p.activation_split_dims_mapping.blnh)\n tr_atten_p.atten_tpl.activation_split_dims_mapping.bld = (\n p.activation_split_dims_mapping.bld)\n if p.deterministic_dropout:\n tr_atten_p.dropout_tpl = layers.DeterministicDropoutLayer.Params()\n tr_atten_p.atten_p.dropout_tpl = layers.DeterministicDropoutLayer.Params()\n\n return self._Graph(\n name,\n ['i'], # input NestedMap with {vec, paddings}\n ['o'], # output NestedMap with {vec, paddings}\n ('i.vec->split_i',\n self.MeshSplit('input_split', p.activation_split_dims_mapping.bld)),\n ('split_i,split_i,i.paddings->o.vec,unused_prob', tr_atten_p),\n ('i.paddings->o.paddings', self._Id('id')))","def attention_mask(model, x):\n config = model.config\n input_mask = model.inputs[\"input_mask\"]\n final_mask = model.builder.customOp(opName=\"AttentionMask\",\n opVersion=1,\n domain=\"ai.graphcore\",\n inputs=[input_mask, x],\n attributes={\"dataType\": model.config.popart_dtype})[0]\n final_mask = model.detach(final_mask)\n return final_mask","def add_mask_layer(self):\n return Masking(mask_value=self.mask_value, input_shape=(self.max_sequence_size, 1))","def make_attention_lstm():\n from tensorflow.keras import activations\n from tensorflow.keras import backend as K\n from tensorflow.keras import constraints, initializers, regularizers\n\n # from keras.legacy import interfaces\n from tensorflow.keras.layers import RNN, InputSpec, Layer\n\n def _time_distributed_dense(\n x,\n w,\n b=None,\n dropout=None,\n input_dim=None,\n output_dim=None,\n timesteps=None,\n training=None,\n ):\n \"\"\"Apply `y . w + b` for every temporal slice y of x.\n\n # Arguments\n x: input tensor.\n w: weight matrix.\n b: optional bias vector.\n dropout: wether to apply dropout (same dropout mask\n for every temporal slice of the input).\n input_dim: integer; optional dimensionality of the input.\n output_dim: integer; optional dimensionality of the output.\n timesteps: integer; optional number of timesteps.\n training: training phase tensor or boolean.\n # Returns\n Output tensor.\n \"\"\"\n if not input_dim:\n input_dim = K.shape(x)[2]\n if not timesteps:\n timesteps = K.shape(x)[1]\n if not output_dim:\n output_dim = K.int_shape(w)[1]\n\n if dropout is not None and 0.0 < dropout < 1.0:\n # apply the same dropout pattern at every timestep\n ones = K.ones_like(K.reshape(x[:, 0, :], (-1, input_dim)))\n dropout_matrix = K.dropout(ones, dropout)\n expanded_dropout_matrix = K.repeat(dropout_matrix, timesteps)\n x = K.in_train_phase(x * expanded_dropout_matrix, x, training=training)\n\n # collapse time dimension and batch dimension together\n x = K.reshape(x, (-1, input_dim))\n x = K.dot(x, w)\n if b is not None:\n x = K.bias_add(x, b)\n # reshape to 3D tensor\n if K.backend() == \"tensorflow\":\n x = K.reshape(x, K.stack([-1, timesteps, output_dim]))\n x.set_shape([None, None, output_dim])\n else:\n x = K.reshape(x, (-1, timesteps, output_dim))\n return x\n\n class AttentionLSTMCell(Layer):\n \"\"\"Long-Short Term Memory unit - with Attention.\n\n # Arguments\n units: Positive integer, dimensionality of the output space.\n activation: Activation function to use\n (see [activations](keras/activations.md)).\n If you pass None, no activation is applied\n (ie. \"linear\" activation: `a(x) = x`).\n recurrent_activation: Activation function to use\n for the recurrent step\n (see [activations](keras/activations.md)).\n attention_activation: Activation function to use\n for the attention step. If you pass None, no activation is applied\n (ie. \"linear\" activation: `a(x) = x`).\n (see [activations](keras/activations.md)).\n use_bias: Boolean, whether the layer uses a bias vector.\n kernel_initializer: Initializer for the `kernel` weights matrix,\n used for the linear transformation of the inputs.\n (see [initializers](../initializers.md)).\n recurrent_initializer: Initializer for the `recurrent_kernel`\n weights matrix,\n used for the linear transformation of the recurrent state.\n (see [initializers](../initializers.md)).\n bias_initializer: Initializer for the bias vector\n (see [initializers](../initializers.md)).\n attention_initializer: Initializer for the `attention_kernel` weights\n matrix, used for the linear transformation of the inputs.\n (see [initializers](../initializers.md)).\n use_chrono_initialization: Boolean.\n If True, add 1 to the bias of the forget gate at initialization.\n Setting it to true will also force `bias_initializer=\"zeros\"`.\n This is recommended in [Jozefowicz et al.]\n (http://www.jmlr.org/proceedings/papers/v37/jozefowicz15.pdf)\n kernel_regularizer: Regularizer function applied to\n the `kernel` weights matrix\n (see [regularizer](../regularizers.md)).\n recurrent_regularizer: Regularizer function applied to\n the `recurrent_kernel` weights matrix\n (see [regularizer](../regularizers.md)).\n bias_regularizer: Regularizer function applied to the bias vector\n (see [regularizer](../regularizers.md)).\n activity_regularizer: Regularizer function applied to\n the output of the layer (its \"activation\").\n (see [regularizer](../regularizers.md)).\n attention_regularizer: Regularizer function applied to\n the `attention_kernel` weights matrix\n (see [regularizer](../regularizers.md)).\n kernel_constraint: Constraint function applied to\n the `kernel` weights matrix\n (see [constraints](../constraints.md)).\n recurrent_constraint: Constraint function applied to\n the `recurrent_kernel` weights matrix\n (see [constraints](../constraints.md)).\n bias_constraint: Constraint function applied to the bias vector\n (see [constraints](../constraints.md)).\n attention_constraint: Constraint function applied to\n the `attention_kernel` weights matrix\n (see [constraints](../constraints.md)).\n dropout: Float between 0 and 1.\n Fraction of the units to drop for\n the linear transformation of the inputs.\n recurrent_dropout: Float between 0 and 1.\n Fraction of the units to drop for\n the linear transformation of the recurrent state.\n return_attention: Returns the attention vector instead of\n the internal state.\n # References\n - [Long short-term memory]\n (http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf)\n (original 1997 paper)\n - [Learning to forget: Continual prediction with LSTM]\n (http://www.mitpressjournals.org/doi/pdf/10.1162/089976600300015015)\n - [Supervised sequence labeling with recurrent neural networks]\n (http://www.cs.toronto.edu/~graves/preprint.pdf)\n - [A Theoretically Grounded Application of Dropout\n in Recurrent Neural Networks]\n (http://arxiv.org/abs/1512.05287)\n - [Bahdanau, Cho & Bengio (2014),\n \"Neural Machine Translation by Jointly Learning to Align and Translate\"]\n (https://arxiv.org/pdf/1409.0473.pdf)\n - [Xu, Ba, Kiros, Cho, Courville, Salakhutdinov, Zemel & Bengio (2016)\n \"Show, Attend and Tell: Neural Image Caption Generation\n with Visual Attention\"]\n (http://arxiv.org/pdf/1502.03044.pdf)\n \"\"\"\n\n _tags = {\"python_dependencies\": \"tensorflow\"}\n\n def __init__(\n self,\n units,\n activation=\"tanh\",\n recurrent_activation=\"hard_sigmoid\",\n attention_activation=\"tanh\",\n use_bias=True,\n kernel_initializer=\"glorot_uniform\",\n recurrent_initializer=\"orthogonal\",\n attention_initializer=\"orthogonal\",\n bias_initializer=\"zeros\",\n unit_forget_bias=True,\n kernel_regularizer=None,\n recurrent_regularizer=None,\n bias_regularizer=None,\n activity_regularizer=None,\n attention_regularizer=None,\n kernel_constraint=None,\n recurrent_constraint=None,\n bias_constraint=None,\n attention_constraint=None,\n dropout=0.0,\n recurrent_dropout=0.0,\n return_attention=False,\n implementation=1,\n **kwargs,\n ):\n super().__init__(**kwargs)\n self.input_spec = [InputSpec(ndim=2)]\n self.units = units\n self.activation = activations.get(activation)\n self.recurrent_activation = activations.get(recurrent_activation)\n self.attention_activation = activations.get(attention_activation)\n self.use_bias = use_bias\n\n self.kernel_initializer = initializers.get(kernel_initializer)\n self.recurrent_initializer = initializers.get(recurrent_initializer)\n self.attention_initializer = initializers.get(attention_initializer)\n self.bias_initializer = initializers.get(bias_initializer)\n self.unit_forget_bias = unit_forget_bias\n\n self.kernel_regularizer = regularizers.get(kernel_regularizer)\n self.recurrent_regularizer = regularizers.get(recurrent_regularizer)\n self.bias_regularizer = regularizers.get(bias_regularizer)\n self.activity_regularizer = regularizers.get(activity_regularizer)\n self.attention_regularizer = regularizers.get(attention_regularizer)\n\n self.kernel_constraint = constraints.get(kernel_constraint)\n self.recurrent_constraint = constraints.get(recurrent_constraint)\n self.bias_constraint = constraints.get(bias_constraint)\n self.attention_constraint = constraints.get(attention_constraint)\n\n self.dropout = min(1.0, max(0.0, dropout))\n self.recurrent_dropout = min(1.0, max(0.0, recurrent_dropout))\n self.return_attention = return_attention\n self._dropout_mask = None\n self._recurrent_dropout_mask = None\n self.implementation = implementation\n self.state_spec = [\n InputSpec(shape=(None, self.units)),\n InputSpec(shape=(None, self.units)),\n ]\n self.state_size = (self.units, self.units)\n\n def build(self, input_shape):\n \"\"\"Build the AttentionLSTMCell object.\"\"\"\n if hasattr(self, \"timesteps\") and self.timesteps is not None:\n self.timestep_dim = self.timesteps\n else:\n self.timestep_dim = 1 # input_shape[0]\n\n self.input_dim = input_shape[-1]\n\n self.kernel = self.add_weight(\n shape=(self.input_dim, self.units * 4),\n name=\"kernel\",\n initializer=self.kernel_initializer,\n regularizer=self.kernel_regularizer,\n constraint=self.kernel_constraint,\n )\n self.recurrent_kernel = self.add_weight(\n shape=(self.units, self.units * 4),\n name=\"recurrent_kernel\",\n initializer=self.recurrent_initializer,\n regularizer=self.recurrent_regularizer,\n constraint=self.recurrent_constraint,\n )\n\n # add attention kernel\n self.attention_kernel = self.add_weight(\n shape=(self.input_dim, self.units * 4),\n name=\"attention_kernel\",\n initializer=self.attention_initializer,\n regularizer=self.attention_regularizer,\n constraint=self.attention_constraint,\n )\n\n # add attention weights\n # weights for attention model\n self.attention_weights = self.add_weight(\n shape=(self.input_dim, self.units),\n name=\"attention_W\",\n initializer=self.attention_initializer,\n regularizer=self.attention_regularizer,\n constraint=self.attention_constraint,\n )\n\n self.attention_recurrent_weights = self.add_weight(\n shape=(self.units, self.units),\n name=\"attention_U\",\n initializer=self.recurrent_initializer,\n regularizer=self.recurrent_regularizer,\n constraint=self.recurrent_constraint,\n )\n\n if self.use_bias:\n if self.unit_forget_bias:\n\n def bias_initializer(shape, *args, **kwargs):\n return K.concatenate(\n [\n self.bias_initializer((self.units,), *args, **kwargs),\n initializers.Ones()((self.units,), *args, **kwargs),\n self.bias_initializer(\n (self.units * 2,), *args, **kwargs\n ),\n ]\n )\n\n else:\n bias_initializer = self.bias_initializer\n self.bias = self.add_weight(\n shape=(self.units * 4,),\n name=\"bias\",\n initializer=bias_initializer,\n regularizer=self.bias_regularizer,\n constraint=self.bias_constraint,\n )\n\n self.attention_bias = self.add_weight(\n shape=(self.units,),\n name=\"attention_b\",\n initializer=self.bias_initializer,\n regularizer=self.bias_regularizer,\n constraint=self.bias_constraint,\n )\n\n self.attention_recurrent_bias = self.add_weight(\n shape=(self.units, 1),\n name=\"attention_v\",\n initializer=self.bias_initializer,\n regularizer=self.bias_regularizer,\n constraint=self.bias_constraint,\n )\n else:\n self.bias = None\n self.attention_bias = None\n self.attention_recurrent_bias = None\n\n self.kernel_i = self.kernel[:, : self.units]\n self.kernel_f = self.kernel[:, self.units : self.units * 2]\n self.kernel_c = self.kernel[:, self.units * 2 : self.units * 3]\n self.kernel_o = self.kernel[:, self.units * 3 :]\n\n self.recurrent_kernel_i = self.recurrent_kernel[:, : self.units]\n self.recurrent_kernel_f = self.recurrent_kernel[\n :, self.units : self.units * 2\n ]\n self.recurrent_kernel_c = self.recurrent_kernel[\n :, self.units * 2 : self.units * 3\n ]\n self.recurrent_kernel_o = self.recurrent_kernel[:, self.units * 3 :]\n\n self.attention_i = self.attention_kernel[:, : self.units]\n self.attention_f = self.attention_kernel[:, self.units : self.units * 2]\n self.attention_c = self.attention_kernel[:, self.units * 2 : self.units * 3]\n self.attention_o = self.attention_kernel[:, self.units * 3 :]\n\n if self.use_bias:\n self.bias_i = self.bias[: self.units]\n self.bias_f = self.bias[self.units : self.units * 2]\n self.bias_c = self.bias[self.units * 2 : self.units * 3]\n self.bias_o = self.bias[self.units * 3 :]\n else:\n self.bias_i = None\n self.bias_f = None\n self.bias_c = None\n self.bias_o = None\n\n self.built = True\n\n def _generate_dropout_mask(self, inputs, training=None):\n if 0 < self.dropout < 1:\n ones = K.ones_like(K.squeeze(inputs[:, 0:1, :], axis=1))\n\n def dropped_inputs():\n return K.dropout(ones, self.dropout)\n\n self._dropout_mask = [\n K.in_train_phase(dropped_inputs, ones, training=training)\n for _ in range(4)\n ]\n else:\n self._dropout_mask = None\n\n def _generate_recurrent_dropout_mask(self, inputs, training=None):\n if 0 < self.recurrent_dropout < 1:\n ones = K.ones_like(K.reshape(inputs[:, 0, 0], (-1, 1)))\n ones = K.tile(ones, (1, self.units))\n\n def dropped_inputs():\n return K.dropout(ones, self.dropout)\n\n self._recurrent_dropout_mask = [\n K.in_train_phase(dropped_inputs, ones, training=training)\n for _ in range(4)\n ]\n else:\n self._recurrent_dropout_mask = None\n\n def call(self, inputs, states, training=None):\n \"\"\"Call the AttentionLSTMCell.\"\"\"\n # dropout matrices for input units\n dp_mask = self._dropout_mask\n # dropout matrices for recurrent units\n rec_dp_mask = self._recurrent_dropout_mask\n\n h_tm1 = states[0] # previous memory state\n c_tm1 = states[1] # previous carry state\n\n # alignment model\n h_att = K.repeat(h_tm1, self.timestep_dim)\n att = _time_distributed_dense(\n inputs,\n self.attention_weights,\n self.attention_bias,\n input_dim=self.input_dim,\n output_dim=self.units,\n timesteps=self.timestep_dim,\n )\n attention_ = self.attention_activation(\n K.dot(h_att, self.attention_recurrent_weights) + att\n ) # energy\n attention_ = K.squeeze(\n K.dot(attention_, self.attention_recurrent_bias), 2\n ) # energy\n\n alpha = K.exp(attention_)\n\n if dp_mask is not None:\n alpha *= dp_mask[0]\n\n alpha /= K.sum(alpha, axis=1, keepdims=True)\n alpha_r = K.repeat(alpha, self.input_dim)\n alpha_r = K.permute_dimensions(alpha_r, (0, 2, 1))\n\n # make context vector (soft attention after Bahdanau et al.)\n z_hat = inputs * alpha_r\n # context_sequence = z_hat\n z_hat = K.sum(z_hat, axis=1)\n\n if self.implementation == 1:\n if 0 < self.dropout < 1.0:\n inputs_i = inputs * dp_mask[0]\n inputs_f = inputs * dp_mask[1]\n inputs_c = inputs * dp_mask[2]\n inputs_o = inputs * dp_mask[3]\n else:\n inputs_i = inputs\n inputs_f = inputs\n inputs_c = inputs\n inputs_o = inputs\n x_i = K.dot(inputs_i, self.kernel_i)\n x_f = K.dot(inputs_f, self.kernel_f)\n x_c = K.dot(inputs_c, self.kernel_c)\n x_o = K.dot(inputs_o, self.kernel_o)\n if self.use_bias:\n x_i = K.bias_add(x_i, self.bias_i)\n x_f = K.bias_add(x_f, self.bias_f)\n x_c = K.bias_add(x_c, self.bias_c)\n x_o = K.bias_add(x_o, self.bias_o)\n\n if 0 < self.recurrent_dropout < 1.0:\n h_tm1_i = h_tm1 * rec_dp_mask[0]\n h_tm1_f = h_tm1 * rec_dp_mask[1]\n h_tm1_c = h_tm1 * rec_dp_mask[2]\n h_tm1_o = h_tm1 * rec_dp_mask[3]\n else:\n h_tm1_i = h_tm1\n h_tm1_f = h_tm1\n h_tm1_c = h_tm1\n h_tm1_o = h_tm1\n i = self.recurrent_activation(\n x_i\n + K.dot(h_tm1_i, self.recurrent_kernel_i)\n + K.dot(z_hat, self.attention_i)\n )\n f = self.recurrent_activation(\n x_f\n + K.dot(h_tm1_f, self.recurrent_kernel_f)\n + K.dot(z_hat, self.attention_f)\n )\n c = f * c_tm1 + i * self.activation(\n x_c\n + K.dot(h_tm1_c, self.recurrent_kernel_c)\n + K.dot(z_hat, self.attention_c)\n )\n o = self.recurrent_activation(\n x_o\n + K.dot(h_tm1_o, self.recurrent_kernel_o)\n + K.dot(z_hat, self.attention_o)\n )\n else:\n if 0.0 < self.dropout < 1.0:\n inputs *= dp_mask[0]\n z = K.dot(inputs, self.kernel)\n if 0.0 < self.recurrent_dropout < 1.0:\n h_tm1 *= rec_dp_mask[0]\n z += K.dot(h_tm1, self.recurrent_kernel)\n z += K.dot(z_hat, self.attention_kernel)\n\n if self.use_bias:\n z = K.bias_add(z, self.bias)\n\n z0 = z[:, : self.units]\n z1 = z[:, self.units : 2 * self.units]\n z2 = z[:, 2 * self.units : 3 * self.units]\n z3 = z[:, 3 * self.units :]\n\n i = self.recurrent_activation(z0)\n f = self.recurrent_activation(z1)\n c = f * c_tm1 + i * self.activation(z2)\n o = self.recurrent_activation(z3)\n\n h = o * self.activation(c)\n if 0 < self.dropout + self.recurrent_dropout:\n if training is None:\n h._uses_learning_phase = True\n return h, [h, c]\n\n class AttentionLSTM(RNN):\n \"\"\"Long-Short Term Memory unit - with Attention.\n\n # Arguments\n units: Positive integer, dimensionality of the output space.\n activation: Activation function to use\n (see [activations](keras/activations.md)).\n If you pass None, no activation is applied\n (ie. \"linear\" activation: `a(x) = x`).\n recurrent_activation: Activation function to use\n for the recurrent step\n (see [activations](keras/activations.md)).\n attention_activation: Activation function to use\n for the attention step. If you pass None, no activation is applied\n (ie. \"linear\" activation: `a(x) = x`).\n (see [activations](keras/activations.md)).\n use_bias: Boolean, whether the layer uses a bias vector.\n kernel_initializer: Initializer for the `kernel` weights matrix,\n used for the linear transformation of the inputs.\n (see [initializers](../initializers.md)).\n recurrent_initializer: Initializer for the `recurrent_kernel`\n weights matrix,\n used for the linear transformation of the recurrent state.\n (see [initializers](../initializers.md)).\n bias_initializer: Initializer for the bias vector\n (see [initializers](../initializers.md)).\n attention_initializer: Initializer for the `attention_kernel` weights\n matrix, used for the linear transformation of the inputs.\n (see [initializers](../initializers.md)).\n use_chrono_initialization: Boolean.\n If True, add 1 to the bias of the forget gate at initialization.\n Setting it to true will also force `bias_initializer=\"zeros\"`.\n This is recommended in [Jozefowicz et al.]\n (http://www.jmlr.org/proceedings/papers/v37/jozefowicz15.pdf)\n kernel_regularizer: Regularizer function applied to\n the `kernel` weights matrix\n (see [regularizer](../regularizers.md)).\n recurrent_regularizer: Regularizer function applied to\n the `recurrent_kernel` weights matrix\n (see [regularizer](../regularizers.md)).\n bias_regularizer: Regularizer function applied to the bias vector\n (see [regularizer](../regularizers.md)).\n activity_regularizer: Regularizer function applied to\n the output of the layer (its \"activation\").\n (see [regularizer](../regularizers.md)).\n attention_regularizer: Regularizer function applied to\n the `attention_kernel` weights matrix\n (see [regularizer](../regularizers.md)).\n kernel_constraint: Constraint function applied to\n the `kernel` weights matrix\n (see [constraints](../constraints.md)).\n recurrent_constraint: Constraint function applied to\n the `recurrent_kernel` weights matrix\n (see [constraints](../constraints.md)).\n bias_constraint: Constraint function applied to the bias vector\n (see [constraints](../constraints.md)).\n attention_constraint: Constraint function applied to\n the `attention_kernel` weights matrix\n (see [constraints](../constraints.md)).\n dropout: Float between 0 and 1.\n Fraction of the units to drop for\n the linear transformation of the inputs.\n recurrent_dropout: Float between 0 and 1.\n Fraction of the units to drop for\n the linear transformation of the recurrent state.\n implementation: Implementation mode, either 1 or 2.\n return_sequences: Boolean. Whether to return the last output.\n in the output sequence, or the full sequence.\n return_state: Boolean. Whether to return the last state\n in addition to the output.\n return_attention: Returns the attention vector instead of\n the internal state.\n go_backwards: Boolean (default False).\n If True, process the input sequence backwards and return the\n reversed sequence.\n stateful: Boolean (default False). If True, the last state\n for each sample at index i in a batch will be used as initial\n state for the sample of index i in the following batch.\n unroll: Boolean (default False).\n If True, the network will be unrolled,\n else a symbolic loop will be used.\n Unrolling can speed-up a RNN,\n although it tends to be more memory-intensive.\n Unrolling is only suitable for short sequences.\n # References\n - [Long short-term memory]\n (http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf)\n (original 1997 paper)\n - [Learning to forget: Continual prediction with LSTM]\n (http://www.mitpressjournals.org/doi/pdf/10.1162/089976600300015015)\n - [Supervised sequence labeling with recurrent neural networks]\n (http://www.cs.toronto.edu/~graves/preprint.pdf)\n - [A Theoretically Grounded Application of Dropout\n in Recurrent Neural Networks]\n (http://arxiv.org/abs/1512.05287)\n - [Bahdanau, Cho & Bengio (2014)\n \"Neural Machine Translation by Jointly Learning to Align and Translate\"]\n (https://arxiv.org/pdf/1409.0473.pdf)\n - [Xu, Ba, Kiros, Cho, Courville, Salakhutdinov, Zemel & Bengio (2016)\n \"Show, Attend and Tell: Neural Image Caption Generation\n with Visual Attention\"]\n (http://arxiv.org/pdf/1502.03044.pdf)\n \"\"\"\n\n _tags = {\"python_dependencies\": \"tensorflow\"}\n\n # '@interfaces.legacy_recurrent_support\n def __init__(\n self,\n units,\n activation=\"tanh\",\n recurrent_activation=\"hard_sigmoid\",\n attention_activation=\"tanh\",\n use_bias=True,\n kernel_initializer=\"glorot_uniform\",\n recurrent_initializer=\"orthogonal\",\n attention_initializer=\"orthogonal\",\n bias_initializer=\"zeros\",\n unit_forget_bias=True,\n kernel_regularizer=None,\n recurrent_regularizer=None,\n bias_regularizer=None,\n activity_regularizer=None,\n attention_regularizer=None,\n kernel_constraint=None,\n recurrent_constraint=None,\n bias_constraint=None,\n attention_constraint=None,\n dropout=0.0,\n recurrent_dropout=0.0,\n implementation=1,\n return_sequences=False,\n return_state=False,\n return_attention=False,\n go_backwards=False,\n stateful=False,\n unroll=False,\n **kwargs,\n ):\n import warnings\n\n if implementation == 0:\n warnings.warn(\n \"`implementation=0` has been deprecated, \"\n \"and now defaults to `implementation=1`.\"\n \"Please update your layer call.\",\n stacklevel=2,\n )\n implementation = 1\n\n if K.backend() == \"cntk\":\n if not kwargs.get(\"unroll\") and (dropout > 0 or recurrent_dropout > 0):\n warnings.warn(\n \"RNN dropout is not supported with the CNTK backend \"\n \"when using dynamic RNNs (i.e. non-unrolled). \"\n \"You can either set `unroll=True`, \"\n \"set `dropout` and `recurrent_dropout` to 0, \"\n \"or use a different backend.\",\n stacklevel=2,\n )\n dropout = 0.0\n recurrent_dropout = 0.0\n\n cell = AttentionLSTMCell(\n units,\n activation=activation,\n recurrent_activation=recurrent_activation,\n attention_activation=attention_activation,\n use_bias=use_bias,\n kernel_initializer=kernel_initializer,\n recurrent_initializer=recurrent_initializer,\n attention_initializer=attention_initializer,\n bias_initializer=bias_initializer,\n unit_forget_bias=unit_forget_bias,\n kernel_regularizer=kernel_regularizer,\n recurrent_regularizer=recurrent_regularizer,\n bias_regularizer=bias_regularizer,\n activity_regularizer=activity_regularizer,\n attention_regularizer=attention_regularizer,\n kernel_constraint=kernel_constraint,\n recurrent_constraint=recurrent_constraint,\n bias_constraint=bias_constraint,\n attention_constraint=attention_constraint,\n dropout=dropout,\n recurrent_dropout=recurrent_dropout,\n return_attention=return_attention,\n implementation=implementation,\n )\n super().__init__(\n cell,\n return_sequences=return_sequences,\n return_state=return_state,\n go_backwards=go_backwards,\n stateful=stateful,\n unroll=unroll,\n **kwargs,\n )\n self.return_attention = return_attention\n\n def build(self, input_shape):\n \"\"\"Build the AttentionLSTM object.\"\"\"\n self.cell.timesteps = input_shape[1]\n self.cell.build(input_shape)\n\n def call(self, inputs, mask=None, training=None, initial_state=None):\n \"\"\"Call the AttentionLSTM object.\"\"\"\n self.cell._generate_dropout_mask(inputs, training=training)\n self.cell._generate_recurrent_dropout_mask(inputs, training=training)\n return super().call(\n inputs, mask=mask, training=training, initial_state=initial_state\n )\n\n @property\n def units(self):\n \"\"\"Return property units.\"\"\"\n return self.cell.units\n\n @property\n def activation(self):\n \"\"\"Return property activation.\"\"\"\n return self.cell.activation\n\n @property\n def recurrent_activation(self):\n \"\"\"Return property recurrent_activation.\"\"\"\n return self.cell.recurrent_activation\n\n @property\n def attention_activation(self):\n \"\"\"Return property attention_activation.\"\"\"\n return self.cell.attention_activation\n\n @property\n def use_bias(self):\n \"\"\"Return property use_bias.\"\"\"\n return self.cell.use_bias\n\n @property\n def kernel_initializer(self):\n \"\"\"Return property kernel_initializer.\"\"\"\n return self.cell.kernel_initializer\n\n @property\n def recurrent_initializer(self):\n \"\"\"Return property recurrent_initializer.\"\"\"\n return self.cell.recurrent_initializer\n\n @property\n def attention_initializer(self):\n \"\"\"Return property attention_initializer.\"\"\"\n return self.cell.attention_initializer\n\n @property\n def bias_initializer(self):\n \"\"\"Return property bias_initializer.\"\"\"\n return self.cell.bias_initializer\n\n @property\n def unit_forget_bias(self):\n \"\"\"Return property unit_forget_bias.\"\"\"\n return self.cell.unit_forget_bias\n\n @property\n def kernel_regularizer(self):\n \"\"\"Return property kernel_regularizer.\"\"\"\n return self.cell.kernel_regularizer\n\n @property\n def recurrent_regularizer(self):\n \"\"\"Return property recurrent_regularizer.\"\"\"\n return self.cell.recurrent_regularizer\n\n @property\n def bias_regularizer(self):\n \"\"\"Return property bias_regularizer.\"\"\"\n return self.cell.bias_regularizer\n\n @property\n def activity_regularizer(self):\n \"\"\"Return property activity_regularizer.\"\"\"\n return self.cell.activity_regularizer\n\n @property\n def attention_regularizer(self):\n \"\"\"Return property attention_regularizer.\"\"\"\n return self.cell.attention_regularizer\n\n @property\n def kernel_constraint(self):\n \"\"\"Return property kernel_constraint.\"\"\"\n return self.cell.kernel_constraint\n\n @property\n def recurrent_constraint(self):\n \"\"\"Return property recurrent_constraint.\"\"\"\n return self.cell.recurrent_constraint\n\n @property\n def bias_constraint(self):\n \"\"\"Return property bias_constraint.\"\"\"\n return self.cell.bias_constraint\n\n @property\n def attention_constraint(self):\n \"\"\"Return property attention_constraint.\"\"\"\n return self.cell.attention_constraint\n\n @property\n def dropout(self):\n \"\"\"Return property dropout.\"\"\"\n return self.cell.dropout\n\n @property\n def recurrent_dropout(self):\n \"\"\"Return property recurrent_dropout.\"\"\"\n return self.cell.recurrent_dropout\n\n @property\n def implementation(self):\n \"\"\"Return property implementation.\"\"\"\n return self.cell.implementation\n\n def get_config(self):\n \"\"\"Return configuration dict of the AttentionLSTM object.\"\"\"\n config = {\n \"units\": self.units,\n \"activation\": activations.serialize(self.activation),\n \"recurrent_activation\": activations.serialize(\n self.recurrent_activation\n ),\n \"attention_activation\": activations.serialize(\n self.attention_activation\n ),\n \"use_bias\": self.use_bias,\n \"kernel_initializer\": initializers.serialize(self.kernel_initializer),\n \"recurrent_initializer\": initializers.serialize(\n self.recurrent_initializer\n ),\n \"bias_initializer\": initializers.serialize(self.bias_initializer),\n \"attention_initializer\": initializers.serialize(\n self.attention_initializer\n ),\n \"use_chrono_initialization\": self.unit_forget_bias,\n \"kernel_regularizer\": regularizers.serialize(self.kernel_regularizer),\n \"recurrent_regularizer\": regularizers.serialize(\n self.recurrent_regularizer\n ),\n \"bias_regularizer\": regularizers.serialize(self.bias_regularizer),\n \"activity_regularizer\": regularizers.serialize(\n self.activity_regularizer\n ),\n \"attention_regularizer\": regularizers.serialize(\n self.attention_regularizer\n ),\n \"kernel_constraint\": constraints.serialize(self.kernel_constraint),\n \"recurrent_constraint\": constraints.serialize(\n self.recurrent_constraint\n ),\n \"bias_constraint\": constraints.serialize(self.bias_constraint),\n \"attention_constraint\": constraints.serialize(\n self.attention_constraint\n ),\n \"dropout\": self.dropout,\n \"recurrent_dropout\": self.recurrent_dropout,\n \"return_attention\": self.return_attention,\n }\n base_config = super().get_config()\n del base_config[\"cell\"]\n return dict(list(base_config.items()) + list(config.items()))\n\n @classmethod\n def from_config(cls, config):\n \"\"\"Create a new AttentionLSTM object from a configuration dict.\"\"\"\n if \"implementation\" in config and config[\"implementation\"] == 0:\n config[\"implementation\"] = 1\n return cls(**config)\n\n return AttentionLSTM","def causal_attention_mask(nd, ns, dtype):\n i = tf.range(nd)[:, None]\n j = tf.range(ns)\n m = i >= j - ns + nd\n return tf.cast(m, dtype)","def call(self, x, mask=None):\n u_i = K.tanh(K.dot(x, self.W) + self.b)\n v = K.squeeze(K.dot(u_i, K.expand_dims(self.u)), axis=-1)\n attention = softmax_masked(v, mask)\n\n return attention","def __init__(self, encoder_hidden_dim, decoder_hidden_dim, T):\n super(TemporalAttentionDecoder, self).__init__()\n\n self.T = T\n self.encoder_hidden_dim = encoder_hidden_dim\n self.decoder_hidden_dim = decoder_hidden_dim\n\n self.attn_layer = nn.Sequential(nn.Linear(2 * decoder_hidden_dim + encoder_hidden_dim, encoder_hidden_dim),\n nn.ReLU(), nn.Linear(encoder_hidden_dim, 1))\n self.lstm_layer = nn.LSTM(input_size=1, hidden_size=decoder_hidden_dim)\n self.fc = nn.Linear(encoder_hidden_dim + 2, 1)\n self.fc_final = nn.Linear(decoder_hidden_dim + encoder_hidden_dim, 1)\n\n self.fc.weight.data.normal_()","def forward(self, x, mask):\n x = self.sublayer[0](x, lambda x: self.self_attn(x, x, x, mask))\n #print('encoder')\n #print(x.shape)\n return self.sublayer[1](x, self.feed_forward)","def get_attention(self, X):\n if self.bn:\n layer = 16\n else:\n layer = 14\n inputs = [K.learning_phase()] + [self.model.inputs[0]]\n _attention_f = K.function(inputs, [\n self.model.layers[layer].output])\n \n return _attention_f([0] + [X])","def make_attn_mask(inp, inp_len, dtype=tf.float32):\n with tf.name_scope(\"encoder_mask\"):\n mask = tf.sequence_mask(inp_len, dtype=dtype, maxlen=tf.shape(inp)[1])\n return mask[:, None, None, :]","def _attention(self, inputs):\n attn_weights = K.batch_dot(x=inputs,\n y=K.permute_dimensions(inputs,\n pattern=(0, 2, 1)))\n return K.permute_dimensions(attn_weights, (0, 2, 1))","def attention_mask(nd, ns, dtype=tf.float32):\n i = tf.range(nd)[:, None]\n j = tf.range(ns)\n m = i >= j - ns + nd\n out = tf.cast(m, dtype)\n return out","def apply_tfmask(feats, max_bin=27, max_time=100):\n flen, dim = feats.shape\n d_mask = random.randint(1, max_bin)\n d_point = random.randint(0, dim - d_mask)\n t_mask = random.randint(1, max_time)\n t_point = random.randint(0, flen - t_mask)\n\n mask = np.ones((flen, dim), dtype=\"d\")\n mask[:, d_point : d_point + d_mask] = 0\n mask[t_point : t_point + t_mask] = 0\n return feats * mask","def get_attention_multiscale_batch(self, X,X_mask):\n layer = -3\n attmodel1 = Model(self.model.inputs,self.model.get_layer('att1').output[1])\n attmodel2 = Model(self.model.inputs,self.model.get_layer('att2').output[1])\n attmodel3 = Model(self.model.inputs,self.model.get_layer('att3').output[1])\n return attmodel1.predict([X,X_mask.reshape(-1,X_mask.shape[1],1)],batch_size=100),attmodel2.predict([X,X_mask.reshape(-1,X_mask.shape[1],1)],batch_size=100),attmodel3.predict([X,X_mask.reshape(-1,X_mask.shape[1],1)],batch_size=100)","def compute_attention_mask(x_mask, mem_mask, x_word_dim, key_word_dim):\r\n if x_mask is None and mem_mask is None:\r\n return None\r\n elif x_mask is None or mem_mask is None:\r\n raise NotImplementedError()\r\n\r\n x_mask = tf.cast(x_mask,dtype=bool)\r\n mem_mask = tf.cast(tf.transpose(mem_mask,perm=[0,2,1]), dtype=bool)\r\n join_mask = tf.logical_and(x_mask, mem_mask)\r\n return join_mask","def attn(self, embed, mask, name=\"\"):\n with tf.variable_scope(\"attn_\"+name):\n K = self.get_trans_param(\"K\")\n Q = self.get_trans_param(\"Q\")\n V = self.get_trans_param(\"V\")\n kdata = tf.einsum(\"nml,lk->nmk\", embed, K)\n qdata = tf.einsum(\"nml,lk->nmk\", embed, Q)\n vdata = tf.einsum(\"nml,lk->nmk\", embed, V) # nbatch x max_atom x n_trans\n kq = tf.einsum(\"nml,nkl->nmk\", qdata, kdata)*(1/math.sqrt(self.n_trans)) # nbatch x max_atom x max_atom\n #mask = tf.expand_dims(mask, 1) # nbatch x 1 x max_atom\n mask = tf.keras.backend.repeat(mask, self.max_atom) \n score = tf.where(mask, -9999*tf.ones_like(kq), kq)\n #score = kq\n #score = tf.scatter_update(tf.Variable(kq, validate_shape=False), mask, -9999)# assign a large number\n w = tf.nn.softmax(score, axis=-1) # calculate attention weight, nbatch x max_atom x max_atom\n vout = tf.einsum(\"nml,nlk->nmk\", w, vdata) # nbatch x max_atom x n_trans\n return vout","def _add_mask(batch, num_batch_dims):\n mask = tf.ones(tf.shape(list(batch.values())[0])[:num_batch_dims])\n if \"mask\" in batch:\n mask *= batch[\"mask\"]\n batch[\"mask\"] = mask\n return batch","def build(self, unused_input_shapes):\n self.query_dense = self._projection_dense_layer(\"query\")\n self.key_dense = self._projection_dense_layer(\"key\")\n self.value_dense = self._projection_dense_layer(\"value\")\n self.attention_probs_dropout = tf.keras.layers.Dropout(\n rate=self.attention_probs_dropout_prob)\n super(CustomAttention, self).build(unused_input_shapes)","def make_inference_attention_mask_3d(source_block, target_block, pad_id):\n # mask = (target_block[:, None, :] != pad_id) * (source_block[:, :, None] != pad_id)\n return make_attention_mask_3d(source_block != pad_id, target_block != pad_id)","def lstm_mask_layer(proj, mask):\n\n return proj * mask[:, :, None]","def _prepare_attended_output(self,\n decoder_hidden_state: torch.Tensor,\n state: Dict[str, torch.Tensor]) -> torch.Tensor:\n # Ensure mask is also a FloatTensor. Or else the multiplication within\n # attention will complain.\n # shape: (batch_size, max_input_sequence_length)\n\n encoder_outputs = state[\"encoder_outputs\"]\n source_mask = state[\"source_mask\"]\n prev_attention = state[\"attention\"]\n att_keys = state[\"att_keys\"]\n att_values = state[\"att_values\"]\n\n # shape: (batch_size, max_input_sequence_length)\n mode = \"soft\" if self.training else \"hard\"\n if isinstance(self._attention, MonotonicAttention):\n encoder_outs: Dict[str, torch.Tensor] = {\n \"value\": state[\"encoder_outputs\"],\n \"mask\": state[\"source_mask\"]\n }\n\n monotonic_attention, chunk_attention = self._attention(\n encoder_outs, decoder_hidden_state, prev_attention, mode=mode)\n # shape: (batch_size, encoder_output_dim)\n attended_output = util.weighted_sum(\n encoder_outputs, chunk_attention)\n attention = monotonic_attention\n elif isinstance(self._attention, StatefulAttention):\n attended_output, attention = self._attention(decoder_hidden_state,\n att_keys, att_values, source_mask)\n else:\n attention = self._attention(\n decoder_hidden_state, source_mask)\n attended_output = util.weighted_sum(\n encoder_outputs, attention)\n\n return attended_output, attention","def convolutional_attention(inputs, filter_size=5, initializer=None,\n reuse=None, name=''):\n with tf.variable_scope('conv_att_{}'.format(name), reuse=reuse) as f:\n dim = inputs.get_shape().as_list()[2]\n filter_shape = filter_shape = [filter_size, dim, 1]\n W1 = tf.get_variable(\"weights\", filter_shape,\n initializer=initializer)\n b1 = tf.get_variable(\"bias\", [1],\n initializer=tf.constant_initializer([0.1]))\n conv = tf.nn.conv1d(inputs, W1, stride=1,\n padding=\"SAME\", data_format=\"NHWC\")\n # this should be bsz x seq_len x 1\n conv += b1\n att = tf.nn.sigmoid(conv)\n weighted_inputs = inputs * att\n return weighted_inputs, att","def apply_attention(inputs,\n attention_mode=None,\n attention_in=None,\n use_5d_mode=False,\n data_format='channels_last'):\n assert data_format == 'channels_last'\n\n h_ch_loc = 2 if use_5d_mode else 1\n\n if attention_mode == 'peer':\n attn = softmax_merge_peer_attentions(attention_in, data_format)\n else:\n attn = tf.reduce_mean(inputs, [h_ch_loc, h_ch_loc+1])\n attn = tf.layers.dense(\n inputs=attn,\n units=inputs.shape[-1],\n kernel_initializer=tf.random_normal_initializer(stddev=.01))\n attn = tf.math.sigmoid(attn)\n channel_attn = tf.expand_dims(tf.expand_dims(attn, h_ch_loc), h_ch_loc)\n\n inputs = tf.multiply(inputs, channel_attn)\n\n return inputs","def get_fc(self, layer):\n return getattr(self, 'attention_{}'.format(layer))","def spec_augment(_spec,\n do_time_warp=True,\n W=40,\n do_freq_mask=True,\n F=20,\n m_f=1,\n reduce_mask_range=0,\n do_time_mask=True,\n T=20,\n m_t=1,\n mask_val='zero'):\n\n _spec_aug = copy.deepcopy(_spec)\n # Step 1 : Time warping, not used\n\n # Step 2 : Frequency masking\n # hard wideband suppression of bw bands starting from f0\n # bw drawn from a uniform distribution from 0 to parameter F\n # f0 drawn from [0, n_bands-bw]\n if do_freq_mask:\n _spec_aug = freq_mask(_spec_aug, F=F, n_masks=m_f, mask_val=mask_val, reduce_mask_range=reduce_mask_range)\n\n # Step 3 : Time masking\n # sound mute of deltat consecutive frames, starting at t0\n # deltat drawn from a uniform distribution from 0 to parameter T\n # t0 drawn from [0, n_frames-deltat]\n if do_time_mask:\n _spec_aug = time_mask(_spec_aug, T=T, n_masks=m_t, mask_val=mask_val)\n\n return _spec_aug","def _apply_attention_constraint(e,\n last_attended_idx,\n backward_window=1,\n forward_window=3):\n # for dygraph to static graph\n # if e.shape[0] != 1:\n # raise NotImplementedError(\n # \"Batch attention constraining is not yet supported.\")\n backward_idx = paddle.cast(\n last_attended_idx - backward_window, dtype='int64')\n forward_idx = paddle.cast(last_attended_idx + forward_window, dtype='int64')\n if backward_idx > 0:\n e[:, :backward_idx] = -float(\"inf\")\n if forward_idx < paddle.shape(e)[1]:\n e[:, forward_idx:] = -float(\"inf\")\n return e","def output_layer_activation(x):\n return x","def lstm_atten(self):\n # Model.\n model = Sequential()\n model.add(LSTM(2048, return_sequences=True,\n input_shape=self.input_shape,\n dropout=0.5))\n model.add(Flatten()) #qiao_added\n # model.add(Dense(1024, activation='relu'))\n # model.add(Dropout(0.5))\n\n attention = Dense(1, activation='tanh')(activations)\n attention = Flatten()(attention)\n attention = Activation('softmax')(attention)\n attention = RepeatVector(2048)(attention)\n attention = Permute([2, 1])(attention)\n\n sent_representation = concatenate([activations, attention], mode='mul')\n sent_representation = Lambda(lambda xin: K.sum(xin, axis=-2), output_shape=(2048,))(sent_representation)\n\n probabilities = Dense(self.nb_classes, activation='softmax')(sent_representation)\n\n model = model(input=self.input_shape, output=probabilities )\n\n dense1800 = Dense(4096, activation='relu')\n\n #dense1800 = Dense(1800, activation='relu', kernel_regularizer=regularizers.l2(0.01))(inputs)\n attention_probs = Dense(4096, activation='sigmoid', name='attention_probs')(dense1800)\n attention_mul = multiply([dense1800, attention_probs], name='attention_mul')\n dense7 = Dense(self.nb_classes, kernel_regularizer=regularizers.l2(0.01), activation='softmax')(attention_mul)\n model = Model(input=[self.input_shape], output=dense7)\n return model","def get_attention(self, temp_data, channel_mask=[0], threshold=100, keep_bad_epochs=False,apply_filters=True):\n\n # Standard Filters\n if(apply_filters):\n temp_data = filters.apply_dc_offset(temp_data)\n temp_data = filters.apply_notch_filter(temp_data)\n\n # Remove bad epochs by identifying bad epochs as those containing\n # energy in 1, 10Hz band above a threshold\n blocks_data = temp_data\n if(keep_bad_epochs == False):\n blocks_data = ft.remove_bad_epochs(temp_data, thresh_fn=self.energy_of_epoch, threshold=threshold,\n channels=channel_mask, sliding_window=True)\n\n # Get band power of each block for all the available channels\n blocks_bandpower = []\n for block in blocks_data:\n\n blocks_bandpower.append(ft.get_bandpower(block.reshape(1, block.shape[0], block.shape[1]),\n channel_mask))\n self.bandpower.append(blocks_bandpower[-1])\n\n # Get the attention_matrix from the bandpower\n attention_per_channel = np.zeros((len(blocks_bandpower), len(channel_mask)))\n for idx, block in enumerate(blocks_bandpower):\n for channel in channel_mask:\n attention_per_channel[idx, channel] = self.attention_per_channel(block[channel])\n attention_per_epoch = self.attention_overall(attention_per_channel[idx])\n self.attention_matrix.append(attention_per_epoch)\n\n # For testing. Remove later\n #print(attention_per_epoch)","def __init__(self, input_dim=6, hidden_dim=128, T=10, in_features=2*128 + 16, num_layers=1, out_features=1):\n super(InputAttentionEncoder, self).__init__()\n self.input_dim = input_dim\n self.hidden_dim = hidden_dim\n self.T = T\n\n in_features = hidden_dim * 2 + T - 1\n\n self.lstm_unit = nn.LSTM(input_size=input_dim, hidden_size=hidden_dim, num_layers=num_layers)\n self.attn_linear = nn.Linear(in_features=in_features, out_features=out_features)\n self.bn1 = nn.BatchNorm1d(out_features)\n self.fc2 = nn.Linear(out_features, out_features)","def TCN(input_dim): \r\n # Number of dilations in order to use for the temporal blocks.\r\n dilations = np.array([1, 2, 4, 8, 16, 32])\r\n\r\n input_dim.insert(0,1)\r\n print(f\"input_dim: {input_dim}\")\r\n input_layer = Input(shape=input_dim)\r\n cropping = 0\r\n assert (sum(dilations) * block_size + 1) == 127, \"Paper specifies receptive field size should be 127\"\r\n \r\n prev_layer, skip_layer, _ = add_temporal_block(input_layer, None, 1, 1, cropping)\r\n \r\n for dilation in dilations:\r\n prev_layer, skip_layer, cropping = add_temporal_block(prev_layer, skip_layer, 2, dilation, cropping)\r\n\r\n output_layer = PReLU(shared_axes=[2, 3])(skip_layer)\r\n output_layer = SpectralNormalization(Conv1D(fixed_filters, kernel_size=1))(output_layer)\r\n output_layer = PReLU(shared_axes=[2, 3])(output_layer)\r\n output_layer = SpectralNormalization(Conv1D(1, kernel_size=1))(output_layer)\r\n\r\n return Model(input_layer, output_layer)","def segment(u_train, l_train, u_test):\n ### Exercise 6.2\n\n # Encode input and gather stats for model\n encoder = WordEncoder()\n encoder.fit(u_train)\n X_train = encoder.transform(u_train, flat=False)\n X_test = encoder.transform(u_test, flat=False)\n input_N = len(u_train)\n maxLen = encoder.max_wordlen\n third_dim = np.shape(X_train)[2]\n\n # Pad output to match input\n paddded_l_train = []\n for label in l_train:\n new_label = np.zeros(maxLen, dtype=int)\n for j, k in enumerate(label):\n new_label[j] = k\n paddded_l_train.append(new_label)\n l_train_array = np.array(paddded_l_train).reshape(input_N, maxLen, 1)\n\n # Build model\n model = Sequential()\n # I could not get the masking layer to work. Tried editing the X_train and Y arrays in numerous ways\n # But couldn't figure out why it wouldn't accept it. Any advice here would be much appreciated!\n # model.add(Embedding(input_dim=maxLen, output_dim=(maxLen, third_dim), mask_zero=True))\n model.add(LSTM(100, input_shape=(maxLen, third_dim), activation=\"relu\", return_sequences=True))\n model.add(Dropout(0.2))\n model.add(TimeDistributed(Dense(1, activation='sigmoid')))\n model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n es = EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=5)\n model.summary()\n model.fit(X_train, l_train_array, epochs=50, callbacks=[es])\n\n predictions = model.predict(X_test)\n # Convert label predictions to segments\n segments = label_to_segments(u_test, predictions)\n\n return segments","def masked_softmax(input_layer,n_nodes, batch_size):\n mask_lower = K.theano.tensor.tril(K.ones((n_nodes, n_nodes)))\n mask_upper = \\\n K.theano.tensor.triu(-100. * K.ones((n_nodes, n_nodes)), 1)\n mask_layer = mask_lower * input_layer + mask_upper\n mask_layer = mask_layer + 0 * K.eye(n_nodes)[0:n_nodes, 0:n_nodes]\n mask_layer = \\\n K.reshape(mask_layer, (batch_size * n_nodes, n_nodes))\n softmax_layer = K.softmax(mask_layer)\n output_layer = K.reshape(softmax_layer, (batch_size, n_nodes, n_nodes))\n return output_layer","def set_layer_mask_data(layer, channel_data, channel_info, array):\n width, height = layer.mask.width, layer.mask.height\n depth, version = layer._psd.depth, layer._psd.version\n byte_aray = (array * 255).astype(np.uint8)\n buf = data_from_array(byte_aray.flatten(), depth)\n channel_data.set_data(buf, width, height, depth, version)\n channel_info.length = channel_data._length","def __call__(self, inputs: tf.Tensor, outputs: tf.Tensor,\n out_mask: tf.Tensor,in_pad_mask: tf.Tensor=None,\n training: bool=False):\n encoder_outputs, enc_attention = self.encoder(\n inputs, in_pad_mask, training\n )\n # shape=(batch_size, inputs_seq_len, d_model)\n\n decoder_outputs, dec_self_attention, dec_enc_attention = self.decoder(\n outputs, encoder_outputs, out_mask, in_pad_mask, training\n )\n # shape=(batch_size, outputs_seq_len, d_model)\n\n attentions = {'encoder': enc_attention,\n 'decoder_self': dec_self_attention,\n 'decoder_encoder': dec_enc_attention}\n\n return decoder_outputs, attentions","def MakeMask(shape, masked_value=0, dtype=K.floatx(), name=None):\n def instantiate(x):\n if dtype is None:\n return layers.Lambda(lambda t: K.not_equal(x, masked_value),\n output_shape=shape,\n name=name)(x)\n else:\n return layers.Lambda(lambda t: K.cast(K.not_equal(x, masked_value), K.floatx()),\n output_shape=shape,\n name=name)(x)\n return instantiate","def attention_mask_future(nd, ns, dtype=tf.float32):\n i = tf.range(nd)[:, None]\n j = tf.range(ns)\n m = i >= j - ns + nd\n out = tf.cast(m, dtype)\n return out","def attention_mask(x):\n mask = torch.zeros(len(x), len(x[0]))\n for i in range(len(x)):\n try:\n index = np.where(x[i]==1)[0][0]\n mask[i][index:] = -np.inf\n except:\n pass\n return mask","def mask_attention(attention, seq_len1, seq_len2):\n dim1 = tensor_utils.shape(attention, 1)\n dim2 = tensor_utils.shape(attention, 2)\n m1 = tf.sequence_mask(seq_len1, dim1)\n m2 = tf.sequence_mask(seq_len2, dim2)\n joint_mask = tf.logical_and(tf.expand_dims(m1, 2), tf.expand_dims(m2, 1))\n return ops.mask_logits(attention, joint_mask)","def call(self, inputs):\n (input_tensor, attention_mask) = tf_utils.unpack_inputs(inputs)\n with tf.name_scope('attention'):\n attention_output, attention_scores = self.attention_layer(\n from_tensor=input_tensor,\n to_tensor=input_tensor,\n attention_mask=attention_mask)\n with tf.name_scope('output'):\n attention_output = self.attention_output_dense(attention_output)\n attention_output = self.attention_dropout(attention_output)\n # Use float32 in keras layer norm and the gelu activation in the\n # intermediate dense layer for numeric stability\n attention_output = self.attention_layer_norm(input_tensor +\n attention_output)\n if self.float_type == tf.float16:\n attention_output = tf.cast(attention_output, tf.float16)\n\n with tf.name_scope('intermediate'):\n intermediate_output = self.intermediate_dense(attention_output)\n if self.float_type == tf.float16:\n intermediate_output = tf.cast(intermediate_output, tf.float16)\n\n with tf.name_scope('output'):\n layer_output = self.output_dense(intermediate_output)\n layer_output = self.output_dropout(layer_output)\n # Use float32 in keras layer norm for numeric stability\n layer_output = self.output_layer_norm(layer_output + attention_output)\n if self.float_type == tf.float16:\n layer_output = tf.cast(layer_output, tf.float16)\n return layer_output, attention_scores","def _data_augment(self, x):\n batch_size = x.size()[0]\n x = x.view(batch_size, -1)\n bias = torch.ones(batch_size, 1).to(self.device)\n x = torch.cat((bias, x), 1)\n\n return x","def attention_mask_key(key_mask, num_tile, dtype=tf.float32):\n key_mask = tf.cast(key_mask, dtype)\n key_mask = tf.tile(key_mask, [num_tile, 1]) # (h*N, seqlen)\n key_mask = tf.expand_dims(key_mask, 1) # (h*N, 1, seqlen)\n mask = key_mask * - tf.cast(1e10, dtype)\n return mask","def forward(self, x: Tensor, mask: Tensor) -> Tensor:\n x_norm = self.layer_norm(x)\n h = self.src_src_att(x_norm, x_norm, x_norm, mask)\n h = self.dropout(h) + x\n o = self.feed_forward(h)\n return o","def Anatomical_attention_gate(featureMap1,featureMap2):\n ndims = len(featureMap1.get_shape()) - 2\n assert ndims in [1, 2, 3], \"ndims should be one of 1, 2, or 3. found: %d\" % ndims\n# input_channels = featureMap1.get_shape().as_list()[-1]\n# batch_size1 = tf.shape(down_in)[0]\n# nf = tf.min(batch_size0,batch_size1)\n featureMap = concatenate([featureMap1, featureMap2])\n Conv = getattr(KL, 'Conv%dD' % ndims)\n tensorweight1 = Conv(1, kernel_size=1, padding='same',\n kernel_initializer='he_normal', use_bias = True, bias_initializer='zeros',strides=1,activation='sigmoid')(featureMap)\n# tensorweight1 = Activation('relu')(tensorweight1)\n w_featureMap1 = Multiply()([featureMap1,tensorweight1])\n tensorweight2 = Conv(1, kernel_size=1, padding='same',\n kernel_initializer='he_normal', use_bias = True, bias_initializer='zeros',strides=1,activation='sigmoid')(featureMap)\n# tensorweight2 = Activation('relu')(tensorweight2)\n w_featureMap2 = Multiply()([featureMap2,tensorweight2])\n w_featureMap = Add()([w_featureMap1,w_featureMap2])\n return w_featureMap","def spec_augment(mel_spec: np.ndarray, n_time_masks: int, time_mask_width: int, n_freq_masks: int, freq_mask_width: int):\n \n offset, begin = 0, 0\n\n for _ in range(n_time_masks):\n offset = np.random.randint(0, time_mask_width)\n begin = np.random.randint(0, mel_spec.shape[1] - offset)\n mel_spec[:, begin: begin + offset] = 0.0\n \n for _ in range(n_freq_masks):\n offset = np.random.randint(0, freq_mask_width)\n begin = np.random.randint(0, mel_spec.shape[0] - offset)\n mel_spec[begin: begin + offset, :] = 0.0\n\n return mel_spec","def forward(self, x, src_states, src_mask, tgt_mask):\n x = self.sublayer[0](x, lambda x: self.self_attn(x, x, x, tgt_mask))\n #print('decoder')\n #print(x.shape)\n x = self.sublayer[1](x, lambda x: self.src_attn(x, src_states, src_states, src_mask))\n #print(x.shape)\n return self.sublayer[2](x, self.feed_forward)","def attention_imp_merge():\n global X_DIM, Y_DIM\n # Load Embeddings matrix\n embedding_weights = joblib.load(config.DUMPED_VECTOR_DIR + 'mb_voc_embeddings.pkl')\n\n # model cnn\n\n model_atn = Sequential()\n model_atn.add(Embedding(max_features,\n embedding_dims,\n input_length=max_len,\n weights=[embedding_weights],\n trainable=True))\n model_atn.add(Bidirectional(GRU(100, return_sequences=True), name='bidirectional'))\n model_atn.add(TimeDistributed(Dense(200), name='time_dist'))\n model_atn.add(AttLayer(name='att'))\n\n model_feature_vec = Sequential()\n model_feature_vec.add(Dense(200, input_dim=N_Features, init='normal', activation='relu'))\n model_feature_vec.add(Dense(100, init='normal', activation='relu'))\n model_feature_vec.add(Dropout(0.2))\n model_feature_vec.add(Dense(50, init='normal', activation='relu'))\n model_feature_vec.add(Dense(10, init='normal', activation='relu'))\n\n merged_layer = Sequential()\n merged_layer.add(Merge([model_atn, model_feature_vec], mode='concat',\n concat_axis=1, name='merge_layer'))\n merged_layer.add(Dense(200, activation='relu'))\n # merged_layer.add(Bidirectional(GRU(100, return_sequences=True), name='bidirectional_2'))\n # merged_layer.add(TimeDistributed(Dense(200), name='time_dist'))\n # merged_layer.add(AttLayer(name='att'))\n merged_layer.add(Dense(1, init='normal', name='combined_dense'))\n\n # # Compile model\n merged_layer.compile(loss='mean_squared_error', optimizer='adam')\n\n print(merged_layer.summary())\n return merged_layer","def add_watermark(self, image, watermark, position='scale', opacity=1, format=None):","def temporal_padding(buffer, clip_len):\n if buffer.shape[0] > clip_len:\n pass\n else:\n pad_len = clip_len - buffer.shape[0] + 1\n npad = ((pad_len, 0), (0, 0), (0, 0), (0,0))\n # buffer = np.pad(buffer, pad_width=npad, mode='constant', constant_values=0)\n buffer = np.pad(buffer, pad_width=npad, mode='mean')\n assert buffer.shape[0] - clip_len > 0, \"Incorrect Padding\"\n return buffer","def spatial_attention(input_feature, kernel_size=7, name=None):\n cbam_feature = input_feature\n avg_pool = layers.Lambda(lambda x: K.mean(x, axis=3, keepdims=True))(cbam_feature)\n max_pool = layers.Lambda(lambda x: K.max(x, axis=3, keepdims=True))(cbam_feature)\n concat = layers.concatenate([avg_pool, max_pool])\n cbam_feature = layers.Conv2D(filters=1,\n kernel_size=kernel_size,\n strides=1,\n padding='same',\n activation='sigmoid',\n kernel_initializer='he_normal',\n use_bias=False,\n name=name + '_sliency')(concat)\n\n return layers.multiply([input_feature, cbam_feature])","def build_attention_mask_3d_padding(source_mask, target_mask):\n mask = make_attention_mask_3d(source_mask, target_mask)\n # invert mask for Megatron\n return mask < 0.5","def task_specific_attention(inputs, output_size, sequence_lengths,\n initializer=layers.xavier_initializer(),\n activation_fn=tf.tanh, scope=None):\n assert len(inputs.get_shape()) == 3 and inputs.get_shape()[-1].value is not None\n\n with tf.variable_scope(scope or 'attention') as scope:\n attention_context_vector = tf.get_variable(name='attention_context_vector',\n shape=[output_size],\n initializer=initializer,\n dtype=tf.float32)\n \n input_projection = layers.fully_connected(inputs, output_size,\n activation_fn=activation_fn,\n scope=scope)\n\n vector_attn = tf.reduce_sum(tf.multiply(input_projection, attention_context_vector), axis=2) \n mask = tf.sequence_mask(sequence_lengths, dtype=tf.float32) \n attention_weights = tf.nn.softmax(vector_attn, axis=1)\n attention_weights = attention_weights*mask\n norms = tf.reduce_sum(attention_weights, axis = 1, keepdims = True) + 1e-6 \n attention_weights = attention_weights / norms\n attention_weights = tf.expand_dims(attention_weights, axis = 2) \n \n weighted_projection = inputs*attention_weights\n outputs = tf.reduce_sum(weighted_projection, axis=1)\n\n return outputs","def build_attention_mask_3d(source_mask, target_mask, attn_mask_type):\n if attn_mask_type == AttnMaskType.padding:\n mask = build_attention_mask_3d_padding(source_mask, target_mask)\n elif attn_mask_type == AttnMaskType.causal:\n mask = build_attention_mask_3d_causal(source_mask, target_mask)\n else:\n raise ValueError(f\"Unsupported attention mask attn_mask_type = {attn_mask_type}\")\n\n return mask","def channel_padding(x):\n #keras.backend.concatenate([x, tf.zeros_like(x)], axis=-1)\n x0=keras.layers.Activation('sigmoid')(x)\n return keras.backend.concatenate([x, x0], axis=-1)","def pixelAttention(self,x):\n b, c, w, h = x.shape\n pre_x = x.permute(0, 2, 3, 1)\n pre_x = pre_x.contiguous().view(b, h * w, c)\n att_x, relations = self.forward_unified(pre_x, pre_x, pre_x)\n att_x = att_x.contiguous().view(b, h, w, c)\n att_x = att_x.permute(0, 3, 1, 2)\n return att_x","def self_attention(self, hidden):\n mul1 = self.attention1(hidden)\n mul2 = self.attention2(mul1)\n return self.softmax(mul2)","def create_attention_mask_from_input_mask(from_tensor, to_mask):\n from_shape = get_shape_list(from_tensor, expected_rank=[2, 3])\n batch_size = from_shape[0]\n from_seq_length = from_shape[1]\n \n to_shape = get_shape_list(to_mask, expected_rank=2)\n to_seq_length = to_shape[1]\n \n to_mask = tf.cast(\n tf.reshape(to_mask, [batch_size, 1, to_seq_length]), tf.float32)\n \n # We don't assume that `from_tensor` is a mask (although it could be). We\n # don't actually care if we attend *from* padding tokens (only *to* padding)\n # tokens so we create a tensor of all ones.\n #\n # `broadcast_ones` = [batch_size, from_seq_length, 1]\n broadcast_ones = tf.ones(\n shape=[batch_size, from_seq_length, 1], dtype=tf.float32)\n \n # Here we broadcast along two dimensions to create the mask.\n mask = broadcast_ones * to_mask\n \n return mask","def _add_bert_self_attention_layer(model_1, model_2):\n\n class Config:\n pass\n\n config = Config()\n config.hidden_size = model_1.all_head_size + model_2.all_head_size\n config.num_attention_heads = (\n model_1.num_attention_heads + model_2.num_attention_heads\n )\n config.output_attentions = model_1.output_attentions\n config.attention_probs_dropout_prob = model_1.dropout.p\n\n return BertSelfAttention(config)","def attention(inp, scope, e_dim, past, config):\n assert inp.shape.ndims == 3 # input should be of shape [batch, seqlen, embeddings] # [batch, sequence, features]\n assert e_dim % config.num_heads == 0 # embedding can be split in heads\n\n if past is not None:\n assert past.shape.ndims == 5 # [batch, 2, heads, seqlen, emebeddings]\n\n def split_heads(x):\n out = split_into_n_states(x, config.num_heads)\n out = tf.transpose(out, [0, 2, 1, 3])\n return out\n\n def merge_heads(x):\n out = merge_n_states(tf.transpose(x, [0, 2, 1, 3]))\n return out\n\n def mask_attention_weights(w):\n # w should have shape [batches, heads, dst_seq, src_seq], where information flows from scr to dst\n _, _, nd, ns = shapes_list(w)\n b = attention_mask(nd, ns, w.dtype)\n b = tf.reshape(b, [1, 1, nd, ns])\n w = w * b - tf.cast(1e10, w.dtype) * (1 - b)\n return w\n\n def multihead_attention(q, k, v):\n w = tf.matmul(q, k, transpose_b=True)\n w *= tf.rsqrt(tf.cast(v.shape[-1].value, w.dtype))\n\n # mask attention weights\n w = mask_attention_weights(w)\n w = softmax_with_reduce_max(w)\n out = tf.matmul(w, v)\n return out\n\n with tf.variable_scope(scope):\n c = conv1d(inp, 'convolutional_attention', e_dim * 3)\n q, k, v = map(split_heads, tf.split(c, 3, axis=2))\n present = tf.stack([k, v], axis=1)\n if past is not None:\n # there is a stack below it\n pk, pv = tf.unstack(past, axis=1)\n k = tf.concat([pk, k], axis=2)\n v = tf.concat([pv, v], axis=2)\n\n attn = multihead_attention(q, k, v)\n attn = merge_heads(attn)\n\n out = conv1d(attn, 'convolutional_projection', e_dim)\n return out, present","def apply_mask(self, parameter):\n if self.mask is None:\n return\n if self.use_double_copies:\n self.unmasked_copy = parameter.clone().detach()\n self.mask_tensor(parameter)\n if self.is_regularization_mask:\n self.mask = None\n return parameter","def channelAttention(self,x):\n b, c, h, w = x.shape\n pre_x = x.contiguous().view(b, c, h * w)\n\n att_x, relations = self.forward_unified(pre_x, pre_x, pre_x)\n att_x = att_x.contiguous().view(b, c, h, w)\n return att_x","def buildMaskedLoss(loss_function, mask_value):\n\n def maskedLossFunction(y_true, y_pred):\n mask = K.cast(K.not_equal(y_true, mask_value), K.floatx())\n return loss_function(y_true * mask, y_pred * mask)\n\n return maskedLossFunction","def identity_mask_propagation(nx_node, nx_graph):\n input_masks = get_input_masks(nx_node, nx_graph)\n assert len(input_masks) == 1\n nx_node['input_masks'] = input_masks\n nx_node['output_mask'] = input_masks[0]","def apply_mask(data, mask_func, seed=None, padding=None):\n shape = np.array(data.shape)\n shape[:-3] = 1\n mask = mask_func(shape, seed)\n if padding is not None:\n mask[:, :, :padding[0]] = 0\n mask[:, :, padding[1]:] = 0 # padding value inclusive on right of zeros\n\n masked_data = data * mask + 0.0 # The + 0.0 removes the sign of the zeros\n return masked_data, mask","def data_augmentation(self, img):\n new_img = img.astype(float)\n # random brightness - the mask bit keeps values from going beyond (0,255)\n value = np.random.randint(-28, 28)\n if value > 0:\n mask = (new_img[:, :, 0] + value) > 255\n if value <= 0:\n mask = (new_img[:, :, 0] + value) < 0\n new_img[:, :, 0] += np.where(mask, 0, value)\n # random shadow - full height, random left/right side, random darkening\n h, w = new_img.shape[0:2]\n mid = np.random.randint(0, w)\n factor = np.random.uniform(0.6, 0.8)\n if np.random.rand() > .5:\n new_img[:, 0:mid, 0] *= factor\n else:\n new_img[:, mid:w, 0] *= factor\n return (new_img.astype(np.uint8))","def ClearRelativeAttentionInTransformerLayer(transformer_params):\n if not issubclass(transformer_params.cls, TransformerLayer):\n raise ValueError('Unsupported input transformer layer: %s' %\n transformer_params.cls)\n trans_params_copy = transformer_params.Copy()\n if trans_params_copy.tr_self_atten_tpl is None:\n trans_params_copy.tr_self_atten_tpl = trans_params_copy.tr_atten_tpl.Copy()\n attention_tpl = trans_params_copy.tr_self_atten_tpl.atten_tpl\n if attention_tpl.cls == MultiHeadedAttentionXL:\n new_attention_tpl = MultiHeadedAttention.Params()\n elif attention_tpl.cls == (LocalSelfAttentionXL):\n new_attention_tpl = LocalSelfAttention.Params()\n else:\n raise ValueError('Unsupported attention params: %s' % attention_tpl.cls)\n\n new_attention_tpl = hyperparams.CopyFieldsTo(\n attention_tpl,\n new_attention_tpl,\n skip=['rel_pos_emb_dim', 'skip_term_b', 'pos_atten_logits_tpl'])\n trans_params_copy.tr_self_atten_tpl.atten_tpl = new_attention_tpl\n return trans_params_copy","def forward(self, encoder_state, context, context_lens):\n attn = self.attention(context, encoder_state.squeeze(0), context_lens)\n return attn","def identity_mask_propagation(nx_node, nx_graph):\n input_masks = get_input_masks(nx_node, nx_graph)\n assert len(input_masks) == 1\n nx_node[\"input_masks\"] = input_masks\n nx_node[\"output_mask\"] = input_masks[0]","def layer_masks(self, module):\n pass\n # return masks","def apply_mask(self, mask, parameters=None):\n if parameters is None:\n self.dates = self.dates[mask]\n for key in self.data.keys():\n self.data[key] = self.data[key][mask]\n\n self.manufacturer = self.manufacturer[mask]\n self.data_file = self.data_file[mask]\n self.serial_number = self.serial_number[mask]\n else:\n for parameter in parameters:\n self.data[parameter][~mask] = np.nan","def augment(image,masks):\n\n # Random horizontal flipping\n if random.random() > 0.5:\n image = TF.hflip(image)\n masks = TF.hflip(masks)\n\n # Random vertical flipping\n if random.random() > 0.5:\n image = TF.vflip(image)\n masks = TF.vflip(masks)\n return image,masks","def build_attention_mask(input_ids): \n attention_masks = [] \n\n # 1 for input and 0 for pad\n for seq in input_ids: \n attention_masks.append([float(i>0) for i in seq])\n\n return attention_masks","def compute_attention(t1, t2):\n dim = t1.shape.as_list()[2]\n init = tf.constant_initializer(1.0 / dim)\n\n t1_logits = ops.last_dim_weighted_sum(t1, \"t1_w\")\n t2_logits = ops.last_dim_weighted_sum(t2, \"t2_w\")\n\n dot_w = tf.get_variable(\n \"dot_w\", shape=dim, initializer=init, dtype=tf.float32)\n # Compute x * dot_weights first, then batch mult with x\n dots = t1 * tf.expand_dims(tf.expand_dims(dot_w, 0), 0)\n dot_logits = tf.matmul(dots, t2, transpose_b=True)\n\n return dot_logits + \\\n tf.expand_dims(t1_logits, 2) + \\\n tf.expand_dims(t2_logits, 1)","def make_attention_mask(source_block, target_block):\n mask = (target_block[None, :] >= 1) * (source_block[:, None] >= 1)\n mask = mask.astype(np.int64)\n # (source_length, target_length)\n return mask","def forward(self,\n x: Tensor = None,\n memory: Tensor = None,\n src_mask: Tensor = None,\n trg_mask: Tensor = None) -> Tensor:\n # decoder/target self-attention\n\n x_norm = self.x_layer_norm(x)\n# print(x_norm)\n# trg_mask()\n# print(trg_mask)\n\n h1 = self.trg_trg_att(x_norm, x_norm, x_norm, mask=trg_mask)\n h1 = self.dropout(h1) + x\n\n\n if self.src_trg_att:\n # source-target attention\n h1_norm = self.dec_layer_norm(h1)\n h2 = self.src_trg_att(memory, memory, h1_norm, mask=src_mask)\n # final position-wise feed-forward layer\n o = self.feed_forward(self.dropout(h2) + h1)\n else:\n o = self.feed_forward(h1)\n return o","def input_mask(self):\n inputs = self.input\n if isinstance(inputs, list):\n return [getattr(x, '_keras_mask', None) for x in inputs]\n else:\n return getattr(inputs, '_keras_mask', None)","def sdp_attention(Q, K, V, mask=None):\n matmul_qk = tf.matmul(Q, K, transpose_b=True)\n scald_qk = tf.cast(tf.shape(K)[-1], tf.float32)\n scald_atten = matmul_qk / tf.math.sqrt(scald_qk)\n\n # masked added to tensor\n if mask is not None:\n scald_attention += (mask * -1e9)\n # weights are the attention weights\n weights = tf.nn.softmax(scald_atten, axis=-1)\n output = tf.matmul(weights, V)\n\n return output, weights","def make_attention_mask_3d(source_mask, target_mask):\n mask = target_mask[:, None, :] * source_mask[:, :, None]\n return mask","def ann_mean(ds, season=None, time_bnds_varname='time_bnds', time_centered=True, n_req=None):\n \n ds = ds.copy() #deep=True)\n\n if n_req is None:\n if season is not None:\n n_req = 2\n else:\n n_req = 8\n \n if time_bnds_varname is None and not time_centered:\n raise NotImplementedError('time_bnds_varname cannot be \"None\" if time_centered=False')\n \n if not time_centered:\n time_units = ds.time.encoding['units']\n time_calendar = ds.time.encoding['calendar']\n\n # compute time bounds array\n time_bound_data = cftime.date2num(\n ds[time_bnds_varname].data, \n units=time_units, \n calendar=time_calendar) \n\n # center time\n time_centered = cftime.num2date(\n time_bound_data.mean(axis=1),\n units=time_units, \n calendar=time_calendar\n ) \n time_attrs = ds.time.attrs\n time_encoding = ds.time.encoding\n\n ds['time'] = xr.DataArray(\n time_centered,\n dims=('time')\n ) \n \n ones = xr.DataArray(\n np.ones((len(ds.time))), \n dims=('time'), \n coords={'time': ds.time},\n )\n time_mask = xr.DataArray(\n np.ones((len(ds.time))), \n dims=('time'), \n coords={'time': ds.time},\n )\n\n group_by_year = 'time.year'\n rename = {'year': 'time'}\n \n if season is not None:\n season = season.upper()\n if season not in ['DJF', 'MAM', 'JJA', 'SON']:\n raise ValueError(f'unknown season: {season}') \n\n ds['austral_year'] = xr.where(ds['time.month'] > 6, ds['time.year'] + 1, ds['time.year'])\n ds = ds.set_coords('austral_year')\n ones = ones.assign_coords({'austral_year': ds.austral_year})\n time_mask = time_mask.assign_coords({'austral_year': ds.austral_year})\n time_mask = time_mask.where(ds['time.season'] == season).fillna(0)\n \n if season == 'DJF':\n group_by_year = 'austral_year'\n rename = {'austral_year': 'time'}\n \n if time_bnds_varname is not None:\n time_wgt = ds[time_bnds_varname].diff(dim=ds[time_bnds_varname].dims[1])\n if time_wgt.dtype == '<m8[ns]':\n time_wgt = time_wgt / np.timedelta64(1, 'D')\n else: \n time_wgt = xr.DataArray(\n np.ones((len(ds.time))), \n dims=('time'), \n coords={'time': ds.time},\n )\n time_wgt = time_wgt.assign_coords(\n {c: da for c, da in ds.coords.items() if 'time' in da.dims}\n )\n \n time_wgt = time_wgt.where(time_mask==1) #.fillna(0.)\n\n ones = ones.where(time_mask==1)\n time_wgt_grouped = time_wgt.groupby(group_by_year, restore_coord_dims=False)\n time_wgt = time_wgt_grouped / time_wgt_grouped.sum(dim=xr.ALL_DIMS)\n\n nyr = len(time_wgt_grouped.groups)\n \n time_wgt = time_wgt.squeeze()\n\n idx_not_nans = ~np.isnan(time_wgt)\n sum_wgt = time_wgt.groupby(group_by_year).sum(dim=xr.ALL_DIMS)\n idx_not_nans = (sum_wgt > 0)\n\n np.testing.assert_almost_equal(\n sum_wgt[idx_not_nans], \n np.ones(idx_not_nans.sum().values)\n )\n\n nontime_vars = set([v for v in ds.variables if 'time' not in ds[v].dims]) - set(ds.coords)\n dsop = ds.drop_vars(nontime_vars)\n\n if time_bnds_varname is not None:\n dsop = dsop.drop_vars(time_bnds_varname) \n \n def weighted_mean_arr(darr, wgts=None):\n # if NaN are present, we need to use individual weights\n cond = darr.isnull()\n ones = xr.where(cond, 0.0, 1.0)\n if season is None:\n mask = (\n darr.resample({'time': 'A'}, restore_coord_dims=False).mean(dim='time').notnull()\n )\n da_sum = (\n (darr * wgts).resample({'time': 'A'}, restore_coord_dims=False).sum(dim='time')\n )\n ones_out = (\n (ones * wgts).resample({'time': 'A'}, restore_coord_dims=False).sum(dim='time')\n )\n count = (\n (ones * wgts.notnull()).resample({'time': 'A'}, restore_coord_dims=False).sum(dim='time')\n )\n else:\n mask = (\n darr.groupby(group_by_year, restore_coord_dims=False).mean(dim='time').notnull()\n ).rename(rename)\n \n da_sum = (\n (darr * wgts).groupby(group_by_year, restore_coord_dims=False).sum(dim='time')\n ).rename(rename)\n \n ones_out = (\n (ones * wgts).groupby(group_by_year, restore_coord_dims=False).sum(dim='time')\n ).rename(rename)\n \n count = (\n (ones * wgts.notnull()).groupby(group_by_year, restore_coord_dims=False).sum(dim='time')\n ).rename(rename)\n\n ones_out = ones_out.where(ones_out > 0.0)\n da_weighted_mean = da_sum / ones_out\n\n return da_weighted_mean.where(mask).where(count >= n_req) \n\n with warnings.catch_warnings():\n warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n ds_ann = dsop.map(weighted_mean_arr, wgts=time_wgt)\n\n # copy attrs\n for v in ds_ann:\n ds_ann[v].attrs = ds[v].attrs\n\n # restore coords\n ds_ann = xr.merge((ds_ann, ds[list(nontime_vars)]))\n\n # eliminate partials\n ndx = (time_wgt_grouped.count(dim=xr.ALL_DIMS) >= n_req).values\n if not ndx.all():\n ds_ann = ds_ann.isel(time=ndx)\n\n return ds_ann","def ExtendWithZeros(size_added, name=None):\n # This automatically infers the batch size from the shape of the input\n # See https://stackoverflow.com/questions/46465813/creating-constant-value-in-keras\n def func(x):\n batch_size = K.shape(x)[0]\n zeros = K.zeros((1, size_added))\n tiledzeros = K.tile(zeros, (batch_size, 1))\n return K.concatenate([x, tiledzeros])\n return keras.layers.Lambda(func, name=name)","def masked_temperature_softmax(x:torch.Tensor, idx:int, T:float=0.01):\n return torch.exp(x[idx, :] / T) / torch.exp(x[idx, :] / T).sum()","def __init__(self, kernel_size=11, log_t=False):\n super(Attention, self).__init__()\n assert kernel_size % 2 == 1, \"Kernel size should be odd for 'same' conv.\"\n padding = (kernel_size - 1) // 2\n self.conv = nn.Conv1d(1, 1, kernel_size, padding=padding)\n self.log_t = log_t","def self_attention(tensor,\n mask=None,\n mask_is_length=True,\n logit_fn=None,\n scale_dot=False,\n normalizer=tf.nn.softmax,\n scope=None,\n reuse=False):\n assert len(tensor.get_shape()) == 3, 'The rank of `tensor` must be 3 but got {}.'.format(\n len(tensor.get_shape()))\n with tf.variable_scope(scope or 'self_att', reuse=reuse):\n hidden_size = tensor.get_shape().as_list()[-1]\n if logit_fn is None:\n logits = tf.layers.dense(tensor, hidden_size, activation=tf.tanh)\n logits = tf.squeeze(tf.layers.dense(logits, 1), 2)\n else:\n logits = logit_fn(tensor)\n if scale_dot:\n logits /= tf.sqrt(hidden_size)\n if mask is not None:\n logits = exp_mask(logits, mask, mask_is_length=mask_is_length)\n weights = normalizer(logits)\n out = tf.reduce_sum(tf.expand_dims(weights, -1) * tensor, 1)\n return out,weights","def forward(\n self,\n embedding_sequence: torch.Tensor,\n encoder_output: torch.Tensor,\n source_mask: torch.Tensor,\n target_mask: torch.Tensor = None,\n apply_target_subsequent_mask: bool = True,\n ):\n\n if apply_target_subsequent_mask:\n # shape : (target_sequence_length, target_sequence_length)\n target_subsequent_mask = make_subsequent_mask(embedding_sequence)\n else:\n target_subsequent_mask = None\n\n embedding_sequence = self.sublayer[0](\n embedding_sequence,\n lambda x: self.self_attn(x, x, x, key_value_mask=target_mask, attention_mask=target_subsequent_mask),\n )\n embedding_sequence = self.sublayer[1](\n embedding_sequence, lambda x: self.src_attn(x, encoder_output, encoder_output, key_value_mask=source_mask)\n )\n return self.sublayer[2](embedding_sequence, self.feed_forward)","def applymask(self,mask):\n self.spec[mask==0]=np.nan","def RelativeAttentionLMLayer(d_feature,\n total_kv_pooling,\n n_heads=1,\n dropout=0.0,\n n_raw_tokens_generated=1,\n max_inference_length=3072,\n chunk_len=None,\n chunk_offset=None,\n mode='train'):\n\n attention = RelativeAttentionLayer(\n d_feature,\n total_kv_pooling,\n n_heads=n_heads,\n dropout=dropout,\n n_raw_tokens_generated=n_raw_tokens_generated,\n max_inference_length=max_inference_length,\n chunk_len=chunk_len,\n chunk_offset=chunk_offset,\n mode=mode)\n\n mask_layer = AttentionMaskLayer(\n total_kv_pooling=total_kv_pooling,\n max_inference_length=max_inference_length,\n chunk_len=chunk_len,\n chunk_offset=chunk_offset,\n n_raw_tokens_generated=n_raw_tokens_generated,\n mode=mode)\n\n return cb.Serial(\n cb.Branch(\n None,\n mask_layer, # vecs, mask\n ),\n attention, # vecs, mask\n cb.Select([0], n_in=2), # vecs\n )","def UseRelativeAttentionInTransformerLayer(transformer_params,\n rel_pos_emb_dim,\n atten_type=ATTEN_TRANSFORMER_XL):\n if not issubclass(transformer_params.cls, TransformerLayer):\n raise ValueError('Unsupported input transformer layer: %s' %\n transformer_params.cls)\n\n if atten_type not in (ATTEN_TRANSFORMER_XL, ATTEN_RPE):\n raise ValueError('Relative attention type: %s unsupported' % atten_type)\n\n # Gets multiheaded attention tpl from self attention config in transformer.\n trans_params_copy = transformer_params.Copy()\n if trans_params_copy.tr_self_atten_tpl is None:\n trans_params_copy.tr_self_atten_tpl = trans_params_copy.tr_atten_tpl.Copy()\n atten_tpl = trans_params_copy.tr_self_atten_tpl.atten_tpl\n\n # If already using relative attention class.\n if atten_tpl.cls in (MultiHeadedAttentionRPE, MultiHeadedAttentionXL,\n LocalSelfAttentionXL):\n atten_tpl.rel_pos_emb_dim = rel_pos_emb_dim\n return trans_params_copy\n\n if atten_type == ATTEN_TRANSFORMER_XL:\n if atten_tpl.cls == MultiHeadedAttention:\n rel_atten_tpl = MultiHeadedAttentionXL.Params()\n elif atten_tpl.cls == LocalSelfAttention:\n rel_atten_tpl = (LocalSelfAttentionXL.Params())\n else:\n raise ValueError('Unsupported attention: %s' % atten_tpl.cls)\n elif atten_type == ATTEN_RPE:\n rel_atten_tpl = MultiHeadedAttentionRPE.Params()\n\n rel_atten_tpl = hyperparams.CopyFieldsTo(atten_tpl, rel_atten_tpl)\n rel_atten_tpl.rel_pos_emb_dim = rel_pos_emb_dim\n\n trans_params_copy.tr_self_atten_tpl.atten_tpl = rel_atten_tpl\n return trans_params_copy","def attention_layer(from_tensor,\n to_tensor,\n attention_mask=None,\n num_attention_heads=1,\n size_per_head=512,\n query_act=None,\n key_act=None,\n value_act=None,\n attention_probs_dropout_prob=0.0,\n initializer_range=0.02,\n do_return_2d_tensor=False,\n batch_size=None,\n from_seq_length=None,\n to_seq_length=None, \n conv_kernel_size=9,\n head_ratio=2,\n conv_type=1,\n from_tensor_mask=None,\n to_tensor_mask=None,\n conv_method='gate'):\n\n def transpose_for_scores(input_tensor, batch_size, num_attention_heads,\n seq_length, width):\n output_tensor = tf.reshape(\n input_tensor, [batch_size, seq_length, num_attention_heads, width])\n\n output_tensor = tf.transpose(output_tensor, [0, 2, 1, 3])\n return output_tensor\n def reshape_for_conv(input_tensor, batch_size, num_attention_heads,\n seq_length, width):\n output_tensor = tf.reshape(\n input_tensor, [batch_size, seq_length, num_attention_heads*width])\n return output_tensor\n\n\n from_shape = bert_utils.get_shape_list(from_tensor, expected_rank=[2, 3])\n to_shape = bert_utils.get_shape_list(to_tensor, expected_rank=[2, 3])\n\n if len(from_shape) != len(to_shape):\n raise ValueError(\n \"The rank of `from_tensor` must match the rank of `to_tensor`.\")\n\n if len(from_shape) == 3:\n batch_size = from_shape[0]\n from_seq_length = from_shape[1]\n to_seq_length = to_shape[1]\n elif len(from_shape) == 2:\n if batch_size is None or from_seq_length is None or to_seq_length is None:\n raise ValueError(\n \"When passing in rank 2 tensors to attention_layer, the values \"\n \"for `batch_size`, `from_seq_length`, and `to_seq_length` \"\n \"must all be specified.\")\n\n # Scalar dimensions referenced here:\n # B = batch size (number of sequences)\n # F = `from_tensor` sequence length\n # T = `to_tensor` sequence length\n # N = `num_attention_heads`\n # H = `size_per_head`\n\n from_tensor_2d = bert_utils.reshape_to_matrix(from_tensor)\n to_tensor_2d = bert_utils.reshape_to_matrix(to_tensor)\n\n\n new_num_attention_heads = int(num_attention_heads/head_ratio)\n if new_num_attention_heads<1:\n head_ratio=num_attention_heads\n num_attention_heads=1\n else:\n num_attention_heads=new_num_attention_heads\n\n # `query_layer` = [B*F, N*H]\n query_layer = tf.layers.dense(\n from_tensor_2d,\n num_attention_heads * size_per_head,\n activation=query_act,\n name=\"query\",\n kernel_initializer=create_initializer(initializer_range))\n\n # `key_layer` = [B*T, N*H]\n key_layer = tf.layers.dense(\n to_tensor_2d,\n num_attention_heads * size_per_head,\n activation=key_act,\n name=\"key\",\n kernel_initializer=create_initializer(initializer_range))\n\n # `value_layer` = [B*T, N*H]\n value_layer = tf.layers.dense(\n to_tensor_2d,\n num_attention_heads * size_per_head,\n activation=value_act,\n name=\"value\",\n kernel_initializer=create_initializer(initializer_range))\n\n if conv_type in ['sdconv']:\n # [B,T, N*H]\n key_conv_attn_layer_input = reshape_for_conv(to_tensor_2d, batch_size, num_attention_heads*head_ratio,\n to_seq_length, size_per_head)\n\n if from_tensor_mask is not None and to_tensor_mask is not None:\n to_tensor_2d_mask = tf.cast(to_tensor_mask, tf.float32)[:, :, None]\n from_tensor_2d_mask = tf.cast(from_tensor_mask, tf.float32)[:, :, None]\n key_conv_attn_layer_input *= to_tensor_2d_mask\n tf.logging.info(\"== apply conv seq-masking on sequence padding ==\")\n\n key_conv_attn_layer = tf.layers.separable_conv1d(key_conv_attn_layer_input,\n num_attention_heads * size_per_head,\n conv_kernel_size,\n padding='same',\n activation=value_act,\n depthwise_initializer=create_initializer(1/conv_kernel_size),\n # depthwise_initializer=create_initializer(initializer_range),\n pointwise_initializer=create_initializer(initializer_range),\n name=\"conv_attn_key\")\n\n if from_tensor_mask is not None and to_tensor_mask is not None:\n key_conv_attn_layer *= to_tensor_2d_mask\n tf.logging.info(\"== apply conv seq-masking on sequence padding ==\")\n\n # [B*T, N*H]\n key_conv_attn_layer = bert_utils.reshape_to_matrix(key_conv_attn_layer)\n if conv_method == 'dot':\n conv_attn_layer = tf.multiply(key_conv_attn_layer, query_layer)\n tf.logging.info(\"== apply conv dot query_layer ==\")\n elif conv_method == 'gate':\n query_gate = tf.layers.dense(\n from_tensor_2d,\n num_attention_heads * size_per_head,\n activation=value_act,\n name=\"conv_query_gate\",\n kernel_initializer=create_initializer(initializer_range))\n\n conv_gated = tf.nn.sigmoid(tf.nn.dropout(query_gate, 1-attention_probs_dropout_prob))\n conv_attn_layer = key_conv_attn_layer * conv_gated + query_layer * (1-conv_gated)\n tf.logging.info(\"== apply conv gate query_layer ==\")\n else:\n conv_attn_layer = tf.multiply(key_conv_attn_layer, query_layer)\n tf.logging.info(\"== apply conv dot query_layer ==\")\n\n # [B*T, N*K]\n conv_kernel_layer = tf.layers.dense(\n conv_attn_layer,\n num_attention_heads * conv_kernel_size,\n activation=value_act,\n name=\"conv_attn_kernel\",\n kernel_initializer=create_initializer(initializer_range))\n # [B*T*N,K,1]\n conv_kernel_layer = tf.reshape(conv_kernel_layer, \n [batch_size*to_seq_length*num_attention_heads, conv_kernel_size, 1])\n \n # conv_kernel_layer = tf.nn.softmax(conv_kernel_layer, axis=1)\n attention_probs = tf.exp(tf.nn.log_softmax(conv_kernel_layer+1e-10, axis=-1))\n \n paddings = tf.constant([[0, 0,], [int((conv_kernel_size-1)/2), int((conv_kernel_size-1)/2)],[0,0]])\n \n conv_out_layer = tf.layers.dense(\n to_tensor_2d,\n num_attention_heads * size_per_head,\n activation=value_act,\n name=\"conv_attn_point\",\n kernel_initializer=create_initializer(initializer_range))\n # [B,T, N*H]\n conv_out_layer = tf.reshape(conv_out_layer,[batch_size,to_seq_length,num_attention_heads * size_per_head])\n if from_tensor_mask is not None and to_tensor_mask is not None:\n conv_out_layer *= to_tensor_2d_mask\n tf.logging.info(\"== apply conv seq-masking on sequence padding ==\")\n\n conv_out_layer = tf.pad(conv_out_layer, paddings, \"CONSTANT\")\n # unfold [B,T, N*H, K]\n unfold_conv_out_layer = tf.stack(\n [tf.slice(conv_out_layer, [0, i, 0],[batch_size,to_seq_length,num_attention_heads * size_per_head]) for i in range(conv_kernel_size)],-1)\n # following only work for gpu version\n # conv_out_layer = tf.reshape(conv_out_layer,[batch_size,to_seq_length,num_attention_heads * size_per_head,1])\n # unfold_conv_out_layer = tf.extract_image_patches(images=conv_out_layer, sizes=[1, conv_kernel_size, 1, 1], strides=[1, 1, 1, 1], rates=[1, 1, 1, 1], padding='SAME')\n\n conv_out_layer = tf.reshape(unfold_conv_out_layer,\n [batch_size*to_seq_length*num_attention_heads ,size_per_head, conv_kernel_size])\n\n conv_out_layer = tf.matmul(conv_out_layer, conv_kernel_layer)\n\n conv_out_layer = tf.reshape(conv_out_layer, [batch_size*to_seq_length, num_attention_heads*size_per_head])\n\n\n # `query_layer` = [B, N, F, H]\n query_layer = transpose_for_scores(query_layer, batch_size,\n num_attention_heads, from_seq_length,\n size_per_head)\n\n # `key_layer` = [B, N, T, H]\n key_layer = transpose_for_scores(key_layer, batch_size, num_attention_heads,\n to_seq_length, size_per_head)\n\n # Take the dot product between \"query\" and \"key\" to get the raw\n # attention scores.\n # `attention_scores` = [B, N, F, T]\n attention_scores = tf.matmul(query_layer, key_layer, transpose_b=True)\n attention_scores = tf.multiply(attention_scores,\n 1.0 / math.sqrt(float(size_per_head)))\n\n if attention_mask is not None:\n # `attention_mask` = [B, 1, F, T]\n attention_mask = tf.expand_dims(attention_mask, axis=[1])\n\n # Since attention_mask is 1.0 for positions we want to attend and 0.0 for\n # masked positions, this operation will create a tensor which is 0.0 for\n # positions we want to attend and -10000.0 for masked positions.\n adder = (1.0 - tf.cast(attention_mask, tf.float32)) * -10000.0\n\n # Since we are adding it to the raw scores before the softmax, this is\n # effectively the same as removing these entirely.\n attention_scores += adder\n\n # Normalize the attention scores to probabilities.\n # `attention_probs` = [B, N, F, T]\n # attention_probs = tf.nn.softmax(attention_scores)\n attention_probs = tf.exp(tf.nn.log_softmax(attention_scores+1e-10))\n\n # This is actually dropping out entire tokens to attend to, which might\n # seem a bit unusual, but is taken from the original Transformer paper.\n attention_probs = dropout(attention_probs, attention_probs_dropout_prob)\n\n # `value_layer` = [B, T, N, H]\n value_layer = tf.reshape(\n value_layer,\n [batch_size, to_seq_length, num_attention_heads, size_per_head])\n\n # `value_layer` = [B, N, T, H]\n value_layer = tf.transpose(value_layer, [0, 2, 1, 3])\n\n # `context_layer` = [B, N, F, H]\n context_layer = tf.matmul(attention_probs, value_layer)\n\n # `context_layer` = [B, F, N, H]\n context_layer = tf.transpose(context_layer, [0, 2, 1, 3])\n\n\n if conv_type in [\"sdconv\"]:\n # only applicable for self-attention, will cause error if from_seq_length not equal to_seq_length\n assert from_seq_length==to_seq_length\n conv_out = tf.reshape(\n conv_out_layer,\n [batch_size , from_seq_length, num_attention_heads , size_per_head])\n context_layer = tf.concat([context_layer, conv_out],2)\n num_attention_heads = num_attention_heads*2\n\n if do_return_2d_tensor:\n # `context_layer` = [B*F, N*H]\n context_layer = tf.reshape(\n context_layer,\n [batch_size * from_seq_length, num_attention_heads * size_per_head])\n else:\n # `context_layer` = [B, F, N*H]\n context_layer = tf.reshape(\n context_layer,\n [batch_size, from_seq_length, num_attention_heads * size_per_head])\n\n return context_layer, attention_probs, value_layer","def inject_latent(self, layer, inputs, target, action):\n del action\n # Latent for stochastic model\n filters = 128\n full_video = tf.stack(inputs + [target], axis=1)\n latent_mean, latent_std = self.construct_latent_tower(\n full_video, time_axis=1)\n latent = common_video.get_gaussian_tensor(latent_mean, latent_std)\n latent = tfl.flatten(latent)\n latent = tf.expand_dims(latent, axis=1)\n latent = tf.expand_dims(latent, axis=1)\n latent_mask = tfl.dense(latent, filters, name=\"latent_mask\")\n zeros_mask = tf.zeros(\n common_layers.shape_list(layer)[:-1] + [filters], dtype=tf.float32)\n layer = tf.concat([layer, latent_mask + zeros_mask], axis=-1)\n extra_loss = self.get_kl_loss([latent_mean], [latent_std])\n return layer, extra_loss","def build_attention_mask_3d_causal(source_mask, target_mask):\n causal_mask = make_inference_history_mask_3d(target_mask)\n mask = make_attention_mask_3d(source_mask, target_mask)\n mask = mask * causal_mask\n # invert mask for Megatron\n return mask < 0.5","def output_mask(self):\n output = self.output\n if isinstance(output, list):\n return [getattr(x, '_keras_mask', None) for x in output]\n else:\n return getattr(output, '_keras_mask', None)","def act(self, x: np.ndarray, t: int = None, noise: np.ndarray = None) -> np.ndarray:","def RelativeAttentionLayer(d_feature,\n total_kv_pooling,\n n_heads=1,\n dropout=0.0,\n n_raw_tokens_generated=1,\n max_inference_length=3072,\n chunk_len=None,\n chunk_offset=None,\n mode='train'):\n pos_emb = PositionalEmbeddings(\n d_feature,\n total_kv_pooling,\n max_inference_length=max_inference_length,\n chunk_len=chunk_len,\n chunk_offset=chunk_offset,\n n_raw_tokens_generated=n_raw_tokens_generated,\n mode=mode)\n\n attention = RelativeAttention( # pylint: disable=no-value-for-parameter\n total_kv_pooling=total_kv_pooling,\n n_heads=n_heads,\n dropout=dropout,\n n_raw_tokens_generated=n_raw_tokens_generated,\n max_inference_length=max_inference_length,\n chunk_len=chunk_len,\n chunk_offset=chunk_offset,\n mode=mode),\n\n assert d_feature % n_heads == 0\n d_head = d_feature // n_heads\n context_bias_layer = core.Weights(\n init.RandomNormalInitializer(1e-6), shape=(1, n_heads, 1, d_head))\n location_bias_layer = core.Weights(\n init.RandomNormalInitializer(1e-6), shape=(1, n_heads, 1, d_head))\n\n return cb.Serial(\n cb.Branch(\n cb.Serial(pos_emb, core.Dense(d_feature)),\n core.Dense(d_feature),\n core.Dense(d_feature),\n core.Dense(d_feature),\n cb.Select([1]) # mask\n ),\n context_bias_layer,\n location_bias_layer,\n attention,\n core.Dense(d_feature),\n )","def show_sent_attention(self, x):\n att_layer = self.model_sent.get_layer('sent_attention')\n prev_tensor = att_layer.input\n\n dummy_layer = Lambda(\n lambda x: att_layer._get_attention_weights(x)\n )(prev_tensor)\n\n return Model(self.model_sent.input, dummy_layer).predict(x)","def apply_layer(self, layer_id, func=..., v=..., inplace=...): # -> None:\n ...","def build(self, input_shape):\n hidden_dim = input_shape[2]\n self.W = self.add_weight(\n name='{}_W'.format(self.name),\n shape=(hidden_dim, hidden_dim,),\n initializer='uniform',\n trainable=True)\n self.b = self.add_weight(\n name='{}_b'.format(self.name),\n shape=(hidden_dim,),\n initializer='zeros',\n trainable=True)\n self.u = self.add_weight(\n name='{}_u'.format(self.name),\n shape=(hidden_dim,),\n initializer='uniform',\n trainable=True)\n super(AttentionLayer, self).build(input_shape)","def attention_layer(from_tensor,\n to_tensor,\n attention_mask=None,\n num_attention_heads=1,\n size_per_head=512,\n query_act=None,\n key_act=None,\n value_act=None,\n attention_probs_dropout_prob=0.0,\n initializer_range=0.02,\n do_return_2d_tensor=False,\n batch_size=None,\n from_seq_length=None,\n to_seq_length=None):\n\n def transpose_for_scores(input_tensor, batch_size, num_attention_heads,\n seq_length, width):\n output_tensor = tf.reshape(\n input_tensor, [batch_size, seq_length, num_attention_heads, width])\n\n output_tensor = tf.transpose(output_tensor, [0, 2, 1, 3])\n return output_tensor\n\n from_shape = get_shape_list(from_tensor, expected_rank=[2, 3])\n to_shape = get_shape_list(to_tensor, expected_rank=[2, 3])\n\n if len(from_shape) != len(to_shape):\n raise ValueError(\n \"The rank of `from_tensor` must match the rank of `to_tensor`.\")\n\n if len(from_shape) == 3:\n batch_size = from_shape[0]\n from_seq_length = from_shape[1]\n to_seq_length = to_shape[1]\n elif len(from_shape) == 2:\n if (batch_size is None or from_seq_length is None or to_seq_length is None):\n raise ValueError(\n \"When passing in rank 2 tensors to attention_layer, the values \"\n \"for `batch_size`, `from_seq_length`, and `to_seq_length` \"\n \"must all be specified.\")\n\n # Scalar dimensions referenced here:\n # B = batch size (number of sequences)\n # F = `from_tensor` sequence length\n # T = `to_tensor` sequence length\n # N = `num_attention_heads`\n # H = `size_per_head`\n\n from_tensor_2d = reshape_to_matrix(from_tensor)\n to_tensor_2d = reshape_to_matrix(to_tensor)\n\n # `query_layer` = [B*F, N*H]\n query_layer = tf.layers.dense(\n from_tensor_2d,\n num_attention_heads * size_per_head,\n activation=query_act,\n name=\"query\",\n kernel_initializer=create_initializer(initializer_range))\n\n # `key_layer` = [B*T, N*H]\n key_layer = tf.layers.dense(\n to_tensor_2d,\n num_attention_heads * size_per_head,\n activation=key_act,\n name=\"key\",\n kernel_initializer=create_initializer(initializer_range))\n\n # `value_layer` = [B*T, N*H]\n value_layer = tf.layers.dense(\n to_tensor_2d,\n num_attention_heads * size_per_head,\n activation=value_act,\n name=\"value\",\n kernel_initializer=create_initializer(initializer_range))\n\n # `query_layer` = [B, N, F, H]\n query_layer = transpose_for_scores(query_layer, batch_size,\n num_attention_heads, from_seq_length,\n size_per_head)\n\n # `key_layer` = [B, N, T, H]\n key_layer = transpose_for_scores(key_layer, batch_size, num_attention_heads,\n to_seq_length, size_per_head)\n\n # Take the dot product between \"query\" and \"key\" to get the raw\n # attention scores.\n # `attention_scores` = [B, N, F, T]\n attention_scores = tf.matmul(query_layer, key_layer, transpose_b=True)\n attention_scores = tf.multiply(attention_scores,\n 1.0 / math.sqrt(float(size_per_head)))\n\n if attention_mask is not None:\n # `attention_mask` = [B, 1, F, T]\n attention_mask = tf.expand_dims(attention_mask, axis=[1])\n\n # Since attention_mask is 1.0 for positions we want to attend and 0.0 for\n # masked positions, this operation will create a tensor which is 0.0 for\n # positions we want to attend and -10000.0 for masked positions.\n adder = (1.0 - tf.cast(attention_mask, tf.float32)) * -10000.0\n\n # Since we are adding it to the raw scores before the softmax, this is\n # effectively the same as removing these entirely.\n attention_scores += adder\n\n # Normalize the attention scores to probabilities.\n # `attention_probs` = [B, N, F, T]\n attention_probs = tf.nn.softmax(attention_scores)\n\n # This is actually dropping out entire tokens to attend to, which might\n # seem a bit unusual, but is taken from the original Transformer paper.\n attention_probs = dropout(attention_probs, attention_probs_dropout_prob)\n\n # `value_layer` = [B, T, N, H]\n value_layer = tf.reshape(\n value_layer,\n [batch_size, to_seq_length, num_attention_heads, size_per_head])\n\n # `value_layer` = [B, N, T, H]\n value_layer = tf.transpose(value_layer, [0, 2, 1, 3])\n\n # `context_layer` = [B, N, F, H]\n context_layer = tf.matmul(attention_probs, value_layer)\n\n # `context_layer` = [B, F, N, H]\n context_layer = tf.transpose(context_layer, [0, 2, 1, 3])\n\n if do_return_2d_tensor:\n # `context_layer` = [B*F, N*V]\n context_layer = tf.reshape(\n context_layer,\n [batch_size * from_seq_length, num_attention_heads * size_per_head])\n else:\n # `context_layer` = [B, F, N*V]\n context_layer = tf.reshape(\n context_layer,\n [batch_size, from_seq_length, num_attention_heads * size_per_head])\n\n return context_layer","def op_attenuator(t):\n att = np.array([[t, 0, 0, 0],\n [0, t, 0, 0],\n [0, 0, t, 0],\n [0, 0, 0, t]])\n return att","def forward(self, tgt, memory, tgt_mask=None, memory_mask=None):\n # m = memory\n # LayerNorm + SelfAtt + Dropout + Residual\n tgt = self.sublayer[0](tgt, lambda x: self.self_attn(x, x, x, tgt_mask))\n # LayerNorm + Att + Dropout + Residual\n tgt = self.sublayer[1](tgt, lambda x: self.memory_attn(x, memory, memory, memory_mask))\n # LayerNorm + FF + Dropout +Residual\n layer_output = self.sublayer[2](tgt, self.feed_forward)\n return layer_output","def local_attention(inputs, num_filters, filter_size=5, initializer=None, reuse=None,\n name=''):\n print(\"Local Attentional\")\n weighted_inputs, _ = convolutional_attention(inputs, filter_size=filter_size,\n initializer=initializer, name='local{}'.format(name),\n reuse=reuse)\n conv_output = build_cnn(weighted_inputs, num_filters, filter_sizes=3,\n initializer=initializer, name='local{}'.format(name),\n reuse=reuse)\n print(conv_output)\n return conv_output"],"string":"[\n \"def _Attention(self, name, is_causal=True):\\n p = self.params\\n tr_atten_p = TransformerAttentionLayer.Params().Set(\\n name='transformer_atten',\\n input_dim=p.model_dim,\\n hidden_dim=p.attention_hidden_dim or p.model_dim,\\n is_masked=is_causal,\\n num_heads=p.num_heads,\\n residual_dropout_prob=p.residual_dropout_prob,\\n atten_dropout_prob=p.atten_dropout_prob,\\n fprop_dtype=p.fprop_dtype,\\n add_unnormalized_input=p.selfatten_add_unnormalized_input,\\n )\\n tr_atten_p.atten_tpl.use_bias = p.use_bias\\n tr_atten_p.atten_tpl.enable_value_proj = p.selfatten_enable_value_proj\\n tr_atten_p.atten_tpl.enable_query_scale = p.enable_query_scale\\n tr_atten_p.atten_tpl.enable_per_dim_scale = p.enable_per_dim_scale\\n tr_atten_p.atten_tpl.device_mesh = p.device_mesh\\n tr_atten_p.atten_tpl.weight_split_dims_mapping = (\\n p.weight_split_dims_mapping.dnh)\\n tr_atten_p.atten_tpl.activation_split_dims_mapping.blnh = (\\n p.activation_split_dims_mapping.blnh)\\n tr_atten_p.atten_tpl.activation_split_dims_mapping.bld = (\\n p.activation_split_dims_mapping.bld)\\n if p.deterministic_dropout:\\n tr_atten_p.dropout_tpl = layers.DeterministicDropoutLayer.Params()\\n tr_atten_p.atten_p.dropout_tpl = layers.DeterministicDropoutLayer.Params()\\n\\n return self._Graph(\\n name,\\n ['i'], # input NestedMap with {vec, paddings}\\n ['o'], # output NestedMap with {vec, paddings}\\n ('i.vec->split_i',\\n self.MeshSplit('input_split', p.activation_split_dims_mapping.bld)),\\n ('split_i,split_i,i.paddings->o.vec,unused_prob', tr_atten_p),\\n ('i.paddings->o.paddings', self._Id('id')))\",\n \"def attention_mask(model, x):\\n config = model.config\\n input_mask = model.inputs[\\\"input_mask\\\"]\\n final_mask = model.builder.customOp(opName=\\\"AttentionMask\\\",\\n opVersion=1,\\n domain=\\\"ai.graphcore\\\",\\n inputs=[input_mask, x],\\n attributes={\\\"dataType\\\": model.config.popart_dtype})[0]\\n final_mask = model.detach(final_mask)\\n return final_mask\",\n \"def add_mask_layer(self):\\n return Masking(mask_value=self.mask_value, input_shape=(self.max_sequence_size, 1))\",\n \"def make_attention_lstm():\\n from tensorflow.keras import activations\\n from tensorflow.keras import backend as K\\n from tensorflow.keras import constraints, initializers, regularizers\\n\\n # from keras.legacy import interfaces\\n from tensorflow.keras.layers import RNN, InputSpec, Layer\\n\\n def _time_distributed_dense(\\n x,\\n w,\\n b=None,\\n dropout=None,\\n input_dim=None,\\n output_dim=None,\\n timesteps=None,\\n training=None,\\n ):\\n \\\"\\\"\\\"Apply `y . w + b` for every temporal slice y of x.\\n\\n # Arguments\\n x: input tensor.\\n w: weight matrix.\\n b: optional bias vector.\\n dropout: wether to apply dropout (same dropout mask\\n for every temporal slice of the input).\\n input_dim: integer; optional dimensionality of the input.\\n output_dim: integer; optional dimensionality of the output.\\n timesteps: integer; optional number of timesteps.\\n training: training phase tensor or boolean.\\n # Returns\\n Output tensor.\\n \\\"\\\"\\\"\\n if not input_dim:\\n input_dim = K.shape(x)[2]\\n if not timesteps:\\n timesteps = K.shape(x)[1]\\n if not output_dim:\\n output_dim = K.int_shape(w)[1]\\n\\n if dropout is not None and 0.0 < dropout < 1.0:\\n # apply the same dropout pattern at every timestep\\n ones = K.ones_like(K.reshape(x[:, 0, :], (-1, input_dim)))\\n dropout_matrix = K.dropout(ones, dropout)\\n expanded_dropout_matrix = K.repeat(dropout_matrix, timesteps)\\n x = K.in_train_phase(x * expanded_dropout_matrix, x, training=training)\\n\\n # collapse time dimension and batch dimension together\\n x = K.reshape(x, (-1, input_dim))\\n x = K.dot(x, w)\\n if b is not None:\\n x = K.bias_add(x, b)\\n # reshape to 3D tensor\\n if K.backend() == \\\"tensorflow\\\":\\n x = K.reshape(x, K.stack([-1, timesteps, output_dim]))\\n x.set_shape([None, None, output_dim])\\n else:\\n x = K.reshape(x, (-1, timesteps, output_dim))\\n return x\\n\\n class AttentionLSTMCell(Layer):\\n \\\"\\\"\\\"Long-Short Term Memory unit - with Attention.\\n\\n # Arguments\\n units: Positive integer, dimensionality of the output space.\\n activation: Activation function to use\\n (see [activations](keras/activations.md)).\\n If you pass None, no activation is applied\\n (ie. \\\"linear\\\" activation: `a(x) = x`).\\n recurrent_activation: Activation function to use\\n for the recurrent step\\n (see [activations](keras/activations.md)).\\n attention_activation: Activation function to use\\n for the attention step. If you pass None, no activation is applied\\n (ie. \\\"linear\\\" activation: `a(x) = x`).\\n (see [activations](keras/activations.md)).\\n use_bias: Boolean, whether the layer uses a bias vector.\\n kernel_initializer: Initializer for the `kernel` weights matrix,\\n used for the linear transformation of the inputs.\\n (see [initializers](../initializers.md)).\\n recurrent_initializer: Initializer for the `recurrent_kernel`\\n weights matrix,\\n used for the linear transformation of the recurrent state.\\n (see [initializers](../initializers.md)).\\n bias_initializer: Initializer for the bias vector\\n (see [initializers](../initializers.md)).\\n attention_initializer: Initializer for the `attention_kernel` weights\\n matrix, used for the linear transformation of the inputs.\\n (see [initializers](../initializers.md)).\\n use_chrono_initialization: Boolean.\\n If True, add 1 to the bias of the forget gate at initialization.\\n Setting it to true will also force `bias_initializer=\\\"zeros\\\"`.\\n This is recommended in [Jozefowicz et al.]\\n (http://www.jmlr.org/proceedings/papers/v37/jozefowicz15.pdf)\\n kernel_regularizer: Regularizer function applied to\\n the `kernel` weights matrix\\n (see [regularizer](../regularizers.md)).\\n recurrent_regularizer: Regularizer function applied to\\n the `recurrent_kernel` weights matrix\\n (see [regularizer](../regularizers.md)).\\n bias_regularizer: Regularizer function applied to the bias vector\\n (see [regularizer](../regularizers.md)).\\n activity_regularizer: Regularizer function applied to\\n the output of the layer (its \\\"activation\\\").\\n (see [regularizer](../regularizers.md)).\\n attention_regularizer: Regularizer function applied to\\n the `attention_kernel` weights matrix\\n (see [regularizer](../regularizers.md)).\\n kernel_constraint: Constraint function applied to\\n the `kernel` weights matrix\\n (see [constraints](../constraints.md)).\\n recurrent_constraint: Constraint function applied to\\n the `recurrent_kernel` weights matrix\\n (see [constraints](../constraints.md)).\\n bias_constraint: Constraint function applied to the bias vector\\n (see [constraints](../constraints.md)).\\n attention_constraint: Constraint function applied to\\n the `attention_kernel` weights matrix\\n (see [constraints](../constraints.md)).\\n dropout: Float between 0 and 1.\\n Fraction of the units to drop for\\n the linear transformation of the inputs.\\n recurrent_dropout: Float between 0 and 1.\\n Fraction of the units to drop for\\n the linear transformation of the recurrent state.\\n return_attention: Returns the attention vector instead of\\n the internal state.\\n # References\\n - [Long short-term memory]\\n (http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf)\\n (original 1997 paper)\\n - [Learning to forget: Continual prediction with LSTM]\\n (http://www.mitpressjournals.org/doi/pdf/10.1162/089976600300015015)\\n - [Supervised sequence labeling with recurrent neural networks]\\n (http://www.cs.toronto.edu/~graves/preprint.pdf)\\n - [A Theoretically Grounded Application of Dropout\\n in Recurrent Neural Networks]\\n (http://arxiv.org/abs/1512.05287)\\n - [Bahdanau, Cho & Bengio (2014),\\n \\\"Neural Machine Translation by Jointly Learning to Align and Translate\\\"]\\n (https://arxiv.org/pdf/1409.0473.pdf)\\n - [Xu, Ba, Kiros, Cho, Courville, Salakhutdinov, Zemel & Bengio (2016)\\n \\\"Show, Attend and Tell: Neural Image Caption Generation\\n with Visual Attention\\\"]\\n (http://arxiv.org/pdf/1502.03044.pdf)\\n \\\"\\\"\\\"\\n\\n _tags = {\\\"python_dependencies\\\": \\\"tensorflow\\\"}\\n\\n def __init__(\\n self,\\n units,\\n activation=\\\"tanh\\\",\\n recurrent_activation=\\\"hard_sigmoid\\\",\\n attention_activation=\\\"tanh\\\",\\n use_bias=True,\\n kernel_initializer=\\\"glorot_uniform\\\",\\n recurrent_initializer=\\\"orthogonal\\\",\\n attention_initializer=\\\"orthogonal\\\",\\n bias_initializer=\\\"zeros\\\",\\n unit_forget_bias=True,\\n kernel_regularizer=None,\\n recurrent_regularizer=None,\\n bias_regularizer=None,\\n activity_regularizer=None,\\n attention_regularizer=None,\\n kernel_constraint=None,\\n recurrent_constraint=None,\\n bias_constraint=None,\\n attention_constraint=None,\\n dropout=0.0,\\n recurrent_dropout=0.0,\\n return_attention=False,\\n implementation=1,\\n **kwargs,\\n ):\\n super().__init__(**kwargs)\\n self.input_spec = [InputSpec(ndim=2)]\\n self.units = units\\n self.activation = activations.get(activation)\\n self.recurrent_activation = activations.get(recurrent_activation)\\n self.attention_activation = activations.get(attention_activation)\\n self.use_bias = use_bias\\n\\n self.kernel_initializer = initializers.get(kernel_initializer)\\n self.recurrent_initializer = initializers.get(recurrent_initializer)\\n self.attention_initializer = initializers.get(attention_initializer)\\n self.bias_initializer = initializers.get(bias_initializer)\\n self.unit_forget_bias = unit_forget_bias\\n\\n self.kernel_regularizer = regularizers.get(kernel_regularizer)\\n self.recurrent_regularizer = regularizers.get(recurrent_regularizer)\\n self.bias_regularizer = regularizers.get(bias_regularizer)\\n self.activity_regularizer = regularizers.get(activity_regularizer)\\n self.attention_regularizer = regularizers.get(attention_regularizer)\\n\\n self.kernel_constraint = constraints.get(kernel_constraint)\\n self.recurrent_constraint = constraints.get(recurrent_constraint)\\n self.bias_constraint = constraints.get(bias_constraint)\\n self.attention_constraint = constraints.get(attention_constraint)\\n\\n self.dropout = min(1.0, max(0.0, dropout))\\n self.recurrent_dropout = min(1.0, max(0.0, recurrent_dropout))\\n self.return_attention = return_attention\\n self._dropout_mask = None\\n self._recurrent_dropout_mask = None\\n self.implementation = implementation\\n self.state_spec = [\\n InputSpec(shape=(None, self.units)),\\n InputSpec(shape=(None, self.units)),\\n ]\\n self.state_size = (self.units, self.units)\\n\\n def build(self, input_shape):\\n \\\"\\\"\\\"Build the AttentionLSTMCell object.\\\"\\\"\\\"\\n if hasattr(self, \\\"timesteps\\\") and self.timesteps is not None:\\n self.timestep_dim = self.timesteps\\n else:\\n self.timestep_dim = 1 # input_shape[0]\\n\\n self.input_dim = input_shape[-1]\\n\\n self.kernel = self.add_weight(\\n shape=(self.input_dim, self.units * 4),\\n name=\\\"kernel\\\",\\n initializer=self.kernel_initializer,\\n regularizer=self.kernel_regularizer,\\n constraint=self.kernel_constraint,\\n )\\n self.recurrent_kernel = self.add_weight(\\n shape=(self.units, self.units * 4),\\n name=\\\"recurrent_kernel\\\",\\n initializer=self.recurrent_initializer,\\n regularizer=self.recurrent_regularizer,\\n constraint=self.recurrent_constraint,\\n )\\n\\n # add attention kernel\\n self.attention_kernel = self.add_weight(\\n shape=(self.input_dim, self.units * 4),\\n name=\\\"attention_kernel\\\",\\n initializer=self.attention_initializer,\\n regularizer=self.attention_regularizer,\\n constraint=self.attention_constraint,\\n )\\n\\n # add attention weights\\n # weights for attention model\\n self.attention_weights = self.add_weight(\\n shape=(self.input_dim, self.units),\\n name=\\\"attention_W\\\",\\n initializer=self.attention_initializer,\\n regularizer=self.attention_regularizer,\\n constraint=self.attention_constraint,\\n )\\n\\n self.attention_recurrent_weights = self.add_weight(\\n shape=(self.units, self.units),\\n name=\\\"attention_U\\\",\\n initializer=self.recurrent_initializer,\\n regularizer=self.recurrent_regularizer,\\n constraint=self.recurrent_constraint,\\n )\\n\\n if self.use_bias:\\n if self.unit_forget_bias:\\n\\n def bias_initializer(shape, *args, **kwargs):\\n return K.concatenate(\\n [\\n self.bias_initializer((self.units,), *args, **kwargs),\\n initializers.Ones()((self.units,), *args, **kwargs),\\n self.bias_initializer(\\n (self.units * 2,), *args, **kwargs\\n ),\\n ]\\n )\\n\\n else:\\n bias_initializer = self.bias_initializer\\n self.bias = self.add_weight(\\n shape=(self.units * 4,),\\n name=\\\"bias\\\",\\n initializer=bias_initializer,\\n regularizer=self.bias_regularizer,\\n constraint=self.bias_constraint,\\n )\\n\\n self.attention_bias = self.add_weight(\\n shape=(self.units,),\\n name=\\\"attention_b\\\",\\n initializer=self.bias_initializer,\\n regularizer=self.bias_regularizer,\\n constraint=self.bias_constraint,\\n )\\n\\n self.attention_recurrent_bias = self.add_weight(\\n shape=(self.units, 1),\\n name=\\\"attention_v\\\",\\n initializer=self.bias_initializer,\\n regularizer=self.bias_regularizer,\\n constraint=self.bias_constraint,\\n )\\n else:\\n self.bias = None\\n self.attention_bias = None\\n self.attention_recurrent_bias = None\\n\\n self.kernel_i = self.kernel[:, : self.units]\\n self.kernel_f = self.kernel[:, self.units : self.units * 2]\\n self.kernel_c = self.kernel[:, self.units * 2 : self.units * 3]\\n self.kernel_o = self.kernel[:, self.units * 3 :]\\n\\n self.recurrent_kernel_i = self.recurrent_kernel[:, : self.units]\\n self.recurrent_kernel_f = self.recurrent_kernel[\\n :, self.units : self.units * 2\\n ]\\n self.recurrent_kernel_c = self.recurrent_kernel[\\n :, self.units * 2 : self.units * 3\\n ]\\n self.recurrent_kernel_o = self.recurrent_kernel[:, self.units * 3 :]\\n\\n self.attention_i = self.attention_kernel[:, : self.units]\\n self.attention_f = self.attention_kernel[:, self.units : self.units * 2]\\n self.attention_c = self.attention_kernel[:, self.units * 2 : self.units * 3]\\n self.attention_o = self.attention_kernel[:, self.units * 3 :]\\n\\n if self.use_bias:\\n self.bias_i = self.bias[: self.units]\\n self.bias_f = self.bias[self.units : self.units * 2]\\n self.bias_c = self.bias[self.units * 2 : self.units * 3]\\n self.bias_o = self.bias[self.units * 3 :]\\n else:\\n self.bias_i = None\\n self.bias_f = None\\n self.bias_c = None\\n self.bias_o = None\\n\\n self.built = True\\n\\n def _generate_dropout_mask(self, inputs, training=None):\\n if 0 < self.dropout < 1:\\n ones = K.ones_like(K.squeeze(inputs[:, 0:1, :], axis=1))\\n\\n def dropped_inputs():\\n return K.dropout(ones, self.dropout)\\n\\n self._dropout_mask = [\\n K.in_train_phase(dropped_inputs, ones, training=training)\\n for _ in range(4)\\n ]\\n else:\\n self._dropout_mask = None\\n\\n def _generate_recurrent_dropout_mask(self, inputs, training=None):\\n if 0 < self.recurrent_dropout < 1:\\n ones = K.ones_like(K.reshape(inputs[:, 0, 0], (-1, 1)))\\n ones = K.tile(ones, (1, self.units))\\n\\n def dropped_inputs():\\n return K.dropout(ones, self.dropout)\\n\\n self._recurrent_dropout_mask = [\\n K.in_train_phase(dropped_inputs, ones, training=training)\\n for _ in range(4)\\n ]\\n else:\\n self._recurrent_dropout_mask = None\\n\\n def call(self, inputs, states, training=None):\\n \\\"\\\"\\\"Call the AttentionLSTMCell.\\\"\\\"\\\"\\n # dropout matrices for input units\\n dp_mask = self._dropout_mask\\n # dropout matrices for recurrent units\\n rec_dp_mask = self._recurrent_dropout_mask\\n\\n h_tm1 = states[0] # previous memory state\\n c_tm1 = states[1] # previous carry state\\n\\n # alignment model\\n h_att = K.repeat(h_tm1, self.timestep_dim)\\n att = _time_distributed_dense(\\n inputs,\\n self.attention_weights,\\n self.attention_bias,\\n input_dim=self.input_dim,\\n output_dim=self.units,\\n timesteps=self.timestep_dim,\\n )\\n attention_ = self.attention_activation(\\n K.dot(h_att, self.attention_recurrent_weights) + att\\n ) # energy\\n attention_ = K.squeeze(\\n K.dot(attention_, self.attention_recurrent_bias), 2\\n ) # energy\\n\\n alpha = K.exp(attention_)\\n\\n if dp_mask is not None:\\n alpha *= dp_mask[0]\\n\\n alpha /= K.sum(alpha, axis=1, keepdims=True)\\n alpha_r = K.repeat(alpha, self.input_dim)\\n alpha_r = K.permute_dimensions(alpha_r, (0, 2, 1))\\n\\n # make context vector (soft attention after Bahdanau et al.)\\n z_hat = inputs * alpha_r\\n # context_sequence = z_hat\\n z_hat = K.sum(z_hat, axis=1)\\n\\n if self.implementation == 1:\\n if 0 < self.dropout < 1.0:\\n inputs_i = inputs * dp_mask[0]\\n inputs_f = inputs * dp_mask[1]\\n inputs_c = inputs * dp_mask[2]\\n inputs_o = inputs * dp_mask[3]\\n else:\\n inputs_i = inputs\\n inputs_f = inputs\\n inputs_c = inputs\\n inputs_o = inputs\\n x_i = K.dot(inputs_i, self.kernel_i)\\n x_f = K.dot(inputs_f, self.kernel_f)\\n x_c = K.dot(inputs_c, self.kernel_c)\\n x_o = K.dot(inputs_o, self.kernel_o)\\n if self.use_bias:\\n x_i = K.bias_add(x_i, self.bias_i)\\n x_f = K.bias_add(x_f, self.bias_f)\\n x_c = K.bias_add(x_c, self.bias_c)\\n x_o = K.bias_add(x_o, self.bias_o)\\n\\n if 0 < self.recurrent_dropout < 1.0:\\n h_tm1_i = h_tm1 * rec_dp_mask[0]\\n h_tm1_f = h_tm1 * rec_dp_mask[1]\\n h_tm1_c = h_tm1 * rec_dp_mask[2]\\n h_tm1_o = h_tm1 * rec_dp_mask[3]\\n else:\\n h_tm1_i = h_tm1\\n h_tm1_f = h_tm1\\n h_tm1_c = h_tm1\\n h_tm1_o = h_tm1\\n i = self.recurrent_activation(\\n x_i\\n + K.dot(h_tm1_i, self.recurrent_kernel_i)\\n + K.dot(z_hat, self.attention_i)\\n )\\n f = self.recurrent_activation(\\n x_f\\n + K.dot(h_tm1_f, self.recurrent_kernel_f)\\n + K.dot(z_hat, self.attention_f)\\n )\\n c = f * c_tm1 + i * self.activation(\\n x_c\\n + K.dot(h_tm1_c, self.recurrent_kernel_c)\\n + K.dot(z_hat, self.attention_c)\\n )\\n o = self.recurrent_activation(\\n x_o\\n + K.dot(h_tm1_o, self.recurrent_kernel_o)\\n + K.dot(z_hat, self.attention_o)\\n )\\n else:\\n if 0.0 < self.dropout < 1.0:\\n inputs *= dp_mask[0]\\n z = K.dot(inputs, self.kernel)\\n if 0.0 < self.recurrent_dropout < 1.0:\\n h_tm1 *= rec_dp_mask[0]\\n z += K.dot(h_tm1, self.recurrent_kernel)\\n z += K.dot(z_hat, self.attention_kernel)\\n\\n if self.use_bias:\\n z = K.bias_add(z, self.bias)\\n\\n z0 = z[:, : self.units]\\n z1 = z[:, self.units : 2 * self.units]\\n z2 = z[:, 2 * self.units : 3 * self.units]\\n z3 = z[:, 3 * self.units :]\\n\\n i = self.recurrent_activation(z0)\\n f = self.recurrent_activation(z1)\\n c = f * c_tm1 + i * self.activation(z2)\\n o = self.recurrent_activation(z3)\\n\\n h = o * self.activation(c)\\n if 0 < self.dropout + self.recurrent_dropout:\\n if training is None:\\n h._uses_learning_phase = True\\n return h, [h, c]\\n\\n class AttentionLSTM(RNN):\\n \\\"\\\"\\\"Long-Short Term Memory unit - with Attention.\\n\\n # Arguments\\n units: Positive integer, dimensionality of the output space.\\n activation: Activation function to use\\n (see [activations](keras/activations.md)).\\n If you pass None, no activation is applied\\n (ie. \\\"linear\\\" activation: `a(x) = x`).\\n recurrent_activation: Activation function to use\\n for the recurrent step\\n (see [activations](keras/activations.md)).\\n attention_activation: Activation function to use\\n for the attention step. If you pass None, no activation is applied\\n (ie. \\\"linear\\\" activation: `a(x) = x`).\\n (see [activations](keras/activations.md)).\\n use_bias: Boolean, whether the layer uses a bias vector.\\n kernel_initializer: Initializer for the `kernel` weights matrix,\\n used for the linear transformation of the inputs.\\n (see [initializers](../initializers.md)).\\n recurrent_initializer: Initializer for the `recurrent_kernel`\\n weights matrix,\\n used for the linear transformation of the recurrent state.\\n (see [initializers](../initializers.md)).\\n bias_initializer: Initializer for the bias vector\\n (see [initializers](../initializers.md)).\\n attention_initializer: Initializer for the `attention_kernel` weights\\n matrix, used for the linear transformation of the inputs.\\n (see [initializers](../initializers.md)).\\n use_chrono_initialization: Boolean.\\n If True, add 1 to the bias of the forget gate at initialization.\\n Setting it to true will also force `bias_initializer=\\\"zeros\\\"`.\\n This is recommended in [Jozefowicz et al.]\\n (http://www.jmlr.org/proceedings/papers/v37/jozefowicz15.pdf)\\n kernel_regularizer: Regularizer function applied to\\n the `kernel` weights matrix\\n (see [regularizer](../regularizers.md)).\\n recurrent_regularizer: Regularizer function applied to\\n the `recurrent_kernel` weights matrix\\n (see [regularizer](../regularizers.md)).\\n bias_regularizer: Regularizer function applied to the bias vector\\n (see [regularizer](../regularizers.md)).\\n activity_regularizer: Regularizer function applied to\\n the output of the layer (its \\\"activation\\\").\\n (see [regularizer](../regularizers.md)).\\n attention_regularizer: Regularizer function applied to\\n the `attention_kernel` weights matrix\\n (see [regularizer](../regularizers.md)).\\n kernel_constraint: Constraint function applied to\\n the `kernel` weights matrix\\n (see [constraints](../constraints.md)).\\n recurrent_constraint: Constraint function applied to\\n the `recurrent_kernel` weights matrix\\n (see [constraints](../constraints.md)).\\n bias_constraint: Constraint function applied to the bias vector\\n (see [constraints](../constraints.md)).\\n attention_constraint: Constraint function applied to\\n the `attention_kernel` weights matrix\\n (see [constraints](../constraints.md)).\\n dropout: Float between 0 and 1.\\n Fraction of the units to drop for\\n the linear transformation of the inputs.\\n recurrent_dropout: Float between 0 and 1.\\n Fraction of the units to drop for\\n the linear transformation of the recurrent state.\\n implementation: Implementation mode, either 1 or 2.\\n return_sequences: Boolean. Whether to return the last output.\\n in the output sequence, or the full sequence.\\n return_state: Boolean. Whether to return the last state\\n in addition to the output.\\n return_attention: Returns the attention vector instead of\\n the internal state.\\n go_backwards: Boolean (default False).\\n If True, process the input sequence backwards and return the\\n reversed sequence.\\n stateful: Boolean (default False). If True, the last state\\n for each sample at index i in a batch will be used as initial\\n state for the sample of index i in the following batch.\\n unroll: Boolean (default False).\\n If True, the network will be unrolled,\\n else a symbolic loop will be used.\\n Unrolling can speed-up a RNN,\\n although it tends to be more memory-intensive.\\n Unrolling is only suitable for short sequences.\\n # References\\n - [Long short-term memory]\\n (http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf)\\n (original 1997 paper)\\n - [Learning to forget: Continual prediction with LSTM]\\n (http://www.mitpressjournals.org/doi/pdf/10.1162/089976600300015015)\\n - [Supervised sequence labeling with recurrent neural networks]\\n (http://www.cs.toronto.edu/~graves/preprint.pdf)\\n - [A Theoretically Grounded Application of Dropout\\n in Recurrent Neural Networks]\\n (http://arxiv.org/abs/1512.05287)\\n - [Bahdanau, Cho & Bengio (2014)\\n \\\"Neural Machine Translation by Jointly Learning to Align and Translate\\\"]\\n (https://arxiv.org/pdf/1409.0473.pdf)\\n - [Xu, Ba, Kiros, Cho, Courville, Salakhutdinov, Zemel & Bengio (2016)\\n \\\"Show, Attend and Tell: Neural Image Caption Generation\\n with Visual Attention\\\"]\\n (http://arxiv.org/pdf/1502.03044.pdf)\\n \\\"\\\"\\\"\\n\\n _tags = {\\\"python_dependencies\\\": \\\"tensorflow\\\"}\\n\\n # '@interfaces.legacy_recurrent_support\\n def __init__(\\n self,\\n units,\\n activation=\\\"tanh\\\",\\n recurrent_activation=\\\"hard_sigmoid\\\",\\n attention_activation=\\\"tanh\\\",\\n use_bias=True,\\n kernel_initializer=\\\"glorot_uniform\\\",\\n recurrent_initializer=\\\"orthogonal\\\",\\n attention_initializer=\\\"orthogonal\\\",\\n bias_initializer=\\\"zeros\\\",\\n unit_forget_bias=True,\\n kernel_regularizer=None,\\n recurrent_regularizer=None,\\n bias_regularizer=None,\\n activity_regularizer=None,\\n attention_regularizer=None,\\n kernel_constraint=None,\\n recurrent_constraint=None,\\n bias_constraint=None,\\n attention_constraint=None,\\n dropout=0.0,\\n recurrent_dropout=0.0,\\n implementation=1,\\n return_sequences=False,\\n return_state=False,\\n return_attention=False,\\n go_backwards=False,\\n stateful=False,\\n unroll=False,\\n **kwargs,\\n ):\\n import warnings\\n\\n if implementation == 0:\\n warnings.warn(\\n \\\"`implementation=0` has been deprecated, \\\"\\n \\\"and now defaults to `implementation=1`.\\\"\\n \\\"Please update your layer call.\\\",\\n stacklevel=2,\\n )\\n implementation = 1\\n\\n if K.backend() == \\\"cntk\\\":\\n if not kwargs.get(\\\"unroll\\\") and (dropout > 0 or recurrent_dropout > 0):\\n warnings.warn(\\n \\\"RNN dropout is not supported with the CNTK backend \\\"\\n \\\"when using dynamic RNNs (i.e. non-unrolled). \\\"\\n \\\"You can either set `unroll=True`, \\\"\\n \\\"set `dropout` and `recurrent_dropout` to 0, \\\"\\n \\\"or use a different backend.\\\",\\n stacklevel=2,\\n )\\n dropout = 0.0\\n recurrent_dropout = 0.0\\n\\n cell = AttentionLSTMCell(\\n units,\\n activation=activation,\\n recurrent_activation=recurrent_activation,\\n attention_activation=attention_activation,\\n use_bias=use_bias,\\n kernel_initializer=kernel_initializer,\\n recurrent_initializer=recurrent_initializer,\\n attention_initializer=attention_initializer,\\n bias_initializer=bias_initializer,\\n unit_forget_bias=unit_forget_bias,\\n kernel_regularizer=kernel_regularizer,\\n recurrent_regularizer=recurrent_regularizer,\\n bias_regularizer=bias_regularizer,\\n activity_regularizer=activity_regularizer,\\n attention_regularizer=attention_regularizer,\\n kernel_constraint=kernel_constraint,\\n recurrent_constraint=recurrent_constraint,\\n bias_constraint=bias_constraint,\\n attention_constraint=attention_constraint,\\n dropout=dropout,\\n recurrent_dropout=recurrent_dropout,\\n return_attention=return_attention,\\n implementation=implementation,\\n )\\n super().__init__(\\n cell,\\n return_sequences=return_sequences,\\n return_state=return_state,\\n go_backwards=go_backwards,\\n stateful=stateful,\\n unroll=unroll,\\n **kwargs,\\n )\\n self.return_attention = return_attention\\n\\n def build(self, input_shape):\\n \\\"\\\"\\\"Build the AttentionLSTM object.\\\"\\\"\\\"\\n self.cell.timesteps = input_shape[1]\\n self.cell.build(input_shape)\\n\\n def call(self, inputs, mask=None, training=None, initial_state=None):\\n \\\"\\\"\\\"Call the AttentionLSTM object.\\\"\\\"\\\"\\n self.cell._generate_dropout_mask(inputs, training=training)\\n self.cell._generate_recurrent_dropout_mask(inputs, training=training)\\n return super().call(\\n inputs, mask=mask, training=training, initial_state=initial_state\\n )\\n\\n @property\\n def units(self):\\n \\\"\\\"\\\"Return property units.\\\"\\\"\\\"\\n return self.cell.units\\n\\n @property\\n def activation(self):\\n \\\"\\\"\\\"Return property activation.\\\"\\\"\\\"\\n return self.cell.activation\\n\\n @property\\n def recurrent_activation(self):\\n \\\"\\\"\\\"Return property recurrent_activation.\\\"\\\"\\\"\\n return self.cell.recurrent_activation\\n\\n @property\\n def attention_activation(self):\\n \\\"\\\"\\\"Return property attention_activation.\\\"\\\"\\\"\\n return self.cell.attention_activation\\n\\n @property\\n def use_bias(self):\\n \\\"\\\"\\\"Return property use_bias.\\\"\\\"\\\"\\n return self.cell.use_bias\\n\\n @property\\n def kernel_initializer(self):\\n \\\"\\\"\\\"Return property kernel_initializer.\\\"\\\"\\\"\\n return self.cell.kernel_initializer\\n\\n @property\\n def recurrent_initializer(self):\\n \\\"\\\"\\\"Return property recurrent_initializer.\\\"\\\"\\\"\\n return self.cell.recurrent_initializer\\n\\n @property\\n def attention_initializer(self):\\n \\\"\\\"\\\"Return property attention_initializer.\\\"\\\"\\\"\\n return self.cell.attention_initializer\\n\\n @property\\n def bias_initializer(self):\\n \\\"\\\"\\\"Return property bias_initializer.\\\"\\\"\\\"\\n return self.cell.bias_initializer\\n\\n @property\\n def unit_forget_bias(self):\\n \\\"\\\"\\\"Return property unit_forget_bias.\\\"\\\"\\\"\\n return self.cell.unit_forget_bias\\n\\n @property\\n def kernel_regularizer(self):\\n \\\"\\\"\\\"Return property kernel_regularizer.\\\"\\\"\\\"\\n return self.cell.kernel_regularizer\\n\\n @property\\n def recurrent_regularizer(self):\\n \\\"\\\"\\\"Return property recurrent_regularizer.\\\"\\\"\\\"\\n return self.cell.recurrent_regularizer\\n\\n @property\\n def bias_regularizer(self):\\n \\\"\\\"\\\"Return property bias_regularizer.\\\"\\\"\\\"\\n return self.cell.bias_regularizer\\n\\n @property\\n def activity_regularizer(self):\\n \\\"\\\"\\\"Return property activity_regularizer.\\\"\\\"\\\"\\n return self.cell.activity_regularizer\\n\\n @property\\n def attention_regularizer(self):\\n \\\"\\\"\\\"Return property attention_regularizer.\\\"\\\"\\\"\\n return self.cell.attention_regularizer\\n\\n @property\\n def kernel_constraint(self):\\n \\\"\\\"\\\"Return property kernel_constraint.\\\"\\\"\\\"\\n return self.cell.kernel_constraint\\n\\n @property\\n def recurrent_constraint(self):\\n \\\"\\\"\\\"Return property recurrent_constraint.\\\"\\\"\\\"\\n return self.cell.recurrent_constraint\\n\\n @property\\n def bias_constraint(self):\\n \\\"\\\"\\\"Return property bias_constraint.\\\"\\\"\\\"\\n return self.cell.bias_constraint\\n\\n @property\\n def attention_constraint(self):\\n \\\"\\\"\\\"Return property attention_constraint.\\\"\\\"\\\"\\n return self.cell.attention_constraint\\n\\n @property\\n def dropout(self):\\n \\\"\\\"\\\"Return property dropout.\\\"\\\"\\\"\\n return self.cell.dropout\\n\\n @property\\n def recurrent_dropout(self):\\n \\\"\\\"\\\"Return property recurrent_dropout.\\\"\\\"\\\"\\n return self.cell.recurrent_dropout\\n\\n @property\\n def implementation(self):\\n \\\"\\\"\\\"Return property implementation.\\\"\\\"\\\"\\n return self.cell.implementation\\n\\n def get_config(self):\\n \\\"\\\"\\\"Return configuration dict of the AttentionLSTM object.\\\"\\\"\\\"\\n config = {\\n \\\"units\\\": self.units,\\n \\\"activation\\\": activations.serialize(self.activation),\\n \\\"recurrent_activation\\\": activations.serialize(\\n self.recurrent_activation\\n ),\\n \\\"attention_activation\\\": activations.serialize(\\n self.attention_activation\\n ),\\n \\\"use_bias\\\": self.use_bias,\\n \\\"kernel_initializer\\\": initializers.serialize(self.kernel_initializer),\\n \\\"recurrent_initializer\\\": initializers.serialize(\\n self.recurrent_initializer\\n ),\\n \\\"bias_initializer\\\": initializers.serialize(self.bias_initializer),\\n \\\"attention_initializer\\\": initializers.serialize(\\n self.attention_initializer\\n ),\\n \\\"use_chrono_initialization\\\": self.unit_forget_bias,\\n \\\"kernel_regularizer\\\": regularizers.serialize(self.kernel_regularizer),\\n \\\"recurrent_regularizer\\\": regularizers.serialize(\\n self.recurrent_regularizer\\n ),\\n \\\"bias_regularizer\\\": regularizers.serialize(self.bias_regularizer),\\n \\\"activity_regularizer\\\": regularizers.serialize(\\n self.activity_regularizer\\n ),\\n \\\"attention_regularizer\\\": regularizers.serialize(\\n self.attention_regularizer\\n ),\\n \\\"kernel_constraint\\\": constraints.serialize(self.kernel_constraint),\\n \\\"recurrent_constraint\\\": constraints.serialize(\\n self.recurrent_constraint\\n ),\\n \\\"bias_constraint\\\": constraints.serialize(self.bias_constraint),\\n \\\"attention_constraint\\\": constraints.serialize(\\n self.attention_constraint\\n ),\\n \\\"dropout\\\": self.dropout,\\n \\\"recurrent_dropout\\\": self.recurrent_dropout,\\n \\\"return_attention\\\": self.return_attention,\\n }\\n base_config = super().get_config()\\n del base_config[\\\"cell\\\"]\\n return dict(list(base_config.items()) + list(config.items()))\\n\\n @classmethod\\n def from_config(cls, config):\\n \\\"\\\"\\\"Create a new AttentionLSTM object from a configuration dict.\\\"\\\"\\\"\\n if \\\"implementation\\\" in config and config[\\\"implementation\\\"] == 0:\\n config[\\\"implementation\\\"] = 1\\n return cls(**config)\\n\\n return AttentionLSTM\",\n \"def causal_attention_mask(nd, ns, dtype):\\n i = tf.range(nd)[:, None]\\n j = tf.range(ns)\\n m = i >= j - ns + nd\\n return tf.cast(m, dtype)\",\n \"def call(self, x, mask=None):\\n u_i = K.tanh(K.dot(x, self.W) + self.b)\\n v = K.squeeze(K.dot(u_i, K.expand_dims(self.u)), axis=-1)\\n attention = softmax_masked(v, mask)\\n\\n return attention\",\n \"def __init__(self, encoder_hidden_dim, decoder_hidden_dim, T):\\n super(TemporalAttentionDecoder, self).__init__()\\n\\n self.T = T\\n self.encoder_hidden_dim = encoder_hidden_dim\\n self.decoder_hidden_dim = decoder_hidden_dim\\n\\n self.attn_layer = nn.Sequential(nn.Linear(2 * decoder_hidden_dim + encoder_hidden_dim, encoder_hidden_dim),\\n nn.ReLU(), nn.Linear(encoder_hidden_dim, 1))\\n self.lstm_layer = nn.LSTM(input_size=1, hidden_size=decoder_hidden_dim)\\n self.fc = nn.Linear(encoder_hidden_dim + 2, 1)\\n self.fc_final = nn.Linear(decoder_hidden_dim + encoder_hidden_dim, 1)\\n\\n self.fc.weight.data.normal_()\",\n \"def forward(self, x, mask):\\n x = self.sublayer[0](x, lambda x: self.self_attn(x, x, x, mask))\\n #print('encoder')\\n #print(x.shape)\\n return self.sublayer[1](x, self.feed_forward)\",\n \"def get_attention(self, X):\\n if self.bn:\\n layer = 16\\n else:\\n layer = 14\\n inputs = [K.learning_phase()] + [self.model.inputs[0]]\\n _attention_f = K.function(inputs, [\\n self.model.layers[layer].output])\\n \\n return _attention_f([0] + [X])\",\n \"def make_attn_mask(inp, inp_len, dtype=tf.float32):\\n with tf.name_scope(\\\"encoder_mask\\\"):\\n mask = tf.sequence_mask(inp_len, dtype=dtype, maxlen=tf.shape(inp)[1])\\n return mask[:, None, None, :]\",\n \"def _attention(self, inputs):\\n attn_weights = K.batch_dot(x=inputs,\\n y=K.permute_dimensions(inputs,\\n pattern=(0, 2, 1)))\\n return K.permute_dimensions(attn_weights, (0, 2, 1))\",\n \"def attention_mask(nd, ns, dtype=tf.float32):\\n i = tf.range(nd)[:, None]\\n j = tf.range(ns)\\n m = i >= j - ns + nd\\n out = tf.cast(m, dtype)\\n return out\",\n \"def apply_tfmask(feats, max_bin=27, max_time=100):\\n flen, dim = feats.shape\\n d_mask = random.randint(1, max_bin)\\n d_point = random.randint(0, dim - d_mask)\\n t_mask = random.randint(1, max_time)\\n t_point = random.randint(0, flen - t_mask)\\n\\n mask = np.ones((flen, dim), dtype=\\\"d\\\")\\n mask[:, d_point : d_point + d_mask] = 0\\n mask[t_point : t_point + t_mask] = 0\\n return feats * mask\",\n \"def get_attention_multiscale_batch(self, X,X_mask):\\n layer = -3\\n attmodel1 = Model(self.model.inputs,self.model.get_layer('att1').output[1])\\n attmodel2 = Model(self.model.inputs,self.model.get_layer('att2').output[1])\\n attmodel3 = Model(self.model.inputs,self.model.get_layer('att3').output[1])\\n return attmodel1.predict([X,X_mask.reshape(-1,X_mask.shape[1],1)],batch_size=100),attmodel2.predict([X,X_mask.reshape(-1,X_mask.shape[1],1)],batch_size=100),attmodel3.predict([X,X_mask.reshape(-1,X_mask.shape[1],1)],batch_size=100)\",\n \"def compute_attention_mask(x_mask, mem_mask, x_word_dim, key_word_dim):\\r\\n if x_mask is None and mem_mask is None:\\r\\n return None\\r\\n elif x_mask is None or mem_mask is None:\\r\\n raise NotImplementedError()\\r\\n\\r\\n x_mask = tf.cast(x_mask,dtype=bool)\\r\\n mem_mask = tf.cast(tf.transpose(mem_mask,perm=[0,2,1]), dtype=bool)\\r\\n join_mask = tf.logical_and(x_mask, mem_mask)\\r\\n return join_mask\",\n \"def attn(self, embed, mask, name=\\\"\\\"):\\n with tf.variable_scope(\\\"attn_\\\"+name):\\n K = self.get_trans_param(\\\"K\\\")\\n Q = self.get_trans_param(\\\"Q\\\")\\n V = self.get_trans_param(\\\"V\\\")\\n kdata = tf.einsum(\\\"nml,lk->nmk\\\", embed, K)\\n qdata = tf.einsum(\\\"nml,lk->nmk\\\", embed, Q)\\n vdata = tf.einsum(\\\"nml,lk->nmk\\\", embed, V) # nbatch x max_atom x n_trans\\n kq = tf.einsum(\\\"nml,nkl->nmk\\\", qdata, kdata)*(1/math.sqrt(self.n_trans)) # nbatch x max_atom x max_atom\\n #mask = tf.expand_dims(mask, 1) # nbatch x 1 x max_atom\\n mask = tf.keras.backend.repeat(mask, self.max_atom) \\n score = tf.where(mask, -9999*tf.ones_like(kq), kq)\\n #score = kq\\n #score = tf.scatter_update(tf.Variable(kq, validate_shape=False), mask, -9999)# assign a large number\\n w = tf.nn.softmax(score, axis=-1) # calculate attention weight, nbatch x max_atom x max_atom\\n vout = tf.einsum(\\\"nml,nlk->nmk\\\", w, vdata) # nbatch x max_atom x n_trans\\n return vout\",\n \"def _add_mask(batch, num_batch_dims):\\n mask = tf.ones(tf.shape(list(batch.values())[0])[:num_batch_dims])\\n if \\\"mask\\\" in batch:\\n mask *= batch[\\\"mask\\\"]\\n batch[\\\"mask\\\"] = mask\\n return batch\",\n \"def build(self, unused_input_shapes):\\n self.query_dense = self._projection_dense_layer(\\\"query\\\")\\n self.key_dense = self._projection_dense_layer(\\\"key\\\")\\n self.value_dense = self._projection_dense_layer(\\\"value\\\")\\n self.attention_probs_dropout = tf.keras.layers.Dropout(\\n rate=self.attention_probs_dropout_prob)\\n super(CustomAttention, self).build(unused_input_shapes)\",\n \"def make_inference_attention_mask_3d(source_block, target_block, pad_id):\\n # mask = (target_block[:, None, :] != pad_id) * (source_block[:, :, None] != pad_id)\\n return make_attention_mask_3d(source_block != pad_id, target_block != pad_id)\",\n \"def lstm_mask_layer(proj, mask):\\n\\n return proj * mask[:, :, None]\",\n \"def _prepare_attended_output(self,\\n decoder_hidden_state: torch.Tensor,\\n state: Dict[str, torch.Tensor]) -> torch.Tensor:\\n # Ensure mask is also a FloatTensor. Or else the multiplication within\\n # attention will complain.\\n # shape: (batch_size, max_input_sequence_length)\\n\\n encoder_outputs = state[\\\"encoder_outputs\\\"]\\n source_mask = state[\\\"source_mask\\\"]\\n prev_attention = state[\\\"attention\\\"]\\n att_keys = state[\\\"att_keys\\\"]\\n att_values = state[\\\"att_values\\\"]\\n\\n # shape: (batch_size, max_input_sequence_length)\\n mode = \\\"soft\\\" if self.training else \\\"hard\\\"\\n if isinstance(self._attention, MonotonicAttention):\\n encoder_outs: Dict[str, torch.Tensor] = {\\n \\\"value\\\": state[\\\"encoder_outputs\\\"],\\n \\\"mask\\\": state[\\\"source_mask\\\"]\\n }\\n\\n monotonic_attention, chunk_attention = self._attention(\\n encoder_outs, decoder_hidden_state, prev_attention, mode=mode)\\n # shape: (batch_size, encoder_output_dim)\\n attended_output = util.weighted_sum(\\n encoder_outputs, chunk_attention)\\n attention = monotonic_attention\\n elif isinstance(self._attention, StatefulAttention):\\n attended_output, attention = self._attention(decoder_hidden_state,\\n att_keys, att_values, source_mask)\\n else:\\n attention = self._attention(\\n decoder_hidden_state, source_mask)\\n attended_output = util.weighted_sum(\\n encoder_outputs, attention)\\n\\n return attended_output, attention\",\n \"def convolutional_attention(inputs, filter_size=5, initializer=None,\\n reuse=None, name=''):\\n with tf.variable_scope('conv_att_{}'.format(name), reuse=reuse) as f:\\n dim = inputs.get_shape().as_list()[2]\\n filter_shape = filter_shape = [filter_size, dim, 1]\\n W1 = tf.get_variable(\\\"weights\\\", filter_shape,\\n initializer=initializer)\\n b1 = tf.get_variable(\\\"bias\\\", [1],\\n initializer=tf.constant_initializer([0.1]))\\n conv = tf.nn.conv1d(inputs, W1, stride=1,\\n padding=\\\"SAME\\\", data_format=\\\"NHWC\\\")\\n # this should be bsz x seq_len x 1\\n conv += b1\\n att = tf.nn.sigmoid(conv)\\n weighted_inputs = inputs * att\\n return weighted_inputs, att\",\n \"def apply_attention(inputs,\\n attention_mode=None,\\n attention_in=None,\\n use_5d_mode=False,\\n data_format='channels_last'):\\n assert data_format == 'channels_last'\\n\\n h_ch_loc = 2 if use_5d_mode else 1\\n\\n if attention_mode == 'peer':\\n attn = softmax_merge_peer_attentions(attention_in, data_format)\\n else:\\n attn = tf.reduce_mean(inputs, [h_ch_loc, h_ch_loc+1])\\n attn = tf.layers.dense(\\n inputs=attn,\\n units=inputs.shape[-1],\\n kernel_initializer=tf.random_normal_initializer(stddev=.01))\\n attn = tf.math.sigmoid(attn)\\n channel_attn = tf.expand_dims(tf.expand_dims(attn, h_ch_loc), h_ch_loc)\\n\\n inputs = tf.multiply(inputs, channel_attn)\\n\\n return inputs\",\n \"def get_fc(self, layer):\\n return getattr(self, 'attention_{}'.format(layer))\",\n \"def spec_augment(_spec,\\n do_time_warp=True,\\n W=40,\\n do_freq_mask=True,\\n F=20,\\n m_f=1,\\n reduce_mask_range=0,\\n do_time_mask=True,\\n T=20,\\n m_t=1,\\n mask_val='zero'):\\n\\n _spec_aug = copy.deepcopy(_spec)\\n # Step 1 : Time warping, not used\\n\\n # Step 2 : Frequency masking\\n # hard wideband suppression of bw bands starting from f0\\n # bw drawn from a uniform distribution from 0 to parameter F\\n # f0 drawn from [0, n_bands-bw]\\n if do_freq_mask:\\n _spec_aug = freq_mask(_spec_aug, F=F, n_masks=m_f, mask_val=mask_val, reduce_mask_range=reduce_mask_range)\\n\\n # Step 3 : Time masking\\n # sound mute of deltat consecutive frames, starting at t0\\n # deltat drawn from a uniform distribution from 0 to parameter T\\n # t0 drawn from [0, n_frames-deltat]\\n if do_time_mask:\\n _spec_aug = time_mask(_spec_aug, T=T, n_masks=m_t, mask_val=mask_val)\\n\\n return _spec_aug\",\n \"def _apply_attention_constraint(e,\\n last_attended_idx,\\n backward_window=1,\\n forward_window=3):\\n # for dygraph to static graph\\n # if e.shape[0] != 1:\\n # raise NotImplementedError(\\n # \\\"Batch attention constraining is not yet supported.\\\")\\n backward_idx = paddle.cast(\\n last_attended_idx - backward_window, dtype='int64')\\n forward_idx = paddle.cast(last_attended_idx + forward_window, dtype='int64')\\n if backward_idx > 0:\\n e[:, :backward_idx] = -float(\\\"inf\\\")\\n if forward_idx < paddle.shape(e)[1]:\\n e[:, forward_idx:] = -float(\\\"inf\\\")\\n return e\",\n \"def output_layer_activation(x):\\n return x\",\n \"def lstm_atten(self):\\n # Model.\\n model = Sequential()\\n model.add(LSTM(2048, return_sequences=True,\\n input_shape=self.input_shape,\\n dropout=0.5))\\n model.add(Flatten()) #qiao_added\\n # model.add(Dense(1024, activation='relu'))\\n # model.add(Dropout(0.5))\\n\\n attention = Dense(1, activation='tanh')(activations)\\n attention = Flatten()(attention)\\n attention = Activation('softmax')(attention)\\n attention = RepeatVector(2048)(attention)\\n attention = Permute([2, 1])(attention)\\n\\n sent_representation = concatenate([activations, attention], mode='mul')\\n sent_representation = Lambda(lambda xin: K.sum(xin, axis=-2), output_shape=(2048,))(sent_representation)\\n\\n probabilities = Dense(self.nb_classes, activation='softmax')(sent_representation)\\n\\n model = model(input=self.input_shape, output=probabilities )\\n\\n dense1800 = Dense(4096, activation='relu')\\n\\n #dense1800 = Dense(1800, activation='relu', kernel_regularizer=regularizers.l2(0.01))(inputs)\\n attention_probs = Dense(4096, activation='sigmoid', name='attention_probs')(dense1800)\\n attention_mul = multiply([dense1800, attention_probs], name='attention_mul')\\n dense7 = Dense(self.nb_classes, kernel_regularizer=regularizers.l2(0.01), activation='softmax')(attention_mul)\\n model = Model(input=[self.input_shape], output=dense7)\\n return model\",\n \"def get_attention(self, temp_data, channel_mask=[0], threshold=100, keep_bad_epochs=False,apply_filters=True):\\n\\n # Standard Filters\\n if(apply_filters):\\n temp_data = filters.apply_dc_offset(temp_data)\\n temp_data = filters.apply_notch_filter(temp_data)\\n\\n # Remove bad epochs by identifying bad epochs as those containing\\n # energy in 1, 10Hz band above a threshold\\n blocks_data = temp_data\\n if(keep_bad_epochs == False):\\n blocks_data = ft.remove_bad_epochs(temp_data, thresh_fn=self.energy_of_epoch, threshold=threshold,\\n channels=channel_mask, sliding_window=True)\\n\\n # Get band power of each block for all the available channels\\n blocks_bandpower = []\\n for block in blocks_data:\\n\\n blocks_bandpower.append(ft.get_bandpower(block.reshape(1, block.shape[0], block.shape[1]),\\n channel_mask))\\n self.bandpower.append(blocks_bandpower[-1])\\n\\n # Get the attention_matrix from the bandpower\\n attention_per_channel = np.zeros((len(blocks_bandpower), len(channel_mask)))\\n for idx, block in enumerate(blocks_bandpower):\\n for channel in channel_mask:\\n attention_per_channel[idx, channel] = self.attention_per_channel(block[channel])\\n attention_per_epoch = self.attention_overall(attention_per_channel[idx])\\n self.attention_matrix.append(attention_per_epoch)\\n\\n # For testing. Remove later\\n #print(attention_per_epoch)\",\n \"def __init__(self, input_dim=6, hidden_dim=128, T=10, in_features=2*128 + 16, num_layers=1, out_features=1):\\n super(InputAttentionEncoder, self).__init__()\\n self.input_dim = input_dim\\n self.hidden_dim = hidden_dim\\n self.T = T\\n\\n in_features = hidden_dim * 2 + T - 1\\n\\n self.lstm_unit = nn.LSTM(input_size=input_dim, hidden_size=hidden_dim, num_layers=num_layers)\\n self.attn_linear = nn.Linear(in_features=in_features, out_features=out_features)\\n self.bn1 = nn.BatchNorm1d(out_features)\\n self.fc2 = nn.Linear(out_features, out_features)\",\n \"def TCN(input_dim): \\r\\n # Number of dilations in order to use for the temporal blocks.\\r\\n dilations = np.array([1, 2, 4, 8, 16, 32])\\r\\n\\r\\n input_dim.insert(0,1)\\r\\n print(f\\\"input_dim: {input_dim}\\\")\\r\\n input_layer = Input(shape=input_dim)\\r\\n cropping = 0\\r\\n assert (sum(dilations) * block_size + 1) == 127, \\\"Paper specifies receptive field size should be 127\\\"\\r\\n \\r\\n prev_layer, skip_layer, _ = add_temporal_block(input_layer, None, 1, 1, cropping)\\r\\n \\r\\n for dilation in dilations:\\r\\n prev_layer, skip_layer, cropping = add_temporal_block(prev_layer, skip_layer, 2, dilation, cropping)\\r\\n\\r\\n output_layer = PReLU(shared_axes=[2, 3])(skip_layer)\\r\\n output_layer = SpectralNormalization(Conv1D(fixed_filters, kernel_size=1))(output_layer)\\r\\n output_layer = PReLU(shared_axes=[2, 3])(output_layer)\\r\\n output_layer = SpectralNormalization(Conv1D(1, kernel_size=1))(output_layer)\\r\\n\\r\\n return Model(input_layer, output_layer)\",\n \"def segment(u_train, l_train, u_test):\\n ### Exercise 6.2\\n\\n # Encode input and gather stats for model\\n encoder = WordEncoder()\\n encoder.fit(u_train)\\n X_train = encoder.transform(u_train, flat=False)\\n X_test = encoder.transform(u_test, flat=False)\\n input_N = len(u_train)\\n maxLen = encoder.max_wordlen\\n third_dim = np.shape(X_train)[2]\\n\\n # Pad output to match input\\n paddded_l_train = []\\n for label in l_train:\\n new_label = np.zeros(maxLen, dtype=int)\\n for j, k in enumerate(label):\\n new_label[j] = k\\n paddded_l_train.append(new_label)\\n l_train_array = np.array(paddded_l_train).reshape(input_N, maxLen, 1)\\n\\n # Build model\\n model = Sequential()\\n # I could not get the masking layer to work. Tried editing the X_train and Y arrays in numerous ways\\n # But couldn't figure out why it wouldn't accept it. Any advice here would be much appreciated!\\n # model.add(Embedding(input_dim=maxLen, output_dim=(maxLen, third_dim), mask_zero=True))\\n model.add(LSTM(100, input_shape=(maxLen, third_dim), activation=\\\"relu\\\", return_sequences=True))\\n model.add(Dropout(0.2))\\n model.add(TimeDistributed(Dense(1, activation='sigmoid')))\\n model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\\n es = EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=5)\\n model.summary()\\n model.fit(X_train, l_train_array, epochs=50, callbacks=[es])\\n\\n predictions = model.predict(X_test)\\n # Convert label predictions to segments\\n segments = label_to_segments(u_test, predictions)\\n\\n return segments\",\n \"def masked_softmax(input_layer,n_nodes, batch_size):\\n mask_lower = K.theano.tensor.tril(K.ones((n_nodes, n_nodes)))\\n mask_upper = \\\\\\n K.theano.tensor.triu(-100. * K.ones((n_nodes, n_nodes)), 1)\\n mask_layer = mask_lower * input_layer + mask_upper\\n mask_layer = mask_layer + 0 * K.eye(n_nodes)[0:n_nodes, 0:n_nodes]\\n mask_layer = \\\\\\n K.reshape(mask_layer, (batch_size * n_nodes, n_nodes))\\n softmax_layer = K.softmax(mask_layer)\\n output_layer = K.reshape(softmax_layer, (batch_size, n_nodes, n_nodes))\\n return output_layer\",\n \"def set_layer_mask_data(layer, channel_data, channel_info, array):\\n width, height = layer.mask.width, layer.mask.height\\n depth, version = layer._psd.depth, layer._psd.version\\n byte_aray = (array * 255).astype(np.uint8)\\n buf = data_from_array(byte_aray.flatten(), depth)\\n channel_data.set_data(buf, width, height, depth, version)\\n channel_info.length = channel_data._length\",\n \"def __call__(self, inputs: tf.Tensor, outputs: tf.Tensor,\\n out_mask: tf.Tensor,in_pad_mask: tf.Tensor=None,\\n training: bool=False):\\n encoder_outputs, enc_attention = self.encoder(\\n inputs, in_pad_mask, training\\n )\\n # shape=(batch_size, inputs_seq_len, d_model)\\n\\n decoder_outputs, dec_self_attention, dec_enc_attention = self.decoder(\\n outputs, encoder_outputs, out_mask, in_pad_mask, training\\n )\\n # shape=(batch_size, outputs_seq_len, d_model)\\n\\n attentions = {'encoder': enc_attention,\\n 'decoder_self': dec_self_attention,\\n 'decoder_encoder': dec_enc_attention}\\n\\n return decoder_outputs, attentions\",\n \"def MakeMask(shape, masked_value=0, dtype=K.floatx(), name=None):\\n def instantiate(x):\\n if dtype is None:\\n return layers.Lambda(lambda t: K.not_equal(x, masked_value),\\n output_shape=shape,\\n name=name)(x)\\n else:\\n return layers.Lambda(lambda t: K.cast(K.not_equal(x, masked_value), K.floatx()),\\n output_shape=shape,\\n name=name)(x)\\n return instantiate\",\n \"def attention_mask_future(nd, ns, dtype=tf.float32):\\n i = tf.range(nd)[:, None]\\n j = tf.range(ns)\\n m = i >= j - ns + nd\\n out = tf.cast(m, dtype)\\n return out\",\n \"def attention_mask(x):\\n mask = torch.zeros(len(x), len(x[0]))\\n for i in range(len(x)):\\n try:\\n index = np.where(x[i]==1)[0][0]\\n mask[i][index:] = -np.inf\\n except:\\n pass\\n return mask\",\n \"def mask_attention(attention, seq_len1, seq_len2):\\n dim1 = tensor_utils.shape(attention, 1)\\n dim2 = tensor_utils.shape(attention, 2)\\n m1 = tf.sequence_mask(seq_len1, dim1)\\n m2 = tf.sequence_mask(seq_len2, dim2)\\n joint_mask = tf.logical_and(tf.expand_dims(m1, 2), tf.expand_dims(m2, 1))\\n return ops.mask_logits(attention, joint_mask)\",\n \"def call(self, inputs):\\n (input_tensor, attention_mask) = tf_utils.unpack_inputs(inputs)\\n with tf.name_scope('attention'):\\n attention_output, attention_scores = self.attention_layer(\\n from_tensor=input_tensor,\\n to_tensor=input_tensor,\\n attention_mask=attention_mask)\\n with tf.name_scope('output'):\\n attention_output = self.attention_output_dense(attention_output)\\n attention_output = self.attention_dropout(attention_output)\\n # Use float32 in keras layer norm and the gelu activation in the\\n # intermediate dense layer for numeric stability\\n attention_output = self.attention_layer_norm(input_tensor +\\n attention_output)\\n if self.float_type == tf.float16:\\n attention_output = tf.cast(attention_output, tf.float16)\\n\\n with tf.name_scope('intermediate'):\\n intermediate_output = self.intermediate_dense(attention_output)\\n if self.float_type == tf.float16:\\n intermediate_output = tf.cast(intermediate_output, tf.float16)\\n\\n with tf.name_scope('output'):\\n layer_output = self.output_dense(intermediate_output)\\n layer_output = self.output_dropout(layer_output)\\n # Use float32 in keras layer norm for numeric stability\\n layer_output = self.output_layer_norm(layer_output + attention_output)\\n if self.float_type == tf.float16:\\n layer_output = tf.cast(layer_output, tf.float16)\\n return layer_output, attention_scores\",\n \"def _data_augment(self, x):\\n batch_size = x.size()[0]\\n x = x.view(batch_size, -1)\\n bias = torch.ones(batch_size, 1).to(self.device)\\n x = torch.cat((bias, x), 1)\\n\\n return x\",\n \"def attention_mask_key(key_mask, num_tile, dtype=tf.float32):\\n key_mask = tf.cast(key_mask, dtype)\\n key_mask = tf.tile(key_mask, [num_tile, 1]) # (h*N, seqlen)\\n key_mask = tf.expand_dims(key_mask, 1) # (h*N, 1, seqlen)\\n mask = key_mask * - tf.cast(1e10, dtype)\\n return mask\",\n \"def forward(self, x: Tensor, mask: Tensor) -> Tensor:\\n x_norm = self.layer_norm(x)\\n h = self.src_src_att(x_norm, x_norm, x_norm, mask)\\n h = self.dropout(h) + x\\n o = self.feed_forward(h)\\n return o\",\n \"def Anatomical_attention_gate(featureMap1,featureMap2):\\n ndims = len(featureMap1.get_shape()) - 2\\n assert ndims in [1, 2, 3], \\\"ndims should be one of 1, 2, or 3. found: %d\\\" % ndims\\n# input_channels = featureMap1.get_shape().as_list()[-1]\\n# batch_size1 = tf.shape(down_in)[0]\\n# nf = tf.min(batch_size0,batch_size1)\\n featureMap = concatenate([featureMap1, featureMap2])\\n Conv = getattr(KL, 'Conv%dD' % ndims)\\n tensorweight1 = Conv(1, kernel_size=1, padding='same',\\n kernel_initializer='he_normal', use_bias = True, bias_initializer='zeros',strides=1,activation='sigmoid')(featureMap)\\n# tensorweight1 = Activation('relu')(tensorweight1)\\n w_featureMap1 = Multiply()([featureMap1,tensorweight1])\\n tensorweight2 = Conv(1, kernel_size=1, padding='same',\\n kernel_initializer='he_normal', use_bias = True, bias_initializer='zeros',strides=1,activation='sigmoid')(featureMap)\\n# tensorweight2 = Activation('relu')(tensorweight2)\\n w_featureMap2 = Multiply()([featureMap2,tensorweight2])\\n w_featureMap = Add()([w_featureMap1,w_featureMap2])\\n return w_featureMap\",\n \"def spec_augment(mel_spec: np.ndarray, n_time_masks: int, time_mask_width: int, n_freq_masks: int, freq_mask_width: int):\\n \\n offset, begin = 0, 0\\n\\n for _ in range(n_time_masks):\\n offset = np.random.randint(0, time_mask_width)\\n begin = np.random.randint(0, mel_spec.shape[1] - offset)\\n mel_spec[:, begin: begin + offset] = 0.0\\n \\n for _ in range(n_freq_masks):\\n offset = np.random.randint(0, freq_mask_width)\\n begin = np.random.randint(0, mel_spec.shape[0] - offset)\\n mel_spec[begin: begin + offset, :] = 0.0\\n\\n return mel_spec\",\n \"def forward(self, x, src_states, src_mask, tgt_mask):\\n x = self.sublayer[0](x, lambda x: self.self_attn(x, x, x, tgt_mask))\\n #print('decoder')\\n #print(x.shape)\\n x = self.sublayer[1](x, lambda x: self.src_attn(x, src_states, src_states, src_mask))\\n #print(x.shape)\\n return self.sublayer[2](x, self.feed_forward)\",\n \"def attention_imp_merge():\\n global X_DIM, Y_DIM\\n # Load Embeddings matrix\\n embedding_weights = joblib.load(config.DUMPED_VECTOR_DIR + 'mb_voc_embeddings.pkl')\\n\\n # model cnn\\n\\n model_atn = Sequential()\\n model_atn.add(Embedding(max_features,\\n embedding_dims,\\n input_length=max_len,\\n weights=[embedding_weights],\\n trainable=True))\\n model_atn.add(Bidirectional(GRU(100, return_sequences=True), name='bidirectional'))\\n model_atn.add(TimeDistributed(Dense(200), name='time_dist'))\\n model_atn.add(AttLayer(name='att'))\\n\\n model_feature_vec = Sequential()\\n model_feature_vec.add(Dense(200, input_dim=N_Features, init='normal', activation='relu'))\\n model_feature_vec.add(Dense(100, init='normal', activation='relu'))\\n model_feature_vec.add(Dropout(0.2))\\n model_feature_vec.add(Dense(50, init='normal', activation='relu'))\\n model_feature_vec.add(Dense(10, init='normal', activation='relu'))\\n\\n merged_layer = Sequential()\\n merged_layer.add(Merge([model_atn, model_feature_vec], mode='concat',\\n concat_axis=1, name='merge_layer'))\\n merged_layer.add(Dense(200, activation='relu'))\\n # merged_layer.add(Bidirectional(GRU(100, return_sequences=True), name='bidirectional_2'))\\n # merged_layer.add(TimeDistributed(Dense(200), name='time_dist'))\\n # merged_layer.add(AttLayer(name='att'))\\n merged_layer.add(Dense(1, init='normal', name='combined_dense'))\\n\\n # # Compile model\\n merged_layer.compile(loss='mean_squared_error', optimizer='adam')\\n\\n print(merged_layer.summary())\\n return merged_layer\",\n \"def add_watermark(self, image, watermark, position='scale', opacity=1, format=None):\",\n \"def temporal_padding(buffer, clip_len):\\n if buffer.shape[0] > clip_len:\\n pass\\n else:\\n pad_len = clip_len - buffer.shape[0] + 1\\n npad = ((pad_len, 0), (0, 0), (0, 0), (0,0))\\n # buffer = np.pad(buffer, pad_width=npad, mode='constant', constant_values=0)\\n buffer = np.pad(buffer, pad_width=npad, mode='mean')\\n assert buffer.shape[0] - clip_len > 0, \\\"Incorrect Padding\\\"\\n return buffer\",\n \"def spatial_attention(input_feature, kernel_size=7, name=None):\\n cbam_feature = input_feature\\n avg_pool = layers.Lambda(lambda x: K.mean(x, axis=3, keepdims=True))(cbam_feature)\\n max_pool = layers.Lambda(lambda x: K.max(x, axis=3, keepdims=True))(cbam_feature)\\n concat = layers.concatenate([avg_pool, max_pool])\\n cbam_feature = layers.Conv2D(filters=1,\\n kernel_size=kernel_size,\\n strides=1,\\n padding='same',\\n activation='sigmoid',\\n kernel_initializer='he_normal',\\n use_bias=False,\\n name=name + '_sliency')(concat)\\n\\n return layers.multiply([input_feature, cbam_feature])\",\n \"def build_attention_mask_3d_padding(source_mask, target_mask):\\n mask = make_attention_mask_3d(source_mask, target_mask)\\n # invert mask for Megatron\\n return mask < 0.5\",\n \"def task_specific_attention(inputs, output_size, sequence_lengths,\\n initializer=layers.xavier_initializer(),\\n activation_fn=tf.tanh, scope=None):\\n assert len(inputs.get_shape()) == 3 and inputs.get_shape()[-1].value is not None\\n\\n with tf.variable_scope(scope or 'attention') as scope:\\n attention_context_vector = tf.get_variable(name='attention_context_vector',\\n shape=[output_size],\\n initializer=initializer,\\n dtype=tf.float32)\\n \\n input_projection = layers.fully_connected(inputs, output_size,\\n activation_fn=activation_fn,\\n scope=scope)\\n\\n vector_attn = tf.reduce_sum(tf.multiply(input_projection, attention_context_vector), axis=2) \\n mask = tf.sequence_mask(sequence_lengths, dtype=tf.float32) \\n attention_weights = tf.nn.softmax(vector_attn, axis=1)\\n attention_weights = attention_weights*mask\\n norms = tf.reduce_sum(attention_weights, axis = 1, keepdims = True) + 1e-6 \\n attention_weights = attention_weights / norms\\n attention_weights = tf.expand_dims(attention_weights, axis = 2) \\n \\n weighted_projection = inputs*attention_weights\\n outputs = tf.reduce_sum(weighted_projection, axis=1)\\n\\n return outputs\",\n \"def build_attention_mask_3d(source_mask, target_mask, attn_mask_type):\\n if attn_mask_type == AttnMaskType.padding:\\n mask = build_attention_mask_3d_padding(source_mask, target_mask)\\n elif attn_mask_type == AttnMaskType.causal:\\n mask = build_attention_mask_3d_causal(source_mask, target_mask)\\n else:\\n raise ValueError(f\\\"Unsupported attention mask attn_mask_type = {attn_mask_type}\\\")\\n\\n return mask\",\n \"def channel_padding(x):\\n #keras.backend.concatenate([x, tf.zeros_like(x)], axis=-1)\\n x0=keras.layers.Activation('sigmoid')(x)\\n return keras.backend.concatenate([x, x0], axis=-1)\",\n \"def pixelAttention(self,x):\\n b, c, w, h = x.shape\\n pre_x = x.permute(0, 2, 3, 1)\\n pre_x = pre_x.contiguous().view(b, h * w, c)\\n att_x, relations = self.forward_unified(pre_x, pre_x, pre_x)\\n att_x = att_x.contiguous().view(b, h, w, c)\\n att_x = att_x.permute(0, 3, 1, 2)\\n return att_x\",\n \"def self_attention(self, hidden):\\n mul1 = self.attention1(hidden)\\n mul2 = self.attention2(mul1)\\n return self.softmax(mul2)\",\n \"def create_attention_mask_from_input_mask(from_tensor, to_mask):\\n from_shape = get_shape_list(from_tensor, expected_rank=[2, 3])\\n batch_size = from_shape[0]\\n from_seq_length = from_shape[1]\\n \\n to_shape = get_shape_list(to_mask, expected_rank=2)\\n to_seq_length = to_shape[1]\\n \\n to_mask = tf.cast(\\n tf.reshape(to_mask, [batch_size, 1, to_seq_length]), tf.float32)\\n \\n # We don't assume that `from_tensor` is a mask (although it could be). We\\n # don't actually care if we attend *from* padding tokens (only *to* padding)\\n # tokens so we create a tensor of all ones.\\n #\\n # `broadcast_ones` = [batch_size, from_seq_length, 1]\\n broadcast_ones = tf.ones(\\n shape=[batch_size, from_seq_length, 1], dtype=tf.float32)\\n \\n # Here we broadcast along two dimensions to create the mask.\\n mask = broadcast_ones * to_mask\\n \\n return mask\",\n \"def _add_bert_self_attention_layer(model_1, model_2):\\n\\n class Config:\\n pass\\n\\n config = Config()\\n config.hidden_size = model_1.all_head_size + model_2.all_head_size\\n config.num_attention_heads = (\\n model_1.num_attention_heads + model_2.num_attention_heads\\n )\\n config.output_attentions = model_1.output_attentions\\n config.attention_probs_dropout_prob = model_1.dropout.p\\n\\n return BertSelfAttention(config)\",\n \"def attention(inp, scope, e_dim, past, config):\\n assert inp.shape.ndims == 3 # input should be of shape [batch, seqlen, embeddings] # [batch, sequence, features]\\n assert e_dim % config.num_heads == 0 # embedding can be split in heads\\n\\n if past is not None:\\n assert past.shape.ndims == 5 # [batch, 2, heads, seqlen, emebeddings]\\n\\n def split_heads(x):\\n out = split_into_n_states(x, config.num_heads)\\n out = tf.transpose(out, [0, 2, 1, 3])\\n return out\\n\\n def merge_heads(x):\\n out = merge_n_states(tf.transpose(x, [0, 2, 1, 3]))\\n return out\\n\\n def mask_attention_weights(w):\\n # w should have shape [batches, heads, dst_seq, src_seq], where information flows from scr to dst\\n _, _, nd, ns = shapes_list(w)\\n b = attention_mask(nd, ns, w.dtype)\\n b = tf.reshape(b, [1, 1, nd, ns])\\n w = w * b - tf.cast(1e10, w.dtype) * (1 - b)\\n return w\\n\\n def multihead_attention(q, k, v):\\n w = tf.matmul(q, k, transpose_b=True)\\n w *= tf.rsqrt(tf.cast(v.shape[-1].value, w.dtype))\\n\\n # mask attention weights\\n w = mask_attention_weights(w)\\n w = softmax_with_reduce_max(w)\\n out = tf.matmul(w, v)\\n return out\\n\\n with tf.variable_scope(scope):\\n c = conv1d(inp, 'convolutional_attention', e_dim * 3)\\n q, k, v = map(split_heads, tf.split(c, 3, axis=2))\\n present = tf.stack([k, v], axis=1)\\n if past is not None:\\n # there is a stack below it\\n pk, pv = tf.unstack(past, axis=1)\\n k = tf.concat([pk, k], axis=2)\\n v = tf.concat([pv, v], axis=2)\\n\\n attn = multihead_attention(q, k, v)\\n attn = merge_heads(attn)\\n\\n out = conv1d(attn, 'convolutional_projection', e_dim)\\n return out, present\",\n \"def apply_mask(self, parameter):\\n if self.mask is None:\\n return\\n if self.use_double_copies:\\n self.unmasked_copy = parameter.clone().detach()\\n self.mask_tensor(parameter)\\n if self.is_regularization_mask:\\n self.mask = None\\n return parameter\",\n \"def channelAttention(self,x):\\n b, c, h, w = x.shape\\n pre_x = x.contiguous().view(b, c, h * w)\\n\\n att_x, relations = self.forward_unified(pre_x, pre_x, pre_x)\\n att_x = att_x.contiguous().view(b, c, h, w)\\n return att_x\",\n \"def buildMaskedLoss(loss_function, mask_value):\\n\\n def maskedLossFunction(y_true, y_pred):\\n mask = K.cast(K.not_equal(y_true, mask_value), K.floatx())\\n return loss_function(y_true * mask, y_pred * mask)\\n\\n return maskedLossFunction\",\n \"def identity_mask_propagation(nx_node, nx_graph):\\n input_masks = get_input_masks(nx_node, nx_graph)\\n assert len(input_masks) == 1\\n nx_node['input_masks'] = input_masks\\n nx_node['output_mask'] = input_masks[0]\",\n \"def apply_mask(data, mask_func, seed=None, padding=None):\\n shape = np.array(data.shape)\\n shape[:-3] = 1\\n mask = mask_func(shape, seed)\\n if padding is not None:\\n mask[:, :, :padding[0]] = 0\\n mask[:, :, padding[1]:] = 0 # padding value inclusive on right of zeros\\n\\n masked_data = data * mask + 0.0 # The + 0.0 removes the sign of the zeros\\n return masked_data, mask\",\n \"def data_augmentation(self, img):\\n new_img = img.astype(float)\\n # random brightness - the mask bit keeps values from going beyond (0,255)\\n value = np.random.randint(-28, 28)\\n if value > 0:\\n mask = (new_img[:, :, 0] + value) > 255\\n if value <= 0:\\n mask = (new_img[:, :, 0] + value) < 0\\n new_img[:, :, 0] += np.where(mask, 0, value)\\n # random shadow - full height, random left/right side, random darkening\\n h, w = new_img.shape[0:2]\\n mid = np.random.randint(0, w)\\n factor = np.random.uniform(0.6, 0.8)\\n if np.random.rand() > .5:\\n new_img[:, 0:mid, 0] *= factor\\n else:\\n new_img[:, mid:w, 0] *= factor\\n return (new_img.astype(np.uint8))\",\n \"def ClearRelativeAttentionInTransformerLayer(transformer_params):\\n if not issubclass(transformer_params.cls, TransformerLayer):\\n raise ValueError('Unsupported input transformer layer: %s' %\\n transformer_params.cls)\\n trans_params_copy = transformer_params.Copy()\\n if trans_params_copy.tr_self_atten_tpl is None:\\n trans_params_copy.tr_self_atten_tpl = trans_params_copy.tr_atten_tpl.Copy()\\n attention_tpl = trans_params_copy.tr_self_atten_tpl.atten_tpl\\n if attention_tpl.cls == MultiHeadedAttentionXL:\\n new_attention_tpl = MultiHeadedAttention.Params()\\n elif attention_tpl.cls == (LocalSelfAttentionXL):\\n new_attention_tpl = LocalSelfAttention.Params()\\n else:\\n raise ValueError('Unsupported attention params: %s' % attention_tpl.cls)\\n\\n new_attention_tpl = hyperparams.CopyFieldsTo(\\n attention_tpl,\\n new_attention_tpl,\\n skip=['rel_pos_emb_dim', 'skip_term_b', 'pos_atten_logits_tpl'])\\n trans_params_copy.tr_self_atten_tpl.atten_tpl = new_attention_tpl\\n return trans_params_copy\",\n \"def forward(self, encoder_state, context, context_lens):\\n attn = self.attention(context, encoder_state.squeeze(0), context_lens)\\n return attn\",\n \"def identity_mask_propagation(nx_node, nx_graph):\\n input_masks = get_input_masks(nx_node, nx_graph)\\n assert len(input_masks) == 1\\n nx_node[\\\"input_masks\\\"] = input_masks\\n nx_node[\\\"output_mask\\\"] = input_masks[0]\",\n \"def layer_masks(self, module):\\n pass\\n # return masks\",\n \"def apply_mask(self, mask, parameters=None):\\n if parameters is None:\\n self.dates = self.dates[mask]\\n for key in self.data.keys():\\n self.data[key] = self.data[key][mask]\\n\\n self.manufacturer = self.manufacturer[mask]\\n self.data_file = self.data_file[mask]\\n self.serial_number = self.serial_number[mask]\\n else:\\n for parameter in parameters:\\n self.data[parameter][~mask] = np.nan\",\n \"def augment(image,masks):\\n\\n # Random horizontal flipping\\n if random.random() > 0.5:\\n image = TF.hflip(image)\\n masks = TF.hflip(masks)\\n\\n # Random vertical flipping\\n if random.random() > 0.5:\\n image = TF.vflip(image)\\n masks = TF.vflip(masks)\\n return image,masks\",\n \"def build_attention_mask(input_ids): \\n attention_masks = [] \\n\\n # 1 for input and 0 for pad\\n for seq in input_ids: \\n attention_masks.append([float(i>0) for i in seq])\\n\\n return attention_masks\",\n \"def compute_attention(t1, t2):\\n dim = t1.shape.as_list()[2]\\n init = tf.constant_initializer(1.0 / dim)\\n\\n t1_logits = ops.last_dim_weighted_sum(t1, \\\"t1_w\\\")\\n t2_logits = ops.last_dim_weighted_sum(t2, \\\"t2_w\\\")\\n\\n dot_w = tf.get_variable(\\n \\\"dot_w\\\", shape=dim, initializer=init, dtype=tf.float32)\\n # Compute x * dot_weights first, then batch mult with x\\n dots = t1 * tf.expand_dims(tf.expand_dims(dot_w, 0), 0)\\n dot_logits = tf.matmul(dots, t2, transpose_b=True)\\n\\n return dot_logits + \\\\\\n tf.expand_dims(t1_logits, 2) + \\\\\\n tf.expand_dims(t2_logits, 1)\",\n \"def make_attention_mask(source_block, target_block):\\n mask = (target_block[None, :] >= 1) * (source_block[:, None] >= 1)\\n mask = mask.astype(np.int64)\\n # (source_length, target_length)\\n return mask\",\n \"def forward(self,\\n x: Tensor = None,\\n memory: Tensor = None,\\n src_mask: Tensor = None,\\n trg_mask: Tensor = None) -> Tensor:\\n # decoder/target self-attention\\n\\n x_norm = self.x_layer_norm(x)\\n# print(x_norm)\\n# trg_mask()\\n# print(trg_mask)\\n\\n h1 = self.trg_trg_att(x_norm, x_norm, x_norm, mask=trg_mask)\\n h1 = self.dropout(h1) + x\\n\\n\\n if self.src_trg_att:\\n # source-target attention\\n h1_norm = self.dec_layer_norm(h1)\\n h2 = self.src_trg_att(memory, memory, h1_norm, mask=src_mask)\\n # final position-wise feed-forward layer\\n o = self.feed_forward(self.dropout(h2) + h1)\\n else:\\n o = self.feed_forward(h1)\\n return o\",\n \"def input_mask(self):\\n inputs = self.input\\n if isinstance(inputs, list):\\n return [getattr(x, '_keras_mask', None) for x in inputs]\\n else:\\n return getattr(inputs, '_keras_mask', None)\",\n \"def sdp_attention(Q, K, V, mask=None):\\n matmul_qk = tf.matmul(Q, K, transpose_b=True)\\n scald_qk = tf.cast(tf.shape(K)[-1], tf.float32)\\n scald_atten = matmul_qk / tf.math.sqrt(scald_qk)\\n\\n # masked added to tensor\\n if mask is not None:\\n scald_attention += (mask * -1e9)\\n # weights are the attention weights\\n weights = tf.nn.softmax(scald_atten, axis=-1)\\n output = tf.matmul(weights, V)\\n\\n return output, weights\",\n \"def make_attention_mask_3d(source_mask, target_mask):\\n mask = target_mask[:, None, :] * source_mask[:, :, None]\\n return mask\",\n \"def ann_mean(ds, season=None, time_bnds_varname='time_bnds', time_centered=True, n_req=None):\\n \\n ds = ds.copy() #deep=True)\\n\\n if n_req is None:\\n if season is not None:\\n n_req = 2\\n else:\\n n_req = 8\\n \\n if time_bnds_varname is None and not time_centered:\\n raise NotImplementedError('time_bnds_varname cannot be \\\"None\\\" if time_centered=False')\\n \\n if not time_centered:\\n time_units = ds.time.encoding['units']\\n time_calendar = ds.time.encoding['calendar']\\n\\n # compute time bounds array\\n time_bound_data = cftime.date2num(\\n ds[time_bnds_varname].data, \\n units=time_units, \\n calendar=time_calendar) \\n\\n # center time\\n time_centered = cftime.num2date(\\n time_bound_data.mean(axis=1),\\n units=time_units, \\n calendar=time_calendar\\n ) \\n time_attrs = ds.time.attrs\\n time_encoding = ds.time.encoding\\n\\n ds['time'] = xr.DataArray(\\n time_centered,\\n dims=('time')\\n ) \\n \\n ones = xr.DataArray(\\n np.ones((len(ds.time))), \\n dims=('time'), \\n coords={'time': ds.time},\\n )\\n time_mask = xr.DataArray(\\n np.ones((len(ds.time))), \\n dims=('time'), \\n coords={'time': ds.time},\\n )\\n\\n group_by_year = 'time.year'\\n rename = {'year': 'time'}\\n \\n if season is not None:\\n season = season.upper()\\n if season not in ['DJF', 'MAM', 'JJA', 'SON']:\\n raise ValueError(f'unknown season: {season}') \\n\\n ds['austral_year'] = xr.where(ds['time.month'] > 6, ds['time.year'] + 1, ds['time.year'])\\n ds = ds.set_coords('austral_year')\\n ones = ones.assign_coords({'austral_year': ds.austral_year})\\n time_mask = time_mask.assign_coords({'austral_year': ds.austral_year})\\n time_mask = time_mask.where(ds['time.season'] == season).fillna(0)\\n \\n if season == 'DJF':\\n group_by_year = 'austral_year'\\n rename = {'austral_year': 'time'}\\n \\n if time_bnds_varname is not None:\\n time_wgt = ds[time_bnds_varname].diff(dim=ds[time_bnds_varname].dims[1])\\n if time_wgt.dtype == '<m8[ns]':\\n time_wgt = time_wgt / np.timedelta64(1, 'D')\\n else: \\n time_wgt = xr.DataArray(\\n np.ones((len(ds.time))), \\n dims=('time'), \\n coords={'time': ds.time},\\n )\\n time_wgt = time_wgt.assign_coords(\\n {c: da for c, da in ds.coords.items() if 'time' in da.dims}\\n )\\n \\n time_wgt = time_wgt.where(time_mask==1) #.fillna(0.)\\n\\n ones = ones.where(time_mask==1)\\n time_wgt_grouped = time_wgt.groupby(group_by_year, restore_coord_dims=False)\\n time_wgt = time_wgt_grouped / time_wgt_grouped.sum(dim=xr.ALL_DIMS)\\n\\n nyr = len(time_wgt_grouped.groups)\\n \\n time_wgt = time_wgt.squeeze()\\n\\n idx_not_nans = ~np.isnan(time_wgt)\\n sum_wgt = time_wgt.groupby(group_by_year).sum(dim=xr.ALL_DIMS)\\n idx_not_nans = (sum_wgt > 0)\\n\\n np.testing.assert_almost_equal(\\n sum_wgt[idx_not_nans], \\n np.ones(idx_not_nans.sum().values)\\n )\\n\\n nontime_vars = set([v for v in ds.variables if 'time' not in ds[v].dims]) - set(ds.coords)\\n dsop = ds.drop_vars(nontime_vars)\\n\\n if time_bnds_varname is not None:\\n dsop = dsop.drop_vars(time_bnds_varname) \\n \\n def weighted_mean_arr(darr, wgts=None):\\n # if NaN are present, we need to use individual weights\\n cond = darr.isnull()\\n ones = xr.where(cond, 0.0, 1.0)\\n if season is None:\\n mask = (\\n darr.resample({'time': 'A'}, restore_coord_dims=False).mean(dim='time').notnull()\\n )\\n da_sum = (\\n (darr * wgts).resample({'time': 'A'}, restore_coord_dims=False).sum(dim='time')\\n )\\n ones_out = (\\n (ones * wgts).resample({'time': 'A'}, restore_coord_dims=False).sum(dim='time')\\n )\\n count = (\\n (ones * wgts.notnull()).resample({'time': 'A'}, restore_coord_dims=False).sum(dim='time')\\n )\\n else:\\n mask = (\\n darr.groupby(group_by_year, restore_coord_dims=False).mean(dim='time').notnull()\\n ).rename(rename)\\n \\n da_sum = (\\n (darr * wgts).groupby(group_by_year, restore_coord_dims=False).sum(dim='time')\\n ).rename(rename)\\n \\n ones_out = (\\n (ones * wgts).groupby(group_by_year, restore_coord_dims=False).sum(dim='time')\\n ).rename(rename)\\n \\n count = (\\n (ones * wgts.notnull()).groupby(group_by_year, restore_coord_dims=False).sum(dim='time')\\n ).rename(rename)\\n\\n ones_out = ones_out.where(ones_out > 0.0)\\n da_weighted_mean = da_sum / ones_out\\n\\n return da_weighted_mean.where(mask).where(count >= n_req) \\n\\n with warnings.catch_warnings():\\n warnings.simplefilter(\\\"ignore\\\", category=RuntimeWarning)\\n ds_ann = dsop.map(weighted_mean_arr, wgts=time_wgt)\\n\\n # copy attrs\\n for v in ds_ann:\\n ds_ann[v].attrs = ds[v].attrs\\n\\n # restore coords\\n ds_ann = xr.merge((ds_ann, ds[list(nontime_vars)]))\\n\\n # eliminate partials\\n ndx = (time_wgt_grouped.count(dim=xr.ALL_DIMS) >= n_req).values\\n if not ndx.all():\\n ds_ann = ds_ann.isel(time=ndx)\\n\\n return ds_ann\",\n \"def ExtendWithZeros(size_added, name=None):\\n # This automatically infers the batch size from the shape of the input\\n # See https://stackoverflow.com/questions/46465813/creating-constant-value-in-keras\\n def func(x):\\n batch_size = K.shape(x)[0]\\n zeros = K.zeros((1, size_added))\\n tiledzeros = K.tile(zeros, (batch_size, 1))\\n return K.concatenate([x, tiledzeros])\\n return keras.layers.Lambda(func, name=name)\",\n \"def masked_temperature_softmax(x:torch.Tensor, idx:int, T:float=0.01):\\n return torch.exp(x[idx, :] / T) / torch.exp(x[idx, :] / T).sum()\",\n \"def __init__(self, kernel_size=11, log_t=False):\\n super(Attention, self).__init__()\\n assert kernel_size % 2 == 1, \\\"Kernel size should be odd for 'same' conv.\\\"\\n padding = (kernel_size - 1) // 2\\n self.conv = nn.Conv1d(1, 1, kernel_size, padding=padding)\\n self.log_t = log_t\",\n \"def self_attention(tensor,\\n mask=None,\\n mask_is_length=True,\\n logit_fn=None,\\n scale_dot=False,\\n normalizer=tf.nn.softmax,\\n scope=None,\\n reuse=False):\\n assert len(tensor.get_shape()) == 3, 'The rank of `tensor` must be 3 but got {}.'.format(\\n len(tensor.get_shape()))\\n with tf.variable_scope(scope or 'self_att', reuse=reuse):\\n hidden_size = tensor.get_shape().as_list()[-1]\\n if logit_fn is None:\\n logits = tf.layers.dense(tensor, hidden_size, activation=tf.tanh)\\n logits = tf.squeeze(tf.layers.dense(logits, 1), 2)\\n else:\\n logits = logit_fn(tensor)\\n if scale_dot:\\n logits /= tf.sqrt(hidden_size)\\n if mask is not None:\\n logits = exp_mask(logits, mask, mask_is_length=mask_is_length)\\n weights = normalizer(logits)\\n out = tf.reduce_sum(tf.expand_dims(weights, -1) * tensor, 1)\\n return out,weights\",\n \"def forward(\\n self,\\n embedding_sequence: torch.Tensor,\\n encoder_output: torch.Tensor,\\n source_mask: torch.Tensor,\\n target_mask: torch.Tensor = None,\\n apply_target_subsequent_mask: bool = True,\\n ):\\n\\n if apply_target_subsequent_mask:\\n # shape : (target_sequence_length, target_sequence_length)\\n target_subsequent_mask = make_subsequent_mask(embedding_sequence)\\n else:\\n target_subsequent_mask = None\\n\\n embedding_sequence = self.sublayer[0](\\n embedding_sequence,\\n lambda x: self.self_attn(x, x, x, key_value_mask=target_mask, attention_mask=target_subsequent_mask),\\n )\\n embedding_sequence = self.sublayer[1](\\n embedding_sequence, lambda x: self.src_attn(x, encoder_output, encoder_output, key_value_mask=source_mask)\\n )\\n return self.sublayer[2](embedding_sequence, self.feed_forward)\",\n \"def applymask(self,mask):\\n self.spec[mask==0]=np.nan\",\n \"def RelativeAttentionLMLayer(d_feature,\\n total_kv_pooling,\\n n_heads=1,\\n dropout=0.0,\\n n_raw_tokens_generated=1,\\n max_inference_length=3072,\\n chunk_len=None,\\n chunk_offset=None,\\n mode='train'):\\n\\n attention = RelativeAttentionLayer(\\n d_feature,\\n total_kv_pooling,\\n n_heads=n_heads,\\n dropout=dropout,\\n n_raw_tokens_generated=n_raw_tokens_generated,\\n max_inference_length=max_inference_length,\\n chunk_len=chunk_len,\\n chunk_offset=chunk_offset,\\n mode=mode)\\n\\n mask_layer = AttentionMaskLayer(\\n total_kv_pooling=total_kv_pooling,\\n max_inference_length=max_inference_length,\\n chunk_len=chunk_len,\\n chunk_offset=chunk_offset,\\n n_raw_tokens_generated=n_raw_tokens_generated,\\n mode=mode)\\n\\n return cb.Serial(\\n cb.Branch(\\n None,\\n mask_layer, # vecs, mask\\n ),\\n attention, # vecs, mask\\n cb.Select([0], n_in=2), # vecs\\n )\",\n \"def UseRelativeAttentionInTransformerLayer(transformer_params,\\n rel_pos_emb_dim,\\n atten_type=ATTEN_TRANSFORMER_XL):\\n if not issubclass(transformer_params.cls, TransformerLayer):\\n raise ValueError('Unsupported input transformer layer: %s' %\\n transformer_params.cls)\\n\\n if atten_type not in (ATTEN_TRANSFORMER_XL, ATTEN_RPE):\\n raise ValueError('Relative attention type: %s unsupported' % atten_type)\\n\\n # Gets multiheaded attention tpl from self attention config in transformer.\\n trans_params_copy = transformer_params.Copy()\\n if trans_params_copy.tr_self_atten_tpl is None:\\n trans_params_copy.tr_self_atten_tpl = trans_params_copy.tr_atten_tpl.Copy()\\n atten_tpl = trans_params_copy.tr_self_atten_tpl.atten_tpl\\n\\n # If already using relative attention class.\\n if atten_tpl.cls in (MultiHeadedAttentionRPE, MultiHeadedAttentionXL,\\n LocalSelfAttentionXL):\\n atten_tpl.rel_pos_emb_dim = rel_pos_emb_dim\\n return trans_params_copy\\n\\n if atten_type == ATTEN_TRANSFORMER_XL:\\n if atten_tpl.cls == MultiHeadedAttention:\\n rel_atten_tpl = MultiHeadedAttentionXL.Params()\\n elif atten_tpl.cls == LocalSelfAttention:\\n rel_atten_tpl = (LocalSelfAttentionXL.Params())\\n else:\\n raise ValueError('Unsupported attention: %s' % atten_tpl.cls)\\n elif atten_type == ATTEN_RPE:\\n rel_atten_tpl = MultiHeadedAttentionRPE.Params()\\n\\n rel_atten_tpl = hyperparams.CopyFieldsTo(atten_tpl, rel_atten_tpl)\\n rel_atten_tpl.rel_pos_emb_dim = rel_pos_emb_dim\\n\\n trans_params_copy.tr_self_atten_tpl.atten_tpl = rel_atten_tpl\\n return trans_params_copy\",\n \"def attention_layer(from_tensor,\\n to_tensor,\\n attention_mask=None,\\n num_attention_heads=1,\\n size_per_head=512,\\n query_act=None,\\n key_act=None,\\n value_act=None,\\n attention_probs_dropout_prob=0.0,\\n initializer_range=0.02,\\n do_return_2d_tensor=False,\\n batch_size=None,\\n from_seq_length=None,\\n to_seq_length=None, \\n conv_kernel_size=9,\\n head_ratio=2,\\n conv_type=1,\\n from_tensor_mask=None,\\n to_tensor_mask=None,\\n conv_method='gate'):\\n\\n def transpose_for_scores(input_tensor, batch_size, num_attention_heads,\\n seq_length, width):\\n output_tensor = tf.reshape(\\n input_tensor, [batch_size, seq_length, num_attention_heads, width])\\n\\n output_tensor = tf.transpose(output_tensor, [0, 2, 1, 3])\\n return output_tensor\\n def reshape_for_conv(input_tensor, batch_size, num_attention_heads,\\n seq_length, width):\\n output_tensor = tf.reshape(\\n input_tensor, [batch_size, seq_length, num_attention_heads*width])\\n return output_tensor\\n\\n\\n from_shape = bert_utils.get_shape_list(from_tensor, expected_rank=[2, 3])\\n to_shape = bert_utils.get_shape_list(to_tensor, expected_rank=[2, 3])\\n\\n if len(from_shape) != len(to_shape):\\n raise ValueError(\\n \\\"The rank of `from_tensor` must match the rank of `to_tensor`.\\\")\\n\\n if len(from_shape) == 3:\\n batch_size = from_shape[0]\\n from_seq_length = from_shape[1]\\n to_seq_length = to_shape[1]\\n elif len(from_shape) == 2:\\n if batch_size is None or from_seq_length is None or to_seq_length is None:\\n raise ValueError(\\n \\\"When passing in rank 2 tensors to attention_layer, the values \\\"\\n \\\"for `batch_size`, `from_seq_length`, and `to_seq_length` \\\"\\n \\\"must all be specified.\\\")\\n\\n # Scalar dimensions referenced here:\\n # B = batch size (number of sequences)\\n # F = `from_tensor` sequence length\\n # T = `to_tensor` sequence length\\n # N = `num_attention_heads`\\n # H = `size_per_head`\\n\\n from_tensor_2d = bert_utils.reshape_to_matrix(from_tensor)\\n to_tensor_2d = bert_utils.reshape_to_matrix(to_tensor)\\n\\n\\n new_num_attention_heads = int(num_attention_heads/head_ratio)\\n if new_num_attention_heads<1:\\n head_ratio=num_attention_heads\\n num_attention_heads=1\\n else:\\n num_attention_heads=new_num_attention_heads\\n\\n # `query_layer` = [B*F, N*H]\\n query_layer = tf.layers.dense(\\n from_tensor_2d,\\n num_attention_heads * size_per_head,\\n activation=query_act,\\n name=\\\"query\\\",\\n kernel_initializer=create_initializer(initializer_range))\\n\\n # `key_layer` = [B*T, N*H]\\n key_layer = tf.layers.dense(\\n to_tensor_2d,\\n num_attention_heads * size_per_head,\\n activation=key_act,\\n name=\\\"key\\\",\\n kernel_initializer=create_initializer(initializer_range))\\n\\n # `value_layer` = [B*T, N*H]\\n value_layer = tf.layers.dense(\\n to_tensor_2d,\\n num_attention_heads * size_per_head,\\n activation=value_act,\\n name=\\\"value\\\",\\n kernel_initializer=create_initializer(initializer_range))\\n\\n if conv_type in ['sdconv']:\\n # [B,T, N*H]\\n key_conv_attn_layer_input = reshape_for_conv(to_tensor_2d, batch_size, num_attention_heads*head_ratio,\\n to_seq_length, size_per_head)\\n\\n if from_tensor_mask is not None and to_tensor_mask is not None:\\n to_tensor_2d_mask = tf.cast(to_tensor_mask, tf.float32)[:, :, None]\\n from_tensor_2d_mask = tf.cast(from_tensor_mask, tf.float32)[:, :, None]\\n key_conv_attn_layer_input *= to_tensor_2d_mask\\n tf.logging.info(\\\"== apply conv seq-masking on sequence padding ==\\\")\\n\\n key_conv_attn_layer = tf.layers.separable_conv1d(key_conv_attn_layer_input,\\n num_attention_heads * size_per_head,\\n conv_kernel_size,\\n padding='same',\\n activation=value_act,\\n depthwise_initializer=create_initializer(1/conv_kernel_size),\\n # depthwise_initializer=create_initializer(initializer_range),\\n pointwise_initializer=create_initializer(initializer_range),\\n name=\\\"conv_attn_key\\\")\\n\\n if from_tensor_mask is not None and to_tensor_mask is not None:\\n key_conv_attn_layer *= to_tensor_2d_mask\\n tf.logging.info(\\\"== apply conv seq-masking on sequence padding ==\\\")\\n\\n # [B*T, N*H]\\n key_conv_attn_layer = bert_utils.reshape_to_matrix(key_conv_attn_layer)\\n if conv_method == 'dot':\\n conv_attn_layer = tf.multiply(key_conv_attn_layer, query_layer)\\n tf.logging.info(\\\"== apply conv dot query_layer ==\\\")\\n elif conv_method == 'gate':\\n query_gate = tf.layers.dense(\\n from_tensor_2d,\\n num_attention_heads * size_per_head,\\n activation=value_act,\\n name=\\\"conv_query_gate\\\",\\n kernel_initializer=create_initializer(initializer_range))\\n\\n conv_gated = tf.nn.sigmoid(tf.nn.dropout(query_gate, 1-attention_probs_dropout_prob))\\n conv_attn_layer = key_conv_attn_layer * conv_gated + query_layer * (1-conv_gated)\\n tf.logging.info(\\\"== apply conv gate query_layer ==\\\")\\n else:\\n conv_attn_layer = tf.multiply(key_conv_attn_layer, query_layer)\\n tf.logging.info(\\\"== apply conv dot query_layer ==\\\")\\n\\n # [B*T, N*K]\\n conv_kernel_layer = tf.layers.dense(\\n conv_attn_layer,\\n num_attention_heads * conv_kernel_size,\\n activation=value_act,\\n name=\\\"conv_attn_kernel\\\",\\n kernel_initializer=create_initializer(initializer_range))\\n # [B*T*N,K,1]\\n conv_kernel_layer = tf.reshape(conv_kernel_layer, \\n [batch_size*to_seq_length*num_attention_heads, conv_kernel_size, 1])\\n \\n # conv_kernel_layer = tf.nn.softmax(conv_kernel_layer, axis=1)\\n attention_probs = tf.exp(tf.nn.log_softmax(conv_kernel_layer+1e-10, axis=-1))\\n \\n paddings = tf.constant([[0, 0,], [int((conv_kernel_size-1)/2), int((conv_kernel_size-1)/2)],[0,0]])\\n \\n conv_out_layer = tf.layers.dense(\\n to_tensor_2d,\\n num_attention_heads * size_per_head,\\n activation=value_act,\\n name=\\\"conv_attn_point\\\",\\n kernel_initializer=create_initializer(initializer_range))\\n # [B,T, N*H]\\n conv_out_layer = tf.reshape(conv_out_layer,[batch_size,to_seq_length,num_attention_heads * size_per_head])\\n if from_tensor_mask is not None and to_tensor_mask is not None:\\n conv_out_layer *= to_tensor_2d_mask\\n tf.logging.info(\\\"== apply conv seq-masking on sequence padding ==\\\")\\n\\n conv_out_layer = tf.pad(conv_out_layer, paddings, \\\"CONSTANT\\\")\\n # unfold [B,T, N*H, K]\\n unfold_conv_out_layer = tf.stack(\\n [tf.slice(conv_out_layer, [0, i, 0],[batch_size,to_seq_length,num_attention_heads * size_per_head]) for i in range(conv_kernel_size)],-1)\\n # following only work for gpu version\\n # conv_out_layer = tf.reshape(conv_out_layer,[batch_size,to_seq_length,num_attention_heads * size_per_head,1])\\n # unfold_conv_out_layer = tf.extract_image_patches(images=conv_out_layer, sizes=[1, conv_kernel_size, 1, 1], strides=[1, 1, 1, 1], rates=[1, 1, 1, 1], padding='SAME')\\n\\n conv_out_layer = tf.reshape(unfold_conv_out_layer,\\n [batch_size*to_seq_length*num_attention_heads ,size_per_head, conv_kernel_size])\\n\\n conv_out_layer = tf.matmul(conv_out_layer, conv_kernel_layer)\\n\\n conv_out_layer = tf.reshape(conv_out_layer, [batch_size*to_seq_length, num_attention_heads*size_per_head])\\n\\n\\n # `query_layer` = [B, N, F, H]\\n query_layer = transpose_for_scores(query_layer, batch_size,\\n num_attention_heads, from_seq_length,\\n size_per_head)\\n\\n # `key_layer` = [B, N, T, H]\\n key_layer = transpose_for_scores(key_layer, batch_size, num_attention_heads,\\n to_seq_length, size_per_head)\\n\\n # Take the dot product between \\\"query\\\" and \\\"key\\\" to get the raw\\n # attention scores.\\n # `attention_scores` = [B, N, F, T]\\n attention_scores = tf.matmul(query_layer, key_layer, transpose_b=True)\\n attention_scores = tf.multiply(attention_scores,\\n 1.0 / math.sqrt(float(size_per_head)))\\n\\n if attention_mask is not None:\\n # `attention_mask` = [B, 1, F, T]\\n attention_mask = tf.expand_dims(attention_mask, axis=[1])\\n\\n # Since attention_mask is 1.0 for positions we want to attend and 0.0 for\\n # masked positions, this operation will create a tensor which is 0.0 for\\n # positions we want to attend and -10000.0 for masked positions.\\n adder = (1.0 - tf.cast(attention_mask, tf.float32)) * -10000.0\\n\\n # Since we are adding it to the raw scores before the softmax, this is\\n # effectively the same as removing these entirely.\\n attention_scores += adder\\n\\n # Normalize the attention scores to probabilities.\\n # `attention_probs` = [B, N, F, T]\\n # attention_probs = tf.nn.softmax(attention_scores)\\n attention_probs = tf.exp(tf.nn.log_softmax(attention_scores+1e-10))\\n\\n # This is actually dropping out entire tokens to attend to, which might\\n # seem a bit unusual, but is taken from the original Transformer paper.\\n attention_probs = dropout(attention_probs, attention_probs_dropout_prob)\\n\\n # `value_layer` = [B, T, N, H]\\n value_layer = tf.reshape(\\n value_layer,\\n [batch_size, to_seq_length, num_attention_heads, size_per_head])\\n\\n # `value_layer` = [B, N, T, H]\\n value_layer = tf.transpose(value_layer, [0, 2, 1, 3])\\n\\n # `context_layer` = [B, N, F, H]\\n context_layer = tf.matmul(attention_probs, value_layer)\\n\\n # `context_layer` = [B, F, N, H]\\n context_layer = tf.transpose(context_layer, [0, 2, 1, 3])\\n\\n\\n if conv_type in [\\\"sdconv\\\"]:\\n # only applicable for self-attention, will cause error if from_seq_length not equal to_seq_length\\n assert from_seq_length==to_seq_length\\n conv_out = tf.reshape(\\n conv_out_layer,\\n [batch_size , from_seq_length, num_attention_heads , size_per_head])\\n context_layer = tf.concat([context_layer, conv_out],2)\\n num_attention_heads = num_attention_heads*2\\n\\n if do_return_2d_tensor:\\n # `context_layer` = [B*F, N*H]\\n context_layer = tf.reshape(\\n context_layer,\\n [batch_size * from_seq_length, num_attention_heads * size_per_head])\\n else:\\n # `context_layer` = [B, F, N*H]\\n context_layer = tf.reshape(\\n context_layer,\\n [batch_size, from_seq_length, num_attention_heads * size_per_head])\\n\\n return context_layer, attention_probs, value_layer\",\n \"def inject_latent(self, layer, inputs, target, action):\\n del action\\n # Latent for stochastic model\\n filters = 128\\n full_video = tf.stack(inputs + [target], axis=1)\\n latent_mean, latent_std = self.construct_latent_tower(\\n full_video, time_axis=1)\\n latent = common_video.get_gaussian_tensor(latent_mean, latent_std)\\n latent = tfl.flatten(latent)\\n latent = tf.expand_dims(latent, axis=1)\\n latent = tf.expand_dims(latent, axis=1)\\n latent_mask = tfl.dense(latent, filters, name=\\\"latent_mask\\\")\\n zeros_mask = tf.zeros(\\n common_layers.shape_list(layer)[:-1] + [filters], dtype=tf.float32)\\n layer = tf.concat([layer, latent_mask + zeros_mask], axis=-1)\\n extra_loss = self.get_kl_loss([latent_mean], [latent_std])\\n return layer, extra_loss\",\n \"def build_attention_mask_3d_causal(source_mask, target_mask):\\n causal_mask = make_inference_history_mask_3d(target_mask)\\n mask = make_attention_mask_3d(source_mask, target_mask)\\n mask = mask * causal_mask\\n # invert mask for Megatron\\n return mask < 0.5\",\n \"def output_mask(self):\\n output = self.output\\n if isinstance(output, list):\\n return [getattr(x, '_keras_mask', None) for x in output]\\n else:\\n return getattr(output, '_keras_mask', None)\",\n \"def act(self, x: np.ndarray, t: int = None, noise: np.ndarray = None) -> np.ndarray:\",\n \"def RelativeAttentionLayer(d_feature,\\n total_kv_pooling,\\n n_heads=1,\\n dropout=0.0,\\n n_raw_tokens_generated=1,\\n max_inference_length=3072,\\n chunk_len=None,\\n chunk_offset=None,\\n mode='train'):\\n pos_emb = PositionalEmbeddings(\\n d_feature,\\n total_kv_pooling,\\n max_inference_length=max_inference_length,\\n chunk_len=chunk_len,\\n chunk_offset=chunk_offset,\\n n_raw_tokens_generated=n_raw_tokens_generated,\\n mode=mode)\\n\\n attention = RelativeAttention( # pylint: disable=no-value-for-parameter\\n total_kv_pooling=total_kv_pooling,\\n n_heads=n_heads,\\n dropout=dropout,\\n n_raw_tokens_generated=n_raw_tokens_generated,\\n max_inference_length=max_inference_length,\\n chunk_len=chunk_len,\\n chunk_offset=chunk_offset,\\n mode=mode),\\n\\n assert d_feature % n_heads == 0\\n d_head = d_feature // n_heads\\n context_bias_layer = core.Weights(\\n init.RandomNormalInitializer(1e-6), shape=(1, n_heads, 1, d_head))\\n location_bias_layer = core.Weights(\\n init.RandomNormalInitializer(1e-6), shape=(1, n_heads, 1, d_head))\\n\\n return cb.Serial(\\n cb.Branch(\\n cb.Serial(pos_emb, core.Dense(d_feature)),\\n core.Dense(d_feature),\\n core.Dense(d_feature),\\n core.Dense(d_feature),\\n cb.Select([1]) # mask\\n ),\\n context_bias_layer,\\n location_bias_layer,\\n attention,\\n core.Dense(d_feature),\\n )\",\n \"def show_sent_attention(self, x):\\n att_layer = self.model_sent.get_layer('sent_attention')\\n prev_tensor = att_layer.input\\n\\n dummy_layer = Lambda(\\n lambda x: att_layer._get_attention_weights(x)\\n )(prev_tensor)\\n\\n return Model(self.model_sent.input, dummy_layer).predict(x)\",\n \"def apply_layer(self, layer_id, func=..., v=..., inplace=...): # -> None:\\n ...\",\n \"def build(self, input_shape):\\n hidden_dim = input_shape[2]\\n self.W = self.add_weight(\\n name='{}_W'.format(self.name),\\n shape=(hidden_dim, hidden_dim,),\\n initializer='uniform',\\n trainable=True)\\n self.b = self.add_weight(\\n name='{}_b'.format(self.name),\\n shape=(hidden_dim,),\\n initializer='zeros',\\n trainable=True)\\n self.u = self.add_weight(\\n name='{}_u'.format(self.name),\\n shape=(hidden_dim,),\\n initializer='uniform',\\n trainable=True)\\n super(AttentionLayer, self).build(input_shape)\",\n \"def attention_layer(from_tensor,\\n to_tensor,\\n attention_mask=None,\\n num_attention_heads=1,\\n size_per_head=512,\\n query_act=None,\\n key_act=None,\\n value_act=None,\\n attention_probs_dropout_prob=0.0,\\n initializer_range=0.02,\\n do_return_2d_tensor=False,\\n batch_size=None,\\n from_seq_length=None,\\n to_seq_length=None):\\n\\n def transpose_for_scores(input_tensor, batch_size, num_attention_heads,\\n seq_length, width):\\n output_tensor = tf.reshape(\\n input_tensor, [batch_size, seq_length, num_attention_heads, width])\\n\\n output_tensor = tf.transpose(output_tensor, [0, 2, 1, 3])\\n return output_tensor\\n\\n from_shape = get_shape_list(from_tensor, expected_rank=[2, 3])\\n to_shape = get_shape_list(to_tensor, expected_rank=[2, 3])\\n\\n if len(from_shape) != len(to_shape):\\n raise ValueError(\\n \\\"The rank of `from_tensor` must match the rank of `to_tensor`.\\\")\\n\\n if len(from_shape) == 3:\\n batch_size = from_shape[0]\\n from_seq_length = from_shape[1]\\n to_seq_length = to_shape[1]\\n elif len(from_shape) == 2:\\n if (batch_size is None or from_seq_length is None or to_seq_length is None):\\n raise ValueError(\\n \\\"When passing in rank 2 tensors to attention_layer, the values \\\"\\n \\\"for `batch_size`, `from_seq_length`, and `to_seq_length` \\\"\\n \\\"must all be specified.\\\")\\n\\n # Scalar dimensions referenced here:\\n # B = batch size (number of sequences)\\n # F = `from_tensor` sequence length\\n # T = `to_tensor` sequence length\\n # N = `num_attention_heads`\\n # H = `size_per_head`\\n\\n from_tensor_2d = reshape_to_matrix(from_tensor)\\n to_tensor_2d = reshape_to_matrix(to_tensor)\\n\\n # `query_layer` = [B*F, N*H]\\n query_layer = tf.layers.dense(\\n from_tensor_2d,\\n num_attention_heads * size_per_head,\\n activation=query_act,\\n name=\\\"query\\\",\\n kernel_initializer=create_initializer(initializer_range))\\n\\n # `key_layer` = [B*T, N*H]\\n key_layer = tf.layers.dense(\\n to_tensor_2d,\\n num_attention_heads * size_per_head,\\n activation=key_act,\\n name=\\\"key\\\",\\n kernel_initializer=create_initializer(initializer_range))\\n\\n # `value_layer` = [B*T, N*H]\\n value_layer = tf.layers.dense(\\n to_tensor_2d,\\n num_attention_heads * size_per_head,\\n activation=value_act,\\n name=\\\"value\\\",\\n kernel_initializer=create_initializer(initializer_range))\\n\\n # `query_layer` = [B, N, F, H]\\n query_layer = transpose_for_scores(query_layer, batch_size,\\n num_attention_heads, from_seq_length,\\n size_per_head)\\n\\n # `key_layer` = [B, N, T, H]\\n key_layer = transpose_for_scores(key_layer, batch_size, num_attention_heads,\\n to_seq_length, size_per_head)\\n\\n # Take the dot product between \\\"query\\\" and \\\"key\\\" to get the raw\\n # attention scores.\\n # `attention_scores` = [B, N, F, T]\\n attention_scores = tf.matmul(query_layer, key_layer, transpose_b=True)\\n attention_scores = tf.multiply(attention_scores,\\n 1.0 / math.sqrt(float(size_per_head)))\\n\\n if attention_mask is not None:\\n # `attention_mask` = [B, 1, F, T]\\n attention_mask = tf.expand_dims(attention_mask, axis=[1])\\n\\n # Since attention_mask is 1.0 for positions we want to attend and 0.0 for\\n # masked positions, this operation will create a tensor which is 0.0 for\\n # positions we want to attend and -10000.0 for masked positions.\\n adder = (1.0 - tf.cast(attention_mask, tf.float32)) * -10000.0\\n\\n # Since we are adding it to the raw scores before the softmax, this is\\n # effectively the same as removing these entirely.\\n attention_scores += adder\\n\\n # Normalize the attention scores to probabilities.\\n # `attention_probs` = [B, N, F, T]\\n attention_probs = tf.nn.softmax(attention_scores)\\n\\n # This is actually dropping out entire tokens to attend to, which might\\n # seem a bit unusual, but is taken from the original Transformer paper.\\n attention_probs = dropout(attention_probs, attention_probs_dropout_prob)\\n\\n # `value_layer` = [B, T, N, H]\\n value_layer = tf.reshape(\\n value_layer,\\n [batch_size, to_seq_length, num_attention_heads, size_per_head])\\n\\n # `value_layer` = [B, N, T, H]\\n value_layer = tf.transpose(value_layer, [0, 2, 1, 3])\\n\\n # `context_layer` = [B, N, F, H]\\n context_layer = tf.matmul(attention_probs, value_layer)\\n\\n # `context_layer` = [B, F, N, H]\\n context_layer = tf.transpose(context_layer, [0, 2, 1, 3])\\n\\n if do_return_2d_tensor:\\n # `context_layer` = [B*F, N*V]\\n context_layer = tf.reshape(\\n context_layer,\\n [batch_size * from_seq_length, num_attention_heads * size_per_head])\\n else:\\n # `context_layer` = [B, F, N*V]\\n context_layer = tf.reshape(\\n context_layer,\\n [batch_size, from_seq_length, num_attention_heads * size_per_head])\\n\\n return context_layer\",\n \"def op_attenuator(t):\\n att = np.array([[t, 0, 0, 0],\\n [0, t, 0, 0],\\n [0, 0, t, 0],\\n [0, 0, 0, t]])\\n return att\",\n \"def forward(self, tgt, memory, tgt_mask=None, memory_mask=None):\\n # m = memory\\n # LayerNorm + SelfAtt + Dropout + Residual\\n tgt = self.sublayer[0](tgt, lambda x: self.self_attn(x, x, x, tgt_mask))\\n # LayerNorm + Att + Dropout + Residual\\n tgt = self.sublayer[1](tgt, lambda x: self.memory_attn(x, memory, memory, memory_mask))\\n # LayerNorm + FF + Dropout +Residual\\n layer_output = self.sublayer[2](tgt, self.feed_forward)\\n return layer_output\",\n \"def local_attention(inputs, num_filters, filter_size=5, initializer=None, reuse=None,\\n name=''):\\n print(\\\"Local Attentional\\\")\\n weighted_inputs, _ = convolutional_attention(inputs, filter_size=filter_size,\\n initializer=initializer, name='local{}'.format(name),\\n reuse=reuse)\\n conv_output = build_cnn(weighted_inputs, num_filters, filter_sizes=3,\\n initializer=initializer, name='local{}'.format(name),\\n reuse=reuse)\\n print(conv_output)\\n return conv_output\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6418364","0.6348513","0.5860708","0.58178973","0.56244344","0.56133187","0.55821043","0.54933465","0.5388436","0.53026986","0.5298122","0.52612346","0.52581245","0.5257906","0.5252626","0.52330077","0.5183299","0.5153909","0.5150206","0.5134586","0.51121294","0.51084644","0.5106471","0.50939184","0.509123","0.50854105","0.5084926","0.50775343","0.50727654","0.50655293","0.5031954","0.5021979","0.5006329","0.5005717","0.4997829","0.49946743","0.4991915","0.49902573","0.4973596","0.49716702","0.497068","0.49693033","0.4966573","0.49649745","0.4963326","0.49576348","0.49499708","0.49330604","0.49288708","0.49255514","0.49227166","0.49210685","0.49085936","0.4907425","0.49054492","0.49017","0.4896091","0.48949593","0.48929116","0.48817885","0.48746914","0.4874373","0.4869024","0.48682013","0.48628044","0.48615235","0.48439232","0.48415038","0.48381436","0.48237243","0.48228803","0.48224765","0.48127598","0.4811192","0.480807","0.4802347","0.47942433","0.47936073","0.47897613","0.47822398","0.47777334","0.47751445","0.47697216","0.4767698","0.47640395","0.47627792","0.47584864","0.4754438","0.47416586","0.47364077","0.47328344","0.47318476","0.4730306","0.47258577","0.471278","0.47048748","0.4690378","0.46897703","0.46896166","0.46882233"],"string":"[\n \"0.6418364\",\n \"0.6348513\",\n \"0.5860708\",\n \"0.58178973\",\n \"0.56244344\",\n \"0.56133187\",\n \"0.55821043\",\n \"0.54933465\",\n \"0.5388436\",\n \"0.53026986\",\n \"0.5298122\",\n \"0.52612346\",\n \"0.52581245\",\n \"0.5257906\",\n \"0.5252626\",\n \"0.52330077\",\n \"0.5183299\",\n \"0.5153909\",\n \"0.5150206\",\n \"0.5134586\",\n \"0.51121294\",\n \"0.51084644\",\n \"0.5106471\",\n \"0.50939184\",\n \"0.509123\",\n \"0.50854105\",\n \"0.5084926\",\n \"0.50775343\",\n \"0.50727654\",\n \"0.50655293\",\n \"0.5031954\",\n \"0.5021979\",\n \"0.5006329\",\n \"0.5005717\",\n \"0.4997829\",\n \"0.49946743\",\n \"0.4991915\",\n \"0.49902573\",\n \"0.4973596\",\n \"0.49716702\",\n \"0.497068\",\n \"0.49693033\",\n \"0.4966573\",\n \"0.49649745\",\n \"0.4963326\",\n \"0.49576348\",\n \"0.49499708\",\n \"0.49330604\",\n \"0.49288708\",\n \"0.49255514\",\n \"0.49227166\",\n \"0.49210685\",\n \"0.49085936\",\n \"0.4907425\",\n \"0.49054492\",\n \"0.49017\",\n \"0.4896091\",\n \"0.48949593\",\n \"0.48929116\",\n \"0.48817885\",\n \"0.48746914\",\n \"0.4874373\",\n \"0.4869024\",\n \"0.48682013\",\n \"0.48628044\",\n \"0.48615235\",\n \"0.48439232\",\n \"0.48415038\",\n \"0.48381436\",\n \"0.48237243\",\n \"0.48228803\",\n \"0.48224765\",\n \"0.48127598\",\n \"0.4811192\",\n \"0.480807\",\n \"0.4802347\",\n \"0.47942433\",\n \"0.47936073\",\n \"0.47897613\",\n \"0.47822398\",\n \"0.47777334\",\n \"0.47751445\",\n \"0.47697216\",\n \"0.4767698\",\n \"0.47640395\",\n \"0.47627792\",\n \"0.47584864\",\n \"0.4754438\",\n \"0.47416586\",\n \"0.47364077\",\n \"0.47328344\",\n \"0.47318476\",\n \"0.4730306\",\n \"0.47258577\",\n \"0.471278\",\n \"0.47048748\",\n \"0.4690378\",\n \"0.46897703\",\n \"0.46896166\",\n \"0.46882233\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.48330575"},"document_rank":{"kind":"string","value":"69"}}},{"rowIdx":81785,"cells":{"query":{"kind":"string","value":"Gets the position of a Fibonacci number and returns the Fibonacci number"},"document":{"kind":"string","value":"def fibonacci_number_counter(p):\r\n if p == 0:\r\n return 0\r\n elif p == 1 or p == 2:\r\n return 1\r\n else:\r\n fibonacci_list = [1, 1]\r\n while len(fibonacci_list) < p:\r\n fibonacci_list.append(fibonacci_list[-1] + fibonacci_list[-2])\r\n\r\n return fibonacci_list[-1]"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_fib(position):\n\n # Base Case: Positions greater thatn 0 or 1, since Fibonacci for 0 is 0 and\n # 1 is 1.\n if position == 0 or position == 1:\n return position\n\n return get_fib(position - 1) + get_fib(position - 2)","def next_fib(f):\n for f in fib:\n i = fib.index(f)\n return f+fib[i-1]","def find_fib(n):\n # fibo = 2.078087 * math.log(n) + 1.672276\n return 0 # fibo","def fibonacci(n):\r\n\r\n if n in past_fib:\r\n return past_fib[n]\r\n \r\n if n == 0 or n == 1:\r\n past_fib[n] = 1\r\n return 1\r\n\r\n total = fibonacci(n-1) + fibonacci(n-2)\r\n past_fib[n] = total\r\n return total","def fast_fibonacci(n):\n return _fast_fibonacci(n)[0]","def fib(n): #Describe \"n\" as a variable in fib sequence\n while n == 0:\n return 0 #establish that 0 position is equal to 0\n if n == 1:\n return 1\n else:\n return fib(n-1) + fib(n-2)","def fibonacci(n):","def fibi(n):\n a, b = 0, 1\n for i in range(n):\n # fibonacci series is next no. is sum of previous two number.\n temp = a\n a = b\n # now nth fibonacci no. is sum of previous two number.\n b = temp+b\n # returning a because a changing each places\n return a","def fib(f1, index):\n if index == 0:\n return 0\n if index == 1:\n return f1\n if (f1, index) not in FIBS_CACHE:\n FIBS_CACHE[f1, index] = fib(f1, index-1) + fib(f1, index-2)\n return FIBS_CACHE[f1, index]","def fib(n:int) -> int:\n if n<= 2:\n return 1\n else:\n return fibonacci.fib(n-1) + fibonacci.fib(n-2)","def nthFibonacci(n):\n\n # Run some basic error checking\n try:\n n = int(n)\n except: # if this fails not a number inputed\n sys.stderr.write('Incorrect data input\\n')\n return None\n if n < 0:\n sys.stderr.write('Only positive integers allowed\\n')\n return None\n \n # since the error checking slows down the recursion we run it as a seperate function\n [Fnm,Fn] = fastrecursivefibonacci(n)\n return Fnm","def optimized_fibonacci(f):\n a = 0\n b = 1\n if f < 2:\n return f\n else:\n for i in range(1, f):\n c = a + b\n a = b\n b = c\n return b","def fibonacci(n):\n if n == 0:\n return 0\n elif n == 1:\n return 1\n else:\n nth = fibonacci(n-1) + fibonacci(n-2)\n return nth","def fibo_element(n):\n f = ()\n if n < 0:\n print(\"Incorrect number\")\n elif n == 0:\n return 0\n elif n == 1:\n return 1\n else:\n return fibo_element(n-1) + fibo_element(n-2)","def fibonacci(number: int) -> int:\n fibs = [0] * (number + 2)\n fibs[0] = 0\n fibs[1] = 1\n for i in range(2, number + 1):\n fibs[i] = fibs[i - 1] + fibs[i - 2]\n return fibs[number]","def fibonacci_number(n):\r\n l = [0, 1] \r\n for i in range(n - 1):\r\n l = [*l, l[-1] + l[-2]]\r\n return l[n - 1]","def fibonacci(n):\n\n if n == 0:\n return 0\n if n == 1:\n return 1\n \n previous = 0\n current = 1\n\n for i in range(n-1):\n previous, current = current, current + previous\n\n return current","def fibonacci(n):\n\tfib_seq = []\n\tnth_term = 0\n\t\n\tfor i in range(0,n+1):\n\t\tif i == 0:\n\t\t\tfib_seq.append(0)\n\t\tif i == 1:\n\t\t\tfib_seq.append(1)\n\t\tif i > 1:\n\t\t\tnth_term = fib_seq[-1] + fib_seq[-2]\n\t\t\tfib_seq.append(nth_term)\n\t\n\tprint(fib_seq)\n\tprint(fib_seq[n])\n\treturn(fib_seq[n])","def fibonacci(a):\n fib = [1,1]\n x = 0\n i = 1\n while x < a:\n x = fib [i] + fib[i-1]\n i += 1\n fib.append(x)\n return i, fib","def fibonacci(n):\n if n in (0, 1):\n return n\n return fibonacci(n - 2) + fibonacci(n - 1)","def fibonacci():\n return sum_series(a=0, b=1)","def fibonacci(n):\n if n in (0, 1):\n return n\n return (fibonacci(n-2) + fibonacci(n-1))","def fibonacci(num):\n if num == 0 or num ==1:\n return 1\n return fibonacci(num-1) + fibonacci (num-2)","def fibonacci(n):\n if n in (0,1):\n return n\n\n return (fibonacci(n-2) + fibonacci(n-1))","def fibonacci(n: int) -> int:\n m = 1 << (n.bit_length() - 1)\n Fn = 0\n Fnm1 = 1\n while m:\n Fn2 = Fn * Fn\n Fn = 2 * Fnm1 * Fn + Fn2\n Fnm1 = Fnm1 * Fnm1 + Fn2\n if n & m:\n Fnm1, Fn = Fn, Fnm1 + Fn\n m >>= 1\n return Fn","def fibonacci (n):\n\tif n == 0:\n\t\treturn 0\n\telif n == 1:\n\t\treturn 1\n\telse:\n\t\treturn fibonacci(n-2) + fibonacci(n-1)","def get_fibonacci_number(self, n) -> int:\n\n if not isinstance(n, int) or n < 0:\n raise ValueError(\"n must be a non-negative integer\")\n\n if n in self.known_cache:\n return self.known_cache[n]\n\n # Without caching known Fibonacci numbers like this, this function\n # will generate a \"maximum recursion depth exceeded\" error\n # (when for sufficiently large Fibonacci numbers).\n # That's because Python doesn't do tail recursion elimination.\n self.known_cache[n] = self.get_fibonacci_number(\n n - 1) + self.get_fibonacci_number(n - 2)\n\n return self.known_cache[n]","def fibonacci(n):\n\tif n == 0:\n\t\treturn 0\n\telif n == 1:\n\t\treturn 1\n\telse:\n\t\treturn fibonacci(n-1) + fibonacci(n-2)","def fibi(n):\n if n == 0: return 0\n if n == 1: return 1\n f_n2, f_n1 = 1, 1\n for i in range(3, n+1):\n f_n2, f_n1 = f_n1, f_n2+f_n1\n return f_n1","def fibo(n):\r\n if n==1:\r\n return 0\r\n elif n==2:\r\n return 1\r\n else:\r\n return fibo(n-1)+fibo(n-2)","def fibonacci(n):\n if n == 0:\n return 0\n elif n == 1:\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)","def fibonacci(n):\n if n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n-2) + fibonacci(n-1)","def fib(i):\n if i < 2: return 1\n return fib(i-1) + fib(i-2)","def fibonacci(n):\n\n if (n == 0):\n return 0\n elif (n == 1):\n return 1\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)","def fibonacci(n):\n print(n)\n if n == 0 or n == 1:\n return 1\n\n return fibonacci(n - 1) + fibonacci(n - 2)","def fibonacci(self, n):\n\n if n == 1:\n return 1\n elif n <= 0:\n return 0\n else:\n return self.fibonacci(n - 1) + self.fibonacci(n - 2)","def fibonacci(n):\n if n == 0:\n return 0\n elif n == 1:\n return 1\n else:\n return (fibonacci(n-1) + fibonacci(n-2))","def fibonacci_numbers():\n print(\"Problem: Fibonacci numbers\")\n\n n = int(input())\n\n result = fib(n)\n print(result)","def fibonacci_iter(n):\n f = []\n for x in range(n + 1):\n if x == 0:\n f.append(x)\n elif x == 1:\n f.append(x)\n else:\n f.append(f[-1] + f[-2])\n return f[-1]","def fibonacci(n):\n fibval = sum_series(n, 0, 1)\n print(fibval)\n return fibval","def fib(index):\n return round((GR**index)/R5)","def fib(n):\n if n in (0, 1): return n\n return fib(n-1) + fib(n-2)","def fibonacci(n):\n if n==0 :\n return 0\n elif n==1:\n return 1\n else:\n return fibonacci(n-1) + fibonacci(n-2)","def fibonacci(n, a = 0, b = 1):\n if n == 0:\n return a\n elif n == 1:\n return b\n else:\n return fibonacci(n - 1, b, a + b)","def fibonacci(n):\n if n <= 1:\n return n \n else:\n return fibonacci(n-1) + fibonacci(n-2)","def fibonacci(n):\n\n if n <= 1:\n return n\n else:\n return (fibonacci(n-1) + fibonacci(n-2))","def fibonacci(n):\n\n if n == 1:\n return 1\n elif n < 1:\n return 0\n else:\n return fibonacci(n-1) + fibonacci(n-2)","def fib_efficient(number: int) -> int:\n if number >= 0:\n return calculate(number)[0]\n return -calculate(-number)[0] if not number % 2 else calculate(-number)[0]","def fibonacci(n):\n sequence = [0, 1]\n for i in range(n + 1):\n value = add(sequence[-2], sequence[-1])\n sequence.append(value)\n return sequence[n]","def fib(n: int) -> int:\n if n == 0: return 0\n if n == 1: return 1\n return fib(n-1) + fib(n-2)","def fib(n):\n if n == 0:\n return 0\n elif n == 1:\n return 1\n else:\n return fib(n - 2) + fib(n - 1)","def fib(n):\n if n == 0: return 0\n if n == 1: return 1\n return fib(n-1) + fib(n-2)","def fibonacci(n):\n if n < 2:\n return n\n return fibonacci(n-1) + fibonacci(n-2)","def fibonacci(n):\n if n < 2:\n return n\n return fibonacci(n-1) + fibonacci(n-2)","def fib(n): \n if n == 0:\n return 0\n elif n == 1:\n return 1\n\n else:\n return fib(n-1) + fib(n-2)","def fibonacci(n):\n if n < 2:\n return n\n return fibonacci(n - 1) + fibonacci(n - 2)","def fibi(n: int) -> int:\n if n == 0:\n return 0\n if n == 1:\n return 1\n f_n2, f_n1 = 1, 1\n for _ in range(3, n+1):\n f_n2, f_n1 = f_n1, f_n2+f_n1\n return f_n1","def fib(n):\n if n == 0:\n return 0\n elif n == 1:\n return 1\n else:\n return fib(n - 1) + fib(n - 2)","def fib_formula(n):\n if n <= 1:\n return n\n else:\n return (fib_formula(n - 1) + fib_formula(n - 2))","def fib(n):\n n = int(n)\n if n <= 1:\n return 1\n\n return fib(n-1) + fib(n-2)","def fib(n): # this line defines the function 'fib' where n is the input value\n i = 0\n j = 1\n n = n - 1\n\n while n >= 0:\n i, j = j, i + j\n n = n - 1\n \n return i","def fib(number: int) -> int:\n return next(islice(generator(number), number, number + 1))","def fib(n: int) -> int:\n if n == 0:\n return 0\n if n == 1:\n return 1\n return fib(n-1) + fib(n-2)","def fibonacci1(n):\n if n in (0, 1):\n return n\n return fibonacci1(n - 2) + fibonacci1(n - 1)","def fib(n):\n if n == 0 or n == 1:\n return n\n else:\n return fib(n-2) + fib(n-1)","def fib(n):\n print(\"fib({})\".format(n))\n if(n <= 2):\n return 1\n else:\n return fib(n-1) + fib(n-2)","def fib(n):\n if n == 1:\n return 1\n else:\n return n + fib(n-1)","def fibonacci0(n):\n assert n == int(n) and n > 0\n if n in [1, 2]:\n return 1\n return fibonacci0(n-1) + fibonacci0(n-2)","def fibonacci0(n):\n assert n == int(n) and n > 0\n if n in [1, 2]:\n return 1\n return fibonacci0(n-1) + fibonacci0(n-2)","def fibonacci(n):\n assert n >= 0 and int(\n n) == n, 'n has to be greater than or equal to 0 and has to be an integer'\n if n in [0, 1]:\n return n\n else:\n return fibonacci(n - 1) + fibonacci(n - 2)","def func(n):\n if n not in fib:\n fib[n] = func(n-1) + func(n-2)\n return fib[n]","def find_fibonacci(x: int) -> bool:\r\n # write your code here\r\n a = 1\r\n b = 1\r\n while True: #Looping sampai ketemu return\r\n if x == 0:\r\n return True\r\n elif b <= x:\r\n if b == x:\r\n return True\r\n else:\r\n temp = b\r\n b = b + a\r\n a = temp\r\n else:\r\n return False","def fibonacci(n):\n\n if n == 1:\n v = 0\n elif n == 2:\n v = 1\n else:\n v = fibonacci(n - 2) + fibonacci(n - 1)\n\n return v","def fib (n):\r\n if n == 0 or n == 1:\r\n return 1\r\n else:\r\n return fib(n-1) + fib(n-2)","def good_fibonacci(n):\n\n if n <= 1:\n return (0,n)\n else:\n (a,b) = good_fibonacci(n-1)\n return (a+b, a)","def _fast_fibonacci(n):\n if n == 0:\n return (0, 1)\n else:\n a, b = _fast_fibonacci(n // 2)\n c = a * (b * 2 - a)\n d = a**2 + b**2\n if n % 2 == 1:\n return (d, c + d)\n else:\n return (c, d)","def fibonacci_n(n):\n sqrt5 = math.sqrt(5)\n phi = (1 + sqrt5) / 2\n psi = (1 - sqrt5) / 2\n return (phi**n - psi**n) // sqrt5","def good_fibonacci(n):\n if n <= 1:\n return (n, 0)\n else:\n (a, b) = good_fibonacci(n-1)\n return (a+b, a)","def fib(n):\n i = 0\n j = 1\n n = n - 1\n\n while n >= 0:\n i, j = j, i + j\n n = n - 1\n return i","def fibonacciN(n):\n previous, current = 1, 1\n k = 2\n while k < n:\n previous, current = current, previous + current\n k += 1\n return current","def fibonacci_iterative(nth_nmb: int) -> int:\n old, new = 0, 1\n if nth_nmb in (0, 1):\n return nth_nmb\n for __ in range(nth_nmb - 1):\n old, new = new, old + new\n return new","def fibonacci():\n yield 0\n element = yield 1\n previous = element\n while element < 1e100:\n current = yield element\n element = previous + current\n if current > 1:\n previous = current\n\n return element","def fib(n):\n if n == 1 or n == 2:\n result = 1\n else:\n result = fib(n-1) + fib(n-2)\n return result","def fibonacci_term(n):\n return int(((1+sqrt(5))**n-(1-sqrt(5))**n)/(2**n*sqrt(5)))","def fib(n):\n if n < 2:\n return n\n else:\n return fib(n-1) + fib(n-2)","def fib(n):\n fib = [0, 1]\n if n > 2:\n for i in range(n):\n fib.append(fib[-1] + fib[-2])\n return fib[n-1]\n else:\n return fib[n-1]","def fibonacci(n: int) -> int:\n if n <= 0:\n raise ValueError(\"The number must be greater than zero.\")\n exit(code=1)\n if n == 1:\n return 0\n elif n == 2:\n return 1\n else:\n return fibonacci(n-1) + fibonacci(n - 2)","def fib(n):\n if n==1 or n==2:\n return 1\n else:\n return fib(n-1)+fib(n-2)","def fib(n):\n a, b = 1, 1\n while n:\n a, b = b, a + b\n n -= 1\n return a","def fibo(n):\n first = 0\n second = 1\n for i in range (1,n+1):\n if (i<=1): \n #begins sequence (terms 0 and 1 do not have two prior terms)\n newVal = i\n else:\n #continues sequence by adding the previous two numbers in the\n #sequence, and updating the variables\n newVal = first + second\n first = second\n second = newVal\n print(i,newVal)","def fibonacci(num):\n sequence = [1, 1]\n for x in range(num-2):\n sequence.append(sequence[x] + sequence[x+1])\n return sequence","def fib (n):\n a,b=0,1\n while b<n:\n\tprint b,\n\ta,b = b,a+b","def fibonacci(number, next_value=1, prev_value=0):\n\n if number == 0:\n return prev_value\n if number == 1:\n return next_value\n\n return fibonacci(number - 1, next_value + prev_value, next_value) # Function is recursive","def fibonacci(x):\n # Type Error\n if type(x) != int:\n raise TypeError(\"x is not a positive integer.\")\n # Value Error\n if x < 0:\n raise ValueError(\"x is not a positive integer.\")\n if x < 3:\n # fibonacci(0) = 0, fibonacci(1) = 1, fibonacci(2) = 1\n return (0, 1, 1)[x]\n else:\n # fibonacci(n) = fibonacci(n-1) + fibonacci(n-2)\n return fibonacci(x - 1) + fibonacci(x - 2)","def fibonacci(n):\n if n < 0:\n raise ValueError(\"n cannot be negative\")\n elif n < 2:\n return n\n else:\n a, b = 0, 1\n for _ in range(n):\n a, b = b, add(a, b)\n return a","def fib(n):\n i = 0\n j = 1\n n = n - 1\n\n while n >= 0:\n i, j = j, i + j\n n = n - 1\n \n return i","def fib(n):\n i = 0\n j = 1\n n = n - 1\n\n while n >= 0:\n i, j = j, i + j\n n = n - 1\n \n return i","def fib(n):\n i = 0\n j = 1\n n = n - 1\n\n while n >= 0:\n i, j = j, i + j\n n = n - 1\n \n return i","def fib(num, fib_0_1=(0, 1)):\n (fib_prev_prev, fib_prev) = fib_0_1 # fib(0), fib(1)\n\n for _ in range(num):\n fib_next, fib_prev = fib_prev, fib_prev_prev + fib_prev\n\n return fib_next","def fib(number):\n if number < 0:\n raise ValueError\n if number in (0, 1):\n return number\n return fib(number - 1) + fib(number - 2)","def fib(k):\n if k == 1:\n return 0\n previous, current = 0, 1 # current is the second Fibonacci number.\n for _ in range(k-2):\n previous, current = current, previous + current\n return current"],"string":"[\n \"def get_fib(position):\\n\\n # Base Case: Positions greater thatn 0 or 1, since Fibonacci for 0 is 0 and\\n # 1 is 1.\\n if position == 0 or position == 1:\\n return position\\n\\n return get_fib(position - 1) + get_fib(position - 2)\",\n \"def next_fib(f):\\n for f in fib:\\n i = fib.index(f)\\n return f+fib[i-1]\",\n \"def find_fib(n):\\n # fibo = 2.078087 * math.log(n) + 1.672276\\n return 0 # fibo\",\n \"def fibonacci(n):\\r\\n\\r\\n if n in past_fib:\\r\\n return past_fib[n]\\r\\n \\r\\n if n == 0 or n == 1:\\r\\n past_fib[n] = 1\\r\\n return 1\\r\\n\\r\\n total = fibonacci(n-1) + fibonacci(n-2)\\r\\n past_fib[n] = total\\r\\n return total\",\n \"def fast_fibonacci(n):\\n return _fast_fibonacci(n)[0]\",\n \"def fib(n): #Describe \\\"n\\\" as a variable in fib sequence\\n while n == 0:\\n return 0 #establish that 0 position is equal to 0\\n if n == 1:\\n return 1\\n else:\\n return fib(n-1) + fib(n-2)\",\n \"def fibonacci(n):\",\n \"def fibi(n):\\n a, b = 0, 1\\n for i in range(n):\\n # fibonacci series is next no. is sum of previous two number.\\n temp = a\\n a = b\\n # now nth fibonacci no. is sum of previous two number.\\n b = temp+b\\n # returning a because a changing each places\\n return a\",\n \"def fib(f1, index):\\n if index == 0:\\n return 0\\n if index == 1:\\n return f1\\n if (f1, index) not in FIBS_CACHE:\\n FIBS_CACHE[f1, index] = fib(f1, index-1) + fib(f1, index-2)\\n return FIBS_CACHE[f1, index]\",\n \"def fib(n:int) -> int:\\n if n<= 2:\\n return 1\\n else:\\n return fibonacci.fib(n-1) + fibonacci.fib(n-2)\",\n \"def nthFibonacci(n):\\n\\n # Run some basic error checking\\n try:\\n n = int(n)\\n except: # if this fails not a number inputed\\n sys.stderr.write('Incorrect data input\\\\n')\\n return None\\n if n < 0:\\n sys.stderr.write('Only positive integers allowed\\\\n')\\n return None\\n \\n # since the error checking slows down the recursion we run it as a seperate function\\n [Fnm,Fn] = fastrecursivefibonacci(n)\\n return Fnm\",\n \"def optimized_fibonacci(f):\\n a = 0\\n b = 1\\n if f < 2:\\n return f\\n else:\\n for i in range(1, f):\\n c = a + b\\n a = b\\n b = c\\n return b\",\n \"def fibonacci(n):\\n if n == 0:\\n return 0\\n elif n == 1:\\n return 1\\n else:\\n nth = fibonacci(n-1) + fibonacci(n-2)\\n return nth\",\n \"def fibo_element(n):\\n f = ()\\n if n < 0:\\n print(\\\"Incorrect number\\\")\\n elif n == 0:\\n return 0\\n elif n == 1:\\n return 1\\n else:\\n return fibo_element(n-1) + fibo_element(n-2)\",\n \"def fibonacci(number: int) -> int:\\n fibs = [0] * (number + 2)\\n fibs[0] = 0\\n fibs[1] = 1\\n for i in range(2, number + 1):\\n fibs[i] = fibs[i - 1] + fibs[i - 2]\\n return fibs[number]\",\n \"def fibonacci_number(n):\\r\\n l = [0, 1] \\r\\n for i in range(n - 1):\\r\\n l = [*l, l[-1] + l[-2]]\\r\\n return l[n - 1]\",\n \"def fibonacci(n):\\n\\n if n == 0:\\n return 0\\n if n == 1:\\n return 1\\n \\n previous = 0\\n current = 1\\n\\n for i in range(n-1):\\n previous, current = current, current + previous\\n\\n return current\",\n \"def fibonacci(n):\\n\\tfib_seq = []\\n\\tnth_term = 0\\n\\t\\n\\tfor i in range(0,n+1):\\n\\t\\tif i == 0:\\n\\t\\t\\tfib_seq.append(0)\\n\\t\\tif i == 1:\\n\\t\\t\\tfib_seq.append(1)\\n\\t\\tif i > 1:\\n\\t\\t\\tnth_term = fib_seq[-1] + fib_seq[-2]\\n\\t\\t\\tfib_seq.append(nth_term)\\n\\t\\n\\tprint(fib_seq)\\n\\tprint(fib_seq[n])\\n\\treturn(fib_seq[n])\",\n \"def fibonacci(a):\\n fib = [1,1]\\n x = 0\\n i = 1\\n while x < a:\\n x = fib [i] + fib[i-1]\\n i += 1\\n fib.append(x)\\n return i, fib\",\n \"def fibonacci(n):\\n if n in (0, 1):\\n return n\\n return fibonacci(n - 2) + fibonacci(n - 1)\",\n \"def fibonacci():\\n return sum_series(a=0, b=1)\",\n \"def fibonacci(n):\\n if n in (0, 1):\\n return n\\n return (fibonacci(n-2) + fibonacci(n-1))\",\n \"def fibonacci(num):\\n if num == 0 or num ==1:\\n return 1\\n return fibonacci(num-1) + fibonacci (num-2)\",\n \"def fibonacci(n):\\n if n in (0,1):\\n return n\\n\\n return (fibonacci(n-2) + fibonacci(n-1))\",\n \"def fibonacci(n: int) -> int:\\n m = 1 << (n.bit_length() - 1)\\n Fn = 0\\n Fnm1 = 1\\n while m:\\n Fn2 = Fn * Fn\\n Fn = 2 * Fnm1 * Fn + Fn2\\n Fnm1 = Fnm1 * Fnm1 + Fn2\\n if n & m:\\n Fnm1, Fn = Fn, Fnm1 + Fn\\n m >>= 1\\n return Fn\",\n \"def fibonacci (n):\\n\\tif n == 0:\\n\\t\\treturn 0\\n\\telif n == 1:\\n\\t\\treturn 1\\n\\telse:\\n\\t\\treturn fibonacci(n-2) + fibonacci(n-1)\",\n \"def get_fibonacci_number(self, n) -> int:\\n\\n if not isinstance(n, int) or n < 0:\\n raise ValueError(\\\"n must be a non-negative integer\\\")\\n\\n if n in self.known_cache:\\n return self.known_cache[n]\\n\\n # Without caching known Fibonacci numbers like this, this function\\n # will generate a \\\"maximum recursion depth exceeded\\\" error\\n # (when for sufficiently large Fibonacci numbers).\\n # That's because Python doesn't do tail recursion elimination.\\n self.known_cache[n] = self.get_fibonacci_number(\\n n - 1) + self.get_fibonacci_number(n - 2)\\n\\n return self.known_cache[n]\",\n \"def fibonacci(n):\\n\\tif n == 0:\\n\\t\\treturn 0\\n\\telif n == 1:\\n\\t\\treturn 1\\n\\telse:\\n\\t\\treturn fibonacci(n-1) + fibonacci(n-2)\",\n \"def fibi(n):\\n if n == 0: return 0\\n if n == 1: return 1\\n f_n2, f_n1 = 1, 1\\n for i in range(3, n+1):\\n f_n2, f_n1 = f_n1, f_n2+f_n1\\n return f_n1\",\n \"def fibo(n):\\r\\n if n==1:\\r\\n return 0\\r\\n elif n==2:\\r\\n return 1\\r\\n else:\\r\\n return fibo(n-1)+fibo(n-2)\",\n \"def fibonacci(n):\\n if n == 0:\\n return 0\\n elif n == 1:\\n return 1\\n else:\\n return fibonacci(n - 1) + fibonacci(n - 2)\",\n \"def fibonacci(n):\\n if n == 1:\\n return 0\\n elif n == 2:\\n return 1\\n else:\\n return fibonacci(n-2) + fibonacci(n-1)\",\n \"def fib(i):\\n if i < 2: return 1\\n return fib(i-1) + fib(i-2)\",\n \"def fibonacci(n):\\n\\n if (n == 0):\\n return 0\\n elif (n == 1):\\n return 1\\n else:\\n return fibonacci(n - 1) + fibonacci(n - 2)\",\n \"def fibonacci(n):\\n print(n)\\n if n == 0 or n == 1:\\n return 1\\n\\n return fibonacci(n - 1) + fibonacci(n - 2)\",\n \"def fibonacci(self, n):\\n\\n if n == 1:\\n return 1\\n elif n <= 0:\\n return 0\\n else:\\n return self.fibonacci(n - 1) + self.fibonacci(n - 2)\",\n \"def fibonacci(n):\\n if n == 0:\\n return 0\\n elif n == 1:\\n return 1\\n else:\\n return (fibonacci(n-1) + fibonacci(n-2))\",\n \"def fibonacci_numbers():\\n print(\\\"Problem: Fibonacci numbers\\\")\\n\\n n = int(input())\\n\\n result = fib(n)\\n print(result)\",\n \"def fibonacci_iter(n):\\n f = []\\n for x in range(n + 1):\\n if x == 0:\\n f.append(x)\\n elif x == 1:\\n f.append(x)\\n else:\\n f.append(f[-1] + f[-2])\\n return f[-1]\",\n \"def fibonacci(n):\\n fibval = sum_series(n, 0, 1)\\n print(fibval)\\n return fibval\",\n \"def fib(index):\\n return round((GR**index)/R5)\",\n \"def fib(n):\\n if n in (0, 1): return n\\n return fib(n-1) + fib(n-2)\",\n \"def fibonacci(n):\\n if n==0 :\\n return 0\\n elif n==1:\\n return 1\\n else:\\n return fibonacci(n-1) + fibonacci(n-2)\",\n \"def fibonacci(n, a = 0, b = 1):\\n if n == 0:\\n return a\\n elif n == 1:\\n return b\\n else:\\n return fibonacci(n - 1, b, a + b)\",\n \"def fibonacci(n):\\n if n <= 1:\\n return n \\n else:\\n return fibonacci(n-1) + fibonacci(n-2)\",\n \"def fibonacci(n):\\n\\n if n <= 1:\\n return n\\n else:\\n return (fibonacci(n-1) + fibonacci(n-2))\",\n \"def fibonacci(n):\\n\\n if n == 1:\\n return 1\\n elif n < 1:\\n return 0\\n else:\\n return fibonacci(n-1) + fibonacci(n-2)\",\n \"def fib_efficient(number: int) -> int:\\n if number >= 0:\\n return calculate(number)[0]\\n return -calculate(-number)[0] if not number % 2 else calculate(-number)[0]\",\n \"def fibonacci(n):\\n sequence = [0, 1]\\n for i in range(n + 1):\\n value = add(sequence[-2], sequence[-1])\\n sequence.append(value)\\n return sequence[n]\",\n \"def fib(n: int) -> int:\\n if n == 0: return 0\\n if n == 1: return 1\\n return fib(n-1) + fib(n-2)\",\n \"def fib(n):\\n if n == 0:\\n return 0\\n elif n == 1:\\n return 1\\n else:\\n return fib(n - 2) + fib(n - 1)\",\n \"def fib(n):\\n if n == 0: return 0\\n if n == 1: return 1\\n return fib(n-1) + fib(n-2)\",\n \"def fibonacci(n):\\n if n < 2:\\n return n\\n return fibonacci(n-1) + fibonacci(n-2)\",\n \"def fibonacci(n):\\n if n < 2:\\n return n\\n return fibonacci(n-1) + fibonacci(n-2)\",\n \"def fib(n): \\n if n == 0:\\n return 0\\n elif n == 1:\\n return 1\\n\\n else:\\n return fib(n-1) + fib(n-2)\",\n \"def fibonacci(n):\\n if n < 2:\\n return n\\n return fibonacci(n - 1) + fibonacci(n - 2)\",\n \"def fibi(n: int) -> int:\\n if n == 0:\\n return 0\\n if n == 1:\\n return 1\\n f_n2, f_n1 = 1, 1\\n for _ in range(3, n+1):\\n f_n2, f_n1 = f_n1, f_n2+f_n1\\n return f_n1\",\n \"def fib(n):\\n if n == 0:\\n return 0\\n elif n == 1:\\n return 1\\n else:\\n return fib(n - 1) + fib(n - 2)\",\n \"def fib_formula(n):\\n if n <= 1:\\n return n\\n else:\\n return (fib_formula(n - 1) + fib_formula(n - 2))\",\n \"def fib(n):\\n n = int(n)\\n if n <= 1:\\n return 1\\n\\n return fib(n-1) + fib(n-2)\",\n \"def fib(n): # this line defines the function 'fib' where n is the input value\\n i = 0\\n j = 1\\n n = n - 1\\n\\n while n >= 0:\\n i, j = j, i + j\\n n = n - 1\\n \\n return i\",\n \"def fib(number: int) -> int:\\n return next(islice(generator(number), number, number + 1))\",\n \"def fib(n: int) -> int:\\n if n == 0:\\n return 0\\n if n == 1:\\n return 1\\n return fib(n-1) + fib(n-2)\",\n \"def fibonacci1(n):\\n if n in (0, 1):\\n return n\\n return fibonacci1(n - 2) + fibonacci1(n - 1)\",\n \"def fib(n):\\n if n == 0 or n == 1:\\n return n\\n else:\\n return fib(n-2) + fib(n-1)\",\n \"def fib(n):\\n print(\\\"fib({})\\\".format(n))\\n if(n <= 2):\\n return 1\\n else:\\n return fib(n-1) + fib(n-2)\",\n \"def fib(n):\\n if n == 1:\\n return 1\\n else:\\n return n + fib(n-1)\",\n \"def fibonacci0(n):\\n assert n == int(n) and n > 0\\n if n in [1, 2]:\\n return 1\\n return fibonacci0(n-1) + fibonacci0(n-2)\",\n \"def fibonacci0(n):\\n assert n == int(n) and n > 0\\n if n in [1, 2]:\\n return 1\\n return fibonacci0(n-1) + fibonacci0(n-2)\",\n \"def fibonacci(n):\\n assert n >= 0 and int(\\n n) == n, 'n has to be greater than or equal to 0 and has to be an integer'\\n if n in [0, 1]:\\n return n\\n else:\\n return fibonacci(n - 1) + fibonacci(n - 2)\",\n \"def func(n):\\n if n not in fib:\\n fib[n] = func(n-1) + func(n-2)\\n return fib[n]\",\n \"def find_fibonacci(x: int) -> bool:\\r\\n # write your code here\\r\\n a = 1\\r\\n b = 1\\r\\n while True: #Looping sampai ketemu return\\r\\n if x == 0:\\r\\n return True\\r\\n elif b <= x:\\r\\n if b == x:\\r\\n return True\\r\\n else:\\r\\n temp = b\\r\\n b = b + a\\r\\n a = temp\\r\\n else:\\r\\n return False\",\n \"def fibonacci(n):\\n\\n if n == 1:\\n v = 0\\n elif n == 2:\\n v = 1\\n else:\\n v = fibonacci(n - 2) + fibonacci(n - 1)\\n\\n return v\",\n \"def fib (n):\\r\\n if n == 0 or n == 1:\\r\\n return 1\\r\\n else:\\r\\n return fib(n-1) + fib(n-2)\",\n \"def good_fibonacci(n):\\n\\n if n <= 1:\\n return (0,n)\\n else:\\n (a,b) = good_fibonacci(n-1)\\n return (a+b, a)\",\n \"def _fast_fibonacci(n):\\n if n == 0:\\n return (0, 1)\\n else:\\n a, b = _fast_fibonacci(n // 2)\\n c = a * (b * 2 - a)\\n d = a**2 + b**2\\n if n % 2 == 1:\\n return (d, c + d)\\n else:\\n return (c, d)\",\n \"def fibonacci_n(n):\\n sqrt5 = math.sqrt(5)\\n phi = (1 + sqrt5) / 2\\n psi = (1 - sqrt5) / 2\\n return (phi**n - psi**n) // sqrt5\",\n \"def good_fibonacci(n):\\n if n <= 1:\\n return (n, 0)\\n else:\\n (a, b) = good_fibonacci(n-1)\\n return (a+b, a)\",\n \"def fib(n):\\n i = 0\\n j = 1\\n n = n - 1\\n\\n while n >= 0:\\n i, j = j, i + j\\n n = n - 1\\n return i\",\n \"def fibonacciN(n):\\n previous, current = 1, 1\\n k = 2\\n while k < n:\\n previous, current = current, previous + current\\n k += 1\\n return current\",\n \"def fibonacci_iterative(nth_nmb: int) -> int:\\n old, new = 0, 1\\n if nth_nmb in (0, 1):\\n return nth_nmb\\n for __ in range(nth_nmb - 1):\\n old, new = new, old + new\\n return new\",\n \"def fibonacci():\\n yield 0\\n element = yield 1\\n previous = element\\n while element < 1e100:\\n current = yield element\\n element = previous + current\\n if current > 1:\\n previous = current\\n\\n return element\",\n \"def fib(n):\\n if n == 1 or n == 2:\\n result = 1\\n else:\\n result = fib(n-1) + fib(n-2)\\n return result\",\n \"def fibonacci_term(n):\\n return int(((1+sqrt(5))**n-(1-sqrt(5))**n)/(2**n*sqrt(5)))\",\n \"def fib(n):\\n if n < 2:\\n return n\\n else:\\n return fib(n-1) + fib(n-2)\",\n \"def fib(n):\\n fib = [0, 1]\\n if n > 2:\\n for i in range(n):\\n fib.append(fib[-1] + fib[-2])\\n return fib[n-1]\\n else:\\n return fib[n-1]\",\n \"def fibonacci(n: int) -> int:\\n if n <= 0:\\n raise ValueError(\\\"The number must be greater than zero.\\\")\\n exit(code=1)\\n if n == 1:\\n return 0\\n elif n == 2:\\n return 1\\n else:\\n return fibonacci(n-1) + fibonacci(n - 2)\",\n \"def fib(n):\\n if n==1 or n==2:\\n return 1\\n else:\\n return fib(n-1)+fib(n-2)\",\n \"def fib(n):\\n a, b = 1, 1\\n while n:\\n a, b = b, a + b\\n n -= 1\\n return a\",\n \"def fibo(n):\\n first = 0\\n second = 1\\n for i in range (1,n+1):\\n if (i<=1): \\n #begins sequence (terms 0 and 1 do not have two prior terms)\\n newVal = i\\n else:\\n #continues sequence by adding the previous two numbers in the\\n #sequence, and updating the variables\\n newVal = first + second\\n first = second\\n second = newVal\\n print(i,newVal)\",\n \"def fibonacci(num):\\n sequence = [1, 1]\\n for x in range(num-2):\\n sequence.append(sequence[x] + sequence[x+1])\\n return sequence\",\n \"def fib (n):\\n a,b=0,1\\n while b<n:\\n\\tprint b,\\n\\ta,b = b,a+b\",\n \"def fibonacci(number, next_value=1, prev_value=0):\\n\\n if number == 0:\\n return prev_value\\n if number == 1:\\n return next_value\\n\\n return fibonacci(number - 1, next_value + prev_value, next_value) # Function is recursive\",\n \"def fibonacci(x):\\n # Type Error\\n if type(x) != int:\\n raise TypeError(\\\"x is not a positive integer.\\\")\\n # Value Error\\n if x < 0:\\n raise ValueError(\\\"x is not a positive integer.\\\")\\n if x < 3:\\n # fibonacci(0) = 0, fibonacci(1) = 1, fibonacci(2) = 1\\n return (0, 1, 1)[x]\\n else:\\n # fibonacci(n) = fibonacci(n-1) + fibonacci(n-2)\\n return fibonacci(x - 1) + fibonacci(x - 2)\",\n \"def fibonacci(n):\\n if n < 0:\\n raise ValueError(\\\"n cannot be negative\\\")\\n elif n < 2:\\n return n\\n else:\\n a, b = 0, 1\\n for _ in range(n):\\n a, b = b, add(a, b)\\n return a\",\n \"def fib(n):\\n i = 0\\n j = 1\\n n = n - 1\\n\\n while n >= 0:\\n i, j = j, i + j\\n n = n - 1\\n \\n return i\",\n \"def fib(n):\\n i = 0\\n j = 1\\n n = n - 1\\n\\n while n >= 0:\\n i, j = j, i + j\\n n = n - 1\\n \\n return i\",\n \"def fib(n):\\n i = 0\\n j = 1\\n n = n - 1\\n\\n while n >= 0:\\n i, j = j, i + j\\n n = n - 1\\n \\n return i\",\n \"def fib(num, fib_0_1=(0, 1)):\\n (fib_prev_prev, fib_prev) = fib_0_1 # fib(0), fib(1)\\n\\n for _ in range(num):\\n fib_next, fib_prev = fib_prev, fib_prev_prev + fib_prev\\n\\n return fib_next\",\n \"def fib(number):\\n if number < 0:\\n raise ValueError\\n if number in (0, 1):\\n return number\\n return fib(number - 1) + fib(number - 2)\",\n \"def fib(k):\\n if k == 1:\\n return 0\\n previous, current = 0, 1 # current is the second Fibonacci number.\\n for _ in range(k-2):\\n previous, current = current, previous + current\\n return current\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.84752756","0.7775988","0.7635731","0.75487685","0.75380415","0.7457801","0.7436363","0.7384562","0.7375154","0.73195016","0.7316325","0.7299088","0.7251135","0.7249416","0.7244615","0.71986157","0.7195691","0.7191518","0.71824896","0.7170513","0.7158625","0.7150435","0.7150051","0.7114091","0.7098507","0.70980316","0.7097658","0.7096846","0.70945925","0.7091264","0.7080944","0.7077899","0.70686054","0.70596945","0.705924","0.7053862","0.70522696","0.70514876","0.7048612","0.70468444","0.704529","0.7032698","0.7030821","0.70286304","0.70285195","0.7014394","0.70143884","0.7013193","0.70126295","0.700465","0.69943815","0.6987821","0.697496","0.697496","0.69703597","0.6967301","0.6953528","0.69518644","0.6947235","0.6942693","0.6942017","0.69415617","0.6936781","0.69281495","0.69279987","0.692736","0.69158816","0.69147265","0.69113666","0.6905424","0.6898718","0.6896723","0.68900913","0.68857247","0.68658054","0.6863881","0.68626606","0.6862456","0.68495303","0.68431526","0.6838933","0.68355745","0.68341094","0.6834074","0.68291044","0.68206364","0.6819428","0.68176186","0.6811422","0.6795806","0.6793584","0.67922944","0.67902684","0.6778187","0.6775513","0.67743564","0.67743564","0.67743564","0.67720383","0.6748295","0.6747799"],"string":"[\n \"0.84752756\",\n \"0.7775988\",\n \"0.7635731\",\n \"0.75487685\",\n \"0.75380415\",\n \"0.7457801\",\n \"0.7436363\",\n \"0.7384562\",\n \"0.7375154\",\n \"0.73195016\",\n \"0.7316325\",\n \"0.7299088\",\n \"0.7251135\",\n \"0.7249416\",\n \"0.7244615\",\n \"0.71986157\",\n \"0.7195691\",\n \"0.7191518\",\n \"0.71824896\",\n \"0.7170513\",\n \"0.7158625\",\n \"0.7150435\",\n \"0.7150051\",\n \"0.7114091\",\n \"0.7098507\",\n \"0.70980316\",\n \"0.7097658\",\n \"0.7096846\",\n \"0.70945925\",\n \"0.7091264\",\n \"0.7080944\",\n \"0.7077899\",\n \"0.70686054\",\n \"0.70596945\",\n \"0.705924\",\n \"0.7053862\",\n \"0.70522696\",\n \"0.70514876\",\n \"0.7048612\",\n \"0.70468444\",\n \"0.704529\",\n \"0.7032698\",\n \"0.7030821\",\n \"0.70286304\",\n \"0.70285195\",\n \"0.7014394\",\n \"0.70143884\",\n \"0.7013193\",\n \"0.70126295\",\n \"0.700465\",\n \"0.69943815\",\n \"0.6987821\",\n \"0.697496\",\n \"0.697496\",\n \"0.69703597\",\n \"0.6967301\",\n \"0.6953528\",\n \"0.69518644\",\n \"0.6947235\",\n \"0.6942693\",\n \"0.6942017\",\n \"0.69415617\",\n \"0.6936781\",\n \"0.69281495\",\n \"0.69279987\",\n \"0.692736\",\n \"0.69158816\",\n \"0.69147265\",\n \"0.69113666\",\n \"0.6905424\",\n \"0.6898718\",\n \"0.6896723\",\n \"0.68900913\",\n \"0.68857247\",\n \"0.68658054\",\n \"0.6863881\",\n \"0.68626606\",\n \"0.6862456\",\n \"0.68495303\",\n \"0.68431526\",\n \"0.6838933\",\n \"0.68355745\",\n \"0.68341094\",\n \"0.6834074\",\n \"0.68291044\",\n \"0.68206364\",\n \"0.6819428\",\n \"0.68176186\",\n \"0.6811422\",\n \"0.6795806\",\n \"0.6793584\",\n \"0.67922944\",\n \"0.67902684\",\n \"0.6778187\",\n \"0.6775513\",\n \"0.67743564\",\n \"0.67743564\",\n \"0.67743564\",\n \"0.67720383\",\n \"0.6748295\",\n \"0.6747799\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":81786,"cells":{"query":{"kind":"string","value":"Get file names from config or user input Also get specified framerate, or default is 10 Hz Open file stream"},"document":{"kind":"string","value":"def setup(self):\n print(\"Looking for \", self.filename)\n if os.path.exists(self.filename):\n n, ext = os.path.splitext(self.filename)[:2]\n if ext == \".h5\" or ext == \".hdf5\":\n with h5py.File(self.filename, \"r\") as file:\n keys = list(file.keys())\n self.data = file[keys[0]].value\n print(\"Behavior Data length is \", self.data.shape[2])\n\n else:\n raise FileNotFoundError"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def read_data_samples(fp):\n if(path.isdir(fp)):\n fps = glob.glob(fp + '\\\\*.txt')\n return list(map(lambda x: read_file(x), fps))","def get_file_list(mixer_file, select_random, use_list_of_files):\n logger = logging.getLogger(get_file_list.__name__)\n files = list()\n\n if use_list_of_files:\n with open(mixer_file, 'r') as list_file:\n for line in list_file:\n files.append(os.path.join('data/raw',line.strip()))\n\n if select_random:\n random.shuffle(files)\n\n else:\n\n mixer = parse_mixer_file(mixer_file)\n\n for m in mixer:\n path = os.path.join(project_dir, m[0])\n all_mixer_files = [os.path.join(path,f) for f in os.listdir(path) \n if os.path.isfile(os.path.join(path, f)) and f.split('.')[-1] == 'csv']\n\n current_files = list()\n # Check if the number of samples is limited\n if m[2] >= 0:\n sample_count = 0\n for f in all_mixer_files:\n # Get number of lines without the header line\n num_lines = sum(1 for line in open(f)) - 1\n\n if (sample_count + num_lines) > m[2]:\n current_files.append((f, m[2] - sample_count))\n sample_count += (m[2] - sample_count)\n break\n else:\n current_files.append((f, -1))\n sample_count += num_lines\n\n if sample_count < m[2]:\n logger.warn('Not enough samples ({} < {}): {}'.format(sample_count, m[2], m[0]))\n else:\n # No limit, take all samples in the files\n current_files = zip(all_mixer_files, [-1]*len(all_mixer_files))\n\n if m[1] < 0:\n # -1 means all .csv files\n files += current_files\n elif m[1] > 0:\n if m[1] > len(current_files):\n logger.warn('Not enough files ({} < {}): {}'.format(len(current_files),\n m[1], m[0]))\n files += current_files[:m[1]]\n\n if select_random:\n random.shuffle(files)\n else:\n files = sorted(files, key=lambda x: int(os.path.basename(x[0]).split('_')[-1].split('.')[0]))\n\n return files","def main(_):\n print('argument to expand', ARGS.video_in)\n print('argument expanded', glob.glob(ARGS.video_in))\n video_count = 0\n for video_filename in glob.glob(ARGS.video_in):\n print('start parsing', video_filename)\n data = skvideo.io.ffprobe(video_filename)['video']\n rate_str = six.ensure_str(data['@r_frame_rate']).split('/')\n rate = float(rate_str[0]) / float(rate_str[1])\n print('detected frame rate:', rate)\n\n print('load frames:')\n video = skvideo.io.vreader(video_filename)\n frame_count = 0\n file_count = 0\n for frame in video:\n if (frame_count > ARGS.offset) and \\\n ((frame_count-ARGS.offset)%ARGS.skip == 0) and \\\n (frame_count/rate >= ARGS.from_s) and \\\n (frame_count/rate <= ARGS.to_s or ARGS.to_s == -1):\n print(frame_count,)\n img = Image.fromarray(frame)\n if ARGS.crop:\n img = crop(img, ARGS.size)\n # save file\n file_number = file_count + video_count * ARGS.multiple + ARGS.start\n if ARGS.format_ext.lower() == 'jpg':\n file_out = os.path.join(ARGS.path_out,\n 'f{:07d}.jpg'.format(file_number))\n img.save(file_out, 'JPEG')\n elif ARGS.format_ext.lower() == 'png':\n file_out = os.path.join(ARGS.path_out,\n 'f{:07d}.png'.format(file_number))\n img.save(file_out, 'PNG')\n else:\n print('unrecognize format', ARGS.format_ext)\n sys.exit()\n file_count += 1\n frame_count += 1\n video_count += 1","def get_file_bpm(path, params = {}):\n try:\n win_s = params['win_s']\n samplerate = params['samplerate']\n hop_s = params['hop_s']\n except:\n \"\"\"\n # super fast\n samplerate, win_s, hop_s = 4000, 128, 64 \n # fast\n samplerate, win_s, hop_s = 8000, 512, 128\n \"\"\"\n # default:\n samplerate, win_s, hop_s = 44100, 1024, 512\n\n s = source(path, samplerate, hop_s)\n samplerate = s.samplerate\n o = tempo(\"specdiff\", win_s, hop_s, samplerate)\n # List of beats, in samples\n beats = []\n # Total number of frames read\n total_frames = 0\n\n while True:\n samples, read = s()\n is_beat = o(samples)\n if is_beat:\n this_beat = o.get_last_s()\n beats.append(this_beat)\n #if o.get_confidence() > .2 and len(beats) > 2.:\n # break\n total_frames += read\n if read < hop_s:\n break\n\n # Convert to periods and to bpm \n bpms = 60./diff(beats)\n b = median(bpms)\n return b","def read(ftype, inDir, inSuffix, startTime, endTime):\n\n\tif ftype == 'ryan': return readRyan(inDir, inSuffix, startTime, endTime)\t\n\telif ftype == 'segmotion': return readSegmotion(inDir, inSuffix, startTime, endTime)\n\telif ftype == 'probsevere': return readProbSevere(inDir, inSuffix, startTime, endTime)","def seqIo_frImgs(fName, header=[], aviName=[], Is=[], sDir=[], name='I', ndig=5, f0=0, f1=1e6):\n \n if aviName!=[]: #avi movie exists\n vc = cv2.VideoCapture(aviName)\n if vc.isOpened(): rval = True\n else:\n rval = False\n print('video not readable')\n return\n fps = vc.get(cv2.cv.CV_CAP_PROP_FPS)\n NUM_FRAMES = int(vc.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT))\n print(NUM_FRAMES)\n IM_TOP_H = vc.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)\n IM_TOP_W = vc.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)\n header['width']=IM_TOP_W\n header['height']=IM_TOP_H\n header['fps']=fps\n\n sw = seqIo_writer(fName,header)\n print('creating seq from AVI')\n # initialize timer\n timer = pb.ProgressBar(widgets=['Converting ', pb.Percentage(), ' -- ',\n pb.FormatLabel('Frame %(value)d'), '/',\n pb.FormatLabel('%(max)d'), ' [', pb.Timer(), '] ',\n pb.Bar(), ' (', pb.ETA(), ') '], maxval=NUM_FRAMES)\n for f in range(NUM_FRAMES):\n rval, im = vc.read()\n if rval:\n im= im.astype(np.uint8)\n sw.addFrame(im)\n timer.update(f)\n sw.close()\n timer.finish()\n elif Is==[]:\n assert(os.path.isdir(sDir))\n sw = seqIo_writer(fName,header)\n frmstr = '%s/%s%%0%ii.%s' % (sDir,name,ndig,header.ext)\n for frame in range(f0,f1):\n f = frmstr % frame\n if not os.path.isfile(f):break\n fid = open(f, 'r')\n if fid<0: sw.close(); assert(False)\n I = fid.read()\n fid.close()\n b = bytearray(I)\n assert (b[0] == 255 and b[1] == 216 and b[-2] == 255 and b[-1] == 217); # JPG\n I = np.array(list(b)).astype(np.uint8)\n sw.addFrame(I,0,0)\n sw.close()\n if frame==f0: print('No images found')\n else:\n nd = len(Is.shape)\n if nd==2: nd=3\n assert(nd<=4)\n nFrm = Is.shape[nd-1]\n header['height']=Is.shape[0]\n header['width']=Is.shape[1]\n sw =seqIo_writer(fName,header)\n if nd==3:\n for f in range(nFrm): sw.addFrame(Is[:,:,f])\n if nd==4:\n for f in range(nFrm): sw.addFrame(Is[:,:,:,f])\n sw.close()","def videoFrames(filename, framerate=1):\n vid_file = os.path.join(os.path.dirname(os.getcwd()), \"Database\", \"Video\", filename)\n print(vid_file)\n assert os.path.isfile(vid_file), \"Given path is not a valid file\"\n tmpdir = os.path.join(os.getcwd(), \"tmp\")\n subprocess.run(\n [\n \"ffmpeg\",\n \"-i\",\n vid_file,\n \"-r\",\n f\"{framerate}\",\n os.path.join(tmpdir, \"img_%04d.jpg\"),\n ]\n )\n return [os.path.join(tmpdir, i) for i in os.listdir(tmpdir) if not i.endswith(\".wav\")]","def get_filenames(b,X,timefac,BW):\r\n\tn = int(200000*X*timefac); nn = int(200000*X*10)\r\n\troot = \"./dat_LE_stream/\"\r\n\trootL = 'C:/AsusWebStorage/MySyncData/TRAFILES/'\r\n\tpodir = \"/b=\"+str(b)+\"/\" if BW else \"/HO/\"\r\n\t\r\n\ttrafile = rootL+\"TRA_BW_b\"+str(b)+\"X\"+str(int(X))+\"n\"+str(nn)+\"seed65438\"\r\n\tif not os.path.isfile(trafile):\r\n\t\ttrafile = rootL+\"TRA_BW_b\"+str(b)+\"X\"+str(int(X))+\"n\"+str(n)+\"seed65438\"\r\n\toutfile = root+podir+os.path.split(trafile)[1][4:]\r\n\t\r\n\trndfile = os.path.split(outfile)[0]+\"/RND_\"+os.path.split(outfile)[1]+\".png\"\r\n\tpdffile = os.path.split(outfile)[0]+\"/PDF_\"+os.path.split(outfile)[1]\r\n\tstrfile = os.path.split(outfile)[0]+\"/STR_\"+os.path.split(outfile)[1]\r\n\t\r\n\treturn trafile,rndfile,pdffile,strfile,n","def gen_fps():\n global data_src ,output_dir \n logger = TaskFileLogger(\"GenFP\")\n\n h_vars = load_hydro_var()\n if not os.path.exists(output_dir):\n os.mkdir(output_dir)\n\n for h_type,var_d in h_vars.items():\n print \"considering %s\" %h_type\n\n t_output_dir = os.path.join(output_dir,h_type)\n if not os.path.exists(t_output_dir):\n print \"creating path %s\" %t_output_dir\n os.mkdir(t_output_dir)\n logger.log(\"%s started\" %(h_type))\n\n for fname in glob.glob(data_src):\n complex_id = os.path.basename(fname).split('.')[0] \n fp_path = os.path.join(t_output_dir,complex_id + \".fp\" )\n if os.path.exists(fp_path):\n #print \"%s processed\" %complex_id\n continue\n print \"processing %s,fp saved as %s\" %(fname , fp_path )\n c = Complex(fname,hydro_dict = var_d)\n c.get_fp()\n c.write_fp_to_file(fp_path)\n\n logger.log(\"%s finished\" %(h_type))","def return_file_read(_):\n return [\"scorevideo LOG\", \"File: log.mat\"]","def __init__(self, inFile = None, inData = None, inRate = None):\n \n # Information about FFMPEG\n self.ffmpeg_info = FFMPEG_info()\n \n if inData is not None:\n if inRate is None:\n print('Set the \"rate\" to the default value (8012 Hz).')\n rate = 8012.0\n self.generate_sound(inData, inRate)\n else: \n if inFile is None:\n inFile = self._selectInput()\n if inFile == 0:\n return\n try:\n self.source = inFile\n self.read_sound(self.source)\n except FileNotFoundError as err:\n print(err)\n inFile = self._selectInput()\n self.source = inFile\n self.read_sound(self.source)","def generate_readers(\n viddir, camname, minopt=0, maxopt=300000, pathonly=False, extension=\".mp4\"\n):\n out = {}\n mp4files = [\n os.path.join(camname, f)\n for f in os.listdir(os.path.join(viddir, camname))\n if extension in f\n and int(f.rsplit(extension)[0]) <= maxopt\n and int(f.rsplit(extension)[0]) >= minopt\n ]\n\n # This is a trick (that should work) for getting rid of\n # awkward sub-directory folder names when they are being used\n mp4files_scrub = [\n os.path.join(\n os.path.normpath(f).split(os.sep)[0], os.path.normpath(f).split(os.sep)[-1]\n )\n for f in mp4files\n ]\n\n pixelformat = \"yuv420p\"\n input_params = []\n output_params = []\n\n for i in range(len(mp4files)):\n if pathonly:\n out[mp4files_scrub[i]] = os.path.join(viddir, mp4files[i])\n else:\n print(\n \"NOTE: Ignoring {} files numbered above {}\".format(extensions, maxopt)\n )\n out[mp4files_scrub[i]] = imageio.get_reader(\n os.path.join(viddir, mp4files[i]),\n pixelformat=pixelformat,\n input_params=input_params,\n output_params=output_params,\n )\n\n return out","def framerate(self):\n return self.config.get('framerate', 15)","def OpenSoundFiles():\n\n wildcard = create_wildcard(\"Sound files\", sppas.src.audiodata.aio.extensionsul)\n wildcard += '|' + create_wildcard(\"All files\", ['*', '*.*'])\n\n files = list()\n dlg = wx.FileDialog(None, \n \"Select sound file(s)\", \n paths.samples, \n \"\", \n wildcard, \n wx.FD_OPEN | wx.MULTIPLE | wx.FD_CHANGE_DIR)\n if dlg.ShowModal() == wx.ID_OK:\n files = dlg.GetPaths()\n\n dlg.Destroy()\n\n return files","def _settings(filename):\n\n with open(filename, 'r') as datafile:\n daq_type = datafile.readline().strip().split(',')[1]\n sample_hz = int(datafile.readline().strip().split(',')[1])\n channels = datafile.readline().strip().split(',')\n return (daq_type, sample_hz, channels)","def read_local_20Hz_files(**kwargs):\n pathlst = kwargs.get('pathlst')\n product = kwargs.get('product')\n varalias = kwargs.get('varalias')\n sdate = kwargs.get('sdate')\n edate = kwargs.get('edate')\n twin = kwargs.get('twin')\n\n # establish coords if defined in config file\n timestr = satellite_dict[product]['vardef']['time']\n lonstr = satellite_dict[product]['vardef']['lons']\n latstr = satellite_dict[product]['vardef']['lats']\n\n # adjust start and end\n sdate = sdate - timedelta(minutes=twin)\n edate = edate + timedelta(minutes=twin)\n # get meta data\n ncmeta = ncdumpMeta(pathlst[0])\n ncvar = get_filevarname(varalias, variable_info,\n satellite_dict[product], ncmeta)\n # retrieve sliced data\n ds = read_netcdfs(pathlst)\n ds_sort = ds.sortby(timestr)\n\n # get indices for included time period\n nptime = ds_sort[timestr].data\n print('here0')\n print(len(nptime))\n #dtime = [parse_date(str(nptime[i])) for i in range(len(nptime))]\n print('here1')\n #idx = find_included_times_pd(dtime, sdate=sdate, edate=edate)\n idx = find_included_times_pd(nptime, sdate=sdate, edate=edate)\n print(len(nptime[idx]))\n print('here2')\n dtime = [parse_date(str(nptime[idx][i])) for i in range(len(nptime[idx]))]\n print(dtime)\n print('here3')\n #dtime = list(np.array(dtime)[idx])\n lons = list(((ds_sort[lonstr].data[idx] - 180) % 360) - 180)\n lats = list(ds_sort[latstr].data[idx])\n\n unxt = (nptime[idx].astype(int) / 10**9)\n\n # make dict and start with stdvarname for varalias\n stdvarname = variable_info[varalias]['standard_name']\n vardict = {}\n vardict[stdvarname] = list(ds_sort[ncvar].data[idx])\n vardict['longitude'] = lons\n vardict['latitude'] = lats\n vardict['time'] = unxt\n vardict['datetime'] = dtime\n vardict['time_unit'] = variable_info['time']['units']\n print(vardict.keys())\n return vardict","def readNextGenSpectrum(fname=''):\n\n print('Reading : ', fname)\n\n with open(fname, 'r') as rfile:\n dum = rfile.readline()\n sdum = dum.split()\n teff = float(sdum[0])\n logg = float(sdum[1])\n mph = float(sdum[2])\n dum = rfile.readline()\n nwav = float(dum.split()[0])\n\n bigline = []\n dum = rfile.readline()\n while dum.strip() != '':\n sdum = dum.split()\n for i in range(len(sdum)):\n bigline.append(float(sdum[i]))\n dum = rfile.readline()\n\n bigline = np.array(bigline)\n # Convert wavelength from angstrom to micron\n wav = bigline[:nwav] / 1e4\n inu = bigline[nwav:2 * nwav]\n bnu = bigline[nwav * 2:nwav * 3]\n\n ii = wav.argsort()\n wav = wav[ii]\n inu = inu[ii] * 1e-8 * wav * 1e4 / np.pi / (29979245800.0 / wav * 1e4)\n bnu = bnu[ii] * 1e-8 * wav * 1e4 / np.pi / (29979245800.0 / wav * 1e4)\n\n #\n # The unit is now erg/s/cm/Hz/ster\n #\n\n return {'teff': teff, 'logg': logg, 'mph': mph, 'nwav': nwav, 'wav': wav, 'inu': inu, 'bnu': bnu}","def file_info(file_name, file_pattern):\n match = re.compile(file_pattern).match(file_name)\n if match:\n basepath = match.group('basepath')\n sensor = match.group('sensor')\n ax = match.group('ax')\n freq = match.group('freq')\n date = match.group('date')\n return basepath, sensor, ax, freq, date\n else:\n return None # there is no file extension to file_name","def do_f(self, parms):\n\t\tprint self.files","def _read_config_file(self):\n wcec = 0\n deadline = 0\n jitter = 0\n init_freq = 0\n freqs_volt = {}\n freqs = []\n volts = []\n config_file_name = self._find_file('sim_simple.config')\n with open(config_file_name, 'rU') as f:\n lines = f.readlines()\n try:\n for freq in lines[0].split():\n freqs.append(float(freq))\n\n for volt in lines[1].split():\n volts.append(float(volt))\n\n for i in range(0, len(freqs)):\n freqs_volt[freqs[i]] = volts[i]\n\n data = lines[2].split()\n wcec = float(data[0])\n deadline = float(data[1])\n period = float(data[2])\n jitter = float(data[3])\n init_freq = float(data[4])\n except ValueError, IndexError:\n print 'Invalid data in config file'\n sys.exit(1)\n\n return wcec, deadline, period, jitter, init_freq, freqs_volt","def readPlayerImageFiles(self):\n currentPath = os.path.dirname(os.path.abspath(__file__))\n listOfFileNames=[]\n for i in os.listdir(currentPath):\n if re.match(\"player\\_\\d+\",i): #i.endswith(\".gif\")\n listOfFileNames.append(currentPath+'/'+i)\n return listOfFileNames","def fillFileList(self, dirName):\n if not os.path.isdir(dirName):\n print(\"Warning: directory doesn't exist\")\n return\n\n self.listFiles.fill(dirName, fileName=None, readFmt=True, addWavNum=True, recursive=True)\n\n # while reading the file, we also collected a list of species present there\n spList = list(self.listFiles.spList)\n # and sample rate info\n fs = list(self.listFiles.fsList)\n\n if len(fs)==0:\n print(\"Warning: no suitable files found\")\n return\n\n # might need better limits on selectable sample rate here\n self.fs.setValue(int(np.min(fs)))\n self.fs.setRange(4000, int(np.max(fs)))\n self.fs.setSingleStep(4000)\n self.fs.setTickInterval(4000)\n\n spList.insert(0, 'Choose species...')\n self.species.clear()\n self.species.addItems(spList)\n if len(spList)==2:\n self.species.setCurrentIndex(1)","def _open_stream(config):\n p = pyaudio.PyAudio()\n stream = p.open(\n format = config[\"format\"],\n channels = config[\"channels\"],\n rate = config[\"rate\"],\n input = True,\n frames_per_buffer = config[\"chunk\"]\n )\n return p, stream","def filesample(filename):\n sampling_rate, samples = wavfile.read(filename)\n times = np.arange(len(samples)) / sampling_rate\n return samples, sampling_rate","def get_frame_rate(filename):\n cmd = ('ffprobe -v 0 -of flat=s=_ -select_streams v:0 -show_entries '\n 'stream=avg_frame_rate -of default=nokey=1:noprint_wrappers=1 ' +\n filename).split()\n pid = subprocess.run(cmd, stdout=subprocess.PIPE,\n universal_newlines=True)\n if pid.returncode != 0:\n return None\n\n frame_rate_exp = pid.stdout.rstrip()\n try:\n frame_rate = float(frame_rate_exp)\n except:\n if frame_rate_exp == 'N/A':\n frame_rate = 0.\n else:\n numerator, denominator = map(float, frame_rate_exp.split('/'))\n if denominator == 0:\n frame_rate = 0\n else:\n frame_rate = numerator / denominator\n return frame_rate","def find_files(config, slot='*'):\n f_pattern = os.path.join(os.path.join(config['path'],config['led_name']), slot+'*' + config['led_name'] + '*'\n + config['current'] + '*' + config['exp_time'] + '*'\n + config['xpos'] + '*' + config['ypos'] + '*')\n print(f_pattern)\n return glob.glob(f_pattern)","def files_sim(config):\n file_sim = sorted(glob.glob(config['str_dir'] + '/simulation/' +\n '{}/{}nm/txt_files/*.txt'.format(\n config['date'], config['wavelength'])))\n return file_sim","def get_frame_by_frame(name=None, fps=4, write_to_disk=False, display_feed=False, on_capture=None):\n\n reset_camera()\n\n if name is None:\n name = \"fbf_\" + str(int(time()))\n \n dname = None\n if write_to_disk:\n chdir(cwd)\n dname = join(dirname(realpath(sys.argv[0])), \"train\", \"data\", name)\n if not exists(dname):\n print(\"Created dir: %s\" % dname)\n mkdir(dname)\n else:\n print(\"Using dir: %s\" % dname)\n else:\n print('Not writing to disk')\n\n def _snap(name, dname, write, display, capture_callback):\n global camera\n s, img = camera.read()\n\n if s and capture_callback:\n img = capture_callback(img)\n\n if s and display:\n cv2.imshow(name, img)\n cv2.waitKey(1) \n\n if write:\n chdir(dname)\n number_of_files = len([item for item in os.listdir(dname) if os.path.isfile(os.path.join(dname, item))])\n path = \"./\" + str(number_of_files + 1) + \".png\"\n if s:\n imwrite(path, img)\n print(\"Saved to \" + dname + \"/\" + str(number_of_files + 1) + \".png\")\n else:\n print(\"Could not read image %d from camera\" % (number_of_files + 1))\n chdir(cwd)\n\n return Timer(1 / fps, _snap, name, dname, write_to_disk, display_feed, on_capture).use_mp()","def read_xyz(filename, freq):\n\n\n#xyz file\n\n Atoms = []\n Coordinates = []\n\n xyz = open(filename)\n frame = 0\n while True:\n\n n_atoms = xyz.readline()\n\n if n_atoms == '':\n break\n else:\n n_atoms = int(n_atoms)\n title = xyz.readline()\n\n if frame%freq==0:\n atoms, coordinates = read_frame(xyz, n_atoms)\n Coordinates.append(coordinates)\n Atoms.append(atoms)\n\n else:\n read_frame(xyz, n_atoms)\n frame+=1\n\n return Atoms, Coordinates","def readAudioFile(path):\n\n extension = os.path.splitext(path)[1]\n\n try:\n # Commented below, as we don't need this\n # #if extension.lower() == '.wav':\n # #[Fs, x] = wavfile.read(path)\n # if extension.lower() == '.aif' or extension.lower() == '.aiff':\n # s = aifc.open(path, 'r')\n # nframes = s.getnframes()\n # strsig = s.readframes(nframes)\n # x = numpy.fromstring(strsig, numpy.short).byteswap()\n # Fs = s.getframerate()\n if extension.lower() == '.mp3' or extension.lower() == '.wav' or extension.lower() == '.au' or extension.lower() == '.ogg':\n try:\n audiofile = AudioSegment.from_file(path)\n except:\n print(\"Error: file not found or other I/O error. \"\n \"(DECODING FAILED)\")\n return -1 ,-1\n\n if audiofile.sample_width == 2:\n data = numpy.fromstring(audiofile._data, numpy.int16)\n elif audiofile.sample_width == 4:\n data = numpy.fromstring(audiofile._data, numpy.int32)\n else:\n return -1, -1\n Fs = audiofile.frame_rate\n x = numpy.array(data[0::audiofile.channels]).T\n else:\n print(\"Error in readAudioFile(): Unknown file type!\")\n return -1, -1\n except IOError:\n print(\"Error: file not found or other I/O error.\")\n return -1, -1\n\n if x.ndim == 2:\n if x.shape[1] == 2:\n x = x.flatten()\n\n return Fs, x","def streaming_from_file(filepath):\r\n pipe = rs.pipeline()\r\n cfg = rs.config()\r\n cfg.enable_device_from_file(filepath, repeat_playback=False)\r\n return pipe, cfg","def sox_get_sample_rates(self, files):\n min_rate = max_rate = None\n files_to_rates_dict = {}\n\n for f in files:\n result = self._process_command('soxi -r \"%s\"' % f, PIPE)\n try:\n rate = int(result[1][0].strip('\\n'))\n except ValueError:\n raise LetMeError('Unable to read sample rate from %s' % f)\n\n files_to_rates_dict[f] = rate\n\n logging.debug('\\nSample rate `%s` for `%s`', rate, f)\n\n if max_rate is None or rate > max_rate:\n max_rate = rate\n\n if min_rate is None or rate < min_rate:\n min_rate = rate\n\n logging.debug('Sample rates: min - %s, max - %s', min_rate, max_rate)\n return min_rate, max_rate, files_to_rates_dict","def get_phase_amplified_frames(\n filename,\n magphase,\n fl,\n fh,\n fs,\n progress_callback = lambda x: x,\n attenuateOtherFreq = False,\n pyrtype = 'octave',\n sigma = 0,\n temporalFilter = FIRWindowBP,\n scalevideo = 1,\n frames = None,\n):\n ## Read Video\n print(\"Preparing capture\")\n vr = cv2.VideoCapture(filename)\n nF = int(vr.get(cv2.CAP_PROP_FRAME_COUNT))\n ret, frame = vr.read()\n h, w, nC = frame.shape\n\n \n print(\"Loading: \", filename)\n vid = np.zeros([h, w, nC, nF],frame.dtype)\n vid[:,:,:,0] = frame\n for k in range(1, nF):\n retval, frame = vr.read()\n if retval:\n vid[:,:,:,k] = frame\n else:\n frames = (0,k)\n break\n progress_callback(10/nF)\n sys.stdout.write('.')\n sys.stdout.flush()\n print('\\n')\n vr.release()\n\n if not frames:\n frames = (0, nF-1)\n\n ## Compute spatial filters \n vid = vid[:,:,:,frames[0]:frames[1]+1]\n h, w, nC, nF = vid.shape\n if scalevideo != 1:\n h, w = int(scalevideo*h), int(scalevideo*w)\n\n print('Computing spatial filters\\n')\n ht = maxSCFpyrHt(np.zeros((h,w)))\n if pyrtype == 'octave':\n filters = getFilters((h, w), np.power(2,np.arange(0,-ht-1,-1).astype(float)), 4)\n print('Using octave bandwidth pyramid\\n') \n elif pyrtype == 'halfOctave': \n filters = getFilters((h, w), np.power(2,np.arange(0,-ht-0.5,-0.5).astype(float)), 8, twidth=0.75)\n print('Using half octave bandwidth pyramid\\n')\n elif pyrtype == 'smoothHalfOctave':\n filters = getFiltersSmoothWindow((h, w), 8, filtersPerOctave = 2) \n print('Using half octave pyramid with smooth window.\\n')\n elif pyrtype == 'quarterOctave':\n filters = getFiltersSmoothWindow((h, w), 8, filtersPerOctave = 4)\n print('Using quarter octave pyramid.\\n')\n else:\n raise ValueError('Invalid Filter Types')\n\n croppedFilters, filtIDX = getFilterIDX(filters)\n \n ## Initialization of motion magnified luma component\n magnifiedLumaFFT = np.zeros((h,w,nF),np.complex64)\n\n def buildLevel(im_dft,k):\n return np.fft.ifft2(\n np.fft.ifftshift(\n np.multiply(croppedFilters[k][0], im_dft[filtIDX[k,0], filtIDX[k,1]])\n )\n )\n\n def reconLevel(im_dft, k):\n return 2*(np.multiply(croppedFilters[k][0], np.fft.fftshift(np.fft.fft2(im_dft))))\n\n ## First compute phase differences from reference frame\n numLevels = len(filters) \n print('Moving video to Fourier domain\\n')\n vidFFT = np.zeros((h,w,nF),dtype=np.complex64)\n for k in range(0, nF):\n originalFrame = vid[:,:,:,k].astype(np.float32)\n originalFrame = cv2.cvtColor(originalFrame, cv2.COLOR_BGR2YUV)\n tVid = cv2.resize(originalFrame[:,:,0], (w, h), 0, 0, cv2.INTER_CUBIC)\n vidFFT[:,:,k] = np.fft.fftshift(np.fft.fft2(tVid))\n sys.stdout.write('.')\n sys.stdout.flush()\n progress_callback(20/nF)\n print('\\n')\n\n refFrame = 0\n for level in range(1, numLevels-1):\n ## Compute phases of level\n # We assume that the video is mostly static\n pyrRef = buildLevel(vidFFT[:,:,refFrame], level)\n pyrRefPhaseOrig = np.divide(pyrRef, np.abs(pyrRef))\n pyrRef = np.angle(pyrRef)\n\n delta = np.zeros((pyrRef.shape[0], pyrRef.shape[1] ,nF), np.float32)\n print('Processing level {0} of {1}\\n'.format(level+1, numLevels))\n\n for frameIDX in range(0, nF):\n filterResponse = buildLevel(vidFFT[:,:,frameIDX], level)\n pyrCurrent = np.angle(filterResponse)\n delta[:,:,frameIDX] = np.mod(np.pi+pyrCurrent-pyrRef,2*np.pi)-np.pi\n \n ## Temporal Filtering\n print('Bandpassing phases\\n')\n delta = temporalFilter(delta, fl/fs, fh/fs) \n\n ## Apply magnification\n eps = 2.2204e-16\n print('Applying magnification\\n')\n for frameIDX in range(0, nF):\n\n phaseOfFrame = delta[:,:,frameIDX]\n originalLevel = buildLevel(vidFFT[:,:,frameIDX], level)\n ## Amplitude Weighted Blur \n if (sigma != 0):\n phaseOfFrame = AmplitudeWeightedBlur(phaseOfFrame, np.abs(originalLevel)+eps, sigma)\n\n # Increase phase variation\n phaseOfFrame = magphase * phaseOfFrame\n \n if attenuateOtherFreq:\n tempOrig = np.multiply(np.abs(originalLevel), pyrRefPhaseOrig)\n else:\n tempOrig = originalLevel\n\n tempTransformOut = np.multiply(np.exp(1j*phaseOfFrame), tempOrig)\n\n curLevelFrame = reconLevel(tempTransformOut, level)\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] = \\\n curLevelFrame + magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX]\n \n progress_callback(50/(numLevels-2))\n\n ## Add unmolested lowpass residual\n level = len(filters)-1\n for frameIDX in range(0, nF):\n try:\n lowpassFrame = np.multiply(vidFFT[filtIDX[level, 0], filtIDX[level, 1] ,frameIDX], np.power(croppedFilters[-1][0], 2))\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] = \\\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] + lowpassFrame\n except IndexError:\n print(\"IndexError\")\n progress_callback(10/nF)\n\n for k in range(0, nF):\n magnifiedLuma = np.fft.ifft2(np.fft.ifftshift(magnifiedLumaFFT[:,:,k])).real\n originalFrame = cv2.cvtColor(vid[:,:,:,k].astype(np.float32), cv2.COLOR_BGR2YUV)\n originalFrame = cv2.resize(originalFrame, (w, h), 0, 0, cv2.INTER_CUBIC)\n originalFrame[:,:,0] = magnifiedLuma\n originalFrame = cv2.cvtColor(originalFrame, cv2.COLOR_YUV2BGR)\n originalFrame = cv2.convertScaleAbs(originalFrame)\n yield originalFrame\n progress_callback(10/nF)","def read(f, normalized=False):\r\n a = pydub.AudioSegment.from_mp3(f)\r\n y = np.array(a.get_array_of_samples())\r\n if a.channels == 2:\r\n y = y.reshape((-1, 2))\r\n if normalized:\r\n return a.frame_rate, np.float32(y) / 2**15\r\n else:\r\n return a.frame_rate, y","def __init__(self, pattern='/graphics/projects/scratch/wieschol/sync-data/*/*_noaudio.low.mp4',\n samples=10, shuffle=True, max_pos_dist=10, min_neg_dist=20, min_pos_dist=5):\n self.files = glob.glob(pattern)\n self.shuffle = shuffle\n self.max_pos_dist = max_pos_dist\n self.min_pos_dist = min_pos_dist\n self.min_neg_dist = min_neg_dist\n self.samples = samples","def __init__(self, renderer: sdl2.render.SDL_Renderer, filepath: str,\n sample_rate: int, loop: bool):\n self.textures: List[sdl2.render.SDL_Texture] = []\n for filename in sorted(os.listdir(filepath)):\n self.textures.append(\n texture_from_bmp(renderer, os.path.join(filepath, filename)))\n\n # Number of times to update current_frame per second\n self.sample_rate = sample_rate\n self.loop = loop\n\n # Index into textures list\n self.current_frame = 0","def get_Metadata_freq(metafile_science):\n\n mslist_file = open(metafile_science, 'r')\n LINES = mslist_file.readlines()\n mslist_file.close()\n\n frame = 'Frame'\n \n for i in range(len(LINES)):\n line = LINES[i]\n if line.find(frame) >=0:\n next_line = LINES[i+1]\n TOKS = next_line.split()\n chan_width = float(TOKS[10])*1000. # convert kHz to Hz\n cfreq = TOKS[12] #MHz\n nchan = TOKS[7]\n\n return chan_width, cfreq, nchan","def get_movie_data(files: list) -> list:\n pass","def readDriverFile(self, input_file):\n\n\n fid = open(self.basePath + input_file,'r')\n\n # Line 1\n line = fid.readline()\n l_input = line.split('!')\n mshfile = l_input[0].rstrip()\n\n # Line 2\n line = fid.readline()\n l_input = line.split('!')\n obsfile = l_input[0].rstrip()\n\n # Line 3\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input=='null':\n topofile = []\n\n else:\n topofile = l_input[0].rstrip()\n\n\n # Line 4\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n mstart = float(l_input[1])\n\n else:\n mstart = l_input[0].rstrip()\n\n # Line 5\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n mref = float(l_input[1])\n\n else:\n mref = l_input[0].rstrip()\n\n # Line 6\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n staticInput = float(l_input[1])\n\n elif l_input[0]=='DEFAULT':\n staticInput = None\n\n else:\n staticInput = l_input[0].rstrip()\n\n\n # Line 7\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input=='DEFAULT':\n magfile = []\n\n else:\n magfile = l_input[0].rstrip()\n\n # Line 8\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input=='DEFAULT':\n wgtfile = []\n\n else:\n wgtfile = l_input[0].rstrip()\n\n # Line 9\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n chi = float(l_input[0])\n\n # Line 10\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n val = np.array(l_input[0:4])\n alphas = val.astype(np.float)\n\n # Line 11\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n val = np.array(l_input[1:3])\n bounds = val.astype(np.float)\n\n else:\n bounds = l_input[0].rstrip()\n\n # Line 12\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n val = np.array(l_input[1:6])\n lpnorms = val.astype(np.float)\n\n else:\n lpnorms = l_input[0].rstrip()\n\n # Line 13\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n val = np.array(l_input[1:3])\n eps = val.astype(np.float)\n\n else:\n eps = [None,None]\n\n self.mshfile = mshfile\n self.obsfile = obsfile\n self.topofile = topofile\n self.mstart = mstart\n self._mrefInput = mref\n self._staticInput = staticInput\n self.magfile = magfile\n self.wgtfile = wgtfile\n self.chi = chi\n self.alphas = alphas\n self.bounds = bounds\n self.lpnorms = lpnorms\n self.eps = eps","def get_video_frame_rate(filename):\n clip = VideoFileClip(filename)\n frame_rate = clip.fps\n clip.close()\n return frame_rate","def audioRead(path):\n data, samplerate = sf.read(path)\n frames = data.shape[0]\n channels = len(data.shape)\n duration = 1/samplerate*frames\n return data, samplerate, path, duration, frames, channels","def INPUT_Periods_file(input):\n \n global events\n \n tb = 3600\n ta = 3600\n \n Period = input['min_date'].split('T')[0] + '_' + \\\n input['max_date'].split('T')[0] + '_' + \\\n str(input['min_mag']) + '_' + str(input['max_mag'])\n eventpath = os.path.join(input['datapath'], Period)\n \n len_events = len(events)\n \n input_period = open(os.path.join(os.getcwd(), 'INPUT-Periods'), 'a+')\n\n for i in range(0, len_events):\n \n str_event = str(events[i]['datetime']-tb) + '_' + \\\n str(events[i]['datetime']+ta) + '_' + \\\n str(events[i]['magnitude'] - 0.01) + '_' + \\\n str(events[i]['magnitude'] + 0.01) + '\\n'\n input_period.writelines(str_event)\n \n input_period.close()\n \n print '************************************************************' \n print 'New INPUT-Periods file is generated in your folder.'\n print 'Now, you could run the program again based on your desired event :)' \n print '************************************************************'\n \n sys.exit()","def f2gif(path,fps):\n print(\"==============================================\")\n print(\"Convert file to GIF!\")\n pathout = path[:-4]+'_'+str(fps)+'.gif'\n if path.endswith('.tif'): \n# import tifffile\n im = tifffile.imread(path)\n nFrames, h,w = im.shape\n dur=1/fps\n clip = []\n for i in range(nFrames):\n fr = cv2.cvtColor(im[i],cv2.COLOR_GRAY2RGB)\n clip.append(mp.ImageClip(fr).set_duration(dur))\n video = mp.concatenate_videoclips(clip, method=\"compose\",ismask=False)#ismask=True to make grayscale\n\n else:\n video = mp.VideoFileClip(path)\n fpsIn = int(video.fps)\n if fps != fpsIn:\n print(\"Conflict in fps! \\n\", \"[0] Use fps of input file;\\n\", \"[1] Use desired fps w/o speedup;\\n\",\n \"[2] Use desired fps w/ speedup:\")\n k = input('Input your selection: ')\n if k == 2:\n sf = fps/fpsIn\n video =video.fx(mp.vfx.speedx, sf)# Not working when sf<1\n elif k == 0:\n fps = fpsIn\n\n video.write_gif(pathout,fps=fps)\n video.reader.close()# To fix handel error problem\n# if path.endswith('.gif'):\n# clip.write_videofile(pathout,fps=fps,codec='libx264', bitrate='32 M',preset='ultrafast')\n print(\"==============================================\")\n print(\"MP4 convertion Done!\")","def read_frame(location, channels, start_time=None, \n end_time=None, duration=None):\n\n if end_time and duration:\n raise ValueError(\"end time and duration are mutually exclusive\")\n \n if type(location) is list:\n locations = location\n else:\n locations = [location]\n\n cum_cache = lal.Cache()\n for source in locations:\n dir_name, file_name = os.path.split(source)\n base_name, file_extension = os.path.splitext(file_name)\n \n if file_extension == \".lcf\" or file_extension == \".cache\":\n cache = lal.CacheImport(source)\n elif file_extension == \".gwf\": \n cache = lalframe.FrOpen(dir_name, file_name).cache\n else:\n raise TypeError(\"Invalid location name\")\n \n cum_cache = lal.CacheMerge(cum_cache, cache)\n \n stream = lalframe.FrStreamCacheOpen(cum_cache)\n \n stream.mode = lalframe.FR_STREAM_VERBOSE_MODE\n lalframe.FrSetMode(stream.mode | lalframe.FR_STREAM_CHECKSUM_MODE,\n stream)\n\n # determine duration of data\n if type(channels) is list:\n first_channel = channels[0]\n else:\n first_channel = channels\n data_length = lalframe.FrStreamGetVectorLength(first_channel, stream)\n channel_type = lalframe.FrStreamGetTimeSeriesType(first_channel, stream)\n create_series_func = _fr_type_map[channel_type][2]\n get_series_metadata_func = _fr_type_map[channel_type][3]\n series = create_series_func(first_channel, stream.epoch, 0, 0,\n lal.ADCCountUnit, 0)\n get_series_metadata_func(series, stream)\n data_duration = data_length * series.deltaT\n\n if start_time is None:\n start_time = stream.epoch*1\n if end_time is None:\n end_time = start_time + data_duration\n\n if type(start_time) is not lal.LIGOTimeGPS:\n start_time = lal.LIGOTimeGPS(start_time)\n if type(end_time) is not lal.LIGOTimeGPS:\n end_time = lal.LIGOTimeGPS(end_time)\n\n if duration is None:\n duration = float(end_time - start_time)\n else:\n duration = float(duration)\n\n # lalframe behaves dangerously with invalid duration so catch it here\n if duration <= 0:\n raise ValueError(\"Negative or null duration\")\n #if duration > data_duration:\n # raise ValueError(\"Requested duration longer than available data\")\n\n if type(channels) is list:\n all_data = []\n for channel in channels:\n channel_data = _read_channel(channel, stream, start_time, duration)\n lalframe.FrStreamSeek(stream, start_time)\n all_data.append(channel_data)\n return all_data\n else:\n return _read_channel(channels, stream, start_time, duration)","def rec_one_shot(self, sec, file_name=None):\n self.__open_noncallback_stream()\n frames = []\n for i in range(int(self.RATE / self.CHUNK * sec)):\n data = self.stream.read(self.CHUNK)\n data = np.fromstring(data, dtype=np.int16)\n frames.append(data)\n self.stream.stop_stream()\n if file_name is not None:\n with wave.open(file_name, 'wb') as wav_file:\n wav_file.setnchannels(self.CHANNELS)\n wav_file.setsampwidth(self.recorder.get_sample_size(self.FORMAT))\n wav_file.setframerate(self.RATE)\n wav_file.writeframes(b''.join(frames))\n frame = np.concatenate(frames, 0)\n self.stop_streaming()\n return frame","def stream_timelapse(path):\n parts = path.split('.')[0].split('_')\n count = int(parts[2])\n filename = parts[0] + '_{0:03d}_{1:03d}.jpg'\n for i in range(count):\n frame = open(filename.format(i, count), 'rb').read()\n yield b'--frame\\r\\nContent-Type: image/jpeg\\r\\nContent-Length: ' + \\\n str(len(frame)).encode() + b'\\r\\n\\r\\n' + frame + b'\\r\\n'\n time.sleep(0.5)","def read_all_files():\n paths = get_all_recording_paths()\n\n return read_by_paths(paths)","def t1_loadNFile(self):\n print \"noisubspectrumFile\"\n filename = tkFileDialog.askopenfilename()\n filename = self.filenameparser(filename)\n self.t1_noifilename = filename","def _default_specs(self):\n # Spectrometer specs\n self.model = \"Flame-S\" # Spectrometer model\n self.fov = 1 # Field of view fo spectrometer (radius of FOV)\n self.ILS = None # Number array holding instrument line shape (possibly don't hold this here?)\n self.fiber_diameter = 1e-3 # Diameter of optical fiber\n self.pix_num = 2048 # Number of pixels\n self.bit_depth = 16 # Bit depth of spectrometer detector\n\n # File information\n self.file_ext = '.npy' # Spectra saved as numpy array\n self.file_ss = '{}ss' # Shutter speed format spec\n self.file_ss_loc = 1 # Shutter speed location in filename\n self.file_spec_type = {'meas': 'Plume', 'dark': 'Dark', 'cal': 'ppmm', 'clear': 'Clear'}\n self.file_datestr = \"%Y-%m-%dT%H%M%S\" # Date/time format spec in filename\n self.file_datestr_loc = 0\n self.plume_params_file = 'plume_params.txt'\n self.plume_speed_id = 'plume_speed='\n self.plume_dist_id = 'plume_distance='\n\n # File which flags that a scan is complete. The file will be empty, just its presence is required\n self.scan_complete = 'complete.txt'\n\n # Acquisition settings\n self.start_int_time = 100 # Starting integration time\n self.start_coadd = 1 # Number of spectra to coadd\n self.framerate = 1 # Framerate of acquisitions (Hz)\n self.wavelengths = None # Wavelengths (nm)\n self.spectrum = None # Spectrum\n self.spectrum_filename = None # Filename for spectrum\n\n self.auto_int = True # Bool for requesting automated integration time adjustment\n self.min_saturation = 0.6 # Minimum saturation accepted before adjusting shutter speed (if auto_ss is True)\n self.max_saturation = 0.9 # Maximum saturation accepted before adjusting shutter speed (if auto_ss is True)\n self.saturation_range = [300, 335] # Range of wavelengths used in checking integration time\n self.saturation_pixels = 2 # Number of pixels to check\n\n # Predefined list of integration times for automatic exposure adjustment\n self.int_list = np.concatenate((np.arange(0.1, 0.5, 0.05),\n np.arange(0.5, 1, 0.1),\n np.arange(1, 5, 0.5),\n np.arange(5, 10, 1),\n np.arange(10, 50, 5),\n np.arange(50, 100, 10),\n np.arange(100, 500, 50),\n np.arange(500, 1000, 100),\n np.arange(10 ** 3, 10 ** 4, 500),\n np.array([10 ** 4])))","def open_read_files(answer_files, answers):\r\n \"\"\"And designates each file to a variable in answers\"\"\"\r\n count = 0\r\n s = 0\r\n answer_files2 = []\r\n for file in answer_files[:]: # Used [:] to get all file_names in answer_files\r\n ans = open(file, mode='r')\r\n print(f\"Opening {ans.name}\")\r\n time.sleep(s)\r\n answers[count] = ans\r\n count += 1\r\n if ans.closed == False: # Section for checking if files are closed\r\n print(f\"Closing {ans.name}\")\r\n ans.close()\r\n answer_files2.append(ans.name)\r\n answer_files.remove(ans.name)\r\n time.sleep(s)\r\n return answer_files2, answers","def file_name_list():\n file_names = []\n hour = h1\n minute = m1\n while hour * 60 + minute <= h2 * 60 + m2:\n file_name = generate_file_name(hour, minute)\n file_names.append(file_name)\n hour, minute = next_time(hour, minute)\n return file_names","def get_parameters_fastcharge(filename, source_directory):\n filename = filename.rsplit('.', 1)[0]\n strname = filename.rsplit('_CH', 1)[0]\n\n # Get date\n date = re.match(r'(\\d+)-(\\d+)-(\\d+)', strname)\n if date is None:\n warnings.warn(\"Date could not be parsed from {}\".format(filename))\n else:\n date = date.group()\n\n # Get channel number\n chno = re.findall(r'(CH+\\d*)', filename)\n if chno:\n chno = chno[0]\n else:\n chno = None\n warnings.warn(\"Channel number could not be parsed from {}\".format(filename))\n\n try:\n param_str = strname.rsplit(date + '_', 1)[1]\n param = param_str.replace('_', '.')\n\n if param.find('.') < 0:\n param = find_meta(filename, source_directory)\n\n q1 = re.findall(r'(\\d+per)', param)[0].split('per')[0]\n cc1 = re.findall(r'(\\d*\\.?\\d+C)', param.split(q1 + 'per.')[0])[0]\n cc2 = re.findall(r'(\\d*\\.?\\d+C)', param.split(q1 + 'per.')[1])[0]\n protocol = cc1+'('+q1+'%)-'+cc2\n except Exception as e:\n warnings.warn(\"Failed to parse protocol for {}: {}\".format(filename, e))\n protocol = None\n\n return date, chno, strname, protocol","def test_get_fasta_fps(self):\r\n\r\n file_basenames = [basename(self.fasta2_fp), basename(self.fasta3_fp),\r\n basename(self.fasta1_fp)]\r\n\r\n actual_fastas = get_fasta_fps(self.input_dir, file_basenames)\r\n\r\n expected_fasta = [self.fasta2_fp, self.fasta3_fp, self.fasta1_fp]\r\n\r\n self.assertEqual(actual_fastas, expected_fasta)","def get_configfile(files,\n seasoncyc_base=None,\n seasoncyc_sim=None,\n base_id='NCEP',\n sim_id='NCEP',\n timewin=1,\n varname='slp',\n seacyc=False,\n cycsmooth=91,\n nanalog=20,\n seasonwin=30,\n distfun='rms',\n outformat='.txt',\n period=[\"1973-01-01\", \"2012-12-31\"],\n bbox=\"-180.0,-90.0,180,90.0\",\n calccor=True,\n silent=False):\n from datetime import datetime as dt\n\n date_stamp = dt.strftime(dt.now(), format='%Y%m%d_%H%M%S')\n LOGGER.info('start configuration file preparation at: %s' % (date_stamp))\n\n # convert True/False to Fortran syntax\n seacyc = str(seacyc)\n calccor = str(calccor)\n silent = str(silent)\n\n # write stuff to configuration file\n # NB: if order or format or number changes, need to edit wps_analogs_viewer.py\n # and template_analogviewer.html where these scripts read in the config\n # params\n config_file = \"config.txt\"\n\n config = open(config_file, \"w\")\n\n config.write(\n '!Configuration file for CASTf90 analogs processes deployed in flyingpigeon\\n')\n config.write('!Created : %s \\n' % (date_stamp))\n config.write('!Version : 0.1.5 \\n')\n config.write('&FILES \\n')\n config.write(' my_files%archivefile = \"{file}\" \\n'.format(\n file=os.path.relpath(files[0])))\n config.write(' my_files%simulationfile = \"{file}\" \\n'.format(\n file=os.path.relpath(files[1])))\n config.write(' my_files%outputfile = \"{file}\" \\n'.format(\n file=os.path.relpath(files[2])))\n\n if seacyc is not 'False':\n config.write(' my_files%seacycfilebase = \"{file}\" \\n'.format(\n file=os.path.relpath(seasoncyc_base)))\n config.write(' my_files%seacycfilesim = \"{file}\" \\n'.format(\n file=os.path.relpath(seasoncyc_sim)))\n\n config.write('/ \\n')\n config.write('&PARAM \\n')\n config.write(' my_params%timewin = {timewin} \\n'.format(timewin=timewin))\n config.write(' my_params%varname = \"{varname}\" \\n'.format(varname=varname))\n config.write(' my_params%seacyc = .{seacyc}. \\n'.format(\n seacyc=seacyc.upper()))\n config.write(' my_params%cycsmooth = {cycsmooth} \\n'.format(\n cycsmooth=cycsmooth))\n config.write(' my_params%nanalog = {nanalog} \\n'.format(nanalog=nanalog))\n config.write(' my_params%seasonwin = {seasonwin} \\n'.format(\n seasonwin=seasonwin))\n config.write(' my_params%distfun = \"{distfun}\" \\n'.format(distfun=distfun))\n config.write(' my_params%calccor = .{calccor}. \\n'.format(\n calccor=calccor.upper()))\n config.write(' my_params%oformat = \"{outformat}\" \\n'.format(\n outformat=outformat)) # \".txt\" # ! if equals \".nc\"\n config.write(' my_params%silent = .{silent}.\\n'.format(\n silent=silent.upper()))\n config.write('/\\n')\n config.write('&ATTS\\n')\n config.write(' my_atts%simsource = \"{sim_id}\" \\n'.format(sim_id=sim_id)) # model name\n config.write(\n ' my_atts%predictorvar = \"{varname}\" \\n'.format(varname=varname))\n config.write(' my_atts%archisource = \"{base_id}\" \\n'.format(base_id=base_id))\n config.write(' my_atts%archiperiod = \"{start},{end}\" \\n'.format(\n start=period[0], end=period[1]))\n config.write(' my_atts%predictordom = \"{bbox}\" \\n'.format(bbox=bbox))\n config.write('/\\n')\n\n config.close()\n return config_file","def open_frame(path,number):\n num=str(number).zfill(3) #Zero filling\n name = glob.glob(path+\"/*\"+num+\"*\")\n if len(name)==0:\n name = glob.glob(path+\"/\"+str(number)+\".png\")\n if len(name)>1:\n print \"too many matches \",len(name),\" found\"\n name = name[0]\n img = Image.open(name)\n img = np.asarray(img)\n img.setflags(write=1)\n return img","def get_audio(name, n):\n audio_path = os.path.join(args.input_folder, name, \"audio.ogg\")\n if not os.path.exists(audio_path):\n ## Some folders have multiple .ogg files, so we need to first combine them into one file. Example:\n ## |── Universe\n ## │ ├── aligned.swc\n ## │ ├── audio1.ogg\n ## │ ├── audio2.ogg\n ## │ ├── audio3.ogg\n ## │ ├── audio4.ogg\n ## │ ├── audiometa.txt\n ## │ ├── info.json\n ## │ ├── wiki.html\n ## │ ├── wiki.txt\n ## │ └── wiki.xml\n\n multiple_ogg_files = []\n for i in range(1, 5):\n path = os.path.join(args.input_folder, name, \"audio\" + str(i) + \".ogg\")\n if os.path.exists(path):\n multiple_ogg_files.append(path)\n else:\n break\n if len(multiple_ogg_files) == 0:\n return\n elif len(multiple_ogg_files) == 1:\n os.system(\"cp \\\"\" + multiple_ogg_files[0] + \"\\\" \\\"\" + audio_path + \"\\\"\")\n else:\n tmp_file_name = \"ffmeg_inputs.txt\"\n print(\"tmp_file_name=\", tmp_file_name)\n with open(tmp_file_name, \"w\", encoding=\"utf-8\") as tmp_file:\n for path in multiple_ogg_files:\n tmp_file.write(\"file '\" + path + \"'\\n\")\n cmd = \"ffmpeg -f concat -i \\\"\" + tmp_file_name + \"\\\" -c copy \\\"\" + audio_path + \"\\\"\"\n print(cmd)\n os.system(cmd)\n\n output_audio_path = args.destination_folder + \"/audio/\" + str(n) + \".ogg\"\n os.system(\"cp \\\"\" + audio_path + \"\\\" \" + output_audio_path)","def get_data(path):\n if path.endswith('.mp3'):\n path = prepare_file(path, path.rstrip('mp3')+'wav')\n x, sr = librosa.load(path, duration=30)\n\n else:\n x, sr = librosa.load(path, duration=30)\n directory, file_name = os.path.split(path)\n return x, sr, file_name","def read_cospectrum(path,d):\r\n spec = []\r\n timeseries = []\r\n for i in range(len(d)):\r\n filename = path + d[i]\r\n\r\n with open(filename, \"r\") as f:\r\n reader = csv.reader(f,delimiter=',')\r\n ct=1\r\n for row in reader:\r\n if ct==6:\r\n Hz = float(row[0].split('_')[-1])\r\n elif ct==7:\r\n height = float(row[0].split('_')[-1])\r\n elif ct==8:\r\n ws = float(row[0].split('_')[-1])\r\n elif ct==9:\r\n avg_period = float(row[0].split('_')[-1])\r\n elif ct==13:\r\n header = row\r\n elif ct>13:\r\n break\r\n ct+=1\r\n \r\n meta = [Hz,height,ws,avg_period]\r\n \r\n thisspec = np.genfromtxt(filename,delimiter=',',skip_header=13)\r\n spec.append(thisspec)\r\n thistime = re.findall('\\d{8}-\\d{4}',filename)[0]\r\n thisdate = datetime.strptime(thistime,'%Y%m%d-%H%M')\r\n timeseries.append(thisdate) \r\n \r\n return spec, timeseries, header, meta","def getVideoFrames(videoFilePath, startFrameNumber=-1, endFrameNumber=-1):\n frames=[]\n vidcap = cv2.VideoCapture(videoFilePath)\n fps=vidcap.get(cv2.CAP_PROP_FPS)\n totalFrame=vidcap.get(cv2.CAP_PROP_FRAME_COUNT)\n if startFrameNumber==-1:\n startFrameNumber = 0\n if endFrameNumber == -1:\n endFrameNumber = totalFrame - 1\n success,image = vidcap.read()\n count = 0\n success = True\n while success:\n image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n image = color.rgb2yiq(image).astype(np.float32)\n \n if count<startFrameNumber:\n success,image = vidcap.read()\n count+=1\n continue\n elif count>=endFrameNumber:\n break\n else: \n frames.append(image)\n success,image = vidcap.read()\n count += 1\n frames=np.array(frames)\n \n return fps, frames","def getFileList(self):\n sid = 86400 # change to 3600 for hour-by-hour\n uDays = range(sid*(int(self.uStart)/sid),sid+(sid*(int(self.uStop)/sid)),sid)\n fileList = []\n sep = os.path.sep\n for d in uDays:\n s = unixTimeToString(d)\n ymdPath = 'year' + s[0:4] + sep + 'month' + s[5:7] + sep + 'day' + s[8:10]\n dirname = self.basePath + sep + ymdPath + sep + self.sensor + sep + 'padhist'\n pattern = '*' + self.sensor + '_hstv*.mat'\n nameList = glob.glob1(dirname,pattern)\n for name in nameList:\n uTime = stringTimeToUnix(name[0:13] + '_00_00.000')\n if ( self.uStart <= uTime <= self.uStop ):\n #print 'IN: %s' % unixTimeToString(uTime)\n fileList.append(dirname + sep + name)\n fileList.sort()\n self.fileList = fileList","def read_data(self):\n self.days = [0, 2, 3, 5, 6, 8, 9, 11, 13, 14]\n path = '../data/'\n data = []\n for day in self.days:\n filename = path + 'spectrum_day{}.txt'.format(day)\n data.append(read_file(filename))\n return data","def fix_file(file_path: str, output_path_fixed: str, target_rate: int=16000,\n channels: int=1, output_path: str=None, min_duration: int=None,\n verbose_level: int=0):\n file_name = file_path.split(os.sep)[-1]\n new_file_path = output_path_fixed + os.sep + file_name\n\n try:\n # Get the audio length\n out = syscommand.system('soxi -D ' + file_path)\n duration = float(out)\n # Get the number of channels\n out = syscommand.system('soxi -c ' + file_path)\n current_n_channels = int(out)\n # Get the current rate\n out = syscommand.system('soxi -r ' + file_path)\n current_rate = int(out)\n if min_duration is not None and duration < min_duration:\n raise Exception(\"Minimum length not satisfied\")\n except Exception as err:\n if str(verbose_level) != '0':\n print(err)\n return None, file_path\n\n if current_rate != target_rate and current_n_channels != channels:\n speed = float(current_rate) / float(target_rate)\n cmd = 'sox -V{} -r 16k {} {} channels 1 ' \\\n 'speed {}'.format(verbose_level, file_path, new_file_path,\n speed)\n if str(verbose_level) == '2':\n print(cmd)\n os.system(cmd)\n return new_file_path, file_path\n elif current_rate != target_rate:\n speed = float(current_rate) / float(target_rate)\n cmd = 'sox -V{} -r 16k {} {} ' \\\n 'speed {}'.format(verbose_level, file_path, new_file_path,\n speed)\n if str(verbose_level) == '2':\n print(cmd)\n os.system(cmd)\n return new_file_path, file_path\n elif current_n_channels != channels:\n cmd = 'sox -V{} {} {} channels 1'.format(verbose_level, file_path,\n new_file_path)\n if str(verbose_level) == '2':\n print(cmd)\n os.system(cmd)\n return new_file_path, file_path\n\n # Copy file if output path were provided and the file is not there\n if output_path is not None:\n copyfile(file_path, new_file_path)\n return file_path, file_path","def getConfig():\n\n config = rFile(\"/var/www/html/config.txt\").split()\n f = int(config[0])\n mode = config[1]\n\n if (f in DABchannels and (mode == \"explore\" or mode == \"monitor\")):\n return f, mode\n else:\n return 227360000, \"explore\" # Kamzik - Bratislava","def fileSetup(path):\n past_fnames = next(os.walk(path))[2]\n f_nums = []\n for f in past_fnames:\n if f.startswith('semi'):\n f_nums.append(int(f[4:8]))\n\n if not f_nums:\n now_fname = '/semi0001.h264'\n else:\n now_fname = '/semi%04d.h264' % (max(f_nums)+1, )\n\n now_fname = path+now_fname\n print 'Current filename: %s' % now_fname\n\n return now_fname","def t9_loadFile(self):\n print \"subspectrumFile\"\n filename = tkFileDialog.askopenfilename()\n filename = \"SubSpectrumData/\" + self.filenameparser(filename)\n orgin_file = self.filenameparser(filename)\n self.t9_filename = filename\n self.t9_orginfilename = orgin_file","def read_recording_names(feature_files):\n all_recording_names = {}\n for feature_file in feature_files:\n in_dir = '/'.join(feature_file.split('/')[:-1])\n name = \"recordings.list\"\n path = os.path.join(in_dir, name)\n if not os.path.exists(path):\n return None\n else:\n with open(path, 'r') as f:\n recording_names = f.readlines()\n recording_names = [recording_name.strip() for recording_name in recording_names]\n # feature file at this position is basically incorrect. it takes the name of the hdf5 file as a key in\n # the dictionary. the directory would be more intuitive. however, cmd_args.input is used later on to\n # access the names which is why this works\n all_recording_names.update({feature_file: recording_names})\n\n return all_recording_names","def getFileList(self):\n print 'getting fileList ...',\n sid = 86400 # change to 3600 for hour-by-hour\n uDays = range(sid*(int(self.uStart)/sid),sid+(sid*(int(self.uStop)/sid)),sid)\n fileList = []\n sep = os.path.sep\n for d in uDays:\n s = unixTimeToString(d)\n ymdPath = 'year' + s[0:4] + sep + 'month' + s[5:7] + sep + 'day' + s[8:10]\n dirname = self.basePath + sep + ymdPath + sep + self.subDir\n pattern = '*' + self.sensor\n nameList = glob.glob1(dirname,pattern)\n for name in nameList:\n ufStart = stringTimeToUnix(name[0:23])\n ufStop = stringTimeToUnix(name[24:47])\n if ( ufStart <= self.uStart <= ufStop ) or ( self.uStart <= ufStart <= self.uStop ) or ( ufStart <= self.uStop <= ufStop ):\n #print 'IN: %s' % unixTimeToString(uTime)\n fileList.append(dirname + sep + name)\n## else:\n## print 'OUT:\\n%s\\n%s\\n%s' % (unixTimeToString(ufStart),unixTimeToString(self.uStart),unixTimeToString(ufStop))\n fileList.sort()\n self.fileList = fileList\n print 'done'","def _load(self, filepath):\n import subprocess as sp\n command = ['ffmpeg',\n '-i', filepath,\n '-f', 's16le',\n '-acodec', 'pcm_s16le',\n '-ac', '1'] # channels: 2 for stereo, 1 for mono\n if self.sampling_rate != SAMPLING_RATE:\n command.extend(['-ar', str(self.sampling_rate)])\n command.append('-')\n # 30s at 44.1 kHz ~= 1.3e6\n proc = sp.run(command, stdout=sp.PIPE, bufsize=10**7, stderr=sp.DEVNULL, check=True)\n\n return np.fromstring(proc.stdout, dtype=\"int16\")","def inputwav(filename):\n data, sr = sf.read(filename)\n print('Decoding \"'+filename+'\"...')\n print('Sample rate is '+str(sr)+'...')\n try:\n ch=len(data[0,])\n except:\n ch=1\n print('File contains '+str(ch)+' audio channel(s)...')\n #Reshape the data so other functions can interpret the array if mono.\n #basically transposing the data\n if ch==1:\n data=data.reshape(-1,1)\n n=len(data)\n #This prevents log(data) producing nan when data is 0\n data[np.where(data==0)]=0.00001\n #convert to dB\n data_dB=20*np.log10(abs(data))\n return n, data,data_dB,sr, ch","def video_audio_files(video_name, path_curr_vid, path_current_frames):\n video_file = f\"{path_curr_vid}{video_name}\"\n audio_file = f\"{path_current_frames}{video_name.replace(VIDEO_EXT,AUDIO_EXT)}\"\n return video_file, audio_file","def getattr(self, path, *args, **pargs):\n path, meta = self.find_cue_path(path)\n if('.flaccuesplit.' in path):\n try:\n raw_path = path\n path, flaccue_details = path.split('.flaccuesplit.')\n path = self.clean_path(path)\n times, extension = os.path.splitext(flaccue_details)\n # Get the info for the base file.\n st = os.lstat(path)\n toreturn = dict((key, getattr(st, key)) for key in (\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\n 'st_nlink', 'st_size', 'st_uid'))\n # Estimate the file size.\n f = mutagen.File(path)\n start, end = times.split('.')\n # Minutes:Seconds:Frames\n # 75 frames per second.\n start_split = [int(x) for x in start.split(':')]\n if(len(start_split) != 3):\n start_time = 0\n else:\n start_time = start_split[0]*60 + start_split[1] + start_split[2]/75\n end_split = [int(x) for x in end.split(':')]\n if(len(end_split) != 3):\n end_time = f.info.length\n else:\n end_time = end_split[0]*60 + end_split[1] + end_split[2]/75\n toreturn['st_size'] = int((end_time - start_time) *\n f.info.channels *\n (f.info.bits_per_sample/8) *\n f.info.sample_rate)\n # Ensure the mode shows the file as readable.\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\n return toreturn\n except Exception:\n print(f'Error getting attributes for {raw_path}:', file=sys.stderr, flush=True)\n import traceback\n traceback.print_exc()\n # Otherwise, just get the normal info.\n path = self.clean_path(path)\n st = os.lstat(path)\n toreturn = dict((key, getattr(st, key)) for key in (\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\n 'st_nlink', 'st_size', 'st_uid'))\n # Ensure the mode shows the file as readable.\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\n return toreturn","def param_info():\n\n\tgizmo_names = syn.getGizmoNames()\n\n\tfor gizmo in gizmo_names:\n\t\tparams = syn.getParameterNames(gizmo)\n\t#doesnt get all parameters from gizmos i.e. WaveFreq\n\n\t# get all info on the 'WaveFreq' parameter\n\tGIZMO = 'aStim2'\n\tPARAMETER = 'WaveFreq'\n\n\t# info = syn.getParameterInfo(GIZMO, PARAMETER)\n\t#\n\t# # get the array size (should be 100)\n\t# sz = syn.getParameterSize(GIZMO, PARAMETER)\n\t#\n\t# # write values 1 to 50 in second half of buffer\n\t# result = syn.setParameterValues(GIZMO, PARAMETER, np.arange(1, 51), 50)\n\t#\n\t# # read all values from buffer\n\t# syn.getParameterValues(GIZMO, PARAMETER, sz)\n\t#\n\t# # get all info on the 'Go' parameter\n\t# PARAMETER = 'Go'\n\t# info = syn.getParameterInfo(GIZMO, PARAMETER)\n\t#\n\t# # flip the switch\n\t# result = syn.setParameterValue(GIZMO, PARAMETER, 1)\n\t#\n\t# # check the value\n\tfreq = syn.getParameterValue(GIZMO, PARAMETER)\n\tprint('value =', freq)\n\tfreq = [freq]\n\n\t# also verify visually that the switch slipped in the run\n\t# time interface. This state change will be logged just\n\t# like any other variable change and saved with the runtime\n\t# state.\n\n\tnumTrials = 5 #total number of trials across stimuli\n\tISI = [2.0, 3.0, 4.0, 5.0] # ISI in seconds\n\n\t# flash parameters\n\tflash_dur = [.001] # flash durs in seconds (100 ms, 200 ms)\n\tluminance = [[1, 1, 1], [.86, .86, .86], [0, .1, 1]] # white , grayish, purple just for testing\n\n\t# auditory parameters\n\tduration = [.005] # in seconds; pulseDur in TDT\n\tsound_levels = [20.0, 40.0, 60.0, 80.0] # dB; waveAmp in TDT\n\n\t# Auditory on (T/F? if T then A+V, if F then Visual only)\n\tstims = {0: \"auditory_only\",\n\t\t\t 1: \"visual_only\",\n\t\t\t 2: \"A+V\"\n\t\t\t }\n\n\texper = Experiment(numTrials=numTrials, ISI=ISI, flash_dur=flash_dur, luminance=luminance, wave_freq=freq,\n\t\t\t\t\t pulse_dur=duration, wave_amp=sound_levels, stimulus=stims)\n\texper.run_experiment()","def readFT(self,file=\"out__1.ft\"):","def get_metadata(my_path):\n with wave.open(my_path, \"rb\") as wave_file:\n frame_rate = wave_file.getframerate()\n channels = wave_file.getnchannels()\n my_format = pyaudio.get_format_from_width(wave_file.getsampwidth())\n return str(frame_rate), str(channels), str(my_format)","def parse_fname(cmd_args):\n\n # Seasonal accumulation file\n if (cmd_args.period == 99):\n f_name = _parse_fname_season(cmd_args)\n else:\n f_name = _parse_fname_hour(cmd_args)\n\n return f_name","def generate_config(filename: str,\n mw_pulse_duration: int = 20,\n flux_pulse_duration: int=40,\n ro_duration: int = 800,\n mw_mw_buffer=0,\n mw_flux_buffer=0,\n flux_mw_buffer=0,\n ro_latency: int = 0,\n mw_latency: int = 0,\n fl_latency: int = 0,\n init_duration: int = 200000):\n\n qubits = ['q0', 'q1', 'q2', 'q3', 'q4', 'q5', 'q6']\n lut_map = ['i {}', 'rx180 {}', 'ry180 {}', 'rx90 {}', 'ry90 {}',\n 'rxm90 {}', 'rym90 {}', 'rphi90 {}', 'spec {}', 'rx12 {}',\n 'square {}']\n flux_tuples = [(\"q2\", \"q0\"), (\"q0\", \"q2\"),\n (\"q0\", \"q3\"), (\"q3\", \"q0\"),\n (\"q3\", \"q1\"), (\"q1\", \"q3\"),\n (\"q1\", \"q4\"), (\"q4\", \"q1\"),\n (\"q2\", \"q5\"), (\"q5\", \"q2\"),\n (\"q5\", \"q3\"), (\"q3\", \"q5\"),\n (\"q3\", \"q6\"), (\"q6\", \"q3\"),\n (\"q6\", \"q4\"), (\"q4\", \"q6\")]\n\n cfg = {\n \"eqasm_compiler\": \"cc_light_compiler\",\n \"hardware_settings\": {\n \"qubit_number\": 7,\n \"cycle_time\": 20,\n \"mw_mw_buffer\": mw_mw_buffer,\n \"mw_flux_buffer\": mw_flux_buffer,\n \"mw_readout_buffer\": 0,\n \"flux_mw_buffer\": flux_mw_buffer,\n \"flux_flux_buffer\": 0,\n \"flux_readout_buffer\": 0,\n \"readout_mw_buffer\": 0,\n \"readout_flux_buffer\": 0,\n \"readout_readout_buffer\": 0},\n \"instructions\": {},\n \"resources\":\n {\"qubits\": {\"count\": 7},\n \"qwgs\": {\"count\": 3,\n \"connection_map\":\n {\n \"0\": [0, 1],\n \"1\": [2, 3, 4],\n \"2\": [5, 6]\n }\n },\n \"meas_units\": {\"count\": 7,\n \"connection_map\": {\"0\": [0],\n \"1\": [1],\n \"2\": [2],\n \"3\": [3],\n \"4\": [4],\n \"5\": [5],\n \"6\": [6]\n }\n },\n # FIXME OpenQL #103\n # \"meas_units\": {\"count\": 2,\n # \"connection_map\": {\"0\": [0, 2, 3, 5, 6],\n # \"1\": [1, 4]}\n # },\n \"edges\": {\"count\": 8,\n \"connection_map\": {\n \"0\": [2],\n \"1\": [3],\n \"2\": [0],\n \"3\": [1],\n \"4\": [6],\n \"5\": [7],\n \"6\": [4],\n \"7\": [5]\n }\n }\n },\n \"topology\":\n {\n \"x_size\": 5,\n \"y_size\": 3,\n \"qubits\":\n [\n {\"id\": 0, \"x\": 1, \"y\": 2},\n {\"id\": 1, \"x\": 3, \"y\": 2},\n {\"id\": 2, \"x\": 0, \"y\": 1},\n {\"id\": 3, \"x\": 2, \"y\": 1},\n {\"id\": 4, \"x\": 4, \"y\": 1},\n {\"id\": 5, \"x\": 1, \"y\": 0},\n {\"id\": 6, \"x\": 3, \"y\": 0}\n ],\n \"edges\":\n [\n {\"id\": 0, \"src\": 2, \"dst\": 0},\n {\"id\": 1, \"src\": 0, \"dst\": 3},\n {\"id\": 2, \"src\": 3, \"dst\": 1},\n {\"id\": 3, \"src\": 1, \"dst\": 4},\n {\"id\": 4, \"src\": 2, \"dst\": 5},\n {\"id\": 5, \"src\": 5, \"dst\": 3},\n {\"id\": 6, \"src\": 3, \"dst\": 6},\n {\"id\": 7, \"src\": 6, \"dst\": 4}\n ]\n },\n\n \"gate_decomposition\": {\n \"measz %0\": [\"measure %0\"],\n \"x %0\": [\"rx180 %0\"],\n \"y %0\": [\"ry180 %0\"],\n \"roty90 %0\": [\"ry90 %0\"],\n \"cnot %0,%1\": [\"ry90 %1\", \"cz %0,%1\", \"ry90 %1\"],\n\n # To support other forms of writing the same gates\n \"x180 %0\": [\"rx180 %0\"],\n \"y180 %0\": [\"ry180 %0\"],\n \"y90 %0\": [\"ry90 %0\"],\n \"x90 %0\": [\"rx90 %0\"],\n \"my90 %0\": [\"rym90 %0\"],\n \"mx90 %0\": [\"rxm90 %0\"],\n\n # Clifford decomposition per Epstein et al. Phys. Rev. A 89, 062321\n # (2014)\n \"cl_0 %0\": ['i %0'],\n \"cl_1 %0\": ['ry90 %0', 'rx90 %0'],\n \"cl_2 %0\": ['rxm90 %0', 'rym90 %0'],\n \"cl_3 %0\": ['rx180 %0'],\n \"cl_4 %0\": ['rym90 %0', 'rxm90 %0'],\n \"cl_5 %0\": ['rx90 %0', 'rym90 %0'],\n \"cl_6 %0\": ['ry180 %0'],\n \"cl_7 %0\": ['rym90 %0', 'rx90 %0'],\n \"cl_8 %0\": ['rx90 %0', 'ry90 %0'],\n \"cl_9 %0\": ['rx180 %0', 'ry180 %0'],\n \"cl_10 %0\": ['ry90 %0', 'rxm90 %0'],\n \"cl_11 %0\": ['rxm90 %0', 'ry90 %0'],\n\n \"cl_12 %0\": ['ry90 %0', 'rx180 %0'],\n \"cl_13 %0\": ['rxm90 %0'],\n \"cl_14 %0\": ['rx90 %0', 'rym90 %0', 'rxm90 %0'],\n \"cl_15 %0\": ['rym90 %0'],\n \"cl_16 %0\": ['rx90 %0'],\n \"cl_17 %0\": ['rx90 %0', 'ry90 %0', 'rx90 %0'],\n \"cl_18 %0\": ['rym90 %0', 'rx180 %0'],\n \"cl_19 %0\": ['rx90 %0', 'ry180 %0'],\n \"cl_20 %0\": ['rx90 %0', 'rym90 %0', 'rx90 %0'],\n \"cl_21 %0\": ['ry90 %0'],\n \"cl_22 %0\": ['rxm90 %0', 'ry180 %0'],\n \"cl_23 %0\": ['rx90 %0', 'ry90 %0', 'rxm90 %0']\n },\n }\n\n for q in qubits:\n cfg[\"instructions\"][\"prepz {}\".format(q)] = {\n \"duration\": init_duration,\n \"latency\": 0,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": True,\n \"type\": \"none\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"prepz\",\n \"cc_light_codeword\": 0,\n \"cc_light_opcode\": 2\n }\n\n for q in qubits:\n cfg[\"instructions\"][\"measure {}\".format(q)] = {\n \"duration\": ro_duration,\n \"latency\": ro_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"readout\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"measz\",\n \"cc_light_codeword\": 0,\n \"cc_light_opcode\": 4\n }\n\n for CW in range(len(lut_map)):\n for q in qubits:\n cfg[\"instructions\"][lut_map[CW].format(q)] = {\n \"duration\": mw_pulse_duration,\n \"latency\": mw_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"mw\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"cw_{:02}\".format(CW),\n \"cc_light_codeword\": CW,\n \"cc_light_opcode\": 8+CW}\n\n cfg[\"instructions\"]['c1'+lut_map[CW].format(q)] = {\n \"duration\": mw_pulse_duration,\n \"latency\": mw_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"mw\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"C1_cw_{:02}\".format(CW),\n \"cc_light_codeword\": CW,\n \"cc_light_opcode\": 32+8+CW,\n \"cc_light_cond\": 1} # 1 means : do if last meas. == 1\n\n\n cfg[\"instructions\"]['c0'+lut_map[CW].format(q)] = {\n \"duration\": mw_pulse_duration,\n \"latency\": mw_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"mw\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"C0_cw_{:02}\".format(CW),\n \"cc_light_codeword\": CW,\n \"cc_light_opcode\": 32+16+CW,\n \"cc_light_cond\": 2} # 2 means : do if last meas. == 0\n\n\n for CW in range(32):\n for q in qubits:\n cfg[\"instructions\"][\"cw_{:02} {}\".format(CW, q)] = {\n \"duration\": mw_pulse_duration,\n \"latency\": mw_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"mw\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"cw_{:02}\".format(CW),\n \"cc_light_codeword\": CW,\n \"cc_light_opcode\": 8+CW}\n\n for q in qubits:\n cfg[\"instructions\"][\"compensate {}\".format(q)] = {\n \"duration\": mw_pulse_duration,\n \"latency\": mw_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"mw\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"cw_00\",\n \"cc_light_codeword\": 0,\n \"cc_light_opcode\": 8+0}\n\n # N.B. The codewords for CZ pulses need to be further specified.\n # I do not expect this to be correct for now.\n for ft in flux_tuples:\n # FIXME add space back in\n cfg[\"instructions\"][\"cz {},{}\".format(ft[0], ft[1])] = {\n \"duration\": flux_pulse_duration,\n \"latency\": fl_latency,\n \"qubits\": [ft[0], ft[1]],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": True,\n \"type\": \"flux\",\n \"cc_light_instr_type\": \"two_qubit_gate\",\n \"cc_light_instr\": \"fl_cw_{:02}\".format(1),\n \"cc_light_right_codeword\": 1,\n \"cc_light_left_codeword\": 1,\n \"cc_light_opcode\": 128+1\n }\n\n for cw_flux in range(8):\n for ft in flux_tuples:\n cfg[\"instructions\"][\"fl_cw_{:02} {},{}\".format(cw_flux,\n ft[0], ft[1])] = {\n \"duration\": flux_pulse_duration,\n \"latency\": fl_latency,\n \"qubits\": [ft[0], ft[1]],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": True,\n \"type\": \"flux\",\n \"cc_light_instr_type\": \"two_qubit_gate\",\n \"cc_light_instr\": \"fl_cw_{:02}\".format(cw_flux),\n \"cc_light_right_codeword\": cw_flux,\n \"cc_light_left_codeword\": cw_flux,\n \"cc_light_opcode\": 128+cw_flux\n }\n\n with open(filename, 'w') as f:\n json.dump(cfg, f, indent=4)","def t8_loadFile(self):\n print \"spectrumFile\"\n filename = tkFileDialog.askopenfilename()\n filename = self.filenameparser(filename)\n self.t8_filename = filename","def read_all_files(\n pathname: Path, index: int = 0, pattern: str = \"dump-Trimer-*.gsd\"\n) -> List[Tuple[Variables, HoomdFrame]]:\n pathname = Path(pathname)\n snapshots = []\n for filename in sorted(glob.glob(str(pathname / pattern))):\n logger.debug(\"Reading %s\", Path(filename).stem)\n with gsd.hoomd.open(str(filename)) as trj:\n try:\n snapshots.append((get_filename_vars(filename), HoomdFrame(trj[index])))\n except IndexError:\n continue\n if not snapshots:\n logger.warning(\n \"There were no files found with a configuration at index %s\", index\n )\n return snapshots","def processFile(filename,length = 256,q=1,fs_in=8000,divide=4,plot=False):\n length = length*divide\n #fs = sample rate, sound = multichannel sound signal\n try:\n fs1, sound = wavfile.read(filename)\n except ValueError:\n print(str(filename) + ' failed to process')\n return 'failed'\n if fs1 != fs_in:\n raise ValueError('Sampling rate should be ' + str(fs_in) + ' for: ' + filename)\n sig1 = sound[:0] #left channel\n pre_emphasis = 0.97\n sig1 = np.append(sig1[0], sig1[1:] - pre_emphasis * sig1[:-1])\n\n \n fs2, sig2 = downsample(sig1,fs1,q)\n N2 = len(sig2)\n sig3 = sig2[N2//2-length:N2//2+length]\n #print(len(sig3))\n\n FFT = abs(scipy.fft(sig3))\n FFT_side = FFT[range(len(FFT)//2)]\n #freqs = scipy.fftpack.fftfreq(sig3.size, 1/fs2)\n #plt.plot(freqs,FFT)\n if len(FFT_side) != length:\n print('ERROR MESSAGE DETAILS')\n print('filename: ' + filename)\n print('length = ' + str(length))\n print('fs_in = ' + str(fs_in))\n print('q = ' + str(q))\n print('divide = ' + str(divide))\n total_time = len(sig1)/fs1\n print('total_time = ' + str(total_time))\n print('Please check: length < total_time*fs//(2*q)')\n print('Check: ' + str(length) + ' < ' + str(total_time*fs1//(2*q)))\n raise ValueError('Length FFT_side != length: ' + str(len(FFT_side)) + ' != ' + str(length))\n \n \n FFT_log = []\n # normalize FFT\n for value in FFT_side:\n value = np.log(value)\n FFT_log.append(value)\n max_val = getMax(FFT_log)[1]\n FFT_norm = []\n for value in FFT_log:\n FFT_norm.append(value/max_val)\n \n \n FFT_side = np.array(FFT_norm)\n FFT_divided = FFT_side[range(length//divide)]\n #plot = True\n if plot == True:\n freqs = scipy.fftpack.fftfreq(sig3.size, 1/fs2)\n freqs_divided = np.array(freqs[range(len(FFT_divided))])\n plt.plot(freqs_divided,FFT_divided) # plotting the complete fft spectrum\n plt.show()\n \n return FFT_divided","def t6_loadFile(self):\n print \"subspectrumFile\"\n filename = tkFileDialog.askopenfilename()\n filename = \"SubSpectrumData/\" + self.filenameparser(filename)\n self.t6_filename = filename","def get_files(file_list, mode):\n\tfile_set = set(file_list)\n\tif \"band\" in mode:\n\t\tband_all_set = set([\"bands.dat.gnu\", \"freq.plot\"])\n\t\tband_file_set = file_set & band_all_set ; remain_file_set = file_set - band_all_set\n\t\tfiles_str = \", \".join([f\"\\033[32m{b}\\033[0m\" for b in band_file_set]) + \"; \" + \", \".join(remain_file_set)\n\tif mode == \"dos\":\n\t\tdos_all_set = set([\"S.dos\"])\n\t\tdos_file_set = file_set & dos_all_set ; remain_file_set = file_set - dos_all_set\n\t\tfiles_str = \", \".join([f\"\\033[32m{d}\\033[0m\" for d in dos_file_set]) + \"; \" + \", \".join(remain_file_set)\n\tprint(f\"Files in the directory: {files_str}\"); file = input(\"Please choose your file (type one only): \")\n\treturn file","def load_time_streams(self, channels=None):\n if channels is None:\n channels = self.get_channels()\n\n if self.data is None:\n self.make_temp_data(channels=channels)\n elif self.data.shape[0] != channels.size:\n self.discard_temp_data()\n self.make_temp_data(channels=channels)\n\n frames = self.integration.frames\n fnf.load_timestream(\n frame_data=frames.data,\n frame_weights=frames.relative_weight,\n frame_valid=frames.valid,\n modeling_frames=frames.is_flagged('MODELING_FLAGS'),\n channel_indices=channels.indices,\n sample_flags=frames.sample_flag,\n timestream=self.data,\n points=self.points)","def read_inputs(self):\n curdir = os.getcwd()\n os.chdir(self.fst_dir)\n rstat = self.readFST()\n if rstat == 0:\n os.chdir(curdir)\n return 0\n # the names of the next files are either set by caller or come from the reading the FAST file\n rstat = self.readNoise()\n rstat = self.readAD()\n rstat = self.readBlade()\n rstat = self.readPtfm()\n os.chdir(curdir)","def get_per_lib_sff_fps(sff_dir):\r\n for dirpath, dirnames, fnames in walk(sff_dir):\r\n for fname in fnames:\r\n if fname.endswith('.sff'):\r\n libname, _ = splitext(fname)\r\n yield libname, join(dirpath, fname)","def get_audio():\n\tbuf = None\n\tnum_new_bytes = BUFFER_SIZE // REFRESH_BUFFER_FACTOR\n\twith open(INFILE) as fifo:\n\t\twhile True:\n\t\t\tif buf is None:\n\t\t\t\tbuf = fifo.read(BUFFER_SIZE)\n\t\t\telse:\n\t\t\t\tbuf = buf[num_new_bytes:] + fifo.read(num_new_bytes)\n\t\t\tyield buf","def t1_loadFile(self):\n print \"subspectrumFile\"\n filename = tkFileDialog.askopenfilename()\n filename = self.filenameparser(filename)\n self.t1_filename = filename","def _default_specs(self):\n # Spectrometer specs\n self.model = \"Flame-S\" # Spectrometer model\n self.fov = None # Field of view fo spectrometer\n self.ILS = None # Number array holding instrument line shape (possibly don't hold this here?)\n self.pix_num = 2048 # Number of pixels\n self.bit_depth = 16 # Bit depth of spectrometer detector\n\n # File information\n self.file_ext = '.npy' # Spectra saved as numpy array\n self.file_ss = '{}ss' # Shutter speed format spec\n self.file_spec_type = {'meas': 'Plume', 'dark': 'Dark', 'cal': 'ppmm', 'clear': 'Clear'}\n self.file_datestr = \"%Y-%m-%dT%H%M%S\" # Date/time format spec in filename\n\n\n\n # Acquisition settings\n self.start_int_time = 100 # Starting integration time\n self.start_coadd = 5 # Number of spectra to coadd\n self.framerate = 1 # Framerate of acquisitions (Hz)\n self.wavelengths = None # Wavelengths (nm)\n self.spectrum = None # Spectrum\n self.spectrum_filename = None # Filename for spectrum\n\n self.auto_int = True # Bool for requesting automated integration time adjustment\n self.min_saturation = 0.5 # Minimum saturation accepted before adjusting shutter speed (if auto_ss is True)\n self.max_saturation = 0.9 # Maximum saturation accepted before adjusting shutter speed (if auto_ss is True)\n self.saturation_range = [320, 330] # Range of wavelengths used in checking integration time\n\n # Predefined list of integration times for automatic exposure adjustment\n self.int_list = np.concatenate((np.arange(1, 10, 1),\n np.arange(10, 50, 5),\n np.arange(50, 100, 10),\n np.arange(100, 500, 50),\n np.arange(500, 1000, 100),\n np.arange(10 ** 3, 10 ** 4, 500),\n np.array([10 ** 4])))","def main():\r\n\r\n ### Choose and Import File\r\n\r\n inSound = Sound()\r\n\r\n rate = inSound.rate\r\n data = inSound.data\r\n dataLength = len(data)\r\n \r\n info = inSound.get_info()\r\n head, filename = os.path.split(info[0]) # get filename of input\r\n \r\n # Decide output directory and filename\r\n outDir = r'out'\r\n outFile = os.path.join(outDir, 'out_'+filename)\r\n\r\n # Check if data has multiple channels, if yes use only one\r\n if(len(data.shape) > 1):\r\n data = data[:,0]\r\n\r\n\r\n ### Set All Parameters\r\n\r\n #get parameters from user dialogue\r\n params = getParameters()\r\n\r\n numChannels = params['numChannels'][0] # number of Channels\r\n loFreq = params['loFreq'][0] # lower bound on frequencies\r\n hiFreq = params['hiFreq'][0] # upper bound on frequencies\r\n plotChannels = params['plotChannels'][0] # if it should plot the Gammatone channels\r\n block_time = params['block_time'][0] # in ms\r\n block_shift = params['block_shift'][0] # in ms\r\n selectChannels = params['selectChannels'][0] # number of channels to activate at a single time\r\n\r\n\r\n ### Filter input file\r\n\r\n filtered, channel_fs = filterDataGamaTone(data, rate, numChannels, loFreq, hiFreq, plotChannels)\r\n\r\n\r\n ### Gammatones -> Stimulation Amplitude for time block\r\n\r\n samples_in_block = np.floor(block_time * rate / 1000).astype('int')\r\n samples_in_shift = np.floor(block_shift * rate / 1000).astype('int')\r\n\r\n summed = gammatoneToAmplitude(filtered, samples_in_block, samples_in_shift)\r\n\r\n # only activate the n electrodes that have the largest stimulation\r\n amps = n_largest_channels(summed, n=selectChannels)\r\n\r\n \r\n #### Sound reconstruction\r\n\r\n # for each timeblock we need to duplicate enough samples to fill it at sample rate\r\n amps_samples = np.repeat(amps, samples_in_shift, axis=1)\r\n #trim end to get same length as input\r\n amps_samples = amps_samples[:,:dataLength] \r\n\r\n # from amplitude samples and frequencies, reconstruct sound\r\n res_data = generateSound(amps_samples, channel_fs, rate)\r\n\r\n\r\n ### Write to output file\r\n write(outFile, rate, res_data)\r\n print('Wrote file to: \\n' + outFile)","def get_frame_list(self):\r\n\r\n logger.debug('Executing frame extraction')\r\n\r\n frames_loaded = False\r\n\r\n # Try to load YAML file with frame list\r\n if os.path.exists(self.frames_file_path):\r\n\r\n print 'Loading YAML file with frame list'\r\n logger.debug('Loading YAML file with frame list')\r\n\r\n f_list = utils.load_YAML_file(self.frames_file_path)\r\n\r\n if f_list:\r\n self.frame_list = f_list\r\n\r\n print 'YAML file with frame_list loaded'\r\n logger.debug('YAML file with frame_list loaded')\r\n\r\n frames_loaded = True\r\n\r\n if not frames_loaded:\r\n\r\n print '\\n\\n### Frame extraction ###\\n'\r\n logger.debug('\\n\\n### Frame extraction ###\\n')\r\n\r\n # Save processing time\r\n start_time = cv2.getTickCount()\r\n\r\n if not (os.path.exists(self.frames_path)):\r\n os.makedirs(self.frames_path)\r\n\r\n # Counter for all frames\r\n frame_counter = 0\r\n\r\n # Value of frame_counter for last analyzed frame\r\n last_anal_frame = 0\r\n\r\n # Open video file\r\n capture = cv2.VideoCapture(self.resource_path)\r\n\r\n self.frame_list = []\r\n\r\n # Save parameters for this video\r\n param_dict = {}\r\n\r\n if capture is None or not capture.isOpened():\r\n\r\n error = 'Error in opening video file'\r\n\r\n print error\r\n logger.debug(error)\r\n\r\n return\r\n\r\n else:\r\n\r\n video_fps = capture.get(cv2.cv.CV_CAP_PROP_FPS)\r\n\r\n param_dict[c.VIDEO_FPS_KEY] = video_fps\r\n\r\n # Original number of frames\r\n tot_frames = capture.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT)\r\n\r\n param_dict[c.VIDEO_TOT_FRAMES_KEY] = tot_frames\r\n\r\n self.fps = video_fps\r\n\r\n self.video_frames = float(tot_frames)\r\n\r\n # Saved frames\r\n saved_frames = 0\r\n\r\n while True:\r\n\r\n # Read frame\r\n ret, frame = capture.read()\r\n\r\n # If no frame is read, abort\r\n if not ret:\r\n break\r\n\r\n used_fps = c.USED_FPS\r\n use_or_fps = c.USE_ORIGINAL_FPS\r\n use_or_res = c.USE_ORIGINAL_RES\r\n used_res_scale_factor = c.USED_RES_SCALE_FACTOR\r\n\r\n if self.params is not None:\r\n\r\n if c.USED_FPS_KEY in self.params:\r\n used_fps = self.params[c.USED_FPS_KEY]\r\n\r\n if c.USE_ORIGINAL_FPS_KEY in self.params:\r\n use_or_fps = self.params[c.USE_ORIGINAL_FPS_KEY]\r\n\r\n if c.USE_ORIGINAL_RES_KEY in self.params:\r\n use_or_res = self.params[c.USE_ORIGINAL_RES_KEY]\r\n\r\n if c.USED_RES_SCALE_FACTOR_KEY in self.params:\r\n used_res_scale_factor = self.params[\r\n c.USED_RES_SCALE_FACTOR_KEY]\r\n\r\n # Next frame to be analyzed\r\n next_frame = last_anal_frame + (video_fps / used_fps) - 1\r\n\r\n if use_or_fps or (frame_counter > next_frame):\r\n\r\n # Frame position in video in milliseconds\r\n elapsed_ms = capture.get(cv2.cv.CV_CAP_PROP_POS_MSEC)\r\n\r\n # print 'elapsed video s =', elapsed_video_s\r\n\r\n fr_name = '%07d.png' % frame_counter\r\n\r\n frame_path = os.path.join(self.frames_path, fr_name)\r\n\r\n # Resize frame\r\n if not use_or_res:\r\n fx = used_res_scale_factor\r\n\r\n fy = used_res_scale_factor\r\n\r\n interp = cv2.INTER_AREA\r\n\r\n frame = cv2.resize(src=frame, dsize=(0, 0),\r\n fx=fx, fy=fy,\r\n interpolation=interp)\r\n\r\n cv2.imwrite(frame_path, frame,\r\n [cv.CV_IMWRITE_PNG_COMPRESSION, 0])\r\n\r\n frame_dict = {c.SAVED_FRAME_NAME_KEY: fr_name,\r\n c.ELAPSED_VIDEO_TIME_KEY: int(elapsed_ms)}\r\n\r\n self.frame_list.append(frame_dict)\r\n\r\n last_anal_frame = frame_counter\r\n\r\n saved_frames += 1\r\n\r\n frame_counter += 1\r\n\r\n self.progress = 100 * (frame_counter / self.video_frames)\r\n\r\n print('progress: ' + str(self.progress) + ' % \\r'),\r\n\r\n del capture\r\n\r\n self.saved_frames = float(saved_frames)\r\n\r\n param_dict[c.VIDEO_SAVED_FRAMES_KEY] = self.saved_frames\r\n\r\n # Save frame list in YAML file\r\n utils.save_YAML_file(self.frames_file_path, self.frame_list)\r\n\r\n # Save video parameters in YAML file\r\n\r\n utils.save_YAML_file(self.params_file_path, param_dict)\r\n\r\n # Save processing time\r\n time_in_clocks = cv2.getTickCount() - start_time\r\n time_in_seconds = time_in_clocks / cv2.getTickFrequency()\r\n\r\n print 'Time for frame extraction:', str(time_in_seconds), 's\\n'\r\n logger.debug(\r\n 'Time for frame extraction:', str(time_in_seconds), 's\\n')\r\n\r\n self.anal_times[c.FRAME_EXTRACTION_TIME_KEY] = time_in_seconds\r\n\r\n utils.save_YAML_file(self.analysis_file_path, self.anal_times)","def split_into_frames(filename_raw, thr_var_per_event=5e-4, downsampling_factor=2, disable_display=False,\n filename_output_video=None):\n\n assert downsampling_factor == int(downsampling_factor), \"Error: downsampling_factor must be an integer\"\n assert downsampling_factor >= 0, \"Error: downsampling_factor must be >= 0\"\n\n mv_adaptive_rate_iterator = AdaptiveRateEventsIterator(input_path=filename_raw,\n thr_var_per_event=thr_var_per_event,\n downsampling_factor=downsampling_factor)\n\n height, width = mv_adaptive_rate_iterator.get_size()\n\n if filename_output_video == None:\n video_process = None\n else:\n assert not os.path.exists(filename_output_video)\n video_process = FFmpegWriter(filename_output_video)\n\n if video_process or not disable_display:\n img_bgr = np.zeros((height, width, 3), dtype=np.uint8)\n\n cv2.namedWindow(\"img\", cv2.WINDOW_NORMAL)\n\n for events in mv_adaptive_rate_iterator:\n assert events.size > 0\n start_ts = events[0][\"t\"]\n end_ts = events[-1][\"t\"]\n print(\"frame: {} -> {} delta_t: {} fps: {} nb_ev: {}\".format(start_ts, end_ts,\n end_ts - start_ts,\n 1e6 / (end_ts - start_ts),\n events.size))\n if video_process or not disable_display:\n img = events_to_diff_image(events, sensor_size=(height, width))\n img_bgr[...] = 0\n img_bgr[img < 0, 0] = 255\n img_bgr[img > 0, 1] = 255\n\n chunk_start_ts = events[0][\"t\"]\n chunk_end_ts = events[-1][\"t\"]\n delta_t_frame = chunk_end_ts - chunk_start_ts + 1\n frame_txt = \"ts: {} -> {} delta_t: {} fps: {} (nb_ev): {}\".format(chunk_start_ts, chunk_end_ts,\n delta_t_frame,\n int(1.e6/delta_t_frame),\n events.size)\n img_bgr[20:45, ...] = 0\n cv2.putText(img_bgr,\n frame_txt,\n (int(0.05 * width), 40),\n cv2.FONT_HERSHEY_PLAIN, 1.0, (200, 200, 100))\n\n if video_process:\n video_process.writeFrame(img_bgr.astype(np.uint8)[..., ::-1])\n if not disable_display:\n cv2.imshow(\"img\", img_bgr)\n if cv2.waitKey(1) & 0xFF == ord('q'):\n break\n\n if video_process:\n video_process.close()\n if not disable_display:\n cv2.destroyAllWindows()","def get_fps(vid_path, prefix):\n _, name = os.path.split(vid_path)\n i1 = name.find(prefix) + len(prefix)\n i2 = name[i1:].find('_')\n fps = int(name[i1:i1+i2])\n\n return fps","def load_batch(self, fpath, match, in_num):\n if in_num == None:\n in_num = input('Please specify IN number: ')\n\n if match == None:\n match = input('Please specify filename string to match for batch loading (ex. \\'_s2_\\'): ')\n\n # get a list of all matching files\n glob_match = f'{fpath}/*{match}*'\n files = glob.glob(glob_match)\n\n # load & concatenate files into a single dataframe\n data = pd.concat((pd.read_csv(file, header = [0, 1], index_col = 0, parse_dates=True, low_memory=False) for file in files)).sort_index()\n\n # extract sampling frequency\n s_freq = 1/(data.index[1] - data.index[0]).total_seconds()\n\n # reset the index to continuous time\n ind_freq = str(int(1/s_freq*1000000))+'us'\n ind_start = '1900-01-01 00:00:00.000'\n ind = pd.date_range(start = ind_start, periods=len(data), freq=ind_freq)\n data.index = ind\n\n # set metadata & attributes\n self.metadata = {'file_info':{'in_num': in_num, 'files': files, 'dir': fpath,\n 'match_phrase': match},\n 'analysis_info':{'s_freq': s_freq} }\n self.data = data\n self.s_freq = s_freq","def get_file_params(file_path):\n fpath, ftype = parse_path(file_path=file_path)\n\n if ftype == \"video\":\n volume, dims = get_video_params(video_path=fpath)\n else:\n volume, dims = get_image_params(image_path=fpath)\n\n return volume, dims","def FitsLookup(raw_filenames, config, config_arguments):\n\n warnings.filterwarnings('ignore')\n\n # Initialize the filelist and the progressbar variable smeantime and\n # total_len\n\n filelist = list()\n meantime = list()\n\n total_len = len(raw_filenames)\n\n # Loop over each file in raw_filenames getting the desired information\n\n for cont, filename in enumerate(raw_filenames):\n\n # Start the time measure\n start = time.time()\n\n # Get the file header\n header = fits.getheader(filename)\n\n # Extract the filetipe and classify it\n typestr = header[config.exposure_type]\n\n if typestr == config.science_type_id:\n img_type = 0\n elif typestr == config.dark_type_id or typestr == config.bias_type_id:\n img_type = 1\n elif typestr == config.flat_type_id:\n img_type = 2\n else:\n img_type = 3\n\n # Extract the filter\n\n filter = header[config.filter]\n\n # Extract the date and correct it with the time convention (night ->\n # 12:00 to 11:59)\n night = datetime.datetime.strptime(\n header[config.observed_date], config.date_format)\n\n if night.hour < 12:\n night = night.date() - datetime.timedelta(days=1)\n\n # Extract the exposure time\n\n exptime = header[config.expousure_time]\n\n # ---- HOW TO ADD MORE CLASSIFIERS TO THE RESULTING NUMPY ARRAY ------\n #\n # Using the header variable and the config_values dictionary you can\n # extract all the values from the file. For example, to extract the temp:\n #\n # >>> temp = header[config_values['temp']]\n #\n # Once you have your new variable, you have to add this to the filelist in\n # the code after this comment. For example, to add the temp in the previous-to-last\n # entry:\n #\n # >>> filelist.append((filename, type, filter, exptime, str(night), temp, header))\n #\n # Finally, you have to modify the numpy dtype. Following with our example, as the temp\n # is a float value, we can modify the dtype as:\n #\n # >>> dtype = np.dtype([('filename', 'S150'), ('type', int),\n # ('filter', 'S10'), ('exptime', int), ('night', 'S10'),\n # ('temp',float),('header', np.object)])\n #\n # Notice that the position of the new type in the dtype variable MUST match the position\n # in which you added your new variable to the filelist. As we added \"temp\" previous-to-last,\n # we have to add ('temp',float) in the position previous-to-last in the dtype.\n #\n # Now, you can use 'temp' for slicing, broadcasting and perform cool numpy stuff in the resulting\n # array. Also, this value will work in the filter_collection function.\n # Yay!\n\n # Append all the information to the filelist. MODIFY HERE IF NEEDED!\n\n filelist.append((filename, img_type, filter,\n exptime, str(night), header))\n\n # Update progress bar\n\n end = time.time()\n meantime.append(end - start)\n\n if config_arguments.verbose_flag and not config_arguments.no_interaction:\n update_progress(float(cont + 1) / total_len,\n np.mean(meantime) * (total_len - (cont + 1)))\n\n # Create the personalized dtype of the numpy array. MODIFY HERE IF NEEDED!\n\n dtype = np.dtype([('filename', 'S150'), ('type', int),\n ('filter', 'S10'), ('exptime', int), ('night', 'S10'), ('header', np.object)])\n\n return np.array(filelist, dtype=dtype)","def read_file(self, *args, **kwargs):\n if self.detector == \"FACET\":\n return self.read_facet(self.filename)\n elif self.detector == \"OpenFace\":\n return self.read_openface(self.filename)\n elif self.detector == \"Affectiva\":\n return self.read_affectiva(self.filename)\n elif self.detector == \"Feat\":\n return self.read_feat(self.filename)\n else:\n print(\"Must specifiy which detector [Feat, FACET, OpenFace, or Affectiva]\")","def get_sorted_fps_U(data_dir, max = 988):\n\n fps = os.listdir(data_dir)\n\n #extract index of timestep from file name\n idx_fps = []\n for fp in fps:\n _, file_number = fp.split(\"LSBU_\")\n #file_number is of form '<IDX>.vtu'\n idx = int(file_number.replace(\".vtu\", \"\"))\n idx_fps.append(idx)\n\n\n #sort by timestep\n assert len(idx_fps) == len(fps)\n zipped_pairs = zip(idx_fps, fps)\n fps_sorted = [x for _, x in sorted(zipped_pairs)]\n\n #add absolute path\n fps_sorted = [data_dir + x for x in fps_sorted]\n\n return fps_sorted","def gen_random_samples():\n if os.path.exists('Song_Samples'):\n pass\n else:\n os.mkdir('Song_Samples')\n for filename in os.listdir(\"Songs\"):\n rate, data = wavfile.read(os.path.join(\"Songs\", filename))\n song_duration = len(data) // rate\n start_point = randint(0, song_duration - SAMPLE_DURATION)\n end_point = start_point + SAMPLE_DURATION\n subprocess.call(['ffmpeg', '-i', os.path.join(\"Songs\", filename),\n '-ss', str(datetime.timedelta(seconds=start_point)), '-to',\n str(datetime.timedelta(seconds=end_point)), '-y', os.path.join(\"Song_Samples\", filename)])","def listfile(self):\n print(\"Opened file(s):\")\n for f in self.fmap:\n print('\\t%s'%(self.files.index(self.fmap[f])),end=':')\n print(f)\n print(\"active file(s):\")\n for i in range(len(self.handle)):\n print('\\t%s'%(self.handle[i]),end=':')\n print(self.fname[i])","def analyzeWAV(inputFile):\n data, fs, nbits = audiolab.wavread(inputFile)\n samplingRate = fs\n return [data, samplingRate]","def get_file_parameters(self, input_file):\n\n #\n # Read the Flag record.\n #\n input_file.seek(0, 0) # 0 = from start of file\n record = input_file.read(FLAG_RECORD_SIZE)\n\n #\n # Check for end of file.\n # If not reached, check for and parse a Flag record.\n #\n if len(record) != FLAG_RECORD_SIZE:\n log.warn(\"EOF reading for flag record\")\n raise SampleException(\"EOF reading for flag record\")\n \n (valid_record, regex_velocity_record, \n regex_end_velocity_record, format_unpack_velocity, \n record_size) = self.parse_flag_record(record)\n\n #\n # If there is a valid Flag record, process the Time record.\n #\n if valid_record:\n #\n # Read the Time record which is at the very end of the file.\n # Note that we don't care if the number of bytes between the\n # Flag record and the Time record is consistent with\n # the flags from the Flag record.\n # Put the file back at the beginning.\n #\n input_file.seek(0 - TIME_RECORD_SIZE, 2) # 2 = from end of file\n record = input_file.read(TIME_RECORD_SIZE)\n times = self.parse_time_record(record)\n input_file.seek(0, 0) # 0 = from start of file\n\n #\n # If the Flag record is invalid, we're done.\n #\n else:\n log.warn(\"Invalid Flag record\")\n raise SampleException(\"Invalid Flag record\")\n\n return valid_record, regex_velocity_record, regex_end_velocity_record, \\\n format_unpack_velocity, record_size, times","def stream_callback(self, in_data, frame_count, time_info, status_flags):\n time_delta = time.time() - self.last_frame_timestamp\n if time_delta == 0:\n time_delta = sys.float_info.min\n fps = int(1.0 / time_delta)\n self.last_frame_timestamp = time.time()\n if DEBUG:\n self.fps_deque.append(fps)\n avg_fps = 0\n for frame_fps in self.fps_deque:\n avg_fps += frame_fps\n avg_fps /= len(self.fps_deque)\n self.log_fps(self.last_frame_timestamp, fps)\n sys.stdout.write(\"\\r{} FPS\".format(avg_fps))\n sys.stdout.flush()\n self.data = np.frombuffer(in_data, dtype=np.float32)\n if self.binned:\n self.binned_fft()\n self.fft_callback(self.fft_bins_y)\n else:\n self.fft()\n self.fft_callback(self.spec_y)\n if self.send_osc:\n self.send_fft_osc()\n return (None, pyaudio.paContinue)"],"string":"[\n \"def read_data_samples(fp):\\n if(path.isdir(fp)):\\n fps = glob.glob(fp + '\\\\\\\\*.txt')\\n return list(map(lambda x: read_file(x), fps))\",\n \"def get_file_list(mixer_file, select_random, use_list_of_files):\\n logger = logging.getLogger(get_file_list.__name__)\\n files = list()\\n\\n if use_list_of_files:\\n with open(mixer_file, 'r') as list_file:\\n for line in list_file:\\n files.append(os.path.join('data/raw',line.strip()))\\n\\n if select_random:\\n random.shuffle(files)\\n\\n else:\\n\\n mixer = parse_mixer_file(mixer_file)\\n\\n for m in mixer:\\n path = os.path.join(project_dir, m[0])\\n all_mixer_files = [os.path.join(path,f) for f in os.listdir(path) \\n if os.path.isfile(os.path.join(path, f)) and f.split('.')[-1] == 'csv']\\n\\n current_files = list()\\n # Check if the number of samples is limited\\n if m[2] >= 0:\\n sample_count = 0\\n for f in all_mixer_files:\\n # Get number of lines without the header line\\n num_lines = sum(1 for line in open(f)) - 1\\n\\n if (sample_count + num_lines) > m[2]:\\n current_files.append((f, m[2] - sample_count))\\n sample_count += (m[2] - sample_count)\\n break\\n else:\\n current_files.append((f, -1))\\n sample_count += num_lines\\n\\n if sample_count < m[2]:\\n logger.warn('Not enough samples ({} < {}): {}'.format(sample_count, m[2], m[0]))\\n else:\\n # No limit, take all samples in the files\\n current_files = zip(all_mixer_files, [-1]*len(all_mixer_files))\\n\\n if m[1] < 0:\\n # -1 means all .csv files\\n files += current_files\\n elif m[1] > 0:\\n if m[1] > len(current_files):\\n logger.warn('Not enough files ({} < {}): {}'.format(len(current_files),\\n m[1], m[0]))\\n files += current_files[:m[1]]\\n\\n if select_random:\\n random.shuffle(files)\\n else:\\n files = sorted(files, key=lambda x: int(os.path.basename(x[0]).split('_')[-1].split('.')[0]))\\n\\n return files\",\n \"def main(_):\\n print('argument to expand', ARGS.video_in)\\n print('argument expanded', glob.glob(ARGS.video_in))\\n video_count = 0\\n for video_filename in glob.glob(ARGS.video_in):\\n print('start parsing', video_filename)\\n data = skvideo.io.ffprobe(video_filename)['video']\\n rate_str = six.ensure_str(data['@r_frame_rate']).split('/')\\n rate = float(rate_str[0]) / float(rate_str[1])\\n print('detected frame rate:', rate)\\n\\n print('load frames:')\\n video = skvideo.io.vreader(video_filename)\\n frame_count = 0\\n file_count = 0\\n for frame in video:\\n if (frame_count > ARGS.offset) and \\\\\\n ((frame_count-ARGS.offset)%ARGS.skip == 0) and \\\\\\n (frame_count/rate >= ARGS.from_s) and \\\\\\n (frame_count/rate <= ARGS.to_s or ARGS.to_s == -1):\\n print(frame_count,)\\n img = Image.fromarray(frame)\\n if ARGS.crop:\\n img = crop(img, ARGS.size)\\n # save file\\n file_number = file_count + video_count * ARGS.multiple + ARGS.start\\n if ARGS.format_ext.lower() == 'jpg':\\n file_out = os.path.join(ARGS.path_out,\\n 'f{:07d}.jpg'.format(file_number))\\n img.save(file_out, 'JPEG')\\n elif ARGS.format_ext.lower() == 'png':\\n file_out = os.path.join(ARGS.path_out,\\n 'f{:07d}.png'.format(file_number))\\n img.save(file_out, 'PNG')\\n else:\\n print('unrecognize format', ARGS.format_ext)\\n sys.exit()\\n file_count += 1\\n frame_count += 1\\n video_count += 1\",\n \"def get_file_bpm(path, params = {}):\\n try:\\n win_s = params['win_s']\\n samplerate = params['samplerate']\\n hop_s = params['hop_s']\\n except:\\n \\\"\\\"\\\"\\n # super fast\\n samplerate, win_s, hop_s = 4000, 128, 64 \\n # fast\\n samplerate, win_s, hop_s = 8000, 512, 128\\n \\\"\\\"\\\"\\n # default:\\n samplerate, win_s, hop_s = 44100, 1024, 512\\n\\n s = source(path, samplerate, hop_s)\\n samplerate = s.samplerate\\n o = tempo(\\\"specdiff\\\", win_s, hop_s, samplerate)\\n # List of beats, in samples\\n beats = []\\n # Total number of frames read\\n total_frames = 0\\n\\n while True:\\n samples, read = s()\\n is_beat = o(samples)\\n if is_beat:\\n this_beat = o.get_last_s()\\n beats.append(this_beat)\\n #if o.get_confidence() > .2 and len(beats) > 2.:\\n # break\\n total_frames += read\\n if read < hop_s:\\n break\\n\\n # Convert to periods and to bpm \\n bpms = 60./diff(beats)\\n b = median(bpms)\\n return b\",\n \"def read(ftype, inDir, inSuffix, startTime, endTime):\\n\\n\\tif ftype == 'ryan': return readRyan(inDir, inSuffix, startTime, endTime)\\t\\n\\telif ftype == 'segmotion': return readSegmotion(inDir, inSuffix, startTime, endTime)\\n\\telif ftype == 'probsevere': return readProbSevere(inDir, inSuffix, startTime, endTime)\",\n \"def seqIo_frImgs(fName, header=[], aviName=[], Is=[], sDir=[], name='I', ndig=5, f0=0, f1=1e6):\\n \\n if aviName!=[]: #avi movie exists\\n vc = cv2.VideoCapture(aviName)\\n if vc.isOpened(): rval = True\\n else:\\n rval = False\\n print('video not readable')\\n return\\n fps = vc.get(cv2.cv.CV_CAP_PROP_FPS)\\n NUM_FRAMES = int(vc.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT))\\n print(NUM_FRAMES)\\n IM_TOP_H = vc.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)\\n IM_TOP_W = vc.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)\\n header['width']=IM_TOP_W\\n header['height']=IM_TOP_H\\n header['fps']=fps\\n\\n sw = seqIo_writer(fName,header)\\n print('creating seq from AVI')\\n # initialize timer\\n timer = pb.ProgressBar(widgets=['Converting ', pb.Percentage(), ' -- ',\\n pb.FormatLabel('Frame %(value)d'), '/',\\n pb.FormatLabel('%(max)d'), ' [', pb.Timer(), '] ',\\n pb.Bar(), ' (', pb.ETA(), ') '], maxval=NUM_FRAMES)\\n for f in range(NUM_FRAMES):\\n rval, im = vc.read()\\n if rval:\\n im= im.astype(np.uint8)\\n sw.addFrame(im)\\n timer.update(f)\\n sw.close()\\n timer.finish()\\n elif Is==[]:\\n assert(os.path.isdir(sDir))\\n sw = seqIo_writer(fName,header)\\n frmstr = '%s/%s%%0%ii.%s' % (sDir,name,ndig,header.ext)\\n for frame in range(f0,f1):\\n f = frmstr % frame\\n if not os.path.isfile(f):break\\n fid = open(f, 'r')\\n if fid<0: sw.close(); assert(False)\\n I = fid.read()\\n fid.close()\\n b = bytearray(I)\\n assert (b[0] == 255 and b[1] == 216 and b[-2] == 255 and b[-1] == 217); # JPG\\n I = np.array(list(b)).astype(np.uint8)\\n sw.addFrame(I,0,0)\\n sw.close()\\n if frame==f0: print('No images found')\\n else:\\n nd = len(Is.shape)\\n if nd==2: nd=3\\n assert(nd<=4)\\n nFrm = Is.shape[nd-1]\\n header['height']=Is.shape[0]\\n header['width']=Is.shape[1]\\n sw =seqIo_writer(fName,header)\\n if nd==3:\\n for f in range(nFrm): sw.addFrame(Is[:,:,f])\\n if nd==4:\\n for f in range(nFrm): sw.addFrame(Is[:,:,:,f])\\n sw.close()\",\n \"def videoFrames(filename, framerate=1):\\n vid_file = os.path.join(os.path.dirname(os.getcwd()), \\\"Database\\\", \\\"Video\\\", filename)\\n print(vid_file)\\n assert os.path.isfile(vid_file), \\\"Given path is not a valid file\\\"\\n tmpdir = os.path.join(os.getcwd(), \\\"tmp\\\")\\n subprocess.run(\\n [\\n \\\"ffmpeg\\\",\\n \\\"-i\\\",\\n vid_file,\\n \\\"-r\\\",\\n f\\\"{framerate}\\\",\\n os.path.join(tmpdir, \\\"img_%04d.jpg\\\"),\\n ]\\n )\\n return [os.path.join(tmpdir, i) for i in os.listdir(tmpdir) if not i.endswith(\\\".wav\\\")]\",\n \"def get_filenames(b,X,timefac,BW):\\r\\n\\tn = int(200000*X*timefac); nn = int(200000*X*10)\\r\\n\\troot = \\\"./dat_LE_stream/\\\"\\r\\n\\trootL = 'C:/AsusWebStorage/MySyncData/TRAFILES/'\\r\\n\\tpodir = \\\"/b=\\\"+str(b)+\\\"/\\\" if BW else \\\"/HO/\\\"\\r\\n\\t\\r\\n\\ttrafile = rootL+\\\"TRA_BW_b\\\"+str(b)+\\\"X\\\"+str(int(X))+\\\"n\\\"+str(nn)+\\\"seed65438\\\"\\r\\n\\tif not os.path.isfile(trafile):\\r\\n\\t\\ttrafile = rootL+\\\"TRA_BW_b\\\"+str(b)+\\\"X\\\"+str(int(X))+\\\"n\\\"+str(n)+\\\"seed65438\\\"\\r\\n\\toutfile = root+podir+os.path.split(trafile)[1][4:]\\r\\n\\t\\r\\n\\trndfile = os.path.split(outfile)[0]+\\\"/RND_\\\"+os.path.split(outfile)[1]+\\\".png\\\"\\r\\n\\tpdffile = os.path.split(outfile)[0]+\\\"/PDF_\\\"+os.path.split(outfile)[1]\\r\\n\\tstrfile = os.path.split(outfile)[0]+\\\"/STR_\\\"+os.path.split(outfile)[1]\\r\\n\\t\\r\\n\\treturn trafile,rndfile,pdffile,strfile,n\",\n \"def gen_fps():\\n global data_src ,output_dir \\n logger = TaskFileLogger(\\\"GenFP\\\")\\n\\n h_vars = load_hydro_var()\\n if not os.path.exists(output_dir):\\n os.mkdir(output_dir)\\n\\n for h_type,var_d in h_vars.items():\\n print \\\"considering %s\\\" %h_type\\n\\n t_output_dir = os.path.join(output_dir,h_type)\\n if not os.path.exists(t_output_dir):\\n print \\\"creating path %s\\\" %t_output_dir\\n os.mkdir(t_output_dir)\\n logger.log(\\\"%s started\\\" %(h_type))\\n\\n for fname in glob.glob(data_src):\\n complex_id = os.path.basename(fname).split('.')[0] \\n fp_path = os.path.join(t_output_dir,complex_id + \\\".fp\\\" )\\n if os.path.exists(fp_path):\\n #print \\\"%s processed\\\" %complex_id\\n continue\\n print \\\"processing %s,fp saved as %s\\\" %(fname , fp_path )\\n c = Complex(fname,hydro_dict = var_d)\\n c.get_fp()\\n c.write_fp_to_file(fp_path)\\n\\n logger.log(\\\"%s finished\\\" %(h_type))\",\n \"def return_file_read(_):\\n return [\\\"scorevideo LOG\\\", \\\"File: log.mat\\\"]\",\n \"def __init__(self, inFile = None, inData = None, inRate = None):\\n \\n # Information about FFMPEG\\n self.ffmpeg_info = FFMPEG_info()\\n \\n if inData is not None:\\n if inRate is None:\\n print('Set the \\\"rate\\\" to the default value (8012 Hz).')\\n rate = 8012.0\\n self.generate_sound(inData, inRate)\\n else: \\n if inFile is None:\\n inFile = self._selectInput()\\n if inFile == 0:\\n return\\n try:\\n self.source = inFile\\n self.read_sound(self.source)\\n except FileNotFoundError as err:\\n print(err)\\n inFile = self._selectInput()\\n self.source = inFile\\n self.read_sound(self.source)\",\n \"def generate_readers(\\n viddir, camname, minopt=0, maxopt=300000, pathonly=False, extension=\\\".mp4\\\"\\n):\\n out = {}\\n mp4files = [\\n os.path.join(camname, f)\\n for f in os.listdir(os.path.join(viddir, camname))\\n if extension in f\\n and int(f.rsplit(extension)[0]) <= maxopt\\n and int(f.rsplit(extension)[0]) >= minopt\\n ]\\n\\n # This is a trick (that should work) for getting rid of\\n # awkward sub-directory folder names when they are being used\\n mp4files_scrub = [\\n os.path.join(\\n os.path.normpath(f).split(os.sep)[0], os.path.normpath(f).split(os.sep)[-1]\\n )\\n for f in mp4files\\n ]\\n\\n pixelformat = \\\"yuv420p\\\"\\n input_params = []\\n output_params = []\\n\\n for i in range(len(mp4files)):\\n if pathonly:\\n out[mp4files_scrub[i]] = os.path.join(viddir, mp4files[i])\\n else:\\n print(\\n \\\"NOTE: Ignoring {} files numbered above {}\\\".format(extensions, maxopt)\\n )\\n out[mp4files_scrub[i]] = imageio.get_reader(\\n os.path.join(viddir, mp4files[i]),\\n pixelformat=pixelformat,\\n input_params=input_params,\\n output_params=output_params,\\n )\\n\\n return out\",\n \"def framerate(self):\\n return self.config.get('framerate', 15)\",\n \"def OpenSoundFiles():\\n\\n wildcard = create_wildcard(\\\"Sound files\\\", sppas.src.audiodata.aio.extensionsul)\\n wildcard += '|' + create_wildcard(\\\"All files\\\", ['*', '*.*'])\\n\\n files = list()\\n dlg = wx.FileDialog(None, \\n \\\"Select sound file(s)\\\", \\n paths.samples, \\n \\\"\\\", \\n wildcard, \\n wx.FD_OPEN | wx.MULTIPLE | wx.FD_CHANGE_DIR)\\n if dlg.ShowModal() == wx.ID_OK:\\n files = dlg.GetPaths()\\n\\n dlg.Destroy()\\n\\n return files\",\n \"def _settings(filename):\\n\\n with open(filename, 'r') as datafile:\\n daq_type = datafile.readline().strip().split(',')[1]\\n sample_hz = int(datafile.readline().strip().split(',')[1])\\n channels = datafile.readline().strip().split(',')\\n return (daq_type, sample_hz, channels)\",\n \"def read_local_20Hz_files(**kwargs):\\n pathlst = kwargs.get('pathlst')\\n product = kwargs.get('product')\\n varalias = kwargs.get('varalias')\\n sdate = kwargs.get('sdate')\\n edate = kwargs.get('edate')\\n twin = kwargs.get('twin')\\n\\n # establish coords if defined in config file\\n timestr = satellite_dict[product]['vardef']['time']\\n lonstr = satellite_dict[product]['vardef']['lons']\\n latstr = satellite_dict[product]['vardef']['lats']\\n\\n # adjust start and end\\n sdate = sdate - timedelta(minutes=twin)\\n edate = edate + timedelta(minutes=twin)\\n # get meta data\\n ncmeta = ncdumpMeta(pathlst[0])\\n ncvar = get_filevarname(varalias, variable_info,\\n satellite_dict[product], ncmeta)\\n # retrieve sliced data\\n ds = read_netcdfs(pathlst)\\n ds_sort = ds.sortby(timestr)\\n\\n # get indices for included time period\\n nptime = ds_sort[timestr].data\\n print('here0')\\n print(len(nptime))\\n #dtime = [parse_date(str(nptime[i])) for i in range(len(nptime))]\\n print('here1')\\n #idx = find_included_times_pd(dtime, sdate=sdate, edate=edate)\\n idx = find_included_times_pd(nptime, sdate=sdate, edate=edate)\\n print(len(nptime[idx]))\\n print('here2')\\n dtime = [parse_date(str(nptime[idx][i])) for i in range(len(nptime[idx]))]\\n print(dtime)\\n print('here3')\\n #dtime = list(np.array(dtime)[idx])\\n lons = list(((ds_sort[lonstr].data[idx] - 180) % 360) - 180)\\n lats = list(ds_sort[latstr].data[idx])\\n\\n unxt = (nptime[idx].astype(int) / 10**9)\\n\\n # make dict and start with stdvarname for varalias\\n stdvarname = variable_info[varalias]['standard_name']\\n vardict = {}\\n vardict[stdvarname] = list(ds_sort[ncvar].data[idx])\\n vardict['longitude'] = lons\\n vardict['latitude'] = lats\\n vardict['time'] = unxt\\n vardict['datetime'] = dtime\\n vardict['time_unit'] = variable_info['time']['units']\\n print(vardict.keys())\\n return vardict\",\n \"def readNextGenSpectrum(fname=''):\\n\\n print('Reading : ', fname)\\n\\n with open(fname, 'r') as rfile:\\n dum = rfile.readline()\\n sdum = dum.split()\\n teff = float(sdum[0])\\n logg = float(sdum[1])\\n mph = float(sdum[2])\\n dum = rfile.readline()\\n nwav = float(dum.split()[0])\\n\\n bigline = []\\n dum = rfile.readline()\\n while dum.strip() != '':\\n sdum = dum.split()\\n for i in range(len(sdum)):\\n bigline.append(float(sdum[i]))\\n dum = rfile.readline()\\n\\n bigline = np.array(bigline)\\n # Convert wavelength from angstrom to micron\\n wav = bigline[:nwav] / 1e4\\n inu = bigline[nwav:2 * nwav]\\n bnu = bigline[nwav * 2:nwav * 3]\\n\\n ii = wav.argsort()\\n wav = wav[ii]\\n inu = inu[ii] * 1e-8 * wav * 1e4 / np.pi / (29979245800.0 / wav * 1e4)\\n bnu = bnu[ii] * 1e-8 * wav * 1e4 / np.pi / (29979245800.0 / wav * 1e4)\\n\\n #\\n # The unit is now erg/s/cm/Hz/ster\\n #\\n\\n return {'teff': teff, 'logg': logg, 'mph': mph, 'nwav': nwav, 'wav': wav, 'inu': inu, 'bnu': bnu}\",\n \"def file_info(file_name, file_pattern):\\n match = re.compile(file_pattern).match(file_name)\\n if match:\\n basepath = match.group('basepath')\\n sensor = match.group('sensor')\\n ax = match.group('ax')\\n freq = match.group('freq')\\n date = match.group('date')\\n return basepath, sensor, ax, freq, date\\n else:\\n return None # there is no file extension to file_name\",\n \"def do_f(self, parms):\\n\\t\\tprint self.files\",\n \"def _read_config_file(self):\\n wcec = 0\\n deadline = 0\\n jitter = 0\\n init_freq = 0\\n freqs_volt = {}\\n freqs = []\\n volts = []\\n config_file_name = self._find_file('sim_simple.config')\\n with open(config_file_name, 'rU') as f:\\n lines = f.readlines()\\n try:\\n for freq in lines[0].split():\\n freqs.append(float(freq))\\n\\n for volt in lines[1].split():\\n volts.append(float(volt))\\n\\n for i in range(0, len(freqs)):\\n freqs_volt[freqs[i]] = volts[i]\\n\\n data = lines[2].split()\\n wcec = float(data[0])\\n deadline = float(data[1])\\n period = float(data[2])\\n jitter = float(data[3])\\n init_freq = float(data[4])\\n except ValueError, IndexError:\\n print 'Invalid data in config file'\\n sys.exit(1)\\n\\n return wcec, deadline, period, jitter, init_freq, freqs_volt\",\n \"def readPlayerImageFiles(self):\\n currentPath = os.path.dirname(os.path.abspath(__file__))\\n listOfFileNames=[]\\n for i in os.listdir(currentPath):\\n if re.match(\\\"player\\\\_\\\\d+\\\",i): #i.endswith(\\\".gif\\\")\\n listOfFileNames.append(currentPath+'/'+i)\\n return listOfFileNames\",\n \"def fillFileList(self, dirName):\\n if not os.path.isdir(dirName):\\n print(\\\"Warning: directory doesn't exist\\\")\\n return\\n\\n self.listFiles.fill(dirName, fileName=None, readFmt=True, addWavNum=True, recursive=True)\\n\\n # while reading the file, we also collected a list of species present there\\n spList = list(self.listFiles.spList)\\n # and sample rate info\\n fs = list(self.listFiles.fsList)\\n\\n if len(fs)==0:\\n print(\\\"Warning: no suitable files found\\\")\\n return\\n\\n # might need better limits on selectable sample rate here\\n self.fs.setValue(int(np.min(fs)))\\n self.fs.setRange(4000, int(np.max(fs)))\\n self.fs.setSingleStep(4000)\\n self.fs.setTickInterval(4000)\\n\\n spList.insert(0, 'Choose species...')\\n self.species.clear()\\n self.species.addItems(spList)\\n if len(spList)==2:\\n self.species.setCurrentIndex(1)\",\n \"def _open_stream(config):\\n p = pyaudio.PyAudio()\\n stream = p.open(\\n format = config[\\\"format\\\"],\\n channels = config[\\\"channels\\\"],\\n rate = config[\\\"rate\\\"],\\n input = True,\\n frames_per_buffer = config[\\\"chunk\\\"]\\n )\\n return p, stream\",\n \"def filesample(filename):\\n sampling_rate, samples = wavfile.read(filename)\\n times = np.arange(len(samples)) / sampling_rate\\n return samples, sampling_rate\",\n \"def get_frame_rate(filename):\\n cmd = ('ffprobe -v 0 -of flat=s=_ -select_streams v:0 -show_entries '\\n 'stream=avg_frame_rate -of default=nokey=1:noprint_wrappers=1 ' +\\n filename).split()\\n pid = subprocess.run(cmd, stdout=subprocess.PIPE,\\n universal_newlines=True)\\n if pid.returncode != 0:\\n return None\\n\\n frame_rate_exp = pid.stdout.rstrip()\\n try:\\n frame_rate = float(frame_rate_exp)\\n except:\\n if frame_rate_exp == 'N/A':\\n frame_rate = 0.\\n else:\\n numerator, denominator = map(float, frame_rate_exp.split('/'))\\n if denominator == 0:\\n frame_rate = 0\\n else:\\n frame_rate = numerator / denominator\\n return frame_rate\",\n \"def find_files(config, slot='*'):\\n f_pattern = os.path.join(os.path.join(config['path'],config['led_name']), slot+'*' + config['led_name'] + '*'\\n + config['current'] + '*' + config['exp_time'] + '*'\\n + config['xpos'] + '*' + config['ypos'] + '*')\\n print(f_pattern)\\n return glob.glob(f_pattern)\",\n \"def files_sim(config):\\n file_sim = sorted(glob.glob(config['str_dir'] + '/simulation/' +\\n '{}/{}nm/txt_files/*.txt'.format(\\n config['date'], config['wavelength'])))\\n return file_sim\",\n \"def get_frame_by_frame(name=None, fps=4, write_to_disk=False, display_feed=False, on_capture=None):\\n\\n reset_camera()\\n\\n if name is None:\\n name = \\\"fbf_\\\" + str(int(time()))\\n \\n dname = None\\n if write_to_disk:\\n chdir(cwd)\\n dname = join(dirname(realpath(sys.argv[0])), \\\"train\\\", \\\"data\\\", name)\\n if not exists(dname):\\n print(\\\"Created dir: %s\\\" % dname)\\n mkdir(dname)\\n else:\\n print(\\\"Using dir: %s\\\" % dname)\\n else:\\n print('Not writing to disk')\\n\\n def _snap(name, dname, write, display, capture_callback):\\n global camera\\n s, img = camera.read()\\n\\n if s and capture_callback:\\n img = capture_callback(img)\\n\\n if s and display:\\n cv2.imshow(name, img)\\n cv2.waitKey(1) \\n\\n if write:\\n chdir(dname)\\n number_of_files = len([item for item in os.listdir(dname) if os.path.isfile(os.path.join(dname, item))])\\n path = \\\"./\\\" + str(number_of_files + 1) + \\\".png\\\"\\n if s:\\n imwrite(path, img)\\n print(\\\"Saved to \\\" + dname + \\\"/\\\" + str(number_of_files + 1) + \\\".png\\\")\\n else:\\n print(\\\"Could not read image %d from camera\\\" % (number_of_files + 1))\\n chdir(cwd)\\n\\n return Timer(1 / fps, _snap, name, dname, write_to_disk, display_feed, on_capture).use_mp()\",\n \"def read_xyz(filename, freq):\\n\\n\\n#xyz file\\n\\n Atoms = []\\n Coordinates = []\\n\\n xyz = open(filename)\\n frame = 0\\n while True:\\n\\n n_atoms = xyz.readline()\\n\\n if n_atoms == '':\\n break\\n else:\\n n_atoms = int(n_atoms)\\n title = xyz.readline()\\n\\n if frame%freq==0:\\n atoms, coordinates = read_frame(xyz, n_atoms)\\n Coordinates.append(coordinates)\\n Atoms.append(atoms)\\n\\n else:\\n read_frame(xyz, n_atoms)\\n frame+=1\\n\\n return Atoms, Coordinates\",\n \"def readAudioFile(path):\\n\\n extension = os.path.splitext(path)[1]\\n\\n try:\\n # Commented below, as we don't need this\\n # #if extension.lower() == '.wav':\\n # #[Fs, x] = wavfile.read(path)\\n # if extension.lower() == '.aif' or extension.lower() == '.aiff':\\n # s = aifc.open(path, 'r')\\n # nframes = s.getnframes()\\n # strsig = s.readframes(nframes)\\n # x = numpy.fromstring(strsig, numpy.short).byteswap()\\n # Fs = s.getframerate()\\n if extension.lower() == '.mp3' or extension.lower() == '.wav' or extension.lower() == '.au' or extension.lower() == '.ogg':\\n try:\\n audiofile = AudioSegment.from_file(path)\\n except:\\n print(\\\"Error: file not found or other I/O error. \\\"\\n \\\"(DECODING FAILED)\\\")\\n return -1 ,-1\\n\\n if audiofile.sample_width == 2:\\n data = numpy.fromstring(audiofile._data, numpy.int16)\\n elif audiofile.sample_width == 4:\\n data = numpy.fromstring(audiofile._data, numpy.int32)\\n else:\\n return -1, -1\\n Fs = audiofile.frame_rate\\n x = numpy.array(data[0::audiofile.channels]).T\\n else:\\n print(\\\"Error in readAudioFile(): Unknown file type!\\\")\\n return -1, -1\\n except IOError:\\n print(\\\"Error: file not found or other I/O error.\\\")\\n return -1, -1\\n\\n if x.ndim == 2:\\n if x.shape[1] == 2:\\n x = x.flatten()\\n\\n return Fs, x\",\n \"def streaming_from_file(filepath):\\r\\n pipe = rs.pipeline()\\r\\n cfg = rs.config()\\r\\n cfg.enable_device_from_file(filepath, repeat_playback=False)\\r\\n return pipe, cfg\",\n \"def sox_get_sample_rates(self, files):\\n min_rate = max_rate = None\\n files_to_rates_dict = {}\\n\\n for f in files:\\n result = self._process_command('soxi -r \\\"%s\\\"' % f, PIPE)\\n try:\\n rate = int(result[1][0].strip('\\\\n'))\\n except ValueError:\\n raise LetMeError('Unable to read sample rate from %s' % f)\\n\\n files_to_rates_dict[f] = rate\\n\\n logging.debug('\\\\nSample rate `%s` for `%s`', rate, f)\\n\\n if max_rate is None or rate > max_rate:\\n max_rate = rate\\n\\n if min_rate is None or rate < min_rate:\\n min_rate = rate\\n\\n logging.debug('Sample rates: min - %s, max - %s', min_rate, max_rate)\\n return min_rate, max_rate, files_to_rates_dict\",\n \"def get_phase_amplified_frames(\\n filename,\\n magphase,\\n fl,\\n fh,\\n fs,\\n progress_callback = lambda x: x,\\n attenuateOtherFreq = False,\\n pyrtype = 'octave',\\n sigma = 0,\\n temporalFilter = FIRWindowBP,\\n scalevideo = 1,\\n frames = None,\\n):\\n ## Read Video\\n print(\\\"Preparing capture\\\")\\n vr = cv2.VideoCapture(filename)\\n nF = int(vr.get(cv2.CAP_PROP_FRAME_COUNT))\\n ret, frame = vr.read()\\n h, w, nC = frame.shape\\n\\n \\n print(\\\"Loading: \\\", filename)\\n vid = np.zeros([h, w, nC, nF],frame.dtype)\\n vid[:,:,:,0] = frame\\n for k in range(1, nF):\\n retval, frame = vr.read()\\n if retval:\\n vid[:,:,:,k] = frame\\n else:\\n frames = (0,k)\\n break\\n progress_callback(10/nF)\\n sys.stdout.write('.')\\n sys.stdout.flush()\\n print('\\\\n')\\n vr.release()\\n\\n if not frames:\\n frames = (0, nF-1)\\n\\n ## Compute spatial filters \\n vid = vid[:,:,:,frames[0]:frames[1]+1]\\n h, w, nC, nF = vid.shape\\n if scalevideo != 1:\\n h, w = int(scalevideo*h), int(scalevideo*w)\\n\\n print('Computing spatial filters\\\\n')\\n ht = maxSCFpyrHt(np.zeros((h,w)))\\n if pyrtype == 'octave':\\n filters = getFilters((h, w), np.power(2,np.arange(0,-ht-1,-1).astype(float)), 4)\\n print('Using octave bandwidth pyramid\\\\n') \\n elif pyrtype == 'halfOctave': \\n filters = getFilters((h, w), np.power(2,np.arange(0,-ht-0.5,-0.5).astype(float)), 8, twidth=0.75)\\n print('Using half octave bandwidth pyramid\\\\n')\\n elif pyrtype == 'smoothHalfOctave':\\n filters = getFiltersSmoothWindow((h, w), 8, filtersPerOctave = 2) \\n print('Using half octave pyramid with smooth window.\\\\n')\\n elif pyrtype == 'quarterOctave':\\n filters = getFiltersSmoothWindow((h, w), 8, filtersPerOctave = 4)\\n print('Using quarter octave pyramid.\\\\n')\\n else:\\n raise ValueError('Invalid Filter Types')\\n\\n croppedFilters, filtIDX = getFilterIDX(filters)\\n \\n ## Initialization of motion magnified luma component\\n magnifiedLumaFFT = np.zeros((h,w,nF),np.complex64)\\n\\n def buildLevel(im_dft,k):\\n return np.fft.ifft2(\\n np.fft.ifftshift(\\n np.multiply(croppedFilters[k][0], im_dft[filtIDX[k,0], filtIDX[k,1]])\\n )\\n )\\n\\n def reconLevel(im_dft, k):\\n return 2*(np.multiply(croppedFilters[k][0], np.fft.fftshift(np.fft.fft2(im_dft))))\\n\\n ## First compute phase differences from reference frame\\n numLevels = len(filters) \\n print('Moving video to Fourier domain\\\\n')\\n vidFFT = np.zeros((h,w,nF),dtype=np.complex64)\\n for k in range(0, nF):\\n originalFrame = vid[:,:,:,k].astype(np.float32)\\n originalFrame = cv2.cvtColor(originalFrame, cv2.COLOR_BGR2YUV)\\n tVid = cv2.resize(originalFrame[:,:,0], (w, h), 0, 0, cv2.INTER_CUBIC)\\n vidFFT[:,:,k] = np.fft.fftshift(np.fft.fft2(tVid))\\n sys.stdout.write('.')\\n sys.stdout.flush()\\n progress_callback(20/nF)\\n print('\\\\n')\\n\\n refFrame = 0\\n for level in range(1, numLevels-1):\\n ## Compute phases of level\\n # We assume that the video is mostly static\\n pyrRef = buildLevel(vidFFT[:,:,refFrame], level)\\n pyrRefPhaseOrig = np.divide(pyrRef, np.abs(pyrRef))\\n pyrRef = np.angle(pyrRef)\\n\\n delta = np.zeros((pyrRef.shape[0], pyrRef.shape[1] ,nF), np.float32)\\n print('Processing level {0} of {1}\\\\n'.format(level+1, numLevels))\\n\\n for frameIDX in range(0, nF):\\n filterResponse = buildLevel(vidFFT[:,:,frameIDX], level)\\n pyrCurrent = np.angle(filterResponse)\\n delta[:,:,frameIDX] = np.mod(np.pi+pyrCurrent-pyrRef,2*np.pi)-np.pi\\n \\n ## Temporal Filtering\\n print('Bandpassing phases\\\\n')\\n delta = temporalFilter(delta, fl/fs, fh/fs) \\n\\n ## Apply magnification\\n eps = 2.2204e-16\\n print('Applying magnification\\\\n')\\n for frameIDX in range(0, nF):\\n\\n phaseOfFrame = delta[:,:,frameIDX]\\n originalLevel = buildLevel(vidFFT[:,:,frameIDX], level)\\n ## Amplitude Weighted Blur \\n if (sigma != 0):\\n phaseOfFrame = AmplitudeWeightedBlur(phaseOfFrame, np.abs(originalLevel)+eps, sigma)\\n\\n # Increase phase variation\\n phaseOfFrame = magphase * phaseOfFrame\\n \\n if attenuateOtherFreq:\\n tempOrig = np.multiply(np.abs(originalLevel), pyrRefPhaseOrig)\\n else:\\n tempOrig = originalLevel\\n\\n tempTransformOut = np.multiply(np.exp(1j*phaseOfFrame), tempOrig)\\n\\n curLevelFrame = reconLevel(tempTransformOut, level)\\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] = \\\\\\n curLevelFrame + magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX]\\n \\n progress_callback(50/(numLevels-2))\\n\\n ## Add unmolested lowpass residual\\n level = len(filters)-1\\n for frameIDX in range(0, nF):\\n try:\\n lowpassFrame = np.multiply(vidFFT[filtIDX[level, 0], filtIDX[level, 1] ,frameIDX], np.power(croppedFilters[-1][0], 2))\\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] = \\\\\\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] + lowpassFrame\\n except IndexError:\\n print(\\\"IndexError\\\")\\n progress_callback(10/nF)\\n\\n for k in range(0, nF):\\n magnifiedLuma = np.fft.ifft2(np.fft.ifftshift(magnifiedLumaFFT[:,:,k])).real\\n originalFrame = cv2.cvtColor(vid[:,:,:,k].astype(np.float32), cv2.COLOR_BGR2YUV)\\n originalFrame = cv2.resize(originalFrame, (w, h), 0, 0, cv2.INTER_CUBIC)\\n originalFrame[:,:,0] = magnifiedLuma\\n originalFrame = cv2.cvtColor(originalFrame, cv2.COLOR_YUV2BGR)\\n originalFrame = cv2.convertScaleAbs(originalFrame)\\n yield originalFrame\\n progress_callback(10/nF)\",\n \"def read(f, normalized=False):\\r\\n a = pydub.AudioSegment.from_mp3(f)\\r\\n y = np.array(a.get_array_of_samples())\\r\\n if a.channels == 2:\\r\\n y = y.reshape((-1, 2))\\r\\n if normalized:\\r\\n return a.frame_rate, np.float32(y) / 2**15\\r\\n else:\\r\\n return a.frame_rate, y\",\n \"def __init__(self, pattern='/graphics/projects/scratch/wieschol/sync-data/*/*_noaudio.low.mp4',\\n samples=10, shuffle=True, max_pos_dist=10, min_neg_dist=20, min_pos_dist=5):\\n self.files = glob.glob(pattern)\\n self.shuffle = shuffle\\n self.max_pos_dist = max_pos_dist\\n self.min_pos_dist = min_pos_dist\\n self.min_neg_dist = min_neg_dist\\n self.samples = samples\",\n \"def __init__(self, renderer: sdl2.render.SDL_Renderer, filepath: str,\\n sample_rate: int, loop: bool):\\n self.textures: List[sdl2.render.SDL_Texture] = []\\n for filename in sorted(os.listdir(filepath)):\\n self.textures.append(\\n texture_from_bmp(renderer, os.path.join(filepath, filename)))\\n\\n # Number of times to update current_frame per second\\n self.sample_rate = sample_rate\\n self.loop = loop\\n\\n # Index into textures list\\n self.current_frame = 0\",\n \"def get_Metadata_freq(metafile_science):\\n\\n mslist_file = open(metafile_science, 'r')\\n LINES = mslist_file.readlines()\\n mslist_file.close()\\n\\n frame = 'Frame'\\n \\n for i in range(len(LINES)):\\n line = LINES[i]\\n if line.find(frame) >=0:\\n next_line = LINES[i+1]\\n TOKS = next_line.split()\\n chan_width = float(TOKS[10])*1000. # convert kHz to Hz\\n cfreq = TOKS[12] #MHz\\n nchan = TOKS[7]\\n\\n return chan_width, cfreq, nchan\",\n \"def get_movie_data(files: list) -> list:\\n pass\",\n \"def readDriverFile(self, input_file):\\n\\n\\n fid = open(self.basePath + input_file,'r')\\n\\n # Line 1\\n line = fid.readline()\\n l_input = line.split('!')\\n mshfile = l_input[0].rstrip()\\n\\n # Line 2\\n line = fid.readline()\\n l_input = line.split('!')\\n obsfile = l_input[0].rstrip()\\n\\n # Line 3\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input=='null':\\n topofile = []\\n\\n else:\\n topofile = l_input[0].rstrip()\\n\\n\\n # Line 4\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n mstart = float(l_input[1])\\n\\n else:\\n mstart = l_input[0].rstrip()\\n\\n # Line 5\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n mref = float(l_input[1])\\n\\n else:\\n mref = l_input[0].rstrip()\\n\\n # Line 6\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n staticInput = float(l_input[1])\\n\\n elif l_input[0]=='DEFAULT':\\n staticInput = None\\n\\n else:\\n staticInput = l_input[0].rstrip()\\n\\n\\n # Line 7\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input=='DEFAULT':\\n magfile = []\\n\\n else:\\n magfile = l_input[0].rstrip()\\n\\n # Line 8\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input=='DEFAULT':\\n wgtfile = []\\n\\n else:\\n wgtfile = l_input[0].rstrip()\\n\\n # Line 9\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n chi = float(l_input[0])\\n\\n # Line 10\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n val = np.array(l_input[0:4])\\n alphas = val.astype(np.float)\\n\\n # Line 11\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n val = np.array(l_input[1:3])\\n bounds = val.astype(np.float)\\n\\n else:\\n bounds = l_input[0].rstrip()\\n\\n # Line 12\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n val = np.array(l_input[1:6])\\n lpnorms = val.astype(np.float)\\n\\n else:\\n lpnorms = l_input[0].rstrip()\\n\\n # Line 13\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n val = np.array(l_input[1:3])\\n eps = val.astype(np.float)\\n\\n else:\\n eps = [None,None]\\n\\n self.mshfile = mshfile\\n self.obsfile = obsfile\\n self.topofile = topofile\\n self.mstart = mstart\\n self._mrefInput = mref\\n self._staticInput = staticInput\\n self.magfile = magfile\\n self.wgtfile = wgtfile\\n self.chi = chi\\n self.alphas = alphas\\n self.bounds = bounds\\n self.lpnorms = lpnorms\\n self.eps = eps\",\n \"def get_video_frame_rate(filename):\\n clip = VideoFileClip(filename)\\n frame_rate = clip.fps\\n clip.close()\\n return frame_rate\",\n \"def audioRead(path):\\n data, samplerate = sf.read(path)\\n frames = data.shape[0]\\n channels = len(data.shape)\\n duration = 1/samplerate*frames\\n return data, samplerate, path, duration, frames, channels\",\n \"def INPUT_Periods_file(input):\\n \\n global events\\n \\n tb = 3600\\n ta = 3600\\n \\n Period = input['min_date'].split('T')[0] + '_' + \\\\\\n input['max_date'].split('T')[0] + '_' + \\\\\\n str(input['min_mag']) + '_' + str(input['max_mag'])\\n eventpath = os.path.join(input['datapath'], Period)\\n \\n len_events = len(events)\\n \\n input_period = open(os.path.join(os.getcwd(), 'INPUT-Periods'), 'a+')\\n\\n for i in range(0, len_events):\\n \\n str_event = str(events[i]['datetime']-tb) + '_' + \\\\\\n str(events[i]['datetime']+ta) + '_' + \\\\\\n str(events[i]['magnitude'] - 0.01) + '_' + \\\\\\n str(events[i]['magnitude'] + 0.01) + '\\\\n'\\n input_period.writelines(str_event)\\n \\n input_period.close()\\n \\n print '************************************************************' \\n print 'New INPUT-Periods file is generated in your folder.'\\n print 'Now, you could run the program again based on your desired event :)' \\n print '************************************************************'\\n \\n sys.exit()\",\n \"def f2gif(path,fps):\\n print(\\\"==============================================\\\")\\n print(\\\"Convert file to GIF!\\\")\\n pathout = path[:-4]+'_'+str(fps)+'.gif'\\n if path.endswith('.tif'): \\n# import tifffile\\n im = tifffile.imread(path)\\n nFrames, h,w = im.shape\\n dur=1/fps\\n clip = []\\n for i in range(nFrames):\\n fr = cv2.cvtColor(im[i],cv2.COLOR_GRAY2RGB)\\n clip.append(mp.ImageClip(fr).set_duration(dur))\\n video = mp.concatenate_videoclips(clip, method=\\\"compose\\\",ismask=False)#ismask=True to make grayscale\\n\\n else:\\n video = mp.VideoFileClip(path)\\n fpsIn = int(video.fps)\\n if fps != fpsIn:\\n print(\\\"Conflict in fps! \\\\n\\\", \\\"[0] Use fps of input file;\\\\n\\\", \\\"[1] Use desired fps w/o speedup;\\\\n\\\",\\n \\\"[2] Use desired fps w/ speedup:\\\")\\n k = input('Input your selection: ')\\n if k == 2:\\n sf = fps/fpsIn\\n video =video.fx(mp.vfx.speedx, sf)# Not working when sf<1\\n elif k == 0:\\n fps = fpsIn\\n\\n video.write_gif(pathout,fps=fps)\\n video.reader.close()# To fix handel error problem\\n# if path.endswith('.gif'):\\n# clip.write_videofile(pathout,fps=fps,codec='libx264', bitrate='32 M',preset='ultrafast')\\n print(\\\"==============================================\\\")\\n print(\\\"MP4 convertion Done!\\\")\",\n \"def read_frame(location, channels, start_time=None, \\n end_time=None, duration=None):\\n\\n if end_time and duration:\\n raise ValueError(\\\"end time and duration are mutually exclusive\\\")\\n \\n if type(location) is list:\\n locations = location\\n else:\\n locations = [location]\\n\\n cum_cache = lal.Cache()\\n for source in locations:\\n dir_name, file_name = os.path.split(source)\\n base_name, file_extension = os.path.splitext(file_name)\\n \\n if file_extension == \\\".lcf\\\" or file_extension == \\\".cache\\\":\\n cache = lal.CacheImport(source)\\n elif file_extension == \\\".gwf\\\": \\n cache = lalframe.FrOpen(dir_name, file_name).cache\\n else:\\n raise TypeError(\\\"Invalid location name\\\")\\n \\n cum_cache = lal.CacheMerge(cum_cache, cache)\\n \\n stream = lalframe.FrStreamCacheOpen(cum_cache)\\n \\n stream.mode = lalframe.FR_STREAM_VERBOSE_MODE\\n lalframe.FrSetMode(stream.mode | lalframe.FR_STREAM_CHECKSUM_MODE,\\n stream)\\n\\n # determine duration of data\\n if type(channels) is list:\\n first_channel = channels[0]\\n else:\\n first_channel = channels\\n data_length = lalframe.FrStreamGetVectorLength(first_channel, stream)\\n channel_type = lalframe.FrStreamGetTimeSeriesType(first_channel, stream)\\n create_series_func = _fr_type_map[channel_type][2]\\n get_series_metadata_func = _fr_type_map[channel_type][3]\\n series = create_series_func(first_channel, stream.epoch, 0, 0,\\n lal.ADCCountUnit, 0)\\n get_series_metadata_func(series, stream)\\n data_duration = data_length * series.deltaT\\n\\n if start_time is None:\\n start_time = stream.epoch*1\\n if end_time is None:\\n end_time = start_time + data_duration\\n\\n if type(start_time) is not lal.LIGOTimeGPS:\\n start_time = lal.LIGOTimeGPS(start_time)\\n if type(end_time) is not lal.LIGOTimeGPS:\\n end_time = lal.LIGOTimeGPS(end_time)\\n\\n if duration is None:\\n duration = float(end_time - start_time)\\n else:\\n duration = float(duration)\\n\\n # lalframe behaves dangerously with invalid duration so catch it here\\n if duration <= 0:\\n raise ValueError(\\\"Negative or null duration\\\")\\n #if duration > data_duration:\\n # raise ValueError(\\\"Requested duration longer than available data\\\")\\n\\n if type(channels) is list:\\n all_data = []\\n for channel in channels:\\n channel_data = _read_channel(channel, stream, start_time, duration)\\n lalframe.FrStreamSeek(stream, start_time)\\n all_data.append(channel_data)\\n return all_data\\n else:\\n return _read_channel(channels, stream, start_time, duration)\",\n \"def rec_one_shot(self, sec, file_name=None):\\n self.__open_noncallback_stream()\\n frames = []\\n for i in range(int(self.RATE / self.CHUNK * sec)):\\n data = self.stream.read(self.CHUNK)\\n data = np.fromstring(data, dtype=np.int16)\\n frames.append(data)\\n self.stream.stop_stream()\\n if file_name is not None:\\n with wave.open(file_name, 'wb') as wav_file:\\n wav_file.setnchannels(self.CHANNELS)\\n wav_file.setsampwidth(self.recorder.get_sample_size(self.FORMAT))\\n wav_file.setframerate(self.RATE)\\n wav_file.writeframes(b''.join(frames))\\n frame = np.concatenate(frames, 0)\\n self.stop_streaming()\\n return frame\",\n \"def stream_timelapse(path):\\n parts = path.split('.')[0].split('_')\\n count = int(parts[2])\\n filename = parts[0] + '_{0:03d}_{1:03d}.jpg'\\n for i in range(count):\\n frame = open(filename.format(i, count), 'rb').read()\\n yield b'--frame\\\\r\\\\nContent-Type: image/jpeg\\\\r\\\\nContent-Length: ' + \\\\\\n str(len(frame)).encode() + b'\\\\r\\\\n\\\\r\\\\n' + frame + b'\\\\r\\\\n'\\n time.sleep(0.5)\",\n \"def read_all_files():\\n paths = get_all_recording_paths()\\n\\n return read_by_paths(paths)\",\n \"def t1_loadNFile(self):\\n print \\\"noisubspectrumFile\\\"\\n filename = tkFileDialog.askopenfilename()\\n filename = self.filenameparser(filename)\\n self.t1_noifilename = filename\",\n \"def _default_specs(self):\\n # Spectrometer specs\\n self.model = \\\"Flame-S\\\" # Spectrometer model\\n self.fov = 1 # Field of view fo spectrometer (radius of FOV)\\n self.ILS = None # Number array holding instrument line shape (possibly don't hold this here?)\\n self.fiber_diameter = 1e-3 # Diameter of optical fiber\\n self.pix_num = 2048 # Number of pixels\\n self.bit_depth = 16 # Bit depth of spectrometer detector\\n\\n # File information\\n self.file_ext = '.npy' # Spectra saved as numpy array\\n self.file_ss = '{}ss' # Shutter speed format spec\\n self.file_ss_loc = 1 # Shutter speed location in filename\\n self.file_spec_type = {'meas': 'Plume', 'dark': 'Dark', 'cal': 'ppmm', 'clear': 'Clear'}\\n self.file_datestr = \\\"%Y-%m-%dT%H%M%S\\\" # Date/time format spec in filename\\n self.file_datestr_loc = 0\\n self.plume_params_file = 'plume_params.txt'\\n self.plume_speed_id = 'plume_speed='\\n self.plume_dist_id = 'plume_distance='\\n\\n # File which flags that a scan is complete. The file will be empty, just its presence is required\\n self.scan_complete = 'complete.txt'\\n\\n # Acquisition settings\\n self.start_int_time = 100 # Starting integration time\\n self.start_coadd = 1 # Number of spectra to coadd\\n self.framerate = 1 # Framerate of acquisitions (Hz)\\n self.wavelengths = None # Wavelengths (nm)\\n self.spectrum = None # Spectrum\\n self.spectrum_filename = None # Filename for spectrum\\n\\n self.auto_int = True # Bool for requesting automated integration time adjustment\\n self.min_saturation = 0.6 # Minimum saturation accepted before adjusting shutter speed (if auto_ss is True)\\n self.max_saturation = 0.9 # Maximum saturation accepted before adjusting shutter speed (if auto_ss is True)\\n self.saturation_range = [300, 335] # Range of wavelengths used in checking integration time\\n self.saturation_pixels = 2 # Number of pixels to check\\n\\n # Predefined list of integration times for automatic exposure adjustment\\n self.int_list = np.concatenate((np.arange(0.1, 0.5, 0.05),\\n np.arange(0.5, 1, 0.1),\\n np.arange(1, 5, 0.5),\\n np.arange(5, 10, 1),\\n np.arange(10, 50, 5),\\n np.arange(50, 100, 10),\\n np.arange(100, 500, 50),\\n np.arange(500, 1000, 100),\\n np.arange(10 ** 3, 10 ** 4, 500),\\n np.array([10 ** 4])))\",\n \"def open_read_files(answer_files, answers):\\r\\n \\\"\\\"\\\"And designates each file to a variable in answers\\\"\\\"\\\"\\r\\n count = 0\\r\\n s = 0\\r\\n answer_files2 = []\\r\\n for file in answer_files[:]: # Used [:] to get all file_names in answer_files\\r\\n ans = open(file, mode='r')\\r\\n print(f\\\"Opening {ans.name}\\\")\\r\\n time.sleep(s)\\r\\n answers[count] = ans\\r\\n count += 1\\r\\n if ans.closed == False: # Section for checking if files are closed\\r\\n print(f\\\"Closing {ans.name}\\\")\\r\\n ans.close()\\r\\n answer_files2.append(ans.name)\\r\\n answer_files.remove(ans.name)\\r\\n time.sleep(s)\\r\\n return answer_files2, answers\",\n \"def file_name_list():\\n file_names = []\\n hour = h1\\n minute = m1\\n while hour * 60 + minute <= h2 * 60 + m2:\\n file_name = generate_file_name(hour, minute)\\n file_names.append(file_name)\\n hour, minute = next_time(hour, minute)\\n return file_names\",\n \"def get_parameters_fastcharge(filename, source_directory):\\n filename = filename.rsplit('.', 1)[0]\\n strname = filename.rsplit('_CH', 1)[0]\\n\\n # Get date\\n date = re.match(r'(\\\\d+)-(\\\\d+)-(\\\\d+)', strname)\\n if date is None:\\n warnings.warn(\\\"Date could not be parsed from {}\\\".format(filename))\\n else:\\n date = date.group()\\n\\n # Get channel number\\n chno = re.findall(r'(CH+\\\\d*)', filename)\\n if chno:\\n chno = chno[0]\\n else:\\n chno = None\\n warnings.warn(\\\"Channel number could not be parsed from {}\\\".format(filename))\\n\\n try:\\n param_str = strname.rsplit(date + '_', 1)[1]\\n param = param_str.replace('_', '.')\\n\\n if param.find('.') < 0:\\n param = find_meta(filename, source_directory)\\n\\n q1 = re.findall(r'(\\\\d+per)', param)[0].split('per')[0]\\n cc1 = re.findall(r'(\\\\d*\\\\.?\\\\d+C)', param.split(q1 + 'per.')[0])[0]\\n cc2 = re.findall(r'(\\\\d*\\\\.?\\\\d+C)', param.split(q1 + 'per.')[1])[0]\\n protocol = cc1+'('+q1+'%)-'+cc2\\n except Exception as e:\\n warnings.warn(\\\"Failed to parse protocol for {}: {}\\\".format(filename, e))\\n protocol = None\\n\\n return date, chno, strname, protocol\",\n \"def test_get_fasta_fps(self):\\r\\n\\r\\n file_basenames = [basename(self.fasta2_fp), basename(self.fasta3_fp),\\r\\n basename(self.fasta1_fp)]\\r\\n\\r\\n actual_fastas = get_fasta_fps(self.input_dir, file_basenames)\\r\\n\\r\\n expected_fasta = [self.fasta2_fp, self.fasta3_fp, self.fasta1_fp]\\r\\n\\r\\n self.assertEqual(actual_fastas, expected_fasta)\",\n \"def get_configfile(files,\\n seasoncyc_base=None,\\n seasoncyc_sim=None,\\n base_id='NCEP',\\n sim_id='NCEP',\\n timewin=1,\\n varname='slp',\\n seacyc=False,\\n cycsmooth=91,\\n nanalog=20,\\n seasonwin=30,\\n distfun='rms',\\n outformat='.txt',\\n period=[\\\"1973-01-01\\\", \\\"2012-12-31\\\"],\\n bbox=\\\"-180.0,-90.0,180,90.0\\\",\\n calccor=True,\\n silent=False):\\n from datetime import datetime as dt\\n\\n date_stamp = dt.strftime(dt.now(), format='%Y%m%d_%H%M%S')\\n LOGGER.info('start configuration file preparation at: %s' % (date_stamp))\\n\\n # convert True/False to Fortran syntax\\n seacyc = str(seacyc)\\n calccor = str(calccor)\\n silent = str(silent)\\n\\n # write stuff to configuration file\\n # NB: if order or format or number changes, need to edit wps_analogs_viewer.py\\n # and template_analogviewer.html where these scripts read in the config\\n # params\\n config_file = \\\"config.txt\\\"\\n\\n config = open(config_file, \\\"w\\\")\\n\\n config.write(\\n '!Configuration file for CASTf90 analogs processes deployed in flyingpigeon\\\\n')\\n config.write('!Created : %s \\\\n' % (date_stamp))\\n config.write('!Version : 0.1.5 \\\\n')\\n config.write('&FILES \\\\n')\\n config.write(' my_files%archivefile = \\\"{file}\\\" \\\\n'.format(\\n file=os.path.relpath(files[0])))\\n config.write(' my_files%simulationfile = \\\"{file}\\\" \\\\n'.format(\\n file=os.path.relpath(files[1])))\\n config.write(' my_files%outputfile = \\\"{file}\\\" \\\\n'.format(\\n file=os.path.relpath(files[2])))\\n\\n if seacyc is not 'False':\\n config.write(' my_files%seacycfilebase = \\\"{file}\\\" \\\\n'.format(\\n file=os.path.relpath(seasoncyc_base)))\\n config.write(' my_files%seacycfilesim = \\\"{file}\\\" \\\\n'.format(\\n file=os.path.relpath(seasoncyc_sim)))\\n\\n config.write('/ \\\\n')\\n config.write('&PARAM \\\\n')\\n config.write(' my_params%timewin = {timewin} \\\\n'.format(timewin=timewin))\\n config.write(' my_params%varname = \\\"{varname}\\\" \\\\n'.format(varname=varname))\\n config.write(' my_params%seacyc = .{seacyc}. \\\\n'.format(\\n seacyc=seacyc.upper()))\\n config.write(' my_params%cycsmooth = {cycsmooth} \\\\n'.format(\\n cycsmooth=cycsmooth))\\n config.write(' my_params%nanalog = {nanalog} \\\\n'.format(nanalog=nanalog))\\n config.write(' my_params%seasonwin = {seasonwin} \\\\n'.format(\\n seasonwin=seasonwin))\\n config.write(' my_params%distfun = \\\"{distfun}\\\" \\\\n'.format(distfun=distfun))\\n config.write(' my_params%calccor = .{calccor}. \\\\n'.format(\\n calccor=calccor.upper()))\\n config.write(' my_params%oformat = \\\"{outformat}\\\" \\\\n'.format(\\n outformat=outformat)) # \\\".txt\\\" # ! if equals \\\".nc\\\"\\n config.write(' my_params%silent = .{silent}.\\\\n'.format(\\n silent=silent.upper()))\\n config.write('/\\\\n')\\n config.write('&ATTS\\\\n')\\n config.write(' my_atts%simsource = \\\"{sim_id}\\\" \\\\n'.format(sim_id=sim_id)) # model name\\n config.write(\\n ' my_atts%predictorvar = \\\"{varname}\\\" \\\\n'.format(varname=varname))\\n config.write(' my_atts%archisource = \\\"{base_id}\\\" \\\\n'.format(base_id=base_id))\\n config.write(' my_atts%archiperiod = \\\"{start},{end}\\\" \\\\n'.format(\\n start=period[0], end=period[1]))\\n config.write(' my_atts%predictordom = \\\"{bbox}\\\" \\\\n'.format(bbox=bbox))\\n config.write('/\\\\n')\\n\\n config.close()\\n return config_file\",\n \"def open_frame(path,number):\\n num=str(number).zfill(3) #Zero filling\\n name = glob.glob(path+\\\"/*\\\"+num+\\\"*\\\")\\n if len(name)==0:\\n name = glob.glob(path+\\\"/\\\"+str(number)+\\\".png\\\")\\n if len(name)>1:\\n print \\\"too many matches \\\",len(name),\\\" found\\\"\\n name = name[0]\\n img = Image.open(name)\\n img = np.asarray(img)\\n img.setflags(write=1)\\n return img\",\n \"def get_audio(name, n):\\n audio_path = os.path.join(args.input_folder, name, \\\"audio.ogg\\\")\\n if not os.path.exists(audio_path):\\n ## Some folders have multiple .ogg files, so we need to first combine them into one file. Example:\\n ## |── Universe\\n ## │ ├── aligned.swc\\n ## │ ├── audio1.ogg\\n ## │ ├── audio2.ogg\\n ## │ ├── audio3.ogg\\n ## │ ├── audio4.ogg\\n ## │ ├── audiometa.txt\\n ## │ ├── info.json\\n ## │ ├── wiki.html\\n ## │ ├── wiki.txt\\n ## │ └── wiki.xml\\n\\n multiple_ogg_files = []\\n for i in range(1, 5):\\n path = os.path.join(args.input_folder, name, \\\"audio\\\" + str(i) + \\\".ogg\\\")\\n if os.path.exists(path):\\n multiple_ogg_files.append(path)\\n else:\\n break\\n if len(multiple_ogg_files) == 0:\\n return\\n elif len(multiple_ogg_files) == 1:\\n os.system(\\\"cp \\\\\\\"\\\" + multiple_ogg_files[0] + \\\"\\\\\\\" \\\\\\\"\\\" + audio_path + \\\"\\\\\\\"\\\")\\n else:\\n tmp_file_name = \\\"ffmeg_inputs.txt\\\"\\n print(\\\"tmp_file_name=\\\", tmp_file_name)\\n with open(tmp_file_name, \\\"w\\\", encoding=\\\"utf-8\\\") as tmp_file:\\n for path in multiple_ogg_files:\\n tmp_file.write(\\\"file '\\\" + path + \\\"'\\\\n\\\")\\n cmd = \\\"ffmpeg -f concat -i \\\\\\\"\\\" + tmp_file_name + \\\"\\\\\\\" -c copy \\\\\\\"\\\" + audio_path + \\\"\\\\\\\"\\\"\\n print(cmd)\\n os.system(cmd)\\n\\n output_audio_path = args.destination_folder + \\\"/audio/\\\" + str(n) + \\\".ogg\\\"\\n os.system(\\\"cp \\\\\\\"\\\" + audio_path + \\\"\\\\\\\" \\\" + output_audio_path)\",\n \"def get_data(path):\\n if path.endswith('.mp3'):\\n path = prepare_file(path, path.rstrip('mp3')+'wav')\\n x, sr = librosa.load(path, duration=30)\\n\\n else:\\n x, sr = librosa.load(path, duration=30)\\n directory, file_name = os.path.split(path)\\n return x, sr, file_name\",\n \"def read_cospectrum(path,d):\\r\\n spec = []\\r\\n timeseries = []\\r\\n for i in range(len(d)):\\r\\n filename = path + d[i]\\r\\n\\r\\n with open(filename, \\\"r\\\") as f:\\r\\n reader = csv.reader(f,delimiter=',')\\r\\n ct=1\\r\\n for row in reader:\\r\\n if ct==6:\\r\\n Hz = float(row[0].split('_')[-1])\\r\\n elif ct==7:\\r\\n height = float(row[0].split('_')[-1])\\r\\n elif ct==8:\\r\\n ws = float(row[0].split('_')[-1])\\r\\n elif ct==9:\\r\\n avg_period = float(row[0].split('_')[-1])\\r\\n elif ct==13:\\r\\n header = row\\r\\n elif ct>13:\\r\\n break\\r\\n ct+=1\\r\\n \\r\\n meta = [Hz,height,ws,avg_period]\\r\\n \\r\\n thisspec = np.genfromtxt(filename,delimiter=',',skip_header=13)\\r\\n spec.append(thisspec)\\r\\n thistime = re.findall('\\\\d{8}-\\\\d{4}',filename)[0]\\r\\n thisdate = datetime.strptime(thistime,'%Y%m%d-%H%M')\\r\\n timeseries.append(thisdate) \\r\\n \\r\\n return spec, timeseries, header, meta\",\n \"def getVideoFrames(videoFilePath, startFrameNumber=-1, endFrameNumber=-1):\\n frames=[]\\n vidcap = cv2.VideoCapture(videoFilePath)\\n fps=vidcap.get(cv2.CAP_PROP_FPS)\\n totalFrame=vidcap.get(cv2.CAP_PROP_FRAME_COUNT)\\n if startFrameNumber==-1:\\n startFrameNumber = 0\\n if endFrameNumber == -1:\\n endFrameNumber = totalFrame - 1\\n success,image = vidcap.read()\\n count = 0\\n success = True\\n while success:\\n image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\\n image = color.rgb2yiq(image).astype(np.float32)\\n \\n if count<startFrameNumber:\\n success,image = vidcap.read()\\n count+=1\\n continue\\n elif count>=endFrameNumber:\\n break\\n else: \\n frames.append(image)\\n success,image = vidcap.read()\\n count += 1\\n frames=np.array(frames)\\n \\n return fps, frames\",\n \"def getFileList(self):\\n sid = 86400 # change to 3600 for hour-by-hour\\n uDays = range(sid*(int(self.uStart)/sid),sid+(sid*(int(self.uStop)/sid)),sid)\\n fileList = []\\n sep = os.path.sep\\n for d in uDays:\\n s = unixTimeToString(d)\\n ymdPath = 'year' + s[0:4] + sep + 'month' + s[5:7] + sep + 'day' + s[8:10]\\n dirname = self.basePath + sep + ymdPath + sep + self.sensor + sep + 'padhist'\\n pattern = '*' + self.sensor + '_hstv*.mat'\\n nameList = glob.glob1(dirname,pattern)\\n for name in nameList:\\n uTime = stringTimeToUnix(name[0:13] + '_00_00.000')\\n if ( self.uStart <= uTime <= self.uStop ):\\n #print 'IN: %s' % unixTimeToString(uTime)\\n fileList.append(dirname + sep + name)\\n fileList.sort()\\n self.fileList = fileList\",\n \"def read_data(self):\\n self.days = [0, 2, 3, 5, 6, 8, 9, 11, 13, 14]\\n path = '../data/'\\n data = []\\n for day in self.days:\\n filename = path + 'spectrum_day{}.txt'.format(day)\\n data.append(read_file(filename))\\n return data\",\n \"def fix_file(file_path: str, output_path_fixed: str, target_rate: int=16000,\\n channels: int=1, output_path: str=None, min_duration: int=None,\\n verbose_level: int=0):\\n file_name = file_path.split(os.sep)[-1]\\n new_file_path = output_path_fixed + os.sep + file_name\\n\\n try:\\n # Get the audio length\\n out = syscommand.system('soxi -D ' + file_path)\\n duration = float(out)\\n # Get the number of channels\\n out = syscommand.system('soxi -c ' + file_path)\\n current_n_channels = int(out)\\n # Get the current rate\\n out = syscommand.system('soxi -r ' + file_path)\\n current_rate = int(out)\\n if min_duration is not None and duration < min_duration:\\n raise Exception(\\\"Minimum length not satisfied\\\")\\n except Exception as err:\\n if str(verbose_level) != '0':\\n print(err)\\n return None, file_path\\n\\n if current_rate != target_rate and current_n_channels != channels:\\n speed = float(current_rate) / float(target_rate)\\n cmd = 'sox -V{} -r 16k {} {} channels 1 ' \\\\\\n 'speed {}'.format(verbose_level, file_path, new_file_path,\\n speed)\\n if str(verbose_level) == '2':\\n print(cmd)\\n os.system(cmd)\\n return new_file_path, file_path\\n elif current_rate != target_rate:\\n speed = float(current_rate) / float(target_rate)\\n cmd = 'sox -V{} -r 16k {} {} ' \\\\\\n 'speed {}'.format(verbose_level, file_path, new_file_path,\\n speed)\\n if str(verbose_level) == '2':\\n print(cmd)\\n os.system(cmd)\\n return new_file_path, file_path\\n elif current_n_channels != channels:\\n cmd = 'sox -V{} {} {} channels 1'.format(verbose_level, file_path,\\n new_file_path)\\n if str(verbose_level) == '2':\\n print(cmd)\\n os.system(cmd)\\n return new_file_path, file_path\\n\\n # Copy file if output path were provided and the file is not there\\n if output_path is not None:\\n copyfile(file_path, new_file_path)\\n return file_path, file_path\",\n \"def getConfig():\\n\\n config = rFile(\\\"/var/www/html/config.txt\\\").split()\\n f = int(config[0])\\n mode = config[1]\\n\\n if (f in DABchannels and (mode == \\\"explore\\\" or mode == \\\"monitor\\\")):\\n return f, mode\\n else:\\n return 227360000, \\\"explore\\\" # Kamzik - Bratislava\",\n \"def fileSetup(path):\\n past_fnames = next(os.walk(path))[2]\\n f_nums = []\\n for f in past_fnames:\\n if f.startswith('semi'):\\n f_nums.append(int(f[4:8]))\\n\\n if not f_nums:\\n now_fname = '/semi0001.h264'\\n else:\\n now_fname = '/semi%04d.h264' % (max(f_nums)+1, )\\n\\n now_fname = path+now_fname\\n print 'Current filename: %s' % now_fname\\n\\n return now_fname\",\n \"def t9_loadFile(self):\\n print \\\"subspectrumFile\\\"\\n filename = tkFileDialog.askopenfilename()\\n filename = \\\"SubSpectrumData/\\\" + self.filenameparser(filename)\\n orgin_file = self.filenameparser(filename)\\n self.t9_filename = filename\\n self.t9_orginfilename = orgin_file\",\n \"def read_recording_names(feature_files):\\n all_recording_names = {}\\n for feature_file in feature_files:\\n in_dir = '/'.join(feature_file.split('/')[:-1])\\n name = \\\"recordings.list\\\"\\n path = os.path.join(in_dir, name)\\n if not os.path.exists(path):\\n return None\\n else:\\n with open(path, 'r') as f:\\n recording_names = f.readlines()\\n recording_names = [recording_name.strip() for recording_name in recording_names]\\n # feature file at this position is basically incorrect. it takes the name of the hdf5 file as a key in\\n # the dictionary. the directory would be more intuitive. however, cmd_args.input is used later on to\\n # access the names which is why this works\\n all_recording_names.update({feature_file: recording_names})\\n\\n return all_recording_names\",\n \"def getFileList(self):\\n print 'getting fileList ...',\\n sid = 86400 # change to 3600 for hour-by-hour\\n uDays = range(sid*(int(self.uStart)/sid),sid+(sid*(int(self.uStop)/sid)),sid)\\n fileList = []\\n sep = os.path.sep\\n for d in uDays:\\n s = unixTimeToString(d)\\n ymdPath = 'year' + s[0:4] + sep + 'month' + s[5:7] + sep + 'day' + s[8:10]\\n dirname = self.basePath + sep + ymdPath + sep + self.subDir\\n pattern = '*' + self.sensor\\n nameList = glob.glob1(dirname,pattern)\\n for name in nameList:\\n ufStart = stringTimeToUnix(name[0:23])\\n ufStop = stringTimeToUnix(name[24:47])\\n if ( ufStart <= self.uStart <= ufStop ) or ( self.uStart <= ufStart <= self.uStop ) or ( ufStart <= self.uStop <= ufStop ):\\n #print 'IN: %s' % unixTimeToString(uTime)\\n fileList.append(dirname + sep + name)\\n## else:\\n## print 'OUT:\\\\n%s\\\\n%s\\\\n%s' % (unixTimeToString(ufStart),unixTimeToString(self.uStart),unixTimeToString(ufStop))\\n fileList.sort()\\n self.fileList = fileList\\n print 'done'\",\n \"def _load(self, filepath):\\n import subprocess as sp\\n command = ['ffmpeg',\\n '-i', filepath,\\n '-f', 's16le',\\n '-acodec', 'pcm_s16le',\\n '-ac', '1'] # channels: 2 for stereo, 1 for mono\\n if self.sampling_rate != SAMPLING_RATE:\\n command.extend(['-ar', str(self.sampling_rate)])\\n command.append('-')\\n # 30s at 44.1 kHz ~= 1.3e6\\n proc = sp.run(command, stdout=sp.PIPE, bufsize=10**7, stderr=sp.DEVNULL, check=True)\\n\\n return np.fromstring(proc.stdout, dtype=\\\"int16\\\")\",\n \"def inputwav(filename):\\n data, sr = sf.read(filename)\\n print('Decoding \\\"'+filename+'\\\"...')\\n print('Sample rate is '+str(sr)+'...')\\n try:\\n ch=len(data[0,])\\n except:\\n ch=1\\n print('File contains '+str(ch)+' audio channel(s)...')\\n #Reshape the data so other functions can interpret the array if mono.\\n #basically transposing the data\\n if ch==1:\\n data=data.reshape(-1,1)\\n n=len(data)\\n #This prevents log(data) producing nan when data is 0\\n data[np.where(data==0)]=0.00001\\n #convert to dB\\n data_dB=20*np.log10(abs(data))\\n return n, data,data_dB,sr, ch\",\n \"def video_audio_files(video_name, path_curr_vid, path_current_frames):\\n video_file = f\\\"{path_curr_vid}{video_name}\\\"\\n audio_file = f\\\"{path_current_frames}{video_name.replace(VIDEO_EXT,AUDIO_EXT)}\\\"\\n return video_file, audio_file\",\n \"def getattr(self, path, *args, **pargs):\\n path, meta = self.find_cue_path(path)\\n if('.flaccuesplit.' in path):\\n try:\\n raw_path = path\\n path, flaccue_details = path.split('.flaccuesplit.')\\n path = self.clean_path(path)\\n times, extension = os.path.splitext(flaccue_details)\\n # Get the info for the base file.\\n st = os.lstat(path)\\n toreturn = dict((key, getattr(st, key)) for key in (\\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\\n 'st_nlink', 'st_size', 'st_uid'))\\n # Estimate the file size.\\n f = mutagen.File(path)\\n start, end = times.split('.')\\n # Minutes:Seconds:Frames\\n # 75 frames per second.\\n start_split = [int(x) for x in start.split(':')]\\n if(len(start_split) != 3):\\n start_time = 0\\n else:\\n start_time = start_split[0]*60 + start_split[1] + start_split[2]/75\\n end_split = [int(x) for x in end.split(':')]\\n if(len(end_split) != 3):\\n end_time = f.info.length\\n else:\\n end_time = end_split[0]*60 + end_split[1] + end_split[2]/75\\n toreturn['st_size'] = int((end_time - start_time) *\\n f.info.channels *\\n (f.info.bits_per_sample/8) *\\n f.info.sample_rate)\\n # Ensure the mode shows the file as readable.\\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\\n return toreturn\\n except Exception:\\n print(f'Error getting attributes for {raw_path}:', file=sys.stderr, flush=True)\\n import traceback\\n traceback.print_exc()\\n # Otherwise, just get the normal info.\\n path = self.clean_path(path)\\n st = os.lstat(path)\\n toreturn = dict((key, getattr(st, key)) for key in (\\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\\n 'st_nlink', 'st_size', 'st_uid'))\\n # Ensure the mode shows the file as readable.\\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\\n return toreturn\",\n \"def param_info():\\n\\n\\tgizmo_names = syn.getGizmoNames()\\n\\n\\tfor gizmo in gizmo_names:\\n\\t\\tparams = syn.getParameterNames(gizmo)\\n\\t#doesnt get all parameters from gizmos i.e. WaveFreq\\n\\n\\t# get all info on the 'WaveFreq' parameter\\n\\tGIZMO = 'aStim2'\\n\\tPARAMETER = 'WaveFreq'\\n\\n\\t# info = syn.getParameterInfo(GIZMO, PARAMETER)\\n\\t#\\n\\t# # get the array size (should be 100)\\n\\t# sz = syn.getParameterSize(GIZMO, PARAMETER)\\n\\t#\\n\\t# # write values 1 to 50 in second half of buffer\\n\\t# result = syn.setParameterValues(GIZMO, PARAMETER, np.arange(1, 51), 50)\\n\\t#\\n\\t# # read all values from buffer\\n\\t# syn.getParameterValues(GIZMO, PARAMETER, sz)\\n\\t#\\n\\t# # get all info on the 'Go' parameter\\n\\t# PARAMETER = 'Go'\\n\\t# info = syn.getParameterInfo(GIZMO, PARAMETER)\\n\\t#\\n\\t# # flip the switch\\n\\t# result = syn.setParameterValue(GIZMO, PARAMETER, 1)\\n\\t#\\n\\t# # check the value\\n\\tfreq = syn.getParameterValue(GIZMO, PARAMETER)\\n\\tprint('value =', freq)\\n\\tfreq = [freq]\\n\\n\\t# also verify visually that the switch slipped in the run\\n\\t# time interface. This state change will be logged just\\n\\t# like any other variable change and saved with the runtime\\n\\t# state.\\n\\n\\tnumTrials = 5 #total number of trials across stimuli\\n\\tISI = [2.0, 3.0, 4.0, 5.0] # ISI in seconds\\n\\n\\t# flash parameters\\n\\tflash_dur = [.001] # flash durs in seconds (100 ms, 200 ms)\\n\\tluminance = [[1, 1, 1], [.86, .86, .86], [0, .1, 1]] # white , grayish, purple just for testing\\n\\n\\t# auditory parameters\\n\\tduration = [.005] # in seconds; pulseDur in TDT\\n\\tsound_levels = [20.0, 40.0, 60.0, 80.0] # dB; waveAmp in TDT\\n\\n\\t# Auditory on (T/F? if T then A+V, if F then Visual only)\\n\\tstims = {0: \\\"auditory_only\\\",\\n\\t\\t\\t 1: \\\"visual_only\\\",\\n\\t\\t\\t 2: \\\"A+V\\\"\\n\\t\\t\\t }\\n\\n\\texper = Experiment(numTrials=numTrials, ISI=ISI, flash_dur=flash_dur, luminance=luminance, wave_freq=freq,\\n\\t\\t\\t\\t\\t pulse_dur=duration, wave_amp=sound_levels, stimulus=stims)\\n\\texper.run_experiment()\",\n \"def readFT(self,file=\\\"out__1.ft\\\"):\",\n \"def get_metadata(my_path):\\n with wave.open(my_path, \\\"rb\\\") as wave_file:\\n frame_rate = wave_file.getframerate()\\n channels = wave_file.getnchannels()\\n my_format = pyaudio.get_format_from_width(wave_file.getsampwidth())\\n return str(frame_rate), str(channels), str(my_format)\",\n \"def parse_fname(cmd_args):\\n\\n # Seasonal accumulation file\\n if (cmd_args.period == 99):\\n f_name = _parse_fname_season(cmd_args)\\n else:\\n f_name = _parse_fname_hour(cmd_args)\\n\\n return f_name\",\n \"def generate_config(filename: str,\\n mw_pulse_duration: int = 20,\\n flux_pulse_duration: int=40,\\n ro_duration: int = 800,\\n mw_mw_buffer=0,\\n mw_flux_buffer=0,\\n flux_mw_buffer=0,\\n ro_latency: int = 0,\\n mw_latency: int = 0,\\n fl_latency: int = 0,\\n init_duration: int = 200000):\\n\\n qubits = ['q0', 'q1', 'q2', 'q3', 'q4', 'q5', 'q6']\\n lut_map = ['i {}', 'rx180 {}', 'ry180 {}', 'rx90 {}', 'ry90 {}',\\n 'rxm90 {}', 'rym90 {}', 'rphi90 {}', 'spec {}', 'rx12 {}',\\n 'square {}']\\n flux_tuples = [(\\\"q2\\\", \\\"q0\\\"), (\\\"q0\\\", \\\"q2\\\"),\\n (\\\"q0\\\", \\\"q3\\\"), (\\\"q3\\\", \\\"q0\\\"),\\n (\\\"q3\\\", \\\"q1\\\"), (\\\"q1\\\", \\\"q3\\\"),\\n (\\\"q1\\\", \\\"q4\\\"), (\\\"q4\\\", \\\"q1\\\"),\\n (\\\"q2\\\", \\\"q5\\\"), (\\\"q5\\\", \\\"q2\\\"),\\n (\\\"q5\\\", \\\"q3\\\"), (\\\"q3\\\", \\\"q5\\\"),\\n (\\\"q3\\\", \\\"q6\\\"), (\\\"q6\\\", \\\"q3\\\"),\\n (\\\"q6\\\", \\\"q4\\\"), (\\\"q4\\\", \\\"q6\\\")]\\n\\n cfg = {\\n \\\"eqasm_compiler\\\": \\\"cc_light_compiler\\\",\\n \\\"hardware_settings\\\": {\\n \\\"qubit_number\\\": 7,\\n \\\"cycle_time\\\": 20,\\n \\\"mw_mw_buffer\\\": mw_mw_buffer,\\n \\\"mw_flux_buffer\\\": mw_flux_buffer,\\n \\\"mw_readout_buffer\\\": 0,\\n \\\"flux_mw_buffer\\\": flux_mw_buffer,\\n \\\"flux_flux_buffer\\\": 0,\\n \\\"flux_readout_buffer\\\": 0,\\n \\\"readout_mw_buffer\\\": 0,\\n \\\"readout_flux_buffer\\\": 0,\\n \\\"readout_readout_buffer\\\": 0},\\n \\\"instructions\\\": {},\\n \\\"resources\\\":\\n {\\\"qubits\\\": {\\\"count\\\": 7},\\n \\\"qwgs\\\": {\\\"count\\\": 3,\\n \\\"connection_map\\\":\\n {\\n \\\"0\\\": [0, 1],\\n \\\"1\\\": [2, 3, 4],\\n \\\"2\\\": [5, 6]\\n }\\n },\\n \\\"meas_units\\\": {\\\"count\\\": 7,\\n \\\"connection_map\\\": {\\\"0\\\": [0],\\n \\\"1\\\": [1],\\n \\\"2\\\": [2],\\n \\\"3\\\": [3],\\n \\\"4\\\": [4],\\n \\\"5\\\": [5],\\n \\\"6\\\": [6]\\n }\\n },\\n # FIXME OpenQL #103\\n # \\\"meas_units\\\": {\\\"count\\\": 2,\\n # \\\"connection_map\\\": {\\\"0\\\": [0, 2, 3, 5, 6],\\n # \\\"1\\\": [1, 4]}\\n # },\\n \\\"edges\\\": {\\\"count\\\": 8,\\n \\\"connection_map\\\": {\\n \\\"0\\\": [2],\\n \\\"1\\\": [3],\\n \\\"2\\\": [0],\\n \\\"3\\\": [1],\\n \\\"4\\\": [6],\\n \\\"5\\\": [7],\\n \\\"6\\\": [4],\\n \\\"7\\\": [5]\\n }\\n }\\n },\\n \\\"topology\\\":\\n {\\n \\\"x_size\\\": 5,\\n \\\"y_size\\\": 3,\\n \\\"qubits\\\":\\n [\\n {\\\"id\\\": 0, \\\"x\\\": 1, \\\"y\\\": 2},\\n {\\\"id\\\": 1, \\\"x\\\": 3, \\\"y\\\": 2},\\n {\\\"id\\\": 2, \\\"x\\\": 0, \\\"y\\\": 1},\\n {\\\"id\\\": 3, \\\"x\\\": 2, \\\"y\\\": 1},\\n {\\\"id\\\": 4, \\\"x\\\": 4, \\\"y\\\": 1},\\n {\\\"id\\\": 5, \\\"x\\\": 1, \\\"y\\\": 0},\\n {\\\"id\\\": 6, \\\"x\\\": 3, \\\"y\\\": 0}\\n ],\\n \\\"edges\\\":\\n [\\n {\\\"id\\\": 0, \\\"src\\\": 2, \\\"dst\\\": 0},\\n {\\\"id\\\": 1, \\\"src\\\": 0, \\\"dst\\\": 3},\\n {\\\"id\\\": 2, \\\"src\\\": 3, \\\"dst\\\": 1},\\n {\\\"id\\\": 3, \\\"src\\\": 1, \\\"dst\\\": 4},\\n {\\\"id\\\": 4, \\\"src\\\": 2, \\\"dst\\\": 5},\\n {\\\"id\\\": 5, \\\"src\\\": 5, \\\"dst\\\": 3},\\n {\\\"id\\\": 6, \\\"src\\\": 3, \\\"dst\\\": 6},\\n {\\\"id\\\": 7, \\\"src\\\": 6, \\\"dst\\\": 4}\\n ]\\n },\\n\\n \\\"gate_decomposition\\\": {\\n \\\"measz %0\\\": [\\\"measure %0\\\"],\\n \\\"x %0\\\": [\\\"rx180 %0\\\"],\\n \\\"y %0\\\": [\\\"ry180 %0\\\"],\\n \\\"roty90 %0\\\": [\\\"ry90 %0\\\"],\\n \\\"cnot %0,%1\\\": [\\\"ry90 %1\\\", \\\"cz %0,%1\\\", \\\"ry90 %1\\\"],\\n\\n # To support other forms of writing the same gates\\n \\\"x180 %0\\\": [\\\"rx180 %0\\\"],\\n \\\"y180 %0\\\": [\\\"ry180 %0\\\"],\\n \\\"y90 %0\\\": [\\\"ry90 %0\\\"],\\n \\\"x90 %0\\\": [\\\"rx90 %0\\\"],\\n \\\"my90 %0\\\": [\\\"rym90 %0\\\"],\\n \\\"mx90 %0\\\": [\\\"rxm90 %0\\\"],\\n\\n # Clifford decomposition per Epstein et al. Phys. Rev. A 89, 062321\\n # (2014)\\n \\\"cl_0 %0\\\": ['i %0'],\\n \\\"cl_1 %0\\\": ['ry90 %0', 'rx90 %0'],\\n \\\"cl_2 %0\\\": ['rxm90 %0', 'rym90 %0'],\\n \\\"cl_3 %0\\\": ['rx180 %0'],\\n \\\"cl_4 %0\\\": ['rym90 %0', 'rxm90 %0'],\\n \\\"cl_5 %0\\\": ['rx90 %0', 'rym90 %0'],\\n \\\"cl_6 %0\\\": ['ry180 %0'],\\n \\\"cl_7 %0\\\": ['rym90 %0', 'rx90 %0'],\\n \\\"cl_8 %0\\\": ['rx90 %0', 'ry90 %0'],\\n \\\"cl_9 %0\\\": ['rx180 %0', 'ry180 %0'],\\n \\\"cl_10 %0\\\": ['ry90 %0', 'rxm90 %0'],\\n \\\"cl_11 %0\\\": ['rxm90 %0', 'ry90 %0'],\\n\\n \\\"cl_12 %0\\\": ['ry90 %0', 'rx180 %0'],\\n \\\"cl_13 %0\\\": ['rxm90 %0'],\\n \\\"cl_14 %0\\\": ['rx90 %0', 'rym90 %0', 'rxm90 %0'],\\n \\\"cl_15 %0\\\": ['rym90 %0'],\\n \\\"cl_16 %0\\\": ['rx90 %0'],\\n \\\"cl_17 %0\\\": ['rx90 %0', 'ry90 %0', 'rx90 %0'],\\n \\\"cl_18 %0\\\": ['rym90 %0', 'rx180 %0'],\\n \\\"cl_19 %0\\\": ['rx90 %0', 'ry180 %0'],\\n \\\"cl_20 %0\\\": ['rx90 %0', 'rym90 %0', 'rx90 %0'],\\n \\\"cl_21 %0\\\": ['ry90 %0'],\\n \\\"cl_22 %0\\\": ['rxm90 %0', 'ry180 %0'],\\n \\\"cl_23 %0\\\": ['rx90 %0', 'ry90 %0', 'rxm90 %0']\\n },\\n }\\n\\n for q in qubits:\\n cfg[\\\"instructions\\\"][\\\"prepz {}\\\".format(q)] = {\\n \\\"duration\\\": init_duration,\\n \\\"latency\\\": 0,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": True,\\n \\\"type\\\": \\\"none\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"prepz\\\",\\n \\\"cc_light_codeword\\\": 0,\\n \\\"cc_light_opcode\\\": 2\\n }\\n\\n for q in qubits:\\n cfg[\\\"instructions\\\"][\\\"measure {}\\\".format(q)] = {\\n \\\"duration\\\": ro_duration,\\n \\\"latency\\\": ro_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"readout\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"measz\\\",\\n \\\"cc_light_codeword\\\": 0,\\n \\\"cc_light_opcode\\\": 4\\n }\\n\\n for CW in range(len(lut_map)):\\n for q in qubits:\\n cfg[\\\"instructions\\\"][lut_map[CW].format(q)] = {\\n \\\"duration\\\": mw_pulse_duration,\\n \\\"latency\\\": mw_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"mw\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"cw_{:02}\\\".format(CW),\\n \\\"cc_light_codeword\\\": CW,\\n \\\"cc_light_opcode\\\": 8+CW}\\n\\n cfg[\\\"instructions\\\"]['c1'+lut_map[CW].format(q)] = {\\n \\\"duration\\\": mw_pulse_duration,\\n \\\"latency\\\": mw_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"mw\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"C1_cw_{:02}\\\".format(CW),\\n \\\"cc_light_codeword\\\": CW,\\n \\\"cc_light_opcode\\\": 32+8+CW,\\n \\\"cc_light_cond\\\": 1} # 1 means : do if last meas. == 1\\n\\n\\n cfg[\\\"instructions\\\"]['c0'+lut_map[CW].format(q)] = {\\n \\\"duration\\\": mw_pulse_duration,\\n \\\"latency\\\": mw_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"mw\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"C0_cw_{:02}\\\".format(CW),\\n \\\"cc_light_codeword\\\": CW,\\n \\\"cc_light_opcode\\\": 32+16+CW,\\n \\\"cc_light_cond\\\": 2} # 2 means : do if last meas. == 0\\n\\n\\n for CW in range(32):\\n for q in qubits:\\n cfg[\\\"instructions\\\"][\\\"cw_{:02} {}\\\".format(CW, q)] = {\\n \\\"duration\\\": mw_pulse_duration,\\n \\\"latency\\\": mw_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"mw\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"cw_{:02}\\\".format(CW),\\n \\\"cc_light_codeword\\\": CW,\\n \\\"cc_light_opcode\\\": 8+CW}\\n\\n for q in qubits:\\n cfg[\\\"instructions\\\"][\\\"compensate {}\\\".format(q)] = {\\n \\\"duration\\\": mw_pulse_duration,\\n \\\"latency\\\": mw_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"mw\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"cw_00\\\",\\n \\\"cc_light_codeword\\\": 0,\\n \\\"cc_light_opcode\\\": 8+0}\\n\\n # N.B. The codewords for CZ pulses need to be further specified.\\n # I do not expect this to be correct for now.\\n for ft in flux_tuples:\\n # FIXME add space back in\\n cfg[\\\"instructions\\\"][\\\"cz {},{}\\\".format(ft[0], ft[1])] = {\\n \\\"duration\\\": flux_pulse_duration,\\n \\\"latency\\\": fl_latency,\\n \\\"qubits\\\": [ft[0], ft[1]],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": True,\\n \\\"type\\\": \\\"flux\\\",\\n \\\"cc_light_instr_type\\\": \\\"two_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"fl_cw_{:02}\\\".format(1),\\n \\\"cc_light_right_codeword\\\": 1,\\n \\\"cc_light_left_codeword\\\": 1,\\n \\\"cc_light_opcode\\\": 128+1\\n }\\n\\n for cw_flux in range(8):\\n for ft in flux_tuples:\\n cfg[\\\"instructions\\\"][\\\"fl_cw_{:02} {},{}\\\".format(cw_flux,\\n ft[0], ft[1])] = {\\n \\\"duration\\\": flux_pulse_duration,\\n \\\"latency\\\": fl_latency,\\n \\\"qubits\\\": [ft[0], ft[1]],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": True,\\n \\\"type\\\": \\\"flux\\\",\\n \\\"cc_light_instr_type\\\": \\\"two_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"fl_cw_{:02}\\\".format(cw_flux),\\n \\\"cc_light_right_codeword\\\": cw_flux,\\n \\\"cc_light_left_codeword\\\": cw_flux,\\n \\\"cc_light_opcode\\\": 128+cw_flux\\n }\\n\\n with open(filename, 'w') as f:\\n json.dump(cfg, f, indent=4)\",\n \"def t8_loadFile(self):\\n print \\\"spectrumFile\\\"\\n filename = tkFileDialog.askopenfilename()\\n filename = self.filenameparser(filename)\\n self.t8_filename = filename\",\n \"def read_all_files(\\n pathname: Path, index: int = 0, pattern: str = \\\"dump-Trimer-*.gsd\\\"\\n) -> List[Tuple[Variables, HoomdFrame]]:\\n pathname = Path(pathname)\\n snapshots = []\\n for filename in sorted(glob.glob(str(pathname / pattern))):\\n logger.debug(\\\"Reading %s\\\", Path(filename).stem)\\n with gsd.hoomd.open(str(filename)) as trj:\\n try:\\n snapshots.append((get_filename_vars(filename), HoomdFrame(trj[index])))\\n except IndexError:\\n continue\\n if not snapshots:\\n logger.warning(\\n \\\"There were no files found with a configuration at index %s\\\", index\\n )\\n return snapshots\",\n \"def processFile(filename,length = 256,q=1,fs_in=8000,divide=4,plot=False):\\n length = length*divide\\n #fs = sample rate, sound = multichannel sound signal\\n try:\\n fs1, sound = wavfile.read(filename)\\n except ValueError:\\n print(str(filename) + ' failed to process')\\n return 'failed'\\n if fs1 != fs_in:\\n raise ValueError('Sampling rate should be ' + str(fs_in) + ' for: ' + filename)\\n sig1 = sound[:0] #left channel\\n pre_emphasis = 0.97\\n sig1 = np.append(sig1[0], sig1[1:] - pre_emphasis * sig1[:-1])\\n\\n \\n fs2, sig2 = downsample(sig1,fs1,q)\\n N2 = len(sig2)\\n sig3 = sig2[N2//2-length:N2//2+length]\\n #print(len(sig3))\\n\\n FFT = abs(scipy.fft(sig3))\\n FFT_side = FFT[range(len(FFT)//2)]\\n #freqs = scipy.fftpack.fftfreq(sig3.size, 1/fs2)\\n #plt.plot(freqs,FFT)\\n if len(FFT_side) != length:\\n print('ERROR MESSAGE DETAILS')\\n print('filename: ' + filename)\\n print('length = ' + str(length))\\n print('fs_in = ' + str(fs_in))\\n print('q = ' + str(q))\\n print('divide = ' + str(divide))\\n total_time = len(sig1)/fs1\\n print('total_time = ' + str(total_time))\\n print('Please check: length < total_time*fs//(2*q)')\\n print('Check: ' + str(length) + ' < ' + str(total_time*fs1//(2*q)))\\n raise ValueError('Length FFT_side != length: ' + str(len(FFT_side)) + ' != ' + str(length))\\n \\n \\n FFT_log = []\\n # normalize FFT\\n for value in FFT_side:\\n value = np.log(value)\\n FFT_log.append(value)\\n max_val = getMax(FFT_log)[1]\\n FFT_norm = []\\n for value in FFT_log:\\n FFT_norm.append(value/max_val)\\n \\n \\n FFT_side = np.array(FFT_norm)\\n FFT_divided = FFT_side[range(length//divide)]\\n #plot = True\\n if plot == True:\\n freqs = scipy.fftpack.fftfreq(sig3.size, 1/fs2)\\n freqs_divided = np.array(freqs[range(len(FFT_divided))])\\n plt.plot(freqs_divided,FFT_divided) # plotting the complete fft spectrum\\n plt.show()\\n \\n return FFT_divided\",\n \"def t6_loadFile(self):\\n print \\\"subspectrumFile\\\"\\n filename = tkFileDialog.askopenfilename()\\n filename = \\\"SubSpectrumData/\\\" + self.filenameparser(filename)\\n self.t6_filename = filename\",\n \"def get_files(file_list, mode):\\n\\tfile_set = set(file_list)\\n\\tif \\\"band\\\" in mode:\\n\\t\\tband_all_set = set([\\\"bands.dat.gnu\\\", \\\"freq.plot\\\"])\\n\\t\\tband_file_set = file_set & band_all_set ; remain_file_set = file_set - band_all_set\\n\\t\\tfiles_str = \\\", \\\".join([f\\\"\\\\033[32m{b}\\\\033[0m\\\" for b in band_file_set]) + \\\"; \\\" + \\\", \\\".join(remain_file_set)\\n\\tif mode == \\\"dos\\\":\\n\\t\\tdos_all_set = set([\\\"S.dos\\\"])\\n\\t\\tdos_file_set = file_set & dos_all_set ; remain_file_set = file_set - dos_all_set\\n\\t\\tfiles_str = \\\", \\\".join([f\\\"\\\\033[32m{d}\\\\033[0m\\\" for d in dos_file_set]) + \\\"; \\\" + \\\", \\\".join(remain_file_set)\\n\\tprint(f\\\"Files in the directory: {files_str}\\\"); file = input(\\\"Please choose your file (type one only): \\\")\\n\\treturn file\",\n \"def load_time_streams(self, channels=None):\\n if channels is None:\\n channels = self.get_channels()\\n\\n if self.data is None:\\n self.make_temp_data(channels=channels)\\n elif self.data.shape[0] != channels.size:\\n self.discard_temp_data()\\n self.make_temp_data(channels=channels)\\n\\n frames = self.integration.frames\\n fnf.load_timestream(\\n frame_data=frames.data,\\n frame_weights=frames.relative_weight,\\n frame_valid=frames.valid,\\n modeling_frames=frames.is_flagged('MODELING_FLAGS'),\\n channel_indices=channels.indices,\\n sample_flags=frames.sample_flag,\\n timestream=self.data,\\n points=self.points)\",\n \"def read_inputs(self):\\n curdir = os.getcwd()\\n os.chdir(self.fst_dir)\\n rstat = self.readFST()\\n if rstat == 0:\\n os.chdir(curdir)\\n return 0\\n # the names of the next files are either set by caller or come from the reading the FAST file\\n rstat = self.readNoise()\\n rstat = self.readAD()\\n rstat = self.readBlade()\\n rstat = self.readPtfm()\\n os.chdir(curdir)\",\n \"def get_per_lib_sff_fps(sff_dir):\\r\\n for dirpath, dirnames, fnames in walk(sff_dir):\\r\\n for fname in fnames:\\r\\n if fname.endswith('.sff'):\\r\\n libname, _ = splitext(fname)\\r\\n yield libname, join(dirpath, fname)\",\n \"def get_audio():\\n\\tbuf = None\\n\\tnum_new_bytes = BUFFER_SIZE // REFRESH_BUFFER_FACTOR\\n\\twith open(INFILE) as fifo:\\n\\t\\twhile True:\\n\\t\\t\\tif buf is None:\\n\\t\\t\\t\\tbuf = fifo.read(BUFFER_SIZE)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tbuf = buf[num_new_bytes:] + fifo.read(num_new_bytes)\\n\\t\\t\\tyield buf\",\n \"def t1_loadFile(self):\\n print \\\"subspectrumFile\\\"\\n filename = tkFileDialog.askopenfilename()\\n filename = self.filenameparser(filename)\\n self.t1_filename = filename\",\n \"def _default_specs(self):\\n # Spectrometer specs\\n self.model = \\\"Flame-S\\\" # Spectrometer model\\n self.fov = None # Field of view fo spectrometer\\n self.ILS = None # Number array holding instrument line shape (possibly don't hold this here?)\\n self.pix_num = 2048 # Number of pixels\\n self.bit_depth = 16 # Bit depth of spectrometer detector\\n\\n # File information\\n self.file_ext = '.npy' # Spectra saved as numpy array\\n self.file_ss = '{}ss' # Shutter speed format spec\\n self.file_spec_type = {'meas': 'Plume', 'dark': 'Dark', 'cal': 'ppmm', 'clear': 'Clear'}\\n self.file_datestr = \\\"%Y-%m-%dT%H%M%S\\\" # Date/time format spec in filename\\n\\n\\n\\n # Acquisition settings\\n self.start_int_time = 100 # Starting integration time\\n self.start_coadd = 5 # Number of spectra to coadd\\n self.framerate = 1 # Framerate of acquisitions (Hz)\\n self.wavelengths = None # Wavelengths (nm)\\n self.spectrum = None # Spectrum\\n self.spectrum_filename = None # Filename for spectrum\\n\\n self.auto_int = True # Bool for requesting automated integration time adjustment\\n self.min_saturation = 0.5 # Minimum saturation accepted before adjusting shutter speed (if auto_ss is True)\\n self.max_saturation = 0.9 # Maximum saturation accepted before adjusting shutter speed (if auto_ss is True)\\n self.saturation_range = [320, 330] # Range of wavelengths used in checking integration time\\n\\n # Predefined list of integration times for automatic exposure adjustment\\n self.int_list = np.concatenate((np.arange(1, 10, 1),\\n np.arange(10, 50, 5),\\n np.arange(50, 100, 10),\\n np.arange(100, 500, 50),\\n np.arange(500, 1000, 100),\\n np.arange(10 ** 3, 10 ** 4, 500),\\n np.array([10 ** 4])))\",\n \"def main():\\r\\n\\r\\n ### Choose and Import File\\r\\n\\r\\n inSound = Sound()\\r\\n\\r\\n rate = inSound.rate\\r\\n data = inSound.data\\r\\n dataLength = len(data)\\r\\n \\r\\n info = inSound.get_info()\\r\\n head, filename = os.path.split(info[0]) # get filename of input\\r\\n \\r\\n # Decide output directory and filename\\r\\n outDir = r'out'\\r\\n outFile = os.path.join(outDir, 'out_'+filename)\\r\\n\\r\\n # Check if data has multiple channels, if yes use only one\\r\\n if(len(data.shape) > 1):\\r\\n data = data[:,0]\\r\\n\\r\\n\\r\\n ### Set All Parameters\\r\\n\\r\\n #get parameters from user dialogue\\r\\n params = getParameters()\\r\\n\\r\\n numChannels = params['numChannels'][0] # number of Channels\\r\\n loFreq = params['loFreq'][0] # lower bound on frequencies\\r\\n hiFreq = params['hiFreq'][0] # upper bound on frequencies\\r\\n plotChannels = params['plotChannels'][0] # if it should plot the Gammatone channels\\r\\n block_time = params['block_time'][0] # in ms\\r\\n block_shift = params['block_shift'][0] # in ms\\r\\n selectChannels = params['selectChannels'][0] # number of channels to activate at a single time\\r\\n\\r\\n\\r\\n ### Filter input file\\r\\n\\r\\n filtered, channel_fs = filterDataGamaTone(data, rate, numChannels, loFreq, hiFreq, plotChannels)\\r\\n\\r\\n\\r\\n ### Gammatones -> Stimulation Amplitude for time block\\r\\n\\r\\n samples_in_block = np.floor(block_time * rate / 1000).astype('int')\\r\\n samples_in_shift = np.floor(block_shift * rate / 1000).astype('int')\\r\\n\\r\\n summed = gammatoneToAmplitude(filtered, samples_in_block, samples_in_shift)\\r\\n\\r\\n # only activate the n electrodes that have the largest stimulation\\r\\n amps = n_largest_channels(summed, n=selectChannels)\\r\\n\\r\\n \\r\\n #### Sound reconstruction\\r\\n\\r\\n # for each timeblock we need to duplicate enough samples to fill it at sample rate\\r\\n amps_samples = np.repeat(amps, samples_in_shift, axis=1)\\r\\n #trim end to get same length as input\\r\\n amps_samples = amps_samples[:,:dataLength] \\r\\n\\r\\n # from amplitude samples and frequencies, reconstruct sound\\r\\n res_data = generateSound(amps_samples, channel_fs, rate)\\r\\n\\r\\n\\r\\n ### Write to output file\\r\\n write(outFile, rate, res_data)\\r\\n print('Wrote file to: \\\\n' + outFile)\",\n \"def get_frame_list(self):\\r\\n\\r\\n logger.debug('Executing frame extraction')\\r\\n\\r\\n frames_loaded = False\\r\\n\\r\\n # Try to load YAML file with frame list\\r\\n if os.path.exists(self.frames_file_path):\\r\\n\\r\\n print 'Loading YAML file with frame list'\\r\\n logger.debug('Loading YAML file with frame list')\\r\\n\\r\\n f_list = utils.load_YAML_file(self.frames_file_path)\\r\\n\\r\\n if f_list:\\r\\n self.frame_list = f_list\\r\\n\\r\\n print 'YAML file with frame_list loaded'\\r\\n logger.debug('YAML file with frame_list loaded')\\r\\n\\r\\n frames_loaded = True\\r\\n\\r\\n if not frames_loaded:\\r\\n\\r\\n print '\\\\n\\\\n### Frame extraction ###\\\\n'\\r\\n logger.debug('\\\\n\\\\n### Frame extraction ###\\\\n')\\r\\n\\r\\n # Save processing time\\r\\n start_time = cv2.getTickCount()\\r\\n\\r\\n if not (os.path.exists(self.frames_path)):\\r\\n os.makedirs(self.frames_path)\\r\\n\\r\\n # Counter for all frames\\r\\n frame_counter = 0\\r\\n\\r\\n # Value of frame_counter for last analyzed frame\\r\\n last_anal_frame = 0\\r\\n\\r\\n # Open video file\\r\\n capture = cv2.VideoCapture(self.resource_path)\\r\\n\\r\\n self.frame_list = []\\r\\n\\r\\n # Save parameters for this video\\r\\n param_dict = {}\\r\\n\\r\\n if capture is None or not capture.isOpened():\\r\\n\\r\\n error = 'Error in opening video file'\\r\\n\\r\\n print error\\r\\n logger.debug(error)\\r\\n\\r\\n return\\r\\n\\r\\n else:\\r\\n\\r\\n video_fps = capture.get(cv2.cv.CV_CAP_PROP_FPS)\\r\\n\\r\\n param_dict[c.VIDEO_FPS_KEY] = video_fps\\r\\n\\r\\n # Original number of frames\\r\\n tot_frames = capture.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT)\\r\\n\\r\\n param_dict[c.VIDEO_TOT_FRAMES_KEY] = tot_frames\\r\\n\\r\\n self.fps = video_fps\\r\\n\\r\\n self.video_frames = float(tot_frames)\\r\\n\\r\\n # Saved frames\\r\\n saved_frames = 0\\r\\n\\r\\n while True:\\r\\n\\r\\n # Read frame\\r\\n ret, frame = capture.read()\\r\\n\\r\\n # If no frame is read, abort\\r\\n if not ret:\\r\\n break\\r\\n\\r\\n used_fps = c.USED_FPS\\r\\n use_or_fps = c.USE_ORIGINAL_FPS\\r\\n use_or_res = c.USE_ORIGINAL_RES\\r\\n used_res_scale_factor = c.USED_RES_SCALE_FACTOR\\r\\n\\r\\n if self.params is not None:\\r\\n\\r\\n if c.USED_FPS_KEY in self.params:\\r\\n used_fps = self.params[c.USED_FPS_KEY]\\r\\n\\r\\n if c.USE_ORIGINAL_FPS_KEY in self.params:\\r\\n use_or_fps = self.params[c.USE_ORIGINAL_FPS_KEY]\\r\\n\\r\\n if c.USE_ORIGINAL_RES_KEY in self.params:\\r\\n use_or_res = self.params[c.USE_ORIGINAL_RES_KEY]\\r\\n\\r\\n if c.USED_RES_SCALE_FACTOR_KEY in self.params:\\r\\n used_res_scale_factor = self.params[\\r\\n c.USED_RES_SCALE_FACTOR_KEY]\\r\\n\\r\\n # Next frame to be analyzed\\r\\n next_frame = last_anal_frame + (video_fps / used_fps) - 1\\r\\n\\r\\n if use_or_fps or (frame_counter > next_frame):\\r\\n\\r\\n # Frame position in video in milliseconds\\r\\n elapsed_ms = capture.get(cv2.cv.CV_CAP_PROP_POS_MSEC)\\r\\n\\r\\n # print 'elapsed video s =', elapsed_video_s\\r\\n\\r\\n fr_name = '%07d.png' % frame_counter\\r\\n\\r\\n frame_path = os.path.join(self.frames_path, fr_name)\\r\\n\\r\\n # Resize frame\\r\\n if not use_or_res:\\r\\n fx = used_res_scale_factor\\r\\n\\r\\n fy = used_res_scale_factor\\r\\n\\r\\n interp = cv2.INTER_AREA\\r\\n\\r\\n frame = cv2.resize(src=frame, dsize=(0, 0),\\r\\n fx=fx, fy=fy,\\r\\n interpolation=interp)\\r\\n\\r\\n cv2.imwrite(frame_path, frame,\\r\\n [cv.CV_IMWRITE_PNG_COMPRESSION, 0])\\r\\n\\r\\n frame_dict = {c.SAVED_FRAME_NAME_KEY: fr_name,\\r\\n c.ELAPSED_VIDEO_TIME_KEY: int(elapsed_ms)}\\r\\n\\r\\n self.frame_list.append(frame_dict)\\r\\n\\r\\n last_anal_frame = frame_counter\\r\\n\\r\\n saved_frames += 1\\r\\n\\r\\n frame_counter += 1\\r\\n\\r\\n self.progress = 100 * (frame_counter / self.video_frames)\\r\\n\\r\\n print('progress: ' + str(self.progress) + ' % \\\\r'),\\r\\n\\r\\n del capture\\r\\n\\r\\n self.saved_frames = float(saved_frames)\\r\\n\\r\\n param_dict[c.VIDEO_SAVED_FRAMES_KEY] = self.saved_frames\\r\\n\\r\\n # Save frame list in YAML file\\r\\n utils.save_YAML_file(self.frames_file_path, self.frame_list)\\r\\n\\r\\n # Save video parameters in YAML file\\r\\n\\r\\n utils.save_YAML_file(self.params_file_path, param_dict)\\r\\n\\r\\n # Save processing time\\r\\n time_in_clocks = cv2.getTickCount() - start_time\\r\\n time_in_seconds = time_in_clocks / cv2.getTickFrequency()\\r\\n\\r\\n print 'Time for frame extraction:', str(time_in_seconds), 's\\\\n'\\r\\n logger.debug(\\r\\n 'Time for frame extraction:', str(time_in_seconds), 's\\\\n')\\r\\n\\r\\n self.anal_times[c.FRAME_EXTRACTION_TIME_KEY] = time_in_seconds\\r\\n\\r\\n utils.save_YAML_file(self.analysis_file_path, self.anal_times)\",\n \"def split_into_frames(filename_raw, thr_var_per_event=5e-4, downsampling_factor=2, disable_display=False,\\n filename_output_video=None):\\n\\n assert downsampling_factor == int(downsampling_factor), \\\"Error: downsampling_factor must be an integer\\\"\\n assert downsampling_factor >= 0, \\\"Error: downsampling_factor must be >= 0\\\"\\n\\n mv_adaptive_rate_iterator = AdaptiveRateEventsIterator(input_path=filename_raw,\\n thr_var_per_event=thr_var_per_event,\\n downsampling_factor=downsampling_factor)\\n\\n height, width = mv_adaptive_rate_iterator.get_size()\\n\\n if filename_output_video == None:\\n video_process = None\\n else:\\n assert not os.path.exists(filename_output_video)\\n video_process = FFmpegWriter(filename_output_video)\\n\\n if video_process or not disable_display:\\n img_bgr = np.zeros((height, width, 3), dtype=np.uint8)\\n\\n cv2.namedWindow(\\\"img\\\", cv2.WINDOW_NORMAL)\\n\\n for events in mv_adaptive_rate_iterator:\\n assert events.size > 0\\n start_ts = events[0][\\\"t\\\"]\\n end_ts = events[-1][\\\"t\\\"]\\n print(\\\"frame: {} -> {} delta_t: {} fps: {} nb_ev: {}\\\".format(start_ts, end_ts,\\n end_ts - start_ts,\\n 1e6 / (end_ts - start_ts),\\n events.size))\\n if video_process or not disable_display:\\n img = events_to_diff_image(events, sensor_size=(height, width))\\n img_bgr[...] = 0\\n img_bgr[img < 0, 0] = 255\\n img_bgr[img > 0, 1] = 255\\n\\n chunk_start_ts = events[0][\\\"t\\\"]\\n chunk_end_ts = events[-1][\\\"t\\\"]\\n delta_t_frame = chunk_end_ts - chunk_start_ts + 1\\n frame_txt = \\\"ts: {} -> {} delta_t: {} fps: {} (nb_ev): {}\\\".format(chunk_start_ts, chunk_end_ts,\\n delta_t_frame,\\n int(1.e6/delta_t_frame),\\n events.size)\\n img_bgr[20:45, ...] = 0\\n cv2.putText(img_bgr,\\n frame_txt,\\n (int(0.05 * width), 40),\\n cv2.FONT_HERSHEY_PLAIN, 1.0, (200, 200, 100))\\n\\n if video_process:\\n video_process.writeFrame(img_bgr.astype(np.uint8)[..., ::-1])\\n if not disable_display:\\n cv2.imshow(\\\"img\\\", img_bgr)\\n if cv2.waitKey(1) & 0xFF == ord('q'):\\n break\\n\\n if video_process:\\n video_process.close()\\n if not disable_display:\\n cv2.destroyAllWindows()\",\n \"def get_fps(vid_path, prefix):\\n _, name = os.path.split(vid_path)\\n i1 = name.find(prefix) + len(prefix)\\n i2 = name[i1:].find('_')\\n fps = int(name[i1:i1+i2])\\n\\n return fps\",\n \"def load_batch(self, fpath, match, in_num):\\n if in_num == None:\\n in_num = input('Please specify IN number: ')\\n\\n if match == None:\\n match = input('Please specify filename string to match for batch loading (ex. \\\\'_s2_\\\\'): ')\\n\\n # get a list of all matching files\\n glob_match = f'{fpath}/*{match}*'\\n files = glob.glob(glob_match)\\n\\n # load & concatenate files into a single dataframe\\n data = pd.concat((pd.read_csv(file, header = [0, 1], index_col = 0, parse_dates=True, low_memory=False) for file in files)).sort_index()\\n\\n # extract sampling frequency\\n s_freq = 1/(data.index[1] - data.index[0]).total_seconds()\\n\\n # reset the index to continuous time\\n ind_freq = str(int(1/s_freq*1000000))+'us'\\n ind_start = '1900-01-01 00:00:00.000'\\n ind = pd.date_range(start = ind_start, periods=len(data), freq=ind_freq)\\n data.index = ind\\n\\n # set metadata & attributes\\n self.metadata = {'file_info':{'in_num': in_num, 'files': files, 'dir': fpath,\\n 'match_phrase': match},\\n 'analysis_info':{'s_freq': s_freq} }\\n self.data = data\\n self.s_freq = s_freq\",\n \"def get_file_params(file_path):\\n fpath, ftype = parse_path(file_path=file_path)\\n\\n if ftype == \\\"video\\\":\\n volume, dims = get_video_params(video_path=fpath)\\n else:\\n volume, dims = get_image_params(image_path=fpath)\\n\\n return volume, dims\",\n \"def FitsLookup(raw_filenames, config, config_arguments):\\n\\n warnings.filterwarnings('ignore')\\n\\n # Initialize the filelist and the progressbar variable smeantime and\\n # total_len\\n\\n filelist = list()\\n meantime = list()\\n\\n total_len = len(raw_filenames)\\n\\n # Loop over each file in raw_filenames getting the desired information\\n\\n for cont, filename in enumerate(raw_filenames):\\n\\n # Start the time measure\\n start = time.time()\\n\\n # Get the file header\\n header = fits.getheader(filename)\\n\\n # Extract the filetipe and classify it\\n typestr = header[config.exposure_type]\\n\\n if typestr == config.science_type_id:\\n img_type = 0\\n elif typestr == config.dark_type_id or typestr == config.bias_type_id:\\n img_type = 1\\n elif typestr == config.flat_type_id:\\n img_type = 2\\n else:\\n img_type = 3\\n\\n # Extract the filter\\n\\n filter = header[config.filter]\\n\\n # Extract the date and correct it with the time convention (night ->\\n # 12:00 to 11:59)\\n night = datetime.datetime.strptime(\\n header[config.observed_date], config.date_format)\\n\\n if night.hour < 12:\\n night = night.date() - datetime.timedelta(days=1)\\n\\n # Extract the exposure time\\n\\n exptime = header[config.expousure_time]\\n\\n # ---- HOW TO ADD MORE CLASSIFIERS TO THE RESULTING NUMPY ARRAY ------\\n #\\n # Using the header variable and the config_values dictionary you can\\n # extract all the values from the file. For example, to extract the temp:\\n #\\n # >>> temp = header[config_values['temp']]\\n #\\n # Once you have your new variable, you have to add this to the filelist in\\n # the code after this comment. For example, to add the temp in the previous-to-last\\n # entry:\\n #\\n # >>> filelist.append((filename, type, filter, exptime, str(night), temp, header))\\n #\\n # Finally, you have to modify the numpy dtype. Following with our example, as the temp\\n # is a float value, we can modify the dtype as:\\n #\\n # >>> dtype = np.dtype([('filename', 'S150'), ('type', int),\\n # ('filter', 'S10'), ('exptime', int), ('night', 'S10'),\\n # ('temp',float),('header', np.object)])\\n #\\n # Notice that the position of the new type in the dtype variable MUST match the position\\n # in which you added your new variable to the filelist. As we added \\\"temp\\\" previous-to-last,\\n # we have to add ('temp',float) in the position previous-to-last in the dtype.\\n #\\n # Now, you can use 'temp' for slicing, broadcasting and perform cool numpy stuff in the resulting\\n # array. Also, this value will work in the filter_collection function.\\n # Yay!\\n\\n # Append all the information to the filelist. MODIFY HERE IF NEEDED!\\n\\n filelist.append((filename, img_type, filter,\\n exptime, str(night), header))\\n\\n # Update progress bar\\n\\n end = time.time()\\n meantime.append(end - start)\\n\\n if config_arguments.verbose_flag and not config_arguments.no_interaction:\\n update_progress(float(cont + 1) / total_len,\\n np.mean(meantime) * (total_len - (cont + 1)))\\n\\n # Create the personalized dtype of the numpy array. MODIFY HERE IF NEEDED!\\n\\n dtype = np.dtype([('filename', 'S150'), ('type', int),\\n ('filter', 'S10'), ('exptime', int), ('night', 'S10'), ('header', np.object)])\\n\\n return np.array(filelist, dtype=dtype)\",\n \"def read_file(self, *args, **kwargs):\\n if self.detector == \\\"FACET\\\":\\n return self.read_facet(self.filename)\\n elif self.detector == \\\"OpenFace\\\":\\n return self.read_openface(self.filename)\\n elif self.detector == \\\"Affectiva\\\":\\n return self.read_affectiva(self.filename)\\n elif self.detector == \\\"Feat\\\":\\n return self.read_feat(self.filename)\\n else:\\n print(\\\"Must specifiy which detector [Feat, FACET, OpenFace, or Affectiva]\\\")\",\n \"def get_sorted_fps_U(data_dir, max = 988):\\n\\n fps = os.listdir(data_dir)\\n\\n #extract index of timestep from file name\\n idx_fps = []\\n for fp in fps:\\n _, file_number = fp.split(\\\"LSBU_\\\")\\n #file_number is of form '<IDX>.vtu'\\n idx = int(file_number.replace(\\\".vtu\\\", \\\"\\\"))\\n idx_fps.append(idx)\\n\\n\\n #sort by timestep\\n assert len(idx_fps) == len(fps)\\n zipped_pairs = zip(idx_fps, fps)\\n fps_sorted = [x for _, x in sorted(zipped_pairs)]\\n\\n #add absolute path\\n fps_sorted = [data_dir + x for x in fps_sorted]\\n\\n return fps_sorted\",\n \"def gen_random_samples():\\n if os.path.exists('Song_Samples'):\\n pass\\n else:\\n os.mkdir('Song_Samples')\\n for filename in os.listdir(\\\"Songs\\\"):\\n rate, data = wavfile.read(os.path.join(\\\"Songs\\\", filename))\\n song_duration = len(data) // rate\\n start_point = randint(0, song_duration - SAMPLE_DURATION)\\n end_point = start_point + SAMPLE_DURATION\\n subprocess.call(['ffmpeg', '-i', os.path.join(\\\"Songs\\\", filename),\\n '-ss', str(datetime.timedelta(seconds=start_point)), '-to',\\n str(datetime.timedelta(seconds=end_point)), '-y', os.path.join(\\\"Song_Samples\\\", filename)])\",\n \"def listfile(self):\\n print(\\\"Opened file(s):\\\")\\n for f in self.fmap:\\n print('\\\\t%s'%(self.files.index(self.fmap[f])),end=':')\\n print(f)\\n print(\\\"active file(s):\\\")\\n for i in range(len(self.handle)):\\n print('\\\\t%s'%(self.handle[i]),end=':')\\n print(self.fname[i])\",\n \"def analyzeWAV(inputFile):\\n data, fs, nbits = audiolab.wavread(inputFile)\\n samplingRate = fs\\n return [data, samplingRate]\",\n \"def get_file_parameters(self, input_file):\\n\\n #\\n # Read the Flag record.\\n #\\n input_file.seek(0, 0) # 0 = from start of file\\n record = input_file.read(FLAG_RECORD_SIZE)\\n\\n #\\n # Check for end of file.\\n # If not reached, check for and parse a Flag record.\\n #\\n if len(record) != FLAG_RECORD_SIZE:\\n log.warn(\\\"EOF reading for flag record\\\")\\n raise SampleException(\\\"EOF reading for flag record\\\")\\n \\n (valid_record, regex_velocity_record, \\n regex_end_velocity_record, format_unpack_velocity, \\n record_size) = self.parse_flag_record(record)\\n\\n #\\n # If there is a valid Flag record, process the Time record.\\n #\\n if valid_record:\\n #\\n # Read the Time record which is at the very end of the file.\\n # Note that we don't care if the number of bytes between the\\n # Flag record and the Time record is consistent with\\n # the flags from the Flag record.\\n # Put the file back at the beginning.\\n #\\n input_file.seek(0 - TIME_RECORD_SIZE, 2) # 2 = from end of file\\n record = input_file.read(TIME_RECORD_SIZE)\\n times = self.parse_time_record(record)\\n input_file.seek(0, 0) # 0 = from start of file\\n\\n #\\n # If the Flag record is invalid, we're done.\\n #\\n else:\\n log.warn(\\\"Invalid Flag record\\\")\\n raise SampleException(\\\"Invalid Flag record\\\")\\n\\n return valid_record, regex_velocity_record, regex_end_velocity_record, \\\\\\n format_unpack_velocity, record_size, times\",\n \"def stream_callback(self, in_data, frame_count, time_info, status_flags):\\n time_delta = time.time() - self.last_frame_timestamp\\n if time_delta == 0:\\n time_delta = sys.float_info.min\\n fps = int(1.0 / time_delta)\\n self.last_frame_timestamp = time.time()\\n if DEBUG:\\n self.fps_deque.append(fps)\\n avg_fps = 0\\n for frame_fps in self.fps_deque:\\n avg_fps += frame_fps\\n avg_fps /= len(self.fps_deque)\\n self.log_fps(self.last_frame_timestamp, fps)\\n sys.stdout.write(\\\"\\\\r{} FPS\\\".format(avg_fps))\\n sys.stdout.flush()\\n self.data = np.frombuffer(in_data, dtype=np.float32)\\n if self.binned:\\n self.binned_fft()\\n self.fft_callback(self.fft_bins_y)\\n else:\\n self.fft()\\n self.fft_callback(self.spec_y)\\n if self.send_osc:\\n self.send_fft_osc()\\n return (None, pyaudio.paContinue)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5744633","0.57154065","0.55288815","0.54487276","0.5439408","0.54362303","0.5347286","0.5314243","0.5279614","0.5239958","0.520664","0.51828444","0.51358587","0.5131761","0.512756","0.5109966","0.5094053","0.5076949","0.506344","0.50362504","0.50106287","0.5003939","0.49958327","0.4977757","0.4976107","0.4975934","0.49716818","0.49677575","0.49623752","0.49622005","0.4941165","0.49404126","0.49318156","0.49178287","0.49156016","0.49128598","0.49070635","0.4896532","0.48932263","0.48868906","0.4886267","0.48785222","0.48734403","0.4865664","0.48649555","0.48562545","0.48558593","0.4850635","0.48485953","0.48476753","0.48454657","0.48414516","0.48402402","0.48336652","0.48330194","0.48307776","0.4826017","0.48221713","0.4821404","0.48211533","0.48183635","0.48159438","0.48146063","0.4814167","0.48114172","0.4810892","0.4809791","0.48073974","0.48064935","0.48056442","0.48053905","0.4805257","0.48044065","0.48037535","0.48035145","0.47994787","0.47923705","0.4790374","0.47826442","0.47817174","0.4778898","0.4768832","0.4765199","0.4760815","0.47571167","0.47509256","0.47439137","0.47392637","0.47375327","0.4736299","0.47296375","0.47292328","0.47286195","0.4727771","0.47262043","0.47239682","0.4721006","0.47205734","0.47077465","0.47012672","0.4694251"],"string":"[\n \"0.5744633\",\n \"0.57154065\",\n \"0.55288815\",\n \"0.54487276\",\n \"0.5439408\",\n \"0.54362303\",\n \"0.5347286\",\n \"0.5314243\",\n \"0.5279614\",\n \"0.5239958\",\n \"0.520664\",\n \"0.51828444\",\n \"0.51358587\",\n \"0.5131761\",\n \"0.512756\",\n \"0.5109966\",\n \"0.5094053\",\n \"0.5076949\",\n \"0.506344\",\n \"0.50362504\",\n \"0.50106287\",\n \"0.5003939\",\n \"0.49958327\",\n \"0.4977757\",\n \"0.4976107\",\n \"0.4975934\",\n \"0.49716818\",\n \"0.49677575\",\n \"0.49623752\",\n \"0.49622005\",\n \"0.4941165\",\n \"0.49404126\",\n \"0.49318156\",\n \"0.49178287\",\n \"0.49156016\",\n \"0.49128598\",\n \"0.49070635\",\n \"0.4896532\",\n \"0.48932263\",\n \"0.48868906\",\n \"0.4886267\",\n \"0.48785222\",\n \"0.48734403\",\n \"0.4865664\",\n \"0.48649555\",\n \"0.48562545\",\n \"0.48558593\",\n \"0.4850635\",\n \"0.48485953\",\n \"0.48476753\",\n \"0.48454657\",\n \"0.48414516\",\n \"0.48402402\",\n \"0.48336652\",\n \"0.48330194\",\n \"0.48307776\",\n \"0.4826017\",\n \"0.48221713\",\n \"0.4821404\",\n \"0.48211533\",\n \"0.48183635\",\n \"0.48159438\",\n \"0.48146063\",\n \"0.4814167\",\n \"0.48114172\",\n \"0.4810892\",\n \"0.4809791\",\n \"0.48073974\",\n \"0.48064935\",\n \"0.48056442\",\n \"0.48053905\",\n \"0.4805257\",\n \"0.48044065\",\n \"0.48037535\",\n \"0.48035145\",\n \"0.47994787\",\n \"0.47923705\",\n \"0.4790374\",\n \"0.47826442\",\n \"0.47817174\",\n \"0.4778898\",\n \"0.4768832\",\n \"0.4765199\",\n \"0.4760815\",\n \"0.47571167\",\n \"0.47509256\",\n \"0.47439137\",\n \"0.47392637\",\n \"0.47375327\",\n \"0.4736299\",\n \"0.47296375\",\n \"0.47292328\",\n \"0.47286195\",\n \"0.4727771\",\n \"0.47262043\",\n \"0.47239682\",\n \"0.4721006\",\n \"0.47205734\",\n \"0.47077465\",\n \"0.47012672\",\n \"0.4694251\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":81787,"cells":{"query":{"kind":"string","value":"Here just return frame from loaded data"},"document":{"kind":"string","value":"def getFrame(self, num):\n\n return self.data[:, :, num]"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def load_data(self):","def load_data(self) -> None:","def _get_raw_data(self, idx=0):\n # Get the time step then make a data frame\n raise NotImplementedError('Code me up!')\n #data = self._data[???]\n return data","def dataframe(self):\n\t\treturn self._dataframe","def dataframe(self):\n frames = []\n for game in self.__iter__():\n df = game.dataframe\n if df is not None:\n frames.append(df)\n if frames == []:\n return None\n return pd.concat(frames)","def __init__(self, dataFrame):\n self.dataFrame = dataFrame","def dataFrame(self):\n return self._dataFrame","def get_frame_data(self):\n # FrameObject is a dictionary of slot names and values.\n frameObject = self.pgdb.sendPgdbFnCall('get-frame-object', self.frameid)\n if not frameObject:\n raise PythonCycError(\"Could not retrieve frame \"+self.frameid+\" from organism (orgid) \"+self.pgdb._orgid)\n else:\n self._gotframe = True\n # Modify slot names to allow Python's syntax (e.g., '_' instead of '-').\n for slot in frameObject:\n self.__dict__[convertLispIdtoPythonId(slot)] = frameObject[slot]\n return self","def load_dataframe(self, path, type_='raw'):\r\n if type_ == 'raw':\r\n return pd.read_csv(path).to_numpy()[:, 1]\r\n elif type_ == 'features':\r\n return pd.read_csv(path, sep=' ', header=None).to_numpy()\r\n else:\r\n raise Exception(\"No type found!\")","def get_data(self)->pd.DataFrame:\n pass","def data_frame(self, arg=None):\n if arg is None:\n return pl.DataFrame()\n if isinstance(arg, pl.DataFrame):\n return arg\n if isinstance(arg, pl.LazyFrame):\n return arg.collect()\n return pl.DataFrame(arg)","def getDataframe(self):\n self._loadCSVFile()\n self._cleanProcessDf()\n return self._df","def load_own_data():\n data = Data()\n features = data.read_selected_features()\n dataframe = data.get_dataframe_with(features)\n return normalize(dataframe.values)","def __load( self, raw_content ):\n return( pd.read_csv( BytesIO( raw_content ) ) )","def load():\n return load_pandas()","def __data_frame(self):\n return self._trajectory","def _data_frame(content):\n response = loads(content)\n key = [x for x in response.keys() if x in c.response_data][0]\n frame = DataFrame(response[key])\n final_frame = _convert(frame)\n return final_frame","def dataframe_extended(self):\n frames = []\n for game in self.__iter__():\n df = game.dataframe_extended\n if df is not None:\n frames.append(df)\n if frames == []:\n return None\n return pd.concat(frames)","def dataframe(self):\n return self.generator.dataframe","def load_data(self):\n raise NotImplementedError()","def data(self):\n return self._frame.copy(deep=True)","def load_data_frame(name):\n\n return DataFrame(name).load()","def _read_data(self):","def read(self, fname, frame=None):\n\n self.resetvals()\n url = urlparse(fname)\n if not self.url:\n self.url = url\n# if frame:\n# self.hdf5_location.set_index(frame)\n self.filename = self.url.path\n if os.path.isfile(self.filename):\n self.hdf5 = h5py.File(self.filename, \"r\")\n else:\n error = \"No such file or directory: %s\" % self.filename\n logger.error(error)\n raise RuntimeError(error)\n self.ds = self.hdf5[self.url.query]\n if isinstance(self.ds, h5py.Group) and (\"data\" in self.ds):\n self.ds = self.ds[\"data\"]\n\n if self.url.fragment:\n slices = self.get_slice()\n self.data = self.ds[self.get_slice()]\n self.nframes = self.ds.shape[self.main_dim]\n else:\n self.data = self.ds[:]\n self.nframes = 1\n self.dim2, self.dim1 = self.data.shape\n self.bytecode = str(self.data.dtype)\n return self","def load_data(self):\n return self._load_data","def _load_data(self):\n\n if not self._cache.exists(config.DATAFRAME_SONG_DATA):\n source_path = os.path.join(config.S3_SONG_DATA, 'A/A/A/*.json') # Note: song database is way big, so we get only a slice of it.\n dataframe = self._get_spark_session().read.json(source_path)\n self._cache.set_source(config.DATAFRAME_SONG_DATA, dataframe)","def post_load(self, data):\n return data","def loader():\n bucket = data_load_variables[\"bucket\"]\n\n if data_load_variables[\"use_lite_dataset\"]:\n dataset_name = data_load_variables[\"lite_dataset_name\"]\n else:\n dataset_name = data_load_variables[\"dataset_name\"]\n\n s3 = boto3.client('s3')\n\n obj = s3.get_object(Bucket=bucket, Key=dataset_name)\n # get object and file (key) from bucket\n\n df = pd.read_csv(obj['Body'])\n return df","def test_frame_to_rows(self):\n pass","def load_data():\n dictionary = corpora.Dictionary.load(app.config['DICTIONARY'])\n matrix = similarities.MatrixSimilarity.load(app.config['MATRIX'])\n model = models.LsiModel.load(app.config['MODEL'])\n df = pd.read_pickle(app.config['DATA_FRAME'])\n return Data(matrix=matrix, model=model, dictionary=dictionary, data_frame=df)","def getDataFrame(self):\n return self.df","def _get_data(self):\n project_name, experiment_id = self.parent._get_parent_identifiers()\n\n self._data = self.repository.get_dataframe_data(\n project_name, self.id, experiment_id=experiment_id\n )","def _load_data(self, comp=None):\n\t\tif comp is None:\n\t\t\tcomp = self._compensation\n\t\tmatrix = self._fcsfile.read_data(fmt='matrix',\n\t\t\tcomp=comp)\n\t\treturn pd.DataFrame(matrix, columns=self._channels)","def load(self):","def load_from_open_file(self, df):\n df.seek(self.pos_start)\n self.data = df.read(self.length).decode('latin1').splitlines()\n self.loaded = True\n return self.data","def _get_frame_data(self):\n\n def _text_formatting(bs4_tag):\n \"\"\"Simple formatting that will be called a lot\"\"\"\n return bs4_tag.get_text().replace('\\n', '')\n\n tables = Character._get_main_page(self._fd).find_all('table', {'class': 'wikitable'})\n result = {}\n for table in tables:\n rows = table.find_all('tr')\n for row in rows:\n move = row.find('th')\n\n if move is not None:\n move_small = move.find('small')\n else:\n continue\n\n if move_small is not None:\n move_name = move.get_text().replace(move_small.get_text(), ' ' + move_small.get_text()).replace(\n '\\n', '')\n else:\n move_name = _text_formatting(move)\n\n move_name = move_name.replace('+', '') # B+C fix\n fd = row.find_all('td')\n\n try:\n result.update({\n move_name: {\n \"Damage\": _text_formatting(fd[0]),\n \"Cancel\": _text_formatting(fd[1]),\n \"Attribute\": _text_formatting(fd[4]),\n \"Guard\": _text_formatting(fd[5]),\n \"Startup\": _text_formatting(fd[6]),\n \"Active\": _text_formatting(fd[7]),\n \"Recovery\": _text_formatting(fd[8]),\n \"Frame Adv\": _text_formatting(fd[9]),\n \"Blockstun\": _text_formatting(fd[11]),\n \"Invul/GP\": _text_formatting(fd[19])\n }\n })\n except (AttributeError, IndexError):\n continue\n\n return result","def _load_df_or_array(self, key: str, idx: Union[None, np.ndarray] = None) -> Union[pd.DataFrame, np.ndarray]:\n if key == self.actions_key:\n if idx is None:\n data = pd.read_hdf(self.path, key=key)\n else:\n data = pd.read_hdf(self.path, key=key, where=idx)\n else:\n with h5py.File(self.path, 'r') as f:\n if idx is None:\n data = f[key][...]\n else:\n data = f[key][idx, ...]\n\n return data","def get_frame(freq: str):\n url = 'http://minikep-db.herokuapp.com/api/frame?freq={}'.format(freq)\n return pd.read_csv(url, converters={0: pd.to_datetime}, index_col=0)","def test_dataframe(self):\n\n url=\"http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data\"\n readerobject=requester.url_to_df(url)\n self.assertIsInstance(readerobject,pd.DataFrame)","def process_frame(self, frame):\n\t\treturn frame","def __init__(self, df):\n self.data = df","def load_data(filename) :\r\n data = Data()\r\n data.load(filename)\r\n return data","def load() -> DataFrame:\n return load_file(__file__, \"default.csv.gz\")","def glass_pandas(self):\n # pandas.set_option('display.width', 120)\n # TODO timeit (git_implementation) vs (my_implementation)\n # * df = pd.DataFrame(json.loads(r.text))\n # * df = df.set_index('t')\n # * df.index = pd.to_datetime(df.index, unit='s')\n # * df = df.sort_index()\n # * s = df.v\n # * s.name = '_'.join(url.split('/')[-2:])\n # * return s\n # for elem in self.loaded:\n # _metric, _data = elem[1]['_metrics'], elem[1]['_data']\n # try:\n # frame_keys = ['t'] + list(_data[0]['o'].keys())\n # framed = pandas.DataFrame(\n # data=[{k: (_data[iters]['t'] if k in 't' else _data[iters]['o'][k])\n # for k in frame_keys} for iters in range(len(_data))],\n # columns=frame_keys)\n # except KeyError:\n # framed = pandas.DataFrame(_data)\n # framed.set_index('t', inplace=True)\n # framed.index = pandas.to_datetime(\n # framed.index.to_flat_index(), unit='s', infer_datetime_format=True)\n # framed.sort_index(inplace=True)\n # framed.name = _metric\n # print(framed.name)\n # print(framed)","def load_vox(data: pd.DataFrame, in_place: bool = False):\n if not in_place:\n mod = data.copy()\n else:\n mod = data\n clips = []\n channels = []\n samplerates = []\n durations = []\n for i, row in mod.iterrows():\n sys.stdout.write(f\"\\r[-] Reading: {i} of {len(mod)} ({i / len(mod) * 100: .2f}%)\")\n sys.stdout.flush()\n with audioread.audio_open(row['file']) as f:\n channels.append(f.channels)\n samplerates.append(f.samplerate)\n durations.append(f.duration)\n data = bytearray()\n for buf in f:\n data = data + buf\n clips.append(data)\n sys.stdout.write(f\"\\r[ ] Read {len(mod)} files into DataFrame.\\r\\n\")\n sys.stdout.flush()\n mod['audio'] = pd.Series(clips)\n mod['channels'] = pd.Series(channels)\n mod['samplerate'] = pd.Series(samplerates)\n mod['duration'] = pd.Series(durations)\n return mod","def get_data(self):","def load_data():\n #read from S3\n df_obs = pd.read_csv('https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/df_obs.csv')\n df_sen = pd.read_csv('https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/df_sentry.csv')\n \n \n #background image to be used\n img_url = 'https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/map_detailed_723.jpeg'\n img_response = requests.get(img_url)\n img = Image.open(BytesIO(img_response.content))\n \n \n #apply translation of coordinates\n df_obs['x'] = df_obs['x'] - 64\n df_obs['y'] = df_obs['y'] - 64\n df_sen['x'] = df_sen['x'] - 64\n df_sen['y'] = df_sen['y'] - 64\n\n #convert time to minutes\n df_obs['time'] = df_obs['time']/60\n df_sen['time'] = df_sen['time']/60\n\n \n return df_obs, df_sen, img","def data(self):\n return self.as_named_DataFrame()","def extract(self) -> pd.core.frame.DataFrame:\n pass","def read(self):\n\n if self.filename.endswith(\".pkl\"):\n logging.debug(\"Loading pickle file %s\", self.filename)\n data = pd.read_pickle(self.filename)\n\n elif self.filename.endswith(\".hdf5\"):\n logging.debug(\"Loading HDF5 file %s\", self.filename)\n with h5py.File(self.filename, \"r\") as data_file:\n\n data = pd.DataFrame(\n {\n column: data_file[\"/haloTrees/%s\" % column].value\n for column in self.columns\n }\n ).set_index(\"nodeIndex\")\n\n # with open(\"./data/cache.pkl\", \"w\") as pickle_file:\n # data.to_pickle(pickle_file)\n\n else:\n raise TypeError(\"Unknown filetype %s\" % self.filename)\n\n return data","def data_frame_creator(self):\n\n rgb_dir = [\n self.dataset_address + sequence_f + rgb_f\n for rgb_f in self.rgb_folder for sequence_f in self.sequence_folder\n ]\n rgb_data = [\n rgb_d + rgb for rgb_d in rgb_dir for rgb in os.listdir(rgb_d)\n ]\n\n depth_dir = [\n self.dataset_address + sequence_f + depth_f\n for depth_f in self.depth_folder\n for sequence_f in self.sequence_folder\n ]\n depth_data = [\n depth_d + depth for depth_d in depth_dir\n for depth in os.listdir(depth_d)\n ]\n\n segmentation_dir = [\n self.dataset_address + sequence_f + segmentation_f\n for segmentation_f in self.segmentation_folder\n for sequence_f in self.sequence_folder\n ]\n segmentation_data = [\n segmentation_d + segmentation\n for segmentation_d in segmentation_dir\n for segmentation in os.listdir(segmentation_d)\n ]\n\n dataset = {\n 'RGB': rgb_data,\n 'DEPTH': depth_data,\n 'SEGMENTATION': segmentation_data\n }\n\n if self.shuffle:\n return pd.DataFrame(dataset).sample(frac=1)\n\n return pd.DataFrame(dataset)","def data_specific_processing(self, dataframe):\n return dataframe","def load_data(dataset_path: str):\n data = arff.loadarff(dataset_path)\n data_frame = pd.DataFrame(data[0])\n return data_frame","def intialize_source():\n raw = loadmat(\"p300backrec2.mat\")\n channels_raw = raw['channels']\n channels = []\n for i in channels_raw[0]:\n channels.extend(list(i))\n X = raw['data']\n marker = raw['marker']\n return X,channels,marker","def process_frames(self, data):\n pass","def process_frames(self, data):\n pass","def process_frames(self, data):\n pass","def process_frames(self, data):\n pass","def process_frames(self, data):\n pass","def get_frame(self, row):\n\n if row not in self.frames:\n if not self.write:\n d = self.memmap[row, :, :]\n if self.file.metadata['interleave'] == 'bil':\n d = d.T\n self.frames[row] = d.copy()\n else:\n self.frames[row] = s.nan * s.zeros((self.n_cols, self.n_bands))\n return self.frames[row]","def get_frame(self, ind):\n pass","def get_frame(self, f):\n return self._frames[f, :]","def load(self) -> pd.DataFrame:\n if os.path.exists(self.file_name):\n df = pd.read_csv(self.file_name, index_col=0)\n df = self._clean(df)\n else:\n _LOG.debug(\"No file '%s'\", self.file_name)\n df = pd.DataFrame()\n return df","def sourceToDataframe(self):\n df = pd.read_excel(self.filename)\n df.columns = df.iloc[10]\n df = df.drop(df.index[:11])\n self.df = df #makes this df accessible to the whole class now\n self.insertODN()\n display(df.head())","def _load(self):\n # Extract the ASCII header (5 first lines)\n with open(self._xst_bin, 'rb') as f:\n header = list(islice(f, 0, 5))\n assert header[0] == b'HeaderStart\\n',\\\n 'Wrong header start'\n assert header[-1] == b'HeaderStop\\n',\\\n 'Wrong header stop'\n header = [s.decode('utf-8') for s in header]\n hd_size = sum([len(s) for s in header])\n\n # Parse informations into a metadata dictionnary\n keys = ['freq', 'ma', 'accu']\n search = ['Freq.List', 'Mr.List', 'accumulation']\n types = ['float64', 'int', 'int']\n for key, word, typ in zip(keys, search, types):\n for h in header:\n if word in h:\n self.meta[key] = np.array(\n h.split('=')[1].split(','),\n dtype=typ\n )\n\n # Deduce the dtype for decoding\n n_ma = self.meta['ma'].size\n n_sb = self.meta['freq'].size\n dtype = np.dtype(\n [('jd', 'float64'),\n ('data', 'complex64', (n_sb, n_ma*n_ma*2 + n_ma))]\n )\n\n # Decoding the binary file\n tmp = np.memmap(\n filename=self._xst_bin,\n dtype='int8',\n mode='r',\n offset=hd_size\n )\n decoded = tmp.view(dtype)\n\n self.data = decoded['data'] / self.meta['accu']\n self.time = Time(decoded['jd'], format='jd', precision=0)\n\n return","def load_processed_data(animal, name, arguments):\r\n\tpath = os.path.join(paths.path2Output, animal, str(arguments['Function']), \r\n\t\t\t\t\t\tstr(arguments['Init']), str(arguments['Rank']), name)\r\n\t\r\n\tmeta_df = pd.read_csv(os.path.join(path,'meta_df.csv'))\r\n\troi_tensor = np.load(os.path.join(path,'roi_tensor.npy'))\r\n\tacti = np.load(os.path.join(path,'acti.npy'))\r\n\tnorm_acti = np.load(os.path.join(path,'norm_acti.npy'))\r\n\tsmoothed_acti = np.load(os.path.join(path,'smoothed_acti.npy'))\r\n\r\n\r\n\treturn meta_df, roi_tensor, acti, norm_acti, smoothed_acti","def read_frame(self):\n return self.decode_frame(self.grab_frame())","def load_data(self, data):\n\n if type(data) is \"json\":\n dataF = pd.read_json(data)\n elif type(data) is list:\n dataF = pd.DataFrame(data)\n else:\n print(\"Other types not implemented\")\n return\n dataF = self.__process_data(dataF)\n self.__dataF = dataF","def __load( self, json_blob ):\n return pd.read_json( json_blob, orient='split' )","def dataframe_extended(self):\n return self.boxscore.dataframe","def load_from_database(filename,key):\n\t# Opening file\n\tstore = pd.HDFStore(filename)\n\t# getting the df\n\tdata = store[key]\n\t# And its metadata\n\tmetadata = store.get_storer(key).attrs.metadata\n\tstore.close()\n\t# Ok returning the data now\n\treturn data, metadata","def loadFringe(self, frame=1, filename=None):\n self.currentFrame = np.int(frame)\n if filename:\n ofdPath = filename\n else:\n ofdPath = os.path.join(self.directory, self.basename +'.ofd')\n\n self.getOfdInfo(ofdPath)\n\n if self.mode == '2channel':\n self.load2Channel()\n if self.mode == '1channel':\n self.load1Channel()\n if self.mode == 'mmap2channel':\n self.mmap2channel()\n if self.mode == 'mmap1channel':\n self.mmap1channel()","def load_data_part(fname):\n if \"_data\" not in fname:\n return None\n # Read data\n data = pd.read_csv(fname)\n # events file\n events_fname = fname.replace('_data', '_events')\n # read event file\n labels = pd.read_csv(events_fname)\n clean = data.drop(['id'], axis=1) # remove id\n labels = labels.drop(['id'], axis=1) # remove id\n return clean, labels","def forward(self, raw_X):\n return make_df(raw_X, self.features)","def data_frame_creator(self):\n sequence_folder = [\n '/SEQ1', '/SEQ2', '/SEQ3', '/SEQ4', '/SEQ5', '/SEQ6'\n ]\n rgb_folder = ['/RGBLeft/', '/RGBRight/']\n depth_folder = ['/DepthLeft/', '/DepthRight/']\n segmentation_folder = ['/GTLeft/', '/GTright/']\n rgb_dir = [\n self.dataset_dir + sequence_f + rgb_f for rgb_f in rgb_folder\n for sequence_f in sequence_folder\n ]\n rgb_data = [\n rgb_d + rgb for rgb_d in rgb_dir for rgb in os.listdir(rgb_d)\n ]\n\n depth_dir = [\n self.dataset_dir + sequence_f + depth_f\n for depth_f in depth_folder\n for sequence_f in sequence_folder\n ]\n depth_data = [\n depth_d + depth for depth_d in depth_dir\n for depth in os.listdir(depth_d)\n ]\n\n segmentation_dir = [\n self.dataset_dir + sequence_f + segmentation_f\n for segmentation_f in segmentation_folder\n for sequence_f in sequence_folder\n ]\n segmentation_data = [\n segmentation_d + segmentation\n for segmentation_d in segmentation_dir\n for segmentation in os.listdir(segmentation_d)\n ]\n\n dataset = {\n 'RGB': rgb_data,\n 'DEPTH': depth_data,\n 'SEGMENTATION': segmentation_data\n }\n\n if self.shuffle:\n return pd.DataFrame(dataset).sample(frac=1, random_state=123)\n\n return pd.DataFrame(dataset)","def load(self):\n\n\t\t# Check if dataset location exists\n\t\tif (not os.path.exists(self._location)):\n\t\t\tprint(\"Error: Dataset location does not exist\")\n\t\t\treturn\n\n\t\tself._frames = sorted(glob.glob(self._location + '/frame*.jpg'))\n\n\t\t# Check if startFrame is beyond dataset bounds\n\t\tif (self._startFrame > len(self._frames)):\n\t\t\tprint(\"Error: Start frame is beyond dataset bounds\")\n\t\t\treturn\n\n\t\t# Check if endFrame is beyond dataset bounds\n\t\tif (self._endFrame > len(self._frames)):\n\t\t\tprint(\"Warning: End frame beyond dataset bounds, setting to end of dataset\")\n\n\t\t# Start buffering threads\n\t\tself._bufferThreadStopped = False\n\t\tself._bufferingThread.start()","def record_data_frame(self):\n return self._record.data_frame","def _load_data(data, n_prev=3):\n docX, docY = [], []\n for i in range(len(data)-n_prev):\n docX.append(data.data.iloc[i:i+n_prev])\n docY.append(data.response.iloc[i+n_prev]) \n\n alsX = np.array(docX)\n alsY = np.array(docY)\n return np.matrix(alsX), np.matrix(alsY).T","def dataframe(self):\n return self.get_target().dataframe()","def _setup_dataframe(self, serie, metadata=None):\n header = self.get_data_header(serie, dataset='cnv')\n df = self.get_data_in_frame(serie, header, dataset='cnv')\n df = self.df_handler.map_column_names_of_dataframe(df)\n\n return df","def get_frame(self, index):\n filename = self.get_filename(index)\n return plt.imread(fname=filename)","def get_zyla_data_object(evt, src):\n o = evt.get(_psana.Zyla.FrameV1, src)\n if o is not None: return o\n\n return None","def _dataframe_from_feather(fn, **kwargs):\n\treturn pd.read_feather(fn, **kwargs)","def load_data():\n d = load_wine()\n data = {colname: d.data[:, i] for i, colname in enumerate(d.feature_names)}\n data[\"target\"] = d.target\n return pd.DataFrame(data)","def _get_data(self):\n raise NotImplementedError()","def _loadData(self, data):\n Movie._loadData(self, data)\n PlexHistory._loadData(self, data)","def loadDataOrig(df, path, im_shape, disp_names=False):\r\n X, y = [], []\r\n for i, item in df.iterrows():\r\n if disp_names == True:\r\n print('i={} {} {}\\n'.format(i, path + item[0], path + item[1]))\r\n img = io.imread(path + item[0])\r\n img = transform.resize(img, im_shape, mode='constant')\r\n img = np.expand_dims(img, -1)\r\n mask = io.imread(path + item[1])\r\n mask = transform.resize(mask, im_shape, mode='constant')\r\n mask = np.expand_dims(mask, -1)\r\n X.append(img)\r\n y.append(mask)\r\n break\r\n X = np.array(X)\r\n y = np.array(y)\r\n\r\n if disp_names == True:\r\n print('X/shape={} y.shape={}\\n'.format(X.shape, y.shape))\r\n\r\n X -= X.mean()\r\n X /= X.std()\r\n\r\n if disp_names == True:\r\n print('### Data loaded')\r\n print('\\t{}'.format(path))\r\n print('\\t{}\\t{}'.format(X.shape, y.shape))\r\n # print( '\\tX:{:.1f}-{:.1f}\\ty:{:.1f}-{:.1f}\\n'.format(X.min(), X.max(), y.min(), y.max()) )\r\n print('\\tX.mean = {}, X.std = {}'.format(X.mean(), X.std()))\r\n print('\\n')\r\n\r\n return X, y","def read_file(fname: str) -> pd.DataFrame:\n raw_data = (\n pd.read_hdf(fname).to_frame().reset_index(level=[0, 1]).loc[ANALYSIS_DATE]\n )\n raw_data[\"date\"] = raw_data.index\n return raw_data","def get_fli_data_object(evt, src):\n o = evt.get(_psana.Fli.FrameV1, src)\n if o is not None: return o\n\n return None","def as_dframe(cls, dataset):\n return dataset.dframe()","def __local_df(soup):\n return __get_local_g1_news(soup)","def __local_df(soup):\n return __get_local_g1_news(soup)","def load(fnames, tag=None, inst_id=None):\n\n if not fnames:\n print('fnames are go')\n warnings.warn('You no got no fname, you no get no data')\n return pysat.DataFrame(None), pysat.Meta(None)\n elif len(fnames) == 1:\n print('fnames are greater than 1')\n meta = pysat.Meta()\n signal_meta = pysat.Meta()\n\n # load the rinex\n data = gr.load(fnames[0])\n # get the metadata from the xarray.Dataset\n xr_attrs = data.attrs\n # format the metadata\n# for at in xr_attrs:\n# print(type(at))\n# meta[at] = {'units': '', 'long_name': at}\n# keys = data.data_vars.keys()\n# for key in keys:\n# # find the xarray equivalents of units and long_name\n# print(key)\n# signal_meta[key] = {meta.labels.units: var_units[key][0],\n# meta.labels.name: var_units[key][1]}\n# # format the data\n# meta['signals'] = signal_meta\n# output = data.variables\n return data, meta\n else:\n raise ValueError('Only one filename currently supported')\n print('no idea wahts goin on')","def load_data(READFILE,load_type=1):\n df = pd.read_csv(READFILE)\n if 'type' in df.columns and load_type is not None:\n df = pd.DataFrame(df[df.type==1])\n df = df.drop('type',axis=1)\n return df","def load(self):\n data = pandas.read_csv(self.path, names=self.names)\n return data","def read(name, db):\n \n # Make connection with the database\n\tconn = sqlite3.connect(db)\n\tdf = pd.read_sql_query(\"select * from \" + name + ';', conn)\n \n # Print loaded data table name and return DataFrame\n\tprint(name + ': loaded')\n\treturn df","def dataFrame(self):\n\n memory_file = StringIO(initial_value=self.sparql_result.decode('utf-8'), newline='\\n')\n reader = DictReader(memory_file)\n\n schema = StructType(\n list(map(lambda f: StructField(f, StringType()), reader.fieldnames))\n )\n\n data = list(map(lambda d: [d[f] for f in reader.fieldnames], list(reader)))\n\n return self.spark.createDataFrame(data, schema)","def __load( self, raw_content ):\n return( pd.read_excel( BytesIO( raw_content ) ) )","def get_data():\n pass","def dataframe(self):\n return self._df","def get_frame_at_index(self, index):\n begin = index\n end = begin + self.frame_size\n\n if begin < 0:\n return self.data\n\n return self.data[begin:end]"],"string":"[\n \"def load_data(self):\",\n \"def load_data(self) -> None:\",\n \"def _get_raw_data(self, idx=0):\\n # Get the time step then make a data frame\\n raise NotImplementedError('Code me up!')\\n #data = self._data[???]\\n return data\",\n \"def dataframe(self):\\n\\t\\treturn self._dataframe\",\n \"def dataframe(self):\\n frames = []\\n for game in self.__iter__():\\n df = game.dataframe\\n if df is not None:\\n frames.append(df)\\n if frames == []:\\n return None\\n return pd.concat(frames)\",\n \"def __init__(self, dataFrame):\\n self.dataFrame = dataFrame\",\n \"def dataFrame(self):\\n return self._dataFrame\",\n \"def get_frame_data(self):\\n # FrameObject is a dictionary of slot names and values.\\n frameObject = self.pgdb.sendPgdbFnCall('get-frame-object', self.frameid)\\n if not frameObject:\\n raise PythonCycError(\\\"Could not retrieve frame \\\"+self.frameid+\\\" from organism (orgid) \\\"+self.pgdb._orgid)\\n else:\\n self._gotframe = True\\n # Modify slot names to allow Python's syntax (e.g., '_' instead of '-').\\n for slot in frameObject:\\n self.__dict__[convertLispIdtoPythonId(slot)] = frameObject[slot]\\n return self\",\n \"def load_dataframe(self, path, type_='raw'):\\r\\n if type_ == 'raw':\\r\\n return pd.read_csv(path).to_numpy()[:, 1]\\r\\n elif type_ == 'features':\\r\\n return pd.read_csv(path, sep=' ', header=None).to_numpy()\\r\\n else:\\r\\n raise Exception(\\\"No type found!\\\")\",\n \"def get_data(self)->pd.DataFrame:\\n pass\",\n \"def data_frame(self, arg=None):\\n if arg is None:\\n return pl.DataFrame()\\n if isinstance(arg, pl.DataFrame):\\n return arg\\n if isinstance(arg, pl.LazyFrame):\\n return arg.collect()\\n return pl.DataFrame(arg)\",\n \"def getDataframe(self):\\n self._loadCSVFile()\\n self._cleanProcessDf()\\n return self._df\",\n \"def load_own_data():\\n data = Data()\\n features = data.read_selected_features()\\n dataframe = data.get_dataframe_with(features)\\n return normalize(dataframe.values)\",\n \"def __load( self, raw_content ):\\n return( pd.read_csv( BytesIO( raw_content ) ) )\",\n \"def load():\\n return load_pandas()\",\n \"def __data_frame(self):\\n return self._trajectory\",\n \"def _data_frame(content):\\n response = loads(content)\\n key = [x for x in response.keys() if x in c.response_data][0]\\n frame = DataFrame(response[key])\\n final_frame = _convert(frame)\\n return final_frame\",\n \"def dataframe_extended(self):\\n frames = []\\n for game in self.__iter__():\\n df = game.dataframe_extended\\n if df is not None:\\n frames.append(df)\\n if frames == []:\\n return None\\n return pd.concat(frames)\",\n \"def dataframe(self):\\n return self.generator.dataframe\",\n \"def load_data(self):\\n raise NotImplementedError()\",\n \"def data(self):\\n return self._frame.copy(deep=True)\",\n \"def load_data_frame(name):\\n\\n return DataFrame(name).load()\",\n \"def _read_data(self):\",\n \"def read(self, fname, frame=None):\\n\\n self.resetvals()\\n url = urlparse(fname)\\n if not self.url:\\n self.url = url\\n# if frame:\\n# self.hdf5_location.set_index(frame)\\n self.filename = self.url.path\\n if os.path.isfile(self.filename):\\n self.hdf5 = h5py.File(self.filename, \\\"r\\\")\\n else:\\n error = \\\"No such file or directory: %s\\\" % self.filename\\n logger.error(error)\\n raise RuntimeError(error)\\n self.ds = self.hdf5[self.url.query]\\n if isinstance(self.ds, h5py.Group) and (\\\"data\\\" in self.ds):\\n self.ds = self.ds[\\\"data\\\"]\\n\\n if self.url.fragment:\\n slices = self.get_slice()\\n self.data = self.ds[self.get_slice()]\\n self.nframes = self.ds.shape[self.main_dim]\\n else:\\n self.data = self.ds[:]\\n self.nframes = 1\\n self.dim2, self.dim1 = self.data.shape\\n self.bytecode = str(self.data.dtype)\\n return self\",\n \"def load_data(self):\\n return self._load_data\",\n \"def _load_data(self):\\n\\n if not self._cache.exists(config.DATAFRAME_SONG_DATA):\\n source_path = os.path.join(config.S3_SONG_DATA, 'A/A/A/*.json') # Note: song database is way big, so we get only a slice of it.\\n dataframe = self._get_spark_session().read.json(source_path)\\n self._cache.set_source(config.DATAFRAME_SONG_DATA, dataframe)\",\n \"def post_load(self, data):\\n return data\",\n \"def loader():\\n bucket = data_load_variables[\\\"bucket\\\"]\\n\\n if data_load_variables[\\\"use_lite_dataset\\\"]:\\n dataset_name = data_load_variables[\\\"lite_dataset_name\\\"]\\n else:\\n dataset_name = data_load_variables[\\\"dataset_name\\\"]\\n\\n s3 = boto3.client('s3')\\n\\n obj = s3.get_object(Bucket=bucket, Key=dataset_name)\\n # get object and file (key) from bucket\\n\\n df = pd.read_csv(obj['Body'])\\n return df\",\n \"def test_frame_to_rows(self):\\n pass\",\n \"def load_data():\\n dictionary = corpora.Dictionary.load(app.config['DICTIONARY'])\\n matrix = similarities.MatrixSimilarity.load(app.config['MATRIX'])\\n model = models.LsiModel.load(app.config['MODEL'])\\n df = pd.read_pickle(app.config['DATA_FRAME'])\\n return Data(matrix=matrix, model=model, dictionary=dictionary, data_frame=df)\",\n \"def getDataFrame(self):\\n return self.df\",\n \"def _get_data(self):\\n project_name, experiment_id = self.parent._get_parent_identifiers()\\n\\n self._data = self.repository.get_dataframe_data(\\n project_name, self.id, experiment_id=experiment_id\\n )\",\n \"def _load_data(self, comp=None):\\n\\t\\tif comp is None:\\n\\t\\t\\tcomp = self._compensation\\n\\t\\tmatrix = self._fcsfile.read_data(fmt='matrix',\\n\\t\\t\\tcomp=comp)\\n\\t\\treturn pd.DataFrame(matrix, columns=self._channels)\",\n \"def load(self):\",\n \"def load_from_open_file(self, df):\\n df.seek(self.pos_start)\\n self.data = df.read(self.length).decode('latin1').splitlines()\\n self.loaded = True\\n return self.data\",\n \"def _get_frame_data(self):\\n\\n def _text_formatting(bs4_tag):\\n \\\"\\\"\\\"Simple formatting that will be called a lot\\\"\\\"\\\"\\n return bs4_tag.get_text().replace('\\\\n', '')\\n\\n tables = Character._get_main_page(self._fd).find_all('table', {'class': 'wikitable'})\\n result = {}\\n for table in tables:\\n rows = table.find_all('tr')\\n for row in rows:\\n move = row.find('th')\\n\\n if move is not None:\\n move_small = move.find('small')\\n else:\\n continue\\n\\n if move_small is not None:\\n move_name = move.get_text().replace(move_small.get_text(), ' ' + move_small.get_text()).replace(\\n '\\\\n', '')\\n else:\\n move_name = _text_formatting(move)\\n\\n move_name = move_name.replace('+', '') # B+C fix\\n fd = row.find_all('td')\\n\\n try:\\n result.update({\\n move_name: {\\n \\\"Damage\\\": _text_formatting(fd[0]),\\n \\\"Cancel\\\": _text_formatting(fd[1]),\\n \\\"Attribute\\\": _text_formatting(fd[4]),\\n \\\"Guard\\\": _text_formatting(fd[5]),\\n \\\"Startup\\\": _text_formatting(fd[6]),\\n \\\"Active\\\": _text_formatting(fd[7]),\\n \\\"Recovery\\\": _text_formatting(fd[8]),\\n \\\"Frame Adv\\\": _text_formatting(fd[9]),\\n \\\"Blockstun\\\": _text_formatting(fd[11]),\\n \\\"Invul/GP\\\": _text_formatting(fd[19])\\n }\\n })\\n except (AttributeError, IndexError):\\n continue\\n\\n return result\",\n \"def _load_df_or_array(self, key: str, idx: Union[None, np.ndarray] = None) -> Union[pd.DataFrame, np.ndarray]:\\n if key == self.actions_key:\\n if idx is None:\\n data = pd.read_hdf(self.path, key=key)\\n else:\\n data = pd.read_hdf(self.path, key=key, where=idx)\\n else:\\n with h5py.File(self.path, 'r') as f:\\n if idx is None:\\n data = f[key][...]\\n else:\\n data = f[key][idx, ...]\\n\\n return data\",\n \"def get_frame(freq: str):\\n url = 'http://minikep-db.herokuapp.com/api/frame?freq={}'.format(freq)\\n return pd.read_csv(url, converters={0: pd.to_datetime}, index_col=0)\",\n \"def test_dataframe(self):\\n\\n url=\\\"http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data\\\"\\n readerobject=requester.url_to_df(url)\\n self.assertIsInstance(readerobject,pd.DataFrame)\",\n \"def process_frame(self, frame):\\n\\t\\treturn frame\",\n \"def __init__(self, df):\\n self.data = df\",\n \"def load_data(filename) :\\r\\n data = Data()\\r\\n data.load(filename)\\r\\n return data\",\n \"def load() -> DataFrame:\\n return load_file(__file__, \\\"default.csv.gz\\\")\",\n \"def glass_pandas(self):\\n # pandas.set_option('display.width', 120)\\n # TODO timeit (git_implementation) vs (my_implementation)\\n # * df = pd.DataFrame(json.loads(r.text))\\n # * df = df.set_index('t')\\n # * df.index = pd.to_datetime(df.index, unit='s')\\n # * df = df.sort_index()\\n # * s = df.v\\n # * s.name = '_'.join(url.split('/')[-2:])\\n # * return s\\n # for elem in self.loaded:\\n # _metric, _data = elem[1]['_metrics'], elem[1]['_data']\\n # try:\\n # frame_keys = ['t'] + list(_data[0]['o'].keys())\\n # framed = pandas.DataFrame(\\n # data=[{k: (_data[iters]['t'] if k in 't' else _data[iters]['o'][k])\\n # for k in frame_keys} for iters in range(len(_data))],\\n # columns=frame_keys)\\n # except KeyError:\\n # framed = pandas.DataFrame(_data)\\n # framed.set_index('t', inplace=True)\\n # framed.index = pandas.to_datetime(\\n # framed.index.to_flat_index(), unit='s', infer_datetime_format=True)\\n # framed.sort_index(inplace=True)\\n # framed.name = _metric\\n # print(framed.name)\\n # print(framed)\",\n \"def load_vox(data: pd.DataFrame, in_place: bool = False):\\n if not in_place:\\n mod = data.copy()\\n else:\\n mod = data\\n clips = []\\n channels = []\\n samplerates = []\\n durations = []\\n for i, row in mod.iterrows():\\n sys.stdout.write(f\\\"\\\\r[-] Reading: {i} of {len(mod)} ({i / len(mod) * 100: .2f}%)\\\")\\n sys.stdout.flush()\\n with audioread.audio_open(row['file']) as f:\\n channels.append(f.channels)\\n samplerates.append(f.samplerate)\\n durations.append(f.duration)\\n data = bytearray()\\n for buf in f:\\n data = data + buf\\n clips.append(data)\\n sys.stdout.write(f\\\"\\\\r[ ] Read {len(mod)} files into DataFrame.\\\\r\\\\n\\\")\\n sys.stdout.flush()\\n mod['audio'] = pd.Series(clips)\\n mod['channels'] = pd.Series(channels)\\n mod['samplerate'] = pd.Series(samplerates)\\n mod['duration'] = pd.Series(durations)\\n return mod\",\n \"def get_data(self):\",\n \"def load_data():\\n #read from S3\\n df_obs = pd.read_csv('https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/df_obs.csv')\\n df_sen = pd.read_csv('https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/df_sentry.csv')\\n \\n \\n #background image to be used\\n img_url = 'https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/map_detailed_723.jpeg'\\n img_response = requests.get(img_url)\\n img = Image.open(BytesIO(img_response.content))\\n \\n \\n #apply translation of coordinates\\n df_obs['x'] = df_obs['x'] - 64\\n df_obs['y'] = df_obs['y'] - 64\\n df_sen['x'] = df_sen['x'] - 64\\n df_sen['y'] = df_sen['y'] - 64\\n\\n #convert time to minutes\\n df_obs['time'] = df_obs['time']/60\\n df_sen['time'] = df_sen['time']/60\\n\\n \\n return df_obs, df_sen, img\",\n \"def data(self):\\n return self.as_named_DataFrame()\",\n \"def extract(self) -> pd.core.frame.DataFrame:\\n pass\",\n \"def read(self):\\n\\n if self.filename.endswith(\\\".pkl\\\"):\\n logging.debug(\\\"Loading pickle file %s\\\", self.filename)\\n data = pd.read_pickle(self.filename)\\n\\n elif self.filename.endswith(\\\".hdf5\\\"):\\n logging.debug(\\\"Loading HDF5 file %s\\\", self.filename)\\n with h5py.File(self.filename, \\\"r\\\") as data_file:\\n\\n data = pd.DataFrame(\\n {\\n column: data_file[\\\"/haloTrees/%s\\\" % column].value\\n for column in self.columns\\n }\\n ).set_index(\\\"nodeIndex\\\")\\n\\n # with open(\\\"./data/cache.pkl\\\", \\\"w\\\") as pickle_file:\\n # data.to_pickle(pickle_file)\\n\\n else:\\n raise TypeError(\\\"Unknown filetype %s\\\" % self.filename)\\n\\n return data\",\n \"def data_frame_creator(self):\\n\\n rgb_dir = [\\n self.dataset_address + sequence_f + rgb_f\\n for rgb_f in self.rgb_folder for sequence_f in self.sequence_folder\\n ]\\n rgb_data = [\\n rgb_d + rgb for rgb_d in rgb_dir for rgb in os.listdir(rgb_d)\\n ]\\n\\n depth_dir = [\\n self.dataset_address + sequence_f + depth_f\\n for depth_f in self.depth_folder\\n for sequence_f in self.sequence_folder\\n ]\\n depth_data = [\\n depth_d + depth for depth_d in depth_dir\\n for depth in os.listdir(depth_d)\\n ]\\n\\n segmentation_dir = [\\n self.dataset_address + sequence_f + segmentation_f\\n for segmentation_f in self.segmentation_folder\\n for sequence_f in self.sequence_folder\\n ]\\n segmentation_data = [\\n segmentation_d + segmentation\\n for segmentation_d in segmentation_dir\\n for segmentation in os.listdir(segmentation_d)\\n ]\\n\\n dataset = {\\n 'RGB': rgb_data,\\n 'DEPTH': depth_data,\\n 'SEGMENTATION': segmentation_data\\n }\\n\\n if self.shuffle:\\n return pd.DataFrame(dataset).sample(frac=1)\\n\\n return pd.DataFrame(dataset)\",\n \"def data_specific_processing(self, dataframe):\\n return dataframe\",\n \"def load_data(dataset_path: str):\\n data = arff.loadarff(dataset_path)\\n data_frame = pd.DataFrame(data[0])\\n return data_frame\",\n \"def intialize_source():\\n raw = loadmat(\\\"p300backrec2.mat\\\")\\n channels_raw = raw['channels']\\n channels = []\\n for i in channels_raw[0]:\\n channels.extend(list(i))\\n X = raw['data']\\n marker = raw['marker']\\n return X,channels,marker\",\n \"def process_frames(self, data):\\n pass\",\n \"def process_frames(self, data):\\n pass\",\n \"def process_frames(self, data):\\n pass\",\n \"def process_frames(self, data):\\n pass\",\n \"def process_frames(self, data):\\n pass\",\n \"def get_frame(self, row):\\n\\n if row not in self.frames:\\n if not self.write:\\n d = self.memmap[row, :, :]\\n if self.file.metadata['interleave'] == 'bil':\\n d = d.T\\n self.frames[row] = d.copy()\\n else:\\n self.frames[row] = s.nan * s.zeros((self.n_cols, self.n_bands))\\n return self.frames[row]\",\n \"def get_frame(self, ind):\\n pass\",\n \"def get_frame(self, f):\\n return self._frames[f, :]\",\n \"def load(self) -> pd.DataFrame:\\n if os.path.exists(self.file_name):\\n df = pd.read_csv(self.file_name, index_col=0)\\n df = self._clean(df)\\n else:\\n _LOG.debug(\\\"No file '%s'\\\", self.file_name)\\n df = pd.DataFrame()\\n return df\",\n \"def sourceToDataframe(self):\\n df = pd.read_excel(self.filename)\\n df.columns = df.iloc[10]\\n df = df.drop(df.index[:11])\\n self.df = df #makes this df accessible to the whole class now\\n self.insertODN()\\n display(df.head())\",\n \"def _load(self):\\n # Extract the ASCII header (5 first lines)\\n with open(self._xst_bin, 'rb') as f:\\n header = list(islice(f, 0, 5))\\n assert header[0] == b'HeaderStart\\\\n',\\\\\\n 'Wrong header start'\\n assert header[-1] == b'HeaderStop\\\\n',\\\\\\n 'Wrong header stop'\\n header = [s.decode('utf-8') for s in header]\\n hd_size = sum([len(s) for s in header])\\n\\n # Parse informations into a metadata dictionnary\\n keys = ['freq', 'ma', 'accu']\\n search = ['Freq.List', 'Mr.List', 'accumulation']\\n types = ['float64', 'int', 'int']\\n for key, word, typ in zip(keys, search, types):\\n for h in header:\\n if word in h:\\n self.meta[key] = np.array(\\n h.split('=')[1].split(','),\\n dtype=typ\\n )\\n\\n # Deduce the dtype for decoding\\n n_ma = self.meta['ma'].size\\n n_sb = self.meta['freq'].size\\n dtype = np.dtype(\\n [('jd', 'float64'),\\n ('data', 'complex64', (n_sb, n_ma*n_ma*2 + n_ma))]\\n )\\n\\n # Decoding the binary file\\n tmp = np.memmap(\\n filename=self._xst_bin,\\n dtype='int8',\\n mode='r',\\n offset=hd_size\\n )\\n decoded = tmp.view(dtype)\\n\\n self.data = decoded['data'] / self.meta['accu']\\n self.time = Time(decoded['jd'], format='jd', precision=0)\\n\\n return\",\n \"def load_processed_data(animal, name, arguments):\\r\\n\\tpath = os.path.join(paths.path2Output, animal, str(arguments['Function']), \\r\\n\\t\\t\\t\\t\\t\\tstr(arguments['Init']), str(arguments['Rank']), name)\\r\\n\\t\\r\\n\\tmeta_df = pd.read_csv(os.path.join(path,'meta_df.csv'))\\r\\n\\troi_tensor = np.load(os.path.join(path,'roi_tensor.npy'))\\r\\n\\tacti = np.load(os.path.join(path,'acti.npy'))\\r\\n\\tnorm_acti = np.load(os.path.join(path,'norm_acti.npy'))\\r\\n\\tsmoothed_acti = np.load(os.path.join(path,'smoothed_acti.npy'))\\r\\n\\r\\n\\r\\n\\treturn meta_df, roi_tensor, acti, norm_acti, smoothed_acti\",\n \"def read_frame(self):\\n return self.decode_frame(self.grab_frame())\",\n \"def load_data(self, data):\\n\\n if type(data) is \\\"json\\\":\\n dataF = pd.read_json(data)\\n elif type(data) is list:\\n dataF = pd.DataFrame(data)\\n else:\\n print(\\\"Other types not implemented\\\")\\n return\\n dataF = self.__process_data(dataF)\\n self.__dataF = dataF\",\n \"def __load( self, json_blob ):\\n return pd.read_json( json_blob, orient='split' )\",\n \"def dataframe_extended(self):\\n return self.boxscore.dataframe\",\n \"def load_from_database(filename,key):\\n\\t# Opening file\\n\\tstore = pd.HDFStore(filename)\\n\\t# getting the df\\n\\tdata = store[key]\\n\\t# And its metadata\\n\\tmetadata = store.get_storer(key).attrs.metadata\\n\\tstore.close()\\n\\t# Ok returning the data now\\n\\treturn data, metadata\",\n \"def loadFringe(self, frame=1, filename=None):\\n self.currentFrame = np.int(frame)\\n if filename:\\n ofdPath = filename\\n else:\\n ofdPath = os.path.join(self.directory, self.basename +'.ofd')\\n\\n self.getOfdInfo(ofdPath)\\n\\n if self.mode == '2channel':\\n self.load2Channel()\\n if self.mode == '1channel':\\n self.load1Channel()\\n if self.mode == 'mmap2channel':\\n self.mmap2channel()\\n if self.mode == 'mmap1channel':\\n self.mmap1channel()\",\n \"def load_data_part(fname):\\n if \\\"_data\\\" not in fname:\\n return None\\n # Read data\\n data = pd.read_csv(fname)\\n # events file\\n events_fname = fname.replace('_data', '_events')\\n # read event file\\n labels = pd.read_csv(events_fname)\\n clean = data.drop(['id'], axis=1) # remove id\\n labels = labels.drop(['id'], axis=1) # remove id\\n return clean, labels\",\n \"def forward(self, raw_X):\\n return make_df(raw_X, self.features)\",\n \"def data_frame_creator(self):\\n sequence_folder = [\\n '/SEQ1', '/SEQ2', '/SEQ3', '/SEQ4', '/SEQ5', '/SEQ6'\\n ]\\n rgb_folder = ['/RGBLeft/', '/RGBRight/']\\n depth_folder = ['/DepthLeft/', '/DepthRight/']\\n segmentation_folder = ['/GTLeft/', '/GTright/']\\n rgb_dir = [\\n self.dataset_dir + sequence_f + rgb_f for rgb_f in rgb_folder\\n for sequence_f in sequence_folder\\n ]\\n rgb_data = [\\n rgb_d + rgb for rgb_d in rgb_dir for rgb in os.listdir(rgb_d)\\n ]\\n\\n depth_dir = [\\n self.dataset_dir + sequence_f + depth_f\\n for depth_f in depth_folder\\n for sequence_f in sequence_folder\\n ]\\n depth_data = [\\n depth_d + depth for depth_d in depth_dir\\n for depth in os.listdir(depth_d)\\n ]\\n\\n segmentation_dir = [\\n self.dataset_dir + sequence_f + segmentation_f\\n for segmentation_f in segmentation_folder\\n for sequence_f in sequence_folder\\n ]\\n segmentation_data = [\\n segmentation_d + segmentation\\n for segmentation_d in segmentation_dir\\n for segmentation in os.listdir(segmentation_d)\\n ]\\n\\n dataset = {\\n 'RGB': rgb_data,\\n 'DEPTH': depth_data,\\n 'SEGMENTATION': segmentation_data\\n }\\n\\n if self.shuffle:\\n return pd.DataFrame(dataset).sample(frac=1, random_state=123)\\n\\n return pd.DataFrame(dataset)\",\n \"def load(self):\\n\\n\\t\\t# Check if dataset location exists\\n\\t\\tif (not os.path.exists(self._location)):\\n\\t\\t\\tprint(\\\"Error: Dataset location does not exist\\\")\\n\\t\\t\\treturn\\n\\n\\t\\tself._frames = sorted(glob.glob(self._location + '/frame*.jpg'))\\n\\n\\t\\t# Check if startFrame is beyond dataset bounds\\n\\t\\tif (self._startFrame > len(self._frames)):\\n\\t\\t\\tprint(\\\"Error: Start frame is beyond dataset bounds\\\")\\n\\t\\t\\treturn\\n\\n\\t\\t# Check if endFrame is beyond dataset bounds\\n\\t\\tif (self._endFrame > len(self._frames)):\\n\\t\\t\\tprint(\\\"Warning: End frame beyond dataset bounds, setting to end of dataset\\\")\\n\\n\\t\\t# Start buffering threads\\n\\t\\tself._bufferThreadStopped = False\\n\\t\\tself._bufferingThread.start()\",\n \"def record_data_frame(self):\\n return self._record.data_frame\",\n \"def _load_data(data, n_prev=3):\\n docX, docY = [], []\\n for i in range(len(data)-n_prev):\\n docX.append(data.data.iloc[i:i+n_prev])\\n docY.append(data.response.iloc[i+n_prev]) \\n\\n alsX = np.array(docX)\\n alsY = np.array(docY)\\n return np.matrix(alsX), np.matrix(alsY).T\",\n \"def dataframe(self):\\n return self.get_target().dataframe()\",\n \"def _setup_dataframe(self, serie, metadata=None):\\n header = self.get_data_header(serie, dataset='cnv')\\n df = self.get_data_in_frame(serie, header, dataset='cnv')\\n df = self.df_handler.map_column_names_of_dataframe(df)\\n\\n return df\",\n \"def get_frame(self, index):\\n filename = self.get_filename(index)\\n return plt.imread(fname=filename)\",\n \"def get_zyla_data_object(evt, src):\\n o = evt.get(_psana.Zyla.FrameV1, src)\\n if o is not None: return o\\n\\n return None\",\n \"def _dataframe_from_feather(fn, **kwargs):\\n\\treturn pd.read_feather(fn, **kwargs)\",\n \"def load_data():\\n d = load_wine()\\n data = {colname: d.data[:, i] for i, colname in enumerate(d.feature_names)}\\n data[\\\"target\\\"] = d.target\\n return pd.DataFrame(data)\",\n \"def _get_data(self):\\n raise NotImplementedError()\",\n \"def _loadData(self, data):\\n Movie._loadData(self, data)\\n PlexHistory._loadData(self, data)\",\n \"def loadDataOrig(df, path, im_shape, disp_names=False):\\r\\n X, y = [], []\\r\\n for i, item in df.iterrows():\\r\\n if disp_names == True:\\r\\n print('i={} {} {}\\\\n'.format(i, path + item[0], path + item[1]))\\r\\n img = io.imread(path + item[0])\\r\\n img = transform.resize(img, im_shape, mode='constant')\\r\\n img = np.expand_dims(img, -1)\\r\\n mask = io.imread(path + item[1])\\r\\n mask = transform.resize(mask, im_shape, mode='constant')\\r\\n mask = np.expand_dims(mask, -1)\\r\\n X.append(img)\\r\\n y.append(mask)\\r\\n break\\r\\n X = np.array(X)\\r\\n y = np.array(y)\\r\\n\\r\\n if disp_names == True:\\r\\n print('X/shape={} y.shape={}\\\\n'.format(X.shape, y.shape))\\r\\n\\r\\n X -= X.mean()\\r\\n X /= X.std()\\r\\n\\r\\n if disp_names == True:\\r\\n print('### Data loaded')\\r\\n print('\\\\t{}'.format(path))\\r\\n print('\\\\t{}\\\\t{}'.format(X.shape, y.shape))\\r\\n # print( '\\\\tX:{:.1f}-{:.1f}\\\\ty:{:.1f}-{:.1f}\\\\n'.format(X.min(), X.max(), y.min(), y.max()) )\\r\\n print('\\\\tX.mean = {}, X.std = {}'.format(X.mean(), X.std()))\\r\\n print('\\\\n')\\r\\n\\r\\n return X, y\",\n \"def read_file(fname: str) -> pd.DataFrame:\\n raw_data = (\\n pd.read_hdf(fname).to_frame().reset_index(level=[0, 1]).loc[ANALYSIS_DATE]\\n )\\n raw_data[\\\"date\\\"] = raw_data.index\\n return raw_data\",\n \"def get_fli_data_object(evt, src):\\n o = evt.get(_psana.Fli.FrameV1, src)\\n if o is not None: return o\\n\\n return None\",\n \"def as_dframe(cls, dataset):\\n return dataset.dframe()\",\n \"def __local_df(soup):\\n return __get_local_g1_news(soup)\",\n \"def __local_df(soup):\\n return __get_local_g1_news(soup)\",\n \"def load(fnames, tag=None, inst_id=None):\\n\\n if not fnames:\\n print('fnames are go')\\n warnings.warn('You no got no fname, you no get no data')\\n return pysat.DataFrame(None), pysat.Meta(None)\\n elif len(fnames) == 1:\\n print('fnames are greater than 1')\\n meta = pysat.Meta()\\n signal_meta = pysat.Meta()\\n\\n # load the rinex\\n data = gr.load(fnames[0])\\n # get the metadata from the xarray.Dataset\\n xr_attrs = data.attrs\\n # format the metadata\\n# for at in xr_attrs:\\n# print(type(at))\\n# meta[at] = {'units': '', 'long_name': at}\\n# keys = data.data_vars.keys()\\n# for key in keys:\\n# # find the xarray equivalents of units and long_name\\n# print(key)\\n# signal_meta[key] = {meta.labels.units: var_units[key][0],\\n# meta.labels.name: var_units[key][1]}\\n# # format the data\\n# meta['signals'] = signal_meta\\n# output = data.variables\\n return data, meta\\n else:\\n raise ValueError('Only one filename currently supported')\\n print('no idea wahts goin on')\",\n \"def load_data(READFILE,load_type=1):\\n df = pd.read_csv(READFILE)\\n if 'type' in df.columns and load_type is not None:\\n df = pd.DataFrame(df[df.type==1])\\n df = df.drop('type',axis=1)\\n return df\",\n \"def load(self):\\n data = pandas.read_csv(self.path, names=self.names)\\n return data\",\n \"def read(name, db):\\n \\n # Make connection with the database\\n\\tconn = sqlite3.connect(db)\\n\\tdf = pd.read_sql_query(\\\"select * from \\\" + name + ';', conn)\\n \\n # Print loaded data table name and return DataFrame\\n\\tprint(name + ': loaded')\\n\\treturn df\",\n \"def dataFrame(self):\\n\\n memory_file = StringIO(initial_value=self.sparql_result.decode('utf-8'), newline='\\\\n')\\n reader = DictReader(memory_file)\\n\\n schema = StructType(\\n list(map(lambda f: StructField(f, StringType()), reader.fieldnames))\\n )\\n\\n data = list(map(lambda d: [d[f] for f in reader.fieldnames], list(reader)))\\n\\n return self.spark.createDataFrame(data, schema)\",\n \"def __load( self, raw_content ):\\n return( pd.read_excel( BytesIO( raw_content ) ) )\",\n \"def get_data():\\n pass\",\n \"def dataframe(self):\\n return self._df\",\n \"def get_frame_at_index(self, index):\\n begin = index\\n end = begin + self.frame_size\\n\\n if begin < 0:\\n return self.data\\n\\n return self.data[begin:end]\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.66847086","0.66500604","0.6578558","0.6544992","0.6464981","0.6419371","0.63444304","0.6261828","0.62608165","0.6257387","0.61691505","0.613629","0.60970247","0.6049352","0.60232645","0.5995074","0.59805757","0.59766096","0.597535","0.59465176","0.5939186","0.5932176","0.5902538","0.58966756","0.5876167","0.58689326","0.58581334","0.58453465","0.5839027","0.5837447","0.58229446","0.58174896","0.5816866","0.5813475","0.5774821","0.5755608","0.57537633","0.57523316","0.5736286","0.5728476","0.5725325","0.5720987","0.5719652","0.57161677","0.57101476","0.57099634","0.57010764","0.5689209","0.56681216","0.56632763","0.56627995","0.5658984","0.56528586","0.5645935","0.5641005","0.5641005","0.5641005","0.5641005","0.5641005","0.5640627","0.56400913","0.56390923","0.5629359","0.5626899","0.56220907","0.56153417","0.5609219","0.56051147","0.56032515","0.55935735","0.5593448","0.5587989","0.5583714","0.55716944","0.5569482","0.5569335","0.55643743","0.55611104","0.55578494","0.55501956","0.5540802","0.5539357","0.5531822","0.5530565","0.5525389","0.55190265","0.5513765","0.5509492","0.55082047","0.5504479","0.5503329","0.5503329","0.5502208","0.54996043","0.5496846","0.54947937","0.54923546","0.5490945","0.54797804","0.54795164","0.54779416"],"string":"[\n \"0.66847086\",\n \"0.66500604\",\n \"0.6578558\",\n \"0.6544992\",\n \"0.6464981\",\n \"0.6419371\",\n \"0.63444304\",\n \"0.6261828\",\n \"0.62608165\",\n \"0.6257387\",\n \"0.61691505\",\n \"0.613629\",\n \"0.60970247\",\n \"0.6049352\",\n \"0.60232645\",\n \"0.5995074\",\n \"0.59805757\",\n \"0.59766096\",\n \"0.597535\",\n \"0.59465176\",\n \"0.5939186\",\n \"0.5932176\",\n \"0.5902538\",\n \"0.58966756\",\n \"0.5876167\",\n \"0.58689326\",\n \"0.58581334\",\n \"0.58453465\",\n \"0.5839027\",\n \"0.5837447\",\n \"0.58229446\",\n \"0.58174896\",\n \"0.5816866\",\n \"0.5813475\",\n \"0.5774821\",\n \"0.5755608\",\n \"0.57537633\",\n \"0.57523316\",\n \"0.5736286\",\n \"0.5728476\",\n \"0.5725325\",\n \"0.5720987\",\n \"0.5719652\",\n \"0.57161677\",\n \"0.57101476\",\n \"0.57099634\",\n \"0.57010764\",\n \"0.5689209\",\n \"0.56681216\",\n \"0.56632763\",\n \"0.56627995\",\n \"0.5658984\",\n \"0.56528586\",\n \"0.5645935\",\n \"0.5641005\",\n \"0.5641005\",\n \"0.5641005\",\n \"0.5641005\",\n \"0.5641005\",\n \"0.5640627\",\n \"0.56400913\",\n \"0.56390923\",\n \"0.5629359\",\n \"0.5626899\",\n \"0.56220907\",\n \"0.56153417\",\n \"0.5609219\",\n \"0.56051147\",\n \"0.56032515\",\n \"0.55935735\",\n \"0.5593448\",\n \"0.5587989\",\n \"0.5583714\",\n \"0.55716944\",\n \"0.5569482\",\n \"0.5569335\",\n \"0.55643743\",\n \"0.55611104\",\n \"0.55578494\",\n \"0.55501956\",\n \"0.5540802\",\n \"0.5539357\",\n \"0.5531822\",\n \"0.5530565\",\n \"0.5525389\",\n \"0.55190265\",\n \"0.5513765\",\n \"0.5509492\",\n \"0.55082047\",\n \"0.5504479\",\n \"0.5503329\",\n \"0.5503329\",\n \"0.5502208\",\n \"0.54996043\",\n \"0.5496846\",\n \"0.54947937\",\n \"0.54923546\",\n \"0.5490945\",\n \"0.54797804\",\n \"0.54795164\",\n \"0.54779416\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":81788,"cells":{"query":{"kind":"string","value":"Get file names from config or user input Also get specified framerate, or default is 10 Hz Open file stream"},"document":{"kind":"string","value":"def setup(self):\n print(\"Looking for \", self.filename)\n if os.path.exists(self.filename):\n file = scio.loadmat(self.filename)\n self.data = np.squeeze(file[\"data\"])\n print(\"Motion Data length is \", len(self.data))\n\n else:\n raise FileNotFoundError"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def read_data_samples(fp):\n if(path.isdir(fp)):\n fps = glob.glob(fp + '\\\\*.txt')\n return list(map(lambda x: read_file(x), fps))","def get_file_list(mixer_file, select_random, use_list_of_files):\n logger = logging.getLogger(get_file_list.__name__)\n files = list()\n\n if use_list_of_files:\n with open(mixer_file, 'r') as list_file:\n for line in list_file:\n files.append(os.path.join('data/raw',line.strip()))\n\n if select_random:\n random.shuffle(files)\n\n else:\n\n mixer = parse_mixer_file(mixer_file)\n\n for m in mixer:\n path = os.path.join(project_dir, m[0])\n all_mixer_files = [os.path.join(path,f) for f in os.listdir(path) \n if os.path.isfile(os.path.join(path, f)) and f.split('.')[-1] == 'csv']\n\n current_files = list()\n # Check if the number of samples is limited\n if m[2] >= 0:\n sample_count = 0\n for f in all_mixer_files:\n # Get number of lines without the header line\n num_lines = sum(1 for line in open(f)) - 1\n\n if (sample_count + num_lines) > m[2]:\n current_files.append((f, m[2] - sample_count))\n sample_count += (m[2] - sample_count)\n break\n else:\n current_files.append((f, -1))\n sample_count += num_lines\n\n if sample_count < m[2]:\n logger.warn('Not enough samples ({} < {}): {}'.format(sample_count, m[2], m[0]))\n else:\n # No limit, take all samples in the files\n current_files = zip(all_mixer_files, [-1]*len(all_mixer_files))\n\n if m[1] < 0:\n # -1 means all .csv files\n files += current_files\n elif m[1] > 0:\n if m[1] > len(current_files):\n logger.warn('Not enough files ({} < {}): {}'.format(len(current_files),\n m[1], m[0]))\n files += current_files[:m[1]]\n\n if select_random:\n random.shuffle(files)\n else:\n files = sorted(files, key=lambda x: int(os.path.basename(x[0]).split('_')[-1].split('.')[0]))\n\n return files","def main(_):\n print('argument to expand', ARGS.video_in)\n print('argument expanded', glob.glob(ARGS.video_in))\n video_count = 0\n for video_filename in glob.glob(ARGS.video_in):\n print('start parsing', video_filename)\n data = skvideo.io.ffprobe(video_filename)['video']\n rate_str = six.ensure_str(data['@r_frame_rate']).split('/')\n rate = float(rate_str[0]) / float(rate_str[1])\n print('detected frame rate:', rate)\n\n print('load frames:')\n video = skvideo.io.vreader(video_filename)\n frame_count = 0\n file_count = 0\n for frame in video:\n if (frame_count > ARGS.offset) and \\\n ((frame_count-ARGS.offset)%ARGS.skip == 0) and \\\n (frame_count/rate >= ARGS.from_s) and \\\n (frame_count/rate <= ARGS.to_s or ARGS.to_s == -1):\n print(frame_count,)\n img = Image.fromarray(frame)\n if ARGS.crop:\n img = crop(img, ARGS.size)\n # save file\n file_number = file_count + video_count * ARGS.multiple + ARGS.start\n if ARGS.format_ext.lower() == 'jpg':\n file_out = os.path.join(ARGS.path_out,\n 'f{:07d}.jpg'.format(file_number))\n img.save(file_out, 'JPEG')\n elif ARGS.format_ext.lower() == 'png':\n file_out = os.path.join(ARGS.path_out,\n 'f{:07d}.png'.format(file_number))\n img.save(file_out, 'PNG')\n else:\n print('unrecognize format', ARGS.format_ext)\n sys.exit()\n file_count += 1\n frame_count += 1\n video_count += 1","def get_file_bpm(path, params = {}):\n try:\n win_s = params['win_s']\n samplerate = params['samplerate']\n hop_s = params['hop_s']\n except:\n \"\"\"\n # super fast\n samplerate, win_s, hop_s = 4000, 128, 64 \n # fast\n samplerate, win_s, hop_s = 8000, 512, 128\n \"\"\"\n # default:\n samplerate, win_s, hop_s = 44100, 1024, 512\n\n s = source(path, samplerate, hop_s)\n samplerate = s.samplerate\n o = tempo(\"specdiff\", win_s, hop_s, samplerate)\n # List of beats, in samples\n beats = []\n # Total number of frames read\n total_frames = 0\n\n while True:\n samples, read = s()\n is_beat = o(samples)\n if is_beat:\n this_beat = o.get_last_s()\n beats.append(this_beat)\n #if o.get_confidence() > .2 and len(beats) > 2.:\n # break\n total_frames += read\n if read < hop_s:\n break\n\n # Convert to periods and to bpm \n bpms = 60./diff(beats)\n b = median(bpms)\n return b","def read(ftype, inDir, inSuffix, startTime, endTime):\n\n\tif ftype == 'ryan': return readRyan(inDir, inSuffix, startTime, endTime)\t\n\telif ftype == 'segmotion': return readSegmotion(inDir, inSuffix, startTime, endTime)\n\telif ftype == 'probsevere': return readProbSevere(inDir, inSuffix, startTime, endTime)","def seqIo_frImgs(fName, header=[], aviName=[], Is=[], sDir=[], name='I', ndig=5, f0=0, f1=1e6):\n \n if aviName!=[]: #avi movie exists\n vc = cv2.VideoCapture(aviName)\n if vc.isOpened(): rval = True\n else:\n rval = False\n print('video not readable')\n return\n fps = vc.get(cv2.cv.CV_CAP_PROP_FPS)\n NUM_FRAMES = int(vc.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT))\n print(NUM_FRAMES)\n IM_TOP_H = vc.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)\n IM_TOP_W = vc.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)\n header['width']=IM_TOP_W\n header['height']=IM_TOP_H\n header['fps']=fps\n\n sw = seqIo_writer(fName,header)\n print('creating seq from AVI')\n # initialize timer\n timer = pb.ProgressBar(widgets=['Converting ', pb.Percentage(), ' -- ',\n pb.FormatLabel('Frame %(value)d'), '/',\n pb.FormatLabel('%(max)d'), ' [', pb.Timer(), '] ',\n pb.Bar(), ' (', pb.ETA(), ') '], maxval=NUM_FRAMES)\n for f in range(NUM_FRAMES):\n rval, im = vc.read()\n if rval:\n im= im.astype(np.uint8)\n sw.addFrame(im)\n timer.update(f)\n sw.close()\n timer.finish()\n elif Is==[]:\n assert(os.path.isdir(sDir))\n sw = seqIo_writer(fName,header)\n frmstr = '%s/%s%%0%ii.%s' % (sDir,name,ndig,header.ext)\n for frame in range(f0,f1):\n f = frmstr % frame\n if not os.path.isfile(f):break\n fid = open(f, 'r')\n if fid<0: sw.close(); assert(False)\n I = fid.read()\n fid.close()\n b = bytearray(I)\n assert (b[0] == 255 and b[1] == 216 and b[-2] == 255 and b[-1] == 217); # JPG\n I = np.array(list(b)).astype(np.uint8)\n sw.addFrame(I,0,0)\n sw.close()\n if frame==f0: print('No images found')\n else:\n nd = len(Is.shape)\n if nd==2: nd=3\n assert(nd<=4)\n nFrm = Is.shape[nd-1]\n header['height']=Is.shape[0]\n header['width']=Is.shape[1]\n sw =seqIo_writer(fName,header)\n if nd==3:\n for f in range(nFrm): sw.addFrame(Is[:,:,f])\n if nd==4:\n for f in range(nFrm): sw.addFrame(Is[:,:,:,f])\n sw.close()","def videoFrames(filename, framerate=1):\n vid_file = os.path.join(os.path.dirname(os.getcwd()), \"Database\", \"Video\", filename)\n print(vid_file)\n assert os.path.isfile(vid_file), \"Given path is not a valid file\"\n tmpdir = os.path.join(os.getcwd(), \"tmp\")\n subprocess.run(\n [\n \"ffmpeg\",\n \"-i\",\n vid_file,\n \"-r\",\n f\"{framerate}\",\n os.path.join(tmpdir, \"img_%04d.jpg\"),\n ]\n )\n return [os.path.join(tmpdir, i) for i in os.listdir(tmpdir) if not i.endswith(\".wav\")]","def get_filenames(b,X,timefac,BW):\r\n\tn = int(200000*X*timefac); nn = int(200000*X*10)\r\n\troot = \"./dat_LE_stream/\"\r\n\trootL = 'C:/AsusWebStorage/MySyncData/TRAFILES/'\r\n\tpodir = \"/b=\"+str(b)+\"/\" if BW else \"/HO/\"\r\n\t\r\n\ttrafile = rootL+\"TRA_BW_b\"+str(b)+\"X\"+str(int(X))+\"n\"+str(nn)+\"seed65438\"\r\n\tif not os.path.isfile(trafile):\r\n\t\ttrafile = rootL+\"TRA_BW_b\"+str(b)+\"X\"+str(int(X))+\"n\"+str(n)+\"seed65438\"\r\n\toutfile = root+podir+os.path.split(trafile)[1][4:]\r\n\t\r\n\trndfile = os.path.split(outfile)[0]+\"/RND_\"+os.path.split(outfile)[1]+\".png\"\r\n\tpdffile = os.path.split(outfile)[0]+\"/PDF_\"+os.path.split(outfile)[1]\r\n\tstrfile = os.path.split(outfile)[0]+\"/STR_\"+os.path.split(outfile)[1]\r\n\t\r\n\treturn trafile,rndfile,pdffile,strfile,n","def gen_fps():\n global data_src ,output_dir \n logger = TaskFileLogger(\"GenFP\")\n\n h_vars = load_hydro_var()\n if not os.path.exists(output_dir):\n os.mkdir(output_dir)\n\n for h_type,var_d in h_vars.items():\n print \"considering %s\" %h_type\n\n t_output_dir = os.path.join(output_dir,h_type)\n if not os.path.exists(t_output_dir):\n print \"creating path %s\" %t_output_dir\n os.mkdir(t_output_dir)\n logger.log(\"%s started\" %(h_type))\n\n for fname in glob.glob(data_src):\n complex_id = os.path.basename(fname).split('.')[0] \n fp_path = os.path.join(t_output_dir,complex_id + \".fp\" )\n if os.path.exists(fp_path):\n #print \"%s processed\" %complex_id\n continue\n print \"processing %s,fp saved as %s\" %(fname , fp_path )\n c = Complex(fname,hydro_dict = var_d)\n c.get_fp()\n c.write_fp_to_file(fp_path)\n\n logger.log(\"%s finished\" %(h_type))","def return_file_read(_):\n return [\"scorevideo LOG\", \"File: log.mat\"]","def __init__(self, inFile = None, inData = None, inRate = None):\n \n # Information about FFMPEG\n self.ffmpeg_info = FFMPEG_info()\n \n if inData is not None:\n if inRate is None:\n print('Set the \"rate\" to the default value (8012 Hz).')\n rate = 8012.0\n self.generate_sound(inData, inRate)\n else: \n if inFile is None:\n inFile = self._selectInput()\n if inFile == 0:\n return\n try:\n self.source = inFile\n self.read_sound(self.source)\n except FileNotFoundError as err:\n print(err)\n inFile = self._selectInput()\n self.source = inFile\n self.read_sound(self.source)","def generate_readers(\n viddir, camname, minopt=0, maxopt=300000, pathonly=False, extension=\".mp4\"\n):\n out = {}\n mp4files = [\n os.path.join(camname, f)\n for f in os.listdir(os.path.join(viddir, camname))\n if extension in f\n and int(f.rsplit(extension)[0]) <= maxopt\n and int(f.rsplit(extension)[0]) >= minopt\n ]\n\n # This is a trick (that should work) for getting rid of\n # awkward sub-directory folder names when they are being used\n mp4files_scrub = [\n os.path.join(\n os.path.normpath(f).split(os.sep)[0], os.path.normpath(f).split(os.sep)[-1]\n )\n for f in mp4files\n ]\n\n pixelformat = \"yuv420p\"\n input_params = []\n output_params = []\n\n for i in range(len(mp4files)):\n if pathonly:\n out[mp4files_scrub[i]] = os.path.join(viddir, mp4files[i])\n else:\n print(\n \"NOTE: Ignoring {} files numbered above {}\".format(extensions, maxopt)\n )\n out[mp4files_scrub[i]] = imageio.get_reader(\n os.path.join(viddir, mp4files[i]),\n pixelformat=pixelformat,\n input_params=input_params,\n output_params=output_params,\n )\n\n return out","def framerate(self):\n return self.config.get('framerate', 15)","def OpenSoundFiles():\n\n wildcard = create_wildcard(\"Sound files\", sppas.src.audiodata.aio.extensionsul)\n wildcard += '|' + create_wildcard(\"All files\", ['*', '*.*'])\n\n files = list()\n dlg = wx.FileDialog(None, \n \"Select sound file(s)\", \n paths.samples, \n \"\", \n wildcard, \n wx.FD_OPEN | wx.MULTIPLE | wx.FD_CHANGE_DIR)\n if dlg.ShowModal() == wx.ID_OK:\n files = dlg.GetPaths()\n\n dlg.Destroy()\n\n return files","def _settings(filename):\n\n with open(filename, 'r') as datafile:\n daq_type = datafile.readline().strip().split(',')[1]\n sample_hz = int(datafile.readline().strip().split(',')[1])\n channels = datafile.readline().strip().split(',')\n return (daq_type, sample_hz, channels)","def read_local_20Hz_files(**kwargs):\n pathlst = kwargs.get('pathlst')\n product = kwargs.get('product')\n varalias = kwargs.get('varalias')\n sdate = kwargs.get('sdate')\n edate = kwargs.get('edate')\n twin = kwargs.get('twin')\n\n # establish coords if defined in config file\n timestr = satellite_dict[product]['vardef']['time']\n lonstr = satellite_dict[product]['vardef']['lons']\n latstr = satellite_dict[product]['vardef']['lats']\n\n # adjust start and end\n sdate = sdate - timedelta(minutes=twin)\n edate = edate + timedelta(minutes=twin)\n # get meta data\n ncmeta = ncdumpMeta(pathlst[0])\n ncvar = get_filevarname(varalias, variable_info,\n satellite_dict[product], ncmeta)\n # retrieve sliced data\n ds = read_netcdfs(pathlst)\n ds_sort = ds.sortby(timestr)\n\n # get indices for included time period\n nptime = ds_sort[timestr].data\n print('here0')\n print(len(nptime))\n #dtime = [parse_date(str(nptime[i])) for i in range(len(nptime))]\n print('here1')\n #idx = find_included_times_pd(dtime, sdate=sdate, edate=edate)\n idx = find_included_times_pd(nptime, sdate=sdate, edate=edate)\n print(len(nptime[idx]))\n print('here2')\n dtime = [parse_date(str(nptime[idx][i])) for i in range(len(nptime[idx]))]\n print(dtime)\n print('here3')\n #dtime = list(np.array(dtime)[idx])\n lons = list(((ds_sort[lonstr].data[idx] - 180) % 360) - 180)\n lats = list(ds_sort[latstr].data[idx])\n\n unxt = (nptime[idx].astype(int) / 10**9)\n\n # make dict and start with stdvarname for varalias\n stdvarname = variable_info[varalias]['standard_name']\n vardict = {}\n vardict[stdvarname] = list(ds_sort[ncvar].data[idx])\n vardict['longitude'] = lons\n vardict['latitude'] = lats\n vardict['time'] = unxt\n vardict['datetime'] = dtime\n vardict['time_unit'] = variable_info['time']['units']\n print(vardict.keys())\n return vardict","def readNextGenSpectrum(fname=''):\n\n print('Reading : ', fname)\n\n with open(fname, 'r') as rfile:\n dum = rfile.readline()\n sdum = dum.split()\n teff = float(sdum[0])\n logg = float(sdum[1])\n mph = float(sdum[2])\n dum = rfile.readline()\n nwav = float(dum.split()[0])\n\n bigline = []\n dum = rfile.readline()\n while dum.strip() != '':\n sdum = dum.split()\n for i in range(len(sdum)):\n bigline.append(float(sdum[i]))\n dum = rfile.readline()\n\n bigline = np.array(bigline)\n # Convert wavelength from angstrom to micron\n wav = bigline[:nwav] / 1e4\n inu = bigline[nwav:2 * nwav]\n bnu = bigline[nwav * 2:nwav * 3]\n\n ii = wav.argsort()\n wav = wav[ii]\n inu = inu[ii] * 1e-8 * wav * 1e4 / np.pi / (29979245800.0 / wav * 1e4)\n bnu = bnu[ii] * 1e-8 * wav * 1e4 / np.pi / (29979245800.0 / wav * 1e4)\n\n #\n # The unit is now erg/s/cm/Hz/ster\n #\n\n return {'teff': teff, 'logg': logg, 'mph': mph, 'nwav': nwav, 'wav': wav, 'inu': inu, 'bnu': bnu}","def file_info(file_name, file_pattern):\n match = re.compile(file_pattern).match(file_name)\n if match:\n basepath = match.group('basepath')\n sensor = match.group('sensor')\n ax = match.group('ax')\n freq = match.group('freq')\n date = match.group('date')\n return basepath, sensor, ax, freq, date\n else:\n return None # there is no file extension to file_name","def do_f(self, parms):\n\t\tprint self.files","def _read_config_file(self):\n wcec = 0\n deadline = 0\n jitter = 0\n init_freq = 0\n freqs_volt = {}\n freqs = []\n volts = []\n config_file_name = self._find_file('sim_simple.config')\n with open(config_file_name, 'rU') as f:\n lines = f.readlines()\n try:\n for freq in lines[0].split():\n freqs.append(float(freq))\n\n for volt in lines[1].split():\n volts.append(float(volt))\n\n for i in range(0, len(freqs)):\n freqs_volt[freqs[i]] = volts[i]\n\n data = lines[2].split()\n wcec = float(data[0])\n deadline = float(data[1])\n period = float(data[2])\n jitter = float(data[3])\n init_freq = float(data[4])\n except ValueError, IndexError:\n print 'Invalid data in config file'\n sys.exit(1)\n\n return wcec, deadline, period, jitter, init_freq, freqs_volt","def readPlayerImageFiles(self):\n currentPath = os.path.dirname(os.path.abspath(__file__))\n listOfFileNames=[]\n for i in os.listdir(currentPath):\n if re.match(\"player\\_\\d+\",i): #i.endswith(\".gif\")\n listOfFileNames.append(currentPath+'/'+i)\n return listOfFileNames","def fillFileList(self, dirName):\n if not os.path.isdir(dirName):\n print(\"Warning: directory doesn't exist\")\n return\n\n self.listFiles.fill(dirName, fileName=None, readFmt=True, addWavNum=True, recursive=True)\n\n # while reading the file, we also collected a list of species present there\n spList = list(self.listFiles.spList)\n # and sample rate info\n fs = list(self.listFiles.fsList)\n\n if len(fs)==0:\n print(\"Warning: no suitable files found\")\n return\n\n # might need better limits on selectable sample rate here\n self.fs.setValue(int(np.min(fs)))\n self.fs.setRange(4000, int(np.max(fs)))\n self.fs.setSingleStep(4000)\n self.fs.setTickInterval(4000)\n\n spList.insert(0, 'Choose species...')\n self.species.clear()\n self.species.addItems(spList)\n if len(spList)==2:\n self.species.setCurrentIndex(1)","def _open_stream(config):\n p = pyaudio.PyAudio()\n stream = p.open(\n format = config[\"format\"],\n channels = config[\"channels\"],\n rate = config[\"rate\"],\n input = True,\n frames_per_buffer = config[\"chunk\"]\n )\n return p, stream","def filesample(filename):\n sampling_rate, samples = wavfile.read(filename)\n times = np.arange(len(samples)) / sampling_rate\n return samples, sampling_rate","def find_files(config, slot='*'):\n f_pattern = os.path.join(os.path.join(config['path'],config['led_name']), slot+'*' + config['led_name'] + '*'\n + config['current'] + '*' + config['exp_time'] + '*'\n + config['xpos'] + '*' + config['ypos'] + '*')\n print(f_pattern)\n return glob.glob(f_pattern)","def get_frame_rate(filename):\n cmd = ('ffprobe -v 0 -of flat=s=_ -select_streams v:0 -show_entries '\n 'stream=avg_frame_rate -of default=nokey=1:noprint_wrappers=1 ' +\n filename).split()\n pid = subprocess.run(cmd, stdout=subprocess.PIPE,\n universal_newlines=True)\n if pid.returncode != 0:\n return None\n\n frame_rate_exp = pid.stdout.rstrip()\n try:\n frame_rate = float(frame_rate_exp)\n except:\n if frame_rate_exp == 'N/A':\n frame_rate = 0.\n else:\n numerator, denominator = map(float, frame_rate_exp.split('/'))\n if denominator == 0:\n frame_rate = 0\n else:\n frame_rate = numerator / denominator\n return frame_rate","def files_sim(config):\n file_sim = sorted(glob.glob(config['str_dir'] + '/simulation/' +\n '{}/{}nm/txt_files/*.txt'.format(\n config['date'], config['wavelength'])))\n return file_sim","def get_frame_by_frame(name=None, fps=4, write_to_disk=False, display_feed=False, on_capture=None):\n\n reset_camera()\n\n if name is None:\n name = \"fbf_\" + str(int(time()))\n \n dname = None\n if write_to_disk:\n chdir(cwd)\n dname = join(dirname(realpath(sys.argv[0])), \"train\", \"data\", name)\n if not exists(dname):\n print(\"Created dir: %s\" % dname)\n mkdir(dname)\n else:\n print(\"Using dir: %s\" % dname)\n else:\n print('Not writing to disk')\n\n def _snap(name, dname, write, display, capture_callback):\n global camera\n s, img = camera.read()\n\n if s and capture_callback:\n img = capture_callback(img)\n\n if s and display:\n cv2.imshow(name, img)\n cv2.waitKey(1) \n\n if write:\n chdir(dname)\n number_of_files = len([item for item in os.listdir(dname) if os.path.isfile(os.path.join(dname, item))])\n path = \"./\" + str(number_of_files + 1) + \".png\"\n if s:\n imwrite(path, img)\n print(\"Saved to \" + dname + \"/\" + str(number_of_files + 1) + \".png\")\n else:\n print(\"Could not read image %d from camera\" % (number_of_files + 1))\n chdir(cwd)\n\n return Timer(1 / fps, _snap, name, dname, write_to_disk, display_feed, on_capture).use_mp()","def readAudioFile(path):\n\n extension = os.path.splitext(path)[1]\n\n try:\n # Commented below, as we don't need this\n # #if extension.lower() == '.wav':\n # #[Fs, x] = wavfile.read(path)\n # if extension.lower() == '.aif' or extension.lower() == '.aiff':\n # s = aifc.open(path, 'r')\n # nframes = s.getnframes()\n # strsig = s.readframes(nframes)\n # x = numpy.fromstring(strsig, numpy.short).byteswap()\n # Fs = s.getframerate()\n if extension.lower() == '.mp3' or extension.lower() == '.wav' or extension.lower() == '.au' or extension.lower() == '.ogg':\n try:\n audiofile = AudioSegment.from_file(path)\n except:\n print(\"Error: file not found or other I/O error. \"\n \"(DECODING FAILED)\")\n return -1 ,-1\n\n if audiofile.sample_width == 2:\n data = numpy.fromstring(audiofile._data, numpy.int16)\n elif audiofile.sample_width == 4:\n data = numpy.fromstring(audiofile._data, numpy.int32)\n else:\n return -1, -1\n Fs = audiofile.frame_rate\n x = numpy.array(data[0::audiofile.channels]).T\n else:\n print(\"Error in readAudioFile(): Unknown file type!\")\n return -1, -1\n except IOError:\n print(\"Error: file not found or other I/O error.\")\n return -1, -1\n\n if x.ndim == 2:\n if x.shape[1] == 2:\n x = x.flatten()\n\n return Fs, x","def read_xyz(filename, freq):\n\n\n#xyz file\n\n Atoms = []\n Coordinates = []\n\n xyz = open(filename)\n frame = 0\n while True:\n\n n_atoms = xyz.readline()\n\n if n_atoms == '':\n break\n else:\n n_atoms = int(n_atoms)\n title = xyz.readline()\n\n if frame%freq==0:\n atoms, coordinates = read_frame(xyz, n_atoms)\n Coordinates.append(coordinates)\n Atoms.append(atoms)\n\n else:\n read_frame(xyz, n_atoms)\n frame+=1\n\n return Atoms, Coordinates","def streaming_from_file(filepath):\r\n pipe = rs.pipeline()\r\n cfg = rs.config()\r\n cfg.enable_device_from_file(filepath, repeat_playback=False)\r\n return pipe, cfg","def sox_get_sample_rates(self, files):\n min_rate = max_rate = None\n files_to_rates_dict = {}\n\n for f in files:\n result = self._process_command('soxi -r \"%s\"' % f, PIPE)\n try:\n rate = int(result[1][0].strip('\\n'))\n except ValueError:\n raise LetMeError('Unable to read sample rate from %s' % f)\n\n files_to_rates_dict[f] = rate\n\n logging.debug('\\nSample rate `%s` for `%s`', rate, f)\n\n if max_rate is None or rate > max_rate:\n max_rate = rate\n\n if min_rate is None or rate < min_rate:\n min_rate = rate\n\n logging.debug('Sample rates: min - %s, max - %s', min_rate, max_rate)\n return min_rate, max_rate, files_to_rates_dict","def get_phase_amplified_frames(\n filename,\n magphase,\n fl,\n fh,\n fs,\n progress_callback = lambda x: x,\n attenuateOtherFreq = False,\n pyrtype = 'octave',\n sigma = 0,\n temporalFilter = FIRWindowBP,\n scalevideo = 1,\n frames = None,\n):\n ## Read Video\n print(\"Preparing capture\")\n vr = cv2.VideoCapture(filename)\n nF = int(vr.get(cv2.CAP_PROP_FRAME_COUNT))\n ret, frame = vr.read()\n h, w, nC = frame.shape\n\n \n print(\"Loading: \", filename)\n vid = np.zeros([h, w, nC, nF],frame.dtype)\n vid[:,:,:,0] = frame\n for k in range(1, nF):\n retval, frame = vr.read()\n if retval:\n vid[:,:,:,k] = frame\n else:\n frames = (0,k)\n break\n progress_callback(10/nF)\n sys.stdout.write('.')\n sys.stdout.flush()\n print('\\n')\n vr.release()\n\n if not frames:\n frames = (0, nF-1)\n\n ## Compute spatial filters \n vid = vid[:,:,:,frames[0]:frames[1]+1]\n h, w, nC, nF = vid.shape\n if scalevideo != 1:\n h, w = int(scalevideo*h), int(scalevideo*w)\n\n print('Computing spatial filters\\n')\n ht = maxSCFpyrHt(np.zeros((h,w)))\n if pyrtype == 'octave':\n filters = getFilters((h, w), np.power(2,np.arange(0,-ht-1,-1).astype(float)), 4)\n print('Using octave bandwidth pyramid\\n') \n elif pyrtype == 'halfOctave': \n filters = getFilters((h, w), np.power(2,np.arange(0,-ht-0.5,-0.5).astype(float)), 8, twidth=0.75)\n print('Using half octave bandwidth pyramid\\n')\n elif pyrtype == 'smoothHalfOctave':\n filters = getFiltersSmoothWindow((h, w), 8, filtersPerOctave = 2) \n print('Using half octave pyramid with smooth window.\\n')\n elif pyrtype == 'quarterOctave':\n filters = getFiltersSmoothWindow((h, w), 8, filtersPerOctave = 4)\n print('Using quarter octave pyramid.\\n')\n else:\n raise ValueError('Invalid Filter Types')\n\n croppedFilters, filtIDX = getFilterIDX(filters)\n \n ## Initialization of motion magnified luma component\n magnifiedLumaFFT = np.zeros((h,w,nF),np.complex64)\n\n def buildLevel(im_dft,k):\n return np.fft.ifft2(\n np.fft.ifftshift(\n np.multiply(croppedFilters[k][0], im_dft[filtIDX[k,0], filtIDX[k,1]])\n )\n )\n\n def reconLevel(im_dft, k):\n return 2*(np.multiply(croppedFilters[k][0], np.fft.fftshift(np.fft.fft2(im_dft))))\n\n ## First compute phase differences from reference frame\n numLevels = len(filters) \n print('Moving video to Fourier domain\\n')\n vidFFT = np.zeros((h,w,nF),dtype=np.complex64)\n for k in range(0, nF):\n originalFrame = vid[:,:,:,k].astype(np.float32)\n originalFrame = cv2.cvtColor(originalFrame, cv2.COLOR_BGR2YUV)\n tVid = cv2.resize(originalFrame[:,:,0], (w, h), 0, 0, cv2.INTER_CUBIC)\n vidFFT[:,:,k] = np.fft.fftshift(np.fft.fft2(tVid))\n sys.stdout.write('.')\n sys.stdout.flush()\n progress_callback(20/nF)\n print('\\n')\n\n refFrame = 0\n for level in range(1, numLevels-1):\n ## Compute phases of level\n # We assume that the video is mostly static\n pyrRef = buildLevel(vidFFT[:,:,refFrame], level)\n pyrRefPhaseOrig = np.divide(pyrRef, np.abs(pyrRef))\n pyrRef = np.angle(pyrRef)\n\n delta = np.zeros((pyrRef.shape[0], pyrRef.shape[1] ,nF), np.float32)\n print('Processing level {0} of {1}\\n'.format(level+1, numLevels))\n\n for frameIDX in range(0, nF):\n filterResponse = buildLevel(vidFFT[:,:,frameIDX], level)\n pyrCurrent = np.angle(filterResponse)\n delta[:,:,frameIDX] = np.mod(np.pi+pyrCurrent-pyrRef,2*np.pi)-np.pi\n \n ## Temporal Filtering\n print('Bandpassing phases\\n')\n delta = temporalFilter(delta, fl/fs, fh/fs) \n\n ## Apply magnification\n eps = 2.2204e-16\n print('Applying magnification\\n')\n for frameIDX in range(0, nF):\n\n phaseOfFrame = delta[:,:,frameIDX]\n originalLevel = buildLevel(vidFFT[:,:,frameIDX], level)\n ## Amplitude Weighted Blur \n if (sigma != 0):\n phaseOfFrame = AmplitudeWeightedBlur(phaseOfFrame, np.abs(originalLevel)+eps, sigma)\n\n # Increase phase variation\n phaseOfFrame = magphase * phaseOfFrame\n \n if attenuateOtherFreq:\n tempOrig = np.multiply(np.abs(originalLevel), pyrRefPhaseOrig)\n else:\n tempOrig = originalLevel\n\n tempTransformOut = np.multiply(np.exp(1j*phaseOfFrame), tempOrig)\n\n curLevelFrame = reconLevel(tempTransformOut, level)\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] = \\\n curLevelFrame + magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX]\n \n progress_callback(50/(numLevels-2))\n\n ## Add unmolested lowpass residual\n level = len(filters)-1\n for frameIDX in range(0, nF):\n try:\n lowpassFrame = np.multiply(vidFFT[filtIDX[level, 0], filtIDX[level, 1] ,frameIDX], np.power(croppedFilters[-1][0], 2))\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] = \\\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] + lowpassFrame\n except IndexError:\n print(\"IndexError\")\n progress_callback(10/nF)\n\n for k in range(0, nF):\n magnifiedLuma = np.fft.ifft2(np.fft.ifftshift(magnifiedLumaFFT[:,:,k])).real\n originalFrame = cv2.cvtColor(vid[:,:,:,k].astype(np.float32), cv2.COLOR_BGR2YUV)\n originalFrame = cv2.resize(originalFrame, (w, h), 0, 0, cv2.INTER_CUBIC)\n originalFrame[:,:,0] = magnifiedLuma\n originalFrame = cv2.cvtColor(originalFrame, cv2.COLOR_YUV2BGR)\n originalFrame = cv2.convertScaleAbs(originalFrame)\n yield originalFrame\n progress_callback(10/nF)","def read(f, normalized=False):\r\n a = pydub.AudioSegment.from_mp3(f)\r\n y = np.array(a.get_array_of_samples())\r\n if a.channels == 2:\r\n y = y.reshape((-1, 2))\r\n if normalized:\r\n return a.frame_rate, np.float32(y) / 2**15\r\n else:\r\n return a.frame_rate, y","def __init__(self, pattern='/graphics/projects/scratch/wieschol/sync-data/*/*_noaudio.low.mp4',\n samples=10, shuffle=True, max_pos_dist=10, min_neg_dist=20, min_pos_dist=5):\n self.files = glob.glob(pattern)\n self.shuffle = shuffle\n self.max_pos_dist = max_pos_dist\n self.min_pos_dist = min_pos_dist\n self.min_neg_dist = min_neg_dist\n self.samples = samples","def __init__(self, renderer: sdl2.render.SDL_Renderer, filepath: str,\n sample_rate: int, loop: bool):\n self.textures: List[sdl2.render.SDL_Texture] = []\n for filename in sorted(os.listdir(filepath)):\n self.textures.append(\n texture_from_bmp(renderer, os.path.join(filepath, filename)))\n\n # Number of times to update current_frame per second\n self.sample_rate = sample_rate\n self.loop = loop\n\n # Index into textures list\n self.current_frame = 0","def get_Metadata_freq(metafile_science):\n\n mslist_file = open(metafile_science, 'r')\n LINES = mslist_file.readlines()\n mslist_file.close()\n\n frame = 'Frame'\n \n for i in range(len(LINES)):\n line = LINES[i]\n if line.find(frame) >=0:\n next_line = LINES[i+1]\n TOKS = next_line.split()\n chan_width = float(TOKS[10])*1000. # convert kHz to Hz\n cfreq = TOKS[12] #MHz\n nchan = TOKS[7]\n\n return chan_width, cfreq, nchan","def get_movie_data(files: list) -> list:\n pass","def readDriverFile(self, input_file):\n\n\n fid = open(self.basePath + input_file,'r')\n\n # Line 1\n line = fid.readline()\n l_input = line.split('!')\n mshfile = l_input[0].rstrip()\n\n # Line 2\n line = fid.readline()\n l_input = line.split('!')\n obsfile = l_input[0].rstrip()\n\n # Line 3\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input=='null':\n topofile = []\n\n else:\n topofile = l_input[0].rstrip()\n\n\n # Line 4\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n mstart = float(l_input[1])\n\n else:\n mstart = l_input[0].rstrip()\n\n # Line 5\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n mref = float(l_input[1])\n\n else:\n mref = l_input[0].rstrip()\n\n # Line 6\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n staticInput = float(l_input[1])\n\n elif l_input[0]=='DEFAULT':\n staticInput = None\n\n else:\n staticInput = l_input[0].rstrip()\n\n\n # Line 7\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input=='DEFAULT':\n magfile = []\n\n else:\n magfile = l_input[0].rstrip()\n\n # Line 8\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input=='DEFAULT':\n wgtfile = []\n\n else:\n wgtfile = l_input[0].rstrip()\n\n # Line 9\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n chi = float(l_input[0])\n\n # Line 10\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n val = np.array(l_input[0:4])\n alphas = val.astype(np.float)\n\n # Line 11\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n val = np.array(l_input[1:3])\n bounds = val.astype(np.float)\n\n else:\n bounds = l_input[0].rstrip()\n\n # Line 12\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n val = np.array(l_input[1:6])\n lpnorms = val.astype(np.float)\n\n else:\n lpnorms = l_input[0].rstrip()\n\n # Line 13\n line = fid.readline()\n l_input = re.split('[!\\s]',line)\n if l_input[0]=='VALUE':\n val = np.array(l_input[1:3])\n eps = val.astype(np.float)\n\n else:\n eps = [None,None]\n\n self.mshfile = mshfile\n self.obsfile = obsfile\n self.topofile = topofile\n self.mstart = mstart\n self._mrefInput = mref\n self._staticInput = staticInput\n self.magfile = magfile\n self.wgtfile = wgtfile\n self.chi = chi\n self.alphas = alphas\n self.bounds = bounds\n self.lpnorms = lpnorms\n self.eps = eps","def get_video_frame_rate(filename):\n clip = VideoFileClip(filename)\n frame_rate = clip.fps\n clip.close()\n return frame_rate","def audioRead(path):\n data, samplerate = sf.read(path)\n frames = data.shape[0]\n channels = len(data.shape)\n duration = 1/samplerate*frames\n return data, samplerate, path, duration, frames, channels","def INPUT_Periods_file(input):\n \n global events\n \n tb = 3600\n ta = 3600\n \n Period = input['min_date'].split('T')[0] + '_' + \\\n input['max_date'].split('T')[0] + '_' + \\\n str(input['min_mag']) + '_' + str(input['max_mag'])\n eventpath = os.path.join(input['datapath'], Period)\n \n len_events = len(events)\n \n input_period = open(os.path.join(os.getcwd(), 'INPUT-Periods'), 'a+')\n\n for i in range(0, len_events):\n \n str_event = str(events[i]['datetime']-tb) + '_' + \\\n str(events[i]['datetime']+ta) + '_' + \\\n str(events[i]['magnitude'] - 0.01) + '_' + \\\n str(events[i]['magnitude'] + 0.01) + '\\n'\n input_period.writelines(str_event)\n \n input_period.close()\n \n print '************************************************************' \n print 'New INPUT-Periods file is generated in your folder.'\n print 'Now, you could run the program again based on your desired event :)' \n print '************************************************************'\n \n sys.exit()","def f2gif(path,fps):\n print(\"==============================================\")\n print(\"Convert file to GIF!\")\n pathout = path[:-4]+'_'+str(fps)+'.gif'\n if path.endswith('.tif'): \n# import tifffile\n im = tifffile.imread(path)\n nFrames, h,w = im.shape\n dur=1/fps\n clip = []\n for i in range(nFrames):\n fr = cv2.cvtColor(im[i],cv2.COLOR_GRAY2RGB)\n clip.append(mp.ImageClip(fr).set_duration(dur))\n video = mp.concatenate_videoclips(clip, method=\"compose\",ismask=False)#ismask=True to make grayscale\n\n else:\n video = mp.VideoFileClip(path)\n fpsIn = int(video.fps)\n if fps != fpsIn:\n print(\"Conflict in fps! \\n\", \"[0] Use fps of input file;\\n\", \"[1] Use desired fps w/o speedup;\\n\",\n \"[2] Use desired fps w/ speedup:\")\n k = input('Input your selection: ')\n if k == 2:\n sf = fps/fpsIn\n video =video.fx(mp.vfx.speedx, sf)# Not working when sf<1\n elif k == 0:\n fps = fpsIn\n\n video.write_gif(pathout,fps=fps)\n video.reader.close()# To fix handel error problem\n# if path.endswith('.gif'):\n# clip.write_videofile(pathout,fps=fps,codec='libx264', bitrate='32 M',preset='ultrafast')\n print(\"==============================================\")\n print(\"MP4 convertion Done!\")","def read_frame(location, channels, start_time=None, \n end_time=None, duration=None):\n\n if end_time and duration:\n raise ValueError(\"end time and duration are mutually exclusive\")\n \n if type(location) is list:\n locations = location\n else:\n locations = [location]\n\n cum_cache = lal.Cache()\n for source in locations:\n dir_name, file_name = os.path.split(source)\n base_name, file_extension = os.path.splitext(file_name)\n \n if file_extension == \".lcf\" or file_extension == \".cache\":\n cache = lal.CacheImport(source)\n elif file_extension == \".gwf\": \n cache = lalframe.FrOpen(dir_name, file_name).cache\n else:\n raise TypeError(\"Invalid location name\")\n \n cum_cache = lal.CacheMerge(cum_cache, cache)\n \n stream = lalframe.FrStreamCacheOpen(cum_cache)\n \n stream.mode = lalframe.FR_STREAM_VERBOSE_MODE\n lalframe.FrSetMode(stream.mode | lalframe.FR_STREAM_CHECKSUM_MODE,\n stream)\n\n # determine duration of data\n if type(channels) is list:\n first_channel = channels[0]\n else:\n first_channel = channels\n data_length = lalframe.FrStreamGetVectorLength(first_channel, stream)\n channel_type = lalframe.FrStreamGetTimeSeriesType(first_channel, stream)\n create_series_func = _fr_type_map[channel_type][2]\n get_series_metadata_func = _fr_type_map[channel_type][3]\n series = create_series_func(first_channel, stream.epoch, 0, 0,\n lal.ADCCountUnit, 0)\n get_series_metadata_func(series, stream)\n data_duration = data_length * series.deltaT\n\n if start_time is None:\n start_time = stream.epoch*1\n if end_time is None:\n end_time = start_time + data_duration\n\n if type(start_time) is not lal.LIGOTimeGPS:\n start_time = lal.LIGOTimeGPS(start_time)\n if type(end_time) is not lal.LIGOTimeGPS:\n end_time = lal.LIGOTimeGPS(end_time)\n\n if duration is None:\n duration = float(end_time - start_time)\n else:\n duration = float(duration)\n\n # lalframe behaves dangerously with invalid duration so catch it here\n if duration <= 0:\n raise ValueError(\"Negative or null duration\")\n #if duration > data_duration:\n # raise ValueError(\"Requested duration longer than available data\")\n\n if type(channels) is list:\n all_data = []\n for channel in channels:\n channel_data = _read_channel(channel, stream, start_time, duration)\n lalframe.FrStreamSeek(stream, start_time)\n all_data.append(channel_data)\n return all_data\n else:\n return _read_channel(channels, stream, start_time, duration)","def rec_one_shot(self, sec, file_name=None):\n self.__open_noncallback_stream()\n frames = []\n for i in range(int(self.RATE / self.CHUNK * sec)):\n data = self.stream.read(self.CHUNK)\n data = np.fromstring(data, dtype=np.int16)\n frames.append(data)\n self.stream.stop_stream()\n if file_name is not None:\n with wave.open(file_name, 'wb') as wav_file:\n wav_file.setnchannels(self.CHANNELS)\n wav_file.setsampwidth(self.recorder.get_sample_size(self.FORMAT))\n wav_file.setframerate(self.RATE)\n wav_file.writeframes(b''.join(frames))\n frame = np.concatenate(frames, 0)\n self.stop_streaming()\n return frame","def read_all_files():\n paths = get_all_recording_paths()\n\n return read_by_paths(paths)","def stream_timelapse(path):\n parts = path.split('.')[0].split('_')\n count = int(parts[2])\n filename = parts[0] + '_{0:03d}_{1:03d}.jpg'\n for i in range(count):\n frame = open(filename.format(i, count), 'rb').read()\n yield b'--frame\\r\\nContent-Type: image/jpeg\\r\\nContent-Length: ' + \\\n str(len(frame)).encode() + b'\\r\\n\\r\\n' + frame + b'\\r\\n'\n time.sleep(0.5)","def t1_loadNFile(self):\n print \"noisubspectrumFile\"\n filename = tkFileDialog.askopenfilename()\n filename = self.filenameparser(filename)\n self.t1_noifilename = filename","def _default_specs(self):\n # Spectrometer specs\n self.model = \"Flame-S\" # Spectrometer model\n self.fov = 1 # Field of view fo spectrometer (radius of FOV)\n self.ILS = None # Number array holding instrument line shape (possibly don't hold this here?)\n self.fiber_diameter = 1e-3 # Diameter of optical fiber\n self.pix_num = 2048 # Number of pixels\n self.bit_depth = 16 # Bit depth of spectrometer detector\n\n # File information\n self.file_ext = '.npy' # Spectra saved as numpy array\n self.file_ss = '{}ss' # Shutter speed format spec\n self.file_ss_loc = 1 # Shutter speed location in filename\n self.file_spec_type = {'meas': 'Plume', 'dark': 'Dark', 'cal': 'ppmm', 'clear': 'Clear'}\n self.file_datestr = \"%Y-%m-%dT%H%M%S\" # Date/time format spec in filename\n self.file_datestr_loc = 0\n self.plume_params_file = 'plume_params.txt'\n self.plume_speed_id = 'plume_speed='\n self.plume_dist_id = 'plume_distance='\n\n # File which flags that a scan is complete. The file will be empty, just its presence is required\n self.scan_complete = 'complete.txt'\n\n # Acquisition settings\n self.start_int_time = 100 # Starting integration time\n self.start_coadd = 1 # Number of spectra to coadd\n self.framerate = 1 # Framerate of acquisitions (Hz)\n self.wavelengths = None # Wavelengths (nm)\n self.spectrum = None # Spectrum\n self.spectrum_filename = None # Filename for spectrum\n\n self.auto_int = True # Bool for requesting automated integration time adjustment\n self.min_saturation = 0.6 # Minimum saturation accepted before adjusting shutter speed (if auto_ss is True)\n self.max_saturation = 0.9 # Maximum saturation accepted before adjusting shutter speed (if auto_ss is True)\n self.saturation_range = [300, 335] # Range of wavelengths used in checking integration time\n self.saturation_pixels = 2 # Number of pixels to check\n\n # Predefined list of integration times for automatic exposure adjustment\n self.int_list = np.concatenate((np.arange(0.1, 0.5, 0.05),\n np.arange(0.5, 1, 0.1),\n np.arange(1, 5, 0.5),\n np.arange(5, 10, 1),\n np.arange(10, 50, 5),\n np.arange(50, 100, 10),\n np.arange(100, 500, 50),\n np.arange(500, 1000, 100),\n np.arange(10 ** 3, 10 ** 4, 500),\n np.array([10 ** 4])))","def open_read_files(answer_files, answers):\r\n \"\"\"And designates each file to a variable in answers\"\"\"\r\n count = 0\r\n s = 0\r\n answer_files2 = []\r\n for file in answer_files[:]: # Used [:] to get all file_names in answer_files\r\n ans = open(file, mode='r')\r\n print(f\"Opening {ans.name}\")\r\n time.sleep(s)\r\n answers[count] = ans\r\n count += 1\r\n if ans.closed == False: # Section for checking if files are closed\r\n print(f\"Closing {ans.name}\")\r\n ans.close()\r\n answer_files2.append(ans.name)\r\n answer_files.remove(ans.name)\r\n time.sleep(s)\r\n return answer_files2, answers","def file_name_list():\n file_names = []\n hour = h1\n minute = m1\n while hour * 60 + minute <= h2 * 60 + m2:\n file_name = generate_file_name(hour, minute)\n file_names.append(file_name)\n hour, minute = next_time(hour, minute)\n return file_names","def get_parameters_fastcharge(filename, source_directory):\n filename = filename.rsplit('.', 1)[0]\n strname = filename.rsplit('_CH', 1)[0]\n\n # Get date\n date = re.match(r'(\\d+)-(\\d+)-(\\d+)', strname)\n if date is None:\n warnings.warn(\"Date could not be parsed from {}\".format(filename))\n else:\n date = date.group()\n\n # Get channel number\n chno = re.findall(r'(CH+\\d*)', filename)\n if chno:\n chno = chno[0]\n else:\n chno = None\n warnings.warn(\"Channel number could not be parsed from {}\".format(filename))\n\n try:\n param_str = strname.rsplit(date + '_', 1)[1]\n param = param_str.replace('_', '.')\n\n if param.find('.') < 0:\n param = find_meta(filename, source_directory)\n\n q1 = re.findall(r'(\\d+per)', param)[0].split('per')[0]\n cc1 = re.findall(r'(\\d*\\.?\\d+C)', param.split(q1 + 'per.')[0])[0]\n cc2 = re.findall(r'(\\d*\\.?\\d+C)', param.split(q1 + 'per.')[1])[0]\n protocol = cc1+'('+q1+'%)-'+cc2\n except Exception as e:\n warnings.warn(\"Failed to parse protocol for {}: {}\".format(filename, e))\n protocol = None\n\n return date, chno, strname, protocol","def test_get_fasta_fps(self):\r\n\r\n file_basenames = [basename(self.fasta2_fp), basename(self.fasta3_fp),\r\n basename(self.fasta1_fp)]\r\n\r\n actual_fastas = get_fasta_fps(self.input_dir, file_basenames)\r\n\r\n expected_fasta = [self.fasta2_fp, self.fasta3_fp, self.fasta1_fp]\r\n\r\n self.assertEqual(actual_fastas, expected_fasta)","def get_configfile(files,\n seasoncyc_base=None,\n seasoncyc_sim=None,\n base_id='NCEP',\n sim_id='NCEP',\n timewin=1,\n varname='slp',\n seacyc=False,\n cycsmooth=91,\n nanalog=20,\n seasonwin=30,\n distfun='rms',\n outformat='.txt',\n period=[\"1973-01-01\", \"2012-12-31\"],\n bbox=\"-180.0,-90.0,180,90.0\",\n calccor=True,\n silent=False):\n from datetime import datetime as dt\n\n date_stamp = dt.strftime(dt.now(), format='%Y%m%d_%H%M%S')\n LOGGER.info('start configuration file preparation at: %s' % (date_stamp))\n\n # convert True/False to Fortran syntax\n seacyc = str(seacyc)\n calccor = str(calccor)\n silent = str(silent)\n\n # write stuff to configuration file\n # NB: if order or format or number changes, need to edit wps_analogs_viewer.py\n # and template_analogviewer.html where these scripts read in the config\n # params\n config_file = \"config.txt\"\n\n config = open(config_file, \"w\")\n\n config.write(\n '!Configuration file for CASTf90 analogs processes deployed in flyingpigeon\\n')\n config.write('!Created : %s \\n' % (date_stamp))\n config.write('!Version : 0.1.5 \\n')\n config.write('&FILES \\n')\n config.write(' my_files%archivefile = \"{file}\" \\n'.format(\n file=os.path.relpath(files[0])))\n config.write(' my_files%simulationfile = \"{file}\" \\n'.format(\n file=os.path.relpath(files[1])))\n config.write(' my_files%outputfile = \"{file}\" \\n'.format(\n file=os.path.relpath(files[2])))\n\n if seacyc is not 'False':\n config.write(' my_files%seacycfilebase = \"{file}\" \\n'.format(\n file=os.path.relpath(seasoncyc_base)))\n config.write(' my_files%seacycfilesim = \"{file}\" \\n'.format(\n file=os.path.relpath(seasoncyc_sim)))\n\n config.write('/ \\n')\n config.write('&PARAM \\n')\n config.write(' my_params%timewin = {timewin} \\n'.format(timewin=timewin))\n config.write(' my_params%varname = \"{varname}\" \\n'.format(varname=varname))\n config.write(' my_params%seacyc = .{seacyc}. \\n'.format(\n seacyc=seacyc.upper()))\n config.write(' my_params%cycsmooth = {cycsmooth} \\n'.format(\n cycsmooth=cycsmooth))\n config.write(' my_params%nanalog = {nanalog} \\n'.format(nanalog=nanalog))\n config.write(' my_params%seasonwin = {seasonwin} \\n'.format(\n seasonwin=seasonwin))\n config.write(' my_params%distfun = \"{distfun}\" \\n'.format(distfun=distfun))\n config.write(' my_params%calccor = .{calccor}. \\n'.format(\n calccor=calccor.upper()))\n config.write(' my_params%oformat = \"{outformat}\" \\n'.format(\n outformat=outformat)) # \".txt\" # ! if equals \".nc\"\n config.write(' my_params%silent = .{silent}.\\n'.format(\n silent=silent.upper()))\n config.write('/\\n')\n config.write('&ATTS\\n')\n config.write(' my_atts%simsource = \"{sim_id}\" \\n'.format(sim_id=sim_id)) # model name\n config.write(\n ' my_atts%predictorvar = \"{varname}\" \\n'.format(varname=varname))\n config.write(' my_atts%archisource = \"{base_id}\" \\n'.format(base_id=base_id))\n config.write(' my_atts%archiperiod = \"{start},{end}\" \\n'.format(\n start=period[0], end=period[1]))\n config.write(' my_atts%predictordom = \"{bbox}\" \\n'.format(bbox=bbox))\n config.write('/\\n')\n\n config.close()\n return config_file","def open_frame(path,number):\n num=str(number).zfill(3) #Zero filling\n name = glob.glob(path+\"/*\"+num+\"*\")\n if len(name)==0:\n name = glob.glob(path+\"/\"+str(number)+\".png\")\n if len(name)>1:\n print \"too many matches \",len(name),\" found\"\n name = name[0]\n img = Image.open(name)\n img = np.asarray(img)\n img.setflags(write=1)\n return img","def get_audio(name, n):\n audio_path = os.path.join(args.input_folder, name, \"audio.ogg\")\n if not os.path.exists(audio_path):\n ## Some folders have multiple .ogg files, so we need to first combine them into one file. Example:\n ## |── Universe\n ## │ ├── aligned.swc\n ## │ ├── audio1.ogg\n ## │ ├── audio2.ogg\n ## │ ├── audio3.ogg\n ## │ ├── audio4.ogg\n ## │ ├── audiometa.txt\n ## │ ├── info.json\n ## │ ├── wiki.html\n ## │ ├── wiki.txt\n ## │ └── wiki.xml\n\n multiple_ogg_files = []\n for i in range(1, 5):\n path = os.path.join(args.input_folder, name, \"audio\" + str(i) + \".ogg\")\n if os.path.exists(path):\n multiple_ogg_files.append(path)\n else:\n break\n if len(multiple_ogg_files) == 0:\n return\n elif len(multiple_ogg_files) == 1:\n os.system(\"cp \\\"\" + multiple_ogg_files[0] + \"\\\" \\\"\" + audio_path + \"\\\"\")\n else:\n tmp_file_name = \"ffmeg_inputs.txt\"\n print(\"tmp_file_name=\", tmp_file_name)\n with open(tmp_file_name, \"w\", encoding=\"utf-8\") as tmp_file:\n for path in multiple_ogg_files:\n tmp_file.write(\"file '\" + path + \"'\\n\")\n cmd = \"ffmpeg -f concat -i \\\"\" + tmp_file_name + \"\\\" -c copy \\\"\" + audio_path + \"\\\"\"\n print(cmd)\n os.system(cmd)\n\n output_audio_path = args.destination_folder + \"/audio/\" + str(n) + \".ogg\"\n os.system(\"cp \\\"\" + audio_path + \"\\\" \" + output_audio_path)","def get_data(path):\n if path.endswith('.mp3'):\n path = prepare_file(path, path.rstrip('mp3')+'wav')\n x, sr = librosa.load(path, duration=30)\n\n else:\n x, sr = librosa.load(path, duration=30)\n directory, file_name = os.path.split(path)\n return x, sr, file_name","def read_cospectrum(path,d):\r\n spec = []\r\n timeseries = []\r\n for i in range(len(d)):\r\n filename = path + d[i]\r\n\r\n with open(filename, \"r\") as f:\r\n reader = csv.reader(f,delimiter=',')\r\n ct=1\r\n for row in reader:\r\n if ct==6:\r\n Hz = float(row[0].split('_')[-1])\r\n elif ct==7:\r\n height = float(row[0].split('_')[-1])\r\n elif ct==8:\r\n ws = float(row[0].split('_')[-1])\r\n elif ct==9:\r\n avg_period = float(row[0].split('_')[-1])\r\n elif ct==13:\r\n header = row\r\n elif ct>13:\r\n break\r\n ct+=1\r\n \r\n meta = [Hz,height,ws,avg_period]\r\n \r\n thisspec = np.genfromtxt(filename,delimiter=',',skip_header=13)\r\n spec.append(thisspec)\r\n thistime = re.findall('\\d{8}-\\d{4}',filename)[0]\r\n thisdate = datetime.strptime(thistime,'%Y%m%d-%H%M')\r\n timeseries.append(thisdate) \r\n \r\n return spec, timeseries, header, meta","def getFileList(self):\n sid = 86400 # change to 3600 for hour-by-hour\n uDays = range(sid*(int(self.uStart)/sid),sid+(sid*(int(self.uStop)/sid)),sid)\n fileList = []\n sep = os.path.sep\n for d in uDays:\n s = unixTimeToString(d)\n ymdPath = 'year' + s[0:4] + sep + 'month' + s[5:7] + sep + 'day' + s[8:10]\n dirname = self.basePath + sep + ymdPath + sep + self.sensor + sep + 'padhist'\n pattern = '*' + self.sensor + '_hstv*.mat'\n nameList = glob.glob1(dirname,pattern)\n for name in nameList:\n uTime = stringTimeToUnix(name[0:13] + '_00_00.000')\n if ( self.uStart <= uTime <= self.uStop ):\n #print 'IN: %s' % unixTimeToString(uTime)\n fileList.append(dirname + sep + name)\n fileList.sort()\n self.fileList = fileList","def getVideoFrames(videoFilePath, startFrameNumber=-1, endFrameNumber=-1):\n frames=[]\n vidcap = cv2.VideoCapture(videoFilePath)\n fps=vidcap.get(cv2.CAP_PROP_FPS)\n totalFrame=vidcap.get(cv2.CAP_PROP_FRAME_COUNT)\n if startFrameNumber==-1:\n startFrameNumber = 0\n if endFrameNumber == -1:\n endFrameNumber = totalFrame - 1\n success,image = vidcap.read()\n count = 0\n success = True\n while success:\n image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n image = color.rgb2yiq(image).astype(np.float32)\n \n if count<startFrameNumber:\n success,image = vidcap.read()\n count+=1\n continue\n elif count>=endFrameNumber:\n break\n else: \n frames.append(image)\n success,image = vidcap.read()\n count += 1\n frames=np.array(frames)\n \n return fps, frames","def read_data(self):\n self.days = [0, 2, 3, 5, 6, 8, 9, 11, 13, 14]\n path = '../data/'\n data = []\n for day in self.days:\n filename = path + 'spectrum_day{}.txt'.format(day)\n data.append(read_file(filename))\n return data","def fileSetup(path):\n past_fnames = next(os.walk(path))[2]\n f_nums = []\n for f in past_fnames:\n if f.startswith('semi'):\n f_nums.append(int(f[4:8]))\n\n if not f_nums:\n now_fname = '/semi0001.h264'\n else:\n now_fname = '/semi%04d.h264' % (max(f_nums)+1, )\n\n now_fname = path+now_fname\n print 'Current filename: %s' % now_fname\n\n return now_fname","def fix_file(file_path: str, output_path_fixed: str, target_rate: int=16000,\n channels: int=1, output_path: str=None, min_duration: int=None,\n verbose_level: int=0):\n file_name = file_path.split(os.sep)[-1]\n new_file_path = output_path_fixed + os.sep + file_name\n\n try:\n # Get the audio length\n out = syscommand.system('soxi -D ' + file_path)\n duration = float(out)\n # Get the number of channels\n out = syscommand.system('soxi -c ' + file_path)\n current_n_channels = int(out)\n # Get the current rate\n out = syscommand.system('soxi -r ' + file_path)\n current_rate = int(out)\n if min_duration is not None and duration < min_duration:\n raise Exception(\"Minimum length not satisfied\")\n except Exception as err:\n if str(verbose_level) != '0':\n print(err)\n return None, file_path\n\n if current_rate != target_rate and current_n_channels != channels:\n speed = float(current_rate) / float(target_rate)\n cmd = 'sox -V{} -r 16k {} {} channels 1 ' \\\n 'speed {}'.format(verbose_level, file_path, new_file_path,\n speed)\n if str(verbose_level) == '2':\n print(cmd)\n os.system(cmd)\n return new_file_path, file_path\n elif current_rate != target_rate:\n speed = float(current_rate) / float(target_rate)\n cmd = 'sox -V{} -r 16k {} {} ' \\\n 'speed {}'.format(verbose_level, file_path, new_file_path,\n speed)\n if str(verbose_level) == '2':\n print(cmd)\n os.system(cmd)\n return new_file_path, file_path\n elif current_n_channels != channels:\n cmd = 'sox -V{} {} {} channels 1'.format(verbose_level, file_path,\n new_file_path)\n if str(verbose_level) == '2':\n print(cmd)\n os.system(cmd)\n return new_file_path, file_path\n\n # Copy file if output path were provided and the file is not there\n if output_path is not None:\n copyfile(file_path, new_file_path)\n return file_path, file_path","def getConfig():\n\n config = rFile(\"/var/www/html/config.txt\").split()\n f = int(config[0])\n mode = config[1]\n\n if (f in DABchannels and (mode == \"explore\" or mode == \"monitor\")):\n return f, mode\n else:\n return 227360000, \"explore\" # Kamzik - Bratislava","def t9_loadFile(self):\n print \"subspectrumFile\"\n filename = tkFileDialog.askopenfilename()\n filename = \"SubSpectrumData/\" + self.filenameparser(filename)\n orgin_file = self.filenameparser(filename)\n self.t9_filename = filename\n self.t9_orginfilename = orgin_file","def read_recording_names(feature_files):\n all_recording_names = {}\n for feature_file in feature_files:\n in_dir = '/'.join(feature_file.split('/')[:-1])\n name = \"recordings.list\"\n path = os.path.join(in_dir, name)\n if not os.path.exists(path):\n return None\n else:\n with open(path, 'r') as f:\n recording_names = f.readlines()\n recording_names = [recording_name.strip() for recording_name in recording_names]\n # feature file at this position is basically incorrect. it takes the name of the hdf5 file as a key in\n # the dictionary. the directory would be more intuitive. however, cmd_args.input is used later on to\n # access the names which is why this works\n all_recording_names.update({feature_file: recording_names})\n\n return all_recording_names","def getFileList(self):\n print 'getting fileList ...',\n sid = 86400 # change to 3600 for hour-by-hour\n uDays = range(sid*(int(self.uStart)/sid),sid+(sid*(int(self.uStop)/sid)),sid)\n fileList = []\n sep = os.path.sep\n for d in uDays:\n s = unixTimeToString(d)\n ymdPath = 'year' + s[0:4] + sep + 'month' + s[5:7] + sep + 'day' + s[8:10]\n dirname = self.basePath + sep + ymdPath + sep + self.subDir\n pattern = '*' + self.sensor\n nameList = glob.glob1(dirname,pattern)\n for name in nameList:\n ufStart = stringTimeToUnix(name[0:23])\n ufStop = stringTimeToUnix(name[24:47])\n if ( ufStart <= self.uStart <= ufStop ) or ( self.uStart <= ufStart <= self.uStop ) or ( ufStart <= self.uStop <= ufStop ):\n #print 'IN: %s' % unixTimeToString(uTime)\n fileList.append(dirname + sep + name)\n## else:\n## print 'OUT:\\n%s\\n%s\\n%s' % (unixTimeToString(ufStart),unixTimeToString(self.uStart),unixTimeToString(ufStop))\n fileList.sort()\n self.fileList = fileList\n print 'done'","def _load(self, filepath):\n import subprocess as sp\n command = ['ffmpeg',\n '-i', filepath,\n '-f', 's16le',\n '-acodec', 'pcm_s16le',\n '-ac', '1'] # channels: 2 for stereo, 1 for mono\n if self.sampling_rate != SAMPLING_RATE:\n command.extend(['-ar', str(self.sampling_rate)])\n command.append('-')\n # 30s at 44.1 kHz ~= 1.3e6\n proc = sp.run(command, stdout=sp.PIPE, bufsize=10**7, stderr=sp.DEVNULL, check=True)\n\n return np.fromstring(proc.stdout, dtype=\"int16\")","def video_audio_files(video_name, path_curr_vid, path_current_frames):\n video_file = f\"{path_curr_vid}{video_name}\"\n audio_file = f\"{path_current_frames}{video_name.replace(VIDEO_EXT,AUDIO_EXT)}\"\n return video_file, audio_file","def inputwav(filename):\n data, sr = sf.read(filename)\n print('Decoding \"'+filename+'\"...')\n print('Sample rate is '+str(sr)+'...')\n try:\n ch=len(data[0,])\n except:\n ch=1\n print('File contains '+str(ch)+' audio channel(s)...')\n #Reshape the data so other functions can interpret the array if mono.\n #basically transposing the data\n if ch==1:\n data=data.reshape(-1,1)\n n=len(data)\n #This prevents log(data) producing nan when data is 0\n data[np.where(data==0)]=0.00001\n #convert to dB\n data_dB=20*np.log10(abs(data))\n return n, data,data_dB,sr, ch","def param_info():\n\n\tgizmo_names = syn.getGizmoNames()\n\n\tfor gizmo in gizmo_names:\n\t\tparams = syn.getParameterNames(gizmo)\n\t#doesnt get all parameters from gizmos i.e. WaveFreq\n\n\t# get all info on the 'WaveFreq' parameter\n\tGIZMO = 'aStim2'\n\tPARAMETER = 'WaveFreq'\n\n\t# info = syn.getParameterInfo(GIZMO, PARAMETER)\n\t#\n\t# # get the array size (should be 100)\n\t# sz = syn.getParameterSize(GIZMO, PARAMETER)\n\t#\n\t# # write values 1 to 50 in second half of buffer\n\t# result = syn.setParameterValues(GIZMO, PARAMETER, np.arange(1, 51), 50)\n\t#\n\t# # read all values from buffer\n\t# syn.getParameterValues(GIZMO, PARAMETER, sz)\n\t#\n\t# # get all info on the 'Go' parameter\n\t# PARAMETER = 'Go'\n\t# info = syn.getParameterInfo(GIZMO, PARAMETER)\n\t#\n\t# # flip the switch\n\t# result = syn.setParameterValue(GIZMO, PARAMETER, 1)\n\t#\n\t# # check the value\n\tfreq = syn.getParameterValue(GIZMO, PARAMETER)\n\tprint('value =', freq)\n\tfreq = [freq]\n\n\t# also verify visually that the switch slipped in the run\n\t# time interface. This state change will be logged just\n\t# like any other variable change and saved with the runtime\n\t# state.\n\n\tnumTrials = 5 #total number of trials across stimuli\n\tISI = [2.0, 3.0, 4.0, 5.0] # ISI in seconds\n\n\t# flash parameters\n\tflash_dur = [.001] # flash durs in seconds (100 ms, 200 ms)\n\tluminance = [[1, 1, 1], [.86, .86, .86], [0, .1, 1]] # white , grayish, purple just for testing\n\n\t# auditory parameters\n\tduration = [.005] # in seconds; pulseDur in TDT\n\tsound_levels = [20.0, 40.0, 60.0, 80.0] # dB; waveAmp in TDT\n\n\t# Auditory on (T/F? if T then A+V, if F then Visual only)\n\tstims = {0: \"auditory_only\",\n\t\t\t 1: \"visual_only\",\n\t\t\t 2: \"A+V\"\n\t\t\t }\n\n\texper = Experiment(numTrials=numTrials, ISI=ISI, flash_dur=flash_dur, luminance=luminance, wave_freq=freq,\n\t\t\t\t\t pulse_dur=duration, wave_amp=sound_levels, stimulus=stims)\n\texper.run_experiment()","def getattr(self, path, *args, **pargs):\n path, meta = self.find_cue_path(path)\n if('.flaccuesplit.' in path):\n try:\n raw_path = path\n path, flaccue_details = path.split('.flaccuesplit.')\n path = self.clean_path(path)\n times, extension = os.path.splitext(flaccue_details)\n # Get the info for the base file.\n st = os.lstat(path)\n toreturn = dict((key, getattr(st, key)) for key in (\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\n 'st_nlink', 'st_size', 'st_uid'))\n # Estimate the file size.\n f = mutagen.File(path)\n start, end = times.split('.')\n # Minutes:Seconds:Frames\n # 75 frames per second.\n start_split = [int(x) for x in start.split(':')]\n if(len(start_split) != 3):\n start_time = 0\n else:\n start_time = start_split[0]*60 + start_split[1] + start_split[2]/75\n end_split = [int(x) for x in end.split(':')]\n if(len(end_split) != 3):\n end_time = f.info.length\n else:\n end_time = end_split[0]*60 + end_split[1] + end_split[2]/75\n toreturn['st_size'] = int((end_time - start_time) *\n f.info.channels *\n (f.info.bits_per_sample/8) *\n f.info.sample_rate)\n # Ensure the mode shows the file as readable.\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\n return toreturn\n except Exception:\n print(f'Error getting attributes for {raw_path}:', file=sys.stderr, flush=True)\n import traceback\n traceback.print_exc()\n # Otherwise, just get the normal info.\n path = self.clean_path(path)\n st = os.lstat(path)\n toreturn = dict((key, getattr(st, key)) for key in (\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\n 'st_nlink', 'st_size', 'st_uid'))\n # Ensure the mode shows the file as readable.\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\n return toreturn","def parse_fname(cmd_args):\n\n # Seasonal accumulation file\n if (cmd_args.period == 99):\n f_name = _parse_fname_season(cmd_args)\n else:\n f_name = _parse_fname_hour(cmd_args)\n\n return f_name","def get_metadata(my_path):\n with wave.open(my_path, \"rb\") as wave_file:\n frame_rate = wave_file.getframerate()\n channels = wave_file.getnchannels()\n my_format = pyaudio.get_format_from_width(wave_file.getsampwidth())\n return str(frame_rate), str(channels), str(my_format)","def readFT(self,file=\"out__1.ft\"):","def generate_config(filename: str,\n mw_pulse_duration: int = 20,\n flux_pulse_duration: int=40,\n ro_duration: int = 800,\n mw_mw_buffer=0,\n mw_flux_buffer=0,\n flux_mw_buffer=0,\n ro_latency: int = 0,\n mw_latency: int = 0,\n fl_latency: int = 0,\n init_duration: int = 200000):\n\n qubits = ['q0', 'q1', 'q2', 'q3', 'q4', 'q5', 'q6']\n lut_map = ['i {}', 'rx180 {}', 'ry180 {}', 'rx90 {}', 'ry90 {}',\n 'rxm90 {}', 'rym90 {}', 'rphi90 {}', 'spec {}', 'rx12 {}',\n 'square {}']\n flux_tuples = [(\"q2\", \"q0\"), (\"q0\", \"q2\"),\n (\"q0\", \"q3\"), (\"q3\", \"q0\"),\n (\"q3\", \"q1\"), (\"q1\", \"q3\"),\n (\"q1\", \"q4\"), (\"q4\", \"q1\"),\n (\"q2\", \"q5\"), (\"q5\", \"q2\"),\n (\"q5\", \"q3\"), (\"q3\", \"q5\"),\n (\"q3\", \"q6\"), (\"q6\", \"q3\"),\n (\"q6\", \"q4\"), (\"q4\", \"q6\")]\n\n cfg = {\n \"eqasm_compiler\": \"cc_light_compiler\",\n \"hardware_settings\": {\n \"qubit_number\": 7,\n \"cycle_time\": 20,\n \"mw_mw_buffer\": mw_mw_buffer,\n \"mw_flux_buffer\": mw_flux_buffer,\n \"mw_readout_buffer\": 0,\n \"flux_mw_buffer\": flux_mw_buffer,\n \"flux_flux_buffer\": 0,\n \"flux_readout_buffer\": 0,\n \"readout_mw_buffer\": 0,\n \"readout_flux_buffer\": 0,\n \"readout_readout_buffer\": 0},\n \"instructions\": {},\n \"resources\":\n {\"qubits\": {\"count\": 7},\n \"qwgs\": {\"count\": 3,\n \"connection_map\":\n {\n \"0\": [0, 1],\n \"1\": [2, 3, 4],\n \"2\": [5, 6]\n }\n },\n \"meas_units\": {\"count\": 7,\n \"connection_map\": {\"0\": [0],\n \"1\": [1],\n \"2\": [2],\n \"3\": [3],\n \"4\": [4],\n \"5\": [5],\n \"6\": [6]\n }\n },\n # FIXME OpenQL #103\n # \"meas_units\": {\"count\": 2,\n # \"connection_map\": {\"0\": [0, 2, 3, 5, 6],\n # \"1\": [1, 4]}\n # },\n \"edges\": {\"count\": 8,\n \"connection_map\": {\n \"0\": [2],\n \"1\": [3],\n \"2\": [0],\n \"3\": [1],\n \"4\": [6],\n \"5\": [7],\n \"6\": [4],\n \"7\": [5]\n }\n }\n },\n \"topology\":\n {\n \"x_size\": 5,\n \"y_size\": 3,\n \"qubits\":\n [\n {\"id\": 0, \"x\": 1, \"y\": 2},\n {\"id\": 1, \"x\": 3, \"y\": 2},\n {\"id\": 2, \"x\": 0, \"y\": 1},\n {\"id\": 3, \"x\": 2, \"y\": 1},\n {\"id\": 4, \"x\": 4, \"y\": 1},\n {\"id\": 5, \"x\": 1, \"y\": 0},\n {\"id\": 6, \"x\": 3, \"y\": 0}\n ],\n \"edges\":\n [\n {\"id\": 0, \"src\": 2, \"dst\": 0},\n {\"id\": 1, \"src\": 0, \"dst\": 3},\n {\"id\": 2, \"src\": 3, \"dst\": 1},\n {\"id\": 3, \"src\": 1, \"dst\": 4},\n {\"id\": 4, \"src\": 2, \"dst\": 5},\n {\"id\": 5, \"src\": 5, \"dst\": 3},\n {\"id\": 6, \"src\": 3, \"dst\": 6},\n {\"id\": 7, \"src\": 6, \"dst\": 4}\n ]\n },\n\n \"gate_decomposition\": {\n \"measz %0\": [\"measure %0\"],\n \"x %0\": [\"rx180 %0\"],\n \"y %0\": [\"ry180 %0\"],\n \"roty90 %0\": [\"ry90 %0\"],\n \"cnot %0,%1\": [\"ry90 %1\", \"cz %0,%1\", \"ry90 %1\"],\n\n # To support other forms of writing the same gates\n \"x180 %0\": [\"rx180 %0\"],\n \"y180 %0\": [\"ry180 %0\"],\n \"y90 %0\": [\"ry90 %0\"],\n \"x90 %0\": [\"rx90 %0\"],\n \"my90 %0\": [\"rym90 %0\"],\n \"mx90 %0\": [\"rxm90 %0\"],\n\n # Clifford decomposition per Epstein et al. Phys. Rev. A 89, 062321\n # (2014)\n \"cl_0 %0\": ['i %0'],\n \"cl_1 %0\": ['ry90 %0', 'rx90 %0'],\n \"cl_2 %0\": ['rxm90 %0', 'rym90 %0'],\n \"cl_3 %0\": ['rx180 %0'],\n \"cl_4 %0\": ['rym90 %0', 'rxm90 %0'],\n \"cl_5 %0\": ['rx90 %0', 'rym90 %0'],\n \"cl_6 %0\": ['ry180 %0'],\n \"cl_7 %0\": ['rym90 %0', 'rx90 %0'],\n \"cl_8 %0\": ['rx90 %0', 'ry90 %0'],\n \"cl_9 %0\": ['rx180 %0', 'ry180 %0'],\n \"cl_10 %0\": ['ry90 %0', 'rxm90 %0'],\n \"cl_11 %0\": ['rxm90 %0', 'ry90 %0'],\n\n \"cl_12 %0\": ['ry90 %0', 'rx180 %0'],\n \"cl_13 %0\": ['rxm90 %0'],\n \"cl_14 %0\": ['rx90 %0', 'rym90 %0', 'rxm90 %0'],\n \"cl_15 %0\": ['rym90 %0'],\n \"cl_16 %0\": ['rx90 %0'],\n \"cl_17 %0\": ['rx90 %0', 'ry90 %0', 'rx90 %0'],\n \"cl_18 %0\": ['rym90 %0', 'rx180 %0'],\n \"cl_19 %0\": ['rx90 %0', 'ry180 %0'],\n \"cl_20 %0\": ['rx90 %0', 'rym90 %0', 'rx90 %0'],\n \"cl_21 %0\": ['ry90 %0'],\n \"cl_22 %0\": ['rxm90 %0', 'ry180 %0'],\n \"cl_23 %0\": ['rx90 %0', 'ry90 %0', 'rxm90 %0']\n },\n }\n\n for q in qubits:\n cfg[\"instructions\"][\"prepz {}\".format(q)] = {\n \"duration\": init_duration,\n \"latency\": 0,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": True,\n \"type\": \"none\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"prepz\",\n \"cc_light_codeword\": 0,\n \"cc_light_opcode\": 2\n }\n\n for q in qubits:\n cfg[\"instructions\"][\"measure {}\".format(q)] = {\n \"duration\": ro_duration,\n \"latency\": ro_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"readout\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"measz\",\n \"cc_light_codeword\": 0,\n \"cc_light_opcode\": 4\n }\n\n for CW in range(len(lut_map)):\n for q in qubits:\n cfg[\"instructions\"][lut_map[CW].format(q)] = {\n \"duration\": mw_pulse_duration,\n \"latency\": mw_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"mw\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"cw_{:02}\".format(CW),\n \"cc_light_codeword\": CW,\n \"cc_light_opcode\": 8+CW}\n\n cfg[\"instructions\"]['c1'+lut_map[CW].format(q)] = {\n \"duration\": mw_pulse_duration,\n \"latency\": mw_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"mw\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"C1_cw_{:02}\".format(CW),\n \"cc_light_codeword\": CW,\n \"cc_light_opcode\": 32+8+CW,\n \"cc_light_cond\": 1} # 1 means : do if last meas. == 1\n\n\n cfg[\"instructions\"]['c0'+lut_map[CW].format(q)] = {\n \"duration\": mw_pulse_duration,\n \"latency\": mw_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"mw\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"C0_cw_{:02}\".format(CW),\n \"cc_light_codeword\": CW,\n \"cc_light_opcode\": 32+16+CW,\n \"cc_light_cond\": 2} # 2 means : do if last meas. == 0\n\n\n for CW in range(32):\n for q in qubits:\n cfg[\"instructions\"][\"cw_{:02} {}\".format(CW, q)] = {\n \"duration\": mw_pulse_duration,\n \"latency\": mw_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"mw\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"cw_{:02}\".format(CW),\n \"cc_light_codeword\": CW,\n \"cc_light_opcode\": 8+CW}\n\n for q in qubits:\n cfg[\"instructions\"][\"compensate {}\".format(q)] = {\n \"duration\": mw_pulse_duration,\n \"latency\": mw_latency,\n \"qubits\": [q],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": False,\n \"type\": \"mw\",\n \"cc_light_instr_type\": \"single_qubit_gate\",\n \"cc_light_instr\": \"cw_00\",\n \"cc_light_codeword\": 0,\n \"cc_light_opcode\": 8+0}\n\n # N.B. The codewords for CZ pulses need to be further specified.\n # I do not expect this to be correct for now.\n for ft in flux_tuples:\n # FIXME add space back in\n cfg[\"instructions\"][\"cz {},{}\".format(ft[0], ft[1])] = {\n \"duration\": flux_pulse_duration,\n \"latency\": fl_latency,\n \"qubits\": [ft[0], ft[1]],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": True,\n \"type\": \"flux\",\n \"cc_light_instr_type\": \"two_qubit_gate\",\n \"cc_light_instr\": \"fl_cw_{:02}\".format(1),\n \"cc_light_right_codeword\": 1,\n \"cc_light_left_codeword\": 1,\n \"cc_light_opcode\": 128+1\n }\n\n for cw_flux in range(8):\n for ft in flux_tuples:\n cfg[\"instructions\"][\"fl_cw_{:02} {},{}\".format(cw_flux,\n ft[0], ft[1])] = {\n \"duration\": flux_pulse_duration,\n \"latency\": fl_latency,\n \"qubits\": [ft[0], ft[1]],\n \"matrix\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\n \"disable_optimization\": True,\n \"type\": \"flux\",\n \"cc_light_instr_type\": \"two_qubit_gate\",\n \"cc_light_instr\": \"fl_cw_{:02}\".format(cw_flux),\n \"cc_light_right_codeword\": cw_flux,\n \"cc_light_left_codeword\": cw_flux,\n \"cc_light_opcode\": 128+cw_flux\n }\n\n with open(filename, 'w') as f:\n json.dump(cfg, f, indent=4)","def t8_loadFile(self):\n print \"spectrumFile\"\n filename = tkFileDialog.askopenfilename()\n filename = self.filenameparser(filename)\n self.t8_filename = filename","def read_all_files(\n pathname: Path, index: int = 0, pattern: str = \"dump-Trimer-*.gsd\"\n) -> List[Tuple[Variables, HoomdFrame]]:\n pathname = Path(pathname)\n snapshots = []\n for filename in sorted(glob.glob(str(pathname / pattern))):\n logger.debug(\"Reading %s\", Path(filename).stem)\n with gsd.hoomd.open(str(filename)) as trj:\n try:\n snapshots.append((get_filename_vars(filename), HoomdFrame(trj[index])))\n except IndexError:\n continue\n if not snapshots:\n logger.warning(\n \"There were no files found with a configuration at index %s\", index\n )\n return snapshots","def t6_loadFile(self):\n print \"subspectrumFile\"\n filename = tkFileDialog.askopenfilename()\n filename = \"SubSpectrumData/\" + self.filenameparser(filename)\n self.t6_filename = filename","def processFile(filename,length = 256,q=1,fs_in=8000,divide=4,plot=False):\n length = length*divide\n #fs = sample rate, sound = multichannel sound signal\n try:\n fs1, sound = wavfile.read(filename)\n except ValueError:\n print(str(filename) + ' failed to process')\n return 'failed'\n if fs1 != fs_in:\n raise ValueError('Sampling rate should be ' + str(fs_in) + ' for: ' + filename)\n sig1 = sound[:0] #left channel\n pre_emphasis = 0.97\n sig1 = np.append(sig1[0], sig1[1:] - pre_emphasis * sig1[:-1])\n\n \n fs2, sig2 = downsample(sig1,fs1,q)\n N2 = len(sig2)\n sig3 = sig2[N2//2-length:N2//2+length]\n #print(len(sig3))\n\n FFT = abs(scipy.fft(sig3))\n FFT_side = FFT[range(len(FFT)//2)]\n #freqs = scipy.fftpack.fftfreq(sig3.size, 1/fs2)\n #plt.plot(freqs,FFT)\n if len(FFT_side) != length:\n print('ERROR MESSAGE DETAILS')\n print('filename: ' + filename)\n print('length = ' + str(length))\n print('fs_in = ' + str(fs_in))\n print('q = ' + str(q))\n print('divide = ' + str(divide))\n total_time = len(sig1)/fs1\n print('total_time = ' + str(total_time))\n print('Please check: length < total_time*fs//(2*q)')\n print('Check: ' + str(length) + ' < ' + str(total_time*fs1//(2*q)))\n raise ValueError('Length FFT_side != length: ' + str(len(FFT_side)) + ' != ' + str(length))\n \n \n FFT_log = []\n # normalize FFT\n for value in FFT_side:\n value = np.log(value)\n FFT_log.append(value)\n max_val = getMax(FFT_log)[1]\n FFT_norm = []\n for value in FFT_log:\n FFT_norm.append(value/max_val)\n \n \n FFT_side = np.array(FFT_norm)\n FFT_divided = FFT_side[range(length//divide)]\n #plot = True\n if plot == True:\n freqs = scipy.fftpack.fftfreq(sig3.size, 1/fs2)\n freqs_divided = np.array(freqs[range(len(FFT_divided))])\n plt.plot(freqs_divided,FFT_divided) # plotting the complete fft spectrum\n plt.show()\n \n return FFT_divided","def get_files(file_list, mode):\n\tfile_set = set(file_list)\n\tif \"band\" in mode:\n\t\tband_all_set = set([\"bands.dat.gnu\", \"freq.plot\"])\n\t\tband_file_set = file_set & band_all_set ; remain_file_set = file_set - band_all_set\n\t\tfiles_str = \", \".join([f\"\\033[32m{b}\\033[0m\" for b in band_file_set]) + \"; \" + \", \".join(remain_file_set)\n\tif mode == \"dos\":\n\t\tdos_all_set = set([\"S.dos\"])\n\t\tdos_file_set = file_set & dos_all_set ; remain_file_set = file_set - dos_all_set\n\t\tfiles_str = \", \".join([f\"\\033[32m{d}\\033[0m\" for d in dos_file_set]) + \"; \" + \", \".join(remain_file_set)\n\tprint(f\"Files in the directory: {files_str}\"); file = input(\"Please choose your file (type one only): \")\n\treturn file","def load_time_streams(self, channels=None):\n if channels is None:\n channels = self.get_channels()\n\n if self.data is None:\n self.make_temp_data(channels=channels)\n elif self.data.shape[0] != channels.size:\n self.discard_temp_data()\n self.make_temp_data(channels=channels)\n\n frames = self.integration.frames\n fnf.load_timestream(\n frame_data=frames.data,\n frame_weights=frames.relative_weight,\n frame_valid=frames.valid,\n modeling_frames=frames.is_flagged('MODELING_FLAGS'),\n channel_indices=channels.indices,\n sample_flags=frames.sample_flag,\n timestream=self.data,\n points=self.points)","def read_inputs(self):\n curdir = os.getcwd()\n os.chdir(self.fst_dir)\n rstat = self.readFST()\n if rstat == 0:\n os.chdir(curdir)\n return 0\n # the names of the next files are either set by caller or come from the reading the FAST file\n rstat = self.readNoise()\n rstat = self.readAD()\n rstat = self.readBlade()\n rstat = self.readPtfm()\n os.chdir(curdir)","def get_per_lib_sff_fps(sff_dir):\r\n for dirpath, dirnames, fnames in walk(sff_dir):\r\n for fname in fnames:\r\n if fname.endswith('.sff'):\r\n libname, _ = splitext(fname)\r\n yield libname, join(dirpath, fname)","def get_audio():\n\tbuf = None\n\tnum_new_bytes = BUFFER_SIZE // REFRESH_BUFFER_FACTOR\n\twith open(INFILE) as fifo:\n\t\twhile True:\n\t\t\tif buf is None:\n\t\t\t\tbuf = fifo.read(BUFFER_SIZE)\n\t\t\telse:\n\t\t\t\tbuf = buf[num_new_bytes:] + fifo.read(num_new_bytes)\n\t\t\tyield buf","def t1_loadFile(self):\n print \"subspectrumFile\"\n filename = tkFileDialog.askopenfilename()\n filename = self.filenameparser(filename)\n self.t1_filename = filename","def _default_specs(self):\n # Spectrometer specs\n self.model = \"Flame-S\" # Spectrometer model\n self.fov = None # Field of view fo spectrometer\n self.ILS = None # Number array holding instrument line shape (possibly don't hold this here?)\n self.pix_num = 2048 # Number of pixels\n self.bit_depth = 16 # Bit depth of spectrometer detector\n\n # File information\n self.file_ext = '.npy' # Spectra saved as numpy array\n self.file_ss = '{}ss' # Shutter speed format spec\n self.file_spec_type = {'meas': 'Plume', 'dark': 'Dark', 'cal': 'ppmm', 'clear': 'Clear'}\n self.file_datestr = \"%Y-%m-%dT%H%M%S\" # Date/time format spec in filename\n\n\n\n # Acquisition settings\n self.start_int_time = 100 # Starting integration time\n self.start_coadd = 5 # Number of spectra to coadd\n self.framerate = 1 # Framerate of acquisitions (Hz)\n self.wavelengths = None # Wavelengths (nm)\n self.spectrum = None # Spectrum\n self.spectrum_filename = None # Filename for spectrum\n\n self.auto_int = True # Bool for requesting automated integration time adjustment\n self.min_saturation = 0.5 # Minimum saturation accepted before adjusting shutter speed (if auto_ss is True)\n self.max_saturation = 0.9 # Maximum saturation accepted before adjusting shutter speed (if auto_ss is True)\n self.saturation_range = [320, 330] # Range of wavelengths used in checking integration time\n\n # Predefined list of integration times for automatic exposure adjustment\n self.int_list = np.concatenate((np.arange(1, 10, 1),\n np.arange(10, 50, 5),\n np.arange(50, 100, 10),\n np.arange(100, 500, 50),\n np.arange(500, 1000, 100),\n np.arange(10 ** 3, 10 ** 4, 500),\n np.array([10 ** 4])))","def main():\r\n\r\n ### Choose and Import File\r\n\r\n inSound = Sound()\r\n\r\n rate = inSound.rate\r\n data = inSound.data\r\n dataLength = len(data)\r\n \r\n info = inSound.get_info()\r\n head, filename = os.path.split(info[0]) # get filename of input\r\n \r\n # Decide output directory and filename\r\n outDir = r'out'\r\n outFile = os.path.join(outDir, 'out_'+filename)\r\n\r\n # Check if data has multiple channels, if yes use only one\r\n if(len(data.shape) > 1):\r\n data = data[:,0]\r\n\r\n\r\n ### Set All Parameters\r\n\r\n #get parameters from user dialogue\r\n params = getParameters()\r\n\r\n numChannels = params['numChannels'][0] # number of Channels\r\n loFreq = params['loFreq'][0] # lower bound on frequencies\r\n hiFreq = params['hiFreq'][0] # upper bound on frequencies\r\n plotChannels = params['plotChannels'][0] # if it should plot the Gammatone channels\r\n block_time = params['block_time'][0] # in ms\r\n block_shift = params['block_shift'][0] # in ms\r\n selectChannels = params['selectChannels'][0] # number of channels to activate at a single time\r\n\r\n\r\n ### Filter input file\r\n\r\n filtered, channel_fs = filterDataGamaTone(data, rate, numChannels, loFreq, hiFreq, plotChannels)\r\n\r\n\r\n ### Gammatones -> Stimulation Amplitude for time block\r\n\r\n samples_in_block = np.floor(block_time * rate / 1000).astype('int')\r\n samples_in_shift = np.floor(block_shift * rate / 1000).astype('int')\r\n\r\n summed = gammatoneToAmplitude(filtered, samples_in_block, samples_in_shift)\r\n\r\n # only activate the n electrodes that have the largest stimulation\r\n amps = n_largest_channels(summed, n=selectChannels)\r\n\r\n \r\n #### Sound reconstruction\r\n\r\n # for each timeblock we need to duplicate enough samples to fill it at sample rate\r\n amps_samples = np.repeat(amps, samples_in_shift, axis=1)\r\n #trim end to get same length as input\r\n amps_samples = amps_samples[:,:dataLength] \r\n\r\n # from amplitude samples and frequencies, reconstruct sound\r\n res_data = generateSound(amps_samples, channel_fs, rate)\r\n\r\n\r\n ### Write to output file\r\n write(outFile, rate, res_data)\r\n print('Wrote file to: \\n' + outFile)","def get_frame_list(self):\r\n\r\n logger.debug('Executing frame extraction')\r\n\r\n frames_loaded = False\r\n\r\n # Try to load YAML file with frame list\r\n if os.path.exists(self.frames_file_path):\r\n\r\n print 'Loading YAML file with frame list'\r\n logger.debug('Loading YAML file with frame list')\r\n\r\n f_list = utils.load_YAML_file(self.frames_file_path)\r\n\r\n if f_list:\r\n self.frame_list = f_list\r\n\r\n print 'YAML file with frame_list loaded'\r\n logger.debug('YAML file with frame_list loaded')\r\n\r\n frames_loaded = True\r\n\r\n if not frames_loaded:\r\n\r\n print '\\n\\n### Frame extraction ###\\n'\r\n logger.debug('\\n\\n### Frame extraction ###\\n')\r\n\r\n # Save processing time\r\n start_time = cv2.getTickCount()\r\n\r\n if not (os.path.exists(self.frames_path)):\r\n os.makedirs(self.frames_path)\r\n\r\n # Counter for all frames\r\n frame_counter = 0\r\n\r\n # Value of frame_counter for last analyzed frame\r\n last_anal_frame = 0\r\n\r\n # Open video file\r\n capture = cv2.VideoCapture(self.resource_path)\r\n\r\n self.frame_list = []\r\n\r\n # Save parameters for this video\r\n param_dict = {}\r\n\r\n if capture is None or not capture.isOpened():\r\n\r\n error = 'Error in opening video file'\r\n\r\n print error\r\n logger.debug(error)\r\n\r\n return\r\n\r\n else:\r\n\r\n video_fps = capture.get(cv2.cv.CV_CAP_PROP_FPS)\r\n\r\n param_dict[c.VIDEO_FPS_KEY] = video_fps\r\n\r\n # Original number of frames\r\n tot_frames = capture.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT)\r\n\r\n param_dict[c.VIDEO_TOT_FRAMES_KEY] = tot_frames\r\n\r\n self.fps = video_fps\r\n\r\n self.video_frames = float(tot_frames)\r\n\r\n # Saved frames\r\n saved_frames = 0\r\n\r\n while True:\r\n\r\n # Read frame\r\n ret, frame = capture.read()\r\n\r\n # If no frame is read, abort\r\n if not ret:\r\n break\r\n\r\n used_fps = c.USED_FPS\r\n use_or_fps = c.USE_ORIGINAL_FPS\r\n use_or_res = c.USE_ORIGINAL_RES\r\n used_res_scale_factor = c.USED_RES_SCALE_FACTOR\r\n\r\n if self.params is not None:\r\n\r\n if c.USED_FPS_KEY in self.params:\r\n used_fps = self.params[c.USED_FPS_KEY]\r\n\r\n if c.USE_ORIGINAL_FPS_KEY in self.params:\r\n use_or_fps = self.params[c.USE_ORIGINAL_FPS_KEY]\r\n\r\n if c.USE_ORIGINAL_RES_KEY in self.params:\r\n use_or_res = self.params[c.USE_ORIGINAL_RES_KEY]\r\n\r\n if c.USED_RES_SCALE_FACTOR_KEY in self.params:\r\n used_res_scale_factor = self.params[\r\n c.USED_RES_SCALE_FACTOR_KEY]\r\n\r\n # Next frame to be analyzed\r\n next_frame = last_anal_frame + (video_fps / used_fps) - 1\r\n\r\n if use_or_fps or (frame_counter > next_frame):\r\n\r\n # Frame position in video in milliseconds\r\n elapsed_ms = capture.get(cv2.cv.CV_CAP_PROP_POS_MSEC)\r\n\r\n # print 'elapsed video s =', elapsed_video_s\r\n\r\n fr_name = '%07d.png' % frame_counter\r\n\r\n frame_path = os.path.join(self.frames_path, fr_name)\r\n\r\n # Resize frame\r\n if not use_or_res:\r\n fx = used_res_scale_factor\r\n\r\n fy = used_res_scale_factor\r\n\r\n interp = cv2.INTER_AREA\r\n\r\n frame = cv2.resize(src=frame, dsize=(0, 0),\r\n fx=fx, fy=fy,\r\n interpolation=interp)\r\n\r\n cv2.imwrite(frame_path, frame,\r\n [cv.CV_IMWRITE_PNG_COMPRESSION, 0])\r\n\r\n frame_dict = {c.SAVED_FRAME_NAME_KEY: fr_name,\r\n c.ELAPSED_VIDEO_TIME_KEY: int(elapsed_ms)}\r\n\r\n self.frame_list.append(frame_dict)\r\n\r\n last_anal_frame = frame_counter\r\n\r\n saved_frames += 1\r\n\r\n frame_counter += 1\r\n\r\n self.progress = 100 * (frame_counter / self.video_frames)\r\n\r\n print('progress: ' + str(self.progress) + ' % \\r'),\r\n\r\n del capture\r\n\r\n self.saved_frames = float(saved_frames)\r\n\r\n param_dict[c.VIDEO_SAVED_FRAMES_KEY] = self.saved_frames\r\n\r\n # Save frame list in YAML file\r\n utils.save_YAML_file(self.frames_file_path, self.frame_list)\r\n\r\n # Save video parameters in YAML file\r\n\r\n utils.save_YAML_file(self.params_file_path, param_dict)\r\n\r\n # Save processing time\r\n time_in_clocks = cv2.getTickCount() - start_time\r\n time_in_seconds = time_in_clocks / cv2.getTickFrequency()\r\n\r\n print 'Time for frame extraction:', str(time_in_seconds), 's\\n'\r\n logger.debug(\r\n 'Time for frame extraction:', str(time_in_seconds), 's\\n')\r\n\r\n self.anal_times[c.FRAME_EXTRACTION_TIME_KEY] = time_in_seconds\r\n\r\n utils.save_YAML_file(self.analysis_file_path, self.anal_times)","def split_into_frames(filename_raw, thr_var_per_event=5e-4, downsampling_factor=2, disable_display=False,\n filename_output_video=None):\n\n assert downsampling_factor == int(downsampling_factor), \"Error: downsampling_factor must be an integer\"\n assert downsampling_factor >= 0, \"Error: downsampling_factor must be >= 0\"\n\n mv_adaptive_rate_iterator = AdaptiveRateEventsIterator(input_path=filename_raw,\n thr_var_per_event=thr_var_per_event,\n downsampling_factor=downsampling_factor)\n\n height, width = mv_adaptive_rate_iterator.get_size()\n\n if filename_output_video == None:\n video_process = None\n else:\n assert not os.path.exists(filename_output_video)\n video_process = FFmpegWriter(filename_output_video)\n\n if video_process or not disable_display:\n img_bgr = np.zeros((height, width, 3), dtype=np.uint8)\n\n cv2.namedWindow(\"img\", cv2.WINDOW_NORMAL)\n\n for events in mv_adaptive_rate_iterator:\n assert events.size > 0\n start_ts = events[0][\"t\"]\n end_ts = events[-1][\"t\"]\n print(\"frame: {} -> {} delta_t: {} fps: {} nb_ev: {}\".format(start_ts, end_ts,\n end_ts - start_ts,\n 1e6 / (end_ts - start_ts),\n events.size))\n if video_process or not disable_display:\n img = events_to_diff_image(events, sensor_size=(height, width))\n img_bgr[...] = 0\n img_bgr[img < 0, 0] = 255\n img_bgr[img > 0, 1] = 255\n\n chunk_start_ts = events[0][\"t\"]\n chunk_end_ts = events[-1][\"t\"]\n delta_t_frame = chunk_end_ts - chunk_start_ts + 1\n frame_txt = \"ts: {} -> {} delta_t: {} fps: {} (nb_ev): {}\".format(chunk_start_ts, chunk_end_ts,\n delta_t_frame,\n int(1.e6/delta_t_frame),\n events.size)\n img_bgr[20:45, ...] = 0\n cv2.putText(img_bgr,\n frame_txt,\n (int(0.05 * width), 40),\n cv2.FONT_HERSHEY_PLAIN, 1.0, (200, 200, 100))\n\n if video_process:\n video_process.writeFrame(img_bgr.astype(np.uint8)[..., ::-1])\n if not disable_display:\n cv2.imshow(\"img\", img_bgr)\n if cv2.waitKey(1) & 0xFF == ord('q'):\n break\n\n if video_process:\n video_process.close()\n if not disable_display:\n cv2.destroyAllWindows()","def get_fps(vid_path, prefix):\n _, name = os.path.split(vid_path)\n i1 = name.find(prefix) + len(prefix)\n i2 = name[i1:].find('_')\n fps = int(name[i1:i1+i2])\n\n return fps","def load_batch(self, fpath, match, in_num):\n if in_num == None:\n in_num = input('Please specify IN number: ')\n\n if match == None:\n match = input('Please specify filename string to match for batch loading (ex. \\'_s2_\\'): ')\n\n # get a list of all matching files\n glob_match = f'{fpath}/*{match}*'\n files = glob.glob(glob_match)\n\n # load & concatenate files into a single dataframe\n data = pd.concat((pd.read_csv(file, header = [0, 1], index_col = 0, parse_dates=True, low_memory=False) for file in files)).sort_index()\n\n # extract sampling frequency\n s_freq = 1/(data.index[1] - data.index[0]).total_seconds()\n\n # reset the index to continuous time\n ind_freq = str(int(1/s_freq*1000000))+'us'\n ind_start = '1900-01-01 00:00:00.000'\n ind = pd.date_range(start = ind_start, periods=len(data), freq=ind_freq)\n data.index = ind\n\n # set metadata & attributes\n self.metadata = {'file_info':{'in_num': in_num, 'files': files, 'dir': fpath,\n 'match_phrase': match},\n 'analysis_info':{'s_freq': s_freq} }\n self.data = data\n self.s_freq = s_freq","def get_file_params(file_path):\n fpath, ftype = parse_path(file_path=file_path)\n\n if ftype == \"video\":\n volume, dims = get_video_params(video_path=fpath)\n else:\n volume, dims = get_image_params(image_path=fpath)\n\n return volume, dims","def FitsLookup(raw_filenames, config, config_arguments):\n\n warnings.filterwarnings('ignore')\n\n # Initialize the filelist and the progressbar variable smeantime and\n # total_len\n\n filelist = list()\n meantime = list()\n\n total_len = len(raw_filenames)\n\n # Loop over each file in raw_filenames getting the desired information\n\n for cont, filename in enumerate(raw_filenames):\n\n # Start the time measure\n start = time.time()\n\n # Get the file header\n header = fits.getheader(filename)\n\n # Extract the filetipe and classify it\n typestr = header[config.exposure_type]\n\n if typestr == config.science_type_id:\n img_type = 0\n elif typestr == config.dark_type_id or typestr == config.bias_type_id:\n img_type = 1\n elif typestr == config.flat_type_id:\n img_type = 2\n else:\n img_type = 3\n\n # Extract the filter\n\n filter = header[config.filter]\n\n # Extract the date and correct it with the time convention (night ->\n # 12:00 to 11:59)\n night = datetime.datetime.strptime(\n header[config.observed_date], config.date_format)\n\n if night.hour < 12:\n night = night.date() - datetime.timedelta(days=1)\n\n # Extract the exposure time\n\n exptime = header[config.expousure_time]\n\n # ---- HOW TO ADD MORE CLASSIFIERS TO THE RESULTING NUMPY ARRAY ------\n #\n # Using the header variable and the config_values dictionary you can\n # extract all the values from the file. For example, to extract the temp:\n #\n # >>> temp = header[config_values['temp']]\n #\n # Once you have your new variable, you have to add this to the filelist in\n # the code after this comment. For example, to add the temp in the previous-to-last\n # entry:\n #\n # >>> filelist.append((filename, type, filter, exptime, str(night), temp, header))\n #\n # Finally, you have to modify the numpy dtype. Following with our example, as the temp\n # is a float value, we can modify the dtype as:\n #\n # >>> dtype = np.dtype([('filename', 'S150'), ('type', int),\n # ('filter', 'S10'), ('exptime', int), ('night', 'S10'),\n # ('temp',float),('header', np.object)])\n #\n # Notice that the position of the new type in the dtype variable MUST match the position\n # in which you added your new variable to the filelist. As we added \"temp\" previous-to-last,\n # we have to add ('temp',float) in the position previous-to-last in the dtype.\n #\n # Now, you can use 'temp' for slicing, broadcasting and perform cool numpy stuff in the resulting\n # array. Also, this value will work in the filter_collection function.\n # Yay!\n\n # Append all the information to the filelist. MODIFY HERE IF NEEDED!\n\n filelist.append((filename, img_type, filter,\n exptime, str(night), header))\n\n # Update progress bar\n\n end = time.time()\n meantime.append(end - start)\n\n if config_arguments.verbose_flag and not config_arguments.no_interaction:\n update_progress(float(cont + 1) / total_len,\n np.mean(meantime) * (total_len - (cont + 1)))\n\n # Create the personalized dtype of the numpy array. MODIFY HERE IF NEEDED!\n\n dtype = np.dtype([('filename', 'S150'), ('type', int),\n ('filter', 'S10'), ('exptime', int), ('night', 'S10'), ('header', np.object)])\n\n return np.array(filelist, dtype=dtype)","def read_file(self, *args, **kwargs):\n if self.detector == \"FACET\":\n return self.read_facet(self.filename)\n elif self.detector == \"OpenFace\":\n return self.read_openface(self.filename)\n elif self.detector == \"Affectiva\":\n return self.read_affectiva(self.filename)\n elif self.detector == \"Feat\":\n return self.read_feat(self.filename)\n else:\n print(\"Must specifiy which detector [Feat, FACET, OpenFace, or Affectiva]\")","def get_sorted_fps_U(data_dir, max = 988):\n\n fps = os.listdir(data_dir)\n\n #extract index of timestep from file name\n idx_fps = []\n for fp in fps:\n _, file_number = fp.split(\"LSBU_\")\n #file_number is of form '<IDX>.vtu'\n idx = int(file_number.replace(\".vtu\", \"\"))\n idx_fps.append(idx)\n\n\n #sort by timestep\n assert len(idx_fps) == len(fps)\n zipped_pairs = zip(idx_fps, fps)\n fps_sorted = [x for _, x in sorted(zipped_pairs)]\n\n #add absolute path\n fps_sorted = [data_dir + x for x in fps_sorted]\n\n return fps_sorted","def listfile(self):\n print(\"Opened file(s):\")\n for f in self.fmap:\n print('\\t%s'%(self.files.index(self.fmap[f])),end=':')\n print(f)\n print(\"active file(s):\")\n for i in range(len(self.handle)):\n print('\\t%s'%(self.handle[i]),end=':')\n print(self.fname[i])","def gen_random_samples():\n if os.path.exists('Song_Samples'):\n pass\n else:\n os.mkdir('Song_Samples')\n for filename in os.listdir(\"Songs\"):\n rate, data = wavfile.read(os.path.join(\"Songs\", filename))\n song_duration = len(data) // rate\n start_point = randint(0, song_duration - SAMPLE_DURATION)\n end_point = start_point + SAMPLE_DURATION\n subprocess.call(['ffmpeg', '-i', os.path.join(\"Songs\", filename),\n '-ss', str(datetime.timedelta(seconds=start_point)), '-to',\n str(datetime.timedelta(seconds=end_point)), '-y', os.path.join(\"Song_Samples\", filename)])","def analyzeWAV(inputFile):\n data, fs, nbits = audiolab.wavread(inputFile)\n samplingRate = fs\n return [data, samplingRate]","def get_file_parameters(self, input_file):\n\n #\n # Read the Flag record.\n #\n input_file.seek(0, 0) # 0 = from start of file\n record = input_file.read(FLAG_RECORD_SIZE)\n\n #\n # Check for end of file.\n # If not reached, check for and parse a Flag record.\n #\n if len(record) != FLAG_RECORD_SIZE:\n log.warn(\"EOF reading for flag record\")\n raise SampleException(\"EOF reading for flag record\")\n \n (valid_record, regex_velocity_record, \n regex_end_velocity_record, format_unpack_velocity, \n record_size) = self.parse_flag_record(record)\n\n #\n # If there is a valid Flag record, process the Time record.\n #\n if valid_record:\n #\n # Read the Time record which is at the very end of the file.\n # Note that we don't care if the number of bytes between the\n # Flag record and the Time record is consistent with\n # the flags from the Flag record.\n # Put the file back at the beginning.\n #\n input_file.seek(0 - TIME_RECORD_SIZE, 2) # 2 = from end of file\n record = input_file.read(TIME_RECORD_SIZE)\n times = self.parse_time_record(record)\n input_file.seek(0, 0) # 0 = from start of file\n\n #\n # If the Flag record is invalid, we're done.\n #\n else:\n log.warn(\"Invalid Flag record\")\n raise SampleException(\"Invalid Flag record\")\n\n return valid_record, regex_velocity_record, regex_end_velocity_record, \\\n format_unpack_velocity, record_size, times","def getFiles(directory, showName, extension):\n os.chdir(directory)\n \n list = []\n \n for file in glob.glob(\"*\"+showName+\"*.\"+extension):\n list.append(file)\n \n return list"],"string":"[\n \"def read_data_samples(fp):\\n if(path.isdir(fp)):\\n fps = glob.glob(fp + '\\\\\\\\*.txt')\\n return list(map(lambda x: read_file(x), fps))\",\n \"def get_file_list(mixer_file, select_random, use_list_of_files):\\n logger = logging.getLogger(get_file_list.__name__)\\n files = list()\\n\\n if use_list_of_files:\\n with open(mixer_file, 'r') as list_file:\\n for line in list_file:\\n files.append(os.path.join('data/raw',line.strip()))\\n\\n if select_random:\\n random.shuffle(files)\\n\\n else:\\n\\n mixer = parse_mixer_file(mixer_file)\\n\\n for m in mixer:\\n path = os.path.join(project_dir, m[0])\\n all_mixer_files = [os.path.join(path,f) for f in os.listdir(path) \\n if os.path.isfile(os.path.join(path, f)) and f.split('.')[-1] == 'csv']\\n\\n current_files = list()\\n # Check if the number of samples is limited\\n if m[2] >= 0:\\n sample_count = 0\\n for f in all_mixer_files:\\n # Get number of lines without the header line\\n num_lines = sum(1 for line in open(f)) - 1\\n\\n if (sample_count + num_lines) > m[2]:\\n current_files.append((f, m[2] - sample_count))\\n sample_count += (m[2] - sample_count)\\n break\\n else:\\n current_files.append((f, -1))\\n sample_count += num_lines\\n\\n if sample_count < m[2]:\\n logger.warn('Not enough samples ({} < {}): {}'.format(sample_count, m[2], m[0]))\\n else:\\n # No limit, take all samples in the files\\n current_files = zip(all_mixer_files, [-1]*len(all_mixer_files))\\n\\n if m[1] < 0:\\n # -1 means all .csv files\\n files += current_files\\n elif m[1] > 0:\\n if m[1] > len(current_files):\\n logger.warn('Not enough files ({} < {}): {}'.format(len(current_files),\\n m[1], m[0]))\\n files += current_files[:m[1]]\\n\\n if select_random:\\n random.shuffle(files)\\n else:\\n files = sorted(files, key=lambda x: int(os.path.basename(x[0]).split('_')[-1].split('.')[0]))\\n\\n return files\",\n \"def main(_):\\n print('argument to expand', ARGS.video_in)\\n print('argument expanded', glob.glob(ARGS.video_in))\\n video_count = 0\\n for video_filename in glob.glob(ARGS.video_in):\\n print('start parsing', video_filename)\\n data = skvideo.io.ffprobe(video_filename)['video']\\n rate_str = six.ensure_str(data['@r_frame_rate']).split('/')\\n rate = float(rate_str[0]) / float(rate_str[1])\\n print('detected frame rate:', rate)\\n\\n print('load frames:')\\n video = skvideo.io.vreader(video_filename)\\n frame_count = 0\\n file_count = 0\\n for frame in video:\\n if (frame_count > ARGS.offset) and \\\\\\n ((frame_count-ARGS.offset)%ARGS.skip == 0) and \\\\\\n (frame_count/rate >= ARGS.from_s) and \\\\\\n (frame_count/rate <= ARGS.to_s or ARGS.to_s == -1):\\n print(frame_count,)\\n img = Image.fromarray(frame)\\n if ARGS.crop:\\n img = crop(img, ARGS.size)\\n # save file\\n file_number = file_count + video_count * ARGS.multiple + ARGS.start\\n if ARGS.format_ext.lower() == 'jpg':\\n file_out = os.path.join(ARGS.path_out,\\n 'f{:07d}.jpg'.format(file_number))\\n img.save(file_out, 'JPEG')\\n elif ARGS.format_ext.lower() == 'png':\\n file_out = os.path.join(ARGS.path_out,\\n 'f{:07d}.png'.format(file_number))\\n img.save(file_out, 'PNG')\\n else:\\n print('unrecognize format', ARGS.format_ext)\\n sys.exit()\\n file_count += 1\\n frame_count += 1\\n video_count += 1\",\n \"def get_file_bpm(path, params = {}):\\n try:\\n win_s = params['win_s']\\n samplerate = params['samplerate']\\n hop_s = params['hop_s']\\n except:\\n \\\"\\\"\\\"\\n # super fast\\n samplerate, win_s, hop_s = 4000, 128, 64 \\n # fast\\n samplerate, win_s, hop_s = 8000, 512, 128\\n \\\"\\\"\\\"\\n # default:\\n samplerate, win_s, hop_s = 44100, 1024, 512\\n\\n s = source(path, samplerate, hop_s)\\n samplerate = s.samplerate\\n o = tempo(\\\"specdiff\\\", win_s, hop_s, samplerate)\\n # List of beats, in samples\\n beats = []\\n # Total number of frames read\\n total_frames = 0\\n\\n while True:\\n samples, read = s()\\n is_beat = o(samples)\\n if is_beat:\\n this_beat = o.get_last_s()\\n beats.append(this_beat)\\n #if o.get_confidence() > .2 and len(beats) > 2.:\\n # break\\n total_frames += read\\n if read < hop_s:\\n break\\n\\n # Convert to periods and to bpm \\n bpms = 60./diff(beats)\\n b = median(bpms)\\n return b\",\n \"def read(ftype, inDir, inSuffix, startTime, endTime):\\n\\n\\tif ftype == 'ryan': return readRyan(inDir, inSuffix, startTime, endTime)\\t\\n\\telif ftype == 'segmotion': return readSegmotion(inDir, inSuffix, startTime, endTime)\\n\\telif ftype == 'probsevere': return readProbSevere(inDir, inSuffix, startTime, endTime)\",\n \"def seqIo_frImgs(fName, header=[], aviName=[], Is=[], sDir=[], name='I', ndig=5, f0=0, f1=1e6):\\n \\n if aviName!=[]: #avi movie exists\\n vc = cv2.VideoCapture(aviName)\\n if vc.isOpened(): rval = True\\n else:\\n rval = False\\n print('video not readable')\\n return\\n fps = vc.get(cv2.cv.CV_CAP_PROP_FPS)\\n NUM_FRAMES = int(vc.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT))\\n print(NUM_FRAMES)\\n IM_TOP_H = vc.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)\\n IM_TOP_W = vc.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)\\n header['width']=IM_TOP_W\\n header['height']=IM_TOP_H\\n header['fps']=fps\\n\\n sw = seqIo_writer(fName,header)\\n print('creating seq from AVI')\\n # initialize timer\\n timer = pb.ProgressBar(widgets=['Converting ', pb.Percentage(), ' -- ',\\n pb.FormatLabel('Frame %(value)d'), '/',\\n pb.FormatLabel('%(max)d'), ' [', pb.Timer(), '] ',\\n pb.Bar(), ' (', pb.ETA(), ') '], maxval=NUM_FRAMES)\\n for f in range(NUM_FRAMES):\\n rval, im = vc.read()\\n if rval:\\n im= im.astype(np.uint8)\\n sw.addFrame(im)\\n timer.update(f)\\n sw.close()\\n timer.finish()\\n elif Is==[]:\\n assert(os.path.isdir(sDir))\\n sw = seqIo_writer(fName,header)\\n frmstr = '%s/%s%%0%ii.%s' % (sDir,name,ndig,header.ext)\\n for frame in range(f0,f1):\\n f = frmstr % frame\\n if not os.path.isfile(f):break\\n fid = open(f, 'r')\\n if fid<0: sw.close(); assert(False)\\n I = fid.read()\\n fid.close()\\n b = bytearray(I)\\n assert (b[0] == 255 and b[1] == 216 and b[-2] == 255 and b[-1] == 217); # JPG\\n I = np.array(list(b)).astype(np.uint8)\\n sw.addFrame(I,0,0)\\n sw.close()\\n if frame==f0: print('No images found')\\n else:\\n nd = len(Is.shape)\\n if nd==2: nd=3\\n assert(nd<=4)\\n nFrm = Is.shape[nd-1]\\n header['height']=Is.shape[0]\\n header['width']=Is.shape[1]\\n sw =seqIo_writer(fName,header)\\n if nd==3:\\n for f in range(nFrm): sw.addFrame(Is[:,:,f])\\n if nd==4:\\n for f in range(nFrm): sw.addFrame(Is[:,:,:,f])\\n sw.close()\",\n \"def videoFrames(filename, framerate=1):\\n vid_file = os.path.join(os.path.dirname(os.getcwd()), \\\"Database\\\", \\\"Video\\\", filename)\\n print(vid_file)\\n assert os.path.isfile(vid_file), \\\"Given path is not a valid file\\\"\\n tmpdir = os.path.join(os.getcwd(), \\\"tmp\\\")\\n subprocess.run(\\n [\\n \\\"ffmpeg\\\",\\n \\\"-i\\\",\\n vid_file,\\n \\\"-r\\\",\\n f\\\"{framerate}\\\",\\n os.path.join(tmpdir, \\\"img_%04d.jpg\\\"),\\n ]\\n )\\n return [os.path.join(tmpdir, i) for i in os.listdir(tmpdir) if not i.endswith(\\\".wav\\\")]\",\n \"def get_filenames(b,X,timefac,BW):\\r\\n\\tn = int(200000*X*timefac); nn = int(200000*X*10)\\r\\n\\troot = \\\"./dat_LE_stream/\\\"\\r\\n\\trootL = 'C:/AsusWebStorage/MySyncData/TRAFILES/'\\r\\n\\tpodir = \\\"/b=\\\"+str(b)+\\\"/\\\" if BW else \\\"/HO/\\\"\\r\\n\\t\\r\\n\\ttrafile = rootL+\\\"TRA_BW_b\\\"+str(b)+\\\"X\\\"+str(int(X))+\\\"n\\\"+str(nn)+\\\"seed65438\\\"\\r\\n\\tif not os.path.isfile(trafile):\\r\\n\\t\\ttrafile = rootL+\\\"TRA_BW_b\\\"+str(b)+\\\"X\\\"+str(int(X))+\\\"n\\\"+str(n)+\\\"seed65438\\\"\\r\\n\\toutfile = root+podir+os.path.split(trafile)[1][4:]\\r\\n\\t\\r\\n\\trndfile = os.path.split(outfile)[0]+\\\"/RND_\\\"+os.path.split(outfile)[1]+\\\".png\\\"\\r\\n\\tpdffile = os.path.split(outfile)[0]+\\\"/PDF_\\\"+os.path.split(outfile)[1]\\r\\n\\tstrfile = os.path.split(outfile)[0]+\\\"/STR_\\\"+os.path.split(outfile)[1]\\r\\n\\t\\r\\n\\treturn trafile,rndfile,pdffile,strfile,n\",\n \"def gen_fps():\\n global data_src ,output_dir \\n logger = TaskFileLogger(\\\"GenFP\\\")\\n\\n h_vars = load_hydro_var()\\n if not os.path.exists(output_dir):\\n os.mkdir(output_dir)\\n\\n for h_type,var_d in h_vars.items():\\n print \\\"considering %s\\\" %h_type\\n\\n t_output_dir = os.path.join(output_dir,h_type)\\n if not os.path.exists(t_output_dir):\\n print \\\"creating path %s\\\" %t_output_dir\\n os.mkdir(t_output_dir)\\n logger.log(\\\"%s started\\\" %(h_type))\\n\\n for fname in glob.glob(data_src):\\n complex_id = os.path.basename(fname).split('.')[0] \\n fp_path = os.path.join(t_output_dir,complex_id + \\\".fp\\\" )\\n if os.path.exists(fp_path):\\n #print \\\"%s processed\\\" %complex_id\\n continue\\n print \\\"processing %s,fp saved as %s\\\" %(fname , fp_path )\\n c = Complex(fname,hydro_dict = var_d)\\n c.get_fp()\\n c.write_fp_to_file(fp_path)\\n\\n logger.log(\\\"%s finished\\\" %(h_type))\",\n \"def return_file_read(_):\\n return [\\\"scorevideo LOG\\\", \\\"File: log.mat\\\"]\",\n \"def __init__(self, inFile = None, inData = None, inRate = None):\\n \\n # Information about FFMPEG\\n self.ffmpeg_info = FFMPEG_info()\\n \\n if inData is not None:\\n if inRate is None:\\n print('Set the \\\"rate\\\" to the default value (8012 Hz).')\\n rate = 8012.0\\n self.generate_sound(inData, inRate)\\n else: \\n if inFile is None:\\n inFile = self._selectInput()\\n if inFile == 0:\\n return\\n try:\\n self.source = inFile\\n self.read_sound(self.source)\\n except FileNotFoundError as err:\\n print(err)\\n inFile = self._selectInput()\\n self.source = inFile\\n self.read_sound(self.source)\",\n \"def generate_readers(\\n viddir, camname, minopt=0, maxopt=300000, pathonly=False, extension=\\\".mp4\\\"\\n):\\n out = {}\\n mp4files = [\\n os.path.join(camname, f)\\n for f in os.listdir(os.path.join(viddir, camname))\\n if extension in f\\n and int(f.rsplit(extension)[0]) <= maxopt\\n and int(f.rsplit(extension)[0]) >= minopt\\n ]\\n\\n # This is a trick (that should work) for getting rid of\\n # awkward sub-directory folder names when they are being used\\n mp4files_scrub = [\\n os.path.join(\\n os.path.normpath(f).split(os.sep)[0], os.path.normpath(f).split(os.sep)[-1]\\n )\\n for f in mp4files\\n ]\\n\\n pixelformat = \\\"yuv420p\\\"\\n input_params = []\\n output_params = []\\n\\n for i in range(len(mp4files)):\\n if pathonly:\\n out[mp4files_scrub[i]] = os.path.join(viddir, mp4files[i])\\n else:\\n print(\\n \\\"NOTE: Ignoring {} files numbered above {}\\\".format(extensions, maxopt)\\n )\\n out[mp4files_scrub[i]] = imageio.get_reader(\\n os.path.join(viddir, mp4files[i]),\\n pixelformat=pixelformat,\\n input_params=input_params,\\n output_params=output_params,\\n )\\n\\n return out\",\n \"def framerate(self):\\n return self.config.get('framerate', 15)\",\n \"def OpenSoundFiles():\\n\\n wildcard = create_wildcard(\\\"Sound files\\\", sppas.src.audiodata.aio.extensionsul)\\n wildcard += '|' + create_wildcard(\\\"All files\\\", ['*', '*.*'])\\n\\n files = list()\\n dlg = wx.FileDialog(None, \\n \\\"Select sound file(s)\\\", \\n paths.samples, \\n \\\"\\\", \\n wildcard, \\n wx.FD_OPEN | wx.MULTIPLE | wx.FD_CHANGE_DIR)\\n if dlg.ShowModal() == wx.ID_OK:\\n files = dlg.GetPaths()\\n\\n dlg.Destroy()\\n\\n return files\",\n \"def _settings(filename):\\n\\n with open(filename, 'r') as datafile:\\n daq_type = datafile.readline().strip().split(',')[1]\\n sample_hz = int(datafile.readline().strip().split(',')[1])\\n channels = datafile.readline().strip().split(',')\\n return (daq_type, sample_hz, channels)\",\n \"def read_local_20Hz_files(**kwargs):\\n pathlst = kwargs.get('pathlst')\\n product = kwargs.get('product')\\n varalias = kwargs.get('varalias')\\n sdate = kwargs.get('sdate')\\n edate = kwargs.get('edate')\\n twin = kwargs.get('twin')\\n\\n # establish coords if defined in config file\\n timestr = satellite_dict[product]['vardef']['time']\\n lonstr = satellite_dict[product]['vardef']['lons']\\n latstr = satellite_dict[product]['vardef']['lats']\\n\\n # adjust start and end\\n sdate = sdate - timedelta(minutes=twin)\\n edate = edate + timedelta(minutes=twin)\\n # get meta data\\n ncmeta = ncdumpMeta(pathlst[0])\\n ncvar = get_filevarname(varalias, variable_info,\\n satellite_dict[product], ncmeta)\\n # retrieve sliced data\\n ds = read_netcdfs(pathlst)\\n ds_sort = ds.sortby(timestr)\\n\\n # get indices for included time period\\n nptime = ds_sort[timestr].data\\n print('here0')\\n print(len(nptime))\\n #dtime = [parse_date(str(nptime[i])) for i in range(len(nptime))]\\n print('here1')\\n #idx = find_included_times_pd(dtime, sdate=sdate, edate=edate)\\n idx = find_included_times_pd(nptime, sdate=sdate, edate=edate)\\n print(len(nptime[idx]))\\n print('here2')\\n dtime = [parse_date(str(nptime[idx][i])) for i in range(len(nptime[idx]))]\\n print(dtime)\\n print('here3')\\n #dtime = list(np.array(dtime)[idx])\\n lons = list(((ds_sort[lonstr].data[idx] - 180) % 360) - 180)\\n lats = list(ds_sort[latstr].data[idx])\\n\\n unxt = (nptime[idx].astype(int) / 10**9)\\n\\n # make dict and start with stdvarname for varalias\\n stdvarname = variable_info[varalias]['standard_name']\\n vardict = {}\\n vardict[stdvarname] = list(ds_sort[ncvar].data[idx])\\n vardict['longitude'] = lons\\n vardict['latitude'] = lats\\n vardict['time'] = unxt\\n vardict['datetime'] = dtime\\n vardict['time_unit'] = variable_info['time']['units']\\n print(vardict.keys())\\n return vardict\",\n \"def readNextGenSpectrum(fname=''):\\n\\n print('Reading : ', fname)\\n\\n with open(fname, 'r') as rfile:\\n dum = rfile.readline()\\n sdum = dum.split()\\n teff = float(sdum[0])\\n logg = float(sdum[1])\\n mph = float(sdum[2])\\n dum = rfile.readline()\\n nwav = float(dum.split()[0])\\n\\n bigline = []\\n dum = rfile.readline()\\n while dum.strip() != '':\\n sdum = dum.split()\\n for i in range(len(sdum)):\\n bigline.append(float(sdum[i]))\\n dum = rfile.readline()\\n\\n bigline = np.array(bigline)\\n # Convert wavelength from angstrom to micron\\n wav = bigline[:nwav] / 1e4\\n inu = bigline[nwav:2 * nwav]\\n bnu = bigline[nwav * 2:nwav * 3]\\n\\n ii = wav.argsort()\\n wav = wav[ii]\\n inu = inu[ii] * 1e-8 * wav * 1e4 / np.pi / (29979245800.0 / wav * 1e4)\\n bnu = bnu[ii] * 1e-8 * wav * 1e4 / np.pi / (29979245800.0 / wav * 1e4)\\n\\n #\\n # The unit is now erg/s/cm/Hz/ster\\n #\\n\\n return {'teff': teff, 'logg': logg, 'mph': mph, 'nwav': nwav, 'wav': wav, 'inu': inu, 'bnu': bnu}\",\n \"def file_info(file_name, file_pattern):\\n match = re.compile(file_pattern).match(file_name)\\n if match:\\n basepath = match.group('basepath')\\n sensor = match.group('sensor')\\n ax = match.group('ax')\\n freq = match.group('freq')\\n date = match.group('date')\\n return basepath, sensor, ax, freq, date\\n else:\\n return None # there is no file extension to file_name\",\n \"def do_f(self, parms):\\n\\t\\tprint self.files\",\n \"def _read_config_file(self):\\n wcec = 0\\n deadline = 0\\n jitter = 0\\n init_freq = 0\\n freqs_volt = {}\\n freqs = []\\n volts = []\\n config_file_name = self._find_file('sim_simple.config')\\n with open(config_file_name, 'rU') as f:\\n lines = f.readlines()\\n try:\\n for freq in lines[0].split():\\n freqs.append(float(freq))\\n\\n for volt in lines[1].split():\\n volts.append(float(volt))\\n\\n for i in range(0, len(freqs)):\\n freqs_volt[freqs[i]] = volts[i]\\n\\n data = lines[2].split()\\n wcec = float(data[0])\\n deadline = float(data[1])\\n period = float(data[2])\\n jitter = float(data[3])\\n init_freq = float(data[4])\\n except ValueError, IndexError:\\n print 'Invalid data in config file'\\n sys.exit(1)\\n\\n return wcec, deadline, period, jitter, init_freq, freqs_volt\",\n \"def readPlayerImageFiles(self):\\n currentPath = os.path.dirname(os.path.abspath(__file__))\\n listOfFileNames=[]\\n for i in os.listdir(currentPath):\\n if re.match(\\\"player\\\\_\\\\d+\\\",i): #i.endswith(\\\".gif\\\")\\n listOfFileNames.append(currentPath+'/'+i)\\n return listOfFileNames\",\n \"def fillFileList(self, dirName):\\n if not os.path.isdir(dirName):\\n print(\\\"Warning: directory doesn't exist\\\")\\n return\\n\\n self.listFiles.fill(dirName, fileName=None, readFmt=True, addWavNum=True, recursive=True)\\n\\n # while reading the file, we also collected a list of species present there\\n spList = list(self.listFiles.spList)\\n # and sample rate info\\n fs = list(self.listFiles.fsList)\\n\\n if len(fs)==0:\\n print(\\\"Warning: no suitable files found\\\")\\n return\\n\\n # might need better limits on selectable sample rate here\\n self.fs.setValue(int(np.min(fs)))\\n self.fs.setRange(4000, int(np.max(fs)))\\n self.fs.setSingleStep(4000)\\n self.fs.setTickInterval(4000)\\n\\n spList.insert(0, 'Choose species...')\\n self.species.clear()\\n self.species.addItems(spList)\\n if len(spList)==2:\\n self.species.setCurrentIndex(1)\",\n \"def _open_stream(config):\\n p = pyaudio.PyAudio()\\n stream = p.open(\\n format = config[\\\"format\\\"],\\n channels = config[\\\"channels\\\"],\\n rate = config[\\\"rate\\\"],\\n input = True,\\n frames_per_buffer = config[\\\"chunk\\\"]\\n )\\n return p, stream\",\n \"def filesample(filename):\\n sampling_rate, samples = wavfile.read(filename)\\n times = np.arange(len(samples)) / sampling_rate\\n return samples, sampling_rate\",\n \"def find_files(config, slot='*'):\\n f_pattern = os.path.join(os.path.join(config['path'],config['led_name']), slot+'*' + config['led_name'] + '*'\\n + config['current'] + '*' + config['exp_time'] + '*'\\n + config['xpos'] + '*' + config['ypos'] + '*')\\n print(f_pattern)\\n return glob.glob(f_pattern)\",\n \"def get_frame_rate(filename):\\n cmd = ('ffprobe -v 0 -of flat=s=_ -select_streams v:0 -show_entries '\\n 'stream=avg_frame_rate -of default=nokey=1:noprint_wrappers=1 ' +\\n filename).split()\\n pid = subprocess.run(cmd, stdout=subprocess.PIPE,\\n universal_newlines=True)\\n if pid.returncode != 0:\\n return None\\n\\n frame_rate_exp = pid.stdout.rstrip()\\n try:\\n frame_rate = float(frame_rate_exp)\\n except:\\n if frame_rate_exp == 'N/A':\\n frame_rate = 0.\\n else:\\n numerator, denominator = map(float, frame_rate_exp.split('/'))\\n if denominator == 0:\\n frame_rate = 0\\n else:\\n frame_rate = numerator / denominator\\n return frame_rate\",\n \"def files_sim(config):\\n file_sim = sorted(glob.glob(config['str_dir'] + '/simulation/' +\\n '{}/{}nm/txt_files/*.txt'.format(\\n config['date'], config['wavelength'])))\\n return file_sim\",\n \"def get_frame_by_frame(name=None, fps=4, write_to_disk=False, display_feed=False, on_capture=None):\\n\\n reset_camera()\\n\\n if name is None:\\n name = \\\"fbf_\\\" + str(int(time()))\\n \\n dname = None\\n if write_to_disk:\\n chdir(cwd)\\n dname = join(dirname(realpath(sys.argv[0])), \\\"train\\\", \\\"data\\\", name)\\n if not exists(dname):\\n print(\\\"Created dir: %s\\\" % dname)\\n mkdir(dname)\\n else:\\n print(\\\"Using dir: %s\\\" % dname)\\n else:\\n print('Not writing to disk')\\n\\n def _snap(name, dname, write, display, capture_callback):\\n global camera\\n s, img = camera.read()\\n\\n if s and capture_callback:\\n img = capture_callback(img)\\n\\n if s and display:\\n cv2.imshow(name, img)\\n cv2.waitKey(1) \\n\\n if write:\\n chdir(dname)\\n number_of_files = len([item for item in os.listdir(dname) if os.path.isfile(os.path.join(dname, item))])\\n path = \\\"./\\\" + str(number_of_files + 1) + \\\".png\\\"\\n if s:\\n imwrite(path, img)\\n print(\\\"Saved to \\\" + dname + \\\"/\\\" + str(number_of_files + 1) + \\\".png\\\")\\n else:\\n print(\\\"Could not read image %d from camera\\\" % (number_of_files + 1))\\n chdir(cwd)\\n\\n return Timer(1 / fps, _snap, name, dname, write_to_disk, display_feed, on_capture).use_mp()\",\n \"def readAudioFile(path):\\n\\n extension = os.path.splitext(path)[1]\\n\\n try:\\n # Commented below, as we don't need this\\n # #if extension.lower() == '.wav':\\n # #[Fs, x] = wavfile.read(path)\\n # if extension.lower() == '.aif' or extension.lower() == '.aiff':\\n # s = aifc.open(path, 'r')\\n # nframes = s.getnframes()\\n # strsig = s.readframes(nframes)\\n # x = numpy.fromstring(strsig, numpy.short).byteswap()\\n # Fs = s.getframerate()\\n if extension.lower() == '.mp3' or extension.lower() == '.wav' or extension.lower() == '.au' or extension.lower() == '.ogg':\\n try:\\n audiofile = AudioSegment.from_file(path)\\n except:\\n print(\\\"Error: file not found or other I/O error. \\\"\\n \\\"(DECODING FAILED)\\\")\\n return -1 ,-1\\n\\n if audiofile.sample_width == 2:\\n data = numpy.fromstring(audiofile._data, numpy.int16)\\n elif audiofile.sample_width == 4:\\n data = numpy.fromstring(audiofile._data, numpy.int32)\\n else:\\n return -1, -1\\n Fs = audiofile.frame_rate\\n x = numpy.array(data[0::audiofile.channels]).T\\n else:\\n print(\\\"Error in readAudioFile(): Unknown file type!\\\")\\n return -1, -1\\n except IOError:\\n print(\\\"Error: file not found or other I/O error.\\\")\\n return -1, -1\\n\\n if x.ndim == 2:\\n if x.shape[1] == 2:\\n x = x.flatten()\\n\\n return Fs, x\",\n \"def read_xyz(filename, freq):\\n\\n\\n#xyz file\\n\\n Atoms = []\\n Coordinates = []\\n\\n xyz = open(filename)\\n frame = 0\\n while True:\\n\\n n_atoms = xyz.readline()\\n\\n if n_atoms == '':\\n break\\n else:\\n n_atoms = int(n_atoms)\\n title = xyz.readline()\\n\\n if frame%freq==0:\\n atoms, coordinates = read_frame(xyz, n_atoms)\\n Coordinates.append(coordinates)\\n Atoms.append(atoms)\\n\\n else:\\n read_frame(xyz, n_atoms)\\n frame+=1\\n\\n return Atoms, Coordinates\",\n \"def streaming_from_file(filepath):\\r\\n pipe = rs.pipeline()\\r\\n cfg = rs.config()\\r\\n cfg.enable_device_from_file(filepath, repeat_playback=False)\\r\\n return pipe, cfg\",\n \"def sox_get_sample_rates(self, files):\\n min_rate = max_rate = None\\n files_to_rates_dict = {}\\n\\n for f in files:\\n result = self._process_command('soxi -r \\\"%s\\\"' % f, PIPE)\\n try:\\n rate = int(result[1][0].strip('\\\\n'))\\n except ValueError:\\n raise LetMeError('Unable to read sample rate from %s' % f)\\n\\n files_to_rates_dict[f] = rate\\n\\n logging.debug('\\\\nSample rate `%s` for `%s`', rate, f)\\n\\n if max_rate is None or rate > max_rate:\\n max_rate = rate\\n\\n if min_rate is None or rate < min_rate:\\n min_rate = rate\\n\\n logging.debug('Sample rates: min - %s, max - %s', min_rate, max_rate)\\n return min_rate, max_rate, files_to_rates_dict\",\n \"def get_phase_amplified_frames(\\n filename,\\n magphase,\\n fl,\\n fh,\\n fs,\\n progress_callback = lambda x: x,\\n attenuateOtherFreq = False,\\n pyrtype = 'octave',\\n sigma = 0,\\n temporalFilter = FIRWindowBP,\\n scalevideo = 1,\\n frames = None,\\n):\\n ## Read Video\\n print(\\\"Preparing capture\\\")\\n vr = cv2.VideoCapture(filename)\\n nF = int(vr.get(cv2.CAP_PROP_FRAME_COUNT))\\n ret, frame = vr.read()\\n h, w, nC = frame.shape\\n\\n \\n print(\\\"Loading: \\\", filename)\\n vid = np.zeros([h, w, nC, nF],frame.dtype)\\n vid[:,:,:,0] = frame\\n for k in range(1, nF):\\n retval, frame = vr.read()\\n if retval:\\n vid[:,:,:,k] = frame\\n else:\\n frames = (0,k)\\n break\\n progress_callback(10/nF)\\n sys.stdout.write('.')\\n sys.stdout.flush()\\n print('\\\\n')\\n vr.release()\\n\\n if not frames:\\n frames = (0, nF-1)\\n\\n ## Compute spatial filters \\n vid = vid[:,:,:,frames[0]:frames[1]+1]\\n h, w, nC, nF = vid.shape\\n if scalevideo != 1:\\n h, w = int(scalevideo*h), int(scalevideo*w)\\n\\n print('Computing spatial filters\\\\n')\\n ht = maxSCFpyrHt(np.zeros((h,w)))\\n if pyrtype == 'octave':\\n filters = getFilters((h, w), np.power(2,np.arange(0,-ht-1,-1).astype(float)), 4)\\n print('Using octave bandwidth pyramid\\\\n') \\n elif pyrtype == 'halfOctave': \\n filters = getFilters((h, w), np.power(2,np.arange(0,-ht-0.5,-0.5).astype(float)), 8, twidth=0.75)\\n print('Using half octave bandwidth pyramid\\\\n')\\n elif pyrtype == 'smoothHalfOctave':\\n filters = getFiltersSmoothWindow((h, w), 8, filtersPerOctave = 2) \\n print('Using half octave pyramid with smooth window.\\\\n')\\n elif pyrtype == 'quarterOctave':\\n filters = getFiltersSmoothWindow((h, w), 8, filtersPerOctave = 4)\\n print('Using quarter octave pyramid.\\\\n')\\n else:\\n raise ValueError('Invalid Filter Types')\\n\\n croppedFilters, filtIDX = getFilterIDX(filters)\\n \\n ## Initialization of motion magnified luma component\\n magnifiedLumaFFT = np.zeros((h,w,nF),np.complex64)\\n\\n def buildLevel(im_dft,k):\\n return np.fft.ifft2(\\n np.fft.ifftshift(\\n np.multiply(croppedFilters[k][0], im_dft[filtIDX[k,0], filtIDX[k,1]])\\n )\\n )\\n\\n def reconLevel(im_dft, k):\\n return 2*(np.multiply(croppedFilters[k][0], np.fft.fftshift(np.fft.fft2(im_dft))))\\n\\n ## First compute phase differences from reference frame\\n numLevels = len(filters) \\n print('Moving video to Fourier domain\\\\n')\\n vidFFT = np.zeros((h,w,nF),dtype=np.complex64)\\n for k in range(0, nF):\\n originalFrame = vid[:,:,:,k].astype(np.float32)\\n originalFrame = cv2.cvtColor(originalFrame, cv2.COLOR_BGR2YUV)\\n tVid = cv2.resize(originalFrame[:,:,0], (w, h), 0, 0, cv2.INTER_CUBIC)\\n vidFFT[:,:,k] = np.fft.fftshift(np.fft.fft2(tVid))\\n sys.stdout.write('.')\\n sys.stdout.flush()\\n progress_callback(20/nF)\\n print('\\\\n')\\n\\n refFrame = 0\\n for level in range(1, numLevels-1):\\n ## Compute phases of level\\n # We assume that the video is mostly static\\n pyrRef = buildLevel(vidFFT[:,:,refFrame], level)\\n pyrRefPhaseOrig = np.divide(pyrRef, np.abs(pyrRef))\\n pyrRef = np.angle(pyrRef)\\n\\n delta = np.zeros((pyrRef.shape[0], pyrRef.shape[1] ,nF), np.float32)\\n print('Processing level {0} of {1}\\\\n'.format(level+1, numLevels))\\n\\n for frameIDX in range(0, nF):\\n filterResponse = buildLevel(vidFFT[:,:,frameIDX], level)\\n pyrCurrent = np.angle(filterResponse)\\n delta[:,:,frameIDX] = np.mod(np.pi+pyrCurrent-pyrRef,2*np.pi)-np.pi\\n \\n ## Temporal Filtering\\n print('Bandpassing phases\\\\n')\\n delta = temporalFilter(delta, fl/fs, fh/fs) \\n\\n ## Apply magnification\\n eps = 2.2204e-16\\n print('Applying magnification\\\\n')\\n for frameIDX in range(0, nF):\\n\\n phaseOfFrame = delta[:,:,frameIDX]\\n originalLevel = buildLevel(vidFFT[:,:,frameIDX], level)\\n ## Amplitude Weighted Blur \\n if (sigma != 0):\\n phaseOfFrame = AmplitudeWeightedBlur(phaseOfFrame, np.abs(originalLevel)+eps, sigma)\\n\\n # Increase phase variation\\n phaseOfFrame = magphase * phaseOfFrame\\n \\n if attenuateOtherFreq:\\n tempOrig = np.multiply(np.abs(originalLevel), pyrRefPhaseOrig)\\n else:\\n tempOrig = originalLevel\\n\\n tempTransformOut = np.multiply(np.exp(1j*phaseOfFrame), tempOrig)\\n\\n curLevelFrame = reconLevel(tempTransformOut, level)\\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] = \\\\\\n curLevelFrame + magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX]\\n \\n progress_callback(50/(numLevels-2))\\n\\n ## Add unmolested lowpass residual\\n level = len(filters)-1\\n for frameIDX in range(0, nF):\\n try:\\n lowpassFrame = np.multiply(vidFFT[filtIDX[level, 0], filtIDX[level, 1] ,frameIDX], np.power(croppedFilters[-1][0], 2))\\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] = \\\\\\n magnifiedLumaFFT[filtIDX[level, 0], filtIDX[level, 1], frameIDX] + lowpassFrame\\n except IndexError:\\n print(\\\"IndexError\\\")\\n progress_callback(10/nF)\\n\\n for k in range(0, nF):\\n magnifiedLuma = np.fft.ifft2(np.fft.ifftshift(magnifiedLumaFFT[:,:,k])).real\\n originalFrame = cv2.cvtColor(vid[:,:,:,k].astype(np.float32), cv2.COLOR_BGR2YUV)\\n originalFrame = cv2.resize(originalFrame, (w, h), 0, 0, cv2.INTER_CUBIC)\\n originalFrame[:,:,0] = magnifiedLuma\\n originalFrame = cv2.cvtColor(originalFrame, cv2.COLOR_YUV2BGR)\\n originalFrame = cv2.convertScaleAbs(originalFrame)\\n yield originalFrame\\n progress_callback(10/nF)\",\n \"def read(f, normalized=False):\\r\\n a = pydub.AudioSegment.from_mp3(f)\\r\\n y = np.array(a.get_array_of_samples())\\r\\n if a.channels == 2:\\r\\n y = y.reshape((-1, 2))\\r\\n if normalized:\\r\\n return a.frame_rate, np.float32(y) / 2**15\\r\\n else:\\r\\n return a.frame_rate, y\",\n \"def __init__(self, pattern='/graphics/projects/scratch/wieschol/sync-data/*/*_noaudio.low.mp4',\\n samples=10, shuffle=True, max_pos_dist=10, min_neg_dist=20, min_pos_dist=5):\\n self.files = glob.glob(pattern)\\n self.shuffle = shuffle\\n self.max_pos_dist = max_pos_dist\\n self.min_pos_dist = min_pos_dist\\n self.min_neg_dist = min_neg_dist\\n self.samples = samples\",\n \"def __init__(self, renderer: sdl2.render.SDL_Renderer, filepath: str,\\n sample_rate: int, loop: bool):\\n self.textures: List[sdl2.render.SDL_Texture] = []\\n for filename in sorted(os.listdir(filepath)):\\n self.textures.append(\\n texture_from_bmp(renderer, os.path.join(filepath, filename)))\\n\\n # Number of times to update current_frame per second\\n self.sample_rate = sample_rate\\n self.loop = loop\\n\\n # Index into textures list\\n self.current_frame = 0\",\n \"def get_Metadata_freq(metafile_science):\\n\\n mslist_file = open(metafile_science, 'r')\\n LINES = mslist_file.readlines()\\n mslist_file.close()\\n\\n frame = 'Frame'\\n \\n for i in range(len(LINES)):\\n line = LINES[i]\\n if line.find(frame) >=0:\\n next_line = LINES[i+1]\\n TOKS = next_line.split()\\n chan_width = float(TOKS[10])*1000. # convert kHz to Hz\\n cfreq = TOKS[12] #MHz\\n nchan = TOKS[7]\\n\\n return chan_width, cfreq, nchan\",\n \"def get_movie_data(files: list) -> list:\\n pass\",\n \"def readDriverFile(self, input_file):\\n\\n\\n fid = open(self.basePath + input_file,'r')\\n\\n # Line 1\\n line = fid.readline()\\n l_input = line.split('!')\\n mshfile = l_input[0].rstrip()\\n\\n # Line 2\\n line = fid.readline()\\n l_input = line.split('!')\\n obsfile = l_input[0].rstrip()\\n\\n # Line 3\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input=='null':\\n topofile = []\\n\\n else:\\n topofile = l_input[0].rstrip()\\n\\n\\n # Line 4\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n mstart = float(l_input[1])\\n\\n else:\\n mstart = l_input[0].rstrip()\\n\\n # Line 5\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n mref = float(l_input[1])\\n\\n else:\\n mref = l_input[0].rstrip()\\n\\n # Line 6\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n staticInput = float(l_input[1])\\n\\n elif l_input[0]=='DEFAULT':\\n staticInput = None\\n\\n else:\\n staticInput = l_input[0].rstrip()\\n\\n\\n # Line 7\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input=='DEFAULT':\\n magfile = []\\n\\n else:\\n magfile = l_input[0].rstrip()\\n\\n # Line 8\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input=='DEFAULT':\\n wgtfile = []\\n\\n else:\\n wgtfile = l_input[0].rstrip()\\n\\n # Line 9\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n chi = float(l_input[0])\\n\\n # Line 10\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n val = np.array(l_input[0:4])\\n alphas = val.astype(np.float)\\n\\n # Line 11\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n val = np.array(l_input[1:3])\\n bounds = val.astype(np.float)\\n\\n else:\\n bounds = l_input[0].rstrip()\\n\\n # Line 12\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n val = np.array(l_input[1:6])\\n lpnorms = val.astype(np.float)\\n\\n else:\\n lpnorms = l_input[0].rstrip()\\n\\n # Line 13\\n line = fid.readline()\\n l_input = re.split('[!\\\\s]',line)\\n if l_input[0]=='VALUE':\\n val = np.array(l_input[1:3])\\n eps = val.astype(np.float)\\n\\n else:\\n eps = [None,None]\\n\\n self.mshfile = mshfile\\n self.obsfile = obsfile\\n self.topofile = topofile\\n self.mstart = mstart\\n self._mrefInput = mref\\n self._staticInput = staticInput\\n self.magfile = magfile\\n self.wgtfile = wgtfile\\n self.chi = chi\\n self.alphas = alphas\\n self.bounds = bounds\\n self.lpnorms = lpnorms\\n self.eps = eps\",\n \"def get_video_frame_rate(filename):\\n clip = VideoFileClip(filename)\\n frame_rate = clip.fps\\n clip.close()\\n return frame_rate\",\n \"def audioRead(path):\\n data, samplerate = sf.read(path)\\n frames = data.shape[0]\\n channels = len(data.shape)\\n duration = 1/samplerate*frames\\n return data, samplerate, path, duration, frames, channels\",\n \"def INPUT_Periods_file(input):\\n \\n global events\\n \\n tb = 3600\\n ta = 3600\\n \\n Period = input['min_date'].split('T')[0] + '_' + \\\\\\n input['max_date'].split('T')[0] + '_' + \\\\\\n str(input['min_mag']) + '_' + str(input['max_mag'])\\n eventpath = os.path.join(input['datapath'], Period)\\n \\n len_events = len(events)\\n \\n input_period = open(os.path.join(os.getcwd(), 'INPUT-Periods'), 'a+')\\n\\n for i in range(0, len_events):\\n \\n str_event = str(events[i]['datetime']-tb) + '_' + \\\\\\n str(events[i]['datetime']+ta) + '_' + \\\\\\n str(events[i]['magnitude'] - 0.01) + '_' + \\\\\\n str(events[i]['magnitude'] + 0.01) + '\\\\n'\\n input_period.writelines(str_event)\\n \\n input_period.close()\\n \\n print '************************************************************' \\n print 'New INPUT-Periods file is generated in your folder.'\\n print 'Now, you could run the program again based on your desired event :)' \\n print '************************************************************'\\n \\n sys.exit()\",\n \"def f2gif(path,fps):\\n print(\\\"==============================================\\\")\\n print(\\\"Convert file to GIF!\\\")\\n pathout = path[:-4]+'_'+str(fps)+'.gif'\\n if path.endswith('.tif'): \\n# import tifffile\\n im = tifffile.imread(path)\\n nFrames, h,w = im.shape\\n dur=1/fps\\n clip = []\\n for i in range(nFrames):\\n fr = cv2.cvtColor(im[i],cv2.COLOR_GRAY2RGB)\\n clip.append(mp.ImageClip(fr).set_duration(dur))\\n video = mp.concatenate_videoclips(clip, method=\\\"compose\\\",ismask=False)#ismask=True to make grayscale\\n\\n else:\\n video = mp.VideoFileClip(path)\\n fpsIn = int(video.fps)\\n if fps != fpsIn:\\n print(\\\"Conflict in fps! \\\\n\\\", \\\"[0] Use fps of input file;\\\\n\\\", \\\"[1] Use desired fps w/o speedup;\\\\n\\\",\\n \\\"[2] Use desired fps w/ speedup:\\\")\\n k = input('Input your selection: ')\\n if k == 2:\\n sf = fps/fpsIn\\n video =video.fx(mp.vfx.speedx, sf)# Not working when sf<1\\n elif k == 0:\\n fps = fpsIn\\n\\n video.write_gif(pathout,fps=fps)\\n video.reader.close()# To fix handel error problem\\n# if path.endswith('.gif'):\\n# clip.write_videofile(pathout,fps=fps,codec='libx264', bitrate='32 M',preset='ultrafast')\\n print(\\\"==============================================\\\")\\n print(\\\"MP4 convertion Done!\\\")\",\n \"def read_frame(location, channels, start_time=None, \\n end_time=None, duration=None):\\n\\n if end_time and duration:\\n raise ValueError(\\\"end time and duration are mutually exclusive\\\")\\n \\n if type(location) is list:\\n locations = location\\n else:\\n locations = [location]\\n\\n cum_cache = lal.Cache()\\n for source in locations:\\n dir_name, file_name = os.path.split(source)\\n base_name, file_extension = os.path.splitext(file_name)\\n \\n if file_extension == \\\".lcf\\\" or file_extension == \\\".cache\\\":\\n cache = lal.CacheImport(source)\\n elif file_extension == \\\".gwf\\\": \\n cache = lalframe.FrOpen(dir_name, file_name).cache\\n else:\\n raise TypeError(\\\"Invalid location name\\\")\\n \\n cum_cache = lal.CacheMerge(cum_cache, cache)\\n \\n stream = lalframe.FrStreamCacheOpen(cum_cache)\\n \\n stream.mode = lalframe.FR_STREAM_VERBOSE_MODE\\n lalframe.FrSetMode(stream.mode | lalframe.FR_STREAM_CHECKSUM_MODE,\\n stream)\\n\\n # determine duration of data\\n if type(channels) is list:\\n first_channel = channels[0]\\n else:\\n first_channel = channels\\n data_length = lalframe.FrStreamGetVectorLength(first_channel, stream)\\n channel_type = lalframe.FrStreamGetTimeSeriesType(first_channel, stream)\\n create_series_func = _fr_type_map[channel_type][2]\\n get_series_metadata_func = _fr_type_map[channel_type][3]\\n series = create_series_func(first_channel, stream.epoch, 0, 0,\\n lal.ADCCountUnit, 0)\\n get_series_metadata_func(series, stream)\\n data_duration = data_length * series.deltaT\\n\\n if start_time is None:\\n start_time = stream.epoch*1\\n if end_time is None:\\n end_time = start_time + data_duration\\n\\n if type(start_time) is not lal.LIGOTimeGPS:\\n start_time = lal.LIGOTimeGPS(start_time)\\n if type(end_time) is not lal.LIGOTimeGPS:\\n end_time = lal.LIGOTimeGPS(end_time)\\n\\n if duration is None:\\n duration = float(end_time - start_time)\\n else:\\n duration = float(duration)\\n\\n # lalframe behaves dangerously with invalid duration so catch it here\\n if duration <= 0:\\n raise ValueError(\\\"Negative or null duration\\\")\\n #if duration > data_duration:\\n # raise ValueError(\\\"Requested duration longer than available data\\\")\\n\\n if type(channels) is list:\\n all_data = []\\n for channel in channels:\\n channel_data = _read_channel(channel, stream, start_time, duration)\\n lalframe.FrStreamSeek(stream, start_time)\\n all_data.append(channel_data)\\n return all_data\\n else:\\n return _read_channel(channels, stream, start_time, duration)\",\n \"def rec_one_shot(self, sec, file_name=None):\\n self.__open_noncallback_stream()\\n frames = []\\n for i in range(int(self.RATE / self.CHUNK * sec)):\\n data = self.stream.read(self.CHUNK)\\n data = np.fromstring(data, dtype=np.int16)\\n frames.append(data)\\n self.stream.stop_stream()\\n if file_name is not None:\\n with wave.open(file_name, 'wb') as wav_file:\\n wav_file.setnchannels(self.CHANNELS)\\n wav_file.setsampwidth(self.recorder.get_sample_size(self.FORMAT))\\n wav_file.setframerate(self.RATE)\\n wav_file.writeframes(b''.join(frames))\\n frame = np.concatenate(frames, 0)\\n self.stop_streaming()\\n return frame\",\n \"def read_all_files():\\n paths = get_all_recording_paths()\\n\\n return read_by_paths(paths)\",\n \"def stream_timelapse(path):\\n parts = path.split('.')[0].split('_')\\n count = int(parts[2])\\n filename = parts[0] + '_{0:03d}_{1:03d}.jpg'\\n for i in range(count):\\n frame = open(filename.format(i, count), 'rb').read()\\n yield b'--frame\\\\r\\\\nContent-Type: image/jpeg\\\\r\\\\nContent-Length: ' + \\\\\\n str(len(frame)).encode() + b'\\\\r\\\\n\\\\r\\\\n' + frame + b'\\\\r\\\\n'\\n time.sleep(0.5)\",\n \"def t1_loadNFile(self):\\n print \\\"noisubspectrumFile\\\"\\n filename = tkFileDialog.askopenfilename()\\n filename = self.filenameparser(filename)\\n self.t1_noifilename = filename\",\n \"def _default_specs(self):\\n # Spectrometer specs\\n self.model = \\\"Flame-S\\\" # Spectrometer model\\n self.fov = 1 # Field of view fo spectrometer (radius of FOV)\\n self.ILS = None # Number array holding instrument line shape (possibly don't hold this here?)\\n self.fiber_diameter = 1e-3 # Diameter of optical fiber\\n self.pix_num = 2048 # Number of pixels\\n self.bit_depth = 16 # Bit depth of spectrometer detector\\n\\n # File information\\n self.file_ext = '.npy' # Spectra saved as numpy array\\n self.file_ss = '{}ss' # Shutter speed format spec\\n self.file_ss_loc = 1 # Shutter speed location in filename\\n self.file_spec_type = {'meas': 'Plume', 'dark': 'Dark', 'cal': 'ppmm', 'clear': 'Clear'}\\n self.file_datestr = \\\"%Y-%m-%dT%H%M%S\\\" # Date/time format spec in filename\\n self.file_datestr_loc = 0\\n self.plume_params_file = 'plume_params.txt'\\n self.plume_speed_id = 'plume_speed='\\n self.plume_dist_id = 'plume_distance='\\n\\n # File which flags that a scan is complete. The file will be empty, just its presence is required\\n self.scan_complete = 'complete.txt'\\n\\n # Acquisition settings\\n self.start_int_time = 100 # Starting integration time\\n self.start_coadd = 1 # Number of spectra to coadd\\n self.framerate = 1 # Framerate of acquisitions (Hz)\\n self.wavelengths = None # Wavelengths (nm)\\n self.spectrum = None # Spectrum\\n self.spectrum_filename = None # Filename for spectrum\\n\\n self.auto_int = True # Bool for requesting automated integration time adjustment\\n self.min_saturation = 0.6 # Minimum saturation accepted before adjusting shutter speed (if auto_ss is True)\\n self.max_saturation = 0.9 # Maximum saturation accepted before adjusting shutter speed (if auto_ss is True)\\n self.saturation_range = [300, 335] # Range of wavelengths used in checking integration time\\n self.saturation_pixels = 2 # Number of pixels to check\\n\\n # Predefined list of integration times for automatic exposure adjustment\\n self.int_list = np.concatenate((np.arange(0.1, 0.5, 0.05),\\n np.arange(0.5, 1, 0.1),\\n np.arange(1, 5, 0.5),\\n np.arange(5, 10, 1),\\n np.arange(10, 50, 5),\\n np.arange(50, 100, 10),\\n np.arange(100, 500, 50),\\n np.arange(500, 1000, 100),\\n np.arange(10 ** 3, 10 ** 4, 500),\\n np.array([10 ** 4])))\",\n \"def open_read_files(answer_files, answers):\\r\\n \\\"\\\"\\\"And designates each file to a variable in answers\\\"\\\"\\\"\\r\\n count = 0\\r\\n s = 0\\r\\n answer_files2 = []\\r\\n for file in answer_files[:]: # Used [:] to get all file_names in answer_files\\r\\n ans = open(file, mode='r')\\r\\n print(f\\\"Opening {ans.name}\\\")\\r\\n time.sleep(s)\\r\\n answers[count] = ans\\r\\n count += 1\\r\\n if ans.closed == False: # Section for checking if files are closed\\r\\n print(f\\\"Closing {ans.name}\\\")\\r\\n ans.close()\\r\\n answer_files2.append(ans.name)\\r\\n answer_files.remove(ans.name)\\r\\n time.sleep(s)\\r\\n return answer_files2, answers\",\n \"def file_name_list():\\n file_names = []\\n hour = h1\\n minute = m1\\n while hour * 60 + minute <= h2 * 60 + m2:\\n file_name = generate_file_name(hour, minute)\\n file_names.append(file_name)\\n hour, minute = next_time(hour, minute)\\n return file_names\",\n \"def get_parameters_fastcharge(filename, source_directory):\\n filename = filename.rsplit('.', 1)[0]\\n strname = filename.rsplit('_CH', 1)[0]\\n\\n # Get date\\n date = re.match(r'(\\\\d+)-(\\\\d+)-(\\\\d+)', strname)\\n if date is None:\\n warnings.warn(\\\"Date could not be parsed from {}\\\".format(filename))\\n else:\\n date = date.group()\\n\\n # Get channel number\\n chno = re.findall(r'(CH+\\\\d*)', filename)\\n if chno:\\n chno = chno[0]\\n else:\\n chno = None\\n warnings.warn(\\\"Channel number could not be parsed from {}\\\".format(filename))\\n\\n try:\\n param_str = strname.rsplit(date + '_', 1)[1]\\n param = param_str.replace('_', '.')\\n\\n if param.find('.') < 0:\\n param = find_meta(filename, source_directory)\\n\\n q1 = re.findall(r'(\\\\d+per)', param)[0].split('per')[0]\\n cc1 = re.findall(r'(\\\\d*\\\\.?\\\\d+C)', param.split(q1 + 'per.')[0])[0]\\n cc2 = re.findall(r'(\\\\d*\\\\.?\\\\d+C)', param.split(q1 + 'per.')[1])[0]\\n protocol = cc1+'('+q1+'%)-'+cc2\\n except Exception as e:\\n warnings.warn(\\\"Failed to parse protocol for {}: {}\\\".format(filename, e))\\n protocol = None\\n\\n return date, chno, strname, protocol\",\n \"def test_get_fasta_fps(self):\\r\\n\\r\\n file_basenames = [basename(self.fasta2_fp), basename(self.fasta3_fp),\\r\\n basename(self.fasta1_fp)]\\r\\n\\r\\n actual_fastas = get_fasta_fps(self.input_dir, file_basenames)\\r\\n\\r\\n expected_fasta = [self.fasta2_fp, self.fasta3_fp, self.fasta1_fp]\\r\\n\\r\\n self.assertEqual(actual_fastas, expected_fasta)\",\n \"def get_configfile(files,\\n seasoncyc_base=None,\\n seasoncyc_sim=None,\\n base_id='NCEP',\\n sim_id='NCEP',\\n timewin=1,\\n varname='slp',\\n seacyc=False,\\n cycsmooth=91,\\n nanalog=20,\\n seasonwin=30,\\n distfun='rms',\\n outformat='.txt',\\n period=[\\\"1973-01-01\\\", \\\"2012-12-31\\\"],\\n bbox=\\\"-180.0,-90.0,180,90.0\\\",\\n calccor=True,\\n silent=False):\\n from datetime import datetime as dt\\n\\n date_stamp = dt.strftime(dt.now(), format='%Y%m%d_%H%M%S')\\n LOGGER.info('start configuration file preparation at: %s' % (date_stamp))\\n\\n # convert True/False to Fortran syntax\\n seacyc = str(seacyc)\\n calccor = str(calccor)\\n silent = str(silent)\\n\\n # write stuff to configuration file\\n # NB: if order or format or number changes, need to edit wps_analogs_viewer.py\\n # and template_analogviewer.html where these scripts read in the config\\n # params\\n config_file = \\\"config.txt\\\"\\n\\n config = open(config_file, \\\"w\\\")\\n\\n config.write(\\n '!Configuration file for CASTf90 analogs processes deployed in flyingpigeon\\\\n')\\n config.write('!Created : %s \\\\n' % (date_stamp))\\n config.write('!Version : 0.1.5 \\\\n')\\n config.write('&FILES \\\\n')\\n config.write(' my_files%archivefile = \\\"{file}\\\" \\\\n'.format(\\n file=os.path.relpath(files[0])))\\n config.write(' my_files%simulationfile = \\\"{file}\\\" \\\\n'.format(\\n file=os.path.relpath(files[1])))\\n config.write(' my_files%outputfile = \\\"{file}\\\" \\\\n'.format(\\n file=os.path.relpath(files[2])))\\n\\n if seacyc is not 'False':\\n config.write(' my_files%seacycfilebase = \\\"{file}\\\" \\\\n'.format(\\n file=os.path.relpath(seasoncyc_base)))\\n config.write(' my_files%seacycfilesim = \\\"{file}\\\" \\\\n'.format(\\n file=os.path.relpath(seasoncyc_sim)))\\n\\n config.write('/ \\\\n')\\n config.write('&PARAM \\\\n')\\n config.write(' my_params%timewin = {timewin} \\\\n'.format(timewin=timewin))\\n config.write(' my_params%varname = \\\"{varname}\\\" \\\\n'.format(varname=varname))\\n config.write(' my_params%seacyc = .{seacyc}. \\\\n'.format(\\n seacyc=seacyc.upper()))\\n config.write(' my_params%cycsmooth = {cycsmooth} \\\\n'.format(\\n cycsmooth=cycsmooth))\\n config.write(' my_params%nanalog = {nanalog} \\\\n'.format(nanalog=nanalog))\\n config.write(' my_params%seasonwin = {seasonwin} \\\\n'.format(\\n seasonwin=seasonwin))\\n config.write(' my_params%distfun = \\\"{distfun}\\\" \\\\n'.format(distfun=distfun))\\n config.write(' my_params%calccor = .{calccor}. \\\\n'.format(\\n calccor=calccor.upper()))\\n config.write(' my_params%oformat = \\\"{outformat}\\\" \\\\n'.format(\\n outformat=outformat)) # \\\".txt\\\" # ! if equals \\\".nc\\\"\\n config.write(' my_params%silent = .{silent}.\\\\n'.format(\\n silent=silent.upper()))\\n config.write('/\\\\n')\\n config.write('&ATTS\\\\n')\\n config.write(' my_atts%simsource = \\\"{sim_id}\\\" \\\\n'.format(sim_id=sim_id)) # model name\\n config.write(\\n ' my_atts%predictorvar = \\\"{varname}\\\" \\\\n'.format(varname=varname))\\n config.write(' my_atts%archisource = \\\"{base_id}\\\" \\\\n'.format(base_id=base_id))\\n config.write(' my_atts%archiperiod = \\\"{start},{end}\\\" \\\\n'.format(\\n start=period[0], end=period[1]))\\n config.write(' my_atts%predictordom = \\\"{bbox}\\\" \\\\n'.format(bbox=bbox))\\n config.write('/\\\\n')\\n\\n config.close()\\n return config_file\",\n \"def open_frame(path,number):\\n num=str(number).zfill(3) #Zero filling\\n name = glob.glob(path+\\\"/*\\\"+num+\\\"*\\\")\\n if len(name)==0:\\n name = glob.glob(path+\\\"/\\\"+str(number)+\\\".png\\\")\\n if len(name)>1:\\n print \\\"too many matches \\\",len(name),\\\" found\\\"\\n name = name[0]\\n img = Image.open(name)\\n img = np.asarray(img)\\n img.setflags(write=1)\\n return img\",\n \"def get_audio(name, n):\\n audio_path = os.path.join(args.input_folder, name, \\\"audio.ogg\\\")\\n if not os.path.exists(audio_path):\\n ## Some folders have multiple .ogg files, so we need to first combine them into one file. Example:\\n ## |── Universe\\n ## │ ├── aligned.swc\\n ## │ ├── audio1.ogg\\n ## │ ├── audio2.ogg\\n ## │ ├── audio3.ogg\\n ## │ ├── audio4.ogg\\n ## │ ├── audiometa.txt\\n ## │ ├── info.json\\n ## │ ├── wiki.html\\n ## │ ├── wiki.txt\\n ## │ └── wiki.xml\\n\\n multiple_ogg_files = []\\n for i in range(1, 5):\\n path = os.path.join(args.input_folder, name, \\\"audio\\\" + str(i) + \\\".ogg\\\")\\n if os.path.exists(path):\\n multiple_ogg_files.append(path)\\n else:\\n break\\n if len(multiple_ogg_files) == 0:\\n return\\n elif len(multiple_ogg_files) == 1:\\n os.system(\\\"cp \\\\\\\"\\\" + multiple_ogg_files[0] + \\\"\\\\\\\" \\\\\\\"\\\" + audio_path + \\\"\\\\\\\"\\\")\\n else:\\n tmp_file_name = \\\"ffmeg_inputs.txt\\\"\\n print(\\\"tmp_file_name=\\\", tmp_file_name)\\n with open(tmp_file_name, \\\"w\\\", encoding=\\\"utf-8\\\") as tmp_file:\\n for path in multiple_ogg_files:\\n tmp_file.write(\\\"file '\\\" + path + \\\"'\\\\n\\\")\\n cmd = \\\"ffmpeg -f concat -i \\\\\\\"\\\" + tmp_file_name + \\\"\\\\\\\" -c copy \\\\\\\"\\\" + audio_path + \\\"\\\\\\\"\\\"\\n print(cmd)\\n os.system(cmd)\\n\\n output_audio_path = args.destination_folder + \\\"/audio/\\\" + str(n) + \\\".ogg\\\"\\n os.system(\\\"cp \\\\\\\"\\\" + audio_path + \\\"\\\\\\\" \\\" + output_audio_path)\",\n \"def get_data(path):\\n if path.endswith('.mp3'):\\n path = prepare_file(path, path.rstrip('mp3')+'wav')\\n x, sr = librosa.load(path, duration=30)\\n\\n else:\\n x, sr = librosa.load(path, duration=30)\\n directory, file_name = os.path.split(path)\\n return x, sr, file_name\",\n \"def read_cospectrum(path,d):\\r\\n spec = []\\r\\n timeseries = []\\r\\n for i in range(len(d)):\\r\\n filename = path + d[i]\\r\\n\\r\\n with open(filename, \\\"r\\\") as f:\\r\\n reader = csv.reader(f,delimiter=',')\\r\\n ct=1\\r\\n for row in reader:\\r\\n if ct==6:\\r\\n Hz = float(row[0].split('_')[-1])\\r\\n elif ct==7:\\r\\n height = float(row[0].split('_')[-1])\\r\\n elif ct==8:\\r\\n ws = float(row[0].split('_')[-1])\\r\\n elif ct==9:\\r\\n avg_period = float(row[0].split('_')[-1])\\r\\n elif ct==13:\\r\\n header = row\\r\\n elif ct>13:\\r\\n break\\r\\n ct+=1\\r\\n \\r\\n meta = [Hz,height,ws,avg_period]\\r\\n \\r\\n thisspec = np.genfromtxt(filename,delimiter=',',skip_header=13)\\r\\n spec.append(thisspec)\\r\\n thistime = re.findall('\\\\d{8}-\\\\d{4}',filename)[0]\\r\\n thisdate = datetime.strptime(thistime,'%Y%m%d-%H%M')\\r\\n timeseries.append(thisdate) \\r\\n \\r\\n return spec, timeseries, header, meta\",\n \"def getFileList(self):\\n sid = 86400 # change to 3600 for hour-by-hour\\n uDays = range(sid*(int(self.uStart)/sid),sid+(sid*(int(self.uStop)/sid)),sid)\\n fileList = []\\n sep = os.path.sep\\n for d in uDays:\\n s = unixTimeToString(d)\\n ymdPath = 'year' + s[0:4] + sep + 'month' + s[5:7] + sep + 'day' + s[8:10]\\n dirname = self.basePath + sep + ymdPath + sep + self.sensor + sep + 'padhist'\\n pattern = '*' + self.sensor + '_hstv*.mat'\\n nameList = glob.glob1(dirname,pattern)\\n for name in nameList:\\n uTime = stringTimeToUnix(name[0:13] + '_00_00.000')\\n if ( self.uStart <= uTime <= self.uStop ):\\n #print 'IN: %s' % unixTimeToString(uTime)\\n fileList.append(dirname + sep + name)\\n fileList.sort()\\n self.fileList = fileList\",\n \"def getVideoFrames(videoFilePath, startFrameNumber=-1, endFrameNumber=-1):\\n frames=[]\\n vidcap = cv2.VideoCapture(videoFilePath)\\n fps=vidcap.get(cv2.CAP_PROP_FPS)\\n totalFrame=vidcap.get(cv2.CAP_PROP_FRAME_COUNT)\\n if startFrameNumber==-1:\\n startFrameNumber = 0\\n if endFrameNumber == -1:\\n endFrameNumber = totalFrame - 1\\n success,image = vidcap.read()\\n count = 0\\n success = True\\n while success:\\n image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\\n image = color.rgb2yiq(image).astype(np.float32)\\n \\n if count<startFrameNumber:\\n success,image = vidcap.read()\\n count+=1\\n continue\\n elif count>=endFrameNumber:\\n break\\n else: \\n frames.append(image)\\n success,image = vidcap.read()\\n count += 1\\n frames=np.array(frames)\\n \\n return fps, frames\",\n \"def read_data(self):\\n self.days = [0, 2, 3, 5, 6, 8, 9, 11, 13, 14]\\n path = '../data/'\\n data = []\\n for day in self.days:\\n filename = path + 'spectrum_day{}.txt'.format(day)\\n data.append(read_file(filename))\\n return data\",\n \"def fileSetup(path):\\n past_fnames = next(os.walk(path))[2]\\n f_nums = []\\n for f in past_fnames:\\n if f.startswith('semi'):\\n f_nums.append(int(f[4:8]))\\n\\n if not f_nums:\\n now_fname = '/semi0001.h264'\\n else:\\n now_fname = '/semi%04d.h264' % (max(f_nums)+1, )\\n\\n now_fname = path+now_fname\\n print 'Current filename: %s' % now_fname\\n\\n return now_fname\",\n \"def fix_file(file_path: str, output_path_fixed: str, target_rate: int=16000,\\n channels: int=1, output_path: str=None, min_duration: int=None,\\n verbose_level: int=0):\\n file_name = file_path.split(os.sep)[-1]\\n new_file_path = output_path_fixed + os.sep + file_name\\n\\n try:\\n # Get the audio length\\n out = syscommand.system('soxi -D ' + file_path)\\n duration = float(out)\\n # Get the number of channels\\n out = syscommand.system('soxi -c ' + file_path)\\n current_n_channels = int(out)\\n # Get the current rate\\n out = syscommand.system('soxi -r ' + file_path)\\n current_rate = int(out)\\n if min_duration is not None and duration < min_duration:\\n raise Exception(\\\"Minimum length not satisfied\\\")\\n except Exception as err:\\n if str(verbose_level) != '0':\\n print(err)\\n return None, file_path\\n\\n if current_rate != target_rate and current_n_channels != channels:\\n speed = float(current_rate) / float(target_rate)\\n cmd = 'sox -V{} -r 16k {} {} channels 1 ' \\\\\\n 'speed {}'.format(verbose_level, file_path, new_file_path,\\n speed)\\n if str(verbose_level) == '2':\\n print(cmd)\\n os.system(cmd)\\n return new_file_path, file_path\\n elif current_rate != target_rate:\\n speed = float(current_rate) / float(target_rate)\\n cmd = 'sox -V{} -r 16k {} {} ' \\\\\\n 'speed {}'.format(verbose_level, file_path, new_file_path,\\n speed)\\n if str(verbose_level) == '2':\\n print(cmd)\\n os.system(cmd)\\n return new_file_path, file_path\\n elif current_n_channels != channels:\\n cmd = 'sox -V{} {} {} channels 1'.format(verbose_level, file_path,\\n new_file_path)\\n if str(verbose_level) == '2':\\n print(cmd)\\n os.system(cmd)\\n return new_file_path, file_path\\n\\n # Copy file if output path were provided and the file is not there\\n if output_path is not None:\\n copyfile(file_path, new_file_path)\\n return file_path, file_path\",\n \"def getConfig():\\n\\n config = rFile(\\\"/var/www/html/config.txt\\\").split()\\n f = int(config[0])\\n mode = config[1]\\n\\n if (f in DABchannels and (mode == \\\"explore\\\" or mode == \\\"monitor\\\")):\\n return f, mode\\n else:\\n return 227360000, \\\"explore\\\" # Kamzik - Bratislava\",\n \"def t9_loadFile(self):\\n print \\\"subspectrumFile\\\"\\n filename = tkFileDialog.askopenfilename()\\n filename = \\\"SubSpectrumData/\\\" + self.filenameparser(filename)\\n orgin_file = self.filenameparser(filename)\\n self.t9_filename = filename\\n self.t9_orginfilename = orgin_file\",\n \"def read_recording_names(feature_files):\\n all_recording_names = {}\\n for feature_file in feature_files:\\n in_dir = '/'.join(feature_file.split('/')[:-1])\\n name = \\\"recordings.list\\\"\\n path = os.path.join(in_dir, name)\\n if not os.path.exists(path):\\n return None\\n else:\\n with open(path, 'r') as f:\\n recording_names = f.readlines()\\n recording_names = [recording_name.strip() for recording_name in recording_names]\\n # feature file at this position is basically incorrect. it takes the name of the hdf5 file as a key in\\n # the dictionary. the directory would be more intuitive. however, cmd_args.input is used later on to\\n # access the names which is why this works\\n all_recording_names.update({feature_file: recording_names})\\n\\n return all_recording_names\",\n \"def getFileList(self):\\n print 'getting fileList ...',\\n sid = 86400 # change to 3600 for hour-by-hour\\n uDays = range(sid*(int(self.uStart)/sid),sid+(sid*(int(self.uStop)/sid)),sid)\\n fileList = []\\n sep = os.path.sep\\n for d in uDays:\\n s = unixTimeToString(d)\\n ymdPath = 'year' + s[0:4] + sep + 'month' + s[5:7] + sep + 'day' + s[8:10]\\n dirname = self.basePath + sep + ymdPath + sep + self.subDir\\n pattern = '*' + self.sensor\\n nameList = glob.glob1(dirname,pattern)\\n for name in nameList:\\n ufStart = stringTimeToUnix(name[0:23])\\n ufStop = stringTimeToUnix(name[24:47])\\n if ( ufStart <= self.uStart <= ufStop ) or ( self.uStart <= ufStart <= self.uStop ) or ( ufStart <= self.uStop <= ufStop ):\\n #print 'IN: %s' % unixTimeToString(uTime)\\n fileList.append(dirname + sep + name)\\n## else:\\n## print 'OUT:\\\\n%s\\\\n%s\\\\n%s' % (unixTimeToString(ufStart),unixTimeToString(self.uStart),unixTimeToString(ufStop))\\n fileList.sort()\\n self.fileList = fileList\\n print 'done'\",\n \"def _load(self, filepath):\\n import subprocess as sp\\n command = ['ffmpeg',\\n '-i', filepath,\\n '-f', 's16le',\\n '-acodec', 'pcm_s16le',\\n '-ac', '1'] # channels: 2 for stereo, 1 for mono\\n if self.sampling_rate != SAMPLING_RATE:\\n command.extend(['-ar', str(self.sampling_rate)])\\n command.append('-')\\n # 30s at 44.1 kHz ~= 1.3e6\\n proc = sp.run(command, stdout=sp.PIPE, bufsize=10**7, stderr=sp.DEVNULL, check=True)\\n\\n return np.fromstring(proc.stdout, dtype=\\\"int16\\\")\",\n \"def video_audio_files(video_name, path_curr_vid, path_current_frames):\\n video_file = f\\\"{path_curr_vid}{video_name}\\\"\\n audio_file = f\\\"{path_current_frames}{video_name.replace(VIDEO_EXT,AUDIO_EXT)}\\\"\\n return video_file, audio_file\",\n \"def inputwav(filename):\\n data, sr = sf.read(filename)\\n print('Decoding \\\"'+filename+'\\\"...')\\n print('Sample rate is '+str(sr)+'...')\\n try:\\n ch=len(data[0,])\\n except:\\n ch=1\\n print('File contains '+str(ch)+' audio channel(s)...')\\n #Reshape the data so other functions can interpret the array if mono.\\n #basically transposing the data\\n if ch==1:\\n data=data.reshape(-1,1)\\n n=len(data)\\n #This prevents log(data) producing nan when data is 0\\n data[np.where(data==0)]=0.00001\\n #convert to dB\\n data_dB=20*np.log10(abs(data))\\n return n, data,data_dB,sr, ch\",\n \"def param_info():\\n\\n\\tgizmo_names = syn.getGizmoNames()\\n\\n\\tfor gizmo in gizmo_names:\\n\\t\\tparams = syn.getParameterNames(gizmo)\\n\\t#doesnt get all parameters from gizmos i.e. WaveFreq\\n\\n\\t# get all info on the 'WaveFreq' parameter\\n\\tGIZMO = 'aStim2'\\n\\tPARAMETER = 'WaveFreq'\\n\\n\\t# info = syn.getParameterInfo(GIZMO, PARAMETER)\\n\\t#\\n\\t# # get the array size (should be 100)\\n\\t# sz = syn.getParameterSize(GIZMO, PARAMETER)\\n\\t#\\n\\t# # write values 1 to 50 in second half of buffer\\n\\t# result = syn.setParameterValues(GIZMO, PARAMETER, np.arange(1, 51), 50)\\n\\t#\\n\\t# # read all values from buffer\\n\\t# syn.getParameterValues(GIZMO, PARAMETER, sz)\\n\\t#\\n\\t# # get all info on the 'Go' parameter\\n\\t# PARAMETER = 'Go'\\n\\t# info = syn.getParameterInfo(GIZMO, PARAMETER)\\n\\t#\\n\\t# # flip the switch\\n\\t# result = syn.setParameterValue(GIZMO, PARAMETER, 1)\\n\\t#\\n\\t# # check the value\\n\\tfreq = syn.getParameterValue(GIZMO, PARAMETER)\\n\\tprint('value =', freq)\\n\\tfreq = [freq]\\n\\n\\t# also verify visually that the switch slipped in the run\\n\\t# time interface. This state change will be logged just\\n\\t# like any other variable change and saved with the runtime\\n\\t# state.\\n\\n\\tnumTrials = 5 #total number of trials across stimuli\\n\\tISI = [2.0, 3.0, 4.0, 5.0] # ISI in seconds\\n\\n\\t# flash parameters\\n\\tflash_dur = [.001] # flash durs in seconds (100 ms, 200 ms)\\n\\tluminance = [[1, 1, 1], [.86, .86, .86], [0, .1, 1]] # white , grayish, purple just for testing\\n\\n\\t# auditory parameters\\n\\tduration = [.005] # in seconds; pulseDur in TDT\\n\\tsound_levels = [20.0, 40.0, 60.0, 80.0] # dB; waveAmp in TDT\\n\\n\\t# Auditory on (T/F? if T then A+V, if F then Visual only)\\n\\tstims = {0: \\\"auditory_only\\\",\\n\\t\\t\\t 1: \\\"visual_only\\\",\\n\\t\\t\\t 2: \\\"A+V\\\"\\n\\t\\t\\t }\\n\\n\\texper = Experiment(numTrials=numTrials, ISI=ISI, flash_dur=flash_dur, luminance=luminance, wave_freq=freq,\\n\\t\\t\\t\\t\\t pulse_dur=duration, wave_amp=sound_levels, stimulus=stims)\\n\\texper.run_experiment()\",\n \"def getattr(self, path, *args, **pargs):\\n path, meta = self.find_cue_path(path)\\n if('.flaccuesplit.' in path):\\n try:\\n raw_path = path\\n path, flaccue_details = path.split('.flaccuesplit.')\\n path = self.clean_path(path)\\n times, extension = os.path.splitext(flaccue_details)\\n # Get the info for the base file.\\n st = os.lstat(path)\\n toreturn = dict((key, getattr(st, key)) for key in (\\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\\n 'st_nlink', 'st_size', 'st_uid'))\\n # Estimate the file size.\\n f = mutagen.File(path)\\n start, end = times.split('.')\\n # Minutes:Seconds:Frames\\n # 75 frames per second.\\n start_split = [int(x) for x in start.split(':')]\\n if(len(start_split) != 3):\\n start_time = 0\\n else:\\n start_time = start_split[0]*60 + start_split[1] + start_split[2]/75\\n end_split = [int(x) for x in end.split(':')]\\n if(len(end_split) != 3):\\n end_time = f.info.length\\n else:\\n end_time = end_split[0]*60 + end_split[1] + end_split[2]/75\\n toreturn['st_size'] = int((end_time - start_time) *\\n f.info.channels *\\n (f.info.bits_per_sample/8) *\\n f.info.sample_rate)\\n # Ensure the mode shows the file as readable.\\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\\n return toreturn\\n except Exception:\\n print(f'Error getting attributes for {raw_path}:', file=sys.stderr, flush=True)\\n import traceback\\n traceback.print_exc()\\n # Otherwise, just get the normal info.\\n path = self.clean_path(path)\\n st = os.lstat(path)\\n toreturn = dict((key, getattr(st, key)) for key in (\\n 'st_atime', 'st_ctime', 'st_gid', 'st_mode', 'st_mtime',\\n 'st_nlink', 'st_size', 'st_uid'))\\n # Ensure the mode shows the file as readable.\\n toreturn['st_mode'] = toreturn['st_mode'] | 0o444\\n return toreturn\",\n \"def parse_fname(cmd_args):\\n\\n # Seasonal accumulation file\\n if (cmd_args.period == 99):\\n f_name = _parse_fname_season(cmd_args)\\n else:\\n f_name = _parse_fname_hour(cmd_args)\\n\\n return f_name\",\n \"def get_metadata(my_path):\\n with wave.open(my_path, \\\"rb\\\") as wave_file:\\n frame_rate = wave_file.getframerate()\\n channels = wave_file.getnchannels()\\n my_format = pyaudio.get_format_from_width(wave_file.getsampwidth())\\n return str(frame_rate), str(channels), str(my_format)\",\n \"def readFT(self,file=\\\"out__1.ft\\\"):\",\n \"def generate_config(filename: str,\\n mw_pulse_duration: int = 20,\\n flux_pulse_duration: int=40,\\n ro_duration: int = 800,\\n mw_mw_buffer=0,\\n mw_flux_buffer=0,\\n flux_mw_buffer=0,\\n ro_latency: int = 0,\\n mw_latency: int = 0,\\n fl_latency: int = 0,\\n init_duration: int = 200000):\\n\\n qubits = ['q0', 'q1', 'q2', 'q3', 'q4', 'q5', 'q6']\\n lut_map = ['i {}', 'rx180 {}', 'ry180 {}', 'rx90 {}', 'ry90 {}',\\n 'rxm90 {}', 'rym90 {}', 'rphi90 {}', 'spec {}', 'rx12 {}',\\n 'square {}']\\n flux_tuples = [(\\\"q2\\\", \\\"q0\\\"), (\\\"q0\\\", \\\"q2\\\"),\\n (\\\"q0\\\", \\\"q3\\\"), (\\\"q3\\\", \\\"q0\\\"),\\n (\\\"q3\\\", \\\"q1\\\"), (\\\"q1\\\", \\\"q3\\\"),\\n (\\\"q1\\\", \\\"q4\\\"), (\\\"q4\\\", \\\"q1\\\"),\\n (\\\"q2\\\", \\\"q5\\\"), (\\\"q5\\\", \\\"q2\\\"),\\n (\\\"q5\\\", \\\"q3\\\"), (\\\"q3\\\", \\\"q5\\\"),\\n (\\\"q3\\\", \\\"q6\\\"), (\\\"q6\\\", \\\"q3\\\"),\\n (\\\"q6\\\", \\\"q4\\\"), (\\\"q4\\\", \\\"q6\\\")]\\n\\n cfg = {\\n \\\"eqasm_compiler\\\": \\\"cc_light_compiler\\\",\\n \\\"hardware_settings\\\": {\\n \\\"qubit_number\\\": 7,\\n \\\"cycle_time\\\": 20,\\n \\\"mw_mw_buffer\\\": mw_mw_buffer,\\n \\\"mw_flux_buffer\\\": mw_flux_buffer,\\n \\\"mw_readout_buffer\\\": 0,\\n \\\"flux_mw_buffer\\\": flux_mw_buffer,\\n \\\"flux_flux_buffer\\\": 0,\\n \\\"flux_readout_buffer\\\": 0,\\n \\\"readout_mw_buffer\\\": 0,\\n \\\"readout_flux_buffer\\\": 0,\\n \\\"readout_readout_buffer\\\": 0},\\n \\\"instructions\\\": {},\\n \\\"resources\\\":\\n {\\\"qubits\\\": {\\\"count\\\": 7},\\n \\\"qwgs\\\": {\\\"count\\\": 3,\\n \\\"connection_map\\\":\\n {\\n \\\"0\\\": [0, 1],\\n \\\"1\\\": [2, 3, 4],\\n \\\"2\\\": [5, 6]\\n }\\n },\\n \\\"meas_units\\\": {\\\"count\\\": 7,\\n \\\"connection_map\\\": {\\\"0\\\": [0],\\n \\\"1\\\": [1],\\n \\\"2\\\": [2],\\n \\\"3\\\": [3],\\n \\\"4\\\": [4],\\n \\\"5\\\": [5],\\n \\\"6\\\": [6]\\n }\\n },\\n # FIXME OpenQL #103\\n # \\\"meas_units\\\": {\\\"count\\\": 2,\\n # \\\"connection_map\\\": {\\\"0\\\": [0, 2, 3, 5, 6],\\n # \\\"1\\\": [1, 4]}\\n # },\\n \\\"edges\\\": {\\\"count\\\": 8,\\n \\\"connection_map\\\": {\\n \\\"0\\\": [2],\\n \\\"1\\\": [3],\\n \\\"2\\\": [0],\\n \\\"3\\\": [1],\\n \\\"4\\\": [6],\\n \\\"5\\\": [7],\\n \\\"6\\\": [4],\\n \\\"7\\\": [5]\\n }\\n }\\n },\\n \\\"topology\\\":\\n {\\n \\\"x_size\\\": 5,\\n \\\"y_size\\\": 3,\\n \\\"qubits\\\":\\n [\\n {\\\"id\\\": 0, \\\"x\\\": 1, \\\"y\\\": 2},\\n {\\\"id\\\": 1, \\\"x\\\": 3, \\\"y\\\": 2},\\n {\\\"id\\\": 2, \\\"x\\\": 0, \\\"y\\\": 1},\\n {\\\"id\\\": 3, \\\"x\\\": 2, \\\"y\\\": 1},\\n {\\\"id\\\": 4, \\\"x\\\": 4, \\\"y\\\": 1},\\n {\\\"id\\\": 5, \\\"x\\\": 1, \\\"y\\\": 0},\\n {\\\"id\\\": 6, \\\"x\\\": 3, \\\"y\\\": 0}\\n ],\\n \\\"edges\\\":\\n [\\n {\\\"id\\\": 0, \\\"src\\\": 2, \\\"dst\\\": 0},\\n {\\\"id\\\": 1, \\\"src\\\": 0, \\\"dst\\\": 3},\\n {\\\"id\\\": 2, \\\"src\\\": 3, \\\"dst\\\": 1},\\n {\\\"id\\\": 3, \\\"src\\\": 1, \\\"dst\\\": 4},\\n {\\\"id\\\": 4, \\\"src\\\": 2, \\\"dst\\\": 5},\\n {\\\"id\\\": 5, \\\"src\\\": 5, \\\"dst\\\": 3},\\n {\\\"id\\\": 6, \\\"src\\\": 3, \\\"dst\\\": 6},\\n {\\\"id\\\": 7, \\\"src\\\": 6, \\\"dst\\\": 4}\\n ]\\n },\\n\\n \\\"gate_decomposition\\\": {\\n \\\"measz %0\\\": [\\\"measure %0\\\"],\\n \\\"x %0\\\": [\\\"rx180 %0\\\"],\\n \\\"y %0\\\": [\\\"ry180 %0\\\"],\\n \\\"roty90 %0\\\": [\\\"ry90 %0\\\"],\\n \\\"cnot %0,%1\\\": [\\\"ry90 %1\\\", \\\"cz %0,%1\\\", \\\"ry90 %1\\\"],\\n\\n # To support other forms of writing the same gates\\n \\\"x180 %0\\\": [\\\"rx180 %0\\\"],\\n \\\"y180 %0\\\": [\\\"ry180 %0\\\"],\\n \\\"y90 %0\\\": [\\\"ry90 %0\\\"],\\n \\\"x90 %0\\\": [\\\"rx90 %0\\\"],\\n \\\"my90 %0\\\": [\\\"rym90 %0\\\"],\\n \\\"mx90 %0\\\": [\\\"rxm90 %0\\\"],\\n\\n # Clifford decomposition per Epstein et al. Phys. Rev. A 89, 062321\\n # (2014)\\n \\\"cl_0 %0\\\": ['i %0'],\\n \\\"cl_1 %0\\\": ['ry90 %0', 'rx90 %0'],\\n \\\"cl_2 %0\\\": ['rxm90 %0', 'rym90 %0'],\\n \\\"cl_3 %0\\\": ['rx180 %0'],\\n \\\"cl_4 %0\\\": ['rym90 %0', 'rxm90 %0'],\\n \\\"cl_5 %0\\\": ['rx90 %0', 'rym90 %0'],\\n \\\"cl_6 %0\\\": ['ry180 %0'],\\n \\\"cl_7 %0\\\": ['rym90 %0', 'rx90 %0'],\\n \\\"cl_8 %0\\\": ['rx90 %0', 'ry90 %0'],\\n \\\"cl_9 %0\\\": ['rx180 %0', 'ry180 %0'],\\n \\\"cl_10 %0\\\": ['ry90 %0', 'rxm90 %0'],\\n \\\"cl_11 %0\\\": ['rxm90 %0', 'ry90 %0'],\\n\\n \\\"cl_12 %0\\\": ['ry90 %0', 'rx180 %0'],\\n \\\"cl_13 %0\\\": ['rxm90 %0'],\\n \\\"cl_14 %0\\\": ['rx90 %0', 'rym90 %0', 'rxm90 %0'],\\n \\\"cl_15 %0\\\": ['rym90 %0'],\\n \\\"cl_16 %0\\\": ['rx90 %0'],\\n \\\"cl_17 %0\\\": ['rx90 %0', 'ry90 %0', 'rx90 %0'],\\n \\\"cl_18 %0\\\": ['rym90 %0', 'rx180 %0'],\\n \\\"cl_19 %0\\\": ['rx90 %0', 'ry180 %0'],\\n \\\"cl_20 %0\\\": ['rx90 %0', 'rym90 %0', 'rx90 %0'],\\n \\\"cl_21 %0\\\": ['ry90 %0'],\\n \\\"cl_22 %0\\\": ['rxm90 %0', 'ry180 %0'],\\n \\\"cl_23 %0\\\": ['rx90 %0', 'ry90 %0', 'rxm90 %0']\\n },\\n }\\n\\n for q in qubits:\\n cfg[\\\"instructions\\\"][\\\"prepz {}\\\".format(q)] = {\\n \\\"duration\\\": init_duration,\\n \\\"latency\\\": 0,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": True,\\n \\\"type\\\": \\\"none\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"prepz\\\",\\n \\\"cc_light_codeword\\\": 0,\\n \\\"cc_light_opcode\\\": 2\\n }\\n\\n for q in qubits:\\n cfg[\\\"instructions\\\"][\\\"measure {}\\\".format(q)] = {\\n \\\"duration\\\": ro_duration,\\n \\\"latency\\\": ro_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"readout\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"measz\\\",\\n \\\"cc_light_codeword\\\": 0,\\n \\\"cc_light_opcode\\\": 4\\n }\\n\\n for CW in range(len(lut_map)):\\n for q in qubits:\\n cfg[\\\"instructions\\\"][lut_map[CW].format(q)] = {\\n \\\"duration\\\": mw_pulse_duration,\\n \\\"latency\\\": mw_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"mw\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"cw_{:02}\\\".format(CW),\\n \\\"cc_light_codeword\\\": CW,\\n \\\"cc_light_opcode\\\": 8+CW}\\n\\n cfg[\\\"instructions\\\"]['c1'+lut_map[CW].format(q)] = {\\n \\\"duration\\\": mw_pulse_duration,\\n \\\"latency\\\": mw_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"mw\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"C1_cw_{:02}\\\".format(CW),\\n \\\"cc_light_codeword\\\": CW,\\n \\\"cc_light_opcode\\\": 32+8+CW,\\n \\\"cc_light_cond\\\": 1} # 1 means : do if last meas. == 1\\n\\n\\n cfg[\\\"instructions\\\"]['c0'+lut_map[CW].format(q)] = {\\n \\\"duration\\\": mw_pulse_duration,\\n \\\"latency\\\": mw_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"mw\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"C0_cw_{:02}\\\".format(CW),\\n \\\"cc_light_codeword\\\": CW,\\n \\\"cc_light_opcode\\\": 32+16+CW,\\n \\\"cc_light_cond\\\": 2} # 2 means : do if last meas. == 0\\n\\n\\n for CW in range(32):\\n for q in qubits:\\n cfg[\\\"instructions\\\"][\\\"cw_{:02} {}\\\".format(CW, q)] = {\\n \\\"duration\\\": mw_pulse_duration,\\n \\\"latency\\\": mw_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"mw\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"cw_{:02}\\\".format(CW),\\n \\\"cc_light_codeword\\\": CW,\\n \\\"cc_light_opcode\\\": 8+CW}\\n\\n for q in qubits:\\n cfg[\\\"instructions\\\"][\\\"compensate {}\\\".format(q)] = {\\n \\\"duration\\\": mw_pulse_duration,\\n \\\"latency\\\": mw_latency,\\n \\\"qubits\\\": [q],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": False,\\n \\\"type\\\": \\\"mw\\\",\\n \\\"cc_light_instr_type\\\": \\\"single_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"cw_00\\\",\\n \\\"cc_light_codeword\\\": 0,\\n \\\"cc_light_opcode\\\": 8+0}\\n\\n # N.B. The codewords for CZ pulses need to be further specified.\\n # I do not expect this to be correct for now.\\n for ft in flux_tuples:\\n # FIXME add space back in\\n cfg[\\\"instructions\\\"][\\\"cz {},{}\\\".format(ft[0], ft[1])] = {\\n \\\"duration\\\": flux_pulse_duration,\\n \\\"latency\\\": fl_latency,\\n \\\"qubits\\\": [ft[0], ft[1]],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": True,\\n \\\"type\\\": \\\"flux\\\",\\n \\\"cc_light_instr_type\\\": \\\"two_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"fl_cw_{:02}\\\".format(1),\\n \\\"cc_light_right_codeword\\\": 1,\\n \\\"cc_light_left_codeword\\\": 1,\\n \\\"cc_light_opcode\\\": 128+1\\n }\\n\\n for cw_flux in range(8):\\n for ft in flux_tuples:\\n cfg[\\\"instructions\\\"][\\\"fl_cw_{:02} {},{}\\\".format(cw_flux,\\n ft[0], ft[1])] = {\\n \\\"duration\\\": flux_pulse_duration,\\n \\\"latency\\\": fl_latency,\\n \\\"qubits\\\": [ft[0], ft[1]],\\n \\\"matrix\\\": [[0.0, 1.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]],\\n \\\"disable_optimization\\\": True,\\n \\\"type\\\": \\\"flux\\\",\\n \\\"cc_light_instr_type\\\": \\\"two_qubit_gate\\\",\\n \\\"cc_light_instr\\\": \\\"fl_cw_{:02}\\\".format(cw_flux),\\n \\\"cc_light_right_codeword\\\": cw_flux,\\n \\\"cc_light_left_codeword\\\": cw_flux,\\n \\\"cc_light_opcode\\\": 128+cw_flux\\n }\\n\\n with open(filename, 'w') as f:\\n json.dump(cfg, f, indent=4)\",\n \"def t8_loadFile(self):\\n print \\\"spectrumFile\\\"\\n filename = tkFileDialog.askopenfilename()\\n filename = self.filenameparser(filename)\\n self.t8_filename = filename\",\n \"def read_all_files(\\n pathname: Path, index: int = 0, pattern: str = \\\"dump-Trimer-*.gsd\\\"\\n) -> List[Tuple[Variables, HoomdFrame]]:\\n pathname = Path(pathname)\\n snapshots = []\\n for filename in sorted(glob.glob(str(pathname / pattern))):\\n logger.debug(\\\"Reading %s\\\", Path(filename).stem)\\n with gsd.hoomd.open(str(filename)) as trj:\\n try:\\n snapshots.append((get_filename_vars(filename), HoomdFrame(trj[index])))\\n except IndexError:\\n continue\\n if not snapshots:\\n logger.warning(\\n \\\"There were no files found with a configuration at index %s\\\", index\\n )\\n return snapshots\",\n \"def t6_loadFile(self):\\n print \\\"subspectrumFile\\\"\\n filename = tkFileDialog.askopenfilename()\\n filename = \\\"SubSpectrumData/\\\" + self.filenameparser(filename)\\n self.t6_filename = filename\",\n \"def processFile(filename,length = 256,q=1,fs_in=8000,divide=4,plot=False):\\n length = length*divide\\n #fs = sample rate, sound = multichannel sound signal\\n try:\\n fs1, sound = wavfile.read(filename)\\n except ValueError:\\n print(str(filename) + ' failed to process')\\n return 'failed'\\n if fs1 != fs_in:\\n raise ValueError('Sampling rate should be ' + str(fs_in) + ' for: ' + filename)\\n sig1 = sound[:0] #left channel\\n pre_emphasis = 0.97\\n sig1 = np.append(sig1[0], sig1[1:] - pre_emphasis * sig1[:-1])\\n\\n \\n fs2, sig2 = downsample(sig1,fs1,q)\\n N2 = len(sig2)\\n sig3 = sig2[N2//2-length:N2//2+length]\\n #print(len(sig3))\\n\\n FFT = abs(scipy.fft(sig3))\\n FFT_side = FFT[range(len(FFT)//2)]\\n #freqs = scipy.fftpack.fftfreq(sig3.size, 1/fs2)\\n #plt.plot(freqs,FFT)\\n if len(FFT_side) != length:\\n print('ERROR MESSAGE DETAILS')\\n print('filename: ' + filename)\\n print('length = ' + str(length))\\n print('fs_in = ' + str(fs_in))\\n print('q = ' + str(q))\\n print('divide = ' + str(divide))\\n total_time = len(sig1)/fs1\\n print('total_time = ' + str(total_time))\\n print('Please check: length < total_time*fs//(2*q)')\\n print('Check: ' + str(length) + ' < ' + str(total_time*fs1//(2*q)))\\n raise ValueError('Length FFT_side != length: ' + str(len(FFT_side)) + ' != ' + str(length))\\n \\n \\n FFT_log = []\\n # normalize FFT\\n for value in FFT_side:\\n value = np.log(value)\\n FFT_log.append(value)\\n max_val = getMax(FFT_log)[1]\\n FFT_norm = []\\n for value in FFT_log:\\n FFT_norm.append(value/max_val)\\n \\n \\n FFT_side = np.array(FFT_norm)\\n FFT_divided = FFT_side[range(length//divide)]\\n #plot = True\\n if plot == True:\\n freqs = scipy.fftpack.fftfreq(sig3.size, 1/fs2)\\n freqs_divided = np.array(freqs[range(len(FFT_divided))])\\n plt.plot(freqs_divided,FFT_divided) # plotting the complete fft spectrum\\n plt.show()\\n \\n return FFT_divided\",\n \"def get_files(file_list, mode):\\n\\tfile_set = set(file_list)\\n\\tif \\\"band\\\" in mode:\\n\\t\\tband_all_set = set([\\\"bands.dat.gnu\\\", \\\"freq.plot\\\"])\\n\\t\\tband_file_set = file_set & band_all_set ; remain_file_set = file_set - band_all_set\\n\\t\\tfiles_str = \\\", \\\".join([f\\\"\\\\033[32m{b}\\\\033[0m\\\" for b in band_file_set]) + \\\"; \\\" + \\\", \\\".join(remain_file_set)\\n\\tif mode == \\\"dos\\\":\\n\\t\\tdos_all_set = set([\\\"S.dos\\\"])\\n\\t\\tdos_file_set = file_set & dos_all_set ; remain_file_set = file_set - dos_all_set\\n\\t\\tfiles_str = \\\", \\\".join([f\\\"\\\\033[32m{d}\\\\033[0m\\\" for d in dos_file_set]) + \\\"; \\\" + \\\", \\\".join(remain_file_set)\\n\\tprint(f\\\"Files in the directory: {files_str}\\\"); file = input(\\\"Please choose your file (type one only): \\\")\\n\\treturn file\",\n \"def load_time_streams(self, channels=None):\\n if channels is None:\\n channels = self.get_channels()\\n\\n if self.data is None:\\n self.make_temp_data(channels=channels)\\n elif self.data.shape[0] != channels.size:\\n self.discard_temp_data()\\n self.make_temp_data(channels=channels)\\n\\n frames = self.integration.frames\\n fnf.load_timestream(\\n frame_data=frames.data,\\n frame_weights=frames.relative_weight,\\n frame_valid=frames.valid,\\n modeling_frames=frames.is_flagged('MODELING_FLAGS'),\\n channel_indices=channels.indices,\\n sample_flags=frames.sample_flag,\\n timestream=self.data,\\n points=self.points)\",\n \"def read_inputs(self):\\n curdir = os.getcwd()\\n os.chdir(self.fst_dir)\\n rstat = self.readFST()\\n if rstat == 0:\\n os.chdir(curdir)\\n return 0\\n # the names of the next files are either set by caller or come from the reading the FAST file\\n rstat = self.readNoise()\\n rstat = self.readAD()\\n rstat = self.readBlade()\\n rstat = self.readPtfm()\\n os.chdir(curdir)\",\n \"def get_per_lib_sff_fps(sff_dir):\\r\\n for dirpath, dirnames, fnames in walk(sff_dir):\\r\\n for fname in fnames:\\r\\n if fname.endswith('.sff'):\\r\\n libname, _ = splitext(fname)\\r\\n yield libname, join(dirpath, fname)\",\n \"def get_audio():\\n\\tbuf = None\\n\\tnum_new_bytes = BUFFER_SIZE // REFRESH_BUFFER_FACTOR\\n\\twith open(INFILE) as fifo:\\n\\t\\twhile True:\\n\\t\\t\\tif buf is None:\\n\\t\\t\\t\\tbuf = fifo.read(BUFFER_SIZE)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tbuf = buf[num_new_bytes:] + fifo.read(num_new_bytes)\\n\\t\\t\\tyield buf\",\n \"def t1_loadFile(self):\\n print \\\"subspectrumFile\\\"\\n filename = tkFileDialog.askopenfilename()\\n filename = self.filenameparser(filename)\\n self.t1_filename = filename\",\n \"def _default_specs(self):\\n # Spectrometer specs\\n self.model = \\\"Flame-S\\\" # Spectrometer model\\n self.fov = None # Field of view fo spectrometer\\n self.ILS = None # Number array holding instrument line shape (possibly don't hold this here?)\\n self.pix_num = 2048 # Number of pixels\\n self.bit_depth = 16 # Bit depth of spectrometer detector\\n\\n # File information\\n self.file_ext = '.npy' # Spectra saved as numpy array\\n self.file_ss = '{}ss' # Shutter speed format spec\\n self.file_spec_type = {'meas': 'Plume', 'dark': 'Dark', 'cal': 'ppmm', 'clear': 'Clear'}\\n self.file_datestr = \\\"%Y-%m-%dT%H%M%S\\\" # Date/time format spec in filename\\n\\n\\n\\n # Acquisition settings\\n self.start_int_time = 100 # Starting integration time\\n self.start_coadd = 5 # Number of spectra to coadd\\n self.framerate = 1 # Framerate of acquisitions (Hz)\\n self.wavelengths = None # Wavelengths (nm)\\n self.spectrum = None # Spectrum\\n self.spectrum_filename = None # Filename for spectrum\\n\\n self.auto_int = True # Bool for requesting automated integration time adjustment\\n self.min_saturation = 0.5 # Minimum saturation accepted before adjusting shutter speed (if auto_ss is True)\\n self.max_saturation = 0.9 # Maximum saturation accepted before adjusting shutter speed (if auto_ss is True)\\n self.saturation_range = [320, 330] # Range of wavelengths used in checking integration time\\n\\n # Predefined list of integration times for automatic exposure adjustment\\n self.int_list = np.concatenate((np.arange(1, 10, 1),\\n np.arange(10, 50, 5),\\n np.arange(50, 100, 10),\\n np.arange(100, 500, 50),\\n np.arange(500, 1000, 100),\\n np.arange(10 ** 3, 10 ** 4, 500),\\n np.array([10 ** 4])))\",\n \"def main():\\r\\n\\r\\n ### Choose and Import File\\r\\n\\r\\n inSound = Sound()\\r\\n\\r\\n rate = inSound.rate\\r\\n data = inSound.data\\r\\n dataLength = len(data)\\r\\n \\r\\n info = inSound.get_info()\\r\\n head, filename = os.path.split(info[0]) # get filename of input\\r\\n \\r\\n # Decide output directory and filename\\r\\n outDir = r'out'\\r\\n outFile = os.path.join(outDir, 'out_'+filename)\\r\\n\\r\\n # Check if data has multiple channels, if yes use only one\\r\\n if(len(data.shape) > 1):\\r\\n data = data[:,0]\\r\\n\\r\\n\\r\\n ### Set All Parameters\\r\\n\\r\\n #get parameters from user dialogue\\r\\n params = getParameters()\\r\\n\\r\\n numChannels = params['numChannels'][0] # number of Channels\\r\\n loFreq = params['loFreq'][0] # lower bound on frequencies\\r\\n hiFreq = params['hiFreq'][0] # upper bound on frequencies\\r\\n plotChannels = params['plotChannels'][0] # if it should plot the Gammatone channels\\r\\n block_time = params['block_time'][0] # in ms\\r\\n block_shift = params['block_shift'][0] # in ms\\r\\n selectChannels = params['selectChannels'][0] # number of channels to activate at a single time\\r\\n\\r\\n\\r\\n ### Filter input file\\r\\n\\r\\n filtered, channel_fs = filterDataGamaTone(data, rate, numChannels, loFreq, hiFreq, plotChannels)\\r\\n\\r\\n\\r\\n ### Gammatones -> Stimulation Amplitude for time block\\r\\n\\r\\n samples_in_block = np.floor(block_time * rate / 1000).astype('int')\\r\\n samples_in_shift = np.floor(block_shift * rate / 1000).astype('int')\\r\\n\\r\\n summed = gammatoneToAmplitude(filtered, samples_in_block, samples_in_shift)\\r\\n\\r\\n # only activate the n electrodes that have the largest stimulation\\r\\n amps = n_largest_channels(summed, n=selectChannels)\\r\\n\\r\\n \\r\\n #### Sound reconstruction\\r\\n\\r\\n # for each timeblock we need to duplicate enough samples to fill it at sample rate\\r\\n amps_samples = np.repeat(amps, samples_in_shift, axis=1)\\r\\n #trim end to get same length as input\\r\\n amps_samples = amps_samples[:,:dataLength] \\r\\n\\r\\n # from amplitude samples and frequencies, reconstruct sound\\r\\n res_data = generateSound(amps_samples, channel_fs, rate)\\r\\n\\r\\n\\r\\n ### Write to output file\\r\\n write(outFile, rate, res_data)\\r\\n print('Wrote file to: \\\\n' + outFile)\",\n \"def get_frame_list(self):\\r\\n\\r\\n logger.debug('Executing frame extraction')\\r\\n\\r\\n frames_loaded = False\\r\\n\\r\\n # Try to load YAML file with frame list\\r\\n if os.path.exists(self.frames_file_path):\\r\\n\\r\\n print 'Loading YAML file with frame list'\\r\\n logger.debug('Loading YAML file with frame list')\\r\\n\\r\\n f_list = utils.load_YAML_file(self.frames_file_path)\\r\\n\\r\\n if f_list:\\r\\n self.frame_list = f_list\\r\\n\\r\\n print 'YAML file with frame_list loaded'\\r\\n logger.debug('YAML file with frame_list loaded')\\r\\n\\r\\n frames_loaded = True\\r\\n\\r\\n if not frames_loaded:\\r\\n\\r\\n print '\\\\n\\\\n### Frame extraction ###\\\\n'\\r\\n logger.debug('\\\\n\\\\n### Frame extraction ###\\\\n')\\r\\n\\r\\n # Save processing time\\r\\n start_time = cv2.getTickCount()\\r\\n\\r\\n if not (os.path.exists(self.frames_path)):\\r\\n os.makedirs(self.frames_path)\\r\\n\\r\\n # Counter for all frames\\r\\n frame_counter = 0\\r\\n\\r\\n # Value of frame_counter for last analyzed frame\\r\\n last_anal_frame = 0\\r\\n\\r\\n # Open video file\\r\\n capture = cv2.VideoCapture(self.resource_path)\\r\\n\\r\\n self.frame_list = []\\r\\n\\r\\n # Save parameters for this video\\r\\n param_dict = {}\\r\\n\\r\\n if capture is None or not capture.isOpened():\\r\\n\\r\\n error = 'Error in opening video file'\\r\\n\\r\\n print error\\r\\n logger.debug(error)\\r\\n\\r\\n return\\r\\n\\r\\n else:\\r\\n\\r\\n video_fps = capture.get(cv2.cv.CV_CAP_PROP_FPS)\\r\\n\\r\\n param_dict[c.VIDEO_FPS_KEY] = video_fps\\r\\n\\r\\n # Original number of frames\\r\\n tot_frames = capture.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT)\\r\\n\\r\\n param_dict[c.VIDEO_TOT_FRAMES_KEY] = tot_frames\\r\\n\\r\\n self.fps = video_fps\\r\\n\\r\\n self.video_frames = float(tot_frames)\\r\\n\\r\\n # Saved frames\\r\\n saved_frames = 0\\r\\n\\r\\n while True:\\r\\n\\r\\n # Read frame\\r\\n ret, frame = capture.read()\\r\\n\\r\\n # If no frame is read, abort\\r\\n if not ret:\\r\\n break\\r\\n\\r\\n used_fps = c.USED_FPS\\r\\n use_or_fps = c.USE_ORIGINAL_FPS\\r\\n use_or_res = c.USE_ORIGINAL_RES\\r\\n used_res_scale_factor = c.USED_RES_SCALE_FACTOR\\r\\n\\r\\n if self.params is not None:\\r\\n\\r\\n if c.USED_FPS_KEY in self.params:\\r\\n used_fps = self.params[c.USED_FPS_KEY]\\r\\n\\r\\n if c.USE_ORIGINAL_FPS_KEY in self.params:\\r\\n use_or_fps = self.params[c.USE_ORIGINAL_FPS_KEY]\\r\\n\\r\\n if c.USE_ORIGINAL_RES_KEY in self.params:\\r\\n use_or_res = self.params[c.USE_ORIGINAL_RES_KEY]\\r\\n\\r\\n if c.USED_RES_SCALE_FACTOR_KEY in self.params:\\r\\n used_res_scale_factor = self.params[\\r\\n c.USED_RES_SCALE_FACTOR_KEY]\\r\\n\\r\\n # Next frame to be analyzed\\r\\n next_frame = last_anal_frame + (video_fps / used_fps) - 1\\r\\n\\r\\n if use_or_fps or (frame_counter > next_frame):\\r\\n\\r\\n # Frame position in video in milliseconds\\r\\n elapsed_ms = capture.get(cv2.cv.CV_CAP_PROP_POS_MSEC)\\r\\n\\r\\n # print 'elapsed video s =', elapsed_video_s\\r\\n\\r\\n fr_name = '%07d.png' % frame_counter\\r\\n\\r\\n frame_path = os.path.join(self.frames_path, fr_name)\\r\\n\\r\\n # Resize frame\\r\\n if not use_or_res:\\r\\n fx = used_res_scale_factor\\r\\n\\r\\n fy = used_res_scale_factor\\r\\n\\r\\n interp = cv2.INTER_AREA\\r\\n\\r\\n frame = cv2.resize(src=frame, dsize=(0, 0),\\r\\n fx=fx, fy=fy,\\r\\n interpolation=interp)\\r\\n\\r\\n cv2.imwrite(frame_path, frame,\\r\\n [cv.CV_IMWRITE_PNG_COMPRESSION, 0])\\r\\n\\r\\n frame_dict = {c.SAVED_FRAME_NAME_KEY: fr_name,\\r\\n c.ELAPSED_VIDEO_TIME_KEY: int(elapsed_ms)}\\r\\n\\r\\n self.frame_list.append(frame_dict)\\r\\n\\r\\n last_anal_frame = frame_counter\\r\\n\\r\\n saved_frames += 1\\r\\n\\r\\n frame_counter += 1\\r\\n\\r\\n self.progress = 100 * (frame_counter / self.video_frames)\\r\\n\\r\\n print('progress: ' + str(self.progress) + ' % \\\\r'),\\r\\n\\r\\n del capture\\r\\n\\r\\n self.saved_frames = float(saved_frames)\\r\\n\\r\\n param_dict[c.VIDEO_SAVED_FRAMES_KEY] = self.saved_frames\\r\\n\\r\\n # Save frame list in YAML file\\r\\n utils.save_YAML_file(self.frames_file_path, self.frame_list)\\r\\n\\r\\n # Save video parameters in YAML file\\r\\n\\r\\n utils.save_YAML_file(self.params_file_path, param_dict)\\r\\n\\r\\n # Save processing time\\r\\n time_in_clocks = cv2.getTickCount() - start_time\\r\\n time_in_seconds = time_in_clocks / cv2.getTickFrequency()\\r\\n\\r\\n print 'Time for frame extraction:', str(time_in_seconds), 's\\\\n'\\r\\n logger.debug(\\r\\n 'Time for frame extraction:', str(time_in_seconds), 's\\\\n')\\r\\n\\r\\n self.anal_times[c.FRAME_EXTRACTION_TIME_KEY] = time_in_seconds\\r\\n\\r\\n utils.save_YAML_file(self.analysis_file_path, self.anal_times)\",\n \"def split_into_frames(filename_raw, thr_var_per_event=5e-4, downsampling_factor=2, disable_display=False,\\n filename_output_video=None):\\n\\n assert downsampling_factor == int(downsampling_factor), \\\"Error: downsampling_factor must be an integer\\\"\\n assert downsampling_factor >= 0, \\\"Error: downsampling_factor must be >= 0\\\"\\n\\n mv_adaptive_rate_iterator = AdaptiveRateEventsIterator(input_path=filename_raw,\\n thr_var_per_event=thr_var_per_event,\\n downsampling_factor=downsampling_factor)\\n\\n height, width = mv_adaptive_rate_iterator.get_size()\\n\\n if filename_output_video == None:\\n video_process = None\\n else:\\n assert not os.path.exists(filename_output_video)\\n video_process = FFmpegWriter(filename_output_video)\\n\\n if video_process or not disable_display:\\n img_bgr = np.zeros((height, width, 3), dtype=np.uint8)\\n\\n cv2.namedWindow(\\\"img\\\", cv2.WINDOW_NORMAL)\\n\\n for events in mv_adaptive_rate_iterator:\\n assert events.size > 0\\n start_ts = events[0][\\\"t\\\"]\\n end_ts = events[-1][\\\"t\\\"]\\n print(\\\"frame: {} -> {} delta_t: {} fps: {} nb_ev: {}\\\".format(start_ts, end_ts,\\n end_ts - start_ts,\\n 1e6 / (end_ts - start_ts),\\n events.size))\\n if video_process or not disable_display:\\n img = events_to_diff_image(events, sensor_size=(height, width))\\n img_bgr[...] = 0\\n img_bgr[img < 0, 0] = 255\\n img_bgr[img > 0, 1] = 255\\n\\n chunk_start_ts = events[0][\\\"t\\\"]\\n chunk_end_ts = events[-1][\\\"t\\\"]\\n delta_t_frame = chunk_end_ts - chunk_start_ts + 1\\n frame_txt = \\\"ts: {} -> {} delta_t: {} fps: {} (nb_ev): {}\\\".format(chunk_start_ts, chunk_end_ts,\\n delta_t_frame,\\n int(1.e6/delta_t_frame),\\n events.size)\\n img_bgr[20:45, ...] = 0\\n cv2.putText(img_bgr,\\n frame_txt,\\n (int(0.05 * width), 40),\\n cv2.FONT_HERSHEY_PLAIN, 1.0, (200, 200, 100))\\n\\n if video_process:\\n video_process.writeFrame(img_bgr.astype(np.uint8)[..., ::-1])\\n if not disable_display:\\n cv2.imshow(\\\"img\\\", img_bgr)\\n if cv2.waitKey(1) & 0xFF == ord('q'):\\n break\\n\\n if video_process:\\n video_process.close()\\n if not disable_display:\\n cv2.destroyAllWindows()\",\n \"def get_fps(vid_path, prefix):\\n _, name = os.path.split(vid_path)\\n i1 = name.find(prefix) + len(prefix)\\n i2 = name[i1:].find('_')\\n fps = int(name[i1:i1+i2])\\n\\n return fps\",\n \"def load_batch(self, fpath, match, in_num):\\n if in_num == None:\\n in_num = input('Please specify IN number: ')\\n\\n if match == None:\\n match = input('Please specify filename string to match for batch loading (ex. \\\\'_s2_\\\\'): ')\\n\\n # get a list of all matching files\\n glob_match = f'{fpath}/*{match}*'\\n files = glob.glob(glob_match)\\n\\n # load & concatenate files into a single dataframe\\n data = pd.concat((pd.read_csv(file, header = [0, 1], index_col = 0, parse_dates=True, low_memory=False) for file in files)).sort_index()\\n\\n # extract sampling frequency\\n s_freq = 1/(data.index[1] - data.index[0]).total_seconds()\\n\\n # reset the index to continuous time\\n ind_freq = str(int(1/s_freq*1000000))+'us'\\n ind_start = '1900-01-01 00:00:00.000'\\n ind = pd.date_range(start = ind_start, periods=len(data), freq=ind_freq)\\n data.index = ind\\n\\n # set metadata & attributes\\n self.metadata = {'file_info':{'in_num': in_num, 'files': files, 'dir': fpath,\\n 'match_phrase': match},\\n 'analysis_info':{'s_freq': s_freq} }\\n self.data = data\\n self.s_freq = s_freq\",\n \"def get_file_params(file_path):\\n fpath, ftype = parse_path(file_path=file_path)\\n\\n if ftype == \\\"video\\\":\\n volume, dims = get_video_params(video_path=fpath)\\n else:\\n volume, dims = get_image_params(image_path=fpath)\\n\\n return volume, dims\",\n \"def FitsLookup(raw_filenames, config, config_arguments):\\n\\n warnings.filterwarnings('ignore')\\n\\n # Initialize the filelist and the progressbar variable smeantime and\\n # total_len\\n\\n filelist = list()\\n meantime = list()\\n\\n total_len = len(raw_filenames)\\n\\n # Loop over each file in raw_filenames getting the desired information\\n\\n for cont, filename in enumerate(raw_filenames):\\n\\n # Start the time measure\\n start = time.time()\\n\\n # Get the file header\\n header = fits.getheader(filename)\\n\\n # Extract the filetipe and classify it\\n typestr = header[config.exposure_type]\\n\\n if typestr == config.science_type_id:\\n img_type = 0\\n elif typestr == config.dark_type_id or typestr == config.bias_type_id:\\n img_type = 1\\n elif typestr == config.flat_type_id:\\n img_type = 2\\n else:\\n img_type = 3\\n\\n # Extract the filter\\n\\n filter = header[config.filter]\\n\\n # Extract the date and correct it with the time convention (night ->\\n # 12:00 to 11:59)\\n night = datetime.datetime.strptime(\\n header[config.observed_date], config.date_format)\\n\\n if night.hour < 12:\\n night = night.date() - datetime.timedelta(days=1)\\n\\n # Extract the exposure time\\n\\n exptime = header[config.expousure_time]\\n\\n # ---- HOW TO ADD MORE CLASSIFIERS TO THE RESULTING NUMPY ARRAY ------\\n #\\n # Using the header variable and the config_values dictionary you can\\n # extract all the values from the file. For example, to extract the temp:\\n #\\n # >>> temp = header[config_values['temp']]\\n #\\n # Once you have your new variable, you have to add this to the filelist in\\n # the code after this comment. For example, to add the temp in the previous-to-last\\n # entry:\\n #\\n # >>> filelist.append((filename, type, filter, exptime, str(night), temp, header))\\n #\\n # Finally, you have to modify the numpy dtype. Following with our example, as the temp\\n # is a float value, we can modify the dtype as:\\n #\\n # >>> dtype = np.dtype([('filename', 'S150'), ('type', int),\\n # ('filter', 'S10'), ('exptime', int), ('night', 'S10'),\\n # ('temp',float),('header', np.object)])\\n #\\n # Notice that the position of the new type in the dtype variable MUST match the position\\n # in which you added your new variable to the filelist. As we added \\\"temp\\\" previous-to-last,\\n # we have to add ('temp',float) in the position previous-to-last in the dtype.\\n #\\n # Now, you can use 'temp' for slicing, broadcasting and perform cool numpy stuff in the resulting\\n # array. Also, this value will work in the filter_collection function.\\n # Yay!\\n\\n # Append all the information to the filelist. MODIFY HERE IF NEEDED!\\n\\n filelist.append((filename, img_type, filter,\\n exptime, str(night), header))\\n\\n # Update progress bar\\n\\n end = time.time()\\n meantime.append(end - start)\\n\\n if config_arguments.verbose_flag and not config_arguments.no_interaction:\\n update_progress(float(cont + 1) / total_len,\\n np.mean(meantime) * (total_len - (cont + 1)))\\n\\n # Create the personalized dtype of the numpy array. MODIFY HERE IF NEEDED!\\n\\n dtype = np.dtype([('filename', 'S150'), ('type', int),\\n ('filter', 'S10'), ('exptime', int), ('night', 'S10'), ('header', np.object)])\\n\\n return np.array(filelist, dtype=dtype)\",\n \"def read_file(self, *args, **kwargs):\\n if self.detector == \\\"FACET\\\":\\n return self.read_facet(self.filename)\\n elif self.detector == \\\"OpenFace\\\":\\n return self.read_openface(self.filename)\\n elif self.detector == \\\"Affectiva\\\":\\n return self.read_affectiva(self.filename)\\n elif self.detector == \\\"Feat\\\":\\n return self.read_feat(self.filename)\\n else:\\n print(\\\"Must specifiy which detector [Feat, FACET, OpenFace, or Affectiva]\\\")\",\n \"def get_sorted_fps_U(data_dir, max = 988):\\n\\n fps = os.listdir(data_dir)\\n\\n #extract index of timestep from file name\\n idx_fps = []\\n for fp in fps:\\n _, file_number = fp.split(\\\"LSBU_\\\")\\n #file_number is of form '<IDX>.vtu'\\n idx = int(file_number.replace(\\\".vtu\\\", \\\"\\\"))\\n idx_fps.append(idx)\\n\\n\\n #sort by timestep\\n assert len(idx_fps) == len(fps)\\n zipped_pairs = zip(idx_fps, fps)\\n fps_sorted = [x for _, x in sorted(zipped_pairs)]\\n\\n #add absolute path\\n fps_sorted = [data_dir + x for x in fps_sorted]\\n\\n return fps_sorted\",\n \"def listfile(self):\\n print(\\\"Opened file(s):\\\")\\n for f in self.fmap:\\n print('\\\\t%s'%(self.files.index(self.fmap[f])),end=':')\\n print(f)\\n print(\\\"active file(s):\\\")\\n for i in range(len(self.handle)):\\n print('\\\\t%s'%(self.handle[i]),end=':')\\n print(self.fname[i])\",\n \"def gen_random_samples():\\n if os.path.exists('Song_Samples'):\\n pass\\n else:\\n os.mkdir('Song_Samples')\\n for filename in os.listdir(\\\"Songs\\\"):\\n rate, data = wavfile.read(os.path.join(\\\"Songs\\\", filename))\\n song_duration = len(data) // rate\\n start_point = randint(0, song_duration - SAMPLE_DURATION)\\n end_point = start_point + SAMPLE_DURATION\\n subprocess.call(['ffmpeg', '-i', os.path.join(\\\"Songs\\\", filename),\\n '-ss', str(datetime.timedelta(seconds=start_point)), '-to',\\n str(datetime.timedelta(seconds=end_point)), '-y', os.path.join(\\\"Song_Samples\\\", filename)])\",\n \"def analyzeWAV(inputFile):\\n data, fs, nbits = audiolab.wavread(inputFile)\\n samplingRate = fs\\n return [data, samplingRate]\",\n \"def get_file_parameters(self, input_file):\\n\\n #\\n # Read the Flag record.\\n #\\n input_file.seek(0, 0) # 0 = from start of file\\n record = input_file.read(FLAG_RECORD_SIZE)\\n\\n #\\n # Check for end of file.\\n # If not reached, check for and parse a Flag record.\\n #\\n if len(record) != FLAG_RECORD_SIZE:\\n log.warn(\\\"EOF reading for flag record\\\")\\n raise SampleException(\\\"EOF reading for flag record\\\")\\n \\n (valid_record, regex_velocity_record, \\n regex_end_velocity_record, format_unpack_velocity, \\n record_size) = self.parse_flag_record(record)\\n\\n #\\n # If there is a valid Flag record, process the Time record.\\n #\\n if valid_record:\\n #\\n # Read the Time record which is at the very end of the file.\\n # Note that we don't care if the number of bytes between the\\n # Flag record and the Time record is consistent with\\n # the flags from the Flag record.\\n # Put the file back at the beginning.\\n #\\n input_file.seek(0 - TIME_RECORD_SIZE, 2) # 2 = from end of file\\n record = input_file.read(TIME_RECORD_SIZE)\\n times = self.parse_time_record(record)\\n input_file.seek(0, 0) # 0 = from start of file\\n\\n #\\n # If the Flag record is invalid, we're done.\\n #\\n else:\\n log.warn(\\\"Invalid Flag record\\\")\\n raise SampleException(\\\"Invalid Flag record\\\")\\n\\n return valid_record, regex_velocity_record, regex_end_velocity_record, \\\\\\n format_unpack_velocity, record_size, times\",\n \"def getFiles(directory, showName, extension):\\n os.chdir(directory)\\n \\n list = []\\n \\n for file in glob.glob(\\\"*\\\"+showName+\\\"*.\\\"+extension):\\n list.append(file)\\n \\n return list\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5744606","0.5714158","0.5527169","0.5447836","0.5439457","0.5434857","0.53462785","0.5313303","0.5279001","0.52396804","0.5205854","0.5181732","0.51353776","0.51318854","0.5127048","0.51090044","0.50929743","0.50770855","0.5064212","0.5035977","0.50109285","0.5004155","0.49946982","0.4977221","0.49759647","0.49749187","0.49723175","0.49664775","0.49615744","0.49608487","0.49401402","0.49395475","0.4930261","0.49167743","0.49152225","0.4912529","0.49049425","0.48956937","0.4891052","0.48860332","0.48859408","0.48781943","0.48727006","0.4863908","0.48630837","0.48563656","0.4854827","0.48506588","0.48474374","0.48468184","0.48459354","0.48402146","0.4839392","0.4832828","0.48322693","0.4831627","0.48256326","0.48209947","0.48207283","0.4819031","0.48180342","0.48155692","0.4815551","0.48139542","0.48119906","0.48118323","0.48095298","0.48064283","0.48055705","0.48054737","0.48052505","0.48052308","0.4805218","0.480336","0.48032907","0.4799239","0.47928905","0.4790935","0.47826898","0.47803324","0.47785896","0.47673255","0.47646457","0.47593552","0.4755924","0.4751863","0.47427246","0.47385442","0.4735915","0.47337273","0.47290012","0.47285742","0.47274968","0.4726595","0.47259796","0.4724018","0.4721213","0.4720223","0.47068426","0.46996155","0.4693514"],"string":"[\n \"0.5744606\",\n \"0.5714158\",\n \"0.5527169\",\n \"0.5447836\",\n \"0.5439457\",\n \"0.5434857\",\n \"0.53462785\",\n \"0.5313303\",\n \"0.5279001\",\n \"0.52396804\",\n \"0.5205854\",\n \"0.5181732\",\n \"0.51353776\",\n \"0.51318854\",\n \"0.5127048\",\n \"0.51090044\",\n \"0.50929743\",\n \"0.50770855\",\n \"0.5064212\",\n \"0.5035977\",\n \"0.50109285\",\n \"0.5004155\",\n \"0.49946982\",\n \"0.4977221\",\n \"0.49759647\",\n \"0.49749187\",\n \"0.49723175\",\n \"0.49664775\",\n \"0.49615744\",\n \"0.49608487\",\n \"0.49401402\",\n \"0.49395475\",\n \"0.4930261\",\n \"0.49167743\",\n \"0.49152225\",\n \"0.4912529\",\n \"0.49049425\",\n \"0.48956937\",\n \"0.4891052\",\n \"0.48860332\",\n \"0.48859408\",\n \"0.48781943\",\n \"0.48727006\",\n \"0.4863908\",\n \"0.48630837\",\n \"0.48563656\",\n \"0.4854827\",\n \"0.48506588\",\n \"0.48474374\",\n \"0.48468184\",\n \"0.48459354\",\n \"0.48402146\",\n \"0.4839392\",\n \"0.4832828\",\n \"0.48322693\",\n \"0.4831627\",\n \"0.48256326\",\n \"0.48209947\",\n \"0.48207283\",\n \"0.4819031\",\n \"0.48180342\",\n \"0.48155692\",\n \"0.4815551\",\n \"0.48139542\",\n \"0.48119906\",\n \"0.48118323\",\n \"0.48095298\",\n \"0.48064283\",\n \"0.48055705\",\n \"0.48054737\",\n \"0.48052505\",\n \"0.48052308\",\n \"0.4805218\",\n \"0.480336\",\n \"0.48032907\",\n \"0.4799239\",\n \"0.47928905\",\n \"0.4790935\",\n \"0.47826898\",\n \"0.47803324\",\n \"0.47785896\",\n \"0.47673255\",\n \"0.47646457\",\n \"0.47593552\",\n \"0.4755924\",\n \"0.4751863\",\n \"0.47427246\",\n \"0.47385442\",\n \"0.4735915\",\n \"0.47337273\",\n \"0.47290012\",\n \"0.47285742\",\n \"0.47274968\",\n \"0.4726595\",\n \"0.47259796\",\n \"0.4724018\",\n \"0.4721213\",\n \"0.4720223\",\n \"0.47068426\",\n \"0.46996155\",\n \"0.4693514\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":81789,"cells":{"query":{"kind":"string","value":"Here just return frame from loaded data"},"document":{"kind":"string","value":"def getFrame(self, num):\n\n return self.data[num]"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def load_data(self):","def load_data(self) -> None:","def _get_raw_data(self, idx=0):\n # Get the time step then make a data frame\n raise NotImplementedError('Code me up!')\n #data = self._data[???]\n return data","def dataframe(self):\n\t\treturn self._dataframe","def dataframe(self):\n frames = []\n for game in self.__iter__():\n df = game.dataframe\n if df is not None:\n frames.append(df)\n if frames == []:\n return None\n return pd.concat(frames)","def __init__(self, dataFrame):\n self.dataFrame = dataFrame","def dataFrame(self):\n return self._dataFrame","def get_frame_data(self):\n # FrameObject is a dictionary of slot names and values.\n frameObject = self.pgdb.sendPgdbFnCall('get-frame-object', self.frameid)\n if not frameObject:\n raise PythonCycError(\"Could not retrieve frame \"+self.frameid+\" from organism (orgid) \"+self.pgdb._orgid)\n else:\n self._gotframe = True\n # Modify slot names to allow Python's syntax (e.g., '_' instead of '-').\n for slot in frameObject:\n self.__dict__[convertLispIdtoPythonId(slot)] = frameObject[slot]\n return self","def load_dataframe(self, path, type_='raw'):\r\n if type_ == 'raw':\r\n return pd.read_csv(path).to_numpy()[:, 1]\r\n elif type_ == 'features':\r\n return pd.read_csv(path, sep=' ', header=None).to_numpy()\r\n else:\r\n raise Exception(\"No type found!\")","def get_data(self)->pd.DataFrame:\n pass","def data_frame(self, arg=None):\n if arg is None:\n return pl.DataFrame()\n if isinstance(arg, pl.DataFrame):\n return arg\n if isinstance(arg, pl.LazyFrame):\n return arg.collect()\n return pl.DataFrame(arg)","def getDataframe(self):\n self._loadCSVFile()\n self._cleanProcessDf()\n return self._df","def load_own_data():\n data = Data()\n features = data.read_selected_features()\n dataframe = data.get_dataframe_with(features)\n return normalize(dataframe.values)","def __load( self, raw_content ):\n return( pd.read_csv( BytesIO( raw_content ) ) )","def load():\n return load_pandas()","def __data_frame(self):\n return self._trajectory","def _data_frame(content):\n response = loads(content)\n key = [x for x in response.keys() if x in c.response_data][0]\n frame = DataFrame(response[key])\n final_frame = _convert(frame)\n return final_frame","def dataframe_extended(self):\n frames = []\n for game in self.__iter__():\n df = game.dataframe_extended\n if df is not None:\n frames.append(df)\n if frames == []:\n return None\n return pd.concat(frames)","def dataframe(self):\n return self.generator.dataframe","def load_data(self):\n raise NotImplementedError()","def data(self):\n return self._frame.copy(deep=True)","def load_data_frame(name):\n\n return DataFrame(name).load()","def _read_data(self):","def read(self, fname, frame=None):\n\n self.resetvals()\n url = urlparse(fname)\n if not self.url:\n self.url = url\n# if frame:\n# self.hdf5_location.set_index(frame)\n self.filename = self.url.path\n if os.path.isfile(self.filename):\n self.hdf5 = h5py.File(self.filename, \"r\")\n else:\n error = \"No such file or directory: %s\" % self.filename\n logger.error(error)\n raise RuntimeError(error)\n self.ds = self.hdf5[self.url.query]\n if isinstance(self.ds, h5py.Group) and (\"data\" in self.ds):\n self.ds = self.ds[\"data\"]\n\n if self.url.fragment:\n slices = self.get_slice()\n self.data = self.ds[self.get_slice()]\n self.nframes = self.ds.shape[self.main_dim]\n else:\n self.data = self.ds[:]\n self.nframes = 1\n self.dim2, self.dim1 = self.data.shape\n self.bytecode = str(self.data.dtype)\n return self","def load_data(self):\n return self._load_data","def _load_data(self):\n\n if not self._cache.exists(config.DATAFRAME_SONG_DATA):\n source_path = os.path.join(config.S3_SONG_DATA, 'A/A/A/*.json') # Note: song database is way big, so we get only a slice of it.\n dataframe = self._get_spark_session().read.json(source_path)\n self._cache.set_source(config.DATAFRAME_SONG_DATA, dataframe)","def post_load(self, data):\n return data","def loader():\n bucket = data_load_variables[\"bucket\"]\n\n if data_load_variables[\"use_lite_dataset\"]:\n dataset_name = data_load_variables[\"lite_dataset_name\"]\n else:\n dataset_name = data_load_variables[\"dataset_name\"]\n\n s3 = boto3.client('s3')\n\n obj = s3.get_object(Bucket=bucket, Key=dataset_name)\n # get object and file (key) from bucket\n\n df = pd.read_csv(obj['Body'])\n return df","def test_frame_to_rows(self):\n pass","def load_data():\n dictionary = corpora.Dictionary.load(app.config['DICTIONARY'])\n matrix = similarities.MatrixSimilarity.load(app.config['MATRIX'])\n model = models.LsiModel.load(app.config['MODEL'])\n df = pd.read_pickle(app.config['DATA_FRAME'])\n return Data(matrix=matrix, model=model, dictionary=dictionary, data_frame=df)","def getDataFrame(self):\n return self.df","def _get_data(self):\n project_name, experiment_id = self.parent._get_parent_identifiers()\n\n self._data = self.repository.get_dataframe_data(\n project_name, self.id, experiment_id=experiment_id\n )","def _load_data(self, comp=None):\n\t\tif comp is None:\n\t\t\tcomp = self._compensation\n\t\tmatrix = self._fcsfile.read_data(fmt='matrix',\n\t\t\tcomp=comp)\n\t\treturn pd.DataFrame(matrix, columns=self._channels)","def load(self):","def load_from_open_file(self, df):\n df.seek(self.pos_start)\n self.data = df.read(self.length).decode('latin1').splitlines()\n self.loaded = True\n return self.data","def _get_frame_data(self):\n\n def _text_formatting(bs4_tag):\n \"\"\"Simple formatting that will be called a lot\"\"\"\n return bs4_tag.get_text().replace('\\n', '')\n\n tables = Character._get_main_page(self._fd).find_all('table', {'class': 'wikitable'})\n result = {}\n for table in tables:\n rows = table.find_all('tr')\n for row in rows:\n move = row.find('th')\n\n if move is not None:\n move_small = move.find('small')\n else:\n continue\n\n if move_small is not None:\n move_name = move.get_text().replace(move_small.get_text(), ' ' + move_small.get_text()).replace(\n '\\n', '')\n else:\n move_name = _text_formatting(move)\n\n move_name = move_name.replace('+', '') # B+C fix\n fd = row.find_all('td')\n\n try:\n result.update({\n move_name: {\n \"Damage\": _text_formatting(fd[0]),\n \"Cancel\": _text_formatting(fd[1]),\n \"Attribute\": _text_formatting(fd[4]),\n \"Guard\": _text_formatting(fd[5]),\n \"Startup\": _text_formatting(fd[6]),\n \"Active\": _text_formatting(fd[7]),\n \"Recovery\": _text_formatting(fd[8]),\n \"Frame Adv\": _text_formatting(fd[9]),\n \"Blockstun\": _text_formatting(fd[11]),\n \"Invul/GP\": _text_formatting(fd[19])\n }\n })\n except (AttributeError, IndexError):\n continue\n\n return result","def _load_df_or_array(self, key: str, idx: Union[None, np.ndarray] = None) -> Union[pd.DataFrame, np.ndarray]:\n if key == self.actions_key:\n if idx is None:\n data = pd.read_hdf(self.path, key=key)\n else:\n data = pd.read_hdf(self.path, key=key, where=idx)\n else:\n with h5py.File(self.path, 'r') as f:\n if idx is None:\n data = f[key][...]\n else:\n data = f[key][idx, ...]\n\n return data","def get_frame(freq: str):\n url = 'http://minikep-db.herokuapp.com/api/frame?freq={}'.format(freq)\n return pd.read_csv(url, converters={0: pd.to_datetime}, index_col=0)","def test_dataframe(self):\n\n url=\"http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data\"\n readerobject=requester.url_to_df(url)\n self.assertIsInstance(readerobject,pd.DataFrame)","def process_frame(self, frame):\n\t\treturn frame","def __init__(self, df):\n self.data = df","def load_data(filename) :\r\n data = Data()\r\n data.load(filename)\r\n return data","def load() -> DataFrame:\n return load_file(__file__, \"default.csv.gz\")","def glass_pandas(self):\n # pandas.set_option('display.width', 120)\n # TODO timeit (git_implementation) vs (my_implementation)\n # * df = pd.DataFrame(json.loads(r.text))\n # * df = df.set_index('t')\n # * df.index = pd.to_datetime(df.index, unit='s')\n # * df = df.sort_index()\n # * s = df.v\n # * s.name = '_'.join(url.split('/')[-2:])\n # * return s\n # for elem in self.loaded:\n # _metric, _data = elem[1]['_metrics'], elem[1]['_data']\n # try:\n # frame_keys = ['t'] + list(_data[0]['o'].keys())\n # framed = pandas.DataFrame(\n # data=[{k: (_data[iters]['t'] if k in 't' else _data[iters]['o'][k])\n # for k in frame_keys} for iters in range(len(_data))],\n # columns=frame_keys)\n # except KeyError:\n # framed = pandas.DataFrame(_data)\n # framed.set_index('t', inplace=True)\n # framed.index = pandas.to_datetime(\n # framed.index.to_flat_index(), unit='s', infer_datetime_format=True)\n # framed.sort_index(inplace=True)\n # framed.name = _metric\n # print(framed.name)\n # print(framed)","def load_vox(data: pd.DataFrame, in_place: bool = False):\n if not in_place:\n mod = data.copy()\n else:\n mod = data\n clips = []\n channels = []\n samplerates = []\n durations = []\n for i, row in mod.iterrows():\n sys.stdout.write(f\"\\r[-] Reading: {i} of {len(mod)} ({i / len(mod) * 100: .2f}%)\")\n sys.stdout.flush()\n with audioread.audio_open(row['file']) as f:\n channels.append(f.channels)\n samplerates.append(f.samplerate)\n durations.append(f.duration)\n data = bytearray()\n for buf in f:\n data = data + buf\n clips.append(data)\n sys.stdout.write(f\"\\r[ ] Read {len(mod)} files into DataFrame.\\r\\n\")\n sys.stdout.flush()\n mod['audio'] = pd.Series(clips)\n mod['channels'] = pd.Series(channels)\n mod['samplerate'] = pd.Series(samplerates)\n mod['duration'] = pd.Series(durations)\n return mod","def get_data(self):","def load_data():\n #read from S3\n df_obs = pd.read_csv('https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/df_obs.csv')\n df_sen = pd.read_csv('https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/df_sentry.csv')\n \n \n #background image to be used\n img_url = 'https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/map_detailed_723.jpeg'\n img_response = requests.get(img_url)\n img = Image.open(BytesIO(img_response.content))\n \n \n #apply translation of coordinates\n df_obs['x'] = df_obs['x'] - 64\n df_obs['y'] = df_obs['y'] - 64\n df_sen['x'] = df_sen['x'] - 64\n df_sen['y'] = df_sen['y'] - 64\n\n #convert time to minutes\n df_obs['time'] = df_obs['time']/60\n df_sen['time'] = df_sen['time']/60\n\n \n return df_obs, df_sen, img","def data(self):\n return self.as_named_DataFrame()","def extract(self) -> pd.core.frame.DataFrame:\n pass","def read(self):\n\n if self.filename.endswith(\".pkl\"):\n logging.debug(\"Loading pickle file %s\", self.filename)\n data = pd.read_pickle(self.filename)\n\n elif self.filename.endswith(\".hdf5\"):\n logging.debug(\"Loading HDF5 file %s\", self.filename)\n with h5py.File(self.filename, \"r\") as data_file:\n\n data = pd.DataFrame(\n {\n column: data_file[\"/haloTrees/%s\" % column].value\n for column in self.columns\n }\n ).set_index(\"nodeIndex\")\n\n # with open(\"./data/cache.pkl\", \"w\") as pickle_file:\n # data.to_pickle(pickle_file)\n\n else:\n raise TypeError(\"Unknown filetype %s\" % self.filename)\n\n return data","def data_frame_creator(self):\n\n rgb_dir = [\n self.dataset_address + sequence_f + rgb_f\n for rgb_f in self.rgb_folder for sequence_f in self.sequence_folder\n ]\n rgb_data = [\n rgb_d + rgb for rgb_d in rgb_dir for rgb in os.listdir(rgb_d)\n ]\n\n depth_dir = [\n self.dataset_address + sequence_f + depth_f\n for depth_f in self.depth_folder\n for sequence_f in self.sequence_folder\n ]\n depth_data = [\n depth_d + depth for depth_d in depth_dir\n for depth in os.listdir(depth_d)\n ]\n\n segmentation_dir = [\n self.dataset_address + sequence_f + segmentation_f\n for segmentation_f in self.segmentation_folder\n for sequence_f in self.sequence_folder\n ]\n segmentation_data = [\n segmentation_d + segmentation\n for segmentation_d in segmentation_dir\n for segmentation in os.listdir(segmentation_d)\n ]\n\n dataset = {\n 'RGB': rgb_data,\n 'DEPTH': depth_data,\n 'SEGMENTATION': segmentation_data\n }\n\n if self.shuffle:\n return pd.DataFrame(dataset).sample(frac=1)\n\n return pd.DataFrame(dataset)","def data_specific_processing(self, dataframe):\n return dataframe","def load_data(dataset_path: str):\n data = arff.loadarff(dataset_path)\n data_frame = pd.DataFrame(data[0])\n return data_frame","def intialize_source():\n raw = loadmat(\"p300backrec2.mat\")\n channels_raw = raw['channels']\n channels = []\n for i in channels_raw[0]:\n channels.extend(list(i))\n X = raw['data']\n marker = raw['marker']\n return X,channels,marker","def process_frames(self, data):\n pass","def process_frames(self, data):\n pass","def process_frames(self, data):\n pass","def process_frames(self, data):\n pass","def process_frames(self, data):\n pass","def get_frame(self, row):\n\n if row not in self.frames:\n if not self.write:\n d = self.memmap[row, :, :]\n if self.file.metadata['interleave'] == 'bil':\n d = d.T\n self.frames[row] = d.copy()\n else:\n self.frames[row] = s.nan * s.zeros((self.n_cols, self.n_bands))\n return self.frames[row]","def get_frame(self, ind):\n pass","def get_frame(self, f):\n return self._frames[f, :]","def load(self) -> pd.DataFrame:\n if os.path.exists(self.file_name):\n df = pd.read_csv(self.file_name, index_col=0)\n df = self._clean(df)\n else:\n _LOG.debug(\"No file '%s'\", self.file_name)\n df = pd.DataFrame()\n return df","def sourceToDataframe(self):\n df = pd.read_excel(self.filename)\n df.columns = df.iloc[10]\n df = df.drop(df.index[:11])\n self.df = df #makes this df accessible to the whole class now\n self.insertODN()\n display(df.head())","def _load(self):\n # Extract the ASCII header (5 first lines)\n with open(self._xst_bin, 'rb') as f:\n header = list(islice(f, 0, 5))\n assert header[0] == b'HeaderStart\\n',\\\n 'Wrong header start'\n assert header[-1] == b'HeaderStop\\n',\\\n 'Wrong header stop'\n header = [s.decode('utf-8') for s in header]\n hd_size = sum([len(s) for s in header])\n\n # Parse informations into a metadata dictionnary\n keys = ['freq', 'ma', 'accu']\n search = ['Freq.List', 'Mr.List', 'accumulation']\n types = ['float64', 'int', 'int']\n for key, word, typ in zip(keys, search, types):\n for h in header:\n if word in h:\n self.meta[key] = np.array(\n h.split('=')[1].split(','),\n dtype=typ\n )\n\n # Deduce the dtype for decoding\n n_ma = self.meta['ma'].size\n n_sb = self.meta['freq'].size\n dtype = np.dtype(\n [('jd', 'float64'),\n ('data', 'complex64', (n_sb, n_ma*n_ma*2 + n_ma))]\n )\n\n # Decoding the binary file\n tmp = np.memmap(\n filename=self._xst_bin,\n dtype='int8',\n mode='r',\n offset=hd_size\n )\n decoded = tmp.view(dtype)\n\n self.data = decoded['data'] / self.meta['accu']\n self.time = Time(decoded['jd'], format='jd', precision=0)\n\n return","def load_processed_data(animal, name, arguments):\r\n\tpath = os.path.join(paths.path2Output, animal, str(arguments['Function']), \r\n\t\t\t\t\t\tstr(arguments['Init']), str(arguments['Rank']), name)\r\n\t\r\n\tmeta_df = pd.read_csv(os.path.join(path,'meta_df.csv'))\r\n\troi_tensor = np.load(os.path.join(path,'roi_tensor.npy'))\r\n\tacti = np.load(os.path.join(path,'acti.npy'))\r\n\tnorm_acti = np.load(os.path.join(path,'norm_acti.npy'))\r\n\tsmoothed_acti = np.load(os.path.join(path,'smoothed_acti.npy'))\r\n\r\n\r\n\treturn meta_df, roi_tensor, acti, norm_acti, smoothed_acti","def read_frame(self):\n return self.decode_frame(self.grab_frame())","def load_data(self, data):\n\n if type(data) is \"json\":\n dataF = pd.read_json(data)\n elif type(data) is list:\n dataF = pd.DataFrame(data)\n else:\n print(\"Other types not implemented\")\n return\n dataF = self.__process_data(dataF)\n self.__dataF = dataF","def __load( self, json_blob ):\n return pd.read_json( json_blob, orient='split' )","def dataframe_extended(self):\n return self.boxscore.dataframe","def load_from_database(filename,key):\n\t# Opening file\n\tstore = pd.HDFStore(filename)\n\t# getting the df\n\tdata = store[key]\n\t# And its metadata\n\tmetadata = store.get_storer(key).attrs.metadata\n\tstore.close()\n\t# Ok returning the data now\n\treturn data, metadata","def loadFringe(self, frame=1, filename=None):\n self.currentFrame = np.int(frame)\n if filename:\n ofdPath = filename\n else:\n ofdPath = os.path.join(self.directory, self.basename +'.ofd')\n\n self.getOfdInfo(ofdPath)\n\n if self.mode == '2channel':\n self.load2Channel()\n if self.mode == '1channel':\n self.load1Channel()\n if self.mode == 'mmap2channel':\n self.mmap2channel()\n if self.mode == 'mmap1channel':\n self.mmap1channel()","def load_data_part(fname):\n if \"_data\" not in fname:\n return None\n # Read data\n data = pd.read_csv(fname)\n # events file\n events_fname = fname.replace('_data', '_events')\n # read event file\n labels = pd.read_csv(events_fname)\n clean = data.drop(['id'], axis=1) # remove id\n labels = labels.drop(['id'], axis=1) # remove id\n return clean, labels","def forward(self, raw_X):\n return make_df(raw_X, self.features)","def data_frame_creator(self):\n sequence_folder = [\n '/SEQ1', '/SEQ2', '/SEQ3', '/SEQ4', '/SEQ5', '/SEQ6'\n ]\n rgb_folder = ['/RGBLeft/', '/RGBRight/']\n depth_folder = ['/DepthLeft/', '/DepthRight/']\n segmentation_folder = ['/GTLeft/', '/GTright/']\n rgb_dir = [\n self.dataset_dir + sequence_f + rgb_f for rgb_f in rgb_folder\n for sequence_f in sequence_folder\n ]\n rgb_data = [\n rgb_d + rgb for rgb_d in rgb_dir for rgb in os.listdir(rgb_d)\n ]\n\n depth_dir = [\n self.dataset_dir + sequence_f + depth_f\n for depth_f in depth_folder\n for sequence_f in sequence_folder\n ]\n depth_data = [\n depth_d + depth for depth_d in depth_dir\n for depth in os.listdir(depth_d)\n ]\n\n segmentation_dir = [\n self.dataset_dir + sequence_f + segmentation_f\n for segmentation_f in segmentation_folder\n for sequence_f in sequence_folder\n ]\n segmentation_data = [\n segmentation_d + segmentation\n for segmentation_d in segmentation_dir\n for segmentation in os.listdir(segmentation_d)\n ]\n\n dataset = {\n 'RGB': rgb_data,\n 'DEPTH': depth_data,\n 'SEGMENTATION': segmentation_data\n }\n\n if self.shuffle:\n return pd.DataFrame(dataset).sample(frac=1, random_state=123)\n\n return pd.DataFrame(dataset)","def load(self):\n\n\t\t# Check if dataset location exists\n\t\tif (not os.path.exists(self._location)):\n\t\t\tprint(\"Error: Dataset location does not exist\")\n\t\t\treturn\n\n\t\tself._frames = sorted(glob.glob(self._location + '/frame*.jpg'))\n\n\t\t# Check if startFrame is beyond dataset bounds\n\t\tif (self._startFrame > len(self._frames)):\n\t\t\tprint(\"Error: Start frame is beyond dataset bounds\")\n\t\t\treturn\n\n\t\t# Check if endFrame is beyond dataset bounds\n\t\tif (self._endFrame > len(self._frames)):\n\t\t\tprint(\"Warning: End frame beyond dataset bounds, setting to end of dataset\")\n\n\t\t# Start buffering threads\n\t\tself._bufferThreadStopped = False\n\t\tself._bufferingThread.start()","def record_data_frame(self):\n return self._record.data_frame","def _load_data(data, n_prev=3):\n docX, docY = [], []\n for i in range(len(data)-n_prev):\n docX.append(data.data.iloc[i:i+n_prev])\n docY.append(data.response.iloc[i+n_prev]) \n\n alsX = np.array(docX)\n alsY = np.array(docY)\n return np.matrix(alsX), np.matrix(alsY).T","def dataframe(self):\n return self.get_target().dataframe()","def _setup_dataframe(self, serie, metadata=None):\n header = self.get_data_header(serie, dataset='cnv')\n df = self.get_data_in_frame(serie, header, dataset='cnv')\n df = self.df_handler.map_column_names_of_dataframe(df)\n\n return df","def get_frame(self, index):\n filename = self.get_filename(index)\n return plt.imread(fname=filename)","def get_zyla_data_object(evt, src):\n o = evt.get(_psana.Zyla.FrameV1, src)\n if o is not None: return o\n\n return None","def _dataframe_from_feather(fn, **kwargs):\n\treturn pd.read_feather(fn, **kwargs)","def load_data():\n d = load_wine()\n data = {colname: d.data[:, i] for i, colname in enumerate(d.feature_names)}\n data[\"target\"] = d.target\n return pd.DataFrame(data)","def _get_data(self):\n raise NotImplementedError()","def _loadData(self, data):\n Movie._loadData(self, data)\n PlexHistory._loadData(self, data)","def loadDataOrig(df, path, im_shape, disp_names=False):\r\n X, y = [], []\r\n for i, item in df.iterrows():\r\n if disp_names == True:\r\n print('i={} {} {}\\n'.format(i, path + item[0], path + item[1]))\r\n img = io.imread(path + item[0])\r\n img = transform.resize(img, im_shape, mode='constant')\r\n img = np.expand_dims(img, -1)\r\n mask = io.imread(path + item[1])\r\n mask = transform.resize(mask, im_shape, mode='constant')\r\n mask = np.expand_dims(mask, -1)\r\n X.append(img)\r\n y.append(mask)\r\n break\r\n X = np.array(X)\r\n y = np.array(y)\r\n\r\n if disp_names == True:\r\n print('X/shape={} y.shape={}\\n'.format(X.shape, y.shape))\r\n\r\n X -= X.mean()\r\n X /= X.std()\r\n\r\n if disp_names == True:\r\n print('### Data loaded')\r\n print('\\t{}'.format(path))\r\n print('\\t{}\\t{}'.format(X.shape, y.shape))\r\n # print( '\\tX:{:.1f}-{:.1f}\\ty:{:.1f}-{:.1f}\\n'.format(X.min(), X.max(), y.min(), y.max()) )\r\n print('\\tX.mean = {}, X.std = {}'.format(X.mean(), X.std()))\r\n print('\\n')\r\n\r\n return X, y","def read_file(fname: str) -> pd.DataFrame:\n raw_data = (\n pd.read_hdf(fname).to_frame().reset_index(level=[0, 1]).loc[ANALYSIS_DATE]\n )\n raw_data[\"date\"] = raw_data.index\n return raw_data","def get_fli_data_object(evt, src):\n o = evt.get(_psana.Fli.FrameV1, src)\n if o is not None: return o\n\n return None","def as_dframe(cls, dataset):\n return dataset.dframe()","def __local_df(soup):\n return __get_local_g1_news(soup)","def __local_df(soup):\n return __get_local_g1_news(soup)","def load(fnames, tag=None, inst_id=None):\n\n if not fnames:\n print('fnames are go')\n warnings.warn('You no got no fname, you no get no data')\n return pysat.DataFrame(None), pysat.Meta(None)\n elif len(fnames) == 1:\n print('fnames are greater than 1')\n meta = pysat.Meta()\n signal_meta = pysat.Meta()\n\n # load the rinex\n data = gr.load(fnames[0])\n # get the metadata from the xarray.Dataset\n xr_attrs = data.attrs\n # format the metadata\n# for at in xr_attrs:\n# print(type(at))\n# meta[at] = {'units': '', 'long_name': at}\n# keys = data.data_vars.keys()\n# for key in keys:\n# # find the xarray equivalents of units and long_name\n# print(key)\n# signal_meta[key] = {meta.labels.units: var_units[key][0],\n# meta.labels.name: var_units[key][1]}\n# # format the data\n# meta['signals'] = signal_meta\n# output = data.variables\n return data, meta\n else:\n raise ValueError('Only one filename currently supported')\n print('no idea wahts goin on')","def load_data(READFILE,load_type=1):\n df = pd.read_csv(READFILE)\n if 'type' in df.columns and load_type is not None:\n df = pd.DataFrame(df[df.type==1])\n df = df.drop('type',axis=1)\n return df","def load(self):\n data = pandas.read_csv(self.path, names=self.names)\n return data","def read(name, db):\n \n # Make connection with the database\n\tconn = sqlite3.connect(db)\n\tdf = pd.read_sql_query(\"select * from \" + name + ';', conn)\n \n # Print loaded data table name and return DataFrame\n\tprint(name + ': loaded')\n\treturn df","def dataFrame(self):\n\n memory_file = StringIO(initial_value=self.sparql_result.decode('utf-8'), newline='\\n')\n reader = DictReader(memory_file)\n\n schema = StructType(\n list(map(lambda f: StructField(f, StringType()), reader.fieldnames))\n )\n\n data = list(map(lambda d: [d[f] for f in reader.fieldnames], list(reader)))\n\n return self.spark.createDataFrame(data, schema)","def __load( self, raw_content ):\n return( pd.read_excel( BytesIO( raw_content ) ) )","def get_data():\n pass","def dataframe(self):\n return self._df","def get_frame_at_index(self, index):\n begin = index\n end = begin + self.frame_size\n\n if begin < 0:\n return self.data\n\n return self.data[begin:end]"],"string":"[\n \"def load_data(self):\",\n \"def load_data(self) -> None:\",\n \"def _get_raw_data(self, idx=0):\\n # Get the time step then make a data frame\\n raise NotImplementedError('Code me up!')\\n #data = self._data[???]\\n return data\",\n \"def dataframe(self):\\n\\t\\treturn self._dataframe\",\n \"def dataframe(self):\\n frames = []\\n for game in self.__iter__():\\n df = game.dataframe\\n if df is not None:\\n frames.append(df)\\n if frames == []:\\n return None\\n return pd.concat(frames)\",\n \"def __init__(self, dataFrame):\\n self.dataFrame = dataFrame\",\n \"def dataFrame(self):\\n return self._dataFrame\",\n \"def get_frame_data(self):\\n # FrameObject is a dictionary of slot names and values.\\n frameObject = self.pgdb.sendPgdbFnCall('get-frame-object', self.frameid)\\n if not frameObject:\\n raise PythonCycError(\\\"Could not retrieve frame \\\"+self.frameid+\\\" from organism (orgid) \\\"+self.pgdb._orgid)\\n else:\\n self._gotframe = True\\n # Modify slot names to allow Python's syntax (e.g., '_' instead of '-').\\n for slot in frameObject:\\n self.__dict__[convertLispIdtoPythonId(slot)] = frameObject[slot]\\n return self\",\n \"def load_dataframe(self, path, type_='raw'):\\r\\n if type_ == 'raw':\\r\\n return pd.read_csv(path).to_numpy()[:, 1]\\r\\n elif type_ == 'features':\\r\\n return pd.read_csv(path, sep=' ', header=None).to_numpy()\\r\\n else:\\r\\n raise Exception(\\\"No type found!\\\")\",\n \"def get_data(self)->pd.DataFrame:\\n pass\",\n \"def data_frame(self, arg=None):\\n if arg is None:\\n return pl.DataFrame()\\n if isinstance(arg, pl.DataFrame):\\n return arg\\n if isinstance(arg, pl.LazyFrame):\\n return arg.collect()\\n return pl.DataFrame(arg)\",\n \"def getDataframe(self):\\n self._loadCSVFile()\\n self._cleanProcessDf()\\n return self._df\",\n \"def load_own_data():\\n data = Data()\\n features = data.read_selected_features()\\n dataframe = data.get_dataframe_with(features)\\n return normalize(dataframe.values)\",\n \"def __load( self, raw_content ):\\n return( pd.read_csv( BytesIO( raw_content ) ) )\",\n \"def load():\\n return load_pandas()\",\n \"def __data_frame(self):\\n return self._trajectory\",\n \"def _data_frame(content):\\n response = loads(content)\\n key = [x for x in response.keys() if x in c.response_data][0]\\n frame = DataFrame(response[key])\\n final_frame = _convert(frame)\\n return final_frame\",\n \"def dataframe_extended(self):\\n frames = []\\n for game in self.__iter__():\\n df = game.dataframe_extended\\n if df is not None:\\n frames.append(df)\\n if frames == []:\\n return None\\n return pd.concat(frames)\",\n \"def dataframe(self):\\n return self.generator.dataframe\",\n \"def load_data(self):\\n raise NotImplementedError()\",\n \"def data(self):\\n return self._frame.copy(deep=True)\",\n \"def load_data_frame(name):\\n\\n return DataFrame(name).load()\",\n \"def _read_data(self):\",\n \"def read(self, fname, frame=None):\\n\\n self.resetvals()\\n url = urlparse(fname)\\n if not self.url:\\n self.url = url\\n# if frame:\\n# self.hdf5_location.set_index(frame)\\n self.filename = self.url.path\\n if os.path.isfile(self.filename):\\n self.hdf5 = h5py.File(self.filename, \\\"r\\\")\\n else:\\n error = \\\"No such file or directory: %s\\\" % self.filename\\n logger.error(error)\\n raise RuntimeError(error)\\n self.ds = self.hdf5[self.url.query]\\n if isinstance(self.ds, h5py.Group) and (\\\"data\\\" in self.ds):\\n self.ds = self.ds[\\\"data\\\"]\\n\\n if self.url.fragment:\\n slices = self.get_slice()\\n self.data = self.ds[self.get_slice()]\\n self.nframes = self.ds.shape[self.main_dim]\\n else:\\n self.data = self.ds[:]\\n self.nframes = 1\\n self.dim2, self.dim1 = self.data.shape\\n self.bytecode = str(self.data.dtype)\\n return self\",\n \"def load_data(self):\\n return self._load_data\",\n \"def _load_data(self):\\n\\n if not self._cache.exists(config.DATAFRAME_SONG_DATA):\\n source_path = os.path.join(config.S3_SONG_DATA, 'A/A/A/*.json') # Note: song database is way big, so we get only a slice of it.\\n dataframe = self._get_spark_session().read.json(source_path)\\n self._cache.set_source(config.DATAFRAME_SONG_DATA, dataframe)\",\n \"def post_load(self, data):\\n return data\",\n \"def loader():\\n bucket = data_load_variables[\\\"bucket\\\"]\\n\\n if data_load_variables[\\\"use_lite_dataset\\\"]:\\n dataset_name = data_load_variables[\\\"lite_dataset_name\\\"]\\n else:\\n dataset_name = data_load_variables[\\\"dataset_name\\\"]\\n\\n s3 = boto3.client('s3')\\n\\n obj = s3.get_object(Bucket=bucket, Key=dataset_name)\\n # get object and file (key) from bucket\\n\\n df = pd.read_csv(obj['Body'])\\n return df\",\n \"def test_frame_to_rows(self):\\n pass\",\n \"def load_data():\\n dictionary = corpora.Dictionary.load(app.config['DICTIONARY'])\\n matrix = similarities.MatrixSimilarity.load(app.config['MATRIX'])\\n model = models.LsiModel.load(app.config['MODEL'])\\n df = pd.read_pickle(app.config['DATA_FRAME'])\\n return Data(matrix=matrix, model=model, dictionary=dictionary, data_frame=df)\",\n \"def getDataFrame(self):\\n return self.df\",\n \"def _get_data(self):\\n project_name, experiment_id = self.parent._get_parent_identifiers()\\n\\n self._data = self.repository.get_dataframe_data(\\n project_name, self.id, experiment_id=experiment_id\\n )\",\n \"def _load_data(self, comp=None):\\n\\t\\tif comp is None:\\n\\t\\t\\tcomp = self._compensation\\n\\t\\tmatrix = self._fcsfile.read_data(fmt='matrix',\\n\\t\\t\\tcomp=comp)\\n\\t\\treturn pd.DataFrame(matrix, columns=self._channels)\",\n \"def load(self):\",\n \"def load_from_open_file(self, df):\\n df.seek(self.pos_start)\\n self.data = df.read(self.length).decode('latin1').splitlines()\\n self.loaded = True\\n return self.data\",\n \"def _get_frame_data(self):\\n\\n def _text_formatting(bs4_tag):\\n \\\"\\\"\\\"Simple formatting that will be called a lot\\\"\\\"\\\"\\n return bs4_tag.get_text().replace('\\\\n', '')\\n\\n tables = Character._get_main_page(self._fd).find_all('table', {'class': 'wikitable'})\\n result = {}\\n for table in tables:\\n rows = table.find_all('tr')\\n for row in rows:\\n move = row.find('th')\\n\\n if move is not None:\\n move_small = move.find('small')\\n else:\\n continue\\n\\n if move_small is not None:\\n move_name = move.get_text().replace(move_small.get_text(), ' ' + move_small.get_text()).replace(\\n '\\\\n', '')\\n else:\\n move_name = _text_formatting(move)\\n\\n move_name = move_name.replace('+', '') # B+C fix\\n fd = row.find_all('td')\\n\\n try:\\n result.update({\\n move_name: {\\n \\\"Damage\\\": _text_formatting(fd[0]),\\n \\\"Cancel\\\": _text_formatting(fd[1]),\\n \\\"Attribute\\\": _text_formatting(fd[4]),\\n \\\"Guard\\\": _text_formatting(fd[5]),\\n \\\"Startup\\\": _text_formatting(fd[6]),\\n \\\"Active\\\": _text_formatting(fd[7]),\\n \\\"Recovery\\\": _text_formatting(fd[8]),\\n \\\"Frame Adv\\\": _text_formatting(fd[9]),\\n \\\"Blockstun\\\": _text_formatting(fd[11]),\\n \\\"Invul/GP\\\": _text_formatting(fd[19])\\n }\\n })\\n except (AttributeError, IndexError):\\n continue\\n\\n return result\",\n \"def _load_df_or_array(self, key: str, idx: Union[None, np.ndarray] = None) -> Union[pd.DataFrame, np.ndarray]:\\n if key == self.actions_key:\\n if idx is None:\\n data = pd.read_hdf(self.path, key=key)\\n else:\\n data = pd.read_hdf(self.path, key=key, where=idx)\\n else:\\n with h5py.File(self.path, 'r') as f:\\n if idx is None:\\n data = f[key][...]\\n else:\\n data = f[key][idx, ...]\\n\\n return data\",\n \"def get_frame(freq: str):\\n url = 'http://minikep-db.herokuapp.com/api/frame?freq={}'.format(freq)\\n return pd.read_csv(url, converters={0: pd.to_datetime}, index_col=0)\",\n \"def test_dataframe(self):\\n\\n url=\\\"http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data\\\"\\n readerobject=requester.url_to_df(url)\\n self.assertIsInstance(readerobject,pd.DataFrame)\",\n \"def process_frame(self, frame):\\n\\t\\treturn frame\",\n \"def __init__(self, df):\\n self.data = df\",\n \"def load_data(filename) :\\r\\n data = Data()\\r\\n data.load(filename)\\r\\n return data\",\n \"def load() -> DataFrame:\\n return load_file(__file__, \\\"default.csv.gz\\\")\",\n \"def glass_pandas(self):\\n # pandas.set_option('display.width', 120)\\n # TODO timeit (git_implementation) vs (my_implementation)\\n # * df = pd.DataFrame(json.loads(r.text))\\n # * df = df.set_index('t')\\n # * df.index = pd.to_datetime(df.index, unit='s')\\n # * df = df.sort_index()\\n # * s = df.v\\n # * s.name = '_'.join(url.split('/')[-2:])\\n # * return s\\n # for elem in self.loaded:\\n # _metric, _data = elem[1]['_metrics'], elem[1]['_data']\\n # try:\\n # frame_keys = ['t'] + list(_data[0]['o'].keys())\\n # framed = pandas.DataFrame(\\n # data=[{k: (_data[iters]['t'] if k in 't' else _data[iters]['o'][k])\\n # for k in frame_keys} for iters in range(len(_data))],\\n # columns=frame_keys)\\n # except KeyError:\\n # framed = pandas.DataFrame(_data)\\n # framed.set_index('t', inplace=True)\\n # framed.index = pandas.to_datetime(\\n # framed.index.to_flat_index(), unit='s', infer_datetime_format=True)\\n # framed.sort_index(inplace=True)\\n # framed.name = _metric\\n # print(framed.name)\\n # print(framed)\",\n \"def load_vox(data: pd.DataFrame, in_place: bool = False):\\n if not in_place:\\n mod = data.copy()\\n else:\\n mod = data\\n clips = []\\n channels = []\\n samplerates = []\\n durations = []\\n for i, row in mod.iterrows():\\n sys.stdout.write(f\\\"\\\\r[-] Reading: {i} of {len(mod)} ({i / len(mod) * 100: .2f}%)\\\")\\n sys.stdout.flush()\\n with audioread.audio_open(row['file']) as f:\\n channels.append(f.channels)\\n samplerates.append(f.samplerate)\\n durations.append(f.duration)\\n data = bytearray()\\n for buf in f:\\n data = data + buf\\n clips.append(data)\\n sys.stdout.write(f\\\"\\\\r[ ] Read {len(mod)} files into DataFrame.\\\\r\\\\n\\\")\\n sys.stdout.flush()\\n mod['audio'] = pd.Series(clips)\\n mod['channels'] = pd.Series(channels)\\n mod['samplerate'] = pd.Series(samplerates)\\n mod['duration'] = pd.Series(durations)\\n return mod\",\n \"def get_data(self):\",\n \"def load_data():\\n #read from S3\\n df_obs = pd.read_csv('https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/df_obs.csv')\\n df_sen = pd.read_csv('https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/df_sentry.csv')\\n \\n \\n #background image to be used\\n img_url = 'https://nadim-kawwa-dota-bucket.s3.us-west-2.amazonaws.com/map_detailed_723.jpeg'\\n img_response = requests.get(img_url)\\n img = Image.open(BytesIO(img_response.content))\\n \\n \\n #apply translation of coordinates\\n df_obs['x'] = df_obs['x'] - 64\\n df_obs['y'] = df_obs['y'] - 64\\n df_sen['x'] = df_sen['x'] - 64\\n df_sen['y'] = df_sen['y'] - 64\\n\\n #convert time to minutes\\n df_obs['time'] = df_obs['time']/60\\n df_sen['time'] = df_sen['time']/60\\n\\n \\n return df_obs, df_sen, img\",\n \"def data(self):\\n return self.as_named_DataFrame()\",\n \"def extract(self) -> pd.core.frame.DataFrame:\\n pass\",\n \"def read(self):\\n\\n if self.filename.endswith(\\\".pkl\\\"):\\n logging.debug(\\\"Loading pickle file %s\\\", self.filename)\\n data = pd.read_pickle(self.filename)\\n\\n elif self.filename.endswith(\\\".hdf5\\\"):\\n logging.debug(\\\"Loading HDF5 file %s\\\", self.filename)\\n with h5py.File(self.filename, \\\"r\\\") as data_file:\\n\\n data = pd.DataFrame(\\n {\\n column: data_file[\\\"/haloTrees/%s\\\" % column].value\\n for column in self.columns\\n }\\n ).set_index(\\\"nodeIndex\\\")\\n\\n # with open(\\\"./data/cache.pkl\\\", \\\"w\\\") as pickle_file:\\n # data.to_pickle(pickle_file)\\n\\n else:\\n raise TypeError(\\\"Unknown filetype %s\\\" % self.filename)\\n\\n return data\",\n \"def data_frame_creator(self):\\n\\n rgb_dir = [\\n self.dataset_address + sequence_f + rgb_f\\n for rgb_f in self.rgb_folder for sequence_f in self.sequence_folder\\n ]\\n rgb_data = [\\n rgb_d + rgb for rgb_d in rgb_dir for rgb in os.listdir(rgb_d)\\n ]\\n\\n depth_dir = [\\n self.dataset_address + sequence_f + depth_f\\n for depth_f in self.depth_folder\\n for sequence_f in self.sequence_folder\\n ]\\n depth_data = [\\n depth_d + depth for depth_d in depth_dir\\n for depth in os.listdir(depth_d)\\n ]\\n\\n segmentation_dir = [\\n self.dataset_address + sequence_f + segmentation_f\\n for segmentation_f in self.segmentation_folder\\n for sequence_f in self.sequence_folder\\n ]\\n segmentation_data = [\\n segmentation_d + segmentation\\n for segmentation_d in segmentation_dir\\n for segmentation in os.listdir(segmentation_d)\\n ]\\n\\n dataset = {\\n 'RGB': rgb_data,\\n 'DEPTH': depth_data,\\n 'SEGMENTATION': segmentation_data\\n }\\n\\n if self.shuffle:\\n return pd.DataFrame(dataset).sample(frac=1)\\n\\n return pd.DataFrame(dataset)\",\n \"def data_specific_processing(self, dataframe):\\n return dataframe\",\n \"def load_data(dataset_path: str):\\n data = arff.loadarff(dataset_path)\\n data_frame = pd.DataFrame(data[0])\\n return data_frame\",\n \"def intialize_source():\\n raw = loadmat(\\\"p300backrec2.mat\\\")\\n channels_raw = raw['channels']\\n channels = []\\n for i in channels_raw[0]:\\n channels.extend(list(i))\\n X = raw['data']\\n marker = raw['marker']\\n return X,channels,marker\",\n \"def process_frames(self, data):\\n pass\",\n \"def process_frames(self, data):\\n pass\",\n \"def process_frames(self, data):\\n pass\",\n \"def process_frames(self, data):\\n pass\",\n \"def process_frames(self, data):\\n pass\",\n \"def get_frame(self, row):\\n\\n if row not in self.frames:\\n if not self.write:\\n d = self.memmap[row, :, :]\\n if self.file.metadata['interleave'] == 'bil':\\n d = d.T\\n self.frames[row] = d.copy()\\n else:\\n self.frames[row] = s.nan * s.zeros((self.n_cols, self.n_bands))\\n return self.frames[row]\",\n \"def get_frame(self, ind):\\n pass\",\n \"def get_frame(self, f):\\n return self._frames[f, :]\",\n \"def load(self) -> pd.DataFrame:\\n if os.path.exists(self.file_name):\\n df = pd.read_csv(self.file_name, index_col=0)\\n df = self._clean(df)\\n else:\\n _LOG.debug(\\\"No file '%s'\\\", self.file_name)\\n df = pd.DataFrame()\\n return df\",\n \"def sourceToDataframe(self):\\n df = pd.read_excel(self.filename)\\n df.columns = df.iloc[10]\\n df = df.drop(df.index[:11])\\n self.df = df #makes this df accessible to the whole class now\\n self.insertODN()\\n display(df.head())\",\n \"def _load(self):\\n # Extract the ASCII header (5 first lines)\\n with open(self._xst_bin, 'rb') as f:\\n header = list(islice(f, 0, 5))\\n assert header[0] == b'HeaderStart\\\\n',\\\\\\n 'Wrong header start'\\n assert header[-1] == b'HeaderStop\\\\n',\\\\\\n 'Wrong header stop'\\n header = [s.decode('utf-8') for s in header]\\n hd_size = sum([len(s) for s in header])\\n\\n # Parse informations into a metadata dictionnary\\n keys = ['freq', 'ma', 'accu']\\n search = ['Freq.List', 'Mr.List', 'accumulation']\\n types = ['float64', 'int', 'int']\\n for key, word, typ in zip(keys, search, types):\\n for h in header:\\n if word in h:\\n self.meta[key] = np.array(\\n h.split('=')[1].split(','),\\n dtype=typ\\n )\\n\\n # Deduce the dtype for decoding\\n n_ma = self.meta['ma'].size\\n n_sb = self.meta['freq'].size\\n dtype = np.dtype(\\n [('jd', 'float64'),\\n ('data', 'complex64', (n_sb, n_ma*n_ma*2 + n_ma))]\\n )\\n\\n # Decoding the binary file\\n tmp = np.memmap(\\n filename=self._xst_bin,\\n dtype='int8',\\n mode='r',\\n offset=hd_size\\n )\\n decoded = tmp.view(dtype)\\n\\n self.data = decoded['data'] / self.meta['accu']\\n self.time = Time(decoded['jd'], format='jd', precision=0)\\n\\n return\",\n \"def load_processed_data(animal, name, arguments):\\r\\n\\tpath = os.path.join(paths.path2Output, animal, str(arguments['Function']), \\r\\n\\t\\t\\t\\t\\t\\tstr(arguments['Init']), str(arguments['Rank']), name)\\r\\n\\t\\r\\n\\tmeta_df = pd.read_csv(os.path.join(path,'meta_df.csv'))\\r\\n\\troi_tensor = np.load(os.path.join(path,'roi_tensor.npy'))\\r\\n\\tacti = np.load(os.path.join(path,'acti.npy'))\\r\\n\\tnorm_acti = np.load(os.path.join(path,'norm_acti.npy'))\\r\\n\\tsmoothed_acti = np.load(os.path.join(path,'smoothed_acti.npy'))\\r\\n\\r\\n\\r\\n\\treturn meta_df, roi_tensor, acti, norm_acti, smoothed_acti\",\n \"def read_frame(self):\\n return self.decode_frame(self.grab_frame())\",\n \"def load_data(self, data):\\n\\n if type(data) is \\\"json\\\":\\n dataF = pd.read_json(data)\\n elif type(data) is list:\\n dataF = pd.DataFrame(data)\\n else:\\n print(\\\"Other types not implemented\\\")\\n return\\n dataF = self.__process_data(dataF)\\n self.__dataF = dataF\",\n \"def __load( self, json_blob ):\\n return pd.read_json( json_blob, orient='split' )\",\n \"def dataframe_extended(self):\\n return self.boxscore.dataframe\",\n \"def load_from_database(filename,key):\\n\\t# Opening file\\n\\tstore = pd.HDFStore(filename)\\n\\t# getting the df\\n\\tdata = store[key]\\n\\t# And its metadata\\n\\tmetadata = store.get_storer(key).attrs.metadata\\n\\tstore.close()\\n\\t# Ok returning the data now\\n\\treturn data, metadata\",\n \"def loadFringe(self, frame=1, filename=None):\\n self.currentFrame = np.int(frame)\\n if filename:\\n ofdPath = filename\\n else:\\n ofdPath = os.path.join(self.directory, self.basename +'.ofd')\\n\\n self.getOfdInfo(ofdPath)\\n\\n if self.mode == '2channel':\\n self.load2Channel()\\n if self.mode == '1channel':\\n self.load1Channel()\\n if self.mode == 'mmap2channel':\\n self.mmap2channel()\\n if self.mode == 'mmap1channel':\\n self.mmap1channel()\",\n \"def load_data_part(fname):\\n if \\\"_data\\\" not in fname:\\n return None\\n # Read data\\n data = pd.read_csv(fname)\\n # events file\\n events_fname = fname.replace('_data', '_events')\\n # read event file\\n labels = pd.read_csv(events_fname)\\n clean = data.drop(['id'], axis=1) # remove id\\n labels = labels.drop(['id'], axis=1) # remove id\\n return clean, labels\",\n \"def forward(self, raw_X):\\n return make_df(raw_X, self.features)\",\n \"def data_frame_creator(self):\\n sequence_folder = [\\n '/SEQ1', '/SEQ2', '/SEQ3', '/SEQ4', '/SEQ5', '/SEQ6'\\n ]\\n rgb_folder = ['/RGBLeft/', '/RGBRight/']\\n depth_folder = ['/DepthLeft/', '/DepthRight/']\\n segmentation_folder = ['/GTLeft/', '/GTright/']\\n rgb_dir = [\\n self.dataset_dir + sequence_f + rgb_f for rgb_f in rgb_folder\\n for sequence_f in sequence_folder\\n ]\\n rgb_data = [\\n rgb_d + rgb for rgb_d in rgb_dir for rgb in os.listdir(rgb_d)\\n ]\\n\\n depth_dir = [\\n self.dataset_dir + sequence_f + depth_f\\n for depth_f in depth_folder\\n for sequence_f in sequence_folder\\n ]\\n depth_data = [\\n depth_d + depth for depth_d in depth_dir\\n for depth in os.listdir(depth_d)\\n ]\\n\\n segmentation_dir = [\\n self.dataset_dir + sequence_f + segmentation_f\\n for segmentation_f in segmentation_folder\\n for sequence_f in sequence_folder\\n ]\\n segmentation_data = [\\n segmentation_d + segmentation\\n for segmentation_d in segmentation_dir\\n for segmentation in os.listdir(segmentation_d)\\n ]\\n\\n dataset = {\\n 'RGB': rgb_data,\\n 'DEPTH': depth_data,\\n 'SEGMENTATION': segmentation_data\\n }\\n\\n if self.shuffle:\\n return pd.DataFrame(dataset).sample(frac=1, random_state=123)\\n\\n return pd.DataFrame(dataset)\",\n \"def load(self):\\n\\n\\t\\t# Check if dataset location exists\\n\\t\\tif (not os.path.exists(self._location)):\\n\\t\\t\\tprint(\\\"Error: Dataset location does not exist\\\")\\n\\t\\t\\treturn\\n\\n\\t\\tself._frames = sorted(glob.glob(self._location + '/frame*.jpg'))\\n\\n\\t\\t# Check if startFrame is beyond dataset bounds\\n\\t\\tif (self._startFrame > len(self._frames)):\\n\\t\\t\\tprint(\\\"Error: Start frame is beyond dataset bounds\\\")\\n\\t\\t\\treturn\\n\\n\\t\\t# Check if endFrame is beyond dataset bounds\\n\\t\\tif (self._endFrame > len(self._frames)):\\n\\t\\t\\tprint(\\\"Warning: End frame beyond dataset bounds, setting to end of dataset\\\")\\n\\n\\t\\t# Start buffering threads\\n\\t\\tself._bufferThreadStopped = False\\n\\t\\tself._bufferingThread.start()\",\n \"def record_data_frame(self):\\n return self._record.data_frame\",\n \"def _load_data(data, n_prev=3):\\n docX, docY = [], []\\n for i in range(len(data)-n_prev):\\n docX.append(data.data.iloc[i:i+n_prev])\\n docY.append(data.response.iloc[i+n_prev]) \\n\\n alsX = np.array(docX)\\n alsY = np.array(docY)\\n return np.matrix(alsX), np.matrix(alsY).T\",\n \"def dataframe(self):\\n return self.get_target().dataframe()\",\n \"def _setup_dataframe(self, serie, metadata=None):\\n header = self.get_data_header(serie, dataset='cnv')\\n df = self.get_data_in_frame(serie, header, dataset='cnv')\\n df = self.df_handler.map_column_names_of_dataframe(df)\\n\\n return df\",\n \"def get_frame(self, index):\\n filename = self.get_filename(index)\\n return plt.imread(fname=filename)\",\n \"def get_zyla_data_object(evt, src):\\n o = evt.get(_psana.Zyla.FrameV1, src)\\n if o is not None: return o\\n\\n return None\",\n \"def _dataframe_from_feather(fn, **kwargs):\\n\\treturn pd.read_feather(fn, **kwargs)\",\n \"def load_data():\\n d = load_wine()\\n data = {colname: d.data[:, i] for i, colname in enumerate(d.feature_names)}\\n data[\\\"target\\\"] = d.target\\n return pd.DataFrame(data)\",\n \"def _get_data(self):\\n raise NotImplementedError()\",\n \"def _loadData(self, data):\\n Movie._loadData(self, data)\\n PlexHistory._loadData(self, data)\",\n \"def loadDataOrig(df, path, im_shape, disp_names=False):\\r\\n X, y = [], []\\r\\n for i, item in df.iterrows():\\r\\n if disp_names == True:\\r\\n print('i={} {} {}\\\\n'.format(i, path + item[0], path + item[1]))\\r\\n img = io.imread(path + item[0])\\r\\n img = transform.resize(img, im_shape, mode='constant')\\r\\n img = np.expand_dims(img, -1)\\r\\n mask = io.imread(path + item[1])\\r\\n mask = transform.resize(mask, im_shape, mode='constant')\\r\\n mask = np.expand_dims(mask, -1)\\r\\n X.append(img)\\r\\n y.append(mask)\\r\\n break\\r\\n X = np.array(X)\\r\\n y = np.array(y)\\r\\n\\r\\n if disp_names == True:\\r\\n print('X/shape={} y.shape={}\\\\n'.format(X.shape, y.shape))\\r\\n\\r\\n X -= X.mean()\\r\\n X /= X.std()\\r\\n\\r\\n if disp_names == True:\\r\\n print('### Data loaded')\\r\\n print('\\\\t{}'.format(path))\\r\\n print('\\\\t{}\\\\t{}'.format(X.shape, y.shape))\\r\\n # print( '\\\\tX:{:.1f}-{:.1f}\\\\ty:{:.1f}-{:.1f}\\\\n'.format(X.min(), X.max(), y.min(), y.max()) )\\r\\n print('\\\\tX.mean = {}, X.std = {}'.format(X.mean(), X.std()))\\r\\n print('\\\\n')\\r\\n\\r\\n return X, y\",\n \"def read_file(fname: str) -> pd.DataFrame:\\n raw_data = (\\n pd.read_hdf(fname).to_frame().reset_index(level=[0, 1]).loc[ANALYSIS_DATE]\\n )\\n raw_data[\\\"date\\\"] = raw_data.index\\n return raw_data\",\n \"def get_fli_data_object(evt, src):\\n o = evt.get(_psana.Fli.FrameV1, src)\\n if o is not None: return o\\n\\n return None\",\n \"def as_dframe(cls, dataset):\\n return dataset.dframe()\",\n \"def __local_df(soup):\\n return __get_local_g1_news(soup)\",\n \"def __local_df(soup):\\n return __get_local_g1_news(soup)\",\n \"def load(fnames, tag=None, inst_id=None):\\n\\n if not fnames:\\n print('fnames are go')\\n warnings.warn('You no got no fname, you no get no data')\\n return pysat.DataFrame(None), pysat.Meta(None)\\n elif len(fnames) == 1:\\n print('fnames are greater than 1')\\n meta = pysat.Meta()\\n signal_meta = pysat.Meta()\\n\\n # load the rinex\\n data = gr.load(fnames[0])\\n # get the metadata from the xarray.Dataset\\n xr_attrs = data.attrs\\n # format the metadata\\n# for at in xr_attrs:\\n# print(type(at))\\n# meta[at] = {'units': '', 'long_name': at}\\n# keys = data.data_vars.keys()\\n# for key in keys:\\n# # find the xarray equivalents of units and long_name\\n# print(key)\\n# signal_meta[key] = {meta.labels.units: var_units[key][0],\\n# meta.labels.name: var_units[key][1]}\\n# # format the data\\n# meta['signals'] = signal_meta\\n# output = data.variables\\n return data, meta\\n else:\\n raise ValueError('Only one filename currently supported')\\n print('no idea wahts goin on')\",\n \"def load_data(READFILE,load_type=1):\\n df = pd.read_csv(READFILE)\\n if 'type' in df.columns and load_type is not None:\\n df = pd.DataFrame(df[df.type==1])\\n df = df.drop('type',axis=1)\\n return df\",\n \"def load(self):\\n data = pandas.read_csv(self.path, names=self.names)\\n return data\",\n \"def read(name, db):\\n \\n # Make connection with the database\\n\\tconn = sqlite3.connect(db)\\n\\tdf = pd.read_sql_query(\\\"select * from \\\" + name + ';', conn)\\n \\n # Print loaded data table name and return DataFrame\\n\\tprint(name + ': loaded')\\n\\treturn df\",\n \"def dataFrame(self):\\n\\n memory_file = StringIO(initial_value=self.sparql_result.decode('utf-8'), newline='\\\\n')\\n reader = DictReader(memory_file)\\n\\n schema = StructType(\\n list(map(lambda f: StructField(f, StringType()), reader.fieldnames))\\n )\\n\\n data = list(map(lambda d: [d[f] for f in reader.fieldnames], list(reader)))\\n\\n return self.spark.createDataFrame(data, schema)\",\n \"def __load( self, raw_content ):\\n return( pd.read_excel( BytesIO( raw_content ) ) )\",\n \"def get_data():\\n pass\",\n \"def dataframe(self):\\n return self._df\",\n \"def get_frame_at_index(self, index):\\n begin = index\\n end = begin + self.frame_size\\n\\n if begin < 0:\\n return self.data\\n\\n return self.data[begin:end]\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.66847086","0.66500604","0.6578558","0.6544992","0.6464981","0.6419371","0.63444304","0.6261828","0.62608165","0.6257387","0.61691505","0.613629","0.60970247","0.6049352","0.60232645","0.5995074","0.59805757","0.59766096","0.597535","0.59465176","0.5939186","0.5932176","0.5902538","0.58966756","0.5876167","0.58689326","0.58581334","0.58453465","0.5839027","0.5837447","0.58229446","0.58174896","0.5816866","0.5813475","0.5774821","0.5755608","0.57537633","0.57523316","0.5736286","0.5728476","0.5725325","0.5720987","0.5719652","0.57161677","0.57101476","0.57099634","0.57010764","0.5689209","0.56681216","0.56632763","0.56627995","0.5658984","0.56528586","0.5645935","0.5641005","0.5641005","0.5641005","0.5641005","0.5641005","0.5640627","0.56400913","0.56390923","0.5629359","0.5626899","0.56220907","0.56153417","0.5609219","0.56051147","0.56032515","0.55935735","0.5593448","0.5587989","0.5583714","0.55716944","0.5569482","0.5569335","0.55643743","0.55611104","0.55578494","0.55501956","0.5540802","0.5539357","0.5531822","0.5530565","0.5525389","0.55190265","0.5513765","0.5509492","0.55082047","0.5504479","0.5503329","0.5503329","0.5502208","0.54996043","0.5496846","0.54947937","0.54923546","0.5490945","0.54797804","0.54795164","0.54779416"],"string":"[\n \"0.66847086\",\n \"0.66500604\",\n \"0.6578558\",\n \"0.6544992\",\n \"0.6464981\",\n \"0.6419371\",\n \"0.63444304\",\n \"0.6261828\",\n \"0.62608165\",\n \"0.6257387\",\n \"0.61691505\",\n \"0.613629\",\n \"0.60970247\",\n \"0.6049352\",\n \"0.60232645\",\n \"0.5995074\",\n \"0.59805757\",\n \"0.59766096\",\n \"0.597535\",\n \"0.59465176\",\n \"0.5939186\",\n \"0.5932176\",\n \"0.5902538\",\n \"0.58966756\",\n \"0.5876167\",\n \"0.58689326\",\n \"0.58581334\",\n \"0.58453465\",\n \"0.5839027\",\n \"0.5837447\",\n \"0.58229446\",\n \"0.58174896\",\n \"0.5816866\",\n \"0.5813475\",\n \"0.5774821\",\n \"0.5755608\",\n \"0.57537633\",\n \"0.57523316\",\n \"0.5736286\",\n \"0.5728476\",\n \"0.5725325\",\n \"0.5720987\",\n \"0.5719652\",\n \"0.57161677\",\n \"0.57101476\",\n \"0.57099634\",\n \"0.57010764\",\n \"0.5689209\",\n \"0.56681216\",\n \"0.56632763\",\n \"0.56627995\",\n \"0.5658984\",\n \"0.56528586\",\n \"0.5645935\",\n \"0.5641005\",\n \"0.5641005\",\n \"0.5641005\",\n \"0.5641005\",\n \"0.5641005\",\n \"0.5640627\",\n \"0.56400913\",\n \"0.56390923\",\n \"0.5629359\",\n \"0.5626899\",\n \"0.56220907\",\n \"0.56153417\",\n \"0.5609219\",\n \"0.56051147\",\n \"0.56032515\",\n \"0.55935735\",\n \"0.5593448\",\n \"0.5587989\",\n \"0.5583714\",\n \"0.55716944\",\n \"0.5569482\",\n \"0.5569335\",\n \"0.55643743\",\n \"0.55611104\",\n \"0.55578494\",\n \"0.55501956\",\n \"0.5540802\",\n \"0.5539357\",\n \"0.5531822\",\n \"0.5530565\",\n \"0.5525389\",\n \"0.55190265\",\n \"0.5513765\",\n \"0.5509492\",\n \"0.55082047\",\n \"0.5504479\",\n \"0.5503329\",\n \"0.5503329\",\n \"0.5502208\",\n \"0.54996043\",\n \"0.5496846\",\n \"0.54947937\",\n \"0.54923546\",\n \"0.5490945\",\n \"0.54797804\",\n \"0.54795164\",\n \"0.54779416\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":81790,"cells":{"query":{"kind":"string","value":"Creates the glove dictionnary from the glove file as a map, where the words are the key Forgets the stopwords"},"document":{"kind":"string","value":"def _extractGloveVects():\n \n embeddings_index = {}\n\n with open(GLOVE_CORPUS_FILE) as f:\n for line in f:\n values = line.split()\n word = values[0].lower()\n if word not in _cachedStopWords:\n coefs = np.asarray(values[1:], dtype='float32')\n embeddings_index[word] = coefs\n\n return embeddings_index"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_glove_dictionary(self, file_path=\"./glove.twitter.27B.25d.txt\"):\n file = open(file_path, \"r\",encoding='utf-8')\n dictionary = {}\n keys = []\n for word_vector in file:\n dictionary[word_vector.split()[0]] = word_vector.split()[1:]\n keys.append(word_vector.split()[0])\n file.close()\n\n file = open(\"./Glove_dict.txt\", \"a\",encoding='utf-8')\n for word in keys:\n file.write(word + '\\n')\n file.close()","def make_word_dict():\n d = dict()\n for line in open('words.txt'):\n word = line.strip().lower()\n d[word] = None\n\n return d","def make_word_dict():\n d = dict()\n fin = open(\"words.txt\")\n for line in fin:\n word = line.strip().lower()\n d[word] = None\n #have to add single letter words to the word list;\n #also, the empty string is considered a word.\n for letter in ['a', 'i', '']:\n d[letter] = letter\n return d","def word_dict():\n fin = open('words.txt')\n w_dict = {}\n for line in fin:\n word = line.strip()\n w_dict[word] = word\n return w_dict","def getDictionary(tsvFile, wordIndex, ngram):\r\n \r\n reader = DescriptionReader(tsvFile, wordIndex, ngram)\r\n dictionary = corpora.Dictionary( d for d in reader )\r\n\r\n # remove stop words and words that appear only once\r\n stoplist = [] # might be specified in the furture\r\n stop_ids = [dictionary.token2id[stopword] for stopword in stoplist\r\n if stopword in dictionary.token2id]\r\n once_ids = [tokenid for tokenid, docfreq in dictionary.dfs.items() if docfreq == 1]\r\n dictionary.filter_tokens(stop_ids + once_ids) # remove stop words and words that appear only once\r\n dictionary.compactify() # remove gaps in id sequence after words that were removed\r\n \r\n return dictionary","def mkwrddct(inputfile):\n fin = open(inputfile)\n words = dict()\n for line in fin:\n w = line.strip()\n words[w] = w\n return words","def create_word_map(tokenized_descriptions_file_path, word_dictionary_output_path):\n if os.path.exists(word_dictionary_output_path):\n print(\"Word map already exists in workspace. Will be reused.\")\n return\n\n print(\"Word map not found. Generating....\")\n\n words_list = []\n words_to_id = {}\n\n with open(tokenized_descriptions_file_path, 'r') as file:\n for line in file:\n tokens = line.strip().split(\",\")\n words_list.extend(tokens[1:])\n\n # remove duplicate words\n words_list = list(set(words_list))\n\n # sorting the words\n words_list = sorted(words_list)\n for i in range(len(words_list)):\n words_to_id[words_list[i]] = i\n\n with open(word_dictionary_output_path, 'w') as f:\n [f.write('{0},{1}'.format(key, value) + \"\\n\") for key, value in words_to_id.items()]","def construct_dict(self):\n i = 0\n self.word2idx = dict()\n fi = open(self.config.word_vec_fi_glove, 'r')\n\n for line in fi:\n self.word2idx[line.split(\" \")[0]] = i\n i += 1\n\n self.vocab_size = i\n self.write_dict()\n fi.close()","def make_mimic_dict(filename):\r\n with open(filename, 'r') as file:\r\n text = file.read().lower().replace(\"'\",'').split()\r\n mimic_dict = {}\r\n prev = ''\r\n for word in text:\r\n if not prev in mimic_dict:\r\n mimic_dict[prev] = [word]\r\n else:\r\n mimic_dict[prev].append(word)\r\n prev = word\r\n return mimic_dict","def fill_in_dict():\n # assign a 'data' list from the txt file\n data = open('words.txt')\n # assign an empty 'my_dict' dictionary\n my_dict = dict()\n\n for word in data:\n # fill in dictionarys wit a keys and empty values\n my_dict[word] = ''\n return(my_dict)","def create_dictionary(filename):\n file = open(filename, 'r')\n text = file.read()\n file.close()\n words = text.split()\n d = {}\n current_word = '$'\n \n for next_word in words:\n if current_word not in d:\n d[current_word] = [next_word]\n else:\n d[current_word] += [next_word]\n if next_word[-1] == '.' or next_word[-1] == '!' or next_word[-1] == '?':\n current_word = '$'\n else:\n current_word = next_word\n return d","def build_word_dict(self, file_type):\n file_name = self.config.parser[file_type + '_dir']\n with open(file_name, 'r') as f:\n for line in f.readlines():\n contents = line.strip().split(' ')\n # an empty line, means seperator for two batch\n # doc id, means a new batch whose `docid` is doc id\n # a word and its tag sepaerated by a blank\n if len(contents) >= 2:\n word, _ = contents[0], contents[1]\n self.word_dict.add_word(word)\n Print(f'word dict from {file_name} is added', 'success')","def read_dictionary():\n with open(FILE, 'r') as f:\n for vocabulary in f:\n if vocabulary[0].strip() not in dict_txt:\n dict_txt[vocabulary[0].strip()] = [vocabulary.strip()]\n else:\n dict_txt[vocabulary[0].strip()].append(vocabulary.strip())","def load_glove_data():\n glove_path = path.join('..', 'data', 'glove', 'glove.twitter.27B.200d.txt')\n f = open(glove_path,'r')\n \n model = {}\n for line in f:\n splitLine = line.split()\n word = splitLine[0]\n embedding = np.array([float(val) for val in splitLine[1:]])\n model[word] = embedding\n \n return model","def read_old_glove(filepath):\n print('reading glove files:', filepath)\n\n word2idx = {}\n word_embed = [['0'] * 300] # word_embed[0] = [0] * 300, represent the <PAD>\n\n with open(filepath, 'r') as f:\n for idx, line in enumerate(f):\n line_list = line.split()\n word = ' '.join(line_list[: len(line_list)-300])\n embed = [num for num in line_list[len(line_list)-300:]]\n\n word2idx[word] = idx + 1\n word_embed.append(embed)\n\n return word2idx, word_embed","def load_wordlist(filename):\n # YOUR CODE HERE\n words = {}\n f = open(filename, 'rU')\n text = f.read()\n text = text.split('\\n')\n for line in text:\n words[line] = 1\n f.close()\n return words","def read_dictionary_from_file(self, stem_flag):\n file_name = \"/dictionary.txt\" if not stem_flag else \"/dictionaryWithStemming.txt\"\n with open(self.posting_and_dictionary_path + file_name, \"r\") as f:\n txt = f.readlines()\n for line in txt:\n l = line.split(\":\")\n pos = l[1].split(\",\")\n e = DictionaryElement(pos[0])\n e.pointer = int(pos[1])\n e.corpus_tf = int(pos[2])\n if not stem_flag:\n self.term_dictionary[l[0]] = e\n else:\n self.term_dictionary_with_stemming[l[0]] = e\n f.close()","def word_list():\n\n d = {}\n with open('words.txt') as fin:\n for line in fin.readlines():\n word = line.strip().lower()\n d[word] = True\n return d","def read_dictionary(filename='/Users/Paul/Documents/c06d.txt'):\n d = dict()\n fin = open(filename)\n for line in fin:\n\n # skip over the comments\n if line[0] == '#': continue\n\n t = line.split()\n word = t[0].lower()\n pron = ' '.join(t[1:])\n d[word] = pron\n\n return d","def create_dictionary(file_dir):\r\n\tword_list = []\r\n\tfile_list = read_files(file_dir, \"lab\") # step 7\r\n\tfor file in file_list:\r\n\t\twith open(file, 'r') as f:\r\n\t\t\ttext = f.read()\r\n\t\tword_list = store_to_dictionary(text, word_list) # step 8cii\r\n\tmake_dictionary_file(file_dir, word_list) # step 9\r","def create_vocabulary(sentences, path):\n print('creating vocab..')\n\n word_dict = dict(); vocabulary = dict()\n for sentence in sentences:\n for word in nltk.word_tokenize(sentence):\n if word not in word_dict:\n word_dict[word] = ''\n word_dict['<s>'] = ''\n word_dict['</s>'] = ''\n\n with open(path, encoding=\"utf8\") as f:\n for line in f:\n word, vec = line.split(' ', 1)\n if word in word_dict:\n vocabulary[word] = np.fromstring(vec, sep=' ')\n\n print('vocabulary was created successfully!')\n return vocabulary","def load_vocab(vocab_file):\n index = 0\n itos = {}\n stoi = {}\n with open(vocab_file, \"r\") as reader:\n while True:\n token = reader.readline()\n if not token:\n break\n token = token.strip()\n itos[index] = token\n stoi[token] = index\n index += 1\n itos[index] = 'style_options'\n stoi['style_options'] = index\n itos[index+1] = 'ambience'\n stoi['ambience'] = index + 1\n return {'itos': itos, 'stoi': stoi, 'len': len(itos)}","def read_dictionary():\n\tglobal dictionary\n\twith open(FILE, \"r\") as f:\n\t\tfor words in f:\n\t\t\tdictionary += words.split()","def generate_dictionary(location):\n f = open('../data/wordlist.txt', 'rb')\n words = Counter(re.findall('[a-z]+', f.read().lower().decode()))\n joblib.dump(words, location)","def load_glove(path):\n with open(path) as f:\n glove = {}\n for line in f.readlines():\n values = line.split()\n word = values[0]\n vector = np.array(values[1:], dtype='float32')\n glove[word] = vector\n return glove","def load_glove(path):\n with open(path) as f:\n glove = {}\n for line in f.readlines():\n values = line.split()\n word = values[0]\n vector = np.array(values[1:], dtype='float32')\n glove[word] = vector\n return glove","def load_terms_dict():\n \tfnm = \"../datasets/bbc/bbc.terms\"\n \tterm_dict = {}\n \twith open(fnm, \"r\") as f:\n \t\tfor wordid, line in enumerate(f.readlines()):\n \t\t\tword = line.strip()\n \t\t\tterm_dict[wordid] = word\n \treturn term_dict","def read_dictionary():\n global dic\n with open(FILE, 'r') as f:\n for line in f:\n word_list = line.split()\n word = word_list[0].strip()\n dic.append(word)","def load_glove_embeddings():\n data = open(\"glove.6B.50d.txt\",'r',encoding=\"utf-8\")\n embeddings = []\n word_index_dict = {'UNK':0}\n index = 1\n for lines in data:\n wordVector = lines.split(\" \")\n if(wordVector[0] in string.punctuation or any(char.isdigit() for char in wordVector[0])):\n continue\n embeddings.append(wordVector[1:-1])\n word_index_dict[wordVector[0]] = index\n index+=1\n print(\"done\")\n\n return embeddings, word_index_dict","def _vector_mapping(self) -> dict:\n words = set()\n for file in os.listdir(self.processed_path):\n doc_path = f\"{self.processed_path}/{file}\"\n with open(doc_path, 'r') as f:\n text_words = f.readline().split()\n words = words.union(set(text_words))\n words = list(words)\n words.sort()\n\n return dict(zip(words, range(len(words))))","def load_gloves(self, dir):\n self.word2vec = {}\n glove_file = os.path.join(dir, 'glove.6B.'+str(self.dim_embed)+'d.txt')\n with open(glove_file, encoding=\"utf8\") as f:\n for line in f:\n l = line.split()\n self.word2vec[l[0]] = [float(x) for x in l[1:]]\n self.word2vec[\"<RARE>\"] = [0. for i in range(self.dim_embed)]\n self.word2vec[\"<EMPTY>\"] = [0. for i in range(self.dim_embed)]","def create_dictionary(filename):\n\tword_set = set()\n\tif os.path.isfile(filename):\n\t\twith open(filename, 'r') as f:\n\t\t\tfor line in iter(f):\n\t\t\t\tword_set.add(line.strip('\\n'))\n\telse:\n\t\tprint \"File not found!\"\n\treturn word_set","def loadGLOVE(filename, vocab):\n dct = {}\n vectors = array.array('d')\n current_idx = 0\n with codecs.open(filename, \"r\", encoding=\"utf-8\") as f:\n for _, line in enumerate(f):\n tokens = line.split(\" \")\n word = tokens[0]\n entries = tokens[1:]\n if not vocab or word in vocab:\n dct[word] = current_idx\n vectors.extend(float(x) for x in entries)\n current_idx += 1\n word_dim = len(entries)\n num_vectors = len(dct)\n tf.logging.info(\"Found {} out of {} vectors in Glove\".format(num_vectors, len(vocab)))\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]","def extract_dictionary(file):\n dict = []\n\n f = open(file, 'r')\n for line in f:\n flist = extract_words(line)\n\n for word in flist:\n if(word not in dict):\n dict.append(word)\n\n f.close()\n\n return dict","def load_dictionary(filename, encoding='utf_8', skip=0, max_words=50000):\n\n d = dict()\n with codecs.open(filename, 'r', encoding=encoding) as f:\n line_counter = 0\n index_counter = 1 # we use 1 for the <EOS> symbol in both languages and 0 for <UNK> words\n\n d['<EOS>'] = index_counter\n index_counter += 1\n\n for line in f.readlines():\n\n line_counter += 1\n\n # check if we have to skip something\n if line_counter > skip:\n # split the line\n s = line.split()\n # get word and its index\n # if index > max. number of words, set it to 0\n if index_counter < max_words:\n word = s[0]\n d[word] = index_counter\n index_counter += 1\n return d","def read_files(self,corpus):\n\n file = open(corpus)\n markov_dictionary = {}\n word_key = ['None', 'None']\n word_list = []\n lastword = \"\"\n #use for loop to make lines in file a list\n for line in file:\n line = line.strip()\n words = line.split(\" \")\n \n # generate keys\n word_key[0] = lastword\n word_key[1] = words[0]\n \n if lastword:\n markov_dictionary[tuple(word_key)] = self.make_values(corpus, word_key)\n\n i = 0\n while i < len(words) - 1:\n word_key[0] = words[i]\n word_key[1] = words[i + 1]\n \n markov_dictionary[tuple(word_key)] = self.make_values(corpus, word_key)\n\n i += 1\n\n lastword = words[len(words) - 1]\n\n # print \"make_chains\", markov_dictionary\n return markov_dictionary","def setKeys():\n keywords['c++'] = {}\n with open('cppkeywords.txt', 'r') as f:\n for i in f:\n i = i.strip('\\n')\n words = map(str, i.split())\n key = words[0]\n words.pop(0)\n keywords['c++'][key] = list(words)\n for j in words:\n MyDict.insert(j)\n keywords['py'] = {}\n with open('pykeywords.txt', 'r') as f:\n for i in f:\n i = i.strip('\\n')\n words = map(str, i.split())\n key = words[0]\n words.pop(0)\n keywords['py'][key] = list(words)\n for j in words:\n MyDict.insert(j)","def build_dict(fname):\n\t\n\twith open(fname) as file:\n\n\t\tword_count_dict = {}\n\n\t\tfor line in file:\n\t\t\tline = line.rstrip()\n\t\t\tline =line.split(' ')\n\t\t\tfor word in line:\n\t\t\t\tword = word.strip('\"!.,?_;():')\n\t\t\t\tword = word.lower()\n\t\t\t\tword_count_dict[word] = word_count_dict.get(word, 0) + 1\n\t\t#return word_count_dict\n\n\t\tfor each in word_count_dict:\n\t\t\tcount = word_count_dict[each]\n\t\t\tprint(each, count)\n\n\t\treturn","def insert_file_to_dictionary():\r\n file = open(sys.argv[1], \"r\")\r\n #movies is my the dictionary\r\n movies = {}\r\n for line in file:\r\n read = line.strip().split(', ')\r\n for i in range(1, len(read)):\r\n if not read[i] in movies:\r\n movies[read[i]] = {read[0]}\r\n else:\r\n movies[read[i]].add(read[0])\r\n return movies","def dictionary_creation(filename):\n\tfp = open(filename)\n\td = dict()\n\tfor line in fp:\n\t\t# print line\n\t\tfor word in line.split():\n\t\t\tword = word.strip(string.punctuation + string.whitespace)\n\t\t\t# print word\n\t\t\tif len(word) >5:\n\t\t\t\tif word not in d:\n\t\t\t\t\t# print 'in'\n\t\t\t\t\td[word] = 1\n\t\t\t\telse:\n\t\t\t\t\t# print 'not in'\n\t\t\t\t\td[word] += 1\n\treturn d\n\n\tfp.close()","def read_dictionary():\n with open(FILE, 'r') as f:\n for line in f:\n words_lst = line.split()\n for word in words_lst:\n dict_list.append(word)","def rm_stopwords(file_path, word_dict):\n\n # read stop word dict and save in stop_dict\n stop_dict = {}\n with open(word_dict) as d:\n for word in d:\n stop_dict[word.strip(\"\\n\")] = 1\n # remove tmp file if exists\n if os.path.exists(file_path + \".tmp\"):\n os.remove(file_path + \".tmp\")\n\n print(\"now remove stop words in %s.\" % file_path)\n # read source file and rm stop word for each line.\n with open(file_path) as f1, open(file_path + \".tmp\", \"w\") as f2:\n for line in f1:\n tmp_list = [] # save words not in stop dict\n words = line.split()\n for word in words:\n if word not in stop_dict:\n tmp_list.append(word)\n words_without_stop = \" \".join(tmp_list)\n to_write = words_without_stop + \"\\n\"\n f2.write(to_write)\n\n # overwrite origin file with file been removed stop words\n shutil.move(file_path + \".tmp\", file_path)\n print(\"stop words in %s has been removed.\" % file_path)","def new_counts_dict():\n\n\tIN_FILES = [\"../_semtag_dataset_webanno_tfidf_inimigo.txt\",\"../_semtag_dataset_webanno_tfidf_publico.txt\" ]\n\n\ttxt = []\n\tfor in_file in IN_FILES:\n\t with codecs.open(in_file,\"r\",\"utf-8\") as fid:\n\t txt += fid.readlines()\n\t#words\n\twords = [w for m in txt for w in m.split()]\n\t#unique words\n\twords = list(set(words))\n\t#word index\n\twrd2idx = {w:-1 for w in words}\n\n\tset_trace()\n\t\n\twith open(COUNTS_DIC,\"w\") as fod:\n\t\tcPickle.dump(wrd2idx, fod, cPickle.HIGHEST_PROTOCOL)","def load_glove_vectors(filename, vocab):\n dct = {}\n vectors = array.array('d')\n current_idx = 0\n with open(filename, \"r\", encoding=\"utf-8\") as f:\n for _, line in enumerate(f):\n tokens = line.split(\" \")\n word = tokens[0]\n entries = tokens[1:]\n if not vocab or word in vocab:\n dct[word] = current_idx\n vectors.extend(float(x) for x in entries)\n current_idx += 1\n word_dim = len(entries)\n num_vectors = len(dct)\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]","def load_train_word_dict():\n train_dict = {}\n with open(TRANSCRIPTION_PATH) as file:\n for line in file:\n if int(line[0:3]) < 300:\n word_id, transcript = str.split(line, \" \")\n train_dict[word_id] = transcript.rstrip('\\n')\n return train_dict","def create_dict(fd):\n # initialize an empty dictionary\n full_dict = {}\n # loop through file\n for line in fd:\n # lowercase everything in line, then split line into a list\n line = line.lower().split()\n # loop through elements in the list of words in the splitted line\n for word in line:\n # strip words from puncuation using string module\n word = word.strip(string.punctuation)\n # if words contains only alphabatic characters and of length > 1\n if word.isalpha() and len(word)!= 1:\n if len(word) in full_dict:\n full_dict[len(word)].add(word)\n else:\n full_dict[len(word)] = set()\n full_dict[len(word)].add(word)\n return full_dict","def read_data(file_path):\n words=[]\n dic_word={}\n actual_text=[]\n for line in open(file_path,encoding='utf-8'):\n words_line=line.strip().split(' ')\n for ite in words_line:\n if ite not in dic_word:\n dic_word[ite]=1\n words.extend(words_line)\n actual_text.append(words_line)\n\n\n #with zipfile.ZipFile(file_path) as f:\n #words = tf.compat.as_str(f.read(f.namelist()[0])).split()\n\n return words,len(dic_word),actual_text","def createDict(self):\n data = d.Dictionary.dictionary\n while True:\n filtered = [line.strip() for line in data if len(line) == self.wordLen]\n if len(filtered) == 0:\n self.setNewLen()\n else:\n break\n return filtered","def ReadMorphit(self):\r\n self.words = {}\r\n with codecs.open(self.MorphItFileName, 'r', 'utf-8') as f:\r\n for line in f.readlines():\r\n line = line.split()\r\n try:\r\n# print (line)\r\n self.words[line[0]] = line[2][:3]\r\n# if line[2][:3] in self.verbTags:\r\n# line[2]=line[2].split(u'+')\r\n# line[2][0]=line[2][0][line[2][0].find(u':')+1:]\r\n except:\r\n pass\r\n return self.words","def make_frequency_dict(path):\n filepath = path#'germanWordList_03.csv'\n wordDict = {}\n f = open(filepath,'r')\n for line in f:\n split = line.split(\",\")\n word = (split[0]).lower()\n temp = float(split[1])\n if word in wordDict:\n val = float(wordDict[word])\n if val > 0:\n num = (temp * val) / (val + temp)\n else:\n num = temp\n else:\n num = temp\n wordDict[word]= num\n return wordDict","def load_file(self, file_path):\n f = open(file_path, \"r\")\n sentences = f.readlines()\n \n word_count = 0\n\n for sentence in sentence: \n for word in sentence.strip().split(\" \"):\n if not (word in self.word_id): #word not in dictionary\n word_id[word] = word_count\n word_count += 1\n\n #self.doc = [[self.word_id[word] for word in sentence.strip().split(\" \")] for sentence in sentences]","def load_tags_vocab(load_path: str) -> dict:\n tags_vocab = dict()\n with open(load_path, 'r') as f:\n lines = f.readlines()\n f.close()\n\n for line in lines:\n key, val = line[:-1].split(' ') # \"\\t\"\n tags_vocab[key] = val\n\n return tags_vocab","def load_glove_vec(fname, vocab):\n word_vecs = {}\n with open(fname, \"rb\") as f:\n for i,line in enumerate(f):\n L = line.split()\n word = L[0].lower()\n if word in vocab:\n word_vecs[word] = np.array(L[1:], dtype='float32')\n return word_vecs","def load_dic():\r\n f = open('../data/phrases-freq.txt')\r\n d = {}\r\n for line in f:\r\n line = line.strip().decode('utf-8')\r\n if line == '' or line[0] == '#':\r\n continue\r\n else:\r\n k, v = line.split()\r\n d[k] = int(v)\r\n return d","def create_bow(vocab, filepath):\n bow = {}\n # TODO: add your code here\n wordcount = 0\n wordcountnone = 0\n c = 0\n\n for i in vocab:\n c+=1\n with open(filepath, 'r', encoding=\"utf-8\") as doc: ###############################################\n for word in doc:\n word = word.strip()\n if(c==1):\n if (word not in vocab):\n wordcountnone += 1\n if(i == str(word)):\n wordcount += 1\n #print(wordcount)\n if(wordcount > 0):\n bow[i] = wordcount\n wordcount = 0\n if(wordcountnone != 0):\n bow[None] = wordcountnone\n return bow","def load_dictionary(location='../data/wordlist.pkl'):\n words = joblib.load(location)\n # Simple plurals not necessary since removed in word correction\n manual_addition = ['sis', 'vixen' ,'ho', 'hoe', 'aint', 'nigga', 'nigger', 'bitch', 'bitches', 'lmao', 'pussy',\n 'fuck', 'fucking', 'fag', 'faggot', 'hater', 'lol', 'yall', 'nfl', 'fucked', 'nips', 'crap',\n 'whitey', 'ghetto', 'mac', 'tho', 'jamming', 'titties', 'dyke', 'fb', 'lmfao', 'bae', 'kanye',\n 'coon', 'smh', 'tweet', 'retweet', 'nbc', 'jk', 'im']\n for word in manual_addition:\n words[word] = 99999 # add word to counter\n return words","def create_lemma_dict(lemma_file):\n\tacademic_words= open(lemma_file)\n\tLEMMA_DICT = {}\n\tfor line in academic_words:\n\t\tline =line.rstrip().rstrip(',')\n\t\twords = line.split(',')\n\t\tstem = words[0]\n\t\tfor word in words:\n\t\t\tLEMMA_DICT[word] = stem\n\n\treturn LEMMA_DICT","def word_frequency():\n\n song = open(\"data/yellow_submarine.txt\")\n d = dict()\n for line in song:\n line = line.strip()\n line = line.lower()\n punctuations = \"\"\"!()-[]{};:'\"\\,<>./?@#$%^&*_~\"\"\" # remove punctuation https://www.programiz.com/python-programming/examples/remove-punctuation\n no_punct = \"\" # remove punctuation\n for char in line: # remove punctuation\n if char not in punctuations: # remove punctuation\n no_punct = no_punct + char # remove punctuation\n words = line.split(\" \")\n for word in words:\n d[word] = d.get(word, 0) + 1\n return d","def __init__(self, filename):\n\n self.term_dict = {}\n for line in open(filename):\n if line.startswith(\"#\"):\n continue\n\n #print line\n word, w_type = line.strip().split(\"\\t\")\n self.term_dict[word.strip().lower()] = \"CHESS_\" + w_type.strip().lower()","def buildCorpus(self, filename, stopwords_file=None):\n with open(filename, 'r') as infile:\n # use pattern.subs\n # doclines = [line.rstrip().lower().split(' ') for line in infile]\n doclines = [self.help_clean(line) for line in infile]\n n_docs = len(doclines)\n self.vocab = list({v for doc in doclines for v in doc})\n if stopwords_file:\n with open(stopwords_file, 'r') as stopfile:\n stops = stopfile.read().split()\n self.vocab = [x for x in self.vocab if x not in stops]\n self.vocab.sort()\n self.documents = []\n for i in range(n_docs):\n self.documents.append({})\n for j in range(len(doclines[i])):\n if doclines[i][j] in self.vocab:\n self.documents[i][j] = self.vocab.index(doclines[i][j])","def buildDict(self, words):\r\n for word in words:\r\n self.trie.addWord(word)","def make_stopwords(filepath='stopwords.txt'):\n sw = open(filepath, \"r\")\n my_stopwords = sw.read()\n my_stopwords = my_stopwords.split(\", \")\n sw.close()\n\n all_stopwords = stopwords.words('english')\n all_stopwords.extend(my_stopwords)\n return all_stopwords","def load_data_for_dict(path, voc_path, need_rem_punkt=True):\n \n table = str.maketrans('', '', string.punctuation)\n\n with open(voc_path) as f:\n word_to_idx = dict(json.load(f))\n dict_size = len(word_to_idx)\n \n with open(path, \"r\") as fin:\n for line in fin:\n line = line.lower()\n sentence = []\n for word in line.split():\n if need_rem_punkt: \n word = word.translate(table) # remove punctuation\n if word not in word_to_idx:\n word_to_idx[word] = dict_size\n dict_size += 1\n\n with open(voc_path, \"w+\") as fout:\n json.dump(word_to_idx, fout)","def build_words_map(self, to_clip=True):\n import clipboard\n import json_utils\n words_map = {}\n rev_map = {}\n rs = []\n all_words=self.get_all_words()\n for word in all_words:\n key = self.get_norm_key(word)\n if len(key) > 0:\n if key in words_map:\n words_map[key].append(word)\n else:\n words_map[key] = [word]\n rev_map[word] = key\n rs.append('%s %s' % (key, word))\n\n print('write to', self.target_file)\n json_utils.write_json_to_file(self.target_file, words_map)\n json_utils.write_json_to_file(self.target_file_rev, rev_map)\n if to_clip:\n print('copy to clipboard ...')\n clipboard.copy('\\n'.join(rs))\n print('done')","def build_stopwords():\r\n\tprint('\\nbuilding stopwords')\r\n\t\r\n\tif load_stopwords():\r\n\t\treturn\r\n\r\n\tglobal stopwords\r\n\tstopwords = nltk.corpus.stopwords.words('english')\r\n\tfor f in os.listdir(paths.path_data_stopwords):\r\n\t\tpath_stopwords = paths.path_data_stopwords + '/' + f\r\n\t\twith open(path_stopwords,'r') as f:\r\n\t\t\tfor l in f:\r\n\t\t\t\tw = l.strip()\r\n\t\t\t\tw = re.sub(r\"[\\x80-\\xff]\",\" \",w)\r\n\t\t\t\tif (w not in stopwords):\r\n\t\t\t\t\tstopwords.append(w)\r\n\t\r\n\t# wip improve with POS and remove numbers\r\n\twith open(paths.path_data_stopwords_txt,'w') as outf:\r\n\t\toutf.write('\\n'.join(stopwords))\r\n\t\r\n\tprint('\\nstopword count : ' + str(len(stopwords)))","def load_words(file_path: str) -> List[Word]:\n \n words = load_words_raw(file_path)\n \n \n words = remove_stop_words(words)\n\n \n words = remove_duplicates(words)\n \n return words","def dict_make():\n f = open('words.txt','r')\n dict1 = f.read().splitlines()\n return filter(lambda z:len(z) >= 4, dict1)","def load_stop_words(stop_word_file):\n stop_words = []\n for line in open(stop_word_file):\n if line.strip()[0:1] != \"#\":\n for word in line.split(): # in case more than one per line\n stop_words.append(word)\n return stop_words","def load_words():\n with open(DICTIONARY) as f:\n return [line.strip() for line in f]","def get_word_list(file_name, to_skip_or_not_to_skip):\n fin = open(file_name) #opening file\n histogram={} \n if to_skip_or_not_to_skip == True: #if I want to skip the header this is set to True\n skip_first_part(fin)\n for line in fin: #runs through lines of book file\n line = line.replace(\"-\",\" \") #takes out dashed, underscroes, numbers, whitespaces, and punctuation\n line = line.replace(\"_\",\" \")\n to_remove = string.punctuation + string.whitespace + '0123456789' \n for word in line.split():\n word = word.strip(to_remove) #running through all words in each line \n if word == 'God' or 'Lord':\n pass\n else:\n word = word.lower()\n histogram[word] = histogram.get(word, 0)+1\n return histogram","def load_defs():\n # Load word definitions\n fname = 'word-definitions.txt'\n with open(fname) as fh:\n lines = fh.readlines()\n \n # Create dictionary keyed by lowercase word\n def_tbl = dict()\n for line in lines:\n # split the dictionary line at the first space\n word, word_def = line.split(sep=None, maxsplit=1)\n # add this entry to the dictionary\n word = word.lower()\n def_tbl[word] = word_def.rstrip()\n return def_tbl","def load_vocab(filename):\n try:\n d = dict()\n with open(filename, encoding='utf-8') as f:\n for idx, word in enumerate(f):\n word = word.strip()\n d[word] = idx\n\n except IOError:\n raise MyIOError(filename)\n return d","def load_wordlist(self, filename):\n reg1 = re.compile(\"^([1-6]{5})[ \\t]+(.*)$\")\n f = open(filename, 'r')\n \n if(self.generate):\n wordlist = []\n reg2 = re.compile(\"^(\\S*)$\")\n for line in f:\n m1 = reg1.match(line)\n m2 = reg2.match(line)\n \n if(m1):\n wordlist.append(m1.group(2))\n elif(m2):\n wordlist.append(m2.group(1))\n \n else:\n wordlist = {}\n for line in f:\n m = reg1.match(line)\n if(m):\n wordlist[int(m.group(1))] = m.group(2)\n \n if((not self.generate and len(wordlist) < 7776) or \n (self.generate and len(wordlist) < 2**13)):\n stderr.write(\"Word list is too short\\n\")\n exit(5)\n \n self.wordlist = wordlist","def _create_deleted_variation_2_dictionary_words(self):\n deleted_variation_2_dictionary_words = defaultdict(set)\n for word in self._word_2_frequency.keys():\n deleted_variations = chain(self._one_edit_deleted_variations(word), self._two_edits_deleted_variations(word))\n for deleted_variation in deleted_variations:\n deleted_variation_2_dictionary_words[deleted_variation].add(word)\n return deleted_variation_2_dictionary_words","def learn(filename):\n word_dict = {} # Create empty dictionary\n first = None\n prev = None\n with open(filename, 'r', encoding='utf-8') as file:\n for line in file:\n list_words = line.lower().split()\n text = []\n for word in list_words:\n # take out leading and trailing punctuation characters\n words = word.strip(string.punctuation + string.digits)\n word_len = len(words)\n if word_len >= 1:\n text.append(words)\n\n if first is None:\n # Get the first word in the text file\n first = text[0]\n # iterate over text\n if prev:\n text.insert(0, prev)\n for counter, word in enumerate(text):\n if word not in word_dict:\n word_dict[word] = list()\n if counter < (len(text) - 1):\n following = counter + 1\n word_dict[word].append(text[following])\n prev = text[-1]\n return first, word_dict # return a tuple","def preprocess(in_file: str, file_out: str) -> tuple:\r\n try:\r\n stop_words = []\r\n if os.path.isfile(\"StopWords.pkl\"):\r\n with open(\"StopWords.pkl\", mode=\"rb\") as pkl:\r\n stop_words = pickle.load(pkl)\r\n else:\r\n with open(\"StopWords.txt\", mode=\"r\") as f1:\r\n for line in f1:\r\n stop_words.append(line.strip(\"\\n\"))\r\n with open(\"StopWords.pkl\", mode=\"wb\") as pkl:\r\n pickle.dump(stop_words, pkl)\r\n\r\n vocab = []\r\n corpus = []\r\n with open(in_file, mode=\"r\") as f:\r\n for line in f:\r\n line = line.rsplit(sep=\"\\t\")\r\n sent = line[1].strip(\" \\n\")\r\n sent = int(sent)\r\n\r\n sentence = process_sentence(line[0])\r\n\r\n [sentence.remove(w) for w in sentence if w in stop_words or w == \"\"]\r\n corpus.append([sentence, sent])\r\n vocab += list(set(sentence) - set(vocab))\r\n\r\n # Sort lists alphabetically\r\n corpus = sorted(corpus)\r\n vocab = sorted(vocab)\r\n vocab.append(\"classlabel\")\r\n to_file(file_out, vocab, corpus)\r\n\r\n return vocab, corpus\r\n except:\r\n catch_err()","def load_dictionary(filename):\n\n word_list = []\n freq_sum = 0\n\n # nacitanie zo suboru\n with open(filename) as f:\n for line in f:\n freq, val = line.split()\n word_list.append(Word(int(freq), val))\n freq_sum += int(freq)\n\n # lexikograficke usporiadanie slov\n word_list_sorted = sorted(word_list, key=operator.attrgetter('value'))\n\n return word_list_sorted, freq_sum","def stopping():\r\n file_content = read_file() # file_content: Dictionary\r\n common_words_list = read_common_words() # common_words_list: List\r\n file_content_with_stopping = remove_common_words(file_content, common_words_list)\r\n return file_content_with_stopping","def readAllWordFeatures(labelFilePathTuples):\n fileFeatureDict = {}\n\n for t in labelFilePathTuples:\n wordFeatures = readWordFeatures(t)\n fileFeatureDict[t[1]] = wordFeatures\n return fileFeatureDict","def file_to_dictionary():\n\n return;","def constitute_word_dict(self):\r\n\r\n #IS THIS NECESSARY WITH DATABASE??\r\n\r\n if self.using_shelf:\r\n for k_temp in self.get_words():\r\n self.delete_word(k_temp)\r\n\r\n for i_temp in [a_temp for a_temp in self.indexes()\r\n if Index(a_temp) > Index(str(0))]:\r\n\r\n self.add_search_words(Index(i_temp),\r\n self.get_text_from_note(i_temp))\r\n display.noteprint((alerts.ATTENTION,\r\n alerts.WORD_DICT_CONSTITUTED))","def make_dictionary(self, train_file, validation_file, test_file):\n print 'constructing vocabulary'\n train_set, test_set, valid_set = set(), set(), set()\n label_set = set()\n ftrain = io.open(train_file, 'r')\n for line in ftrain:\n entity, label = map(clean, line.rstrip().split('\\t')[:2])\n train_set |= set(list(entity))\n label_set |= set(label.split(','))\n\n fvalid = io.open(train_file, 'r')\n for line in fvalid:\n entity, label = map(clean, line.rstrip().split('\\t')[:2])\n valid_set |= set(list(entity))\n label_set |= set(label.split(','))\n\n ftest = io.open(test_file, 'r')\n for line in ftest:\n entity, label = map(clean, line.rstrip().split('\\t')[:2])\n test_set |= set(list(entity))\n # label_set |= set(label.split(','))\n \n print '# chars in training ', len(train_set)\n print '# chars in validation ', len(valid_set)\n print '# chars in testing ', len(test_set)\n print '# chars in (testing-training-validation) ', len(test_set-train_set-valid_set)\n print '# labels', len(label_set)\n\n vocabulary = list(train_set | test_set | valid_set)\n vocab_size = len(vocabulary)\n chardict = dict(zip(vocabulary, range(1,vocab_size+1)))\n chardict[u' '] = 0\n labeldict = dict(zip(list(label_set), range(len(label_set))))\n \n return chardict, labeldict","def build_word_dict(self, examples):\n word_dict = TokenDictionary()\n for w in self.load_words(examples):\n word_dict.add(w)\n return word_dict","def get_keywords(text):\n tokens = [word.lower() for word in word_tokenize(text)]\n\n # tag words as verb, noun etc\n tagged_words = pos_tag(tokens)\n\n # retrieve list of boring words from file\n stopwords_file = os.path.join(BASE_DIR, 'data', 'stopwords.txt')\n with open(stopwords_file, 'r', encoding='utf-8') as f:\n stopwords = [line.rstrip(linesep) for line in f]\n \n #We don't want keywords to contain anything in this list\n forbidden = ['.',',',';',':','?','!','+',')','(','[',']','/','<','>','\"','©','1','2','3','4','5','6','7','8','9','0']\n\n # NLTK Chunking - detects noun phrases and phrases of form verb noun or adj noun\n patterns = \"\"\"NP: {<JJ>*<NN><NNS>}\n {<JJR><NNS>}\n {<JJ>*<NNS>}\n {<NN><NNS>} \n {<JJ><NNS>}\n {<JJ>*<NN>*}\n {<NN>*}\n {<NNS>*}\"\"\"\n chunker = RegexpParser(patterns)\n chunks = chunker.parse(tagged_words)\n\n #these are the phrases we want, as lists within a list\n validphrases = []\n for t in chunks.subtrees():\n if t.label() == 'NP':\n validphrases.append([x for x,y in t.leaves()])\n\n #turning lists within lists into actual noun phrases i.e [[radiation], [breast,cancer]] becomes [radiation, breast cancer]\n #sorry for my horrible code\n #trees suck\n lemmatizables = []\n for sublist in validphrases:\n lemmatizables.append(' '.join(sublist))\n\n lemmatizer = WordNetLemmatizer()\n lems = [lemmatizer.lemmatize(x) for x in lemmatizables]\n\n #removing stopwords after lemmatizinga, then removing anything containing punctuation or a number\n lems = filter(lambda lem: lem not in stopwords, lems)\n lems = filter(lambda lem: not any(char in lem for char in forbidden), lems)\n\n return tuple(lems)","def read_gulordava_corpus(corpus_dir: str) -> dict:\n def _read_file(path: str) -> List[str]:\n with open(path, \"r\") as f:\n return f.readlines()\n\n sentences = _read_file(f\"{corpus_dir}/generated.text\")\n sentence_info = _read_file(f\"{corpus_dir}/generated.tab\")[1:] # Skip header line\n labelled_corpus = {}\n\n for i, sentence in enumerate(sentences):\n right_info, wrong_info = sentence_info[2*i], sentence_info[2*i+1]\n\n # Parse lines\n right_info, wrong_info = right_info.split(\"\\t\"), wrong_info.split(\"\\t\")\n constr_id, sent_id, correct_number, right_form, class_, type_ = right_info[1:7]\n len_context, len_prefix, sent = right_info[11:14]\n constr_id_wrong, sent_id_wrong, _, wrong_form, class_wrong, type_wrong = wrong_info[1:7]\n sent_wrong = wrong_info[13]\n\n assert class_ == \"correct\" and class_wrong == \"wrong\"\n assert constr_id == constr_id_wrong and sent_id == sent_id_wrong and sent == sent_wrong and type_ == type_wrong\n\n len_prefix, len_context = int(len_prefix), int(len_context)\n subj_pos = len_prefix - len_context\n verb_pos = len_prefix\n sentence = sent.split()\n\n misc_info = {\n \"raw\": sent,\n \"subj_pos\": subj_pos,\n \"verb_pos\": verb_pos,\n \"right_form\": right_form,\n \"wrong_form\": wrong_form,\n \"correct_number\": correct_number,\n \"sent_id\": sent_id,\n \"constr_id\": constr_id,\n \"type\": type_\n }\n\n labelled_sentence = {\n \"sen\": sentence, \"labels\": [0 if correct_number == \"sing\" else 1] * len(sentence), **misc_info\n }\n labelled_corpus[i] = labelled_sentence\n\n return labelled_corpus","def read_file(filename):\n print(\"Reading dictionary: \" +filename)\n word_dict = set()\n\n dictionary = open(filename)\n\n # Read each word from the dictionary\n for word in dictionary:\n # Remove the trailing newline character\n word = word.rstrip('\\n')\n\n # Convert to lowercase\n word = word.lower()\n\n word_dict.add(word)\n\n dictionary.close()\n\n return word_dict","def load(filename):\n\n print \"Loading dictionary...\"\n dictionary = Dictionary()\n print \" Loading file...\"\n whole_file = file(filename).read().upper()\n print \" Splitting file...\"\n words = whole_file.split()\n print \" Removing unsuitable words...\"\n words = dictionary.remove_unsuitable_words(words)\n print \" Building data structures...\"\n dictionary.set_words(words)\n\n print \" Loaded %d words\" % len(dictionary.words)\n print \" Unique letter size:\"\n print \" No blanks: %d\" % len(dictionary.letters_map)\n print \" One blank: %d\" % len(dictionary.letters_map_one_blank)\n print \" Two blanks: %d\" % len(dictionary.letters_map_two_blanks)\n\n return dictionary","def load_vocabulary():\n global vocabulary_list, vocabulary_dict\n vocabulary_list = []\n vocabulary_dict = {}\n\n with open(_VOCABULARY_PATH, 'r') as f:\n for index, line in enumerate(f):\n line = line.strip()\n vocabulary_dict[line] = index\n vocabulary_list.append(line)","def word_frequency_in_file(filename):\n words = {}\n fin = open(filename)\n punctuation = string.punctuation\n for line in fin:\n line = line.translate( # Replace punctuation with spaces\n str.maketrans(punctuation, ' ' * len(punctuation)))\n line = line.lower()\n line_words = line.split()\n for word in line_words: # Process each word in the line.\n if word in words:\n words[word] += 1\n else:\n words[word] = 1\n return words","def load_morphoit(self, path=None):\n path = path or self.path\n # f = open(path,'r')\n f = codecs.open(path, 'r', 'latin-1')\n lines = f.readlines()\n f.close()\n self.lemma_dict.clear()\n self.tag_dict.clear()\n self.suffix_dict.clear()\n self.word_tag_dict.clear()\n n_entries = 0\n for line in lines:\n line = line.strip()\n if line:\n # entry = line.split()\n entry = line.split(u'\\u0009') # entry has TAB delimited items\n n = len(entry)\n word = entry[0]\n if n > 1:\n lemma = entry[1]\n else:\n lemma = 'lemma?'\n if n > 2:\n tags = entry[2]\n if tags:\n splitted_tags = tags.split(u':')\n tag = splitted_tags[0]\n if tag == u'SMI': # smile ?\n continue\n else:\n tag = 'tag?'\n n_entries += 1\n if self.use_defaultdict:\n self.lemma_dict[lemma].append(word)\n self.tag_dict[tag] += 1\n self.word_tag_dict[word][tag] += 1\n else:\n words = self.lemma_dict.get(lemma, []); words.append(word); self.lemma_dict[lemma] = words\n self.tag_dict[tag] = self.tag_dict.get(tag, 0) + 1\n dict = self.word_tag_dict.get(word, {})\n \"\"\" only occurrence in corpus will increment the counter !\n dict[tag] = dict.get(tag, 0) + 1\n \"\"\"\n if dict.get(tag, None) is None:\n dict[tag] = 0\n self.word_tag_dict[word] = dict\n length = len(word)\n reversed = util.reverse(word)\n max = min(length, MAX_SUFFIX)\n for i in range(MIN_SUFFIX, max):\n suffix = reversed[:i]\n if self.use_defaultdict:\n self.suffix_dict[suffix][tag] += 1\n else: # defaultdicts cannot be pickled !\n dict = self.suffix_dict.get(suffix, {})\n dict[tag] = dict.get(tag, 0) + 1\n self.suffix_dict[suffix] = dict\n return len(lines), n_entries","def load():\n for line in open(config.filepath, 'r'):\n line = line.strip()\n line_sorted = ''.join(sorted(line))\n\n if line_sorted not in Words.hashed:\n Words.hashed[line_sorted] = []\n\n # Store the real hashed as a list\n # We need line_sorted as the key for fast lookup later\n Words.hashed[line_sorted].append(line)\n\n # Also add the word to a standard list\n # We'll use this to quickly determine wordiness later\n Words.words.append(line)","def read_from_file():\n\n plik=open('data.txt')\n for line in plik:\n (key, temp, weat, pres)=line.split()\n dict_from_file[key]=[temp, weat.replace('_',' '), pres]","def _parse_word_dict(dict_f_name):\n if os.path.isfile(dict_f_name):\n word_dict = {}\n with open(dict_f_name) as f:\n for line in f:\n w, idx = line.strip().split(\" \")\n word_dict[w.strip()] = int(idx)\n return word_dict\n else:\n error(\"Dict not exists: %s\" % dict_f_name)","def get_weibo_data(vocab_file, vector_file):\n if os.path.exists(\"word_misc.pkl\"):\n return cPickle.load(open(\"word_misc.pkl\", \"rb\"))\n\n word_misc, word2id, id2word = {}, {}, {}\n word_count = 0\n\n # vocab file\n print \"Building vocabulary ...\"\n for lines in open(vocab_file).readlines():\n word = lines.split()[0]\n if not is_unwanted_words(word, ['', '\\n']):\n word2id[word] = word_count\n id2word[word_count] = word\n word_count += 1\n word2id['_START'] = word_count\n id2word[word_count] = '_START'\n word_count += 1\n word2id['_END'] = word_count\n id2word[word_count] = '_END'\n word_count += 1\n word2id['_UNK'] = word_count\n id2word[word_count] = '_UNK'\n word_count += 1\n word2id['_MASK'] = word_count\n id2word[word_count] = '_MASK'\n word_count += 1\n print \"Vocabulary size:\", word_count\n\n # Initialization is refered to in https://www.tensorflow.org/versions/r0.7/tutorials/word2vec/index.html\n word_emb = (1/np.sqrt(word_count)*(2*np.random.rand(word_count, options['embedding_size']) - 1)).tolist()\n\n # load word vectors\n for lines in open(vector_file).readlines()[1:]:\n word = lines.split()[0]\n #if word == '</s>' or word not in word2id.keys():\n # continue\n if word not in word2id.keys():\n continue\n ids = word2id[word]\n #print ids, lines, len(word_emb)\n word_emb[ids] = [float(w) for w in lines.split()[1:]]\n\n print len(word_emb), \"words have been loaded with\", len(word_emb[0]), \"dimensions\"\n\n # load word misc\n word_misc['id2word'] = id2word\n word_misc['word2id'] = word2id\n word_misc['word_count'] = word_count\n word_misc['word_emb'] = word_emb\n cPickle.dump(word_misc, open(\"word_misc.pkl\", \"wb\"))\n print \"Dump complete.\"\n return word_misc","def load_typos_moe(file_name):\n \n # log = logging.getLogger(\"robust_ner\")\n\n file_path = os.path.join(f\"resources/typos/\", f\"{file_name}\")\n\n typos = dict()\n for line in open(file_path):\n line = line.strip().split()\n\n if len(line) != 2:\n #log.warning(f\"len(line) = {len(line)} != 2 (line: {line})\")\n continue\n\n value = line[0]\n key = line[1]\n\n #print(key, value)\n \n if key not in typos:\n typos[key] = list()\n\n typos[key].append(value)\n \n return typos","def get_glove_vocab(filename):\n print(\"Building vocab...\")\n vocab = set()\n with open(filename, encoding='utf-8') as f:\n for line in f:\n # print(line.split(' ')[0])\n word = line.strip().split(' ')[0]\n vocab.add(word)\n print(\"- done. {} tokens\".format(len(vocab)))\n return vocab","def remove_stopwords(self, value):\n with open(\"grandpy/stop_words.json\", encoding=\"utf-8\") as json_file:\n stopwords = json.load(json_file)\n key_words = [word for word in value if word not in stopwords[\"stop_words\"]]\n return key_words","def loadVoc(vocabFName):\n f = open(vocabFName, 'r')\n lines = f.readlines()\n f.close()\n result = dict()\n for idx, val in enumerate(lines):\n word = val.strip('\\n')\n result[word] = idx\n return result","def print_word_freq(file):\n # with open(file, 'r') as text the r as the second arguement means that my intentions are to read the file\n with open(file, 'r') as text:\n # this reads the entire file and puts this into text string\n text_string = text.read()\n # returns the string respresentation of text string without removing special characters so you can see what you need to remove\n # print(repr(text_string))\n # this removes the specified characters from the text string\n text_string = text_string.replace(\",\", \"\")\n text_string = text_string.replace(\".\", \"\")\n text_string = text_string.replace(\"—\", \" \")\n text_string = text_string.replace(\"-\", \" \")\n text_string = text_string.replace(\"?\", \"\")\n text_string = text_string.replace(\":\", \"\")\n text_string = text_string.replace(\"'\", \"\")\n text_string = text_string.replace(\"\\\\n\", \"\")\n text_string = text_string.replace(\"’\", \"\")\n text_string = text_string.replace(\"]\", \"\")\n text_string = text_string.replace(\"[\", \"\")\n text_string = text_string.replace(\"\\\"\", \"\")\n # takes the text string and makes all the characters lower case\n text_string = text_string.lower()\n # takes the text string and splits all the words into a list this splits from space to space\n words_list = text_string.split()\n # a dictionary is a key and a value\n no_stop_words = {}\n # for loop that will cycle through the words list\n for word in words_list:\n # checking to see if the word is stop words\n if word not in STOP_WORDS:\n # if the word is already in the dictionary no stop words increment the value by 1\n if word in no_stop_words:\n no_stop_words[word] += 1\n # if the word is not in the dictionary no stop words add this to the dictionary and give it a value of 1\n else:\n no_stop_words[word] = 1\n \n sorted_dict = {}\n sorted_keys = sorted(no_stop_words, key=no_stop_words.get, reverse=True)\n \n for w in sorted_keys:\n sorted_dict[w] = no_stop_words[w]\n \n for key in sorted_dict:\n print(f\"{key:>15} | {sorted_dict[key]:2} {'*' * sorted_dict[key]}\")\n \n # good practice to ensure that we are properly closing the file in use at the end of the function\n text.close()","def get_dict(fname):\n out_set, tot_count = {}, 0\n with open(fname, 'r') as fid:\n word_arr = fid.read().split('\\n')\n for ele in word_arr:\n if len(ele) > 0:\n out_set[(ele.split()[0])] = tot_count\n tot_count += 1\n return out_set"],"string":"[\n \"def get_glove_dictionary(self, file_path=\\\"./glove.twitter.27B.25d.txt\\\"):\\n file = open(file_path, \\\"r\\\",encoding='utf-8')\\n dictionary = {}\\n keys = []\\n for word_vector in file:\\n dictionary[word_vector.split()[0]] = word_vector.split()[1:]\\n keys.append(word_vector.split()[0])\\n file.close()\\n\\n file = open(\\\"./Glove_dict.txt\\\", \\\"a\\\",encoding='utf-8')\\n for word in keys:\\n file.write(word + '\\\\n')\\n file.close()\",\n \"def make_word_dict():\\n d = dict()\\n for line in open('words.txt'):\\n word = line.strip().lower()\\n d[word] = None\\n\\n return d\",\n \"def make_word_dict():\\n d = dict()\\n fin = open(\\\"words.txt\\\")\\n for line in fin:\\n word = line.strip().lower()\\n d[word] = None\\n #have to add single letter words to the word list;\\n #also, the empty string is considered a word.\\n for letter in ['a', 'i', '']:\\n d[letter] = letter\\n return d\",\n \"def word_dict():\\n fin = open('words.txt')\\n w_dict = {}\\n for line in fin:\\n word = line.strip()\\n w_dict[word] = word\\n return w_dict\",\n \"def getDictionary(tsvFile, wordIndex, ngram):\\r\\n \\r\\n reader = DescriptionReader(tsvFile, wordIndex, ngram)\\r\\n dictionary = corpora.Dictionary( d for d in reader )\\r\\n\\r\\n # remove stop words and words that appear only once\\r\\n stoplist = [] # might be specified in the furture\\r\\n stop_ids = [dictionary.token2id[stopword] for stopword in stoplist\\r\\n if stopword in dictionary.token2id]\\r\\n once_ids = [tokenid for tokenid, docfreq in dictionary.dfs.items() if docfreq == 1]\\r\\n dictionary.filter_tokens(stop_ids + once_ids) # remove stop words and words that appear only once\\r\\n dictionary.compactify() # remove gaps in id sequence after words that were removed\\r\\n \\r\\n return dictionary\",\n \"def mkwrddct(inputfile):\\n fin = open(inputfile)\\n words = dict()\\n for line in fin:\\n w = line.strip()\\n words[w] = w\\n return words\",\n \"def create_word_map(tokenized_descriptions_file_path, word_dictionary_output_path):\\n if os.path.exists(word_dictionary_output_path):\\n print(\\\"Word map already exists in workspace. Will be reused.\\\")\\n return\\n\\n print(\\\"Word map not found. Generating....\\\")\\n\\n words_list = []\\n words_to_id = {}\\n\\n with open(tokenized_descriptions_file_path, 'r') as file:\\n for line in file:\\n tokens = line.strip().split(\\\",\\\")\\n words_list.extend(tokens[1:])\\n\\n # remove duplicate words\\n words_list = list(set(words_list))\\n\\n # sorting the words\\n words_list = sorted(words_list)\\n for i in range(len(words_list)):\\n words_to_id[words_list[i]] = i\\n\\n with open(word_dictionary_output_path, 'w') as f:\\n [f.write('{0},{1}'.format(key, value) + \\\"\\\\n\\\") for key, value in words_to_id.items()]\",\n \"def construct_dict(self):\\n i = 0\\n self.word2idx = dict()\\n fi = open(self.config.word_vec_fi_glove, 'r')\\n\\n for line in fi:\\n self.word2idx[line.split(\\\" \\\")[0]] = i\\n i += 1\\n\\n self.vocab_size = i\\n self.write_dict()\\n fi.close()\",\n \"def make_mimic_dict(filename):\\r\\n with open(filename, 'r') as file:\\r\\n text = file.read().lower().replace(\\\"'\\\",'').split()\\r\\n mimic_dict = {}\\r\\n prev = ''\\r\\n for word in text:\\r\\n if not prev in mimic_dict:\\r\\n mimic_dict[prev] = [word]\\r\\n else:\\r\\n mimic_dict[prev].append(word)\\r\\n prev = word\\r\\n return mimic_dict\",\n \"def fill_in_dict():\\n # assign a 'data' list from the txt file\\n data = open('words.txt')\\n # assign an empty 'my_dict' dictionary\\n my_dict = dict()\\n\\n for word in data:\\n # fill in dictionarys wit a keys and empty values\\n my_dict[word] = ''\\n return(my_dict)\",\n \"def create_dictionary(filename):\\n file = open(filename, 'r')\\n text = file.read()\\n file.close()\\n words = text.split()\\n d = {}\\n current_word = '$'\\n \\n for next_word in words:\\n if current_word not in d:\\n d[current_word] = [next_word]\\n else:\\n d[current_word] += [next_word]\\n if next_word[-1] == '.' or next_word[-1] == '!' or next_word[-1] == '?':\\n current_word = '$'\\n else:\\n current_word = next_word\\n return d\",\n \"def build_word_dict(self, file_type):\\n file_name = self.config.parser[file_type + '_dir']\\n with open(file_name, 'r') as f:\\n for line in f.readlines():\\n contents = line.strip().split(' ')\\n # an empty line, means seperator for two batch\\n # doc id, means a new batch whose `docid` is doc id\\n # a word and its tag sepaerated by a blank\\n if len(contents) >= 2:\\n word, _ = contents[0], contents[1]\\n self.word_dict.add_word(word)\\n Print(f'word dict from {file_name} is added', 'success')\",\n \"def read_dictionary():\\n with open(FILE, 'r') as f:\\n for vocabulary in f:\\n if vocabulary[0].strip() not in dict_txt:\\n dict_txt[vocabulary[0].strip()] = [vocabulary.strip()]\\n else:\\n dict_txt[vocabulary[0].strip()].append(vocabulary.strip())\",\n \"def load_glove_data():\\n glove_path = path.join('..', 'data', 'glove', 'glove.twitter.27B.200d.txt')\\n f = open(glove_path,'r')\\n \\n model = {}\\n for line in f:\\n splitLine = line.split()\\n word = splitLine[0]\\n embedding = np.array([float(val) for val in splitLine[1:]])\\n model[word] = embedding\\n \\n return model\",\n \"def read_old_glove(filepath):\\n print('reading glove files:', filepath)\\n\\n word2idx = {}\\n word_embed = [['0'] * 300] # word_embed[0] = [0] * 300, represent the <PAD>\\n\\n with open(filepath, 'r') as f:\\n for idx, line in enumerate(f):\\n line_list = line.split()\\n word = ' '.join(line_list[: len(line_list)-300])\\n embed = [num for num in line_list[len(line_list)-300:]]\\n\\n word2idx[word] = idx + 1\\n word_embed.append(embed)\\n\\n return word2idx, word_embed\",\n \"def load_wordlist(filename):\\n # YOUR CODE HERE\\n words = {}\\n f = open(filename, 'rU')\\n text = f.read()\\n text = text.split('\\\\n')\\n for line in text:\\n words[line] = 1\\n f.close()\\n return words\",\n \"def read_dictionary_from_file(self, stem_flag):\\n file_name = \\\"/dictionary.txt\\\" if not stem_flag else \\\"/dictionaryWithStemming.txt\\\"\\n with open(self.posting_and_dictionary_path + file_name, \\\"r\\\") as f:\\n txt = f.readlines()\\n for line in txt:\\n l = line.split(\\\":\\\")\\n pos = l[1].split(\\\",\\\")\\n e = DictionaryElement(pos[0])\\n e.pointer = int(pos[1])\\n e.corpus_tf = int(pos[2])\\n if not stem_flag:\\n self.term_dictionary[l[0]] = e\\n else:\\n self.term_dictionary_with_stemming[l[0]] = e\\n f.close()\",\n \"def word_list():\\n\\n d = {}\\n with open('words.txt') as fin:\\n for line in fin.readlines():\\n word = line.strip().lower()\\n d[word] = True\\n return d\",\n \"def read_dictionary(filename='/Users/Paul/Documents/c06d.txt'):\\n d = dict()\\n fin = open(filename)\\n for line in fin:\\n\\n # skip over the comments\\n if line[0] == '#': continue\\n\\n t = line.split()\\n word = t[0].lower()\\n pron = ' '.join(t[1:])\\n d[word] = pron\\n\\n return d\",\n \"def create_dictionary(file_dir):\\r\\n\\tword_list = []\\r\\n\\tfile_list = read_files(file_dir, \\\"lab\\\") # step 7\\r\\n\\tfor file in file_list:\\r\\n\\t\\twith open(file, 'r') as f:\\r\\n\\t\\t\\ttext = f.read()\\r\\n\\t\\tword_list = store_to_dictionary(text, word_list) # step 8cii\\r\\n\\tmake_dictionary_file(file_dir, word_list) # step 9\\r\",\n \"def create_vocabulary(sentences, path):\\n print('creating vocab..')\\n\\n word_dict = dict(); vocabulary = dict()\\n for sentence in sentences:\\n for word in nltk.word_tokenize(sentence):\\n if word not in word_dict:\\n word_dict[word] = ''\\n word_dict['<s>'] = ''\\n word_dict['</s>'] = ''\\n\\n with open(path, encoding=\\\"utf8\\\") as f:\\n for line in f:\\n word, vec = line.split(' ', 1)\\n if word in word_dict:\\n vocabulary[word] = np.fromstring(vec, sep=' ')\\n\\n print('vocabulary was created successfully!')\\n return vocabulary\",\n \"def load_vocab(vocab_file):\\n index = 0\\n itos = {}\\n stoi = {}\\n with open(vocab_file, \\\"r\\\") as reader:\\n while True:\\n token = reader.readline()\\n if not token:\\n break\\n token = token.strip()\\n itos[index] = token\\n stoi[token] = index\\n index += 1\\n itos[index] = 'style_options'\\n stoi['style_options'] = index\\n itos[index+1] = 'ambience'\\n stoi['ambience'] = index + 1\\n return {'itos': itos, 'stoi': stoi, 'len': len(itos)}\",\n \"def read_dictionary():\\n\\tglobal dictionary\\n\\twith open(FILE, \\\"r\\\") as f:\\n\\t\\tfor words in f:\\n\\t\\t\\tdictionary += words.split()\",\n \"def generate_dictionary(location):\\n f = open('../data/wordlist.txt', 'rb')\\n words = Counter(re.findall('[a-z]+', f.read().lower().decode()))\\n joblib.dump(words, location)\",\n \"def load_glove(path):\\n with open(path) as f:\\n glove = {}\\n for line in f.readlines():\\n values = line.split()\\n word = values[0]\\n vector = np.array(values[1:], dtype='float32')\\n glove[word] = vector\\n return glove\",\n \"def load_glove(path):\\n with open(path) as f:\\n glove = {}\\n for line in f.readlines():\\n values = line.split()\\n word = values[0]\\n vector = np.array(values[1:], dtype='float32')\\n glove[word] = vector\\n return glove\",\n \"def load_terms_dict():\\n \\tfnm = \\\"../datasets/bbc/bbc.terms\\\"\\n \\tterm_dict = {}\\n \\twith open(fnm, \\\"r\\\") as f:\\n \\t\\tfor wordid, line in enumerate(f.readlines()):\\n \\t\\t\\tword = line.strip()\\n \\t\\t\\tterm_dict[wordid] = word\\n \\treturn term_dict\",\n \"def read_dictionary():\\n global dic\\n with open(FILE, 'r') as f:\\n for line in f:\\n word_list = line.split()\\n word = word_list[0].strip()\\n dic.append(word)\",\n \"def load_glove_embeddings():\\n data = open(\\\"glove.6B.50d.txt\\\",'r',encoding=\\\"utf-8\\\")\\n embeddings = []\\n word_index_dict = {'UNK':0}\\n index = 1\\n for lines in data:\\n wordVector = lines.split(\\\" \\\")\\n if(wordVector[0] in string.punctuation or any(char.isdigit() for char in wordVector[0])):\\n continue\\n embeddings.append(wordVector[1:-1])\\n word_index_dict[wordVector[0]] = index\\n index+=1\\n print(\\\"done\\\")\\n\\n return embeddings, word_index_dict\",\n \"def _vector_mapping(self) -> dict:\\n words = set()\\n for file in os.listdir(self.processed_path):\\n doc_path = f\\\"{self.processed_path}/{file}\\\"\\n with open(doc_path, 'r') as f:\\n text_words = f.readline().split()\\n words = words.union(set(text_words))\\n words = list(words)\\n words.sort()\\n\\n return dict(zip(words, range(len(words))))\",\n \"def load_gloves(self, dir):\\n self.word2vec = {}\\n glove_file = os.path.join(dir, 'glove.6B.'+str(self.dim_embed)+'d.txt')\\n with open(glove_file, encoding=\\\"utf8\\\") as f:\\n for line in f:\\n l = line.split()\\n self.word2vec[l[0]] = [float(x) for x in l[1:]]\\n self.word2vec[\\\"<RARE>\\\"] = [0. for i in range(self.dim_embed)]\\n self.word2vec[\\\"<EMPTY>\\\"] = [0. for i in range(self.dim_embed)]\",\n \"def create_dictionary(filename):\\n\\tword_set = set()\\n\\tif os.path.isfile(filename):\\n\\t\\twith open(filename, 'r') as f:\\n\\t\\t\\tfor line in iter(f):\\n\\t\\t\\t\\tword_set.add(line.strip('\\\\n'))\\n\\telse:\\n\\t\\tprint \\\"File not found!\\\"\\n\\treturn word_set\",\n \"def loadGLOVE(filename, vocab):\\n dct = {}\\n vectors = array.array('d')\\n current_idx = 0\\n with codecs.open(filename, \\\"r\\\", encoding=\\\"utf-8\\\") as f:\\n for _, line in enumerate(f):\\n tokens = line.split(\\\" \\\")\\n word = tokens[0]\\n entries = tokens[1:]\\n if not vocab or word in vocab:\\n dct[word] = current_idx\\n vectors.extend(float(x) for x in entries)\\n current_idx += 1\\n word_dim = len(entries)\\n num_vectors = len(dct)\\n tf.logging.info(\\\"Found {} out of {} vectors in Glove\\\".format(num_vectors, len(vocab)))\\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]\",\n \"def extract_dictionary(file):\\n dict = []\\n\\n f = open(file, 'r')\\n for line in f:\\n flist = extract_words(line)\\n\\n for word in flist:\\n if(word not in dict):\\n dict.append(word)\\n\\n f.close()\\n\\n return dict\",\n \"def load_dictionary(filename, encoding='utf_8', skip=0, max_words=50000):\\n\\n d = dict()\\n with codecs.open(filename, 'r', encoding=encoding) as f:\\n line_counter = 0\\n index_counter = 1 # we use 1 for the <EOS> symbol in both languages and 0 for <UNK> words\\n\\n d['<EOS>'] = index_counter\\n index_counter += 1\\n\\n for line in f.readlines():\\n\\n line_counter += 1\\n\\n # check if we have to skip something\\n if line_counter > skip:\\n # split the line\\n s = line.split()\\n # get word and its index\\n # if index > max. number of words, set it to 0\\n if index_counter < max_words:\\n word = s[0]\\n d[word] = index_counter\\n index_counter += 1\\n return d\",\n \"def read_files(self,corpus):\\n\\n file = open(corpus)\\n markov_dictionary = {}\\n word_key = ['None', 'None']\\n word_list = []\\n lastword = \\\"\\\"\\n #use for loop to make lines in file a list\\n for line in file:\\n line = line.strip()\\n words = line.split(\\\" \\\")\\n \\n # generate keys\\n word_key[0] = lastword\\n word_key[1] = words[0]\\n \\n if lastword:\\n markov_dictionary[tuple(word_key)] = self.make_values(corpus, word_key)\\n\\n i = 0\\n while i < len(words) - 1:\\n word_key[0] = words[i]\\n word_key[1] = words[i + 1]\\n \\n markov_dictionary[tuple(word_key)] = self.make_values(corpus, word_key)\\n\\n i += 1\\n\\n lastword = words[len(words) - 1]\\n\\n # print \\\"make_chains\\\", markov_dictionary\\n return markov_dictionary\",\n \"def setKeys():\\n keywords['c++'] = {}\\n with open('cppkeywords.txt', 'r') as f:\\n for i in f:\\n i = i.strip('\\\\n')\\n words = map(str, i.split())\\n key = words[0]\\n words.pop(0)\\n keywords['c++'][key] = list(words)\\n for j in words:\\n MyDict.insert(j)\\n keywords['py'] = {}\\n with open('pykeywords.txt', 'r') as f:\\n for i in f:\\n i = i.strip('\\\\n')\\n words = map(str, i.split())\\n key = words[0]\\n words.pop(0)\\n keywords['py'][key] = list(words)\\n for j in words:\\n MyDict.insert(j)\",\n \"def build_dict(fname):\\n\\t\\n\\twith open(fname) as file:\\n\\n\\t\\tword_count_dict = {}\\n\\n\\t\\tfor line in file:\\n\\t\\t\\tline = line.rstrip()\\n\\t\\t\\tline =line.split(' ')\\n\\t\\t\\tfor word in line:\\n\\t\\t\\t\\tword = word.strip('\\\"!.,?_;():')\\n\\t\\t\\t\\tword = word.lower()\\n\\t\\t\\t\\tword_count_dict[word] = word_count_dict.get(word, 0) + 1\\n\\t\\t#return word_count_dict\\n\\n\\t\\tfor each in word_count_dict:\\n\\t\\t\\tcount = word_count_dict[each]\\n\\t\\t\\tprint(each, count)\\n\\n\\t\\treturn\",\n \"def insert_file_to_dictionary():\\r\\n file = open(sys.argv[1], \\\"r\\\")\\r\\n #movies is my the dictionary\\r\\n movies = {}\\r\\n for line in file:\\r\\n read = line.strip().split(', ')\\r\\n for i in range(1, len(read)):\\r\\n if not read[i] in movies:\\r\\n movies[read[i]] = {read[0]}\\r\\n else:\\r\\n movies[read[i]].add(read[0])\\r\\n return movies\",\n \"def dictionary_creation(filename):\\n\\tfp = open(filename)\\n\\td = dict()\\n\\tfor line in fp:\\n\\t\\t# print line\\n\\t\\tfor word in line.split():\\n\\t\\t\\tword = word.strip(string.punctuation + string.whitespace)\\n\\t\\t\\t# print word\\n\\t\\t\\tif len(word) >5:\\n\\t\\t\\t\\tif word not in d:\\n\\t\\t\\t\\t\\t# print 'in'\\n\\t\\t\\t\\t\\td[word] = 1\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t# print 'not in'\\n\\t\\t\\t\\t\\td[word] += 1\\n\\treturn d\\n\\n\\tfp.close()\",\n \"def read_dictionary():\\n with open(FILE, 'r') as f:\\n for line in f:\\n words_lst = line.split()\\n for word in words_lst:\\n dict_list.append(word)\",\n \"def rm_stopwords(file_path, word_dict):\\n\\n # read stop word dict and save in stop_dict\\n stop_dict = {}\\n with open(word_dict) as d:\\n for word in d:\\n stop_dict[word.strip(\\\"\\\\n\\\")] = 1\\n # remove tmp file if exists\\n if os.path.exists(file_path + \\\".tmp\\\"):\\n os.remove(file_path + \\\".tmp\\\")\\n\\n print(\\\"now remove stop words in %s.\\\" % file_path)\\n # read source file and rm stop word for each line.\\n with open(file_path) as f1, open(file_path + \\\".tmp\\\", \\\"w\\\") as f2:\\n for line in f1:\\n tmp_list = [] # save words not in stop dict\\n words = line.split()\\n for word in words:\\n if word not in stop_dict:\\n tmp_list.append(word)\\n words_without_stop = \\\" \\\".join(tmp_list)\\n to_write = words_without_stop + \\\"\\\\n\\\"\\n f2.write(to_write)\\n\\n # overwrite origin file with file been removed stop words\\n shutil.move(file_path + \\\".tmp\\\", file_path)\\n print(\\\"stop words in %s has been removed.\\\" % file_path)\",\n \"def new_counts_dict():\\n\\n\\tIN_FILES = [\\\"../_semtag_dataset_webanno_tfidf_inimigo.txt\\\",\\\"../_semtag_dataset_webanno_tfidf_publico.txt\\\" ]\\n\\n\\ttxt = []\\n\\tfor in_file in IN_FILES:\\n\\t with codecs.open(in_file,\\\"r\\\",\\\"utf-8\\\") as fid:\\n\\t txt += fid.readlines()\\n\\t#words\\n\\twords = [w for m in txt for w in m.split()]\\n\\t#unique words\\n\\twords = list(set(words))\\n\\t#word index\\n\\twrd2idx = {w:-1 for w in words}\\n\\n\\tset_trace()\\n\\t\\n\\twith open(COUNTS_DIC,\\\"w\\\") as fod:\\n\\t\\tcPickle.dump(wrd2idx, fod, cPickle.HIGHEST_PROTOCOL)\",\n \"def load_glove_vectors(filename, vocab):\\n dct = {}\\n vectors = array.array('d')\\n current_idx = 0\\n with open(filename, \\\"r\\\", encoding=\\\"utf-8\\\") as f:\\n for _, line in enumerate(f):\\n tokens = line.split(\\\" \\\")\\n word = tokens[0]\\n entries = tokens[1:]\\n if not vocab or word in vocab:\\n dct[word] = current_idx\\n vectors.extend(float(x) for x in entries)\\n current_idx += 1\\n word_dim = len(entries)\\n num_vectors = len(dct)\\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]\",\n \"def load_train_word_dict():\\n train_dict = {}\\n with open(TRANSCRIPTION_PATH) as file:\\n for line in file:\\n if int(line[0:3]) < 300:\\n word_id, transcript = str.split(line, \\\" \\\")\\n train_dict[word_id] = transcript.rstrip('\\\\n')\\n return train_dict\",\n \"def create_dict(fd):\\n # initialize an empty dictionary\\n full_dict = {}\\n # loop through file\\n for line in fd:\\n # lowercase everything in line, then split line into a list\\n line = line.lower().split()\\n # loop through elements in the list of words in the splitted line\\n for word in line:\\n # strip words from puncuation using string module\\n word = word.strip(string.punctuation)\\n # if words contains only alphabatic characters and of length > 1\\n if word.isalpha() and len(word)!= 1:\\n if len(word) in full_dict:\\n full_dict[len(word)].add(word)\\n else:\\n full_dict[len(word)] = set()\\n full_dict[len(word)].add(word)\\n return full_dict\",\n \"def read_data(file_path):\\n words=[]\\n dic_word={}\\n actual_text=[]\\n for line in open(file_path,encoding='utf-8'):\\n words_line=line.strip().split(' ')\\n for ite in words_line:\\n if ite not in dic_word:\\n dic_word[ite]=1\\n words.extend(words_line)\\n actual_text.append(words_line)\\n\\n\\n #with zipfile.ZipFile(file_path) as f:\\n #words = tf.compat.as_str(f.read(f.namelist()[0])).split()\\n\\n return words,len(dic_word),actual_text\",\n \"def createDict(self):\\n data = d.Dictionary.dictionary\\n while True:\\n filtered = [line.strip() for line in data if len(line) == self.wordLen]\\n if len(filtered) == 0:\\n self.setNewLen()\\n else:\\n break\\n return filtered\",\n \"def ReadMorphit(self):\\r\\n self.words = {}\\r\\n with codecs.open(self.MorphItFileName, 'r', 'utf-8') as f:\\r\\n for line in f.readlines():\\r\\n line = line.split()\\r\\n try:\\r\\n# print (line)\\r\\n self.words[line[0]] = line[2][:3]\\r\\n# if line[2][:3] in self.verbTags:\\r\\n# line[2]=line[2].split(u'+')\\r\\n# line[2][0]=line[2][0][line[2][0].find(u':')+1:]\\r\\n except:\\r\\n pass\\r\\n return self.words\",\n \"def make_frequency_dict(path):\\n filepath = path#'germanWordList_03.csv'\\n wordDict = {}\\n f = open(filepath,'r')\\n for line in f:\\n split = line.split(\\\",\\\")\\n word = (split[0]).lower()\\n temp = float(split[1])\\n if word in wordDict:\\n val = float(wordDict[word])\\n if val > 0:\\n num = (temp * val) / (val + temp)\\n else:\\n num = temp\\n else:\\n num = temp\\n wordDict[word]= num\\n return wordDict\",\n \"def load_file(self, file_path):\\n f = open(file_path, \\\"r\\\")\\n sentences = f.readlines()\\n \\n word_count = 0\\n\\n for sentence in sentence: \\n for word in sentence.strip().split(\\\" \\\"):\\n if not (word in self.word_id): #word not in dictionary\\n word_id[word] = word_count\\n word_count += 1\\n\\n #self.doc = [[self.word_id[word] for word in sentence.strip().split(\\\" \\\")] for sentence in sentences]\",\n \"def load_tags_vocab(load_path: str) -> dict:\\n tags_vocab = dict()\\n with open(load_path, 'r') as f:\\n lines = f.readlines()\\n f.close()\\n\\n for line in lines:\\n key, val = line[:-1].split(' ') # \\\"\\\\t\\\"\\n tags_vocab[key] = val\\n\\n return tags_vocab\",\n \"def load_glove_vec(fname, vocab):\\n word_vecs = {}\\n with open(fname, \\\"rb\\\") as f:\\n for i,line in enumerate(f):\\n L = line.split()\\n word = L[0].lower()\\n if word in vocab:\\n word_vecs[word] = np.array(L[1:], dtype='float32')\\n return word_vecs\",\n \"def load_dic():\\r\\n f = open('../data/phrases-freq.txt')\\r\\n d = {}\\r\\n for line in f:\\r\\n line = line.strip().decode('utf-8')\\r\\n if line == '' or line[0] == '#':\\r\\n continue\\r\\n else:\\r\\n k, v = line.split()\\r\\n d[k] = int(v)\\r\\n return d\",\n \"def create_bow(vocab, filepath):\\n bow = {}\\n # TODO: add your code here\\n wordcount = 0\\n wordcountnone = 0\\n c = 0\\n\\n for i in vocab:\\n c+=1\\n with open(filepath, 'r', encoding=\\\"utf-8\\\") as doc: ###############################################\\n for word in doc:\\n word = word.strip()\\n if(c==1):\\n if (word not in vocab):\\n wordcountnone += 1\\n if(i == str(word)):\\n wordcount += 1\\n #print(wordcount)\\n if(wordcount > 0):\\n bow[i] = wordcount\\n wordcount = 0\\n if(wordcountnone != 0):\\n bow[None] = wordcountnone\\n return bow\",\n \"def load_dictionary(location='../data/wordlist.pkl'):\\n words = joblib.load(location)\\n # Simple plurals not necessary since removed in word correction\\n manual_addition = ['sis', 'vixen' ,'ho', 'hoe', 'aint', 'nigga', 'nigger', 'bitch', 'bitches', 'lmao', 'pussy',\\n 'fuck', 'fucking', 'fag', 'faggot', 'hater', 'lol', 'yall', 'nfl', 'fucked', 'nips', 'crap',\\n 'whitey', 'ghetto', 'mac', 'tho', 'jamming', 'titties', 'dyke', 'fb', 'lmfao', 'bae', 'kanye',\\n 'coon', 'smh', 'tweet', 'retweet', 'nbc', 'jk', 'im']\\n for word in manual_addition:\\n words[word] = 99999 # add word to counter\\n return words\",\n \"def create_lemma_dict(lemma_file):\\n\\tacademic_words= open(lemma_file)\\n\\tLEMMA_DICT = {}\\n\\tfor line in academic_words:\\n\\t\\tline =line.rstrip().rstrip(',')\\n\\t\\twords = line.split(',')\\n\\t\\tstem = words[0]\\n\\t\\tfor word in words:\\n\\t\\t\\tLEMMA_DICT[word] = stem\\n\\n\\treturn LEMMA_DICT\",\n \"def word_frequency():\\n\\n song = open(\\\"data/yellow_submarine.txt\\\")\\n d = dict()\\n for line in song:\\n line = line.strip()\\n line = line.lower()\\n punctuations = \\\"\\\"\\\"!()-[]{};:'\\\"\\\\,<>./?@#$%^&*_~\\\"\\\"\\\" # remove punctuation https://www.programiz.com/python-programming/examples/remove-punctuation\\n no_punct = \\\"\\\" # remove punctuation\\n for char in line: # remove punctuation\\n if char not in punctuations: # remove punctuation\\n no_punct = no_punct + char # remove punctuation\\n words = line.split(\\\" \\\")\\n for word in words:\\n d[word] = d.get(word, 0) + 1\\n return d\",\n \"def __init__(self, filename):\\n\\n self.term_dict = {}\\n for line in open(filename):\\n if line.startswith(\\\"#\\\"):\\n continue\\n\\n #print line\\n word, w_type = line.strip().split(\\\"\\\\t\\\")\\n self.term_dict[word.strip().lower()] = \\\"CHESS_\\\" + w_type.strip().lower()\",\n \"def buildCorpus(self, filename, stopwords_file=None):\\n with open(filename, 'r') as infile:\\n # use pattern.subs\\n # doclines = [line.rstrip().lower().split(' ') for line in infile]\\n doclines = [self.help_clean(line) for line in infile]\\n n_docs = len(doclines)\\n self.vocab = list({v for doc in doclines for v in doc})\\n if stopwords_file:\\n with open(stopwords_file, 'r') as stopfile:\\n stops = stopfile.read().split()\\n self.vocab = [x for x in self.vocab if x not in stops]\\n self.vocab.sort()\\n self.documents = []\\n for i in range(n_docs):\\n self.documents.append({})\\n for j in range(len(doclines[i])):\\n if doclines[i][j] in self.vocab:\\n self.documents[i][j] = self.vocab.index(doclines[i][j])\",\n \"def buildDict(self, words):\\r\\n for word in words:\\r\\n self.trie.addWord(word)\",\n \"def make_stopwords(filepath='stopwords.txt'):\\n sw = open(filepath, \\\"r\\\")\\n my_stopwords = sw.read()\\n my_stopwords = my_stopwords.split(\\\", \\\")\\n sw.close()\\n\\n all_stopwords = stopwords.words('english')\\n all_stopwords.extend(my_stopwords)\\n return all_stopwords\",\n \"def load_data_for_dict(path, voc_path, need_rem_punkt=True):\\n \\n table = str.maketrans('', '', string.punctuation)\\n\\n with open(voc_path) as f:\\n word_to_idx = dict(json.load(f))\\n dict_size = len(word_to_idx)\\n \\n with open(path, \\\"r\\\") as fin:\\n for line in fin:\\n line = line.lower()\\n sentence = []\\n for word in line.split():\\n if need_rem_punkt: \\n word = word.translate(table) # remove punctuation\\n if word not in word_to_idx:\\n word_to_idx[word] = dict_size\\n dict_size += 1\\n\\n with open(voc_path, \\\"w+\\\") as fout:\\n json.dump(word_to_idx, fout)\",\n \"def build_words_map(self, to_clip=True):\\n import clipboard\\n import json_utils\\n words_map = {}\\n rev_map = {}\\n rs = []\\n all_words=self.get_all_words()\\n for word in all_words:\\n key = self.get_norm_key(word)\\n if len(key) > 0:\\n if key in words_map:\\n words_map[key].append(word)\\n else:\\n words_map[key] = [word]\\n rev_map[word] = key\\n rs.append('%s %s' % (key, word))\\n\\n print('write to', self.target_file)\\n json_utils.write_json_to_file(self.target_file, words_map)\\n json_utils.write_json_to_file(self.target_file_rev, rev_map)\\n if to_clip:\\n print('copy to clipboard ...')\\n clipboard.copy('\\\\n'.join(rs))\\n print('done')\",\n \"def build_stopwords():\\r\\n\\tprint('\\\\nbuilding stopwords')\\r\\n\\t\\r\\n\\tif load_stopwords():\\r\\n\\t\\treturn\\r\\n\\r\\n\\tglobal stopwords\\r\\n\\tstopwords = nltk.corpus.stopwords.words('english')\\r\\n\\tfor f in os.listdir(paths.path_data_stopwords):\\r\\n\\t\\tpath_stopwords = paths.path_data_stopwords + '/' + f\\r\\n\\t\\twith open(path_stopwords,'r') as f:\\r\\n\\t\\t\\tfor l in f:\\r\\n\\t\\t\\t\\tw = l.strip()\\r\\n\\t\\t\\t\\tw = re.sub(r\\\"[\\\\x80-\\\\xff]\\\",\\\" \\\",w)\\r\\n\\t\\t\\t\\tif (w not in stopwords):\\r\\n\\t\\t\\t\\t\\tstopwords.append(w)\\r\\n\\t\\r\\n\\t# wip improve with POS and remove numbers\\r\\n\\twith open(paths.path_data_stopwords_txt,'w') as outf:\\r\\n\\t\\toutf.write('\\\\n'.join(stopwords))\\r\\n\\t\\r\\n\\tprint('\\\\nstopword count : ' + str(len(stopwords)))\",\n \"def load_words(file_path: str) -> List[Word]:\\n \\n words = load_words_raw(file_path)\\n \\n \\n words = remove_stop_words(words)\\n\\n \\n words = remove_duplicates(words)\\n \\n return words\",\n \"def dict_make():\\n f = open('words.txt','r')\\n dict1 = f.read().splitlines()\\n return filter(lambda z:len(z) >= 4, dict1)\",\n \"def load_stop_words(stop_word_file):\\n stop_words = []\\n for line in open(stop_word_file):\\n if line.strip()[0:1] != \\\"#\\\":\\n for word in line.split(): # in case more than one per line\\n stop_words.append(word)\\n return stop_words\",\n \"def load_words():\\n with open(DICTIONARY) as f:\\n return [line.strip() for line in f]\",\n \"def get_word_list(file_name, to_skip_or_not_to_skip):\\n fin = open(file_name) #opening file\\n histogram={} \\n if to_skip_or_not_to_skip == True: #if I want to skip the header this is set to True\\n skip_first_part(fin)\\n for line in fin: #runs through lines of book file\\n line = line.replace(\\\"-\\\",\\\" \\\") #takes out dashed, underscroes, numbers, whitespaces, and punctuation\\n line = line.replace(\\\"_\\\",\\\" \\\")\\n to_remove = string.punctuation + string.whitespace + '0123456789' \\n for word in line.split():\\n word = word.strip(to_remove) #running through all words in each line \\n if word == 'God' or 'Lord':\\n pass\\n else:\\n word = word.lower()\\n histogram[word] = histogram.get(word, 0)+1\\n return histogram\",\n \"def load_defs():\\n # Load word definitions\\n fname = 'word-definitions.txt'\\n with open(fname) as fh:\\n lines = fh.readlines()\\n \\n # Create dictionary keyed by lowercase word\\n def_tbl = dict()\\n for line in lines:\\n # split the dictionary line at the first space\\n word, word_def = line.split(sep=None, maxsplit=1)\\n # add this entry to the dictionary\\n word = word.lower()\\n def_tbl[word] = word_def.rstrip()\\n return def_tbl\",\n \"def load_vocab(filename):\\n try:\\n d = dict()\\n with open(filename, encoding='utf-8') as f:\\n for idx, word in enumerate(f):\\n word = word.strip()\\n d[word] = idx\\n\\n except IOError:\\n raise MyIOError(filename)\\n return d\",\n \"def load_wordlist(self, filename):\\n reg1 = re.compile(\\\"^([1-6]{5})[ \\\\t]+(.*)$\\\")\\n f = open(filename, 'r')\\n \\n if(self.generate):\\n wordlist = []\\n reg2 = re.compile(\\\"^(\\\\S*)$\\\")\\n for line in f:\\n m1 = reg1.match(line)\\n m2 = reg2.match(line)\\n \\n if(m1):\\n wordlist.append(m1.group(2))\\n elif(m2):\\n wordlist.append(m2.group(1))\\n \\n else:\\n wordlist = {}\\n for line in f:\\n m = reg1.match(line)\\n if(m):\\n wordlist[int(m.group(1))] = m.group(2)\\n \\n if((not self.generate and len(wordlist) < 7776) or \\n (self.generate and len(wordlist) < 2**13)):\\n stderr.write(\\\"Word list is too short\\\\n\\\")\\n exit(5)\\n \\n self.wordlist = wordlist\",\n \"def _create_deleted_variation_2_dictionary_words(self):\\n deleted_variation_2_dictionary_words = defaultdict(set)\\n for word in self._word_2_frequency.keys():\\n deleted_variations = chain(self._one_edit_deleted_variations(word), self._two_edits_deleted_variations(word))\\n for deleted_variation in deleted_variations:\\n deleted_variation_2_dictionary_words[deleted_variation].add(word)\\n return deleted_variation_2_dictionary_words\",\n \"def learn(filename):\\n word_dict = {} # Create empty dictionary\\n first = None\\n prev = None\\n with open(filename, 'r', encoding='utf-8') as file:\\n for line in file:\\n list_words = line.lower().split()\\n text = []\\n for word in list_words:\\n # take out leading and trailing punctuation characters\\n words = word.strip(string.punctuation + string.digits)\\n word_len = len(words)\\n if word_len >= 1:\\n text.append(words)\\n\\n if first is None:\\n # Get the first word in the text file\\n first = text[0]\\n # iterate over text\\n if prev:\\n text.insert(0, prev)\\n for counter, word in enumerate(text):\\n if word not in word_dict:\\n word_dict[word] = list()\\n if counter < (len(text) - 1):\\n following = counter + 1\\n word_dict[word].append(text[following])\\n prev = text[-1]\\n return first, word_dict # return a tuple\",\n \"def preprocess(in_file: str, file_out: str) -> tuple:\\r\\n try:\\r\\n stop_words = []\\r\\n if os.path.isfile(\\\"StopWords.pkl\\\"):\\r\\n with open(\\\"StopWords.pkl\\\", mode=\\\"rb\\\") as pkl:\\r\\n stop_words = pickle.load(pkl)\\r\\n else:\\r\\n with open(\\\"StopWords.txt\\\", mode=\\\"r\\\") as f1:\\r\\n for line in f1:\\r\\n stop_words.append(line.strip(\\\"\\\\n\\\"))\\r\\n with open(\\\"StopWords.pkl\\\", mode=\\\"wb\\\") as pkl:\\r\\n pickle.dump(stop_words, pkl)\\r\\n\\r\\n vocab = []\\r\\n corpus = []\\r\\n with open(in_file, mode=\\\"r\\\") as f:\\r\\n for line in f:\\r\\n line = line.rsplit(sep=\\\"\\\\t\\\")\\r\\n sent = line[1].strip(\\\" \\\\n\\\")\\r\\n sent = int(sent)\\r\\n\\r\\n sentence = process_sentence(line[0])\\r\\n\\r\\n [sentence.remove(w) for w in sentence if w in stop_words or w == \\\"\\\"]\\r\\n corpus.append([sentence, sent])\\r\\n vocab += list(set(sentence) - set(vocab))\\r\\n\\r\\n # Sort lists alphabetically\\r\\n corpus = sorted(corpus)\\r\\n vocab = sorted(vocab)\\r\\n vocab.append(\\\"classlabel\\\")\\r\\n to_file(file_out, vocab, corpus)\\r\\n\\r\\n return vocab, corpus\\r\\n except:\\r\\n catch_err()\",\n \"def load_dictionary(filename):\\n\\n word_list = []\\n freq_sum = 0\\n\\n # nacitanie zo suboru\\n with open(filename) as f:\\n for line in f:\\n freq, val = line.split()\\n word_list.append(Word(int(freq), val))\\n freq_sum += int(freq)\\n\\n # lexikograficke usporiadanie slov\\n word_list_sorted = sorted(word_list, key=operator.attrgetter('value'))\\n\\n return word_list_sorted, freq_sum\",\n \"def stopping():\\r\\n file_content = read_file() # file_content: Dictionary\\r\\n common_words_list = read_common_words() # common_words_list: List\\r\\n file_content_with_stopping = remove_common_words(file_content, common_words_list)\\r\\n return file_content_with_stopping\",\n \"def readAllWordFeatures(labelFilePathTuples):\\n fileFeatureDict = {}\\n\\n for t in labelFilePathTuples:\\n wordFeatures = readWordFeatures(t)\\n fileFeatureDict[t[1]] = wordFeatures\\n return fileFeatureDict\",\n \"def file_to_dictionary():\\n\\n return;\",\n \"def constitute_word_dict(self):\\r\\n\\r\\n #IS THIS NECESSARY WITH DATABASE??\\r\\n\\r\\n if self.using_shelf:\\r\\n for k_temp in self.get_words():\\r\\n self.delete_word(k_temp)\\r\\n\\r\\n for i_temp in [a_temp for a_temp in self.indexes()\\r\\n if Index(a_temp) > Index(str(0))]:\\r\\n\\r\\n self.add_search_words(Index(i_temp),\\r\\n self.get_text_from_note(i_temp))\\r\\n display.noteprint((alerts.ATTENTION,\\r\\n alerts.WORD_DICT_CONSTITUTED))\",\n \"def make_dictionary(self, train_file, validation_file, test_file):\\n print 'constructing vocabulary'\\n train_set, test_set, valid_set = set(), set(), set()\\n label_set = set()\\n ftrain = io.open(train_file, 'r')\\n for line in ftrain:\\n entity, label = map(clean, line.rstrip().split('\\\\t')[:2])\\n train_set |= set(list(entity))\\n label_set |= set(label.split(','))\\n\\n fvalid = io.open(train_file, 'r')\\n for line in fvalid:\\n entity, label = map(clean, line.rstrip().split('\\\\t')[:2])\\n valid_set |= set(list(entity))\\n label_set |= set(label.split(','))\\n\\n ftest = io.open(test_file, 'r')\\n for line in ftest:\\n entity, label = map(clean, line.rstrip().split('\\\\t')[:2])\\n test_set |= set(list(entity))\\n # label_set |= set(label.split(','))\\n \\n print '# chars in training ', len(train_set)\\n print '# chars in validation ', len(valid_set)\\n print '# chars in testing ', len(test_set)\\n print '# chars in (testing-training-validation) ', len(test_set-train_set-valid_set)\\n print '# labels', len(label_set)\\n\\n vocabulary = list(train_set | test_set | valid_set)\\n vocab_size = len(vocabulary)\\n chardict = dict(zip(vocabulary, range(1,vocab_size+1)))\\n chardict[u' '] = 0\\n labeldict = dict(zip(list(label_set), range(len(label_set))))\\n \\n return chardict, labeldict\",\n \"def build_word_dict(self, examples):\\n word_dict = TokenDictionary()\\n for w in self.load_words(examples):\\n word_dict.add(w)\\n return word_dict\",\n \"def get_keywords(text):\\n tokens = [word.lower() for word in word_tokenize(text)]\\n\\n # tag words as verb, noun etc\\n tagged_words = pos_tag(tokens)\\n\\n # retrieve list of boring words from file\\n stopwords_file = os.path.join(BASE_DIR, 'data', 'stopwords.txt')\\n with open(stopwords_file, 'r', encoding='utf-8') as f:\\n stopwords = [line.rstrip(linesep) for line in f]\\n \\n #We don't want keywords to contain anything in this list\\n forbidden = ['.',',',';',':','?','!','+',')','(','[',']','/','<','>','\\\"','©','1','2','3','4','5','6','7','8','9','0']\\n\\n # NLTK Chunking - detects noun phrases and phrases of form verb noun or adj noun\\n patterns = \\\"\\\"\\\"NP: {<JJ>*<NN><NNS>}\\n {<JJR><NNS>}\\n {<JJ>*<NNS>}\\n {<NN><NNS>} \\n {<JJ><NNS>}\\n {<JJ>*<NN>*}\\n {<NN>*}\\n {<NNS>*}\\\"\\\"\\\"\\n chunker = RegexpParser(patterns)\\n chunks = chunker.parse(tagged_words)\\n\\n #these are the phrases we want, as lists within a list\\n validphrases = []\\n for t in chunks.subtrees():\\n if t.label() == 'NP':\\n validphrases.append([x for x,y in t.leaves()])\\n\\n #turning lists within lists into actual noun phrases i.e [[radiation], [breast,cancer]] becomes [radiation, breast cancer]\\n #sorry for my horrible code\\n #trees suck\\n lemmatizables = []\\n for sublist in validphrases:\\n lemmatizables.append(' '.join(sublist))\\n\\n lemmatizer = WordNetLemmatizer()\\n lems = [lemmatizer.lemmatize(x) for x in lemmatizables]\\n\\n #removing stopwords after lemmatizinga, then removing anything containing punctuation or a number\\n lems = filter(lambda lem: lem not in stopwords, lems)\\n lems = filter(lambda lem: not any(char in lem for char in forbidden), lems)\\n\\n return tuple(lems)\",\n \"def read_gulordava_corpus(corpus_dir: str) -> dict:\\n def _read_file(path: str) -> List[str]:\\n with open(path, \\\"r\\\") as f:\\n return f.readlines()\\n\\n sentences = _read_file(f\\\"{corpus_dir}/generated.text\\\")\\n sentence_info = _read_file(f\\\"{corpus_dir}/generated.tab\\\")[1:] # Skip header line\\n labelled_corpus = {}\\n\\n for i, sentence in enumerate(sentences):\\n right_info, wrong_info = sentence_info[2*i], sentence_info[2*i+1]\\n\\n # Parse lines\\n right_info, wrong_info = right_info.split(\\\"\\\\t\\\"), wrong_info.split(\\\"\\\\t\\\")\\n constr_id, sent_id, correct_number, right_form, class_, type_ = right_info[1:7]\\n len_context, len_prefix, sent = right_info[11:14]\\n constr_id_wrong, sent_id_wrong, _, wrong_form, class_wrong, type_wrong = wrong_info[1:7]\\n sent_wrong = wrong_info[13]\\n\\n assert class_ == \\\"correct\\\" and class_wrong == \\\"wrong\\\"\\n assert constr_id == constr_id_wrong and sent_id == sent_id_wrong and sent == sent_wrong and type_ == type_wrong\\n\\n len_prefix, len_context = int(len_prefix), int(len_context)\\n subj_pos = len_prefix - len_context\\n verb_pos = len_prefix\\n sentence = sent.split()\\n\\n misc_info = {\\n \\\"raw\\\": sent,\\n \\\"subj_pos\\\": subj_pos,\\n \\\"verb_pos\\\": verb_pos,\\n \\\"right_form\\\": right_form,\\n \\\"wrong_form\\\": wrong_form,\\n \\\"correct_number\\\": correct_number,\\n \\\"sent_id\\\": sent_id,\\n \\\"constr_id\\\": constr_id,\\n \\\"type\\\": type_\\n }\\n\\n labelled_sentence = {\\n \\\"sen\\\": sentence, \\\"labels\\\": [0 if correct_number == \\\"sing\\\" else 1] * len(sentence), **misc_info\\n }\\n labelled_corpus[i] = labelled_sentence\\n\\n return labelled_corpus\",\n \"def read_file(filename):\\n print(\\\"Reading dictionary: \\\" +filename)\\n word_dict = set()\\n\\n dictionary = open(filename)\\n\\n # Read each word from the dictionary\\n for word in dictionary:\\n # Remove the trailing newline character\\n word = word.rstrip('\\\\n')\\n\\n # Convert to lowercase\\n word = word.lower()\\n\\n word_dict.add(word)\\n\\n dictionary.close()\\n\\n return word_dict\",\n \"def load(filename):\\n\\n print \\\"Loading dictionary...\\\"\\n dictionary = Dictionary()\\n print \\\" Loading file...\\\"\\n whole_file = file(filename).read().upper()\\n print \\\" Splitting file...\\\"\\n words = whole_file.split()\\n print \\\" Removing unsuitable words...\\\"\\n words = dictionary.remove_unsuitable_words(words)\\n print \\\" Building data structures...\\\"\\n dictionary.set_words(words)\\n\\n print \\\" Loaded %d words\\\" % len(dictionary.words)\\n print \\\" Unique letter size:\\\"\\n print \\\" No blanks: %d\\\" % len(dictionary.letters_map)\\n print \\\" One blank: %d\\\" % len(dictionary.letters_map_one_blank)\\n print \\\" Two blanks: %d\\\" % len(dictionary.letters_map_two_blanks)\\n\\n return dictionary\",\n \"def load_vocabulary():\\n global vocabulary_list, vocabulary_dict\\n vocabulary_list = []\\n vocabulary_dict = {}\\n\\n with open(_VOCABULARY_PATH, 'r') as f:\\n for index, line in enumerate(f):\\n line = line.strip()\\n vocabulary_dict[line] = index\\n vocabulary_list.append(line)\",\n \"def word_frequency_in_file(filename):\\n words = {}\\n fin = open(filename)\\n punctuation = string.punctuation\\n for line in fin:\\n line = line.translate( # Replace punctuation with spaces\\n str.maketrans(punctuation, ' ' * len(punctuation)))\\n line = line.lower()\\n line_words = line.split()\\n for word in line_words: # Process each word in the line.\\n if word in words:\\n words[word] += 1\\n else:\\n words[word] = 1\\n return words\",\n \"def load_morphoit(self, path=None):\\n path = path or self.path\\n # f = open(path,'r')\\n f = codecs.open(path, 'r', 'latin-1')\\n lines = f.readlines()\\n f.close()\\n self.lemma_dict.clear()\\n self.tag_dict.clear()\\n self.suffix_dict.clear()\\n self.word_tag_dict.clear()\\n n_entries = 0\\n for line in lines:\\n line = line.strip()\\n if line:\\n # entry = line.split()\\n entry = line.split(u'\\\\u0009') # entry has TAB delimited items\\n n = len(entry)\\n word = entry[0]\\n if n > 1:\\n lemma = entry[1]\\n else:\\n lemma = 'lemma?'\\n if n > 2:\\n tags = entry[2]\\n if tags:\\n splitted_tags = tags.split(u':')\\n tag = splitted_tags[0]\\n if tag == u'SMI': # smile ?\\n continue\\n else:\\n tag = 'tag?'\\n n_entries += 1\\n if self.use_defaultdict:\\n self.lemma_dict[lemma].append(word)\\n self.tag_dict[tag] += 1\\n self.word_tag_dict[word][tag] += 1\\n else:\\n words = self.lemma_dict.get(lemma, []); words.append(word); self.lemma_dict[lemma] = words\\n self.tag_dict[tag] = self.tag_dict.get(tag, 0) + 1\\n dict = self.word_tag_dict.get(word, {})\\n \\\"\\\"\\\" only occurrence in corpus will increment the counter !\\n dict[tag] = dict.get(tag, 0) + 1\\n \\\"\\\"\\\"\\n if dict.get(tag, None) is None:\\n dict[tag] = 0\\n self.word_tag_dict[word] = dict\\n length = len(word)\\n reversed = util.reverse(word)\\n max = min(length, MAX_SUFFIX)\\n for i in range(MIN_SUFFIX, max):\\n suffix = reversed[:i]\\n if self.use_defaultdict:\\n self.suffix_dict[suffix][tag] += 1\\n else: # defaultdicts cannot be pickled !\\n dict = self.suffix_dict.get(suffix, {})\\n dict[tag] = dict.get(tag, 0) + 1\\n self.suffix_dict[suffix] = dict\\n return len(lines), n_entries\",\n \"def load():\\n for line in open(config.filepath, 'r'):\\n line = line.strip()\\n line_sorted = ''.join(sorted(line))\\n\\n if line_sorted not in Words.hashed:\\n Words.hashed[line_sorted] = []\\n\\n # Store the real hashed as a list\\n # We need line_sorted as the key for fast lookup later\\n Words.hashed[line_sorted].append(line)\\n\\n # Also add the word to a standard list\\n # We'll use this to quickly determine wordiness later\\n Words.words.append(line)\",\n \"def read_from_file():\\n\\n plik=open('data.txt')\\n for line in plik:\\n (key, temp, weat, pres)=line.split()\\n dict_from_file[key]=[temp, weat.replace('_',' '), pres]\",\n \"def _parse_word_dict(dict_f_name):\\n if os.path.isfile(dict_f_name):\\n word_dict = {}\\n with open(dict_f_name) as f:\\n for line in f:\\n w, idx = line.strip().split(\\\" \\\")\\n word_dict[w.strip()] = int(idx)\\n return word_dict\\n else:\\n error(\\\"Dict not exists: %s\\\" % dict_f_name)\",\n \"def get_weibo_data(vocab_file, vector_file):\\n if os.path.exists(\\\"word_misc.pkl\\\"):\\n return cPickle.load(open(\\\"word_misc.pkl\\\", \\\"rb\\\"))\\n\\n word_misc, word2id, id2word = {}, {}, {}\\n word_count = 0\\n\\n # vocab file\\n print \\\"Building vocabulary ...\\\"\\n for lines in open(vocab_file).readlines():\\n word = lines.split()[0]\\n if not is_unwanted_words(word, ['', '\\\\n']):\\n word2id[word] = word_count\\n id2word[word_count] = word\\n word_count += 1\\n word2id['_START'] = word_count\\n id2word[word_count] = '_START'\\n word_count += 1\\n word2id['_END'] = word_count\\n id2word[word_count] = '_END'\\n word_count += 1\\n word2id['_UNK'] = word_count\\n id2word[word_count] = '_UNK'\\n word_count += 1\\n word2id['_MASK'] = word_count\\n id2word[word_count] = '_MASK'\\n word_count += 1\\n print \\\"Vocabulary size:\\\", word_count\\n\\n # Initialization is refered to in https://www.tensorflow.org/versions/r0.7/tutorials/word2vec/index.html\\n word_emb = (1/np.sqrt(word_count)*(2*np.random.rand(word_count, options['embedding_size']) - 1)).tolist()\\n\\n # load word vectors\\n for lines in open(vector_file).readlines()[1:]:\\n word = lines.split()[0]\\n #if word == '</s>' or word not in word2id.keys():\\n # continue\\n if word not in word2id.keys():\\n continue\\n ids = word2id[word]\\n #print ids, lines, len(word_emb)\\n word_emb[ids] = [float(w) for w in lines.split()[1:]]\\n\\n print len(word_emb), \\\"words have been loaded with\\\", len(word_emb[0]), \\\"dimensions\\\"\\n\\n # load word misc\\n word_misc['id2word'] = id2word\\n word_misc['word2id'] = word2id\\n word_misc['word_count'] = word_count\\n word_misc['word_emb'] = word_emb\\n cPickle.dump(word_misc, open(\\\"word_misc.pkl\\\", \\\"wb\\\"))\\n print \\\"Dump complete.\\\"\\n return word_misc\",\n \"def load_typos_moe(file_name):\\n \\n # log = logging.getLogger(\\\"robust_ner\\\")\\n\\n file_path = os.path.join(f\\\"resources/typos/\\\", f\\\"{file_name}\\\")\\n\\n typos = dict()\\n for line in open(file_path):\\n line = line.strip().split()\\n\\n if len(line) != 2:\\n #log.warning(f\\\"len(line) = {len(line)} != 2 (line: {line})\\\")\\n continue\\n\\n value = line[0]\\n key = line[1]\\n\\n #print(key, value)\\n \\n if key not in typos:\\n typos[key] = list()\\n\\n typos[key].append(value)\\n \\n return typos\",\n \"def get_glove_vocab(filename):\\n print(\\\"Building vocab...\\\")\\n vocab = set()\\n with open(filename, encoding='utf-8') as f:\\n for line in f:\\n # print(line.split(' ')[0])\\n word = line.strip().split(' ')[0]\\n vocab.add(word)\\n print(\\\"- done. {} tokens\\\".format(len(vocab)))\\n return vocab\",\n \"def remove_stopwords(self, value):\\n with open(\\\"grandpy/stop_words.json\\\", encoding=\\\"utf-8\\\") as json_file:\\n stopwords = json.load(json_file)\\n key_words = [word for word in value if word not in stopwords[\\\"stop_words\\\"]]\\n return key_words\",\n \"def loadVoc(vocabFName):\\n f = open(vocabFName, 'r')\\n lines = f.readlines()\\n f.close()\\n result = dict()\\n for idx, val in enumerate(lines):\\n word = val.strip('\\\\n')\\n result[word] = idx\\n return result\",\n \"def print_word_freq(file):\\n # with open(file, 'r') as text the r as the second arguement means that my intentions are to read the file\\n with open(file, 'r') as text:\\n # this reads the entire file and puts this into text string\\n text_string = text.read()\\n # returns the string respresentation of text string without removing special characters so you can see what you need to remove\\n # print(repr(text_string))\\n # this removes the specified characters from the text string\\n text_string = text_string.replace(\\\",\\\", \\\"\\\")\\n text_string = text_string.replace(\\\".\\\", \\\"\\\")\\n text_string = text_string.replace(\\\"—\\\", \\\" \\\")\\n text_string = text_string.replace(\\\"-\\\", \\\" \\\")\\n text_string = text_string.replace(\\\"?\\\", \\\"\\\")\\n text_string = text_string.replace(\\\":\\\", \\\"\\\")\\n text_string = text_string.replace(\\\"'\\\", \\\"\\\")\\n text_string = text_string.replace(\\\"\\\\\\\\n\\\", \\\"\\\")\\n text_string = text_string.replace(\\\"’\\\", \\\"\\\")\\n text_string = text_string.replace(\\\"]\\\", \\\"\\\")\\n text_string = text_string.replace(\\\"[\\\", \\\"\\\")\\n text_string = text_string.replace(\\\"\\\\\\\"\\\", \\\"\\\")\\n # takes the text string and makes all the characters lower case\\n text_string = text_string.lower()\\n # takes the text string and splits all the words into a list this splits from space to space\\n words_list = text_string.split()\\n # a dictionary is a key and a value\\n no_stop_words = {}\\n # for loop that will cycle through the words list\\n for word in words_list:\\n # checking to see if the word is stop words\\n if word not in STOP_WORDS:\\n # if the word is already in the dictionary no stop words increment the value by 1\\n if word in no_stop_words:\\n no_stop_words[word] += 1\\n # if the word is not in the dictionary no stop words add this to the dictionary and give it a value of 1\\n else:\\n no_stop_words[word] = 1\\n \\n sorted_dict = {}\\n sorted_keys = sorted(no_stop_words, key=no_stop_words.get, reverse=True)\\n \\n for w in sorted_keys:\\n sorted_dict[w] = no_stop_words[w]\\n \\n for key in sorted_dict:\\n print(f\\\"{key:>15} | {sorted_dict[key]:2} {'*' * sorted_dict[key]}\\\")\\n \\n # good practice to ensure that we are properly closing the file in use at the end of the function\\n text.close()\",\n \"def get_dict(fname):\\n out_set, tot_count = {}, 0\\n with open(fname, 'r') as fid:\\n word_arr = fid.read().split('\\\\n')\\n for ele in word_arr:\\n if len(ele) > 0:\\n out_set[(ele.split()[0])] = tot_count\\n tot_count += 1\\n return out_set\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7701295","0.7338579","0.6947404","0.69307244","0.6922794","0.6919339","0.68388474","0.67719364","0.6673551","0.66312903","0.6379227","0.6355576","0.63511074","0.63474447","0.6342942","0.633822","0.6330652","0.6327623","0.6324111","0.6315943","0.63043386","0.6296059","0.62826985","0.6263534","0.6250823","0.6250823","0.6237962","0.62349033","0.6222401","0.6220409","0.6183221","0.617273","0.6156887","0.6152538","0.61300147","0.61084497","0.61004454","0.6098865","0.6094496","0.6078715","0.6061231","0.6048259","0.6012546","0.60124063","0.60007656","0.5986777","0.59792376","0.5953106","0.59430134","0.5933307","0.5927915","0.5926435","0.5906","0.58987874","0.5886003","0.58819425","0.58739376","0.58701354","0.5868672","0.5859639","0.58577305","0.5836164","0.5833204","0.5832511","0.58296585","0.58296037","0.58274364","0.58193696","0.58144534","0.5796704","0.579286","0.579173","0.57770944","0.5759827","0.575713","0.5748684","0.57464755","0.5732038","0.5726195","0.5726011","0.57258326","0.5725617","0.5721249","0.5713285","0.5710737","0.57099503","0.5703947","0.5702394","0.56985873","0.56935614","0.56870246","0.5684626","0.5676977","0.5674354","0.5670929","0.5661069","0.56567025","0.5648459","0.56406754","0.563883"],"string":"[\n \"0.7701295\",\n \"0.7338579\",\n \"0.6947404\",\n \"0.69307244\",\n \"0.6922794\",\n \"0.6919339\",\n \"0.68388474\",\n \"0.67719364\",\n \"0.6673551\",\n \"0.66312903\",\n \"0.6379227\",\n \"0.6355576\",\n \"0.63511074\",\n \"0.63474447\",\n \"0.6342942\",\n \"0.633822\",\n \"0.6330652\",\n \"0.6327623\",\n \"0.6324111\",\n \"0.6315943\",\n \"0.63043386\",\n \"0.6296059\",\n \"0.62826985\",\n \"0.6263534\",\n \"0.6250823\",\n \"0.6250823\",\n \"0.6237962\",\n \"0.62349033\",\n \"0.6222401\",\n \"0.6220409\",\n \"0.6183221\",\n \"0.617273\",\n \"0.6156887\",\n \"0.6152538\",\n \"0.61300147\",\n \"0.61084497\",\n \"0.61004454\",\n \"0.6098865\",\n \"0.6094496\",\n \"0.6078715\",\n \"0.6061231\",\n \"0.6048259\",\n \"0.6012546\",\n \"0.60124063\",\n \"0.60007656\",\n \"0.5986777\",\n \"0.59792376\",\n \"0.5953106\",\n \"0.59430134\",\n \"0.5933307\",\n \"0.5927915\",\n \"0.5926435\",\n \"0.5906\",\n \"0.58987874\",\n \"0.5886003\",\n \"0.58819425\",\n \"0.58739376\",\n \"0.58701354\",\n \"0.5868672\",\n \"0.5859639\",\n \"0.58577305\",\n \"0.5836164\",\n \"0.5833204\",\n \"0.5832511\",\n \"0.58296585\",\n \"0.58296037\",\n \"0.58274364\",\n \"0.58193696\",\n \"0.58144534\",\n \"0.5796704\",\n \"0.579286\",\n \"0.579173\",\n \"0.57770944\",\n \"0.5759827\",\n \"0.575713\",\n \"0.5748684\",\n \"0.57464755\",\n \"0.5732038\",\n \"0.5726195\",\n \"0.5726011\",\n \"0.57258326\",\n \"0.5725617\",\n \"0.5721249\",\n \"0.5713285\",\n \"0.5710737\",\n \"0.57099503\",\n \"0.5703947\",\n \"0.5702394\",\n \"0.56985873\",\n \"0.56935614\",\n \"0.56870246\",\n \"0.5684626\",\n \"0.5676977\",\n \"0.5674354\",\n \"0.5670929\",\n \"0.5661069\",\n \"0.56567025\",\n \"0.5648459\",\n \"0.56406754\",\n \"0.563883\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6140933"},"document_rank":{"kind":"string","value":"34"}}},{"rowIdx":81791,"cells":{"query":{"kind":"string","value":"Save the GloVe dictionary memory Object into binary file"},"document":{"kind":"string","value":"def saveGloveDicIntoFile(gloveDic):\n \n np.save(GLOVE_DICT_FILE, np.asarray([gloveDic]))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def save_to_file(self, filename):\n outMap = {}\n for kanal in self._datastoreMap:\n # svaki pojedini Datastore se zna zapakirati u mapu (dictionary)\n outMap[kanal] = self._datastoreMap[kanal].store2dict()\n # serialize u binary string\n binstr = pickle.dumps(outMap)\n # zapis u file\n with open(filename, 'wb') as f:\n f.write(binstr)","def save_viz_object(viz_object: OrqVizObject, filename: str):\n\n with open(filename, \"wb\") as f:\n pickle.dump(viz_object, f)","def save_dictionary(filename, obj):\n filename = os.path.join(FILE_DIR, 'assets/obj/' + filename)\n with open(filename, 'wb') as output:\n pickle.dump(obj, output, pickle.HIGHEST_PROTOCOL)","def save_dict(obj, name, path):\n with open(os.path.join(path, name) + '.pkl', 'wb') as f:\n to_be_told = f.tell()\n for pair in obj.items():\n pickle.dump(pair, f, pickle.HIGHEST_PROTOCOL)","def save(object, filename, protocol = 0):\n file = gzip.GzipFile(filename, 'wb')\n file.write(pickle.dumps(object, protocol))\n file.close()","def savemodel(self, fname):\n if not fname.endswith('.gz'):\n fname += '.gz'\n D = {'clf':self.clf, 'vocab':self.vocab,\n 'idxlabelmap':self.labelmap}\n with gzip.open(fname, 'w') as fout:\n dump(D, fout)\n print 'Save model into file: {}'.format(fname)","def save(object, filename, protocol = 0):\n file = gzip.GzipFile(filename, 'wb')\n file.write(pickle.dumps(object, protocol))\n file.close()","def save_file(obj, file_path):\n with gzip.open(file_path, \"wb\") as fp:\n fp.write(json.dumps(obj).encode('utf-8'))","def save(self, path='dict.pic'):\n with open(path, 'wb') as f:\n pickle.dump(self.__dictionary, f)","def Save(self, filename: str):\n data_object = {\n \"input_layer_count\" : self.input_layer_size,\n \"hidden_layer_count\" : self.hidden_layer_size,\n \"output_layer_count\" : self.output_layer_size,\n\n \"hidden_layer_biases\" : self.hidden_layer_biases.tolist(),\n \"output_layer_biases\" : self.output_layer_biases.tolist(),\n\n \"input_to_hidden_weights\" : self.input_to_hidden_weights.tolist(),\n \"hidden_to_output_weights\" : self.hidden_to_output_weights.tolist()\n }\n\n with open(filename, \"w\") as f:\n json.dump(data_object, f)","def save(self):\n pickle.dump([self.word2vec, self.img2sentence, self.word_freq, self.num_words, self.word2idx, self.idx2word], open(self.save_file, 'wb'), protocol=4)","def save_to_disk(name, object):\n shortname = _dumpify(_compress_name(name) + '.pkl')\n print 'save_to_disk(%s)' % shortname\n pkl_file = open(shortname , 'wb')\n pickle.dump(object, pkl_file, -1) # Pickle the list using the highest protocol available.\n pkl_file.close()","def save_object(self, filename, data):\n with open(filename, 'wb') as outp: # Overwrites any existing file.\n pickle.dump(data, outp, pickle.HIGHEST_PROTOCOL)","def save(self, target):\n from six.moves.cPickle import dump\n data = self.serialize()\n with open(target, 'wb') as f:\n dump(data, f)","def save(self, target):\n from six.moves.cPickle import dump\n data = self.serialize()\n with open(target, 'wb') as f:\n dump(data, f)","def save(self, fname, compression='blosc'):\n\n bo = {\n 'data': self.data.values,\n 'locs': self.locs,\n 'sessions': self.sessions,\n 'sample_rate': self.sample_rate,\n 'kurtosis': self.kurtosis,\n 'kurtosis_threshold' : self.kurtosis_threshold,\n 'meta': self.meta,\n 'date_created': self.date_created,\n 'minimum_voxel_size': self.minimum_voxel_size,\n 'maximum_voxel_size': self.maximum_voxel_size,\n 'label' : self.label,\n 'filter' : self.filter,\n }\n\n if fname[-3:] != '.bo':\n fname += '.bo'\n\n dd.io.save(fname, bo, compression=compression)","def save(self, filename):\n with open(filename, \"wb\") as f:\n pkl.dump(self, f)","def save_object(obj, filename):\n\n result = pickle.dumps(obj)\n with gzip.GzipFile(filename, 'wb') as dest: dest.write(result)\n dest.close()","def dumpme(self) :\n fileName = \"./data/oP4_ModelBuilder.dump\"\n with open(fileName,\"wb\") as dumpedFile:\n oPickler = pickle.Pickler(dumpedFile)\n oPickler.dump(self)","def save(self):\n with open(self.__file_path, \"w\", encoding=\"UTF-8\") as file:\n parsed_dict = {\n key: value.to_dict()\n for key, value in self.__objects.items()\n }\n save_data(parsed_dict, file)","def serialize(self): \n with open(self.path+self.name, \"wb\") as pfile:\n pickle.dump(self.pyObj, pfile)","def save_object(path,object):\r\n with open(path,\"wb\") as f:\r\n pickle.dump(object,f,pickle.HIGHEST_PROTOCOL)","def save(self):\n\n with open(FileStorage.__file_path, \"w\") as file:\n dictionary = {}\n for a, b in FileStorage.__objects.items():\n dictionary[a] = b.to_dict()\n ink = json.dumps(dictionary)\n file.write(ink)","def save_obj(obj, path ):\n with open(path, 'wb') as f:\n pickle.dump(obj, f)","def save_dictionary(myDict, filepath):\r\n # context manager write binary\r\n with open(filepath, 'wb') as file:\r\n # pickle save\r\n pickle.dump(myDict, file)","def save(self) -> None:\n with open(dict_path, 'w', encoding='utf-8') as dictionary_file:\n json.dump(self.data, dictionary_file, indent=2, separators=(',', ':'), ensure_ascii=False)","def save(self, path):\n with open(path, 'wb') as f:\n pkl.dump(self, f)","def save(self, file_name):\n logger.warning(\"save embeddings and name mappings to `%s`\" % file_name)\n\n objects = EasyDict()\n for name in dir(self.graph):\n object = getattr(self.graph, name)\n if isinstance(object, list) and len(object) > 0 and isinstance(object[0], str): # id2name\n objects[name] = object\n for name in dir(self.solver):\n object = getattr(self.solver, name)\n if isinstance(object, np.ndarray): # embedding\n objects[name] = object\n\n with open(file_name, \"wb\") as fout:\n pickle.dump(objects, fout, protocol=pickle.HIGHEST_PROTOCOL)","def save(self):\n a_copy = FileStorage.__objects\n obj_dict = {obj: a_copy[obj].to_dict() for obj in a_copy.keys()}\n with open(FileStorage.__file_path, \"w\") as f:\n json.dump(obj_dict, f)","def save_dict(emb, path_to_vec, dim=100):\n word_vec = {}\n for w in emb.keys():\n word_vec[w] = emb[w]\n with open(path_to_vec + f'embedding_{str(dim)}d.txt', 'w') as file:\n for w, v in word_vec.items():\n file.write(w + ' ')\n for el in v:\n file.write(\"{:.20f}\".format(float(el)) + ' ')\n file.write('\\n')","def save_trained_model(self, filename):\n d = self.pack_npz()\n with open(filename, 'wb') as f:\n np.savez(f, base_str=super(SpatialGP, self).__repr_base_params__(), **d)","def save(self, filename):\n with gzip.open(filename, \"w\") as f:\n f.write(pickle.dumps(self))","def save(net,dic,path):\n dict_m = net.state_dict()\n dict_m[\"word_dic\"] = dic \n torch.save(dict_m,path)","def save(self, target, withdP=False):\n from six.moves.cPickle import dump\n data = self.serialize(withdP=withdP)\n with open(target, 'wb') as f:\n dump(data, f)","def save(self, target, withdP=False):\n from six.moves.cPickle import dump\n data = self.serialize(withdP=withdP)\n with open(target, 'wb') as f:\n dump(data, f)","def save(net,dic,path):\n dict_m = net.state_dict()\n dict_m[\"word_dic\"] = dic\n torch.save(dict_m,path)","def save_model(self, step):\n\n # file_name = params['name']\n # pickle.dump(self, gzip.open(file_name, 'wb'))","async def dump(self, data: dict, file: IO):","def write_object_file_to_file(self, file_name):\n with open(file_name, 'wb+') as file:\n file.write(self.object_file.to_binary_array())","def createGloveDic():\n saveGloveDicIntoFile(_extractGloveVects())","def to_file(self, file_io):\n pickle.dump(self.__object, file_io)","def save_object(obj, filename):\n with open(filename, 'wb') as output:\n pickle.dump(obj, output, protocol=2)","def save_object(obj, filename):\r\n with open(filename, 'wb') as output:\r\n pickle.dump(obj, output)","def save(self, output, data):","def save(self):\n with open(FileStorage.__file_path, 'w') as saves:\n copy_dict = {key: self.__objects[key].to_dict()\n for key in self.__objects}\n json.dump(copy_dict, saves)","def dump(self, path):\n torch.save(self,path)","def save_obj(obj, name):\n with open('../../data/' + name + '.pkl', 'wb') as f:\n pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)","def save_obj(obj, name):\n with open('../../data/' + name + '.pkl', 'wb') as f:\n pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)","def save(datastream):","def _save_obj(obj, name):\n with open('/bigdisk/pickles/' + name, 'w') as f:\n pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)","def save_to(self, f: BinaryIO):\n raise NotImplementedError","def save(obj, filename):\n import pickle\n with open(filename, 'w') as f:\n pickle.dump(obj, f, protocol=pickle.HIGHEST_PROTOCOL)","def save(self, filename):\n data = {\"sizes\": self.sizes,\n \"weights\": [w.tolist() for w in self.weights],\n \"biases\": [b.tolist() for b in self.biases]}\n f = open(filename, \"w\")\n json.dump(data, f)\n f.close()","def pickle_save(file_path, obj):\n with open(file_path, 'wb') as f:\n pickle.dump(obj, f)","def save_to_fileobj(self, fileobj):\n writetags(fileobj, self.__dxftags__(), self.ENCODING)","def _save_binary(file_name, data):\n with open(file_name, \"wb\") as f:\n cp.dump(data, f)","def save(self):\n pickle.dump(self, open(self.path, \"wb\"))","def save(self):\n\t\tif os.path.exists(\"%s.obj\" % (self.name)):\n\t\t\tos.system(\"rm -f %s.obj\" % (self.name))\n\t\telse: pass\n\t\tfile = open(\"%s.obj\" % (self.name), \"wb\")\n\t\tif callable(self.obj):\n\t\t\tif \"dill\" in sys.modules:\n\t\t\t\ttry:\n\t\t\t\t\tpickle.dump(self.obj, file)\n\t\t\t\texcept:\n\t\t\t\t\twarnings.warn(\"\"\"\\\nCould not pickle function. The following attribute will not be saved with \\\nthis output: %s\"\"\" % (self.name), UserWarning)\n\t\t\t\t\tpickle.dump(None, file)\n\t\t\telse:\n\t\t\t\twarnings.warn(\"\"\"\\\nEncoding functions along with VICE outputs requires the package dill \\\n(installable via pip). The following attribute will not be saved with this \\\noutput: %s\"\"\" % (self.name), UserWarning)\n\t\t\t\ttry:\n\t\t\t\t\tpickle.dump(self._default, file)\n\t\t\t\texcept:\n\t\t\t\t\tpickle.dump(None, file)\n\t\telse:\n\t\t\ttry:\n\t\t\t\tpickle.dump(self.obj, file)\n\t\t\texcept:\n\t\t\t\twarnings.warn(\"\"\"Could not save object %s with this VICE \\\noutput.\"\"\" % (self.name), UserWarning)\n\t\t\t\tpickle.dump(None, file)\n\t\tfile.close()","def write_to_disk(self):\n text_file = open(self.file_path, \"w\")\n text_file.write(str(self))\n text_file.close()\n # dump to pickle\n pickle.dump(self.blockchain, open(self.pickle_path, \"wb\"))","def save(self):\n if self._filename:\n with open(self._filename, 'w') as f:\n json.dump(self._dict, f, sort_keys=True, indent=4,\n separators=(',', ': '))\n else:\n raise PoseError(\"Please load map first\")","def save(self, fname):\n with open(fname, \"wb\") as f:\n cloudpickle.dump(self, f)\n # pickle.dump(self, open(fname, 'wb'))","def save_obj(obj, path: str):\n with open(path, 'wb') as h:\n pickle.dump(obj, h)","def to_file(self, file): \n try:\n import dill as pickle\n except ImportError:\n logger.error(\"Cannot write to file, dill not installed \\n\"\n \"pip install dill\")\n return\n try:\n logger.info('Writing GeologicalModel to: {}'.format(file))\n pickle.dump(self,open(file,'wb'))\n except pickle.PicklingError:\n logger.error('Error saving file')","def save_obj(obj, name):\n \n with open(name + '.pkl', 'wb') as objec:\n pickle.dump(obj, objec)","def saveobject(obj, filename):\n # import cPickle as pickle\n with open(filename, 'wb') as output:\n pickle.dump(obj, output, pickle.HIGHEST_PROTOCOL)","def dump_pkl(obj, path):\r\n f = open(path, 'wb')\r\n try:\r\n cPickle.dump(obj, f, protocol=cPickle.HIGHEST_PROTOCOL)\r\n finally:\r\n f.close()","def save_obj(obj, saved_name ):\n with open( saved_name + '.pkl', 'wb') as f:\n pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)","def save_object(obj, filename):\n with open(filename, 'wb') as output_file: # Overwrites any existing file.\n pickle.dump(obj, output_file, pickle.HIGHEST_PROTOCOL)","def save(net, txt_dict, path):\n dict_m = net.state_dict()\n _ = txt_dict\n torch.save(dict_m,path)","def save(self):\n data = (\n self.Joints,\n self.Links,\n self.joint_syms,\n self.global_syms,\n self.name,\n self.sym_prefix,\n )\n cloudpickle.dump(data, open(self.save_filename, \"wb\"))","def dump(self, outfile):\n with open(outfile, 'wb') as picklefile:\n pickle.dump(\n {str(key): value for key, value in self.data.items()},\n picklefile)","def dump_pklgz(filename: str, obj, **kwargs):\n with open_gz(filename, 'wb') as f:\n return pickle.dump(obj, f)","def save_data_to_disk(self):\n Omega_M = self.theta_fid[0]\n for key in self.data.keys():\n np.save(f'./preloaded_data/{Omega_M}_{self.delta_theta[0]}_{key}.npy', self.data[key])","def save_dict_pickle(PATH, data, filename):\n with open(PATH + '/' + filename + \".pkl\",\"wb\") as f:\n pickle.dump(data,f)\n print(filename, \"created\")","def save_memory(self, filename):\n \n\n with open(filename + '/obses.npy', 'wb') as f:\n np.save(f, self.obses)\n \n with open(filename + '/actions.npy', 'wb') as f:\n np.save(f, self.actions)\n\n with open(filename + '/next_obses.npy', 'wb') as f:\n np.save(f, self.next_obses)\n \n with open(filename + '/rewards.npy', 'wb') as f:\n np.save(f, self.rewards)\n \n with open(filename + '/not_dones.npy', 'wb') as f:\n np.save(f, self.not_dones)\n \n with open(filename + '/not_dones_no_max.npy', 'wb') as f:\n np.save(f, self.not_dones_no_max)\n\n with open(filename + '/index.txt', 'w') as f:\n f.write(\"{}\".format(self.idx))\n\n print(\"save buffer to {}\".format(filename))","def save_var(filename, data, protocol = -1, allow_dill=False):\n if filename.endswith('.gz') :\n open_method = gzip.open\n else:\n open_method = open\n\n output = open_method(filename, 'wb')\n try:\n # Pickle dictionary using given protocol\n std_pickle.dump(data, output, protocol)\n finally:\n output.close()\n\n return","def save(self, path):\n np.savez_compressed(path, **self.model_dict)","def save_(self):\n if not self._edited:\n return\n data = {'history': self.dump()}\n with open(os.path.join(os.path.dirname(self.arch_handler.dicomdir_path), self.SAVE_NAME), \"w\") as outfile:\n json.dump(data, outfile)\n self._edited = False","def save_obj(obj, name):\r\n with open('../pickle/' + name + '.pkl', 'wb') as fout:\r\n pickle.dump(obj, fout, pickle.HIGHEST_PROTOCOL)\r\n # end with\r","def save_object(obj, fpath):\r\n with open(fpath, 'wb') as o:\r\n pickle.dump(obj, o)","def save_pickle(obj, filename):\n with open(filename, 'wb') as file:\n pickle.dump(obj, file)","def save(self):\n d1 = {}\n with open(self.__file_path, mode=\"w\") as f:\n for k, v in self.__objects.items():\n d1[k] = v.to_dict()\n json.dump(d1, f)","def save(self, filename):\n model_dict = {'model_state_dict': self.state_dict(),\n 'init_args': {\"vocab_size\": self.vocab_size,\n \"embeddings_size\": self.embeddings_size,\n \"hidden_size\": self.hidden_size,\n \"mlp_hidden_size\": self.mlp_hidden_size,\n \"dropout\": self.dropout}}\n torch.save(model_dict, filename)","def save_data(data: DataObj):\n\n filename = os.path.join(DATA_DIR, data.uuid)\n contents = {k: _s(v) for k, v in data._asdict().items()}\n contents = json.dumps(contents, ensure_ascii=False, sort_keys=True, indent=2)\n\n logger.info('writing %s', filename)\n with open(filename, 'wb') as fp:\n fp.write(_b(contents))\n\n del contents\n del data\n gc.collect(1)","def save_as(self, filename: str) -> None:\n save_data = lzma.compress(pickle.dumps(self))\n with open(filename, \"wb\") as f:\n f.write(save_data)","def save_vectorizer(self, vectorizer_filepath):\n with open(vectorizer_filepath, \"w\") as fp:\n json.dump(self._vectorizer.to_serializable(), fp)","def picklesave(obj, path):\n with open(path, 'wb') as file:\n pickle.dump(obj, file)","def save_class_representation(self):\n class_dict = {}\n for key, value in self.class_dict.items():\n class_dict['-'.join(key)] = list(value)\n with open('data/class_vectors.txt', 'w') as file:\n json.dump(class_dict, file)\n return class_dict","def save_model(self):\n\n self.check_model()\n\n with open(self.filename, 'wb') as file:\n pickle.dump({'model': self.model, 'vec': self.vectorizer, 'vec_data': self.vectorized_data,\n 'df': self.df_topic_keywords}, file)","def save_histogram_data(self, histogram_data, obj_name):\n dirname = os.path.dirname(os.path.abspath(__file__))\n histogram_data_dir = os.path.join(dirname, '../data/histogram_data')\n if not os.path.exists(histogram_data_dir):\n os.mkdir(histogram_data_dir)\n filename = os.path.join(histogram_data_dir, obj_name + '_' + self.color_name + '.pkl.gz')\n with gzip.open(filename, 'wb') as f:\n pickle.dump(histogram_data, f)","def pickle_object(Object, file):\n filehandler = open(file, 'wb')\n pickle.dump(Object, filehandler)\n filehandler.close()","def save_sample_dict(self):\n with open(self._sample_dict_path, 'w+') as fp:\n pickle.dump(self.sample_dict, fp)","def pickle_to_file(obj, path):\n pickle.dump(obj, open(path, 'wb'))","def save_object(obj, file_name):\n file_name = osp.abspath(file_name)\n with open(file_name, 'wb') as f:\n pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)","def pickle_write(file_path, obj):\n\n with open(file_path, 'wb') as file:\n pickle.dump(obj, file)","def dump_pth(filename, obj, **kwargs):\n import torch\n return torch.save(obj, filename)","def save_object(o, fn):\n return dump_object(o, fn)","def save(self):\n if not self.fileKey:\n log.error(\"attempted to save a closed wallet\")\n return\n encrypted = self.fileKey.encrypt(tinyjson.dump(self).encode()).hex()\n w = tinyjson.dump({\n \"keyparams\": self.fileKey.params(),\n \"wallet\": encrypted,\n })\n helpers.saveFile(self.path, w)","def save(cls):\n playerdata = getAttributes(cls)\n Data.object_dump(playerdata, \"savedata.dat\")\n del playerdata","def save(self, filename):\n data = {\"sizes\": self.sizes,\n \"weights\": [w.tolist() for w in self.weights],\n \"biases\": [b.tolist() for b in self.biases],\n \"cost\": str(self.cost.__name__)}\n f = open(filename, \"w\")\n json.dump(data, f)\n f.close()"],"string":"[\n \"def save_to_file(self, filename):\\n outMap = {}\\n for kanal in self._datastoreMap:\\n # svaki pojedini Datastore se zna zapakirati u mapu (dictionary)\\n outMap[kanal] = self._datastoreMap[kanal].store2dict()\\n # serialize u binary string\\n binstr = pickle.dumps(outMap)\\n # zapis u file\\n with open(filename, 'wb') as f:\\n f.write(binstr)\",\n \"def save_viz_object(viz_object: OrqVizObject, filename: str):\\n\\n with open(filename, \\\"wb\\\") as f:\\n pickle.dump(viz_object, f)\",\n \"def save_dictionary(filename, obj):\\n filename = os.path.join(FILE_DIR, 'assets/obj/' + filename)\\n with open(filename, 'wb') as output:\\n pickle.dump(obj, output, pickle.HIGHEST_PROTOCOL)\",\n \"def save_dict(obj, name, path):\\n with open(os.path.join(path, name) + '.pkl', 'wb') as f:\\n to_be_told = f.tell()\\n for pair in obj.items():\\n pickle.dump(pair, f, pickle.HIGHEST_PROTOCOL)\",\n \"def save(object, filename, protocol = 0):\\n file = gzip.GzipFile(filename, 'wb')\\n file.write(pickle.dumps(object, protocol))\\n file.close()\",\n \"def savemodel(self, fname):\\n if not fname.endswith('.gz'):\\n fname += '.gz'\\n D = {'clf':self.clf, 'vocab':self.vocab,\\n 'idxlabelmap':self.labelmap}\\n with gzip.open(fname, 'w') as fout:\\n dump(D, fout)\\n print 'Save model into file: {}'.format(fname)\",\n \"def save(object, filename, protocol = 0):\\n file = gzip.GzipFile(filename, 'wb')\\n file.write(pickle.dumps(object, protocol))\\n file.close()\",\n \"def save_file(obj, file_path):\\n with gzip.open(file_path, \\\"wb\\\") as fp:\\n fp.write(json.dumps(obj).encode('utf-8'))\",\n \"def save(self, path='dict.pic'):\\n with open(path, 'wb') as f:\\n pickle.dump(self.__dictionary, f)\",\n \"def Save(self, filename: str):\\n data_object = {\\n \\\"input_layer_count\\\" : self.input_layer_size,\\n \\\"hidden_layer_count\\\" : self.hidden_layer_size,\\n \\\"output_layer_count\\\" : self.output_layer_size,\\n\\n \\\"hidden_layer_biases\\\" : self.hidden_layer_biases.tolist(),\\n \\\"output_layer_biases\\\" : self.output_layer_biases.tolist(),\\n\\n \\\"input_to_hidden_weights\\\" : self.input_to_hidden_weights.tolist(),\\n \\\"hidden_to_output_weights\\\" : self.hidden_to_output_weights.tolist()\\n }\\n\\n with open(filename, \\\"w\\\") as f:\\n json.dump(data_object, f)\",\n \"def save(self):\\n pickle.dump([self.word2vec, self.img2sentence, self.word_freq, self.num_words, self.word2idx, self.idx2word], open(self.save_file, 'wb'), protocol=4)\",\n \"def save_to_disk(name, object):\\n shortname = _dumpify(_compress_name(name) + '.pkl')\\n print 'save_to_disk(%s)' % shortname\\n pkl_file = open(shortname , 'wb')\\n pickle.dump(object, pkl_file, -1) # Pickle the list using the highest protocol available.\\n pkl_file.close()\",\n \"def save_object(self, filename, data):\\n with open(filename, 'wb') as outp: # Overwrites any existing file.\\n pickle.dump(data, outp, pickle.HIGHEST_PROTOCOL)\",\n \"def save(self, target):\\n from six.moves.cPickle import dump\\n data = self.serialize()\\n with open(target, 'wb') as f:\\n dump(data, f)\",\n \"def save(self, target):\\n from six.moves.cPickle import dump\\n data = self.serialize()\\n with open(target, 'wb') as f:\\n dump(data, f)\",\n \"def save(self, fname, compression='blosc'):\\n\\n bo = {\\n 'data': self.data.values,\\n 'locs': self.locs,\\n 'sessions': self.sessions,\\n 'sample_rate': self.sample_rate,\\n 'kurtosis': self.kurtosis,\\n 'kurtosis_threshold' : self.kurtosis_threshold,\\n 'meta': self.meta,\\n 'date_created': self.date_created,\\n 'minimum_voxel_size': self.minimum_voxel_size,\\n 'maximum_voxel_size': self.maximum_voxel_size,\\n 'label' : self.label,\\n 'filter' : self.filter,\\n }\\n\\n if fname[-3:] != '.bo':\\n fname += '.bo'\\n\\n dd.io.save(fname, bo, compression=compression)\",\n \"def save(self, filename):\\n with open(filename, \\\"wb\\\") as f:\\n pkl.dump(self, f)\",\n \"def save_object(obj, filename):\\n\\n result = pickle.dumps(obj)\\n with gzip.GzipFile(filename, 'wb') as dest: dest.write(result)\\n dest.close()\",\n \"def dumpme(self) :\\n fileName = \\\"./data/oP4_ModelBuilder.dump\\\"\\n with open(fileName,\\\"wb\\\") as dumpedFile:\\n oPickler = pickle.Pickler(dumpedFile)\\n oPickler.dump(self)\",\n \"def save(self):\\n with open(self.__file_path, \\\"w\\\", encoding=\\\"UTF-8\\\") as file:\\n parsed_dict = {\\n key: value.to_dict()\\n for key, value in self.__objects.items()\\n }\\n save_data(parsed_dict, file)\",\n \"def serialize(self): \\n with open(self.path+self.name, \\\"wb\\\") as pfile:\\n pickle.dump(self.pyObj, pfile)\",\n \"def save_object(path,object):\\r\\n with open(path,\\\"wb\\\") as f:\\r\\n pickle.dump(object,f,pickle.HIGHEST_PROTOCOL)\",\n \"def save(self):\\n\\n with open(FileStorage.__file_path, \\\"w\\\") as file:\\n dictionary = {}\\n for a, b in FileStorage.__objects.items():\\n dictionary[a] = b.to_dict()\\n ink = json.dumps(dictionary)\\n file.write(ink)\",\n \"def save_obj(obj, path ):\\n with open(path, 'wb') as f:\\n pickle.dump(obj, f)\",\n \"def save_dictionary(myDict, filepath):\\r\\n # context manager write binary\\r\\n with open(filepath, 'wb') as file:\\r\\n # pickle save\\r\\n pickle.dump(myDict, file)\",\n \"def save(self) -> None:\\n with open(dict_path, 'w', encoding='utf-8') as dictionary_file:\\n json.dump(self.data, dictionary_file, indent=2, separators=(',', ':'), ensure_ascii=False)\",\n \"def save(self, path):\\n with open(path, 'wb') as f:\\n pkl.dump(self, f)\",\n \"def save(self, file_name):\\n logger.warning(\\\"save embeddings and name mappings to `%s`\\\" % file_name)\\n\\n objects = EasyDict()\\n for name in dir(self.graph):\\n object = getattr(self.graph, name)\\n if isinstance(object, list) and len(object) > 0 and isinstance(object[0], str): # id2name\\n objects[name] = object\\n for name in dir(self.solver):\\n object = getattr(self.solver, name)\\n if isinstance(object, np.ndarray): # embedding\\n objects[name] = object\\n\\n with open(file_name, \\\"wb\\\") as fout:\\n pickle.dump(objects, fout, protocol=pickle.HIGHEST_PROTOCOL)\",\n \"def save(self):\\n a_copy = FileStorage.__objects\\n obj_dict = {obj: a_copy[obj].to_dict() for obj in a_copy.keys()}\\n with open(FileStorage.__file_path, \\\"w\\\") as f:\\n json.dump(obj_dict, f)\",\n \"def save_dict(emb, path_to_vec, dim=100):\\n word_vec = {}\\n for w in emb.keys():\\n word_vec[w] = emb[w]\\n with open(path_to_vec + f'embedding_{str(dim)}d.txt', 'w') as file:\\n for w, v in word_vec.items():\\n file.write(w + ' ')\\n for el in v:\\n file.write(\\\"{:.20f}\\\".format(float(el)) + ' ')\\n file.write('\\\\n')\",\n \"def save_trained_model(self, filename):\\n d = self.pack_npz()\\n with open(filename, 'wb') as f:\\n np.savez(f, base_str=super(SpatialGP, self).__repr_base_params__(), **d)\",\n \"def save(self, filename):\\n with gzip.open(filename, \\\"w\\\") as f:\\n f.write(pickle.dumps(self))\",\n \"def save(net,dic,path):\\n dict_m = net.state_dict()\\n dict_m[\\\"word_dic\\\"] = dic \\n torch.save(dict_m,path)\",\n \"def save(self, target, withdP=False):\\n from six.moves.cPickle import dump\\n data = self.serialize(withdP=withdP)\\n with open(target, 'wb') as f:\\n dump(data, f)\",\n \"def save(self, target, withdP=False):\\n from six.moves.cPickle import dump\\n data = self.serialize(withdP=withdP)\\n with open(target, 'wb') as f:\\n dump(data, f)\",\n \"def save(net,dic,path):\\n dict_m = net.state_dict()\\n dict_m[\\\"word_dic\\\"] = dic\\n torch.save(dict_m,path)\",\n \"def save_model(self, step):\\n\\n # file_name = params['name']\\n # pickle.dump(self, gzip.open(file_name, 'wb'))\",\n \"async def dump(self, data: dict, file: IO):\",\n \"def write_object_file_to_file(self, file_name):\\n with open(file_name, 'wb+') as file:\\n file.write(self.object_file.to_binary_array())\",\n \"def createGloveDic():\\n saveGloveDicIntoFile(_extractGloveVects())\",\n \"def to_file(self, file_io):\\n pickle.dump(self.__object, file_io)\",\n \"def save_object(obj, filename):\\n with open(filename, 'wb') as output:\\n pickle.dump(obj, output, protocol=2)\",\n \"def save_object(obj, filename):\\r\\n with open(filename, 'wb') as output:\\r\\n pickle.dump(obj, output)\",\n \"def save(self, output, data):\",\n \"def save(self):\\n with open(FileStorage.__file_path, 'w') as saves:\\n copy_dict = {key: self.__objects[key].to_dict()\\n for key in self.__objects}\\n json.dump(copy_dict, saves)\",\n \"def dump(self, path):\\n torch.save(self,path)\",\n \"def save_obj(obj, name):\\n with open('../../data/' + name + '.pkl', 'wb') as f:\\n pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)\",\n \"def save_obj(obj, name):\\n with open('../../data/' + name + '.pkl', 'wb') as f:\\n pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)\",\n \"def save(datastream):\",\n \"def _save_obj(obj, name):\\n with open('/bigdisk/pickles/' + name, 'w') as f:\\n pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)\",\n \"def save_to(self, f: BinaryIO):\\n raise NotImplementedError\",\n \"def save(obj, filename):\\n import pickle\\n with open(filename, 'w') as f:\\n pickle.dump(obj, f, protocol=pickle.HIGHEST_PROTOCOL)\",\n \"def save(self, filename):\\n data = {\\\"sizes\\\": self.sizes,\\n \\\"weights\\\": [w.tolist() for w in self.weights],\\n \\\"biases\\\": [b.tolist() for b in self.biases]}\\n f = open(filename, \\\"w\\\")\\n json.dump(data, f)\\n f.close()\",\n \"def pickle_save(file_path, obj):\\n with open(file_path, 'wb') as f:\\n pickle.dump(obj, f)\",\n \"def save_to_fileobj(self, fileobj):\\n writetags(fileobj, self.__dxftags__(), self.ENCODING)\",\n \"def _save_binary(file_name, data):\\n with open(file_name, \\\"wb\\\") as f:\\n cp.dump(data, f)\",\n \"def save(self):\\n pickle.dump(self, open(self.path, \\\"wb\\\"))\",\n \"def save(self):\\n\\t\\tif os.path.exists(\\\"%s.obj\\\" % (self.name)):\\n\\t\\t\\tos.system(\\\"rm -f %s.obj\\\" % (self.name))\\n\\t\\telse: pass\\n\\t\\tfile = open(\\\"%s.obj\\\" % (self.name), \\\"wb\\\")\\n\\t\\tif callable(self.obj):\\n\\t\\t\\tif \\\"dill\\\" in sys.modules:\\n\\t\\t\\t\\ttry:\\n\\t\\t\\t\\t\\tpickle.dump(self.obj, file)\\n\\t\\t\\t\\texcept:\\n\\t\\t\\t\\t\\twarnings.warn(\\\"\\\"\\\"\\\\\\nCould not pickle function. The following attribute will not be saved with \\\\\\nthis output: %s\\\"\\\"\\\" % (self.name), UserWarning)\\n\\t\\t\\t\\t\\tpickle.dump(None, file)\\n\\t\\t\\telse:\\n\\t\\t\\t\\twarnings.warn(\\\"\\\"\\\"\\\\\\nEncoding functions along with VICE outputs requires the package dill \\\\\\n(installable via pip). The following attribute will not be saved with this \\\\\\noutput: %s\\\"\\\"\\\" % (self.name), UserWarning)\\n\\t\\t\\t\\ttry:\\n\\t\\t\\t\\t\\tpickle.dump(self._default, file)\\n\\t\\t\\t\\texcept:\\n\\t\\t\\t\\t\\tpickle.dump(None, file)\\n\\t\\telse:\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tpickle.dump(self.obj, file)\\n\\t\\t\\texcept:\\n\\t\\t\\t\\twarnings.warn(\\\"\\\"\\\"Could not save object %s with this VICE \\\\\\noutput.\\\"\\\"\\\" % (self.name), UserWarning)\\n\\t\\t\\t\\tpickle.dump(None, file)\\n\\t\\tfile.close()\",\n \"def write_to_disk(self):\\n text_file = open(self.file_path, \\\"w\\\")\\n text_file.write(str(self))\\n text_file.close()\\n # dump to pickle\\n pickle.dump(self.blockchain, open(self.pickle_path, \\\"wb\\\"))\",\n \"def save(self):\\n if self._filename:\\n with open(self._filename, 'w') as f:\\n json.dump(self._dict, f, sort_keys=True, indent=4,\\n separators=(',', ': '))\\n else:\\n raise PoseError(\\\"Please load map first\\\")\",\n \"def save(self, fname):\\n with open(fname, \\\"wb\\\") as f:\\n cloudpickle.dump(self, f)\\n # pickle.dump(self, open(fname, 'wb'))\",\n \"def save_obj(obj, path: str):\\n with open(path, 'wb') as h:\\n pickle.dump(obj, h)\",\n \"def to_file(self, file): \\n try:\\n import dill as pickle\\n except ImportError:\\n logger.error(\\\"Cannot write to file, dill not installed \\\\n\\\"\\n \\\"pip install dill\\\")\\n return\\n try:\\n logger.info('Writing GeologicalModel to: {}'.format(file))\\n pickle.dump(self,open(file,'wb'))\\n except pickle.PicklingError:\\n logger.error('Error saving file')\",\n \"def save_obj(obj, name):\\n \\n with open(name + '.pkl', 'wb') as objec:\\n pickle.dump(obj, objec)\",\n \"def saveobject(obj, filename):\\n # import cPickle as pickle\\n with open(filename, 'wb') as output:\\n pickle.dump(obj, output, pickle.HIGHEST_PROTOCOL)\",\n \"def dump_pkl(obj, path):\\r\\n f = open(path, 'wb')\\r\\n try:\\r\\n cPickle.dump(obj, f, protocol=cPickle.HIGHEST_PROTOCOL)\\r\\n finally:\\r\\n f.close()\",\n \"def save_obj(obj, saved_name ):\\n with open( saved_name + '.pkl', 'wb') as f:\\n pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)\",\n \"def save_object(obj, filename):\\n with open(filename, 'wb') as output_file: # Overwrites any existing file.\\n pickle.dump(obj, output_file, pickle.HIGHEST_PROTOCOL)\",\n \"def save(net, txt_dict, path):\\n dict_m = net.state_dict()\\n _ = txt_dict\\n torch.save(dict_m,path)\",\n \"def save(self):\\n data = (\\n self.Joints,\\n self.Links,\\n self.joint_syms,\\n self.global_syms,\\n self.name,\\n self.sym_prefix,\\n )\\n cloudpickle.dump(data, open(self.save_filename, \\\"wb\\\"))\",\n \"def dump(self, outfile):\\n with open(outfile, 'wb') as picklefile:\\n pickle.dump(\\n {str(key): value for key, value in self.data.items()},\\n picklefile)\",\n \"def dump_pklgz(filename: str, obj, **kwargs):\\n with open_gz(filename, 'wb') as f:\\n return pickle.dump(obj, f)\",\n \"def save_data_to_disk(self):\\n Omega_M = self.theta_fid[0]\\n for key in self.data.keys():\\n np.save(f'./preloaded_data/{Omega_M}_{self.delta_theta[0]}_{key}.npy', self.data[key])\",\n \"def save_dict_pickle(PATH, data, filename):\\n with open(PATH + '/' + filename + \\\".pkl\\\",\\\"wb\\\") as f:\\n pickle.dump(data,f)\\n print(filename, \\\"created\\\")\",\n \"def save_memory(self, filename):\\n \\n\\n with open(filename + '/obses.npy', 'wb') as f:\\n np.save(f, self.obses)\\n \\n with open(filename + '/actions.npy', 'wb') as f:\\n np.save(f, self.actions)\\n\\n with open(filename + '/next_obses.npy', 'wb') as f:\\n np.save(f, self.next_obses)\\n \\n with open(filename + '/rewards.npy', 'wb') as f:\\n np.save(f, self.rewards)\\n \\n with open(filename + '/not_dones.npy', 'wb') as f:\\n np.save(f, self.not_dones)\\n \\n with open(filename + '/not_dones_no_max.npy', 'wb') as f:\\n np.save(f, self.not_dones_no_max)\\n\\n with open(filename + '/index.txt', 'w') as f:\\n f.write(\\\"{}\\\".format(self.idx))\\n\\n print(\\\"save buffer to {}\\\".format(filename))\",\n \"def save_var(filename, data, protocol = -1, allow_dill=False):\\n if filename.endswith('.gz') :\\n open_method = gzip.open\\n else:\\n open_method = open\\n\\n output = open_method(filename, 'wb')\\n try:\\n # Pickle dictionary using given protocol\\n std_pickle.dump(data, output, protocol)\\n finally:\\n output.close()\\n\\n return\",\n \"def save(self, path):\\n np.savez_compressed(path, **self.model_dict)\",\n \"def save_(self):\\n if not self._edited:\\n return\\n data = {'history': self.dump()}\\n with open(os.path.join(os.path.dirname(self.arch_handler.dicomdir_path), self.SAVE_NAME), \\\"w\\\") as outfile:\\n json.dump(data, outfile)\\n self._edited = False\",\n \"def save_obj(obj, name):\\r\\n with open('../pickle/' + name + '.pkl', 'wb') as fout:\\r\\n pickle.dump(obj, fout, pickle.HIGHEST_PROTOCOL)\\r\\n # end with\\r\",\n \"def save_object(obj, fpath):\\r\\n with open(fpath, 'wb') as o:\\r\\n pickle.dump(obj, o)\",\n \"def save_pickle(obj, filename):\\n with open(filename, 'wb') as file:\\n pickle.dump(obj, file)\",\n \"def save(self):\\n d1 = {}\\n with open(self.__file_path, mode=\\\"w\\\") as f:\\n for k, v in self.__objects.items():\\n d1[k] = v.to_dict()\\n json.dump(d1, f)\",\n \"def save(self, filename):\\n model_dict = {'model_state_dict': self.state_dict(),\\n 'init_args': {\\\"vocab_size\\\": self.vocab_size,\\n \\\"embeddings_size\\\": self.embeddings_size,\\n \\\"hidden_size\\\": self.hidden_size,\\n \\\"mlp_hidden_size\\\": self.mlp_hidden_size,\\n \\\"dropout\\\": self.dropout}}\\n torch.save(model_dict, filename)\",\n \"def save_data(data: DataObj):\\n\\n filename = os.path.join(DATA_DIR, data.uuid)\\n contents = {k: _s(v) for k, v in data._asdict().items()}\\n contents = json.dumps(contents, ensure_ascii=False, sort_keys=True, indent=2)\\n\\n logger.info('writing %s', filename)\\n with open(filename, 'wb') as fp:\\n fp.write(_b(contents))\\n\\n del contents\\n del data\\n gc.collect(1)\",\n \"def save_as(self, filename: str) -> None:\\n save_data = lzma.compress(pickle.dumps(self))\\n with open(filename, \\\"wb\\\") as f:\\n f.write(save_data)\",\n \"def save_vectorizer(self, vectorizer_filepath):\\n with open(vectorizer_filepath, \\\"w\\\") as fp:\\n json.dump(self._vectorizer.to_serializable(), fp)\",\n \"def picklesave(obj, path):\\n with open(path, 'wb') as file:\\n pickle.dump(obj, file)\",\n \"def save_class_representation(self):\\n class_dict = {}\\n for key, value in self.class_dict.items():\\n class_dict['-'.join(key)] = list(value)\\n with open('data/class_vectors.txt', 'w') as file:\\n json.dump(class_dict, file)\\n return class_dict\",\n \"def save_model(self):\\n\\n self.check_model()\\n\\n with open(self.filename, 'wb') as file:\\n pickle.dump({'model': self.model, 'vec': self.vectorizer, 'vec_data': self.vectorized_data,\\n 'df': self.df_topic_keywords}, file)\",\n \"def save_histogram_data(self, histogram_data, obj_name):\\n dirname = os.path.dirname(os.path.abspath(__file__))\\n histogram_data_dir = os.path.join(dirname, '../data/histogram_data')\\n if not os.path.exists(histogram_data_dir):\\n os.mkdir(histogram_data_dir)\\n filename = os.path.join(histogram_data_dir, obj_name + '_' + self.color_name + '.pkl.gz')\\n with gzip.open(filename, 'wb') as f:\\n pickle.dump(histogram_data, f)\",\n \"def pickle_object(Object, file):\\n filehandler = open(file, 'wb')\\n pickle.dump(Object, filehandler)\\n filehandler.close()\",\n \"def save_sample_dict(self):\\n with open(self._sample_dict_path, 'w+') as fp:\\n pickle.dump(self.sample_dict, fp)\",\n \"def pickle_to_file(obj, path):\\n pickle.dump(obj, open(path, 'wb'))\",\n \"def save_object(obj, file_name):\\n file_name = osp.abspath(file_name)\\n with open(file_name, 'wb') as f:\\n pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)\",\n \"def pickle_write(file_path, obj):\\n\\n with open(file_path, 'wb') as file:\\n pickle.dump(obj, file)\",\n \"def dump_pth(filename, obj, **kwargs):\\n import torch\\n return torch.save(obj, filename)\",\n \"def save_object(o, fn):\\n return dump_object(o, fn)\",\n \"def save(self):\\n if not self.fileKey:\\n log.error(\\\"attempted to save a closed wallet\\\")\\n return\\n encrypted = self.fileKey.encrypt(tinyjson.dump(self).encode()).hex()\\n w = tinyjson.dump({\\n \\\"keyparams\\\": self.fileKey.params(),\\n \\\"wallet\\\": encrypted,\\n })\\n helpers.saveFile(self.path, w)\",\n \"def save(cls):\\n playerdata = getAttributes(cls)\\n Data.object_dump(playerdata, \\\"savedata.dat\\\")\\n del playerdata\",\n \"def save(self, filename):\\n data = {\\\"sizes\\\": self.sizes,\\n \\\"weights\\\": [w.tolist() for w in self.weights],\\n \\\"biases\\\": [b.tolist() for b in self.biases],\\n \\\"cost\\\": str(self.cost.__name__)}\\n f = open(filename, \\\"w\\\")\\n json.dump(data, f)\\n f.close()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6844523","0.66101277","0.65988386","0.6553184","0.65457076","0.6461133","0.6404799","0.6393051","0.6333784","0.63045895","0.6251503","0.6237465","0.6224473","0.62162364","0.62162364","0.62048894","0.6202406","0.6202227","0.62018937","0.62000716","0.61975724","0.61801237","0.6173234","0.61647904","0.6164025","0.61575365","0.6154654","0.61514187","0.6149242","0.61446136","0.6128747","0.61267924","0.6119229","0.6117679","0.6117679","0.61109406","0.6097921","0.6091059","0.60895556","0.60775954","0.6068654","0.6040258","0.6002933","0.5999954","0.59962463","0.5992267","0.5992233","0.5992233","0.59831613","0.5967907","0.5965577","0.59560764","0.5953717","0.5951795","0.5944192","0.5940767","0.593775","0.59358513","0.5931523","0.59267694","0.5925285","0.59234315","0.59225553","0.5922029","0.5921383","0.5920784","0.59199387","0.59115005","0.59064335","0.590182","0.5893364","0.58915377","0.588869","0.58876973","0.5883327","0.58751655","0.58747095","0.58710176","0.5870107","0.5869236","0.5861298","0.58584315","0.5850309","0.58467543","0.58432025","0.5841395","0.5839417","0.5833036","0.5822326","0.58213973","0.5803182","0.5802928","0.57988834","0.57979614","0.5797183","0.57948613","0.57860804","0.57792217","0.57780755","0.57717276"],"string":"[\n \"0.6844523\",\n \"0.66101277\",\n \"0.65988386\",\n \"0.6553184\",\n \"0.65457076\",\n \"0.6461133\",\n \"0.6404799\",\n \"0.6393051\",\n \"0.6333784\",\n \"0.63045895\",\n \"0.6251503\",\n \"0.6237465\",\n \"0.6224473\",\n \"0.62162364\",\n \"0.62162364\",\n \"0.62048894\",\n \"0.6202406\",\n \"0.6202227\",\n \"0.62018937\",\n \"0.62000716\",\n \"0.61975724\",\n \"0.61801237\",\n \"0.6173234\",\n \"0.61647904\",\n \"0.6164025\",\n \"0.61575365\",\n \"0.6154654\",\n \"0.61514187\",\n \"0.6149242\",\n \"0.61446136\",\n \"0.6128747\",\n \"0.61267924\",\n \"0.6119229\",\n \"0.6117679\",\n \"0.6117679\",\n \"0.61109406\",\n \"0.6097921\",\n \"0.6091059\",\n \"0.60895556\",\n \"0.60775954\",\n \"0.6068654\",\n \"0.6040258\",\n \"0.6002933\",\n \"0.5999954\",\n \"0.59962463\",\n \"0.5992267\",\n \"0.5992233\",\n \"0.5992233\",\n \"0.59831613\",\n \"0.5967907\",\n \"0.5965577\",\n \"0.59560764\",\n \"0.5953717\",\n \"0.5951795\",\n \"0.5944192\",\n \"0.5940767\",\n \"0.593775\",\n \"0.59358513\",\n \"0.5931523\",\n \"0.59267694\",\n \"0.5925285\",\n \"0.59234315\",\n \"0.59225553\",\n \"0.5922029\",\n \"0.5921383\",\n \"0.5920784\",\n \"0.59199387\",\n \"0.59115005\",\n \"0.59064335\",\n \"0.590182\",\n \"0.5893364\",\n \"0.58915377\",\n \"0.588869\",\n \"0.58876973\",\n \"0.5883327\",\n \"0.58751655\",\n \"0.58747095\",\n \"0.58710176\",\n \"0.5870107\",\n \"0.5869236\",\n \"0.5861298\",\n \"0.58584315\",\n \"0.5850309\",\n \"0.58467543\",\n \"0.58432025\",\n \"0.5841395\",\n \"0.5839417\",\n \"0.5833036\",\n \"0.5822326\",\n \"0.58213973\",\n \"0.5803182\",\n \"0.5802928\",\n \"0.57988834\",\n \"0.57979614\",\n \"0.5797183\",\n \"0.57948613\",\n \"0.57860804\",\n \"0.57792217\",\n \"0.57780755\",\n \"0.57717276\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6865105"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81792,"cells":{"query":{"kind":"string","value":"Create an memory Object of GloVe dictionary from binary file"},"document":{"kind":"string","value":"def loadGloveDicFromFile():\n \n #if the resource file is not present, creates the file containing all vectors\n #and return vectors\n if not isfile(GLOVE_DICT_FILE):\n vects = _extractGloveVects()\n saveGloveDicIntoFile(vects)\n return vects\n \n return np.load(GLOVE_DICT_FILE)[0]"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def build_from_file(path):\n with open(path) as obj:\n raw_file = obj.read()\n file_lines = [line.split(\" \") for line in raw_file.split(\"\\n\")]\n\n vertices = {}\n faces = []\n for number, line in enumerate(file_lines):\n if line[0] == \"v\":\n vertices[number + 1] = tuple(map(float, line[1:]))\n if line[0] == \"f\":\n face = []\n for index in line[1:]:\n face.append(vertices[int(index)])\n face.append(vertices[int(line[1])])\n faces.append(face)\n return Object(points=faces)","def load_glove(path):\n with open(path) as f:\n glove = {}\n for line in f.readlines():\n values = line.split()\n word = values[0]\n vector = np.array(values[1:], dtype='float32')\n glove[word] = vector\n return glove","def load_glove(path):\n with open(path) as f:\n glove = {}\n for line in f.readlines():\n values = line.split()\n word = values[0]\n vector = np.array(values[1:], dtype='float32')\n glove[word] = vector\n return glove","def load_dict(path_to_vec):\n emb = {}\n with open(path_to_vec, 'r', errors='ignore', encoding='utf8') as f:\n for line in f:\n values = line.split()\n word = values[0]\n vector = np.asarray(values[1:], \"float32\")\n emb[word] = vector\n return emb","def readInstance(self):\n file = open(self.fName, 'r')\n self.genSize = int(file.readline())\n self.data = {}\n for line in file:\n (id, x, y) = line.split()\n self.data[int(id)] = (int(x), int(y))\n file.close()","def load_glove_data():\n glove_path = path.join('..', 'data', 'glove', 'glove.twitter.27B.200d.txt')\n f = open(glove_path,'r')\n \n model = {}\n for line in f:\n splitLine = line.split()\n word = splitLine[0]\n embedding = np.array([float(val) for val in splitLine[1:]])\n model[word] = embedding\n \n return model","def read_pkl(infile):\n # loading\n if infile is not None:\n logging.info('No pkl provided. Creating a new object')\n pkl = pickle.load(bz2.open(infile, 'r'))\n else:\n logging.info('Reading in: {}'.format(infile))\n # creating new object\n pkl = {'taxonomy' : {}, 'markers' : {}}\n return pkl","def load(filename):\n file = gzip.GzipFile(filename, 'rb')\n object = cPickle.load(file)\n file.close()\n return object","def load_viz_object(filename: str) -> OrqVizObject:\n\n with open(filename, \"rb\") as f:\n loaded_object = pickle.load(f)\n\n return loaded_object","def load(filename):\n file = gzip.GzipFile(filename, 'rb')\n buffer = \"\"\n while 1:\n data = file.read()\n if data == \"\":\n break\n buffer += data\n object = pickle.loads(buffer)\n file.close()\n return object","def load(filename):\n file = gzip.GzipFile(filename, 'rb')\n buffer = \"\"\n while True:\n data = file.read()\n if data == \"\":\n break\n buffer += data\n object = pickle.loads(buffer)\n file.close()\n return object","def load_from_file(self, filename):\n # clear datastore mape\n self._datastoreMap = {}\n # citanje filea\n with open(filename, 'rb') as f:\n binstr = f.read()\n inMap = pickle.loads(binstr)\n # za svaki kanal moramo dodati element u _datastoreMap\n for kanal in inMap:\n # stvaramo instancu Datastore\n self._datastoreMap[kanal] = DataStore()\n # instanca Datastore zna se otpakirati iz mape (dictionary)\n self._datastoreMap[kanal].dict2store(inMap[kanal])","def load_fragGC_pickle(inFH):\n fojb = pickle.load(inFH)\n\n d = dict()\n for x in fojb:\n taxon_name = x[0]\n d[taxon_name] = dict()\n d[taxon_name]['fragLength'] = []\n d[taxon_name]['fragGC'] = []\n \n for scaf,v in x[1].items(): \n for z in v:\n # fragStart, fragLength, fragGC\n d[taxon_name]['fragLength'].append(z[1])\n d[taxon_name]['fragGC'].append(z[2]) \n return d","def load_obj(file, **kwargs):\n v = []\n vt = []\n vn = []\n f = []\n for line in file:\n if line.startswith(\"v \"):\n v.append([float(x) for x in line[2:].split()])\n elif line.startswith(\"vt \"):\n vt.append([float(x) for x in line[3:].split()])\n elif line.startswith(\"vn \"):\n vn.append([float(x) for x in line[3:].split()])\n elif line.startswith(\"f \"):\n f.append([[int(x) for x in fv.split('/')] for fv in line[2:].split()])\n\n # now produce the full buffers\n f = np.array(f, dtype='i4')\n f[f > 0] -= 1\n v = np.array(v, dtype='f4')[f[:, :, 0].ravel()]\n vt = np.array(vt, dtype='f4')[f[:, :, 1].ravel()]\n vn = np.array(vn, dtype='f4')[f[:, :, 2].ravel()]\n\n # NOTE: we could identify unique vertices in f and shave off memory requirements. we could.\n\n return Geometry({'pos': v, 'uv': vt, 'normal': vn}, primitive=Primitives.TRIANGLES, **kwargs)","def load_dictionary(filepath):\r\n # context manager read binary\r\n with open(filepath, 'rb') as file:\r\n # pickle load\r\n return pickle.load(file)","def load(filename):\n file = gzip.GzipFile(filename, 'rb')\n buffer = \"\"\n while True:\n data = file.read()\n if data == \"\":\n break\n buffer += data\n object = pickle.loads(buffer)\n file.close()\n return object","def __init__(self, path, bigendian=False, use_mmap=None):\n self.rd = DictReader(path, bigendian, use_mmap)\n with self.rd as r:\n node_size = r.get_int()\n tind_size = r.get_int()\n tail_size = r.get_int()\n self.num_keys = tind_size\n self.begs = r.get_intarray(tind_size)\n self.base = r.get_intarray(node_size)\n self.lens = r.get_shortarray(tind_size)\n self.chck = r.get_chararray(node_size)\n self.tail = r.get_chararray(tail_size)","def load_object(filename):\n\n with gzip.GzipFile(filename, 'rb') as source: result = source.read()\n ret = pickle.loads(result)\n source.close()\n\n return ret","def load_pkl(self, name, file_object=None):\n if file_object:\n f = file_object\n else:\n f = gzip.open(name, 'rb')\n temp = pickle.load(f)\n if temp.ht_version < HT_OLD_COMPAT_VERSION:\n raise ValueError('Version of ' + name + ' is ' + str(temp.ht_version)\n + ' which is not at least ' +\n str(HT_OLD_COMPAT_VERSION))\n # assert temp.ht_version >= HT_COMPAT_VERSION\n params = temp.params\n self.hashbits = temp.hashbits\n self.depth = temp.depth\n if hasattr(temp, 'maxtimebits'):\n self.maxtimebits = temp.maxtimebits\n else:\n self.maxtimebits = _bitsfor(temp.maxtime)\n if temp.ht_version < HT_COMPAT_VERSION:\n # Need to upgrade the database.\n print(\"Loading database version\", temp.ht_version,\n \"in compatibility mode.\")\n # Offset all the nonzero bins with one ID count.\n temp.table += np.array(1 << self.maxtimebits).astype(np.uint32) * (\n temp.table != 0)\n temp.ht_version = HT_VERSION\n self.table = temp.table\n self.ht_version = temp.ht_version\n self.counts = temp.counts\n self.names = temp.names\n self.hashesperid = np.array(temp.hashesperid).astype(np.uint32)\n self.dirty = False\n self.params = params","def createGloveDic():\n saveGloveDicIntoFile(_extractGloveVects())","def load_bin_vec(filename):\n w2v = {}\n with open(filename, 'r') as f:\n header = f.readline()\n vocab_size, emb_size = map(int, header.split())\n for line in f:\n cline = line.split()\n w2v[cline[0]] = np.array(cline[1:], dtype=np.float64)\n return w2v, emb_size, vocab_size","def load(path: str) -> \"DataDescriptor\":\n\n\t\twith open(path, \"r\") as f:\n\t\t\tinfo_dict = json.load(f)\n\n\t\treturn DataDescriptor(\n\t\t\tn_gram_size=int(info_dict[\"n_gram_size\"]),\n\t\t\tcaseless=bool(info_dict[\"caseless\"]),\n\t\t\tignore_punctuation=bool(info_dict[\"ignore_punctuation\"]),\n\t\t\tadd_pos_tags=bool(info_dict[\"add_pos_tags\"]),\n\t\t\tuses_lemma=bool(info_dict[\"uses_lemma\"]),\n\t\t\tuses_sentences=bool(info_dict[\"uses_sentences\"])\n\t\t)","def load(npz):\n e = np.load(npz, allow_pickle=True)\n return EOMap(\n e['dataStore'],\n e['etas'],\n e['etaEdges'],\n e['omegas'],\n e['omeEdges'],\n e['iHKLList'],\n plane_data(e)\n )","def load_dictionary(filename):\n filename = os.path.join(FILE_DIR, 'assets/obj/' + filename)\n try:\n with open(filename, 'rb') as input:\n return pickle.load(input)\n except Exception as e:\n print(\"exception\", e)","def file_to_dictionary():\n\n return;","def load_object(self, filename):\n with open(filename, 'rb') as inp: # Overwrites any existing file.\n data = pickle.load(inp)\n return data","def load_glove_vec(fname):\n word_vecs = {}\n length = 0\n with open(fname, \"rb\") as f:\n for i, line in enumerate(f):\n L = line.split()\n word = L[0].lower()\n word_vecs[word] = np.array(L[1:], dtype='float32')\n if length == 0:\n length = len(word_vecs[word])\n return word_vecs, length","def load(filename):\n return GesFile(filename)","def construct_dict(self):\n i = 0\n self.word2idx = dict()\n fi = open(self.config.word_vec_fi_glove, 'r')\n\n for line in fi:\n self.word2idx[line.split(\" \")[0]] = i\n i += 1\n\n self.vocab_size = i\n self.write_dict()\n fi.close()","def loadGLOVE(filename, vocab):\n dct = {}\n vectors = array.array('d')\n current_idx = 0\n with codecs.open(filename, \"r\", encoding=\"utf-8\") as f:\n for _, line in enumerate(f):\n tokens = line.split(\" \")\n word = tokens[0]\n entries = tokens[1:]\n if not vocab or word in vocab:\n dct[word] = current_idx\n vectors.extend(float(x) for x in entries)\n current_idx += 1\n word_dim = len(entries)\n num_vectors = len(dct)\n tf.logging.info(\"Found {} out of {} vectors in Glove\".format(num_vectors, len(vocab)))\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]","def from_dict(cls, dikt) -> 'DataFileFormat':\n return util.deserialize_model(dikt, cls)","def __init__(self, file):\n with open(file, 'r') as f:\n self.vocab = json.loads(f.read())","def load_mb_obj(in_file):\n\n mth = 0\n metaballs = []\n vertices = []\n vcolors = []\n vnormals = []\n faces = []\n\n if in_file.endswith(\".gz\"):\n f_in = gzip.open(in_file, 'rt')\n else:\n f_in = open(in_file, 'r')\n\n for line in f_in:\n vals = line.split()\n\n if len(vals) == 0:\n continue\n\n if vals[0] == \"#\":\n if (len(vals) > 2):\n if vals[1] == \"mth\":\n mth = float(vals[2])\n\n if vals[1] == \"mb\":\n mb = Metaball(float(vals[2]),\n float(vals[3]),\n float(vals[4]),\n float(vals[5]),\n float(vals[6]))\n metaballs.append(mb)\n\n if vals[0] == \"v\":\n v = [float(x) for x in vals[1:4]]\n vertices.append(v)\n\n if len(vals) == 7:\n vc = [float(x) for x in vals[4:7]]\n vcolors.append(vc)\n\n if vals[0] == \"vn\":\n vn = [float(x) for x in vals[1:4]]\n vnormals.append(vn)\n\n if vals[0] == \"f\":\n fvi = []\n\n for f in vals[1:]:\n w = f.split(\"/\")\n fvi.append(int(w[0]) - 1)\n\n faces.append(fvi)\n\n f_in.close()\n\n print(\"load \"+in_file+\": {:d} cells\".format(len(vertices)))\n\n return (Metaballs(metaballs, mth),\n np.array(vertices),\n np.array(vcolors),\n np.array(vnormals),\n np.array(faces))","def load(cls, file: str):\n\n bfh = cls()\n\n with open(file, 'br') as sgy:\n # get the endian\n endian = gfunc.grab_endiannes(sgy)\n\n # skip the TFH, read the BFH bytes\n sgy.seek(3200)\n raw = sgy.read(400)\n\n # unpack and store the values\n values = struct.unpack(endian + const.BFHFS, raw)\n bfh._dict = dict(zip(const.BFHCOLS, values))\n\n return bfh","def load_skeleton(skel_file) -> Dict:\n with open(skel_file, 'rb') as handle:\n skel_dict = pickle.load(handle)\n\n return skel_dict","async def load(self, file: IO) -> dict:","def load_data(filename):\r\n with open(filename,'rb') as f:\r\n data = pk.load(f,encoding='bytes')\r\n return data[b'data'],data[b'labels']","def load (cls, file):\n with open(file) as f:\n raw = json.load(f)\n obj = PasswordSetCharacteristics()\n obj.lengths = cls.to_num_dict(raw['lengths'])\n obj.lower_counts = cls.to_num_dict(raw['lowerCounts'])\n obj.upper_counts = cls.to_num_dict(raw['upperCounts'])\n obj.digit_counts = cls.to_num_dict(raw['digitCounts'])\n obj.symbol_counts = cls.to_num_dict(raw['symbolCounts'])\n obj.class_counts = cls.to_num_dict(raw['classCounts'])\n obj.word_counts = cls.to_num_dict(raw['wordCounts'])\n return obj","def from_file(cls, file_obj):\n kdm = cls(file_obj.read())\n return kdm","def unpickle(file):\r\n\timport cPickle\r\n\tfo = open(file, 'rb')\r\n\tdict = cPickle.load(fo)\r\n\tfo.close()\r\n\treturn dict","def load(cls, filename):\n return cPickle.load(open(filename, \"rb\"))","def load_object(filename):\r\n with open(filename, 'rb') as input:\r\n obj = pickle.load(input)\r\n return obj","def binary_to_dictionary(\n binary: bytes,\n filename: str | None = None\n) -> 'FileDict':\n\n assert isinstance(binary, bytes)\n\n mimetype = magic.from_buffer(binary, mime=True)\n\n # according to https://tools.ietf.org/html/rfc7111, text/csv should be used\n if mimetype == 'application/csv':\n mimetype = 'text/csv'\n\n gzipdata = BytesIO()\n\n with gzip.GzipFile(fileobj=gzipdata, mode='wb') as f:\n f.write(binary)\n\n return {\n 'data': base64.b64encode(gzipdata.getvalue()).decode('ascii'),\n 'filename': filename,\n 'mimetype': mimetype,\n 'size': len(binary)\n }","def load_glove(file_path: str, return_embedding_size: bool=False) ->Dict[str, np.ndarray]:\n logger.info(f' Loading Glove format file {file_path}')\n embeddings = {}\n embedding_size = 0\n with open_file(file_path, 'r', encoding='utf-8') as f:\n found_line = False\n while not found_line:\n line = f.readline()\n if line:\n embedding_size = len(line.split()) - 1\n found_line = True\n with open_file(file_path, 'r', encoding='utf-8') as f:\n for line_number, line in enumerate(f):\n if line:\n try:\n split = line.split()\n if len(split) != embedding_size + 1:\n raise ValueError(f'Line {line_number} is of length {len(split)}, while expected length is {embedding_size + 1}.')\n word = split[0]\n embedding = np.array([float(val) for val in split[-embedding_size:]])\n embeddings[word] = embedding\n except ValueError:\n logger.warning('Line {} in the GloVe file {} is malformed, skipping it'.format(line_number, file_path))\n logger.info(f' {len(embeddings)} embeddings loaded')\n if return_embedding_size:\n return embeddings, embedding_size\n return embeddings","def readobject(filename):\n # import cPickle as pickle\n with open(filename, 'rb') as input_file:\n return pickle.load(input_file)","def load_glove_vec(fname, vocab):\n word_vecs = {}\n with open(fname, \"rb\") as f:\n for i,line in enumerate(f):\n L = line.split()\n word = L[0].lower()\n if word in vocab:\n word_vecs[word] = np.array(L[1:], dtype='float32')\n return word_vecs","def _read(self):\n # initializng data dictionary\n self.data={}\n\n f = FortranFile(self.filename)\n # Default omnivor binary header\n self.data['MK'] = f.readInts('i')\n self.data['itime'] = f.readInts('i')\n self.data['version'] = f.readString()\n self.data['file_id'] = f.readInts('i')\n self.data['sversion'] = f.readString()\n # Velocity field\n self.data['stype'] = f.readString()\n self.data['is_grid'] = f.readInts('i')\n nCPs = f.readInts('i')\n self.data['nCPs'] = nCPs\n if self.data['MK'] == 8:\n real_char='d'\n else:\n real_char='f'\n if self.data['is_grid']:\n #print('File is a velocity grid file')\n n1 = f.readInts('i')\n n2 = f.readInts('i')\n n3 = f.readInts('i')\n self.data['n1'] = n1\n self.data['n2'] = n2\n self.data['n3'] = n3\n self.data['is_straight'] = f.readInts('i')\n self.data['v1'] = f.readReals(real_char)\n self.data['v2'] = f.readReals(real_char)\n self.data['v3'] = f.readReals(real_char)\n\n CPs_raw = f.readReals(real_char)\n Utot_raw = f.readReals(real_char)\n CPs = np.reshape(CPs_raw,(3,nCPs),order = 'F')\n Utot = np.reshape(Utot_raw,(3,nCPs),order = 'F')\n\n acc=-1\n CPsTab = np.zeros((3, n1,n2,n3))\n UtotTab = np.zeros((3, n1,n2,n3))\n # Reshaping the nasty way (this is natural order). \n for i in range(0,n1):\n for j in range(0,n2):\n for k in range(0,n3):\n acc=acc+1\n CPsTab[0:3,i,j,k] = CPs[0:3,acc]\n UtotTab[0:3,i,j,k] = Utot[0:3,acc]\n\n self.data['CPs'] = CPs\n self.data['CPsTab'] = CPsTab\n self.data['Utot'] = Utot\n self.data['UtotTab'] = UtotTab","def unpickle(self, file):\n import pickle\n with open(file, 'rb') as fo:\n dict = pickle.load(fo, encoding='bytes')\n return dict","def load_data(filename) :\r\n data = Data()\r\n data.load(filename)\r\n return data","def load(self, path='dict.pic'):\n with open(path, 'rb') as f:\n self.__dictionary = pickle.load(f)\n self.__vocab_size = len(self.__dictionary)\n\n if self.__verbose:\n print('Loading Tokenizer, vocab size:', self.vocab_size())","def load_bin_vec(fname, vocab):\n word_vecs = {}\n with open(fname, \"rb\") as f:\n header = f.readline()\n vocab_size, layer1_size = map(int, header.split())\n binary_len = np.dtype('float32').itemsize * layer1_size\n for line in xrange(vocab_size):\n word = []\n while True:\n ch = f.read(1)\n if ch == ' ':\n word = ''.join(word)\n break\n if ch != '\\n':\n word.append(ch)\n if word in vocab:\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32') \n else:\n f.read(binary_len)\n cPickle.dump(word_vecs, open(\"./data/word_vecs.pkl\", \"w\"))\n return word_vecs","def create_from_file(filename: str):\n if not os.path.isfile(filename):\n raise FileNotFoundError(\"Failed to find GeneSet file \" + filename)\n\n with open(filename, \"rb\") as binary_reader:\n (gene_sets, gene_set_size, gene_set_names, interactors, n_curated, n_interactors) = \\\n pickle.load(binary_reader)\n\n gene_set = GeneSet(dict())\n gene_set.gene_sets = gene_sets\n gene_set.gene_set_size = gene_set_size\n gene_set.gene_set_names = gene_set_names\n gene_set.interactors = interactors\n gene_set.n_curated = n_curated\n gene_set.n_interactors = n_interactors\n\n return gene_set","def load(cls, filepath) -> 'Word2VecEmbedding':\n with open(filepath, 'rb') as f:\n embedding = pickle.load(f)\n embedding.word2idx = {spell: idx for idx, spell in enumerate(embedding.vocab.idx2word)}\n return embedding","def load_object(filename):\n with open(filename, 'rb') as input_file: # Overwrites any existing file.\n obj = pickle.load(input_file)\n return obj","def get_glove_embedding():\n embedding = {}\n N = 400_000\n print(\"Reading glove embedding...\")\n with open(GLOVE_EMBD_PATH, \"rb\") as f:\n for line in tqdm(f, total=N):\n line = line.decode().split()\n word = line[0].lower()\n vector = np.array(line[1:]).astype(np.float32)\n embedding[word] = vector\n\n return embedding","def load_vector_dictionary():\n return read_word2vecs_from_file(VECTOR_FILE)","def load_glb(self):\n with open(str(self.path), \"rb\") as fd:\n # Check header\n magic = fd.read(4)\n if magic != GLTF_MAGIC_HEADER:\n raise ValueError(\n \"{} has incorrect header {} != {}\".format(\n self.path, magic, GLTF_MAGIC_HEADER\n )\n )\n\n version = struct.unpack(\"<I\", fd.read(4))[0]\n if version != 2:\n raise ValueError(\n \"{} has unsupported version {}\".format(self.path, version)\n )\n\n # Total file size including headers\n _ = struct.unpack(\"<I\", fd.read(4))[0] # noqa\n\n # Chunk 0 - json\n chunk_0_length = struct.unpack(\"<I\", fd.read(4))[0]\n chunk_0_type = fd.read(4)\n if chunk_0_type != b\"JSON\":\n raise ValueError(\n \"Expected JSON chunk, not {} in file {}\".format(\n chunk_0_type, self.path\n )\n )\n\n json_meta = fd.read(chunk_0_length).decode()\n\n # chunk 1 - binary buffer\n chunk_1_length = struct.unpack(\"<I\", fd.read(4))[0]\n chunk_1_type = fd.read(4)\n if chunk_1_type != b\"BIN\\x00\":\n raise ValueError(\n \"Expected BIN chunk, not {} in file {}\".format(\n chunk_1_type, self.path\n )\n )\n\n self.gltf = GLTFMeta(\n self.path,\n json.loads(json_meta),\n self.meta,\n binary_buffer=fd.read(chunk_1_length),\n )","def getFlightDict():\n\n dictionary = {}\n f = open(filename3,'rb') \n\n dictionary = pickle.load(f)\n f.close()\n return dictionary","def readSoft2Dict(softFileName,index=11):\n import gzip\n probe2Entrez = {}\n Flag = False\n if softFileName[-2:] == \"gz\":\n softHandle = gzip.open(softFileName,\"rt\")\n else:\n softHandle = open(softFileName,\"r\")\n softMatrix = softHandle.readlines()\n for line in softMatrix:\n line = line.split(\"\\t\")\n #if len(line[0]) <5 :\n # print(line[0].lower())\n if len(line) <= index:\n continue\n if Flag:\n #print(line)\n if line[0] in probe2Entrez.keys():\n probe2Entrez[line[0]].append(line)\n else:\n probe2Entrez[line[0]] = [line]\n if line[0].lower() == 'id':\n Flag = True\n multipleKeyList = []\n for key in probe2Entrez: #discard probs refer to multiple genes\n if len(probe2Entrez[key]) > 1:\n multipleKeyList.append(key)\n for key in multipleKeyList: #can't del keys of dictionary when iterating it\n del probe2Entrez[key]\n return probe2Entrez","def unpickle(file):\n\timport pickle\n\twith open(file, 'rb') as fo:\n\t dict = pickle.load(fo, encoding='bytes')\n\treturn dict","def init_from_obj_file(cls, f, scale=1, density=1):\n lines = [line.strip() for line in f.readlines()]\n vertices = []\n indexes = []\n for line in lines:\n if line.startswith(\"v\"): # vertex\n nums = list(map(float, string_to_list(line[2:])))\n vertices.append(scale * np.array(nums[:3]))\n # x.append(nums[0] * scale)\n # y.append(nums[1] * scale)\n # z.append(nums[2] * scale)\n elif line.startswith(\"f\"): # face\n nums = list(map(lambda a: int(a) - 1, string_to_list(line[2:])))\n indexes.append(nums)\n return cls(vertices, indexes, density)","def from_file(filename, decomposer=None, rx=None, ax=None):\n from six.moves.cPickle import load\n with open(filename, 'rb') as f:\n data = load(f)\n return SOAPVector.from_dict(data, decomposer, rx, ax)","def load_object(path):\r\n with open(path,\"rb\") as f:\r\n object = pickle.load(f) \r\n return object","def _load_glove_vec(fname, vocab):\n print 'load glove...'\n word_vecs = {}\n cnt = 0\n l = open(fname,'r').readline()\n embedding_size = len(l.strip().split()) -1\n print 'embedding vector size: %d'%(embedding_size)\n with open(fname, \"r\") as f:\n for l in f:\n stemp = l.strip().split(' ',1)\n assert len(stemp) == 2\n word = stemp[0]\n if word in vocab:\n word_vecs[stemp[0]] = np.fromstring(' '.join(stemp[1:]),sep = ' ')\n cnt+=1\n if cnt%10000==0:\n print '%d lines...'%cnt\n return (word_vecs,embedding_size)","def from_dict(cls, dikt) -> 'Garage':\n return util.deserialize_model(dikt, cls)","def load_bin_vec(fname, vocab):\n word_vecs = {}\n with open(fname, \"rb\") as f:\n header = f.readline()\n vocab_size, layer1_size = map(int, header.split())\n binary_len = np.dtype('float32').itemsize * layer1_size\n # print(vocab_size)\n for line in range(vocab_size):\n # print(line)\n word = []\n while True:\n ch = f.read(1)\n if ch == ' ':\n word = ''.join(word)\n break\n if ch != '\\n':\n word.append(ch)\n # print(word)\n if word in vocab:\n # print(word)\n word_vecs[word] = np.frombuffer(f.read(binary_len), dtype='float32')\n else:\n f.read(binary_len)\n\n return word_vecs","def load_gensim_dictionary_model(path_to_gensim_dictionary_model):\n dct = Dictionary.load(path_to_gensim_dictionary_model)\n return dct","def load_binary_data(self, encoding='utf8'):\n\n # TODO use smart_open again when https://github.com/RaRe-Technologies/smart_open/issues/207 will be fixed\n with open(self.file_name, 'rb') as f:\n self.load_model_params(f)\n self.load_dict(f, encoding=encoding)\n self.load_vectors(f)","def load(cls,filename):\n obj = None\n f = open(filename,'r')\n try:\n obj = pickle.load(f)\n obj.filename = filename\n finally:\n f.close()\n return obj","def load(self, filename = 'array_zest', path = '/home/eric/dev/insitu/data/zs_recovery/'):\n lpath_filename = path + filename + '.pkl'\n f = open(lpath_filename, 'rb')\n tmp_dict = pickle.load(f)\n f.close()\n self.__dict__.update(tmp_dict)","def load_POD(POD_file):\n if not os.path.isfile(POD_file):\n raise RuntimeError('POD file specified is not a valid file')\n\n # Load data from file\n print('Loading POD data from {}'.format(POD_file))\n POD_data = scutils.load_data(POD_file)\n\n # Generate POD object\n rom = POD(POD_data['POD_info'])\n\n return rom","def load_gltf(self):\n with open(str(self.path)) as fd:\n self.gltf = GLTFMeta(self.path, json.load(fd), self.meta)","def load_obj(path):\n with open(path, 'rb') as f:\n return pickle.load(f)","def load_object(fpath):\r\n with open(fpath, 'rb') as i:\r\n return pickle.load(i)","def from_file( cls, filename ):\n with open( filename, 'r' ) as stream:\n data = yaml.load( stream )\n notes = data.get( 'notes' )\n type = data.get( 'type' )\n vaspmeta = VASPMeta( data['title'], \n data['description'], \n data['status'], \n notes=notes, \n type=type )\n return vaspmeta","def loadFileEGG(model, fileName):\r\n model.coordinateSystem = \"Y-up\"\r\n model.materialList = {}\r\n model.textureList = {}\r\n model.vertexGroupList = {}\r\n model.vertexList = []\r\n model.polygonList = []\r\n model.childModelList = []\r\n model.parentModel = None\r\n model.childModel = [] # don't really need parent and child pointers but will speed up traversing tree\r\n model.vNormal = False\r\n model.vGroup = {} # holds the information for each vertex group\r\n\r\n # read in the file and parse into some arrays\r\n\r\n if fileName[0] != '/':\r\n fileName = sys.path[0] + '/' + fileName\r\n filePath = os.path.split(os.path.abspath(fileName))[0]\r\n if VERBOSE:\r\n print(filePath)\r\n f = open(fileName, 'r')\r\n l = f.read() # whole thing as a string in memory this will only work for reasonably small files!!!\r\n\r\n ############### function to parse file as one off process to avoid re-traversing string #########\r\n # convertes the '<a> b { c <d> e {f} <g> h {i} }' structure\r\n # into nested arrays ['a', 'b', 'c',[['d','e','',['','','f',[]]],['g','h','',['','','i',[]]]]]\r\n def pRec(x, bReg, l, i):\r\n while 1:\r\n try:\r\n nxtFind = advance_iterator(bReg)\r\n j = nxtFind.start()\r\n except:\r\n return i+1\r\n c = l[j]\r\n if c == \"<\": # add entry to array at this level\r\n if len(x[3]) == 0: x[2] = l[i:j].strip() # text after \"{\" and before \"<Tabxyz>\"\r\n i = j+1 # save marker for start of descriptor\r\n x[3].append([\"\", \"\", \"\", []])\r\n\r\n elif c == \"{\":\r\n xn = x[3][len(x[3])-1]\r\n tx = l[i-1:j].strip().split()\r\n xn[0] = tx[0] #x[0] & x[1] is the \"<Tabxyz>\" & \"123\" prior to \"{\"\r\n xn[1] = tx[1] if len(tx) > 1 else \"\"\r\n i = pRec(xn, bReg, l, j+1)\r\n else: #i.e. c=\"}\" # go up one level of recursion\r\n if len(x[3]) == 0: x[2] = l[i:j].strip()\r\n return j+1\r\n ################### end of pRec #################\r\n\r\n ####### go through all the nested <Groups> ####################\r\n def groupDrill(gp, np):\r\n structVList = {}\r\n offsetVList = {}\r\n structPList = []\r\n offset = 0\r\n #numv = 0\r\n #numi = 0\r\n for x in gp:\r\n if len(x) == 0: continue\r\n if (\"<Group>\" in x[0]):\r\n if len(x[1]) > 0:\r\n nextnp = np+x[1]\r\n else:\r\n nextnp = np+str(randint(10000, 99999))\r\n groupDrill(x[3], nextnp)\r\n else:\r\n #build vertex, polygon, normal, triangles, UVs etc etc\r\n if \"<VertexPool>\" in x[0]:\r\n vp = x[1]\r\n structVList[vp] = []\r\n offsetVList[vp] = offset\r\n for v in x[3]:\r\n #if \"<Vertex>\" in v[0]: #try with this test first!\r\n coords = [float(n) for n in v[2].strip().split()] # before first < error if no coords!\r\n # texture mapping\r\n UVcoords = []\r\n normal = []\r\n for u in v[3]:\r\n if \"<UV>\" in u[0]: UVcoords = [float(n) for n in u[2].strip().split()]\r\n #TODO get UVtangent and UVbinormal out of UVset (and use them!)\r\n # if (\"<Tangent>\" in vList[v]): UVtangent = [float(n) for n in (extBracket(\"<Tangent>\", vList[v]))[0].split()] # not sure how to use this at this stage\r\n #else: UVtangent = []\r\n # if (\"<Binormal>\" in vList[v]): UVbinormal = [float(n) for n in (extBracket(\"<Binormal>\", vList[v]))[0].split()] # not sure how to use this at this stage\r\n #else: UVbinormal = []\r\n # normals, used in 'smoothing' edges between polygons\r\n if \"<Normal>\" in u[0]: normal = [float(n) for n in u[2].strip().split()]\r\n vInt = int(v[1])\r\n while (len(structVList[vp]) < (vInt+1)): structVList[vp].append(\"\")\r\n structVList[vp][vInt] = (vertex(coords, UVcoords, normal))\r\n offset += 1\r\n #\r\n # now go through splitting out the Polygons from this Group same level as vertexGroup\r\n if \"<Polygon>\" in x[0]:\r\n normal = []\r\n rgba = []\r\n MRef = \"\"\r\n TRef = \"\"\r\n for p in x[3]:\r\n if (\"<Normal>\" in p[0]): normal = [float(n) for n in p[2].strip().split()]\r\n if (\"<RGBA>\" in p[0]): rgba = [float(n) for n in p[2].strip().split()]\r\n if (\"<MRef>\" in p[0]): MRef = p[2].strip()\r\n if (\"<TRef>\" in p[0]): TRef = p[2].strip()\r\n if (\"<VertexRef>\" in p[0]):\r\n vref = []\r\n for n in p[2].strip().split():\r\n vref.append(int(n))\r\n #numv += 1\r\n #numi += 3\r\n #numi -= 6 # number of corners of triangle = (n-2)*3 where n is the number of corners of face\r\n vpKey = p[3][0][2].strip() # ought to do a for r in p[3]; if \"Ref in...\r\n # add to list\r\n #while (len(structPList) < (p+1)): structPList.append(\"\")\r\n #\r\n structPList.append(polygon(normal, rgba, MRef, TRef, vref, vpKey))\r\n\r\n # now go through the polygons in order of vertexPool+id, trying to ensure that the polygon arrays in each group are built in the order of vertexPool names\r\n # only cope with one material and one texture per group\r\n #numv -= 1\r\n #numi -= 1\r\n g_vertices = []\r\n g_normals = []\r\n g_tex_coords = []\r\n g_indices = []\r\n nv = 0 # vertex counter in this material\r\n #ni = 0 # triangle vertex count in this material\r\n\r\n gMRef = \"\"\r\n gTRef = \"\"\r\n nP = len(structPList)\r\n for p in xrange(nP):\r\n if (len(structPList[p].MRef) > 0): gMRef = structPList[p].MRef\r\n else: gMRef = \"\"\r\n if (len(structPList[p].TRef) > 0): gTRef = structPList[p].TRef\r\n else: gTRef = \"\"\r\n\r\n vpKey = structPList[p].vpKey\r\n vref = structPList[p].vref\r\n startV = nv\r\n for j in vref:\r\n\r\n if (len(structVList[vpKey][j].normal) > 0): model.vNormal = True\r\n else: model.vNormal = False\r\n if model.coordinateSystem == \"z-up\":\r\n thisV = [structVList[vpKey][j].coords[1], structVList[vpKey][j].coords[2], -structVList[vpKey][j].coords[0]]\r\n if model.vNormal:\r\n thisN = [structVList[vpKey][j].normal[1], structVList[vpKey][j].normal[2], -structVList[vpKey][j].normal[0]]\r\n else:\r\n thisV = [structVList[vpKey][j].coords[0], structVList[vpKey][j].coords[1], -structVList[vpKey][j].coords[2]]\r\n if model.vNormal:\r\n thisN = [structVList[vpKey][j].normal[0], structVList[vpKey][j].normal[1], -structVList[vpKey][j].normal[2]]\r\n g_vertices.append(thisV)\r\n if model.vNormal: nml = thisN\r\n else: nml = structPList[p].normal\r\n g_normals.append(nml)\r\n uvc = structVList[vpKey][j].UVcoords\r\n if (len(uvc) == 2):\r\n g_tex_coords.append(uvc)\r\n else:\r\n g_tex_coords.append([0.0, 0.0])\r\n nv += 1\r\n n = nv - startV - 1\r\n for j in range(1, n):\r\n g_indices.append((startV, startV + j + 1, startV + j))\r\n\r\n ilen = len(g_vertices)\r\n if ilen > 0:\r\n if len(g_normals) != len(g_vertices):\r\n g_normals = None # force Buffer.__init__() to generate normals\r\n model.buf.append(Buffer(model, g_vertices, g_tex_coords, g_indices, g_normals))\r\n n = len(model.buf) - 1\r\n model.vGroup[np] = n\r\n\r\n model.buf[n].indicesLen = ilen\r\n model.buf[n].material = (0.0, 0.0, 0.0, 0.0)\r\n model.buf[n].ttype = GL_TRIANGLES\r\n\r\n # load the texture file TODO check if same as previously loaded files (for other loadModel()s)\r\n if (gTRef in model.textureList):\r\n model.buf[model.vGroup[np]].textures = [model.textureList[gTRef][\"texID\"]]\r\n model.buf[model.vGroup[np]].texFile = model.textureList[gTRef][\"filename\"]\r\n else:\r\n model.buf[model.vGroup[np]].textures = []\r\n model.buf[model.vGroup[np]].texFile = None\r\n #TODO don't create this array if texture being used but should be able to combine\r\n if (gMRef in model.materialList):\r\n redVal = float(model.materialList[gMRef][\"diffr\"])\r\n grnVal = float(model.materialList[gMRef][\"diffg\"])\r\n bluVal = float(model.materialList[gMRef][\"diffb\"])\r\n model.buf[model.vGroup[np]].material = (redVal, grnVal, bluVal, 1.0)\r\n model.buf[model.vGroup[np]].unib[3:6] = [redVal, grnVal, bluVal]\r\n\r\n else: model.buf[model.vGroup[np]].material = (0.0, 0.0, 0.0, 0.0)\r\n ####### end of groupDrill function #####################\r\n\r\n bReg = re.finditer('[{}<]', l)\r\n xx = [\"\", \"\", \"\", []]\r\n pRec(xx, bReg, l, 0)\r\n l = None #in case it's running out of memory?\r\n f.close()\r\n\r\n for x in xx[3]:\r\n if \"<Texture>\" in x[0]:\r\n model.textureList[x[1]] = {}\r\n for i in xrange(len(x[3])): model.textureList[x[1]][x[3][i][1]] = x[3][i][2]\r\n model.textureList[x[1]][\"filename\"] = x[2].strip(\"\\\"\")\r\n if VERBOSE:\r\n print(filePath, model.textureList[x[1]][\"filename\"])\r\n model.textureList[x[1]][\"texID\"] = Texture(os.path.join(filePath, model.textureList[x[1]][\"filename\"]), False, True) # load from file\r\n if \"<CoordinateSystem>\" in x[0]:\r\n model.coordinateSystem = x[2].lower()\r\n if \"<Material>\" in x[0]:\r\n model.materialList[x[1]] = {}\r\n for i in xrange(len(x[3])): model.materialList[x[1]][x[3][i][1]] = x[3][i][2]\r\n if \"<Group>\" in x[0]:\r\n groupDrill(x[3], x[1])","def deserialize(self, str):\n try:\n end = 0\n start = end\n end += 24\n self.thumb = _get_struct_3d().unpack(str[start:end])\n start = end\n end += 24\n self.index = _get_struct_3d().unpack(str[start:end])\n start = end\n end += 24\n self.middle = _get_struct_3d().unpack(str[start:end])\n start = end\n end += 24\n self.ring = _get_struct_3d().unpack(str[start:end])\n start = end\n end += 24\n self.little = _get_struct_3d().unpack(str[start:end])\n return self\n except struct.error as e:\n raise genpy.DeserializationError(e) # most likely buffer underfill","def load_glove_vectors(filename, vocab):\n dct = {}\n vectors = array.array('d')\n current_idx = 0\n with open(filename, \"r\", encoding=\"utf-8\") as f:\n for _, line in enumerate(f):\n tokens = line.split(\" \")\n word = tokens[0]\n entries = tokens[1:]\n if not vocab or word in vocab:\n dct[word] = current_idx\n vectors.extend(float(x) for x in entries)\n current_idx += 1\n word_dim = len(entries)\n num_vectors = len(dct)\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]","def fileobject_to_dict(fo):\n if fo.allocated():\n # proc = subprocess.Popen(['./extract_strings', fo.inode()], stdout=subprocess.PIPE)\n # contents = proc.stdout.read()\n return {\n 'atime_dt': epoch_to_dt(fo.atime()),\n 'compressed_b': fo.compressed(),\n 'contents_t': string.translate(fo.contents(), filter),\n 'contents_display': string.translate(fo.contents(), filter),\n 'crtime_dt': epoch_to_dt(fo.crtime()),\n 'ctime_dt': epoch_to_dt(fo.ctime()),\n 'dtime_dt': epoch_to_dt(fo.dtime()),\n 'encrypted_b': fo.encrypted(),\n 'extension_facet': fo.ext(),\n 'fileid_i': int(fo._tags['id']),\n 'filename_display': fo.filename(),\n 'filename_t': fo.filename(),\n 'filesize_l': long(fo.filesize()),\n 'fragments_i': int(fo.fragments()),\n 'gid_i': int(fo._tags['gid']),\n #'id': uuid.uuid4(),\n 'id': hashlib.sha1(os.path.basename(IMAGE) + '_' + fo.inode()).hexdigest(),\n #'imagefile': fo._tags['imagefile'],\n 'inode_i': int(fo.inode()),\n 'libmagic_display': fo.libmagic(),\n 'libmagic_facet': fo.libmagic(),\n 'md5_s': fo.md5(),\n 'meta_type_i': fo._tags['meta_type'],\n 'mode_facet': int(fo._tags['mode']),\n 'mode_i': int(fo._tags['mode']),\n 'mtime_dt': epoch_to_dt(fo.mtime()),\n 'nlink_i': fo._tags['nlink'],\n 'name_type_s': fo.name_type(),\n 'partition_i': int(fo.partition()),\n 'sha1_s': fo.sha1(),\n 'uid_i': int(fo._tags['uid']),\n 'volume_display': IMAGE,\n 'volume_facet': os.path.basename(IMAGE)\n }\n else:\n return None","def unpickle(filename: str) -> dict:\n with open(os.path.join(f\"{ROOT_DIR}/dataset/\", filename), \"rb\") as file:\n dict = pickle.load(file, encoding=\"bytes\")\n return dict","def load_bin_vec(fname, vocab):\n word_vecs = {}\n with open(fname, \"rb\") as f:\n header = f.readline()\n vocab_size, layer1_size = map(int, header.split())\n binary_len = np.dtype('float32').itemsize * layer1_size\n for line in xrange(vocab_size):\n word = []\n while True:\n ch = f.read(1)\n if ch == ' ':\n word = ''.join(word)\n break\n if ch != '\\n':\n word.append(ch) \n if word in vocab:\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32') \n else:\n f.read(binary_len)\n return word_vecs","def load_glove(self, path, vocab_size=None, dim=None, reserve_zero=True, reserve_oov_token=True):\n\n # Infer vocab size by reading number of lines\n if vocab_size is None:\n vocab_size = 0\n with open(path, 'r') as f:\n for line in f:\n vocab_size += 1\n\n # Infer vector dim by reading a single line\n if dim is None:\n with open(path, 'r') as f:\n dim = len(f.readline().split(u' ')) - 1\n\n words = []\n\n self.allow_oov = reserve_oov_token\n self.reserve_zero = reserve_zero\n\n if self.reserve_zero:\n words.append('__ZERO__')\n if self.allow_oov:\n words.append('__OUT_OF_VOCAB__')\n self.oov_index = len(words) - 1\n\n self._matrix = np.zeros((vocab_size+len(words), dim))\n # Assign random vector for OOV token if it exists\n if \"__OUT_OF_VOCAB__\" in words:\n self._matrix[self.oov_index] = np.random.randn(dim, )\n\n update = words.append # Speedup\n with open(path, 'r') as f:\n for i in tqdm(range(len(words), self.matrix.shape[0])):\n split = f.readline().split(u' ', 1)\n update(split[0])\n self._matrix[i] = np.fromstring(split[1], 'f', sep=u' ')\n\n self.vocab = words","def _load(self):\n # Extract the ASCII header (5 first lines)\n with open(self._xst_bin, 'rb') as f:\n header = list(islice(f, 0, 5))\n assert header[0] == b'HeaderStart\\n',\\\n 'Wrong header start'\n assert header[-1] == b'HeaderStop\\n',\\\n 'Wrong header stop'\n header = [s.decode('utf-8') for s in header]\n hd_size = sum([len(s) for s in header])\n\n # Parse informations into a metadata dictionnary\n keys = ['freq', 'ma', 'accu']\n search = ['Freq.List', 'Mr.List', 'accumulation']\n types = ['float64', 'int', 'int']\n for key, word, typ in zip(keys, search, types):\n for h in header:\n if word in h:\n self.meta[key] = np.array(\n h.split('=')[1].split(','),\n dtype=typ\n )\n\n # Deduce the dtype for decoding\n n_ma = self.meta['ma'].size\n n_sb = self.meta['freq'].size\n dtype = np.dtype(\n [('jd', 'float64'),\n ('data', 'complex64', (n_sb, n_ma*n_ma*2 + n_ma))]\n )\n\n # Decoding the binary file\n tmp = np.memmap(\n filename=self._xst_bin,\n dtype='int8',\n mode='r',\n offset=hd_size\n )\n decoded = tmp.view(dtype)\n\n self.data = decoded['data'] / self.meta['accu']\n self.time = Time(decoded['jd'], format='jd', precision=0)\n\n return","def __init__(self, filename=None):\n self.metgauges = {}\n self.obsgauges = {}\n if filename:\n self.read(filename)","def load_object(filepath):\n with open(filepath, 'rb') as f:\n obj = pickle.load(f)\n return obj","def read(cls, filename: str) -> Objdict:\n obj = config.read(filename)\n return cls.from_obj(obj)","def readGBK(filename):\r\n gnome_record = SeqIO.read(filename, \"genbank\")\r\n return gnome_record","def load_bin_vec(self, fname, vocab):\n word_vecs = {}\n with open(fname, \"rb\") as f:\n header = f.readline()\n print header\n vocab_size, layer1_size = map(int, header.split())\n binary_len = np.dtype('float32').itemsize * layer1_size\n for line in xrange(vocab_size):\n word = []\n while True:\n ch = f.read(1)\n if ch == ' ':\n word = ''.join(word)\n break\n if ch != '\\n':\n word.append(ch)\n if word in vocab:\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32')\n # logger.info(word_vecs[word])\n else:\n f.read(binary_len)\n # logger.info(\"num words already in word2vec: \" + str(len(word_vecs)))\n return word_vecs","def from_dict(cls, dikt) -> 'ImageData':\n return util.deserialize_model(dikt, cls)","def load_bin_vec(fname, vocab):\n word_vecs = {}\n with open(fname, \"rb\") as f:\n header = f.readline()\n vocab_size, layer1_size = map(int, header.split())\n binary_len = np.dtype('float32').itemsize * layer1_size\n for line in xrange(vocab_size):\n word = []\n while True:\n ch = f.read(1)\n if ch == ' ':\n word = ''.join(word).lower()\n break\n if ch != '\\n':\n word.append(ch) \n if word in vocab:\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32') \n else:\n f.read(binary_len)\n return word_vecs","def deserialize(self, str):\n try:\n end = 0\n _x = self\n start = end\n end += 100\n (_x.id, _x.age, _x.velocidad_relativa_x, _x.velocidad_relativa_y, _x.velocidad_absoluta_x, _x.velocidad_absoluta_y, _x.velocidad_absoluta_sigma_x, _x.velocidad_absoluta_sigma_y, _x.bounding_box_centro_x, _x.bounding_box_centro_y, _x.bounding_box_largo, _x.bounding_box_ancho, _x.object_box_centro_x, _x.object_box_centro_y, _x.object_box_orientacion, _x.object_box_size_x, _x.object_box_size_y, _x.clasificacion, _x.clasificacion_age, _x.clasificacion_certeza, _x.punto_cercano_x, _x.punto_cercano_y, _x.punto_referencia_x, _x.punto_referencia_y, _x.punto_referencia_sigma_x, _x.punto_referencia_sigma_y,) = _get_struct_h16fh8f().unpack(str[start:end])\n return self\n except struct.error as e:\n raise genpy.DeserializationError(e) #most likely buffer underfill","def load_dictionary(cls, args, filename, source=True):\n dictionary = Dictionary.load(filename)\n dictionary.add_symbol(\"<mask>\")\n return dictionary","def load_model(self, **params):\n \t# file_name = params['name']\n # return pickle.load(gzip.open(file_name, 'rb'))","def from_genbank(cls, filename):\n\t\tseq_record = SeqIO.read(filename, 'genbank')\n\t\trec = cls(seq_record=seq_record)\n\t\treturn rec","def glove(data_fname='glove.840B.300d.txt', out_fname='glove.pkl'):\n words, U, dim = [], [], None\n with open(DATA_DIR + data_fname, 'rb') as f:\n for j, line in enumerate(f):\n x = line.strip().split()\n word, vector, d = x[0], np.ravel(x[1:]), len(x) - 1\n if dim is None: dim = d\n elif d != dim: raise Exception('{0}: {1}!={2}'.format(j, dim, d))\n U.append(vector)\n words.append(word)\n U = np.array(U)\n print \"Found {0} words\".format(len(words))\n print \"Found {0}x{1} embedding matrix\".format(*U.shape)\n with open(DATA_DIR + out_fname, 'wb') as f:\n cPickle.dump((words, U), f)","def load_word2vec(self, path, binary=True, reserve_zero=True, reserve_oov_token=True):\n self.allow_oov = reserve_oov_token\n self.reserve_zero = reserve_zero\n words = []\n if self.reserve_zero:\n words.append('__ZERO__')\n if self.allow_oov:\n words.append('__OUT_OF_VOCAB__')\n self.oov_index = len(words) - 1\n\n if binary:\n with open(path, 'rb') as f:\n # Get number of vectors and vector size\n # from first line\n num_vectors, vector_size = map(\n int, f.readline().decode('UTF-8').split())\n FLOAT_SIZE = 4\n\n self._matrix = np.zeros(\n [num_vectors + len(words), vector_size], dtype='float32')\n # Assign random vector for OOV token if it exists\n if self.allow_oov:\n self._matrix[self.oov_index] = np.random.randn(vector_size, )\n\n update = words.append # Speedup\n for i in tqdm(range(len(words), num_vectors+len(words))):\n # Reads until a whitespace is found (get a word)\n word = b\"\"\n while True:\n char = f.read(1)\n if char == b\" \":\n break\n word += char\n update(word)\n #Read vector\n vecs = f.read(FLOAT_SIZE * vector_size)\n self._matrix[i] = np.frombuffer(vecs, 'f')\n\n self.vocab = words\n else:\n print(\"This feature is yet to be implemented\")","def load_bin_vec(fname, vocab):\n word_vecs = {}\n with open(fname, \"rb\") as f:\n header = f.readline()\n vocab_size, layer1_size = map(int, header.split())\n binary_len = np.dtype('float32').itemsize * layer1_size\n for line in xrange(vocab_size):\n word = []\n while True:\n ch = f.read(1)\n if ch == ' ':\n word = ''.join(word)\n break\n if ch != '\\n':\n word.append(ch) \n if word in vocab:\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32') \n else:\n f.read(binary_len)\n return word_vecs","def load_bin_vec(fname, vocab):\n word_vecs = {}\n with open(fname, \"rb\") as f:\n header = f.readline()\n vocab_size, layer1_size = map(int, header.split())\n binary_len = np.dtype('float32').itemsize * layer1_size\n for line in xrange(vocab_size):\n word = []\n while True:\n ch = f.read(1)\n if ch == ' ':\n word = ''.join(word)\n break\n if ch != '\\n':\n word.append(ch) \n if word in vocab:\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32') \n else:\n f.read(binary_len)\n return word_vecs","def decode(binary):\n name, fields = JsonCoder.decode(binary)\n dataclass = dataclasses.make_dataclass(\n name, [(key, type(value)) for key, value in fields.items()]\n )\n instance = dataclass(**fields)\n return instance","def deserialize_model_pickle(filename):\n from sst import shape\n sys.modules['shape'] = shape\n with open(filename, 'rb') as handle:\n to_pickle = pickle.load(handle)\n return to_pickle"],"string":"[\n \"def build_from_file(path):\\n with open(path) as obj:\\n raw_file = obj.read()\\n file_lines = [line.split(\\\" \\\") for line in raw_file.split(\\\"\\\\n\\\")]\\n\\n vertices = {}\\n faces = []\\n for number, line in enumerate(file_lines):\\n if line[0] == \\\"v\\\":\\n vertices[number + 1] = tuple(map(float, line[1:]))\\n if line[0] == \\\"f\\\":\\n face = []\\n for index in line[1:]:\\n face.append(vertices[int(index)])\\n face.append(vertices[int(line[1])])\\n faces.append(face)\\n return Object(points=faces)\",\n \"def load_glove(path):\\n with open(path) as f:\\n glove = {}\\n for line in f.readlines():\\n values = line.split()\\n word = values[0]\\n vector = np.array(values[1:], dtype='float32')\\n glove[word] = vector\\n return glove\",\n \"def load_glove(path):\\n with open(path) as f:\\n glove = {}\\n for line in f.readlines():\\n values = line.split()\\n word = values[0]\\n vector = np.array(values[1:], dtype='float32')\\n glove[word] = vector\\n return glove\",\n \"def load_dict(path_to_vec):\\n emb = {}\\n with open(path_to_vec, 'r', errors='ignore', encoding='utf8') as f:\\n for line in f:\\n values = line.split()\\n word = values[0]\\n vector = np.asarray(values[1:], \\\"float32\\\")\\n emb[word] = vector\\n return emb\",\n \"def readInstance(self):\\n file = open(self.fName, 'r')\\n self.genSize = int(file.readline())\\n self.data = {}\\n for line in file:\\n (id, x, y) = line.split()\\n self.data[int(id)] = (int(x), int(y))\\n file.close()\",\n \"def load_glove_data():\\n glove_path = path.join('..', 'data', 'glove', 'glove.twitter.27B.200d.txt')\\n f = open(glove_path,'r')\\n \\n model = {}\\n for line in f:\\n splitLine = line.split()\\n word = splitLine[0]\\n embedding = np.array([float(val) for val in splitLine[1:]])\\n model[word] = embedding\\n \\n return model\",\n \"def read_pkl(infile):\\n # loading\\n if infile is not None:\\n logging.info('No pkl provided. Creating a new object')\\n pkl = pickle.load(bz2.open(infile, 'r'))\\n else:\\n logging.info('Reading in: {}'.format(infile))\\n # creating new object\\n pkl = {'taxonomy' : {}, 'markers' : {}}\\n return pkl\",\n \"def load(filename):\\n file = gzip.GzipFile(filename, 'rb')\\n object = cPickle.load(file)\\n file.close()\\n return object\",\n \"def load_viz_object(filename: str) -> OrqVizObject:\\n\\n with open(filename, \\\"rb\\\") as f:\\n loaded_object = pickle.load(f)\\n\\n return loaded_object\",\n \"def load(filename):\\n file = gzip.GzipFile(filename, 'rb')\\n buffer = \\\"\\\"\\n while 1:\\n data = file.read()\\n if data == \\\"\\\":\\n break\\n buffer += data\\n object = pickle.loads(buffer)\\n file.close()\\n return object\",\n \"def load(filename):\\n file = gzip.GzipFile(filename, 'rb')\\n buffer = \\\"\\\"\\n while True:\\n data = file.read()\\n if data == \\\"\\\":\\n break\\n buffer += data\\n object = pickle.loads(buffer)\\n file.close()\\n return object\",\n \"def load_from_file(self, filename):\\n # clear datastore mape\\n self._datastoreMap = {}\\n # citanje filea\\n with open(filename, 'rb') as f:\\n binstr = f.read()\\n inMap = pickle.loads(binstr)\\n # za svaki kanal moramo dodati element u _datastoreMap\\n for kanal in inMap:\\n # stvaramo instancu Datastore\\n self._datastoreMap[kanal] = DataStore()\\n # instanca Datastore zna se otpakirati iz mape (dictionary)\\n self._datastoreMap[kanal].dict2store(inMap[kanal])\",\n \"def load_fragGC_pickle(inFH):\\n fojb = pickle.load(inFH)\\n\\n d = dict()\\n for x in fojb:\\n taxon_name = x[0]\\n d[taxon_name] = dict()\\n d[taxon_name]['fragLength'] = []\\n d[taxon_name]['fragGC'] = []\\n \\n for scaf,v in x[1].items(): \\n for z in v:\\n # fragStart, fragLength, fragGC\\n d[taxon_name]['fragLength'].append(z[1])\\n d[taxon_name]['fragGC'].append(z[2]) \\n return d\",\n \"def load_obj(file, **kwargs):\\n v = []\\n vt = []\\n vn = []\\n f = []\\n for line in file:\\n if line.startswith(\\\"v \\\"):\\n v.append([float(x) for x in line[2:].split()])\\n elif line.startswith(\\\"vt \\\"):\\n vt.append([float(x) for x in line[3:].split()])\\n elif line.startswith(\\\"vn \\\"):\\n vn.append([float(x) for x in line[3:].split()])\\n elif line.startswith(\\\"f \\\"):\\n f.append([[int(x) for x in fv.split('/')] for fv in line[2:].split()])\\n\\n # now produce the full buffers\\n f = np.array(f, dtype='i4')\\n f[f > 0] -= 1\\n v = np.array(v, dtype='f4')[f[:, :, 0].ravel()]\\n vt = np.array(vt, dtype='f4')[f[:, :, 1].ravel()]\\n vn = np.array(vn, dtype='f4')[f[:, :, 2].ravel()]\\n\\n # NOTE: we could identify unique vertices in f and shave off memory requirements. we could.\\n\\n return Geometry({'pos': v, 'uv': vt, 'normal': vn}, primitive=Primitives.TRIANGLES, **kwargs)\",\n \"def load_dictionary(filepath):\\r\\n # context manager read binary\\r\\n with open(filepath, 'rb') as file:\\r\\n # pickle load\\r\\n return pickle.load(file)\",\n \"def load(filename):\\n file = gzip.GzipFile(filename, 'rb')\\n buffer = \\\"\\\"\\n while True:\\n data = file.read()\\n if data == \\\"\\\":\\n break\\n buffer += data\\n object = pickle.loads(buffer)\\n file.close()\\n return object\",\n \"def __init__(self, path, bigendian=False, use_mmap=None):\\n self.rd = DictReader(path, bigendian, use_mmap)\\n with self.rd as r:\\n node_size = r.get_int()\\n tind_size = r.get_int()\\n tail_size = r.get_int()\\n self.num_keys = tind_size\\n self.begs = r.get_intarray(tind_size)\\n self.base = r.get_intarray(node_size)\\n self.lens = r.get_shortarray(tind_size)\\n self.chck = r.get_chararray(node_size)\\n self.tail = r.get_chararray(tail_size)\",\n \"def load_object(filename):\\n\\n with gzip.GzipFile(filename, 'rb') as source: result = source.read()\\n ret = pickle.loads(result)\\n source.close()\\n\\n return ret\",\n \"def load_pkl(self, name, file_object=None):\\n if file_object:\\n f = file_object\\n else:\\n f = gzip.open(name, 'rb')\\n temp = pickle.load(f)\\n if temp.ht_version < HT_OLD_COMPAT_VERSION:\\n raise ValueError('Version of ' + name + ' is ' + str(temp.ht_version)\\n + ' which is not at least ' +\\n str(HT_OLD_COMPAT_VERSION))\\n # assert temp.ht_version >= HT_COMPAT_VERSION\\n params = temp.params\\n self.hashbits = temp.hashbits\\n self.depth = temp.depth\\n if hasattr(temp, 'maxtimebits'):\\n self.maxtimebits = temp.maxtimebits\\n else:\\n self.maxtimebits = _bitsfor(temp.maxtime)\\n if temp.ht_version < HT_COMPAT_VERSION:\\n # Need to upgrade the database.\\n print(\\\"Loading database version\\\", temp.ht_version,\\n \\\"in compatibility mode.\\\")\\n # Offset all the nonzero bins with one ID count.\\n temp.table += np.array(1 << self.maxtimebits).astype(np.uint32) * (\\n temp.table != 0)\\n temp.ht_version = HT_VERSION\\n self.table = temp.table\\n self.ht_version = temp.ht_version\\n self.counts = temp.counts\\n self.names = temp.names\\n self.hashesperid = np.array(temp.hashesperid).astype(np.uint32)\\n self.dirty = False\\n self.params = params\",\n \"def createGloveDic():\\n saveGloveDicIntoFile(_extractGloveVects())\",\n \"def load_bin_vec(filename):\\n w2v = {}\\n with open(filename, 'r') as f:\\n header = f.readline()\\n vocab_size, emb_size = map(int, header.split())\\n for line in f:\\n cline = line.split()\\n w2v[cline[0]] = np.array(cline[1:], dtype=np.float64)\\n return w2v, emb_size, vocab_size\",\n \"def load(path: str) -> \\\"DataDescriptor\\\":\\n\\n\\t\\twith open(path, \\\"r\\\") as f:\\n\\t\\t\\tinfo_dict = json.load(f)\\n\\n\\t\\treturn DataDescriptor(\\n\\t\\t\\tn_gram_size=int(info_dict[\\\"n_gram_size\\\"]),\\n\\t\\t\\tcaseless=bool(info_dict[\\\"caseless\\\"]),\\n\\t\\t\\tignore_punctuation=bool(info_dict[\\\"ignore_punctuation\\\"]),\\n\\t\\t\\tadd_pos_tags=bool(info_dict[\\\"add_pos_tags\\\"]),\\n\\t\\t\\tuses_lemma=bool(info_dict[\\\"uses_lemma\\\"]),\\n\\t\\t\\tuses_sentences=bool(info_dict[\\\"uses_sentences\\\"])\\n\\t\\t)\",\n \"def load(npz):\\n e = np.load(npz, allow_pickle=True)\\n return EOMap(\\n e['dataStore'],\\n e['etas'],\\n e['etaEdges'],\\n e['omegas'],\\n e['omeEdges'],\\n e['iHKLList'],\\n plane_data(e)\\n )\",\n \"def load_dictionary(filename):\\n filename = os.path.join(FILE_DIR, 'assets/obj/' + filename)\\n try:\\n with open(filename, 'rb') as input:\\n return pickle.load(input)\\n except Exception as e:\\n print(\\\"exception\\\", e)\",\n \"def file_to_dictionary():\\n\\n return;\",\n \"def load_object(self, filename):\\n with open(filename, 'rb') as inp: # Overwrites any existing file.\\n data = pickle.load(inp)\\n return data\",\n \"def load_glove_vec(fname):\\n word_vecs = {}\\n length = 0\\n with open(fname, \\\"rb\\\") as f:\\n for i, line in enumerate(f):\\n L = line.split()\\n word = L[0].lower()\\n word_vecs[word] = np.array(L[1:], dtype='float32')\\n if length == 0:\\n length = len(word_vecs[word])\\n return word_vecs, length\",\n \"def load(filename):\\n return GesFile(filename)\",\n \"def construct_dict(self):\\n i = 0\\n self.word2idx = dict()\\n fi = open(self.config.word_vec_fi_glove, 'r')\\n\\n for line in fi:\\n self.word2idx[line.split(\\\" \\\")[0]] = i\\n i += 1\\n\\n self.vocab_size = i\\n self.write_dict()\\n fi.close()\",\n \"def loadGLOVE(filename, vocab):\\n dct = {}\\n vectors = array.array('d')\\n current_idx = 0\\n with codecs.open(filename, \\\"r\\\", encoding=\\\"utf-8\\\") as f:\\n for _, line in enumerate(f):\\n tokens = line.split(\\\" \\\")\\n word = tokens[0]\\n entries = tokens[1:]\\n if not vocab or word in vocab:\\n dct[word] = current_idx\\n vectors.extend(float(x) for x in entries)\\n current_idx += 1\\n word_dim = len(entries)\\n num_vectors = len(dct)\\n tf.logging.info(\\\"Found {} out of {} vectors in Glove\\\".format(num_vectors, len(vocab)))\\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]\",\n \"def from_dict(cls, dikt) -> 'DataFileFormat':\\n return util.deserialize_model(dikt, cls)\",\n \"def __init__(self, file):\\n with open(file, 'r') as f:\\n self.vocab = json.loads(f.read())\",\n \"def load_mb_obj(in_file):\\n\\n mth = 0\\n metaballs = []\\n vertices = []\\n vcolors = []\\n vnormals = []\\n faces = []\\n\\n if in_file.endswith(\\\".gz\\\"):\\n f_in = gzip.open(in_file, 'rt')\\n else:\\n f_in = open(in_file, 'r')\\n\\n for line in f_in:\\n vals = line.split()\\n\\n if len(vals) == 0:\\n continue\\n\\n if vals[0] == \\\"#\\\":\\n if (len(vals) > 2):\\n if vals[1] == \\\"mth\\\":\\n mth = float(vals[2])\\n\\n if vals[1] == \\\"mb\\\":\\n mb = Metaball(float(vals[2]),\\n float(vals[3]),\\n float(vals[4]),\\n float(vals[5]),\\n float(vals[6]))\\n metaballs.append(mb)\\n\\n if vals[0] == \\\"v\\\":\\n v = [float(x) for x in vals[1:4]]\\n vertices.append(v)\\n\\n if len(vals) == 7:\\n vc = [float(x) for x in vals[4:7]]\\n vcolors.append(vc)\\n\\n if vals[0] == \\\"vn\\\":\\n vn = [float(x) for x in vals[1:4]]\\n vnormals.append(vn)\\n\\n if vals[0] == \\\"f\\\":\\n fvi = []\\n\\n for f in vals[1:]:\\n w = f.split(\\\"/\\\")\\n fvi.append(int(w[0]) - 1)\\n\\n faces.append(fvi)\\n\\n f_in.close()\\n\\n print(\\\"load \\\"+in_file+\\\": {:d} cells\\\".format(len(vertices)))\\n\\n return (Metaballs(metaballs, mth),\\n np.array(vertices),\\n np.array(vcolors),\\n np.array(vnormals),\\n np.array(faces))\",\n \"def load(cls, file: str):\\n\\n bfh = cls()\\n\\n with open(file, 'br') as sgy:\\n # get the endian\\n endian = gfunc.grab_endiannes(sgy)\\n\\n # skip the TFH, read the BFH bytes\\n sgy.seek(3200)\\n raw = sgy.read(400)\\n\\n # unpack and store the values\\n values = struct.unpack(endian + const.BFHFS, raw)\\n bfh._dict = dict(zip(const.BFHCOLS, values))\\n\\n return bfh\",\n \"def load_skeleton(skel_file) -> Dict:\\n with open(skel_file, 'rb') as handle:\\n skel_dict = pickle.load(handle)\\n\\n return skel_dict\",\n \"async def load(self, file: IO) -> dict:\",\n \"def load_data(filename):\\r\\n with open(filename,'rb') as f:\\r\\n data = pk.load(f,encoding='bytes')\\r\\n return data[b'data'],data[b'labels']\",\n \"def load (cls, file):\\n with open(file) as f:\\n raw = json.load(f)\\n obj = PasswordSetCharacteristics()\\n obj.lengths = cls.to_num_dict(raw['lengths'])\\n obj.lower_counts = cls.to_num_dict(raw['lowerCounts'])\\n obj.upper_counts = cls.to_num_dict(raw['upperCounts'])\\n obj.digit_counts = cls.to_num_dict(raw['digitCounts'])\\n obj.symbol_counts = cls.to_num_dict(raw['symbolCounts'])\\n obj.class_counts = cls.to_num_dict(raw['classCounts'])\\n obj.word_counts = cls.to_num_dict(raw['wordCounts'])\\n return obj\",\n \"def from_file(cls, file_obj):\\n kdm = cls(file_obj.read())\\n return kdm\",\n \"def unpickle(file):\\r\\n\\timport cPickle\\r\\n\\tfo = open(file, 'rb')\\r\\n\\tdict = cPickle.load(fo)\\r\\n\\tfo.close()\\r\\n\\treturn dict\",\n \"def load(cls, filename):\\n return cPickle.load(open(filename, \\\"rb\\\"))\",\n \"def load_object(filename):\\r\\n with open(filename, 'rb') as input:\\r\\n obj = pickle.load(input)\\r\\n return obj\",\n \"def binary_to_dictionary(\\n binary: bytes,\\n filename: str | None = None\\n) -> 'FileDict':\\n\\n assert isinstance(binary, bytes)\\n\\n mimetype = magic.from_buffer(binary, mime=True)\\n\\n # according to https://tools.ietf.org/html/rfc7111, text/csv should be used\\n if mimetype == 'application/csv':\\n mimetype = 'text/csv'\\n\\n gzipdata = BytesIO()\\n\\n with gzip.GzipFile(fileobj=gzipdata, mode='wb') as f:\\n f.write(binary)\\n\\n return {\\n 'data': base64.b64encode(gzipdata.getvalue()).decode('ascii'),\\n 'filename': filename,\\n 'mimetype': mimetype,\\n 'size': len(binary)\\n }\",\n \"def load_glove(file_path: str, return_embedding_size: bool=False) ->Dict[str, np.ndarray]:\\n logger.info(f' Loading Glove format file {file_path}')\\n embeddings = {}\\n embedding_size = 0\\n with open_file(file_path, 'r', encoding='utf-8') as f:\\n found_line = False\\n while not found_line:\\n line = f.readline()\\n if line:\\n embedding_size = len(line.split()) - 1\\n found_line = True\\n with open_file(file_path, 'r', encoding='utf-8') as f:\\n for line_number, line in enumerate(f):\\n if line:\\n try:\\n split = line.split()\\n if len(split) != embedding_size + 1:\\n raise ValueError(f'Line {line_number} is of length {len(split)}, while expected length is {embedding_size + 1}.')\\n word = split[0]\\n embedding = np.array([float(val) for val in split[-embedding_size:]])\\n embeddings[word] = embedding\\n except ValueError:\\n logger.warning('Line {} in the GloVe file {} is malformed, skipping it'.format(line_number, file_path))\\n logger.info(f' {len(embeddings)} embeddings loaded')\\n if return_embedding_size:\\n return embeddings, embedding_size\\n return embeddings\",\n \"def readobject(filename):\\n # import cPickle as pickle\\n with open(filename, 'rb') as input_file:\\n return pickle.load(input_file)\",\n \"def load_glove_vec(fname, vocab):\\n word_vecs = {}\\n with open(fname, \\\"rb\\\") as f:\\n for i,line in enumerate(f):\\n L = line.split()\\n word = L[0].lower()\\n if word in vocab:\\n word_vecs[word] = np.array(L[1:], dtype='float32')\\n return word_vecs\",\n \"def _read(self):\\n # initializng data dictionary\\n self.data={}\\n\\n f = FortranFile(self.filename)\\n # Default omnivor binary header\\n self.data['MK'] = f.readInts('i')\\n self.data['itime'] = f.readInts('i')\\n self.data['version'] = f.readString()\\n self.data['file_id'] = f.readInts('i')\\n self.data['sversion'] = f.readString()\\n # Velocity field\\n self.data['stype'] = f.readString()\\n self.data['is_grid'] = f.readInts('i')\\n nCPs = f.readInts('i')\\n self.data['nCPs'] = nCPs\\n if self.data['MK'] == 8:\\n real_char='d'\\n else:\\n real_char='f'\\n if self.data['is_grid']:\\n #print('File is a velocity grid file')\\n n1 = f.readInts('i')\\n n2 = f.readInts('i')\\n n3 = f.readInts('i')\\n self.data['n1'] = n1\\n self.data['n2'] = n2\\n self.data['n3'] = n3\\n self.data['is_straight'] = f.readInts('i')\\n self.data['v1'] = f.readReals(real_char)\\n self.data['v2'] = f.readReals(real_char)\\n self.data['v3'] = f.readReals(real_char)\\n\\n CPs_raw = f.readReals(real_char)\\n Utot_raw = f.readReals(real_char)\\n CPs = np.reshape(CPs_raw,(3,nCPs),order = 'F')\\n Utot = np.reshape(Utot_raw,(3,nCPs),order = 'F')\\n\\n acc=-1\\n CPsTab = np.zeros((3, n1,n2,n3))\\n UtotTab = np.zeros((3, n1,n2,n3))\\n # Reshaping the nasty way (this is natural order). \\n for i in range(0,n1):\\n for j in range(0,n2):\\n for k in range(0,n3):\\n acc=acc+1\\n CPsTab[0:3,i,j,k] = CPs[0:3,acc]\\n UtotTab[0:3,i,j,k] = Utot[0:3,acc]\\n\\n self.data['CPs'] = CPs\\n self.data['CPsTab'] = CPsTab\\n self.data['Utot'] = Utot\\n self.data['UtotTab'] = UtotTab\",\n \"def unpickle(self, file):\\n import pickle\\n with open(file, 'rb') as fo:\\n dict = pickle.load(fo, encoding='bytes')\\n return dict\",\n \"def load_data(filename) :\\r\\n data = Data()\\r\\n data.load(filename)\\r\\n return data\",\n \"def load(self, path='dict.pic'):\\n with open(path, 'rb') as f:\\n self.__dictionary = pickle.load(f)\\n self.__vocab_size = len(self.__dictionary)\\n\\n if self.__verbose:\\n print('Loading Tokenizer, vocab size:', self.vocab_size())\",\n \"def load_bin_vec(fname, vocab):\\n word_vecs = {}\\n with open(fname, \\\"rb\\\") as f:\\n header = f.readline()\\n vocab_size, layer1_size = map(int, header.split())\\n binary_len = np.dtype('float32').itemsize * layer1_size\\n for line in xrange(vocab_size):\\n word = []\\n while True:\\n ch = f.read(1)\\n if ch == ' ':\\n word = ''.join(word)\\n break\\n if ch != '\\\\n':\\n word.append(ch)\\n if word in vocab:\\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32') \\n else:\\n f.read(binary_len)\\n cPickle.dump(word_vecs, open(\\\"./data/word_vecs.pkl\\\", \\\"w\\\"))\\n return word_vecs\",\n \"def create_from_file(filename: str):\\n if not os.path.isfile(filename):\\n raise FileNotFoundError(\\\"Failed to find GeneSet file \\\" + filename)\\n\\n with open(filename, \\\"rb\\\") as binary_reader:\\n (gene_sets, gene_set_size, gene_set_names, interactors, n_curated, n_interactors) = \\\\\\n pickle.load(binary_reader)\\n\\n gene_set = GeneSet(dict())\\n gene_set.gene_sets = gene_sets\\n gene_set.gene_set_size = gene_set_size\\n gene_set.gene_set_names = gene_set_names\\n gene_set.interactors = interactors\\n gene_set.n_curated = n_curated\\n gene_set.n_interactors = n_interactors\\n\\n return gene_set\",\n \"def load(cls, filepath) -> 'Word2VecEmbedding':\\n with open(filepath, 'rb') as f:\\n embedding = pickle.load(f)\\n embedding.word2idx = {spell: idx for idx, spell in enumerate(embedding.vocab.idx2word)}\\n return embedding\",\n \"def load_object(filename):\\n with open(filename, 'rb') as input_file: # Overwrites any existing file.\\n obj = pickle.load(input_file)\\n return obj\",\n \"def get_glove_embedding():\\n embedding = {}\\n N = 400_000\\n print(\\\"Reading glove embedding...\\\")\\n with open(GLOVE_EMBD_PATH, \\\"rb\\\") as f:\\n for line in tqdm(f, total=N):\\n line = line.decode().split()\\n word = line[0].lower()\\n vector = np.array(line[1:]).astype(np.float32)\\n embedding[word] = vector\\n\\n return embedding\",\n \"def load_vector_dictionary():\\n return read_word2vecs_from_file(VECTOR_FILE)\",\n \"def load_glb(self):\\n with open(str(self.path), \\\"rb\\\") as fd:\\n # Check header\\n magic = fd.read(4)\\n if magic != GLTF_MAGIC_HEADER:\\n raise ValueError(\\n \\\"{} has incorrect header {} != {}\\\".format(\\n self.path, magic, GLTF_MAGIC_HEADER\\n )\\n )\\n\\n version = struct.unpack(\\\"<I\\\", fd.read(4))[0]\\n if version != 2:\\n raise ValueError(\\n \\\"{} has unsupported version {}\\\".format(self.path, version)\\n )\\n\\n # Total file size including headers\\n _ = struct.unpack(\\\"<I\\\", fd.read(4))[0] # noqa\\n\\n # Chunk 0 - json\\n chunk_0_length = struct.unpack(\\\"<I\\\", fd.read(4))[0]\\n chunk_0_type = fd.read(4)\\n if chunk_0_type != b\\\"JSON\\\":\\n raise ValueError(\\n \\\"Expected JSON chunk, not {} in file {}\\\".format(\\n chunk_0_type, self.path\\n )\\n )\\n\\n json_meta = fd.read(chunk_0_length).decode()\\n\\n # chunk 1 - binary buffer\\n chunk_1_length = struct.unpack(\\\"<I\\\", fd.read(4))[0]\\n chunk_1_type = fd.read(4)\\n if chunk_1_type != b\\\"BIN\\\\x00\\\":\\n raise ValueError(\\n \\\"Expected BIN chunk, not {} in file {}\\\".format(\\n chunk_1_type, self.path\\n )\\n )\\n\\n self.gltf = GLTFMeta(\\n self.path,\\n json.loads(json_meta),\\n self.meta,\\n binary_buffer=fd.read(chunk_1_length),\\n )\",\n \"def getFlightDict():\\n\\n dictionary = {}\\n f = open(filename3,'rb') \\n\\n dictionary = pickle.load(f)\\n f.close()\\n return dictionary\",\n \"def readSoft2Dict(softFileName,index=11):\\n import gzip\\n probe2Entrez = {}\\n Flag = False\\n if softFileName[-2:] == \\\"gz\\\":\\n softHandle = gzip.open(softFileName,\\\"rt\\\")\\n else:\\n softHandle = open(softFileName,\\\"r\\\")\\n softMatrix = softHandle.readlines()\\n for line in softMatrix:\\n line = line.split(\\\"\\\\t\\\")\\n #if len(line[0]) <5 :\\n # print(line[0].lower())\\n if len(line) <= index:\\n continue\\n if Flag:\\n #print(line)\\n if line[0] in probe2Entrez.keys():\\n probe2Entrez[line[0]].append(line)\\n else:\\n probe2Entrez[line[0]] = [line]\\n if line[0].lower() == 'id':\\n Flag = True\\n multipleKeyList = []\\n for key in probe2Entrez: #discard probs refer to multiple genes\\n if len(probe2Entrez[key]) > 1:\\n multipleKeyList.append(key)\\n for key in multipleKeyList: #can't del keys of dictionary when iterating it\\n del probe2Entrez[key]\\n return probe2Entrez\",\n \"def unpickle(file):\\n\\timport pickle\\n\\twith open(file, 'rb') as fo:\\n\\t dict = pickle.load(fo, encoding='bytes')\\n\\treturn dict\",\n \"def init_from_obj_file(cls, f, scale=1, density=1):\\n lines = [line.strip() for line in f.readlines()]\\n vertices = []\\n indexes = []\\n for line in lines:\\n if line.startswith(\\\"v\\\"): # vertex\\n nums = list(map(float, string_to_list(line[2:])))\\n vertices.append(scale * np.array(nums[:3]))\\n # x.append(nums[0] * scale)\\n # y.append(nums[1] * scale)\\n # z.append(nums[2] * scale)\\n elif line.startswith(\\\"f\\\"): # face\\n nums = list(map(lambda a: int(a) - 1, string_to_list(line[2:])))\\n indexes.append(nums)\\n return cls(vertices, indexes, density)\",\n \"def from_file(filename, decomposer=None, rx=None, ax=None):\\n from six.moves.cPickle import load\\n with open(filename, 'rb') as f:\\n data = load(f)\\n return SOAPVector.from_dict(data, decomposer, rx, ax)\",\n \"def load_object(path):\\r\\n with open(path,\\\"rb\\\") as f:\\r\\n object = pickle.load(f) \\r\\n return object\",\n \"def _load_glove_vec(fname, vocab):\\n print 'load glove...'\\n word_vecs = {}\\n cnt = 0\\n l = open(fname,'r').readline()\\n embedding_size = len(l.strip().split()) -1\\n print 'embedding vector size: %d'%(embedding_size)\\n with open(fname, \\\"r\\\") as f:\\n for l in f:\\n stemp = l.strip().split(' ',1)\\n assert len(stemp) == 2\\n word = stemp[0]\\n if word in vocab:\\n word_vecs[stemp[0]] = np.fromstring(' '.join(stemp[1:]),sep = ' ')\\n cnt+=1\\n if cnt%10000==0:\\n print '%d lines...'%cnt\\n return (word_vecs,embedding_size)\",\n \"def from_dict(cls, dikt) -> 'Garage':\\n return util.deserialize_model(dikt, cls)\",\n \"def load_bin_vec(fname, vocab):\\n word_vecs = {}\\n with open(fname, \\\"rb\\\") as f:\\n header = f.readline()\\n vocab_size, layer1_size = map(int, header.split())\\n binary_len = np.dtype('float32').itemsize * layer1_size\\n # print(vocab_size)\\n for line in range(vocab_size):\\n # print(line)\\n word = []\\n while True:\\n ch = f.read(1)\\n if ch == ' ':\\n word = ''.join(word)\\n break\\n if ch != '\\\\n':\\n word.append(ch)\\n # print(word)\\n if word in vocab:\\n # print(word)\\n word_vecs[word] = np.frombuffer(f.read(binary_len), dtype='float32')\\n else:\\n f.read(binary_len)\\n\\n return word_vecs\",\n \"def load_gensim_dictionary_model(path_to_gensim_dictionary_model):\\n dct = Dictionary.load(path_to_gensim_dictionary_model)\\n return dct\",\n \"def load_binary_data(self, encoding='utf8'):\\n\\n # TODO use smart_open again when https://github.com/RaRe-Technologies/smart_open/issues/207 will be fixed\\n with open(self.file_name, 'rb') as f:\\n self.load_model_params(f)\\n self.load_dict(f, encoding=encoding)\\n self.load_vectors(f)\",\n \"def load(cls,filename):\\n obj = None\\n f = open(filename,'r')\\n try:\\n obj = pickle.load(f)\\n obj.filename = filename\\n finally:\\n f.close()\\n return obj\",\n \"def load(self, filename = 'array_zest', path = '/home/eric/dev/insitu/data/zs_recovery/'):\\n lpath_filename = path + filename + '.pkl'\\n f = open(lpath_filename, 'rb')\\n tmp_dict = pickle.load(f)\\n f.close()\\n self.__dict__.update(tmp_dict)\",\n \"def load_POD(POD_file):\\n if not os.path.isfile(POD_file):\\n raise RuntimeError('POD file specified is not a valid file')\\n\\n # Load data from file\\n print('Loading POD data from {}'.format(POD_file))\\n POD_data = scutils.load_data(POD_file)\\n\\n # Generate POD object\\n rom = POD(POD_data['POD_info'])\\n\\n return rom\",\n \"def load_gltf(self):\\n with open(str(self.path)) as fd:\\n self.gltf = GLTFMeta(self.path, json.load(fd), self.meta)\",\n \"def load_obj(path):\\n with open(path, 'rb') as f:\\n return pickle.load(f)\",\n \"def load_object(fpath):\\r\\n with open(fpath, 'rb') as i:\\r\\n return pickle.load(i)\",\n \"def from_file( cls, filename ):\\n with open( filename, 'r' ) as stream:\\n data = yaml.load( stream )\\n notes = data.get( 'notes' )\\n type = data.get( 'type' )\\n vaspmeta = VASPMeta( data['title'], \\n data['description'], \\n data['status'], \\n notes=notes, \\n type=type )\\n return vaspmeta\",\n \"def loadFileEGG(model, fileName):\\r\\n model.coordinateSystem = \\\"Y-up\\\"\\r\\n model.materialList = {}\\r\\n model.textureList = {}\\r\\n model.vertexGroupList = {}\\r\\n model.vertexList = []\\r\\n model.polygonList = []\\r\\n model.childModelList = []\\r\\n model.parentModel = None\\r\\n model.childModel = [] # don't really need parent and child pointers but will speed up traversing tree\\r\\n model.vNormal = False\\r\\n model.vGroup = {} # holds the information for each vertex group\\r\\n\\r\\n # read in the file and parse into some arrays\\r\\n\\r\\n if fileName[0] != '/':\\r\\n fileName = sys.path[0] + '/' + fileName\\r\\n filePath = os.path.split(os.path.abspath(fileName))[0]\\r\\n if VERBOSE:\\r\\n print(filePath)\\r\\n f = open(fileName, 'r')\\r\\n l = f.read() # whole thing as a string in memory this will only work for reasonably small files!!!\\r\\n\\r\\n ############### function to parse file as one off process to avoid re-traversing string #########\\r\\n # convertes the '<a> b { c <d> e {f} <g> h {i} }' structure\\r\\n # into nested arrays ['a', 'b', 'c',[['d','e','',['','','f',[]]],['g','h','',['','','i',[]]]]]\\r\\n def pRec(x, bReg, l, i):\\r\\n while 1:\\r\\n try:\\r\\n nxtFind = advance_iterator(bReg)\\r\\n j = nxtFind.start()\\r\\n except:\\r\\n return i+1\\r\\n c = l[j]\\r\\n if c == \\\"<\\\": # add entry to array at this level\\r\\n if len(x[3]) == 0: x[2] = l[i:j].strip() # text after \\\"{\\\" and before \\\"<Tabxyz>\\\"\\r\\n i = j+1 # save marker for start of descriptor\\r\\n x[3].append([\\\"\\\", \\\"\\\", \\\"\\\", []])\\r\\n\\r\\n elif c == \\\"{\\\":\\r\\n xn = x[3][len(x[3])-1]\\r\\n tx = l[i-1:j].strip().split()\\r\\n xn[0] = tx[0] #x[0] & x[1] is the \\\"<Tabxyz>\\\" & \\\"123\\\" prior to \\\"{\\\"\\r\\n xn[1] = tx[1] if len(tx) > 1 else \\\"\\\"\\r\\n i = pRec(xn, bReg, l, j+1)\\r\\n else: #i.e. c=\\\"}\\\" # go up one level of recursion\\r\\n if len(x[3]) == 0: x[2] = l[i:j].strip()\\r\\n return j+1\\r\\n ################### end of pRec #################\\r\\n\\r\\n ####### go through all the nested <Groups> ####################\\r\\n def groupDrill(gp, np):\\r\\n structVList = {}\\r\\n offsetVList = {}\\r\\n structPList = []\\r\\n offset = 0\\r\\n #numv = 0\\r\\n #numi = 0\\r\\n for x in gp:\\r\\n if len(x) == 0: continue\\r\\n if (\\\"<Group>\\\" in x[0]):\\r\\n if len(x[1]) > 0:\\r\\n nextnp = np+x[1]\\r\\n else:\\r\\n nextnp = np+str(randint(10000, 99999))\\r\\n groupDrill(x[3], nextnp)\\r\\n else:\\r\\n #build vertex, polygon, normal, triangles, UVs etc etc\\r\\n if \\\"<VertexPool>\\\" in x[0]:\\r\\n vp = x[1]\\r\\n structVList[vp] = []\\r\\n offsetVList[vp] = offset\\r\\n for v in x[3]:\\r\\n #if \\\"<Vertex>\\\" in v[0]: #try with this test first!\\r\\n coords = [float(n) for n in v[2].strip().split()] # before first < error if no coords!\\r\\n # texture mapping\\r\\n UVcoords = []\\r\\n normal = []\\r\\n for u in v[3]:\\r\\n if \\\"<UV>\\\" in u[0]: UVcoords = [float(n) for n in u[2].strip().split()]\\r\\n #TODO get UVtangent and UVbinormal out of UVset (and use them!)\\r\\n # if (\\\"<Tangent>\\\" in vList[v]): UVtangent = [float(n) for n in (extBracket(\\\"<Tangent>\\\", vList[v]))[0].split()] # not sure how to use this at this stage\\r\\n #else: UVtangent = []\\r\\n # if (\\\"<Binormal>\\\" in vList[v]): UVbinormal = [float(n) for n in (extBracket(\\\"<Binormal>\\\", vList[v]))[0].split()] # not sure how to use this at this stage\\r\\n #else: UVbinormal = []\\r\\n # normals, used in 'smoothing' edges between polygons\\r\\n if \\\"<Normal>\\\" in u[0]: normal = [float(n) for n in u[2].strip().split()]\\r\\n vInt = int(v[1])\\r\\n while (len(structVList[vp]) < (vInt+1)): structVList[vp].append(\\\"\\\")\\r\\n structVList[vp][vInt] = (vertex(coords, UVcoords, normal))\\r\\n offset += 1\\r\\n #\\r\\n # now go through splitting out the Polygons from this Group same level as vertexGroup\\r\\n if \\\"<Polygon>\\\" in x[0]:\\r\\n normal = []\\r\\n rgba = []\\r\\n MRef = \\\"\\\"\\r\\n TRef = \\\"\\\"\\r\\n for p in x[3]:\\r\\n if (\\\"<Normal>\\\" in p[0]): normal = [float(n) for n in p[2].strip().split()]\\r\\n if (\\\"<RGBA>\\\" in p[0]): rgba = [float(n) for n in p[2].strip().split()]\\r\\n if (\\\"<MRef>\\\" in p[0]): MRef = p[2].strip()\\r\\n if (\\\"<TRef>\\\" in p[0]): TRef = p[2].strip()\\r\\n if (\\\"<VertexRef>\\\" in p[0]):\\r\\n vref = []\\r\\n for n in p[2].strip().split():\\r\\n vref.append(int(n))\\r\\n #numv += 1\\r\\n #numi += 3\\r\\n #numi -= 6 # number of corners of triangle = (n-2)*3 where n is the number of corners of face\\r\\n vpKey = p[3][0][2].strip() # ought to do a for r in p[3]; if \\\"Ref in...\\r\\n # add to list\\r\\n #while (len(structPList) < (p+1)): structPList.append(\\\"\\\")\\r\\n #\\r\\n structPList.append(polygon(normal, rgba, MRef, TRef, vref, vpKey))\\r\\n\\r\\n # now go through the polygons in order of vertexPool+id, trying to ensure that the polygon arrays in each group are built in the order of vertexPool names\\r\\n # only cope with one material and one texture per group\\r\\n #numv -= 1\\r\\n #numi -= 1\\r\\n g_vertices = []\\r\\n g_normals = []\\r\\n g_tex_coords = []\\r\\n g_indices = []\\r\\n nv = 0 # vertex counter in this material\\r\\n #ni = 0 # triangle vertex count in this material\\r\\n\\r\\n gMRef = \\\"\\\"\\r\\n gTRef = \\\"\\\"\\r\\n nP = len(structPList)\\r\\n for p in xrange(nP):\\r\\n if (len(structPList[p].MRef) > 0): gMRef = structPList[p].MRef\\r\\n else: gMRef = \\\"\\\"\\r\\n if (len(structPList[p].TRef) > 0): gTRef = structPList[p].TRef\\r\\n else: gTRef = \\\"\\\"\\r\\n\\r\\n vpKey = structPList[p].vpKey\\r\\n vref = structPList[p].vref\\r\\n startV = nv\\r\\n for j in vref:\\r\\n\\r\\n if (len(structVList[vpKey][j].normal) > 0): model.vNormal = True\\r\\n else: model.vNormal = False\\r\\n if model.coordinateSystem == \\\"z-up\\\":\\r\\n thisV = [structVList[vpKey][j].coords[1], structVList[vpKey][j].coords[2], -structVList[vpKey][j].coords[0]]\\r\\n if model.vNormal:\\r\\n thisN = [structVList[vpKey][j].normal[1], structVList[vpKey][j].normal[2], -structVList[vpKey][j].normal[0]]\\r\\n else:\\r\\n thisV = [structVList[vpKey][j].coords[0], structVList[vpKey][j].coords[1], -structVList[vpKey][j].coords[2]]\\r\\n if model.vNormal:\\r\\n thisN = [structVList[vpKey][j].normal[0], structVList[vpKey][j].normal[1], -structVList[vpKey][j].normal[2]]\\r\\n g_vertices.append(thisV)\\r\\n if model.vNormal: nml = thisN\\r\\n else: nml = structPList[p].normal\\r\\n g_normals.append(nml)\\r\\n uvc = structVList[vpKey][j].UVcoords\\r\\n if (len(uvc) == 2):\\r\\n g_tex_coords.append(uvc)\\r\\n else:\\r\\n g_tex_coords.append([0.0, 0.0])\\r\\n nv += 1\\r\\n n = nv - startV - 1\\r\\n for j in range(1, n):\\r\\n g_indices.append((startV, startV + j + 1, startV + j))\\r\\n\\r\\n ilen = len(g_vertices)\\r\\n if ilen > 0:\\r\\n if len(g_normals) != len(g_vertices):\\r\\n g_normals = None # force Buffer.__init__() to generate normals\\r\\n model.buf.append(Buffer(model, g_vertices, g_tex_coords, g_indices, g_normals))\\r\\n n = len(model.buf) - 1\\r\\n model.vGroup[np] = n\\r\\n\\r\\n model.buf[n].indicesLen = ilen\\r\\n model.buf[n].material = (0.0, 0.0, 0.0, 0.0)\\r\\n model.buf[n].ttype = GL_TRIANGLES\\r\\n\\r\\n # load the texture file TODO check if same as previously loaded files (for other loadModel()s)\\r\\n if (gTRef in model.textureList):\\r\\n model.buf[model.vGroup[np]].textures = [model.textureList[gTRef][\\\"texID\\\"]]\\r\\n model.buf[model.vGroup[np]].texFile = model.textureList[gTRef][\\\"filename\\\"]\\r\\n else:\\r\\n model.buf[model.vGroup[np]].textures = []\\r\\n model.buf[model.vGroup[np]].texFile = None\\r\\n #TODO don't create this array if texture being used but should be able to combine\\r\\n if (gMRef in model.materialList):\\r\\n redVal = float(model.materialList[gMRef][\\\"diffr\\\"])\\r\\n grnVal = float(model.materialList[gMRef][\\\"diffg\\\"])\\r\\n bluVal = float(model.materialList[gMRef][\\\"diffb\\\"])\\r\\n model.buf[model.vGroup[np]].material = (redVal, grnVal, bluVal, 1.0)\\r\\n model.buf[model.vGroup[np]].unib[3:6] = [redVal, grnVal, bluVal]\\r\\n\\r\\n else: model.buf[model.vGroup[np]].material = (0.0, 0.0, 0.0, 0.0)\\r\\n ####### end of groupDrill function #####################\\r\\n\\r\\n bReg = re.finditer('[{}<]', l)\\r\\n xx = [\\\"\\\", \\\"\\\", \\\"\\\", []]\\r\\n pRec(xx, bReg, l, 0)\\r\\n l = None #in case it's running out of memory?\\r\\n f.close()\\r\\n\\r\\n for x in xx[3]:\\r\\n if \\\"<Texture>\\\" in x[0]:\\r\\n model.textureList[x[1]] = {}\\r\\n for i in xrange(len(x[3])): model.textureList[x[1]][x[3][i][1]] = x[3][i][2]\\r\\n model.textureList[x[1]][\\\"filename\\\"] = x[2].strip(\\\"\\\\\\\"\\\")\\r\\n if VERBOSE:\\r\\n print(filePath, model.textureList[x[1]][\\\"filename\\\"])\\r\\n model.textureList[x[1]][\\\"texID\\\"] = Texture(os.path.join(filePath, model.textureList[x[1]][\\\"filename\\\"]), False, True) # load from file\\r\\n if \\\"<CoordinateSystem>\\\" in x[0]:\\r\\n model.coordinateSystem = x[2].lower()\\r\\n if \\\"<Material>\\\" in x[0]:\\r\\n model.materialList[x[1]] = {}\\r\\n for i in xrange(len(x[3])): model.materialList[x[1]][x[3][i][1]] = x[3][i][2]\\r\\n if \\\"<Group>\\\" in x[0]:\\r\\n groupDrill(x[3], x[1])\",\n \"def deserialize(self, str):\\n try:\\n end = 0\\n start = end\\n end += 24\\n self.thumb = _get_struct_3d().unpack(str[start:end])\\n start = end\\n end += 24\\n self.index = _get_struct_3d().unpack(str[start:end])\\n start = end\\n end += 24\\n self.middle = _get_struct_3d().unpack(str[start:end])\\n start = end\\n end += 24\\n self.ring = _get_struct_3d().unpack(str[start:end])\\n start = end\\n end += 24\\n self.little = _get_struct_3d().unpack(str[start:end])\\n return self\\n except struct.error as e:\\n raise genpy.DeserializationError(e) # most likely buffer underfill\",\n \"def load_glove_vectors(filename, vocab):\\n dct = {}\\n vectors = array.array('d')\\n current_idx = 0\\n with open(filename, \\\"r\\\", encoding=\\\"utf-8\\\") as f:\\n for _, line in enumerate(f):\\n tokens = line.split(\\\" \\\")\\n word = tokens[0]\\n entries = tokens[1:]\\n if not vocab or word in vocab:\\n dct[word] = current_idx\\n vectors.extend(float(x) for x in entries)\\n current_idx += 1\\n word_dim = len(entries)\\n num_vectors = len(dct)\\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]\",\n \"def fileobject_to_dict(fo):\\n if fo.allocated():\\n # proc = subprocess.Popen(['./extract_strings', fo.inode()], stdout=subprocess.PIPE)\\n # contents = proc.stdout.read()\\n return {\\n 'atime_dt': epoch_to_dt(fo.atime()),\\n 'compressed_b': fo.compressed(),\\n 'contents_t': string.translate(fo.contents(), filter),\\n 'contents_display': string.translate(fo.contents(), filter),\\n 'crtime_dt': epoch_to_dt(fo.crtime()),\\n 'ctime_dt': epoch_to_dt(fo.ctime()),\\n 'dtime_dt': epoch_to_dt(fo.dtime()),\\n 'encrypted_b': fo.encrypted(),\\n 'extension_facet': fo.ext(),\\n 'fileid_i': int(fo._tags['id']),\\n 'filename_display': fo.filename(),\\n 'filename_t': fo.filename(),\\n 'filesize_l': long(fo.filesize()),\\n 'fragments_i': int(fo.fragments()),\\n 'gid_i': int(fo._tags['gid']),\\n #'id': uuid.uuid4(),\\n 'id': hashlib.sha1(os.path.basename(IMAGE) + '_' + fo.inode()).hexdigest(),\\n #'imagefile': fo._tags['imagefile'],\\n 'inode_i': int(fo.inode()),\\n 'libmagic_display': fo.libmagic(),\\n 'libmagic_facet': fo.libmagic(),\\n 'md5_s': fo.md5(),\\n 'meta_type_i': fo._tags['meta_type'],\\n 'mode_facet': int(fo._tags['mode']),\\n 'mode_i': int(fo._tags['mode']),\\n 'mtime_dt': epoch_to_dt(fo.mtime()),\\n 'nlink_i': fo._tags['nlink'],\\n 'name_type_s': fo.name_type(),\\n 'partition_i': int(fo.partition()),\\n 'sha1_s': fo.sha1(),\\n 'uid_i': int(fo._tags['uid']),\\n 'volume_display': IMAGE,\\n 'volume_facet': os.path.basename(IMAGE)\\n }\\n else:\\n return None\",\n \"def unpickle(filename: str) -> dict:\\n with open(os.path.join(f\\\"{ROOT_DIR}/dataset/\\\", filename), \\\"rb\\\") as file:\\n dict = pickle.load(file, encoding=\\\"bytes\\\")\\n return dict\",\n \"def load_bin_vec(fname, vocab):\\n word_vecs = {}\\n with open(fname, \\\"rb\\\") as f:\\n header = f.readline()\\n vocab_size, layer1_size = map(int, header.split())\\n binary_len = np.dtype('float32').itemsize * layer1_size\\n for line in xrange(vocab_size):\\n word = []\\n while True:\\n ch = f.read(1)\\n if ch == ' ':\\n word = ''.join(word)\\n break\\n if ch != '\\\\n':\\n word.append(ch) \\n if word in vocab:\\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32') \\n else:\\n f.read(binary_len)\\n return word_vecs\",\n \"def load_glove(self, path, vocab_size=None, dim=None, reserve_zero=True, reserve_oov_token=True):\\n\\n # Infer vocab size by reading number of lines\\n if vocab_size is None:\\n vocab_size = 0\\n with open(path, 'r') as f:\\n for line in f:\\n vocab_size += 1\\n\\n # Infer vector dim by reading a single line\\n if dim is None:\\n with open(path, 'r') as f:\\n dim = len(f.readline().split(u' ')) - 1\\n\\n words = []\\n\\n self.allow_oov = reserve_oov_token\\n self.reserve_zero = reserve_zero\\n\\n if self.reserve_zero:\\n words.append('__ZERO__')\\n if self.allow_oov:\\n words.append('__OUT_OF_VOCAB__')\\n self.oov_index = len(words) - 1\\n\\n self._matrix = np.zeros((vocab_size+len(words), dim))\\n # Assign random vector for OOV token if it exists\\n if \\\"__OUT_OF_VOCAB__\\\" in words:\\n self._matrix[self.oov_index] = np.random.randn(dim, )\\n\\n update = words.append # Speedup\\n with open(path, 'r') as f:\\n for i in tqdm(range(len(words), self.matrix.shape[0])):\\n split = f.readline().split(u' ', 1)\\n update(split[0])\\n self._matrix[i] = np.fromstring(split[1], 'f', sep=u' ')\\n\\n self.vocab = words\",\n \"def _load(self):\\n # Extract the ASCII header (5 first lines)\\n with open(self._xst_bin, 'rb') as f:\\n header = list(islice(f, 0, 5))\\n assert header[0] == b'HeaderStart\\\\n',\\\\\\n 'Wrong header start'\\n assert header[-1] == b'HeaderStop\\\\n',\\\\\\n 'Wrong header stop'\\n header = [s.decode('utf-8') for s in header]\\n hd_size = sum([len(s) for s in header])\\n\\n # Parse informations into a metadata dictionnary\\n keys = ['freq', 'ma', 'accu']\\n search = ['Freq.List', 'Mr.List', 'accumulation']\\n types = ['float64', 'int', 'int']\\n for key, word, typ in zip(keys, search, types):\\n for h in header:\\n if word in h:\\n self.meta[key] = np.array(\\n h.split('=')[1].split(','),\\n dtype=typ\\n )\\n\\n # Deduce the dtype for decoding\\n n_ma = self.meta['ma'].size\\n n_sb = self.meta['freq'].size\\n dtype = np.dtype(\\n [('jd', 'float64'),\\n ('data', 'complex64', (n_sb, n_ma*n_ma*2 + n_ma))]\\n )\\n\\n # Decoding the binary file\\n tmp = np.memmap(\\n filename=self._xst_bin,\\n dtype='int8',\\n mode='r',\\n offset=hd_size\\n )\\n decoded = tmp.view(dtype)\\n\\n self.data = decoded['data'] / self.meta['accu']\\n self.time = Time(decoded['jd'], format='jd', precision=0)\\n\\n return\",\n \"def __init__(self, filename=None):\\n self.metgauges = {}\\n self.obsgauges = {}\\n if filename:\\n self.read(filename)\",\n \"def load_object(filepath):\\n with open(filepath, 'rb') as f:\\n obj = pickle.load(f)\\n return obj\",\n \"def read(cls, filename: str) -> Objdict:\\n obj = config.read(filename)\\n return cls.from_obj(obj)\",\n \"def readGBK(filename):\\r\\n gnome_record = SeqIO.read(filename, \\\"genbank\\\")\\r\\n return gnome_record\",\n \"def load_bin_vec(self, fname, vocab):\\n word_vecs = {}\\n with open(fname, \\\"rb\\\") as f:\\n header = f.readline()\\n print header\\n vocab_size, layer1_size = map(int, header.split())\\n binary_len = np.dtype('float32').itemsize * layer1_size\\n for line in xrange(vocab_size):\\n word = []\\n while True:\\n ch = f.read(1)\\n if ch == ' ':\\n word = ''.join(word)\\n break\\n if ch != '\\\\n':\\n word.append(ch)\\n if word in vocab:\\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32')\\n # logger.info(word_vecs[word])\\n else:\\n f.read(binary_len)\\n # logger.info(\\\"num words already in word2vec: \\\" + str(len(word_vecs)))\\n return word_vecs\",\n \"def from_dict(cls, dikt) -> 'ImageData':\\n return util.deserialize_model(dikt, cls)\",\n \"def load_bin_vec(fname, vocab):\\n word_vecs = {}\\n with open(fname, \\\"rb\\\") as f:\\n header = f.readline()\\n vocab_size, layer1_size = map(int, header.split())\\n binary_len = np.dtype('float32').itemsize * layer1_size\\n for line in xrange(vocab_size):\\n word = []\\n while True:\\n ch = f.read(1)\\n if ch == ' ':\\n word = ''.join(word).lower()\\n break\\n if ch != '\\\\n':\\n word.append(ch) \\n if word in vocab:\\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32') \\n else:\\n f.read(binary_len)\\n return word_vecs\",\n \"def deserialize(self, str):\\n try:\\n end = 0\\n _x = self\\n start = end\\n end += 100\\n (_x.id, _x.age, _x.velocidad_relativa_x, _x.velocidad_relativa_y, _x.velocidad_absoluta_x, _x.velocidad_absoluta_y, _x.velocidad_absoluta_sigma_x, _x.velocidad_absoluta_sigma_y, _x.bounding_box_centro_x, _x.bounding_box_centro_y, _x.bounding_box_largo, _x.bounding_box_ancho, _x.object_box_centro_x, _x.object_box_centro_y, _x.object_box_orientacion, _x.object_box_size_x, _x.object_box_size_y, _x.clasificacion, _x.clasificacion_age, _x.clasificacion_certeza, _x.punto_cercano_x, _x.punto_cercano_y, _x.punto_referencia_x, _x.punto_referencia_y, _x.punto_referencia_sigma_x, _x.punto_referencia_sigma_y,) = _get_struct_h16fh8f().unpack(str[start:end])\\n return self\\n except struct.error as e:\\n raise genpy.DeserializationError(e) #most likely buffer underfill\",\n \"def load_dictionary(cls, args, filename, source=True):\\n dictionary = Dictionary.load(filename)\\n dictionary.add_symbol(\\\"<mask>\\\")\\n return dictionary\",\n \"def load_model(self, **params):\\n \\t# file_name = params['name']\\n # return pickle.load(gzip.open(file_name, 'rb'))\",\n \"def from_genbank(cls, filename):\\n\\t\\tseq_record = SeqIO.read(filename, 'genbank')\\n\\t\\trec = cls(seq_record=seq_record)\\n\\t\\treturn rec\",\n \"def glove(data_fname='glove.840B.300d.txt', out_fname='glove.pkl'):\\n words, U, dim = [], [], None\\n with open(DATA_DIR + data_fname, 'rb') as f:\\n for j, line in enumerate(f):\\n x = line.strip().split()\\n word, vector, d = x[0], np.ravel(x[1:]), len(x) - 1\\n if dim is None: dim = d\\n elif d != dim: raise Exception('{0}: {1}!={2}'.format(j, dim, d))\\n U.append(vector)\\n words.append(word)\\n U = np.array(U)\\n print \\\"Found {0} words\\\".format(len(words))\\n print \\\"Found {0}x{1} embedding matrix\\\".format(*U.shape)\\n with open(DATA_DIR + out_fname, 'wb') as f:\\n cPickle.dump((words, U), f)\",\n \"def load_word2vec(self, path, binary=True, reserve_zero=True, reserve_oov_token=True):\\n self.allow_oov = reserve_oov_token\\n self.reserve_zero = reserve_zero\\n words = []\\n if self.reserve_zero:\\n words.append('__ZERO__')\\n if self.allow_oov:\\n words.append('__OUT_OF_VOCAB__')\\n self.oov_index = len(words) - 1\\n\\n if binary:\\n with open(path, 'rb') as f:\\n # Get number of vectors and vector size\\n # from first line\\n num_vectors, vector_size = map(\\n int, f.readline().decode('UTF-8').split())\\n FLOAT_SIZE = 4\\n\\n self._matrix = np.zeros(\\n [num_vectors + len(words), vector_size], dtype='float32')\\n # Assign random vector for OOV token if it exists\\n if self.allow_oov:\\n self._matrix[self.oov_index] = np.random.randn(vector_size, )\\n\\n update = words.append # Speedup\\n for i in tqdm(range(len(words), num_vectors+len(words))):\\n # Reads until a whitespace is found (get a word)\\n word = b\\\"\\\"\\n while True:\\n char = f.read(1)\\n if char == b\\\" \\\":\\n break\\n word += char\\n update(word)\\n #Read vector\\n vecs = f.read(FLOAT_SIZE * vector_size)\\n self._matrix[i] = np.frombuffer(vecs, 'f')\\n\\n self.vocab = words\\n else:\\n print(\\\"This feature is yet to be implemented\\\")\",\n \"def load_bin_vec(fname, vocab):\\n word_vecs = {}\\n with open(fname, \\\"rb\\\") as f:\\n header = f.readline()\\n vocab_size, layer1_size = map(int, header.split())\\n binary_len = np.dtype('float32').itemsize * layer1_size\\n for line in xrange(vocab_size):\\n word = []\\n while True:\\n ch = f.read(1)\\n if ch == ' ':\\n word = ''.join(word)\\n break\\n if ch != '\\\\n':\\n word.append(ch) \\n if word in vocab:\\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32') \\n else:\\n f.read(binary_len)\\n return word_vecs\",\n \"def load_bin_vec(fname, vocab):\\n word_vecs = {}\\n with open(fname, \\\"rb\\\") as f:\\n header = f.readline()\\n vocab_size, layer1_size = map(int, header.split())\\n binary_len = np.dtype('float32').itemsize * layer1_size\\n for line in xrange(vocab_size):\\n word = []\\n while True:\\n ch = f.read(1)\\n if ch == ' ':\\n word = ''.join(word)\\n break\\n if ch != '\\\\n':\\n word.append(ch) \\n if word in vocab:\\n word_vecs[word] = np.fromstring(f.read(binary_len), dtype='float32') \\n else:\\n f.read(binary_len)\\n return word_vecs\",\n \"def decode(binary):\\n name, fields = JsonCoder.decode(binary)\\n dataclass = dataclasses.make_dataclass(\\n name, [(key, type(value)) for key, value in fields.items()]\\n )\\n instance = dataclass(**fields)\\n return instance\",\n \"def deserialize_model_pickle(filename):\\n from sst import shape\\n sys.modules['shape'] = shape\\n with open(filename, 'rb') as handle:\\n to_pickle = pickle.load(handle)\\n return to_pickle\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6563649","0.6548593","0.6548593","0.6302663","0.62614805","0.6254731","0.6220778","0.61928546","0.61538893","0.6052055","0.6007737","0.59501976","0.594304","0.59378004","0.5926469","0.59219426","0.5878771","0.5871942","0.58663714","0.58638996","0.58558017","0.58536375","0.5843014","0.5814264","0.5813759","0.58079785","0.58063596","0.579893","0.5797004","0.57743365","0.57720315","0.5753046","0.5747806","0.5708494","0.5707649","0.5697847","0.5685982","0.5677556","0.56695104","0.565613","0.565462","0.5652877","0.56522626","0.56294566","0.5628976","0.5625389","0.5621337","0.5607063","0.5601734","0.5601548","0.56012917","0.5595923","0.55951446","0.5591751","0.55804354","0.55787444","0.55773646","0.5562483","0.5561085","0.5551149","0.5547286","0.5543676","0.5541258","0.55354655","0.552214","0.5521382","0.5520766","0.5517075","0.55107784","0.5507628","0.55029815","0.5495219","0.54919624","0.548614","0.5477254","0.54756844","0.5471313","0.5470743","0.54694927","0.5469378","0.54684216","0.546801","0.54621214","0.5456397","0.545527","0.5449687","0.5446167","0.5445013","0.5440625","0.5436375","0.5428888","0.5427809","0.5422407","0.54211414","0.5418811","0.5418711","0.54166144","0.54166144","0.541626","0.5406068"],"string":"[\n \"0.6563649\",\n \"0.6548593\",\n \"0.6548593\",\n \"0.6302663\",\n \"0.62614805\",\n \"0.6254731\",\n \"0.6220778\",\n \"0.61928546\",\n \"0.61538893\",\n \"0.6052055\",\n \"0.6007737\",\n \"0.59501976\",\n \"0.594304\",\n \"0.59378004\",\n \"0.5926469\",\n \"0.59219426\",\n \"0.5878771\",\n \"0.5871942\",\n \"0.58663714\",\n \"0.58638996\",\n \"0.58558017\",\n \"0.58536375\",\n \"0.5843014\",\n \"0.5814264\",\n \"0.5813759\",\n \"0.58079785\",\n \"0.58063596\",\n \"0.579893\",\n \"0.5797004\",\n \"0.57743365\",\n \"0.57720315\",\n \"0.5753046\",\n \"0.5747806\",\n \"0.5708494\",\n \"0.5707649\",\n \"0.5697847\",\n \"0.5685982\",\n \"0.5677556\",\n \"0.56695104\",\n \"0.565613\",\n \"0.565462\",\n \"0.5652877\",\n \"0.56522626\",\n \"0.56294566\",\n \"0.5628976\",\n \"0.5625389\",\n \"0.5621337\",\n \"0.5607063\",\n \"0.5601734\",\n \"0.5601548\",\n \"0.56012917\",\n \"0.5595923\",\n \"0.55951446\",\n \"0.5591751\",\n \"0.55804354\",\n \"0.55787444\",\n \"0.55773646\",\n \"0.5562483\",\n \"0.5561085\",\n \"0.5551149\",\n \"0.5547286\",\n \"0.5543676\",\n \"0.5541258\",\n \"0.55354655\",\n \"0.552214\",\n \"0.5521382\",\n \"0.5520766\",\n \"0.5517075\",\n \"0.55107784\",\n \"0.5507628\",\n \"0.55029815\",\n \"0.5495219\",\n \"0.54919624\",\n \"0.548614\",\n \"0.5477254\",\n \"0.54756844\",\n \"0.5471313\",\n \"0.5470743\",\n \"0.54694927\",\n \"0.5469378\",\n \"0.54684216\",\n \"0.546801\",\n \"0.54621214\",\n \"0.5456397\",\n \"0.545527\",\n \"0.5449687\",\n \"0.5446167\",\n \"0.5445013\",\n \"0.5440625\",\n \"0.5436375\",\n \"0.5428888\",\n \"0.5427809\",\n \"0.5422407\",\n \"0.54211414\",\n \"0.5418811\",\n \"0.5418711\",\n \"0.54166144\",\n \"0.54166144\",\n \"0.541626\",\n \"0.5406068\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.60128707"},"document_rank":{"kind":"string","value":"10"}}},{"rowIdx":81793,"cells":{"query":{"kind":"string","value":"Create dictionary of vectors and save it into file"},"document":{"kind":"string","value":"def createGloveDic():\n saveGloveDicIntoFile(_extractGloveVects())"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def save_dict(emb, path_to_vec, dim=100):\n word_vec = {}\n for w in emb.keys():\n word_vec[w] = emb[w]\n with open(path_to_vec + f'embedding_{str(dim)}d.txt', 'w') as file:\n for w, v in word_vec.items():\n file.write(w + ' ')\n for el in v:\n file.write(\"{:.20f}\".format(float(el)) + ' ')\n file.write('\\n')","def construct_dict(self):\n i = 0\n self.word2idx = dict()\n fi = open(self.config.word_vec_fi_glove, 'r')\n\n for line in fi:\n self.word2idx[line.split(\" \")[0]] = i\n i += 1\n\n self.vocab_size = i\n self.write_dict()\n fi.close()","def load_dict(path_to_vec):\n emb = {}\n with open(path_to_vec, 'r', errors='ignore', encoding='utf8') as f:\n for line in f:\n values = line.split()\n word = values[0]\n vector = np.asarray(values[1:], \"float32\")\n emb[word] = vector\n return emb","def dump_vecs():\n v_file = os.path.join(TMP_DIR, 'vectorizer.pickle')\n d_file = os.path.join(TMP_DIR, 'dectorizer.pickle')\n f_file = os.path.join(TMP_DIR, 'freq.pickle')\n \n with open(v_file, 'wb') as f:\n pickle.dump(VECTORIZER, f)\n with open(d_file, 'wb') as f:\n pickle.dump(CECTORIZER, f)","def write_vectors(self, filename):\n svu.write_realvectors(self,filename)","def load_vector_dictionary():\n return read_word2vecs_from_file(VECTOR_FILE)","def write_vector(vector, outfile):\r\n out_dir = os.path.dirname(outfile)\r\n if not os.path.exists(out_dir):\r\n os.makedirs(out_dir)\r\n\r\n vector = vector.copy()\r\n for k in vector:\r\n if isinstance(vector[k], np.ndarray):\r\n vector[k] = vector[k].round(4).tolist()\r\n with open(outfile, 'w') as f:\r\n json.dump(vector, f)\r\n f.write('\\n')\r\n\r\n print(\" ... wrote {}\".format(outfile))","def write_vector(vector, outfile):\n out_dir = os.path.dirname(outfile)\n if not os.path.exists(out_dir):\n os.makedirs(out_dir)\n\n vector = vector.copy()\n for k in vector:\n if isinstance(vector[k], np.ndarray):\n vector[k] = vector[k].round(4).tolist()\n with open(outfile, 'w') as f:\n json.dump(vector, f, separators=(',', ': '), indent=4)\n f.write('\\n')\n\n print(\" ... wrote {}\".format(outfile))","def _vector_mapping(self) -> dict:\n words = set()\n for file in os.listdir(self.processed_path):\n doc_path = f\"{self.processed_path}/{file}\"\n with open(doc_path, 'r') as f:\n text_words = f.readline().split()\n words = words.union(set(text_words))\n words = list(words)\n words.sort()\n\n return dict(zip(words, range(len(words))))","def dump_w2vdictionary(outfilename,wordlist,matrix):\n ostream = open(outfilename,'w')\n print('%d %d'%(len(wordlist),matrix.shape[1]),file=ostream)\n for word,vec in zip(wordlist,matrix):\n print(' '.join([word]+ [ str(elt) for elt in vec]),file=ostream)\n ostream.close()","def save_class_representation(self):\n class_dict = {}\n for key, value in self.class_dict.items():\n class_dict['-'.join(key)] = list(value)\n with open('data/class_vectors.txt', 'w') as file:\n json.dump(class_dict, file)\n return class_dict","def save_document_representations(reps, path):\n file = h5py.File(path, 'w')\n\n for name, vector_dict in reps.items():\n vectors = [vector_dict[i] for i in vector_dict.keys()]\n file.create_dataset(name, data=vectors)\n\n file.close()","def as_dict(self):\r\n return {self.words[i]: self.vectors[i] for i in range(self.n)}","def getVectors(self):\n vectors = dict()\n i = 0\n N = len(self.db.invertedIndex)\n for w, (idf, docs) in self.db.invertedIndex.items():\n for doc, tf in docs.items():\n try:\n vectors[doc][i] = tf * idf\n except KeyError as k:\n vectors[doc] = {i: tf * idf}\n i += 1\n i = 0;\n return vectors","def create_vector_dict(self):\n return self.MOVE_DATA","def create_vector_dict(self):\n return self.MOVE_DATA","def write_vecs(self, vecs_fname):\r\n header = f'{self.vectors.shape[0]} {self.vectors.shape[1]}'\r\n np.savetxt(vecs_fname, np.hstack([self.words.reshape(-1, 1), self.vectors]), fmt='%s', header=header)","def gather_and_save_vectors(path, words_vec = collections.defaultdict(list), features = []):\n with open(path, 'rt', encoding='mac_roman') as csvfile:\n csvreader = csv.reader(csvfile, delimiter=' ', quotechar='\"')\n for row in csvreader:\n words_vec, features = countize(row[3], row[2], words_vec, features)\n try:\n words_vec, features = countize(row[6], row[2], words_vec, features)\n except:\n pass\n pickle.dump(words_vec, open(\"ind_vectors.data\", \"wb\"))\n pickle.dump(features, open(\"i_features.data\", \"wb\"))\n return words_vec, features","def save_vectorizer(self, vectorizer_filepath):\n with open(vectorizer_filepath, \"w\") as fp:\n json.dump(self._vectorizer.to_serializable(), fp)","def new_counts_dict():\n\n\tIN_FILES = [\"../_semtag_dataset_webanno_tfidf_inimigo.txt\",\"../_semtag_dataset_webanno_tfidf_publico.txt\" ]\n\n\ttxt = []\n\tfor in_file in IN_FILES:\n\t with codecs.open(in_file,\"r\",\"utf-8\") as fid:\n\t txt += fid.readlines()\n\t#words\n\twords = [w for m in txt for w in m.split()]\n\t#unique words\n\twords = list(set(words))\n\t#word index\n\twrd2idx = {w:-1 for w in words}\n\n\tset_trace()\n\t\n\twith open(COUNTS_DIC,\"w\") as fod:\n\t\tcPickle.dump(wrd2idx, fod, cPickle.HIGHEST_PROTOCOL)","def get_dict(self):\n return {key: value for key, value in zip(self._words, self._vecs)}","def saveGloveDicIntoFile(gloveDic):\n \n np.save(GLOVE_DICT_FILE, np.asarray([gloveDic]))","def dictionary_saver(d, filename):\n json_friendly_d = {json.dumps(k):v for k,v in d.items()}\n sklearn.externals.joblib.dump(json_friendly_d, filename)","def get_W(word_vecs, k=100,path='wordemb'):\n vocab_size = len(word_vecs)\n word_idx_map = dict()\n W = np.zeros(shape=(vocab_size+1, k), dtype='float32')\n W[0] = np.zeros(k, dtype='float32')\n i = 1\n f =open(path+'.word','w')\n for word in word_vecs:\n # print(\"#############################\")\n # print(word_vecs[word].shape)\n # print(word)\n # print(W[i].shape)\n # print(\"#############################\")\n W[i] = word_vecs[word]\n f.write(word+'\\n')\n word_idx_map[word] = i\n i += 1\n np.savetxt(path+'.txt',W,fmt='%.7f', delimiter=' ')\n f.close()\n return W, word_idx_map","def save_embeddings(self, filename, binary=True):\n with open(filename, \"wb\", encoding=\"utf8\") as fout:\n fout.write(\"%s %s\\n\" % self._vecs.shape)\n # store in sorted order: most frequent words at the top\n for i, word in enumerate(self._words):\n row = self._vecs[i]\n if binary:\n fout.write(word + b\" \" + row.tostring())\n else:\n fout.write(\n \"%s %s\\n\" % (word, \" \".join(\"%f\" % val for val in row))\n )","def dict2file(dict, filename, foldername):\n if foldername:\n if not os.path.exists(\"../Created_QD/\" + foldername):\n os.makedirs(\"../Created_QD/\" + foldername)\n file = open(\"../Created_QD/\" + foldername + \"/\" + filename + \".xyz\", \"w\")\n else:\n file = open(\"../Created_QD/\" + filename + \".xyz\", \"w\")\n file.write(\" \\n\\n\")\n for atom, values in dict.items():\n file.write(values['element'] + \"\\t\" + str(values['coor'][0]) + \"\\t\\t\" +\n str(values['coor'][1]) + \"\\t\\t\" + str(values['coor'][2]) + \"\\n\")\n file.seek(0)\n file.write(str(len(dict)))\n file.close()\n print(\"\\nQuantum Dot created :)\")","def WriteFile( self ):\n with open( \"BasisVector.in\" , \"w\" ) as outfile:\n firstLine = \" \" + str( self.NQ ) + \\\n \" \" + str( self.Nbranches ) + \\\n \" \" + str( self.NatomsUC ) + \\\n \" \" + str( self.dim ) + \"\\n\"\n outfile.write( firstLine )\n for qq in range( self.NQ ): ## loop over Q vectors\n lineQ = [ \"{:15.8f}\".format( x ) for x in \n self.QVectors[ qq , : ] ]\n lineQ = \"\".join( lineQ )\n outfile.write( lineQ + \"\\n\" )\n for branch in range( self.Nbranches ): ## loop over branches\n for atom in range( self.NatomsUC ): ## loop over atoms in unit cell\n line = [ \"{:15.8f}\".format( x ) for x in \n self.EigenVectors[ qq , branch , atom , : ] ]\n line = \"\".join( line )\n outfile.write( line + \"\\n\" )\n outfile.write( \"\\n\" )\n outfile.write( \"\\n\" )","def compute_kappa_map(lens_vec, size, size_map):\n\n par_file_name = \"kappa_map.par\"\n fit_file_name = \"kappa_map.fits\"\n z_source = 2.0\n size_map = size_map * 1.05\n\n file_map = open(par_file_name, 'w')\n\n conv_lens_vec(lens_vec)\n\n file_map.write(\"runmode\\n\" )\n file_map.write(\" reference 3 0 0\\n\")\n file_map.write(\" verbose 0\\n\" )\n file_map.write(\" mass 3 \" + str(size) + \" \" + \\\n str(lens_vec[0][\"z_lens\"]) + \" \" + fit_file_name + \"\\n\")\n file_map.write(\" end\\n\")\n file_map.write(\"source\\n\")\n file_map.write(\" z_source \" + str(z_source) + \"\\n\")\n file_map.write(\" end\\n\")\n file_map.write(\"grille\\n\")\n file_map.write(\" nombre 128\\n\")\n file_map.write(\" nlens 4\\n\")\n file_map.write(\" nlens_crit 1\\n\")\n file_map.write(\" nlens_opt 0\\n\")\n file_map.write(\" polaire 1\\n\")\n file_map.write(\" end\\n\")\n\n\n for i in range(len(lens_vec)):\n string_out = 'potential ' + str(i) + '\\n'\n file_map.write(string_out)\n #print string_out,\n for keys in lens_vec[i].keys():\n string_out = ' ' + keys + ' ' + str(lens_vec[i][keys]) + \\\n '\\n'\n #print string_out,\n file_map.write(string_out)\n file_map.write(' end\\n')\n\n file_map.write(\"cosmology\\n\")\n file_map.write(\" H0 70.0\\n\")\n file_map.write(\" omega 0.3\\n\")\n file_map.write(\" lambda 0.7\\n\")\n file_map.write(\" end\\n\")\n file_map.write(\"champ\\n\")\n file_map.write(\" xmin -101\\n\")\n file_map.write(\" xmax 100\\n\")\n file_map.write(\" ymin -101\\n\")\n file_map.write(\" ymax 100\\n\")\n file_map.write(\" dmax \" + str(size_map) + \"\\n\")\n file_map.write(\" end\\n\")\n file_map.write(\"fini\\n\")\n\n file_map.close()","def serialize_box_vectors(box_vectors, to_file=''):\n assert box_vectors is not None\n xmlBox_vectors = ET.Element('box_vectors')\n box_vectors_unitless = box_vectors.value_in_unit(nanometer)\n xmlA = ET.SubElement(xmlBox_vectors, 'A')\n xmlAx = ET.SubElement(xmlA, 'x')\n xmlAx.text = str(box_vectors_unitless[0][0])\n xmlAy = ET.SubElement(xmlA, 'y')\n xmlAy.text = str(box_vectors_unitless[0][1])\n xmlAz = ET.SubElement(xmlA, 'z')\n xmlAz.text = str(box_vectors_unitless[0][2])\n xmlB = ET.SubElement(xmlBox_vectors, 'B')\n xmlBx = ET.SubElement(xmlB, 'x')\n xmlBx.text = str(box_vectors_unitless[1][0])\n xmlBy = ET.SubElement(xmlB, 'y')\n xmlBy.text = str(box_vectors_unitless[1][1])\n xmlBz = ET.SubElement(xmlB, 'z')\n xmlBz.text = str(box_vectors_unitless[1][2])\n xmlC = ET.SubElement(xmlBox_vectors, 'C')\n xmlCx = ET.SubElement(xmlC, 'x')\n xmlCx.text = str(box_vectors_unitless[2][0])\n xmlCy = ET.SubElement(xmlC, 'y')\n xmlCy.text = str(box_vectors_unitless[2][1])\n xmlCz = ET.SubElement(xmlC, 'z')\n xmlCz.text = str(box_vectors_unitless[2][2])\n \n xmlstr = minidom.parseString(ET.tostring(xmlBox_vectors)).toprettyxml(\n indent=\" \")\n \n if to_file:\n our_file=open(to_file, 'w')\n our_file.write(xmlstr)\n our_file.close()\n \n return xmlstr","def _dump_interest_vector(self, user_id: int,\n vector_name: str,\n vector: Dict[int, int]) -> None:\n\n key = self._key_format.format(id=user_id, name=vector_name)\n self._redis.hmset(key, vector)","def save_vectors (feat_vec = None, labels = None, file_extension = None):\n\n feat_file_name = 'output/' + file_extension + '.feature'\n label_file_name = 'output/' + file_extension + '.label'\n\n prettyPrint('Saving feature vector file: {0} ... \\n'\n 'Saving Labels file: {1} ... '.format(feat_file_name, label_file_name), color.CYAN)\n\n #Save feature vector to disk\n with open(feat_file_name, 'w') as f:\n pickle.dump(feat_vec, f)\n #Save label file\n with open(label_file_name, 'w') as f:\n pickle.dump(labels, f)","def vector_to_dict(self, vector, original_dictionary):\n new_dictionary = {}\n current_index = 0\n for key,item in original_dictionary.items():\n new_index = current_index + item.size\n new_dictionary[f'{key}'] = np.reshape(vector[current_index:new_index],item.shape)\n current_index = new_index\n return new_dictionary","def _extractGloveVects():\n \n embeddings_index = {}\n\n with open(GLOVE_CORPUS_FILE) as f:\n for line in f:\n values = line.split()\n word = values[0].lower()\n if word not in _cachedStopWords:\n coefs = np.asarray(values[1:], dtype='float32')\n embeddings_index[word] = coefs\n\n return embeddings_index","def get_glove_dictionary(self, file_path=\"./glove.twitter.27B.25d.txt\"):\n file = open(file_path, \"r\",encoding='utf-8')\n dictionary = {}\n keys = []\n for word_vector in file:\n dictionary[word_vector.split()[0]] = word_vector.split()[1:]\n keys.append(word_vector.split()[0])\n file.close()\n\n file = open(\"./Glove_dict.txt\", \"a\",encoding='utf-8')\n for word in keys:\n file.write(word + '\\n')\n file.close()","def write_mat_file(self):\n mat_dict = {}\n mat_dict['Lx_p'] = self.Lx_p\n mat_dict['Ly_p'] = self.Ly_p\n mat_dict['Lz_p'] = self.Lz_p\n mat_dict['Lo'] = self.obst.get_Lo()\n mat_dict['Ny_divs'] = self.N_divs\n mat_dict['rho_p'] = self.rho_p\n mat_dict['nu_p'] = self.nu_p\n mat_dict['snl'] = list(np.union1d(self.obst_list[:],self.solid_list[:]))\n mat_dict['inl'] = list(self.inlet_list[:])\n mat_dict['onl'] = list(self.outlet_list[:])\n\n scipy.io.savemat('geometry_description',mat_dict)","def export(self, outpath):\n fout = open(outpath, \"w\")\n\n # Header takes the guesswork out of loading by recording how many lines, vector dims\n fout.write(str(self.n_words) + \" \" + str(self.n_dim) + \"\\n\")\n for token in self.id2word:\n vector_components = [\"%.6f\" % number for number in self[token]]\n vector_as_string = \" \".join(vector_components)\n\n out_line = token + \" \" + vector_as_string + \"\\n\"\n fout.write(out_line)\n\n fout.close()","def vec_to_dict(docVec):\n return {dimension:value for dimension, value in enumerate(docVec)}","def save_to_file(self, filename):\n outMap = {}\n for kanal in self._datastoreMap:\n # svaki pojedini Datastore se zna zapakirati u mapu (dictionary)\n outMap[kanal] = self._datastoreMap[kanal].store2dict()\n # serialize u binary string\n binstr = pickle.dumps(outMap)\n # zapis u file\n with open(filename, 'wb') as f:\n f.write(binstr)","def write_features(self):\r\n def pack_keypoint(keypoints, descriptors):\r\n kpts = np.array([[kp.pt[0], kp.pt[1], kp.size,\r\n kp.angle, kp.response, kp.octave,\r\n kp.class_id]\r\n for kp in keypoints])\r\n desc = np.array(descriptors)\r\n return kpts, desc\r\n\r\n filename = self.features_path + self.id\r\n kpts, desc = pack_keypoint(self.keypoints, self.descriptors)\r\n logging.info(f'Writing features of image {self.name} to file...')\r\n np.savez(filename, keypoints=kpts, descriptors=desc)\r\n logging.info('Features saved.')","def makeDictionary(self):\n self.dictionary = {}\n for i in range(len(self.movie)):\n if self.movie[i] in self.dictionary:\n vectors = self.dictionary[self.movie[i]]\n vectors[self.user[i]] = self.rating[i]\n self.dictionary[self.movie[i]] = vectors\n else:\n newMovie = dict([(self.user[i], self.rating[i])])\n self.dictionary[self.movie[i]] = newMovie\n return self.dictionary","def write_vocabulary():\n with open('../data/vocabulary.txt', 'w') as vocabulary_file:\n vocabulary = generate_vocabulary()\n word_count = sum(vocabulary.values())\n print(word_count)\n vocabs_str = [(\"%s %d\" % (key, value)) for key, value in vocabulary.items()]\n vocabulary_file.write('\\n'.join(vocabs_str))","def save(self, dirname=None):\n self.genio.save(dirname)\n logging.info(\n f'Saved word vectorizations for {dirname}')","def file_to_dictionary():\n\n return;","def load_glove_vectors(filename, vocab):\n dct = {}\n vectors = array.array('d')\n current_idx = 0\n with open(filename, \"r\", encoding=\"utf-8\") as f:\n for _, line in enumerate(f):\n tokens = line.split(\" \")\n word = tokens[0]\n entries = tokens[1:]\n if not vocab or word in vocab:\n dct[word] = current_idx\n vectors.extend(float(x) for x in entries)\n current_idx += 1\n word_dim = len(entries)\n num_vectors = len(dct)\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]","def make_dict_database(file_name):\n f = h5py.File(file_name,'r')\n\n num_games = len(f.keys())\n db = {'input' : np.zeros((num_games, 181)), 'output' : np.zeros((num_games, 2))}\n for i, g in enumerate(f.keys()):\n db['input'][i] = f[g]['input'][:]\n db['output'][i] = f[g]['win_probs'][:]\n \n return db","def load_bin_vec(filename):\n w2v = {}\n with open(filename, 'r') as f:\n header = f.readline()\n vocab_size, emb_size = map(int, header.split())\n for line in f:\n cline = line.split()\n w2v[cline[0]] = np.array(cline[1:], dtype=np.float64)\n return w2v, emb_size, vocab_size","def create_sample_vectors(cleaned_data_directory, out_vectors_path):\n vectors = []\n\n for filename in os.listdir(cleaned_data_directory):\n if not filename.endswith(\".txt\"):\n continue\n\n path = os.path.join(cleaned_data_directory, filename)\n f = open(path, mode='r', encoding='utf8')\n\n print(\"Processing\", path)\n\n lang = filename[:2]\n lang_number = language_codes.index(lang)\n\n print(f\"\\tLanguage: {lang} ({lang_number})\")\n print(\"\\tReading...\", end=' ')\n\n file_content = f.read()\n content_length = len(file_content)\n\n print(\"done.\")\n print(\"\\tExtracting vectors...\", end=' ')\n\n sample_start_index = 0\n count = 0\n\n while sample_start_index + text_sample_size < content_length:\n sample = get_sample(file_content, sample_start_index, text_sample_size)\n input_vector = build_input_vector(sample)\n vector = input_vector + [lang_number]\n vectors.append(vector)\n sample_start_index += text_sample_size\n count += 1\n\n print(\"done.\")\n print(f\"\\tExtracted {count} vectors.\")\n\n del file_content\n\n print(f\"Total {len(vectors)} vectors.\")\n\n np_vectors = np.array(vectors, dtype=np.uint16)\n np.random.shuffle(np_vectors)\n\n print(f\"Converted to NumPy array, shape: {np_vectors.shape}.\")\n\n np.savez_compressed(out_vectors_path, data=np_vectors)\n\n print(f\"Saved to {out_vectors_path}.\")","def save(self, filename):\n data = {\"sizes\": self.sizes,\n \"weights\": [w.tolist() for w in self.weights],\n \"biases\": [b.tolist() for b in self.biases]}\n f = open(filename, \"w\")\n json.dump(data, f)\n f.close()","def _generate_vector(article, save=False):\n tf = term_frequency.get_vector(article)\n vector = generate_vector(article['body'], tf)\n if save:\n if not os.path.isdir(os.path.join(os.path.dirname(__file__), './tf_idfs')):\n os.mkdir(os.path.join(os.path.dirname(__file__), './tf_idfs'))\n print(\"Created directory to store tf_idfs.\")\n with open(_tf_idf_path(article['id']), 'w') as json_file:\n json.dump(vector, json_file)\n return vector","def save(self):\n \n with open(os.path.join(self.output_dir, 'terms.dict'), 'wb') as f:\n pkl.dump(self.term_id_map, f)\n with open(os.path.join(self.output_dir, 'docs.dict'), 'wb') as f:\n pkl.dump(self.doc_id_map, f)","def load_vectors(self, weights_path: str) -> dict:\n vectors = {}\n for file in os.listdir(weights_path):\n v_path = f\"{weights_path}/{file}\"\n res = re.search(\"(.+).npy\", v_path)\n # filename without extension\n if res:\n filename = res.group(1)\n\n vectors[filename] = np.load(v_path)\n\n return vectors","def save_data(self, **kwargs):\n\n file = kwargs['file']\n with open(file, 'w') as data_file:\n for item in self._items.values():\n data_string = '{'\n item_dict = item.to_dict()\n\n for key, value in item_dict.items():\n data_string += f'\"{key}\":\"{value}\",'\n\n data_string = data_string[:-1]\n data_string += '}\\n'\n data_file.write(data_string)","def create_dicts():\n load_data_for_dict('data/atis/train/seq.in', 'data/atis/voc/vocabulary.json')\n load_data_for_dict('data/atis/valid/seq.in', 'data/atis/voc/vocabulary.json')\n load_data_for_dict('data/atis/test/seq.in', 'data/atis/voc/vocabulary.json') \n load_data_for_dict('data/atis/train/seq.out', 'data/atis/voc/slot_vocabulary.json')","def save_serendipity_dic(y, filename):\n store = pd.io.pytables.HDFStore(y)\n mat = store.matrix\n store.close()\n n = len(mat.columns)\n ser = 1 - mat.sum(axis=1) / n\n\n f = open(filename, \"w\")\n cPickle.dump(ser.to_dict(), f, protocol=2)\n f.close()","def create_vectors(list_dict, num_words):\n x = [] # list that will hold data \n\n for d in list_dict:\n # initializing numpy vector\n # it contains 5,000 (number of words) zeros\n temp = np.zeros(num_words, dtype=np.float64)\n for key, val in d.items():\n if key < num_words:\n key -= 1 # indexing in data starts at 1\n temp[key] = 1 # adding word and its frequency to vector \n # temp[key] = val\n x.append(temp) # appends vector to x \n\n return x","def build_doc_sense_vec(self):\n\t\twith codecs.open(self.vocab_file, encoding='utf-8', mode='r') as infile:\n\t\t\tline = infile.readline()\n\t\t\ti = 0\n\t\t\twhile line:\n\t\t\t\tword = line.split()[0]\n\t\t\t\tif not self.word2IdVocabulary.has_key(word):\n\t\t\t\t\t# print i, word\n\t\t\t\t\t# else:\n\t\t\t\t\tself.word2IdVocabulary[word] = i\n\t\t\t\tif not self.id2WordVocabulary.has_key(i):\n\t\t\t\t\tself.id2WordVocabulary[i] = word\n\t\t\t\tline = infile.readline()\n\t\t\t\ti += 1\n\t\t\tself.vocab_num = len(self.word2IdVocabulary)\n\t\t\tprint \"vocabulary number:\" + str(self.vocab_num)\n\n\t\twith codecs.open(self.vec_file, encoding='utf-8', mode='r') as vecfile:\n\t\t\twith codecs.open(self.vec_out_file, encoding='utf-8', mode='a+') as vec_outfile:\n\n\t\t\t\tfor i, line in enumerate(vecfile):\n\t\t\t\t\tif i % 10000 == 0:\n\t\t\t\t\t\tprint i\n\t\t\t\t\t# if i > 72:\n\t\t\t\t\t# \tbreak\n\t\t\t\t\tif i == 0:\n\t\t\t\t\t\ta, b, c = map(int, line.split()[:3])\n\t\t\t\t\t\tprint('Number of sememes: {}\\n'\n\t\t\t\t\t\t\t 'Number of words: {}\\n'\n\t\t\t\t\t\t\t 'Dimension of vectors: {}'.format(a, b, c))\n\t\t\t\t\telif i > 462667:\n\t\t\t\t\t\tsline = line.strip('\\n').split()\n\t\t\t\t\t\tword = sline[0]\n\t\t\t\t\t\tvector_list = []\n\t\t\t\t\t\tvector_list.append(sline[1:])\n\t\t\t\t\t\tvector_array = np.array(vector_list)\n\t\t\t\t\t\tword_id = self.word2IdVocabulary[word]\n\t\t\t\t\t\tif not self.vectors.has_key(word_id):\n\t\t\t\t\t\t\tself.vectors[word_id] = vector_array\n\t\t\t\t\t\t# vector_mean = np.mean(vector_array, axis=0)\n\t\t\t\t\t\tif not self.vector_mean.has_key(word_id):\n\t\t\t\t\t\t\tself.vector_mean[word_id] = vector_array\n\t\t\t\t\t\t# vec_outfile.write(line)\n\t\t\t\t\telif i > 462887:\n\t\t\t\t\t\tbreak\n\t\t\t\t\telse:\n\t\t\t\t\t\tsline = line.strip('\\n').split()\n\t\t\t\t\t\tword = sline[0]\n\t\t\t\t\t\tsense_num = int(sline[1])\n\t\t\t\t\t\tvectors = sline[2:sense_num*c+2] # (sense_num*c+2)\n\t\t\t\t\t\tvector_list = []\n\t\t\t\t\t\tfor start in range(0, len(vectors), c):\n\t\t\t\t\t\t\tvector_list.append(list(map(float, vectors[start: start+c])))\n\t\t\t\t\t\tvector_array = np.array(vector_list)\n\t\t\t\t\t\tword_id = self.word2IdVocabulary[word]\n\t\t\t\t\t\tif not self.vectors.has_key(word_id):\n\t\t\t\t\t\t\tself.vectors[word_id] = vector_array\n\t\t\t\t\t\tvector_mean = np.mean(vector_array, axis=0)\n\t\t\t\t\t\tif not self.vector_mean.has_key(word_id):\n\t\t\t\t\t\t\tself.vector_mean[word_id] = vector_mean\n\t\t\t\t\t\t'''j = 0\n\t\t\t\t\t\tfor each_sense_vec in vector_array:\n\t\t\t\t\t\t\tif len(vector_array) > 1:\n\t\t\t\t\t\t\t\tnew_line = word + '_' + str(j) + ' ' + np.array2string(each_sense_vec, max_line_width=2000,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tformatter={'float_kind': lambda x: '%6f' % x})[1:-1] + '\\n'\n\t\t\t\t\t\t\t\tj += 1\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tnew_line = word + ' ' + np.array2string(each_sense_vec, max_line_width=2000,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t formatter={'float_kind': lambda\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t x: '%6f' % x})[1:-1] + '\\n'\n\n\t\t\t\t\t\t\tvec_outfile.write(new_line)'''\n\n\t\twith codecs.open(self.doc_file, encoding='utf-8', mode='r') as docfile:\n\t\t\twith codecs.open(self.doc_out_file, encoding='utf-8', mode='a+') as doc_outfile:\n\t\t\t\twith codecs.open(self.vec_out_file_bydoc, encoding='utf-8', mode='a+') as vec_outfile_bydoc:\n\t\t\t\t\tprint \"Processing document file......\"\n\t\t\t\t\tline = docfile.readline().strip('\\n')\n\t\t\t\t\twhile line:\n\t\t\t\t\t\twords = line.split()\n\t\t\t\t\t\tnew_words = [x for x in words]\n\t\t\t\t\t\tfor i in range(len(words)):\n\t\t\t\t\t\t\tword_id = self.word2IdVocabulary[words[i]]\n\t\t\t\t\t\t\tsense_vecs = self.vectors[word_id]\n\t\t\t\t\t\t\tsense_num = len(sense_vecs)\n\t\t\t\t\t\t\tif sense_num > 1:\n\t\t\t\t\t\t\t\tcontext_words = []\n\t\t\t\t\t\t\t\tfor x in range(i-int(self.context_num), i+int(self.context_num)+1):\n\t\t\t\t\t\t\t\t\tif x != i and 0 <= x < len(words):\n\t\t\t\t\t\t\t\t\t\tcontext_words.append(words[x])\n\t\t\t\t\t\t\t\tsense_index = self.select_attention(context_words, sense_vecs)\n\t\t\t\t\t\t\t\tword_vec_i = sense_vecs[sense_index]\n\t\t\t\t\t\t\t\tnew_wordi = words[i] + '_' + str(sense_index)\n\t\t\t\t\t\t\t\tself.vector_word_doc[new_wordi.encode('utf-8')] = word_vec_i\n\t\t\t\t\t\t\t\tnew_words[i] = new_wordi\n\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\tword_vec_i = sense_vecs[0]\n\t\t\t\t\t\t\t\tself.vector_word_doc[words[i].encode('utf-8')] = word_vec_i\n\t\t\t\t\t\t\tvec_outfile_bydoc.write(new_words[i] + ' ' + np.array2string(word_vec_i, max_line_width=2000,\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t formatter={'float_kind': lambda x: '%6f' % x})[1:-1] + '\\n')\n\n\t\t\t\t\t\tdoc_outfile.write(' '.join(new_words) + '\\n')\n\n\t\t\t\t\t\tline = docfile.readline()\n\n\t\treturn self.vector_word_doc","def save_vec(vec, h5file, slab, name):\n atom = tables.Atom.from_dtype(vec.dtype)\n ca = h5file.create_carray(slab, name, atom, vec.shape)\n ca[:] = vec","def create_vocabulary(sentences, path):\n print('creating vocab..')\n\n word_dict = dict(); vocabulary = dict()\n for sentence in sentences:\n for word in nltk.word_tokenize(sentence):\n if word not in word_dict:\n word_dict[word] = ''\n word_dict['<s>'] = ''\n word_dict['</s>'] = ''\n\n with open(path, encoding=\"utf8\") as f:\n for line in f:\n word, vec = line.split(' ', 1)\n if word in word_dict:\n vocabulary[word] = np.fromstring(vec, sep=' ')\n\n print('vocabulary was created successfully!')\n return vocabulary","def store_model_poses(self, model_name, file_to_store=\"poses.yaml\" ):\n \n with open(file_to_store, 'w') as outfile:\n\n #inizializzo il dict vuoto con chiave models e value lista vuota\n\n dict_in = dict(models = [])\n\n now_dict = dict_in\n\n el_listaURDF = self.get_square_pose()\n now_dict[\"models\"].append(el_listaURDF) #sostituire con now_dict\n rospy.loginfo(\"now_dict URDF inizializzato\")\n\n # aggiorno il dizionario con tutti gli elementi presenti nella lista\n for robot_name in model_name :\n\n now_pose = self.get_pose_of_model(robot_name)\n el_lista = self.reformat_pose_to_dict(now_pose) #ritorna un dizionario che sarà elemento della lista\n now_dict[\"models\"].append(el_lista) #eseguo l'append nella lista di models\n \n rospy.loginfo(\"now_dict sdf inizializzati\")\n \n # una volta inizializzati i models sdf posso scrivere nel file .yaml anche la posizione in cui deve essere spawnata l urdf\n # devo creare l'ultimo elemento dict della lista e fare l'append alla lista che andrà in scrittura\n\n \"\"\"\n {\"name\" : \"ferrari\" , \n \"type\" : \"urdf\" , \n \"package\" : \"autopark\" , \n \"pose \":self.seq(lista_parametri) \n }\n \n \"\"\"\n \n\n # Scrittura su file .yaml\n \n yaml = ruamel.yaml.YAML()\n yaml.indent(mapping=3, sequence=4, offset=2) #comando per indentare correttamente come nel file spawn_obj\n yaml.dump(now_dict, sys.stdout) #comando per stampare nella shell per visualizzare il corretto formato\n \n yaml.dump(now_dict, outfile) #comando che stampa all'interno del file .yaml\n\n rospy.loginfo(\"numero auto sdf spawnate : \" + str(len(now_dict[\"models\"])-1))","def save_to_file():\n dict_from_file.update(temp_dict)\n plik=open('data.txt', 'w')\n for key in dict_from_file.keys():\n plik.write(key)\n plik.write(\" \")\n plik.write(str(dict_from_file[key][0]))\n plik.write(' ')\n plik.write(dict_from_file[key][1].replace(' ','_'))\n plik.write(' ')\n plik.write(str(dict_from_file[key][2]))\n plik.write('\\n')","def build_vocab(sentences_list, vocab_size, visual_fld):\n words = [word for sentence in sentences_list for word in sentence]\n utils.safe_mkdir(visual_fld)\n with open(os.path.join(visual_fld, 'vocab.tsv'), 'w') as fd:\n dictionary = {}\n index_dictionary = {}\n count = [('UNK', -1)]\n count.extend(Counter(words).most_common(vocab_size - 1))\n for index, (word, _) in enumerate(count):\n dictionary[word] = index\n index_dictionary[index] = word\n fd.write(word + '\\n')\n\n return dictionary, index_dictionary","def creating_feature_vector():\r\n\twordlist = []\r\n\tlabel = \"\"\r\n\tfw = open(\"feature_vector.txt\", \"w+\", encoding = \"utf-8\")\r\n\twith open(\"D:\\\\Python_Prac\\\\wordstag\\\\modules\\\\HI_EN_TRAIN.txt\", \"r\", encoding = \"utf-8\") as f:\r\n\t\tfor line in f:\r\n\t\t\twordlist.append(line)\r\n\t\tfor index, line in enumerate(wordlist):\r\n\t\t\tif line == \"\\n\":\r\n\t\t\t\tcontinue\r\n\t\t\tcontext = line.split(\"\\t\")\r\n\t\t\tlabel = context[1]\r\n\t\t\tfeature_vector = label+\" \"\r\n\t\t\tngram_vector = ngram_frequency(str(context[0]))\r\n\t\t\tfor vector in ngram_vector:\r\n\t\t\t\tfeature_vector += str(vector)+\" \"\r\n\t\t\tfeature_vector += str(is_english(context[0]))+\" \"\r\n\t\t\tfeature_vector += str(is_hindi(context[0]))+\" \"\r\n\t\t\tfeature_vector += str(is_abbr(context[0]))+\" \"\r\n\t\t\tfeature_vector += str(med_in_english(context[0]))+\" \"\r\n\t\t\tfeature_vector += str(med_in_hindi(context[0]))+\" \"\r\n\t\t\tbefore = [0,0,0]\r\n\t\t\tafter = [0,0,0]\r\n\t\t\tfor i in range(3):\r\n\t\t\t\tif (index-i) < 0 or (index-i+1) > len(wordlist)-1:\r\n\t\t\t\t\tcontinue\r\n\t\t\t\tbefore[2-i] = get_word_context(wordlist[index-i+1].split(\"\\t\")[0])\r\n\t\t\tfor i in range(3):\r\n\t\t\t\tif (index+i+1) > len(wordlist)-1:\r\n\t\t\t\t\tcontinue\r\n\t\t\t\tafter[2-i] = get_word_context(wordlist[index+i+1].split(\"\\t\")[0])\r\n\t\t\tfor i in before:\r\n\t\t\t\tfeature_vector += str(i)+\" \"\r\n\t\t\tfor i in after:\r\n\t\t\t\tfeature_vector += str(i)+\" \"\r\n\t\t\tfeature_vector += \"\\n\"\r\n\t\t\tfw.write(feature_vector)\r\n\t\t\tprint(\"Proceeding...\"+str(index+1)+\" of 16683\")\r\n\r\n\tfw.close()","def get_label_vectors():\n print(\"Retrieving label vectors...\")\n label_dict = {} # instantiate dict for labels:vectors\n categories = sorted([c for c in os.listdir('images/') if c[0] != '.']) # ignore hidden files\n x = np.zeros(len(categories)) # zero vector of number of categories\n for i, c in enumerate(categories): # get index and category for images\n y = x.copy() # use copy of x\n y[i] = 1 # set label index to true\n label_dict[c] = y.copy() # create label:vector\n\n return label_dict","def make_vectors_output(coord_dict, add_vectors, num_coords, color, ids, display_name='trace', state='on'):\n # default parameters\n which_set = 0\n tip_fraction = 0.5\n arrow_colors = {'line_color': color, 'head_color': color}\n \n # header for section in kin file\n result = []\n result.append('@vectorlist {%s} dimension=%s %s' % (display_name, num_coords, state))\n \n # selecting the edges to draw in this batch\n edges = []\n for k, v in add_vectors['vectors'].iteritems():\n edges = edges + [(v[i][1],v[i+1][1]) for i in range(len(v[:-1])) if v[i][1] in ids]\n \n # creating \"vectors\"\n for edge in edges:\n id_fr, id_to = edge\n # extract the coords of each vertex\n pt_fr = coord_dict[id_fr][:num_coords]\n pt_to = coord_dict[id_to][:num_coords]\n\n # different tip color for each destination coords file\n #tip_color = kinemage_colors[which_set % len(kinemage_colors)]\n # plot a color 'tip' on the line (certain % of line length)\n # this gets the coords of the beginning of the 'tip'\n diffs = (pt_to-pt_fr) * (1-tip_fraction)\n middles = pt_fr + diffs\n # add a default-color line segment\n \n # modified to use user defined\n tip_color = arrow_colors['head_color']\n label_color = arrow_colors['line_color']\n \n result.append('%s %s' % \\\n (' '.join(map(str, pt_fr)),label_color))\n result.append('%s %s P' % \\\n (' '.join(map(str, middles)),label_color))\n # add the tip-colored line segment\n result.append('%s %s' % \\\n (' '.join(map(str, middles)), tip_color))\n result.append('%s %s P' % \\\n (' '.join(map(str, pt_to)), tip_color)) \n return result","def file_write(filename, dic):\n d = dic \n f = open(filename, 'w') \n f.write(str(d))\n f.close()","def save_id_dict(self) -> None:\n # convert sets to lists\n forward_map = {k: list(v) for k, v in self.forward_map.items()}\n # write to file\n with open(self.mapping_file, 'w') as outf:\n json.dump(\n [forward_map, self.backward_map],\n outf, indent=4, sort_keys=True\n )","def save(self, filename):\n with open(filename, \"w\", encoding=\"utf8\") as f:\n f.write(\n \"\\n\".join(\n [\n w + \" \" + \" \".join([str(x) for x in v])\n for w, v in zip(self._words, self._vecs)\n ]\n )\n )\n print(\"Wrote\", self.n, \"words to\", filename)","def load_vectors(vec_file, info_file, buckets):\n vectors = np.load(vec_file)\n with open(info_file, 'r') as f:\n info = json.load(f)\n\n if len(info['sequence_id_list']) != len(info['instance_id_list']):\n raise ValueError('Invalid info file: len(info[''sequence_id_list'']) should be equal to len(info[''instance_id_list'']) but got %d != %d' % (len(info['sequence_id_list']), len(info['instance_id_list'])))\n if vectors.shape[0] != len(info['instance_id_list']):\n raise ValueError('Number of vectors and length of info list are not identical. %d != %d' % (len(info['sequence_id_list']), len(info['instance_id_list'])))\n\n num_vec, vec_dim = vectors.shape\n prev_seq_id, prev_ins_id = None, None\n seq_ids = {i: [] for i in xrange(len(buckets))}\n ins_ids = {i: [] for i in xrange(len(buckets))}\n data = {i: [] for i in xrange(len(buckets))}\n\n for vec_idx in tqdm(xrange(num_vec)):\n curr_seq_id, curr_ins_id = info['sequence_id_list'][vec_idx], info['instance_id_list'][vec_idx]\n if curr_seq_id != prev_seq_id or curr_ins_id != prev_ins_id:\n if prev_seq_id is not None:\n bucket_id, curr_sample = bucketing(vec_count, buckets, vec_dim, curr_sample)\n seq_ids[bucket_id].append(prev_seq_id)\n ins_ids[bucket_id].append(prev_ins_id)\n data[bucket_id].append(curr_sample)\n vec_count = 1\n curr_sample = vectors[vec_idx]\n else:\n vec_count += 1\n curr_sample = np.vstack((curr_sample, vectors[vec_idx]))\n prev_seq_id = curr_seq_id\n prev_ins_id = curr_ins_id\n\n # throw the last sample into bucket\n bucket_id, curr_sample = bucketing(vec_count, buckets, vec_dim, curr_sample)\n seq_ids[bucket_id].append(prev_seq_id)\n ins_ids[bucket_id].append(prev_ins_id)\n data[bucket_id].append(curr_sample)\n\n return data, seq_ids, ins_ids","def load_glove(path):\n with open(path) as f:\n glove = {}\n for line in f.readlines():\n values = line.split()\n word = values[0]\n vector = np.array(values[1:], dtype='float32')\n glove[word] = vector\n return glove","def load_glove(path):\n with open(path) as f:\n glove = {}\n for line in f.readlines():\n values = line.split()\n word = values[0]\n vector = np.array(values[1:], dtype='float32')\n glove[word] = vector\n return glove","def loadGLOVE(filename, vocab):\n dct = {}\n vectors = array.array('d')\n current_idx = 0\n with codecs.open(filename, \"r\", encoding=\"utf-8\") as f:\n for _, line in enumerate(f):\n tokens = line.split(\" \")\n word = tokens[0]\n entries = tokens[1:]\n if not vocab or word in vocab:\n dct[word] = current_idx\n vectors.extend(float(x) for x in entries)\n current_idx += 1\n word_dim = len(entries)\n num_vectors = len(dct)\n tf.logging.info(\"Found {} out of {} vectors in Glove\".format(num_vectors, len(vocab)))\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]","def SaveDictFile(file,dict_):\n with open(file,'w') as f:\n for id in dict_:\n f.write(dict_[id] + \"=\" + str(id)+\"\\n\")","def save_track_to_dict(self, filename):\n\n # save track data\n track_dict = {\n 'size': self.size,\n 'points': self.points,\n 'pivots': self.pivots,\n 'seed': self.noise_seed,\n 'data': self.track_data\n }\n\n np.save(\"./static/\" + filename, track_dict)\n\n print(\"Track saved successfully\")","def loadGloveDicFromFile():\n \n #if the resource file is not present, creates the file containing all vectors\n #and return vectors\n if not isfile(GLOVE_DICT_FILE):\n vects = _extractGloveVects()\n saveGloveDicIntoFile(vects)\n return vects\n \n return np.load(GLOVE_DICT_FILE)[0]","def save(self, path):\n\n if not os.path.exists(path):\n os.makedirs(path)\n\n np.save(os.path.join(path, 'V.npy'), self.V.cpu().numpy())\n\n if self.W is not None:\n np.save(os.path.join(path, 'W.npy'), self.W.cpu().numpy())\n\n if self.vb is not None:\n np.save(os.path.join(path, 'v_bias.npy'), self.vb.cpu().numpy())\n\n if self.wb is not None:\n np.save(os.path.join(path, 'w_bias.npy'), self.wb.cpu().numpy())\n\n if self.dictionary is not None:\n self.dictionary.save(os.path.join(path, 'dictionary'))","def create_data_vector(self,regression_out_dict={},phage_file=None,\n k_cutoff=0.00):\n\n self.data_vector = []\n self.seq_strings = []\n\n # If the user specifies a human-readable file, use that rather than the\n # input dictionary.\n if phage_file != None:\n \n with open(phage_file) as data:\n\n next(data)\n for line in data:\n try:\n num, seq, k_glob, theta_glob, k_ind, theta_ind = line.split()\n except ValueError:\n num, seq, k_ind, k_min, k_max = line.split()\n\n if float(k_ind) > k_cutoff:\n\n self.seq_strings.append(seq)\n\n self.data_vector.append(\n np.array([self._alphabet_dict[s] for s in seq],\n dtype=self.internal_type))\n\n else:\n for k in regression_out_dict.keys():\n if regression_out_dict[k][0] > k_cutoff:\n self.seq_strings.append(k)\n self.data_vector.append(\n np.array([self._alphabet_dict[s] for s in k],\n dtype=self.internal_type))\n\n self.data_vector = np.array(self.data_vector)\n self.seq_strings = np.array(self.seq_strings)","def serialize_dictionaries(self,\n output_file,\n restrict_to = None):\n io.write_symbol_table_dict(output_file, self._symtab, restrict_to)","def saveNewData(self, newvec, fname=None):\n assert len(newvec) == len(self.allimgs), \\\n 'List is uncompatible with images %d != %d' % (len(newvec), len(self.allimgs))\n if fname and not self.record_mode:\n self.fout = open(fname, 'w')\n self.record_mode = True\n for path, y, pred in zip(self.allimgs, self.ally, newvec):\n self.fout.write('%s %d %d\\n' % (path, y, pred))","def save(self, file_name):\n logger.warning(\"save embeddings and name mappings to `%s`\" % file_name)\n\n objects = EasyDict()\n for name in dir(self.graph):\n object = getattr(self.graph, name)\n if isinstance(object, list) and len(object) > 0 and isinstance(object[0], str): # id2name\n objects[name] = object\n for name in dir(self.solver):\n object = getattr(self.solver, name)\n if isinstance(object, np.ndarray): # embedding\n objects[name] = object\n\n with open(file_name, \"wb\") as fout:\n pickle.dump(objects, fout, protocol=pickle.HIGHEST_PROTOCOL)","def set_recording_vectors(self, i):\n #soma_v_vec = h.Vector() # Membrane potential vector at soma\n setattr(self, 'soma_v_vec_' + str(i), h.Vector() )\n #dend_v_vec = h.Vector() # Membrane potential vector at dendrite\n setattr(self, 'dend_v_vec_' + str(i), h.Vector() )\n \n getattr(self, 'soma_v_vec_' + str(i)).record(self.cells[i].soma(0.5)._ref_v)\n neuron_utils.createStateVariable(id='v_vec_soma_' + str(i) , name='v_vec_soma_' + str(i) ,\n units='mV', python_variable={\"record_variable\": getattr(self, 'soma_v_vec_' + str(i)),\n \"segment\": self.cells[i].soma(0.5)})\n\n getattr(self, 'dend_v_vec_' + str(i)).record(self.cells[i].dend(0.5)._ref_v)\n neuron_utils.createStateVariable(id='v_vec_dend_' + str(i) , name='v_vec_dend_' + str(i) ,\n units='mV', python_variable={\"record_variable\": getattr(self, 'dend_v_vec_' + str(i)),\n \"segment\": self.cells[i].dend(0.5)})","def _call_writeVec(vecObj, filename, mode):\n res = vecObj.writeVec(filename, mode)\n return res","def creer_dictionnaire_vide():\n dico = {}\n return dico","def test_export(self):\n\n v = Vector({ 'x': 3 })\n e = v.to_array()\n self.assertEqual(v.attributes, Vector.from_array(e).attributes)\n self.assertEqual(v.dimensions, Vector.from_array(e).dimensions)\n self.assertEqual(v.__dict__, Vector.from_array(e).__dict__)","def _store(self):\n store_dict = {}\n for key in self._data:\n val = self._data[key]\n if SparseParameter._is_supported_matrix(val):\n serial_string = SparseParameter._serialize_matrix(val)\n store_dict[\"%s%s\" % (key, SparseParameter.IDENTIFIER)] = serial_string\n else:\n store_dict[key] = val\n\n return store_dict","def featurize(vector,features):\n dictionary = collections.defaultdict(lambda:0)\n for feature in iter(set(features)):\n dictionary[feature] = [vector[key][feature] if feature in vector[key] else 0 for key in vector] #populates vectors with zeroes where there's no value in an industry for an n-gram.\n return dictionary","def make_wordvec_dict(f_name, out_fname, threads):\n # Make list of unique words\n word_list = list(load_pickle(f_name))\n\n # Send job to workers\n per_f = int(len(word_list) / threads) + 1\n logging.info('Per Thread {}'.format(per_f))\n pool = mp.Pool(processes=threads)\n processes = [\n pool.apply_async(parallel_word_dict, args=(word_list, per_f * (x - 1), per_f * x)) for x in\n range(1, threads + 1)]\n\n # Get data and put it out\n output = [process.get() for process in processes]\n out_dict = {}\n for ele in output:\n out_dict = {**out_dict, **ele}\n pool.close()\n save_pickle(out_dict, out_fname)\n logging.info('Made Dictionary Using Spacy')","def exportFoldFile(vectors, authors, fileName):\n with open(fileName, \"w\") as fFile:\n for idv, vec in enumerate(vectors):\n [fFile.write(str(val)+',') for val in vec]\n fFile.write(authors[idv] + '\\n')","def make_vasp_defect_files(dictio, path_base, task_id, compo, hse=False):\n count=1\n for site in dictio:\n for charge in site['charges']:\n print charge\n for s in site['supercells']:\n dict_transf={'history':[{'source':task_id}], 'compo': compo.to_dict, 'defect_type': site['short_name'], 'defect_site': site['unique_sites'].to_dict, 'charge': charge, 'supercell': s['size']}\n dict_params=MPVaspInputSet().get_all_vasp_input(s['structure'])\n incar=dict_params['INCAR']\n incar['IBRION']=2\n incar['ISIF']=0\n incar['ISPIN']=1\n incar['LWAVE']=False\n #incar['EDIFF']=0.0001\n incar['EDIFF']=0.001\n incar['ISMEAR']=0\n incar['SIGMA']=0.05\n incar['LVHAR']=True\n incar['LORBIT']=11\n incar['ALGO']=\"Fast\"\n #incar['ALGO']=\"Normal\"\n if hse == True:\n incar['LHFCALC']=True\n incar[\"ALGO\"]=\"All\"\n incar[\"HFSCREEN\"]=0.2\n incar[\"PRECFOCK\"]=\"Fast\"\n incar[\"AEXX\"]=0.45\n kpoint=Kpoints.monkhorst_automatic()\n path=path_base+\"/\"+compo.reduced_formula+\"_\"+str(task_id)+\"/\"+str(site['short_name'])+\"/\"+\"charge\"+str(charge)+\"/\"\n os.makedirs(path)\n f=open(path+\"/transformations.json\",'w')\n f.write(json.dumps(dict_transf))\n comp=s['structure'].composition\n sum_elec=0\n elts=set()\n for p in dict_params['POTCAR']:\n if p.element not in elts:\n sum_elec+=comp.to_dict[p.element]*p.nelectrons\n elts.add(p.element)\n #print p.element\n #print comp.to_dict[p.element]\n #print p.valence\n print sum_elec\n if charge != 0:\n incar['NELECT']=sum_elec-charge\n dict_params['POTCAR'].write_file(path+\"POTCAR\")\n incar.write_file(path+\"INCAR\")\n kpoint.write_file(path+\"KPOINTS\")\n dict_params['POSCAR'].write_file(path+\"POSCAR\")\n #print Poscar(s['structure'])\n #Poscar(s['structure']).write_file(path+\"POSCAR\")\n count=count+1\n f.close()","def savez(d,file):\n np.savez(file,row=d.row,col=d.col,data=d.data,shape=d.shape)","def make_sol_dict():\n file_names = [\"FORMAT3_Copy of KommuneMTPLforTriangle.xls\",\n \"C Triangulations analysis R2017 GC20161109.xls\",\n \"EVOLUTION 2017 _ M+F - Triangles cat nat brut net.xls\",\n \"Bsp8 _ Dreiecke aus GCNA für CU1.4.1.xls\",\n \"Analysis MTPL MOD.xls\",\n \"Bsp6 _ Dreiecke aus GCNA für CU1.4.1.xls\",\n \"FORMAT6_sinistres.xls\",\n \"FORMAT1_LOSSES-MTPL-OVER-500-GROUP-2005_modified.xls\"]\n solutions_dict = dict()\n raw_dict = dict()\n for file_name in file_names:\n sr_list, file_name = ExcelLoader.load_excel(pdir.RESOURCES_DIR + \"/raw_test_files/\" + file_name)\n dh = DataHolder()\n for sr in sr_list:\n dh.add_sheet(sr.sheet_name, pd.DataFrame(columns=sr.headers, data=sr.row_vals),\n pd.DataFrame(columns=sr.headers, data=sr.xls_types), orig_sheet_name=sr.sheet_name)\n\n dh = SheetPreProcessor.separate_components(dh)\n raw_dict[file_name] = dh.encode()\n dh = HorizontalMerger.horizontal_merge(dh)\n #temp_path = pdir.RESOURCES_DIR + \"/temp/\"\n #dh.write_excel(temp_path + file_name)\n solutions_dict[file_name] = dh\n solutions_dict = MergePararametersOptimizer.make_ind_col_dict(solutions_dict)\n with open(pdir.RESOURCES_DIR + \"/test/merge_solutions.obj\", \"wb\") as temp_file:\n pickle.dump(solutions_dict, temp_file)\n with open(pdir.RESOURCES_DIR + \"/test/raw_test.obj\", \"wb\") as temp_file:\n pickle.dump(raw_dict, temp_file)","def test_export_attributes(self):\n\n v = Vector({ 'x': 3 }, { \"y\": True })\n e = v.to_array()\n self.assertEqual(v.attributes, Vector.from_array(e).attributes)\n self.assertEqual(v.__dict__, Vector.from_array(e).__dict__)","def save(self):\n if not os.path.exists(self.dictionary_save_path) and self.dictionary_save_path != \"\":\n os.makedirs(self.dictionary_save_path)\n with open(self.dictionary_save_path + \"dictionary\", 'w') as f:\n f.write(\"{}\\n\".format(len(self.dictionary)))\n\n for word in self.dictionary:\n f.write(\"{}\\t{}\\n\".format(self.dictionary[word]['id'], word))","def save(self) -> None:\n with open(dict_path, 'w', encoding='utf-8') as dictionary_file:\n json.dump(self.data, dictionary_file, indent=2, separators=(',', ':'), ensure_ascii=False)","def transform_word_vectors(self):\n print('Transforming word vectors')\n \n self.train_X_tfidfvec = self.get_word_vectors(self.train_X)\n self.val_X_tfidfvec = self.get_word_vectors(self.val_X)\n self.test_X_tfidfvec = self.get_word_vectors(self.test_X)\n if self.savename is not None:\n with open(self.savename + '_X_tfidfvec.obj','wb') as f:\n pickle.dump((self.train_X_tfidfvec,self.val_X_tfidfvec,self.test_X_tfidfvec),f) \n print('Done transforming word vectors')","def save(self,filepath):\n d = self.X.tocoo(copy=False)\n v = self.col_view.tocoo(copy=False)\n np.savez(filepath,row=d.row,col=d.col,data=d.data,shape=d.shape,\n v_row=v.row,v_col=v.col,v_data=v.data,v_shape=v.shape)","def extract_word2vec(fichier, words_indices): \n \n word2vec={} #\n \n #\n with open(fichier,\"r\",encoding=\"utf-8\") as file:\n for line in file:\n line = line.replace(\" \\n\",\"\").split(\" \")\n # Lecture des informations du fichier\n # nombre de mots presents et nombre de features\n if len(line)==2 :\n nb_words=int(line[0])\n nb_feats=int(line[1])\n \n #\n else:\n if line[0] in words_indices:\n word, vec = line[0],np.array(line[1:])\n word2vec[word]=vec\n\n print(\"{} embbedings de taille {} pertinent parmi les {} du fichier\".format(len(word2vec), nb_feats, nb_words))\n\n return word2vec, nb_feats","def to_file(self, fn):\n store.store_dict(fn, 'trainalgorithm', self.to_dict())","def Save(self, filename: str):\n data_object = {\n \"input_layer_count\" : self.input_layer_size,\n \"hidden_layer_count\" : self.hidden_layer_size,\n \"output_layer_count\" : self.output_layer_size,\n\n \"hidden_layer_biases\" : self.hidden_layer_biases.tolist(),\n \"output_layer_biases\" : self.output_layer_biases.tolist(),\n\n \"input_to_hidden_weights\" : self.input_to_hidden_weights.tolist(),\n \"hidden_to_output_weights\" : self.hidden_to_output_weights.tolist()\n }\n\n with open(filename, \"w\") as f:\n json.dump(data_object, f)","def make_total_dict_db(list_files):\n for i, file_name in enumerate(list_files):\n print('Processing file', file_name)\n db = make_dict_database(file_name)\n if not i:\n total_input = db['input']\n total_output = db['output']\n else:\n total_input = np.concatenate((total_input, db['input']))\n total_output = np.concatenate((total_output, db['output']))\n \n d = {'input' : total_input, 'output' : total_output} \n \n import cPickle as pickle\n pickle.dump(d, open('data/domino_main.db', \"w+\"))","def save_items(self, path):\n os.makedirs(path, exist_ok=True)\n np.save(os.path.join(path, 'ids'), self.item_ids)\n np.save(os.path.join(path, 'titles'), self.item_titles)\n np.save(os.path.join(path, 'embeddings'), self.item_vectors)\n np.save(os.path.join(path, 'categories'), self.item_categories)"],"string":"[\n \"def save_dict(emb, path_to_vec, dim=100):\\n word_vec = {}\\n for w in emb.keys():\\n word_vec[w] = emb[w]\\n with open(path_to_vec + f'embedding_{str(dim)}d.txt', 'w') as file:\\n for w, v in word_vec.items():\\n file.write(w + ' ')\\n for el in v:\\n file.write(\\\"{:.20f}\\\".format(float(el)) + ' ')\\n file.write('\\\\n')\",\n \"def construct_dict(self):\\n i = 0\\n self.word2idx = dict()\\n fi = open(self.config.word_vec_fi_glove, 'r')\\n\\n for line in fi:\\n self.word2idx[line.split(\\\" \\\")[0]] = i\\n i += 1\\n\\n self.vocab_size = i\\n self.write_dict()\\n fi.close()\",\n \"def load_dict(path_to_vec):\\n emb = {}\\n with open(path_to_vec, 'r', errors='ignore', encoding='utf8') as f:\\n for line in f:\\n values = line.split()\\n word = values[0]\\n vector = np.asarray(values[1:], \\\"float32\\\")\\n emb[word] = vector\\n return emb\",\n \"def dump_vecs():\\n v_file = os.path.join(TMP_DIR, 'vectorizer.pickle')\\n d_file = os.path.join(TMP_DIR, 'dectorizer.pickle')\\n f_file = os.path.join(TMP_DIR, 'freq.pickle')\\n \\n with open(v_file, 'wb') as f:\\n pickle.dump(VECTORIZER, f)\\n with open(d_file, 'wb') as f:\\n pickle.dump(CECTORIZER, f)\",\n \"def write_vectors(self, filename):\\n svu.write_realvectors(self,filename)\",\n \"def load_vector_dictionary():\\n return read_word2vecs_from_file(VECTOR_FILE)\",\n \"def write_vector(vector, outfile):\\r\\n out_dir = os.path.dirname(outfile)\\r\\n if not os.path.exists(out_dir):\\r\\n os.makedirs(out_dir)\\r\\n\\r\\n vector = vector.copy()\\r\\n for k in vector:\\r\\n if isinstance(vector[k], np.ndarray):\\r\\n vector[k] = vector[k].round(4).tolist()\\r\\n with open(outfile, 'w') as f:\\r\\n json.dump(vector, f)\\r\\n f.write('\\\\n')\\r\\n\\r\\n print(\\\" ... wrote {}\\\".format(outfile))\",\n \"def write_vector(vector, outfile):\\n out_dir = os.path.dirname(outfile)\\n if not os.path.exists(out_dir):\\n os.makedirs(out_dir)\\n\\n vector = vector.copy()\\n for k in vector:\\n if isinstance(vector[k], np.ndarray):\\n vector[k] = vector[k].round(4).tolist()\\n with open(outfile, 'w') as f:\\n json.dump(vector, f, separators=(',', ': '), indent=4)\\n f.write('\\\\n')\\n\\n print(\\\" ... wrote {}\\\".format(outfile))\",\n \"def _vector_mapping(self) -> dict:\\n words = set()\\n for file in os.listdir(self.processed_path):\\n doc_path = f\\\"{self.processed_path}/{file}\\\"\\n with open(doc_path, 'r') as f:\\n text_words = f.readline().split()\\n words = words.union(set(text_words))\\n words = list(words)\\n words.sort()\\n\\n return dict(zip(words, range(len(words))))\",\n \"def dump_w2vdictionary(outfilename,wordlist,matrix):\\n ostream = open(outfilename,'w')\\n print('%d %d'%(len(wordlist),matrix.shape[1]),file=ostream)\\n for word,vec in zip(wordlist,matrix):\\n print(' '.join([word]+ [ str(elt) for elt in vec]),file=ostream)\\n ostream.close()\",\n \"def save_class_representation(self):\\n class_dict = {}\\n for key, value in self.class_dict.items():\\n class_dict['-'.join(key)] = list(value)\\n with open('data/class_vectors.txt', 'w') as file:\\n json.dump(class_dict, file)\\n return class_dict\",\n \"def save_document_representations(reps, path):\\n file = h5py.File(path, 'w')\\n\\n for name, vector_dict in reps.items():\\n vectors = [vector_dict[i] for i in vector_dict.keys()]\\n file.create_dataset(name, data=vectors)\\n\\n file.close()\",\n \"def as_dict(self):\\r\\n return {self.words[i]: self.vectors[i] for i in range(self.n)}\",\n \"def getVectors(self):\\n vectors = dict()\\n i = 0\\n N = len(self.db.invertedIndex)\\n for w, (idf, docs) in self.db.invertedIndex.items():\\n for doc, tf in docs.items():\\n try:\\n vectors[doc][i] = tf * idf\\n except KeyError as k:\\n vectors[doc] = {i: tf * idf}\\n i += 1\\n i = 0;\\n return vectors\",\n \"def create_vector_dict(self):\\n return self.MOVE_DATA\",\n \"def create_vector_dict(self):\\n return self.MOVE_DATA\",\n \"def write_vecs(self, vecs_fname):\\r\\n header = f'{self.vectors.shape[0]} {self.vectors.shape[1]}'\\r\\n np.savetxt(vecs_fname, np.hstack([self.words.reshape(-1, 1), self.vectors]), fmt='%s', header=header)\",\n \"def gather_and_save_vectors(path, words_vec = collections.defaultdict(list), features = []):\\n with open(path, 'rt', encoding='mac_roman') as csvfile:\\n csvreader = csv.reader(csvfile, delimiter=' ', quotechar='\\\"')\\n for row in csvreader:\\n words_vec, features = countize(row[3], row[2], words_vec, features)\\n try:\\n words_vec, features = countize(row[6], row[2], words_vec, features)\\n except:\\n pass\\n pickle.dump(words_vec, open(\\\"ind_vectors.data\\\", \\\"wb\\\"))\\n pickle.dump(features, open(\\\"i_features.data\\\", \\\"wb\\\"))\\n return words_vec, features\",\n \"def save_vectorizer(self, vectorizer_filepath):\\n with open(vectorizer_filepath, \\\"w\\\") as fp:\\n json.dump(self._vectorizer.to_serializable(), fp)\",\n \"def new_counts_dict():\\n\\n\\tIN_FILES = [\\\"../_semtag_dataset_webanno_tfidf_inimigo.txt\\\",\\\"../_semtag_dataset_webanno_tfidf_publico.txt\\\" ]\\n\\n\\ttxt = []\\n\\tfor in_file in IN_FILES:\\n\\t with codecs.open(in_file,\\\"r\\\",\\\"utf-8\\\") as fid:\\n\\t txt += fid.readlines()\\n\\t#words\\n\\twords = [w for m in txt for w in m.split()]\\n\\t#unique words\\n\\twords = list(set(words))\\n\\t#word index\\n\\twrd2idx = {w:-1 for w in words}\\n\\n\\tset_trace()\\n\\t\\n\\twith open(COUNTS_DIC,\\\"w\\\") as fod:\\n\\t\\tcPickle.dump(wrd2idx, fod, cPickle.HIGHEST_PROTOCOL)\",\n \"def get_dict(self):\\n return {key: value for key, value in zip(self._words, self._vecs)}\",\n \"def saveGloveDicIntoFile(gloveDic):\\n \\n np.save(GLOVE_DICT_FILE, np.asarray([gloveDic]))\",\n \"def dictionary_saver(d, filename):\\n json_friendly_d = {json.dumps(k):v for k,v in d.items()}\\n sklearn.externals.joblib.dump(json_friendly_d, filename)\",\n \"def get_W(word_vecs, k=100,path='wordemb'):\\n vocab_size = len(word_vecs)\\n word_idx_map = dict()\\n W = np.zeros(shape=(vocab_size+1, k), dtype='float32')\\n W[0] = np.zeros(k, dtype='float32')\\n i = 1\\n f =open(path+'.word','w')\\n for word in word_vecs:\\n # print(\\\"#############################\\\")\\n # print(word_vecs[word].shape)\\n # print(word)\\n # print(W[i].shape)\\n # print(\\\"#############################\\\")\\n W[i] = word_vecs[word]\\n f.write(word+'\\\\n')\\n word_idx_map[word] = i\\n i += 1\\n np.savetxt(path+'.txt',W,fmt='%.7f', delimiter=' ')\\n f.close()\\n return W, word_idx_map\",\n \"def save_embeddings(self, filename, binary=True):\\n with open(filename, \\\"wb\\\", encoding=\\\"utf8\\\") as fout:\\n fout.write(\\\"%s %s\\\\n\\\" % self._vecs.shape)\\n # store in sorted order: most frequent words at the top\\n for i, word in enumerate(self._words):\\n row = self._vecs[i]\\n if binary:\\n fout.write(word + b\\\" \\\" + row.tostring())\\n else:\\n fout.write(\\n \\\"%s %s\\\\n\\\" % (word, \\\" \\\".join(\\\"%f\\\" % val for val in row))\\n )\",\n \"def dict2file(dict, filename, foldername):\\n if foldername:\\n if not os.path.exists(\\\"../Created_QD/\\\" + foldername):\\n os.makedirs(\\\"../Created_QD/\\\" + foldername)\\n file = open(\\\"../Created_QD/\\\" + foldername + \\\"/\\\" + filename + \\\".xyz\\\", \\\"w\\\")\\n else:\\n file = open(\\\"../Created_QD/\\\" + filename + \\\".xyz\\\", \\\"w\\\")\\n file.write(\\\" \\\\n\\\\n\\\")\\n for atom, values in dict.items():\\n file.write(values['element'] + \\\"\\\\t\\\" + str(values['coor'][0]) + \\\"\\\\t\\\\t\\\" +\\n str(values['coor'][1]) + \\\"\\\\t\\\\t\\\" + str(values['coor'][2]) + \\\"\\\\n\\\")\\n file.seek(0)\\n file.write(str(len(dict)))\\n file.close()\\n print(\\\"\\\\nQuantum Dot created :)\\\")\",\n \"def WriteFile( self ):\\n with open( \\\"BasisVector.in\\\" , \\\"w\\\" ) as outfile:\\n firstLine = \\\" \\\" + str( self.NQ ) + \\\\\\n \\\" \\\" + str( self.Nbranches ) + \\\\\\n \\\" \\\" + str( self.NatomsUC ) + \\\\\\n \\\" \\\" + str( self.dim ) + \\\"\\\\n\\\"\\n outfile.write( firstLine )\\n for qq in range( self.NQ ): ## loop over Q vectors\\n lineQ = [ \\\"{:15.8f}\\\".format( x ) for x in \\n self.QVectors[ qq , : ] ]\\n lineQ = \\\"\\\".join( lineQ )\\n outfile.write( lineQ + \\\"\\\\n\\\" )\\n for branch in range( self.Nbranches ): ## loop over branches\\n for atom in range( self.NatomsUC ): ## loop over atoms in unit cell\\n line = [ \\\"{:15.8f}\\\".format( x ) for x in \\n self.EigenVectors[ qq , branch , atom , : ] ]\\n line = \\\"\\\".join( line )\\n outfile.write( line + \\\"\\\\n\\\" )\\n outfile.write( \\\"\\\\n\\\" )\\n outfile.write( \\\"\\\\n\\\" )\",\n \"def compute_kappa_map(lens_vec, size, size_map):\\n\\n par_file_name = \\\"kappa_map.par\\\"\\n fit_file_name = \\\"kappa_map.fits\\\"\\n z_source = 2.0\\n size_map = size_map * 1.05\\n\\n file_map = open(par_file_name, 'w')\\n\\n conv_lens_vec(lens_vec)\\n\\n file_map.write(\\\"runmode\\\\n\\\" )\\n file_map.write(\\\" reference 3 0 0\\\\n\\\")\\n file_map.write(\\\" verbose 0\\\\n\\\" )\\n file_map.write(\\\" mass 3 \\\" + str(size) + \\\" \\\" + \\\\\\n str(lens_vec[0][\\\"z_lens\\\"]) + \\\" \\\" + fit_file_name + \\\"\\\\n\\\")\\n file_map.write(\\\" end\\\\n\\\")\\n file_map.write(\\\"source\\\\n\\\")\\n file_map.write(\\\" z_source \\\" + str(z_source) + \\\"\\\\n\\\")\\n file_map.write(\\\" end\\\\n\\\")\\n file_map.write(\\\"grille\\\\n\\\")\\n file_map.write(\\\" nombre 128\\\\n\\\")\\n file_map.write(\\\" nlens 4\\\\n\\\")\\n file_map.write(\\\" nlens_crit 1\\\\n\\\")\\n file_map.write(\\\" nlens_opt 0\\\\n\\\")\\n file_map.write(\\\" polaire 1\\\\n\\\")\\n file_map.write(\\\" end\\\\n\\\")\\n\\n\\n for i in range(len(lens_vec)):\\n string_out = 'potential ' + str(i) + '\\\\n'\\n file_map.write(string_out)\\n #print string_out,\\n for keys in lens_vec[i].keys():\\n string_out = ' ' + keys + ' ' + str(lens_vec[i][keys]) + \\\\\\n '\\\\n'\\n #print string_out,\\n file_map.write(string_out)\\n file_map.write(' end\\\\n')\\n\\n file_map.write(\\\"cosmology\\\\n\\\")\\n file_map.write(\\\" H0 70.0\\\\n\\\")\\n file_map.write(\\\" omega 0.3\\\\n\\\")\\n file_map.write(\\\" lambda 0.7\\\\n\\\")\\n file_map.write(\\\" end\\\\n\\\")\\n file_map.write(\\\"champ\\\\n\\\")\\n file_map.write(\\\" xmin -101\\\\n\\\")\\n file_map.write(\\\" xmax 100\\\\n\\\")\\n file_map.write(\\\" ymin -101\\\\n\\\")\\n file_map.write(\\\" ymax 100\\\\n\\\")\\n file_map.write(\\\" dmax \\\" + str(size_map) + \\\"\\\\n\\\")\\n file_map.write(\\\" end\\\\n\\\")\\n file_map.write(\\\"fini\\\\n\\\")\\n\\n file_map.close()\",\n \"def serialize_box_vectors(box_vectors, to_file=''):\\n assert box_vectors is not None\\n xmlBox_vectors = ET.Element('box_vectors')\\n box_vectors_unitless = box_vectors.value_in_unit(nanometer)\\n xmlA = ET.SubElement(xmlBox_vectors, 'A')\\n xmlAx = ET.SubElement(xmlA, 'x')\\n xmlAx.text = str(box_vectors_unitless[0][0])\\n xmlAy = ET.SubElement(xmlA, 'y')\\n xmlAy.text = str(box_vectors_unitless[0][1])\\n xmlAz = ET.SubElement(xmlA, 'z')\\n xmlAz.text = str(box_vectors_unitless[0][2])\\n xmlB = ET.SubElement(xmlBox_vectors, 'B')\\n xmlBx = ET.SubElement(xmlB, 'x')\\n xmlBx.text = str(box_vectors_unitless[1][0])\\n xmlBy = ET.SubElement(xmlB, 'y')\\n xmlBy.text = str(box_vectors_unitless[1][1])\\n xmlBz = ET.SubElement(xmlB, 'z')\\n xmlBz.text = str(box_vectors_unitless[1][2])\\n xmlC = ET.SubElement(xmlBox_vectors, 'C')\\n xmlCx = ET.SubElement(xmlC, 'x')\\n xmlCx.text = str(box_vectors_unitless[2][0])\\n xmlCy = ET.SubElement(xmlC, 'y')\\n xmlCy.text = str(box_vectors_unitless[2][1])\\n xmlCz = ET.SubElement(xmlC, 'z')\\n xmlCz.text = str(box_vectors_unitless[2][2])\\n \\n xmlstr = minidom.parseString(ET.tostring(xmlBox_vectors)).toprettyxml(\\n indent=\\\" \\\")\\n \\n if to_file:\\n our_file=open(to_file, 'w')\\n our_file.write(xmlstr)\\n our_file.close()\\n \\n return xmlstr\",\n \"def _dump_interest_vector(self, user_id: int,\\n vector_name: str,\\n vector: Dict[int, int]) -> None:\\n\\n key = self._key_format.format(id=user_id, name=vector_name)\\n self._redis.hmset(key, vector)\",\n \"def save_vectors (feat_vec = None, labels = None, file_extension = None):\\n\\n feat_file_name = 'output/' + file_extension + '.feature'\\n label_file_name = 'output/' + file_extension + '.label'\\n\\n prettyPrint('Saving feature vector file: {0} ... \\\\n'\\n 'Saving Labels file: {1} ... '.format(feat_file_name, label_file_name), color.CYAN)\\n\\n #Save feature vector to disk\\n with open(feat_file_name, 'w') as f:\\n pickle.dump(feat_vec, f)\\n #Save label file\\n with open(label_file_name, 'w') as f:\\n pickle.dump(labels, f)\",\n \"def vector_to_dict(self, vector, original_dictionary):\\n new_dictionary = {}\\n current_index = 0\\n for key,item in original_dictionary.items():\\n new_index = current_index + item.size\\n new_dictionary[f'{key}'] = np.reshape(vector[current_index:new_index],item.shape)\\n current_index = new_index\\n return new_dictionary\",\n \"def _extractGloveVects():\\n \\n embeddings_index = {}\\n\\n with open(GLOVE_CORPUS_FILE) as f:\\n for line in f:\\n values = line.split()\\n word = values[0].lower()\\n if word not in _cachedStopWords:\\n coefs = np.asarray(values[1:], dtype='float32')\\n embeddings_index[word] = coefs\\n\\n return embeddings_index\",\n \"def get_glove_dictionary(self, file_path=\\\"./glove.twitter.27B.25d.txt\\\"):\\n file = open(file_path, \\\"r\\\",encoding='utf-8')\\n dictionary = {}\\n keys = []\\n for word_vector in file:\\n dictionary[word_vector.split()[0]] = word_vector.split()[1:]\\n keys.append(word_vector.split()[0])\\n file.close()\\n\\n file = open(\\\"./Glove_dict.txt\\\", \\\"a\\\",encoding='utf-8')\\n for word in keys:\\n file.write(word + '\\\\n')\\n file.close()\",\n \"def write_mat_file(self):\\n mat_dict = {}\\n mat_dict['Lx_p'] = self.Lx_p\\n mat_dict['Ly_p'] = self.Ly_p\\n mat_dict['Lz_p'] = self.Lz_p\\n mat_dict['Lo'] = self.obst.get_Lo()\\n mat_dict['Ny_divs'] = self.N_divs\\n mat_dict['rho_p'] = self.rho_p\\n mat_dict['nu_p'] = self.nu_p\\n mat_dict['snl'] = list(np.union1d(self.obst_list[:],self.solid_list[:]))\\n mat_dict['inl'] = list(self.inlet_list[:])\\n mat_dict['onl'] = list(self.outlet_list[:])\\n\\n scipy.io.savemat('geometry_description',mat_dict)\",\n \"def export(self, outpath):\\n fout = open(outpath, \\\"w\\\")\\n\\n # Header takes the guesswork out of loading by recording how many lines, vector dims\\n fout.write(str(self.n_words) + \\\" \\\" + str(self.n_dim) + \\\"\\\\n\\\")\\n for token in self.id2word:\\n vector_components = [\\\"%.6f\\\" % number for number in self[token]]\\n vector_as_string = \\\" \\\".join(vector_components)\\n\\n out_line = token + \\\" \\\" + vector_as_string + \\\"\\\\n\\\"\\n fout.write(out_line)\\n\\n fout.close()\",\n \"def vec_to_dict(docVec):\\n return {dimension:value for dimension, value in enumerate(docVec)}\",\n \"def save_to_file(self, filename):\\n outMap = {}\\n for kanal in self._datastoreMap:\\n # svaki pojedini Datastore se zna zapakirati u mapu (dictionary)\\n outMap[kanal] = self._datastoreMap[kanal].store2dict()\\n # serialize u binary string\\n binstr = pickle.dumps(outMap)\\n # zapis u file\\n with open(filename, 'wb') as f:\\n f.write(binstr)\",\n \"def write_features(self):\\r\\n def pack_keypoint(keypoints, descriptors):\\r\\n kpts = np.array([[kp.pt[0], kp.pt[1], kp.size,\\r\\n kp.angle, kp.response, kp.octave,\\r\\n kp.class_id]\\r\\n for kp in keypoints])\\r\\n desc = np.array(descriptors)\\r\\n return kpts, desc\\r\\n\\r\\n filename = self.features_path + self.id\\r\\n kpts, desc = pack_keypoint(self.keypoints, self.descriptors)\\r\\n logging.info(f'Writing features of image {self.name} to file...')\\r\\n np.savez(filename, keypoints=kpts, descriptors=desc)\\r\\n logging.info('Features saved.')\",\n \"def makeDictionary(self):\\n self.dictionary = {}\\n for i in range(len(self.movie)):\\n if self.movie[i] in self.dictionary:\\n vectors = self.dictionary[self.movie[i]]\\n vectors[self.user[i]] = self.rating[i]\\n self.dictionary[self.movie[i]] = vectors\\n else:\\n newMovie = dict([(self.user[i], self.rating[i])])\\n self.dictionary[self.movie[i]] = newMovie\\n return self.dictionary\",\n \"def write_vocabulary():\\n with open('../data/vocabulary.txt', 'w') as vocabulary_file:\\n vocabulary = generate_vocabulary()\\n word_count = sum(vocabulary.values())\\n print(word_count)\\n vocabs_str = [(\\\"%s %d\\\" % (key, value)) for key, value in vocabulary.items()]\\n vocabulary_file.write('\\\\n'.join(vocabs_str))\",\n \"def save(self, dirname=None):\\n self.genio.save(dirname)\\n logging.info(\\n f'Saved word vectorizations for {dirname}')\",\n \"def file_to_dictionary():\\n\\n return;\",\n \"def load_glove_vectors(filename, vocab):\\n dct = {}\\n vectors = array.array('d')\\n current_idx = 0\\n with open(filename, \\\"r\\\", encoding=\\\"utf-8\\\") as f:\\n for _, line in enumerate(f):\\n tokens = line.split(\\\" \\\")\\n word = tokens[0]\\n entries = tokens[1:]\\n if not vocab or word in vocab:\\n dct[word] = current_idx\\n vectors.extend(float(x) for x in entries)\\n current_idx += 1\\n word_dim = len(entries)\\n num_vectors = len(dct)\\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]\",\n \"def make_dict_database(file_name):\\n f = h5py.File(file_name,'r')\\n\\n num_games = len(f.keys())\\n db = {'input' : np.zeros((num_games, 181)), 'output' : np.zeros((num_games, 2))}\\n for i, g in enumerate(f.keys()):\\n db['input'][i] = f[g]['input'][:]\\n db['output'][i] = f[g]['win_probs'][:]\\n \\n return db\",\n \"def load_bin_vec(filename):\\n w2v = {}\\n with open(filename, 'r') as f:\\n header = f.readline()\\n vocab_size, emb_size = map(int, header.split())\\n for line in f:\\n cline = line.split()\\n w2v[cline[0]] = np.array(cline[1:], dtype=np.float64)\\n return w2v, emb_size, vocab_size\",\n \"def create_sample_vectors(cleaned_data_directory, out_vectors_path):\\n vectors = []\\n\\n for filename in os.listdir(cleaned_data_directory):\\n if not filename.endswith(\\\".txt\\\"):\\n continue\\n\\n path = os.path.join(cleaned_data_directory, filename)\\n f = open(path, mode='r', encoding='utf8')\\n\\n print(\\\"Processing\\\", path)\\n\\n lang = filename[:2]\\n lang_number = language_codes.index(lang)\\n\\n print(f\\\"\\\\tLanguage: {lang} ({lang_number})\\\")\\n print(\\\"\\\\tReading...\\\", end=' ')\\n\\n file_content = f.read()\\n content_length = len(file_content)\\n\\n print(\\\"done.\\\")\\n print(\\\"\\\\tExtracting vectors...\\\", end=' ')\\n\\n sample_start_index = 0\\n count = 0\\n\\n while sample_start_index + text_sample_size < content_length:\\n sample = get_sample(file_content, sample_start_index, text_sample_size)\\n input_vector = build_input_vector(sample)\\n vector = input_vector + [lang_number]\\n vectors.append(vector)\\n sample_start_index += text_sample_size\\n count += 1\\n\\n print(\\\"done.\\\")\\n print(f\\\"\\\\tExtracted {count} vectors.\\\")\\n\\n del file_content\\n\\n print(f\\\"Total {len(vectors)} vectors.\\\")\\n\\n np_vectors = np.array(vectors, dtype=np.uint16)\\n np.random.shuffle(np_vectors)\\n\\n print(f\\\"Converted to NumPy array, shape: {np_vectors.shape}.\\\")\\n\\n np.savez_compressed(out_vectors_path, data=np_vectors)\\n\\n print(f\\\"Saved to {out_vectors_path}.\\\")\",\n \"def save(self, filename):\\n data = {\\\"sizes\\\": self.sizes,\\n \\\"weights\\\": [w.tolist() for w in self.weights],\\n \\\"biases\\\": [b.tolist() for b in self.biases]}\\n f = open(filename, \\\"w\\\")\\n json.dump(data, f)\\n f.close()\",\n \"def _generate_vector(article, save=False):\\n tf = term_frequency.get_vector(article)\\n vector = generate_vector(article['body'], tf)\\n if save:\\n if not os.path.isdir(os.path.join(os.path.dirname(__file__), './tf_idfs')):\\n os.mkdir(os.path.join(os.path.dirname(__file__), './tf_idfs'))\\n print(\\\"Created directory to store tf_idfs.\\\")\\n with open(_tf_idf_path(article['id']), 'w') as json_file:\\n json.dump(vector, json_file)\\n return vector\",\n \"def save(self):\\n \\n with open(os.path.join(self.output_dir, 'terms.dict'), 'wb') as f:\\n pkl.dump(self.term_id_map, f)\\n with open(os.path.join(self.output_dir, 'docs.dict'), 'wb') as f:\\n pkl.dump(self.doc_id_map, f)\",\n \"def load_vectors(self, weights_path: str) -> dict:\\n vectors = {}\\n for file in os.listdir(weights_path):\\n v_path = f\\\"{weights_path}/{file}\\\"\\n res = re.search(\\\"(.+).npy\\\", v_path)\\n # filename without extension\\n if res:\\n filename = res.group(1)\\n\\n vectors[filename] = np.load(v_path)\\n\\n return vectors\",\n \"def save_data(self, **kwargs):\\n\\n file = kwargs['file']\\n with open(file, 'w') as data_file:\\n for item in self._items.values():\\n data_string = '{'\\n item_dict = item.to_dict()\\n\\n for key, value in item_dict.items():\\n data_string += f'\\\"{key}\\\":\\\"{value}\\\",'\\n\\n data_string = data_string[:-1]\\n data_string += '}\\\\n'\\n data_file.write(data_string)\",\n \"def create_dicts():\\n load_data_for_dict('data/atis/train/seq.in', 'data/atis/voc/vocabulary.json')\\n load_data_for_dict('data/atis/valid/seq.in', 'data/atis/voc/vocabulary.json')\\n load_data_for_dict('data/atis/test/seq.in', 'data/atis/voc/vocabulary.json') \\n load_data_for_dict('data/atis/train/seq.out', 'data/atis/voc/slot_vocabulary.json')\",\n \"def save_serendipity_dic(y, filename):\\n store = pd.io.pytables.HDFStore(y)\\n mat = store.matrix\\n store.close()\\n n = len(mat.columns)\\n ser = 1 - mat.sum(axis=1) / n\\n\\n f = open(filename, \\\"w\\\")\\n cPickle.dump(ser.to_dict(), f, protocol=2)\\n f.close()\",\n \"def create_vectors(list_dict, num_words):\\n x = [] # list that will hold data \\n\\n for d in list_dict:\\n # initializing numpy vector\\n # it contains 5,000 (number of words) zeros\\n temp = np.zeros(num_words, dtype=np.float64)\\n for key, val in d.items():\\n if key < num_words:\\n key -= 1 # indexing in data starts at 1\\n temp[key] = 1 # adding word and its frequency to vector \\n # temp[key] = val\\n x.append(temp) # appends vector to x \\n\\n return x\",\n \"def build_doc_sense_vec(self):\\n\\t\\twith codecs.open(self.vocab_file, encoding='utf-8', mode='r') as infile:\\n\\t\\t\\tline = infile.readline()\\n\\t\\t\\ti = 0\\n\\t\\t\\twhile line:\\n\\t\\t\\t\\tword = line.split()[0]\\n\\t\\t\\t\\tif not self.word2IdVocabulary.has_key(word):\\n\\t\\t\\t\\t\\t# print i, word\\n\\t\\t\\t\\t\\t# else:\\n\\t\\t\\t\\t\\tself.word2IdVocabulary[word] = i\\n\\t\\t\\t\\tif not self.id2WordVocabulary.has_key(i):\\n\\t\\t\\t\\t\\tself.id2WordVocabulary[i] = word\\n\\t\\t\\t\\tline = infile.readline()\\n\\t\\t\\t\\ti += 1\\n\\t\\t\\tself.vocab_num = len(self.word2IdVocabulary)\\n\\t\\t\\tprint \\\"vocabulary number:\\\" + str(self.vocab_num)\\n\\n\\t\\twith codecs.open(self.vec_file, encoding='utf-8', mode='r') as vecfile:\\n\\t\\t\\twith codecs.open(self.vec_out_file, encoding='utf-8', mode='a+') as vec_outfile:\\n\\n\\t\\t\\t\\tfor i, line in enumerate(vecfile):\\n\\t\\t\\t\\t\\tif i % 10000 == 0:\\n\\t\\t\\t\\t\\t\\tprint i\\n\\t\\t\\t\\t\\t# if i > 72:\\n\\t\\t\\t\\t\\t# \\tbreak\\n\\t\\t\\t\\t\\tif i == 0:\\n\\t\\t\\t\\t\\t\\ta, b, c = map(int, line.split()[:3])\\n\\t\\t\\t\\t\\t\\tprint('Number of sememes: {}\\\\n'\\n\\t\\t\\t\\t\\t\\t\\t 'Number of words: {}\\\\n'\\n\\t\\t\\t\\t\\t\\t\\t 'Dimension of vectors: {}'.format(a, b, c))\\n\\t\\t\\t\\t\\telif i > 462667:\\n\\t\\t\\t\\t\\t\\tsline = line.strip('\\\\n').split()\\n\\t\\t\\t\\t\\t\\tword = sline[0]\\n\\t\\t\\t\\t\\t\\tvector_list = []\\n\\t\\t\\t\\t\\t\\tvector_list.append(sline[1:])\\n\\t\\t\\t\\t\\t\\tvector_array = np.array(vector_list)\\n\\t\\t\\t\\t\\t\\tword_id = self.word2IdVocabulary[word]\\n\\t\\t\\t\\t\\t\\tif not self.vectors.has_key(word_id):\\n\\t\\t\\t\\t\\t\\t\\tself.vectors[word_id] = vector_array\\n\\t\\t\\t\\t\\t\\t# vector_mean = np.mean(vector_array, axis=0)\\n\\t\\t\\t\\t\\t\\tif not self.vector_mean.has_key(word_id):\\n\\t\\t\\t\\t\\t\\t\\tself.vector_mean[word_id] = vector_array\\n\\t\\t\\t\\t\\t\\t# vec_outfile.write(line)\\n\\t\\t\\t\\t\\telif i > 462887:\\n\\t\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\tsline = line.strip('\\\\n').split()\\n\\t\\t\\t\\t\\t\\tword = sline[0]\\n\\t\\t\\t\\t\\t\\tsense_num = int(sline[1])\\n\\t\\t\\t\\t\\t\\tvectors = sline[2:sense_num*c+2] # (sense_num*c+2)\\n\\t\\t\\t\\t\\t\\tvector_list = []\\n\\t\\t\\t\\t\\t\\tfor start in range(0, len(vectors), c):\\n\\t\\t\\t\\t\\t\\t\\tvector_list.append(list(map(float, vectors[start: start+c])))\\n\\t\\t\\t\\t\\t\\tvector_array = np.array(vector_list)\\n\\t\\t\\t\\t\\t\\tword_id = self.word2IdVocabulary[word]\\n\\t\\t\\t\\t\\t\\tif not self.vectors.has_key(word_id):\\n\\t\\t\\t\\t\\t\\t\\tself.vectors[word_id] = vector_array\\n\\t\\t\\t\\t\\t\\tvector_mean = np.mean(vector_array, axis=0)\\n\\t\\t\\t\\t\\t\\tif not self.vector_mean.has_key(word_id):\\n\\t\\t\\t\\t\\t\\t\\tself.vector_mean[word_id] = vector_mean\\n\\t\\t\\t\\t\\t\\t'''j = 0\\n\\t\\t\\t\\t\\t\\tfor each_sense_vec in vector_array:\\n\\t\\t\\t\\t\\t\\t\\tif len(vector_array) > 1:\\n\\t\\t\\t\\t\\t\\t\\t\\tnew_line = word + '_' + str(j) + ' ' + np.array2string(each_sense_vec, max_line_width=2000,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tformatter={'float_kind': lambda x: '%6f' % x})[1:-1] + '\\\\n'\\n\\t\\t\\t\\t\\t\\t\\t\\tj += 1\\n\\t\\t\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\t\\t\\tnew_line = word + ' ' + np.array2string(each_sense_vec, max_line_width=2000,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t formatter={'float_kind': lambda\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t x: '%6f' % x})[1:-1] + '\\\\n'\\n\\n\\t\\t\\t\\t\\t\\t\\tvec_outfile.write(new_line)'''\\n\\n\\t\\twith codecs.open(self.doc_file, encoding='utf-8', mode='r') as docfile:\\n\\t\\t\\twith codecs.open(self.doc_out_file, encoding='utf-8', mode='a+') as doc_outfile:\\n\\t\\t\\t\\twith codecs.open(self.vec_out_file_bydoc, encoding='utf-8', mode='a+') as vec_outfile_bydoc:\\n\\t\\t\\t\\t\\tprint \\\"Processing document file......\\\"\\n\\t\\t\\t\\t\\tline = docfile.readline().strip('\\\\n')\\n\\t\\t\\t\\t\\twhile line:\\n\\t\\t\\t\\t\\t\\twords = line.split()\\n\\t\\t\\t\\t\\t\\tnew_words = [x for x in words]\\n\\t\\t\\t\\t\\t\\tfor i in range(len(words)):\\n\\t\\t\\t\\t\\t\\t\\tword_id = self.word2IdVocabulary[words[i]]\\n\\t\\t\\t\\t\\t\\t\\tsense_vecs = self.vectors[word_id]\\n\\t\\t\\t\\t\\t\\t\\tsense_num = len(sense_vecs)\\n\\t\\t\\t\\t\\t\\t\\tif sense_num > 1:\\n\\t\\t\\t\\t\\t\\t\\t\\tcontext_words = []\\n\\t\\t\\t\\t\\t\\t\\t\\tfor x in range(i-int(self.context_num), i+int(self.context_num)+1):\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tif x != i and 0 <= x < len(words):\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tcontext_words.append(words[x])\\n\\t\\t\\t\\t\\t\\t\\t\\tsense_index = self.select_attention(context_words, sense_vecs)\\n\\t\\t\\t\\t\\t\\t\\t\\tword_vec_i = sense_vecs[sense_index]\\n\\t\\t\\t\\t\\t\\t\\t\\tnew_wordi = words[i] + '_' + str(sense_index)\\n\\t\\t\\t\\t\\t\\t\\t\\tself.vector_word_doc[new_wordi.encode('utf-8')] = word_vec_i\\n\\t\\t\\t\\t\\t\\t\\t\\tnew_words[i] = new_wordi\\n\\n\\t\\t\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\t\\t\\tword_vec_i = sense_vecs[0]\\n\\t\\t\\t\\t\\t\\t\\t\\tself.vector_word_doc[words[i].encode('utf-8')] = word_vec_i\\n\\t\\t\\t\\t\\t\\t\\tvec_outfile_bydoc.write(new_words[i] + ' ' + np.array2string(word_vec_i, max_line_width=2000,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t formatter={'float_kind': lambda x: '%6f' % x})[1:-1] + '\\\\n')\\n\\n\\t\\t\\t\\t\\t\\tdoc_outfile.write(' '.join(new_words) + '\\\\n')\\n\\n\\t\\t\\t\\t\\t\\tline = docfile.readline()\\n\\n\\t\\treturn self.vector_word_doc\",\n \"def save_vec(vec, h5file, slab, name):\\n atom = tables.Atom.from_dtype(vec.dtype)\\n ca = h5file.create_carray(slab, name, atom, vec.shape)\\n ca[:] = vec\",\n \"def create_vocabulary(sentences, path):\\n print('creating vocab..')\\n\\n word_dict = dict(); vocabulary = dict()\\n for sentence in sentences:\\n for word in nltk.word_tokenize(sentence):\\n if word not in word_dict:\\n word_dict[word] = ''\\n word_dict['<s>'] = ''\\n word_dict['</s>'] = ''\\n\\n with open(path, encoding=\\\"utf8\\\") as f:\\n for line in f:\\n word, vec = line.split(' ', 1)\\n if word in word_dict:\\n vocabulary[word] = np.fromstring(vec, sep=' ')\\n\\n print('vocabulary was created successfully!')\\n return vocabulary\",\n \"def store_model_poses(self, model_name, file_to_store=\\\"poses.yaml\\\" ):\\n \\n with open(file_to_store, 'w') as outfile:\\n\\n #inizializzo il dict vuoto con chiave models e value lista vuota\\n\\n dict_in = dict(models = [])\\n\\n now_dict = dict_in\\n\\n el_listaURDF = self.get_square_pose()\\n now_dict[\\\"models\\\"].append(el_listaURDF) #sostituire con now_dict\\n rospy.loginfo(\\\"now_dict URDF inizializzato\\\")\\n\\n # aggiorno il dizionario con tutti gli elementi presenti nella lista\\n for robot_name in model_name :\\n\\n now_pose = self.get_pose_of_model(robot_name)\\n el_lista = self.reformat_pose_to_dict(now_pose) #ritorna un dizionario che sarà elemento della lista\\n now_dict[\\\"models\\\"].append(el_lista) #eseguo l'append nella lista di models\\n \\n rospy.loginfo(\\\"now_dict sdf inizializzati\\\")\\n \\n # una volta inizializzati i models sdf posso scrivere nel file .yaml anche la posizione in cui deve essere spawnata l urdf\\n # devo creare l'ultimo elemento dict della lista e fare l'append alla lista che andrà in scrittura\\n\\n \\\"\\\"\\\"\\n {\\\"name\\\" : \\\"ferrari\\\" , \\n \\\"type\\\" : \\\"urdf\\\" , \\n \\\"package\\\" : \\\"autopark\\\" , \\n \\\"pose \\\":self.seq(lista_parametri) \\n }\\n \\n \\\"\\\"\\\"\\n \\n\\n # Scrittura su file .yaml\\n \\n yaml = ruamel.yaml.YAML()\\n yaml.indent(mapping=3, sequence=4, offset=2) #comando per indentare correttamente come nel file spawn_obj\\n yaml.dump(now_dict, sys.stdout) #comando per stampare nella shell per visualizzare il corretto formato\\n \\n yaml.dump(now_dict, outfile) #comando che stampa all'interno del file .yaml\\n\\n rospy.loginfo(\\\"numero auto sdf spawnate : \\\" + str(len(now_dict[\\\"models\\\"])-1))\",\n \"def save_to_file():\\n dict_from_file.update(temp_dict)\\n plik=open('data.txt', 'w')\\n for key in dict_from_file.keys():\\n plik.write(key)\\n plik.write(\\\" \\\")\\n plik.write(str(dict_from_file[key][0]))\\n plik.write(' ')\\n plik.write(dict_from_file[key][1].replace(' ','_'))\\n plik.write(' ')\\n plik.write(str(dict_from_file[key][2]))\\n plik.write('\\\\n')\",\n \"def build_vocab(sentences_list, vocab_size, visual_fld):\\n words = [word for sentence in sentences_list for word in sentence]\\n utils.safe_mkdir(visual_fld)\\n with open(os.path.join(visual_fld, 'vocab.tsv'), 'w') as fd:\\n dictionary = {}\\n index_dictionary = {}\\n count = [('UNK', -1)]\\n count.extend(Counter(words).most_common(vocab_size - 1))\\n for index, (word, _) in enumerate(count):\\n dictionary[word] = index\\n index_dictionary[index] = word\\n fd.write(word + '\\\\n')\\n\\n return dictionary, index_dictionary\",\n \"def creating_feature_vector():\\r\\n\\twordlist = []\\r\\n\\tlabel = \\\"\\\"\\r\\n\\tfw = open(\\\"feature_vector.txt\\\", \\\"w+\\\", encoding = \\\"utf-8\\\")\\r\\n\\twith open(\\\"D:\\\\\\\\Python_Prac\\\\\\\\wordstag\\\\\\\\modules\\\\\\\\HI_EN_TRAIN.txt\\\", \\\"r\\\", encoding = \\\"utf-8\\\") as f:\\r\\n\\t\\tfor line in f:\\r\\n\\t\\t\\twordlist.append(line)\\r\\n\\t\\tfor index, line in enumerate(wordlist):\\r\\n\\t\\t\\tif line == \\\"\\\\n\\\":\\r\\n\\t\\t\\t\\tcontinue\\r\\n\\t\\t\\tcontext = line.split(\\\"\\\\t\\\")\\r\\n\\t\\t\\tlabel = context[1]\\r\\n\\t\\t\\tfeature_vector = label+\\\" \\\"\\r\\n\\t\\t\\tngram_vector = ngram_frequency(str(context[0]))\\r\\n\\t\\t\\tfor vector in ngram_vector:\\r\\n\\t\\t\\t\\tfeature_vector += str(vector)+\\\" \\\"\\r\\n\\t\\t\\tfeature_vector += str(is_english(context[0]))+\\\" \\\"\\r\\n\\t\\t\\tfeature_vector += str(is_hindi(context[0]))+\\\" \\\"\\r\\n\\t\\t\\tfeature_vector += str(is_abbr(context[0]))+\\\" \\\"\\r\\n\\t\\t\\tfeature_vector += str(med_in_english(context[0]))+\\\" \\\"\\r\\n\\t\\t\\tfeature_vector += str(med_in_hindi(context[0]))+\\\" \\\"\\r\\n\\t\\t\\tbefore = [0,0,0]\\r\\n\\t\\t\\tafter = [0,0,0]\\r\\n\\t\\t\\tfor i in range(3):\\r\\n\\t\\t\\t\\tif (index-i) < 0 or (index-i+1) > len(wordlist)-1:\\r\\n\\t\\t\\t\\t\\tcontinue\\r\\n\\t\\t\\t\\tbefore[2-i] = get_word_context(wordlist[index-i+1].split(\\\"\\\\t\\\")[0])\\r\\n\\t\\t\\tfor i in range(3):\\r\\n\\t\\t\\t\\tif (index+i+1) > len(wordlist)-1:\\r\\n\\t\\t\\t\\t\\tcontinue\\r\\n\\t\\t\\t\\tafter[2-i] = get_word_context(wordlist[index+i+1].split(\\\"\\\\t\\\")[0])\\r\\n\\t\\t\\tfor i in before:\\r\\n\\t\\t\\t\\tfeature_vector += str(i)+\\\" \\\"\\r\\n\\t\\t\\tfor i in after:\\r\\n\\t\\t\\t\\tfeature_vector += str(i)+\\\" \\\"\\r\\n\\t\\t\\tfeature_vector += \\\"\\\\n\\\"\\r\\n\\t\\t\\tfw.write(feature_vector)\\r\\n\\t\\t\\tprint(\\\"Proceeding...\\\"+str(index+1)+\\\" of 16683\\\")\\r\\n\\r\\n\\tfw.close()\",\n \"def get_label_vectors():\\n print(\\\"Retrieving label vectors...\\\")\\n label_dict = {} # instantiate dict for labels:vectors\\n categories = sorted([c for c in os.listdir('images/') if c[0] != '.']) # ignore hidden files\\n x = np.zeros(len(categories)) # zero vector of number of categories\\n for i, c in enumerate(categories): # get index and category for images\\n y = x.copy() # use copy of x\\n y[i] = 1 # set label index to true\\n label_dict[c] = y.copy() # create label:vector\\n\\n return label_dict\",\n \"def make_vectors_output(coord_dict, add_vectors, num_coords, color, ids, display_name='trace', state='on'):\\n # default parameters\\n which_set = 0\\n tip_fraction = 0.5\\n arrow_colors = {'line_color': color, 'head_color': color}\\n \\n # header for section in kin file\\n result = []\\n result.append('@vectorlist {%s} dimension=%s %s' % (display_name, num_coords, state))\\n \\n # selecting the edges to draw in this batch\\n edges = []\\n for k, v in add_vectors['vectors'].iteritems():\\n edges = edges + [(v[i][1],v[i+1][1]) for i in range(len(v[:-1])) if v[i][1] in ids]\\n \\n # creating \\\"vectors\\\"\\n for edge in edges:\\n id_fr, id_to = edge\\n # extract the coords of each vertex\\n pt_fr = coord_dict[id_fr][:num_coords]\\n pt_to = coord_dict[id_to][:num_coords]\\n\\n # different tip color for each destination coords file\\n #tip_color = kinemage_colors[which_set % len(kinemage_colors)]\\n # plot a color 'tip' on the line (certain % of line length)\\n # this gets the coords of the beginning of the 'tip'\\n diffs = (pt_to-pt_fr) * (1-tip_fraction)\\n middles = pt_fr + diffs\\n # add a default-color line segment\\n \\n # modified to use user defined\\n tip_color = arrow_colors['head_color']\\n label_color = arrow_colors['line_color']\\n \\n result.append('%s %s' % \\\\\\n (' '.join(map(str, pt_fr)),label_color))\\n result.append('%s %s P' % \\\\\\n (' '.join(map(str, middles)),label_color))\\n # add the tip-colored line segment\\n result.append('%s %s' % \\\\\\n (' '.join(map(str, middles)), tip_color))\\n result.append('%s %s P' % \\\\\\n (' '.join(map(str, pt_to)), tip_color)) \\n return result\",\n \"def file_write(filename, dic):\\n d = dic \\n f = open(filename, 'w') \\n f.write(str(d))\\n f.close()\",\n \"def save_id_dict(self) -> None:\\n # convert sets to lists\\n forward_map = {k: list(v) for k, v in self.forward_map.items()}\\n # write to file\\n with open(self.mapping_file, 'w') as outf:\\n json.dump(\\n [forward_map, self.backward_map],\\n outf, indent=4, sort_keys=True\\n )\",\n \"def save(self, filename):\\n with open(filename, \\\"w\\\", encoding=\\\"utf8\\\") as f:\\n f.write(\\n \\\"\\\\n\\\".join(\\n [\\n w + \\\" \\\" + \\\" \\\".join([str(x) for x in v])\\n for w, v in zip(self._words, self._vecs)\\n ]\\n )\\n )\\n print(\\\"Wrote\\\", self.n, \\\"words to\\\", filename)\",\n \"def load_vectors(vec_file, info_file, buckets):\\n vectors = np.load(vec_file)\\n with open(info_file, 'r') as f:\\n info = json.load(f)\\n\\n if len(info['sequence_id_list']) != len(info['instance_id_list']):\\n raise ValueError('Invalid info file: len(info[''sequence_id_list'']) should be equal to len(info[''instance_id_list'']) but got %d != %d' % (len(info['sequence_id_list']), len(info['instance_id_list'])))\\n if vectors.shape[0] != len(info['instance_id_list']):\\n raise ValueError('Number of vectors and length of info list are not identical. %d != %d' % (len(info['sequence_id_list']), len(info['instance_id_list'])))\\n\\n num_vec, vec_dim = vectors.shape\\n prev_seq_id, prev_ins_id = None, None\\n seq_ids = {i: [] for i in xrange(len(buckets))}\\n ins_ids = {i: [] for i in xrange(len(buckets))}\\n data = {i: [] for i in xrange(len(buckets))}\\n\\n for vec_idx in tqdm(xrange(num_vec)):\\n curr_seq_id, curr_ins_id = info['sequence_id_list'][vec_idx], info['instance_id_list'][vec_idx]\\n if curr_seq_id != prev_seq_id or curr_ins_id != prev_ins_id:\\n if prev_seq_id is not None:\\n bucket_id, curr_sample = bucketing(vec_count, buckets, vec_dim, curr_sample)\\n seq_ids[bucket_id].append(prev_seq_id)\\n ins_ids[bucket_id].append(prev_ins_id)\\n data[bucket_id].append(curr_sample)\\n vec_count = 1\\n curr_sample = vectors[vec_idx]\\n else:\\n vec_count += 1\\n curr_sample = np.vstack((curr_sample, vectors[vec_idx]))\\n prev_seq_id = curr_seq_id\\n prev_ins_id = curr_ins_id\\n\\n # throw the last sample into bucket\\n bucket_id, curr_sample = bucketing(vec_count, buckets, vec_dim, curr_sample)\\n seq_ids[bucket_id].append(prev_seq_id)\\n ins_ids[bucket_id].append(prev_ins_id)\\n data[bucket_id].append(curr_sample)\\n\\n return data, seq_ids, ins_ids\",\n \"def load_glove(path):\\n with open(path) as f:\\n glove = {}\\n for line in f.readlines():\\n values = line.split()\\n word = values[0]\\n vector = np.array(values[1:], dtype='float32')\\n glove[word] = vector\\n return glove\",\n \"def load_glove(path):\\n with open(path) as f:\\n glove = {}\\n for line in f.readlines():\\n values = line.split()\\n word = values[0]\\n vector = np.array(values[1:], dtype='float32')\\n glove[word] = vector\\n return glove\",\n \"def loadGLOVE(filename, vocab):\\n dct = {}\\n vectors = array.array('d')\\n current_idx = 0\\n with codecs.open(filename, \\\"r\\\", encoding=\\\"utf-8\\\") as f:\\n for _, line in enumerate(f):\\n tokens = line.split(\\\" \\\")\\n word = tokens[0]\\n entries = tokens[1:]\\n if not vocab or word in vocab:\\n dct[word] = current_idx\\n vectors.extend(float(x) for x in entries)\\n current_idx += 1\\n word_dim = len(entries)\\n num_vectors = len(dct)\\n tf.logging.info(\\\"Found {} out of {} vectors in Glove\\\".format(num_vectors, len(vocab)))\\n return [np.array(vectors).reshape(num_vectors, word_dim), dct]\",\n \"def SaveDictFile(file,dict_):\\n with open(file,'w') as f:\\n for id in dict_:\\n f.write(dict_[id] + \\\"=\\\" + str(id)+\\\"\\\\n\\\")\",\n \"def save_track_to_dict(self, filename):\\n\\n # save track data\\n track_dict = {\\n 'size': self.size,\\n 'points': self.points,\\n 'pivots': self.pivots,\\n 'seed': self.noise_seed,\\n 'data': self.track_data\\n }\\n\\n np.save(\\\"./static/\\\" + filename, track_dict)\\n\\n print(\\\"Track saved successfully\\\")\",\n \"def loadGloveDicFromFile():\\n \\n #if the resource file is not present, creates the file containing all vectors\\n #and return vectors\\n if not isfile(GLOVE_DICT_FILE):\\n vects = _extractGloveVects()\\n saveGloveDicIntoFile(vects)\\n return vects\\n \\n return np.load(GLOVE_DICT_FILE)[0]\",\n \"def save(self, path):\\n\\n if not os.path.exists(path):\\n os.makedirs(path)\\n\\n np.save(os.path.join(path, 'V.npy'), self.V.cpu().numpy())\\n\\n if self.W is not None:\\n np.save(os.path.join(path, 'W.npy'), self.W.cpu().numpy())\\n\\n if self.vb is not None:\\n np.save(os.path.join(path, 'v_bias.npy'), self.vb.cpu().numpy())\\n\\n if self.wb is not None:\\n np.save(os.path.join(path, 'w_bias.npy'), self.wb.cpu().numpy())\\n\\n if self.dictionary is not None:\\n self.dictionary.save(os.path.join(path, 'dictionary'))\",\n \"def create_data_vector(self,regression_out_dict={},phage_file=None,\\n k_cutoff=0.00):\\n\\n self.data_vector = []\\n self.seq_strings = []\\n\\n # If the user specifies a human-readable file, use that rather than the\\n # input dictionary.\\n if phage_file != None:\\n \\n with open(phage_file) as data:\\n\\n next(data)\\n for line in data:\\n try:\\n num, seq, k_glob, theta_glob, k_ind, theta_ind = line.split()\\n except ValueError:\\n num, seq, k_ind, k_min, k_max = line.split()\\n\\n if float(k_ind) > k_cutoff:\\n\\n self.seq_strings.append(seq)\\n\\n self.data_vector.append(\\n np.array([self._alphabet_dict[s] for s in seq],\\n dtype=self.internal_type))\\n\\n else:\\n for k in regression_out_dict.keys():\\n if regression_out_dict[k][0] > k_cutoff:\\n self.seq_strings.append(k)\\n self.data_vector.append(\\n np.array([self._alphabet_dict[s] for s in k],\\n dtype=self.internal_type))\\n\\n self.data_vector = np.array(self.data_vector)\\n self.seq_strings = np.array(self.seq_strings)\",\n \"def serialize_dictionaries(self,\\n output_file,\\n restrict_to = None):\\n io.write_symbol_table_dict(output_file, self._symtab, restrict_to)\",\n \"def saveNewData(self, newvec, fname=None):\\n assert len(newvec) == len(self.allimgs), \\\\\\n 'List is uncompatible with images %d != %d' % (len(newvec), len(self.allimgs))\\n if fname and not self.record_mode:\\n self.fout = open(fname, 'w')\\n self.record_mode = True\\n for path, y, pred in zip(self.allimgs, self.ally, newvec):\\n self.fout.write('%s %d %d\\\\n' % (path, y, pred))\",\n \"def save(self, file_name):\\n logger.warning(\\\"save embeddings and name mappings to `%s`\\\" % file_name)\\n\\n objects = EasyDict()\\n for name in dir(self.graph):\\n object = getattr(self.graph, name)\\n if isinstance(object, list) and len(object) > 0 and isinstance(object[0], str): # id2name\\n objects[name] = object\\n for name in dir(self.solver):\\n object = getattr(self.solver, name)\\n if isinstance(object, np.ndarray): # embedding\\n objects[name] = object\\n\\n with open(file_name, \\\"wb\\\") as fout:\\n pickle.dump(objects, fout, protocol=pickle.HIGHEST_PROTOCOL)\",\n \"def set_recording_vectors(self, i):\\n #soma_v_vec = h.Vector() # Membrane potential vector at soma\\n setattr(self, 'soma_v_vec_' + str(i), h.Vector() )\\n #dend_v_vec = h.Vector() # Membrane potential vector at dendrite\\n setattr(self, 'dend_v_vec_' + str(i), h.Vector() )\\n \\n getattr(self, 'soma_v_vec_' + str(i)).record(self.cells[i].soma(0.5)._ref_v)\\n neuron_utils.createStateVariable(id='v_vec_soma_' + str(i) , name='v_vec_soma_' + str(i) ,\\n units='mV', python_variable={\\\"record_variable\\\": getattr(self, 'soma_v_vec_' + str(i)),\\n \\\"segment\\\": self.cells[i].soma(0.5)})\\n\\n getattr(self, 'dend_v_vec_' + str(i)).record(self.cells[i].dend(0.5)._ref_v)\\n neuron_utils.createStateVariable(id='v_vec_dend_' + str(i) , name='v_vec_dend_' + str(i) ,\\n units='mV', python_variable={\\\"record_variable\\\": getattr(self, 'dend_v_vec_' + str(i)),\\n \\\"segment\\\": self.cells[i].dend(0.5)})\",\n \"def _call_writeVec(vecObj, filename, mode):\\n res = vecObj.writeVec(filename, mode)\\n return res\",\n \"def creer_dictionnaire_vide():\\n dico = {}\\n return dico\",\n \"def test_export(self):\\n\\n v = Vector({ 'x': 3 })\\n e = v.to_array()\\n self.assertEqual(v.attributes, Vector.from_array(e).attributes)\\n self.assertEqual(v.dimensions, Vector.from_array(e).dimensions)\\n self.assertEqual(v.__dict__, Vector.from_array(e).__dict__)\",\n \"def _store(self):\\n store_dict = {}\\n for key in self._data:\\n val = self._data[key]\\n if SparseParameter._is_supported_matrix(val):\\n serial_string = SparseParameter._serialize_matrix(val)\\n store_dict[\\\"%s%s\\\" % (key, SparseParameter.IDENTIFIER)] = serial_string\\n else:\\n store_dict[key] = val\\n\\n return store_dict\",\n \"def featurize(vector,features):\\n dictionary = collections.defaultdict(lambda:0)\\n for feature in iter(set(features)):\\n dictionary[feature] = [vector[key][feature] if feature in vector[key] else 0 for key in vector] #populates vectors with zeroes where there's no value in an industry for an n-gram.\\n return dictionary\",\n \"def make_wordvec_dict(f_name, out_fname, threads):\\n # Make list of unique words\\n word_list = list(load_pickle(f_name))\\n\\n # Send job to workers\\n per_f = int(len(word_list) / threads) + 1\\n logging.info('Per Thread {}'.format(per_f))\\n pool = mp.Pool(processes=threads)\\n processes = [\\n pool.apply_async(parallel_word_dict, args=(word_list, per_f * (x - 1), per_f * x)) for x in\\n range(1, threads + 1)]\\n\\n # Get data and put it out\\n output = [process.get() for process in processes]\\n out_dict = {}\\n for ele in output:\\n out_dict = {**out_dict, **ele}\\n pool.close()\\n save_pickle(out_dict, out_fname)\\n logging.info('Made Dictionary Using Spacy')\",\n \"def exportFoldFile(vectors, authors, fileName):\\n with open(fileName, \\\"w\\\") as fFile:\\n for idv, vec in enumerate(vectors):\\n [fFile.write(str(val)+',') for val in vec]\\n fFile.write(authors[idv] + '\\\\n')\",\n \"def make_vasp_defect_files(dictio, path_base, task_id, compo, hse=False):\\n count=1\\n for site in dictio:\\n for charge in site['charges']:\\n print charge\\n for s in site['supercells']:\\n dict_transf={'history':[{'source':task_id}], 'compo': compo.to_dict, 'defect_type': site['short_name'], 'defect_site': site['unique_sites'].to_dict, 'charge': charge, 'supercell': s['size']}\\n dict_params=MPVaspInputSet().get_all_vasp_input(s['structure'])\\n incar=dict_params['INCAR']\\n incar['IBRION']=2\\n incar['ISIF']=0\\n incar['ISPIN']=1\\n incar['LWAVE']=False\\n #incar['EDIFF']=0.0001\\n incar['EDIFF']=0.001\\n incar['ISMEAR']=0\\n incar['SIGMA']=0.05\\n incar['LVHAR']=True\\n incar['LORBIT']=11\\n incar['ALGO']=\\\"Fast\\\"\\n #incar['ALGO']=\\\"Normal\\\"\\n if hse == True:\\n incar['LHFCALC']=True\\n incar[\\\"ALGO\\\"]=\\\"All\\\"\\n incar[\\\"HFSCREEN\\\"]=0.2\\n incar[\\\"PRECFOCK\\\"]=\\\"Fast\\\"\\n incar[\\\"AEXX\\\"]=0.45\\n kpoint=Kpoints.monkhorst_automatic()\\n path=path_base+\\\"/\\\"+compo.reduced_formula+\\\"_\\\"+str(task_id)+\\\"/\\\"+str(site['short_name'])+\\\"/\\\"+\\\"charge\\\"+str(charge)+\\\"/\\\"\\n os.makedirs(path)\\n f=open(path+\\\"/transformations.json\\\",'w')\\n f.write(json.dumps(dict_transf))\\n comp=s['structure'].composition\\n sum_elec=0\\n elts=set()\\n for p in dict_params['POTCAR']:\\n if p.element not in elts:\\n sum_elec+=comp.to_dict[p.element]*p.nelectrons\\n elts.add(p.element)\\n #print p.element\\n #print comp.to_dict[p.element]\\n #print p.valence\\n print sum_elec\\n if charge != 0:\\n incar['NELECT']=sum_elec-charge\\n dict_params['POTCAR'].write_file(path+\\\"POTCAR\\\")\\n incar.write_file(path+\\\"INCAR\\\")\\n kpoint.write_file(path+\\\"KPOINTS\\\")\\n dict_params['POSCAR'].write_file(path+\\\"POSCAR\\\")\\n #print Poscar(s['structure'])\\n #Poscar(s['structure']).write_file(path+\\\"POSCAR\\\")\\n count=count+1\\n f.close()\",\n \"def savez(d,file):\\n np.savez(file,row=d.row,col=d.col,data=d.data,shape=d.shape)\",\n \"def make_sol_dict():\\n file_names = [\\\"FORMAT3_Copy of KommuneMTPLforTriangle.xls\\\",\\n \\\"C Triangulations analysis R2017 GC20161109.xls\\\",\\n \\\"EVOLUTION 2017 _ M+F - Triangles cat nat brut net.xls\\\",\\n \\\"Bsp8 _ Dreiecke aus GCNA für CU1.4.1.xls\\\",\\n \\\"Analysis MTPL MOD.xls\\\",\\n \\\"Bsp6 _ Dreiecke aus GCNA für CU1.4.1.xls\\\",\\n \\\"FORMAT6_sinistres.xls\\\",\\n \\\"FORMAT1_LOSSES-MTPL-OVER-500-GROUP-2005_modified.xls\\\"]\\n solutions_dict = dict()\\n raw_dict = dict()\\n for file_name in file_names:\\n sr_list, file_name = ExcelLoader.load_excel(pdir.RESOURCES_DIR + \\\"/raw_test_files/\\\" + file_name)\\n dh = DataHolder()\\n for sr in sr_list:\\n dh.add_sheet(sr.sheet_name, pd.DataFrame(columns=sr.headers, data=sr.row_vals),\\n pd.DataFrame(columns=sr.headers, data=sr.xls_types), orig_sheet_name=sr.sheet_name)\\n\\n dh = SheetPreProcessor.separate_components(dh)\\n raw_dict[file_name] = dh.encode()\\n dh = HorizontalMerger.horizontal_merge(dh)\\n #temp_path = pdir.RESOURCES_DIR + \\\"/temp/\\\"\\n #dh.write_excel(temp_path + file_name)\\n solutions_dict[file_name] = dh\\n solutions_dict = MergePararametersOptimizer.make_ind_col_dict(solutions_dict)\\n with open(pdir.RESOURCES_DIR + \\\"/test/merge_solutions.obj\\\", \\\"wb\\\") as temp_file:\\n pickle.dump(solutions_dict, temp_file)\\n with open(pdir.RESOURCES_DIR + \\\"/test/raw_test.obj\\\", \\\"wb\\\") as temp_file:\\n pickle.dump(raw_dict, temp_file)\",\n \"def test_export_attributes(self):\\n\\n v = Vector({ 'x': 3 }, { \\\"y\\\": True })\\n e = v.to_array()\\n self.assertEqual(v.attributes, Vector.from_array(e).attributes)\\n self.assertEqual(v.__dict__, Vector.from_array(e).__dict__)\",\n \"def save(self):\\n if not os.path.exists(self.dictionary_save_path) and self.dictionary_save_path != \\\"\\\":\\n os.makedirs(self.dictionary_save_path)\\n with open(self.dictionary_save_path + \\\"dictionary\\\", 'w') as f:\\n f.write(\\\"{}\\\\n\\\".format(len(self.dictionary)))\\n\\n for word in self.dictionary:\\n f.write(\\\"{}\\\\t{}\\\\n\\\".format(self.dictionary[word]['id'], word))\",\n \"def save(self) -> None:\\n with open(dict_path, 'w', encoding='utf-8') as dictionary_file:\\n json.dump(self.data, dictionary_file, indent=2, separators=(',', ':'), ensure_ascii=False)\",\n \"def transform_word_vectors(self):\\n print('Transforming word vectors')\\n \\n self.train_X_tfidfvec = self.get_word_vectors(self.train_X)\\n self.val_X_tfidfvec = self.get_word_vectors(self.val_X)\\n self.test_X_tfidfvec = self.get_word_vectors(self.test_X)\\n if self.savename is not None:\\n with open(self.savename + '_X_tfidfvec.obj','wb') as f:\\n pickle.dump((self.train_X_tfidfvec,self.val_X_tfidfvec,self.test_X_tfidfvec),f) \\n print('Done transforming word vectors')\",\n \"def save(self,filepath):\\n d = self.X.tocoo(copy=False)\\n v = self.col_view.tocoo(copy=False)\\n np.savez(filepath,row=d.row,col=d.col,data=d.data,shape=d.shape,\\n v_row=v.row,v_col=v.col,v_data=v.data,v_shape=v.shape)\",\n \"def extract_word2vec(fichier, words_indices): \\n \\n word2vec={} #\\n \\n #\\n with open(fichier,\\\"r\\\",encoding=\\\"utf-8\\\") as file:\\n for line in file:\\n line = line.replace(\\\" \\\\n\\\",\\\"\\\").split(\\\" \\\")\\n # Lecture des informations du fichier\\n # nombre de mots presents et nombre de features\\n if len(line)==2 :\\n nb_words=int(line[0])\\n nb_feats=int(line[1])\\n \\n #\\n else:\\n if line[0] in words_indices:\\n word, vec = line[0],np.array(line[1:])\\n word2vec[word]=vec\\n\\n print(\\\"{} embbedings de taille {} pertinent parmi les {} du fichier\\\".format(len(word2vec), nb_feats, nb_words))\\n\\n return word2vec, nb_feats\",\n \"def to_file(self, fn):\\n store.store_dict(fn, 'trainalgorithm', self.to_dict())\",\n \"def Save(self, filename: str):\\n data_object = {\\n \\\"input_layer_count\\\" : self.input_layer_size,\\n \\\"hidden_layer_count\\\" : self.hidden_layer_size,\\n \\\"output_layer_count\\\" : self.output_layer_size,\\n\\n \\\"hidden_layer_biases\\\" : self.hidden_layer_biases.tolist(),\\n \\\"output_layer_biases\\\" : self.output_layer_biases.tolist(),\\n\\n \\\"input_to_hidden_weights\\\" : self.input_to_hidden_weights.tolist(),\\n \\\"hidden_to_output_weights\\\" : self.hidden_to_output_weights.tolist()\\n }\\n\\n with open(filename, \\\"w\\\") as f:\\n json.dump(data_object, f)\",\n \"def make_total_dict_db(list_files):\\n for i, file_name in enumerate(list_files):\\n print('Processing file', file_name)\\n db = make_dict_database(file_name)\\n if not i:\\n total_input = db['input']\\n total_output = db['output']\\n else:\\n total_input = np.concatenate((total_input, db['input']))\\n total_output = np.concatenate((total_output, db['output']))\\n \\n d = {'input' : total_input, 'output' : total_output} \\n \\n import cPickle as pickle\\n pickle.dump(d, open('data/domino_main.db', \\\"w+\\\"))\",\n \"def save_items(self, path):\\n os.makedirs(path, exist_ok=True)\\n np.save(os.path.join(path, 'ids'), self.item_ids)\\n np.save(os.path.join(path, 'titles'), self.item_titles)\\n np.save(os.path.join(path, 'embeddings'), self.item_vectors)\\n np.save(os.path.join(path, 'categories'), self.item_categories)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68721676","0.6824662","0.6620886","0.6619933","0.65735036","0.6529465","0.6515113","0.6493432","0.6476171","0.6336338","0.6321563","0.62979835","0.62917596","0.62372684","0.61660385","0.61660385","0.61642545","0.6095442","0.60460395","0.60164315","0.5974042","0.5973243","0.5968918","0.5968757","0.5963073","0.5954586","0.5947966","0.5902539","0.5902292","0.5888828","0.5876568","0.58728707","0.58603007","0.58517903","0.5848551","0.58367383","0.5824935","0.58114845","0.57935315","0.5769585","0.5763683","0.57619584","0.5730254","0.5727164","0.57223696","0.57108396","0.5709741","0.56906915","0.56904125","0.5684933","0.566704","0.56640387","0.5661383","0.56605184","0.5654314","0.5637525","0.5635179","0.56331533","0.56330997","0.562822","0.56241983","0.5611003","0.5608481","0.55958974","0.5583888","0.55799526","0.55738354","0.556666","0.55597466","0.55597466","0.55424744","0.55373544","0.5536047","0.5531667","0.5527061","0.5519418","0.551629","0.5513186","0.5511959","0.55068165","0.5506547","0.55064076","0.55021757","0.5500564","0.5471727","0.5471083","0.5451266","0.54505247","0.5440736","0.5438029","0.54359984","0.54298747","0.5424753","0.5415758","0.5414353","0.5412862","0.5401664","0.5393006","0.5392073","0.5391411"],"string":"[\n \"0.68721676\",\n \"0.6824662\",\n \"0.6620886\",\n \"0.6619933\",\n \"0.65735036\",\n \"0.6529465\",\n \"0.6515113\",\n \"0.6493432\",\n \"0.6476171\",\n \"0.6336338\",\n \"0.6321563\",\n \"0.62979835\",\n \"0.62917596\",\n \"0.62372684\",\n \"0.61660385\",\n \"0.61660385\",\n \"0.61642545\",\n \"0.6095442\",\n \"0.60460395\",\n \"0.60164315\",\n \"0.5974042\",\n \"0.5973243\",\n \"0.5968918\",\n \"0.5968757\",\n \"0.5963073\",\n \"0.5954586\",\n \"0.5947966\",\n \"0.5902539\",\n \"0.5902292\",\n \"0.5888828\",\n \"0.5876568\",\n \"0.58728707\",\n \"0.58603007\",\n \"0.58517903\",\n \"0.5848551\",\n \"0.58367383\",\n \"0.5824935\",\n \"0.58114845\",\n \"0.57935315\",\n \"0.5769585\",\n \"0.5763683\",\n \"0.57619584\",\n \"0.5730254\",\n \"0.5727164\",\n \"0.57223696\",\n \"0.57108396\",\n \"0.5709741\",\n \"0.56906915\",\n \"0.56904125\",\n \"0.5684933\",\n \"0.566704\",\n \"0.56640387\",\n \"0.5661383\",\n \"0.56605184\",\n \"0.5654314\",\n \"0.5637525\",\n \"0.5635179\",\n \"0.56331533\",\n \"0.56330997\",\n \"0.562822\",\n \"0.56241983\",\n \"0.5611003\",\n \"0.5608481\",\n \"0.55958974\",\n \"0.5583888\",\n \"0.55799526\",\n \"0.55738354\",\n \"0.556666\",\n \"0.55597466\",\n \"0.55597466\",\n \"0.55424744\",\n \"0.55373544\",\n \"0.5536047\",\n \"0.5531667\",\n \"0.5527061\",\n \"0.5519418\",\n \"0.551629\",\n \"0.5513186\",\n \"0.5511959\",\n \"0.55068165\",\n \"0.5506547\",\n \"0.55064076\",\n \"0.55021757\",\n \"0.5500564\",\n \"0.5471727\",\n \"0.5471083\",\n \"0.5451266\",\n \"0.54505247\",\n \"0.5440736\",\n \"0.5438029\",\n \"0.54359984\",\n \"0.54298747\",\n \"0.5424753\",\n \"0.5415758\",\n \"0.5414353\",\n \"0.5412862\",\n \"0.5401664\",\n \"0.5393006\",\n \"0.5392073\",\n \"0.5391411\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.675696"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":81794,"cells":{"query":{"kind":"string","value":"Called from admin interface when page is moved. Should be used on all the places which are changing page position. Used like an interface to mptt, but after move is done page_moved signal is fired."},"document":{"kind":"string","value":"def move_page(self, target, position='first-child'):\n self.move_to(target, position)\n # fire signal\n \n self.force_moderation_action = PageModeratorState.ACTION_MOVE\n cms_signals.page_moved.send(sender=Page, instance=self) #titles get saved before moderation\n self.save(change_state=True) # always save the page after move, because of publisher"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def post_save_page(instance, raw, created, **kwargs):\n old_page = instance.old_page\n del(instance.old_page)\n \n if settings.CMS_MODERATOR:\n # tell moderator something was happen with this page\n from cms.utils.moderator import page_changed\n page_changed(instance, old_page)","def moveEvent(self, *args, **kwargs):\n self.windowMoved.emit()","def MovePage(self, page, new_idx):\r\n \r\n idx = self.GetIdxFromWindow(page)\r\n if idx == -1:\r\n return False\r\n\r\n # get page entry, make a copy of it\r\n p = self.GetPage(idx)\r\n\r\n # remove old page entry\r\n self.RemovePage(page)\r\n\r\n # insert page where it should be\r\n self.InsertPage(page, p, new_idx)\r\n\r\n return True","def has_move_page_permission(self, request):\n return self.has_generic_permission(request, \"move_page\")","def page_changed(self):\n if self.current >= 0:\n if self.not_again:\n self.not_again = False\n return\n ok = self.check_oldpage(self.current)\n if not ok:\n self.not_again = True\n self.nb.setCurrentIndex(self.current)\n return\n self.current = self.nb.currentIndex()\n go = self.nb.currentWidget()\n if go.first_time:\n go.first_time = False\n go.create_widgets()\n go.create_actions()\n msg = go.refresh_screen(self.current_data)\n if msg:\n qtw.QMessageBox.information(self, self.title, msg)\n self.current = 0\n self.nb.setCurrentIndex(self.current)\n go.refresh_screen(self.current_data)","def OnMoving(self, event):\r\n\r\n # notify the owner manager that the pane is moving\r\n self.OnMoveStart(event)","def process_IN_MOVED_FROM(self, event):","def OnMove(self, event):\r\n\r\n if self._owner_mgr:\r\n self._owner_mgr.OnFloatingPaneMoved(self._pane_window, event)","def ev_windowmoved(self, event: WindowMoved) -> None:","def position_changed(self, position):\n pass","def on_page_changed(e):\n\n e.Skip()","def on_moved(self, event):\n print(\"Moved\")\n time.sleep(5)\n self.moveFile(event.dest_path)","def moveEvent(self, event):\n\n self.settings.setValue(\"geometry\", self.saveGeometry())\n\n super().moveEvent(event)","def change_page(self, direction):\r\n if direction == \"right\":\r\n self.model.increment_page()\r\n else:\r\n self.model.decrement_page()","def process_IN_MOVED_TO(self, event):","def on_position_change(self) -> None:\n pass","def OnMoveFinished(self):\r\n\r\n # notify the owner manager that the pane has finished moving\r\n if self._owner_mgr:\r\n self._owner_mgr._action_window = self._pane_window\r\n point = wx.GetMousePosition()\r\n if self._is_toolbar:\r\n self._owner_mgr.OnLeftUp_DragToolbarPane(point)\r\n else:\r\n self._owner_mgr.OnLeftUp_DragFloatingPane(point)\r\n\r\n self._owner_mgr.OnFloatingPaneMoved(self._pane_window, point)","def onMove(self,event=None):\n if self.app.DEBUG:\n print 'Event: Parent: %s.onMove'%self.__class__\n if self.redraw:self.redraw()","def handleMove(self):\n pass","def move_measurement(self, move):\n if len(self.mgr.obj.measurements) == 0:\n return\n idx = self.measurementsListWidget.currentRow()\n key = list(self.mgr.obj.measurements)[idx]\n idx_max = self.measurementsListWidget.count() - 1\n if (idx+move < 0) or (idx+move > idx_max):\n return\n self.mgr.obj.move_measurement(key, idx+move)\n\n self.load_measurements()\n self.measurementsListWidget.setCurrentRow(idx+move)\n self.mgr.changed = True","def mouse_move_callback(self, event):\n # TODO drag and drop figuriek\n print(\"moving at \", event.x + self.offset_x, event.y + self.offset_y)","def move_step(self, move):\n # Check that the move is valid\n steps = self.mgr.obj.steps\n if len(steps) == 0:\n return\n idx = self.stepsListWidget.currentRow()\n idx_max = len(steps) - 1\n if (idx+move < 0) or (idx+move > idx_max):\n return\n \n # Insert the step at its new location, then delete it at the old location\n steps.insert(idx+move+(move>0), steps[idx])\n del steps[idx if move>0 else idx+1]\n \n self.load_steps()\n self.stepsListWidget.setCurrentRow(idx+move)\n self.mgr.changed = True","def OnMove(self, event):\r\n\r\n if isinstance(self._frame, AuiFloatingFrame) and self._frame.IsShownOnScreen():\r\n if event is not None:\r\n event.Skip()\r\n return\r\n\r\n docked, hAlign, vAlign, monitor = self._is_docked\r\n if docked:\r\n self.Snap()\r\n\r\n for pane in self._panes:\r\n if pane.IsSnappable():\r\n if pane.IsFloating() and pane.IsShown():\r\n self.SnapPane(pane, pane.floating_pos, pane.floating_size, True)","def _onmove(self, event):","def increase_page_view(sender, **kwargs):\n pass","def ev_windowmoved(self, event: tcod.event.WindowMoved) -> T | None:","def splitterMoved(self, p_int, p_int_1): # real signature unknown; restored from __doc__\n pass","def wiki_page_changed(self, page, version, t, comment, author, ipnr):\n if 'wiki' not in self.sources:\n return\n gnp = GrowlNotificationPacket(notification='wiki',\n title='Page updated',\n description=self._wiki_repr(page,\n comment))\n gs = GrowlSender(self.env)\n gs.notify(self._get_hosts('wiki'), gnp)","def on_page_changing(e):\n\n e.Skip()","def page_changed(page, old_page=None, force_moderation_action=None):\n # Only record changes on the draft version\n if not page.publisher_is_draft:\n return\n # get user from thread locals\n from cms.utils.permissions import get_current_user\n user = get_current_user()\n\n if force_moderation_action:\n PageModeratorState(user=user, page=page, action=force_moderation_action).save()\n page.save() # sets the page to dirty\n return\n\n if not old_page:\n # just newly created page\n PageModeratorState(user=user, page=page, action=PageModeratorState.ACTION_ADD).save()","def OnMoveStart(self, event):\r\n\r\n # notify the owner manager that the pane has started to move\r\n if self._owner_mgr:\r\n if self._owner_mgr._from_move:\r\n return\r\n self._owner_mgr._action_window = self._pane_window\r\n point = wx.GetMousePosition()\r\n action_offset = point - self.GetPosition()\r\n\r\n if self._is_toolbar:\r\n self._owner_mgr._toolbar_action_offset = action_offset\r\n self._owner_mgr.OnMotion_DragToolbarPane(point)\r\n else:\r\n self._owner_mgr._action_offset = action_offset\r\n self._owner_mgr.OnMotion_DragFloatingPane(point)","def move(self):\n pass","def notify(self):\n if self.GetParent() is not None:\n evt = PageChangeEvent(from_page=self.GetName(),\n to_page=\"page_annot_actions\",\n fct=\"\")\n evt.SetEventObject(self)\n wx.PostEvent(self.GetParent(), evt)","def _update_page(self):\n\n project = self._project\n\n self._pyqt5_page.project = project\n self._pyqt4_page.project = project\n\n if project.application_is_pyqt5:\n self._pyqt5_page.configure()\n self._pyqt4_page.clear()\n\n self.setCurrentWidget(self._pyqt5_page)\n else:\n self._pyqt5_page.clear()\n self._pyqt4_page.configure()\n\n self.setCurrentWidget(self._pyqt4_page)","def on_moved(self, event):\n\n # build the relative source and destination paths\n source_path = event.src_path.replace(self.root_path, \".\")\n destination_path = event.dest_path.replace(self.root_path, '.')\n is_directory = event.is_directory\n\n # propagate the moved event if server connection is established\n if self.protocol.connected:\n self.protocol.send_move_event(is_directory, source_path, destination_path)\n else:\n logging.info(\"Connection with server has not been established, changes will not be propagated.\")","def touch_moved(self, touch):\n\t\tpass","def on_mouse_move(self, event: PointEvent):\n self.x = event.x\n self.y = event.y\n self.handle_mouse(self.x, self.y)","def move(self):\n raise NotImplementedError","def move(self):\n \n self.position = self.explore()","def move(self, move):\n raise NotImplementedError()","def resizeEvent(self, *args, **kwargs):\n self.windowMoved.emit()","def on_increased_position(self, order) -> None:\n pass","def pre_move_hook(self, from_module, to_module):\n raise NotImplementedError()","def updateServePosition(self):\n pass","def on_page_publish(sender, instance, language, **kwargs):\n if getattr(settings, \"RICHIE_KEEP_SEARCH_UPDATED\", True):\n transaction.on_commit(lambda: update_page_extension(instance, language))","def move(self, pos):\n self.widget.move(*pos)","def wiki_page_deleted(self, page):\n if 'wiki' not in self.sources:\n return\n gnp = GrowlNotificationPacket(notification='wiki',\n title='Page deleted',\n description=self._wiki_repr(page))\n gs = GrowlSender(self.env)\n gs.notify(self._get_hosts('wiki'), gnp)","def MoveToSlide(self, event):\n pass","def process_IN_MOVE_SELF(self, event):","def move(self, move):\n if move == 'UP' and not self.order is 1:\n try:\n # Get previous\n mm = Slide.objects.filter(order__lt=self.order).order_by('-order')[0]\n\n # Set order for itself\n self.order = mm.order\n self.save()\n\n # Set order for the previous # Not needed anymore, because of the automatic ordering in save()\n #mm.order += 1\n #mm.save()\n print(\"Save move\")\n except IndexError:\n pass\n elif move == 'DOWN':\n try:\n mm = Slide.objects.filter(order__gt=self.order).order_by('order')[0]\n\n # Set order for next previous\n mm.order = self.order\n mm.save()\n\n # Set order for itself # Not needed anymore, because of the automatic ordering in save()\n #self.order = mm.order\n #self.save()\n except IndexError:\n pass","def motorPositionChanged(self, absolutePosition):\n pass","def page_down(self):\n counter = self.get_entry_count_per_screen()\n while counter != 0 and self.pointer < (len(self.contents)-1):\n logging.debug(\"moved down\")\n self.pointer += 1\n counter -= 1\n self.refresh()\n self.reset_scrolling()\n return True","def setCurrentPage(self):\n pass","def mouseMoveEvent (self, event):\n self.itemMoved = True\n super(DiagramItem, self).mouseMoveEvent(event)","def cleanupPage(self, *args, **kwargs):\n if self.wizard.wizard.currentId() > 0:\n prev_page_id = self.wizard.wizard.currentId() - 1\n prev_page = self.wizard.wizard.page(prev_page_id)\n prev_page.progress_bar.setValue(0)","def moveAttachment(self, originalPage, originalName, newPage = None, newName = None):\n return self.pm_getSpaceManager().moveAttachment(self._unbox(originalPage), originalName, self._unbox(newPage), newName)","def page_up(self):\n counter = self.get_entry_count_per_screen()\n while counter != 0 and self.pointer != 0:\n logging.debug(\"moved down\")\n self.pointer -= 1\n counter -= 1\n self.refresh()\n self.reset_scrolling()\n return True","def onMoveUp(self):\n self.mainGrid.moveUp()","def OnFloatingPaneMoved(self, wnd, eventOrPt):\r\n \r\n pane = self.GetPane(wnd)\r\n if not pane.IsOk():\r\n raise Exception(\"Pane window not found\")\r\n\r\n if not pane.IsSnappable():\r\n return\r\n\r\n if isinstance(eventOrPt, wx.Point):\r\n pane_pos = wx.Point(*eventOrPt)\r\n else:\r\n pane_pos = eventOrPt.GetPosition()\r\n\r\n pane_size = pane.floating_size\r\n\r\n self.SnapPane(pane, pane_pos, pane_size, False)","def table_move_update():\n pos = self.variables.table.get_current_position()\n self.table_move_ui.x_move.setProperty(\"value\", int(pos[0]))\n self.table_move_ui.y_move.setProperty(\"value\", int(pos[1]))\n self.table_move_ui.z_move.setProperty(\"value\", int(pos[2]))","def on_mouse_move(self, win, xpos, ypos):\n old = self.mouse\n self.mouse = (xpos, glfw.get_window_size(win)[1] - ypos)\n if glfw.get_mouse_button(win, glfw.MOUSE_BUTTON_LEFT):\n self.drag(old, self.mouse, glfw.get_window_size(win))\n if glfw.get_mouse_button(win, glfw.MOUSE_BUTTON_RIGHT):\n self.pan(old, self.mouse)","def on_mouse_move(self, win, xpos, ypos):\n old = self.mouse\n self.mouse = (xpos, glfw.get_window_size(win)[1] - ypos)\n if glfw.get_mouse_button(win, glfw.MOUSE_BUTTON_LEFT):\n self.drag(old, self.mouse, glfw.get_window_size(win))\n if glfw.get_mouse_button(win, glfw.MOUSE_BUTTON_RIGHT):\n self.pan(old, self.mouse)","def on_mouse_move(self, event):\n self.mouse = [event.xdata, event.ydata]\n\n # Update pan view on mouse move\n if self.panning is True:\n for a in self.pan_axes:\n a.drag_pan(1, event.key, event.x, event.y)\n\n # Async re-draw (redraws only on thread idle state, uses timer on backend)\n self.canvas.draw_idle()\n\n ##### Temporary place-holder for cached update #####\n self.update_screen_request.emit([0, 0, 0, 0, 0])","def process_IN_MOVED_TO(self, event):\n self.ProcessFile(event.name)","def move(self, new_location):\n self.current_location = new_location","def move(self,fileName,destDir):\n self.unload(fileName)\n FileInfos.move(self,fileName,destDir)","def pre_save_page(instance, raw, **kwargs):\n instance.old_page = None\n try:\n instance.old_page = Page.objects.get(pk=instance.pk)\n except ObjectDoesNotExist:\n pass","def onMoveDown(self):\n self.mainGrid.moveDown()","def move(self, direction):\n # replace with your code\n pass","def move(self, direction):\n # replace with your code\n pass","def onMoveLeft(self):\n self.mainGrid.moveLeft()","def copy_page(self, target, site, position='first-child', copy_permissions=True, copy_moderation=True):\n from cms.utils.moderator import update_moderation_message\n \n descendants = [self] + list(self.get_descendants().order_by('-rght'))\n tree = [target]\n level_dif = self.level - target.level - 1\n first = True\n for page in descendants:\n new_level = page.level - level_dif\n dif = new_level - tree[-1].level \n if dif < 0:\n tree = tree[:dif-1]\n \n titles = list(page.title_set.all())\n plugins = list(page.cmsplugin_set.all().order_by('tree_id', '-rght'))\n \n origin_id = page.id\n # IMPORTANT NOTE: self gets changed in next few lines to page!!\n \n page.pk = None\n page.level = None\n page.rght = None\n page.lft = None\n page.tree_id = None\n page.status = Page.MODERATOR_NEED_APPROVEMENT\n page.parent = tree[-1]\n page.public_id = None\n page.reverse_id = None\n page.save()\n \n update_moderation_message(page, _('Page was copied.'))\n \n # copy moderation, permissions if necessary\n if settings.CMS_PERMISSION and copy_permissions:\n for permission in PagePermission.objects.filter(page__id=origin_id):\n permission.pk = None\n permission.page = page\n permission.save()\n \n if settings.CMS_MODERATOR and copy_moderation:\n for moderator in PageModerator.objects.filter(page__id=origin_id):\n moderator.pk = None\n moderator.page = page\n moderator.save()\n \n if first:\n first = False\n page.move_to(target, position)\n page.site = site\n page.save()\n for title in titles:\n title.pk = None\n title.public_id = None\n title.page = page\n title.slug = get_available_slug(title)\n title.save()\n ptree = []\n for p in plugins:\n plugin, cls = p.get_plugin_instance()\n p.page = page\n p.pk = None\n p.id = None\n p.tree_id = None\n p.lft = None\n p.rght = None\n p.public_id = None\n p.inherited_public_id = None\n \n if p.parent:\n pdif = p.level - ptree[-1].level\n if pdif < 0:\n ptree = ptree[:pdif-1]\n p.parent = ptree[-1]\n if pdif != 0:\n ptree.append(p)\n else:\n ptree = [p]\n p.level = None\n p.save()\n if plugin:\n plugin.pk = p.pk\n plugin.id = p.pk\n plugin.page = page\n plugin.tree_id = p.tree_id\n plugin.lft = p.lft\n plugin.rght = p.rght\n plugin.level = p.level\n plugin.cmsplugin_ptr = p\n plugin.inherited_public_id = p.inherited_public_id\n plugin.public_id = p.pk\n plugin.save()\n if dif != 0:\n tree.append(page)","def onStartMovingSouthCommand(self, *args):\n if not self.going_south:\n self.going_south = 1\n self.moveEntity()","def emitMouseMoveEvent(self, location, currentKbKey, draggedItems, items):\n # emit the mouseMoveEvent signal\n self.mouseMove.emit(self, location, currentKbKey, draggedItems, items)","def OnMove(self, event):\n self.SetStatusText(\"%.2f, %.2f\"%tuple(event.Coords))\n event.Skip()","def on_moved(self, event):\n super(myEventHandler,self).on_moved(event)\n #moveto events from external folders have no src_path\n source = event.src_path\n dest = event.dest_path\n if event.is_directory:\n splitpath = split(source)\n splitdest = split(dest)\n if splitpath[1] == splitdest[1]:\n try:\n #where are we moving from\n pass\n #file = splitpath[1]\n #pathtoonedir = self.onedir.getonedirrectory()\n #oldpath = splitpath[0].replace(pathtoonedir ,\"\")\n #calculate new path\n #newpath = splitdest[0].replace(pathtoonedir ,\"\")\n #if oldpath is \"\":\n # oldpath = os.path.sep\n #self.onedir.movefile(file,newpath,oldpath)\n except OSError as e:\n print \"Error copying file! \" + e\n exit(1)\n else:\n #rename!!!!!!!!\n oldname = source\n newname = dest\n pathtoonedir = self.onedir.getonedirrectory()\n oldname = oldname.replace(pathtoonedir ,\"\")\n newname = newname.replace(pathtoonedir ,\"\")\n self.onedir.renamedirectory(oldname,newname)\n else:\n #if it comes from outside the folder structure\n if source is None:\n try:\n #use os.path.split to get file name and path\n splitpath = split(dest)\n file = splitpath[1]\n pathtoonedir = self.onedir.getonedirrectory()\n relpath = splitpath[0].replace(pathtoonedir ,\"\")\n self.onedir.sendfile(file, relpath)\n except OSError as e:\n print \"Error copying file! \" + e.strerror\n exit(1)\n except IOError as e:\n print \"IOerror creating file \" + e.strerror\n else:\n #file was moved!\n #check if name stays the same i.e. it's a move not a rename!\n splitpath = split(source)\n splitdest = split(dest)\n if splitpath[1] == splitdest[1]:\n try:\n #where are we moving from\n file = splitpath[1]\n pathtoonedir = self.onedir.getonedirrectory()\n oldpath = splitpath[0].replace(pathtoonedir ,\"\")\n #calculate new path\n newpath = splitdest[0].replace(pathtoonedir ,\"\")\n if oldpath is \"\":\n oldpath = os.path.sep\n self.onedir.movefile(file,newpath,oldpath)\n except OSError as e:\n print \"Error copying file! \" + e\n exit(1)\n else:\n #rename!!!!!!!!\n file = splitpath[1]\n newname = splitdest[1]\n pathtoonedir = self.onedir.getonedirrectory()\n path = splitpath[0].replace(pathtoonedir ,\"\")\n if path is \"\":\n path = os.path.sep\n else:\n path = path[1:]\n self.onedir.rename(file,path,newname)","def move(self, *args, **kw):\n return self.execute_action('move', *args, **kw)","def cleanupPage(self, *args, **kwargs):\n if self.wizard.wizard.currentId() > 0:\n prev_page_id = self.wizard.wizard.currentId() - 1\n prev_page = self.wizard.wizard.page(prev_page_id)\n\n if not isinstance(prev_page, FileSetupPage):\n prev_page.progress_bar.setValue(0)","def setCurrentPage(self, widget):\r\n\r\n # block the signals during the update\r\n self.ui.actionShowSettings.blockSignals(True)\r\n self.ui.actionShowFiles.blockSignals(True)\r\n self.ui.actionShowDocumentation.blockSignals(True)\r\n self.ui.actionShowLog.blockSignals(True)\r\n self.ui.actionShowResults.blockSignals(True)\r\n\r\n self.ui.stackedWidget.setCurrentWidget(widget)\r\n\r\n # toggle the actions\r\n self.ui.actionShowSettings.setChecked(widget == self.ui.settingsPage)\r\n self.ui.actionShowFiles.setChecked(widget == self.ui.filesPage)\r\n self.ui.actionShowDocumentation.setChecked(widget == self.ui.documentationPage)\r\n self.ui.actionShowLog.setChecked(widget == self.ui.logPage)\r\n self.ui.actionShowResults.setChecked(widget == self.ui.resultPage)\r\n\r\n # un-block the signals during the update\r\n self.ui.actionShowSettings.blockSignals(False)\r\n self.ui.actionShowFiles.blockSignals(False)\r\n self.ui.actionShowDocumentation.blockSignals(False)\r\n self.ui.actionShowLog.blockSignals(False)\r\n self.ui.actionShowResults.blockSignals(False)","def execute_move(self, game_state):\n # Set new location based on which ghost this is\n game_state.ghosts_pos[self.ghost_id] = self.next_move","def execute_move(self, game_state):\n # Set new location based on which ghost this is\n game_state.ghosts_pos[self.ghost_id] = self.next_move","def OnMoveEvent(self, event):\r\n\r\n win_rect = self.GetRect()\r\n\r\n if win_rect == self._last_rect:\r\n return\r\n\r\n # skip the first move event\r\n if self._last_rect.IsEmpty(): \r\n self._last_rect = wx.Rect(*win_rect)\r\n return\r\n \r\n # skip if moving too fast to avoid massive redraws and\r\n # jumping hint windows\r\n if abs(win_rect.x - self._last_rect.x) > 3 or abs(win_rect.y - self._last_rect.y) > 3:\r\n self._last3_rect = wx.Rect(*self._last2_rect)\r\n self._last2_rect = wx.Rect(*self._last_rect)\r\n self._last_rect = wx.Rect(*win_rect)\r\n return\r\n\r\n # prevent frame redocking during resize\r\n if self._last_rect.GetSize() != win_rect.GetSize():\r\n self._last3_rect = wx.Rect(*self._last2_rect)\r\n self._last2_rect = wx.Rect(*self._last_rect)\r\n self._last_rect = wx.Rect(*win_rect)\r\n return\r\n\r\n self._last3_rect = wx.Rect(*self._last2_rect)\r\n self._last2_rect = wx.Rect(*self._last_rect)\r\n self._last_rect = wx.Rect(*win_rect)\r\n\r\n if _VERSION_STRING < \"2.9\":\r\n leftDown = wx.GetMouseState().LeftDown()\r\n else:\r\n leftDown = wx.GetMouseState().LeftIsDown()\r\n\r\n if not leftDown:\r\n return\r\n\r\n if not self._moving: \r\n self.OnMoveStart(event)\r\n self._moving = True\r\n\r\n if self._last3_rect.IsEmpty():\r\n return\r\n\r\n self.OnMoving(event)","def _move(self, move: Tile):\n if not self.game_state:\n raise RuntimeError(\"Cannot call move when the game has not started!\")\n # Adversaries are supposed to be notified of new info right before they move.\n if issubclass(type(self.current_turn), Enemy):\n current_enemy = next(enemy for enemy in self.enemy_list if enemy.entity.name == self.current_turn.entity.name)\n self._notify_adversary(current_enemy)\n # Players that are alive before this move\n pre_players = self.game_state.get_current_characters()\n completed_before_turn = self.game_state.get_completed_characters()\n if move != None:\n self._move_and_update(move)\n else:\n self.current_turn.notify(self._format_move_result_notification(None, Moveresult.OK))\n # Notify players and adversaries of changes to the gamestate, including players who were killed\n # on this turn. Note that this usually results in one rendering per move to all entities.\n self._update_players()\n self._update_adversaries()\n self._handle_completed_characters(completed_before_turn)\n self._handle_killed_players(pre_players)\n self.current_turn = self.turn_order.next()","def mouseMoveEvent(self, event):\n if self.view_state.tracking == TrackingMode.FREE and event.buttons() == QtCore.Qt.LeftButton:\n # Calculate the change in mouse position.\n new_mouse_pos = np.array([event.x(), event.y()])\n mouse_delta = new_mouse_pos - self.view_state.mouse\n\n # Add this to the view centre.\n self.view_state.centre = self.view_state.centre - mouse_delta * (1 / self.view_state.scale)\n self.view_state.mouse = new_mouse_pos","def wiki_page_version_deleted(self, page):\n if 'wiki' not in self.sources:\n return\n gnp = GrowlNotificationPacket(notification='wiki',\n title='Page suppressed',\n description=self._wiki_repr(page))\n gs = GrowlSender(self.env)\n gs.notify(self._get_hosts('wiki'), gnp)","def cb_move(self, event):\n if not self.move_timer.IsRunning():\n self.move_timer.StartOnce(2000)","def on_olderButton_clicked(self):\n self.emit(SIGNAL(\"RT_NEXT_PAGE\"))\n self.recordings_table.next_page()","def OnIdle(self, event):\r\n\r\n if self._moving: \r\n if _VERSION_STRING < \"2.9\":\r\n leftDown = wx.GetMouseState().LeftDown()\r\n else:\r\n leftDown = wx.GetMouseState().LeftIsDown()\r\n\r\n if not leftDown:\r\n self._moving = False\r\n self.OnMoveFinished()\r\n else: \r\n event.RequestMore()","def wiki_page_added(self, page):\n if 'wiki' not in self.sources:\n return\n gnp = GrowlNotificationPacket(notification='wiki',\n title='Page created',\n description=page.name)\n gs = GrowlSender(self.env)\n gs.notify(self._get_hosts('wiki'), gnp)","def update_position(position):\n pass","def move(self, x, y):\n\n\t\tself._window.move(x, y)","def move(self) -> None:\n\n if self.move_up:\n self.__moveUpIfPossible()\n if self.move_down:\n self.__moveDownIfPossible()","def move_move(self, event):\n self.canvas.scan_dragto(event.x, event.y, gain=1)","def move(self):\n \n self.position = self.wander()","def move_widget(self, widget, position):\r\n\r\n newwidget = self.widgets_list[widget]\r\n\r\n # Move the widget in the list at the specified position\r\n self.widgets_list.insert(newwidget, position)\r\n self.widgets_list.pop(self.widgets_list[widget])\r\n\r\n # Refresh the scroll area\r\n self._refresh()","def _pos_changed(self, timestamp=None, value=None, **kwargs):\n self._set_position(value)","def _on_motion(self, event):\n if not self._visual_drag.winfo_ismapped():\n return\n\n if self._drag_cols and self._dragged_col is not None:\n self._drag_col(event)\n elif self._drag_rows and self._dragged_row is not None:\n self._drag_row(event)","def update_pos(self, move):\n change = Maze.moves[move]\n self.current_pos[0] += change[0]\n self.current_pos[1] += change[1]","def ReDockPage(self, pane):\r\n\r\n root_manager = framemanager.GetManager(self) \r\n\r\n pane.window.__floating_size__ = wx.Size(*pane.floating_size)\r\n page_index = pane.window.__page_index__\r\n text_colour = pane.window.__text_colour__\r\n control = pane.window.__control__\r\n \r\n root_manager.DetachPane(pane.window)\r\n self.InsertPage(page_index, pane.window, pane.caption, True, pane.icon, control=control)\r\n\r\n self.SetPageTextColour(page_index, text_colour)\r\n self.GetActiveTabCtrl().DoShowHide()\r\n self.DoSizing()\r\n if control:\r\n self.UpdateTabCtrlHeight(force=True)\r\n \r\n self._mgr.Update()\r\n root_manager.Update()","def on_mouse_movement(self, event: wx.MouseEvent) -> None:\n if not event.Dragging():\n self._drag_start_pos = None\n return\n # self.CaptureMouse()\n if self._drag_start_pos is None:\n self._drag_start_pos = event.GetPosition()\n else:\n current_pos = event.GetPosition()\n change = self._drag_start_pos - current_pos\n self.SetPosition(self.GetPosition() - change)"],"string":"[\n \"def post_save_page(instance, raw, created, **kwargs):\\n old_page = instance.old_page\\n del(instance.old_page)\\n \\n if settings.CMS_MODERATOR:\\n # tell moderator something was happen with this page\\n from cms.utils.moderator import page_changed\\n page_changed(instance, old_page)\",\n \"def moveEvent(self, *args, **kwargs):\\n self.windowMoved.emit()\",\n \"def MovePage(self, page, new_idx):\\r\\n \\r\\n idx = self.GetIdxFromWindow(page)\\r\\n if idx == -1:\\r\\n return False\\r\\n\\r\\n # get page entry, make a copy of it\\r\\n p = self.GetPage(idx)\\r\\n\\r\\n # remove old page entry\\r\\n self.RemovePage(page)\\r\\n\\r\\n # insert page where it should be\\r\\n self.InsertPage(page, p, new_idx)\\r\\n\\r\\n return True\",\n \"def has_move_page_permission(self, request):\\n return self.has_generic_permission(request, \\\"move_page\\\")\",\n \"def page_changed(self):\\n if self.current >= 0:\\n if self.not_again:\\n self.not_again = False\\n return\\n ok = self.check_oldpage(self.current)\\n if not ok:\\n self.not_again = True\\n self.nb.setCurrentIndex(self.current)\\n return\\n self.current = self.nb.currentIndex()\\n go = self.nb.currentWidget()\\n if go.first_time:\\n go.first_time = False\\n go.create_widgets()\\n go.create_actions()\\n msg = go.refresh_screen(self.current_data)\\n if msg:\\n qtw.QMessageBox.information(self, self.title, msg)\\n self.current = 0\\n self.nb.setCurrentIndex(self.current)\\n go.refresh_screen(self.current_data)\",\n \"def OnMoving(self, event):\\r\\n\\r\\n # notify the owner manager that the pane is moving\\r\\n self.OnMoveStart(event)\",\n \"def process_IN_MOVED_FROM(self, event):\",\n \"def OnMove(self, event):\\r\\n\\r\\n if self._owner_mgr:\\r\\n self._owner_mgr.OnFloatingPaneMoved(self._pane_window, event)\",\n \"def ev_windowmoved(self, event: WindowMoved) -> None:\",\n \"def position_changed(self, position):\\n pass\",\n \"def on_page_changed(e):\\n\\n e.Skip()\",\n \"def on_moved(self, event):\\n print(\\\"Moved\\\")\\n time.sleep(5)\\n self.moveFile(event.dest_path)\",\n \"def moveEvent(self, event):\\n\\n self.settings.setValue(\\\"geometry\\\", self.saveGeometry())\\n\\n super().moveEvent(event)\",\n \"def change_page(self, direction):\\r\\n if direction == \\\"right\\\":\\r\\n self.model.increment_page()\\r\\n else:\\r\\n self.model.decrement_page()\",\n \"def process_IN_MOVED_TO(self, event):\",\n \"def on_position_change(self) -> None:\\n pass\",\n \"def OnMoveFinished(self):\\r\\n\\r\\n # notify the owner manager that the pane has finished moving\\r\\n if self._owner_mgr:\\r\\n self._owner_mgr._action_window = self._pane_window\\r\\n point = wx.GetMousePosition()\\r\\n if self._is_toolbar:\\r\\n self._owner_mgr.OnLeftUp_DragToolbarPane(point)\\r\\n else:\\r\\n self._owner_mgr.OnLeftUp_DragFloatingPane(point)\\r\\n\\r\\n self._owner_mgr.OnFloatingPaneMoved(self._pane_window, point)\",\n \"def onMove(self,event=None):\\n if self.app.DEBUG:\\n print 'Event: Parent: %s.onMove'%self.__class__\\n if self.redraw:self.redraw()\",\n \"def handleMove(self):\\n pass\",\n \"def move_measurement(self, move):\\n if len(self.mgr.obj.measurements) == 0:\\n return\\n idx = self.measurementsListWidget.currentRow()\\n key = list(self.mgr.obj.measurements)[idx]\\n idx_max = self.measurementsListWidget.count() - 1\\n if (idx+move < 0) or (idx+move > idx_max):\\n return\\n self.mgr.obj.move_measurement(key, idx+move)\\n\\n self.load_measurements()\\n self.measurementsListWidget.setCurrentRow(idx+move)\\n self.mgr.changed = True\",\n \"def mouse_move_callback(self, event):\\n # TODO drag and drop figuriek\\n print(\\\"moving at \\\", event.x + self.offset_x, event.y + self.offset_y)\",\n \"def move_step(self, move):\\n # Check that the move is valid\\n steps = self.mgr.obj.steps\\n if len(steps) == 0:\\n return\\n idx = self.stepsListWidget.currentRow()\\n idx_max = len(steps) - 1\\n if (idx+move < 0) or (idx+move > idx_max):\\n return\\n \\n # Insert the step at its new location, then delete it at the old location\\n steps.insert(idx+move+(move>0), steps[idx])\\n del steps[idx if move>0 else idx+1]\\n \\n self.load_steps()\\n self.stepsListWidget.setCurrentRow(idx+move)\\n self.mgr.changed = True\",\n \"def OnMove(self, event):\\r\\n\\r\\n if isinstance(self._frame, AuiFloatingFrame) and self._frame.IsShownOnScreen():\\r\\n if event is not None:\\r\\n event.Skip()\\r\\n return\\r\\n\\r\\n docked, hAlign, vAlign, monitor = self._is_docked\\r\\n if docked:\\r\\n self.Snap()\\r\\n\\r\\n for pane in self._panes:\\r\\n if pane.IsSnappable():\\r\\n if pane.IsFloating() and pane.IsShown():\\r\\n self.SnapPane(pane, pane.floating_pos, pane.floating_size, True)\",\n \"def _onmove(self, event):\",\n \"def increase_page_view(sender, **kwargs):\\n pass\",\n \"def ev_windowmoved(self, event: tcod.event.WindowMoved) -> T | None:\",\n \"def splitterMoved(self, p_int, p_int_1): # real signature unknown; restored from __doc__\\n pass\",\n \"def wiki_page_changed(self, page, version, t, comment, author, ipnr):\\n if 'wiki' not in self.sources:\\n return\\n gnp = GrowlNotificationPacket(notification='wiki',\\n title='Page updated',\\n description=self._wiki_repr(page,\\n comment))\\n gs = GrowlSender(self.env)\\n gs.notify(self._get_hosts('wiki'), gnp)\",\n \"def on_page_changing(e):\\n\\n e.Skip()\",\n \"def page_changed(page, old_page=None, force_moderation_action=None):\\n # Only record changes on the draft version\\n if not page.publisher_is_draft:\\n return\\n # get user from thread locals\\n from cms.utils.permissions import get_current_user\\n user = get_current_user()\\n\\n if force_moderation_action:\\n PageModeratorState(user=user, page=page, action=force_moderation_action).save()\\n page.save() # sets the page to dirty\\n return\\n\\n if not old_page:\\n # just newly created page\\n PageModeratorState(user=user, page=page, action=PageModeratorState.ACTION_ADD).save()\",\n \"def OnMoveStart(self, event):\\r\\n\\r\\n # notify the owner manager that the pane has started to move\\r\\n if self._owner_mgr:\\r\\n if self._owner_mgr._from_move:\\r\\n return\\r\\n self._owner_mgr._action_window = self._pane_window\\r\\n point = wx.GetMousePosition()\\r\\n action_offset = point - self.GetPosition()\\r\\n\\r\\n if self._is_toolbar:\\r\\n self._owner_mgr._toolbar_action_offset = action_offset\\r\\n self._owner_mgr.OnMotion_DragToolbarPane(point)\\r\\n else:\\r\\n self._owner_mgr._action_offset = action_offset\\r\\n self._owner_mgr.OnMotion_DragFloatingPane(point)\",\n \"def move(self):\\n pass\",\n \"def notify(self):\\n if self.GetParent() is not None:\\n evt = PageChangeEvent(from_page=self.GetName(),\\n to_page=\\\"page_annot_actions\\\",\\n fct=\\\"\\\")\\n evt.SetEventObject(self)\\n wx.PostEvent(self.GetParent(), evt)\",\n \"def _update_page(self):\\n\\n project = self._project\\n\\n self._pyqt5_page.project = project\\n self._pyqt4_page.project = project\\n\\n if project.application_is_pyqt5:\\n self._pyqt5_page.configure()\\n self._pyqt4_page.clear()\\n\\n self.setCurrentWidget(self._pyqt5_page)\\n else:\\n self._pyqt5_page.clear()\\n self._pyqt4_page.configure()\\n\\n self.setCurrentWidget(self._pyqt4_page)\",\n \"def on_moved(self, event):\\n\\n # build the relative source and destination paths\\n source_path = event.src_path.replace(self.root_path, \\\".\\\")\\n destination_path = event.dest_path.replace(self.root_path, '.')\\n is_directory = event.is_directory\\n\\n # propagate the moved event if server connection is established\\n if self.protocol.connected:\\n self.protocol.send_move_event(is_directory, source_path, destination_path)\\n else:\\n logging.info(\\\"Connection with server has not been established, changes will not be propagated.\\\")\",\n \"def touch_moved(self, touch):\\n\\t\\tpass\",\n \"def on_mouse_move(self, event: PointEvent):\\n self.x = event.x\\n self.y = event.y\\n self.handle_mouse(self.x, self.y)\",\n \"def move(self):\\n raise NotImplementedError\",\n \"def move(self):\\n \\n self.position = self.explore()\",\n \"def move(self, move):\\n raise NotImplementedError()\",\n \"def resizeEvent(self, *args, **kwargs):\\n self.windowMoved.emit()\",\n \"def on_increased_position(self, order) -> None:\\n pass\",\n \"def pre_move_hook(self, from_module, to_module):\\n raise NotImplementedError()\",\n \"def updateServePosition(self):\\n pass\",\n \"def on_page_publish(sender, instance, language, **kwargs):\\n if getattr(settings, \\\"RICHIE_KEEP_SEARCH_UPDATED\\\", True):\\n transaction.on_commit(lambda: update_page_extension(instance, language))\",\n \"def move(self, pos):\\n self.widget.move(*pos)\",\n \"def wiki_page_deleted(self, page):\\n if 'wiki' not in self.sources:\\n return\\n gnp = GrowlNotificationPacket(notification='wiki',\\n title='Page deleted',\\n description=self._wiki_repr(page))\\n gs = GrowlSender(self.env)\\n gs.notify(self._get_hosts('wiki'), gnp)\",\n \"def MoveToSlide(self, event):\\n pass\",\n \"def process_IN_MOVE_SELF(self, event):\",\n \"def move(self, move):\\n if move == 'UP' and not self.order is 1:\\n try:\\n # Get previous\\n mm = Slide.objects.filter(order__lt=self.order).order_by('-order')[0]\\n\\n # Set order for itself\\n self.order = mm.order\\n self.save()\\n\\n # Set order for the previous # Not needed anymore, because of the automatic ordering in save()\\n #mm.order += 1\\n #mm.save()\\n print(\\\"Save move\\\")\\n except IndexError:\\n pass\\n elif move == 'DOWN':\\n try:\\n mm = Slide.objects.filter(order__gt=self.order).order_by('order')[0]\\n\\n # Set order for next previous\\n mm.order = self.order\\n mm.save()\\n\\n # Set order for itself # Not needed anymore, because of the automatic ordering in save()\\n #self.order = mm.order\\n #self.save()\\n except IndexError:\\n pass\",\n \"def motorPositionChanged(self, absolutePosition):\\n pass\",\n \"def page_down(self):\\n counter = self.get_entry_count_per_screen()\\n while counter != 0 and self.pointer < (len(self.contents)-1):\\n logging.debug(\\\"moved down\\\")\\n self.pointer += 1\\n counter -= 1\\n self.refresh()\\n self.reset_scrolling()\\n return True\",\n \"def setCurrentPage(self):\\n pass\",\n \"def mouseMoveEvent (self, event):\\n self.itemMoved = True\\n super(DiagramItem, self).mouseMoveEvent(event)\",\n \"def cleanupPage(self, *args, **kwargs):\\n if self.wizard.wizard.currentId() > 0:\\n prev_page_id = self.wizard.wizard.currentId() - 1\\n prev_page = self.wizard.wizard.page(prev_page_id)\\n prev_page.progress_bar.setValue(0)\",\n \"def moveAttachment(self, originalPage, originalName, newPage = None, newName = None):\\n return self.pm_getSpaceManager().moveAttachment(self._unbox(originalPage), originalName, self._unbox(newPage), newName)\",\n \"def page_up(self):\\n counter = self.get_entry_count_per_screen()\\n while counter != 0 and self.pointer != 0:\\n logging.debug(\\\"moved down\\\")\\n self.pointer -= 1\\n counter -= 1\\n self.refresh()\\n self.reset_scrolling()\\n return True\",\n \"def onMoveUp(self):\\n self.mainGrid.moveUp()\",\n \"def OnFloatingPaneMoved(self, wnd, eventOrPt):\\r\\n \\r\\n pane = self.GetPane(wnd)\\r\\n if not pane.IsOk():\\r\\n raise Exception(\\\"Pane window not found\\\")\\r\\n\\r\\n if not pane.IsSnappable():\\r\\n return\\r\\n\\r\\n if isinstance(eventOrPt, wx.Point):\\r\\n pane_pos = wx.Point(*eventOrPt)\\r\\n else:\\r\\n pane_pos = eventOrPt.GetPosition()\\r\\n\\r\\n pane_size = pane.floating_size\\r\\n\\r\\n self.SnapPane(pane, pane_pos, pane_size, False)\",\n \"def table_move_update():\\n pos = self.variables.table.get_current_position()\\n self.table_move_ui.x_move.setProperty(\\\"value\\\", int(pos[0]))\\n self.table_move_ui.y_move.setProperty(\\\"value\\\", int(pos[1]))\\n self.table_move_ui.z_move.setProperty(\\\"value\\\", int(pos[2]))\",\n \"def on_mouse_move(self, win, xpos, ypos):\\n old = self.mouse\\n self.mouse = (xpos, glfw.get_window_size(win)[1] - ypos)\\n if glfw.get_mouse_button(win, glfw.MOUSE_BUTTON_LEFT):\\n self.drag(old, self.mouse, glfw.get_window_size(win))\\n if glfw.get_mouse_button(win, glfw.MOUSE_BUTTON_RIGHT):\\n self.pan(old, self.mouse)\",\n \"def on_mouse_move(self, win, xpos, ypos):\\n old = self.mouse\\n self.mouse = (xpos, glfw.get_window_size(win)[1] - ypos)\\n if glfw.get_mouse_button(win, glfw.MOUSE_BUTTON_LEFT):\\n self.drag(old, self.mouse, glfw.get_window_size(win))\\n if glfw.get_mouse_button(win, glfw.MOUSE_BUTTON_RIGHT):\\n self.pan(old, self.mouse)\",\n \"def on_mouse_move(self, event):\\n self.mouse = [event.xdata, event.ydata]\\n\\n # Update pan view on mouse move\\n if self.panning is True:\\n for a in self.pan_axes:\\n a.drag_pan(1, event.key, event.x, event.y)\\n\\n # Async re-draw (redraws only on thread idle state, uses timer on backend)\\n self.canvas.draw_idle()\\n\\n ##### Temporary place-holder for cached update #####\\n self.update_screen_request.emit([0, 0, 0, 0, 0])\",\n \"def process_IN_MOVED_TO(self, event):\\n self.ProcessFile(event.name)\",\n \"def move(self, new_location):\\n self.current_location = new_location\",\n \"def move(self,fileName,destDir):\\n self.unload(fileName)\\n FileInfos.move(self,fileName,destDir)\",\n \"def pre_save_page(instance, raw, **kwargs):\\n instance.old_page = None\\n try:\\n instance.old_page = Page.objects.get(pk=instance.pk)\\n except ObjectDoesNotExist:\\n pass\",\n \"def onMoveDown(self):\\n self.mainGrid.moveDown()\",\n \"def move(self, direction):\\n # replace with your code\\n pass\",\n \"def move(self, direction):\\n # replace with your code\\n pass\",\n \"def onMoveLeft(self):\\n self.mainGrid.moveLeft()\",\n \"def copy_page(self, target, site, position='first-child', copy_permissions=True, copy_moderation=True):\\n from cms.utils.moderator import update_moderation_message\\n \\n descendants = [self] + list(self.get_descendants().order_by('-rght'))\\n tree = [target]\\n level_dif = self.level - target.level - 1\\n first = True\\n for page in descendants:\\n new_level = page.level - level_dif\\n dif = new_level - tree[-1].level \\n if dif < 0:\\n tree = tree[:dif-1]\\n \\n titles = list(page.title_set.all())\\n plugins = list(page.cmsplugin_set.all().order_by('tree_id', '-rght'))\\n \\n origin_id = page.id\\n # IMPORTANT NOTE: self gets changed in next few lines to page!!\\n \\n page.pk = None\\n page.level = None\\n page.rght = None\\n page.lft = None\\n page.tree_id = None\\n page.status = Page.MODERATOR_NEED_APPROVEMENT\\n page.parent = tree[-1]\\n page.public_id = None\\n page.reverse_id = None\\n page.save()\\n \\n update_moderation_message(page, _('Page was copied.'))\\n \\n # copy moderation, permissions if necessary\\n if settings.CMS_PERMISSION and copy_permissions:\\n for permission in PagePermission.objects.filter(page__id=origin_id):\\n permission.pk = None\\n permission.page = page\\n permission.save()\\n \\n if settings.CMS_MODERATOR and copy_moderation:\\n for moderator in PageModerator.objects.filter(page__id=origin_id):\\n moderator.pk = None\\n moderator.page = page\\n moderator.save()\\n \\n if first:\\n first = False\\n page.move_to(target, position)\\n page.site = site\\n page.save()\\n for title in titles:\\n title.pk = None\\n title.public_id = None\\n title.page = page\\n title.slug = get_available_slug(title)\\n title.save()\\n ptree = []\\n for p in plugins:\\n plugin, cls = p.get_plugin_instance()\\n p.page = page\\n p.pk = None\\n p.id = None\\n p.tree_id = None\\n p.lft = None\\n p.rght = None\\n p.public_id = None\\n p.inherited_public_id = None\\n \\n if p.parent:\\n pdif = p.level - ptree[-1].level\\n if pdif < 0:\\n ptree = ptree[:pdif-1]\\n p.parent = ptree[-1]\\n if pdif != 0:\\n ptree.append(p)\\n else:\\n ptree = [p]\\n p.level = None\\n p.save()\\n if plugin:\\n plugin.pk = p.pk\\n plugin.id = p.pk\\n plugin.page = page\\n plugin.tree_id = p.tree_id\\n plugin.lft = p.lft\\n plugin.rght = p.rght\\n plugin.level = p.level\\n plugin.cmsplugin_ptr = p\\n plugin.inherited_public_id = p.inherited_public_id\\n plugin.public_id = p.pk\\n plugin.save()\\n if dif != 0:\\n tree.append(page)\",\n \"def onStartMovingSouthCommand(self, *args):\\n if not self.going_south:\\n self.going_south = 1\\n self.moveEntity()\",\n \"def emitMouseMoveEvent(self, location, currentKbKey, draggedItems, items):\\n # emit the mouseMoveEvent signal\\n self.mouseMove.emit(self, location, currentKbKey, draggedItems, items)\",\n \"def OnMove(self, event):\\n self.SetStatusText(\\\"%.2f, %.2f\\\"%tuple(event.Coords))\\n event.Skip()\",\n \"def on_moved(self, event):\\n super(myEventHandler,self).on_moved(event)\\n #moveto events from external folders have no src_path\\n source = event.src_path\\n dest = event.dest_path\\n if event.is_directory:\\n splitpath = split(source)\\n splitdest = split(dest)\\n if splitpath[1] == splitdest[1]:\\n try:\\n #where are we moving from\\n pass\\n #file = splitpath[1]\\n #pathtoonedir = self.onedir.getonedirrectory()\\n #oldpath = splitpath[0].replace(pathtoonedir ,\\\"\\\")\\n #calculate new path\\n #newpath = splitdest[0].replace(pathtoonedir ,\\\"\\\")\\n #if oldpath is \\\"\\\":\\n # oldpath = os.path.sep\\n #self.onedir.movefile(file,newpath,oldpath)\\n except OSError as e:\\n print \\\"Error copying file! \\\" + e\\n exit(1)\\n else:\\n #rename!!!!!!!!\\n oldname = source\\n newname = dest\\n pathtoonedir = self.onedir.getonedirrectory()\\n oldname = oldname.replace(pathtoonedir ,\\\"\\\")\\n newname = newname.replace(pathtoonedir ,\\\"\\\")\\n self.onedir.renamedirectory(oldname,newname)\\n else:\\n #if it comes from outside the folder structure\\n if source is None:\\n try:\\n #use os.path.split to get file name and path\\n splitpath = split(dest)\\n file = splitpath[1]\\n pathtoonedir = self.onedir.getonedirrectory()\\n relpath = splitpath[0].replace(pathtoonedir ,\\\"\\\")\\n self.onedir.sendfile(file, relpath)\\n except OSError as e:\\n print \\\"Error copying file! \\\" + e.strerror\\n exit(1)\\n except IOError as e:\\n print \\\"IOerror creating file \\\" + e.strerror\\n else:\\n #file was moved!\\n #check if name stays the same i.e. it's a move not a rename!\\n splitpath = split(source)\\n splitdest = split(dest)\\n if splitpath[1] == splitdest[1]:\\n try:\\n #where are we moving from\\n file = splitpath[1]\\n pathtoonedir = self.onedir.getonedirrectory()\\n oldpath = splitpath[0].replace(pathtoonedir ,\\\"\\\")\\n #calculate new path\\n newpath = splitdest[0].replace(pathtoonedir ,\\\"\\\")\\n if oldpath is \\\"\\\":\\n oldpath = os.path.sep\\n self.onedir.movefile(file,newpath,oldpath)\\n except OSError as e:\\n print \\\"Error copying file! \\\" + e\\n exit(1)\\n else:\\n #rename!!!!!!!!\\n file = splitpath[1]\\n newname = splitdest[1]\\n pathtoonedir = self.onedir.getonedirrectory()\\n path = splitpath[0].replace(pathtoonedir ,\\\"\\\")\\n if path is \\\"\\\":\\n path = os.path.sep\\n else:\\n path = path[1:]\\n self.onedir.rename(file,path,newname)\",\n \"def move(self, *args, **kw):\\n return self.execute_action('move', *args, **kw)\",\n \"def cleanupPage(self, *args, **kwargs):\\n if self.wizard.wizard.currentId() > 0:\\n prev_page_id = self.wizard.wizard.currentId() - 1\\n prev_page = self.wizard.wizard.page(prev_page_id)\\n\\n if not isinstance(prev_page, FileSetupPage):\\n prev_page.progress_bar.setValue(0)\",\n \"def setCurrentPage(self, widget):\\r\\n\\r\\n # block the signals during the update\\r\\n self.ui.actionShowSettings.blockSignals(True)\\r\\n self.ui.actionShowFiles.blockSignals(True)\\r\\n self.ui.actionShowDocumentation.blockSignals(True)\\r\\n self.ui.actionShowLog.blockSignals(True)\\r\\n self.ui.actionShowResults.blockSignals(True)\\r\\n\\r\\n self.ui.stackedWidget.setCurrentWidget(widget)\\r\\n\\r\\n # toggle the actions\\r\\n self.ui.actionShowSettings.setChecked(widget == self.ui.settingsPage)\\r\\n self.ui.actionShowFiles.setChecked(widget == self.ui.filesPage)\\r\\n self.ui.actionShowDocumentation.setChecked(widget == self.ui.documentationPage)\\r\\n self.ui.actionShowLog.setChecked(widget == self.ui.logPage)\\r\\n self.ui.actionShowResults.setChecked(widget == self.ui.resultPage)\\r\\n\\r\\n # un-block the signals during the update\\r\\n self.ui.actionShowSettings.blockSignals(False)\\r\\n self.ui.actionShowFiles.blockSignals(False)\\r\\n self.ui.actionShowDocumentation.blockSignals(False)\\r\\n self.ui.actionShowLog.blockSignals(False)\\r\\n self.ui.actionShowResults.blockSignals(False)\",\n \"def execute_move(self, game_state):\\n # Set new location based on which ghost this is\\n game_state.ghosts_pos[self.ghost_id] = self.next_move\",\n \"def execute_move(self, game_state):\\n # Set new location based on which ghost this is\\n game_state.ghosts_pos[self.ghost_id] = self.next_move\",\n \"def OnMoveEvent(self, event):\\r\\n\\r\\n win_rect = self.GetRect()\\r\\n\\r\\n if win_rect == self._last_rect:\\r\\n return\\r\\n\\r\\n # skip the first move event\\r\\n if self._last_rect.IsEmpty(): \\r\\n self._last_rect = wx.Rect(*win_rect)\\r\\n return\\r\\n \\r\\n # skip if moving too fast to avoid massive redraws and\\r\\n # jumping hint windows\\r\\n if abs(win_rect.x - self._last_rect.x) > 3 or abs(win_rect.y - self._last_rect.y) > 3:\\r\\n self._last3_rect = wx.Rect(*self._last2_rect)\\r\\n self._last2_rect = wx.Rect(*self._last_rect)\\r\\n self._last_rect = wx.Rect(*win_rect)\\r\\n return\\r\\n\\r\\n # prevent frame redocking during resize\\r\\n if self._last_rect.GetSize() != win_rect.GetSize():\\r\\n self._last3_rect = wx.Rect(*self._last2_rect)\\r\\n self._last2_rect = wx.Rect(*self._last_rect)\\r\\n self._last_rect = wx.Rect(*win_rect)\\r\\n return\\r\\n\\r\\n self._last3_rect = wx.Rect(*self._last2_rect)\\r\\n self._last2_rect = wx.Rect(*self._last_rect)\\r\\n self._last_rect = wx.Rect(*win_rect)\\r\\n\\r\\n if _VERSION_STRING < \\\"2.9\\\":\\r\\n leftDown = wx.GetMouseState().LeftDown()\\r\\n else:\\r\\n leftDown = wx.GetMouseState().LeftIsDown()\\r\\n\\r\\n if not leftDown:\\r\\n return\\r\\n\\r\\n if not self._moving: \\r\\n self.OnMoveStart(event)\\r\\n self._moving = True\\r\\n\\r\\n if self._last3_rect.IsEmpty():\\r\\n return\\r\\n\\r\\n self.OnMoving(event)\",\n \"def _move(self, move: Tile):\\n if not self.game_state:\\n raise RuntimeError(\\\"Cannot call move when the game has not started!\\\")\\n # Adversaries are supposed to be notified of new info right before they move.\\n if issubclass(type(self.current_turn), Enemy):\\n current_enemy = next(enemy for enemy in self.enemy_list if enemy.entity.name == self.current_turn.entity.name)\\n self._notify_adversary(current_enemy)\\n # Players that are alive before this move\\n pre_players = self.game_state.get_current_characters()\\n completed_before_turn = self.game_state.get_completed_characters()\\n if move != None:\\n self._move_and_update(move)\\n else:\\n self.current_turn.notify(self._format_move_result_notification(None, Moveresult.OK))\\n # Notify players and adversaries of changes to the gamestate, including players who were killed\\n # on this turn. Note that this usually results in one rendering per move to all entities.\\n self._update_players()\\n self._update_adversaries()\\n self._handle_completed_characters(completed_before_turn)\\n self._handle_killed_players(pre_players)\\n self.current_turn = self.turn_order.next()\",\n \"def mouseMoveEvent(self, event):\\n if self.view_state.tracking == TrackingMode.FREE and event.buttons() == QtCore.Qt.LeftButton:\\n # Calculate the change in mouse position.\\n new_mouse_pos = np.array([event.x(), event.y()])\\n mouse_delta = new_mouse_pos - self.view_state.mouse\\n\\n # Add this to the view centre.\\n self.view_state.centre = self.view_state.centre - mouse_delta * (1 / self.view_state.scale)\\n self.view_state.mouse = new_mouse_pos\",\n \"def wiki_page_version_deleted(self, page):\\n if 'wiki' not in self.sources:\\n return\\n gnp = GrowlNotificationPacket(notification='wiki',\\n title='Page suppressed',\\n description=self._wiki_repr(page))\\n gs = GrowlSender(self.env)\\n gs.notify(self._get_hosts('wiki'), gnp)\",\n \"def cb_move(self, event):\\n if not self.move_timer.IsRunning():\\n self.move_timer.StartOnce(2000)\",\n \"def on_olderButton_clicked(self):\\n self.emit(SIGNAL(\\\"RT_NEXT_PAGE\\\"))\\n self.recordings_table.next_page()\",\n \"def OnIdle(self, event):\\r\\n\\r\\n if self._moving: \\r\\n if _VERSION_STRING < \\\"2.9\\\":\\r\\n leftDown = wx.GetMouseState().LeftDown()\\r\\n else:\\r\\n leftDown = wx.GetMouseState().LeftIsDown()\\r\\n\\r\\n if not leftDown:\\r\\n self._moving = False\\r\\n self.OnMoveFinished()\\r\\n else: \\r\\n event.RequestMore()\",\n \"def wiki_page_added(self, page):\\n if 'wiki' not in self.sources:\\n return\\n gnp = GrowlNotificationPacket(notification='wiki',\\n title='Page created',\\n description=page.name)\\n gs = GrowlSender(self.env)\\n gs.notify(self._get_hosts('wiki'), gnp)\",\n \"def update_position(position):\\n pass\",\n \"def move(self, x, y):\\n\\n\\t\\tself._window.move(x, y)\",\n \"def move(self) -> None:\\n\\n if self.move_up:\\n self.__moveUpIfPossible()\\n if self.move_down:\\n self.__moveDownIfPossible()\",\n \"def move_move(self, event):\\n self.canvas.scan_dragto(event.x, event.y, gain=1)\",\n \"def move(self):\\n \\n self.position = self.wander()\",\n \"def move_widget(self, widget, position):\\r\\n\\r\\n newwidget = self.widgets_list[widget]\\r\\n\\r\\n # Move the widget in the list at the specified position\\r\\n self.widgets_list.insert(newwidget, position)\\r\\n self.widgets_list.pop(self.widgets_list[widget])\\r\\n\\r\\n # Refresh the scroll area\\r\\n self._refresh()\",\n \"def _pos_changed(self, timestamp=None, value=None, **kwargs):\\n self._set_position(value)\",\n \"def _on_motion(self, event):\\n if not self._visual_drag.winfo_ismapped():\\n return\\n\\n if self._drag_cols and self._dragged_col is not None:\\n self._drag_col(event)\\n elif self._drag_rows and self._dragged_row is not None:\\n self._drag_row(event)\",\n \"def update_pos(self, move):\\n change = Maze.moves[move]\\n self.current_pos[0] += change[0]\\n self.current_pos[1] += change[1]\",\n \"def ReDockPage(self, pane):\\r\\n\\r\\n root_manager = framemanager.GetManager(self) \\r\\n\\r\\n pane.window.__floating_size__ = wx.Size(*pane.floating_size)\\r\\n page_index = pane.window.__page_index__\\r\\n text_colour = pane.window.__text_colour__\\r\\n control = pane.window.__control__\\r\\n \\r\\n root_manager.DetachPane(pane.window)\\r\\n self.InsertPage(page_index, pane.window, pane.caption, True, pane.icon, control=control)\\r\\n\\r\\n self.SetPageTextColour(page_index, text_colour)\\r\\n self.GetActiveTabCtrl().DoShowHide()\\r\\n self.DoSizing()\\r\\n if control:\\r\\n self.UpdateTabCtrlHeight(force=True)\\r\\n \\r\\n self._mgr.Update()\\r\\n root_manager.Update()\",\n \"def on_mouse_movement(self, event: wx.MouseEvent) -> None:\\n if not event.Dragging():\\n self._drag_start_pos = None\\n return\\n # self.CaptureMouse()\\n if self._drag_start_pos is None:\\n self._drag_start_pos = event.GetPosition()\\n else:\\n current_pos = event.GetPosition()\\n change = self._drag_start_pos - current_pos\\n self.SetPosition(self.GetPosition() - change)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.64120024","0.6210927","0.6112562","0.6102588","0.60626286","0.6050393","0.599529","0.59568924","0.59317076","0.57837987","0.57799387","0.5729946","0.5728036","0.5711554","0.57115483","0.568866","0.55789995","0.5550567","0.55030763","0.54747677","0.546125","0.54537874","0.54510105","0.54202896","0.54132056","0.5393233","0.5365565","0.5355497","0.53313875","0.5317065","0.5299301","0.52990055","0.52859306","0.5275385","0.52469623","0.524466","0.52432877","0.5237619","0.5218835","0.5213385","0.51961666","0.51888335","0.5163704","0.5155799","0.5123524","0.51017","0.5092435","0.50756","0.5075427","0.50550777","0.504659","0.5040642","0.5038598","0.5038569","0.5031405","0.50155085","0.50146466","0.5014104","0.5008783","0.50082016","0.49994096","0.49994096","0.49565545","0.4954643","0.49518472","0.49510077","0.49469876","0.49431163","0.4942173","0.4942173","0.49354237","0.49246493","0.49182647","0.49065146","0.49037576","0.48675916","0.4829577","0.48232976","0.48105922","0.48079956","0.48079956","0.48034456","0.4788467","0.47866702","0.4782235","0.4760213","0.47593567","0.47512734","0.47485062","0.473043","0.47216728","0.47188497","0.47142747","0.47121316","0.47105393","0.4709556","0.47072968","0.470364","0.47035632","0.47000107"],"string":"[\n \"0.64120024\",\n \"0.6210927\",\n \"0.6112562\",\n \"0.6102588\",\n \"0.60626286\",\n \"0.6050393\",\n \"0.599529\",\n \"0.59568924\",\n \"0.59317076\",\n \"0.57837987\",\n \"0.57799387\",\n \"0.5729946\",\n \"0.5728036\",\n \"0.5711554\",\n \"0.57115483\",\n \"0.568866\",\n \"0.55789995\",\n \"0.5550567\",\n \"0.55030763\",\n \"0.54747677\",\n \"0.546125\",\n \"0.54537874\",\n \"0.54510105\",\n \"0.54202896\",\n \"0.54132056\",\n \"0.5393233\",\n \"0.5365565\",\n \"0.5355497\",\n \"0.53313875\",\n \"0.5317065\",\n \"0.5299301\",\n \"0.52990055\",\n \"0.52859306\",\n \"0.5275385\",\n \"0.52469623\",\n \"0.524466\",\n \"0.52432877\",\n \"0.5237619\",\n \"0.5218835\",\n \"0.5213385\",\n \"0.51961666\",\n \"0.51888335\",\n \"0.5163704\",\n \"0.5155799\",\n \"0.5123524\",\n \"0.51017\",\n \"0.5092435\",\n \"0.50756\",\n \"0.5075427\",\n \"0.50550777\",\n \"0.504659\",\n \"0.5040642\",\n \"0.5038598\",\n \"0.5038569\",\n \"0.5031405\",\n \"0.50155085\",\n \"0.50146466\",\n \"0.5014104\",\n \"0.5008783\",\n \"0.50082016\",\n \"0.49994096\",\n \"0.49994096\",\n \"0.49565545\",\n \"0.4954643\",\n \"0.49518472\",\n \"0.49510077\",\n \"0.49469876\",\n \"0.49431163\",\n \"0.4942173\",\n \"0.4942173\",\n \"0.49354237\",\n \"0.49246493\",\n \"0.49182647\",\n \"0.49065146\",\n \"0.49037576\",\n \"0.48675916\",\n \"0.4829577\",\n \"0.48232976\",\n \"0.48105922\",\n \"0.48079956\",\n \"0.48079956\",\n \"0.48034456\",\n \"0.4788467\",\n \"0.47866702\",\n \"0.4782235\",\n \"0.4760213\",\n \"0.47593567\",\n \"0.47512734\",\n \"0.47485062\",\n \"0.473043\",\n \"0.47216728\",\n \"0.47188497\",\n \"0.47142747\",\n \"0.47121316\",\n \"0.47105393\",\n \"0.4709556\",\n \"0.47072968\",\n \"0.470364\",\n \"0.47035632\",\n \"0.47000107\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7220067"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81795,"cells":{"query":{"kind":"string","value":"copy a page and all its descendants to a new location Doesn't checks for add page permissions anymore, this is done in PageAdmin."},"document":{"kind":"string","value":"def copy_page(self, target, site, position='first-child', copy_permissions=True, copy_moderation=True):\n from cms.utils.moderator import update_moderation_message\n \n descendants = [self] + list(self.get_descendants().order_by('-rght'))\n tree = [target]\n level_dif = self.level - target.level - 1\n first = True\n for page in descendants:\n new_level = page.level - level_dif\n dif = new_level - tree[-1].level \n if dif < 0:\n tree = tree[:dif-1]\n \n titles = list(page.title_set.all())\n plugins = list(page.cmsplugin_set.all().order_by('tree_id', '-rght'))\n \n origin_id = page.id\n # IMPORTANT NOTE: self gets changed in next few lines to page!!\n \n page.pk = None\n page.level = None\n page.rght = None\n page.lft = None\n page.tree_id = None\n page.status = Page.MODERATOR_NEED_APPROVEMENT\n page.parent = tree[-1]\n page.public_id = None\n page.reverse_id = None\n page.save()\n \n update_moderation_message(page, _('Page was copied.'))\n \n # copy moderation, permissions if necessary\n if settings.CMS_PERMISSION and copy_permissions:\n for permission in PagePermission.objects.filter(page__id=origin_id):\n permission.pk = None\n permission.page = page\n permission.save()\n \n if settings.CMS_MODERATOR and copy_moderation:\n for moderator in PageModerator.objects.filter(page__id=origin_id):\n moderator.pk = None\n moderator.page = page\n moderator.save()\n \n if first:\n first = False\n page.move_to(target, position)\n page.site = site\n page.save()\n for title in titles:\n title.pk = None\n title.public_id = None\n title.page = page\n title.slug = get_available_slug(title)\n title.save()\n ptree = []\n for p in plugins:\n plugin, cls = p.get_plugin_instance()\n p.page = page\n p.pk = None\n p.id = None\n p.tree_id = None\n p.lft = None\n p.rght = None\n p.public_id = None\n p.inherited_public_id = None\n \n if p.parent:\n pdif = p.level - ptree[-1].level\n if pdif < 0:\n ptree = ptree[:pdif-1]\n p.parent = ptree[-1]\n if pdif != 0:\n ptree.append(p)\n else:\n ptree = [p]\n p.level = None\n p.save()\n if plugin:\n plugin.pk = p.pk\n plugin.id = p.pk\n plugin.page = page\n plugin.tree_id = p.tree_id\n plugin.lft = p.lft\n plugin.rght = p.rght\n plugin.level = p.level\n plugin.cmsplugin_ptr = p\n plugin.inherited_public_id = p.inherited_public_id\n plugin.public_id = p.pk\n plugin.save()\n if dif != 0:\n tree.append(page)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def copy_pages(config):\n\n if \"Pages\" not in config:\n INFO(\"No information about pages\")\n return\n\n target_path = os.path.join(config[\"target\"][\"path\"],\n constants.PAGES_FOLDER)\n\n pages = config[\"Pages\"]\n params = {\n # \"rename\": None,\n \"exclude\": None,\n \"include\": None\n }\n\n if not isinstance(pages, (list, tuple)):\n pages = (pages,)\n\n new_pages = []\n for page in pages:\n if isinstance(page, (str, unicode)):\n _page = {\n \"path\": normalize_path(page, config)\n }\n\n if not _page[\"path\"].rstrip(\"\\/\").lower().endswith(\"pages\"):\n new_pages.append(page)\n else:\n if isinstance(page, dict):\n _page[\"path\"] = normalize_path(page[\"path\"], config)\n\n for param in params:\n params[param] = val = page.get(param, None)\n if val and not isinstance(val, (list, tuple, dict)):\n params[param] = (val,)\n\n if params[\"exclude\"]:\n params[\"exclude\"] = convert_to_regexp(params[\"exclude\"])\n\n if params[\"include\"]:\n params[\"include\"] = convert_to_regexp(params[\"include\"])\n\n if not os.path.exists(_page[\"path\"]):\n ERROR(\"No such directory: '%s'\", _page[\"path\"])\n continue\n\n for folder in os.listdir(_page[\"path\"]):\n\n # if folder in exclude list - continue\n if params[\"exclude\"] and check_by_regexps(folder, params[\"exclude\"]):\n continue\n\n # if folder not in include list - continue\n if params[\"include\"] and not check_by_regexps(folder, params[\"include\"]):\n continue\n\n folder_path = os.path.join(_page[\"path\"], folder)\n\n if not os.path.isdir(folder_path):\n ERROR(\"Page can't be file: %s\", folder_path)\n continue\n\n new_page = _page.copy()\n new_page[\"path\"] = folder_path\n new_pages.append(new_page)\n\n\n for page in new_pages:\n\n if isinstance(page, (str, unicode)):\n page = {\n \"path\": page\n }\n\n # normalize path - replace alias with real path\n page[\"path\"] = normalize_path(page[\"path\"], config)\n if not os.path.exists(page[\"path\"]):\n ERROR(\"No such directory: '{}'\".format(page[\"path\"]))\n continue\n\n # if name not defined - got it from folder name\n if not page.get(\"name\", \"\"):\n page[\"name\"] = os.path.split(page[\"path\"].rstrip(\"\\/\"))[1]\n page[\"rename\"] = False\n\n copy_path = os.path.join(target_path, page[\"name\"])\n if os.path.exists(copy_path):\n ERROR(\"Directory already exists: '{}'\".format(copy_path))\n continue\n\n if page.get(\"mode\", \"\") not in (\"move\", \"copy\"):\n page[\"mode\"] = \"move\"\n\n # copy page to new folder\n DEBUG(\"Copy '{}' to '{}'\".format(page[\"path\"], copy_path))\n shutil.copytree(page[\"path\"], copy_path)\n\n info_path = os.path.join(copy_path, constants.INFO_FILE)\n with fopen(info_path, \"rb\") as hdlr:\n info = json_load(hdlr, critical=True)\n\n if page.get(\"rename\", True):\n info[\"attrs\"][\"Name\"] = page[\"name\"]\n\n with fopen(info_path, \"wb\") as hdlr:\n json_dump(info, hdlr, critical=True)\n\n # if page not copied continue, else need to change all guids to new\n if page[\"mode\"] == \"move\":\n continue\n\n new_guid = gen_guid()\n old_guid = info[\"attrs\"][\"ID\"]\n\n GUIDS_TO_REPLACE[old_guid] = new_guid\n GUIDS_TO_REPLACE[old_guid.replace(\"-\", \"_\")] = new_guid.replace(\"-\", \"_\")\n\n INFO(\"Pages were copied successfully\")","def impersonate_other_page(page, other_page):\n page.path = other_page.path\n page.depth = other_page.depth\n page.url_path = other_page.url_path\n page.title = other_page.title","def add_page_to( self, content, dest):\n index = len(dest.xpath(\"./*\"))\n dest.insert(index + 1, content)","def test_copy_page_nested_plugin_moved_parent_plugin(self):\n with SettingsOverride(CMS_MODERATOR=False, CMS_PERMISSION=False):\n templates = []\n # setup page 1\n page_one = create_page(u\"Three Placeholder\", u\"col_three.html\", u\"en\",\n position=u\"last-child\", published=True, in_navigation=True)\n page_one_ph_one = page_one.placeholders.get(slot=u\"col_sidebar\")\n page_one_ph_two = page_one.placeholders.get(slot=u\"col_left\")\n page_one_ph_three = page_one.placeholders.get(slot=u\"col_right\")\n # add the text plugin to placeholder one\n text_plugin_en = add_plugin(page_one_ph_one, u\"TextPlugin\", u\"en\", body=u\"Hello World\")\n self.assertEquals(text_plugin_en.id, CMSPlugin.objects.all()[0].id)\n self.assertEquals(text_plugin_en.get_children().count(), 0)\n pre_add_plugin_count = CMSPlugin.objects.count()\n self.assertEqual(pre_add_plugin_count, 1)\n # add a plugin to placeholder twho\n pre_nesting_body = u\"<p>the nested text plugin with a link inside</p>\"\n text_plugin_two = add_plugin(page_one_ph_two, u\"TextPlugin\", u\"en\", body=pre_nesting_body)\n text_plugin_two = self.reload(text_plugin_two)\n # prepare nestin plugin\n page_one_ph_two = self.reload(page_one_ph_two)\n text_plugin_two = self.reload(text_plugin_two)\n link_plugin = add_plugin(page_one_ph_two, u\"LinkPlugin\", u\"en\", target=text_plugin_two)\n link_plugin.name = u\"django-cms Link\"\n link_plugin.url = u\"https://www.django-cms.org\" \n link_plugin.parent = text_plugin_two\n link_plugin.save()\n # reload after every save\n link_plugin = self.reload(link_plugin)\n text_plugin_two = self.reload(text_plugin_two)\n in_txt = u\"\"\"<img id=\"plugin_obj_%s\" title=\"Link\" alt=\"Link\" src=\"/static/cms/images/plugins/link.png\">\"\"\"\n nesting_body = \"%s<p>%s</p>\" % (text_plugin_two.body, (in_txt % (link_plugin.id)))\n # emulate the editor in admin that adds some txt for the nested plugin\n text_plugin_two.body = nesting_body\n text_plugin_two.save()\n text_plugin_two = self.reload(text_plugin_two)\n # the link is attached as a child?\n self.assertEquals(text_plugin_two.get_children().count(), 1)\n post_add_plugin_count = CMSPlugin.objects.count()\n self.assertEqual(post_add_plugin_count, 3)\n page_one.save()\n # get the plugins from the original page\n page_one = self.reload(page_one)\n page_one_ph_one = page_one.placeholders.get(slot = u\"col_sidebar\")\n page_one_ph_two = page_one.placeholders.get(slot = u\"col_left\")\n page_one_ph_three = page_one.placeholders.get(slot = u\"col_right\")\n # verify the plugins got created\n org_placeholder_one_plugins = page_one_ph_one.get_plugins()\n self.assertEquals(len(org_placeholder_one_plugins), 1)\n org_placeholder_two_plugins = page_one_ph_two.get_plugins()\n self.assertEquals(len(org_placeholder_two_plugins), 2)\n org_placeholder_three_plugins = page_one_ph_three.get_plugins()\n self.assertEquals(len(org_placeholder_three_plugins), 0)\n self.assertEquals(page_one.placeholders.count(), 3)\n \n placeholder_count = Placeholder.objects.count()\n self.assertEquals(placeholder_count, 3)\n self.assertEquals(CMSPlugin.objects.count(), 3)\n page_one_plugins = CMSPlugin.objects.all()\n # setup page_copy_target\n page_copy_target = create_page(\"Three Placeholder - page copy target\", \"col_three.html\", \"en\",\n position=\"last-child\", published=True, in_navigation=True)\n all_page_count = Page.objects.all().count()\n pre_copy_placeholder_count = Placeholder.objects.count()\n self.assertEquals(pre_copy_placeholder_count, 6)\n superuser = self.get_superuser()\n with self.login_user_context(superuser):\n # now move the parent text plugin to another placeholder\n post_data = {\n u'placeholder': u\"col_right\",\n u'placeholder_id': u\"%s\" % (page_one_ph_three.id),\n u'ids': u\"%s\" % (text_plugin_two.id),\n u'plugin_id': u\"%s\" % (text_plugin_two.id),\n }\n edit_url = URL_CMS_MOVE_PLUGIN % (page_one.id)\n response = self.client.post(edit_url, post_data)\n self.assertEqual(response.status_code, 200)\n self.assertEqual(response.content, u'ok')\n # check if the plugin got moved\n page_one = self.reload(page_one)\n text_plugin_two = self.reload(text_plugin_two)\n page_one_ph_one = page_one.placeholders.get(slot = u\"col_sidebar\")\n page_one_ph_two = page_one.placeholders.get(slot = u\"col_left\")\n page_one_ph_three = page_one.placeholders.get(slot = u\"col_right\")\n \n org_placeholder_one_plugins = page_one_ph_one.get_plugins()\n self.assertEquals(len(org_placeholder_one_plugins), 1)\n org_placeholder_two_plugins = page_one_ph_two.get_plugins()\n # the plugin got moved and child got moved\n self.assertEquals(len(org_placeholder_two_plugins), 0)\n org_placeholder_three_plugins = page_one_ph_three.get_plugins()\n self.assertEquals(len(org_placeholder_three_plugins), 2)\n # copy the page\n page_two = self.copy_page(page_one, page_copy_target)\n # validate the expected pages,placeholders,plugins,pluginbodies\n after_copy_page_plugin_count = CMSPlugin.objects.count()\n self.assertEquals(after_copy_page_plugin_count, 6)\n after_copy_page_count = Page.objects.all().count()\n after_copy_placeholder_count = Placeholder.objects.count()\n self.assertTrue((after_copy_page_count > all_page_count), msg = u\"no new page after copy\")\n self.assertTrue((after_copy_page_plugin_count > post_add_plugin_count), msg = u\"plugin count is not grown\")\n self.assertTrue((after_copy_placeholder_count > pre_copy_placeholder_count), msg = u\"placeholder count is not grown\") \n self.assertTrue((after_copy_page_count == 3), msg = u\"no new page after copy\")\n # validate the structure\n # orginal placeholder\n page_one = self.reload(page_one)\n page_one_ph_one = page_one.placeholders.get(slot=u\"col_sidebar\")\n page_one_ph_two = page_one.placeholders.get(slot=u\"col_left\")\n page_one_ph_three = page_one.placeholders.get(slot=u\"col_right\")\n # check if there are multiple pages assigned to this placeholders\n found_page = page_one_ph_one.page if page_one_ph_one else None\n self.assertEqual(found_page, page_one)\n found_page = page_one_ph_two.page if page_one_ph_two else None\n self.assertEqual(found_page, page_one)\n found_page = page_one_ph_three.page if page_one_ph_three else None\n self.assertEqual(found_page, page_one)\n page_two = self.reload(page_two)\n page_two_ph_one = page_two.placeholders.get(slot = u\"col_sidebar\")\n page_two_ph_two = page_two.placeholders.get(slot = u\"col_left\")\n page_two_ph_three = page_two.placeholders.get(slot = u\"col_right\")\n # check if there are multiple pages assigned to this placeholders\n found_page = page_two_ph_one.page if page_two_ph_one else None\n self.assertEqual(found_page, page_two)\n found_page = page_two_ph_two.page if page_two_ph_two else None\n self.assertEqual(found_page, page_two)\n found_page = page_two_ph_three.page if page_two_ph_three else None\n self.assertEqual(found_page, page_two)\n # check the stored placeholders org vs copy\n msg = u'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_one.pk, page_one_ph_one.pk, page_two.pk)\n self.assertNotEquals(page_two_ph_one.pk, page_one_ph_one.pk, msg)\n msg = u'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_two.pk, page_one_ph_two.pk, page_two.pk)\n self.assertNotEquals(page_two_ph_two.pk, page_one_ph_two.pk, msg)\n msg = u'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_three.pk, page_one_ph_three.pk, page_two.pk)\n self.assertNotEquals(page_two_ph_three.pk, page_one_ph_three.pk, msg)\n # get the plugins from the original page\n org_placeholder_one_plugins = page_one_ph_one.get_plugins()\n self.assertEquals(len(org_placeholder_one_plugins), 1)\n org_placeholder_two_plugins = page_one_ph_two.get_plugins()\n self.assertEquals(len(org_placeholder_two_plugins), 0)\n org_placeholder_three_plugins = page_one_ph_three.get_plugins()\n self.assertEquals(len(org_placeholder_three_plugins), 2)\n # get the plugins from the copied page\n copied_placeholder_one_plugins = page_two_ph_one.get_plugins()\n self.assertEquals(len(copied_placeholder_one_plugins), 1)\n copied_placeholder_two_plugins = page_two_ph_two.get_plugins()\n self.assertEquals(len(copied_placeholder_two_plugins), 0)\n copied_placeholder_three_plugins = page_two_ph_three.get_plugins()\n self.assertEquals(len(copied_placeholder_three_plugins), 2)\n # verify the plugins got copied\n # placeholder 1\n count_plugins_copied = len(copied_placeholder_one_plugins)\n count_plugins_org = len(org_placeholder_one_plugins)\n msg = u\"plugin count %s %s for placeholder one not equal\" % (count_plugins_copied, count_plugins_org)\n self.assertEquals(count_plugins_copied, count_plugins_org, msg) \n # placeholder 2\n count_plugins_copied = len(copied_placeholder_two_plugins)\n count_plugins_org = len(org_placeholder_two_plugins)\n msg = u\"plugin count %s %s for placeholder two not equal\" % (count_plugins_copied, count_plugins_org)\n self.assertEquals(count_plugins_copied, count_plugins_org, msg) \n # placeholder 3\n count_plugins_copied = len(copied_placeholder_three_plugins)\n count_plugins_org = len(org_placeholder_three_plugins)\n msg = u\"plugin count %s %s for placeholder three not equal\" % (count_plugins_copied, count_plugins_org)\n self.assertEquals(count_plugins_copied, count_plugins_org, msg)\n # verify the body of text plugin with nested link plugin\n # org to copied \n org_nested_text_plugin = None\n # do this iteration to find the real text plugin with the attached link\n # the inheritance mechanism for the cmsplugins works through \n # (tuple)get_plugin_instance()\n for x in org_placeholder_three_plugins: \n if x.plugin_type == u\"TextPlugin\":\n instance = x.get_plugin_instance()[0]\n if instance.body.startswith(pre_nesting_body):\n org_nested_text_plugin = instance\n break\n copied_nested_text_plugin = None\n for x in copied_placeholder_three_plugins: \n if x.plugin_type == u\"TextPlugin\":\n instance = x.get_plugin_instance()[0]\n if instance.body.startswith(pre_nesting_body):\n copied_nested_text_plugin = instance\n break\n msg = u\"orginal nested text plugin not found\"\n self.assertNotEquals(org_nested_text_plugin, None, msg=msg)\n msg = u\"copied nested text plugin not found\"\n self.assertNotEquals(copied_nested_text_plugin, None, msg=msg)\n # get the children ids of the texplugin with a nested link\n # to check if the body of the text is generated correctly\n org_link_child_plugin = org_nested_text_plugin.get_children()[0]\n copied_link_child_plugin = copied_nested_text_plugin.get_children()[0]\n # validate the textplugin body texts\n msg = u\"org plugin and copied plugin are the same\"\n self.assertTrue(org_link_child_plugin.id != copied_link_child_plugin.id, msg)\n needle = u\"plugin_obj_%s\"\n msg = u\"child plugin id differs to parent in body plugin_obj_id\"\n # linked child is in body\n self.assertTrue(org_nested_text_plugin.body.find(needle % (org_link_child_plugin.id)) != -1, msg)\n msg = u\"copy: child plugin id differs to parent in body plugin_obj_id\"\n self.assertTrue(copied_nested_text_plugin.body.find(needle % (copied_link_child_plugin.id)) != -1, msg)\n # really nothing else\n msg = u\"child link plugin id differs to parent body plugin_obj_id\"\n self.assertTrue(org_nested_text_plugin.body.find(needle % (copied_link_child_plugin.id)) == -1, msg)\n msg = u\"copy: child link plugin id differs to parent body plugin_obj_id\"\n self.assertTrue(copied_nested_text_plugin.body.find(needle % (org_link_child_plugin.id)) == -1, msg)\n # now reverse lookup the placeholders from the plugins\n org_placeholder = org_link_child_plugin.placeholder\n copied_placeholder = copied_link_child_plugin.placeholder\n msg = u\"placeholder of the orginal plugin and copied plugin are the same\"\n ok = ((org_placeholder.id != copied_placeholder.id))\n self.assertTrue(ok, msg)","def _create_copy(self, node, direction):\n new_node = copy.copy(node)\n new_node.set_uri(direction)\n new_location = get_location(direction)\n # Insert into db \n self.sm.create_node(new_node.tostring(), direction, NODETYPES[node.TYPE], location = new_location)\n return new_location","def edit(self, **kwargs):\n response = self._requester.request(\n \"PUT\",\n \"{}s/{}/pages/{}\".format(self.parent_type, self.parent_id, self.url),\n _kwargs=combine_kwargs(**kwargs),\n )\n\n page_json = response.json()\n page_json.update({\"course_id\": self.course_id})\n super(Page, self).set_attributes(page_json)\n\n return self","def create_page_in_admin(comicsite,title,content=\"testcontent\",permission_lvl=\"\"):\n \n if permission_lvl == \"\":\n permission_lvl = Page.ALL\n \n page_admin = PageAdmin(Page,admin.site)\n page = Page.objects.create(title=title,\n comicsite=comicsite,\n html=content,\n permission_lvl=permission_lvl)\n page_admin.first_save(page)\n return page","def test_copy_page_nested_plugin(self):\n with SettingsOverride(CMS_MODERATOR=False, CMS_PERMISSION=False):\n templates = []\n # setup page 1\n page_one = create_page(u\"Three Placeholder\", u\"col_three.html\", u\"en\",\n position=u\"last-child\", published=True, in_navigation=True)\n page_one_ph_one = page_one.placeholders.get(slot=u\"col_sidebar\")\n page_one_ph_two = page_one.placeholders.get(slot=u\"col_left\")\n page_one_ph_three = page_one.placeholders.get(slot=u\"col_right\")\n # add the text plugin to placeholder one\n text_plugin_en = add_plugin(page_one_ph_one, u\"TextPlugin\", u\"en\", body=\"Hello World\")\n self.assertEquals(text_plugin_en.id, CMSPlugin.objects.all()[0].id)\n self.assertEquals(text_plugin_en.get_children().count(), 0)\n pre_add_plugin_count = CMSPlugin.objects.count()\n self.assertEqual(pre_add_plugin_count, 1)\n ###\n # add a plugin to placeholder two\n ###\n pre_nesting_body = u\"<p>the nested text plugin with a link inside</p>\"\n text_plugin_two = add_plugin(page_one_ph_two, u\"TextPlugin\", u\"en\", body=pre_nesting_body)\n text_plugin_two = self.reload(text_plugin_two)\n # prepare nesting plugin\n page_one_ph_two = self.reload(page_one_ph_two)\n text_plugin_two = self.reload(text_plugin_two)\n link_plugin = add_plugin(page_one_ph_two, u\"LinkPlugin\", u\"en\", target=text_plugin_two)\n link_plugin.name = u\"django-cms Link\"\n link_plugin.url = u\"https://www.django-cms.org\" \n link_plugin.parent = text_plugin_two\n link_plugin.save()\n \n link_plugin = self.reload(link_plugin)\n text_plugin_two = self.reload(text_plugin_two)\n in_txt = \"\"\"<img id=\"plugin_obj_%s\" title=\"Link\" alt=\"Link\" src=\"/static/cms/images/plugins/link.png\">\"\"\"\n nesting_body = \"%s<p>%s</p>\" % (text_plugin_two.body, (in_txt % (link_plugin.id)))\n # emulate the editor in admin that adds some txt for the nested plugin\n text_plugin_two.body = nesting_body\n text_plugin_two.save()\n text_plugin_two = self.reload(text_plugin_two)\n # the link is attached as a child?\n self.assertEquals(text_plugin_two.get_children().count(), 1)\n post_add_plugin_count = CMSPlugin.objects.count()\n self.assertEqual(post_add_plugin_count, 3)\n page_one.save()\n # get the plugins from the original page\n page_one = self.reload(page_one)\n page_one_ph_one = page_one.placeholders.get(slot = u\"col_sidebar\")\n page_one_ph_two = page_one.placeholders.get(slot = u\"col_left\")\n page_one_ph_three = page_one.placeholders.get(slot = u\"col_right\")\n # verifiy the plugins got created\n org_placeholder_one_plugins = page_one_ph_one.get_plugins()\n self.assertEquals(len(org_placeholder_one_plugins), 1)\n org_placeholder_two_plugins = page_one_ph_two.get_plugins()\n self.assertEquals(len(org_placeholder_two_plugins), 2)\n org_placeholder_three_plugins = page_one_ph_three.get_plugins()\n self.assertEquals(len(org_placeholder_three_plugins), 0)\n self.assertEquals(page_one.placeholders.count(), 3)\n placeholder_count = Placeholder.objects.count()\n self.assertEquals(placeholder_count, 3)\n self.assertEquals(CMSPlugin.objects.count(), 3)\n page_one_plugins = CMSPlugin.objects.all()\n ##\n # setup page_copy_target page\n ##\n page_copy_target = create_page(\"Three Placeholder - page copy target\", \"col_three.html\", \"en\",\n position=\"last-child\", published=True, in_navigation=True)\n all_page_count = Page.objects.all().count()\n pre_copy_placeholder_count = Placeholder.objects.count()\n self.assertEquals(pre_copy_placeholder_count, 6)\n # copy the page\n superuser = self.get_superuser()\n with self.login_user_context(superuser):\n page_two = self.copy_page(page_one, page_copy_target)\n # validate the expected pages,placeholders,plugins,pluginbodies\n after_copy_page_plugin_count = CMSPlugin.objects.count()\n self.assertEquals(after_copy_page_plugin_count, 6)\n # check the amount of copied stuff\n after_copy_page_count = Page.objects.all().count()\n after_copy_placeholder_count = Placeholder.objects.count()\n self.assertTrue((after_copy_page_count > all_page_count), msg = u\"no new page after copy\")\n self.assertTrue((after_copy_page_plugin_count > post_add_plugin_count), msg = u\"plugin count is not grown\")\n self.assertTrue((after_copy_placeholder_count > pre_copy_placeholder_count), msg = u\"placeholder count is not grown\") \n self.assertTrue((after_copy_page_count == 3), msg = u\"no new page after copy\")\n # orginal placeholder\n page_one = self.reload(page_one)\n page_one_ph_one = page_one.placeholders.get(slot = u\"col_sidebar\")\n page_one_ph_two = page_one.placeholders.get(slot = u\"col_left\")\n page_one_ph_three = page_one.placeholders.get(slot = u\"col_right\")\n # check if there are multiple pages assigned to this placeholders\n found_page = page_one_ph_one.page if page_one_ph_one else None\n self.assertEqual(found_page, page_one)\n found_page = page_one_ph_two.page if page_one_ph_two else None\n self.assertEqual(found_page, page_one)\n found_page = page_one_ph_three.page if page_one_ph_three else None\n self.assertEqual(found_page, page_one)\n \n page_two = self.reload(page_two)\n page_two_ph_one = page_two.placeholders.get(slot = u\"col_sidebar\")\n page_two_ph_two = page_two.placeholders.get(slot = u\"col_left\")\n page_two_ph_three = page_two.placeholders.get(slot = u\"col_right\")\n # check if there are multiple pages assigned to this placeholders\n found_page = page_two_ph_one.page if page_two_ph_one else None\n self.assertEqual(found_page, page_two)\n found_page = page_two_ph_two.page if page_two_ph_two else None\n self.assertEqual(found_page, page_two)\n found_page = page_two_ph_three.page if page_two_ph_three else None\n self.assertEqual(found_page, page_two)\n # check the stored placeholders org vs copy\n msg = 'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_one.pk, page_one_ph_one.pk, page_two.pk)\n self.assertNotEquals(page_two_ph_one.pk, page_one_ph_one.pk, msg)\n msg = 'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_two.pk, page_one_ph_two.pk, page_two.pk)\n self.assertNotEquals(page_two_ph_two.pk, page_one_ph_two.pk, msg)\n msg = 'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_three.pk, page_one_ph_three.pk, page_two.pk)\n self.assertNotEquals(page_two_ph_three.pk, page_one_ph_three.pk, msg)\n # get the plugins from the original page\n org_placeholder_one_plugins = page_one_ph_one.get_plugins()\n self.assertEquals(len(org_placeholder_one_plugins), 1)\n org_placeholder_two_plugins = page_one_ph_two.get_plugins()\n self.assertEquals(len(org_placeholder_two_plugins), 2)\n org_placeholder_three_plugins = page_one_ph_three.get_plugins()\n self.assertEquals(len(org_placeholder_three_plugins), 0)\n # get the plugins from the copied page\n copied_placeholder_one_plugins = page_two_ph_one.get_plugins()\n self.assertEquals(len(copied_placeholder_one_plugins), 1)\n copied_placeholder_two_plugins = page_two_ph_two.get_plugins()\n self.assertEquals(len(copied_placeholder_two_plugins), 2)\n copied_placeholder_three_plugins = page_two_ph_three.get_plugins()\n self.assertEquals(len(copied_placeholder_three_plugins), 0)\n # verify the plugins got copied\n # placeholder 1\n count_plugins_copied = len(copied_placeholder_one_plugins)\n count_plugins_org = len(org_placeholder_one_plugins)\n msg = u\"plugin count %s %s for placeholder one not equal\" % (count_plugins_copied, count_plugins_org)\n self.assertEquals(count_plugins_copied, count_plugins_org, msg) \n # placeholder 2\n count_plugins_copied = len(copied_placeholder_two_plugins)\n count_plugins_org = len(org_placeholder_two_plugins)\n msg = u\"plugin count %s %s for placeholder two not equal\" % (count_plugins_copied, count_plugins_org)\n self.assertEquals(count_plugins_copied, count_plugins_org, msg) \n # placeholder 3\n count_plugins_copied = len(copied_placeholder_three_plugins)\n count_plugins_org = len(org_placeholder_three_plugins)\n msg = u\"plugin count %s %s for placeholder three not equal\" % (count_plugins_copied, count_plugins_org)\n self.assertEquals(count_plugins_copied, count_plugins_org, msg)\n # verify the body of text plugin with nested link plugin\n # org to copied \n org_nested_text_plugin = None\n # do this iteration to find the real text plugin with the attached link\n # the inheritance mechanism for the cmsplugins works through \n # (tuple)get_plugin_instance()\n for x in org_placeholder_two_plugins: \n if x.plugin_type == u\"TextPlugin\":\n instance = x.get_plugin_instance()[0]\n if instance.body.startswith(pre_nesting_body):\n org_nested_text_plugin = instance\n break\n copied_nested_text_plugin = None\n for x in copied_placeholder_two_plugins: \n if x.plugin_type == u\"TextPlugin\":\n instance = x.get_plugin_instance()[0]\n if instance.body.startswith(pre_nesting_body):\n copied_nested_text_plugin = instance\n break\n msg = u\"orginal nested text plugin not found\"\n self.assertNotEquals(org_nested_text_plugin, None, msg=msg)\n msg = u\"copied nested text plugin not found\"\n self.assertNotEquals(copied_nested_text_plugin, None, msg=msg)\n # get the children ids of the texplugin with a nested link\n # to check if the body of the text is genrated correctly\n org_link_child_plugin = org_nested_text_plugin.get_children()[0]\n copied_link_child_plugin = copied_nested_text_plugin.get_children()[0]\n # validate the textplugin body texts\n msg = u\"org plugin and copied plugin are the same\"\n self.assertTrue(org_link_child_plugin.id != copied_link_child_plugin.id, msg)\n needle = u\"plugin_obj_%s\"\n msg = u\"child plugin id differs to parent in body plugin_obj_id\"\n # linked child is in body\n self.assertTrue(org_nested_text_plugin.body.find(needle % (org_link_child_plugin.id)) != -1, msg)\n msg = u\"copy: child plugin id differs to parent in body plugin_obj_id\"\n self.assertTrue(copied_nested_text_plugin.body.find(needle % (copied_link_child_plugin.id)) != -1, msg)\n # really nothing else\n msg = u\"child link plugin id differs to parent body plugin_obj_id\"\n self.assertTrue(org_nested_text_plugin.body.find(needle % (copied_link_child_plugin.id)) == -1, msg)\n msg = u\"copy: child link plugin id differs to parent body plugin_obj_id\"\n self.assertTrue(copied_nested_text_plugin.body.find(needle % (org_link_child_plugin.id)) == -1, msg)\n # now reverse lookup the placeholders from the plugins\n org_placeholder = org_link_child_plugin.placeholder\n copied_placeholder = copied_link_child_plugin.placeholder\n msg = u\"placeholder of the orginal plugin and copied plugin are the same\"\n ok = ((org_placeholder.id != copied_placeholder.id))\n self.assertTrue(ok, msg)","def copy_structure(self, other_directory):\n pass","def cpr(src, dst):\n shutil.copytree(src, dst)","def test_placeholder_inherit_content(self):\n from pages import settings as pages_settings\n setattr(pages_settings, \"PAGE_USE_SITE_ID\", False)\n author = User.objects.all()[0]\n p1 = self.new_page(content={'inher':'parent-content'})\n p2 = self.new_page()\n template = django.template.loader.get_template('pages/tests/test7.html')\n context = Context({'current_page': p2, 'lang':'en-us'})\n self.assertEqual(template.render(context), '')\n \n p2.move_to(p1, position='first-child')\n self.assertEqual(template.render(context), 'parent-content')","def update_children(page, prefix=None, walked_pages=None):\n walked_pages = walked_pages if walked_pages else []\n # Perfix used to determine the children path.\n page_segment = page.path\n if prefix:\n page_segment = prefix + '/' + page_segment\n page.real_path = page_segment\n page.save()\n for child in page.children.all():\n # Update the real path for this descendant.\n if child in walked_pages:\n # This page has been processed before, ignore.\n continue\n walked_pages.append(child)\n update_children(child, page_segment, walked_pages)\n return True","def create_page_in_projectadmin(comicsite,title,content=\"testcontent\",permission_lvl=\"\",comicsite_for_page=\"\"):\n # to be able to test creating a page for a different comicsite from this admin\n # should not be possible, but that's what tests are for\n if comicsite_for_page == \"\":\n comicsite_for_page = comicsite\n \n # Rename, trying to call comicsite 'project' everywhere. Doing a full\n # rename is very hard however \n project = comicsite\n \n \n # Create the overarching admin interface for any single project \n projectadminsite = get_projectadmin(project)\n \n # Each model in the admin interface has its own model admin, which is\n # wrapped and modified by projectadminsite. Get this modified modeladmin\n pageadmin = projectadminsite._registry[Page]\n\n # Now create the page and save in the correct project-only modified object\n # admin...\n if permission_lvl == \"\":\n permission_lvl = Page.ALL\n \n page = Page.objects.create(title=title,\n comicsite=comicsite,\n html=content,\n permission_lvl=permission_lvl)\n pageadmin.first_save(page)\n return page","def copytree(src, dest):\n shutil.copytree(src, dest)\n restorecon(dest, recursive=True)","def menu_save_copy(self, event=None):\n if self.app.children:\n self.app.childActive.saveCopy()","def post(self, request, doc_id):\n before = request.POST.get('before', False)\n after = request.POST.get('after', False)\n\n try:\n document = Document.objects.get(id=doc_id)\n except Document.DoesNotExist:\n raise Http404(\"Document does not exists\")\n\n if request.user.has_perm(\n Access.PERM_WRITE, document\n ):\n Document.paste_pages(\n user=request.user,\n parent_id=document.parent,\n dst_document=document,\n doc_pages=request.pages.all(),\n before=before,\n after=after\n )\n\n request.pages.clear()\n\n return Response(status=status.HTTP_204_NO_CONTENT)\n\n return Response(\n status=status.HTTP_403_FORBIDDEN,\n data={\n 'msg': _(\n \"You don't have permissions to paste pages\"\n \" in this document.\"\n )\n }\n )","def copy(self):\r\n ret=' '\r\n if self.REQUEST.SESSION.has_key('my_path'):\r\n\t zpath=self.REQUEST.SESSION['my_path'].replace('toolbox_root','').strip('/')\r\n\t #ret=zpath\r\n\t if self.REQUEST.SESSION.has_key('copy_bild'):\r\n\t\t cp_bild=self.REQUEST.SESSION['copy_bild'].split('/')[-1].strip('/')\r\n\t\t cp_path=str('/').join(self.REQUEST.SESSION['copy_bild'].split('/')[0:-1])\r\n\t\t #ret+=' '+cp_path+' '+cp_bild\r\n\t\t if cp_path!=zpath:\r\n\t\t \tn_id=search_id(self,self.restrictedTraverse(zpath).objectValues('Image'))\r\n\t\t \t#ret+=' '+n_id\r\n\t\t\tfor x in liste_val:\r\n\t\t\t\ttry:\r\n\t\t\t\t\tfor obj in self.restrictedTraverse(cp_path).objectValues('Image'):\r\n\t\t\t\t\t if str(obj.getId())[0:6]==cp_bild:\r\n\t\t\t\t\t\tmy_clip=self.restrictedTraverse(cp_path).manage_copyObjects([obj.getId()])\r\n\t\t\t\t\t\tcopied=self.restrictedTraverse(zpath).manage_pasteObjects(my_clip)\r\n\t\t\t\t\t\t#ret+=' new id : '+str(copied[0]['new_id'])\r\n\t\t\t\t\t\t#if str(copied[0]['new_id']).split('_')[0]!=n_id:\r\n\t\t\t\t\t\t#\tself.restrictedTraverse(zpath).manage_renameObjects([str(copied[0]['new_id'])],[str(n_id+x)])\r\n\t\t\t\t\t\t\t#ret +=' False '\r\n\t\t\t\t\t\t#ret+='<br>\\n'\r\n\t\t\t\texcept:\r\n\t\t\t\t\tret+=''\r\n else:\r\n\t ret=' '\r\n return ' '","def copy(\n syn,\n entity,\n destinationId,\n skipCopyWikiPage=False,\n skipCopyAnnotations=False,\n **kwargs,\n):\n updateLinks = kwargs.get(\"updateLinks\", True)\n updateSynIds = kwargs.get(\"updateSynIds\", True)\n entitySubPageId = kwargs.get(\"entitySubPageId\", None)\n destinationSubPageId = kwargs.get(\"destinationSubPageId\", None)\n\n mapping = _copyRecursive(\n syn, entity, destinationId, skipCopyAnnotations=skipCopyAnnotations, **kwargs\n )\n if not skipCopyWikiPage:\n for oldEnt in mapping:\n copyWiki(\n syn,\n oldEnt,\n mapping[oldEnt],\n entitySubPageId=entitySubPageId,\n destinationSubPageId=destinationSubPageId,\n updateLinks=updateLinks,\n updateSynIds=updateSynIds,\n entityMap=mapping,\n )\n return mapping","def copy_drafts():\r\n draft_dir = path(source_dir) / course_name / DRAFT_DIR\r\n if draft_dir.isdir():\r\n shutil.copytree(draft_dir, copy_root / DRAFT_DIR)","def copydir(self):\n pass","def new_page(request, parent_id):\n if parent_id:\n parent_page = models.Page.get_by_id(int(parent_id))\n else:\n parent_page = models.Page.get_root()\n if parent_page:\n # there is a root, lets force everything to be a child of the root\n # and set the parent_id\n parent_id = parent_page.key().id()\n else:\n # TODO(gpennington): Figure out a more intuitive method for site\n # initialization\n parent_page = utility.set_up_data_store()\n return utility.edit_updated_page(parent_page.key().id())\n\n if not parent_page.user_can_write(request.profile):\n return utility.forbidden(request)\n return edit_page(request, None, parent_id=parent_id)","def copySpecial():\n depNode = nuke.dependencies(nuke.selectedNode())\n dependNode = nuke.dependentNodes(nuke.INPUTS or nuke.HIDDEN_INPUTS or nuke.EXPRESSIONS, [nuke.selectedNode()])\n i = 0\n if dependNode[0].Class() in ['Scene', 'MergeGeo']:\n i = nuke.inputs(dependNode[0])+1\n\n nuke.nodeCopy(nukescripts.cut_paste_file())\n\n for node in nuke.allNodes():\n node['selected'].setValue(0)\n\n nuke.nodePaste(nukescripts.cut_paste_file())\n\n newNode = nuke.selectedNode()\n newNode.setInput(0, depNode[0])\n dependNode[0].setInput(i+1, newNode)","def add_page(self, page): \n self.pages.append(Page(page))","def edit_page(request, page_id, parent_id=None):\n page = None\n files = None\n\n if page_id:\n page = models.Page.get_by_id(int(page_id))\n if not page:\n return utility.page_not_found(\n request, 'No page exists with id %r.' % page_id)\n if not page.user_can_write(request.profile):\n return utility.forbidden(request)\n files = list(\n models.FileStore.all().filter('parent_page =', page).order('name'))\n for item in files:\n item.icon = '/static/images/fileicons/%s.png' % item.name.split('.')[-1]\n\n acl_data = None\n\n if page:\n all_group_keys = [\n g.key() for g in models.UserGroup.all().order('name')]\n groups_without_write_keys = [\n k for k in all_group_keys if k not in page.acl.group_write]\n groups_without_read_keys = [\n k for k in all_group_keys if k not in page.acl.group_read]\n acl_data = {\n 'groups_without_write': models.UserGroup.get(groups_without_write_keys),\n 'groups_without_read': models.UserGroup.get(groups_without_read_keys),\n 'group_write': models.UserGroup.get(page.acl.group_write),\n 'group_read': models.UserGroup.get(page.acl.group_read),\n 'user_write': models.UserProfile.get(page.acl.user_write),\n 'user_read': models.UserProfile.get(page.acl.user_read),\n 'inherits_acl': page.inherits_acl(),\n }\n\n if not request.POST:\n form = forms.PageEditForm(data=None, instance=page)\n return utility.respond(request, 'admin/edit_page',\n {'form': form, 'page': page, 'files': files,\n 'acl_data': acl_data})\n\n form = forms.PageEditForm(data=request.POST, instance=page)\n\n if not form.errors:\n try:\n page = form.save(commit=False)\n except ValueError, err:\n form.errors['__all__'] = unicode(err)\n if form.errors:\n return utility.respond(request, 'admin/edit_page',\n {'form': form, 'page': page, 'files': files})\n\n page.content = request.POST['editorHtml']\n if parent_id and not page.parent_page:\n page.parent_page = models.Page.get_by_id(int(parent_id))\n page.put()\n\n return utility.edit_updated_page(page.key().id(),\n message_id='msgChangesSaved')","def copy_children(self):\n\n # Create a group\n self.fileh.create_group('/', 'agroup')\n # Create several objects there\n for i in range(10):\n # Create a new array\n self.fileh.create_array('/agroup', 'array' + str(i), self.a1)\n # Excercise copy_children\n for i in range(self.nobjects):\n # Create another group for destination\n self.fileh.create_group('/', 'anothergroup' + str(i))\n # Copy children from /agroup to /anothergroup+i\n self.fileh.copy_children('/agroup', '/anothergroup' + str(i))\n # Put a mark\n self.fileh.mark()\n # Unwind all marks sequentially\n for i in range(self.niter):\n t1 = clock()\n for i in range(self.nobjects):\n self.fileh.undo()\n if verbose:\n print(\"u\", end=' ')\n if verbose:\n print()\n undo = clock() - t1\n # Rewind all marks sequentially\n t1 = clock()\n for i in range(self.nobjects):\n self.fileh.redo()\n if verbose:\n print(\"r\", end=' ')\n if verbose:\n print()\n redo = clock() - t1\n\n print((\"Time for Undo, Redo (copy_children):\", undo, \"s, \",\n redo, \"s\"))","def MovePage(self, page, new_idx):\r\n \r\n idx = self.GetIdxFromWindow(page)\r\n if idx == -1:\r\n return False\r\n\r\n # get page entry, make a copy of it\r\n p = self.GetPage(idx)\r\n\r\n # remove old page entry\r\n self.RemovePage(page)\r\n\r\n # insert page where it should be\r\n self.InsertPage(page, p, new_idx)\r\n\r\n return True","def testCopyCollection(self):\n copy = self.node.copy_collection()\n\n self.assertEqual(\n self.node.type,\n copy.type\n )\n\n self.assertEqual(\n self.node.desc,\n copy.desc\n )\n\n self.assertEqual(\n self.node.input_desc,\n copy.input_desc\n )\n\n self.assertEqual(\n self.node.viewing_desc,\n copy.viewing_desc\n )\n\n self.assertEqual(\n self.node.all_children,\n copy.all_children\n )","def copy(self):","def __copy__(self):\n return self.__class__(self.baseurl, self.template, self.selection[:],\n self.slice[:], self.application)","def process_page(html,dest):\n html0 = html[:]\n to_root = os.path.relpath(export_path,dest)\n to_root = to_root[1:]# Change '../' or '..' to '.' or './'\n \n # Fix links to directories first since that is easier to find\n html,N1 = re_dirlinks.subn(r'\\1=\"/\\2/index.html\"',html)\n \n # all pages links\n html,N2 = re_all.subn(r'\\1=\"/_all/\\2/index.html\"',html)\n \n # Add index.html for any other internal links. NOTE: by preprocessing\n # all internal links from the main content will already end in .html so this\n # is just special pages.\n for match in re_intlinks.finditer(html):\n dest = match.groups()[-1]\n ext = os.path.splitext(dest)[-1]\n if ext == '':\n old = r'{}=\"/{}\"'.format(*match.groups())\n new = r'{}=\"/{}\"'.format(match.groups()[0], os.path.join(match.groups()[1],'index.html') )\n html = html.replace(old,new)\n \n # Now make all links to the root\n html,N3 = re_intlinks.subn(r'\\1=\"{}/\\2\"'.format(to_root),html)\n \n # Remove the search stuff\n out = []\n ff = False\n for line in html.split('\\n'):\n if not ff and '<!-- search -->' not in line:\n out.append(line)\n continue\n \n if '<!-- search -->' in line:\n ff = True\n \n if ff and '<!-- /search -->' in line:\n ff = False\n\n html = '\\n'.join(out)\n return html","def copyTo(self, folder):\n copyUrl = self.metaData.getLink(\"copy\")\n\n if not hasattr(folder, \"metaData\"): raise TypeError(\"Your newFolder does not have a metaData property\")\n assert getattr(folder, \"selfLink\")\n assert copyUrl is not None\n\n header = self._baseHeader.copy()\n header['Content-type'] = \"application/vnd.huddle.data+json\"\n body = '{ \"targetFolder\":{ \"link\":{ \"rel\": \"self\", \"href\": \"' + folder.selfLink + '\" } } }'\n\n response = self._adapter.postRequest(copyUrl, header, body)\n\n return Document(self._client, response['Headers']['location'])","def move_page(self, target, position='first-child'):\n self.move_to(target, position)\n # fire signal\n \n self.force_moderation_action = PageModeratorState.ACTION_MOVE\n cms_signals.page_moved.send(sender=Page, instance=self) #titles get saved before moderation\n self.save(change_state=True) # always save the page after move, because of publisher","def copy():\n copy2(per, per_old)","def copy_tree(self, infile, outfile,\n preserve_mode=1, preserve_times=1, preserve_symlinks=0,\n level=1, condition=None):\n return copy_tree(\n infile, outfile,\n preserve_mode,preserve_times,preserve_symlinks,\n not self.force,\n dry_run=self.dry_run,\n condition=condition)","def insert_copied(self, *args):\n copy = self.get_copied_food()\n if copy is not None:\n fsp = self.get_food_search_panel()\n fsp.reset_food_icon()\n if type(copy.food) == Food:\n food = FoodUsage(food=copy.food, amount=decimal.Decimal(100))\n if self.meal.foods is None:\n self.meal.foods = [food]\n else:\n self.meal.foods.append(food)\n\n self.add_food_node(food)\n else: # copy.food is Recipe\n recipe_exec = Recipe(name=copy.food.name, is_template=False, notes=\"\",\n serving_size=decimal.Decimal(1), template=copy.food)\n for ing in copy.food.ingredients:\n recipe_exec.add_food(ing.food, ing.amount)\n self.meal.add_recipe(recipe_exec)\n recipe_node = TreeViewRecipe(recipe=recipe_exec,\n meal_tree_box=self.meal_tree_box,\n parent_node=self)\n fsp.remove_copy()\n self.update_text(True)","def _copyTemplate(sourceBase, destination):\n source = os.path.normpath(os.path.join(sourceBase, \"_New_Region\", \"Template\"))\n copy_tree(source, destination, preserve_mode=1, preserve_times=1, preserve_symlinks=1)","def on_page_content(self, content, page, config, files):\n logging.debug(\"--- on_pre_page ---\")\n logging.debug(self.config)\n logging.debug(page.__repr__())\n\n source_dir = os.path.dirname(page.file.abs_src_path)\n logging.debug('source dir: ' + source_dir)\n\n dest_dir = os.path.dirname(page.file.abs_dest_path)\n os.makedirs(dest_dir, exist_ok=True)\n exists_dest_dir = os.path.isdir(dest_dir)\n logging.debug('dest dir: ' + dest_dir +\n ' (exists: ' + str(exists_dest_dir) + ')')\n\n source_file = os.path.join(source_dir, '.htaccess')\n exists_dest_file = os.path.isfile(source_file)\n logging.debug('source file: ' + source_file +\n ' (exists: ' + str(exists_dest_file) + ')')\n\n exists_dest_file and utils.copy_file(source_file, dest_dir)\n logging.debug(\"--- /on_pre_page ---\")\n\n return content","def CopyTo(self, *args, **kwargs):\n pass","def change_directory(\n self,\n destination: PagePathLike\n ) -> None:\n try:\n full_path: str = self.explode(destination)\n except OutOfBoundsPageError as e:\n raise e\n\n if full_path not in self:\n raise NoSuchPageError(full_path)\n elif full_path == self.current_page.path:\n return\n\n self._back_page_history_stack.append(self._current_page)\n self._current_page = self[full_path]","def save(self, force_insert=False, force_update=False):\n if self.moderate_descendants:\n self.moderate_children = True\n else:\n self.moderate_children = False\n super(PageModerator, self).save(force_insert, force_update)","def create_page(self, space, title, body, parent_id=None, update_message=None):\n page_structure = {\n 'title': title,\n 'type': 'page',\n 'space': {\n 'key': space\n },\n 'body': {\n 'storage': {\n 'value': body,\n 'representation': 'storage'\n }\n }\n }\n\n if parent_id is not None:\n if type(parent_id) is str:\n parent_id = int(parent_id)\n page_structure['ancestors'] = [{'id': parent_id}]\n\n if update_message is not None:\n page_structure['version'] = {'message': update_message}\n\n print(json.dumps(page_structure))\n return self.api.content.post(json=page_structure)","def make_site_dx(context):\n portal = getSite()\n\n if portal._tree is not None:\n # We assume the object has been already initialized\n return\n\n portal._initBTrees()\n\n for obj_meta in portal._objects:\n obj_id = obj_meta[\"id\"]\n logger.info(\"Migrating object %r\", obj_id)\n # Load the content object ...\n obj = portal.__dict__.pop(obj_id)\n if not isinstance(obj, Broken) and obj_id not in (\n \"portal_quickinstaller\",\n \"portal_form_controller\",\n ):\n # ...and insert it into the btree.\n # Use _setOb so we don't reindex stuff: the paths stay the same.\n portal._setOb(obj_id, obj)\n\n delattr(portal, \"_objects\")\n portal._p_changed = True","def copy_tree_checker(src, dst):\n copy_tree(src, dst)\n return True","def update_page_entity(self,pid,pge):\n if not hasattr(self,'_pages_entities'):\n self.load_pages()\n else:\n pgs = self.get_pages_list()\n for i in xrange(len(pgs)):\n pe = pgs[i]\n if pe.key().id() == pid:\n pgs[i] = pge\n break","def _copy_subdag(self, user_id, destination_version, block_key, source_blocks, destination_blocks, blacklist):\n orphans = set()\n destination_block = destination_blocks.get(block_key)\n new_block = source_blocks[block_key]\n if destination_block:\n # reorder children to correspond to whatever order holds for source.\n # remove any which source no longer claims (put into orphans)\n # add any which are being copied\n source_children = new_block.fields.get('children', [])\n existing_children = destination_block.fields.get('children', [])\n destination_reordered = SparseList()\n for child in existing_children:\n try:\n index = source_children.index(child)\n destination_reordered[index] = child\n except ValueError:\n orphans.add(BlockKey(*child))\n if blacklist != EXCLUDE_ALL:\n for index, child in enumerate(source_children):\n if child not in blacklist:\n destination_reordered[index] = child\n # the history of the published leaps between publications and only points to\n # previously published versions.\n previous_version = destination_block.edit_info.update_version\n destination_block = copy.deepcopy(new_block)\n destination_block.fields['children'] = destination_reordered.compact_list()\n destination_block.edit_info.previous_version = previous_version\n destination_block.edit_info.update_version = destination_version\n destination_block.edit_info.edited_by = user_id\n destination_block.edit_info.edited_on = datetime.datetime.now(UTC)\n else:\n destination_block = self._new_block(\n user_id, new_block.block_type,\n self._filter_blacklist(copy.copy(new_block.fields), blacklist),\n new_block.definition,\n destination_version,\n raw=True,\n asides=new_block.asides,\n block_defaults=new_block.defaults\n )\n # Extend the block's new edit_info with any extra edit_info fields from the source (e.g. original_usage):\n for key, val in new_block.edit_info.to_storable().items():\n if getattr(destination_block.edit_info, key) is None:\n setattr(destination_block.edit_info, key, val)\n\n # If the block we are copying from was itself a copy, then just\n # reference the original source, rather than the copy.\n destination_block.edit_info.source_version = (\n new_block.edit_info.source_version or new_block.edit_info.update_version\n )\n\n if blacklist != EXCLUDE_ALL:\n for child in destination_block.fields.get('children', []):\n if child not in blacklist:\n orphans.update(\n self._copy_subdag(\n user_id, destination_version, BlockKey(*child), source_blocks, destination_blocks, blacklist\n )\n )\n destination_blocks[block_key] = destination_block\n return orphans","def copyWiki(\n syn,\n entity,\n destinationId,\n entitySubPageId=None,\n destinationSubPageId=None,\n updateLinks=True,\n updateSynIds=True,\n entityMap=None,\n):\n\n # Validate input parameters\n if entitySubPageId:\n entitySubPageId = str(int(entitySubPageId))\n if destinationSubPageId:\n destinationSubPageId = str(int(destinationSubPageId))\n\n oldOwn = syn.get(entity, downloadFile=False)\n # getWikiHeaders fails when there is no wiki\n\n try:\n oldWikiHeaders = syn.getWikiHeaders(oldOwn)\n except SynapseHTTPError as e:\n if e.response.status_code == 404:\n return []\n else:\n raise e\n\n newOwn = syn.get(destinationId, downloadFile=False)\n wikiIdMap = dict()\n newWikis = dict()\n # If entitySubPageId is given but not destinationSubPageId, set the pageId to \"\" (will get the root page)\n # A entitySubPage could be copied to a project without any wiki pages, this has to be checked\n newWikiPage = None\n if destinationSubPageId:\n try:\n newWikiPage = syn.getWiki(newOwn, destinationSubPageId)\n except SynapseHTTPError as e:\n if e.response.status_code == 404:\n pass\n else:\n raise e\n if entitySubPageId:\n oldWikiHeaders = _getSubWikiHeaders(oldWikiHeaders, entitySubPageId)\n\n if not oldWikiHeaders:\n return []\n\n for wikiHeader in oldWikiHeaders:\n wiki = syn.getWiki(oldOwn, wikiHeader[\"id\"])\n syn.logger.info(\"Got wiki %s\" % wikiHeader[\"id\"])\n if not wiki.get(\"attachmentFileHandleIds\"):\n new_file_handles = []\n else:\n results = [\n syn._getFileHandleDownload(\n filehandleId, wiki.id, objectType=\"WikiAttachment\"\n )\n for filehandleId in wiki[\"attachmentFileHandleIds\"]\n ]\n # Get rid of the previews\n nopreviews = [\n attach[\"fileHandle\"]\n for attach in results\n if not attach[\"fileHandle\"][\"isPreview\"]\n ]\n contentTypes = [attach[\"contentType\"] for attach in nopreviews]\n fileNames = [attach[\"fileName\"] for attach in nopreviews]\n copiedFileHandles = copyFileHandles(\n syn,\n nopreviews,\n [\"WikiAttachment\"] * len(nopreviews),\n [wiki.id] * len(nopreviews),\n contentTypes,\n fileNames,\n )\n # Check if failurecodes exist\n for filehandle in copiedFileHandles:\n if filehandle.get(\"failureCode\") is not None:\n raise ValueError(\n \"%s dataFileHandleId: %s\"\n % (\n filehandle[\"failureCode\"],\n filehandle[\"originalFileHandleId\"],\n )\n )\n new_file_handles = [\n filehandle[\"newFileHandle\"][\"id\"] for filehandle in copiedFileHandles\n ]\n # for some reason some wikis don't have titles?\n if hasattr(wikiHeader, \"parentId\"):\n newWikiPage = Wiki(\n owner=newOwn,\n title=wiki.get(\"title\", \"\"),\n markdown=wiki.markdown,\n fileHandles=new_file_handles,\n parentWikiId=wikiIdMap[wiki.parentWikiId],\n )\n newWikiPage = syn.store(newWikiPage)\n else:\n if destinationSubPageId is not None and newWikiPage is not None:\n newWikiPage[\"attachmentFileHandleIds\"] = new_file_handles\n newWikiPage[\"markdown\"] = wiki[\"markdown\"]\n newWikiPage[\"title\"] = wiki.get(\"title\", \"\")\n # Need to add logic to update titles here\n newWikiPage = syn.store(newWikiPage)\n else:\n newWikiPage = Wiki(\n owner=newOwn,\n title=wiki.get(\"title\", \"\"),\n markdown=wiki.markdown,\n fileHandles=new_file_handles,\n parentWikiId=destinationSubPageId,\n )\n newWikiPage = syn.store(newWikiPage)\n newWikis[newWikiPage[\"id\"]] = newWikiPage\n wikiIdMap[wiki[\"id\"]] = newWikiPage[\"id\"]\n\n if updateLinks:\n syn.logger.info(\"Updating internal links:\\n\")\n newWikis = _updateInternalLinks(newWikis, wikiIdMap, entity, destinationId)\n syn.logger.info(\"Done updating internal links.\\n\")\n\n if updateSynIds and entityMap is not None:\n syn.logger.info(\"Updating Synapse references:\\n\")\n newWikis = _updateSynIds(newWikis, wikiIdMap, entityMap)\n syn.logger.info(\"Done updating Synapse IDs.\\n\")\n\n syn.logger.info(\"Storing new Wikis\\n\")\n for oldWikiId in wikiIdMap.keys():\n newWikiId = wikiIdMap[oldWikiId]\n newWikis[newWikiId] = syn.store(newWikis[newWikiId])\n syn.logger.info(\"\\tStored: %s\\n\" % newWikiId)\n return syn.getWikiHeaders(newOwn)","def create_copy(request, pk):\n report = get_object_or_404(Report, pk=pk)\n new_report = duplicate(report, changes=(\n ('name', '{0} (copy)'.format(report.name)),\n ('user_created', request.user),\n ('user_modified', request.user),\n ))\n # duplicate does not get related\n for display in report.displayfield_set.all():\n new_display = copy.copy(display)\n new_display.pk = None\n new_display.report = new_report\n new_display.save()\n for report_filter in report.filterfield_set.all():\n new_filter = copy.copy(report_filter)\n new_filter.pk = None\n new_filter.report = new_report\n new_filter.save()\n return redirect(new_report)","def has_move_page_permission(self, request):\n return self.has_generic_permission(request, \"move_page\")","def test_copy_plugins(self):\n # create some objects\n page_en = create_page(\"CopyPluginTestPage (EN)\", \"nav_playground.html\", \"en\")\n page_de = create_page(\"CopyPluginTestPage (DE)\", \"nav_playground.html\", \"de\")\n ph_en = page_en.placeholders.get(slot=\"body\")\n ph_de = page_de.placeholders.get(slot=\"body\")\n \n # add the text plugin\n text_plugin_en = add_plugin(ph_en, \"TextPlugin\", \"en\", body=\"Hello World\")\n self.assertEquals(text_plugin_en.pk, CMSPlugin.objects.all()[0].pk)\n \n # add a *nested* link plugin\n link_plugin_en = add_plugin(ph_en, \"LinkPlugin\", \"en\", target=text_plugin_en,\n name=\"A Link\", url=\"https://www.django-cms.org\")\n \n # the call above to add a child makes a plugin reload required here.\n text_plugin_en = self.reload(text_plugin_en)\n \n # check the relations\n self.assertEquals(text_plugin_en.get_children().count(), 1)\n self.assertEqual(link_plugin_en.parent.pk, text_plugin_en.pk)\n \n # just sanity check that so far everything went well\n self.assertEqual(CMSPlugin.objects.count(), 2)\n \n # copy the plugins to the german placeholder\n copy_plugins_to(ph_en.cmsplugin_set.all(), ph_de, 'de')\n \n self.assertEqual(ph_de.cmsplugin_set.filter(parent=None).count(), 1)\n text_plugin_de = ph_de.cmsplugin_set.get(parent=None).get_plugin_instance()[0]\n self.assertEqual(text_plugin_de.get_children().count(), 1)\n link_plugin_de = text_plugin_de.get_children().get().get_plugin_instance()[0]\n \n \n # check we have twice as many plugins as before\n self.assertEqual(CMSPlugin.objects.count(), 4)\n \n # check language plugins\n self.assertEqual(CMSPlugin.objects.filter(language='de').count(), 2)\n self.assertEqual(CMSPlugin.objects.filter(language='en').count(), 2)\n \n \n text_plugin_en = self.reload(text_plugin_en)\n link_plugin_en = self.reload(link_plugin_en)\n \n # check the relations in english didn't change\n self.assertEquals(text_plugin_en.get_children().count(), 1)\n self.assertEqual(link_plugin_en.parent.pk, text_plugin_en.pk)\n \n self.assertEqual(link_plugin_de.name, link_plugin_en.name)\n self.assertEqual(link_plugin_de.url, link_plugin_en.url)\n \n self.assertEqual(text_plugin_de.body, text_plugin_en.body)","def _add_page_to_storage(page: Page):\n if page:\n if page.valid_mime:\n CrawlerStorageManager.create_file_from_page(page)\n page.save_to_json_file()","def editPage(self, page):\n return Page.create(self.pm_getSpaceManager().editPage(page.toDict()), self._modelDataManager)","def test_config_step_copy(self):\n\n install_step = self.ConfigStep.create({\n 'name': 'install_step',\n 'job_type': 'install_odoo'\n })\n\n run_step = self.ConfigStep.create({\n 'name': 'run_step',\n 'job_type': 'run_odoo',\n })\n\n create_step = self.ConfigStep.create({\n 'name': 'test_step',\n 'job_type': 'create_build',\n })\n\n config = self.Config.create({'name': 'test_config'})\n StepOrder = self.env['runbot.build.config.step.order']\n # Creation order is impoortant to reproduce the Odoo copy bug/feature :-)\n StepOrder.create({'sequence': 15, 'step_id': run_step.id, 'config_id': config.id})\n StepOrder.create({'sequence': 10, 'step_id': create_step.id, 'config_id': config.id})\n StepOrder.create({'sequence': 12, 'step_id': install_step.id, 'config_id': config.id})\n\n dup_config = config.copy()\n self.assertEqual(dup_config.step_order_ids.mapped('step_id'), config.step_order_ids.mapped('step_id'))","def update_pagesToCrawl(self, page):\n # check if the page from which we got URLs pass the pageFilter\n pass_filter = False\n for p in self.pageFilter:\n if p in page.url:\n pass_filter = True\n\n if pass_filter:\n for url in page.urls:\n # update the set if url not already crawled\n if url not in self.pagesCrawled:\n self.pagesToCrawl.add(url)\n\n # update pagesToCrawl_dict\n if url in self.pagesToCrawl_dict:\n self.pagesToCrawl_dict[url].append(page.url)\n else:\n self.pagesToCrawl_dict[url] = [page.url]","def copy(self, src, dest):\n\n src = os.path.join(os.path.dirname(__file__), \"collections\", \"kitchensink\", src)\n dest = os.path.join(self.checkout, dest)\n if os.path.isdir(src):\n shutil.copytree(src, dest)\n else:\n shutil.copy(src, dest)\n return dest","def _copyRecursive(\n syn, entity, destinationId, mapping=None, skipCopyAnnotations=False, **kwargs\n):\n\n version = kwargs.get(\"version\", None)\n setProvenance = kwargs.get(\"setProvenance\", \"traceback\")\n excludeTypes = kwargs.get(\"excludeTypes\", [])\n updateExisting = kwargs.get(\"updateExisting\", False)\n if mapping is None:\n mapping = dict()\n # Check that passed in excludeTypes is file, table, and link\n if not isinstance(excludeTypes, list):\n raise ValueError(\"Excluded types must be a list\")\n elif not all([i in [\"file\", \"link\", \"table\"] for i in excludeTypes]):\n raise ValueError(\n \"Excluded types can only be a list of these values: file, table, and link\"\n )\n\n ent = syn.get(entity, downloadFile=False)\n if ent.id == destinationId:\n raise ValueError(\"destinationId cannot be the same as entity id\")\n\n if (isinstance(ent, Project) or isinstance(ent, Folder)) and version is not None:\n raise ValueError(\"Cannot specify version when copying a project of folder\")\n\n if not isinstance(ent, (Project, Folder, File, Link, Schema, Entity)):\n raise ValueError(\"Not able to copy this type of file\")\n\n permissions = syn.restGET(\"/entity/{}/permissions\".format(ent.id))\n # Don't copy entities without DOWNLOAD permissions\n if not permissions[\"canDownload\"]:\n syn.logger.warning(\n \"%s not copied - this file lacks download permission\" % ent.id\n )\n return mapping\n\n access_requirements = syn.restGET(\"/entity/{}/accessRequirement\".format(ent.id))\n # If there are any access requirements, don't copy files\n if access_requirements[\"results\"]:\n syn.logger.warning(\n \"{} not copied - this file has access restrictions\".format(ent.id)\n )\n return mapping\n copiedId = None\n\n if isinstance(ent, Project):\n if not isinstance(syn.get(destinationId), Project):\n raise ValueError(\n \"You must give a destinationId of a new project to copy projects\"\n )\n copiedId = destinationId\n # Projects include Docker repos, and Docker repos cannot be copied\n # with the Synapse rest API. Entity views currently also aren't\n # supported\n entities = syn.getChildren(\n entity, includeTypes=[\"folder\", \"file\", \"table\", \"link\"]\n )\n for i in entities:\n mapping = _copyRecursive(\n syn,\n i[\"id\"],\n destinationId,\n mapping=mapping,\n skipCopyAnnotations=skipCopyAnnotations,\n **kwargs,\n )\n elif isinstance(ent, Folder):\n copiedId = _copyFolder(\n syn,\n ent.id,\n destinationId,\n mapping=mapping,\n skipCopyAnnotations=skipCopyAnnotations,\n **kwargs,\n )\n elif isinstance(ent, File) and \"file\" not in excludeTypes:\n copiedId = _copyFile(\n syn,\n ent.id,\n destinationId,\n version=version,\n updateExisting=updateExisting,\n setProvenance=setProvenance,\n skipCopyAnnotations=skipCopyAnnotations,\n )\n elif isinstance(ent, Link) and \"link\" not in excludeTypes:\n copiedId = _copyLink(syn, ent.id, destinationId, updateExisting=updateExisting)\n elif isinstance(ent, Schema) and \"table\" not in excludeTypes:\n copiedId = _copyTable(syn, ent.id, destinationId, updateExisting=updateExisting)\n # This is currently done because copyLink returns None sometimes\n if copiedId is not None:\n mapping[ent.id] = copiedId\n syn.logger.info(\"Copied %s to %s\" % (ent.id, copiedId))\n else:\n syn.logger.info(\"%s not copied\" % ent.id)\n return mapping","def copy_tree(t):\n return tree(label(t), [copy_tree(b) for b in branches(t)])","def copy_subtree(src, dst):\n for src_f in os.listdir(src):\n src_path = os.path.join(src, src_f)\n if os.path.isdir(src_path):\n dst_path = os.path.join(dst, src_f)\n if not os.path.exists(dst_path):\n shutil.copytree(src_path, dst_path)\n else:\n ProcessJson.copy_subtree(src_path, dst_path)\n elif os.path.isfile(src_path):\n dst_path = os.path.join(dst, src_f)\n if not os.path.exists(dst_path):\n shutil.copy(src_path, dst_path)","def copy(self):\n copy = Node(self.node_data, self.tree_type, self.parent)\n if self.children:\n copy.children = [c.copy() for c in self.children]\n for c in copy.children:\n c.parent = copy\n return copy","def create_page_from_import(request, parent_page, page_class, parsed_doc):\n\n page = page_class.create_from_import(parsed_doc, request.user)\n\n edit_handler = page_class.get_edit_handler()\n edit_handler = edit_handler.bind_to(request=request, instance=page)\n form_class = edit_handler.get_form_class()\n\n next_url = get_valid_next_url_from_request(request)\n\n form = form_class(instance=page, parent_page=parent_page)\n has_unsaved_changes = False\n\n edit_handler = edit_handler.bind_to(form=form)\n\n return render(\n request,\n \"wagtailadmin/pages/create.html\",\n {\n \"content_type\": page.content_type,\n \"page_class\": page_class,\n \"parent_page\": parent_page,\n \"edit_handler\": edit_handler,\n \"action_menu\": PageActionMenu(\n request, view=\"create\", parent_page=parent_page\n ),\n \"preview_modes\": page.preview_modes,\n \"form\": form,\n \"next\": next_url,\n \"has_unsaved_changes\": has_unsaved_changes,\n },\n )","def copy(self):\n pass","def copy(self):\n pass","def copy(self):\n pass","def clone(context, request):\n if request.has_permission('create'):\n return {\n 'name': 'clone',\n 'title': 'Clone',\n 'profile': '/profiles/{ti.name}.json'.format(ti=context.type_info),\n 'href': '{item_uri}#!clone'.format(item_uri=request.resource_path(context)),\n }","def post_save_page(instance, raw, created, **kwargs):\n old_page = instance.old_page\n del(instance.old_page)\n \n if settings.CMS_MODERATOR:\n # tell moderator something was happen with this page\n from cms.utils.moderator import page_changed\n page_changed(instance, old_page)","def pre_save_page(instance, raw, **kwargs):\n instance.old_page = None\n try:\n instance.old_page = Page.objects.get(pk=instance.pk)\n except ObjectDoesNotExist:\n pass","def ress_move_on_page(self, content=None):\n outside_ress = self.outside_ress\n content = content or self.content\n\n for blo in outside_ress:\n\n mch = re.search(r'(\\s|\\t)-block %s'%blo, content) # blo = links, onload etc\n\n if not mch:\n\n warn(blo+' block is undefined in root template %s'%self.origin.__str__()) # raise Exception(blo+' block is undefined in root template %s'%origin.__str__())\n\n super_block = r'\\t\\t={ block.super }\\n'\n content = re.sub(\n r'(-extends \"[\\w\\.]+\")\"', r'\\1\\n\\t-block %s%s%s'%(\n blo, super_block, __indent_block(r'\\t\\t', outside_ress[blo].value)\n ),\n content\n )\n\n else:\n _blo = self.__indent_block(mch.groups()[0]+' '*4, outside_ress[blo].value)\n\n # (\\s|\\t)-block \\w+(([\\s:]*={ *block.super *})|) ={ *block.super *} - \\2\n\n content = re.sub(r'(\\s|\\t)(-block %s)'%blo, r'\\1\\2\\n'+_blo, content)\n\n## _blo = _indent_block(mch.groups()[0]+' '*8, blo)\n## _blo = '\\n\\1 :javascript\\n' + _blo\n\n return content","def test_copy_textplugin(self):\n page = create_page(\"page\", \"nav_playground.html\", \"en\")\n \n placeholder = page.placeholders.get(slot='body')\n\n plugin_base = CMSPlugin(\n plugin_type='TextPlugin',\n placeholder=placeholder,\n position=1,\n language=self.FIRST_LANG)\n plugin_base.insert_at(None, position='last-child', save=False)\n\n plugin = Text(body='')\n plugin_base.set_base_attr(plugin)\n plugin.save()\n\n plugin_ref_1_base = CMSPlugin(\n plugin_type='TextPlugin',\n placeholder=placeholder,\n position=1,\n language=self.FIRST_LANG)\n plugin_ref_1_base.insert_at(plugin_base, position='last-child', save=False)\n\n plugin_ref_1 = Text(body='')\n plugin_ref_1_base.set_base_attr(plugin_ref_1)\n plugin_ref_1.save()\n\n plugin_ref_2_base = CMSPlugin(\n plugin_type='TextPlugin',\n placeholder=placeholder,\n position=2,\n language=self.FIRST_LANG)\n plugin_ref_2_base.insert_at(plugin_base, position='last-child', save=False)\n\n plugin_ref_2 = Text(body='')\n plugin_ref_2_base.set_base_attr(plugin_ref_2)\n\n plugin_ref_2.save()\n\n plugin.body = plugin_tags_to_admin_html(' {{ plugin_object %s }} {{ plugin_object %s }} ' % (str(plugin_ref_1.pk), str(plugin_ref_2.pk)))\n plugin.save()\n self.assertEquals(plugin.pk, 1)\n page_data = self.get_new_page_data()\n\n #create 2nd language page\n page_data.update({\n 'language': self.SECOND_LANG,\n 'title': \"%s %s\" % (page.get_title(), self.SECOND_LANG),\n })\n response = self.client.post(URL_CMS_PAGE_CHANGE % page.pk + \"?language=%s\" % self.SECOND_LANG, page_data)\n self.assertRedirects(response, URL_CMS_PAGE)\n\n self.assertEquals(CMSPlugin.objects.filter(language=self.FIRST_LANG).count(), 3)\n self.assertEquals(CMSPlugin.objects.filter(language=self.SECOND_LANG).count(), 0)\n self.assertEquals(CMSPlugin.objects.count(), 3)\n self.assertEquals(Page.objects.all().count(), 1)\n\n copy_data = {\n 'placeholder': placeholder.pk,\n 'language': self.SECOND_LANG,\n 'copy_from': self.FIRST_LANG,\n }\n response = self.client.post(URL_CMS_PAGE + \"copy-plugins/\", copy_data)\n self.assertEquals(response.status_code, 200)\n self.assertEqual(response.content.count('<li '), 3)\n # assert copy success\n self.assertEquals(CMSPlugin.objects.filter(language=self.FIRST_LANG).count(), 3)\n self.assertEquals(CMSPlugin.objects.filter(language=self.SECOND_LANG).count(), 3)\n self.assertEquals(CMSPlugin.objects.count(), 6)\n\n new_plugin = Text.objects.get(pk=6)\n self.assertEquals(plugin_tags_to_id_list(new_plugin.body), [u'4', u'5'])","def _copy_margin(\n self,\n margin_content: UIContent,\n new_screen: Screen,\n write_position: WritePosition,\n move_x: int,\n width: int,\n ) -> None:\n xpos = write_position.xpos + move_x\n ypos = write_position.ypos\n\n margin_write_position = WritePosition(xpos, ypos, width, write_position.height)\n self._copy_body(margin_content, new_screen, margin_write_position, 0, width)","def offline_copy(_export_path):\n global export_path\n export_path = _export_path\n \n # First, monkey patch the original config\n main.NBCONFIG.protectect_dirs = []\n main.NBCONFIG.protected_users = {}\n main.NBCONFIG.edit_users = {}\n \n # Now monkey patch NBweb\n main.REQUIRELOGIN = False\n\n pages = []\n\n # Copy and work all source files \n for dirpath,dirnames,filenames in os.walk(NBCONFIG.source):\n for dirname in dirnames[:]: # Iterate a copy since we will delete in place\n if any(dirname.startswith(i) for i in ['.']):\n dirnames.remove(dirname) # So we do not parse it later\n continue\n if dirname == '_scratch':\n dirnames.remove(dirname) # So we do not parse it later\n continue\n \n # Names\n src_systemname = os.path.join(dirpath,dirname)\n rootname = os.path.relpath(src_systemname,NBCONFIG.source) # No leading / though\n dest_systemname = os.path.join(export_path,rootname)\n \n mkdir(rootname,isfile=False) # Will make the dir no matter what\n \n # Index\n dest = os.path.join(export_path,rootname, 'index.html')\n \n # Exclusions.\n if main.exclusion_check(utils.join('/',rootname +'/')):\n with open(dest,'w',encoding='utf8') as FF:\n FF.write('')\n continue\n \n try:\n html = main.main_route('/' + rootname + '/')\n except HTTPError:\n # Likely some additional resource in _NBweb\n try:\n os.rmdir(dest_systemname) # Should be empty\n except OSError:\n pass\n os.symlink(src_systemname,dest_systemname)\n continue\n \n \n html = process_page(html,dest)\n with open(dest,'w',encoding='utf8') as FF:\n FF.write(html)\n \n # _all\n dest = os.path.join(export_path,'_all',rootname, 'index.html')\n mkdir(dest,isfile=True,isfull=True)\n \n html = main.allpage('/'+ rootname +'/')\n html = process_page(html,dest)\n with open(dest,'w',encoding='utf8') as FF:\n FF.write(html)\n \n \n # Loop each file\n for filename in filenames:\n if os.path.splitext(filename)[0] == 'index':\n continue # Already made above\n \n # Names\n src_systemname = os.path.join(dirpath,filename)\n rootname = os.path.relpath(src_systemname,NBCONFIG.source) # No leading / though\n dest_systemname = os.path.join(export_path,rootname)\n \n mkdir(rootname,isfile=True) # Will make the dir no matter what\n try:\n os.symlink(src_systemname,dest_systemname) \n except OSError:\n os.remove(dest_systemname)\n os.symlink(src_systemname,dest_systemname)\n \n rootbasename,ext = os.path.splitext(rootname)\n if ext in NBCONFIG.extensions:\n dest = os.path.join(export_path,rootbasename + '.html')\n try:\n html = main.main_route(rootbasename + '.html')\n except:\n print('Issue with: {}'.format(rootname))\n \n html = process_page(html,dest)\n \n with open(dest,'w',encoding='utf8') as FF:\n FF.write(html)\n pages.append(rootbasename)\n\n ## Index pages\n # Home page w/o blog\n dest_systemname = os.path.join(export_path,'')\n dest = os.path.join(export_path,'index.html')\n \n html0 = main.main_route('/',map_view=True)\n \n html = process_page(html0,dest)\n with open(dest,'w',encoding='utf8') as FF:\n FF.write(html)\n\n # Also write the sitemap\n dest = os.path.join(export_path,'_sitemap/index.html')\n mkdir('/_sitemap',isfile=False)\n html = process_page(html0,dest)\n with open(dest,'w',encoding='utf8') as FF:\n FF.write(html)\n \n # _all\n dest = os.path.join(export_path,'_all','index.html')\n \n html = main.allpage('/')\n html = process_page(html,dest)\n with open(dest,'w',encoding='utf8') as FF:\n FF.write(html)\n \n ## Blog Pages\n if len(NBCONFIG.blog_dirs) > 0:\n blog_num = 0\n while True:\n dest = os.path.join(export_path,'_blog',unicode(blog_num),'index.html')\n \n try:\n html = main.main_route('/',map_view=False,blog_num=blog_num)\n except HTTPError:\n break # At the last one\n \n mkdir(dest,isfile=True,isfull=True) \n \n html = process_page(html,dest)\n with open(dest,'w',encoding='utf8') as FF:\n FF.write(html)\n blog_num += 1\n # Make the home page. \n dest = os.path.join(export_path,'index.html')\n html = main.main_route('/',map_view=False,blog_num=0)\n html = process_page(html,dest)\n with open(dest,'w',encoding='utf8') as FF:\n FF.write(html)\n \n ## Special Pages\n make_random_forward(pages)\n \n # Tags\n dest = os.path.join(export_path,'_tags/index.html')\n mkdir(dest,isfile=True,isfull=True) \n html = main.return_tags()\n html = process_page(html,dest)\n with open(dest,'w',encoding='utf8') as FF:\n FF.write(html)\n \n # ToDos\n dest = os.path.join(export_path,'_todo/index.html')\n mkdir(dest,isfile=True,isfull=True) \n html = main.return_todo()\n html = process_page(html,dest)\n with open(dest,'w',encoding='utf8') as FF:\n FF.write(html)\n \n txt = main.return_todo_txt()\n dest = os.path.join(export_path,'_todo/todo.txt')\n with open(dest,'w',encoding='utf8') as FF:\n FF.write(txt)\n \n # Galleries\n cpsym( utils.join(NBCONFIG.scratch_path,'_galleries'),utils.join(export_path,'_galleries'))\n \n ## Clean up\n for F in [utils.join(export_path,'_NBweb',a) for a in ['NBCONFIG.py','NBCONFIG.pyc','template.html']]:\n try:\n os.remove(F)\n except:\n pass\n \n # Make sure there are never any directory listings\n for dirpath,dirnames,filenames in os.walk(export_path):\n if 'index.html' not in filenames:\n with open(utils.join(dirpath,'index.html'),'w',encoding='utf8') as F:\n F.write('')","def copy_skel(src, dest):\n md_common.copytree(src, dest)","def copy(self):\n # YOUR CODE HERE\n raise NotImplementedError()","def prepare_wiki_page(self, req, page, fields):\r\n pass","def _copy_from_template(\n self, source_structures, source_keys, dest_structure, new_parent_block_key, user_id, head_validation\n ):\n new_blocks = set()\n\n new_children = list() # ordered list of the new children of new_parent_block_key\n\n for usage_key in source_keys:\n src_course_key = usage_key.course_key\n hashable_source_id = src_course_key.for_version(None)\n block_key = BlockKey(usage_key.block_type, usage_key.block_id)\n source_structure = source_structures[src_course_key]\n\n if block_key not in source_structure['blocks']:\n raise ItemNotFoundError(usage_key)\n source_block_info = source_structure['blocks'][block_key]\n\n # Compute a new block ID. This new block ID must be consistent when this\n # method is called with the same (source_key, dest_structure) pair\n unique_data = \"{}:{}:{}\".format(\n str(hashable_source_id).encode(\"utf-8\"),\n block_key.id,\n new_parent_block_key.id,\n )\n new_block_id = hashlib.sha1(unique_data.encode('utf-8')).hexdigest()[:20]\n new_block_key = BlockKey(block_key.type, new_block_id)\n\n # Now clone block_key to new_block_key:\n new_block_info = copy.deepcopy(source_block_info)\n # Note that new_block_info now points to the same definition ID entry as source_block_info did\n existing_block_info = dest_structure['blocks'].get(new_block_key, BlockData())\n # Inherit the Scope.settings values from 'fields' to 'defaults'\n new_block_info.defaults = new_block_info.fields\n\n # <workaround>\n # CAPA modules store their 'markdown' value (an alternate representation of their content)\n # in Scope.settings rather than Scope.content :-/\n # markdown is a field that really should not be overridable - it fundamentally changes the content.\n # capa modules also use a custom editor that always saves their markdown field to the metadata,\n # even if it hasn't changed, which breaks our override system.\n # So until capa modules are fixed, we special-case them and remove their markdown fields,\n # forcing the inherited version to use XML only.\n if usage_key.block_type == 'problem' and 'markdown' in new_block_info.defaults:\n del new_block_info.defaults['markdown']\n # </workaround>\n\n # Preserve any existing overrides\n new_block_info.fields = existing_block_info.fields\n\n if 'children' in new_block_info.defaults:\n del new_block_info.defaults['children'] # Will be set later\n\n new_block_info.edit_info = existing_block_info.edit_info\n new_block_info.edit_info.previous_version = new_block_info.edit_info.update_version\n new_block_info.edit_info.update_version = dest_structure['_id']\n # Note we do not set 'source_version' - it's only used for copying identical blocks\n # from draft to published as part of publishing workflow.\n # Setting it to the source_block_info structure version here breaks split_draft's has_changes() method.\n new_block_info.edit_info.edited_by = user_id\n new_block_info.edit_info.edited_on = datetime.datetime.now(UTC)\n new_block_info.edit_info.original_usage = str(usage_key.replace(branch=None, version_guid=None))\n new_block_info.edit_info.original_usage_version = source_block_info.edit_info.update_version\n dest_structure['blocks'][new_block_key] = new_block_info\n\n children = source_block_info.fields.get('children')\n if children:\n children = [src_course_key.make_usage_key(child.type, child.id) for child in children]\n new_blocks |= self._copy_from_template(\n source_structures, children, dest_structure, new_block_key, user_id, head_validation\n )\n\n new_blocks.add(new_block_key)\n # And add new_block_key to the list of new_parent_block_key's new children:\n new_children.append(new_block_key)\n\n # Update the children of new_parent_block_key\n dest_structure['blocks'][new_parent_block_key].fields['children'] = new_children\n\n return new_blocks","def publish(self, fields=None, exclude=None):\n # clean moderation log\n self.pagemoderatorstate_set.all().delete()\n \n # can be this page published?\n if self.mptt_can_publish():\n self.moderator_state = Page.MODERATOR_APPROVED\n else:\n self.moderator_state = Page.MODERATOR_APPROVED_WAITING_FOR_PARENTS\n \n self.save(change_state=False)\n \n if not fields:\n public = self.public\n if public:\n if public.tree_id != self.tree_id: #moved over trees\n tree_ids = [self.tree_id, public.tree_id]\n else:\n tree_ids = [self.tree_id]\n \n dirty = False\n if self.lft != public.lft or self.rght != public.rght or self.level != public.level:#moved in tree\n dirty = True\n if dirty or len(tree_ids) == 2:\n pages = list(Page.objects.filter(tree_id__in=tree_ids).order_by(\"tree_id\", \"level\", \"lft\"))\n fields = []\n names = [\"lft\",\"rght\",\"tree_id\", \"level\", \"parent\", \"created_by\", \"changed_by\", \"site\"]\n for field in self._meta.fields:\n if field.name in names:\n fields.append(field)\n ids = []\n for page in pages:\n if page.pk != self.pk:\n page.publish(fields=fields)\n ids.append(page.pk)\n titles = Title.objects.filter(page__in=ids)\n title_fields = []\n names = [\"path\"]\n for field in Title._meta.fields:\n if field.name in names:\n title_fields.append(field)\n for title in titles:\n title.publish(fields=title_fields)\n else:\n pass\n #print \"no public found\" \n \n # publish, but only if all parents are published!! - this will need a flag\n try:\n published = super(Page, self).publish(fields, exclude)\n except MpttCantPublish:\n return \n \n # page was published, check if there are some childs, which are waiting\n # for publishing (because of the parent)\n publish_set = self.children.filter(moderator_state = Page.MODERATOR_APPROVED_WAITING_FOR_PARENTS)\n for page in publish_set:\n # recursive call to all childrens....\n page.moderator_state = Page.MODERATOR_APPROVED\n page.save(change_state=False)\n page.publish()\n \n # fire signal after publishing is done\n return published","def copytree(self, name, source, dest, symlinks=False):\n self.m.path.assert_absolute(source)\n self.m.path.assert_absolute(dest)\n args = ['--symlinks'] if symlinks else []\n self._run(name, ['copytree'] + args + [source, dest])\n self.m.path.mock_copy_paths(source, dest)","def copy_one(self, src, dest):\n if self.manager.no_sourcemaps and self.is_ignored_sourcemap(src.name):\n return\n\n if dest.is_dir():\n shutil.rmtree(dest)\n elif dest.exists():\n dest.unlink()\n\n if not dest.parent.exists():\n self.log.debug(f\"creating folder {dest.parent}\")\n dest.parent.mkdir(parents=True)\n\n self.maybe_timestamp(dest.parent)\n\n copytree_kwargs = {}\n\n if self.manager.no_sourcemaps:\n copytree_kwargs[\"ignore\"] = SOURCEMAP_IGNORE_PATTERNS\n\n if src.is_dir():\n shutil.copytree(src, dest, **copytree_kwargs)\n else:\n shutil.copy2(src, dest)\n\n self.maybe_timestamp(dest)","def test_copy_details(self):\n self.tc_id = \"Ts_002\"\n self.tc_desc = \"Verify the user is able to copy the location type details\"\n self.tc_step = \"TC Start\"\n\n registration = RegistrationPage(self.driver)\n\n self.tc_step = \"Launch the url\"\n registration.launchUrl(self.url)\n\n self.tc_step = \"Enter the basic registration details\"\n registration.clickVendorLogin()\n registration.clickRegisterButton()\n registration.enterBasicRegistrationDetails(self.firstname, self.lastname, self.vendorname, self.fnsnumber,\n self.primaryemail, self.primaryphno, self.psw, self.cpsw,\n self.continfo)\n registration.basicRegButton()\n self.tc_step = \"Enter the public registration details\"\n registration.enterPublicRegistrationDetails(self.publicemail, self.publicphno, self.publicwebsite,\n self.businessdesc, self.products)\n registration.publicRegButton()\n self.tc_step = \"Enter the location details\"\n registration.clickCSAButton()\n registration.clickLocationYesButton()\n registration.csalocationTypeDetails(self.pickupsitename, self.adrs1, self.adrs2, self.zipcode, self.spzl_instruction)\n registration.chooseCity()\n registration.csacopy()\n registration.addmore()\n registration.remove()\n registration.confirmremove()\n registration.saveonlyCsa()\n self.assertEqual(registration.verifyRegistration(),\"Healthy Incentives Program (HIP)\",\"Login Success\")","def copy(self, new_tree):\n new_node = new_tree.new_tree_node(parent=self.parent, node_id=self.id)\n new_node.name = self.name\n new_node.branch = self.branch\n new_node.support = self.support\n new_node.support_type = self.support_type\n new_node.comment = self.comment\n new_node.children = self.children[::]\n new_node._been_processed = self._been_processed\n return new_node","def copy(self):\n new_tree = Tree(support_label=self._support_label, remove_name_quotes=self._remove_name_quotes)\n new_tree.name = self.name\n new_tree._is_cladogram = self._is_cladogram\n new_tree._cladogram_branch = self._cladogram_branch\n new_tree._node_id_template = self._node_id_template\n new_tree._node_ids = self._node_ids.copy()\n new_tree._node_id_index = self._node_id_index\n new_tree.root = self.root.copy(new_tree)\n self.copy_nodes(self.root, new_tree.root, new_tree)\n new_tree.process_tree_nodes()\n return new_tree","def _copy_published_modules_to_course(self, new_course, old_course_loc, course_key, user):\r\n course_version_locator = new_course.id\r\n\r\n # iterate over published course elements. Wildcarding rather than descending b/c some elements are orphaned (e.g.,\r\n # course about pages, conditionals)\r\n for module in self.direct_modulestore.get_items(course_key):\r\n # don't copy the course again. No drafts should get here but check\r\n if module.location != old_course_loc and not getattr(module, 'is_draft', False):\r\n # create split_xblock using split.create_item\r\n # where block_id is computed by translate_location_to_locator\r\n new_locator = self.loc_mapper.translate_location(\r\n module.location, True, add_entry_if_missing=True\r\n )\r\n # NOTE: the below auto populates the children when it migrates the parent; so,\r\n # it doesn't need the parent as the first arg. That is, it translates and populates\r\n # the 'children' field as it goes.\r\n _new_module = self.split_modulestore.create_item(\r\n course_version_locator, module.category, user.id,\r\n block_id=new_locator.block_id,\r\n fields=self._get_json_fields_translate_references(module, course_key, True),\r\n continue_version=True\r\n )\r\n # after done w/ published items, add version for 'draft' pointing to the published structure\r\n index_info = self.split_modulestore.get_course_index_info(course_version_locator)\r\n versions = index_info['versions']\r\n versions['draft'] = versions['published']\r\n self.split_modulestore.update_course_index(index_info)\r\n\r\n # clean up orphans in published version: in old mongo, parents pointed to the union of their published and draft\r\n # children which meant some pointers were to non-existent locations in 'direct'\r\n self.split_modulestore.internal_clean_children(course_version_locator)","def copy(self,item,destName,destDir=None):\n if item == self.lastKey: return\n destDir = destDir or self.dir\n apath = self.dir.join(item)\n apath.copyTo(destDir.join(destName))\n if destDir == self.dir:\n self.data[destName] = installer = copy.copy(self.data[item])\n installer.isActive = False\n self.refreshOrder()\n self.moveArchives([destName],self.data[item].order+1)","def copy_elements(self):\n self.tmp_hook_dir = tempfile.mkdtemp()\n for element in self.elements:\n element_dir = self.loaded_elements[element].directory\n dir_util.copy_tree(element_dir, self.tmp_hook_dir)\n try:\n os.unlink('/tmp/in_target.d')\n except:\n pass\n os.symlink(self.tmp_hook_dir, '/tmp/in_target.d')\n\n # elements expect this environment variable to be set\n os.environ['TMP_HOOKS_PATH'] = self.tmp_hook_dir\n tmp_path = '%s/bin' % self.tmp_hook_dir\n if 'PATH' in os.environ:\n tmp_path = os.environ[\"PATH\"] + os.pathsep + tmp_path\n os.environ[\"PATH\"] = tmp_path","def copyDir(self, src, subpath):\n dst = self.output_path + \"/\" + subpath\n shutil.copytree(src, dst)","def copy(self, event):\n return","def copy(self, keep_uid=False, new_parent=None):\n obj = self.__class__(\n parent=new_parent or self.parent,\n data=self.data,\n id=self.id if keep_uid else str(uuid.uuid1()),\n )\n if new_parent or not keep_uid:\n obj.url = obj.generate_url()\n else:\n obj.url = self.url\n return obj","def tree_copy_selection(in_tree, out_tree, selection):\n for entry in in_tree:\n if selection(entry):\n out_tree.Fill()","def __copyFiles(self):\n if os.path.isdir(self.__sourcePath):\n shutil.copytree(self.__sourcePath, self.__targetPath)\n else:\n shutil.copy2(self.__sourcePath, self.__targetPath)","def create_page(self):","def copy_one(self, src, dest):\n if dest.is_dir():\n shutil.rmtree(dest)\n elif dest.exists():\n dest.unlink()\n\n if not dest.parent.exists():\n self.log.debug(f\"creating folder {dest.parent}\")\n dest.parent.mkdir(parents=True)\n\n self.maybe_timestamp(dest.parent)\n\n if src.is_dir():\n shutil.copytree(src, dest)\n else:\n shutil.copy2(src, dest)\n\n self.maybe_timestamp(dest)","def copy(self, to_folder, page_size=1000, chunk_size=100, **copy_kwargs):\n ids = self._id_only_copy_self()\n ids.page_size = page_size\n return self.folder_collection.account.bulk_copy(\n ids=ids, to_folder=to_folder, chunk_size=chunk_size, **copy_kwargs\n )","def create_page_objects(self, data):\n for page in data['pages']:\n self.create_page(page)","def copy(self, user_id, source_course, destination_course, subtree_list=None, blacklist=None):\n # get the destination's index, and source and destination structures.\n with self.bulk_operations(source_course):\n source_structure = self._lookup_course(source_course).structure\n\n with self.bulk_operations(destination_course):\n index_entry = self.get_course_index(destination_course)\n if index_entry is None:\n # brand new course\n raise ItemNotFoundError(destination_course)\n if destination_course.branch not in index_entry['versions']:\n # must be copying the dag root if there's no current dag\n root_block_key = source_structure['root']\n if not any(root_block_key == BlockKey.from_usage_key(subtree) for subtree in subtree_list):\n raise ItemNotFoundError(f'Must publish course root {root_block_key}')\n root_source = source_structure['blocks'][root_block_key]\n # create branch\n destination_structure = self._new_structure(\n user_id, root_block_key,\n # leave off the fields b/c the children must be filtered\n definition_id=root_source.definition,\n )\n else:\n destination_structure = self._lookup_course(destination_course).structure\n destination_structure = self.version_structure(destination_course, destination_structure, user_id)\n\n if blacklist != EXCLUDE_ALL:\n blacklist = [BlockKey.from_usage_key(shunned) for shunned in blacklist or []]\n # iterate over subtree list filtering out blacklist.\n orphans = set()\n destination_blocks = destination_structure['blocks']\n for subtree_root in subtree_list:\n if BlockKey.from_usage_key(subtree_root) != source_structure['root']:\n # find the parents and put root in the right sequence\n parents = self._get_parents_from_structure(BlockKey.from_usage_key(subtree_root), source_structure)\n parent_found = False\n for parent in parents:\n # If a parent isn't found in the destination_blocks, it's possible it was renamed\n # in the course export. Continue and only throw an exception if *no* parents are found.\n if parent in destination_blocks:\n parent_found = True\n orphans.update(\n self._sync_children(\n source_structure['blocks'][parent],\n destination_blocks[parent],\n BlockKey.from_usage_key(subtree_root)\n )\n )\n if len(parents) and not parent_found: # lint-amnesty, pylint: disable=len-as-condition\n raise ItemNotFoundError(parents)\n # update/create the subtree and its children in destination (skipping blacklist)\n orphans.update(\n self._copy_subdag(\n user_id, destination_structure['_id'],\n BlockKey.from_usage_key(subtree_root),\n source_structure['blocks'],\n destination_blocks,\n blacklist\n )\n )\n # remove any remaining orphans\n for orphan in orphans:\n # orphans will include moved as well as deleted xblocks. Only delete the deleted ones.\n self._delete_if_true_orphan(orphan, destination_structure)\n\n # update the db\n self.update_structure(destination_course, destination_structure)\n self._update_head(destination_course, index_entry, destination_course.branch, destination_structure['_id'])","def copyTo(self, newFolder):\n copyUri = self.metaData.getLink(\"copy\")\n\n if not hasattr(newFolder, \"metaData\"): raise TypeError(\"Your newFolder does not have a metaData property\")\n if not hasattr(newFolder, \"selfLink\"): raise TypeError(\"Your folder object is missing a selfLink\")\n assert copyUri is not None\n\n header = self._baseHeader.copy()\n header['Content-Type'] = \"application/vnd.huddle.data+json\"\n body = '{ \"targetFolder\":{ \"link\":{ \"rel\": \"self\", \"href\": \"' + newFolder.selfLink + '\" } } }'\n response = self._adapter.postRequest(copyUri, header, body)\n\n return Folder(self._client, response['Headers']['location'])","def copy_with_children(self, new_children):\n new_box = self.copy()\n new_box.children = list(new_children)\n\n # Clear and reset removed decorations as we don't want to keep the\n # previous data, for example when a box is split between two pages.\n self.remove_decoration_sides = set()\n\n return new_box","def copy_recursively(src, dst, overwrite=False, changed_only=True):\n if os.path.isdir(src):\n copytree(src, dst, overwrite, changed_only)\n else:\n copyfile(src, dst, overwrite, changed_only)","def svn_client_copy5(svn_commit_info_t_commit_info_p, apr_array_header_t_sources, char_dst_path, svn_boolean_t_copy_as_child, svn_boolean_t_make_parents, svn_boolean_t_ignore_externals, apr_hash_t_revprop_table, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\n pass","def test_clone_scenario(self):\n pass","def copy_templates(self, in_dir):\n self.copy_contents(in_dir, subdir=\"templates\")","def copy(self, source, target, recursive=True):\n if recursive:\n command = 'cp -R %s %s'\n else:\n command = 'cp %s %s'\n self.communicate(command % (source, target))","def test_after_creation_copy():\n builder = TreeBuilder()\n builder.create_root(0)\n builder.add_child(2, move=True)\n builder.add_child(13)\n builder.move_to_parent()\n builder.add_child(7)\n\n t1 = builder.build()\n\n builder.move_to_root()\n builder.set_data(4)\n builder.add_child(3, move=True)\n builder.add_child(15)\n\n t2 = builder.build()\n\n assert t2 is not t1\n assert t2[0] is not t1[0]\n assert t2[0][0] is not t1[0][0]\n assert t2[1] is not t1[1]\n\n assert t2.data == 4\n assert t2[0].data == 2\n assert t2[0][0].data == 13\n assert t2[1].data == 7\n assert t2[2].data == 3\n assert t2[2][0].data == 15\n\n assert len(t2) == 3\n assert len(t2[0]) == 1\n assert len(t2[1]) == 0\n assert len(t2[2]) == 1"],"string":"[\n \"def copy_pages(config):\\n\\n if \\\"Pages\\\" not in config:\\n INFO(\\\"No information about pages\\\")\\n return\\n\\n target_path = os.path.join(config[\\\"target\\\"][\\\"path\\\"],\\n constants.PAGES_FOLDER)\\n\\n pages = config[\\\"Pages\\\"]\\n params = {\\n # \\\"rename\\\": None,\\n \\\"exclude\\\": None,\\n \\\"include\\\": None\\n }\\n\\n if not isinstance(pages, (list, tuple)):\\n pages = (pages,)\\n\\n new_pages = []\\n for page in pages:\\n if isinstance(page, (str, unicode)):\\n _page = {\\n \\\"path\\\": normalize_path(page, config)\\n }\\n\\n if not _page[\\\"path\\\"].rstrip(\\\"\\\\/\\\").lower().endswith(\\\"pages\\\"):\\n new_pages.append(page)\\n else:\\n if isinstance(page, dict):\\n _page[\\\"path\\\"] = normalize_path(page[\\\"path\\\"], config)\\n\\n for param in params:\\n params[param] = val = page.get(param, None)\\n if val and not isinstance(val, (list, tuple, dict)):\\n params[param] = (val,)\\n\\n if params[\\\"exclude\\\"]:\\n params[\\\"exclude\\\"] = convert_to_regexp(params[\\\"exclude\\\"])\\n\\n if params[\\\"include\\\"]:\\n params[\\\"include\\\"] = convert_to_regexp(params[\\\"include\\\"])\\n\\n if not os.path.exists(_page[\\\"path\\\"]):\\n ERROR(\\\"No such directory: '%s'\\\", _page[\\\"path\\\"])\\n continue\\n\\n for folder in os.listdir(_page[\\\"path\\\"]):\\n\\n # if folder in exclude list - continue\\n if params[\\\"exclude\\\"] and check_by_regexps(folder, params[\\\"exclude\\\"]):\\n continue\\n\\n # if folder not in include list - continue\\n if params[\\\"include\\\"] and not check_by_regexps(folder, params[\\\"include\\\"]):\\n continue\\n\\n folder_path = os.path.join(_page[\\\"path\\\"], folder)\\n\\n if not os.path.isdir(folder_path):\\n ERROR(\\\"Page can't be file: %s\\\", folder_path)\\n continue\\n\\n new_page = _page.copy()\\n new_page[\\\"path\\\"] = folder_path\\n new_pages.append(new_page)\\n\\n\\n for page in new_pages:\\n\\n if isinstance(page, (str, unicode)):\\n page = {\\n \\\"path\\\": page\\n }\\n\\n # normalize path - replace alias with real path\\n page[\\\"path\\\"] = normalize_path(page[\\\"path\\\"], config)\\n if not os.path.exists(page[\\\"path\\\"]):\\n ERROR(\\\"No such directory: '{}'\\\".format(page[\\\"path\\\"]))\\n continue\\n\\n # if name not defined - got it from folder name\\n if not page.get(\\\"name\\\", \\\"\\\"):\\n page[\\\"name\\\"] = os.path.split(page[\\\"path\\\"].rstrip(\\\"\\\\/\\\"))[1]\\n page[\\\"rename\\\"] = False\\n\\n copy_path = os.path.join(target_path, page[\\\"name\\\"])\\n if os.path.exists(copy_path):\\n ERROR(\\\"Directory already exists: '{}'\\\".format(copy_path))\\n continue\\n\\n if page.get(\\\"mode\\\", \\\"\\\") not in (\\\"move\\\", \\\"copy\\\"):\\n page[\\\"mode\\\"] = \\\"move\\\"\\n\\n # copy page to new folder\\n DEBUG(\\\"Copy '{}' to '{}'\\\".format(page[\\\"path\\\"], copy_path))\\n shutil.copytree(page[\\\"path\\\"], copy_path)\\n\\n info_path = os.path.join(copy_path, constants.INFO_FILE)\\n with fopen(info_path, \\\"rb\\\") as hdlr:\\n info = json_load(hdlr, critical=True)\\n\\n if page.get(\\\"rename\\\", True):\\n info[\\\"attrs\\\"][\\\"Name\\\"] = page[\\\"name\\\"]\\n\\n with fopen(info_path, \\\"wb\\\") as hdlr:\\n json_dump(info, hdlr, critical=True)\\n\\n # if page not copied continue, else need to change all guids to new\\n if page[\\\"mode\\\"] == \\\"move\\\":\\n continue\\n\\n new_guid = gen_guid()\\n old_guid = info[\\\"attrs\\\"][\\\"ID\\\"]\\n\\n GUIDS_TO_REPLACE[old_guid] = new_guid\\n GUIDS_TO_REPLACE[old_guid.replace(\\\"-\\\", \\\"_\\\")] = new_guid.replace(\\\"-\\\", \\\"_\\\")\\n\\n INFO(\\\"Pages were copied successfully\\\")\",\n \"def impersonate_other_page(page, other_page):\\n page.path = other_page.path\\n page.depth = other_page.depth\\n page.url_path = other_page.url_path\\n page.title = other_page.title\",\n \"def add_page_to( self, content, dest):\\n index = len(dest.xpath(\\\"./*\\\"))\\n dest.insert(index + 1, content)\",\n \"def test_copy_page_nested_plugin_moved_parent_plugin(self):\\n with SettingsOverride(CMS_MODERATOR=False, CMS_PERMISSION=False):\\n templates = []\\n # setup page 1\\n page_one = create_page(u\\\"Three Placeholder\\\", u\\\"col_three.html\\\", u\\\"en\\\",\\n position=u\\\"last-child\\\", published=True, in_navigation=True)\\n page_one_ph_one = page_one.placeholders.get(slot=u\\\"col_sidebar\\\")\\n page_one_ph_two = page_one.placeholders.get(slot=u\\\"col_left\\\")\\n page_one_ph_three = page_one.placeholders.get(slot=u\\\"col_right\\\")\\n # add the text plugin to placeholder one\\n text_plugin_en = add_plugin(page_one_ph_one, u\\\"TextPlugin\\\", u\\\"en\\\", body=u\\\"Hello World\\\")\\n self.assertEquals(text_plugin_en.id, CMSPlugin.objects.all()[0].id)\\n self.assertEquals(text_plugin_en.get_children().count(), 0)\\n pre_add_plugin_count = CMSPlugin.objects.count()\\n self.assertEqual(pre_add_plugin_count, 1)\\n # add a plugin to placeholder twho\\n pre_nesting_body = u\\\"<p>the nested text plugin with a link inside</p>\\\"\\n text_plugin_two = add_plugin(page_one_ph_two, u\\\"TextPlugin\\\", u\\\"en\\\", body=pre_nesting_body)\\n text_plugin_two = self.reload(text_plugin_two)\\n # prepare nestin plugin\\n page_one_ph_two = self.reload(page_one_ph_two)\\n text_plugin_two = self.reload(text_plugin_two)\\n link_plugin = add_plugin(page_one_ph_two, u\\\"LinkPlugin\\\", u\\\"en\\\", target=text_plugin_two)\\n link_plugin.name = u\\\"django-cms Link\\\"\\n link_plugin.url = u\\\"https://www.django-cms.org\\\" \\n link_plugin.parent = text_plugin_two\\n link_plugin.save()\\n # reload after every save\\n link_plugin = self.reload(link_plugin)\\n text_plugin_two = self.reload(text_plugin_two)\\n in_txt = u\\\"\\\"\\\"<img id=\\\"plugin_obj_%s\\\" title=\\\"Link\\\" alt=\\\"Link\\\" src=\\\"/static/cms/images/plugins/link.png\\\">\\\"\\\"\\\"\\n nesting_body = \\\"%s<p>%s</p>\\\" % (text_plugin_two.body, (in_txt % (link_plugin.id)))\\n # emulate the editor in admin that adds some txt for the nested plugin\\n text_plugin_two.body = nesting_body\\n text_plugin_two.save()\\n text_plugin_two = self.reload(text_plugin_two)\\n # the link is attached as a child?\\n self.assertEquals(text_plugin_two.get_children().count(), 1)\\n post_add_plugin_count = CMSPlugin.objects.count()\\n self.assertEqual(post_add_plugin_count, 3)\\n page_one.save()\\n # get the plugins from the original page\\n page_one = self.reload(page_one)\\n page_one_ph_one = page_one.placeholders.get(slot = u\\\"col_sidebar\\\")\\n page_one_ph_two = page_one.placeholders.get(slot = u\\\"col_left\\\")\\n page_one_ph_three = page_one.placeholders.get(slot = u\\\"col_right\\\")\\n # verify the plugins got created\\n org_placeholder_one_plugins = page_one_ph_one.get_plugins()\\n self.assertEquals(len(org_placeholder_one_plugins), 1)\\n org_placeholder_two_plugins = page_one_ph_two.get_plugins()\\n self.assertEquals(len(org_placeholder_two_plugins), 2)\\n org_placeholder_three_plugins = page_one_ph_three.get_plugins()\\n self.assertEquals(len(org_placeholder_three_plugins), 0)\\n self.assertEquals(page_one.placeholders.count(), 3)\\n \\n placeholder_count = Placeholder.objects.count()\\n self.assertEquals(placeholder_count, 3)\\n self.assertEquals(CMSPlugin.objects.count(), 3)\\n page_one_plugins = CMSPlugin.objects.all()\\n # setup page_copy_target\\n page_copy_target = create_page(\\\"Three Placeholder - page copy target\\\", \\\"col_three.html\\\", \\\"en\\\",\\n position=\\\"last-child\\\", published=True, in_navigation=True)\\n all_page_count = Page.objects.all().count()\\n pre_copy_placeholder_count = Placeholder.objects.count()\\n self.assertEquals(pre_copy_placeholder_count, 6)\\n superuser = self.get_superuser()\\n with self.login_user_context(superuser):\\n # now move the parent text plugin to another placeholder\\n post_data = {\\n u'placeholder': u\\\"col_right\\\",\\n u'placeholder_id': u\\\"%s\\\" % (page_one_ph_three.id),\\n u'ids': u\\\"%s\\\" % (text_plugin_two.id),\\n u'plugin_id': u\\\"%s\\\" % (text_plugin_two.id),\\n }\\n edit_url = URL_CMS_MOVE_PLUGIN % (page_one.id)\\n response = self.client.post(edit_url, post_data)\\n self.assertEqual(response.status_code, 200)\\n self.assertEqual(response.content, u'ok')\\n # check if the plugin got moved\\n page_one = self.reload(page_one)\\n text_plugin_two = self.reload(text_plugin_two)\\n page_one_ph_one = page_one.placeholders.get(slot = u\\\"col_sidebar\\\")\\n page_one_ph_two = page_one.placeholders.get(slot = u\\\"col_left\\\")\\n page_one_ph_three = page_one.placeholders.get(slot = u\\\"col_right\\\")\\n \\n org_placeholder_one_plugins = page_one_ph_one.get_plugins()\\n self.assertEquals(len(org_placeholder_one_plugins), 1)\\n org_placeholder_two_plugins = page_one_ph_two.get_plugins()\\n # the plugin got moved and child got moved\\n self.assertEquals(len(org_placeholder_two_plugins), 0)\\n org_placeholder_three_plugins = page_one_ph_three.get_plugins()\\n self.assertEquals(len(org_placeholder_three_plugins), 2)\\n # copy the page\\n page_two = self.copy_page(page_one, page_copy_target)\\n # validate the expected pages,placeholders,plugins,pluginbodies\\n after_copy_page_plugin_count = CMSPlugin.objects.count()\\n self.assertEquals(after_copy_page_plugin_count, 6)\\n after_copy_page_count = Page.objects.all().count()\\n after_copy_placeholder_count = Placeholder.objects.count()\\n self.assertTrue((after_copy_page_count > all_page_count), msg = u\\\"no new page after copy\\\")\\n self.assertTrue((after_copy_page_plugin_count > post_add_plugin_count), msg = u\\\"plugin count is not grown\\\")\\n self.assertTrue((after_copy_placeholder_count > pre_copy_placeholder_count), msg = u\\\"placeholder count is not grown\\\") \\n self.assertTrue((after_copy_page_count == 3), msg = u\\\"no new page after copy\\\")\\n # validate the structure\\n # orginal placeholder\\n page_one = self.reload(page_one)\\n page_one_ph_one = page_one.placeholders.get(slot=u\\\"col_sidebar\\\")\\n page_one_ph_two = page_one.placeholders.get(slot=u\\\"col_left\\\")\\n page_one_ph_three = page_one.placeholders.get(slot=u\\\"col_right\\\")\\n # check if there are multiple pages assigned to this placeholders\\n found_page = page_one_ph_one.page if page_one_ph_one else None\\n self.assertEqual(found_page, page_one)\\n found_page = page_one_ph_two.page if page_one_ph_two else None\\n self.assertEqual(found_page, page_one)\\n found_page = page_one_ph_three.page if page_one_ph_three else None\\n self.assertEqual(found_page, page_one)\\n page_two = self.reload(page_two)\\n page_two_ph_one = page_two.placeholders.get(slot = u\\\"col_sidebar\\\")\\n page_two_ph_two = page_two.placeholders.get(slot = u\\\"col_left\\\")\\n page_two_ph_three = page_two.placeholders.get(slot = u\\\"col_right\\\")\\n # check if there are multiple pages assigned to this placeholders\\n found_page = page_two_ph_one.page if page_two_ph_one else None\\n self.assertEqual(found_page, page_two)\\n found_page = page_two_ph_two.page if page_two_ph_two else None\\n self.assertEqual(found_page, page_two)\\n found_page = page_two_ph_three.page if page_two_ph_three else None\\n self.assertEqual(found_page, page_two)\\n # check the stored placeholders org vs copy\\n msg = u'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_one.pk, page_one_ph_one.pk, page_two.pk)\\n self.assertNotEquals(page_two_ph_one.pk, page_one_ph_one.pk, msg)\\n msg = u'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_two.pk, page_one_ph_two.pk, page_two.pk)\\n self.assertNotEquals(page_two_ph_two.pk, page_one_ph_two.pk, msg)\\n msg = u'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_three.pk, page_one_ph_three.pk, page_two.pk)\\n self.assertNotEquals(page_two_ph_three.pk, page_one_ph_three.pk, msg)\\n # get the plugins from the original page\\n org_placeholder_one_plugins = page_one_ph_one.get_plugins()\\n self.assertEquals(len(org_placeholder_one_plugins), 1)\\n org_placeholder_two_plugins = page_one_ph_two.get_plugins()\\n self.assertEquals(len(org_placeholder_two_plugins), 0)\\n org_placeholder_three_plugins = page_one_ph_three.get_plugins()\\n self.assertEquals(len(org_placeholder_three_plugins), 2)\\n # get the plugins from the copied page\\n copied_placeholder_one_plugins = page_two_ph_one.get_plugins()\\n self.assertEquals(len(copied_placeholder_one_plugins), 1)\\n copied_placeholder_two_plugins = page_two_ph_two.get_plugins()\\n self.assertEquals(len(copied_placeholder_two_plugins), 0)\\n copied_placeholder_three_plugins = page_two_ph_three.get_plugins()\\n self.assertEquals(len(copied_placeholder_three_plugins), 2)\\n # verify the plugins got copied\\n # placeholder 1\\n count_plugins_copied = len(copied_placeholder_one_plugins)\\n count_plugins_org = len(org_placeholder_one_plugins)\\n msg = u\\\"plugin count %s %s for placeholder one not equal\\\" % (count_plugins_copied, count_plugins_org)\\n self.assertEquals(count_plugins_copied, count_plugins_org, msg) \\n # placeholder 2\\n count_plugins_copied = len(copied_placeholder_two_plugins)\\n count_plugins_org = len(org_placeholder_two_plugins)\\n msg = u\\\"plugin count %s %s for placeholder two not equal\\\" % (count_plugins_copied, count_plugins_org)\\n self.assertEquals(count_plugins_copied, count_plugins_org, msg) \\n # placeholder 3\\n count_plugins_copied = len(copied_placeholder_three_plugins)\\n count_plugins_org = len(org_placeholder_three_plugins)\\n msg = u\\\"plugin count %s %s for placeholder three not equal\\\" % (count_plugins_copied, count_plugins_org)\\n self.assertEquals(count_plugins_copied, count_plugins_org, msg)\\n # verify the body of text plugin with nested link plugin\\n # org to copied \\n org_nested_text_plugin = None\\n # do this iteration to find the real text plugin with the attached link\\n # the inheritance mechanism for the cmsplugins works through \\n # (tuple)get_plugin_instance()\\n for x in org_placeholder_three_plugins: \\n if x.plugin_type == u\\\"TextPlugin\\\":\\n instance = x.get_plugin_instance()[0]\\n if instance.body.startswith(pre_nesting_body):\\n org_nested_text_plugin = instance\\n break\\n copied_nested_text_plugin = None\\n for x in copied_placeholder_three_plugins: \\n if x.plugin_type == u\\\"TextPlugin\\\":\\n instance = x.get_plugin_instance()[0]\\n if instance.body.startswith(pre_nesting_body):\\n copied_nested_text_plugin = instance\\n break\\n msg = u\\\"orginal nested text plugin not found\\\"\\n self.assertNotEquals(org_nested_text_plugin, None, msg=msg)\\n msg = u\\\"copied nested text plugin not found\\\"\\n self.assertNotEquals(copied_nested_text_plugin, None, msg=msg)\\n # get the children ids of the texplugin with a nested link\\n # to check if the body of the text is generated correctly\\n org_link_child_plugin = org_nested_text_plugin.get_children()[0]\\n copied_link_child_plugin = copied_nested_text_plugin.get_children()[0]\\n # validate the textplugin body texts\\n msg = u\\\"org plugin and copied plugin are the same\\\"\\n self.assertTrue(org_link_child_plugin.id != copied_link_child_plugin.id, msg)\\n needle = u\\\"plugin_obj_%s\\\"\\n msg = u\\\"child plugin id differs to parent in body plugin_obj_id\\\"\\n # linked child is in body\\n self.assertTrue(org_nested_text_plugin.body.find(needle % (org_link_child_plugin.id)) != -1, msg)\\n msg = u\\\"copy: child plugin id differs to parent in body plugin_obj_id\\\"\\n self.assertTrue(copied_nested_text_plugin.body.find(needle % (copied_link_child_plugin.id)) != -1, msg)\\n # really nothing else\\n msg = u\\\"child link plugin id differs to parent body plugin_obj_id\\\"\\n self.assertTrue(org_nested_text_plugin.body.find(needle % (copied_link_child_plugin.id)) == -1, msg)\\n msg = u\\\"copy: child link plugin id differs to parent body plugin_obj_id\\\"\\n self.assertTrue(copied_nested_text_plugin.body.find(needle % (org_link_child_plugin.id)) == -1, msg)\\n # now reverse lookup the placeholders from the plugins\\n org_placeholder = org_link_child_plugin.placeholder\\n copied_placeholder = copied_link_child_plugin.placeholder\\n msg = u\\\"placeholder of the orginal plugin and copied plugin are the same\\\"\\n ok = ((org_placeholder.id != copied_placeholder.id))\\n self.assertTrue(ok, msg)\",\n \"def _create_copy(self, node, direction):\\n new_node = copy.copy(node)\\n new_node.set_uri(direction)\\n new_location = get_location(direction)\\n # Insert into db \\n self.sm.create_node(new_node.tostring(), direction, NODETYPES[node.TYPE], location = new_location)\\n return new_location\",\n \"def edit(self, **kwargs):\\n response = self._requester.request(\\n \\\"PUT\\\",\\n \\\"{}s/{}/pages/{}\\\".format(self.parent_type, self.parent_id, self.url),\\n _kwargs=combine_kwargs(**kwargs),\\n )\\n\\n page_json = response.json()\\n page_json.update({\\\"course_id\\\": self.course_id})\\n super(Page, self).set_attributes(page_json)\\n\\n return self\",\n \"def create_page_in_admin(comicsite,title,content=\\\"testcontent\\\",permission_lvl=\\\"\\\"):\\n \\n if permission_lvl == \\\"\\\":\\n permission_lvl = Page.ALL\\n \\n page_admin = PageAdmin(Page,admin.site)\\n page = Page.objects.create(title=title,\\n comicsite=comicsite,\\n html=content,\\n permission_lvl=permission_lvl)\\n page_admin.first_save(page)\\n return page\",\n \"def test_copy_page_nested_plugin(self):\\n with SettingsOverride(CMS_MODERATOR=False, CMS_PERMISSION=False):\\n templates = []\\n # setup page 1\\n page_one = create_page(u\\\"Three Placeholder\\\", u\\\"col_three.html\\\", u\\\"en\\\",\\n position=u\\\"last-child\\\", published=True, in_navigation=True)\\n page_one_ph_one = page_one.placeholders.get(slot=u\\\"col_sidebar\\\")\\n page_one_ph_two = page_one.placeholders.get(slot=u\\\"col_left\\\")\\n page_one_ph_three = page_one.placeholders.get(slot=u\\\"col_right\\\")\\n # add the text plugin to placeholder one\\n text_plugin_en = add_plugin(page_one_ph_one, u\\\"TextPlugin\\\", u\\\"en\\\", body=\\\"Hello World\\\")\\n self.assertEquals(text_plugin_en.id, CMSPlugin.objects.all()[0].id)\\n self.assertEquals(text_plugin_en.get_children().count(), 0)\\n pre_add_plugin_count = CMSPlugin.objects.count()\\n self.assertEqual(pre_add_plugin_count, 1)\\n ###\\n # add a plugin to placeholder two\\n ###\\n pre_nesting_body = u\\\"<p>the nested text plugin with a link inside</p>\\\"\\n text_plugin_two = add_plugin(page_one_ph_two, u\\\"TextPlugin\\\", u\\\"en\\\", body=pre_nesting_body)\\n text_plugin_two = self.reload(text_plugin_two)\\n # prepare nesting plugin\\n page_one_ph_two = self.reload(page_one_ph_two)\\n text_plugin_two = self.reload(text_plugin_two)\\n link_plugin = add_plugin(page_one_ph_two, u\\\"LinkPlugin\\\", u\\\"en\\\", target=text_plugin_two)\\n link_plugin.name = u\\\"django-cms Link\\\"\\n link_plugin.url = u\\\"https://www.django-cms.org\\\" \\n link_plugin.parent = text_plugin_two\\n link_plugin.save()\\n \\n link_plugin = self.reload(link_plugin)\\n text_plugin_two = self.reload(text_plugin_two)\\n in_txt = \\\"\\\"\\\"<img id=\\\"plugin_obj_%s\\\" title=\\\"Link\\\" alt=\\\"Link\\\" src=\\\"/static/cms/images/plugins/link.png\\\">\\\"\\\"\\\"\\n nesting_body = \\\"%s<p>%s</p>\\\" % (text_plugin_two.body, (in_txt % (link_plugin.id)))\\n # emulate the editor in admin that adds some txt for the nested plugin\\n text_plugin_two.body = nesting_body\\n text_plugin_two.save()\\n text_plugin_two = self.reload(text_plugin_two)\\n # the link is attached as a child?\\n self.assertEquals(text_plugin_two.get_children().count(), 1)\\n post_add_plugin_count = CMSPlugin.objects.count()\\n self.assertEqual(post_add_plugin_count, 3)\\n page_one.save()\\n # get the plugins from the original page\\n page_one = self.reload(page_one)\\n page_one_ph_one = page_one.placeholders.get(slot = u\\\"col_sidebar\\\")\\n page_one_ph_two = page_one.placeholders.get(slot = u\\\"col_left\\\")\\n page_one_ph_three = page_one.placeholders.get(slot = u\\\"col_right\\\")\\n # verifiy the plugins got created\\n org_placeholder_one_plugins = page_one_ph_one.get_plugins()\\n self.assertEquals(len(org_placeholder_one_plugins), 1)\\n org_placeholder_two_plugins = page_one_ph_two.get_plugins()\\n self.assertEquals(len(org_placeholder_two_plugins), 2)\\n org_placeholder_three_plugins = page_one_ph_three.get_plugins()\\n self.assertEquals(len(org_placeholder_three_plugins), 0)\\n self.assertEquals(page_one.placeholders.count(), 3)\\n placeholder_count = Placeholder.objects.count()\\n self.assertEquals(placeholder_count, 3)\\n self.assertEquals(CMSPlugin.objects.count(), 3)\\n page_one_plugins = CMSPlugin.objects.all()\\n ##\\n # setup page_copy_target page\\n ##\\n page_copy_target = create_page(\\\"Three Placeholder - page copy target\\\", \\\"col_three.html\\\", \\\"en\\\",\\n position=\\\"last-child\\\", published=True, in_navigation=True)\\n all_page_count = Page.objects.all().count()\\n pre_copy_placeholder_count = Placeholder.objects.count()\\n self.assertEquals(pre_copy_placeholder_count, 6)\\n # copy the page\\n superuser = self.get_superuser()\\n with self.login_user_context(superuser):\\n page_two = self.copy_page(page_one, page_copy_target)\\n # validate the expected pages,placeholders,plugins,pluginbodies\\n after_copy_page_plugin_count = CMSPlugin.objects.count()\\n self.assertEquals(after_copy_page_plugin_count, 6)\\n # check the amount of copied stuff\\n after_copy_page_count = Page.objects.all().count()\\n after_copy_placeholder_count = Placeholder.objects.count()\\n self.assertTrue((after_copy_page_count > all_page_count), msg = u\\\"no new page after copy\\\")\\n self.assertTrue((after_copy_page_plugin_count > post_add_plugin_count), msg = u\\\"plugin count is not grown\\\")\\n self.assertTrue((after_copy_placeholder_count > pre_copy_placeholder_count), msg = u\\\"placeholder count is not grown\\\") \\n self.assertTrue((after_copy_page_count == 3), msg = u\\\"no new page after copy\\\")\\n # orginal placeholder\\n page_one = self.reload(page_one)\\n page_one_ph_one = page_one.placeholders.get(slot = u\\\"col_sidebar\\\")\\n page_one_ph_two = page_one.placeholders.get(slot = u\\\"col_left\\\")\\n page_one_ph_three = page_one.placeholders.get(slot = u\\\"col_right\\\")\\n # check if there are multiple pages assigned to this placeholders\\n found_page = page_one_ph_one.page if page_one_ph_one else None\\n self.assertEqual(found_page, page_one)\\n found_page = page_one_ph_two.page if page_one_ph_two else None\\n self.assertEqual(found_page, page_one)\\n found_page = page_one_ph_three.page if page_one_ph_three else None\\n self.assertEqual(found_page, page_one)\\n \\n page_two = self.reload(page_two)\\n page_two_ph_one = page_two.placeholders.get(slot = u\\\"col_sidebar\\\")\\n page_two_ph_two = page_two.placeholders.get(slot = u\\\"col_left\\\")\\n page_two_ph_three = page_two.placeholders.get(slot = u\\\"col_right\\\")\\n # check if there are multiple pages assigned to this placeholders\\n found_page = page_two_ph_one.page if page_two_ph_one else None\\n self.assertEqual(found_page, page_two)\\n found_page = page_two_ph_two.page if page_two_ph_two else None\\n self.assertEqual(found_page, page_two)\\n found_page = page_two_ph_three.page if page_two_ph_three else None\\n self.assertEqual(found_page, page_two)\\n # check the stored placeholders org vs copy\\n msg = 'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_one.pk, page_one_ph_one.pk, page_two.pk)\\n self.assertNotEquals(page_two_ph_one.pk, page_one_ph_one.pk, msg)\\n msg = 'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_two.pk, page_one_ph_two.pk, page_two.pk)\\n self.assertNotEquals(page_two_ph_two.pk, page_one_ph_two.pk, msg)\\n msg = 'placehoder ids copy:%s org:%s copied page %s are identical - tree broken' % (page_two_ph_three.pk, page_one_ph_three.pk, page_two.pk)\\n self.assertNotEquals(page_two_ph_three.pk, page_one_ph_three.pk, msg)\\n # get the plugins from the original page\\n org_placeholder_one_plugins = page_one_ph_one.get_plugins()\\n self.assertEquals(len(org_placeholder_one_plugins), 1)\\n org_placeholder_two_plugins = page_one_ph_two.get_plugins()\\n self.assertEquals(len(org_placeholder_two_plugins), 2)\\n org_placeholder_three_plugins = page_one_ph_three.get_plugins()\\n self.assertEquals(len(org_placeholder_three_plugins), 0)\\n # get the plugins from the copied page\\n copied_placeholder_one_plugins = page_two_ph_one.get_plugins()\\n self.assertEquals(len(copied_placeholder_one_plugins), 1)\\n copied_placeholder_two_plugins = page_two_ph_two.get_plugins()\\n self.assertEquals(len(copied_placeholder_two_plugins), 2)\\n copied_placeholder_three_plugins = page_two_ph_three.get_plugins()\\n self.assertEquals(len(copied_placeholder_three_plugins), 0)\\n # verify the plugins got copied\\n # placeholder 1\\n count_plugins_copied = len(copied_placeholder_one_plugins)\\n count_plugins_org = len(org_placeholder_one_plugins)\\n msg = u\\\"plugin count %s %s for placeholder one not equal\\\" % (count_plugins_copied, count_plugins_org)\\n self.assertEquals(count_plugins_copied, count_plugins_org, msg) \\n # placeholder 2\\n count_plugins_copied = len(copied_placeholder_two_plugins)\\n count_plugins_org = len(org_placeholder_two_plugins)\\n msg = u\\\"plugin count %s %s for placeholder two not equal\\\" % (count_plugins_copied, count_plugins_org)\\n self.assertEquals(count_plugins_copied, count_plugins_org, msg) \\n # placeholder 3\\n count_plugins_copied = len(copied_placeholder_three_plugins)\\n count_plugins_org = len(org_placeholder_three_plugins)\\n msg = u\\\"plugin count %s %s for placeholder three not equal\\\" % (count_plugins_copied, count_plugins_org)\\n self.assertEquals(count_plugins_copied, count_plugins_org, msg)\\n # verify the body of text plugin with nested link plugin\\n # org to copied \\n org_nested_text_plugin = None\\n # do this iteration to find the real text plugin with the attached link\\n # the inheritance mechanism for the cmsplugins works through \\n # (tuple)get_plugin_instance()\\n for x in org_placeholder_two_plugins: \\n if x.plugin_type == u\\\"TextPlugin\\\":\\n instance = x.get_plugin_instance()[0]\\n if instance.body.startswith(pre_nesting_body):\\n org_nested_text_plugin = instance\\n break\\n copied_nested_text_plugin = None\\n for x in copied_placeholder_two_plugins: \\n if x.plugin_type == u\\\"TextPlugin\\\":\\n instance = x.get_plugin_instance()[0]\\n if instance.body.startswith(pre_nesting_body):\\n copied_nested_text_plugin = instance\\n break\\n msg = u\\\"orginal nested text plugin not found\\\"\\n self.assertNotEquals(org_nested_text_plugin, None, msg=msg)\\n msg = u\\\"copied nested text plugin not found\\\"\\n self.assertNotEquals(copied_nested_text_plugin, None, msg=msg)\\n # get the children ids of the texplugin with a nested link\\n # to check if the body of the text is genrated correctly\\n org_link_child_plugin = org_nested_text_plugin.get_children()[0]\\n copied_link_child_plugin = copied_nested_text_plugin.get_children()[0]\\n # validate the textplugin body texts\\n msg = u\\\"org plugin and copied plugin are the same\\\"\\n self.assertTrue(org_link_child_plugin.id != copied_link_child_plugin.id, msg)\\n needle = u\\\"plugin_obj_%s\\\"\\n msg = u\\\"child plugin id differs to parent in body plugin_obj_id\\\"\\n # linked child is in body\\n self.assertTrue(org_nested_text_plugin.body.find(needle % (org_link_child_plugin.id)) != -1, msg)\\n msg = u\\\"copy: child plugin id differs to parent in body plugin_obj_id\\\"\\n self.assertTrue(copied_nested_text_plugin.body.find(needle % (copied_link_child_plugin.id)) != -1, msg)\\n # really nothing else\\n msg = u\\\"child link plugin id differs to parent body plugin_obj_id\\\"\\n self.assertTrue(org_nested_text_plugin.body.find(needle % (copied_link_child_plugin.id)) == -1, msg)\\n msg = u\\\"copy: child link plugin id differs to parent body plugin_obj_id\\\"\\n self.assertTrue(copied_nested_text_plugin.body.find(needle % (org_link_child_plugin.id)) == -1, msg)\\n # now reverse lookup the placeholders from the plugins\\n org_placeholder = org_link_child_plugin.placeholder\\n copied_placeholder = copied_link_child_plugin.placeholder\\n msg = u\\\"placeholder of the orginal plugin and copied plugin are the same\\\"\\n ok = ((org_placeholder.id != copied_placeholder.id))\\n self.assertTrue(ok, msg)\",\n \"def copy_structure(self, other_directory):\\n pass\",\n \"def cpr(src, dst):\\n shutil.copytree(src, dst)\",\n \"def test_placeholder_inherit_content(self):\\n from pages import settings as pages_settings\\n setattr(pages_settings, \\\"PAGE_USE_SITE_ID\\\", False)\\n author = User.objects.all()[0]\\n p1 = self.new_page(content={'inher':'parent-content'})\\n p2 = self.new_page()\\n template = django.template.loader.get_template('pages/tests/test7.html')\\n context = Context({'current_page': p2, 'lang':'en-us'})\\n self.assertEqual(template.render(context), '')\\n \\n p2.move_to(p1, position='first-child')\\n self.assertEqual(template.render(context), 'parent-content')\",\n \"def update_children(page, prefix=None, walked_pages=None):\\n walked_pages = walked_pages if walked_pages else []\\n # Perfix used to determine the children path.\\n page_segment = page.path\\n if prefix:\\n page_segment = prefix + '/' + page_segment\\n page.real_path = page_segment\\n page.save()\\n for child in page.children.all():\\n # Update the real path for this descendant.\\n if child in walked_pages:\\n # This page has been processed before, ignore.\\n continue\\n walked_pages.append(child)\\n update_children(child, page_segment, walked_pages)\\n return True\",\n \"def create_page_in_projectadmin(comicsite,title,content=\\\"testcontent\\\",permission_lvl=\\\"\\\",comicsite_for_page=\\\"\\\"):\\n # to be able to test creating a page for a different comicsite from this admin\\n # should not be possible, but that's what tests are for\\n if comicsite_for_page == \\\"\\\":\\n comicsite_for_page = comicsite\\n \\n # Rename, trying to call comicsite 'project' everywhere. Doing a full\\n # rename is very hard however \\n project = comicsite\\n \\n \\n # Create the overarching admin interface for any single project \\n projectadminsite = get_projectadmin(project)\\n \\n # Each model in the admin interface has its own model admin, which is\\n # wrapped and modified by projectadminsite. Get this modified modeladmin\\n pageadmin = projectadminsite._registry[Page]\\n\\n # Now create the page and save in the correct project-only modified object\\n # admin...\\n if permission_lvl == \\\"\\\":\\n permission_lvl = Page.ALL\\n \\n page = Page.objects.create(title=title,\\n comicsite=comicsite,\\n html=content,\\n permission_lvl=permission_lvl)\\n pageadmin.first_save(page)\\n return page\",\n \"def copytree(src, dest):\\n shutil.copytree(src, dest)\\n restorecon(dest, recursive=True)\",\n \"def menu_save_copy(self, event=None):\\n if self.app.children:\\n self.app.childActive.saveCopy()\",\n \"def post(self, request, doc_id):\\n before = request.POST.get('before', False)\\n after = request.POST.get('after', False)\\n\\n try:\\n document = Document.objects.get(id=doc_id)\\n except Document.DoesNotExist:\\n raise Http404(\\\"Document does not exists\\\")\\n\\n if request.user.has_perm(\\n Access.PERM_WRITE, document\\n ):\\n Document.paste_pages(\\n user=request.user,\\n parent_id=document.parent,\\n dst_document=document,\\n doc_pages=request.pages.all(),\\n before=before,\\n after=after\\n )\\n\\n request.pages.clear()\\n\\n return Response(status=status.HTTP_204_NO_CONTENT)\\n\\n return Response(\\n status=status.HTTP_403_FORBIDDEN,\\n data={\\n 'msg': _(\\n \\\"You don't have permissions to paste pages\\\"\\n \\\" in this document.\\\"\\n )\\n }\\n )\",\n \"def copy(self):\\r\\n ret=' '\\r\\n if self.REQUEST.SESSION.has_key('my_path'):\\r\\n\\t zpath=self.REQUEST.SESSION['my_path'].replace('toolbox_root','').strip('/')\\r\\n\\t #ret=zpath\\r\\n\\t if self.REQUEST.SESSION.has_key('copy_bild'):\\r\\n\\t\\t cp_bild=self.REQUEST.SESSION['copy_bild'].split('/')[-1].strip('/')\\r\\n\\t\\t cp_path=str('/').join(self.REQUEST.SESSION['copy_bild'].split('/')[0:-1])\\r\\n\\t\\t #ret+=' '+cp_path+' '+cp_bild\\r\\n\\t\\t if cp_path!=zpath:\\r\\n\\t\\t \\tn_id=search_id(self,self.restrictedTraverse(zpath).objectValues('Image'))\\r\\n\\t\\t \\t#ret+=' '+n_id\\r\\n\\t\\t\\tfor x in liste_val:\\r\\n\\t\\t\\t\\ttry:\\r\\n\\t\\t\\t\\t\\tfor obj in self.restrictedTraverse(cp_path).objectValues('Image'):\\r\\n\\t\\t\\t\\t\\t if str(obj.getId())[0:6]==cp_bild:\\r\\n\\t\\t\\t\\t\\t\\tmy_clip=self.restrictedTraverse(cp_path).manage_copyObjects([obj.getId()])\\r\\n\\t\\t\\t\\t\\t\\tcopied=self.restrictedTraverse(zpath).manage_pasteObjects(my_clip)\\r\\n\\t\\t\\t\\t\\t\\t#ret+=' new id : '+str(copied[0]['new_id'])\\r\\n\\t\\t\\t\\t\\t\\t#if str(copied[0]['new_id']).split('_')[0]!=n_id:\\r\\n\\t\\t\\t\\t\\t\\t#\\tself.restrictedTraverse(zpath).manage_renameObjects([str(copied[0]['new_id'])],[str(n_id+x)])\\r\\n\\t\\t\\t\\t\\t\\t\\t#ret +=' False '\\r\\n\\t\\t\\t\\t\\t\\t#ret+='<br>\\\\n'\\r\\n\\t\\t\\t\\texcept:\\r\\n\\t\\t\\t\\t\\tret+=''\\r\\n else:\\r\\n\\t ret=' '\\r\\n return ' '\",\n \"def copy(\\n syn,\\n entity,\\n destinationId,\\n skipCopyWikiPage=False,\\n skipCopyAnnotations=False,\\n **kwargs,\\n):\\n updateLinks = kwargs.get(\\\"updateLinks\\\", True)\\n updateSynIds = kwargs.get(\\\"updateSynIds\\\", True)\\n entitySubPageId = kwargs.get(\\\"entitySubPageId\\\", None)\\n destinationSubPageId = kwargs.get(\\\"destinationSubPageId\\\", None)\\n\\n mapping = _copyRecursive(\\n syn, entity, destinationId, skipCopyAnnotations=skipCopyAnnotations, **kwargs\\n )\\n if not skipCopyWikiPage:\\n for oldEnt in mapping:\\n copyWiki(\\n syn,\\n oldEnt,\\n mapping[oldEnt],\\n entitySubPageId=entitySubPageId,\\n destinationSubPageId=destinationSubPageId,\\n updateLinks=updateLinks,\\n updateSynIds=updateSynIds,\\n entityMap=mapping,\\n )\\n return mapping\",\n \"def copy_drafts():\\r\\n draft_dir = path(source_dir) / course_name / DRAFT_DIR\\r\\n if draft_dir.isdir():\\r\\n shutil.copytree(draft_dir, copy_root / DRAFT_DIR)\",\n \"def copydir(self):\\n pass\",\n \"def new_page(request, parent_id):\\n if parent_id:\\n parent_page = models.Page.get_by_id(int(parent_id))\\n else:\\n parent_page = models.Page.get_root()\\n if parent_page:\\n # there is a root, lets force everything to be a child of the root\\n # and set the parent_id\\n parent_id = parent_page.key().id()\\n else:\\n # TODO(gpennington): Figure out a more intuitive method for site\\n # initialization\\n parent_page = utility.set_up_data_store()\\n return utility.edit_updated_page(parent_page.key().id())\\n\\n if not parent_page.user_can_write(request.profile):\\n return utility.forbidden(request)\\n return edit_page(request, None, parent_id=parent_id)\",\n \"def copySpecial():\\n depNode = nuke.dependencies(nuke.selectedNode())\\n dependNode = nuke.dependentNodes(nuke.INPUTS or nuke.HIDDEN_INPUTS or nuke.EXPRESSIONS, [nuke.selectedNode()])\\n i = 0\\n if dependNode[0].Class() in ['Scene', 'MergeGeo']:\\n i = nuke.inputs(dependNode[0])+1\\n\\n nuke.nodeCopy(nukescripts.cut_paste_file())\\n\\n for node in nuke.allNodes():\\n node['selected'].setValue(0)\\n\\n nuke.nodePaste(nukescripts.cut_paste_file())\\n\\n newNode = nuke.selectedNode()\\n newNode.setInput(0, depNode[0])\\n dependNode[0].setInput(i+1, newNode)\",\n \"def add_page(self, page): \\n self.pages.append(Page(page))\",\n \"def edit_page(request, page_id, parent_id=None):\\n page = None\\n files = None\\n\\n if page_id:\\n page = models.Page.get_by_id(int(page_id))\\n if not page:\\n return utility.page_not_found(\\n request, 'No page exists with id %r.' % page_id)\\n if not page.user_can_write(request.profile):\\n return utility.forbidden(request)\\n files = list(\\n models.FileStore.all().filter('parent_page =', page).order('name'))\\n for item in files:\\n item.icon = '/static/images/fileicons/%s.png' % item.name.split('.')[-1]\\n\\n acl_data = None\\n\\n if page:\\n all_group_keys = [\\n g.key() for g in models.UserGroup.all().order('name')]\\n groups_without_write_keys = [\\n k for k in all_group_keys if k not in page.acl.group_write]\\n groups_without_read_keys = [\\n k for k in all_group_keys if k not in page.acl.group_read]\\n acl_data = {\\n 'groups_without_write': models.UserGroup.get(groups_without_write_keys),\\n 'groups_without_read': models.UserGroup.get(groups_without_read_keys),\\n 'group_write': models.UserGroup.get(page.acl.group_write),\\n 'group_read': models.UserGroup.get(page.acl.group_read),\\n 'user_write': models.UserProfile.get(page.acl.user_write),\\n 'user_read': models.UserProfile.get(page.acl.user_read),\\n 'inherits_acl': page.inherits_acl(),\\n }\\n\\n if not request.POST:\\n form = forms.PageEditForm(data=None, instance=page)\\n return utility.respond(request, 'admin/edit_page',\\n {'form': form, 'page': page, 'files': files,\\n 'acl_data': acl_data})\\n\\n form = forms.PageEditForm(data=request.POST, instance=page)\\n\\n if not form.errors:\\n try:\\n page = form.save(commit=False)\\n except ValueError, err:\\n form.errors['__all__'] = unicode(err)\\n if form.errors:\\n return utility.respond(request, 'admin/edit_page',\\n {'form': form, 'page': page, 'files': files})\\n\\n page.content = request.POST['editorHtml']\\n if parent_id and not page.parent_page:\\n page.parent_page = models.Page.get_by_id(int(parent_id))\\n page.put()\\n\\n return utility.edit_updated_page(page.key().id(),\\n message_id='msgChangesSaved')\",\n \"def copy_children(self):\\n\\n # Create a group\\n self.fileh.create_group('/', 'agroup')\\n # Create several objects there\\n for i in range(10):\\n # Create a new array\\n self.fileh.create_array('/agroup', 'array' + str(i), self.a1)\\n # Excercise copy_children\\n for i in range(self.nobjects):\\n # Create another group for destination\\n self.fileh.create_group('/', 'anothergroup' + str(i))\\n # Copy children from /agroup to /anothergroup+i\\n self.fileh.copy_children('/agroup', '/anothergroup' + str(i))\\n # Put a mark\\n self.fileh.mark()\\n # Unwind all marks sequentially\\n for i in range(self.niter):\\n t1 = clock()\\n for i in range(self.nobjects):\\n self.fileh.undo()\\n if verbose:\\n print(\\\"u\\\", end=' ')\\n if verbose:\\n print()\\n undo = clock() - t1\\n # Rewind all marks sequentially\\n t1 = clock()\\n for i in range(self.nobjects):\\n self.fileh.redo()\\n if verbose:\\n print(\\\"r\\\", end=' ')\\n if verbose:\\n print()\\n redo = clock() - t1\\n\\n print((\\\"Time for Undo, Redo (copy_children):\\\", undo, \\\"s, \\\",\\n redo, \\\"s\\\"))\",\n \"def MovePage(self, page, new_idx):\\r\\n \\r\\n idx = self.GetIdxFromWindow(page)\\r\\n if idx == -1:\\r\\n return False\\r\\n\\r\\n # get page entry, make a copy of it\\r\\n p = self.GetPage(idx)\\r\\n\\r\\n # remove old page entry\\r\\n self.RemovePage(page)\\r\\n\\r\\n # insert page where it should be\\r\\n self.InsertPage(page, p, new_idx)\\r\\n\\r\\n return True\",\n \"def testCopyCollection(self):\\n copy = self.node.copy_collection()\\n\\n self.assertEqual(\\n self.node.type,\\n copy.type\\n )\\n\\n self.assertEqual(\\n self.node.desc,\\n copy.desc\\n )\\n\\n self.assertEqual(\\n self.node.input_desc,\\n copy.input_desc\\n )\\n\\n self.assertEqual(\\n self.node.viewing_desc,\\n copy.viewing_desc\\n )\\n\\n self.assertEqual(\\n self.node.all_children,\\n copy.all_children\\n )\",\n \"def copy(self):\",\n \"def __copy__(self):\\n return self.__class__(self.baseurl, self.template, self.selection[:],\\n self.slice[:], self.application)\",\n \"def process_page(html,dest):\\n html0 = html[:]\\n to_root = os.path.relpath(export_path,dest)\\n to_root = to_root[1:]# Change '../' or '..' to '.' or './'\\n \\n # Fix links to directories first since that is easier to find\\n html,N1 = re_dirlinks.subn(r'\\\\1=\\\"/\\\\2/index.html\\\"',html)\\n \\n # all pages links\\n html,N2 = re_all.subn(r'\\\\1=\\\"/_all/\\\\2/index.html\\\"',html)\\n \\n # Add index.html for any other internal links. NOTE: by preprocessing\\n # all internal links from the main content will already end in .html so this\\n # is just special pages.\\n for match in re_intlinks.finditer(html):\\n dest = match.groups()[-1]\\n ext = os.path.splitext(dest)[-1]\\n if ext == '':\\n old = r'{}=\\\"/{}\\\"'.format(*match.groups())\\n new = r'{}=\\\"/{}\\\"'.format(match.groups()[0], os.path.join(match.groups()[1],'index.html') )\\n html = html.replace(old,new)\\n \\n # Now make all links to the root\\n html,N3 = re_intlinks.subn(r'\\\\1=\\\"{}/\\\\2\\\"'.format(to_root),html)\\n \\n # Remove the search stuff\\n out = []\\n ff = False\\n for line in html.split('\\\\n'):\\n if not ff and '<!-- search -->' not in line:\\n out.append(line)\\n continue\\n \\n if '<!-- search -->' in line:\\n ff = True\\n \\n if ff and '<!-- /search -->' in line:\\n ff = False\\n\\n html = '\\\\n'.join(out)\\n return html\",\n \"def copyTo(self, folder):\\n copyUrl = self.metaData.getLink(\\\"copy\\\")\\n\\n if not hasattr(folder, \\\"metaData\\\"): raise TypeError(\\\"Your newFolder does not have a metaData property\\\")\\n assert getattr(folder, \\\"selfLink\\\")\\n assert copyUrl is not None\\n\\n header = self._baseHeader.copy()\\n header['Content-type'] = \\\"application/vnd.huddle.data+json\\\"\\n body = '{ \\\"targetFolder\\\":{ \\\"link\\\":{ \\\"rel\\\": \\\"self\\\", \\\"href\\\": \\\"' + folder.selfLink + '\\\" } } }'\\n\\n response = self._adapter.postRequest(copyUrl, header, body)\\n\\n return Document(self._client, response['Headers']['location'])\",\n \"def move_page(self, target, position='first-child'):\\n self.move_to(target, position)\\n # fire signal\\n \\n self.force_moderation_action = PageModeratorState.ACTION_MOVE\\n cms_signals.page_moved.send(sender=Page, instance=self) #titles get saved before moderation\\n self.save(change_state=True) # always save the page after move, because of publisher\",\n \"def copy():\\n copy2(per, per_old)\",\n \"def copy_tree(self, infile, outfile,\\n preserve_mode=1, preserve_times=1, preserve_symlinks=0,\\n level=1, condition=None):\\n return copy_tree(\\n infile, outfile,\\n preserve_mode,preserve_times,preserve_symlinks,\\n not self.force,\\n dry_run=self.dry_run,\\n condition=condition)\",\n \"def insert_copied(self, *args):\\n copy = self.get_copied_food()\\n if copy is not None:\\n fsp = self.get_food_search_panel()\\n fsp.reset_food_icon()\\n if type(copy.food) == Food:\\n food = FoodUsage(food=copy.food, amount=decimal.Decimal(100))\\n if self.meal.foods is None:\\n self.meal.foods = [food]\\n else:\\n self.meal.foods.append(food)\\n\\n self.add_food_node(food)\\n else: # copy.food is Recipe\\n recipe_exec = Recipe(name=copy.food.name, is_template=False, notes=\\\"\\\",\\n serving_size=decimal.Decimal(1), template=copy.food)\\n for ing in copy.food.ingredients:\\n recipe_exec.add_food(ing.food, ing.amount)\\n self.meal.add_recipe(recipe_exec)\\n recipe_node = TreeViewRecipe(recipe=recipe_exec,\\n meal_tree_box=self.meal_tree_box,\\n parent_node=self)\\n fsp.remove_copy()\\n self.update_text(True)\",\n \"def _copyTemplate(sourceBase, destination):\\n source = os.path.normpath(os.path.join(sourceBase, \\\"_New_Region\\\", \\\"Template\\\"))\\n copy_tree(source, destination, preserve_mode=1, preserve_times=1, preserve_symlinks=1)\",\n \"def on_page_content(self, content, page, config, files):\\n logging.debug(\\\"--- on_pre_page ---\\\")\\n logging.debug(self.config)\\n logging.debug(page.__repr__())\\n\\n source_dir = os.path.dirname(page.file.abs_src_path)\\n logging.debug('source dir: ' + source_dir)\\n\\n dest_dir = os.path.dirname(page.file.abs_dest_path)\\n os.makedirs(dest_dir, exist_ok=True)\\n exists_dest_dir = os.path.isdir(dest_dir)\\n logging.debug('dest dir: ' + dest_dir +\\n ' (exists: ' + str(exists_dest_dir) + ')')\\n\\n source_file = os.path.join(source_dir, '.htaccess')\\n exists_dest_file = os.path.isfile(source_file)\\n logging.debug('source file: ' + source_file +\\n ' (exists: ' + str(exists_dest_file) + ')')\\n\\n exists_dest_file and utils.copy_file(source_file, dest_dir)\\n logging.debug(\\\"--- /on_pre_page ---\\\")\\n\\n return content\",\n \"def CopyTo(self, *args, **kwargs):\\n pass\",\n \"def change_directory(\\n self,\\n destination: PagePathLike\\n ) -> None:\\n try:\\n full_path: str = self.explode(destination)\\n except OutOfBoundsPageError as e:\\n raise e\\n\\n if full_path not in self:\\n raise NoSuchPageError(full_path)\\n elif full_path == self.current_page.path:\\n return\\n\\n self._back_page_history_stack.append(self._current_page)\\n self._current_page = self[full_path]\",\n \"def save(self, force_insert=False, force_update=False):\\n if self.moderate_descendants:\\n self.moderate_children = True\\n else:\\n self.moderate_children = False\\n super(PageModerator, self).save(force_insert, force_update)\",\n \"def create_page(self, space, title, body, parent_id=None, update_message=None):\\n page_structure = {\\n 'title': title,\\n 'type': 'page',\\n 'space': {\\n 'key': space\\n },\\n 'body': {\\n 'storage': {\\n 'value': body,\\n 'representation': 'storage'\\n }\\n }\\n }\\n\\n if parent_id is not None:\\n if type(parent_id) is str:\\n parent_id = int(parent_id)\\n page_structure['ancestors'] = [{'id': parent_id}]\\n\\n if update_message is not None:\\n page_structure['version'] = {'message': update_message}\\n\\n print(json.dumps(page_structure))\\n return self.api.content.post(json=page_structure)\",\n \"def make_site_dx(context):\\n portal = getSite()\\n\\n if portal._tree is not None:\\n # We assume the object has been already initialized\\n return\\n\\n portal._initBTrees()\\n\\n for obj_meta in portal._objects:\\n obj_id = obj_meta[\\\"id\\\"]\\n logger.info(\\\"Migrating object %r\\\", obj_id)\\n # Load the content object ...\\n obj = portal.__dict__.pop(obj_id)\\n if not isinstance(obj, Broken) and obj_id not in (\\n \\\"portal_quickinstaller\\\",\\n \\\"portal_form_controller\\\",\\n ):\\n # ...and insert it into the btree.\\n # Use _setOb so we don't reindex stuff: the paths stay the same.\\n portal._setOb(obj_id, obj)\\n\\n delattr(portal, \\\"_objects\\\")\\n portal._p_changed = True\",\n \"def copy_tree_checker(src, dst):\\n copy_tree(src, dst)\\n return True\",\n \"def update_page_entity(self,pid,pge):\\n if not hasattr(self,'_pages_entities'):\\n self.load_pages()\\n else:\\n pgs = self.get_pages_list()\\n for i in xrange(len(pgs)):\\n pe = pgs[i]\\n if pe.key().id() == pid:\\n pgs[i] = pge\\n break\",\n \"def _copy_subdag(self, user_id, destination_version, block_key, source_blocks, destination_blocks, blacklist):\\n orphans = set()\\n destination_block = destination_blocks.get(block_key)\\n new_block = source_blocks[block_key]\\n if destination_block:\\n # reorder children to correspond to whatever order holds for source.\\n # remove any which source no longer claims (put into orphans)\\n # add any which are being copied\\n source_children = new_block.fields.get('children', [])\\n existing_children = destination_block.fields.get('children', [])\\n destination_reordered = SparseList()\\n for child in existing_children:\\n try:\\n index = source_children.index(child)\\n destination_reordered[index] = child\\n except ValueError:\\n orphans.add(BlockKey(*child))\\n if blacklist != EXCLUDE_ALL:\\n for index, child in enumerate(source_children):\\n if child not in blacklist:\\n destination_reordered[index] = child\\n # the history of the published leaps between publications and only points to\\n # previously published versions.\\n previous_version = destination_block.edit_info.update_version\\n destination_block = copy.deepcopy(new_block)\\n destination_block.fields['children'] = destination_reordered.compact_list()\\n destination_block.edit_info.previous_version = previous_version\\n destination_block.edit_info.update_version = destination_version\\n destination_block.edit_info.edited_by = user_id\\n destination_block.edit_info.edited_on = datetime.datetime.now(UTC)\\n else:\\n destination_block = self._new_block(\\n user_id, new_block.block_type,\\n self._filter_blacklist(copy.copy(new_block.fields), blacklist),\\n new_block.definition,\\n destination_version,\\n raw=True,\\n asides=new_block.asides,\\n block_defaults=new_block.defaults\\n )\\n # Extend the block's new edit_info with any extra edit_info fields from the source (e.g. original_usage):\\n for key, val in new_block.edit_info.to_storable().items():\\n if getattr(destination_block.edit_info, key) is None:\\n setattr(destination_block.edit_info, key, val)\\n\\n # If the block we are copying from was itself a copy, then just\\n # reference the original source, rather than the copy.\\n destination_block.edit_info.source_version = (\\n new_block.edit_info.source_version or new_block.edit_info.update_version\\n )\\n\\n if blacklist != EXCLUDE_ALL:\\n for child in destination_block.fields.get('children', []):\\n if child not in blacklist:\\n orphans.update(\\n self._copy_subdag(\\n user_id, destination_version, BlockKey(*child), source_blocks, destination_blocks, blacklist\\n )\\n )\\n destination_blocks[block_key] = destination_block\\n return orphans\",\n \"def copyWiki(\\n syn,\\n entity,\\n destinationId,\\n entitySubPageId=None,\\n destinationSubPageId=None,\\n updateLinks=True,\\n updateSynIds=True,\\n entityMap=None,\\n):\\n\\n # Validate input parameters\\n if entitySubPageId:\\n entitySubPageId = str(int(entitySubPageId))\\n if destinationSubPageId:\\n destinationSubPageId = str(int(destinationSubPageId))\\n\\n oldOwn = syn.get(entity, downloadFile=False)\\n # getWikiHeaders fails when there is no wiki\\n\\n try:\\n oldWikiHeaders = syn.getWikiHeaders(oldOwn)\\n except SynapseHTTPError as e:\\n if e.response.status_code == 404:\\n return []\\n else:\\n raise e\\n\\n newOwn = syn.get(destinationId, downloadFile=False)\\n wikiIdMap = dict()\\n newWikis = dict()\\n # If entitySubPageId is given but not destinationSubPageId, set the pageId to \\\"\\\" (will get the root page)\\n # A entitySubPage could be copied to a project without any wiki pages, this has to be checked\\n newWikiPage = None\\n if destinationSubPageId:\\n try:\\n newWikiPage = syn.getWiki(newOwn, destinationSubPageId)\\n except SynapseHTTPError as e:\\n if e.response.status_code == 404:\\n pass\\n else:\\n raise e\\n if entitySubPageId:\\n oldWikiHeaders = _getSubWikiHeaders(oldWikiHeaders, entitySubPageId)\\n\\n if not oldWikiHeaders:\\n return []\\n\\n for wikiHeader in oldWikiHeaders:\\n wiki = syn.getWiki(oldOwn, wikiHeader[\\\"id\\\"])\\n syn.logger.info(\\\"Got wiki %s\\\" % wikiHeader[\\\"id\\\"])\\n if not wiki.get(\\\"attachmentFileHandleIds\\\"):\\n new_file_handles = []\\n else:\\n results = [\\n syn._getFileHandleDownload(\\n filehandleId, wiki.id, objectType=\\\"WikiAttachment\\\"\\n )\\n for filehandleId in wiki[\\\"attachmentFileHandleIds\\\"]\\n ]\\n # Get rid of the previews\\n nopreviews = [\\n attach[\\\"fileHandle\\\"]\\n for attach in results\\n if not attach[\\\"fileHandle\\\"][\\\"isPreview\\\"]\\n ]\\n contentTypes = [attach[\\\"contentType\\\"] for attach in nopreviews]\\n fileNames = [attach[\\\"fileName\\\"] for attach in nopreviews]\\n copiedFileHandles = copyFileHandles(\\n syn,\\n nopreviews,\\n [\\\"WikiAttachment\\\"] * len(nopreviews),\\n [wiki.id] * len(nopreviews),\\n contentTypes,\\n fileNames,\\n )\\n # Check if failurecodes exist\\n for filehandle in copiedFileHandles:\\n if filehandle.get(\\\"failureCode\\\") is not None:\\n raise ValueError(\\n \\\"%s dataFileHandleId: %s\\\"\\n % (\\n filehandle[\\\"failureCode\\\"],\\n filehandle[\\\"originalFileHandleId\\\"],\\n )\\n )\\n new_file_handles = [\\n filehandle[\\\"newFileHandle\\\"][\\\"id\\\"] for filehandle in copiedFileHandles\\n ]\\n # for some reason some wikis don't have titles?\\n if hasattr(wikiHeader, \\\"parentId\\\"):\\n newWikiPage = Wiki(\\n owner=newOwn,\\n title=wiki.get(\\\"title\\\", \\\"\\\"),\\n markdown=wiki.markdown,\\n fileHandles=new_file_handles,\\n parentWikiId=wikiIdMap[wiki.parentWikiId],\\n )\\n newWikiPage = syn.store(newWikiPage)\\n else:\\n if destinationSubPageId is not None and newWikiPage is not None:\\n newWikiPage[\\\"attachmentFileHandleIds\\\"] = new_file_handles\\n newWikiPage[\\\"markdown\\\"] = wiki[\\\"markdown\\\"]\\n newWikiPage[\\\"title\\\"] = wiki.get(\\\"title\\\", \\\"\\\")\\n # Need to add logic to update titles here\\n newWikiPage = syn.store(newWikiPage)\\n else:\\n newWikiPage = Wiki(\\n owner=newOwn,\\n title=wiki.get(\\\"title\\\", \\\"\\\"),\\n markdown=wiki.markdown,\\n fileHandles=new_file_handles,\\n parentWikiId=destinationSubPageId,\\n )\\n newWikiPage = syn.store(newWikiPage)\\n newWikis[newWikiPage[\\\"id\\\"]] = newWikiPage\\n wikiIdMap[wiki[\\\"id\\\"]] = newWikiPage[\\\"id\\\"]\\n\\n if updateLinks:\\n syn.logger.info(\\\"Updating internal links:\\\\n\\\")\\n newWikis = _updateInternalLinks(newWikis, wikiIdMap, entity, destinationId)\\n syn.logger.info(\\\"Done updating internal links.\\\\n\\\")\\n\\n if updateSynIds and entityMap is not None:\\n syn.logger.info(\\\"Updating Synapse references:\\\\n\\\")\\n newWikis = _updateSynIds(newWikis, wikiIdMap, entityMap)\\n syn.logger.info(\\\"Done updating Synapse IDs.\\\\n\\\")\\n\\n syn.logger.info(\\\"Storing new Wikis\\\\n\\\")\\n for oldWikiId in wikiIdMap.keys():\\n newWikiId = wikiIdMap[oldWikiId]\\n newWikis[newWikiId] = syn.store(newWikis[newWikiId])\\n syn.logger.info(\\\"\\\\tStored: %s\\\\n\\\" % newWikiId)\\n return syn.getWikiHeaders(newOwn)\",\n \"def create_copy(request, pk):\\n report = get_object_or_404(Report, pk=pk)\\n new_report = duplicate(report, changes=(\\n ('name', '{0} (copy)'.format(report.name)),\\n ('user_created', request.user),\\n ('user_modified', request.user),\\n ))\\n # duplicate does not get related\\n for display in report.displayfield_set.all():\\n new_display = copy.copy(display)\\n new_display.pk = None\\n new_display.report = new_report\\n new_display.save()\\n for report_filter in report.filterfield_set.all():\\n new_filter = copy.copy(report_filter)\\n new_filter.pk = None\\n new_filter.report = new_report\\n new_filter.save()\\n return redirect(new_report)\",\n \"def has_move_page_permission(self, request):\\n return self.has_generic_permission(request, \\\"move_page\\\")\",\n \"def test_copy_plugins(self):\\n # create some objects\\n page_en = create_page(\\\"CopyPluginTestPage (EN)\\\", \\\"nav_playground.html\\\", \\\"en\\\")\\n page_de = create_page(\\\"CopyPluginTestPage (DE)\\\", \\\"nav_playground.html\\\", \\\"de\\\")\\n ph_en = page_en.placeholders.get(slot=\\\"body\\\")\\n ph_de = page_de.placeholders.get(slot=\\\"body\\\")\\n \\n # add the text plugin\\n text_plugin_en = add_plugin(ph_en, \\\"TextPlugin\\\", \\\"en\\\", body=\\\"Hello World\\\")\\n self.assertEquals(text_plugin_en.pk, CMSPlugin.objects.all()[0].pk)\\n \\n # add a *nested* link plugin\\n link_plugin_en = add_plugin(ph_en, \\\"LinkPlugin\\\", \\\"en\\\", target=text_plugin_en,\\n name=\\\"A Link\\\", url=\\\"https://www.django-cms.org\\\")\\n \\n # the call above to add a child makes a plugin reload required here.\\n text_plugin_en = self.reload(text_plugin_en)\\n \\n # check the relations\\n self.assertEquals(text_plugin_en.get_children().count(), 1)\\n self.assertEqual(link_plugin_en.parent.pk, text_plugin_en.pk)\\n \\n # just sanity check that so far everything went well\\n self.assertEqual(CMSPlugin.objects.count(), 2)\\n \\n # copy the plugins to the german placeholder\\n copy_plugins_to(ph_en.cmsplugin_set.all(), ph_de, 'de')\\n \\n self.assertEqual(ph_de.cmsplugin_set.filter(parent=None).count(), 1)\\n text_plugin_de = ph_de.cmsplugin_set.get(parent=None).get_plugin_instance()[0]\\n self.assertEqual(text_plugin_de.get_children().count(), 1)\\n link_plugin_de = text_plugin_de.get_children().get().get_plugin_instance()[0]\\n \\n \\n # check we have twice as many plugins as before\\n self.assertEqual(CMSPlugin.objects.count(), 4)\\n \\n # check language plugins\\n self.assertEqual(CMSPlugin.objects.filter(language='de').count(), 2)\\n self.assertEqual(CMSPlugin.objects.filter(language='en').count(), 2)\\n \\n \\n text_plugin_en = self.reload(text_plugin_en)\\n link_plugin_en = self.reload(link_plugin_en)\\n \\n # check the relations in english didn't change\\n self.assertEquals(text_plugin_en.get_children().count(), 1)\\n self.assertEqual(link_plugin_en.parent.pk, text_plugin_en.pk)\\n \\n self.assertEqual(link_plugin_de.name, link_plugin_en.name)\\n self.assertEqual(link_plugin_de.url, link_plugin_en.url)\\n \\n self.assertEqual(text_plugin_de.body, text_plugin_en.body)\",\n \"def _add_page_to_storage(page: Page):\\n if page:\\n if page.valid_mime:\\n CrawlerStorageManager.create_file_from_page(page)\\n page.save_to_json_file()\",\n \"def editPage(self, page):\\n return Page.create(self.pm_getSpaceManager().editPage(page.toDict()), self._modelDataManager)\",\n \"def test_config_step_copy(self):\\n\\n install_step = self.ConfigStep.create({\\n 'name': 'install_step',\\n 'job_type': 'install_odoo'\\n })\\n\\n run_step = self.ConfigStep.create({\\n 'name': 'run_step',\\n 'job_type': 'run_odoo',\\n })\\n\\n create_step = self.ConfigStep.create({\\n 'name': 'test_step',\\n 'job_type': 'create_build',\\n })\\n\\n config = self.Config.create({'name': 'test_config'})\\n StepOrder = self.env['runbot.build.config.step.order']\\n # Creation order is impoortant to reproduce the Odoo copy bug/feature :-)\\n StepOrder.create({'sequence': 15, 'step_id': run_step.id, 'config_id': config.id})\\n StepOrder.create({'sequence': 10, 'step_id': create_step.id, 'config_id': config.id})\\n StepOrder.create({'sequence': 12, 'step_id': install_step.id, 'config_id': config.id})\\n\\n dup_config = config.copy()\\n self.assertEqual(dup_config.step_order_ids.mapped('step_id'), config.step_order_ids.mapped('step_id'))\",\n \"def update_pagesToCrawl(self, page):\\n # check if the page from which we got URLs pass the pageFilter\\n pass_filter = False\\n for p in self.pageFilter:\\n if p in page.url:\\n pass_filter = True\\n\\n if pass_filter:\\n for url in page.urls:\\n # update the set if url not already crawled\\n if url not in self.pagesCrawled:\\n self.pagesToCrawl.add(url)\\n\\n # update pagesToCrawl_dict\\n if url in self.pagesToCrawl_dict:\\n self.pagesToCrawl_dict[url].append(page.url)\\n else:\\n self.pagesToCrawl_dict[url] = [page.url]\",\n \"def copy(self, src, dest):\\n\\n src = os.path.join(os.path.dirname(__file__), \\\"collections\\\", \\\"kitchensink\\\", src)\\n dest = os.path.join(self.checkout, dest)\\n if os.path.isdir(src):\\n shutil.copytree(src, dest)\\n else:\\n shutil.copy(src, dest)\\n return dest\",\n \"def _copyRecursive(\\n syn, entity, destinationId, mapping=None, skipCopyAnnotations=False, **kwargs\\n):\\n\\n version = kwargs.get(\\\"version\\\", None)\\n setProvenance = kwargs.get(\\\"setProvenance\\\", \\\"traceback\\\")\\n excludeTypes = kwargs.get(\\\"excludeTypes\\\", [])\\n updateExisting = kwargs.get(\\\"updateExisting\\\", False)\\n if mapping is None:\\n mapping = dict()\\n # Check that passed in excludeTypes is file, table, and link\\n if not isinstance(excludeTypes, list):\\n raise ValueError(\\\"Excluded types must be a list\\\")\\n elif not all([i in [\\\"file\\\", \\\"link\\\", \\\"table\\\"] for i in excludeTypes]):\\n raise ValueError(\\n \\\"Excluded types can only be a list of these values: file, table, and link\\\"\\n )\\n\\n ent = syn.get(entity, downloadFile=False)\\n if ent.id == destinationId:\\n raise ValueError(\\\"destinationId cannot be the same as entity id\\\")\\n\\n if (isinstance(ent, Project) or isinstance(ent, Folder)) and version is not None:\\n raise ValueError(\\\"Cannot specify version when copying a project of folder\\\")\\n\\n if not isinstance(ent, (Project, Folder, File, Link, Schema, Entity)):\\n raise ValueError(\\\"Not able to copy this type of file\\\")\\n\\n permissions = syn.restGET(\\\"/entity/{}/permissions\\\".format(ent.id))\\n # Don't copy entities without DOWNLOAD permissions\\n if not permissions[\\\"canDownload\\\"]:\\n syn.logger.warning(\\n \\\"%s not copied - this file lacks download permission\\\" % ent.id\\n )\\n return mapping\\n\\n access_requirements = syn.restGET(\\\"/entity/{}/accessRequirement\\\".format(ent.id))\\n # If there are any access requirements, don't copy files\\n if access_requirements[\\\"results\\\"]:\\n syn.logger.warning(\\n \\\"{} not copied - this file has access restrictions\\\".format(ent.id)\\n )\\n return mapping\\n copiedId = None\\n\\n if isinstance(ent, Project):\\n if not isinstance(syn.get(destinationId), Project):\\n raise ValueError(\\n \\\"You must give a destinationId of a new project to copy projects\\\"\\n )\\n copiedId = destinationId\\n # Projects include Docker repos, and Docker repos cannot be copied\\n # with the Synapse rest API. Entity views currently also aren't\\n # supported\\n entities = syn.getChildren(\\n entity, includeTypes=[\\\"folder\\\", \\\"file\\\", \\\"table\\\", \\\"link\\\"]\\n )\\n for i in entities:\\n mapping = _copyRecursive(\\n syn,\\n i[\\\"id\\\"],\\n destinationId,\\n mapping=mapping,\\n skipCopyAnnotations=skipCopyAnnotations,\\n **kwargs,\\n )\\n elif isinstance(ent, Folder):\\n copiedId = _copyFolder(\\n syn,\\n ent.id,\\n destinationId,\\n mapping=mapping,\\n skipCopyAnnotations=skipCopyAnnotations,\\n **kwargs,\\n )\\n elif isinstance(ent, File) and \\\"file\\\" not in excludeTypes:\\n copiedId = _copyFile(\\n syn,\\n ent.id,\\n destinationId,\\n version=version,\\n updateExisting=updateExisting,\\n setProvenance=setProvenance,\\n skipCopyAnnotations=skipCopyAnnotations,\\n )\\n elif isinstance(ent, Link) and \\\"link\\\" not in excludeTypes:\\n copiedId = _copyLink(syn, ent.id, destinationId, updateExisting=updateExisting)\\n elif isinstance(ent, Schema) and \\\"table\\\" not in excludeTypes:\\n copiedId = _copyTable(syn, ent.id, destinationId, updateExisting=updateExisting)\\n # This is currently done because copyLink returns None sometimes\\n if copiedId is not None:\\n mapping[ent.id] = copiedId\\n syn.logger.info(\\\"Copied %s to %s\\\" % (ent.id, copiedId))\\n else:\\n syn.logger.info(\\\"%s not copied\\\" % ent.id)\\n return mapping\",\n \"def copy_tree(t):\\n return tree(label(t), [copy_tree(b) for b in branches(t)])\",\n \"def copy_subtree(src, dst):\\n for src_f in os.listdir(src):\\n src_path = os.path.join(src, src_f)\\n if os.path.isdir(src_path):\\n dst_path = os.path.join(dst, src_f)\\n if not os.path.exists(dst_path):\\n shutil.copytree(src_path, dst_path)\\n else:\\n ProcessJson.copy_subtree(src_path, dst_path)\\n elif os.path.isfile(src_path):\\n dst_path = os.path.join(dst, src_f)\\n if not os.path.exists(dst_path):\\n shutil.copy(src_path, dst_path)\",\n \"def copy(self):\\n copy = Node(self.node_data, self.tree_type, self.parent)\\n if self.children:\\n copy.children = [c.copy() for c in self.children]\\n for c in copy.children:\\n c.parent = copy\\n return copy\",\n \"def create_page_from_import(request, parent_page, page_class, parsed_doc):\\n\\n page = page_class.create_from_import(parsed_doc, request.user)\\n\\n edit_handler = page_class.get_edit_handler()\\n edit_handler = edit_handler.bind_to(request=request, instance=page)\\n form_class = edit_handler.get_form_class()\\n\\n next_url = get_valid_next_url_from_request(request)\\n\\n form = form_class(instance=page, parent_page=parent_page)\\n has_unsaved_changes = False\\n\\n edit_handler = edit_handler.bind_to(form=form)\\n\\n return render(\\n request,\\n \\\"wagtailadmin/pages/create.html\\\",\\n {\\n \\\"content_type\\\": page.content_type,\\n \\\"page_class\\\": page_class,\\n \\\"parent_page\\\": parent_page,\\n \\\"edit_handler\\\": edit_handler,\\n \\\"action_menu\\\": PageActionMenu(\\n request, view=\\\"create\\\", parent_page=parent_page\\n ),\\n \\\"preview_modes\\\": page.preview_modes,\\n \\\"form\\\": form,\\n \\\"next\\\": next_url,\\n \\\"has_unsaved_changes\\\": has_unsaved_changes,\\n },\\n )\",\n \"def copy(self):\\n pass\",\n \"def copy(self):\\n pass\",\n \"def copy(self):\\n pass\",\n \"def clone(context, request):\\n if request.has_permission('create'):\\n return {\\n 'name': 'clone',\\n 'title': 'Clone',\\n 'profile': '/profiles/{ti.name}.json'.format(ti=context.type_info),\\n 'href': '{item_uri}#!clone'.format(item_uri=request.resource_path(context)),\\n }\",\n \"def post_save_page(instance, raw, created, **kwargs):\\n old_page = instance.old_page\\n del(instance.old_page)\\n \\n if settings.CMS_MODERATOR:\\n # tell moderator something was happen with this page\\n from cms.utils.moderator import page_changed\\n page_changed(instance, old_page)\",\n \"def pre_save_page(instance, raw, **kwargs):\\n instance.old_page = None\\n try:\\n instance.old_page = Page.objects.get(pk=instance.pk)\\n except ObjectDoesNotExist:\\n pass\",\n \"def ress_move_on_page(self, content=None):\\n outside_ress = self.outside_ress\\n content = content or self.content\\n\\n for blo in outside_ress:\\n\\n mch = re.search(r'(\\\\s|\\\\t)-block %s'%blo, content) # blo = links, onload etc\\n\\n if not mch:\\n\\n warn(blo+' block is undefined in root template %s'%self.origin.__str__()) # raise Exception(blo+' block is undefined in root template %s'%origin.__str__())\\n\\n super_block = r'\\\\t\\\\t={ block.super }\\\\n'\\n content = re.sub(\\n r'(-extends \\\"[\\\\w\\\\.]+\\\")\\\"', r'\\\\1\\\\n\\\\t-block %s%s%s'%(\\n blo, super_block, __indent_block(r'\\\\t\\\\t', outside_ress[blo].value)\\n ),\\n content\\n )\\n\\n else:\\n _blo = self.__indent_block(mch.groups()[0]+' '*4, outside_ress[blo].value)\\n\\n # (\\\\s|\\\\t)-block \\\\w+(([\\\\s:]*={ *block.super *})|) ={ *block.super *} - \\\\2\\n\\n content = re.sub(r'(\\\\s|\\\\t)(-block %s)'%blo, r'\\\\1\\\\2\\\\n'+_blo, content)\\n\\n## _blo = _indent_block(mch.groups()[0]+' '*8, blo)\\n## _blo = '\\\\n\\\\1 :javascript\\\\n' + _blo\\n\\n return content\",\n \"def test_copy_textplugin(self):\\n page = create_page(\\\"page\\\", \\\"nav_playground.html\\\", \\\"en\\\")\\n \\n placeholder = page.placeholders.get(slot='body')\\n\\n plugin_base = CMSPlugin(\\n plugin_type='TextPlugin',\\n placeholder=placeholder,\\n position=1,\\n language=self.FIRST_LANG)\\n plugin_base.insert_at(None, position='last-child', save=False)\\n\\n plugin = Text(body='')\\n plugin_base.set_base_attr(plugin)\\n plugin.save()\\n\\n plugin_ref_1_base = CMSPlugin(\\n plugin_type='TextPlugin',\\n placeholder=placeholder,\\n position=1,\\n language=self.FIRST_LANG)\\n plugin_ref_1_base.insert_at(plugin_base, position='last-child', save=False)\\n\\n plugin_ref_1 = Text(body='')\\n plugin_ref_1_base.set_base_attr(plugin_ref_1)\\n plugin_ref_1.save()\\n\\n plugin_ref_2_base = CMSPlugin(\\n plugin_type='TextPlugin',\\n placeholder=placeholder,\\n position=2,\\n language=self.FIRST_LANG)\\n plugin_ref_2_base.insert_at(plugin_base, position='last-child', save=False)\\n\\n plugin_ref_2 = Text(body='')\\n plugin_ref_2_base.set_base_attr(plugin_ref_2)\\n\\n plugin_ref_2.save()\\n\\n plugin.body = plugin_tags_to_admin_html(' {{ plugin_object %s }} {{ plugin_object %s }} ' % (str(plugin_ref_1.pk), str(plugin_ref_2.pk)))\\n plugin.save()\\n self.assertEquals(plugin.pk, 1)\\n page_data = self.get_new_page_data()\\n\\n #create 2nd language page\\n page_data.update({\\n 'language': self.SECOND_LANG,\\n 'title': \\\"%s %s\\\" % (page.get_title(), self.SECOND_LANG),\\n })\\n response = self.client.post(URL_CMS_PAGE_CHANGE % page.pk + \\\"?language=%s\\\" % self.SECOND_LANG, page_data)\\n self.assertRedirects(response, URL_CMS_PAGE)\\n\\n self.assertEquals(CMSPlugin.objects.filter(language=self.FIRST_LANG).count(), 3)\\n self.assertEquals(CMSPlugin.objects.filter(language=self.SECOND_LANG).count(), 0)\\n self.assertEquals(CMSPlugin.objects.count(), 3)\\n self.assertEquals(Page.objects.all().count(), 1)\\n\\n copy_data = {\\n 'placeholder': placeholder.pk,\\n 'language': self.SECOND_LANG,\\n 'copy_from': self.FIRST_LANG,\\n }\\n response = self.client.post(URL_CMS_PAGE + \\\"copy-plugins/\\\", copy_data)\\n self.assertEquals(response.status_code, 200)\\n self.assertEqual(response.content.count('<li '), 3)\\n # assert copy success\\n self.assertEquals(CMSPlugin.objects.filter(language=self.FIRST_LANG).count(), 3)\\n self.assertEquals(CMSPlugin.objects.filter(language=self.SECOND_LANG).count(), 3)\\n self.assertEquals(CMSPlugin.objects.count(), 6)\\n\\n new_plugin = Text.objects.get(pk=6)\\n self.assertEquals(plugin_tags_to_id_list(new_plugin.body), [u'4', u'5'])\",\n \"def _copy_margin(\\n self,\\n margin_content: UIContent,\\n new_screen: Screen,\\n write_position: WritePosition,\\n move_x: int,\\n width: int,\\n ) -> None:\\n xpos = write_position.xpos + move_x\\n ypos = write_position.ypos\\n\\n margin_write_position = WritePosition(xpos, ypos, width, write_position.height)\\n self._copy_body(margin_content, new_screen, margin_write_position, 0, width)\",\n \"def offline_copy(_export_path):\\n global export_path\\n export_path = _export_path\\n \\n # First, monkey patch the original config\\n main.NBCONFIG.protectect_dirs = []\\n main.NBCONFIG.protected_users = {}\\n main.NBCONFIG.edit_users = {}\\n \\n # Now monkey patch NBweb\\n main.REQUIRELOGIN = False\\n\\n pages = []\\n\\n # Copy and work all source files \\n for dirpath,dirnames,filenames in os.walk(NBCONFIG.source):\\n for dirname in dirnames[:]: # Iterate a copy since we will delete in place\\n if any(dirname.startswith(i) for i in ['.']):\\n dirnames.remove(dirname) # So we do not parse it later\\n continue\\n if dirname == '_scratch':\\n dirnames.remove(dirname) # So we do not parse it later\\n continue\\n \\n # Names\\n src_systemname = os.path.join(dirpath,dirname)\\n rootname = os.path.relpath(src_systemname,NBCONFIG.source) # No leading / though\\n dest_systemname = os.path.join(export_path,rootname)\\n \\n mkdir(rootname,isfile=False) # Will make the dir no matter what\\n \\n # Index\\n dest = os.path.join(export_path,rootname, 'index.html')\\n \\n # Exclusions.\\n if main.exclusion_check(utils.join('/',rootname +'/')):\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write('')\\n continue\\n \\n try:\\n html = main.main_route('/' + rootname + '/')\\n except HTTPError:\\n # Likely some additional resource in _NBweb\\n try:\\n os.rmdir(dest_systemname) # Should be empty\\n except OSError:\\n pass\\n os.symlink(src_systemname,dest_systemname)\\n continue\\n \\n \\n html = process_page(html,dest)\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(html)\\n \\n # _all\\n dest = os.path.join(export_path,'_all',rootname, 'index.html')\\n mkdir(dest,isfile=True,isfull=True)\\n \\n html = main.allpage('/'+ rootname +'/')\\n html = process_page(html,dest)\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(html)\\n \\n \\n # Loop each file\\n for filename in filenames:\\n if os.path.splitext(filename)[0] == 'index':\\n continue # Already made above\\n \\n # Names\\n src_systemname = os.path.join(dirpath,filename)\\n rootname = os.path.relpath(src_systemname,NBCONFIG.source) # No leading / though\\n dest_systemname = os.path.join(export_path,rootname)\\n \\n mkdir(rootname,isfile=True) # Will make the dir no matter what\\n try:\\n os.symlink(src_systemname,dest_systemname) \\n except OSError:\\n os.remove(dest_systemname)\\n os.symlink(src_systemname,dest_systemname)\\n \\n rootbasename,ext = os.path.splitext(rootname)\\n if ext in NBCONFIG.extensions:\\n dest = os.path.join(export_path,rootbasename + '.html')\\n try:\\n html = main.main_route(rootbasename + '.html')\\n except:\\n print('Issue with: {}'.format(rootname))\\n \\n html = process_page(html,dest)\\n \\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(html)\\n pages.append(rootbasename)\\n\\n ## Index pages\\n # Home page w/o blog\\n dest_systemname = os.path.join(export_path,'')\\n dest = os.path.join(export_path,'index.html')\\n \\n html0 = main.main_route('/',map_view=True)\\n \\n html = process_page(html0,dest)\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(html)\\n\\n # Also write the sitemap\\n dest = os.path.join(export_path,'_sitemap/index.html')\\n mkdir('/_sitemap',isfile=False)\\n html = process_page(html0,dest)\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(html)\\n \\n # _all\\n dest = os.path.join(export_path,'_all','index.html')\\n \\n html = main.allpage('/')\\n html = process_page(html,dest)\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(html)\\n \\n ## Blog Pages\\n if len(NBCONFIG.blog_dirs) > 0:\\n blog_num = 0\\n while True:\\n dest = os.path.join(export_path,'_blog',unicode(blog_num),'index.html')\\n \\n try:\\n html = main.main_route('/',map_view=False,blog_num=blog_num)\\n except HTTPError:\\n break # At the last one\\n \\n mkdir(dest,isfile=True,isfull=True) \\n \\n html = process_page(html,dest)\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(html)\\n blog_num += 1\\n # Make the home page. \\n dest = os.path.join(export_path,'index.html')\\n html = main.main_route('/',map_view=False,blog_num=0)\\n html = process_page(html,dest)\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(html)\\n \\n ## Special Pages\\n make_random_forward(pages)\\n \\n # Tags\\n dest = os.path.join(export_path,'_tags/index.html')\\n mkdir(dest,isfile=True,isfull=True) \\n html = main.return_tags()\\n html = process_page(html,dest)\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(html)\\n \\n # ToDos\\n dest = os.path.join(export_path,'_todo/index.html')\\n mkdir(dest,isfile=True,isfull=True) \\n html = main.return_todo()\\n html = process_page(html,dest)\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(html)\\n \\n txt = main.return_todo_txt()\\n dest = os.path.join(export_path,'_todo/todo.txt')\\n with open(dest,'w',encoding='utf8') as FF:\\n FF.write(txt)\\n \\n # Galleries\\n cpsym( utils.join(NBCONFIG.scratch_path,'_galleries'),utils.join(export_path,'_galleries'))\\n \\n ## Clean up\\n for F in [utils.join(export_path,'_NBweb',a) for a in ['NBCONFIG.py','NBCONFIG.pyc','template.html']]:\\n try:\\n os.remove(F)\\n except:\\n pass\\n \\n # Make sure there are never any directory listings\\n for dirpath,dirnames,filenames in os.walk(export_path):\\n if 'index.html' not in filenames:\\n with open(utils.join(dirpath,'index.html'),'w',encoding='utf8') as F:\\n F.write('')\",\n \"def copy_skel(src, dest):\\n md_common.copytree(src, dest)\",\n \"def copy(self):\\n # YOUR CODE HERE\\n raise NotImplementedError()\",\n \"def prepare_wiki_page(self, req, page, fields):\\r\\n pass\",\n \"def _copy_from_template(\\n self, source_structures, source_keys, dest_structure, new_parent_block_key, user_id, head_validation\\n ):\\n new_blocks = set()\\n\\n new_children = list() # ordered list of the new children of new_parent_block_key\\n\\n for usage_key in source_keys:\\n src_course_key = usage_key.course_key\\n hashable_source_id = src_course_key.for_version(None)\\n block_key = BlockKey(usage_key.block_type, usage_key.block_id)\\n source_structure = source_structures[src_course_key]\\n\\n if block_key not in source_structure['blocks']:\\n raise ItemNotFoundError(usage_key)\\n source_block_info = source_structure['blocks'][block_key]\\n\\n # Compute a new block ID. This new block ID must be consistent when this\\n # method is called with the same (source_key, dest_structure) pair\\n unique_data = \\\"{}:{}:{}\\\".format(\\n str(hashable_source_id).encode(\\\"utf-8\\\"),\\n block_key.id,\\n new_parent_block_key.id,\\n )\\n new_block_id = hashlib.sha1(unique_data.encode('utf-8')).hexdigest()[:20]\\n new_block_key = BlockKey(block_key.type, new_block_id)\\n\\n # Now clone block_key to new_block_key:\\n new_block_info = copy.deepcopy(source_block_info)\\n # Note that new_block_info now points to the same definition ID entry as source_block_info did\\n existing_block_info = dest_structure['blocks'].get(new_block_key, BlockData())\\n # Inherit the Scope.settings values from 'fields' to 'defaults'\\n new_block_info.defaults = new_block_info.fields\\n\\n # <workaround>\\n # CAPA modules store their 'markdown' value (an alternate representation of their content)\\n # in Scope.settings rather than Scope.content :-/\\n # markdown is a field that really should not be overridable - it fundamentally changes the content.\\n # capa modules also use a custom editor that always saves their markdown field to the metadata,\\n # even if it hasn't changed, which breaks our override system.\\n # So until capa modules are fixed, we special-case them and remove their markdown fields,\\n # forcing the inherited version to use XML only.\\n if usage_key.block_type == 'problem' and 'markdown' in new_block_info.defaults:\\n del new_block_info.defaults['markdown']\\n # </workaround>\\n\\n # Preserve any existing overrides\\n new_block_info.fields = existing_block_info.fields\\n\\n if 'children' in new_block_info.defaults:\\n del new_block_info.defaults['children'] # Will be set later\\n\\n new_block_info.edit_info = existing_block_info.edit_info\\n new_block_info.edit_info.previous_version = new_block_info.edit_info.update_version\\n new_block_info.edit_info.update_version = dest_structure['_id']\\n # Note we do not set 'source_version' - it's only used for copying identical blocks\\n # from draft to published as part of publishing workflow.\\n # Setting it to the source_block_info structure version here breaks split_draft's has_changes() method.\\n new_block_info.edit_info.edited_by = user_id\\n new_block_info.edit_info.edited_on = datetime.datetime.now(UTC)\\n new_block_info.edit_info.original_usage = str(usage_key.replace(branch=None, version_guid=None))\\n new_block_info.edit_info.original_usage_version = source_block_info.edit_info.update_version\\n dest_structure['blocks'][new_block_key] = new_block_info\\n\\n children = source_block_info.fields.get('children')\\n if children:\\n children = [src_course_key.make_usage_key(child.type, child.id) for child in children]\\n new_blocks |= self._copy_from_template(\\n source_structures, children, dest_structure, new_block_key, user_id, head_validation\\n )\\n\\n new_blocks.add(new_block_key)\\n # And add new_block_key to the list of new_parent_block_key's new children:\\n new_children.append(new_block_key)\\n\\n # Update the children of new_parent_block_key\\n dest_structure['blocks'][new_parent_block_key].fields['children'] = new_children\\n\\n return new_blocks\",\n \"def publish(self, fields=None, exclude=None):\\n # clean moderation log\\n self.pagemoderatorstate_set.all().delete()\\n \\n # can be this page published?\\n if self.mptt_can_publish():\\n self.moderator_state = Page.MODERATOR_APPROVED\\n else:\\n self.moderator_state = Page.MODERATOR_APPROVED_WAITING_FOR_PARENTS\\n \\n self.save(change_state=False)\\n \\n if not fields:\\n public = self.public\\n if public:\\n if public.tree_id != self.tree_id: #moved over trees\\n tree_ids = [self.tree_id, public.tree_id]\\n else:\\n tree_ids = [self.tree_id]\\n \\n dirty = False\\n if self.lft != public.lft or self.rght != public.rght or self.level != public.level:#moved in tree\\n dirty = True\\n if dirty or len(tree_ids) == 2:\\n pages = list(Page.objects.filter(tree_id__in=tree_ids).order_by(\\\"tree_id\\\", \\\"level\\\", \\\"lft\\\"))\\n fields = []\\n names = [\\\"lft\\\",\\\"rght\\\",\\\"tree_id\\\", \\\"level\\\", \\\"parent\\\", \\\"created_by\\\", \\\"changed_by\\\", \\\"site\\\"]\\n for field in self._meta.fields:\\n if field.name in names:\\n fields.append(field)\\n ids = []\\n for page in pages:\\n if page.pk != self.pk:\\n page.publish(fields=fields)\\n ids.append(page.pk)\\n titles = Title.objects.filter(page__in=ids)\\n title_fields = []\\n names = [\\\"path\\\"]\\n for field in Title._meta.fields:\\n if field.name in names:\\n title_fields.append(field)\\n for title in titles:\\n title.publish(fields=title_fields)\\n else:\\n pass\\n #print \\\"no public found\\\" \\n \\n # publish, but only if all parents are published!! - this will need a flag\\n try:\\n published = super(Page, self).publish(fields, exclude)\\n except MpttCantPublish:\\n return \\n \\n # page was published, check if there are some childs, which are waiting\\n # for publishing (because of the parent)\\n publish_set = self.children.filter(moderator_state = Page.MODERATOR_APPROVED_WAITING_FOR_PARENTS)\\n for page in publish_set:\\n # recursive call to all childrens....\\n page.moderator_state = Page.MODERATOR_APPROVED\\n page.save(change_state=False)\\n page.publish()\\n \\n # fire signal after publishing is done\\n return published\",\n \"def copytree(self, name, source, dest, symlinks=False):\\n self.m.path.assert_absolute(source)\\n self.m.path.assert_absolute(dest)\\n args = ['--symlinks'] if symlinks else []\\n self._run(name, ['copytree'] + args + [source, dest])\\n self.m.path.mock_copy_paths(source, dest)\",\n \"def copy_one(self, src, dest):\\n if self.manager.no_sourcemaps and self.is_ignored_sourcemap(src.name):\\n return\\n\\n if dest.is_dir():\\n shutil.rmtree(dest)\\n elif dest.exists():\\n dest.unlink()\\n\\n if not dest.parent.exists():\\n self.log.debug(f\\\"creating folder {dest.parent}\\\")\\n dest.parent.mkdir(parents=True)\\n\\n self.maybe_timestamp(dest.parent)\\n\\n copytree_kwargs = {}\\n\\n if self.manager.no_sourcemaps:\\n copytree_kwargs[\\\"ignore\\\"] = SOURCEMAP_IGNORE_PATTERNS\\n\\n if src.is_dir():\\n shutil.copytree(src, dest, **copytree_kwargs)\\n else:\\n shutil.copy2(src, dest)\\n\\n self.maybe_timestamp(dest)\",\n \"def test_copy_details(self):\\n self.tc_id = \\\"Ts_002\\\"\\n self.tc_desc = \\\"Verify the user is able to copy the location type details\\\"\\n self.tc_step = \\\"TC Start\\\"\\n\\n registration = RegistrationPage(self.driver)\\n\\n self.tc_step = \\\"Launch the url\\\"\\n registration.launchUrl(self.url)\\n\\n self.tc_step = \\\"Enter the basic registration details\\\"\\n registration.clickVendorLogin()\\n registration.clickRegisterButton()\\n registration.enterBasicRegistrationDetails(self.firstname, self.lastname, self.vendorname, self.fnsnumber,\\n self.primaryemail, self.primaryphno, self.psw, self.cpsw,\\n self.continfo)\\n registration.basicRegButton()\\n self.tc_step = \\\"Enter the public registration details\\\"\\n registration.enterPublicRegistrationDetails(self.publicemail, self.publicphno, self.publicwebsite,\\n self.businessdesc, self.products)\\n registration.publicRegButton()\\n self.tc_step = \\\"Enter the location details\\\"\\n registration.clickCSAButton()\\n registration.clickLocationYesButton()\\n registration.csalocationTypeDetails(self.pickupsitename, self.adrs1, self.adrs2, self.zipcode, self.spzl_instruction)\\n registration.chooseCity()\\n registration.csacopy()\\n registration.addmore()\\n registration.remove()\\n registration.confirmremove()\\n registration.saveonlyCsa()\\n self.assertEqual(registration.verifyRegistration(),\\\"Healthy Incentives Program (HIP)\\\",\\\"Login Success\\\")\",\n \"def copy(self, new_tree):\\n new_node = new_tree.new_tree_node(parent=self.parent, node_id=self.id)\\n new_node.name = self.name\\n new_node.branch = self.branch\\n new_node.support = self.support\\n new_node.support_type = self.support_type\\n new_node.comment = self.comment\\n new_node.children = self.children[::]\\n new_node._been_processed = self._been_processed\\n return new_node\",\n \"def copy(self):\\n new_tree = Tree(support_label=self._support_label, remove_name_quotes=self._remove_name_quotes)\\n new_tree.name = self.name\\n new_tree._is_cladogram = self._is_cladogram\\n new_tree._cladogram_branch = self._cladogram_branch\\n new_tree._node_id_template = self._node_id_template\\n new_tree._node_ids = self._node_ids.copy()\\n new_tree._node_id_index = self._node_id_index\\n new_tree.root = self.root.copy(new_tree)\\n self.copy_nodes(self.root, new_tree.root, new_tree)\\n new_tree.process_tree_nodes()\\n return new_tree\",\n \"def _copy_published_modules_to_course(self, new_course, old_course_loc, course_key, user):\\r\\n course_version_locator = new_course.id\\r\\n\\r\\n # iterate over published course elements. Wildcarding rather than descending b/c some elements are orphaned (e.g.,\\r\\n # course about pages, conditionals)\\r\\n for module in self.direct_modulestore.get_items(course_key):\\r\\n # don't copy the course again. No drafts should get here but check\\r\\n if module.location != old_course_loc and not getattr(module, 'is_draft', False):\\r\\n # create split_xblock using split.create_item\\r\\n # where block_id is computed by translate_location_to_locator\\r\\n new_locator = self.loc_mapper.translate_location(\\r\\n module.location, True, add_entry_if_missing=True\\r\\n )\\r\\n # NOTE: the below auto populates the children when it migrates the parent; so,\\r\\n # it doesn't need the parent as the first arg. That is, it translates and populates\\r\\n # the 'children' field as it goes.\\r\\n _new_module = self.split_modulestore.create_item(\\r\\n course_version_locator, module.category, user.id,\\r\\n block_id=new_locator.block_id,\\r\\n fields=self._get_json_fields_translate_references(module, course_key, True),\\r\\n continue_version=True\\r\\n )\\r\\n # after done w/ published items, add version for 'draft' pointing to the published structure\\r\\n index_info = self.split_modulestore.get_course_index_info(course_version_locator)\\r\\n versions = index_info['versions']\\r\\n versions['draft'] = versions['published']\\r\\n self.split_modulestore.update_course_index(index_info)\\r\\n\\r\\n # clean up orphans in published version: in old mongo, parents pointed to the union of their published and draft\\r\\n # children which meant some pointers were to non-existent locations in 'direct'\\r\\n self.split_modulestore.internal_clean_children(course_version_locator)\",\n \"def copy(self,item,destName,destDir=None):\\n if item == self.lastKey: return\\n destDir = destDir or self.dir\\n apath = self.dir.join(item)\\n apath.copyTo(destDir.join(destName))\\n if destDir == self.dir:\\n self.data[destName] = installer = copy.copy(self.data[item])\\n installer.isActive = False\\n self.refreshOrder()\\n self.moveArchives([destName],self.data[item].order+1)\",\n \"def copy_elements(self):\\n self.tmp_hook_dir = tempfile.mkdtemp()\\n for element in self.elements:\\n element_dir = self.loaded_elements[element].directory\\n dir_util.copy_tree(element_dir, self.tmp_hook_dir)\\n try:\\n os.unlink('/tmp/in_target.d')\\n except:\\n pass\\n os.symlink(self.tmp_hook_dir, '/tmp/in_target.d')\\n\\n # elements expect this environment variable to be set\\n os.environ['TMP_HOOKS_PATH'] = self.tmp_hook_dir\\n tmp_path = '%s/bin' % self.tmp_hook_dir\\n if 'PATH' in os.environ:\\n tmp_path = os.environ[\\\"PATH\\\"] + os.pathsep + tmp_path\\n os.environ[\\\"PATH\\\"] = tmp_path\",\n \"def copyDir(self, src, subpath):\\n dst = self.output_path + \\\"/\\\" + subpath\\n shutil.copytree(src, dst)\",\n \"def copy(self, event):\\n return\",\n \"def copy(self, keep_uid=False, new_parent=None):\\n obj = self.__class__(\\n parent=new_parent or self.parent,\\n data=self.data,\\n id=self.id if keep_uid else str(uuid.uuid1()),\\n )\\n if new_parent or not keep_uid:\\n obj.url = obj.generate_url()\\n else:\\n obj.url = self.url\\n return obj\",\n \"def tree_copy_selection(in_tree, out_tree, selection):\\n for entry in in_tree:\\n if selection(entry):\\n out_tree.Fill()\",\n \"def __copyFiles(self):\\n if os.path.isdir(self.__sourcePath):\\n shutil.copytree(self.__sourcePath, self.__targetPath)\\n else:\\n shutil.copy2(self.__sourcePath, self.__targetPath)\",\n \"def create_page(self):\",\n \"def copy_one(self, src, dest):\\n if dest.is_dir():\\n shutil.rmtree(dest)\\n elif dest.exists():\\n dest.unlink()\\n\\n if not dest.parent.exists():\\n self.log.debug(f\\\"creating folder {dest.parent}\\\")\\n dest.parent.mkdir(parents=True)\\n\\n self.maybe_timestamp(dest.parent)\\n\\n if src.is_dir():\\n shutil.copytree(src, dest)\\n else:\\n shutil.copy2(src, dest)\\n\\n self.maybe_timestamp(dest)\",\n \"def copy(self, to_folder, page_size=1000, chunk_size=100, **copy_kwargs):\\n ids = self._id_only_copy_self()\\n ids.page_size = page_size\\n return self.folder_collection.account.bulk_copy(\\n ids=ids, to_folder=to_folder, chunk_size=chunk_size, **copy_kwargs\\n )\",\n \"def create_page_objects(self, data):\\n for page in data['pages']:\\n self.create_page(page)\",\n \"def copy(self, user_id, source_course, destination_course, subtree_list=None, blacklist=None):\\n # get the destination's index, and source and destination structures.\\n with self.bulk_operations(source_course):\\n source_structure = self._lookup_course(source_course).structure\\n\\n with self.bulk_operations(destination_course):\\n index_entry = self.get_course_index(destination_course)\\n if index_entry is None:\\n # brand new course\\n raise ItemNotFoundError(destination_course)\\n if destination_course.branch not in index_entry['versions']:\\n # must be copying the dag root if there's no current dag\\n root_block_key = source_structure['root']\\n if not any(root_block_key == BlockKey.from_usage_key(subtree) for subtree in subtree_list):\\n raise ItemNotFoundError(f'Must publish course root {root_block_key}')\\n root_source = source_structure['blocks'][root_block_key]\\n # create branch\\n destination_structure = self._new_structure(\\n user_id, root_block_key,\\n # leave off the fields b/c the children must be filtered\\n definition_id=root_source.definition,\\n )\\n else:\\n destination_structure = self._lookup_course(destination_course).structure\\n destination_structure = self.version_structure(destination_course, destination_structure, user_id)\\n\\n if blacklist != EXCLUDE_ALL:\\n blacklist = [BlockKey.from_usage_key(shunned) for shunned in blacklist or []]\\n # iterate over subtree list filtering out blacklist.\\n orphans = set()\\n destination_blocks = destination_structure['blocks']\\n for subtree_root in subtree_list:\\n if BlockKey.from_usage_key(subtree_root) != source_structure['root']:\\n # find the parents and put root in the right sequence\\n parents = self._get_parents_from_structure(BlockKey.from_usage_key(subtree_root), source_structure)\\n parent_found = False\\n for parent in parents:\\n # If a parent isn't found in the destination_blocks, it's possible it was renamed\\n # in the course export. Continue and only throw an exception if *no* parents are found.\\n if parent in destination_blocks:\\n parent_found = True\\n orphans.update(\\n self._sync_children(\\n source_structure['blocks'][parent],\\n destination_blocks[parent],\\n BlockKey.from_usage_key(subtree_root)\\n )\\n )\\n if len(parents) and not parent_found: # lint-amnesty, pylint: disable=len-as-condition\\n raise ItemNotFoundError(parents)\\n # update/create the subtree and its children in destination (skipping blacklist)\\n orphans.update(\\n self._copy_subdag(\\n user_id, destination_structure['_id'],\\n BlockKey.from_usage_key(subtree_root),\\n source_structure['blocks'],\\n destination_blocks,\\n blacklist\\n )\\n )\\n # remove any remaining orphans\\n for orphan in orphans:\\n # orphans will include moved as well as deleted xblocks. Only delete the deleted ones.\\n self._delete_if_true_orphan(orphan, destination_structure)\\n\\n # update the db\\n self.update_structure(destination_course, destination_structure)\\n self._update_head(destination_course, index_entry, destination_course.branch, destination_structure['_id'])\",\n \"def copyTo(self, newFolder):\\n copyUri = self.metaData.getLink(\\\"copy\\\")\\n\\n if not hasattr(newFolder, \\\"metaData\\\"): raise TypeError(\\\"Your newFolder does not have a metaData property\\\")\\n if not hasattr(newFolder, \\\"selfLink\\\"): raise TypeError(\\\"Your folder object is missing a selfLink\\\")\\n assert copyUri is not None\\n\\n header = self._baseHeader.copy()\\n header['Content-Type'] = \\\"application/vnd.huddle.data+json\\\"\\n body = '{ \\\"targetFolder\\\":{ \\\"link\\\":{ \\\"rel\\\": \\\"self\\\", \\\"href\\\": \\\"' + newFolder.selfLink + '\\\" } } }'\\n response = self._adapter.postRequest(copyUri, header, body)\\n\\n return Folder(self._client, response['Headers']['location'])\",\n \"def copy_with_children(self, new_children):\\n new_box = self.copy()\\n new_box.children = list(new_children)\\n\\n # Clear and reset removed decorations as we don't want to keep the\\n # previous data, for example when a box is split between two pages.\\n self.remove_decoration_sides = set()\\n\\n return new_box\",\n \"def copy_recursively(src, dst, overwrite=False, changed_only=True):\\n if os.path.isdir(src):\\n copytree(src, dst, overwrite, changed_only)\\n else:\\n copyfile(src, dst, overwrite, changed_only)\",\n \"def svn_client_copy5(svn_commit_info_t_commit_info_p, apr_array_header_t_sources, char_dst_path, svn_boolean_t_copy_as_child, svn_boolean_t_make_parents, svn_boolean_t_ignore_externals, apr_hash_t_revprop_table, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\\n pass\",\n \"def test_clone_scenario(self):\\n pass\",\n \"def copy_templates(self, in_dir):\\n self.copy_contents(in_dir, subdir=\\\"templates\\\")\",\n \"def copy(self, source, target, recursive=True):\\n if recursive:\\n command = 'cp -R %s %s'\\n else:\\n command = 'cp %s %s'\\n self.communicate(command % (source, target))\",\n \"def test_after_creation_copy():\\n builder = TreeBuilder()\\n builder.create_root(0)\\n builder.add_child(2, move=True)\\n builder.add_child(13)\\n builder.move_to_parent()\\n builder.add_child(7)\\n\\n t1 = builder.build()\\n\\n builder.move_to_root()\\n builder.set_data(4)\\n builder.add_child(3, move=True)\\n builder.add_child(15)\\n\\n t2 = builder.build()\\n\\n assert t2 is not t1\\n assert t2[0] is not t1[0]\\n assert t2[0][0] is not t1[0][0]\\n assert t2[1] is not t1[1]\\n\\n assert t2.data == 4\\n assert t2[0].data == 2\\n assert t2[0][0].data == 13\\n assert t2[1].data == 7\\n assert t2[2].data == 3\\n assert t2[2][0].data == 15\\n\\n assert len(t2) == 3\\n assert len(t2[0]) == 1\\n assert len(t2[1]) == 0\\n assert len(t2[2]) == 1\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67569137","0.62102824","0.6115456","0.6008251","0.57991344","0.57538474","0.57470375","0.5713914","0.56825674","0.5637052","0.55938256","0.55267644","0.5525658","0.5520369","0.55132717","0.5499208","0.54576015","0.5446981","0.53665066","0.53636324","0.5321026","0.5318288","0.5308671","0.52852565","0.5263091","0.52399856","0.52201885","0.5203947","0.5203075","0.5201322","0.5198105","0.5195509","0.5194574","0.5184954","0.51648813","0.5160063","0.5149524","0.513353","0.51257324","0.5118069","0.51046234","0.5102647","0.509383","0.50891656","0.50808823","0.50804704","0.5060388","0.50534505","0.5050857","0.50324297","0.50168777","0.5009173","0.4999175","0.49970105","0.4996341","0.4996328","0.4993972","0.49903762","0.49824923","0.49698833","0.49698833","0.49698833","0.49623132","0.4960324","0.4957832","0.4954106","0.49535656","0.49534446","0.49499464","0.4939369","0.4939363","0.49340132","0.49324647","0.49228576","0.49148723","0.49122295","0.4907966","0.48958027","0.48858845","0.4885826","0.48804176","0.4876388","0.48732075","0.4872541","0.48656818","0.4865168","0.486477","0.4863353","0.48630607","0.48588172","0.48574248","0.48486587","0.48476887","0.48443145","0.48417786","0.48386034","0.4837945","0.4834117","0.4833921","0.4824145"],"string":"[\n \"0.67569137\",\n \"0.62102824\",\n \"0.6115456\",\n \"0.6008251\",\n \"0.57991344\",\n \"0.57538474\",\n \"0.57470375\",\n \"0.5713914\",\n \"0.56825674\",\n \"0.5637052\",\n \"0.55938256\",\n \"0.55267644\",\n \"0.5525658\",\n \"0.5520369\",\n \"0.55132717\",\n \"0.5499208\",\n \"0.54576015\",\n \"0.5446981\",\n \"0.53665066\",\n \"0.53636324\",\n \"0.5321026\",\n \"0.5318288\",\n \"0.5308671\",\n \"0.52852565\",\n \"0.5263091\",\n \"0.52399856\",\n \"0.52201885\",\n \"0.5203947\",\n \"0.5203075\",\n \"0.5201322\",\n \"0.5198105\",\n \"0.5195509\",\n \"0.5194574\",\n \"0.5184954\",\n \"0.51648813\",\n \"0.5160063\",\n \"0.5149524\",\n \"0.513353\",\n \"0.51257324\",\n \"0.5118069\",\n \"0.51046234\",\n \"0.5102647\",\n \"0.509383\",\n \"0.50891656\",\n \"0.50808823\",\n \"0.50804704\",\n \"0.5060388\",\n \"0.50534505\",\n \"0.5050857\",\n \"0.50324297\",\n \"0.50168777\",\n \"0.5009173\",\n \"0.4999175\",\n \"0.49970105\",\n \"0.4996341\",\n \"0.4996328\",\n \"0.4993972\",\n \"0.49903762\",\n \"0.49824923\",\n \"0.49698833\",\n \"0.49698833\",\n \"0.49698833\",\n \"0.49623132\",\n \"0.4960324\",\n \"0.4957832\",\n \"0.4954106\",\n \"0.49535656\",\n \"0.49534446\",\n \"0.49499464\",\n \"0.4939369\",\n \"0.4939363\",\n \"0.49340132\",\n \"0.49324647\",\n \"0.49228576\",\n \"0.49148723\",\n \"0.49122295\",\n \"0.4907966\",\n \"0.48958027\",\n \"0.48858845\",\n \"0.4885826\",\n \"0.48804176\",\n \"0.4876388\",\n \"0.48732075\",\n \"0.4872541\",\n \"0.48656818\",\n \"0.4865168\",\n \"0.486477\",\n \"0.4863353\",\n \"0.48630607\",\n \"0.48588172\",\n \"0.48574248\",\n \"0.48486587\",\n \"0.48476887\",\n \"0.48443145\",\n \"0.48417786\",\n \"0.48386034\",\n \"0.4837945\",\n \"0.4834117\",\n \"0.4833921\",\n \"0.4824145\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.79622966"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81796,"cells":{"query":{"kind":"string","value":"get the calculated status of the page based on published_date, published_end_date, and status"},"document":{"kind":"string","value":"def get_calculated_status(self):\n if settings.CMS_SHOW_START_DATE:\n if self.publication_date > datetime.now():\n return False\n \n if settings.CMS_SHOW_END_DATE and self.publication_end_date:\n if self.publication_end_date < datetime.now():\n return True\n\n return self.published"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_page_caculated_status(self):\n from pages import settings as pages_settings\n setattr(pages_settings, \"PAGE_SHOW_START_DATE\", True)\n yesterday = datetime.datetime.now() - datetime.timedelta(days=1)\n tomorrow = datetime.datetime.now() + datetime.timedelta(days=1)\n\n page = self.new_page()\n self.assertEqual(page.calculated_status, Page.PUBLISHED)\n page.publication_date = tomorrow\n self.assertEqual(page.calculated_status, Page.DRAFT)\n page.publication_date = yesterday\n self.assertEqual(page.calculated_status, Page.PUBLISHED)\n setattr(pages_settings, \"PAGE_SHOW_END_DATE\", True)\n page.publication_end_date = yesterday\n self.assertEqual(page.calculated_status, Page.EXPIRED)","def publication_status(self):\n content = self.context.get_silva_object()\n status = None\n unapproved_version = content.get_unapproved_version()\n approved_version = content.get_approved_version()\n public_version = content.get_public_version()\n previous_versions = content.get_previous_versions()\n if unapproved_version and unapproved_version == self.context.id:\n status = \"unapproved\"\n elif approved_version and approved_version == self.context.id:\n status = \"approved\"\n elif public_version and public_version == self.context.id:\n status = \"public\"\n else:\n if previous_versions and previous_versions[-1] == self.context.id:\n status = \"last_closed\"\n elif self.context.id in previous_versions:\n status = \"closed\"\n else:\n # this is a completely new version not even registered\n # with the machinery yet\n status = 'unapproved'\n return status","def show_publish_status(self, obj):\n if obj.publish_status > 0:\n return mark_safe(\"<span style=\\\"color: #0c0;\\\"><b>ALWAYS</b></span> Available\")\n elif obj.publish_status < 0:\n return mark_safe(\"<span style=\\\"color: #c00;\\\"><B>NEVER</b></span> Available\")\n else: # it EQUALS zero\n if obj.live_as_of is None:\n return \"Never Published\"\n else:\n dstr = obj.live_as_of.strftime(\"%x\")\n if is_in_the_future(obj.live_as_of):\n return mark_safe(\"<b>Goes LIVE: %s</b>\"% dstr)\n else:\n return mark_safe(\"<B>LIVE</B> <span style=\\\"color: #999;\\\">as of: %s</style>\" % dstr)\n return \"???\"","def gatekeeper_show_publish_status(self, obj):\n if obj.publish_status > 0:\n return mark_safe(\"<span style=\\\"color: #0c0;\\\"><b>ALWAYS</b></span> Available\")\n elif obj.publish_status < 0:\n return mark_safe(\"<span style=\\\"color: #c00;\\\"><B>NEVER</b></span> Available\")\n else: # it EQUALS zero\n if obj.live_as_of is None:\n return \"Never Published\"\n else:\n dstr = obj.live_as_of.strftime(\"%x\")\n if is_in_the_future(obj.live_as_of):\n return mark_safe(\"<b>Goes LIVE: %s</b>\"% dstr)\n else:\n return mark_safe(\"<B>LIVE</B> <span style=\\\"color: #999;\\\">as of: %s</style>\" % dstr)\n return \"???\"","def test_public_status_page_get_public_status_pages(self):\n pass","def get_published(self):\n return self.filter(status=\"P\")","def test_public_status_page_get_public_status_page(self):\n pass","def get_status(self):\r\n if self.read_pages == 0:\r\n self.status = \"unread\"\r\n elif self.read_pages == self.pages:\r\n self.status = \"finished\"\r\n else:\r\n self.status = \"reading\"\r\n return self.status","def getStatus(entry, vType):\n data = db.Database(filename=\"IFB299.db\")\n fine = data.retrieveFine(vType, entry['Citation_Number'])\n if fine['Payment_status'] == \"Pending\":\n date = dt.datetime.strptime(entry['Date'],'%d/%m/%Y')\n overdue = dt.datetime.now().date() - date.date()\n if overdue.days >= 7:\n return \"Overdue\"\n else:\n return \"Pending\"\n else:\n return \"Paid\"","def aggregate_status(request):\n try:\n model = 'item'\n start_date = request.GET.get('startDate', None)\n end_date = request.GET.get('endDate', None)\n\n items = __getQuerysetGivenInterval(model, start_date, end_date)\n\n agg_status = list(items.values('status')\n .annotate(count=Count('status')))\n\n result = {'result': agg_status}\n\n return JsonResponse(result, status=200)\n except BaseException as e:\n print(e.args)\n return HttpResponseBadRequest()","def week_report_handle(fans_type):\n\t#import pdb;pdb.set_trace()\n\tlast_day = datetime.date.today()-timedelta(days=datetime.datetime.today().weekday() + 1)\n\ttoday = datetime.date.today()\n\n\tfans_pages = FansPage.objects.filter(fans_type=fans_type, date__gte=last_day, date__lte=today).order_by(\"date\")\n\n\tstart = fans_pages[0]\n\tlast = fans_pages[len(fans_pages) - 1]\n\n\t#talk_about_is = (last.talk_about_is - start.talk_about_is) / (start.talk_about_is + 0.0) * 100\n\ttalk_about_is = (last.talk_about_is - start.talk_about_is)\n\t#total_like_count = (last.total_like_count - start.total_like_count) / (start.total_like_count + 0.0) * 100\n\ttotal_like_count = (last.total_like_count - start.total_like_count)\n\t#total_fans = (last.total_fans - start.total_fans) / (start.total_fans + 0.0) * 100\n\ttotal_fans = (last.total_fans - start.total_fans)\n\treturn {\"talk_about_is\":talk_about_is, \"total_like_count\":total_like_count, \"total_fans\":total_fans, \"start\":start.date, \"last\":last.date}","def _get_published(self):\n return self.__published","def _get_status_from_qry(self):\n active_deadline = self.get_active_deadline()\n return active_deadline.status","def test_public_status_page_post_public_status_page(self):\n pass","def test_active_and_date_range(self):\n\n url = '/%s/job-types/status/?is_active=true&started=%s&ended=%s' % ( self.api,\n '2016-01-01T00:00:00Z',\n '2016-01-02T00:00:00Z')\n response = self.client.generic('GET', url)\n self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)\n\n result = json.loads(response.content)\n self.assertEqual(len(result['results']), 3)\n self.assertEqual(result['results'][0]['job_type']['name'], self.job1.job_type.name)\n self.assertEqual(len(result['results'][0]['job_counts']), 0)","def test_paginate(self):\n db = get_session(self.app)\n\n statuses = []\n with self.app.app_context():\n p = project(save=True)\n u = user(save=True)\n\n # Create 100 statuses\n for i in range(30):\n statuses.append(status(project=p, user=u,\n created=datetime(2012, 5, 25),\n save=True))\n\n for i in range(30):\n statuses.append(status(project=p, user=u,\n created=datetime(2012, 6, 25),\n save=True))\n\n for i in range(40):\n statuses.append(status(project=p, user=u,\n created=datetime(2012, 7, 25),\n save=True))\n\n s = db.query(Status).order_by(Status.id)\n\n # Test simple pagination\n page = paginate(s, page=1)\n\n eq_(page.pages, 5)\n\n eq_(page.has_prev, False)\n eq_(page.has_next, True)\n\n page = paginate(s, page=3)\n eq_(page.has_prev, True)\n eq_(page.has_next, True)\n\n page = paginate(s, page=5)\n eq_(page.has_prev, True)\n eq_(page.has_next, False)\n\n # Test date filtered pagination\n page = paginate(s, page=1, startdate=datetime(2012, 5, 28))\n eq_(page.pages, 4)\n\n page = paginate(s, page=1, startdate=datetime(2012, 5, 28),\n enddate=datetime(2012, 6, 28))\n eq_(page.pages, 2)\n\n page = paginate(s, page=1, enddate=datetime(2012, 6, 28))\n eq_(page.pages, 3)","def schedule(request,status):\n\tnow = datetime.today()\n\tsched = Sample.objects.all()\n\tif status:\n\t\tsched = Sample.objects.filter(status=status)\n\tsched = sched.order_by('date_added')\n\tsched = [(now + timedelta(i+1), s) for i,s in enumerate(sched)]\n\treturn render_to_response('schedule/schedule.html', \n\t\t\t\t\t\t\t{'sched': sched},\n\t\t\t\t\t\t\tcontext_instance=RequestContext(request))","def historical():\n\n return {\n 'page': 'historical',\n }","def get_status() -> None:\n assert scraper.get_status() == True","def get_page_status_list(self, blogid=1):\n \n return self.execute('wp.getPageStatusList', blogid, self.username, self.password)","def get_status(cls, request, status):\n event_status = request.dbsession.query(cls)\\\n .filter_by(status=status).one()\n return event_status","def getStatus():","def active(self, **kwargs):\r\n now = date.today()\r\n return self.visible(is_approved=True, start_date__lte=now, end_date__gte=now, **kwargs)","def pfp_status(context):\n current = context['prescription']\n return \"{0}, {1}, {2}, {3}, {4}\".format(\n current.get_planning_status_display(),\n current.get_endorsement_status_display(),\n current.get_approval_status_display(),\n current.get_ignition_status_display(),\n current.get_status_display()\n )","def property_details(request, property_id):\n\n property = get_object_or_404(Property, pk=property_id)\n reserved_dates = []\n\n reserved_all = Booking.objects.filter(book_property=property, book_check_in__gte=datetime.date.today())\n for reserved in reserved_all:\n delta = reserved.book_check_out - reserved.book_check_in\n\n for i in range(delta.days + 1):\n format_date = (reserved.book_check_in + datetime.timedelta(days=i)).strftime(\"'%m/%d/%Y'\")\n reserved_dates.append(format_date)\n # print(format_date)\n\n separator = ', '\n reserved = separator.join(reserved_dates)\n\n book_ses = request.session.get('book_ses', [])\n booked_dates=[]\n\n if any(d['property'] == property_id for d in book_ses):\n # for one_book in book_ses:\n for i in range(len(book_ses)):\n one_book = book_ses[i] \n if(one_book['property'] == property_id):\n old_in = datetime.datetime.strptime(one_book['check_in'],'%Y-%m-%d')\n old_out = datetime.datetime.strptime(one_book['check_out'], '%Y-%m-%d') \n delta_old = old_out-old_in \n for i in range(delta_old.days + 1):\n format_date = (old_in + datetime.timedelta(days=i)).strftime(\"'%Y-%m-%d'\")\n booked_dates.append(format_date)\n print('ok')\n\n booked = separator.join(booked_dates)\n\n context = {\n 'property': property,\n 'reserved': reserved,\n 'booked': booked\n }\n\n return render(request, 'properties/property_details.html', context)","def month_report_handle(fans_type):\n\tstart = datetime.date.today() - timedelta(days=datetime.date.today().day - 1)\n\ttoday = datetime.date.today()\n\t#import pdb;pdb.set_trace()\n\t#fans_list = [\"wwwttshow\", \"ttshowpet\", \"draw.fans\", \"TTShowMusic\", \"GoodNews.FANS\"]\n\tfans_pages = FansPage.objects.filter(fans_type=fans_type, date__gte=start, date__lte=today).order_by(\"date\")\n\n\tstart = fans_pages[0]\n\tlast = fans_pages[len(fans_pages) - 1]\n\n\ttalk_about_is = (last.talk_about_is - start.talk_about_is)\n\ttotal_like_count = (last.total_like_count - start.total_like_count)\n\ttotal_fans = (last.total_fans - start.total_fans)\n\treturn {\"talk_about_is\":talk_about_is, \"total_like_count\":total_like_count, \"total_fans\":total_fans, \"start\":start.date, \"last\":last.date}","def get_time_in_status(self, issue, state):\n \n# current_datetime = str(dt.now()).split('.')[0].replace(' ', 'T') # The current datetime\n\n if ((issue['fields']['issuetype']['name'] == \"Sub-task\") and (issue['fields']['status']['name'] == \"In Progress\")) or \\\n ((issue['fields']['issuetype']['name'] == \"New Feature\") and (issue['fields']['status']['name'] not in [\"Open\", \"In Progress\", \"Reopened\", \"Resolved\", \"Closed\"])):\n print \"Getting time in status for %s\" % issue['fields']['status']['name']\n # At first assume state is first, last and only state in case no changelog, if there's a changelog we'll revise later.\n # First state create time same as issue created datetime \n cicdt = dt.strptime(issue['fields']['created'].split('.')[0], \"%Y-%m-%dT%H:%M:%S\") # Current item create datetime\n nicd = dt.strptime(str(dt.now()).split('.')[0].replace(' ', 'T'), \"%Y-%m-%dT%H:%M:%S\") # Next item create datetime\n diff = nicd - cicdt # Time the issue has been in that state\n \n # If there's a changelog history go thru it else use issue create date and current date for time in status\n # If there's no changelog/histories then we're still in first state, nothing has changed\n if not len(issue['changelog']['histories']):\n print \"no changelog for %s\" % issue['key']\n self.issue_objs[issue['key']].time_in_status = diff.days\n else:\n # If there is a changelog look for the value \"status\", changes may be something other than status\n print \"There's a changelog for issue %s\" % issue['key']\n# print json.dumps(issue, indent=4)\n \n # Go thru changelog histories to see if any of the changes are \"status\" for this state, also get last status or sprint if New Feature\n status_change_found = False\n for histories_item in issue['changelog']['histories']:\n if ((histories_item['items'][0]['field'] == 'status') and (histories_item['items'][0]['toString'] == state)):\n print \"There's a status change\"\n status_change_found = True\n \n # Get oldest sprint and status within config.change_period days ago for New Features \n if (issue['fields']['issuetype']['name'] == \"New Feature\") and \\\n ((histories_item['items'][0]['field'] == 'Milestone(s)') or (histories_item['items'][0]['field'] == 'status')):\n hicdt = dt.strptime(histories_item['created'].split('.')[0], \"%Y-%m-%dT%H:%M:%S\").date() # histories item create datetime\n if hicdt < date.today()-timedelta(days=int(self.config.get('default', 'change_period'))):\n print \"change too old %s, getting next histories item\" % hicdt\n continue # If older than config.change_period days then we don't care, get next histories item\n else:\n print \"recent change %s \" % hicdt\n if histories_item['items'][0]['field'] == 'Milestone(s)':\n self.issue_objs[issue['key']].last_sprint = histories_item['items'][0]['fromString'] # last sprint if issue less that config.change_period old\n print \"last_sprint %s\" % self.issue_objs[issue['key']].last_sprint\n break # Got the oldest change within change_period\n if histories_item['items'][0]['field'] == 'status':\n self.issue_objs[issue['key']].last_status = histories_item['items'][0]['fromString'] # last status if issue less that config.change_period old\n print \"last_status %s\" % self.issue_objs[issue['key']].last_status\n break # Got the oldest change within change_period\n \n # If there was a change in status calculate time in status from changelog\n if(status_change_found):\n total_days = 0 # Accumulate all the diffs for each time in this state\n # Go thru changelog histories to see if this issue was in this state before.\n for i, histories_item in enumerate(issue['changelog']['histories']):\n # All the different kinds of things that have changed, we're only interested in 'status'\n \n # Display all the changelog history items\n if (0):\n for k, v in histories_item.items():\n print \"issue['changelog']['histories'] key: %s value: %s\" % (k, v)\n print \"issue['changelog']['histories']['items'] %s\" % histories_item['items']\n for item in histories_item['items']:\n print \"histories_item['items'] %s\" % item\n print \"histories_item['items'][0] %s\" %histories_item['items'][0]\n for item2 in histories_item['items'][0]:\n print \"histories_item['items'][0] %s %s\" % (item2, histories_item['items'][0][item2])\n \n # If status record we're interested in is found, look for next status change or use current date for end date\n # If status \"Pending\" for New Features or \"Open\" for Sub-tasks there is no change entry for that, it's first state, use created date.\n if ((histories_item['items'][0]['field'] == 'status') and (histories_item['items'][0]['toString'] == state)):\n current_status_create_datetime = histories_item['created'].split('.')[0]\n \n # Go thru future history changes until the next status change\n status_found = False\n for j in range(i+1, len(issue['changelog']['histories'])):\n if (issue['changelog']['histories'][j]['items'][0]['field'] == 'status'):\n next_item_create_date = issue['changelog']['histories'][j]['created'].split('.')[0] # Only next status change not any change\n print \"%s. next histories item created: %s\" % (j, next_item_create_date)\n status_found = True\n break # Break the for loop, next status found\n \n if not status_found: \n next_item_create_date = str(dt.now()).split('.')[0].replace(' ', 'T') # The current datetime \n print \"No next histories item, using today's date: %s\" % (next_item_create_date)\n \n cscdt = dt.strptime(current_status_create_datetime, \"%Y-%m-%dT%H:%M:%S\") # Current status create datetime\n nicdt = dt.strptime(next_item_create_date, \"%Y-%m-%dT%H:%M:%S\") # Next item create datetime\n \n print \"Current status create date for %s: %s\" % (issue['key'], cscdt)\n print \"Next item create date for %s: %s\" % (issue['key'], nicdt)\n \n diff = nicdt - cscdt # The number of days the issue has been in that state\n total_days += diff.days # Accumulate all the times this issue has been in this state.\n self.issue_objs[issue['key']].time_in_status = total_days\n else:\n self.issue_objs[issue['key']].time_in_status = diff.days # No change in status, days in status is issue created date to now","def test_pages_created_happy_case(self):\n metric = PagesCreated(\n namespaces=[301, 302, 303],\n start_date='2013-06-19 00:00:00',\n end_date='2013-08-21 00:00:00'\n )\n results = metric(self.user_ids, self.mwSession)\n\n assert_equal(results[self.editors[0].user_id]['pages_created'], 3)\n assert_equal(results[self.editors[1].user_id]['pages_created'], 1)","def _get_archive_status(self):\n\t\t# if we have a result of the search\n\t\t# check if any of our segments are in it\n\t\tfor ele in self.elements:\n\t\t\tif ele.pool_search():\n\t\t\t\tele.status = 'archived'\n\t\t\telse:\n\t\t\t\tele.status = 'pending'","def getCMSStatus(self):\n data = auth.getContent('%s/PageZero?FORMAT=XML' % self._base_url_)\n data = tree.fromstring(data)\n\n s = data.find('PageZeroSample')\n cms = CMSStatus()\n try:\n cms.collection_time = datetime.strptime(s.find('collectionTimeGMT').text+' GMT', '%Y.%m.%d %H:%M:%S %Z')\n cms.magnetic_field = float(s.find('bField').text)\n cms.magnet_current = float(s.find('magCur').text)\n cms.vacuum_pressure = float(s.find('vacuum').text)\n cms.feds_state['TRG'] = s.find('IO_TRG').text=='IN'\n cms.feds_state['CSC'] = s.find('IO_CSC').text=='IN'\n cms.feds_state['DAQ'] = s.find('IO_DAQ').text=='IN'\n cms.feds_state['DQM'] = s.find('IO_DQM').text=='IN'\n cms.feds_state['DT'] = s.find('IO_DT').text=='IN'\n cms.feds_state['ECAL'] = s.find('IO_ECAL').text=='IN'\n cms.feds_state['ES'] = s.find('IO_ES').text=='IN'\n cms.feds_state['HCAL'] = s.find('IO_HCAL').text=='IN'\n cms.feds_state['PIXEL'] = s.find('IO_PIXEL').text=='IN'\n cms.feds_state['RPC'] = s.find('IO_RPC').text=='IN'\n cms.feds_state['SCAL'] = s.find('IO_SCAL').text=='IN'\n cms.feds_state['TRACKER'] = s.find('IO_TRACKER').text=='IN'\n cms.feds_state['CASTOR'] = s.find('IO_CASTOR').text=='IN'\n cms.feds_state['HF'] = s.find('IO_HFLUMI').text=='IN'\n cms.feds_state['CTPPS'] = s.find('IO_CTPPS_TOT').text=='IN'\n cms.daq_state = s.find('state').text\n cms.dead_time = float(s.find('deadTimeActivePercent').text)\n cms.t0_transfer = s.find('tier0Transfer').text=='ON'\n cms.run_number = int(s.find('runNumber').text)\n cms.lumi_section = int(s.find('lumiSegmentNr').text)\n cms.l1_menu = s.find('l1Menu').text\n cms.hlt_rate = float(s.find('hltRate').text)\n cms.instant_lumi = float(s.find('instantLumi').text)\n cms.fill_lumi = float(s.find('lumiFill').text)\n cms.crossing_angle = float(s.find('angle').text)\n except AttributeError:\n print 'ERROR in parsing the CMS status report'\n pass\n\n return cms","def task7(self, doc_uuid):\n page_totalRead ={}\n page_reads = {} \n for entry in self.records:\n if((entry['event_type'] == 'pagereadtime') and (entry['subject_doc_id'] == doc_uuid)):\n if (entry['subject_page'] in page_totalRead):\n page_totalRead[entry['subject_page']] += int(entry['event_readtime'])\n else:\n page_totalRead[entry['subject_page']] = int(entry['event_readtime'])\n if(entry['subject_page'] in page_reads):\n page_reads[entry['subject_page']] += 1\n else:\n page_reads[entry['subject_page']] = 1\n page_meanRead = {}\n for page in page_totalRead:\n if (page in page_reads):\n page_meanRead[page] = page_totalRead[page]/page_reads[page]\n GUI.show_line(page_meanRead, \"Page\", \"Mean Read Time\", \"Retention\")","async def get_status(self):\n data = await self.gen_req(self.status_url)\n return data['data']['attributes']['releasedAt'], data['data']['attributes']['version']","def test_public_status_page_patch_public_status_page(self):\n pass","def get_status(self):\n # find status\n # search in summary file first\n self.status = \"running\"\n status = self.search_summary(\"status\")\n if status:\n self.status = status.split()[1]\n # define running time\n # search in summary file first\n self.running_time = \"00:00:00\"\n running_time = self.search_summary(\"running-time\")\n if running_time:\n self.running_time = running_time.split()[1]\n # calculate running time\n else:\n now = datetime.datetime.now()\n elapsed_time = (now - self.ctime).seconds\n hours, remainder = divmod(elapsed_time, 3600)\n minutes, seconds = divmod(remainder, 60)\n self.running_time = (\n f\"{int(hours):02}:{int(minutes):02}:{int(seconds):02}\"\n )","def status(self):","def compute_campaign_status(end_date):\n status = bool('False')\n if end_date is not None and end_date.strftime('%Y-%m-%d %H:%M') < datetime.now().strftime('%Y-%m-%d %H:%M'):\n status = bool('True')\n return status","def _get_status(self):\n if self._state in [\"processed\", \"error\"]:\n return self._state\n \n get_resp = requests.get(self.location, cookies={\"session\": self.session})\n\n self._state = get_resp.json()[\"status\"]\n self.slice_time = get_resp.json()[\"slice_time\"]\n \n return self._state","def is_published(self):\n now = timezone.now()\n return now >= self.pub_date","def _get_status(self):\n return self.__status","def event_get_status():\n event = Event.query.filter_by(is_current=True).first() or \\\n Event.query.order_by(Event.id.desc()).first()\n if not event:\n return jsonify(status='')\n return jsonify(status=event.status_text or '')","def test_date_range(self):\n\n url = '/%s/job-types/status/?started=%s&ended=%s' % ( self.api,\n '2015-01-01T00:00:00Z',\n '2015-01-02T00:00:00Z')\n response = self.client.generic('GET', url)\n self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)\n\n result = json.loads(response.content)\n self.assertEqual(len(result['results']), 4)","def status():\n _request('worklog/status/')","def get_status(self):\n statuses = dict(PRODUCTHISTORY_CHOICES)\n return statuses.get(self.status, \"N/A\")","def GetStatus(self):\r\n return self.status","def test_get_page_of_activities():\n \n # get activities on page that won't have activities\n r = get_page_of_activities(None, 50)\n assert r.status_code == 200\n assert r.json() is None\n\n # get values only after certain time\n r = get_page_of_activities(\"2020-12-27T19:45:05Z\", 1)\n assert r.status_code == 200\n # check that all necessary objects are included\n r_json = r.json()\n assert r_json is not None\n assert \"id\" in r_json\n assert \"type\" in r_json\n assert \"start_date\" in r_json\n # check that we only got objects that occured after last_activity_date param\n for x in r_json:\n assert datetime.strptime(x[\"start_date\"], \"%Y-%m-%dT%H:%M:%SZ\") < datetime.strptime(\"2020-12-27T19:45:05Z\", \"%Y-%m-%dT%H:%M:%SZ\")\n \n # check that returns all activities on page\n r_all_none = get_page_of_activities(None, 1)\n assert r_all_none.status_code == 200\n r_all_none_json = r_all_none.json()\n assert r_all_none_json is not None\n assert \"id\" in r_all_none_json\n assert \"type\" in r_all_none_json\n assert \"start_date\" in r_all_none_json\n # should return all activities because I have none prior to 2020\n r_all_date = get_page_of_activities(\"2019-12-22T19:41:05Z\", 1)\n assert r_all_date.status_code == 200\n r_all_date_json = r_all_date.json()\n assert r_all_date_json is not None\n assert \"id\" in r_all_date_json\n assert \"type\" in r_all_date_json\n assert \"start_date\" in r_all_date_json\n\n # test to see if both methods to return all activities on page worked\n assert len(r_all_date_json) == len(r_all_none_json)\n\n # try to get activities from future is error\n r = get_page_of_activities(\"2025-12-22T19:41:05Z\", 1)\n assert r.status_code != 200","def get_status(self):\n\n # update status\n # TODO: this needs to consider \"partial\" status based on the testcodes that are defined\n # in the panel.\n # get the condition OK aliquot condition instance\n result_item_cls = models.get_model(self._meta.app_label, 'resultitem')\n aliquot_condition_ok = AliquotCondition.objects.get_ok()\n if not self.aliquot.aliquot_condition:\n # how can this be ??\n status = 'ERROR'\n elif result_item_cls.objects.filter(result__order=self) or self.panel.panel_type == 'STORAGE':\n # test aliquot condition and set the order status\n if self.aliquot.aliquot_condition == aliquot_condition_ok:\n status = 'COMPLETE'\n else:\n # has results or is stored but condition is not 10\n # was this meant to be a storage panel?\n status = 'ERROR'\n elif self.aliquot.aliquot_condition != aliquot_condition_ok:\n status = 'REDRAW'\n else:\n status = 'PENDING'\n # regardless of status, check that order was not deleted on DMIS\n dmis_tools = DmisTools()\n if dmis_tools.is_withdrawn_order(self):\n # other aspects of result visibility must consider this value\n status = 'WITHDRAWN'\n return status","def get_status_stat(qs):\n return [ { 'status':'total', 'count':qs.count() } ] +\\\n [ { 'status':str(x['status']), 'count':str(x['count']) }\n for x in qs.values('status').annotate(count=Count('id')) ]","def filter_status_as_of(self, status_date: datetime.date) -> QuerySet:\n return self.model._filter_queryset_status_as_of(self, status_date)","def status(self):\n props = self.properties\n if props:\n if props.get('created'):\n return CREATED_STATUS","def test_auto_set_published_on_status_change(self): \n title = ('Transportation Challenges Limit Education Choices for '\n 'Denver Parents')\n summary = \"\"\"\n Many families in the Denver metro area use public\n transportation instead of a school bus because for them, a\n quality education is worth hours of daily commuting. Colorado's\n school choice program is meant to foster educational equity,\n but the families who benefit most are those who have time and\n money to travel. Low-income families are often left in a lurch.\n \"\"\"\n byline = \"Mile High Connects\"\n story = create_story(title=title, summary=summary, byline=byline)\n # Default status should be draft \n self.assertEqual(story.status, 'draft')\n # and there should be no published date\n self.assertEqual(story.published, None)\n story.status = 'published'\n story.save()\n self.assertNowish(story.published)","def test_auto_set_published_on_status_change(self): \n title = ('Transportation Challenges Limit Education Choices for '\n 'Denver Parents')\n summary = \"\"\"\n Many families in the Denver metro area use public\n transportation instead of a school bus because for them, a\n quality education is worth hours of daily commuting. Colorado's\n school choice program is meant to foster educational equity,\n but the families who benefit most are those who have time and\n money to travel. Low-income families are often left in a lurch.\n \"\"\"\n byline = \"Mile High Connects\"\n story = create_story(title=title, summary=summary, byline=byline)\n # Default status should be draft \n self.assertEqual(story.status, 'draft')\n # and there should be no published date\n self.assertEqual(story.published, None)\n story.status = 'published'\n story.save()\n self.assertNowish(story.published)","def goalStatus(self, fromdt, todt):\r\n ret = {}\r\n tot = self.totalSaved(fromdt, todt)\r\n\r\n return dict([(g, tot - g.amount) for g in self.goals])","def get_rebuild_status(self, rebuild_status_url):\n if getattr(self.settings, 'AK_TEST', False):\n return self.TEST_DATA.get('get_rebuild_status')\n res = self.client.get(rebuild_status_url) \n if res.status_code == 200:\n res_dict = json.loads(res.text)\n rv = {'res': res}\n rv['finished'] = res_dict.get('finished', None)\n rv['finished_at'] = res_dict.get('finished_at', None)\n rv['target_count'] = res_dict.get('results', None)\n return rv\n else:\n return None","def document_status(document_id: uuid.UUID, db: Session = Depends(get_db)):\n document_status = get_document_status(db, document_id)\n return document_status","def status_summary(self):\n base_query_set = super(PeeringSessionManager, self).get_queryset()\n summary = base_query_set.annotate(\n label=models.Case(\n models.When(provisioning_state=2, then=models.Case(\n models.When(admin_state=2, then=models.Case(\n models.When(operational_state=6,\n then=models.Value('Up')),\n default=models.Value('Down')\n )),\n default=models.Value('Admin Down')\n )),\n models.When(provisioning_state=1,\n then=models.Value('Provisioning')),\n default=models.Value('None'),\n output_field=models.CharField()\n )).values('label').annotate(value=models.Count('label'))\n return summary","def test_on_homepage_published_only(self):\n\tpublished_titles = (\n\t \"The Power of Play: Playground Locations in the Children's Corridor\",\n\t \"Birth Trends in the Children's Corridor: Focus on Foreign-born Mothers\")\n\tunpublished_titles = (\n\t \"Shattered Dreams: Revitalizing Hope in Original Aurora\",\n\t \"A School Fight Rallies Hinkley High School Mothers to Organize\",\n\t \"Transportation Challenges Limit Education Choices for Denver Parents\")\n\tfor title in published_titles + unpublished_titles:\n\t status = 'draft'\n\t if title in published_titles:\n\t\tstatus = 'published'\n\t create_story(title=title, on_homepage=True, status=status)\n\t\t\t \n\thomepage_stories = Story.objects.on_homepage()\n\tself.assertEqual(homepage_stories.count(), len(published_titles))\n\tfor title in published_titles:\n\t self.has_story_title(title, homepage_stories)","def test_on_homepage_published_only(self):\n\tpublished_titles = (\n\t \"The Power of Play: Playground Locations in the Children's Corridor\",\n\t \"Birth Trends in the Children's Corridor: Focus on Foreign-born Mothers\")\n\tunpublished_titles = (\n\t \"Shattered Dreams: Revitalizing Hope in Original Aurora\",\n\t \"A School Fight Rallies Hinkley High School Mothers to Organize\",\n\t \"Transportation Challenges Limit Education Choices for Denver Parents\")\n\tfor title in published_titles + unpublished_titles:\n\t status = 'draft'\n\t if title in published_titles:\n\t\tstatus = 'published'\n\t create_story(title=title, on_homepage=True, status=status)\n\t\t\t \n\thomepage_stories = Story.objects.on_homepage()\n\tself.assertEqual(homepage_stories.count(), len(published_titles))\n\tfor title in published_titles:\n\t self.has_story_title(title, homepage_stories)","def status( self ):\n duration = datetime.datetime.now() - self.startTime\n status = {\n 'start': self.startTime.isoformat(),\n 'now': datetime.datetime.now().isoformat(),\n 'duration': duration.total_seconds(),\n 'bookmark': 0,\n 'events': 0,\n 'cumulative_rate': 0,\n 'processes': [],\n 'state': {\n 'id': self.state,\n 'description': definitions.STATE_STRING[self.state]\n }\n }\n\n # Sending pipes to processes which are not running or shutting down\n # will lead to errors and deadlocks. Loop through to detect errors.\n if self.state == definitions.STATE_RUNNING:\n # Loop through all processes and just check we're running properly\n for proxy in self.processes:\n if not proxy.process.is_alive():\n self.logger.info( 'Process {0} is dead.'.format( proxy.name ))\n self.state = definitions.STATE_ERROR\n break\n\n if proxy.request( 'status' )['state'] == definitions.STATE_ERROR:\n self.logger.info( 'Process {0} state is {1}.'.format(\n proxy.name,\n definitions.STATE_STRING[ definitions.STATE_ERROR ]\n ))\n\n self.state = definitions.STATE_ERROR\n break\n\n # Now do the actual status checks\n if self.state == definitions.STATE_RUNNING:\n # Loop through processes in order\n for proxy in self.processes:\n response = proxy.request('status')\n\n proc = {\n 'name': proxy.name,\n 'pid': proxy.process.pid,\n 'count': response['count'],\n 'sleep': response['sleep']\n }\n\n status['events'] = proc['count']\n status['processes'].append( proc )\n\n if 'bookmark' in response:\n status['bookmark'] = response['bookmark']\n\n status['cumulative_rate'] = round(\n status['events'] / duration.total_seconds(), 2)\n\n return status","def normalize_dates(end_date, start_date, today_date):\n if start_date < today_date or end_date < today_date:\n return {'status': False, 'message': 'Sorry, you cannot enter a past date'}\n elif end_date < start_date:\n return {'status': False, 'message': 'Sorry, end date must be after start date'}\n else:\n return {'status': True, 'message': 'Validation successful'}","def get_published_date(self):\n return self._get_date_or_timestamp('published')","def calc_published_state(self, state: str, path: Path, reference_image_count: int) -> str:\n\n if not (path.exists() and state == 'published'):\n return \"\"\n\n\n # noinspection PyTypeChecker\n ig_file_count = 0\n for root, dirs, files in os.walk(path):\n\n # Trivial case\n if not Path(root,'archive').exists():\n return self._web_pub_text\n\n for image_groups in os.scandir(join(root, 'archive')):\n if not image_groups.is_dir():\n continue\n for ig_root, ig_dirs, ig_files in os.walk(image_groups):\n ig_file_count += len(ig_files)\n\n # approximate\n return self._web_pub_text if float(ig_file_count) < (\n 0.3 * float(reference_image_count)) else self._full_pub_text","def check_status():\n logger.debug(\"Starting the check_status() routine.\")\n\n url = \"https://www.toggl.com/api/v8/time_entries/current\"\n token = os.environ[\"TOGGL_API_TOKEN\"]\n auth_token = base64.b64encode(f\"{token}:api_token\".encode()).decode()\n resp = requests.get(url, headers={\"Authorization\": \"Basic \" + auth_token})\n\n cols = \"id\", \"duration\", \"description\"\n status = {k: v for k, v in (resp.json()[\"data\"] or {}).items() if k in cols}\n logger.debug(f\"{'Something' if 'id' in status else 'Something'} is being tracked.\")\n\n return status","def get_status(request):\n ecc_server_status_list = get_ecc_server_statuses(request)\n data_router_status_list = get_data_router_statuses(request)\n overall_state, overall_state_name = calculate_overall_state(request)\n\n current_run = request.experiment.latest_run\n if current_run is not None:\n run_number = current_run.run_number\n start_time = current_run.start_datetime.strftime('%b %d %Y, %H:%M:%S')\n duration_str = current_run.duration_string\n run_title = current_run.title\n run_class = current_run.get_run_class_display()\n else:\n run_number = None\n start_time = None\n duration_str = None\n run_title = None\n run_class = None\n\n output = {\n 'overall_state': overall_state,\n 'overall_state_name': overall_state_name,\n 'ecc_server_status_list': ecc_server_status_list,\n 'data_router_status_list': data_router_status_list,\n 'run_number': run_number,\n 'start_time': start_time,\n 'run_duration': duration_str,\n 'run_title': run_title,\n 'run_class': run_class,\n }\n\n return output","def test_status_weeks_at_year_end(self):\n d = datetime(2014, 1, 1, 12, 13, 45, 0)\n with self.app.app_context():\n u = user(username='testuser', save=True)\n s = status(content='my status update', created=d, user=u, save=True)\n eq_(s.week_start.strftime(\"%Y-%m-%d\"), \"2013-12-30\")\n eq_(s.week_end.strftime(\"%Y-%m-%d\"), \"2014-01-05\")","def generate_status_page():\n status = renew_status()\n now = datetime.datetime.now()\n\n # update statistics\n update_statistics(status)\n\n # add stats to status\n status = add_statistics_to_status(status)\n\n # calculate datetime from oldest key\n stats_first = datetime.datetime.strptime(\n overall_oldest_key, '%Y%m%d%H%M')\n\n # downtimes\n if 'display_downtimes' in CONFIG and CONFIG['display_downtimes']:\n display_downtimes = True\n downtimes = [{\n 'host': host[0],\n 'downtimes': get_downtimes(host[0]),\n } for host in CONFIG['hosts']]\n else:\n display_downtimes = False\n downtimes = []\n\n # load template\n with open(CONFIG['template_file']) as template_file:\n template = Template(template_file.read())\n print(template.render({\n 'time': _format_datetime(now),\n 'status': status,\n 'stats_first': _format_datetime(stats_first),\n 'display_downtimes': display_downtimes,\n 'downtimes': downtimes,\n 'title': CONFIG['title'],\n 'refresh_interval': CONFIG['refresh_interval'],\n }))","def getPublishedTime(self): #$NON-NLS-1$\r","def status(self):\n r = requests.get('/'.join([self.base_url, self.ENDPOINT_STATUS]))\n return r.json()","def test_status_weeks_at_year_start(self):\n d = datetime(2013, 12, 31, 12, 13, 45, 0)\n with self.app.app_context():\n u = user(username='testuser', save=True)\n s = status(content='my status update', created=d, user=u, save=True)\n eq_(s.week_start.strftime(\"%Y-%m-%d\"), \"2013-12-30\")\n eq_(s.week_end.strftime(\"%Y-%m-%d\"), \"2014-01-05\")","def get_object_status(obj):\n return get_object_parameter(obj, 'status')","def get_status(intervention: dict) -> dict:\n for key, values in intervention.items():\n if not values:\n intervention['status'] = \"Brouillon\"\n break\n\n if intervention.get('date_intervention'):\n if not intervention.get('status'):\n if intervention['date_intervention'] < datetime.now():\n intervention['status'] = \"Terminée\"\n else:\n intervention['status'] = \"Validée\"\n\n intervention['date_intervention'] = intervention['date_intervention'].strftime(\"%m/%d/%Y %H:%M:%S\")\n\n return intervention","def _updated_or_published(mf):\n\n\tprops = mf['properties']\n\n\t# construct updated/published date of mf\n\tif 'updated' in props:\n\t\treturn props['updated'][0]\n\telif 'published' in props:\n\t\treturn props['published'][0]\n\telse:\n\t\treturn None","def build_progress_report(self):\n report = super(self.__class__, self).build_progress_report()\n report['publishing'] = self._generate_publishing_section()\n return report","def get_status(self, render_via_ajax):\r\n ugettext = self.system.service(self, \"i18n\").ugettext\r\n status_list = []\r\n current_task_human_name = \"\"\r\n for i in xrange(0, len(self.task_xml)):\r\n human_task_name = self.extract_human_name_from_task(self.task_xml[i])\r\n human_task_name = ugettext(human_task_name)\r\n # Extract the name of the current task for screen readers.\r\n if self.current_task_number == i:\r\n current_task_human_name = human_task_name\r\n task_data = {\r\n 'task_number': i + 1,\r\n 'human_task': human_task_name,\r\n 'current': self.current_task_number == i\r\n }\r\n status_list.append(task_data)\r\n\r\n context = {\r\n 'status_list': status_list,\r\n 'grader_type_image_dict': GRADER_TYPE_IMAGE_DICT,\r\n 'legend_list': LEGEND_LIST,\r\n 'render_via_ajax': render_via_ajax,\r\n 'current_task_human_name': current_task_human_name,\r\n }\r\n status_html = self.system.render_template(\r\n \"{0}/combined_open_ended_status.html\".format(self.TEMPLATE_DIR), context\r\n )\r\n\r\n return status_html","def test_build_status_page_from_desired_state(\n status_page_v1: StatusPageV1,\n):\n page = build_status_page(status_page_v1)\n assert page.name == \"page\"\n assert len(page.components) == 2\n assert {c.group_name for c in page.components if c.group_name} == {\"group-1\"}\n assert {c.name for c in page.components} == {\"ai-component-1\", \"ai-component-2\"}","def customer_summary(self, status='fully-paid', billtype=None, start_date=None, end_date=None):\n query = self.get_queryset()\n if status == 'fully-paid':\n query = query.filter(status=status)\n if status == 'pending':\n query = query.filter(status=status)\n if billtype:\n query = query.filter(billtype__name=billtype)\n if start_date and end_date:\n query = query.filter(\n models.Q(month__gte=start_date) &\n models.Q(month__lte=end_date)\n )\n\n return query.aggregate(models.Sum('amount'))['amount__sum']","def queryset(self, request):\r\n TODAY = datetime.date.today()\r\n YEAR = int(TODAY.year)\r\n qs = super(PresentationAdmin, self).queryset(request)\r\n start_date = datetime.date(YEAR, 1, 1)\r\n return qs.filter(date_created__gte=start_date)","def _publish_status(self, state='complete'):\n self.logger.debug('Recording catalog status: \"{}\"'.format(state))\n self.status_table.update_item(\n {'api_version': self.api_version},\n {\n 'state': state,\n 'timestamp': time.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n 'catalog_url': '{0}/v{1}/catalog.json'.format(self.api_url, self.api_version)\n }\n )","def getMyDocumentsInProgress( self, REQUEST=None, member=None, check_only=None ):\n results = {}\n now = DateTime()\n\n membership = getToolByName( self, 'portal_membership' )\n metadata = getToolByName( self, 'portal_metadata' )\n username = member or membership.getAuthenticatedMember().getUserName()\n\n if REQUEST is not None:\n period = int(REQUEST.get('period', '0'))\n else:\n period = None\n\n indexes = {}\n indexes['Creator'] = [ username ]\n indexes['implements'] = [ 'isVersionable' ]\n if period:\n days = period == 5 and 90 or period == 4 and 30 or period == 3 and 14 or period == 2 and 7 or 0\n if days > 0:\n created_till = DateTime()\n created_from = created_till - float(days * 3600 * 24) / 86400\n indexes['created'] = { 'query' : ( created_from, created_till and created_till + 0.99999 ), 'range' : 'min:max' }\n else:\n now = DateTime()\n created_from = DateTime(int(now.strftime('%Y')), int(now.strftime('%m')), int(now.strftime('%d')))\n indexes['created'] = { 'query' : created_from, 'range' : 'min' }\n\n documents = self.searchResults( type='query', REQUEST=REQUEST, **indexes )\n\n if check_only:\n if not documents: return 0\n elif not documents:\n return ( 0, [] )\n\n for r in documents:\n obj = r.getObject()\n if obj is None:\n continue\n if not username in membership.getObjectOwners( obj ):\n continue\n if not ( obj.implements('isDocument') or obj.implements('isVersionable') ):\n continue\n\n category = obj.Category()\n\n if not results.has_key(category):\n results[category] = []\n\n info = {}\n\n info['document_title'] = obj.Title().strip()\n obj_description = obj.Description().strip()\n info['document_description'] = info['document_title'] != obj_description and obj_description\n info['creator'] = obj.Creator()\n info['creation_date'] = r['created']\n info['recipient_agency'] = CustomAttributeValue( obj, 'recipient_agency' )\n\n executor = CustomAttributeValue( obj, 'executor' )\n if executor:\n info['executor'] = type(executor) not in ( ListType, TupleType ) and [ executor ] or executor\n else:\n info['executor'] = []\n\n signatory = CustomAttributeValue( obj, 'signatory' )\n if signatory:\n if type(signatory) not in ( ListType, TupleType ):\n signatory = [ signatory ]\n info['signatory'] = [ x for x in signatory if x not in info['executor'] ]\n else:\n info['signatory'] = []\n\n info['registry_id'] = obj.registry_ids() and obj.getInfoForLink( mode=2 ) or ''\n info['resolution'] = obj.getDocumentResolution( no_absolute=1 )\n info['view_url'] = obj.absolute_url( canonical=1, no_version=1 ) + '/view?expand=1'\n info['new'] = 0\n\n try: effective_date = int((now - info['creation_date']) * 10**8)\n except: effective_date = 0\n\n info['sortkey'] = ( '0000000000' + str(effective_date) )[ -10: ]\n results[ category ].append( info )\n\n interrupt_thread( self )\n\n if check_only: return len(results.keys()) > 0 and 1 or 0\n\n res = []\n custom_categories = CustomCategoryIds()\n max_categories = len(custom_categories)\n\n for category in results.keys():\n x = max_categories\n for n in range(0, max_categories):\n if category == custom_categories[n]:\n x = n\n break\n\n category_title = ( x < max_categories and category[4:]+'s' ) or 'Another Documents'\n res.append( ( x, category_title, results[ category ] ) )\n\n res.sort()\n\n results = []\n total = 0\n\n for x, category, documents in res:\n results.append( { 'category' : category, 'documents' : documents } )\n total += len( documents )\n\n if check_only: return total > 0 and 1 or 0\n return ( total, results )","def get(self):\n\n return self.get_request_handler(request.headers).get_all_employment_status()","def was_published_recently(self):\n now = timezone.now()\n return now - datetime.timedelta(days=1) <= self.pub_date <= now","def test_public_status_page_get_authorizations_for_public_status_page(self):\n pass","def get_state_in_period(course_key, from_date, to_date):\n enrollment_stat = (\n EnrollmentTabCache.objects\n .filter(course_id=course_key, created__range=(from_date, to_date))\n .values('unenroll', 'enroll', 'total', 'created')\n .order_by('created')\n )\n return enrollment_stat","def get_status_for_experiment(self, id):\n # open = 'open'\n running = 'running'\n finished = 'finished'\n waiting = 'waiting'\n\n experiment = Experiment.get(id)\n date_time_now = datetime.datetime.now()\n start_datetime = experiment.startDatetime\n end_datetime = experiment.endDatetime\n if start_datetime >= end_datetime:\n # validate this earlier\n return None\n if start_datetime <= date_time_now and date_time_now <= end_datetime:\n return running\n elif date_time_now > end_datetime:\n return finished\n elif date_time_now < start_datetime:\n return waiting\n return None","def published_after(self) -> Type[QuerySet]:\n return Post.objects.filter(published__gt=self.published, published__lt=timezone.now()) if self.is_published() else Post.objects.none()","def update_campaign_status(self):\n if self.status == CAMPAIGN_STATUS.START:\n return \"<a href='%s'>Pause</a> | <a href='%s'>Abort</a> | <a href='%s'>Stop</a>\" % \\\n (reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.PAUSE]),\n reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.ABORT]),\n reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.END]))\n\n if self.status == CAMPAIGN_STATUS.PAUSE:\n return \"<a href='%s'>Start</a> | <a href='%s'>Abort</a> | <a href='%s'>Stop</a>\" % \\\n (reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.START]),\n reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.ABORT]),\n reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.END]))\n\n if self.status == CAMPAIGN_STATUS.ABORT:\n return \"<a href='%s'>Start</a> | <a href='%s'>Pause</a> | <a href='%s'>Stop</a>\" % \\\n (reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.START]),\n reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.PAUSE]),\n reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.END]))\n\n if self.status == CAMPAIGN_STATUS.END:\n return \"<a href='%s'>Start</a> | <a href='%s'>Pause</a> | <a href='%s'>Abort</a>\" % \\\n (reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.START]),\n reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.PAUSE]),\n reverse('dialer_campaign.views.update_campaign_status_admin',\n args=[self.pk, CAMPAIGN_STATUS.ABORT]))","def _get_state_for_date(squadron_url: str, date_number: str, base_state: dict) -> dict:\n state = base_state.copy()#don't mutate the original\n state['__EVENTTARGET'] = 'ctrlCalendar'\n state['__EVENTARGUMENT'] = date_number\n html_string = _get_page_html(squadron_url, state)\n date_state = _get_state_values_from_html(html_string)\n return date_state","def _do_status(self) -> Dict[str, Any]:\n return {}","def _do_status(self) -> Dict[str, Any]:\n return {}","def get_pp_status(case_dict):\n # ---------------------------------------------------------------------\n logger.debug(\"get_pp_status\")\n\n # initialize status variables\n msg_avg = dict()\n msg_diags = dict()\n diag_comps = [\"atm\", \"ice\", \"lnd\", \"ocn\"]\n\n pp_dir = os.path.join(case_dict[\"CASEROOT\"], \"postprocess\")\n pp_log_dir = os.path.join(case_dict[\"CASEROOT\"], \"postprocess\", \"logs\")\n\n msg_avg[\"atm\"] = \"COMPLETED SUCCESSFULLY\"\n msg_diags[\"atm\"] = \"Successfully completed generating atmosphere diagnostics\"\n case_dict[\"atm_avg_dates\"] = case_dict[\"atm_diag_dates\"] = get_diag_dates(\n \"atm\", pp_dir\n )\n\n msg_avg[\"ice\"] = \"Successfully completed generating ice climatology averages\"\n msg_diags[\"ice\"] = \"Successfully completed generating ice diagnostics\"\n case_dict[\"ice_avg_dates\"] = case_dict[\"ice_diag_dates\"] = get_diag_dates(\n \"ice\", pp_dir\n )\n\n msg_avg[\"lnd\"] = \"COMPLETED SUCCESSFULLY\"\n msg_diags[\"lnd\"] = \"Successfully completed generating land diagnostics\"\n case_dict[\"lnd_avg_dates\"] = case_dict[\"lnd_diag_dates\"] = get_diag_dates(\n \"lnd\", pp_dir\n )\n\n msg_avg[\"ocn\"] = \"Successfully completed generating ocean climatology averages\"\n msg_diags[\"ocn\"] = \"Successfully completed generating ocean diagnostics\"\n case_dict[\"ocn_avg_dates\"] = case_dict[\"ocn_diag_dates\"] = get_diag_dates(\n \"ocn\", pp_dir\n )\n\n for comp in diag_comps:\n case_dict[comp + \"_avg_status\"] = \"Unknown\"\n case_dict[comp + \"_diag_status\"] = \"Unknown\"\n\n if comp != \"ocn\":\n case_dict[comp + \"_avg_path\"] = os.path.join(\n case_dict[\"DOUT_S_ROOT\"], comp, \"proc/climo\"\n )\n case_dict[comp + \"_avg_size\"] = get_disk_usage(\n case_dict[comp + \"_avg_path\"]\n )\n case_dict[comp + \"_diag_path\"] = os.path.join(\n case_dict[\"DOUT_S_ROOT\"], comp, \"proc/diag\"\n )\n case_dict[comp + \"_diag_size\"] = get_disk_usage(\n case_dict[comp + \"_diag_path\"]\n )\n else:\n case_dict[comp + \"_avg_path\"] = os.path.join(\n case_dict[\"DOUT_S_ROOT\"], comp, \"proc/climo*\"\n )\n case_dict[comp + \"_avg_size\"] = get_ocn_disk_usage(\n case_dict[comp + \"_avg_path\"]\n )\n case_dict[comp + \"_diag_path\"] = os.path.join(\n case_dict[\"DOUT_S_ROOT\"], comp, \"proc/diag*\"\n )\n case_dict[comp + \"_diag_size\"] = get_ocn_disk_usage(\n case_dict[comp + \"_diag_path\"]\n )\n\n avg_logs = list()\n avg_file_pattern = \"{0}/{1}_averages.log.*\".format(pp_log_dir, comp)\n avg_logs = glob.glob(avg_file_pattern)\n\n if avg_logs:\n log_file = max(avg_logs, key=os.path.getctime)\n if is_last_process_complete(\n log_file, msg_avg[comp], \"Average list complies with standards.\"\n ):\n case_dict[comp + \"_avg_status\"] = \"Succeeded\"\n else:\n case_dict[comp + \"_avg_status\"] = \"Started\"\n\n diag_logs = list()\n diag_file_pattern = \"{0}/{1}_diagnostics.log.*\".format(pp_log_dir, comp)\n diag_logs = glob.glob(diag_file_pattern)\n\n if diag_logs:\n log_file = max(diag_logs, key=os.path.getctime)\n if is_last_process_complete(log_file, msg_diags[comp], \"ncks version\"):\n case_dict[comp + \"_diag_status\"] = \"Succeeded\"\n else:\n case_dict[comp + \"_diag_status\"] = \"Started\"\n\n # get overall timeseries status\n case_dict[\"timeseries_status\"] = \"Unknown\"\n case_dict[\"timeseries_path\"] = get_pp_path(pp_dir, \"timeseries\")\n case_dict[\"timeseries_size\"] = 0\n case_dict[\"timeseries_dates\"] = \"{0}-{1}\".format(\n case_dict[\"RUN_STARTDATE\"].replace(\"-\", \"\"),\n case_dict[\"RUN_STARTDATE\"].replace(\"-\", \"\"),\n )\n case_dict[\"timeseries_total_time\"] = 0\n tseries_logs = list()\n tseries_file_pattern = \"{0}/timeseries.log.*\".format(pp_log_dir)\n tseries_logs = glob.glob(tseries_file_pattern)\n if tseries_logs:\n log_file = max(tseries_logs, key=os.path.getctime)\n if is_last_process_complete(\n filepath=log_file, expect_text=\"Successfully completed\", fail_text=\"opening\"\n ):\n case_dict[\"timeseries_status\"] = \"Succeeded\"\n with open(log_file, \"r\") as fname:\n log_content = fname.readlines()\n total_time = [line for line in log_content if \"Total Time:\" in line]\n case_dict[\"timeseries_total_time\"] = \" \".join(total_time[0].split())\n else:\n case_dict[\"timeseries_status\"] = \"Started\"\n sta_dates = case_dict[\"sta_last_date\"].split(\"-\")\n case_dict[\"timeseries_dates\"] = \"{0}-{1}\".format(\n case_dict[\"RUN_STARTDATE\"].replace(\"-\", \"\"), \"\".join(sta_dates[:-1])\n )\n for comp in _pp_tseries_comps:\n tseries_path = \"{0}/{1}/proc/tseries\".format(\n case_dict[\"timeseries_path\"], comp\n )\n case_dict[\"timeseries_size\"] += get_disk_usage(tseries_path)\n\n # get iconform status = this initializes files in the POSTPROCESS_PATH\n case_dict[\"iconform_status\"] = \"Unknown\"\n case_dict[\"iconform_path\"] = \"\"\n case_dict[\"iconform_size\"] = 0\n case_dict[\"iconform_dates\"] = case_dict[\"timeseries_dates\"]\n\n iconform_logs = list()\n iconform_file_pattern = \"{0}/iconform.log.*\".format(pp_log_dir)\n iconform_logs = glob.glob(iconform_file_pattern)\n if iconform_logs:\n log_file = max(iconform_logs, key=os.path.getctime)\n if is_last_process_complete(\n log_file,\n \"Successfully created the conform tool\",\n \"Running createOutputSpecs\",\n ):\n case_dict[\"iconform_status\"] = \"Succeeded\"\n else:\n case_dict[\"iconform_status\"] = \"Started\"\n\n # get xconform status\n case_dict[\"xconform_path\"] = \"\"\n case_dict[\"xconform_path\"] = get_pp_path(pp_dir, \"xconform\")\n case_dict[\"xconform_status\"] = \"Unknown\"\n case_dict[\"xconform_size\"] = get_disk_usage(case_dict[\"xconform_path\"])\n case_dict[\"xconform_dates\"] = case_dict[\"timeseries_dates\"]\n case_dict[\"xconform_total_time\"] = 0\n\n xconform_logs = list()\n xconform_file_pattern = \"{0}/xconform.log.*\".format(pp_log_dir)\n xconform_logs = glob.glob(xconform_file_pattern)\n if xconform_logs:\n log_file = max(xconform_logs, key=os.path.getctime)\n if is_last_process_complete(\n log_file,\n \"Successfully completed converting all files\",\n \"cesm_conform_generator INFO\",\n ):\n case_dict[\"xconform_status\"] = \"Succeeded\"\n case_dict[\"xconform_size\"] = get_disk_usage(case_dict[\"xconform_path\"])\n with open(log_file, \"r\") as fname:\n log_content = fname.readlines()\n total_time = [line for line in log_content if \"Total Time:\" in line]\n if total_time:\n case_dict[\"xconform_total_time\"] = \" \".join(total_time[0].split())\n else:\n case_dict[\"xconform_status\"] = \"Started\"\n\n return case_dict","def date(self):\n return self.status.created_at","def get_status():\n data = {\n 'status': 'up',\n }\n jsn = json.dumps(data)\n\n resp = Response(jsn, status=200, mimetype='application/json')\n\n return resp","def test_get_ordinal():\n for (index, status) in enumerate(['draft', 'published', 'archived']):\n yield (tools.eq_, BlogPostStatus.get_ordinal(status), index)","def test_project_recent_statuses(self):\n with self.app.app_context():\n p = project(save=True)\n u = user(save=True)\n\n # Create 70 statuses\n for i in range(70):\n status(project=p, user=u, save=True)\n\n s = status(project=p, user=u, save=True)\n\n # Create 30 replies\n for i in range(30):\n status(project=p, user=u, reply_to=s, save=True)\n\n # Should not include replies\n page = p.recent_statuses()\n eq_(page.pages, 4)","def test_previous_next_link_status(self):\n\n page_states = {\n 1: {\n 'expected_previous_status': \"disabled\",\n 'expected_next_status': \"\",\n },\n 2: {\n 'expected_previous_status': \"\",\n 'expected_next_status': \"\",\n },\n 50: {\n 'expected_previous_status': \"\",\n 'expected_next_status': \"disabled\",\n }\n }\n\n for curr_page, value in page_states.iteritems():\n previous_link_status, next_link_status = _get_previous_next_link_status(50, curr_page)\n self.assertEqual(value['expected_previous_status'], previous_link_status)\n self.assertEqual(value['expected_next_status'], next_link_status)","def data_collection_status(self, **kwargs):\n\n return self.api_request(self._get_method_fullname(\"data_collection_status\"), kwargs)","def view_date(request, year, month, day):\n logged_in = request.user.is_authenticated()\n\n try:\n date = datetime.date(int(year), int(month), int(day))\n except:\n return HttpResponse('bad date (somehow)')\n \n if date > datetime.date.today() and not logged_in:\n return HttpResponse('this newsletter has yet to be published')\n\n items = NewsItem.objects.all().filter(date_to_publish=date).order_by('position')\n left_sections = {\n 0: None,\n 1: None,\n 2: None,\n }\n right_sections = {\n 3: None,\n 4: None,\n 5: None,\n }\n extras = []\n \n for item in items:\n item_position = item.position\n if item.content:\n if item_position < 3:\n left_sections[item.position] = item\n elif item_position <= 5:\n right_sections[item.position] = item\n else:\n extras.append(item)\n\n args = {\n 'left_sections': left_sections,\n 'right_sections': right_sections,\n 'extras': extras,\n 'date': date.isoformat(),\n 'logged_in': logged_in,\n 'SUBSITE': SUBSITE,\n 'CDN': CDN, #included here for when we go live and need a place for people to view the newsletter\n }\n return render(request, 'newsletter.html', args)","def get_status_data():\n\n return dict(\n celery=_get_celery_status(),\n users=_get_users_stats(),\n daemons=_get_daemons_status(),\n settings=_get_settings(),\n files=_get_files_status(),\n languages=_get_languages_status(),\n sets=_get_sets_status(),\n )","def is_published(self) -> bool:\n return self.published and self.published <= timezone.now()","def test_public_status_page_put_public_status_page(self):\n pass","def test_public_documents_current_endpoint(self):\n\n # Grab the current public documents.\n public_documents_current = self.federal_client.public_inspection_documents_current()\n\n # Make sure we have a response.\n self.assertIsNotNone(public_documents_current)\n\n # And make sure we have some results, this should return more than 10.\n self.assertGreaterEqual(public_documents_current['count'], 10)"],"string":"[\n \"def test_page_caculated_status(self):\\n from pages import settings as pages_settings\\n setattr(pages_settings, \\\"PAGE_SHOW_START_DATE\\\", True)\\n yesterday = datetime.datetime.now() - datetime.timedelta(days=1)\\n tomorrow = datetime.datetime.now() + datetime.timedelta(days=1)\\n\\n page = self.new_page()\\n self.assertEqual(page.calculated_status, Page.PUBLISHED)\\n page.publication_date = tomorrow\\n self.assertEqual(page.calculated_status, Page.DRAFT)\\n page.publication_date = yesterday\\n self.assertEqual(page.calculated_status, Page.PUBLISHED)\\n setattr(pages_settings, \\\"PAGE_SHOW_END_DATE\\\", True)\\n page.publication_end_date = yesterday\\n self.assertEqual(page.calculated_status, Page.EXPIRED)\",\n \"def publication_status(self):\\n content = self.context.get_silva_object()\\n status = None\\n unapproved_version = content.get_unapproved_version()\\n approved_version = content.get_approved_version()\\n public_version = content.get_public_version()\\n previous_versions = content.get_previous_versions()\\n if unapproved_version and unapproved_version == self.context.id:\\n status = \\\"unapproved\\\"\\n elif approved_version and approved_version == self.context.id:\\n status = \\\"approved\\\"\\n elif public_version and public_version == self.context.id:\\n status = \\\"public\\\"\\n else:\\n if previous_versions and previous_versions[-1] == self.context.id:\\n status = \\\"last_closed\\\"\\n elif self.context.id in previous_versions:\\n status = \\\"closed\\\"\\n else:\\n # this is a completely new version not even registered\\n # with the machinery yet\\n status = 'unapproved'\\n return status\",\n \"def show_publish_status(self, obj):\\n if obj.publish_status > 0:\\n return mark_safe(\\\"<span style=\\\\\\\"color: #0c0;\\\\\\\"><b>ALWAYS</b></span> Available\\\")\\n elif obj.publish_status < 0:\\n return mark_safe(\\\"<span style=\\\\\\\"color: #c00;\\\\\\\"><B>NEVER</b></span> Available\\\")\\n else: # it EQUALS zero\\n if obj.live_as_of is None:\\n return \\\"Never Published\\\"\\n else:\\n dstr = obj.live_as_of.strftime(\\\"%x\\\")\\n if is_in_the_future(obj.live_as_of):\\n return mark_safe(\\\"<b>Goes LIVE: %s</b>\\\"% dstr)\\n else:\\n return mark_safe(\\\"<B>LIVE</B> <span style=\\\\\\\"color: #999;\\\\\\\">as of: %s</style>\\\" % dstr)\\n return \\\"???\\\"\",\n \"def gatekeeper_show_publish_status(self, obj):\\n if obj.publish_status > 0:\\n return mark_safe(\\\"<span style=\\\\\\\"color: #0c0;\\\\\\\"><b>ALWAYS</b></span> Available\\\")\\n elif obj.publish_status < 0:\\n return mark_safe(\\\"<span style=\\\\\\\"color: #c00;\\\\\\\"><B>NEVER</b></span> Available\\\")\\n else: # it EQUALS zero\\n if obj.live_as_of is None:\\n return \\\"Never Published\\\"\\n else:\\n dstr = obj.live_as_of.strftime(\\\"%x\\\")\\n if is_in_the_future(obj.live_as_of):\\n return mark_safe(\\\"<b>Goes LIVE: %s</b>\\\"% dstr)\\n else:\\n return mark_safe(\\\"<B>LIVE</B> <span style=\\\\\\\"color: #999;\\\\\\\">as of: %s</style>\\\" % dstr)\\n return \\\"???\\\"\",\n \"def test_public_status_page_get_public_status_pages(self):\\n pass\",\n \"def get_published(self):\\n return self.filter(status=\\\"P\\\")\",\n \"def test_public_status_page_get_public_status_page(self):\\n pass\",\n \"def get_status(self):\\r\\n if self.read_pages == 0:\\r\\n self.status = \\\"unread\\\"\\r\\n elif self.read_pages == self.pages:\\r\\n self.status = \\\"finished\\\"\\r\\n else:\\r\\n self.status = \\\"reading\\\"\\r\\n return self.status\",\n \"def getStatus(entry, vType):\\n data = db.Database(filename=\\\"IFB299.db\\\")\\n fine = data.retrieveFine(vType, entry['Citation_Number'])\\n if fine['Payment_status'] == \\\"Pending\\\":\\n date = dt.datetime.strptime(entry['Date'],'%d/%m/%Y')\\n overdue = dt.datetime.now().date() - date.date()\\n if overdue.days >= 7:\\n return \\\"Overdue\\\"\\n else:\\n return \\\"Pending\\\"\\n else:\\n return \\\"Paid\\\"\",\n \"def aggregate_status(request):\\n try:\\n model = 'item'\\n start_date = request.GET.get('startDate', None)\\n end_date = request.GET.get('endDate', None)\\n\\n items = __getQuerysetGivenInterval(model, start_date, end_date)\\n\\n agg_status = list(items.values('status')\\n .annotate(count=Count('status')))\\n\\n result = {'result': agg_status}\\n\\n return JsonResponse(result, status=200)\\n except BaseException as e:\\n print(e.args)\\n return HttpResponseBadRequest()\",\n \"def week_report_handle(fans_type):\\n\\t#import pdb;pdb.set_trace()\\n\\tlast_day = datetime.date.today()-timedelta(days=datetime.datetime.today().weekday() + 1)\\n\\ttoday = datetime.date.today()\\n\\n\\tfans_pages = FansPage.objects.filter(fans_type=fans_type, date__gte=last_day, date__lte=today).order_by(\\\"date\\\")\\n\\n\\tstart = fans_pages[0]\\n\\tlast = fans_pages[len(fans_pages) - 1]\\n\\n\\t#talk_about_is = (last.talk_about_is - start.talk_about_is) / (start.talk_about_is + 0.0) * 100\\n\\ttalk_about_is = (last.talk_about_is - start.talk_about_is)\\n\\t#total_like_count = (last.total_like_count - start.total_like_count) / (start.total_like_count + 0.0) * 100\\n\\ttotal_like_count = (last.total_like_count - start.total_like_count)\\n\\t#total_fans = (last.total_fans - start.total_fans) / (start.total_fans + 0.0) * 100\\n\\ttotal_fans = (last.total_fans - start.total_fans)\\n\\treturn {\\\"talk_about_is\\\":talk_about_is, \\\"total_like_count\\\":total_like_count, \\\"total_fans\\\":total_fans, \\\"start\\\":start.date, \\\"last\\\":last.date}\",\n \"def _get_published(self):\\n return self.__published\",\n \"def _get_status_from_qry(self):\\n active_deadline = self.get_active_deadline()\\n return active_deadline.status\",\n \"def test_public_status_page_post_public_status_page(self):\\n pass\",\n \"def test_active_and_date_range(self):\\n\\n url = '/%s/job-types/status/?is_active=true&started=%s&ended=%s' % ( self.api,\\n '2016-01-01T00:00:00Z',\\n '2016-01-02T00:00:00Z')\\n response = self.client.generic('GET', url)\\n self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)\\n\\n result = json.loads(response.content)\\n self.assertEqual(len(result['results']), 3)\\n self.assertEqual(result['results'][0]['job_type']['name'], self.job1.job_type.name)\\n self.assertEqual(len(result['results'][0]['job_counts']), 0)\",\n \"def test_paginate(self):\\n db = get_session(self.app)\\n\\n statuses = []\\n with self.app.app_context():\\n p = project(save=True)\\n u = user(save=True)\\n\\n # Create 100 statuses\\n for i in range(30):\\n statuses.append(status(project=p, user=u,\\n created=datetime(2012, 5, 25),\\n save=True))\\n\\n for i in range(30):\\n statuses.append(status(project=p, user=u,\\n created=datetime(2012, 6, 25),\\n save=True))\\n\\n for i in range(40):\\n statuses.append(status(project=p, user=u,\\n created=datetime(2012, 7, 25),\\n save=True))\\n\\n s = db.query(Status).order_by(Status.id)\\n\\n # Test simple pagination\\n page = paginate(s, page=1)\\n\\n eq_(page.pages, 5)\\n\\n eq_(page.has_prev, False)\\n eq_(page.has_next, True)\\n\\n page = paginate(s, page=3)\\n eq_(page.has_prev, True)\\n eq_(page.has_next, True)\\n\\n page = paginate(s, page=5)\\n eq_(page.has_prev, True)\\n eq_(page.has_next, False)\\n\\n # Test date filtered pagination\\n page = paginate(s, page=1, startdate=datetime(2012, 5, 28))\\n eq_(page.pages, 4)\\n\\n page = paginate(s, page=1, startdate=datetime(2012, 5, 28),\\n enddate=datetime(2012, 6, 28))\\n eq_(page.pages, 2)\\n\\n page = paginate(s, page=1, enddate=datetime(2012, 6, 28))\\n eq_(page.pages, 3)\",\n \"def schedule(request,status):\\n\\tnow = datetime.today()\\n\\tsched = Sample.objects.all()\\n\\tif status:\\n\\t\\tsched = Sample.objects.filter(status=status)\\n\\tsched = sched.order_by('date_added')\\n\\tsched = [(now + timedelta(i+1), s) for i,s in enumerate(sched)]\\n\\treturn render_to_response('schedule/schedule.html', \\n\\t\\t\\t\\t\\t\\t\\t{'sched': sched},\\n\\t\\t\\t\\t\\t\\t\\tcontext_instance=RequestContext(request))\",\n \"def historical():\\n\\n return {\\n 'page': 'historical',\\n }\",\n \"def get_status() -> None:\\n assert scraper.get_status() == True\",\n \"def get_page_status_list(self, blogid=1):\\n \\n return self.execute('wp.getPageStatusList', blogid, self.username, self.password)\",\n \"def get_status(cls, request, status):\\n event_status = request.dbsession.query(cls)\\\\\\n .filter_by(status=status).one()\\n return event_status\",\n \"def getStatus():\",\n \"def active(self, **kwargs):\\r\\n now = date.today()\\r\\n return self.visible(is_approved=True, start_date__lte=now, end_date__gte=now, **kwargs)\",\n \"def pfp_status(context):\\n current = context['prescription']\\n return \\\"{0}, {1}, {2}, {3}, {4}\\\".format(\\n current.get_planning_status_display(),\\n current.get_endorsement_status_display(),\\n current.get_approval_status_display(),\\n current.get_ignition_status_display(),\\n current.get_status_display()\\n )\",\n \"def property_details(request, property_id):\\n\\n property = get_object_or_404(Property, pk=property_id)\\n reserved_dates = []\\n\\n reserved_all = Booking.objects.filter(book_property=property, book_check_in__gte=datetime.date.today())\\n for reserved in reserved_all:\\n delta = reserved.book_check_out - reserved.book_check_in\\n\\n for i in range(delta.days + 1):\\n format_date = (reserved.book_check_in + datetime.timedelta(days=i)).strftime(\\\"'%m/%d/%Y'\\\")\\n reserved_dates.append(format_date)\\n # print(format_date)\\n\\n separator = ', '\\n reserved = separator.join(reserved_dates)\\n\\n book_ses = request.session.get('book_ses', [])\\n booked_dates=[]\\n\\n if any(d['property'] == property_id for d in book_ses):\\n # for one_book in book_ses:\\n for i in range(len(book_ses)):\\n one_book = book_ses[i] \\n if(one_book['property'] == property_id):\\n old_in = datetime.datetime.strptime(one_book['check_in'],'%Y-%m-%d')\\n old_out = datetime.datetime.strptime(one_book['check_out'], '%Y-%m-%d') \\n delta_old = old_out-old_in \\n for i in range(delta_old.days + 1):\\n format_date = (old_in + datetime.timedelta(days=i)).strftime(\\\"'%Y-%m-%d'\\\")\\n booked_dates.append(format_date)\\n print('ok')\\n\\n booked = separator.join(booked_dates)\\n\\n context = {\\n 'property': property,\\n 'reserved': reserved,\\n 'booked': booked\\n }\\n\\n return render(request, 'properties/property_details.html', context)\",\n \"def month_report_handle(fans_type):\\n\\tstart = datetime.date.today() - timedelta(days=datetime.date.today().day - 1)\\n\\ttoday = datetime.date.today()\\n\\t#import pdb;pdb.set_trace()\\n\\t#fans_list = [\\\"wwwttshow\\\", \\\"ttshowpet\\\", \\\"draw.fans\\\", \\\"TTShowMusic\\\", \\\"GoodNews.FANS\\\"]\\n\\tfans_pages = FansPage.objects.filter(fans_type=fans_type, date__gte=start, date__lte=today).order_by(\\\"date\\\")\\n\\n\\tstart = fans_pages[0]\\n\\tlast = fans_pages[len(fans_pages) - 1]\\n\\n\\ttalk_about_is = (last.talk_about_is - start.talk_about_is)\\n\\ttotal_like_count = (last.total_like_count - start.total_like_count)\\n\\ttotal_fans = (last.total_fans - start.total_fans)\\n\\treturn {\\\"talk_about_is\\\":talk_about_is, \\\"total_like_count\\\":total_like_count, \\\"total_fans\\\":total_fans, \\\"start\\\":start.date, \\\"last\\\":last.date}\",\n \"def get_time_in_status(self, issue, state):\\n \\n# current_datetime = str(dt.now()).split('.')[0].replace(' ', 'T') # The current datetime\\n\\n if ((issue['fields']['issuetype']['name'] == \\\"Sub-task\\\") and (issue['fields']['status']['name'] == \\\"In Progress\\\")) or \\\\\\n ((issue['fields']['issuetype']['name'] == \\\"New Feature\\\") and (issue['fields']['status']['name'] not in [\\\"Open\\\", \\\"In Progress\\\", \\\"Reopened\\\", \\\"Resolved\\\", \\\"Closed\\\"])):\\n print \\\"Getting time in status for %s\\\" % issue['fields']['status']['name']\\n # At first assume state is first, last and only state in case no changelog, if there's a changelog we'll revise later.\\n # First state create time same as issue created datetime \\n cicdt = dt.strptime(issue['fields']['created'].split('.')[0], \\\"%Y-%m-%dT%H:%M:%S\\\") # Current item create datetime\\n nicd = dt.strptime(str(dt.now()).split('.')[0].replace(' ', 'T'), \\\"%Y-%m-%dT%H:%M:%S\\\") # Next item create datetime\\n diff = nicd - cicdt # Time the issue has been in that state\\n \\n # If there's a changelog history go thru it else use issue create date and current date for time in status\\n # If there's no changelog/histories then we're still in first state, nothing has changed\\n if not len(issue['changelog']['histories']):\\n print \\\"no changelog for %s\\\" % issue['key']\\n self.issue_objs[issue['key']].time_in_status = diff.days\\n else:\\n # If there is a changelog look for the value \\\"status\\\", changes may be something other than status\\n print \\\"There's a changelog for issue %s\\\" % issue['key']\\n# print json.dumps(issue, indent=4)\\n \\n # Go thru changelog histories to see if any of the changes are \\\"status\\\" for this state, also get last status or sprint if New Feature\\n status_change_found = False\\n for histories_item in issue['changelog']['histories']:\\n if ((histories_item['items'][0]['field'] == 'status') and (histories_item['items'][0]['toString'] == state)):\\n print \\\"There's a status change\\\"\\n status_change_found = True\\n \\n # Get oldest sprint and status within config.change_period days ago for New Features \\n if (issue['fields']['issuetype']['name'] == \\\"New Feature\\\") and \\\\\\n ((histories_item['items'][0]['field'] == 'Milestone(s)') or (histories_item['items'][0]['field'] == 'status')):\\n hicdt = dt.strptime(histories_item['created'].split('.')[0], \\\"%Y-%m-%dT%H:%M:%S\\\").date() # histories item create datetime\\n if hicdt < date.today()-timedelta(days=int(self.config.get('default', 'change_period'))):\\n print \\\"change too old %s, getting next histories item\\\" % hicdt\\n continue # If older than config.change_period days then we don't care, get next histories item\\n else:\\n print \\\"recent change %s \\\" % hicdt\\n if histories_item['items'][0]['field'] == 'Milestone(s)':\\n self.issue_objs[issue['key']].last_sprint = histories_item['items'][0]['fromString'] # last sprint if issue less that config.change_period old\\n print \\\"last_sprint %s\\\" % self.issue_objs[issue['key']].last_sprint\\n break # Got the oldest change within change_period\\n if histories_item['items'][0]['field'] == 'status':\\n self.issue_objs[issue['key']].last_status = histories_item['items'][0]['fromString'] # last status if issue less that config.change_period old\\n print \\\"last_status %s\\\" % self.issue_objs[issue['key']].last_status\\n break # Got the oldest change within change_period\\n \\n # If there was a change in status calculate time in status from changelog\\n if(status_change_found):\\n total_days = 0 # Accumulate all the diffs for each time in this state\\n # Go thru changelog histories to see if this issue was in this state before.\\n for i, histories_item in enumerate(issue['changelog']['histories']):\\n # All the different kinds of things that have changed, we're only interested in 'status'\\n \\n # Display all the changelog history items\\n if (0):\\n for k, v in histories_item.items():\\n print \\\"issue['changelog']['histories'] key: %s value: %s\\\" % (k, v)\\n print \\\"issue['changelog']['histories']['items'] %s\\\" % histories_item['items']\\n for item in histories_item['items']:\\n print \\\"histories_item['items'] %s\\\" % item\\n print \\\"histories_item['items'][0] %s\\\" %histories_item['items'][0]\\n for item2 in histories_item['items'][0]:\\n print \\\"histories_item['items'][0] %s %s\\\" % (item2, histories_item['items'][0][item2])\\n \\n # If status record we're interested in is found, look for next status change or use current date for end date\\n # If status \\\"Pending\\\" for New Features or \\\"Open\\\" for Sub-tasks there is no change entry for that, it's first state, use created date.\\n if ((histories_item['items'][0]['field'] == 'status') and (histories_item['items'][0]['toString'] == state)):\\n current_status_create_datetime = histories_item['created'].split('.')[0]\\n \\n # Go thru future history changes until the next status change\\n status_found = False\\n for j in range(i+1, len(issue['changelog']['histories'])):\\n if (issue['changelog']['histories'][j]['items'][0]['field'] == 'status'):\\n next_item_create_date = issue['changelog']['histories'][j]['created'].split('.')[0] # Only next status change not any change\\n print \\\"%s. next histories item created: %s\\\" % (j, next_item_create_date)\\n status_found = True\\n break # Break the for loop, next status found\\n \\n if not status_found: \\n next_item_create_date = str(dt.now()).split('.')[0].replace(' ', 'T') # The current datetime \\n print \\\"No next histories item, using today's date: %s\\\" % (next_item_create_date)\\n \\n cscdt = dt.strptime(current_status_create_datetime, \\\"%Y-%m-%dT%H:%M:%S\\\") # Current status create datetime\\n nicdt = dt.strptime(next_item_create_date, \\\"%Y-%m-%dT%H:%M:%S\\\") # Next item create datetime\\n \\n print \\\"Current status create date for %s: %s\\\" % (issue['key'], cscdt)\\n print \\\"Next item create date for %s: %s\\\" % (issue['key'], nicdt)\\n \\n diff = nicdt - cscdt # The number of days the issue has been in that state\\n total_days += diff.days # Accumulate all the times this issue has been in this state.\\n self.issue_objs[issue['key']].time_in_status = total_days\\n else:\\n self.issue_objs[issue['key']].time_in_status = diff.days # No change in status, days in status is issue created date to now\",\n \"def test_pages_created_happy_case(self):\\n metric = PagesCreated(\\n namespaces=[301, 302, 303],\\n start_date='2013-06-19 00:00:00',\\n end_date='2013-08-21 00:00:00'\\n )\\n results = metric(self.user_ids, self.mwSession)\\n\\n assert_equal(results[self.editors[0].user_id]['pages_created'], 3)\\n assert_equal(results[self.editors[1].user_id]['pages_created'], 1)\",\n \"def _get_archive_status(self):\\n\\t\\t# if we have a result of the search\\n\\t\\t# check if any of our segments are in it\\n\\t\\tfor ele in self.elements:\\n\\t\\t\\tif ele.pool_search():\\n\\t\\t\\t\\tele.status = 'archived'\\n\\t\\t\\telse:\\n\\t\\t\\t\\tele.status = 'pending'\",\n \"def getCMSStatus(self):\\n data = auth.getContent('%s/PageZero?FORMAT=XML' % self._base_url_)\\n data = tree.fromstring(data)\\n\\n s = data.find('PageZeroSample')\\n cms = CMSStatus()\\n try:\\n cms.collection_time = datetime.strptime(s.find('collectionTimeGMT').text+' GMT', '%Y.%m.%d %H:%M:%S %Z')\\n cms.magnetic_field = float(s.find('bField').text)\\n cms.magnet_current = float(s.find('magCur').text)\\n cms.vacuum_pressure = float(s.find('vacuum').text)\\n cms.feds_state['TRG'] = s.find('IO_TRG').text=='IN'\\n cms.feds_state['CSC'] = s.find('IO_CSC').text=='IN'\\n cms.feds_state['DAQ'] = s.find('IO_DAQ').text=='IN'\\n cms.feds_state['DQM'] = s.find('IO_DQM').text=='IN'\\n cms.feds_state['DT'] = s.find('IO_DT').text=='IN'\\n cms.feds_state['ECAL'] = s.find('IO_ECAL').text=='IN'\\n cms.feds_state['ES'] = s.find('IO_ES').text=='IN'\\n cms.feds_state['HCAL'] = s.find('IO_HCAL').text=='IN'\\n cms.feds_state['PIXEL'] = s.find('IO_PIXEL').text=='IN'\\n cms.feds_state['RPC'] = s.find('IO_RPC').text=='IN'\\n cms.feds_state['SCAL'] = s.find('IO_SCAL').text=='IN'\\n cms.feds_state['TRACKER'] = s.find('IO_TRACKER').text=='IN'\\n cms.feds_state['CASTOR'] = s.find('IO_CASTOR').text=='IN'\\n cms.feds_state['HF'] = s.find('IO_HFLUMI').text=='IN'\\n cms.feds_state['CTPPS'] = s.find('IO_CTPPS_TOT').text=='IN'\\n cms.daq_state = s.find('state').text\\n cms.dead_time = float(s.find('deadTimeActivePercent').text)\\n cms.t0_transfer = s.find('tier0Transfer').text=='ON'\\n cms.run_number = int(s.find('runNumber').text)\\n cms.lumi_section = int(s.find('lumiSegmentNr').text)\\n cms.l1_menu = s.find('l1Menu').text\\n cms.hlt_rate = float(s.find('hltRate').text)\\n cms.instant_lumi = float(s.find('instantLumi').text)\\n cms.fill_lumi = float(s.find('lumiFill').text)\\n cms.crossing_angle = float(s.find('angle').text)\\n except AttributeError:\\n print 'ERROR in parsing the CMS status report'\\n pass\\n\\n return cms\",\n \"def task7(self, doc_uuid):\\n page_totalRead ={}\\n page_reads = {} \\n for entry in self.records:\\n if((entry['event_type'] == 'pagereadtime') and (entry['subject_doc_id'] == doc_uuid)):\\n if (entry['subject_page'] in page_totalRead):\\n page_totalRead[entry['subject_page']] += int(entry['event_readtime'])\\n else:\\n page_totalRead[entry['subject_page']] = int(entry['event_readtime'])\\n if(entry['subject_page'] in page_reads):\\n page_reads[entry['subject_page']] += 1\\n else:\\n page_reads[entry['subject_page']] = 1\\n page_meanRead = {}\\n for page in page_totalRead:\\n if (page in page_reads):\\n page_meanRead[page] = page_totalRead[page]/page_reads[page]\\n GUI.show_line(page_meanRead, \\\"Page\\\", \\\"Mean Read Time\\\", \\\"Retention\\\")\",\n \"async def get_status(self):\\n data = await self.gen_req(self.status_url)\\n return data['data']['attributes']['releasedAt'], data['data']['attributes']['version']\",\n \"def test_public_status_page_patch_public_status_page(self):\\n pass\",\n \"def get_status(self):\\n # find status\\n # search in summary file first\\n self.status = \\\"running\\\"\\n status = self.search_summary(\\\"status\\\")\\n if status:\\n self.status = status.split()[1]\\n # define running time\\n # search in summary file first\\n self.running_time = \\\"00:00:00\\\"\\n running_time = self.search_summary(\\\"running-time\\\")\\n if running_time:\\n self.running_time = running_time.split()[1]\\n # calculate running time\\n else:\\n now = datetime.datetime.now()\\n elapsed_time = (now - self.ctime).seconds\\n hours, remainder = divmod(elapsed_time, 3600)\\n minutes, seconds = divmod(remainder, 60)\\n self.running_time = (\\n f\\\"{int(hours):02}:{int(minutes):02}:{int(seconds):02}\\\"\\n )\",\n \"def status(self):\",\n \"def compute_campaign_status(end_date):\\n status = bool('False')\\n if end_date is not None and end_date.strftime('%Y-%m-%d %H:%M') < datetime.now().strftime('%Y-%m-%d %H:%M'):\\n status = bool('True')\\n return status\",\n \"def _get_status(self):\\n if self._state in [\\\"processed\\\", \\\"error\\\"]:\\n return self._state\\n \\n get_resp = requests.get(self.location, cookies={\\\"session\\\": self.session})\\n\\n self._state = get_resp.json()[\\\"status\\\"]\\n self.slice_time = get_resp.json()[\\\"slice_time\\\"]\\n \\n return self._state\",\n \"def is_published(self):\\n now = timezone.now()\\n return now >= self.pub_date\",\n \"def _get_status(self):\\n return self.__status\",\n \"def event_get_status():\\n event = Event.query.filter_by(is_current=True).first() or \\\\\\n Event.query.order_by(Event.id.desc()).first()\\n if not event:\\n return jsonify(status='')\\n return jsonify(status=event.status_text or '')\",\n \"def test_date_range(self):\\n\\n url = '/%s/job-types/status/?started=%s&ended=%s' % ( self.api,\\n '2015-01-01T00:00:00Z',\\n '2015-01-02T00:00:00Z')\\n response = self.client.generic('GET', url)\\n self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)\\n\\n result = json.loads(response.content)\\n self.assertEqual(len(result['results']), 4)\",\n \"def status():\\n _request('worklog/status/')\",\n \"def get_status(self):\\n statuses = dict(PRODUCTHISTORY_CHOICES)\\n return statuses.get(self.status, \\\"N/A\\\")\",\n \"def GetStatus(self):\\r\\n return self.status\",\n \"def test_get_page_of_activities():\\n \\n # get activities on page that won't have activities\\n r = get_page_of_activities(None, 50)\\n assert r.status_code == 200\\n assert r.json() is None\\n\\n # get values only after certain time\\n r = get_page_of_activities(\\\"2020-12-27T19:45:05Z\\\", 1)\\n assert r.status_code == 200\\n # check that all necessary objects are included\\n r_json = r.json()\\n assert r_json is not None\\n assert \\\"id\\\" in r_json\\n assert \\\"type\\\" in r_json\\n assert \\\"start_date\\\" in r_json\\n # check that we only got objects that occured after last_activity_date param\\n for x in r_json:\\n assert datetime.strptime(x[\\\"start_date\\\"], \\\"%Y-%m-%dT%H:%M:%SZ\\\") < datetime.strptime(\\\"2020-12-27T19:45:05Z\\\", \\\"%Y-%m-%dT%H:%M:%SZ\\\")\\n \\n # check that returns all activities on page\\n r_all_none = get_page_of_activities(None, 1)\\n assert r_all_none.status_code == 200\\n r_all_none_json = r_all_none.json()\\n assert r_all_none_json is not None\\n assert \\\"id\\\" in r_all_none_json\\n assert \\\"type\\\" in r_all_none_json\\n assert \\\"start_date\\\" in r_all_none_json\\n # should return all activities because I have none prior to 2020\\n r_all_date = get_page_of_activities(\\\"2019-12-22T19:41:05Z\\\", 1)\\n assert r_all_date.status_code == 200\\n r_all_date_json = r_all_date.json()\\n assert r_all_date_json is not None\\n assert \\\"id\\\" in r_all_date_json\\n assert \\\"type\\\" in r_all_date_json\\n assert \\\"start_date\\\" in r_all_date_json\\n\\n # test to see if both methods to return all activities on page worked\\n assert len(r_all_date_json) == len(r_all_none_json)\\n\\n # try to get activities from future is error\\n r = get_page_of_activities(\\\"2025-12-22T19:41:05Z\\\", 1)\\n assert r.status_code != 200\",\n \"def get_status(self):\\n\\n # update status\\n # TODO: this needs to consider \\\"partial\\\" status based on the testcodes that are defined\\n # in the panel.\\n # get the condition OK aliquot condition instance\\n result_item_cls = models.get_model(self._meta.app_label, 'resultitem')\\n aliquot_condition_ok = AliquotCondition.objects.get_ok()\\n if not self.aliquot.aliquot_condition:\\n # how can this be ??\\n status = 'ERROR'\\n elif result_item_cls.objects.filter(result__order=self) or self.panel.panel_type == 'STORAGE':\\n # test aliquot condition and set the order status\\n if self.aliquot.aliquot_condition == aliquot_condition_ok:\\n status = 'COMPLETE'\\n else:\\n # has results or is stored but condition is not 10\\n # was this meant to be a storage panel?\\n status = 'ERROR'\\n elif self.aliquot.aliquot_condition != aliquot_condition_ok:\\n status = 'REDRAW'\\n else:\\n status = 'PENDING'\\n # regardless of status, check that order was not deleted on DMIS\\n dmis_tools = DmisTools()\\n if dmis_tools.is_withdrawn_order(self):\\n # other aspects of result visibility must consider this value\\n status = 'WITHDRAWN'\\n return status\",\n \"def get_status_stat(qs):\\n return [ { 'status':'total', 'count':qs.count() } ] +\\\\\\n [ { 'status':str(x['status']), 'count':str(x['count']) }\\n for x in qs.values('status').annotate(count=Count('id')) ]\",\n \"def filter_status_as_of(self, status_date: datetime.date) -> QuerySet:\\n return self.model._filter_queryset_status_as_of(self, status_date)\",\n \"def status(self):\\n props = self.properties\\n if props:\\n if props.get('created'):\\n return CREATED_STATUS\",\n \"def test_auto_set_published_on_status_change(self): \\n title = ('Transportation Challenges Limit Education Choices for '\\n 'Denver Parents')\\n summary = \\\"\\\"\\\"\\n Many families in the Denver metro area use public\\n transportation instead of a school bus because for them, a\\n quality education is worth hours of daily commuting. Colorado's\\n school choice program is meant to foster educational equity,\\n but the families who benefit most are those who have time and\\n money to travel. Low-income families are often left in a lurch.\\n \\\"\\\"\\\"\\n byline = \\\"Mile High Connects\\\"\\n story = create_story(title=title, summary=summary, byline=byline)\\n # Default status should be draft \\n self.assertEqual(story.status, 'draft')\\n # and there should be no published date\\n self.assertEqual(story.published, None)\\n story.status = 'published'\\n story.save()\\n self.assertNowish(story.published)\",\n \"def test_auto_set_published_on_status_change(self): \\n title = ('Transportation Challenges Limit Education Choices for '\\n 'Denver Parents')\\n summary = \\\"\\\"\\\"\\n Many families in the Denver metro area use public\\n transportation instead of a school bus because for them, a\\n quality education is worth hours of daily commuting. Colorado's\\n school choice program is meant to foster educational equity,\\n but the families who benefit most are those who have time and\\n money to travel. Low-income families are often left in a lurch.\\n \\\"\\\"\\\"\\n byline = \\\"Mile High Connects\\\"\\n story = create_story(title=title, summary=summary, byline=byline)\\n # Default status should be draft \\n self.assertEqual(story.status, 'draft')\\n # and there should be no published date\\n self.assertEqual(story.published, None)\\n story.status = 'published'\\n story.save()\\n self.assertNowish(story.published)\",\n \"def goalStatus(self, fromdt, todt):\\r\\n ret = {}\\r\\n tot = self.totalSaved(fromdt, todt)\\r\\n\\r\\n return dict([(g, tot - g.amount) for g in self.goals])\",\n \"def get_rebuild_status(self, rebuild_status_url):\\n if getattr(self.settings, 'AK_TEST', False):\\n return self.TEST_DATA.get('get_rebuild_status')\\n res = self.client.get(rebuild_status_url) \\n if res.status_code == 200:\\n res_dict = json.loads(res.text)\\n rv = {'res': res}\\n rv['finished'] = res_dict.get('finished', None)\\n rv['finished_at'] = res_dict.get('finished_at', None)\\n rv['target_count'] = res_dict.get('results', None)\\n return rv\\n else:\\n return None\",\n \"def document_status(document_id: uuid.UUID, db: Session = Depends(get_db)):\\n document_status = get_document_status(db, document_id)\\n return document_status\",\n \"def status_summary(self):\\n base_query_set = super(PeeringSessionManager, self).get_queryset()\\n summary = base_query_set.annotate(\\n label=models.Case(\\n models.When(provisioning_state=2, then=models.Case(\\n models.When(admin_state=2, then=models.Case(\\n models.When(operational_state=6,\\n then=models.Value('Up')),\\n default=models.Value('Down')\\n )),\\n default=models.Value('Admin Down')\\n )),\\n models.When(provisioning_state=1,\\n then=models.Value('Provisioning')),\\n default=models.Value('None'),\\n output_field=models.CharField()\\n )).values('label').annotate(value=models.Count('label'))\\n return summary\",\n \"def test_on_homepage_published_only(self):\\n\\tpublished_titles = (\\n\\t \\\"The Power of Play: Playground Locations in the Children's Corridor\\\",\\n\\t \\\"Birth Trends in the Children's Corridor: Focus on Foreign-born Mothers\\\")\\n\\tunpublished_titles = (\\n\\t \\\"Shattered Dreams: Revitalizing Hope in Original Aurora\\\",\\n\\t \\\"A School Fight Rallies Hinkley High School Mothers to Organize\\\",\\n\\t \\\"Transportation Challenges Limit Education Choices for Denver Parents\\\")\\n\\tfor title in published_titles + unpublished_titles:\\n\\t status = 'draft'\\n\\t if title in published_titles:\\n\\t\\tstatus = 'published'\\n\\t create_story(title=title, on_homepage=True, status=status)\\n\\t\\t\\t \\n\\thomepage_stories = Story.objects.on_homepage()\\n\\tself.assertEqual(homepage_stories.count(), len(published_titles))\\n\\tfor title in published_titles:\\n\\t self.has_story_title(title, homepage_stories)\",\n \"def test_on_homepage_published_only(self):\\n\\tpublished_titles = (\\n\\t \\\"The Power of Play: Playground Locations in the Children's Corridor\\\",\\n\\t \\\"Birth Trends in the Children's Corridor: Focus on Foreign-born Mothers\\\")\\n\\tunpublished_titles = (\\n\\t \\\"Shattered Dreams: Revitalizing Hope in Original Aurora\\\",\\n\\t \\\"A School Fight Rallies Hinkley High School Mothers to Organize\\\",\\n\\t \\\"Transportation Challenges Limit Education Choices for Denver Parents\\\")\\n\\tfor title in published_titles + unpublished_titles:\\n\\t status = 'draft'\\n\\t if title in published_titles:\\n\\t\\tstatus = 'published'\\n\\t create_story(title=title, on_homepage=True, status=status)\\n\\t\\t\\t \\n\\thomepage_stories = Story.objects.on_homepage()\\n\\tself.assertEqual(homepage_stories.count(), len(published_titles))\\n\\tfor title in published_titles:\\n\\t self.has_story_title(title, homepage_stories)\",\n \"def status( self ):\\n duration = datetime.datetime.now() - self.startTime\\n status = {\\n 'start': self.startTime.isoformat(),\\n 'now': datetime.datetime.now().isoformat(),\\n 'duration': duration.total_seconds(),\\n 'bookmark': 0,\\n 'events': 0,\\n 'cumulative_rate': 0,\\n 'processes': [],\\n 'state': {\\n 'id': self.state,\\n 'description': definitions.STATE_STRING[self.state]\\n }\\n }\\n\\n # Sending pipes to processes which are not running or shutting down\\n # will lead to errors and deadlocks. Loop through to detect errors.\\n if self.state == definitions.STATE_RUNNING:\\n # Loop through all processes and just check we're running properly\\n for proxy in self.processes:\\n if not proxy.process.is_alive():\\n self.logger.info( 'Process {0} is dead.'.format( proxy.name ))\\n self.state = definitions.STATE_ERROR\\n break\\n\\n if proxy.request( 'status' )['state'] == definitions.STATE_ERROR:\\n self.logger.info( 'Process {0} state is {1}.'.format(\\n proxy.name,\\n definitions.STATE_STRING[ definitions.STATE_ERROR ]\\n ))\\n\\n self.state = definitions.STATE_ERROR\\n break\\n\\n # Now do the actual status checks\\n if self.state == definitions.STATE_RUNNING:\\n # Loop through processes in order\\n for proxy in self.processes:\\n response = proxy.request('status')\\n\\n proc = {\\n 'name': proxy.name,\\n 'pid': proxy.process.pid,\\n 'count': response['count'],\\n 'sleep': response['sleep']\\n }\\n\\n status['events'] = proc['count']\\n status['processes'].append( proc )\\n\\n if 'bookmark' in response:\\n status['bookmark'] = response['bookmark']\\n\\n status['cumulative_rate'] = round(\\n status['events'] / duration.total_seconds(), 2)\\n\\n return status\",\n \"def normalize_dates(end_date, start_date, today_date):\\n if start_date < today_date or end_date < today_date:\\n return {'status': False, 'message': 'Sorry, you cannot enter a past date'}\\n elif end_date < start_date:\\n return {'status': False, 'message': 'Sorry, end date must be after start date'}\\n else:\\n return {'status': True, 'message': 'Validation successful'}\",\n \"def get_published_date(self):\\n return self._get_date_or_timestamp('published')\",\n \"def calc_published_state(self, state: str, path: Path, reference_image_count: int) -> str:\\n\\n if not (path.exists() and state == 'published'):\\n return \\\"\\\"\\n\\n\\n # noinspection PyTypeChecker\\n ig_file_count = 0\\n for root, dirs, files in os.walk(path):\\n\\n # Trivial case\\n if not Path(root,'archive').exists():\\n return self._web_pub_text\\n\\n for image_groups in os.scandir(join(root, 'archive')):\\n if not image_groups.is_dir():\\n continue\\n for ig_root, ig_dirs, ig_files in os.walk(image_groups):\\n ig_file_count += len(ig_files)\\n\\n # approximate\\n return self._web_pub_text if float(ig_file_count) < (\\n 0.3 * float(reference_image_count)) else self._full_pub_text\",\n \"def check_status():\\n logger.debug(\\\"Starting the check_status() routine.\\\")\\n\\n url = \\\"https://www.toggl.com/api/v8/time_entries/current\\\"\\n token = os.environ[\\\"TOGGL_API_TOKEN\\\"]\\n auth_token = base64.b64encode(f\\\"{token}:api_token\\\".encode()).decode()\\n resp = requests.get(url, headers={\\\"Authorization\\\": \\\"Basic \\\" + auth_token})\\n\\n cols = \\\"id\\\", \\\"duration\\\", \\\"description\\\"\\n status = {k: v for k, v in (resp.json()[\\\"data\\\"] or {}).items() if k in cols}\\n logger.debug(f\\\"{'Something' if 'id' in status else 'Something'} is being tracked.\\\")\\n\\n return status\",\n \"def get_status(request):\\n ecc_server_status_list = get_ecc_server_statuses(request)\\n data_router_status_list = get_data_router_statuses(request)\\n overall_state, overall_state_name = calculate_overall_state(request)\\n\\n current_run = request.experiment.latest_run\\n if current_run is not None:\\n run_number = current_run.run_number\\n start_time = current_run.start_datetime.strftime('%b %d %Y, %H:%M:%S')\\n duration_str = current_run.duration_string\\n run_title = current_run.title\\n run_class = current_run.get_run_class_display()\\n else:\\n run_number = None\\n start_time = None\\n duration_str = None\\n run_title = None\\n run_class = None\\n\\n output = {\\n 'overall_state': overall_state,\\n 'overall_state_name': overall_state_name,\\n 'ecc_server_status_list': ecc_server_status_list,\\n 'data_router_status_list': data_router_status_list,\\n 'run_number': run_number,\\n 'start_time': start_time,\\n 'run_duration': duration_str,\\n 'run_title': run_title,\\n 'run_class': run_class,\\n }\\n\\n return output\",\n \"def test_status_weeks_at_year_end(self):\\n d = datetime(2014, 1, 1, 12, 13, 45, 0)\\n with self.app.app_context():\\n u = user(username='testuser', save=True)\\n s = status(content='my status update', created=d, user=u, save=True)\\n eq_(s.week_start.strftime(\\\"%Y-%m-%d\\\"), \\\"2013-12-30\\\")\\n eq_(s.week_end.strftime(\\\"%Y-%m-%d\\\"), \\\"2014-01-05\\\")\",\n \"def generate_status_page():\\n status = renew_status()\\n now = datetime.datetime.now()\\n\\n # update statistics\\n update_statistics(status)\\n\\n # add stats to status\\n status = add_statistics_to_status(status)\\n\\n # calculate datetime from oldest key\\n stats_first = datetime.datetime.strptime(\\n overall_oldest_key, '%Y%m%d%H%M')\\n\\n # downtimes\\n if 'display_downtimes' in CONFIG and CONFIG['display_downtimes']:\\n display_downtimes = True\\n downtimes = [{\\n 'host': host[0],\\n 'downtimes': get_downtimes(host[0]),\\n } for host in CONFIG['hosts']]\\n else:\\n display_downtimes = False\\n downtimes = []\\n\\n # load template\\n with open(CONFIG['template_file']) as template_file:\\n template = Template(template_file.read())\\n print(template.render({\\n 'time': _format_datetime(now),\\n 'status': status,\\n 'stats_first': _format_datetime(stats_first),\\n 'display_downtimes': display_downtimes,\\n 'downtimes': downtimes,\\n 'title': CONFIG['title'],\\n 'refresh_interval': CONFIG['refresh_interval'],\\n }))\",\n \"def getPublishedTime(self): #$NON-NLS-1$\\r\",\n \"def status(self):\\n r = requests.get('/'.join([self.base_url, self.ENDPOINT_STATUS]))\\n return r.json()\",\n \"def test_status_weeks_at_year_start(self):\\n d = datetime(2013, 12, 31, 12, 13, 45, 0)\\n with self.app.app_context():\\n u = user(username='testuser', save=True)\\n s = status(content='my status update', created=d, user=u, save=True)\\n eq_(s.week_start.strftime(\\\"%Y-%m-%d\\\"), \\\"2013-12-30\\\")\\n eq_(s.week_end.strftime(\\\"%Y-%m-%d\\\"), \\\"2014-01-05\\\")\",\n \"def get_object_status(obj):\\n return get_object_parameter(obj, 'status')\",\n \"def get_status(intervention: dict) -> dict:\\n for key, values in intervention.items():\\n if not values:\\n intervention['status'] = \\\"Brouillon\\\"\\n break\\n\\n if intervention.get('date_intervention'):\\n if not intervention.get('status'):\\n if intervention['date_intervention'] < datetime.now():\\n intervention['status'] = \\\"Terminée\\\"\\n else:\\n intervention['status'] = \\\"Validée\\\"\\n\\n intervention['date_intervention'] = intervention['date_intervention'].strftime(\\\"%m/%d/%Y %H:%M:%S\\\")\\n\\n return intervention\",\n \"def _updated_or_published(mf):\\n\\n\\tprops = mf['properties']\\n\\n\\t# construct updated/published date of mf\\n\\tif 'updated' in props:\\n\\t\\treturn props['updated'][0]\\n\\telif 'published' in props:\\n\\t\\treturn props['published'][0]\\n\\telse:\\n\\t\\treturn None\",\n \"def build_progress_report(self):\\n report = super(self.__class__, self).build_progress_report()\\n report['publishing'] = self._generate_publishing_section()\\n return report\",\n \"def get_status(self, render_via_ajax):\\r\\n ugettext = self.system.service(self, \\\"i18n\\\").ugettext\\r\\n status_list = []\\r\\n current_task_human_name = \\\"\\\"\\r\\n for i in xrange(0, len(self.task_xml)):\\r\\n human_task_name = self.extract_human_name_from_task(self.task_xml[i])\\r\\n human_task_name = ugettext(human_task_name)\\r\\n # Extract the name of the current task for screen readers.\\r\\n if self.current_task_number == i:\\r\\n current_task_human_name = human_task_name\\r\\n task_data = {\\r\\n 'task_number': i + 1,\\r\\n 'human_task': human_task_name,\\r\\n 'current': self.current_task_number == i\\r\\n }\\r\\n status_list.append(task_data)\\r\\n\\r\\n context = {\\r\\n 'status_list': status_list,\\r\\n 'grader_type_image_dict': GRADER_TYPE_IMAGE_DICT,\\r\\n 'legend_list': LEGEND_LIST,\\r\\n 'render_via_ajax': render_via_ajax,\\r\\n 'current_task_human_name': current_task_human_name,\\r\\n }\\r\\n status_html = self.system.render_template(\\r\\n \\\"{0}/combined_open_ended_status.html\\\".format(self.TEMPLATE_DIR), context\\r\\n )\\r\\n\\r\\n return status_html\",\n \"def test_build_status_page_from_desired_state(\\n status_page_v1: StatusPageV1,\\n):\\n page = build_status_page(status_page_v1)\\n assert page.name == \\\"page\\\"\\n assert len(page.components) == 2\\n assert {c.group_name for c in page.components if c.group_name} == {\\\"group-1\\\"}\\n assert {c.name for c in page.components} == {\\\"ai-component-1\\\", \\\"ai-component-2\\\"}\",\n \"def customer_summary(self, status='fully-paid', billtype=None, start_date=None, end_date=None):\\n query = self.get_queryset()\\n if status == 'fully-paid':\\n query = query.filter(status=status)\\n if status == 'pending':\\n query = query.filter(status=status)\\n if billtype:\\n query = query.filter(billtype__name=billtype)\\n if start_date and end_date:\\n query = query.filter(\\n models.Q(month__gte=start_date) &\\n models.Q(month__lte=end_date)\\n )\\n\\n return query.aggregate(models.Sum('amount'))['amount__sum']\",\n \"def queryset(self, request):\\r\\n TODAY = datetime.date.today()\\r\\n YEAR = int(TODAY.year)\\r\\n qs = super(PresentationAdmin, self).queryset(request)\\r\\n start_date = datetime.date(YEAR, 1, 1)\\r\\n return qs.filter(date_created__gte=start_date)\",\n \"def _publish_status(self, state='complete'):\\n self.logger.debug('Recording catalog status: \\\"{}\\\"'.format(state))\\n self.status_table.update_item(\\n {'api_version': self.api_version},\\n {\\n 'state': state,\\n 'timestamp': time.strftime(\\\"%Y-%m-%dT%H:%M:%SZ\\\"),\\n 'catalog_url': '{0}/v{1}/catalog.json'.format(self.api_url, self.api_version)\\n }\\n )\",\n \"def getMyDocumentsInProgress( self, REQUEST=None, member=None, check_only=None ):\\n results = {}\\n now = DateTime()\\n\\n membership = getToolByName( self, 'portal_membership' )\\n metadata = getToolByName( self, 'portal_metadata' )\\n username = member or membership.getAuthenticatedMember().getUserName()\\n\\n if REQUEST is not None:\\n period = int(REQUEST.get('period', '0'))\\n else:\\n period = None\\n\\n indexes = {}\\n indexes['Creator'] = [ username ]\\n indexes['implements'] = [ 'isVersionable' ]\\n if period:\\n days = period == 5 and 90 or period == 4 and 30 or period == 3 and 14 or period == 2 and 7 or 0\\n if days > 0:\\n created_till = DateTime()\\n created_from = created_till - float(days * 3600 * 24) / 86400\\n indexes['created'] = { 'query' : ( created_from, created_till and created_till + 0.99999 ), 'range' : 'min:max' }\\n else:\\n now = DateTime()\\n created_from = DateTime(int(now.strftime('%Y')), int(now.strftime('%m')), int(now.strftime('%d')))\\n indexes['created'] = { 'query' : created_from, 'range' : 'min' }\\n\\n documents = self.searchResults( type='query', REQUEST=REQUEST, **indexes )\\n\\n if check_only:\\n if not documents: return 0\\n elif not documents:\\n return ( 0, [] )\\n\\n for r in documents:\\n obj = r.getObject()\\n if obj is None:\\n continue\\n if not username in membership.getObjectOwners( obj ):\\n continue\\n if not ( obj.implements('isDocument') or obj.implements('isVersionable') ):\\n continue\\n\\n category = obj.Category()\\n\\n if not results.has_key(category):\\n results[category] = []\\n\\n info = {}\\n\\n info['document_title'] = obj.Title().strip()\\n obj_description = obj.Description().strip()\\n info['document_description'] = info['document_title'] != obj_description and obj_description\\n info['creator'] = obj.Creator()\\n info['creation_date'] = r['created']\\n info['recipient_agency'] = CustomAttributeValue( obj, 'recipient_agency' )\\n\\n executor = CustomAttributeValue( obj, 'executor' )\\n if executor:\\n info['executor'] = type(executor) not in ( ListType, TupleType ) and [ executor ] or executor\\n else:\\n info['executor'] = []\\n\\n signatory = CustomAttributeValue( obj, 'signatory' )\\n if signatory:\\n if type(signatory) not in ( ListType, TupleType ):\\n signatory = [ signatory ]\\n info['signatory'] = [ x for x in signatory if x not in info['executor'] ]\\n else:\\n info['signatory'] = []\\n\\n info['registry_id'] = obj.registry_ids() and obj.getInfoForLink( mode=2 ) or ''\\n info['resolution'] = obj.getDocumentResolution( no_absolute=1 )\\n info['view_url'] = obj.absolute_url( canonical=1, no_version=1 ) + '/view?expand=1'\\n info['new'] = 0\\n\\n try: effective_date = int((now - info['creation_date']) * 10**8)\\n except: effective_date = 0\\n\\n info['sortkey'] = ( '0000000000' + str(effective_date) )[ -10: ]\\n results[ category ].append( info )\\n\\n interrupt_thread( self )\\n\\n if check_only: return len(results.keys()) > 0 and 1 or 0\\n\\n res = []\\n custom_categories = CustomCategoryIds()\\n max_categories = len(custom_categories)\\n\\n for category in results.keys():\\n x = max_categories\\n for n in range(0, max_categories):\\n if category == custom_categories[n]:\\n x = n\\n break\\n\\n category_title = ( x < max_categories and category[4:]+'s' ) or 'Another Documents'\\n res.append( ( x, category_title, results[ category ] ) )\\n\\n res.sort()\\n\\n results = []\\n total = 0\\n\\n for x, category, documents in res:\\n results.append( { 'category' : category, 'documents' : documents } )\\n total += len( documents )\\n\\n if check_only: return total > 0 and 1 or 0\\n return ( total, results )\",\n \"def get(self):\\n\\n return self.get_request_handler(request.headers).get_all_employment_status()\",\n \"def was_published_recently(self):\\n now = timezone.now()\\n return now - datetime.timedelta(days=1) <= self.pub_date <= now\",\n \"def test_public_status_page_get_authorizations_for_public_status_page(self):\\n pass\",\n \"def get_state_in_period(course_key, from_date, to_date):\\n enrollment_stat = (\\n EnrollmentTabCache.objects\\n .filter(course_id=course_key, created__range=(from_date, to_date))\\n .values('unenroll', 'enroll', 'total', 'created')\\n .order_by('created')\\n )\\n return enrollment_stat\",\n \"def get_status_for_experiment(self, id):\\n # open = 'open'\\n running = 'running'\\n finished = 'finished'\\n waiting = 'waiting'\\n\\n experiment = Experiment.get(id)\\n date_time_now = datetime.datetime.now()\\n start_datetime = experiment.startDatetime\\n end_datetime = experiment.endDatetime\\n if start_datetime >= end_datetime:\\n # validate this earlier\\n return None\\n if start_datetime <= date_time_now and date_time_now <= end_datetime:\\n return running\\n elif date_time_now > end_datetime:\\n return finished\\n elif date_time_now < start_datetime:\\n return waiting\\n return None\",\n \"def published_after(self) -> Type[QuerySet]:\\n return Post.objects.filter(published__gt=self.published, published__lt=timezone.now()) if self.is_published() else Post.objects.none()\",\n \"def update_campaign_status(self):\\n if self.status == CAMPAIGN_STATUS.START:\\n return \\\"<a href='%s'>Pause</a> | <a href='%s'>Abort</a> | <a href='%s'>Stop</a>\\\" % \\\\\\n (reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.PAUSE]),\\n reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.ABORT]),\\n reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.END]))\\n\\n if self.status == CAMPAIGN_STATUS.PAUSE:\\n return \\\"<a href='%s'>Start</a> | <a href='%s'>Abort</a> | <a href='%s'>Stop</a>\\\" % \\\\\\n (reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.START]),\\n reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.ABORT]),\\n reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.END]))\\n\\n if self.status == CAMPAIGN_STATUS.ABORT:\\n return \\\"<a href='%s'>Start</a> | <a href='%s'>Pause</a> | <a href='%s'>Stop</a>\\\" % \\\\\\n (reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.START]),\\n reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.PAUSE]),\\n reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.END]))\\n\\n if self.status == CAMPAIGN_STATUS.END:\\n return \\\"<a href='%s'>Start</a> | <a href='%s'>Pause</a> | <a href='%s'>Abort</a>\\\" % \\\\\\n (reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.START]),\\n reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.PAUSE]),\\n reverse('dialer_campaign.views.update_campaign_status_admin',\\n args=[self.pk, CAMPAIGN_STATUS.ABORT]))\",\n \"def _get_state_for_date(squadron_url: str, date_number: str, base_state: dict) -> dict:\\n state = base_state.copy()#don't mutate the original\\n state['__EVENTTARGET'] = 'ctrlCalendar'\\n state['__EVENTARGUMENT'] = date_number\\n html_string = _get_page_html(squadron_url, state)\\n date_state = _get_state_values_from_html(html_string)\\n return date_state\",\n \"def _do_status(self) -> Dict[str, Any]:\\n return {}\",\n \"def _do_status(self) -> Dict[str, Any]:\\n return {}\",\n \"def get_pp_status(case_dict):\\n # ---------------------------------------------------------------------\\n logger.debug(\\\"get_pp_status\\\")\\n\\n # initialize status variables\\n msg_avg = dict()\\n msg_diags = dict()\\n diag_comps = [\\\"atm\\\", \\\"ice\\\", \\\"lnd\\\", \\\"ocn\\\"]\\n\\n pp_dir = os.path.join(case_dict[\\\"CASEROOT\\\"], \\\"postprocess\\\")\\n pp_log_dir = os.path.join(case_dict[\\\"CASEROOT\\\"], \\\"postprocess\\\", \\\"logs\\\")\\n\\n msg_avg[\\\"atm\\\"] = \\\"COMPLETED SUCCESSFULLY\\\"\\n msg_diags[\\\"atm\\\"] = \\\"Successfully completed generating atmosphere diagnostics\\\"\\n case_dict[\\\"atm_avg_dates\\\"] = case_dict[\\\"atm_diag_dates\\\"] = get_diag_dates(\\n \\\"atm\\\", pp_dir\\n )\\n\\n msg_avg[\\\"ice\\\"] = \\\"Successfully completed generating ice climatology averages\\\"\\n msg_diags[\\\"ice\\\"] = \\\"Successfully completed generating ice diagnostics\\\"\\n case_dict[\\\"ice_avg_dates\\\"] = case_dict[\\\"ice_diag_dates\\\"] = get_diag_dates(\\n \\\"ice\\\", pp_dir\\n )\\n\\n msg_avg[\\\"lnd\\\"] = \\\"COMPLETED SUCCESSFULLY\\\"\\n msg_diags[\\\"lnd\\\"] = \\\"Successfully completed generating land diagnostics\\\"\\n case_dict[\\\"lnd_avg_dates\\\"] = case_dict[\\\"lnd_diag_dates\\\"] = get_diag_dates(\\n \\\"lnd\\\", pp_dir\\n )\\n\\n msg_avg[\\\"ocn\\\"] = \\\"Successfully completed generating ocean climatology averages\\\"\\n msg_diags[\\\"ocn\\\"] = \\\"Successfully completed generating ocean diagnostics\\\"\\n case_dict[\\\"ocn_avg_dates\\\"] = case_dict[\\\"ocn_diag_dates\\\"] = get_diag_dates(\\n \\\"ocn\\\", pp_dir\\n )\\n\\n for comp in diag_comps:\\n case_dict[comp + \\\"_avg_status\\\"] = \\\"Unknown\\\"\\n case_dict[comp + \\\"_diag_status\\\"] = \\\"Unknown\\\"\\n\\n if comp != \\\"ocn\\\":\\n case_dict[comp + \\\"_avg_path\\\"] = os.path.join(\\n case_dict[\\\"DOUT_S_ROOT\\\"], comp, \\\"proc/climo\\\"\\n )\\n case_dict[comp + \\\"_avg_size\\\"] = get_disk_usage(\\n case_dict[comp + \\\"_avg_path\\\"]\\n )\\n case_dict[comp + \\\"_diag_path\\\"] = os.path.join(\\n case_dict[\\\"DOUT_S_ROOT\\\"], comp, \\\"proc/diag\\\"\\n )\\n case_dict[comp + \\\"_diag_size\\\"] = get_disk_usage(\\n case_dict[comp + \\\"_diag_path\\\"]\\n )\\n else:\\n case_dict[comp + \\\"_avg_path\\\"] = os.path.join(\\n case_dict[\\\"DOUT_S_ROOT\\\"], comp, \\\"proc/climo*\\\"\\n )\\n case_dict[comp + \\\"_avg_size\\\"] = get_ocn_disk_usage(\\n case_dict[comp + \\\"_avg_path\\\"]\\n )\\n case_dict[comp + \\\"_diag_path\\\"] = os.path.join(\\n case_dict[\\\"DOUT_S_ROOT\\\"], comp, \\\"proc/diag*\\\"\\n )\\n case_dict[comp + \\\"_diag_size\\\"] = get_ocn_disk_usage(\\n case_dict[comp + \\\"_diag_path\\\"]\\n )\\n\\n avg_logs = list()\\n avg_file_pattern = \\\"{0}/{1}_averages.log.*\\\".format(pp_log_dir, comp)\\n avg_logs = glob.glob(avg_file_pattern)\\n\\n if avg_logs:\\n log_file = max(avg_logs, key=os.path.getctime)\\n if is_last_process_complete(\\n log_file, msg_avg[comp], \\\"Average list complies with standards.\\\"\\n ):\\n case_dict[comp + \\\"_avg_status\\\"] = \\\"Succeeded\\\"\\n else:\\n case_dict[comp + \\\"_avg_status\\\"] = \\\"Started\\\"\\n\\n diag_logs = list()\\n diag_file_pattern = \\\"{0}/{1}_diagnostics.log.*\\\".format(pp_log_dir, comp)\\n diag_logs = glob.glob(diag_file_pattern)\\n\\n if diag_logs:\\n log_file = max(diag_logs, key=os.path.getctime)\\n if is_last_process_complete(log_file, msg_diags[comp], \\\"ncks version\\\"):\\n case_dict[comp + \\\"_diag_status\\\"] = \\\"Succeeded\\\"\\n else:\\n case_dict[comp + \\\"_diag_status\\\"] = \\\"Started\\\"\\n\\n # get overall timeseries status\\n case_dict[\\\"timeseries_status\\\"] = \\\"Unknown\\\"\\n case_dict[\\\"timeseries_path\\\"] = get_pp_path(pp_dir, \\\"timeseries\\\")\\n case_dict[\\\"timeseries_size\\\"] = 0\\n case_dict[\\\"timeseries_dates\\\"] = \\\"{0}-{1}\\\".format(\\n case_dict[\\\"RUN_STARTDATE\\\"].replace(\\\"-\\\", \\\"\\\"),\\n case_dict[\\\"RUN_STARTDATE\\\"].replace(\\\"-\\\", \\\"\\\"),\\n )\\n case_dict[\\\"timeseries_total_time\\\"] = 0\\n tseries_logs = list()\\n tseries_file_pattern = \\\"{0}/timeseries.log.*\\\".format(pp_log_dir)\\n tseries_logs = glob.glob(tseries_file_pattern)\\n if tseries_logs:\\n log_file = max(tseries_logs, key=os.path.getctime)\\n if is_last_process_complete(\\n filepath=log_file, expect_text=\\\"Successfully completed\\\", fail_text=\\\"opening\\\"\\n ):\\n case_dict[\\\"timeseries_status\\\"] = \\\"Succeeded\\\"\\n with open(log_file, \\\"r\\\") as fname:\\n log_content = fname.readlines()\\n total_time = [line for line in log_content if \\\"Total Time:\\\" in line]\\n case_dict[\\\"timeseries_total_time\\\"] = \\\" \\\".join(total_time[0].split())\\n else:\\n case_dict[\\\"timeseries_status\\\"] = \\\"Started\\\"\\n sta_dates = case_dict[\\\"sta_last_date\\\"].split(\\\"-\\\")\\n case_dict[\\\"timeseries_dates\\\"] = \\\"{0}-{1}\\\".format(\\n case_dict[\\\"RUN_STARTDATE\\\"].replace(\\\"-\\\", \\\"\\\"), \\\"\\\".join(sta_dates[:-1])\\n )\\n for comp in _pp_tseries_comps:\\n tseries_path = \\\"{0}/{1}/proc/tseries\\\".format(\\n case_dict[\\\"timeseries_path\\\"], comp\\n )\\n case_dict[\\\"timeseries_size\\\"] += get_disk_usage(tseries_path)\\n\\n # get iconform status = this initializes files in the POSTPROCESS_PATH\\n case_dict[\\\"iconform_status\\\"] = \\\"Unknown\\\"\\n case_dict[\\\"iconform_path\\\"] = \\\"\\\"\\n case_dict[\\\"iconform_size\\\"] = 0\\n case_dict[\\\"iconform_dates\\\"] = case_dict[\\\"timeseries_dates\\\"]\\n\\n iconform_logs = list()\\n iconform_file_pattern = \\\"{0}/iconform.log.*\\\".format(pp_log_dir)\\n iconform_logs = glob.glob(iconform_file_pattern)\\n if iconform_logs:\\n log_file = max(iconform_logs, key=os.path.getctime)\\n if is_last_process_complete(\\n log_file,\\n \\\"Successfully created the conform tool\\\",\\n \\\"Running createOutputSpecs\\\",\\n ):\\n case_dict[\\\"iconform_status\\\"] = \\\"Succeeded\\\"\\n else:\\n case_dict[\\\"iconform_status\\\"] = \\\"Started\\\"\\n\\n # get xconform status\\n case_dict[\\\"xconform_path\\\"] = \\\"\\\"\\n case_dict[\\\"xconform_path\\\"] = get_pp_path(pp_dir, \\\"xconform\\\")\\n case_dict[\\\"xconform_status\\\"] = \\\"Unknown\\\"\\n case_dict[\\\"xconform_size\\\"] = get_disk_usage(case_dict[\\\"xconform_path\\\"])\\n case_dict[\\\"xconform_dates\\\"] = case_dict[\\\"timeseries_dates\\\"]\\n case_dict[\\\"xconform_total_time\\\"] = 0\\n\\n xconform_logs = list()\\n xconform_file_pattern = \\\"{0}/xconform.log.*\\\".format(pp_log_dir)\\n xconform_logs = glob.glob(xconform_file_pattern)\\n if xconform_logs:\\n log_file = max(xconform_logs, key=os.path.getctime)\\n if is_last_process_complete(\\n log_file,\\n \\\"Successfully completed converting all files\\\",\\n \\\"cesm_conform_generator INFO\\\",\\n ):\\n case_dict[\\\"xconform_status\\\"] = \\\"Succeeded\\\"\\n case_dict[\\\"xconform_size\\\"] = get_disk_usage(case_dict[\\\"xconform_path\\\"])\\n with open(log_file, \\\"r\\\") as fname:\\n log_content = fname.readlines()\\n total_time = [line for line in log_content if \\\"Total Time:\\\" in line]\\n if total_time:\\n case_dict[\\\"xconform_total_time\\\"] = \\\" \\\".join(total_time[0].split())\\n else:\\n case_dict[\\\"xconform_status\\\"] = \\\"Started\\\"\\n\\n return case_dict\",\n \"def date(self):\\n return self.status.created_at\",\n \"def get_status():\\n data = {\\n 'status': 'up',\\n }\\n jsn = json.dumps(data)\\n\\n resp = Response(jsn, status=200, mimetype='application/json')\\n\\n return resp\",\n \"def test_get_ordinal():\\n for (index, status) in enumerate(['draft', 'published', 'archived']):\\n yield (tools.eq_, BlogPostStatus.get_ordinal(status), index)\",\n \"def test_project_recent_statuses(self):\\n with self.app.app_context():\\n p = project(save=True)\\n u = user(save=True)\\n\\n # Create 70 statuses\\n for i in range(70):\\n status(project=p, user=u, save=True)\\n\\n s = status(project=p, user=u, save=True)\\n\\n # Create 30 replies\\n for i in range(30):\\n status(project=p, user=u, reply_to=s, save=True)\\n\\n # Should not include replies\\n page = p.recent_statuses()\\n eq_(page.pages, 4)\",\n \"def test_previous_next_link_status(self):\\n\\n page_states = {\\n 1: {\\n 'expected_previous_status': \\\"disabled\\\",\\n 'expected_next_status': \\\"\\\",\\n },\\n 2: {\\n 'expected_previous_status': \\\"\\\",\\n 'expected_next_status': \\\"\\\",\\n },\\n 50: {\\n 'expected_previous_status': \\\"\\\",\\n 'expected_next_status': \\\"disabled\\\",\\n }\\n }\\n\\n for curr_page, value in page_states.iteritems():\\n previous_link_status, next_link_status = _get_previous_next_link_status(50, curr_page)\\n self.assertEqual(value['expected_previous_status'], previous_link_status)\\n self.assertEqual(value['expected_next_status'], next_link_status)\",\n \"def data_collection_status(self, **kwargs):\\n\\n return self.api_request(self._get_method_fullname(\\\"data_collection_status\\\"), kwargs)\",\n \"def view_date(request, year, month, day):\\n logged_in = request.user.is_authenticated()\\n\\n try:\\n date = datetime.date(int(year), int(month), int(day))\\n except:\\n return HttpResponse('bad date (somehow)')\\n \\n if date > datetime.date.today() and not logged_in:\\n return HttpResponse('this newsletter has yet to be published')\\n\\n items = NewsItem.objects.all().filter(date_to_publish=date).order_by('position')\\n left_sections = {\\n 0: None,\\n 1: None,\\n 2: None,\\n }\\n right_sections = {\\n 3: None,\\n 4: None,\\n 5: None,\\n }\\n extras = []\\n \\n for item in items:\\n item_position = item.position\\n if item.content:\\n if item_position < 3:\\n left_sections[item.position] = item\\n elif item_position <= 5:\\n right_sections[item.position] = item\\n else:\\n extras.append(item)\\n\\n args = {\\n 'left_sections': left_sections,\\n 'right_sections': right_sections,\\n 'extras': extras,\\n 'date': date.isoformat(),\\n 'logged_in': logged_in,\\n 'SUBSITE': SUBSITE,\\n 'CDN': CDN, #included here for when we go live and need a place for people to view the newsletter\\n }\\n return render(request, 'newsletter.html', args)\",\n \"def get_status_data():\\n\\n return dict(\\n celery=_get_celery_status(),\\n users=_get_users_stats(),\\n daemons=_get_daemons_status(),\\n settings=_get_settings(),\\n files=_get_files_status(),\\n languages=_get_languages_status(),\\n sets=_get_sets_status(),\\n )\",\n \"def is_published(self) -> bool:\\n return self.published and self.published <= timezone.now()\",\n \"def test_public_status_page_put_public_status_page(self):\\n pass\",\n \"def test_public_documents_current_endpoint(self):\\n\\n # Grab the current public documents.\\n public_documents_current = self.federal_client.public_inspection_documents_current()\\n\\n # Make sure we have a response.\\n self.assertIsNotNone(public_documents_current)\\n\\n # And make sure we have some results, this should return more than 10.\\n self.assertGreaterEqual(public_documents_current['count'], 10)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68869996","0.613938","0.58442456","0.57751507","0.57710797","0.57653105","0.564951","0.55711806","0.54949707","0.54802895","0.5322023","0.53194374","0.53085303","0.52722406","0.5250116","0.51886964","0.5137271","0.5119178","0.50824904","0.50594455","0.5058787","0.50578064","0.5008095","0.50046563","0.49946377","0.49933183","0.49735945","0.496896","0.4965856","0.4964619","0.4957359","0.495701","0.49499235","0.49400944","0.4929259","0.49202278","0.4918095","0.49160898","0.49094516","0.49054283","0.49001718","0.4885768","0.4871628","0.4855159","0.485141","0.48491138","0.4829343","0.48273894","0.48265204","0.48231965","0.48231965","0.48145595","0.4806825","0.47878549","0.47835284","0.47669214","0.47669214","0.47643608","0.4760505","0.47587308","0.4757553","0.47565436","0.4756453","0.4754998","0.47528878","0.4743153","0.47364658","0.4734314","0.47337776","0.47295177","0.47253856","0.47220385","0.47091892","0.4706461","0.4696427","0.46960387","0.46948797","0.46940058","0.46876016","0.46753278","0.46743214","0.46742818","0.46723032","0.46713975","0.46706748","0.4668132","0.46638468","0.46638468","0.46595934","0.46557584","0.465547","0.46539423","0.46477607","0.46451592","0.4641971","0.46403125","0.46340162","0.46334642","0.46322247","0.46234167"],"string":"[\n \"0.68869996\",\n \"0.613938\",\n \"0.58442456\",\n \"0.57751507\",\n \"0.57710797\",\n \"0.57653105\",\n \"0.564951\",\n \"0.55711806\",\n \"0.54949707\",\n \"0.54802895\",\n \"0.5322023\",\n \"0.53194374\",\n \"0.53085303\",\n \"0.52722406\",\n \"0.5250116\",\n \"0.51886964\",\n \"0.5137271\",\n \"0.5119178\",\n \"0.50824904\",\n \"0.50594455\",\n \"0.5058787\",\n \"0.50578064\",\n \"0.5008095\",\n \"0.50046563\",\n \"0.49946377\",\n \"0.49933183\",\n \"0.49735945\",\n \"0.496896\",\n \"0.4965856\",\n \"0.4964619\",\n \"0.4957359\",\n \"0.495701\",\n \"0.49499235\",\n \"0.49400944\",\n \"0.4929259\",\n \"0.49202278\",\n \"0.4918095\",\n \"0.49160898\",\n \"0.49094516\",\n \"0.49054283\",\n \"0.49001718\",\n \"0.4885768\",\n \"0.4871628\",\n \"0.4855159\",\n \"0.485141\",\n \"0.48491138\",\n \"0.4829343\",\n \"0.48273894\",\n \"0.48265204\",\n \"0.48231965\",\n \"0.48231965\",\n \"0.48145595\",\n \"0.4806825\",\n \"0.47878549\",\n \"0.47835284\",\n \"0.47669214\",\n \"0.47669214\",\n \"0.47643608\",\n \"0.4760505\",\n \"0.47587308\",\n \"0.4757553\",\n \"0.47565436\",\n \"0.4756453\",\n \"0.4754998\",\n \"0.47528878\",\n \"0.4743153\",\n \"0.47364658\",\n \"0.4734314\",\n \"0.47337776\",\n \"0.47295177\",\n \"0.47253856\",\n \"0.47220385\",\n \"0.47091892\",\n \"0.4706461\",\n \"0.4696427\",\n \"0.46960387\",\n \"0.46948797\",\n \"0.46940058\",\n \"0.46876016\",\n \"0.46753278\",\n \"0.46743214\",\n \"0.46742818\",\n \"0.46723032\",\n \"0.46713975\",\n \"0.46706748\",\n \"0.4668132\",\n \"0.46638468\",\n \"0.46638468\",\n \"0.46595934\",\n \"0.46557584\",\n \"0.465547\",\n \"0.46539423\",\n \"0.46477607\",\n \"0.46451592\",\n \"0.4641971\",\n \"0.46403125\",\n \"0.46340162\",\n \"0.46334642\",\n \"0.46322247\",\n \"0.46234167\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7154325"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":81797,"cells":{"query":{"kind":"string","value":"get the list of all existing languages for this page"},"document":{"kind":"string","value":"def get_languages(self):\n titles = Title.objects.filter(page=self)\n if not hasattr(self, \"languages_cache\"):\n languages = []\n for t in titles:\n if t.language not in languages:\n languages.append(t.language)\n self.languages_cache = languages\n return self.languages_cache"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_all_languages():\n\tdef _get():\n\t\tif not frappe.db:\n\t\t\tfrappe.connect()\n\t\treturn frappe.db.sql_list('select name from tabLanguage')\n\treturn frappe.cache().get_value('languages', _get)","def languages(self):\r\n url = '{0}/{1}'.format(self.get_url(), 'languages')\r\n\r\n return http.Request('GET', url), parsers.parse_json","def languages(self):\n\n return self._request('/languages')","def wikiLanguages():\n return languages","def languages():\n r = requests.get('http://translate.yandex.net/api/v1/tr.json/getLangs')\n return r.json['dirs']","def get_langs():\r\n temp = \"\"\r\n translate_client = translate.Client()\r\n for i in translate_client.get_languages():\r\n temp += i['name'] + \": \" + i['language'] + \"\\n\"\r\n\r\n return temp","def get_langs(id):","def get_languages(self):\n language_list = []\n url = '%s%s/languages.xml' % (self.URL_API, self.API_KEY)\n data = urllib.urlopen(url)\n root = cElementTree.parse(data).getroot()\n for language in root.iter('Language'):\n language_list.append(language.find('abbreviation').text)\n return language_list","def fetch_languages(self):\r\n \r\n # tokenize, clean and filter document tokens \r\n toks = [re.sub(r'[^a-zA-Z]','', tok.text.lower().strip()) for tok in self.doc]\r\n toks = [tok for tok in toks if len(tok)>1 and tok in LANGUAGES]\r\n toks = sorted(set(toks))\r\n \r\n return toks","def GetLanguages(cls):\n return sorted(cls._LANGUAGE_PER_TAG.items())","def available_languages(self):\n data = self._run(\n url_path=\"languages/available\"\n )\n return data['result'].get('languages', [])","def languages(self):\n return self._languages","def list(self):\n for key, value in self.languages.iteritems():\n print key, value","def allLocales(self):\n return util.parseLocales(urlopen(self.all_url).read())","def get_languages():\n\n api = (api_name, 'languages')\n\n response = make_request(api=api, action='get', **{})\n status_code = response.status_code\n content = response.text\n\n msg = str(status_code) + ' : ' + content\n \n logger.debug(\"response from spanglish languages: {}\".format(response))\n logger.debug(\"response statuscode from spanglish languages: {}\".format(status_code))\n\n click.echo(\"response message: %s \" % msg)","def book_language_list(request):\n languages = Language.objects.all().order_by('-name')\n return render(request, 'library/book_language_list.html', {\"languages\": languages, })","def getLanguages(self):\n return self.__getColumnData(Q_LANGUAGES, 'language')","def languages(self):\n return LanguageCodes.english_names","def getAvailableLanguages(self):\n url = \"http://www.youtube.com/api/timedtext?v=%s&type=list\" % self.video_id\n xml = urllib2.urlopen(url)\n tree = ET.parse(xml)\n root = tree.getroot()\n languages = {}\n for child in root:\n languages[child.attrib[\"lang_code\"]] = child.attrib[\"lang_translated\"]\n return languages","def get_all(self, lang: str = None):\n pass","def test_get_languages(self):\n languages = get_languages(self.edition_data[\"languages\"])\n self.assertEqual(languages, [\"English\"])","def get_all_languages(with_language_name: bool = False) -> list:\n\n\tdef get_language_codes():\n\t\treturn frappe.get_all(\"Language\", filters={\"enabled\": 1}, pluck=\"name\")\n\n\tdef get_all_language_with_name():\n\t\treturn frappe.get_all(\"Language\", [\"language_code\", \"language_name\"], {\"enabled\": 1})\n\n\tif not frappe.db:\n\t\tfrappe.connect()\n\n\tif with_language_name:\n\t\treturn frappe.cache.get_value(\"languages_with_name\", get_all_language_with_name)\n\telse:\n\t\treturn frappe.cache.get_value(\"languages\", get_language_codes)","def get_native_languages(self):\n return self.userlanguage_set.filter(level='N')","def languages_display(self):\n is_draft = self.extended_object.publisher_is_draft\n node = self.extended_object.node\n current_and_descendant_nodes = node.__class__.get_tree(parent=node)\n\n course_runs = (\n CourseRun.objects.filter(\n direct_course__extended_object__node__in=current_and_descendant_nodes,\n direct_course__extended_object__publisher_is_draft=is_draft,\n )\n .exclude(catalog_visibility=\"hidden\")\n .only(\"languages\")\n )\n languages = list(\n {x for course_languages in course_runs for x in course_languages.languages}\n )\n instance = CourseRun(languages=languages)\n return instance.get_languages_display()","async def langs(self, context):\n languages = get_langs(context.message.guild)\n await context.channel.send(LANG_LIST.format(nb_lang=len(languages), langs=enum(languages)))","def languages(self):\n if not self.has_languages:\n self._languages = dict(self._lodgeit.pastes.getLanguages())\n return self._languages","def find_languages(self, obj):\n languages = set()\n\n def add_langs(item):\n if hasattr(item, 'keys'): # pragma: nocover\n languages.update(item.keys())\n\n for browser in obj.all_browsers:\n add_langs(browser.name)\n add_langs(browser.note)\n\n for feature in chain([obj], obj.child_features):\n add_langs(feature.mdn_uri)\n add_langs(feature.name)\n\n for maturity in obj.all_maturities:\n add_langs(maturity.name)\n\n for reference in obj.all_references:\n add_langs(reference.note)\n\n for section in obj.all_sections:\n add_langs(section.number)\n add_langs(section.name)\n add_langs(section.subpath)\n\n for spec in obj.all_specs:\n add_langs(spec.name)\n add_langs(spec.uri)\n\n for support in obj.all_supports:\n add_langs(support.note)\n\n for version in obj.all_versions:\n add_langs(version.release_notes_uri)\n add_langs(version.note)\n\n if 'zxx' in languages:\n # No linguistic content\n languages.remove('zxx')\n if 'en' in languages:\n languages.remove('en')\n return ['en'] + sorted(languages)\n else:\n return sorted(languages)","def _get_available_languages(self):\n return stopwords.fileids()","def languages(self) -> localedata.LocaleDataDict:\n return self._data['languages']","async def get_multilingual(filename: str):\n query_result = {\"langList\": []}\n database = get_db()\n query_displayname = database.AQLQuery(\n query=main_queries.QUERY_MULTILINGUAL_LANGS,\n bindVars={\n \"filename\": filename\n },\n rawResults=True\n )\n query_result = {\"langList\": query_displayname.result[0]}\n return query_result","def get_languages(request):\n if request.is_ajax():\n publications = Publication.objects.all()\n language_list = []\n for pub in publications:\n languages = pub.languages.all()\n for lang in languages:\n language_list.append({\"pub\": pub.pk,\"pub_name\":pub.name,\"lang\": u\"%s\" % lang.pk,\"name_lang\":lang.alias})\n data = simplejson.dumps(language_list)\n return HttpResponse(data)","def get_learning_languages(self):\n return self.userlanguage_set.exclude(level='N')","def autocomplete_languages():\n languages = Language.query.all()\n return jsonify(json_list=[language.name for language in languages])","def grepo(request):\n return {\n \"GREPO_LANGUAGES\": Language.objects.all().values_list(\"name\", flat=True)\n }","def GetLanguages():\n return GetDataFromCsvFile('languages.csv')","def Languages(self, default=[\"en\"]):\n return self.data.get('metadata', {}).get('languages', default)","def languages():\n return \", \".join(sorted(\"{}: '{}'\".format(gTTS.LANGUAGES[k], k) for k in gTTS.LANGUAGES))","def available_languages():\n utility = queryUtility(ILanguageAvailability)\n if utility is not None:\n return utility.getAvailableLanguages()\n return [DEFAULT_LANGUAGE]","def get_queryset(self):\n\n return Localization.objects.all()","def getLocales(self):\n pass","def langs(cls):\n codes = cls.codes[:]\n\n if hasattr(cls, 'test_codes'):\n codes += cls.test_codes\n\n codes += cls.closed_wikis\n\n # shortcut this classproperty\n cls.langs = {code: f'{code}.{cls.domain}' for code in codes}\n cls.langs.update({alias: f'{code}.{cls.domain}'\n for alias, code in cls.code_aliases.items()})\n\n return cls.langs","def list_project_languages(self, project_id):\n data = self._run(\n url_path=\"languages/list\",\n id=project_id\n )\n return data['result'].get('languages', [])","def languages(query, pos):\n lemma, results = etym(query, pos, ETYMOLOGY)\n languages = set()\n if not results:\n lemma, results = etym(query, None, ETYMOLOGY)\n for result in results:\n languages.update(set(result['languages']))\n return languages","def released_languages_list(self):\r\n if not self.released_languages.strip(): # pylint: disable=no-member\r\n return []\r\n\r\n languages = [lang.strip() for lang in self.released_languages.split(',')] # pylint: disable=no-member\r\n # Put in alphabetical order\r\n languages.sort()\r\n return languages","def list_languages(self):\n known = [ob.capitalize() for ob in self.caller.languages.known_languages]\n known += [\"Arvani\"]\n self.msg(\"{wYou can currently speak:{n %s\" % \", \".join(known))\n self.msg(\n \"You can learn %s additional languages.\"\n % self.caller.languages.additional_languages\n )","async def getLanguages(self, body=\"\"):\n payload = {}\n \n # Parameter validation\n schema = ConfigurationValidator.getLanguages()\n schema.dump(schema.load(payload))\n \n\n url_with_params = await create_url_with_params(api_url=self._urls[\"getLanguages\"], proccessed_params=\"\"\"{\"required\":[],\"optional\":[],\"query\":[],\"headers\":[],\"path\":[]}\"\"\", )\n query_string = await create_query_string()\n headers = {\n \"Authorization\": \"Bearer \" + base64.b64encode(\"{}:{}\".format(self._conf.applicationID, self._conf.applicationToken).encode()).decode()\n }\n if self._conf.locationDetails:\n headers[\"x-location-detail\"] = ujson.dumps(self._conf.locationDetails)\n for h in self._conf.extraHeaders:\n headers.update(h)\n exclude_headers = []\n for key, val in headers.items():\n if not key.startswith(\"x-fp-\"):\n exclude_headers.append(key)\n return await AiohttpHelper().aiohttp_request(\"GET\", url_with_params, headers=get_headers_with_signature(urlparse(self._urls[\"getLanguages\"]).netloc, \"get\", await create_url_without_domain(\"/service/application/configuration/v1.0/languages\", ), query_string, headers, body, exclude_headers=exclude_headers), data=body, cookies=self._conf.cookies)","def get_queryset(self):\r\n username = self.kwargs['username']\r\n return models.LanguagesKnown.objects.filter(username = username).order_by('-id')","def get_languages(self) -> dict:\n request_url = self.__API_URL.format(user=self._user,\n project=self._project)\n response = self._http.request('GET', request_url,\n headers=config.HEADERS)\n\n # Handle limits and wrong responses\n if response.status > 205:\n raise StatusError(status=response.status)\n\n return json.loads(response.data)","def ListConceptLanguages(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def languages_by_id(self, repository_id, access_token=None):\n return self._complete_request_by_id(\n repository_id, \"languages\", access_token)","def getFilteredLanguages(self, data):\n def filterLanguage(dataItem):\n return dataItem['type'] == 'language'\n return list(filter(filterLanguage, data))","def get_localizations(request):\n return JsonResponse(get_all_objects(Localization, LocalizationSerializer), safe=False)","def list_of_langs(data):\n lang_codes = []\n for lang_data in data:\n lang_codes.append(lang_data.get('value'))\n return lang_codes","def get_available_translations(localedir=None):\n\n localedir = localedir or gettext._default_localedir\n\n # usually there are no message files for en\n messagefiles = sorted(glob.glob(localedir + \"/*/LC_MESSAGES/anaconda.mo\") +\n [\"blob/en/blob/blob\"])\n trans_gen = (path.split(os.path.sep)[-3] for path in messagefiles)\n\n langs = set()\n\n for trans in trans_gen:\n parts = parse_langcode(trans)\n lang = parts.get(\"language\", \"\")\n if lang and lang not in langs:\n langs.add(lang)\n # check if there are any locales for the language\n locales = get_language_locales(lang)\n if not locales:\n continue\n\n yield lang","def listSupportedHyphenationLanguages(cls, path=None):\n lib = cls.__getLib()\n\n def listOperation(p):\n return lib.voikkoListSupportedHyphenationLanguages(p)\n\n return cls.__listSupportedLanguagesForOperation(path, lib, listOperation)","def load_languages():\n _langs = []\n with open('conf/languages.csv') as f:\n for _line in f.readlines():\n _langs.append(_line[0:-1]) # chop line separetor\n return _langs","def public_get_languages(\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = PublicGetLanguages.create(\n namespace=namespace,\n )\n return run_request(request, additional_headers=x_additional_headers, **kwargs)","def released_langs(self):\r\n language_options = DarkLangConfig.current().released_languages_list\r\n if settings.LANGUAGE_CODE not in language_options:\r\n language_options.append(settings.LANGUAGE_CODE)\r\n return language_options","def get_report_translations(request):\n\n id_report = request.GET.get('id_report',None)\n if id_report is not None:\n languages = []\n lang = Report.objects.filter(id_report = id_report)\n for el in lang:\n if el.language not in languages:\n languages.append(el.language)\n\n json_resp = {}\n # print(languages)\n json_resp['languages'] = languages\n return JsonResponse(json_resp)","def get_available_languages(domain):\r\n if domain in _AVAILABLE_LANGUAGES:\r\n return copy.copy(_AVAILABLE_LANGUAGES[domain])\r\n\r\n localedir = '%s_LOCALEDIR' % domain.upper()\r\n find = lambda x: gettext.find(domain,\r\n localedir=os.environ.get(localedir),\r\n languages=[x])\r\n\r\n # NOTE(mrodden): en_US should always be available (and first in case\r\n # order matters) since our in-line message strings are en_US\r\n language_list = ['en_US']\r\n # NOTE(luisg): Babel <1.0 used a function called list(), which was\r\n # renamed to locale_identifiers() in >=1.0, the requirements master list\r\n # requires >=0.9.6, uncapped, so defensively work with both. We can remove\r\n # this check when the master list updates to >=1.0, and all projects udpate\r\n list_identifiers = (getattr(localedata, 'list', None) or\r\n getattr(localedata, 'locale_identifiers'))\r\n locale_identifiers = list_identifiers()\r\n for i in locale_identifiers:\r\n if find(i) is not None:\r\n language_list.append(i)\r\n _AVAILABLE_LANGUAGES[domain] = language_list\r\n return copy.copy(language_list)","def getPossibleLangs(self):\n lst = {}\n for e in self._values:\n for lang in e.getLangCodes():\n lst[ lang ] = 1\n return lst.keys()","def get_languages(config_filepath):\n load_classifier(config_filepath)\n print(classifier.get_languages())","async def public_get_languages_async(\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = PublicGetLanguages.create(\n namespace=namespace,\n )\n return await run_request_async(\n request, additional_headers=x_additional_headers, **kwargs\n )","def browserLanguages(request):\n fallback = []\n accepted = request.http_accept_language\n if accepted:\n # Extract the languages names from the string\n accepted = accepted.split(',')\n accepted = map(lambda x: x.split(';')[0], accepted)\n # Add base language for each sub language. If the user specified\n # a sub language like \"en-us\", we will try to to provide it or\n # a least the base language \"en\" in this case.\n for lang in accepted:\n lang = lang.lower()\n fallback.append(lang)\n if '-' in lang:\n baselang = lang.split('-')[0]\n fallback.append(baselang)\n return fallback","def get_language_list_gui():\n _ = get_gettext()\n language = {}\n language['connect'] = _(\"Connect\")\n language['ip'] = _(\"IP\")\n language['netmask'] = _(\"Netmask\")\n language['gateway'] = _('Gateway')\n language['dns'] = _('DNS')\n language['use_static_ip'] = _('Use Static IPs')\n language['use_static_dns'] = _('Use Static DNS')\n language['use_encryption'] = _('Use Encryption')\n language['advanced_settings'] = _('Advanced Settings')\n language['wired_network'] = _('Wired Network')\n language['wired_network_instructions'] = _('To connect to a wired network,'\n ' you must create a network profile. To create a network profile, type a'\n ' name that describes this network, and press Add.')\n language['automatic_connect'] = _('Automatically connect to this network')\n language['secured'] = _('Secured')\n language['unsecured'] = _('Unsecured')\n language['channel'] = _('Channel')\n language['preferences'] = _('Preferences')\n language['wpa_supplicant_driver'] = _('WPA Supplicant Driver')\n language['wireless_interface'] = _('Wireless Interface')\n language['wired_interface'] = _('Wired Interface')\n language['hidden_network'] = _('Hidden Network')\n language['hidden_network_essid'] = _('Hidden Network ESSID')\n language['connected_to_wireless'] = _('Connected to $A at $B (IP: $C)')\n language['connected_to_wired'] = _('Connected to wired network (IP: $A)')\n language['not_connected'] = _('Not connected')\n language['no_wireless_networks_found'] = _('No wireless networks found.')\n language['killswitch_enabled'] = _('Wireless Kill Switch Enabled')\n language['key'] = _('Key')\n language['username'] = _('Username')\n language['password'] = _('Password')\n language['anonymous_identity'] = _('Anonymous Identity')\n language['identity'] = _('Identity')\n language['authentication'] = _('Authentication')\n language['path_to_pac_file'] = _('Path to PAC File')\n language['select_a_network'] = _('Choose from the networks below:')\n language['connecting'] = _('Connecting...')\n language['wired_always_on'] = _('Always show wired interface')\n language['auto_reconnect'] = _('Automatically reconnect on connection loss')\n language['create_adhoc_network'] = _('Create an Ad-Hoc Network')\n language['essid'] = _('ESSID')\n language['use_wep_encryption'] = _('Use Encryption (WEP only)')\n language['before_script'] = _('Run script before connect')\n language['after_script'] = _('Run script after connect')\n language['disconnect_script'] = _('Run disconnect script')\n language['script_settings'] = _('Scripts')\n language['use_ics'] = _('Activate Internet Connection Sharing')\n language['madwifi_for_adhoc'] = _('Check if using madwifi/atheros drivers')\n language['default_wired'] = _('Use as default profile (overwrites any previous default)')\n language['use_debug_mode'] = _('Enable debug mode')\n language['use_global_dns'] = _('Use global DNS servers')\n language['use_default_profile'] = _('Use default profile on wired autoconnect')\n language['show_wired_list'] = _('Prompt for profile on wired autoconnect')\n language['use_last_used_profile'] = _('Use last used profile on wired autoconnect')\n language['choose_wired_profile'] = _('Select or create a wired profile to connect with')\n language['wired_network_found'] = _('Wired connection detected')\n language['stop_showing_chooser'] = _('Stop Showing Autoconnect pop-up temporarily')\n language['display_type_dialog'] = _('Use dBm to measure signal strength')\n language['scripts'] = _('Scripts')\n language['invalid_address'] = _('Invalid address in $A entry.')\n language['global_settings'] = _('Use these settings for all networks sharing this essid')\n language['encrypt_info_missing'] = _('Required encryption information is missing.')\n language['enable_encryption'] = _('This network requires encryption to be enabled.')\n language['wicd_auto_config'] = _('Automatic (recommended)')\n language[\"gen_settings\"] = _(\"General Settings\")\n language[\"ext_programs\"] = _(\"External Programs\")\n language[\"dhcp_client\"] = _(\"DHCP Client\")\n language[\"wired_detect\"] = _(\"Wired Link Detection\")\n language[\"route_flush\"] = _(\"Route Table Flushing\")\n language[\"backend\"] = _(\"Backend\")\n language[\"backend_alert\"] = _(\"Changes to your backend won't occur until the daemon is restarted.\")\n language['0'] = _('0')\n language['1'] = _('1')\n language['2'] = _('2')\n language['3'] = _('3')\n language['4'] = _('4')\n language['5'] = _('5')\n language['6'] = _('6')\n language['7'] = _('7')\n language['8'] = _('8')\n language['9'] = _('9')\n language['interface_down'] = _('Putting interface down...')\n language['resetting_ip_address'] = _('Resetting IP address...')\n language['interface_up'] = _('Putting interface up...')\n language['setting_encryption_info'] = _('Setting encryption info')\n language['removing_old_connection'] = _('Removing old connection...')\n language['generating_psk'] = _('Generating PSK...')\n language['generating_wpa_config'] = _('Generating WPA configuration file...')\n language['flushing_routing_table'] = _('Flushing the routing table...')\n language['configuring_interface'] = _('Configuring wireless interface...')\n language['validating_authentication'] = _('Validating authentication...')\n language['setting_broadcast_address'] = _('Setting broadcast address...')\n language['setting_static_dns'] = _('Setting static DNS servers...')\n language['setting_static_ip'] = _('Setting static IP addresses...')\n language['running_dhcp'] = _('Obtaining IP address...')\n language['dhcp_failed'] = _('Connection Failed: Unable to Get IP Address')\n language['aborted'] = _('Connection Cancelled')\n language['bad_pass'] = _('Connection Failed: Bad password')\n language['done'] = _('Done connecting...')\n return language","def languages(request, region_slug):\n try:\n region = Region.objects.get(slug=region_slug)\n\n result = list(\n map(\n lambda l: {\n \"id\": l.language.id,\n \"code\": l.language.code,\n \"native_name\": l.language.name,\n \"dir\": l.language.text_direction,\n },\n region.language_tree_nodes.filter(active=True),\n )\n )\n return JsonResponse(\n result, safe=False\n ) # Turn off Safe-Mode to allow serializing arrays\n except ObjectDoesNotExist:\n return HttpResponse(\n f'No Region found with name \"{region_slug}\".',\n content_type=\"text/plain\",\n status=404,\n )","def sorted_languages():\n # Python 3: Use functools.cmp_to_key\n def compare(a, b):\n if a.name == u\"English\":\n return -1\n elif b.name == u\"English\":\n return 1\n else:\n return cmp(a, b)\n return sorted(Language.query.all(), cmp=compare)","def languages_by_name(self, username, repository_name, access_token=None):\n return self._complete_request_by_name(\n username, repository_name, \"languages\", access_token)","def langs(cls):\n codes = cls.codes\n\n if hasattr(cls, 'code_aliases'):\n codes += tuple(cls.code_aliases.keys())\n\n return {code: cls.domain for code in codes}","def test_langs(self):\n self._api.Init(lang=\"eng\")\n lang = self._api.GetInitLanguagesAsString()\n self.assertEqual(lang, \"eng\")\n langs = self._api.GetLoadedLanguages()\n self.assertEqual(langs, [\"eng\"])\n self.assertIn(\"eng\", self._api.GetAvailableLanguages())","def overview():\r\n # Update the list of languages allowed on the site, \r\n # except for the language used by your users at that time.\r\n if request.method == 'POST':\r\n lan_object = Languages()\r\n data = lan_object.update()\r\n message = lan_object.message\r\n status = lan_object.status\r\n \r\n # Gets documents from the collections of all languages \r\n languages_list = g.languages_object.get_languages(1)\r\n language_chosen = g.languages_object.get_languages(2)\r\n return render_template( '{}/index.html'.format(MODULE_DIR), **locals())","def get_stores(self):\n # don't be confused by the name here: these are stores, not locales.\n # The website is French-only.\n return self._request_json(\"/locales\")[\"locales\"]","def get_supported_languages ( self ):\n supported_lang = self.service_creator.company_supported_languages ( )\n supported_lang = \", \".join ( supported_lang )\n return jsonify ( {\"Supported languages\": supported_lang} )","def get_languages_info(repo):\n assert \"languages_url\" in repo, \"Languages URL is missing.\"\n response = requests.get(repo[\"languages_url\"])\n data = response.json()\n return data","def find_languages_jahia(soup_jahia, host_jahia):\n languages = soup_jahia.find('ul', {'id' : 'languages'})\n jahia_lang_curr = \"\"\n jahia_other_link = \"\"\n if languages is not None:\n for language in languages.findAll('li'):\n if language.has_attr('class'):\n jahia_lang_curr = language.getText().strip().lower()\n else:\n jahia_other_link = host_jahia + language.find('a')['href']\n return (jahia_lang_curr, jahia_other_link)","def listSupportedGrammarCheckingLanguages(cls, path=None):\n lib = cls.__getLib()\n\n def listOperation(p):\n return lib.voikkoListSupportedGrammarCheckingLanguages(p)\n\n return cls.__listSupportedLanguagesForOperation(path, lib, listOperation)","def get_lang_to_export(self, cr, uid, external_session, context=None):\n\n if context is None:\n return []\n else:\n return context.get('lang_to_export') or [context.get('lang')]","def get_languages(\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = GetLanguages.create(\n namespace=namespace,\n )\n return run_request(request, additional_headers=x_additional_headers, **kwargs)","def get_locales(self) -> List[str]:\n\n return self.possible_locale_list","def list(self):\n fields = ['uuid', 'name', 'description', 'compiler_versions',\n 'os_platform']\n response = self.client.languagepacks.list()\n cliutils.print_list(response, fields)","def codes(cls):\n return set(cls.langs.keys())","def language_tags(self):\n return self.properties.get(\"languageTags\", StringCollection())","def broaden(self) -> 'List[Language]':\n return [Language.get(tag) for tag in self.broader_tags()]","def vocabularies(self, lang):\n\n payload = {'lang': lang}\n req = requests.get(self.api_base + 'vocabularies', params=payload)\n req.raise_for_status()\n return req.json()['vocabularies']","async def get_languages_async(\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = GetLanguages.create(\n namespace=namespace,\n )\n return await run_request_async(\n request, additional_headers=x_additional_headers, **kwargs\n )","def get_language_locales(lang):\n\n parts = parse_langcode(lang)\n if \"language\" not in parts:\n raise InvalidLocaleSpec(\"'%s' is not a valid language\" % lang)\n\n return langtable.list_locales(languageId=parts[\"language\"],\n territoryId=parts.get(\"territory\", \"\"),\n scriptId=parts.get(\"script\", \"\"))","def domains(cls) -> Set[str]:\n return set(cls.langs.values())","def get_list_for_dropdown(self):\n\t\tlanguage = translation.get_language()\n\t\tcategories = cache.get('%s_%s' % (CATEGORY_LIST_CACHE_KEY, language))\n\t\tif not categories:\n\t\t\tcategories = self.filter(is_active=True).order_by('name')\n\t\t\tcache.set('%s_%s' % (CATEGORY_LIST_CACHE_KEY, language), categories, CACHE_TIMEOUT)\n\n\t\treturn categories","def get_localization(self):\n return self._request_data(\"/lokarria/localization\")","def test_list_source_language(self):\n\n # check if documentalist has access to the list view\n self.login_documentalist()\n response = self.client.get('/languages/' )\n\n # 403 = unauthorized\n self.assertEqual(response.status_code, 403)\n\n self.client.logout()\n self.login_admin()\n\n response = self.client.get('/languages/')\n self.assertContains(response, \"português\")","def listSupportedSpellingLanguages(cls, path=None):\n lib = cls.__getLib()\n\n def listOperation(p):\n return lib.voikkoListSupportedSpellingLanguages(p)\n\n return cls.__listSupportedLanguagesForOperation(path, lib, listOperation)","def GetLanguageInfo(*args, **kwargs):\n return _gdi_.Locale_GetLanguageInfo(*args, **kwargs)","def route_video_languages():\n\n result = video_dal_retriever.retrieve_languages()\n return jsonify({'languages' : result})","def make_translated_text():\n return {\n code: ''\n for code, name\n in settings.LANGUAGES\n }","def get_available_locales(self):\n # TODO: Assuming first server is good - need to make fallback logic\n return self.session.get_any(\"{base}{request_url}\".format(base=self.servers[0],\n request_url=F\"/GetAvailableLocales/\"))","def load_language_codes(self, path): \n try:\n fp = open(path, 'r+')\n languages = [line for line in fp.readlines()]\n fp.close\n except:\n print('Failed to read languages file.')\n return\n \n self.languages = languages","def _get_pages():\n pages = {}\n\n # Create the root pages.\n for path in _get_paths():\n pages[path] = {}\n\n # Create the intl pages.\n for locale in locales:\n for path in _get_paths():\n pages[('/intl/' + locale + path)] = {}\n\n return pages","def initialise_languages():\n is_language_folder = r\"^[^\\\\\\.]*\" # Cannot have backslash or dot.\n language_folder_path = os.path.join(definitions.ROOT_DIR, \"languages\")\n\n for root, dirs, files in os.walk(language_folder_path):\n for name in files:\n if name.startswith(\"_NEW_\") or name.startswith(\"_CHANGED_\"):\n # Files that are auto-generated will not be added.\n continue\n\n full_dir = os.path.join(root, name)\n relative_dir = full_dir.replace(language_folder_path + \"\\\\\", \"\")\n\n match = re.match(is_language_folder, relative_dir)\n language_id = match.group(0)\n\n language = None\n if language_id != \"cache\":\n language = definitions.LANGUAGES[language_id]\n else:\n language = definitions.CACHE_LANGUAGE\n\n if relative_dir == \"{id}\\\\commands.json\".format(id=language_id):\n # Take the commands.\n definitions.COMMANDS.add_command_localisation(full_dir, language_id)\n\n elif relative_dir == \"{id}\\\\languages.json\".format(id=language_id):\n # Take the languages.\n language.add_languages(full_dir)\n\n elif relative_dir == \"{id}\\\\meta.json\".format(id=language_id):\n # Take the metadata.\n language.add_meta(full_dir)\n\n elif relative_dir == \"{id}\\\\permissions.json\".format(id=language_id):\n # Take the permissions.\n language.add_permission_names(full_dir)\n\n elif relative_dir == \"{id}\\\\units.json\".format(id=language_id):\n language.add_units(full_dir)\n\n else:\n # Take the keys\n language.add_keys_from_path(full_dir)\n\n for name in dirs:\n full_dir = os.path.join(root, name)\n relative_dir = full_dir.replace(language_folder_path + \"\\\\\", \"\")\n\n match = re.fullmatch(is_language_folder, relative_dir)\n if match is not None:\n if name != \"cache\":\n definitions.LANGUAGES[name] = Language(name)\n else:\n definitions.CACHE_LANGUAGE = Language(name)","def get_lang(self):\n\n path = self.get_lang_path()\n for language in self.languages:\n if language in path:\n return language","def test_get_languages(self):\n title = ('Transportation Challenges Limit Education Choices for '\n 'Denver Parents')\n summary = \"\"\"\n Many families in the Denver metro area use public\n transportation instead of a school bus because for them, a\n quality education is worth hours of daily commuting. Colorado's\n school choice program is meant to foster educational equity,\n but the families who benefit most are those who have time and\n money to travel. Low-income families are often left in a lurch.\n \"\"\"\n byline = \"Mile High Connects\"\n story = create_story(title=title, summary=summary, byline=byline)\n self.assertEqual([settings.LANGUAGE_CODE], story.get_languages())"],"string":"[\n \"def get_all_languages():\\n\\tdef _get():\\n\\t\\tif not frappe.db:\\n\\t\\t\\tfrappe.connect()\\n\\t\\treturn frappe.db.sql_list('select name from tabLanguage')\\n\\treturn frappe.cache().get_value('languages', _get)\",\n \"def languages(self):\\r\\n url = '{0}/{1}'.format(self.get_url(), 'languages')\\r\\n\\r\\n return http.Request('GET', url), parsers.parse_json\",\n \"def languages(self):\\n\\n return self._request('/languages')\",\n \"def wikiLanguages():\\n return languages\",\n \"def languages():\\n r = requests.get('http://translate.yandex.net/api/v1/tr.json/getLangs')\\n return r.json['dirs']\",\n \"def get_langs():\\r\\n temp = \\\"\\\"\\r\\n translate_client = translate.Client()\\r\\n for i in translate_client.get_languages():\\r\\n temp += i['name'] + \\\": \\\" + i['language'] + \\\"\\\\n\\\"\\r\\n\\r\\n return temp\",\n \"def get_langs(id):\",\n \"def get_languages(self):\\n language_list = []\\n url = '%s%s/languages.xml' % (self.URL_API, self.API_KEY)\\n data = urllib.urlopen(url)\\n root = cElementTree.parse(data).getroot()\\n for language in root.iter('Language'):\\n language_list.append(language.find('abbreviation').text)\\n return language_list\",\n \"def fetch_languages(self):\\r\\n \\r\\n # tokenize, clean and filter document tokens \\r\\n toks = [re.sub(r'[^a-zA-Z]','', tok.text.lower().strip()) for tok in self.doc]\\r\\n toks = [tok for tok in toks if len(tok)>1 and tok in LANGUAGES]\\r\\n toks = sorted(set(toks))\\r\\n \\r\\n return toks\",\n \"def GetLanguages(cls):\\n return sorted(cls._LANGUAGE_PER_TAG.items())\",\n \"def available_languages(self):\\n data = self._run(\\n url_path=\\\"languages/available\\\"\\n )\\n return data['result'].get('languages', [])\",\n \"def languages(self):\\n return self._languages\",\n \"def list(self):\\n for key, value in self.languages.iteritems():\\n print key, value\",\n \"def allLocales(self):\\n return util.parseLocales(urlopen(self.all_url).read())\",\n \"def get_languages():\\n\\n api = (api_name, 'languages')\\n\\n response = make_request(api=api, action='get', **{})\\n status_code = response.status_code\\n content = response.text\\n\\n msg = str(status_code) + ' : ' + content\\n \\n logger.debug(\\\"response from spanglish languages: {}\\\".format(response))\\n logger.debug(\\\"response statuscode from spanglish languages: {}\\\".format(status_code))\\n\\n click.echo(\\\"response message: %s \\\" % msg)\",\n \"def book_language_list(request):\\n languages = Language.objects.all().order_by('-name')\\n return render(request, 'library/book_language_list.html', {\\\"languages\\\": languages, })\",\n \"def getLanguages(self):\\n return self.__getColumnData(Q_LANGUAGES, 'language')\",\n \"def languages(self):\\n return LanguageCodes.english_names\",\n \"def getAvailableLanguages(self):\\n url = \\\"http://www.youtube.com/api/timedtext?v=%s&type=list\\\" % self.video_id\\n xml = urllib2.urlopen(url)\\n tree = ET.parse(xml)\\n root = tree.getroot()\\n languages = {}\\n for child in root:\\n languages[child.attrib[\\\"lang_code\\\"]] = child.attrib[\\\"lang_translated\\\"]\\n return languages\",\n \"def get_all(self, lang: str = None):\\n pass\",\n \"def test_get_languages(self):\\n languages = get_languages(self.edition_data[\\\"languages\\\"])\\n self.assertEqual(languages, [\\\"English\\\"])\",\n \"def get_all_languages(with_language_name: bool = False) -> list:\\n\\n\\tdef get_language_codes():\\n\\t\\treturn frappe.get_all(\\\"Language\\\", filters={\\\"enabled\\\": 1}, pluck=\\\"name\\\")\\n\\n\\tdef get_all_language_with_name():\\n\\t\\treturn frappe.get_all(\\\"Language\\\", [\\\"language_code\\\", \\\"language_name\\\"], {\\\"enabled\\\": 1})\\n\\n\\tif not frappe.db:\\n\\t\\tfrappe.connect()\\n\\n\\tif with_language_name:\\n\\t\\treturn frappe.cache.get_value(\\\"languages_with_name\\\", get_all_language_with_name)\\n\\telse:\\n\\t\\treturn frappe.cache.get_value(\\\"languages\\\", get_language_codes)\",\n \"def get_native_languages(self):\\n return self.userlanguage_set.filter(level='N')\",\n \"def languages_display(self):\\n is_draft = self.extended_object.publisher_is_draft\\n node = self.extended_object.node\\n current_and_descendant_nodes = node.__class__.get_tree(parent=node)\\n\\n course_runs = (\\n CourseRun.objects.filter(\\n direct_course__extended_object__node__in=current_and_descendant_nodes,\\n direct_course__extended_object__publisher_is_draft=is_draft,\\n )\\n .exclude(catalog_visibility=\\\"hidden\\\")\\n .only(\\\"languages\\\")\\n )\\n languages = list(\\n {x for course_languages in course_runs for x in course_languages.languages}\\n )\\n instance = CourseRun(languages=languages)\\n return instance.get_languages_display()\",\n \"async def langs(self, context):\\n languages = get_langs(context.message.guild)\\n await context.channel.send(LANG_LIST.format(nb_lang=len(languages), langs=enum(languages)))\",\n \"def languages(self):\\n if not self.has_languages:\\n self._languages = dict(self._lodgeit.pastes.getLanguages())\\n return self._languages\",\n \"def find_languages(self, obj):\\n languages = set()\\n\\n def add_langs(item):\\n if hasattr(item, 'keys'): # pragma: nocover\\n languages.update(item.keys())\\n\\n for browser in obj.all_browsers:\\n add_langs(browser.name)\\n add_langs(browser.note)\\n\\n for feature in chain([obj], obj.child_features):\\n add_langs(feature.mdn_uri)\\n add_langs(feature.name)\\n\\n for maturity in obj.all_maturities:\\n add_langs(maturity.name)\\n\\n for reference in obj.all_references:\\n add_langs(reference.note)\\n\\n for section in obj.all_sections:\\n add_langs(section.number)\\n add_langs(section.name)\\n add_langs(section.subpath)\\n\\n for spec in obj.all_specs:\\n add_langs(spec.name)\\n add_langs(spec.uri)\\n\\n for support in obj.all_supports:\\n add_langs(support.note)\\n\\n for version in obj.all_versions:\\n add_langs(version.release_notes_uri)\\n add_langs(version.note)\\n\\n if 'zxx' in languages:\\n # No linguistic content\\n languages.remove('zxx')\\n if 'en' in languages:\\n languages.remove('en')\\n return ['en'] + sorted(languages)\\n else:\\n return sorted(languages)\",\n \"def _get_available_languages(self):\\n return stopwords.fileids()\",\n \"def languages(self) -> localedata.LocaleDataDict:\\n return self._data['languages']\",\n \"async def get_multilingual(filename: str):\\n query_result = {\\\"langList\\\": []}\\n database = get_db()\\n query_displayname = database.AQLQuery(\\n query=main_queries.QUERY_MULTILINGUAL_LANGS,\\n bindVars={\\n \\\"filename\\\": filename\\n },\\n rawResults=True\\n )\\n query_result = {\\\"langList\\\": query_displayname.result[0]}\\n return query_result\",\n \"def get_languages(request):\\n if request.is_ajax():\\n publications = Publication.objects.all()\\n language_list = []\\n for pub in publications:\\n languages = pub.languages.all()\\n for lang in languages:\\n language_list.append({\\\"pub\\\": pub.pk,\\\"pub_name\\\":pub.name,\\\"lang\\\": u\\\"%s\\\" % lang.pk,\\\"name_lang\\\":lang.alias})\\n data = simplejson.dumps(language_list)\\n return HttpResponse(data)\",\n \"def get_learning_languages(self):\\n return self.userlanguage_set.exclude(level='N')\",\n \"def autocomplete_languages():\\n languages = Language.query.all()\\n return jsonify(json_list=[language.name for language in languages])\",\n \"def grepo(request):\\n return {\\n \\\"GREPO_LANGUAGES\\\": Language.objects.all().values_list(\\\"name\\\", flat=True)\\n }\",\n \"def GetLanguages():\\n return GetDataFromCsvFile('languages.csv')\",\n \"def Languages(self, default=[\\\"en\\\"]):\\n return self.data.get('metadata', {}).get('languages', default)\",\n \"def languages():\\n return \\\", \\\".join(sorted(\\\"{}: '{}'\\\".format(gTTS.LANGUAGES[k], k) for k in gTTS.LANGUAGES))\",\n \"def available_languages():\\n utility = queryUtility(ILanguageAvailability)\\n if utility is not None:\\n return utility.getAvailableLanguages()\\n return [DEFAULT_LANGUAGE]\",\n \"def get_queryset(self):\\n\\n return Localization.objects.all()\",\n \"def getLocales(self):\\n pass\",\n \"def langs(cls):\\n codes = cls.codes[:]\\n\\n if hasattr(cls, 'test_codes'):\\n codes += cls.test_codes\\n\\n codes += cls.closed_wikis\\n\\n # shortcut this classproperty\\n cls.langs = {code: f'{code}.{cls.domain}' for code in codes}\\n cls.langs.update({alias: f'{code}.{cls.domain}'\\n for alias, code in cls.code_aliases.items()})\\n\\n return cls.langs\",\n \"def list_project_languages(self, project_id):\\n data = self._run(\\n url_path=\\\"languages/list\\\",\\n id=project_id\\n )\\n return data['result'].get('languages', [])\",\n \"def languages(query, pos):\\n lemma, results = etym(query, pos, ETYMOLOGY)\\n languages = set()\\n if not results:\\n lemma, results = etym(query, None, ETYMOLOGY)\\n for result in results:\\n languages.update(set(result['languages']))\\n return languages\",\n \"def released_languages_list(self):\\r\\n if not self.released_languages.strip(): # pylint: disable=no-member\\r\\n return []\\r\\n\\r\\n languages = [lang.strip() for lang in self.released_languages.split(',')] # pylint: disable=no-member\\r\\n # Put in alphabetical order\\r\\n languages.sort()\\r\\n return languages\",\n \"def list_languages(self):\\n known = [ob.capitalize() for ob in self.caller.languages.known_languages]\\n known += [\\\"Arvani\\\"]\\n self.msg(\\\"{wYou can currently speak:{n %s\\\" % \\\", \\\".join(known))\\n self.msg(\\n \\\"You can learn %s additional languages.\\\"\\n % self.caller.languages.additional_languages\\n )\",\n \"async def getLanguages(self, body=\\\"\\\"):\\n payload = {}\\n \\n # Parameter validation\\n schema = ConfigurationValidator.getLanguages()\\n schema.dump(schema.load(payload))\\n \\n\\n url_with_params = await create_url_with_params(api_url=self._urls[\\\"getLanguages\\\"], proccessed_params=\\\"\\\"\\\"{\\\"required\\\":[],\\\"optional\\\":[],\\\"query\\\":[],\\\"headers\\\":[],\\\"path\\\":[]}\\\"\\\"\\\", )\\n query_string = await create_query_string()\\n headers = {\\n \\\"Authorization\\\": \\\"Bearer \\\" + base64.b64encode(\\\"{}:{}\\\".format(self._conf.applicationID, self._conf.applicationToken).encode()).decode()\\n }\\n if self._conf.locationDetails:\\n headers[\\\"x-location-detail\\\"] = ujson.dumps(self._conf.locationDetails)\\n for h in self._conf.extraHeaders:\\n headers.update(h)\\n exclude_headers = []\\n for key, val in headers.items():\\n if not key.startswith(\\\"x-fp-\\\"):\\n exclude_headers.append(key)\\n return await AiohttpHelper().aiohttp_request(\\\"GET\\\", url_with_params, headers=get_headers_with_signature(urlparse(self._urls[\\\"getLanguages\\\"]).netloc, \\\"get\\\", await create_url_without_domain(\\\"/service/application/configuration/v1.0/languages\\\", ), query_string, headers, body, exclude_headers=exclude_headers), data=body, cookies=self._conf.cookies)\",\n \"def get_queryset(self):\\r\\n username = self.kwargs['username']\\r\\n return models.LanguagesKnown.objects.filter(username = username).order_by('-id')\",\n \"def get_languages(self) -> dict:\\n request_url = self.__API_URL.format(user=self._user,\\n project=self._project)\\n response = self._http.request('GET', request_url,\\n headers=config.HEADERS)\\n\\n # Handle limits and wrong responses\\n if response.status > 205:\\n raise StatusError(status=response.status)\\n\\n return json.loads(response.data)\",\n \"def ListConceptLanguages(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def languages_by_id(self, repository_id, access_token=None):\\n return self._complete_request_by_id(\\n repository_id, \\\"languages\\\", access_token)\",\n \"def getFilteredLanguages(self, data):\\n def filterLanguage(dataItem):\\n return dataItem['type'] == 'language'\\n return list(filter(filterLanguage, data))\",\n \"def get_localizations(request):\\n return JsonResponse(get_all_objects(Localization, LocalizationSerializer), safe=False)\",\n \"def list_of_langs(data):\\n lang_codes = []\\n for lang_data in data:\\n lang_codes.append(lang_data.get('value'))\\n return lang_codes\",\n \"def get_available_translations(localedir=None):\\n\\n localedir = localedir or gettext._default_localedir\\n\\n # usually there are no message files for en\\n messagefiles = sorted(glob.glob(localedir + \\\"/*/LC_MESSAGES/anaconda.mo\\\") +\\n [\\\"blob/en/blob/blob\\\"])\\n trans_gen = (path.split(os.path.sep)[-3] for path in messagefiles)\\n\\n langs = set()\\n\\n for trans in trans_gen:\\n parts = parse_langcode(trans)\\n lang = parts.get(\\\"language\\\", \\\"\\\")\\n if lang and lang not in langs:\\n langs.add(lang)\\n # check if there are any locales for the language\\n locales = get_language_locales(lang)\\n if not locales:\\n continue\\n\\n yield lang\",\n \"def listSupportedHyphenationLanguages(cls, path=None):\\n lib = cls.__getLib()\\n\\n def listOperation(p):\\n return lib.voikkoListSupportedHyphenationLanguages(p)\\n\\n return cls.__listSupportedLanguagesForOperation(path, lib, listOperation)\",\n \"def load_languages():\\n _langs = []\\n with open('conf/languages.csv') as f:\\n for _line in f.readlines():\\n _langs.append(_line[0:-1]) # chop line separetor\\n return _langs\",\n \"def public_get_languages(\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = PublicGetLanguages.create(\\n namespace=namespace,\\n )\\n return run_request(request, additional_headers=x_additional_headers, **kwargs)\",\n \"def released_langs(self):\\r\\n language_options = DarkLangConfig.current().released_languages_list\\r\\n if settings.LANGUAGE_CODE not in language_options:\\r\\n language_options.append(settings.LANGUAGE_CODE)\\r\\n return language_options\",\n \"def get_report_translations(request):\\n\\n id_report = request.GET.get('id_report',None)\\n if id_report is not None:\\n languages = []\\n lang = Report.objects.filter(id_report = id_report)\\n for el in lang:\\n if el.language not in languages:\\n languages.append(el.language)\\n\\n json_resp = {}\\n # print(languages)\\n json_resp['languages'] = languages\\n return JsonResponse(json_resp)\",\n \"def get_available_languages(domain):\\r\\n if domain in _AVAILABLE_LANGUAGES:\\r\\n return copy.copy(_AVAILABLE_LANGUAGES[domain])\\r\\n\\r\\n localedir = '%s_LOCALEDIR' % domain.upper()\\r\\n find = lambda x: gettext.find(domain,\\r\\n localedir=os.environ.get(localedir),\\r\\n languages=[x])\\r\\n\\r\\n # NOTE(mrodden): en_US should always be available (and first in case\\r\\n # order matters) since our in-line message strings are en_US\\r\\n language_list = ['en_US']\\r\\n # NOTE(luisg): Babel <1.0 used a function called list(), which was\\r\\n # renamed to locale_identifiers() in >=1.0, the requirements master list\\r\\n # requires >=0.9.6, uncapped, so defensively work with both. We can remove\\r\\n # this check when the master list updates to >=1.0, and all projects udpate\\r\\n list_identifiers = (getattr(localedata, 'list', None) or\\r\\n getattr(localedata, 'locale_identifiers'))\\r\\n locale_identifiers = list_identifiers()\\r\\n for i in locale_identifiers:\\r\\n if find(i) is not None:\\r\\n language_list.append(i)\\r\\n _AVAILABLE_LANGUAGES[domain] = language_list\\r\\n return copy.copy(language_list)\",\n \"def getPossibleLangs(self):\\n lst = {}\\n for e in self._values:\\n for lang in e.getLangCodes():\\n lst[ lang ] = 1\\n return lst.keys()\",\n \"def get_languages(config_filepath):\\n load_classifier(config_filepath)\\n print(classifier.get_languages())\",\n \"async def public_get_languages_async(\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = PublicGetLanguages.create(\\n namespace=namespace,\\n )\\n return await run_request_async(\\n request, additional_headers=x_additional_headers, **kwargs\\n )\",\n \"def browserLanguages(request):\\n fallback = []\\n accepted = request.http_accept_language\\n if accepted:\\n # Extract the languages names from the string\\n accepted = accepted.split(',')\\n accepted = map(lambda x: x.split(';')[0], accepted)\\n # Add base language for each sub language. If the user specified\\n # a sub language like \\\"en-us\\\", we will try to to provide it or\\n # a least the base language \\\"en\\\" in this case.\\n for lang in accepted:\\n lang = lang.lower()\\n fallback.append(lang)\\n if '-' in lang:\\n baselang = lang.split('-')[0]\\n fallback.append(baselang)\\n return fallback\",\n \"def get_language_list_gui():\\n _ = get_gettext()\\n language = {}\\n language['connect'] = _(\\\"Connect\\\")\\n language['ip'] = _(\\\"IP\\\")\\n language['netmask'] = _(\\\"Netmask\\\")\\n language['gateway'] = _('Gateway')\\n language['dns'] = _('DNS')\\n language['use_static_ip'] = _('Use Static IPs')\\n language['use_static_dns'] = _('Use Static DNS')\\n language['use_encryption'] = _('Use Encryption')\\n language['advanced_settings'] = _('Advanced Settings')\\n language['wired_network'] = _('Wired Network')\\n language['wired_network_instructions'] = _('To connect to a wired network,'\\n ' you must create a network profile. To create a network profile, type a'\\n ' name that describes this network, and press Add.')\\n language['automatic_connect'] = _('Automatically connect to this network')\\n language['secured'] = _('Secured')\\n language['unsecured'] = _('Unsecured')\\n language['channel'] = _('Channel')\\n language['preferences'] = _('Preferences')\\n language['wpa_supplicant_driver'] = _('WPA Supplicant Driver')\\n language['wireless_interface'] = _('Wireless Interface')\\n language['wired_interface'] = _('Wired Interface')\\n language['hidden_network'] = _('Hidden Network')\\n language['hidden_network_essid'] = _('Hidden Network ESSID')\\n language['connected_to_wireless'] = _('Connected to $A at $B (IP: $C)')\\n language['connected_to_wired'] = _('Connected to wired network (IP: $A)')\\n language['not_connected'] = _('Not connected')\\n language['no_wireless_networks_found'] = _('No wireless networks found.')\\n language['killswitch_enabled'] = _('Wireless Kill Switch Enabled')\\n language['key'] = _('Key')\\n language['username'] = _('Username')\\n language['password'] = _('Password')\\n language['anonymous_identity'] = _('Anonymous Identity')\\n language['identity'] = _('Identity')\\n language['authentication'] = _('Authentication')\\n language['path_to_pac_file'] = _('Path to PAC File')\\n language['select_a_network'] = _('Choose from the networks below:')\\n language['connecting'] = _('Connecting...')\\n language['wired_always_on'] = _('Always show wired interface')\\n language['auto_reconnect'] = _('Automatically reconnect on connection loss')\\n language['create_adhoc_network'] = _('Create an Ad-Hoc Network')\\n language['essid'] = _('ESSID')\\n language['use_wep_encryption'] = _('Use Encryption (WEP only)')\\n language['before_script'] = _('Run script before connect')\\n language['after_script'] = _('Run script after connect')\\n language['disconnect_script'] = _('Run disconnect script')\\n language['script_settings'] = _('Scripts')\\n language['use_ics'] = _('Activate Internet Connection Sharing')\\n language['madwifi_for_adhoc'] = _('Check if using madwifi/atheros drivers')\\n language['default_wired'] = _('Use as default profile (overwrites any previous default)')\\n language['use_debug_mode'] = _('Enable debug mode')\\n language['use_global_dns'] = _('Use global DNS servers')\\n language['use_default_profile'] = _('Use default profile on wired autoconnect')\\n language['show_wired_list'] = _('Prompt for profile on wired autoconnect')\\n language['use_last_used_profile'] = _('Use last used profile on wired autoconnect')\\n language['choose_wired_profile'] = _('Select or create a wired profile to connect with')\\n language['wired_network_found'] = _('Wired connection detected')\\n language['stop_showing_chooser'] = _('Stop Showing Autoconnect pop-up temporarily')\\n language['display_type_dialog'] = _('Use dBm to measure signal strength')\\n language['scripts'] = _('Scripts')\\n language['invalid_address'] = _('Invalid address in $A entry.')\\n language['global_settings'] = _('Use these settings for all networks sharing this essid')\\n language['encrypt_info_missing'] = _('Required encryption information is missing.')\\n language['enable_encryption'] = _('This network requires encryption to be enabled.')\\n language['wicd_auto_config'] = _('Automatic (recommended)')\\n language[\\\"gen_settings\\\"] = _(\\\"General Settings\\\")\\n language[\\\"ext_programs\\\"] = _(\\\"External Programs\\\")\\n language[\\\"dhcp_client\\\"] = _(\\\"DHCP Client\\\")\\n language[\\\"wired_detect\\\"] = _(\\\"Wired Link Detection\\\")\\n language[\\\"route_flush\\\"] = _(\\\"Route Table Flushing\\\")\\n language[\\\"backend\\\"] = _(\\\"Backend\\\")\\n language[\\\"backend_alert\\\"] = _(\\\"Changes to your backend won't occur until the daemon is restarted.\\\")\\n language['0'] = _('0')\\n language['1'] = _('1')\\n language['2'] = _('2')\\n language['3'] = _('3')\\n language['4'] = _('4')\\n language['5'] = _('5')\\n language['6'] = _('6')\\n language['7'] = _('7')\\n language['8'] = _('8')\\n language['9'] = _('9')\\n language['interface_down'] = _('Putting interface down...')\\n language['resetting_ip_address'] = _('Resetting IP address...')\\n language['interface_up'] = _('Putting interface up...')\\n language['setting_encryption_info'] = _('Setting encryption info')\\n language['removing_old_connection'] = _('Removing old connection...')\\n language['generating_psk'] = _('Generating PSK...')\\n language['generating_wpa_config'] = _('Generating WPA configuration file...')\\n language['flushing_routing_table'] = _('Flushing the routing table...')\\n language['configuring_interface'] = _('Configuring wireless interface...')\\n language['validating_authentication'] = _('Validating authentication...')\\n language['setting_broadcast_address'] = _('Setting broadcast address...')\\n language['setting_static_dns'] = _('Setting static DNS servers...')\\n language['setting_static_ip'] = _('Setting static IP addresses...')\\n language['running_dhcp'] = _('Obtaining IP address...')\\n language['dhcp_failed'] = _('Connection Failed: Unable to Get IP Address')\\n language['aborted'] = _('Connection Cancelled')\\n language['bad_pass'] = _('Connection Failed: Bad password')\\n language['done'] = _('Done connecting...')\\n return language\",\n \"def languages(request, region_slug):\\n try:\\n region = Region.objects.get(slug=region_slug)\\n\\n result = list(\\n map(\\n lambda l: {\\n \\\"id\\\": l.language.id,\\n \\\"code\\\": l.language.code,\\n \\\"native_name\\\": l.language.name,\\n \\\"dir\\\": l.language.text_direction,\\n },\\n region.language_tree_nodes.filter(active=True),\\n )\\n )\\n return JsonResponse(\\n result, safe=False\\n ) # Turn off Safe-Mode to allow serializing arrays\\n except ObjectDoesNotExist:\\n return HttpResponse(\\n f'No Region found with name \\\"{region_slug}\\\".',\\n content_type=\\\"text/plain\\\",\\n status=404,\\n )\",\n \"def sorted_languages():\\n # Python 3: Use functools.cmp_to_key\\n def compare(a, b):\\n if a.name == u\\\"English\\\":\\n return -1\\n elif b.name == u\\\"English\\\":\\n return 1\\n else:\\n return cmp(a, b)\\n return sorted(Language.query.all(), cmp=compare)\",\n \"def languages_by_name(self, username, repository_name, access_token=None):\\n return self._complete_request_by_name(\\n username, repository_name, \\\"languages\\\", access_token)\",\n \"def langs(cls):\\n codes = cls.codes\\n\\n if hasattr(cls, 'code_aliases'):\\n codes += tuple(cls.code_aliases.keys())\\n\\n return {code: cls.domain for code in codes}\",\n \"def test_langs(self):\\n self._api.Init(lang=\\\"eng\\\")\\n lang = self._api.GetInitLanguagesAsString()\\n self.assertEqual(lang, \\\"eng\\\")\\n langs = self._api.GetLoadedLanguages()\\n self.assertEqual(langs, [\\\"eng\\\"])\\n self.assertIn(\\\"eng\\\", self._api.GetAvailableLanguages())\",\n \"def overview():\\r\\n # Update the list of languages allowed on the site, \\r\\n # except for the language used by your users at that time.\\r\\n if request.method == 'POST':\\r\\n lan_object = Languages()\\r\\n data = lan_object.update()\\r\\n message = lan_object.message\\r\\n status = lan_object.status\\r\\n \\r\\n # Gets documents from the collections of all languages \\r\\n languages_list = g.languages_object.get_languages(1)\\r\\n language_chosen = g.languages_object.get_languages(2)\\r\\n return render_template( '{}/index.html'.format(MODULE_DIR), **locals())\",\n \"def get_stores(self):\\n # don't be confused by the name here: these are stores, not locales.\\n # The website is French-only.\\n return self._request_json(\\\"/locales\\\")[\\\"locales\\\"]\",\n \"def get_supported_languages ( self ):\\n supported_lang = self.service_creator.company_supported_languages ( )\\n supported_lang = \\\", \\\".join ( supported_lang )\\n return jsonify ( {\\\"Supported languages\\\": supported_lang} )\",\n \"def get_languages_info(repo):\\n assert \\\"languages_url\\\" in repo, \\\"Languages URL is missing.\\\"\\n response = requests.get(repo[\\\"languages_url\\\"])\\n data = response.json()\\n return data\",\n \"def find_languages_jahia(soup_jahia, host_jahia):\\n languages = soup_jahia.find('ul', {'id' : 'languages'})\\n jahia_lang_curr = \\\"\\\"\\n jahia_other_link = \\\"\\\"\\n if languages is not None:\\n for language in languages.findAll('li'):\\n if language.has_attr('class'):\\n jahia_lang_curr = language.getText().strip().lower()\\n else:\\n jahia_other_link = host_jahia + language.find('a')['href']\\n return (jahia_lang_curr, jahia_other_link)\",\n \"def listSupportedGrammarCheckingLanguages(cls, path=None):\\n lib = cls.__getLib()\\n\\n def listOperation(p):\\n return lib.voikkoListSupportedGrammarCheckingLanguages(p)\\n\\n return cls.__listSupportedLanguagesForOperation(path, lib, listOperation)\",\n \"def get_lang_to_export(self, cr, uid, external_session, context=None):\\n\\n if context is None:\\n return []\\n else:\\n return context.get('lang_to_export') or [context.get('lang')]\",\n \"def get_languages(\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = GetLanguages.create(\\n namespace=namespace,\\n )\\n return run_request(request, additional_headers=x_additional_headers, **kwargs)\",\n \"def get_locales(self) -> List[str]:\\n\\n return self.possible_locale_list\",\n \"def list(self):\\n fields = ['uuid', 'name', 'description', 'compiler_versions',\\n 'os_platform']\\n response = self.client.languagepacks.list()\\n cliutils.print_list(response, fields)\",\n \"def codes(cls):\\n return set(cls.langs.keys())\",\n \"def language_tags(self):\\n return self.properties.get(\\\"languageTags\\\", StringCollection())\",\n \"def broaden(self) -> 'List[Language]':\\n return [Language.get(tag) for tag in self.broader_tags()]\",\n \"def vocabularies(self, lang):\\n\\n payload = {'lang': lang}\\n req = requests.get(self.api_base + 'vocabularies', params=payload)\\n req.raise_for_status()\\n return req.json()['vocabularies']\",\n \"async def get_languages_async(\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = GetLanguages.create(\\n namespace=namespace,\\n )\\n return await run_request_async(\\n request, additional_headers=x_additional_headers, **kwargs\\n )\",\n \"def get_language_locales(lang):\\n\\n parts = parse_langcode(lang)\\n if \\\"language\\\" not in parts:\\n raise InvalidLocaleSpec(\\\"'%s' is not a valid language\\\" % lang)\\n\\n return langtable.list_locales(languageId=parts[\\\"language\\\"],\\n territoryId=parts.get(\\\"territory\\\", \\\"\\\"),\\n scriptId=parts.get(\\\"script\\\", \\\"\\\"))\",\n \"def domains(cls) -> Set[str]:\\n return set(cls.langs.values())\",\n \"def get_list_for_dropdown(self):\\n\\t\\tlanguage = translation.get_language()\\n\\t\\tcategories = cache.get('%s_%s' % (CATEGORY_LIST_CACHE_KEY, language))\\n\\t\\tif not categories:\\n\\t\\t\\tcategories = self.filter(is_active=True).order_by('name')\\n\\t\\t\\tcache.set('%s_%s' % (CATEGORY_LIST_CACHE_KEY, language), categories, CACHE_TIMEOUT)\\n\\n\\t\\treturn categories\",\n \"def get_localization(self):\\n return self._request_data(\\\"/lokarria/localization\\\")\",\n \"def test_list_source_language(self):\\n\\n # check if documentalist has access to the list view\\n self.login_documentalist()\\n response = self.client.get('/languages/' )\\n\\n # 403 = unauthorized\\n self.assertEqual(response.status_code, 403)\\n\\n self.client.logout()\\n self.login_admin()\\n\\n response = self.client.get('/languages/')\\n self.assertContains(response, \\\"português\\\")\",\n \"def listSupportedSpellingLanguages(cls, path=None):\\n lib = cls.__getLib()\\n\\n def listOperation(p):\\n return lib.voikkoListSupportedSpellingLanguages(p)\\n\\n return cls.__listSupportedLanguagesForOperation(path, lib, listOperation)\",\n \"def GetLanguageInfo(*args, **kwargs):\\n return _gdi_.Locale_GetLanguageInfo(*args, **kwargs)\",\n \"def route_video_languages():\\n\\n result = video_dal_retriever.retrieve_languages()\\n return jsonify({'languages' : result})\",\n \"def make_translated_text():\\n return {\\n code: ''\\n for code, name\\n in settings.LANGUAGES\\n }\",\n \"def get_available_locales(self):\\n # TODO: Assuming first server is good - need to make fallback logic\\n return self.session.get_any(\\\"{base}{request_url}\\\".format(base=self.servers[0],\\n request_url=F\\\"/GetAvailableLocales/\\\"))\",\n \"def load_language_codes(self, path): \\n try:\\n fp = open(path, 'r+')\\n languages = [line for line in fp.readlines()]\\n fp.close\\n except:\\n print('Failed to read languages file.')\\n return\\n \\n self.languages = languages\",\n \"def _get_pages():\\n pages = {}\\n\\n # Create the root pages.\\n for path in _get_paths():\\n pages[path] = {}\\n\\n # Create the intl pages.\\n for locale in locales:\\n for path in _get_paths():\\n pages[('/intl/' + locale + path)] = {}\\n\\n return pages\",\n \"def initialise_languages():\\n is_language_folder = r\\\"^[^\\\\\\\\\\\\.]*\\\" # Cannot have backslash or dot.\\n language_folder_path = os.path.join(definitions.ROOT_DIR, \\\"languages\\\")\\n\\n for root, dirs, files in os.walk(language_folder_path):\\n for name in files:\\n if name.startswith(\\\"_NEW_\\\") or name.startswith(\\\"_CHANGED_\\\"):\\n # Files that are auto-generated will not be added.\\n continue\\n\\n full_dir = os.path.join(root, name)\\n relative_dir = full_dir.replace(language_folder_path + \\\"\\\\\\\\\\\", \\\"\\\")\\n\\n match = re.match(is_language_folder, relative_dir)\\n language_id = match.group(0)\\n\\n language = None\\n if language_id != \\\"cache\\\":\\n language = definitions.LANGUAGES[language_id]\\n else:\\n language = definitions.CACHE_LANGUAGE\\n\\n if relative_dir == \\\"{id}\\\\\\\\commands.json\\\".format(id=language_id):\\n # Take the commands.\\n definitions.COMMANDS.add_command_localisation(full_dir, language_id)\\n\\n elif relative_dir == \\\"{id}\\\\\\\\languages.json\\\".format(id=language_id):\\n # Take the languages.\\n language.add_languages(full_dir)\\n\\n elif relative_dir == \\\"{id}\\\\\\\\meta.json\\\".format(id=language_id):\\n # Take the metadata.\\n language.add_meta(full_dir)\\n\\n elif relative_dir == \\\"{id}\\\\\\\\permissions.json\\\".format(id=language_id):\\n # Take the permissions.\\n language.add_permission_names(full_dir)\\n\\n elif relative_dir == \\\"{id}\\\\\\\\units.json\\\".format(id=language_id):\\n language.add_units(full_dir)\\n\\n else:\\n # Take the keys\\n language.add_keys_from_path(full_dir)\\n\\n for name in dirs:\\n full_dir = os.path.join(root, name)\\n relative_dir = full_dir.replace(language_folder_path + \\\"\\\\\\\\\\\", \\\"\\\")\\n\\n match = re.fullmatch(is_language_folder, relative_dir)\\n if match is not None:\\n if name != \\\"cache\\\":\\n definitions.LANGUAGES[name] = Language(name)\\n else:\\n definitions.CACHE_LANGUAGE = Language(name)\",\n \"def get_lang(self):\\n\\n path = self.get_lang_path()\\n for language in self.languages:\\n if language in path:\\n return language\",\n \"def test_get_languages(self):\\n title = ('Transportation Challenges Limit Education Choices for '\\n 'Denver Parents')\\n summary = \\\"\\\"\\\"\\n Many families in the Denver metro area use public\\n transportation instead of a school bus because for them, a\\n quality education is worth hours of daily commuting. Colorado's\\n school choice program is meant to foster educational equity,\\n but the families who benefit most are those who have time and\\n money to travel. Low-income families are often left in a lurch.\\n \\\"\\\"\\\"\\n byline = \\\"Mile High Connects\\\"\\n story = create_story(title=title, summary=summary, byline=byline)\\n self.assertEqual([settings.LANGUAGE_CODE], story.get_languages())\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7950742","0.79043835","0.78993666","0.78554344","0.76446795","0.75309783","0.74677473","0.74178064","0.7268602","0.723141","0.71480125","0.70844215","0.7034048","0.7020481","0.6945113","0.69438887","0.6939026","0.6901797","0.68972915","0.6825298","0.67698455","0.67538047","0.6750807","0.67196023","0.6709264","0.6692018","0.668155","0.6613192","0.660937","0.65832174","0.6556364","0.6553354","0.6544356","0.6538855","0.6526654","0.6507543","0.6505888","0.6499473","0.6496207","0.6492546","0.6490599","0.6449226","0.6436408","0.6419917","0.6419503","0.6413823","0.64122033","0.63945675","0.6368463","0.6329893","0.6326412","0.6295646","0.62925977","0.62876165","0.62652075","0.6258392","0.6255085","0.6254774","0.622648","0.6217653","0.62070924","0.6198646","0.6180007","0.61792064","0.61757606","0.6175107","0.61690176","0.6142627","0.6132669","0.61106956","0.60839784","0.6083898","0.60559976","0.6054538","0.6024162","0.6018168","0.6017244","0.60005975","0.5988706","0.59390336","0.59384334","0.59291774","0.5926117","0.59204906","0.5899988","0.5886855","0.5883011","0.5860904","0.58603007","0.583624","0.58359474","0.5831716","0.5823689","0.5816141","0.5798093","0.5789824","0.57743526","0.5768035","0.5744742","0.57304406"],"string":"[\n \"0.7950742\",\n \"0.79043835\",\n \"0.78993666\",\n \"0.78554344\",\n \"0.76446795\",\n \"0.75309783\",\n \"0.74677473\",\n \"0.74178064\",\n \"0.7268602\",\n \"0.723141\",\n \"0.71480125\",\n \"0.70844215\",\n \"0.7034048\",\n \"0.7020481\",\n \"0.6945113\",\n \"0.69438887\",\n \"0.6939026\",\n \"0.6901797\",\n \"0.68972915\",\n \"0.6825298\",\n \"0.67698455\",\n \"0.67538047\",\n \"0.6750807\",\n \"0.67196023\",\n \"0.6709264\",\n \"0.6692018\",\n \"0.668155\",\n \"0.6613192\",\n \"0.660937\",\n \"0.65832174\",\n \"0.6556364\",\n \"0.6553354\",\n \"0.6544356\",\n \"0.6538855\",\n \"0.6526654\",\n \"0.6507543\",\n \"0.6505888\",\n \"0.6499473\",\n \"0.6496207\",\n \"0.6492546\",\n \"0.6490599\",\n \"0.6449226\",\n \"0.6436408\",\n \"0.6419917\",\n \"0.6419503\",\n \"0.6413823\",\n \"0.64122033\",\n \"0.63945675\",\n \"0.6368463\",\n \"0.6329893\",\n \"0.6326412\",\n \"0.6295646\",\n \"0.62925977\",\n \"0.62876165\",\n \"0.62652075\",\n \"0.6258392\",\n \"0.6255085\",\n \"0.6254774\",\n \"0.622648\",\n \"0.6217653\",\n \"0.62070924\",\n \"0.6198646\",\n \"0.6180007\",\n \"0.61792064\",\n \"0.61757606\",\n \"0.6175107\",\n \"0.61690176\",\n \"0.6142627\",\n \"0.6132669\",\n \"0.61106956\",\n \"0.60839784\",\n \"0.6083898\",\n \"0.60559976\",\n \"0.6054538\",\n \"0.6024162\",\n \"0.6018168\",\n \"0.6017244\",\n \"0.60005975\",\n \"0.5988706\",\n \"0.59390336\",\n \"0.59384334\",\n \"0.59291774\",\n \"0.5926117\",\n \"0.59204906\",\n \"0.5899988\",\n \"0.5886855\",\n \"0.5883011\",\n \"0.5860904\",\n \"0.58603007\",\n \"0.583624\",\n \"0.58359474\",\n \"0.5831716\",\n \"0.5823689\",\n \"0.5816141\",\n \"0.5798093\",\n \"0.5789824\",\n \"0.57743526\",\n \"0.5768035\",\n \"0.5744742\",\n \"0.57304406\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7613201"},"document_rank":{"kind":"string","value":"5"}}},{"rowIdx":81798,"cells":{"query":{"kind":"string","value":"Helper function for accessing wanted / current title. If wanted title doesn't exists, EmptyTitle instance will be returned."},"document":{"kind":"string","value":"def get_title_obj(self, language=None, fallback=True, version_id=None, force_reload=False):\n self._get_title_cache(language, fallback, version_id, force_reload)\n if self.title_cache:\n return self.title_cache\n return EmptyTitle()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_title():","def get_title(self):\n return self.run_command('get_title')[0]","def get_title(self) -> Optional[str]:\n return self.title","def get_title(cls, obj, **kwargs):\n if isinstance(obj.data, dict):\n titles = filter(None, get_value(obj.data, \"titles.title\", []))\n if titles:\n # Show first title that evaluates to True\n return titles[0]\n return \"No title available\"","def get_title(self):\n return self._get_title_()","def get_title(self):\n return self.title","def get_title(self):\n return self.title","def get_title(self):\n return self.title","def get_title(self):\n title = self.title\n if not title and self.parent_id:\n title = self.parent.title\n return title","def safe_title(self):\n try:\n return self.title\n except ObjectDoesNotExist:\n return None","def title(self):\n return self.get(self._names[\"title\"])","def title(self):\n return self.get(self._names[\"title\"])","def current(self):\n return self.title_headings[self._idx]","def get_title(self):\n return self._title","def get_title(self):\n return self._title","def get_title(self):\n return self._title","def get_title(self, obj):\n title = obj.habit.title\n return title","def get_title(self):\n return self.metadata['title']","def get_title(self):\n\n return self.title","def getTitle(self, item):\n return item.Title() or item.getId()","def Title(self, default={}):\n return HEP.TitleObject(self.data.get('title', default))","def title(self):\n return self.run_command('title')[0]","def getTitle(self):\n return self._title","def GetTitle(self):\n return self._title","def get_title(self) -> str:\n pass","def get_title(self):\n\n return self._title","def title(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"title\")","def title(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"title\")","def title(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"title\")","def title(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"title\")","def title(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"title\")","def get_title(self):\n return self._select_interface(self._rc_get_title, self._http_get_title)","def title(self):\n\n return self._title","def test_get_title(double_title, single_title, empty_title):\n assert get_title(double_title) == \"Parton distributions with LHC data\"\n assert get_title(single_title) == \"The Large Hadron Collider\"\n assert get_title(empty_title) == \"\"\n\n no_title_key = {\n \"not_titles\": []\n }\n assert get_title(no_title_key) == \"\"","def title(self) -> Optional[str]:\n return self.get(\"/Title\")","def Title(self, default=None):\n return self.data.get('title', default)","def get_title(self):\n\n title = ''\n doc = self.article.doc\n\n title_element = self.parser.getElementsByTag(doc, tag='title')\n # no title found\n if title_element is None or len(title_element) == 0:\n return title\n\n # title elem found\n title_text = self.parser.getText(title_element[0])\n used_delimeter = False\n\n # split title with |\n if '|' in title_text:\n title_text = self.split_title(title_text, PIPE_SPLITTER)\n used_delimeter = True\n\n # split title with -\n if not used_delimeter and '-' in title_text:\n title_text = self.split_title(title_text, DASH_SPLITTER)\n used_delimeter = True\n\n # split title with »\n if not used_delimeter and u'»' in title_text:\n title_text = self.split_title(title_text, ARROWS_SPLITTER)\n used_delimeter = True\n\n # split title with :\n if not used_delimeter and ':' in title_text:\n title_text = self.split_title(title_text, COLON_SPLITTER)\n used_delimeter = True\n\n title = MOTLEY_REPLACEMENT.replaceAll(title_text)\n return title","def getTitle(self):\n return self.__title__","def title(self) -> Title:\n return self._title","def configured_title(self):\n return self.get('title', self.DEFAULT_SPACE_TITLE)","def title(self):\n return self.get(\"title\")","def get_title(self):\n meta = self.get_meta_data()\n if \"og:title\" in meta:\n return meta[\"og:title\"]\n else:\n soup = BeautifulSoup(self.TARGET_DATA)\n title = soup.find('title')\n if title:\n return title.text\n else:\n return \"No Title\"","def get_title_repr(self) -> str:\n try:\n return Title[self.title].value\n except (KeyError, ValueError):\n pass","def title(self):\n if self._title is None:\n if Path(self.rst_path).exists():\n self._title = self.get_title_from_rst()\n elif Path(self.ipynb_path).exists():\n self._title = self.get_title_from_ipynb()\n else:\n pass\n return self._title","def get_title(self):\n try:\n return self.get_translation().title\n except MissingTranslation:\n return _(\"(No title)\")","def title(self):\n return self.values.get('title')","def title(self):\n return self['title']","def title(self) -> Optional[str]:\n if self._title is not None:\n return self._title\n if self._target_object is not None and isinstance(\n self._target_object, pystac.Catalog\n ):\n return self._target_object.title\n return None","def selected_title(self):\r\n try:\r\n return menu_selected[self.name]\r\n except KeyError:\r\n return NavButton.selected_title(self)","def istitle(self):\n return istitle(self)","def getTitle(self):\n\n return self._title","def title(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"title\")","def check_title(self):\n currenttitle = self.driver.title\n assert self.TITLE in currenttitle, 'Title not expected. Actual: ' + currenttitle + ', Expected: ' + self.TITLE","def title(self):\n return self.container['title']","async def title(self):\n if not hasattr(self, \"_title\"):\n self._title = await Stack.fetch_stack_value(self, \"http://purl.org/dc/terms/title\", await self.uuid)\n return self._title","def parsed_title(self):\n return parse_pr_title(self.title)","def title(self) -> str:\n return pulumi.get(self, \"title\")","def title(self) -> str:\n return pulumi.get(self, \"title\")","def title(self) -> str:\n return pulumi.get(self, \"title\")","def title(self):\n return self._title","def title(self):\n return self._title","def title(self):\n return self._title","def title(self):\n return self._title","def title(self):\n return self._title","def title(self):\n return self._title","def title(self) -> str:\n\t\t# pylint: disable=unsubscriptable-object\n\t\treturn self.value[1]","def _parse_title(self, item):\n title = item[\"Title\"]\n return title","def title(self):\n\t\treturn self.page_title","def title(self):\n return self.properties.get('Title', None)","def getTitle(self):\n\n # print(self.soupObject.title.string)\n try:\n s = self.soupObject.find(\"meta\", attrs={\"name\": \"twitter:title\"})\n self.title = str(s['content'])\n self.title = self.title.replace(\"/\", \"\")\n self.title = self.title.strip()\n if not self.title:\n s = int(\"deliberateError\")\n\n # except\n except:\n self.title = \"Amazonsubtitles\"\n\n pass","def selected_title(self):\r\n return self.title","def short_title(self):\n if hasattr(self, \"title\"):\n return self.title\n else:\n return \"\"","def get_title(self):\n title = self.driver.title\n return title","def title(self):\n return self.metadata.get('title')","def current(self, title):\n if self.valid_title(title):\n return self.timers[title]['last']\n else:\n return 0","def get_title(reg_doc):\n parent = reg_doc.xpath('//PART/HD')[0]\n title = parent.text\n return title","def _parse_title(self, item):\n title_str = \" \".join(item.css(\"td:first-child *::text\").extract()).strip()\n content_match = re.search(r\"(?<=\\().*(?=\\))\", title_str)\n if not content_match:\n return \"Advisory Board\"\n return content_match.group().title()","def get_title(self):\n return SettingsBase.get_setting(self, 'title')","def get_window_title(self):\n\n return self.window_title","def title(self):\n return self.__values['title']","def title(self):\n return self.browser.get_attribute(\"title\", self)","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def title(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"title\")","def get_title(self):\n title_tag = self.soup.find('title').text\n title_list = string.split(sep='-')\n self.title = title_list[0].strip()","def title(self):\n title_element = self.dom.find(\".//title\")\n if title_element is None or title_element.text is None:\n return \"\"\n else:\n return title_element.text.strip()"],"string":"[\n \"def get_title():\",\n \"def get_title(self):\\n return self.run_command('get_title')[0]\",\n \"def get_title(self) -> Optional[str]:\\n return self.title\",\n \"def get_title(cls, obj, **kwargs):\\n if isinstance(obj.data, dict):\\n titles = filter(None, get_value(obj.data, \\\"titles.title\\\", []))\\n if titles:\\n # Show first title that evaluates to True\\n return titles[0]\\n return \\\"No title available\\\"\",\n \"def get_title(self):\\n return self._get_title_()\",\n \"def get_title(self):\\n return self.title\",\n \"def get_title(self):\\n return self.title\",\n \"def get_title(self):\\n return self.title\",\n \"def get_title(self):\\n title = self.title\\n if not title and self.parent_id:\\n title = self.parent.title\\n return title\",\n \"def safe_title(self):\\n try:\\n return self.title\\n except ObjectDoesNotExist:\\n return None\",\n \"def title(self):\\n return self.get(self._names[\\\"title\\\"])\",\n \"def title(self):\\n return self.get(self._names[\\\"title\\\"])\",\n \"def current(self):\\n return self.title_headings[self._idx]\",\n \"def get_title(self):\\n return self._title\",\n \"def get_title(self):\\n return self._title\",\n \"def get_title(self):\\n return self._title\",\n \"def get_title(self, obj):\\n title = obj.habit.title\\n return title\",\n \"def get_title(self):\\n return self.metadata['title']\",\n \"def get_title(self):\\n\\n return self.title\",\n \"def getTitle(self, item):\\n return item.Title() or item.getId()\",\n \"def Title(self, default={}):\\n return HEP.TitleObject(self.data.get('title', default))\",\n \"def title(self):\\n return self.run_command('title')[0]\",\n \"def getTitle(self):\\n return self._title\",\n \"def GetTitle(self):\\n return self._title\",\n \"def get_title(self) -> str:\\n pass\",\n \"def get_title(self):\\n\\n return self._title\",\n \"def title(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def get_title(self):\\n return self._select_interface(self._rc_get_title, self._http_get_title)\",\n \"def title(self):\\n\\n return self._title\",\n \"def test_get_title(double_title, single_title, empty_title):\\n assert get_title(double_title) == \\\"Parton distributions with LHC data\\\"\\n assert get_title(single_title) == \\\"The Large Hadron Collider\\\"\\n assert get_title(empty_title) == \\\"\\\"\\n\\n no_title_key = {\\n \\\"not_titles\\\": []\\n }\\n assert get_title(no_title_key) == \\\"\\\"\",\n \"def title(self) -> Optional[str]:\\n return self.get(\\\"/Title\\\")\",\n \"def Title(self, default=None):\\n return self.data.get('title', default)\",\n \"def get_title(self):\\n\\n title = ''\\n doc = self.article.doc\\n\\n title_element = self.parser.getElementsByTag(doc, tag='title')\\n # no title found\\n if title_element is None or len(title_element) == 0:\\n return title\\n\\n # title elem found\\n title_text = self.parser.getText(title_element[0])\\n used_delimeter = False\\n\\n # split title with |\\n if '|' in title_text:\\n title_text = self.split_title(title_text, PIPE_SPLITTER)\\n used_delimeter = True\\n\\n # split title with -\\n if not used_delimeter and '-' in title_text:\\n title_text = self.split_title(title_text, DASH_SPLITTER)\\n used_delimeter = True\\n\\n # split title with »\\n if not used_delimeter and u'»' in title_text:\\n title_text = self.split_title(title_text, ARROWS_SPLITTER)\\n used_delimeter = True\\n\\n # split title with :\\n if not used_delimeter and ':' in title_text:\\n title_text = self.split_title(title_text, COLON_SPLITTER)\\n used_delimeter = True\\n\\n title = MOTLEY_REPLACEMENT.replaceAll(title_text)\\n return title\",\n \"def getTitle(self):\\n return self.__title__\",\n \"def title(self) -> Title:\\n return self._title\",\n \"def configured_title(self):\\n return self.get('title', self.DEFAULT_SPACE_TITLE)\",\n \"def title(self):\\n return self.get(\\\"title\\\")\",\n \"def get_title(self):\\n meta = self.get_meta_data()\\n if \\\"og:title\\\" in meta:\\n return meta[\\\"og:title\\\"]\\n else:\\n soup = BeautifulSoup(self.TARGET_DATA)\\n title = soup.find('title')\\n if title:\\n return title.text\\n else:\\n return \\\"No Title\\\"\",\n \"def get_title_repr(self) -> str:\\n try:\\n return Title[self.title].value\\n except (KeyError, ValueError):\\n pass\",\n \"def title(self):\\n if self._title is None:\\n if Path(self.rst_path).exists():\\n self._title = self.get_title_from_rst()\\n elif Path(self.ipynb_path).exists():\\n self._title = self.get_title_from_ipynb()\\n else:\\n pass\\n return self._title\",\n \"def get_title(self):\\n try:\\n return self.get_translation().title\\n except MissingTranslation:\\n return _(\\\"(No title)\\\")\",\n \"def title(self):\\n return self.values.get('title')\",\n \"def title(self):\\n return self['title']\",\n \"def title(self) -> Optional[str]:\\n if self._title is not None:\\n return self._title\\n if self._target_object is not None and isinstance(\\n self._target_object, pystac.Catalog\\n ):\\n return self._target_object.title\\n return None\",\n \"def selected_title(self):\\r\\n try:\\r\\n return menu_selected[self.name]\\r\\n except KeyError:\\r\\n return NavButton.selected_title(self)\",\n \"def istitle(self):\\n return istitle(self)\",\n \"def getTitle(self):\\n\\n return self._title\",\n \"def title(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def check_title(self):\\n currenttitle = self.driver.title\\n assert self.TITLE in currenttitle, 'Title not expected. Actual: ' + currenttitle + ', Expected: ' + self.TITLE\",\n \"def title(self):\\n return self.container['title']\",\n \"async def title(self):\\n if not hasattr(self, \\\"_title\\\"):\\n self._title = await Stack.fetch_stack_value(self, \\\"http://purl.org/dc/terms/title\\\", await self.uuid)\\n return self._title\",\n \"def parsed_title(self):\\n return parse_pr_title(self.title)\",\n \"def title(self) -> str:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> str:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> str:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self):\\n return self._title\",\n \"def title(self):\\n return self._title\",\n \"def title(self):\\n return self._title\",\n \"def title(self):\\n return self._title\",\n \"def title(self):\\n return self._title\",\n \"def title(self):\\n return self._title\",\n \"def title(self) -> str:\\n\\t\\t# pylint: disable=unsubscriptable-object\\n\\t\\treturn self.value[1]\",\n \"def _parse_title(self, item):\\n title = item[\\\"Title\\\"]\\n return title\",\n \"def title(self):\\n\\t\\treturn self.page_title\",\n \"def title(self):\\n return self.properties.get('Title', None)\",\n \"def getTitle(self):\\n\\n # print(self.soupObject.title.string)\\n try:\\n s = self.soupObject.find(\\\"meta\\\", attrs={\\\"name\\\": \\\"twitter:title\\\"})\\n self.title = str(s['content'])\\n self.title = self.title.replace(\\\"/\\\", \\\"\\\")\\n self.title = self.title.strip()\\n if not self.title:\\n s = int(\\\"deliberateError\\\")\\n\\n # except\\n except:\\n self.title = \\\"Amazonsubtitles\\\"\\n\\n pass\",\n \"def selected_title(self):\\r\\n return self.title\",\n \"def short_title(self):\\n if hasattr(self, \\\"title\\\"):\\n return self.title\\n else:\\n return \\\"\\\"\",\n \"def get_title(self):\\n title = self.driver.title\\n return title\",\n \"def title(self):\\n return self.metadata.get('title')\",\n \"def current(self, title):\\n if self.valid_title(title):\\n return self.timers[title]['last']\\n else:\\n return 0\",\n \"def get_title(reg_doc):\\n parent = reg_doc.xpath('//PART/HD')[0]\\n title = parent.text\\n return title\",\n \"def _parse_title(self, item):\\n title_str = \\\" \\\".join(item.css(\\\"td:first-child *::text\\\").extract()).strip()\\n content_match = re.search(r\\\"(?<=\\\\().*(?=\\\\))\\\", title_str)\\n if not content_match:\\n return \\\"Advisory Board\\\"\\n return content_match.group().title()\",\n \"def get_title(self):\\n return SettingsBase.get_setting(self, 'title')\",\n \"def get_window_title(self):\\n\\n return self.window_title\",\n \"def title(self):\\n return self.__values['title']\",\n \"def title(self):\\n return self.browser.get_attribute(\\\"title\\\", self)\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def get_title(self):\\n title_tag = self.soup.find('title').text\\n title_list = string.split(sep='-')\\n self.title = title_list[0].strip()\",\n \"def title(self):\\n title_element = self.dom.find(\\\".//title\\\")\\n if title_element is None or title_element.text is None:\\n return \\\"\\\"\\n else:\\n return title_element.text.strip()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7317102","0.7292215","0.7144462","0.7138358","0.70548296","0.7035024","0.7035024","0.7035024","0.7024971","0.7007832","0.6984208","0.6984208","0.69815016","0.69728166","0.69728166","0.69728166","0.6934254","0.68951046","0.68767846","0.68251956","0.6817628","0.6802512","0.6790152","0.67708194","0.67592907","0.67462224","0.6702948","0.6702948","0.6702948","0.6702948","0.6702948","0.67025715","0.6700838","0.6688426","0.668644","0.6664847","0.6657235","0.664502","0.6641055","0.66321206","0.66134685","0.6607853","0.6588632","0.6586029","0.6568574","0.6530646","0.6525037","0.6524416","0.65044314","0.6499982","0.6499522","0.64829475","0.64753723","0.64673513","0.6466069","0.6463529","0.6462674","0.6462674","0.6462674","0.64617866","0.64617866","0.64617866","0.64617866","0.64617866","0.64617866","0.64580643","0.6449829","0.6421725","0.64111876","0.6397006","0.63919723","0.6389227","0.63799614","0.63728964","0.63324183","0.63143516","0.63064885","0.6306158","0.630339","0.6295465","0.62888396","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.62882346","0.6287632","0.62861764"],"string":"[\n \"0.7317102\",\n \"0.7292215\",\n \"0.7144462\",\n \"0.7138358\",\n \"0.70548296\",\n \"0.7035024\",\n \"0.7035024\",\n \"0.7035024\",\n \"0.7024971\",\n \"0.7007832\",\n \"0.6984208\",\n \"0.6984208\",\n \"0.69815016\",\n \"0.69728166\",\n \"0.69728166\",\n \"0.69728166\",\n \"0.6934254\",\n \"0.68951046\",\n \"0.68767846\",\n \"0.68251956\",\n \"0.6817628\",\n \"0.6802512\",\n \"0.6790152\",\n \"0.67708194\",\n \"0.67592907\",\n \"0.67462224\",\n \"0.6702948\",\n \"0.6702948\",\n \"0.6702948\",\n \"0.6702948\",\n \"0.6702948\",\n \"0.67025715\",\n \"0.6700838\",\n \"0.6688426\",\n \"0.668644\",\n \"0.6664847\",\n \"0.6657235\",\n \"0.664502\",\n \"0.6641055\",\n \"0.66321206\",\n \"0.66134685\",\n \"0.6607853\",\n \"0.6588632\",\n \"0.6586029\",\n \"0.6568574\",\n \"0.6530646\",\n \"0.6525037\",\n \"0.6524416\",\n \"0.65044314\",\n \"0.6499982\",\n \"0.6499522\",\n \"0.64829475\",\n \"0.64753723\",\n \"0.64673513\",\n \"0.6466069\",\n \"0.6463529\",\n \"0.6462674\",\n \"0.6462674\",\n \"0.6462674\",\n \"0.64617866\",\n \"0.64617866\",\n \"0.64617866\",\n \"0.64617866\",\n \"0.64617866\",\n \"0.64617866\",\n \"0.64580643\",\n \"0.6449829\",\n \"0.6421725\",\n \"0.64111876\",\n \"0.6397006\",\n \"0.63919723\",\n \"0.6389227\",\n \"0.63799614\",\n \"0.63728964\",\n \"0.63324183\",\n \"0.63143516\",\n \"0.63064885\",\n \"0.6306158\",\n \"0.630339\",\n \"0.6295465\",\n \"0.62888396\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.62882346\",\n \"0.6287632\",\n \"0.62861764\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":81799,"cells":{"query":{"kind":"string","value":"Helper function for getting attribute or None from wanted/current title."},"document":{"kind":"string","value":"def get_title_obj_attribute(self, attrname, language=None, fallback=True, version_id=None, force_reload=False):\n try:\n return getattr(self.get_title_obj(language, fallback, version_id, force_reload), attrname)\n except AttributeError:\n return None"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_title(self) -> Optional[str]:\n return self.title","def get_title():","def get_title(self):\n return self.run_command('get_title')[0]","def getAttrName(self, context):\r\n return self.attr if self.attr is not None else context.attr","def _get_attribute(self):\n return self.split_text[1] if len(self.split_text) > 1 else \"\"","def get_title(cls, obj, **kwargs):\n if isinstance(obj.data, dict):\n titles = filter(None, get_value(obj.data, \"titles.title\", []))\n if titles:\n # Show first title that evaluates to True\n return titles[0]\n return \"No title available\"","def get_attr(self, location, attr, default=None):\r\n return self.get_attrs(location).get(attr, default)","def title(self) -> Optional[str]:\n if self._title is not None:\n return self._title\n if self._target_object is not None and isinstance(\n self._target_object, pystac.Catalog\n ):\n return self._target_object.title\n return None","def title(self) -> Optional[str]:\n return self.get(\"/Title\")","def get(self, attr):\n try:\n return getattr(self, attr)\n except:\n print(\"%s is not an attribute of this instance\" % attr)\n return None","def title_or_id(context):\n title = getattr(context, 'title', '')\n if not title:\n if hasattr(context, '__name__'):\n title = getattr(context, '__name__', '')\n elif hasattr(context, 'getId'):\n title = context.getId()\n return title","def title(self) -> \"str\":\n return self._attrs.get(\"title\")","def title(self) -> \"str\":\n return self._attrs.get(\"title\")","def title(self) -> \"str\":\n return self._attrs.get(\"title\")","def title(self) -> \"str\":\n return self._attrs.get(\"title\")","def title(self):\n return self.get(self._names[\"title\"])","def title(self):\n return self.get(self._names[\"title\"])","def get_title(self):\n return self.metadata['title']","def find_info( attr, kw, metadata, default='' ):\n str_attr = str(attr)\n return kw.get( str_attr, metadata.get( str_attr, default ) )","def get_title(self):\n return self.title","def get_title(self):\n return self.title","def get_title(self):\n return self.title","def title(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"title\")","def title(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"title\")","def title(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"title\")","def title(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"title\")","def title(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"title\")","def get_title(self):\n return self._get_title_()","def get_attr(attributes, name):\n try:\n return attributes.getValue(name)\n except KeyError:\n return None","def safe_title(self):\n try:\n return self.title\n except ObjectDoesNotExist:\n return None","def attr(elem, attr):\n try:\n return elem[attr]\n except:\n return \"\"","def attr(elem, attr):\n try:\n return elem[attr]\n except:\n return \"\"","def get_propattr(self, naam, attr):\r\n h = self._root.find(naam)\r\n if h is None:\r\n h = \"\"\r\n else:\r\n hh = h.get(attr)\r\n if hh is None:\r\n h = \"\"\r\n else:\r\n h = hh\r\n return h","def get_prop(node, name):\n title = node.get(\"title\")\n props = title.split(\";\")\n for prop in props:\n (key, args) = prop.split(None, 1)\n args = args.strip('\"')\n if key == name:\n return args\n return None","def getTitle(self, item):\n return item.Title() or item.getId()","def get_title(self, obj):\n title = obj.habit.title\n return title","def get_alt(self, obj):\n return obj.Description() or obj.Title()","def get_title(self):\n meta = self.get_meta_data()\n if \"og:title\" in meta:\n return meta[\"og:title\"]\n else:\n soup = BeautifulSoup(self.TARGET_DATA)\n title = soup.find('title')\n if title:\n return title.text\n else:\n return \"No Title\"","def title(self):\n return self.get(\"title\")","def get_feature_title(self, feature):\n data = feature.properties.get(self.feature_title_property.key, '')\\\n if self.feature_title_property else feature.identifier\n return data or feature.identifier","def title(self):\n return self.browser.get_attribute(\"title\", self)","def get_title(self):\n title = self.title\n if not title and self.parent_id:\n title = self.parent.title\n return title","def getattribute(objeto, name: str):\r\n # Get internal dict value matching name.\r\n value = objeto.__dict__.get(name)\r\n if not value:\r\n # Raise AttributeError if attribute value not found.\r\n return None\r\n # Return attribute value.\r\n return value","def attribute(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"attribute\")","def attribute(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"attribute\")","def attribute(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"attribute\")","def get_date_if_not_none(element):\n if element is None:\n text = None\n else:\n text = element.attrs.get('title')\n return text","def Title(self, default=None):\n return self.data.get('title', default)","def get_title(self) -> str:\n pass","def get_title(self):\n return self._title","def get_title(self):\n return self._title","def get_title(self):\n return self._title","def title(self):\n return self.run_command('title')[0]","def get_attr(name):\n userDoc = get_user()\n _idx = userDoc.index.get(name, None)\n\n if _idx is not None:\n return userDoc.attributes[_idx]\n else:\n return None","def get_attr(obj, attr):\n return getattr(obj, attr)","def _get_attr(self, attr, root=None):\n with self._h5file('r') as h5file:\n if root is None:\n obj = h5file\n else:\n obj = h5file[root]\n return get_decoded(obj.attrs, attr)[attr]","def title(self):\n\n return self._title","def title(self):\n return self['title']","def getTitle(movieInfo):\n if \"title\" in movieInfo:\n #We remove the punctuation\n title = \"\".join(c for c in movieInfo[\"title\"] if c not in punctuation)\n #We return the title as a list of words in the right format\n return [ _format(w) for w in title.split() ]\n else:\n raise AttributeError(\"%s instance has no attribute title\" % movieInfo)","def title(self) -> str:\n\t\t# pylint: disable=unsubscriptable-object\n\t\treturn self.value[1]","def get_title(reg_doc):\n parent = reg_doc.xpath('//PART/HD')[0]\n title = parent.text\n return title","def get_info_about(attr):\n return getattr(get_info_about, attr)","def get_subname(get, node):\n if isinstance(node, ast.Attribute) and get(node.value) == 'parent':\n return node.attr","def get_title(self):\n\n return self.title","def short_title(self):\n if hasattr(self, \"title\"):\n return self.title\n else:\n return \"\"","def get_title(doc):\r\n title_nodes = doc.getElementsByTagName('title')\r\n if len(title_nodes) > 0:\r\n return title_nodes[0].firstChild.nodeValue","def getAttr(self, name, *args):\n if len(args) > 0:\n return self.attrs.get( name, args[0] )\n return self.attrs[name]","def getattr(self, name, *default):\n for attr in self.attributes:\n if attr.name.lower() == name.lower():\n return attr\n else:\n if default:\n return default[0]\n raise KeyError(name)","def try_to_get_attribute(self, entry, *args):\n try:\n result = entry\n for arg in args:\n result = result[arg]\n return result\n except AttributeError:\n return None","def getAttr(self, key=None):\n if key is None:\n return self.attribute\n else:\n return self.attribute.get(key)","def title(self) -> str:\n return self._search_in_properties(ATTR_TITLE)","def __getattr__(self, attr):\n return self.product.get(attr, \"\")","def OnGetItemAttr( self, item ):\n if self.indicated > -1 and item == self.indicated:\n return self.indicated_attribute\n return None","def getitem(\n self, obj: t.Any, argument: t.Union[str, t.Any]\n ) -> t.Union[t.Any, Undefined]:\n try:\n return obj[argument]\n except (AttributeError, TypeError, LookupError):\n if isinstance(argument, str):\n try:\n attr = str(argument)\n except Exception:\n pass\n else:\n try:\n return getattr(obj, attr)\n except AttributeError:\n pass\n return self.undefined(obj=obj, name=argument)","def _getter(obj, attr):\n _get = attrgetter(attr)\n try:\n return _get(obj)\n except:\n return None","def __getattr__(self, item):\n return getattr(self.desc, item)","def title_or_url(node):\r\n title = getattr(node, 'display_name', None)\r\n if not title:\r\n title = node.location.to_deprecated_string()\r\n return title","def title(self):\n return self.properties.get('Title', None)","def _parse_title(self, item):\n title = item[\"Title\"]\n return title","def configured_title(self):\n return self.get('title', self.DEFAULT_SPACE_TITLE)","def get_title(line):\n title = line.split(' (')[0]\n return title","def get(self, att):\n return getattr(self, att)","def get_attr(self, name: str):\n return self.call(name)","def get_title_repr(self) -> str:\n try:\n return Title[self.title].value\n except (KeyError, ValueError):\n pass","def __title(self, conf):\n return conf[\"conf_json\"][0][\"title\"]","async def title(self):\n if not hasattr(self, \"_title\"):\n self._title = await Stack.fetch_stack_value(self, \"http://purl.org/dc/terms/title\", await self.uuid)\n return self._title","def getAttribute(self, username, attribute):\n if username in self.contents:\n if attribute in self.contents[username]:\n return self.contents[username][attribute]\n else:\n self.log.warning(\"Attribute '{}' not found for user '{}'\".format(attribute, username))\n return None\n else:\n self.log.warning(\"User '{}' not found\".format(username))","def get_title(article):\n title = article.find(\"div\", class_=\"col-sm-6 product_main\").h1.text\n return title","def __get_attr_helper(self, object, field, default=None):\n # TODO: Make PR to fix this ^ bug\n if hasattr(object, field):\n return getattr(object, field)\n\n return default","def get_attribute(self, attribute: str) -> str:\n pass","def title(self):\n return self.metadata.get('title')","def _get_optional_attribute(self, profile, attribute, default_value=\"\"):\n self.validate_root()\n self.is_valid_profile(profile)\n if attribute not in self.config[self.ROOT][profile]:\n return default_value\n return self.config[self.ROOT][profile][attribute]","def get_title(self):\n title = self.driver.title\n return title","def __getattribute__(self,name):\n try:\n return object.__getattribute__(self,name)\n except AttributeError:\n extraPO = object.__getattribute__(self,'_extraPO')\n\n if hasattr(extraPO,name):\n return getattr(extraPO,name) # HIDDEN!\n\n _attr_err_msg = object.__getattribute__(self,'_attr_err_msg')\n\n raise AttributeError(_attr_err_msg(name,[self,extraPO]))","def selected_title(self):\r\n try:\r\n return menu_selected[self.name]\r\n except KeyError:\r\n return NavButton.selected_title(self)","def title(self) -> float:\n return self.product.name if self.product else self.name","def get_attr(self, name, default=None):\n try:\n return self.managedobjectattribute_set.get(key=name).value\n except ManagedObjectAttribute.DoesNotExist:\n return default","def name(self):\r\n titles = self.q(css=self._bounded_selector(self.NAME_SELECTOR)).text\r\n if titles:\r\n return titles[0]\r\n else:\r\n return None","def get_title(mods):\n title = mods.find(\"{{{0}}}titleInfo/{{{0}}}title\".format(common.MODS_NS))\n return title.text","def get(self, name, default=None):\n try:\n return self.__getattribute__(name, default)\n except AttributeError:\n return default"],"string":"[\n \"def get_title(self) -> Optional[str]:\\n return self.title\",\n \"def get_title():\",\n \"def get_title(self):\\n return self.run_command('get_title')[0]\",\n \"def getAttrName(self, context):\\r\\n return self.attr if self.attr is not None else context.attr\",\n \"def _get_attribute(self):\\n return self.split_text[1] if len(self.split_text) > 1 else \\\"\\\"\",\n \"def get_title(cls, obj, **kwargs):\\n if isinstance(obj.data, dict):\\n titles = filter(None, get_value(obj.data, \\\"titles.title\\\", []))\\n if titles:\\n # Show first title that evaluates to True\\n return titles[0]\\n return \\\"No title available\\\"\",\n \"def get_attr(self, location, attr, default=None):\\r\\n return self.get_attrs(location).get(attr, default)\",\n \"def title(self) -> Optional[str]:\\n if self._title is not None:\\n return self._title\\n if self._target_object is not None and isinstance(\\n self._target_object, pystac.Catalog\\n ):\\n return self._target_object.title\\n return None\",\n \"def title(self) -> Optional[str]:\\n return self.get(\\\"/Title\\\")\",\n \"def get(self, attr):\\n try:\\n return getattr(self, attr)\\n except:\\n print(\\\"%s is not an attribute of this instance\\\" % attr)\\n return None\",\n \"def title_or_id(context):\\n title = getattr(context, 'title', '')\\n if not title:\\n if hasattr(context, '__name__'):\\n title = getattr(context, '__name__', '')\\n elif hasattr(context, 'getId'):\\n title = context.getId()\\n return title\",\n \"def title(self) -> \\\"str\\\":\\n return self._attrs.get(\\\"title\\\")\",\n \"def title(self) -> \\\"str\\\":\\n return self._attrs.get(\\\"title\\\")\",\n \"def title(self) -> \\\"str\\\":\\n return self._attrs.get(\\\"title\\\")\",\n \"def title(self) -> \\\"str\\\":\\n return self._attrs.get(\\\"title\\\")\",\n \"def title(self):\\n return self.get(self._names[\\\"title\\\"])\",\n \"def title(self):\\n return self.get(self._names[\\\"title\\\"])\",\n \"def get_title(self):\\n return self.metadata['title']\",\n \"def find_info( attr, kw, metadata, default='' ):\\n str_attr = str(attr)\\n return kw.get( str_attr, metadata.get( str_attr, default ) )\",\n \"def get_title(self):\\n return self.title\",\n \"def get_title(self):\\n return self.title\",\n \"def get_title(self):\\n return self.title\",\n \"def title(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def title(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"title\\\")\",\n \"def get_title(self):\\n return self._get_title_()\",\n \"def get_attr(attributes, name):\\n try:\\n return attributes.getValue(name)\\n except KeyError:\\n return None\",\n \"def safe_title(self):\\n try:\\n return self.title\\n except ObjectDoesNotExist:\\n return None\",\n \"def attr(elem, attr):\\n try:\\n return elem[attr]\\n except:\\n return \\\"\\\"\",\n \"def attr(elem, attr):\\n try:\\n return elem[attr]\\n except:\\n return \\\"\\\"\",\n \"def get_propattr(self, naam, attr):\\r\\n h = self._root.find(naam)\\r\\n if h is None:\\r\\n h = \\\"\\\"\\r\\n else:\\r\\n hh = h.get(attr)\\r\\n if hh is None:\\r\\n h = \\\"\\\"\\r\\n else:\\r\\n h = hh\\r\\n return h\",\n \"def get_prop(node, name):\\n title = node.get(\\\"title\\\")\\n props = title.split(\\\";\\\")\\n for prop in props:\\n (key, args) = prop.split(None, 1)\\n args = args.strip('\\\"')\\n if key == name:\\n return args\\n return None\",\n \"def getTitle(self, item):\\n return item.Title() or item.getId()\",\n \"def get_title(self, obj):\\n title = obj.habit.title\\n return title\",\n \"def get_alt(self, obj):\\n return obj.Description() or obj.Title()\",\n \"def get_title(self):\\n meta = self.get_meta_data()\\n if \\\"og:title\\\" in meta:\\n return meta[\\\"og:title\\\"]\\n else:\\n soup = BeautifulSoup(self.TARGET_DATA)\\n title = soup.find('title')\\n if title:\\n return title.text\\n else:\\n return \\\"No Title\\\"\",\n \"def title(self):\\n return self.get(\\\"title\\\")\",\n \"def get_feature_title(self, feature):\\n data = feature.properties.get(self.feature_title_property.key, '')\\\\\\n if self.feature_title_property else feature.identifier\\n return data or feature.identifier\",\n \"def title(self):\\n return self.browser.get_attribute(\\\"title\\\", self)\",\n \"def get_title(self):\\n title = self.title\\n if not title and self.parent_id:\\n title = self.parent.title\\n return title\",\n \"def getattribute(objeto, name: str):\\r\\n # Get internal dict value matching name.\\r\\n value = objeto.__dict__.get(name)\\r\\n if not value:\\r\\n # Raise AttributeError if attribute value not found.\\r\\n return None\\r\\n # Return attribute value.\\r\\n return value\",\n \"def attribute(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"attribute\\\")\",\n \"def attribute(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"attribute\\\")\",\n \"def attribute(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"attribute\\\")\",\n \"def get_date_if_not_none(element):\\n if element is None:\\n text = None\\n else:\\n text = element.attrs.get('title')\\n return text\",\n \"def Title(self, default=None):\\n return self.data.get('title', default)\",\n \"def get_title(self) -> str:\\n pass\",\n \"def get_title(self):\\n return self._title\",\n \"def get_title(self):\\n return self._title\",\n \"def get_title(self):\\n return self._title\",\n \"def title(self):\\n return self.run_command('title')[0]\",\n \"def get_attr(name):\\n userDoc = get_user()\\n _idx = userDoc.index.get(name, None)\\n\\n if _idx is not None:\\n return userDoc.attributes[_idx]\\n else:\\n return None\",\n \"def get_attr(obj, attr):\\n return getattr(obj, attr)\",\n \"def _get_attr(self, attr, root=None):\\n with self._h5file('r') as h5file:\\n if root is None:\\n obj = h5file\\n else:\\n obj = h5file[root]\\n return get_decoded(obj.attrs, attr)[attr]\",\n \"def title(self):\\n\\n return self._title\",\n \"def title(self):\\n return self['title']\",\n \"def getTitle(movieInfo):\\n if \\\"title\\\" in movieInfo:\\n #We remove the punctuation\\n title = \\\"\\\".join(c for c in movieInfo[\\\"title\\\"] if c not in punctuation)\\n #We return the title as a list of words in the right format\\n return [ _format(w) for w in title.split() ]\\n else:\\n raise AttributeError(\\\"%s instance has no attribute title\\\" % movieInfo)\",\n \"def title(self) -> str:\\n\\t\\t# pylint: disable=unsubscriptable-object\\n\\t\\treturn self.value[1]\",\n \"def get_title(reg_doc):\\n parent = reg_doc.xpath('//PART/HD')[0]\\n title = parent.text\\n return title\",\n \"def get_info_about(attr):\\n return getattr(get_info_about, attr)\",\n \"def get_subname(get, node):\\n if isinstance(node, ast.Attribute) and get(node.value) == 'parent':\\n return node.attr\",\n \"def get_title(self):\\n\\n return self.title\",\n \"def short_title(self):\\n if hasattr(self, \\\"title\\\"):\\n return self.title\\n else:\\n return \\\"\\\"\",\n \"def get_title(doc):\\r\\n title_nodes = doc.getElementsByTagName('title')\\r\\n if len(title_nodes) > 0:\\r\\n return title_nodes[0].firstChild.nodeValue\",\n \"def getAttr(self, name, *args):\\n if len(args) > 0:\\n return self.attrs.get( name, args[0] )\\n return self.attrs[name]\",\n \"def getattr(self, name, *default):\\n for attr in self.attributes:\\n if attr.name.lower() == name.lower():\\n return attr\\n else:\\n if default:\\n return default[0]\\n raise KeyError(name)\",\n \"def try_to_get_attribute(self, entry, *args):\\n try:\\n result = entry\\n for arg in args:\\n result = result[arg]\\n return result\\n except AttributeError:\\n return None\",\n \"def getAttr(self, key=None):\\n if key is None:\\n return self.attribute\\n else:\\n return self.attribute.get(key)\",\n \"def title(self) -> str:\\n return self._search_in_properties(ATTR_TITLE)\",\n \"def __getattr__(self, attr):\\n return self.product.get(attr, \\\"\\\")\",\n \"def OnGetItemAttr( self, item ):\\n if self.indicated > -1 and item == self.indicated:\\n return self.indicated_attribute\\n return None\",\n \"def getitem(\\n self, obj: t.Any, argument: t.Union[str, t.Any]\\n ) -> t.Union[t.Any, Undefined]:\\n try:\\n return obj[argument]\\n except (AttributeError, TypeError, LookupError):\\n if isinstance(argument, str):\\n try:\\n attr = str(argument)\\n except Exception:\\n pass\\n else:\\n try:\\n return getattr(obj, attr)\\n except AttributeError:\\n pass\\n return self.undefined(obj=obj, name=argument)\",\n \"def _getter(obj, attr):\\n _get = attrgetter(attr)\\n try:\\n return _get(obj)\\n except:\\n return None\",\n \"def __getattr__(self, item):\\n return getattr(self.desc, item)\",\n \"def title_or_url(node):\\r\\n title = getattr(node, 'display_name', None)\\r\\n if not title:\\r\\n title = node.location.to_deprecated_string()\\r\\n return title\",\n \"def title(self):\\n return self.properties.get('Title', None)\",\n \"def _parse_title(self, item):\\n title = item[\\\"Title\\\"]\\n return title\",\n \"def configured_title(self):\\n return self.get('title', self.DEFAULT_SPACE_TITLE)\",\n \"def get_title(line):\\n title = line.split(' (')[0]\\n return title\",\n \"def get(self, att):\\n return getattr(self, att)\",\n \"def get_attr(self, name: str):\\n return self.call(name)\",\n \"def get_title_repr(self) -> str:\\n try:\\n return Title[self.title].value\\n except (KeyError, ValueError):\\n pass\",\n \"def __title(self, conf):\\n return conf[\\\"conf_json\\\"][0][\\\"title\\\"]\",\n \"async def title(self):\\n if not hasattr(self, \\\"_title\\\"):\\n self._title = await Stack.fetch_stack_value(self, \\\"http://purl.org/dc/terms/title\\\", await self.uuid)\\n return self._title\",\n \"def getAttribute(self, username, attribute):\\n if username in self.contents:\\n if attribute in self.contents[username]:\\n return self.contents[username][attribute]\\n else:\\n self.log.warning(\\\"Attribute '{}' not found for user '{}'\\\".format(attribute, username))\\n return None\\n else:\\n self.log.warning(\\\"User '{}' not found\\\".format(username))\",\n \"def get_title(article):\\n title = article.find(\\\"div\\\", class_=\\\"col-sm-6 product_main\\\").h1.text\\n return title\",\n \"def __get_attr_helper(self, object, field, default=None):\\n # TODO: Make PR to fix this ^ bug\\n if hasattr(object, field):\\n return getattr(object, field)\\n\\n return default\",\n \"def get_attribute(self, attribute: str) -> str:\\n pass\",\n \"def title(self):\\n return self.metadata.get('title')\",\n \"def _get_optional_attribute(self, profile, attribute, default_value=\\\"\\\"):\\n self.validate_root()\\n self.is_valid_profile(profile)\\n if attribute not in self.config[self.ROOT][profile]:\\n return default_value\\n return self.config[self.ROOT][profile][attribute]\",\n \"def get_title(self):\\n title = self.driver.title\\n return title\",\n \"def __getattribute__(self,name):\\n try:\\n return object.__getattribute__(self,name)\\n except AttributeError:\\n extraPO = object.__getattribute__(self,'_extraPO')\\n\\n if hasattr(extraPO,name):\\n return getattr(extraPO,name) # HIDDEN!\\n\\n _attr_err_msg = object.__getattribute__(self,'_attr_err_msg')\\n\\n raise AttributeError(_attr_err_msg(name,[self,extraPO]))\",\n \"def selected_title(self):\\r\\n try:\\r\\n return menu_selected[self.name]\\r\\n except KeyError:\\r\\n return NavButton.selected_title(self)\",\n \"def title(self) -> float:\\n return self.product.name if self.product else self.name\",\n \"def get_attr(self, name, default=None):\\n try:\\n return self.managedobjectattribute_set.get(key=name).value\\n except ManagedObjectAttribute.DoesNotExist:\\n return default\",\n \"def name(self):\\r\\n titles = self.q(css=self._bounded_selector(self.NAME_SELECTOR)).text\\r\\n if titles:\\r\\n return titles[0]\\r\\n else:\\r\\n return None\",\n \"def get_title(mods):\\n title = mods.find(\\\"{{{0}}}titleInfo/{{{0}}}title\\\".format(common.MODS_NS))\\n return title.text\",\n \"def get(self, name, default=None):\\n try:\\n return self.__getattribute__(name, default)\\n except AttributeError:\\n return default\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6739067","0.6692714","0.65235364","0.63904065","0.63688284","0.6344936","0.6288744","0.62723464","0.62668854","0.62502044","0.6228555","0.6215669","0.6215669","0.6215669","0.6215669","0.6191291","0.6191291","0.61492777","0.6135957","0.61327934","0.61327934","0.61327934","0.61280537","0.61280537","0.61280537","0.61280537","0.61280537","0.6125419","0.61230046","0.6112481","0.61122185","0.61122185","0.6109725","0.61094314","0.6104993","0.6099451","0.60868835","0.6060397","0.603659","0.6010346","0.60086906","0.60023665","0.5983982","0.5983496","0.5983496","0.5983496","0.5976143","0.5973214","0.59432775","0.5939006","0.5939006","0.5939006","0.5932887","0.59050035","0.5898641","0.58985984","0.58885455","0.58823115","0.58795863","0.58764434","0.58756447","0.5872827","0.5856093","0.58497196","0.5847494","0.58362347","0.58300734","0.5826567","0.5820205","0.5813995","0.5809035","0.57815564","0.57728976","0.57636887","0.57601833","0.5757536","0.57517934","0.574895","0.574493","0.57441026","0.5727351","0.57163733","0.57133466","0.5701146","0.5698315","0.56914896","0.56908023","0.5689189","0.56803685","0.56801623","0.5674343","0.56712824","0.5661557","0.56540877","0.5647789","0.5647532","0.5639027","0.56384957","0.56202346","0.5616633"],"string":"[\n \"0.6739067\",\n \"0.6692714\",\n \"0.65235364\",\n \"0.63904065\",\n \"0.63688284\",\n \"0.6344936\",\n \"0.6288744\",\n \"0.62723464\",\n \"0.62668854\",\n \"0.62502044\",\n \"0.6228555\",\n \"0.6215669\",\n \"0.6215669\",\n \"0.6215669\",\n \"0.6215669\",\n \"0.6191291\",\n \"0.6191291\",\n \"0.61492777\",\n \"0.6135957\",\n \"0.61327934\",\n \"0.61327934\",\n \"0.61327934\",\n \"0.61280537\",\n \"0.61280537\",\n \"0.61280537\",\n \"0.61280537\",\n \"0.61280537\",\n \"0.6125419\",\n \"0.61230046\",\n \"0.6112481\",\n \"0.61122185\",\n \"0.61122185\",\n \"0.6109725\",\n \"0.61094314\",\n \"0.6104993\",\n \"0.6099451\",\n \"0.60868835\",\n \"0.6060397\",\n \"0.603659\",\n \"0.6010346\",\n \"0.60086906\",\n \"0.60023665\",\n \"0.5983982\",\n \"0.5983496\",\n \"0.5983496\",\n \"0.5983496\",\n \"0.5976143\",\n \"0.5973214\",\n \"0.59432775\",\n \"0.5939006\",\n \"0.5939006\",\n \"0.5939006\",\n \"0.5932887\",\n \"0.59050035\",\n \"0.5898641\",\n \"0.58985984\",\n \"0.58885455\",\n \"0.58823115\",\n \"0.58795863\",\n \"0.58764434\",\n \"0.58756447\",\n \"0.5872827\",\n \"0.5856093\",\n \"0.58497196\",\n \"0.5847494\",\n \"0.58362347\",\n \"0.58300734\",\n \"0.5826567\",\n \"0.5820205\",\n \"0.5813995\",\n \"0.5809035\",\n \"0.57815564\",\n \"0.57728976\",\n \"0.57636887\",\n \"0.57601833\",\n \"0.5757536\",\n \"0.57517934\",\n \"0.574895\",\n \"0.574493\",\n \"0.57441026\",\n \"0.5727351\",\n \"0.57163733\",\n \"0.57133466\",\n \"0.5701146\",\n \"0.5698315\",\n \"0.56914896\",\n \"0.56908023\",\n \"0.5689189\",\n \"0.56803685\",\n \"0.56801623\",\n \"0.5674343\",\n \"0.56712824\",\n \"0.5661557\",\n \"0.56540877\",\n \"0.5647789\",\n \"0.5647532\",\n \"0.5639027\",\n \"0.56384957\",\n \"0.56202346\",\n \"0.5616633\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6898922"},"document_rank":{"kind":"string","value":"0"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":817,"numItemsPerPage":100,"numTotalItems":95772,"offset":81700,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4NjE1MzM5MiwianRpIjoiZWU4YzQwODItOWUwMS00MzZiLWIyZTYtZGUwYmQ4NGI0MTU0Iiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3ODYxNTY5OTIsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.bEseMKS_HUk6tfRV1Z0MpvUVX05gRTezqxh_SuBB8LCb7fkADwlczSWwLtVqBXp054bUYUPhjBGV06blD7LrBQ","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Add gene IDs manually into the GEMPRO project. | def add_gene_ids(self, genes_list):
orig_num_genes = len(self.genes)
for g in list(set(genes_list)):
if not self.genes.has_id(g):
new_gene = GenePro(id=g, pdb_file_type=self.pdb_file_type, root_dir=self.genes_dir)
if self.model:
self.model... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _add_transform_genes(self):\n self._alleles.add(pu.make_int_gene(1, 1, 10, 1)) # 'AR' backshift (p)\n self._alleles.add(pu.make_choice_gene(1, [0, 1, 2])) # 'I' backshift (d) \n self._alleles.add(pu.make_choice_gene(1, [1, 2, 3])) # 'MA' backshift (q)\n self._alleles.add(pu.make_int... | [
"0.6379106",
"0.6361385",
"0.6263955",
"0.596308",
"0.59268",
"0.5925437",
"0.59055984",
"0.5817298",
"0.5774752",
"0.5773884",
"0.5769448",
"0.575296",
"0.57183534",
"0.5694724",
"0.5691077",
"0.5668569",
"0.5660597",
"0.56413335",
"0.5637899",
"0.5637372",
"0.56202716",
"... | 0.787999 | 0 |
Map all genes in the model to KEGG IDs using the KEGG service. | def kegg_mapping_and_metadata(self, kegg_organism_code, custom_gene_mapping=None, outdir=None,
set_as_representative=False, force_rerun=False):
# First map all of the organism's KEGG genes to UniProt
kegg_to_uniprot = ssbio.databases.kegg.map_kegg_all_genes(organism_co... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def kegg_converter():\n from tools import prot_id_converter\n \n protList = []\n headerFlag = True\n with open(\"../bob/processed/24h_bobprots_up_full.csv\",\"r\") as inpF:\n for inpLine in inpF:\n if headerFlag:\n headerFlag = False\n continue\n inpList = inpLine.split(\",\")\n ... | [
"0.563114",
"0.5574154",
"0.5559782",
"0.5551251",
"0.5546921",
"0.5503381",
"0.54362684",
"0.5342943",
"0.5341184",
"0.5323929",
"0.5317131",
"0.53079814",
"0.53045225",
"0.5293822",
"0.5272457",
"0.5237042",
"0.51907456",
"0.5179292",
"0.51766217",
"0.5175532",
"0.51710236"... | 0.55860746 | 1 |
Map all genes in the model to KEGG IDs using the KEGG service. | def kegg_mapping_and_metadata_parallelize(self, sc, kegg_organism_code, custom_gene_mapping=None, outdir=None,
set_as_representative=False, force_rerun=False):
# First map all of the organism's KEGG genes to UniProt
kegg_to_uniprot = ssbio.databases.kegg.ma... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def kegg_converter():\n from tools import prot_id_converter\n \n protList = []\n headerFlag = True\n with open(\"../bob/processed/24h_bobprots_up_full.csv\",\"r\") as inpF:\n for inpLine in inpF:\n if headerFlag:\n headerFlag = False\n continue\n inpList = inpLine.split(\",\")\n ... | [
"0.563196",
"0.55852866",
"0.55733615",
"0.55593973",
"0.55501753",
"0.5543938",
"0.55040264",
"0.54342514",
"0.53412634",
"0.53399163",
"0.532083",
"0.5315044",
"0.5306522",
"0.53050053",
"0.52929395",
"0.5270264",
"0.5236628",
"0.51889944",
"0.51782745",
"0.51738745",
"0.51... | 0.5175416 | 19 |
Map all genes in the model to UniProt IDs using the UniProt mapping service. Also download all metadata and sequences. | def uniprot_mapping_and_metadata(self, model_gene_source, custom_gene_mapping=None, outdir=None,
set_as_representative=False, force_rerun=False):
# Allow model gene --> custom ID mapping ({'TM_1012':'TM1012'})
if custom_gene_mapping:
genes_to_map = list(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def manual_uniprot_mapping(self, gene_to_uniprot_dict, outdir=None, set_as_representative=True):\n for g, u in tqdm(gene_to_uniprot_dict.items()):\n g = str(g)\n gene = self.genes.get_by_id(g)\n\n try:\n uniprot_prop = gene.protein.load_uniprot(uniprot_id=u,\n... | [
"0.75125813",
"0.6454647",
"0.60671085",
"0.6022228",
"0.55977786",
"0.55617076",
"0.55605453",
"0.5559257",
"0.5417317",
"0.537197",
"0.5368202",
"0.5332463",
"0.53020674",
"0.5237105",
"0.52121115",
"0.51696676",
"0.5088646",
"0.50799626",
"0.5067423",
"0.50670326",
"0.5027... | 0.7611813 | 0 |
Read a manual dictionary of model gene IDs > UniProt IDs. By default sets them as representative. This allows for mapping of the missing genes, or overriding of automatic mappings. | def manual_uniprot_mapping(self, gene_to_uniprot_dict, outdir=None, set_as_representative=True):
for g, u in tqdm(gene_to_uniprot_dict.items()):
g = str(g)
gene = self.genes.get_by_id(g)
try:
uniprot_prop = gene.protein.load_uniprot(uniprot_id=u,
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def uniprot_mapping_and_metadata(self, model_gene_source, custom_gene_mapping=None, outdir=None,\n set_as_representative=False, force_rerun=False):\n\n # Allow model gene --> custom ID mapping ({'TM_1012':'TM1012'})\n if custom_gene_mapping:\n genes_to_m... | [
"0.6403121",
"0.5933689",
"0.58469325",
"0.58061844",
"0.5766849",
"0.57401544",
"0.5734687",
"0.57258844",
"0.57226133",
"0.57076377",
"0.56597966",
"0.5640181",
"0.5619734",
"0.56024665",
"0.5573105",
"0.5537513",
"0.5523887",
"0.55108166",
"0.54736066",
"0.5461213",
"0.543... | 0.71531695 | 0 |
Read a manual input dictionary of model gene IDs > protein sequences. By default sets them as representative. | def manual_seq_mapping(self, gene_to_seq_dict, outdir=None, write_fasta_files=True, set_as_representative=True):
if outdir:
outdir_set = True
else:
outdir_set = False
# Save the sequence information in individual FASTA files
for g, s in gene_to_seq_dict.items():
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def manual_uniprot_mapping(self, gene_to_uniprot_dict, outdir=None, set_as_representative=True):\n for g, u in tqdm(gene_to_uniprot_dict.items()):\n g = str(g)\n gene = self.genes.get_by_id(g)\n\n try:\n uniprot_prop = gene.protein.load_uniprot(uniprot_id=u,\n... | [
"0.578603",
"0.5672215",
"0.5651235",
"0.56188124",
"0.55466795",
"0.55115235",
"0.54341066",
"0.5378654",
"0.53599185",
"0.53536785",
"0.5351185",
"0.53492874",
"0.5341383",
"0.53390723",
"0.52942526",
"0.528401",
"0.5254791",
"0.5242005",
"0.52400976",
"0.523667",
"0.522224... | 0.63073754 | 0 |
Automatically consolidate loaded sequences (manual, UniProt, or KEGG) and set a single representative sequence. Manually set representative sequences override all existing mappings. UniProt mappings override KEGG mappings except when KEGG mappings have PDBs associated with them and UniProt doesn't. | def set_representative_sequence(self, force_rerun=False):
# TODO: rethink use of multiple database sources - may lead to inconsistency with genome sources
successfully_mapped_counter = 0
for g in tqdm(self.genes):
repseq = g.protein.set_representative_sequence(force_rerun=force_rer... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def initial_sequence_loading(self, work_dir: str):\n # preprocess FASTA with sequences\n # rename IUPAC to N symbols using sed\n fasta_raw = self.from_param(\"manifest_data\", \"fasta_dna\")\n fasta_clean = self.pjc(work_dir, \"fasta\", \"seq_no_iupac.fasta\")\n self.remove_IUP... | [
"0.6016545",
"0.593349",
"0.5745965",
"0.55212516",
"0.5425716",
"0.5406029",
"0.53563493",
"0.531381",
"0.5310087",
"0.530175",
"0.5292923",
"0.5184581",
"0.5143346",
"0.5078548",
"0.5064941",
"0.5030632",
"0.4981743",
"0.49592844",
"0.49414554",
"0.4931738",
"0.4923748",
... | 0.59329545 | 2 |
Write all the model's sequences as a single FASTA file. By default, sets IDs to model gene IDs. | def write_representative_sequences_file(self, outname, outdir=None, set_ids_from_model=True):
if not outdir:
outdir = self.data_dir
if not outdir:
raise ValueError('Output directory must be specified')
outfile = op.join(outdir, outname + '.faa')
tmp = [... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save_seqs_to_file(self):\n if self.blast_type == 'local':\n self.seq_file = os.path.join(self.cwd,\n 'db',\n \"{0}_seqs.fas\".format(self.gene_code))\n queryset = Sequences.objects.all().filter(gene_cod... | [
"0.7703567",
"0.68488854",
"0.68150365",
"0.66532373",
"0.6577866",
"0.65711606",
"0.6558072",
"0.6446043",
"0.64120615",
"0.6376058",
"0.6327507",
"0.63195807",
"0.6264189",
"0.61669415",
"0.6066071",
"0.6019347",
"0.60165673",
"0.6009975",
"0.600401",
"0.5998313",
"0.597920... | 0.7649602 | 1 |
Run Biopython ProteinAnalysis and EMBOSS pepstats to summarize basic statistics of all protein sequences. Results are stored in the protein's respective SeqProp objects at ``.annotations`` | def get_sequence_properties(self, clean_seq=False, representatives_only=True):
for g in tqdm(self.genes):
g.protein.get_sequence_properties(clean_seq=clean_seq, representative_only=representatives_only) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run(self):\n\n # TODO: MOVE TO INIT?\n self.afile = write_amino_acid_masses()\n self.modfile = self.mods.write_modifications_file(mod_type=\"ptm\")\n self.modfile2 = self.mods.write_modifications_file(mod_type=\"sptm\")\n #\n\n self._read_peptide_information()\n\n ... | [
"0.58181006",
"0.5602432",
"0.5474755",
"0.5441378",
"0.5377746",
"0.5277402",
"0.52675635",
"0.5208659",
"0.5205044",
"0.5202254",
"0.51815295",
"0.51808584",
"0.51549906",
"0.5146859",
"0.51310307",
"0.5126919",
"0.5113819",
"0.5107288",
"0.509881",
"0.50788367",
"0.5047152... | 0.0 | -1 |
Run Biopython ProteinAnalysis and EMBOSS pepstats to summarize basic statistics of all protein sequences. Results are stored in the protein's respective SeqProp objects at ``.annotations`` | def get_sequence_sliding_window_properties(self, scale, window, representatives_only=True):
for g in tqdm(self.genes):
g.protein.get_sequence_sliding_window_properties(scale=scale, window=window,
representative_only=representatives_only) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run(self):\n\n # TODO: MOVE TO INIT?\n self.afile = write_amino_acid_masses()\n self.modfile = self.mods.write_modifications_file(mod_type=\"ptm\")\n self.modfile2 = self.mods.write_modifications_file(mod_type=\"sptm\")\n #\n\n self._read_peptide_information()\n\n ... | [
"0.58185875",
"0.56039363",
"0.5476142",
"0.5443091",
"0.5378449",
"0.5278634",
"0.52680093",
"0.52093285",
"0.52068824",
"0.52031213",
"0.51807773",
"0.51793027",
"0.51542205",
"0.5149298",
"0.5131479",
"0.51278746",
"0.511534",
"0.51086545",
"0.5099683",
"0.50781924",
"0.50... | 0.0 | -1 |
Run and parse ``SCRATCH`` results to predict secondary structure and solvent accessibility. | def get_scratch_predictions(self, path_to_scratch, results_dir, scratch_basename='scratch', num_cores=1,
exposed_buried_cutoff=25, custom_gene_mapping=None):
if not self.genome_path:
# Write all sequences as one file
all_seqs = self.write_representative_se... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test__rules__std_L003_process_raw_stack(generate_test_segments, test_elems, result):\r\n cfg = FluffConfig()\r\n r = get_rule_from_set(\"L003\", config=cfg)\r\n test_stack = generate_test_segments(test_elems)\r\n res = r._process_raw_stack(test_stack)\r\n print(res)\r\n # Verify structure\r\n... | [
"0.5453937",
"0.51707166",
"0.5124746",
"0.5067195",
"0.5060421",
"0.50340503",
"0.50077313",
"0.4995311",
"0.49860317",
"0.49587095",
"0.49418697",
"0.49291307",
"0.49152204",
"0.49127287",
"0.49121913",
"0.48993307",
"0.48830223",
"0.48630846",
"0.48607942",
"0.48574045",
"... | 0.6049171 | 0 |
Parse TMHMM results and store in the representative sequences. This is a basic function to parse prerun TMHMM results. Run TMHMM from the | def get_tmhmm_predictions(self, tmhmm_results, custom_gene_mapping=None):
# TODO: refactor to Protein class?
tmhmm_dict = ssbio.protein.sequence.properties.tmhmm.parse_tmhmm_long(tmhmm_results)
counter = 0
for g in tqdm(self.genes_with_a_representative_sequence):
if custom_g... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def parse(self):\n\n try:\n query = SearchIO.parse(self.resultsFile, \"hmmer3-text\").next()\n except StopIteration:\n raise RuntimeError(\"Invalid HMMER output\")\n\n\n self.hmmLength = query.seq_len\n self.total_gaps = [0]*self.hmmLength\n num_hits = 0\n ... | [
"0.718328",
"0.6031104",
"0.55474675",
"0.554094",
"0.54378474",
"0.5321816",
"0.5314905",
"0.52604496",
"0.52468085",
"0.5240826",
"0.52207154",
"0.52113825",
"0.5194342",
"0.5175062",
"0.5160311",
"0.5124177",
"0.5114975",
"0.5098633",
"0.50890535",
"0.50630784",
"0.5060001... | 0.6237841 | 1 |
BLAST each representative protein sequence to the PDB. Saves raw BLAST results (XML files). | def blast_seqs_to_pdb(self, seq_ident_cutoff=0, evalue=0.0001, all_genes=False, display_link=False,
outdir=None, force_rerun=False):
counter = 0
for g in tqdm(self.genes_with_a_representative_sequence):
# If all_genes=False, BLAST only genes without a uniprot -> pd... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exec_blast(infile, config_file, out_name):\n\tdb, evalue = parse_config(config_file, \"blast\")\n\tfasta_string = SeqIO.read(infile, format=\"fasta\")\n\tresult_handle = NCBIWWW.qblast(\"blastp\", \"nr\", fasta_string.seq)\n\toutput= out_name + \".xml\"\n\tsave_file = open(output, \"w\")\n\tsave_file.write(res... | [
"0.66139734",
"0.6583862",
"0.65296185",
"0.64392793",
"0.6255687",
"0.61307186",
"0.610086",
"0.6055964",
"0.5927576",
"0.58890635",
"0.58672094",
"0.5843568",
"0.5821608",
"0.5803",
"0.5789289",
"0.57518595",
"0.5740719",
"0.5657906",
"0.5657839",
"0.5632192",
"0.56158704",... | 0.67663527 | 0 |
Map all representative sequences' UniProt ID to PDB IDs using the PDBe "Best Structures" API. Will save a JSON file of the results to each protein's ``sequences`` folder. | def map_uniprot_to_pdb(self, seq_ident_cutoff=0.0, outdir=None, force_rerun=False):
# First get all UniProt IDs and check if they have PDBs
all_representative_uniprots = []
for g in self.genes_with_a_representative_sequence:
uniprot_id = g.protein.representative_sequence.uniprot
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def write_representative_sequences_file(self, outname, outdir=None, set_ids_from_model=True):\n\n if not outdir:\n outdir = self.data_dir\n if not outdir:\n raise ValueError('Output directory must be specified')\n\n outfile = op.join(outdir, outname + '.faa')\n\n ... | [
"0.610109",
"0.6068264",
"0.59874815",
"0.58739364",
"0.5861211",
"0.5749738",
"0.57296085",
"0.5710959",
"0.5675845",
"0.5658217",
"0.5652435",
"0.56386983",
"0.5631127",
"0.5621135",
"0.5585365",
"0.55756485",
"0.5574747",
"0.554423",
"0.55214447",
"0.5519574",
"0.5488832",... | 0.69787073 | 0 |
Copy homology models to the GEMPRO project. | def get_manual_homology_models(self, input_dict, outdir=None, clean=True, force_rerun=False):
if outdir:
outdir_set = True
else:
outdir_set = False
counter = 0
for g in tqdm(self.genes):
if g.id not in input_dict:
continue
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def makeModel(self):\n\n # Get the script\n modelScript = os.path.join(self.datapath, 'make3FGLxml.py')\n if not os.path.isfile(modelScript):\n # download it\n print(\"\\t=== Downloading make3FGLxml.py ===\")\n os.system('wget https://fermi.gsfc.nasa.gov/ssc/da... | [
"0.5996931",
"0.5607615",
"0.5403388",
"0.539973",
"0.5358105",
"0.53344375",
"0.5272187",
"0.5250301",
"0.5243482",
"0.5218756",
"0.5218072",
"0.52161586",
"0.51627207",
"0.51617354",
"0.51608515",
"0.51242393",
"0.5118167",
"0.51130074",
"0.51084733",
"0.50734",
"0.50628847... | 0.61267424 | 0 |
Copy generated ITASSER models from a directory to the GEMPRO directory. | def get_itasser_models(self, homology_raw_dir, custom_itasser_name_mapping=None, outdir=None, force_rerun=False):
counter = 0
for g in tqdm(self.genes):
if custom_itasser_name_mapping and g.id in custom_itasser_name_mapping:
hom_id = custom_itasser_name_mapping[g.id]
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def copyModels():\n\n # Create the local path if it doesn't exist\n createPath(opts.local_path)\n if not opts.local_path.endswith('/'): opts.local_path = opts.local_path + '/'\n\n sys.stdout.write(\"Copying the model files to the local path: %s ...\\n\\n\" % (opts.local_path))\n\n \"\"\"\n # Copy... | [
"0.6478024",
"0.6302617",
"0.60242254",
"0.5965898",
"0.5961495",
"0.5955651",
"0.591861",
"0.58981764",
"0.5849643",
"0.58346474",
"0.5819575",
"0.581556",
"0.5721305",
"0.57172716",
"0.57066035",
"0.5671232",
"0.5665389",
"0.56633633",
"0.5657864",
"0.56418204",
"0.56418204... | 0.6195266 | 2 |
Set all representative structure for proteins from a structure in the structures attribute. Each gene can have a combination of the following, which will be analyzed to set a representative structure. Homology model(s) Ranked PDBs BLASTed PDBs If the ``always_use_homology`` flag is true, homology models are always set ... | def set_representative_structure(self, seq_outdir=None, struct_outdir=None, pdb_file_type=None,
engine='needle', always_use_homology=False, rez_cutoff=0.0,
seq_ident_cutoff=0.5, allow_missing_on_termini=0.2,
a... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _use_structure_for_label(self, configuration):\n\n # Initialize with the current user option value\n use_structures = self.options['structures']\n\n # But don't use structures if one or more species in the configuration \n # do not have structure data\n for spec in configurat... | [
"0.5631592",
"0.5539555",
"0.5113406",
"0.50993943",
"0.5098184",
"0.5064794",
"0.5059432",
"0.49745953",
"0.4968545",
"0.4948768",
"0.4903572",
"0.490325",
"0.48968196",
"0.4873015",
"0.4863114",
"0.4784549",
"0.4777041",
"0.47675347",
"0.47664335",
"0.47510993",
"0.47313488... | 0.7305333 | 0 |
Prepare to run ITASSER homology modeling for genes without structures, or all genes. | def prep_itasser_modeling(self, itasser_installation, itlib_folder, runtype, create_in_dir=None,
execute_from_dir=None, all_genes=False, print_exec=False, **kwargs):
if not create_in_dir:
if not self.data_dir:
raise ValueError('Output directory must be spe... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build(self):\n\t\n\t\tprint 'BUILDING HOMOLOGY MODELS'\n\t\tif self.procedure != 'mutator': self.get_targets()\n\t\tself.get_templates()\n\t\tif self.procedure == 'single': self.build_model_single()\n\t\telif self.procedure == 'multi': self.build_model_multi()\n\t\telif self.procedure == 'mutator': self.build_... | [
"0.5894737",
"0.587222",
"0.58079857",
"0.5715369",
"0.5680783",
"0.56516254",
"0.564085",
"0.56005704",
"0.5589831",
"0.5576413",
"0.5542736",
"0.551361",
"0.5513122",
"0.55016124",
"0.550024",
"0.5468261",
"0.54510504",
"0.5430583",
"0.54272515",
"0.542462",
"0.54098403",
... | 0.60910213 | 0 |
Download ALL mapped experimental structures to each protein's structures directory. | def pdb_downloader_and_metadata(self, outdir=None, pdb_file_type=None, force_rerun=False):
if not pdb_file_type:
pdb_file_type = self.pdb_file_type
counter = 0
for g in tqdm(self.genes):
pdbs = g.protein.pdb_downloader_and_metadata(outdir=outdir, pdb_file_type=pdb_file_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def download_structure(self):\n pdbl = PDBList()\n pdbl.retrieve_pdb_file(self.struct_name, pdir=self.struct_dir)",
"def download_models_and_data():\n\n for file in DATA_FILES:\n download_file(file[\"url\"], file[\"path\"])",
"def download_genotype_data():\n print(\"downloading genot... | [
"0.6037206",
"0.59987074",
"0.5837045",
"0.5769285",
"0.57660973",
"0.57463247",
"0.57460105",
"0.56247157",
"0.5559726",
"0.5527695",
"0.545999",
"0.5443209",
"0.54300445",
"0.5329254",
"0.5288044",
"0.5280283",
"0.52704644",
"0.52487636",
"0.5248658",
"0.5201878",
"0.519949... | 0.5401219 | 13 |
Run DSSP on structures and store calculations. | def get_dssp_annotations(self, representatives_only=True, force_rerun=False):
for g in tqdm(self.genes):
g.protein.get_dssp_annotations(representative_only=representatives_only, force_rerun=force_rerun) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def call_dssp(self):\n import dssp_features\n output_name_A = \"output/\" + self.complex_name + \"_\" + self.chains[0] + \"_dssp.txt\"\n dssp_command_A = \"dssp -i \" + self.complex_name_A + \" > \" + output_name_A\n os.system(dssp_command_A)\n dssp_chain_A = dssp_features.DSSP_f... | [
"0.70517874",
"0.58411133",
"0.56528515",
"0.5490418",
"0.5473682",
"0.54647654",
"0.5445875",
"0.5428461",
"0.54253674",
"0.535116",
"0.5342631",
"0.5324522",
"0.53242445",
"0.5322637",
"0.5322276",
"0.5304264",
"0.5298354",
"0.5294854",
"0.5272032",
"0.5269717",
"0.5267885"... | 0.0 | -1 |
Run DSSP on structures and store calculations. | def get_dssp_annotations_parallelize(self, sc, representatives_only=True, force_rerun=False):
genes_rdd = sc.parallelize(self.genes)
def get_dssp_annotation(g):
g.protein.get_dssp_annotations(representative_only=representatives_only, force_rerun=force_rerun)
return g
re... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def call_dssp(self):\n import dssp_features\n output_name_A = \"output/\" + self.complex_name + \"_\" + self.chains[0] + \"_dssp.txt\"\n dssp_command_A = \"dssp -i \" + self.complex_name_A + \" > \" + output_name_A\n os.system(dssp_command_A)\n dssp_chain_A = dssp_features.DSSP_f... | [
"0.70526546",
"0.58418775",
"0.5653659",
"0.54898846",
"0.5473753",
"0.54652107",
"0.5447118",
"0.54290944",
"0.5425851",
"0.5350949",
"0.53426653",
"0.5324783",
"0.5324408",
"0.5323901",
"0.53231215",
"0.53046083",
"0.5298966",
"0.52963674",
"0.5272521",
"0.5269802",
"0.5269... | 0.0 | -1 |
Run MSMS on structures and store calculations. | def get_msms_annotations(self, representatives_only=True, force_rerun=False):
for g in tqdm(self.genes):
g.protein.get_msms_annotations(representative_only=representatives_only, force_rerun=force_rerun) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def perform_calculations(collector):\n result = {}\n try:\n radius, mass = Calculator.calculate_radius_mass(collector)\n result['radius'] = radius\n result['mass'] = mass\n average_density = Calculator.calculate_average_density(radius,\n ... | [
"0.6071868",
"0.58869225",
"0.5866962",
"0.58051217",
"0.5799538",
"0.5704183",
"0.5637838",
"0.5555172",
"0.54383713",
"0.5412853",
"0.5401304",
"0.5325587",
"0.5311658",
"0.53054404",
"0.52957356",
"0.5240921",
"0.5220982",
"0.5193444",
"0.5183969",
"0.51734614",
"0.5167927... | 0.0 | -1 |
Run MSMS on structures and store calculations. | def get_msms_annotations_parallelize(self, sc, representatives_only=True, force_rerun=False):
genes_rdd = sc.parallelize(self.genes)
def get_msms_annotation(g):
g.protein.get_msms_annotations(representative_only=representatives_only, force_rerun=force_rerun)
return g
re... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def perform_calculations(collector):\n result = {}\n try:\n radius, mass = Calculator.calculate_radius_mass(collector)\n result['radius'] = radius\n result['mass'] = mass\n average_density = Calculator.calculate_average_density(radius,\n ... | [
"0.6071868",
"0.58869225",
"0.5866962",
"0.58051217",
"0.5799538",
"0.5704183",
"0.5637838",
"0.5555172",
"0.54383713",
"0.5412853",
"0.5401304",
"0.5325587",
"0.5311658",
"0.53054404",
"0.52957356",
"0.5240921",
"0.5220982",
"0.5193444",
"0.5183969",
"0.51734614",
"0.5167927... | 0.0 | -1 |
Run freesasa on structures and store calculations. | def get_freesasa_annotations(self, include_hetatms=False, representatives_only=True, force_rerun=False):
for g in tqdm(self.genes):
g.protein.get_freesasa_annotations(include_hetatms=include_hetatms,
representative_only=representatives_only,
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run_analysis(self):\n\n self._apply_loads_to_framat_model()\n\n # ----- Run the FramAT analysis -----\n results = standard_run(args=StdRunArgs(filename=self.own_files['model_file'], verbose=True))\n self.last_solution = results\n\n # ----- Share loads -----\n logger.in... | [
"0.6980309",
"0.6318951",
"0.6232673",
"0.60748464",
"0.5921279",
"0.5824286",
"0.5790136",
"0.5772901",
"0.57608694",
"0.57494456",
"0.57234335",
"0.56578684",
"0.5651609",
"0.5612166",
"0.5606721",
"0.5604897",
"0.5604186",
"0.55726767",
"0.55719376",
"0.55543053",
"0.55538... | 0.0 | -1 |
Run freesasa on structures and store calculations. | def get_freesasa_annotations_parallelize(self, sc, include_hetatms=False,
representatives_only=True, force_rerun=False):
genes_rdd = sc.parallelize(self.genes)
def get_freesasa_annotation(g):
g.protein.get_freesasa_annotations(include_hetatms=inc... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run_analysis(self):\n\n self._apply_loads_to_framat_model()\n\n # ----- Run the FramAT analysis -----\n results = standard_run(args=StdRunArgs(filename=self.own_files['model_file'], verbose=True))\n self.last_solution = results\n\n # ----- Share loads -----\n logger.in... | [
"0.69801366",
"0.6316988",
"0.6230642",
"0.60748374",
"0.5920034",
"0.5824195",
"0.5789938",
"0.577425",
"0.5760711",
"0.5749059",
"0.57218057",
"0.56583464",
"0.56520665",
"0.56142336",
"0.56094056",
"0.5603997",
"0.5603649",
"0.5574297",
"0.55710286",
"0.5553558",
"0.555345... | 0.0 | -1 |
Run Biopython's disulfide bridge finder and store found bridges. | def find_disulfide_bridges(self, representatives_only=True):
for g in tqdm(self.genes):
g.protein.find_disulfide_bridges(representative_only=representatives_only) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def bridge(gwc = 0, brc = bridge_int):\n# bridge interface list\n br_interface = []\n# bridge ip addresses list\n gw_ipaddr = []\n# bridge network list\n gw_network = []\n# gatweway start number list\n gw_number = 0\n\n# fill all lists for bridge\n for i in netifaces.ifaddresses(bridge_int)[netifaces.AF_... | [
"0.5722066",
"0.56421185",
"0.55387205",
"0.54129124",
"0.5339122",
"0.5317713",
"0.5291248",
"0.5289518",
"0.5201121",
"0.51779175",
"0.5120208",
"0.50416565",
"0.5035486",
"0.5010023",
"0.49626023",
"0.49342176",
"0.49176186",
"0.48929974",
"0.4889427",
"0.48860794",
"0.488... | 0.53551966 | 4 |
Run Biopython's disulfide bridge finder and store found bridges. | def find_disulfide_bridges_parallelize(self, sc, representatives_only=True):
genes_rdd = sc.parallelize(self.genes)
def find_disulfide_bridges(g):
g.protein.find_disulfide_bridges(representative_only=representatives_only)
return g
result = genes_rdd.map(find_disulfide_b... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def bridge(gwc = 0, brc = bridge_int):\n# bridge interface list\n br_interface = []\n# bridge ip addresses list\n gw_ipaddr = []\n# bridge network list\n gw_network = []\n# gatweway start number list\n gw_number = 0\n\n# fill all lists for bridge\n for i in netifaces.ifaddresses(bridge_int)[netifaces.AF_... | [
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"0.4889931",
"0.48860416",
"0.48856... | 0.5290128 | 7 |
Save all Proteins as pickle files currently development code for parallelization purposes. Also clears the protein attribute in all genes! | def save_protein_pickles_and_reset_protein(self):
self.gene_protein_pickles = {}
for g in tqdm(self.genes):
if g.protein.representative_sequence:
initproteinpickle = op.join(g.protein.protein_dir, '{}_protein.pckl'.format(g.id))
g.protein.save_pickle(initprote... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _save(self):\n # TODO: Use local.punny dump (when written)\n with open(filename, 'w') as f:\n pickle = Pickler(f)\n pickle.dump(self.pungen.puns)",
"def save_all(cls, dirpath=\".\"):\n for n, v in cls.__data.items():\n pickle.dump(v, open(cls.dirpath + n ... | [
"0.6193186",
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"0.54926723",
"0.54900473",
"0.5416714",
"0.54038894",
"0.53814983... | 0.7695337 | 0 |
run the quantum circuit. | def run(self, shots=DEF_SHOTS, reset_qubits=True, reset_cmem=True, reset_qcirc=True):
if self.backend.name == 'qlazy_qstate_simulator':
result = run_qlazy_qstate_simulator(self.qstate, self.qcirc, self.cmem, shots=shots)
self.reset(reset_qubits, reset_cmem, reset_qcirc)
elif self... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run_sim(self):\n self.operator, var_form, opt = self.generate_VQE_args()\n\n backend = Aer.get_backend('statevector_simulator')\n quantum_instance = QuantumInstance(backend=backend)\n vqe = VQE(self.operator, var_form, opt) \n\n self.result = vqe.run(quantum_instance)\n solution = self.extrac... | [
"0.6475484",
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"0.5766902",
"0.5748436",
"0.57332987",
"0.5721311",
"0.57128... | 0.54874796 | 47 |
add measurement gate (Zbasis). | def measure(self, qid, cid=None, ctrl=None):
self.__add_quantum_gate(kind=MEASURE, qid=qid, cid=cid, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _represent_ZGate(self, basis, **options):\n _format = options.get('format', 'sympy')\n n = 1\n definite_state = 0\n for it in reversed(self.qubit_values):\n definite_state += n*it\n n = n*2\n result = [0]*(2**self.dimension)\n result[int(definite_... | [
"0.57827705",
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"0.518905",
"0.51349676",
"0.5126275",
"0.5115005",... | 0.0 | -1 |
add H gate (hadamard gate). | def h(self, q0, ctrl=None):
self.__add_quantum_gate(kind=HADAMARD, qid=[q0])
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def H(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.H, qubit_expr)",
"def one_step(self, x, h):\n concatHX = torch.cat((x, h), 1)\n zt = self.sigmoid(self.linearZ(concatHX))\n rt = self.sigmoid(self.linearR(concatHX))\n ht = (1-zt)*h + zt* self.tanh(self.linearH(rt*co... | [
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"0.55545986",
"0.5546688",
"0.55118287",
"0.5500624",
"0.549... | 0.64646775 | 0 |
add root X gate. | def xr(self, q0, ctrl=None):
self.__add_quantum_gate(kind=ROOT_PAULI_X, qid=[q0], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def double_add(self, x):\n self.add(x*2)",
"def add(self, x):\n self.sum += (1 / self.counter) * (x - self.sum)\n self.counter += 1",
"def add(self, x):\n self.sum += x\n self.n += 1",
"def add_x(self, x, add):\n return (x + add) % self.x_len",
"def add(self, x):\n... | [
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"0.5121168",
"0.5118317",
"0.51017565",
... | 0.5430207 | 8 |
add root X dagger gate (hermmitian conjugate of root X gate). | def xr_dg(self, q0, ctrl=None):
self.__add_quantum_gate(kind=ROOT_PAULI_X_, qid=[q0], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def G(x,mu,T):\r\n den1 = np.cosh(mu/(kb*T))/np.sinh(x/(kb*T))\r\n den2 = np.tanh(x/(kb*T))\r\n\r\n return 1/(den1 + den2)",
"def g(self, X):\n\n return (X[0])**2 - 2*X[0] + X[1]**3 - 2",
"def DEX(self, *_):\n self._dec_or_inc_register('X', increment=False)",
"def g(self, x):\n ... | [
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"0.48278... | 0.48627827 | 17 |
add S dagger gate (hermitian conjugate of S gate). | def s_dg(self, q0, ctrl=None):
self.__add_quantum_gate(kind=PHASE_SHIFT_S_, qid=[q0], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sdg(self, q):\n if isinstance(q, QuantumRegister):\n instructions = InstructionSet()\n for j in range(q.size):\n instructions.add(self.sdg((q, j)))\n return instructions\n\n self._check_qubit(q)\n return self._attach(SdgGate(q, self))",
"def s_derivation(self, p, s, a... | [
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"0.488642",
"0.48804927",
"0.48585668",
"0.48501772",
"0.48... | 0.51566285 | 3 |
add T dagger gate (hermitian conjugate of T gate). | def t_dg(self, q0, ctrl=None):
self.__add_quantum_gate(kind=PHASE_SHIFT_T_, qid=[q0], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _add_entanglement_gate(self, gate_method, qubit_1, qubit_2):\r\n sig = signature(gate_method)\r\n\r\n # parametrized gate like a controlled single qubit rotation\r\n if 'theta' in sig.parameters:\r\n try:\r\n gate_method(self.circuit, self.parameters[next(self.ind... | [
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"0.4888838",
"0.4888838",
"0.48756477",
"0.48502102",
"0... | 0.524924 | 3 |
add RX gate (rotation around Xaxis). | def rx(self, q0, phase=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=ROTATION_X, qid=[q0], phase=phase, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rx(self, angle: float) -> \"Mate\":\n a = angle / 180 * pi\n self.y_dir = Mate._rotate(self.y_dir, self.x_dir, a)\n self.z_dir = Mate._rotate(self.z_dir, self.x_dir, a)\n return self",
"def rx(self, angle: float, center: Onion[Iterable[Onion[float, int]], Point3D] = None) -> 'Comp... | [
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"0.5010519",
"0.49932432",
"0.49489382",
"0.49301413",
... | 0.62692696 | 2 |
add RY gate (rotation around Yaxis). | def ry(self, q0, phase=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=ROTATION_Y, qid=[q0], phase=phase, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rot_y(angle):\n sangle = math.sin(angle)\n cangle = math.cos(angle)\n ry = np.array([[cangle, 0.0, -sangle],\n [0.0, 1.0, 0.0],\n [sangle, 0.0, cangle]])\n return ry",
"def rotate_y(angle):\n log.dev(\"lib.mathp.rotate_y is deprecated. Use lib.rotation.R2 in... | [
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"0.58337736",
"0.5821165",
... | 0.64825207 | 3 |
add RZ gate (rotation around Zaxis). | def rz(self, q0, phase=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=ROTATION_Z, qid=[q0], phase=phase, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rz(self, phi, q): # pylint: disable=invalid-name\n return self.append(RZGate(phi), [q], [])",
"def rotateZ(self, *args, **kwargs):\n ...",
"def _r_z(angle: tf.Tensor) -> tf.Tensor:\n zero = tf.constant(0, dtype=tf.float64)\n exponent = tf.complex(zero, angle)\n exp = tf.exp(... | [
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"0.5860597... | 0.6309543 | 9 |
add P gate (phase shift gate). | def p(self, q0, phase=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=PHASE_SHIFT, qid=[q0], phase=phase, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add(self, p):\n self._pumps.add(p)",
"def __add__(self, p: np.ndarray):\n return Quaternion(self.to_array() + p)",
"def Add(p, q):\n return p*q",
"def point_addition(self, P, Q):\n\t\traise Exception(NotImplemented)",
"def PLP(self, *_):\n self.reg.P = self.pop()",
"def update... | [
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"0.5204293",
... | 0.61503357 | 1 |
add U1 gate (by IBM). | def u1(self, q0, alpha=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=ROTATION_U1, qid=[q0], phase=alpha, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cu1(self, q0, q1, alpha=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U1, qid=[q0,q1], phase=alpha, ctrl=ctrl)\n return self",
"def _action_op_u1(self, plaq):\n # if self.link_type == 'U1':\n # return np.cos(plaq)\n return tf.math.cos(plaq)",
"def... | [
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"0.5656396... | 0.62217534 | 1 |
add U2 gate (by IBM). | def u2(self, q0, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=ROTATION_U2, qid=[q0], phase=alpha, phase1=beta, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n q... | [
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"0.5730032",
"0.5722179... | 0.6176404 | 7 |
add U3 gate (by IBM). | def u3(self, q0, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=ROTATION_U3, qid=[q0], phase=alpha, phase1=beta,
phase2=gamma, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __iadd__( self, vector3 ):\n return self.add( vector3 )",
"def cu3(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U3, qid=[q0,q1], phase=alpha, phase1=beta,\n phase2=gamma, ctrl=ctrl)\n ... | [
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"0.54163665",
"0.5363699... | 0.61557925 | 2 |
add CX gate (controlled X gate, controlled NOT gate, CNOT gate). | def cx(self, q0, q1, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def CX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)",
"def add(self, y):\n return circuit.add(self, y)",
"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return ... | [
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"0.5043... | 0.57537436 | 1 |
operate CY gate (controlled X gate). | def cy(self, q0, q1, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)
self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)
self.__add_quantum_gate(kind=PHASE_SHIFT_S, qid=[q0], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cy(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CY(), target=[control, target])",
"def CX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CX, qubit_expr)",
"def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])",... | [
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"0.53088343",
"0.52476794",
"0.5232436",
"0.5232274",
"0.5184903",
"0.5168113",
"0.5129279",
"0.51265514",
"0.5118267... | 0.60488343 | 2 |
add CZ gate (controlled Z gate). | def cz(self, q0, q1, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def CZ(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CZ, qubit_expr)",
"def cz(control: QubitInput, target: QubitInput) -> Instruction:\n return Instruction(CZ(), target=[control, target])",
"def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])",
"de... | [
"0.6692847",
"0.6502453",
"0.593888",
"0.57899",
"0.57899",
"0.569876",
"0.56540734",
"0.56317514",
"0.55797076",
"0.55053544",
"0.54111063",
"0.53825223",
"0.53213876",
"0.5233289",
"0.52176267",
"0.52100134",
"0.5150845",
"0.51389116",
"0.51233536",
"0.50904244",
"0.505567"... | 0.6522352 | 1 |
add CXR gate (controlled root X gate). | def cxr(self, q0, q1, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cxr_dg(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)\n return self",
"def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])",
"def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED... | [
"0.60456556",
"0.5788765",
"0.5551391",
"0.5473348",
"0.53226703",
"0.5244496",
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"0.5173726",
"0.51487964",
"0.510389",
"0.50781316",
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"0.49753806",
"0.49564382",
"0.493396",
"0.49102163",
"0.48927242",
"0.48697314",
"0.4860... | 0.65724874 | 0 |
add CXR dagger gate (controlled XR dagger gate). | def cxr_dg(self, q0, q1, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_XR_, qid=[q0,q1], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cxr(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_XR, qid=[q0,q1], ctrl=ctrl)\n return self",
"def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])",
"def _gcl(x, r, D, Ia, Ct):\n\n Area = np.pi * D ** 2.0 / 4.0\n m = 1.0 / (np.sq... | [
"0.5829941",
"0.5677816",
"0.5607042",
"0.5547162",
"0.5384019",
"0.52695274",
"0.51288795",
"0.50940967",
"0.50349534",
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"0.48516476",
"0.48199007",
"0.48017424",
"0.47675318",
"0.47669303",
"... | 0.6386473 | 0 |
add CH gate (controlled H gate). | def ch(self, q0, q1, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_H, qid=[q0,q1], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_append_one_wire_gate(self, circuit):\n gate = jet.GateFactory.create(\"H\")\n circuit.append_gate(gate, wire_ids=[3])\n assert gate.indices == [\"3-1\", \"3-0\"]\n assert list(circuit.operations)[-1] == jet.Operation(gate, [3])\n assert list(circuit.wires) == [\n ... | [
"0.593194",
"0.55942816",
"0.55546916",
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"0.53084034",
"0.5280236",
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"0.5245822",
"0.52261335",
"0.522333",
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"0.5163261",
"0.51590973",
"0.5119946",
"0.50677484",
"0.5060551",
"0.50518656",
"0.5038371... | 0.66249025 | 0 |
add CS gate (controlled S gate). | def cs(self, q0, q1, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_S, qid=[q0,q1], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = ... | [
"0.61474854",
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"0.5245407",
"0.5190346",
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"0.50532585",
"0.5031381",
"0.5031352",
"0.49834308",
"0.494981",
"0.492664... | 0.6095033 | 1 |
add CS dagger gate (controlled S dagger gate). | def cs_dg(self, q0, q1, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_S_, qid=[q0,q1], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gate(self):\n self.gatedFrames = IVUS_gating(self.images, self.ivusPullbackRate, self.dicom.CineRate)",
"def build_glyCB(self, gCBd: Dihedron): # -> None:\n ...",
"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == Non... | [
"0.5338038",
"0.5312894",
"0.52970165",
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"0.517592",
"0.51653695",
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"0.50336796",
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"0.49150544",
"0.4883801",
"0.48823026",
"0.48561972",
"0.48432097",
"0.48432097",
"0.48407... | 0.5636926 | 0 |
add CT gate (controlled T gate). | def ct(self, q0, q1, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_T, qid=[q0,q1], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])",
"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n... | [
"0.6381244",
"0.6276733",
"0.6038881",
"0.60035855",
"0.597752",
"0.5808486",
"0.55988115",
"0.55569977",
"0.55378765",
"0.5425379",
"0.53594565",
"0.5328162",
"0.5316508",
"0.52781427",
"0.5276781",
"0.52332044",
"0.52280194",
"0.5162224",
"0.5160193",
"0.5147565",
"0.513996... | 0.61273205 | 2 |
add CT dagger gate (controlled T dagger gate). | def ct_dg(self, q0, q1, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_T_, qid=[q0,q1], ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_glyCB(self, gCBd: Dihedron): # -> None:\n ...",
"def addGateDag(self, dag, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToDag == None:\n return None\n \n gate = self._gatesToDag[gate.qasm()]\n\n if cregs == None:\n ... | [
"0.57742953",
"0.56914765",
"0.55658096",
"0.55089957",
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"0.5290461",
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"0.512335",
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"0.49066445",
"0.4892633",
"0.48817962",
"0.48796433",
"0.48612082",
"0.4... | 0.5654775 | 2 |
add CP gate (controlled P gate). | def cp(self, q0, q1, phase=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_P, qid=[q0,q1], phase=phase, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = ... | [
"0.5904704",
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"0.56965774",
"0.5647329",
"0.56336844",
"0.55492866",
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"0.52863276",
"0.5273215",
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"0.5182098",
"0.51805395",
"0.5169316",
"0.51630926",
"0.51592803",
"0.5153... | 0.61328435 | 0 |
add CRX gate (controlled RX gate). | def crx(self, q0, q1, phase=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_RX, qid=[q0,q1], phase=phase, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])",
"def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])",
"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gat... | [
"0.6399722",
"0.6240949",
"0.58750856",
"0.5635678",
"0.5619368",
"0.534809",
"0.53249425",
"0.53150433",
"0.52717066",
"0.52563894",
"0.52543056",
"0.5253364",
"0.5244658",
"0.5180739",
"0.5163616",
"0.51406276",
"0.513891",
"0.50769234",
"0.50509804",
"0.5044092",
"0.501908... | 0.630366 | 1 |
add CRY gate (controlled RY gate). | def cry(self, q0, q1, phase=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_RY, qid=[q0,q1], phase=phase, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])",
"def cy(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_Z, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n self.__add_quantum_gate(kind... | [
"0.5383607",
"0.53207576",
"0.523361",
"0.5175593",
"0.5152383",
"0.5134093",
"0.50781554",
"0.50374013",
"0.50269675",
"0.5018746",
"0.5007231",
"0.49872983",
"0.4968603",
"0.49366578",
"0.49154067",
"0.4913415",
"0.4904036",
"0.48859322",
"0.48642954",
"0.48608968",
"0.4823... | 0.54176253 | 0 |
add CRZ gate (controlled RZ gate). | def crz(self, q0, q1, phase=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_RZ, qid=[q0,q1], phase=phase, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def crz(self, theta, ctl, tgt):\n return self.append(CrzGate(theta), [ctl, tgt], [])",
"def __init__(self, theta):\n super().__init__(\"crz\", 2, [theta], num_ctrl_qubits=1)\n self.base_gate = RZGate(theta)",
"def rz(self, phi, q): # pylint: disable=invalid-name\n return self.append(RZGate... | [
"0.6958848",
"0.61419284",
"0.6064584",
"0.56396747",
"0.5535329",
"0.5404921",
"0.5390143",
"0.53515494",
"0.5310394",
"0.52780074",
"0.5277078",
"0.5226025",
"0.5192308",
"0.5169303",
"0.5124667",
"0.5121535",
"0.5059638",
"0.5004625",
"0.4980288",
"0.49734604",
"0.49685302... | 0.66018766 | 1 |
add CU1 gate (controlled U1 gate). | def cu1(self, q0, q1, alpha=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_U1, qid=[q0,q1], phase=alpha, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)\n return self",
"def _add_2_bit_oracle_with_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister, ancilla: Qubit) -> None:\n if ... | [
"0.58692527",
"0.58496964",
"0.57497954",
"0.57320833",
"0.5699937",
"0.5659775",
"0.55907893",
"0.5577817",
"0.55392885",
"0.54260707",
"0.53691983",
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"0.5285583",
"0.5258641",
"0.5211102",
"0.5174425",
"0.5146771",
"0.513239",
"0.51196... | 0.7375347 | 0 |
add CU2 gate (controlled U2 gate). | def cu2(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_U2, qid=[q0,q1], phase=alpha, phase1=beta, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _add_2_bit_oracle_without_ancilla_1_0(qc: QuantumCircuit, register: QuantumRegister) -> None:\n if len(list(register)) != 2:\n raise ValueError(f\"Need QuantumRegister with exactly 2 qubits, but got {len(list(register))} instead.\")\n\n qc.x(register[0])\n qc.cz(register[1], register[0])\n q... | [
"0.63387585",
"0.60368437",
"0.59752756",
"0.5968923",
"0.5940657",
"0.58799356",
"0.5746586",
"0.5703197",
"0.56583536",
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"0.53551805",
"0.5338436",
"0.53347147",
"0.53148663",
"0.528607",
"0.5... | 0.70731705 | 0 |
add CU3 gate (controlled U3 gate). | def cu3(self, q0, q1, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):
self.__add_quantum_gate(kind=CONTROLLED_U3, qid=[q0,q1], phase=alpha, phase1=beta,
phase2=gamma, ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def u3(self, q0, alpha=DEF_PHASE, beta=DEF_PHASE, gamma=DEF_PHASE, ctrl=None):\n self.__add_quantum_gate(kind=ROTATION_U3, qid=[q0], phase=alpha, phase1=beta,\n phase2=gamma, ctrl=ctrl)\n return self",
"def test_special_U3(self):\n self.check_oneq_special_cases... | [
"0.6172833",
"0.60709476",
"0.59816235",
"0.597661",
"0.58950996",
"0.5756811",
"0.57265884",
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"0.5533537",
"0.54784715",
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"0.5308488",
"0.52944463",
"0.5283771",
"0.5253617",
"0.5241266",
"0.52193... | 0.69713616 | 0 |
add CCX gate (toffoli gate, controlled controlled X gate). | def ccx(self, q0, q1, q2, ctrl=None):
self.cxr(q1,q2,ctrl=ctrl).cx(q0,q1,ctrl=ctrl).cxr_dg(q1,q2,ctrl=ctrl)
self.cx(q0,q1,ctrl=ctrl).cxr(q0,q2,ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ccx(self, ctl1, ctl2, tgt):\n return self.append(ToffoliGate(), [ctl1, ctl2, tgt], [])",
"def cx(self, q0, q1, ctrl=None):\n self.__add_quantum_gate(kind=CONTROLLED_X, qid=[q0,q1], ctrl=ctrl)\n return self",
"def CX(self, qubit_expr):\n self.apply_gate_operation(cirq.ops.CX, qubit_e... | [
"0.63400793",
"0.5722614",
"0.57119",
"0.555426",
"0.5540648",
"0.5507331",
"0.5357815",
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"0.53307414",
"0.5300384",
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"0.51508355",
"0.51378155",
"0.5125027",
"0.50955683",
"0.50826627",
"0.5060708",
"0.5052761",
"0.50502384",
"0.5042433... | 0.0 | -1 |
add CSW gate (fredkin gate, controlled swap gate). | def csw(self, q0, q1, q2, ctrl=None):
self.cx(q2,q1,ctrl=ctrl).ccx(q0,q1,q2,ctrl=ctrl).cx(q2,q1,ctrl=ctrl)
return self | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def addGateCircuit(self, circuit, gate, qregs, cregs = None, ancillas = None):\n if self._gates == None or self._gatesToCircuit == None:\n return None\n\n gate = self._gatesToCircuit[gate.qasm()]\n \n circuit = circuit.copy()\n\n if cregs == None:\n cregs = ... | [
"0.59902334",
"0.5926082",
"0.5785358",
"0.567691",
"0.5651704",
"0.5646367",
"0.5568842",
"0.5285402",
"0.5262861",
"0.5240311",
"0.5238952",
"0.52281916",
"0.5196213",
"0.51387995",
"0.5098061",
"0.50610805",
"0.50459075",
"0.49702364",
"0.49483865",
"0.49053276",
"0.488355... | 0.56252754 | 6 |
Ensure that we have snapshots for a given volume | def run(connection, volume_id, interval='daily', max_snapshots=0, name=''):
try:
volumes = connection.get_all_volumes([volume_id])
except EC2ResponseError as error:
logging.error(kayvee.formatLog("ebs-snapshots", "error", "failed to connect to AWS", {"msg": error.message}))
return
f... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def snapshot_volumes(self) -> bool:\n return pulumi.get(self, \"snapshot_volumes\")",
"def get_volume_snapshots(self, volume):\n LOG.debug('get_volume_snapshot starts')\n pool_name = self.configuration.rbd_pool\n volume_name = 'volume-%s' % encodeutils.safe_encode(volume[\"id\"])\n ... | [
"0.6860214",
"0.68374085",
"0.6810308",
"0.6785922",
"0.67043364",
"0.66553533",
"0.65876997",
"0.65367866",
"0.64045566",
"0.6373387",
"0.6342591",
"0.62254906",
"0.6165685",
"0.60885876",
"0.60594773",
"0.6057364",
"0.6054742",
"0.6044898",
"0.60077125",
"0.6006443",
"0.600... | 0.5774927 | 34 |
Create a new snapshot | def _create_snapshot(connection, volume, name=''):
logging.info(kayvee.formatLog("ebs-snapshots", "info", "creating new snapshot", {"volume": volume.id}))
snapshot = volume.create_snapshot(
description="automatic snapshot by ebs-snapshots")
if not name:
name = '{}-snapshot'.format(volume.id)... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_snapshot(store, dataset, snapshot, description_fields, snapshot_changes):\n validate_snapshot_name(store, dataset, snapshot)\n validate_datalad_config(store, dataset)\n update_description(store, dataset, description_fields)\n update_changes(store, dataset, snapshot, snapshot_changes)\n sa... | [
"0.79396224",
"0.79085445",
"0.7880862",
"0.78679043",
"0.77699107",
"0.77232075",
"0.7571505",
"0.7500152",
"0.7409868",
"0.73697287",
"0.7301827",
"0.7300242",
"0.72600234",
"0.72017276",
"0.71182054",
"0.7031012",
"0.69631094",
"0.69143236",
"0.69007653",
"0.68159884",
"0.... | 0.752988 | 7 |
Ensure that a given volume has an appropriate snapshot | def _ensure_snapshot(connection, volume, interval, name):
if interval not in VALID_INTERVALS:
logging.warning(kayvee.formatLog("ebs-snapshots", "warning", "invalid snapshotting interval", {
"volume": volume.id,
"interval": interval
}))
return
snapshots = connecti... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_create_volume_from_snapshot(self, mock_ghn):\n ctxt = context.get_admin_context()\n extra_specs = {}\n type_ref = volume_types.create(ctxt, 'hgst-1', extra_specs)\n snap = {'id': '1', 'name': 'volume1', 'display_name': '',\n 'volume_type_id': type_ref['id'], 'siz... | [
"0.72817236",
"0.68085235",
"0.6774093",
"0.67722756",
"0.67518574",
"0.66919476",
"0.66683424",
"0.66099256",
"0.6593119",
"0.6561201",
"0.64276564",
"0.64078516",
"0.64017785",
"0.63788575",
"0.63636637",
"0.6321371",
"0.62975985",
"0.62808114",
"0.6255119",
"0.62545985",
"... | 0.6775116 | 2 |
Get the custom argument names and their defaults for this callbacks object. | def args_map_custom(cls) -> dict:
args = {}
args.update(cls.args_map_export())
args.update({"json_flat": False})
return args | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_defaults(self):\n default_dict = {}\n args, varargs, keyword, defaults = inspect.getargspec(self.exec_obj)\n if defaults:\n default_dict = dict(zip(args[-len(defaults):], defaults))\n return default_dict",
"def _default_arguments(self, obj):\n \n ... | [
"0.61624855",
"0.6132843",
"0.6095295",
"0.60910934",
"0.6068363",
"0.6068363",
"0.6029796",
"0.5978995",
"0.5969861",
"0.5933815",
"0.5930009",
"0.5890643",
"0.58816427",
"0.5855672",
"0.5841174",
"0.5833141",
"0.58139366",
"0.5811528",
"0.58108425",
"0.57942617",
"0.5759906... | 0.5322465 | 100 |
Start this callbacks object. | def start(self, **kwargs):
super(Json, self).start(**kwargs)
flat = self.get_arg_value("json_flat")
self._first_row = True
self.open_fd()
begin = "" if flat else "["
self._fd.write(begin) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Start(self) :\n\t\t...",
"def start(self):\n if self._start_event is None:\n _call_spawn_callbacks(self)\n hub = get_my_hub(self) # pylint:disable=undefined-variable\n self._start_event = hub.loop.run_callback(self.switch)",
"def on_init_start(self):\n for cal... | [
"0.7341116",
"0.72688156",
"0.72455454",
"0.72304714",
"0.7201714",
"0.71944135",
"0.7172131",
"0.7172131",
"0.7169214",
"0.7162993",
"0.71609396",
"0.7144856",
"0.7144856",
"0.7144856",
"0.7144856",
"0.7144856",
"0.7144856",
"0.7144856",
"0.7144856",
"0.7108717",
"0.7108717"... | 0.0 | -1 |
Stop this callbacks object. | def stop(self, **kwargs):
super(Json, self).stop(**kwargs)
flat = self.get_arg_value("json_flat")
self.do_export_schema()
end = "" if flat else "\n]"
self._fd.write(end)
self.close_fd() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def stop(self):\n callbacks_to_invoke = None\n self.__condition.acquire()\n if self.__is_running:\n callbacks_to_invoke = self.__on_stop_callbacks\n self.__on_stop_callbacks = []\n self.__is_running = False\n self.__condition.notifyAll()\n sel... | [
"0.7963989",
"0.7829633",
"0.77804077",
"0.77698517",
"0.7754477",
"0.7754477",
"0.7754477",
"0.7754477",
"0.7754477",
"0.7754477",
"0.7754477",
"0.7754477",
"0.7754477",
"0.7754477",
"0.7754477",
"0.7751761",
"0.7751761",
"0.7730036",
"0.7728273",
"0.7700817",
"0.7687963",
... | 0.0 | -1 |
Process the callbacks for current row. | def process_row(self, row: Union[List[dict], dict]) -> List[dict]:
rows = listify(row)
rows = self.do_pre_row(rows=rows)
row_return = [{"internal_axon_id": row["internal_axon_id"]} for row in rows]
rows = self.do_row(rows=rows)
self.write_rows(rows=rows)
del rows, row
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_row_callback(self, row_idx, callback):\n self.row_config[row_idx]['callback'] = callback",
"def handleRowDataChange(self, changedItem ):\n with Tracer(traceLogger):\n # Figure out which row this widget is in\n row = changedItem.row()\n column = changedItem.c... | [
"0.6472857",
"0.5750757",
"0.5650037",
"0.5516797",
"0.5459125",
"0.54315567",
"0.542719",
"0.5388466",
"0.5336627",
"0.53299576",
"0.5304679",
"0.52980345",
"0.52818644",
"0.52797127",
"0.5246277",
"0.5232472",
"0.52007216",
"0.5188484",
"0.5181919",
"0.5174036",
"0.5146636"... | 0.4780201 | 60 |
Write rows to the file descriptor. | def write_rows(self, rows: Union[List[dict], dict]):
rows = listify(rows)
flat = self.get_arg_value("json_flat")
indent = None if flat else 2
prefix = " " * indent if indent else ""
for row in rows:
if self._first_row:
pre = "" if flat else "\n"
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def write(self, row):\n bytes = struct.pack(self.pack_format, *row)\n self.f.write(bytes)",
"def store_rows(self, course_id, filename, rows):\r\n output_buffer = StringIO()\r\n csv.writer(output_buffer).writerows(rows)\r\n self.store(course_id, filename, output_buffer)",
"def... | [
"0.65288514",
"0.64927477",
"0.63778",
"0.63315696",
"0.63270783",
"0.6293423",
"0.6291826",
"0.62790984",
"0.6272529",
"0.6243658",
"0.62395215",
"0.6211141",
"0.61144894",
"0.6026084",
"0.60218585",
"0.59980494",
"0.5994269",
"0.5977457",
"0.5938158",
"0.5935091",
"0.592530... | 0.5914556 | 21 |
Add schema rows to the output. | def do_export_schema(self):
export_schema = self.get_arg_value("export_schema")
if export_schema:
row = {"schemas": self.final_schemas}
self.write_rows(rows=row)
del row | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_rows(self):\n for row in self.rows:\n self.table.add_row(row)",
"def append_row(self):\r\n values = []\r\n vals_to_insert = ''\r\n\r\n for key in Output.COLUMNS:\r\n values.append(str(self[key]))\r\n\r\n # Replace any Quotes in parsed record with d... | [
"0.67264223",
"0.6197562",
"0.61581135",
"0.5907348",
"0.59029365",
"0.5833993",
"0.58154505",
"0.57763284",
"0.57446873",
"0.5742718",
"0.56974214",
"0.56769365",
"0.56498146",
"0.5647206",
"0.5645583",
"0.56280947",
"0.5627587",
"0.56085706",
"0.553828",
"0.5537964",
"0.553... | 0.65681523 | 1 |
Return all the buffered objects, in the correct order as well as their index | def items(self):
ix_obj = list(self.d_buffer.keys())
ix_obj.sort()
l_obj = [self.d_buffer[ix] for ix in ix_obj]
return ix_obj, l_obj | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get(self):\n assert self.ptr == self.max_size\n self.ptr, self.path_start_idx = 0, 0\n return [self.obs_buf, self.act_buf, self.adv_buf, self.ret_buf, self.val_buf]",
"def BufferList(self) -> _n_2_t_0[_n_0_t_11[_n_0_t_6]]:",
"def __getitem__(self, index):\n return self.buffer[index]... | [
"0.60331285",
"0.600125",
"0.59499425",
"0.5791308",
"0.57847834",
"0.57847834",
"0.57508755",
"0.5720811",
"0.56735605",
"0.5663488",
"0.56373197",
"0.5627264",
"0.5612106",
"0.5609416",
"0.5598592",
"0.5567743",
"0.55047196",
"0.5464387",
"0.544293",
"0.54306895",
"0.541305... | 0.66548544 | 0 |
Add one particular item, with a specific index to the buffer If the item is already buffered do not add it again Argument | def add_item(self, item, index):
if index in self.d_buffer.keys():
return True
elif len(self) < self._size:
self.d_buffer.update({index: item})
return True
else:
return False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add(self, item):\r\n if len(self.buff)==self.size: self.buff.pop(0)\r\n self.buff.append(item)",
"def add_next(self, item, index):\n if index in self.d_buffer.keys():\n return\n if len(self) == self.size:\n self.pop_first()\n self.add_item(item, index)... | [
"0.76870745",
"0.76835316",
"0.7008656",
"0.68846583",
"0.6850312",
"0.6849075",
"0.67566377",
"0.67298174",
"0.6627526",
"0.6571266",
"0.6514428",
"0.64295965",
"0.6416794",
"0.6378212",
"0.6364589",
"0.6336134",
"0.63103914",
"0.6234741",
"0.623079",
"0.6226195",
"0.6119101... | 0.7550045 | 2 |
Remove one particular item from the buffer | def pop_item(self, index):
ix, obj = self.items
if index < len(ix):
self.d_buffer.pop(ix[index])
else:
raise IndexError('Buffer does not have {0} elements'.format(index)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def take(self, item): \n self.contents.remove(item)",
"def __delitem__(self, where):\n with self._lock:\n self._current_bytes -= self._data[where]\n del self._data[where]\n self._order.remove(where)",
"def remove(self, item: T) -> None:\n index = self.index... | [
"0.7478718",
"0.7395259",
"0.70754623",
"0.70754623",
"0.70691514",
"0.7067231",
"0.6973058",
"0.6886449",
"0.6886449",
"0.68595606",
"0.6845985",
"0.6819009",
"0.67979664",
"0.6790535",
"0.6789824",
"0.6737365",
"0.6720759",
"0.67044306",
"0.66581875",
"0.66425633",
"0.66389... | 0.7550008 | 0 |
Remove the first item in the buffer | def pop_first(self):
self.pop_item(0) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_first(self):\n self.deque.pop(0)",
"def delete(self):\n first = self.data[0]\n self.data.pop(0)\n self.size = self.size - 1\n return first",
"def pop_item(self, index):\n ix, obj = self.items\n if index < len(ix):\n self.d_buffer.pop(ix[ind... | [
"0.77843237",
"0.7342911",
"0.71000373",
"0.68947244",
"0.688018",
"0.68741614",
"0.6867453",
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"0.661845",
"0.66004205",
"0.6579086",
"0.65492535",
"0.6534603",
"0.6392726",
"0.6383168",
"0.636512... | 0.73949045 | 1 |
Remove the last item in the buffer | def pop_last(self):
self.pop_item(-1) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_last(self):\n self.deque.pop()",
"def pop(self):\n value = self.buffer[self.end - 1]\n self.buffer[self.end - 1] = None\n self.end = (self.end - 1) % len(self.buffer)\n return value",
"def pop(self):\n data = self.buffer.getvalue()\n self.buffer.seek(0)\n ... | [
"0.7669612",
"0.7375816",
"0.73687816",
"0.7366045",
"0.71360344",
"0.70445234",
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"0.6571084",
"0.6533281",
"0.65202886",
"0.6503479",
"0.64959717",
"0.64928275",
"0.6475953... | 0.7435102 | 1 |
Add a new item at the end of the buffer and drop one item if necessary (from the beginning) | def add_next(self, item, index):
if index in self.d_buffer.keys():
return
if len(self) == self.size:
self.pop_first()
self.add_item(item, index) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add(self, item):\r\n if len(self.buff)==self.size: self.buff.pop(0)\r\n self.buff.append(item)",
"def delayed_buffer_item(self, buffer_item, buffer_item_len, item):\n item_copy = copy.copy(item)\n if buffer_item is None:\n buffer_item = buffer_item_len * [item_copy]\n ... | [
"0.781679",
"0.69368887",
"0.69074106",
"0.6848678",
"0.6844897",
"0.6722651",
"0.6693831",
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"0.65031815",
"0.64660585",
"0.64001614",
"0.6381809",
"0.6352038",
"0.628194",
"0.6240794",
"0.6232624",
"0.62238234",
"0.62209296",
"0.62180114",
"0.62095904",
"0.620959... | 0.7406223 | 1 |
Add a new item at the beginning of the buffer and drop one item if necessary (from the end) | def add_prev(self, item, index):
if index in self.d_buffer.keys():
return
if len(self) == self._size:
self.pop_last()
self.add_item(item, index) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add(self, item):\r\n if len(self.buff)==self.size: self.buff.pop(0)\r\n self.buff.append(item)",
"def add_next(self, item, index):\n if index in self.d_buffer.keys():\n return\n if len(self) == self.size:\n self.pop_first()\n self.add_item(item, index)... | [
"0.7400422",
"0.71560556",
"0.69278336",
"0.6553957",
"0.6530426",
"0.6513943",
"0.6506356",
"0.6479094",
"0.64768803",
"0.6469337",
"0.63909703",
"0.62929386",
"0.6251014",
"0.624164",
"0.6228138",
"0.6228138",
"0.6215412",
"0.6198763",
"0.61914164",
"0.6188572",
"0.6176583"... | 0.70878935 | 2 |
In response to a signal, stops filling the buffer Argument signum frame | def stop_filling(self, signum, frame):
self._filling = False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def handler(signum, frame):\n m.signal()",
"def signal_handler(self, signum, frame):\n self._running = False",
"def signal_kernel(self, signum: int):",
"def signal_kernel(self, signum):\n pass",
"def sigterm(signum, frame):\n loop.stop()",
"def signal(self, args):\n pass",
"d... | [
"0.71383697",
"0.6638584",
"0.66365296",
"0.65838414",
"0.65606594",
"0.651072",
"0.6385658",
"0.633539",
"0.6274212",
"0.62507004",
"0.61414415",
"0.6116271",
"0.6104604",
"0.60822886",
"0.60652584",
"0.60652584",
"0.60072625",
"0.59255743",
"0.5915507",
"0.58945",
"0.589175... | 0.6557572 | 5 |
Get a new picture to put in the buffer | def get_new_item(self, index):
if index not in self.d_buffer.keys():
if 0 <= index < self.n_im:
return self.stack[index]
# Does not raise an error in case of wrong index for easier
# handling upstream
else:
return None
else:... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def take_pic(self):\n \n try:\n if os.path.isfile(self.pics_path):\n os.remove(self.pics_path)\n self.camera.capture(self.pics_path, use_video_port=True)\n except:\n print(\"Error when recording image\")\n exit()\n \n try... | [
"0.67637736",
"0.66389644",
"0.6545607",
"0.649641",
"0.64811593",
"0.6454082",
"0.64298207",
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"0.63116366",
"0.6224079",
"0.6165722",
"0.6156108",
"0.61227834",
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"0.6073141",
"0.60558736",
"0.5991578",
"0.5963383",
"0.593771",
"0.5916153",
"0.591615... | 0.0 | -1 |
Returns a dictionary which maps subfolder > example > source wavs list. Returns a hierarchical dict of relative source file paths when given a folder produced by scaper. | def make_example_dict_from_folder(
folder_sources, subset='all', ss_regex=re.compile(r'example.*_sources'),
pattern='_sources', subfolder_events=('background', 'foreground')):
if subset == 'all':
subfolders = ['train', 'validation', 'eval']
else:
subfolders = [subset]
sources_for_mix = {}
for su... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def extract_folder_file_structure() -> Dict[str, List[str]]:\n folders_and_files = {}\n for path_to_folder in glob.glob(f\"{ZULIPTERMINAL}/**/\", recursive=True):\n complete_directory_path = Path(path_to_folder)\n if complete_directory_path.name in FOLDERS_TO_EXCLUDE:\n continue\n ... | [
"0.6020198",
"0.6010303",
"0.5987424",
"0.59563166",
"0.59123486",
"0.58793145",
"0.581208",
"0.5806299",
"0.5796214",
"0.57869065",
"0.5786168",
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"0.57851917",
"0.5748538",
"0.56930906",
"0.5687381",
"0.5681763",
"0.5676166",
"0.56466466",
"0.5594708",
"0.5585946... | 0.7107858 | 0 |
Makes a tab separated list of examples from a top folder. | def make_example_list_from_folder(
folder_sources, subset='all', ss_regex=re.compile(r'example.*_sources'),
pattern='_sources', subfolder_events=('background', 'foreground')):
example_dict = make_example_dict_from_folder(
folder_sources, subset=subset, ss_regex=ss_regex, pattern=pattern,
subfolder... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def generate_test_list(tdir):\n\n # Skip this if it already exists\n if os.path.exists(os.path.join(tdir.name, \"kstest-list\")):\n return\n\n kstest_log = os.path.join(tdir.name, \"kstest.log\")\n with open(kstest_log) as f:\n for line in f.readlines():\n if not line.startswit... | [
"0.6358621",
"0.60888994",
"0.60677725",
"0.585937",
"0.5713878",
"0.5649388",
"0.5635742",
"0.5621542",
"0.5621542",
"0.55692166",
"0.55307424",
"0.54785776",
"0.54528546",
"0.54419327",
"0.54034835",
"0.5394622",
"0.53802747",
"0.53779495",
"0.53719294",
"0.53674066",
"0.53... | 0.50884354 | 59 |
Checks and possibly corrects a scaper produced example. | def check_and_correct_example(example, root_dir,
check_length, fix_length,
check_mix, fix_mix,
sample_rate=16000, duration=10.0,
chat=False):
# Earlier versions of scaper had a tendency to make mist... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_is_gene_continuously_amplified_wrong_input(self):\n self.assertEqual(\"Wrong input data\", is_gene_continuously_amplified(13))",
"def run_sample_checks(sub: Submission, logger):\n\n samples = sub.sample\n factors = [f.value for f in sub.study.experimental_factor]\n organisms = set()\n ... | [
"0.58382",
"0.5788629",
"0.57696885",
"0.57351416",
"0.5699103",
"0.56888586",
"0.5672273",
"0.5641919",
"0.5641791",
"0.5625378",
"0.5616322",
"0.55867195",
"0.55762357",
"0.5548231",
"0.55378455",
"0.55378455",
"0.55378455",
"0.55340374",
"0.5527008",
"0.5521629",
"0.551697... | 0.64715683 | 0 |
Test that searching for part of the beer name and mfg name works | def test_compound_match(self):
query_string = f'{self.beer.name[:10]}+{self.beer.manufacturer.name[:5]}'
tap = TapFactory(beer=self.beer)
response = self.client.get(
f'{self.url}?search={query_string.upper()}',
)
eq_(response.status_code, 200)
eq_(len(response... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_search_checkname(self):\n self.assertEquals(self.t['Scrubs'].search('my first')[0]['episodename'], 'My First Day')\n self.assertEquals(self.t['My Name Is Earl'].search('Faked His Own Death')[0]['episodename'], 'Faked His Own Death')",
"def test_name(self):\n\n self.check_search(\n ... | [
"0.78682476",
"0.7367077",
"0.69262975",
"0.6646887",
"0.6576953",
"0.64594865",
"0.6428426",
"0.64177704",
"0.6337653",
"0.6327376",
"0.6301725",
"0.62890095",
"0.6284056",
"0.6256203",
"0.6250491",
"0.6238765",
"0.6238765",
"0.6227155",
"0.62223715",
"0.62219703",
"0.621814... | 0.5681 | 84 |
Wrapper for dot product operation, in order to be compatible with both Theano and Tensorflow | def dot_product(x, kernel):
if K.backend() == 'tensorflow':
# todo: check that this is correct
return K.squeeze(K.dot(x, K.expand_dims(kernel)), axis=-1)
else:
return K.dot(x, kernel) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def dot_prod(t1: torch.Tensor, t2: torch.Tensor, verbose: bool = False):\n assert t1.size() == t2.size(), \"Sizes for dot-product must match\"\n return mo.dot_prod(t1, t2, verbose)",
"def _dot(a, b):\n return np.einsum('ijk,ikl->ijl', a, b)",
"def dot(a, b):\r\n a, b = as_tensor_variable(a), as_ten... | [
"0.7651723",
"0.76122725",
"0.75896275",
"0.75178",
"0.74978065",
"0.74902385",
"0.74902385",
"0.74902385",
"0.74902385",
"0.7466889",
"0.74378735",
"0.7429341",
"0.7418364",
"0.73810273",
"0.7376632",
"0.7343613",
"0.7331493",
"0.73104995",
"0.7309816",
"0.72749436",
"0.7270... | 0.7535402 | 3 |
Keras Layer that implements an Attention mechanism for temporal data. Supports Masking. | def __init__(self,
W_regularizer=None, b_regularizer=None,
W_constraint=None, b_constraint=None,
bias=True,
return_attention=False,
**kwargs):
self.supports_masking = True
self.return_attention = return_attention
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _Attention(self, name, is_causal=True):\n p = self.params\n tr_atten_p = TransformerAttentionLayer.Params().Set(\n name='transformer_atten',\n input_dim=p.model_dim,\n hidden_dim=p.attention_hidden_dim or p.model_dim,\n is_masked=is_causal,\n num_heads=p.num_heads,\n ... | [
"0.6418364",
"0.6348513",
"0.5860708",
"0.58178973",
"0.56244344",
"0.56133187",
"0.55821043",
"0.54933465",
"0.5388436",
"0.53026986",
"0.5298122",
"0.52612346",
"0.52581245",
"0.5257906",
"0.5252626",
"0.52330077",
"0.5183299",
"0.5153909",
"0.5150206",
"0.5134586",
"0.5112... | 0.48330575 | 69 |
Gets the position of a Fibonacci number and returns the Fibonacci number | def fibonacci_number_counter(p):
if p == 0:
return 0
elif p == 1 or p == 2:
return 1
else:
fibonacci_list = [1, 1]
while len(fibonacci_list) < p:
fibonacci_list.append(fibonacci_list[-1] + fibonacci_list[-2])
return fibonacci_list[-1] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_fib(position):\n\n # Base Case: Positions greater thatn 0 or 1, since Fibonacci for 0 is 0 and\n # 1 is 1.\n if position == 0 or position == 1:\n return position\n\n return get_fib(position - 1) + get_fib(position - 2)",
"def next_fib(f):\n for f in fib:\n i = fib.index(f)\n ... | [
"0.84752756",
"0.7775988",
"0.7635731",
"0.75487685",
"0.75380415",
"0.7457801",
"0.7436363",
"0.7384562",
"0.7375154",
"0.73195016",
"0.7316325",
"0.7299088",
"0.7251135",
"0.7249416",
"0.7244615",
"0.71986157",
"0.7195691",
"0.7191518",
"0.71824896",
"0.7170513",
"0.7158625... | 0.0 | -1 |
Get file names from config or user input Also get specified framerate, or default is 10 Hz Open file stream | def setup(self):
print("Looking for ", self.filename)
if os.path.exists(self.filename):
n, ext = os.path.splitext(self.filename)[:2]
if ext == ".h5" or ext == ".hdf5":
with h5py.File(self.filename, "r") as file:
keys = list(file.keys())
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def read_data_samples(fp):\n if(path.isdir(fp)):\n fps = glob.glob(fp + '\\\\*.txt')\n return list(map(lambda x: read_file(x), fps))",
"def get_file_list(mixer_file, select_random, use_list_of_files):\n logger = logging.getLogger(get_file_list.__name__)\n files = list()\n\n if use_list_of_files:\... | [
"0.5744633",
"0.57154065",
"0.55288815",
"0.54487276",
"0.5439408",
"0.54362303",
"0.5347286",
"0.5314243",
"0.5279614",
"0.5239958",
"0.520664",
"0.51828444",
"0.51358587",
"0.5131761",
"0.512756",
"0.5109966",
"0.5094053",
"0.5076949",
"0.506344",
"0.50362504",
"0.50106287"... | 0.0 | -1 |
Here just return frame from loaded data | def getFrame(self, num):
return self.data[:, :, num] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_data(self):",
"def load_data(self) -> None:",
"def _get_raw_data(self, idx=0):\n # Get the time step then make a data frame\n raise NotImplementedError('Code me up!')\n #data = self._data[???]\n return data",
"def dataframe(self):\n\t\treturn self._dataframe",
"def data... | [
"0.66847086",
"0.66500604",
"0.6578558",
"0.6544992",
"0.6464981",
"0.6419371",
"0.63444304",
"0.6261828",
"0.62608165",
"0.6257387",
"0.61691505",
"0.613629",
"0.60970247",
"0.6049352",
"0.60232645",
"0.5995074",
"0.59805757",
"0.59766096",
"0.597535",
"0.59465176",
"0.59391... | 0.0 | -1 |
Get file names from config or user input Also get specified framerate, or default is 10 Hz Open file stream | def setup(self):
print("Looking for ", self.filename)
if os.path.exists(self.filename):
file = scio.loadmat(self.filename)
self.data = np.squeeze(file["data"])
print("Motion Data length is ", len(self.data))
else:
raise FileNotFoundError | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def read_data_samples(fp):\n if(path.isdir(fp)):\n fps = glob.glob(fp + '\\\\*.txt')\n return list(map(lambda x: read_file(x), fps))",
"def get_file_list(mixer_file, select_random, use_list_of_files):\n logger = logging.getLogger(get_file_list.__name__)\n files = list()\n\n if use_list_of_files:\... | [
"0.5744606",
"0.5714158",
"0.5527169",
"0.5447836",
"0.5439457",
"0.5434857",
"0.53462785",
"0.5313303",
"0.5279001",
"0.52396804",
"0.5205854",
"0.5181732",
"0.51353776",
"0.51318854",
"0.5127048",
"0.51090044",
"0.50929743",
"0.50770855",
"0.5064212",
"0.5035977",
"0.501092... | 0.0 | -1 |
Here just return frame from loaded data | def getFrame(self, num):
return self.data[num] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_data(self):",
"def load_data(self) -> None:",
"def _get_raw_data(self, idx=0):\n # Get the time step then make a data frame\n raise NotImplementedError('Code me up!')\n #data = self._data[???]\n return data",
"def dataframe(self):\n\t\treturn self._dataframe",
"def data... | [
"0.66847086",
"0.66500604",
"0.6578558",
"0.6544992",
"0.6464981",
"0.6419371",
"0.63444304",
"0.6261828",
"0.62608165",
"0.6257387",
"0.61691505",
"0.613629",
"0.60970247",
"0.6049352",
"0.60232645",
"0.5995074",
"0.59805757",
"0.59766096",
"0.597535",
"0.59465176",
"0.59391... | 0.0 | -1 |
Creates the glove dictionnary from the glove file as a map, where the words are the key Forgets the stopwords | def _extractGloveVects():
embeddings_index = {}
with open(GLOVE_CORPUS_FILE) as f:
for line in f:
values = line.split()
word = values[0].lower()
if word not in _cachedStopWords:
coefs = np.asarray(values[1:], dtype='float32')
embe... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_glove_dictionary(self, file_path=\"./glove.twitter.27B.25d.txt\"):\n file = open(file_path, \"r\",encoding='utf-8')\n dictionary = {}\n keys = []\n for word_vector in file:\n dictionary[word_vector.split()[0]] = word_vector.split()[1:]\n keys.append(word_ve... | [
"0.7701295",
"0.7338579",
"0.6947404",
"0.69307244",
"0.6922794",
"0.6919339",
"0.68388474",
"0.67719364",
"0.6673551",
"0.66312903",
"0.6379227",
"0.6355576",
"0.63511074",
"0.63474447",
"0.6342942",
"0.633822",
"0.6330652",
"0.6327623",
"0.6324111",
"0.6315943",
"0.63043386... | 0.6140933 | 34 |
Save the GloVe dictionary memory Object into binary file | def saveGloveDicIntoFile(gloveDic):
np.save(GLOVE_DICT_FILE, np.asarray([gloveDic])) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save_to_file(self, filename):\n outMap = {}\n for kanal in self._datastoreMap:\n # svaki pojedini Datastore se zna zapakirati u mapu (dictionary)\n outMap[kanal] = self._datastoreMap[kanal].store2dict()\n # serialize u binary string\n binstr = pickle.dumps(outM... | [
"0.6844523",
"0.66101277",
"0.65988386",
"0.6553184",
"0.65457076",
"0.6461133",
"0.6404799",
"0.6393051",
"0.6333784",
"0.63045895",
"0.6251503",
"0.6237465",
"0.6224473",
"0.62162364",
"0.62162364",
"0.62048894",
"0.6202406",
"0.6202227",
"0.62018937",
"0.62000716",
"0.6197... | 0.6865105 | 0 |
Create an memory Object of GloVe dictionary from binary file | def loadGloveDicFromFile():
#if the resource file is not present, creates the file containing all vectors
#and return vectors
if not isfile(GLOVE_DICT_FILE):
vects = _extractGloveVects()
saveGloveDicIntoFile(vects)
return vects
return np.load(GLOVE_DICT_FILE)[0] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_from_file(path):\n with open(path) as obj:\n raw_file = obj.read()\n file_lines = [line.split(\" \") for line in raw_file.split(\"\\n\")]\n\n vertices = {}\n faces = []\n for number, line in enumerate(file_lines):\n if line[0] == \"v\":\n ... | [
"0.6563649",
"0.6548593",
"0.6548593",
"0.6302663",
"0.62614805",
"0.6254731",
"0.6220778",
"0.61928546",
"0.61538893",
"0.6052055",
"0.6007737",
"0.59501976",
"0.594304",
"0.59378004",
"0.5926469",
"0.59219426",
"0.5878771",
"0.5871942",
"0.58663714",
"0.58638996",
"0.585580... | 0.60128707 | 10 |
Create dictionary of vectors and save it into file | def createGloveDic():
saveGloveDicIntoFile(_extractGloveVects()) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save_dict(emb, path_to_vec, dim=100):\n word_vec = {}\n for w in emb.keys():\n word_vec[w] = emb[w]\n with open(path_to_vec + f'embedding_{str(dim)}d.txt', 'w') as file:\n for w, v in word_vec.items():\n file.write(w + ' ')\n for el in v:\n file.write... | [
"0.68721676",
"0.6824662",
"0.6620886",
"0.6619933",
"0.65735036",
"0.6529465",
"0.6515113",
"0.6493432",
"0.6476171",
"0.6336338",
"0.6321563",
"0.62979835",
"0.62917596",
"0.62372684",
"0.61660385",
"0.61660385",
"0.61642545",
"0.6095442",
"0.60460395",
"0.60164315",
"0.597... | 0.675696 | 2 |
Called from admin interface when page is moved. Should be used on all the places which are changing page position. Used like an interface to mptt, but after move is done page_moved signal is fired. | def move_page(self, target, position='first-child'):
self.move_to(target, position)
# fire signal
self.force_moderation_action = PageModeratorState.ACTION_MOVE
cms_signals.page_moved.send(sender=Page, instance=self) #titles get saved before moderation
self.save(change_st... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def post_save_page(instance, raw, created, **kwargs):\n old_page = instance.old_page\n del(instance.old_page)\n \n if settings.CMS_MODERATOR:\n # tell moderator something was happen with this page\n from cms.utils.moderator import page_changed\n page_changed(instance, old_page)",
... | [
"0.64120024",
"0.6210927",
"0.6112562",
"0.6102588",
"0.60626286",
"0.6050393",
"0.599529",
"0.59568924",
"0.59317076",
"0.57837987",
"0.57799387",
"0.5729946",
"0.5728036",
"0.5711554",
"0.57115483",
"0.568866",
"0.55789995",
"0.5550567",
"0.55030763",
"0.54747677",
"0.54612... | 0.7220067 | 0 |
copy a page and all its descendants to a new location Doesn't checks for add page permissions anymore, this is done in PageAdmin. | def copy_page(self, target, site, position='first-child', copy_permissions=True, copy_moderation=True):
from cms.utils.moderator import update_moderation_message
descendants = [self] + list(self.get_descendants().order_by('-rght'))
tree = [target]
level_dif = self.level - target... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def copy_pages(config):\n\n if \"Pages\" not in config:\n INFO(\"No information about pages\")\n return\n\n target_path = os.path.join(config[\"target\"][\"path\"],\n constants.PAGES_FOLDER)\n\n pages = config[\"Pages\"]\n params = {\n # \"rename\": No... | [
"0.67569137",
"0.62102824",
"0.6115456",
"0.6008251",
"0.57991344",
"0.57538474",
"0.57470375",
"0.5713914",
"0.56825674",
"0.5637052",
"0.55938256",
"0.55267644",
"0.5525658",
"0.5520369",
"0.55132717",
"0.5499208",
"0.54576015",
"0.5446981",
"0.53665066",
"0.53636324",
"0.5... | 0.79622966 | 0 |
get the calculated status of the page based on published_date, published_end_date, and status | def get_calculated_status(self):
if settings.CMS_SHOW_START_DATE:
if self.publication_date > datetime.now():
return False
if settings.CMS_SHOW_END_DATE and self.publication_end_date:
if self.publication_end_date < datetime.now():
return Tr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_page_caculated_status(self):\n from pages import settings as pages_settings\n setattr(pages_settings, \"PAGE_SHOW_START_DATE\", True)\n yesterday = datetime.datetime.now() - datetime.timedelta(days=1)\n tomorrow = datetime.datetime.now() + datetime.timedelta(days=1)\n\n ... | [
"0.68869996",
"0.613938",
"0.58442456",
"0.57751507",
"0.57710797",
"0.57653105",
"0.564951",
"0.55711806",
"0.54949707",
"0.54802895",
"0.5322023",
"0.53194374",
"0.53085303",
"0.52722406",
"0.5250116",
"0.51886964",
"0.5137271",
"0.5119178",
"0.50824904",
"0.50594455",
"0.5... | 0.7154325 | 0 |
get the list of all existing languages for this page | def get_languages(self):
titles = Title.objects.filter(page=self)
if not hasattr(self, "languages_cache"):
languages = []
for t in titles:
if t.language not in languages:
languages.append(t.language)
self.languages_cache = languages... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_all_languages():\n\tdef _get():\n\t\tif not frappe.db:\n\t\t\tfrappe.connect()\n\t\treturn frappe.db.sql_list('select name from tabLanguage')\n\treturn frappe.cache().get_value('languages', _get)",
"def languages(self):\r\n url = '{0}/{1}'.format(self.get_url(), 'languages')\r\n\r\n return ... | [
"0.7950742",
"0.79043835",
"0.78993666",
"0.78554344",
"0.76446795",
"0.75309783",
"0.74677473",
"0.74178064",
"0.7268602",
"0.723141",
"0.71480125",
"0.70844215",
"0.7034048",
"0.7020481",
"0.6945113",
"0.69438887",
"0.6939026",
"0.6901797",
"0.68972915",
"0.6825298",
"0.676... | 0.7613201 | 5 |
Helper function for accessing wanted / current title. If wanted title doesn't exists, EmptyTitle instance will be returned. | def get_title_obj(self, language=None, fallback=True, version_id=None, force_reload=False):
self._get_title_cache(language, fallback, version_id, force_reload)
if self.title_cache:
return self.title_cache
return EmptyTitle() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_title():",
"def get_title(self):\n return self.run_command('get_title')[0]",
"def get_title(self) -> Optional[str]:\n return self.title",
"def get_title(cls, obj, **kwargs):\n if isinstance(obj.data, dict):\n titles = filter(None, get_value(obj.data, \"titles.title\", []))... | [
"0.7317102",
"0.7292215",
"0.7144462",
"0.7138358",
"0.70548296",
"0.7035024",
"0.7035024",
"0.7035024",
"0.7024971",
"0.7007832",
"0.6984208",
"0.6984208",
"0.69815016",
"0.69728166",
"0.69728166",
"0.69728166",
"0.6934254",
"0.68951046",
"0.68767846",
"0.68251956",
"0.68176... | 0.0 | -1 |
Helper function for getting attribute or None from wanted/current title. | def get_title_obj_attribute(self, attrname, language=None, fallback=True, version_id=None, force_reload=False):
try:
return getattr(self.get_title_obj(language, fallback, version_id, force_reload), attrname)
except AttributeError:
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_title(self) -> Optional[str]:\n return self.title",
"def get_title():",
"def get_title(self):\n return self.run_command('get_title')[0]",
"def getAttrName(self, context):\r\n return self.attr if self.attr is not None else context.attr",
"def _get_attribute(self):\n return se... | [
"0.6739067",
"0.6692714",
"0.65235364",
"0.63904065",
"0.63688284",
"0.6344936",
"0.6288744",
"0.62723464",
"0.62668854",
"0.62502044",
"0.6228555",
"0.6215669",
"0.6215669",
"0.6215669",
"0.6215669",
"0.6191291",
"0.6191291",
"0.61492777",
"0.6135957",
"0.61327934",
"0.61327... | 0.6898922 | 0 |
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