> (16 - self.camera.pixel_bits)).astype(np.uint16)\n\n ndx = self.dpar.cur_cap\n\n if self.dpar.cap_live_swap:\n pix, gray = self._get_pixmap(frame, self.dpar.iwindow[ndx])\n self.live_screen.live_title = self._cap_title(ndx)\n self.live_screen.setPixmap(pix)\n else:\n pix, gray = self._get_pixmap(frame[::4,::4], self.dpar.iwindow[ndx])\n self.cap_screen.cap_title = self._cap_title(ndx)\n self.cap_screen.setPixmap(pix)\n self.cap_screen.format_for_cap() # This is because first time, format is for \"no stills\".","def update_image(self, surface):\n self.ui_widget.update_image(surface=surface)","def run(self):\n \n count = 0\n while True:\n self.__ticker.tick()\n\n self.update()\n img = self.get_new_image()\n if img == None:\n print \"not receiving images yet...\"\n else:\n if self.verbose:\n cv.ShowImage(\"SnapShotSaver\", img)\n cv.WaitKey(10)\n cv.SaveImage(\"%s/%s_%d.png\" % (self.destination, self.prefix, count), img)\n count += 1","def update_image(self, cv_img):\n \n qt_img = self.convert_cv_qt(cv_img)\n self.image_label.setPixmap(qt_img)\n #pass","def update_image(self):\n if self.filenames:\n pos = self.slider.value()\n proj, flat, dark, theta = dx.read_aps_32id(self.filenames, proj=(pos, pos+1))\n if self.ffc_correction:\n image = proj[0,:,:].astype(np.float)/flat[0,:,:].astype(np.float)\n else:\n image = proj[0,:,:].astype(np.float)\n self.image_item.setImage(image)","def update_image(self, cv_img):\n qt_img = self.convert_cv_qt(cv_img)\n self.image_label.setPixmap(qt_img)","def update_image(self, cv_img):\n qt_img = self.convert_cv_qt(cv_img)\n self.image_label.setPixmap(qt_img)","def _update_frame(self):\n # check if continue\n if self._keep_updating:\n self.__frame = self._cam.get_display_frame()\n if self.__frame is not None:\n self._cvn_camera_viewfinder.create_image(0, 0, image=self.__frame, anchor=tk.NW)\n\n self._root.after(self._delay, self._update_frame)","def update(self):\r\n while True:\r\n # if the thread indicator variable is set, stop the thread\r\n if self.stopped:\r\n self.webcam.release()\r\n return\r\n # otherwise, read the next frame from the webcam stream\r\n grabbed, frame = self.webcam.read()\r\n '''if self.cam_zoom:\r\n frame = self.zoom(frame)'''\r\n with self.read_lock:\r\n self.grabbed = grabbed\r\n try:\r\n #self.frame = cv2.resize(frame, (self.width, self.height))\r\n self.frame = frame\r\n except:\r\n None","def refreshImages(self):\n fileName1 = \"DECK/\" + str(self.card1) + \".gif\"\n fileName2 = \"DECK/\" + str(self.card2) + \".gif\"\n fileName3 = \"DECK/\" + str('b') + \".gif\"\n self.image1 = PhotoImage(file = fileName1)\n self.cardLabel1[\"image\"] = self.image1\n self.image2 = PhotoImage(file = fileName2)\n self.cardLabel2[\"image\"] = self.image2\n self.image3 = PhotoImage(file = fileName3)\n self.cardLabel3[\"image\"] = self.image3","def update_display(self):\n self.lick_plot_0.setData(self.k+self.T,self.buffer[:,1]) \n self.lick_plot_1.setData(self.k+self.T,self.buffer[:,2]) \n self.breathing_plot.setData(self.k+self.T,self.buffer[:,0]) \n \n if self.settings.movie_on.value():\n self.camera_image.setImage(self.camera.read())\n if self.settings.save_movie.value():\n self.camera.write()\n \n #print(self.buffer_h5.size)","def update_img(self):\n self.img = np.array(self.image)","def update_image(self):\n if self.filenames:\n pos = self.slider.value()\n image = read_tiff(self.filenames[pos])\n self.image_item.setImage(image)","def update_image(self, cv_img):\n qt_img = self.convert_cv_qt(cv_img)\n self.label.setPixmap(qt_img)","def update_current_image(self):\n\n rect = (0, 0, self.variables.canvas_width, self.variables.canvas_height)\n if self.variables.canvas_image_object is not None:\n self.variables.canvas_image_object.update_canvas_display_image_from_canvas_rect(rect)\n self.set_image_from_numpy_array(self.variables.canvas_image_object.display_image)\n self.update()","def update_image(self, cv_img):\n self.updated_temp_goal_image = cv_img\n qt_img = self.convert_cv_qt(cv_img)\n self.image_label.setPixmap(qt_img)","def update_image(self):\n if self.first is None or self.second is None:\n LOG.warn(\"No images set yet\")\n else:\n pos = self.slider.value()\n moved = np.roll(self.second, self.second.shape[0] / 2 - pos, axis=0)\n self.image_item.setImage(moved - self.first)","def update_image(self, img):\r\n qt_img = self.convert_cv_qt(img)\r\n self.main.caption_feed.setPixmap(qt_img)","def update_movie(self, file_name):\n try:\n pix = QPixmap(file_name)\n self.cur_imageRect['width'] = pix.width()\n self.cur_imageRect['height'] = pix.height()\n if self.isFullScreen():\n width = self.screen_width\n height = self.screen_height\n padding_left = 0\n padding_top = 0\n else:\n width = 1000\n height = 450\n padding_left = 40\n padding_top = 50\n scale = min(width / pix.width(), height / pix.height())\n self.video_label.setGeometry(padding_left, padding_top, pix.width() * scale, pix.height() * scale)\n self.video_label.clear()\n self.video_label.setPixmap(pix)\n except:\n pass\n os.remove(file_name)","def update(self):\n self.imagecounter +=1\n if self.imagecounter > 7:\n self.imagecounter = 0\n self.image = pygame.image.load(self.pictures[self.imagecounter])\n self.rect = self.image.get_rect()\n self.rect.left = self.x\n self.rect.top = self.y","def updateScreen(self):\n\t\ttry:\n\t\t\tfile1 = open(self.imageFile, \"rb\")\n\t\texcept:\n\t\t\ttkMessageBox.showerror('Play', '\"' + self.imageFile + '\" could not be played.')\n\t\t\texit()\n\n\t\t# Reset event variables for tracking playing/paused/stopped states\n\t\tself.pauseEvent.clear()\n\t\tself.stopEvent.clear()\n\n\t\tcounter = 0\n\t\twhile 1:\n\t\t\tval = file1.read(5) # Read the next 5 byte header\n\t\t\tif val == '': # End of video file has been reached\n\t\t\t\tself.stopEvent.set() # Playback has finished\n\t\t\t\ttkMessageBox.showinfo(\"Play\", \"Playback has finished.\")\n\t\t\t\tfile1.close()\n\t\t\t\texit()\n\t\t\tdata = file1.read(int(val)) # Read the current JPEG image\n\t\t\tcounter += 1\n\t\t\ttemp_file_name = str(counter) + \".jpeg\"\n\t\t\tfile2 = open(temp_file_name, \"wb\")\n\t\t\tfile2.write(data)\n\t\t\tfile2.close()\n\t\t\ttime.sleep(0.035)\n\t\t\tphoto = ImageTk.PhotoImage(Image.open(temp_file_name))\n\t\t\tself.label.configure(image = photo, height=288)\n\t\t\tself.label.image = photo\n\t\t\tos.remove(temp_file_name) # Comment out this line if you want the extracted JPEG images to remain on disk after playback finishes.\n\t\t\twhile self.pauseEvent.isSet(): # Pause playback until an Exit, Resume or Stop command is issued\n\t\t\t\t\n\t\t\t\t# Case where an Exit or Stop command is issued whilst playback has been paused\n\t\t\t\tif self.stopEvent.isSet():\n\t\t\t\t\tfile1.close()\n\t\t\t\t\tself.quitEvent.clear() # Inform the main thread that it may proceed to close the Pirate GUI window.\n\t\t\t\t\texit() # Kill the playback thread only\n\t\t\t\t\n\t\t\t\tpass # Keep looping\n\t\t\t\n\t\t\t# Case where an Stop command is issued during playback\n\t\t\tif self.stopEvent.isSet():\n\t\t\t\tfile1.close()\n\t\t\t\tself.quitEvent.clear() # Inform the main thread that it may proceed to close the Pirate GUI window.\n\t\t\t\texit() # Kill the playback thread only","def update(self):\r\n for f in self.stream:\r\n # if the thread indicator variable is set, stop the thread\r\n # and release camera resources\r\n if self.stopped:\r\n self.stream.close()\r\n self.rawCapture.close()\r\n self.camera.close()\r\n return\r\n # grab the frame from the stream and clear the stream in\r\n # preparation for the next frame\r\n frame = f.array\r\n self.rawCapture.truncate(0)\r\n with self.read_lock:\r\n self.frame = frame","def update(self):\n while not rospy.is_shutdown():\n self.calculate_frame()\n for callback in self.callbacks:\n callback(self.keypoints, self.image)","def reload_image(self):\n img = self.img_manager.update_image()\n\n q_image = PyQt5.QtGui.QImage.fromData(img.read())\n q_pixmap = PyQt5.QtGui.QPixmap.fromImage(q_image)\n\n self.image_widget.setPixmap(q_pixmap)","def update(self):\n # Get frame from video source:\n ret, frame = self.vid.read()\n\n if ret:\n # Convert the captured frame into grayscale\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n gray = cv2.equalizeHist(gray)\n\n # Get all faces from the video frame\n faces = self.faceCascade.detectMultiScale(gray, 1.2,5)\n\n # For each face in faces\n for (x, y, w, h) in faces:\n # Create rectangle around the face\n cv2.rectangle(frame, (x-20,y-20), (x+w+20,y+h+20), (0,255,0), 4)\n\n # Recognize the face belongs to which ID\n Id = self.recognizer.predict(gray[y:y+h,x:x+w])\n\n ### IDENTIFICATION & SOCKET CODE GOES HERE\n if Id[0] == self.user_id:\n # If the target face is found 10 times then access is granted\n self.identification_count += 1\n if self.identification_count > 10:\n self.master.switch_frame(AccessGranted)\n\n name_to_put = self.user_name\n else:\n name_to_put = \"Unknown - Access Denied\"\n\n # Put text describe who is in the picture\n cv2.rectangle(frame, (x-22,y-90), (x+w+22, y-22), (0,255,0), -1)\n cv2.putText(frame, str(name_to_put), (x,y-40), self.font, 2, (255,255,255), 3)\n\n self.after(50, self.update)","def display_images():\n vc = cv2.VideoCapture(0) # Open webcam\n figure, ax = plt.subplots(1, 2, figsize=(10, 5)) # Intiialise plot\n\n count = 0 # Counter for number of aquired frames\n intensity = [] # Append intensity across time\n\n # For loop over generator here\n intensity.append(imageintensity)\n plot_image_and_brightness() # Call plot function\n count += 1\n\n # This triggers exit sequences when user presses q\n if cv2.waitKey(1) & 0xFF == ord('q'):\n # Clean up here\n plt.close('all') # close plots\n generator.close() # Use generator exit for clean up,\n break # break loop","def show(self):\n if self.video:\n self.video.write(self.img)\n cv2.imshow('Simpy', self.img)\n cv2.waitKey(1000 // self.fps)","def prepare_images(self):\n\n qt_original_image = self.convert_image_to_QTformat(self.original_image)\n self.send_original_photo_to_gui.emit(qt_original_image)\n\n self.processed_image = self.procces_image(self.original_image)\n qt_processed_image = self.convert_image_to_QTformat(self.processed_image)\n self.send_processed_photo_to_gui.emit(qt_processed_image)","def update(self):\n self.moving_sprites.update() \n self.static_sprites.update()\n self.camera.update(self.player)","def _update(self):\n self.cv.update()","def updateMovie(self, imageFile):\r\n\t\tframe = ImageTk.PhotoImage(Image.open(imageFile))\r\n\t\tself.label.configure(image=frame, height=300)\r\n\t\tself.label.image = frame","def display_video_stream(self):\n\n t = time.time()\n\n frame = self.video_stream.read()\n # frame = self.capture.read()[1]\n\n frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n frame = cv2.flip(frame, 1)\n\n qimage = array2qimage(frame)\n\n # image = QImage(frame, frame.shape[1], frame.shape[0], # faster, but potentially causes memory leak?\n # frame.strides[0], QImage.Format_RGB888)\n self._webcam_stream_qlabel.setPixmap(QPixmap.fromImage(qimage))\n self._webcam_stream_qlabel.update()\n\n if MainApp.PRINT_CAM_LATENCY:\n print(\"\\r{:.2}\".format(time.time()-t), end='')","def update_frame(self):\n if not self.image_queue: return\n image = self.image_queue.pop()\n self.image_queue.rotate(-1)\n self.original_image = image\n self.altered_image = image.copy()\n\n if self.tracking:\n self.update_frame_tracking()\n self.display_image(True)\n elif self.calibrating:\n self.update_frame_calibrating()\n self.display_image(True)\n else:\n image = cv2.flip(self.altered_image, 1)\n self.display_image(True)","def _update_screen(self) -> None:\n # setup the source image with an alpha channel\n alpha = 255 * np.ones_like(self.image[..., 0:1])\n image = np.concatenate([self._image, alpha], axis=-1).astype(np.uint8)\n # setup the super pixel segmentations\n super_pixels = np.zeros_like(self.image)\n super_pixels = mark_boundaries(\n super_pixels,\n self._super_pixel_segments,\n self._super_pixel_color\n )\n # concatenate the first channel of sup as the alpha channel\n super_pixels = [super_pixels, super_pixels[..., 0:1]]\n super_pixels = np.concatenate(super_pixels, axis=-1).astype(np.uint8)\n # setup the segmentation image with an alpha channel scaled by the\n # opacity parameter of the application [0, 9]\n intensity = 255 * (self._opacity / 9)\n intensity = intensity * np.ones_like(self._segmentation[..., 0:1])\n segmentation = np.concatenate([self._segmentation, intensity], axis=-1)\n segmentation = segmentation.astype(np.uint8)\n # send the images to the window\n self._view.show([image, segmentation, super_pixels])","def displayImages(self):\n\n plt.figure(figsize=(8,6))\n plt.subplot(1,2,1)\n plt.imshow( self.original_image, cmap=\"gray\")\n plt.title(\"Original Image\")\n plt.subplot(1,2,2)\n plt.imshow( self.blurred_image, cmap=\"gray\")\n plt.title(\"Blurred Image\")","def _update_images(self, axis=None, draw=True):\n self._update_base_images(axis=axis)\n if draw:\n self._draw(axis)","def _image(self):\n print(\"imaging\")\n self.images.append(self.device_control.image())\n yield","def update_image(self, image):\n raise NotImplementedError()","def __video_loop(self):\n # Keep looping over frames until we are instructed to stop\n while not self.__quit.is_set():\n # Get the correct frame\n self.__frame = self.__detect.frame\n if self.__frame is None:\n continue\n\n # Convert BGR color to RGB and\n # make it to pillow format\n image = cv2.cvtColor(self.__frame, cv2.COLOR_BGR2RGB)\n image = Image.fromarray(image)\n image = ImageTk.PhotoImage(image)\n\n # If the panel is not None, initialize it\n if self.__panel is None:\n self.__panel = tk.Label(image=image)\n self.__panel.image = image\n self.__panel.grid(row=0,\n column=0,\n rowspan=4,\n padx=10,\n pady=10)\n else: # Otherwise, simply update the panel\n self.__panel.configure(image=image)\n self.__panel.image = image\n\n # Output the detected categories\n text = \"\"\n for name, count in self.__detect.categories.items():\n text = f\"{name}: {count}\\n\"\n self.__info_label.configure(text=text)","def _update_(self,update_background=True):\n # -- Make sure the fundamental update (if any) are made\n super(Image,self)._update_()\n # - Data\n self._update_data_(update_background=update_background)","def update_image(self):\n modified_since = (\n dict(modified__gt=self.image_updated) if self.image_updated else {}\n )\n if self.image_path and self.image_path != \"__uploaded__\":\n # Does the file need updating?\n images = self.files.filter(\n current=True, path=self.image_path, **modified_since\n ).order_by(\"-modified\")\n if len(images) > 0:\n self.set_image_from_file(images[0])\n else:\n # Try to find an image for the project and use the most\n # recently modified since the image was last updated\n images = self.files.filter(\n current=True, mimetype__startswith=\"image/\", **modified_since,\n ).order_by(\"-modified\")\n if len(images) > 0:\n self.set_image_from_file(images[0])","def let_camera_update_parameters(path_to_images, name_image, video_source=\"/dev/video0\"):\n subprocess_cmd(\"ffmpeg -f video4linux2 -s 1280x720 -i {} -ss 00:00:02 -frames 1 ./{}/{} -loglevel error -nostats\".format(video_source, path_to_images, name_image))","def update(self):\n if self.mudpi.is_prepared:\n if self.duration > self.delay.total_seconds():\n if self.record_video:\n self.capture_recording(duration=self.record_duration)\n else:\n self.capture_image()\n self.reset_duration()","def update(self) -> None:\n self.all_sprites.update()","def image_cb(self, msg):\n self.has_image = True\n self.camera_image = msg","def update_image(self, data):\n self.image_data.append(data)\n if len(self.image_data) > self.image_height:\n self.image_data = self.image_data[1:]\n\n self.image_render += 1\n\n # A 200 pixel tall image squashed into the render view does not\n # appear unpleasantely jumpy when scrolled by 5\n if self.image_render % 5 != 0 and self.image_render != 1:\n return\n\n img_data = range(len(self.image_data))\n\n position = 0\n while position < len(img_data):\n img_data[position] = self.image_data[position]\n position += 1\n\n new_data = numpy.array(img_data).astype(float)\n\n mid = self.main_image_dialog\n mid.image.set_data(new_data)\n\n # If you do autoscale here, it tends to jump around in appearing\n # to stretch to the window and be in 'normal' size\n mid.get_plot().replot()","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 snapshot(self):\n\n if self.pj[OBSERVATIONS][self.observationId][TYPE] in [MEDIA]:\n\n if self.playerType == VLC:\n\n if self.playMode == FFMPEG:\n\n for idx, media in enumerate(self.pj[OBSERVATIONS][self.observationId][FILE][PLAYER1]):\n if self.FFmpegGlobalFrame < sum(self.duration[0:idx + 1]):\n\n p = pathlib.Path(media)\n snapshotFilePath = str(p.parent / \"{}_{}.png\".format(p.stem, self.FFmpegGlobalFrame))\n\n if self.detachFrameViewer or self.second_player():\n self.frame_viewer1.lbFrame.pixmap().save(snapshotFilePath)\n elif not self.detachFrameViewer:\n self.lbFFmpeg.pixmap().save(snapshotFilePath)\n self.statusbar.showMessage(\"Snapshot player #1 saved in {}\".format(snapshotFilePath), 0)\n break\n\n if self.second_player():\n for idx, media in enumerate(self.pj[OBSERVATIONS][self.observationId][FILE][PLAYER2]):\n if self.FFmpegGlobalFrame2 < sum(self.duration2[0:idx + 1]):\n p = pathlib.Path(media)\n snapshotFilePath = str(p.parent / \"{}_{}.png\".format(p.stem, self.FFmpegGlobalFrame2))\n\n self.frame_viewer2.lbFrame.pixmap().save(snapshotFilePath)\n self.statusbar.showMessage(\"Snapshot player #2 saved in {}\".format(snapshotFilePath), 0)\n break\n\n else: # VLC\n\n current_media_path = url2path(self.mediaplayer.get_media().get_mrl())\n # TODO: replace with pathlib\n dirName, fileName = os.path.split(current_media_path)\n self.mediaplayer.video_take_snapshot(0, \"{dirName}{sep}{fileNameWOExt}_{time}.png\".format(\n dirName=dirName,\n sep=os.sep,\n fileNameWOExt=os.path.splitext(fileName)[0],\n time=self.mediaplayer.get_time()),\n 0, 0)\n\n # check if multi mode\n # second video together\n if self.simultaneousMedia:\n current_media_path = url2path(self.mediaplayer2.get_media().get_mrl())\n\n dirName, fileName = os.path.split(current_media_path)\n self.mediaplayer2.video_take_snapshot(0, \"{dirName}{sep}{fileNameWOExt}_{time}.png\".format(\n dirName=dirName,\n sep=os.sep,\n fileNameWOExt=os.path.splitext(fileName)[0],\n time=self.mediaplayer2.get_time()),\n 0, 0)","def display(self):\n\t\tself.imgDisplay.set_from_pixbuf(self.getVisible())\n\t\tgc.collect()","def run(self):\n\n # capture from web cam\n cap = cv2.VideoCapture(self.gstreamer_pipeline(), cv2.CAP_GSTREAMER)\n while self._run_flag:\n ret, cv_img = cap.read()\n if ret:\n self.change_pixmap_signal.emit(cv_img)\n # shut down capture system\n cap.release()","def update_graphics(self, new_image_ref):\n self.image_ref = new_image_ref\n self.init_graphics()","def setImages( self, event_key, images ):\n print \"event index\",event_key[0]\n self.run = event_key[1]\n self.subrun = event_key[2]\n self.event_num = event_key[3]\n print self.run,self.subrun,self.event_num\n self.images = images\n #print self.images.img_v\n #for img in self.images.img_v:\n # print img.shape\n self.labeltools.setImage( event_key[0], self.images )","def manage_image_cache(self, context, all_instances):\n self.image_cache_manager.update(context, all_instances)","def update(self):\n \n for track in self.tracks:\n track.update()","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 preview(self):\n win_name = 'RTSP'\n cv2.namedWindow(win_name, cv2.WINDOW_AUTOSIZE)\n cv2.moveWindow(win_name,20,20)\n self.open()\n while(self.isOpened()):\n cv2.imshow(win_name,self._stream.read()[1])\n #if self._latest is not None:\n # cv2.imshow(win_name,self._latest)\n if cv2.waitKey(25) & 0xFF == ord('q'):\n break\n cv2.waitKey()\n cv2.destroyAllWindows()\n cv2.waitKey()","def populateImagesList(self):\n \n self._gui_server.getImagesList(self._populateImagesList)","def displayImg(self):\r\n\r\n\t# If you want to skip n frames, set value to 0 to see all images\r\n\tSKIP = 4500\r\n for idx in range(len(self.centers)):\r\n\t if idx < SKIP:\r\n\t\tcontinue\r\n file_left = self.lefts[idx][5]\r\n file_center = self.centers[idx][5]\r\n file_right = self.rights[idx][5]\r\n\r\n img_left = cv2.imread(os.path.join(self.pathDir, file_left), \\\r\n cv2.IMREAD_COLOR)\r\n img_center = cv2.imread(os.path.join(self.pathDir, file_center), \\\r\n cv2.IMREAD_COLOR)\r\n img_right = cv2.imread(os.path.join(self.pathDir, file_right), \\\r\n cv2.IMREAD_COLOR)\r\n\r\n\t #Resize the image to 50%\r\n img_l = cv2.resize(img_left, None, fx=0.5, fy=0.5, \\\r\n interpolation = cv2.INTER_LINEAR)\r\n img_c = cv2.resize(img_center, None, fx=0.5, fy=0.5, \\\r\n interpolation = cv2.INTER_LINEAR)\r\n img_r = cv2.resize(img_right, None, fx=0.5, fy=0.5, \\\r\n interpolation = cv2.INTER_LINEAR)\r\n \r\n height, width = img_c.shape[:2]\r\n new_img = np.zeros((height, width*3, img_c.shape[2]),\r\n np.uint8)\r\n\r\n #Adding sequence numbers and Time\r\n\t #Left\r\n strTime = self.timestampToStr(self.lefts[idx][1])\r\n\t self.putTextToImg(img_l, self.lefts[idx][0], strTime, height)\r\n\t #Center\r\n\t strTime = self.timestampToStr(self.centers[idx][1])\r\n\t self.putTextToImg(img_c, self.centers[idx][0], strTime, height)\r\n\t #Right\r\n\t strTime = self.timestampToStr(self.rights[idx][1])\r\n\t self.putTextToImg(img_r, self.rights[idx][0], strTime, height)\r\n\t \r\n\t angle = float(self.angles_at_timestamps[idx])\r\n\t speed = float(self.speed_at_timestamps[idx])\r\n\r\n\t print \"speed: %f - angle: %f\" % (speed, angle)\r\n\r\n\t self.draw_path_on(img_c, speed, angle)\r\n\r\n\t #Generate the new image\r\n for i in range(height):\r\n new_img[i] = np.concatenate((img_l[i, : ], img_c[i, : ], \\\r\n img_r[i, : ]))\r\n \r\n\r\n cv2.imshow('Udacity Challenge 2 - Viewer', new_img)\r\n key = cv2.waitKey(30)\r\n\r\n # Press q to exit\r\n if key == ord('q'):\r\n break\r\n\r\n cv2.destroyAllWindows()","def showSnapshots(self):\n from .utils import sp\n s = self.getSnapshots()\n ax = sp(len(s))\n for i, S in enumerate(s):\n ax[i].imshow(S)","def __videoThread(self):\n\n self.frameList = []\n\n fpsTimer = FpsTimer(self.fps)\n printf(\"Starting videoStream thread.\")\n while self.running:\n fpsTimer.wait()\n if not fpsTimer.ready(): continue\n if self.setCamera is not None: self.__setNewCamera(self.setCamera)\n if self.paused: continue\n if self.cap is None: continue\n\n\n # Get a new frame\n ret, newFrame = self.cap.read()\n\n if not ret: # If a frame was not successfully returned\n printf(\"ERROR: while reading frame from Cam. Setting camera again...\")\n self.__setNewCamera(self.cameraID)\n cv2.waitKey(1000)\n continue\n\n\n # Do frame related work\n with self.frameLock:\n self.frame = newFrame\n\n # Add a frame to the frameList that records the 5 latest frames for Vision uses\n self.frameList.insert(0, self.frame.copy())\n # print(\"len\", len(self.frameList), \"Curr frames: \", [id(frame) for frame in self.frameList])\n while len(self.frameList) > 10:\n del self.frameList[-1]\n\n # Keep track of new frames by counting them. (100 is an arbitrary number)\n if self.frameCount >= 100:\n self.frameCount = 0\n else:\n self.frameCount += 1\n\n\n # Run any work functions that must be run. Expect no results. Work should be run before filters.\n if len(self.workList) > 0:\n # print(\"Work: \", self.workList)\n with self.workLock:\n for workFunc in self.workList:\n workFunc(self.frame)\n\n\n\n # Run any filters that must be run, save the results in self.filterFrame\n if len(self.filterList) > 0:\n # print(\"Filters: \", self.filterList)\n with self.filterLock:\n filterFrame = self.getFrame()\n for filterFunc in self.filterList:\n filterFrame = filterFunc(filterFrame)\n\n # Draw FPS on the screen\n fps = str(int(round(fpsTimer.currentFPS, 0)))\n cv2.putText(filterFrame, fps, (10, 20), cv2.FONT_HERSHEY_PLAIN, 1.25, (255, 255, 255), 2)\n\n self.filterFrame = filterFrame\n\n\n else:\n self.filterFrame = self.frame\n\n printf(\"VideoStream Thread has ended\")","def setPhoto(self, index):\n\n # Indicate that an image is being loaded.\n self.image_loading_busy = True\n\n image = self.frames.frames_mono(index)\n\n super(VideoFrameSelector, self).setPhoto(image,\n overlay_exclude_mark=not self.index_included[index])","def update(i):\n print(\"{}/{}\".format(i, len(embs[query])))\n ims[0].set_data(unnorm(frames[query][i]))\n ims[1].set_data(unnorm(frames[candidate][nns[i]]))\n plt.tight_layout()","def image_cb(self, msg):\n self.has_image = True\n self.camera_image_msg = msg","def updateImageGroups(self):\n self.img_grps = self.splitImages()\n grps = self.img_grps\n self.detail.clear()\n detail = \"Available Groups : \\n\"\n if len(grps) >= 1:\n for i in range(len(grps)):\n detail += \"Group \"+ str(i+1)+ \" : \" + str(grps[i][0]) + \" ... \" + str(grps[i][-1]) + '\\n'\n\n self.detail.insertPlainText(detail)\n self.detail.moveCursor(QTextCursor.End)","def _visualize_numpy_video(vid):\r\n\r\n plt.axis('off')\r\n\r\n num_frames = vid.shape[0]\r\n img = plt.imshow(vid[0])\r\n\r\n for i in range(1, num_frames):\r\n img.set_data(vid[i])\r\n plt.pause(1.0 / 25.0)\r\n\r\n plt.show()","def run(self):\n self.run_tasks()\n self.images = np.array(self.images)\n self.shapes.extend(self.images.shape[-2:])\n\n self.images = np.reshape(self.images, self.shapes)","def on_image_change(self, value):\n self.current_image.setImage( self._model.image )","def run(self):\n\n for file_cnt, file_path in enumerate(self.files_found):\n video_timer = SimbaTimer()\n video_timer.start_timer()\n _, self.video_name, _ = get_fn_ext(file_path)\n self.video_info, self.px_per_mm, self.fps = self.read_video_info(\n video_name=self.video_name\n )\n self.width, self.height = int(\n self.video_info[\"Resolution_width\"].values[0]\n ), int(self.video_info[\"Resolution_height\"].values[0])\n if self.video_setting:\n self.fourcc = cv2.VideoWriter_fourcc(*Formats.MP4_CODEC.value)\n self.video_save_path = os.path.join(\n self.heatmap_clf_location_dir, self.video_name + \".mp4\"\n )\n self.writer = cv2.VideoWriter(\n self.video_save_path,\n self.fourcc,\n self.fps,\n (self.width, self.height),\n )\n if self.frame_setting:\n self.save_video_folder = os.path.join(\n self.heatmap_clf_location_dir, self.video_name\n )\n if not os.path.exists(self.save_video_folder):\n os.makedirs(self.save_video_folder)\n self.data_df = read_df(file_path=file_path, file_type=self.file_type)\n clf_array, aspect_ratio = self.__calculate_bin_attr(\n data_df=self.data_df,\n clf_name=self.clf_name,\n bp_lst=self.bp_lst,\n px_per_mm=self.px_per_mm,\n img_width=self.width,\n img_height=self.height,\n bin_size=self.bin_size,\n fps=self.fps,\n )\n\n if self.max_scale == \"auto\":\n self.max_scale = self.__calculate_max_scale(clf_array=clf_array)\n if self.max_scale == 0:\n self.max_scale = 1\n\n if self.final_img_setting:\n self.make_clf_heatmap_plot(\n frm_data=clf_array[-1, :, :],\n max_scale=self.max_scale,\n palette=self.palette,\n aspect_ratio=aspect_ratio,\n file_name=os.path.join(\n self.heatmap_clf_location_dir,\n self.video_name + \"_final_frm.png\",\n ),\n shading=self.shading,\n clf_name=self.clf_name,\n img_size=(self.width, self.height),\n final_img=True,\n )\n\n if self.video_setting or self.frame_setting:\n for frm_cnt, cumulative_frm_idx in enumerate(range(clf_array.shape[0])):\n frm_data = clf_array[cumulative_frm_idx, :, :]\n cum_df = pd.DataFrame(frm_data).reset_index()\n cum_df = cum_df.melt(\n id_vars=\"index\",\n value_vars=None,\n var_name=None,\n value_name=\"seconds\",\n col_level=None,\n ).rename(\n columns={\"index\": \"vertical_idx\", \"variable\": \"horizontal_idx\"}\n )\n cum_df[\"color\"] = (\n (cum_df[\"seconds\"].astype(float) / float(self.max_scale))\n .round(2)\n .clip(upper=100)\n )\n color_array = np.zeros(\n (\n len(cum_df[\"vertical_idx\"].unique()),\n len(cum_df[\"horizontal_idx\"].unique()),\n )\n )\n for i in range(color_array.shape[0]):\n for j in range(color_array.shape[1]):\n value = cum_df[\"color\"][\n (cum_df[\"horizontal_idx\"] == j)\n & (cum_df[\"vertical_idx\"] == i)\n ].values[0]\n color_array[i, j] = value\n\n fig = plt.figure()\n im_ratio = color_array.shape[0] / color_array.shape[1]\n plt.pcolormesh(\n color_array,\n shading=self.shading,\n cmap=self.palette,\n rasterized=True,\n alpha=1,\n vmin=0.0,\n vmax=float(self.max_scale),\n )\n plt.gca().invert_yaxis()\n plt.xticks([])\n plt.yticks([])\n plt.axis(\"off\")\n plt.tick_params(axis=\"both\", which=\"both\", length=0)\n cb = plt.colorbar(pad=0.0, fraction=0.023 * im_ratio)\n cb.ax.tick_params(size=0)\n cb.outline.set_visible(False)\n cb.set_label(\n \"{} (seconds)\".format(self.clf_name), rotation=270, labelpad=10\n )\n plt.tight_layout()\n plt.gca().set_aspect(aspect_ratio)\n canvas = FigureCanvas(fig)\n canvas.draw()\n mat = np.array(canvas.renderer._renderer)\n image = cv2.cvtColor(mat, cv2.COLOR_RGB2BGR)\n image = cv2.resize(image, (self.width, self.height))\n image = np.uint8(image)\n plt.close()\n\n if self.video_setting:\n self.writer.write(image)\n if self.frame_setting:\n frame_save_path = os.path.join(\n self.save_video_folder, str(frm_cnt) + \".png\"\n )\n cv2.imwrite(frame_save_path, image)\n print(\n \"Created heatmap frame: {} / {}. Video: {} ({}/{})\".format(\n str(frm_cnt + 1),\n str(len(self.data_df)),\n self.video_name,\n str(file_cnt + 1),\n len(self.files_found),\n )\n )\n\n if self.video_setting:\n self.writer.release()\n\n video_timer.stop_timer()\n print(\n \"Heatmap plot for video {} saved (elapsed time: {}s) ... \".format(\n self.video_name, video_timer.elapsed_time_str\n )\n )\n\n self.timer.stop_timer()\n stdout_success(\n msg=\"All heatmap visualizations created in project_folder/frames/output/heatmaps_classifier_locations directory\",\n elapsed_time=\"self.timer.elapsed_time_str\",\n )","def current_image_changed(self, value):\n\n if (self._current_image_index != self._ui.imageFileNavigatorView.currentIndex()):\n self.all_models.current_id = self._file_table_model._filelist[self._ui.imageFileNavigatorView.currentIndex()]\n self._current_image_index = self._ui.imageFileNavigatorView.currentIndex()\n self._main_controller.update_models_from_file_table(self._file_table_model._data[self._current_image_index])\n #self._model.image_scale = float(self._file_table_model._data[self._current_image_index][3])\n self._ui.segmentationMaskFileDisplay.setText(self._model.segmentation_label)","def update(self):\n if self.imageprocessor is None:\n return\n\n processedlist = self.imageprocessor.get_results(self.currentLotImage)\n if not processedlist: # no parking spots outlined\n return\n\n for spot in processedlist:\n self.getSingleSpot(spot[0]).status = spot[1].lower()","def __update_image(self, image_msg: Image):\n self.image = self.bridge.imgmsg_to_cv2(image_msg, desired_encoding='rgb8')\n\n if self.__listener != None:\n self.__listener(self.image,image_msg.header.stamp)","def run(self):\n while not self.is_stop():\n content = self.render()\n fid, frame = content['fid'], content['container_frame']\n\n if not self.is_pause():\n # Send request\n request = { 'action': 'detect' }\n self.send(request)\n\n # Send raw frames to workers\n video_frames = []\n for panel in self.panel_to_channel.keys():\n media_frame = panel.media_cache\n media_frame = cv2.resize(media_frame, self.trans_resolution)\n frame_bytes = cv2.imencode('.jpg', media_frame)[1]\n video_frames.append({ 'panel': panel, 'frame_bytes': frame_bytes })\n self.parallel_send_videos(video_frames)\n\n # Catch response from remote worker\n response = self.recv()\n if response is None:\n break\n\n # Handle server response\n handler = self.event_handler[response['action']]\n new_content = handler(response)\n fid, frame = new_content['fid'], new_content['container_frame']\n last_frame = frame\n\n # Show applications\n cv2.imshow(self.winname, frame)\n cv2.setTrackbarPos(self.barname, self.winname, fid)\n\n # Handling keyboard events\n key = cv2.waitKey(1) & 0xff\n self.keyboaord_handler(key)\n\n cv2.destroyAllWindows()","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 render(self, window):\r\n # Update images\r\n for i in self.images:\r\n i.undraw()\r\n\r\n if self.alive == False:\r\n self.images[3].draw(window)\r\n elif self.scared == True:\r\n self.images[2].draw(window)\r\n elif self.a == True:\r\n self.images[0].draw(window)\r\n elif self.a == False:\r\n self.images[1].draw(window)\r\n\r\n # Move images\r\n toX = (self.boundingBox.pos.getX() - (self.images[0].getAnchor().getX() - 20))\r\n toY = (self.boundingBox.pos.getY() - (self.images[0].getAnchor().getY() - 20))\r\n\r\n for i in self.images:\r\n i.move(toX, toY)","def update_image_all_projects(self):\n projects = Project.objects.all(temporary=False)\n for project in projects:\n project.update_image()","def pause_update(self):\n try:\n self._base_inst.sigImageChanged.disconnect()\n except AttributeError:\n pass","def update_elements(self):\n \n if self.gallery != 'http://null':\n result = urlfetch.fetch(self.gallery)\n if result.status_code == 200:\n #BREAKPOINT()\n self.resolved_gallery = self.unpick_rss(result)\n self.put()","def parse():\n all_players = list(FACE_IMAGE_LOCATIONS.keys())\n face_encodings = VideoParser.__load_faces_encodings(all_players)\n player_occurrences = VideoParser.__get_player_occurrences(all_players, face_encodings)\n VideoParser.__save_parsed_video(player_occurrences)"],"string":"[\n \"def update(self):\\n print('VIDEO: Video Stream started')\\n while True:\\n if self.stopped:\\n return\\n (self.grabbed, self.frame) = self.stream.read()\",\n \"def viewUpdate(self):\\n # Update Capture\\n imgtk = self.model.capture\\n self.updateImage(self.view.lmain, imgtk)\\n # Update Stitch \\n imgtk = self.model.stitch\\n self.updateImage(self.view.rmain, imgtk)\\n self.view.dist.set(self.model.dist)\",\n \"def refresh(self):\\r\\n # todo, use vid_info as property instead of this\\r\\n # reset properties and rebuild streams\\r\\n self.setup()\",\n \"def update(self):\\n self.frame = self.video_stream.read()\",\n \"def update(self, frame = None):\\n if type(frame) == type(None):\\n frame = self.video.get_frame()\\n height, width, channel = frame.shape\\n bytesPerLine = 3 * width\\n image = QImage(frame.data, width, height, bytesPerLine, QImage.Format_RGB888)\\n self.pixmap = QtGui.QPixmap(image)\\n size = self.size()\\n scaledPix = self.pixmap.scaled(size, Qt.KeepAspectRatio, transformMode = Qt.FastTransformation)\\n self.setPixmap(scaledPix)\\n\\n QtCore.QCoreApplication.processEvents()\",\n \"def update_image(self, cv_img):\\n qt_img = self.convert_cv_qt(cv_img)\\n self.camera_feed.setPixmap(qt_img)\",\n \"def video_loop(self):\\n if not self.isReplay:\\n if self.initStream:\\n print('[SB Live] Starting live video stream...')\\n self.replayStream.release()\\n self.vs.open(0)\\n self.initStream = False\\n print('[SB Live] Live video stream started')\\n if self.cClear:\\n self.cache.release()\\n os.remove('sblive/cache/replay.mov')\\n self.cache.open('sblive/cache/replay.mov', self.fourcc, 10.0, (1280, 720))\\n self.cClear = False\\n ok, frame = self.vs.read() # read frame from video stream\\n if ok: # frame captured without any errors\\n key = cv2.waitKey(1)\\n cv2image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA) # convert colors from BGR to RGBA\\n self.cache.write(frame)\\n self.current_image = Image.fromarray(cv2image) # convert image for PIL\\n imgtk = ImageTk.PhotoImage(image=self.current_image) # convert image for tkinter\\n \\n self.panel.imgtk = imgtk # anchor imgtk so it does not be deleted by garbage-collector\\n self.panel.config(image=imgtk) # show the image\\n else:\\n if self.initStream:\\n print('[SB Live] Starting replay video stream...')\\n self.cache.release()\\n self.vs.release()\\n self.replayStream.open('sblive/cache/replay.mov')\\n self.initStream = False\\n print('[SB Live] Replay video stream started')\\n ok, frame = self.replayStream.read()\\n if ok:\\n key = cv2.waitKey(1)\\n cv2image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA) # convert colors from BGR to RGBA\\n self.current_image = Image.fromarray(cv2image) # convert image for PIL\\n imgtk = ImageTk.PhotoImage(image=self.current_image) # convert image for tkinter\\n \\n self.panel.imgtk = imgtk # anchor imgtk so it does not be deleted by garbage-collector\\n self.panel.config(image=imgtk) # show the image\\n else:\\n self.replayStream.release()\\n self.replayStream.open('sblive/cache/replay.mov')\\n if not self.killThread:\\n self.root.after(30, self.video_loop) # call the same function after 30 milliseconds\",\n \"def updateImages(self, msg, arg2=None):\\n\\t\\tself.picPaths = msg\\n\\t\\tself.totalPictures = len(self.picPaths)\\n\\t\\tself.loadImage(self.picPaths[0])\",\n \"def update_display(self):\\n \\n # check availability of display queue of the wide camera\\n# if not hasattr(self,'wide_disp_queue'):\\n# pass\\n# elif self.wide_disp_queue.empty():\\n# pass\\n# else:\\n# try:\\n# wide_disp_image = self.wide_disp_queue.get()\\n# \\n# self.wide_disp_counter += 1\\n# self.wide_disp_counter %= 2\\n# if self.wide_disp_counter == 0:\\n# if type(wide_disp_image) == np.ndarray:\\n# if wide_disp_image.shape == (self.wide_cam.settings.height.value(),self.wide_cam.settings.width.value()):\\n# try:\\n# self.wide_cam_image.setImage(wide_disp_image)\\n# except Exception as ex:\\n# print('Error: %s' % ex)\\n# except Exception as ex:\\n# print(\\\"Error: %s\\\" % ex)\\n \\n # check availability of display queue of the track camera \\n if not hasattr(self,'track_disp_queue'):\\n pass\\n elif self.track_disp_queue.empty():\\n pass\\n else:\\n try:\\n track_disp_image = self.track_disp_queue.get()\\n self.track_disp_counter += 1\\n self.track_disp_counter %= 4\\n if self.track_disp_counter == 0:\\n if type(track_disp_image) == np.ndarray:\\n if track_disp_image.shape == (self.track_cam.settings.height.value(),self.track_cam.settings.width.value()):\\n try:\\n self.track_cam_image.setImage(track_disp_image)\\n except Exception as ex:\\n print('Error: %s' % ex)\\n \\n x = int(self.settings.x.value())\\n y = int(self.settings.y.value())\\n self.tracker_data[:] = 0\\n self.tracker_data[x,y] = 1\\n self.tracker_image.setImage(np.copy(self.tracker_data))\\n except Exception as ex:\\n print(\\\"Error: %s\\\" % ex)\",\n \"def update_imgs(self):\\n\\n for b in self.gamebuttons:\\n b.update_img()\\n self.start_but.update_img()\",\n \"def update_visuals(self):\\n\\n result, data = self.dev.grab_pipe()\\n if not result:\\n log.critical(\\\"Problem grabbing pipe\\\")\\n\\n if self.live_updates == True:\\n self.update_graph(data)\\n self.curve_render += 1\\n self.update_image(data)\\n self.check_image(self.curve_render)\\n\\n self.update_fps()\\n self.data_timer.start(0)\",\n \"def setVidFrame(self, ori_images):\\n self.cleanThread()\\n if ori_images == 0:\\n logging.critical(\\\"Video Image number 0\\\")\\n else:\\n self.buildRunDictMain(ori_images)\",\n \"def update_image(self):\\n self.image = Image.fromarray(self.img)\",\n \"def update(self):\\n while not self.stopped:\\n time.sleep(0.01)\\n self.grab_image()\",\n \"def video_loop(self):\\n\\n _, img = self.vs.read()\\n img = imutils.resize(img, width=self.width)\\n image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\\n image = Image.fromarray(image)\\n image = ImageTk.PhotoImage(image)\\n self.frame.configure(image=image)\\n self.frame.photo = image\\n\\n self.top.after(self.fps, self.video_loop)\",\n \"def show_images(processed_video, unprocessed_video, arraylength, isFirst, levels, calculating_boarder, fps):\\n processed_video = upsample_images(processed_video, unprocessed_video, arraylength, levels)\\n if not isFirst:\\n processed_video = processed_video[-calculating_boarder:]\\n for image in processed_video:\\n time.sleep(1/fps)\\n cv2.imshow(\\\"colour changes pulse\\\", image)\\n if cv2.waitKey(1) & 0xFF == ord('q'):\\n break\",\n \"def update_image(self, cv_img):\\n qt_img = self.convert_cv_qt(cv_img)\\n if(self.iscapture):\\n print(\\\"update\\\")\\n direct = self.label1.text()\\n if direct == \\\"~default\\\":\\n direct = \\\"face_dataframes\\\"\\n else:\\n direct = direct + \\\"/face_dataframes\\\"\\n \\n if (not os.path.exists(direct)):\\n os.mkdir(direct)\\n cv2.imwrite(\\\"{1}/{2}{0}.jpeg\\\".format(self.count, direct,self.textbox.text()), cv_img)\\n self.iscapture = False\\n self.label2.setText(\\\"Image # 0{0} Saved\\\".format(self.count))\\n self.pushButton0.setEnabled(False)\\n self.count += 1\\n \\n \\n if(self.count == 6):\\n #print(\\\"greater\\\")\\n self.pushButton.setEnabled(False)\\n self.pushButton2.setDisabled(False)\\n\\n\\n self.image_label.setPixmap(qt_img)\",\n \"def update_image(self, cv_img):\\n\\t\\tqt_img = self.ImageEdits(cv_img)\\n\\t\\tself.camera.setPixmap(qt_img)\",\n \"def update(self):\\n cv2.imshow(self.window_name, self.map.get_crop())\",\n \"def updateDisplay(self):\\n if self._displayPjt:\\n self._displayPjt.updateim()\\n if self._displayUsr:\\n self._displayUsr.updateim()\\n if self._displayVtk:\\n self._displayVtk.updateim()\",\n \"def run(self):\\n\\n im = None\\n while im == None:\\n im = self.vid_mem_reader.get_latest_image()\\n if im == None:\\n print \\\"not receiving images yet...\\\"\\n time.sleep(0.2)\\n\\n #Wait for video source to be ready:\\n #TODO: Shoud use vidmemreader, but this one never seem to return a resolution (at time of writing):\\n #res = self.vid_mem_reader.get_resolution()\\n \\n #TODO: This should work, but it doesn't because OpenCV keeps on complaining about that im is not a IPL image \\n #(while if you print it, it seems to be a IPL image).\\n #print im\\n size = cv.GetSize(im[0])\\n #print size\\n self.res = ({'width':size[0], 'height':size[1]})\\n res = self.res\\n\\n self.transformer = util.speed_angle.SpeedAngle(None, res['width'], res['height'])\\n \\n while True:\\n self.__ticker.tick()\\n start_time = time.time()\\n img = self.get_new_image()\\n ''' Parallel Process Inside this module\\n \\n im = np.asarray(img[:,:])\\n time_spent = time.time() - start_time\\n \\n #Parallel process\\n \\n self.parallel_rotate_image(im)\\n self.logger.debug(\\\"Set one finished\\\")\\n \\n print \\\"Image Length: \\\", self.rotatedImages\\n for img in self.rotatedImages:\\n self.get_faces(img[0])\\n self.update()\\n \\n self.rotatedImages = []\\n '''\\n im = np.asarray(img[:,:])\\n \\n image = self.rotate_image( im, [self.rotation])\\n self.get_faces(image)\\n self.update()\\n\\n #TODO: To be removed and or configurable:\\n directory = \\\"/tmp/emergency/\\\"\\n if not os.path.exists(directory):\\n os.makedirs(directory) \\n try:\\n cv.SaveImage(directory + \\\"image.png\\\", image)\\n except:\\n print \\\"ERROR: Could not write image to /tmp/emergency/\\\"\",\n \"def update_image(self, cv_img):\\n\\t\\tqt_img = self.convert_cv_qt(cv_img)\\n\\t\\tself.label.setPixmap(qt_img)\\n\\t\\tself.display_info()\",\n \"def update_cap_image(self):\\n\\n fn = self._get_cap_filename()\\n try:\\n im = PIL.Image.open(fn)\\n except FileNotFoundError:\\n return\\n\\n frame = np.array(im)\\n\\n \\\"\\\"\\\"\\n frame = cv2.imread(fn, cv2.IMREAD_ANYDEPTH)\\n if (frame is None):\\n return\\n \\\"\\\"\\\"\\n\\n frame = (frame >> (16 - self.camera.pixel_bits)).astype(np.uint16)\\n\\n ndx = self.dpar.cur_cap\\n\\n if self.dpar.cap_live_swap:\\n pix, gray = self._get_pixmap(frame, self.dpar.iwindow[ndx])\\n self.live_screen.live_title = self._cap_title(ndx)\\n self.live_screen.setPixmap(pix)\\n else:\\n pix, gray = self._get_pixmap(frame[::4,::4], self.dpar.iwindow[ndx])\\n self.cap_screen.cap_title = self._cap_title(ndx)\\n self.cap_screen.setPixmap(pix)\\n self.cap_screen.format_for_cap() # This is because first time, format is for \\\"no stills\\\".\",\n \"def update_image(self, surface):\\n self.ui_widget.update_image(surface=surface)\",\n \"def run(self):\\n \\n count = 0\\n while True:\\n self.__ticker.tick()\\n\\n self.update()\\n img = self.get_new_image()\\n if img == None:\\n print \\\"not receiving images yet...\\\"\\n else:\\n if self.verbose:\\n cv.ShowImage(\\\"SnapShotSaver\\\", img)\\n cv.WaitKey(10)\\n cv.SaveImage(\\\"%s/%s_%d.png\\\" % (self.destination, self.prefix, count), img)\\n count += 1\",\n \"def update_image(self, cv_img):\\n \\n qt_img = self.convert_cv_qt(cv_img)\\n self.image_label.setPixmap(qt_img)\\n #pass\",\n \"def update_image(self):\\n if self.filenames:\\n pos = self.slider.value()\\n proj, flat, dark, theta = dx.read_aps_32id(self.filenames, proj=(pos, pos+1))\\n if self.ffc_correction:\\n image = proj[0,:,:].astype(np.float)/flat[0,:,:].astype(np.float)\\n else:\\n image = proj[0,:,:].astype(np.float)\\n self.image_item.setImage(image)\",\n \"def update_image(self, cv_img):\\n qt_img = self.convert_cv_qt(cv_img)\\n self.image_label.setPixmap(qt_img)\",\n \"def update_image(self, cv_img):\\n qt_img = self.convert_cv_qt(cv_img)\\n self.image_label.setPixmap(qt_img)\",\n \"def _update_frame(self):\\n # check if continue\\n if self._keep_updating:\\n self.__frame = self._cam.get_display_frame()\\n if self.__frame is not None:\\n self._cvn_camera_viewfinder.create_image(0, 0, image=self.__frame, anchor=tk.NW)\\n\\n self._root.after(self._delay, self._update_frame)\",\n \"def update(self):\\r\\n while True:\\r\\n # if the thread indicator variable is set, stop the thread\\r\\n if self.stopped:\\r\\n self.webcam.release()\\r\\n return\\r\\n # otherwise, read the next frame from the webcam stream\\r\\n grabbed, frame = self.webcam.read()\\r\\n '''if self.cam_zoom:\\r\\n frame = self.zoom(frame)'''\\r\\n with self.read_lock:\\r\\n self.grabbed = grabbed\\r\\n try:\\r\\n #self.frame = cv2.resize(frame, (self.width, self.height))\\r\\n self.frame = frame\\r\\n except:\\r\\n None\",\n \"def refreshImages(self):\\n fileName1 = \\\"DECK/\\\" + str(self.card1) + \\\".gif\\\"\\n fileName2 = \\\"DECK/\\\" + str(self.card2) + \\\".gif\\\"\\n fileName3 = \\\"DECK/\\\" + str('b') + \\\".gif\\\"\\n self.image1 = PhotoImage(file = fileName1)\\n self.cardLabel1[\\\"image\\\"] = self.image1\\n self.image2 = PhotoImage(file = fileName2)\\n self.cardLabel2[\\\"image\\\"] = self.image2\\n self.image3 = PhotoImage(file = fileName3)\\n self.cardLabel3[\\\"image\\\"] = self.image3\",\n \"def update_display(self):\\n self.lick_plot_0.setData(self.k+self.T,self.buffer[:,1]) \\n self.lick_plot_1.setData(self.k+self.T,self.buffer[:,2]) \\n self.breathing_plot.setData(self.k+self.T,self.buffer[:,0]) \\n \\n if self.settings.movie_on.value():\\n self.camera_image.setImage(self.camera.read())\\n if self.settings.save_movie.value():\\n self.camera.write()\\n \\n #print(self.buffer_h5.size)\",\n \"def update_img(self):\\n self.img = np.array(self.image)\",\n \"def update_image(self):\\n if self.filenames:\\n pos = self.slider.value()\\n image = read_tiff(self.filenames[pos])\\n self.image_item.setImage(image)\",\n \"def update_image(self, cv_img):\\n qt_img = self.convert_cv_qt(cv_img)\\n self.label.setPixmap(qt_img)\",\n \"def update_current_image(self):\\n\\n rect = (0, 0, self.variables.canvas_width, self.variables.canvas_height)\\n if self.variables.canvas_image_object is not None:\\n self.variables.canvas_image_object.update_canvas_display_image_from_canvas_rect(rect)\\n self.set_image_from_numpy_array(self.variables.canvas_image_object.display_image)\\n self.update()\",\n \"def update_image(self, cv_img):\\n self.updated_temp_goal_image = cv_img\\n qt_img = self.convert_cv_qt(cv_img)\\n self.image_label.setPixmap(qt_img)\",\n \"def update_image(self):\\n if self.first is None or self.second is None:\\n LOG.warn(\\\"No images set yet\\\")\\n else:\\n pos = self.slider.value()\\n moved = np.roll(self.second, self.second.shape[0] / 2 - pos, axis=0)\\n self.image_item.setImage(moved - self.first)\",\n \"def update_image(self, img):\\r\\n qt_img = self.convert_cv_qt(img)\\r\\n self.main.caption_feed.setPixmap(qt_img)\",\n \"def update_movie(self, file_name):\\n try:\\n pix = QPixmap(file_name)\\n self.cur_imageRect['width'] = pix.width()\\n self.cur_imageRect['height'] = pix.height()\\n if self.isFullScreen():\\n width = self.screen_width\\n height = self.screen_height\\n padding_left = 0\\n padding_top = 0\\n else:\\n width = 1000\\n height = 450\\n padding_left = 40\\n padding_top = 50\\n scale = min(width / pix.width(), height / pix.height())\\n self.video_label.setGeometry(padding_left, padding_top, pix.width() * scale, pix.height() * scale)\\n self.video_label.clear()\\n self.video_label.setPixmap(pix)\\n except:\\n pass\\n os.remove(file_name)\",\n \"def update(self):\\n self.imagecounter +=1\\n if self.imagecounter > 7:\\n self.imagecounter = 0\\n self.image = pygame.image.load(self.pictures[self.imagecounter])\\n self.rect = self.image.get_rect()\\n self.rect.left = self.x\\n self.rect.top = self.y\",\n \"def updateScreen(self):\\n\\t\\ttry:\\n\\t\\t\\tfile1 = open(self.imageFile, \\\"rb\\\")\\n\\t\\texcept:\\n\\t\\t\\ttkMessageBox.showerror('Play', '\\\"' + self.imageFile + '\\\" could not be played.')\\n\\t\\t\\texit()\\n\\n\\t\\t# Reset event variables for tracking playing/paused/stopped states\\n\\t\\tself.pauseEvent.clear()\\n\\t\\tself.stopEvent.clear()\\n\\n\\t\\tcounter = 0\\n\\t\\twhile 1:\\n\\t\\t\\tval = file1.read(5) # Read the next 5 byte header\\n\\t\\t\\tif val == '': # End of video file has been reached\\n\\t\\t\\t\\tself.stopEvent.set() # Playback has finished\\n\\t\\t\\t\\ttkMessageBox.showinfo(\\\"Play\\\", \\\"Playback has finished.\\\")\\n\\t\\t\\t\\tfile1.close()\\n\\t\\t\\t\\texit()\\n\\t\\t\\tdata = file1.read(int(val)) # Read the current JPEG image\\n\\t\\t\\tcounter += 1\\n\\t\\t\\ttemp_file_name = str(counter) + \\\".jpeg\\\"\\n\\t\\t\\tfile2 = open(temp_file_name, \\\"wb\\\")\\n\\t\\t\\tfile2.write(data)\\n\\t\\t\\tfile2.close()\\n\\t\\t\\ttime.sleep(0.035)\\n\\t\\t\\tphoto = ImageTk.PhotoImage(Image.open(temp_file_name))\\n\\t\\t\\tself.label.configure(image = photo, height=288)\\n\\t\\t\\tself.label.image = photo\\n\\t\\t\\tos.remove(temp_file_name) # Comment out this line if you want the extracted JPEG images to remain on disk after playback finishes.\\n\\t\\t\\twhile self.pauseEvent.isSet(): # Pause playback until an Exit, Resume or Stop command is issued\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t# Case where an Exit or Stop command is issued whilst playback has been paused\\n\\t\\t\\t\\tif self.stopEvent.isSet():\\n\\t\\t\\t\\t\\tfile1.close()\\n\\t\\t\\t\\t\\tself.quitEvent.clear() # Inform the main thread that it may proceed to close the Pirate GUI window.\\n\\t\\t\\t\\t\\texit() # Kill the playback thread only\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tpass # Keep looping\\n\\t\\t\\t\\n\\t\\t\\t# Case where an Stop command is issued during playback\\n\\t\\t\\tif self.stopEvent.isSet():\\n\\t\\t\\t\\tfile1.close()\\n\\t\\t\\t\\tself.quitEvent.clear() # Inform the main thread that it may proceed to close the Pirate GUI window.\\n\\t\\t\\t\\texit() # Kill the playback thread only\",\n \"def update(self):\\r\\n for f in self.stream:\\r\\n # if the thread indicator variable is set, stop the thread\\r\\n # and release camera resources\\r\\n if self.stopped:\\r\\n self.stream.close()\\r\\n self.rawCapture.close()\\r\\n self.camera.close()\\r\\n return\\r\\n # grab the frame from the stream and clear the stream in\\r\\n # preparation for the next frame\\r\\n frame = f.array\\r\\n self.rawCapture.truncate(0)\\r\\n with self.read_lock:\\r\\n self.frame = frame\",\n \"def update(self):\\n while not rospy.is_shutdown():\\n self.calculate_frame()\\n for callback in self.callbacks:\\n callback(self.keypoints, self.image)\",\n \"def reload_image(self):\\n img = self.img_manager.update_image()\\n\\n q_image = PyQt5.QtGui.QImage.fromData(img.read())\\n q_pixmap = PyQt5.QtGui.QPixmap.fromImage(q_image)\\n\\n self.image_widget.setPixmap(q_pixmap)\",\n \"def update(self):\\n # Get frame from video source:\\n ret, frame = self.vid.read()\\n\\n if ret:\\n # Convert the captured frame into grayscale\\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\\n gray = cv2.equalizeHist(gray)\\n\\n # Get all faces from the video frame\\n faces = self.faceCascade.detectMultiScale(gray, 1.2,5)\\n\\n # For each face in faces\\n for (x, y, w, h) in faces:\\n # Create rectangle around the face\\n cv2.rectangle(frame, (x-20,y-20), (x+w+20,y+h+20), (0,255,0), 4)\\n\\n # Recognize the face belongs to which ID\\n Id = self.recognizer.predict(gray[y:y+h,x:x+w])\\n\\n ### IDENTIFICATION & SOCKET CODE GOES HERE\\n if Id[0] == self.user_id:\\n # If the target face is found 10 times then access is granted\\n self.identification_count += 1\\n if self.identification_count > 10:\\n self.master.switch_frame(AccessGranted)\\n\\n name_to_put = self.user_name\\n else:\\n name_to_put = \\\"Unknown - Access Denied\\\"\\n\\n # Put text describe who is in the picture\\n cv2.rectangle(frame, (x-22,y-90), (x+w+22, y-22), (0,255,0), -1)\\n cv2.putText(frame, str(name_to_put), (x,y-40), self.font, 2, (255,255,255), 3)\\n\\n self.after(50, self.update)\",\n \"def display_images():\\n vc = cv2.VideoCapture(0) # Open webcam\\n figure, ax = plt.subplots(1, 2, figsize=(10, 5)) # Intiialise plot\\n\\n count = 0 # Counter for number of aquired frames\\n intensity = [] # Append intensity across time\\n\\n # For loop over generator here\\n intensity.append(imageintensity)\\n plot_image_and_brightness() # Call plot function\\n count += 1\\n\\n # This triggers exit sequences when user presses q\\n if cv2.waitKey(1) & 0xFF == ord('q'):\\n # Clean up here\\n plt.close('all') # close plots\\n generator.close() # Use generator exit for clean up,\\n break # break loop\",\n \"def show(self):\\n if self.video:\\n self.video.write(self.img)\\n cv2.imshow('Simpy', self.img)\\n cv2.waitKey(1000 // self.fps)\",\n \"def prepare_images(self):\\n\\n qt_original_image = self.convert_image_to_QTformat(self.original_image)\\n self.send_original_photo_to_gui.emit(qt_original_image)\\n\\n self.processed_image = self.procces_image(self.original_image)\\n qt_processed_image = self.convert_image_to_QTformat(self.processed_image)\\n self.send_processed_photo_to_gui.emit(qt_processed_image)\",\n \"def update(self):\\n self.moving_sprites.update() \\n self.static_sprites.update()\\n self.camera.update(self.player)\",\n \"def _update(self):\\n self.cv.update()\",\n \"def updateMovie(self, imageFile):\\r\\n\\t\\tframe = ImageTk.PhotoImage(Image.open(imageFile))\\r\\n\\t\\tself.label.configure(image=frame, height=300)\\r\\n\\t\\tself.label.image = frame\",\n \"def display_video_stream(self):\\n\\n t = time.time()\\n\\n frame = self.video_stream.read()\\n # frame = self.capture.read()[1]\\n\\n frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\\n frame = cv2.flip(frame, 1)\\n\\n qimage = array2qimage(frame)\\n\\n # image = QImage(frame, frame.shape[1], frame.shape[0], # faster, but potentially causes memory leak?\\n # frame.strides[0], QImage.Format_RGB888)\\n self._webcam_stream_qlabel.setPixmap(QPixmap.fromImage(qimage))\\n self._webcam_stream_qlabel.update()\\n\\n if MainApp.PRINT_CAM_LATENCY:\\n print(\\\"\\\\r{:.2}\\\".format(time.time()-t), end='')\",\n \"def update_frame(self):\\n if not self.image_queue: return\\n image = self.image_queue.pop()\\n self.image_queue.rotate(-1)\\n self.original_image = image\\n self.altered_image = image.copy()\\n\\n if self.tracking:\\n self.update_frame_tracking()\\n self.display_image(True)\\n elif self.calibrating:\\n self.update_frame_calibrating()\\n self.display_image(True)\\n else:\\n image = cv2.flip(self.altered_image, 1)\\n self.display_image(True)\",\n \"def _update_screen(self) -> None:\\n # setup the source image with an alpha channel\\n alpha = 255 * np.ones_like(self.image[..., 0:1])\\n image = np.concatenate([self._image, alpha], axis=-1).astype(np.uint8)\\n # setup the super pixel segmentations\\n super_pixels = np.zeros_like(self.image)\\n super_pixels = mark_boundaries(\\n super_pixels,\\n self._super_pixel_segments,\\n self._super_pixel_color\\n )\\n # concatenate the first channel of sup as the alpha channel\\n super_pixels = [super_pixels, super_pixels[..., 0:1]]\\n super_pixels = np.concatenate(super_pixels, axis=-1).astype(np.uint8)\\n # setup the segmentation image with an alpha channel scaled by the\\n # opacity parameter of the application [0, 9]\\n intensity = 255 * (self._opacity / 9)\\n intensity = intensity * np.ones_like(self._segmentation[..., 0:1])\\n segmentation = np.concatenate([self._segmentation, intensity], axis=-1)\\n segmentation = segmentation.astype(np.uint8)\\n # send the images to the window\\n self._view.show([image, segmentation, super_pixels])\",\n \"def displayImages(self):\\n\\n plt.figure(figsize=(8,6))\\n plt.subplot(1,2,1)\\n plt.imshow( self.original_image, cmap=\\\"gray\\\")\\n plt.title(\\\"Original Image\\\")\\n plt.subplot(1,2,2)\\n plt.imshow( self.blurred_image, cmap=\\\"gray\\\")\\n plt.title(\\\"Blurred Image\\\")\",\n \"def _update_images(self, axis=None, draw=True):\\n self._update_base_images(axis=axis)\\n if draw:\\n self._draw(axis)\",\n \"def _image(self):\\n print(\\\"imaging\\\")\\n self.images.append(self.device_control.image())\\n yield\",\n \"def update_image(self, image):\\n raise NotImplementedError()\",\n \"def __video_loop(self):\\n # Keep looping over frames until we are instructed to stop\\n while not self.__quit.is_set():\\n # Get the correct frame\\n self.__frame = self.__detect.frame\\n if self.__frame is None:\\n continue\\n\\n # Convert BGR color to RGB and\\n # make it to pillow format\\n image = cv2.cvtColor(self.__frame, cv2.COLOR_BGR2RGB)\\n image = Image.fromarray(image)\\n image = ImageTk.PhotoImage(image)\\n\\n # If the panel is not None, initialize it\\n if self.__panel is None:\\n self.__panel = tk.Label(image=image)\\n self.__panel.image = image\\n self.__panel.grid(row=0,\\n column=0,\\n rowspan=4,\\n padx=10,\\n pady=10)\\n else: # Otherwise, simply update the panel\\n self.__panel.configure(image=image)\\n self.__panel.image = image\\n\\n # Output the detected categories\\n text = \\\"\\\"\\n for name, count in self.__detect.categories.items():\\n text = f\\\"{name}: {count}\\\\n\\\"\\n self.__info_label.configure(text=text)\",\n \"def _update_(self,update_background=True):\\n # -- Make sure the fundamental update (if any) are made\\n super(Image,self)._update_()\\n # - Data\\n self._update_data_(update_background=update_background)\",\n \"def update_image(self):\\n modified_since = (\\n dict(modified__gt=self.image_updated) if self.image_updated else {}\\n )\\n if self.image_path and self.image_path != \\\"__uploaded__\\\":\\n # Does the file need updating?\\n images = self.files.filter(\\n current=True, path=self.image_path, **modified_since\\n ).order_by(\\\"-modified\\\")\\n if len(images) > 0:\\n self.set_image_from_file(images[0])\\n else:\\n # Try to find an image for the project and use the most\\n # recently modified since the image was last updated\\n images = self.files.filter(\\n current=True, mimetype__startswith=\\\"image/\\\", **modified_since,\\n ).order_by(\\\"-modified\\\")\\n if len(images) > 0:\\n self.set_image_from_file(images[0])\",\n \"def let_camera_update_parameters(path_to_images, name_image, video_source=\\\"/dev/video0\\\"):\\n subprocess_cmd(\\\"ffmpeg -f video4linux2 -s 1280x720 -i {} -ss 00:00:02 -frames 1 ./{}/{} -loglevel error -nostats\\\".format(video_source, path_to_images, name_image))\",\n \"def update(self):\\n if self.mudpi.is_prepared:\\n if self.duration > self.delay.total_seconds():\\n if self.record_video:\\n self.capture_recording(duration=self.record_duration)\\n else:\\n self.capture_image()\\n self.reset_duration()\",\n \"def update(self) -> None:\\n self.all_sprites.update()\",\n \"def image_cb(self, msg):\\n self.has_image = True\\n self.camera_image = msg\",\n \"def update_image(self, data):\\n self.image_data.append(data)\\n if len(self.image_data) > self.image_height:\\n self.image_data = self.image_data[1:]\\n\\n self.image_render += 1\\n\\n # A 200 pixel tall image squashed into the render view does not\\n # appear unpleasantely jumpy when scrolled by 5\\n if self.image_render % 5 != 0 and self.image_render != 1:\\n return\\n\\n img_data = range(len(self.image_data))\\n\\n position = 0\\n while position < len(img_data):\\n img_data[position] = self.image_data[position]\\n position += 1\\n\\n new_data = numpy.array(img_data).astype(float)\\n\\n mid = self.main_image_dialog\\n mid.image.set_data(new_data)\\n\\n # If you do autoscale here, it tends to jump around in appearing\\n # to stretch to the window and be in 'normal' size\\n mid.get_plot().replot()\",\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 snapshot(self):\\n\\n if self.pj[OBSERVATIONS][self.observationId][TYPE] in [MEDIA]:\\n\\n if self.playerType == VLC:\\n\\n if self.playMode == FFMPEG:\\n\\n for idx, media in enumerate(self.pj[OBSERVATIONS][self.observationId][FILE][PLAYER1]):\\n if self.FFmpegGlobalFrame < sum(self.duration[0:idx + 1]):\\n\\n p = pathlib.Path(media)\\n snapshotFilePath = str(p.parent / \\\"{}_{}.png\\\".format(p.stem, self.FFmpegGlobalFrame))\\n\\n if self.detachFrameViewer or self.second_player():\\n self.frame_viewer1.lbFrame.pixmap().save(snapshotFilePath)\\n elif not self.detachFrameViewer:\\n self.lbFFmpeg.pixmap().save(snapshotFilePath)\\n self.statusbar.showMessage(\\\"Snapshot player #1 saved in {}\\\".format(snapshotFilePath), 0)\\n break\\n\\n if self.second_player():\\n for idx, media in enumerate(self.pj[OBSERVATIONS][self.observationId][FILE][PLAYER2]):\\n if self.FFmpegGlobalFrame2 < sum(self.duration2[0:idx + 1]):\\n p = pathlib.Path(media)\\n snapshotFilePath = str(p.parent / \\\"{}_{}.png\\\".format(p.stem, self.FFmpegGlobalFrame2))\\n\\n self.frame_viewer2.lbFrame.pixmap().save(snapshotFilePath)\\n self.statusbar.showMessage(\\\"Snapshot player #2 saved in {}\\\".format(snapshotFilePath), 0)\\n break\\n\\n else: # VLC\\n\\n current_media_path = url2path(self.mediaplayer.get_media().get_mrl())\\n # TODO: replace with pathlib\\n dirName, fileName = os.path.split(current_media_path)\\n self.mediaplayer.video_take_snapshot(0, \\\"{dirName}{sep}{fileNameWOExt}_{time}.png\\\".format(\\n dirName=dirName,\\n sep=os.sep,\\n fileNameWOExt=os.path.splitext(fileName)[0],\\n time=self.mediaplayer.get_time()),\\n 0, 0)\\n\\n # check if multi mode\\n # second video together\\n if self.simultaneousMedia:\\n current_media_path = url2path(self.mediaplayer2.get_media().get_mrl())\\n\\n dirName, fileName = os.path.split(current_media_path)\\n self.mediaplayer2.video_take_snapshot(0, \\\"{dirName}{sep}{fileNameWOExt}_{time}.png\\\".format(\\n dirName=dirName,\\n sep=os.sep,\\n fileNameWOExt=os.path.splitext(fileName)[0],\\n time=self.mediaplayer2.get_time()),\\n 0, 0)\",\n \"def display(self):\\n\\t\\tself.imgDisplay.set_from_pixbuf(self.getVisible())\\n\\t\\tgc.collect()\",\n \"def run(self):\\n\\n # capture from web cam\\n cap = cv2.VideoCapture(self.gstreamer_pipeline(), cv2.CAP_GSTREAMER)\\n while self._run_flag:\\n ret, cv_img = cap.read()\\n if ret:\\n self.change_pixmap_signal.emit(cv_img)\\n # shut down capture system\\n cap.release()\",\n \"def update_graphics(self, new_image_ref):\\n self.image_ref = new_image_ref\\n self.init_graphics()\",\n \"def setImages( self, event_key, images ):\\n print \\\"event index\\\",event_key[0]\\n self.run = event_key[1]\\n self.subrun = event_key[2]\\n self.event_num = event_key[3]\\n print self.run,self.subrun,self.event_num\\n self.images = images\\n #print self.images.img_v\\n #for img in self.images.img_v:\\n # print img.shape\\n self.labeltools.setImage( event_key[0], self.images )\",\n \"def manage_image_cache(self, context, all_instances):\\n self.image_cache_manager.update(context, all_instances)\",\n \"def update(self):\\n \\n for track in self.tracks:\\n track.update()\",\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 preview(self):\\n win_name = 'RTSP'\\n cv2.namedWindow(win_name, cv2.WINDOW_AUTOSIZE)\\n cv2.moveWindow(win_name,20,20)\\n self.open()\\n while(self.isOpened()):\\n cv2.imshow(win_name,self._stream.read()[1])\\n #if self._latest is not None:\\n # cv2.imshow(win_name,self._latest)\\n if cv2.waitKey(25) & 0xFF == ord('q'):\\n break\\n cv2.waitKey()\\n cv2.destroyAllWindows()\\n cv2.waitKey()\",\n \"def populateImagesList(self):\\n \\n self._gui_server.getImagesList(self._populateImagesList)\",\n \"def displayImg(self):\\r\\n\\r\\n\\t# If you want to skip n frames, set value to 0 to see all images\\r\\n\\tSKIP = 4500\\r\\n for idx in range(len(self.centers)):\\r\\n\\t if idx < SKIP:\\r\\n\\t\\tcontinue\\r\\n file_left = self.lefts[idx][5]\\r\\n file_center = self.centers[idx][5]\\r\\n file_right = self.rights[idx][5]\\r\\n\\r\\n img_left = cv2.imread(os.path.join(self.pathDir, file_left), \\\\\\r\\n cv2.IMREAD_COLOR)\\r\\n img_center = cv2.imread(os.path.join(self.pathDir, file_center), \\\\\\r\\n cv2.IMREAD_COLOR)\\r\\n img_right = cv2.imread(os.path.join(self.pathDir, file_right), \\\\\\r\\n cv2.IMREAD_COLOR)\\r\\n\\r\\n\\t #Resize the image to 50%\\r\\n img_l = cv2.resize(img_left, None, fx=0.5, fy=0.5, \\\\\\r\\n interpolation = cv2.INTER_LINEAR)\\r\\n img_c = cv2.resize(img_center, None, fx=0.5, fy=0.5, \\\\\\r\\n interpolation = cv2.INTER_LINEAR)\\r\\n img_r = cv2.resize(img_right, None, fx=0.5, fy=0.5, \\\\\\r\\n interpolation = cv2.INTER_LINEAR)\\r\\n \\r\\n height, width = img_c.shape[:2]\\r\\n new_img = np.zeros((height, width*3, img_c.shape[2]),\\r\\n np.uint8)\\r\\n\\r\\n #Adding sequence numbers and Time\\r\\n\\t #Left\\r\\n strTime = self.timestampToStr(self.lefts[idx][1])\\r\\n\\t self.putTextToImg(img_l, self.lefts[idx][0], strTime, height)\\r\\n\\t #Center\\r\\n\\t strTime = self.timestampToStr(self.centers[idx][1])\\r\\n\\t self.putTextToImg(img_c, self.centers[idx][0], strTime, height)\\r\\n\\t #Right\\r\\n\\t strTime = self.timestampToStr(self.rights[idx][1])\\r\\n\\t self.putTextToImg(img_r, self.rights[idx][0], strTime, height)\\r\\n\\t \\r\\n\\t angle = float(self.angles_at_timestamps[idx])\\r\\n\\t speed = float(self.speed_at_timestamps[idx])\\r\\n\\r\\n\\t print \\\"speed: %f - angle: %f\\\" % (speed, angle)\\r\\n\\r\\n\\t self.draw_path_on(img_c, speed, angle)\\r\\n\\r\\n\\t #Generate the new image\\r\\n for i in range(height):\\r\\n new_img[i] = np.concatenate((img_l[i, : ], img_c[i, : ], \\\\\\r\\n img_r[i, : ]))\\r\\n \\r\\n\\r\\n cv2.imshow('Udacity Challenge 2 - Viewer', new_img)\\r\\n key = cv2.waitKey(30)\\r\\n\\r\\n # Press q to exit\\r\\n if key == ord('q'):\\r\\n break\\r\\n\\r\\n cv2.destroyAllWindows()\",\n \"def showSnapshots(self):\\n from .utils import sp\\n s = self.getSnapshots()\\n ax = sp(len(s))\\n for i, S in enumerate(s):\\n ax[i].imshow(S)\",\n \"def __videoThread(self):\\n\\n self.frameList = []\\n\\n fpsTimer = FpsTimer(self.fps)\\n printf(\\\"Starting videoStream thread.\\\")\\n while self.running:\\n fpsTimer.wait()\\n if not fpsTimer.ready(): continue\\n if self.setCamera is not None: self.__setNewCamera(self.setCamera)\\n if self.paused: continue\\n if self.cap is None: continue\\n\\n\\n # Get a new frame\\n ret, newFrame = self.cap.read()\\n\\n if not ret: # If a frame was not successfully returned\\n printf(\\\"ERROR: while reading frame from Cam. Setting camera again...\\\")\\n self.__setNewCamera(self.cameraID)\\n cv2.waitKey(1000)\\n continue\\n\\n\\n # Do frame related work\\n with self.frameLock:\\n self.frame = newFrame\\n\\n # Add a frame to the frameList that records the 5 latest frames for Vision uses\\n self.frameList.insert(0, self.frame.copy())\\n # print(\\\"len\\\", len(self.frameList), \\\"Curr frames: \\\", [id(frame) for frame in self.frameList])\\n while len(self.frameList) > 10:\\n del self.frameList[-1]\\n\\n # Keep track of new frames by counting them. (100 is an arbitrary number)\\n if self.frameCount >= 100:\\n self.frameCount = 0\\n else:\\n self.frameCount += 1\\n\\n\\n # Run any work functions that must be run. Expect no results. Work should be run before filters.\\n if len(self.workList) > 0:\\n # print(\\\"Work: \\\", self.workList)\\n with self.workLock:\\n for workFunc in self.workList:\\n workFunc(self.frame)\\n\\n\\n\\n # Run any filters that must be run, save the results in self.filterFrame\\n if len(self.filterList) > 0:\\n # print(\\\"Filters: \\\", self.filterList)\\n with self.filterLock:\\n filterFrame = self.getFrame()\\n for filterFunc in self.filterList:\\n filterFrame = filterFunc(filterFrame)\\n\\n # Draw FPS on the screen\\n fps = str(int(round(fpsTimer.currentFPS, 0)))\\n cv2.putText(filterFrame, fps, (10, 20), cv2.FONT_HERSHEY_PLAIN, 1.25, (255, 255, 255), 2)\\n\\n self.filterFrame = filterFrame\\n\\n\\n else:\\n self.filterFrame = self.frame\\n\\n printf(\\\"VideoStream Thread has ended\\\")\",\n \"def setPhoto(self, index):\\n\\n # Indicate that an image is being loaded.\\n self.image_loading_busy = True\\n\\n image = self.frames.frames_mono(index)\\n\\n super(VideoFrameSelector, self).setPhoto(image,\\n overlay_exclude_mark=not self.index_included[index])\",\n \"def update(i):\\n print(\\\"{}/{}\\\".format(i, len(embs[query])))\\n ims[0].set_data(unnorm(frames[query][i]))\\n ims[1].set_data(unnorm(frames[candidate][nns[i]]))\\n plt.tight_layout()\",\n \"def image_cb(self, msg):\\n self.has_image = True\\n self.camera_image_msg = msg\",\n \"def updateImageGroups(self):\\n self.img_grps = self.splitImages()\\n grps = self.img_grps\\n self.detail.clear()\\n detail = \\\"Available Groups : \\\\n\\\"\\n if len(grps) >= 1:\\n for i in range(len(grps)):\\n detail += \\\"Group \\\"+ str(i+1)+ \\\" : \\\" + str(grps[i][0]) + \\\" ... \\\" + str(grps[i][-1]) + '\\\\n'\\n\\n self.detail.insertPlainText(detail)\\n self.detail.moveCursor(QTextCursor.End)\",\n \"def _visualize_numpy_video(vid):\\r\\n\\r\\n plt.axis('off')\\r\\n\\r\\n num_frames = vid.shape[0]\\r\\n img = plt.imshow(vid[0])\\r\\n\\r\\n for i in range(1, num_frames):\\r\\n img.set_data(vid[i])\\r\\n plt.pause(1.0 / 25.0)\\r\\n\\r\\n plt.show()\",\n \"def run(self):\\n self.run_tasks()\\n self.images = np.array(self.images)\\n self.shapes.extend(self.images.shape[-2:])\\n\\n self.images = np.reshape(self.images, self.shapes)\",\n \"def on_image_change(self, value):\\n self.current_image.setImage( self._model.image )\",\n \"def run(self):\\n\\n for file_cnt, file_path in enumerate(self.files_found):\\n video_timer = SimbaTimer()\\n video_timer.start_timer()\\n _, self.video_name, _ = get_fn_ext(file_path)\\n self.video_info, self.px_per_mm, self.fps = self.read_video_info(\\n video_name=self.video_name\\n )\\n self.width, self.height = int(\\n self.video_info[\\\"Resolution_width\\\"].values[0]\\n ), int(self.video_info[\\\"Resolution_height\\\"].values[0])\\n if self.video_setting:\\n self.fourcc = cv2.VideoWriter_fourcc(*Formats.MP4_CODEC.value)\\n self.video_save_path = os.path.join(\\n self.heatmap_clf_location_dir, self.video_name + \\\".mp4\\\"\\n )\\n self.writer = cv2.VideoWriter(\\n self.video_save_path,\\n self.fourcc,\\n self.fps,\\n (self.width, self.height),\\n )\\n if self.frame_setting:\\n self.save_video_folder = os.path.join(\\n self.heatmap_clf_location_dir, self.video_name\\n )\\n if not os.path.exists(self.save_video_folder):\\n os.makedirs(self.save_video_folder)\\n self.data_df = read_df(file_path=file_path, file_type=self.file_type)\\n clf_array, aspect_ratio = self.__calculate_bin_attr(\\n data_df=self.data_df,\\n clf_name=self.clf_name,\\n bp_lst=self.bp_lst,\\n px_per_mm=self.px_per_mm,\\n img_width=self.width,\\n img_height=self.height,\\n bin_size=self.bin_size,\\n fps=self.fps,\\n )\\n\\n if self.max_scale == \\\"auto\\\":\\n self.max_scale = self.__calculate_max_scale(clf_array=clf_array)\\n if self.max_scale == 0:\\n self.max_scale = 1\\n\\n if self.final_img_setting:\\n self.make_clf_heatmap_plot(\\n frm_data=clf_array[-1, :, :],\\n max_scale=self.max_scale,\\n palette=self.palette,\\n aspect_ratio=aspect_ratio,\\n file_name=os.path.join(\\n self.heatmap_clf_location_dir,\\n self.video_name + \\\"_final_frm.png\\\",\\n ),\\n shading=self.shading,\\n clf_name=self.clf_name,\\n img_size=(self.width, self.height),\\n final_img=True,\\n )\\n\\n if self.video_setting or self.frame_setting:\\n for frm_cnt, cumulative_frm_idx in enumerate(range(clf_array.shape[0])):\\n frm_data = clf_array[cumulative_frm_idx, :, :]\\n cum_df = pd.DataFrame(frm_data).reset_index()\\n cum_df = cum_df.melt(\\n id_vars=\\\"index\\\",\\n value_vars=None,\\n var_name=None,\\n value_name=\\\"seconds\\\",\\n col_level=None,\\n ).rename(\\n columns={\\\"index\\\": \\\"vertical_idx\\\", \\\"variable\\\": \\\"horizontal_idx\\\"}\\n )\\n cum_df[\\\"color\\\"] = (\\n (cum_df[\\\"seconds\\\"].astype(float) / float(self.max_scale))\\n .round(2)\\n .clip(upper=100)\\n )\\n color_array = np.zeros(\\n (\\n len(cum_df[\\\"vertical_idx\\\"].unique()),\\n len(cum_df[\\\"horizontal_idx\\\"].unique()),\\n )\\n )\\n for i in range(color_array.shape[0]):\\n for j in range(color_array.shape[1]):\\n value = cum_df[\\\"color\\\"][\\n (cum_df[\\\"horizontal_idx\\\"] == j)\\n & (cum_df[\\\"vertical_idx\\\"] == i)\\n ].values[0]\\n color_array[i, j] = value\\n\\n fig = plt.figure()\\n im_ratio = color_array.shape[0] / color_array.shape[1]\\n plt.pcolormesh(\\n color_array,\\n shading=self.shading,\\n cmap=self.palette,\\n rasterized=True,\\n alpha=1,\\n vmin=0.0,\\n vmax=float(self.max_scale),\\n )\\n plt.gca().invert_yaxis()\\n plt.xticks([])\\n plt.yticks([])\\n plt.axis(\\\"off\\\")\\n plt.tick_params(axis=\\\"both\\\", which=\\\"both\\\", length=0)\\n cb = plt.colorbar(pad=0.0, fraction=0.023 * im_ratio)\\n cb.ax.tick_params(size=0)\\n cb.outline.set_visible(False)\\n cb.set_label(\\n \\\"{} (seconds)\\\".format(self.clf_name), rotation=270, labelpad=10\\n )\\n plt.tight_layout()\\n plt.gca().set_aspect(aspect_ratio)\\n canvas = FigureCanvas(fig)\\n canvas.draw()\\n mat = np.array(canvas.renderer._renderer)\\n image = cv2.cvtColor(mat, cv2.COLOR_RGB2BGR)\\n image = cv2.resize(image, (self.width, self.height))\\n image = np.uint8(image)\\n plt.close()\\n\\n if self.video_setting:\\n self.writer.write(image)\\n if self.frame_setting:\\n frame_save_path = os.path.join(\\n self.save_video_folder, str(frm_cnt) + \\\".png\\\"\\n )\\n cv2.imwrite(frame_save_path, image)\\n print(\\n \\\"Created heatmap frame: {} / {}. Video: {} ({}/{})\\\".format(\\n str(frm_cnt + 1),\\n str(len(self.data_df)),\\n self.video_name,\\n str(file_cnt + 1),\\n len(self.files_found),\\n )\\n )\\n\\n if self.video_setting:\\n self.writer.release()\\n\\n video_timer.stop_timer()\\n print(\\n \\\"Heatmap plot for video {} saved (elapsed time: {}s) ... \\\".format(\\n self.video_name, video_timer.elapsed_time_str\\n )\\n )\\n\\n self.timer.stop_timer()\\n stdout_success(\\n msg=\\\"All heatmap visualizations created in project_folder/frames/output/heatmaps_classifier_locations directory\\\",\\n elapsed_time=\\\"self.timer.elapsed_time_str\\\",\\n )\",\n \"def current_image_changed(self, value):\\n\\n if (self._current_image_index != self._ui.imageFileNavigatorView.currentIndex()):\\n self.all_models.current_id = self._file_table_model._filelist[self._ui.imageFileNavigatorView.currentIndex()]\\n self._current_image_index = self._ui.imageFileNavigatorView.currentIndex()\\n self._main_controller.update_models_from_file_table(self._file_table_model._data[self._current_image_index])\\n #self._model.image_scale = float(self._file_table_model._data[self._current_image_index][3])\\n self._ui.segmentationMaskFileDisplay.setText(self._model.segmentation_label)\",\n \"def update(self):\\n if self.imageprocessor is None:\\n return\\n\\n processedlist = self.imageprocessor.get_results(self.currentLotImage)\\n if not processedlist: # no parking spots outlined\\n return\\n\\n for spot in processedlist:\\n self.getSingleSpot(spot[0]).status = spot[1].lower()\",\n \"def __update_image(self, image_msg: Image):\\n self.image = self.bridge.imgmsg_to_cv2(image_msg, desired_encoding='rgb8')\\n\\n if self.__listener != None:\\n self.__listener(self.image,image_msg.header.stamp)\",\n \"def run(self):\\n while not self.is_stop():\\n content = self.render()\\n fid, frame = content['fid'], content['container_frame']\\n\\n if not self.is_pause():\\n # Send request\\n request = { 'action': 'detect' }\\n self.send(request)\\n\\n # Send raw frames to workers\\n video_frames = []\\n for panel in self.panel_to_channel.keys():\\n media_frame = panel.media_cache\\n media_frame = cv2.resize(media_frame, self.trans_resolution)\\n frame_bytes = cv2.imencode('.jpg', media_frame)[1]\\n video_frames.append({ 'panel': panel, 'frame_bytes': frame_bytes })\\n self.parallel_send_videos(video_frames)\\n\\n # Catch response from remote worker\\n response = self.recv()\\n if response is None:\\n break\\n\\n # Handle server response\\n handler = self.event_handler[response['action']]\\n new_content = handler(response)\\n fid, frame = new_content['fid'], new_content['container_frame']\\n last_frame = frame\\n\\n # Show applications\\n cv2.imshow(self.winname, frame)\\n cv2.setTrackbarPos(self.barname, self.winname, fid)\\n\\n # Handling keyboard events\\n key = cv2.waitKey(1) & 0xff\\n self.keyboaord_handler(key)\\n\\n cv2.destroyAllWindows()\",\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 render(self, window):\\r\\n # Update images\\r\\n for i in self.images:\\r\\n i.undraw()\\r\\n\\r\\n if self.alive == False:\\r\\n self.images[3].draw(window)\\r\\n elif self.scared == True:\\r\\n self.images[2].draw(window)\\r\\n elif self.a == True:\\r\\n self.images[0].draw(window)\\r\\n elif self.a == False:\\r\\n self.images[1].draw(window)\\r\\n\\r\\n # Move images\\r\\n toX = (self.boundingBox.pos.getX() - (self.images[0].getAnchor().getX() - 20))\\r\\n toY = (self.boundingBox.pos.getY() - (self.images[0].getAnchor().getY() - 20))\\r\\n\\r\\n for i in self.images:\\r\\n i.move(toX, toY)\",\n \"def update_image_all_projects(self):\\n projects = Project.objects.all(temporary=False)\\n for project in projects:\\n project.update_image()\",\n \"def pause_update(self):\\n try:\\n self._base_inst.sigImageChanged.disconnect()\\n except AttributeError:\\n pass\",\n \"def update_elements(self):\\n \\n if self.gallery != 'http://null':\\n result = urlfetch.fetch(self.gallery)\\n if result.status_code == 200:\\n #BREAKPOINT()\\n self.resolved_gallery = self.unpick_rss(result)\\n self.put()\",\n \"def parse():\\n all_players = list(FACE_IMAGE_LOCATIONS.keys())\\n face_encodings = VideoParser.__load_faces_encodings(all_players)\\n player_occurrences = VideoParser.__get_player_occurrences(all_players, face_encodings)\\n VideoParser.__save_parsed_video(player_occurrences)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67444074","0.6730207","0.6720518","0.67168564","0.6591318","0.657772","0.6577194","0.64696455","0.6445771","0.64267576","0.64083344","0.6405238","0.6402562","0.6371376","0.6345765","0.63317454","0.62935567","0.62902534","0.6285674","0.6278713","0.62650186","0.626164","0.6199037","0.6198393","0.6190942","0.61784947","0.6167083","0.61226094","0.61226094","0.61217725","0.61159575","0.61052155","0.61004305","0.6075937","0.6044152","0.60433316","0.6030097","0.6029385","0.6006537","0.5993231","0.5985193","0.5973861","0.5955756","0.5955204","0.59497243","0.59042734","0.59024835","0.5899099","0.58803874","0.58696073","0.5867566","0.5864249","0.58424735","0.5838369","0.5837763","0.58349615","0.58245003","0.5808617","0.58073276","0.58035797","0.5800815","0.57917345","0.57829326","0.5763415","0.57525504","0.5747299","0.5740505","0.57331175","0.569173","0.5660525","0.5660058","0.5636037","0.56346923","0.56183857","0.5614729","0.56126267","0.561155","0.56010306","0.55915976","0.55867887","0.55847585","0.55742735","0.5572766","0.556064","0.55500835","0.55464447","0.55448264","0.5542821","0.5535527","0.5532402","0.55310196","0.55296963","0.5528102","0.55272186","0.5521286","0.5516842","0.5510081","0.5503591","0.54989","0.54985785"],"string":"[\n \"0.67444074\",\n \"0.6730207\",\n \"0.6720518\",\n \"0.67168564\",\n \"0.6591318\",\n \"0.657772\",\n \"0.6577194\",\n \"0.64696455\",\n \"0.6445771\",\n \"0.64267576\",\n \"0.64083344\",\n \"0.6405238\",\n \"0.6402562\",\n \"0.6371376\",\n \"0.6345765\",\n \"0.63317454\",\n \"0.62935567\",\n \"0.62902534\",\n \"0.6285674\",\n \"0.6278713\",\n \"0.62650186\",\n \"0.626164\",\n \"0.6199037\",\n \"0.6198393\",\n \"0.6190942\",\n \"0.61784947\",\n \"0.6167083\",\n \"0.61226094\",\n \"0.61226094\",\n \"0.61217725\",\n \"0.61159575\",\n \"0.61052155\",\n \"0.61004305\",\n \"0.6075937\",\n \"0.6044152\",\n \"0.60433316\",\n \"0.6030097\",\n \"0.6029385\",\n \"0.6006537\",\n \"0.5993231\",\n \"0.5985193\",\n \"0.5973861\",\n \"0.5955756\",\n \"0.5955204\",\n \"0.59497243\",\n \"0.59042734\",\n \"0.59024835\",\n \"0.5899099\",\n \"0.58803874\",\n \"0.58696073\",\n \"0.5867566\",\n \"0.5864249\",\n \"0.58424735\",\n \"0.5838369\",\n \"0.5837763\",\n \"0.58349615\",\n \"0.58245003\",\n \"0.5808617\",\n \"0.58073276\",\n \"0.58035797\",\n \"0.5800815\",\n \"0.57917345\",\n \"0.57829326\",\n \"0.5763415\",\n \"0.57525504\",\n \"0.5747299\",\n \"0.5740505\",\n \"0.57331175\",\n \"0.569173\",\n \"0.5660525\",\n \"0.5660058\",\n \"0.5636037\",\n \"0.56346923\",\n \"0.56183857\",\n \"0.5614729\",\n \"0.56126267\",\n \"0.561155\",\n \"0.56010306\",\n \"0.55915976\",\n \"0.55867887\",\n \"0.55847585\",\n \"0.55742735\",\n \"0.5572766\",\n \"0.556064\",\n \"0.55500835\",\n \"0.55464447\",\n \"0.55448264\",\n \"0.5542821\",\n \"0.5535527\",\n \"0.5532402\",\n \"0.55310196\",\n \"0.55296963\",\n \"0.5528102\",\n \"0.55272186\",\n \"0.5521286\",\n \"0.5516842\",\n \"0.5510081\",\n \"0.5503591\",\n \"0.54989\",\n \"0.54985785\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7045872"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":18681,"cells":{"query":{"kind":"string","value":"Update the vision choices when a new device is selected."},"document":{"kind":"string","value":"def updateDevice(self, *args):\r\n\r\n # Update the list of vision choices and the default vision choice\r\n self._appChoice[\"vision\"] = [choice[0] for choice in self._system[self._appString[\"device\"].get()]]\r\n self._appString[\"vision\"].set(self._appChoice[\"vision\"][0])\r\n\r\n # Delete the old choices fromt the option menu\r\n menu = self._appOption[\"vision\"][\"menu\"]\r\n menu.delete(0, \"end\")\r\n\r\n # Add the new list of choices to the option menu\r\n for string in self._appChoice[\"vision\"]:\r\n menu.add_command(label=string, command=lambda value=string: self._appString[\"vision\"].set(value))"},"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 updateVision(self, *args):\r\n\r\n # Update the list of frame choices and the default frame choice\r\n self._appChoice[\"frame\"] = [choice[0] for choice in self._system[self._appString[\"device\"].get()][self._appString[\"vision\"].get()]]\r\n self._appString[\"frame\"].set(self._appChoice[\"frame\"][0])\r\n\r\n # Delete the old choices fromt the option menu\r\n menu = self._appOption[\"frame\"][\"menu\"]\r\n menu.delete(0, \"end\")\r\n\r\n # Add the new list of choices to the option menu\r\n for string in self._appChoice[\"frame\"]:\r\n menu.add_command(label=string, command=lambda value=string: self._appString[\"frame\"].set(value))","def device_selected(self, uid):\n if uid == self.cur_uid:\n print \"Already Selected\"\n return\n # This line is going to return \"DEVICE_LABEL\" so you may as well skip it\n pid_key = \"DEVICE_LABEL\"\n self.dev_label.set(\"%s (%s)\"%(self._uid_dict[uid][pid_key][\"label\"], uid))\n self.ola_thread.rdm_get(self.universe.get(), uid, 0, \"IDENTIFY_DEVICE\", \n lambda b, s, uid = uid:self._get_identify_complete(uid, b, s))\n\n if \"SUPPORTED_PARAMETERS\" not in self._uid_dict[uid]:\n self.ola_thread.rdm_get(\n self.universe.get(), uid, 0, \"SUPPORTED_PARAMETERS\",\n lambda b, l, uid = uid:self._get_pids_complete(uid, b, l))\n else:\n self._notebook.Update()\n self.cur_uid = uid","def update_selection(self):\n raise NotImplementedError","def _selected_bridge_changed(self, new):\n if self.bridges[new] is None:\n bridge_desc_file = os.path.join(BRIDGES_PATH, new + u'.json')\n bridge = self.load_bridge_info(bridge_desc_file)\n self.bridges[new] = bridge\n\n self.bridge = self.bridges[new]\n self.channels = [channel for instrument in self.bridge.children\n for sensor in instrument.children\n for channel in sensor.children]","def set_choices(self):\n self.check_idxs()\n np.random.seed()\n self.choices = np.random.choice(self.running_idxs, self.num_selections)\n self.running_idxs = np.delete(self.running_idxs, self.choices)\n self.choices = torch.tensor(self.choices).cuda()","def setupDeviceGui(self):\n\n dropDowns = list(self.drivers[driver]['uiDriver'] for driver in self.drivers)\n for dropDown in dropDowns:\n dropDown.clear()\n dropDown.setView(PyQt5.QtWidgets.QListView())\n dropDown.addItem('No device selected')\n\n # adding special items\n self.drivers['dome']['uiDriver'].addItem('INDI')\n self.drivers['imaging']['uiDriver'].addItem('INDI')\n self.drivers['sensorWeather']['uiDriver'].addItem('INDI')\n self.drivers['directWeather']['uiDriver'].addItem('Built-In')\n self.drivers['onlineWeather']['uiDriver'].addItem('Built-In')\n self.drivers['cover']['uiDriver'].addItem('INDI')\n self.drivers['skymeter']['uiDriver'].addItem('INDI')\n self.drivers['telescope']['uiDriver'].addItem('INDI')\n self.drivers['power']['uiDriver'].addItem('INDI')\n self.drivers['relay']['uiDriver'].addItem('Built-In')\n for app in self.app.astrometry.solverAvailable:\n self.drivers['astrometry']['uiDriver'].addItem(app)\n self.drivers['remote']['uiDriver'].addItem('Built-In')\n self.drivers['measure']['uiDriver'].addItem('Built-In')\n\n return True","def select(self):\n if not self._selected:\n \tself._selected = True\n\t\tself.log(\"device {} is now selected\".format(self._secondary_address))","def vistrailChanged(self):\n from vistrails.gui.vistrails_window import _app\n select_node = True\n if _app._previous_view and _app._previous_view.window() != self.window():\n select_node = False\n self.scene().setupScene(self.controller, select_node)\n if self.controller and self.controller.reset_version_view:\n self.scene().fitToAllViews()\n if self.controller:\n # self.versionProp.updateVersion(self.controller.current_version)\n self.versionProp.updateVersion(self.controller.current_version)\n self.emit(QtCore.SIGNAL(\"vistrailChanged()\"))","def update_dev(self, *args):\r\n try:\r\n self.localSDK.get_version()\r\n except IOError:\r\n kT.debug_log('IO Error', sys.exc_info()[2])\r\n try:\r\n self.newProj.name = self.widgetList[3].get()\r\n except IndexError:\r\n kT.debug_log('Index Error', sys.exc_info()[2])\r\n self.newProj.setKsdkPath(self.localSDK.path)\r\n self.newProj.sdkVer = self.localSDK.version\r\n\r\n if self.advancedDevType.get():\r\n\r\n self.widgetList[34].state([\"!disabled\"])\r\n\r\n ### Widget 7 is the label for the device drop down menu\r\n self.widgetList[7].config(text='Board:')\r\n\r\n try:\r\n self.widgetList[31].config(command=lambda: self.begin_advanced_gen(self.master, None))\r\n except TclError:\r\n kT.debug_log('Tcl Error', sys.exc_info()[2])\r\n\r\n ### Widget 8 is te drop down menu for the devices\r\n self.widgetList[8].config(textvariable=self.advBrdSelect)\r\n self.widgetList[8]['values'] = self.localSDK.brdList\r\n try:\r\n self.widgetList[8].current(int(self.currBoard) - 1)\r\n except IOError: ## Catch the case where the user hasn't selected anything\r\n self.widgetList[8].current(0)\r\n except ValueError: ## Catch the case where there is no device given in manifest\r\n self.widgetList[8].current(0)\r\n else:\r\n try:\r\n self.widgetList[34].state([\"disabled\"])\r\n\r\n ### Widget 7 is the label for the device drop down menu\r\n self.widgetList[7].config(text='Device:')\r\n\r\n self.widgetList[31].config(command=lambda: self.package_select(self.master))\r\n\r\n ### Widget 8 is te drop down menu for the devices\r\n self.widgetList[8].config(textvariable=self.advDevSelect)\r\n self.widgetList[8]['values'] = self.localSDK.devList\r\n except IndexError:\r\n kT.debug_log('IndexError', sys.exc_info()[2])\r\n\r\n try:\r\n self.newProj.add_board(self.currBoard, self.localSDK.brdList)\r\n self.widgetList[8].current(self.localSDK.devList.index(self.newProj.device[0]))\r\n except IndexError:\r\n kT.debug_log('IndexError', sys.exc_info()[2])\r\n except IOError: ## Catch the case where the user hasn't selected anything\r\n try:\r\n self.widgetList[8].current(0)\r\n except IndexError:\r\n kT.debug_log('IndexError', sys.exc_info()[2])\r\n except ValueError: ## Catch the case where there is no device given in manifest\r\n try:\r\n self.widgetList[8].current(0)\r\n except IndexError:\r\n kT.debug_log('Index Error', sys.exc_info()[2])\r\n \r\n #FIXME Radka add special method for updating path \r\n self._update_project_path()","def _add_device(self, uid, succeeded, data):\n # TODO: Bug: on discover the label in the label in the device option menu \n # doesn't change and if you try to select the first device it tells \n # you that it is already selected\n if succeeded:\n self._uid_dict.setdefault(uid, {})[\"DEVICE_LABEL\"] = data\n self.device_menu[\"menu\"].add_command( label = \"%s (%s)\"%(\n self._uid_dict[uid][\"DEVICE_LABEL\"][\"label\"], uid), \n command = lambda:self.device_selected(uid))\n else:\n self._uid_dict.setdefault(uid, {})[\"DEVICE_LABEL\"] = {\"label\":\"\"}\n self.device_menu[\"menu\"].add_command( label = \"%s\" % uid, \n command = lambda:self.device_selected(uid))\n self._uid_dict[uid][\"index\"] = self.device_menu[\"menu\"].index(tk.END)","def state_chosen_do(cfg, app, win, events):","def img_dict_updated(self, change):\n if change[\"value\"]:\n self.select_dataset(self.io_model.img_dict_default_selected_item)\n self.init_plot_status()","def setupDeviceGui(self):\n\n # all dropdown have disabled as capability\n dropDowns = list(self.drivers[driver]['uiDropDown'] for driver in self.drivers)\n for dropDown in dropDowns:\n dropDown.clear()\n dropDown.setView(PyQt5.QtWidgets.QListView())\n dropDown.addItem('device disabled')\n\n # adding driver items with applicable framework\n for driver in self.drivers:\n if not hasattr(self.drivers[driver]['class'], 'run'):\n continue\n for framework in self.drivers[driver]['class'].run.keys():\n self.drivers[driver]['uiDropDown'].addItem(framework)\n\n return True","def update_selection(self):\n\n # clear all boxes\n self.clear_boxes()\n self.draw_figure(self.s)\n\n # update temperature list\n if self.Data[self.s]['T_or_MW'] == \"T\":\n self.temperatures = np.array(self.Data[self.s]['t_Arai']) - 273.\n else:\n self.temperatures = np.array(self.Data[self.s]['t_Arai'])\n\n self.T_list = [\"%.0f\" % T for T in self.temperatures]\n self.tmin_box.SetItems(self.T_list)\n self.tmax_box.SetItems(self.T_list)\n self.tmin_box.SetValue(\"\")\n self.tmax_box.SetValue(\"\")\n self.Blab_window.SetValue(\n \"%.0f\" % (float(self.Data[self.s]['pars']['lab_dc_field']) * 1e6))\n if \"saved\" in self.Data[self.s]['pars']:\n self.pars = self.Data[self.s]['pars']\n self.update_GUI_with_new_interpretation()\n self.Add_text(self.s)\n self.write_sample_box()","def update_view(self, selected):\n pass","def update_device_list(self, device_list):\n self.device_list = device_list\n\n self.device_combo.clear()\n\n if not device_list:\n return\n\n self.device_combo.addItem(\"\")\n\n active_entry = None\n\n for dev in device_list:\n\n action_string = \"{model:<18} - {contype:<7} - {serial}\".format(model=dev.model,\n contype=dev.device_type,\n serial=dev.serial)\n if dev.serial == self.serial:\n active_entry = action_string\n self.device_combo.addItem(action_string)\n\n if active_entry is not None:\n self.device_combo.setCurrentText(active_entry)","def _selected_labels_changed(self, name, old, new):\n if self.value_lock.acquire(False):\n try:\n self.value = [self._options_dict[name] for name in new]\n finally:\n self.value_lock.release()","def graphs_change():\n d = curdoc()\n _remove_fig(d)\n _remove_selection(d)\n graph_val = d.get_model_by_name(GRAPH_SELECTION).value\n model_id, message_name, model_type = run_handlers.get_modelid_messagename_type(d)\n props = run_handlers.get_model_properties(model_id, message_name, model_type)\n\n if graph_val in [\"line\", \"scatter\", \"step\"]:\n # never want to plot this special string field\n field_options = [\"{0} : {1}\".format(k, props[k]) for k in props if not any(apv in k for apv in [ APV_MODEL ] ) ]\n xselect = Select(title=\"X Axis\", value=DEFAULT_UNSELECTED, options=field_options + [DEFAULT_UNSELECTED], name=X_AXIS_SELECTION)\n yselect = Select(title=\"Y Axis\", value=DEFAULT_UNSELECTED, options=field_options + [DEFAULT_UNSELECTED], name=Y_AXIS_SELECTION)\n xselect.on_change('value', lambda attr, old, new: make_2axis_graph())\n yselect.on_change('value', lambda attr, old, new: make_2axis_graph())\n d.add_root(column(Div(text=\"\"), row(widgetbox([xselect]), widgetbox([yselect])), name=FIELD_SELECTION))\n\n if graph_val in [\"image\"]:\n # alter the field options for known non-image fields\n field_options = [\"{0} : {1}\".format(k, props[k]) for k in props if not any(apv in k for apv in [APV_RECVD, APV_SEQNO, APV_MODEL] ) ]\n imageselect = Select(title=\"Image Field\", value=DEFAULT_UNSELECTED, options=[DEFAULT_UNSELECTED] + field_options, name=IMAGE_SELECTION)\n mimeselect = Select(title=\"MIME Type\", value=DEFAULT_UNSELECTED, options=[DEFAULT_UNSELECTED] + SUPPORTED_MIME_TYPES, name=MIME_SELECTION)\n imageselect.on_change('value', lambda attr, old, new: image_selection_change())\n mimeselect.on_change('value', lambda attr, old, new: image_selection_change())\n d.add_root(column(Div(text=\"\"), widgetbox([imageselect, mimeselect]), name=IMAGE_MIME_SELECTION))\n\n if graph_val in [\"table\"]:\n # TODO: limit selectable columns to whose of the same size (table height)\n # use just the field name; don't show properties in the multi-select box\n col_options = [k for k in props if not any (apv in k for apv in [APV_RECVD, APV_SEQNO, APV_MODEL] ) ]\n columnmultiselect = MultiSelect(title=\"Columns:\", value=[], options=col_options, name=COLUMN_MULTISELECT)\n columnmultiselect.on_change('value', lambda attr, old, new: column_selection_change())\n d.add_root(column(Div(text=\"\"), widgetbox([columnmultiselect]), name=COLUMN_SELECTION))\n\n if graph_val in [\"raw\"]:\n p = figure(plot_width=500, plot_height=500,\n background_fill_color=\"white\",\n y_range=(-40, 0), title=\"\", name=FIGURE_MODEL)\n p.xaxis.visible = False\n p.yaxis.visible = False\n sind = run_handlers.get_source_index(d.session_context.id, model_id, message_name)\n _install_callback_and_cds(sind, model_id, message_name, stream_limit=1)\n p.text(x='apv_sequence_number',\n y=0,\n text='apv_model_as_string',\n source=d.get_model_by_name(sind),\n text_font_size=\"10pt\",\n text_line_height=0.7,\n text_baseline=\"top\",\n text_align=\"left\")\n p.x_range.follow = \"end\" # don't jam all the data into the graph; \"window\" it\n p.x_range.follow_interval = 1 # don't jam all the data into the graph; \"window\" it\n p.x_range.range_padding = 0\n d.add_root(p)","def updateAvailablePorts(self):\n # Build a port list\n device_list_all = comports()\n self.device_choices = list()\n for device in device_list_all:\n self.device_choices.append(device[0])\n\n if len(self.device_choices) < 1:\n tkinter.messagebox.showerror('No Available Serial Ports','No serial ports are available.')","def update(self):\n self.platform_list.update()\n self.enemy_list.update()","def on_change(self, attr, old, new):\n n = self.labels.index(new) + 1 # Select 0-indexed\n self.notify(set_figures(n))","def apply_changes(self, updated_talk=None):\r\n self.presentationModel.select()\r\n self.select_talk(updated_talk)\r\n self.update_autocomplete_fields()","def modelselec_change():\n d = curdoc()\n _remove_fig(d)\n _remove_selection(d)\n d.remove_root(d.get_model_by_name(AFTER_MODEL_SELECTION))\n modelselec = d.get_model_by_name(MODEL_SELECTION)\n msv = modelselec.value\n if msv != DEFAULT_UNSELECTED:\n model_id, message_name, model_type = run_handlers.get_modelid_messagename_type(d)\n if model_type == \"protobuf\":\n message = Select(title=\"Message Selection\", value=DEFAULT_UNSELECTED, options=list(data.proto_data_structure[model_id][\"messages\"].keys()) + [DEFAULT_UNSELECTED], name=MESSAGE_SELECTION)\n graphs = Select(title=\"Graph Selection\", value=DEFAULT_UNSELECTED, options=[], name=GRAPH_SELECTION)\n message.on_change('value', lambda attr, old, new: message_change())\n graphs.on_change('value', lambda attr, old, new: graphs_change())\n selec = row(widgetbox([message]), widgetbox([graphs]), name=AFTER_MODEL_SELECTION)\n else: # there is no message selection here\n graphs = Select(title=\"Graph Selection\", value=DEFAULT_UNSELECTED, options=GRAPH_OPTIONS, name=GRAPH_SELECTION)\n graphs.on_change('value', lambda attr, old, new: graphs_change())\n selec = row(widgetbox([graphs]), name=AFTER_MODEL_SELECTION)\n d.add_root(selec)\n d.add_root(selec)","def choose_devices(devices, query=False):\n # Style for selection interface\n style = style_from_dict({\n Token.Separator: '#FF00AA',\n Token.QuestionMark: '#00AAFF bold',\n Token.Selected: '#00AAFF', # default\n Token.Pointer: '#00FF00 bold',\n Token.Instruction: '#FFAA00', # default\n Token.Answer: '#00AAFF bold',\n Token.Question: '#FF00AA',\n })\n\n choice_list = []\n current_type = None\n name_len = max([len(dev.f_name) for dev in devices]) + 1\n\n if query:\n print('Querying all devices for version numbers. '\n 'This may take a minute...')\n choice_list.append(Separator('Name'.center(name_len)\n + 'Firmware'.center(15)\n + 'Core'.center(7) + 'State'))\n for device in devices:\n if device.type != current_type:\n current_type = device.type\n sep_str = ' {} '.format(current_type).center(name_len + 29, '=')\n choice_list.append(Separator(sep_str))\n menu_text = device.f_name.ljust(name_len)\n if query and device.software == 'tasmota':\n device.query_tas_status()\n if 'tas_version' in device.reported:\n menu_text += device.reported['tas_version'].ljust(15)\n menu_text += device.reported['core_version'].ljust(7)\n if device.reported['power'] is not None:\n menu_text += device.reported['power']\n else:\n menu_text += 'Offline'\n choice_list.append({'name': menu_text, 'value': device.f_name})\n\n # Ask the user to choose which devices to flash\n questions = [\n {\n 'type': 'checkbox',\n 'message': 'Select Devices',\n 'name': 'device_selection',\n 'choices': choice_list,\n }\n ]\n answers = prompt(questions, style=style)\n selected_devices = [device for device in devices if device.f_name \\\n in answers['device_selection']]\n return selected_devices","def _selectionChangedSlot(self, _):\r\n\r\n self._updateButtonStates()","def update(self):\n self.platform_list.update()\n #self.enemy_list.update()\n self.enemy_list.update()\n self.bullet_list.update()\n self.active_sprite_list.update()","def poll_selection(self):\r\n osName = platform.system()\r\n\r\n ## Check if the user changed the KSDK_path\r\n try:\r\n checkPath = self.widgetList[1].get()\r\n if checkPath != self.localSDK.path:\r\n self.ask_set_directory(True, 1)\r\n\r\n ## Check if user updated project name\r\n checkName = self.widgetList[4].get()\r\n if checkName != self.newProj.name:\r\n if kT.check_proj_name(checkName):\r\n self.newProj.name = checkName\r\n else:\r\n self.newProj.name = None\r\n if self.prevName != checkName:\r\n tkMessageBox.showinfo(\"Invalid Project Name\",\\\r\n \"No spaces or special characters.\")\r\n self.prevName = checkName\r\n kT.debug_log(\"Invalid name\")\r\n except AttributeError:\r\n kT.debug_log(\"Basic Changed menu\", sys.exc_info()[2])\r\n #return\r\n\r\n try:\r\n now = self.widgetList[6].curselection()\r\n if now != self.curr:\r\n if len(self.widgetList[6].curselection()) > 0:\r\n try:\r\n self.displayBoard = PhotoImage(data=self.imageList[int(now[0])])\r\n except IndexError:\r\n kT.debug_log(now[0], sys.exc_info()[2])\r\n self.widgetList[8].grid_remove()\r\n self.widgetList[8] = Button(self, \\\r\n image=self.displayBoard, \\\r\n command=lambda:\\\r\n self.web_launch(self.localSDK.brdList[\\\r\n int(self.widgetList[6].curselection()[0])]))\r\n self.widgetList[8].image = self.displayBoard\r\n self.widgetList[8].grid(row=5, column=3, columnspan=3, sticky=E+W+N+S)\r\n self.widgetList[8].bind(\"<Enter>\", \\\r\n lambda h: self.update_tips('Is this your board?\\n' + \\\r\n 'If so, ' + \\\r\n 'then clicking on the board' + \\\r\n ' image will take you to the ' + \\\r\n 'board homepage on ' + \\\r\n 'freescale.com.\\n\\n'))\r\n self.widgetList[8].bind(\"<Leave>\", \\\r\n lambda h: self.update_tips(self.defaultHelp))\r\n self.curr = now\r\n try:\r\n self.currBoard = int(self.widgetList[6].curselection()[0]) + 1\r\n # Clear out driver list and board\r\n self.newProj.board = ()\r\n self.newProj.drvList = []\r\n # Configure ksdkProj given GUI state\r\n self.localSDK.get_version()\r\n self.newProj.name = self.widgetList[4].get()\r\n self.newProj.setKsdkPath(self.localSDK.path)\r\n self.newProj.sdkVer = self.localSDK.version\r\n self.newProj.useBSP = not self.localSDK.isNewVersion()\r\n except IndexError:\r\n self.displayBoard = PhotoImage(data=kImg.boardImages['kds_icon.gif'])\r\n self.widgetList[8].config(image=self.displayBoard)\r\n self.widgetList[8].image = self.displayBoard\r\n self.widgetList[8].config(command=lambda: self.web_launch(kImg.boardImages['NoPreview.gif']))\r\n kT.debug_log(\"Index Error\", sys.exc_info()[2])\r\n #return\r\n except IndexError:\r\n kT.debug_log(\"Index Error\", sys.exc_info()[2])\r\n #return\r\n except AttributeError:\r\n kT.debug_log(\"AttributeError\", sys.exc_info()[2])\r\n return\r\n\r\n self._retLoop = self.after(250, self.poll_selection)","def update_rec_configs_choice(self):\n # this will update the configuration choices in reconstruction tab\n # fill out the config_id choice bar by reading configuration files names\n self.rec_ids = []\n for file in os.listdir(os.path.join(self.main_win.experiment_dir, 'conf')):\n if file.endswith('_config_rec'):\n self.rec_ids.append(file[0:len(file) - len('_config_rec')])\n if len(self.rec_ids) > 0:\n self.rec_id.addItems(self.rec_ids)\n self.rec_id.show()","def update(self):\n #update checkboxes\n self.average_check_box.SetValue(self.parent.fftsink.average)\n self.use_persistence_check_box.SetValue(self.parent.fftsink.use_persistence)\n self.peak_hold_check_box.SetValue(self.parent.fftsink.peak_hold)\n #update radio buttons\n try:\n index = list(DIV_LEVELS).index(self.parent.fftsink.y_per_div)\n self.radio_buttons[index].SetValue(True)\n except: pass","def _selection_changed(self, i):\n\n # Check if we have disconnected\n if i < 0:\n return\n # First check if we need to stop the old block\n if self._started_previous and self._previous_config:\n logger.debug(\"Should stop config [%s], stopping!\",\n self._previous_config.name)\n self._previous_config.delete()\n\n # Remove our callback for the previous config\n if self._previous_config:\n self._previous_config.data_received_cb.remove_callback(\n self._log_data_signal_wrapper)\n self._previous_config.error_cb.remove_callback(\n self._log_error_signal_wrapper)\n\n lg = self._model.get_config(i)\n if not lg.started:\n logger.debug(\"Config [%s] not started, starting!\", lg.name)\n self._started_previous = True\n lg.start()\n else:\n self._started_previous = False\n self._plot.removeAllDatasets()\n color_selector = 0\n\n self._plot.set_title(lg.name)\n\n self.avgsumvalue = dict();\n self.avgsumnumb = 0;\n for d in lg.variables:\n self._plot.add_curve(d.name, self.colors[\n color_selector % len(self.colors)])\n color_selector += 1\n self.avgsumvalue[d.name]=0;\n lg.data_received_cb.add_callback(self._log_data_signal_wrapper)\n lg.error_cb.add_callback(self._log_error_signal_wrapper)\n\n self._previous_config = lg","def state_choose_do(cfg, app, win, events):","def update_selection(self, game, obj):\n self.clear()\n if obj:\n if obj in game.towers:\n self.selected_tower = obj\n self.update_selection_tower(self.selected_tower)\n elif obj in game.monsters:\n self.selected_monster = obj\n self.update_selection_monster(self.selected_monster)\n elif obj in self.monsters_images:\n self.selected_monster = obj\n self.update_selection_monster(self.selected_monster, False)","def __menu_item_chosen(self, m):\n # Get selected item\n self.__selected_robot = m.index\n\n # Update the checkboxes/sliders for the selected robot\n self.__ui_controls.get('chkbox_ref').checked = \\\n self.__robots[self.__selected_robot].ref_shown\n\n self.__ui_controls.get('chkbox_rob').checked = \\\n self.__robots[self.__selected_robot].rob_shown\n\n self.__ui_controls.get('sld_opc').value = \\\n self.__robots[self.__selected_robot].opacity","def _update_gui(self):\r\n \r\n # Update the RF button.\r\n rf_on = self.api.get_output()\r\n if rf_on == None: rf_on = True\r\n self.button_rf.set_checked(rf_on, block_events=True).enable()\r\n \r\n # Update the combo; we block first just in case the value doesn't \"change\"\r\n if self.api == None: self.label_instrument_name.set_text('Simulation')\r\n else:\r\n if self.api.get_mode() == 'Fixed': self.combo_mode.set_value(0, block_events=True).enable()\r\n else: self.combo_mode.set_value(1, block_events=True).enable()\r\n self._combo_mode_changed()\r\n \r\n # Update the list plot\r\n self.query_list()","def gdl_changed(self, signal_name, device_udi, *args):\n global copiant\n if not copiant: #If not filecopy started, regenerate partition_list\n if signal_name==\"DeviceAdded\":\n obj = self.bus.get_object(\"org.freedesktop.UDisks\", device_udi)\n dev = dbus.Interface(obj, 'org.freedesktop.UDisks.Device')\n if str(dev.GetPropertyStringList(\"info.capabilities\")).find(\"volume\")>=0: #If it's a volume\n self.llista_particions()\t#Reload partition list\n if signal_name==\"DeviceRemoved\":\n self.llista_particions()","def _after_plot_list_load(self):\r\n self.button_send_list.enable()\r\n self.label_list_status.set_text('Shown list does not match device list.')","def pressSCV(self):\n\t\t\t\n\t\tm_name = self.ui.findChild(QWidget, \"m_name\")\n\t\tm_name.setText(\"Sensorinen neurografia\")\n\t\t\n\t\t\n\t\tprint \"SCV button pressed\"\n\t\t# Make a database query and draw a graph and distribution\n\t\t\n\t\t# set every checkbox back to the initial state\n\t\t\n\t\tif self.patient_chosen:\n\t\t\t# Make a database query which fetches the patient's SCV data.\n\t\t\tprint \"showing patient SCV data\"\n\t\t\n\t\tself.current_measurement = \"SCV\"\t\n\t\treturn","def OnButtonClick(self):\n self.choice()","def update_choice(self, value):\n if self.p is not None:\n if value == \"none\":\n self.other_text.delete('1.0', tk.END)\n self.other_text.insert('1.0', \"\")\n if value == \"categories\":\n self.other_text.delete('1.0', tk.END)\n self.other_text.insert('1.0', self.p.categories)\n if value == \"pageid\":\n self.other_text.delete('1.0', tk.END)\n self.other_text.insert('1.0', self.p.pageid)\n if value == \"sections\":\n self.other_text.delete('1.0', tk.END)\n self.other_text.insert('1.0', self.p.sections)\n if value == \"html\":\n self.other_text.delete('1.0', tk.END)\n self.other_text.insert('1.0', self.p.html())","def callback_selectstate(self, attrname, old, new):\n self._update_chart(self.selectstate.value)","def update(self):\n self.platform_list.update()\n self.exit_sprite.update()\n self.bagGroup.update()\n self.enemy_list.update()","def update_variations(self, **kwargs):\n pass","def _selected_label_changed(self, name, old, new):\n if self.value_lock.acquire(False):\n try:\n self.value = self._options_dict[new]\n finally:\n self.value_lock.release()","def handle_selection_eng(self):\n choice = self.get_input()\n if choice == '1':\n self.login_menu()\n elif choice == '2':\n self.authenticate_qr()\n elif choice == '3':\n self.authenticate_bluetooth()\n elif choice == '4':\n self.is_user = True\n self.display_main()","def select( self ):\n self._has_change = True","def refresh(self):\n selected = []\n if not self.__new_service:\n selected = [str(t.text()) for t in\n self.__service_list.selectedItems()]\n\n self.__service_list.clear()\n if not self.__show:\n self.__services = opencue.api.getDefaultServices()\n else:\n self.__services = self.__show.getServiceOverrides()\n\n for service in self.__services:\n item = QtWidgets.QListWidgetItem(service.name())\n self.__service_list.addItem(item)\n\n if service.name() in selected:\n item.setSelected(True)\n\n self.__service_list.sortItems()","def update(self):\n self.device = self._api.device_query(self._hardware_address, {})","def _channelList_changed(self):\n self.oscilloscope.visibleChannels = self.channelList","def _update_all_devices(self):\n self.all_devices = []\n self.all_devices.extend(self.keyboards)\n self.all_devices.extend(self.mice)\n self.all_devices.extend(self.gamepads)\n self.all_devices.extend(self.other_devices)","def check_device_changes(self):\n\n #---------------------------------------------------------------------------\n # USB ports\n current_serial_devices = self.enumerate_serial_devices()\n\n for device in self.old_serial_devices:\n if device not in current_serial_devices:\n print(\"Removed USB port: \", device)\n self.removed_serial_devices.append(device)\n\n self.arduino_change_signal.emit('OFF')\n\n for device in current_serial_devices:\n if device not in self.old_serial_devices:\n print(\"Added USB port: \", device)\n self.added_serial_devices.append(device)\n\n self.arduino_change_signal.emit('ON')\n\n self.old_serial_devices = current_serial_devices\n\n #---------------------------------------------------------------------------\n # MIDI port detection\n current_midi_devices = self.enumerate_midi_devices()\n\n for device in self.old_midi_devices:\n if device not in current_midi_devices:\n print(\"Removed MIDI port: \", device)\n self.removed_midi_devices.append(device)\n\n self.piano_change_signal.emit('OFF')\n\n for device in current_midi_devices:\n if device not in self.old_midi_devices:\n print(\"Added MIDI port: \", device)\n self.added_midi_devices.append(device)\n\n self.piano_change_signal.emit('ON')\n\n self.old_midi_devices = current_midi_devices","def on_update(self, evt):\n print(evt)\n for name in self.widgetNames:\n try:\n widget = wx.FindWindowByName(name)\n if isinstance(widget, wx.ComboBox):\n selection = widget.GetValue()\n choices = widget.GetItems()\n choices.insert(0, selection)\n value = choices\n else:\n value = widget.GetValue()\n\n data = self.tree.GetPyData(self.current_selection)\n data['Config'][name] = value\n self.tree.SetPyData(self.current_selection, data)\n except Exception as E:\n logging.error(\"{0!s}: {1!s}\".format(E, name))\n raise E","def UpdateDisplay(self):\n ##Jconf\n self.chJconf.Clear()\n for name in self.state.GetSurface(\"JconfDict\").GetNames():\n self.chJconf.Append(name)\n self.chJconf.SetStringSelection(self.state.GetSurface(\"JconfSelection\"))\n self.chJconf.Enable(self.state.IsEnabled(\"JconfDict\") == True and\n self.state.IsEnabled(\"JconfSelection\") == True and\n self.state.GetSurface(\"Xplorer\") == True)\n self.bEditJconf.Enable(self.state.IsEnabled(\"JconfDict\") and\n self.state.GetSurface(\"Xplorer\") == True)\n ##Name Server\n self.cbNameServer.SetValue(self.state.GetSurface(\"NameServer\"))\n self.cbNameServer.Enable(self.state.IsEnabled(\"NameServer\"))\n ##Conductor\n self.cbConductor.SetValue(self.state.GetSurface(\"Conductor\"))\n self.cbConductor.Enable(self.state.IsEnabled(\"Conductor\"))\n ##Xplorer\n self.cbXplorer.SetValue(self.state.GetSurface(\"Xplorer\"))\n self.cbXplorer.Enable(self.state.IsEnabled(\"Xplorer\"))\n ##Desktop Mode\n self.cbDesktop.SetValue(self.state.GetSurface(\"DesktopMode\"))\n self.cbDesktop.Enable(self.state.IsEnabled(\"DesktopMode\"))\n ##Xplorer Type\n if self.state.GetSurface(\"DesktopMode\"):\n self.rbXplorer.SetSelection(0)\n else:\n if (self.state.GetSurface(\"XplorerType\") == \"OSG-VEP\"):\n self.rbXplorer.SetSelection(0)\n else:\n self.rbXplorer.SetSelection(1)\n self.rbXplorer.Enable(self.state.IsEnabled(\"XplorerType\") == True and\n self.state.GetSurface(\"DesktopMode\") == False and\n self.state.GetSurface(\"Xplorer\") == True)\n ##Cluster Node button\n self.bCluster.Enable(CLUSTER_ENABLED and\n self.state.GetSurface(\"Xplorer\") == True and\n self.state.GetSurface(\"DesktopMode\") == False and\n self.state.GetSurface(\"XplorerType\") == \"OSG-VEPC\")\n return","def Update(self, mode = UPDATE_MODE.all):\r\n aux_versions = dstore.Get(\"versions\")\r\n \r\n if(aux_versions['hw'] != None): \r\n Ui().lineHwVersion.setText(str(aux_versions['hw'])) \r\n else:\r\n Ui().lineHwVersion.setText(\"- -\")\r\n \r\n if(aux_versions['fw'] != None): \r\n Ui().lineFwVersion.setText(str(aux_versions['fw'])) \r\n else:\r\n Ui().lineFwVersion.setText(\"- -\") \r\n \r\n \r\n \r\n \"\"\" TERMINAL INFO \"\"\"\r\n aux_terminal_info = dstore.Get(\"terminal_info\", \"GET\")\r\n \r\n \"\"\" number of cells \"\"\"\r\n if(aux_terminal_info['number_of_cells'] != None):\r\n Ui().lineCells.setText(str(aux_terminal_info['number_of_cells'])) \r\n else:\r\n Ui().lineCells.setText(\"-\") \r\n \r\n \r\n \"\"\" battery \"\"\"\r\n if(aux_terminal_info['battery'] != None):\r\n Ui().lineBattery.setText(str(aux_terminal_info['battery'])+\" %\") \r\n else:\r\n Ui().lineBattery.setText(\"-- %\") \r\n \r\n \"\"\" speaker \"\"\" \r\n if(aux_terminal_info['speaker']['keys'] == True):\r\n Ui().lineSpeakerKeys.setText(\"ON\")\r\n Ui().pushSpeakerKeys.setText(\"OFF\")\r\n Ui().pushSpeakerKeys.setEnabled(True)\r\n Ui().pushSpeakerSystem.setEnabled(True)\r\n Ui().pushSpeakerTiming.setEnabled(True)\r\n elif(aux_terminal_info['speaker']['keys'] == False):\r\n Ui().lineSpeakerKeys.setText(\"OFF\")\r\n Ui().pushSpeakerKeys.setText(\"ON\")\r\n Ui().pushSpeakerKeys.setEnabled(True)\r\n Ui().pushSpeakerSystem.setEnabled(True)\r\n Ui().pushSpeakerTiming.setEnabled(True)\r\n else:\r\n Ui().lineSpeakerKeys.setText(\"- -\")\r\n Ui().pushSpeakerKeys.setText(\"- -\")\r\n \r\n if(aux_terminal_info['speaker']['system'] == True):\r\n Ui().lineSpeakerSystem.setText(\"ON\")\r\n Ui().pushSpeakerSystem.setText(\"OFF\")\r\n Ui().pushSpeakerSystem.setEnabled(True)\r\n elif(aux_terminal_info['speaker']['system'] == False):\r\n Ui().lineSpeakerSystem.setText(\"OFF\")\r\n Ui().pushSpeakerSystem.setText(\"ON\")\r\n Ui().pushSpeakerSystem.setEnabled(True)\r\n else:\r\n Ui().lineSpeakerSystem.setText(\"- -\")\r\n Ui().pushSpeakerSystem.setText(\"- -\")\r\n Ui().pushSpeakerSystem.setEnabled(False)\r\n \r\n if(aux_terminal_info['speaker']['timing'] == True):\r\n Ui().lineSpeakerTiming.setText(\"ON\")\r\n Ui().pushSpeakerTiming.setText(\"OFF\")\r\n Ui().pushSpeakerTiming.setEnabled(True)\r\n elif(aux_terminal_info['speaker']['timing'] == False):\r\n Ui().lineSpeakerTiming.setText(\"OFF\")\r\n Ui().pushSpeakerTiming.setText(\"ON\")\r\n Ui().pushSpeakerTiming.setEnabled(True)\r\n else: \r\n Ui().lineSpeakerTiming.setText(\"- -\")\r\n Ui().pushSpeakerTiming.setText(\"- -\")\r\n Ui().pushSpeakerTiming.setEnabled(False)\r\n \r\n if(aux_terminal_info['speaker']['keys'] == None or aux_terminal_info['speaker']['timing']==None or aux_terminal_info['speaker']['system']==None): \r\n Ui().pushSpeakerKeys.setEnabled(False)\r\n Ui().pushSpeakerSystem.setEnabled(False)\r\n Ui().pushSpeakerTiming.setEnabled(False)\r\n else:\r\n Ui().pushSpeakerKeys.setEnabled(True)\r\n Ui().pushSpeakerSystem.setEnabled(True)\r\n Ui().pushSpeakerTiming.setEnabled(True)\r\n \r\n \r\n return True","def update_plot_det_items(self,param):\n items=param.value()['selected']\n self.settings.child('scan_options', 'plot_from').setOpts(limits=items)","def ChannelSelect(self):\n self.active_mode = 'default'\n self.reset_buttons()\n # Dialog to choose channels from specific brain regions\n w = SelectChannelsDialog(\n stringlist=self.model.all_regions,\n checked=self.model.regions_mask\n )\n all_locs = self.model.electrodes_table['location'][self.model.electrical_series_channel_ids]\n self.model.channels_mask = np.zeros(len(all_locs))\n for loc in w.choices:\n self.model.channels_mask += all_locs == np.array(loc)\n # Indices of channels from chosen regions\n self.model.channels_mask_ind = np.where(self.model.channels_mask)[0]\n self.model.n_channels_total = len(self.model.channels_mask_ind)\n # Reset channels span control\n self.model.lastCh = np.minimum(16, self.model.n_channels_total)\n self.model.firstCh = 1\n self.model.nChToShow = self.model.lastCh - self.model.firstCh + 1\n self.qline0.setText(str(self.model.lastCh))\n self.qline1.setText(str(self.model.firstCh))\n # Update signals plot\n self.model.selectedChannels = self.model.channels_mask_ind[self.model.firstCh - 1:self.model.lastCh]\n self.model.refreshScreen()","def handle_selection_main(self):\n choice = self.get_input()\n if choice == '1':\n self.display_cust()\n elif choice == '2':\n self.is_user = False\n self.display_eng()","def update(self):\n self.device.update()","def update(self):\n self.device.update()","def choices(self, choices):\n\n self._choices = choices","def change(self):\r\n\r\n # If checkboxes are available, check status and set boat speed reference line visibility accordingly.\r\n if self.cb:\r\n if self.cb_bt.checkState() == QtCore.Qt.Checked:\r\n for item in self.bt:\r\n item.set_visible(True)\r\n else:\r\n for item in self.bt:\r\n item.set_visible(False)\r\n # GGA\r\n if self.cb_gga.checkState() == QtCore.Qt.Checked:\r\n for item in self.gga:\r\n item.set_visible(True)\r\n # self.gga[0].set_visible(True)\r\n elif self.gga is not None:\r\n for item in self.gga:\r\n item.set_visible(False)\r\n # self.gga[0].set_visible(False)\r\n # VTG\r\n if self.cb_vtg.checkState() == QtCore.Qt.Checked:\r\n for item in self.vtg:\r\n item.set_visible(True)\r\n # self.vtg[0].set_visible(True)\r\n elif self.vtg is not None:\r\n for item in self.vtg:\r\n item.set_visible(False)\r\n # self.vtg[0].set_visible(False)\r\n\r\n # Draw canvas\r\n self.canvas.draw()","def update(self):\n # If the game is not over.\n if self.tictactoe:\n # If the player is human, the choice can only be detected by the game,\n # because the player has no responsibility over the window\n if self.player.chooser:\n choice = self.choice\n self.choice = None\n else:\n choice = self.player.play(self.tictactoe)\n self.tictactoe.choose(choice)\n else:\n if self.on:\n self.end_time = time.time()\n self.on = False\n if self.restart_at_end:\n if time.time() - self.end_time > self.end_duration:\n self.restart()","def choose(self, choice):\n if self.available(choice):\n self.select(choice)","def pressMCV(self):\n\t\t\n\t\tm_name = self.ui.findChild(QWidget, \"m_name\")\n\t\tm_name.setText(\"Motorinen neurografia\")\n\t\t\n\t\tprint \"MCV button pressed\"\t\t\n\t\t# update graph and distribution\n\t\t# o set parameters to defaults (length, sd, medianus T)\n\t\t# o clear regression checkbox\n\t\t# o draw the MCV verrokki graph and distribution (set graph as default tab)\n\t\t\n\t\t# set comboboxes back to the default state \n\t\t# Default: summary of the patient MCV data\n\t\tif self.patient_chosen:\n\t\t\tprint \"showing patient MCV data\"\t\t\n\t\t\n\t\tself.current_measurement = \"MCV\"\n\t\treturn","def evo_selected(self):\n pub.sendMessage(\"EVO_SELECTED\", id=self.id, location=self.location)","def onSelected(self):\n pass","def update_change(self):\n self.meas_selected_number = self.__input_meas.value()\n self.meas_selected_series = self.__input_series.value()\n self.selected_data = self.__input_select.value()\n self.noice_reduction_number = self.__input_noice.value()\n self.particle_size_number = self.__input_p_size.value()\n self.particle_density_number = self.__input_p_density.value()\n self.saturation_percentage = self.__input_saturation_percentage.value()\n\n # print(\"Selected series:\", self.meas_selected_series)\n # print(\"Selected measurement:\", self.meas_selected_number)\n\n if not 1 <= self.meas_selected_number <= 17: # In series 2 there's measurement 0, but that's a copy of the 8th\n raise ValueError\n if self.noice_reduction_number < 0:\n raise ValueError\n if self.particle_size_number <= 0:\n raise ValueError\n if self.particle_density_number < 0:\n raise ValueError\n if not 0 <= self.saturation_percentage <= 100:\n raise ValueError\n\n meas_index = self.meas_selected_number - 1\n if self.meas_selected_series == 1:\n self.measurement = self.meas_pressure[meas_index]\n elif self.meas_selected_series == 2:\n self.measurement = self.meas_mixture[meas_index]\n else:\n raise ValueError\n\n if self.selected_data == 1:\n self.data = toolbox_2.remove_noise(self.measurement.p_diff, self.noice_reduction_number)\n elif self.selected_data == 2:\n self.data = toolbox_2.remove_noise(self.measurement.p_abs, self.noice_reduction_number)\n elif self.selected_data == 3:\n self.data = toolbox_2.remove_noise(\n toolbox_2.flip_and_normalize(self.measurement.ext), self.noice_reduction_number)\n self.plot_zoom.setYRange(-0.1, 1, padding=0)\n elif self.selected_data == 4:\n self.data = toolbox_2.remove_noise(self.measurement.ext, self.noice_reduction_number)\n else:\n raise ValueError\n\n self.index_of_drop = toolbox_2.find_drop_index(self.measurement.p_diff)\n # time vector starts from the beginning of pressure drop\n time = self.measurement.time - self.measurement.time[self.index_of_drop]\n\n self.update_distribution()\n\n if self.first_update:\n self.curve_select = self.plot_select.plot(time, self.data)\n self.curve_zoom = self.plot_zoom.plot(self.measurement.time, self.data)\n self.curve_simulate = self.plot_zoom.plot(pen=pg.mkPen((100, 255, 200)))\n\n self.curve_distribution_cumulative = self.plot_distribution.plot(\n pen=pg.mkPen((100, 200, 255)),\n name=\"´ Kumulatiivinen pitoisuus\",\n symbolBrush=(80, 160, 201), symbolPen='w')\n self.curve_distribution = self.plot_distribution.plot(\n name=\"Pitoisuusjakauma\", symbolBrush=(50, 50, 255), symbolPen='w')\n self.curve_rotatometer = self.plot_rotatometer.plot(\n name=\"Mitattu pitoisuus\", symbolBrush=(50, 50, 255), symbolPen='w')\n self.curve_rotatometer_fit = self.plot_rotatometer.plot(\n pen=pg.mkPen((100, 255, 200)), name=\"´ Ideaalinen pitoisuus\")\n\n self.first_update = False\n else:\n self.curve_select.setData(time, self.data)\n self.curve_zoom.setData(time, self.data)\n\n self.curve_distribution.setData(self.particle_distribution_x, self.particle_distribution_y*1e-10)\n self.curve_distribution_cumulative.setData(self.smallest_particles, self.number_counts*1e-10)\n self.curve_rotatometer.setData(np.array([4, 6, 8, 10, 12, 14, 16, 18]), self.number_counts_2*1e-10)\n x = np.linspace(3.5, 20, 100)\n self.curve_rotatometer_fit.setData(x, self.number_counts_2[0]*4*(1/x)*1e-10)\n\n if self.simulate_bool:\n self.simulation()\n\n self.set_labels()\n\n # set the graphs to the point of pressure drop, units are in seconds\n self.plot_select.setXRange(-2, 4, padding=0)\n self.plot_zoom.setXRange(0, 0.3, padding=0)\n self.line.setX(0.1)\n\n self.update_zoom_region()\n # self.update_zoom_plot()","def _update_model(self, idx):\n self._wfield.update(self._choices[idx][0])","def _update_device_types(self):\n device_types = self.adapter.device_types()\n for device_type in device_types.items:\n key = device_type.id\n self._make_up_to_date('/device_types', key, device_type)","def selectionChanged(self, selected, deselected):\n rows = [self.model.nodeFromIndex(row) for row in self.selmod1.selectedRows()]\n self.updateStats(rows)","def async_update_device(self) -> None:","def _on_selection_changed(self, selection):\n if self._updating_selection:\n return\n\n self._updating_selection = True\n\n self._tree_selection.unselect_all()\n for widget in selection:\n gadget_iter = self._find_iter_by_widget(widget)\n if gadget_iter:\n select_iter(self._tree_view, gadget_iter)\n\n self._updating_selection = False","def switch_arrangment(self, new_arrangment):\n #Clear Figures to avoid memory leak\n for figure in self.figures:\n figure.clear()\n plt.close(figure)\n \n #Close the exisiting display\n self.destroy()\n \n #Generate user interface\n UI = SD_UI(tuning = self.tuning_flag,\n location = self.location,\n language = self.language,\n arrangment = new_arrangment)\n \n #Run the new user interface\n UI.mainloop()","def choice_changed(self, seg, name):\n section, option = name\n v = seg.segments[seg.selected_index]\n _stash.config.set(section, option, v)\n self.save()","def updateSGProDeviceNameList(self, deviceNames):\n self.ui.sgproDeviceList.clear()\n self.ui.sgproDeviceList.setView(QListView())\n for deviceName in deviceNames:\n self.ui.sgproDeviceList.addItem(deviceName)\n return True","def update(self):\n self._device = self._geizhals.parse()","def __init__(self, hass: HomeAssistant, client: VisonicClient, visonic_device: PySensorDevice):\n SelectEntity.__init__(self)\n #_LOGGER.debug(\"Creating select entity for %s\",visonic_device.getDeviceName())\n self.hass = hass\n self._client = client\n self._visonic_device = visonic_device\n self._panel = client.getPanelID()\n if self._panel > 0:\n self._name = \"visonic_p\" + str(self._panel) + \"_\" + visonic_device.getDeviceName().lower()\n else:\n self._name = \"visonic_\" + visonic_device.getDeviceName().lower()\n self._is_available = self._visonic_device.isEnrolled()\n self._is_armed = not self._visonic_device.isBypass()\n self._pending_state_is_armed = None\n self._dispatcher = client.getDispatcher()","def _update_selection(self, qindex1, qindex2):\n m = self.model()\n self._do_select(m.qindex2index(qindex1), m.qindex2index(qindex2))","def onSelect_specimen(self, event):\n new_s = self.specimens_box.GetValue()\n if self.select_specimen(new_s):\n self.update_selection()\n else:\n self.specimens_box.SetValue(self.s)\n self.user_warning(\n \"no specimen %s reverting to old specimen %s\" % (new_s, self.s))","def modify_devices(self):\n\n for i in self._nodes.items():\n node = i[1]\n devices = node[\"devices\"]\n other_devices = devices[\"other_devices\"]\n kernel_devices = devices[\"kernel_devices\"]\n dpdk_devices = devices[\"dpdk_devices\"]\n\n if other_devices:\n self._modify_other_devices(\n node, other_devices, kernel_devices, dpdk_devices\n )\n\n # Get the devices again for this node\n self._get_device(node)\n devices = node[\"devices\"]\n kernel_devices = devices[\"kernel_devices\"]\n dpdk_devices = devices[\"dpdk_devices\"]\n\n klen = len(kernel_devices)\n if klen > 0:\n print(\"\\nThese devices are safe to be used with VPP.\\n\")\n VppPCIUtil.show_vpp_devices(kernel_devices)\n question = (\n \"\\nWould you like to use any of these \" \"device(s) for VPP [y/N]? \"\n )\n answer = self._ask_user_yn(question, \"n\")\n if answer == \"y\":\n vppd = {}\n for dit in kernel_devices.items():\n dvid = dit[0]\n device = dit[1]\n question = \"Would you like to use device {} \".format(dvid)\n question += \"for VPP [y/N]? \"\n answer = self._ask_user_yn(question, \"n\")\n if answer == \"y\":\n vppd[dvid] = device\n for dit in vppd.items():\n dvid = dit[0]\n device = dit[1]\n if (\n \"unused\" in device\n and len(device[\"unused\"]) != 0\n and device[\"unused\"][0] != \"\"\n ):\n driver = device[\"unused\"][0]\n question = \"Would you like to bind the driver {} for {} [y/N]? \".format(\n driver, dvid\n )\n answer = self._ask_user_yn(question, \"n\")\n if answer == \"y\":\n logging.debug(\n \"Binding device {} to driver {}\".format(\n dvid, driver\n )\n )\n ret = VppPCIUtil.bind_vpp_device(node, driver, dvid)\n if ret:\n logging.debug(\n \"Could not bind device {}\".format(dvid)\n )\n dpdk_devices[dvid] = device\n del kernel_devices[dvid]\n\n dlen = len(dpdk_devices)\n if dlen > 0:\n print(\"\\nThese device(s) are already using DPDK.\\n\")\n VppPCIUtil.show_vpp_devices(dpdk_devices, show_interfaces=False)\n question = \"\\nWould you like to remove any of \"\n question += \"these device(s) [y/N]? \"\n answer = self._ask_user_yn(question, \"n\")\n if answer == \"y\":\n vppdl = {}\n for dit in dpdk_devices.items():\n dvid = dit[0]\n device = dit[1]\n question = \"Would you like to remove {} [y/N]? \".format(dvid)\n answer = self._ask_user_yn(question, \"n\")\n if answer == \"y\":\n vppdl[dvid] = device\n for dit in vppdl.items():\n dvid = dit[0]\n device = dit[1]\n if (\n \"unused\" in device\n and len(device[\"unused\"]) != 0\n and device[\"unused\"][0] != \"\"\n ):\n driver = device[\"unused\"][0]\n logging.debug(\n \"Binding device {} to driver {}\".format(dvid, driver)\n )\n ret = VppPCIUtil.bind_vpp_device(node, driver, dvid)\n if ret:\n logging.debug(\"Could not bind device {}\".format(dvid))\n else:\n kernel_devices[dvid] = device\n del dpdk_devices[dvid]\n\n interfaces = {}\n for dit in dpdk_devices.items():\n dvid = dit[0]\n device = dit[1]\n VppPCIUtil.vpp_create_interface(interfaces, dvid, device)\n node[\"interfaces\"] = interfaces\n\n self._update_auto_config()\n self.updateconfig()","def on_feature_choice(self, event):\n\n self.log.trace(\"Handle feature selection by user.\")\n result = {'successful': False}\n\n try:\n # determine feature selected\n module_name=None\n if not self.custom_module: module_name = self.input_module.GetString(self.input_module.GetSelection())\n feature_name = event.GetString()\n\n self.story_choices = []\n for selection in DEFAULT_SEL:\n self.story_choices.append(selection)\n if feature_name.lower() == CUSTOM_SEL.lower():\n # set custom flag\n self.custom_feature = True\n # show custom input\n self.input_custom_feature.Show()\n else:\n # clear custom flag\n self.custom_feature = False\n # make sure custom field is hidden\n self.input_custom_feature.Hide()\n if feature_name.lower() != BLANK_SEL.lower():\n # return all features for module\n self.log.trace(\"Rebuilding user story list for %s module ...\" % feature_name)\n stories = \\\n self.database.return_user_stories_for_feature(feature_name, module=module_name)['user stories']\n\n # build story list\n for story in stories:\n self.story_choices.append(story['name'])\n\n # set feature choices to selection\n self.input_story.SetItems(self.story_choices)\n self._update_story_input_according_to_custom_feature_flag()\n self.log.trace(\"User Story list for %s feature rebuilt.\" % feature_name)\n\n # reset test selections\n self.log.trace(\"Reseting test list ...\")\n self.test_choices = []\n for selection in DEFAULT_SEL:\n self.test_choices.append(selection)\n self.input_test.SetItems(self.test_choices)\n self._update_test_input_according_to_custom_story_flag()\n self.log.trace(\"Test list reset.\")\n\n # reset testcase selections\n self.log.trace(\"Reseting test case list ...\")\n self.testcase_choices = []\n for selection in DEFAULT_SEL:\n self.testcase_choices.append(selection)\n self.input_testcase.SetItems(self.testcase_choices)\n self._update_testcase_input_according_to_custom_test_flag()\n self.log.trace(\"Test case list reset.\")\n\n result['successful'] = True\n except BaseException, e:\n self.handle_exception(e, \"handle feature selection by user\")\n\n # return\n return result","def image_selection_change():\n\n def return_image(val, model_id, message_name, field_name, mime, sind):\n \"\"\"Returns a URL resolvable by the probe\"\"\"\n column_data_source = curdoc().get_model_by_name(sind)\n index = column_data_source.tags[0]\n url = \"http://{0}/image/\".format(_host) + \"---\".join([model_id, message_name, field_name, mime, sind, str(index)])\n return url\n\n d = curdoc()\n _remove_fig(d)\n model_id, message_name, _ = run_handlers.get_modelid_messagename_type(d)\n image_field = d.get_model_by_name(IMAGE_SELECTION).value.split(\" :\")[0]\n mime = d.get_model_by_name(MIME_SELECTION).value\n\n if image_field != DEFAULT_UNSELECTED and mime != DEFAULT_UNSELECTED:\n plot = figure(plot_width=500, plot_height=500, title=\"\", x_range=Range1d(start=0, end=1), y_range=Range1d(start=0, end=1), name=FIGURE_MODEL)\n sind = run_handlers.get_source_index(d.session_context.id, model_id, message_name, image_field + mime)\n\n _install_callback_and_cds(sind, model_id, message_name,\n {image_field: [return_image, {\"model_id\": model_id,\n \"message_name\": message_name,\n \"field_name\": image_field,\n \"mime\": mime,\n \"sind\": sind}]},\n stream_limit=1)\n plot.image_url(url=image_field, x=0, y=1, h=1, w=1, source=d.get_model_by_name(sind))\n d.add_root(plot)","def update_list_view(self):\n # Clear the list/tree view.\n self.list_view.clear()\n\n # Find all the selected things in Maya.\n selected = cmds.ls(selection=True)\n\n # For each of the selected things, create a widget item.\n for thing in selected:\n item = QtGui.QListWidgetItem(thing)\n item.setFlags(item.flags() | QtCore.Qt.ItemIsEditable)\n self.list_view.addItem(item)\n # Set the flags on the widget item so it is editable.","def updateacc(cls):\n cls.var_1.set('')\n cls.right_accentry['menu'].delete(0, 'end')\n\n # Insert list of new options (tk._setit hooks them up to var)\n temp = database3.Db03(\"\", \"\")\n new_choices = temp.accounts()\n for choice in new_choices:\n cls.right_accentry['menu'].add_command(label=choice, \\\n command=tk._setit(cls.var_1, choice, God.changedacc))\n try:\n cls.var_1.set(new_choices[0])\n except IndexError:\n cls.var_1.set('None')\n God.changedacc()","def selection_changed(self):\n self.emit('selection_changed')","def on_mount_changed(self, btn):\n sender = self.sender()\n if sender == self.ui.radio_smd:\n self.mdl.cmp.mount = ComponentBase.MOUNT_SMD\n elif sender == self.ui.radio_tht:\n self.mdl.cmp.mount = ComponentBase.MOUNT_THT\n self.refresh_svg_canvas()","def updateSelectionArea(self):\n self.machine.setSelectionArea(self.points,\n fill='hatch',\n color=self.machine.color)\n eventDict = prepareDrawingSignal('drawingProgress',\n 'polygon',\n self.points,\n self.machine.parameters)\n self.machine.plot.notify(**eventDict)","def add_robot(self, robot):\n # ALTHOUGH THE DOCUMENTATION SAYS THAT MENU CHOICES CAN BE UPDATED,\n # THE PACKAGE DOES NOT ALLOW IT.\n # THUS THIS 'HACK' MUST BE DONE TO REFRESH THE UI WITH AN UPDATED LIST\n\n # Save the list of robot names\n new_list = []\n for name in self.__ui_controls.get('menu_robots').choices:\n new_list.append(name)\n # Add the new one\n new_list.append(robot.name)\n\n # Add robot to list\n self.__robots.append(robot)\n self.__selected_robot = len(self.__robots) - 1\n\n num_options = 4\n # Add spot for current robot settings\n self.__teachpanel.append([[0] * num_options] * robot.num_joints)\n\n # Add robot joint sliders\n i = 0\n for joint in robot.joints:\n if joint.qlim[0] == joint.qlim[1]:\n self.__teachpanel[self.__selected_robot][i] = [\n joint.qlim[0], joint.qlim[1],\n joint.theta, None]\n else:\n string = \"{:.2f} rad ({:.2f} deg)\".format(\n joint.theta, degrees(joint.theta))\n self.__teachpanel[self.__selected_robot][i] = [\n joint.qlim[0], joint.qlim[1],\n joint.theta, wtext(text=string)]\n i += 1\n\n # Refresh the caption\n self.__reload_caption(new_list)\n\n # Set it as selected\n self.__ui_controls.get('menu_robots').index = \\\n len(self.__robots) - 1\n\n # Place camera based on robots effective radius * 1.25\n if robot.robot is not None:\n radius = sum([abs(link.a) + abs(link.d) for link in robot.robot.links]) * 1.25\n self.scene.camera.pos = vector(radius, radius, radius) + get_pose_pos(robot.joints[1].get_pose())\n self.scene.camera.axis = vector(-radius, -radius, -radius)","def change_device(self):\n if self.state.ser:\n UsbHost.close_port(self.state.ser)\n device = self.CBDevices.currentText()\n if device:\n comport = self.devices[int(device)]\n self.state.ser = UsbHost.open_port(comport)\n if not self.state.ser:\n self.statusbar.showMessage(\"Выбранный порт более недоступен. Произведите повторный поиск\")\n return\n answer: str = self.UsbHost.send_command(self.state.ser, \"ping\", device)\n if answer in wrong_answers:\n error_message(\"Выбранный девайс не отвечает\")\n self.statusbar.showMessage(\"Выбранный порт более недоступен. Произведите повторный поиск\")\n return\n self.state.device_id = int(device)\n self.state.comport = comport\n self.create_message()\n self.set_controls_state(True)\n self.BtnL1.click()\n self.BtnAttenuate.click()\n self.SpinDACValue.setValue(35000)\n self.BtnSetDACValue.click()\n self.set_sw(\"0 1\")","def recognize(self):\n from datetime import datetime\n from RecognitionDialog import QRecognitionDialog\n\n # save alarm\n self.save_alarm_enable(False)\n\n app_doc_data = AppDocData.instance()\n current_drawing, currentPid = None, None\n\n if self.graphicsView.hasImage():\n current_drawing = app_doc_data.activeDrawing\n currentPid = app_doc_data.activeDrawing.name\n\n # get checked drawings\n drawing_top = self.treeWidgetDrawingList.topLevelItem(0)\n count = drawing_top.childCount()\n checked_drawings = {}\n for idx in range(count):\n child = drawing_top.child(idx)\n if child.checkState(0) == Qt.Checked and child.data(Qt.UserRole, 0):\n checked_drawings[child.data(Qt.UserRole, 0)] = child\n # up to here\n\n # if there is no checked drawing\n if current_drawing and currentPid and not checked_drawings:\n for idx in range(count):\n child = drawing_top.child(idx)\n if child.data(Qt.UserRole, 0) is current_drawing:\n checked_drawings[child.data(Qt.UserRole, 0)] = child\n\n if not checked_drawings:\n self.showImageSelectionMessageBox()\n return\n\n try:\n self.onClearLog()\n dlg = QRecognitionDialog(self, [drawing for drawing in checked_drawings.keys()])\n dlg.exec_()\n\n if current_drawing and current_drawing in checked_drawings.keys() and dlg.isTreated:\n self.open_image_drawing(current_drawing, force=True)\n\n # save working date-time\n _now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')\n for drawing, tree_item in checked_drawings.items():\n drawing.datetime = _now\n tree_item.setText(1, _now)\n #app_doc_data.saveDrawings(checked_drawings.keys())\n self.changeViewCheckedState(True)\n # up to here\n except Exception as ex:\n message = 'error occurred({}) in {}:{}'.format(repr(ex), sys.exc_info()[-1].tb_frame.f_code.co_filename,\n sys.exc_info()[-1].tb_lineno)\n self.addMessage.emit(MessageType.Error, message)\n\n # save alarm\n self.save_alarm_enable(True)","def set_current(idx):\n\n dev_dict = {dev.uuid: dev for dev in G.DEVICE_LIST}\n if idx in dev_dict:\n current_dev = dev_dict[idx]\n elif isinstance(idx, int) and idx < len(G.DEVICE_LIST):\n current_dev = G.DEVICE_LIST[idx]\n else:\n raise IndexError(\"device idx not found in: %s or %s\" % (\n list(dev_dict.keys()), list(range(len(G.DEVICE_LIST)))))\n G.DEVICE = current_dev","def setDisplayChoice(self, settings: ghidra.docking.settings.Settings, choice: unicode) -> None:\n ...","def _updateSelectedItem(self):\n plot = self.plot\n if plot is not None:\n selected = plot.selection().getSelectedItems()\n # Give priority to image over scatter\n for klass in (items.ImageBase, items.Scatter):\n for item in selected:\n if isinstance(item, klass):\n # Found a matching item, use it\n self.getHistogramWidget().setItem(item)\n return\n self.getHistogramWidget().setItem(None)","def _update_hardware_control_from_gui(self):\n self._under_hardware_control = self.widgets['hardware_control'].isChecked()","def update_(self):\n self.update_listbox()\n self.update_infobox()\n self.update_statusbar()\n self.listbox.select_set(0)\n self.listbox.focus_set()","def setChoices(self, choices):\n self.getGtkObject('property_liststore').clear()\n for choice in choices:\n self.getGtkObject('property_liststore').append([str(choice)])","def OnSelectionUpdated(self, characterId):\n pass","def update(self, choices, clear=False):\n if clear:\n self._weights.clear()\n self._weights.update(choices)\n self._generate_p()","def onChange(self, event_id: int, datadictionary: dict):\n #_LOGGER.debug(\"Select Sensor onchange %s\", str(self._name))\n # Update the current value based on the device state\n if self._visonic_device is not None:\n self._is_available = self._visonic_device.isEnrolled()\n self._is_armed = not self._visonic_device.isBypass()\n else:\n _LOGGER.debug(\"Select on change called but sensor is not defined\")\n\n if self._pending_state_is_armed is not None and self._pending_state_is_armed == self._is_armed:\n _LOGGER.debug(\"Change Implemented in panel\")\n self._pending_state_is_armed = None\n\n # Ask HA to schedule an update\n self.schedule_update_ha_state(True)","def service_changed(self):\n\n if self.ui.comboBox_service.currentText() == \"Google\":\n self.ui.label_id.setEnabled(False)\n self.ui.lineEdit_id.setEnabled(False)\n self.ui.label_key.setEnabled(False)\n self.ui.lineEdit_key.setEnabled(False)\n self.ui.label_language.setEnabled(True)\n self.ui.lineEdit_language.setEnabled(True)\n self.ui.textEdit_notes.setText(self.google_text)\n if self.ui.comboBox_service.currentText() == \"Microsoft Bing Voice Recognition\":\n self.ui.label_id.setEnabled(False)\n self.ui.lineEdit_id.setEnabled(False)\n self.ui.label_key.setEnabled(True)\n self.ui.lineEdit_key.setEnabled(True)\n self.ui.label_language.setEnabled(True)\n self.ui.lineEdit_language.setEnabled(True)\n self.ui.textEdit_notes.setText(\"Bing\\nBing Voice Recognition API keys 32-character lowercase hexadecimal strings\")\n if self.ui.comboBox_service.currentText() == \"Wit.ai\":\n self.ui.label_id.setEnabled(False)\n self.ui.lineEdit_id.setEnabled(False)\n self.ui.label_key.setEnabled(True)\n self.ui.lineEdit_key.setEnabled(True)\n self.ui.label_language.setEnabled(False)\n self.ui.lineEdit_language.setEnabled(False)\n self.ui.textEdit_notes.setText(\"Wit.ai\\nWit.ai keys are 32-character uppercase alphanumeric strings\")\n if self.ui.comboBox_service.currentText() == \"Houndify\":\n self.ui.label_id.setEnabled(True)\n self.ui.lineEdit_id.setEnabled(True)\n self.ui.label_key.setEnabled(True)\n self.ui.lineEdit_key.setEnabled(True)\n self.ui.label_language.setEnabled(False)\n self.ui.lineEdit_language.setEnabled(False)\n msg = \"Houndify\\nHoundify client IDs and keys are Base64-encoded strings\\n\"\n msg += \"www.houndify.com\"\n self.ui.textEdit_notes.setText(msg)\n if self.ui.comboBox_service.currentText() == \"IBM Speech\":\n self.ui.label_id.setEnabled(True)\n self.ui.lineEdit_id.setEnabled(True)\n self.ui.label_key.setEnabled(True)\n self.ui.lineEdit_key.setEnabled(True)\n self.ui.label_language.setEnabled(True)\n self.ui.lineEdit_language.setEnabled(True)\n msg = \"IBM Speech to text\\n\"\n msg += \"usernames are strings of the form XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX\\n\"\n msg += \"passwords are mixed-case alphanumeric strings\"\n self.ui.textEdit_notes.setText(msg)","async def async_step_device(self, user_input=None):\n if user_input:\n if user_input[CONF_HOST] == CONF_MANUAL_INPUT:\n return await self.async_step_configure()\n\n for device in self.devices:\n if device[CONF_HOST] == user_input[CONF_HOST]:\n self.device_id = device[CONF_DEVICE_ID]\n self.onvif_config = {\n CONF_NAME: device[CONF_NAME],\n CONF_HOST: device[CONF_HOST],\n CONF_PORT: device[CONF_PORT],\n }\n return await self.async_step_configure()\n\n discovery = await async_discovery(self.hass)\n for device in discovery:\n configured = any(\n entry.unique_id == device[CONF_DEVICE_ID]\n for entry in self._async_current_entries()\n )\n\n if not configured:\n self.devices.append(device)\n\n if LOGGER.isEnabledFor(logging.DEBUG):\n LOGGER.debug(\"Discovered ONVIF devices %s\", pformat(self.devices))\n\n if self.devices:\n devices = {CONF_MANUAL_INPUT: CONF_MANUAL_INPUT}\n for device in self.devices:\n description = f\"{device[CONF_NAME]} ({device[CONF_HOST]})\"\n if hardware := device[CONF_HARDWARE]:\n description += f\" [{hardware}]\"\n devices[device[CONF_HOST]] = description\n\n return self.async_show_form(\n step_id=\"device\",\n data_schema=vol.Schema({vol.Optional(CONF_HOST): vol.In(devices)}),\n )\n\n return await self.async_step_configure()"],"string":"[\n \"def updateVision(self, *args):\\r\\n\\r\\n # Update the list of frame choices and the default frame choice\\r\\n self._appChoice[\\\"frame\\\"] = [choice[0] for choice in self._system[self._appString[\\\"device\\\"].get()][self._appString[\\\"vision\\\"].get()]]\\r\\n self._appString[\\\"frame\\\"].set(self._appChoice[\\\"frame\\\"][0])\\r\\n\\r\\n # Delete the old choices fromt the option menu\\r\\n menu = self._appOption[\\\"frame\\\"][\\\"menu\\\"]\\r\\n menu.delete(0, \\\"end\\\")\\r\\n\\r\\n # Add the new list of choices to the option menu\\r\\n for string in self._appChoice[\\\"frame\\\"]:\\r\\n menu.add_command(label=string, command=lambda value=string: self._appString[\\\"frame\\\"].set(value))\",\n \"def device_selected(self, uid):\\n if uid == self.cur_uid:\\n print \\\"Already Selected\\\"\\n return\\n # This line is going to return \\\"DEVICE_LABEL\\\" so you may as well skip it\\n pid_key = \\\"DEVICE_LABEL\\\"\\n self.dev_label.set(\\\"%s (%s)\\\"%(self._uid_dict[uid][pid_key][\\\"label\\\"], uid))\\n self.ola_thread.rdm_get(self.universe.get(), uid, 0, \\\"IDENTIFY_DEVICE\\\", \\n lambda b, s, uid = uid:self._get_identify_complete(uid, b, s))\\n\\n if \\\"SUPPORTED_PARAMETERS\\\" not in self._uid_dict[uid]:\\n self.ola_thread.rdm_get(\\n self.universe.get(), uid, 0, \\\"SUPPORTED_PARAMETERS\\\",\\n lambda b, l, uid = uid:self._get_pids_complete(uid, b, l))\\n else:\\n self._notebook.Update()\\n self.cur_uid = uid\",\n \"def update_selection(self):\\n raise NotImplementedError\",\n \"def _selected_bridge_changed(self, new):\\n if self.bridges[new] is None:\\n bridge_desc_file = os.path.join(BRIDGES_PATH, new + u'.json')\\n bridge = self.load_bridge_info(bridge_desc_file)\\n self.bridges[new] = bridge\\n\\n self.bridge = self.bridges[new]\\n self.channels = [channel for instrument in self.bridge.children\\n for sensor in instrument.children\\n for channel in sensor.children]\",\n \"def set_choices(self):\\n self.check_idxs()\\n np.random.seed()\\n self.choices = np.random.choice(self.running_idxs, self.num_selections)\\n self.running_idxs = np.delete(self.running_idxs, self.choices)\\n self.choices = torch.tensor(self.choices).cuda()\",\n \"def setupDeviceGui(self):\\n\\n dropDowns = list(self.drivers[driver]['uiDriver'] for driver in self.drivers)\\n for dropDown in dropDowns:\\n dropDown.clear()\\n dropDown.setView(PyQt5.QtWidgets.QListView())\\n dropDown.addItem('No device selected')\\n\\n # adding special items\\n self.drivers['dome']['uiDriver'].addItem('INDI')\\n self.drivers['imaging']['uiDriver'].addItem('INDI')\\n self.drivers['sensorWeather']['uiDriver'].addItem('INDI')\\n self.drivers['directWeather']['uiDriver'].addItem('Built-In')\\n self.drivers['onlineWeather']['uiDriver'].addItem('Built-In')\\n self.drivers['cover']['uiDriver'].addItem('INDI')\\n self.drivers['skymeter']['uiDriver'].addItem('INDI')\\n self.drivers['telescope']['uiDriver'].addItem('INDI')\\n self.drivers['power']['uiDriver'].addItem('INDI')\\n self.drivers['relay']['uiDriver'].addItem('Built-In')\\n for app in self.app.astrometry.solverAvailable:\\n self.drivers['astrometry']['uiDriver'].addItem(app)\\n self.drivers['remote']['uiDriver'].addItem('Built-In')\\n self.drivers['measure']['uiDriver'].addItem('Built-In')\\n\\n return True\",\n \"def select(self):\\n if not self._selected:\\n \\tself._selected = True\\n\\t\\tself.log(\\\"device {} is now selected\\\".format(self._secondary_address))\",\n \"def vistrailChanged(self):\\n from vistrails.gui.vistrails_window import _app\\n select_node = True\\n if _app._previous_view and _app._previous_view.window() != self.window():\\n select_node = False\\n self.scene().setupScene(self.controller, select_node)\\n if self.controller and self.controller.reset_version_view:\\n self.scene().fitToAllViews()\\n if self.controller:\\n # self.versionProp.updateVersion(self.controller.current_version)\\n self.versionProp.updateVersion(self.controller.current_version)\\n self.emit(QtCore.SIGNAL(\\\"vistrailChanged()\\\"))\",\n \"def update_dev(self, *args):\\r\\n try:\\r\\n self.localSDK.get_version()\\r\\n except IOError:\\r\\n kT.debug_log('IO Error', sys.exc_info()[2])\\r\\n try:\\r\\n self.newProj.name = self.widgetList[3].get()\\r\\n except IndexError:\\r\\n kT.debug_log('Index Error', sys.exc_info()[2])\\r\\n self.newProj.setKsdkPath(self.localSDK.path)\\r\\n self.newProj.sdkVer = self.localSDK.version\\r\\n\\r\\n if self.advancedDevType.get():\\r\\n\\r\\n self.widgetList[34].state([\\\"!disabled\\\"])\\r\\n\\r\\n ### Widget 7 is the label for the device drop down menu\\r\\n self.widgetList[7].config(text='Board:')\\r\\n\\r\\n try:\\r\\n self.widgetList[31].config(command=lambda: self.begin_advanced_gen(self.master, None))\\r\\n except TclError:\\r\\n kT.debug_log('Tcl Error', sys.exc_info()[2])\\r\\n\\r\\n ### Widget 8 is te drop down menu for the devices\\r\\n self.widgetList[8].config(textvariable=self.advBrdSelect)\\r\\n self.widgetList[8]['values'] = self.localSDK.brdList\\r\\n try:\\r\\n self.widgetList[8].current(int(self.currBoard) - 1)\\r\\n except IOError: ## Catch the case where the user hasn't selected anything\\r\\n self.widgetList[8].current(0)\\r\\n except ValueError: ## Catch the case where there is no device given in manifest\\r\\n self.widgetList[8].current(0)\\r\\n else:\\r\\n try:\\r\\n self.widgetList[34].state([\\\"disabled\\\"])\\r\\n\\r\\n ### Widget 7 is the label for the device drop down menu\\r\\n self.widgetList[7].config(text='Device:')\\r\\n\\r\\n self.widgetList[31].config(command=lambda: self.package_select(self.master))\\r\\n\\r\\n ### Widget 8 is te drop down menu for the devices\\r\\n self.widgetList[8].config(textvariable=self.advDevSelect)\\r\\n self.widgetList[8]['values'] = self.localSDK.devList\\r\\n except IndexError:\\r\\n kT.debug_log('IndexError', sys.exc_info()[2])\\r\\n\\r\\n try:\\r\\n self.newProj.add_board(self.currBoard, self.localSDK.brdList)\\r\\n self.widgetList[8].current(self.localSDK.devList.index(self.newProj.device[0]))\\r\\n except IndexError:\\r\\n kT.debug_log('IndexError', sys.exc_info()[2])\\r\\n except IOError: ## Catch the case where the user hasn't selected anything\\r\\n try:\\r\\n self.widgetList[8].current(0)\\r\\n except IndexError:\\r\\n kT.debug_log('IndexError', sys.exc_info()[2])\\r\\n except ValueError: ## Catch the case where there is no device given in manifest\\r\\n try:\\r\\n self.widgetList[8].current(0)\\r\\n except IndexError:\\r\\n kT.debug_log('Index Error', sys.exc_info()[2])\\r\\n \\r\\n #FIXME Radka add special method for updating path \\r\\n self._update_project_path()\",\n \"def _add_device(self, uid, succeeded, data):\\n # TODO: Bug: on discover the label in the label in the device option menu \\n # doesn't change and if you try to select the first device it tells \\n # you that it is already selected\\n if succeeded:\\n self._uid_dict.setdefault(uid, {})[\\\"DEVICE_LABEL\\\"] = data\\n self.device_menu[\\\"menu\\\"].add_command( label = \\\"%s (%s)\\\"%(\\n self._uid_dict[uid][\\\"DEVICE_LABEL\\\"][\\\"label\\\"], uid), \\n command = lambda:self.device_selected(uid))\\n else:\\n self._uid_dict.setdefault(uid, {})[\\\"DEVICE_LABEL\\\"] = {\\\"label\\\":\\\"\\\"}\\n self.device_menu[\\\"menu\\\"].add_command( label = \\\"%s\\\" % uid, \\n command = lambda:self.device_selected(uid))\\n self._uid_dict[uid][\\\"index\\\"] = self.device_menu[\\\"menu\\\"].index(tk.END)\",\n \"def state_chosen_do(cfg, app, win, events):\",\n \"def img_dict_updated(self, change):\\n if change[\\\"value\\\"]:\\n self.select_dataset(self.io_model.img_dict_default_selected_item)\\n self.init_plot_status()\",\n \"def setupDeviceGui(self):\\n\\n # all dropdown have disabled as capability\\n dropDowns = list(self.drivers[driver]['uiDropDown'] for driver in self.drivers)\\n for dropDown in dropDowns:\\n dropDown.clear()\\n dropDown.setView(PyQt5.QtWidgets.QListView())\\n dropDown.addItem('device disabled')\\n\\n # adding driver items with applicable framework\\n for driver in self.drivers:\\n if not hasattr(self.drivers[driver]['class'], 'run'):\\n continue\\n for framework in self.drivers[driver]['class'].run.keys():\\n self.drivers[driver]['uiDropDown'].addItem(framework)\\n\\n return True\",\n \"def update_selection(self):\\n\\n # clear all boxes\\n self.clear_boxes()\\n self.draw_figure(self.s)\\n\\n # update temperature list\\n if self.Data[self.s]['T_or_MW'] == \\\"T\\\":\\n self.temperatures = np.array(self.Data[self.s]['t_Arai']) - 273.\\n else:\\n self.temperatures = np.array(self.Data[self.s]['t_Arai'])\\n\\n self.T_list = [\\\"%.0f\\\" % T for T in self.temperatures]\\n self.tmin_box.SetItems(self.T_list)\\n self.tmax_box.SetItems(self.T_list)\\n self.tmin_box.SetValue(\\\"\\\")\\n self.tmax_box.SetValue(\\\"\\\")\\n self.Blab_window.SetValue(\\n \\\"%.0f\\\" % (float(self.Data[self.s]['pars']['lab_dc_field']) * 1e6))\\n if \\\"saved\\\" in self.Data[self.s]['pars']:\\n self.pars = self.Data[self.s]['pars']\\n self.update_GUI_with_new_interpretation()\\n self.Add_text(self.s)\\n self.write_sample_box()\",\n \"def update_view(self, selected):\\n pass\",\n \"def update_device_list(self, device_list):\\n self.device_list = device_list\\n\\n self.device_combo.clear()\\n\\n if not device_list:\\n return\\n\\n self.device_combo.addItem(\\\"\\\")\\n\\n active_entry = None\\n\\n for dev in device_list:\\n\\n action_string = \\\"{model:<18} - {contype:<7} - {serial}\\\".format(model=dev.model,\\n contype=dev.device_type,\\n serial=dev.serial)\\n if dev.serial == self.serial:\\n active_entry = action_string\\n self.device_combo.addItem(action_string)\\n\\n if active_entry is not None:\\n self.device_combo.setCurrentText(active_entry)\",\n \"def _selected_labels_changed(self, name, old, new):\\n if self.value_lock.acquire(False):\\n try:\\n self.value = [self._options_dict[name] for name in new]\\n finally:\\n self.value_lock.release()\",\n \"def graphs_change():\\n d = curdoc()\\n _remove_fig(d)\\n _remove_selection(d)\\n graph_val = d.get_model_by_name(GRAPH_SELECTION).value\\n model_id, message_name, model_type = run_handlers.get_modelid_messagename_type(d)\\n props = run_handlers.get_model_properties(model_id, message_name, model_type)\\n\\n if graph_val in [\\\"line\\\", \\\"scatter\\\", \\\"step\\\"]:\\n # never want to plot this special string field\\n field_options = [\\\"{0} : {1}\\\".format(k, props[k]) for k in props if not any(apv in k for apv in [ APV_MODEL ] ) ]\\n xselect = Select(title=\\\"X Axis\\\", value=DEFAULT_UNSELECTED, options=field_options + [DEFAULT_UNSELECTED], name=X_AXIS_SELECTION)\\n yselect = Select(title=\\\"Y Axis\\\", value=DEFAULT_UNSELECTED, options=field_options + [DEFAULT_UNSELECTED], name=Y_AXIS_SELECTION)\\n xselect.on_change('value', lambda attr, old, new: make_2axis_graph())\\n yselect.on_change('value', lambda attr, old, new: make_2axis_graph())\\n d.add_root(column(Div(text=\\\"\\\"), row(widgetbox([xselect]), widgetbox([yselect])), name=FIELD_SELECTION))\\n\\n if graph_val in [\\\"image\\\"]:\\n # alter the field options for known non-image fields\\n field_options = [\\\"{0} : {1}\\\".format(k, props[k]) for k in props if not any(apv in k for apv in [APV_RECVD, APV_SEQNO, APV_MODEL] ) ]\\n imageselect = Select(title=\\\"Image Field\\\", value=DEFAULT_UNSELECTED, options=[DEFAULT_UNSELECTED] + field_options, name=IMAGE_SELECTION)\\n mimeselect = Select(title=\\\"MIME Type\\\", value=DEFAULT_UNSELECTED, options=[DEFAULT_UNSELECTED] + SUPPORTED_MIME_TYPES, name=MIME_SELECTION)\\n imageselect.on_change('value', lambda attr, old, new: image_selection_change())\\n mimeselect.on_change('value', lambda attr, old, new: image_selection_change())\\n d.add_root(column(Div(text=\\\"\\\"), widgetbox([imageselect, mimeselect]), name=IMAGE_MIME_SELECTION))\\n\\n if graph_val in [\\\"table\\\"]:\\n # TODO: limit selectable columns to whose of the same size (table height)\\n # use just the field name; don't show properties in the multi-select box\\n col_options = [k for k in props if not any (apv in k for apv in [APV_RECVD, APV_SEQNO, APV_MODEL] ) ]\\n columnmultiselect = MultiSelect(title=\\\"Columns:\\\", value=[], options=col_options, name=COLUMN_MULTISELECT)\\n columnmultiselect.on_change('value', lambda attr, old, new: column_selection_change())\\n d.add_root(column(Div(text=\\\"\\\"), widgetbox([columnmultiselect]), name=COLUMN_SELECTION))\\n\\n if graph_val in [\\\"raw\\\"]:\\n p = figure(plot_width=500, plot_height=500,\\n background_fill_color=\\\"white\\\",\\n y_range=(-40, 0), title=\\\"\\\", name=FIGURE_MODEL)\\n p.xaxis.visible = False\\n p.yaxis.visible = False\\n sind = run_handlers.get_source_index(d.session_context.id, model_id, message_name)\\n _install_callback_and_cds(sind, model_id, message_name, stream_limit=1)\\n p.text(x='apv_sequence_number',\\n y=0,\\n text='apv_model_as_string',\\n source=d.get_model_by_name(sind),\\n text_font_size=\\\"10pt\\\",\\n text_line_height=0.7,\\n text_baseline=\\\"top\\\",\\n text_align=\\\"left\\\")\\n p.x_range.follow = \\\"end\\\" # don't jam all the data into the graph; \\\"window\\\" it\\n p.x_range.follow_interval = 1 # don't jam all the data into the graph; \\\"window\\\" it\\n p.x_range.range_padding = 0\\n d.add_root(p)\",\n \"def updateAvailablePorts(self):\\n # Build a port list\\n device_list_all = comports()\\n self.device_choices = list()\\n for device in device_list_all:\\n self.device_choices.append(device[0])\\n\\n if len(self.device_choices) < 1:\\n tkinter.messagebox.showerror('No Available Serial Ports','No serial ports are available.')\",\n \"def update(self):\\n self.platform_list.update()\\n self.enemy_list.update()\",\n \"def on_change(self, attr, old, new):\\n n = self.labels.index(new) + 1 # Select 0-indexed\\n self.notify(set_figures(n))\",\n \"def apply_changes(self, updated_talk=None):\\r\\n self.presentationModel.select()\\r\\n self.select_talk(updated_talk)\\r\\n self.update_autocomplete_fields()\",\n \"def modelselec_change():\\n d = curdoc()\\n _remove_fig(d)\\n _remove_selection(d)\\n d.remove_root(d.get_model_by_name(AFTER_MODEL_SELECTION))\\n modelselec = d.get_model_by_name(MODEL_SELECTION)\\n msv = modelselec.value\\n if msv != DEFAULT_UNSELECTED:\\n model_id, message_name, model_type = run_handlers.get_modelid_messagename_type(d)\\n if model_type == \\\"protobuf\\\":\\n message = Select(title=\\\"Message Selection\\\", value=DEFAULT_UNSELECTED, options=list(data.proto_data_structure[model_id][\\\"messages\\\"].keys()) + [DEFAULT_UNSELECTED], name=MESSAGE_SELECTION)\\n graphs = Select(title=\\\"Graph Selection\\\", value=DEFAULT_UNSELECTED, options=[], name=GRAPH_SELECTION)\\n message.on_change('value', lambda attr, old, new: message_change())\\n graphs.on_change('value', lambda attr, old, new: graphs_change())\\n selec = row(widgetbox([message]), widgetbox([graphs]), name=AFTER_MODEL_SELECTION)\\n else: # there is no message selection here\\n graphs = Select(title=\\\"Graph Selection\\\", value=DEFAULT_UNSELECTED, options=GRAPH_OPTIONS, name=GRAPH_SELECTION)\\n graphs.on_change('value', lambda attr, old, new: graphs_change())\\n selec = row(widgetbox([graphs]), name=AFTER_MODEL_SELECTION)\\n d.add_root(selec)\\n d.add_root(selec)\",\n \"def choose_devices(devices, query=False):\\n # Style for selection interface\\n style = style_from_dict({\\n Token.Separator: '#FF00AA',\\n Token.QuestionMark: '#00AAFF bold',\\n Token.Selected: '#00AAFF', # default\\n Token.Pointer: '#00FF00 bold',\\n Token.Instruction: '#FFAA00', # default\\n Token.Answer: '#00AAFF bold',\\n Token.Question: '#FF00AA',\\n })\\n\\n choice_list = []\\n current_type = None\\n name_len = max([len(dev.f_name) for dev in devices]) + 1\\n\\n if query:\\n print('Querying all devices for version numbers. '\\n 'This may take a minute...')\\n choice_list.append(Separator('Name'.center(name_len)\\n + 'Firmware'.center(15)\\n + 'Core'.center(7) + 'State'))\\n for device in devices:\\n if device.type != current_type:\\n current_type = device.type\\n sep_str = ' {} '.format(current_type).center(name_len + 29, '=')\\n choice_list.append(Separator(sep_str))\\n menu_text = device.f_name.ljust(name_len)\\n if query and device.software == 'tasmota':\\n device.query_tas_status()\\n if 'tas_version' in device.reported:\\n menu_text += device.reported['tas_version'].ljust(15)\\n menu_text += device.reported['core_version'].ljust(7)\\n if device.reported['power'] is not None:\\n menu_text += device.reported['power']\\n else:\\n menu_text += 'Offline'\\n choice_list.append({'name': menu_text, 'value': device.f_name})\\n\\n # Ask the user to choose which devices to flash\\n questions = [\\n {\\n 'type': 'checkbox',\\n 'message': 'Select Devices',\\n 'name': 'device_selection',\\n 'choices': choice_list,\\n }\\n ]\\n answers = prompt(questions, style=style)\\n selected_devices = [device for device in devices if device.f_name \\\\\\n in answers['device_selection']]\\n return selected_devices\",\n \"def _selectionChangedSlot(self, _):\\r\\n\\r\\n self._updateButtonStates()\",\n \"def update(self):\\n self.platform_list.update()\\n #self.enemy_list.update()\\n self.enemy_list.update()\\n self.bullet_list.update()\\n self.active_sprite_list.update()\",\n \"def poll_selection(self):\\r\\n osName = platform.system()\\r\\n\\r\\n ## Check if the user changed the KSDK_path\\r\\n try:\\r\\n checkPath = self.widgetList[1].get()\\r\\n if checkPath != self.localSDK.path:\\r\\n self.ask_set_directory(True, 1)\\r\\n\\r\\n ## Check if user updated project name\\r\\n checkName = self.widgetList[4].get()\\r\\n if checkName != self.newProj.name:\\r\\n if kT.check_proj_name(checkName):\\r\\n self.newProj.name = checkName\\r\\n else:\\r\\n self.newProj.name = None\\r\\n if self.prevName != checkName:\\r\\n tkMessageBox.showinfo(\\\"Invalid Project Name\\\",\\\\\\r\\n \\\"No spaces or special characters.\\\")\\r\\n self.prevName = checkName\\r\\n kT.debug_log(\\\"Invalid name\\\")\\r\\n except AttributeError:\\r\\n kT.debug_log(\\\"Basic Changed menu\\\", sys.exc_info()[2])\\r\\n #return\\r\\n\\r\\n try:\\r\\n now = self.widgetList[6].curselection()\\r\\n if now != self.curr:\\r\\n if len(self.widgetList[6].curselection()) > 0:\\r\\n try:\\r\\n self.displayBoard = PhotoImage(data=self.imageList[int(now[0])])\\r\\n except IndexError:\\r\\n kT.debug_log(now[0], sys.exc_info()[2])\\r\\n self.widgetList[8].grid_remove()\\r\\n self.widgetList[8] = Button(self, \\\\\\r\\n image=self.displayBoard, \\\\\\r\\n command=lambda:\\\\\\r\\n self.web_launch(self.localSDK.brdList[\\\\\\r\\n int(self.widgetList[6].curselection()[0])]))\\r\\n self.widgetList[8].image = self.displayBoard\\r\\n self.widgetList[8].grid(row=5, column=3, columnspan=3, sticky=E+W+N+S)\\r\\n self.widgetList[8].bind(\\\"<Enter>\\\", \\\\\\r\\n lambda h: self.update_tips('Is this your board?\\\\n' + \\\\\\r\\n 'If so, ' + \\\\\\r\\n 'then clicking on the board' + \\\\\\r\\n ' image will take you to the ' + \\\\\\r\\n 'board homepage on ' + \\\\\\r\\n 'freescale.com.\\\\n\\\\n'))\\r\\n self.widgetList[8].bind(\\\"<Leave>\\\", \\\\\\r\\n lambda h: self.update_tips(self.defaultHelp))\\r\\n self.curr = now\\r\\n try:\\r\\n self.currBoard = int(self.widgetList[6].curselection()[0]) + 1\\r\\n # Clear out driver list and board\\r\\n self.newProj.board = ()\\r\\n self.newProj.drvList = []\\r\\n # Configure ksdkProj given GUI state\\r\\n self.localSDK.get_version()\\r\\n self.newProj.name = self.widgetList[4].get()\\r\\n self.newProj.setKsdkPath(self.localSDK.path)\\r\\n self.newProj.sdkVer = self.localSDK.version\\r\\n self.newProj.useBSP = not self.localSDK.isNewVersion()\\r\\n except IndexError:\\r\\n self.displayBoard = PhotoImage(data=kImg.boardImages['kds_icon.gif'])\\r\\n self.widgetList[8].config(image=self.displayBoard)\\r\\n self.widgetList[8].image = self.displayBoard\\r\\n self.widgetList[8].config(command=lambda: self.web_launch(kImg.boardImages['NoPreview.gif']))\\r\\n kT.debug_log(\\\"Index Error\\\", sys.exc_info()[2])\\r\\n #return\\r\\n except IndexError:\\r\\n kT.debug_log(\\\"Index Error\\\", sys.exc_info()[2])\\r\\n #return\\r\\n except AttributeError:\\r\\n kT.debug_log(\\\"AttributeError\\\", sys.exc_info()[2])\\r\\n return\\r\\n\\r\\n self._retLoop = self.after(250, self.poll_selection)\",\n \"def update_rec_configs_choice(self):\\n # this will update the configuration choices in reconstruction tab\\n # fill out the config_id choice bar by reading configuration files names\\n self.rec_ids = []\\n for file in os.listdir(os.path.join(self.main_win.experiment_dir, 'conf')):\\n if file.endswith('_config_rec'):\\n self.rec_ids.append(file[0:len(file) - len('_config_rec')])\\n if len(self.rec_ids) > 0:\\n self.rec_id.addItems(self.rec_ids)\\n self.rec_id.show()\",\n \"def update(self):\\n #update checkboxes\\n self.average_check_box.SetValue(self.parent.fftsink.average)\\n self.use_persistence_check_box.SetValue(self.parent.fftsink.use_persistence)\\n self.peak_hold_check_box.SetValue(self.parent.fftsink.peak_hold)\\n #update radio buttons\\n try:\\n index = list(DIV_LEVELS).index(self.parent.fftsink.y_per_div)\\n self.radio_buttons[index].SetValue(True)\\n except: pass\",\n \"def _selection_changed(self, i):\\n\\n # Check if we have disconnected\\n if i < 0:\\n return\\n # First check if we need to stop the old block\\n if self._started_previous and self._previous_config:\\n logger.debug(\\\"Should stop config [%s], stopping!\\\",\\n self._previous_config.name)\\n self._previous_config.delete()\\n\\n # Remove our callback for the previous config\\n if self._previous_config:\\n self._previous_config.data_received_cb.remove_callback(\\n self._log_data_signal_wrapper)\\n self._previous_config.error_cb.remove_callback(\\n self._log_error_signal_wrapper)\\n\\n lg = self._model.get_config(i)\\n if not lg.started:\\n logger.debug(\\\"Config [%s] not started, starting!\\\", lg.name)\\n self._started_previous = True\\n lg.start()\\n else:\\n self._started_previous = False\\n self._plot.removeAllDatasets()\\n color_selector = 0\\n\\n self._plot.set_title(lg.name)\\n\\n self.avgsumvalue = dict();\\n self.avgsumnumb = 0;\\n for d in lg.variables:\\n self._plot.add_curve(d.name, self.colors[\\n color_selector % len(self.colors)])\\n color_selector += 1\\n self.avgsumvalue[d.name]=0;\\n lg.data_received_cb.add_callback(self._log_data_signal_wrapper)\\n lg.error_cb.add_callback(self._log_error_signal_wrapper)\\n\\n self._previous_config = lg\",\n \"def state_choose_do(cfg, app, win, events):\",\n \"def update_selection(self, game, obj):\\n self.clear()\\n if obj:\\n if obj in game.towers:\\n self.selected_tower = obj\\n self.update_selection_tower(self.selected_tower)\\n elif obj in game.monsters:\\n self.selected_monster = obj\\n self.update_selection_monster(self.selected_monster)\\n elif obj in self.monsters_images:\\n self.selected_monster = obj\\n self.update_selection_monster(self.selected_monster, False)\",\n \"def __menu_item_chosen(self, m):\\n # Get selected item\\n self.__selected_robot = m.index\\n\\n # Update the checkboxes/sliders for the selected robot\\n self.__ui_controls.get('chkbox_ref').checked = \\\\\\n self.__robots[self.__selected_robot].ref_shown\\n\\n self.__ui_controls.get('chkbox_rob').checked = \\\\\\n self.__robots[self.__selected_robot].rob_shown\\n\\n self.__ui_controls.get('sld_opc').value = \\\\\\n self.__robots[self.__selected_robot].opacity\",\n \"def _update_gui(self):\\r\\n \\r\\n # Update the RF button.\\r\\n rf_on = self.api.get_output()\\r\\n if rf_on == None: rf_on = True\\r\\n self.button_rf.set_checked(rf_on, block_events=True).enable()\\r\\n \\r\\n # Update the combo; we block first just in case the value doesn't \\\"change\\\"\\r\\n if self.api == None: self.label_instrument_name.set_text('Simulation')\\r\\n else:\\r\\n if self.api.get_mode() == 'Fixed': self.combo_mode.set_value(0, block_events=True).enable()\\r\\n else: self.combo_mode.set_value(1, block_events=True).enable()\\r\\n self._combo_mode_changed()\\r\\n \\r\\n # Update the list plot\\r\\n self.query_list()\",\n \"def gdl_changed(self, signal_name, device_udi, *args):\\n global copiant\\n if not copiant: #If not filecopy started, regenerate partition_list\\n if signal_name==\\\"DeviceAdded\\\":\\n obj = self.bus.get_object(\\\"org.freedesktop.UDisks\\\", device_udi)\\n dev = dbus.Interface(obj, 'org.freedesktop.UDisks.Device')\\n if str(dev.GetPropertyStringList(\\\"info.capabilities\\\")).find(\\\"volume\\\")>=0: #If it's a volume\\n self.llista_particions()\\t#Reload partition list\\n if signal_name==\\\"DeviceRemoved\\\":\\n self.llista_particions()\",\n \"def _after_plot_list_load(self):\\r\\n self.button_send_list.enable()\\r\\n self.label_list_status.set_text('Shown list does not match device list.')\",\n \"def pressSCV(self):\\n\\t\\t\\t\\n\\t\\tm_name = self.ui.findChild(QWidget, \\\"m_name\\\")\\n\\t\\tm_name.setText(\\\"Sensorinen neurografia\\\")\\n\\t\\t\\n\\t\\t\\n\\t\\tprint \\\"SCV button pressed\\\"\\n\\t\\t# Make a database query and draw a graph and distribution\\n\\t\\t\\n\\t\\t# set every checkbox back to the initial state\\n\\t\\t\\n\\t\\tif self.patient_chosen:\\n\\t\\t\\t# Make a database query which fetches the patient's SCV data.\\n\\t\\t\\tprint \\\"showing patient SCV data\\\"\\n\\t\\t\\n\\t\\tself.current_measurement = \\\"SCV\\\"\\t\\n\\t\\treturn\",\n \"def OnButtonClick(self):\\n self.choice()\",\n \"def update_choice(self, value):\\n if self.p is not None:\\n if value == \\\"none\\\":\\n self.other_text.delete('1.0', tk.END)\\n self.other_text.insert('1.0', \\\"\\\")\\n if value == \\\"categories\\\":\\n self.other_text.delete('1.0', tk.END)\\n self.other_text.insert('1.0', self.p.categories)\\n if value == \\\"pageid\\\":\\n self.other_text.delete('1.0', tk.END)\\n self.other_text.insert('1.0', self.p.pageid)\\n if value == \\\"sections\\\":\\n self.other_text.delete('1.0', tk.END)\\n self.other_text.insert('1.0', self.p.sections)\\n if value == \\\"html\\\":\\n self.other_text.delete('1.0', tk.END)\\n self.other_text.insert('1.0', self.p.html())\",\n \"def callback_selectstate(self, attrname, old, new):\\n self._update_chart(self.selectstate.value)\",\n \"def update(self):\\n self.platform_list.update()\\n self.exit_sprite.update()\\n self.bagGroup.update()\\n self.enemy_list.update()\",\n \"def update_variations(self, **kwargs):\\n pass\",\n \"def _selected_label_changed(self, name, old, new):\\n if self.value_lock.acquire(False):\\n try:\\n self.value = self._options_dict[new]\\n finally:\\n self.value_lock.release()\",\n \"def handle_selection_eng(self):\\n choice = self.get_input()\\n if choice == '1':\\n self.login_menu()\\n elif choice == '2':\\n self.authenticate_qr()\\n elif choice == '3':\\n self.authenticate_bluetooth()\\n elif choice == '4':\\n self.is_user = True\\n self.display_main()\",\n \"def select( self ):\\n self._has_change = True\",\n \"def refresh(self):\\n selected = []\\n if not self.__new_service:\\n selected = [str(t.text()) for t in\\n self.__service_list.selectedItems()]\\n\\n self.__service_list.clear()\\n if not self.__show:\\n self.__services = opencue.api.getDefaultServices()\\n else:\\n self.__services = self.__show.getServiceOverrides()\\n\\n for service in self.__services:\\n item = QtWidgets.QListWidgetItem(service.name())\\n self.__service_list.addItem(item)\\n\\n if service.name() in selected:\\n item.setSelected(True)\\n\\n self.__service_list.sortItems()\",\n \"def update(self):\\n self.device = self._api.device_query(self._hardware_address, {})\",\n \"def _channelList_changed(self):\\n self.oscilloscope.visibleChannels = self.channelList\",\n \"def _update_all_devices(self):\\n self.all_devices = []\\n self.all_devices.extend(self.keyboards)\\n self.all_devices.extend(self.mice)\\n self.all_devices.extend(self.gamepads)\\n self.all_devices.extend(self.other_devices)\",\n \"def check_device_changes(self):\\n\\n #---------------------------------------------------------------------------\\n # USB ports\\n current_serial_devices = self.enumerate_serial_devices()\\n\\n for device in self.old_serial_devices:\\n if device not in current_serial_devices:\\n print(\\\"Removed USB port: \\\", device)\\n self.removed_serial_devices.append(device)\\n\\n self.arduino_change_signal.emit('OFF')\\n\\n for device in current_serial_devices:\\n if device not in self.old_serial_devices:\\n print(\\\"Added USB port: \\\", device)\\n self.added_serial_devices.append(device)\\n\\n self.arduino_change_signal.emit('ON')\\n\\n self.old_serial_devices = current_serial_devices\\n\\n #---------------------------------------------------------------------------\\n # MIDI port detection\\n current_midi_devices = self.enumerate_midi_devices()\\n\\n for device in self.old_midi_devices:\\n if device not in current_midi_devices:\\n print(\\\"Removed MIDI port: \\\", device)\\n self.removed_midi_devices.append(device)\\n\\n self.piano_change_signal.emit('OFF')\\n\\n for device in current_midi_devices:\\n if device not in self.old_midi_devices:\\n print(\\\"Added MIDI port: \\\", device)\\n self.added_midi_devices.append(device)\\n\\n self.piano_change_signal.emit('ON')\\n\\n self.old_midi_devices = current_midi_devices\",\n \"def on_update(self, evt):\\n print(evt)\\n for name in self.widgetNames:\\n try:\\n widget = wx.FindWindowByName(name)\\n if isinstance(widget, wx.ComboBox):\\n selection = widget.GetValue()\\n choices = widget.GetItems()\\n choices.insert(0, selection)\\n value = choices\\n else:\\n value = widget.GetValue()\\n\\n data = self.tree.GetPyData(self.current_selection)\\n data['Config'][name] = value\\n self.tree.SetPyData(self.current_selection, data)\\n except Exception as E:\\n logging.error(\\\"{0!s}: {1!s}\\\".format(E, name))\\n raise E\",\n \"def UpdateDisplay(self):\\n ##Jconf\\n self.chJconf.Clear()\\n for name in self.state.GetSurface(\\\"JconfDict\\\").GetNames():\\n self.chJconf.Append(name)\\n self.chJconf.SetStringSelection(self.state.GetSurface(\\\"JconfSelection\\\"))\\n self.chJconf.Enable(self.state.IsEnabled(\\\"JconfDict\\\") == True and\\n self.state.IsEnabled(\\\"JconfSelection\\\") == True and\\n self.state.GetSurface(\\\"Xplorer\\\") == True)\\n self.bEditJconf.Enable(self.state.IsEnabled(\\\"JconfDict\\\") and\\n self.state.GetSurface(\\\"Xplorer\\\") == True)\\n ##Name Server\\n self.cbNameServer.SetValue(self.state.GetSurface(\\\"NameServer\\\"))\\n self.cbNameServer.Enable(self.state.IsEnabled(\\\"NameServer\\\"))\\n ##Conductor\\n self.cbConductor.SetValue(self.state.GetSurface(\\\"Conductor\\\"))\\n self.cbConductor.Enable(self.state.IsEnabled(\\\"Conductor\\\"))\\n ##Xplorer\\n self.cbXplorer.SetValue(self.state.GetSurface(\\\"Xplorer\\\"))\\n self.cbXplorer.Enable(self.state.IsEnabled(\\\"Xplorer\\\"))\\n ##Desktop Mode\\n self.cbDesktop.SetValue(self.state.GetSurface(\\\"DesktopMode\\\"))\\n self.cbDesktop.Enable(self.state.IsEnabled(\\\"DesktopMode\\\"))\\n ##Xplorer Type\\n if self.state.GetSurface(\\\"DesktopMode\\\"):\\n self.rbXplorer.SetSelection(0)\\n else:\\n if (self.state.GetSurface(\\\"XplorerType\\\") == \\\"OSG-VEP\\\"):\\n self.rbXplorer.SetSelection(0)\\n else:\\n self.rbXplorer.SetSelection(1)\\n self.rbXplorer.Enable(self.state.IsEnabled(\\\"XplorerType\\\") == True and\\n self.state.GetSurface(\\\"DesktopMode\\\") == False and\\n self.state.GetSurface(\\\"Xplorer\\\") == True)\\n ##Cluster Node button\\n self.bCluster.Enable(CLUSTER_ENABLED and\\n self.state.GetSurface(\\\"Xplorer\\\") == True and\\n self.state.GetSurface(\\\"DesktopMode\\\") == False and\\n self.state.GetSurface(\\\"XplorerType\\\") == \\\"OSG-VEPC\\\")\\n return\",\n \"def Update(self, mode = UPDATE_MODE.all):\\r\\n aux_versions = dstore.Get(\\\"versions\\\")\\r\\n \\r\\n if(aux_versions['hw'] != None): \\r\\n Ui().lineHwVersion.setText(str(aux_versions['hw'])) \\r\\n else:\\r\\n Ui().lineHwVersion.setText(\\\"- -\\\")\\r\\n \\r\\n if(aux_versions['fw'] != None): \\r\\n Ui().lineFwVersion.setText(str(aux_versions['fw'])) \\r\\n else:\\r\\n Ui().lineFwVersion.setText(\\\"- -\\\") \\r\\n \\r\\n \\r\\n \\r\\n \\\"\\\"\\\" TERMINAL INFO \\\"\\\"\\\"\\r\\n aux_terminal_info = dstore.Get(\\\"terminal_info\\\", \\\"GET\\\")\\r\\n \\r\\n \\\"\\\"\\\" number of cells \\\"\\\"\\\"\\r\\n if(aux_terminal_info['number_of_cells'] != None):\\r\\n Ui().lineCells.setText(str(aux_terminal_info['number_of_cells'])) \\r\\n else:\\r\\n Ui().lineCells.setText(\\\"-\\\") \\r\\n \\r\\n \\r\\n \\\"\\\"\\\" battery \\\"\\\"\\\"\\r\\n if(aux_terminal_info['battery'] != None):\\r\\n Ui().lineBattery.setText(str(aux_terminal_info['battery'])+\\\" %\\\") \\r\\n else:\\r\\n Ui().lineBattery.setText(\\\"-- %\\\") \\r\\n \\r\\n \\\"\\\"\\\" speaker \\\"\\\"\\\" \\r\\n if(aux_terminal_info['speaker']['keys'] == True):\\r\\n Ui().lineSpeakerKeys.setText(\\\"ON\\\")\\r\\n Ui().pushSpeakerKeys.setText(\\\"OFF\\\")\\r\\n Ui().pushSpeakerKeys.setEnabled(True)\\r\\n Ui().pushSpeakerSystem.setEnabled(True)\\r\\n Ui().pushSpeakerTiming.setEnabled(True)\\r\\n elif(aux_terminal_info['speaker']['keys'] == False):\\r\\n Ui().lineSpeakerKeys.setText(\\\"OFF\\\")\\r\\n Ui().pushSpeakerKeys.setText(\\\"ON\\\")\\r\\n Ui().pushSpeakerKeys.setEnabled(True)\\r\\n Ui().pushSpeakerSystem.setEnabled(True)\\r\\n Ui().pushSpeakerTiming.setEnabled(True)\\r\\n else:\\r\\n Ui().lineSpeakerKeys.setText(\\\"- -\\\")\\r\\n Ui().pushSpeakerKeys.setText(\\\"- -\\\")\\r\\n \\r\\n if(aux_terminal_info['speaker']['system'] == True):\\r\\n Ui().lineSpeakerSystem.setText(\\\"ON\\\")\\r\\n Ui().pushSpeakerSystem.setText(\\\"OFF\\\")\\r\\n Ui().pushSpeakerSystem.setEnabled(True)\\r\\n elif(aux_terminal_info['speaker']['system'] == False):\\r\\n Ui().lineSpeakerSystem.setText(\\\"OFF\\\")\\r\\n Ui().pushSpeakerSystem.setText(\\\"ON\\\")\\r\\n Ui().pushSpeakerSystem.setEnabled(True)\\r\\n else:\\r\\n Ui().lineSpeakerSystem.setText(\\\"- -\\\")\\r\\n Ui().pushSpeakerSystem.setText(\\\"- -\\\")\\r\\n Ui().pushSpeakerSystem.setEnabled(False)\\r\\n \\r\\n if(aux_terminal_info['speaker']['timing'] == True):\\r\\n Ui().lineSpeakerTiming.setText(\\\"ON\\\")\\r\\n Ui().pushSpeakerTiming.setText(\\\"OFF\\\")\\r\\n Ui().pushSpeakerTiming.setEnabled(True)\\r\\n elif(aux_terminal_info['speaker']['timing'] == False):\\r\\n Ui().lineSpeakerTiming.setText(\\\"OFF\\\")\\r\\n Ui().pushSpeakerTiming.setText(\\\"ON\\\")\\r\\n Ui().pushSpeakerTiming.setEnabled(True)\\r\\n else: \\r\\n Ui().lineSpeakerTiming.setText(\\\"- -\\\")\\r\\n Ui().pushSpeakerTiming.setText(\\\"- -\\\")\\r\\n Ui().pushSpeakerTiming.setEnabled(False)\\r\\n \\r\\n if(aux_terminal_info['speaker']['keys'] == None or aux_terminal_info['speaker']['timing']==None or aux_terminal_info['speaker']['system']==None): \\r\\n Ui().pushSpeakerKeys.setEnabled(False)\\r\\n Ui().pushSpeakerSystem.setEnabled(False)\\r\\n Ui().pushSpeakerTiming.setEnabled(False)\\r\\n else:\\r\\n Ui().pushSpeakerKeys.setEnabled(True)\\r\\n Ui().pushSpeakerSystem.setEnabled(True)\\r\\n Ui().pushSpeakerTiming.setEnabled(True)\\r\\n \\r\\n \\r\\n return True\",\n \"def update_plot_det_items(self,param):\\n items=param.value()['selected']\\n self.settings.child('scan_options', 'plot_from').setOpts(limits=items)\",\n \"def ChannelSelect(self):\\n self.active_mode = 'default'\\n self.reset_buttons()\\n # Dialog to choose channels from specific brain regions\\n w = SelectChannelsDialog(\\n stringlist=self.model.all_regions,\\n checked=self.model.regions_mask\\n )\\n all_locs = self.model.electrodes_table['location'][self.model.electrical_series_channel_ids]\\n self.model.channels_mask = np.zeros(len(all_locs))\\n for loc in w.choices:\\n self.model.channels_mask += all_locs == np.array(loc)\\n # Indices of channels from chosen regions\\n self.model.channels_mask_ind = np.where(self.model.channels_mask)[0]\\n self.model.n_channels_total = len(self.model.channels_mask_ind)\\n # Reset channels span control\\n self.model.lastCh = np.minimum(16, self.model.n_channels_total)\\n self.model.firstCh = 1\\n self.model.nChToShow = self.model.lastCh - self.model.firstCh + 1\\n self.qline0.setText(str(self.model.lastCh))\\n self.qline1.setText(str(self.model.firstCh))\\n # Update signals plot\\n self.model.selectedChannels = self.model.channels_mask_ind[self.model.firstCh - 1:self.model.lastCh]\\n self.model.refreshScreen()\",\n \"def handle_selection_main(self):\\n choice = self.get_input()\\n if choice == '1':\\n self.display_cust()\\n elif choice == '2':\\n self.is_user = False\\n self.display_eng()\",\n \"def update(self):\\n self.device.update()\",\n \"def update(self):\\n self.device.update()\",\n \"def choices(self, choices):\\n\\n self._choices = choices\",\n \"def change(self):\\r\\n\\r\\n # If checkboxes are available, check status and set boat speed reference line visibility accordingly.\\r\\n if self.cb:\\r\\n if self.cb_bt.checkState() == QtCore.Qt.Checked:\\r\\n for item in self.bt:\\r\\n item.set_visible(True)\\r\\n else:\\r\\n for item in self.bt:\\r\\n item.set_visible(False)\\r\\n # GGA\\r\\n if self.cb_gga.checkState() == QtCore.Qt.Checked:\\r\\n for item in self.gga:\\r\\n item.set_visible(True)\\r\\n # self.gga[0].set_visible(True)\\r\\n elif self.gga is not None:\\r\\n for item in self.gga:\\r\\n item.set_visible(False)\\r\\n # self.gga[0].set_visible(False)\\r\\n # VTG\\r\\n if self.cb_vtg.checkState() == QtCore.Qt.Checked:\\r\\n for item in self.vtg:\\r\\n item.set_visible(True)\\r\\n # self.vtg[0].set_visible(True)\\r\\n elif self.vtg is not None:\\r\\n for item in self.vtg:\\r\\n item.set_visible(False)\\r\\n # self.vtg[0].set_visible(False)\\r\\n\\r\\n # Draw canvas\\r\\n self.canvas.draw()\",\n \"def update(self):\\n # If the game is not over.\\n if self.tictactoe:\\n # If the player is human, the choice can only be detected by the game,\\n # because the player has no responsibility over the window\\n if self.player.chooser:\\n choice = self.choice\\n self.choice = None\\n else:\\n choice = self.player.play(self.tictactoe)\\n self.tictactoe.choose(choice)\\n else:\\n if self.on:\\n self.end_time = time.time()\\n self.on = False\\n if self.restart_at_end:\\n if time.time() - self.end_time > self.end_duration:\\n self.restart()\",\n \"def choose(self, choice):\\n if self.available(choice):\\n self.select(choice)\",\n \"def pressMCV(self):\\n\\t\\t\\n\\t\\tm_name = self.ui.findChild(QWidget, \\\"m_name\\\")\\n\\t\\tm_name.setText(\\\"Motorinen neurografia\\\")\\n\\t\\t\\n\\t\\tprint \\\"MCV button pressed\\\"\\t\\t\\n\\t\\t# update graph and distribution\\n\\t\\t# o set parameters to defaults (length, sd, medianus T)\\n\\t\\t# o clear regression checkbox\\n\\t\\t# o draw the MCV verrokki graph and distribution (set graph as default tab)\\n\\t\\t\\n\\t\\t# set comboboxes back to the default state \\n\\t\\t# Default: summary of the patient MCV data\\n\\t\\tif self.patient_chosen:\\n\\t\\t\\tprint \\\"showing patient MCV data\\\"\\t\\t\\n\\t\\t\\n\\t\\tself.current_measurement = \\\"MCV\\\"\\n\\t\\treturn\",\n \"def evo_selected(self):\\n pub.sendMessage(\\\"EVO_SELECTED\\\", id=self.id, location=self.location)\",\n \"def onSelected(self):\\n pass\",\n \"def update_change(self):\\n self.meas_selected_number = self.__input_meas.value()\\n self.meas_selected_series = self.__input_series.value()\\n self.selected_data = self.__input_select.value()\\n self.noice_reduction_number = self.__input_noice.value()\\n self.particle_size_number = self.__input_p_size.value()\\n self.particle_density_number = self.__input_p_density.value()\\n self.saturation_percentage = self.__input_saturation_percentage.value()\\n\\n # print(\\\"Selected series:\\\", self.meas_selected_series)\\n # print(\\\"Selected measurement:\\\", self.meas_selected_number)\\n\\n if not 1 <= self.meas_selected_number <= 17: # In series 2 there's measurement 0, but that's a copy of the 8th\\n raise ValueError\\n if self.noice_reduction_number < 0:\\n raise ValueError\\n if self.particle_size_number <= 0:\\n raise ValueError\\n if self.particle_density_number < 0:\\n raise ValueError\\n if not 0 <= self.saturation_percentage <= 100:\\n raise ValueError\\n\\n meas_index = self.meas_selected_number - 1\\n if self.meas_selected_series == 1:\\n self.measurement = self.meas_pressure[meas_index]\\n elif self.meas_selected_series == 2:\\n self.measurement = self.meas_mixture[meas_index]\\n else:\\n raise ValueError\\n\\n if self.selected_data == 1:\\n self.data = toolbox_2.remove_noise(self.measurement.p_diff, self.noice_reduction_number)\\n elif self.selected_data == 2:\\n self.data = toolbox_2.remove_noise(self.measurement.p_abs, self.noice_reduction_number)\\n elif self.selected_data == 3:\\n self.data = toolbox_2.remove_noise(\\n toolbox_2.flip_and_normalize(self.measurement.ext), self.noice_reduction_number)\\n self.plot_zoom.setYRange(-0.1, 1, padding=0)\\n elif self.selected_data == 4:\\n self.data = toolbox_2.remove_noise(self.measurement.ext, self.noice_reduction_number)\\n else:\\n raise ValueError\\n\\n self.index_of_drop = toolbox_2.find_drop_index(self.measurement.p_diff)\\n # time vector starts from the beginning of pressure drop\\n time = self.measurement.time - self.measurement.time[self.index_of_drop]\\n\\n self.update_distribution()\\n\\n if self.first_update:\\n self.curve_select = self.plot_select.plot(time, self.data)\\n self.curve_zoom = self.plot_zoom.plot(self.measurement.time, self.data)\\n self.curve_simulate = self.plot_zoom.plot(pen=pg.mkPen((100, 255, 200)))\\n\\n self.curve_distribution_cumulative = self.plot_distribution.plot(\\n pen=pg.mkPen((100, 200, 255)),\\n name=\\\"´ Kumulatiivinen pitoisuus\\\",\\n symbolBrush=(80, 160, 201), symbolPen='w')\\n self.curve_distribution = self.plot_distribution.plot(\\n name=\\\"Pitoisuusjakauma\\\", symbolBrush=(50, 50, 255), symbolPen='w')\\n self.curve_rotatometer = self.plot_rotatometer.plot(\\n name=\\\"Mitattu pitoisuus\\\", symbolBrush=(50, 50, 255), symbolPen='w')\\n self.curve_rotatometer_fit = self.plot_rotatometer.plot(\\n pen=pg.mkPen((100, 255, 200)), name=\\\"´ Ideaalinen pitoisuus\\\")\\n\\n self.first_update = False\\n else:\\n self.curve_select.setData(time, self.data)\\n self.curve_zoom.setData(time, self.data)\\n\\n self.curve_distribution.setData(self.particle_distribution_x, self.particle_distribution_y*1e-10)\\n self.curve_distribution_cumulative.setData(self.smallest_particles, self.number_counts*1e-10)\\n self.curve_rotatometer.setData(np.array([4, 6, 8, 10, 12, 14, 16, 18]), self.number_counts_2*1e-10)\\n x = np.linspace(3.5, 20, 100)\\n self.curve_rotatometer_fit.setData(x, self.number_counts_2[0]*4*(1/x)*1e-10)\\n\\n if self.simulate_bool:\\n self.simulation()\\n\\n self.set_labels()\\n\\n # set the graphs to the point of pressure drop, units are in seconds\\n self.plot_select.setXRange(-2, 4, padding=0)\\n self.plot_zoom.setXRange(0, 0.3, padding=0)\\n self.line.setX(0.1)\\n\\n self.update_zoom_region()\\n # self.update_zoom_plot()\",\n \"def _update_model(self, idx):\\n self._wfield.update(self._choices[idx][0])\",\n \"def _update_device_types(self):\\n device_types = self.adapter.device_types()\\n for device_type in device_types.items:\\n key = device_type.id\\n self._make_up_to_date('/device_types', key, device_type)\",\n \"def selectionChanged(self, selected, deselected):\\n rows = [self.model.nodeFromIndex(row) for row in self.selmod1.selectedRows()]\\n self.updateStats(rows)\",\n \"def async_update_device(self) -> None:\",\n \"def _on_selection_changed(self, selection):\\n if self._updating_selection:\\n return\\n\\n self._updating_selection = True\\n\\n self._tree_selection.unselect_all()\\n for widget in selection:\\n gadget_iter = self._find_iter_by_widget(widget)\\n if gadget_iter:\\n select_iter(self._tree_view, gadget_iter)\\n\\n self._updating_selection = False\",\n \"def switch_arrangment(self, new_arrangment):\\n #Clear Figures to avoid memory leak\\n for figure in self.figures:\\n figure.clear()\\n plt.close(figure)\\n \\n #Close the exisiting display\\n self.destroy()\\n \\n #Generate user interface\\n UI = SD_UI(tuning = self.tuning_flag,\\n location = self.location,\\n language = self.language,\\n arrangment = new_arrangment)\\n \\n #Run the new user interface\\n UI.mainloop()\",\n \"def choice_changed(self, seg, name):\\n section, option = name\\n v = seg.segments[seg.selected_index]\\n _stash.config.set(section, option, v)\\n self.save()\",\n \"def updateSGProDeviceNameList(self, deviceNames):\\n self.ui.sgproDeviceList.clear()\\n self.ui.sgproDeviceList.setView(QListView())\\n for deviceName in deviceNames:\\n self.ui.sgproDeviceList.addItem(deviceName)\\n return True\",\n \"def update(self):\\n self._device = self._geizhals.parse()\",\n \"def __init__(self, hass: HomeAssistant, client: VisonicClient, visonic_device: PySensorDevice):\\n SelectEntity.__init__(self)\\n #_LOGGER.debug(\\\"Creating select entity for %s\\\",visonic_device.getDeviceName())\\n self.hass = hass\\n self._client = client\\n self._visonic_device = visonic_device\\n self._panel = client.getPanelID()\\n if self._panel > 0:\\n self._name = \\\"visonic_p\\\" + str(self._panel) + \\\"_\\\" + visonic_device.getDeviceName().lower()\\n else:\\n self._name = \\\"visonic_\\\" + visonic_device.getDeviceName().lower()\\n self._is_available = self._visonic_device.isEnrolled()\\n self._is_armed = not self._visonic_device.isBypass()\\n self._pending_state_is_armed = None\\n self._dispatcher = client.getDispatcher()\",\n \"def _update_selection(self, qindex1, qindex2):\\n m = self.model()\\n self._do_select(m.qindex2index(qindex1), m.qindex2index(qindex2))\",\n \"def onSelect_specimen(self, event):\\n new_s = self.specimens_box.GetValue()\\n if self.select_specimen(new_s):\\n self.update_selection()\\n else:\\n self.specimens_box.SetValue(self.s)\\n self.user_warning(\\n \\\"no specimen %s reverting to old specimen %s\\\" % (new_s, self.s))\",\n \"def modify_devices(self):\\n\\n for i in self._nodes.items():\\n node = i[1]\\n devices = node[\\\"devices\\\"]\\n other_devices = devices[\\\"other_devices\\\"]\\n kernel_devices = devices[\\\"kernel_devices\\\"]\\n dpdk_devices = devices[\\\"dpdk_devices\\\"]\\n\\n if other_devices:\\n self._modify_other_devices(\\n node, other_devices, kernel_devices, dpdk_devices\\n )\\n\\n # Get the devices again for this node\\n self._get_device(node)\\n devices = node[\\\"devices\\\"]\\n kernel_devices = devices[\\\"kernel_devices\\\"]\\n dpdk_devices = devices[\\\"dpdk_devices\\\"]\\n\\n klen = len(kernel_devices)\\n if klen > 0:\\n print(\\\"\\\\nThese devices are safe to be used with VPP.\\\\n\\\")\\n VppPCIUtil.show_vpp_devices(kernel_devices)\\n question = (\\n \\\"\\\\nWould you like to use any of these \\\" \\\"device(s) for VPP [y/N]? \\\"\\n )\\n answer = self._ask_user_yn(question, \\\"n\\\")\\n if answer == \\\"y\\\":\\n vppd = {}\\n for dit in kernel_devices.items():\\n dvid = dit[0]\\n device = dit[1]\\n question = \\\"Would you like to use device {} \\\".format(dvid)\\n question += \\\"for VPP [y/N]? \\\"\\n answer = self._ask_user_yn(question, \\\"n\\\")\\n if answer == \\\"y\\\":\\n vppd[dvid] = device\\n for dit in vppd.items():\\n dvid = dit[0]\\n device = dit[1]\\n if (\\n \\\"unused\\\" in device\\n and len(device[\\\"unused\\\"]) != 0\\n and device[\\\"unused\\\"][0] != \\\"\\\"\\n ):\\n driver = device[\\\"unused\\\"][0]\\n question = \\\"Would you like to bind the driver {} for {} [y/N]? \\\".format(\\n driver, dvid\\n )\\n answer = self._ask_user_yn(question, \\\"n\\\")\\n if answer == \\\"y\\\":\\n logging.debug(\\n \\\"Binding device {} to driver {}\\\".format(\\n dvid, driver\\n )\\n )\\n ret = VppPCIUtil.bind_vpp_device(node, driver, dvid)\\n if ret:\\n logging.debug(\\n \\\"Could not bind device {}\\\".format(dvid)\\n )\\n dpdk_devices[dvid] = device\\n del kernel_devices[dvid]\\n\\n dlen = len(dpdk_devices)\\n if dlen > 0:\\n print(\\\"\\\\nThese device(s) are already using DPDK.\\\\n\\\")\\n VppPCIUtil.show_vpp_devices(dpdk_devices, show_interfaces=False)\\n question = \\\"\\\\nWould you like to remove any of \\\"\\n question += \\\"these device(s) [y/N]? \\\"\\n answer = self._ask_user_yn(question, \\\"n\\\")\\n if answer == \\\"y\\\":\\n vppdl = {}\\n for dit in dpdk_devices.items():\\n dvid = dit[0]\\n device = dit[1]\\n question = \\\"Would you like to remove {} [y/N]? \\\".format(dvid)\\n answer = self._ask_user_yn(question, \\\"n\\\")\\n if answer == \\\"y\\\":\\n vppdl[dvid] = device\\n for dit in vppdl.items():\\n dvid = dit[0]\\n device = dit[1]\\n if (\\n \\\"unused\\\" in device\\n and len(device[\\\"unused\\\"]) != 0\\n and device[\\\"unused\\\"][0] != \\\"\\\"\\n ):\\n driver = device[\\\"unused\\\"][0]\\n logging.debug(\\n \\\"Binding device {} to driver {}\\\".format(dvid, driver)\\n )\\n ret = VppPCIUtil.bind_vpp_device(node, driver, dvid)\\n if ret:\\n logging.debug(\\\"Could not bind device {}\\\".format(dvid))\\n else:\\n kernel_devices[dvid] = device\\n del dpdk_devices[dvid]\\n\\n interfaces = {}\\n for dit in dpdk_devices.items():\\n dvid = dit[0]\\n device = dit[1]\\n VppPCIUtil.vpp_create_interface(interfaces, dvid, device)\\n node[\\\"interfaces\\\"] = interfaces\\n\\n self._update_auto_config()\\n self.updateconfig()\",\n \"def on_feature_choice(self, event):\\n\\n self.log.trace(\\\"Handle feature selection by user.\\\")\\n result = {'successful': False}\\n\\n try:\\n # determine feature selected\\n module_name=None\\n if not self.custom_module: module_name = self.input_module.GetString(self.input_module.GetSelection())\\n feature_name = event.GetString()\\n\\n self.story_choices = []\\n for selection in DEFAULT_SEL:\\n self.story_choices.append(selection)\\n if feature_name.lower() == CUSTOM_SEL.lower():\\n # set custom flag\\n self.custom_feature = True\\n # show custom input\\n self.input_custom_feature.Show()\\n else:\\n # clear custom flag\\n self.custom_feature = False\\n # make sure custom field is hidden\\n self.input_custom_feature.Hide()\\n if feature_name.lower() != BLANK_SEL.lower():\\n # return all features for module\\n self.log.trace(\\\"Rebuilding user story list for %s module ...\\\" % feature_name)\\n stories = \\\\\\n self.database.return_user_stories_for_feature(feature_name, module=module_name)['user stories']\\n\\n # build story list\\n for story in stories:\\n self.story_choices.append(story['name'])\\n\\n # set feature choices to selection\\n self.input_story.SetItems(self.story_choices)\\n self._update_story_input_according_to_custom_feature_flag()\\n self.log.trace(\\\"User Story list for %s feature rebuilt.\\\" % feature_name)\\n\\n # reset test selections\\n self.log.trace(\\\"Reseting test list ...\\\")\\n self.test_choices = []\\n for selection in DEFAULT_SEL:\\n self.test_choices.append(selection)\\n self.input_test.SetItems(self.test_choices)\\n self._update_test_input_according_to_custom_story_flag()\\n self.log.trace(\\\"Test list reset.\\\")\\n\\n # reset testcase selections\\n self.log.trace(\\\"Reseting test case list ...\\\")\\n self.testcase_choices = []\\n for selection in DEFAULT_SEL:\\n self.testcase_choices.append(selection)\\n self.input_testcase.SetItems(self.testcase_choices)\\n self._update_testcase_input_according_to_custom_test_flag()\\n self.log.trace(\\\"Test case list reset.\\\")\\n\\n result['successful'] = True\\n except BaseException, e:\\n self.handle_exception(e, \\\"handle feature selection by user\\\")\\n\\n # return\\n return result\",\n \"def image_selection_change():\\n\\n def return_image(val, model_id, message_name, field_name, mime, sind):\\n \\\"\\\"\\\"Returns a URL resolvable by the probe\\\"\\\"\\\"\\n column_data_source = curdoc().get_model_by_name(sind)\\n index = column_data_source.tags[0]\\n url = \\\"http://{0}/image/\\\".format(_host) + \\\"---\\\".join([model_id, message_name, field_name, mime, sind, str(index)])\\n return url\\n\\n d = curdoc()\\n _remove_fig(d)\\n model_id, message_name, _ = run_handlers.get_modelid_messagename_type(d)\\n image_field = d.get_model_by_name(IMAGE_SELECTION).value.split(\\\" :\\\")[0]\\n mime = d.get_model_by_name(MIME_SELECTION).value\\n\\n if image_field != DEFAULT_UNSELECTED and mime != DEFAULT_UNSELECTED:\\n plot = figure(plot_width=500, plot_height=500, title=\\\"\\\", x_range=Range1d(start=0, end=1), y_range=Range1d(start=0, end=1), name=FIGURE_MODEL)\\n sind = run_handlers.get_source_index(d.session_context.id, model_id, message_name, image_field + mime)\\n\\n _install_callback_and_cds(sind, model_id, message_name,\\n {image_field: [return_image, {\\\"model_id\\\": model_id,\\n \\\"message_name\\\": message_name,\\n \\\"field_name\\\": image_field,\\n \\\"mime\\\": mime,\\n \\\"sind\\\": sind}]},\\n stream_limit=1)\\n plot.image_url(url=image_field, x=0, y=1, h=1, w=1, source=d.get_model_by_name(sind))\\n d.add_root(plot)\",\n \"def update_list_view(self):\\n # Clear the list/tree view.\\n self.list_view.clear()\\n\\n # Find all the selected things in Maya.\\n selected = cmds.ls(selection=True)\\n\\n # For each of the selected things, create a widget item.\\n for thing in selected:\\n item = QtGui.QListWidgetItem(thing)\\n item.setFlags(item.flags() | QtCore.Qt.ItemIsEditable)\\n self.list_view.addItem(item)\\n # Set the flags on the widget item so it is editable.\",\n \"def updateacc(cls):\\n cls.var_1.set('')\\n cls.right_accentry['menu'].delete(0, 'end')\\n\\n # Insert list of new options (tk._setit hooks them up to var)\\n temp = database3.Db03(\\\"\\\", \\\"\\\")\\n new_choices = temp.accounts()\\n for choice in new_choices:\\n cls.right_accentry['menu'].add_command(label=choice, \\\\\\n command=tk._setit(cls.var_1, choice, God.changedacc))\\n try:\\n cls.var_1.set(new_choices[0])\\n except IndexError:\\n cls.var_1.set('None')\\n God.changedacc()\",\n \"def selection_changed(self):\\n self.emit('selection_changed')\",\n \"def on_mount_changed(self, btn):\\n sender = self.sender()\\n if sender == self.ui.radio_smd:\\n self.mdl.cmp.mount = ComponentBase.MOUNT_SMD\\n elif sender == self.ui.radio_tht:\\n self.mdl.cmp.mount = ComponentBase.MOUNT_THT\\n self.refresh_svg_canvas()\",\n \"def updateSelectionArea(self):\\n self.machine.setSelectionArea(self.points,\\n fill='hatch',\\n color=self.machine.color)\\n eventDict = prepareDrawingSignal('drawingProgress',\\n 'polygon',\\n self.points,\\n self.machine.parameters)\\n self.machine.plot.notify(**eventDict)\",\n \"def add_robot(self, robot):\\n # ALTHOUGH THE DOCUMENTATION SAYS THAT MENU CHOICES CAN BE UPDATED,\\n # THE PACKAGE DOES NOT ALLOW IT.\\n # THUS THIS 'HACK' MUST BE DONE TO REFRESH THE UI WITH AN UPDATED LIST\\n\\n # Save the list of robot names\\n new_list = []\\n for name in self.__ui_controls.get('menu_robots').choices:\\n new_list.append(name)\\n # Add the new one\\n new_list.append(robot.name)\\n\\n # Add robot to list\\n self.__robots.append(robot)\\n self.__selected_robot = len(self.__robots) - 1\\n\\n num_options = 4\\n # Add spot for current robot settings\\n self.__teachpanel.append([[0] * num_options] * robot.num_joints)\\n\\n # Add robot joint sliders\\n i = 0\\n for joint in robot.joints:\\n if joint.qlim[0] == joint.qlim[1]:\\n self.__teachpanel[self.__selected_robot][i] = [\\n joint.qlim[0], joint.qlim[1],\\n joint.theta, None]\\n else:\\n string = \\\"{:.2f} rad ({:.2f} deg)\\\".format(\\n joint.theta, degrees(joint.theta))\\n self.__teachpanel[self.__selected_robot][i] = [\\n joint.qlim[0], joint.qlim[1],\\n joint.theta, wtext(text=string)]\\n i += 1\\n\\n # Refresh the caption\\n self.__reload_caption(new_list)\\n\\n # Set it as selected\\n self.__ui_controls.get('menu_robots').index = \\\\\\n len(self.__robots) - 1\\n\\n # Place camera based on robots effective radius * 1.25\\n if robot.robot is not None:\\n radius = sum([abs(link.a) + abs(link.d) for link in robot.robot.links]) * 1.25\\n self.scene.camera.pos = vector(radius, radius, radius) + get_pose_pos(robot.joints[1].get_pose())\\n self.scene.camera.axis = vector(-radius, -radius, -radius)\",\n \"def change_device(self):\\n if self.state.ser:\\n UsbHost.close_port(self.state.ser)\\n device = self.CBDevices.currentText()\\n if device:\\n comport = self.devices[int(device)]\\n self.state.ser = UsbHost.open_port(comport)\\n if not self.state.ser:\\n self.statusbar.showMessage(\\\"Выбранный порт более недоступен. Произведите повторный поиск\\\")\\n return\\n answer: str = self.UsbHost.send_command(self.state.ser, \\\"ping\\\", device)\\n if answer in wrong_answers:\\n error_message(\\\"Выбранный девайс не отвечает\\\")\\n self.statusbar.showMessage(\\\"Выбранный порт более недоступен. Произведите повторный поиск\\\")\\n return\\n self.state.device_id = int(device)\\n self.state.comport = comport\\n self.create_message()\\n self.set_controls_state(True)\\n self.BtnL1.click()\\n self.BtnAttenuate.click()\\n self.SpinDACValue.setValue(35000)\\n self.BtnSetDACValue.click()\\n self.set_sw(\\\"0 1\\\")\",\n \"def recognize(self):\\n from datetime import datetime\\n from RecognitionDialog import QRecognitionDialog\\n\\n # save alarm\\n self.save_alarm_enable(False)\\n\\n app_doc_data = AppDocData.instance()\\n current_drawing, currentPid = None, None\\n\\n if self.graphicsView.hasImage():\\n current_drawing = app_doc_data.activeDrawing\\n currentPid = app_doc_data.activeDrawing.name\\n\\n # get checked drawings\\n drawing_top = self.treeWidgetDrawingList.topLevelItem(0)\\n count = drawing_top.childCount()\\n checked_drawings = {}\\n for idx in range(count):\\n child = drawing_top.child(idx)\\n if child.checkState(0) == Qt.Checked and child.data(Qt.UserRole, 0):\\n checked_drawings[child.data(Qt.UserRole, 0)] = child\\n # up to here\\n\\n # if there is no checked drawing\\n if current_drawing and currentPid and not checked_drawings:\\n for idx in range(count):\\n child = drawing_top.child(idx)\\n if child.data(Qt.UserRole, 0) is current_drawing:\\n checked_drawings[child.data(Qt.UserRole, 0)] = child\\n\\n if not checked_drawings:\\n self.showImageSelectionMessageBox()\\n return\\n\\n try:\\n self.onClearLog()\\n dlg = QRecognitionDialog(self, [drawing for drawing in checked_drawings.keys()])\\n dlg.exec_()\\n\\n if current_drawing and current_drawing in checked_drawings.keys() and dlg.isTreated:\\n self.open_image_drawing(current_drawing, force=True)\\n\\n # save working date-time\\n _now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')\\n for drawing, tree_item in checked_drawings.items():\\n drawing.datetime = _now\\n tree_item.setText(1, _now)\\n #app_doc_data.saveDrawings(checked_drawings.keys())\\n self.changeViewCheckedState(True)\\n # up to here\\n except Exception as ex:\\n message = 'error occurred({}) in {}:{}'.format(repr(ex), sys.exc_info()[-1].tb_frame.f_code.co_filename,\\n sys.exc_info()[-1].tb_lineno)\\n self.addMessage.emit(MessageType.Error, message)\\n\\n # save alarm\\n self.save_alarm_enable(True)\",\n \"def set_current(idx):\\n\\n dev_dict = {dev.uuid: dev for dev in G.DEVICE_LIST}\\n if idx in dev_dict:\\n current_dev = dev_dict[idx]\\n elif isinstance(idx, int) and idx < len(G.DEVICE_LIST):\\n current_dev = G.DEVICE_LIST[idx]\\n else:\\n raise IndexError(\\\"device idx not found in: %s or %s\\\" % (\\n list(dev_dict.keys()), list(range(len(G.DEVICE_LIST)))))\\n G.DEVICE = current_dev\",\n \"def setDisplayChoice(self, settings: ghidra.docking.settings.Settings, choice: unicode) -> None:\\n ...\",\n \"def _updateSelectedItem(self):\\n plot = self.plot\\n if plot is not None:\\n selected = plot.selection().getSelectedItems()\\n # Give priority to image over scatter\\n for klass in (items.ImageBase, items.Scatter):\\n for item in selected:\\n if isinstance(item, klass):\\n # Found a matching item, use it\\n self.getHistogramWidget().setItem(item)\\n return\\n self.getHistogramWidget().setItem(None)\",\n \"def _update_hardware_control_from_gui(self):\\n self._under_hardware_control = self.widgets['hardware_control'].isChecked()\",\n \"def update_(self):\\n self.update_listbox()\\n self.update_infobox()\\n self.update_statusbar()\\n self.listbox.select_set(0)\\n self.listbox.focus_set()\",\n \"def setChoices(self, choices):\\n self.getGtkObject('property_liststore').clear()\\n for choice in choices:\\n self.getGtkObject('property_liststore').append([str(choice)])\",\n \"def OnSelectionUpdated(self, characterId):\\n pass\",\n \"def update(self, choices, clear=False):\\n if clear:\\n self._weights.clear()\\n self._weights.update(choices)\\n self._generate_p()\",\n \"def onChange(self, event_id: int, datadictionary: dict):\\n #_LOGGER.debug(\\\"Select Sensor onchange %s\\\", str(self._name))\\n # Update the current value based on the device state\\n if self._visonic_device is not None:\\n self._is_available = self._visonic_device.isEnrolled()\\n self._is_armed = not self._visonic_device.isBypass()\\n else:\\n _LOGGER.debug(\\\"Select on change called but sensor is not defined\\\")\\n\\n if self._pending_state_is_armed is not None and self._pending_state_is_armed == self._is_armed:\\n _LOGGER.debug(\\\"Change Implemented in panel\\\")\\n self._pending_state_is_armed = None\\n\\n # Ask HA to schedule an update\\n self.schedule_update_ha_state(True)\",\n \"def service_changed(self):\\n\\n if self.ui.comboBox_service.currentText() == \\\"Google\\\":\\n self.ui.label_id.setEnabled(False)\\n self.ui.lineEdit_id.setEnabled(False)\\n self.ui.label_key.setEnabled(False)\\n self.ui.lineEdit_key.setEnabled(False)\\n self.ui.label_language.setEnabled(True)\\n self.ui.lineEdit_language.setEnabled(True)\\n self.ui.textEdit_notes.setText(self.google_text)\\n if self.ui.comboBox_service.currentText() == \\\"Microsoft Bing Voice Recognition\\\":\\n self.ui.label_id.setEnabled(False)\\n self.ui.lineEdit_id.setEnabled(False)\\n self.ui.label_key.setEnabled(True)\\n self.ui.lineEdit_key.setEnabled(True)\\n self.ui.label_language.setEnabled(True)\\n self.ui.lineEdit_language.setEnabled(True)\\n self.ui.textEdit_notes.setText(\\\"Bing\\\\nBing Voice Recognition API keys 32-character lowercase hexadecimal strings\\\")\\n if self.ui.comboBox_service.currentText() == \\\"Wit.ai\\\":\\n self.ui.label_id.setEnabled(False)\\n self.ui.lineEdit_id.setEnabled(False)\\n self.ui.label_key.setEnabled(True)\\n self.ui.lineEdit_key.setEnabled(True)\\n self.ui.label_language.setEnabled(False)\\n self.ui.lineEdit_language.setEnabled(False)\\n self.ui.textEdit_notes.setText(\\\"Wit.ai\\\\nWit.ai keys are 32-character uppercase alphanumeric strings\\\")\\n if self.ui.comboBox_service.currentText() == \\\"Houndify\\\":\\n self.ui.label_id.setEnabled(True)\\n self.ui.lineEdit_id.setEnabled(True)\\n self.ui.label_key.setEnabled(True)\\n self.ui.lineEdit_key.setEnabled(True)\\n self.ui.label_language.setEnabled(False)\\n self.ui.lineEdit_language.setEnabled(False)\\n msg = \\\"Houndify\\\\nHoundify client IDs and keys are Base64-encoded strings\\\\n\\\"\\n msg += \\\"www.houndify.com\\\"\\n self.ui.textEdit_notes.setText(msg)\\n if self.ui.comboBox_service.currentText() == \\\"IBM Speech\\\":\\n self.ui.label_id.setEnabled(True)\\n self.ui.lineEdit_id.setEnabled(True)\\n self.ui.label_key.setEnabled(True)\\n self.ui.lineEdit_key.setEnabled(True)\\n self.ui.label_language.setEnabled(True)\\n self.ui.lineEdit_language.setEnabled(True)\\n msg = \\\"IBM Speech to text\\\\n\\\"\\n msg += \\\"usernames are strings of the form XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX\\\\n\\\"\\n msg += \\\"passwords are mixed-case alphanumeric strings\\\"\\n self.ui.textEdit_notes.setText(msg)\",\n \"async def async_step_device(self, user_input=None):\\n if user_input:\\n if user_input[CONF_HOST] == CONF_MANUAL_INPUT:\\n return await self.async_step_configure()\\n\\n for device in self.devices:\\n if device[CONF_HOST] == user_input[CONF_HOST]:\\n self.device_id = device[CONF_DEVICE_ID]\\n self.onvif_config = {\\n CONF_NAME: device[CONF_NAME],\\n CONF_HOST: device[CONF_HOST],\\n CONF_PORT: device[CONF_PORT],\\n }\\n return await self.async_step_configure()\\n\\n discovery = await async_discovery(self.hass)\\n for device in discovery:\\n configured = any(\\n entry.unique_id == device[CONF_DEVICE_ID]\\n for entry in self._async_current_entries()\\n )\\n\\n if not configured:\\n self.devices.append(device)\\n\\n if LOGGER.isEnabledFor(logging.DEBUG):\\n LOGGER.debug(\\\"Discovered ONVIF devices %s\\\", pformat(self.devices))\\n\\n if self.devices:\\n devices = {CONF_MANUAL_INPUT: CONF_MANUAL_INPUT}\\n for device in self.devices:\\n description = f\\\"{device[CONF_NAME]} ({device[CONF_HOST]})\\\"\\n if hardware := device[CONF_HARDWARE]:\\n description += f\\\" [{hardware}]\\\"\\n devices[device[CONF_HOST]] = description\\n\\n return self.async_show_form(\\n step_id=\\\"device\\\",\\n data_schema=vol.Schema({vol.Optional(CONF_HOST): vol.In(devices)}),\\n )\\n\\n return await self.async_step_configure()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68089235","0.59843624","0.5973282","0.5937724","0.5828414","0.58241105","0.5739061","0.56566024","0.56519794","0.5624004","0.5604147","0.5591249","0.55712897","0.5546274","0.5538931","0.54759663","0.54590356","0.54416597","0.54367846","0.54256344","0.54246885","0.5420892","0.5395128","0.53674567","0.5347316","0.5330627","0.5329606","0.53228045","0.53176385","0.5273428","0.5273316","0.52671146","0.52664953","0.5252115","0.52426594","0.52133864","0.51856786","0.5163194","0.51617795","0.51520497","0.5150084","0.5144257","0.5144048","0.5140567","0.51321983","0.51227385","0.5122445","0.5120002","0.5104338","0.51039886","0.50985724","0.50982064","0.50826097","0.5081965","0.50735176","0.50683796","0.50557166","0.50557166","0.50435984","0.50408447","0.50386405","0.5034566","0.5032792","0.50236523","0.5022418","0.50195044","0.5018343","0.5015777","0.501505","0.50132537","0.5013184","0.50101686","0.50076807","0.5007015","0.5003344","0.50004494","0.49985445","0.49848607","0.4976618","0.4966123","0.49655667","0.4957128","0.49544302","0.4947123","0.49434924","0.4941358","0.49389023","0.49357602","0.4933433","0.49288517","0.49201098","0.49157098","0.49152434","0.4913158","0.4911873","0.4902929","0.4902324","0.4899876","0.48933217","0.48907524"],"string":"[\n \"0.68089235\",\n \"0.59843624\",\n \"0.5973282\",\n \"0.5937724\",\n \"0.5828414\",\n \"0.58241105\",\n \"0.5739061\",\n \"0.56566024\",\n \"0.56519794\",\n \"0.5624004\",\n \"0.5604147\",\n \"0.5591249\",\n \"0.55712897\",\n \"0.5546274\",\n \"0.5538931\",\n \"0.54759663\",\n \"0.54590356\",\n \"0.54416597\",\n \"0.54367846\",\n \"0.54256344\",\n \"0.54246885\",\n \"0.5420892\",\n \"0.5395128\",\n \"0.53674567\",\n \"0.5347316\",\n \"0.5330627\",\n \"0.5329606\",\n \"0.53228045\",\n \"0.53176385\",\n \"0.5273428\",\n \"0.5273316\",\n \"0.52671146\",\n \"0.52664953\",\n \"0.5252115\",\n \"0.52426594\",\n \"0.52133864\",\n \"0.51856786\",\n \"0.5163194\",\n \"0.51617795\",\n \"0.51520497\",\n \"0.5150084\",\n \"0.5144257\",\n \"0.5144048\",\n \"0.5140567\",\n \"0.51321983\",\n \"0.51227385\",\n \"0.5122445\",\n \"0.5120002\",\n \"0.5104338\",\n \"0.51039886\",\n \"0.50985724\",\n \"0.50982064\",\n \"0.50826097\",\n \"0.5081965\",\n \"0.50735176\",\n \"0.50683796\",\n \"0.50557166\",\n \"0.50557166\",\n \"0.50435984\",\n \"0.50408447\",\n \"0.50386405\",\n \"0.5034566\",\n \"0.5032792\",\n \"0.50236523\",\n \"0.5022418\",\n \"0.50195044\",\n \"0.5018343\",\n \"0.5015777\",\n \"0.501505\",\n \"0.50132537\",\n \"0.5013184\",\n \"0.50101686\",\n \"0.50076807\",\n \"0.5007015\",\n \"0.5003344\",\n \"0.50004494\",\n \"0.49985445\",\n \"0.49848607\",\n \"0.4976618\",\n \"0.4966123\",\n \"0.49655667\",\n \"0.4957128\",\n \"0.49544302\",\n \"0.4947123\",\n \"0.49434924\",\n \"0.4941358\",\n \"0.49389023\",\n \"0.49357602\",\n \"0.4933433\",\n \"0.49288517\",\n \"0.49201098\",\n \"0.49157098\",\n \"0.49152434\",\n \"0.4913158\",\n \"0.4911873\",\n \"0.4902929\",\n \"0.4902324\",\n \"0.4899876\",\n \"0.48933217\",\n \"0.48907524\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.82246095"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":18682,"cells":{"query":{"kind":"string","value":"Update the frame choices whena new vision is selected."},"document":{"kind":"string","value":"def updateVision(self, *args):\r\n\r\n # Update the list of frame choices and the default frame choice\r\n self._appChoice[\"frame\"] = [choice[0] for choice in self._system[self._appString[\"device\"].get()][self._appString[\"vision\"].get()]]\r\n self._appString[\"frame\"].set(self._appChoice[\"frame\"][0])\r\n\r\n # Delete the old choices fromt the option menu\r\n menu = self._appOption[\"frame\"][\"menu\"]\r\n menu.delete(0, \"end\")\r\n\r\n # Add the new list of choices to the option menu\r\n for string in self._appChoice[\"frame\"]:\r\n menu.add_command(label=string, command=lambda value=string: self._appString[\"frame\"].set(value))"},"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 slider_frames_changed(self):\n\n # Again, please note the difference between indexing and GUI displays.\n index = self.slider_frames.value() - 1\n\n # Differentiate between frame ordering (by quality or chronologically).\n if self.frame_ordering == \"quality\":\n self.frame_index = self.quality_sorted_indices[index]\n self.quality_index = index\n\n else:\n self.frame_index = index\n self.quality_index = self.rank_indices[self.frame_index]\n\n # Adjust the frame list and select the current frame.\n\n self.listWidget.setCurrentRow(index, QtCore.QItemSelectionModel.SelectCurrent)\n\n # Update the image in the viewer.\n self.frame_selector.setPhoto(self.frame_index)\n self.listWidget.setFocus()","def hook_frame_selected(self):","def update_selection(self):\n raise NotImplementedError","def update_selection(self):\n\n # clear all boxes\n self.clear_boxes()\n self.draw_figure(self.s)\n\n # update temperature list\n if self.Data[self.s]['T_or_MW'] == \"T\":\n self.temperatures = np.array(self.Data[self.s]['t_Arai']) - 273.\n else:\n self.temperatures = np.array(self.Data[self.s]['t_Arai'])\n\n self.T_list = [\"%.0f\" % T for T in self.temperatures]\n self.tmin_box.SetItems(self.T_list)\n self.tmax_box.SetItems(self.T_list)\n self.tmin_box.SetValue(\"\")\n self.tmax_box.SetValue(\"\")\n self.Blab_window.SetValue(\n \"%.0f\" % (float(self.Data[self.s]['pars']['lab_dc_field']) * 1e6))\n if \"saved\" in self.Data[self.s]['pars']:\n self.pars = self.Data[self.s]['pars']\n self.update_GUI_with_new_interpretation()\n self.Add_text(self.s)\n self.write_sample_box()","def updateDevice(self, *args):\r\n\r\n # Update the list of vision choices and the default vision choice\r\n self._appChoice[\"vision\"] = [choice[0] for choice in self._system[self._appString[\"device\"].get()]]\r\n self._appString[\"vision\"].set(self._appChoice[\"vision\"][0])\r\n\r\n # Delete the old choices fromt the option menu\r\n menu = self._appOption[\"vision\"][\"menu\"]\r\n menu.delete(0, \"end\")\r\n\r\n # Add the new list of choices to the option menu\r\n for string in self._appChoice[\"vision\"]:\r\n menu.add_command(label=string, command=lambda value=string: self._appString[\"vision\"].set(value))","def _selectionChangedSlot(self, _):\r\n\r\n self._updateButtonStates()","def change_frame(self, frame):\r\n pass","def use_triggered(self):\n\n self.select_items()\n if self.items_selected:\n for index, item in enumerate(self.items_selected):\n index_selected = self.indices_selected[index]\n frame_selected = index_selected + 1\n item.setText(\"Frame %i included\" % frame_selected)\n item.setBackground(self.background_included)\n item.setForeground(QtGui.QColor(0, 0, 0))\n self.index_included[index_selected] = True\n self.frame_selector.setPhoto(self.frame_index)","def _update_gui(self):\r\n \r\n # Update the RF button.\r\n rf_on = self.api.get_output()\r\n if rf_on == None: rf_on = True\r\n self.button_rf.set_checked(rf_on, block_events=True).enable()\r\n \r\n # Update the combo; we block first just in case the value doesn't \"change\"\r\n if self.api == None: self.label_instrument_name.set_text('Simulation')\r\n else:\r\n if self.api.get_mode() == 'Fixed': self.combo_mode.set_value(0, block_events=True).enable()\r\n else: self.combo_mode.set_value(1, block_events=True).enable()\r\n self._combo_mode_changed()\r\n \r\n # Update the list plot\r\n self.query_list()","def accept(self):\n self.selInsts = [x.get() for x in self.selInstsVar]\n self.selParams = [x.get() for x in self.selParamsVar]\n self.updateTitle()\n self.window.grab_release()\n self.window.destroy()\n self.instBoxes = []\n self.paramBoxes = []\n self.subRows = []\n self.selInstsVar = []\n self.selParamsVar = []\n self.addRow = []\n self.instTraces = []","def ChannelSelect(self):\n self.active_mode = 'default'\n self.reset_buttons()\n # Dialog to choose channels from specific brain regions\n w = SelectChannelsDialog(\n stringlist=self.model.all_regions,\n checked=self.model.regions_mask\n )\n all_locs = self.model.electrodes_table['location'][self.model.electrical_series_channel_ids]\n self.model.channels_mask = np.zeros(len(all_locs))\n for loc in w.choices:\n self.model.channels_mask += all_locs == np.array(loc)\n # Indices of channels from chosen regions\n self.model.channels_mask_ind = np.where(self.model.channels_mask)[0]\n self.model.n_channels_total = len(self.model.channels_mask_ind)\n # Reset channels span control\n self.model.lastCh = np.minimum(16, self.model.n_channels_total)\n self.model.firstCh = 1\n self.model.nChToShow = self.model.lastCh - self.model.firstCh + 1\n self.qline0.setText(str(self.model.lastCh))\n self.qline1.setText(str(self.model.firstCh))\n # Update signals plot\n self.model.selectedChannels = self.model.channels_mask_ind[self.model.firstCh - 1:self.model.lastCh]\n self.model.refreshScreen()","def hook_frame_unselected(self):","def update_view(self, selected):\n pass","def __init__(self, parent_gui, configuration, frames, rank_frames, stacked_image_log_file,\n signal_finished):\n\n super(FrameSelectorWidget, self).__init__(parent_gui)\n self.setupUi(self)\n\n # Keep references to upper level objects.\n self.parent_gui = parent_gui\n self.configuration = configuration\n self.stacked_image_log_file = stacked_image_log_file\n self.signal_finished = signal_finished\n self.frames = frames\n self.index_included = frames.index_included.copy()\n self.quality_sorted_indices = rank_frames.quality_sorted_indices\n self.rank_indices = rank_frames.rank_indices\n\n # Start with ordering frames by quality. This can be changed by the user using a radio\n # button.\n self.frame_ordering = \"quality\"\n\n # Initialize the frame list selection.\n self.items_selected = None\n self.indices_selected = None\n\n # Set colors for the frame list.\n self.background_included = QtGui.QColor(130, 255, 130)\n self.foreground_included = QtGui.QColor(0, 0, 0)\n self.background_excluded = QtGui.QColor(120, 120, 120)\n self.foreground_excluded = QtGui.QColor(255, 255, 255)\n\n self.addButton.clicked.connect(self.use_triggered)\n self.removeButton.clicked.connect(self.not_use_triggered)\n\n # Be careful: Indices are counted from 0, while widget contents are counted from 1 (to make\n # it easier for the user.\n self.quality_index = 0\n self.frame_index = self.quality_sorted_indices[self.quality_index]\n\n # Set up the frame selector and put it in the upper left corner.\n self.frame_selector = VideoFrameSelector(self.frames, self.index_included, self.frame_index)\n self.frame_selector.setObjectName(\"frame_selector\")\n self.gridLayout.addWidget(self.frame_selector, 0, 0, 2, 3)\n\n # Initialize the list widget.\n self.fill_list_widget()\n self.listWidget.setSelectionMode(QtWidgets.QAbstractItemView.ExtendedSelection)\n self.listWidget.installEventFilter(self)\n self.listWidget.itemClicked.connect(self.select_items)\n self.listWidget.currentRowChanged.connect(self.synchronize_slider)\n\n # Group widget elements which are to be blocked during player execution in a list.\n self.widget_elements = [self.listWidget,\n self.slider_frames,\n self.addButton,\n self.removeButton,\n self.pushButton_play,\n self.GroupBox_frame_sorting]\n\n # Initialize a variable for communication with the frame_player object later.\n self.run_player = False\n\n # Create the frame player thread and start it. The player displays frames in succession.\n # It is pushed on a different thread because otherwise the user could not stop it before it\n # finishes.\n self.player_thread = QtCore.QThread()\n self.frame_player = FramePlayer(self)\n self.frame_player.moveToThread(self.player_thread)\n self.frame_player.block_widgets_signal.connect(self.block_widgets)\n self.frame_player.unblock_widgets_signal.connect(self.unblock_widgets)\n self.frame_player.set_photo_signal.connect(self.frame_selector.setPhoto)\n self.frame_player.set_slider_value.connect(self.slider_frames.setValue)\n self.frame_player_start_signal.connect(self.frame_player.play)\n self.player_thread.start()\n\n # Initialization of GUI elements\n self.slider_frames.setMinimum(1)\n self.slider_frames.setMaximum(self.frames.number)\n self.slider_frames.setValue(self.quality_index + 1)\n self.radioButton_quality.setChecked(True)\n\n self.gridLayout.setColumnStretch(0, 7)\n self.gridLayout.setColumnStretch(1, 0)\n self.gridLayout.setColumnStretch(2, 0)\n self.gridLayout.setColumnStretch(3, 0)\n self.gridLayout.setColumnStretch(4, 1)\n self.gridLayout.setRowStretch(0, 0)\n self.gridLayout.setRowStretch(1, 0)\n\n # Connect signals with slots.\n self.buttonBox.accepted.connect(self.done)\n self.buttonBox.rejected.connect(self.reject)\n self.slider_frames.valueChanged.connect(self.slider_frames_changed)\n self.pushButton_play.clicked.connect(self.pushbutton_play_clicked)\n self.pushButton_stop.clicked.connect(self.pushbutton_stop_clicked)\n self.radioButton_quality.toggled.connect(self.radiobutton_quality_changed)\n\n if self.configuration.global_parameters_protocol_level > 0:\n Miscellaneous.protocol(\"+++ Start selecting frames +++\", self.stacked_image_log_file)","def radiobutton_quality_changed(self):\n\n # Block listWidget signals. Otherwise, changes to the widget triggered by changing the\n # slider would cause trouble.\n self.listWidget.blockSignals(True)\n\n if self.frame_ordering == \"quality\":\n self.frame_ordering = \"chronological\"\n self.slider_frames.setValue(self.frame_index + 1)\n else:\n self.frame_ordering = \"quality\"\n self.slider_frames.setValue(self.quality_index + 1)\n\n self.fill_list_widget()\n\n # Unblock listWidget signals again.\n self.listWidget.blockSignals(False)","def _selection_changed(self, i):\n\n # Check if we have disconnected\n if i < 0:\n return\n # First check if we need to stop the old block\n if self._started_previous and self._previous_config:\n logger.debug(\"Should stop config [%s], stopping!\",\n self._previous_config.name)\n self._previous_config.delete()\n\n # Remove our callback for the previous config\n if self._previous_config:\n self._previous_config.data_received_cb.remove_callback(\n self._log_data_signal_wrapper)\n self._previous_config.error_cb.remove_callback(\n self._log_error_signal_wrapper)\n\n lg = self._model.get_config(i)\n if not lg.started:\n logger.debug(\"Config [%s] not started, starting!\", lg.name)\n self._started_previous = True\n lg.start()\n else:\n self._started_previous = False\n self._plot.removeAllDatasets()\n color_selector = 0\n\n self._plot.set_title(lg.name)\n\n self.avgsumvalue = dict();\n self.avgsumnumb = 0;\n for d in lg.variables:\n self._plot.add_curve(d.name, self.colors[\n color_selector % len(self.colors)])\n color_selector += 1\n self.avgsumvalue[d.name]=0;\n lg.data_received_cb.add_callback(self._log_data_signal_wrapper)\n lg.error_cb.add_callback(self._log_error_signal_wrapper)\n\n self._previous_config = lg","def select_items(self):\n\n self.listWidget.currentItem().setSelected(True)\n self.items_selected = self.listWidget.selectedItems()\n\n if self.frame_ordering == \"quality\":\n self.indices_selected = [self.quality_sorted_indices[self.listWidget.row(item)] for item\n in self.items_selected]\n self.frame_index = self.indices_selected[0]\n self.quality_index = self.rank_indices[self.frame_index]\n else:\n self.indices_selected = [self.listWidget.row(item) for item in self.items_selected]\n self.frame_index = self.indices_selected[0]\n self.quality_index = self.rank_indices[self.frame_index]\n\n self.synchronize_slider()","def update_species_frames(self):\n pass","def _selected_bridge_changed(self, new):\n if self.bridges[new] is None:\n bridge_desc_file = os.path.join(BRIDGES_PATH, new + u'.json')\n bridge = self.load_bridge_info(bridge_desc_file)\n self.bridges[new] = bridge\n\n self.bridge = self.bridges[new]\n self.channels = [channel for instrument in self.bridge.children\n for sensor in instrument.children\n for channel in sensor.children]","def graphs_change():\n d = curdoc()\n _remove_fig(d)\n _remove_selection(d)\n graph_val = d.get_model_by_name(GRAPH_SELECTION).value\n model_id, message_name, model_type = run_handlers.get_modelid_messagename_type(d)\n props = run_handlers.get_model_properties(model_id, message_name, model_type)\n\n if graph_val in [\"line\", \"scatter\", \"step\"]:\n # never want to plot this special string field\n field_options = [\"{0} : {1}\".format(k, props[k]) for k in props if not any(apv in k for apv in [ APV_MODEL ] ) ]\n xselect = Select(title=\"X Axis\", value=DEFAULT_UNSELECTED, options=field_options + [DEFAULT_UNSELECTED], name=X_AXIS_SELECTION)\n yselect = Select(title=\"Y Axis\", value=DEFAULT_UNSELECTED, options=field_options + [DEFAULT_UNSELECTED], name=Y_AXIS_SELECTION)\n xselect.on_change('value', lambda attr, old, new: make_2axis_graph())\n yselect.on_change('value', lambda attr, old, new: make_2axis_graph())\n d.add_root(column(Div(text=\"\"), row(widgetbox([xselect]), widgetbox([yselect])), name=FIELD_SELECTION))\n\n if graph_val in [\"image\"]:\n # alter the field options for known non-image fields\n field_options = [\"{0} : {1}\".format(k, props[k]) for k in props if not any(apv in k for apv in [APV_RECVD, APV_SEQNO, APV_MODEL] ) ]\n imageselect = Select(title=\"Image Field\", value=DEFAULT_UNSELECTED, options=[DEFAULT_UNSELECTED] + field_options, name=IMAGE_SELECTION)\n mimeselect = Select(title=\"MIME Type\", value=DEFAULT_UNSELECTED, options=[DEFAULT_UNSELECTED] + SUPPORTED_MIME_TYPES, name=MIME_SELECTION)\n imageselect.on_change('value', lambda attr, old, new: image_selection_change())\n mimeselect.on_change('value', lambda attr, old, new: image_selection_change())\n d.add_root(column(Div(text=\"\"), widgetbox([imageselect, mimeselect]), name=IMAGE_MIME_SELECTION))\n\n if graph_val in [\"table\"]:\n # TODO: limit selectable columns to whose of the same size (table height)\n # use just the field name; don't show properties in the multi-select box\n col_options = [k for k in props if not any (apv in k for apv in [APV_RECVD, APV_SEQNO, APV_MODEL] ) ]\n columnmultiselect = MultiSelect(title=\"Columns:\", value=[], options=col_options, name=COLUMN_MULTISELECT)\n columnmultiselect.on_change('value', lambda attr, old, new: column_selection_change())\n d.add_root(column(Div(text=\"\"), widgetbox([columnmultiselect]), name=COLUMN_SELECTION))\n\n if graph_val in [\"raw\"]:\n p = figure(plot_width=500, plot_height=500,\n background_fill_color=\"white\",\n y_range=(-40, 0), title=\"\", name=FIGURE_MODEL)\n p.xaxis.visible = False\n p.yaxis.visible = False\n sind = run_handlers.get_source_index(d.session_context.id, model_id, message_name)\n _install_callback_and_cds(sind, model_id, message_name, stream_limit=1)\n p.text(x='apv_sequence_number',\n y=0,\n text='apv_model_as_string',\n source=d.get_model_by_name(sind),\n text_font_size=\"10pt\",\n text_line_height=0.7,\n text_baseline=\"top\",\n text_align=\"left\")\n p.x_range.follow = \"end\" # don't jam all the data into the graph; \"window\" it\n p.x_range.follow_interval = 1 # don't jam all the data into the graph; \"window\" it\n p.x_range.range_padding = 0\n d.add_root(p)","def on_selection(self, analysis_selection, make_new_analysis):\n landmark_indexes = self.landmark_index_from_selection(\n analysis_selection)\n if self.demo_type == DemoType.HYPERSPECTRAL_DEMO:\n # Pass area influenced to the hyperspectral viewer\n self.data_gui.set_static_mask(\n self.analysis.get_area_of_influence(landmark_indexes))\n\n if make_new_analysis:\n self.make_new_analysis(self.analysis, analysis_selection)\n else:\n if self.demo_type == DemoType.LABELLED_DEMO:\n # Pass data indexes to labelled viewer\n self.data_gui.set_image_indexes(\n self.data_index_from_selection(analysis_selection))","def on_change(self, attr, old, new):\n n = self.labels.index(new) + 1 # Select 0-indexed\n self.notify(set_figures(n))","def img_dict_updated(self, change):\n if change[\"value\"]:\n self.select_dataset(self.io_model.img_dict_default_selected_item)\n self.init_plot_status()","def state_chosen_do(cfg, app, win, events):","def SelectPresentation(self, event):\n pass","def update(self):\r\n\r\n # Update the vision frames in the system\r\n self._system.update()\r\n\r\n # Create blank PIL images to hold the video streams\r\n layered = PIL.Image.new('RGBA', (400, 400))\r\n stacked = PIL.Image.new('RGBA', (200, 800))\r\n control = PIL.Image.new('RGBA', (600, 800))\r\n\r\n focalpoint = self._system[self._appString[\"device\"].get()].focalpoint()\r\n # print(focalpoint)\r\n\r\n # Get each vision key and vision for the selected device\r\n visionList = [(visionKey, vision) for visionKey, vision in self._system[self._appString[\"device\"].get()]]\r\n\r\n # Loop through each vision in the vision list\r\n for i, (visionKey, vision) in enumerate(visionList):\r\n\r\n # Grab the frames from the vision when it is \"curr\"\r\n frameList = [frame for frameKey, frame in vision if frameKey==self._appString[\"frame\"].get()]\r\n\r\n # Loop through each frame in the frame list\r\n for frame in frameList:\r\n\r\n # Get the properties and turn the image into RGBA\r\n ratio, size = vision.properties()\r\n rgbFrame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)\r\n\r\n # print(rgbFrame.shape)\r\n width, height, channels = rgbFrame.shape\r\n\r\n # Paste the images together in layered\r\n\r\n imgFrame = PIL.Image.fromarray(cv2.resize(rgbFrame, (int(400 * ratio), int(400 * ratio))))\r\n layered.paste(imgFrame, (int(200 * (1 - ratio)), int(200 * (1 - ratio))))\r\n\r\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (200 / width)), int(200 * (1 - ratio) - focalpoint[1] * (200 / height))))\r\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (200 // width)), int(200 * (1 - ratio) - focalpoint[1] * (200 // height))))\r\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (ratio ** -1)), int(200 * (1 - ratio) - focalpoint[1] * (ratio ** -1))))\r\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (200/width) / ratio), int(200 * (1 - ratio) - focalpoint[1] * (200/height) / ratio)))\r\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (200 / width)), int(200 * (1 - ratio) - focalpoint[1] * (200 / height))))\r\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (ratio ** -1) / 200), int(200 * (1 - ratio) - focalpoint[1] * (ratio ** -1) / 200)))\r\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (400//width * (1- ratio))), int(200 * (1 - ratio) - focalpoint[1] * (400//height * (1 - ratio)))))\r\n\r\n # Paste the images together in stacked\r\n imgFrame = PIL.Image.fromarray(cv2.resize(rgbFrame, (200, 200)))\r\n stacked.paste(imgFrame, (0, 200 * i))\r\n\r\n # Add the stacked image to the canvas\r\n self._pilFrames[\"stacked\"] = PIL.ImageTk.PhotoImage(image=stacked)\r\n self._appCanvas[\"stacked\"].create_image(100, 0, image=self._pilFrames[\"stacked\"], anchor=tkinter.NW)\r\n\r\n # Add the layered image to the canvas\r\n self._pilFrames[\"layered\"] = PIL.ImageTk.PhotoImage(image=layered)\r\n self._appCanvas[\"layered\"].create_image(0, 0, image=self._pilFrames[\"layered\"], anchor=tkinter.NW)\r\n\r\n # Add the control image to the canvas\r\n imgFrame = cv2.cvtColor(self._system[self._appString[\"device\"].get()][self._appString[\"vision\"].get()][self._appString[\"frame\"].get()], cv2.COLOR_BGR2RGBA)\r\n control = PIL.Image.fromarray(cv2.resize(imgFrame, (600, 600)))\r\n self._pilFrames[\"control\"] = PIL.ImageTk.PhotoImage(image=control)\r\n self._appCanvas[\"control\"].create_image(100, 90, image=self._pilFrames[\"control\"], anchor=tkinter.NW)\r\n\r\n # Continue to update with a delay of 15\r\n self.after(15, self.update)","def launch_GUV_GUI(self):\n for i in self.parameters['selected_series']:\n print(f\"Analysing series {i}\")\n self.stack.bundle_axes = 'yx'\n finderparams = ParameterList(filename=self.parameters['filename'],\n channel=self.parameters['channel'],\n intensity_channel=self.parameters['intensity_channel'],\n pixel_microns=self.parameters['pixel_microns'])\n if self.has_multiple_series:\n self.stack.default_coords['v'] = i\n finderparams.series = i\n GUV_Control(self.stack, finderparams) # launch the GUI that can find GUVs and let the user remove them\n \n self.quit()","def refresh(self):\n\n # Set Graphics scene\n self.setScene(QtGui.QGraphicsScene())\n self._connections = set()\n self._nodes = {}\n self._selection = set()\n self._manipulation_mode = 0\n self._selection_rect = None","def image_selection_change():\n\n def return_image(val, model_id, message_name, field_name, mime, sind):\n \"\"\"Returns a URL resolvable by the probe\"\"\"\n column_data_source = curdoc().get_model_by_name(sind)\n index = column_data_source.tags[0]\n url = \"http://{0}/image/\".format(_host) + \"---\".join([model_id, message_name, field_name, mime, sind, str(index)])\n return url\n\n d = curdoc()\n _remove_fig(d)\n model_id, message_name, _ = run_handlers.get_modelid_messagename_type(d)\n image_field = d.get_model_by_name(IMAGE_SELECTION).value.split(\" :\")[0]\n mime = d.get_model_by_name(MIME_SELECTION).value\n\n if image_field != DEFAULT_UNSELECTED and mime != DEFAULT_UNSELECTED:\n plot = figure(plot_width=500, plot_height=500, title=\"\", x_range=Range1d(start=0, end=1), y_range=Range1d(start=0, end=1), name=FIGURE_MODEL)\n sind = run_handlers.get_source_index(d.session_context.id, model_id, message_name, image_field + mime)\n\n _install_callback_and_cds(sind, model_id, message_name,\n {image_field: [return_image, {\"model_id\": model_id,\n \"message_name\": message_name,\n \"field_name\": image_field,\n \"mime\": mime,\n \"sind\": sind}]},\n stream_limit=1)\n plot.image_url(url=image_field, x=0, y=1, h=1, w=1, source=d.get_model_by_name(sind))\n d.add_root(plot)","def callback_selectstate(self, attrname, old, new):\n self._update_chart(self.selectstate.value)","def on_feature_choice(self, event):\n\n self.log.trace(\"Handle feature selection by user.\")\n result = {'successful': False}\n\n try:\n # determine feature selected\n module_name=None\n if not self.custom_module: module_name = self.input_module.GetString(self.input_module.GetSelection())\n feature_name = event.GetString()\n\n self.story_choices = []\n for selection in DEFAULT_SEL:\n self.story_choices.append(selection)\n if feature_name.lower() == CUSTOM_SEL.lower():\n # set custom flag\n self.custom_feature = True\n # show custom input\n self.input_custom_feature.Show()\n else:\n # clear custom flag\n self.custom_feature = False\n # make sure custom field is hidden\n self.input_custom_feature.Hide()\n if feature_name.lower() != BLANK_SEL.lower():\n # return all features for module\n self.log.trace(\"Rebuilding user story list for %s module ...\" % feature_name)\n stories = \\\n self.database.return_user_stories_for_feature(feature_name, module=module_name)['user stories']\n\n # build story list\n for story in stories:\n self.story_choices.append(story['name'])\n\n # set feature choices to selection\n self.input_story.SetItems(self.story_choices)\n self._update_story_input_according_to_custom_feature_flag()\n self.log.trace(\"User Story list for %s feature rebuilt.\" % feature_name)\n\n # reset test selections\n self.log.trace(\"Reseting test list ...\")\n self.test_choices = []\n for selection in DEFAULT_SEL:\n self.test_choices.append(selection)\n self.input_test.SetItems(self.test_choices)\n self._update_test_input_according_to_custom_story_flag()\n self.log.trace(\"Test list reset.\")\n\n # reset testcase selections\n self.log.trace(\"Reseting test case list ...\")\n self.testcase_choices = []\n for selection in DEFAULT_SEL:\n self.testcase_choices.append(selection)\n self.input_testcase.SetItems(self.testcase_choices)\n self._update_testcase_input_according_to_custom_test_flag()\n self.log.trace(\"Test case list reset.\")\n\n result['successful'] = True\n except BaseException, e:\n self.handle_exception(e, \"handle feature selection by user\")\n\n # return\n return result","def collection_selected(self):\n self.processgraph.set_collection(str(self.collectionBox.currentText()))\n self.reload_processgraph_view()","def update(self):\n #update checkboxes\n self.average_check_box.SetValue(self.parent.fftsink.average)\n self.use_persistence_check_box.SetValue(self.parent.fftsink.use_persistence)\n self.peak_hold_check_box.SetValue(self.parent.fftsink.peak_hold)\n #update radio buttons\n try:\n index = list(DIV_LEVELS).index(self.parent.fftsink.y_per_div)\n self.radio_buttons[index].SetValue(True)\n except: pass","def OnPageChanged(self, page=None, trigger=None):\n if trigger in [\"parm_batch\", \"fit_batch\", \"page_add_batch\",\n \"tab_init\", \"tab_browse\"]:\n return\n # When parent changes\n # This is a necessary function for PyCorrFit.\n # This is stuff that should be done when the active page\n # of the notebook changes.\n if self.parent.notebook.GetPageCount() == 0:\n self.Selector.SelectBox.SetItems([])\n self.Selector.sp.Disable()\n else:\n oldlabels = self.Selector.curvelabels\n self.Selector.sp.Enable()\n # Sticky behavior cleaned up in 0.7.8\n curvedict, labels = self.GetCurvedict()\n self.Selector.curvedict = curvedict\n self.Selector.labels = labels\n self.Selector.ProcessDict()\n self.labels = labels\n if oldlabels != self.Selector.curvelabels:\n self.Selector.SelectBox.SetItems(\n self.Selector.curvelabels)\n for i in np.arange(len(self.Selector.curvekeys)):\n self.Selector.SelectBox.SetSelection(i)\n self.Selector.OnUpdatePlot(trigger=trigger)","def _selected_labels_changed(self, name, old, new):\n if self.value_lock.acquire(False):\n try:\n self.value = [self._options_dict[name] for name in new]\n finally:\n self.value_lock.release()","def _update_frame(self):\n # check if continue\n if self._keep_updating:\n self.__frame = self._cam.get_display_frame()\n if self.__frame is not None:\n self._cvn_camera_viewfinder.create_image(0, 0, image=self.__frame, anchor=tk.NW)\n\n self._root.after(self._delay, self._update_frame)","def OnFrameShow(self):\r\n\r\n\t\t# Update local copy of config\r\n\t\tself._configtmp.update(self._config)\r\n\r\n\t\t# Fix notebook background color when switching themes in XP\r\n\t\tself.notebookApp.SetBackgroundColour(\\\r\n\t\t\tself.notebookApp.GetThemeBackgroundColour())\r\n\r\n\t\t# Set flag\r\n\t\tself.toggleButtonRateFlag.SetValue(self._configtmp[\"flagimage\"])\r\n\r\n\t\t# Set ratings\r\n\t\tself._iconstars = [icons.getGrayStarBitmap(),\r\n\t\t\ticons.getYellowStarBitmap(),\r\n\t\t\ticons.getGrayOrangeStarBitmap(),\r\n\t\t\ticons.getYellowOrangeStarBitmap()]\r\n\t\tself.SetStars()\r\n\r\n\t\t# Set image info\r\n\t\tself.textCtrlImageInfo.Clear()\r\n\t\tself.textCtrlImageInfo.WriteText(self._configtmp[\"imageinfo\"])\r\n\r\n\t\t# If login still valid, change text on Sign In page\r\n\t\tif (self._configtmp[\"userhash\"] != \"00000000000000000000000000000000\"):\r\n\t\t\tself.staticTextSignedIn.SetLabel(\" You are signed in.\")\r\n\t\telse:\r\n\t\t\tself.staticTextSignedIn.SetLabel(\"You are not signed in.\")\r\n\t\tusername = self._configtmp[\"username\"]\r\n\t\tself.textCtrlLogin.Clear()\r\n\t\tself.textCtrlLogin.WriteText(username)\r\n\r\n\t\t# Set options\r\n\t\t_ratelist = [1, 2, 3, 4, 5]\r\n\t\tself.choiceOptionRatedAtLeast.SetSelection(\r\n\t\t\t_ratelist.index(self._configtmp[\"ratedatleast\"]))\r\n\t\t_percentlist = [5, 10, 20, 50, 75, 100]\r\n\t\tself.choiceOptionPercentUnrated.SetSelection(\r\n\t\t\t_percentlist.index(self._configtmp[\"percentnew\"]))\r\n\t\t_changeeverylist = [900, 1800, 3600, 7200, 14400, 28800, 86400,\r\n\t\t\t172800, 345600, 604800]\r\n\t\tself.choiceOptionChangeEvery.SetSelection(\r\n\t\t\t_changeeverylist.index(self._configtmp[\"changeevery\"]))\r\n\r\n\t\t# Update complete, show frame\r\n\t\tself.Show()\r\n\t\tself.Raise()","def _updateSelectedItem(self):\n plot = self.plot\n if plot is not None:\n selected = plot.selection().getSelectedItems()\n # Give priority to image over scatter\n for klass in (items.ImageBase, items.Scatter):\n for item in selected:\n if isinstance(item, klass):\n # Found a matching item, use it\n self.getHistogramWidget().setItem(item)\n return\n self.getHistogramWidget().setItem(None)","def sgnRenderCurrentFrame(self):\n\n self.uiSaveSelectedRenders()\n\n self.core.render(self.lstSelectedRenders, bCurrentFrame = True)","def _update_visual(self):\n\n # Check if the options are opened\n if self._is_opened:\n\n self._option_border.set_color(self.border_press)\n\n else:\n\n self._option_border.set_color((0, 0, 0, 0))","def synchronize_slider(self):\n\n # Block slider signals to avoid a shortcut.\n self.slider_frames.blockSignals(True)\n\n if self.frame_ordering == \"quality\":\n self.quality_index = self.listWidget.currentRow()\n self.frame_index = self.quality_sorted_indices[self.quality_index]\n self.slider_frames.setValue(self.quality_index + 1)\n else:\n self.frame_index = self.listWidget.currentRow()\n self.quality_index = self.rank_indices[self.frame_index]\n self.slider_frames.setValue(self.frame_index + 1)\n\n # Unblock the slider signals again.\n self.slider_frames.blockSignals(False)\n\n # Update the image in the viewer.\n self.frame_selector.setPhoto(self.frame_index)","def vistrailChanged(self):\n from vistrails.gui.vistrails_window import _app\n select_node = True\n if _app._previous_view and _app._previous_view.window() != self.window():\n select_node = False\n self.scene().setupScene(self.controller, select_node)\n if self.controller and self.controller.reset_version_view:\n self.scene().fitToAllViews()\n if self.controller:\n # self.versionProp.updateVersion(self.controller.current_version)\n self.versionProp.updateVersion(self.controller.current_version)\n self.emit(QtCore.SIGNAL(\"vistrailChanged()\"))","def poll_selection(self):\r\n osName = platform.system()\r\n\r\n ## Check if the user changed the KSDK_path\r\n try:\r\n checkPath = self.widgetList[1].get()\r\n if checkPath != self.localSDK.path:\r\n self.ask_set_directory(True, 1)\r\n\r\n ## Check if user updated project name\r\n checkName = self.widgetList[4].get()\r\n if checkName != self.newProj.name:\r\n if kT.check_proj_name(checkName):\r\n self.newProj.name = checkName\r\n else:\r\n self.newProj.name = None\r\n if self.prevName != checkName:\r\n tkMessageBox.showinfo(\"Invalid Project Name\",\\\r\n \"No spaces or special characters.\")\r\n self.prevName = checkName\r\n kT.debug_log(\"Invalid name\")\r\n except AttributeError:\r\n kT.debug_log(\"Basic Changed menu\", sys.exc_info()[2])\r\n #return\r\n\r\n try:\r\n now = self.widgetList[6].curselection()\r\n if now != self.curr:\r\n if len(self.widgetList[6].curselection()) > 0:\r\n try:\r\n self.displayBoard = PhotoImage(data=self.imageList[int(now[0])])\r\n except IndexError:\r\n kT.debug_log(now[0], sys.exc_info()[2])\r\n self.widgetList[8].grid_remove()\r\n self.widgetList[8] = Button(self, \\\r\n image=self.displayBoard, \\\r\n command=lambda:\\\r\n self.web_launch(self.localSDK.brdList[\\\r\n int(self.widgetList[6].curselection()[0])]))\r\n self.widgetList[8].image = self.displayBoard\r\n self.widgetList[8].grid(row=5, column=3, columnspan=3, sticky=E+W+N+S)\r\n self.widgetList[8].bind(\"<Enter>\", \\\r\n lambda h: self.update_tips('Is this your board?\\n' + \\\r\n 'If so, ' + \\\r\n 'then clicking on the board' + \\\r\n ' image will take you to the ' + \\\r\n 'board homepage on ' + \\\r\n 'freescale.com.\\n\\n'))\r\n self.widgetList[8].bind(\"<Leave>\", \\\r\n lambda h: self.update_tips(self.defaultHelp))\r\n self.curr = now\r\n try:\r\n self.currBoard = int(self.widgetList[6].curselection()[0]) + 1\r\n # Clear out driver list and board\r\n self.newProj.board = ()\r\n self.newProj.drvList = []\r\n # Configure ksdkProj given GUI state\r\n self.localSDK.get_version()\r\n self.newProj.name = self.widgetList[4].get()\r\n self.newProj.setKsdkPath(self.localSDK.path)\r\n self.newProj.sdkVer = self.localSDK.version\r\n self.newProj.useBSP = not self.localSDK.isNewVersion()\r\n except IndexError:\r\n self.displayBoard = PhotoImage(data=kImg.boardImages['kds_icon.gif'])\r\n self.widgetList[8].config(image=self.displayBoard)\r\n self.widgetList[8].image = self.displayBoard\r\n self.widgetList[8].config(command=lambda: self.web_launch(kImg.boardImages['NoPreview.gif']))\r\n kT.debug_log(\"Index Error\", sys.exc_info()[2])\r\n #return\r\n except IndexError:\r\n kT.debug_log(\"Index Error\", sys.exc_info()[2])\r\n #return\r\n except AttributeError:\r\n kT.debug_log(\"AttributeError\", sys.exc_info()[2])\r\n return\r\n\r\n self._retLoop = self.after(250, self.poll_selection)","def update(self):\r\n\r\n self.cmbAssembly.handler_block(self._lst_handler_id[0])\r\n self.cmbAssembly.set_active(self._model.assembly_id)\r\n self.cmbAssembly.handler_unblock(self._lst_handler_id[0])\r\n\r\n self.cmbDistribution.handler_block(self._lst_handler_id[1])\r\n self.cmbDistribution.set_active(self._model.distribution_id)\r\n self.cmbDistribution.handler_unblock(self._lst_handler_id[1])\r\n\r\n self.cmbConfType.handler_block(self._lst_handler_id[2])\r\n self.cmbConfType.set_active(self._model.confidence_type)\r\n self.cmbConfType.handler_unblock(self._lst_handler_id[2])\r\n\r\n self.cmbConfMethod.handler_block(self._lst_handler_id[3])\r\n self.cmbConfMethod.set_active(self._model.confidence_method)\r\n self.cmbConfMethod.handler_unblock(self._lst_handler_id[3])\r\n\r\n self.cmbFitMethod.handler_block(self._lst_handler_id[4])\r\n self.cmbFitMethod.set_active(self._model.fit_method)\r\n self.cmbFitMethod.handler_unblock(self._lst_handler_id[4])\r\n\r\n self.txtDescription.handler_block(self._lst_handler_id[5])\r\n self.txtDescription.set_text(self._model.description)\r\n self.txtDescription.handler_unblock(self._lst_handler_id[5])\r\n\r\n self.txtConfidence.handler_block(self._lst_handler_id[6])\r\n if self._model.confidence < 1.0:\r\n Configurationidence = self._model.confidence * 100.0\r\n else:\r\n Configurationidence = self._model.confidence\r\n self.txtConfidence.set_text(str(Configurationidence))\r\n self.txtConfidence.handler_unblock(self._lst_handler_id[6])\r\n\r\n self.txtStartTime.handler_block(self._lst_handler_id[7])\r\n self.txtStartTime.set_text(str(self._model.start_time))\r\n self.txtStartTime.handler_unblock(self._lst_handler_id[7])\r\n\r\n self.txtEndTime.handler_block(self._lst_handler_id[8])\r\n self.txtEndTime.set_text(str(self._model.rel_time))\r\n self.txtEndTime.handler_unblock(self._lst_handler_id[8])\r\n\r\n self.txtRelPoints.handler_block(self._lst_handler_id[9])\r\n self.txtRelPoints.set_text(str(self._model.n_rel_points))\r\n self.txtRelPoints.handler_unblock(self._lst_handler_id[9])\r\n\r\n self.txtStartDate.handler_block(self._lst_handler_id[10])\r\n _start_date = Utilities.ordinal_to_date(self._model.start_date)\r\n self.txtStartDate.set_text(str(_start_date))\r\n self.txtStartDate.handler_unblock(self._lst_handler_id[10])\r\n\r\n self.txtEndDate.handler_block(self._lst_handler_id[11])\r\n _end_date = Utilities.ordinal_to_date(self._model.end_date)\r\n self.txtEndDate.set_text(str(_end_date))\r\n self.txtEndDate.handler_unblock(self._lst_handler_id[11])\r\n\r\n return False","def OnButtonClick(self):\n self.choice()","def onSelected(self):\n pass","def start_GUI(self):\n experiment_names = list(GUI.api.get_experiment_names())\n #selected_exp = None #value picked in the list\n\n branch_log_dict = GUI.api.get_branching_indep_to_dep()\n #Separate columns for a new trial and a new experiment\n\n col_new_trial = [[sg.Radio('New Trial', \"RADIO1\", default=True, enable_events = True, key=\"new_trial_radio\", metadata='not_disable')],\n [sg.Text(text = \"Please pick your experiment from the list below:\")], \n [sg.Listbox(values=experiment_names, size=(30, 6), key=\"list\", select_mode = sg.LISTBOX_SELECT_MODE_SINGLE, enable_events= True)]]\n \n\n #metadata ahs true if we need to input filed\n col_new_experiment = [[sg.Radio('New experiment', \"RADIO1\", enable_events=True, key=\"new_exp_radio\", metadata='not_disable')]]\n col_new_experiment.extend(self.make_fields())#add fields to the form\n layout = [[sg.Column(col_new_trial), sg.Column(col_new_experiment)], \n [sg.Button(button_text= \"OK\", enable_events= True, key =\"OK\")]]\n \n window = sg.Window('New Data', layout, keep_on_top=True)#Creation of the window\n while True:\n event, values = window.read()\n # End program if user closes window or\n # presses the OK button\n # you can use switch-case here instead of if statements\n if event == sg.WIN_CLOSED:\n #Indicate abort\n return None, None, None, None\n elif event == \"new_exp_radio\":#if new experiment is picked, then disable the elements for the new trial\n #for evey field on which branching logic depends on, disable everything not selected\n window['list'].update(disabled = True)\n for row in col_new_experiment:\n for elem in row:\n if(elem.metadata != 'not_disable' and not isinstance(elem, sg.Text)):#do not block the radio button):\n window[elem.Key].update(disabled = False)\n \n self.clear_disable_all(window, branch_log_dict, col_new_experiment)#we could just enable a few, instead\n elif event == \"new_trial_radio\":#if new trial is picked, disable the elements for the new experiment, enable for the new trua\n #disable everything in the form\n for row in col_new_experiment:\n for elem in row:\n if(elem.metadata != 'not_disable' and not isinstance(elem, sg.Text)):#do not block the radio button and do not update textboxes\n window[elem.Key].update(disabled = True)\n #enable the listbox\n \n window['list'].update(disabled = False)\n elif event == \"OK\":\n field_missing = False\n #Check if the listbox has a value or the form has a value\n if values['new_exp_radio']:#we are doing new expriment\n # printing_params = {\"paxton\":\"\"}\n printing_params = {}\n #Check the all the stuff in the form of the new experiment\n for row in col_new_experiment:\n if(field_missing):\n break#do not check anymore\n for elem in row:\n if(elem.metadata != 'not_disable' and not isinstance(elem, sg.Text)):#do not check labels and the radio button\n if (elem.metadata and values[elem.Key]== \"\"): #value ahs to be filled and not empty\n field_missing = True\n sg.popup_ok('Required fields are missing!')#if at least one field is empty, throw a popup and stop checking\n break # Shows OK button\n #if at least one field does not have a value, then we generate a popup\n elif(values[elem.Key] != \"\"):#add to the dictonary of params\n printing_params[elem.Key] = values[elem.Key]\n \n if not field_missing:\n #if everything is filled, then validate\n \n #if user closes the popup, then the print is considered bad by default\n is_valid, field_name = self.validate_fields(window, values)\n if(is_valid):\n print_result, folderPath = self.getPicturesPrintEval()\n window.close()\n #now, we also return print_result\n return \"add_record\", printing_params, print_result, folderPath\n else:\n sg.popup_ok(\"The field could not be validated: \" + field_name)\n \n elif values['new_trial_radio']:#could use else\n if values['list'] == []:\n sg.popup_ok('Required fields are missing!')\n continue#go to while loop\n #we got here, so we now know the record_id of the experiment we want to do the new trial for\n record_lst = GUI.api.get_elements(values['list'][0])\n #create a new window with print quality + pictures\n print_result, folderPath = self.getPicturesPrintEval()\n window.close()\n return \"add_trial\", record_lst, print_result, folderPath\n elif event in branch_log_dict:#if branching logic is dependent on this element\n #we could only enable/disable stuff affected by the element\n self.enable_selected(window, copy.deepcopy(values), branch_log_dict, event)\n self.disable_not_selected(window, copy.deepcopy(values), branch_log_dict, event)","def modelselec_change():\n d = curdoc()\n _remove_fig(d)\n _remove_selection(d)\n d.remove_root(d.get_model_by_name(AFTER_MODEL_SELECTION))\n modelselec = d.get_model_by_name(MODEL_SELECTION)\n msv = modelselec.value\n if msv != DEFAULT_UNSELECTED:\n model_id, message_name, model_type = run_handlers.get_modelid_messagename_type(d)\n if model_type == \"protobuf\":\n message = Select(title=\"Message Selection\", value=DEFAULT_UNSELECTED, options=list(data.proto_data_structure[model_id][\"messages\"].keys()) + [DEFAULT_UNSELECTED], name=MESSAGE_SELECTION)\n graphs = Select(title=\"Graph Selection\", value=DEFAULT_UNSELECTED, options=[], name=GRAPH_SELECTION)\n message.on_change('value', lambda attr, old, new: message_change())\n graphs.on_change('value', lambda attr, old, new: graphs_change())\n selec = row(widgetbox([message]), widgetbox([graphs]), name=AFTER_MODEL_SELECTION)\n else: # there is no message selection here\n graphs = Select(title=\"Graph Selection\", value=DEFAULT_UNSELECTED, options=GRAPH_OPTIONS, name=GRAPH_SELECTION)\n graphs.on_change('value', lambda attr, old, new: graphs_change())\n selec = row(widgetbox([graphs]), name=AFTER_MODEL_SELECTION)\n d.add_root(selec)\n d.add_root(selec)","def update_rec_configs_choice(self):\n # this will update the configuration choices in reconstruction tab\n # fill out the config_id choice bar by reading configuration files names\n self.rec_ids = []\n for file in os.listdir(os.path.join(self.main_win.experiment_dir, 'conf')):\n if file.endswith('_config_rec'):\n self.rec_ids.append(file[0:len(file) - len('_config_rec')])\n if len(self.rec_ids) > 0:\n self.rec_id.addItems(self.rec_ids)\n self.rec_id.show()","def update_(self):\n self.update_listbox()\n self.update_infobox()\n self.update_statusbar()\n self.listbox.select_set(0)\n self.listbox.focus_set()","def run(self):\n split_old_type = self.old_type.split(\"/\")\n types_list = None\n \n if isinstance(self.object, scg_objects.SCgNode):\n types_list = scg_alphabet.get_node_types()\n elif isinstance(self.object, scg_objects.SCgPair):\n types_list = scg_alphabet.get_pair_types()\n else:\n raise Exception(\"Unknown object type %s\" % str(self.object))\n \n assert len(types_list) > 0\n \n split_types = [] \n for _type in types_list:\n split_types.append(_type.split(\"/\"))\n \n # parse possible values and create controls for changing them\n for idx in xrange(0, len(split_types[0])):\n values = []\n for _type in split_types:\n if not _type[idx] in values:\n values.append(_type[idx])\n \n ctrl = ChoiceControl(values, split_old_type[idx], self.panel, self.updateType)\n \n self.controls.append(ctrl)\n \n # layout created controls\n height = 5\n \n for ctrl in self.controls:\n ctrl.panel.setPosition(3, height)\n height += ctrl.panel.getHeight() + 5\n width = ctrl.panel.getWidth()\n \n self.button_ok.setPosition(10, height + 10)\n self.button_cancel.setPosition(65, height + 10)\n \n pos = render_engine.pos3dTo2dWindow(self.object.getPosition() + self.object.getScale() / 2)\n # make some offset\n width += 20\n height += 45 \n self.panel.setSize(width, height)\n \n # sure that dialog isn't placed out of screen \n x, y = pos\n x2 = x + width\n y2 = y + height\n \n if x2 >= render_engine.Window.width:\n x = render_engine.Window.width - width\n elif x < 0:\n x = 0\n \n if y2 >= render_engine.Window.height:\n y = render_engine.Window.height - height\n elif y < 0:\n y = 0 \n \n self.panel.setPosition(x, y)\n \n # show panel\n self.panel.setVisible(True)","def update_visualizer(self):\n if self.visualizer:\n if self.frame_count == 2:\n self.visualizer.add_geometry(self.vis_points)\n self.visualizer.update_geometry(self.vis_points)\n self.visualizer.poll_events()\n self.visualizer.update_renderer()\n time.sleep(0.001)\n self.frame_count += 1","def player_processframe_event(self, frame):\n\t\tpaths = self._panel_path.value.datasets\n\t\tareas = self._panel_area.value.datasets\n\t\tcolors = self._panel_colors.value.datasets\n\t\timages = self._panel_imgs.value.images\n\n\t\t# check if should use the current frame or an image selected to background\n\t\tframe = frame if len(images)!=1 else images[0].image.copy()\n\t\tindex = self._player.video_index-1\n\t\n\t\tfor path in paths:\n\t\t\t# draw the path if the option is selected\n\t\t\tif self._drawpath.value: path.draw_path(frame, None, index)\n\n\t\t\tarea = self.get_object_area(path, areas, index)\n\t\t\tif area is not None:\n\t\t\t\tcolor \t = self.get_object_color(path, colors, index)\n\t\t\t\tposition = path.get_position(index)\n\t\t\t\t\n\t\t\t\tif position is not None and area is not None and color is not None:\n\t\t\t\t\tradius = int(round(math.sqrt(area/math.pi)))\t\t\t\t\n\t\t\t\t\tcv2.circle(frame, position, radius, color, -1)\n\n\t\tself.draw_events(index, frame)\n\n\t\treturn frame","def onFrameUpdated(self):\n pass","def update(self):\n # Get frame from video source:\n ret, frame = self.vid.read()\n\n if ret:\n # Convert the captured frame into grayscale\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n gray = cv2.equalizeHist(gray)\n\n # Get all faces from the video frame\n faces = self.faceCascade.detectMultiScale(gray, 1.2,5)\n\n # For each face in faces\n for (x, y, w, h) in faces:\n # Create rectangle around the face\n cv2.rectangle(frame, (x-20,y-20), (x+w+20,y+h+20), (0,255,0), 4)\n\n # Recognize the face belongs to which ID\n Id = self.recognizer.predict(gray[y:y+h,x:x+w])\n\n ### IDENTIFICATION & SOCKET CODE GOES HERE\n if Id[0] == self.user_id:\n # If the target face is found 10 times then access is granted\n self.identification_count += 1\n if self.identification_count > 10:\n self.master.switch_frame(AccessGranted)\n\n name_to_put = self.user_name\n else:\n name_to_put = \"Unknown - Access Denied\"\n\n # Put text describe who is in the picture\n cv2.rectangle(frame, (x-22,y-90), (x+w+22, y-22), (0,255,0), -1)\n cv2.putText(frame, str(name_to_put), (x,y-40), self.font, 2, (255,255,255), 3)\n\n self.after(50, self.update)","def setupOptionsFrame(self):\n\n # CPU / CUDA options\n self.device.addItems([\"cuda\", \"cpu\"])\n self.scriptedEffect.addLabeledOptionsWidget(\"Device:\", self.device)\n\n self.modality.addItems([\"CT\", \"MRI\"])\n self.scriptedEffect.addLabeledOptionsWidget(\"Modality:\", self.modality)\n\n # Add ROI options\n self.roiSelector.nodeTypes = ['vtkMRMLMarkupsROINode']\n self.roiSelector.noneEnabled = True\n self.roiSelector.setMRMLScene(slicer.mrmlScene)\n self.scriptedEffect.addLabeledOptionsWidget(\"ROI: \", self.roiSelector)\n\n # Toggle ROI visibility button\n toggleROIVisibilityButton = qt.QPushButton(\"Toggle ROI Visibility\")\n toggleROIVisibilityButton.objectName = self.__class__.__name__ + 'ToggleROIVisibility'\n toggleROIVisibilityButton.setToolTip(\"Toggle selected ROI visibility\")\n toggleROIVisibilityButton.connect('clicked()', self.toggleROIVisibility)\n self.scriptedEffect.addOptionsWidget(toggleROIVisibilityButton)\n\n # Apply button\n applyButton = qt.QPushButton(\"Apply\")\n applyButton.objectName = self.__class__.__name__ + 'Apply'\n applyButton.setToolTip(\"Extract liver from input volume\")\n applyButton.connect('clicked()', self.onApply)\n self.scriptedEffect.addOptionsWidget(applyButton)","def selectFrame(event, x, y, flags, param):\n global drag_start, sel, patch\n if event == cv2.EVENT_LBUTTONDOWN:\n drag_start = x, y\n sel = 0,0,0,0\n elif event == cv2.EVENT_LBUTTONUP:\n if sel[2] > sel[0] and sel[3] > sel[1]:\n patch = frame[sel[1]:sel[3],sel[0]:sel[2]]\n cv2.imshow(\"result\", patch)\n color_data[\"upperPt\"] = sel[:1]\n color_data[\"lowerPt\"] = sel[2:]\n drag_start = None\n elif drag_start:\n #print flags\n if flags & cv2.EVENT_FLAG_LBUTTON:\n minpos = min(drag_start[0], x), min(drag_start[1], y)\n maxpos = max(drag_start[0], x), max(drag_start[1], y)\n sel = minpos[0], minpos[1], maxpos[0], maxpos[1]\n #img = cv2.cvtColor(frame, cv2.COLOR_GRAY2BGR)\n img = frame.copy()\n cv2.rectangle(img, (sel[0], sel[1]), (sel[2], sel[3]), (0,255,255), 1)\n cv2.imshow(\"select ROI\", img)\n else:\n print(\"selection is complete\")\n print(sel)\n drag_start = None","def upd_view():\n global state, current_view, show_actives, current_filename\n nonlocal img, listbox\n\n with data_lock:\n if state == 1:\n current_filename = None\n state = 2\n listbox.delete(0, tk.END)\n for item in current_view.actions.by_type(wtl.actions.Click):\n wtl_uid = str(item.target.wtl_uid)\n text = item.target.metadata[\"text\"]\n listbox.insert(tk.END, wtl_uid + f\" ({text})\")\n\n if state == 2:\n filename = \"first\" if show_actives.get() == 0 else \"is_active\"\n if filename != current_filename:\n current_filename = filename\n current_view.snapshot.screenshots[filename].save(Path(\".\"))\n img = tk.PhotoImage(file=f\"{filename}.png\")\n canvas.create_image(5, 5, anchor=tk.NW, image=img)\n\n window.after(250, upd_view)","def _handle_gui_set(self,p_name):\n if self._live_update:\n self._update_param_from_tkvar(p_name)","def selectionChanged(self, selected, deselected):\n rows = [self.model.nodeFromIndex(row) for row in self.selmod1.selectedRows()]\n self.updateStats(rows)","def switch_frames(self, new_frameName):\n\n if new_frameName in self.__frame_names:\n\n #Give rise to a new frame\n\n if new_frameName == \"image_frame\":\n image_frame= ImageFrame.Image_Frame(self.master,\n self.width,\n self.height)\n image_frame.place(x = 0, y = 0)\n \n\n elif new_frameName == \"audio_frame\":\n audio_frame = AudioFrame.Audio_Frame(self.master,\n self.width,\n self.height)\n audio_frame.place(x = 0, y = 0)\n\n elif new_frameName == \"doc_frame\":\n not_yet = notReadyYetFrame.Not_Ready_Yet_Frame(self.master,\n self.width,\n self.height)\n not_yet.place(x = 0, y = 0)\n\n else:\n not_yet = notReadyYetFrame.Not_Ready_Yet_Frame(self.master,\n self.width,\n self.height)\n not_yet.place(x = 0, y = 0)\n\n #Destroy the current frame\n self.place_forget()\n self.destroy()","def state_choose_do(cfg, app, win, events):","def apply_selection(self, rv, index, is_selected):\r\n self.selected = is_selected","def plot_changed(self):\n self.plotType = self.ui.selectPlotType.currentText()\n self.value_changed()","def apply_changes(self, updated_talk=None):\r\n self.presentationModel.select()\r\n self.select_talk(updated_talk)\r\n self.update_autocomplete_fields()","def changement_frame(self):\n\n for widget in self.fenetre_scores.winfo_children():\n widget.pack_forget()\n\n for widget in self.fenetre_regles.winfo_children():\n widget.pack_forget()\n\n for widget in self.frame_jeu.winfo_children():\n widget.pack_forget()\n\n for widget in self.winfo_children():\n if widget != self.titre:\n widget.pack_forget()","def UpdateDisplay(self):\n ##Jconf\n self.chJconf.Clear()\n for name in self.state.GetSurface(\"JconfDict\").GetNames():\n self.chJconf.Append(name)\n self.chJconf.SetStringSelection(self.state.GetSurface(\"JconfSelection\"))\n self.chJconf.Enable(self.state.IsEnabled(\"JconfDict\") == True and\n self.state.IsEnabled(\"JconfSelection\") == True and\n self.state.GetSurface(\"Xplorer\") == True)\n self.bEditJconf.Enable(self.state.IsEnabled(\"JconfDict\") and\n self.state.GetSurface(\"Xplorer\") == True)\n ##Name Server\n self.cbNameServer.SetValue(self.state.GetSurface(\"NameServer\"))\n self.cbNameServer.Enable(self.state.IsEnabled(\"NameServer\"))\n ##Conductor\n self.cbConductor.SetValue(self.state.GetSurface(\"Conductor\"))\n self.cbConductor.Enable(self.state.IsEnabled(\"Conductor\"))\n ##Xplorer\n self.cbXplorer.SetValue(self.state.GetSurface(\"Xplorer\"))\n self.cbXplorer.Enable(self.state.IsEnabled(\"Xplorer\"))\n ##Desktop Mode\n self.cbDesktop.SetValue(self.state.GetSurface(\"DesktopMode\"))\n self.cbDesktop.Enable(self.state.IsEnabled(\"DesktopMode\"))\n ##Xplorer Type\n if self.state.GetSurface(\"DesktopMode\"):\n self.rbXplorer.SetSelection(0)\n else:\n if (self.state.GetSurface(\"XplorerType\") == \"OSG-VEP\"):\n self.rbXplorer.SetSelection(0)\n else:\n self.rbXplorer.SetSelection(1)\n self.rbXplorer.Enable(self.state.IsEnabled(\"XplorerType\") == True and\n self.state.GetSurface(\"DesktopMode\") == False and\n self.state.GetSurface(\"Xplorer\") == True)\n ##Cluster Node button\n self.bCluster.Enable(CLUSTER_ENABLED and\n self.state.GetSurface(\"Xplorer\") == True and\n self.state.GetSurface(\"DesktopMode\") == False and\n self.state.GetSurface(\"XplorerType\") == \"OSG-VEPC\")\n return","def select_ORF(self):\n if self.data.has_key('ORF_selected'):\n del self.data['ORF_selected']\n self.data['DNAseq_status']='ORF_CHANGED'\n #if no orf previously then this must be a new record?\n else:\n self.data['DNAseq_status']='NEW SEQ'\n\n # Start the ORF selection\n import ORF_module\n X=ORF_module.ORF_handler(self)\n if self.data.has_key('ORF_selected'):\n start=self.data['ORF_selected']['start']\n stop=self.data['ORF_selected']['stop']\n frame=self.data['ORF_selected']['frame']\n ORF_num=self.data['ORF_selected']['number']\n #\n base_start=(start-1)*3+(frame-1)\n base_stop=stop*3+(frame-1)\n\n # mark that we have an ORF and get rid of all useless info\n self.data['Project saved']=None\n #\n # Activate the primer design button(s)\n #\n else:\n pass\n #\n # Update everything\n #\n self.assess_status()\n # Update view\n self.update_sequence_window()\n #self.data['DNAseq_status']='ALTERED'\n\n return","def misc_select(self, event):\n\n self.selected_index = event.GetIndex()\n self.update_properties()","def onSelect_specimen(self, event):\n new_s = self.specimens_box.GetValue()\n if self.select_specimen(new_s):\n self.update_selection()\n else:\n self.specimens_box.SetValue(self.s)\n self.user_warning(\n \"no specimen %s reverting to old specimen %s\" % (new_s, self.s))","def _selection_changed(self, event):\n if self.typeCombo.get() in Constants.TASKS[0:3]:\n if self.subjectAdded == False:\n self._placeWidgets(self.subjectLabel, self.subjectCombo)\n self.subjectAdded = True\n else:\n if self.subjectAdded:\n # Hide subject label and combobox\n self.subjectLabel.place_forget()\n self.subjectCombo.place_forget()\n self.subjectAdded = False\n self.row -= 1","def selection_changed(self):\n filter_name = self.cb_selectes_filter.currentText()\n\n # show filter description\n self.infob.setText(filters_dict[filter_name].__doc__)\n #print(self.selected_filter)\n\n self.compute(filter_name)\n # afficher\n self.update_display()\n\n self.commit()","def change(self):\r\n\r\n # If checkboxes are available, check status and set boat speed reference line visibility accordingly.\r\n if self.cb:\r\n if self.cb_bt.checkState() == QtCore.Qt.Checked:\r\n for item in self.bt:\r\n item.set_visible(True)\r\n else:\r\n for item in self.bt:\r\n item.set_visible(False)\r\n # GGA\r\n if self.cb_gga.checkState() == QtCore.Qt.Checked:\r\n for item in self.gga:\r\n item.set_visible(True)\r\n # self.gga[0].set_visible(True)\r\n elif self.gga is not None:\r\n for item in self.gga:\r\n item.set_visible(False)\r\n # self.gga[0].set_visible(False)\r\n # VTG\r\n if self.cb_vtg.checkState() == QtCore.Qt.Checked:\r\n for item in self.vtg:\r\n item.set_visible(True)\r\n # self.vtg[0].set_visible(True)\r\n elif self.vtg is not None:\r\n for item in self.vtg:\r\n item.set_visible(False)\r\n # self.vtg[0].set_visible(False)\r\n\r\n # Draw canvas\r\n self.canvas.draw()","def updateFrame(self, image):\n self.currentFrame += 1\n self.image = image.copy()\n\n detected = self.car_detector.detectCars(image)\n picks = self.car_detector.non_max_suppression_fast(detected, 0.2)\n\n self.logger.debug(\" CURRENT CAR LIST\\n\")\n self.printCars()\n\n self.logger.debug(\"\\nNew Picks {0!s}\\n\".format(picks))\n\n self.addCars(picks)\n self.removeOldCars()\n if len(self.cars) == 0:\n self.logger.debug(\"EMPTY.... HELP\")\n # self.printCars()\n return self.drawCars()","def select( self ):\n self._has_change = True","def __call__(self):\n self.brain._update_fscale(self.factor)\n for key in self.brain.keys:\n if self.widgets[key] is not None:\n self.widgets[key].set_value(self.brain._data[key])","def _sync_gui(self):\n self._update_buttons()\n\n self.turn_value_label.config(text=self.turn_value_text)\n self.selected_piece_value_label.config(text=self.selected_piece_value_text)\n\n self.update()","def _on_selection_changed(self, selection):\n if self._updating_selection:\n return\n\n self._updating_selection = True\n\n self._tree_selection.unselect_all()\n for widget in selection:\n gadget_iter = self._find_iter_by_widget(widget)\n if gadget_iter:\n select_iter(self._tree_view, gadget_iter)\n\n self._updating_selection = False","def updateSelectionArea(self):\n self.machine.setSelectionArea(self.points,\n fill='hatch',\n color=self.machine.color)\n eventDict = prepareDrawingSignal('drawingProgress',\n 'polygon',\n self.points,\n self.machine.parameters)\n self.machine.plot.notify(**eventDict)","def apply_selection(self, rv, index, is_selected):\n self.selected = is_selected","def select(self, image):\n self.original = image\n self.boundings = []","def update_selection(self, game, obj):\n self.clear()\n if obj:\n if obj in game.towers:\n self.selected_tower = obj\n self.update_selection_tower(self.selected_tower)\n elif obj in game.monsters:\n self.selected_monster = obj\n self.update_selection_monster(self.selected_monster)\n elif obj in self.monsters_images:\n self.selected_monster = obj\n self.update_selection_monster(self.selected_monster, False)","def _visibleChannels_changed(self):\n for i in range(0,8):\n if i in self.visibleChannels:\n self.masterContainer.plots[\"channel\"+str(i)][0].visible=True\n else:\n print i\n self.masterContainer.plots[\"channel\"+str(i)][0].visible=False","def updateBtnSelect(self):\n logger.debug(\"update buttons\")\n currSelection = cmds.ls(selection = True)\n currTab = self.tabwidget.currentWidget()\n\n minus = [] #list of objects deselected\n added = [] #list of objects added to selection\n\n for i in self.previousSelection:\n if i not in currSelection: #object has been deselected\n minus.append(i) #add to deselected list\n for j in currSelection:\n if j not in self.previousSelection: #object has been added to selection\n added.append(j)\n\n #updated the number of selected objects for each button asociated with an object in one of the lists\n for a in added:\n logger.debug(\"added \"+a)\n if a in self.objects[currTab]:\n for btn in self.objects[currTab][a]:\n btn.numSel+=1 #add one to the number of objects selected in the list of connections for the button\n if btn.numSel == len(btn.connection): #change outline if the number selected is equal to the total number of objects connected to the button\n btn.selected = True\n btn.setChecked(True)\n\n for m in minus:\n logger.debug(\"minus \"+m)\n if m in self.objects[currTab]:\n for btn in self.objects[currTab][m]:\n btn.numSel-=1 #subtract one to the number of objects selected in the list of connections for the button\n logger.debug(btn.numSel)\n if btn.numSel < len(btn.connection): #change outline if the number selected is less than the total number of objects connected to the button\n btn.selected = False\n btn.setChecked(False)\n\n self.previousSelection= currSelection\n\n\n if(self.edit ==True):\n logger.debug(\"checkboxes\")\n #updates the list of checkboxes\n self.clearLayout(self.vbox) #clear list\n sl = cmds.ls(sl = True) #get selection\n for obj in sl: #add a checkbox for each object in selection\n checkbox = QtWidgets.QCheckBox(obj)\n checkbox.setChecked(True)\n checkbox.stateChanged.connect(lambda state, o=obj, c=checkbox: self.stateChanged(o, c))\n self.vbox.addWidget(checkbox) #add to layout","def init_gui(self):\r\n self.root.title('Video Resizer')\r\n self.root.option_add('*tearOff', 'FALSE')\r\n self.grid(column=0, row=0, sticky='nsew')\r\n\r\n # Buttons getvideos, save videos, start resize\r\n self.openButton = ttk.Button(self, width=8, text=\"Browse\", command=self.getVideosPath)\r\n self.openButton.grid(column=1, row=2)\r\n self.saveButton = ttk.Button(self, width=8, text=\"Browse\", command=self.getCapturePath)\r\n self.saveButton.grid(column=3, row=2)\r\n self.startButton = ttk.Button(self, text='Start to Resize', command=self.startResizing)\r\n self.startButton.grid(column=0, row=5)\r\n self.multiStartButton = ttk.Button(self, text='Start to multi Resize', command=self.startMultiResizing)\r\n self.multiStartButton.grid(column=2, row=5)\r\n\r\n # listbox to choose what video type to save\r\n # add a label for the combobox\r\n ttk.Label(self, text=\"Select Video Type to Save\").grid(column=0, row=4)\r\n\r\n def clickMe():\r\n \"\"\"\r\n button clicked to select video type\r\n called when action is clicked\r\n :return:\r\n \"\"\"\r\n global Format\r\n Format = typeToChoose.get()\r\n print(Format)\r\n action.configure(text='selected ' + Format) # show the selected item after clicked\r\n action.configure(state='disabled') # button disabled after clicked\r\n\r\n # Button\r\n action = ttk.Button(self, text=\"Select \", command=clickMe)\r\n action.grid(column=2, row=4)\r\n\r\n # Combobox\r\n typeToChoose = StringVar()\r\n # value in combobox is formatType\r\n numberChosen = ttk.Combobox(self, width=12, textvariable=typeToChoose, values=self.formatTypes)\r\n numberChosen.grid(column=1, row=4)\r\n numberChosen.current(0)\r\n\r\n # Frame show info related to the resizing process\r\n self.resultFrame = ttk.LabelFrame(self, text='Result', height=100)\r\n self.resultFrame.grid(column=0, row=6, columnspan=4, sticky='nesw')\r\n self.resultLabel = ttk.Label(self.resultFrame, text='')\r\n self.resultLabel.grid(column=0, row=0)\r\n\r\n # Labels that remain constant throughout execution.\r\n ttk.Label(self, text='Video Resizer').grid(column=0, row=0, columnspan=4)\r\n ttk.Label(self, text='Select videos').grid(column=0, row=2, sticky='w')\r\n ttk.Label(self, text='Saving folder').grid(column=2, row=2, sticky='w')\r\n ttk.Separator(self, orient='horizontal').grid(column=0, row=1, columnspan=4, sticky='ew')\r\n\r\n # configure for the window grid\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=5)","def changeFormation(self, *args):\n\n # get the number of balls\n # formation = self.numberOfBallsSelector.get(first=None, last=None)\n newNBalls = int(self.numberOfBallsSelector.get())\n\n if newNBalls >= self.nBalls:\n for i in range(self.nBalls, newNBalls):\n # for some reason self.initballstate gets edited if ballstates gets edited\n self.ballStates[i] = [1.5, 0.75, 0, 0]\n\n # TODO: change this later after we figure out proper initial ball locations\n self.ballStates[i][2] += random.uniform(-3, 3)\n self.ballStates[i][3] += random.uniform(-3, 3)\n\n self.nBalls = newNBalls\n self.balls = tuple(map(str, range(self.nBalls)))\n # self.saveParameters()\n # recreate combobox with updated number of balls\n self.ballSelector = Pmw.ComboBox(self, label_text='Choose Ball',\n labelpos='nw', selectioncommand=self.changeBall,\n scrolledlist_items=self.balls, dropdown=1)\n self.ballSelector.grid(column=0, row=3)\n self.ballSelector.selectitem(self.currentBall)","def selection_changed(self):\n self.emit('selection_changed')","def param_changes_button_clicked():\n for label in param_change_labels:\n if label.visible:\n param_changes_button.label = 'Show Parameter Changes'\n label.visible = False\n label.text_alpha = 0 # label.visible does not work, so we use this instead\n else:\n param_changes_button.label = 'Hide Parameter Changes'\n label.visible = True\n label.text_alpha = 1","def sgnRenderAllFrames(self):\n\n self.uiSaveSelectedRenders()\n\n self.core.render(self.lstSelectedRenders, bEverything = True)","def refreshActiveFrames(self, event=None):\n self.unloadAllFrames()\n self.checkFramesHaveData()\n\n try:\n self.contentFrame.currFrame.built = False\n except AttributeError:\n pass\n\n try:\n if self.contentFrame.currFrame.hasRequiredData():\n self.contentFrame.currFrame.enter()\n else:\n self.frameBtnCmds[0](self)\n except AttributeError:\n self.frameBtnCmds[0](self)","def _on_frame_changed(self, change):\n self._set_coordinates(self.frame)","def __reload_caption(self, new_list):\n # Remove all UI elements\n for item in self.__ui_controls:\n if self.__ui_controls.get(item) is None:\n continue\n self.__ui_controls.get(item).delete()\n for item in self.__teachpanel_sliders:\n item.delete()\n self.__teachpanel_sliders = []\n # Restore the caption\n self.scene.caption = self.__default_caption\n # Create the updated caption.\n self.__load_mode_ui(new_list)","def on_module_choice(self, event):\n\n self.log.trace(\"Handle module selection by user.\")\n result = {'successful': False}\n\n try:\n # determine module selected\n module_name = event.GetString()\n\n self.feature_choices = []\n for selection in DEFAULT_SEL:\n self.feature_choices.append(selection)\n if module_name.lower() == CUSTOM_SEL.lower():\n # set custom flag\n self.custom_module = True\n # show custom input\n self.input_custom_module.Show()\n else:\n # clear custom flag\n self.custom_module = False\n # make sure custom field is hidden\n self.input_custom_module.Hide()\n if module_name.lower() != BLANK_SEL.lower():\n # return all features for module\n self.log.trace(\"Rebuilding feature list for %s module ...\" % module_name)\n features = self.database.return_features_for_module(module_name)['features']\n\n # build feature list\n for feature in features:\n self.feature_choices.append(feature['name'])\n\n # set feature choices to selection\n self.input_feature.SetItems(self.feature_choices)\n self._update_feature_input_according_to_custom_module_flag()\n self.log.trace(\"Feature list for %s module rebuilt.\" % module_name)\n\n # reset user story selections\n self.log.trace(\"Reseting user story list ...\")\n self.story_choices = []\n for selection in DEFAULT_SEL:\n self.story_choices.append(selection)\n self.input_story.SetItems(self.story_choices)\n self._update_story_input_according_to_custom_feature_flag()\n self.log.trace(\"User story list reset.\")\n\n # reset test selections\n self.log.trace(\"Reseting test list ...\")\n self.test_choices = []\n for selection in DEFAULT_SEL:\n self.test_choices.append(selection)\n self.input_test.SetItems(self.test_choices)\n self._update_test_input_according_to_custom_story_flag()\n self.log.trace(\"Test list reset.\")\n\n # reset testcase selections\n self.log.trace(\"Reseting test case list ...\")\n self.testcase_choices = []\n for selection in DEFAULT_SEL:\n self.testcase_choices.append(selection)\n self.input_testcase.SetItems(self.testcase_choices)\n self._update_testcase_input_according_to_custom_test_flag()\n self.log.trace(\"Test case list reset.\")\n\n result['successful'] = True\n except BaseException, e:\n self.handle_exception(e, \"handle module selection by user\")\n\n # return\n return result","def done(self):\n\n # Check if the status of frames has changed.\n indices_included = []\n indices_excluded = []\n for index in range(self.frames.number_original):\n if self.index_included[index] and not self.frames.index_included[index]:\n indices_included.append(index)\n self.frames.index_included[index] = True\n elif not self.index_included[index] and self.frames.index_included[index]:\n indices_excluded.append(index)\n self.frames.index_included[index] = False\n\n # Write the changes in frame selection to the protocol.\n if self.configuration.global_parameters_protocol_level > 1:\n if indices_included:\n Miscellaneous.protocol(\n \" The user has included the following frames into the stacking \"\n \"workflow: \" + str(\n [item + 1 for item in indices_included]), self.stacked_image_log_file,\n precede_with_timestamp=False)\n if indices_excluded:\n Miscellaneous.protocol(\n \" The user has excluded the following frames from the stacking \"\n \"workflow: \" + str(\n [item + 1 for item in indices_excluded]), self.stacked_image_log_file,\n precede_with_timestamp=False)\n frames_remaining = sum(self.frames.index_included)\n if frames_remaining != self.frames.number:\n Miscellaneous.protocol(\" \" + str(\n frames_remaining) + \" frames will be used in the stacking workflow.\",\n self.stacked_image_log_file, precede_with_timestamp=False)\n\n # Send a completion message. The \"execute_rank_frames\" method is triggered on the workflow\n # thread. The signal payload is True if the status was changed for at least one frame.\n # In this case, the index translation table is updated before the frame ranking starts.\n if self.parent_gui is not None:\n self.signal_finished.emit()\n\n # Close the Window.\n self.player_thread.quit()\n self.close()","def onLoadSegmentationButton(self):\n inputVolume = self.inputSelector.currentNode()\n segmentationFile = self.segmentationsPath + self.segmentationFilesComboBox.currentText\n \n loadedSegmentationVolumeNode = slicer.util.loadVolume(segmentationFile)\n voxels = slicer.util.arrayFromVolume(loadedSegmentationVolumeNode)\n imgLabel = np.copy(voxels)\n \n tmpVoxels = np.copy(voxels)\n tmpVoxels[:] = imgLabel[:]\n \n slicer.util.updateVolumeFromArray(loadedSegmentationVolumeNode, tmpVoxels)\n \n removeLastSegmentation = self.removeLastSegmentationCheckBox.isChecked() \n showBackGround = self.showBackGroundCheckBox.isChecked()\n displaySegmentationMap(loadedSegmentationVolumeNode, imgLabel, self.labelColorsList, removeLastSegmentation, showBackGround)\n \n slicer.util.setSliceViewerLayers(background=inputVolume)","def _after_plot_list_load(self):\r\n self.button_send_list.enable()\r\n self.label_list_status.set_text('Shown list does not match device list.')","def state_changed(self):\n if self.goto and self.get_position() != self.c.p:\n self.goto_node()\n\n if self.mode == 'edit':\n self.edit_frame.show()\n self.view_frame.hide()\n elif self.mode == 'view':\n self.edit_frame.hide()\n self.view_frame.show()\n else:\n self.edit_frame.show()\n self.view_frame.show()\n\n self.update_position(self.c.p)","def updateWidget(self):\n\n if self.frame1.state() == 'normal':\n self.frame2.deiconify()\n self.frame1.withdraw()\n else:\n self.frame2.withdraw()\n self.frame2.update()\n self.frame2.deiconify()\n self.frame1.title(\"%s's turn\" % self.usernames[1])\n self.frame2.title(\"%s's turn\" % self.usernames[0])\n showDialogBox(\"%s's turn first!\" % self.usernames[0])\n self.frame1.update()\n self.frame2.update()","def update_choice(self, value):\n if self.p is not None:\n if value == \"none\":\n self.other_text.delete('1.0', tk.END)\n self.other_text.insert('1.0', \"\")\n if value == \"categories\":\n self.other_text.delete('1.0', tk.END)\n self.other_text.insert('1.0', self.p.categories)\n if value == \"pageid\":\n self.other_text.delete('1.0', tk.END)\n self.other_text.insert('1.0', self.p.pageid)\n if value == \"sections\":\n self.other_text.delete('1.0', tk.END)\n self.other_text.insert('1.0', self.p.sections)\n if value == \"html\":\n self.other_text.delete('1.0', tk.END)\n self.other_text.insert('1.0', self.p.html())","def createFrame(self):\n \n tkinterListBoxDialog.createFrame(self)\n self.addFrameButtons()"],"string":"[\n \"def slider_frames_changed(self):\\n\\n # Again, please note the difference between indexing and GUI displays.\\n index = self.slider_frames.value() - 1\\n\\n # Differentiate between frame ordering (by quality or chronologically).\\n if self.frame_ordering == \\\"quality\\\":\\n self.frame_index = self.quality_sorted_indices[index]\\n self.quality_index = index\\n\\n else:\\n self.frame_index = index\\n self.quality_index = self.rank_indices[self.frame_index]\\n\\n # Adjust the frame list and select the current frame.\\n\\n self.listWidget.setCurrentRow(index, QtCore.QItemSelectionModel.SelectCurrent)\\n\\n # Update the image in the viewer.\\n self.frame_selector.setPhoto(self.frame_index)\\n self.listWidget.setFocus()\",\n \"def hook_frame_selected(self):\",\n \"def update_selection(self):\\n raise NotImplementedError\",\n \"def update_selection(self):\\n\\n # clear all boxes\\n self.clear_boxes()\\n self.draw_figure(self.s)\\n\\n # update temperature list\\n if self.Data[self.s]['T_or_MW'] == \\\"T\\\":\\n self.temperatures = np.array(self.Data[self.s]['t_Arai']) - 273.\\n else:\\n self.temperatures = np.array(self.Data[self.s]['t_Arai'])\\n\\n self.T_list = [\\\"%.0f\\\" % T for T in self.temperatures]\\n self.tmin_box.SetItems(self.T_list)\\n self.tmax_box.SetItems(self.T_list)\\n self.tmin_box.SetValue(\\\"\\\")\\n self.tmax_box.SetValue(\\\"\\\")\\n self.Blab_window.SetValue(\\n \\\"%.0f\\\" % (float(self.Data[self.s]['pars']['lab_dc_field']) * 1e6))\\n if \\\"saved\\\" in self.Data[self.s]['pars']:\\n self.pars = self.Data[self.s]['pars']\\n self.update_GUI_with_new_interpretation()\\n self.Add_text(self.s)\\n self.write_sample_box()\",\n \"def updateDevice(self, *args):\\r\\n\\r\\n # Update the list of vision choices and the default vision choice\\r\\n self._appChoice[\\\"vision\\\"] = [choice[0] for choice in self._system[self._appString[\\\"device\\\"].get()]]\\r\\n self._appString[\\\"vision\\\"].set(self._appChoice[\\\"vision\\\"][0])\\r\\n\\r\\n # Delete the old choices fromt the option menu\\r\\n menu = self._appOption[\\\"vision\\\"][\\\"menu\\\"]\\r\\n menu.delete(0, \\\"end\\\")\\r\\n\\r\\n # Add the new list of choices to the option menu\\r\\n for string in self._appChoice[\\\"vision\\\"]:\\r\\n menu.add_command(label=string, command=lambda value=string: self._appString[\\\"vision\\\"].set(value))\",\n \"def _selectionChangedSlot(self, _):\\r\\n\\r\\n self._updateButtonStates()\",\n \"def change_frame(self, frame):\\r\\n pass\",\n \"def use_triggered(self):\\n\\n self.select_items()\\n if self.items_selected:\\n for index, item in enumerate(self.items_selected):\\n index_selected = self.indices_selected[index]\\n frame_selected = index_selected + 1\\n item.setText(\\\"Frame %i included\\\" % frame_selected)\\n item.setBackground(self.background_included)\\n item.setForeground(QtGui.QColor(0, 0, 0))\\n self.index_included[index_selected] = True\\n self.frame_selector.setPhoto(self.frame_index)\",\n \"def _update_gui(self):\\r\\n \\r\\n # Update the RF button.\\r\\n rf_on = self.api.get_output()\\r\\n if rf_on == None: rf_on = True\\r\\n self.button_rf.set_checked(rf_on, block_events=True).enable()\\r\\n \\r\\n # Update the combo; we block first just in case the value doesn't \\\"change\\\"\\r\\n if self.api == None: self.label_instrument_name.set_text('Simulation')\\r\\n else:\\r\\n if self.api.get_mode() == 'Fixed': self.combo_mode.set_value(0, block_events=True).enable()\\r\\n else: self.combo_mode.set_value(1, block_events=True).enable()\\r\\n self._combo_mode_changed()\\r\\n \\r\\n # Update the list plot\\r\\n self.query_list()\",\n \"def accept(self):\\n self.selInsts = [x.get() for x in self.selInstsVar]\\n self.selParams = [x.get() for x in self.selParamsVar]\\n self.updateTitle()\\n self.window.grab_release()\\n self.window.destroy()\\n self.instBoxes = []\\n self.paramBoxes = []\\n self.subRows = []\\n self.selInstsVar = []\\n self.selParamsVar = []\\n self.addRow = []\\n self.instTraces = []\",\n \"def ChannelSelect(self):\\n self.active_mode = 'default'\\n self.reset_buttons()\\n # Dialog to choose channels from specific brain regions\\n w = SelectChannelsDialog(\\n stringlist=self.model.all_regions,\\n checked=self.model.regions_mask\\n )\\n all_locs = self.model.electrodes_table['location'][self.model.electrical_series_channel_ids]\\n self.model.channels_mask = np.zeros(len(all_locs))\\n for loc in w.choices:\\n self.model.channels_mask += all_locs == np.array(loc)\\n # Indices of channels from chosen regions\\n self.model.channels_mask_ind = np.where(self.model.channels_mask)[0]\\n self.model.n_channels_total = len(self.model.channels_mask_ind)\\n # Reset channels span control\\n self.model.lastCh = np.minimum(16, self.model.n_channels_total)\\n self.model.firstCh = 1\\n self.model.nChToShow = self.model.lastCh - self.model.firstCh + 1\\n self.qline0.setText(str(self.model.lastCh))\\n self.qline1.setText(str(self.model.firstCh))\\n # Update signals plot\\n self.model.selectedChannels = self.model.channels_mask_ind[self.model.firstCh - 1:self.model.lastCh]\\n self.model.refreshScreen()\",\n \"def hook_frame_unselected(self):\",\n \"def update_view(self, selected):\\n pass\",\n \"def __init__(self, parent_gui, configuration, frames, rank_frames, stacked_image_log_file,\\n signal_finished):\\n\\n super(FrameSelectorWidget, self).__init__(parent_gui)\\n self.setupUi(self)\\n\\n # Keep references to upper level objects.\\n self.parent_gui = parent_gui\\n self.configuration = configuration\\n self.stacked_image_log_file = stacked_image_log_file\\n self.signal_finished = signal_finished\\n self.frames = frames\\n self.index_included = frames.index_included.copy()\\n self.quality_sorted_indices = rank_frames.quality_sorted_indices\\n self.rank_indices = rank_frames.rank_indices\\n\\n # Start with ordering frames by quality. This can be changed by the user using a radio\\n # button.\\n self.frame_ordering = \\\"quality\\\"\\n\\n # Initialize the frame list selection.\\n self.items_selected = None\\n self.indices_selected = None\\n\\n # Set colors for the frame list.\\n self.background_included = QtGui.QColor(130, 255, 130)\\n self.foreground_included = QtGui.QColor(0, 0, 0)\\n self.background_excluded = QtGui.QColor(120, 120, 120)\\n self.foreground_excluded = QtGui.QColor(255, 255, 255)\\n\\n self.addButton.clicked.connect(self.use_triggered)\\n self.removeButton.clicked.connect(self.not_use_triggered)\\n\\n # Be careful: Indices are counted from 0, while widget contents are counted from 1 (to make\\n # it easier for the user.\\n self.quality_index = 0\\n self.frame_index = self.quality_sorted_indices[self.quality_index]\\n\\n # Set up the frame selector and put it in the upper left corner.\\n self.frame_selector = VideoFrameSelector(self.frames, self.index_included, self.frame_index)\\n self.frame_selector.setObjectName(\\\"frame_selector\\\")\\n self.gridLayout.addWidget(self.frame_selector, 0, 0, 2, 3)\\n\\n # Initialize the list widget.\\n self.fill_list_widget()\\n self.listWidget.setSelectionMode(QtWidgets.QAbstractItemView.ExtendedSelection)\\n self.listWidget.installEventFilter(self)\\n self.listWidget.itemClicked.connect(self.select_items)\\n self.listWidget.currentRowChanged.connect(self.synchronize_slider)\\n\\n # Group widget elements which are to be blocked during player execution in a list.\\n self.widget_elements = [self.listWidget,\\n self.slider_frames,\\n self.addButton,\\n self.removeButton,\\n self.pushButton_play,\\n self.GroupBox_frame_sorting]\\n\\n # Initialize a variable for communication with the frame_player object later.\\n self.run_player = False\\n\\n # Create the frame player thread and start it. The player displays frames in succession.\\n # It is pushed on a different thread because otherwise the user could not stop it before it\\n # finishes.\\n self.player_thread = QtCore.QThread()\\n self.frame_player = FramePlayer(self)\\n self.frame_player.moveToThread(self.player_thread)\\n self.frame_player.block_widgets_signal.connect(self.block_widgets)\\n self.frame_player.unblock_widgets_signal.connect(self.unblock_widgets)\\n self.frame_player.set_photo_signal.connect(self.frame_selector.setPhoto)\\n self.frame_player.set_slider_value.connect(self.slider_frames.setValue)\\n self.frame_player_start_signal.connect(self.frame_player.play)\\n self.player_thread.start()\\n\\n # Initialization of GUI elements\\n self.slider_frames.setMinimum(1)\\n self.slider_frames.setMaximum(self.frames.number)\\n self.slider_frames.setValue(self.quality_index + 1)\\n self.radioButton_quality.setChecked(True)\\n\\n self.gridLayout.setColumnStretch(0, 7)\\n self.gridLayout.setColumnStretch(1, 0)\\n self.gridLayout.setColumnStretch(2, 0)\\n self.gridLayout.setColumnStretch(3, 0)\\n self.gridLayout.setColumnStretch(4, 1)\\n self.gridLayout.setRowStretch(0, 0)\\n self.gridLayout.setRowStretch(1, 0)\\n\\n # Connect signals with slots.\\n self.buttonBox.accepted.connect(self.done)\\n self.buttonBox.rejected.connect(self.reject)\\n self.slider_frames.valueChanged.connect(self.slider_frames_changed)\\n self.pushButton_play.clicked.connect(self.pushbutton_play_clicked)\\n self.pushButton_stop.clicked.connect(self.pushbutton_stop_clicked)\\n self.radioButton_quality.toggled.connect(self.radiobutton_quality_changed)\\n\\n if self.configuration.global_parameters_protocol_level > 0:\\n Miscellaneous.protocol(\\\"+++ Start selecting frames +++\\\", self.stacked_image_log_file)\",\n \"def radiobutton_quality_changed(self):\\n\\n # Block listWidget signals. Otherwise, changes to the widget triggered by changing the\\n # slider would cause trouble.\\n self.listWidget.blockSignals(True)\\n\\n if self.frame_ordering == \\\"quality\\\":\\n self.frame_ordering = \\\"chronological\\\"\\n self.slider_frames.setValue(self.frame_index + 1)\\n else:\\n self.frame_ordering = \\\"quality\\\"\\n self.slider_frames.setValue(self.quality_index + 1)\\n\\n self.fill_list_widget()\\n\\n # Unblock listWidget signals again.\\n self.listWidget.blockSignals(False)\",\n \"def _selection_changed(self, i):\\n\\n # Check if we have disconnected\\n if i < 0:\\n return\\n # First check if we need to stop the old block\\n if self._started_previous and self._previous_config:\\n logger.debug(\\\"Should stop config [%s], stopping!\\\",\\n self._previous_config.name)\\n self._previous_config.delete()\\n\\n # Remove our callback for the previous config\\n if self._previous_config:\\n self._previous_config.data_received_cb.remove_callback(\\n self._log_data_signal_wrapper)\\n self._previous_config.error_cb.remove_callback(\\n self._log_error_signal_wrapper)\\n\\n lg = self._model.get_config(i)\\n if not lg.started:\\n logger.debug(\\\"Config [%s] not started, starting!\\\", lg.name)\\n self._started_previous = True\\n lg.start()\\n else:\\n self._started_previous = False\\n self._plot.removeAllDatasets()\\n color_selector = 0\\n\\n self._plot.set_title(lg.name)\\n\\n self.avgsumvalue = dict();\\n self.avgsumnumb = 0;\\n for d in lg.variables:\\n self._plot.add_curve(d.name, self.colors[\\n color_selector % len(self.colors)])\\n color_selector += 1\\n self.avgsumvalue[d.name]=0;\\n lg.data_received_cb.add_callback(self._log_data_signal_wrapper)\\n lg.error_cb.add_callback(self._log_error_signal_wrapper)\\n\\n self._previous_config = lg\",\n \"def select_items(self):\\n\\n self.listWidget.currentItem().setSelected(True)\\n self.items_selected = self.listWidget.selectedItems()\\n\\n if self.frame_ordering == \\\"quality\\\":\\n self.indices_selected = [self.quality_sorted_indices[self.listWidget.row(item)] for item\\n in self.items_selected]\\n self.frame_index = self.indices_selected[0]\\n self.quality_index = self.rank_indices[self.frame_index]\\n else:\\n self.indices_selected = [self.listWidget.row(item) for item in self.items_selected]\\n self.frame_index = self.indices_selected[0]\\n self.quality_index = self.rank_indices[self.frame_index]\\n\\n self.synchronize_slider()\",\n \"def update_species_frames(self):\\n pass\",\n \"def _selected_bridge_changed(self, new):\\n if self.bridges[new] is None:\\n bridge_desc_file = os.path.join(BRIDGES_PATH, new + u'.json')\\n bridge = self.load_bridge_info(bridge_desc_file)\\n self.bridges[new] = bridge\\n\\n self.bridge = self.bridges[new]\\n self.channels = [channel for instrument in self.bridge.children\\n for sensor in instrument.children\\n for channel in sensor.children]\",\n \"def graphs_change():\\n d = curdoc()\\n _remove_fig(d)\\n _remove_selection(d)\\n graph_val = d.get_model_by_name(GRAPH_SELECTION).value\\n model_id, message_name, model_type = run_handlers.get_modelid_messagename_type(d)\\n props = run_handlers.get_model_properties(model_id, message_name, model_type)\\n\\n if graph_val in [\\\"line\\\", \\\"scatter\\\", \\\"step\\\"]:\\n # never want to plot this special string field\\n field_options = [\\\"{0} : {1}\\\".format(k, props[k]) for k in props if not any(apv in k for apv in [ APV_MODEL ] ) ]\\n xselect = Select(title=\\\"X Axis\\\", value=DEFAULT_UNSELECTED, options=field_options + [DEFAULT_UNSELECTED], name=X_AXIS_SELECTION)\\n yselect = Select(title=\\\"Y Axis\\\", value=DEFAULT_UNSELECTED, options=field_options + [DEFAULT_UNSELECTED], name=Y_AXIS_SELECTION)\\n xselect.on_change('value', lambda attr, old, new: make_2axis_graph())\\n yselect.on_change('value', lambda attr, old, new: make_2axis_graph())\\n d.add_root(column(Div(text=\\\"\\\"), row(widgetbox([xselect]), widgetbox([yselect])), name=FIELD_SELECTION))\\n\\n if graph_val in [\\\"image\\\"]:\\n # alter the field options for known non-image fields\\n field_options = [\\\"{0} : {1}\\\".format(k, props[k]) for k in props if not any(apv in k for apv in [APV_RECVD, APV_SEQNO, APV_MODEL] ) ]\\n imageselect = Select(title=\\\"Image Field\\\", value=DEFAULT_UNSELECTED, options=[DEFAULT_UNSELECTED] + field_options, name=IMAGE_SELECTION)\\n mimeselect = Select(title=\\\"MIME Type\\\", value=DEFAULT_UNSELECTED, options=[DEFAULT_UNSELECTED] + SUPPORTED_MIME_TYPES, name=MIME_SELECTION)\\n imageselect.on_change('value', lambda attr, old, new: image_selection_change())\\n mimeselect.on_change('value', lambda attr, old, new: image_selection_change())\\n d.add_root(column(Div(text=\\\"\\\"), widgetbox([imageselect, mimeselect]), name=IMAGE_MIME_SELECTION))\\n\\n if graph_val in [\\\"table\\\"]:\\n # TODO: limit selectable columns to whose of the same size (table height)\\n # use just the field name; don't show properties in the multi-select box\\n col_options = [k for k in props if not any (apv in k for apv in [APV_RECVD, APV_SEQNO, APV_MODEL] ) ]\\n columnmultiselect = MultiSelect(title=\\\"Columns:\\\", value=[], options=col_options, name=COLUMN_MULTISELECT)\\n columnmultiselect.on_change('value', lambda attr, old, new: column_selection_change())\\n d.add_root(column(Div(text=\\\"\\\"), widgetbox([columnmultiselect]), name=COLUMN_SELECTION))\\n\\n if graph_val in [\\\"raw\\\"]:\\n p = figure(plot_width=500, plot_height=500,\\n background_fill_color=\\\"white\\\",\\n y_range=(-40, 0), title=\\\"\\\", name=FIGURE_MODEL)\\n p.xaxis.visible = False\\n p.yaxis.visible = False\\n sind = run_handlers.get_source_index(d.session_context.id, model_id, message_name)\\n _install_callback_and_cds(sind, model_id, message_name, stream_limit=1)\\n p.text(x='apv_sequence_number',\\n y=0,\\n text='apv_model_as_string',\\n source=d.get_model_by_name(sind),\\n text_font_size=\\\"10pt\\\",\\n text_line_height=0.7,\\n text_baseline=\\\"top\\\",\\n text_align=\\\"left\\\")\\n p.x_range.follow = \\\"end\\\" # don't jam all the data into the graph; \\\"window\\\" it\\n p.x_range.follow_interval = 1 # don't jam all the data into the graph; \\\"window\\\" it\\n p.x_range.range_padding = 0\\n d.add_root(p)\",\n \"def on_selection(self, analysis_selection, make_new_analysis):\\n landmark_indexes = self.landmark_index_from_selection(\\n analysis_selection)\\n if self.demo_type == DemoType.HYPERSPECTRAL_DEMO:\\n # Pass area influenced to the hyperspectral viewer\\n self.data_gui.set_static_mask(\\n self.analysis.get_area_of_influence(landmark_indexes))\\n\\n if make_new_analysis:\\n self.make_new_analysis(self.analysis, analysis_selection)\\n else:\\n if self.demo_type == DemoType.LABELLED_DEMO:\\n # Pass data indexes to labelled viewer\\n self.data_gui.set_image_indexes(\\n self.data_index_from_selection(analysis_selection))\",\n \"def on_change(self, attr, old, new):\\n n = self.labels.index(new) + 1 # Select 0-indexed\\n self.notify(set_figures(n))\",\n \"def img_dict_updated(self, change):\\n if change[\\\"value\\\"]:\\n self.select_dataset(self.io_model.img_dict_default_selected_item)\\n self.init_plot_status()\",\n \"def state_chosen_do(cfg, app, win, events):\",\n \"def SelectPresentation(self, event):\\n pass\",\n \"def update(self):\\r\\n\\r\\n # Update the vision frames in the system\\r\\n self._system.update()\\r\\n\\r\\n # Create blank PIL images to hold the video streams\\r\\n layered = PIL.Image.new('RGBA', (400, 400))\\r\\n stacked = PIL.Image.new('RGBA', (200, 800))\\r\\n control = PIL.Image.new('RGBA', (600, 800))\\r\\n\\r\\n focalpoint = self._system[self._appString[\\\"device\\\"].get()].focalpoint()\\r\\n # print(focalpoint)\\r\\n\\r\\n # Get each vision key and vision for the selected device\\r\\n visionList = [(visionKey, vision) for visionKey, vision in self._system[self._appString[\\\"device\\\"].get()]]\\r\\n\\r\\n # Loop through each vision in the vision list\\r\\n for i, (visionKey, vision) in enumerate(visionList):\\r\\n\\r\\n # Grab the frames from the vision when it is \\\"curr\\\"\\r\\n frameList = [frame for frameKey, frame in vision if frameKey==self._appString[\\\"frame\\\"].get()]\\r\\n\\r\\n # Loop through each frame in the frame list\\r\\n for frame in frameList:\\r\\n\\r\\n # Get the properties and turn the image into RGBA\\r\\n ratio, size = vision.properties()\\r\\n rgbFrame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)\\r\\n\\r\\n # print(rgbFrame.shape)\\r\\n width, height, channels = rgbFrame.shape\\r\\n\\r\\n # Paste the images together in layered\\r\\n\\r\\n imgFrame = PIL.Image.fromarray(cv2.resize(rgbFrame, (int(400 * ratio), int(400 * ratio))))\\r\\n layered.paste(imgFrame, (int(200 * (1 - ratio)), int(200 * (1 - ratio))))\\r\\n\\r\\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (200 / width)), int(200 * (1 - ratio) - focalpoint[1] * (200 / height))))\\r\\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (200 // width)), int(200 * (1 - ratio) - focalpoint[1] * (200 // height))))\\r\\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (ratio ** -1)), int(200 * (1 - ratio) - focalpoint[1] * (ratio ** -1))))\\r\\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (200/width) / ratio), int(200 * (1 - ratio) - focalpoint[1] * (200/height) / ratio)))\\r\\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (200 / width)), int(200 * (1 - ratio) - focalpoint[1] * (200 / height))))\\r\\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (ratio ** -1) / 200), int(200 * (1 - ratio) - focalpoint[1] * (ratio ** -1) / 200)))\\r\\n # layered.paste(imgFrame, (int(200 * (1 - ratio) + focalpoint[0] * (400//width * (1- ratio))), int(200 * (1 - ratio) - focalpoint[1] * (400//height * (1 - ratio)))))\\r\\n\\r\\n # Paste the images together in stacked\\r\\n imgFrame = PIL.Image.fromarray(cv2.resize(rgbFrame, (200, 200)))\\r\\n stacked.paste(imgFrame, (0, 200 * i))\\r\\n\\r\\n # Add the stacked image to the canvas\\r\\n self._pilFrames[\\\"stacked\\\"] = PIL.ImageTk.PhotoImage(image=stacked)\\r\\n self._appCanvas[\\\"stacked\\\"].create_image(100, 0, image=self._pilFrames[\\\"stacked\\\"], anchor=tkinter.NW)\\r\\n\\r\\n # Add the layered image to the canvas\\r\\n self._pilFrames[\\\"layered\\\"] = PIL.ImageTk.PhotoImage(image=layered)\\r\\n self._appCanvas[\\\"layered\\\"].create_image(0, 0, image=self._pilFrames[\\\"layered\\\"], anchor=tkinter.NW)\\r\\n\\r\\n # Add the control image to the canvas\\r\\n imgFrame = cv2.cvtColor(self._system[self._appString[\\\"device\\\"].get()][self._appString[\\\"vision\\\"].get()][self._appString[\\\"frame\\\"].get()], cv2.COLOR_BGR2RGBA)\\r\\n control = PIL.Image.fromarray(cv2.resize(imgFrame, (600, 600)))\\r\\n self._pilFrames[\\\"control\\\"] = PIL.ImageTk.PhotoImage(image=control)\\r\\n self._appCanvas[\\\"control\\\"].create_image(100, 90, image=self._pilFrames[\\\"control\\\"], anchor=tkinter.NW)\\r\\n\\r\\n # Continue to update with a delay of 15\\r\\n self.after(15, self.update)\",\n \"def launch_GUV_GUI(self):\\n for i in self.parameters['selected_series']:\\n print(f\\\"Analysing series {i}\\\")\\n self.stack.bundle_axes = 'yx'\\n finderparams = ParameterList(filename=self.parameters['filename'],\\n channel=self.parameters['channel'],\\n intensity_channel=self.parameters['intensity_channel'],\\n pixel_microns=self.parameters['pixel_microns'])\\n if self.has_multiple_series:\\n self.stack.default_coords['v'] = i\\n finderparams.series = i\\n GUV_Control(self.stack, finderparams) # launch the GUI that can find GUVs and let the user remove them\\n \\n self.quit()\",\n \"def refresh(self):\\n\\n # Set Graphics scene\\n self.setScene(QtGui.QGraphicsScene())\\n self._connections = set()\\n self._nodes = {}\\n self._selection = set()\\n self._manipulation_mode = 0\\n self._selection_rect = None\",\n \"def image_selection_change():\\n\\n def return_image(val, model_id, message_name, field_name, mime, sind):\\n \\\"\\\"\\\"Returns a URL resolvable by the probe\\\"\\\"\\\"\\n column_data_source = curdoc().get_model_by_name(sind)\\n index = column_data_source.tags[0]\\n url = \\\"http://{0}/image/\\\".format(_host) + \\\"---\\\".join([model_id, message_name, field_name, mime, sind, str(index)])\\n return url\\n\\n d = curdoc()\\n _remove_fig(d)\\n model_id, message_name, _ = run_handlers.get_modelid_messagename_type(d)\\n image_field = d.get_model_by_name(IMAGE_SELECTION).value.split(\\\" :\\\")[0]\\n mime = d.get_model_by_name(MIME_SELECTION).value\\n\\n if image_field != DEFAULT_UNSELECTED and mime != DEFAULT_UNSELECTED:\\n plot = figure(plot_width=500, plot_height=500, title=\\\"\\\", x_range=Range1d(start=0, end=1), y_range=Range1d(start=0, end=1), name=FIGURE_MODEL)\\n sind = run_handlers.get_source_index(d.session_context.id, model_id, message_name, image_field + mime)\\n\\n _install_callback_and_cds(sind, model_id, message_name,\\n {image_field: [return_image, {\\\"model_id\\\": model_id,\\n \\\"message_name\\\": message_name,\\n \\\"field_name\\\": image_field,\\n \\\"mime\\\": mime,\\n \\\"sind\\\": sind}]},\\n stream_limit=1)\\n plot.image_url(url=image_field, x=0, y=1, h=1, w=1, source=d.get_model_by_name(sind))\\n d.add_root(plot)\",\n \"def callback_selectstate(self, attrname, old, new):\\n self._update_chart(self.selectstate.value)\",\n \"def on_feature_choice(self, event):\\n\\n self.log.trace(\\\"Handle feature selection by user.\\\")\\n result = {'successful': False}\\n\\n try:\\n # determine feature selected\\n module_name=None\\n if not self.custom_module: module_name = self.input_module.GetString(self.input_module.GetSelection())\\n feature_name = event.GetString()\\n\\n self.story_choices = []\\n for selection in DEFAULT_SEL:\\n self.story_choices.append(selection)\\n if feature_name.lower() == CUSTOM_SEL.lower():\\n # set custom flag\\n self.custom_feature = True\\n # show custom input\\n self.input_custom_feature.Show()\\n else:\\n # clear custom flag\\n self.custom_feature = False\\n # make sure custom field is hidden\\n self.input_custom_feature.Hide()\\n if feature_name.lower() != BLANK_SEL.lower():\\n # return all features for module\\n self.log.trace(\\\"Rebuilding user story list for %s module ...\\\" % feature_name)\\n stories = \\\\\\n self.database.return_user_stories_for_feature(feature_name, module=module_name)['user stories']\\n\\n # build story list\\n for story in stories:\\n self.story_choices.append(story['name'])\\n\\n # set feature choices to selection\\n self.input_story.SetItems(self.story_choices)\\n self._update_story_input_according_to_custom_feature_flag()\\n self.log.trace(\\\"User Story list for %s feature rebuilt.\\\" % feature_name)\\n\\n # reset test selections\\n self.log.trace(\\\"Reseting test list ...\\\")\\n self.test_choices = []\\n for selection in DEFAULT_SEL:\\n self.test_choices.append(selection)\\n self.input_test.SetItems(self.test_choices)\\n self._update_test_input_according_to_custom_story_flag()\\n self.log.trace(\\\"Test list reset.\\\")\\n\\n # reset testcase selections\\n self.log.trace(\\\"Reseting test case list ...\\\")\\n self.testcase_choices = []\\n for selection in DEFAULT_SEL:\\n self.testcase_choices.append(selection)\\n self.input_testcase.SetItems(self.testcase_choices)\\n self._update_testcase_input_according_to_custom_test_flag()\\n self.log.trace(\\\"Test case list reset.\\\")\\n\\n result['successful'] = True\\n except BaseException, e:\\n self.handle_exception(e, \\\"handle feature selection by user\\\")\\n\\n # return\\n return result\",\n \"def collection_selected(self):\\n self.processgraph.set_collection(str(self.collectionBox.currentText()))\\n self.reload_processgraph_view()\",\n \"def update(self):\\n #update checkboxes\\n self.average_check_box.SetValue(self.parent.fftsink.average)\\n self.use_persistence_check_box.SetValue(self.parent.fftsink.use_persistence)\\n self.peak_hold_check_box.SetValue(self.parent.fftsink.peak_hold)\\n #update radio buttons\\n try:\\n index = list(DIV_LEVELS).index(self.parent.fftsink.y_per_div)\\n self.radio_buttons[index].SetValue(True)\\n except: pass\",\n \"def OnPageChanged(self, page=None, trigger=None):\\n if trigger in [\\\"parm_batch\\\", \\\"fit_batch\\\", \\\"page_add_batch\\\",\\n \\\"tab_init\\\", \\\"tab_browse\\\"]:\\n return\\n # When parent changes\\n # This is a necessary function for PyCorrFit.\\n # This is stuff that should be done when the active page\\n # of the notebook changes.\\n if self.parent.notebook.GetPageCount() == 0:\\n self.Selector.SelectBox.SetItems([])\\n self.Selector.sp.Disable()\\n else:\\n oldlabels = self.Selector.curvelabels\\n self.Selector.sp.Enable()\\n # Sticky behavior cleaned up in 0.7.8\\n curvedict, labels = self.GetCurvedict()\\n self.Selector.curvedict = curvedict\\n self.Selector.labels = labels\\n self.Selector.ProcessDict()\\n self.labels = labels\\n if oldlabels != self.Selector.curvelabels:\\n self.Selector.SelectBox.SetItems(\\n self.Selector.curvelabels)\\n for i in np.arange(len(self.Selector.curvekeys)):\\n self.Selector.SelectBox.SetSelection(i)\\n self.Selector.OnUpdatePlot(trigger=trigger)\",\n \"def _selected_labels_changed(self, name, old, new):\\n if self.value_lock.acquire(False):\\n try:\\n self.value = [self._options_dict[name] for name in new]\\n finally:\\n self.value_lock.release()\",\n \"def _update_frame(self):\\n # check if continue\\n if self._keep_updating:\\n self.__frame = self._cam.get_display_frame()\\n if self.__frame is not None:\\n self._cvn_camera_viewfinder.create_image(0, 0, image=self.__frame, anchor=tk.NW)\\n\\n self._root.after(self._delay, self._update_frame)\",\n \"def OnFrameShow(self):\\r\\n\\r\\n\\t\\t# Update local copy of config\\r\\n\\t\\tself._configtmp.update(self._config)\\r\\n\\r\\n\\t\\t# Fix notebook background color when switching themes in XP\\r\\n\\t\\tself.notebookApp.SetBackgroundColour(\\\\\\r\\n\\t\\t\\tself.notebookApp.GetThemeBackgroundColour())\\r\\n\\r\\n\\t\\t# Set flag\\r\\n\\t\\tself.toggleButtonRateFlag.SetValue(self._configtmp[\\\"flagimage\\\"])\\r\\n\\r\\n\\t\\t# Set ratings\\r\\n\\t\\tself._iconstars = [icons.getGrayStarBitmap(),\\r\\n\\t\\t\\ticons.getYellowStarBitmap(),\\r\\n\\t\\t\\ticons.getGrayOrangeStarBitmap(),\\r\\n\\t\\t\\ticons.getYellowOrangeStarBitmap()]\\r\\n\\t\\tself.SetStars()\\r\\n\\r\\n\\t\\t# Set image info\\r\\n\\t\\tself.textCtrlImageInfo.Clear()\\r\\n\\t\\tself.textCtrlImageInfo.WriteText(self._configtmp[\\\"imageinfo\\\"])\\r\\n\\r\\n\\t\\t# If login still valid, change text on Sign In page\\r\\n\\t\\tif (self._configtmp[\\\"userhash\\\"] != \\\"00000000000000000000000000000000\\\"):\\r\\n\\t\\t\\tself.staticTextSignedIn.SetLabel(\\\" You are signed in.\\\")\\r\\n\\t\\telse:\\r\\n\\t\\t\\tself.staticTextSignedIn.SetLabel(\\\"You are not signed in.\\\")\\r\\n\\t\\tusername = self._configtmp[\\\"username\\\"]\\r\\n\\t\\tself.textCtrlLogin.Clear()\\r\\n\\t\\tself.textCtrlLogin.WriteText(username)\\r\\n\\r\\n\\t\\t# Set options\\r\\n\\t\\t_ratelist = [1, 2, 3, 4, 5]\\r\\n\\t\\tself.choiceOptionRatedAtLeast.SetSelection(\\r\\n\\t\\t\\t_ratelist.index(self._configtmp[\\\"ratedatleast\\\"]))\\r\\n\\t\\t_percentlist = [5, 10, 20, 50, 75, 100]\\r\\n\\t\\tself.choiceOptionPercentUnrated.SetSelection(\\r\\n\\t\\t\\t_percentlist.index(self._configtmp[\\\"percentnew\\\"]))\\r\\n\\t\\t_changeeverylist = [900, 1800, 3600, 7200, 14400, 28800, 86400,\\r\\n\\t\\t\\t172800, 345600, 604800]\\r\\n\\t\\tself.choiceOptionChangeEvery.SetSelection(\\r\\n\\t\\t\\t_changeeverylist.index(self._configtmp[\\\"changeevery\\\"]))\\r\\n\\r\\n\\t\\t# Update complete, show frame\\r\\n\\t\\tself.Show()\\r\\n\\t\\tself.Raise()\",\n \"def _updateSelectedItem(self):\\n plot = self.plot\\n if plot is not None:\\n selected = plot.selection().getSelectedItems()\\n # Give priority to image over scatter\\n for klass in (items.ImageBase, items.Scatter):\\n for item in selected:\\n if isinstance(item, klass):\\n # Found a matching item, use it\\n self.getHistogramWidget().setItem(item)\\n return\\n self.getHistogramWidget().setItem(None)\",\n \"def sgnRenderCurrentFrame(self):\\n\\n self.uiSaveSelectedRenders()\\n\\n self.core.render(self.lstSelectedRenders, bCurrentFrame = True)\",\n \"def _update_visual(self):\\n\\n # Check if the options are opened\\n if self._is_opened:\\n\\n self._option_border.set_color(self.border_press)\\n\\n else:\\n\\n self._option_border.set_color((0, 0, 0, 0))\",\n \"def synchronize_slider(self):\\n\\n # Block slider signals to avoid a shortcut.\\n self.slider_frames.blockSignals(True)\\n\\n if self.frame_ordering == \\\"quality\\\":\\n self.quality_index = self.listWidget.currentRow()\\n self.frame_index = self.quality_sorted_indices[self.quality_index]\\n self.slider_frames.setValue(self.quality_index + 1)\\n else:\\n self.frame_index = self.listWidget.currentRow()\\n self.quality_index = self.rank_indices[self.frame_index]\\n self.slider_frames.setValue(self.frame_index + 1)\\n\\n # Unblock the slider signals again.\\n self.slider_frames.blockSignals(False)\\n\\n # Update the image in the viewer.\\n self.frame_selector.setPhoto(self.frame_index)\",\n \"def vistrailChanged(self):\\n from vistrails.gui.vistrails_window import _app\\n select_node = True\\n if _app._previous_view and _app._previous_view.window() != self.window():\\n select_node = False\\n self.scene().setupScene(self.controller, select_node)\\n if self.controller and self.controller.reset_version_view:\\n self.scene().fitToAllViews()\\n if self.controller:\\n # self.versionProp.updateVersion(self.controller.current_version)\\n self.versionProp.updateVersion(self.controller.current_version)\\n self.emit(QtCore.SIGNAL(\\\"vistrailChanged()\\\"))\",\n \"def poll_selection(self):\\r\\n osName = platform.system()\\r\\n\\r\\n ## Check if the user changed the KSDK_path\\r\\n try:\\r\\n checkPath = self.widgetList[1].get()\\r\\n if checkPath != self.localSDK.path:\\r\\n self.ask_set_directory(True, 1)\\r\\n\\r\\n ## Check if user updated project name\\r\\n checkName = self.widgetList[4].get()\\r\\n if checkName != self.newProj.name:\\r\\n if kT.check_proj_name(checkName):\\r\\n self.newProj.name = checkName\\r\\n else:\\r\\n self.newProj.name = None\\r\\n if self.prevName != checkName:\\r\\n tkMessageBox.showinfo(\\\"Invalid Project Name\\\",\\\\\\r\\n \\\"No spaces or special characters.\\\")\\r\\n self.prevName = checkName\\r\\n kT.debug_log(\\\"Invalid name\\\")\\r\\n except AttributeError:\\r\\n kT.debug_log(\\\"Basic Changed menu\\\", sys.exc_info()[2])\\r\\n #return\\r\\n\\r\\n try:\\r\\n now = self.widgetList[6].curselection()\\r\\n if now != self.curr:\\r\\n if len(self.widgetList[6].curselection()) > 0:\\r\\n try:\\r\\n self.displayBoard = PhotoImage(data=self.imageList[int(now[0])])\\r\\n except IndexError:\\r\\n kT.debug_log(now[0], sys.exc_info()[2])\\r\\n self.widgetList[8].grid_remove()\\r\\n self.widgetList[8] = Button(self, \\\\\\r\\n image=self.displayBoard, \\\\\\r\\n command=lambda:\\\\\\r\\n self.web_launch(self.localSDK.brdList[\\\\\\r\\n int(self.widgetList[6].curselection()[0])]))\\r\\n self.widgetList[8].image = self.displayBoard\\r\\n self.widgetList[8].grid(row=5, column=3, columnspan=3, sticky=E+W+N+S)\\r\\n self.widgetList[8].bind(\\\"<Enter>\\\", \\\\\\r\\n lambda h: self.update_tips('Is this your board?\\\\n' + \\\\\\r\\n 'If so, ' + \\\\\\r\\n 'then clicking on the board' + \\\\\\r\\n ' image will take you to the ' + \\\\\\r\\n 'board homepage on ' + \\\\\\r\\n 'freescale.com.\\\\n\\\\n'))\\r\\n self.widgetList[8].bind(\\\"<Leave>\\\", \\\\\\r\\n lambda h: self.update_tips(self.defaultHelp))\\r\\n self.curr = now\\r\\n try:\\r\\n self.currBoard = int(self.widgetList[6].curselection()[0]) + 1\\r\\n # Clear out driver list and board\\r\\n self.newProj.board = ()\\r\\n self.newProj.drvList = []\\r\\n # Configure ksdkProj given GUI state\\r\\n self.localSDK.get_version()\\r\\n self.newProj.name = self.widgetList[4].get()\\r\\n self.newProj.setKsdkPath(self.localSDK.path)\\r\\n self.newProj.sdkVer = self.localSDK.version\\r\\n self.newProj.useBSP = not self.localSDK.isNewVersion()\\r\\n except IndexError:\\r\\n self.displayBoard = PhotoImage(data=kImg.boardImages['kds_icon.gif'])\\r\\n self.widgetList[8].config(image=self.displayBoard)\\r\\n self.widgetList[8].image = self.displayBoard\\r\\n self.widgetList[8].config(command=lambda: self.web_launch(kImg.boardImages['NoPreview.gif']))\\r\\n kT.debug_log(\\\"Index Error\\\", sys.exc_info()[2])\\r\\n #return\\r\\n except IndexError:\\r\\n kT.debug_log(\\\"Index Error\\\", sys.exc_info()[2])\\r\\n #return\\r\\n except AttributeError:\\r\\n kT.debug_log(\\\"AttributeError\\\", sys.exc_info()[2])\\r\\n return\\r\\n\\r\\n self._retLoop = self.after(250, self.poll_selection)\",\n \"def update(self):\\r\\n\\r\\n self.cmbAssembly.handler_block(self._lst_handler_id[0])\\r\\n self.cmbAssembly.set_active(self._model.assembly_id)\\r\\n self.cmbAssembly.handler_unblock(self._lst_handler_id[0])\\r\\n\\r\\n self.cmbDistribution.handler_block(self._lst_handler_id[1])\\r\\n self.cmbDistribution.set_active(self._model.distribution_id)\\r\\n self.cmbDistribution.handler_unblock(self._lst_handler_id[1])\\r\\n\\r\\n self.cmbConfType.handler_block(self._lst_handler_id[2])\\r\\n self.cmbConfType.set_active(self._model.confidence_type)\\r\\n self.cmbConfType.handler_unblock(self._lst_handler_id[2])\\r\\n\\r\\n self.cmbConfMethod.handler_block(self._lst_handler_id[3])\\r\\n self.cmbConfMethod.set_active(self._model.confidence_method)\\r\\n self.cmbConfMethod.handler_unblock(self._lst_handler_id[3])\\r\\n\\r\\n self.cmbFitMethod.handler_block(self._lst_handler_id[4])\\r\\n self.cmbFitMethod.set_active(self._model.fit_method)\\r\\n self.cmbFitMethod.handler_unblock(self._lst_handler_id[4])\\r\\n\\r\\n self.txtDescription.handler_block(self._lst_handler_id[5])\\r\\n self.txtDescription.set_text(self._model.description)\\r\\n self.txtDescription.handler_unblock(self._lst_handler_id[5])\\r\\n\\r\\n self.txtConfidence.handler_block(self._lst_handler_id[6])\\r\\n if self._model.confidence < 1.0:\\r\\n Configurationidence = self._model.confidence * 100.0\\r\\n else:\\r\\n Configurationidence = self._model.confidence\\r\\n self.txtConfidence.set_text(str(Configurationidence))\\r\\n self.txtConfidence.handler_unblock(self._lst_handler_id[6])\\r\\n\\r\\n self.txtStartTime.handler_block(self._lst_handler_id[7])\\r\\n self.txtStartTime.set_text(str(self._model.start_time))\\r\\n self.txtStartTime.handler_unblock(self._lst_handler_id[7])\\r\\n\\r\\n self.txtEndTime.handler_block(self._lst_handler_id[8])\\r\\n self.txtEndTime.set_text(str(self._model.rel_time))\\r\\n self.txtEndTime.handler_unblock(self._lst_handler_id[8])\\r\\n\\r\\n self.txtRelPoints.handler_block(self._lst_handler_id[9])\\r\\n self.txtRelPoints.set_text(str(self._model.n_rel_points))\\r\\n self.txtRelPoints.handler_unblock(self._lst_handler_id[9])\\r\\n\\r\\n self.txtStartDate.handler_block(self._lst_handler_id[10])\\r\\n _start_date = Utilities.ordinal_to_date(self._model.start_date)\\r\\n self.txtStartDate.set_text(str(_start_date))\\r\\n self.txtStartDate.handler_unblock(self._lst_handler_id[10])\\r\\n\\r\\n self.txtEndDate.handler_block(self._lst_handler_id[11])\\r\\n _end_date = Utilities.ordinal_to_date(self._model.end_date)\\r\\n self.txtEndDate.set_text(str(_end_date))\\r\\n self.txtEndDate.handler_unblock(self._lst_handler_id[11])\\r\\n\\r\\n return False\",\n \"def OnButtonClick(self):\\n self.choice()\",\n \"def onSelected(self):\\n pass\",\n \"def start_GUI(self):\\n experiment_names = list(GUI.api.get_experiment_names())\\n #selected_exp = None #value picked in the list\\n\\n branch_log_dict = GUI.api.get_branching_indep_to_dep()\\n #Separate columns for a new trial and a new experiment\\n\\n col_new_trial = [[sg.Radio('New Trial', \\\"RADIO1\\\", default=True, enable_events = True, key=\\\"new_trial_radio\\\", metadata='not_disable')],\\n [sg.Text(text = \\\"Please pick your experiment from the list below:\\\")], \\n [sg.Listbox(values=experiment_names, size=(30, 6), key=\\\"list\\\", select_mode = sg.LISTBOX_SELECT_MODE_SINGLE, enable_events= True)]]\\n \\n\\n #metadata ahs true if we need to input filed\\n col_new_experiment = [[sg.Radio('New experiment', \\\"RADIO1\\\", enable_events=True, key=\\\"new_exp_radio\\\", metadata='not_disable')]]\\n col_new_experiment.extend(self.make_fields())#add fields to the form\\n layout = [[sg.Column(col_new_trial), sg.Column(col_new_experiment)], \\n [sg.Button(button_text= \\\"OK\\\", enable_events= True, key =\\\"OK\\\")]]\\n \\n window = sg.Window('New Data', layout, keep_on_top=True)#Creation of the window\\n while True:\\n event, values = window.read()\\n # End program if user closes window or\\n # presses the OK button\\n # you can use switch-case here instead of if statements\\n if event == sg.WIN_CLOSED:\\n #Indicate abort\\n return None, None, None, None\\n elif event == \\\"new_exp_radio\\\":#if new experiment is picked, then disable the elements for the new trial\\n #for evey field on which branching logic depends on, disable everything not selected\\n window['list'].update(disabled = True)\\n for row in col_new_experiment:\\n for elem in row:\\n if(elem.metadata != 'not_disable' and not isinstance(elem, sg.Text)):#do not block the radio button):\\n window[elem.Key].update(disabled = False)\\n \\n self.clear_disable_all(window, branch_log_dict, col_new_experiment)#we could just enable a few, instead\\n elif event == \\\"new_trial_radio\\\":#if new trial is picked, disable the elements for the new experiment, enable for the new trua\\n #disable everything in the form\\n for row in col_new_experiment:\\n for elem in row:\\n if(elem.metadata != 'not_disable' and not isinstance(elem, sg.Text)):#do not block the radio button and do not update textboxes\\n window[elem.Key].update(disabled = True)\\n #enable the listbox\\n \\n window['list'].update(disabled = False)\\n elif event == \\\"OK\\\":\\n field_missing = False\\n #Check if the listbox has a value or the form has a value\\n if values['new_exp_radio']:#we are doing new expriment\\n # printing_params = {\\\"paxton\\\":\\\"\\\"}\\n printing_params = {}\\n #Check the all the stuff in the form of the new experiment\\n for row in col_new_experiment:\\n if(field_missing):\\n break#do not check anymore\\n for elem in row:\\n if(elem.metadata != 'not_disable' and not isinstance(elem, sg.Text)):#do not check labels and the radio button\\n if (elem.metadata and values[elem.Key]== \\\"\\\"): #value ahs to be filled and not empty\\n field_missing = True\\n sg.popup_ok('Required fields are missing!')#if at least one field is empty, throw a popup and stop checking\\n break # Shows OK button\\n #if at least one field does not have a value, then we generate a popup\\n elif(values[elem.Key] != \\\"\\\"):#add to the dictonary of params\\n printing_params[elem.Key] = values[elem.Key]\\n \\n if not field_missing:\\n #if everything is filled, then validate\\n \\n #if user closes the popup, then the print is considered bad by default\\n is_valid, field_name = self.validate_fields(window, values)\\n if(is_valid):\\n print_result, folderPath = self.getPicturesPrintEval()\\n window.close()\\n #now, we also return print_result\\n return \\\"add_record\\\", printing_params, print_result, folderPath\\n else:\\n sg.popup_ok(\\\"The field could not be validated: \\\" + field_name)\\n \\n elif values['new_trial_radio']:#could use else\\n if values['list'] == []:\\n sg.popup_ok('Required fields are missing!')\\n continue#go to while loop\\n #we got here, so we now know the record_id of the experiment we want to do the new trial for\\n record_lst = GUI.api.get_elements(values['list'][0])\\n #create a new window with print quality + pictures\\n print_result, folderPath = self.getPicturesPrintEval()\\n window.close()\\n return \\\"add_trial\\\", record_lst, print_result, folderPath\\n elif event in branch_log_dict:#if branching logic is dependent on this element\\n #we could only enable/disable stuff affected by the element\\n self.enable_selected(window, copy.deepcopy(values), branch_log_dict, event)\\n self.disable_not_selected(window, copy.deepcopy(values), branch_log_dict, event)\",\n \"def modelselec_change():\\n d = curdoc()\\n _remove_fig(d)\\n _remove_selection(d)\\n d.remove_root(d.get_model_by_name(AFTER_MODEL_SELECTION))\\n modelselec = d.get_model_by_name(MODEL_SELECTION)\\n msv = modelselec.value\\n if msv != DEFAULT_UNSELECTED:\\n model_id, message_name, model_type = run_handlers.get_modelid_messagename_type(d)\\n if model_type == \\\"protobuf\\\":\\n message = Select(title=\\\"Message Selection\\\", value=DEFAULT_UNSELECTED, options=list(data.proto_data_structure[model_id][\\\"messages\\\"].keys()) + [DEFAULT_UNSELECTED], name=MESSAGE_SELECTION)\\n graphs = Select(title=\\\"Graph Selection\\\", value=DEFAULT_UNSELECTED, options=[], name=GRAPH_SELECTION)\\n message.on_change('value', lambda attr, old, new: message_change())\\n graphs.on_change('value', lambda attr, old, new: graphs_change())\\n selec = row(widgetbox([message]), widgetbox([graphs]), name=AFTER_MODEL_SELECTION)\\n else: # there is no message selection here\\n graphs = Select(title=\\\"Graph Selection\\\", value=DEFAULT_UNSELECTED, options=GRAPH_OPTIONS, name=GRAPH_SELECTION)\\n graphs.on_change('value', lambda attr, old, new: graphs_change())\\n selec = row(widgetbox([graphs]), name=AFTER_MODEL_SELECTION)\\n d.add_root(selec)\\n d.add_root(selec)\",\n \"def update_rec_configs_choice(self):\\n # this will update the configuration choices in reconstruction tab\\n # fill out the config_id choice bar by reading configuration files names\\n self.rec_ids = []\\n for file in os.listdir(os.path.join(self.main_win.experiment_dir, 'conf')):\\n if file.endswith('_config_rec'):\\n self.rec_ids.append(file[0:len(file) - len('_config_rec')])\\n if len(self.rec_ids) > 0:\\n self.rec_id.addItems(self.rec_ids)\\n self.rec_id.show()\",\n \"def update_(self):\\n self.update_listbox()\\n self.update_infobox()\\n self.update_statusbar()\\n self.listbox.select_set(0)\\n self.listbox.focus_set()\",\n \"def run(self):\\n split_old_type = self.old_type.split(\\\"/\\\")\\n types_list = None\\n \\n if isinstance(self.object, scg_objects.SCgNode):\\n types_list = scg_alphabet.get_node_types()\\n elif isinstance(self.object, scg_objects.SCgPair):\\n types_list = scg_alphabet.get_pair_types()\\n else:\\n raise Exception(\\\"Unknown object type %s\\\" % str(self.object))\\n \\n assert len(types_list) > 0\\n \\n split_types = [] \\n for _type in types_list:\\n split_types.append(_type.split(\\\"/\\\"))\\n \\n # parse possible values and create controls for changing them\\n for idx in xrange(0, len(split_types[0])):\\n values = []\\n for _type in split_types:\\n if not _type[idx] in values:\\n values.append(_type[idx])\\n \\n ctrl = ChoiceControl(values, split_old_type[idx], self.panel, self.updateType)\\n \\n self.controls.append(ctrl)\\n \\n # layout created controls\\n height = 5\\n \\n for ctrl in self.controls:\\n ctrl.panel.setPosition(3, height)\\n height += ctrl.panel.getHeight() + 5\\n width = ctrl.panel.getWidth()\\n \\n self.button_ok.setPosition(10, height + 10)\\n self.button_cancel.setPosition(65, height + 10)\\n \\n pos = render_engine.pos3dTo2dWindow(self.object.getPosition() + self.object.getScale() / 2)\\n # make some offset\\n width += 20\\n height += 45 \\n self.panel.setSize(width, height)\\n \\n # sure that dialog isn't placed out of screen \\n x, y = pos\\n x2 = x + width\\n y2 = y + height\\n \\n if x2 >= render_engine.Window.width:\\n x = render_engine.Window.width - width\\n elif x < 0:\\n x = 0\\n \\n if y2 >= render_engine.Window.height:\\n y = render_engine.Window.height - height\\n elif y < 0:\\n y = 0 \\n \\n self.panel.setPosition(x, y)\\n \\n # show panel\\n self.panel.setVisible(True)\",\n \"def update_visualizer(self):\\n if self.visualizer:\\n if self.frame_count == 2:\\n self.visualizer.add_geometry(self.vis_points)\\n self.visualizer.update_geometry(self.vis_points)\\n self.visualizer.poll_events()\\n self.visualizer.update_renderer()\\n time.sleep(0.001)\\n self.frame_count += 1\",\n \"def player_processframe_event(self, frame):\\n\\t\\tpaths = self._panel_path.value.datasets\\n\\t\\tareas = self._panel_area.value.datasets\\n\\t\\tcolors = self._panel_colors.value.datasets\\n\\t\\timages = self._panel_imgs.value.images\\n\\n\\t\\t# check if should use the current frame or an image selected to background\\n\\t\\tframe = frame if len(images)!=1 else images[0].image.copy()\\n\\t\\tindex = self._player.video_index-1\\n\\t\\n\\t\\tfor path in paths:\\n\\t\\t\\t# draw the path if the option is selected\\n\\t\\t\\tif self._drawpath.value: path.draw_path(frame, None, index)\\n\\n\\t\\t\\tarea = self.get_object_area(path, areas, index)\\n\\t\\t\\tif area is not None:\\n\\t\\t\\t\\tcolor \\t = self.get_object_color(path, colors, index)\\n\\t\\t\\t\\tposition = path.get_position(index)\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif position is not None and area is not None and color is not None:\\n\\t\\t\\t\\t\\tradius = int(round(math.sqrt(area/math.pi)))\\t\\t\\t\\t\\n\\t\\t\\t\\t\\tcv2.circle(frame, position, radius, color, -1)\\n\\n\\t\\tself.draw_events(index, frame)\\n\\n\\t\\treturn frame\",\n \"def onFrameUpdated(self):\\n pass\",\n \"def update(self):\\n # Get frame from video source:\\n ret, frame = self.vid.read()\\n\\n if ret:\\n # Convert the captured frame into grayscale\\n gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\\n gray = cv2.equalizeHist(gray)\\n\\n # Get all faces from the video frame\\n faces = self.faceCascade.detectMultiScale(gray, 1.2,5)\\n\\n # For each face in faces\\n for (x, y, w, h) in faces:\\n # Create rectangle around the face\\n cv2.rectangle(frame, (x-20,y-20), (x+w+20,y+h+20), (0,255,0), 4)\\n\\n # Recognize the face belongs to which ID\\n Id = self.recognizer.predict(gray[y:y+h,x:x+w])\\n\\n ### IDENTIFICATION & SOCKET CODE GOES HERE\\n if Id[0] == self.user_id:\\n # If the target face is found 10 times then access is granted\\n self.identification_count += 1\\n if self.identification_count > 10:\\n self.master.switch_frame(AccessGranted)\\n\\n name_to_put = self.user_name\\n else:\\n name_to_put = \\\"Unknown - Access Denied\\\"\\n\\n # Put text describe who is in the picture\\n cv2.rectangle(frame, (x-22,y-90), (x+w+22, y-22), (0,255,0), -1)\\n cv2.putText(frame, str(name_to_put), (x,y-40), self.font, 2, (255,255,255), 3)\\n\\n self.after(50, self.update)\",\n \"def setupOptionsFrame(self):\\n\\n # CPU / CUDA options\\n self.device.addItems([\\\"cuda\\\", \\\"cpu\\\"])\\n self.scriptedEffect.addLabeledOptionsWidget(\\\"Device:\\\", self.device)\\n\\n self.modality.addItems([\\\"CT\\\", \\\"MRI\\\"])\\n self.scriptedEffect.addLabeledOptionsWidget(\\\"Modality:\\\", self.modality)\\n\\n # Add ROI options\\n self.roiSelector.nodeTypes = ['vtkMRMLMarkupsROINode']\\n self.roiSelector.noneEnabled = True\\n self.roiSelector.setMRMLScene(slicer.mrmlScene)\\n self.scriptedEffect.addLabeledOptionsWidget(\\\"ROI: \\\", self.roiSelector)\\n\\n # Toggle ROI visibility button\\n toggleROIVisibilityButton = qt.QPushButton(\\\"Toggle ROI Visibility\\\")\\n toggleROIVisibilityButton.objectName = self.__class__.__name__ + 'ToggleROIVisibility'\\n toggleROIVisibilityButton.setToolTip(\\\"Toggle selected ROI visibility\\\")\\n toggleROIVisibilityButton.connect('clicked()', self.toggleROIVisibility)\\n self.scriptedEffect.addOptionsWidget(toggleROIVisibilityButton)\\n\\n # Apply button\\n applyButton = qt.QPushButton(\\\"Apply\\\")\\n applyButton.objectName = self.__class__.__name__ + 'Apply'\\n applyButton.setToolTip(\\\"Extract liver from input volume\\\")\\n applyButton.connect('clicked()', self.onApply)\\n self.scriptedEffect.addOptionsWidget(applyButton)\",\n \"def selectFrame(event, x, y, flags, param):\\n global drag_start, sel, patch\\n if event == cv2.EVENT_LBUTTONDOWN:\\n drag_start = x, y\\n sel = 0,0,0,0\\n elif event == cv2.EVENT_LBUTTONUP:\\n if sel[2] > sel[0] and sel[3] > sel[1]:\\n patch = frame[sel[1]:sel[3],sel[0]:sel[2]]\\n cv2.imshow(\\\"result\\\", patch)\\n color_data[\\\"upperPt\\\"] = sel[:1]\\n color_data[\\\"lowerPt\\\"] = sel[2:]\\n drag_start = None\\n elif drag_start:\\n #print flags\\n if flags & cv2.EVENT_FLAG_LBUTTON:\\n minpos = min(drag_start[0], x), min(drag_start[1], y)\\n maxpos = max(drag_start[0], x), max(drag_start[1], y)\\n sel = minpos[0], minpos[1], maxpos[0], maxpos[1]\\n #img = cv2.cvtColor(frame, cv2.COLOR_GRAY2BGR)\\n img = frame.copy()\\n cv2.rectangle(img, (sel[0], sel[1]), (sel[2], sel[3]), (0,255,255), 1)\\n cv2.imshow(\\\"select ROI\\\", img)\\n else:\\n print(\\\"selection is complete\\\")\\n print(sel)\\n drag_start = None\",\n \"def upd_view():\\n global state, current_view, show_actives, current_filename\\n nonlocal img, listbox\\n\\n with data_lock:\\n if state == 1:\\n current_filename = None\\n state = 2\\n listbox.delete(0, tk.END)\\n for item in current_view.actions.by_type(wtl.actions.Click):\\n wtl_uid = str(item.target.wtl_uid)\\n text = item.target.metadata[\\\"text\\\"]\\n listbox.insert(tk.END, wtl_uid + f\\\" ({text})\\\")\\n\\n if state == 2:\\n filename = \\\"first\\\" if show_actives.get() == 0 else \\\"is_active\\\"\\n if filename != current_filename:\\n current_filename = filename\\n current_view.snapshot.screenshots[filename].save(Path(\\\".\\\"))\\n img = tk.PhotoImage(file=f\\\"{filename}.png\\\")\\n canvas.create_image(5, 5, anchor=tk.NW, image=img)\\n\\n window.after(250, upd_view)\",\n \"def _handle_gui_set(self,p_name):\\n if self._live_update:\\n self._update_param_from_tkvar(p_name)\",\n \"def selectionChanged(self, selected, deselected):\\n rows = [self.model.nodeFromIndex(row) for row in self.selmod1.selectedRows()]\\n self.updateStats(rows)\",\n \"def switch_frames(self, new_frameName):\\n\\n if new_frameName in self.__frame_names:\\n\\n #Give rise to a new frame\\n\\n if new_frameName == \\\"image_frame\\\":\\n image_frame= ImageFrame.Image_Frame(self.master,\\n self.width,\\n self.height)\\n image_frame.place(x = 0, y = 0)\\n \\n\\n elif new_frameName == \\\"audio_frame\\\":\\n audio_frame = AudioFrame.Audio_Frame(self.master,\\n self.width,\\n self.height)\\n audio_frame.place(x = 0, y = 0)\\n\\n elif new_frameName == \\\"doc_frame\\\":\\n not_yet = notReadyYetFrame.Not_Ready_Yet_Frame(self.master,\\n self.width,\\n self.height)\\n not_yet.place(x = 0, y = 0)\\n\\n else:\\n not_yet = notReadyYetFrame.Not_Ready_Yet_Frame(self.master,\\n self.width,\\n self.height)\\n not_yet.place(x = 0, y = 0)\\n\\n #Destroy the current frame\\n self.place_forget()\\n self.destroy()\",\n \"def state_choose_do(cfg, app, win, events):\",\n \"def apply_selection(self, rv, index, is_selected):\\r\\n self.selected = is_selected\",\n \"def plot_changed(self):\\n self.plotType = self.ui.selectPlotType.currentText()\\n self.value_changed()\",\n \"def apply_changes(self, updated_talk=None):\\r\\n self.presentationModel.select()\\r\\n self.select_talk(updated_talk)\\r\\n self.update_autocomplete_fields()\",\n \"def changement_frame(self):\\n\\n for widget in self.fenetre_scores.winfo_children():\\n widget.pack_forget()\\n\\n for widget in self.fenetre_regles.winfo_children():\\n widget.pack_forget()\\n\\n for widget in self.frame_jeu.winfo_children():\\n widget.pack_forget()\\n\\n for widget in self.winfo_children():\\n if widget != self.titre:\\n widget.pack_forget()\",\n \"def UpdateDisplay(self):\\n ##Jconf\\n self.chJconf.Clear()\\n for name in self.state.GetSurface(\\\"JconfDict\\\").GetNames():\\n self.chJconf.Append(name)\\n self.chJconf.SetStringSelection(self.state.GetSurface(\\\"JconfSelection\\\"))\\n self.chJconf.Enable(self.state.IsEnabled(\\\"JconfDict\\\") == True and\\n self.state.IsEnabled(\\\"JconfSelection\\\") == True and\\n self.state.GetSurface(\\\"Xplorer\\\") == True)\\n self.bEditJconf.Enable(self.state.IsEnabled(\\\"JconfDict\\\") and\\n self.state.GetSurface(\\\"Xplorer\\\") == True)\\n ##Name Server\\n self.cbNameServer.SetValue(self.state.GetSurface(\\\"NameServer\\\"))\\n self.cbNameServer.Enable(self.state.IsEnabled(\\\"NameServer\\\"))\\n ##Conductor\\n self.cbConductor.SetValue(self.state.GetSurface(\\\"Conductor\\\"))\\n self.cbConductor.Enable(self.state.IsEnabled(\\\"Conductor\\\"))\\n ##Xplorer\\n self.cbXplorer.SetValue(self.state.GetSurface(\\\"Xplorer\\\"))\\n self.cbXplorer.Enable(self.state.IsEnabled(\\\"Xplorer\\\"))\\n ##Desktop Mode\\n self.cbDesktop.SetValue(self.state.GetSurface(\\\"DesktopMode\\\"))\\n self.cbDesktop.Enable(self.state.IsEnabled(\\\"DesktopMode\\\"))\\n ##Xplorer Type\\n if self.state.GetSurface(\\\"DesktopMode\\\"):\\n self.rbXplorer.SetSelection(0)\\n else:\\n if (self.state.GetSurface(\\\"XplorerType\\\") == \\\"OSG-VEP\\\"):\\n self.rbXplorer.SetSelection(0)\\n else:\\n self.rbXplorer.SetSelection(1)\\n self.rbXplorer.Enable(self.state.IsEnabled(\\\"XplorerType\\\") == True and\\n self.state.GetSurface(\\\"DesktopMode\\\") == False and\\n self.state.GetSurface(\\\"Xplorer\\\") == True)\\n ##Cluster Node button\\n self.bCluster.Enable(CLUSTER_ENABLED and\\n self.state.GetSurface(\\\"Xplorer\\\") == True and\\n self.state.GetSurface(\\\"DesktopMode\\\") == False and\\n self.state.GetSurface(\\\"XplorerType\\\") == \\\"OSG-VEPC\\\")\\n return\",\n \"def select_ORF(self):\\n if self.data.has_key('ORF_selected'):\\n del self.data['ORF_selected']\\n self.data['DNAseq_status']='ORF_CHANGED'\\n #if no orf previously then this must be a new record?\\n else:\\n self.data['DNAseq_status']='NEW SEQ'\\n\\n # Start the ORF selection\\n import ORF_module\\n X=ORF_module.ORF_handler(self)\\n if self.data.has_key('ORF_selected'):\\n start=self.data['ORF_selected']['start']\\n stop=self.data['ORF_selected']['stop']\\n frame=self.data['ORF_selected']['frame']\\n ORF_num=self.data['ORF_selected']['number']\\n #\\n base_start=(start-1)*3+(frame-1)\\n base_stop=stop*3+(frame-1)\\n\\n # mark that we have an ORF and get rid of all useless info\\n self.data['Project saved']=None\\n #\\n # Activate the primer design button(s)\\n #\\n else:\\n pass\\n #\\n # Update everything\\n #\\n self.assess_status()\\n # Update view\\n self.update_sequence_window()\\n #self.data['DNAseq_status']='ALTERED'\\n\\n return\",\n \"def misc_select(self, event):\\n\\n self.selected_index = event.GetIndex()\\n self.update_properties()\",\n \"def onSelect_specimen(self, event):\\n new_s = self.specimens_box.GetValue()\\n if self.select_specimen(new_s):\\n self.update_selection()\\n else:\\n self.specimens_box.SetValue(self.s)\\n self.user_warning(\\n \\\"no specimen %s reverting to old specimen %s\\\" % (new_s, self.s))\",\n \"def _selection_changed(self, event):\\n if self.typeCombo.get() in Constants.TASKS[0:3]:\\n if self.subjectAdded == False:\\n self._placeWidgets(self.subjectLabel, self.subjectCombo)\\n self.subjectAdded = True\\n else:\\n if self.subjectAdded:\\n # Hide subject label and combobox\\n self.subjectLabel.place_forget()\\n self.subjectCombo.place_forget()\\n self.subjectAdded = False\\n self.row -= 1\",\n \"def selection_changed(self):\\n filter_name = self.cb_selectes_filter.currentText()\\n\\n # show filter description\\n self.infob.setText(filters_dict[filter_name].__doc__)\\n #print(self.selected_filter)\\n\\n self.compute(filter_name)\\n # afficher\\n self.update_display()\\n\\n self.commit()\",\n \"def change(self):\\r\\n\\r\\n # If checkboxes are available, check status and set boat speed reference line visibility accordingly.\\r\\n if self.cb:\\r\\n if self.cb_bt.checkState() == QtCore.Qt.Checked:\\r\\n for item in self.bt:\\r\\n item.set_visible(True)\\r\\n else:\\r\\n for item in self.bt:\\r\\n item.set_visible(False)\\r\\n # GGA\\r\\n if self.cb_gga.checkState() == QtCore.Qt.Checked:\\r\\n for item in self.gga:\\r\\n item.set_visible(True)\\r\\n # self.gga[0].set_visible(True)\\r\\n elif self.gga is not None:\\r\\n for item in self.gga:\\r\\n item.set_visible(False)\\r\\n # self.gga[0].set_visible(False)\\r\\n # VTG\\r\\n if self.cb_vtg.checkState() == QtCore.Qt.Checked:\\r\\n for item in self.vtg:\\r\\n item.set_visible(True)\\r\\n # self.vtg[0].set_visible(True)\\r\\n elif self.vtg is not None:\\r\\n for item in self.vtg:\\r\\n item.set_visible(False)\\r\\n # self.vtg[0].set_visible(False)\\r\\n\\r\\n # Draw canvas\\r\\n self.canvas.draw()\",\n \"def updateFrame(self, image):\\n self.currentFrame += 1\\n self.image = image.copy()\\n\\n detected = self.car_detector.detectCars(image)\\n picks = self.car_detector.non_max_suppression_fast(detected, 0.2)\\n\\n self.logger.debug(\\\" CURRENT CAR LIST\\\\n\\\")\\n self.printCars()\\n\\n self.logger.debug(\\\"\\\\nNew Picks {0!s}\\\\n\\\".format(picks))\\n\\n self.addCars(picks)\\n self.removeOldCars()\\n if len(self.cars) == 0:\\n self.logger.debug(\\\"EMPTY.... HELP\\\")\\n # self.printCars()\\n return self.drawCars()\",\n \"def select( self ):\\n self._has_change = True\",\n \"def __call__(self):\\n self.brain._update_fscale(self.factor)\\n for key in self.brain.keys:\\n if self.widgets[key] is not None:\\n self.widgets[key].set_value(self.brain._data[key])\",\n \"def _sync_gui(self):\\n self._update_buttons()\\n\\n self.turn_value_label.config(text=self.turn_value_text)\\n self.selected_piece_value_label.config(text=self.selected_piece_value_text)\\n\\n self.update()\",\n \"def _on_selection_changed(self, selection):\\n if self._updating_selection:\\n return\\n\\n self._updating_selection = True\\n\\n self._tree_selection.unselect_all()\\n for widget in selection:\\n gadget_iter = self._find_iter_by_widget(widget)\\n if gadget_iter:\\n select_iter(self._tree_view, gadget_iter)\\n\\n self._updating_selection = False\",\n \"def updateSelectionArea(self):\\n self.machine.setSelectionArea(self.points,\\n fill='hatch',\\n color=self.machine.color)\\n eventDict = prepareDrawingSignal('drawingProgress',\\n 'polygon',\\n self.points,\\n self.machine.parameters)\\n self.machine.plot.notify(**eventDict)\",\n \"def apply_selection(self, rv, index, is_selected):\\n self.selected = is_selected\",\n \"def select(self, image):\\n self.original = image\\n self.boundings = []\",\n \"def update_selection(self, game, obj):\\n self.clear()\\n if obj:\\n if obj in game.towers:\\n self.selected_tower = obj\\n self.update_selection_tower(self.selected_tower)\\n elif obj in game.monsters:\\n self.selected_monster = obj\\n self.update_selection_monster(self.selected_monster)\\n elif obj in self.monsters_images:\\n self.selected_monster = obj\\n self.update_selection_monster(self.selected_monster, False)\",\n \"def _visibleChannels_changed(self):\\n for i in range(0,8):\\n if i in self.visibleChannels:\\n self.masterContainer.plots[\\\"channel\\\"+str(i)][0].visible=True\\n else:\\n print i\\n self.masterContainer.plots[\\\"channel\\\"+str(i)][0].visible=False\",\n \"def updateBtnSelect(self):\\n logger.debug(\\\"update buttons\\\")\\n currSelection = cmds.ls(selection = True)\\n currTab = self.tabwidget.currentWidget()\\n\\n minus = [] #list of objects deselected\\n added = [] #list of objects added to selection\\n\\n for i in self.previousSelection:\\n if i not in currSelection: #object has been deselected\\n minus.append(i) #add to deselected list\\n for j in currSelection:\\n if j not in self.previousSelection: #object has been added to selection\\n added.append(j)\\n\\n #updated the number of selected objects for each button asociated with an object in one of the lists\\n for a in added:\\n logger.debug(\\\"added \\\"+a)\\n if a in self.objects[currTab]:\\n for btn in self.objects[currTab][a]:\\n btn.numSel+=1 #add one to the number of objects selected in the list of connections for the button\\n if btn.numSel == len(btn.connection): #change outline if the number selected is equal to the total number of objects connected to the button\\n btn.selected = True\\n btn.setChecked(True)\\n\\n for m in minus:\\n logger.debug(\\\"minus \\\"+m)\\n if m in self.objects[currTab]:\\n for btn in self.objects[currTab][m]:\\n btn.numSel-=1 #subtract one to the number of objects selected in the list of connections for the button\\n logger.debug(btn.numSel)\\n if btn.numSel < len(btn.connection): #change outline if the number selected is less than the total number of objects connected to the button\\n btn.selected = False\\n btn.setChecked(False)\\n\\n self.previousSelection= currSelection\\n\\n\\n if(self.edit ==True):\\n logger.debug(\\\"checkboxes\\\")\\n #updates the list of checkboxes\\n self.clearLayout(self.vbox) #clear list\\n sl = cmds.ls(sl = True) #get selection\\n for obj in sl: #add a checkbox for each object in selection\\n checkbox = QtWidgets.QCheckBox(obj)\\n checkbox.setChecked(True)\\n checkbox.stateChanged.connect(lambda state, o=obj, c=checkbox: self.stateChanged(o, c))\\n self.vbox.addWidget(checkbox) #add to layout\",\n \"def init_gui(self):\\r\\n self.root.title('Video Resizer')\\r\\n self.root.option_add('*tearOff', 'FALSE')\\r\\n self.grid(column=0, row=0, sticky='nsew')\\r\\n\\r\\n # Buttons getvideos, save videos, start resize\\r\\n self.openButton = ttk.Button(self, width=8, text=\\\"Browse\\\", command=self.getVideosPath)\\r\\n self.openButton.grid(column=1, row=2)\\r\\n self.saveButton = ttk.Button(self, width=8, text=\\\"Browse\\\", command=self.getCapturePath)\\r\\n self.saveButton.grid(column=3, row=2)\\r\\n self.startButton = ttk.Button(self, text='Start to Resize', command=self.startResizing)\\r\\n self.startButton.grid(column=0, row=5)\\r\\n self.multiStartButton = ttk.Button(self, text='Start to multi Resize', command=self.startMultiResizing)\\r\\n self.multiStartButton.grid(column=2, row=5)\\r\\n\\r\\n # listbox to choose what video type to save\\r\\n # add a label for the combobox\\r\\n ttk.Label(self, text=\\\"Select Video Type to Save\\\").grid(column=0, row=4)\\r\\n\\r\\n def clickMe():\\r\\n \\\"\\\"\\\"\\r\\n button clicked to select video type\\r\\n called when action is clicked\\r\\n :return:\\r\\n \\\"\\\"\\\"\\r\\n global Format\\r\\n Format = typeToChoose.get()\\r\\n print(Format)\\r\\n action.configure(text='selected ' + Format) # show the selected item after clicked\\r\\n action.configure(state='disabled') # button disabled after clicked\\r\\n\\r\\n # Button\\r\\n action = ttk.Button(self, text=\\\"Select \\\", command=clickMe)\\r\\n action.grid(column=2, row=4)\\r\\n\\r\\n # Combobox\\r\\n typeToChoose = StringVar()\\r\\n # value in combobox is formatType\\r\\n numberChosen = ttk.Combobox(self, width=12, textvariable=typeToChoose, values=self.formatTypes)\\r\\n numberChosen.grid(column=1, row=4)\\r\\n numberChosen.current(0)\\r\\n\\r\\n # Frame show info related to the resizing process\\r\\n self.resultFrame = ttk.LabelFrame(self, text='Result', height=100)\\r\\n self.resultFrame.grid(column=0, row=6, columnspan=4, sticky='nesw')\\r\\n self.resultLabel = ttk.Label(self.resultFrame, text='')\\r\\n self.resultLabel.grid(column=0, row=0)\\r\\n\\r\\n # Labels that remain constant throughout execution.\\r\\n ttk.Label(self, text='Video Resizer').grid(column=0, row=0, columnspan=4)\\r\\n ttk.Label(self, text='Select videos').grid(column=0, row=2, sticky='w')\\r\\n ttk.Label(self, text='Saving folder').grid(column=2, row=2, sticky='w')\\r\\n ttk.Separator(self, orient='horizontal').grid(column=0, row=1, columnspan=4, sticky='ew')\\r\\n\\r\\n # configure for the window grid\\r\\n for child in self.winfo_children():\\r\\n child.grid_configure(padx=5, pady=5)\",\n \"def changeFormation(self, *args):\\n\\n # get the number of balls\\n # formation = self.numberOfBallsSelector.get(first=None, last=None)\\n newNBalls = int(self.numberOfBallsSelector.get())\\n\\n if newNBalls >= self.nBalls:\\n for i in range(self.nBalls, newNBalls):\\n # for some reason self.initballstate gets edited if ballstates gets edited\\n self.ballStates[i] = [1.5, 0.75, 0, 0]\\n\\n # TODO: change this later after we figure out proper initial ball locations\\n self.ballStates[i][2] += random.uniform(-3, 3)\\n self.ballStates[i][3] += random.uniform(-3, 3)\\n\\n self.nBalls = newNBalls\\n self.balls = tuple(map(str, range(self.nBalls)))\\n # self.saveParameters()\\n # recreate combobox with updated number of balls\\n self.ballSelector = Pmw.ComboBox(self, label_text='Choose Ball',\\n labelpos='nw', selectioncommand=self.changeBall,\\n scrolledlist_items=self.balls, dropdown=1)\\n self.ballSelector.grid(column=0, row=3)\\n self.ballSelector.selectitem(self.currentBall)\",\n \"def selection_changed(self):\\n self.emit('selection_changed')\",\n \"def param_changes_button_clicked():\\n for label in param_change_labels:\\n if label.visible:\\n param_changes_button.label = 'Show Parameter Changes'\\n label.visible = False\\n label.text_alpha = 0 # label.visible does not work, so we use this instead\\n else:\\n param_changes_button.label = 'Hide Parameter Changes'\\n label.visible = True\\n label.text_alpha = 1\",\n \"def sgnRenderAllFrames(self):\\n\\n self.uiSaveSelectedRenders()\\n\\n self.core.render(self.lstSelectedRenders, bEverything = True)\",\n \"def refreshActiveFrames(self, event=None):\\n self.unloadAllFrames()\\n self.checkFramesHaveData()\\n\\n try:\\n self.contentFrame.currFrame.built = False\\n except AttributeError:\\n pass\\n\\n try:\\n if self.contentFrame.currFrame.hasRequiredData():\\n self.contentFrame.currFrame.enter()\\n else:\\n self.frameBtnCmds[0](self)\\n except AttributeError:\\n self.frameBtnCmds[0](self)\",\n \"def _on_frame_changed(self, change):\\n self._set_coordinates(self.frame)\",\n \"def __reload_caption(self, new_list):\\n # Remove all UI elements\\n for item in self.__ui_controls:\\n if self.__ui_controls.get(item) is None:\\n continue\\n self.__ui_controls.get(item).delete()\\n for item in self.__teachpanel_sliders:\\n item.delete()\\n self.__teachpanel_sliders = []\\n # Restore the caption\\n self.scene.caption = self.__default_caption\\n # Create the updated caption.\\n self.__load_mode_ui(new_list)\",\n \"def on_module_choice(self, event):\\n\\n self.log.trace(\\\"Handle module selection by user.\\\")\\n result = {'successful': False}\\n\\n try:\\n # determine module selected\\n module_name = event.GetString()\\n\\n self.feature_choices = []\\n for selection in DEFAULT_SEL:\\n self.feature_choices.append(selection)\\n if module_name.lower() == CUSTOM_SEL.lower():\\n # set custom flag\\n self.custom_module = True\\n # show custom input\\n self.input_custom_module.Show()\\n else:\\n # clear custom flag\\n self.custom_module = False\\n # make sure custom field is hidden\\n self.input_custom_module.Hide()\\n if module_name.lower() != BLANK_SEL.lower():\\n # return all features for module\\n self.log.trace(\\\"Rebuilding feature list for %s module ...\\\" % module_name)\\n features = self.database.return_features_for_module(module_name)['features']\\n\\n # build feature list\\n for feature in features:\\n self.feature_choices.append(feature['name'])\\n\\n # set feature choices to selection\\n self.input_feature.SetItems(self.feature_choices)\\n self._update_feature_input_according_to_custom_module_flag()\\n self.log.trace(\\\"Feature list for %s module rebuilt.\\\" % module_name)\\n\\n # reset user story selections\\n self.log.trace(\\\"Reseting user story list ...\\\")\\n self.story_choices = []\\n for selection in DEFAULT_SEL:\\n self.story_choices.append(selection)\\n self.input_story.SetItems(self.story_choices)\\n self._update_story_input_according_to_custom_feature_flag()\\n self.log.trace(\\\"User story list reset.\\\")\\n\\n # reset test selections\\n self.log.trace(\\\"Reseting test list ...\\\")\\n self.test_choices = []\\n for selection in DEFAULT_SEL:\\n self.test_choices.append(selection)\\n self.input_test.SetItems(self.test_choices)\\n self._update_test_input_according_to_custom_story_flag()\\n self.log.trace(\\\"Test list reset.\\\")\\n\\n # reset testcase selections\\n self.log.trace(\\\"Reseting test case list ...\\\")\\n self.testcase_choices = []\\n for selection in DEFAULT_SEL:\\n self.testcase_choices.append(selection)\\n self.input_testcase.SetItems(self.testcase_choices)\\n self._update_testcase_input_according_to_custom_test_flag()\\n self.log.trace(\\\"Test case list reset.\\\")\\n\\n result['successful'] = True\\n except BaseException, e:\\n self.handle_exception(e, \\\"handle module selection by user\\\")\\n\\n # return\\n return result\",\n \"def done(self):\\n\\n # Check if the status of frames has changed.\\n indices_included = []\\n indices_excluded = []\\n for index in range(self.frames.number_original):\\n if self.index_included[index] and not self.frames.index_included[index]:\\n indices_included.append(index)\\n self.frames.index_included[index] = True\\n elif not self.index_included[index] and self.frames.index_included[index]:\\n indices_excluded.append(index)\\n self.frames.index_included[index] = False\\n\\n # Write the changes in frame selection to the protocol.\\n if self.configuration.global_parameters_protocol_level > 1:\\n if indices_included:\\n Miscellaneous.protocol(\\n \\\" The user has included the following frames into the stacking \\\"\\n \\\"workflow: \\\" + str(\\n [item + 1 for item in indices_included]), self.stacked_image_log_file,\\n precede_with_timestamp=False)\\n if indices_excluded:\\n Miscellaneous.protocol(\\n \\\" The user has excluded the following frames from the stacking \\\"\\n \\\"workflow: \\\" + str(\\n [item + 1 for item in indices_excluded]), self.stacked_image_log_file,\\n precede_with_timestamp=False)\\n frames_remaining = sum(self.frames.index_included)\\n if frames_remaining != self.frames.number:\\n Miscellaneous.protocol(\\\" \\\" + str(\\n frames_remaining) + \\\" frames will be used in the stacking workflow.\\\",\\n self.stacked_image_log_file, precede_with_timestamp=False)\\n\\n # Send a completion message. The \\\"execute_rank_frames\\\" method is triggered on the workflow\\n # thread. The signal payload is True if the status was changed for at least one frame.\\n # In this case, the index translation table is updated before the frame ranking starts.\\n if self.parent_gui is not None:\\n self.signal_finished.emit()\\n\\n # Close the Window.\\n self.player_thread.quit()\\n self.close()\",\n \"def onLoadSegmentationButton(self):\\n inputVolume = self.inputSelector.currentNode()\\n segmentationFile = self.segmentationsPath + self.segmentationFilesComboBox.currentText\\n \\n loadedSegmentationVolumeNode = slicer.util.loadVolume(segmentationFile)\\n voxels = slicer.util.arrayFromVolume(loadedSegmentationVolumeNode)\\n imgLabel = np.copy(voxels)\\n \\n tmpVoxels = np.copy(voxels)\\n tmpVoxels[:] = imgLabel[:]\\n \\n slicer.util.updateVolumeFromArray(loadedSegmentationVolumeNode, tmpVoxels)\\n \\n removeLastSegmentation = self.removeLastSegmentationCheckBox.isChecked() \\n showBackGround = self.showBackGroundCheckBox.isChecked()\\n displaySegmentationMap(loadedSegmentationVolumeNode, imgLabel, self.labelColorsList, removeLastSegmentation, showBackGround)\\n \\n slicer.util.setSliceViewerLayers(background=inputVolume)\",\n \"def _after_plot_list_load(self):\\r\\n self.button_send_list.enable()\\r\\n self.label_list_status.set_text('Shown list does not match device list.')\",\n \"def state_changed(self):\\n if self.goto and self.get_position() != self.c.p:\\n self.goto_node()\\n\\n if self.mode == 'edit':\\n self.edit_frame.show()\\n self.view_frame.hide()\\n elif self.mode == 'view':\\n self.edit_frame.hide()\\n self.view_frame.show()\\n else:\\n self.edit_frame.show()\\n self.view_frame.show()\\n\\n self.update_position(self.c.p)\",\n \"def updateWidget(self):\\n\\n if self.frame1.state() == 'normal':\\n self.frame2.deiconify()\\n self.frame1.withdraw()\\n else:\\n self.frame2.withdraw()\\n self.frame2.update()\\n self.frame2.deiconify()\\n self.frame1.title(\\\"%s's turn\\\" % self.usernames[1])\\n self.frame2.title(\\\"%s's turn\\\" % self.usernames[0])\\n showDialogBox(\\\"%s's turn first!\\\" % self.usernames[0])\\n self.frame1.update()\\n self.frame2.update()\",\n \"def update_choice(self, value):\\n if self.p is not None:\\n if value == \\\"none\\\":\\n self.other_text.delete('1.0', tk.END)\\n self.other_text.insert('1.0', \\\"\\\")\\n if value == \\\"categories\\\":\\n self.other_text.delete('1.0', tk.END)\\n self.other_text.insert('1.0', self.p.categories)\\n if value == \\\"pageid\\\":\\n self.other_text.delete('1.0', tk.END)\\n self.other_text.insert('1.0', self.p.pageid)\\n if value == \\\"sections\\\":\\n self.other_text.delete('1.0', tk.END)\\n self.other_text.insert('1.0', self.p.sections)\\n if value == \\\"html\\\":\\n self.other_text.delete('1.0', tk.END)\\n self.other_text.insert('1.0', self.p.html())\",\n \"def createFrame(self):\\n \\n tkinterListBoxDialog.createFrame(self)\\n self.addFrameButtons()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67221683","0.647668","0.6142463","0.60368323","0.6010365","0.59839","0.594206","0.5939723","0.5774318","0.57701164","0.5685508","0.56649303","0.5623016","0.5616354","0.5597576","0.55696803","0.5566506","0.5529806","0.5504718","0.54967684","0.5455349","0.54481906","0.5441665","0.5428047","0.5419617","0.54100496","0.540215","0.5366627","0.536203","0.5361787","0.5348161","0.53435355","0.53303784","0.53246135","0.5324376","0.53196377","0.5314886","0.5305258","0.530002","0.52972347","0.5295162","0.52942675","0.5280796","0.5267688","0.52606905","0.5257092","0.5248317","0.52461755","0.5245246","0.5240856","0.52272224","0.5224156","0.5223133","0.5222158","0.52212054","0.5213293","0.5208864","0.52047306","0.51944417","0.5194131","0.5193659","0.51930094","0.5189313","0.5184994","0.5184713","0.51803064","0.5173485","0.51641864","0.51587766","0.5148659","0.5147764","0.5145625","0.51411456","0.5138306","0.5135131","0.5125266","0.51246446","0.51221555","0.5121974","0.51218617","0.51202285","0.51081544","0.5099349","0.509932","0.5098061","0.5097882","0.50906783","0.5089606","0.5075097","0.50726223","0.5072271","0.50688934","0.5063931","0.5063705","0.50587386","0.50536466","0.5049001","0.50467366","0.50434697","0.5039356"],"string":"[\n \"0.67221683\",\n \"0.647668\",\n \"0.6142463\",\n \"0.60368323\",\n \"0.6010365\",\n \"0.59839\",\n \"0.594206\",\n \"0.5939723\",\n \"0.5774318\",\n \"0.57701164\",\n \"0.5685508\",\n \"0.56649303\",\n \"0.5623016\",\n \"0.5616354\",\n \"0.5597576\",\n \"0.55696803\",\n \"0.5566506\",\n \"0.5529806\",\n \"0.5504718\",\n \"0.54967684\",\n \"0.5455349\",\n \"0.54481906\",\n \"0.5441665\",\n \"0.5428047\",\n \"0.5419617\",\n \"0.54100496\",\n \"0.540215\",\n \"0.5366627\",\n \"0.536203\",\n \"0.5361787\",\n \"0.5348161\",\n \"0.53435355\",\n \"0.53303784\",\n \"0.53246135\",\n \"0.5324376\",\n \"0.53196377\",\n \"0.5314886\",\n \"0.5305258\",\n \"0.530002\",\n \"0.52972347\",\n \"0.5295162\",\n \"0.52942675\",\n \"0.5280796\",\n \"0.5267688\",\n \"0.52606905\",\n \"0.5257092\",\n \"0.5248317\",\n \"0.52461755\",\n \"0.5245246\",\n \"0.5240856\",\n \"0.52272224\",\n \"0.5224156\",\n \"0.5223133\",\n \"0.5222158\",\n \"0.52212054\",\n \"0.5213293\",\n \"0.5208864\",\n \"0.52047306\",\n \"0.51944417\",\n \"0.5194131\",\n \"0.5193659\",\n \"0.51930094\",\n \"0.5189313\",\n \"0.5184994\",\n \"0.5184713\",\n \"0.51803064\",\n \"0.5173485\",\n \"0.51641864\",\n \"0.51587766\",\n \"0.5148659\",\n \"0.5147764\",\n \"0.5145625\",\n \"0.51411456\",\n \"0.5138306\",\n \"0.5135131\",\n \"0.5125266\",\n \"0.51246446\",\n \"0.51221555\",\n \"0.5121974\",\n \"0.51218617\",\n \"0.51202285\",\n \"0.51081544\",\n \"0.5099349\",\n \"0.509932\",\n \"0.5098061\",\n \"0.5097882\",\n \"0.50906783\",\n \"0.5089606\",\n \"0.5075097\",\n \"0.50726223\",\n \"0.5072271\",\n \"0.50688934\",\n \"0.5063931\",\n \"0.5063705\",\n \"0.50587386\",\n \"0.50536466\",\n \"0.5049001\",\n \"0.50467366\",\n \"0.50434697\",\n \"0.5039356\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.777694"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":18683,"cells":{"query":{"kind":"string","value":"Creates an interactive echelle environment with a variable deltanu slider. If you're working in a Jupyter notebook/lab environment, you must call `%matplotlib notebook` before running this."},"document":{"kind":"string","value":"def interact_echelle(\n freq,\n power,\n dnu_min,\n dnu_max,\n step=None,\n cmap=\"BuPu\",\n ax=None,\n smooth=False,\n smooth_filter_width=50.0,\n scale=None,\n return_coords=False,\n backend=\"bokeh\",\n notebook_url=\"localhost:8888\",\n plot_method=\"fast\",\n sampling=2,\n **kwargs\n):\n\n if dnu_max < dnu_min:\n raise ValueError(\"Maximum range can not be less than minimum\")\n\n if smooth_filter_width < 1:\n raise ValueError(\"The smooth filter width can not be less than 1!\")\n\n if smooth:\n power = smooth_power(power, smooth_filter_width)\n\n x, y, z = echelle(\n freq, power, (dnu_max + dnu_min) / 2.0, sampling=sampling, **kwargs\n )\n\n if scale is \"sqrt\":\n z = np.sqrt(z)\n elif scale is \"log\":\n z = np.log10(z)\n\n if step is None:\n step = 5 * np.median(np.diff(freq))\n if backend == \"matplotlib\":\n # Create the matplotlib version of the interactive\n # form. This should only really be done\n # if the user is working from the terminal.\n if ax is None:\n fig, ax = plt.subplots(figsize=[6.4, 9])\n else:\n fig = plt.gcf()\n\n if plot_method is \"fast\":\n line = ax.pcolorfast((x.min(), x.max()), (y.min(), y.max()), z, cmap=cmap)\n else:\n line = ax.imshow(\n z,\n aspect=\"auto\",\n extent=(x.min(), x.max(), y.min(), y.max()),\n origin=\"lower\",\n cmap=cmap,\n )\n\n axfreq = plt.axes([0.1, 0.025, 0.8, 0.02])\n valfmt = \"%1.\" + str(len(str(step).split(\".\")[-1])) + \"f\"\n slider = Slider(\n axfreq,\n \"\\u0394\\u03BD\",\n dnu_min,\n dnu_max,\n valinit=(dnu_max + dnu_min) / 2.0,\n valstep=step,\n valfmt=valfmt,\n )\n\n def update(dnu):\n x, y, z = echelle(freq, power, dnu, sampling=1, **kwargs)\n if scale is not None:\n if scale is \"sqrt\":\n z = np.sqrt(z)\n elif scale is \"log\":\n z = np.log10(z)\n line.set_array(z)\n line.set_extent((x.min(), x.max(), y.min(), y.max()))\n ax.set_xlim(0, dnu)\n fig.canvas.blit(ax.bbox)\n\n def on_key_press(event):\n if event.key == \"left\":\n new_dnu = slider.val - slider.valstep\n elif event.key == \"right\":\n new_dnu = slider.val + slider.valstep\n else:\n new_dnu = slider.val\n\n slider.set_val(new_dnu)\n update(new_dnu)\n\n def on_click(event):\n ix, iy = event.xdata, event.ydata\n coords.append((ix, iy))\n\n fig.canvas.mpl_connect(\"key_press_event\", on_key_press)\n slider.on_changed(update)\n\n ax.set_xlabel(\"Frequency mod \\u0394\\u03BD\")\n ax.set_ylabel(\"Frequency\")\n plt.subplots_adjust(\n left=0.1,\n right=0.95,\n bottom=0.1,\n top=0.95,\n )\n plt.show()\n\n if return_coords:\n coords = []\n fig.canvas.mpl_connect(\"button_press_event\", on_click)\n return coords\n\n elif backend == \"bokeh\":\n # Otherwise we use Bokeh.\n try:\n import bokeh\n except:\n raise ImportError(\"You need to install the Bokeh package.\")\n\n from bokeh.io import show, output_notebook, push_notebook\n from bokeh.plotting import figure, ColumnDataSource\n from bokeh.layouts import column\n from bokeh.models import CustomJS, ColumnDataSource, FreehandDrawTool\n from bokeh.models import Slider as b_Slider\n\n import warnings\n from bokeh.util.warnings import BokehUserWarning\n\n # This is a terrible hack and I hate Bokeh\n warnings.simplefilter(\"ignore\", BokehUserWarning)\n\n def create_interact_ui(doc):\n source = ColumnDataSource(\n data={\n \"image\": [z],\n \"x\": x,\n \"y\": y,\n \"dw\": [x.max() - x.min()],\n \"dh\": [y.max() - y.min()],\n }\n )\n\n plot = figure(\n x_range=(x.min(), x.max()),\n y_range=(y.min(), y.max()),\n plot_width=550,\n plot_height=600,\n )\n\n palette = get_bokeh_palette(cmap)\n\n full_plot = plot.image(\n image=\"image\",\n x=\"x\",\n y=\"y\",\n dw=\"dw\",\n dh=y.max() - y.min(),\n source=source,\n palette=palette,\n )\n\n plot.xaxis.axis_label = \"Frequency mod \\u0394\\u03BD\"\n plot.yaxis.axis_label = \"Frequency\"\n\n slider = b_Slider(\n start=dnu_min,\n end=dnu_max,\n value=(dnu_min + dnu_max) / 2,\n step=step,\n title=\"\\u0394\\u03BD\",\n format=\"0.000\",\n )\n\n # Slider callback\n def update_upon_dnu_change(attr, old, new):\n x, y, z = echelle(\n freq,\n power,\n new,\n sampling=sampling,\n )\n if scale is not None:\n if scale is \"sqrt\":\n z = np.sqrt(z)\n elif scale is \"log\":\n z = np.log10(z)\n full_plot.data_source.data[\"image\"] = [z]\n full_plot.data_source.data[\"dw\"] = [x.max() - x.min()]\n plot.x_range.start = x.min()\n plot.x_range.end = x.max()\n\n slider.on_change(\"value\", update_upon_dnu_change)\n\n # Adjust some toolbar options\n r = plot.multi_line(line_width=15, alpha=0.2, color=\"red\")\n plot.add_tools(FreehandDrawTool(renderers=[r]))\n plot.toolbar.logo = None\n plot.toolbar.active_drag = None\n\n # Layout all of the plots\n widgets_and_figures = column(slider, plot)\n doc.add_root(widgets_and_figures)\n\n output_notebook(verbose=False, hide_banner=True)\n return show(create_interact_ui, notebook_url=notebook_url)\n\n else:\n raise ValueError(\"'backend' must be either 'matplotlib' or 'bokeh\")"},"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 editor_example():\n agent_sensors = [sensors.RGBCamera, sensors.LocationSensor, sensors.VelocitySensor]\n agent = AgentDefinition(\"uav0\", agents.UavAgent, agent_sensors)\n env = HolodeckEnvironment([agent], start_world=False)\n env.agents[\"uav0\"].set_control_scheme(1)\n command = [0, 0, 10, 50]\n\n for i in range(10):\n env.reset()\n for _ in range(1000):\n state, reward, terminal, _ = env.step(command)","def loop_menuDolar():\r\n window = menuDolar.Ventana()\r\n\r\n while True:\r\n event, value = window.read()\r\n\r\n if event in ('Volver', '-exit-'):\r\n break\r\n \r\n if event == '-actual-':\r\n window.hide()\r\n gd.actual()\r\n window.un_hide()\r\n\r\n if event == '-inc-':\r\n window.hide()\r\n gd.incremento()\r\n window.un_hide()\r\n \r\n if event == '-menor-':\r\n window.hide()\r\n gd.menor()\r\n window.un_hide()\r\n \r\n return window","def rundemo(no,fig=False):\n import qutipf90mc.examples as examples\n print 'running demo #',str(no),'from qutip'\n raw_input('press a key to continue')\n funcstr = 'examples.ex_'+str(no)+'.run()'\n ex_code = compile(funcstr,'<string>','exec')\n if (fig): plt.figure()\n eval(ex_code)","def liquidity1_interact():\r\n date = wd.DatePicker(value = yesterday, description = \"选择日期\")\r\n threshold = wd.FloatSlider(value = 20, min = 0, max = 200, step = 1,\r\n description = \"单日可变现能力监测数值(%)\", tooltip = \"单击数值可进行编辑\", style = style)\r\n showAll = wd.Checkbox(value = False, description = '查看所有组合')\r\n verbose = wd.Checkbox(value = False, description = \"查看单日可变现能力的具体信息\")\r\n liqui_layout = wd.interact_manual(port_liquidity1_pre, date = date, threshold = threshold, verbose = verbose, showAll = showAll)\r\n liqui_layout.widget.children[4].description = \"开始查询\"\r\n liqui_layout.widget.children[4].button_style = \"danger\"\r\n display(liqui_layout)\r\n return None","def demo(name):\n x, y = demo_data[name]\n\n# _models = [models.Const1D(0), models.Gaussian1D(3, 1, .3), models.Gaussian1D(3, 2, .3)]\n# _models = [models.Const1D(0)]\n _models = None\n\n mv = ModelBrowser(x, y, y * 0, _models)\n\n mv.show()\n\n from glue.qt import get_qapp\n get_qapp().exec_()","def shell(state):\n IPython.embed(colors=\"Neutral\", banner1=BANNER, user_ns={\"sdk\": state.sdk})","def createViewerInput():\n if 'VIEWER_INPUT' not in [node.name() for node in nuke.allNodes()]:\n for node in nuke.allNodes():\n node['selected'].setValue(False)\n nuke.createNode(\"dmpViewerInput\")\n node = nuke.toNode('VIEWER_INPUT')\n node.showControlPanel()\n node['selected'].setValue(False)\n else:\n nuke.toNode('VIEWER_INPUT').showControlPanel()\n #nuke.delete(nuke.toNode('VIEWER_INPUT'))","def interact(self):\n param_min = self.param_vals[0]\n param_max = self.param_vals[-1]\n param_step = self.param_vals[1] - self.param_vals[0]\n\n qbt_indices = [index for (index, subsystem) in self.sweep.hilbertspace.qbt_subsys_list]\n osc_indices = [index for (index, subsystem) in self.sweep.hilbertspace.osc_subsys_list]\n\n param_slider = ipywidgets.FloatSlider(min=param_min, max=param_max, step=param_step,\n description=self.param_name, continuous_update=False)\n photon_slider = ipywidgets.IntSlider(value=1, min=1, max=4, description='photon number')\n initial_slider = ipywidgets.IntSlider(value=0, min=0, max=self.evals_count, description='initial state index')\n final_slider = ipywidgets.IntSlider(value=1, min=1, max=self.evals_count, description='final state index')\n\n qbt_dropdown = ipywidgets.Dropdown(options=qbt_indices, description='qubit subsys')\n osc_dropdown = ipywidgets.Dropdown(options=osc_indices, description='oscillator subsys')\n\n def update_min_final_index(*args):\n final_slider.min = initial_slider.value + 1\n\n initial_slider.observe(update_min_final_index, 'value')\n\n out = ipywidgets.interactive_output(self.plot_explorer_panels,\n {'param_val': param_slider,\n 'photonnumber': photon_slider,\n 'initial_index': initial_slider,\n 'final_index': final_slider,\n 'qbt_index': qbt_dropdown,\n 'osc_index': osc_dropdown\n })\n\n left_box = ipywidgets.VBox([param_slider])\n mid_box = ipywidgets.VBox([initial_slider, final_slider, photon_slider])\n right_box = ipywidgets.VBox([qbt_dropdown, osc_dropdown])\n\n user_interface = ipywidgets.HBox([left_box, mid_box, right_box])\n display(user_interface, out)","def eda():\n dataset = mgr.current_dataset()\n if dataset is None:\n return redirect(url_for('main.datasets'))\n loaded_names = mgr.list_loaded()\n mgr.dump_data(dataset) # Pickle data and write to Docker volume\n # Generate session ID and obtain JavaScript from Bokeh server\n session_id = generate_session_id()\n script = server_session(url='http://bokeh:5006/eda/',\n session_id=session_id)\n # Replace Docker alias in URL with localhost\n script = script.replace(\"http://bokeh:5006\", \"http://localhost:5006\")\n # Use the script in the rendered page\n return render_template(\"dataset_preview.html\", script=script,\n data_names=loaded_names)","def main():\r\n # create the EdenLudo sample\r\n EdenEvolves = EdenLudo()\r\n # ru-n the scene\r\n run()","def vp_start_gui():\n global val, w, root\n root = tk.Tk()\n plot_support.set_Tk_var()\n top = Toplevel1(root)\n plot_support.init(root, top)\n root.mainloop()","def vis_difference(self):\n print(self.init_vec)\n\n init = self.init_output.numpy()\n\n alphas = np.linspace(0, 1, 20)\n for i, alpha in enumerate(alphas):\n\n display.clear_output(wait=True)\n norm = [torch.linalg.norm(torch.tensor(\n self.init_vec + alpha*self.eigen[i]), axis=1).detach().numpy() for i in range(2)]\n\n diff = np.array([self.compute_difference(\n alpha, self.eigen[i]) for i in range(2)])\n\n fig = plt.figure(figsize=(14, 12), tight_layout=True)\n fig.suptitle(\"Latent direction variation\", fontsize=20)\n gs = gridspec.GridSpec(2, 2)\n\n ax_temp = plt.subplot(gs[0, :])\n ax_temp.scatter(\n init[:, 0], init[:, 1])\n ax_temp.set_title(\"Initial Dataset\")\n ax_temp.set_xlim(-1, 1)\n ax_temp.set_ylim(-1, 1)\n [s.set_visible(False) for s in ax_temp.spines.values()]\n\n for j in range(2):\n ax_temp = plt.subplot(gs[1, j])\n sc = ax_temp.quiver(\n init[:, 0], init[:, 1], diff[j, :, 0], diff[j, :, 1], norm[j])\n sc.set_clim(np.min(norm[j]), np.max(norm[j]))\n plt.colorbar(sc)\n ax_temp.set_title(\n \"Direction: {}, alpha: {}\".format(j+1, alpha))\n ax_temp.set_xlim(-1, 1)\n ax_temp.set_ylim(-1, 1)\n [s.set_visible(False) for s in ax_temp.spines.values()]\n\n plt.savefig(\"frames_dir/fig_{}\".format(i))\n plt.show()","def main(arg):\n global new, left, right, app, backgroundcolor, dragon\n global size, x, y, win, timer, linecolor, number\n number, linecolor, backgroundcolor = arg_decode(arg)\n new = generate_dragon(number) # Generate dragon plot values\n\n app = QtGui.QApplication([]) # create plot application\n size = (len(new)+1) # get size of new\n x = np.zeros(size) # create array of zeros based on size of new\n y = np.zeros(size)\n\n # set plot application settings\n win = pg.GraphicsLayoutWidget(show=True, title=\"Dragon\")\n win.setBackground(backgroundcolor)\n win.resize(1024, 768)\n\n plot = win.addPlot(title=\"Dragon plot\") # add plot\n\n static_posx = [-1, 0, 0] # predefined cords for lines\n static_posy = [0, 0, -1] #\n dragon = plot.plot(static_posx, static_posy, pen=linecolor)\n dragon = plot.plot(x, y, pen=linecolor) # plot empty arrays\n timer = QtCore.QTimer() # Init timer\n timer.timeout.connect(update) # join timer update to funtion\n timer.start(1) # set timer update time","def create_widgets(self):\n # self.var_spherical = IntVar()\n # self.var_3d = IntVar()\n # self.var_spatial_audio = IntVar()\n # self.button_open[\"command\"] = self.action_open\n # self.button_inject[\"command\"] = self.action_inject\n pass","def demonstrate(self):\n self.env.render()\n self.action = 0\n\n # Control actions with keys\n @self.env.viewer.window.event\n def on_key_press(symbol, modifiers):\n self.action = Task.act(symbol)\n\n # Default to no action\n @self.env.viewer.window.event\n def on_key_release(symbol, modifiers):\n self.action = 0\n\n # Perform actions on a timer\n def tick(dt):\n if not self.ended():\n self.perform(self.action, render=True, delay=SLOW)\n self.update()\n pyglet.clock.schedule_once(tick, 0)\n\n tick(0)\n pyglet.app.run()","def interactive():\n IPython.start_ipython(argv=[])","def switch_arrangment(self, new_arrangment):\n #Clear Figures to avoid memory leak\n for figure in self.figures:\n figure.clear()\n plt.close(figure)\n \n #Close the exisiting display\n self.destroy()\n \n #Generate user interface\n UI = SD_UI(tuning = self.tuning_flag,\n location = self.location,\n language = self.language,\n arrangment = new_arrangment)\n \n #Run the new user interface\n UI.mainloop()","def create_figure(self) -> None:\n plt.ion()\n self.fig = plt.figure(1)\n self.axis = self.fig.add_subplot(111, xlim=(0, 1), ylim=(0, 1))\n self.axis.grid(True)\n plt.xticks(np.linspace(0, 1, self._param[\"n_v\"] + 1))\n plt.yticks(np.linspace(0, 1, self._param[\"n_v\"] + 1))\n a_plt, = self.axis.plot([], [], 'bx', markersize=5)\n l_plt, = self.axis.plot([], [], 'r.', markersize=15)\n self.plots = [a_plt, l_plt]","def guiFurnishGlobals(par):\n\n # plot settings\n from matplotlib import rcParams\n rcParams['axes.labelsize'] = 14 \n rcParams['xtick.labelsize'] = 12\n rcParams['ytick.labelsize'] = 12 \n rcParams['legend.fontsize'] = 12\n rcParams['lines.linewidth'] = 2\n\n # experimental data\n t, Gexp, wG = GetExpData(par['GexpFile'])\n n = len(t)\n ns = par['ns'] # discretization of 'tau'\n\n tmin = t[0];\n tmax = t[n-1];\n\n # determine frequency window\n if par['FreqEnd'] == 1:\n smin = np.exp(-np.pi/2) * tmin; smax = np.exp(np.pi/2) * tmax\t\t\n elif par['FreqEnd'] == 2:\n smin = tmin; smax = tmax\n elif par['FreqEnd'] == 3:\n smin = np.exp(+np.pi/2) * tmin; smax = np.exp(-np.pi/2) * tmax\t\t\n\n hs = (smax/smin)**(1./(ns-1))\n s = smin * hs**np.arange(ns)\n kernMat = getKernMat(s,t)\n\n # toggle flags to prevent printing\n\n par['verbose'] = False\n par['plotting'] = False\n\n # load lamda, rho, eta\n lam, rho, eta = np.loadtxt('output/rho-eta.dat', unpack=True)\n\n\n plt.clf()\n\n return s, t, kernMat, Gexp, par, lam, rho, eta","def main():\n # Load properties that will be needed\n store = [Storage.Storage(2), Storage.Storage(4)] \n pre_energy = [s.get(\"free_energy\") for s in store]\n post_energy = [s.get(\"post_energy\") for s in store]\n x_range = store[0].get(\"x_range\")\n xlocs = np.arange(x_range[0], x_range[1], x_range[2])\n y_range = store[0].get(\"y_range\")\n ylocs = np.arange(y_range[0], y_range[1], y_range[2])\n # Calculate step size\n xb2steps = stepsize(pre_energy[0], post_energy[0], xlocs) \n xb4steps = stepsize(pre_energy[1], post_energy[1], xlocs) \n # Set up the figure\n fig = plt.figure(1, figsize=(7.5,2.5)) \n axe = (fig.add_subplot(1, 2, 1), fig.add_subplot(1, 2, 2))\n # Plot the results\n axe[0].plot(ylocs, xb4steps, color='#FF466F', lw=4)\n axe[1].plot(ylocs, xb2steps, color='#76D753', lw=4)\n # Annotate the plots\n axe[0].set_title(\"4sXB step size\")\n axe[0].set_xlabel(\"Lattice spacing (nm)\") \n axe[0].set_ylabel(\"Step size (nm)\")\n axe[0].set_xlim((25.5, 39))\n axe[0].set_ylim((1, 8))\n axe[1].set_title(\"2sXB step size\")\n axe[1].set_xlabel(\"Lattice spacing (nm)\") \n axe[1].set_ylabel(\"Step size (nm)\")\n axe[1].set_xlim((25.5, 39))\n axe[1].set_ylim((1, 8))\n # Display the plots\n fig.subplots_adjust(wspace=0.25, hspace=0.48,\n left=0.08, right=0.98,\n top=0.85, bottom=0.21)\n plt.show()","def EnvironmentTab():\n\n mainTab = cmds.columnLayout(adjustableColumn=True, columnAttach=('both', 20))\n \n ### Physical Light\n cmds.separator(height=10, style=\"none\")\n cmds.text(label=\"Physical Light:\", align=\"left\")\n # Slider to select the elevation\n elevationSlider = cmds.floatSliderGrp(label=\"Elevation\", field=True, value=45, min=0, max=90, \n dragCommand=lambda value:EC.elevationChange(value),\n changeCommand=lambda value:EC.elevationChange(value))\n # Slider to select the azimuth (simulat to the height, kinda)\n azimuthSlider = cmds.floatSliderGrp(label=\"Azimuth\", field=True, value=90, min=0, max=360, \n dragCommand=lambda value:EC.azimuthChange(value),\n changeCommand=lambda value:EC.azimuthChange(value))\n # Slider for the light's intensity\n intensitySlider = cmds.floatSliderGrp(label=\"Intensity\", field=True, value=1, min=.1, max=10, \n dragCommand=lambda value:EC.intensityChange(value),\n changeCommand=lambda value:EC.intensityChange(value))\n\n cmds.separator(height=5, style=\"none\")\n cmds.button(label='Create Sky Dome', command=lambda x: EC.createSkyLight(elevationSlider, azimuthSlider, intensitySlider))\n\n ### Environment fog\n cmds.separator(height=20)\n cmds.text(label=\"Environment Fog:\", align=\"left\")\n # Slider for the color\n colorSlider = cmds.colorSliderGrp(label=\"Color\", rgb=(1,1,1), \n dragCommand=lambda value:EC.colorChange(colorSlider),\n changeCommand=lambda value:EC.colorChange(colorSlider))\n # Slider for fog's distance\n distanceSlider = cmds.floatSliderGrp(label=\"Distance\", field=True, value=.02, min=0, max=1000, step=.01, \n dragCommand=lambda value:EC.distanceChange(value), \n changeCommand=lambda value:EC.distanceChange(value))\n # Slider for fog's height\n heightSlider = cmds.floatSliderGrp(label=\"Height\", field=True, value=5, min=0, max=1000, step=.1, \n dragCommand=lambda value:EC.heightChange(value),\n changeCommand=lambda value:EC.heightChange(value))\n\n cmds.separator(height=5, style=\"none\")\n cmds.button(label='Create Environment Fog', command=lambda x: EC.createAiFog(colorSlider, distanceSlider, heightSlider))\n\n cmds.setParent('..')\n\n return mainTab","def update(self):\n self.plot.draw()\n \n func=str(self.edit1b.currentText())\n if self.win.test()==0:\n x=np.linspace(0,10,200)\n elif self.win.test()==1:\n x=np.linspace(0,0.40,200)\n \n pattern1=r'Steel'\n pattern2=r'Aluminium'\n pattern3=r'[\\d]+'\n \n if (func!='Comparison Chart'):\n self.edit2b.setDisabled(False)\n self.edit3b.setDisabled(False)\n self.edit4b.setDisabled(False)\n if (func=='Quenched/Tempered Steel'):\n alpha = 0.0025\n elif (func=='Annealed Steel'):\n alpha = 0.01\n elif (func=='Steel (input Su)'):\n S = str(self.edit2b.text())\n if (self.win.test()==0):\n S = str(float(S)/6.895)\n alpha = notch.alpha(eval(S))\n elif (func=='Aluminium Alloy 356.0 as cast'):\n rho = 0.08\n elif (func=='Aluminium Alloy 6061'):\n rho = 0.025\n elif (func=='Aluminium Alloy 7075'):\n rho = 0.015\n elif (func=='Material dropdown'):\n pass\n \n y1=[]\n if re.search(pattern1,func):\n Su=notch.su_s(alpha)\n if (self.win.test()==0):\n Su = Su*6.895\n for i in range(len(x)):\n y1.append(notch.nsp(alpha,x[i],self.win.test()))\n y=np.asarray(y1)\n if (re.search(pattern3,str(self.edit3b.text()))):\n r=eval(str(self.edit3b.text()))\n self.edit4b.setText(str(notch.nsp(alpha,r,self.win.test())))\n elif re.search(pattern2,func):\n Su=notch.su_a(rho)\n if (self.win.test()==0):\n Su = Su*6.895\n for i in range(len(x)):\n y1.append(notch.nsn(rho,x[i],self.win.test()))\n y=np.asarray(y1)\n if (re.search(pattern3,str(self.edit3b.text()))):\n r=eval(str(self.edit3b.text()))\n self.edit4b.setText(str(notch.nsn(rho,r,self.win.test())))\n \n self.edit2b.setText(str(Su))\n func1 = 'Steel (Su='+str(self.edit2b.text())+')'\n if (func!='Steel (input Su)'):\n self.plot.redraw(x,y,func, self.xlabel)\n elif (func=='Steel (input Su)'):\n self.plot.redraw(x,y,func1, self.xlabel)\n \n elif (func=='Comparison Chart'):\n self.edit2b.setText(\"\")\n self.edit2b.setDisabled(True)\n self.edit3b.setText(\"\")\n self.edit3b.setDisabled(True)\n self.edit4b.setText(\"\")\n self.edit4b.setDisabled(True)\n self.plot.draw_comp(self.xlabel, self.win.test())","def eta_ ( self ) :\n from GaudiConfUtils.ConfigurableGenerators import FilterDesktop\n from StandardParticles import StdLooseEta2gg as inpts \n ##\n return self.make_selection (\n 'EtaStd' ,\n FilterDesktop ,\n [ inpts ] ,\n Code = self['Eta2ggCut'] ,\n )","def main():\n main = tk.Tk()\n\n # Add Title\n main.title(\"Space Craft Creator\")\n\n # Disable Resizing\n main.resizable(False, False)\n\n data = Data()\n\n spacecraft = Spacecraft(data)\n\n notebook = Notebook(main)\n\n spacecraft_tab = spacecraft.make_tab(notebook)\n\n notebook.add(spacecraft_tab, text=\"Spacecraft\")\n for key, subsystem in spacecraft.subsections.items():\n notebook.add(subsystem.make_tab(notebook), text=key)\n notebook.add(spacecraft.sizes.make_tab(notebook), text=\"Sizes\")\n notebook.add(spacecraft.velocities.make_tab(notebook), text=\"Velocity Profiles\")\n\n notebook.grid(column=0, row=0)\n notebook.enable_traversal()\n\n button = Button(main, text=\"Caclulate\", command=spacecraft.calculate)\n button.grid(column=0, row=1)\n\n main.mainloop()","def interactive(self, name='grid', bind_x=True, bind_y=True):\n encodings = []\n if bind_x:\n encodings.append('x')\n if bind_y:\n encodings.append('y')\n self.selection = {name: {'bind': 'scales',\n 'type': 'interval',\n 'encodings': encodings}}\n return self","def main():\n PanelDemo().mainloop()","def edit():\n\n curitem = treeview.focus().strip(\"#\")\n select_values = series_dict[curitem]\n editent2var.set(\"thumbnails\\\\\")\n\n def raging_fire():\n \"\"\"call back function for edit button in the edit window\"\"\"\n\n if editspin1.get() != '0': # season\n select_values[0] = int(editspin1.get())\n select_values[3] = \"{}\".format(datetime.datetime.now()) # update the modify date\n with open('series_table.json', 'w') as f:\n json.dump(series_dict, f, indent=2)\n\n if editspin2.get() != '0': # episode\n select_values[1] = int(editspin2.get())\n select_values[3] = \"{}\".format(datetime.datetime.now()) # update the modify date\n with open('series_table.json', 'w') as f:\n json.dump(series_dict, f, indent=2)\n\n if editentvar.get() != curitem: # name\n series_dict[editentvar.get().title()] = series_dict.pop(curitem) # update the modify date\n select_values[3] = \"{}\".format(datetime.datetime.now())\n with open('series_table.json', 'w') as f:\n json.dump(series_dict, f, indent=2)\n\n if editent2var.get() != select_values[2]: # pic\n select_values[3] = \"{}\".format(datetime.datetime.now()) # update the modify date\n select_values[2] = editent2var.get()\n with open('series_table.json', 'w') as f:\n json.dump(series_dict, f, indent=2)\n\n edittop.destroy()\n\n if curitem != \"\": # test if an item is highlighted first\n \"\"\"the actual ecit window widgets\"\"\"\n edittop = Toplevel()\n\n editlab1 = Label(edittop, text=\"Current Tv-Series title : \")\n editlab1.grid(row=1, column=1, sticky=W, pady=4)\n\n editent = Entry(edittop, textvariable=editentvar, width=30)\n editentvar.set(curitem)\n editent.grid(row=1, column=2, sticky=W, pady=4)\n\n editlab2 = Label(edittop, text=\"Current Season {}, chance to : \".format(select_values[0]))\n editlab2.grid(row=2, column=1, sticky=W, pady=4)\n\n editspin1 = Spinbox(edittop, from_=0, to=1000, width=5)\n editspin1.grid(row=2, column=2, sticky=W, pady=4)\n\n editlab3 = Label(edittop, text=\"Current Episode {}, change to : \".format(select_values[1]))\n editlab3.grid(row=3, column=1, sticky=W, pady=4)\n\n editspin2 = Spinbox(edittop, from_=0, to=1000, width=5)\n editspin2.grid(row=3, column=2, sticky=W, pady=4)\n\n editlab4 = Label(edittop, text=\"Change image to : \")\n editlab4.grid(row=4, column=1, sticky=W, pady=4)\n\n editent2 = Entry(edittop, textvariable=editent2var, width=35)\n editent2var.set(select_values[2])\n editent2.grid(row=4, column=2, sticky=E, pady=4)\n\n editbut = Button(edittop, text='Edit', command=raging_fire)\n editbut.grid(row=5, column=1, sticky=W, pady=4, padx=20)\n\n download_thumbbut = Button(edittop, text=\"Download The thumbnail\", command=download_thumb)\n download_thumbbut.grid(row=5, column=2, sticky=W, pady=4, padx=20)\n\n edittop.geometry(\"400x200+200+300\")\n edittop.title(\"Edit properties of {} \".format(curitem).upper())","def make_interactive(model: EpamModel, Xy_raw: pd.DataFrame):\n \n def inner(base_example: int = 0):\n \"\"\"Inner function that does the work.\"\"\"\n EX = Xy_raw.iloc[base_example]\n print(\"Base Example IDs:\")\n print((Xy_raw.index[[base_example]]).to_frame().reset_index(drop=True).iloc[0].rename(index=base_example))\n\n def get_widget(col: str):\n V = EX[col]\n if 'Tak' in Xy_raw[col].values.tolist():\n zz = [\"Tak\", \"Nie\", \"Nie wiadomo\"]\n return w.Select(options=zz, value=\"Nie wiadomo\" if (V not in zz) else V)\n\n d = Xy_raw[col].dtype\n if d == \"int64\":\n return w.IntSlider(min=Xy_raw[col].min(), max=Xy_raw[col].max(), value=V)\n elif d == \"float64\":\n return w.FloatText(value=V)#Xy_raw[col].mean())\n\n def _f(s):\n try:\n return float(s)\n except:\n return np.nan\n avg_val = Xy_raw[col].apply(_f).mean()\n if pd.isnull(V):\n V = str(avg_val)\n return w.Text(value=V)\n\n\n def make_pred(**vals):\n my_X_raw = pd.Series(vals).to_frame().T\n my_X_raw = my_X_raw.astype(Xy_raw.drop(columns=[basic_target]).dtypes)\n my_X = cleanup_df(my_X_raw)#.astype(X.dtypes)\n\n ifd = model.ifd_\n with model.build_model(my_X) as m:\n _ppc_oos = pm.fast_sample_posterior_predictive(ifd)\n ifd_oos = az.from_pymc3(posterior_predictive=_ppc_oos)\n ppc_oos = ifd_oos.posterior_predictive['y_pred']\n y_oos = ppc_oos.mean([\"chain\", \"draw\"]).to_series()\n\n # y_prob = model.predict_proba(my_X)\n print(\"Prediction:\", y_oos.iloc[0])\n\n widgets = {k: get_widget(k) for k in Xy_raw.drop(columns=[basic_target]).columns}\n \n w.interact_manual(make_pred, **widgets)\n return w.interact(\n inner, \n base_example=w.IntText(min=0, max=len(Xy_raw)-1, value=0, description=\"Base Case\")\n )","def setupVariableAxes(self):\n if self.var is None:\n return\n \n if (self.axisList is None):\n self.axisList = self.var.getAxisList()\n self.axisOrder = range(len(self.axisList))\n\n self.clear() \n self.setAxesNames()\n \n # Iterate through the variables axes & init each axis widget\n axisIndex = 0\n for axis, axisName in zip(self.axisList, self.axesNames):\n # Create the axis widget\n axisWidget = QAxis(axis, axisName, axisIndex, self)\n axisWidget.setAxisButtonText(axisName)\n self.axisWidgets.append(axisWidget)\n\n # Setup the layout for each axis\n row = self.gridLayout.rowCount()\n self.gridLayout.addWidget(axisWidget.getAxisButton(), row, 0)\n self.gridLayout.addWidget(axisWidget, row, 1) \n self.gridLayout.addWidget(axisWidget.getAxisOperationsButton(), row, 2)\n\n # Create separator line between each axis widget\n vline = QtGui.QFrame()\n vline.setFrameStyle(QtGui.QFrame.HLine | QtGui.QFrame.Sunken)\n self.gridLayout.addWidget(vline, row+1, 0, 1,\n self.gridLayout.columnCount())\n\n axisIndex += 1\n\n self.gridLayout.setRowStretch(self.gridLayout.rowCount(), 1)","def main():\n app = guisupport.get_app_qt4()\n\n if INPROCESS:\n from qtconsole.inprocess import QtInProcessKernelManager\n km = QtInProcessKernelManager()\n else:\n from qtconsole.manager import QtKernelManager\n km = QtKernelManager()\n km.start_kernel()\n km.kernel.gui = 'qt4'\n kc = km.client()\n kc.start_channels()\n\n widget = RichJupyterWidget()\n widget.kernel_manager = km\n widget.kernel_client = kc\n if CLEANSHUTDOWN: # slow exit on CTRL+D\n def stop():\n kc.stop_channels()\n km.shutdown_kernel()\n app.exit()\n widget.exit_requested.connect(stop)\n else: # fast exit on CTRL+D\n widget.exit_requested.connect(app.quit)\n widget.show()\n guisupport.start_event_loop_qt4(app)","def _create_3D_pane(self):\n\t\t\n panel = wx.Panel(self,-1)\n self.interactor3d = wxVTKRenderWindowInteractor(panel, -1, (600,800))\n self.generate_button = wx.Button(panel, label=\"Generate 3D view\")\n self.text_position = wx.StaticText(panel, -1, \"Dose (Gy) \" , wx.Point(0, 0))\n self.slider_dose3d = wx.Slider(panel, -1, 75, 60, 100, wx.DefaultPosition, wx.Size( 100,-1 ), wx.SL_HORIZONTAL)\n self.spin_dose3d = wx.SpinCtrl(panel, wx.ID_ANY, str(self.slider_dose3d.GetValue()), wx.DefaultPosition, wx.Size( 70,-1 ), wx.SP_ARROW_KEYS, min=0, max=100, initial=11)\t\n\t\t\n button_sizer = wx.BoxSizer(wx.HORIZONTAL)\n button_sizer.AddSpacer(30)\n button_sizer.Add(self.generate_button)\n button_sizer.AddSpacer(30)\n button_sizer.Add(self.text_position)\n button_sizer.Add(self.slider_dose3d)\n button_sizer.Add(self.spin_dose3d)\n\t\t\n listsizer = wx.BoxSizer(wx.VERTICAL)\n listsizer.Add(self.interactor3d, 1, wx.EXPAND|wx.BOTTOM, 7)\n listsizer.Add(button_sizer)\n panel.SetSizer(listsizer)\n listsizer.Fit(panel)\n\t\t\n self._create_orientation_widget(self.interactor3d)\n return panel","def run_ejercicio_3():\n\n # Parametros para el ejercicio\n lower = 0\n upper = 4 * np.pi\n number_of_points = 100\n\n print(f\"Separando el intervalo [{lower}, {upper}] en {number_of_points} puntos equidistantes\")\n values = np.linspace(lower, upper, number_of_points)\n print(\"\")\n\n print(f\"Mapeando los valores a las tres funciones dadas\")\n sin_values, cos_values, complex_function_values = map_values_to_functions(values)\n print(\"\")\n\n print(f\"Los valores son: {values}\\n\")\n print(f\"Valores en el seno: {sin_values}\\n\")\n print(f\"Valores en el coseno: {cos_values}\\n\")\n print(f\"Valores en tanh(sin + cos): {complex_function_values}\\n\")\n print(\"\")\n wait_for_user_input()\n\n print(\"Mostrando la grafica de los valores\")\n plot_three_functions(values, sin_values, cos_values, complex_function_values)","def interact(self):\n # We use a library_interact instead of a normal interact here,\n # since this is an interact in the library, and a normal\n # \"@interact\" is all mangled.\n\n from sage.interacts.library import library_interact\n from sagenb.notebook.interact import slider, input_box, selector\n\n # self._last holds the last state of all controls. This allows\n # us to deduce which control changed to cause the update, or that\n # nothing changed, in which case we assume the user requested to\n # re-evaluate the input box (for some reason -- currently there is\n # no point in doing so). It is a shortcoming of @interact that\n # we have to do this.\n self._last = None\n\n # two sliders and a box to put in commands with an evaluate button.\n @library_interact\n def dbg(frame = slider(vmin=0, vmax=len(self._stack)-1, step_size=1, default=len(self._stack)-1, label='stack frame'),\n lines = slider(vmin=3, vmax=99, step_size=2, default=11, label='lines of context'),\n command = input_box(\"\", label=\"\", type=str),\n button = selector(['Evaluate'], label='', buttons=True)\n ):\n\n if self._last is None:\n self._last = {'command':command, 'button':button, 'lines':lines, 'frame':frame}\n\n if self._last['lines'] != lines:\n # they dragged the number-of-lines slider, so done\n pass\n elif self._last['command'] != command and command.strip():\n # they changed the command, so evaluate that\n self.evaluate(command)\n elif self._last['frame'] != frame:\n # they dragged the frame slider.\n self._curframe_index = frame\n elif command:\n # must have hit the evaluate button\n self.evaluate(command)\n\n print('<html><hr>{}</html>'.format(self.listing(lines//2)))\n # save control state for next time around\n self._last = {'command':command, 'button':button, 'lines':lines, 'frame':frame}\n\n dbg()","def add_sliders(self):\n\n\t\tself.scale_dict = {}\n\t\tinnov_str = simpledialog.askstring(\"Get Innovations.\", \n\t\t\t\"What innovation numbers do you want sliders for (separate with commas)?\")\n\t\tinnov_nums = innov_str.split(\",\")\n\t\tfor innov in innov_nums:\n\t\t\tself.scale_dict[innov] = tk.Scale(self, from_=-20, \n\t\t\t\tto=20, orient=tk.HORIZONTAL)\n\t\t\ttk.Label(self, text=\"Slider for #{0}\".format(innov)).pack()\n\t\t\tself.scale_dict[innov].pack(pady=10)\n\t\ttk.Button(self, text=\"Apply\", command=lambda: self.slider_update_CPPN()).pack()\n\n\n\t\ttk.Button(self, text=\"Exit\", command=self.quit).pack(pady=(20,10))","def isoslider(surface_dic, surface_value_dic, min_value=0):\r\n return \\\r\nf\"\"\"\r\n\\n\\nclass IsoLevel(tk.Variable):\r\n def __init__(self, master, name, level):\r\n tk.Variable.__init__(self, master, value=level)\r\n self.name = name\r\n self.trace('w', self.callback)\r\n\r\n def callback(self, *args):\r\n cmd.isolevel(self.name, self.get())\r\n\r\n def increment(self, event=None, delta=0.1):\r\n self.set(round(float(self.get()) + delta, 2))\r\n\r\n def decrement(self, event=None):\r\n self.increment(None, -0.1)\r\n\r\n\r\nsurface_list = {surface_dic}\r\nsurface_max_list = {surface_value_dic}\r\n\r\ntop = tk.Toplevel(plugins.get_tk_root())\r\n\r\nmaster = tk.Frame(top, padx=10, pady=10)\r\nmaster.pack(fill=\"both\", expand=1)\r\n\r\nfor child in list(master.children.values()):\r\n child.destroy()\r\n\r\n\r\nrow_counter = 0\r\nfor identifier, component_dic in surface_list.items():\r\n # add calculation identifier\r\n tk.Label(master, text=identifier).grid(row=row_counter, column=0, sticky=\"w\")\r\n row_counter += 1\r\n \r\n for component_id, surfaces in component_dic.items():\r\n # add collection label, e.g. superstar or hotspot etc.\r\n tk.Label(master, text=component_id).grid(row=row_counter, column=1, sticky='w')\r\n row_counter += 1\r\n \r\n for i, surface in enumerate(surfaces):\r\n # add grid type label\r\n probe = surface.split(\"_\")[-2]\r\n tk.Label(master, text=probe).grid(row=row_counter, column=2, sticky=\"w\")\r\n \r\n # slider code \r\n v = IsoLevel(master, surface, 5)\r\n e = tk.Scale(master, orient=tk.HORIZONTAL, from_={min_value}, to=surface_max_list[identifier][component_id],\r\n resolution=0.1, showvalue=0, variable=v)\r\n e.grid(row=row_counter, column=3, sticky=\"ew\")\r\n\r\n e = tk.Entry(master, textvariable=v, width=4)\r\n e.grid(row=row_counter, column=4, sticky=\"e\")\r\n master.columnconfigure(3, weight=1)\r\n row_counter += 1\r\n\\n\\n\r\n\"\"\"","def launch_new_instance():\n import IPython\n\n IPython.Shell.start().mainloop()","def test_visuThreeD1(self):\n\n visu_logic = slicer.modules.visuThreeDWidget.logic\n #visu_logic.set_user_table(self.user_table)\n #visu_logic.set_user_file('/work/maria5/EBDS_CIVILITY/DataShare/TestMatricesForVisualization/AAL78/PerNodeMetrics/Conte_EigenVectorCentrality_4Yr_AAL78Regions.csv')\n #visu_logic.set_user_file('/Users/Wieke/Documents/visuThreeD/neo-0042-4year_AvgSym_normFull.csv')\n # visu_logic.create_node_actors()\n # visu_logic.create_line_actors()\n # visu_logic.update()\n #visu_logic.set_node_range()","def main():\n\tif mc.window( 'curveScatter_WIN', q = 1, ex = 1 ):\n\t\tmc.deleteUI( 'curveScatter_WIN' )\n\tPyForm=CurveScatterUI()\n\tPyForm.show()","def __init__(self, controller):\n self.controller = controller\n\n self.electoral_distribution = None\n\n # Shows the forecast for electoral college votes over time.\n self.ecvdistribution = figure(\n title=\"\"\"Electoral college votes distribution\"\"\",\n x_axis_type=\"\"\"linear\"\"\",\n x_axis_label=\"\"\"Electoral college votes\"\"\",\n y_axis_label=\"\"\"Probability\"\"\",\n sizing_mode=\"\"\"stretch_both\"\"\")\n # Fake data to make sure we don't get an empty renderer message\n self.cds = ColumnDataSource(\n data={'Electoral college votes': list(range(539)),\n 'Democratic distribution': norm.pdf(range(539),\n loc=200,\n scale=100),\n 'Republican distribution': norm.pdf(range(539),\n loc=400,\n scale=100)}\n )\n _dg = self.ecvdistribution.vbar(\n x='Electoral college votes',\n top='Democratic distribution',\n fill_color='blue',\n line_color='blue',\n line_width=1,\n width=1,\n alpha=0.2,\n source=self.cds)\n _rg = self.ecvdistribution.vbar(\n x='Electoral college votes',\n top='Republican distribution',\n fill_color='red',\n line_color='red',\n line_width=1,\n width=1,\n alpha=0.2,\n source=self.cds)\n # 270 to win line\n _win270 = Span(location=270, dimension='height')\n self.ecvdistribution.add_layout(_win270)\n # Add a legend outside of the plot\n _legend = Legend(items=[('Democratic', [_dg]),\n ('Republican', [_rg])],\n location='top_right')\n self.ecvdistribution.add_layout(_legend, 'right')\n self.ecvdistribution.legend.click_policy = \"hide\"\n self.ecvdistribution.y_range.only_visible = True\n\n # The date for charting.\n self.choosethedatefordisplay = DateSlider(\n title=\"\"\"Choose the date for display\"\"\",\n start=\"\"\"2018-11-13T20:20:39+00:00\"\"\",\n end=\"\"\"2025-11-13T20:20:39+00:00\"\"\",\n step=24*60*60*1000,\n value=\"\"\"2018-11-13T20:20:39+00:00\"\"\",\n sizing_mode=\"stretch_width\")\n\n # Layout the widgets\n r1 = row(children=[Spacer(width=10),\n self.choosethedatefordisplay,\n Spacer(width=10)],\n sizing_mode='stretch_width')\n self.layout = column(children=[self.ecvdistribution,\n r1,\n Spacer(height=75,\n sizing_mode='scale_width')],\n sizing_mode='stretch_both')\n self.panel = Panel(child=self.layout,\n title='Vote forecast distribution')","def figure2():\n # sim_data_XPP = pd.read_csv(\"XPP.dat\", delimiter=\" \", header=None) # Load the XPP simulation\n\n plot_settings = {'y_limits': [-25, 0],\n 'x_limits': None,\n 'y_ticks': [-25, -20, -15, -10, -5, 0],\n 'locator_size': 2.5,\n 'y_label': 'Current (nA)',\n 'x_ticks': [],\n 'scale_size': 0,\n 'x_label': \"\",\n 'scale_loc': 4,\n 'figure_name': 'figure_2',\n 'legend': ['I-Na', 'I-NaP'],\n 'legend_size': 8,\n 'y_on': True}\n\n t, y = solver(100) # Integrate solution\n t_short = np.where((t >= 8) & (t <= 18))[0] # shorter time bounds for plots A and C\n v, m, h, m_nap, h_na_p, n, m_t, h_t, m_p, m_n, h_n, z_sk, m_a, h_a, m_h, ca = y[:, ].T # Extract all variables\n\n \"\"\"\n Explicitly calculate all currents: Extra constants duplicated from function dydt to calculate currents\n \"\"\"\n g_na_bar = 0.7\n g_nap_bar = 0.05\n g_k_bar = 1.3\n g_p_bar = 0.05\n g_leak = 0.005\n g_a_bar = 1.0\n e_na = 60\n e_k = -80\n e_leak = -50\n e_ca = 40\n g_t_bar = 0.1\n g_n_bar = 0.05\n g_sk_bar = 0.3\n\n \"\"\"\n Calculate currents used in the plot\n \"\"\"\n i_na = g_na_bar * (m ** 3) * h * (v - e_na)\n i_na_p = g_nap_bar * m_nap * h_na_p * (v - e_na)\n i_k = g_k_bar * (n ** 4) * (v - e_k)\n i_leak = g_leak * (v - e_leak)\n i_t = g_t_bar * m_t * h_t * (v - e_ca)\n i_n = g_n_bar * m_n * h_n * (v - e_ca)\n i_p = g_p_bar * m_p * (v - e_ca)\n i_sk = g_sk_bar * (z_sk ** 2) * (v - e_k)\n i_a = g_a_bar * m_a * h_a * (v - e_k)\n\n plt.figure(figsize=(5, 3), dpi=96) # Create figure\n\n plt.subplot(2, 2, 1) # Generate subplot 1 (top left)\n plt.plot(t[t_short], i_na[t_short], 'k-')\n plt.plot(t[t_short], i_na_p[t_short], c='k', linestyle='dotted')\n alter_figure(plot_settings) # Alter figure for publication\n\n plt.subplot(2, 2, 2) # Generate subplot 2 (top right)\n plt.plot(t, i_t + i_n + i_p, 'k-')\n plt.plot(t, i_t, c='k', linestyle='dotted')\n plt.plot(t, i_p, 'k--')\n plt.plot(t, i_n, 'k-.')\n\n plot_settings['y_limits'] = [-2.5, 0]\n plot_settings['y_ticks'] = [-2.5, -2, -1.5, -1, -0.5, 0]\n plot_settings['locator_size'] = 0.25\n plot_settings['y_label'] = \"\"\n plot_settings['legend'] = ['I-Ca', 'I-T', 'I-P', 'I-N']\n alter_figure(plot_settings) # Alter figure for publication\n\n plt.subplot(2, 2, 3) # Generate subplot 3 (bottom left)\n plt.plot(t[t_short], i_k[t_short], 'k-')\n plt.plot(t[t_short], i_a[t_short], c='k', linestyle='dotted')\n plt.plot(t[t_short], i_leak[t_short], 'k-.')\n\n plot_settings['y_limits'] = [0, 25]\n plot_settings['y_ticks'] = [0, 5, 10, 15, 20, 25]\n plot_settings['locator_size'] = 2.5\n plot_settings['y_label'] = \"Current (nA)\"\n plot_settings['legend'] = ['I-K', 'I-A', 'I-leak']\n plot_settings['scale_size'] = 2\n plot_settings['scale_loc'] = 2\n alter_figure(plot_settings) # Alter figure for publication\n\n plt.subplot(2, 2, 4) # Generate subplot 4 (bottom left)\n\n plt.plot(t, i_sk, 'k-')\n # plt.plot(sim_data_XPP[0][900:]-200,sim_data_XPP[34][900:]) # Isk for XPP data\n\n plot_settings['y_limits'] = [0, 1]\n plot_settings['y_ticks'] = [0, 0.2, 0.4, 0.6, 0.8, 1]\n plot_settings['locator_size'] = 0.2\n plot_settings['y_label'] = \"\"\n plot_settings['legend'] = ['I-SK']\n plot_settings['scale_size'] = 20\n plot_settings['scale_loc'] = 2\n alter_figure(plot_settings, close=True) # Alter figure for publication","def plot_delta_curve(deltas, prefix, tdir):\n # get figure and axes\n fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(6, 4))\n\n # plot reward curve\n k = deltas['k']\n d = deltas['d']\n ax.plot(k, d, color='g')\n ax.set_title('Delta Convergence ({})'.format(prefix))\n ax.set_ylabel('Delta Value')\n ax.set_xlabel('Episodes')\n ax.grid(linestyle='dotted')\n fig.tight_layout()\n\n # save figure\n plotpath = get_abspath('{}_deltas.png'.format(prefix), tdir)\n plt.savefig(plotpath)\n plt.close()","def softDeformer():\n softDeformerUI()","def demo():\n ...","def dynamic_figure(r=None,z=None,t=None):\n global yt, t0, nt, zcut, theta, cnt, main_title\n\n if r is None:\n RunTimeError(\"r is None\")\n if z is None:\n RunTimeError(\"z is None\")\n if t is None:\n RunTimeError(\"t is None\")\n \n theta = linspace( 0.0, 2.0*scipy.pi, num=100)\n \n R, Z = meshgrid(r,z)\n \n fu = FuModel(nt=100)\n \n ycube = fu.FuCon(R, Z, t) # ycube[:,:,:] DATA CUBE!!!\n\n #-----------------------------FIGURES------------------------------\n fig = figure(figsize=(6,8.5))\n \n t0 = 0\n yt = ycube[:,:,t0]\n \n titulo = 'Fu drug diffusion model: t = %07.2f' % t[t0]\n main_title=fig.text(0.25, 0.95, titulo,\n horizontalalignment='left',\n fontproperties=FontProperties(size=16))\n \n cmap = cm.cool\n subplots_adjust(hspace=0.0)\n \n subplot(211)\n ax = gca()\n im1 = imshow(yt,\n interpolation='bilinear',\n cmap=cmap,\n origin='lower',\n extent=(0,1.0,z[0],z[-1]),\n aspect = 0.23\n )\n \n xlabel(r'R = r/a', fontsize=14)\n ylabel(r'Z = z/l', fontsize=14)\n\n subplot(212,aspect='equal')\n ax = gca()\n\n #\n #--- cylindrical cross-section\n \n RAD, THETA = meshgrid(r,theta)\n Xpos = RAD*cos(THETA)\n Ypos = RAD*sin(THETA)\n \n #\n # top cap of cylinder\n #\n #zcut = len(z)-1\n zcut = 0\n if z[0] != 0.0:\n zcut = int(len(z)/2+0.5)\n title('Z = %f'%z[zcut],fontsize=16)\n #\n # Take a cross-section of the cylinder at some point Z ==> radius array of length len(r) \n # -----\n # Trick\n # -----\n # Now create a matrix[len(theta),len(r)] by replicating the above array len(theta) times\n # along dimension 0\n #\n \n zx = outer( ones(len(theta)), yt[zcut,:] )\n \n im2 = pcolormesh(Xpos, Ypos,\n zx,\n shading='flat',\n cmap=cmap)\n \n xlabel(r'X/a', fontsize=14)\n ylabel(r'Y/a', fontsize=14)\n \n #\n #--- new axis for colorbar\n #\n norm = colors.Normalize(vmin=0.0, vmax=1.0)\n im1.set_norm(norm)\n im2.set_norm(norm)\n im1.add_observer(im2)\n \n pos = ax.get_position()\n l, b, w, h = getattr(pos, 'bounds', pos)\n cax = axes([l+w+0.015, b, 0.025, h]) # setup colorbar axes\n colorbar(im1, cax, orientation='vertical') \n \n manager = get_current_fig_manager()\n \n cnt = 0\n files = []\n nt = len(t)\n #\n #------------------------------------------------------------------\n def updatefig(*args):\n global yt, t0, nt, zcut, theta, cnt, main_title\n \n t0 += 1\n if t0 > nt-1:\n return False\n \n yt = ycube[:,:,t0]\n zx = outer( ones(len(theta)), yt[zcut,:] )\n Nx, Ny = yt.shape\n im1.set_array(yt)\n im2.set_array(ravel(zx[0:Nx-1,0:Ny-1]))\n titulo = 'Fu drug diffusion model: t = %07.2f' % t[t0]\n main_title.set_text(titulo)\n manager.canvas.draw()\n \n #fname = '_tmp%03d.jpg' % t0\n fname = '_tmp%03d.png' % t0\n savefig(fname)\n files.append(fname)\n \n cnt += 1\n return True\n #\n #------------------------------------------------------------------\n\n cnt = 0\n gobject.idle_add(updatefig)\n\n ioff()\n show()\n\n command = \"ffmpeg -r 10 -sameq -i _tmp%03d.png test.mp4\"\n #command = \"mencoder -ovc xvid -xvidencopts \" + \\\n # \"pass=2:bitrate=15999:max_bframes=0 \" + \\\n # \"-oac copy -mf fps=10:type=jpeg 'mf://_tmp*.jpg' -vf harddup -ofps 10 \" + \\\n # \"-noskip -of avi -o outputfile.avi\"\n os.system(command)\n for fname in files: os.remove(fname) #clean up\n\n return True","def show():\n setup()\n plt.show()","def run_pendulum_example(duration=1.0, playback=True, show=True):\n\n builder = DiagramBuilder()\n plant, scene_graph = AddMultibodyPlantSceneGraph(builder, 0.0)\n parser = Parser(plant)\n parser.AddModelFromFile(FindResourceOrThrow(\n \"drake/examples/pendulum/Pendulum.urdf\")\n )\n plant.WeldFrames(plant.world_frame(), plant.GetFrameByName(\"base\"))\n plant.Finalize()\n\n pose_bundle_output_port = scene_graph.get_pose_bundle_output_port()\n T_VW = np.array([[1., 0., 0., 0.],\n [0., 0., 1., 0.],\n [0., 0., 0., 1.]])\n visualizer = builder.AddSystem(PlanarSceneGraphVisualizer(\n scene_graph, T_VW=T_VW,\n xlim=[-1.2, 1.2], ylim=[-1.2, 1.2], show=show))\n \n builder.Connect(pose_bundle_output_port, visualizer.get_input_port(0))\n if playback:\n visualizer.start_recording()\n \n diagram = builder.Build()\n simulator = Simulator(diagram)\n simulator.Initialize()\n simulator.set_target_realtime_rate(1.0)\n\n # Fix the input port to zero\n plant_context = diagram.GetMutableSubsystemContext(\n plant, simulator.get_mutable_context()\n )\n plant.get_actuation_input_port().FixValue(\n plant_context, np.zeros(plant.num_actuators())\n )\n plant_context.SetContinuousState([0.5, 0.1])\n simulator.AdvanceTo(duration)\n\n if playback:\n visualizer.stop_recording()\n ani = visualizer.get_recording_as_animation()\n return ani\n else:\n return None","def __init__(self):\r\n EasyFrame.__init__(self, title=\"Investment Calculator\")\r\n self.addLabel(text=\"Initial amount\", row=0, column=0)\r\n self.addLabel(text=\"Number of years\", row=1, column=0)\r\n self.addLabel(text=\"Interest rate in %\", row=2, column=0)\r\n self.amount = self.addFloatField(value=0.0, row=0, column=1)\r\n self.period = self.addIntegerField(value=0, row=1, column=1)\r\n self.rate = self.addIntegerField(value=0, row=2, column=1)\r\n\r\n self.outputArea = self.addTextArea(\"\", row=4, column=0, columnspan=2, width=50, height=15)\r\n\r\n self.compute = self.addButton(text=\"Compute\", row=3, column=0, columnspan=2, command=self.compute)","def main():\n viewer = Viewer()\n\n # paramètre de transformation des paramètres\n #sol\n ground_size = 512\n ground_offset = 20\n\n #dinosaure\n characters_offset_x = 0\n characters_offset_y = -20\n characters_offset_z = 0\n characters_scale = 15\n characters_rotate_deg = 180\n\n #forêt\n forest_offset = -15\n forest_scale = 1.5\n\n #skybox\n Skysphere_scale = 3\n\n characters = Node(transform = translate(characters_offset_x, characters_offset_y, characters_offset_z) @ scale(characters_scale) @ rotate(axis=(0, 1, 0), angle = characters_rotate_deg))\n characters.add(*load_skinned(\"dino/Dinosaurus_roar.dae\"))\n\n forest = Node(transform = translate(0, forest_offset, 0) @ scale(forest_scale))\n forest.add(*load_textured(\"trees9/forest.obj\"))\n\n ground = Node(transform = translate(-ground_size>>1, ground_offset, -ground_size>>1))\n ground.add(sol(ground_size))\n\n Skysphere = Node(transform = scale(Skysphere_scale))\n Skysphere.add(*load_textured(\"Skysphere/skysphere.obj\"))\n\n scene = Node(transform = identity(), children = [characters, forest, ground, Skysphere])\n\n viewer.add(scene)\n\n viewer.run()","def switch_context(self, new_location):\n #Clear Figures to avoid memory leak\n for figure in self.figures:\n figure.clear()\n plt.close(figure)\n \n #Close the exisiting display\n self.destroy()\n \n #Generate user interface\n UI = SD_UI(tuning = self.tuning_flag,\n location = new_location,\n language = self.language,\n arrangment = self.arrangment)\n \n #Run the new user interface\n UI.mainloop()","def abrir_demo(self, widget, data=None):\n\t\tself.w3.hide()\n\t\tself.w5.show_all()","def dynamics(self,eta,nu,u_actual,u_control,sampleTime): \n \n # Current velocities\n u_c = self.V_c * math.cos(self.beta_c - eta[5]) # current surge velocity\n v_c = self.V_c * math.sin(self.beta_c - eta[5]) # current sway velocity \n \n nu_c = np.array([u_c,v_c,0,0,0,0],float) # current velocity vector\n nu_r = nu - nu_c # relative velocity vector\n \n U_r = math.sqrt( nu_r[0]**2 + nu_r[1]**2 ) # relative speed\n \n # Rudder command and actual rudder angle\n delta_c = u_control[0]\n delta = u_actual[0]\n \n # Rudder forces and moment (Fossen 2021, Chapter 9.5.1)\n b = 0.7 * self.T # rudder height\n AR = b**2 / self.Lambda # aspect ratio: Lamdba = b**2/AR \n CN = 6.13 * self.Lambda / ( self.Lambda + 2.25 ) # normal coefficient\n t_R = 1 - 0.28 * self.Cb - 0.55\n a_H = 0.4\n x_R = -0.45 * self.L\n x_H = -1.0 * self.L\n\n Xdd = -0.5 * ( 1 - t_R ) * self.rho * U_r**2 * AR * CN\n Yd = -0.25 * ( 1 + a_H ) * self.rho * U_r**2 * AR * CN \n Nd = -0.25 * ( x_R + a_H * x_H ) * self.rho * U_r**2 * AR * CN \n \n # Control forces and moment\n delta_R = -delta # physical rudder angle (rad)\n T = self.tau_X # thrust (N)\n t_deduction = 0.1 # thrust deduction number\n tau1 = ( 1 - t_deduction ) * T - Xdd * math.sin( delta_R )**2 \n tau2 = -Yd * math.sin( 2 * delta_R ) \n tau6 = -Nd * math.sin( 2 * delta_R ) \n tau = np.array( [ tau1, tau2, tau6 ],float) \n \n # Linear maneuvering model\n T_surge = self.L # approx. time constant in surge (s)\n xg = 0 # approx. x-coordinate, CG (m) \n \n # 3-DOF ship model\n [M,N] = clarke83(U_r,self.L, self.B, self.T,self.Cb,self.R66,xg,T_surge)\n Minv = np.linalg.inv(M)\n nu3 = np.array( [ nu_r[0], nu_r[1], nu_r[5] ]) \n nu3_dot = np.matmul( Minv, tau - np.matmul(N,nu3) ) \n \n # 6-DOF ship model\n nu_dot = np.array( [ nu3_dot[0],nu3_dot[1],0,0,0,nu3_dot[2] ]) \n\n # Rudder angle saturation\n if ( abs(delta) >= self.deltaMax * math.pi / 180 ):\n delta = np.sign(delta) * self.deltaMax * math.pi / 180\n \n # Rudder dynamics\n delta_dot = (delta_c - delta) / self.T_delta \n\n # Forward Euler integration [k+1]\n nu = nu + sampleTime * nu_dot\n delta = delta + sampleTime * delta_dot\n\n u_actual = np.array([delta],float) \n\n return nu, u_actual","def recipe_dv360_editor(config, auth_dv, auth_sheet, auth_bigquery, recipe_name, recipe_slug, command):\n\n dataset(config, {\n '__comment__':'Ensure dataset exists.',\n 'auth':auth_bigquery,\n 'dataset':recipe_slug\n })\n\n drive(config, {\n '__comment__':'Copy the default template to sheet with the recipe name',\n 'auth':auth_sheet,\n 'copy':{\n 'source':'https://docs.google.com/spreadsheets/d/18G6cGo4j5SsY08H8P53R22D_Pm6m-zkE6APd3EDLf2c/',\n 'destination':recipe_name\n }\n })\n\n dv_editor(config, {\n '__comment':'Depending on users choice, execute a different part of the solution.',\n 'auth_dv':auth_dv,\n 'auth_sheets':auth_sheet,\n 'auth_bigquery':auth_bigquery,\n 'sheet':recipe_name,\n 'dataset':recipe_slug,\n 'command':command\n })","def vp_start_gui():\n global top, app\n app = tk.Tk()\n ui_support.set_Tk_var()\n top = Window(app)\n top.price_panel.old_matrix_checkbox.select()\n top.price_panel.select_old()\n top.generic_panel.dynamic_stop_checkbox.select()\n top.generic_panel.select_dynamic()\n ui_support.init(app, top)\n app.mainloop()","def main():\n geom = dde.geometry.TimeDomain(0, 3)\n y0 = initial_condition()\n for i in range(0,C)\n # ic3 = dde.IC(geom, lambda X: 27, boundary, component=5)\n data = dde.data.PDE(\n geom,\n SLE_DL,\n [ic1, ic2, ic3, observe_y0, observe_y1, observe_y2],\n num_domain=400,\n num_boundary=2,\n anchors=observe_t,\n )","def debug_with_new(shell, workflow):\n projFilePath = \"/magnetic/test_project.ilp\"\n\n # New project\n shell.createAndLoadNewProject(projFilePath)\n\n # Add a file\n from ilastik.applets.dataSelection.opDataSelection import DatasetInfo\n info = DatasetInfo()\n #info.filePath = '/magnetic/gigacube.h5'\n info.filePath = '/magnetic/synapse_small.npy'\n #info.filePath = '/magnetic/singleslice.h5'\n opDataSelection = workflow.dataSelectionApplet.topLevelOperator\n opDataSelection.Dataset.resize(1)\n opDataSelection.Dataset[0].setValue(info)\n \n # Set some features\n import numpy\n featApplet = workflow.applets[2]\n featureGui = featApplet.gui\n opFeatures = featApplet.topLevelOperator\n # sigma: 0.3 0.7 1.0 1.6 3.5 5.0 10.0\n selections = numpy.array( [[True, False, False, False, False, False, False],\n [False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False], # ST EVs\n [False, False, False, False, False, False, False],\n [False, False, False, False, False, False, False], # GGM\n [False, False, False, False, False, False, False]] )\n opFeatures.SelectionMatrix.setValue(selections)\n opFeatures.Scales.setValue( featureGui.ScalesList )\n opFeatures.FeatureIds.setValue( featureGui.FeatureIds )\n\n # Select the labeling drawer\n shell.setSelectedAppletDrawer(3)\n\n # Save the project\n shell.onSaveProjectActionTriggered()","def edit_pane_test_open(event):\n c = event['c']\n\n if not hasattr(c, '__edit_pane_test'):\n c.__edit_pane_test = True\n\n\n class MinimalDemoProvider:\n\n def ns_provides(self):\n return [(\"Demo editor\", \"__demo_provider_minimal_slider\")]\n\n def ns_provide(self, id_):\n if id_ == \"__demo_provider_minimal_slider\":\n w = LeoEditPane(c=c, mode='split')\n return w\n return None\n\n def ns_provider_id(self):\n return \"__demo_provider_minimal\"\n\n c.free_layout.get_top_splitter().register_provider(MinimalDemoProvider())\n\n s = c.free_layout.get_top_splitter()\n s.open_window(\"__demo_provider_minimal_slider\")","def alldemos():\n rundemo(24,fig=True)\n rundemo(30,fig=True)\n rundemo(31,fig=True)\n rundemo(33)\n rundemo(34)","def main():\n prior = np.asarray([2.0, 4e-6, 1e-4])\n priorCov = np.diag(np.asarray([5.0, 1e-2, 1.0]))\n independentVariable = np.arange(0.0, 5.0e-5, 1e-7)\n \n truth = np.asarray([2.5, 1.2e-5, 4e-4])\n observation = (truth[0] * np.exp(-independentVariable/(truth[1])) + \n truth[2] + np.random.normal(0.0, 0.1, independentVariable.shape))\n observationError = (0.1 * np.sqrt(truth[0] * \n np.exp(-independentVariable/(truth[1]))) + math.sqrt(truth[2]))\n \n model = decay(prior=prior, priorCov=priorCov, \n otherModelParam=None, \n parameterNames=[\"a\", \"tau\", \"offset\"], \n verbose=2,\n observation=observation, \n observationError=observationError,\n independentVariable=independentVariable)\n \n oe = OE(model=model, maxiter=8)\n \n oe()\n \n# print(oe)\n# print(model)\n# \n# model.plot()\n \n return oe, model","def main():\n pycalcApp = QApplication(sys.argv)\n pycalcView = PyCalcUi()\n pycalcView.show()\n model = evaluateExpression\n PyCalcController(model=model, view=pycalcView)\n sys.exit(pycalcApp.exec())","def visualize_electrodes(self):\n ShowElectrodesDialog(parent=self)","def vis_d():\n \n data_gen = generator(fixed_noise)\n# loss = d_loss(discriminator(data_gen), discriminator(grid))\n loss = g_loss(discriminator(grid))\n loss.backward()\n \n grads = - grid.grad.data.numpy()\n grid.grad.data *= 0 \n plt.quiver(X_grid, Y_grid, grads[:, 0], grads[:, 1], color='black',alpha=0.9)","def main():\n configuration = ConfigParser()\n configuration.read_file(open('src/default.ini'))\n configuration.read(['config.ini'])\n push_exception_handler(reraise_exceptions=True)\n # Create the GUI (this does NOT start the GUI event loop).\n gui = GUI()\n\n # Create a Task and add it to a TaskWindow.\n task = S4LVisualizationTask(configuration=configuration)\n window = TaskWindow(size=(configuration.getint('Display', 'window_width'),\n configuration.getint('Display', 'window_height')))\n window.add_task(task)\n\n # Show the window.\n window.open()\n\n # Start the GUI event loop.\n gui.start_event_loop()","def show_derivative(self):\n for trace in self.plotWidget.plotDataItems:\n dt = float(trace.attrs['dt'])\n dtrace = np.diff(trace.data)\n x = pgplot.make_xvector(dtrace, dt)\n self.plotWidget.plot(x, dtrace, pen=pg.mkPen('r'))","def run_shell(options):\n from IPython import embed\n embed()","def view():\r\n # collect figures in list\r\n figures = list(map(plt.figure, plt.get_fignums()))\r\n # start app\r\n app = QtWidgets.QApplication(sys.argv)\r\n main = Main()\r\n\r\n if figures:\r\n for count, figure in enumerate(figures):\r\n # main names for figures\r\n name = f\"{figure.number}\"\r\n # aliases for figures\r\n titles = [figure.axes[0].get_title(loc=i) for i in [\r\n \"left\", \"center\", \"right\"]]\r\n titles = [i for i in titles if i]\r\n title = f\"{count+1}- {titles[0]}\" if titles else \"\"\r\n axes_labels = f\"{count+1}- {figure.axes[0].get_ylabel()} vs {figure.axes[0].get_xlabel()} \"\r\n fignum = f\"Figure {figure.number}\"\r\n # Append figure to App\r\n main.append_fig(title, axes_labels, fignum, name, figure)\r\n\r\n main.show()\r\n sys.exit(app.exec_())","def ex13gui():\n\n #pylint: disable=E1101\n root = tkcomponents.create('Simple interest')\n\n principal_label = rx.Observable.just('What is the principal amount?')\n principal = tkcomponents.input_stream(root, principal_label, 0).map(decimal.Decimal)\n\n rate_label = rx.Observable.just('What is the rate?')\n rate = tkcomponents.input_stream(root, rate_label, 1).map(decimal.Decimal)\n\n term_label = rx.Observable.just('What is the number of years?')\n term = tkcomponents.input_stream(root, term_label, 2).map(int).map(decimal.Decimal)\n\n frequency_label = rx.Observable.just(\n 'What is the number of times interest is compounded per year?')\n frequency = tkcomponents.input_stream(root, frequency_label, 3).map(int).map(decimal.Decimal)\n\n tkcomponents.output_label(\n root,\n rx.Observable.combine_latest(principal, rate, term, frequency, calculate_amount), 4)\n root.mainloop()","def __init__(self, parent):\n super(Demo5, self).__init__(parent)\n self.angle = 0.0\n self.replication = 1.0\n self.offset = 0.0\n self.deltaRep = 1\n self.revolution = 0\n self.stepsPer90 = 180\n self.stepsLeft = self.stepsPer90\n self.deltaAng = 90.0\n self.deltaOff = 0.15\n self.spin = True\n self.x2yAspect = 1.0\n self.texture = None","def iplot_paulivec(rho, options=None):\n\n # HTML\n html_template = Template(\"\"\"\n <p>\n <div id=\"paulivec_$divNumber\"></div>\n </p>\n \"\"\")\n\n # JavaScript\n javascript_template = Template(\"\"\"\n <script>\n requirejs.config({\n paths: {\n qVisualization: \"https://qvisualization.mybluemix.net/q-visualizations\"\n }\n });\n\n require([\"qVisualization\"], function(qVisualizations) {\n qVisualizations.plotState(\"paulivec_$divNumber\",\n \"paulivec\",\n $executions,\n $options);\n });\n </script>\n \"\"\")\n\n if not options:\n options = {}\n\n # Process data and execute\n div_number = str(time.time())\n div_number = re.sub('[.]', '', div_number)\n\n if 'slider' in options and options['slider'] is True:\n options['slider'] = 1\n else:\n options['slider'] = 0\n\n if 'show_legend' in options and options['show_legend'] is False:\n options['show_legend'] = 0\n else:\n options['show_legend'] = 1\n\n data_to_plot = []\n rho_data = process_data(rho)\n data_to_plot.append(dict(\n data=rho_data\n ))\n\n html = html_template.substitute({\n 'divNumber': div_number\n })\n\n javascript = javascript_template.substitute({\n 'divNumber': div_number,\n 'executions': data_to_plot,\n 'options': options\n })\n\n display(HTML(html + javascript))","def delta_vel(p1=database['K+'], p2=database['pi+'], p3=database['p+'], pmin=0, pmax=80):\r\n p_range = np.linspace(pmin, pmax, 1000)\r\n m1 = p1.mass\r\n m2 = p2.mass\r\n m3 = p3.mass\r\n dv2, dv3 = [], []\r\n for p in p_range:\r\n v1 = c*beta(p, m1)\r\n v2 = c*beta(p, m2)\r\n v3 = c*beta(p, m3)\r\n dv2.append(abs(v1-v2))\r\n dv3.append(abs(v1-v3))\r\n fig = plt.figure(figsize=[10, 5])\r\n ax = fig.add_subplot(1, 1, 1)\r\n# p1_name = r'K$^+$'\r\n# p2_name = r'$\\pi^+$'\r\n# p3_name = r'p$^+$'\r\n ax.plot(p_range, dv2, 'r', label=r'$\\left|v_{K^+}-v_{\\pi^+}\\right|$')\r\n ax.plot(p_range, dv3, 'b', label=r'$\\left|v_{K^+}-v_{p^+}\\right|$')\r\n ax.set_xlabel('p / GeV', fontsize=20)\r\n ax.set_ylabel(r'$\\left|\\Delta v\\right|$ / $ms^{-1}$', fontsize=20)\r\n ax.axvline(75, color='k', label='p = 75 GeV')\r\n ax.set_xticks(np.arange(pmin, pmax+1, 1))\r\n ax.set_xticklabels(np.arange(pmin, pmax+1, 1))\r\n ax.grid()\r\n ax.minorticks_on()\r\n ax.set_xlim(pmin, pmax)\r\n# ax.set_ylim(np.min(v1+v2))\r\n ax.legend(fontsize=20, loc=[0.65, 0.2])\r\n plt.show\r\n return","def Deboucle3D(*args):\n return _BRepAlgo.BRepAlgo_Tool_Deboucle3D(*args)","def create_figure_new(self):\n kw = {}\n self.p = figure(plot_height=400, plot_width=400, tools='pan,wheel_zoom,box_zoom,reset,hover', **kw)\n self.p.circle(x=[0],y=[0])","def editor_multi_agent_example():\n agent_definitions = [\n AgentDefinition(\"uav0\", agents.UavAgent, [sensors.RGBCamera, sensors.LocationSensor]),\n AgentDefinition(\"uav1\", agents.UavAgent, [sensors.LocationSensor, sensors.VelocitySensor])\n ]\n env = HolodeckEnvironment(agent_definitions, start_world=False)\n\n cmd0 = np.array([0, 0, -2, 10])\n cmd1 = np.array([0, 0, 5, 10])\n\n for i in range(10):\n env.reset()\n env.act(\"uav0\", cmd0)\n env.act(\"uav1\", cmd1)\n for _ in range(1000):\n states = env.tick()","def viewerSettings():\n node = nuke.thisNode()\n node.knob('near').setValue(100)\n node.knob('far').setValue(500000)\n node.knob('grid_display').setValue(False)\n node.knob('gl_lighting').setValue(1)","def debug():\n # \"EMBEDDED_MODE\" is True precisely when the Sage notebook is running.\n from sage.plot.plot import EMBEDDED_MODE\n if not EMBEDDED_MODE:\n # Must be the command line, so suggest using the IPython debugger.\n print(\"You should use %debug on the command line.\")\n else:\n # Create the Debug object and make it interactive.\n Debug().interact()","def actuator_environment(self):\n self.INPUT_DATA_SIZE = 23\n self.pushButton_reload.setEnabled(0)\n self.listWidget_link.setEnabled(0)\n self.listWidget_link.clear()","def show_derivativeCursor(self, var):\n if self.derivativeThreshold.isChecked(): \n self.plotWidget.derivativeCursorThsPos = 0\n self.plotWidget.derivativeCursorThs = pg.InfiniteLine(pos=self.plotWidget.derivativeCursorThsPos,\n angle=0, movable=True, pen=pg.mkPen('#FFD000', width=2))\n self.plotWidget.addItem(self.plotWidget.derivativeCursorThs)\n self.plotWidget.derivativeCursorThs.sigPositionChanged.connect(self.update_derivativeThreshold)\n else:\n self.plotWidget.derivativeCursorThsPos = []\n self.plotWidget.removeItem(self.plotWidget.derivativeCursorThs)","def modelEditor(*args, activeComponentsXray: bool=True, activeCustomEnvironment: AnyStr=\"\",\n activeCustomGeometry: Union[AnyStr, bool]=\"\", activeCustomLighSet: Union[AnyStr,\n bool]=\"\", activeCustomOverrideGeometry: Union[AnyStr, bool]=\"\",\n activeCustomRenderer: Union[AnyStr, bool]=\"\", activeOnly: bool=True,\n activeShadingGraph: Union[AnyStr, bool]=\"\", activeView: bool=True, addObjects:\n AnyStr=\"\", addSelected: bool=True, addSelectedObjects: bool=True, allObjects:\n bool=True, backfaceCulling: bool=True, bufferMode: Union[AnyStr, bool]=\"\",\n bumpResolution: Union[List[int, int], bool]=None, camera: Union[AnyStr,\n bool]=\"\", cameraName: AnyStr=\"\", cameraSet: Union[AnyStr, bool]=\"\",\n cameraSetup: bool=True, cameras: bool=True, capture: Union[AnyStr, bool]=\"\",\n captureSequenceNumber: Union[int, bool]=0, clipGhosts: bool=True, cmEnabled:\n bool=True, colorMap: bool=True, colorResolution: Union[List[int, int],\n bool]=None, control: bool=True, controlVertices: bool=True, cullingOverride:\n Union[AnyStr, bool]=\"\", default: bool=True, defineTemplate: AnyStr=\"\",\n deformers: bool=True, dimensions: bool=True, displayAppearance: Union[AnyStr,\n bool]=\"\", displayLights: Union[AnyStr, bool]=\"\", displayTextures: bool=True,\n docTag: Union[AnyStr, bool]=\"\", dynamicConstraints: bool=True, dynamics:\n bool=True, editorChanged: Union[Script, bool]=None, exists: bool=True,\n exposure: Union[float, bool]=0.0, filter: Union[AnyStr, bool]=\"\",\n filteredObjectList: bool=True, fluids: bool=True, fogColor: Union[List[float,\n float, float, float], bool]=None, fogDensity: Union[float, bool]=0.0, fogEnd:\n Union[float, bool]=0.0, fogMode: Union[AnyStr, bool]=\"\", fogSource:\n Union[AnyStr, bool]=\"\", fogStart: Union[float, bool]=0.0, fogging: bool=True,\n follicles: bool=True, forceMainConnection: Union[AnyStr, bool]=\"\", gamma:\n Union[float, bool]=0.0, greasePencils: bool=True, grid: bool=True, hairSystems:\n bool=True, handles: bool=True, headsUpDisplay: bool=True, height: bool=True,\n highlightConnection: Union[AnyStr, bool]=\"\", hulls: bool=True, ignorePanZoom:\n bool=True, ikHandles: bool=True, imagePlane: bool=True, interactive: bool=True,\n interactiveBackFaceCull: bool=True, interactiveDisableShadows: bool=True,\n isFiltered: bool=True, jointXray: bool=True, joints: bool=True, lights:\n bool=True, lineWidth: Union[float, bool]=0.0, locators: bool=True,\n lockMainConnection: bool=True, lowQualityLighting: bool=True,\n mainListConnection: Union[AnyStr, bool]=\"\", manipulators: bool=True,\n maxConstantTransparency: Union[float, bool]=0.0, maximumNumHardwareLights:\n bool=True, modelPanel: AnyStr=\"\", motionTrails: bool=True, nCloths: bool=True,\n nParticles: bool=True, nRigids: bool=True, noUndo: bool=True, nurbsCurves:\n bool=True, nurbsSurfaces: bool=True, objectFilter: Union[Script, bool]=None,\n objectFilterList: Union[Script, bool]=None, objectFilterListUI: Union[Script,\n bool]=None, objectFilterShowInHUD: bool=True, objectFilterUI: Union[Script,\n bool]=None, occlusionCulling: bool=True, panel: Union[AnyStr, bool]=\"\", parent:\n Union[AnyStr, bool]=\"\", particleInstancers: bool=True, pivots: bool=True,\n planes: bool=True, pluginObjects: Union[List[AnyStr, bool], List[List[AnyStr,\n bool]]]=None, pluginShapes: bool=True, polymeshes: bool=True,\n queryPluginObjects: Union[AnyStr, bool]=\"\", removeSelected: bool=True,\n rendererDeviceName: bool=True, rendererList: bool=True, rendererListUI:\n bool=True, rendererName: Union[AnyStr, bool]=\"\", rendererOverrideList:\n bool=True, rendererOverrideListUI: bool=True, rendererOverrideName:\n Union[AnyStr, bool]=\"\", resetCustomCamera: bool=True, sceneRenderFilter:\n Union[AnyStr, bool]=\"\", selectionConnection: Union[AnyStr, bool]=\"\",\n selectionHiliteDisplay: bool=True, setSelected: bool=True, shadingModel:\n Union[int, bool]=0, shadows: bool=True, smallObjectCulling: bool=True,\n smallObjectThreshold: Union[float, bool]=0.0, smoothWireframe: bool=True,\n sortTransparent: bool=True, stateString: bool=True, stereoDrawMode: bool=True,\n strokes: bool=True, subdivSurfaces: bool=True, textureAnisotropic: bool=True,\n textureCompression: bool=True, textureDisplay: Union[AnyStr, bool]=\"\",\n textureEnvironmentMap: bool=True, textureHilight: bool=True, textureMaxSize:\n Union[int, bool]=0, textureMemoryUsed: bool=True, textureSampling: Union[int,\n bool]=0, textures: bool=True, toggleExposure: bool=True, toggleGamma: bool=True,\n transpInShadows: bool=True, transparencyAlgorithm: Union[AnyStr, bool]=\"\",\n twoSidedLighting: bool=True, unParent: bool=True, unlockMainConnection:\n bool=True, updateColorMode: bool=True, updateMainConnection: bool=True,\n useBaseRenderer: bool=True, useColorIndex: bool=True, useDefaultMaterial:\n bool=True, useInteractiveMode: bool=True, useRGBImagePlane: bool=True,\n useReducedRenderer: bool=True, useTemplate: AnyStr=\"\", userNode: Union[AnyStr,\n bool]=\"\", viewObjects: bool=True, viewSelected: bool=True, viewTransformName:\n Union[AnyStr, bool]=\"\", viewType: bool=True, width: bool=True,\n wireframeBackingStore: bool=True, wireframeOnShaded: bool=True, xray: bool=True,\n q=True, query=True, e=True, edit=True, **kwargs)->Union[AnyStr, Any]:\n pass","def create_exercise(exam_date, num, path_ex_folder, path_yaml):\n global images_to_add\n global REL_PATH_IMAGES\n REL_PATH_IMAGES = 'img_' + exam_date\n images_to_add = []\n path_mode_free = path_ex_folder + '/modo_libero/' # new folder for the considered submission mode\n os.mkdir(path_mode_free)\n exer = read_exercise_yaml(path_yaml) # reading the given yaml\n notebook = nb.v4.new_notebook() # creating the new notebook\n #print(exer['name'])\n if exer['name'] in ('graphs_flow','graphs_trees', 'graphs_planarity','graphs_paths'):\n insert_graph_import(notebook) #required graph import\n insert_no_scroll(notebook) #no scroll of output div\n else:\t\n insert_import_mode_free(notebook) # required import\n insert_start_button(notebook) # start button to run cells with tag 'run_start'\n insert_hide_code(notebook) # hide all code cells\n insert_user_bar_lib(notebook,path_ex_folder) # insert user_bar.py in a code cell\n insert_heading(notebook, exer['title']) # heading with title\n insert_description1(notebook, exer['description1'], exam_date, path_ex_folder) # description 1\n if 'description2' in exer:\n insert_description2(notebook, exer['description2']) # description 2\n insert_tasks(notebook, exer['tasks']) # inserting the several tasks\n if exer['name'] in ('lp_duality', 'lp_interactive', 'lp_modelling', 'lp_two_phases'): # other libraries needed for some types of exercises\n insert_needed_import(notebook, exer['name'])\n if int(num) >= 10: # writing the notebook and saving it in the correct folder\n note_name = 'Esercizio_' + num + '.ipynb'\n prev_folder = 'esercizio_' + num\n else:\n note_name = 'Esercizio_0' + num + '.ipynb'\n prev_folder = 'esercizio_0' + num\n insert_rendition(notebook, note_name)\n nb.write(notebook, note_name)\n os.rename(os.getcwd()+ '/' + note_name, path_mode_free + '/' + note_name)\n os.system(\"jupyter trust \" + path_mode_free + note_name) # signing the notebook in order to make it trusted\n insert_suppl_folders(path_mode_free) # inserting the supplementary folders (i.e., 'allegati', 'img')\n if exer['name'] in ('graphs_flow','graphs_trees', 'graphs_planarity','graphs_paths'):\n insert_graph_folder(path_mode_free)\n if 'tags' in exer:\n e_dict = {'title':exer['title'],'tags':exer['tags'],'tot_points':0,'link':'http://127.0.0.1:8888/notebooks/'+prev_folder+'/modo_libero/' + note_name, 'tasks':exer['tasks']}\n else:\n\t e_dict = {'title':exer['title'],'tags':[],'tot_points':0,'link':'http://127.0.0.1:8888/notebooks/'+prev_folder+'/modo_libero/' + note_name, 'tasks':exer['tasks']}\n return e_dict","def plots():\n out = interactive_output(generate_plots, {'gsize':gridSlider, 'ra':RABox, 'ra':RASlider, 'dec':DECBox, 'dec':DECSlider, 'ang':radBox, 'ang':radSlider, 'style':hexDrop})\n return display(widgrid, out)","def run_interactive():\n from cherrypy import engine\n \n # This is what quickstart does but we don't block\n engine.signals.subscribe()\n engine.start()\n #engine.block()","def deactivate(self, newmode = None):\n\t\tself.urmaswin.Show(0) \n\t\tself.urmaswin.enableRendering(0) \n\t\tself.urmaswin.controlpanel.Show(0)\n\t\tself.visualizer.sliderWin.SetDefaultSize(self.origSliderWinSize)\n\n\t\tif not self.doLockSliderPanel and newmode != \"3d\":\n\t\t\tprint \"\\n\\n*** DEACTIVATING ANIMATOR\\n\"\n\t\t\tself.visualizer.setCurrentSliderPanel(self.visualizer.sliderPanel) \n\t\t\tself.visualizer.sliderPanel.Show(1)\n\t\tif newmode != \"3d\":\n\t\t\tself.menuManager.mainToolbar.EnableTool(MenuManager.ID_ADJUST, 1)\n\t\t\tself.menuManager.mainToolbar.EnableTool(MenuManager.ID_RESTORE, 1)\n\t\t\tself.menuManager.mainToolbar.EnableTool(MenuManager.ID_COLOCALIZATION, 1)\n\t\t\tself.menuManager.mainToolbar.EnableTool(MenuManager.ID_COLORMERGING, 1)\n\t\tself.urmaswin.cleanMenu()","def notebook():\n pass","def notebook():\n pass","def agentbasedsim_evol(aenv, pienv, xi,\n L=1, nind=10, ngens=[100],\n mutrate=1e-4, mutsize=0.025,\n ainit=None, piinit=None, pupinit=None, epsiloninit=None,\n evolvep=True,\n evolveq=True,\n evolvepup=False,\n evolveepsilon=False,\n prng=None):\n\n prng = prng if prng else np.random\n\n mutrateisnumber = isinstance(mutrate, numbers.Number) \n mutsizeisnumber = isinstance(mutsize, numbers.Number) \n \n alpha, beta = from_api(aenv, pienv)\n\n # all parameters need to be in array form if cython acceleration is used\n if usecstepmarkov:\n alpha = _arrayify(alpha, L)\n beta = _arrayify(beta, L)\n\n # p,q can now change dynamically.\n if (ainit is not None) and (piinit is not None) and (pupinit is not None) and (epsiloninit is not None):\n # Initialize all to the same value\n pinit, qinit = from_api(ainit, piinit)\n p = np.clip(np.ones((nind, L)) * pinit, 0, 1)\n q = np.clip(np.ones((nind, L)) * qinit, 0, 1)\n pup = np.clip(np.ones((nind, L)) * pupinit, 0, 1)\n epsilon = np.clip(np.ones(nind) * epsiloninit, 0, 1)\n else:\n # Initialize uniformly\n p = prng.random((nind, L))\n q = prng.random((nind, L))\n pup = prng.random((nind, L))\n epsilon = prng.random(nind)\n \n # Initialize all to the same value, then add randomness\n #p = np.clip(np.ones((nind, L)) * pinit + np.random.normal(scale = mutsizeinit, size = (nind, L)), 0, 1)\n #q = np.clip(np.ones((nind, L)) * qinit + np.random.normal(scale = mutsizeinit, size = (nind, L)), 0, 1)\n # Initialize uniformly in a, pi\n #p, q = from_api(prng.random((nind, L)), prng.random((nind, L)))\n\n env = np.zeros(L, dtype = bool)\n ind = np.zeros((nind, L), dtype = bool)\n\n totoffsprings = np.zeros(max(ngens))\n as_ = np.zeros((len(ngens), L))\n pis = np.zeros((len(ngens), L))\n pups = np.zeros((len(ngens), L))\n epsilons = np.zeros(len(ngens))\n\n # number of generations at which to output\n ngencounter = 0\n # for performance: avoid array look up at each step\n ngennext = ngens[0]-1\n\n # for performance: precomputations\n # (checked if actually saving significant amounts of time)\n nind_arange = np.arange(nind)\n if mutrateisnumber:\n totmutrate = mutrate * L * nind\n # if mutsize is constant then assign it for all generations\n if mutsizeisnumber:\n mutsize_gen = mutsize\n\n for generation in range(max(ngens)):\n # time step environment\n rand = prng.rand(L)\n env = stepmarkov(env, alpha, beta, rand)\n # acquire via crispr\n rand = prng.rand(nind, L)\n ind, nacquired = stepcrispr(env, ind, pup, rand)\n # calculate growth rate\n noffspring = xi(ind, env, epsilon, pup)\n\n # for performance: use np.add.reduce directly to avoid np.sum overhead\n #totoffspring = noffspring.sum()\n totoffspring = np.add.reduce(noffspring)\n # time step population\n indoffspring = nind_arange.repeat(prng.multinomial(nind, noffspring/totoffspring))\n parent = ind.take(indoffspring, axis=0)\n rand = prng.rand(nind, L)\n ind = stepmarkov2d(parent, p, q, rand)\n # inherit strategies\n p = p.take(indoffspring, axis=0)\n q = q.take(indoffspring, axis=0)\n pup = pup.take(indoffspring, axis=0)\n epsilon = epsilon.take(indoffspring, axis=0)\n # mutate strategies\n if not mutrateisnumber:\n totmutrate = mutrate(generation) * L * nind\n if not mutsizeisnumber:\n mutsize_gen = mutsize(generation)\n for c in range(prng.poisson(totmutrate)):\n # pick random site \n i, j = prng.randint(nind), prng.randint(L)\n if evolvep:\n ptmp = p[i, j] + prng.normal(scale=mutsize_gen)\n # ensure that there is at least some switching\n # needed for sensible definition of pi\n while (ptmp <= 0.0) or (ptmp > 1):\n ptmp = p[i, j] + prng.normal(scale=mutsize_gen)\n p[i, j] = ptmp\n if evolveq:\n qtmp = q[i, j] + prng.normal(scale=mutsize_gen)\n while (qtmp <= 0.0) or (qtmp > 1):\n qtmp = q[i, j] + prng.normal(scale=mutsize_gen)\n q[i, j] = qtmp\n if evolvepup:\n puptmp = pup[i, j] + prng.normal(scale=mutsize_gen)\n while (puptmp <= 0.0) or (puptmp > 1):\n puptmp = pup[i, j] + prng.normal(scale=mutsize_gen)\n pup[i, j] = puptmp \n if evolveepsilon:\n epsilontmp = epsilon[i] + prng.normal(scale=mutsize_gen)\n while (epsilontmp <= 0.0) or (epsilontmp > 1):\n epsilontmp = epsilon[i] + prng.normal(scale=mutsize_gen)\n epsilon[i] = epsilontmp \n\n \n # store data\n totoffsprings[generation] = totoffspring\n if generation == ngennext:\n a, pi = to_api(p, q)\n as_[ngencounter] = a.mean(axis=0)\n pis[ngencounter] = pi.mean(axis=0)\n if evolvepup:\n pups[ngencounter] = pup.mean(axis=0)\n if evolveepsilon:\n epsilons[ngencounter] = epsilon.mean(axis=0)\n ngencounter += 1\n if ngencounter >= len(ngens):\n break\n ngennext = ngens[ngencounter]-1\n\n return totoffsprings / nind, pis, as_, pups, epsilons","def editor():\n pass","def plot_vanHove_dt(comp,conn,start,step_size,steps):\n \n (fin,) = conn.execute(\"select fout from comps where comp_key = ?\",comp).fetchone()\n (max_step,) = conn.execute(\"select max_step from vanHove_prams where comp_key = ?\",comp).fetchone()\n Fin = h5py.File(fin,'r')\n g = Fin[fd('vanHove',comp[0])]\n\n temp = g.attrs['temperature']\n dtime = g.attrs['dtime']\n\n\n # istatus = plots.non_i_plot_start()\n \n fig = mplt.figure()\n fig.suptitle(r'van Hove dist temp: %.2f dtime: %d'% (temp,dtime))\n dims = figure_out_grid(steps)\n \n plt_count = 1\n outs = []\n tmps = []\n for j in range(start,start+step_size*steps, step_size):\n (edges,count,x_lim) = _extract_vanHove(g,j+1,1,5)\n if len(count) < 50:\n plt_count += 1\n continue\n #count = count/np.sum(count)\n \n sp_arg = dims +(plt_count,)\n ax = fig.add_subplot(*sp_arg)\n ax.grid(True)\n\n \n alpha = _alpha2(edges,count)\n \n ax.set_ylabel(r'$\\log{P(N)}$')\n ax.step(edges,np.log((count/np.sum(count))),lw=2)\n ax.set_title(r'$\\alpha_2 = %.2f$'%alpha + ' j:%d '%j )\n ax.set_xlim(x_lim)\n plt_count += 1\n\n mplt.draw()\n\n # plots.non_i_plot_start(istatus)\n\n del g\n Fin.close()\n del Fin","def main():\n # Create our array of x values\n x = np.linspace(-np.pi, np.pi)\n\n # plot x and sin(x)\n plt.plot(x, np.sin(x))\n\n # plot x and cos(x)\n plt.plot(x, np.cos(x))\n\n #Add title and labels\n plt.title(\"Graph of Sine and Cosine\")\n plt.xlabel(\"Radians\")\n\n # Show graph in matplotlib gui\n plt.show()","def storefront_dimension():\n\n\tfrom rpw.ui.forms import Label, ComboBox, Separator, Button, FlexForm\n\n\tcurrentView = uidoc.ActiveView\n\ttheta = math.pi*0.5\n\taxis_z = Autodesk.Revit.DB.Line.CreateBound(XYZ(0,0,0),XYZ(0,0,1))\n\tsearchDist = 4\n\toffsetDim = 1\n\n\t#Get the linear dimension types in the doc to select from\n\tallDimensionTypes = GetAllElements(doc, None, Autodesk.Revit.DB.DimensionType)\n\tlinearDimensionTypes = {}\n\n\tautodimOptions = {\"Laser Layout\": \"Laser Layout\", \"Partition Plan\" : \"Partition Plan\"}\n\n\tfor elemId in allDimensionTypes:\n\t\tdT = doc.GetElement(elemId)\n\t\tif \"Linear\" in dT.FamilyName:\n\t\t\tdTName = dT.get_Parameter(BuiltInParameter.ALL_MODEL_TYPE_NAME).AsString()\n\t\t\tlinearDimensionTypes[dTName] = dT\n\n\n\t#Select dimension settings\n\tcomponents = [Label('Dimension Distance From Datums'),\n\t\t\t\t\tComboBox(\"combobox1\", {\"4'-0''\": 4.0, \"8'-0''\": 8.0}),\n\t\t\t\t\tLabel('Dimension Type'),\n\t\t\t\t\tComboBox(\"combobox2\", linearDimensionTypes),\n\t\t\t\t\tLabel('Dimension Function'),\n\t\t\t\t\tComboBox(\"combobox3\", autodimOptions),\n\t\t\t\t\tLabel('System'),\n\t\t\t\t\tComboBox(\"combobox4\", {\"Elite\": \"Elite\", \"MODE\": \"MODE\", \"Extravega\": \"Extravega\"}),\n\t\t\t\t\tSeparator(),\n\t\t\t\t\tButton('Go')]\n\n\tform = FlexForm(\"Storefront Auto Dim\", components)\n\tform.show()\n\n\tif not form.values:\n\t\tsys.exit()\n\telse: \n\t\tsearchDist = form.values[\"combobox1\"]\n\t\tselectedDimType = form.values[\"combobox2\"]\n\t\tautodimOption = form.values[\"combobox3\"]\n\t\tsystemName = form.values[\"combobox4\"]\n\n\tif autodimOption == \"Laser Layout\":\n\n\t\t#Get walls for datum lines to measure to\n\t\tallWalls = GetAllElements(doc, BuiltInCategory.OST_Walls, Autodesk.Revit.DB.Wall, currentView=True)\n\t\t#storefrontWalls = FilterElementsByName(doc, allWalls, [\"Storefront\",\"Storefront\"], False)\n\n\t\twith rpw.db.Transaction(\"Auto Dim Lines\"):\n\t\t\t# Gather all the lines to filter and delete the ones we dont want.\n\t\t\tallLines = list(GetElementsInView(BuiltInCategory.OST_Lines, Autodesk.Revit.DB.CurveElement, currentView.Id))\n\n\t\t\tfor lineId1 in allLines:\n\t\t\t\tline1 = doc.GetElement(lineId1)\n\t\t\t\tlineName = line1.LineStyle.Name\n\t\t\t\t\n\t\t\t\tif (\"Full\" in lineName or \"Partial\" in lineName) and line1.GeometryCurve.IsBound:\n\t\t\t\t\trefArray = ReferenceArray()\n\t\t\t\t\tlineReference =line1.GeometryCurve\n\n\t\t\t\t\tline1StartPoint = lineReference.GetEndPoint(0)\n\t\t\t\t\tline1EndPoint = lineReference.GetEndPoint(1)\n\n\t\t\t\t\tx1 = line1EndPoint.X - line1StartPoint.X\n\t\t\t\t\ty1 = line1EndPoint.Y - line1StartPoint.Y\n\n\t\t\t\t\tvect1Norm = XYZ(y1 * -1, x1, 0).Normalize()\n\t\t\t\t\tvect1 = vect1Norm.Multiply(offsetDim)\n\n\t\t\t\t\tpoint1 = line1StartPoint.Add(vect1)\n\t\t\t\t\tpoint2 = line1EndPoint.Add(vect1)\n\n\t\t\t\t\tdimLine = Autodesk.Revit.DB.Line.CreateBound(point1, point2)\n\n\t\t\t\t\trefArray.Append(lineReference.GetEndPointReference(0)) \n\t\t\t\t\trefArray.Append(lineReference.GetEndPointReference(1))\n\t\t\t\t\tnewDim = doc.Create.NewDimension(currentView, dimLine, refArray)\n\t\t\t\t\tnewDim.DimensionType = selectedDimType\n\t\t\t\t\n\t\t\t\t\n\t\t\t\telif \"control\" in lineName.lower() and line1.GeometryCurve.IsBound:\n\n\t\t\t\t\tfor wallId in allWalls:\n\t\t\t\t\t\twall = doc.GetElement(wallId)\n\t\t\t\t\t\tif \"Basic\" in str(wall.WallType.Kind):\n\t\t\t\t\t\t\tline2 = wall.Location.Curve\n\n\t\t\t\t\t\t\t#Crazy way to get the wall centerline as a Reference object\n\t\t\t\t\t\t\tunique = wall.UniqueId\n\t\t\t\t\t\t\trefString = System.String.Format(\"{0}:{1}:{2}\",unique,-9999,1)\n\t\t\t\t\t\t\twall_centre = Reference.ParseFromStableRepresentation(doc,refString)\n\n\t\t\t\t\t\t\tline2StartPoint = line2.Evaluate(0, True)\n\t\t\t\t\t\t\tline2Midpoint = line2.Evaluate(0.5, True)\n\n\t\t\t\t\t\t\tx1 = line2Midpoint.X - line2StartPoint.X\n\t\t\t\t\t\t\ty1 = line2Midpoint.Y - line2StartPoint.Y\n\t\t\t\t\t\t\tz1 = line2Midpoint.Z\n\n\t\t\t\t\t\t\tvect1Norm = XYZ(x1,y1,0).Normalize()\n\t\t\t\t\t\t\tvect1 = vect1Norm.Multiply(searchDist)\n\n\t\t\t\t\t\t\t#Create the vectors\n\t\t\t\t\t\t\tvect2 = XYZ(vect1.Y * -1, vect1.X, vect1.Z)\n\t\t\t\t\t\t\tvect3 = XYZ(vect1.Y, vect1.X * -1, vect1.Z)\n\n\t\t\t\t\t\t\t#Add them to the midpoints\n\t\t\t\t\t\t\tpoint1 = line2Midpoint.Add(vect2)\n\t\t\t\t\t\t\tpoint2 = line2Midpoint.Add(vect3)\n\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t#Create the line that will be used to test intersections with datum lines\n\t\t\t\t\t\t\ttestLine = Autodesk.Revit.DB.Line.CreateBound(point1, point2)\n\t\t\t\t\t\t\t \n\t\t\t\t\t\t\t#Create the datum line at the same z level as the test intersection lines\n\t\t\t\t\t\t\tline1GC = line1.GeometryCurve\n\t\t\t\t\t\t\tdatumPoint1 = line1GC.GetEndPoint(0)\n\t\t\t\t\t\t\tdatumPoint2 = line1GC.GetEndPoint(1)\n\n\t\t\t\t\t\t\tdatumPoint1 = XYZ(datumPoint1.X, datumPoint1.Y, line2Midpoint.Z)\n\t\t\t\t\t\t\tdatumPoint2 = XYZ(datumPoint2.X, datumPoint2.Y, line2Midpoint.Z)\n\n\t\t\t\t\t\t\tflattenedDatumLine = Autodesk.Revit.DB.Line.CreateBound(datumPoint1, datumPoint2)\n\n\t\t\t\t\t\t\tintersection = RevitCurveCurveIntersection(flattenedDatumLine, testLine)\n\n\t\t\t\t\t\t\tif intersection:\n\n\t\t\t\t\t\t\t\t#Adjust the position parameter based on distance away\n\t\t\t\t\t\t\t\t#from the datum line so they are easier to read\n\n\t\t\t\t\t\t\t\tposFactor = (line2Midpoint.DistanceTo(intersection)/searchDist) * (line2StartPoint.DistanceTo(line2Midpoint)/2)\n\t\t\t\t\t\t\t\tadjustVect = vect1Norm.Multiply(posFactor)\n\n\t\t\t\t\t\t\t\tp1 = line2Midpoint.Add(adjustVect)\n\t\t\t\t\t\t\t\tp2 = intersection.Add(adjustVect)\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tif p1.DistanceTo(p2) > app.ShortCurveTolerance:\n\t\t\t\t\t\t\t\t\tdimLine = Autodesk.Revit.DB.Line.CreateBound(p1, p2)\n\t\t\t\t\t\t\t\t\trefArray = ReferenceArray()\n\t\t\t\t\t\t\t\t\t#lineReference =line1.GeometryCurve\n\t\t\t\t\t\t\t\t\trefArray.Append(line1.GeometryCurve.Reference)\n\t\t\t\t\t\t\t\t\trefArray.Append(wall_centre)\n\t\t\t\t\t\t\t\t\tnewDim = doc.Create.NewDimension(currentView, dimLine, refArray)\n\t\t\t\t\t\t\t\t\tnewDim.DimensionType = selectedDimType\n\n\telif autodimOption == \"Partition Plan\":\n\n\t\t\"\"\"\n\t\tCreates sill dimensions for partition install plans\n\t\t\"\"\" \n\n\t\tallStorefrontWalls = rpw.db.Collector(of_class='Wall', \n\t\t\t\t\t\t\t\t\t\t\tview=currentView, \n\t\t\t\t\t\t\t\t\t\t\twhere=lambda x: (str(x.WallType.Kind) == \"Curtain\") and (systemName.lower() in x.Name.lower()))\n\n\t\tallStorefrontPanels = []\n\t\tallStorefrontMullions = []\n\n\t\t#Collect mullions\n\t\tfor sfwall in allStorefrontWalls:\n\t\t\tfor sfMullionsId in sfwall.CurtainGrid.GetMullionIds():\n\t\t\t\tallStorefrontMullions.append(doc.GetElement(sfMullionsId))\n\n\t\twith rpw.db.Transaction(\"Auto Dim Sills\"):\n\n\t\t\tfor sfMullion in allStorefrontMullions:\n\t\t\t\t\n\t\t\t\tif \"sill\" in sfMullion.Name.lower() and sfMullion.LocationCurve:\n\n\t\t\t\t\tmullionDirection = sfMullion.LocationCurve.Direction\n\n\t\t\t\t\trefArray = ReferenceArray()\n\t\t\t\t\tedgeCurve = None\n\n\t\t\t\t\toptions = app.Create.NewGeometryOptions()\n\t\t\t\t\toptions.IncludeNonVisibleObjects = True\n\t\t\t\t\toptions.ComputeReferences = True\n\n\t\t\t\t\tfaces = []\n\t\t\t\t\tperpFace = None\n\n\t\t\t\t\tmullionGeo = sfMullion.get_Geometry(options)\n\n\t\t\t\t\tfor item in list(mullionGeo):\n\t\t\t\t\t\tgeometry = list(item.GetInstanceGeometry())\n\t\t\t\t\t\tfor geo in geometry:\n\t\t\t\t\t\t\tif type(geo) == Autodesk.Revit.DB.Solid:\n\t\t\t\t\t\t\t\tif list(geo.Faces.GetEnumerator()):\n\t\t\t\t\t\t\t\t\tfaces = list(geo.Faces.GetEnumerator()) \n\t\t\t\t\t\tif faces:\n\t\t\t\t\t\t\tbreak\n\n\t\t\t\t\tfor face in faces:\n\n\t\t\t\t\t\tfaceDirection = face.FaceNormal\n\n\n\t\t\t\t\t\tif abs(90-((faceDirection.AngleTo(mullionDirection)*360)/ (2*math.pi))) < 0.01 and faceDirection.Z == 1 :\n\t\t\t\t\t\t\t#print \"found face\"\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tedgeloops = list(face.EdgeLoops)[0]\n\t\t\t\t\t\t\tedgesFound = 0\n\n\t\t\t\t\t\t\tfor edge in edgeloops:\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t#if abs(edge.AsCurve().Direction.Z) == 1:\n\t\t\t\t\t\t\t\tif abs(180-((edge.AsCurve().Direction.AngleTo(mullionDirection)*360)/ (2*math.pi))) < 0.01:\n\n\t\t\t\t\t\t\t\t\tedgeCurve = Autodesk.Revit.DB.Line.CreateBound(edge.AsCurve().GetEndPoint(0), edge.AsCurve().GetEndPoint(1))\n\n\t\t\t\t\t\t\t\t\tedgesFound += 1\n\t\t\t\t\t\t\t\t\tbreak\n\t\t\t\t\t\t\tbreak\n\n\t\t\t\t\tif edgesFound >= 1:\n\t\t\t\t\t\n\t\t\t\t\t\tline1 = sfMullion.LocationCurve\n\n\t\t\t\t\t\tline1StartPoint = line1.GetEndPoint(0)\n\t\t\t\t\t\tline1EndPoint = line1.GetEndPoint(1)\n\n\t\t\t\t\t\tx1 = line1EndPoint.X - line1StartPoint.X\n\t\t\t\t\t\ty1 = line1EndPoint.Y - line1StartPoint.Y\n\n\t\t\t\t\t\tvect1Norm = XYZ(y1 * -1, x1, 0).Normalize()\n\t\t\t\t\t\tvect1 = vect1Norm.Multiply(offsetDim)\n\n\t\t\t\t\t\tpoint1 = line1StartPoint.Add(vect1)\n\t\t\t\t\t\tpoint2 = line1EndPoint.Add(vect1)\n\n\t\t\t\t\t\tdimLine = Autodesk.Revit.DB.Line.CreateBound(point1, point2)\n\n\t\t\t\t\t\tif edgeCurve:\n\t\t\t\t\t\t\tdummyDetail = doc.Create.NewDetailCurve(currentView, edgeCurve)\n\n\t\t\t\t\t\t\trefArray.Append(dummyDetail.GeometryCurve.GetEndPointReference(0)) \n\t\t\t\t\t\t\trefArray.Append(dummyDetail.GeometryCurve.GetEndPointReference(1))\n\n\t\t\t\t\t\t\tnewDim = doc.Create.NewDimension(currentView, dimLine, refArray)\n\t\t\t\t\t\t\tnewDim.DimensionType = selectedDimType","def front_wheel_from_axis():","def den_evolve(self, delt, txp, src):\n self.ne += (-txp.dfluxe + src.se)*delt\n self.ni += (-txp.dfluxi + src.si)*delt","def slider_dragged(self):\n pass","def jupyter():","def __init__(self, parent=None):\n QtGui.QWidget.__init__(self, parent)\n \n self.setWindowTitle('The Visual Climate Data Analysis Tools - (VCDAT)')\n layout = QtGui.QVBoxLayout()\n self.setLayout(layout)\n\n # Init Menu Widget\n self.menuWidget = QMenuWidget(self)\n\n # Init File Widget\n vsplitter = QtGui.QSplitter(QtCore.Qt.Vertical) \n fileWidget = QLabeledWidgetContainer(QCDATFileWidget(),\n 'FILE VARIABLES')\n vsplitter.addWidget(fileWidget)\n\n # Init Defined Variables Widget\n definedVar = QLabeledWidgetContainer(QDefinedVariable(),\n 'DEFINED VARIABLES')\n vsplitter.addWidget(definedVar)\n hsplitter = QtGui.QSplitter(QtCore.Qt.Horizontal)\n hsplitter.addWidget(vsplitter)\n\n # Init Var Plotting Widget\n varView = QLabeledWidgetContainer(QVariableView(),\n 'PLOTTING')\n hsplitter.addWidget(varView)\n hsplitter.setStretchFactor(1, 1)\n layout.addWidget(hsplitter)\n\n # Init guiController\n guiController = GuiController(fileWidget.getWidget(),\n definedVar.getWidget(),\n varView.getWidget())\n guiController.initTeachingCommands()\n self.guiController = guiController # So guicontroller doesn't get garbage collected\n\n # Connect signals between self & GuiController\n self.connect(self, QtCore.SIGNAL('setRecordCommands'),\n guiController.setRecordCommands)\n self.connect(self, QtCore.SIGNAL('viewTeachingCommands'),\n guiController.viewTeachingCommands)\n self.connect(self, QtCore.SIGNAL('closeTeachingCommands'),\n guiController.closeTeachingCommands) \n\n # Connect Signals between QVariableView & QDefinedVariable\n varView.connect(definedVar.getWidget(), QtCore.SIGNAL('selectDefinedVariableEvent'),\n varView.getWidget().selectDefinedVariableEvent)\n varView.connect(definedVar.getWidget(), QtCore.SIGNAL('setupDefinedVariableAxes'),\n varView.getWidget().setupDefinedVariableAxes)\n definedVar.connect(varView.getWidget(), QtCore.SIGNAL('plotPressed'),\n definedVar.getWidget().defineQuickplot)\n definedVar.connect(varView.getWidget(), QtCore.SIGNAL('defineVariable'),\n definedVar.getWidget().defineVariable)\n\n # Connect Signals between QFileWidget & QVariableView\n varView.connect(fileWidget.getWidget(), QtCore.SIGNAL('variableChanged'),\n varView.getWidget().setupDefinedVariableAxes)\n varView.connect(fileWidget.getWidget(), QtCore.SIGNAL('defineVariableEvent'),\n varView.getWidget().defineVariableEvent)","def flopViewer():\n allV = nuke.allNodes('Viewer')\n pV = allV[0]\n List = nuke.selectedNodes()\n nuke.selectAll()\n nuke.invertSelection()\n try:\n n = nuke.toNode('VIEWER_INPUT')\n if n.Class() == 'Mirror':\n n['Vertical'].setValue(not n['Vertical'].value())\n for i in allV:\n i['input_process'].setValue(not n['Vertical'].value() + n['Horizontal'].value() == 0)\n if n['Vertical'].value() + n['Horizontal'].value() == 0:\n nuke.delete(n)\n nuke.selectAll()\n nuke.invertSelection()\n else:\n nuke.message(\"Another Viewer Input already exists.\\nAborting to avoid conflict\")\n \n except:\n n = nuke.Node('Mirror',inpanel=False)\n n['xpos'].setValue(pV.xpos()+150)\n n['ypos'].setValue(pV.ypos())\n n['name'].setValue('VIEWER_INPUT')\n n['hide_input'].setValue(1)\n n['Vertical'].setValue(not n['Vertical'].value())\n nuke.selectAll()\n nuke.invertSelection()\n for i in List:\n i['selected'].setValue(True)\n for i in List:\n i['selected'].setValue(True)","def ion():\n plt.ion()","def generate_widgets(self):\n\n self.plot_canvas()\n\n # Select which m component to plot ------------------------------------\n\n mcomp_dropdown = ipw.Dropdown(options=['x', 'y', 'z', 'hls'],\n # description=r'$\\text{Plot}\\,\\,m_{i}$',\n value='z'\n )\n mcomp_dropdown.observe(lambda b: self.static_plot_component_colorbar(\n m_component=mcomp_dropdown.value))\n mcomp_dropdown_text = ipw.Label(r'$\\text{Plot}\\,\\,m_{i}$')\n mcomp_dropdown_text.width = '100px'\n\n mcomp_box = ipw.HBox(children=[mcomp_dropdown_text, mcomp_dropdown])\n\n # Button to start relaxation ------------------------------------------\n\n # We use two boxes with the maximum time and the number of steps\n run_box = ipw.FloatText()\n run_box_2 = ipw.FloatText()\n # Default values for the boxes\n run_box.value = 10\n run_box_2.value = 100\n # Change left and right margins\n run_box.layout.margin = '0px 50px'\n run_box.layout.width = '100px'\n run_box_2.layout.margin = '0px 50px'\n run_box_2.layout.width = '100px'\n\n # The button to start the relaxation of the system, using the values in\n # the boxes\n run_button = ipw.Button(description='Run sim!')\n run_button.layout.margin = '0px 50px'\n # The action requires a variable for the button (?). We just\n # impose it in a lambda function\n run_button.on_click(lambda b: self.relax(b,\n max_time=run_box.value * 1e-9,\n time_steps=run_box_2.value,\n m_component=mcomp_dropdown.value\n )\n )\n # run_button.margin = '0px 20px'\n run_button.layout.background_color = '#9c0909'\n run_button.color = 'white'\n\n run_box_text = ipw.Label(r'$\\text{Time [ns]}$')\n run_box_text.width = '50px'\n run_box_2_text = ipw.Label(r'$\\text{Steps}$')\n run_box_2_text.width = '50px'\n\n # Align everything in a horizontal box\n run_container = ipw.HBox(children=[run_box_text, run_box,\n run_box_2_text, run_box_2,\n run_button]\n )\n\n # Boxes to update the Zeeman field ------------------------------------\n\n zeeman_box_texts = [ipw.Label(r'$B_x\\,\\,\\text{[T]}$'),\n ipw.Label(r'$B_y\\,\\,\\text{[T]}$'),\n ipw.Label(r'$B_z\\,\\,\\text{[T]}$')\n ]\n for text in zeeman_box_texts:\n text.width = '50px'\n\n zeeman_box_x = ipw.FloatText()\n zeeman_box_y = ipw.FloatText()\n zeeman_box_z = ipw.FloatText()\n\n # Show the default value in the box\n zeeman_box_x.value = self.B[0]\n zeeman_box_x.layout.width = '50px'\n zeeman_box_x.layout.margin = '0px 50px'\n zeeman_box_y.value = self.B[1]\n zeeman_box_y.layout.width = '50px'\n zeeman_box_y.layout.margin = '0px 50px'\n zeeman_box_z.value = self.B[2]\n zeeman_box_z.layout.width = '50px'\n zeeman_box_z.layout.margin = '0px 50px'\n\n # Update the simulation using a button\n zeeman_button = ipw.Button(description='Update field')\n zeeman_button.on_click(\n lambda button: self.update_Zeeman_field((zeeman_box_x.value,\n zeeman_box_y.value,\n zeeman_box_z.value,\n )\n )\n )\n\n # Draw the default Field in the plot title\n self.title_text.set_text('Field: {} T'.format(\n self.sim.get_interaction('Zeeman').B0))\n self.fig.canvas.draw()\n\n zeeman_container = ipw.HBox(children=[zeeman_box_texts[0],\n zeeman_box_x,\n zeeman_box_texts[1],\n zeeman_box_y,\n zeeman_box_texts[2],\n zeeman_box_z,\n zeeman_button\n ]\n )\n\n # DMI magnitude box ---------------------------------------------------\n\n DMI_box_text = ipw.Label(r'$\\text{DMI [meV]}$')\n DMI_box_text.width = '50px'\n\n DMI_box = ipw.FloatText()\n\n # Show the default value in the box\n DMI_box.value = round(self.D / const.meV, 2)\n DMI_box.layout.width = '60px'\n DMI_box.layout.margin = '0px 50px'\n\n # Update the simulation using a button\n DMI_button = ipw.Button(description='Update')\n DMI_button.on_click(\n lambda button: self.update_DMI(DMI_box.value)\n )\n\n DMI_container = ipw.HBox(children=[DMI_box_text, DMI_box,\n DMI_button],\n )\n\n # Anisotropy -----------------------------------------------------------\n\n # anisotropy_box_text = ipw.Label(r'$\\text{Anisotropy [meV]}$')\n # anisotropy_box_text.width = '100px'\n\n # anisotropy_box = ipw.FloatText()\n\n # # Show the default value in the box\n # anisotropy_box.value = round(self.ku / const.meV, 2)\n # anisotropy_box.layout.width = '60px'\n # anisotropy_box.layout.margin = '0px 50px'\n\n # # Update the simulation using a button\n # anisotropy_button = ipw.Button(description='Update')\n # anisotropy_button.on_click(\n # lambda button: self.update_anisotropy(anisotropy_box.value)\n # )\n\n # anisotropy_container = ipw.HBox(children=[anisotropy_box_text,\n # anisotropy_box,\n # anisotropy_button]\n # )\n\n # Initial state -------------------------------------------------------\n\n # Options for the initial states. The values of the keys are the\n # initial magnetisation functions for Fidimag\n init_state_select = ipw.RadioButtons(\n options={'Skyrmion':\n lambda pos: self.skyrmion_m_field(pos, sign=1),\n '2-PI-Vortex':\n lambda pos: self.skyrmion_m_field(pos, sign=1,\n core=-1,\n pi_factor=2,\n out_skyrmion_dir=(0, 0, -1)\n ),\n '3-PI-Vortex':\n lambda pos: self.skyrmion_m_field(pos, sign=1,\n pi_factor=3,\n ),\n 'Helicoid':\n lambda pos: self.helicoid_m_field(pos),\n 'Sk-Helicoid':\n lambda pos: self.sk_helicoid_m_field(pos),\n 'Random':\n lambda pos: np.random.uniform(-1, 1, 3),\n 'Uniform':\n (0, 0, -1)\n },\n # description=r'$\\text{Initial State}$'\n )\n init_state_select.selected_label = 'Skyrmion'\n\n # We need the extra variable for the buttons action\n def update_state(b):\n self.generate_m_field(m_function=init_state_select.value)\n self.update_plot_component(mcomp_dropdown.value)\n\n # The selection changes are taken with the observe method\n init_state_select.observe(update_state)\n\n init_state_select_text = ipw.Label(r'$\\text{Initial State}$')\n init_state_select_text.width = '100px'\n\n init_state_select_box = ipw.HBox(children=[init_state_select_text,\n init_state_select]\n )\n\n # Pin boundaries button -----------------------------------------------\n\n pin_button = ipw.Button(description='Pin boundaries')\n pin_button.on_click(\n lambda button: self.pin_boundaries(plot_component=mcomp_dropdown.value)\n )\n\n unpin_button = ipw.Button(description='Unpin boundaries')\n unpin_button.on_click(\n lambda button: self.release_boundaries()\n )\n\n pin_box = ipw.HBox(children=[pin_button, unpin_button])\n pin_box.layout.margin = '20px 0px'\n\n # Display -------------------------------------------------------------\n\n display(mcomp_box)\n display(zeeman_container)\n display(DMI_container)\n # display(anisotropy_container)\n display(init_state_select_box)\n display(pin_box)\n display(run_container)\n\n # return","def run(self):\n self.root.title(\"Etymology relations\")\n self.root.geometry(\"1080x600\")\n self.root.deiconify()\n self.root.mainloop()","def console(self):\r\n\r\n go_on = True\r\n while go_on:\r\n console = DisplayList([self.headings.ADD_MENU,\r\n self.headings.DELETE_MENU,\r\n self.headings.SHOW_MENU,\r\n self.headings.CLEAR_MENU,\r\n self.headings.QUIT_MENU,\r\n '(N)otebook'*self.using_database],\r\n displayobject=self.displayobject)\r\n i = input()\r\n if i in self.ADDTERMS:\r\n\r\n self.add(input(self.headings.KEYMACRO), [x_temp.strip() for x_temp in input(self.headings.KEYS).split(',')])\r\n elif i in self.DELETETERMS:\r\n\r\n while True:\r\n self.show_kd()\r\n to_delete = input (self.headings.DELETE)\r\n if to_delete == EMPTYCHAR:\r\n break\r\n if to_delete.isnumeric() and int(to_delete) > 0 and int(to_delete) < len(self.query(term1='kd',action='get'))+1:\r\n from_temp = sorted(list(self.query(term1='kd',action='get')),\r\n key=lambda x_temp: x_temp.lower())[int(to_delete)-1]\r\n to_temp = self.query(term1='kd',term2=from_temp,action='get')\r\n \r\n self.delete(from_temp,to_temp[0])\r\n\r\n\r\n elif i in self.SHOWTERMS:\r\n self.show_kd()\r\n elif i in self.CLEARTERMS:\r\n if input(self.headings.ARE_YOU_SURE) in YESTERMS:\r\n self.query(term1='kd',action='delete')\r\n elif i in ['n','N'] and self.using_database:\r\n self.db_cursor.execute('SELECT notebook FROM notebooks')\r\n notebooks = [x[0] for x in self.db_cursor.fetchall()]\r\n self.displayobject.noteprint(('NOTEBOOKS','\\n'.join(notebooks)))\r\n action = input('NAME OF EXISTING OR NEW NOTEBOOK?').strip()\r\n if action in notebooks:\r\n self.notebookname = action\r\n else:\r\n if input('Do you want to creat a new notebook titled '+action) in YESTERMS:\r\n self.notebookname = action\r\n self.db_cursor.execute(\"INSERT OR REPLACE INTO notebooks (notebook) VALUES (?);\",(self.notebookname,))\r\n \r\n \r\n elif i in self.QUITTERMS:\r\n go_on = False","def main():\r\n root = tk.Tk()\r\n root.geometry(\"250x100+300+300\")\r\n TrendProg(root)\r\n root.mainloop()","def default_door():\n X = [0.0, 0.14, 1.12, 1.26]\n Y = [0.0, 0.14, 2.24]\n Z = [-0.14, 0.14]\n V, F = True, False\n occupancy = [\n [[V], [V]],\n [[V], [F]],\n [[V], [V]]\n ]\n return w7.window(X, Y, Z, occupancy)"],"string":"[\n \"def editor_example():\\n agent_sensors = [sensors.RGBCamera, sensors.LocationSensor, sensors.VelocitySensor]\\n agent = AgentDefinition(\\\"uav0\\\", agents.UavAgent, agent_sensors)\\n env = HolodeckEnvironment([agent], start_world=False)\\n env.agents[\\\"uav0\\\"].set_control_scheme(1)\\n command = [0, 0, 10, 50]\\n\\n for i in range(10):\\n env.reset()\\n for _ in range(1000):\\n state, reward, terminal, _ = env.step(command)\",\n \"def loop_menuDolar():\\r\\n window = menuDolar.Ventana()\\r\\n\\r\\n while True:\\r\\n event, value = window.read()\\r\\n\\r\\n if event in ('Volver', '-exit-'):\\r\\n break\\r\\n \\r\\n if event == '-actual-':\\r\\n window.hide()\\r\\n gd.actual()\\r\\n window.un_hide()\\r\\n\\r\\n if event == '-inc-':\\r\\n window.hide()\\r\\n gd.incremento()\\r\\n window.un_hide()\\r\\n \\r\\n if event == '-menor-':\\r\\n window.hide()\\r\\n gd.menor()\\r\\n window.un_hide()\\r\\n \\r\\n return window\",\n \"def rundemo(no,fig=False):\\n import qutipf90mc.examples as examples\\n print 'running demo #',str(no),'from qutip'\\n raw_input('press a key to continue')\\n funcstr = 'examples.ex_'+str(no)+'.run()'\\n ex_code = compile(funcstr,'<string>','exec')\\n if (fig): plt.figure()\\n eval(ex_code)\",\n \"def liquidity1_interact():\\r\\n date = wd.DatePicker(value = yesterday, description = \\\"选择日期\\\")\\r\\n threshold = wd.FloatSlider(value = 20, min = 0, max = 200, step = 1,\\r\\n description = \\\"单日可变现能力监测数值(%)\\\", tooltip = \\\"单击数值可进行编辑\\\", style = style)\\r\\n showAll = wd.Checkbox(value = False, description = '查看所有组合')\\r\\n verbose = wd.Checkbox(value = False, description = \\\"查看单日可变现能力的具体信息\\\")\\r\\n liqui_layout = wd.interact_manual(port_liquidity1_pre, date = date, threshold = threshold, verbose = verbose, showAll = showAll)\\r\\n liqui_layout.widget.children[4].description = \\\"开始查询\\\"\\r\\n liqui_layout.widget.children[4].button_style = \\\"danger\\\"\\r\\n display(liqui_layout)\\r\\n return None\",\n \"def demo(name):\\n x, y = demo_data[name]\\n\\n# _models = [models.Const1D(0), models.Gaussian1D(3, 1, .3), models.Gaussian1D(3, 2, .3)]\\n# _models = [models.Const1D(0)]\\n _models = None\\n\\n mv = ModelBrowser(x, y, y * 0, _models)\\n\\n mv.show()\\n\\n from glue.qt import get_qapp\\n get_qapp().exec_()\",\n \"def shell(state):\\n IPython.embed(colors=\\\"Neutral\\\", banner1=BANNER, user_ns={\\\"sdk\\\": state.sdk})\",\n \"def createViewerInput():\\n if 'VIEWER_INPUT' not in [node.name() for node in nuke.allNodes()]:\\n for node in nuke.allNodes():\\n node['selected'].setValue(False)\\n nuke.createNode(\\\"dmpViewerInput\\\")\\n node = nuke.toNode('VIEWER_INPUT')\\n node.showControlPanel()\\n node['selected'].setValue(False)\\n else:\\n nuke.toNode('VIEWER_INPUT').showControlPanel()\\n #nuke.delete(nuke.toNode('VIEWER_INPUT'))\",\n \"def interact(self):\\n param_min = self.param_vals[0]\\n param_max = self.param_vals[-1]\\n param_step = self.param_vals[1] - self.param_vals[0]\\n\\n qbt_indices = [index for (index, subsystem) in self.sweep.hilbertspace.qbt_subsys_list]\\n osc_indices = [index for (index, subsystem) in self.sweep.hilbertspace.osc_subsys_list]\\n\\n param_slider = ipywidgets.FloatSlider(min=param_min, max=param_max, step=param_step,\\n description=self.param_name, continuous_update=False)\\n photon_slider = ipywidgets.IntSlider(value=1, min=1, max=4, description='photon number')\\n initial_slider = ipywidgets.IntSlider(value=0, min=0, max=self.evals_count, description='initial state index')\\n final_slider = ipywidgets.IntSlider(value=1, min=1, max=self.evals_count, description='final state index')\\n\\n qbt_dropdown = ipywidgets.Dropdown(options=qbt_indices, description='qubit subsys')\\n osc_dropdown = ipywidgets.Dropdown(options=osc_indices, description='oscillator subsys')\\n\\n def update_min_final_index(*args):\\n final_slider.min = initial_slider.value + 1\\n\\n initial_slider.observe(update_min_final_index, 'value')\\n\\n out = ipywidgets.interactive_output(self.plot_explorer_panels,\\n {'param_val': param_slider,\\n 'photonnumber': photon_slider,\\n 'initial_index': initial_slider,\\n 'final_index': final_slider,\\n 'qbt_index': qbt_dropdown,\\n 'osc_index': osc_dropdown\\n })\\n\\n left_box = ipywidgets.VBox([param_slider])\\n mid_box = ipywidgets.VBox([initial_slider, final_slider, photon_slider])\\n right_box = ipywidgets.VBox([qbt_dropdown, osc_dropdown])\\n\\n user_interface = ipywidgets.HBox([left_box, mid_box, right_box])\\n display(user_interface, out)\",\n \"def eda():\\n dataset = mgr.current_dataset()\\n if dataset is None:\\n return redirect(url_for('main.datasets'))\\n loaded_names = mgr.list_loaded()\\n mgr.dump_data(dataset) # Pickle data and write to Docker volume\\n # Generate session ID and obtain JavaScript from Bokeh server\\n session_id = generate_session_id()\\n script = server_session(url='http://bokeh:5006/eda/',\\n session_id=session_id)\\n # Replace Docker alias in URL with localhost\\n script = script.replace(\\\"http://bokeh:5006\\\", \\\"http://localhost:5006\\\")\\n # Use the script in the rendered page\\n return render_template(\\\"dataset_preview.html\\\", script=script,\\n data_names=loaded_names)\",\n \"def main():\\r\\n # create the EdenLudo sample\\r\\n EdenEvolves = EdenLudo()\\r\\n # ru-n the scene\\r\\n run()\",\n \"def vp_start_gui():\\n global val, w, root\\n root = tk.Tk()\\n plot_support.set_Tk_var()\\n top = Toplevel1(root)\\n plot_support.init(root, top)\\n root.mainloop()\",\n \"def vis_difference(self):\\n print(self.init_vec)\\n\\n init = self.init_output.numpy()\\n\\n alphas = np.linspace(0, 1, 20)\\n for i, alpha in enumerate(alphas):\\n\\n display.clear_output(wait=True)\\n norm = [torch.linalg.norm(torch.tensor(\\n self.init_vec + alpha*self.eigen[i]), axis=1).detach().numpy() for i in range(2)]\\n\\n diff = np.array([self.compute_difference(\\n alpha, self.eigen[i]) for i in range(2)])\\n\\n fig = plt.figure(figsize=(14, 12), tight_layout=True)\\n fig.suptitle(\\\"Latent direction variation\\\", fontsize=20)\\n gs = gridspec.GridSpec(2, 2)\\n\\n ax_temp = plt.subplot(gs[0, :])\\n ax_temp.scatter(\\n init[:, 0], init[:, 1])\\n ax_temp.set_title(\\\"Initial Dataset\\\")\\n ax_temp.set_xlim(-1, 1)\\n ax_temp.set_ylim(-1, 1)\\n [s.set_visible(False) for s in ax_temp.spines.values()]\\n\\n for j in range(2):\\n ax_temp = plt.subplot(gs[1, j])\\n sc = ax_temp.quiver(\\n init[:, 0], init[:, 1], diff[j, :, 0], diff[j, :, 1], norm[j])\\n sc.set_clim(np.min(norm[j]), np.max(norm[j]))\\n plt.colorbar(sc)\\n ax_temp.set_title(\\n \\\"Direction: {}, alpha: {}\\\".format(j+1, alpha))\\n ax_temp.set_xlim(-1, 1)\\n ax_temp.set_ylim(-1, 1)\\n [s.set_visible(False) for s in ax_temp.spines.values()]\\n\\n plt.savefig(\\\"frames_dir/fig_{}\\\".format(i))\\n plt.show()\",\n \"def main(arg):\\n global new, left, right, app, backgroundcolor, dragon\\n global size, x, y, win, timer, linecolor, number\\n number, linecolor, backgroundcolor = arg_decode(arg)\\n new = generate_dragon(number) # Generate dragon plot values\\n\\n app = QtGui.QApplication([]) # create plot application\\n size = (len(new)+1) # get size of new\\n x = np.zeros(size) # create array of zeros based on size of new\\n y = np.zeros(size)\\n\\n # set plot application settings\\n win = pg.GraphicsLayoutWidget(show=True, title=\\\"Dragon\\\")\\n win.setBackground(backgroundcolor)\\n win.resize(1024, 768)\\n\\n plot = win.addPlot(title=\\\"Dragon plot\\\") # add plot\\n\\n static_posx = [-1, 0, 0] # predefined cords for lines\\n static_posy = [0, 0, -1] #\\n dragon = plot.plot(static_posx, static_posy, pen=linecolor)\\n dragon = plot.plot(x, y, pen=linecolor) # plot empty arrays\\n timer = QtCore.QTimer() # Init timer\\n timer.timeout.connect(update) # join timer update to funtion\\n timer.start(1) # set timer update time\",\n \"def create_widgets(self):\\n # self.var_spherical = IntVar()\\n # self.var_3d = IntVar()\\n # self.var_spatial_audio = IntVar()\\n # self.button_open[\\\"command\\\"] = self.action_open\\n # self.button_inject[\\\"command\\\"] = self.action_inject\\n pass\",\n \"def demonstrate(self):\\n self.env.render()\\n self.action = 0\\n\\n # Control actions with keys\\n @self.env.viewer.window.event\\n def on_key_press(symbol, modifiers):\\n self.action = Task.act(symbol)\\n\\n # Default to no action\\n @self.env.viewer.window.event\\n def on_key_release(symbol, modifiers):\\n self.action = 0\\n\\n # Perform actions on a timer\\n def tick(dt):\\n if not self.ended():\\n self.perform(self.action, render=True, delay=SLOW)\\n self.update()\\n pyglet.clock.schedule_once(tick, 0)\\n\\n tick(0)\\n pyglet.app.run()\",\n \"def interactive():\\n IPython.start_ipython(argv=[])\",\n \"def switch_arrangment(self, new_arrangment):\\n #Clear Figures to avoid memory leak\\n for figure in self.figures:\\n figure.clear()\\n plt.close(figure)\\n \\n #Close the exisiting display\\n self.destroy()\\n \\n #Generate user interface\\n UI = SD_UI(tuning = self.tuning_flag,\\n location = self.location,\\n language = self.language,\\n arrangment = new_arrangment)\\n \\n #Run the new user interface\\n UI.mainloop()\",\n \"def create_figure(self) -> None:\\n plt.ion()\\n self.fig = plt.figure(1)\\n self.axis = self.fig.add_subplot(111, xlim=(0, 1), ylim=(0, 1))\\n self.axis.grid(True)\\n plt.xticks(np.linspace(0, 1, self._param[\\\"n_v\\\"] + 1))\\n plt.yticks(np.linspace(0, 1, self._param[\\\"n_v\\\"] + 1))\\n a_plt, = self.axis.plot([], [], 'bx', markersize=5)\\n l_plt, = self.axis.plot([], [], 'r.', markersize=15)\\n self.plots = [a_plt, l_plt]\",\n \"def guiFurnishGlobals(par):\\n\\n # plot settings\\n from matplotlib import rcParams\\n rcParams['axes.labelsize'] = 14 \\n rcParams['xtick.labelsize'] = 12\\n rcParams['ytick.labelsize'] = 12 \\n rcParams['legend.fontsize'] = 12\\n rcParams['lines.linewidth'] = 2\\n\\n # experimental data\\n t, Gexp, wG = GetExpData(par['GexpFile'])\\n n = len(t)\\n ns = par['ns'] # discretization of 'tau'\\n\\n tmin = t[0];\\n tmax = t[n-1];\\n\\n # determine frequency window\\n if par['FreqEnd'] == 1:\\n smin = np.exp(-np.pi/2) * tmin; smax = np.exp(np.pi/2) * tmax\\t\\t\\n elif par['FreqEnd'] == 2:\\n smin = tmin; smax = tmax\\n elif par['FreqEnd'] == 3:\\n smin = np.exp(+np.pi/2) * tmin; smax = np.exp(-np.pi/2) * tmax\\t\\t\\n\\n hs = (smax/smin)**(1./(ns-1))\\n s = smin * hs**np.arange(ns)\\n kernMat = getKernMat(s,t)\\n\\n # toggle flags to prevent printing\\n\\n par['verbose'] = False\\n par['plotting'] = False\\n\\n # load lamda, rho, eta\\n lam, rho, eta = np.loadtxt('output/rho-eta.dat', unpack=True)\\n\\n\\n plt.clf()\\n\\n return s, t, kernMat, Gexp, par, lam, rho, eta\",\n \"def main():\\n # Load properties that will be needed\\n store = [Storage.Storage(2), Storage.Storage(4)] \\n pre_energy = [s.get(\\\"free_energy\\\") for s in store]\\n post_energy = [s.get(\\\"post_energy\\\") for s in store]\\n x_range = store[0].get(\\\"x_range\\\")\\n xlocs = np.arange(x_range[0], x_range[1], x_range[2])\\n y_range = store[0].get(\\\"y_range\\\")\\n ylocs = np.arange(y_range[0], y_range[1], y_range[2])\\n # Calculate step size\\n xb2steps = stepsize(pre_energy[0], post_energy[0], xlocs) \\n xb4steps = stepsize(pre_energy[1], post_energy[1], xlocs) \\n # Set up the figure\\n fig = plt.figure(1, figsize=(7.5,2.5)) \\n axe = (fig.add_subplot(1, 2, 1), fig.add_subplot(1, 2, 2))\\n # Plot the results\\n axe[0].plot(ylocs, xb4steps, color='#FF466F', lw=4)\\n axe[1].plot(ylocs, xb2steps, color='#76D753', lw=4)\\n # Annotate the plots\\n axe[0].set_title(\\\"4sXB step size\\\")\\n axe[0].set_xlabel(\\\"Lattice spacing (nm)\\\") \\n axe[0].set_ylabel(\\\"Step size (nm)\\\")\\n axe[0].set_xlim((25.5, 39))\\n axe[0].set_ylim((1, 8))\\n axe[1].set_title(\\\"2sXB step size\\\")\\n axe[1].set_xlabel(\\\"Lattice spacing (nm)\\\") \\n axe[1].set_ylabel(\\\"Step size (nm)\\\")\\n axe[1].set_xlim((25.5, 39))\\n axe[1].set_ylim((1, 8))\\n # Display the plots\\n fig.subplots_adjust(wspace=0.25, hspace=0.48,\\n left=0.08, right=0.98,\\n top=0.85, bottom=0.21)\\n plt.show()\",\n \"def EnvironmentTab():\\n\\n mainTab = cmds.columnLayout(adjustableColumn=True, columnAttach=('both', 20))\\n \\n ### Physical Light\\n cmds.separator(height=10, style=\\\"none\\\")\\n cmds.text(label=\\\"Physical Light:\\\", align=\\\"left\\\")\\n # Slider to select the elevation\\n elevationSlider = cmds.floatSliderGrp(label=\\\"Elevation\\\", field=True, value=45, min=0, max=90, \\n dragCommand=lambda value:EC.elevationChange(value),\\n changeCommand=lambda value:EC.elevationChange(value))\\n # Slider to select the azimuth (simulat to the height, kinda)\\n azimuthSlider = cmds.floatSliderGrp(label=\\\"Azimuth\\\", field=True, value=90, min=0, max=360, \\n dragCommand=lambda value:EC.azimuthChange(value),\\n changeCommand=lambda value:EC.azimuthChange(value))\\n # Slider for the light's intensity\\n intensitySlider = cmds.floatSliderGrp(label=\\\"Intensity\\\", field=True, value=1, min=.1, max=10, \\n dragCommand=lambda value:EC.intensityChange(value),\\n changeCommand=lambda value:EC.intensityChange(value))\\n\\n cmds.separator(height=5, style=\\\"none\\\")\\n cmds.button(label='Create Sky Dome', command=lambda x: EC.createSkyLight(elevationSlider, azimuthSlider, intensitySlider))\\n\\n ### Environment fog\\n cmds.separator(height=20)\\n cmds.text(label=\\\"Environment Fog:\\\", align=\\\"left\\\")\\n # Slider for the color\\n colorSlider = cmds.colorSliderGrp(label=\\\"Color\\\", rgb=(1,1,1), \\n dragCommand=lambda value:EC.colorChange(colorSlider),\\n changeCommand=lambda value:EC.colorChange(colorSlider))\\n # Slider for fog's distance\\n distanceSlider = cmds.floatSliderGrp(label=\\\"Distance\\\", field=True, value=.02, min=0, max=1000, step=.01, \\n dragCommand=lambda value:EC.distanceChange(value), \\n changeCommand=lambda value:EC.distanceChange(value))\\n # Slider for fog's height\\n heightSlider = cmds.floatSliderGrp(label=\\\"Height\\\", field=True, value=5, min=0, max=1000, step=.1, \\n dragCommand=lambda value:EC.heightChange(value),\\n changeCommand=lambda value:EC.heightChange(value))\\n\\n cmds.separator(height=5, style=\\\"none\\\")\\n cmds.button(label='Create Environment Fog', command=lambda x: EC.createAiFog(colorSlider, distanceSlider, heightSlider))\\n\\n cmds.setParent('..')\\n\\n return mainTab\",\n \"def update(self):\\n self.plot.draw()\\n \\n func=str(self.edit1b.currentText())\\n if self.win.test()==0:\\n x=np.linspace(0,10,200)\\n elif self.win.test()==1:\\n x=np.linspace(0,0.40,200)\\n \\n pattern1=r'Steel'\\n pattern2=r'Aluminium'\\n pattern3=r'[\\\\d]+'\\n \\n if (func!='Comparison Chart'):\\n self.edit2b.setDisabled(False)\\n self.edit3b.setDisabled(False)\\n self.edit4b.setDisabled(False)\\n if (func=='Quenched/Tempered Steel'):\\n alpha = 0.0025\\n elif (func=='Annealed Steel'):\\n alpha = 0.01\\n elif (func=='Steel (input Su)'):\\n S = str(self.edit2b.text())\\n if (self.win.test()==0):\\n S = str(float(S)/6.895)\\n alpha = notch.alpha(eval(S))\\n elif (func=='Aluminium Alloy 356.0 as cast'):\\n rho = 0.08\\n elif (func=='Aluminium Alloy 6061'):\\n rho = 0.025\\n elif (func=='Aluminium Alloy 7075'):\\n rho = 0.015\\n elif (func=='Material dropdown'):\\n pass\\n \\n y1=[]\\n if re.search(pattern1,func):\\n Su=notch.su_s(alpha)\\n if (self.win.test()==0):\\n Su = Su*6.895\\n for i in range(len(x)):\\n y1.append(notch.nsp(alpha,x[i],self.win.test()))\\n y=np.asarray(y1)\\n if (re.search(pattern3,str(self.edit3b.text()))):\\n r=eval(str(self.edit3b.text()))\\n self.edit4b.setText(str(notch.nsp(alpha,r,self.win.test())))\\n elif re.search(pattern2,func):\\n Su=notch.su_a(rho)\\n if (self.win.test()==0):\\n Su = Su*6.895\\n for i in range(len(x)):\\n y1.append(notch.nsn(rho,x[i],self.win.test()))\\n y=np.asarray(y1)\\n if (re.search(pattern3,str(self.edit3b.text()))):\\n r=eval(str(self.edit3b.text()))\\n self.edit4b.setText(str(notch.nsn(rho,r,self.win.test())))\\n \\n self.edit2b.setText(str(Su))\\n func1 = 'Steel (Su='+str(self.edit2b.text())+')'\\n if (func!='Steel (input Su)'):\\n self.plot.redraw(x,y,func, self.xlabel)\\n elif (func=='Steel (input Su)'):\\n self.plot.redraw(x,y,func1, self.xlabel)\\n \\n elif (func=='Comparison Chart'):\\n self.edit2b.setText(\\\"\\\")\\n self.edit2b.setDisabled(True)\\n self.edit3b.setText(\\\"\\\")\\n self.edit3b.setDisabled(True)\\n self.edit4b.setText(\\\"\\\")\\n self.edit4b.setDisabled(True)\\n self.plot.draw_comp(self.xlabel, self.win.test())\",\n \"def eta_ ( self ) :\\n from GaudiConfUtils.ConfigurableGenerators import FilterDesktop\\n from StandardParticles import StdLooseEta2gg as inpts \\n ##\\n return self.make_selection (\\n 'EtaStd' ,\\n FilterDesktop ,\\n [ inpts ] ,\\n Code = self['Eta2ggCut'] ,\\n )\",\n \"def main():\\n main = tk.Tk()\\n\\n # Add Title\\n main.title(\\\"Space Craft Creator\\\")\\n\\n # Disable Resizing\\n main.resizable(False, False)\\n\\n data = Data()\\n\\n spacecraft = Spacecraft(data)\\n\\n notebook = Notebook(main)\\n\\n spacecraft_tab = spacecraft.make_tab(notebook)\\n\\n notebook.add(spacecraft_tab, text=\\\"Spacecraft\\\")\\n for key, subsystem in spacecraft.subsections.items():\\n notebook.add(subsystem.make_tab(notebook), text=key)\\n notebook.add(spacecraft.sizes.make_tab(notebook), text=\\\"Sizes\\\")\\n notebook.add(spacecraft.velocities.make_tab(notebook), text=\\\"Velocity Profiles\\\")\\n\\n notebook.grid(column=0, row=0)\\n notebook.enable_traversal()\\n\\n button = Button(main, text=\\\"Caclulate\\\", command=spacecraft.calculate)\\n button.grid(column=0, row=1)\\n\\n main.mainloop()\",\n \"def interactive(self, name='grid', bind_x=True, bind_y=True):\\n encodings = []\\n if bind_x:\\n encodings.append('x')\\n if bind_y:\\n encodings.append('y')\\n self.selection = {name: {'bind': 'scales',\\n 'type': 'interval',\\n 'encodings': encodings}}\\n return self\",\n \"def main():\\n PanelDemo().mainloop()\",\n \"def edit():\\n\\n curitem = treeview.focus().strip(\\\"#\\\")\\n select_values = series_dict[curitem]\\n editent2var.set(\\\"thumbnails\\\\\\\\\\\")\\n\\n def raging_fire():\\n \\\"\\\"\\\"call back function for edit button in the edit window\\\"\\\"\\\"\\n\\n if editspin1.get() != '0': # season\\n select_values[0] = int(editspin1.get())\\n select_values[3] = \\\"{}\\\".format(datetime.datetime.now()) # update the modify date\\n with open('series_table.json', 'w') as f:\\n json.dump(series_dict, f, indent=2)\\n\\n if editspin2.get() != '0': # episode\\n select_values[1] = int(editspin2.get())\\n select_values[3] = \\\"{}\\\".format(datetime.datetime.now()) # update the modify date\\n with open('series_table.json', 'w') as f:\\n json.dump(series_dict, f, indent=2)\\n\\n if editentvar.get() != curitem: # name\\n series_dict[editentvar.get().title()] = series_dict.pop(curitem) # update the modify date\\n select_values[3] = \\\"{}\\\".format(datetime.datetime.now())\\n with open('series_table.json', 'w') as f:\\n json.dump(series_dict, f, indent=2)\\n\\n if editent2var.get() != select_values[2]: # pic\\n select_values[3] = \\\"{}\\\".format(datetime.datetime.now()) # update the modify date\\n select_values[2] = editent2var.get()\\n with open('series_table.json', 'w') as f:\\n json.dump(series_dict, f, indent=2)\\n\\n edittop.destroy()\\n\\n if curitem != \\\"\\\": # test if an item is highlighted first\\n \\\"\\\"\\\"the actual ecit window widgets\\\"\\\"\\\"\\n edittop = Toplevel()\\n\\n editlab1 = Label(edittop, text=\\\"Current Tv-Series title : \\\")\\n editlab1.grid(row=1, column=1, sticky=W, pady=4)\\n\\n editent = Entry(edittop, textvariable=editentvar, width=30)\\n editentvar.set(curitem)\\n editent.grid(row=1, column=2, sticky=W, pady=4)\\n\\n editlab2 = Label(edittop, text=\\\"Current Season {}, chance to : \\\".format(select_values[0]))\\n editlab2.grid(row=2, column=1, sticky=W, pady=4)\\n\\n editspin1 = Spinbox(edittop, from_=0, to=1000, width=5)\\n editspin1.grid(row=2, column=2, sticky=W, pady=4)\\n\\n editlab3 = Label(edittop, text=\\\"Current Episode {}, change to : \\\".format(select_values[1]))\\n editlab3.grid(row=3, column=1, sticky=W, pady=4)\\n\\n editspin2 = Spinbox(edittop, from_=0, to=1000, width=5)\\n editspin2.grid(row=3, column=2, sticky=W, pady=4)\\n\\n editlab4 = Label(edittop, text=\\\"Change image to : \\\")\\n editlab4.grid(row=4, column=1, sticky=W, pady=4)\\n\\n editent2 = Entry(edittop, textvariable=editent2var, width=35)\\n editent2var.set(select_values[2])\\n editent2.grid(row=4, column=2, sticky=E, pady=4)\\n\\n editbut = Button(edittop, text='Edit', command=raging_fire)\\n editbut.grid(row=5, column=1, sticky=W, pady=4, padx=20)\\n\\n download_thumbbut = Button(edittop, text=\\\"Download The thumbnail\\\", command=download_thumb)\\n download_thumbbut.grid(row=5, column=2, sticky=W, pady=4, padx=20)\\n\\n edittop.geometry(\\\"400x200+200+300\\\")\\n edittop.title(\\\"Edit properties of {} \\\".format(curitem).upper())\",\n \"def make_interactive(model: EpamModel, Xy_raw: pd.DataFrame):\\n \\n def inner(base_example: int = 0):\\n \\\"\\\"\\\"Inner function that does the work.\\\"\\\"\\\"\\n EX = Xy_raw.iloc[base_example]\\n print(\\\"Base Example IDs:\\\")\\n print((Xy_raw.index[[base_example]]).to_frame().reset_index(drop=True).iloc[0].rename(index=base_example))\\n\\n def get_widget(col: str):\\n V = EX[col]\\n if 'Tak' in Xy_raw[col].values.tolist():\\n zz = [\\\"Tak\\\", \\\"Nie\\\", \\\"Nie wiadomo\\\"]\\n return w.Select(options=zz, value=\\\"Nie wiadomo\\\" if (V not in zz) else V)\\n\\n d = Xy_raw[col].dtype\\n if d == \\\"int64\\\":\\n return w.IntSlider(min=Xy_raw[col].min(), max=Xy_raw[col].max(), value=V)\\n elif d == \\\"float64\\\":\\n return w.FloatText(value=V)#Xy_raw[col].mean())\\n\\n def _f(s):\\n try:\\n return float(s)\\n except:\\n return np.nan\\n avg_val = Xy_raw[col].apply(_f).mean()\\n if pd.isnull(V):\\n V = str(avg_val)\\n return w.Text(value=V)\\n\\n\\n def make_pred(**vals):\\n my_X_raw = pd.Series(vals).to_frame().T\\n my_X_raw = my_X_raw.astype(Xy_raw.drop(columns=[basic_target]).dtypes)\\n my_X = cleanup_df(my_X_raw)#.astype(X.dtypes)\\n\\n ifd = model.ifd_\\n with model.build_model(my_X) as m:\\n _ppc_oos = pm.fast_sample_posterior_predictive(ifd)\\n ifd_oos = az.from_pymc3(posterior_predictive=_ppc_oos)\\n ppc_oos = ifd_oos.posterior_predictive['y_pred']\\n y_oos = ppc_oos.mean([\\\"chain\\\", \\\"draw\\\"]).to_series()\\n\\n # y_prob = model.predict_proba(my_X)\\n print(\\\"Prediction:\\\", y_oos.iloc[0])\\n\\n widgets = {k: get_widget(k) for k in Xy_raw.drop(columns=[basic_target]).columns}\\n \\n w.interact_manual(make_pred, **widgets)\\n return w.interact(\\n inner, \\n base_example=w.IntText(min=0, max=len(Xy_raw)-1, value=0, description=\\\"Base Case\\\")\\n )\",\n \"def setupVariableAxes(self):\\n if self.var is None:\\n return\\n \\n if (self.axisList is None):\\n self.axisList = self.var.getAxisList()\\n self.axisOrder = range(len(self.axisList))\\n\\n self.clear() \\n self.setAxesNames()\\n \\n # Iterate through the variables axes & init each axis widget\\n axisIndex = 0\\n for axis, axisName in zip(self.axisList, self.axesNames):\\n # Create the axis widget\\n axisWidget = QAxis(axis, axisName, axisIndex, self)\\n axisWidget.setAxisButtonText(axisName)\\n self.axisWidgets.append(axisWidget)\\n\\n # Setup the layout for each axis\\n row = self.gridLayout.rowCount()\\n self.gridLayout.addWidget(axisWidget.getAxisButton(), row, 0)\\n self.gridLayout.addWidget(axisWidget, row, 1) \\n self.gridLayout.addWidget(axisWidget.getAxisOperationsButton(), row, 2)\\n\\n # Create separator line between each axis widget\\n vline = QtGui.QFrame()\\n vline.setFrameStyle(QtGui.QFrame.HLine | QtGui.QFrame.Sunken)\\n self.gridLayout.addWidget(vline, row+1, 0, 1,\\n self.gridLayout.columnCount())\\n\\n axisIndex += 1\\n\\n self.gridLayout.setRowStretch(self.gridLayout.rowCount(), 1)\",\n \"def main():\\n app = guisupport.get_app_qt4()\\n\\n if INPROCESS:\\n from qtconsole.inprocess import QtInProcessKernelManager\\n km = QtInProcessKernelManager()\\n else:\\n from qtconsole.manager import QtKernelManager\\n km = QtKernelManager()\\n km.start_kernel()\\n km.kernel.gui = 'qt4'\\n kc = km.client()\\n kc.start_channels()\\n\\n widget = RichJupyterWidget()\\n widget.kernel_manager = km\\n widget.kernel_client = kc\\n if CLEANSHUTDOWN: # slow exit on CTRL+D\\n def stop():\\n kc.stop_channels()\\n km.shutdown_kernel()\\n app.exit()\\n widget.exit_requested.connect(stop)\\n else: # fast exit on CTRL+D\\n widget.exit_requested.connect(app.quit)\\n widget.show()\\n guisupport.start_event_loop_qt4(app)\",\n \"def _create_3D_pane(self):\\n\\t\\t\\n panel = wx.Panel(self,-1)\\n self.interactor3d = wxVTKRenderWindowInteractor(panel, -1, (600,800))\\n self.generate_button = wx.Button(panel, label=\\\"Generate 3D view\\\")\\n self.text_position = wx.StaticText(panel, -1, \\\"Dose (Gy) \\\" , wx.Point(0, 0))\\n self.slider_dose3d = wx.Slider(panel, -1, 75, 60, 100, wx.DefaultPosition, wx.Size( 100,-1 ), wx.SL_HORIZONTAL)\\n self.spin_dose3d = wx.SpinCtrl(panel, wx.ID_ANY, str(self.slider_dose3d.GetValue()), wx.DefaultPosition, wx.Size( 70,-1 ), wx.SP_ARROW_KEYS, min=0, max=100, initial=11)\\t\\n\\t\\t\\n button_sizer = wx.BoxSizer(wx.HORIZONTAL)\\n button_sizer.AddSpacer(30)\\n button_sizer.Add(self.generate_button)\\n button_sizer.AddSpacer(30)\\n button_sizer.Add(self.text_position)\\n button_sizer.Add(self.slider_dose3d)\\n button_sizer.Add(self.spin_dose3d)\\n\\t\\t\\n listsizer = wx.BoxSizer(wx.VERTICAL)\\n listsizer.Add(self.interactor3d, 1, wx.EXPAND|wx.BOTTOM, 7)\\n listsizer.Add(button_sizer)\\n panel.SetSizer(listsizer)\\n listsizer.Fit(panel)\\n\\t\\t\\n self._create_orientation_widget(self.interactor3d)\\n return panel\",\n \"def run_ejercicio_3():\\n\\n # Parametros para el ejercicio\\n lower = 0\\n upper = 4 * np.pi\\n number_of_points = 100\\n\\n print(f\\\"Separando el intervalo [{lower}, {upper}] en {number_of_points} puntos equidistantes\\\")\\n values = np.linspace(lower, upper, number_of_points)\\n print(\\\"\\\")\\n\\n print(f\\\"Mapeando los valores a las tres funciones dadas\\\")\\n sin_values, cos_values, complex_function_values = map_values_to_functions(values)\\n print(\\\"\\\")\\n\\n print(f\\\"Los valores son: {values}\\\\n\\\")\\n print(f\\\"Valores en el seno: {sin_values}\\\\n\\\")\\n print(f\\\"Valores en el coseno: {cos_values}\\\\n\\\")\\n print(f\\\"Valores en tanh(sin + cos): {complex_function_values}\\\\n\\\")\\n print(\\\"\\\")\\n wait_for_user_input()\\n\\n print(\\\"Mostrando la grafica de los valores\\\")\\n plot_three_functions(values, sin_values, cos_values, complex_function_values)\",\n \"def interact(self):\\n # We use a library_interact instead of a normal interact here,\\n # since this is an interact in the library, and a normal\\n # \\\"@interact\\\" is all mangled.\\n\\n from sage.interacts.library import library_interact\\n from sagenb.notebook.interact import slider, input_box, selector\\n\\n # self._last holds the last state of all controls. This allows\\n # us to deduce which control changed to cause the update, or that\\n # nothing changed, in which case we assume the user requested to\\n # re-evaluate the input box (for some reason -- currently there is\\n # no point in doing so). It is a shortcoming of @interact that\\n # we have to do this.\\n self._last = None\\n\\n # two sliders and a box to put in commands with an evaluate button.\\n @library_interact\\n def dbg(frame = slider(vmin=0, vmax=len(self._stack)-1, step_size=1, default=len(self._stack)-1, label='stack frame'),\\n lines = slider(vmin=3, vmax=99, step_size=2, default=11, label='lines of context'),\\n command = input_box(\\\"\\\", label=\\\"\\\", type=str),\\n button = selector(['Evaluate'], label='', buttons=True)\\n ):\\n\\n if self._last is None:\\n self._last = {'command':command, 'button':button, 'lines':lines, 'frame':frame}\\n\\n if self._last['lines'] != lines:\\n # they dragged the number-of-lines slider, so done\\n pass\\n elif self._last['command'] != command and command.strip():\\n # they changed the command, so evaluate that\\n self.evaluate(command)\\n elif self._last['frame'] != frame:\\n # they dragged the frame slider.\\n self._curframe_index = frame\\n elif command:\\n # must have hit the evaluate button\\n self.evaluate(command)\\n\\n print('<html><hr>{}</html>'.format(self.listing(lines//2)))\\n # save control state for next time around\\n self._last = {'command':command, 'button':button, 'lines':lines, 'frame':frame}\\n\\n dbg()\",\n \"def add_sliders(self):\\n\\n\\t\\tself.scale_dict = {}\\n\\t\\tinnov_str = simpledialog.askstring(\\\"Get Innovations.\\\", \\n\\t\\t\\t\\\"What innovation numbers do you want sliders for (separate with commas)?\\\")\\n\\t\\tinnov_nums = innov_str.split(\\\",\\\")\\n\\t\\tfor innov in innov_nums:\\n\\t\\t\\tself.scale_dict[innov] = tk.Scale(self, from_=-20, \\n\\t\\t\\t\\tto=20, orient=tk.HORIZONTAL)\\n\\t\\t\\ttk.Label(self, text=\\\"Slider for #{0}\\\".format(innov)).pack()\\n\\t\\t\\tself.scale_dict[innov].pack(pady=10)\\n\\t\\ttk.Button(self, text=\\\"Apply\\\", command=lambda: self.slider_update_CPPN()).pack()\\n\\n\\n\\t\\ttk.Button(self, text=\\\"Exit\\\", command=self.quit).pack(pady=(20,10))\",\n \"def isoslider(surface_dic, surface_value_dic, min_value=0):\\r\\n return \\\\\\r\\nf\\\"\\\"\\\"\\r\\n\\\\n\\\\nclass IsoLevel(tk.Variable):\\r\\n def __init__(self, master, name, level):\\r\\n tk.Variable.__init__(self, master, value=level)\\r\\n self.name = name\\r\\n self.trace('w', self.callback)\\r\\n\\r\\n def callback(self, *args):\\r\\n cmd.isolevel(self.name, self.get())\\r\\n\\r\\n def increment(self, event=None, delta=0.1):\\r\\n self.set(round(float(self.get()) + delta, 2))\\r\\n\\r\\n def decrement(self, event=None):\\r\\n self.increment(None, -0.1)\\r\\n\\r\\n\\r\\nsurface_list = {surface_dic}\\r\\nsurface_max_list = {surface_value_dic}\\r\\n\\r\\ntop = tk.Toplevel(plugins.get_tk_root())\\r\\n\\r\\nmaster = tk.Frame(top, padx=10, pady=10)\\r\\nmaster.pack(fill=\\\"both\\\", expand=1)\\r\\n\\r\\nfor child in list(master.children.values()):\\r\\n child.destroy()\\r\\n\\r\\n\\r\\nrow_counter = 0\\r\\nfor identifier, component_dic in surface_list.items():\\r\\n # add calculation identifier\\r\\n tk.Label(master, text=identifier).grid(row=row_counter, column=0, sticky=\\\"w\\\")\\r\\n row_counter += 1\\r\\n \\r\\n for component_id, surfaces in component_dic.items():\\r\\n # add collection label, e.g. superstar or hotspot etc.\\r\\n tk.Label(master, text=component_id).grid(row=row_counter, column=1, sticky='w')\\r\\n row_counter += 1\\r\\n \\r\\n for i, surface in enumerate(surfaces):\\r\\n # add grid type label\\r\\n probe = surface.split(\\\"_\\\")[-2]\\r\\n tk.Label(master, text=probe).grid(row=row_counter, column=2, sticky=\\\"w\\\")\\r\\n \\r\\n # slider code \\r\\n v = IsoLevel(master, surface, 5)\\r\\n e = tk.Scale(master, orient=tk.HORIZONTAL, from_={min_value}, to=surface_max_list[identifier][component_id],\\r\\n resolution=0.1, showvalue=0, variable=v)\\r\\n e.grid(row=row_counter, column=3, sticky=\\\"ew\\\")\\r\\n\\r\\n e = tk.Entry(master, textvariable=v, width=4)\\r\\n e.grid(row=row_counter, column=4, sticky=\\\"e\\\")\\r\\n master.columnconfigure(3, weight=1)\\r\\n row_counter += 1\\r\\n\\\\n\\\\n\\r\\n\\\"\\\"\\\"\",\n \"def launch_new_instance():\\n import IPython\\n\\n IPython.Shell.start().mainloop()\",\n \"def test_visuThreeD1(self):\\n\\n visu_logic = slicer.modules.visuThreeDWidget.logic\\n #visu_logic.set_user_table(self.user_table)\\n #visu_logic.set_user_file('/work/maria5/EBDS_CIVILITY/DataShare/TestMatricesForVisualization/AAL78/PerNodeMetrics/Conte_EigenVectorCentrality_4Yr_AAL78Regions.csv')\\n #visu_logic.set_user_file('/Users/Wieke/Documents/visuThreeD/neo-0042-4year_AvgSym_normFull.csv')\\n # visu_logic.create_node_actors()\\n # visu_logic.create_line_actors()\\n # visu_logic.update()\\n #visu_logic.set_node_range()\",\n \"def main():\\n\\tif mc.window( 'curveScatter_WIN', q = 1, ex = 1 ):\\n\\t\\tmc.deleteUI( 'curveScatter_WIN' )\\n\\tPyForm=CurveScatterUI()\\n\\tPyForm.show()\",\n \"def __init__(self, controller):\\n self.controller = controller\\n\\n self.electoral_distribution = None\\n\\n # Shows the forecast for electoral college votes over time.\\n self.ecvdistribution = figure(\\n title=\\\"\\\"\\\"Electoral college votes distribution\\\"\\\"\\\",\\n x_axis_type=\\\"\\\"\\\"linear\\\"\\\"\\\",\\n x_axis_label=\\\"\\\"\\\"Electoral college votes\\\"\\\"\\\",\\n y_axis_label=\\\"\\\"\\\"Probability\\\"\\\"\\\",\\n sizing_mode=\\\"\\\"\\\"stretch_both\\\"\\\"\\\")\\n # Fake data to make sure we don't get an empty renderer message\\n self.cds = ColumnDataSource(\\n data={'Electoral college votes': list(range(539)),\\n 'Democratic distribution': norm.pdf(range(539),\\n loc=200,\\n scale=100),\\n 'Republican distribution': norm.pdf(range(539),\\n loc=400,\\n scale=100)}\\n )\\n _dg = self.ecvdistribution.vbar(\\n x='Electoral college votes',\\n top='Democratic distribution',\\n fill_color='blue',\\n line_color='blue',\\n line_width=1,\\n width=1,\\n alpha=0.2,\\n source=self.cds)\\n _rg = self.ecvdistribution.vbar(\\n x='Electoral college votes',\\n top='Republican distribution',\\n fill_color='red',\\n line_color='red',\\n line_width=1,\\n width=1,\\n alpha=0.2,\\n source=self.cds)\\n # 270 to win line\\n _win270 = Span(location=270, dimension='height')\\n self.ecvdistribution.add_layout(_win270)\\n # Add a legend outside of the plot\\n _legend = Legend(items=[('Democratic', [_dg]),\\n ('Republican', [_rg])],\\n location='top_right')\\n self.ecvdistribution.add_layout(_legend, 'right')\\n self.ecvdistribution.legend.click_policy = \\\"hide\\\"\\n self.ecvdistribution.y_range.only_visible = True\\n\\n # The date for charting.\\n self.choosethedatefordisplay = DateSlider(\\n title=\\\"\\\"\\\"Choose the date for display\\\"\\\"\\\",\\n start=\\\"\\\"\\\"2018-11-13T20:20:39+00:00\\\"\\\"\\\",\\n end=\\\"\\\"\\\"2025-11-13T20:20:39+00:00\\\"\\\"\\\",\\n step=24*60*60*1000,\\n value=\\\"\\\"\\\"2018-11-13T20:20:39+00:00\\\"\\\"\\\",\\n sizing_mode=\\\"stretch_width\\\")\\n\\n # Layout the widgets\\n r1 = row(children=[Spacer(width=10),\\n self.choosethedatefordisplay,\\n Spacer(width=10)],\\n sizing_mode='stretch_width')\\n self.layout = column(children=[self.ecvdistribution,\\n r1,\\n Spacer(height=75,\\n sizing_mode='scale_width')],\\n sizing_mode='stretch_both')\\n self.panel = Panel(child=self.layout,\\n title='Vote forecast distribution')\",\n \"def figure2():\\n # sim_data_XPP = pd.read_csv(\\\"XPP.dat\\\", delimiter=\\\" \\\", header=None) # Load the XPP simulation\\n\\n plot_settings = {'y_limits': [-25, 0],\\n 'x_limits': None,\\n 'y_ticks': [-25, -20, -15, -10, -5, 0],\\n 'locator_size': 2.5,\\n 'y_label': 'Current (nA)',\\n 'x_ticks': [],\\n 'scale_size': 0,\\n 'x_label': \\\"\\\",\\n 'scale_loc': 4,\\n 'figure_name': 'figure_2',\\n 'legend': ['I-Na', 'I-NaP'],\\n 'legend_size': 8,\\n 'y_on': True}\\n\\n t, y = solver(100) # Integrate solution\\n t_short = np.where((t >= 8) & (t <= 18))[0] # shorter time bounds for plots A and C\\n v, m, h, m_nap, h_na_p, n, m_t, h_t, m_p, m_n, h_n, z_sk, m_a, h_a, m_h, ca = y[:, ].T # Extract all variables\\n\\n \\\"\\\"\\\"\\n Explicitly calculate all currents: Extra constants duplicated from function dydt to calculate currents\\n \\\"\\\"\\\"\\n g_na_bar = 0.7\\n g_nap_bar = 0.05\\n g_k_bar = 1.3\\n g_p_bar = 0.05\\n g_leak = 0.005\\n g_a_bar = 1.0\\n e_na = 60\\n e_k = -80\\n e_leak = -50\\n e_ca = 40\\n g_t_bar = 0.1\\n g_n_bar = 0.05\\n g_sk_bar = 0.3\\n\\n \\\"\\\"\\\"\\n Calculate currents used in the plot\\n \\\"\\\"\\\"\\n i_na = g_na_bar * (m ** 3) * h * (v - e_na)\\n i_na_p = g_nap_bar * m_nap * h_na_p * (v - e_na)\\n i_k = g_k_bar * (n ** 4) * (v - e_k)\\n i_leak = g_leak * (v - e_leak)\\n i_t = g_t_bar * m_t * h_t * (v - e_ca)\\n i_n = g_n_bar * m_n * h_n * (v - e_ca)\\n i_p = g_p_bar * m_p * (v - e_ca)\\n i_sk = g_sk_bar * (z_sk ** 2) * (v - e_k)\\n i_a = g_a_bar * m_a * h_a * (v - e_k)\\n\\n plt.figure(figsize=(5, 3), dpi=96) # Create figure\\n\\n plt.subplot(2, 2, 1) # Generate subplot 1 (top left)\\n plt.plot(t[t_short], i_na[t_short], 'k-')\\n plt.plot(t[t_short], i_na_p[t_short], c='k', linestyle='dotted')\\n alter_figure(plot_settings) # Alter figure for publication\\n\\n plt.subplot(2, 2, 2) # Generate subplot 2 (top right)\\n plt.plot(t, i_t + i_n + i_p, 'k-')\\n plt.plot(t, i_t, c='k', linestyle='dotted')\\n plt.plot(t, i_p, 'k--')\\n plt.plot(t, i_n, 'k-.')\\n\\n plot_settings['y_limits'] = [-2.5, 0]\\n plot_settings['y_ticks'] = [-2.5, -2, -1.5, -1, -0.5, 0]\\n plot_settings['locator_size'] = 0.25\\n plot_settings['y_label'] = \\\"\\\"\\n plot_settings['legend'] = ['I-Ca', 'I-T', 'I-P', 'I-N']\\n alter_figure(plot_settings) # Alter figure for publication\\n\\n plt.subplot(2, 2, 3) # Generate subplot 3 (bottom left)\\n plt.plot(t[t_short], i_k[t_short], 'k-')\\n plt.plot(t[t_short], i_a[t_short], c='k', linestyle='dotted')\\n plt.plot(t[t_short], i_leak[t_short], 'k-.')\\n\\n plot_settings['y_limits'] = [0, 25]\\n plot_settings['y_ticks'] = [0, 5, 10, 15, 20, 25]\\n plot_settings['locator_size'] = 2.5\\n plot_settings['y_label'] = \\\"Current (nA)\\\"\\n plot_settings['legend'] = ['I-K', 'I-A', 'I-leak']\\n plot_settings['scale_size'] = 2\\n plot_settings['scale_loc'] = 2\\n alter_figure(plot_settings) # Alter figure for publication\\n\\n plt.subplot(2, 2, 4) # Generate subplot 4 (bottom left)\\n\\n plt.plot(t, i_sk, 'k-')\\n # plt.plot(sim_data_XPP[0][900:]-200,sim_data_XPP[34][900:]) # Isk for XPP data\\n\\n plot_settings['y_limits'] = [0, 1]\\n plot_settings['y_ticks'] = [0, 0.2, 0.4, 0.6, 0.8, 1]\\n plot_settings['locator_size'] = 0.2\\n plot_settings['y_label'] = \\\"\\\"\\n plot_settings['legend'] = ['I-SK']\\n plot_settings['scale_size'] = 20\\n plot_settings['scale_loc'] = 2\\n alter_figure(plot_settings, close=True) # Alter figure for publication\",\n \"def plot_delta_curve(deltas, prefix, tdir):\\n # get figure and axes\\n fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(6, 4))\\n\\n # plot reward curve\\n k = deltas['k']\\n d = deltas['d']\\n ax.plot(k, d, color='g')\\n ax.set_title('Delta Convergence ({})'.format(prefix))\\n ax.set_ylabel('Delta Value')\\n ax.set_xlabel('Episodes')\\n ax.grid(linestyle='dotted')\\n fig.tight_layout()\\n\\n # save figure\\n plotpath = get_abspath('{}_deltas.png'.format(prefix), tdir)\\n plt.savefig(plotpath)\\n plt.close()\",\n \"def softDeformer():\\n softDeformerUI()\",\n \"def demo():\\n ...\",\n \"def dynamic_figure(r=None,z=None,t=None):\\n global yt, t0, nt, zcut, theta, cnt, main_title\\n\\n if r is None:\\n RunTimeError(\\\"r is None\\\")\\n if z is None:\\n RunTimeError(\\\"z is None\\\")\\n if t is None:\\n RunTimeError(\\\"t is None\\\")\\n \\n theta = linspace( 0.0, 2.0*scipy.pi, num=100)\\n \\n R, Z = meshgrid(r,z)\\n \\n fu = FuModel(nt=100)\\n \\n ycube = fu.FuCon(R, Z, t) # ycube[:,:,:] DATA CUBE!!!\\n\\n #-----------------------------FIGURES------------------------------\\n fig = figure(figsize=(6,8.5))\\n \\n t0 = 0\\n yt = ycube[:,:,t0]\\n \\n titulo = 'Fu drug diffusion model: t = %07.2f' % t[t0]\\n main_title=fig.text(0.25, 0.95, titulo,\\n horizontalalignment='left',\\n fontproperties=FontProperties(size=16))\\n \\n cmap = cm.cool\\n subplots_adjust(hspace=0.0)\\n \\n subplot(211)\\n ax = gca()\\n im1 = imshow(yt,\\n interpolation='bilinear',\\n cmap=cmap,\\n origin='lower',\\n extent=(0,1.0,z[0],z[-1]),\\n aspect = 0.23\\n )\\n \\n xlabel(r'R = r/a', fontsize=14)\\n ylabel(r'Z = z/l', fontsize=14)\\n\\n subplot(212,aspect='equal')\\n ax = gca()\\n\\n #\\n #--- cylindrical cross-section\\n \\n RAD, THETA = meshgrid(r,theta)\\n Xpos = RAD*cos(THETA)\\n Ypos = RAD*sin(THETA)\\n \\n #\\n # top cap of cylinder\\n #\\n #zcut = len(z)-1\\n zcut = 0\\n if z[0] != 0.0:\\n zcut = int(len(z)/2+0.5)\\n title('Z = %f'%z[zcut],fontsize=16)\\n #\\n # Take a cross-section of the cylinder at some point Z ==> radius array of length len(r) \\n # -----\\n # Trick\\n # -----\\n # Now create a matrix[len(theta),len(r)] by replicating the above array len(theta) times\\n # along dimension 0\\n #\\n \\n zx = outer( ones(len(theta)), yt[zcut,:] )\\n \\n im2 = pcolormesh(Xpos, Ypos,\\n zx,\\n shading='flat',\\n cmap=cmap)\\n \\n xlabel(r'X/a', fontsize=14)\\n ylabel(r'Y/a', fontsize=14)\\n \\n #\\n #--- new axis for colorbar\\n #\\n norm = colors.Normalize(vmin=0.0, vmax=1.0)\\n im1.set_norm(norm)\\n im2.set_norm(norm)\\n im1.add_observer(im2)\\n \\n pos = ax.get_position()\\n l, b, w, h = getattr(pos, 'bounds', pos)\\n cax = axes([l+w+0.015, b, 0.025, h]) # setup colorbar axes\\n colorbar(im1, cax, orientation='vertical') \\n \\n manager = get_current_fig_manager()\\n \\n cnt = 0\\n files = []\\n nt = len(t)\\n #\\n #------------------------------------------------------------------\\n def updatefig(*args):\\n global yt, t0, nt, zcut, theta, cnt, main_title\\n \\n t0 += 1\\n if t0 > nt-1:\\n return False\\n \\n yt = ycube[:,:,t0]\\n zx = outer( ones(len(theta)), yt[zcut,:] )\\n Nx, Ny = yt.shape\\n im1.set_array(yt)\\n im2.set_array(ravel(zx[0:Nx-1,0:Ny-1]))\\n titulo = 'Fu drug diffusion model: t = %07.2f' % t[t0]\\n main_title.set_text(titulo)\\n manager.canvas.draw()\\n \\n #fname = '_tmp%03d.jpg' % t0\\n fname = '_tmp%03d.png' % t0\\n savefig(fname)\\n files.append(fname)\\n \\n cnt += 1\\n return True\\n #\\n #------------------------------------------------------------------\\n\\n cnt = 0\\n gobject.idle_add(updatefig)\\n\\n ioff()\\n show()\\n\\n command = \\\"ffmpeg -r 10 -sameq -i _tmp%03d.png test.mp4\\\"\\n #command = \\\"mencoder -ovc xvid -xvidencopts \\\" + \\\\\\n # \\\"pass=2:bitrate=15999:max_bframes=0 \\\" + \\\\\\n # \\\"-oac copy -mf fps=10:type=jpeg 'mf://_tmp*.jpg' -vf harddup -ofps 10 \\\" + \\\\\\n # \\\"-noskip -of avi -o outputfile.avi\\\"\\n os.system(command)\\n for fname in files: os.remove(fname) #clean up\\n\\n return True\",\n \"def show():\\n setup()\\n plt.show()\",\n \"def run_pendulum_example(duration=1.0, playback=True, show=True):\\n\\n builder = DiagramBuilder()\\n plant, scene_graph = AddMultibodyPlantSceneGraph(builder, 0.0)\\n parser = Parser(plant)\\n parser.AddModelFromFile(FindResourceOrThrow(\\n \\\"drake/examples/pendulum/Pendulum.urdf\\\")\\n )\\n plant.WeldFrames(plant.world_frame(), plant.GetFrameByName(\\\"base\\\"))\\n plant.Finalize()\\n\\n pose_bundle_output_port = scene_graph.get_pose_bundle_output_port()\\n T_VW = np.array([[1., 0., 0., 0.],\\n [0., 0., 1., 0.],\\n [0., 0., 0., 1.]])\\n visualizer = builder.AddSystem(PlanarSceneGraphVisualizer(\\n scene_graph, T_VW=T_VW,\\n xlim=[-1.2, 1.2], ylim=[-1.2, 1.2], show=show))\\n \\n builder.Connect(pose_bundle_output_port, visualizer.get_input_port(0))\\n if playback:\\n visualizer.start_recording()\\n \\n diagram = builder.Build()\\n simulator = Simulator(diagram)\\n simulator.Initialize()\\n simulator.set_target_realtime_rate(1.0)\\n\\n # Fix the input port to zero\\n plant_context = diagram.GetMutableSubsystemContext(\\n plant, simulator.get_mutable_context()\\n )\\n plant.get_actuation_input_port().FixValue(\\n plant_context, np.zeros(plant.num_actuators())\\n )\\n plant_context.SetContinuousState([0.5, 0.1])\\n simulator.AdvanceTo(duration)\\n\\n if playback:\\n visualizer.stop_recording()\\n ani = visualizer.get_recording_as_animation()\\n return ani\\n else:\\n return None\",\n \"def __init__(self):\\r\\n EasyFrame.__init__(self, title=\\\"Investment Calculator\\\")\\r\\n self.addLabel(text=\\\"Initial amount\\\", row=0, column=0)\\r\\n self.addLabel(text=\\\"Number of years\\\", row=1, column=0)\\r\\n self.addLabel(text=\\\"Interest rate in %\\\", row=2, column=0)\\r\\n self.amount = self.addFloatField(value=0.0, row=0, column=1)\\r\\n self.period = self.addIntegerField(value=0, row=1, column=1)\\r\\n self.rate = self.addIntegerField(value=0, row=2, column=1)\\r\\n\\r\\n self.outputArea = self.addTextArea(\\\"\\\", row=4, column=0, columnspan=2, width=50, height=15)\\r\\n\\r\\n self.compute = self.addButton(text=\\\"Compute\\\", row=3, column=0, columnspan=2, command=self.compute)\",\n \"def main():\\n viewer = Viewer()\\n\\n # paramètre de transformation des paramètres\\n #sol\\n ground_size = 512\\n ground_offset = 20\\n\\n #dinosaure\\n characters_offset_x = 0\\n characters_offset_y = -20\\n characters_offset_z = 0\\n characters_scale = 15\\n characters_rotate_deg = 180\\n\\n #forêt\\n forest_offset = -15\\n forest_scale = 1.5\\n\\n #skybox\\n Skysphere_scale = 3\\n\\n characters = Node(transform = translate(characters_offset_x, characters_offset_y, characters_offset_z) @ scale(characters_scale) @ rotate(axis=(0, 1, 0), angle = characters_rotate_deg))\\n characters.add(*load_skinned(\\\"dino/Dinosaurus_roar.dae\\\"))\\n\\n forest = Node(transform = translate(0, forest_offset, 0) @ scale(forest_scale))\\n forest.add(*load_textured(\\\"trees9/forest.obj\\\"))\\n\\n ground = Node(transform = translate(-ground_size>>1, ground_offset, -ground_size>>1))\\n ground.add(sol(ground_size))\\n\\n Skysphere = Node(transform = scale(Skysphere_scale))\\n Skysphere.add(*load_textured(\\\"Skysphere/skysphere.obj\\\"))\\n\\n scene = Node(transform = identity(), children = [characters, forest, ground, Skysphere])\\n\\n viewer.add(scene)\\n\\n viewer.run()\",\n \"def switch_context(self, new_location):\\n #Clear Figures to avoid memory leak\\n for figure in self.figures:\\n figure.clear()\\n plt.close(figure)\\n \\n #Close the exisiting display\\n self.destroy()\\n \\n #Generate user interface\\n UI = SD_UI(tuning = self.tuning_flag,\\n location = new_location,\\n language = self.language,\\n arrangment = self.arrangment)\\n \\n #Run the new user interface\\n UI.mainloop()\",\n \"def abrir_demo(self, widget, data=None):\\n\\t\\tself.w3.hide()\\n\\t\\tself.w5.show_all()\",\n \"def dynamics(self,eta,nu,u_actual,u_control,sampleTime): \\n \\n # Current velocities\\n u_c = self.V_c * math.cos(self.beta_c - eta[5]) # current surge velocity\\n v_c = self.V_c * math.sin(self.beta_c - eta[5]) # current sway velocity \\n \\n nu_c = np.array([u_c,v_c,0,0,0,0],float) # current velocity vector\\n nu_r = nu - nu_c # relative velocity vector\\n \\n U_r = math.sqrt( nu_r[0]**2 + nu_r[1]**2 ) # relative speed\\n \\n # Rudder command and actual rudder angle\\n delta_c = u_control[0]\\n delta = u_actual[0]\\n \\n # Rudder forces and moment (Fossen 2021, Chapter 9.5.1)\\n b = 0.7 * self.T # rudder height\\n AR = b**2 / self.Lambda # aspect ratio: Lamdba = b**2/AR \\n CN = 6.13 * self.Lambda / ( self.Lambda + 2.25 ) # normal coefficient\\n t_R = 1 - 0.28 * self.Cb - 0.55\\n a_H = 0.4\\n x_R = -0.45 * self.L\\n x_H = -1.0 * self.L\\n\\n Xdd = -0.5 * ( 1 - t_R ) * self.rho * U_r**2 * AR * CN\\n Yd = -0.25 * ( 1 + a_H ) * self.rho * U_r**2 * AR * CN \\n Nd = -0.25 * ( x_R + a_H * x_H ) * self.rho * U_r**2 * AR * CN \\n \\n # Control forces and moment\\n delta_R = -delta # physical rudder angle (rad)\\n T = self.tau_X # thrust (N)\\n t_deduction = 0.1 # thrust deduction number\\n tau1 = ( 1 - t_deduction ) * T - Xdd * math.sin( delta_R )**2 \\n tau2 = -Yd * math.sin( 2 * delta_R ) \\n tau6 = -Nd * math.sin( 2 * delta_R ) \\n tau = np.array( [ tau1, tau2, tau6 ],float) \\n \\n # Linear maneuvering model\\n T_surge = self.L # approx. time constant in surge (s)\\n xg = 0 # approx. x-coordinate, CG (m) \\n \\n # 3-DOF ship model\\n [M,N] = clarke83(U_r,self.L, self.B, self.T,self.Cb,self.R66,xg,T_surge)\\n Minv = np.linalg.inv(M)\\n nu3 = np.array( [ nu_r[0], nu_r[1], nu_r[5] ]) \\n nu3_dot = np.matmul( Minv, tau - np.matmul(N,nu3) ) \\n \\n # 6-DOF ship model\\n nu_dot = np.array( [ nu3_dot[0],nu3_dot[1],0,0,0,nu3_dot[2] ]) \\n\\n # Rudder angle saturation\\n if ( abs(delta) >= self.deltaMax * math.pi / 180 ):\\n delta = np.sign(delta) * self.deltaMax * math.pi / 180\\n \\n # Rudder dynamics\\n delta_dot = (delta_c - delta) / self.T_delta \\n\\n # Forward Euler integration [k+1]\\n nu = nu + sampleTime * nu_dot\\n delta = delta + sampleTime * delta_dot\\n\\n u_actual = np.array([delta],float) \\n\\n return nu, u_actual\",\n \"def recipe_dv360_editor(config, auth_dv, auth_sheet, auth_bigquery, recipe_name, recipe_slug, command):\\n\\n dataset(config, {\\n '__comment__':'Ensure dataset exists.',\\n 'auth':auth_bigquery,\\n 'dataset':recipe_slug\\n })\\n\\n drive(config, {\\n '__comment__':'Copy the default template to sheet with the recipe name',\\n 'auth':auth_sheet,\\n 'copy':{\\n 'source':'https://docs.google.com/spreadsheets/d/18G6cGo4j5SsY08H8P53R22D_Pm6m-zkE6APd3EDLf2c/',\\n 'destination':recipe_name\\n }\\n })\\n\\n dv_editor(config, {\\n '__comment':'Depending on users choice, execute a different part of the solution.',\\n 'auth_dv':auth_dv,\\n 'auth_sheets':auth_sheet,\\n 'auth_bigquery':auth_bigquery,\\n 'sheet':recipe_name,\\n 'dataset':recipe_slug,\\n 'command':command\\n })\",\n \"def vp_start_gui():\\n global top, app\\n app = tk.Tk()\\n ui_support.set_Tk_var()\\n top = Window(app)\\n top.price_panel.old_matrix_checkbox.select()\\n top.price_panel.select_old()\\n top.generic_panel.dynamic_stop_checkbox.select()\\n top.generic_panel.select_dynamic()\\n ui_support.init(app, top)\\n app.mainloop()\",\n \"def main():\\n geom = dde.geometry.TimeDomain(0, 3)\\n y0 = initial_condition()\\n for i in range(0,C)\\n # ic3 = dde.IC(geom, lambda X: 27, boundary, component=5)\\n data = dde.data.PDE(\\n geom,\\n SLE_DL,\\n [ic1, ic2, ic3, observe_y0, observe_y1, observe_y2],\\n num_domain=400,\\n num_boundary=2,\\n anchors=observe_t,\\n )\",\n \"def debug_with_new(shell, workflow):\\n projFilePath = \\\"/magnetic/test_project.ilp\\\"\\n\\n # New project\\n shell.createAndLoadNewProject(projFilePath)\\n\\n # Add a file\\n from ilastik.applets.dataSelection.opDataSelection import DatasetInfo\\n info = DatasetInfo()\\n #info.filePath = '/magnetic/gigacube.h5'\\n info.filePath = '/magnetic/synapse_small.npy'\\n #info.filePath = '/magnetic/singleslice.h5'\\n opDataSelection = workflow.dataSelectionApplet.topLevelOperator\\n opDataSelection.Dataset.resize(1)\\n opDataSelection.Dataset[0].setValue(info)\\n \\n # Set some features\\n import numpy\\n featApplet = workflow.applets[2]\\n featureGui = featApplet.gui\\n opFeatures = featApplet.topLevelOperator\\n # sigma: 0.3 0.7 1.0 1.6 3.5 5.0 10.0\\n selections = numpy.array( [[True, False, False, False, False, False, False],\\n [False, False, False, False, False, False, False],\\n [False, False, False, False, False, False, False], # ST EVs\\n [False, False, False, False, False, False, False],\\n [False, False, False, False, False, False, False], # GGM\\n [False, False, False, False, False, False, False]] )\\n opFeatures.SelectionMatrix.setValue(selections)\\n opFeatures.Scales.setValue( featureGui.ScalesList )\\n opFeatures.FeatureIds.setValue( featureGui.FeatureIds )\\n\\n # Select the labeling drawer\\n shell.setSelectedAppletDrawer(3)\\n\\n # Save the project\\n shell.onSaveProjectActionTriggered()\",\n \"def edit_pane_test_open(event):\\n c = event['c']\\n\\n if not hasattr(c, '__edit_pane_test'):\\n c.__edit_pane_test = True\\n\\n\\n class MinimalDemoProvider:\\n\\n def ns_provides(self):\\n return [(\\\"Demo editor\\\", \\\"__demo_provider_minimal_slider\\\")]\\n\\n def ns_provide(self, id_):\\n if id_ == \\\"__demo_provider_minimal_slider\\\":\\n w = LeoEditPane(c=c, mode='split')\\n return w\\n return None\\n\\n def ns_provider_id(self):\\n return \\\"__demo_provider_minimal\\\"\\n\\n c.free_layout.get_top_splitter().register_provider(MinimalDemoProvider())\\n\\n s = c.free_layout.get_top_splitter()\\n s.open_window(\\\"__demo_provider_minimal_slider\\\")\",\n \"def alldemos():\\n rundemo(24,fig=True)\\n rundemo(30,fig=True)\\n rundemo(31,fig=True)\\n rundemo(33)\\n rundemo(34)\",\n \"def main():\\n prior = np.asarray([2.0, 4e-6, 1e-4])\\n priorCov = np.diag(np.asarray([5.0, 1e-2, 1.0]))\\n independentVariable = np.arange(0.0, 5.0e-5, 1e-7)\\n \\n truth = np.asarray([2.5, 1.2e-5, 4e-4])\\n observation = (truth[0] * np.exp(-independentVariable/(truth[1])) + \\n truth[2] + np.random.normal(0.0, 0.1, independentVariable.shape))\\n observationError = (0.1 * np.sqrt(truth[0] * \\n np.exp(-independentVariable/(truth[1]))) + math.sqrt(truth[2]))\\n \\n model = decay(prior=prior, priorCov=priorCov, \\n otherModelParam=None, \\n parameterNames=[\\\"a\\\", \\\"tau\\\", \\\"offset\\\"], \\n verbose=2,\\n observation=observation, \\n observationError=observationError,\\n independentVariable=independentVariable)\\n \\n oe = OE(model=model, maxiter=8)\\n \\n oe()\\n \\n# print(oe)\\n# print(model)\\n# \\n# model.plot()\\n \\n return oe, model\",\n \"def main():\\n pycalcApp = QApplication(sys.argv)\\n pycalcView = PyCalcUi()\\n pycalcView.show()\\n model = evaluateExpression\\n PyCalcController(model=model, view=pycalcView)\\n sys.exit(pycalcApp.exec())\",\n \"def visualize_electrodes(self):\\n ShowElectrodesDialog(parent=self)\",\n \"def vis_d():\\n \\n data_gen = generator(fixed_noise)\\n# loss = d_loss(discriminator(data_gen), discriminator(grid))\\n loss = g_loss(discriminator(grid))\\n loss.backward()\\n \\n grads = - grid.grad.data.numpy()\\n grid.grad.data *= 0 \\n plt.quiver(X_grid, Y_grid, grads[:, 0], grads[:, 1], color='black',alpha=0.9)\",\n \"def main():\\n configuration = ConfigParser()\\n configuration.read_file(open('src/default.ini'))\\n configuration.read(['config.ini'])\\n push_exception_handler(reraise_exceptions=True)\\n # Create the GUI (this does NOT start the GUI event loop).\\n gui = GUI()\\n\\n # Create a Task and add it to a TaskWindow.\\n task = S4LVisualizationTask(configuration=configuration)\\n window = TaskWindow(size=(configuration.getint('Display', 'window_width'),\\n configuration.getint('Display', 'window_height')))\\n window.add_task(task)\\n\\n # Show the window.\\n window.open()\\n\\n # Start the GUI event loop.\\n gui.start_event_loop()\",\n \"def show_derivative(self):\\n for trace in self.plotWidget.plotDataItems:\\n dt = float(trace.attrs['dt'])\\n dtrace = np.diff(trace.data)\\n x = pgplot.make_xvector(dtrace, dt)\\n self.plotWidget.plot(x, dtrace, pen=pg.mkPen('r'))\",\n \"def run_shell(options):\\n from IPython import embed\\n embed()\",\n \"def view():\\r\\n # collect figures in list\\r\\n figures = list(map(plt.figure, plt.get_fignums()))\\r\\n # start app\\r\\n app = QtWidgets.QApplication(sys.argv)\\r\\n main = Main()\\r\\n\\r\\n if figures:\\r\\n for count, figure in enumerate(figures):\\r\\n # main names for figures\\r\\n name = f\\\"{figure.number}\\\"\\r\\n # aliases for figures\\r\\n titles = [figure.axes[0].get_title(loc=i) for i in [\\r\\n \\\"left\\\", \\\"center\\\", \\\"right\\\"]]\\r\\n titles = [i for i in titles if i]\\r\\n title = f\\\"{count+1}- {titles[0]}\\\" if titles else \\\"\\\"\\r\\n axes_labels = f\\\"{count+1}- {figure.axes[0].get_ylabel()} vs {figure.axes[0].get_xlabel()} \\\"\\r\\n fignum = f\\\"Figure {figure.number}\\\"\\r\\n # Append figure to App\\r\\n main.append_fig(title, axes_labels, fignum, name, figure)\\r\\n\\r\\n main.show()\\r\\n sys.exit(app.exec_())\",\n \"def ex13gui():\\n\\n #pylint: disable=E1101\\n root = tkcomponents.create('Simple interest')\\n\\n principal_label = rx.Observable.just('What is the principal amount?')\\n principal = tkcomponents.input_stream(root, principal_label, 0).map(decimal.Decimal)\\n\\n rate_label = rx.Observable.just('What is the rate?')\\n rate = tkcomponents.input_stream(root, rate_label, 1).map(decimal.Decimal)\\n\\n term_label = rx.Observable.just('What is the number of years?')\\n term = tkcomponents.input_stream(root, term_label, 2).map(int).map(decimal.Decimal)\\n\\n frequency_label = rx.Observable.just(\\n 'What is the number of times interest is compounded per year?')\\n frequency = tkcomponents.input_stream(root, frequency_label, 3).map(int).map(decimal.Decimal)\\n\\n tkcomponents.output_label(\\n root,\\n rx.Observable.combine_latest(principal, rate, term, frequency, calculate_amount), 4)\\n root.mainloop()\",\n \"def __init__(self, parent):\\n super(Demo5, self).__init__(parent)\\n self.angle = 0.0\\n self.replication = 1.0\\n self.offset = 0.0\\n self.deltaRep = 1\\n self.revolution = 0\\n self.stepsPer90 = 180\\n self.stepsLeft = self.stepsPer90\\n self.deltaAng = 90.0\\n self.deltaOff = 0.15\\n self.spin = True\\n self.x2yAspect = 1.0\\n self.texture = None\",\n \"def iplot_paulivec(rho, options=None):\\n\\n # HTML\\n html_template = Template(\\\"\\\"\\\"\\n <p>\\n <div id=\\\"paulivec_$divNumber\\\"></div>\\n </p>\\n \\\"\\\"\\\")\\n\\n # JavaScript\\n javascript_template = Template(\\\"\\\"\\\"\\n <script>\\n requirejs.config({\\n paths: {\\n qVisualization: \\\"https://qvisualization.mybluemix.net/q-visualizations\\\"\\n }\\n });\\n\\n require([\\\"qVisualization\\\"], function(qVisualizations) {\\n qVisualizations.plotState(\\\"paulivec_$divNumber\\\",\\n \\\"paulivec\\\",\\n $executions,\\n $options);\\n });\\n </script>\\n \\\"\\\"\\\")\\n\\n if not options:\\n options = {}\\n\\n # Process data and execute\\n div_number = str(time.time())\\n div_number = re.sub('[.]', '', div_number)\\n\\n if 'slider' in options and options['slider'] is True:\\n options['slider'] = 1\\n else:\\n options['slider'] = 0\\n\\n if 'show_legend' in options and options['show_legend'] is False:\\n options['show_legend'] = 0\\n else:\\n options['show_legend'] = 1\\n\\n data_to_plot = []\\n rho_data = process_data(rho)\\n data_to_plot.append(dict(\\n data=rho_data\\n ))\\n\\n html = html_template.substitute({\\n 'divNumber': div_number\\n })\\n\\n javascript = javascript_template.substitute({\\n 'divNumber': div_number,\\n 'executions': data_to_plot,\\n 'options': options\\n })\\n\\n display(HTML(html + javascript))\",\n \"def delta_vel(p1=database['K+'], p2=database['pi+'], p3=database['p+'], pmin=0, pmax=80):\\r\\n p_range = np.linspace(pmin, pmax, 1000)\\r\\n m1 = p1.mass\\r\\n m2 = p2.mass\\r\\n m3 = p3.mass\\r\\n dv2, dv3 = [], []\\r\\n for p in p_range:\\r\\n v1 = c*beta(p, m1)\\r\\n v2 = c*beta(p, m2)\\r\\n v3 = c*beta(p, m3)\\r\\n dv2.append(abs(v1-v2))\\r\\n dv3.append(abs(v1-v3))\\r\\n fig = plt.figure(figsize=[10, 5])\\r\\n ax = fig.add_subplot(1, 1, 1)\\r\\n# p1_name = r'K$^+$'\\r\\n# p2_name = r'$\\\\pi^+$'\\r\\n# p3_name = r'p$^+$'\\r\\n ax.plot(p_range, dv2, 'r', label=r'$\\\\left|v_{K^+}-v_{\\\\pi^+}\\\\right|$')\\r\\n ax.plot(p_range, dv3, 'b', label=r'$\\\\left|v_{K^+}-v_{p^+}\\\\right|$')\\r\\n ax.set_xlabel('p / GeV', fontsize=20)\\r\\n ax.set_ylabel(r'$\\\\left|\\\\Delta v\\\\right|$ / $ms^{-1}$', fontsize=20)\\r\\n ax.axvline(75, color='k', label='p = 75 GeV')\\r\\n ax.set_xticks(np.arange(pmin, pmax+1, 1))\\r\\n ax.set_xticklabels(np.arange(pmin, pmax+1, 1))\\r\\n ax.grid()\\r\\n ax.minorticks_on()\\r\\n ax.set_xlim(pmin, pmax)\\r\\n# ax.set_ylim(np.min(v1+v2))\\r\\n ax.legend(fontsize=20, loc=[0.65, 0.2])\\r\\n plt.show\\r\\n return\",\n \"def Deboucle3D(*args):\\n return _BRepAlgo.BRepAlgo_Tool_Deboucle3D(*args)\",\n \"def create_figure_new(self):\\n kw = {}\\n self.p = figure(plot_height=400, plot_width=400, tools='pan,wheel_zoom,box_zoom,reset,hover', **kw)\\n self.p.circle(x=[0],y=[0])\",\n \"def editor_multi_agent_example():\\n agent_definitions = [\\n AgentDefinition(\\\"uav0\\\", agents.UavAgent, [sensors.RGBCamera, sensors.LocationSensor]),\\n AgentDefinition(\\\"uav1\\\", agents.UavAgent, [sensors.LocationSensor, sensors.VelocitySensor])\\n ]\\n env = HolodeckEnvironment(agent_definitions, start_world=False)\\n\\n cmd0 = np.array([0, 0, -2, 10])\\n cmd1 = np.array([0, 0, 5, 10])\\n\\n for i in range(10):\\n env.reset()\\n env.act(\\\"uav0\\\", cmd0)\\n env.act(\\\"uav1\\\", cmd1)\\n for _ in range(1000):\\n states = env.tick()\",\n \"def viewerSettings():\\n node = nuke.thisNode()\\n node.knob('near').setValue(100)\\n node.knob('far').setValue(500000)\\n node.knob('grid_display').setValue(False)\\n node.knob('gl_lighting').setValue(1)\",\n \"def debug():\\n # \\\"EMBEDDED_MODE\\\" is True precisely when the Sage notebook is running.\\n from sage.plot.plot import EMBEDDED_MODE\\n if not EMBEDDED_MODE:\\n # Must be the command line, so suggest using the IPython debugger.\\n print(\\\"You should use %debug on the command line.\\\")\\n else:\\n # Create the Debug object and make it interactive.\\n Debug().interact()\",\n \"def actuator_environment(self):\\n self.INPUT_DATA_SIZE = 23\\n self.pushButton_reload.setEnabled(0)\\n self.listWidget_link.setEnabled(0)\\n self.listWidget_link.clear()\",\n \"def show_derivativeCursor(self, var):\\n if self.derivativeThreshold.isChecked(): \\n self.plotWidget.derivativeCursorThsPos = 0\\n self.plotWidget.derivativeCursorThs = pg.InfiniteLine(pos=self.plotWidget.derivativeCursorThsPos,\\n angle=0, movable=True, pen=pg.mkPen('#FFD000', width=2))\\n self.plotWidget.addItem(self.plotWidget.derivativeCursorThs)\\n self.plotWidget.derivativeCursorThs.sigPositionChanged.connect(self.update_derivativeThreshold)\\n else:\\n self.plotWidget.derivativeCursorThsPos = []\\n self.plotWidget.removeItem(self.plotWidget.derivativeCursorThs)\",\n \"def modelEditor(*args, activeComponentsXray: bool=True, activeCustomEnvironment: AnyStr=\\\"\\\",\\n activeCustomGeometry: Union[AnyStr, bool]=\\\"\\\", activeCustomLighSet: Union[AnyStr,\\n bool]=\\\"\\\", activeCustomOverrideGeometry: Union[AnyStr, bool]=\\\"\\\",\\n activeCustomRenderer: Union[AnyStr, bool]=\\\"\\\", activeOnly: bool=True,\\n activeShadingGraph: Union[AnyStr, bool]=\\\"\\\", activeView: bool=True, addObjects:\\n AnyStr=\\\"\\\", addSelected: bool=True, addSelectedObjects: bool=True, allObjects:\\n bool=True, backfaceCulling: bool=True, bufferMode: Union[AnyStr, bool]=\\\"\\\",\\n bumpResolution: Union[List[int, int], bool]=None, camera: Union[AnyStr,\\n bool]=\\\"\\\", cameraName: AnyStr=\\\"\\\", cameraSet: Union[AnyStr, bool]=\\\"\\\",\\n cameraSetup: bool=True, cameras: bool=True, capture: Union[AnyStr, bool]=\\\"\\\",\\n captureSequenceNumber: Union[int, bool]=0, clipGhosts: bool=True, cmEnabled:\\n bool=True, colorMap: bool=True, colorResolution: Union[List[int, int],\\n bool]=None, control: bool=True, controlVertices: bool=True, cullingOverride:\\n Union[AnyStr, bool]=\\\"\\\", default: bool=True, defineTemplate: AnyStr=\\\"\\\",\\n deformers: bool=True, dimensions: bool=True, displayAppearance: Union[AnyStr,\\n bool]=\\\"\\\", displayLights: Union[AnyStr, bool]=\\\"\\\", displayTextures: bool=True,\\n docTag: Union[AnyStr, bool]=\\\"\\\", dynamicConstraints: bool=True, dynamics:\\n bool=True, editorChanged: Union[Script, bool]=None, exists: bool=True,\\n exposure: Union[float, bool]=0.0, filter: Union[AnyStr, bool]=\\\"\\\",\\n filteredObjectList: bool=True, fluids: bool=True, fogColor: Union[List[float,\\n float, float, float], bool]=None, fogDensity: Union[float, bool]=0.0, fogEnd:\\n Union[float, bool]=0.0, fogMode: Union[AnyStr, bool]=\\\"\\\", fogSource:\\n Union[AnyStr, bool]=\\\"\\\", fogStart: Union[float, bool]=0.0, fogging: bool=True,\\n follicles: bool=True, forceMainConnection: Union[AnyStr, bool]=\\\"\\\", gamma:\\n Union[float, bool]=0.0, greasePencils: bool=True, grid: bool=True, hairSystems:\\n bool=True, handles: bool=True, headsUpDisplay: bool=True, height: bool=True,\\n highlightConnection: Union[AnyStr, bool]=\\\"\\\", hulls: bool=True, ignorePanZoom:\\n bool=True, ikHandles: bool=True, imagePlane: bool=True, interactive: bool=True,\\n interactiveBackFaceCull: bool=True, interactiveDisableShadows: bool=True,\\n isFiltered: bool=True, jointXray: bool=True, joints: bool=True, lights:\\n bool=True, lineWidth: Union[float, bool]=0.0, locators: bool=True,\\n lockMainConnection: bool=True, lowQualityLighting: bool=True,\\n mainListConnection: Union[AnyStr, bool]=\\\"\\\", manipulators: bool=True,\\n maxConstantTransparency: Union[float, bool]=0.0, maximumNumHardwareLights:\\n bool=True, modelPanel: AnyStr=\\\"\\\", motionTrails: bool=True, nCloths: bool=True,\\n nParticles: bool=True, nRigids: bool=True, noUndo: bool=True, nurbsCurves:\\n bool=True, nurbsSurfaces: bool=True, objectFilter: Union[Script, bool]=None,\\n objectFilterList: Union[Script, bool]=None, objectFilterListUI: Union[Script,\\n bool]=None, objectFilterShowInHUD: bool=True, objectFilterUI: Union[Script,\\n bool]=None, occlusionCulling: bool=True, panel: Union[AnyStr, bool]=\\\"\\\", parent:\\n Union[AnyStr, bool]=\\\"\\\", particleInstancers: bool=True, pivots: bool=True,\\n planes: bool=True, pluginObjects: Union[List[AnyStr, bool], List[List[AnyStr,\\n bool]]]=None, pluginShapes: bool=True, polymeshes: bool=True,\\n queryPluginObjects: Union[AnyStr, bool]=\\\"\\\", removeSelected: bool=True,\\n rendererDeviceName: bool=True, rendererList: bool=True, rendererListUI:\\n bool=True, rendererName: Union[AnyStr, bool]=\\\"\\\", rendererOverrideList:\\n bool=True, rendererOverrideListUI: bool=True, rendererOverrideName:\\n Union[AnyStr, bool]=\\\"\\\", resetCustomCamera: bool=True, sceneRenderFilter:\\n Union[AnyStr, bool]=\\\"\\\", selectionConnection: Union[AnyStr, bool]=\\\"\\\",\\n selectionHiliteDisplay: bool=True, setSelected: bool=True, shadingModel:\\n Union[int, bool]=0, shadows: bool=True, smallObjectCulling: bool=True,\\n smallObjectThreshold: Union[float, bool]=0.0, smoothWireframe: bool=True,\\n sortTransparent: bool=True, stateString: bool=True, stereoDrawMode: bool=True,\\n strokes: bool=True, subdivSurfaces: bool=True, textureAnisotropic: bool=True,\\n textureCompression: bool=True, textureDisplay: Union[AnyStr, bool]=\\\"\\\",\\n textureEnvironmentMap: bool=True, textureHilight: bool=True, textureMaxSize:\\n Union[int, bool]=0, textureMemoryUsed: bool=True, textureSampling: Union[int,\\n bool]=0, textures: bool=True, toggleExposure: bool=True, toggleGamma: bool=True,\\n transpInShadows: bool=True, transparencyAlgorithm: Union[AnyStr, bool]=\\\"\\\",\\n twoSidedLighting: bool=True, unParent: bool=True, unlockMainConnection:\\n bool=True, updateColorMode: bool=True, updateMainConnection: bool=True,\\n useBaseRenderer: bool=True, useColorIndex: bool=True, useDefaultMaterial:\\n bool=True, useInteractiveMode: bool=True, useRGBImagePlane: bool=True,\\n useReducedRenderer: bool=True, useTemplate: AnyStr=\\\"\\\", userNode: Union[AnyStr,\\n bool]=\\\"\\\", viewObjects: bool=True, viewSelected: bool=True, viewTransformName:\\n Union[AnyStr, bool]=\\\"\\\", viewType: bool=True, width: bool=True,\\n wireframeBackingStore: bool=True, wireframeOnShaded: bool=True, xray: bool=True,\\n q=True, query=True, e=True, edit=True, **kwargs)->Union[AnyStr, Any]:\\n pass\",\n \"def create_exercise(exam_date, num, path_ex_folder, path_yaml):\\n global images_to_add\\n global REL_PATH_IMAGES\\n REL_PATH_IMAGES = 'img_' + exam_date\\n images_to_add = []\\n path_mode_free = path_ex_folder + '/modo_libero/' # new folder for the considered submission mode\\n os.mkdir(path_mode_free)\\n exer = read_exercise_yaml(path_yaml) # reading the given yaml\\n notebook = nb.v4.new_notebook() # creating the new notebook\\n #print(exer['name'])\\n if exer['name'] in ('graphs_flow','graphs_trees', 'graphs_planarity','graphs_paths'):\\n insert_graph_import(notebook) #required graph import\\n insert_no_scroll(notebook) #no scroll of output div\\n else:\\t\\n insert_import_mode_free(notebook) # required import\\n insert_start_button(notebook) # start button to run cells with tag 'run_start'\\n insert_hide_code(notebook) # hide all code cells\\n insert_user_bar_lib(notebook,path_ex_folder) # insert user_bar.py in a code cell\\n insert_heading(notebook, exer['title']) # heading with title\\n insert_description1(notebook, exer['description1'], exam_date, path_ex_folder) # description 1\\n if 'description2' in exer:\\n insert_description2(notebook, exer['description2']) # description 2\\n insert_tasks(notebook, exer['tasks']) # inserting the several tasks\\n if exer['name'] in ('lp_duality', 'lp_interactive', 'lp_modelling', 'lp_two_phases'): # other libraries needed for some types of exercises\\n insert_needed_import(notebook, exer['name'])\\n if int(num) >= 10: # writing the notebook and saving it in the correct folder\\n note_name = 'Esercizio_' + num + '.ipynb'\\n prev_folder = 'esercizio_' + num\\n else:\\n note_name = 'Esercizio_0' + num + '.ipynb'\\n prev_folder = 'esercizio_0' + num\\n insert_rendition(notebook, note_name)\\n nb.write(notebook, note_name)\\n os.rename(os.getcwd()+ '/' + note_name, path_mode_free + '/' + note_name)\\n os.system(\\\"jupyter trust \\\" + path_mode_free + note_name) # signing the notebook in order to make it trusted\\n insert_suppl_folders(path_mode_free) # inserting the supplementary folders (i.e., 'allegati', 'img')\\n if exer['name'] in ('graphs_flow','graphs_trees', 'graphs_planarity','graphs_paths'):\\n insert_graph_folder(path_mode_free)\\n if 'tags' in exer:\\n e_dict = {'title':exer['title'],'tags':exer['tags'],'tot_points':0,'link':'http://127.0.0.1:8888/notebooks/'+prev_folder+'/modo_libero/' + note_name, 'tasks':exer['tasks']}\\n else:\\n\\t e_dict = {'title':exer['title'],'tags':[],'tot_points':0,'link':'http://127.0.0.1:8888/notebooks/'+prev_folder+'/modo_libero/' + note_name, 'tasks':exer['tasks']}\\n return e_dict\",\n \"def plots():\\n out = interactive_output(generate_plots, {'gsize':gridSlider, 'ra':RABox, 'ra':RASlider, 'dec':DECBox, 'dec':DECSlider, 'ang':radBox, 'ang':radSlider, 'style':hexDrop})\\n return display(widgrid, out)\",\n \"def run_interactive():\\n from cherrypy import engine\\n \\n # This is what quickstart does but we don't block\\n engine.signals.subscribe()\\n engine.start()\\n #engine.block()\",\n \"def deactivate(self, newmode = None):\\n\\t\\tself.urmaswin.Show(0) \\n\\t\\tself.urmaswin.enableRendering(0) \\n\\t\\tself.urmaswin.controlpanel.Show(0)\\n\\t\\tself.visualizer.sliderWin.SetDefaultSize(self.origSliderWinSize)\\n\\n\\t\\tif not self.doLockSliderPanel and newmode != \\\"3d\\\":\\n\\t\\t\\tprint \\\"\\\\n\\\\n*** DEACTIVATING ANIMATOR\\\\n\\\"\\n\\t\\t\\tself.visualizer.setCurrentSliderPanel(self.visualizer.sliderPanel) \\n\\t\\t\\tself.visualizer.sliderPanel.Show(1)\\n\\t\\tif newmode != \\\"3d\\\":\\n\\t\\t\\tself.menuManager.mainToolbar.EnableTool(MenuManager.ID_ADJUST, 1)\\n\\t\\t\\tself.menuManager.mainToolbar.EnableTool(MenuManager.ID_RESTORE, 1)\\n\\t\\t\\tself.menuManager.mainToolbar.EnableTool(MenuManager.ID_COLOCALIZATION, 1)\\n\\t\\t\\tself.menuManager.mainToolbar.EnableTool(MenuManager.ID_COLORMERGING, 1)\\n\\t\\tself.urmaswin.cleanMenu()\",\n \"def notebook():\\n pass\",\n \"def notebook():\\n pass\",\n \"def agentbasedsim_evol(aenv, pienv, xi,\\n L=1, nind=10, ngens=[100],\\n mutrate=1e-4, mutsize=0.025,\\n ainit=None, piinit=None, pupinit=None, epsiloninit=None,\\n evolvep=True,\\n evolveq=True,\\n evolvepup=False,\\n evolveepsilon=False,\\n prng=None):\\n\\n prng = prng if prng else np.random\\n\\n mutrateisnumber = isinstance(mutrate, numbers.Number) \\n mutsizeisnumber = isinstance(mutsize, numbers.Number) \\n \\n alpha, beta = from_api(aenv, pienv)\\n\\n # all parameters need to be in array form if cython acceleration is used\\n if usecstepmarkov:\\n alpha = _arrayify(alpha, L)\\n beta = _arrayify(beta, L)\\n\\n # p,q can now change dynamically.\\n if (ainit is not None) and (piinit is not None) and (pupinit is not None) and (epsiloninit is not None):\\n # Initialize all to the same value\\n pinit, qinit = from_api(ainit, piinit)\\n p = np.clip(np.ones((nind, L)) * pinit, 0, 1)\\n q = np.clip(np.ones((nind, L)) * qinit, 0, 1)\\n pup = np.clip(np.ones((nind, L)) * pupinit, 0, 1)\\n epsilon = np.clip(np.ones(nind) * epsiloninit, 0, 1)\\n else:\\n # Initialize uniformly\\n p = prng.random((nind, L))\\n q = prng.random((nind, L))\\n pup = prng.random((nind, L))\\n epsilon = prng.random(nind)\\n \\n # Initialize all to the same value, then add randomness\\n #p = np.clip(np.ones((nind, L)) * pinit + np.random.normal(scale = mutsizeinit, size = (nind, L)), 0, 1)\\n #q = np.clip(np.ones((nind, L)) * qinit + np.random.normal(scale = mutsizeinit, size = (nind, L)), 0, 1)\\n # Initialize uniformly in a, pi\\n #p, q = from_api(prng.random((nind, L)), prng.random((nind, L)))\\n\\n env = np.zeros(L, dtype = bool)\\n ind = np.zeros((nind, L), dtype = bool)\\n\\n totoffsprings = np.zeros(max(ngens))\\n as_ = np.zeros((len(ngens), L))\\n pis = np.zeros((len(ngens), L))\\n pups = np.zeros((len(ngens), L))\\n epsilons = np.zeros(len(ngens))\\n\\n # number of generations at which to output\\n ngencounter = 0\\n # for performance: avoid array look up at each step\\n ngennext = ngens[0]-1\\n\\n # for performance: precomputations\\n # (checked if actually saving significant amounts of time)\\n nind_arange = np.arange(nind)\\n if mutrateisnumber:\\n totmutrate = mutrate * L * nind\\n # if mutsize is constant then assign it for all generations\\n if mutsizeisnumber:\\n mutsize_gen = mutsize\\n\\n for generation in range(max(ngens)):\\n # time step environment\\n rand = prng.rand(L)\\n env = stepmarkov(env, alpha, beta, rand)\\n # acquire via crispr\\n rand = prng.rand(nind, L)\\n ind, nacquired = stepcrispr(env, ind, pup, rand)\\n # calculate growth rate\\n noffspring = xi(ind, env, epsilon, pup)\\n\\n # for performance: use np.add.reduce directly to avoid np.sum overhead\\n #totoffspring = noffspring.sum()\\n totoffspring = np.add.reduce(noffspring)\\n # time step population\\n indoffspring = nind_arange.repeat(prng.multinomial(nind, noffspring/totoffspring))\\n parent = ind.take(indoffspring, axis=0)\\n rand = prng.rand(nind, L)\\n ind = stepmarkov2d(parent, p, q, rand)\\n # inherit strategies\\n p = p.take(indoffspring, axis=0)\\n q = q.take(indoffspring, axis=0)\\n pup = pup.take(indoffspring, axis=0)\\n epsilon = epsilon.take(indoffspring, axis=0)\\n # mutate strategies\\n if not mutrateisnumber:\\n totmutrate = mutrate(generation) * L * nind\\n if not mutsizeisnumber:\\n mutsize_gen = mutsize(generation)\\n for c in range(prng.poisson(totmutrate)):\\n # pick random site \\n i, j = prng.randint(nind), prng.randint(L)\\n if evolvep:\\n ptmp = p[i, j] + prng.normal(scale=mutsize_gen)\\n # ensure that there is at least some switching\\n # needed for sensible definition of pi\\n while (ptmp <= 0.0) or (ptmp > 1):\\n ptmp = p[i, j] + prng.normal(scale=mutsize_gen)\\n p[i, j] = ptmp\\n if evolveq:\\n qtmp = q[i, j] + prng.normal(scale=mutsize_gen)\\n while (qtmp <= 0.0) or (qtmp > 1):\\n qtmp = q[i, j] + prng.normal(scale=mutsize_gen)\\n q[i, j] = qtmp\\n if evolvepup:\\n puptmp = pup[i, j] + prng.normal(scale=mutsize_gen)\\n while (puptmp <= 0.0) or (puptmp > 1):\\n puptmp = pup[i, j] + prng.normal(scale=mutsize_gen)\\n pup[i, j] = puptmp \\n if evolveepsilon:\\n epsilontmp = epsilon[i] + prng.normal(scale=mutsize_gen)\\n while (epsilontmp <= 0.0) or (epsilontmp > 1):\\n epsilontmp = epsilon[i] + prng.normal(scale=mutsize_gen)\\n epsilon[i] = epsilontmp \\n\\n \\n # store data\\n totoffsprings[generation] = totoffspring\\n if generation == ngennext:\\n a, pi = to_api(p, q)\\n as_[ngencounter] = a.mean(axis=0)\\n pis[ngencounter] = pi.mean(axis=0)\\n if evolvepup:\\n pups[ngencounter] = pup.mean(axis=0)\\n if evolveepsilon:\\n epsilons[ngencounter] = epsilon.mean(axis=0)\\n ngencounter += 1\\n if ngencounter >= len(ngens):\\n break\\n ngennext = ngens[ngencounter]-1\\n\\n return totoffsprings / nind, pis, as_, pups, epsilons\",\n \"def editor():\\n pass\",\n \"def plot_vanHove_dt(comp,conn,start,step_size,steps):\\n \\n (fin,) = conn.execute(\\\"select fout from comps where comp_key = ?\\\",comp).fetchone()\\n (max_step,) = conn.execute(\\\"select max_step from vanHove_prams where comp_key = ?\\\",comp).fetchone()\\n Fin = h5py.File(fin,'r')\\n g = Fin[fd('vanHove',comp[0])]\\n\\n temp = g.attrs['temperature']\\n dtime = g.attrs['dtime']\\n\\n\\n # istatus = plots.non_i_plot_start()\\n \\n fig = mplt.figure()\\n fig.suptitle(r'van Hove dist temp: %.2f dtime: %d'% (temp,dtime))\\n dims = figure_out_grid(steps)\\n \\n plt_count = 1\\n outs = []\\n tmps = []\\n for j in range(start,start+step_size*steps, step_size):\\n (edges,count,x_lim) = _extract_vanHove(g,j+1,1,5)\\n if len(count) < 50:\\n plt_count += 1\\n continue\\n #count = count/np.sum(count)\\n \\n sp_arg = dims +(plt_count,)\\n ax = fig.add_subplot(*sp_arg)\\n ax.grid(True)\\n\\n \\n alpha = _alpha2(edges,count)\\n \\n ax.set_ylabel(r'$\\\\log{P(N)}$')\\n ax.step(edges,np.log((count/np.sum(count))),lw=2)\\n ax.set_title(r'$\\\\alpha_2 = %.2f$'%alpha + ' j:%d '%j )\\n ax.set_xlim(x_lim)\\n plt_count += 1\\n\\n mplt.draw()\\n\\n # plots.non_i_plot_start(istatus)\\n\\n del g\\n Fin.close()\\n del Fin\",\n \"def main():\\n # Create our array of x values\\n x = np.linspace(-np.pi, np.pi)\\n\\n # plot x and sin(x)\\n plt.plot(x, np.sin(x))\\n\\n # plot x and cos(x)\\n plt.plot(x, np.cos(x))\\n\\n #Add title and labels\\n plt.title(\\\"Graph of Sine and Cosine\\\")\\n plt.xlabel(\\\"Radians\\\")\\n\\n # Show graph in matplotlib gui\\n plt.show()\",\n \"def storefront_dimension():\\n\\n\\tfrom rpw.ui.forms import Label, ComboBox, Separator, Button, FlexForm\\n\\n\\tcurrentView = uidoc.ActiveView\\n\\ttheta = math.pi*0.5\\n\\taxis_z = Autodesk.Revit.DB.Line.CreateBound(XYZ(0,0,0),XYZ(0,0,1))\\n\\tsearchDist = 4\\n\\toffsetDim = 1\\n\\n\\t#Get the linear dimension types in the doc to select from\\n\\tallDimensionTypes = GetAllElements(doc, None, Autodesk.Revit.DB.DimensionType)\\n\\tlinearDimensionTypes = {}\\n\\n\\tautodimOptions = {\\\"Laser Layout\\\": \\\"Laser Layout\\\", \\\"Partition Plan\\\" : \\\"Partition Plan\\\"}\\n\\n\\tfor elemId in allDimensionTypes:\\n\\t\\tdT = doc.GetElement(elemId)\\n\\t\\tif \\\"Linear\\\" in dT.FamilyName:\\n\\t\\t\\tdTName = dT.get_Parameter(BuiltInParameter.ALL_MODEL_TYPE_NAME).AsString()\\n\\t\\t\\tlinearDimensionTypes[dTName] = dT\\n\\n\\n\\t#Select dimension settings\\n\\tcomponents = [Label('Dimension Distance From Datums'),\\n\\t\\t\\t\\t\\tComboBox(\\\"combobox1\\\", {\\\"4'-0''\\\": 4.0, \\\"8'-0''\\\": 8.0}),\\n\\t\\t\\t\\t\\tLabel('Dimension Type'),\\n\\t\\t\\t\\t\\tComboBox(\\\"combobox2\\\", linearDimensionTypes),\\n\\t\\t\\t\\t\\tLabel('Dimension Function'),\\n\\t\\t\\t\\t\\tComboBox(\\\"combobox3\\\", autodimOptions),\\n\\t\\t\\t\\t\\tLabel('System'),\\n\\t\\t\\t\\t\\tComboBox(\\\"combobox4\\\", {\\\"Elite\\\": \\\"Elite\\\", \\\"MODE\\\": \\\"MODE\\\", \\\"Extravega\\\": \\\"Extravega\\\"}),\\n\\t\\t\\t\\t\\tSeparator(),\\n\\t\\t\\t\\t\\tButton('Go')]\\n\\n\\tform = FlexForm(\\\"Storefront Auto Dim\\\", components)\\n\\tform.show()\\n\\n\\tif not form.values:\\n\\t\\tsys.exit()\\n\\telse: \\n\\t\\tsearchDist = form.values[\\\"combobox1\\\"]\\n\\t\\tselectedDimType = form.values[\\\"combobox2\\\"]\\n\\t\\tautodimOption = form.values[\\\"combobox3\\\"]\\n\\t\\tsystemName = form.values[\\\"combobox4\\\"]\\n\\n\\tif autodimOption == \\\"Laser Layout\\\":\\n\\n\\t\\t#Get walls for datum lines to measure to\\n\\t\\tallWalls = GetAllElements(doc, BuiltInCategory.OST_Walls, Autodesk.Revit.DB.Wall, currentView=True)\\n\\t\\t#storefrontWalls = FilterElementsByName(doc, allWalls, [\\\"Storefront\\\",\\\"Storefront\\\"], False)\\n\\n\\t\\twith rpw.db.Transaction(\\\"Auto Dim Lines\\\"):\\n\\t\\t\\t# Gather all the lines to filter and delete the ones we dont want.\\n\\t\\t\\tallLines = list(GetElementsInView(BuiltInCategory.OST_Lines, Autodesk.Revit.DB.CurveElement, currentView.Id))\\n\\n\\t\\t\\tfor lineId1 in allLines:\\n\\t\\t\\t\\tline1 = doc.GetElement(lineId1)\\n\\t\\t\\t\\tlineName = line1.LineStyle.Name\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif (\\\"Full\\\" in lineName or \\\"Partial\\\" in lineName) and line1.GeometryCurve.IsBound:\\n\\t\\t\\t\\t\\trefArray = ReferenceArray()\\n\\t\\t\\t\\t\\tlineReference =line1.GeometryCurve\\n\\n\\t\\t\\t\\t\\tline1StartPoint = lineReference.GetEndPoint(0)\\n\\t\\t\\t\\t\\tline1EndPoint = lineReference.GetEndPoint(1)\\n\\n\\t\\t\\t\\t\\tx1 = line1EndPoint.X - line1StartPoint.X\\n\\t\\t\\t\\t\\ty1 = line1EndPoint.Y - line1StartPoint.Y\\n\\n\\t\\t\\t\\t\\tvect1Norm = XYZ(y1 * -1, x1, 0).Normalize()\\n\\t\\t\\t\\t\\tvect1 = vect1Norm.Multiply(offsetDim)\\n\\n\\t\\t\\t\\t\\tpoint1 = line1StartPoint.Add(vect1)\\n\\t\\t\\t\\t\\tpoint2 = line1EndPoint.Add(vect1)\\n\\n\\t\\t\\t\\t\\tdimLine = Autodesk.Revit.DB.Line.CreateBound(point1, point2)\\n\\n\\t\\t\\t\\t\\trefArray.Append(lineReference.GetEndPointReference(0)) \\n\\t\\t\\t\\t\\trefArray.Append(lineReference.GetEndPointReference(1))\\n\\t\\t\\t\\t\\tnewDim = doc.Create.NewDimension(currentView, dimLine, refArray)\\n\\t\\t\\t\\t\\tnewDim.DimensionType = selectedDimType\\n\\t\\t\\t\\t\\n\\t\\t\\t\\t\\n\\t\\t\\t\\telif \\\"control\\\" in lineName.lower() and line1.GeometryCurve.IsBound:\\n\\n\\t\\t\\t\\t\\tfor wallId in allWalls:\\n\\t\\t\\t\\t\\t\\twall = doc.GetElement(wallId)\\n\\t\\t\\t\\t\\t\\tif \\\"Basic\\\" in str(wall.WallType.Kind):\\n\\t\\t\\t\\t\\t\\t\\tline2 = wall.Location.Curve\\n\\n\\t\\t\\t\\t\\t\\t\\t#Crazy way to get the wall centerline as a Reference object\\n\\t\\t\\t\\t\\t\\t\\tunique = wall.UniqueId\\n\\t\\t\\t\\t\\t\\t\\trefString = System.String.Format(\\\"{0}:{1}:{2}\\\",unique,-9999,1)\\n\\t\\t\\t\\t\\t\\t\\twall_centre = Reference.ParseFromStableRepresentation(doc,refString)\\n\\n\\t\\t\\t\\t\\t\\t\\tline2StartPoint = line2.Evaluate(0, True)\\n\\t\\t\\t\\t\\t\\t\\tline2Midpoint = line2.Evaluate(0.5, True)\\n\\n\\t\\t\\t\\t\\t\\t\\tx1 = line2Midpoint.X - line2StartPoint.X\\n\\t\\t\\t\\t\\t\\t\\ty1 = line2Midpoint.Y - line2StartPoint.Y\\n\\t\\t\\t\\t\\t\\t\\tz1 = line2Midpoint.Z\\n\\n\\t\\t\\t\\t\\t\\t\\tvect1Norm = XYZ(x1,y1,0).Normalize()\\n\\t\\t\\t\\t\\t\\t\\tvect1 = vect1Norm.Multiply(searchDist)\\n\\n\\t\\t\\t\\t\\t\\t\\t#Create the vectors\\n\\t\\t\\t\\t\\t\\t\\tvect2 = XYZ(vect1.Y * -1, vect1.X, vect1.Z)\\n\\t\\t\\t\\t\\t\\t\\tvect3 = XYZ(vect1.Y, vect1.X * -1, vect1.Z)\\n\\n\\t\\t\\t\\t\\t\\t\\t#Add them to the midpoints\\n\\t\\t\\t\\t\\t\\t\\tpoint1 = line2Midpoint.Add(vect2)\\n\\t\\t\\t\\t\\t\\t\\tpoint2 = line2Midpoint.Add(vect3)\\n\\n\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t#Create the line that will be used to test intersections with datum lines\\n\\t\\t\\t\\t\\t\\t\\ttestLine = Autodesk.Revit.DB.Line.CreateBound(point1, point2)\\n\\t\\t\\t\\t\\t\\t\\t \\n\\t\\t\\t\\t\\t\\t\\t#Create the datum line at the same z level as the test intersection lines\\n\\t\\t\\t\\t\\t\\t\\tline1GC = line1.GeometryCurve\\n\\t\\t\\t\\t\\t\\t\\tdatumPoint1 = line1GC.GetEndPoint(0)\\n\\t\\t\\t\\t\\t\\t\\tdatumPoint2 = line1GC.GetEndPoint(1)\\n\\n\\t\\t\\t\\t\\t\\t\\tdatumPoint1 = XYZ(datumPoint1.X, datumPoint1.Y, line2Midpoint.Z)\\n\\t\\t\\t\\t\\t\\t\\tdatumPoint2 = XYZ(datumPoint2.X, datumPoint2.Y, line2Midpoint.Z)\\n\\n\\t\\t\\t\\t\\t\\t\\tflattenedDatumLine = Autodesk.Revit.DB.Line.CreateBound(datumPoint1, datumPoint2)\\n\\n\\t\\t\\t\\t\\t\\t\\tintersection = RevitCurveCurveIntersection(flattenedDatumLine, testLine)\\n\\n\\t\\t\\t\\t\\t\\t\\tif intersection:\\n\\n\\t\\t\\t\\t\\t\\t\\t\\t#Adjust the position parameter based on distance away\\n\\t\\t\\t\\t\\t\\t\\t\\t#from the datum line so they are easier to read\\n\\n\\t\\t\\t\\t\\t\\t\\t\\tposFactor = (line2Midpoint.DistanceTo(intersection)/searchDist) * (line2StartPoint.DistanceTo(line2Midpoint)/2)\\n\\t\\t\\t\\t\\t\\t\\t\\tadjustVect = vect1Norm.Multiply(posFactor)\\n\\n\\t\\t\\t\\t\\t\\t\\t\\tp1 = line2Midpoint.Add(adjustVect)\\n\\t\\t\\t\\t\\t\\t\\t\\tp2 = intersection.Add(adjustVect)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\tif p1.DistanceTo(p2) > app.ShortCurveTolerance:\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tdimLine = Autodesk.Revit.DB.Line.CreateBound(p1, p2)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\trefArray = ReferenceArray()\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t#lineReference =line1.GeometryCurve\\n\\t\\t\\t\\t\\t\\t\\t\\t\\trefArray.Append(line1.GeometryCurve.Reference)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\trefArray.Append(wall_centre)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tnewDim = doc.Create.NewDimension(currentView, dimLine, refArray)\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tnewDim.DimensionType = selectedDimType\\n\\n\\telif autodimOption == \\\"Partition Plan\\\":\\n\\n\\t\\t\\\"\\\"\\\"\\n\\t\\tCreates sill dimensions for partition install plans\\n\\t\\t\\\"\\\"\\\" \\n\\n\\t\\tallStorefrontWalls = rpw.db.Collector(of_class='Wall', \\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tview=currentView, \\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\twhere=lambda x: (str(x.WallType.Kind) == \\\"Curtain\\\") and (systemName.lower() in x.Name.lower()))\\n\\n\\t\\tallStorefrontPanels = []\\n\\t\\tallStorefrontMullions = []\\n\\n\\t\\t#Collect mullions\\n\\t\\tfor sfwall in allStorefrontWalls:\\n\\t\\t\\tfor sfMullionsId in sfwall.CurtainGrid.GetMullionIds():\\n\\t\\t\\t\\tallStorefrontMullions.append(doc.GetElement(sfMullionsId))\\n\\n\\t\\twith rpw.db.Transaction(\\\"Auto Dim Sills\\\"):\\n\\n\\t\\t\\tfor sfMullion in allStorefrontMullions:\\n\\t\\t\\t\\t\\n\\t\\t\\t\\tif \\\"sill\\\" in sfMullion.Name.lower() and sfMullion.LocationCurve:\\n\\n\\t\\t\\t\\t\\tmullionDirection = sfMullion.LocationCurve.Direction\\n\\n\\t\\t\\t\\t\\trefArray = ReferenceArray()\\n\\t\\t\\t\\t\\tedgeCurve = None\\n\\n\\t\\t\\t\\t\\toptions = app.Create.NewGeometryOptions()\\n\\t\\t\\t\\t\\toptions.IncludeNonVisibleObjects = True\\n\\t\\t\\t\\t\\toptions.ComputeReferences = True\\n\\n\\t\\t\\t\\t\\tfaces = []\\n\\t\\t\\t\\t\\tperpFace = None\\n\\n\\t\\t\\t\\t\\tmullionGeo = sfMullion.get_Geometry(options)\\n\\n\\t\\t\\t\\t\\tfor item in list(mullionGeo):\\n\\t\\t\\t\\t\\t\\tgeometry = list(item.GetInstanceGeometry())\\n\\t\\t\\t\\t\\t\\tfor geo in geometry:\\n\\t\\t\\t\\t\\t\\t\\tif type(geo) == Autodesk.Revit.DB.Solid:\\n\\t\\t\\t\\t\\t\\t\\t\\tif list(geo.Faces.GetEnumerator()):\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tfaces = list(geo.Faces.GetEnumerator()) \\n\\t\\t\\t\\t\\t\\tif faces:\\n\\t\\t\\t\\t\\t\\t\\tbreak\\n\\n\\t\\t\\t\\t\\tfor face in faces:\\n\\n\\t\\t\\t\\t\\t\\tfaceDirection = face.FaceNormal\\n\\n\\n\\t\\t\\t\\t\\t\\tif abs(90-((faceDirection.AngleTo(mullionDirection)*360)/ (2*math.pi))) < 0.01 and faceDirection.Z == 1 :\\n\\t\\t\\t\\t\\t\\t\\t#print \\\"found face\\\"\\n\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\tedgeloops = list(face.EdgeLoops)[0]\\n\\t\\t\\t\\t\\t\\t\\tedgesFound = 0\\n\\n\\t\\t\\t\\t\\t\\t\\tfor edge in edgeloops:\\n\\t\\t\\t\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\t\\t\\t#if abs(edge.AsCurve().Direction.Z) == 1:\\n\\t\\t\\t\\t\\t\\t\\t\\tif abs(180-((edge.AsCurve().Direction.AngleTo(mullionDirection)*360)/ (2*math.pi))) < 0.01:\\n\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tedgeCurve = Autodesk.Revit.DB.Line.CreateBound(edge.AsCurve().GetEndPoint(0), edge.AsCurve().GetEndPoint(1))\\n\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tedgesFound += 1\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\t\\t\\t\\tbreak\\n\\n\\t\\t\\t\\t\\tif edgesFound >= 1:\\n\\t\\t\\t\\t\\t\\n\\t\\t\\t\\t\\t\\tline1 = sfMullion.LocationCurve\\n\\n\\t\\t\\t\\t\\t\\tline1StartPoint = line1.GetEndPoint(0)\\n\\t\\t\\t\\t\\t\\tline1EndPoint = line1.GetEndPoint(1)\\n\\n\\t\\t\\t\\t\\t\\tx1 = line1EndPoint.X - line1StartPoint.X\\n\\t\\t\\t\\t\\t\\ty1 = line1EndPoint.Y - line1StartPoint.Y\\n\\n\\t\\t\\t\\t\\t\\tvect1Norm = XYZ(y1 * -1, x1, 0).Normalize()\\n\\t\\t\\t\\t\\t\\tvect1 = vect1Norm.Multiply(offsetDim)\\n\\n\\t\\t\\t\\t\\t\\tpoint1 = line1StartPoint.Add(vect1)\\n\\t\\t\\t\\t\\t\\tpoint2 = line1EndPoint.Add(vect1)\\n\\n\\t\\t\\t\\t\\t\\tdimLine = Autodesk.Revit.DB.Line.CreateBound(point1, point2)\\n\\n\\t\\t\\t\\t\\t\\tif edgeCurve:\\n\\t\\t\\t\\t\\t\\t\\tdummyDetail = doc.Create.NewDetailCurve(currentView, edgeCurve)\\n\\n\\t\\t\\t\\t\\t\\t\\trefArray.Append(dummyDetail.GeometryCurve.GetEndPointReference(0)) \\n\\t\\t\\t\\t\\t\\t\\trefArray.Append(dummyDetail.GeometryCurve.GetEndPointReference(1))\\n\\n\\t\\t\\t\\t\\t\\t\\tnewDim = doc.Create.NewDimension(currentView, dimLine, refArray)\\n\\t\\t\\t\\t\\t\\t\\tnewDim.DimensionType = selectedDimType\",\n \"def front_wheel_from_axis():\",\n \"def den_evolve(self, delt, txp, src):\\n self.ne += (-txp.dfluxe + src.se)*delt\\n self.ni += (-txp.dfluxi + src.si)*delt\",\n \"def slider_dragged(self):\\n pass\",\n \"def jupyter():\",\n \"def __init__(self, parent=None):\\n QtGui.QWidget.__init__(self, parent)\\n \\n self.setWindowTitle('The Visual Climate Data Analysis Tools - (VCDAT)')\\n layout = QtGui.QVBoxLayout()\\n self.setLayout(layout)\\n\\n # Init Menu Widget\\n self.menuWidget = QMenuWidget(self)\\n\\n # Init File Widget\\n vsplitter = QtGui.QSplitter(QtCore.Qt.Vertical) \\n fileWidget = QLabeledWidgetContainer(QCDATFileWidget(),\\n 'FILE VARIABLES')\\n vsplitter.addWidget(fileWidget)\\n\\n # Init Defined Variables Widget\\n definedVar = QLabeledWidgetContainer(QDefinedVariable(),\\n 'DEFINED VARIABLES')\\n vsplitter.addWidget(definedVar)\\n hsplitter = QtGui.QSplitter(QtCore.Qt.Horizontal)\\n hsplitter.addWidget(vsplitter)\\n\\n # Init Var Plotting Widget\\n varView = QLabeledWidgetContainer(QVariableView(),\\n 'PLOTTING')\\n hsplitter.addWidget(varView)\\n hsplitter.setStretchFactor(1, 1)\\n layout.addWidget(hsplitter)\\n\\n # Init guiController\\n guiController = GuiController(fileWidget.getWidget(),\\n definedVar.getWidget(),\\n varView.getWidget())\\n guiController.initTeachingCommands()\\n self.guiController = guiController # So guicontroller doesn't get garbage collected\\n\\n # Connect signals between self & GuiController\\n self.connect(self, QtCore.SIGNAL('setRecordCommands'),\\n guiController.setRecordCommands)\\n self.connect(self, QtCore.SIGNAL('viewTeachingCommands'),\\n guiController.viewTeachingCommands)\\n self.connect(self, QtCore.SIGNAL('closeTeachingCommands'),\\n guiController.closeTeachingCommands) \\n\\n # Connect Signals between QVariableView & QDefinedVariable\\n varView.connect(definedVar.getWidget(), QtCore.SIGNAL('selectDefinedVariableEvent'),\\n varView.getWidget().selectDefinedVariableEvent)\\n varView.connect(definedVar.getWidget(), QtCore.SIGNAL('setupDefinedVariableAxes'),\\n varView.getWidget().setupDefinedVariableAxes)\\n definedVar.connect(varView.getWidget(), QtCore.SIGNAL('plotPressed'),\\n definedVar.getWidget().defineQuickplot)\\n definedVar.connect(varView.getWidget(), QtCore.SIGNAL('defineVariable'),\\n definedVar.getWidget().defineVariable)\\n\\n # Connect Signals between QFileWidget & QVariableView\\n varView.connect(fileWidget.getWidget(), QtCore.SIGNAL('variableChanged'),\\n varView.getWidget().setupDefinedVariableAxes)\\n varView.connect(fileWidget.getWidget(), QtCore.SIGNAL('defineVariableEvent'),\\n varView.getWidget().defineVariableEvent)\",\n \"def flopViewer():\\n allV = nuke.allNodes('Viewer')\\n pV = allV[0]\\n List = nuke.selectedNodes()\\n nuke.selectAll()\\n nuke.invertSelection()\\n try:\\n n = nuke.toNode('VIEWER_INPUT')\\n if n.Class() == 'Mirror':\\n n['Vertical'].setValue(not n['Vertical'].value())\\n for i in allV:\\n i['input_process'].setValue(not n['Vertical'].value() + n['Horizontal'].value() == 0)\\n if n['Vertical'].value() + n['Horizontal'].value() == 0:\\n nuke.delete(n)\\n nuke.selectAll()\\n nuke.invertSelection()\\n else:\\n nuke.message(\\\"Another Viewer Input already exists.\\\\nAborting to avoid conflict\\\")\\n \\n except:\\n n = nuke.Node('Mirror',inpanel=False)\\n n['xpos'].setValue(pV.xpos()+150)\\n n['ypos'].setValue(pV.ypos())\\n n['name'].setValue('VIEWER_INPUT')\\n n['hide_input'].setValue(1)\\n n['Vertical'].setValue(not n['Vertical'].value())\\n nuke.selectAll()\\n nuke.invertSelection()\\n for i in List:\\n i['selected'].setValue(True)\\n for i in List:\\n i['selected'].setValue(True)\",\n \"def ion():\\n plt.ion()\",\n \"def generate_widgets(self):\\n\\n self.plot_canvas()\\n\\n # Select which m component to plot ------------------------------------\\n\\n mcomp_dropdown = ipw.Dropdown(options=['x', 'y', 'z', 'hls'],\\n # description=r'$\\\\text{Plot}\\\\,\\\\,m_{i}$',\\n value='z'\\n )\\n mcomp_dropdown.observe(lambda b: self.static_plot_component_colorbar(\\n m_component=mcomp_dropdown.value))\\n mcomp_dropdown_text = ipw.Label(r'$\\\\text{Plot}\\\\,\\\\,m_{i}$')\\n mcomp_dropdown_text.width = '100px'\\n\\n mcomp_box = ipw.HBox(children=[mcomp_dropdown_text, mcomp_dropdown])\\n\\n # Button to start relaxation ------------------------------------------\\n\\n # We use two boxes with the maximum time and the number of steps\\n run_box = ipw.FloatText()\\n run_box_2 = ipw.FloatText()\\n # Default values for the boxes\\n run_box.value = 10\\n run_box_2.value = 100\\n # Change left and right margins\\n run_box.layout.margin = '0px 50px'\\n run_box.layout.width = '100px'\\n run_box_2.layout.margin = '0px 50px'\\n run_box_2.layout.width = '100px'\\n\\n # The button to start the relaxation of the system, using the values in\\n # the boxes\\n run_button = ipw.Button(description='Run sim!')\\n run_button.layout.margin = '0px 50px'\\n # The action requires a variable for the button (?). We just\\n # impose it in a lambda function\\n run_button.on_click(lambda b: self.relax(b,\\n max_time=run_box.value * 1e-9,\\n time_steps=run_box_2.value,\\n m_component=mcomp_dropdown.value\\n )\\n )\\n # run_button.margin = '0px 20px'\\n run_button.layout.background_color = '#9c0909'\\n run_button.color = 'white'\\n\\n run_box_text = ipw.Label(r'$\\\\text{Time [ns]}$')\\n run_box_text.width = '50px'\\n run_box_2_text = ipw.Label(r'$\\\\text{Steps}$')\\n run_box_2_text.width = '50px'\\n\\n # Align everything in a horizontal box\\n run_container = ipw.HBox(children=[run_box_text, run_box,\\n run_box_2_text, run_box_2,\\n run_button]\\n )\\n\\n # Boxes to update the Zeeman field ------------------------------------\\n\\n zeeman_box_texts = [ipw.Label(r'$B_x\\\\,\\\\,\\\\text{[T]}$'),\\n ipw.Label(r'$B_y\\\\,\\\\,\\\\text{[T]}$'),\\n ipw.Label(r'$B_z\\\\,\\\\,\\\\text{[T]}$')\\n ]\\n for text in zeeman_box_texts:\\n text.width = '50px'\\n\\n zeeman_box_x = ipw.FloatText()\\n zeeman_box_y = ipw.FloatText()\\n zeeman_box_z = ipw.FloatText()\\n\\n # Show the default value in the box\\n zeeman_box_x.value = self.B[0]\\n zeeman_box_x.layout.width = '50px'\\n zeeman_box_x.layout.margin = '0px 50px'\\n zeeman_box_y.value = self.B[1]\\n zeeman_box_y.layout.width = '50px'\\n zeeman_box_y.layout.margin = '0px 50px'\\n zeeman_box_z.value = self.B[2]\\n zeeman_box_z.layout.width = '50px'\\n zeeman_box_z.layout.margin = '0px 50px'\\n\\n # Update the simulation using a button\\n zeeman_button = ipw.Button(description='Update field')\\n zeeman_button.on_click(\\n lambda button: self.update_Zeeman_field((zeeman_box_x.value,\\n zeeman_box_y.value,\\n zeeman_box_z.value,\\n )\\n )\\n )\\n\\n # Draw the default Field in the plot title\\n self.title_text.set_text('Field: {} T'.format(\\n self.sim.get_interaction('Zeeman').B0))\\n self.fig.canvas.draw()\\n\\n zeeman_container = ipw.HBox(children=[zeeman_box_texts[0],\\n zeeman_box_x,\\n zeeman_box_texts[1],\\n zeeman_box_y,\\n zeeman_box_texts[2],\\n zeeman_box_z,\\n zeeman_button\\n ]\\n )\\n\\n # DMI magnitude box ---------------------------------------------------\\n\\n DMI_box_text = ipw.Label(r'$\\\\text{DMI [meV]}$')\\n DMI_box_text.width = '50px'\\n\\n DMI_box = ipw.FloatText()\\n\\n # Show the default value in the box\\n DMI_box.value = round(self.D / const.meV, 2)\\n DMI_box.layout.width = '60px'\\n DMI_box.layout.margin = '0px 50px'\\n\\n # Update the simulation using a button\\n DMI_button = ipw.Button(description='Update')\\n DMI_button.on_click(\\n lambda button: self.update_DMI(DMI_box.value)\\n )\\n\\n DMI_container = ipw.HBox(children=[DMI_box_text, DMI_box,\\n DMI_button],\\n )\\n\\n # Anisotropy -----------------------------------------------------------\\n\\n # anisotropy_box_text = ipw.Label(r'$\\\\text{Anisotropy [meV]}$')\\n # anisotropy_box_text.width = '100px'\\n\\n # anisotropy_box = ipw.FloatText()\\n\\n # # Show the default value in the box\\n # anisotropy_box.value = round(self.ku / const.meV, 2)\\n # anisotropy_box.layout.width = '60px'\\n # anisotropy_box.layout.margin = '0px 50px'\\n\\n # # Update the simulation using a button\\n # anisotropy_button = ipw.Button(description='Update')\\n # anisotropy_button.on_click(\\n # lambda button: self.update_anisotropy(anisotropy_box.value)\\n # )\\n\\n # anisotropy_container = ipw.HBox(children=[anisotropy_box_text,\\n # anisotropy_box,\\n # anisotropy_button]\\n # )\\n\\n # Initial state -------------------------------------------------------\\n\\n # Options for the initial states. The values of the keys are the\\n # initial magnetisation functions for Fidimag\\n init_state_select = ipw.RadioButtons(\\n options={'Skyrmion':\\n lambda pos: self.skyrmion_m_field(pos, sign=1),\\n '2-PI-Vortex':\\n lambda pos: self.skyrmion_m_field(pos, sign=1,\\n core=-1,\\n pi_factor=2,\\n out_skyrmion_dir=(0, 0, -1)\\n ),\\n '3-PI-Vortex':\\n lambda pos: self.skyrmion_m_field(pos, sign=1,\\n pi_factor=3,\\n ),\\n 'Helicoid':\\n lambda pos: self.helicoid_m_field(pos),\\n 'Sk-Helicoid':\\n lambda pos: self.sk_helicoid_m_field(pos),\\n 'Random':\\n lambda pos: np.random.uniform(-1, 1, 3),\\n 'Uniform':\\n (0, 0, -1)\\n },\\n # description=r'$\\\\text{Initial State}$'\\n )\\n init_state_select.selected_label = 'Skyrmion'\\n\\n # We need the extra variable for the buttons action\\n def update_state(b):\\n self.generate_m_field(m_function=init_state_select.value)\\n self.update_plot_component(mcomp_dropdown.value)\\n\\n # The selection changes are taken with the observe method\\n init_state_select.observe(update_state)\\n\\n init_state_select_text = ipw.Label(r'$\\\\text{Initial State}$')\\n init_state_select_text.width = '100px'\\n\\n init_state_select_box = ipw.HBox(children=[init_state_select_text,\\n init_state_select]\\n )\\n\\n # Pin boundaries button -----------------------------------------------\\n\\n pin_button = ipw.Button(description='Pin boundaries')\\n pin_button.on_click(\\n lambda button: self.pin_boundaries(plot_component=mcomp_dropdown.value)\\n )\\n\\n unpin_button = ipw.Button(description='Unpin boundaries')\\n unpin_button.on_click(\\n lambda button: self.release_boundaries()\\n )\\n\\n pin_box = ipw.HBox(children=[pin_button, unpin_button])\\n pin_box.layout.margin = '20px 0px'\\n\\n # Display -------------------------------------------------------------\\n\\n display(mcomp_box)\\n display(zeeman_container)\\n display(DMI_container)\\n # display(anisotropy_container)\\n display(init_state_select_box)\\n display(pin_box)\\n display(run_container)\\n\\n # return\",\n \"def run(self):\\n self.root.title(\\\"Etymology relations\\\")\\n self.root.geometry(\\\"1080x600\\\")\\n self.root.deiconify()\\n self.root.mainloop()\",\n \"def console(self):\\r\\n\\r\\n go_on = True\\r\\n while go_on:\\r\\n console = DisplayList([self.headings.ADD_MENU,\\r\\n self.headings.DELETE_MENU,\\r\\n self.headings.SHOW_MENU,\\r\\n self.headings.CLEAR_MENU,\\r\\n self.headings.QUIT_MENU,\\r\\n '(N)otebook'*self.using_database],\\r\\n displayobject=self.displayobject)\\r\\n i = input()\\r\\n if i in self.ADDTERMS:\\r\\n\\r\\n self.add(input(self.headings.KEYMACRO), [x_temp.strip() for x_temp in input(self.headings.KEYS).split(',')])\\r\\n elif i in self.DELETETERMS:\\r\\n\\r\\n while True:\\r\\n self.show_kd()\\r\\n to_delete = input (self.headings.DELETE)\\r\\n if to_delete == EMPTYCHAR:\\r\\n break\\r\\n if to_delete.isnumeric() and int(to_delete) > 0 and int(to_delete) < len(self.query(term1='kd',action='get'))+1:\\r\\n from_temp = sorted(list(self.query(term1='kd',action='get')),\\r\\n key=lambda x_temp: x_temp.lower())[int(to_delete)-1]\\r\\n to_temp = self.query(term1='kd',term2=from_temp,action='get')\\r\\n \\r\\n self.delete(from_temp,to_temp[0])\\r\\n\\r\\n\\r\\n elif i in self.SHOWTERMS:\\r\\n self.show_kd()\\r\\n elif i in self.CLEARTERMS:\\r\\n if input(self.headings.ARE_YOU_SURE) in YESTERMS:\\r\\n self.query(term1='kd',action='delete')\\r\\n elif i in ['n','N'] and self.using_database:\\r\\n self.db_cursor.execute('SELECT notebook FROM notebooks')\\r\\n notebooks = [x[0] for x in self.db_cursor.fetchall()]\\r\\n self.displayobject.noteprint(('NOTEBOOKS','\\\\n'.join(notebooks)))\\r\\n action = input('NAME OF EXISTING OR NEW NOTEBOOK?').strip()\\r\\n if action in notebooks:\\r\\n self.notebookname = action\\r\\n else:\\r\\n if input('Do you want to creat a new notebook titled '+action) in YESTERMS:\\r\\n self.notebookname = action\\r\\n self.db_cursor.execute(\\\"INSERT OR REPLACE INTO notebooks (notebook) VALUES (?);\\\",(self.notebookname,))\\r\\n \\r\\n \\r\\n elif i in self.QUITTERMS:\\r\\n go_on = False\",\n \"def main():\\r\\n root = tk.Tk()\\r\\n root.geometry(\\\"250x100+300+300\\\")\\r\\n TrendProg(root)\\r\\n root.mainloop()\",\n \"def default_door():\\n X = [0.0, 0.14, 1.12, 1.26]\\n Y = [0.0, 0.14, 2.24]\\n Z = [-0.14, 0.14]\\n V, F = True, False\\n occupancy = [\\n [[V], [V]],\\n [[V], [F]],\\n [[V], [V]]\\n ]\\n return w7.window(X, Y, Z, occupancy)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.54224694","0.52515614","0.5237333","0.5127714","0.5104529","0.5093767","0.50813234","0.5066324","0.4892671","0.48902854","0.48725274","0.48507506","0.48250785","0.48107544","0.47614673","0.4716767","0.46999207","0.46977425","0.46767718","0.4671984","0.4671545","0.4667316","0.46652034","0.46635106","0.46554312","0.46242163","0.4622872","0.46062526","0.4605395","0.45960927","0.4590389","0.45878688","0.45636177","0.4562192","0.45591986","0.45542824","0.45532328","0.45419982","0.45395643","0.45324036","0.45235777","0.4518782","0.45142108","0.450751","0.45073596","0.45070058","0.4504747","0.44983894","0.44957507","0.44945258","0.44939056","0.44923952","0.4481125","0.44739237","0.44697073","0.44689897","0.44668838","0.44602743","0.44590652","0.44526652","0.44479832","0.44459504","0.44445008","0.44419268","0.44404098","0.44369543","0.44261703","0.44247794","0.4419525","0.4417424","0.44153622","0.44131905","0.44098422","0.43983802","0.4390107","0.4380158","0.43782657","0.43731213","0.43660647","0.4361383","0.43571752","0.4357066","0.4357066","0.43551937","0.43542334","0.43540785","0.43506813","0.43505344","0.43505204","0.4347949","0.43463182","0.43435183","0.43433118","0.43383235","0.4337507","0.43343806","0.43322378","0.43289784","0.4327472","0.4325557"],"string":"[\n \"0.54224694\",\n \"0.52515614\",\n \"0.5237333\",\n \"0.5127714\",\n \"0.5104529\",\n \"0.5093767\",\n \"0.50813234\",\n \"0.5066324\",\n \"0.4892671\",\n \"0.48902854\",\n \"0.48725274\",\n \"0.48507506\",\n \"0.48250785\",\n \"0.48107544\",\n \"0.47614673\",\n \"0.4716767\",\n \"0.46999207\",\n \"0.46977425\",\n \"0.46767718\",\n \"0.4671984\",\n \"0.4671545\",\n \"0.4667316\",\n \"0.46652034\",\n \"0.46635106\",\n \"0.46554312\",\n \"0.46242163\",\n \"0.4622872\",\n \"0.46062526\",\n \"0.4605395\",\n \"0.45960927\",\n \"0.4590389\",\n \"0.45878688\",\n \"0.45636177\",\n \"0.4562192\",\n \"0.45591986\",\n \"0.45542824\",\n \"0.45532328\",\n \"0.45419982\",\n \"0.45395643\",\n \"0.45324036\",\n \"0.45235777\",\n \"0.4518782\",\n \"0.45142108\",\n \"0.450751\",\n \"0.45073596\",\n \"0.45070058\",\n \"0.4504747\",\n \"0.44983894\",\n \"0.44957507\",\n \"0.44945258\",\n \"0.44939056\",\n \"0.44923952\",\n \"0.4481125\",\n \"0.44739237\",\n \"0.44697073\",\n \"0.44689897\",\n \"0.44668838\",\n \"0.44602743\",\n \"0.44590652\",\n \"0.44526652\",\n \"0.44479832\",\n \"0.44459504\",\n \"0.44445008\",\n \"0.44419268\",\n \"0.44404098\",\n \"0.44369543\",\n \"0.44261703\",\n \"0.44247794\",\n \"0.4419525\",\n \"0.4417424\",\n \"0.44153622\",\n \"0.44131905\",\n \"0.44098422\",\n \"0.43983802\",\n \"0.4390107\",\n \"0.4380158\",\n \"0.43782657\",\n \"0.43731213\",\n \"0.43660647\",\n \"0.4361383\",\n \"0.43571752\",\n \"0.4357066\",\n \"0.4357066\",\n \"0.43551937\",\n \"0.43542334\",\n \"0.43540785\",\n \"0.43506813\",\n \"0.43505344\",\n \"0.43505204\",\n \"0.4347949\",\n \"0.43463182\",\n \"0.43435183\",\n \"0.43433118\",\n \"0.43383235\",\n \"0.4337507\",\n \"0.43343806\",\n \"0.43322378\",\n \"0.43289784\",\n \"0.4327472\",\n \"0.4325557\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.4808876"},"document_rank":{"kind":"string","value":"14"}}},{"rowIdx":18684,"cells":{"query":{"kind":"string","value":"Creates a color palette compatible with Bokeh from a matplotlib cmap name."},"document":{"kind":"string","value":"def get_bokeh_palette(cmap):\n from bokeh.colors import RGB\n from matplotlib import cm\n\n # Solution adapted from\n # https://stackoverflow.com/questions/31883097/elegant-way-to-match-a-string-to-a-random-color-matplotlib\n m_RGB = (255 * plt.get_cmap(cmap)(range(256))).astype(\"int\")\n return [RGB(*tuple(rgb)).to_hex() for rgb in m_RGB]"},"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 palette_from_mpl_name(name):\n if name in CMAPS:\n return CMAPS[name]\n\n rgba = plt.get_cmap(name)(np.linspace(0, 1, 256))\n palette = [to_hex(color) for color in rgba]\n return palette","def get_palette(palette_name):\n\n if hasattr(plt.cm, palette_name):\n cmap = getattr(plt.cm, palette_name)\n elif palette_name in list(mpl_cm.cmap_d.keys()):\n cmap = mpl_cm.get_cmap(palette_name)\n else:\n print(\"Error, color option '\", palette_name, \"' not a valid option\")\n sys.exit(1)\n\n return cmap","def get_cmap(n, name='Paired'):\n return plt.cm.get_cmap(name, n)","def get_cmap(n, name='hsv'):\n return plt.cm.get_cmap(name, n)","def get_cmap(n, name='hsv'):\n return plt.cm.get_cmap(name, n)","def get_cmap(n, name='jet'):\n return plt.cm.get_cmap(name, n)","def get_cmap(n, name=\"hsv\"):\n return plt.cm.get_cmap(name, n)","def get_cmap(n, name=\"hsv\"):\n return plt.cm.get_cmap(name, n)","def get_cmap(n, name=\"hsv\"):\n return plt.cm.get_cmap(name, n)","def get_cmap(cmap=None):\n if cmap:\n if isinstance(cmap, (mpl.colors.Colormap)):\n colormap = cmap\n elif cmap in cmo.cmapnames:\n colormap = cmo.cmap_d[cmap]\n elif cmap in plt.colormaps():\n colormap = plt.get_cmap(cmap)\n else:\n raise ValueError(\n \"Get unrecognised name for the colormap `{}`. Colormaps should be from standard matplotlib set of from cmocean package.\".format(\n cmap\n )\n )\n else:\n colormap = plt.get_cmap(\"Spectral_r\")\n\n return colormap","def colormap(cats, mplmap='auto', categorical=None):\n # Should automatically choose the right colormaps for:\n # categorical data\n # sequential data (low, high important)\n # diverging data (low, mid, high important)\n global DEF_SEQUENTIAL\n from matplotlib import cm\n\n if hasattr(cm, 'inferno'):\n DEF_SEQUENTIAL = 'inferno'\n else:\n DEF_SEQUENTIAL = 'BrBG'\n\n # strip units\n units = None # TODO: build a color bar with units\n if hasattr(cats[0], 'magnitude'):\n arr = u.array(cats)\n units = arr.units\n cats = arr.magnitude\n is_categorical = False\n else:\n is_categorical = not isinstance(cats[0], (float, int))\n\n if categorical is not None:\n is_categorical = categorical\n\n if is_categorical:\n values = _map_categories_to_ints(cats)\n if mplmap == 'auto':\n mplmap = DEF_CATEGORICAL\n else:\n values = np.array(list(map(float, cats)))\n if mplmap == 'auto':\n mplmap = DEF_SEQUENTIAL\n\n rgb = _cmap_to_rgb(mplmap, values)\n hexcolors = [webcolors.rgb_to_hex(np.array(c)) for c in rgb]\n return hexcolors","def mpl_palette(name, n_colors=6):\n brewer_qual_pals = {\"Accent\": 8, \"Dark2\": 8, \"Paired\": 12,\n \"Pastel1\": 9, \"Pastel2\": 8,\n \"Set1\": 9, \"Set2\": 8, \"Set3\": 12}\n\n if name.endswith(\"_d\"):\n pal = [\"#333333\"]\n pal.extend(color_palette(name.replace(\"_d\", \"_r\"), 2))\n cmap = blend_palette(pal, n_colors, as_cmap=True)\n else:\n cmap = getattr(mpl.cm, name)\n if name in brewer_qual_pals:\n bins = np.linspace(0, 1, brewer_qual_pals[name])[:n_colors]\n else:\n bins = np.linspace(0, 1, n_colors + 2)[1:-1]\n palette = list(map(tuple, cmap(bins)[:, :3]))\n\n return _ColorPalette(palette)","def cmap_to_pil_palette(cmap):\n # return (255.*np.array(\n # map(lambda x: cmap(x)[0:3], np.linspace(0., 1.,256)))\n # .ravel()).astype('int')\n return (255. * np.array(\n [cmap(x)[:3] for x in np.linspace(0,1,256)]).ravel().astype('int'))","def make_colormap(colormap = 'rainbow_r', bins = 256, add_alpha = True, invert_alpha = False, cmap_name = 'costum',\n discrete = False, return_cmap = False):\n \n if isinstance(colormap, str): # if input is string (so existent colormap)\n\n # get colormap\n cmap = cm.get_cmap(colormap)\n\n else: # is list of strings\n cvals = np.arange(len(colormap))\n norm = plt.Normalize(min(cvals),max(cvals))\n tuples = list(zip(map(norm,cvals), colormap))\n cmap = colors.LinearSegmentedColormap.from_list(\"\", tuples)\n \n if discrete == True: # if we want a discrete colormap from list\n cmap = colors.ListedColormap(colormap)\n bins = int(len(colormap))\n\n # convert into array\n cmap_array = cmap(range(bins))\n\n # reshape array for map\n new_map = []\n for i in range(cmap_array.shape[-1]):\n new_map.append(np.tile(cmap_array[...,i],(bins,1)))\n\n new_map = np.moveaxis(np.array(new_map), 0, -1)\n \n if add_alpha: \n # make alpha array\n if invert_alpha == True: # in case we want to invert alpha (y from 1 to 0 instead pf 0 to 1)\n _, alpha = np.meshgrid(np.linspace(0, 1, bins, endpoint=False), 1-np.linspace(0, 1, bins))\n else:\n _, alpha = np.meshgrid(np.linspace(0, 1, bins, endpoint=False), np.linspace(0, 1, bins, endpoint=False))\n\n # add alpha channel\n new_map[...,-1] = alpha\n cmap_ext = (0,1,0,1)\n else:\n new_map = new_map[:1,...].copy() \n cmap_ext = (0,100,0,1)\n \n fig = plt.figure(figsize=(1,1))\n ax = fig.add_axes([0,0,1,1])\n # plot \n plt.imshow(new_map,\n extent = cmap_ext,\n origin = 'lower')\n ax.axis('off')\n\n if add_alpha: \n rgb_fn = op.join(op.split(cortex.database.default_filestore)[\n 0], 'colormaps', cmap_name+'_alpha_bins_%d.png'%bins)\n else:\n rgb_fn = op.join(op.split(cortex.database.default_filestore)[\n 0], 'colormaps', cmap_name+'_bins_%d.png'%bins)\n #misc.imsave(rgb_fn, new_map)\n plt.savefig(rgb_fn, dpi = 200,transparent=True)\n\n if return_cmap:\n return cmap\n else:\n return rgb_fn","def cmap(num,cmap = plt.cm.gist_earth_r):\n return cmap(np.linspace(0, 1, num))","def generate_n_colors(n, cmap_name='tab20'):\n pt_region_colormap = plt.get_cmap(cmap_name)\n max_i = len(pt_region_colormap.colors)\n return [pt_region_colormap(i % max_i) for i in range(n)]","def color_mapper(cmap: str, vmin: float=0, vmax: float=1, alpha: float=1):\n\n alpha = int(255 * alpha)\n\n cmap = plt.get_cmap(cmap)\n cNorm = Normalize(vmin=vmin, vmax=vmax)\n scalarMap = cm.ScalarMappable(norm=cNorm, cmap=cmap)\n\n def mapper(value):\n \"\"\"\n This is the function that gets returned\n\n Parameters\n ----------\n value A number between vmin and vmax\n\n Returns\n -------\n An RGB color\n\n \"\"\"\n\n out = scalarMap.to_rgba(value)\n\n if isinstance(out, tuple):\n return tuple([255 * out[i] for i in range(3)] + [alpha])\n\n elif isinstance(out, np.ndarray):\n out[:, :-1] *= 255\n out[:, 3] = alpha\n return out\n\n return mapper","def get_density_cmap():\n # Add completely white color to Reds colormap in Matplotlib\n list_colors = plt.cm.datad['Reds']\n list_colors = list(list_colors)\n list_colors.insert(0, (1, 1, 1))\n list_colors.insert(0, (1, 1, 1))\n lscm = matplotlib.colors.LinearSegmentedColormap.from_list(\"my_Reds\", list_colors)\n return lscm","def set_cmap_cb(self, w, index):\n old_cmap_name = self._cmap_name\n name = cmap.get_names()[index]\n self.cmap_name = name\n self.pipeline.push(StageAction(self,\n dict(cmap_name=old_cmap_name),\n dict(cmap_name=self._cmap_name),\n descr=\"rgbmap / change cmap\"))\n\n self.pipeline.run_from(self)","def discrete_cmap(n_colors: int, base_cmap: str) -> Colormap:\r\n # https://gist.github.com/jakevdp/91077b0cae40f8f8244a\r\n base = plt.cm.get_cmap(base_cmap)\r\n color_list = base(np.linspace(0, 1, n_colors))\r\n cmap_name = base.name + str(n_colors)\r\n\r\n return base.from_list(cmap_name, color_list, n_colors)","def create_label_colormap():\n colormap = np.array([\n [128, 64, 128],\n [244, 35, 232],\n [ 70, 70, 70],\n [102, 102, 156],\n [190, 153, 153],\n [153, 153, 153],\n [250, 170, 30],\n [220, 220, 0],\n [107, 142, 35],\n [152, 251, 152],\n [ 70, 130, 180],\n [220, 20, 60],\n [255, 0, 0],\n [ 0, 0, 142],\n [ 0, 0, 70],\n [ 0, 60, 100],\n [ 0, 80, 100],\n [ 0, 0, 230],\n [119, 11, 32],\n [ 0, 0, 0]], dtype=np.uint8)\n return colormap","def colormap(self):\n palette = [(0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0),\n (111, 74, 0), (81, 0, 81), (128, 64, 128), (244, 35, 232),\n (250, 170, 160), (230, 150, 140), (70, 70, 70),\n (102, 102, 156), (190, 153, 153), (180, 165, 180),\n (150, 100, 100), (150, 120, 90), (153, 153, 153),\n (153, 153, 153), (250, 170, 30), (220, 220, 0),\n (107, 142, 35), (152, 251, 152), (70, 130, 180),\n (220, 20, 60), (255, 0, 0), (0, 0, 142), (0, 0, 70),\n (0, 60, 100), (0, 0, 90), (0, 0, 110), (0, 80, 100),\n (0, 0, 230), (119, 11, 32), (0, 0, 142)]\n\n num_colors = self[0][1].shape[-1]\n colormap = np.zeros((num_colors, 3), dtype=int)\n for i in range(num_colors):\n colormap[i, ...] = palette[self._update_labels_dict[i]]\n return colormap","def create_cycler_colors(color_scheme):\n cmap = cm.get_cmap(color_scheme) # PiYG\n cycler_colors = []\n\n for i in range(cmap.N):\n rgba = cmap(i)\n # rgb2hex accepts rgb or rgba\n cycler_colors.append(matplotlib.colors.rgb2hex(rgba)) \n \n return cycler_colors","def set_cmap(self, cmap: str | Colormap | matplotlib.colors.Colormap):\n if self._image is None:\n raise RuntimeError(\"You add data with `set_data` before setting cmaps\")\n self._image.set_cmap(cmap)\n self._widget._mgui_set_value(self._image.make_image())","def cmap(self):\n return self._palette","def _color_palette(n_colors=4, cmap='viridis', extrema=False):\n if extrema:\n bins = np.linspace(0, 1, n_colors)\n else:\n bins = np.linspace(0, 1, n_colors * 2 - 1 + 2)[1:-1:2]\n\n cmap = plt.get_cmap(cmap)\n palette = list(map(tuple, cmap(bins)[:, :3]))\n return palette","def set_palette(name=\"default\", ncontours=255):\n\n if name == \"gray\" or name == \"grayscale\":\n stops = [0.00, 0.34, 0.61, 0.84, 1.00]\n red = [1.00, 0.95, 0.95, 0.65, 0.15]\n green = [1.00, 0.85, 0.7, 0.5, 0.3]\n blue = [0.95, 0.6, 0.3, 0.45, 0.65]\n # elif name == \"whatever\":\n # (define more palettes)\n elif name == \"chris\":\n stops = [ 0.00, 0.34, 0.61, 0.84, 1.00 ]\n red = [ 1.0, 0.95, 0.95, 0.65, 0.15 ]\n green = [ 1.0, 0.85, 0.7, 0.5, 0.3 ]\n blue = [ 0.95, 0.6 , 0.3, 0.45, 0.65 ]\n else:\n # default palette, looks cool\n stops = [0.00, 0.34, 0.61, 0.84, 1.00]\n red = [0.00, 0.00, 0.87, 1.00, 0.51]\n green = [0.00, 0.81, 1.00, 0.20, 0.00]\n blue = [0.51, 1.00, 0.12, 0.00, 0.00]\n\n s = array('d', stops)\n r = array('d', red)\n g = array('d', green)\n b = array('d', blue)\n\n npoints = len(s)\n rt.TColor.CreateGradientColorTable(npoints, s, r, g, b, ncontours)\n rt.gStyle.SetNumberContours(ncontours)","def assigning_colors():\n rgb_colors = {}\n for name, hex in matplotlib.colors.cnames.items():\n color = []\n # So the values are from 0-255 and not 0-1\n for i in matplotlib.colors.to_rgb(hex):\n color.append(int(i * 255))\n\n color = tuple(color)\n rgb_colors[name] = color\n\n return rgb_colors","def getColorMap(colors):\n # Normalise RGBs\n norm_colors = []\n for color in colors:\n norm_colors.append([val / 255. for val in color])\n # create color map\n cmap = cols.ListedColormap(norm_colors)\n\n return cmap","def grayscale_cmap(cmap):\n # cmap = cm.get_cmap(cmap)\n map_colors = cmap(np.arange(cmap.N))\n\n # convert RGBA to perceived grayscale luminance\n # cf. http://alienryderflex.com/hsp.html\n RGB_weight = [0.299, 0.587, 0.114]\n luminance = np.sqrt(np.dot(map_colors[:, :3] ** 2, RGB_weight))\n map_colors[:, :3] = luminance[:, np.newaxis]\n\n return colors.LinearSegmentedColormap.from_list(cmap.name + \"_gray\", map_colors, cmap.N)","def plot_cmap(cmap):\n gradient = np.linspace(0, 1, 256)\n gradient = np.vstack((gradient, gradient))\n pylab.imshow(gradient, aspect='auto', cmap=cmap)\n pylab.show()","def discrete_cmap(N, base_cmap=None):\n base = plt.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def register_cccmacms(cmap='all'):\n \n \n #print 'registering cmaps'\n \n \n \n \n \n \n # define individual colors as RGB triples\n \n \n # from colorwheel.m\n \n \n # =============================================\n \n \n # kem_w20 (20) OR blue2red_w20\n \n \n # blueish at top, white in middle, reddish at bottom\n \n \n \n cpool = np.array([ [153,255,255], \\\n \n \n [204,255,229], \\\n \n \n [240,255,240],\\\n \n \n [204,255,153],\\\n \n \n [178,255,102],\\\n \n \n [216,255,76],\\\n \n \n [255,255,51],\\\n \n \n [255,220,51],\\\n \n \n [255,187,51],\\\n \n \n [255,153,51],\\\n \n \n [255,0,0],\\\n \n \n [204,0,0],\\\n \n \n [153,0,0]], \\\n \n \n dtype=float)\n \n \n \n acccbar = (cpool/255.)\n \n \n thecmap = col.ListedColormap(acccbar,'acccbar')\n \n \n cm.register_cmap(cmap=thecmap)\n\n return","def color_palette(n_colors=4, cmap='viridis', extrema=False):\n if extrema:\n bins = np.linspace(0, 1, n_colors)\n else:\n bins = np.linspace(0, 1, n_colors * 2 - 1 + 2)[1:-1:2]\n\n cmap = plt.get_cmap(cmap)\n palette = list(map(tuple, cmap(bins)[:, :3]))\n return palette","def discrete_cmap(N, base_cmap=None):\n # Note that if base_cmap is a string or None, you can simply do\n # return plt.cm.get_cmap(base_cmap, N)\n # The following works for string, None, or a colormap instance:\n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def discrete_cmap(N, base_cmap=None):\n\n # Note that if base_cmap is a string or None, you can simply do\n # return plt.cm.get_cmap(base_cmap, N)\n # The following works for string, None, or a colormap instance:\n\n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def discrete_cmap(N, base_cmap=None):\n\n # Note that if base_cmap is a string or None, you can simply do\n # return plt.cm.get_cmap(base_cmap, N)\n # The following works for string, None, or a colormap instance:\n\n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def discrete_cmap(N, base_cmap=None):\n\n # Note that if base_cmap is a string or None, you can simply do\n # return plt.cm.get_cmap(base_cmap, N)\n # The following works for string, None, or a colormap instance:\n\n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def discrete_cmap(N, base_cmap=None):\n\n # Note that if base_cmap is a string or None, you can simply do\n # return plt.cm.get_cmap(base_cmap, N)\n # The following works for string, None, or a colormap instance:\n\n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def display_cmap_color_range(cmap_style='rainbow'):\n cmap = plt.get_cmap(cmap_style)\n for c in range(256):\n plt.scatter([c], [0], s=500, c=cmap(c), lw=0)\n plt.show()","def get_colormap(values, cmap='jet', colorbar=True, log=False):\n by_value = not isinstance(values, int)\n if not by_value:\n colorbar = False\n if by_value:\n cmap = plt.get_cmap(cmap)\n if log:\n colors = [cmap(x) for x in tools.maths.normalise(np.log10(values))]\n else:\n colors = [cmap(x) for x in tools.maths.normalise(np.array(values))]\n else:\n cmap = plt.get_cmap(cmap, values)\n colors = [cmap(x) for x in range(values)]\n if colorbar:\n if log:\n norm = mpl.colors.LogNorm(vmin=min(values), vmax=max(values))\n else:\n norm = mpl.colors.Normalize(vmin=min(values), vmax=max(values))\n sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)\n sm.set_array([])\n if isinstance(colorbar, str):\n label = colorbar\n else:\n label = ''\n plt.colorbar(sm, label=label)\n return colors","def get_cmap(n):\n cmap_fn = plt.cm.get_cmap('hsv', n+1)\n colors = [cmap_fn(i + 1)[:3] for i in range(n)]\n random.shuffle(colors)\n cmap = (np.array(colors) * 255.0).astype(np.uint8)\n return cmap","def colors_to_cmap(colors):\n colors = np.asarray(colors)\n if colors.shape[1] == 3:\n colors = np.hstack((colors, np.ones((len(colors),1))))\n steps = (0.5 + np.asarray(range(len(colors)-1), dtype=np.float))/(len(colors) - 1)\n return matplotlib.colors.LinearSegmentedColormap(\n 'auto_cmap',\n {clrname: ([(0, col[0], col[0])] + \n [(step, c0, c1) for (step,c0,c1) in zip(steps, col[:-1], col[1:])] + \n [(1, col[-1], col[-1])])\n for (clridx,clrname) in enumerate(['red', 'green', 'blue', 'alpha'])\n for col in [colors[:,clridx]]},\n N=len(colors))","def discrete_cmap(N, base_cmap=None):\n \n # Note that if base_cmap is a string or None, you can simply do\n # return plt.cm.get_cmap(base_cmap, N)\n # The following works for string, None, or a colormap instance:\n \n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def discrete_cmap(N, base_cmap=None):\n \n # Note that if base_cmap is a string or None, you can simply do\n # return plt.cm.get_cmap(base_cmap, N)\n # The following works for string, None, or a colormap instance:\n \n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def discrete_cmap(N, base_cmap=None):\n \n # Note that if base_cmap is a string or None, you can simply do\n # return plt.cm.get_cmap(base_cmap, N)\n # The following works for string, None, or a colormap instance:\n \n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def discrete_cmap(N, base_cmap=None):\n # see https://gist.github.com/jakevdp/91077b0cae40f8f8244a\n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def generate_mass_palette(masses):\n mass_cmap = matplotlib.cm.get_cmap(\"plasma\")\n palette = {mass: mass_cmap(i / len(masses)) for i, mass in enumerate(masses)}\n palette[999] = \"grey\" # total pressure\n palette[5] = \"black\" # Pirani pressure\n return palette","def generate_colormap(scale_range=(0.0, 1.0), hue_range=(0.8, 0.0),\n saturation_range=(1.0, 1.0), value_range=(0.8, 0.8),\n nan_color=(0.2, 0.2, 0.2, 1.0)):\n lookup_table = vtk.vtkLookupTable()\n lookup_table.SetRange(scale_range)\n\n lookup_table.SetHueRange(hue_range)\n lookup_table.SetSaturationRange(saturation_range)\n lookup_table.SetValueRange(value_range)\n lookup_table.SetNanColor(nan_color)\n lookup_table.Build()\n return lookup_table","def discrete_cmap(N, base_cmap=None):\n\n # Note that if base_cmap is a string or None, you can simply do\n # return plt.cm.get_cmap(base_cmap, N)\n # The following works for string, None, or a colormap instance:\n # By Jake VanderPlas\n # License: BSD-style\n\n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return base.from_list(cmap_name, color_list, N)","def discrete_cmap(N, base_cmap=None):\n\t# Note that if base_cmap is a string or None, you can simply do\n\t# return plt.cm.get_cmap(base_cmap, N)\n\t# The following works for string, None, or a colormap instance:\n\tbase = plt.cm.get_cmap(base_cmap)\n\tcolor_list = base(np.linspace(0, 1, N))\n\tcmap_name = base.name + str(N)\n\treturn base.from_list(cmap_name, color_list, N)","def check_colormap(cmap):\n names = set(['BrBG', 'PiYG', 'PRGn', 'PuOr', 'RdBu', 'RdGy', 'RdYlBu', 'RdYlGn', 'Spectral',\n 'Blues', 'BuGn', 'BuPu', 'GnBu', 'Greens', 'Greys', 'Oranges', 'OrRd', 'PuBu',\n 'PuBuGn', 'PuRd', 'Purples', 'RdPu', 'Reds', 'YlGn', 'YlGnBu', 'YlOrBr', 'YlOrRd',\n 'Accent', 'Dark2', 'Paired', 'Pastel1', 'Pastel2', 'Set1', 'Set2', 'Set3', 'Lightning'])\n if cmap not in names:\n raise Exception(\"Invalid cmap '%s', must be one of %s\" % (cmap, names))\n else:\n return cmap","def get_colors(nlevels, colormap=None):\n if colormap is None:\n from matplotlib.pyplot import cm\n colormap = cm.rainbow\n return colormap(np.linspace(0, 1, nlevels))","def discrete_cmap(N, base_cmap=None):\n\n # Note that if base_cmap is a string or None, you can simply do\n # return plt.cm.get_cmap(base_cmap, N)\n # The following works for string, None, or a colormap instance:\n\n base = plt.cm.get_cmap(base_cmap)\n color_list = base(np.linspace(0, 1, N))\n cmap_name = base.name + str(N)\n return matplotlib.colors.LinearSegmentedColormap \\\n .from_list(cmap_name, color_list, N)","def test_colormap_discrete():\n with TestingCanvas(size=size, bgcolor='w') as c:\n idata = np.linspace(255, 0, size[0]*size[1]).astype(np.ubyte)\n data = idata.reshape((size[0], size[1]))\n image = Image(cmap=Colormap(colors=['r', 'g', 'b'],\n interpolation='zero'),\n clim='auto', parent=c.scene)\n image.set_data(data)\n assert_image_approved(c.render(), \"visuals/colormap_rgb.png\")","def test_density_colormap(self):\n cmap = matplotlib.cm.get_cmap('density')\n np.testing.assert_allclose(cmap(0.0), [0.214, 0.152, 0.535, 1], atol=0.001)\n np.testing.assert_allclose(cmap(1.0), [0.988, 0.978, 0.042, 1], atol=0.001)","def _get_colors(num_colors):\n cmap = plt.get_cmap()\n return [cmap(1. * i / num_colors) for i in range(num_colors)]","def make_colormap(colors):\n#-------------------------\n from matplotlib.colors import LinearSegmentedColormap, ColorConverter\n from numpy import sort\n z = sort(colors.keys())\n n = len(z)\n z1 = min(z)\n zn = max(z)\n x0 = (z - z1) / (zn - z1)\n CC = ColorConverter()\n R = []\n G = []\n B = []\n for i in range(n):\n #i'th color at level z[i]:\n Ci = colors[z[i]]\n if type(Ci) == str:\n # a hex string of form '#ff0000' for example (for red)\n RGB = CC.to_rgb(Ci)\n else:\n # assume it's an RGB triple already:\n RGB = Ci\n R.append(RGB[0])\n G.append(RGB[1])\n B.append(RGB[2])\n cmap_dict = {}\n cmap_dict['red'] = [(x0[i],R[i],R[i]) for i in range(len(R))]\n cmap_dict['green'] = [(x0[i],G[i],G[i]) for i in range(len(G))]\n cmap_dict['blue'] = [(x0[i],B[i],B[i]) for i in range(len(B))]\n mymap = LinearSegmentedColormap('mymap',cmap_dict)\n return mymap","def transparent_cmap(cmap, N=255):\n if type(cmap) == str:\n mycmap = plt.get_cmap(cmap)\n else:\n mycmap = cmap\n mycmap._init()\n mycmap._lut[0, -1] = 0\n return mycmap","def create_pascal_label_colormap():\r\n colormap = np.zeros((256, 3), dtype = int)\r\n ind = np.arange(256, dtype=int)\r\n\r\n for shift in reversed(range(8)):\r\n for channel in range(3):\r\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\r\n ind >>= 3\r\n\r\n return colormap","def test_colormap():\n with TestingCanvas(size=size, bgcolor='w') as c:\n idata = np.linspace(255, 0, size[0]*size[1]).astype(np.ubyte)\n data = idata.reshape((size[0], size[1]))\n image = Image(cmap=Colormap(colors=['k', 'w', 'r'],\n controls=[0.0, 0.1, 1.0]),\n clim='auto', parent=c.scene)\n image.set_data(data)\n assert_image_approved(c.render(), \"visuals/colormap_kwr.png\")","def get_mpl_colormap(self):\n return mpl.colors.ListedColormap(self.get_colors().astype(float) / 255.0)","def create_pascal_label_colormap():\n colormap = np.zeros((256, 3), dtype=int)\n ind = np.arange(256, dtype=int)\n\n for shift in reversed(range(8)):\n for channel in range(3):\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\n ind >>= 3\n\n return colormap","def create_pascal_label_colormap():\n colormap = np.zeros((256, 3), dtype=int)\n ind = np.arange(256, dtype=int)\n\n for shift in reversed(range(8)):\n for channel in range(3):\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\n ind >>= 3\n\n return colormap","def create_pascal_label_colormap():\n colormap = np.zeros((256, 3), dtype=int)\n ind = np.arange(256, dtype=int)\n\n for shift in reversed(range(8)):\n for channel in range(3):\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\n ind >>= 3\n\n return colormap","def create_pascal_label_colormap():\n colormap = np.zeros((256, 3), dtype=int)\n ind = np.arange(256, dtype=int)\n\n for shift in reversed(range(8)):\n for channel in range(3):\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\n ind >>= 3\n\n return colormap","def norm_cmap(values, cmap, vmin=None, vmax=None):\n mn = vmin or min(values)\n mx = vmax or max(values)\n norm = Normalize(vmin=mn, vmax=mx)\n n_cmap = plt.cm.ScalarMappable(norm=norm, cmap=cmap)\n\n rgb_colors = [n_cmap.to_rgba(value) for value in values]\n\n return n_cmap, rgb_colors","def parse_cmap(cmap, field=None):\n if cmap is None:\n cmap = get_field_colormap(field)\n return cmap","def SetColorMap(self, colormap, contrast=None, bias=None):\n extra = ''\n if contrast is not None:\n extra += '%f,' % contrast\n if bias is not None:\n extra += '%f,' % bias\n fmt = dict(wid=self.wid,cmap=colormap, extra=extra, suffix=self.suffix)\n command = \"JS9.SetColormap('{cmap}', {extra} {{display:'{wid}{suffix}'}});\".format(**fmt)\n get_ipython().run_cell_magic('javascript', '', command)","def transparent_cmap(cmap, alpha=0.8, N=255):\n mycmap = cmap\n mycmap._init()\n mycmap._lut[:, -1] = np.linspace(0, alpha, N + 4)\n return mycmap","def get_colormap(level_values: np.ndarray) -> np.ndarray:\n color_dimension = level_values # change to desired fourth dimension\n color_min, color_max = color_dimension.min(), color_dimension.max()\n norm = colors.Normalize(color_min, color_max)\n m = plt.cm.ScalarMappable(norm=norm, cmap=\"Spectral_r\")\n m.set_array([])\n face_colors = m.to_rgba(color_dimension)\n\n return face_colors","def create_pascal_label_colormap():\n colormap = np.zeros((256, 3), dtype=int)\n ind = np.arrange(256, dtype=int)\n\n for shift in reversed(range(8)):\n for channel in range(3):\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\n ind >>=3\n\n return colormap","def from_name (name_str):\n if name_str in colour_names:\n return Colour(*colour_names[name_str])\n raise KeyError(\"'%s' is not a recognized colour name\"%name_str)","def gen_colors(nbeads):\n\n # use colormap (blue, red, green)\n # blue 0.0, 0.0, 1.0\n # red: 1.0, 0.0, 0.0\n # green: 0.0, 1.0, 1.0\n\n my_cmap = cm.get_cmap('jet')\n minval = 0\n maxval = nbeads - 1\n norm = mplcolors.Normalize(minval, maxval)\n \n sphere_rgbcolor = []\n for i in range(nbeads):\n si = my_cmap(norm(i))\n sphere_rgbcolor.append([si[0], si[1], si[2]])\n\n return sphere_rgbcolor","def create_colormap(color_list: Sequence[str], n_colors: int) -> NDArrayFloat:\n cmap = LinearSegmentedColormap.from_list(name=\"dummy_name\", colors=color_list)\n colorscale: NDArrayFloat = np.array(\n [cmap(k * 1 / n_colors) for k in range(n_colors)]\n )\n # ignore the 4th alpha channel\n return colorscale[:, :3]","def create_riskmap(colormap):\n \n # Note that this code is tricky - remember to return a lambda expression\n risk_norm = mpl.colors.Normalize(vmin = MIN_LOG_RISK, vmax = MAX_LOG_RISK)\n color_mapper = mpl.cm.ScalarMappable(norm = risk_norm, cmap = colormap)\n return lambda risk : color_mapper.to_rgba(math.log(risk, 10))","def _create_color_map(self, hue, data):\n if hue in self.categorical_columns:\n # adding suffix to column name to get unique str values\n factors = sorted(set(data[hue + self.categorical_suffix]))\n if len(factors) <= self._max_categories_internal_limit:\n cmap = factor_cmap(\n hue + self.categorical_suffix,\n palette=self._categorical_palette[len(factors)],\n factors=factors\n )\n else:\n # If there is too many categories, None is returned\n cmap = None\n else:\n values = data[hue]\n cmap = linear_cmap(\n hue,\n palette=self.plot_design.contrary_color_linear_palette,\n low=min(values),\n high=max(values)\n )\n\n return cmap","def get_colormap(self):\n return colors.colormaps[self.name]","def get_colormap(self):\n return colors.colormaps[self.name]","def transparent_cmap(cmap, alpha, N=255):\n mycmap = cmap\n mycmap._init()\n mycmap._lut[:, -1] = np.linspace(0, 0.8, N + 4)\n return mycmap","def create_colour_scheme(alphabet=\"cinema\", colourscheme=\"hls\"):\n \n # List of all available alphabets from pepdata library + the all / dna alphabet\n alphabets_available = [\"cinema\", \"all\", \"dna\", \"gbmr4\", \"sdm12\", \"hsdm17\", \n \"hp2\", \"murphy10\", \"alex6\", \"aromatic2\", \"hp_vs_aromatic\"]\n # Default value, colouring scheme as used in the cinema alignment tool\n if alphabet == \"cinema\":\n return {\"A\": \"#c1ffc1\", \"B\": \"#ffffff\", \"C\": \"#50d433\", \"D\": \"#088446\",\n \"E\": \"#088446\", \"F\": \"#de94e3\", \"G\": \"#c1ffc1\", \"H\": \"#191996\",\n \"I\": \"#91b4ff\", \"J\": \"#ffffff\", \"K\": \"#ffa500\", \"L\": \"#91b4ff\",\n \"M\": \"#91b4ff\", \"N\": \"#088446\", \"O\": \"#ffffff\", \"P\": \"#ffb6c1\",\n \"Q\": \"#088446\", \"R\": \"#ffa500\", \"S\": \"#ce0000\", \"T\": \"#ce0000\",\n \"U\": \"#ffffff\", \"V\": \"#91b4ff\", \"W\": \"#de94e3\", \"X\": \"#ffffff\",\n \"Y\": \"#de94e3\", \"Z\": \"#ffffff\"}\n # If the alphabet is found in the reduced alphabets file:\n if alphabet in alphabets_available:\n alphabet = eval(alphabet)\n alphabet_values = set(alphabet.values())\n colours = sns.color_palette(colourscheme, len(alphabet_values)).as_hex()\n for keys in alphabet.keys():\n alphabet[keys] = colours[alphabet[keys]]\n else:\n print(\"Colour input\", alphabet, \"not available.\")\n sys.exit(1)\n return alphabet","def colorify(data, vmin=None, vmax=None, cmap=plt.cm.Spectral):\n import matplotlib.colors as colors\n\n _vmin = vmin or min(data)\n _vmax = vmax or max(data)\n cNorm = colors.normalize(vmin=_vmin, vmax=_vmax)\n\n scalarMap = plt.cm.ScalarMappable(norm=cNorm, cmap=cmap)\n colors = map(scalarMap.to_rgba, data)\n return colors, scalarMap","def fl_mapcolorname(colr, rgbcolrname):\n _fl_mapcolorname = library.cfuncproto(\n library.load_so_libforms(), \"fl_mapcolorname\",\\\n cty.c_long, [xfdata.FL_COLOR, xfdata.STRING],\\\n \"\"\"long int fl_mapcolorname(FL_COLOR col, const char * name)\"\"\")\n library.check_if_flinitialized()\n #library.checknonfatal_allowed_value_in_list(colr, xfdata.COLOR_list)\n ul_colr = library.convert_to_FL_COLOR(colr)\n s_rgbcolrname = library.convert_to_bytestrc(rgbcolrname)\n library.keep_elem_refs(colr, ul_colr, rgbcolrname, s_rgbcolrname)\n retval = _fl_mapcolorname(ul_colr, s_rgbcolrname)\n return retval","def _to_plotly_palette(scl, transparence=None):\n if not MATPLOTLIB_INSTALLED:\n soft_dependency_error(str(sys._getframe().f_code.co_name)+\"()\", \"matplotlib\")\n _out = []\n for color in scl:\n plotly_col = [255 * _c for _c in mplc.to_rgba(color)]\n if transparence:\n assert 0. <= transparence <= 1.0\n plotly_col[3] = transparence\n plotly_col = \"rgba({:.0f}, {:.0f}, {:.0f}, {:.4f})\".format(*plotly_col)\n else:\n plotly_col = \"rgb({:.0f}, {:.0f}, {:.0f})\".format(*plotly_col[:3])\n _out.append(plotly_col)\n return _out","def create_cityscapes_label_colormap():\r\n colormap = np.zeros((256, 3), dtype=np.uint8)\r\n colormap[0] = [128, 64, 128]\r\n colormap[1] = [244, 35, 232]\r\n colormap[2] = [70, 70, 70]\r\n colormap[3] = [102, 102, 156]\r\n colormap[4] = [190, 153, 153]\r\n colormap[5] = [153, 153, 153]\r\n colormap[6] = [250, 170, 30]\r\n colormap[7] = [220, 220, 0]\r\n colormap[8] = [107, 142, 35]\r\n colormap[9] = [152, 251, 152]\r\n colormap[10] = [70, 130, 180]\r\n colormap[11] = [220, 20, 60]\r\n colormap[12] = [255, 0, 0]\r\n colormap[13] = [0, 0, 142]\r\n colormap[14] = [0, 0, 70]\r\n colormap[15] = [0, 60, 100]\r\n colormap[16] = [0, 80, 100]\r\n colormap[17] = [0, 0, 230]\r\n colormap[18] = [119, 11, 32]\r\n return colormap","def _to_plotly_palette(scl, transparence=None):\n if transparence:\n return ['rgb({0},{1},{2},{3})'.format(r*255, g*255, b*255, transparence) for r, g, b in scl]\n else:\n return ['rgb({0},{1},{2})'.format(r*255, g*255, b*255) for r, g, b in scl]","def _map_to_2d_cmap(data1, data2, vmin, vmax, vmin2, vmax2, cmap):\n # load 2D cmap image\n cmap_directory = cortex.options.config.get(\"webgl\", \"colormaps\")\n cmap_image = plt.imread(os.path.join(cmap_directory, \"%s.png\" % cmap))\n\n # Normalize the data\n dim1 = np.clip(Normalize(vmin, vmax)(data1), 0, 1)\n dim2 = np.clip(1 - Normalize(vmin2, vmax2)(data2), 0, 1)\n\n # 2D indices of the data on the 2D cmap\n dim1 = np.round(dim1 * (cmap_image.shape[1] - 1))\n dim1 = np.nan_to_num(dim1).astype(np.uint32)\n dim2 = np.round(dim2 * (cmap_image.shape[0] - 1))\n dim2 = np.nan_to_num(dim2).astype(np.uint32)\n\n mapped_rgba = cmap_image[dim2.ravel(), dim1.ravel()]\n\n # Preserve nan values with alpha = 0\n nans = np.logical_or(np.isnan(data1), np.isnan(data2))\n mapped_rgba[nans, 3] = 0\n\n return mapped_rgba, cmap_image","def test_colormap_single_hue():\n with TestingCanvas(size=size, bgcolor='w') as c:\n idata = np.linspace(255, 0, size[0]*size[1]).astype(np.ubyte)\n data = idata.reshape((size[0], size[1]))\n image = Image(cmap=get_colormap('single_hue', 255),\n clim='auto', parent=c.scene)\n image.set_data(data)\n assert_image_approved(c.render(), \"visuals/colormap_hue.png\")","def remap_prefixes(cmap):\n cmap[\"MGI\"] = \"http://identifiers.org/mgi/MGI:\"\n cmap[\"WB\"] = \"http://identifiers.org/wormbase/\"\n return cmap","def molmol_colours(name):\n\n # Initialise the dictionary of colours.\n colours = {}\n\n # The colours sorted by the RGB float values.\n colours['black'] = [0.000, 0.000, 0.000]\n colours['navy'] = [0.000, 0.000, 0.502]\n colours['blue'] = [0.000, 0.000, 1.000]\n colours['dark green'] = [0.000, 0.392, 0.000]\n colours['green'] = [0.000, 1.000, 0.000]\n colours['cyan'] = [0.000, 1.000, 1.000]\n colours['turquoise'] = [0.251, 0.878, 0.816]\n colours['royal blue'] = [0.255, 0.412, 0.882]\n colours['aquamarine'] = [0.498, 1.000, 0.831]\n colours['sky green'] = [0.529, 0.808, 0.922]\n colours['dark violet'] = [0.580, 0.000, 0.827]\n colours['pale green'] = [0.596, 0.984, 0.596]\n colours['purple'] = [0.627, 0.125, 0.941]\n colours['brown'] = [0.647, 0.165, 0.165]\n colours['light blue'] = [0.678, 0.847, 0.902]\n colours['grey'] = [0.745, 0.745, 0.745]\n colours['light grey'] = [0.827, 0.827, 0.827]\n colours['violet'] = [0.933, 0.510, 0.933]\n colours['light coral'] = [0.941, 0.502, 0.502]\n colours['khaki'] = [0.941, 0.902, 0.549]\n colours['beige'] = [0.961, 0.961, 0.863]\n colours['red'] = [1.000, 0.000, 0.000]\n colours['magenta'] = [1.000, 0.000, 1.000]\n colours['deep pink'] = [1.000, 0.078, 0.576]\n colours['orange red'] = [1.000, 0.271, 0.000]\n colours['hot pink'] = [1.000, 0.412, 0.706]\n colours['coral'] = [1.000, 0.498, 0.314]\n colours['dark orange'] = [1.000, 0.549, 0.000]\n colours['orange'] = [1.000, 0.647, 0.000]\n colours['pink'] = [1.000, 0.753, 0.796]\n colours['gold'] = [1.000, 0.843, 0.000]\n colours['yellow'] = [1.000, 1.000, 0.000]\n colours['light yellow'] = [1.000, 1.000, 0.878]\n colours['ivory'] = [1.000, 1.000, 0.941]\n colours['white'] = [1.000, 1.000, 1.000]\n\n # Convert to numpy arrays.\n for key in colours:\n colours[key] = array(colours[key], float64)\n\n # Invalid colour string.\n if name not in colours:\n raise RelaxInvalidColourError(name)\n\n # Return the RGB colour array.\n return colours[name]","def read_colormap(name):\n\n path = get_demo_file(name + '.c3g')\n\n out = []\n with open(path, 'r') as file:\n for line in file:\n if 'rgb(' not in line:\n continue\n line = line.split('(')[-1].split(')')[0]\n out.append([float(n) for n in line.split(',')])\n\n return np.asarray(out).astype(float) / 256.","def colorify(data, vmin=None, vmax=None, cmap=plt.cm.Spectral):\n try:\n from matplotlib.colors import Normalize\n except ImportError:\n # old mpl\n\n from matplotlib.colors import normalize as Normalize\n\n _vmin = vmin or min(data)\n _vmax = vmax or max(data)\n cNorm = Normalize(vmin=_vmin, vmax=_vmax)\n\n scalarMap = plt.cm.ScalarMappable(norm=cNorm, cmap=cmap)\n try:\n colors = scalarMap.to_rgba(data)\n except:\n colors = list(map(scalarMap.to_rgba, data))\n return colors, scalarMap","def binary_cmap(color='red', alpha=1.):\n if color == 'red':\n color_code = (1., 0., 0., alpha)\n elif color == 'green':\n color_code = (0., 1., 0., alpha)\n elif color == 'blue':\n color_code = (0., 0., 1., alpha)\n else:\n color_code = color\n transparent_code = (1., 1., 1., 0.)\n return ListedColormap([transparent_code, color_code])","def create_colormap(seg_map):\n\tcolormap = np.zeros((256, 3), dtype=int)\n\tind = np.arange(256, dtype=int)\n\tfor shift in reversed(range(8)):\n\t\tfor channel in range(3):\n\t\t\tcolormap[:, channel] |= ((ind >> channel) & 1) << shift \n\t\tind >>= 3\n\treturn colormap[seg_map]","def _get_cmap_colors(cmap, n, cc = 0, callfn = None):\r\n if callfn is None: callfn = _get_cmap_colors.__name__\r\n # sanity checks\r\n if not isinstance(cmap, str):\r\n raise TypeError(\"{0}: error: cmap must be a string matplotlib color \"\r\n \"map\".format(callfn))\r\n if not isinstance(n, int):\r\n raise TypeError(\"{0}: error: n must be a positive integer\"\r\n \"\".format(callfn))\r\n if n < 1:\r\n raise ValueError(\"{0}: error: int n must be positive\".format(callfn))\r\n if (not isinstance(cc, float)) and (not isinstance(cc, int)):\r\n raise TypeError(\"{0}: error: cc must be a float in range [0, 1)\"\r\n \"\".format(callfn))\r\n if (cc < 0) or (cc >= 1):\r\n raise ValueError(\"{0}: error: float cc outside range [0, 1)\"\r\n \"\".format(callfn))\r\n # take range [0.5 * cc, 1 - 0.5 * cc] and split it into n pieces; the\r\n # collected points are midpoints of each interval. reduces color contrast.\r\n colors = [0.5 * cc + (1 - cc) * (i + 0.5) / n for i in range(n)]\r\n # try to get the colormap\r\n try: cmap = getattr(cm, cmap)\r\n except AttributeError as ae:\r\n ae.args = [\"{0}: error: unknown color map \\\"{1}\\\"\".format(callfn, cmap)]\r\n raise ae\r\n # if cmap is not a Colormap, raise a TypeError\r\n if not isinstance(cmap, Colormap):\r\n raise TypeError(\"{0}: error: {1} is not a valid Colormap\"\r\n \"\".format(callfn, cmap))\r\n # retrieve colors using color points and return\r\n for i in range(n): colors[i] = cmap(colors[i])\r\n # return ListedColormap from colors\r\n return ListedColormap(colors, name = cmap.name + \"_listed\", N = n)","def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name=\"shiftedcmap\"):\n cdict = {\"red\": [], \"green\": [], \"blue\": [], \"alpha\": []}\n\n # regular index to compute the colors\n reg_index = np.linspace(start, stop, 257)\n\n # shifted index to match the data\n shift_index = np.hstack(\n [\n np.linspace(0.0, midpoint, 128, endpoint=False),\n np.linspace(midpoint, 1.0, 129, endpoint=True),\n ]\n )\n\n for ri, si in zip(reg_index, shift_index):\n r, g, b, a = cmap(ri)\n\n cdict[\"red\"].append((si, r, r))\n cdict[\"green\"].append((si, g, g))\n cdict[\"blue\"].append((si, b, b))\n cdict[\"alpha\"].append((si, a, a))\n\n newcmap = mpl.colors.LinearSegmentedColormap(name, cdict)\n\n return newcmap","def compile_palette(palette_list):\n global _COMPILED_PALETTE\n _COMPILED_PALETTE = {}\n\n for color in palette_list:\n r_sum = math.fabs(color[0] ** _MAGNITUDE)\n g_sum = math.fabs(color[1] ** _MAGNITUDE)\n b_sum = math.fabs(color[2] ** _MAGNITUDE)\n\n _COMPILED_PALETTE[color] = [r_sum, g_sum, b_sum]","def map_values_to_color(self, df, col_name):\n # map values to colors in hex via\n # creating a hex Look up table table and apply the normalized data to it\n norm = mcolors.Normalize(vmin=np.nanmin(df[col_name].values),\n vmax=np.nanmax(df[col_name].values), clip=True)\n # alternative way of generating hex values\n # mapper = plt.cm.ScalarMappable(norm=norm, cmap=plt.cm.viridis)\n # a = mapper.to_rgba(df[col_name])\n # color_col_name = col_name + '_color'\n # df[color_col_name] = np.apply_along_axis(mcolors.to_hex, 1, a)\n\n lut = plt.cm.viridis(np.linspace(0,1,256))\n lut = np.apply_along_axis(mcolors.to_hex, 1, lut)\n a = (norm(df[col_name].values)*255).astype(np.int16)\n color_col_name = col_name + '_color'\n df[color_col_name] = lut[a]\n return df","def cmap2pixmap(cmap, steps=50):\n import numpy as np\n\n inds = np.linspace(0, 1, steps)\n n = len(cmap.clst) - 1\n tups = [cmap.clst[int(x * n)] for x in inds]\n rgbas = [QColor(int(r * 255), int(g * 255),\n int(b * 255), 255).rgba() for r, g, b in tups]\n im = QImage(steps, 1, QImage.Format_Indexed8)\n im.setColorTable(rgbas)\n for i in range(steps):\n im.setPixel(i, 0, i)\n im = im.scaled(128, 32)\n pm = QPixmap.fromImage(im)\n return pm","def cmap(self):\n return self._cmap"],"string":"[\n \"def palette_from_mpl_name(name):\\n if name in CMAPS:\\n return CMAPS[name]\\n\\n rgba = plt.get_cmap(name)(np.linspace(0, 1, 256))\\n palette = [to_hex(color) for color in rgba]\\n return palette\",\n \"def get_palette(palette_name):\\n\\n if hasattr(plt.cm, palette_name):\\n cmap = getattr(plt.cm, palette_name)\\n elif palette_name in list(mpl_cm.cmap_d.keys()):\\n cmap = mpl_cm.get_cmap(palette_name)\\n else:\\n print(\\\"Error, color option '\\\", palette_name, \\\"' not a valid option\\\")\\n sys.exit(1)\\n\\n return cmap\",\n \"def get_cmap(n, name='Paired'):\\n return plt.cm.get_cmap(name, n)\",\n \"def get_cmap(n, name='hsv'):\\n return plt.cm.get_cmap(name, n)\",\n \"def get_cmap(n, name='hsv'):\\n return plt.cm.get_cmap(name, n)\",\n \"def get_cmap(n, name='jet'):\\n return plt.cm.get_cmap(name, n)\",\n \"def get_cmap(n, name=\\\"hsv\\\"):\\n return plt.cm.get_cmap(name, n)\",\n \"def get_cmap(n, name=\\\"hsv\\\"):\\n return plt.cm.get_cmap(name, n)\",\n \"def get_cmap(n, name=\\\"hsv\\\"):\\n return plt.cm.get_cmap(name, n)\",\n \"def get_cmap(cmap=None):\\n if cmap:\\n if isinstance(cmap, (mpl.colors.Colormap)):\\n colormap = cmap\\n elif cmap in cmo.cmapnames:\\n colormap = cmo.cmap_d[cmap]\\n elif cmap in plt.colormaps():\\n colormap = plt.get_cmap(cmap)\\n else:\\n raise ValueError(\\n \\\"Get unrecognised name for the colormap `{}`. Colormaps should be from standard matplotlib set of from cmocean package.\\\".format(\\n cmap\\n )\\n )\\n else:\\n colormap = plt.get_cmap(\\\"Spectral_r\\\")\\n\\n return colormap\",\n \"def colormap(cats, mplmap='auto', categorical=None):\\n # Should automatically choose the right colormaps for:\\n # categorical data\\n # sequential data (low, high important)\\n # diverging data (low, mid, high important)\\n global DEF_SEQUENTIAL\\n from matplotlib import cm\\n\\n if hasattr(cm, 'inferno'):\\n DEF_SEQUENTIAL = 'inferno'\\n else:\\n DEF_SEQUENTIAL = 'BrBG'\\n\\n # strip units\\n units = None # TODO: build a color bar with units\\n if hasattr(cats[0], 'magnitude'):\\n arr = u.array(cats)\\n units = arr.units\\n cats = arr.magnitude\\n is_categorical = False\\n else:\\n is_categorical = not isinstance(cats[0], (float, int))\\n\\n if categorical is not None:\\n is_categorical = categorical\\n\\n if is_categorical:\\n values = _map_categories_to_ints(cats)\\n if mplmap == 'auto':\\n mplmap = DEF_CATEGORICAL\\n else:\\n values = np.array(list(map(float, cats)))\\n if mplmap == 'auto':\\n mplmap = DEF_SEQUENTIAL\\n\\n rgb = _cmap_to_rgb(mplmap, values)\\n hexcolors = [webcolors.rgb_to_hex(np.array(c)) for c in rgb]\\n return hexcolors\",\n \"def mpl_palette(name, n_colors=6):\\n brewer_qual_pals = {\\\"Accent\\\": 8, \\\"Dark2\\\": 8, \\\"Paired\\\": 12,\\n \\\"Pastel1\\\": 9, \\\"Pastel2\\\": 8,\\n \\\"Set1\\\": 9, \\\"Set2\\\": 8, \\\"Set3\\\": 12}\\n\\n if name.endswith(\\\"_d\\\"):\\n pal = [\\\"#333333\\\"]\\n pal.extend(color_palette(name.replace(\\\"_d\\\", \\\"_r\\\"), 2))\\n cmap = blend_palette(pal, n_colors, as_cmap=True)\\n else:\\n cmap = getattr(mpl.cm, name)\\n if name in brewer_qual_pals:\\n bins = np.linspace(0, 1, brewer_qual_pals[name])[:n_colors]\\n else:\\n bins = np.linspace(0, 1, n_colors + 2)[1:-1]\\n palette = list(map(tuple, cmap(bins)[:, :3]))\\n\\n return _ColorPalette(palette)\",\n \"def cmap_to_pil_palette(cmap):\\n # return (255.*np.array(\\n # map(lambda x: cmap(x)[0:3], np.linspace(0., 1.,256)))\\n # .ravel()).astype('int')\\n return (255. * np.array(\\n [cmap(x)[:3] for x in np.linspace(0,1,256)]).ravel().astype('int'))\",\n \"def make_colormap(colormap = 'rainbow_r', bins = 256, add_alpha = True, invert_alpha = False, cmap_name = 'costum',\\n discrete = False, return_cmap = False):\\n \\n if isinstance(colormap, str): # if input is string (so existent colormap)\\n\\n # get colormap\\n cmap = cm.get_cmap(colormap)\\n\\n else: # is list of strings\\n cvals = np.arange(len(colormap))\\n norm = plt.Normalize(min(cvals),max(cvals))\\n tuples = list(zip(map(norm,cvals), colormap))\\n cmap = colors.LinearSegmentedColormap.from_list(\\\"\\\", tuples)\\n \\n if discrete == True: # if we want a discrete colormap from list\\n cmap = colors.ListedColormap(colormap)\\n bins = int(len(colormap))\\n\\n # convert into array\\n cmap_array = cmap(range(bins))\\n\\n # reshape array for map\\n new_map = []\\n for i in range(cmap_array.shape[-1]):\\n new_map.append(np.tile(cmap_array[...,i],(bins,1)))\\n\\n new_map = np.moveaxis(np.array(new_map), 0, -1)\\n \\n if add_alpha: \\n # make alpha array\\n if invert_alpha == True: # in case we want to invert alpha (y from 1 to 0 instead pf 0 to 1)\\n _, alpha = np.meshgrid(np.linspace(0, 1, bins, endpoint=False), 1-np.linspace(0, 1, bins))\\n else:\\n _, alpha = np.meshgrid(np.linspace(0, 1, bins, endpoint=False), np.linspace(0, 1, bins, endpoint=False))\\n\\n # add alpha channel\\n new_map[...,-1] = alpha\\n cmap_ext = (0,1,0,1)\\n else:\\n new_map = new_map[:1,...].copy() \\n cmap_ext = (0,100,0,1)\\n \\n fig = plt.figure(figsize=(1,1))\\n ax = fig.add_axes([0,0,1,1])\\n # plot \\n plt.imshow(new_map,\\n extent = cmap_ext,\\n origin = 'lower')\\n ax.axis('off')\\n\\n if add_alpha: \\n rgb_fn = op.join(op.split(cortex.database.default_filestore)[\\n 0], 'colormaps', cmap_name+'_alpha_bins_%d.png'%bins)\\n else:\\n rgb_fn = op.join(op.split(cortex.database.default_filestore)[\\n 0], 'colormaps', cmap_name+'_bins_%d.png'%bins)\\n #misc.imsave(rgb_fn, new_map)\\n plt.savefig(rgb_fn, dpi = 200,transparent=True)\\n\\n if return_cmap:\\n return cmap\\n else:\\n return rgb_fn\",\n \"def cmap(num,cmap = plt.cm.gist_earth_r):\\n return cmap(np.linspace(0, 1, num))\",\n \"def generate_n_colors(n, cmap_name='tab20'):\\n pt_region_colormap = plt.get_cmap(cmap_name)\\n max_i = len(pt_region_colormap.colors)\\n return [pt_region_colormap(i % max_i) for i in range(n)]\",\n \"def color_mapper(cmap: str, vmin: float=0, vmax: float=1, alpha: float=1):\\n\\n alpha = int(255 * alpha)\\n\\n cmap = plt.get_cmap(cmap)\\n cNorm = Normalize(vmin=vmin, vmax=vmax)\\n scalarMap = cm.ScalarMappable(norm=cNorm, cmap=cmap)\\n\\n def mapper(value):\\n \\\"\\\"\\\"\\n This is the function that gets returned\\n\\n Parameters\\n ----------\\n value A number between vmin and vmax\\n\\n Returns\\n -------\\n An RGB color\\n\\n \\\"\\\"\\\"\\n\\n out = scalarMap.to_rgba(value)\\n\\n if isinstance(out, tuple):\\n return tuple([255 * out[i] for i in range(3)] + [alpha])\\n\\n elif isinstance(out, np.ndarray):\\n out[:, :-1] *= 255\\n out[:, 3] = alpha\\n return out\\n\\n return mapper\",\n \"def get_density_cmap():\\n # Add completely white color to Reds colormap in Matplotlib\\n list_colors = plt.cm.datad['Reds']\\n list_colors = list(list_colors)\\n list_colors.insert(0, (1, 1, 1))\\n list_colors.insert(0, (1, 1, 1))\\n lscm = matplotlib.colors.LinearSegmentedColormap.from_list(\\\"my_Reds\\\", list_colors)\\n return lscm\",\n \"def set_cmap_cb(self, w, index):\\n old_cmap_name = self._cmap_name\\n name = cmap.get_names()[index]\\n self.cmap_name = name\\n self.pipeline.push(StageAction(self,\\n dict(cmap_name=old_cmap_name),\\n dict(cmap_name=self._cmap_name),\\n descr=\\\"rgbmap / change cmap\\\"))\\n\\n self.pipeline.run_from(self)\",\n \"def discrete_cmap(n_colors: int, base_cmap: str) -> Colormap:\\r\\n # https://gist.github.com/jakevdp/91077b0cae40f8f8244a\\r\\n base = plt.cm.get_cmap(base_cmap)\\r\\n color_list = base(np.linspace(0, 1, n_colors))\\r\\n cmap_name = base.name + str(n_colors)\\r\\n\\r\\n return base.from_list(cmap_name, color_list, n_colors)\",\n \"def create_label_colormap():\\n colormap = np.array([\\n [128, 64, 128],\\n [244, 35, 232],\\n [ 70, 70, 70],\\n [102, 102, 156],\\n [190, 153, 153],\\n [153, 153, 153],\\n [250, 170, 30],\\n [220, 220, 0],\\n [107, 142, 35],\\n [152, 251, 152],\\n [ 70, 130, 180],\\n [220, 20, 60],\\n [255, 0, 0],\\n [ 0, 0, 142],\\n [ 0, 0, 70],\\n [ 0, 60, 100],\\n [ 0, 80, 100],\\n [ 0, 0, 230],\\n [119, 11, 32],\\n [ 0, 0, 0]], dtype=np.uint8)\\n return colormap\",\n \"def colormap(self):\\n palette = [(0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0), (0, 0, 0),\\n (111, 74, 0), (81, 0, 81), (128, 64, 128), (244, 35, 232),\\n (250, 170, 160), (230, 150, 140), (70, 70, 70),\\n (102, 102, 156), (190, 153, 153), (180, 165, 180),\\n (150, 100, 100), (150, 120, 90), (153, 153, 153),\\n (153, 153, 153), (250, 170, 30), (220, 220, 0),\\n (107, 142, 35), (152, 251, 152), (70, 130, 180),\\n (220, 20, 60), (255, 0, 0), (0, 0, 142), (0, 0, 70),\\n (0, 60, 100), (0, 0, 90), (0, 0, 110), (0, 80, 100),\\n (0, 0, 230), (119, 11, 32), (0, 0, 142)]\\n\\n num_colors = self[0][1].shape[-1]\\n colormap = np.zeros((num_colors, 3), dtype=int)\\n for i in range(num_colors):\\n colormap[i, ...] = palette[self._update_labels_dict[i]]\\n return colormap\",\n \"def create_cycler_colors(color_scheme):\\n cmap = cm.get_cmap(color_scheme) # PiYG\\n cycler_colors = []\\n\\n for i in range(cmap.N):\\n rgba = cmap(i)\\n # rgb2hex accepts rgb or rgba\\n cycler_colors.append(matplotlib.colors.rgb2hex(rgba)) \\n \\n return cycler_colors\",\n \"def set_cmap(self, cmap: str | Colormap | matplotlib.colors.Colormap):\\n if self._image is None:\\n raise RuntimeError(\\\"You add data with `set_data` before setting cmaps\\\")\\n self._image.set_cmap(cmap)\\n self._widget._mgui_set_value(self._image.make_image())\",\n \"def cmap(self):\\n return self._palette\",\n \"def _color_palette(n_colors=4, cmap='viridis', extrema=False):\\n if extrema:\\n bins = np.linspace(0, 1, n_colors)\\n else:\\n bins = np.linspace(0, 1, n_colors * 2 - 1 + 2)[1:-1:2]\\n\\n cmap = plt.get_cmap(cmap)\\n palette = list(map(tuple, cmap(bins)[:, :3]))\\n return palette\",\n \"def set_palette(name=\\\"default\\\", ncontours=255):\\n\\n if name == \\\"gray\\\" or name == \\\"grayscale\\\":\\n stops = [0.00, 0.34, 0.61, 0.84, 1.00]\\n red = [1.00, 0.95, 0.95, 0.65, 0.15]\\n green = [1.00, 0.85, 0.7, 0.5, 0.3]\\n blue = [0.95, 0.6, 0.3, 0.45, 0.65]\\n # elif name == \\\"whatever\\\":\\n # (define more palettes)\\n elif name == \\\"chris\\\":\\n stops = [ 0.00, 0.34, 0.61, 0.84, 1.00 ]\\n red = [ 1.0, 0.95, 0.95, 0.65, 0.15 ]\\n green = [ 1.0, 0.85, 0.7, 0.5, 0.3 ]\\n blue = [ 0.95, 0.6 , 0.3, 0.45, 0.65 ]\\n else:\\n # default palette, looks cool\\n stops = [0.00, 0.34, 0.61, 0.84, 1.00]\\n red = [0.00, 0.00, 0.87, 1.00, 0.51]\\n green = [0.00, 0.81, 1.00, 0.20, 0.00]\\n blue = [0.51, 1.00, 0.12, 0.00, 0.00]\\n\\n s = array('d', stops)\\n r = array('d', red)\\n g = array('d', green)\\n b = array('d', blue)\\n\\n npoints = len(s)\\n rt.TColor.CreateGradientColorTable(npoints, s, r, g, b, ncontours)\\n rt.gStyle.SetNumberContours(ncontours)\",\n \"def assigning_colors():\\n rgb_colors = {}\\n for name, hex in matplotlib.colors.cnames.items():\\n color = []\\n # So the values are from 0-255 and not 0-1\\n for i in matplotlib.colors.to_rgb(hex):\\n color.append(int(i * 255))\\n\\n color = tuple(color)\\n rgb_colors[name] = color\\n\\n return rgb_colors\",\n \"def getColorMap(colors):\\n # Normalise RGBs\\n norm_colors = []\\n for color in colors:\\n norm_colors.append([val / 255. for val in color])\\n # create color map\\n cmap = cols.ListedColormap(norm_colors)\\n\\n return cmap\",\n \"def grayscale_cmap(cmap):\\n # cmap = cm.get_cmap(cmap)\\n map_colors = cmap(np.arange(cmap.N))\\n\\n # convert RGBA to perceived grayscale luminance\\n # cf. http://alienryderflex.com/hsp.html\\n RGB_weight = [0.299, 0.587, 0.114]\\n luminance = np.sqrt(np.dot(map_colors[:, :3] ** 2, RGB_weight))\\n map_colors[:, :3] = luminance[:, np.newaxis]\\n\\n return colors.LinearSegmentedColormap.from_list(cmap.name + \\\"_gray\\\", map_colors, cmap.N)\",\n \"def plot_cmap(cmap):\\n gradient = np.linspace(0, 1, 256)\\n gradient = np.vstack((gradient, gradient))\\n pylab.imshow(gradient, aspect='auto', cmap=cmap)\\n pylab.show()\",\n \"def discrete_cmap(N, base_cmap=None):\\n base = plt.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def register_cccmacms(cmap='all'):\\n \\n \\n #print 'registering cmaps'\\n \\n \\n \\n \\n \\n \\n # define individual colors as RGB triples\\n \\n \\n # from colorwheel.m\\n \\n \\n # =============================================\\n \\n \\n # kem_w20 (20) OR blue2red_w20\\n \\n \\n # blueish at top, white in middle, reddish at bottom\\n \\n \\n \\n cpool = np.array([ [153,255,255], \\\\\\n \\n \\n [204,255,229], \\\\\\n \\n \\n [240,255,240],\\\\\\n \\n \\n [204,255,153],\\\\\\n \\n \\n [178,255,102],\\\\\\n \\n \\n [216,255,76],\\\\\\n \\n \\n [255,255,51],\\\\\\n \\n \\n [255,220,51],\\\\\\n \\n \\n [255,187,51],\\\\\\n \\n \\n [255,153,51],\\\\\\n \\n \\n [255,0,0],\\\\\\n \\n \\n [204,0,0],\\\\\\n \\n \\n [153,0,0]], \\\\\\n \\n \\n dtype=float)\\n \\n \\n \\n acccbar = (cpool/255.)\\n \\n \\n thecmap = col.ListedColormap(acccbar,'acccbar')\\n \\n \\n cm.register_cmap(cmap=thecmap)\\n\\n return\",\n \"def color_palette(n_colors=4, cmap='viridis', extrema=False):\\n if extrema:\\n bins = np.linspace(0, 1, n_colors)\\n else:\\n bins = np.linspace(0, 1, n_colors * 2 - 1 + 2)[1:-1:2]\\n\\n cmap = plt.get_cmap(cmap)\\n palette = list(map(tuple, cmap(bins)[:, :3]))\\n return palette\",\n \"def discrete_cmap(N, base_cmap=None):\\n # Note that if base_cmap is a string or None, you can simply do\\n # return plt.cm.get_cmap(base_cmap, N)\\n # The following works for string, None, or a colormap instance:\\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def discrete_cmap(N, base_cmap=None):\\n\\n # Note that if base_cmap is a string or None, you can simply do\\n # return plt.cm.get_cmap(base_cmap, N)\\n # The following works for string, None, or a colormap instance:\\n\\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def discrete_cmap(N, base_cmap=None):\\n\\n # Note that if base_cmap is a string or None, you can simply do\\n # return plt.cm.get_cmap(base_cmap, N)\\n # The following works for string, None, or a colormap instance:\\n\\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def discrete_cmap(N, base_cmap=None):\\n\\n # Note that if base_cmap is a string or None, you can simply do\\n # return plt.cm.get_cmap(base_cmap, N)\\n # The following works for string, None, or a colormap instance:\\n\\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def discrete_cmap(N, base_cmap=None):\\n\\n # Note that if base_cmap is a string or None, you can simply do\\n # return plt.cm.get_cmap(base_cmap, N)\\n # The following works for string, None, or a colormap instance:\\n\\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def display_cmap_color_range(cmap_style='rainbow'):\\n cmap = plt.get_cmap(cmap_style)\\n for c in range(256):\\n plt.scatter([c], [0], s=500, c=cmap(c), lw=0)\\n plt.show()\",\n \"def get_colormap(values, cmap='jet', colorbar=True, log=False):\\n by_value = not isinstance(values, int)\\n if not by_value:\\n colorbar = False\\n if by_value:\\n cmap = plt.get_cmap(cmap)\\n if log:\\n colors = [cmap(x) for x in tools.maths.normalise(np.log10(values))]\\n else:\\n colors = [cmap(x) for x in tools.maths.normalise(np.array(values))]\\n else:\\n cmap = plt.get_cmap(cmap, values)\\n colors = [cmap(x) for x in range(values)]\\n if colorbar:\\n if log:\\n norm = mpl.colors.LogNorm(vmin=min(values), vmax=max(values))\\n else:\\n norm = mpl.colors.Normalize(vmin=min(values), vmax=max(values))\\n sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)\\n sm.set_array([])\\n if isinstance(colorbar, str):\\n label = colorbar\\n else:\\n label = ''\\n plt.colorbar(sm, label=label)\\n return colors\",\n \"def get_cmap(n):\\n cmap_fn = plt.cm.get_cmap('hsv', n+1)\\n colors = [cmap_fn(i + 1)[:3] for i in range(n)]\\n random.shuffle(colors)\\n cmap = (np.array(colors) * 255.0).astype(np.uint8)\\n return cmap\",\n \"def colors_to_cmap(colors):\\n colors = np.asarray(colors)\\n if colors.shape[1] == 3:\\n colors = np.hstack((colors, np.ones((len(colors),1))))\\n steps = (0.5 + np.asarray(range(len(colors)-1), dtype=np.float))/(len(colors) - 1)\\n return matplotlib.colors.LinearSegmentedColormap(\\n 'auto_cmap',\\n {clrname: ([(0, col[0], col[0])] + \\n [(step, c0, c1) for (step,c0,c1) in zip(steps, col[:-1], col[1:])] + \\n [(1, col[-1], col[-1])])\\n for (clridx,clrname) in enumerate(['red', 'green', 'blue', 'alpha'])\\n for col in [colors[:,clridx]]},\\n N=len(colors))\",\n \"def discrete_cmap(N, base_cmap=None):\\n \\n # Note that if base_cmap is a string or None, you can simply do\\n # return plt.cm.get_cmap(base_cmap, N)\\n # The following works for string, None, or a colormap instance:\\n \\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def discrete_cmap(N, base_cmap=None):\\n \\n # Note that if base_cmap is a string or None, you can simply do\\n # return plt.cm.get_cmap(base_cmap, N)\\n # The following works for string, None, or a colormap instance:\\n \\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def discrete_cmap(N, base_cmap=None):\\n \\n # Note that if base_cmap is a string or None, you can simply do\\n # return plt.cm.get_cmap(base_cmap, N)\\n # The following works for string, None, or a colormap instance:\\n \\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def discrete_cmap(N, base_cmap=None):\\n # see https://gist.github.com/jakevdp/91077b0cae40f8f8244a\\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def generate_mass_palette(masses):\\n mass_cmap = matplotlib.cm.get_cmap(\\\"plasma\\\")\\n palette = {mass: mass_cmap(i / len(masses)) for i, mass in enumerate(masses)}\\n palette[999] = \\\"grey\\\" # total pressure\\n palette[5] = \\\"black\\\" # Pirani pressure\\n return palette\",\n \"def generate_colormap(scale_range=(0.0, 1.0), hue_range=(0.8, 0.0),\\n saturation_range=(1.0, 1.0), value_range=(0.8, 0.8),\\n nan_color=(0.2, 0.2, 0.2, 1.0)):\\n lookup_table = vtk.vtkLookupTable()\\n lookup_table.SetRange(scale_range)\\n\\n lookup_table.SetHueRange(hue_range)\\n lookup_table.SetSaturationRange(saturation_range)\\n lookup_table.SetValueRange(value_range)\\n lookup_table.SetNanColor(nan_color)\\n lookup_table.Build()\\n return lookup_table\",\n \"def discrete_cmap(N, base_cmap=None):\\n\\n # Note that if base_cmap is a string or None, you can simply do\\n # return plt.cm.get_cmap(base_cmap, N)\\n # The following works for string, None, or a colormap instance:\\n # By Jake VanderPlas\\n # License: BSD-style\\n\\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return base.from_list(cmap_name, color_list, N)\",\n \"def discrete_cmap(N, base_cmap=None):\\n\\t# Note that if base_cmap is a string or None, you can simply do\\n\\t# return plt.cm.get_cmap(base_cmap, N)\\n\\t# The following works for string, None, or a colormap instance:\\n\\tbase = plt.cm.get_cmap(base_cmap)\\n\\tcolor_list = base(np.linspace(0, 1, N))\\n\\tcmap_name = base.name + str(N)\\n\\treturn base.from_list(cmap_name, color_list, N)\",\n \"def check_colormap(cmap):\\n names = set(['BrBG', 'PiYG', 'PRGn', 'PuOr', 'RdBu', 'RdGy', 'RdYlBu', 'RdYlGn', 'Spectral',\\n 'Blues', 'BuGn', 'BuPu', 'GnBu', 'Greens', 'Greys', 'Oranges', 'OrRd', 'PuBu',\\n 'PuBuGn', 'PuRd', 'Purples', 'RdPu', 'Reds', 'YlGn', 'YlGnBu', 'YlOrBr', 'YlOrRd',\\n 'Accent', 'Dark2', 'Paired', 'Pastel1', 'Pastel2', 'Set1', 'Set2', 'Set3', 'Lightning'])\\n if cmap not in names:\\n raise Exception(\\\"Invalid cmap '%s', must be one of %s\\\" % (cmap, names))\\n else:\\n return cmap\",\n \"def get_colors(nlevels, colormap=None):\\n if colormap is None:\\n from matplotlib.pyplot import cm\\n colormap = cm.rainbow\\n return colormap(np.linspace(0, 1, nlevels))\",\n \"def discrete_cmap(N, base_cmap=None):\\n\\n # Note that if base_cmap is a string or None, you can simply do\\n # return plt.cm.get_cmap(base_cmap, N)\\n # The following works for string, None, or a colormap instance:\\n\\n base = plt.cm.get_cmap(base_cmap)\\n color_list = base(np.linspace(0, 1, N))\\n cmap_name = base.name + str(N)\\n return matplotlib.colors.LinearSegmentedColormap \\\\\\n .from_list(cmap_name, color_list, N)\",\n \"def test_colormap_discrete():\\n with TestingCanvas(size=size, bgcolor='w') as c:\\n idata = np.linspace(255, 0, size[0]*size[1]).astype(np.ubyte)\\n data = idata.reshape((size[0], size[1]))\\n image = Image(cmap=Colormap(colors=['r', 'g', 'b'],\\n interpolation='zero'),\\n clim='auto', parent=c.scene)\\n image.set_data(data)\\n assert_image_approved(c.render(), \\\"visuals/colormap_rgb.png\\\")\",\n \"def test_density_colormap(self):\\n cmap = matplotlib.cm.get_cmap('density')\\n np.testing.assert_allclose(cmap(0.0), [0.214, 0.152, 0.535, 1], atol=0.001)\\n np.testing.assert_allclose(cmap(1.0), [0.988, 0.978, 0.042, 1], atol=0.001)\",\n \"def _get_colors(num_colors):\\n cmap = plt.get_cmap()\\n return [cmap(1. * i / num_colors) for i in range(num_colors)]\",\n \"def make_colormap(colors):\\n#-------------------------\\n from matplotlib.colors import LinearSegmentedColormap, ColorConverter\\n from numpy import sort\\n z = sort(colors.keys())\\n n = len(z)\\n z1 = min(z)\\n zn = max(z)\\n x0 = (z - z1) / (zn - z1)\\n CC = ColorConverter()\\n R = []\\n G = []\\n B = []\\n for i in range(n):\\n #i'th color at level z[i]:\\n Ci = colors[z[i]]\\n if type(Ci) == str:\\n # a hex string of form '#ff0000' for example (for red)\\n RGB = CC.to_rgb(Ci)\\n else:\\n # assume it's an RGB triple already:\\n RGB = Ci\\n R.append(RGB[0])\\n G.append(RGB[1])\\n B.append(RGB[2])\\n cmap_dict = {}\\n cmap_dict['red'] = [(x0[i],R[i],R[i]) for i in range(len(R))]\\n cmap_dict['green'] = [(x0[i],G[i],G[i]) for i in range(len(G))]\\n cmap_dict['blue'] = [(x0[i],B[i],B[i]) for i in range(len(B))]\\n mymap = LinearSegmentedColormap('mymap',cmap_dict)\\n return mymap\",\n \"def transparent_cmap(cmap, N=255):\\n if type(cmap) == str:\\n mycmap = plt.get_cmap(cmap)\\n else:\\n mycmap = cmap\\n mycmap._init()\\n mycmap._lut[0, -1] = 0\\n return mycmap\",\n \"def create_pascal_label_colormap():\\r\\n colormap = np.zeros((256, 3), dtype = int)\\r\\n ind = np.arange(256, dtype=int)\\r\\n\\r\\n for shift in reversed(range(8)):\\r\\n for channel in range(3):\\r\\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\\r\\n ind >>= 3\\r\\n\\r\\n return colormap\",\n \"def test_colormap():\\n with TestingCanvas(size=size, bgcolor='w') as c:\\n idata = np.linspace(255, 0, size[0]*size[1]).astype(np.ubyte)\\n data = idata.reshape((size[0], size[1]))\\n image = Image(cmap=Colormap(colors=['k', 'w', 'r'],\\n controls=[0.0, 0.1, 1.0]),\\n clim='auto', parent=c.scene)\\n image.set_data(data)\\n assert_image_approved(c.render(), \\\"visuals/colormap_kwr.png\\\")\",\n \"def get_mpl_colormap(self):\\n return mpl.colors.ListedColormap(self.get_colors().astype(float) / 255.0)\",\n \"def create_pascal_label_colormap():\\n colormap = np.zeros((256, 3), dtype=int)\\n ind = np.arange(256, dtype=int)\\n\\n for shift in reversed(range(8)):\\n for channel in range(3):\\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\\n ind >>= 3\\n\\n return colormap\",\n \"def create_pascal_label_colormap():\\n colormap = np.zeros((256, 3), dtype=int)\\n ind = np.arange(256, dtype=int)\\n\\n for shift in reversed(range(8)):\\n for channel in range(3):\\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\\n ind >>= 3\\n\\n return colormap\",\n \"def create_pascal_label_colormap():\\n colormap = np.zeros((256, 3), dtype=int)\\n ind = np.arange(256, dtype=int)\\n\\n for shift in reversed(range(8)):\\n for channel in range(3):\\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\\n ind >>= 3\\n\\n return colormap\",\n \"def create_pascal_label_colormap():\\n colormap = np.zeros((256, 3), dtype=int)\\n ind = np.arange(256, dtype=int)\\n\\n for shift in reversed(range(8)):\\n for channel in range(3):\\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\\n ind >>= 3\\n\\n return colormap\",\n \"def norm_cmap(values, cmap, vmin=None, vmax=None):\\n mn = vmin or min(values)\\n mx = vmax or max(values)\\n norm = Normalize(vmin=mn, vmax=mx)\\n n_cmap = plt.cm.ScalarMappable(norm=norm, cmap=cmap)\\n\\n rgb_colors = [n_cmap.to_rgba(value) for value in values]\\n\\n return n_cmap, rgb_colors\",\n \"def parse_cmap(cmap, field=None):\\n if cmap is None:\\n cmap = get_field_colormap(field)\\n return cmap\",\n \"def SetColorMap(self, colormap, contrast=None, bias=None):\\n extra = ''\\n if contrast is not None:\\n extra += '%f,' % contrast\\n if bias is not None:\\n extra += '%f,' % bias\\n fmt = dict(wid=self.wid,cmap=colormap, extra=extra, suffix=self.suffix)\\n command = \\\"JS9.SetColormap('{cmap}', {extra} {{display:'{wid}{suffix}'}});\\\".format(**fmt)\\n get_ipython().run_cell_magic('javascript', '', command)\",\n \"def transparent_cmap(cmap, alpha=0.8, N=255):\\n mycmap = cmap\\n mycmap._init()\\n mycmap._lut[:, -1] = np.linspace(0, alpha, N + 4)\\n return mycmap\",\n \"def get_colormap(level_values: np.ndarray) -> np.ndarray:\\n color_dimension = level_values # change to desired fourth dimension\\n color_min, color_max = color_dimension.min(), color_dimension.max()\\n norm = colors.Normalize(color_min, color_max)\\n m = plt.cm.ScalarMappable(norm=norm, cmap=\\\"Spectral_r\\\")\\n m.set_array([])\\n face_colors = m.to_rgba(color_dimension)\\n\\n return face_colors\",\n \"def create_pascal_label_colormap():\\n colormap = np.zeros((256, 3), dtype=int)\\n ind = np.arrange(256, dtype=int)\\n\\n for shift in reversed(range(8)):\\n for channel in range(3):\\n colormap[:, channel] |= ((ind >> channel) & 1) << shift\\n ind >>=3\\n\\n return colormap\",\n \"def from_name (name_str):\\n if name_str in colour_names:\\n return Colour(*colour_names[name_str])\\n raise KeyError(\\\"'%s' is not a recognized colour name\\\"%name_str)\",\n \"def gen_colors(nbeads):\\n\\n # use colormap (blue, red, green)\\n # blue 0.0, 0.0, 1.0\\n # red: 1.0, 0.0, 0.0\\n # green: 0.0, 1.0, 1.0\\n\\n my_cmap = cm.get_cmap('jet')\\n minval = 0\\n maxval = nbeads - 1\\n norm = mplcolors.Normalize(minval, maxval)\\n \\n sphere_rgbcolor = []\\n for i in range(nbeads):\\n si = my_cmap(norm(i))\\n sphere_rgbcolor.append([si[0], si[1], si[2]])\\n\\n return sphere_rgbcolor\",\n \"def create_colormap(color_list: Sequence[str], n_colors: int) -> NDArrayFloat:\\n cmap = LinearSegmentedColormap.from_list(name=\\\"dummy_name\\\", colors=color_list)\\n colorscale: NDArrayFloat = np.array(\\n [cmap(k * 1 / n_colors) for k in range(n_colors)]\\n )\\n # ignore the 4th alpha channel\\n return colorscale[:, :3]\",\n \"def create_riskmap(colormap):\\n \\n # Note that this code is tricky - remember to return a lambda expression\\n risk_norm = mpl.colors.Normalize(vmin = MIN_LOG_RISK, vmax = MAX_LOG_RISK)\\n color_mapper = mpl.cm.ScalarMappable(norm = risk_norm, cmap = colormap)\\n return lambda risk : color_mapper.to_rgba(math.log(risk, 10))\",\n \"def _create_color_map(self, hue, data):\\n if hue in self.categorical_columns:\\n # adding suffix to column name to get unique str values\\n factors = sorted(set(data[hue + self.categorical_suffix]))\\n if len(factors) <= self._max_categories_internal_limit:\\n cmap = factor_cmap(\\n hue + self.categorical_suffix,\\n palette=self._categorical_palette[len(factors)],\\n factors=factors\\n )\\n else:\\n # If there is too many categories, None is returned\\n cmap = None\\n else:\\n values = data[hue]\\n cmap = linear_cmap(\\n hue,\\n palette=self.plot_design.contrary_color_linear_palette,\\n low=min(values),\\n high=max(values)\\n )\\n\\n return cmap\",\n \"def get_colormap(self):\\n return colors.colormaps[self.name]\",\n \"def get_colormap(self):\\n return colors.colormaps[self.name]\",\n \"def transparent_cmap(cmap, alpha, N=255):\\n mycmap = cmap\\n mycmap._init()\\n mycmap._lut[:, -1] = np.linspace(0, 0.8, N + 4)\\n return mycmap\",\n \"def create_colour_scheme(alphabet=\\\"cinema\\\", colourscheme=\\\"hls\\\"):\\n \\n # List of all available alphabets from pepdata library + the all / dna alphabet\\n alphabets_available = [\\\"cinema\\\", \\\"all\\\", \\\"dna\\\", \\\"gbmr4\\\", \\\"sdm12\\\", \\\"hsdm17\\\", \\n \\\"hp2\\\", \\\"murphy10\\\", \\\"alex6\\\", \\\"aromatic2\\\", \\\"hp_vs_aromatic\\\"]\\n # Default value, colouring scheme as used in the cinema alignment tool\\n if alphabet == \\\"cinema\\\":\\n return {\\\"A\\\": \\\"#c1ffc1\\\", \\\"B\\\": \\\"#ffffff\\\", \\\"C\\\": \\\"#50d433\\\", \\\"D\\\": \\\"#088446\\\",\\n \\\"E\\\": \\\"#088446\\\", \\\"F\\\": \\\"#de94e3\\\", \\\"G\\\": \\\"#c1ffc1\\\", \\\"H\\\": \\\"#191996\\\",\\n \\\"I\\\": \\\"#91b4ff\\\", \\\"J\\\": \\\"#ffffff\\\", \\\"K\\\": \\\"#ffa500\\\", \\\"L\\\": \\\"#91b4ff\\\",\\n \\\"M\\\": \\\"#91b4ff\\\", \\\"N\\\": \\\"#088446\\\", \\\"O\\\": \\\"#ffffff\\\", \\\"P\\\": \\\"#ffb6c1\\\",\\n \\\"Q\\\": \\\"#088446\\\", \\\"R\\\": \\\"#ffa500\\\", \\\"S\\\": \\\"#ce0000\\\", \\\"T\\\": \\\"#ce0000\\\",\\n \\\"U\\\": \\\"#ffffff\\\", \\\"V\\\": \\\"#91b4ff\\\", \\\"W\\\": \\\"#de94e3\\\", \\\"X\\\": \\\"#ffffff\\\",\\n \\\"Y\\\": \\\"#de94e3\\\", \\\"Z\\\": \\\"#ffffff\\\"}\\n # If the alphabet is found in the reduced alphabets file:\\n if alphabet in alphabets_available:\\n alphabet = eval(alphabet)\\n alphabet_values = set(alphabet.values())\\n colours = sns.color_palette(colourscheme, len(alphabet_values)).as_hex()\\n for keys in alphabet.keys():\\n alphabet[keys] = colours[alphabet[keys]]\\n else:\\n print(\\\"Colour input\\\", alphabet, \\\"not available.\\\")\\n sys.exit(1)\\n return alphabet\",\n \"def colorify(data, vmin=None, vmax=None, cmap=plt.cm.Spectral):\\n import matplotlib.colors as colors\\n\\n _vmin = vmin or min(data)\\n _vmax = vmax or max(data)\\n cNorm = colors.normalize(vmin=_vmin, vmax=_vmax)\\n\\n scalarMap = plt.cm.ScalarMappable(norm=cNorm, cmap=cmap)\\n colors = map(scalarMap.to_rgba, data)\\n return colors, scalarMap\",\n \"def fl_mapcolorname(colr, rgbcolrname):\\n _fl_mapcolorname = library.cfuncproto(\\n library.load_so_libforms(), \\\"fl_mapcolorname\\\",\\\\\\n cty.c_long, [xfdata.FL_COLOR, xfdata.STRING],\\\\\\n \\\"\\\"\\\"long int fl_mapcolorname(FL_COLOR col, const char * name)\\\"\\\"\\\")\\n library.check_if_flinitialized()\\n #library.checknonfatal_allowed_value_in_list(colr, xfdata.COLOR_list)\\n ul_colr = library.convert_to_FL_COLOR(colr)\\n s_rgbcolrname = library.convert_to_bytestrc(rgbcolrname)\\n library.keep_elem_refs(colr, ul_colr, rgbcolrname, s_rgbcolrname)\\n retval = _fl_mapcolorname(ul_colr, s_rgbcolrname)\\n return retval\",\n \"def _to_plotly_palette(scl, transparence=None):\\n if not MATPLOTLIB_INSTALLED:\\n soft_dependency_error(str(sys._getframe().f_code.co_name)+\\\"()\\\", \\\"matplotlib\\\")\\n _out = []\\n for color in scl:\\n plotly_col = [255 * _c for _c in mplc.to_rgba(color)]\\n if transparence:\\n assert 0. <= transparence <= 1.0\\n plotly_col[3] = transparence\\n plotly_col = \\\"rgba({:.0f}, {:.0f}, {:.0f}, {:.4f})\\\".format(*plotly_col)\\n else:\\n plotly_col = \\\"rgb({:.0f}, {:.0f}, {:.0f})\\\".format(*plotly_col[:3])\\n _out.append(plotly_col)\\n return _out\",\n \"def create_cityscapes_label_colormap():\\r\\n colormap = np.zeros((256, 3), dtype=np.uint8)\\r\\n colormap[0] = [128, 64, 128]\\r\\n colormap[1] = [244, 35, 232]\\r\\n colormap[2] = [70, 70, 70]\\r\\n colormap[3] = [102, 102, 156]\\r\\n colormap[4] = [190, 153, 153]\\r\\n colormap[5] = [153, 153, 153]\\r\\n colormap[6] = [250, 170, 30]\\r\\n colormap[7] = [220, 220, 0]\\r\\n colormap[8] = [107, 142, 35]\\r\\n colormap[9] = [152, 251, 152]\\r\\n colormap[10] = [70, 130, 180]\\r\\n colormap[11] = [220, 20, 60]\\r\\n colormap[12] = [255, 0, 0]\\r\\n colormap[13] = [0, 0, 142]\\r\\n colormap[14] = [0, 0, 70]\\r\\n colormap[15] = [0, 60, 100]\\r\\n colormap[16] = [0, 80, 100]\\r\\n colormap[17] = [0, 0, 230]\\r\\n colormap[18] = [119, 11, 32]\\r\\n return colormap\",\n \"def _to_plotly_palette(scl, transparence=None):\\n if transparence:\\n return ['rgb({0},{1},{2},{3})'.format(r*255, g*255, b*255, transparence) for r, g, b in scl]\\n else:\\n return ['rgb({0},{1},{2})'.format(r*255, g*255, b*255) for r, g, b in scl]\",\n \"def _map_to_2d_cmap(data1, data2, vmin, vmax, vmin2, vmax2, cmap):\\n # load 2D cmap image\\n cmap_directory = cortex.options.config.get(\\\"webgl\\\", \\\"colormaps\\\")\\n cmap_image = plt.imread(os.path.join(cmap_directory, \\\"%s.png\\\" % cmap))\\n\\n # Normalize the data\\n dim1 = np.clip(Normalize(vmin, vmax)(data1), 0, 1)\\n dim2 = np.clip(1 - Normalize(vmin2, vmax2)(data2), 0, 1)\\n\\n # 2D indices of the data on the 2D cmap\\n dim1 = np.round(dim1 * (cmap_image.shape[1] - 1))\\n dim1 = np.nan_to_num(dim1).astype(np.uint32)\\n dim2 = np.round(dim2 * (cmap_image.shape[0] - 1))\\n dim2 = np.nan_to_num(dim2).astype(np.uint32)\\n\\n mapped_rgba = cmap_image[dim2.ravel(), dim1.ravel()]\\n\\n # Preserve nan values with alpha = 0\\n nans = np.logical_or(np.isnan(data1), np.isnan(data2))\\n mapped_rgba[nans, 3] = 0\\n\\n return mapped_rgba, cmap_image\",\n \"def test_colormap_single_hue():\\n with TestingCanvas(size=size, bgcolor='w') as c:\\n idata = np.linspace(255, 0, size[0]*size[1]).astype(np.ubyte)\\n data = idata.reshape((size[0], size[1]))\\n image = Image(cmap=get_colormap('single_hue', 255),\\n clim='auto', parent=c.scene)\\n image.set_data(data)\\n assert_image_approved(c.render(), \\\"visuals/colormap_hue.png\\\")\",\n \"def remap_prefixes(cmap):\\n cmap[\\\"MGI\\\"] = \\\"http://identifiers.org/mgi/MGI:\\\"\\n cmap[\\\"WB\\\"] = \\\"http://identifiers.org/wormbase/\\\"\\n return cmap\",\n \"def molmol_colours(name):\\n\\n # Initialise the dictionary of colours.\\n colours = {}\\n\\n # The colours sorted by the RGB float values.\\n colours['black'] = [0.000, 0.000, 0.000]\\n colours['navy'] = [0.000, 0.000, 0.502]\\n colours['blue'] = [0.000, 0.000, 1.000]\\n colours['dark green'] = [0.000, 0.392, 0.000]\\n colours['green'] = [0.000, 1.000, 0.000]\\n colours['cyan'] = [0.000, 1.000, 1.000]\\n colours['turquoise'] = [0.251, 0.878, 0.816]\\n colours['royal blue'] = [0.255, 0.412, 0.882]\\n colours['aquamarine'] = [0.498, 1.000, 0.831]\\n colours['sky green'] = [0.529, 0.808, 0.922]\\n colours['dark violet'] = [0.580, 0.000, 0.827]\\n colours['pale green'] = [0.596, 0.984, 0.596]\\n colours['purple'] = [0.627, 0.125, 0.941]\\n colours['brown'] = [0.647, 0.165, 0.165]\\n colours['light blue'] = [0.678, 0.847, 0.902]\\n colours['grey'] = [0.745, 0.745, 0.745]\\n colours['light grey'] = [0.827, 0.827, 0.827]\\n colours['violet'] = [0.933, 0.510, 0.933]\\n colours['light coral'] = [0.941, 0.502, 0.502]\\n colours['khaki'] = [0.941, 0.902, 0.549]\\n colours['beige'] = [0.961, 0.961, 0.863]\\n colours['red'] = [1.000, 0.000, 0.000]\\n colours['magenta'] = [1.000, 0.000, 1.000]\\n colours['deep pink'] = [1.000, 0.078, 0.576]\\n colours['orange red'] = [1.000, 0.271, 0.000]\\n colours['hot pink'] = [1.000, 0.412, 0.706]\\n colours['coral'] = [1.000, 0.498, 0.314]\\n colours['dark orange'] = [1.000, 0.549, 0.000]\\n colours['orange'] = [1.000, 0.647, 0.000]\\n colours['pink'] = [1.000, 0.753, 0.796]\\n colours['gold'] = [1.000, 0.843, 0.000]\\n colours['yellow'] = [1.000, 1.000, 0.000]\\n colours['light yellow'] = [1.000, 1.000, 0.878]\\n colours['ivory'] = [1.000, 1.000, 0.941]\\n colours['white'] = [1.000, 1.000, 1.000]\\n\\n # Convert to numpy arrays.\\n for key in colours:\\n colours[key] = array(colours[key], float64)\\n\\n # Invalid colour string.\\n if name not in colours:\\n raise RelaxInvalidColourError(name)\\n\\n # Return the RGB colour array.\\n return colours[name]\",\n \"def read_colormap(name):\\n\\n path = get_demo_file(name + '.c3g')\\n\\n out = []\\n with open(path, 'r') as file:\\n for line in file:\\n if 'rgb(' not in line:\\n continue\\n line = line.split('(')[-1].split(')')[0]\\n out.append([float(n) for n in line.split(',')])\\n\\n return np.asarray(out).astype(float) / 256.\",\n \"def colorify(data, vmin=None, vmax=None, cmap=plt.cm.Spectral):\\n try:\\n from matplotlib.colors import Normalize\\n except ImportError:\\n # old mpl\\n\\n from matplotlib.colors import normalize as Normalize\\n\\n _vmin = vmin or min(data)\\n _vmax = vmax or max(data)\\n cNorm = Normalize(vmin=_vmin, vmax=_vmax)\\n\\n scalarMap = plt.cm.ScalarMappable(norm=cNorm, cmap=cmap)\\n try:\\n colors = scalarMap.to_rgba(data)\\n except:\\n colors = list(map(scalarMap.to_rgba, data))\\n return colors, scalarMap\",\n \"def binary_cmap(color='red', alpha=1.):\\n if color == 'red':\\n color_code = (1., 0., 0., alpha)\\n elif color == 'green':\\n color_code = (0., 1., 0., alpha)\\n elif color == 'blue':\\n color_code = (0., 0., 1., alpha)\\n else:\\n color_code = color\\n transparent_code = (1., 1., 1., 0.)\\n return ListedColormap([transparent_code, color_code])\",\n \"def create_colormap(seg_map):\\n\\tcolormap = np.zeros((256, 3), dtype=int)\\n\\tind = np.arange(256, dtype=int)\\n\\tfor shift in reversed(range(8)):\\n\\t\\tfor channel in range(3):\\n\\t\\t\\tcolormap[:, channel] |= ((ind >> channel) & 1) << shift \\n\\t\\tind >>= 3\\n\\treturn colormap[seg_map]\",\n \"def _get_cmap_colors(cmap, n, cc = 0, callfn = None):\\r\\n if callfn is None: callfn = _get_cmap_colors.__name__\\r\\n # sanity checks\\r\\n if not isinstance(cmap, str):\\r\\n raise TypeError(\\\"{0}: error: cmap must be a string matplotlib color \\\"\\r\\n \\\"map\\\".format(callfn))\\r\\n if not isinstance(n, int):\\r\\n raise TypeError(\\\"{0}: error: n must be a positive integer\\\"\\r\\n \\\"\\\".format(callfn))\\r\\n if n < 1:\\r\\n raise ValueError(\\\"{0}: error: int n must be positive\\\".format(callfn))\\r\\n if (not isinstance(cc, float)) and (not isinstance(cc, int)):\\r\\n raise TypeError(\\\"{0}: error: cc must be a float in range [0, 1)\\\"\\r\\n \\\"\\\".format(callfn))\\r\\n if (cc < 0) or (cc >= 1):\\r\\n raise ValueError(\\\"{0}: error: float cc outside range [0, 1)\\\"\\r\\n \\\"\\\".format(callfn))\\r\\n # take range [0.5 * cc, 1 - 0.5 * cc] and split it into n pieces; the\\r\\n # collected points are midpoints of each interval. reduces color contrast.\\r\\n colors = [0.5 * cc + (1 - cc) * (i + 0.5) / n for i in range(n)]\\r\\n # try to get the colormap\\r\\n try: cmap = getattr(cm, cmap)\\r\\n except AttributeError as ae:\\r\\n ae.args = [\\\"{0}: error: unknown color map \\\\\\\"{1}\\\\\\\"\\\".format(callfn, cmap)]\\r\\n raise ae\\r\\n # if cmap is not a Colormap, raise a TypeError\\r\\n if not isinstance(cmap, Colormap):\\r\\n raise TypeError(\\\"{0}: error: {1} is not a valid Colormap\\\"\\r\\n \\\"\\\".format(callfn, cmap))\\r\\n # retrieve colors using color points and return\\r\\n for i in range(n): colors[i] = cmap(colors[i])\\r\\n # return ListedColormap from colors\\r\\n return ListedColormap(colors, name = cmap.name + \\\"_listed\\\", N = n)\",\n \"def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name=\\\"shiftedcmap\\\"):\\n cdict = {\\\"red\\\": [], \\\"green\\\": [], \\\"blue\\\": [], \\\"alpha\\\": []}\\n\\n # regular index to compute the colors\\n reg_index = np.linspace(start, stop, 257)\\n\\n # shifted index to match the data\\n shift_index = np.hstack(\\n [\\n np.linspace(0.0, midpoint, 128, endpoint=False),\\n np.linspace(midpoint, 1.0, 129, endpoint=True),\\n ]\\n )\\n\\n for ri, si in zip(reg_index, shift_index):\\n r, g, b, a = cmap(ri)\\n\\n cdict[\\\"red\\\"].append((si, r, r))\\n cdict[\\\"green\\\"].append((si, g, g))\\n cdict[\\\"blue\\\"].append((si, b, b))\\n cdict[\\\"alpha\\\"].append((si, a, a))\\n\\n newcmap = mpl.colors.LinearSegmentedColormap(name, cdict)\\n\\n return newcmap\",\n \"def compile_palette(palette_list):\\n global _COMPILED_PALETTE\\n _COMPILED_PALETTE = {}\\n\\n for color in palette_list:\\n r_sum = math.fabs(color[0] ** _MAGNITUDE)\\n g_sum = math.fabs(color[1] ** _MAGNITUDE)\\n b_sum = math.fabs(color[2] ** _MAGNITUDE)\\n\\n _COMPILED_PALETTE[color] = [r_sum, g_sum, b_sum]\",\n \"def map_values_to_color(self, df, col_name):\\n # map values to colors in hex via\\n # creating a hex Look up table table and apply the normalized data to it\\n norm = mcolors.Normalize(vmin=np.nanmin(df[col_name].values),\\n vmax=np.nanmax(df[col_name].values), clip=True)\\n # alternative way of generating hex values\\n # mapper = plt.cm.ScalarMappable(norm=norm, cmap=plt.cm.viridis)\\n # a = mapper.to_rgba(df[col_name])\\n # color_col_name = col_name + '_color'\\n # df[color_col_name] = np.apply_along_axis(mcolors.to_hex, 1, a)\\n\\n lut = plt.cm.viridis(np.linspace(0,1,256))\\n lut = np.apply_along_axis(mcolors.to_hex, 1, lut)\\n a = (norm(df[col_name].values)*255).astype(np.int16)\\n color_col_name = col_name + '_color'\\n df[color_col_name] = lut[a]\\n return df\",\n \"def cmap2pixmap(cmap, steps=50):\\n import numpy as np\\n\\n inds = np.linspace(0, 1, steps)\\n n = len(cmap.clst) - 1\\n tups = [cmap.clst[int(x * n)] for x in inds]\\n rgbas = [QColor(int(r * 255), int(g * 255),\\n int(b * 255), 255).rgba() for r, g, b in tups]\\n im = QImage(steps, 1, QImage.Format_Indexed8)\\n im.setColorTable(rgbas)\\n for i in range(steps):\\n im.setPixel(i, 0, i)\\n im = im.scaled(128, 32)\\n pm = QPixmap.fromImage(im)\\n return pm\",\n \"def cmap(self):\\n return self._cmap\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.8101128","0.6942909","0.6776598","0.6741528","0.6741528","0.66666794","0.66659963","0.66659963","0.66659963","0.6503461","0.6470813","0.6413775","0.63696545","0.6352337","0.631037","0.61285675","0.61251086","0.6121512","0.6044165","0.60116994","0.60105366","0.5997186","0.59899193","0.59587944","0.59356815","0.5935643","0.59344226","0.5924718","0.5918142","0.5903378","0.5900839","0.58989257","0.58714914","0.5857217","0.58479255","0.5844519","0.5844519","0.5844519","0.5844519","0.58285666","0.58281356","0.5827933","0.5824135","0.58234614","0.58234614","0.58234614","0.58171326","0.5809652","0.57992077","0.57632536","0.5750439","0.5745679","0.57054675","0.57035536","0.56981814","0.56728685","0.5656211","0.5650979","0.5641368","0.5615681","0.5613908","0.5610505","0.55943626","0.55943626","0.55910325","0.55910325","0.5590747","0.5587044","0.5572421","0.5559716","0.5559136","0.5552183","0.55484504","0.5534495","0.5531092","0.5527726","0.54870033","0.54765844","0.54765844","0.54726714","0.546448","0.54609406","0.5457046","0.5449945","0.5447359","0.5429035","0.5427029","0.5415557","0.5413298","0.5407485","0.53996134","0.5394317","0.5389181","0.5382244","0.5380487","0.53744894","0.53660417","0.53480536","0.5328364","0.532065"],"string":"[\n \"0.8101128\",\n \"0.6942909\",\n \"0.6776598\",\n \"0.6741528\",\n \"0.6741528\",\n \"0.66666794\",\n \"0.66659963\",\n \"0.66659963\",\n \"0.66659963\",\n \"0.6503461\",\n \"0.6470813\",\n \"0.6413775\",\n \"0.63696545\",\n \"0.6352337\",\n \"0.631037\",\n \"0.61285675\",\n \"0.61251086\",\n \"0.6121512\",\n \"0.6044165\",\n \"0.60116994\",\n \"0.60105366\",\n \"0.5997186\",\n \"0.59899193\",\n \"0.59587944\",\n \"0.59356815\",\n \"0.5935643\",\n \"0.59344226\",\n \"0.5924718\",\n \"0.5918142\",\n \"0.5903378\",\n \"0.5900839\",\n \"0.58989257\",\n \"0.58714914\",\n \"0.5857217\",\n \"0.58479255\",\n \"0.5844519\",\n \"0.5844519\",\n \"0.5844519\",\n \"0.5844519\",\n \"0.58285666\",\n \"0.58281356\",\n \"0.5827933\",\n \"0.5824135\",\n \"0.58234614\",\n \"0.58234614\",\n \"0.58234614\",\n \"0.58171326\",\n \"0.5809652\",\n \"0.57992077\",\n \"0.57632536\",\n \"0.5750439\",\n \"0.5745679\",\n \"0.57054675\",\n \"0.57035536\",\n \"0.56981814\",\n \"0.56728685\",\n \"0.5656211\",\n \"0.5650979\",\n \"0.5641368\",\n \"0.5615681\",\n \"0.5613908\",\n \"0.5610505\",\n \"0.55943626\",\n \"0.55943626\",\n \"0.55910325\",\n \"0.55910325\",\n \"0.5590747\",\n \"0.5587044\",\n \"0.5572421\",\n \"0.5559716\",\n \"0.5559136\",\n \"0.5552183\",\n \"0.55484504\",\n \"0.5534495\",\n \"0.5531092\",\n \"0.5527726\",\n \"0.54870033\",\n \"0.54765844\",\n \"0.54765844\",\n \"0.54726714\",\n \"0.546448\",\n \"0.54609406\",\n \"0.5457046\",\n \"0.5449945\",\n \"0.5447359\",\n \"0.5429035\",\n \"0.5427029\",\n \"0.5415557\",\n \"0.5413298\",\n \"0.5407485\",\n \"0.53996134\",\n \"0.5394317\",\n \"0.5389181\",\n \"0.5382244\",\n \"0.5380487\",\n \"0.53744894\",\n \"0.53660417\",\n \"0.53480536\",\n \"0.5328364\",\n \"0.532065\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6990008"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":18685,"cells":{"query":{"kind":"string","value":"instead of return a cursor object, find_one() returns one document. so when you look up document by it's _id (_id field is always unique), use find_one() method."},"document":{"kind":"string","value":"def find_one():\n fmter.tpl._straightline(\"one document\", 100)\n result = users.find_one({})\n print(type(result))\n ppt(result)\n \n fmter.tpl._straightline(\"none result\", 100)\n result = users.find_one({\"_id\": 100})\n print(type(result))\n ppt(result)"},"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 find_one(self, collection, query):\n obj = getattr(self.db, collection)\n result = obj.find_one(query)\n return result","def first(self, **kwargs):\n return self.find(**kwargs).first()","def one(self):\n try:\n return self[0]\n except IndexError:\n raise self.document.DoesNotExist","def get_one(collection: Collection, query: Dict[str, Any]):\n data = collection.find_one(query)\n if data is None:\n raise CannotFindItemInDatabase(query, data, collection.name)\n return data","def find_one(self, criteria):\n return self.connection.find_one(criteria)","async def find_one(self, collection_name: str, filter_dict: dict, *args, catch_error: bool = True, **kwargs):\n collection = self.database.get_collection(collection_name)\n result = None\n try:\n result = await collection.find_one(filter_dict, *args, **kwargs)\n self.debug_log(collection_name, f\"Found a document {result} in '{collection_name}' \"\n f\"with options '{args, kwargs}'\")\n except BaseException as e:\n self.error_log(collection_name, f\"Could not execute 'find_one'-command in '{collection_name}' \"\n f\"with options '{args, kwargs}'\",\n err=e)\n if not catch_error:\n raise e\n return result","def fetchone(self) -> Any:\n return self.cursor.fetchone()","def get_single_data(document_id):\n data = collection.find_one({'_id': ObjectId(document_id)})\n return data","async def find_one(\n self, query: Union[dict, MotycQuery] = None, *,\n _id=None,\n inject_default_id: bool = None\n ) -> T:\n\n mongo_query = self.build_mongo_query(query, _id=_id)\n\n document = await self.collection.find_one(mongo_query)\n\n if document is None: raise NotFound(mongo_query)\n return self.parse_document(document, inject_default_id=inject_default_id)","def find_one(cls, query, select=None, as_dict=False):\n record = cls.collection.find_one(query, select)\n\n return record if as_dict else cls(record)","async def find_one(self, **query):\n\n return await self._expand(await self.db.get_one(**query))","def find(cls, id=None):\n return cls.query.filter_by(id=id).one_or_none()","def find_one(self, user_id):\n pass","def obj_get(self, request=None, **kwargs):\n return Document(self.get_collection(request).find_one({\n \"_id\": ObjectId(kwargs.get(\"pk\"))\n }))","def find_by_id(cls, object_id):\n try:\n return mongo_db[cls.__collection__].find_one({\"_id\": ObjectId(object_id)})\n except InvalidId:\n # TODO: Log the exception\n print('Invalid bson id: {}'.format(object_id))\n return None","def first(self):\n try:\n data = self.get_cursor()[0]\n return self.from_(**self.prepare_data(data))\n except IndexError:\n return None","def find_by_id(cls, doc_id: str):\n document = None\n if doc_id:\n try:\n document = cls.query.get(doc_id)\n except Exception as db_exception: # noqa: B902; return nicer error\n current_app.logger.error('Db2Document.find_by_id exception: ' + str(db_exception))\n raise DatabaseException(db_exception)\n if document:\n document.strip()\n return document","def get_one(self, object):\n self.lock.acquire()\n result = self.__Session.query(object).first()\n self.lock.release()\n return result","async def get_one(self, where: t.Mapping[str, t.Any]) -> t.Optional[Model]:\n\n data = await self.collection.find_one(where)\n return self.model_class(**data) if data else None","def fetchone(cursor):\n\t# type: (Cursor, ) -> Any\n\n\trows = cursor.fetchall()\n\tif len(rows) == 0:\n\t\traise NoResult(\"No result found\")\n\telif len(rows) == 1:\n\t\treturn rows[0]\n\telse:\n\t\traise InconsistentState(\"More than one result found\")","def find_one(self, query, collection_name='talent5__staff_collection'):\r\n collection = self.get_collection(collection_name)\r\n\r\n if collection is None:\r\n return None\r\n else:\r\n return collection.find_one(query)","def find_one(cls, attr):\n result = cls.db().find_one(attr, True)\n\n if result is not None:\n return cls(result)\n\n return None","def get(self, query_data=None, id_obj=None):\n if id_obj:\n return self.collection.find_one({'_id': id_obj})\n return self.collection.find_one(query_data)","def fetchone(self):\n row = self.cursor.fetchone()\n\n if row is None:\n return None\n\n if self.model.single:\n return self.__instance_from_db(self.model, row)\n else:\n return tuple(self.__instance_from_db(m, row) for m in self.model.models)","def document(self):\n query = {\"_id\": ObjectId(self.document_id)}\n return Document(get_collection(\"documents\").find_one(query))","def find_one_byprimaryid(cls, primaryid, defaultval = None):\n return cls.dbm().modelclass_find_one_byprimaryid(cls, primaryid, defaultval)","def first_or_raise(self):\n res = super(CustomQuery, self).first()\n if not res:\n raise NotFoundException\n return res","def getFirstDocument(address=\"\", database=\"\", collection=\"\"):\n\n document = []\n client = connectMongo(address, database, collection)\n\n document.append(client.find_one())\n\n return document","def find_first(cls, **kwargs):\n return cls.query.filter_by(**kwargs).first()","def get(self, id, model_type=None):\n # If collection is not specified, use the collection when this client is\n if not model_type:\n collection = self._collection\n else:\n collection = self._db[model_type]\n\n print 'mongo.get(): id={}'.format(id)\n if id:\n obj = collection.find_one({'_id': ObjectId(id)})\n if not obj:\n raise DbProviderError(\"DB record for {} is not found\".format(id))\n obj['_id'] = str(obj['_id'])\n else:\n obj = {}\n return obj","def _query_and_fetchone(self, query):\n with self._connect() as conn:\n cur = conn.cursor()\n cur.execute(query)\n result = cur.fetchone()\n\n return result","def fetchone(self, autoConvert=True, format=None):\r\n if self._closed:\r\n raise Error('The cursor has been closed.')\r\n if self.connection._closed:\r\n raise Error('The connection to the database has been closed.')\r\n if self.info['results'] == None:\r\n raise Error('Previous call to execute() did not produce a result set. No results to fetch.')\r\n else:\r\n res = self.fetchmany(1, format)\r\n if res == ():\r\n return None\r\n else:\r\n return res[0]","async def get_one(self, pk):\n\n return await self._expand(await self.db.get_one(pk=pk))","async def find_one_and_update(self, spec, update_fields, upsert=False, return_document=False, fields=None, cursor=None):\n if not cursor:\n cursor = self._cursor\n spec[DELETE_FLAG] = {\"$ne\": True}\n if \"_id\" in spec:\n spec[\"_id\"] = self._convert_id_object(spec[\"_id\"])\n result = await cursor.find_one_and_update(spec, update_fields, projection=fields, upsert=upsert, return_document=return_document)\n #if result and \"_id\" in result:\n # result[\"_id\"] = str(result[\"_id\"])\n return result, None","def one(self):\n self.limit(2)\n u = self.get_cursor()\n u = list(u)\n assert u, \"expected one object\"\n if len(u) > 1:\n assert u, \"expected one object, more than one received\"\n return self.from_(**self.prepare_data(u[0]))","def get_one_by_id(self, object, id):\n self.lock.acquire()\n result = self.__Session.query(object).get(id)\n self.lock.release()\n return result","async def get_one(self, where):\n\n pass","def findone(cls, *lst, **dct):\n query = cls.where(*lst, **dct).select()\n result = query.execute()\n return result.fetchone()","async def find_one_and_delete(self, spec, fields=None, cursor=None):\n if not cursor:\n cursor = self._cursor\n spec[DELETE_FLAG] = {\"$ne\": True}\n if \"_id\" in spec:\n spec[\"_id\"] = self._convert_id_object(spec[\"_id\"])\n result = await cursor.find_one_and_delete(spec, projection=fields)\n #if result and \"_id\" in result:\n # result[\"_id\"] = str(result[\"_id\"])\n return result, None","def fetchOne(self,query):\n# self.updateDBAndLog(query)\n# tup = self.cursor.fetchone()\n\tself.updateLog(query)\n\tcur = self.db.cursor()\n\tcur.execute(query)\n\ttup = cur.fetchone()\n\tcur.close()\n\treturn tup","def query_one(self, *args, **kwargs):\n kwargs.setdefault('error_if_multiple', True)\n records = self.query(*args, **kwargs)\n return records[0] if records else None","def get_document_by_id(document_id):\n return Documents.query.filter_by(id=document_id).first()","def fetch_one(q, *params):\n db = Database()\n db.cur.execute(q, params)\n ret = db.cur.fetchone()\n db.con.close()\n return ret","def test_find_one(self):\n person1 = self.Person(name=\"User A\", age=20)\n person1.save()\n person2 = self.Person(name=\"User B\", age=30)\n person2.save()\n\n # Retrieve the first person from the database\n person = self.Person.objects.first()\n assert isinstance(person, self.Person)\n assert person.name == \"User A\"\n assert person.age == 20\n\n # Use a query to filter the people found to just person2\n person = self.Person.objects(age=30).first()\n assert person.name == \"User B\"\n\n person = self.Person.objects(age__lt=30).first()\n assert person.name == \"User A\"\n\n # Use array syntax\n person = self.Person.objects[0]\n assert person.name == \"User A\"\n\n person = self.Person.objects[1]\n assert person.name == \"User B\"\n\n with pytest.raises(IndexError):\n self.Person.objects[2]\n\n # Find a document using just the object id\n person = self.Person.objects.with_id(person1.id)\n assert person.name == \"User A\"\n\n with pytest.raises(InvalidQueryError):\n self.Person.objects(name=\"User A\").with_id(person1.id)","def get(cls, db, id):\n doc = cls.collection(db).find_one(filter={ '_id': ObjectId(id) })\n return Todo(**doc)","def find_one(self, select, tables, on={}, filter={}):\n query, args = self.__build_find_query(select, tables, on, filter)\n\n cur = self.conn.cursor()\n\n try:\n cur.execute(query, args)\n result = cur.fetchone()\n except Exception as e:\n # logger = Logger.getInstance()\n # logger.log(context=self.__class__.__name__,\n # method=\"fetch_all\",\n # msg=f\"query: {query}; Excpetion {e}\")\n print(e)\n result = None\n finally:\n cur.close()\n return result","def fetch_one(cls: Type[_T], session: Session, identifier: int) -> _T:\n return Query(cls, session=session).get(identifier)","async def get_object(conn: Database, query):\n return await conn.fetch_one(query=query)","def select_one(cls, pk):\n with sqlite3.connect(cls.dbpath) as conn:\n conn.row_factory = sqlite3.Row\n curs = conn.cursor()\n sql = f\"\"\"SELECT * FROM {cls.tablename} WHERE pk =?;\"\"\"\n curs.execute(sql, (pk,)) #don't forget to put a comma after single value inputs\n row = curs.fetchone()\n return cls(**row)","def find_one(cls, dataset_id):\n return super(cls, cls).find_one({DATASET_ID: dataset_id})","def get_first_item(cls):\n return cls.query.first()","def find_one(self, query, fields=None):\n # get raw result\n record = self._find_one(query)\n # if no result found\n if record is None:\n return None\n # handle `fields` parameter\n if fields is None:\n # if fields not given - return raw result\n result = record.to_id_dict()\n elif isinstance(fields, str):\n # chose one value\n result = record[fields]\n elif isinstance(fields, list):\n # chose only values matching given fields\n result = record.get_fields_list(fields)\n else:\n raise TypeError(f\"`fields` should be of one of types: \"\n f\"`None`, `str` or `list`. got: {type(fields)}\")\n return result","def fetch_one(cls, limiter=None):\n return cls.where(limiter).fetch_one()","def fetchone(self):\n try:\n return next(self._results)\n except StopIteration:\n return None","def get(self, _id):\n try:\n doc = self._db[_id]\n # For speed testing\n del self._db[_id]\n except KeyError:\n return None\n else:\n return self._parse_doc(doc)","def retrieveById(self, doc_id=None):\n obj = self.find_one({'_id': doc_id if id else self.get('_id')})\n if obj:\n self._import(obj)\n return True\n return False","def by_id(cls, _id):\n return dbsession.query(cls).filter_by(id=_id).first()","def by_id(cls, _id):\n return dbsession.query(cls).filter_by(id=_id).first()","def by_id(cls, _id):\n return dbsession.query(cls).filter_by(id=_id).first()","def get_record(self, collection_name, filter):\n\n try:\n self.logger.info('in get_record()')\n collection = self.get_db()[collection_name]\n record = collection.find_one(filter)\n self.logger.info('in get_record()')\n return record\n except Exception as e:\n self.logger.error(f'Error occurred while getting records {e}')","def get_one(self, index, *args, **kw):\n person = M.People.query.get(index=index)\n log.debug('person {}'.format(person))\n if(person):\n kw['_id'] = person._id\n return super(PeopleAPIController, self).get_one(*args, **kw)","def get_document(self, doc_id: int) -> Optional[Users]:\n try:\n doc = self.session.query(CandidatesDocuments).get(doc_id)\n\n return doc\n except Exception as excpt:\n self.session.rollback()\n print(f'Could not get doc: {excpt}')\n\n return None","def find(self, *args, **kwds):\n return self.collection.find(*args, **kwds)","def find_one_bywhereclause(cls, whereclause):\n return cls.dbm().modelclass_find_one_bywhereclause(cls, whereclause)","async def get(self, id=None, alias=None, **kwargs):\n\n from jetengine import Q\n\n if id is None and not kwargs:\n raise RuntimeError(\"Either an id or a filter must be provided to get\")\n\n if id is not None:\n if not isinstance(id, ObjectId):\n id = ObjectId(id)\n\n filters = {\"_id\": id}\n else:\n filters = Q(**kwargs)\n filters = self.get_query_from_filters(filters)\n\n instance = await self.coll(alias).find_one(filters, projection=self._loaded_fields.to_query(self.__klass__))\n if instance is None:\n return None\n else:\n doc = self.__klass__.from_son(\n instance,\n # if _loaded_fields is not empty then\n # document is partly loaded\n _is_partly_loaded=bool(self._loaded_fields),\n # set projections for references (if any)\n _reference_loaded_fields=self._reference_loaded_fields,\n )\n if self.is_lazy:\n return doc\n else:\n await doc.load_references()\n return doc","def find_exact(self, **kwargs):\n results = list(self.find(**kwargs))\n if len(results) == 1:\n return results[0]\n return None","def find_one(\n self,\n *args,\n projection_model: Optional[Type[BaseModel]] = None,\n session: Optional[ClientSession] = None\n ):\n self.find_expressions += args\n self.project(projection_model)\n self.set_session(session=session)\n return self","def find_by_doc_id(cls, doc_reg_id: str):\n document = None\n if doc_reg_id:\n try:\n document = cls.query.filter(Db2Document.id == doc_reg_id).one_or_none()\n except Exception as db_exception: # noqa: B902; return nicer error\n current_app.logger.error('Db2Document.find_by_doc_id exception: ' + str(db_exception))\n raise DatabaseException(db_exception)\n if document:\n document.strip()\n return document","def by_id(cls, id):\n try:\n return DBSession.query(cls).filter(cls.id == id).one()\n except (NoResultFound, MultipleResultsFound):\n return None","def fetch_one(self, sql):\n curs = self.q(sql, True)\n row = curs.fetchone()\n if curs._have_unread_result():\n curs.fetchall()\n curs.close()\n\n if row:\n return row[0]\n else:\n return None","def query_fetchone(self, q, param=None):\r\n try:\r\n c = self.connection.cursor()\r\n if param is None:\r\n c.execute(q)\r\n else:\r\n c.execute(q, param)\r\n self.logger.log(logger.LogLevel.DEBUG, 'database.fetchone: %s | %s' % (q, param)) \r\n return c.fetchone()\r\n except Exception as e:\r\n self.logger.log(logger.LogLevel.ERROR, 'database.fetchone: %s. %s | %s' % (e, q, param))\r\n return False","async def find_by_id(self, _id: int) -> Record:\n conn: Connection\n async with self.db_pool.acquire() as conn:\n return await conn.fetchrow(\n f\"SELECT * FROM {self.table_name} WHERE {self.primary_key}=$1\",\n _id,\n )","def fetchone(self):\n\n self._check_executed()\n\n if self._query_id == -1:\n msg = \"query didn't result in a resultset\"\n self._exception_handler(ProgrammingError, msg)\n\n if self.rownumber >= self.rowcount:\n return None\n\n if self.rownumber >= (self._offset + len(self._rows)):\n self.nextset()\n\n result = self._rows[self.rownumber - self._offset]\n self.rownumber += 1\n return result","def first(self, **opts):\n try:\n return next(self.find(**opts))\n except StopIteration:\n if 'default' in opts:\n return opts['default']\n else:\n raise KeyError(\"no matching objects\")","def get_one_event(cls, event_id):\n try:\n event = events_coll.find_one({\"_id\": ObjectId(event_id)})\n return cls(**event)\n except Exception as e:\n print(e)","async def one(\n self,\n statement: Executable,\n params: t.Optional[\n t.Union[t.Mapping[str, t.Any], t.Sequence[t.Mapping[str, t.Any]]]\n ] = None,\n execution_options: t.Optional[t.Mapping[str, t.Any]] = None,\n bind_arguments: t.Optional[t.Mapping[str, t.Any]] = None,\n ) -> t.Any:\n result = await self.execute(\n statement, params, execution_options=execution_options, bind_arguments=bind_arguments\n )\n if isinstance(result, sa.engine.CursorResult):\n item = result.one()\n else:\n item = result.scalar_one()\n return item","async def fetch_single(self, query: str, args: Optional[Iterable]=None) -> Any:\n res = await self.fetch_row(query, args)\n ret = None\n if res and len(res) == 1:\n ret = res[0]\n return ret","def returnOne(self):\n try:\n # self.checkValName()\n self.cursor.execute(self.query % self.val)\n self.results = self.conn.fetchone()\n except Exception as e:\n print \"Query failed: %s \" % e","def find(cls, **kwargs):\n return cls.query.filter_by(**kwargs).first()","def _get_mongo_session(self, sid):\n return self.coll.find_one({'sid': sid})","def fetch_obj(type, id, error=404, new_id=False):\n if id is None:\n abort(error)\n obj_q = Session.query(type)\n obj = obj_q.get(int(id))\n #else:\n # obj = obj_q.filter(type.ID==int(id)).first()\n\n if obj is None:\n abort(error)\n return obj","def fetchone(self, sql, val=()):\n cursor = self.__db.cursor()\n cursor.execute(sql, val)\n return cursor.fetchone()","def find(self, primary_key):\n sql = '{} WHERE {} = %s'.format(self._select(), self.PRIMARY_KEY)\n cursor = yield self._pool.execute(sql, [primary_key])\n result = cursor.fetchmany(1)\n return self.convert_result_to_object(result)","def find_by_id(cls, _id):\n user = cls.query.filter_by(id=_id).first()\n return user","def get_single_user(username):\n user = mongo.db.users.find_one({\"username\": username})\n user[\"_id\"] = str(user[\"_id\"])\n return user","def single(self):\n records = list(self)\n num_records = len(records)\n if num_records == 0:\n raise ResultError(\"Cannot retrieve a single record, because this result is empty.\")\n elif num_records != 1:\n raise ResultError(\"Expected a result with a single record, but this result contains at least one more.\")\n else:\n return records[0]","def get_task(task_id):\n return db.task.find_one({'_id': ObjectId(task_id)})","def find(self, id, columns=None):\n if not columns:\n columns = ['*']\n\n return self.where('id', '=', id).first(1, columns)","def returnOne(self):\n try:\n # self.checkValName()\n self.dbc.execute(self.query, self.val)\n self.results = self.dbc.fetchone()\n except MySQLdb.Error, e:\n print \"Query failed: %s \" % e","def find(self, user_id: UserId) -> Optional[U]:\n ...","def _dictfetchone(self):\n data = self._dictfetchall()\n if data:\n return data[0]\n return {}","def single(self, strict: bool = False) -> t.Optional[Record]:\n self._buffer(2)\n buffer = self._record_buffer\n self._record_buffer = deque()\n self._exhaust()\n if not buffer:\n if not strict:\n return None\n raise ResultNotSingleError(\n self,\n \"No records found. \"\n \"Make sure your query returns exactly one record.\"\n )\n elif len(buffer) > 1:\n res = buffer.popleft()\n if not strict:\n warn(\"Expected a result with a single record, \"\n \"but found multiple.\")\n return res\n else:\n raise ResultNotSingleError(\n self,\n \"More than one record found. \"\n \"Make sure your query returns exactly one record.\"\n )\n return buffer.popleft()","def fetch_one(cls, sql, **kwargs):\n conn = kwargs['conn']\n\n cursor = conn.cursor(dictionary=True, buffered=False)\n for _ in cursor.execute(sql, kwargs.get('args'), multi=True):\n pass\n\n result = cursor.fetchone()\n cls.close(conn, cursor)\n\n return result","def get_by_id(cls, id):\n try:\n return cls.objects.get(id=id)\n except(IntegrityError, OperationalError):\n return None","def find_by_id(cls, iid: int):\n return cls.query.filter_by(id=iid).first()","def one(self, except_all=False):\n\n length = len(self)\n if length > 1:\n raise MultipleResultsFound(\"%s results found.\" % length)\n\n result = self.first()\n if result is None and except_all:\n raise NoResultFound\n return result","def get_one(self, arg):\n if self.validator.assert_id(arg):\n return self.get_item(item_id=arg)\n\n elif arg == 'schema':\n return self.validator.schema\n\n else:\n pecan.abort(404)","def get_document(obj):\n try:\n return ES.get(\n index=obj.get_index_name(), doc_type=obj.get_document_type(), id=obj.pk)\n except NotFoundError:\n raise DocumentNotFound(obj.get_index_name(), obj.pk)","def scalar(self):\n try:\n ret = self.one()\n if not isinstance(ret, collections_abc.Sequence):\n return ret\n return ret[0]\n except orm_exc.NoResultFound:\n return None","def fetchone(self):\n self._check_closed()\n if self._result_set is None:\n raise Error(\"Previous execute did not produce any results or no call was issued yet\")\n self.rownumber += 1\n return self._result_set.fetchone(self.session)"],"string":"[\n \"def find_one(self, collection, query):\\n obj = getattr(self.db, collection)\\n result = obj.find_one(query)\\n return result\",\n \"def first(self, **kwargs):\\n return self.find(**kwargs).first()\",\n \"def one(self):\\n try:\\n return self[0]\\n except IndexError:\\n raise self.document.DoesNotExist\",\n \"def get_one(collection: Collection, query: Dict[str, Any]):\\n data = collection.find_one(query)\\n if data is None:\\n raise CannotFindItemInDatabase(query, data, collection.name)\\n return data\",\n \"def find_one(self, criteria):\\n return self.connection.find_one(criteria)\",\n \"async def find_one(self, collection_name: str, filter_dict: dict, *args, catch_error: bool = True, **kwargs):\\n collection = self.database.get_collection(collection_name)\\n result = None\\n try:\\n result = await collection.find_one(filter_dict, *args, **kwargs)\\n self.debug_log(collection_name, f\\\"Found a document {result} in '{collection_name}' \\\"\\n f\\\"with options '{args, kwargs}'\\\")\\n except BaseException as e:\\n self.error_log(collection_name, f\\\"Could not execute 'find_one'-command in '{collection_name}' \\\"\\n f\\\"with options '{args, kwargs}'\\\",\\n err=e)\\n if not catch_error:\\n raise e\\n return result\",\n \"def fetchone(self) -> Any:\\n return self.cursor.fetchone()\",\n \"def get_single_data(document_id):\\n data = collection.find_one({'_id': ObjectId(document_id)})\\n return data\",\n \"async def find_one(\\n self, query: Union[dict, MotycQuery] = None, *,\\n _id=None,\\n inject_default_id: bool = None\\n ) -> T:\\n\\n mongo_query = self.build_mongo_query(query, _id=_id)\\n\\n document = await self.collection.find_one(mongo_query)\\n\\n if document is None: raise NotFound(mongo_query)\\n return self.parse_document(document, inject_default_id=inject_default_id)\",\n \"def find_one(cls, query, select=None, as_dict=False):\\n record = cls.collection.find_one(query, select)\\n\\n return record if as_dict else cls(record)\",\n \"async def find_one(self, **query):\\n\\n return await self._expand(await self.db.get_one(**query))\",\n \"def find(cls, id=None):\\n return cls.query.filter_by(id=id).one_or_none()\",\n \"def find_one(self, user_id):\\n pass\",\n \"def obj_get(self, request=None, **kwargs):\\n return Document(self.get_collection(request).find_one({\\n \\\"_id\\\": ObjectId(kwargs.get(\\\"pk\\\"))\\n }))\",\n \"def find_by_id(cls, object_id):\\n try:\\n return mongo_db[cls.__collection__].find_one({\\\"_id\\\": ObjectId(object_id)})\\n except InvalidId:\\n # TODO: Log the exception\\n print('Invalid bson id: {}'.format(object_id))\\n return None\",\n \"def first(self):\\n try:\\n data = self.get_cursor()[0]\\n return self.from_(**self.prepare_data(data))\\n except IndexError:\\n return None\",\n \"def find_by_id(cls, doc_id: str):\\n document = None\\n if doc_id:\\n try:\\n document = cls.query.get(doc_id)\\n except Exception as db_exception: # noqa: B902; return nicer error\\n current_app.logger.error('Db2Document.find_by_id exception: ' + str(db_exception))\\n raise DatabaseException(db_exception)\\n if document:\\n document.strip()\\n return document\",\n \"def get_one(self, object):\\n self.lock.acquire()\\n result = self.__Session.query(object).first()\\n self.lock.release()\\n return result\",\n \"async def get_one(self, where: t.Mapping[str, t.Any]) -> t.Optional[Model]:\\n\\n data = await self.collection.find_one(where)\\n return self.model_class(**data) if data else None\",\n \"def fetchone(cursor):\\n\\t# type: (Cursor, ) -> Any\\n\\n\\trows = cursor.fetchall()\\n\\tif len(rows) == 0:\\n\\t\\traise NoResult(\\\"No result found\\\")\\n\\telif len(rows) == 1:\\n\\t\\treturn rows[0]\\n\\telse:\\n\\t\\traise InconsistentState(\\\"More than one result found\\\")\",\n \"def find_one(self, query, collection_name='talent5__staff_collection'):\\r\\n collection = self.get_collection(collection_name)\\r\\n\\r\\n if collection is None:\\r\\n return None\\r\\n else:\\r\\n return collection.find_one(query)\",\n \"def find_one(cls, attr):\\n result = cls.db().find_one(attr, True)\\n\\n if result is not None:\\n return cls(result)\\n\\n return None\",\n \"def get(self, query_data=None, id_obj=None):\\n if id_obj:\\n return self.collection.find_one({'_id': id_obj})\\n return self.collection.find_one(query_data)\",\n \"def fetchone(self):\\n row = self.cursor.fetchone()\\n\\n if row is None:\\n return None\\n\\n if self.model.single:\\n return self.__instance_from_db(self.model, row)\\n else:\\n return tuple(self.__instance_from_db(m, row) for m in self.model.models)\",\n \"def document(self):\\n query = {\\\"_id\\\": ObjectId(self.document_id)}\\n return Document(get_collection(\\\"documents\\\").find_one(query))\",\n \"def find_one_byprimaryid(cls, primaryid, defaultval = None):\\n return cls.dbm().modelclass_find_one_byprimaryid(cls, primaryid, defaultval)\",\n \"def first_or_raise(self):\\n res = super(CustomQuery, self).first()\\n if not res:\\n raise NotFoundException\\n return res\",\n \"def getFirstDocument(address=\\\"\\\", database=\\\"\\\", collection=\\\"\\\"):\\n\\n document = []\\n client = connectMongo(address, database, collection)\\n\\n document.append(client.find_one())\\n\\n return document\",\n \"def find_first(cls, **kwargs):\\n return cls.query.filter_by(**kwargs).first()\",\n \"def get(self, id, model_type=None):\\n # If collection is not specified, use the collection when this client is\\n if not model_type:\\n collection = self._collection\\n else:\\n collection = self._db[model_type]\\n\\n print 'mongo.get(): id={}'.format(id)\\n if id:\\n obj = collection.find_one({'_id': ObjectId(id)})\\n if not obj:\\n raise DbProviderError(\\\"DB record for {} is not found\\\".format(id))\\n obj['_id'] = str(obj['_id'])\\n else:\\n obj = {}\\n return obj\",\n \"def _query_and_fetchone(self, query):\\n with self._connect() as conn:\\n cur = conn.cursor()\\n cur.execute(query)\\n result = cur.fetchone()\\n\\n return result\",\n \"def fetchone(self, autoConvert=True, format=None):\\r\\n if self._closed:\\r\\n raise Error('The cursor has been closed.')\\r\\n if self.connection._closed:\\r\\n raise Error('The connection to the database has been closed.')\\r\\n if self.info['results'] == None:\\r\\n raise Error('Previous call to execute() did not produce a result set. No results to fetch.')\\r\\n else:\\r\\n res = self.fetchmany(1, format)\\r\\n if res == ():\\r\\n return None\\r\\n else:\\r\\n return res[0]\",\n \"async def get_one(self, pk):\\n\\n return await self._expand(await self.db.get_one(pk=pk))\",\n \"async def find_one_and_update(self, spec, update_fields, upsert=False, return_document=False, fields=None, cursor=None):\\n if not cursor:\\n cursor = self._cursor\\n spec[DELETE_FLAG] = {\\\"$ne\\\": True}\\n if \\\"_id\\\" in spec:\\n spec[\\\"_id\\\"] = self._convert_id_object(spec[\\\"_id\\\"])\\n result = await cursor.find_one_and_update(spec, update_fields, projection=fields, upsert=upsert, return_document=return_document)\\n #if result and \\\"_id\\\" in result:\\n # result[\\\"_id\\\"] = str(result[\\\"_id\\\"])\\n return result, None\",\n \"def one(self):\\n self.limit(2)\\n u = self.get_cursor()\\n u = list(u)\\n assert u, \\\"expected one object\\\"\\n if len(u) > 1:\\n assert u, \\\"expected one object, more than one received\\\"\\n return self.from_(**self.prepare_data(u[0]))\",\n \"def get_one_by_id(self, object, id):\\n self.lock.acquire()\\n result = self.__Session.query(object).get(id)\\n self.lock.release()\\n return result\",\n \"async def get_one(self, where):\\n\\n pass\",\n \"def findone(cls, *lst, **dct):\\n query = cls.where(*lst, **dct).select()\\n result = query.execute()\\n return result.fetchone()\",\n \"async def find_one_and_delete(self, spec, fields=None, cursor=None):\\n if not cursor:\\n cursor = self._cursor\\n spec[DELETE_FLAG] = {\\\"$ne\\\": True}\\n if \\\"_id\\\" in spec:\\n spec[\\\"_id\\\"] = self._convert_id_object(spec[\\\"_id\\\"])\\n result = await cursor.find_one_and_delete(spec, projection=fields)\\n #if result and \\\"_id\\\" in result:\\n # result[\\\"_id\\\"] = str(result[\\\"_id\\\"])\\n return result, None\",\n \"def fetchOne(self,query):\\n# self.updateDBAndLog(query)\\n# tup = self.cursor.fetchone()\\n\\tself.updateLog(query)\\n\\tcur = self.db.cursor()\\n\\tcur.execute(query)\\n\\ttup = cur.fetchone()\\n\\tcur.close()\\n\\treturn tup\",\n \"def query_one(self, *args, **kwargs):\\n kwargs.setdefault('error_if_multiple', True)\\n records = self.query(*args, **kwargs)\\n return records[0] if records else None\",\n \"def get_document_by_id(document_id):\\n return Documents.query.filter_by(id=document_id).first()\",\n \"def fetch_one(q, *params):\\n db = Database()\\n db.cur.execute(q, params)\\n ret = db.cur.fetchone()\\n db.con.close()\\n return ret\",\n \"def test_find_one(self):\\n person1 = self.Person(name=\\\"User A\\\", age=20)\\n person1.save()\\n person2 = self.Person(name=\\\"User B\\\", age=30)\\n person2.save()\\n\\n # Retrieve the first person from the database\\n person = self.Person.objects.first()\\n assert isinstance(person, self.Person)\\n assert person.name == \\\"User A\\\"\\n assert person.age == 20\\n\\n # Use a query to filter the people found to just person2\\n person = self.Person.objects(age=30).first()\\n assert person.name == \\\"User B\\\"\\n\\n person = self.Person.objects(age__lt=30).first()\\n assert person.name == \\\"User A\\\"\\n\\n # Use array syntax\\n person = self.Person.objects[0]\\n assert person.name == \\\"User A\\\"\\n\\n person = self.Person.objects[1]\\n assert person.name == \\\"User B\\\"\\n\\n with pytest.raises(IndexError):\\n self.Person.objects[2]\\n\\n # Find a document using just the object id\\n person = self.Person.objects.with_id(person1.id)\\n assert person.name == \\\"User A\\\"\\n\\n with pytest.raises(InvalidQueryError):\\n self.Person.objects(name=\\\"User A\\\").with_id(person1.id)\",\n \"def get(cls, db, id):\\n doc = cls.collection(db).find_one(filter={ '_id': ObjectId(id) })\\n return Todo(**doc)\",\n \"def find_one(self, select, tables, on={}, filter={}):\\n query, args = self.__build_find_query(select, tables, on, filter)\\n\\n cur = self.conn.cursor()\\n\\n try:\\n cur.execute(query, args)\\n result = cur.fetchone()\\n except Exception as e:\\n # logger = Logger.getInstance()\\n # logger.log(context=self.__class__.__name__,\\n # method=\\\"fetch_all\\\",\\n # msg=f\\\"query: {query}; Excpetion {e}\\\")\\n print(e)\\n result = None\\n finally:\\n cur.close()\\n return result\",\n \"def fetch_one(cls: Type[_T], session: Session, identifier: int) -> _T:\\n return Query(cls, session=session).get(identifier)\",\n \"async def get_object(conn: Database, query):\\n return await conn.fetch_one(query=query)\",\n \"def select_one(cls, pk):\\n with sqlite3.connect(cls.dbpath) as conn:\\n conn.row_factory = sqlite3.Row\\n curs = conn.cursor()\\n sql = f\\\"\\\"\\\"SELECT * FROM {cls.tablename} WHERE pk =?;\\\"\\\"\\\"\\n curs.execute(sql, (pk,)) #don't forget to put a comma after single value inputs\\n row = curs.fetchone()\\n return cls(**row)\",\n \"def find_one(cls, dataset_id):\\n return super(cls, cls).find_one({DATASET_ID: dataset_id})\",\n \"def get_first_item(cls):\\n return cls.query.first()\",\n \"def find_one(self, query, fields=None):\\n # get raw result\\n record = self._find_one(query)\\n # if no result found\\n if record is None:\\n return None\\n # handle `fields` parameter\\n if fields is None:\\n # if fields not given - return raw result\\n result = record.to_id_dict()\\n elif isinstance(fields, str):\\n # chose one value\\n result = record[fields]\\n elif isinstance(fields, list):\\n # chose only values matching given fields\\n result = record.get_fields_list(fields)\\n else:\\n raise TypeError(f\\\"`fields` should be of one of types: \\\"\\n f\\\"`None`, `str` or `list`. got: {type(fields)}\\\")\\n return result\",\n \"def fetch_one(cls, limiter=None):\\n return cls.where(limiter).fetch_one()\",\n \"def fetchone(self):\\n try:\\n return next(self._results)\\n except StopIteration:\\n return None\",\n \"def get(self, _id):\\n try:\\n doc = self._db[_id]\\n # For speed testing\\n del self._db[_id]\\n except KeyError:\\n return None\\n else:\\n return self._parse_doc(doc)\",\n \"def retrieveById(self, doc_id=None):\\n obj = self.find_one({'_id': doc_id if id else self.get('_id')})\\n if obj:\\n self._import(obj)\\n return True\\n return False\",\n \"def by_id(cls, _id):\\n return dbsession.query(cls).filter_by(id=_id).first()\",\n \"def by_id(cls, _id):\\n return dbsession.query(cls).filter_by(id=_id).first()\",\n \"def by_id(cls, _id):\\n return dbsession.query(cls).filter_by(id=_id).first()\",\n \"def get_record(self, collection_name, filter):\\n\\n try:\\n self.logger.info('in get_record()')\\n collection = self.get_db()[collection_name]\\n record = collection.find_one(filter)\\n self.logger.info('in get_record()')\\n return record\\n except Exception as e:\\n self.logger.error(f'Error occurred while getting records {e}')\",\n \"def get_one(self, index, *args, **kw):\\n person = M.People.query.get(index=index)\\n log.debug('person {}'.format(person))\\n if(person):\\n kw['_id'] = person._id\\n return super(PeopleAPIController, self).get_one(*args, **kw)\",\n \"def get_document(self, doc_id: int) -> Optional[Users]:\\n try:\\n doc = self.session.query(CandidatesDocuments).get(doc_id)\\n\\n return doc\\n except Exception as excpt:\\n self.session.rollback()\\n print(f'Could not get doc: {excpt}')\\n\\n return None\",\n \"def find(self, *args, **kwds):\\n return self.collection.find(*args, **kwds)\",\n \"def find_one_bywhereclause(cls, whereclause):\\n return cls.dbm().modelclass_find_one_bywhereclause(cls, whereclause)\",\n \"async def get(self, id=None, alias=None, **kwargs):\\n\\n from jetengine import Q\\n\\n if id is None and not kwargs:\\n raise RuntimeError(\\\"Either an id or a filter must be provided to get\\\")\\n\\n if id is not None:\\n if not isinstance(id, ObjectId):\\n id = ObjectId(id)\\n\\n filters = {\\\"_id\\\": id}\\n else:\\n filters = Q(**kwargs)\\n filters = self.get_query_from_filters(filters)\\n\\n instance = await self.coll(alias).find_one(filters, projection=self._loaded_fields.to_query(self.__klass__))\\n if instance is None:\\n return None\\n else:\\n doc = self.__klass__.from_son(\\n instance,\\n # if _loaded_fields is not empty then\\n # document is partly loaded\\n _is_partly_loaded=bool(self._loaded_fields),\\n # set projections for references (if any)\\n _reference_loaded_fields=self._reference_loaded_fields,\\n )\\n if self.is_lazy:\\n return doc\\n else:\\n await doc.load_references()\\n return doc\",\n \"def find_exact(self, **kwargs):\\n results = list(self.find(**kwargs))\\n if len(results) == 1:\\n return results[0]\\n return None\",\n \"def find_one(\\n self,\\n *args,\\n projection_model: Optional[Type[BaseModel]] = None,\\n session: Optional[ClientSession] = None\\n ):\\n self.find_expressions += args\\n self.project(projection_model)\\n self.set_session(session=session)\\n return self\",\n \"def find_by_doc_id(cls, doc_reg_id: str):\\n document = None\\n if doc_reg_id:\\n try:\\n document = cls.query.filter(Db2Document.id == doc_reg_id).one_or_none()\\n except Exception as db_exception: # noqa: B902; return nicer error\\n current_app.logger.error('Db2Document.find_by_doc_id exception: ' + str(db_exception))\\n raise DatabaseException(db_exception)\\n if document:\\n document.strip()\\n return document\",\n \"def by_id(cls, id):\\n try:\\n return DBSession.query(cls).filter(cls.id == id).one()\\n except (NoResultFound, MultipleResultsFound):\\n return None\",\n \"def fetch_one(self, sql):\\n curs = self.q(sql, True)\\n row = curs.fetchone()\\n if curs._have_unread_result():\\n curs.fetchall()\\n curs.close()\\n\\n if row:\\n return row[0]\\n else:\\n return None\",\n \"def query_fetchone(self, q, param=None):\\r\\n try:\\r\\n c = self.connection.cursor()\\r\\n if param is None:\\r\\n c.execute(q)\\r\\n else:\\r\\n c.execute(q, param)\\r\\n self.logger.log(logger.LogLevel.DEBUG, 'database.fetchone: %s | %s' % (q, param)) \\r\\n return c.fetchone()\\r\\n except Exception as e:\\r\\n self.logger.log(logger.LogLevel.ERROR, 'database.fetchone: %s. %s | %s' % (e, q, param))\\r\\n return False\",\n \"async def find_by_id(self, _id: int) -> Record:\\n conn: Connection\\n async with self.db_pool.acquire() as conn:\\n return await conn.fetchrow(\\n f\\\"SELECT * FROM {self.table_name} WHERE {self.primary_key}=$1\\\",\\n _id,\\n )\",\n \"def fetchone(self):\\n\\n self._check_executed()\\n\\n if self._query_id == -1:\\n msg = \\\"query didn't result in a resultset\\\"\\n self._exception_handler(ProgrammingError, msg)\\n\\n if self.rownumber >= self.rowcount:\\n return None\\n\\n if self.rownumber >= (self._offset + len(self._rows)):\\n self.nextset()\\n\\n result = self._rows[self.rownumber - self._offset]\\n self.rownumber += 1\\n return result\",\n \"def first(self, **opts):\\n try:\\n return next(self.find(**opts))\\n except StopIteration:\\n if 'default' in opts:\\n return opts['default']\\n else:\\n raise KeyError(\\\"no matching objects\\\")\",\n \"def get_one_event(cls, event_id):\\n try:\\n event = events_coll.find_one({\\\"_id\\\": ObjectId(event_id)})\\n return cls(**event)\\n except Exception as e:\\n print(e)\",\n \"async def one(\\n self,\\n statement: Executable,\\n params: t.Optional[\\n t.Union[t.Mapping[str, t.Any], t.Sequence[t.Mapping[str, t.Any]]]\\n ] = None,\\n execution_options: t.Optional[t.Mapping[str, t.Any]] = None,\\n bind_arguments: t.Optional[t.Mapping[str, t.Any]] = None,\\n ) -> t.Any:\\n result = await self.execute(\\n statement, params, execution_options=execution_options, bind_arguments=bind_arguments\\n )\\n if isinstance(result, sa.engine.CursorResult):\\n item = result.one()\\n else:\\n item = result.scalar_one()\\n return item\",\n \"async def fetch_single(self, query: str, args: Optional[Iterable]=None) -> Any:\\n res = await self.fetch_row(query, args)\\n ret = None\\n if res and len(res) == 1:\\n ret = res[0]\\n return ret\",\n \"def returnOne(self):\\n try:\\n # self.checkValName()\\n self.cursor.execute(self.query % self.val)\\n self.results = self.conn.fetchone()\\n except Exception as e:\\n print \\\"Query failed: %s \\\" % e\",\n \"def find(cls, **kwargs):\\n return cls.query.filter_by(**kwargs).first()\",\n \"def _get_mongo_session(self, sid):\\n return self.coll.find_one({'sid': sid})\",\n \"def fetch_obj(type, id, error=404, new_id=False):\\n if id is None:\\n abort(error)\\n obj_q = Session.query(type)\\n obj = obj_q.get(int(id))\\n #else:\\n # obj = obj_q.filter(type.ID==int(id)).first()\\n\\n if obj is None:\\n abort(error)\\n return obj\",\n \"def fetchone(self, sql, val=()):\\n cursor = self.__db.cursor()\\n cursor.execute(sql, val)\\n return cursor.fetchone()\",\n \"def find(self, primary_key):\\n sql = '{} WHERE {} = %s'.format(self._select(), self.PRIMARY_KEY)\\n cursor = yield self._pool.execute(sql, [primary_key])\\n result = cursor.fetchmany(1)\\n return self.convert_result_to_object(result)\",\n \"def find_by_id(cls, _id):\\n user = cls.query.filter_by(id=_id).first()\\n return user\",\n \"def get_single_user(username):\\n user = mongo.db.users.find_one({\\\"username\\\": username})\\n user[\\\"_id\\\"] = str(user[\\\"_id\\\"])\\n return user\",\n \"def single(self):\\n records = list(self)\\n num_records = len(records)\\n if num_records == 0:\\n raise ResultError(\\\"Cannot retrieve a single record, because this result is empty.\\\")\\n elif num_records != 1:\\n raise ResultError(\\\"Expected a result with a single record, but this result contains at least one more.\\\")\\n else:\\n return records[0]\",\n \"def get_task(task_id):\\n return db.task.find_one({'_id': ObjectId(task_id)})\",\n \"def find(self, id, columns=None):\\n if not columns:\\n columns = ['*']\\n\\n return self.where('id', '=', id).first(1, columns)\",\n \"def returnOne(self):\\n try:\\n # self.checkValName()\\n self.dbc.execute(self.query, self.val)\\n self.results = self.dbc.fetchone()\\n except MySQLdb.Error, e:\\n print \\\"Query failed: %s \\\" % e\",\n \"def find(self, user_id: UserId) -> Optional[U]:\\n ...\",\n \"def _dictfetchone(self):\\n data = self._dictfetchall()\\n if data:\\n return data[0]\\n return {}\",\n \"def single(self, strict: bool = False) -> t.Optional[Record]:\\n self._buffer(2)\\n buffer = self._record_buffer\\n self._record_buffer = deque()\\n self._exhaust()\\n if not buffer:\\n if not strict:\\n return None\\n raise ResultNotSingleError(\\n self,\\n \\\"No records found. \\\"\\n \\\"Make sure your query returns exactly one record.\\\"\\n )\\n elif len(buffer) > 1:\\n res = buffer.popleft()\\n if not strict:\\n warn(\\\"Expected a result with a single record, \\\"\\n \\\"but found multiple.\\\")\\n return res\\n else:\\n raise ResultNotSingleError(\\n self,\\n \\\"More than one record found. \\\"\\n \\\"Make sure your query returns exactly one record.\\\"\\n )\\n return buffer.popleft()\",\n \"def fetch_one(cls, sql, **kwargs):\\n conn = kwargs['conn']\\n\\n cursor = conn.cursor(dictionary=True, buffered=False)\\n for _ in cursor.execute(sql, kwargs.get('args'), multi=True):\\n pass\\n\\n result = cursor.fetchone()\\n cls.close(conn, cursor)\\n\\n return result\",\n \"def get_by_id(cls, id):\\n try:\\n return cls.objects.get(id=id)\\n except(IntegrityError, OperationalError):\\n return None\",\n \"def find_by_id(cls, iid: int):\\n return cls.query.filter_by(id=iid).first()\",\n \"def one(self, except_all=False):\\n\\n length = len(self)\\n if length > 1:\\n raise MultipleResultsFound(\\\"%s results found.\\\" % length)\\n\\n result = self.first()\\n if result is None and except_all:\\n raise NoResultFound\\n return result\",\n \"def get_one(self, arg):\\n if self.validator.assert_id(arg):\\n return self.get_item(item_id=arg)\\n\\n elif arg == 'schema':\\n return self.validator.schema\\n\\n else:\\n pecan.abort(404)\",\n \"def get_document(obj):\\n try:\\n return ES.get(\\n index=obj.get_index_name(), doc_type=obj.get_document_type(), id=obj.pk)\\n except NotFoundError:\\n raise DocumentNotFound(obj.get_index_name(), obj.pk)\",\n \"def scalar(self):\\n try:\\n ret = self.one()\\n if not isinstance(ret, collections_abc.Sequence):\\n return ret\\n return ret[0]\\n except orm_exc.NoResultFound:\\n return None\",\n \"def fetchone(self):\\n self._check_closed()\\n if self._result_set is None:\\n raise Error(\\\"Previous execute did not produce any results or no call was issued yet\\\")\\n self.rownumber += 1\\n return self._result_set.fetchone(self.session)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7754107","0.7186727","0.7182808","0.715503","0.69664955","0.6931495","0.69100857","0.6904317","0.6898412","0.6841113","0.68210936","0.6808862","0.679702","0.6777635","0.67716956","0.6718852","0.6685826","0.66839063","0.66428053","0.6642651","0.66407835","0.6631507","0.66231894","0.65974617","0.65802956","0.65712774","0.65319496","0.6519915","0.6492244","0.64813393","0.6476199","0.6465319","0.64631295","0.6440141","0.6431312","0.6431041","0.6427448","0.64167535","0.6410483","0.6398157","0.6389911","0.63704777","0.63686043","0.63665706","0.6360341","0.6349469","0.63218534","0.6249437","0.62484056","0.6235093","0.62287927","0.6220761","0.62192935","0.6197069","0.61960495","0.6169605","0.6158771","0.6158771","0.6158771","0.61514217","0.61183923","0.6102424","0.6094291","0.60792005","0.607839","0.60736096","0.605296","0.6050421","0.6048594","0.6044614","0.6044568","0.6043685","0.60400736","0.6032931","0.6032353","0.6021323","0.60002834","0.5988546","0.59625804","0.595652","0.59305364","0.5929339","0.59288174","0.59206396","0.59165007","0.58965796","0.5892179","0.58899784","0.5882167","0.5880011","0.5867442","0.58625907","0.5859698","0.5852753","0.585268","0.58431655","0.58386296","0.57978266","0.5793688","0.57883924"],"string":"[\n \"0.7754107\",\n \"0.7186727\",\n \"0.7182808\",\n \"0.715503\",\n \"0.69664955\",\n \"0.6931495\",\n \"0.69100857\",\n \"0.6904317\",\n \"0.6898412\",\n \"0.6841113\",\n \"0.68210936\",\n \"0.6808862\",\n \"0.679702\",\n \"0.6777635\",\n \"0.67716956\",\n \"0.6718852\",\n \"0.6685826\",\n \"0.66839063\",\n \"0.66428053\",\n \"0.6642651\",\n \"0.66407835\",\n \"0.6631507\",\n \"0.66231894\",\n \"0.65974617\",\n \"0.65802956\",\n \"0.65712774\",\n \"0.65319496\",\n \"0.6519915\",\n \"0.6492244\",\n \"0.64813393\",\n \"0.6476199\",\n \"0.6465319\",\n \"0.64631295\",\n \"0.6440141\",\n \"0.6431312\",\n \"0.6431041\",\n \"0.6427448\",\n \"0.64167535\",\n \"0.6410483\",\n \"0.6398157\",\n \"0.6389911\",\n \"0.63704777\",\n \"0.63686043\",\n \"0.63665706\",\n \"0.6360341\",\n \"0.6349469\",\n \"0.63218534\",\n \"0.6249437\",\n \"0.62484056\",\n \"0.6235093\",\n \"0.62287927\",\n \"0.6220761\",\n \"0.62192935\",\n \"0.6197069\",\n \"0.61960495\",\n \"0.6169605\",\n \"0.6158771\",\n \"0.6158771\",\n \"0.6158771\",\n \"0.61514217\",\n \"0.61183923\",\n \"0.6102424\",\n \"0.6094291\",\n \"0.60792005\",\n \"0.607839\",\n \"0.60736096\",\n \"0.605296\",\n \"0.6050421\",\n \"0.6048594\",\n \"0.6044614\",\n \"0.6044568\",\n \"0.6043685\",\n \"0.60400736\",\n \"0.6032931\",\n \"0.6032353\",\n \"0.6021323\",\n \"0.60002834\",\n \"0.5988546\",\n \"0.59625804\",\n \"0.595652\",\n \"0.59305364\",\n \"0.5929339\",\n \"0.59288174\",\n \"0.59206396\",\n \"0.59165007\",\n \"0.58965796\",\n \"0.5892179\",\n \"0.58899784\",\n \"0.5882167\",\n \"0.5880011\",\n \"0.5867442\",\n \"0.58625907\",\n \"0.5859698\",\n \"0.5852753\",\n \"0.585268\",\n \"0.58431655\",\n \"0.58386296\",\n \"0.57978266\",\n \"0.5793688\",\n \"0.57883924\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7955518"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":18686,"cells":{"query":{"kind":"string","value":"because document can be nested, so you can use field.sub_field.subfield. ... to access children fields"},"document":{"kind":"string","value":"def dot_notation():\n ppt(list(\n users.find({\"profile.enthnicity\": \"asian\"})\n ))"},"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 subfield():\n return Subfield()","def _get_nested(nested_dict, field):\n print(nested_dict, field)\n keys = field.split('.')\n current = nested_dict\n for k in keys:\n print('key', k, 'current', current)\n # return None for nested fields without a value in this doc\n if isinstance(current, list):\n # this list could contain anything. skip objects not containing `k`.\n return [x[k] for x in current if x.get(k) is not None]\n if not k in current:\n current = None\n break\n current = current[k]\n return current","def test_exec_js_field_sub(self):\n\n class Comment(EmbeddedDocument):\n content = StringField(db_field=\"body\")\n\n class BlogPost(Document):\n name = StringField(db_field=\"doc-name\")\n comments = ListField(EmbeddedDocumentField(Comment), db_field=\"cmnts\")\n\n BlogPost.drop_collection()\n\n comments1 = [Comment(content=\"cool\"), Comment(content=\"yay\")]\n post1 = BlogPost(name=\"post1\", comments=comments1)\n post1.save()\n\n comments2 = [Comment(content=\"nice stuff\")]\n post2 = BlogPost(name=\"post2\", comments=comments2)\n post2.save()\n\n code = \"\"\"\n function getComments() {\n var comments = [];\n db[collection].find(query).forEach(function(doc) {\n var docComments = doc[~comments];\n for (var i = 0; i < docComments.length; i++) {\n comments.push({\n 'document': doc[~name],\n 'comment': doc[~comments][i][~comments.content]\n });\n }\n });\n return comments;\n }\n \"\"\"\n\n sub_code = BlogPost.objects._sub_js_fields(code)\n code_chunks = ['doc[\"cmnts\"];', 'doc[\"doc-name\"],', 'doc[\"cmnts\"][i][\"body\"]']\n for chunk in code_chunks:\n assert chunk in sub_code\n\n results = BlogPost.objects.exec_js(code)\n expected_results = [\n {\"comment\": \"cool\", \"document\": \"post1\"},\n {\"comment\": \"yay\", \"document\": \"post1\"},\n {\"comment\": \"nice stuff\", \"document\": \"post2\"},\n ]\n assert results == expected_results\n\n # Test template style\n code = \"{{~comments.content}}\"\n sub_code = BlogPost.objects._sub_js_fields(code)\n assert \"cmnts.body\" == sub_code\n\n BlogPost.drop_collection()","def _nested_lookup(doc, field):\n value = doc\n keys = field.split(\".\")\n try:\n for k in keys:\n value = value[k]\n except KeyError:\n return None\n\n return str(value)","def test_get_field(test_client):\n test_dict = {\"kfc\": {\"item\": \"chickens\"}}\n assert test_client.get_field(\"kfc.item\", doc=test_dict) == \"chickens\"","def _getFields(obj, tree=None, retval=None, fileobj=None):\n fieldAttributes = {'/FT': 'Field Type', '/Parent': 'Parent', '/T': 'Field Name', '/TU': 'Alternate Field Name',\n '/TM': 'Mapping Name', '/Ff': 'Field Flags', '/V': 'Value', '/DV': 'Default Value'}\n if retval is None:\n retval = OrderedDict()\n catalog = obj.trailer[\"/Root\"]\n # get the AcroForm tree\n if \"/AcroForm\" in catalog:\n tree = catalog[\"/AcroForm\"]\n else:\n return None\n if tree is None:\n return retval\n\n obj._checkKids(tree, retval, fileobj)\n for attr in fieldAttributes:\n if attr in tree:\n # Tree is a field\n obj._buildField(tree, retval, fileobj, fieldAttributes)\n break\n\n if \"/Fields\" in tree:\n fields = tree[\"/Fields\"]\n for f in fields:\n field = f.getObject()\n obj._buildField(field, retval, fileobj, fieldAttributes)\n\n return retval","def getUuidDocSubfield(coll, uuid, field, subField):\n mongoColl = mongoConfigColls[coll]\n query = { 'field' : field, 'apiviz_front_uuid' : uuid }\n result = mongoColl.find_one(query)\n log_app.debug(\"getUuidDocSubfield / result : %s\", result )\n return result[subField]","def nested_lookup(doc, field):\n value = doc\n keys = field.split(\".\")\n try:\n for k in keys:\n if isinstance(value, (list, tuple)):\n # assuming we have a list of dict with k as one of the keys\n stype = set([type(e) for e in value])\n if not stype:\n return None\n assert len(stype) == 1 and stype == {dict}, \"Expecting a list of dict, found types: %s\" % stype\n value = [e[k] for e in value if e.get(k)]\n # can't go further ?\n return value\n else:\n value = value[k]\n except KeyError:\n return None\n\n return value","def stored_fields(self, docnum):\r\n return self.doc_reader[docnum]","def get_content_field(self):\n for _, field in self.fields.items():\n if field.document is True:\n return field.index_fieldname","def get_fields_in_model(instance):\n assert isinstance(instance, Document)\n return instance._fields","def get_dict_value(field_name, doc):\n\n def get_array_value(doc, key):\n \"\"\"\n Takes a dictionary (doc) and a string (key) representing a dictionary\n key and one or more array indexes, e.g. \"location[0][1]\". Returns the\n corresponding value from the dictionary.\n \"\"\"\n # split key at the start of array values, e.g. 'loc[0]' -> ['loc', '0]']\n key_parts = key.split('[')\n\n # get the name of the parent field, e.g. \"loc\"\n key = key_parts.pop(0)\n\n # get the dictionary value, which is the first array\n array = doc[key]\n\n while len(key_parts) > 0:\n\n index = key_parts.pop(0)\n\n # remove trailing bracket from index value\n index = index.replace(']', '')\n\n # need to convert the string to an integer to use it as an index\n index = int(index)\n\n value = array[index]\n\n # step into the next array\n array = value\n\n return value\n\n if isinstance(field_name, str):\n\n doc_copy = deepcopy(doc)\n\n # parse the string into a list of keys\n keys = field_name.split('.')\n value = ''\n\n try:\n while len(keys) > 0:\n\n if isinstance(doc_copy, dict):\n\n key = keys.pop(0)\n\n # remove any leading or trailing whitespaces\n key.strip()\n\n # check if the key includes an array index (e.g., 'location[0]')\n if '[' in key:\n value = get_array_value(doc_copy, key)\n else:\n value = doc_copy[key]\n\n doc_copy = value\n\n else:\n return doc_copy\n\n except KeyError:\n # log this error so user knows to correct field_name\n # LOGGER.warning('The field_name \"%s\" cannot be found in the document %s.',\n # field_name, str(doc)[:160])\n return None\n\n return value","def field(self):\n return self.__field","def field(self):\n return self.reference.field","def get_fields(self):\n for child in self.children:\n if isinstance(child, MyTextField):\n yield child","def namespaced_fields(self):\n ...","def getSubfield(h, field, Lsubs):\n\td = {}\t\n\tfor k in Lsubs:\n\t\ttheElement = h.documentElement.getElementsByTagName(field)[0]\n\t\td[k] = str(theElement.getAttribute(k))\n\treturn d","def fields(self):\n ...","def test_map_field_recursive_case(self):\n field = 'content.title'\n mapping = {\n 'type': 'text',\n 'index': True\n }\n\n actual = mapper._map_field(mapping, field)\n expected = {\n 'properties': {\n 'content': {\n 'properties': {\n 'title': {\n 'type': 'text',\n 'index': True\n }\n }\n }\n }\n }\n self.assertEqual(actual, expected)","def field(self, field):\n return self.__getitem__(field)","def fields(self):","def _filter_doc_fields(cls, tag, user, document):\n query = {\n 'query': {\n 'bool': {\n 'must': [\n {\n \"term\": {\n \"doc_type__v1\": cls.document_type\n }\n },\n {\n \"term\": {\n \"is_active__v1\": True\n }\n }\n ]\n }\n }\n }\n if tag:\n query['query']['bool']['must'].append(\n {\n 'term': {\n \"tag__v1\": tag\n }\n }\n )\n if user:\n query['query']['bool']['should'] = [\n {\n 'nested': {\n 'path': 'permissions__v1.users__v1',\n 'filter': {\n {\n 'term': {\n 'permissions__v1.users__v1.id': user['id']\n }\n }\n }\n }\n },\n {\n 'nested': {\n 'path': 'permissions__v1.groups__v1',\n 'filter': {\n {\n 'term': {\n 'permissions__v1.groups__v1.id': u' OR '.join(user['groups'])\n }\n }\n }\n }\n },\n {\n 'term': {\n 'tag.public': True\n }\n }\n ]\n es_response_raw = get_es_response(\n req_session.get(get_path_search('field-version'),\n data=json.dumps(query)))\n es_response = es_response_raw.json()\n db_fields = map(lambda x: x['field__v1'], es_response['hits']['hits'])\n document_new = {}\n for key in document:\n if key in db_fields:\n document_new[key] = document[key]\n return document_new","def test_nested():\n # pylint: disable=no-member\n assert issubclass(NestedSchema, graphene.ObjectType)\n assert isinstance(NestedSchema.name, graphene.String)\n assert isinstance(NestedSchema.leaf, graphene.Field)\n assert str(NestedSchema.leaf.type) == \"Leaf\"\n assert isinstance(NestedSchema.leaf.type.value, graphene.String)\n assert isinstance(NestedSchema.leaf.type.leaflets, graphene.List)","def _get_child_fields(self, cr, uid, ids, context=None):\n res = self.search(cr, uid, [('parent_id','child_of',ids)], context=context)\n return res","def get_field(self, field_name):\n all_fields = self._fields.items(self._fields.root)\n print(\"all_fields\", all_fields)\n for name, field in all_fields:\n print(name, field_name)\n if name == field_name:\n return field","def getdocfield(fieldname):\t\t\n\tl = [d for d in doctype_dl if d.doctype=='DocField' and d.fieldname==fieldname]\n\treturn l and l[0] or None","def __get__(self, instance, owner):\n if instance is None:\n # Document class being used rather than a document object\n return self\n\n ReferenceField = _import_class(\"ReferenceField\")\n GenericReferenceField = _import_class(\"GenericReferenceField\")\n EmbeddedDocumentListField = _import_class(\"EmbeddedDocumentListField\")\n\n auto_dereference = instance._fields[self.name]._auto_dereference\n\n dereference = auto_dereference and (\n self.field is None\n or isinstance(self.field, (GenericReferenceField, ReferenceField))\n )\n\n if (\n instance._initialised\n and dereference\n and instance._data.get(self.name)\n and not getattr(instance._data[self.name], \"_dereferenced\", False)\n ):\n ref_values = instance._data.get(self.name)\n instance._data[self.name] = self._lazy_load_refs(\n ref_values=ref_values, instance=instance, name=self.name, max_depth=1\n )\n if hasattr(instance._data[self.name], \"_dereferenced\"):\n instance._data[self.name]._dereferenced = True\n\n value = super().__get__(instance, owner)\n\n # Convert lists / values so we can watch for any changes on them\n if isinstance(value, (list, tuple)):\n if issubclass(type(self), EmbeddedDocumentListField) and not isinstance(\n value, EmbeddedDocumentList\n ):\n value = EmbeddedDocumentList(value, instance, self.name)\n elif not isinstance(value, BaseList):\n value = BaseList(value, instance, self.name)\n instance._data[self.name] = value\n elif isinstance(value, dict) and not isinstance(value, BaseDict):\n value = BaseDict(value, instance, self.name)\n instance._data[self.name] = value\n\n if (\n auto_dereference\n and instance._initialised\n and isinstance(value, (BaseList, BaseDict))\n and not value._dereferenced\n ):\n value = self._lazy_load_refs(\n ref_values=value, instance=instance, name=self.name, max_depth=1\n )\n value._dereferenced = True\n instance._data[self.name] = value\n\n return value","def db_fields(self):","def subfieldFactory(name):\n from pythia.pyre.inventory import facility\n return facility(name, family=\"subfield\", factory=Subfield)","def GetSubfieldDef(fielddef):\n\n format_, addrdef, datadef, arraydef, validate, cmd, converter = GetFieldDef(fielddef, fields='format_, addrdef, datadef, arraydef, validate, cmd, converter')\n\n # create new arraydef\n if len(arraydef) > 1:\n arraydef = arraydef[1:]\n else:\n arraydef = None\n\n # create new datadef\n if isinstance(datadef, tuple):\n if cmd is not None:\n datadef = (arraydef, validate, cmd)\n else:\n datadef = (arraydef, validate)\n else:\n datadef = arraydef\n\n # set new field def\n subfielddef = None\n if converter is not None:\n subfielddef = (format_, addrdef, datadef, converter)\n else:\n subfielddef = (format_, addrdef, datadef)\n\n return subfielddef","def get_fields():\n return jsonify(result=Tree.fields())","def Fields(self):\n return self._fields","def stored_fields(self, docnum):\n\t\treturn self.index.collection.get(docnum).keys()","def get_fields(node):\r\n return dict(iter_fields(node))","def extract_doc(self, doc):\n if doc.pod_path.endswith('.yaml'):\n raw_data = yaml.load(\n doc.pod.read_file(doc.pod_path), Loader=yaml_utils.PlainTextYamlLoader)\n else:\n raw_data = doc.format.front_matter.raw_data\n\n if not raw_data:\n print('No raw data found for document: {}'.format(doc.pod_path))\n return\n\n data = collections.OrderedDict()\n\n tagged_keys = tuple(['{}@'.format(key)\n for key in COLLECTION_META_KEYS])\n\n for key, value in raw_data.items():\n if key in COLLECTION_META_KEYS or key.startswith(tagged_keys):\n normal_key = key.lstrip('$')\n if 'path' in key:\n # Use `__NONE` as sentinel to support equating a `value` of None.\n collection_path = self.blueprint.get(\n key, self.blueprint.get(normal_key, '__NONE'))\n # Skip the paths that are the same as the collection.\n if collection_path == value:\n continue\n data[normal_key] = value\n\n if data:\n self.paths[doc.collection_sub_path[1:]] = data","def iter_child_nodes(node):\r\n for name, field in iter_fields(node):\r\n if isinstance(field, AST):\r\n yield field\r\n elif isinstance(field, list):\r\n for item in field:\r\n if isinstance(item, AST):\r\n yield item","def __call__(self, collection, field):\n pass","def get_as_subtext_field(field, field_title=None) -> str:\n s = \"\"\n if field:\n s = f\"{field} | \"\n else:\n return \"\"\n\n if field_title:\n s = f\"{field_title}: \" + s\n\n return s","def get_as_subtext_field(field, field_title=None) -> str:\n s = \"\"\n if field:\n s = f\"{field} | \"\n else:\n return \"\"\n\n if field_title:\n s = f\"{field_title}: \" + s\n\n return s","def get_field(self, field):\r\n if field not in self.fields:\r\n raise ValueError(\"Invalid field: {}. Must be one of: {}\"\r\n .format(field, self.fields))\r\n sub = set(meta[field] for meta in self.data)\r\n return sub","def field(self):\n return self.__field","def get_field(self):\n return self","def mask_custom_field(self, custom_field, doc_type):\n\t\tcustom_field.fields.update({\n\t\t\t'doctype': 'DocField',\n\t\t\t'parent': doc_type,\n\t\t\t'parentfield': 'fields',\n\t\t\t'parenttype': 'DocType',\n\t\t})","def process(node, model, editable, get=get_name):\n if node.tag in VIEW_TYPES:\n # determine whether this view is editable\n editable = editable and _view_is_editable(node)\n elif node.tag in ('field', 'groupby'):\n # determine whether the field is editable\n field = model._fields.get(node.get('name'))\n if field:\n editable = editable and field_is_editable(field, node)\n\n for key, val in node.items():\n if not val:\n continue\n if key in ATTRS_WITH_FIELD_NAMES:\n process_expr(val, get, key, val)\n elif key == 'attrs':\n process_attrs(val, get, key, val)\n\n if node.tag in ('field', 'groupby') and field and field.relational:\n if editable and not node.get('domain'):\n domain = field._description_domain(env)\n # process the field's domain as if it was in the view\n if isinstance(domain, str):\n process_expr(domain, get, 'domain', domain)\n # retrieve subfields of 'parent'\n model = env[field.comodel_name]\n get = partial(get_subname, get)\n\n for child in node:\n if node.tag == 'search' and child.tag == 'searchpanel':\n # searchpanel part has to be validated independently\n continue\n process(child, model, editable, get)","def get_fields(self):\n for field in self.fields_box.children:\n if isinstance(field, MyTextField):\n yield field","def objectFields(self):\n raise NotImplementedError","def field(self):\n return self._field","def field(self):\n return self._field","def field(self):\n return self._field","def field(self):\n return self._field","def get_as_subtext_field(field, field_title=None) -> str:\n s = \"\"\n if field:\n s = f\"{field} | \"\n else:\n return \"\"\n\n if field_title:\n s = f\"{field_title} :\" + s\n\n return s","def test_query_generic_embedded_document(self):\n\n class A(EmbeddedDocument):\n a_name = StringField()\n\n class B(EmbeddedDocument):\n b_name = StringField()\n\n class Doc(Document):\n document = GenericEmbeddedDocumentField(choices=(A, B))\n\n Doc.drop_collection()\n Doc(document=A(a_name=\"A doc\")).save()\n Doc(document=B(b_name=\"B doc\")).save()\n\n # Using raw in filter working fine\n assert Doc.objects(__raw__={\"document.a_name\": \"A doc\"}).count() == 1\n assert Doc.objects(__raw__={\"document.b_name\": \"B doc\"}).count() == 1\n assert Doc.objects(document__a_name=\"A doc\").count() == 1\n assert Doc.objects(document__b_name=\"B doc\").count() == 1","def subdocument(db_type):\n if db_type != \"ephemeraldb\":\n pytest.skip(\"ephemeraldb test only\")\n yield EphemeralDocument(\n {\"_id\": 1, \"hello\": \"there\", \"mighty\": \"duck\", \"and\": {\"the\": \"drake\"}}\n )","def test_entities__Entity__getRawField__3(entity_with_field, field):\n assert field == entity_with_field.getRawField(field.__name__)","def test_reference_field_find(self):\n\n class BlogPost(Document):\n content = StringField()\n author = ReferenceField(self.Person)\n\n BlogPost.drop_collection()\n self.Person.drop_collection()\n\n me = self.Person(name=\"Test User\").save()\n BlogPost(content=\"test 123\", author=me).save()\n\n assert 1 == BlogPost.objects(author=me).count()\n assert 1 == BlogPost.objects(author=me.pk).count()\n assert 1 == BlogPost.objects(author=\"%s\" % me.pk).count()\n\n assert 1 == BlogPost.objects(author__in=[me]).count()\n assert 1 == BlogPost.objects(author__in=[me.pk]).count()\n assert 1 == BlogPost.objects(author__in=[\"%s\" % me.pk]).count()","def iter_fields(node):\r\n for field in getattr(node, '_fields', ()) or ():\r\n try:\r\n yield field, getattr(node, field)\r\n except AttributeError:\r\n pass","def get_field(self, bib_entry, field):\n output = bib_entry.fields[field] if field in bib_entry.fields else \"\"\n return self.strip_braces(output)","def getFieldValue(self, field, no_html=False, external_id=True, depth=1, optimize=False):\n if field[\"type\"] == \"category\":\n if field[\"config\"][\"settings\"][\"multiple\"]:\n values = []\n for category in field[\"values\"]:\n values.append(category[\"value\"][\"text\"])\n return values\n else:\n return field[\"values\"][0][\"value\"][\"text\"]\n elif field[\"type\"] == \"image\":\n values = []\n for image in field['values']:\n values.append([image[\"value\"][\"mimetype\"], image[\"value\"][\"file_id\"]])\n return values\n elif field[\"type\"] == \"date\":\n return field[\"values\"][0]\n elif field[\"type\"] == \"app\":\n itemID = field[\"values\"][0][\"value\"][\"item_id\"]\n appID = field[\"values\"][0][\"value\"][\"app\"][\"app_id\"]\n if depth<=0:\n return itemID\n else:\n if optimize:#Si es necesario optimizar la carga del item\n try: #Intenta buscar la lista de items como un atributo en self\n items = getattr(self, str(appID))\n except AttributeError:\n #Como no los encontró, crea una nueva PodioAPI con la appID de destino y le pide los items\n if self.client:\n nested_api = self\n else:\n try:\n nested_api = self.__class__(appID)\n except: #TODO: Especificar la excepcion que es de tipo \"DoesNotExist\"\n raise Exception(\"Hubo un error creando el nuevo objeto 'PodioApi' para el item relacionado con app_id %s. Por favor agregar el app_id y el app_token de esa aplicacion a la base de datos\" % appID)\n items = nested_api.get_filtered_items(None, depth=depth-1)\n #Luego crea el atributo para que esta llamada no se repita\n setattr(self, str(appID), items)\n #Ya teniendo a todos los items, busca entre la lista aquel cuya ID es igual al item ID de la referencia, y lo pone como valor del campo.\n item = None\n for i in items:\n if i[\"item\"] == int(itemID):\n item = i\n\n else:\n data = self._client.Item.find(int(itemID))\n if not external_id:\n item = self.make_dict(data, external_id=external_id, depth=depth-1)\n else:\n item = self.makeDict(data, nested=True)\n return item\n elif field[\"type\"] == \"text\":\n text = field[\"values\"][0][\"value\"]\n if no_html and field[\"config\"][\"settings\"][\"format\"] == 'html':\n print (text.encode('utf-8'))\n html_text = BeautifulSoup(text, \"html5lib\")\n for p_tag in html_text.find_all('p'):\n p_tag.unwrap()\n for br_tag in html_text.find_all('br'):\n br_tag.name=\"text:line-break\"\n html_text.find('html').unwrap()\n html_text.find('head').unwrap()\n html_text.find('body').unwrap()\n text = unicode(html_text)\n #text = strip_tags(text)\n return text\n elif field[\"type\"] == \"embed\":\n return field[\"values\"][0][\"embed\"][\"url\"]\n else:\n #print field[\"type\"]\n return field[\"values\"][0][\"value\"]","def on_get_field(self, ins, const, obj):\n pass","def find_all(self, field):\n result = []\n for c in self.children:\n if c.name == field:\n result.append(c)\n result += c.find_all(field)\n return result","def field(self):\n return None","def getSubDataField(self, name, indices): \n if (indices >= self.__numExamples).any() or (indices < 0).any(): \n raise ValueError(\"Invalid example indices\")\n \n if name not in self.__examples: \n raise ValueError(\"Field does not exist: \" + name)\n\n\n return self.__examples[name][ix_(indices)]","def fieldOfView(self):\n return self._fieldOfView","def base_field(self):\n return self.field[1]","def test_get_document_with_fields(index_with_documents):\n response = index_with_documents().get_document(\"500682\", {\"fields\": [\"id\", \"title\"]})\n assert isinstance(response, Document)\n assert hasattr(response, \"title\")\n assert not hasattr(response, \"poster\")\n # assert 'poster' not in response\n assert response.title == \"The Highwaymen\"","def get_field(key, obj):\n\n val = obj\n\n for subkey in key.split('.'):\n val = val[subkey]\n\n return val","def _get_fields_from_root(self, cr, uid, ids, context=None):\n res = self.pool.get('xml.export.field').search(cr, uid, [('export_id','in',ids)], context=context)\n return res","def get_fields(self):\n fields = super().get_fields()\n fields['children'] = ForumListSerializer(read_only=True, many=True)\n return fields","def field(self):\r\n return self.value","def get_fields(self):\r\n return self.fields","def getChildren(tree, node, Dict):\r\n if node.children:\r\n for child in node.children:\r\n tree.dictDepth = tree.dictDepth+\"$$\"+child.name\r\n dictString = \"Dict[tree.root.name]\"\r\n for each in [e for e in tree.dictDepth.split(\"$$\") if not e == \"\"]:\r\n dictString+=\"['{}']\".format(each)\r\n exec(dictString+\"={'__files__':\"+str(child.files)+\"}\")\r\n \r\n if child.children:\r\n tree.getChildren(child, Dict)\r\n else:\r\n A, B = tree.dictDepth.rsplit(\"$$\"+child.name,1)\r\n tree.dictDepth = A+B\r\n try:\r\n A, B = tree.dictDepth.rsplit(\"$$\"+node.name,1)\r\n tree.dictDepth = A+B\r\n except:\r\n pass\r\n return Dict","def dump_record(record):\n rec = E.record()\n\n leader = record.get('leader')\n if leader:\n rec.append(E.leader(leader))\n\n if isinstance(record, GroupableOrderedDict):\n items = record.iteritems(with_order=False, repeated=True)\n else:\n items = iteritems(record)\n\n for df, subfields in items:\n # Control fields\n if len(df) == 3:\n if isinstance(subfields, string_types):\n controlfield = E.controlfield(subfields)\n controlfield.attrib['tag'] = df[0:3]\n rec.append(controlfield)\n elif isinstance(subfields, (list, tuple, set)):\n for subfield in subfields:\n controlfield = E.controlfield(subfield)\n controlfield.attrib['tag'] = df[0:3]\n rec.append(controlfield)\n else:\n # Skip leader.\n if df == 'leader':\n continue\n\n if not isinstance(subfields, (list, tuple, set)):\n subfields = (subfields,)\n\n df = df.replace('_', ' ')\n for subfield in subfields:\n if not isinstance(subfield, (list, tuple, set)):\n subfield = [subfield]\n\n for s in subfield:\n datafield = E.datafield()\n datafield.attrib['tag'] = df[0:3]\n datafield.attrib['ind1'] = df[3]\n datafield.attrib['ind2'] = df[4]\n\n if isinstance(s, GroupableOrderedDict):\n items = s.iteritems(with_order=False, repeated=True)\n elif isinstance(s, dict):\n items = iteritems(s)\n else:\n datafield.append(E.subfield(s))\n\n items = tuple()\n\n for code, value in items:\n if not isinstance(value, string_types):\n for v in value:\n datafield.append(E.subfield(v, code=code))\n else:\n datafield.append(E.subfield(value, code=code))\n\n rec.append(datafield)\n return rec","def check_attachment_fields(self):\n for field_name, field in self.fields.items():\n if isinstance(field, serializers.ListSerializer):\n if hasattr(field.child, \"field\"):\n for child_name, child in field.child.field.items():\n self.handle_attachment_field(child, child_name)\n else:\n self.handle_attachment_field(field, field_name)","def get_field(self, field):\n return self.extra_fields[field]","def get_field_attr(name):\n # de variant met een repeating group (entiteit, dataitem) levert hier nog een probleem op.\n # is dat omdat er twee entiteiten in 1 scherm staan?\n fields = []\n opts = my.rectypes[name]._meta\n for x in opts.get_fields(): # fields:\n fldname = x.name\n fldtype = x.get_internal_type()\n if fldname == 'id' or fldtype in ('ForeignKey', 'ManyToManyField'):\n # if fldname == 'id' or any((x.many2one, x.many2many, x.one2many))\n continue\n try:\n length = x.max_length\n except AttributeError:\n length = -1\n fields.append((fldname, fldtype[:-5], length))\n return fields","def test_field_resolution_single_inheritance_with_child_field_defined(self):\n child_field = ChildWithTheSameField()._get_fields()[\"name\"]\n self.assertEqual(child_field.default, \"C\")","def _handle_gfk_field_node(self, node, field):\n if node.getElementsByTagName('None'):\n return None\n ct_key = node.getAttribute(\"d:to\").split(NATURAL_KEY_JOINER)\n ctype = ContentType.objects.get_by_natural_key(*ct_key)\n Model = ctype.model_class()\n if hasattr(Model._default_manager, 'get_by_natural_key'):\n value = getInnerText(node).strip()\n field_value = value.split(NATURAL_KEY_JOINER)\n obj = Model._default_manager.db_manager(self.db).get_by_natural_key(*field_value)\n return obj\n else:\n field_value = getInnerText(node).strip()\n return Model._default_manager.db_manager(self.db).get(pk=Model._meta.pk.to_python(field_value))","def find(self, _id):\n _id = ObjectId(_id)\n model = self.mongo.db.userfield.find_one({\"fields._id\":_id})\n for field in model['fields']:\n if field['_id']==_id:\n return field","def __getattribute__(self, attr_k):\n # Getting the value of the field\n attr = object.__getattribute__(self, attr_k)\n attr_type = type(attr)\n if issubclass(attr_type, Field) or \\\n issubclass(attr_type, ReferenceManyField):\n return attr.value\n else:\n return attr","def parseInternalField(fn):\n content = getFileContent(fn)\n if content is not None:\n return parseInternalFieldContent(content)\n else:\n return None","def only(self, *fields):\n for field in fields:\n path = \".\".join(self.document._meta.resolve_subfield_hierarchy(field.split(\".\")))\n self._only_fields.add(path)\n if self.query._Cursor__fields is None:\n # Identifier and version fields must always be included\n self.query._Cursor__fields = { \"_id\" : 1, \"_version\" : 1 }\n\n self.query._Cursor__fields.update({ path : 1 })\n\n return self","def outputText(self, item, titleMode, internal=False):\n result = []\n for child in item.childList:\n field = child.nodeFormat().findField(self.name)\n if field:\n text = field.outputText(child, titleMode, internal)\n if text:\n result.append(text)\n return globalref.docRef.childFieldSep.join(result)","def handle_doc (collection, mode, doc) :\n\n name = doc['_id']\n\n if mode == 'list' :\n\n for key in doc :\n print \" | | | +-- %s\" % (key)\n\n elif mode == 'tree' :\n print \" | | +-- doc %s\" % (name)\n for key in doc :\n print \" | | | +-- %s\" % (key)\n\n elif mode == 'dump' :\n print \" | | +-- doc %s\" % (name)\n for key in doc :\n txt_in = pprint.pformat (doc[key])\n txt_out = \"\"\n lnum = 1\n for line in txt_in.split ('\\n') :\n if lnum != 1 :\n txt_out += ' | | | | '\n txt_out += line\n txt_out += '\\n'\n lnum += 1\n\n print \" | | | +-- %-10s : %s\" % (key, txt_out[:-1]) # remove last \\n","def parseInternalFieldContent(content):\n isBinary = isBinaryFormat(content)\n for ln, lc in enumerate(content):\n if lc.startswith(b'internalField'):\n if b'nonuniform' in lc:\n return parseDataNonuniform(content, ln, len(content), isBinary)\n elif b'uniform' in lc:\n return parseDataUniform(content[ln])\n break\n return None","def pull_fields(self, org):\n pass","def get(self, collection_id, parent_id, object_id,\n id_field=DEFAULT_ID_FIELD,\n modified_field=DEFAULT_MODIFIED_FIELD,\n auth=None):\n obj = Session.query(self.collection).get(object_id)\n # TODO: verify permissions\n if obj is None or obj.deleted:\n raise RecordNotFoundError()\n return obj.deserialize()","def retrieve(self, gl_rec, cache, fields=None, asdict=False):\n rv = []\n\n storage = self.storage\n gl_id, value = None, None\n gbl, piece = storage.split(';')\n sub_file = gl_rec[gbl]\n\n # Ignore the header for now.\n\n # Gets hit with nested subfiles.\n if fields == None:\n asdict = True\n fields = self.fields\n\n fieldnames = [f.label for f in fields]\n\n for (rowid, value) in sub_file.keys_with_decendants():\n if not valid_rowid(rowid):\n break\n row = []\n sub_file_row = sub_file[rowid]\n for field in fields:\n row.append(field.retrieve(sub_file_row, cache))\n if asdict:\n row = dict(zip(fieldnames, row))\n row['_rowid'] = rowid\n rv.append(row)\n\n return rv","def test_nested_query():\n schema = graphene.Schema(query=NestedQuery)\n response = schema.execute(\"{topLevel {name, leaf {value , leaflets {value} } } }\")\n assert to_dict(response.data) == {\n \"topLevel\": {\n \"name\": \"top level name\",\n \"leaf\": {\n \"value\": \"some leaf value\",\n \"leaflets\": [{\"value\": \"subleaf1\"}, {\"value\": \"subleaf2\"}],\n },\n }\n }","def test_field_resolution_multiple_inheritance_with_child_field_defined(self):\n child_field = ChildWithMultipleParentsAndTheSameField()._get_fields()[\"name\"]\n self.assertEqual(child_field.default, \"C\")","def _get_fields(self):\n return self._fields","def sefields(cls: Type[Any], serialize_class_var: bool = False) -> Iterator[SeField[Any]]:\n for f in fields(SeField, cls, serialize_class_var=serialize_class_var):\n f.parent = SeField(None, \"obj\") # type: ignore\n yield f","def fields_for_doc(doc, fields=None, exclude=None, widgets=None, formfield_callback=None):\n field_list = []\n ignored = []\n for name, field in doc._fields.items():\n if fields is not None and not name in fields:\n continue\n if exclude and name in exclude:\n continue\n if widgets and name in widgets:\n kwargs = {'widget': widgets[name]}\n else:\n kwargs = {}\n\n if formfield_callback is None:\n formfield = mongofield_to_formfield(field, **kwargs)\n if not formfield:\n raise TypeError((\"%s is an unsupported field types at the moment, you should put it in the exclude list\") % field)\n elif not callable(formfield_callback):\n raise TypeError('formfiled_callback must be a function or callable')\n else:\n formfield = formfield_callback(field, **kwargs)\n\n if formfield:\n field_list.append((name, formfield))\n else:\n ignored.append(name)\n field_dict = SortedDict(field_list)\n if fields:\n field_dict = SortedDict(\n [(f, field_dict.get(f)) for f in fields\n if ((not exclude) or (exclude and f not in exclude) and (f not in ignored))]\n )\n return field_dict","def test_document_form_has_right_fields(self):\n form = DocumentForm()\n self.assertEqual(len(form.fields.keys()), 2)\n self.assertIn('file', form.fields.keys())\n self.assertIn('doctype', form.fields.keys())","def fields(self, _only_called=False, **kwargs):\n\n # Check for an operator and transform to mongo-style if there is one\n operators = [\"slice\"]\n cleaned_fields = []\n for key, value in kwargs.items():\n parts = key.split(\"__\")\n if parts[0] in operators:\n op = parts.pop(0)\n value = {\"$\" + op: value}\n\n key = \".\".join(parts)\n try:\n field_name, value = self._check_valid_field_name_to_project(key, value)\n except ValueError as e:\n raise e\n\n cleaned_fields.append((field_name, value))\n\n # divide fields on groups by their values\n # (ONLY group, EXCLUDE group etc.) and add them to _loaded_fields\n # as an appropriate QueryFieldList\n fields = sorted(cleaned_fields, key=operator.itemgetter(1))\n for value, group in itertools.groupby(fields, lambda x: x[1]):\n fields = [field for field, value in group]\n self._loaded_fields += QueryFieldList(fields, value=value, _only_called=_only_called)\n\n return self","def _do_index_fields(self, doc, generator, obj, obj_weight):\n for field in self.fields + self.tags:\n # Trying to resolve field value or skip it\n # Отладочка:\n # print(field, field.resolve(obj))\n try:\n value = field.resolve(obj)\n if value is None:\n continue\n except AttributeError:\n continue\n if field.prefix:\n fvalue = field.convert(value)\n doc.add_value(field.number, fvalue)\n prefix = smart_text(field.get_tag())\n value = smart_text(value)\n generator.index_text_without_positions(value, field.weight*obj_weight, prefix)\n if prefix: # if prefixed then also index without prefix\n generator.index_text_without_positions(value, field.weight*obj_weight)","def getDocObjects(row, field):\n\n doc = nlp_larg(str(row[field]).lower())\n\n return doc","def find_field(field_id, typeform_survey):\n survey = typeform_survey\n fields = [ field for field in survey.get('fields') if field.get('id') == field_id ]\n field = None\n if len(fields) == 1:\n return fields[0]\n\n # check if field is part of a group?\n group_fields = [\n field.get('properties', {}).get('fields') for field in survey.get('fields') if field.get('type') == 'group'\n ]\n # group_fields = [ [field, field, field], [field, field]]\n # flatten list\n group_fields = [item for sublist in group_fields for item in sublist]\n fields = [ field for field in group_fields if field.get('id') == field_id ]\n if len(fields) == 1:\n return fields[0]\n return None","def fields(self):\r\n pass","def navigate_to_field(self, field):\n raise NotImplementedError()","def form_NestedStructures(request):\n schema = schemaish.Structure()\n schema.add( 'a', schemaish.String())\n schema.add( 'b', schemaish.String())\n\n sub_schema = schemaish.Structure()\n sub_schema.add('x',schemaish.String())\n\n schema.add('c', sub_schema)\n\n\n form = formish.Form(schema, 'form')\n\n return form","def test_get_changed_fields_query_count(self):\n\n class Person(Document):\n name = StringField()\n owns = ListField(ReferenceField(\"Organization\"))\n projects = ListField(ReferenceField(\"Project\"))\n\n class Organization(Document):\n name = StringField()\n owner = ReferenceField(Person)\n employees = ListField(ReferenceField(Person))\n\n class Project(Document):\n name = StringField()\n\n Person.drop_collection()\n Organization.drop_collection()\n Project.drop_collection()\n\n r1 = Project(name=\"r1\").save()\n r2 = Project(name=\"r2\").save()\n r3 = Project(name=\"r3\").save()\n p1 = Person(name=\"p1\", projects=[r1, r2]).save()\n p2 = Person(name=\"p2\", projects=[r2, r3]).save()\n o1 = Organization(name=\"o1\", employees=[p1]).save()\n\n with query_counter() as q:\n assert q == 0\n\n # Fetching a document should result in a query.\n org = Organization.objects.get(id=o1.id)\n assert q == 1\n\n # Checking changed fields of a newly fetched document should not\n # result in a query.\n org._get_changed_fields()\n assert q == 1\n\n # Saving a doc without changing any of its fields should not result\n # in a query (with or without cascade=False).\n org = Organization.objects.get(id=o1.id)\n with query_counter() as q:\n org.save()\n assert q == 0\n\n org = Organization.objects.get(id=o1.id)\n with query_counter() as q:\n org.save(cascade=False)\n assert q == 0\n\n # Saving a doc after you append a reference to it should result in\n # two db operations (a query for the reference and an update).\n # TODO dereferencing of p2 shouldn't be necessary.\n org = Organization.objects.get(id=o1.id)\n with query_counter() as q:\n org.employees.append(p2) # dereferences p2\n org.save() # saves the org\n assert q == 2"],"string":"[\n \"def subfield():\\n return Subfield()\",\n \"def _get_nested(nested_dict, field):\\n print(nested_dict, field)\\n keys = field.split('.')\\n current = nested_dict\\n for k in keys:\\n print('key', k, 'current', current)\\n # return None for nested fields without a value in this doc\\n if isinstance(current, list):\\n # this list could contain anything. skip objects not containing `k`.\\n return [x[k] for x in current if x.get(k) is not None]\\n if not k in current:\\n current = None\\n break\\n current = current[k]\\n return current\",\n \"def test_exec_js_field_sub(self):\\n\\n class Comment(EmbeddedDocument):\\n content = StringField(db_field=\\\"body\\\")\\n\\n class BlogPost(Document):\\n name = StringField(db_field=\\\"doc-name\\\")\\n comments = ListField(EmbeddedDocumentField(Comment), db_field=\\\"cmnts\\\")\\n\\n BlogPost.drop_collection()\\n\\n comments1 = [Comment(content=\\\"cool\\\"), Comment(content=\\\"yay\\\")]\\n post1 = BlogPost(name=\\\"post1\\\", comments=comments1)\\n post1.save()\\n\\n comments2 = [Comment(content=\\\"nice stuff\\\")]\\n post2 = BlogPost(name=\\\"post2\\\", comments=comments2)\\n post2.save()\\n\\n code = \\\"\\\"\\\"\\n function getComments() {\\n var comments = [];\\n db[collection].find(query).forEach(function(doc) {\\n var docComments = doc[~comments];\\n for (var i = 0; i < docComments.length; i++) {\\n comments.push({\\n 'document': doc[~name],\\n 'comment': doc[~comments][i][~comments.content]\\n });\\n }\\n });\\n return comments;\\n }\\n \\\"\\\"\\\"\\n\\n sub_code = BlogPost.objects._sub_js_fields(code)\\n code_chunks = ['doc[\\\"cmnts\\\"];', 'doc[\\\"doc-name\\\"],', 'doc[\\\"cmnts\\\"][i][\\\"body\\\"]']\\n for chunk in code_chunks:\\n assert chunk in sub_code\\n\\n results = BlogPost.objects.exec_js(code)\\n expected_results = [\\n {\\\"comment\\\": \\\"cool\\\", \\\"document\\\": \\\"post1\\\"},\\n {\\\"comment\\\": \\\"yay\\\", \\\"document\\\": \\\"post1\\\"},\\n {\\\"comment\\\": \\\"nice stuff\\\", \\\"document\\\": \\\"post2\\\"},\\n ]\\n assert results == expected_results\\n\\n # Test template style\\n code = \\\"{{~comments.content}}\\\"\\n sub_code = BlogPost.objects._sub_js_fields(code)\\n assert \\\"cmnts.body\\\" == sub_code\\n\\n BlogPost.drop_collection()\",\n \"def _nested_lookup(doc, field):\\n value = doc\\n keys = field.split(\\\".\\\")\\n try:\\n for k in keys:\\n value = value[k]\\n except KeyError:\\n return None\\n\\n return str(value)\",\n \"def test_get_field(test_client):\\n test_dict = {\\\"kfc\\\": {\\\"item\\\": \\\"chickens\\\"}}\\n assert test_client.get_field(\\\"kfc.item\\\", doc=test_dict) == \\\"chickens\\\"\",\n \"def _getFields(obj, tree=None, retval=None, fileobj=None):\\n fieldAttributes = {'/FT': 'Field Type', '/Parent': 'Parent', '/T': 'Field Name', '/TU': 'Alternate Field Name',\\n '/TM': 'Mapping Name', '/Ff': 'Field Flags', '/V': 'Value', '/DV': 'Default Value'}\\n if retval is None:\\n retval = OrderedDict()\\n catalog = obj.trailer[\\\"/Root\\\"]\\n # get the AcroForm tree\\n if \\\"/AcroForm\\\" in catalog:\\n tree = catalog[\\\"/AcroForm\\\"]\\n else:\\n return None\\n if tree is None:\\n return retval\\n\\n obj._checkKids(tree, retval, fileobj)\\n for attr in fieldAttributes:\\n if attr in tree:\\n # Tree is a field\\n obj._buildField(tree, retval, fileobj, fieldAttributes)\\n break\\n\\n if \\\"/Fields\\\" in tree:\\n fields = tree[\\\"/Fields\\\"]\\n for f in fields:\\n field = f.getObject()\\n obj._buildField(field, retval, fileobj, fieldAttributes)\\n\\n return retval\",\n \"def getUuidDocSubfield(coll, uuid, field, subField):\\n mongoColl = mongoConfigColls[coll]\\n query = { 'field' : field, 'apiviz_front_uuid' : uuid }\\n result = mongoColl.find_one(query)\\n log_app.debug(\\\"getUuidDocSubfield / result : %s\\\", result )\\n return result[subField]\",\n \"def nested_lookup(doc, field):\\n value = doc\\n keys = field.split(\\\".\\\")\\n try:\\n for k in keys:\\n if isinstance(value, (list, tuple)):\\n # assuming we have a list of dict with k as one of the keys\\n stype = set([type(e) for e in value])\\n if not stype:\\n return None\\n assert len(stype) == 1 and stype == {dict}, \\\"Expecting a list of dict, found types: %s\\\" % stype\\n value = [e[k] for e in value if e.get(k)]\\n # can't go further ?\\n return value\\n else:\\n value = value[k]\\n except KeyError:\\n return None\\n\\n return value\",\n \"def stored_fields(self, docnum):\\r\\n return self.doc_reader[docnum]\",\n \"def get_content_field(self):\\n for _, field in self.fields.items():\\n if field.document is True:\\n return field.index_fieldname\",\n \"def get_fields_in_model(instance):\\n assert isinstance(instance, Document)\\n return instance._fields\",\n \"def get_dict_value(field_name, doc):\\n\\n def get_array_value(doc, key):\\n \\\"\\\"\\\"\\n Takes a dictionary (doc) and a string (key) representing a dictionary\\n key and one or more array indexes, e.g. \\\"location[0][1]\\\". Returns the\\n corresponding value from the dictionary.\\n \\\"\\\"\\\"\\n # split key at the start of array values, e.g. 'loc[0]' -> ['loc', '0]']\\n key_parts = key.split('[')\\n\\n # get the name of the parent field, e.g. \\\"loc\\\"\\n key = key_parts.pop(0)\\n\\n # get the dictionary value, which is the first array\\n array = doc[key]\\n\\n while len(key_parts) > 0:\\n\\n index = key_parts.pop(0)\\n\\n # remove trailing bracket from index value\\n index = index.replace(']', '')\\n\\n # need to convert the string to an integer to use it as an index\\n index = int(index)\\n\\n value = array[index]\\n\\n # step into the next array\\n array = value\\n\\n return value\\n\\n if isinstance(field_name, str):\\n\\n doc_copy = deepcopy(doc)\\n\\n # parse the string into a list of keys\\n keys = field_name.split('.')\\n value = ''\\n\\n try:\\n while len(keys) > 0:\\n\\n if isinstance(doc_copy, dict):\\n\\n key = keys.pop(0)\\n\\n # remove any leading or trailing whitespaces\\n key.strip()\\n\\n # check if the key includes an array index (e.g., 'location[0]')\\n if '[' in key:\\n value = get_array_value(doc_copy, key)\\n else:\\n value = doc_copy[key]\\n\\n doc_copy = value\\n\\n else:\\n return doc_copy\\n\\n except KeyError:\\n # log this error so user knows to correct field_name\\n # LOGGER.warning('The field_name \\\"%s\\\" cannot be found in the document %s.',\\n # field_name, str(doc)[:160])\\n return None\\n\\n return value\",\n \"def field(self):\\n return self.__field\",\n \"def field(self):\\n return self.reference.field\",\n \"def get_fields(self):\\n for child in self.children:\\n if isinstance(child, MyTextField):\\n yield child\",\n \"def namespaced_fields(self):\\n ...\",\n \"def getSubfield(h, field, Lsubs):\\n\\td = {}\\t\\n\\tfor k in Lsubs:\\n\\t\\ttheElement = h.documentElement.getElementsByTagName(field)[0]\\n\\t\\td[k] = str(theElement.getAttribute(k))\\n\\treturn d\",\n \"def fields(self):\\n ...\",\n \"def test_map_field_recursive_case(self):\\n field = 'content.title'\\n mapping = {\\n 'type': 'text',\\n 'index': True\\n }\\n\\n actual = mapper._map_field(mapping, field)\\n expected = {\\n 'properties': {\\n 'content': {\\n 'properties': {\\n 'title': {\\n 'type': 'text',\\n 'index': True\\n }\\n }\\n }\\n }\\n }\\n self.assertEqual(actual, expected)\",\n \"def field(self, field):\\n return self.__getitem__(field)\",\n \"def fields(self):\",\n \"def _filter_doc_fields(cls, tag, user, document):\\n query = {\\n 'query': {\\n 'bool': {\\n 'must': [\\n {\\n \\\"term\\\": {\\n \\\"doc_type__v1\\\": cls.document_type\\n }\\n },\\n {\\n \\\"term\\\": {\\n \\\"is_active__v1\\\": True\\n }\\n }\\n ]\\n }\\n }\\n }\\n if tag:\\n query['query']['bool']['must'].append(\\n {\\n 'term': {\\n \\\"tag__v1\\\": tag\\n }\\n }\\n )\\n if user:\\n query['query']['bool']['should'] = [\\n {\\n 'nested': {\\n 'path': 'permissions__v1.users__v1',\\n 'filter': {\\n {\\n 'term': {\\n 'permissions__v1.users__v1.id': user['id']\\n }\\n }\\n }\\n }\\n },\\n {\\n 'nested': {\\n 'path': 'permissions__v1.groups__v1',\\n 'filter': {\\n {\\n 'term': {\\n 'permissions__v1.groups__v1.id': u' OR '.join(user['groups'])\\n }\\n }\\n }\\n }\\n },\\n {\\n 'term': {\\n 'tag.public': True\\n }\\n }\\n ]\\n es_response_raw = get_es_response(\\n req_session.get(get_path_search('field-version'),\\n data=json.dumps(query)))\\n es_response = es_response_raw.json()\\n db_fields = map(lambda x: x['field__v1'], es_response['hits']['hits'])\\n document_new = {}\\n for key in document:\\n if key in db_fields:\\n document_new[key] = document[key]\\n return document_new\",\n \"def test_nested():\\n # pylint: disable=no-member\\n assert issubclass(NestedSchema, graphene.ObjectType)\\n assert isinstance(NestedSchema.name, graphene.String)\\n assert isinstance(NestedSchema.leaf, graphene.Field)\\n assert str(NestedSchema.leaf.type) == \\\"Leaf\\\"\\n assert isinstance(NestedSchema.leaf.type.value, graphene.String)\\n assert isinstance(NestedSchema.leaf.type.leaflets, graphene.List)\",\n \"def _get_child_fields(self, cr, uid, ids, context=None):\\n res = self.search(cr, uid, [('parent_id','child_of',ids)], context=context)\\n return res\",\n \"def get_field(self, field_name):\\n all_fields = self._fields.items(self._fields.root)\\n print(\\\"all_fields\\\", all_fields)\\n for name, field in all_fields:\\n print(name, field_name)\\n if name == field_name:\\n return field\",\n \"def getdocfield(fieldname):\\t\\t\\n\\tl = [d for d in doctype_dl if d.doctype=='DocField' and d.fieldname==fieldname]\\n\\treturn l and l[0] or None\",\n \"def __get__(self, instance, owner):\\n if instance is None:\\n # Document class being used rather than a document object\\n return self\\n\\n ReferenceField = _import_class(\\\"ReferenceField\\\")\\n GenericReferenceField = _import_class(\\\"GenericReferenceField\\\")\\n EmbeddedDocumentListField = _import_class(\\\"EmbeddedDocumentListField\\\")\\n\\n auto_dereference = instance._fields[self.name]._auto_dereference\\n\\n dereference = auto_dereference and (\\n self.field is None\\n or isinstance(self.field, (GenericReferenceField, ReferenceField))\\n )\\n\\n if (\\n instance._initialised\\n and dereference\\n and instance._data.get(self.name)\\n and not getattr(instance._data[self.name], \\\"_dereferenced\\\", False)\\n ):\\n ref_values = instance._data.get(self.name)\\n instance._data[self.name] = self._lazy_load_refs(\\n ref_values=ref_values, instance=instance, name=self.name, max_depth=1\\n )\\n if hasattr(instance._data[self.name], \\\"_dereferenced\\\"):\\n instance._data[self.name]._dereferenced = True\\n\\n value = super().__get__(instance, owner)\\n\\n # Convert lists / values so we can watch for any changes on them\\n if isinstance(value, (list, tuple)):\\n if issubclass(type(self), EmbeddedDocumentListField) and not isinstance(\\n value, EmbeddedDocumentList\\n ):\\n value = EmbeddedDocumentList(value, instance, self.name)\\n elif not isinstance(value, BaseList):\\n value = BaseList(value, instance, self.name)\\n instance._data[self.name] = value\\n elif isinstance(value, dict) and not isinstance(value, BaseDict):\\n value = BaseDict(value, instance, self.name)\\n instance._data[self.name] = value\\n\\n if (\\n auto_dereference\\n and instance._initialised\\n and isinstance(value, (BaseList, BaseDict))\\n and not value._dereferenced\\n ):\\n value = self._lazy_load_refs(\\n ref_values=value, instance=instance, name=self.name, max_depth=1\\n )\\n value._dereferenced = True\\n instance._data[self.name] = value\\n\\n return value\",\n \"def db_fields(self):\",\n \"def subfieldFactory(name):\\n from pythia.pyre.inventory import facility\\n return facility(name, family=\\\"subfield\\\", factory=Subfield)\",\n \"def GetSubfieldDef(fielddef):\\n\\n format_, addrdef, datadef, arraydef, validate, cmd, converter = GetFieldDef(fielddef, fields='format_, addrdef, datadef, arraydef, validate, cmd, converter')\\n\\n # create new arraydef\\n if len(arraydef) > 1:\\n arraydef = arraydef[1:]\\n else:\\n arraydef = None\\n\\n # create new datadef\\n if isinstance(datadef, tuple):\\n if cmd is not None:\\n datadef = (arraydef, validate, cmd)\\n else:\\n datadef = (arraydef, validate)\\n else:\\n datadef = arraydef\\n\\n # set new field def\\n subfielddef = None\\n if converter is not None:\\n subfielddef = (format_, addrdef, datadef, converter)\\n else:\\n subfielddef = (format_, addrdef, datadef)\\n\\n return subfielddef\",\n \"def get_fields():\\n return jsonify(result=Tree.fields())\",\n \"def Fields(self):\\n return self._fields\",\n \"def stored_fields(self, docnum):\\n\\t\\treturn self.index.collection.get(docnum).keys()\",\n \"def get_fields(node):\\r\\n return dict(iter_fields(node))\",\n \"def extract_doc(self, doc):\\n if doc.pod_path.endswith('.yaml'):\\n raw_data = yaml.load(\\n doc.pod.read_file(doc.pod_path), Loader=yaml_utils.PlainTextYamlLoader)\\n else:\\n raw_data = doc.format.front_matter.raw_data\\n\\n if not raw_data:\\n print('No raw data found for document: {}'.format(doc.pod_path))\\n return\\n\\n data = collections.OrderedDict()\\n\\n tagged_keys = tuple(['{}@'.format(key)\\n for key in COLLECTION_META_KEYS])\\n\\n for key, value in raw_data.items():\\n if key in COLLECTION_META_KEYS or key.startswith(tagged_keys):\\n normal_key = key.lstrip('$')\\n if 'path' in key:\\n # Use `__NONE` as sentinel to support equating a `value` of None.\\n collection_path = self.blueprint.get(\\n key, self.blueprint.get(normal_key, '__NONE'))\\n # Skip the paths that are the same as the collection.\\n if collection_path == value:\\n continue\\n data[normal_key] = value\\n\\n if data:\\n self.paths[doc.collection_sub_path[1:]] = data\",\n \"def iter_child_nodes(node):\\r\\n for name, field in iter_fields(node):\\r\\n if isinstance(field, AST):\\r\\n yield field\\r\\n elif isinstance(field, list):\\r\\n for item in field:\\r\\n if isinstance(item, AST):\\r\\n yield item\",\n \"def __call__(self, collection, field):\\n pass\",\n \"def get_as_subtext_field(field, field_title=None) -> str:\\n s = \\\"\\\"\\n if field:\\n s = f\\\"{field} | \\\"\\n else:\\n return \\\"\\\"\\n\\n if field_title:\\n s = f\\\"{field_title}: \\\" + s\\n\\n return s\",\n \"def get_as_subtext_field(field, field_title=None) -> str:\\n s = \\\"\\\"\\n if field:\\n s = f\\\"{field} | \\\"\\n else:\\n return \\\"\\\"\\n\\n if field_title:\\n s = f\\\"{field_title}: \\\" + s\\n\\n return s\",\n \"def get_field(self, field):\\r\\n if field not in self.fields:\\r\\n raise ValueError(\\\"Invalid field: {}. Must be one of: {}\\\"\\r\\n .format(field, self.fields))\\r\\n sub = set(meta[field] for meta in self.data)\\r\\n return sub\",\n \"def field(self):\\n return self.__field\",\n \"def get_field(self):\\n return self\",\n \"def mask_custom_field(self, custom_field, doc_type):\\n\\t\\tcustom_field.fields.update({\\n\\t\\t\\t'doctype': 'DocField',\\n\\t\\t\\t'parent': doc_type,\\n\\t\\t\\t'parentfield': 'fields',\\n\\t\\t\\t'parenttype': 'DocType',\\n\\t\\t})\",\n \"def process(node, model, editable, get=get_name):\\n if node.tag in VIEW_TYPES:\\n # determine whether this view is editable\\n editable = editable and _view_is_editable(node)\\n elif node.tag in ('field', 'groupby'):\\n # determine whether the field is editable\\n field = model._fields.get(node.get('name'))\\n if field:\\n editable = editable and field_is_editable(field, node)\\n\\n for key, val in node.items():\\n if not val:\\n continue\\n if key in ATTRS_WITH_FIELD_NAMES:\\n process_expr(val, get, key, val)\\n elif key == 'attrs':\\n process_attrs(val, get, key, val)\\n\\n if node.tag in ('field', 'groupby') and field and field.relational:\\n if editable and not node.get('domain'):\\n domain = field._description_domain(env)\\n # process the field's domain as if it was in the view\\n if isinstance(domain, str):\\n process_expr(domain, get, 'domain', domain)\\n # retrieve subfields of 'parent'\\n model = env[field.comodel_name]\\n get = partial(get_subname, get)\\n\\n for child in node:\\n if node.tag == 'search' and child.tag == 'searchpanel':\\n # searchpanel part has to be validated independently\\n continue\\n process(child, model, editable, get)\",\n \"def get_fields(self):\\n for field in self.fields_box.children:\\n if isinstance(field, MyTextField):\\n yield field\",\n \"def objectFields(self):\\n raise NotImplementedError\",\n \"def field(self):\\n return self._field\",\n \"def field(self):\\n return self._field\",\n \"def field(self):\\n return self._field\",\n \"def field(self):\\n return self._field\",\n \"def get_as_subtext_field(field, field_title=None) -> str:\\n s = \\\"\\\"\\n if field:\\n s = f\\\"{field} | \\\"\\n else:\\n return \\\"\\\"\\n\\n if field_title:\\n s = f\\\"{field_title} :\\\" + s\\n\\n return s\",\n \"def test_query_generic_embedded_document(self):\\n\\n class A(EmbeddedDocument):\\n a_name = StringField()\\n\\n class B(EmbeddedDocument):\\n b_name = StringField()\\n\\n class Doc(Document):\\n document = GenericEmbeddedDocumentField(choices=(A, B))\\n\\n Doc.drop_collection()\\n Doc(document=A(a_name=\\\"A doc\\\")).save()\\n Doc(document=B(b_name=\\\"B doc\\\")).save()\\n\\n # Using raw in filter working fine\\n assert Doc.objects(__raw__={\\\"document.a_name\\\": \\\"A doc\\\"}).count() == 1\\n assert Doc.objects(__raw__={\\\"document.b_name\\\": \\\"B doc\\\"}).count() == 1\\n assert Doc.objects(document__a_name=\\\"A doc\\\").count() == 1\\n assert Doc.objects(document__b_name=\\\"B doc\\\").count() == 1\",\n \"def subdocument(db_type):\\n if db_type != \\\"ephemeraldb\\\":\\n pytest.skip(\\\"ephemeraldb test only\\\")\\n yield EphemeralDocument(\\n {\\\"_id\\\": 1, \\\"hello\\\": \\\"there\\\", \\\"mighty\\\": \\\"duck\\\", \\\"and\\\": {\\\"the\\\": \\\"drake\\\"}}\\n )\",\n \"def test_entities__Entity__getRawField__3(entity_with_field, field):\\n assert field == entity_with_field.getRawField(field.__name__)\",\n \"def test_reference_field_find(self):\\n\\n class BlogPost(Document):\\n content = StringField()\\n author = ReferenceField(self.Person)\\n\\n BlogPost.drop_collection()\\n self.Person.drop_collection()\\n\\n me = self.Person(name=\\\"Test User\\\").save()\\n BlogPost(content=\\\"test 123\\\", author=me).save()\\n\\n assert 1 == BlogPost.objects(author=me).count()\\n assert 1 == BlogPost.objects(author=me.pk).count()\\n assert 1 == BlogPost.objects(author=\\\"%s\\\" % me.pk).count()\\n\\n assert 1 == BlogPost.objects(author__in=[me]).count()\\n assert 1 == BlogPost.objects(author__in=[me.pk]).count()\\n assert 1 == BlogPost.objects(author__in=[\\\"%s\\\" % me.pk]).count()\",\n \"def iter_fields(node):\\r\\n for field in getattr(node, '_fields', ()) or ():\\r\\n try:\\r\\n yield field, getattr(node, field)\\r\\n except AttributeError:\\r\\n pass\",\n \"def get_field(self, bib_entry, field):\\n output = bib_entry.fields[field] if field in bib_entry.fields else \\\"\\\"\\n return self.strip_braces(output)\",\n \"def getFieldValue(self, field, no_html=False, external_id=True, depth=1, optimize=False):\\n if field[\\\"type\\\"] == \\\"category\\\":\\n if field[\\\"config\\\"][\\\"settings\\\"][\\\"multiple\\\"]:\\n values = []\\n for category in field[\\\"values\\\"]:\\n values.append(category[\\\"value\\\"][\\\"text\\\"])\\n return values\\n else:\\n return field[\\\"values\\\"][0][\\\"value\\\"][\\\"text\\\"]\\n elif field[\\\"type\\\"] == \\\"image\\\":\\n values = []\\n for image in field['values']:\\n values.append([image[\\\"value\\\"][\\\"mimetype\\\"], image[\\\"value\\\"][\\\"file_id\\\"]])\\n return values\\n elif field[\\\"type\\\"] == \\\"date\\\":\\n return field[\\\"values\\\"][0]\\n elif field[\\\"type\\\"] == \\\"app\\\":\\n itemID = field[\\\"values\\\"][0][\\\"value\\\"][\\\"item_id\\\"]\\n appID = field[\\\"values\\\"][0][\\\"value\\\"][\\\"app\\\"][\\\"app_id\\\"]\\n if depth<=0:\\n return itemID\\n else:\\n if optimize:#Si es necesario optimizar la carga del item\\n try: #Intenta buscar la lista de items como un atributo en self\\n items = getattr(self, str(appID))\\n except AttributeError:\\n #Como no los encontró, crea una nueva PodioAPI con la appID de destino y le pide los items\\n if self.client:\\n nested_api = self\\n else:\\n try:\\n nested_api = self.__class__(appID)\\n except: #TODO: Especificar la excepcion que es de tipo \\\"DoesNotExist\\\"\\n raise Exception(\\\"Hubo un error creando el nuevo objeto 'PodioApi' para el item relacionado con app_id %s. Por favor agregar el app_id y el app_token de esa aplicacion a la base de datos\\\" % appID)\\n items = nested_api.get_filtered_items(None, depth=depth-1)\\n #Luego crea el atributo para que esta llamada no se repita\\n setattr(self, str(appID), items)\\n #Ya teniendo a todos los items, busca entre la lista aquel cuya ID es igual al item ID de la referencia, y lo pone como valor del campo.\\n item = None\\n for i in items:\\n if i[\\\"item\\\"] == int(itemID):\\n item = i\\n\\n else:\\n data = self._client.Item.find(int(itemID))\\n if not external_id:\\n item = self.make_dict(data, external_id=external_id, depth=depth-1)\\n else:\\n item = self.makeDict(data, nested=True)\\n return item\\n elif field[\\\"type\\\"] == \\\"text\\\":\\n text = field[\\\"values\\\"][0][\\\"value\\\"]\\n if no_html and field[\\\"config\\\"][\\\"settings\\\"][\\\"format\\\"] == 'html':\\n print (text.encode('utf-8'))\\n html_text = BeautifulSoup(text, \\\"html5lib\\\")\\n for p_tag in html_text.find_all('p'):\\n p_tag.unwrap()\\n for br_tag in html_text.find_all('br'):\\n br_tag.name=\\\"text:line-break\\\"\\n html_text.find('html').unwrap()\\n html_text.find('head').unwrap()\\n html_text.find('body').unwrap()\\n text = unicode(html_text)\\n #text = strip_tags(text)\\n return text\\n elif field[\\\"type\\\"] == \\\"embed\\\":\\n return field[\\\"values\\\"][0][\\\"embed\\\"][\\\"url\\\"]\\n else:\\n #print field[\\\"type\\\"]\\n return field[\\\"values\\\"][0][\\\"value\\\"]\",\n \"def on_get_field(self, ins, const, obj):\\n pass\",\n \"def find_all(self, field):\\n result = []\\n for c in self.children:\\n if c.name == field:\\n result.append(c)\\n result += c.find_all(field)\\n return result\",\n \"def field(self):\\n return None\",\n \"def getSubDataField(self, name, indices): \\n if (indices >= self.__numExamples).any() or (indices < 0).any(): \\n raise ValueError(\\\"Invalid example indices\\\")\\n \\n if name not in self.__examples: \\n raise ValueError(\\\"Field does not exist: \\\" + name)\\n\\n\\n return self.__examples[name][ix_(indices)]\",\n \"def fieldOfView(self):\\n return self._fieldOfView\",\n \"def base_field(self):\\n return self.field[1]\",\n \"def test_get_document_with_fields(index_with_documents):\\n response = index_with_documents().get_document(\\\"500682\\\", {\\\"fields\\\": [\\\"id\\\", \\\"title\\\"]})\\n assert isinstance(response, Document)\\n assert hasattr(response, \\\"title\\\")\\n assert not hasattr(response, \\\"poster\\\")\\n # assert 'poster' not in response\\n assert response.title == \\\"The Highwaymen\\\"\",\n \"def get_field(key, obj):\\n\\n val = obj\\n\\n for subkey in key.split('.'):\\n val = val[subkey]\\n\\n return val\",\n \"def _get_fields_from_root(self, cr, uid, ids, context=None):\\n res = self.pool.get('xml.export.field').search(cr, uid, [('export_id','in',ids)], context=context)\\n return res\",\n \"def get_fields(self):\\n fields = super().get_fields()\\n fields['children'] = ForumListSerializer(read_only=True, many=True)\\n return fields\",\n \"def field(self):\\r\\n return self.value\",\n \"def get_fields(self):\\r\\n return self.fields\",\n \"def getChildren(tree, node, Dict):\\r\\n if node.children:\\r\\n for child in node.children:\\r\\n tree.dictDepth = tree.dictDepth+\\\"$$\\\"+child.name\\r\\n dictString = \\\"Dict[tree.root.name]\\\"\\r\\n for each in [e for e in tree.dictDepth.split(\\\"$$\\\") if not e == \\\"\\\"]:\\r\\n dictString+=\\\"['{}']\\\".format(each)\\r\\n exec(dictString+\\\"={'__files__':\\\"+str(child.files)+\\\"}\\\")\\r\\n \\r\\n if child.children:\\r\\n tree.getChildren(child, Dict)\\r\\n else:\\r\\n A, B = tree.dictDepth.rsplit(\\\"$$\\\"+child.name,1)\\r\\n tree.dictDepth = A+B\\r\\n try:\\r\\n A, B = tree.dictDepth.rsplit(\\\"$$\\\"+node.name,1)\\r\\n tree.dictDepth = A+B\\r\\n except:\\r\\n pass\\r\\n return Dict\",\n \"def dump_record(record):\\n rec = E.record()\\n\\n leader = record.get('leader')\\n if leader:\\n rec.append(E.leader(leader))\\n\\n if isinstance(record, GroupableOrderedDict):\\n items = record.iteritems(with_order=False, repeated=True)\\n else:\\n items = iteritems(record)\\n\\n for df, subfields in items:\\n # Control fields\\n if len(df) == 3:\\n if isinstance(subfields, string_types):\\n controlfield = E.controlfield(subfields)\\n controlfield.attrib['tag'] = df[0:3]\\n rec.append(controlfield)\\n elif isinstance(subfields, (list, tuple, set)):\\n for subfield in subfields:\\n controlfield = E.controlfield(subfield)\\n controlfield.attrib['tag'] = df[0:3]\\n rec.append(controlfield)\\n else:\\n # Skip leader.\\n if df == 'leader':\\n continue\\n\\n if not isinstance(subfields, (list, tuple, set)):\\n subfields = (subfields,)\\n\\n df = df.replace('_', ' ')\\n for subfield in subfields:\\n if not isinstance(subfield, (list, tuple, set)):\\n subfield = [subfield]\\n\\n for s in subfield:\\n datafield = E.datafield()\\n datafield.attrib['tag'] = df[0:3]\\n datafield.attrib['ind1'] = df[3]\\n datafield.attrib['ind2'] = df[4]\\n\\n if isinstance(s, GroupableOrderedDict):\\n items = s.iteritems(with_order=False, repeated=True)\\n elif isinstance(s, dict):\\n items = iteritems(s)\\n else:\\n datafield.append(E.subfield(s))\\n\\n items = tuple()\\n\\n for code, value in items:\\n if not isinstance(value, string_types):\\n for v in value:\\n datafield.append(E.subfield(v, code=code))\\n else:\\n datafield.append(E.subfield(value, code=code))\\n\\n rec.append(datafield)\\n return rec\",\n \"def check_attachment_fields(self):\\n for field_name, field in self.fields.items():\\n if isinstance(field, serializers.ListSerializer):\\n if hasattr(field.child, \\\"field\\\"):\\n for child_name, child in field.child.field.items():\\n self.handle_attachment_field(child, child_name)\\n else:\\n self.handle_attachment_field(field, field_name)\",\n \"def get_field(self, field):\\n return self.extra_fields[field]\",\n \"def get_field_attr(name):\\n # de variant met een repeating group (entiteit, dataitem) levert hier nog een probleem op.\\n # is dat omdat er twee entiteiten in 1 scherm staan?\\n fields = []\\n opts = my.rectypes[name]._meta\\n for x in opts.get_fields(): # fields:\\n fldname = x.name\\n fldtype = x.get_internal_type()\\n if fldname == 'id' or fldtype in ('ForeignKey', 'ManyToManyField'):\\n # if fldname == 'id' or any((x.many2one, x.many2many, x.one2many))\\n continue\\n try:\\n length = x.max_length\\n except AttributeError:\\n length = -1\\n fields.append((fldname, fldtype[:-5], length))\\n return fields\",\n \"def test_field_resolution_single_inheritance_with_child_field_defined(self):\\n child_field = ChildWithTheSameField()._get_fields()[\\\"name\\\"]\\n self.assertEqual(child_field.default, \\\"C\\\")\",\n \"def _handle_gfk_field_node(self, node, field):\\n if node.getElementsByTagName('None'):\\n return None\\n ct_key = node.getAttribute(\\\"d:to\\\").split(NATURAL_KEY_JOINER)\\n ctype = ContentType.objects.get_by_natural_key(*ct_key)\\n Model = ctype.model_class()\\n if hasattr(Model._default_manager, 'get_by_natural_key'):\\n value = getInnerText(node).strip()\\n field_value = value.split(NATURAL_KEY_JOINER)\\n obj = Model._default_manager.db_manager(self.db).get_by_natural_key(*field_value)\\n return obj\\n else:\\n field_value = getInnerText(node).strip()\\n return Model._default_manager.db_manager(self.db).get(pk=Model._meta.pk.to_python(field_value))\",\n \"def find(self, _id):\\n _id = ObjectId(_id)\\n model = self.mongo.db.userfield.find_one({\\\"fields._id\\\":_id})\\n for field in model['fields']:\\n if field['_id']==_id:\\n return field\",\n \"def __getattribute__(self, attr_k):\\n # Getting the value of the field\\n attr = object.__getattribute__(self, attr_k)\\n attr_type = type(attr)\\n if issubclass(attr_type, Field) or \\\\\\n issubclass(attr_type, ReferenceManyField):\\n return attr.value\\n else:\\n return attr\",\n \"def parseInternalField(fn):\\n content = getFileContent(fn)\\n if content is not None:\\n return parseInternalFieldContent(content)\\n else:\\n return None\",\n \"def only(self, *fields):\\n for field in fields:\\n path = \\\".\\\".join(self.document._meta.resolve_subfield_hierarchy(field.split(\\\".\\\")))\\n self._only_fields.add(path)\\n if self.query._Cursor__fields is None:\\n # Identifier and version fields must always be included\\n self.query._Cursor__fields = { \\\"_id\\\" : 1, \\\"_version\\\" : 1 }\\n\\n self.query._Cursor__fields.update({ path : 1 })\\n\\n return self\",\n \"def outputText(self, item, titleMode, internal=False):\\n result = []\\n for child in item.childList:\\n field = child.nodeFormat().findField(self.name)\\n if field:\\n text = field.outputText(child, titleMode, internal)\\n if text:\\n result.append(text)\\n return globalref.docRef.childFieldSep.join(result)\",\n \"def handle_doc (collection, mode, doc) :\\n\\n name = doc['_id']\\n\\n if mode == 'list' :\\n\\n for key in doc :\\n print \\\" | | | +-- %s\\\" % (key)\\n\\n elif mode == 'tree' :\\n print \\\" | | +-- doc %s\\\" % (name)\\n for key in doc :\\n print \\\" | | | +-- %s\\\" % (key)\\n\\n elif mode == 'dump' :\\n print \\\" | | +-- doc %s\\\" % (name)\\n for key in doc :\\n txt_in = pprint.pformat (doc[key])\\n txt_out = \\\"\\\"\\n lnum = 1\\n for line in txt_in.split ('\\\\n') :\\n if lnum != 1 :\\n txt_out += ' | | | | '\\n txt_out += line\\n txt_out += '\\\\n'\\n lnum += 1\\n\\n print \\\" | | | +-- %-10s : %s\\\" % (key, txt_out[:-1]) # remove last \\\\n\",\n \"def parseInternalFieldContent(content):\\n isBinary = isBinaryFormat(content)\\n for ln, lc in enumerate(content):\\n if lc.startswith(b'internalField'):\\n if b'nonuniform' in lc:\\n return parseDataNonuniform(content, ln, len(content), isBinary)\\n elif b'uniform' in lc:\\n return parseDataUniform(content[ln])\\n break\\n return None\",\n \"def pull_fields(self, org):\\n pass\",\n \"def get(self, collection_id, parent_id, object_id,\\n id_field=DEFAULT_ID_FIELD,\\n modified_field=DEFAULT_MODIFIED_FIELD,\\n auth=None):\\n obj = Session.query(self.collection).get(object_id)\\n # TODO: verify permissions\\n if obj is None or obj.deleted:\\n raise RecordNotFoundError()\\n return obj.deserialize()\",\n \"def retrieve(self, gl_rec, cache, fields=None, asdict=False):\\n rv = []\\n\\n storage = self.storage\\n gl_id, value = None, None\\n gbl, piece = storage.split(';')\\n sub_file = gl_rec[gbl]\\n\\n # Ignore the header for now.\\n\\n # Gets hit with nested subfiles.\\n if fields == None:\\n asdict = True\\n fields = self.fields\\n\\n fieldnames = [f.label for f in fields]\\n\\n for (rowid, value) in sub_file.keys_with_decendants():\\n if not valid_rowid(rowid):\\n break\\n row = []\\n sub_file_row = sub_file[rowid]\\n for field in fields:\\n row.append(field.retrieve(sub_file_row, cache))\\n if asdict:\\n row = dict(zip(fieldnames, row))\\n row['_rowid'] = rowid\\n rv.append(row)\\n\\n return rv\",\n \"def test_nested_query():\\n schema = graphene.Schema(query=NestedQuery)\\n response = schema.execute(\\\"{topLevel {name, leaf {value , leaflets {value} } } }\\\")\\n assert to_dict(response.data) == {\\n \\\"topLevel\\\": {\\n \\\"name\\\": \\\"top level name\\\",\\n \\\"leaf\\\": {\\n \\\"value\\\": \\\"some leaf value\\\",\\n \\\"leaflets\\\": [{\\\"value\\\": \\\"subleaf1\\\"}, {\\\"value\\\": \\\"subleaf2\\\"}],\\n },\\n }\\n }\",\n \"def test_field_resolution_multiple_inheritance_with_child_field_defined(self):\\n child_field = ChildWithMultipleParentsAndTheSameField()._get_fields()[\\\"name\\\"]\\n self.assertEqual(child_field.default, \\\"C\\\")\",\n \"def _get_fields(self):\\n return self._fields\",\n \"def sefields(cls: Type[Any], serialize_class_var: bool = False) -> Iterator[SeField[Any]]:\\n for f in fields(SeField, cls, serialize_class_var=serialize_class_var):\\n f.parent = SeField(None, \\\"obj\\\") # type: ignore\\n yield f\",\n \"def fields_for_doc(doc, fields=None, exclude=None, widgets=None, formfield_callback=None):\\n field_list = []\\n ignored = []\\n for name, field in doc._fields.items():\\n if fields is not None and not name in fields:\\n continue\\n if exclude and name in exclude:\\n continue\\n if widgets and name in widgets:\\n kwargs = {'widget': widgets[name]}\\n else:\\n kwargs = {}\\n\\n if formfield_callback is None:\\n formfield = mongofield_to_formfield(field, **kwargs)\\n if not formfield:\\n raise TypeError((\\\"%s is an unsupported field types at the moment, you should put it in the exclude list\\\") % field)\\n elif not callable(formfield_callback):\\n raise TypeError('formfiled_callback must be a function or callable')\\n else:\\n formfield = formfield_callback(field, **kwargs)\\n\\n if formfield:\\n field_list.append((name, formfield))\\n else:\\n ignored.append(name)\\n field_dict = SortedDict(field_list)\\n if fields:\\n field_dict = SortedDict(\\n [(f, field_dict.get(f)) for f in fields\\n if ((not exclude) or (exclude and f not in exclude) and (f not in ignored))]\\n )\\n return field_dict\",\n \"def test_document_form_has_right_fields(self):\\n form = DocumentForm()\\n self.assertEqual(len(form.fields.keys()), 2)\\n self.assertIn('file', form.fields.keys())\\n self.assertIn('doctype', form.fields.keys())\",\n \"def fields(self, _only_called=False, **kwargs):\\n\\n # Check for an operator and transform to mongo-style if there is one\\n operators = [\\\"slice\\\"]\\n cleaned_fields = []\\n for key, value in kwargs.items():\\n parts = key.split(\\\"__\\\")\\n if parts[0] in operators:\\n op = parts.pop(0)\\n value = {\\\"$\\\" + op: value}\\n\\n key = \\\".\\\".join(parts)\\n try:\\n field_name, value = self._check_valid_field_name_to_project(key, value)\\n except ValueError as e:\\n raise e\\n\\n cleaned_fields.append((field_name, value))\\n\\n # divide fields on groups by their values\\n # (ONLY group, EXCLUDE group etc.) and add them to _loaded_fields\\n # as an appropriate QueryFieldList\\n fields = sorted(cleaned_fields, key=operator.itemgetter(1))\\n for value, group in itertools.groupby(fields, lambda x: x[1]):\\n fields = [field for field, value in group]\\n self._loaded_fields += QueryFieldList(fields, value=value, _only_called=_only_called)\\n\\n return self\",\n \"def _do_index_fields(self, doc, generator, obj, obj_weight):\\n for field in self.fields + self.tags:\\n # Trying to resolve field value or skip it\\n # Отладочка:\\n # print(field, field.resolve(obj))\\n try:\\n value = field.resolve(obj)\\n if value is None:\\n continue\\n except AttributeError:\\n continue\\n if field.prefix:\\n fvalue = field.convert(value)\\n doc.add_value(field.number, fvalue)\\n prefix = smart_text(field.get_tag())\\n value = smart_text(value)\\n generator.index_text_without_positions(value, field.weight*obj_weight, prefix)\\n if prefix: # if prefixed then also index without prefix\\n generator.index_text_without_positions(value, field.weight*obj_weight)\",\n \"def getDocObjects(row, field):\\n\\n doc = nlp_larg(str(row[field]).lower())\\n\\n return doc\",\n \"def find_field(field_id, typeform_survey):\\n survey = typeform_survey\\n fields = [ field for field in survey.get('fields') if field.get('id') == field_id ]\\n field = None\\n if len(fields) == 1:\\n return fields[0]\\n\\n # check if field is part of a group?\\n group_fields = [\\n field.get('properties', {}).get('fields') for field in survey.get('fields') if field.get('type') == 'group'\\n ]\\n # group_fields = [ [field, field, field], [field, field]]\\n # flatten list\\n group_fields = [item for sublist in group_fields for item in sublist]\\n fields = [ field for field in group_fields if field.get('id') == field_id ]\\n if len(fields) == 1:\\n return fields[0]\\n return None\",\n \"def fields(self):\\r\\n pass\",\n \"def navigate_to_field(self, field):\\n raise NotImplementedError()\",\n \"def form_NestedStructures(request):\\n schema = schemaish.Structure()\\n schema.add( 'a', schemaish.String())\\n schema.add( 'b', schemaish.String())\\n\\n sub_schema = schemaish.Structure()\\n sub_schema.add('x',schemaish.String())\\n\\n schema.add('c', sub_schema)\\n\\n\\n form = formish.Form(schema, 'form')\\n\\n return form\",\n \"def test_get_changed_fields_query_count(self):\\n\\n class Person(Document):\\n name = StringField()\\n owns = ListField(ReferenceField(\\\"Organization\\\"))\\n projects = ListField(ReferenceField(\\\"Project\\\"))\\n\\n class Organization(Document):\\n name = StringField()\\n owner = ReferenceField(Person)\\n employees = ListField(ReferenceField(Person))\\n\\n class Project(Document):\\n name = StringField()\\n\\n Person.drop_collection()\\n Organization.drop_collection()\\n Project.drop_collection()\\n\\n r1 = Project(name=\\\"r1\\\").save()\\n r2 = Project(name=\\\"r2\\\").save()\\n r3 = Project(name=\\\"r3\\\").save()\\n p1 = Person(name=\\\"p1\\\", projects=[r1, r2]).save()\\n p2 = Person(name=\\\"p2\\\", projects=[r2, r3]).save()\\n o1 = Organization(name=\\\"o1\\\", employees=[p1]).save()\\n\\n with query_counter() as q:\\n assert q == 0\\n\\n # Fetching a document should result in a query.\\n org = Organization.objects.get(id=o1.id)\\n assert q == 1\\n\\n # Checking changed fields of a newly fetched document should not\\n # result in a query.\\n org._get_changed_fields()\\n assert q == 1\\n\\n # Saving a doc without changing any of its fields should not result\\n # in a query (with or without cascade=False).\\n org = Organization.objects.get(id=o1.id)\\n with query_counter() as q:\\n org.save()\\n assert q == 0\\n\\n org = Organization.objects.get(id=o1.id)\\n with query_counter() as q:\\n org.save(cascade=False)\\n assert q == 0\\n\\n # Saving a doc after you append a reference to it should result in\\n # two db operations (a query for the reference and an update).\\n # TODO dereferencing of p2 shouldn't be necessary.\\n org = Organization.objects.get(id=o1.id)\\n with query_counter() as q:\\n org.employees.append(p2) # dereferences p2\\n org.save() # saves the org\\n assert q == 2\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7141398","0.6325323","0.628575","0.62599593","0.6144266","0.59896255","0.5943311","0.58616906","0.5857536","0.5824355","0.57983726","0.5751088","0.56624633","0.56524676","0.5632159","0.56152475","0.56012654","0.5580025","0.5523471","0.5508865","0.549159","0.54641545","0.5436384","0.5399983","0.53847635","0.53686446","0.5358888","0.5335111","0.5297383","0.5290377","0.5276286","0.5270747","0.5266785","0.5242111","0.5226177","0.5184222","0.51742935","0.5172473","0.5172473","0.51506233","0.51497215","0.5141481","0.51353437","0.51305467","0.51204985","0.5120118","0.511795","0.511795","0.511795","0.511795","0.5105329","0.51012385","0.50997424","0.5079177","0.5049926","0.5047131","0.50451744","0.50418067","0.504059","0.50371116","0.5036772","0.5015716","0.5015312","0.50099677","0.5009199","0.5007651","0.49849033","0.4983012","0.4976871","0.49645734","0.49367675","0.4935335","0.49268386","0.4923338","0.492082","0.491297","0.49022424","0.4901343","0.4895874","0.48925567","0.48578432","0.48463526","0.48459446","0.48450878","0.48371053","0.48341256","0.4831232","0.48257604","0.48238054","0.48207998","0.4818789","0.48182625","0.48153895","0.48151731","0.4814523","0.48135656","0.48121852","0.48118713","0.4797502","0.47935292","0.47929108"],"string":"[\n \"0.7141398\",\n \"0.6325323\",\n \"0.628575\",\n \"0.62599593\",\n \"0.6144266\",\n \"0.59896255\",\n \"0.5943311\",\n \"0.58616906\",\n \"0.5857536\",\n \"0.5824355\",\n \"0.57983726\",\n \"0.5751088\",\n \"0.56624633\",\n \"0.56524676\",\n \"0.5632159\",\n \"0.56152475\",\n \"0.56012654\",\n \"0.5580025\",\n \"0.5523471\",\n \"0.5508865\",\n \"0.549159\",\n \"0.54641545\",\n \"0.5436384\",\n \"0.5399983\",\n \"0.53847635\",\n \"0.53686446\",\n \"0.5358888\",\n \"0.5335111\",\n \"0.5297383\",\n \"0.5290377\",\n \"0.5276286\",\n \"0.5270747\",\n \"0.5266785\",\n \"0.5242111\",\n \"0.5226177\",\n \"0.5184222\",\n \"0.51742935\",\n \"0.5172473\",\n \"0.5172473\",\n \"0.51506233\",\n \"0.51497215\",\n \"0.5141481\",\n \"0.51353437\",\n \"0.51305467\",\n \"0.51204985\",\n \"0.5120118\",\n \"0.511795\",\n \"0.511795\",\n \"0.511795\",\n \"0.511795\",\n \"0.5105329\",\n \"0.51012385\",\n \"0.50997424\",\n \"0.5079177\",\n \"0.5049926\",\n \"0.5047131\",\n \"0.50451744\",\n \"0.50418067\",\n \"0.504059\",\n \"0.50371116\",\n \"0.5036772\",\n \"0.5015716\",\n \"0.5015312\",\n \"0.50099677\",\n \"0.5009199\",\n \"0.5007651\",\n \"0.49849033\",\n \"0.4983012\",\n \"0.4976871\",\n \"0.49645734\",\n \"0.49367675\",\n \"0.4935335\",\n \"0.49268386\",\n \"0.4923338\",\n \"0.492082\",\n \"0.491297\",\n \"0.49022424\",\n \"0.4901343\",\n \"0.4895874\",\n \"0.48925567\",\n \"0.48578432\",\n \"0.48463526\",\n \"0.48459446\",\n \"0.48450878\",\n \"0.48371053\",\n \"0.48341256\",\n \"0.4831232\",\n \"0.48257604\",\n \"0.48238054\",\n \"0.48207998\",\n \"0.4818789\",\n \"0.48182625\",\n \"0.48153895\",\n \"0.48151731\",\n \"0.4814523\",\n \"0.48135656\",\n \"0.48121852\",\n \"0.48118713\",\n \"0.4797502\",\n \"0.47935292\",\n \"0.47929108\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":18687,"cells":{"query":{"kind":"string","value":"Fills out the model by invoking C{svnlook}"},"document":{"kind":"string","value":"def _populateModel(self):\n\n self.repoPath = self.argv[1]\n self.rev = self.argv[2]\n self.model.rev = self.rev\n self.model.repo = os.path.split(self.repoPath)[-1]\n self.prefix = (self.addRepoPrefix() and ('/' + self.model.repo)) or ''\n\n # First, get the user and log message\n lines = self._svnlook('info')\n self.model.user = lines[0][:-1]\n self.model.log = ''.join(lines[3:]).strip()\n\n # Now build an initial tree of file and tree changes\n for line in self._svnlook('changed'):\n action = self.actions[line[0]]\n target = '/' + line[4:-1]\n\n if target.endswith('/'):\n directory = self.model.directory(self.prefix + target)\n directory.action = action\n else:\n parts = target.split('/')\n name = parts[-1]\n directoryPath = '/' + '/'.join(parts[0:-1]) + '/'\n\n file = File(name, self.model.directory(self.prefix + directoryPath), action)\n\n # Markers to tell us when we hit a new diff\n markers = ['Modified', 'Added', 'Copied', 'Deleted', 'Property changes on']\n\n # Recontruct each diff by parsing through the output of svnlook line by line\n diffs = []\n partialDiff = None\n\n #A marker word after a \"____\" line is a change in a property and shouldn't be added as a change\n #in a file. InProperty keeps track of this. If it's 0 this is a normal line, any larger \n #and it's a property line.\n inProperty = 1\n for line in self.getDiffLines():\n inProperty = max(0, inProperty-1)\n if line == \"___________________________________________________________________\\n\":\n inProperty = 2\n\n # Look for Modified:, Added:, etc.\n if line[0:line.find(':')] in markers and not inProperty > 0:\n # Handle starting a new diff\n partialDiff = [line]\n diffs.append(partialDiff)\n elif partialDiff:\n partialDiff.append(line)\n\n if len(diffs) == 0:\n for file in self.model.files():\n file.delta = '<Unavailable>'\n file.diff = ''\n\n # And finally parse through the diffs and save them into our tree of changes\n for diff in diffs:\n # Use [:-1] to leave of the trailing \\n\n start = diff[0].find(': ') + 2\n stop = diff[0].find('(') - 1 # -1 ignores the space before the paren\n if stop == -2: stop = len(diff[0])\n\n filePath = '/' + diff[0][:-1][start:stop]\n\n # This could be a file or a directory - going ahead with the .file()\n # call for most directories is fine as it will just return null.\n #\n # Howeever, root / will exception out as an invalid file path so\n # just special case it\n if filePath == '/':\n file = None\n else:\n file = self.model.file(self.prefix + filePath)\n\n # Maybe its a directory\n if file:\n isFile = True\n else:\n file = self.model.directory(self.prefix + filePath + '/')\n isFile = False\n\n if not diff[0].startswith('Property changes on:'):\n file.delta, file.diff = self._parse_diff(diff)\n else:\n if file.diff:\n # Only files will already have a diff set\n file.diff = file.diff + '\\n\\n' + ''.join(diff)\n else:\n # If the 'Property changes on' line is here without a\n # file.diff, that file.diff will never come because it would\n # have been printed before us\n if isFile:\n sep = '===================================================================\\n\\n'\n file.diff = ''.join([sep] + diff)\n file.delta = '+0 -0'\n else:\n file.diff = ''.join(diff)"},"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 update_model(self):\n pass # TODO: Implement this.","def build_model():","def update_model(self):\n pass","def updateModel(self):\n pass","def loadAdjustedModel(self):\r\n # Load model in GUI\r\n addModel(self.trcFilePath.replace('.trc','.osim'))","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/data/analysis/user/make3FGLxml.py -O {}'.format(modelScript))\n\n # Create the model using Tyrel's script\n galModel = os.path.join(self.diffpath, 'gll_iem_v06.fits')\n isoModel = os.path.join(self.diffpath, 'iso_'+self.irf+'_v06.txt')\n if (not os.path.isfile(galModel)) or (not os.path.isfile(isoModel)):\n print(\"\\t=== Unable to find the diffuse models, check the variable '$FERMI_DIR' ===\")\n return\n if not os.path.isdir(self.extpath):\n print(\"\\t=== Unable to find models of extended sources, check the variable '$LATEXTDIR' ===\")\n return\n if not os.path.isfile(self.fermicat):\n # download it\n print(\"\\t=== Downloading 3FGL catalog ===\")\n os.system('wget https://fermi.gsfc.nasa.gov/ssc/data/access/lat/4yr_catalog/gll_psc_v16.fit -O {}'.format(self.fermicat))\n\n os.popen(\"python {} {} {} -o {} -G {} -g 'gll_iem_v06'\\\n -I {} -i 'iso_source_v06' -e {} -r 5 -R 10 -ER 10\\\n -s 9 -m False -GIF False\".format(modelScript, self.fermicat,\n self.ft1, self.model, galModel, isoModel, self.extpath))\n\n # Add the target to the model\n tmpName = self.model + '.tmp'\n rfil = open(self.model, 'r')\n wfil = open(tmpName, 'w')\n # Copy the XML to the temporary model\n wfil.writelines([l for l in rfil.readlines() if not l=='</source_library>']) # copy everything but the last line\n wfil.write(' <source ROI_Center_Distance=\"0.00\" name=\"TARGET\" type=\"PointSource\">\\n')\n wfil.write(' <spectrum type=\"PowerLaw2\">\\n')\n wfil.write(' <parameter free=\"1\" max=\"1000\" min=\"1e-05\" name=\"Integral\" scale=\"1e-08\" value=\"0.3591824258\"/>\\n')\n wfil.write(' <parameter free=\"1\" max=\"1\" min=\"-5\" name=\"Index\" scale=\"1\" value=\"-2.7\"/>\\n')\n wfil.write(' <parameter free=\"0\" max=\"1000000\" min=\"20\" name=\"LowerLimit\" scale=\"1\" value=\"100\"/>\\n')\n wfil.write('<parameter free=\"0\" max=\"1000000\" min=\"20\" name=\"UpperLimit\" scale=\"1\" value=\"100000\"/>\\n')\n wfil.write(' </spectrum>\\n')\n wfil.write(' <spatialModel type=\"SkyDirFunction\">\\n')\n wfil.write(' <parameter free=\"0\" max=\"360.0\" min=\"-360.0\" name=\"RA\" scale=\"1.0\" value=\"'+str(self.ra)+'\"/>\\n')\n wfil.write(' <parameter free=\"0\" max=\"360.0\" min=\"-360.0\" name=\"DEC\" scale=\"1.0\" value=\"'+str(self.dec)+'\"/>\\n')\n wfil.write(' </spatialModel>\\n')\n wfil.write(' </source>\\n')\n wfil.write('</source_library>\\n')\n rfil.close()\n wfil.close()\n\n os.remove(self.model)\n os.rename(tmpName, self.model)\n \n print(\"\\t=== Source model {} added ===\".format(self.model))\n return","def build(self):\n labelled_documents = self.get_labelled_documents_queryset()\n\n self.model = self.build_model(labelled_documents)\n self.save_model()","def revision(self):\n self.r3.reuse = self.r2\n self.r3.case = self.case\n self.r3.revise()\n self.r2.predictionGenre = self.case.playlist_genre\n self.r2.predictionSubGenre =self.case.playlist_subgenre\n print()","def model(self, new_model):\n if self.locations.empty:\n raise RuntimeError(\"Cannot create a model until locations exist\")\n writer = ModelWriter(self, self.dismod_file)\n new_model.write(writer)\n writer.close()","def __init__(self):\n this = _diff.new_svn_patch_t()\n try:\n self.this.append(this)\n except __builtin__.Exception:\n self.this = this","def reset(self):\n self.vna.write(edit_list(self.model))\n self.vna.write(clear_list(self.model))","def save(self):\n\n if not self.revertable:\n return\n\n state = {}\n for x in self.toSave:\n state[x] = deepcopy(self.toSave[x]())\n\n #made a new model, reparent it so it displays\n state[\"model\"].reparentTo(base.render)\n\n #add it to the stack\n self.stack.append(state)\n\n for s in self.stack:\n s[\"model\"].setPos(s[\"model\"].getPos() + Vec3(0,0,-THING_REVERT_DISTANCE))","def ClearModels(self):\n self._modelFileNames = []\n self._models = []\n self.Modified(readAgain=True)","def test_model_found(arguments):\n ...","def handle(self, *args, **kwargs):\n # Part model\n try:\n print(\"Rebuilding Part objects\")\n\n from part.models import Part\n Part.objects.rebuild()\n except Exception:\n print(\"Error rebuilding Part objects\")\n\n # Part category\n try:\n print(\"Rebuilding PartCategory objects\")\n\n from part.models import PartCategory\n PartCategory.objects.rebuild()\n except Exception:\n print(\"Error rebuilding PartCategory objects\")\n\n # StockItem model\n try:\n print(\"Rebuilding StockItem objects\")\n\n from stock.models import StockItem\n StockItem.objects.rebuild()\n except Exception:\n print(\"Error rebuilding StockItem objects\")\n\n # StockLocation model\n try:\n print(\"Rebuilding StockLocation objects\")\n\n from stock.models import StockLocation\n StockLocation.objects.rebuild()\n except Exception:\n print(\"Error rebuilding StockLocation objects\")\n\n # Build model\n try:\n print(\"Rebuilding Build objects\")\n\n from build.models import Build\n Build.objects.rebuild()\n except Exception:\n print(\"Error rebuilding Build objects\")","def update_model(command):\n namespace = app.main(command)\n assert namespace.command == 'um' or namespace.command == \"updatemodel\"","def test_po_migration(self):\n PurchaseOrder = self.new_state.apps.get_model('order', 'purchaseorder')\n for ii in range(10):\n\n po = PurchaseOrder.objects.get(reference=f\"{ii}-abcde\")\n self.assertEqual(po.extra_lines.count(), 1)\n self.assertEqual(po.lines.count(), 1)\n\n # TODO @matmair fix this test!!!\n # SalesOrder = self.new_state.apps.get_model('order', 'salesorder')\n # for ii in range(10):\n # so = SalesOrder.objects.get(reference=f\"{ii}-xyz\")\n # self.assertEqual(so.extra_lines, 1)\n # self.assertEqual(so.lines.count(), 1)","def __init__(self):\n self.model = None","def __init__(self):\n self.model = None","def model(self):","def model(self):","def model(self):","def model(self):","def model(self):","def update(self,wsname,fname,storelist=[]):\n import os\n from ROOT import RooWorkspace, TFile\n\n # Create the ws with the model and data available\n w = RooWorkspace(wsname,'Workspace')\n wsImport = getattr(w,'import')\n # Put the models \n for rawtuple in self.__models.values():\n model = rawtuple[0]\n anythingelse = rawtuple[1:]\n wsImport(model)\n # Put whatever the user want to store\n for _item in storelist:\n wsImport(_item)\n\n # Check if the fname already exist\n file_exist = os.path.isfile(fname)\n if file_exist:\n # Create a new auxiliar file, to provisionaly\n # store the ws \n auxfname = '_auxroot.root'\n w.writeToFile(auxfname)\n # Previously delete the old Workspace, if any\n _rootfile = TFile(fname)\n _rootfile.Delete(wsname+';*')\n _rootfile.Delete(\"ProcessID*;*\")\n _rootfile.Close()\n # Open the auxiliary file\n _aux = TFile(auxfname)\n # and copy the ws to the rootfile\n w = _aux.Get(wsname)\n # and copy the ws to the rootfile\n w.writeToFile(fname,False)\n\n if file_exist:\n # And closing and removing auxfile\n _aux.Close()\n os.remove(auxfname)","def onBuildModels(self):\n if self.refSeriesNumber != '-1':\n ref = self.refSeriesNumber\n refLongName = self.seriesMap[ref]['LongName']\n labelNodes = slicer.util.getNodes('*'+refLongName+'*-label*')\n\n numNodes = slicer.mrmlScene.GetNumberOfNodesByClass( \"vtkMRMLModelHierarchyNode\" )\n outHierarchy = None\n\n for n in xrange(numNodes):\n node = slicer.mrmlScene.GetNthNodeByClass( n, \"vtkMRMLModelHierarchyNode\" )\n if node.GetName() == 'mpReview-'+refLongName:\n outHierarchy = node\n break\n\n # Remove the previous models\n if outHierarchy:\n collection = vtk.vtkCollection()\n outHierarchy.GetChildrenModelNodes(collection)\n n = collection.GetNumberOfItems()\n if n != 0:\n for i in xrange(n):\n modelNode = collection.GetItemAsObject(i)\n slicer.mrmlScene.RemoveNode(modelNode)\n\n # if models hierarchy does not exist, create it.\n else:\n outHierarchy = slicer.vtkMRMLModelHierarchyNode()\n outHierarchy.SetScene( slicer.mrmlScene )\n outHierarchy.SetName( 'mpReview-'+refLongName )\n slicer.mrmlScene.AddNode( outHierarchy )\n\n progress = self.makeProgressIndicator(len(labelNodes))\n step = 0\n for label in labelNodes.values():\n labelName = label.GetName().split(':')[1]\n structureName = labelName[labelName[:-6].rfind(\"-\")+1:-6]\n # Only save labels with known structure names\n if any(structureName in s for s in self.structureNames):\n parameters = {}\n parameters[\"InputVolume\"] = label.GetID()\n parameters['FilterType'] = \"Sinc\"\n parameters['GenerateAll'] = True\n\n parameters[\"JointSmoothing\"] = False\n parameters[\"SplitNormals\"] = True\n parameters[\"PointNormals\"] = True\n parameters[\"SkipUnNamed\"] = True\n\n # create models for all labels\n parameters[\"StartLabel\"] = -1\n parameters[\"EndLabel\"] = -1\n\n parameters[\"Decimate\"] = 0\n parameters[\"Smooth\"] = 0\n\n parameters[\"ModelSceneFile\"] = outHierarchy\n\n progress.labelText = '\\nMaking Model for %s' % structureName\n progress.setValue(step)\n if progress.wasCanceled:\n break\n\n try:\n modelMaker = slicer.modules.modelmaker\n self.CLINode = slicer.cli.run(modelMaker, self.CLINode,\n parameters, wait_for_completion=True)\n except AttributeError:\n qt.QMessageBox.critical(slicer.util.mainWindow(),'Editor', 'The ModelMaker module is not available<p>Perhaps it was disabled in the application settings or did not load correctly.')\n step += 1\n progress.close()\n #\n\n if outHierarchy:\n collection = vtk.vtkCollection()\n outHierarchy.GetChildrenModelNodes(collection)\n n = collection.GetNumberOfItems()\n if n != 0:\n for i in xrange(n):\n modelNode = collection.GetItemAsObject(i)\n displayNode = modelNode.GetDisplayNode()\n displayNode.SetSliceIntersectionVisibility(1)\n displayNode.SetSliceIntersectionThickness(2)\n self.modelsVisibilityButton.checked = False\n self.updateViewRenderer()","def test_persistence_old_model(self):\n loaded = PoincareModel.load(datapath('poincare_test_3.4.0'))\n self.assertEqual(loaded.kv.syn0.shape, (239, 2))\n self.assertEqual(len(loaded.kv.vocab), 239)\n self.assertEqual(loaded.size, 2)\n self.assertEqual(len(loaded.all_relations), 200)","def load_cobra_model(self, model):\n self.model = ModelPro(model)\n for g in self.model.genes:\n if self.genes_dir:\n g.root_dir = self.genes_dir\n g.protein.pdb_file_type = self.pdb_file_type\n self.genes = self.model.genes\n\n log.info('{}: loaded model'.format(model.id))\n log.info('{}: number of reactions'.format(len(self.model.reactions)))\n log.info('{}: number of reactions linked to a gene'.format(ssbio.core.modelpro.true_num_reactions(self.model)))\n log.info('{}: number of genes (excluding spontaneous)'.format(ssbio.core.modelpro.true_num_genes(self.model,\n custom_spont_id=self.custom_spont_id)))\n log.info('{}: number of metabolites'.format(len(self.model.metabolites)))\n log.warning('IMPORTANT: All Gene objects have been transformed into GenePro '\n 'objects, and will be for any new ones')","def build_model(self):\n pass","def build_model(self):\n pass","def init_model(self):\n pass","def run(self):\r\n # Close any open models\r\n self.cleanUp()\r\n # Dynamically select file to preview\r\n self.selectTrial() \r\n # Add adjusted COM (RRA/CMC) model\r\n self.loadAdjustedModel()\r\n # Hide the markers from view\r\n self.hideModelMarkers()\r\n # Load CMC motion to model\r\n self.loadCMCMotion()","def restore(self, model_file, head_i=0, trunk=False):\n if trunk:\n self.model_trunk.load_weights(model_file)\n else:\n self.models[head_i].load_weights(model_file)\n self.model = self.models[head_i]","def test_updating_the_project(self):\n modified_po = copy.deepcopy(base_purchase_order)","def test_override_model(self):\n\n class MyModel(FileObject):\n def render(self):\n return self.content\n\n class MyFBO(FBO):\n path = TEST_FILES_ROOT\n metadata = FileObject.MetadataInFileHead\n model = MyModel\n\n self.assertEqual(\n 'My little explicit YAML test.\\n',\n MyFBO().objects.get(name='test2.rst').render(),\n )","def main(quiet=False):\n if quiet:\n output_stream = StringIO()\n else:\n output_stream = sys.stdout\n\n newpath = r'%s/models' % os.getcwdu()\n if not os.path.exists(newpath): os.makedirs(newpath)\n newpath = r'%s/out' % os.getcwdu()\n if not os.path.exists(newpath): os.makedirs(newpath)\n existing = sorted(os.listdir('%s/%s' % (os.getcwdu(), 'models'))) \n\n urls = [\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/parameters.fits.gz',\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/2J.fits',\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/2H.fits',\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/2K.fits',\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/I1.fits',\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/I2.fits',\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/I3.fits',\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/I4.fits',\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/M1.fits',\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/M2.fits',\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/M3.fits',\n 'http://caravan.astro.wisc.edu/protostars/files/extinction_law.tar.gz'\n ]\n file_names = [\n 'models/parameters.fits.gz',\n 'models/2J.fits',\n 'models/2H.fits',\n 'models/2K.fits',\n 'models/I1.fits',\n 'models/I2.fits',\n 'models/I3.fits',\n 'models/I4.fits',\n 'models/M1.fits',\n 'models/M2.fits',\n 'models/M3.fits',\n 'models/extinction_law.tar.gz']\n\n for i in range(len(urls)):\n if not os.path.isfile(file_names[i]):\n f = open(file_names[i], 'wb')\n f.write(urllib2.urlopen(urls[i]).read())\n f.close()\n print('Downloaded %s from %s' % (file_names[i],urls[i]), file=output_stream)\n\n if not os.path.isfile('modesl/extinction_law.ascii'):\n f = tarfile.open('models/extinction_law.tar.gz', 'r:gz')\n try: f.extractall()\n finally: f.close()","def snapshot(self):\n for ref, (m, _) in self._models.items():\n m.snapshot = not m.snapshot\n (self, root, doc, comm) = state._views[ref]\n if comm and 'embedded' not in root.tags:\n push(doc, comm)","def test_Base_model(self):\n with patch('sys.stdout', new=StringIO()) as f:\n HBNBCommand().onecmd(\"create BaseModel\")\n id = f.getvalue().strip()\n self.assertTrue(type(f), str)\n self.assertEqual(len(id), 36)\n\n with patch('sys.stdout', new=StringIO()) as f:\n HBNBCommand().onecmd(\"update BaseModel \" + str(id) + \" name Manga\")\n self.assertTrue(type(f), str)\n self.assertEqual(f.getvalue().strip(), \"\")\n\n with patch('sys.stdout', new=StringIO()) as f:\n HBNBCommand().onecmd(\"show BaseModel \" + str(id))\n self.assertTrue(\"name\" in f.getvalue().strip())\n self.assertTrue(\"Manga\" in f.getvalue().strip())","def __init__(self, modelpath):\n self.modelpath = Path(modelpath)\n if not self.modelpath.is_file():\n raise FileNotFoundError(f\"{self.modelpath} does not exist\")\n self.model = Word2Vec.load(modelpath)\n elems = self.modelpath.name.rsplit('.', 1)[0].split('-')[-3:]\n self.r = int(elems[0][1:])\n self.p = float(elems[1][1:])\n self.q = float(elems[2][1:])\n print(f'{len(self.model.wv.index2word)} sub-structures with dimension {self.model.vector_size}')","def __init__(self, model):\n\t\tself.model = model","def runModel(quickLogger,\n\t base,\n modelFile=\"\",\n\t irfs=\"P7SOURCE_V6\",\n run=True):\n \n if(modelFile):\n model = modelFile\n else:\n model = base+\"_likeMinuit.xml\"\n\n\n try:\n checkForFiles(quickLogger,\n [base+\"_srcMaps.fits\",\n model,\n base+\"_ltcube.fits\",\n base+\"_BinnedExpMap.fits\"])\n except(FileNotFound):\n quickLogger.critical(\"One or more needed files do not exist.\")\n return\n\n model_map['srcmaps'] = base+\"_srcMaps.fits\"\n model_map['srcmdl'] = model\n model_map['outfile'] = base+\"_modelMap.fits\"\n model_map['expcube'] = base+\"_ltcube.fits\"\n model_map['irfs'] = irfs\n model_map['bexpmap'] = base+\"_BinnedExpMap.fits\"\n \n runCommand(model_map,quickLogger,run)","def update_view(self):\n for row in self.view.obj_list:\n for obj in row:\n obj._update(self.model)","def create_models( self ):","def save(self):\n self._initial_vms = self.selected_vms","def _build_model(self):\n raise NotImplementedError()","def load_model(self) -> Any:","def test08(self):\n model = self.setup_model02()\n model.x[1].fix(1)\n\n model.dual[model.g] = 1\n model.ipopt_zL_out[model.x[1]] = 1\n model.ipopt_zL_out[model.x[2]] = 1\n model.ipopt_zU_out[model.x[1]] = 1\n model.ipopt_zU_out[model.x[2]] = 1\n\n to_json(model, fname=self.fname, wts=StoreSpec.suffix())\n\n model.dual[model.g] = 10\n model.ipopt_zL_out[model.x[1]] = 10\n model.ipopt_zL_out[model.x[2]] = 10\n model.ipopt_zU_out[model.x[1]] = 10\n model.ipopt_zU_out[model.x[2]] = 10\n model.g.deactivate()\n model.x[1].setlb(-4)\n model.x[1].unfix()\n model.x[2].fix(6)\n\n from_json(model, fname=self.fname, wts=StoreSpec.suffix())\n assert value(model.x[1]) == 1\n assert value(model.x[2]) == 6\n assert not model.x[1].fixed\n assert model.x[2].fixed\n assert not model.g.active\n assert model.dual[model.g] == 1\n assert model.ipopt_zL_out[model.x[1]] == 1\n assert model.ipopt_zL_out[model.x[2]] == 1\n assert model.ipopt_zU_out[model.x[1]] == 1\n assert model.ipopt_zU_out[model.x[2]] == 1\n assert model.x[1].lb == -4","def main():\n\n # Create argument parser\n parser = ArgumentParser()\n parser.add_argument('datadir', type=str, help='Directory of LC files')\n parser.add_argument('metatable', type=str,\n help='Metatable containing each object, redshift, peak time guess, mwebv, object type')\n parser.add_argument('--zpt', type=float, default=DEFAULT_ZPT, help='Zero point of LCs')\n parser.add_argument('--lm', type=float, default=DEFAULT_LIM_MAG, help='Survey limiting magnitude')\n parser.add_argument('--outdir', type=str, default='./products/',\n help='Path in which to save the LC data (single file)')\n args = parser.parse_args()\n\n objs, redshifts, obj_types, peaks, ebvs = read_in_meta_table(args.metatable)\n\n # Grab all the LC files in the input directory\n file_names = []\n for obj in objs:\n file_name = args.datadir + 'PS1_PS1MD_' + obj + '.snana.dat'\n file_names.append(file_name)\n\n # Create a list of LC objects from the data files\n lc_list = read_in_LC_files(file_names, objs)\n\n # This needs to be redone when retrained\n # TODO: Need to change this whenever you retrain...\n filt_dict = {'g': 0, 'r': 1, 'i': 2, 'z': 3}\n wvs = np.asarray([5460, 6800, 7450, 8700])\n\n # Update the LC objects with info from the metatable\n my_lcs = []\n for i, my_lc in enumerate(lc_list):\n my_lc.add_LC_info(zpt=args.zpt, mwebv=ebvs[i],\n redshift=redshifts[i], lim_mag=args.lm,\n obj_type=obj_types[i])\n my_lc.get_abs_mags()\n my_lc.sort_lc()\n pmjd = my_lc.find_peak(peaks[i])\n my_lc.shift_lc(pmjd)\n my_lc.correct_time_dilation()\n my_lc.filter_names_to_numbers(filt_dict)\n my_lc.correct_extinction(wvs)\n my_lc.cut_lc()\n my_lc.make_dense_LC(4)\n my_lcs.append(my_lc)\n save_lcs(my_lcs, args.outdir)","def initialize_model(self):\n pass","def add(self):\r\n self._svn('add')","def test07(self):\n model = self.setup_model02()\n model.x[1].fix(1)\n wts = StoreSpec.isfixed()\n to_json(model, fname=self.fname, human_read=True, wts=wts)\n model.g.deactivate()\n model.x[1].setlb(-4)\n model.x[1].unfix()\n model.x[2].fix(6)\n from_json(model, fname=self.fname, wts=wts)\n assert value(model.x[1]) == 1\n assert model.x[1].lb == -4\n assert value(model.x[2]) == 6\n assert model.x[1].fixed\n assert not model.x[2].fixed\n assert not model.g.active","def skel_model(action, install_path_mp, install_path_zfs, jname):\n # init vars\n # mp - mount point, zfs - zfs point\n skel_path_mp = '%s-SKELETON' % install_path_mp\n skel_path_zfs = '%s-SKELETON' % install_path_zfs\n rw_path_mp = '%s-RW' % install_path_mp\n rw_path_zfs = '%s-RW' % install_path_zfs\n \n if action == 'init':\n# create SKELETON MODEL\n# http://www.freebsd.org/doc/en_US.ISO8859-1/books/handbook/jails-application.html\n log(\" INFO: Init BASE-SKELETON zfs START\")\n# Create a skeleton for the read-write portion of the system\n os.system('zfs create %s' % skel_path_zfs)\n os.system('zfs set mountpoint=%s %s' % (skel_path_mp, skel_path_zfs))\n os.system('zfs create %s' % rw_path_zfs)\n os.system('zfs set mountpoint=%s %s' % (rw_path_mp, rw_path_zfs))\n\n os.system('mkdir -p %s/home %s/usr-X11R6 %s/distfiles %s/usr-share-keys/pkg' % (skel_path_mp, skel_path_mp, skel_path_mp, skel_path_mp))\n os.system('mv %s/etc %s' % (install_path_mp, skel_path_mp ))\n os.system('mv %s/usr/local %s/usr-local' % (install_path_mp, skel_path_mp ))\n os.system('mv %s/tmp %s' % (install_path_mp, skel_path_mp ))\n os.system('mv %s/var %s' % (install_path_mp, skel_path_mp ))\n os.system('mv %s/root %s' % (install_path_mp, skel_path_mp ))\n# mergemaster to install missing configuration files. Then, remove the the extra directories that mergemaster creates:\n# os.system('mergemaster -t %s/var/tmp/temproot -D %s -i' % (skel_path, skel_path))\n# os.system('rm -R %(key)s/bin %(key)s/boot %(key)s/lib %(key)s/libexec %(key)s/mnt %(key)s/proc %(key)s/rescue %(key)s/sbin %(key)s/sys %(key)s/usr %(key)s/dev' % {'key': skel_path})\n# Now, symlink the read-write file system to the read-only file system. Ensure that the symlinks are created in the correct s/ locations as the creation of directories in the wrong locations will cause the installation to fail.\n os.chdir('%s' % install_path_mp)\n os.system('mkdir SROOT')\n os.system('ln -s SROOT/etc etc')\n os.system('ln -s SROOT/home home')\n os.system('ln -s SROOT/root root')\n os.system('ln -s /SROOT/usr-local usr/local')\n os.system('ln -s /SROOT/usr-share-keys usr/share/keys')\n os.system('ln -s /SROOT/usr-X11R6 usr/X11R6')\n os.system('ln -s /SROOT/distfiles usr/ports/distfiles')\n os.system('ln -s SROOT/tmp tmp')\n os.system('ln -s SROOT/var var')\n# Create a generic /home/j/skel/etc/make.conf containing this line\n os.system('echo \\\"WRKDIRPREFIX?= /SROOT/portbuild\\\" > %s/etc/make.conf' % skel_path_mp )\n# Create zfs BASE-SKELETON snapshot which will be used for installation \n os.system('zfs snapshot %s@install' % skel_path_zfs)\n log(\" INFO: Init BASE-SKELETON zfs FINISH\")\n \n# install SKELETON jail \n if action == 'install':\n# install RW fs for jail\n os.system('zfs send %s/BASE-SKELETON@install | zfs receive -F %s/BASE-RW/%s' % (jzfs, jzfs, jname))\n# remove receive snapshot \n os.system('zfs destroy %s/BASE-RW/%s@install' % (jzfs, jname))\n# create jail local config - mount skel model for jail hosme dir\n if jname == 'BASE-update':\n os.system('echo \\\"%sBASE %s%s nullfs rw 0 0\\\" > %sBASE-RW/%s/etc/fstab' % (jpath, jpath, jname, jpath, jname))\n else:\n os.system('echo \\\"%sBASE %s%s nullfs ro 0 0\\\" > %sBASE-RW/%s/etc/fstab' % (jpath, jpath, jname, jpath, jname))\n \n os.system('echo \\\"%sBASE-RW/%s %s%s/SROOT nullfs rw 0 0\\\" >> %sBASE-RW/%s/etc/fstab' % (jpath, jname, jpath, jname, jpath, jname))\n temp_add_cfg = ['### BASE mount settings ###', 'mount.fstab=\"%sBASE-RW/%s/etc/fstab\";' % (jpath, jname), 'mount.devfs;']\n return temp_add_cfg","def update(self):\n \n dbpath, config = self._start()\n \n self.config.obo = check_file(config.obo, dbpath, \"obo\") \n desc_file = check_file(config.model_descriptions, dbpath,\n \"model_descriptions\", allow_none=True) \n phen_file = check_file(config.model_phenotypes, dbpath,\n \"model_phenotypes\", allow_none=True)\n \n summary = self._update(desc_file, phen_file) \n if len(summary[\"incorrect_ids\"]) == 0 and not config.skip_compute:\n self._compute(models=summary[\"new_phenotypes\"])\n \n self._end()","def init_from_scratch(args, train_exs, dev_exs):\n \n # Build a dictionary from the data sqls+queries (train/dev splits)\n logger.info('-' * 100)\n logger.info('Build vocab')\n \n vocab = build_vocab(train_exs + dev_exs, args)\n logger.info('Num words = %d' % vocab.size())\n \n # Initialize model\n model = CopyNet(args, vocab)\n logger.info('-' * 100)\n logger.info('Model Architecture')\n logger.info(model)\n if args.embedding_file:\n model.load_embeddings(vocab.tokens(), args.embedding_file)\n \n return model, vocab","def test_make_update_script_for_model(self):\n\n self.setup_model_params()\n self.write_file(self.first_model_path, self.base_source)\n self.write_file(self.second_model_path, self.base_source + self.model_source)\n\n source_script = self.pyscript.make_update_script_for_model(\n engine=self.engine,\n oldmodel=load_model('testmodel_first:meta'),\n model=load_model('testmodel_second:meta'),\n repository=self.repo_path,\n )\n\n self.assertTrue(\"['User'].create()\" in source_script)\n self.assertTrue(\"['User'].drop()\" in source_script)","def test_edit_baseline(self):\n baseline = createContentInContainer(self.folder, 'stageable_type')\n working_copy = self.do_checkout(baseline)\n baseline.title = u'new title'\n\n # XXX: aq_base is necessary to prevent error:\n # \"TypeError: Can't pickle objects in acquisition wrappers.\"\n # in CMFEdition\n notify(ObjectModifiedEvent(aq_base(baseline)))\n\n relation = get_checkout_relation(baseline)\n annotation = IWCAnnotator(baseline).get_relation()\n self.assertIsNotNone(relation)\n self.assertEqual(relation, annotation)","def populate_models(tree) :\n\te_root = tree.getroot()\n\tpopulate_crisis(e_root)\n\tpopulate_person(e_root)\n\tpopulate_org(e_root)","def testGetReigsteredModel(self):\n from soc.models.student import Student\n model = models_logic.getModel('soc.models.student.Student')\n self.assertEqual(model, Student)","def generateModelEdit(data):\n\n global h_model\n h_model.append(\"\")\n h_model.append(\"\\t// In-Table edit support:\")\n h_model.append(\"\\tvoid store(const QString &sign, const QString &code);\")\n generateModelFlags(data)\n generateModelSetData(data)","def __init__(self):\n self.incidents_models = {}\n self.risks = []\n self.incidents_models = None","def main():\r\n \r\n world = WorldModel()\r\n #uncomment these lines and comment out the next 2 if you want to use the\r\n #full Baxter model\r\n #print \"Loading full Baxter model (be patient, this will take a minute)...\"\r\n #world.loadElement(os.path.join(model_dir,\"baxter.rob\"))\r\n print \"Loading simplified Baxter model...\"\r\n world.loadElement(os.path.join(model_dir,\"baxter_col.rob\"))\r\n print \"Loading Kiva pod model...\"\r\n world.loadElement(os.path.join(model_dir,\"kiva_pod/model.obj\"))\r\n print \"Loading plane model...\"\r\n world.loadElement(os.path.join(model_dir,\"plane.env\"))\r\n \r\n #shift the Baxter up a bit (95cm)\r\n Rbase,tbase = world.robot(0).getLink(0).getParentTransform()\r\n world.robot(0).getLink(0).setParentTransform(Rbase,(0,0,0.95))\r\n \r\n #translate pod to be in front of the robot, and rotate the pod by 90 degrees \r\n Trel = (so3.rotation((0,0,1),math.pi/2),[1.1,0,0])\r\n T = world.rigidObject(0).getTransform()\r\n world.rigidObject(0).setTransform(*se3.mul(Trel,T))\r\n \r\n #run the visualizer\r\n visualizer = MyGLViewer(world)\r\n visualizer.run()","def updateTree(self):\n self.reset()\n self.resetTree() \n self.read()","def _screener_init(self):\n subject = 0\n self.model.uu.remove(subject) # selects from untested and performs e\n self.model.tt.append(subject)\n self.model.b -= (self.cz + self.cy) # update budget\n self.model.z[subject] = self.z[subject] # update model\n self.model.y[subject] = self.y[subject]","def svn_info_t_copyfrom_rev_get(svn_info_t_self): # real signature unknown; restored from __doc__\n pass","def repo_init(_request):\n python = models.Repository.query(models.Repository.name == 'Python').get()\n if python is None:\n python = models.Repository(name='Python', url=SVN_ROOT)\n python.put()\n pybranches = []\n else:\n pybranches = list(models.Branch.query(models.Branch.repo_key == python.key))\n for category, name, url in BRANCHES:\n url = python.url + url\n for br in pybranches:\n if (br.category, br.name, br.url) == (category, name, url):\n break\n else:\n br = models.Branch(repo_key=python.key, repo_name='Python',\n category=category, name=name, url=url)\n br.put()\n return HttpResponseRedirect(reverse(repos))","def build(self):\n raise Exception(\" not implemented in base model\")","def __init__(self, model):\n self.model = model","def __init__(self, model):\n self.model = model","def __init__(self, model):\n self.model = model","def __init__(self, model):\n self.model = model","def save(self, *args, **kwargs):\n self.pk = None\n super(AbstractRevision, self).save(*args, **kwargs)\n self.tracked_model.current_revision = self\n self.tracked_model.save()","def edited_file_locations(self):","def dump_model(self):","def load_model():\n global obj\n obj = NutritionTableDetector()\n print(\"Weights Loaded!\")","def testSave(self):\n\n # Generate temp file path\n index = os.path.join(tempfile.gettempdir(), \"bm25\")\n os.makedirs(index, exist_ok=True)\n\n model = self.method(\"bm25\")\n model.save(index)\n model.load(index)","def _populate_table_files(model):\n # Get list of all files\n if model is Software:\n paths_found = {path.path for path in _recursive_scan(app.config['DEVICE_SW_DRIVE'], '.exe')}\n elif model is File:\n paths_found = {path.path for path in _recursive_scan()}\n else:\n raise TypeError('Type of File or Software expected as model.')\n paths_existing = {file.path for file in model.query.all()}\n\n # Paths that have been deleted from host but still exist in DB\n for path in paths_existing - paths_found:\n model.query.filter_by(path=path).update({'stored': False})\n\n # Paths that are found and exists in DB\n for path in paths_found.intersection(paths_existing):\n model.query.filter_by(path=path).update({'stored': True})\n\n # Paths found that doesn't exist in the DB\n paths_new = paths_found - paths_existing\n for path in paths_new:\n name = os.path.split(path)[1]\n new_model = model(name=name, path=path)\n db.session.add(new_model)\n\n db.session.commit()","def model_input(step=0.1):\n model = np.loadtxt('start_model.dat',dtype={'names': ('H', 'VP','VS','RHO','QP','QS',\\\n 'ETAP','ETAS','FREFP','FREFS'),'formats': ('f4', 'f4','f4','f4',\\\n 'f4','f4','f4','f4','f4','f4')}, skiprows=1)\n \n f = open('model96_input.tmp', 'w+')\n f.write('model_step96.in\\nIsotropic model\\n0\\n')\n d = np.loadtxt('cumul_depths.tmp')\n for i in np.arange(len(d)):\n for k, s in enumerate(np.arange(0,d[-1],step)):\n if s < d[i] and i==0:\n f.write('%s %s %s %s %s %s %s %s %s %s\\n'\n %(step, model['VP'][i], model['VS'][i], model['RHO'][i],\\\n model['QP'][i], model['QS'][i], model['ETAP'][i], model['ETAS'][i],\\\n model['FREFP'][i], model['FREFS'][i]))\n if i > 0:\n if s < d[i] and s > d[i-1]:\n f.write('%s %s %s %s %s %s %s %s %s %s\\n'\n %(step, model['VP'][i], model['VS'][i], model['RHO'][i],\\\n model['QP'][i], model['QS'][i], model['ETAP'][i], model['ETAS'][i],\\\n model['FREFP'][i], model['FREFS'][i]))\n f.close()\n os.system(\"mkmod96 < model96_input.tmp\")\n print (\">> Model_step96.in is ready... next step is comp_disp.bash\")\n print ('>> nlayers =', k)\n print (\">> Change nlayer in eigenfucntion_*.bash!!!!\")\n print (\">> mkmod96\")","def load_model(self):\n pass","def test_update_list_changes_data(qtbot):\n # Given\n model = SourcesModel()\n assert model.rowCount() == 0\n\n sources = []\n source = Source(\"I001\", \"Test\", \"Person\", \"Pub\", \"Abbr\")\n sources.append(source)\n\n # When\n with qtbot.waitSignals([model.modelAboutToBeReset, model.modelReset]):\n model.update_list(sources)\n\n # Then\n assert model.rowCount() == 1","def update_model(self, budget=0):\n self._log(\"start updateing model with budget {}\".format(budget))\n\n # check if enough observations available for model building\n if len(self.searchspace.keys()) > len(self.get_metrics_array(budget=budget)):\n self._log(\n \"not enough observations available to build with budget {} yet. At least {} needed, got {}\".format(\n budget,\n len(self.searchspace.keys()),\n len(self.get_metrics_array(budget=budget)),\n )\n )\n return\n\n # create model without any data\n model = clone(self.base_model)\n\n Xi, yi = self.get_XY(\n budget=budget,\n interim_results=self.interim_results,\n interim_results_interval=self.interim_results_interval,\n )\n\n # fit model with data\n model.fit(Xi, yi)\n\n self._log(\"fitted model with data\")\n\n # update model of budget\n self.models[budget] = model","def refresh(self):\n\n assets_model = self.data[\"model\"][\"assets\"]\n assets_model.clear()\n\n has = {\"children\": False}\n\n project = io.ObjectId(os.environ[\"MINDBENDER__PROJECT\"])\n assets = io.find({\"type\": \"asset\", \"parent\": project})\n for asset in sorted(assets, key=lambda i: i[\"name\"]):\n item = QtWidgets.QListWidgetItem(asset[\"name\"])\n item.setData(QtCore.Qt.ItemIsEnabled, True)\n item.setData(DocumentRole, asset)\n assets_model.addItem(item)\n has[\"children\"] = True\n\n if not has[\"children\"]:\n item = QtWidgets.QListWidgetItem(\"No assets found\")\n item.setData(QtCore.Qt.ItemIsEnabled, False)\n assets_model.addItem(item)\n\n assets_model.setFocus()\n assets_model.setCurrentRow(0)\n self.data[\"button\"][\"load\"].hide()\n self.data[\"button\"][\"stop\"].hide()","def push_model(config):\n util_logger.info('Backing up the model files to wandb')\n martifact = wandb.Artifact('%s_model' % config.wandb_name, type='model')\n martifact.add_dir(os.path.join(config.output_dir,\"best_model\"))\n #matrifact.add_file(os.path.join(config.output_dir,\"trainer_config.json\"))\n wandb.log_artifact(martifact)","def object_cmd(args):\n if len(args) >= 1:\n a = [ args[0], 0 ]\n model_cmd(a)\n else:\n error(\"Usage...\")","def test_import_crisis(self):\r\n tree = self.crisis_tree\r\n root = tree.getroot()\r\n assert importer.put_objects(root) == True","def test_xmlrpc_ir_model_search(self):\n o = self.xmlrpc_object\n db_name = common.get_db_name()\n ids = o.execute(db_name, self.admin_uid, 'admin', 'ir.model', 'search', [])\n self.assertIsInstance(ids, list)\n ids = o.execute(db_name, self.admin_uid, 'admin', 'ir.model', 'search', [], {})\n self.assertIsInstance(ids, list)","def test_make_update_script_direction(self):\n\n self.setup_model_params()\n self.write_file(self.first_model_path, self.base_source)\n self.write_file(self.second_model_path, self.base_source + self.model_source)\n\n source_script = self.pyscript.make_update_script_for_model(\n engine=self.engine,\n oldmodel=load_model('testmodel_first:meta'),\n model=load_model('testmodel_second:meta'),\n repository=self.repo_path,\n )\n\n self.assertTrue(0\n < source_script.find('upgrade')\n < source_script.find(\"['User'].create()\")\n < source_script.find('downgrade')\n < source_script.find(\"['User'].drop()\"))","def pickUp(self):\n pos = self.getRoverLocation()\n item = self.map[pos.y,pos.x]\n if type(item) == Part:\n self.inventory.addPart(str(item))\n self.map[pos.y,pos.x] = None","def _prepare_model(model):\n\n # Ensure there is at least 1 load combination to solve if the user didn't define any\n if model.LoadCombos == {}:\n # Create and add a default load combination to the dictionary of load combinations\n model.LoadCombos['Combo 1'] = LoadCombo('Combo 1', factors={'Case 1':1.0})\n \n # Generate all meshes\n for mesh in model.Meshes.values():\n if mesh.is_generated == False:\n mesh.generate()\n\n # Activate all springs and members for all load combinations\n for spring in model.Springs.values():\n for combo_name in model.LoadCombos.keys():\n spring.active[combo_name] = True\n \n # Activate all physical members for all load combinations\n for phys_member in model.Members.values():\n for combo_name in model.LoadCombos.keys():\n phys_member.active[combo_name] = True\n \n # Assign an internal ID to all nodes and elements in the model. This number is different from the name used by the user to identify nodes and elements.\n _renumber(model)","def load_full_model(self, session, model_dir):\n self.full_saver.restore(session, model_dir)","def __init__(self):\n Model.__init__(self)\n self.rellenar_lista()","def reset_model(self):\n raise NotImplementedError","def reset_model(self):\n raise NotImplementedError","def reset_model(self):\n raise NotImplementedError","def automark(self):\n\n index_list = self.ui.tableWidget.selectionModel().selectedIndexes()\n rows = []\n for i in index_list:\n rows.append(i.row())\n rows = list(set(rows)) # duplicate rows due to multiple columns\n if len(rows) == 0:\n return\n selected_files = []\n filenames = \"\"\n for r in rows:\n if self.allfiles[r][2] is not None and self.allfiles[r][2] != \"\":\n selected_files.append(self.allfiles[r])\n filenames += self.allfiles[r][1] + \" \"\n ui_se = DialogGetStartAndEndMarks(self.case['name'], filenames)\n ok = ui_se.exec()\n if not ok:\n return\n start_mark = ui_se.get_start_mark()\n end_mark = ui_se.get_end_mark()\n if start_mark == \"\" or end_mark == \"\":\n Message(self.app, _(\"Warning\"), _('Cannot have blank text marks'), \"warning\").exec()\n return\n msg = _(\"Auto assign text to case: \") + self.case['name']\n msg += _(\"\\nUsing \") + start_mark + _(\" and \") + end_mark + _(\"\\nIn files:\\n\")\n msg += filenames\n warning_msg = \"\"\n already_assigned = \"\"\n entries = 0\n cur = self.app.conn.cursor()\n for f in selected_files:\n cur.execute(\"select name, id, fulltext, memo, owner, date from source where id=?\",\n [f[0]])\n currentfile = cur.fetchone()\n text = currentfile[2]\n text_starts = [match.start() for match in re.finditer(re.escape(start_mark), text)]\n text_ends = [match.start() for match in re.finditer(re.escape(end_mark), text)]\n # Add new code linkage items to database\n already_assigned = \"\"\n for start_pos in text_starts:\n text_end_iterator = 0\n try:\n while start_pos >= text_ends[text_end_iterator]:\n text_end_iterator += 1\n except IndexError:\n text_end_iterator = -1\n warning_msg += _(\"Auto assign. Could not find an end mark: \") + f[1] + \" \" + end_mark + \"\\n\"\n if text_end_iterator >= 0:\n pos1 = text_ends[text_end_iterator]\n item = {'caseid': self.case['caseid'], 'fid': f[0],\n 'pos0': start_pos, 'pos1': pos1,\n 'owner': self.app.settings['codername'],\n 'date': datetime.datetime.now().astimezone().strftime(\"%Y-%m-%d %H:%M:%S\"), 'memo': \"\"}\n # Check if already assigned to case_text\n sql = \"select id from case_text where caseid=? and fid=? and pos0=? and pos1=?\"\n cur.execute(sql, [item['caseid'], item['fid'], item['pos0'], item['pos1']])\n res = cur.fetchone()\n if res is None:\n sql = \"insert into case_text (caseid,fid,pos0,pos1,owner,date,memo) values(?,?,?,?,?,?,?)\"\n cur.execute(sql, (item['caseid'], item['fid'], item['pos0'], item['pos1'],\n item['owner'], item['date'], item['memo']))\n entries += 1\n self.app.conn.commit()\n else:\n already_assigned = _(\"\\nAlready assigned.\")\n # Update messages and table widget\n self.get_files()\n self.fill_table()\n # Text file is loaded in browser then update the highlights\n self.load_case_text()\n self.highlight()\n msg += \"\\n\" + str(entries) + _(\" sections found.\")\n Message(self.app, _(\"File added to case\"), msg + \"\\n\" + warning_msg + \"\\n\" + already_assigned).exec()\n self.parent_textEdit.append(msg)\n self.parent_textEdit.append(warning_msg)\n self.app.delete_backup = False","def create_model(self):\n self.create_model_file()\n self.create_model_unit_test()\n self.add_model_to_list()\n self.readme_reminder()","def pick_up(self):","def update_vluln_table():","def build_sys_rec_model():\n print(\"building model...\")\n model = Merchant2VecModel()\n model.train(final_training=True)\n model.save_model()","def load_rentedout():","def SetModel( self, loader ):\n self.loader = loader\n self.adapter,tree,rows = self.RootNode( )\n self.listControl.integrateRecords( rows.values())\n self.activated_node = tree\n self.squareMap.SetModel( tree, self.adapter )\n self.RecordHistory()"],"string":"[\n \"def update_model(self):\\n pass # TODO: Implement this.\",\n \"def build_model():\",\n \"def update_model(self):\\n pass\",\n \"def updateModel(self):\\n pass\",\n \"def loadAdjustedModel(self):\\r\\n # Load model in GUI\\r\\n addModel(self.trcFilePath.replace('.trc','.osim'))\",\n \"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/data/analysis/user/make3FGLxml.py -O {}'.format(modelScript))\\n\\n # Create the model using Tyrel's script\\n galModel = os.path.join(self.diffpath, 'gll_iem_v06.fits')\\n isoModel = os.path.join(self.diffpath, 'iso_'+self.irf+'_v06.txt')\\n if (not os.path.isfile(galModel)) or (not os.path.isfile(isoModel)):\\n print(\\\"\\\\t=== Unable to find the diffuse models, check the variable '$FERMI_DIR' ===\\\")\\n return\\n if not os.path.isdir(self.extpath):\\n print(\\\"\\\\t=== Unable to find models of extended sources, check the variable '$LATEXTDIR' ===\\\")\\n return\\n if not os.path.isfile(self.fermicat):\\n # download it\\n print(\\\"\\\\t=== Downloading 3FGL catalog ===\\\")\\n os.system('wget https://fermi.gsfc.nasa.gov/ssc/data/access/lat/4yr_catalog/gll_psc_v16.fit -O {}'.format(self.fermicat))\\n\\n os.popen(\\\"python {} {} {} -o {} -G {} -g 'gll_iem_v06'\\\\\\n -I {} -i 'iso_source_v06' -e {} -r 5 -R 10 -ER 10\\\\\\n -s 9 -m False -GIF False\\\".format(modelScript, self.fermicat,\\n self.ft1, self.model, galModel, isoModel, self.extpath))\\n\\n # Add the target to the model\\n tmpName = self.model + '.tmp'\\n rfil = open(self.model, 'r')\\n wfil = open(tmpName, 'w')\\n # Copy the XML to the temporary model\\n wfil.writelines([l for l in rfil.readlines() if not l=='</source_library>']) # copy everything but the last line\\n wfil.write(' <source ROI_Center_Distance=\\\"0.00\\\" name=\\\"TARGET\\\" type=\\\"PointSource\\\">\\\\n')\\n wfil.write(' <spectrum type=\\\"PowerLaw2\\\">\\\\n')\\n wfil.write(' <parameter free=\\\"1\\\" max=\\\"1000\\\" min=\\\"1e-05\\\" name=\\\"Integral\\\" scale=\\\"1e-08\\\" value=\\\"0.3591824258\\\"/>\\\\n')\\n wfil.write(' <parameter free=\\\"1\\\" max=\\\"1\\\" min=\\\"-5\\\" name=\\\"Index\\\" scale=\\\"1\\\" value=\\\"-2.7\\\"/>\\\\n')\\n wfil.write(' <parameter free=\\\"0\\\" max=\\\"1000000\\\" min=\\\"20\\\" name=\\\"LowerLimit\\\" scale=\\\"1\\\" value=\\\"100\\\"/>\\\\n')\\n wfil.write('<parameter free=\\\"0\\\" max=\\\"1000000\\\" min=\\\"20\\\" name=\\\"UpperLimit\\\" scale=\\\"1\\\" value=\\\"100000\\\"/>\\\\n')\\n wfil.write(' </spectrum>\\\\n')\\n wfil.write(' <spatialModel type=\\\"SkyDirFunction\\\">\\\\n')\\n wfil.write(' <parameter free=\\\"0\\\" max=\\\"360.0\\\" min=\\\"-360.0\\\" name=\\\"RA\\\" scale=\\\"1.0\\\" value=\\\"'+str(self.ra)+'\\\"/>\\\\n')\\n wfil.write(' <parameter free=\\\"0\\\" max=\\\"360.0\\\" min=\\\"-360.0\\\" name=\\\"DEC\\\" scale=\\\"1.0\\\" value=\\\"'+str(self.dec)+'\\\"/>\\\\n')\\n wfil.write(' </spatialModel>\\\\n')\\n wfil.write(' </source>\\\\n')\\n wfil.write('</source_library>\\\\n')\\n rfil.close()\\n wfil.close()\\n\\n os.remove(self.model)\\n os.rename(tmpName, self.model)\\n \\n print(\\\"\\\\t=== Source model {} added ===\\\".format(self.model))\\n return\",\n \"def build(self):\\n labelled_documents = self.get_labelled_documents_queryset()\\n\\n self.model = self.build_model(labelled_documents)\\n self.save_model()\",\n \"def revision(self):\\n self.r3.reuse = self.r2\\n self.r3.case = self.case\\n self.r3.revise()\\n self.r2.predictionGenre = self.case.playlist_genre\\n self.r2.predictionSubGenre =self.case.playlist_subgenre\\n print()\",\n \"def model(self, new_model):\\n if self.locations.empty:\\n raise RuntimeError(\\\"Cannot create a model until locations exist\\\")\\n writer = ModelWriter(self, self.dismod_file)\\n new_model.write(writer)\\n writer.close()\",\n \"def __init__(self):\\n this = _diff.new_svn_patch_t()\\n try:\\n self.this.append(this)\\n except __builtin__.Exception:\\n self.this = this\",\n \"def reset(self):\\n self.vna.write(edit_list(self.model))\\n self.vna.write(clear_list(self.model))\",\n \"def save(self):\\n\\n if not self.revertable:\\n return\\n\\n state = {}\\n for x in self.toSave:\\n state[x] = deepcopy(self.toSave[x]())\\n\\n #made a new model, reparent it so it displays\\n state[\\\"model\\\"].reparentTo(base.render)\\n\\n #add it to the stack\\n self.stack.append(state)\\n\\n for s in self.stack:\\n s[\\\"model\\\"].setPos(s[\\\"model\\\"].getPos() + Vec3(0,0,-THING_REVERT_DISTANCE))\",\n \"def ClearModels(self):\\n self._modelFileNames = []\\n self._models = []\\n self.Modified(readAgain=True)\",\n \"def test_model_found(arguments):\\n ...\",\n \"def handle(self, *args, **kwargs):\\n # Part model\\n try:\\n print(\\\"Rebuilding Part objects\\\")\\n\\n from part.models import Part\\n Part.objects.rebuild()\\n except Exception:\\n print(\\\"Error rebuilding Part objects\\\")\\n\\n # Part category\\n try:\\n print(\\\"Rebuilding PartCategory objects\\\")\\n\\n from part.models import PartCategory\\n PartCategory.objects.rebuild()\\n except Exception:\\n print(\\\"Error rebuilding PartCategory objects\\\")\\n\\n # StockItem model\\n try:\\n print(\\\"Rebuilding StockItem objects\\\")\\n\\n from stock.models import StockItem\\n StockItem.objects.rebuild()\\n except Exception:\\n print(\\\"Error rebuilding StockItem objects\\\")\\n\\n # StockLocation model\\n try:\\n print(\\\"Rebuilding StockLocation objects\\\")\\n\\n from stock.models import StockLocation\\n StockLocation.objects.rebuild()\\n except Exception:\\n print(\\\"Error rebuilding StockLocation objects\\\")\\n\\n # Build model\\n try:\\n print(\\\"Rebuilding Build objects\\\")\\n\\n from build.models import Build\\n Build.objects.rebuild()\\n except Exception:\\n print(\\\"Error rebuilding Build objects\\\")\",\n \"def update_model(command):\\n namespace = app.main(command)\\n assert namespace.command == 'um' or namespace.command == \\\"updatemodel\\\"\",\n \"def test_po_migration(self):\\n PurchaseOrder = self.new_state.apps.get_model('order', 'purchaseorder')\\n for ii in range(10):\\n\\n po = PurchaseOrder.objects.get(reference=f\\\"{ii}-abcde\\\")\\n self.assertEqual(po.extra_lines.count(), 1)\\n self.assertEqual(po.lines.count(), 1)\\n\\n # TODO @matmair fix this test!!!\\n # SalesOrder = self.new_state.apps.get_model('order', 'salesorder')\\n # for ii in range(10):\\n # so = SalesOrder.objects.get(reference=f\\\"{ii}-xyz\\\")\\n # self.assertEqual(so.extra_lines, 1)\\n # self.assertEqual(so.lines.count(), 1)\",\n \"def __init__(self):\\n self.model = None\",\n \"def __init__(self):\\n self.model = None\",\n \"def model(self):\",\n \"def model(self):\",\n \"def model(self):\",\n \"def model(self):\",\n \"def model(self):\",\n \"def update(self,wsname,fname,storelist=[]):\\n import os\\n from ROOT import RooWorkspace, TFile\\n\\n # Create the ws with the model and data available\\n w = RooWorkspace(wsname,'Workspace')\\n wsImport = getattr(w,'import')\\n # Put the models \\n for rawtuple in self.__models.values():\\n model = rawtuple[0]\\n anythingelse = rawtuple[1:]\\n wsImport(model)\\n # Put whatever the user want to store\\n for _item in storelist:\\n wsImport(_item)\\n\\n # Check if the fname already exist\\n file_exist = os.path.isfile(fname)\\n if file_exist:\\n # Create a new auxiliar file, to provisionaly\\n # store the ws \\n auxfname = '_auxroot.root'\\n w.writeToFile(auxfname)\\n # Previously delete the old Workspace, if any\\n _rootfile = TFile(fname)\\n _rootfile.Delete(wsname+';*')\\n _rootfile.Delete(\\\"ProcessID*;*\\\")\\n _rootfile.Close()\\n # Open the auxiliary file\\n _aux = TFile(auxfname)\\n # and copy the ws to the rootfile\\n w = _aux.Get(wsname)\\n # and copy the ws to the rootfile\\n w.writeToFile(fname,False)\\n\\n if file_exist:\\n # And closing and removing auxfile\\n _aux.Close()\\n os.remove(auxfname)\",\n \"def onBuildModels(self):\\n if self.refSeriesNumber != '-1':\\n ref = self.refSeriesNumber\\n refLongName = self.seriesMap[ref]['LongName']\\n labelNodes = slicer.util.getNodes('*'+refLongName+'*-label*')\\n\\n numNodes = slicer.mrmlScene.GetNumberOfNodesByClass( \\\"vtkMRMLModelHierarchyNode\\\" )\\n outHierarchy = None\\n\\n for n in xrange(numNodes):\\n node = slicer.mrmlScene.GetNthNodeByClass( n, \\\"vtkMRMLModelHierarchyNode\\\" )\\n if node.GetName() == 'mpReview-'+refLongName:\\n outHierarchy = node\\n break\\n\\n # Remove the previous models\\n if outHierarchy:\\n collection = vtk.vtkCollection()\\n outHierarchy.GetChildrenModelNodes(collection)\\n n = collection.GetNumberOfItems()\\n if n != 0:\\n for i in xrange(n):\\n modelNode = collection.GetItemAsObject(i)\\n slicer.mrmlScene.RemoveNode(modelNode)\\n\\n # if models hierarchy does not exist, create it.\\n else:\\n outHierarchy = slicer.vtkMRMLModelHierarchyNode()\\n outHierarchy.SetScene( slicer.mrmlScene )\\n outHierarchy.SetName( 'mpReview-'+refLongName )\\n slicer.mrmlScene.AddNode( outHierarchy )\\n\\n progress = self.makeProgressIndicator(len(labelNodes))\\n step = 0\\n for label in labelNodes.values():\\n labelName = label.GetName().split(':')[1]\\n structureName = labelName[labelName[:-6].rfind(\\\"-\\\")+1:-6]\\n # Only save labels with known structure names\\n if any(structureName in s for s in self.structureNames):\\n parameters = {}\\n parameters[\\\"InputVolume\\\"] = label.GetID()\\n parameters['FilterType'] = \\\"Sinc\\\"\\n parameters['GenerateAll'] = True\\n\\n parameters[\\\"JointSmoothing\\\"] = False\\n parameters[\\\"SplitNormals\\\"] = True\\n parameters[\\\"PointNormals\\\"] = True\\n parameters[\\\"SkipUnNamed\\\"] = True\\n\\n # create models for all labels\\n parameters[\\\"StartLabel\\\"] = -1\\n parameters[\\\"EndLabel\\\"] = -1\\n\\n parameters[\\\"Decimate\\\"] = 0\\n parameters[\\\"Smooth\\\"] = 0\\n\\n parameters[\\\"ModelSceneFile\\\"] = outHierarchy\\n\\n progress.labelText = '\\\\nMaking Model for %s' % structureName\\n progress.setValue(step)\\n if progress.wasCanceled:\\n break\\n\\n try:\\n modelMaker = slicer.modules.modelmaker\\n self.CLINode = slicer.cli.run(modelMaker, self.CLINode,\\n parameters, wait_for_completion=True)\\n except AttributeError:\\n qt.QMessageBox.critical(slicer.util.mainWindow(),'Editor', 'The ModelMaker module is not available<p>Perhaps it was disabled in the application settings or did not load correctly.')\\n step += 1\\n progress.close()\\n #\\n\\n if outHierarchy:\\n collection = vtk.vtkCollection()\\n outHierarchy.GetChildrenModelNodes(collection)\\n n = collection.GetNumberOfItems()\\n if n != 0:\\n for i in xrange(n):\\n modelNode = collection.GetItemAsObject(i)\\n displayNode = modelNode.GetDisplayNode()\\n displayNode.SetSliceIntersectionVisibility(1)\\n displayNode.SetSliceIntersectionThickness(2)\\n self.modelsVisibilityButton.checked = False\\n self.updateViewRenderer()\",\n \"def test_persistence_old_model(self):\\n loaded = PoincareModel.load(datapath('poincare_test_3.4.0'))\\n self.assertEqual(loaded.kv.syn0.shape, (239, 2))\\n self.assertEqual(len(loaded.kv.vocab), 239)\\n self.assertEqual(loaded.size, 2)\\n self.assertEqual(len(loaded.all_relations), 200)\",\n \"def load_cobra_model(self, model):\\n self.model = ModelPro(model)\\n for g in self.model.genes:\\n if self.genes_dir:\\n g.root_dir = self.genes_dir\\n g.protein.pdb_file_type = self.pdb_file_type\\n self.genes = self.model.genes\\n\\n log.info('{}: loaded model'.format(model.id))\\n log.info('{}: number of reactions'.format(len(self.model.reactions)))\\n log.info('{}: number of reactions linked to a gene'.format(ssbio.core.modelpro.true_num_reactions(self.model)))\\n log.info('{}: number of genes (excluding spontaneous)'.format(ssbio.core.modelpro.true_num_genes(self.model,\\n custom_spont_id=self.custom_spont_id)))\\n log.info('{}: number of metabolites'.format(len(self.model.metabolites)))\\n log.warning('IMPORTANT: All Gene objects have been transformed into GenePro '\\n 'objects, and will be for any new ones')\",\n \"def build_model(self):\\n pass\",\n \"def build_model(self):\\n pass\",\n \"def init_model(self):\\n pass\",\n \"def run(self):\\r\\n # Close any open models\\r\\n self.cleanUp()\\r\\n # Dynamically select file to preview\\r\\n self.selectTrial() \\r\\n # Add adjusted COM (RRA/CMC) model\\r\\n self.loadAdjustedModel()\\r\\n # Hide the markers from view\\r\\n self.hideModelMarkers()\\r\\n # Load CMC motion to model\\r\\n self.loadCMCMotion()\",\n \"def restore(self, model_file, head_i=0, trunk=False):\\n if trunk:\\n self.model_trunk.load_weights(model_file)\\n else:\\n self.models[head_i].load_weights(model_file)\\n self.model = self.models[head_i]\",\n \"def test_updating_the_project(self):\\n modified_po = copy.deepcopy(base_purchase_order)\",\n \"def test_override_model(self):\\n\\n class MyModel(FileObject):\\n def render(self):\\n return self.content\\n\\n class MyFBO(FBO):\\n path = TEST_FILES_ROOT\\n metadata = FileObject.MetadataInFileHead\\n model = MyModel\\n\\n self.assertEqual(\\n 'My little explicit YAML test.\\\\n',\\n MyFBO().objects.get(name='test2.rst').render(),\\n )\",\n \"def main(quiet=False):\\n if quiet:\\n output_stream = StringIO()\\n else:\\n output_stream = sys.stdout\\n\\n newpath = r'%s/models' % os.getcwdu()\\n if not os.path.exists(newpath): os.makedirs(newpath)\\n newpath = r'%s/out' % os.getcwdu()\\n if not os.path.exists(newpath): os.makedirs(newpath)\\n existing = sorted(os.listdir('%s/%s' % (os.getcwdu(), 'models'))) \\n\\n urls = [\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/parameters.fits.gz',\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/2J.fits',\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/2H.fits',\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/2K.fits',\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/I1.fits',\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/I2.fits',\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/I3.fits',\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/I4.fits',\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/M1.fits',\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/M2.fits',\\n 'http://www.mpia-hd.mpg.de/~robitaille/share/andreas/M3.fits',\\n 'http://caravan.astro.wisc.edu/protostars/files/extinction_law.tar.gz'\\n ]\\n file_names = [\\n 'models/parameters.fits.gz',\\n 'models/2J.fits',\\n 'models/2H.fits',\\n 'models/2K.fits',\\n 'models/I1.fits',\\n 'models/I2.fits',\\n 'models/I3.fits',\\n 'models/I4.fits',\\n 'models/M1.fits',\\n 'models/M2.fits',\\n 'models/M3.fits',\\n 'models/extinction_law.tar.gz']\\n\\n for i in range(len(urls)):\\n if not os.path.isfile(file_names[i]):\\n f = open(file_names[i], 'wb')\\n f.write(urllib2.urlopen(urls[i]).read())\\n f.close()\\n print('Downloaded %s from %s' % (file_names[i],urls[i]), file=output_stream)\\n\\n if not os.path.isfile('modesl/extinction_law.ascii'):\\n f = tarfile.open('models/extinction_law.tar.gz', 'r:gz')\\n try: f.extractall()\\n finally: f.close()\",\n \"def snapshot(self):\\n for ref, (m, _) in self._models.items():\\n m.snapshot = not m.snapshot\\n (self, root, doc, comm) = state._views[ref]\\n if comm and 'embedded' not in root.tags:\\n push(doc, comm)\",\n \"def test_Base_model(self):\\n with patch('sys.stdout', new=StringIO()) as f:\\n HBNBCommand().onecmd(\\\"create BaseModel\\\")\\n id = f.getvalue().strip()\\n self.assertTrue(type(f), str)\\n self.assertEqual(len(id), 36)\\n\\n with patch('sys.stdout', new=StringIO()) as f:\\n HBNBCommand().onecmd(\\\"update BaseModel \\\" + str(id) + \\\" name Manga\\\")\\n self.assertTrue(type(f), str)\\n self.assertEqual(f.getvalue().strip(), \\\"\\\")\\n\\n with patch('sys.stdout', new=StringIO()) as f:\\n HBNBCommand().onecmd(\\\"show BaseModel \\\" + str(id))\\n self.assertTrue(\\\"name\\\" in f.getvalue().strip())\\n self.assertTrue(\\\"Manga\\\" in f.getvalue().strip())\",\n \"def __init__(self, modelpath):\\n self.modelpath = Path(modelpath)\\n if not self.modelpath.is_file():\\n raise FileNotFoundError(f\\\"{self.modelpath} does not exist\\\")\\n self.model = Word2Vec.load(modelpath)\\n elems = self.modelpath.name.rsplit('.', 1)[0].split('-')[-3:]\\n self.r = int(elems[0][1:])\\n self.p = float(elems[1][1:])\\n self.q = float(elems[2][1:])\\n print(f'{len(self.model.wv.index2word)} sub-structures with dimension {self.model.vector_size}')\",\n \"def __init__(self, model):\\n\\t\\tself.model = model\",\n \"def runModel(quickLogger,\\n\\t base,\\n modelFile=\\\"\\\",\\n\\t irfs=\\\"P7SOURCE_V6\\\",\\n run=True):\\n \\n if(modelFile):\\n model = modelFile\\n else:\\n model = base+\\\"_likeMinuit.xml\\\"\\n\\n\\n try:\\n checkForFiles(quickLogger,\\n [base+\\\"_srcMaps.fits\\\",\\n model,\\n base+\\\"_ltcube.fits\\\",\\n base+\\\"_BinnedExpMap.fits\\\"])\\n except(FileNotFound):\\n quickLogger.critical(\\\"One or more needed files do not exist.\\\")\\n return\\n\\n model_map['srcmaps'] = base+\\\"_srcMaps.fits\\\"\\n model_map['srcmdl'] = model\\n model_map['outfile'] = base+\\\"_modelMap.fits\\\"\\n model_map['expcube'] = base+\\\"_ltcube.fits\\\"\\n model_map['irfs'] = irfs\\n model_map['bexpmap'] = base+\\\"_BinnedExpMap.fits\\\"\\n \\n runCommand(model_map,quickLogger,run)\",\n \"def update_view(self):\\n for row in self.view.obj_list:\\n for obj in row:\\n obj._update(self.model)\",\n \"def create_models( self ):\",\n \"def save(self):\\n self._initial_vms = self.selected_vms\",\n \"def _build_model(self):\\n raise NotImplementedError()\",\n \"def load_model(self) -> Any:\",\n \"def test08(self):\\n model = self.setup_model02()\\n model.x[1].fix(1)\\n\\n model.dual[model.g] = 1\\n model.ipopt_zL_out[model.x[1]] = 1\\n model.ipopt_zL_out[model.x[2]] = 1\\n model.ipopt_zU_out[model.x[1]] = 1\\n model.ipopt_zU_out[model.x[2]] = 1\\n\\n to_json(model, fname=self.fname, wts=StoreSpec.suffix())\\n\\n model.dual[model.g] = 10\\n model.ipopt_zL_out[model.x[1]] = 10\\n model.ipopt_zL_out[model.x[2]] = 10\\n model.ipopt_zU_out[model.x[1]] = 10\\n model.ipopt_zU_out[model.x[2]] = 10\\n model.g.deactivate()\\n model.x[1].setlb(-4)\\n model.x[1].unfix()\\n model.x[2].fix(6)\\n\\n from_json(model, fname=self.fname, wts=StoreSpec.suffix())\\n assert value(model.x[1]) == 1\\n assert value(model.x[2]) == 6\\n assert not model.x[1].fixed\\n assert model.x[2].fixed\\n assert not model.g.active\\n assert model.dual[model.g] == 1\\n assert model.ipopt_zL_out[model.x[1]] == 1\\n assert model.ipopt_zL_out[model.x[2]] == 1\\n assert model.ipopt_zU_out[model.x[1]] == 1\\n assert model.ipopt_zU_out[model.x[2]] == 1\\n assert model.x[1].lb == -4\",\n \"def main():\\n\\n # Create argument parser\\n parser = ArgumentParser()\\n parser.add_argument('datadir', type=str, help='Directory of LC files')\\n parser.add_argument('metatable', type=str,\\n help='Metatable containing each object, redshift, peak time guess, mwebv, object type')\\n parser.add_argument('--zpt', type=float, default=DEFAULT_ZPT, help='Zero point of LCs')\\n parser.add_argument('--lm', type=float, default=DEFAULT_LIM_MAG, help='Survey limiting magnitude')\\n parser.add_argument('--outdir', type=str, default='./products/',\\n help='Path in which to save the LC data (single file)')\\n args = parser.parse_args()\\n\\n objs, redshifts, obj_types, peaks, ebvs = read_in_meta_table(args.metatable)\\n\\n # Grab all the LC files in the input directory\\n file_names = []\\n for obj in objs:\\n file_name = args.datadir + 'PS1_PS1MD_' + obj + '.snana.dat'\\n file_names.append(file_name)\\n\\n # Create a list of LC objects from the data files\\n lc_list = read_in_LC_files(file_names, objs)\\n\\n # This needs to be redone when retrained\\n # TODO: Need to change this whenever you retrain...\\n filt_dict = {'g': 0, 'r': 1, 'i': 2, 'z': 3}\\n wvs = np.asarray([5460, 6800, 7450, 8700])\\n\\n # Update the LC objects with info from the metatable\\n my_lcs = []\\n for i, my_lc in enumerate(lc_list):\\n my_lc.add_LC_info(zpt=args.zpt, mwebv=ebvs[i],\\n redshift=redshifts[i], lim_mag=args.lm,\\n obj_type=obj_types[i])\\n my_lc.get_abs_mags()\\n my_lc.sort_lc()\\n pmjd = my_lc.find_peak(peaks[i])\\n my_lc.shift_lc(pmjd)\\n my_lc.correct_time_dilation()\\n my_lc.filter_names_to_numbers(filt_dict)\\n my_lc.correct_extinction(wvs)\\n my_lc.cut_lc()\\n my_lc.make_dense_LC(4)\\n my_lcs.append(my_lc)\\n save_lcs(my_lcs, args.outdir)\",\n \"def initialize_model(self):\\n pass\",\n \"def add(self):\\r\\n self._svn('add')\",\n \"def test07(self):\\n model = self.setup_model02()\\n model.x[1].fix(1)\\n wts = StoreSpec.isfixed()\\n to_json(model, fname=self.fname, human_read=True, wts=wts)\\n model.g.deactivate()\\n model.x[1].setlb(-4)\\n model.x[1].unfix()\\n model.x[2].fix(6)\\n from_json(model, fname=self.fname, wts=wts)\\n assert value(model.x[1]) == 1\\n assert model.x[1].lb == -4\\n assert value(model.x[2]) == 6\\n assert model.x[1].fixed\\n assert not model.x[2].fixed\\n assert not model.g.active\",\n \"def skel_model(action, install_path_mp, install_path_zfs, jname):\\n # init vars\\n # mp - mount point, zfs - zfs point\\n skel_path_mp = '%s-SKELETON' % install_path_mp\\n skel_path_zfs = '%s-SKELETON' % install_path_zfs\\n rw_path_mp = '%s-RW' % install_path_mp\\n rw_path_zfs = '%s-RW' % install_path_zfs\\n \\n if action == 'init':\\n# create SKELETON MODEL\\n# http://www.freebsd.org/doc/en_US.ISO8859-1/books/handbook/jails-application.html\\n log(\\\" INFO: Init BASE-SKELETON zfs START\\\")\\n# Create a skeleton for the read-write portion of the system\\n os.system('zfs create %s' % skel_path_zfs)\\n os.system('zfs set mountpoint=%s %s' % (skel_path_mp, skel_path_zfs))\\n os.system('zfs create %s' % rw_path_zfs)\\n os.system('zfs set mountpoint=%s %s' % (rw_path_mp, rw_path_zfs))\\n\\n os.system('mkdir -p %s/home %s/usr-X11R6 %s/distfiles %s/usr-share-keys/pkg' % (skel_path_mp, skel_path_mp, skel_path_mp, skel_path_mp))\\n os.system('mv %s/etc %s' % (install_path_mp, skel_path_mp ))\\n os.system('mv %s/usr/local %s/usr-local' % (install_path_mp, skel_path_mp ))\\n os.system('mv %s/tmp %s' % (install_path_mp, skel_path_mp ))\\n os.system('mv %s/var %s' % (install_path_mp, skel_path_mp ))\\n os.system('mv %s/root %s' % (install_path_mp, skel_path_mp ))\\n# mergemaster to install missing configuration files. Then, remove the the extra directories that mergemaster creates:\\n# os.system('mergemaster -t %s/var/tmp/temproot -D %s -i' % (skel_path, skel_path))\\n# os.system('rm -R %(key)s/bin %(key)s/boot %(key)s/lib %(key)s/libexec %(key)s/mnt %(key)s/proc %(key)s/rescue %(key)s/sbin %(key)s/sys %(key)s/usr %(key)s/dev' % {'key': skel_path})\\n# Now, symlink the read-write file system to the read-only file system. Ensure that the symlinks are created in the correct s/ locations as the creation of directories in the wrong locations will cause the installation to fail.\\n os.chdir('%s' % install_path_mp)\\n os.system('mkdir SROOT')\\n os.system('ln -s SROOT/etc etc')\\n os.system('ln -s SROOT/home home')\\n os.system('ln -s SROOT/root root')\\n os.system('ln -s /SROOT/usr-local usr/local')\\n os.system('ln -s /SROOT/usr-share-keys usr/share/keys')\\n os.system('ln -s /SROOT/usr-X11R6 usr/X11R6')\\n os.system('ln -s /SROOT/distfiles usr/ports/distfiles')\\n os.system('ln -s SROOT/tmp tmp')\\n os.system('ln -s SROOT/var var')\\n# Create a generic /home/j/skel/etc/make.conf containing this line\\n os.system('echo \\\\\\\"WRKDIRPREFIX?= /SROOT/portbuild\\\\\\\" > %s/etc/make.conf' % skel_path_mp )\\n# Create zfs BASE-SKELETON snapshot which will be used for installation \\n os.system('zfs snapshot %s@install' % skel_path_zfs)\\n log(\\\" INFO: Init BASE-SKELETON zfs FINISH\\\")\\n \\n# install SKELETON jail \\n if action == 'install':\\n# install RW fs for jail\\n os.system('zfs send %s/BASE-SKELETON@install | zfs receive -F %s/BASE-RW/%s' % (jzfs, jzfs, jname))\\n# remove receive snapshot \\n os.system('zfs destroy %s/BASE-RW/%s@install' % (jzfs, jname))\\n# create jail local config - mount skel model for jail hosme dir\\n if jname == 'BASE-update':\\n os.system('echo \\\\\\\"%sBASE %s%s nullfs rw 0 0\\\\\\\" > %sBASE-RW/%s/etc/fstab' % (jpath, jpath, jname, jpath, jname))\\n else:\\n os.system('echo \\\\\\\"%sBASE %s%s nullfs ro 0 0\\\\\\\" > %sBASE-RW/%s/etc/fstab' % (jpath, jpath, jname, jpath, jname))\\n \\n os.system('echo \\\\\\\"%sBASE-RW/%s %s%s/SROOT nullfs rw 0 0\\\\\\\" >> %sBASE-RW/%s/etc/fstab' % (jpath, jname, jpath, jname, jpath, jname))\\n temp_add_cfg = ['### BASE mount settings ###', 'mount.fstab=\\\"%sBASE-RW/%s/etc/fstab\\\";' % (jpath, jname), 'mount.devfs;']\\n return temp_add_cfg\",\n \"def update(self):\\n \\n dbpath, config = self._start()\\n \\n self.config.obo = check_file(config.obo, dbpath, \\\"obo\\\") \\n desc_file = check_file(config.model_descriptions, dbpath,\\n \\\"model_descriptions\\\", allow_none=True) \\n phen_file = check_file(config.model_phenotypes, dbpath,\\n \\\"model_phenotypes\\\", allow_none=True)\\n \\n summary = self._update(desc_file, phen_file) \\n if len(summary[\\\"incorrect_ids\\\"]) == 0 and not config.skip_compute:\\n self._compute(models=summary[\\\"new_phenotypes\\\"])\\n \\n self._end()\",\n \"def init_from_scratch(args, train_exs, dev_exs):\\n \\n # Build a dictionary from the data sqls+queries (train/dev splits)\\n logger.info('-' * 100)\\n logger.info('Build vocab')\\n \\n vocab = build_vocab(train_exs + dev_exs, args)\\n logger.info('Num words = %d' % vocab.size())\\n \\n # Initialize model\\n model = CopyNet(args, vocab)\\n logger.info('-' * 100)\\n logger.info('Model Architecture')\\n logger.info(model)\\n if args.embedding_file:\\n model.load_embeddings(vocab.tokens(), args.embedding_file)\\n \\n return model, vocab\",\n \"def test_make_update_script_for_model(self):\\n\\n self.setup_model_params()\\n self.write_file(self.first_model_path, self.base_source)\\n self.write_file(self.second_model_path, self.base_source + self.model_source)\\n\\n source_script = self.pyscript.make_update_script_for_model(\\n engine=self.engine,\\n oldmodel=load_model('testmodel_first:meta'),\\n model=load_model('testmodel_second:meta'),\\n repository=self.repo_path,\\n )\\n\\n self.assertTrue(\\\"['User'].create()\\\" in source_script)\\n self.assertTrue(\\\"['User'].drop()\\\" in source_script)\",\n \"def test_edit_baseline(self):\\n baseline = createContentInContainer(self.folder, 'stageable_type')\\n working_copy = self.do_checkout(baseline)\\n baseline.title = u'new title'\\n\\n # XXX: aq_base is necessary to prevent error:\\n # \\\"TypeError: Can't pickle objects in acquisition wrappers.\\\"\\n # in CMFEdition\\n notify(ObjectModifiedEvent(aq_base(baseline)))\\n\\n relation = get_checkout_relation(baseline)\\n annotation = IWCAnnotator(baseline).get_relation()\\n self.assertIsNotNone(relation)\\n self.assertEqual(relation, annotation)\",\n \"def populate_models(tree) :\\n\\te_root = tree.getroot()\\n\\tpopulate_crisis(e_root)\\n\\tpopulate_person(e_root)\\n\\tpopulate_org(e_root)\",\n \"def testGetReigsteredModel(self):\\n from soc.models.student import Student\\n model = models_logic.getModel('soc.models.student.Student')\\n self.assertEqual(model, Student)\",\n \"def generateModelEdit(data):\\n\\n global h_model\\n h_model.append(\\\"\\\")\\n h_model.append(\\\"\\\\t// In-Table edit support:\\\")\\n h_model.append(\\\"\\\\tvoid store(const QString &sign, const QString &code);\\\")\\n generateModelFlags(data)\\n generateModelSetData(data)\",\n \"def __init__(self):\\n self.incidents_models = {}\\n self.risks = []\\n self.incidents_models = None\",\n \"def main():\\r\\n \\r\\n world = WorldModel()\\r\\n #uncomment these lines and comment out the next 2 if you want to use the\\r\\n #full Baxter model\\r\\n #print \\\"Loading full Baxter model (be patient, this will take a minute)...\\\"\\r\\n #world.loadElement(os.path.join(model_dir,\\\"baxter.rob\\\"))\\r\\n print \\\"Loading simplified Baxter model...\\\"\\r\\n world.loadElement(os.path.join(model_dir,\\\"baxter_col.rob\\\"))\\r\\n print \\\"Loading Kiva pod model...\\\"\\r\\n world.loadElement(os.path.join(model_dir,\\\"kiva_pod/model.obj\\\"))\\r\\n print \\\"Loading plane model...\\\"\\r\\n world.loadElement(os.path.join(model_dir,\\\"plane.env\\\"))\\r\\n \\r\\n #shift the Baxter up a bit (95cm)\\r\\n Rbase,tbase = world.robot(0).getLink(0).getParentTransform()\\r\\n world.robot(0).getLink(0).setParentTransform(Rbase,(0,0,0.95))\\r\\n \\r\\n #translate pod to be in front of the robot, and rotate the pod by 90 degrees \\r\\n Trel = (so3.rotation((0,0,1),math.pi/2),[1.1,0,0])\\r\\n T = world.rigidObject(0).getTransform()\\r\\n world.rigidObject(0).setTransform(*se3.mul(Trel,T))\\r\\n \\r\\n #run the visualizer\\r\\n visualizer = MyGLViewer(world)\\r\\n visualizer.run()\",\n \"def updateTree(self):\\n self.reset()\\n self.resetTree() \\n self.read()\",\n \"def _screener_init(self):\\n subject = 0\\n self.model.uu.remove(subject) # selects from untested and performs e\\n self.model.tt.append(subject)\\n self.model.b -= (self.cz + self.cy) # update budget\\n self.model.z[subject] = self.z[subject] # update model\\n self.model.y[subject] = self.y[subject]\",\n \"def svn_info_t_copyfrom_rev_get(svn_info_t_self): # real signature unknown; restored from __doc__\\n pass\",\n \"def repo_init(_request):\\n python = models.Repository.query(models.Repository.name == 'Python').get()\\n if python is None:\\n python = models.Repository(name='Python', url=SVN_ROOT)\\n python.put()\\n pybranches = []\\n else:\\n pybranches = list(models.Branch.query(models.Branch.repo_key == python.key))\\n for category, name, url in BRANCHES:\\n url = python.url + url\\n for br in pybranches:\\n if (br.category, br.name, br.url) == (category, name, url):\\n break\\n else:\\n br = models.Branch(repo_key=python.key, repo_name='Python',\\n category=category, name=name, url=url)\\n br.put()\\n return HttpResponseRedirect(reverse(repos))\",\n \"def build(self):\\n raise Exception(\\\" not implemented in base model\\\")\",\n \"def __init__(self, model):\\n self.model = model\",\n \"def __init__(self, model):\\n self.model = model\",\n \"def __init__(self, model):\\n self.model = model\",\n \"def __init__(self, model):\\n self.model = model\",\n \"def save(self, *args, **kwargs):\\n self.pk = None\\n super(AbstractRevision, self).save(*args, **kwargs)\\n self.tracked_model.current_revision = self\\n self.tracked_model.save()\",\n \"def edited_file_locations(self):\",\n \"def dump_model(self):\",\n \"def load_model():\\n global obj\\n obj = NutritionTableDetector()\\n print(\\\"Weights Loaded!\\\")\",\n \"def testSave(self):\\n\\n # Generate temp file path\\n index = os.path.join(tempfile.gettempdir(), \\\"bm25\\\")\\n os.makedirs(index, exist_ok=True)\\n\\n model = self.method(\\\"bm25\\\")\\n model.save(index)\\n model.load(index)\",\n \"def _populate_table_files(model):\\n # Get list of all files\\n if model is Software:\\n paths_found = {path.path for path in _recursive_scan(app.config['DEVICE_SW_DRIVE'], '.exe')}\\n elif model is File:\\n paths_found = {path.path for path in _recursive_scan()}\\n else:\\n raise TypeError('Type of File or Software expected as model.')\\n paths_existing = {file.path for file in model.query.all()}\\n\\n # Paths that have been deleted from host but still exist in DB\\n for path in paths_existing - paths_found:\\n model.query.filter_by(path=path).update({'stored': False})\\n\\n # Paths that are found and exists in DB\\n for path in paths_found.intersection(paths_existing):\\n model.query.filter_by(path=path).update({'stored': True})\\n\\n # Paths found that doesn't exist in the DB\\n paths_new = paths_found - paths_existing\\n for path in paths_new:\\n name = os.path.split(path)[1]\\n new_model = model(name=name, path=path)\\n db.session.add(new_model)\\n\\n db.session.commit()\",\n \"def model_input(step=0.1):\\n model = np.loadtxt('start_model.dat',dtype={'names': ('H', 'VP','VS','RHO','QP','QS',\\\\\\n 'ETAP','ETAS','FREFP','FREFS'),'formats': ('f4', 'f4','f4','f4',\\\\\\n 'f4','f4','f4','f4','f4','f4')}, skiprows=1)\\n \\n f = open('model96_input.tmp', 'w+')\\n f.write('model_step96.in\\\\nIsotropic model\\\\n0\\\\n')\\n d = np.loadtxt('cumul_depths.tmp')\\n for i in np.arange(len(d)):\\n for k, s in enumerate(np.arange(0,d[-1],step)):\\n if s < d[i] and i==0:\\n f.write('%s %s %s %s %s %s %s %s %s %s\\\\n'\\n %(step, model['VP'][i], model['VS'][i], model['RHO'][i],\\\\\\n model['QP'][i], model['QS'][i], model['ETAP'][i], model['ETAS'][i],\\\\\\n model['FREFP'][i], model['FREFS'][i]))\\n if i > 0:\\n if s < d[i] and s > d[i-1]:\\n f.write('%s %s %s %s %s %s %s %s %s %s\\\\n'\\n %(step, model['VP'][i], model['VS'][i], model['RHO'][i],\\\\\\n model['QP'][i], model['QS'][i], model['ETAP'][i], model['ETAS'][i],\\\\\\n model['FREFP'][i], model['FREFS'][i]))\\n f.close()\\n os.system(\\\"mkmod96 < model96_input.tmp\\\")\\n print (\\\">> Model_step96.in is ready... next step is comp_disp.bash\\\")\\n print ('>> nlayers =', k)\\n print (\\\">> Change nlayer in eigenfucntion_*.bash!!!!\\\")\\n print (\\\">> mkmod96\\\")\",\n \"def load_model(self):\\n pass\",\n \"def test_update_list_changes_data(qtbot):\\n # Given\\n model = SourcesModel()\\n assert model.rowCount() == 0\\n\\n sources = []\\n source = Source(\\\"I001\\\", \\\"Test\\\", \\\"Person\\\", \\\"Pub\\\", \\\"Abbr\\\")\\n sources.append(source)\\n\\n # When\\n with qtbot.waitSignals([model.modelAboutToBeReset, model.modelReset]):\\n model.update_list(sources)\\n\\n # Then\\n assert model.rowCount() == 1\",\n \"def update_model(self, budget=0):\\n self._log(\\\"start updateing model with budget {}\\\".format(budget))\\n\\n # check if enough observations available for model building\\n if len(self.searchspace.keys()) > len(self.get_metrics_array(budget=budget)):\\n self._log(\\n \\\"not enough observations available to build with budget {} yet. At least {} needed, got {}\\\".format(\\n budget,\\n len(self.searchspace.keys()),\\n len(self.get_metrics_array(budget=budget)),\\n )\\n )\\n return\\n\\n # create model without any data\\n model = clone(self.base_model)\\n\\n Xi, yi = self.get_XY(\\n budget=budget,\\n interim_results=self.interim_results,\\n interim_results_interval=self.interim_results_interval,\\n )\\n\\n # fit model with data\\n model.fit(Xi, yi)\\n\\n self._log(\\\"fitted model with data\\\")\\n\\n # update model of budget\\n self.models[budget] = model\",\n \"def refresh(self):\\n\\n assets_model = self.data[\\\"model\\\"][\\\"assets\\\"]\\n assets_model.clear()\\n\\n has = {\\\"children\\\": False}\\n\\n project = io.ObjectId(os.environ[\\\"MINDBENDER__PROJECT\\\"])\\n assets = io.find({\\\"type\\\": \\\"asset\\\", \\\"parent\\\": project})\\n for asset in sorted(assets, key=lambda i: i[\\\"name\\\"]):\\n item = QtWidgets.QListWidgetItem(asset[\\\"name\\\"])\\n item.setData(QtCore.Qt.ItemIsEnabled, True)\\n item.setData(DocumentRole, asset)\\n assets_model.addItem(item)\\n has[\\\"children\\\"] = True\\n\\n if not has[\\\"children\\\"]:\\n item = QtWidgets.QListWidgetItem(\\\"No assets found\\\")\\n item.setData(QtCore.Qt.ItemIsEnabled, False)\\n assets_model.addItem(item)\\n\\n assets_model.setFocus()\\n assets_model.setCurrentRow(0)\\n self.data[\\\"button\\\"][\\\"load\\\"].hide()\\n self.data[\\\"button\\\"][\\\"stop\\\"].hide()\",\n \"def push_model(config):\\n util_logger.info('Backing up the model files to wandb')\\n martifact = wandb.Artifact('%s_model' % config.wandb_name, type='model')\\n martifact.add_dir(os.path.join(config.output_dir,\\\"best_model\\\"))\\n #matrifact.add_file(os.path.join(config.output_dir,\\\"trainer_config.json\\\"))\\n wandb.log_artifact(martifact)\",\n \"def object_cmd(args):\\n if len(args) >= 1:\\n a = [ args[0], 0 ]\\n model_cmd(a)\\n else:\\n error(\\\"Usage...\\\")\",\n \"def test_import_crisis(self):\\r\\n tree = self.crisis_tree\\r\\n root = tree.getroot()\\r\\n assert importer.put_objects(root) == True\",\n \"def test_xmlrpc_ir_model_search(self):\\n o = self.xmlrpc_object\\n db_name = common.get_db_name()\\n ids = o.execute(db_name, self.admin_uid, 'admin', 'ir.model', 'search', [])\\n self.assertIsInstance(ids, list)\\n ids = o.execute(db_name, self.admin_uid, 'admin', 'ir.model', 'search', [], {})\\n self.assertIsInstance(ids, list)\",\n \"def test_make_update_script_direction(self):\\n\\n self.setup_model_params()\\n self.write_file(self.first_model_path, self.base_source)\\n self.write_file(self.second_model_path, self.base_source + self.model_source)\\n\\n source_script = self.pyscript.make_update_script_for_model(\\n engine=self.engine,\\n oldmodel=load_model('testmodel_first:meta'),\\n model=load_model('testmodel_second:meta'),\\n repository=self.repo_path,\\n )\\n\\n self.assertTrue(0\\n < source_script.find('upgrade')\\n < source_script.find(\\\"['User'].create()\\\")\\n < source_script.find('downgrade')\\n < source_script.find(\\\"['User'].drop()\\\"))\",\n \"def pickUp(self):\\n pos = self.getRoverLocation()\\n item = self.map[pos.y,pos.x]\\n if type(item) == Part:\\n self.inventory.addPart(str(item))\\n self.map[pos.y,pos.x] = None\",\n \"def _prepare_model(model):\\n\\n # Ensure there is at least 1 load combination to solve if the user didn't define any\\n if model.LoadCombos == {}:\\n # Create and add a default load combination to the dictionary of load combinations\\n model.LoadCombos['Combo 1'] = LoadCombo('Combo 1', factors={'Case 1':1.0})\\n \\n # Generate all meshes\\n for mesh in model.Meshes.values():\\n if mesh.is_generated == False:\\n mesh.generate()\\n\\n # Activate all springs and members for all load combinations\\n for spring in model.Springs.values():\\n for combo_name in model.LoadCombos.keys():\\n spring.active[combo_name] = True\\n \\n # Activate all physical members for all load combinations\\n for phys_member in model.Members.values():\\n for combo_name in model.LoadCombos.keys():\\n phys_member.active[combo_name] = True\\n \\n # Assign an internal ID to all nodes and elements in the model. This number is different from the name used by the user to identify nodes and elements.\\n _renumber(model)\",\n \"def load_full_model(self, session, model_dir):\\n self.full_saver.restore(session, model_dir)\",\n \"def __init__(self):\\n Model.__init__(self)\\n self.rellenar_lista()\",\n \"def reset_model(self):\\n raise NotImplementedError\",\n \"def reset_model(self):\\n raise NotImplementedError\",\n \"def reset_model(self):\\n raise NotImplementedError\",\n \"def automark(self):\\n\\n index_list = self.ui.tableWidget.selectionModel().selectedIndexes()\\n rows = []\\n for i in index_list:\\n rows.append(i.row())\\n rows = list(set(rows)) # duplicate rows due to multiple columns\\n if len(rows) == 0:\\n return\\n selected_files = []\\n filenames = \\\"\\\"\\n for r in rows:\\n if self.allfiles[r][2] is not None and self.allfiles[r][2] != \\\"\\\":\\n selected_files.append(self.allfiles[r])\\n filenames += self.allfiles[r][1] + \\\" \\\"\\n ui_se = DialogGetStartAndEndMarks(self.case['name'], filenames)\\n ok = ui_se.exec()\\n if not ok:\\n return\\n start_mark = ui_se.get_start_mark()\\n end_mark = ui_se.get_end_mark()\\n if start_mark == \\\"\\\" or end_mark == \\\"\\\":\\n Message(self.app, _(\\\"Warning\\\"), _('Cannot have blank text marks'), \\\"warning\\\").exec()\\n return\\n msg = _(\\\"Auto assign text to case: \\\") + self.case['name']\\n msg += _(\\\"\\\\nUsing \\\") + start_mark + _(\\\" and \\\") + end_mark + _(\\\"\\\\nIn files:\\\\n\\\")\\n msg += filenames\\n warning_msg = \\\"\\\"\\n already_assigned = \\\"\\\"\\n entries = 0\\n cur = self.app.conn.cursor()\\n for f in selected_files:\\n cur.execute(\\\"select name, id, fulltext, memo, owner, date from source where id=?\\\",\\n [f[0]])\\n currentfile = cur.fetchone()\\n text = currentfile[2]\\n text_starts = [match.start() for match in re.finditer(re.escape(start_mark), text)]\\n text_ends = [match.start() for match in re.finditer(re.escape(end_mark), text)]\\n # Add new code linkage items to database\\n already_assigned = \\\"\\\"\\n for start_pos in text_starts:\\n text_end_iterator = 0\\n try:\\n while start_pos >= text_ends[text_end_iterator]:\\n text_end_iterator += 1\\n except IndexError:\\n text_end_iterator = -1\\n warning_msg += _(\\\"Auto assign. Could not find an end mark: \\\") + f[1] + \\\" \\\" + end_mark + \\\"\\\\n\\\"\\n if text_end_iterator >= 0:\\n pos1 = text_ends[text_end_iterator]\\n item = {'caseid': self.case['caseid'], 'fid': f[0],\\n 'pos0': start_pos, 'pos1': pos1,\\n 'owner': self.app.settings['codername'],\\n 'date': datetime.datetime.now().astimezone().strftime(\\\"%Y-%m-%d %H:%M:%S\\\"), 'memo': \\\"\\\"}\\n # Check if already assigned to case_text\\n sql = \\\"select id from case_text where caseid=? and fid=? and pos0=? and pos1=?\\\"\\n cur.execute(sql, [item['caseid'], item['fid'], item['pos0'], item['pos1']])\\n res = cur.fetchone()\\n if res is None:\\n sql = \\\"insert into case_text (caseid,fid,pos0,pos1,owner,date,memo) values(?,?,?,?,?,?,?)\\\"\\n cur.execute(sql, (item['caseid'], item['fid'], item['pos0'], item['pos1'],\\n item['owner'], item['date'], item['memo']))\\n entries += 1\\n self.app.conn.commit()\\n else:\\n already_assigned = _(\\\"\\\\nAlready assigned.\\\")\\n # Update messages and table widget\\n self.get_files()\\n self.fill_table()\\n # Text file is loaded in browser then update the highlights\\n self.load_case_text()\\n self.highlight()\\n msg += \\\"\\\\n\\\" + str(entries) + _(\\\" sections found.\\\")\\n Message(self.app, _(\\\"File added to case\\\"), msg + \\\"\\\\n\\\" + warning_msg + \\\"\\\\n\\\" + already_assigned).exec()\\n self.parent_textEdit.append(msg)\\n self.parent_textEdit.append(warning_msg)\\n self.app.delete_backup = False\",\n \"def create_model(self):\\n self.create_model_file()\\n self.create_model_unit_test()\\n self.add_model_to_list()\\n self.readme_reminder()\",\n \"def pick_up(self):\",\n \"def update_vluln_table():\",\n \"def build_sys_rec_model():\\n print(\\\"building model...\\\")\\n model = Merchant2VecModel()\\n model.train(final_training=True)\\n model.save_model()\",\n \"def load_rentedout():\",\n \"def SetModel( self, loader ):\\n self.loader = loader\\n self.adapter,tree,rows = self.RootNode( )\\n self.listControl.integrateRecords( rows.values())\\n self.activated_node = tree\\n self.squareMap.SetModel( tree, self.adapter )\\n self.RecordHistory()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5480063","0.54420656","0.5437654","0.53411984","0.5257772","0.5196333","0.51816934","0.50881743","0.5072814","0.50495183","0.50386804","0.5009755","0.499261","0.49754384","0.49611595","0.49506703","0.49395007","0.4916408","0.4916408","0.49122566","0.49122566","0.49122566","0.49122566","0.49122566","0.49096972","0.49089012","0.48955873","0.48922318","0.48882458","0.48882458","0.48877302","0.48874334","0.48860008","0.48791128","0.4878904","0.48713878","0.4865361","0.4854096","0.48428786","0.48418853","0.48254168","0.47854137","0.4772098","0.4766585","0.47648814","0.47640008","0.47632152","0.4762361","0.4758888","0.4752753","0.4751506","0.47319406","0.47238663","0.4722596","0.472015","0.47184694","0.4714782","0.47100833","0.47096756","0.47072056","0.47071365","0.47032708","0.47016084","0.46980402","0.46973586","0.46964237","0.46907985","0.46907985","0.46907985","0.46907985","0.46865752","0.4682835","0.46808887","0.46785757","0.46776068","0.46760058","0.46749526","0.46717006","0.46706086","0.46650806","0.46531022","0.46530187","0.46519056","0.46485117","0.46462175","0.46421418","0.46414092","0.46383572","0.46347564","0.46312013","0.463045","0.463045","0.463045","0.4629014","0.46274132","0.46265534","0.46257025","0.4621984","0.46208325","0.4619623"],"string":"[\n \"0.5480063\",\n \"0.54420656\",\n \"0.5437654\",\n \"0.53411984\",\n \"0.5257772\",\n \"0.5196333\",\n \"0.51816934\",\n \"0.50881743\",\n \"0.5072814\",\n \"0.50495183\",\n \"0.50386804\",\n \"0.5009755\",\n \"0.499261\",\n \"0.49754384\",\n \"0.49611595\",\n \"0.49506703\",\n \"0.49395007\",\n \"0.4916408\",\n \"0.4916408\",\n \"0.49122566\",\n \"0.49122566\",\n \"0.49122566\",\n \"0.49122566\",\n \"0.49122566\",\n \"0.49096972\",\n \"0.49089012\",\n \"0.48955873\",\n \"0.48922318\",\n \"0.48882458\",\n \"0.48882458\",\n \"0.48877302\",\n \"0.48874334\",\n \"0.48860008\",\n \"0.48791128\",\n \"0.4878904\",\n \"0.48713878\",\n \"0.4865361\",\n \"0.4854096\",\n \"0.48428786\",\n \"0.48418853\",\n \"0.48254168\",\n \"0.47854137\",\n \"0.4772098\",\n \"0.4766585\",\n \"0.47648814\",\n \"0.47640008\",\n \"0.47632152\",\n \"0.4762361\",\n \"0.4758888\",\n \"0.4752753\",\n \"0.4751506\",\n \"0.47319406\",\n \"0.47238663\",\n \"0.4722596\",\n \"0.472015\",\n \"0.47184694\",\n \"0.4714782\",\n \"0.47100833\",\n \"0.47096756\",\n \"0.47072056\",\n \"0.47071365\",\n \"0.47032708\",\n \"0.47016084\",\n \"0.46980402\",\n \"0.46973586\",\n \"0.46964237\",\n \"0.46907985\",\n \"0.46907985\",\n \"0.46907985\",\n \"0.46907985\",\n \"0.46865752\",\n \"0.4682835\",\n \"0.46808887\",\n \"0.46785757\",\n \"0.46776068\",\n \"0.46760058\",\n \"0.46749526\",\n \"0.46717006\",\n \"0.46706086\",\n \"0.46650806\",\n \"0.46531022\",\n \"0.46530187\",\n \"0.46519056\",\n \"0.46485117\",\n \"0.46462175\",\n \"0.46421418\",\n \"0.46414092\",\n \"0.46383572\",\n \"0.46347564\",\n \"0.46312013\",\n \"0.463045\",\n \"0.463045\",\n \"0.463045\",\n \"0.4629014\",\n \"0.46274132\",\n \"0.46265534\",\n \"0.46257025\",\n \"0.4621984\",\n \"0.46208325\",\n \"0.4619623\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.69316125"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":18688,"cells":{"query":{"kind":"string","value":"Gera o codigo rml do cabecalho"},"document":{"kind":"string","value":"def cabecalho(dic_cabecalho,dat_ordem,imagem):\n\n tmp=''\n tmp+='\\t\\t\\t\\t<image x=\"4.1cm\" y=\"26.9cm\" width=\"74\" height=\"60\" file=\"' + imagem + '\"/>\\n'\n tmp+='\\t\\t\\t\\t<lines>3.3cm 26.3cm 19.5cm 26.3cm</lines>\\n'\n tmp+='\\t\\t\\t\\t<setFont name=\"Helvetica-Bold\" size=\"15\"/>\\n'\n tmp+='\\t\\t\\t\\t<drawString x=\"6.7cm\" y=\"28.1cm\">' + dic_cabecalho['nom_casa'] + '</drawString>\\n'\n tmp+='\\t\\t\\t\\t<setFont name=\"Helvetica\" size=\"11\"/>\\n'\n tmp+='\\t\\t\\t\\t<drawString x=\"6.7cm\" y=\"27.6cm\">' + 'Estado de ' + dic_cabecalho['nom_estado'] + '</drawString>\\n'\n return tmp"},"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(self):","def mezclar_bolsa(self):","def load_ccs9():\n ccs9 = pd.read_csv(pkg_resources.resource_filename(__name__,'$dxref 2015.csv'))\n ccs9 = ccs9.reset_index()\n for col in ccs9.columns:\n ccs9.loc[:,col]=ccs9[col].str.strip('\\'')\n ccs9.columns=ccs9.iloc[0,:]\n ccs9 = ccs9.iloc[1:,:]\n ccs9 = ccs9.replace(r'^\\s*$', np.nan, regex=True)\n ccs9 = ccs9.loc[ccs9['ICD-9-CM CODE'].notnull(),:]\n ccs9.loc[:,'ICD-9-CM CODE'] = ccs9['ICD-9-CM CODE'].str.replace(' ','')\n ccs9.loc[:,'CCS CATEGORY'] = ccs9['CCS CATEGORY'].str.replace(' ','')\n ccs9 = ccs9.iloc[:,0:4] \n ccs9_labels = pd.read_csv(pkg_resources.resource_filename(__name__,'dxlabel 2015.csv'))\n ccs9 = ccs9.merge(ccs9_labels,how='left',left_on='CCS CATEGORY',right_on='CCS DIAGNOSIS CATEGORIES')\n ccs9.drop('CCS CATEGORY DESCRIPTION',axis=1,inplace=True)\n ccs9.drop('CCS DIAGNOSIS CATEGORIES',axis=1,inplace=True)\n ccs9.columns = [i.replace('CCS DIAGNOSIS CATEGORIES LABELS','CCS CATEGORY DESCRIPTION') for i in ccs9.columns]\n return ccs9","def lcia_methods__metadata(self):\r\n with UnicodeReader(os.path.join(dirpath, \"categoryUUIDs.csv\"), \r\n encoding='latin-1', \r\n delimiter=dt) as csv_file:\r\n next(csv_file) \r\n csv_data = [{'name': (line[0], line[2], line[4]),\r\n 'description': line[7]\r\n } for line in csv_file]\r\n \r\n filename = \"LCIA_implementation_2019.xlsx\" # this was donwloaded and updated on Oct 2019 from ecoinvent website. \r\n wb = xlrd.open_workbook(os.path.join(dirpath, filename))\r\n #characterizaton factors\r\n sheet= wb.sheet_by_name(\"CFs\")\r\n cf_data = [{\r\n 'method': (sheet.cell(row, 0).value,\r\n sheet.cell(row, 1).value,\r\n sheet.cell(row, 2).value),\r\n 'name': sheet.cell(row, 3).value,\r\n 'categories': (sheet.cell(row, 4).value, sheet.cell(row, 5).value),\r\n 'amount': sheet.cell(row, 7).value\r\n }\r\n for row in range(1, sheet.nrows)\r\n if sheet.cell(row, 0).value not in \r\n {'selected LCI results, additional', 'selected LCI results'} and isinstance(sheet.cell(row, 7).value, Number)]\r\n #units\r\n sheet= wb.sheet_by_name(\"units\")\r\n units = {(sheet.cell(row, 0).value, sheet.cell(row, 1).value, \r\n sheet.cell(row, 2).value): sheet.cell(row, 4).value for row in range(1, sheet.nrows)}\r\n return csv_data, cf_data, units, filename","def build(c):","def mol_to_cbor(mol: masm.Molecule) -> str:\n serializer = masm.JsonSerialization\n cbor_format = serializer.BinaryFormat.CBOR\n serialization = serializer(mol)\n cbor_binary = serialization.to_binary(cbor_format)\n return serializer.base_64_encode(cbor_binary)","def get_model_and_assets():\n\n return common.read_model('cloth_corner.xml'),common.ASSETS","def load_data(self):","def presenetCar():","def read_meta(self):\n meta = cPickle.load(open('../sugar_analysis_data/META-CABALLO2.pkl'))\n self.meta_sn_name_list = []\n self.meta_zcmb = []\n self.meta_x0 =[]\n self.meta_x0_err = []\n self.meta_x1 =[]\n self.meta_x1_err = []\n self.meta_c = []\n self.meta_c_err = []\n self.meta_mb = []\n self.meta_mb_err = []\n self.meta_cov_x0_x1 = [] \n self.meta_cov_x0_c = []\n self.meta_cov_x1_c = []\n self.meta_cov_mb_x1 = []\n self.meta_cov_mb_c = [] \n self.meta_zhl = []\n self.meta_zhl_err = []\n self.meta_idr = []\n for meta_sn_name in meta.keys(): \n \n if meta[meta_sn_name]['idr.subset'] != 'bad' and meta[meta_sn_name]['idr.subset'] != 'auxiliary':\n \n self.meta_sn_name_list.append(meta_sn_name)\n self.meta_zhl_err.append(meta[meta_sn_name]['host.zhelio.err'])\n self.meta_zhl.append(meta[meta_sn_name]['host.zhelio'])\n self.meta_zcmb.append(meta[meta_sn_name]['host.zcmb'])\n self.meta_x0.append(meta[meta_sn_name]['salt2.X0'])\n self.meta_x0_err.append(meta[meta_sn_name]['salt2.X0.err'])\n self.meta_x1.append(meta[meta_sn_name]['salt2.X1'])\n self.meta_x1_err.append(meta[meta_sn_name]['salt2.X1.err'])\n self.meta_c.append(meta[meta_sn_name]['salt2.Color'])\n self.meta_c_err.append(meta[meta_sn_name]['salt2.Color.err'])\n self.meta_mb.append(meta[meta_sn_name]['salt2.RestFrameMag_0_B'])\n self.meta_mb_err.append(meta[meta_sn_name]['salt2.RestFrameMag_0_B.err'])\n self.meta_cov_x0_x1.append(meta[meta_sn_name]['salt2.CovX0X1'])\n self.meta_cov_x0_c.append(meta[meta_sn_name]['salt2.CovColorX0'])\n self.meta_cov_x1_c.append(meta[meta_sn_name]['salt2.CovColorX1'])\n self.meta_cov_mb_x1.append(meta[meta_sn_name]['salt2.CovRestFrameMag_0_BX1'])\n self.meta_cov_mb_c.append(meta[meta_sn_name]['salt2.CovColorRestFrameMag_0_B'])\n self.meta_idr.append(meta[meta_sn_name]['idr.subset'])\n \n self.meta_idr = np.array(self.meta_idr)\n self.meta_zcmb = np.array(self.meta_zcmb)\n self.meta_zhl = np.array(self.meta_zhl)\n self.meta_zhl_err = np.array(self.meta_zhl_err)\n self.meta_x0 = np.array(self.meta_x0)\n self.meta_x0_err = np.array(self.meta_x0_err)\n self.meta_x1 = np.array(self.meta_x1)\n self.meta_x1_err = np.array(self.meta_x1_err) \n self.meta_c = np.array(self.meta_c)\n self.meta_c_err = np.array(self.meta_c_err)\n self.meta_mb = np.array(self.meta_mb)\n self.meta_mb_err = np.array(self.meta_mb_err)\n self.meta_cov_x0_x1 = np.array(self.meta_cov_x0_x1)\n self.meta_cov_x0_c = np.array(self.meta_cov_x0_c)\n self.meta_cov_x1_c = np.array(self.meta_cov_x1_c)\n self.meta_cov_mb_x1 = np.array(self.meta_cov_mb_x1)\n self.meta_cov_mb_c = np.array(self.meta_cov_mb_c)","def processa_compra(self, compra):\n\n print(\"Boleto criado!\\n\" + compra.nota_fiscal)","def convertion_binaire_arbre(self):\r\n binary_code = self.root.conversion_binaire('')\r\n binary_dict = {}\r\n binary_code = binary_code.strip().split(\"\\n\")\r\n for element in binary_code:\r\n binary_dict[element.split(\":\")[0]] = element.split(\":\")[1]\r\n return binary_dict","def agregar_bolsa(self, letra, cantidad):","def load_data():\r\n print ('Loadng all the file one time......')\r\n if not os.path.exists('cifar.pkl'):\r\n set_data()\r\n with open('cifar.pkl', 'rb') as cifar_pickle:\r\n data = six.moves.cPickle.load(cifar_pickle)\r\n return data","def _download_cxr_model(self):\n file_id = \"1KIsLmVv8jKTVG_LxchMZAvR7rugHy7uB\"\n download_from_google_drive(file_id=file_id, folder=\"data/\", name=\"covid_cxr.zip\")","def read_acbr(self):\n return self.ACBR","def model() -> Any:\n with open(\"airbnb_regressor.pickle\",\"rb\") as f:\n model = pickle.load(f)\n return model","def CL(self):","def load(self, filename):\n # XXX Hay que comprobar los datos leidos y lanzar excepcion\n f = open(filename)\n prelaciones = []\n asig = []\n rec = []\n l = f.readline()\n while l:\n # Activities and following activities\n if l[0:21] == 'PRECEDENCE RELATIONS:':\n f.readline()\n l = f.readline()\n while l[0] != '*':\n data = l.split()\n prel = (data[0], data[3:])\n prelaciones.append(prel)\n l = f.readline()\n\n # Activity duration and resource units needed\n if l[0] == '-':\n l = f.readline()\n while l[0] != '*':\n asig.append(l.split())\n l = f.readline()\n\n # Name, type and unit of resources\n if l[0:22] == 'RESOURCEAVAILABILITIES':\n l = f.readline()\n while l[0] != '*':\n rec.append(l.split())\n l = f.readline()\n\n l = f.readline()\n \n # Create data structure\n cont = 1\n activities = []\n for prelacion in prelaciones:\n activities.append([cont, prelacion[0], prelacion[1], '', '', '', '', '', ('Beta')])\n cont += 1 \n\n # Update activities duration\n for n in range(len(asig)): \n activities[n][6] = float(asig[n][2])\n\n # Update resources\n i = 1\n m = 0\n resources = []\n if len(rec) < 2:\n raise InvalidFileFormatException()\n\n for n in range(len(rec[1])):\n # Renewable\n if rec[0][m]=='R' or rec[0][m][0]=='R':\n if rec[0][m]=='R':\n row=[rec[0][m]+rec[0][i], 'Renewable', '', rec[1][n]] \n m+=2\n else:\n row=[rec[0][m], 'Renewable', '', rec[1][n]] \n m+=1 \n # Non Renewable\n elif rec[0][m]=='N' or rec[0][m][0]=='N':\n if rec[0][m]=='N':\n row=[rec[0][m]+rec[0][i], 'Non renewable', rec[1][n], '']\n m+=2\n else:\n row=[rec[0][m], 'Non renewable', rec[1][n], ''] \n m+=1\n # Double constrained\n elif rec[0][m]=='D' or rec[0][m][0]=='D':\n if rec[0][m]=='D':\n row=[rec[0][m]+rec[0][i], 'Double constrained', rec[1][n], rec[1][n]]\n m+=2\n else:\n row=[rec[0][m], 'Double constrained', rec[1][n], rec[1][n]] \n m+=1\n \n resources.append(row)\n i += 2\n # Note: Unlimited resources are not present on PSPLIB projects and so \n # not taken into account here\n\n # Resources needed per activity\n asignation = []\n for n in range(len(asig)): \n for m in range(3, 3+len(rec[1])): #len(self.rec[1]): number of resources \n if asig[n][m] != '0': #unused resources are not shown\n i = m-3\n row = [asig[n][0], resources[i][0], asig[n][m]] \n asignation.append(row)\n \n return (activities, [], resources, asignation)","def archivoXlFormateado(archivo):\r\n return ow(archivo, formatting_info=True)","def crf_entities():\n if not os.path.isfile(PATH_ENTITIES['crf']['model']):\n print('downloading ENTITIES frozen CRF model')\n download_file(\n S3_PATH_ENTITIES['crf']['model'], PATH_ENTITIES['crf']['model']\n )\n with open(PATH_ENTITIES['crf']['model'], 'rb') as fopen:\n model = pickle.load(fopen)\n return CRF(model)","def climat_model_build(self) :\n dict_climat = dict()\n list_state = self._df.ORIGIN_STATE_ABR.unique().tolist()\n # Climat tempéré océanique : 1\n dict_climat['WA']=1\n dict_climat['OR']=1\n\n # Climat tempéré continental sec : 2\n list_climate_2 = ['ID','MT','WY','UT','CO','ND','SD','NE','KS','OK']\n for state in list_climate_2 :\n dict_climat[state]=2\n\n # Climat tempéré continental pacifique : 3\n\n # Climat sub-tropical : 4\n list_climate_4 = ['VA','NC','GA','FL','AL','TN','MS','LA','AR']\n for state in list_climate_4 :\n dict_climat[state]= 4\n\n # Climat Aride : 5\n list_climate_5 = ['AZ','TX','NM','NV']\n for state in list_climate_5 :\n dict_climat[state]= 5\n\n # Climat tempéré méditéranéen : 6\n list_climate_6 = ['CA']\n for state in list_climate_6 :\n dict_climat[state]= 6\n\n for state in list_state :\n if state not in dict_climat.keys() :\n dict_climat[state] = 3\n\n self.dict_climat = dict_climat\n self._df['ORIGIN_CLIMAT'] = self._df.ORIGIN_STATE_ABR.apply(self._state_climate_build)\n self._df['DEST_CLIMAT'] = self._df.DEST_STATE_ABR.apply(self._state_climate_build)","def on_load(self):\n filename = QtGui.QFileDialog.getOpenFileName(self, \"Open file\", \"\", \"*.scc\")\n print(\"Load file \", filename)\n if filename == \"\":\n return\n f = open(filename, mode=\"rb\")\n state = pickle.load(f)\n f.close() \n cmp = ComponentRect()\n cmp.set_state(state)\n self.mdl.set_component(cmp)","def mol_from_cbor(cbor_str: str) -> masm.Molecule:\n serializer = masm.JsonSerialization\n cbor_binary = serializer.base_64_decode(cbor_str)\n cbor_format = serializer.BinaryFormat.CBOR\n serialization = serializer(cbor_binary, cbor_format)\n return serialization.to_molecule()","def descompactar(caminho, nome, formato):\n\n # Abre e le o arquivo\n arquivo = Arquivo(caminho, nome, formato)\n cabecalho_compactado = arquivo.ler()\n\n #----------------------------------------\n\n # Descompactacao do cabecalho por meio do gzip\n cabecalho = g.decompress(cabecalho_compactado)\n\n #----------------------------------------\n\n # Cabecalho\n numero_magico = int.from_bytes(cabecalho[0:1], byteorder=\"big\") \n if numero_magico != 42:\n exit()\n\n largura = int.from_bytes(cabecalho[1:3], byteorder=\"big\")\n altura = int.from_bytes(cabecalho[3:5], byteorder=\"big\")\n quantidade_cores = int.from_bytes(cabecalho[5:6], byteorder=\"big\")\n lista = list(cabecalho[6:262])\n conteudo = list(cabecalho[262:len(cabecalho)])\n\n #----------------------------------------\n \n # Amplia para 8 bits\n bit = Bitwise(6)\n imagem_rotulada = bit.ampliar(conteudo, largura*altura)\n\n #----------------------------------------\n\n # Cria a tabela\n matriz = [[lista[y], lista[y+1], lista[y+2], lista[y+3]] for y in range(0, len(lista), 4)]\n tabela = Tabela(matriz)\n\n #----------------------------------------\n\n # Cria um objeto da classe Imagem\n final = Imagem(caminho, nome+\"_som\", \"TIFF\")\n # Salva a imagem\n final.salvar(largura, altura, imagem_rotulada, tabela)","def load(self):\n pass","def load(self):\n pass","def load(self):\n pass","def load(self):\n pass","def load_building_blocks(path):\t\t\n\t#TODO : automatization\n\tbenzene = Building_Block(abbrev=\"B\", num_atoms=6,origin=0, para_pos=3, para_angle=0, meta_pos=4 , meta_angle = -np.pi/3., ortho_pos=5, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\"/benzene.xyz\")\n\tnapthtalene = Building_Block(abbrev=\"N\", num_atoms=18,origin=0, para_pos=12, para_angle=0., meta_pos=11 , meta_angle = -np.pi/3., ortho_pos=10, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\"/naphtalene.xyz\")\n\tdbPc1 = Building_Block(abbrev=\"dbPc1\", num_atoms=32,origin=13, para_pos=1, para_angle=0, meta_pos=0 , meta_angle = +np.pi/3., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\"/dbPc1_block.xyz\")\n\tdbPc4 = Building_Block(abbrev=\"dbPc4\", num_atoms=55,origin=22, para_pos=1, para_angle=0, meta_pos=0 , meta_angle = -np.pi/3., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\"/dbPc4.xyz\")\n\tdbPc6 = Building_Block(abbrev=\"dbPc6\", num_atoms=52,origin=17, para_pos=0, para_angle=0, meta_pos=1 , meta_angle = -np.pi/3., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\"/dbPc6.xyz\")\n\tdbPc5 = Building_Block(abbrev=\"dbPc5\", num_atoms=58,origin=12, para_pos=26, para_angle=0, meta_pos=20 , meta_angle = -np.pi/3., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\"/dbPc5.xyz\")\n\tpseudo_para_naph_PCP = Building_Block(abbrev=\"pseudo-para_naph_PCP\", num_atoms=44,origin=0, para_pos=18, para_angle=0, meta_pos=16 , meta_angle = -np.pi/3, ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\"/pseudo-para_naph_PCP.xyz\")\n\tline =Building_Block(abbrev=\"line\", num_atoms=4,origin=0, para_pos=1, para_angle=0, meta_pos=1 , meta_angle = 0., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\"/line.xyz\")\n\t#rot=Building_Block(abbrev=\"line\", num_atoms=47,origin=6, para_pos=16, para_angle=0, meta_pos=20 , meta_angle = 0., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=2, path=path+\"/rot.xyz\")\n\t#stacked_anth=Building_Block(abbrev=\"stacked_anth\", num_atoms=62,origin=3, para_pos=22, para_angle=0, meta_pos=30 , meta_angle = 0., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=2, path=path+\"/stacked_anth.xyz\")\n\t\n\tbuilding_blocks = [benzene,napthtalene,dbPc1,dbPc4,dbPc6, dbPc5,pseudo_para_naph_PCP, line]\n\n\treturn building_blocks","def read_redmapper():\n redfile = os.path.join(os.sep, 'global', 'work', 'projects', \n 'redmapper', 'redmapper_isedfit_v5.10_centrals.fits.gz')\n print('Reading {}'.format(redfile))\n cat = fitsio.read(redfile, ext=1)\n return cat","def readSurfaceGeo(b18path):\n if not os.path.isfile(b18path):\n print(\"b18 building file not found! Please check!\")\n pass\n else:\n b18file = open(b18path,\"r\")\n b18data = b18file.readlines()\n srfGeoBlock = getDataParagraph(\"_EXTENSION_BuildingGeometry_START_\", \"_EXTENSION_BuildingGeometry_END_\", b18data)\n #now get vertex's coordinate xyz\n vertexdict = dict() #{vertexID:[x,y,z]}\n srfbasicinfo = dict() #{surfaceID:[vertexID]}\n srfInfo = dict() #{surfaceID:[vertices coordinate]}\n for line in srfGeoBlock:\n dline = line.split()\n if \"vertex\" in dline:\n vertexdict[int(dline[1])] = [float(xyz) for xyz in dline[2:]] #{vertexID:[x,y,z]}\n if \"wall\" in dline or \"window\" in dline or \"floor\" in dline or \"ceiling\" in dline or \"roof\" in dline:\n srfbasicinfo[int(dline[1])] = [[int(nrID) for nrID in dline[2:]],dline[0]] #{surfaceID:[[vertexID],construction]}\n #print srfbasicinfo[int(dline[1])]\n for key in srfbasicinfo.keys():\n srfInfo[key] = []\n for vertices in srfbasicinfo[key][0]:\n srfInfo[key].append(vertexdict[vertices])\n b18file.close()\n return srfInfo,vertexdict,srfbasicinfo\n #actually only need srfInfo\n #just getting everything out for now, incase will need to use those","def get_roidb(self):\n # get all the images_ids in this dataset\n img_ids = self._COCO.getImgIds()\n # sort the ids, make each time the same order\n img_ids.sort()\n # load the 'image' of the COCO dataset\n roidb = copy.deepcopy(self._COCO.loadImgs(img_ids))\n for entry in roidb:\n # predefine some attribute of each image\n self._prep_roidb_entry(entry)\n\n # for cahce_dir\n if not os.path.exists(self.cache_dir):\n os.mkdir(self.cache_dir)\n cache_file = os.path.join(self.cache_dir, self.annFile + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n self._read_roidb_from_cachefile(roidb, cache_file)\n print('{} gt roidb loaded from {}'.format(self.annFile, cache_file))\n else:\n for entry in roidb:\n self._add_roidb_from_annotations(entry)\n with open(cache_file, 'wb') as f:\n pickle.dump(roidb, f, pickle.HIGHEST_PROTOCOL)\n print('wrote gt roidb to {}'.format(cache_file))\n return roidb","def load_data(self) -> None:","def load_cci9():\n cci9 = pd.read_csv(pkg_resources.resource_filename(__name__,'cci2015.csv'),skiprows=1)\n cci9.columns = [i.strip('\\'') for i in cci9.columns]\n \n for col in cci9.columns:\n cci9.loc[:,col] = cci9[col].str.strip('\\'')\n cci9 = cci9.replace(r'^\\s*$', np.nan, regex=True)\n cci9.columns=[i.replace('CATEGORY DESCRIPTION','CHRONIC') for i in cci9.columns]\n\n dict_bodysystem=[\n ('1' ,'Infectious and parasitic disease'),\n ('2' ,'Neoplasms'),\n ('3' ,'Endocrine, nutritional, and metabolic diseases and immunity disorders'),\n ('4' ,'Diseases of blood and blood-forming organs'),\n ('5' ,'Mental disorders'),\n ('6' ,'Diseases of the nervous system and sense organs'),\n ('7' ,'Diseases of the circulatory system'),\n ('8' ,'Diseases of the respiratory system'),\n ('9' ,'Diseases of the digestive system'),\n ('10','Diseases of the genitourinary system'),\n ('11','Complications of pregnancy, childbirth, and the puerperium'),\n ('12','Diseases of the skin and subcutaneous tissue'),\n ('13','Diseases of the musculoskeletal system'),\n ('14','Congenital anomalies'),\n ('15','Certain conditions originating in the perinatal period'),\n ('16','Symptoms, signs, and ill-defined conditions'),\n ('17','Injury and poisoning'),\n ('18','Factors influencing health status and contact with health service'),\n ]\n \n cci9 = cci9.merge(pd.DataFrame(dict_bodysystem,columns=['BODY SYSTEM','BODY SYSTEM DESCRIPTION']),how='left',on='BODY SYSTEM')\n \n cci9.loc[:,'ICD-9-CM CODE'] = cci9['ICD-9-CM CODE'].str.replace(' ','')\n \n return cci9","def to_ir(self):","def cargar_atril(self,lista,bolsa):\n self.atril = lista\n self.bolsa = bolsa","def _build(self):","def _build(self):","def import_cml(self, fname):\n self.ftype = 'cml'\n with open(fname) as f:\n lines = f.readlines()\n self.n_atom = 0\n self.n_connect = 0\n self.sym = []\n self.at_num = []\n self.xyz = []\n self.connect = []\n for i in range(len(lines)):\n if lines[i].split()[0] == '<atom':\n self.n_atom += 1\n tmp = lines[i].split()\n self.sym.append(tmp[2].split('\"')[1])\n self.at_num.append(self.sym2num(tmp[2].split('\"')[1]))\n x = float(tmp[3].split('\"')[1])\n y = float(tmp[4].split('\"')[1])\n z = float(tmp[5].split('\"')[1])\n self.xyz.append([x, y, z])\n elif lines[i].split()[0] == '<bond':\n self.n_connect += 1\n tmp = lines[i].split()\n a = int(tmp[1].split('\"')[1].split('a')[1])\n b = int(tmp[2].split('\"')[0].split('a')[1])\n self.connect.append([a, b])\n self.xyz = np.array(self.xyz)","def read(self):\n import cclib\n from pybel import readfile\n\n molecule = next(readfile(\"orca\", self._file))\n\n atom_numbers = []\n coordinates = []\n\n for atom in molecule:\n atom_number = atom.atomicnum\n atom_numbers.append(atom_number)\n for coord in atom.coords:\n coordinates.append(coord)\n\n molecular_mass = molecule.exactmass\n\n cjson = {\n \"chemical json\": 0,\n \"atoms\": {\n \"elements\": {\"number\": atom_numbers},\n \"coords\": {\"3d\": coordinates},\n },\n \"properties\": {\"molecular mass\": molecular_mass},\n }\n\n data = cclib.io.ccread(self._file)\n\n # Add calculated properties\n if hasattr(data, \"scfenergies\"):\n if len(data.scfenergies) > 0:\n energy = data.scfenergies[-1] * EV_TO_J_MOL\n cjson.setdefault(\"properties\", {})[\"totalEnergy\"] = energy\n\n if hasattr(data, \"gbasis\"):\n basis = _cclib_to_cjson_basis(data.gbasis)\n cjson[\"basisSet\"] = basis\n\n if hasattr(data, \"vibfreqs\"):\n vibfreqs = list(data.vibfreqs)\n cjson.setdefault(\"vibrations\", {})[\"frequencies\"] = vibfreqs\n\n if hasattr(data, \"vibdisps\"):\n vibdisps = _cclib_to_cjson_vibdisps(data.vibdisps)\n cjson.setdefault(\"vibrations\", {})[\"eigenVectors\"] = vibdisps\n\n # Add a placeholder intensities array\n if \"vibrations\" in cjson and \"frequencies\" in cjson[\"vibrations\"]:\n if \"intensities\" not in cjson[\"vibrations\"]:\n cjson[\"vibrations\"][\"intensities\"] = [\n 1 for i in range(len(cjson[\"vibrations\"][\"frequencies\"]))\n ]\n if \"modes\" not in cjson[\"vibrations\"]:\n cjson[\"vibrations\"][\"modes\"] = [\n i + 1 for i in range(len(cjson[\"vibrations\"][\"frequencies\"]))\n ]\n\n return cjson","def build():","def ReadGBMCatalogueOneLine(nameGrb, path_catlogue_csv = \"/disk/gamma/cta/store/takhsm/FermiData/catalogue/GBM-BusrtCatalogue_20170623.csv\"):\n dct_info = {}\n num_lines = sum(1 for line in open(path_catlogue_csv))\n csv = pandas.read_csv(path_catlogue_csv)\n for iGrb in range(num_lines-1):\n if int(nameGrb) == int(csv.ix[iGrb,'name']):\n dct_info['ra'] = float(csv.ix[iGrb,'ra'])\n dct_info['dec'] = float(csv.ix[iGrb,'dec']) \n dct_info['trigger_time'] = pMETandMJD.ConvertMjdToMet(float(csv.ix[iGrb,'trigger_time']))\n dct_info['error_radius'] = float(csv.ix[iGrb,'error_radius'])\n return dct_info","def load_resource():\n resource_file = 'curves/' + self.combo_box[\"class\"].get() + '.json'\n self.classes[\"fractal\"].curve.load_from_resource(\n resource_file)\n self.classes[\"fractal\"].curve.set_parent_parameters()\n self.classes[\"parameters\"].rules_frame_class.fill_entries_from_rules(\n self.classes[\"fractal\"].rules)\n self.classes[\"parameters\"].set_base_length_entry(\n self.classes[\"fractal\"].base_length)\n self.classes[\"parameters\"].rules_frame_class.render_preview()","def _load_model(self):\n with open(self.filepath, 'rb') as file:\n self.cmodel = pickle.load(file)","def create_cab(self):\n cab = Cab()\n cab.type = self.info['type']\n cab.driver_name = self.info.get('driver_name')\n cab.rc_number = self.info['rc_number']\n cab.city_id = self.info['city_id']\n cab.company_name = self.info['company_name']\n cab.model_name = self.info['model_name']\n cab.update_time = datetime.utcnow().replace(microsecond=0)\n self.cab_id = self.save(cab)\n\n # we can do asynchronously\n self.create_cab_state()\n return self.cab_id","def read(self):","def __bytes__(self):\n line1=self.name.encode(\"ascii\").ljust(24,b\" \")\n line2=b\"1 %05dU %02d%03d%-3b %02d%012.8f %c.%08d %c%05d%+01d %c%05d%+01d 0 %04d\" %\\\n (self.id,self.desig[\"year\"]%100,self.desig[\"launch\"],\\\n self.desig[\"object\"].encode(\"ascii\"),self.epoch[\"year\"]%100,\\\n self.epoch[\"day\"],b\"-\" if self.fdmm<0 else b\" \",abs(self.fdmm*1.e8),\\\n b\"-\" if self.sdmm<0 else b\" \",\\\n abs(self.sdmm*pow(10,5-(ceil(log(abs(self.sdmm),10)) if \\\n abs(self.sdmm)>0 else 0))),\\\n (ceil(log(abs(self.sdmm),10)) if abs(self.sdmm)>0 else 0),\\\n b\"-\" if self.bstar<0 else b\" \",\\\n abs(self.bstar*pow(10,5-(ceil(log(abs(self.bstar),10)) if \\\n abs(self.bstar)>0 else 0))),\\\n (ceil(log(abs(self.bstar),10)) if abs(self.bstar)>0 else 0),\\\n self.nr,)\n line3=b\"2 %05d %08.4f %08.4f %07d %08.4f %08.4f %011.8f%05d\" %\\\n (self.id,self.inc,self.raan,self.ecc*1.e7,self.aop,\\\n self.ma,self.mm,self.revol,)\n l2cs=0\n for c in line2:\n bc=bytes([c])\n if bc.isdigit():\n l2cs+=int(bc.decode(\"ascii\"))\n elif bc==b\"-\":\n l2cs+=1\n l2cs%=10\n\n l3cs=0\n for c in line3:\n bc=bytes([c])\n if bc.isdigit():\n l3cs+=int(bc.decode(\"ascii\"))\n elif bc==b\"-\":\n l3cs+=1\n l3cs%=10\n return line1+b\"\\r\\n\"+line2+str(l2cs).encode(\"ascii\")+b\"\\r\\n\"+line3+\\\n str(l3cs).encode(\"ascii\")+b\"\\r\\n\"","def load(self):\n return","def convert_uncompressed_RLE_COCO_type(\n element: Dict, height: int, width: int\n ) -> Dict:\n p = maskUtils.frPyObjects(element, height, width)\n return p","def build(self):","def build(self):","def build(self):","def _read_data(self):","def exportCrises ( c ) :\n assert str(type(c)) == \"<type '_mysql.connection'>\"\n xml = \"\"\n cr = sqlQuery ( c, \"select * from Crises;\" )\n for i in cr :\n cL = sqlQuery ( c, \"select * from CrisisLocations where crisisID = '\" + i [ 0 ] + \"';\" )\n hI = sqlQuery ( c, \"select * from HumanImpact where crisisID = '\" + i [ 0 ] + \"';\" )\n rN = sqlQuery ( c, \"select * from ResourceNeeded where crisisID = '\" + i [ 0 ] + \"';\" )\n wTH = sqlQuery ( c, \"select * from WaysToHelp where crisisID = '\" + i [ 0 ] + \"';\" )\n cER = sqlQuery ( c, \"select * from CrisisExternalResources where crisisID = '\" + i [ 0 ] + \"';\" )\n cTP = sqlQuery ( c, \"select * from CrisesToPeople where crisisID = '\" + i [ 0 ] + \"';\" )\n oTC = sqlQuery ( c, \"select * from OrganizationsToCrises where crisisID = '\" + i [ 0 ] + \"';\" )\n xml += openTagAtt ( \"Crisis\", \"crisisIdent\", i [ 0 ] )\n xml += openCloseTag ( \"Name\", i [ 1 ] )\n xml += closeTagAtt ( \"Kind\", \"crisisKindIdent\", i [ 2 ] )\n for j in cL :\n xml += openTag ( \"Location\" )\n xml += openCloseTag ( \"Locality\", j [ 1 ] )\n xml += openCloseTag ( \"Region\", j [ 2 ] )\n xml += openCloseTag ( \"Country\", j [ 3 ] )\n xml += closeTag ( \"Location\" )\n xml += openTag ( \"StartDateTime\" )\n xml += openCloseTag ( \"Date\", i [ 3 ] )\n xml += openCloseTag ( \"Time\", i [ 4 ] )\n xml += closeTag ( \"StartDateTime\" )\n xml += openTag ( \"EndDateTime\" )\n xml += openCloseTag ( \"Date\", i [ 5 ] )\n xml += openCloseTag ( \"Time\", i [ 6 ] )\n xml += closeTag ( \"EndDateTime\" )\n for j in hI :\n xml += openTag ( \"HumanImpact\" )\n xml += openCloseTag ( \"Type\", j [ 1 ] )\n xml += openCloseTag ( \"Number\", j [ 2 ] )\n xml += closeTag ( \"HumanImpact\" )\n xml += openCloseTag ( \"EconomicImpact\", i [ 7 ] )\n for j in rN :\n xml += openCloseTag ( \"ResourceNeeded\", j [ 1 ] )\n for j in wTH :\n xml += openCloseTag ( \"WaysToHelp\", j [ 1 ] )\n xml += openTag ( \"ExternalResources\" )\n for j in cER :\n xml += openCloseTag ( j [ 1 ] , j [ 2 ] )\n xml += closeTag ( \"ExternalResources\" )\n xml += openTag ( \"RelatedPersons\" )\n for j in cTP :\n xml += closeTagAtt ( \"RelatedPerson\" , \"personIdent\", j [ 1 ] )\n xml += closeTag ( \"RelatedPersons\" )\n xml += openTag ( \"RelatedOrganizations\" )\n for j in oTC :\n xml += closeTagAtt ( \"RelatedOrganization\" , \"organizationIdent\", j [ 0 ] )\n xml += closeTag ( \"RelatedOrganizations\" )\n xml += closeTag ( \"Crisis\" )\n assert str ( type ( xml ) ) == \"<type 'str'>\"\n return xml","def afficherOBJ(self):\r\n str_abr = self.abr.afficher()## appel de l'affichage d'un ABR\r\n return str(self.debut)+':'+str(self.fin)+';'+str_abr ##concaténation du resultat\r","def boma(self):\n\n filename = filedialog.askopenfile(initialdir=self.root.cache_dir,\n title='Select AVL Multilevel BOM',\n filetypes=[('Comma-Separated Values', '.csv')])\n self.a_entry.clear()\n self.a_entry.insert(tk.END, filename.name)\n self.root.cache_dir = filename\n self.bom_a = filename.name","def _load_obcfile(casename=None): \n\n data={}\n\n if casename==None:\n print('_load_obcfile requires a filename to load.')\n return\n try:\n fp=open(casename+'_obc.dat','r')\n except IOError:\n print('_load_obcfile: invalid case name.')\n return data\n\n obc_str=fp.readline().split('=')\n obc_num=int(obc_str[1])\n t_data1=np.genfromtxt(casename+'_obc.dat',skip_header=1)\n fp.close()\n\n data['obcf_num']=obc_num\n data['obcf_numbers']=t_data1[:,0]\n data['obcf_nodes']=t_data1[:,1]\n data['obcf_value']=t_data1[:,2]\n\n \n return data","def __str__(self):\r\n return self.afficherOBJ()","def callback_rocm_bitcode_path(rocdl_dir=None):\n # seems link order matters.\n\n if rocdl_dir is None:\n if exists(\"/opt/rocm/amdgcn/bitcode/\"):\n rocdl_dir = \"/opt/rocm/amdgcn/bitcode/\" # starting with rocm 3.9\n else:\n rocdl_dir = \"/opt/rocm/lib/\" # until rocm 3.8\n\n bitcode_names = [\n \"oclc_daz_opt_on\",\n \"ocml\",\n \"irif\", # this does not exist in rocm 3.9, drop eventually\n \"oclc_correctly_rounded_sqrt_off\",\n \"oclc_correctly_rounded_sqrt_on\",\n \"oclc_daz_opt_off\",\n \"oclc_finite_only_off\",\n \"oclc_finite_only_on\",\n # todo (t-vi): an alternative might be to scan for the\n \"oclc_isa_version_803\",\n \"oclc_isa_version_900\", # isa version files (if the linker throws out\n \"oclc_isa_version_906\", # the unneeded ones or we filter for the arch we need)\n \"oclc_isa_version_1030\",\n \"oclc_unsafe_math_off\",\n \"oclc_unsafe_math_on\",\n \"oclc_wavefrontsize64_on\",\n \"oclc_abi_version_500\",\n ]\n\n bitcode_files = []\n for n in bitcode_names:\n p = join(rocdl_dir, n + \".bc\") # rocm >= 3.9\n if not exists(p): # rocm <= 3.8\n p = join(rocdl_dir, n + \".amdgcn.bc\")\n if exists(p):\n bitcode_files.append(p)\n elif \"isa_version\" not in n and n not in {\"irif\"}:\n raise RuntimeError(\"could not find bitcode \" + n)\n\n return tvm.runtime.convert(bitcode_files)","def crear_arbol():\n print (\"En este programa te brindamos 2 opciones para crear arboles, elige la que mas se adapte a tu objetivo\")\n \n try:\n crear=int(input(\"1. Crear un arbol de manera aleatoria\\n2. Introducir los datos en forma de arreglo\\n\"))\n except:\n print(\"Valor Invalido\")\n \n if crear==1:\n print(\"\\nExcelente! Tu arbol sera generado de forma aleatoria. Solo necesitamos aclarar que tipo de arbol quieres\")\n while True:\n try:\n altura=int(input(\"\\nAñade la altura de tu arbol: \"))\n except:\n print(\"El valor introducido no es valido!\")\n else:\n break\n \n perfecto=input(\"\\n¿Deseas crear un arbol perfecto? (si/no): \")\n if perfecto.lower()!=\"no\":\n perfecto=True\n else:\n perfecto=False\n \n arbol=tree(height=altura, is_perfect=perfecto)\n return arbol\n \n elif crear==2:\n print(\"\\nExcelente! Tu arbol sera generado en base a un arreglo. Solo necesitamos recibir los valores\")\n valores=[]\n counter=0\n print(\"\\nIntroduce los valores en orden. El valor inicial sera considerado la raiz. Los valores se ordenaran de izquiera a derecha.\" +\n \"Deja el valor en blanco para saltar ese espacio. Escribe -1 para dejar de añadir valores\")\n valor=\" \"\n while valor!=\"-1\":\n valor=input(f\"Introduzca el valor {counter}: \")\n if valor==\"\":\n valor=None\n valores.append(valor)\n counter+=1\n else:\n valores.append(int(valor))\n counter+=1\n valores.pop()\n root=build(valores)\n return root","def serialize(self):","def get_jarfile(self):","def encode(category_main : ):","def readmodel(model = 'dominguez'):\n ebl_file_path = os.path.join(os.path.split(__file__)[0],'data/')\n\n if model == 'kneiske':\n file_name = join(ebl_file_path , 'ebl_nuFnu_tanja.dat')\n elif model == 'franceschini':\n file_name = join(ebl_file_path , 'ebl_franceschini.dat')\n elif model == 'dominguez':\n file_name = join(ebl_file_path , 'ebl_dominguez11.out')\n elif model == 'dominguez-upper':\n file_name = join(ebl_file_path , 'ebl_upper_uncertainties_dominguez11.out')\n elif model == 'dominguez-lower':\n file_name = join(ebl_file_path , 'ebl_lower_uncertainties_dominguez11.out')\n elif model == 'inoue':\n file_name = join(ebl_file_path , 'EBL_z_0_baseline.dat')\n #file_name = join(ebl_file_path , 'EBL_proper_baseline.dat')\n elif model == 'inoue-low-pop3':\n file_name = join(ebl_file_path , 'EBL_z_0_low_pop3.dat')\n #file_name = join(ebl_file_path , 'EBL_proper_low_pop3.dat')\n elif model == 'inoue-up-pop3':\n file_name = join(ebl_file_path , 'EBL_z_0_up_pop3.dat')\n #file_name = join(ebl_file_path , 'EBL_proper_up_pop3.dat')\n elif model == 'gilmore':\n file_name = join(ebl_file_path , 'eblflux_fiducial.dat')\n elif model == 'gilmore-fixed':\n file_name = join(ebl_file_path , 'eblflux_fixed.dat')\n elif model == 'cuba':\n file_name = join(ebl_file_path , 'CUBA_UVB.dat')\n elif model == 'finke':\n file_name = join(ebl_file_path , 'ebl_modelC_Finke.txt')\n else:\n raise ValueError(\"Unknown EBL model chosen!\")\n\n data = np.loadtxt(file_name)\n if model.find('inoue') >= 0:\n z = np.array([0.])\n #z = data[0,1:]\n #nuInu = data[:,1]\n lmu = data[:,0]\n nuInu = np.array([data[:,1]]).T\n raise ValueError('Inoue models not correctly implemented at the moment, choose another model')\n\n elif model.find('gilmore') >= 0:\n z = data[0,1:]\n lmu = data[1:,0] * 1e-4 # convert from Angstrom to micro meter\n nuInu = data[1:,1:] \n nuInu[nuInu == 0.] = 1e-20 * np.ones(np.sum(nuInu == 0.))\n \n # convert from ergs/s/cm^2/Ang/sr to nW/m^2/sr\n nuInu = (nuInu.T * data[1:,0]).T * 1e4 * 1e-7 * 1e9 \n\n elif model == 'cuba':\n z = data[0,1:-1]\n lmu = data[1:,0] * 1e-4\n nuInu = data[1:,1:-1]\n\n # replace zeros by 1e-40\n idx = np.where(data[1:,1:-1] == 0.)\n nuInu[idx] = np.ones(np.sum(nuInu == 0.)) * 1e-20\n\n # in erg / cm^2 / s / sr\n nuInu = (nuInu.T * c.c.value / (lmu * 1e-6)).T \n nuInu *= 1e6 # in nW / m^2 / sr\n\n # check where lmu is not strictly increasing\n idx = np.where(np.diff(lmu) == 0.)\n for i in idx[0]:\n lmu[i+1] = (lmu[i + 2] + lmu[i]) / 2.\n\n else:\n z = data[0,1:]\n lmu = data[1:,0]\n nuInu = data[1:,1:]\n if model == 'finke': \n lmu = lmu[::-1] * 1e-4\n nuInu = nuInu[::-1]\n\n return EBL(z,lmu,nuInu, model = model)","def load(self):\n return None","def cma_bst(redownload: bool = False) -> Dataset:\n return Dataset.get(\"cma_bst\", redownload=redownload)","def load_stoic_from_sbml(file_name, split_bidirectional_fluxes=False):\n from lxml import etree\n for ext in ['', '.xml', '.xml.gz', '.gz']:\n if os.path.isfile(file_name+ext):\n file_name = file_name+ext\n break\n tree = etree.parse(file_name)\n root = tree.getroot()\n assert root.tag.endswith ('sbml'), `root.tag`\n version = int(root.attrib['version'])\n level = int(root.attrib['level'])\n if level in [2,3]:\n default_stoichiometry = '1'\n else:\n default_stoichiometry = None\n compartments = {}\n species = []\n modifiers = []\n species_all = []\n reactions = []\n species_reactions = defaultdict (lambda:[])\n reactions_species = defaultdict (lambda:[])\n reactions_info = defaultdict(lambda:dict(modifiers=[],reactants=[],products=[],\n boundary_specie_stoichiometry={},annotation=[],\n compartments = set()))\n species_info = defaultdict(lambda:dict())\n matrix = {}\n for model in root:\n for item in model:\n if item.tag.endswith('listOfCompartments'):\n for compartment in item:\n compartments[compartment.attrib['id']] = compartment.attrib\n elif item.tag.endswith('listOfSpecies'):\n for specie in item:\n species_all.append(specie.attrib['id'])\n species_info[specie.attrib['id']]['compartment'] = specie.attrib['compartment']\n species_info[specie.attrib['id']]['name'] = specie.attrib.get('name', specie.attrib['id'])\n elif item.tag.endswith('listOfReactions'):\n for reaction in item:\n\n reversible =eval(reaction.attrib.get('reversible', 'False').title())\n reaction_id = reaction.attrib['id']\n name = reaction.attrib.get('name', reaction_id)\n assert reaction_id not in reactions,`reaction_id`\n reactions.append(reaction_id)\n reaction_index = len(reactions)-1\n reactions_info[reaction_id]['name'] = name\n\n if split_bidirectional_fluxes and reversible:\n reaction_id2 = '%s_r' % (reaction_id)\n assert reaction_id2 not in reactions,`reaction_id2`\n reactions.append(reaction_id2)\n reaction_index2 = len(reactions)-1\n reactions_info[reaction_id2]['name'] = name+'_r'\n reactions_info[reaction_id]['reversible'] = False\n reactions_info[reaction_id2]['reversible'] = False\n else:\n reaction_id2 = reaction_index2 = None\n reactions_info[reaction_id]['reversible'] = reversible\n\n for part in reaction:\n if part.tag.endswith ('listOfReactants'):\n for reactant in part:\n assert reactant.tag.endswith('speciesReference'), `reactant.tag`\n specie_id = reactant.attrib['species']\n stoichiometry = -obj2num(reactant.attrib.get('stoichiometry', default_stoichiometry))\n reactions_info[reaction_id]['reactants'].append(specie_id)\n try:\n specie_index = species.index(specie_id)\n except ValueError:\n species.append(specie_id)\n specie_index = len(species)-1\n assert stoichiometry,`stoichiometry`\n matrix[specie_index, reaction_index] = stoichiometry\n species_reactions[specie_index].append(reaction_index)\n reactions_species[reaction_index].append(specie_index) \n reactions_info[reaction_id]['compartments'].add(species_info[specie_id]['compartment'])\n if reaction_index2 is not None:\n reactions_info[reaction_id2]['reactants'].append(specie_id)\n matrix[specie_index, reaction_index2] = -stoichiometry\n species_reactions[specie_index].append(reaction_index2)\n reactions_species[reaction_index2].append(specie_index) \n reactions_info[reaction_id2]['compartments'].add(species_info[specie_id]['compartment'])\n elif part.tag.endswith ('listOfProducts'):\n for product in part:\n assert product.tag.endswith('speciesReference'), `product.tag`\n specie_id = product.attrib['species']\n stoichiometry = obj2num(product.attrib.get('stoichiometry', default_stoichiometry))\n reactions_info[reaction_id]['products'].append(specie_id)\n try:\n specie_index = species.index(specie_id)\n except ValueError:\n species.append(specie_id)\n specie_index = len(species)-1\n assert stoichiometry,`stoichiometry`\n matrix[specie_index, reaction_index] = stoichiometry\n species_reactions[specie_index].append(reaction_index)\n reactions_species[reaction_index].append(specie_index)\n reactions_info[reaction_id]['compartments'].add(species_info[specie_id]['compartment'])\n if reaction_index2 is not None:\n reactions_info[reaction_id2]['products'].append(specie_id)\n matrix[specie_index, reaction_index2] = -stoichiometry\n species_reactions[specie_index].append(reaction_index2)\n reactions_species[reaction_index2].append(specie_index)\n reactions_info[reaction_id2]['compartments'].add(species_info[specie_id]['compartment'])\n elif part.tag.endswith ('listOfModifiers'):\n for modifier in part:\n assert modifier.tag.endswith('modifierSpeciesReference'), `modifier.tag`\n specie_id = product.attrib['species']\n reactions_info[reaction_id]['modifiers'].append(specie_id)\n reactions_info[reaction_id]['compartments'].add(species_info[specie_id]['compartment'])\n continue\n elif part.tag.endswith ('annotation'):\n reactions_info[reaction_id]['annotation'].append(part.text)\n continue\n elif re.match(r'.*(kineticLaw|notes)\\Z', part.tag): \n continue\n else:\n print 'get_stoichiometry:warning:unprocessed reaction element: %r' % (part.tag)\n continue\n\n\n elif re.match (r'.*(annotation|notes|listOfSpeciesTypes|listOfUnitDefinitions)\\Z', item.tag):\n pass\n else:\n print 'get_stoichiometry:warning:unprocessed model element: %r' % (item.tag)\n\n return matrix, species, reactions, species_info, reactions_info","def get_encoded_faces_arrested():\n encoded = {}\n # c=0\n with open(\"arrested.pkl\",\"rb\") as f:\n encoded=pickle.load(f)\n return encoded","def archivoXl(archivo):\r\n return ow(archivo)","def load_model(self, **params):\n \t# file_name = params['name']\n # return pickle.load(gzip.open(file_name, 'rb'))","def to_xml_dict(self):\n self._check_required_fields()\n\n root = odict[\n \"r:import\": odict[\n \"@xmlns:r\": \"http://resolver.nkp.cz/v3/\",\n \"r:monograph\": odict[\n \"r:titleInfo\": odict[\n \"r:title\": self.title,\n ],\n ],\n ]\n ]\n mono_root = root[\"r:import\"][\"r:monograph\"]\n\n # subtitle\n MonographComposer._assign_pattern(\n mono_root[\"r:titleInfo\"],\n \"r:subTitle\",\n self.subtitle\n )\n\n # handle ccnb, isbn, uuid\n self._add_identifier(mono_root, \"ccnb\")\n self._add_identifier(mono_root, \"isbn\")\n self._add_identifier(mono_root, \"other_id\", out=\"otherId\")\n\n # add form of the book\n MonographComposer._assign_pattern(\n mono_root,\n \"r:documentType\",\n self.document_type\n )\n\n mono_root[\"r:digitalBorn\"] = \"true\" if self.digital_born else \"false\"\n\n if self.author:\n mono_root[\"r:primaryOriginator\"] = odict[\n \"@type\": \"AUTHOR\",\n \"#text\": self.author\n ]\n\n if any([self.place, self.publisher, self.year]):\n publ = odict()\n\n MonographComposer._assign_pattern(\n publ,\n \"r:publisher\",\n self.publisher\n )\n MonographComposer._assign_pattern(publ, \"r:place\", self.place)\n MonographComposer._assign_pattern(publ, \"r:year\", self.year)\n\n mono_root[\"r:publication\"] = publ\n\n if self.format:\n format_dict = MonographComposer._create_path(\n root,\n odict,\n [\n \"r:import\",\n \"r:digitalDocument\",\n \"r:technicalMetadata\",\n \"r:format\",\n ]\n )\n\n format_dict[\"#text\"] = self.format\n\n return root","def __init__(self):\n\n super(aero_csm_component,self).__init__()","def gt_roidb(self):\n # cache_path: data/cache/Actions/\n # self.name: rcnn_<>_<>\n print \"cache_path:\", self.cache_path\n\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n # Get image_index and gt_roidb\n # self._anno_filepath: data/Actions/${datatype}/anno_file.txt\n self._image_index, gt_roidb = self._load_action_annotation(self._anno_filepath)\n\n print \"cache_file:\", cache_file\n with open(cache_file, 'wb') as fid:\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print\n print 'wrote gt roidb to {}'.format(cache_file)\n\n return gt_roidb\n\n\n # ##################################################\n # \n # ##################################################","def init():\n return _libsbml.FbcToCobraConverter_init()","def load_model():\n global columns\n global data\n \n model = pickle.load(open('MedCostModel.pkl', 'rb'))\n data = pd.read_csv('MedCosts.csv')\n data = data.drop(columns=['charges'])\n columns = data.columns\n return(model)","def load(self):\n #print self.fileInfo.name\n progress = self.progress\n filePath = os.path.join(self.fileInfo.dir,self.fileInfo.name)\n self.fileSize = os.path.getsize(filePath)\n #--Localize\n cells = self.cells\n records = self.records\n canSave = self.canSave\n skipObjRecords = self.skipObjRecords\n contTypes = set(['CREC','CNTC','NPCC'])\n levTypes = set(('LEVC','LEVI'))\n debrisIds = self.debrisIds\n debrisTypes = set(debrisIds.keys())\n #--Header\n inPath = os.path.join(self.fileInfo.dir,self.fileInfo.name)\n ins = Tes3Reader(self.fileInfo.name,file(inPath,'rb'))\n (name,size,delFlag,recFlag) = ins.unpackRecHeader()\n self.tes3 = Tes3(name,size,delFlag,recFlag,ins,True)\n if not canSave: del self.tes3.others[:]\n #--Progress info\n progress = self.progress\n progress(0.0,'Loading '+self.fileInfo.name)\n #--Raw data read\n while not ins.atEnd():\n #--Get record info and handle it\n (name,size,delFlag,recFlag) = ins.unpackRecHeader()\n #print \"%s [%d]\" % (name,size)\n #--CELL?\n if name == 'CELL':\n record = Cell(name,size,delFlag,recFlag,ins,0,skipObjRecords)\n cells.append(record)\n if canSave: records.append(record)\n #--Contents\n elif canSave and name in contTypes:\n if name == 'CREC':\n record = Crec(name,size,delFlag,recFlag,ins,True)\n elif name == 'CNTC':\n record = Cntc(name,size,delFlag,recFlag,ins,True)\n else:\n record = Npcc(name,size,delFlag,recFlag,ins,True)\n self.conts.append(record)\n self.conts_id[record.getId()] = record\n records.append(record)\n #--File Map\n elif name == 'FMAP':\n record = Fmap(name,size,delFlag,recFlag,ins)\n self.fmap = record\n records.append(record)\n #--Landscapes\n elif name == 'LAND':\n record = Land(name,size,delFlag,recFlag,ins)\n self.lands[record.getId()] = record\n records.append(record)\n #--Scripts\n elif canSave and name == 'SCPT':\n record = Scpt(name,size,delFlag,recFlag,ins,True)\n records.append(record)\n if record.getRef():\n self.refs_scpt[record] = record.getRef()\n #--Save debris info?\n elif name in debrisTypes:\n record = Record(name,size,delFlag,recFlag,ins)\n id = record.getId()\n if id:\n debrisIds[name].append(id.lower())\n if canSave:\n records.append(record)\n #--Skip Non-cell?\n elif not canSave:\n ins.seek(size,1,name)\n #--Keep non-cell?\n else:\n records.append(Record(name,size,delFlag,recFlag,ins))\n #--Done Reading\n ins.close()\n #--Analyze Cells\n cntCells = 0\n progress.setMax(len(self.cells))\n for cell in self.cells:\n cell.load(None,1)\n self.cells_id[cell.getId()] = cell\n if not canSave:\n cell.data = None #--Free some memory\n #--Progress\n cntCells += 1\n progress(cntCells)\n #--Scripts\n if self.refs_scpt:\n self.updateScptRefs()","def gexf_graph():\n # you must replace these lines and supply your own graph\n \n \n \n my_gexf = Gexf(\"JiajiaXie\", \"My awesome graph\")\n graph=my_gexf.addGraph(\"undirected\", \"static\", \"My awesome networks\")\n \n atr1=graph.addNodeAttribute('Type',type='string')\n\n\n for set in data_specific:\n if graph.nodeExists(set['set_num']) ==0:\n tm1=graph.addNode(set['set_num'], set['name'], r='0', g='0', b='0')\n tm1.addAttribute(atr1,\"set\")\n\n\n\n counter_test=1\n for set, part in data_parts.items():\n for key, part_list in part.items():\n interme =part_list['color']\n red=interme[0]+interme[1]\n green=interme[2]+interme[3]\n blue=interme[4]+interme[5]\n\n red_de=str(int(red,16))\n green_de=str(int(green,16))\n blue_de=str(int(blue,16))\n if graph.nodeExists(part_list['id'])==0:\n tm2=graph.addNode(part_list['id'], part_list['part_name'],r=red_de, g=green_de, b = blue_de)\n tm2.addAttribute(atr1,\"part\")\n\n\n counter_test+=1\n graph.addEdge(\"_\"+str(counter_test), set, part_list['id'], part_list['quantity'])\n\n\n\n f=open('bricks_graph.gexf','wb')\n my_gexf.write(f)\n\n\n return my_gexf.graphs[0]","def creation_srcmdl(dir_cat,SourceRA,SourceDec,SourceROI,distmin,name,outputfile,emin,emax):\n\tf_liste_sour=\"a.txt\"\n\n\tlect_ca(dir_cat,SourceRA,SourceDec,SourceROI,distmin,name,f_liste_sour,name)\n\tXML_EC_PL(name, f_liste_sour, outputfile, emin,emax)\n\tos.system(\"rm -rf a.txt\")","def parse_ben_sb(parent_directory, code):\n s_b = np.loadtxt(parent_directory+code+'res_ave.out')\n return s_b","def __str__(self):\n return self.idBaixasReceber","def load(self):\n\n raise NotImplementedError","def cargar_colores():\n try:\n col = open(os.path.join(absolute_path, \"lib\", \"info\",\"config\" ,\"colores.json\"),\"r\")\n dic_col = json.load(col)\n col.close()\n except (FileNotFoundError):\n sg.popup(\"No se encontro colores.json \\n usando colores predeterminados\",keep_on_top=True)\n dic_col = {\n \"facil\": {\n \"\": \"#FFFFFF\",\n \"+\": \"#ff6699\",\n \"++\": \"#ff99cc\",\n \"+++\": \"#efcfe8\",\n \"++++\": \"#c1a4ff\",\n \"-\": \"#9999ff\",\n \"--\": \"#9966cc\",\n \"---\": \"#6633cc\"\n },\n \"medio\": {\n \"\": \"#82b1ff\",\n \"+\": \"white\",\n \"++\": \"#d50000\",\n \"+++\": \"#efcfe8\",\n \"++++\": \"#c1a4ff\",\n \"-\": \"#c5cae9\",\n \"--\": \"#ffeb3b\",\n \"---\": \"#ff5722\"\n },\n \"dificil\": {\n \"\": \"#e4f3fa\",\n \"+\": \"#f89d89\",\n \"++\": \"#e59e72\",\n \"+++\": \"#9986a9\",\n \"++++\": \"#ce5a57\",\n \"-\": \"#efd692\",\n \"--\": \"#5386a6\",\n \"---\": \"#4fadac\"\n },\n \"atril\":\"#006699\",\n \"letra_jugador\": \"#8da8b7\",\n \"letra_pc\": \"#fed0b9\"\n }\n finally:\n return (dic_col)","def get_model(branch, internet):\n\n url = 'https://raw.githubusercontent.com/sot/chandra_models/master/chandra_models/xija/'\n local_dir = '/AXAFLIB/chandra_models/chandra_models/xija/'\n\n if internet:\n model_spec_url = url + branch # aca/aca_spec.json'\n with urlopen(model_spec_url) as url:\n response = url.read()\n f = response.decode('utf-8')\n else:\n with open(home + local_dir + branch) as fid: # 'aca/aca_spec.json', 'rb') as fid:\n f = fid.read()\n return json.loads(f)","def recuperation(nom):\r\n with open(nom, \"rb\") as fichier:\r\n monDepickler = pickle.Unpickler(fichier)\r\n contenu = monDepickler.load()\r\n\r\n return contenu","def COD(fp):\n lcod = unpack('>H', fp.read(2))[0]\n scod = unpack('B', fp.read(1))[0]\n sgcod = {\n 'progression_order' : unpack('B', fp.read(1))[0],\n 'nr_layers' : unpack('>H', fp.read(2))[0],\n 'mc_transform' : unpack('B', fp.read(1))[0],\n }\n\n # SPcod\n _decomp_levels = unpack('B', fp.read(1))[0]\n _block_width = unpack('B', fp.read(1))[0]\n _block_height = unpack('B', fp.read(1))[0]\n _block_style = unpack('B', fp.read(1))[0]\n _transform = unpack('B', fp.read(1))[0]\n\n _precincts = []\n has_precincts = _get_bit(scod, 7)\n if has_precincts == 1:\n for ii in range(_decomp_levels + 1):\n _precincts.append(unpack('B', fp.read(1))[0])\n\n info = {\n 'Lcod' : lcod,\n 'Scod' : scod,\n 'SGcod' : sgcod,\n 'SPcod' : {\n 'decomp_levels' : _decomp_levels,\n 'block_width' : _block_width,\n 'block_height' : _block_height,\n 'block_style' : _block_style,\n 'transform' : _transform\n }\n }\n\n if has_precincts:\n info['SPcod']['precincts'] = _precincts\n\n return info","def __repr__(self):\n return \"compo of mix %d from file %s\"%(self.m_mix,self.m_filename)","def bimport(filepath, resource_path=None, imgi_import=True, imge_import=True, seq_import=True, mov_import=True, txti_import=True, txte_import=True,\r\n script_import=True, img_embed=False, txt_embed=None, skip_sha1=False, img_merge=True):\r\n \r\n filepath = bpy.path.abspath(filepath) #Ensure path is absolute\r\n \r\n if resource_path is None or resource_path.strip() == \"\":\r\n resource_path = None\r\n else:\r\n resource_path = bpy.path.abspath(resource_path) #Ensure path is absolute\r\n \r\n if path.splitext(filepath)[1] == \".blib\":\r\n try:\r\n archive = zf.ZipFile(filepath, 'r')\r\n except zf.BadZipFile:\r\n raise InvalidBlibFile(\"File is not a valid Blender library\")\r\n \r\n blib = True\r\n try:\r\n file_checksum, blibtype, file_version, compatible, *rest = archive.comment.decode(\"utf-8\").split(\" \")\r\n except ValueError:\r\n raise InvalidBlibFile(\"File is broken, missing meta-data\")\r\n \r\n compatible = Version(compatible)\r\n \r\n if blibtype == \"cycles\":\r\n if compatible <= version:\r\n if archive.testzip() is not None:\r\n raise InvalidBlibFile(\"File is broken\")\r\n else:\r\n if not skip_sha1:\r\n checksum = archive_sha1(archive)\r\n \r\n if not file_checksum == checksum.hexdigest():\r\n raise InvalidBlibFile(\"Checksum does not match, file may be broken or have been altered\\n\"\r\n 'Run with \"skip_sha1\" to ignore checksum')\r\n else:\r\n raise BlibVersionError(\"File has incompatible version of blib\")\r\n else:\r\n raise BlibTypeError(\"File is not a valid Cycles material\")\r\n try:\r\n xml_file = archive.open(\"structure.xml\", 'r')\r\n except KeyError:\r\n raise InvalidBlibFile(\"File is broken, missing structure XML\")\r\n tree = ET.ElementTree(file=xml_file)\r\n xml_file.close()\r\n xroot = tree.getroot()\r\n \r\n elif path.splitext(filepath)[1] == \".xml\":\r\n tree = ET.ElementTree(file=filepath)\r\n xroot = tree.getroot()\r\n blib = False\r\n xversion = Version(xroot.attrib[\"compatible\"])\r\n if xversion > version:\r\n raise BlibVersionError(\"File has incompatible version of blib\")\r\n \r\n else:\r\n raise InvalidBlibFile(\"File is not a Blender library\")\r\n \r\n if xroot.tag != \"blib\":\r\n raise InvalidBlibFile(\"File is not a Blender library\")\r\n \r\n if xroot.attrib[\"type\"] != \"cycles\":\r\n raise BlibTypeError(\"File is not a valid Cycles material\")\r\n \r\n failed = {}\r\n imgs = {}\r\n txts = {}\r\n txt_paths = {}\r\n grps = {}\r\n scripts = {}\r\n resources = {\r\n \"images\": imgs,\r\n \"texts\": txts,\r\n \"text_paths\": txt_paths,\r\n \"groups\": grps,\r\n \"scripts\": scripts,\r\n }\r\n txt_dir = ResourceDir(\"texts\", resource_path)\r\n xres = xroot.find(\"resources\")\r\n \r\n #Import resources\r\n if xres is not None:\r\n ximgs = xres.find(\"images\")\r\n xtxts = xres.find(\"texts\")\r\n xgrps = xres.find(\"groups\")\r\n tmp_path = ResourceDir(\"tmp\", resource_path)\r\n path_dict = {}\r\n \r\n #Images\r\n if ximgs is not None and (imgi_import or imge_import or seq_import or mov_import) and blib:\r\n img_dir = ResourceDir(\"images\", resource_path)\r\n hash_dict = None\r\n sfv_update = False\r\n for ximg in ximgs:\r\n if ximg.attrib[\"source\"] in {'FILE', 'GENERATED'}:\r\n if ximg.attrib[\"origin\"] == \"internal\":\r\n if not imgi_import:\r\n pass\r\n else:\r\n if not imge_import:\r\n pass\r\n elif ximg.attrib[\"source\"] == 'SEQUENCE':\r\n if not seq_import:\r\n pass\r\n elif ximg.attrib[\"source\"] == 'MOVIE':\r\n if not mov_import:\r\n pass\r\n \r\n #Write image to temporary folder, and pack in Blender\r\n if ximg.attrib[\"source\"] in {'FILE', 'GENERATED'} and (img_embed or (img_embed is None and ximg.attrib[\"origin\"] == \"internal\")):\r\n ipath = extract_image(archive, ximg.attrib[\"path\"], str(tmp_path), path_dict, failed)\r\n if ipath is None:\r\n pass\r\n \r\n try:\r\n img = bpy.data.images.load(ipath)\r\n except:\r\n fail(failed, \"images\", \"import image '{}', unknown reason\".format(ximg.attrib[\"path\"]))\r\n else:\r\n img.source = ximg.attrib[\"source\"]\r\n try:\r\n img.pack()\r\n except:\r\n bpy.data.images.remove(img)\r\n fail(failed, \"images\", \"pack image '{}', unknown reason\".format(ximg.attrib[\"path\"]))\r\n else:\r\n img.filepath = \"\"\r\n imgs[ximg.attrib[\"name\"]] = img\r\n \r\n else: #Write image to resource folder, and load in Blender\r\n if img_merge and ximg.attrib[\"source\"] != 'SEQUENCE': #Use existing image in resources if available\r\n try:\r\n comment = archive.getinfo(ximg.attrib[\"path\"]).comment.decode(\"utf-8\")\r\n except KeyError:\r\n fail(failed, \"images\", \"import image '{}', file is missing\".format(ximg.attrib[\"path\"]))\r\n pass\r\n \r\n com_path = path_dict[comment] if comment != \"\" else \"\"\r\n com_name = path.basename(path.dirname(com_path))\r\n if comment != \"\" and com_name != \"tmp\":\r\n ipath = com_path\r\n path_dict[ximg.attrib[\"path\"]] = ipath\r\n else:\r\n #Create hash dictionary only in the first iteration\r\n if hash_dict is None:\r\n hash_path = path.join(img_dir.root, \"list.sfv\")\r\n hash_dict = {}\r\n if path.isfile(hash_path):\r\n sfv = re.compile(r\"(.*) (.*?)$\")\r\n hash_file = open(hash_path, 'r', encoding=\"utf-8\")\r\n for line in hash_file:\r\n key = sfv.sub(r\"\\2\", line).strip()\r\n val = sfv.sub(r\"\\1\", line).strip()\r\n if key in hash_dict and val in hash_dict[key]:\r\n sfv_update = True\r\n else:\r\n hash_dict.setdefault(key, []).append(val)\r\n hash_file.close()\r\n hash_bkp = hash_dict.copy()\r\n \r\n #Check if files match and set path to appropriate image\r\n img_path = ximg.attrib[\"path\"] if comment == \"\" else comment\r\n try:\r\n crc = format(archive.getinfo(img_path).CRC, 'x')\r\n except KeyError:\r\n fail(failed, \"images\", \"import image '{}', file is missing\".format(ximg.attrib[\"path\"]))\r\n pass\r\n \r\n if crc in hash_dict:\r\n i = 0\r\n while i < len(hash_dict[crc]):\r\n val = hash_dict[crc][i]\r\n fpath = path.join(img_dir.root, val)\r\n if path.isfile(fpath):\r\n fsize = path.getsize(fpath)\r\n zsize = archive.getinfo(img_path).file_size\r\n if fsize == zsize:\r\n ffile = open(fpath, 'rb')\r\n zfile = archive.open(img_path, 'r')\r\n if files_equal(ffile, zfile):\r\n ipath = fpath\r\n path_dict[ximg.attrib[\"path\"]] = ipath\r\n ffile.close()\r\n zfile.close()\r\n break\r\n ffile.close()\r\n zfile.close()\r\n else:\r\n hash_dict[crc].remove(val)\r\n i -= 1\r\n i += 1\r\n else:\r\n ipath = extract_image(archive, ximg.attrib[\"path\"], str(img_dir), path_dict, failed)\r\n if ipath is None:\r\n pass\r\n \r\n hash_dict[crc].append(path.relpath(ipath, img_dir.root))\r\n else:\r\n ipath = extract_image(archive, ximg.attrib[\"path\"], str(img_dir), path_dict, failed)\r\n if ipath is None:\r\n pass\r\n \r\n hash_dict[crc] = [path.relpath(ipath, img_dir.root)]\r\n else: #Use image in archive, even if duplicate\r\n if ximg.attrib[\"source\"] == 'SEQUENCE':\r\n seq_dir = path.dirname(ximg.attrib[\"path\"])\r\n dir_name = ximg.attrib[\"path\"].split(\"/\")[-2]\r\n seq_path = path.join(str(img_dir), dir_name)\r\n makedirs(seq_path)\r\n seq_imgs = [img for img in archive.namelist() if img.startswith(seq_dir)]\r\n for img in seq_imgs:\r\n i_tmp_path = extract_image(archive, img, seq_path, path_dict, failed)\r\n if img == ximg.attrib[\"path\"]:\r\n ipath = i_tmp_path\r\n if ipath is None:\r\n break\r\n if ipath is None:\r\n rmtree(seq_path)\r\n pass\r\n else:\r\n ipath = extract_image(archive, ximg.attrib[\"path\"], str(img_dir), path_dict, failed)\r\n if ipath is None:\r\n pass\r\n \r\n #load image to Blender\r\n try:\r\n img = bpy.data.images.load(ipath)\r\n except:\r\n fail(failed, \"images\", \"import image '{}', unknown reason\".format(ximg.attrib[\"path\"]))\r\n else:\r\n img.source = ximg.attrib[\"source\"]\r\n imgs[ximg.attrib[\"name\"]] = img\r\n \r\n if tmp_path:\r\n for item in listdir(str(tmp_path)):\r\n fpath = path.join(str(tmp_path), item)\r\n if path.isfile(fpath):\r\n remove(fpath)\r\n \r\n #Update hash file if list has changed\r\n if hash_dict is not None and (hash_dict != hash_bkp or sfv_update):\r\n hash_path = path.join(img_dir.root, \"list.sfv\")\r\n hash_file = open(hash_path, 'w', encoding=\"utf-8\")\r\n for key in hash_dict:\r\n for val in hash_dict[key]:\r\n hash_file.write(val + \" \" + key + \"\\n\")\r\n hash_file.close()\r\n \r\n #Texts\r\n if xtxts is not None and (txti_import or txte_import):\r\n for xtxt in xtxts:\r\n if xtxt.attrib[\"origin\"] == \"internal\":\r\n if txti_import:\r\n if \"path\" in xtxt.attrib:\r\n if blib:\r\n if txt_embed == False:\r\n import_texts(\"zip\", \"ext\", xtxt, txts, failed, archive, txt_dir)\r\n else:\r\n import_texts(\"zip\", \"int\", xtxt, txts, failed, archive, txt_dir)\r\n else:\r\n if txt_embed == False:\r\n import_texts(\"xml\", \"ext\", xtxt, txts, failed, None, txt_dir)\r\n else:\r\n import_texts(\"xml\", \"int\", xtxt, txts, failed, None, txt_dir)\r\n \r\n else:\r\n if txte_import:\r\n if \"path\" in xtxt.attrib:\r\n if blib:\r\n if txt_embed == True:\r\n import_texts(\"zip\", \"int\", xtxt, txts, failed, archive, txt_dir, txt_paths)\r\n else:\r\n import_texts(\"zip\", \"ext\", xtxt, txts, failed, archive, txt_dir, txt_paths)\r\n else:\r\n if txt_embed == True:\r\n import_texts(\"xml\", \"int\", xtxt, txts, failed, None, txt_dir, txt_paths)\r\n else:\r\n import_texts(\"xml\", \"ext\", xtxt, txts, failed, None, txt_dir, txt_paths)\r\n \r\n #Groups\r\n if xgrps is not None:\r\n for xgrp in xgrps:\r\n xnodes = xgrp.find(\"nodes\")\r\n xlinks = xgrp.find(\"links\")\r\n grp = bpy.data.node_groups.new(xgrp.attrib[\"name\"], xgrp.attrib[\"bl_idname\"])\r\n grps[xgrp.attrib[\"name\"]] = grp\r\n if xnodes is not None:\r\n build_tree(xnodes, xlinks, grp, resources, txt_embed, txt_dir, blib, script_import, archive, failed)\r\n \r\n #Import material\r\n xmat = xroot.find(\"main\")\r\n \r\n if xmat is not None:\r\n xcycles = xmat.find(\"cycles_settings\")\r\n xnodes = xmat.find(\"nodes\")\r\n xlinks = xmat.find(\"links\")\r\n \r\n mat = bpy.data.materials.new(xmat.attrib[\"name\"])\r\n set_attributes(mat, xmat, failed)\r\n set_attributes(mat.cycles, xcycles, failed)\r\n mat.use_nodes = True\r\n mat.node_tree.nodes.clear()\r\n build_tree(xnodes, xlinks, mat.node_tree, resources, txt_embed, txt_dir, blib, script_import, archive, failed)\r\n if blib:\r\n archive.close()\r\n for f in failed:\r\n print(\"{} {} failed to be imported/assigned.\".format(failed[f], f))\r\n return mat\r\n else:\r\n if blib:\r\n archive.close()\r\n for f in failed:\r\n print(\"{} {} failed to be imported/assigned.\".format(failed[f], f))\r\n return grp","def find_mcc_tree():\n command = \"phyltr cat -b 10 --no-annotation indoeuropean.nex | \" \\\n \"phyltr support --sort | \" \\\n \"head -n 1 > mcct.nex\"\n subprocess.call(command, shell=True)","def write_gro(strucC,data_file):\n #\n latvec = strucC.getLatVec()\n\n gro_lines = \" com2gro \\n\"\n gro_lines += \" %-2i \\n\" %( int(len(strucC.ptclC)) )\n atom_indx = 0 \n for pid, pt_i in strucC.ptclC:\n atom_indx += 1\n if( atom_indx > 10000): atom_indx = 1\n r_i = pt_i.position\n r_i_nm = [units.convert_angstroms_nm(r_i[0]) ,units.convert_angstroms_nm(r_i[1]) ,units.convert_angstroms_nm(r_i[2]) ]\n gro_lines += \"%5d%-5s%5s%5d%8.3f%8.3f%8.3f\\n\" % (atom_indx,pt_i.tagsDict[\"resname\"][:5],pt_i.tagsDict[\"label\"][:5],atom_indx,r_i_nm[0],r_i_nm[1],r_i_nm[2] )\n if( atom_indx > 99999 ):\n atom_indx = 1\n \n gro_lines += \" %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f \\n\" % (units.convert_angstroms_nm(latvec[0][0]),units.convert_angstroms_nm(latvec[1][1]),units.convert_angstroms_nm(latvec[2][2]),units.convert_angstroms_nm(latvec[0][1]),units.convert_angstroms_nm(latvec[0][2]),units.convert_angstroms_nm(latvec[1][0]),units.convert_angstroms_nm(latvec[1][2]),units.convert_angstroms_nm(latvec[2][0]),units.convert_angstroms_nm(latvec[2][1])) \n\n F = open( data_file, 'w' )\n F.write(gro_lines)\n F.close()","def write_gro(strucC,data_file):\n #\n latvec = strucC.getLatVec()\n\n gro_lines = \" com2gro \\n\"\n gro_lines += \" %-2i \\n\" %( int(len(strucC.ptclC)) )\n atom_indx = 0 \n for pid, pt_i in strucC.ptclC:\n atom_indx += 1\n if( atom_indx > 10000): atom_indx = 1\n r_i = pt_i.position\n r_i_nm = [units.convert_angstroms_nm(r_i[0]) ,units.convert_angstroms_nm(r_i[1]) ,units.convert_angstroms_nm(r_i[2]) ]\n gro_lines += \"%5d%-5s%5s%5d%8.3f%8.3f%8.3f\\n\" % (atom_indx,pt_i.tagsDict[\"resname\"][:5],pt_i.tagsDict[\"label\"][:5],atom_indx,r_i_nm[0],r_i_nm[1],r_i_nm[2] )\n if( atom_indx > 99999 ):\n atom_indx = 1\n \n gro_lines += \" %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f \\n\" % (units.convert_angstroms_nm(latvec[0][0]),units.convert_angstroms_nm(latvec[1][1]),units.convert_angstroms_nm(latvec[2][2]),units.convert_angstroms_nm(latvec[0][1]),units.convert_angstroms_nm(latvec[0][2]),units.convert_angstroms_nm(latvec[1][0]),units.convert_angstroms_nm(latvec[1][2]),units.convert_angstroms_nm(latvec[2][0]),units.convert_angstroms_nm(latvec[2][1])) \n\n F = open( data_file, 'w' )\n F.write(gro_lines)\n F.close()","def __init__(self, raw_facil, raw_gir, raw_geo, proj):\n address1 = raw_facil.get('address1')\n address2 = raw_facil.get('address2')\n\n lon_lat = None\n if raw_geo:\n lon_lat = proj(\n raw_geo['longitude'],\n raw_geo['latitude'],\n inverse=True\n )\n\n self._init_attributes()\n self.source = 'facil-location'\n self.bldg_id = raw_facil['id']\n self.type = 'building'\n self.tags = []\n self.banner_abbreviation = raw_facil.get('abbreviation')\n self.name = raw_facil.get('name')\n self.campus = self._get_pretty_campus(raw_facil.get('campus'))\n self.address = self._get_address(address1, address2)\n self.city = raw_facil.get('city')\n self.state = raw_facil.get('state')\n self.zip = raw_facil.get('zip')\n self.geo_location = self._create_geo_location(\n lon_lat[0] if lon_lat else None,\n lon_lat[1] if lon_lat else None\n )\n self.geometry = self._create_geometry(\n raw_geo['coordinatesType'] if raw_geo else None,\n raw_geo['coordinates'] if raw_geo else None\n )\n self.gir_count = raw_gir['count'] if raw_gir else 0\n self.gir_limit = bool(raw_gir['limit'].strip()) if raw_gir and raw_gir['limit'] else None\n self.gir_locations = raw_gir['all'].strip() if raw_gir else None\n self.arcgis_abbreviation = (\n (raw_geo.get('abbreviation') if raw_geo else None)\n or (raw_gir.get('abbreviation') if raw_gir else None)\n )\n self.relationships = {'services': {'data': []}}\n self.merge = False\n self.open_hours = None\n self.description = None\n self.descriptionHtml = None\n self.images = None\n self.thumbnails = []\n self.website = None\n self.synonyms = None","def cargar_bolsa(self,lista):\n self.bolsa = lista","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 read_biocontext(name: str) -> PREFIX_MAP:\n path_to_jsonld = HERE / \"registry\" / f\"{name}.jsonld\"\n with open(path_to_jsonld) as file:\n return extract_prefixmap(json.load(file))\n # return read_remote_jsonld_context(\"https://raw.githubusercontent.com/prefixcommons/biocontext/master/registry/\"+name+\".jsonld\")","def getBaseMonetaria(self):\n #Obtener la url de descarga del cvs\n urlPackage=\"https://datos.gob.ar/api/3/action/package_show?id=sspm-factores-explicacion-base-monetaria\"\n s=requests.get(urlPackage).content\n objJson = json.loads(s)\n resultado = objJson['result']['resources']\n selector = 0\n ultimoResultado = resultado[selector]\n urlDescarga = ultimoResultado['url']\n descripcion = ultimoResultado['description']\n print(\"Descargando: {}\".format(descripcion))\n print(\"Archivo: {}\".format(urlDescarga))\n \n #Descargar la url con cvs y generar pandas dataframe\n contenidoCVS = requests.get(urlDescarga).content\n flujoCVS = io.StringIO(contenidoCVS.decode('utf-8'))\n df_temp = pd.read_csv(flujoCVS)\n \n #transform string to datetime\n df_temp['indice_tiempo'] = pd.to_datetime(df_temp['indice_tiempo'], format='%Y-%m-%d', errors='ignore')\n df_temp['indice_tiempo'] = df_temp['indice_tiempo'].dt.date\n #set index\n df_temp.set_index('indice_tiempo', inplace=True)\n \n return df_temp","def zip_imagenet100c():\n #First make sure the directory we are given is correct!\n if not os.path.isdir(DATA_SRC_ROOT):\n raise Exception(\"Bad filepath given\")\n\n #create the destiantion directories if they don't exist\n if not os.path.isdir(IMAGENET100_DIR):\n os.mkdir(IMAGENET100_DIR)\n\n #grab the subset wnids for the 100 class-subset\n with open(IMAGENET100_CLASSES) as f:\n subset_wnids = f.readlines()\n subset_wnids = [x.strip() for x in subset_wnids] #list of the 100 WNIDs we grab\n\n #Grab the names of all of the folders inside the root data source\n #Structure is distortion/sub_distortion/level/wnids\n for distortion in os.listdir(DATA_SRC_ROOT):\n if distortion != \"meta.bin\":\n print(distortion)\n\n folder_path = os.path.join(DATA_SRC_ROOT, distortion)\n\n if not os.path.isdir(folder_path):\n continue\n\n for sub_distortion in os.listdir(folder_path):\n print(sub_distortion)\n\n subfolder_path = os.path.join(folder_path, sub_distortion)\n\n if not os.path.isdir(subfolder_path):\n continue\n\n for level in os.listdir(subfolder_path):\n print(level)\n\n level_path = os.path.join(subfolder_path, level)\n\n #grab the correcrt validation d9recotires\n for wnid in os.listdir(level_path):\n wnid_path = os.path.join(level_path, wnid)\n\n if not os.path.isdir(wnid_path):\n continue\n\n if wnid in subset_wnids:\n dest_path = os.path.join(IMAGENET100_DIR, distortion, sub_distortion, level, wnid)\n\n shutil.copytree(wnid_path, dest_path)\n\n #copy the metadata bin file\n meta_file = os.path.join(DATA_SRC_ROOT, 'meta.bin')\n meta_dest = os.path.join(IMAGENET100_DIR, 'meta.bin')\n\n shutil.copy(meta_file, meta_dest)\n\n #Zip the destinatio file\n shutil.make_archive(ZIP_PATH + '/ImageNet100C', 'tar', IMAGENET100_DIR)","def _blob(self):\n self.__rewrite_sldIdLst()\n # # at least the following needs to be added before using\n # # _reltype_ordering again for Presentation\n # self.__rewrite_notesMasterIdLst()\n # self.__rewrite_handoutMasterIdLst()\n # self.__rewrite_sldMasterIdLst()\n return super(Presentation, self)._blob","def mapping_stratum(download_files =True):\r\n # get code description _index \r\n ix_= AGSO_PROPERTIES['props_codes'].index('name')\r\n def mfunc_(d): \r\n \"\"\" Set individual layer in dict of properties \"\"\"\r\n _p= {c: k.lower() if c not in ('code', 'label', 'name') else k \r\n for c, k in zip(AGSO_PROPERTIES['props_codes'], d) }\r\n id_= d[ix_].replace('/', '_').replace(\r\n ' ', '_').replace('\"', '').replace(\"'\", '').lower()\r\n return id_, _p \r\n rock_and_structural_props =list()\r\n for agso_data in tuple(set_agso_properties(download_files)): \r\n # remove the header of the property file\r\n rock_and_structural_props.append(\r\n dict(map( lambda x: mfunc_(x), agso_data[1:])))\r\n \r\n return tuple(rock_and_structural_props)","def _serialise(self):\n # TODO (M Foley)\n pass"],"string":"[\n \"def load(self):\",\n \"def mezclar_bolsa(self):\",\n \"def load_ccs9():\\n ccs9 = pd.read_csv(pkg_resources.resource_filename(__name__,'$dxref 2015.csv'))\\n ccs9 = ccs9.reset_index()\\n for col in ccs9.columns:\\n ccs9.loc[:,col]=ccs9[col].str.strip('\\\\'')\\n ccs9.columns=ccs9.iloc[0,:]\\n ccs9 = ccs9.iloc[1:,:]\\n ccs9 = ccs9.replace(r'^\\\\s*$', np.nan, regex=True)\\n ccs9 = ccs9.loc[ccs9['ICD-9-CM CODE'].notnull(),:]\\n ccs9.loc[:,'ICD-9-CM CODE'] = ccs9['ICD-9-CM CODE'].str.replace(' ','')\\n ccs9.loc[:,'CCS CATEGORY'] = ccs9['CCS CATEGORY'].str.replace(' ','')\\n ccs9 = ccs9.iloc[:,0:4] \\n ccs9_labels = pd.read_csv(pkg_resources.resource_filename(__name__,'dxlabel 2015.csv'))\\n ccs9 = ccs9.merge(ccs9_labels,how='left',left_on='CCS CATEGORY',right_on='CCS DIAGNOSIS CATEGORIES')\\n ccs9.drop('CCS CATEGORY DESCRIPTION',axis=1,inplace=True)\\n ccs9.drop('CCS DIAGNOSIS CATEGORIES',axis=1,inplace=True)\\n ccs9.columns = [i.replace('CCS DIAGNOSIS CATEGORIES LABELS','CCS CATEGORY DESCRIPTION') for i in ccs9.columns]\\n return ccs9\",\n \"def lcia_methods__metadata(self):\\r\\n with UnicodeReader(os.path.join(dirpath, \\\"categoryUUIDs.csv\\\"), \\r\\n encoding='latin-1', \\r\\n delimiter=dt) as csv_file:\\r\\n next(csv_file) \\r\\n csv_data = [{'name': (line[0], line[2], line[4]),\\r\\n 'description': line[7]\\r\\n } for line in csv_file]\\r\\n \\r\\n filename = \\\"LCIA_implementation_2019.xlsx\\\" # this was donwloaded and updated on Oct 2019 from ecoinvent website. \\r\\n wb = xlrd.open_workbook(os.path.join(dirpath, filename))\\r\\n #characterizaton factors\\r\\n sheet= wb.sheet_by_name(\\\"CFs\\\")\\r\\n cf_data = [{\\r\\n 'method': (sheet.cell(row, 0).value,\\r\\n sheet.cell(row, 1).value,\\r\\n sheet.cell(row, 2).value),\\r\\n 'name': sheet.cell(row, 3).value,\\r\\n 'categories': (sheet.cell(row, 4).value, sheet.cell(row, 5).value),\\r\\n 'amount': sheet.cell(row, 7).value\\r\\n }\\r\\n for row in range(1, sheet.nrows)\\r\\n if sheet.cell(row, 0).value not in \\r\\n {'selected LCI results, additional', 'selected LCI results'} and isinstance(sheet.cell(row, 7).value, Number)]\\r\\n #units\\r\\n sheet= wb.sheet_by_name(\\\"units\\\")\\r\\n units = {(sheet.cell(row, 0).value, sheet.cell(row, 1).value, \\r\\n sheet.cell(row, 2).value): sheet.cell(row, 4).value for row in range(1, sheet.nrows)}\\r\\n return csv_data, cf_data, units, filename\",\n \"def build(c):\",\n \"def mol_to_cbor(mol: masm.Molecule) -> str:\\n serializer = masm.JsonSerialization\\n cbor_format = serializer.BinaryFormat.CBOR\\n serialization = serializer(mol)\\n cbor_binary = serialization.to_binary(cbor_format)\\n return serializer.base_64_encode(cbor_binary)\",\n \"def get_model_and_assets():\\n\\n return common.read_model('cloth_corner.xml'),common.ASSETS\",\n \"def load_data(self):\",\n \"def presenetCar():\",\n \"def read_meta(self):\\n meta = cPickle.load(open('../sugar_analysis_data/META-CABALLO2.pkl'))\\n self.meta_sn_name_list = []\\n self.meta_zcmb = []\\n self.meta_x0 =[]\\n self.meta_x0_err = []\\n self.meta_x1 =[]\\n self.meta_x1_err = []\\n self.meta_c = []\\n self.meta_c_err = []\\n self.meta_mb = []\\n self.meta_mb_err = []\\n self.meta_cov_x0_x1 = [] \\n self.meta_cov_x0_c = []\\n self.meta_cov_x1_c = []\\n self.meta_cov_mb_x1 = []\\n self.meta_cov_mb_c = [] \\n self.meta_zhl = []\\n self.meta_zhl_err = []\\n self.meta_idr = []\\n for meta_sn_name in meta.keys(): \\n \\n if meta[meta_sn_name]['idr.subset'] != 'bad' and meta[meta_sn_name]['idr.subset'] != 'auxiliary':\\n \\n self.meta_sn_name_list.append(meta_sn_name)\\n self.meta_zhl_err.append(meta[meta_sn_name]['host.zhelio.err'])\\n self.meta_zhl.append(meta[meta_sn_name]['host.zhelio'])\\n self.meta_zcmb.append(meta[meta_sn_name]['host.zcmb'])\\n self.meta_x0.append(meta[meta_sn_name]['salt2.X0'])\\n self.meta_x0_err.append(meta[meta_sn_name]['salt2.X0.err'])\\n self.meta_x1.append(meta[meta_sn_name]['salt2.X1'])\\n self.meta_x1_err.append(meta[meta_sn_name]['salt2.X1.err'])\\n self.meta_c.append(meta[meta_sn_name]['salt2.Color'])\\n self.meta_c_err.append(meta[meta_sn_name]['salt2.Color.err'])\\n self.meta_mb.append(meta[meta_sn_name]['salt2.RestFrameMag_0_B'])\\n self.meta_mb_err.append(meta[meta_sn_name]['salt2.RestFrameMag_0_B.err'])\\n self.meta_cov_x0_x1.append(meta[meta_sn_name]['salt2.CovX0X1'])\\n self.meta_cov_x0_c.append(meta[meta_sn_name]['salt2.CovColorX0'])\\n self.meta_cov_x1_c.append(meta[meta_sn_name]['salt2.CovColorX1'])\\n self.meta_cov_mb_x1.append(meta[meta_sn_name]['salt2.CovRestFrameMag_0_BX1'])\\n self.meta_cov_mb_c.append(meta[meta_sn_name]['salt2.CovColorRestFrameMag_0_B'])\\n self.meta_idr.append(meta[meta_sn_name]['idr.subset'])\\n \\n self.meta_idr = np.array(self.meta_idr)\\n self.meta_zcmb = np.array(self.meta_zcmb)\\n self.meta_zhl = np.array(self.meta_zhl)\\n self.meta_zhl_err = np.array(self.meta_zhl_err)\\n self.meta_x0 = np.array(self.meta_x0)\\n self.meta_x0_err = np.array(self.meta_x0_err)\\n self.meta_x1 = np.array(self.meta_x1)\\n self.meta_x1_err = np.array(self.meta_x1_err) \\n self.meta_c = np.array(self.meta_c)\\n self.meta_c_err = np.array(self.meta_c_err)\\n self.meta_mb = np.array(self.meta_mb)\\n self.meta_mb_err = np.array(self.meta_mb_err)\\n self.meta_cov_x0_x1 = np.array(self.meta_cov_x0_x1)\\n self.meta_cov_x0_c = np.array(self.meta_cov_x0_c)\\n self.meta_cov_x1_c = np.array(self.meta_cov_x1_c)\\n self.meta_cov_mb_x1 = np.array(self.meta_cov_mb_x1)\\n self.meta_cov_mb_c = np.array(self.meta_cov_mb_c)\",\n \"def processa_compra(self, compra):\\n\\n print(\\\"Boleto criado!\\\\n\\\" + compra.nota_fiscal)\",\n \"def convertion_binaire_arbre(self):\\r\\n binary_code = self.root.conversion_binaire('')\\r\\n binary_dict = {}\\r\\n binary_code = binary_code.strip().split(\\\"\\\\n\\\")\\r\\n for element in binary_code:\\r\\n binary_dict[element.split(\\\":\\\")[0]] = element.split(\\\":\\\")[1]\\r\\n return binary_dict\",\n \"def agregar_bolsa(self, letra, cantidad):\",\n \"def load_data():\\r\\n print ('Loadng all the file one time......')\\r\\n if not os.path.exists('cifar.pkl'):\\r\\n set_data()\\r\\n with open('cifar.pkl', 'rb') as cifar_pickle:\\r\\n data = six.moves.cPickle.load(cifar_pickle)\\r\\n return data\",\n \"def _download_cxr_model(self):\\n file_id = \\\"1KIsLmVv8jKTVG_LxchMZAvR7rugHy7uB\\\"\\n download_from_google_drive(file_id=file_id, folder=\\\"data/\\\", name=\\\"covid_cxr.zip\\\")\",\n \"def read_acbr(self):\\n return self.ACBR\",\n \"def model() -> Any:\\n with open(\\\"airbnb_regressor.pickle\\\",\\\"rb\\\") as f:\\n model = pickle.load(f)\\n return model\",\n \"def CL(self):\",\n \"def load(self, filename):\\n # XXX Hay que comprobar los datos leidos y lanzar excepcion\\n f = open(filename)\\n prelaciones = []\\n asig = []\\n rec = []\\n l = f.readline()\\n while l:\\n # Activities and following activities\\n if l[0:21] == 'PRECEDENCE RELATIONS:':\\n f.readline()\\n l = f.readline()\\n while l[0] != '*':\\n data = l.split()\\n prel = (data[0], data[3:])\\n prelaciones.append(prel)\\n l = f.readline()\\n\\n # Activity duration and resource units needed\\n if l[0] == '-':\\n l = f.readline()\\n while l[0] != '*':\\n asig.append(l.split())\\n l = f.readline()\\n\\n # Name, type and unit of resources\\n if l[0:22] == 'RESOURCEAVAILABILITIES':\\n l = f.readline()\\n while l[0] != '*':\\n rec.append(l.split())\\n l = f.readline()\\n\\n l = f.readline()\\n \\n # Create data structure\\n cont = 1\\n activities = []\\n for prelacion in prelaciones:\\n activities.append([cont, prelacion[0], prelacion[1], '', '', '', '', '', ('Beta')])\\n cont += 1 \\n\\n # Update activities duration\\n for n in range(len(asig)): \\n activities[n][6] = float(asig[n][2])\\n\\n # Update resources\\n i = 1\\n m = 0\\n resources = []\\n if len(rec) < 2:\\n raise InvalidFileFormatException()\\n\\n for n in range(len(rec[1])):\\n # Renewable\\n if rec[0][m]=='R' or rec[0][m][0]=='R':\\n if rec[0][m]=='R':\\n row=[rec[0][m]+rec[0][i], 'Renewable', '', rec[1][n]] \\n m+=2\\n else:\\n row=[rec[0][m], 'Renewable', '', rec[1][n]] \\n m+=1 \\n # Non Renewable\\n elif rec[0][m]=='N' or rec[0][m][0]=='N':\\n if rec[0][m]=='N':\\n row=[rec[0][m]+rec[0][i], 'Non renewable', rec[1][n], '']\\n m+=2\\n else:\\n row=[rec[0][m], 'Non renewable', rec[1][n], ''] \\n m+=1\\n # Double constrained\\n elif rec[0][m]=='D' or rec[0][m][0]=='D':\\n if rec[0][m]=='D':\\n row=[rec[0][m]+rec[0][i], 'Double constrained', rec[1][n], rec[1][n]]\\n m+=2\\n else:\\n row=[rec[0][m], 'Double constrained', rec[1][n], rec[1][n]] \\n m+=1\\n \\n resources.append(row)\\n i += 2\\n # Note: Unlimited resources are not present on PSPLIB projects and so \\n # not taken into account here\\n\\n # Resources needed per activity\\n asignation = []\\n for n in range(len(asig)): \\n for m in range(3, 3+len(rec[1])): #len(self.rec[1]): number of resources \\n if asig[n][m] != '0': #unused resources are not shown\\n i = m-3\\n row = [asig[n][0], resources[i][0], asig[n][m]] \\n asignation.append(row)\\n \\n return (activities, [], resources, asignation)\",\n \"def archivoXlFormateado(archivo):\\r\\n return ow(archivo, formatting_info=True)\",\n \"def crf_entities():\\n if not os.path.isfile(PATH_ENTITIES['crf']['model']):\\n print('downloading ENTITIES frozen CRF model')\\n download_file(\\n S3_PATH_ENTITIES['crf']['model'], PATH_ENTITIES['crf']['model']\\n )\\n with open(PATH_ENTITIES['crf']['model'], 'rb') as fopen:\\n model = pickle.load(fopen)\\n return CRF(model)\",\n \"def climat_model_build(self) :\\n dict_climat = dict()\\n list_state = self._df.ORIGIN_STATE_ABR.unique().tolist()\\n # Climat tempéré océanique : 1\\n dict_climat['WA']=1\\n dict_climat['OR']=1\\n\\n # Climat tempéré continental sec : 2\\n list_climate_2 = ['ID','MT','WY','UT','CO','ND','SD','NE','KS','OK']\\n for state in list_climate_2 :\\n dict_climat[state]=2\\n\\n # Climat tempéré continental pacifique : 3\\n\\n # Climat sub-tropical : 4\\n list_climate_4 = ['VA','NC','GA','FL','AL','TN','MS','LA','AR']\\n for state in list_climate_4 :\\n dict_climat[state]= 4\\n\\n # Climat Aride : 5\\n list_climate_5 = ['AZ','TX','NM','NV']\\n for state in list_climate_5 :\\n dict_climat[state]= 5\\n\\n # Climat tempéré méditéranéen : 6\\n list_climate_6 = ['CA']\\n for state in list_climate_6 :\\n dict_climat[state]= 6\\n\\n for state in list_state :\\n if state not in dict_climat.keys() :\\n dict_climat[state] = 3\\n\\n self.dict_climat = dict_climat\\n self._df['ORIGIN_CLIMAT'] = self._df.ORIGIN_STATE_ABR.apply(self._state_climate_build)\\n self._df['DEST_CLIMAT'] = self._df.DEST_STATE_ABR.apply(self._state_climate_build)\",\n \"def on_load(self):\\n filename = QtGui.QFileDialog.getOpenFileName(self, \\\"Open file\\\", \\\"\\\", \\\"*.scc\\\")\\n print(\\\"Load file \\\", filename)\\n if filename == \\\"\\\":\\n return\\n f = open(filename, mode=\\\"rb\\\")\\n state = pickle.load(f)\\n f.close() \\n cmp = ComponentRect()\\n cmp.set_state(state)\\n self.mdl.set_component(cmp)\",\n \"def mol_from_cbor(cbor_str: str) -> masm.Molecule:\\n serializer = masm.JsonSerialization\\n cbor_binary = serializer.base_64_decode(cbor_str)\\n cbor_format = serializer.BinaryFormat.CBOR\\n serialization = serializer(cbor_binary, cbor_format)\\n return serialization.to_molecule()\",\n \"def descompactar(caminho, nome, formato):\\n\\n # Abre e le o arquivo\\n arquivo = Arquivo(caminho, nome, formato)\\n cabecalho_compactado = arquivo.ler()\\n\\n #----------------------------------------\\n\\n # Descompactacao do cabecalho por meio do gzip\\n cabecalho = g.decompress(cabecalho_compactado)\\n\\n #----------------------------------------\\n\\n # Cabecalho\\n numero_magico = int.from_bytes(cabecalho[0:1], byteorder=\\\"big\\\") \\n if numero_magico != 42:\\n exit()\\n\\n largura = int.from_bytes(cabecalho[1:3], byteorder=\\\"big\\\")\\n altura = int.from_bytes(cabecalho[3:5], byteorder=\\\"big\\\")\\n quantidade_cores = int.from_bytes(cabecalho[5:6], byteorder=\\\"big\\\")\\n lista = list(cabecalho[6:262])\\n conteudo = list(cabecalho[262:len(cabecalho)])\\n\\n #----------------------------------------\\n \\n # Amplia para 8 bits\\n bit = Bitwise(6)\\n imagem_rotulada = bit.ampliar(conteudo, largura*altura)\\n\\n #----------------------------------------\\n\\n # Cria a tabela\\n matriz = [[lista[y], lista[y+1], lista[y+2], lista[y+3]] for y in range(0, len(lista), 4)]\\n tabela = Tabela(matriz)\\n\\n #----------------------------------------\\n\\n # Cria um objeto da classe Imagem\\n final = Imagem(caminho, nome+\\\"_som\\\", \\\"TIFF\\\")\\n # Salva a imagem\\n final.salvar(largura, altura, imagem_rotulada, tabela)\",\n \"def load(self):\\n pass\",\n \"def load(self):\\n pass\",\n \"def load(self):\\n pass\",\n \"def load(self):\\n pass\",\n \"def load_building_blocks(path):\\t\\t\\n\\t#TODO : automatization\\n\\tbenzene = Building_Block(abbrev=\\\"B\\\", num_atoms=6,origin=0, para_pos=3, para_angle=0, meta_pos=4 , meta_angle = -np.pi/3., ortho_pos=5, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\\\"/benzene.xyz\\\")\\n\\tnapthtalene = Building_Block(abbrev=\\\"N\\\", num_atoms=18,origin=0, para_pos=12, para_angle=0., meta_pos=11 , meta_angle = -np.pi/3., ortho_pos=10, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\\\"/naphtalene.xyz\\\")\\n\\tdbPc1 = Building_Block(abbrev=\\\"dbPc1\\\", num_atoms=32,origin=13, para_pos=1, para_angle=0, meta_pos=0 , meta_angle = +np.pi/3., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\\\"/dbPc1_block.xyz\\\")\\n\\tdbPc4 = Building_Block(abbrev=\\\"dbPc4\\\", num_atoms=55,origin=22, para_pos=1, para_angle=0, meta_pos=0 , meta_angle = -np.pi/3., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\\\"/dbPc4.xyz\\\")\\n\\tdbPc6 = Building_Block(abbrev=\\\"dbPc6\\\", num_atoms=52,origin=17, para_pos=0, para_angle=0, meta_pos=1 , meta_angle = -np.pi/3., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\\\"/dbPc6.xyz\\\")\\n\\tdbPc5 = Building_Block(abbrev=\\\"dbPc5\\\", num_atoms=58,origin=12, para_pos=26, para_angle=0, meta_pos=20 , meta_angle = -np.pi/3., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\\\"/dbPc5.xyz\\\")\\n\\tpseudo_para_naph_PCP = Building_Block(abbrev=\\\"pseudo-para_naph_PCP\\\", num_atoms=44,origin=0, para_pos=18, para_angle=0, meta_pos=16 , meta_angle = -np.pi/3, ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\\\"/pseudo-para_naph_PCP.xyz\\\")\\n\\tline =Building_Block(abbrev=\\\"line\\\", num_atoms=4,origin=0, para_pos=1, para_angle=0, meta_pos=1 , meta_angle = 0., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=1, path=path+\\\"/line.xyz\\\")\\n\\t#rot=Building_Block(abbrev=\\\"line\\\", num_atoms=47,origin=6, para_pos=16, para_angle=0, meta_pos=20 , meta_angle = 0., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=2, path=path+\\\"/rot.xyz\\\")\\n\\t#stacked_anth=Building_Block(abbrev=\\\"stacked_anth\\\", num_atoms=62,origin=3, para_pos=22, para_angle=0, meta_pos=30 , meta_angle = 0., ortho_pos=0, ortho_angle=-2.*np.pi/3, fixed_left = -1,complexity=2, path=path+\\\"/stacked_anth.xyz\\\")\\n\\t\\n\\tbuilding_blocks = [benzene,napthtalene,dbPc1,dbPc4,dbPc6, dbPc5,pseudo_para_naph_PCP, line]\\n\\n\\treturn building_blocks\",\n \"def read_redmapper():\\n redfile = os.path.join(os.sep, 'global', 'work', 'projects', \\n 'redmapper', 'redmapper_isedfit_v5.10_centrals.fits.gz')\\n print('Reading {}'.format(redfile))\\n cat = fitsio.read(redfile, ext=1)\\n return cat\",\n \"def readSurfaceGeo(b18path):\\n if not os.path.isfile(b18path):\\n print(\\\"b18 building file not found! Please check!\\\")\\n pass\\n else:\\n b18file = open(b18path,\\\"r\\\")\\n b18data = b18file.readlines()\\n srfGeoBlock = getDataParagraph(\\\"_EXTENSION_BuildingGeometry_START_\\\", \\\"_EXTENSION_BuildingGeometry_END_\\\", b18data)\\n #now get vertex's coordinate xyz\\n vertexdict = dict() #{vertexID:[x,y,z]}\\n srfbasicinfo = dict() #{surfaceID:[vertexID]}\\n srfInfo = dict() #{surfaceID:[vertices coordinate]}\\n for line in srfGeoBlock:\\n dline = line.split()\\n if \\\"vertex\\\" in dline:\\n vertexdict[int(dline[1])] = [float(xyz) for xyz in dline[2:]] #{vertexID:[x,y,z]}\\n if \\\"wall\\\" in dline or \\\"window\\\" in dline or \\\"floor\\\" in dline or \\\"ceiling\\\" in dline or \\\"roof\\\" in dline:\\n srfbasicinfo[int(dline[1])] = [[int(nrID) for nrID in dline[2:]],dline[0]] #{surfaceID:[[vertexID],construction]}\\n #print srfbasicinfo[int(dline[1])]\\n for key in srfbasicinfo.keys():\\n srfInfo[key] = []\\n for vertices in srfbasicinfo[key][0]:\\n srfInfo[key].append(vertexdict[vertices])\\n b18file.close()\\n return srfInfo,vertexdict,srfbasicinfo\\n #actually only need srfInfo\\n #just getting everything out for now, incase will need to use those\",\n \"def get_roidb(self):\\n # get all the images_ids in this dataset\\n img_ids = self._COCO.getImgIds()\\n # sort the ids, make each time the same order\\n img_ids.sort()\\n # load the 'image' of the COCO dataset\\n roidb = copy.deepcopy(self._COCO.loadImgs(img_ids))\\n for entry in roidb:\\n # predefine some attribute of each image\\n self._prep_roidb_entry(entry)\\n\\n # for cahce_dir\\n if not os.path.exists(self.cache_dir):\\n os.mkdir(self.cache_dir)\\n cache_file = os.path.join(self.cache_dir, self.annFile + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n self._read_roidb_from_cachefile(roidb, cache_file)\\n print('{} gt roidb loaded from {}'.format(self.annFile, cache_file))\\n else:\\n for entry in roidb:\\n self._add_roidb_from_annotations(entry)\\n with open(cache_file, 'wb') as f:\\n pickle.dump(roidb, f, pickle.HIGHEST_PROTOCOL)\\n print('wrote gt roidb to {}'.format(cache_file))\\n return roidb\",\n \"def load_data(self) -> None:\",\n \"def load_cci9():\\n cci9 = pd.read_csv(pkg_resources.resource_filename(__name__,'cci2015.csv'),skiprows=1)\\n cci9.columns = [i.strip('\\\\'') for i in cci9.columns]\\n \\n for col in cci9.columns:\\n cci9.loc[:,col] = cci9[col].str.strip('\\\\'')\\n cci9 = cci9.replace(r'^\\\\s*$', np.nan, regex=True)\\n cci9.columns=[i.replace('CATEGORY DESCRIPTION','CHRONIC') for i in cci9.columns]\\n\\n dict_bodysystem=[\\n ('1' ,'Infectious and parasitic disease'),\\n ('2' ,'Neoplasms'),\\n ('3' ,'Endocrine, nutritional, and metabolic diseases and immunity disorders'),\\n ('4' ,'Diseases of blood and blood-forming organs'),\\n ('5' ,'Mental disorders'),\\n ('6' ,'Diseases of the nervous system and sense organs'),\\n ('7' ,'Diseases of the circulatory system'),\\n ('8' ,'Diseases of the respiratory system'),\\n ('9' ,'Diseases of the digestive system'),\\n ('10','Diseases of the genitourinary system'),\\n ('11','Complications of pregnancy, childbirth, and the puerperium'),\\n ('12','Diseases of the skin and subcutaneous tissue'),\\n ('13','Diseases of the musculoskeletal system'),\\n ('14','Congenital anomalies'),\\n ('15','Certain conditions originating in the perinatal period'),\\n ('16','Symptoms, signs, and ill-defined conditions'),\\n ('17','Injury and poisoning'),\\n ('18','Factors influencing health status and contact with health service'),\\n ]\\n \\n cci9 = cci9.merge(pd.DataFrame(dict_bodysystem,columns=['BODY SYSTEM','BODY SYSTEM DESCRIPTION']),how='left',on='BODY SYSTEM')\\n \\n cci9.loc[:,'ICD-9-CM CODE'] = cci9['ICD-9-CM CODE'].str.replace(' ','')\\n \\n return cci9\",\n \"def to_ir(self):\",\n \"def cargar_atril(self,lista,bolsa):\\n self.atril = lista\\n self.bolsa = bolsa\",\n \"def _build(self):\",\n \"def _build(self):\",\n \"def import_cml(self, fname):\\n self.ftype = 'cml'\\n with open(fname) as f:\\n lines = f.readlines()\\n self.n_atom = 0\\n self.n_connect = 0\\n self.sym = []\\n self.at_num = []\\n self.xyz = []\\n self.connect = []\\n for i in range(len(lines)):\\n if lines[i].split()[0] == '<atom':\\n self.n_atom += 1\\n tmp = lines[i].split()\\n self.sym.append(tmp[2].split('\\\"')[1])\\n self.at_num.append(self.sym2num(tmp[2].split('\\\"')[1]))\\n x = float(tmp[3].split('\\\"')[1])\\n y = float(tmp[4].split('\\\"')[1])\\n z = float(tmp[5].split('\\\"')[1])\\n self.xyz.append([x, y, z])\\n elif lines[i].split()[0] == '<bond':\\n self.n_connect += 1\\n tmp = lines[i].split()\\n a = int(tmp[1].split('\\\"')[1].split('a')[1])\\n b = int(tmp[2].split('\\\"')[0].split('a')[1])\\n self.connect.append([a, b])\\n self.xyz = np.array(self.xyz)\",\n \"def read(self):\\n import cclib\\n from pybel import readfile\\n\\n molecule = next(readfile(\\\"orca\\\", self._file))\\n\\n atom_numbers = []\\n coordinates = []\\n\\n for atom in molecule:\\n atom_number = atom.atomicnum\\n atom_numbers.append(atom_number)\\n for coord in atom.coords:\\n coordinates.append(coord)\\n\\n molecular_mass = molecule.exactmass\\n\\n cjson = {\\n \\\"chemical json\\\": 0,\\n \\\"atoms\\\": {\\n \\\"elements\\\": {\\\"number\\\": atom_numbers},\\n \\\"coords\\\": {\\\"3d\\\": coordinates},\\n },\\n \\\"properties\\\": {\\\"molecular mass\\\": molecular_mass},\\n }\\n\\n data = cclib.io.ccread(self._file)\\n\\n # Add calculated properties\\n if hasattr(data, \\\"scfenergies\\\"):\\n if len(data.scfenergies) > 0:\\n energy = data.scfenergies[-1] * EV_TO_J_MOL\\n cjson.setdefault(\\\"properties\\\", {})[\\\"totalEnergy\\\"] = energy\\n\\n if hasattr(data, \\\"gbasis\\\"):\\n basis = _cclib_to_cjson_basis(data.gbasis)\\n cjson[\\\"basisSet\\\"] = basis\\n\\n if hasattr(data, \\\"vibfreqs\\\"):\\n vibfreqs = list(data.vibfreqs)\\n cjson.setdefault(\\\"vibrations\\\", {})[\\\"frequencies\\\"] = vibfreqs\\n\\n if hasattr(data, \\\"vibdisps\\\"):\\n vibdisps = _cclib_to_cjson_vibdisps(data.vibdisps)\\n cjson.setdefault(\\\"vibrations\\\", {})[\\\"eigenVectors\\\"] = vibdisps\\n\\n # Add a placeholder intensities array\\n if \\\"vibrations\\\" in cjson and \\\"frequencies\\\" in cjson[\\\"vibrations\\\"]:\\n if \\\"intensities\\\" not in cjson[\\\"vibrations\\\"]:\\n cjson[\\\"vibrations\\\"][\\\"intensities\\\"] = [\\n 1 for i in range(len(cjson[\\\"vibrations\\\"][\\\"frequencies\\\"]))\\n ]\\n if \\\"modes\\\" not in cjson[\\\"vibrations\\\"]:\\n cjson[\\\"vibrations\\\"][\\\"modes\\\"] = [\\n i + 1 for i in range(len(cjson[\\\"vibrations\\\"][\\\"frequencies\\\"]))\\n ]\\n\\n return cjson\",\n \"def build():\",\n \"def ReadGBMCatalogueOneLine(nameGrb, path_catlogue_csv = \\\"/disk/gamma/cta/store/takhsm/FermiData/catalogue/GBM-BusrtCatalogue_20170623.csv\\\"):\\n dct_info = {}\\n num_lines = sum(1 for line in open(path_catlogue_csv))\\n csv = pandas.read_csv(path_catlogue_csv)\\n for iGrb in range(num_lines-1):\\n if int(nameGrb) == int(csv.ix[iGrb,'name']):\\n dct_info['ra'] = float(csv.ix[iGrb,'ra'])\\n dct_info['dec'] = float(csv.ix[iGrb,'dec']) \\n dct_info['trigger_time'] = pMETandMJD.ConvertMjdToMet(float(csv.ix[iGrb,'trigger_time']))\\n dct_info['error_radius'] = float(csv.ix[iGrb,'error_radius'])\\n return dct_info\",\n \"def load_resource():\\n resource_file = 'curves/' + self.combo_box[\\\"class\\\"].get() + '.json'\\n self.classes[\\\"fractal\\\"].curve.load_from_resource(\\n resource_file)\\n self.classes[\\\"fractal\\\"].curve.set_parent_parameters()\\n self.classes[\\\"parameters\\\"].rules_frame_class.fill_entries_from_rules(\\n self.classes[\\\"fractal\\\"].rules)\\n self.classes[\\\"parameters\\\"].set_base_length_entry(\\n self.classes[\\\"fractal\\\"].base_length)\\n self.classes[\\\"parameters\\\"].rules_frame_class.render_preview()\",\n \"def _load_model(self):\\n with open(self.filepath, 'rb') as file:\\n self.cmodel = pickle.load(file)\",\n \"def create_cab(self):\\n cab = Cab()\\n cab.type = self.info['type']\\n cab.driver_name = self.info.get('driver_name')\\n cab.rc_number = self.info['rc_number']\\n cab.city_id = self.info['city_id']\\n cab.company_name = self.info['company_name']\\n cab.model_name = self.info['model_name']\\n cab.update_time = datetime.utcnow().replace(microsecond=0)\\n self.cab_id = self.save(cab)\\n\\n # we can do asynchronously\\n self.create_cab_state()\\n return self.cab_id\",\n \"def read(self):\",\n \"def __bytes__(self):\\n line1=self.name.encode(\\\"ascii\\\").ljust(24,b\\\" \\\")\\n line2=b\\\"1 %05dU %02d%03d%-3b %02d%012.8f %c.%08d %c%05d%+01d %c%05d%+01d 0 %04d\\\" %\\\\\\n (self.id,self.desig[\\\"year\\\"]%100,self.desig[\\\"launch\\\"],\\\\\\n self.desig[\\\"object\\\"].encode(\\\"ascii\\\"),self.epoch[\\\"year\\\"]%100,\\\\\\n self.epoch[\\\"day\\\"],b\\\"-\\\" if self.fdmm<0 else b\\\" \\\",abs(self.fdmm*1.e8),\\\\\\n b\\\"-\\\" if self.sdmm<0 else b\\\" \\\",\\\\\\n abs(self.sdmm*pow(10,5-(ceil(log(abs(self.sdmm),10)) if \\\\\\n abs(self.sdmm)>0 else 0))),\\\\\\n (ceil(log(abs(self.sdmm),10)) if abs(self.sdmm)>0 else 0),\\\\\\n b\\\"-\\\" if self.bstar<0 else b\\\" \\\",\\\\\\n abs(self.bstar*pow(10,5-(ceil(log(abs(self.bstar),10)) if \\\\\\n abs(self.bstar)>0 else 0))),\\\\\\n (ceil(log(abs(self.bstar),10)) if abs(self.bstar)>0 else 0),\\\\\\n self.nr,)\\n line3=b\\\"2 %05d %08.4f %08.4f %07d %08.4f %08.4f %011.8f%05d\\\" %\\\\\\n (self.id,self.inc,self.raan,self.ecc*1.e7,self.aop,\\\\\\n self.ma,self.mm,self.revol,)\\n l2cs=0\\n for c in line2:\\n bc=bytes([c])\\n if bc.isdigit():\\n l2cs+=int(bc.decode(\\\"ascii\\\"))\\n elif bc==b\\\"-\\\":\\n l2cs+=1\\n l2cs%=10\\n\\n l3cs=0\\n for c in line3:\\n bc=bytes([c])\\n if bc.isdigit():\\n l3cs+=int(bc.decode(\\\"ascii\\\"))\\n elif bc==b\\\"-\\\":\\n l3cs+=1\\n l3cs%=10\\n return line1+b\\\"\\\\r\\\\n\\\"+line2+str(l2cs).encode(\\\"ascii\\\")+b\\\"\\\\r\\\\n\\\"+line3+\\\\\\n str(l3cs).encode(\\\"ascii\\\")+b\\\"\\\\r\\\\n\\\"\",\n \"def load(self):\\n return\",\n \"def convert_uncompressed_RLE_COCO_type(\\n element: Dict, height: int, width: int\\n ) -> Dict:\\n p = maskUtils.frPyObjects(element, height, width)\\n return p\",\n \"def build(self):\",\n \"def build(self):\",\n \"def build(self):\",\n \"def _read_data(self):\",\n \"def exportCrises ( c ) :\\n assert str(type(c)) == \\\"<type '_mysql.connection'>\\\"\\n xml = \\\"\\\"\\n cr = sqlQuery ( c, \\\"select * from Crises;\\\" )\\n for i in cr :\\n cL = sqlQuery ( c, \\\"select * from CrisisLocations where crisisID = '\\\" + i [ 0 ] + \\\"';\\\" )\\n hI = sqlQuery ( c, \\\"select * from HumanImpact where crisisID = '\\\" + i [ 0 ] + \\\"';\\\" )\\n rN = sqlQuery ( c, \\\"select * from ResourceNeeded where crisisID = '\\\" + i [ 0 ] + \\\"';\\\" )\\n wTH = sqlQuery ( c, \\\"select * from WaysToHelp where crisisID = '\\\" + i [ 0 ] + \\\"';\\\" )\\n cER = sqlQuery ( c, \\\"select * from CrisisExternalResources where crisisID = '\\\" + i [ 0 ] + \\\"';\\\" )\\n cTP = sqlQuery ( c, \\\"select * from CrisesToPeople where crisisID = '\\\" + i [ 0 ] + \\\"';\\\" )\\n oTC = sqlQuery ( c, \\\"select * from OrganizationsToCrises where crisisID = '\\\" + i [ 0 ] + \\\"';\\\" )\\n xml += openTagAtt ( \\\"Crisis\\\", \\\"crisisIdent\\\", i [ 0 ] )\\n xml += openCloseTag ( \\\"Name\\\", i [ 1 ] )\\n xml += closeTagAtt ( \\\"Kind\\\", \\\"crisisKindIdent\\\", i [ 2 ] )\\n for j in cL :\\n xml += openTag ( \\\"Location\\\" )\\n xml += openCloseTag ( \\\"Locality\\\", j [ 1 ] )\\n xml += openCloseTag ( \\\"Region\\\", j [ 2 ] )\\n xml += openCloseTag ( \\\"Country\\\", j [ 3 ] )\\n xml += closeTag ( \\\"Location\\\" )\\n xml += openTag ( \\\"StartDateTime\\\" )\\n xml += openCloseTag ( \\\"Date\\\", i [ 3 ] )\\n xml += openCloseTag ( \\\"Time\\\", i [ 4 ] )\\n xml += closeTag ( \\\"StartDateTime\\\" )\\n xml += openTag ( \\\"EndDateTime\\\" )\\n xml += openCloseTag ( \\\"Date\\\", i [ 5 ] )\\n xml += openCloseTag ( \\\"Time\\\", i [ 6 ] )\\n xml += closeTag ( \\\"EndDateTime\\\" )\\n for j in hI :\\n xml += openTag ( \\\"HumanImpact\\\" )\\n xml += openCloseTag ( \\\"Type\\\", j [ 1 ] )\\n xml += openCloseTag ( \\\"Number\\\", j [ 2 ] )\\n xml += closeTag ( \\\"HumanImpact\\\" )\\n xml += openCloseTag ( \\\"EconomicImpact\\\", i [ 7 ] )\\n for j in rN :\\n xml += openCloseTag ( \\\"ResourceNeeded\\\", j [ 1 ] )\\n for j in wTH :\\n xml += openCloseTag ( \\\"WaysToHelp\\\", j [ 1 ] )\\n xml += openTag ( \\\"ExternalResources\\\" )\\n for j in cER :\\n xml += openCloseTag ( j [ 1 ] , j [ 2 ] )\\n xml += closeTag ( \\\"ExternalResources\\\" )\\n xml += openTag ( \\\"RelatedPersons\\\" )\\n for j in cTP :\\n xml += closeTagAtt ( \\\"RelatedPerson\\\" , \\\"personIdent\\\", j [ 1 ] )\\n xml += closeTag ( \\\"RelatedPersons\\\" )\\n xml += openTag ( \\\"RelatedOrganizations\\\" )\\n for j in oTC :\\n xml += closeTagAtt ( \\\"RelatedOrganization\\\" , \\\"organizationIdent\\\", j [ 0 ] )\\n xml += closeTag ( \\\"RelatedOrganizations\\\" )\\n xml += closeTag ( \\\"Crisis\\\" )\\n assert str ( type ( xml ) ) == \\\"<type 'str'>\\\"\\n return xml\",\n \"def afficherOBJ(self):\\r\\n str_abr = self.abr.afficher()## appel de l'affichage d'un ABR\\r\\n return str(self.debut)+':'+str(self.fin)+';'+str_abr ##concaténation du resultat\\r\",\n \"def boma(self):\\n\\n filename = filedialog.askopenfile(initialdir=self.root.cache_dir,\\n title='Select AVL Multilevel BOM',\\n filetypes=[('Comma-Separated Values', '.csv')])\\n self.a_entry.clear()\\n self.a_entry.insert(tk.END, filename.name)\\n self.root.cache_dir = filename\\n self.bom_a = filename.name\",\n \"def _load_obcfile(casename=None): \\n\\n data={}\\n\\n if casename==None:\\n print('_load_obcfile requires a filename to load.')\\n return\\n try:\\n fp=open(casename+'_obc.dat','r')\\n except IOError:\\n print('_load_obcfile: invalid case name.')\\n return data\\n\\n obc_str=fp.readline().split('=')\\n obc_num=int(obc_str[1])\\n t_data1=np.genfromtxt(casename+'_obc.dat',skip_header=1)\\n fp.close()\\n\\n data['obcf_num']=obc_num\\n data['obcf_numbers']=t_data1[:,0]\\n data['obcf_nodes']=t_data1[:,1]\\n data['obcf_value']=t_data1[:,2]\\n\\n \\n return data\",\n \"def __str__(self):\\r\\n return self.afficherOBJ()\",\n \"def callback_rocm_bitcode_path(rocdl_dir=None):\\n # seems link order matters.\\n\\n if rocdl_dir is None:\\n if exists(\\\"/opt/rocm/amdgcn/bitcode/\\\"):\\n rocdl_dir = \\\"/opt/rocm/amdgcn/bitcode/\\\" # starting with rocm 3.9\\n else:\\n rocdl_dir = \\\"/opt/rocm/lib/\\\" # until rocm 3.8\\n\\n bitcode_names = [\\n \\\"oclc_daz_opt_on\\\",\\n \\\"ocml\\\",\\n \\\"irif\\\", # this does not exist in rocm 3.9, drop eventually\\n \\\"oclc_correctly_rounded_sqrt_off\\\",\\n \\\"oclc_correctly_rounded_sqrt_on\\\",\\n \\\"oclc_daz_opt_off\\\",\\n \\\"oclc_finite_only_off\\\",\\n \\\"oclc_finite_only_on\\\",\\n # todo (t-vi): an alternative might be to scan for the\\n \\\"oclc_isa_version_803\\\",\\n \\\"oclc_isa_version_900\\\", # isa version files (if the linker throws out\\n \\\"oclc_isa_version_906\\\", # the unneeded ones or we filter for the arch we need)\\n \\\"oclc_isa_version_1030\\\",\\n \\\"oclc_unsafe_math_off\\\",\\n \\\"oclc_unsafe_math_on\\\",\\n \\\"oclc_wavefrontsize64_on\\\",\\n \\\"oclc_abi_version_500\\\",\\n ]\\n\\n bitcode_files = []\\n for n in bitcode_names:\\n p = join(rocdl_dir, n + \\\".bc\\\") # rocm >= 3.9\\n if not exists(p): # rocm <= 3.8\\n p = join(rocdl_dir, n + \\\".amdgcn.bc\\\")\\n if exists(p):\\n bitcode_files.append(p)\\n elif \\\"isa_version\\\" not in n and n not in {\\\"irif\\\"}:\\n raise RuntimeError(\\\"could not find bitcode \\\" + n)\\n\\n return tvm.runtime.convert(bitcode_files)\",\n \"def crear_arbol():\\n print (\\\"En este programa te brindamos 2 opciones para crear arboles, elige la que mas se adapte a tu objetivo\\\")\\n \\n try:\\n crear=int(input(\\\"1. Crear un arbol de manera aleatoria\\\\n2. Introducir los datos en forma de arreglo\\\\n\\\"))\\n except:\\n print(\\\"Valor Invalido\\\")\\n \\n if crear==1:\\n print(\\\"\\\\nExcelente! Tu arbol sera generado de forma aleatoria. Solo necesitamos aclarar que tipo de arbol quieres\\\")\\n while True:\\n try:\\n altura=int(input(\\\"\\\\nAñade la altura de tu arbol: \\\"))\\n except:\\n print(\\\"El valor introducido no es valido!\\\")\\n else:\\n break\\n \\n perfecto=input(\\\"\\\\n¿Deseas crear un arbol perfecto? (si/no): \\\")\\n if perfecto.lower()!=\\\"no\\\":\\n perfecto=True\\n else:\\n perfecto=False\\n \\n arbol=tree(height=altura, is_perfect=perfecto)\\n return arbol\\n \\n elif crear==2:\\n print(\\\"\\\\nExcelente! Tu arbol sera generado en base a un arreglo. Solo necesitamos recibir los valores\\\")\\n valores=[]\\n counter=0\\n print(\\\"\\\\nIntroduce los valores en orden. El valor inicial sera considerado la raiz. Los valores se ordenaran de izquiera a derecha.\\\" +\\n \\\"Deja el valor en blanco para saltar ese espacio. Escribe -1 para dejar de añadir valores\\\")\\n valor=\\\" \\\"\\n while valor!=\\\"-1\\\":\\n valor=input(f\\\"Introduzca el valor {counter}: \\\")\\n if valor==\\\"\\\":\\n valor=None\\n valores.append(valor)\\n counter+=1\\n else:\\n valores.append(int(valor))\\n counter+=1\\n valores.pop()\\n root=build(valores)\\n return root\",\n \"def serialize(self):\",\n \"def get_jarfile(self):\",\n \"def encode(category_main : ):\",\n \"def readmodel(model = 'dominguez'):\\n ebl_file_path = os.path.join(os.path.split(__file__)[0],'data/')\\n\\n if model == 'kneiske':\\n file_name = join(ebl_file_path , 'ebl_nuFnu_tanja.dat')\\n elif model == 'franceschini':\\n file_name = join(ebl_file_path , 'ebl_franceschini.dat')\\n elif model == 'dominguez':\\n file_name = join(ebl_file_path , 'ebl_dominguez11.out')\\n elif model == 'dominguez-upper':\\n file_name = join(ebl_file_path , 'ebl_upper_uncertainties_dominguez11.out')\\n elif model == 'dominguez-lower':\\n file_name = join(ebl_file_path , 'ebl_lower_uncertainties_dominguez11.out')\\n elif model == 'inoue':\\n file_name = join(ebl_file_path , 'EBL_z_0_baseline.dat')\\n #file_name = join(ebl_file_path , 'EBL_proper_baseline.dat')\\n elif model == 'inoue-low-pop3':\\n file_name = join(ebl_file_path , 'EBL_z_0_low_pop3.dat')\\n #file_name = join(ebl_file_path , 'EBL_proper_low_pop3.dat')\\n elif model == 'inoue-up-pop3':\\n file_name = join(ebl_file_path , 'EBL_z_0_up_pop3.dat')\\n #file_name = join(ebl_file_path , 'EBL_proper_up_pop3.dat')\\n elif model == 'gilmore':\\n file_name = join(ebl_file_path , 'eblflux_fiducial.dat')\\n elif model == 'gilmore-fixed':\\n file_name = join(ebl_file_path , 'eblflux_fixed.dat')\\n elif model == 'cuba':\\n file_name = join(ebl_file_path , 'CUBA_UVB.dat')\\n elif model == 'finke':\\n file_name = join(ebl_file_path , 'ebl_modelC_Finke.txt')\\n else:\\n raise ValueError(\\\"Unknown EBL model chosen!\\\")\\n\\n data = np.loadtxt(file_name)\\n if model.find('inoue') >= 0:\\n z = np.array([0.])\\n #z = data[0,1:]\\n #nuInu = data[:,1]\\n lmu = data[:,0]\\n nuInu = np.array([data[:,1]]).T\\n raise ValueError('Inoue models not correctly implemented at the moment, choose another model')\\n\\n elif model.find('gilmore') >= 0:\\n z = data[0,1:]\\n lmu = data[1:,0] * 1e-4 # convert from Angstrom to micro meter\\n nuInu = data[1:,1:] \\n nuInu[nuInu == 0.] = 1e-20 * np.ones(np.sum(nuInu == 0.))\\n \\n # convert from ergs/s/cm^2/Ang/sr to nW/m^2/sr\\n nuInu = (nuInu.T * data[1:,0]).T * 1e4 * 1e-7 * 1e9 \\n\\n elif model == 'cuba':\\n z = data[0,1:-1]\\n lmu = data[1:,0] * 1e-4\\n nuInu = data[1:,1:-1]\\n\\n # replace zeros by 1e-40\\n idx = np.where(data[1:,1:-1] == 0.)\\n nuInu[idx] = np.ones(np.sum(nuInu == 0.)) * 1e-20\\n\\n # in erg / cm^2 / s / sr\\n nuInu = (nuInu.T * c.c.value / (lmu * 1e-6)).T \\n nuInu *= 1e6 # in nW / m^2 / sr\\n\\n # check where lmu is not strictly increasing\\n idx = np.where(np.diff(lmu) == 0.)\\n for i in idx[0]:\\n lmu[i+1] = (lmu[i + 2] + lmu[i]) / 2.\\n\\n else:\\n z = data[0,1:]\\n lmu = data[1:,0]\\n nuInu = data[1:,1:]\\n if model == 'finke': \\n lmu = lmu[::-1] * 1e-4\\n nuInu = nuInu[::-1]\\n\\n return EBL(z,lmu,nuInu, model = model)\",\n \"def load(self):\\n return None\",\n \"def cma_bst(redownload: bool = False) -> Dataset:\\n return Dataset.get(\\\"cma_bst\\\", redownload=redownload)\",\n \"def load_stoic_from_sbml(file_name, split_bidirectional_fluxes=False):\\n from lxml import etree\\n for ext in ['', '.xml', '.xml.gz', '.gz']:\\n if os.path.isfile(file_name+ext):\\n file_name = file_name+ext\\n break\\n tree = etree.parse(file_name)\\n root = tree.getroot()\\n assert root.tag.endswith ('sbml'), `root.tag`\\n version = int(root.attrib['version'])\\n level = int(root.attrib['level'])\\n if level in [2,3]:\\n default_stoichiometry = '1'\\n else:\\n default_stoichiometry = None\\n compartments = {}\\n species = []\\n modifiers = []\\n species_all = []\\n reactions = []\\n species_reactions = defaultdict (lambda:[])\\n reactions_species = defaultdict (lambda:[])\\n reactions_info = defaultdict(lambda:dict(modifiers=[],reactants=[],products=[],\\n boundary_specie_stoichiometry={},annotation=[],\\n compartments = set()))\\n species_info = defaultdict(lambda:dict())\\n matrix = {}\\n for model in root:\\n for item in model:\\n if item.tag.endswith('listOfCompartments'):\\n for compartment in item:\\n compartments[compartment.attrib['id']] = compartment.attrib\\n elif item.tag.endswith('listOfSpecies'):\\n for specie in item:\\n species_all.append(specie.attrib['id'])\\n species_info[specie.attrib['id']]['compartment'] = specie.attrib['compartment']\\n species_info[specie.attrib['id']]['name'] = specie.attrib.get('name', specie.attrib['id'])\\n elif item.tag.endswith('listOfReactions'):\\n for reaction in item:\\n\\n reversible =eval(reaction.attrib.get('reversible', 'False').title())\\n reaction_id = reaction.attrib['id']\\n name = reaction.attrib.get('name', reaction_id)\\n assert reaction_id not in reactions,`reaction_id`\\n reactions.append(reaction_id)\\n reaction_index = len(reactions)-1\\n reactions_info[reaction_id]['name'] = name\\n\\n if split_bidirectional_fluxes and reversible:\\n reaction_id2 = '%s_r' % (reaction_id)\\n assert reaction_id2 not in reactions,`reaction_id2`\\n reactions.append(reaction_id2)\\n reaction_index2 = len(reactions)-1\\n reactions_info[reaction_id2]['name'] = name+'_r'\\n reactions_info[reaction_id]['reversible'] = False\\n reactions_info[reaction_id2]['reversible'] = False\\n else:\\n reaction_id2 = reaction_index2 = None\\n reactions_info[reaction_id]['reversible'] = reversible\\n\\n for part in reaction:\\n if part.tag.endswith ('listOfReactants'):\\n for reactant in part:\\n assert reactant.tag.endswith('speciesReference'), `reactant.tag`\\n specie_id = reactant.attrib['species']\\n stoichiometry = -obj2num(reactant.attrib.get('stoichiometry', default_stoichiometry))\\n reactions_info[reaction_id]['reactants'].append(specie_id)\\n try:\\n specie_index = species.index(specie_id)\\n except ValueError:\\n species.append(specie_id)\\n specie_index = len(species)-1\\n assert stoichiometry,`stoichiometry`\\n matrix[specie_index, reaction_index] = stoichiometry\\n species_reactions[specie_index].append(reaction_index)\\n reactions_species[reaction_index].append(specie_index) \\n reactions_info[reaction_id]['compartments'].add(species_info[specie_id]['compartment'])\\n if reaction_index2 is not None:\\n reactions_info[reaction_id2]['reactants'].append(specie_id)\\n matrix[specie_index, reaction_index2] = -stoichiometry\\n species_reactions[specie_index].append(reaction_index2)\\n reactions_species[reaction_index2].append(specie_index) \\n reactions_info[reaction_id2]['compartments'].add(species_info[specie_id]['compartment'])\\n elif part.tag.endswith ('listOfProducts'):\\n for product in part:\\n assert product.tag.endswith('speciesReference'), `product.tag`\\n specie_id = product.attrib['species']\\n stoichiometry = obj2num(product.attrib.get('stoichiometry', default_stoichiometry))\\n reactions_info[reaction_id]['products'].append(specie_id)\\n try:\\n specie_index = species.index(specie_id)\\n except ValueError:\\n species.append(specie_id)\\n specie_index = len(species)-1\\n assert stoichiometry,`stoichiometry`\\n matrix[specie_index, reaction_index] = stoichiometry\\n species_reactions[specie_index].append(reaction_index)\\n reactions_species[reaction_index].append(specie_index)\\n reactions_info[reaction_id]['compartments'].add(species_info[specie_id]['compartment'])\\n if reaction_index2 is not None:\\n reactions_info[reaction_id2]['products'].append(specie_id)\\n matrix[specie_index, reaction_index2] = -stoichiometry\\n species_reactions[specie_index].append(reaction_index2)\\n reactions_species[reaction_index2].append(specie_index)\\n reactions_info[reaction_id2]['compartments'].add(species_info[specie_id]['compartment'])\\n elif part.tag.endswith ('listOfModifiers'):\\n for modifier in part:\\n assert modifier.tag.endswith('modifierSpeciesReference'), `modifier.tag`\\n specie_id = product.attrib['species']\\n reactions_info[reaction_id]['modifiers'].append(specie_id)\\n reactions_info[reaction_id]['compartments'].add(species_info[specie_id]['compartment'])\\n continue\\n elif part.tag.endswith ('annotation'):\\n reactions_info[reaction_id]['annotation'].append(part.text)\\n continue\\n elif re.match(r'.*(kineticLaw|notes)\\\\Z', part.tag): \\n continue\\n else:\\n print 'get_stoichiometry:warning:unprocessed reaction element: %r' % (part.tag)\\n continue\\n\\n\\n elif re.match (r'.*(annotation|notes|listOfSpeciesTypes|listOfUnitDefinitions)\\\\Z', item.tag):\\n pass\\n else:\\n print 'get_stoichiometry:warning:unprocessed model element: %r' % (item.tag)\\n\\n return matrix, species, reactions, species_info, reactions_info\",\n \"def get_encoded_faces_arrested():\\n encoded = {}\\n # c=0\\n with open(\\\"arrested.pkl\\\",\\\"rb\\\") as f:\\n encoded=pickle.load(f)\\n return encoded\",\n \"def archivoXl(archivo):\\r\\n return ow(archivo)\",\n \"def load_model(self, **params):\\n \\t# file_name = params['name']\\n # return pickle.load(gzip.open(file_name, 'rb'))\",\n \"def to_xml_dict(self):\\n self._check_required_fields()\\n\\n root = odict[\\n \\\"r:import\\\": odict[\\n \\\"@xmlns:r\\\": \\\"http://resolver.nkp.cz/v3/\\\",\\n \\\"r:monograph\\\": odict[\\n \\\"r:titleInfo\\\": odict[\\n \\\"r:title\\\": self.title,\\n ],\\n ],\\n ]\\n ]\\n mono_root = root[\\\"r:import\\\"][\\\"r:monograph\\\"]\\n\\n # subtitle\\n MonographComposer._assign_pattern(\\n mono_root[\\\"r:titleInfo\\\"],\\n \\\"r:subTitle\\\",\\n self.subtitle\\n )\\n\\n # handle ccnb, isbn, uuid\\n self._add_identifier(mono_root, \\\"ccnb\\\")\\n self._add_identifier(mono_root, \\\"isbn\\\")\\n self._add_identifier(mono_root, \\\"other_id\\\", out=\\\"otherId\\\")\\n\\n # add form of the book\\n MonographComposer._assign_pattern(\\n mono_root,\\n \\\"r:documentType\\\",\\n self.document_type\\n )\\n\\n mono_root[\\\"r:digitalBorn\\\"] = \\\"true\\\" if self.digital_born else \\\"false\\\"\\n\\n if self.author:\\n mono_root[\\\"r:primaryOriginator\\\"] = odict[\\n \\\"@type\\\": \\\"AUTHOR\\\",\\n \\\"#text\\\": self.author\\n ]\\n\\n if any([self.place, self.publisher, self.year]):\\n publ = odict()\\n\\n MonographComposer._assign_pattern(\\n publ,\\n \\\"r:publisher\\\",\\n self.publisher\\n )\\n MonographComposer._assign_pattern(publ, \\\"r:place\\\", self.place)\\n MonographComposer._assign_pattern(publ, \\\"r:year\\\", self.year)\\n\\n mono_root[\\\"r:publication\\\"] = publ\\n\\n if self.format:\\n format_dict = MonographComposer._create_path(\\n root,\\n odict,\\n [\\n \\\"r:import\\\",\\n \\\"r:digitalDocument\\\",\\n \\\"r:technicalMetadata\\\",\\n \\\"r:format\\\",\\n ]\\n )\\n\\n format_dict[\\\"#text\\\"] = self.format\\n\\n return root\",\n \"def __init__(self):\\n\\n super(aero_csm_component,self).__init__()\",\n \"def gt_roidb(self):\\n # cache_path: data/cache/Actions/\\n # self.name: rcnn_<>_<>\\n print \\\"cache_path:\\\", self.cache_path\\n\\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n # Get image_index and gt_roidb\\n # self._anno_filepath: data/Actions/${datatype}/anno_file.txt\\n self._image_index, gt_roidb = self._load_action_annotation(self._anno_filepath)\\n\\n print \\\"cache_file:\\\", cache_file\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print\\n print 'wrote gt roidb to {}'.format(cache_file)\\n\\n return gt_roidb\\n\\n\\n # ##################################################\\n # \\n # ##################################################\",\n \"def init():\\n return _libsbml.FbcToCobraConverter_init()\",\n \"def load_model():\\n global columns\\n global data\\n \\n model = pickle.load(open('MedCostModel.pkl', 'rb'))\\n data = pd.read_csv('MedCosts.csv')\\n data = data.drop(columns=['charges'])\\n columns = data.columns\\n return(model)\",\n \"def load(self):\\n #print self.fileInfo.name\\n progress = self.progress\\n filePath = os.path.join(self.fileInfo.dir,self.fileInfo.name)\\n self.fileSize = os.path.getsize(filePath)\\n #--Localize\\n cells = self.cells\\n records = self.records\\n canSave = self.canSave\\n skipObjRecords = self.skipObjRecords\\n contTypes = set(['CREC','CNTC','NPCC'])\\n levTypes = set(('LEVC','LEVI'))\\n debrisIds = self.debrisIds\\n debrisTypes = set(debrisIds.keys())\\n #--Header\\n inPath = os.path.join(self.fileInfo.dir,self.fileInfo.name)\\n ins = Tes3Reader(self.fileInfo.name,file(inPath,'rb'))\\n (name,size,delFlag,recFlag) = ins.unpackRecHeader()\\n self.tes3 = Tes3(name,size,delFlag,recFlag,ins,True)\\n if not canSave: del self.tes3.others[:]\\n #--Progress info\\n progress = self.progress\\n progress(0.0,'Loading '+self.fileInfo.name)\\n #--Raw data read\\n while not ins.atEnd():\\n #--Get record info and handle it\\n (name,size,delFlag,recFlag) = ins.unpackRecHeader()\\n #print \\\"%s [%d]\\\" % (name,size)\\n #--CELL?\\n if name == 'CELL':\\n record = Cell(name,size,delFlag,recFlag,ins,0,skipObjRecords)\\n cells.append(record)\\n if canSave: records.append(record)\\n #--Contents\\n elif canSave and name in contTypes:\\n if name == 'CREC':\\n record = Crec(name,size,delFlag,recFlag,ins,True)\\n elif name == 'CNTC':\\n record = Cntc(name,size,delFlag,recFlag,ins,True)\\n else:\\n record = Npcc(name,size,delFlag,recFlag,ins,True)\\n self.conts.append(record)\\n self.conts_id[record.getId()] = record\\n records.append(record)\\n #--File Map\\n elif name == 'FMAP':\\n record = Fmap(name,size,delFlag,recFlag,ins)\\n self.fmap = record\\n records.append(record)\\n #--Landscapes\\n elif name == 'LAND':\\n record = Land(name,size,delFlag,recFlag,ins)\\n self.lands[record.getId()] = record\\n records.append(record)\\n #--Scripts\\n elif canSave and name == 'SCPT':\\n record = Scpt(name,size,delFlag,recFlag,ins,True)\\n records.append(record)\\n if record.getRef():\\n self.refs_scpt[record] = record.getRef()\\n #--Save debris info?\\n elif name in debrisTypes:\\n record = Record(name,size,delFlag,recFlag,ins)\\n id = record.getId()\\n if id:\\n debrisIds[name].append(id.lower())\\n if canSave:\\n records.append(record)\\n #--Skip Non-cell?\\n elif not canSave:\\n ins.seek(size,1,name)\\n #--Keep non-cell?\\n else:\\n records.append(Record(name,size,delFlag,recFlag,ins))\\n #--Done Reading\\n ins.close()\\n #--Analyze Cells\\n cntCells = 0\\n progress.setMax(len(self.cells))\\n for cell in self.cells:\\n cell.load(None,1)\\n self.cells_id[cell.getId()] = cell\\n if not canSave:\\n cell.data = None #--Free some memory\\n #--Progress\\n cntCells += 1\\n progress(cntCells)\\n #--Scripts\\n if self.refs_scpt:\\n self.updateScptRefs()\",\n \"def gexf_graph():\\n # you must replace these lines and supply your own graph\\n \\n \\n \\n my_gexf = Gexf(\\\"JiajiaXie\\\", \\\"My awesome graph\\\")\\n graph=my_gexf.addGraph(\\\"undirected\\\", \\\"static\\\", \\\"My awesome networks\\\")\\n \\n atr1=graph.addNodeAttribute('Type',type='string')\\n\\n\\n for set in data_specific:\\n if graph.nodeExists(set['set_num']) ==0:\\n tm1=graph.addNode(set['set_num'], set['name'], r='0', g='0', b='0')\\n tm1.addAttribute(atr1,\\\"set\\\")\\n\\n\\n\\n counter_test=1\\n for set, part in data_parts.items():\\n for key, part_list in part.items():\\n interme =part_list['color']\\n red=interme[0]+interme[1]\\n green=interme[2]+interme[3]\\n blue=interme[4]+interme[5]\\n\\n red_de=str(int(red,16))\\n green_de=str(int(green,16))\\n blue_de=str(int(blue,16))\\n if graph.nodeExists(part_list['id'])==0:\\n tm2=graph.addNode(part_list['id'], part_list['part_name'],r=red_de, g=green_de, b = blue_de)\\n tm2.addAttribute(atr1,\\\"part\\\")\\n\\n\\n counter_test+=1\\n graph.addEdge(\\\"_\\\"+str(counter_test), set, part_list['id'], part_list['quantity'])\\n\\n\\n\\n f=open('bricks_graph.gexf','wb')\\n my_gexf.write(f)\\n\\n\\n return my_gexf.graphs[0]\",\n \"def creation_srcmdl(dir_cat,SourceRA,SourceDec,SourceROI,distmin,name,outputfile,emin,emax):\\n\\tf_liste_sour=\\\"a.txt\\\"\\n\\n\\tlect_ca(dir_cat,SourceRA,SourceDec,SourceROI,distmin,name,f_liste_sour,name)\\n\\tXML_EC_PL(name, f_liste_sour, outputfile, emin,emax)\\n\\tos.system(\\\"rm -rf a.txt\\\")\",\n \"def parse_ben_sb(parent_directory, code):\\n s_b = np.loadtxt(parent_directory+code+'res_ave.out')\\n return s_b\",\n \"def __str__(self):\\n return self.idBaixasReceber\",\n \"def load(self):\\n\\n raise NotImplementedError\",\n \"def cargar_colores():\\n try:\\n col = open(os.path.join(absolute_path, \\\"lib\\\", \\\"info\\\",\\\"config\\\" ,\\\"colores.json\\\"),\\\"r\\\")\\n dic_col = json.load(col)\\n col.close()\\n except (FileNotFoundError):\\n sg.popup(\\\"No se encontro colores.json \\\\n usando colores predeterminados\\\",keep_on_top=True)\\n dic_col = {\\n \\\"facil\\\": {\\n \\\"\\\": \\\"#FFFFFF\\\",\\n \\\"+\\\": \\\"#ff6699\\\",\\n \\\"++\\\": \\\"#ff99cc\\\",\\n \\\"+++\\\": \\\"#efcfe8\\\",\\n \\\"++++\\\": \\\"#c1a4ff\\\",\\n \\\"-\\\": \\\"#9999ff\\\",\\n \\\"--\\\": \\\"#9966cc\\\",\\n \\\"---\\\": \\\"#6633cc\\\"\\n },\\n \\\"medio\\\": {\\n \\\"\\\": \\\"#82b1ff\\\",\\n \\\"+\\\": \\\"white\\\",\\n \\\"++\\\": \\\"#d50000\\\",\\n \\\"+++\\\": \\\"#efcfe8\\\",\\n \\\"++++\\\": \\\"#c1a4ff\\\",\\n \\\"-\\\": \\\"#c5cae9\\\",\\n \\\"--\\\": \\\"#ffeb3b\\\",\\n \\\"---\\\": \\\"#ff5722\\\"\\n },\\n \\\"dificil\\\": {\\n \\\"\\\": \\\"#e4f3fa\\\",\\n \\\"+\\\": \\\"#f89d89\\\",\\n \\\"++\\\": \\\"#e59e72\\\",\\n \\\"+++\\\": \\\"#9986a9\\\",\\n \\\"++++\\\": \\\"#ce5a57\\\",\\n \\\"-\\\": \\\"#efd692\\\",\\n \\\"--\\\": \\\"#5386a6\\\",\\n \\\"---\\\": \\\"#4fadac\\\"\\n },\\n \\\"atril\\\":\\\"#006699\\\",\\n \\\"letra_jugador\\\": \\\"#8da8b7\\\",\\n \\\"letra_pc\\\": \\\"#fed0b9\\\"\\n }\\n finally:\\n return (dic_col)\",\n \"def get_model(branch, internet):\\n\\n url = 'https://raw.githubusercontent.com/sot/chandra_models/master/chandra_models/xija/'\\n local_dir = '/AXAFLIB/chandra_models/chandra_models/xija/'\\n\\n if internet:\\n model_spec_url = url + branch # aca/aca_spec.json'\\n with urlopen(model_spec_url) as url:\\n response = url.read()\\n f = response.decode('utf-8')\\n else:\\n with open(home + local_dir + branch) as fid: # 'aca/aca_spec.json', 'rb') as fid:\\n f = fid.read()\\n return json.loads(f)\",\n \"def recuperation(nom):\\r\\n with open(nom, \\\"rb\\\") as fichier:\\r\\n monDepickler = pickle.Unpickler(fichier)\\r\\n contenu = monDepickler.load()\\r\\n\\r\\n return contenu\",\n \"def COD(fp):\\n lcod = unpack('>H', fp.read(2))[0]\\n scod = unpack('B', fp.read(1))[0]\\n sgcod = {\\n 'progression_order' : unpack('B', fp.read(1))[0],\\n 'nr_layers' : unpack('>H', fp.read(2))[0],\\n 'mc_transform' : unpack('B', fp.read(1))[0],\\n }\\n\\n # SPcod\\n _decomp_levels = unpack('B', fp.read(1))[0]\\n _block_width = unpack('B', fp.read(1))[0]\\n _block_height = unpack('B', fp.read(1))[0]\\n _block_style = unpack('B', fp.read(1))[0]\\n _transform = unpack('B', fp.read(1))[0]\\n\\n _precincts = []\\n has_precincts = _get_bit(scod, 7)\\n if has_precincts == 1:\\n for ii in range(_decomp_levels + 1):\\n _precincts.append(unpack('B', fp.read(1))[0])\\n\\n info = {\\n 'Lcod' : lcod,\\n 'Scod' : scod,\\n 'SGcod' : sgcod,\\n 'SPcod' : {\\n 'decomp_levels' : _decomp_levels,\\n 'block_width' : _block_width,\\n 'block_height' : _block_height,\\n 'block_style' : _block_style,\\n 'transform' : _transform\\n }\\n }\\n\\n if has_precincts:\\n info['SPcod']['precincts'] = _precincts\\n\\n return info\",\n \"def __repr__(self):\\n return \\\"compo of mix %d from file %s\\\"%(self.m_mix,self.m_filename)\",\n \"def bimport(filepath, resource_path=None, imgi_import=True, imge_import=True, seq_import=True, mov_import=True, txti_import=True, txte_import=True,\\r\\n script_import=True, img_embed=False, txt_embed=None, skip_sha1=False, img_merge=True):\\r\\n \\r\\n filepath = bpy.path.abspath(filepath) #Ensure path is absolute\\r\\n \\r\\n if resource_path is None or resource_path.strip() == \\\"\\\":\\r\\n resource_path = None\\r\\n else:\\r\\n resource_path = bpy.path.abspath(resource_path) #Ensure path is absolute\\r\\n \\r\\n if path.splitext(filepath)[1] == \\\".blib\\\":\\r\\n try:\\r\\n archive = zf.ZipFile(filepath, 'r')\\r\\n except zf.BadZipFile:\\r\\n raise InvalidBlibFile(\\\"File is not a valid Blender library\\\")\\r\\n \\r\\n blib = True\\r\\n try:\\r\\n file_checksum, blibtype, file_version, compatible, *rest = archive.comment.decode(\\\"utf-8\\\").split(\\\" \\\")\\r\\n except ValueError:\\r\\n raise InvalidBlibFile(\\\"File is broken, missing meta-data\\\")\\r\\n \\r\\n compatible = Version(compatible)\\r\\n \\r\\n if blibtype == \\\"cycles\\\":\\r\\n if compatible <= version:\\r\\n if archive.testzip() is not None:\\r\\n raise InvalidBlibFile(\\\"File is broken\\\")\\r\\n else:\\r\\n if not skip_sha1:\\r\\n checksum = archive_sha1(archive)\\r\\n \\r\\n if not file_checksum == checksum.hexdigest():\\r\\n raise InvalidBlibFile(\\\"Checksum does not match, file may be broken or have been altered\\\\n\\\"\\r\\n 'Run with \\\"skip_sha1\\\" to ignore checksum')\\r\\n else:\\r\\n raise BlibVersionError(\\\"File has incompatible version of blib\\\")\\r\\n else:\\r\\n raise BlibTypeError(\\\"File is not a valid Cycles material\\\")\\r\\n try:\\r\\n xml_file = archive.open(\\\"structure.xml\\\", 'r')\\r\\n except KeyError:\\r\\n raise InvalidBlibFile(\\\"File is broken, missing structure XML\\\")\\r\\n tree = ET.ElementTree(file=xml_file)\\r\\n xml_file.close()\\r\\n xroot = tree.getroot()\\r\\n \\r\\n elif path.splitext(filepath)[1] == \\\".xml\\\":\\r\\n tree = ET.ElementTree(file=filepath)\\r\\n xroot = tree.getroot()\\r\\n blib = False\\r\\n xversion = Version(xroot.attrib[\\\"compatible\\\"])\\r\\n if xversion > version:\\r\\n raise BlibVersionError(\\\"File has incompatible version of blib\\\")\\r\\n \\r\\n else:\\r\\n raise InvalidBlibFile(\\\"File is not a Blender library\\\")\\r\\n \\r\\n if xroot.tag != \\\"blib\\\":\\r\\n raise InvalidBlibFile(\\\"File is not a Blender library\\\")\\r\\n \\r\\n if xroot.attrib[\\\"type\\\"] != \\\"cycles\\\":\\r\\n raise BlibTypeError(\\\"File is not a valid Cycles material\\\")\\r\\n \\r\\n failed = {}\\r\\n imgs = {}\\r\\n txts = {}\\r\\n txt_paths = {}\\r\\n grps = {}\\r\\n scripts = {}\\r\\n resources = {\\r\\n \\\"images\\\": imgs,\\r\\n \\\"texts\\\": txts,\\r\\n \\\"text_paths\\\": txt_paths,\\r\\n \\\"groups\\\": grps,\\r\\n \\\"scripts\\\": scripts,\\r\\n }\\r\\n txt_dir = ResourceDir(\\\"texts\\\", resource_path)\\r\\n xres = xroot.find(\\\"resources\\\")\\r\\n \\r\\n #Import resources\\r\\n if xres is not None:\\r\\n ximgs = xres.find(\\\"images\\\")\\r\\n xtxts = xres.find(\\\"texts\\\")\\r\\n xgrps = xres.find(\\\"groups\\\")\\r\\n tmp_path = ResourceDir(\\\"tmp\\\", resource_path)\\r\\n path_dict = {}\\r\\n \\r\\n #Images\\r\\n if ximgs is not None and (imgi_import or imge_import or seq_import or mov_import) and blib:\\r\\n img_dir = ResourceDir(\\\"images\\\", resource_path)\\r\\n hash_dict = None\\r\\n sfv_update = False\\r\\n for ximg in ximgs:\\r\\n if ximg.attrib[\\\"source\\\"] in {'FILE', 'GENERATED'}:\\r\\n if ximg.attrib[\\\"origin\\\"] == \\\"internal\\\":\\r\\n if not imgi_import:\\r\\n pass\\r\\n else:\\r\\n if not imge_import:\\r\\n pass\\r\\n elif ximg.attrib[\\\"source\\\"] == 'SEQUENCE':\\r\\n if not seq_import:\\r\\n pass\\r\\n elif ximg.attrib[\\\"source\\\"] == 'MOVIE':\\r\\n if not mov_import:\\r\\n pass\\r\\n \\r\\n #Write image to temporary folder, and pack in Blender\\r\\n if ximg.attrib[\\\"source\\\"] in {'FILE', 'GENERATED'} and (img_embed or (img_embed is None and ximg.attrib[\\\"origin\\\"] == \\\"internal\\\")):\\r\\n ipath = extract_image(archive, ximg.attrib[\\\"path\\\"], str(tmp_path), path_dict, failed)\\r\\n if ipath is None:\\r\\n pass\\r\\n \\r\\n try:\\r\\n img = bpy.data.images.load(ipath)\\r\\n except:\\r\\n fail(failed, \\\"images\\\", \\\"import image '{}', unknown reason\\\".format(ximg.attrib[\\\"path\\\"]))\\r\\n else:\\r\\n img.source = ximg.attrib[\\\"source\\\"]\\r\\n try:\\r\\n img.pack()\\r\\n except:\\r\\n bpy.data.images.remove(img)\\r\\n fail(failed, \\\"images\\\", \\\"pack image '{}', unknown reason\\\".format(ximg.attrib[\\\"path\\\"]))\\r\\n else:\\r\\n img.filepath = \\\"\\\"\\r\\n imgs[ximg.attrib[\\\"name\\\"]] = img\\r\\n \\r\\n else: #Write image to resource folder, and load in Blender\\r\\n if img_merge and ximg.attrib[\\\"source\\\"] != 'SEQUENCE': #Use existing image in resources if available\\r\\n try:\\r\\n comment = archive.getinfo(ximg.attrib[\\\"path\\\"]).comment.decode(\\\"utf-8\\\")\\r\\n except KeyError:\\r\\n fail(failed, \\\"images\\\", \\\"import image '{}', file is missing\\\".format(ximg.attrib[\\\"path\\\"]))\\r\\n pass\\r\\n \\r\\n com_path = path_dict[comment] if comment != \\\"\\\" else \\\"\\\"\\r\\n com_name = path.basename(path.dirname(com_path))\\r\\n if comment != \\\"\\\" and com_name != \\\"tmp\\\":\\r\\n ipath = com_path\\r\\n path_dict[ximg.attrib[\\\"path\\\"]] = ipath\\r\\n else:\\r\\n #Create hash dictionary only in the first iteration\\r\\n if hash_dict is None:\\r\\n hash_path = path.join(img_dir.root, \\\"list.sfv\\\")\\r\\n hash_dict = {}\\r\\n if path.isfile(hash_path):\\r\\n sfv = re.compile(r\\\"(.*) (.*?)$\\\")\\r\\n hash_file = open(hash_path, 'r', encoding=\\\"utf-8\\\")\\r\\n for line in hash_file:\\r\\n key = sfv.sub(r\\\"\\\\2\\\", line).strip()\\r\\n val = sfv.sub(r\\\"\\\\1\\\", line).strip()\\r\\n if key in hash_dict and val in hash_dict[key]:\\r\\n sfv_update = True\\r\\n else:\\r\\n hash_dict.setdefault(key, []).append(val)\\r\\n hash_file.close()\\r\\n hash_bkp = hash_dict.copy()\\r\\n \\r\\n #Check if files match and set path to appropriate image\\r\\n img_path = ximg.attrib[\\\"path\\\"] if comment == \\\"\\\" else comment\\r\\n try:\\r\\n crc = format(archive.getinfo(img_path).CRC, 'x')\\r\\n except KeyError:\\r\\n fail(failed, \\\"images\\\", \\\"import image '{}', file is missing\\\".format(ximg.attrib[\\\"path\\\"]))\\r\\n pass\\r\\n \\r\\n if crc in hash_dict:\\r\\n i = 0\\r\\n while i < len(hash_dict[crc]):\\r\\n val = hash_dict[crc][i]\\r\\n fpath = path.join(img_dir.root, val)\\r\\n if path.isfile(fpath):\\r\\n fsize = path.getsize(fpath)\\r\\n zsize = archive.getinfo(img_path).file_size\\r\\n if fsize == zsize:\\r\\n ffile = open(fpath, 'rb')\\r\\n zfile = archive.open(img_path, 'r')\\r\\n if files_equal(ffile, zfile):\\r\\n ipath = fpath\\r\\n path_dict[ximg.attrib[\\\"path\\\"]] = ipath\\r\\n ffile.close()\\r\\n zfile.close()\\r\\n break\\r\\n ffile.close()\\r\\n zfile.close()\\r\\n else:\\r\\n hash_dict[crc].remove(val)\\r\\n i -= 1\\r\\n i += 1\\r\\n else:\\r\\n ipath = extract_image(archive, ximg.attrib[\\\"path\\\"], str(img_dir), path_dict, failed)\\r\\n if ipath is None:\\r\\n pass\\r\\n \\r\\n hash_dict[crc].append(path.relpath(ipath, img_dir.root))\\r\\n else:\\r\\n ipath = extract_image(archive, ximg.attrib[\\\"path\\\"], str(img_dir), path_dict, failed)\\r\\n if ipath is None:\\r\\n pass\\r\\n \\r\\n hash_dict[crc] = [path.relpath(ipath, img_dir.root)]\\r\\n else: #Use image in archive, even if duplicate\\r\\n if ximg.attrib[\\\"source\\\"] == 'SEQUENCE':\\r\\n seq_dir = path.dirname(ximg.attrib[\\\"path\\\"])\\r\\n dir_name = ximg.attrib[\\\"path\\\"].split(\\\"/\\\")[-2]\\r\\n seq_path = path.join(str(img_dir), dir_name)\\r\\n makedirs(seq_path)\\r\\n seq_imgs = [img for img in archive.namelist() if img.startswith(seq_dir)]\\r\\n for img in seq_imgs:\\r\\n i_tmp_path = extract_image(archive, img, seq_path, path_dict, failed)\\r\\n if img == ximg.attrib[\\\"path\\\"]:\\r\\n ipath = i_tmp_path\\r\\n if ipath is None:\\r\\n break\\r\\n if ipath is None:\\r\\n rmtree(seq_path)\\r\\n pass\\r\\n else:\\r\\n ipath = extract_image(archive, ximg.attrib[\\\"path\\\"], str(img_dir), path_dict, failed)\\r\\n if ipath is None:\\r\\n pass\\r\\n \\r\\n #load image to Blender\\r\\n try:\\r\\n img = bpy.data.images.load(ipath)\\r\\n except:\\r\\n fail(failed, \\\"images\\\", \\\"import image '{}', unknown reason\\\".format(ximg.attrib[\\\"path\\\"]))\\r\\n else:\\r\\n img.source = ximg.attrib[\\\"source\\\"]\\r\\n imgs[ximg.attrib[\\\"name\\\"]] = img\\r\\n \\r\\n if tmp_path:\\r\\n for item in listdir(str(tmp_path)):\\r\\n fpath = path.join(str(tmp_path), item)\\r\\n if path.isfile(fpath):\\r\\n remove(fpath)\\r\\n \\r\\n #Update hash file if list has changed\\r\\n if hash_dict is not None and (hash_dict != hash_bkp or sfv_update):\\r\\n hash_path = path.join(img_dir.root, \\\"list.sfv\\\")\\r\\n hash_file = open(hash_path, 'w', encoding=\\\"utf-8\\\")\\r\\n for key in hash_dict:\\r\\n for val in hash_dict[key]:\\r\\n hash_file.write(val + \\\" \\\" + key + \\\"\\\\n\\\")\\r\\n hash_file.close()\\r\\n \\r\\n #Texts\\r\\n if xtxts is not None and (txti_import or txte_import):\\r\\n for xtxt in xtxts:\\r\\n if xtxt.attrib[\\\"origin\\\"] == \\\"internal\\\":\\r\\n if txti_import:\\r\\n if \\\"path\\\" in xtxt.attrib:\\r\\n if blib:\\r\\n if txt_embed == False:\\r\\n import_texts(\\\"zip\\\", \\\"ext\\\", xtxt, txts, failed, archive, txt_dir)\\r\\n else:\\r\\n import_texts(\\\"zip\\\", \\\"int\\\", xtxt, txts, failed, archive, txt_dir)\\r\\n else:\\r\\n if txt_embed == False:\\r\\n import_texts(\\\"xml\\\", \\\"ext\\\", xtxt, txts, failed, None, txt_dir)\\r\\n else:\\r\\n import_texts(\\\"xml\\\", \\\"int\\\", xtxt, txts, failed, None, txt_dir)\\r\\n \\r\\n else:\\r\\n if txte_import:\\r\\n if \\\"path\\\" in xtxt.attrib:\\r\\n if blib:\\r\\n if txt_embed == True:\\r\\n import_texts(\\\"zip\\\", \\\"int\\\", xtxt, txts, failed, archive, txt_dir, txt_paths)\\r\\n else:\\r\\n import_texts(\\\"zip\\\", \\\"ext\\\", xtxt, txts, failed, archive, txt_dir, txt_paths)\\r\\n else:\\r\\n if txt_embed == True:\\r\\n import_texts(\\\"xml\\\", \\\"int\\\", xtxt, txts, failed, None, txt_dir, txt_paths)\\r\\n else:\\r\\n import_texts(\\\"xml\\\", \\\"ext\\\", xtxt, txts, failed, None, txt_dir, txt_paths)\\r\\n \\r\\n #Groups\\r\\n if xgrps is not None:\\r\\n for xgrp in xgrps:\\r\\n xnodes = xgrp.find(\\\"nodes\\\")\\r\\n xlinks = xgrp.find(\\\"links\\\")\\r\\n grp = bpy.data.node_groups.new(xgrp.attrib[\\\"name\\\"], xgrp.attrib[\\\"bl_idname\\\"])\\r\\n grps[xgrp.attrib[\\\"name\\\"]] = grp\\r\\n if xnodes is not None:\\r\\n build_tree(xnodes, xlinks, grp, resources, txt_embed, txt_dir, blib, script_import, archive, failed)\\r\\n \\r\\n #Import material\\r\\n xmat = xroot.find(\\\"main\\\")\\r\\n \\r\\n if xmat is not None:\\r\\n xcycles = xmat.find(\\\"cycles_settings\\\")\\r\\n xnodes = xmat.find(\\\"nodes\\\")\\r\\n xlinks = xmat.find(\\\"links\\\")\\r\\n \\r\\n mat = bpy.data.materials.new(xmat.attrib[\\\"name\\\"])\\r\\n set_attributes(mat, xmat, failed)\\r\\n set_attributes(mat.cycles, xcycles, failed)\\r\\n mat.use_nodes = True\\r\\n mat.node_tree.nodes.clear()\\r\\n build_tree(xnodes, xlinks, mat.node_tree, resources, txt_embed, txt_dir, blib, script_import, archive, failed)\\r\\n if blib:\\r\\n archive.close()\\r\\n for f in failed:\\r\\n print(\\\"{} {} failed to be imported/assigned.\\\".format(failed[f], f))\\r\\n return mat\\r\\n else:\\r\\n if blib:\\r\\n archive.close()\\r\\n for f in failed:\\r\\n print(\\\"{} {} failed to be imported/assigned.\\\".format(failed[f], f))\\r\\n return grp\",\n \"def find_mcc_tree():\\n command = \\\"phyltr cat -b 10 --no-annotation indoeuropean.nex | \\\" \\\\\\n \\\"phyltr support --sort | \\\" \\\\\\n \\\"head -n 1 > mcct.nex\\\"\\n subprocess.call(command, shell=True)\",\n \"def write_gro(strucC,data_file):\\n #\\n latvec = strucC.getLatVec()\\n\\n gro_lines = \\\" com2gro \\\\n\\\"\\n gro_lines += \\\" %-2i \\\\n\\\" %( int(len(strucC.ptclC)) )\\n atom_indx = 0 \\n for pid, pt_i in strucC.ptclC:\\n atom_indx += 1\\n if( atom_indx > 10000): atom_indx = 1\\n r_i = pt_i.position\\n r_i_nm = [units.convert_angstroms_nm(r_i[0]) ,units.convert_angstroms_nm(r_i[1]) ,units.convert_angstroms_nm(r_i[2]) ]\\n gro_lines += \\\"%5d%-5s%5s%5d%8.3f%8.3f%8.3f\\\\n\\\" % (atom_indx,pt_i.tagsDict[\\\"resname\\\"][:5],pt_i.tagsDict[\\\"label\\\"][:5],atom_indx,r_i_nm[0],r_i_nm[1],r_i_nm[2] )\\n if( atom_indx > 99999 ):\\n atom_indx = 1\\n \\n gro_lines += \\\" %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f \\\\n\\\" % (units.convert_angstroms_nm(latvec[0][0]),units.convert_angstroms_nm(latvec[1][1]),units.convert_angstroms_nm(latvec[2][2]),units.convert_angstroms_nm(latvec[0][1]),units.convert_angstroms_nm(latvec[0][2]),units.convert_angstroms_nm(latvec[1][0]),units.convert_angstroms_nm(latvec[1][2]),units.convert_angstroms_nm(latvec[2][0]),units.convert_angstroms_nm(latvec[2][1])) \\n\\n F = open( data_file, 'w' )\\n F.write(gro_lines)\\n F.close()\",\n \"def write_gro(strucC,data_file):\\n #\\n latvec = strucC.getLatVec()\\n\\n gro_lines = \\\" com2gro \\\\n\\\"\\n gro_lines += \\\" %-2i \\\\n\\\" %( int(len(strucC.ptclC)) )\\n atom_indx = 0 \\n for pid, pt_i in strucC.ptclC:\\n atom_indx += 1\\n if( atom_indx > 10000): atom_indx = 1\\n r_i = pt_i.position\\n r_i_nm = [units.convert_angstroms_nm(r_i[0]) ,units.convert_angstroms_nm(r_i[1]) ,units.convert_angstroms_nm(r_i[2]) ]\\n gro_lines += \\\"%5d%-5s%5s%5d%8.3f%8.3f%8.3f\\\\n\\\" % (atom_indx,pt_i.tagsDict[\\\"resname\\\"][:5],pt_i.tagsDict[\\\"label\\\"][:5],atom_indx,r_i_nm[0],r_i_nm[1],r_i_nm[2] )\\n if( atom_indx > 99999 ):\\n atom_indx = 1\\n \\n gro_lines += \\\" %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f \\\\n\\\" % (units.convert_angstroms_nm(latvec[0][0]),units.convert_angstroms_nm(latvec[1][1]),units.convert_angstroms_nm(latvec[2][2]),units.convert_angstroms_nm(latvec[0][1]),units.convert_angstroms_nm(latvec[0][2]),units.convert_angstroms_nm(latvec[1][0]),units.convert_angstroms_nm(latvec[1][2]),units.convert_angstroms_nm(latvec[2][0]),units.convert_angstroms_nm(latvec[2][1])) \\n\\n F = open( data_file, 'w' )\\n F.write(gro_lines)\\n F.close()\",\n \"def __init__(self, raw_facil, raw_gir, raw_geo, proj):\\n address1 = raw_facil.get('address1')\\n address2 = raw_facil.get('address2')\\n\\n lon_lat = None\\n if raw_geo:\\n lon_lat = proj(\\n raw_geo['longitude'],\\n raw_geo['latitude'],\\n inverse=True\\n )\\n\\n self._init_attributes()\\n self.source = 'facil-location'\\n self.bldg_id = raw_facil['id']\\n self.type = 'building'\\n self.tags = []\\n self.banner_abbreviation = raw_facil.get('abbreviation')\\n self.name = raw_facil.get('name')\\n self.campus = self._get_pretty_campus(raw_facil.get('campus'))\\n self.address = self._get_address(address1, address2)\\n self.city = raw_facil.get('city')\\n self.state = raw_facil.get('state')\\n self.zip = raw_facil.get('zip')\\n self.geo_location = self._create_geo_location(\\n lon_lat[0] if lon_lat else None,\\n lon_lat[1] if lon_lat else None\\n )\\n self.geometry = self._create_geometry(\\n raw_geo['coordinatesType'] if raw_geo else None,\\n raw_geo['coordinates'] if raw_geo else None\\n )\\n self.gir_count = raw_gir['count'] if raw_gir else 0\\n self.gir_limit = bool(raw_gir['limit'].strip()) if raw_gir and raw_gir['limit'] else None\\n self.gir_locations = raw_gir['all'].strip() if raw_gir else None\\n self.arcgis_abbreviation = (\\n (raw_geo.get('abbreviation') if raw_geo else None)\\n or (raw_gir.get('abbreviation') if raw_gir else None)\\n )\\n self.relationships = {'services': {'data': []}}\\n self.merge = False\\n self.open_hours = None\\n self.description = None\\n self.descriptionHtml = None\\n self.images = None\\n self.thumbnails = []\\n self.website = None\\n self.synonyms = None\",\n \"def cargar_bolsa(self,lista):\\n self.bolsa = lista\",\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 read_biocontext(name: str) -> PREFIX_MAP:\\n path_to_jsonld = HERE / \\\"registry\\\" / f\\\"{name}.jsonld\\\"\\n with open(path_to_jsonld) as file:\\n return extract_prefixmap(json.load(file))\\n # return read_remote_jsonld_context(\\\"https://raw.githubusercontent.com/prefixcommons/biocontext/master/registry/\\\"+name+\\\".jsonld\\\")\",\n \"def getBaseMonetaria(self):\\n #Obtener la url de descarga del cvs\\n urlPackage=\\\"https://datos.gob.ar/api/3/action/package_show?id=sspm-factores-explicacion-base-monetaria\\\"\\n s=requests.get(urlPackage).content\\n objJson = json.loads(s)\\n resultado = objJson['result']['resources']\\n selector = 0\\n ultimoResultado = resultado[selector]\\n urlDescarga = ultimoResultado['url']\\n descripcion = ultimoResultado['description']\\n print(\\\"Descargando: {}\\\".format(descripcion))\\n print(\\\"Archivo: {}\\\".format(urlDescarga))\\n \\n #Descargar la url con cvs y generar pandas dataframe\\n contenidoCVS = requests.get(urlDescarga).content\\n flujoCVS = io.StringIO(contenidoCVS.decode('utf-8'))\\n df_temp = pd.read_csv(flujoCVS)\\n \\n #transform string to datetime\\n df_temp['indice_tiempo'] = pd.to_datetime(df_temp['indice_tiempo'], format='%Y-%m-%d', errors='ignore')\\n df_temp['indice_tiempo'] = df_temp['indice_tiempo'].dt.date\\n #set index\\n df_temp.set_index('indice_tiempo', inplace=True)\\n \\n return df_temp\",\n \"def zip_imagenet100c():\\n #First make sure the directory we are given is correct!\\n if not os.path.isdir(DATA_SRC_ROOT):\\n raise Exception(\\\"Bad filepath given\\\")\\n\\n #create the destiantion directories if they don't exist\\n if not os.path.isdir(IMAGENET100_DIR):\\n os.mkdir(IMAGENET100_DIR)\\n\\n #grab the subset wnids for the 100 class-subset\\n with open(IMAGENET100_CLASSES) as f:\\n subset_wnids = f.readlines()\\n subset_wnids = [x.strip() for x in subset_wnids] #list of the 100 WNIDs we grab\\n\\n #Grab the names of all of the folders inside the root data source\\n #Structure is distortion/sub_distortion/level/wnids\\n for distortion in os.listdir(DATA_SRC_ROOT):\\n if distortion != \\\"meta.bin\\\":\\n print(distortion)\\n\\n folder_path = os.path.join(DATA_SRC_ROOT, distortion)\\n\\n if not os.path.isdir(folder_path):\\n continue\\n\\n for sub_distortion in os.listdir(folder_path):\\n print(sub_distortion)\\n\\n subfolder_path = os.path.join(folder_path, sub_distortion)\\n\\n if not os.path.isdir(subfolder_path):\\n continue\\n\\n for level in os.listdir(subfolder_path):\\n print(level)\\n\\n level_path = os.path.join(subfolder_path, level)\\n\\n #grab the correcrt validation d9recotires\\n for wnid in os.listdir(level_path):\\n wnid_path = os.path.join(level_path, wnid)\\n\\n if not os.path.isdir(wnid_path):\\n continue\\n\\n if wnid in subset_wnids:\\n dest_path = os.path.join(IMAGENET100_DIR, distortion, sub_distortion, level, wnid)\\n\\n shutil.copytree(wnid_path, dest_path)\\n\\n #copy the metadata bin file\\n meta_file = os.path.join(DATA_SRC_ROOT, 'meta.bin')\\n meta_dest = os.path.join(IMAGENET100_DIR, 'meta.bin')\\n\\n shutil.copy(meta_file, meta_dest)\\n\\n #Zip the destinatio file\\n shutil.make_archive(ZIP_PATH + '/ImageNet100C', 'tar', IMAGENET100_DIR)\",\n \"def _blob(self):\\n self.__rewrite_sldIdLst()\\n # # at least the following needs to be added before using\\n # # _reltype_ordering again for Presentation\\n # self.__rewrite_notesMasterIdLst()\\n # self.__rewrite_handoutMasterIdLst()\\n # self.__rewrite_sldMasterIdLst()\\n return super(Presentation, self)._blob\",\n \"def mapping_stratum(download_files =True):\\r\\n # get code description _index \\r\\n ix_= AGSO_PROPERTIES['props_codes'].index('name')\\r\\n def mfunc_(d): \\r\\n \\\"\\\"\\\" Set individual layer in dict of properties \\\"\\\"\\\"\\r\\n _p= {c: k.lower() if c not in ('code', 'label', 'name') else k \\r\\n for c, k in zip(AGSO_PROPERTIES['props_codes'], d) }\\r\\n id_= d[ix_].replace('/', '_').replace(\\r\\n ' ', '_').replace('\\\"', '').replace(\\\"'\\\", '').lower()\\r\\n return id_, _p \\r\\n rock_and_structural_props =list()\\r\\n for agso_data in tuple(set_agso_properties(download_files)): \\r\\n # remove the header of the property file\\r\\n rock_and_structural_props.append(\\r\\n dict(map( lambda x: mfunc_(x), agso_data[1:])))\\r\\n \\r\\n return tuple(rock_and_structural_props)\",\n \"def _serialise(self):\\n # TODO (M Foley)\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.55839115","0.55125","0.53216106","0.5215636","0.5121315","0.5116958","0.51138484","0.5088174","0.49747437","0.4962377","0.49491808","0.49370742","0.4935785","0.4934977","0.49025398","0.4889983","0.48558292","0.4849866","0.48489085","0.48460174","0.48455277","0.48432562","0.48404643","0.48305163","0.4825298","0.48055714","0.48055714","0.48055714","0.48055714","0.480072","0.47821066","0.47734442","0.47662497","0.47658414","0.47610596","0.4760768","0.4759377","0.4757339","0.4757339","0.47376674","0.47263193","0.4704761","0.4681357","0.46707702","0.46699145","0.46667227","0.46662223","0.46580783","0.4655924","0.46558383","0.46482208","0.46482208","0.46482208","0.4646141","0.46358317","0.46254238","0.46242774","0.46242294","0.46232957","0.46163377","0.4604624","0.46044922","0.46010175","0.45990375","0.45837322","0.45773283","0.45758364","0.45694777","0.45690352","0.45659944","0.45641813","0.45610553","0.45589265","0.4558362","0.4557259","0.45526877","0.45520204","0.45474327","0.45471853","0.4541755","0.45415843","0.45404312","0.45362893","0.4535568","0.45313478","0.4526519","0.45263398","0.45239946","0.4523082","0.45200393","0.45200393","0.45184743","0.4516838","0.45167792","0.45162565","0.4513842","0.45129558","0.45103392","0.4508837","0.45060512"],"string":"[\n \"0.55839115\",\n \"0.55125\",\n \"0.53216106\",\n \"0.5215636\",\n \"0.5121315\",\n \"0.5116958\",\n \"0.51138484\",\n \"0.5088174\",\n \"0.49747437\",\n \"0.4962377\",\n \"0.49491808\",\n \"0.49370742\",\n \"0.4935785\",\n \"0.4934977\",\n \"0.49025398\",\n \"0.4889983\",\n \"0.48558292\",\n \"0.4849866\",\n \"0.48489085\",\n \"0.48460174\",\n \"0.48455277\",\n \"0.48432562\",\n \"0.48404643\",\n \"0.48305163\",\n \"0.4825298\",\n \"0.48055714\",\n \"0.48055714\",\n \"0.48055714\",\n \"0.48055714\",\n \"0.480072\",\n \"0.47821066\",\n \"0.47734442\",\n \"0.47662497\",\n \"0.47658414\",\n \"0.47610596\",\n \"0.4760768\",\n \"0.4759377\",\n \"0.4757339\",\n \"0.4757339\",\n \"0.47376674\",\n \"0.47263193\",\n \"0.4704761\",\n \"0.4681357\",\n \"0.46707702\",\n \"0.46699145\",\n \"0.46667227\",\n \"0.46662223\",\n \"0.46580783\",\n \"0.4655924\",\n \"0.46558383\",\n \"0.46482208\",\n \"0.46482208\",\n \"0.46482208\",\n \"0.4646141\",\n \"0.46358317\",\n \"0.46254238\",\n \"0.46242774\",\n \"0.46242294\",\n \"0.46232957\",\n \"0.46163377\",\n \"0.4604624\",\n \"0.46044922\",\n \"0.46010175\",\n \"0.45990375\",\n \"0.45837322\",\n \"0.45773283\",\n \"0.45758364\",\n \"0.45694777\",\n \"0.45690352\",\n \"0.45659944\",\n \"0.45641813\",\n \"0.45610553\",\n \"0.45589265\",\n \"0.4558362\",\n \"0.4557259\",\n \"0.45526877\",\n \"0.45520204\",\n \"0.45474327\",\n \"0.45471853\",\n \"0.4541755\",\n \"0.45415843\",\n \"0.45404312\",\n \"0.45362893\",\n \"0.4535568\",\n \"0.45313478\",\n \"0.4526519\",\n \"0.45263398\",\n \"0.45239946\",\n \"0.4523082\",\n \"0.45200393\",\n \"0.45200393\",\n \"0.45184743\",\n \"0.4516838\",\n \"0.45167792\",\n \"0.45162565\",\n \"0.4513842\",\n \"0.45129558\",\n \"0.45103392\",\n \"0.4508837\",\n \"0.45060512\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.55939573"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":18689,"cells":{"query":{"kind":"string","value":"Gera o codigo rml do rodape"},"document":{"kind":"string","value":"def rodape(lst_rodape):\n\n tmp=''\n tmp=''\n tmp+='\\t\\t\\t\\t<lines>3.3cm 2.2cm 19.5cm 2.2cm</lines>\\n'\n tmp+='\\t\\t\\t\\t<setFont name=\"Helvetica\" size=\"8\"/>\\n'\n tmp+='\\t\\t\\t\\t<drawString x=\"3.3cm\" y=\"2.4cm\">' + lst_rodape[2] + '</drawString>\\n'\n tmp+='\\t\\t\\t\\t<drawString x=\"18.4cm\" y=\"2.4cm\">Página <pageNumber/></drawString>\\n'\n tmp+='\\t\\t\\t\\t<drawCentredString x=\"11.5cm\" y=\"1.7cm\">' + lst_rodape[0] + '</drawCentredString>\\n'\n tmp+='\\t\\t\\t\\t<drawCentredString x=\"11.5cm\" y=\"1.3cm\">' + lst_rodape[1] + '</drawCentredString>\\n'\n\n return tmp"},"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 rop():\n return","def lro(self) -> global___Snippet.Lro:","def get_rouge(ref_path, pred_path):\n print(\"###########cal rouge###############\")\n source_lines = [line.strip() for line in codecs.open(ref_path, \"r\", \"utf-8\").readlines()]\n pred_lines = [ pred.strip() for pred in codecs.open(pred_path, \"r\", \"utf-8\").readlines() ]\n assert len(source_lines) == len(pred_lines)\n rou = rouge.Rouge()\n scores = rou.get_scores(pred_lines, source_lines)\n ave_scores = rou.get_scores(pred_lines, source_lines, avg=True)\n result = OrderedDict()\n result[\"ave_scores\"] = ave_scores\n result[\"detail_scores\"] = scores\n print(ave_scores)\n print(\"############end rouge#############\\n\")\n return result","def _regr_basic():","def to_ir(self):","def gt_roidb(self):\n # cache_path: data/cache/Actions/\n # self.name: rcnn_<>_<>\n print \"cache_path:\", self.cache_path\n\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n # Get image_index and gt_roidb\n # self._anno_filepath: data/Actions/${datatype}/anno_file.txt\n self._image_index, gt_roidb = self._load_action_annotation(self._anno_filepath)\n\n print \"cache_file:\", cache_file\n with open(cache_file, 'wb') as fid:\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print\n print 'wrote gt roidb to {}'.format(cache_file)\n\n return gt_roidb\n\n\n # ##################################################\n # \n # ##################################################","def gt_roidb(self):\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\n if os.path.exists(cache_file):# and False:\n with open(cache_file, 'rb') as fid:\n try:\n roidb = pickle.load(fid)\n except:\n roidb = pickle.load(fid, encoding='bytes')\n print('{} gt roidb loaded from {}'.format(self.name, cache_file))\n return roidb\n\n gt_roidb = [self._load_pascal_annotation(index)\n for index in self.image_index]\n #with open(cache_file, 'wb') as fid:\n # pickle.dump(gt_roidb, fid, pickle.HIGHEST_PROTOCOL)\n #print('wrote gt roidb to {}'.format(cache_file))\n\n return gt_roidb","def gt_roidb(self):\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n num_image = len(self.image_index)\n if cfg.MNC_MODE:\n gt_roidb = [self._load_sbd_annotations(index) for index in xrange(num_image)]\n else:\n gt_roidb = [self._load_pascal_annotations(index) for index in xrange(num_image)]\n with open(cache_file, 'wb') as fid:\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print 'wrote gt roidb to {}'.format(cache_file)\n return gt_roidb","def get_roidb(self):\n # get all the images_ids in this dataset\n img_ids = self._COCO.getImgIds()\n # sort the ids, make each time the same order\n img_ids.sort()\n # load the 'image' of the COCO dataset\n roidb = copy.deepcopy(self._COCO.loadImgs(img_ids))\n for entry in roidb:\n # predefine some attribute of each image\n self._prep_roidb_entry(entry)\n\n # for cahce_dir\n if not os.path.exists(self.cache_dir):\n os.mkdir(self.cache_dir)\n cache_file = os.path.join(self.cache_dir, self.annFile + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n self._read_roidb_from_cachefile(roidb, cache_file)\n print('{} gt roidb loaded from {}'.format(self.annFile, cache_file))\n else:\n for entry in roidb:\n self._add_roidb_from_annotations(entry)\n with open(cache_file, 'wb') as f:\n pickle.dump(roidb, f, pickle.HIGHEST_PROTOCOL)\n print('wrote gt roidb to {}'.format(cache_file))\n return roidb","def gt_roidb(self):\n cache_file = os.path.join(self.cfg.cache_path, self.cfg.name + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print('{} gt roidb loaded from {}'.format(self.cfg.name, cache_file))\n return roidb\n\n # self.image_index = self._load_image_set_index()\n gt_roidb = [self._load_pascal_annotation(index)\n for index in self.image_index]\n with open(cache_file, 'wb') as fid:\n cPickle.dump(gt_roidb, fid, protocol=-1)\n print('wrote gt roidb to {}'.format(cache_file))\n\n return gt_roidb","def residue_ramachandran_type(residue) :\n if residue_amino(residue)==\"GLY\" :\n return rama_GLYCINE\n elif residue_amino(residue)==\"PRO\" :\n return rama_PROLINE\n elif residue_amino(next_residue(residue))==\"PRO\" :\n #exlcudes those that are Pro or Gly\n return rama_PRE_PRO\n else :\n return rama_GENERAL","def load_proposal_roidb(dataset_name, image_set_name, root_path, dataset_path, result_path=None,\n proposal='rpn', append_gt=True, flip=False):\n imdb = eval(dataset_name)(image_set_name, root_path, dataset_path, result_path)\n\n gt_roidb = imdb.gt_roidb()\n roidb = eval('imdb.' + proposal + '_roidb')(gt_roidb, append_gt)\n if flip:\n roidb = imdb.append_flipped_images(roidb)\n return roidb","def load_proposal_roidb(dataset_name, image_set_name, root_path, dataset_path, result_path=None,\n proposal='rpn', append_gt=True, flip=False,proposal_path='proposals', only_gt=False,\n get_imdb=False, load_mask=False):\n imdb = eval(dataset_name)(image_set_name, root_path, dataset_path, result_path,load_mask=load_mask)\n\n roidb = imdb.gt_roidb()\n #roidb = roidb[:1000]\n if not only_gt:\n roidb = eval('imdb.' + proposal + '_roidb')(roidb, append_gt,proposal_path=proposal_path)\n else:\n # Make sure boxes are converted to float\n for r in roidb:\n r['boxes'] = r['boxes'].astype(np.float32)\n if flip:\n roidb = imdb.append_flipped_images(roidb)\n\n if get_imdb:\n return roidb, imdb\n\n return roidb","def findROICentres(smt_file): #{\n rois = []\n ary = None\n state = 0\n roi_centres = { \n 'head_ct': None,\n 'neck_cb': None,\n 'shoulder_l': None,\n 'shoulder_r': None,\n 'elbow_l': None,\n 'elbow_r': None,\n 'pelvis_c': None,\n 'wrist_l': None,\n 'wrist_r': None,\n 'hip_l': None,\n 'hip_r': None,\n 'knee_l': None,\n 'knee_r': None,\n 'ankle_l': None,\n 'ankle_r': None,\n 'toes_e': None}\n\n vrbMsg(1, 'findROICentres() smt_file = ' + smt_file)\n # Read the smoothed Woolz object and create a NumPy array from it\n err_num, smt_obj = readWoolzObj(smt_file)\n if(not bool(err_num)): #{\n\t err_num, org, ary = wlzObjToNP(smt_obj)\n #}\n sz = np.shape(ary)\n vrbMsg(5, 'findROICentres() object size = ' + str(sz))\n # Work down the scan finding coordinates, ordering has dependency\n # but this is checked in the individual functions\n if((sz[0] >= img_size_min) and (sz[1] >= img_size_min)): #{\n findProfileHeadCT(roi_centres, ary)\n findProfileToes(roi_centres, ary)\n #}\n if(bool(roi_centres['toes_e']) and bool(roi_centres['head_ct'])): #{\n findProfileShoulders(roi_centres, ary)\n findProfilePelvis(roi_centres, ary)\n findProfileHip(roi_centres, ary)\n findProfileElbow(roi_centres, ary)\n findProfileWrist(roi_centres, ary)\n findProfileKnee(roi_centres, ary)\n findProfileAnkle(roi_centres, ary)\n rois = roi_centres\n for cen in rois: #{\n # numpy gives int64 which is not always handled (eg by json) so convert\n pos = rois[cen]\n if(not (pos is None)): #{\n rois[cen] = [int(pos[0]), int(pos[1])]\n #}\n #}\n #}\n vrbMsg(1, 'findROICentres() rois = ' + str(rois))\n return rois","def gt_roidb(self):\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n gt_roidb = [self._load_pascal_annotation(index)\n for index in self.image_index]\n with open(cache_file, 'wb') as fid:\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print 'wrote gt roidb to {}'.format(cache_file)\n\n return gt_roidb","def gt_roidb(self):\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n raw_annotations = self._load_annotations()\n gt_roidb = self._format_raw_annotations(raw_annotations)\n with open(cache_file, 'wb') as fid:\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print 'wrote gt roidb to {}'.format(cache_file)\n\n return gt_roidb","def toRadString(self):\r\n pass","def gt_roidb(self):\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n gt_roidb = [self._load_nimble_annotation(index)\n for index in self.image_index]\n with open(cache_file, 'wb') as fid:\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print 'wrote gt roidb to {}'.format(cache_file)\n\n return gt_roidb","def mezclar_bolsa(self):","def risePen(gcode):\r\n gcode.append(\"M300 S46\")\r\n #gcode.append(\"G0 Z0.1000\")\r","def ROCKSTAR_ASCII():\n dt= [\n ('haloid' , np.int64), #id\n ('n_particles' , np.int64), #num_p\n ('mhalo' , np.float32), #mvir \n ('mbasic' , np.float32), #mbound_vir \n ('rvir' , np.float32), #rvir\n ('vmax' , np.float32), #vmax\n ('rvmax' , np.float32), #rvmax\n ('vrms' , np.float32), #vrms \n ('x_pos' , np.float32), #x\n ('y_pos' , np.float32), #y\n ('z_pos' , np.float32), #z\n ('x_vel' , np.float32), #vx\n ('y_vel' , np.float32), #vy\n ('z_vel' , np.float32), #vz\n ('x_ang' , np.float32), #Jx\n ('y_ang' , np.float32), #Jy\n ('z_ang' , np.float32), #Jz\n ('engery' , np.float32), #E\n ('spinParameter' , np.float32), #Spin\n ('unc_pos' , np.float32), #PosUncertainty\n ('unc_vel' , np.float32), #VelUncertainty\n ('x_vel_bulk' , np.float32), #bulx_vx\n ('y_vel_bulk' , np.float32), #bulx_vy\n ('z_vel_bulk' , np.float32), #bulx_vz\n ('unc_vel_bulk' , np.float32), #BulkVelUnc\n ('n_core' , np.int64), #n_core\n ('mhalo_200b' , np.float32), #m200b \n ('mhalo_200c' , np.float32), #m200c\n ('mhalo_500c' , np.float32), #m500c\n ('mhalo_2500c' , np.float32), #m2500c\n ('x_off' , np.float32), #Xoff\n ('v_off' , np.float32), #Yoff\n ('spin_Bullock' , np.float32), #spin_bullock\n ('b_to_a' , np.float32), #b_to_a \n ('c_to_a' , np.float32), #c_to_a\n ('x_a' , np.float32), #A[x]\n ('y_a' , np.float32), #A[y]\n ('z_a' , np.float32), #A[z] \n ('b_to_a_500c' , np.float32), #b_to_a(500c)\n ('c_to_a_500c' , np.float32), #c_to_a(500c) \n ('x_a_500c' , np.float32), #A[x](500c) \n ('y_a_500c' , np.float32), #A[y](500c) \n ('z_a_500c' , np.float32), #A[z](500c)\n ('rscale' , np.float32), #rs \n ('rscale_Klypin' , np.float32), #rs_Klypin\n ('T_U' , np.float32), #T/|U|\n ('Mpseudo_Behroozi', np.float32), #M_pe_Behroozi\n ('Mpseudo_Diemer' , np.float32), #M_pe_Diemer\n ('rhalf_mass' , np.float32), #Halfmass_Radius\n ('idx' , np.int64), #internal debugging quantity\n ('i_so' , np.int64), #internal debugging quantity\n ('i_ph' , np.int64), #internal debugging quantity\n ('n_particle_child', np.int64), #internal debugging quantity\n ('mmetric' , np.float32) #internal debugging quantity \n ] \n return dt","def constroi(self):\n\n #---------------------------------------------------------\n # nnos = numero de nos\n # ngl = numero de graus de liberdade\n # ID entra como matriz de zeros e uns e sai com uma matriz\n # contendo os indices dos graus de liberdade e\n # zeros nas restriçoes\n # con = contem a conectividade de cada elemento\n # --------------------------------------------------------\n nnos = len(self.ID)\n ngl = 0.0\n\n for i in range(nnos):\n for j in range(2):\n n = self.ID[i][j]\n if n >= 1:\n self.ID[i][j]=0.0\n else:\n ngl = ngl + 1\n self.ID[i][j] = ngl\n\n self.LD = np.zeros((self.nelm,4))\n for i in range(self.nelm):\n for j in range(2):\n self.LD[i][j] = self.ID[self.conect[i][0]][j]\n self.LD[i][j+2] = self.ID[self.conect[i][1]][j]\n return np.transpose(self.LD)","def rauzy_diagram(self, **args):\n return LabelledRauzyDiagram(self, **args)","def rauzy_diagram(self, **kargs):\n return LabelledRauzyDiagram(self, **kargs)","def parse_R(self, line: str):\n\n # R node1 node2 __value\n # R name node1 node2 __value\n name, node1, node2, value = self.parse_two_node_component(line,\"ohm\")\n return IComponent.R(node1, node2, value, name)","def make_rat():\n rats_path = os.path.dirname(__file__)\n models_path = os.path.join(rats_path, '..', 'models')\n recon22_path = os.path.join(models_path, 'recon_2.2.xml')\n rambo_path = os.path.join(rats_path, 'rambo.xml')\n sbml = read_sbml(recon22_path)\n\n# v_sol, f_opt = optimize_cobra_model(sbml, 1000)\n# print 'optimal growth rate:\\t%g\\n'%(f_opt)\n\n # map hgnc to rat\n hgnc_map = {}\n hgnc_map_file = os.path.join(rats_path, 'ensembl_hgnc_to_rat.txt')\n with open(hgnc_map_file, 'rU') as csvfile:\n reader = csv.reader(csvfile, delimiter='\\t')\n for row in reader:\n # ensembl = row[0].strip()\n hgnc = row[1].strip()\n hgnc = hgnc.replace('HGNC:','')\n if len(row) > 2:\n rat = row[2].strip()\n else:\n rat = ''\n\n if hgnc not in hgnc_map:\n hgnc_map[hgnc] = ''\n if not hgnc_map[hgnc]:\n hgnc_map[hgnc] = rat\n\n model = sbml.getModel()\n to_remove = []\n for reaction in model.getListOfReactions().clone():\n rID = reaction.getId()\n ga_human = get_notes_field(rID, 'GENE_ASSOCIATION', sbml)\n if ga_human:\n ga_human = ga_human.replace('HGNC:', '') \n ga_rat = ga_human\n for hgnc in re.findall(r'\\b\\S+\\b', ga_human):\n if (hgnc not in ['and', 'or', 'AND', 'OR']):\n if hgnc in hgnc_map:\n rat = hgnc_map[hgnc]\n else:\n print 'HGNC:%s\\tnot found'%hgnc\n rat = ''\n if not rat:\n rat = 'False'\n ga_rat = re.sub(r'\\b' + hgnc + r'\\b', rat, ga_rat)\n ga_rat = to_dnf(ga_rat)\n set_notes_field(rID, 'GENE_ASSOCIATION', ga_rat, sbml)\n\n# if not ga_rat:\n# to_remove.append(rID)\n# print '%s\\t[%s]\\n%s\\n'%(rID, reaction.getName(), ga_human)\n# print '%s of %s reactions removed\\n'%(len(to_remove), model.getNumReactions())\n\n for rID in to_remove:\n model.removeReaction(rID)\n\n model.setName('rambo')\n model.setId('rambo')\n model.setMetaId('meta_' + model.getId())\n model.setAnnotation(model.getAnnotation())\n\n write_sbml(sbml, rambo_path)\n\n v_sol, f_opt = optimize_cobra_model(sbml, 1000)\n print 'optimal growth rate:\\t%g\\n'%(f_opt)","def ridgelen(id,ir,jr,fr):\n\n\n\tlr=ridgelenloop(id,ir,jr,fr)\n\n\treturn lr","def getRoverImage(self):\n # Your code goes here, this code is just an example\n return 'mario.ppm'","def selective_search_roidb(self):\n # cache_path: data/cache/Actions/\n # self.name: rcnn_<>_<>\n # cache_file: data/cache/Actions/rcnn_<datatype>_<imageset>_selective_search_roidb.pkl\n cache_file = None\n if cfg.LESSEN_DEBUG_TIME:\n lessen_debug_str = cfg.LESSEN_DEBUG_STR\n cache_file = os.path.join(self.cache_path, self.name + \"_\" + \n lessen_debug_str + '_selective_search_roidb.pkl')\n else:\n cache_file = os.path.join(self.cache_path, self.name + '_selective_search_roidb.pkl')\n\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} ss roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n if self._image_set != 'test':\n gt_roidb = self.gt_roidb()\n gt_roidb, ss_roidb = self._load_selective_search_roidb(gt_roidb)\n roidb = action_datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)\n else:\n roidb = self._load_selective_search_roidb(None)\n\n\n with open(cache_file, 'wb') as fid:\n cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print 'wrote ss roidb to {}'.format(cache_file)\n\n return roidb","def obtenerRecorrido(nodo, dist):\n\n recorrido = []\n #Obtenemos el recorrido siguiendo la referencia al padre desde el ultimo nodo.\n while(nodo.getPadre() is not None):\n recorrido.append(nodo.getId())\n nodo = nodo.getPadre()\n #El ciclo termina antes de agregar al padre, por lo que se agrega.\n recorrido.append(nodo.getId())\n camino = \"\"\n #Se recorre el arreglo a la inversa para empezar con la primera ciudad\n for i in range(len(recorrido)-1, 0, -1):\n #Por cada ciudad se calcula la distancia con la siguiente\n camino += \"[C\" + str(recorrido[i]) + \"] -> \" + str(dist[recorrido[i]][recorrido[i-1]]) + \" -> \"\n #La ultima ciudad no tiene siguiente\n camino += \"[C\" + str(recorrido[0]) + \"]\"\n return camino","def generar_red_neuronal (codigo, estadisticas=True):\n \n path = \"../data/entrenamiento/\" + str(codigo) + \"/\"\n \n f = open(path + \"data_neural_network_\" + str(codigo) + \".txt\")\n cab = str(f.readline())[:-1]\n cab = cab.replace(\"'\",\"\")\n cab = cab.replace(\" \",\"\")\n cabeceras = cab[1:-1].split(\",\")\n l_etiquetas = str(f.readline())[:-1].split(\",\")\n atributos = str(f.readline())[:-1].split(\",,\")\n f.close()\n\n l_atributos = []\n for atributo in atributos:\n l_atributos.append(atributo.split(\",\"))\n\n etiquetas = set(l_etiquetas) \n clases = sorted(list(etiquetas))\n \n l_atributos = np.array(l_atributos, \"float32\")\n l_etiquetas = np.array(l_etiquetas, \"float32\")\n \n\n #Separamos los datos que vamos a utilizar de entrenamiento y para realizar el test\n #datos de pruebas (0.25) de los de entrenamiento (0.75)\n X_train, X_test, y_train, y_test = train_test_split(l_atributos,l_etiquetas,test_size = 0.25,random_state = 0)\n\n #Creamos la red neuronal \n red = MLPClassifier(max_iter=100000, hidden_layer_sizes=(50,25))\n #Entrenamos la red neuronal\n red.fit(X_train, y_train)\n\n #Predicion de los resultados del bloque test\n y_pred = red.predict(X_test)\n #Matriz de confusion\n cm = confusion_matrix(y_test, y_pred)\n #Reportes\n report = classification_report(y_test, y_pred) \n\n\n\n if estadisticas == True:\n f=open(path + \"export_neural_network_statistics_\" + str(codigo) + \".txt\",\"w\") \n f.write(\"************************ CLASS *************************\\n\")\n for i in range(len(clases)):\n f.write(str(clases[i]) + \"\\n\")\n f.write(\"\\n\\n\")\n f.write(\"********************** FEATURES **********************\\n\")\n for i in range(len(cabeceras[:-1])):\n f.write(str(cabeceras[i]) + \"\\n\")\n f.write(\"\\n\\n\")\n f.write(\"************************ SCORE *************************\\n\")\n f.write(\"With Test data: \" + str(red.score(X_test, y_test)) + \"\\n\")\n f.write(\"With Training data: \" + str(red.score(X_train, y_train)) + \"\\n\")\n f.write(\"\\n\\n\")\n f.write(\"****************** CONFUSION MATRIX ********************\\n\")\n if len(clases)==2:\n f.write(\"\\t0\\t1\\n\")\n f.write(\"---------------------\\n\")\n f.write(\"0 |\\t\"+ str(cm[0][0]) +\"\\t\"+ str(cm[0][1]) +\"\\n\")\n f.write(\"1 |\\t\"+ str(cm[1][0]) +\"\\t\"+ str(cm[1][1]) +\"\\n\")\n if len(clases)==3:\n f.write(\"\\t0\\t1\\t2\\n\")\n f.write(\"--------------------------------\\n\")\n f.write(\"0 |\\t\"+ str(cm[0][0]) +\"\\t\"+ str(cm[0][1]) +\"\\t\"+ str(cm[0][2]) +\"\\n\")\n f.write(\"1 |\\t\"+ str(cm[1][0]) +\"\\t\"+ str(cm[1][1]) +\"\\t\"+ str(cm[1][2]) +\"\\n\")\n f.write(\"2 |\\t\"+ str(cm[2][0]) +\"\\t\"+ str(cm[2][1]) +\"\\t\"+ str(cm[2][2]) +\"\\n\")\n if len(clases)==4:\n f.write(\"\\t0\\t1\\t2\\t3\\n\")\n f.write(\"----------------------------------------------\\n\")\n f.write(\"0 |\\t\"+ str(cm[0][0]) +\"\\t\"+ str(cm[0][1]) +\"\\t\"+ str(cm[0][2]) +\"\\t\"+ str(cm[0][3]) +\"\\n\")\n f.write(\"1 |\\t\"+ str(cm[1][0]) +\"\\t\"+ str(cm[1][1]) +\"\\t\"+ str(cm[1][2]) +\"\\t\"+ str(cm[1][3]) +\"\\n\")\n f.write(\"2 |\\t\"+ str(cm[2][0]) +\"\\t\"+ str(cm[2][1]) +\"\\t\"+ str(cm[2][2]) +\"\\t\"+ str(cm[2][3]) +\"\\n\")\n f.write(\"3 |\\t\"+ str(cm[3][0]) +\"\\t\"+ str(cm[3][1]) +\"\\t\"+ str(cm[3][2]) +\"\\t\"+ str(cm[3][3]) +\"\\n\")\n f.write(\"\\n\\n\")\n f.write(\"************************ REPORT ***********************\\n\")\n f.write(report)\n f.close()\n \n print(str(codigo) + \": neural network created\") \n return (red, red.score(X_test, y_test))","def abstract(res):\n o = r'\\begin{center}'\n #o += r'\\begin{tikzpicture}[x={(-0.5cm,-0.5cm)}, y={(0.966cm,-0.2588cm)}, z={(0cm,1cm)}, scale=0.6, color={lightgray},opacity=.5]'\n #o += r'\\tikzset{facestyle/.style={fill=lightgray,draw=black,very thin,line join=round}}'\n o += r'\\begin{tikzpicture}' + '\\n'\n o += r'\\draw[blue!40!white] (0,0) rectangle (6,4); \\fill[blue!10!white] (2.4,4) rectangle (3.6,4.15);' + '\\n'\n for i in range(res[7]):\n x,y = random.randrange(2,538)/100.0,random.randrange(2,300)/100.0\n o += r'\\filldraw[fill=green!30!white,draw=white] (%s,%s) rectangle (%s,%s);'%(x,y,(x+0.58),(y+0.38)) + '\\n'\n o += r'\\filldraw[white] (%s,%s) -- (%s,%s);'%((x+0.29),(y+0.19),(x+0.58),(y+0.38)) + '\\n'\n o += r'\\filldraw[white] (%s,%s) -- (%s,%s);'%(x,(y+0.38),(x+0.29),(y+0.19)) + '\\n'\n o += r'\\end{tikzpicture}\\end{center}' + '\\n'\n\n o += r'\\begin{tabular}{|l|l|}' + '\\n' + r'\\hline' + '\\n'\n o += r'Election name& \\texttt{\"%s\"}\\\\'%res[1]\n o += r'Box number& \\texttt{%s}\\\\'%res[2]\n o += r'State& \\texttt{%s}\\\\'%('closed' if res[5] == cloSt else ('vote' if res[5] == votSt else 'register'))\n o += r'Registration end& \\textit{%s}\\\\'%res[3]\n o += r'Vote closing& \\textit{%s}\\\\'%res[4]\n o += r'Casted/registered& $%s/%s$\\\\'%(res[7],res[6]) +'\\n'\n o += r'\\hline\\end{tabular}' + '\\n'\n o += r'\\quad' + '\\n'\n o += r'\\begin{tabular}{|l|l|}\\hline'\n l = res[8].items()\n l.sort(key = operator.itemgetter(1),reverse=True)\n n = 0\n for x in l:\n o += r'%s & %s\\\\'%(r'\\textit{%s}'%x[0] if x[0] == 'White Ballot' else r'\\texttt{%s}'%x[0],x[1]) \n if n == 0:\n o += r'\\hline' + '\\n'\n n += 1\n o += r'\\hline\\end{tabular}' + '\\n'\n\n\n #o += r'\\item The designer\\textquoteright s digital signature of this document (the source file \\texttt{oeu.py}) is: \\tiny $$\\verb!%s!$$ \\normalsize'%rsa(IKey).sign(open(__file__).read()) + '\\n'\n\n return r'\\begin{abstract}' + abstract.__doc__ + r'\\end{abstract}' + o","def rond(self):\n return self._rond.get_waarde()","def genotype(rsid):\n if rsid[0] == 'I' or rsid[0] == 'i':\n return { 'error': 'Cannot find indicators, must use rs #s'}\n soup = BeautifulSoup(urllib.urlopen('http://snpedia.com/index.php/Special:Browse/' + rsid).read())\n trows = soup('table')[1].find_all('tr')\n if len(trows) < 2:\n return { 'error': 'That rsid does not have any data/does not exist.' }\n locations = getLocations(soup)\n genotypeData = getData(locations, soup)\n genotypeData['rsid'] = rsid\n return genotypeData","def mainRoads(osm_path): \n return retrieve(osm_path,'lines',['highway','oneway','lanes','maxspeed'],**{'highway':[\"='primary' or \",\"='trunk' or \",\"='motorway' or \",\"='motorway_link' or \",\"='trunk_link' or \",\"='primary_link' or \", \"='secondary' or \",\"='tertiary' or \",\"='tertiary_link'\"]})","def buildRomaniagraph(Graph):\n \n g=Graph()\n for name in ('Oradea','Zerind','Arad','Timisoara', 'Lugoj','Mehadia', \n 'Dobreta','Sibiu','Fagaras','Rimnicu Vilcea','Pitesti','Craiova',\n 'Bucharest','Giurgiu','Urziceni','Hirsova','Eforie','Vaslui',\n 'Iasi','Nearnt'):\n g.addNode(Node(name))\n \n \n g.addEdge(Edge(g.getNode('Oradea'),g.getNode('Zerind')))\n g.addEdge(Edge(g.getNode('Oradea'),g.getNode('Sibiu')))\n g.addEdge(Edge(g.getNode('Zerind'),g.getNode('Arad')))\n g.addEdge(Edge(g.getNode('Arad'),g.getNode('Timisoara')))\n g.addEdge(Edge(g.getNode('Lugoj'),g.getNode('Timisoara')))\n g.addEdge(Edge(g.getNode('Lugoj'),g.getNode('Mehadia')))\n g.addEdge(Edge(g.getNode('Mehadia'),g.getNode('Dobreta')))\n g.addEdge(Edge(g.getNode('Dobreta'),g.getNode('Craiova')))\n g.addEdge(Edge(g.getNode('Craiova'),g.getNode('Pitesti')))\n g.addEdge(Edge(g.getNode('Craiova'),g.getNode('Rimnicu Vilcea')))\n g.addEdge(Edge(g.getNode('Rimnicu Vilcea'),g.getNode('Sibiu')))\n g.addEdge(Edge(g.getNode('Sibiu'),g.getNode('Fagaras')))\n g.addEdge(Edge(g.getNode('Pitesti'),g.getNode('Bucharest')))\n g.addEdge(Edge(g.getNode('Bucharest'),g.getNode('Giurgiu')))\n g.addEdge(Edge(g.getNode('Bucharest'),g.getNode('Urziceni')))\n g.addEdge(Edge(g.getNode('Arad'),g.getNode('Sibiu')))\n g.addEdge(Edge(g.getNode('Rimnicu Vilcea'),g.getNode('Pitesti')))\n g.addEdge(Edge(g.getNode('Bucharest'),g.getNode('Fagaras')))\n g.addEdge(Edge(g.getNode('Vaslui'),g.getNode('Urziceni')))\n g.addEdge(Edge(g.getNode('Hirsova'),g.getNode('Urziceni')))\n g.addEdge(Edge(g.getNode('Hirsova'),g.getNode('Eforie')))\n g.addEdge(Edge(g.getNode('Vaslui'),g.getNode('Iasi')))\n g.addEdge(Edge(g.getNode('Iasi'),g.getNode('Nearnt')))\n \n return g","def test_RUMI():\r\n\r\n start = 11051\r\n end = 11902\r\n read_poems(start, end)","def gt_roidb(self):\n \"\"\"\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n \"\"\"\n gt_roidb = [self._load_kitti_annotation(index)\n for index in self.image_index]\n \"\"\"\n with open(cache_file, 'wb') as fid:\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print 'wrote gt roidb to {}'.format(cache_file)\n \"\"\"\n\n return gt_roidb","async def get_roi(self):","def _repr_(self):\n return \"Lie algebra %s over %s\" % (self._classification,\n self.base_ring())","def test_visualize_rdkit(self):\n import IPython\n\n mol = Molecule().from_smiles(\"CCO\")\n\n assert isinstance(mol.visualize(backend=\"rdkit\"), IPython.core.display.SVG)","def get_training_roidb(self,imdb):\n if self.config.TRAIN.USE_FLIPPED:\n print('Appending horizontally-flipped training examples...')\n imdb.append_flipped_images()\n print('done')\n \n print('Preparing training data...')\n if self.config.TRAIN.HAS_RPN:\n self.prepare_roidb(imdb)\n else:\n self.prepare_roidb(imdb)\n print('done')\n \n return imdb.roidb","def validateRaxmlModels(self, input): \n filename=input+\".mg.modelFromMG.txt\"\n arq = open(filename, \"r\")\n output = \"\"\n conteudo = arq.readlines()\n seqcont = 0\n output = \"True\"\n modelogerado = \"\"\n listamodelos = ['DAYHOFF', 'DCMUT', 'JTT', 'MTREV', 'WAG', 'RTREV', 'CPREV',\n 'VT', 'BLOSUM62', 'MTMAM', 'MTART', 'MTZOA', 'LG', 'PMB',\n 'HIVB', 'HIVW', 'JTTDCMUT', 'FLU','GTR']\n\n if len(conteudo) == 0 or len(conteudo) > 1:\n output = \"False\"\n else:\n modelogerado = conteudo[0].strip()\n if modelogerado.upper() not in listamodelos:\n print \"Teste\"\n output = \"False\" \n \n return {\"MG_MODEL\":modelogerado, \"MG_MODEL_VALID\":output}","def pyradigms_from_adj(main_data):\n # names are not in files. Hard code here instead\n roi_names = [\n 'L_ant_med_OFC_1', 'L_post_med_OFC_1', 'L_ant_VMPFC', 'L_post_med_OFC_2', 'L_ant_med_OFC_2',\n 'L_vent_ACC', 'L_subg_cingulate', 'L_rostr_ACC', 'R_ant_med_OFC_1', 'R_post_med_OFC_1', 'R_ant_VMPFC',\n 'R_post_med_OFC_2','R_ant_med_OFC_2','R_vent_ACC', 'R_subg_cingulate', 'R_rostr_ACC', 'L_caudate',\n 'L_NAC', 'L_putamen', 'R_caudate', 'R_NAC', 'R_putamen', 'VTA']\n\n # output of ROI_TempCor.R nested inside visit directories\n prefix=\"vmpfc_striatal_vta_mean_gsr_pearson_adj_pearson.txt\"\n\n # each connectivity set has their own path to the adjacency matrix\n fc_globs = {'bkgrd': f'/Volumes/Hera/Projects/mMR_PETDA/subjs/1*_2*/func/*{prefix}',\n 'rest1': f'/Volumes/Zeus/preproc/petrest_rac1/MHRest_FM_ica/1*_2*/*{prefix}',\n 'rest2': f'/Volumes/Zeus/preproc/petrest_rac2/MHRest_FM_ica/1*_2*/*{prefix}'}\n\n # 'Regr' b/c age is continuous.\n # allow_nan_inf might be a mistake. easy for now (20201208)\n FCds = {k: RegrDataset(allow_nan_inf=True) for k in fc_globs.keys()}\n FCds['bkgrd'].description = \"Functional connectivity w/23 ROIs from task chunked background timeseries\"\n FCds['rest1'].description = \"Functional connectivity w/23 ROIs from first rest timeseries\"\n FCds['rest2'].description = \"Functional connectivity w/23 ROIs from second rest timeseries\"\n\n # 253 roi-roi pairs for each of background, rest1, and rest1\n # use info stored in the super wide dataframe to get age and session id from each file\n # to create each samplet that composes each (bkgrd,rest1,2) of the connectivity datasets\n for k in fc_globs.keys():\n roi = ROI_FC(fc_globs[k], roi_names)\n main_data.all_adj_into(FCds[k], roi, f'data/conn_adj_{k}.csv')\n \n return FCds","def get_rlp(self, rlp):\n xyz = cm.sphere_to_cart(r=rlp[0], lam=rlp[1], phi=rlp[2])\n return self.get_xyz(xyz=xyz)","def gt_roidb(self):\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n annotations_data = open(self.annotations_file, 'r')\n #self.ann_json_data = json.load(annotations_data)\n gt_roidb = [self._load_hover_annotation(line)\n for line in annotations_data]\n annotations_data.close()\n# pdb.set_trace()\n with open(cache_file, 'wb') as fid:\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print 'wrote gt roidb to {}'.format(cache_file)\n\n return gt_roidb","def radrad(rxn_class):\n return rxn_class[2]","def selective_search_roidb(self):\n cache_file = os.path.join(self.cache_path,\n self.name + '_selective_search_roidb.pkl')\n\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} ss roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n # if int(self._year) == 2007 or self._image_set != 'test':\n gt_roidb = self.gt_roidb()\n ss_roidb = self._load_selective_search_roidb(gt_roidb)\n roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)\n # else:\n # roidb = self._load_selective_search_roidb(None)\n with open(cache_file, 'wb') as fid:\n cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print 'wrote ss roidb to {}'.format(cache_file)\n\n return roidb","def load_gt_roidb(dataset_name, image_set_name, root_path, dataset_path, result_path=None,\n flip=False):\n imdb = eval(dataset_name)(image_set_name, root_path, dataset_path, result_path)\n roidb = imdb.gt_roidb()\n if flip:\n roidb = imdb.append_flipped_images(roidb)\n return roidb","def load_gt_roidb(dataset_name, image_set_name, root_path, dataset_path, result_path=None,\n flip=False):\n imdb = eval(dataset_name)(image_set_name, root_path, dataset_path, result_path)\n roidb = imdb.gt_roidb()\n if flip:\n roidb = imdb.append_flipped_images(roidb)\n return roidb","def get_rz(self):\n return self.rz","def llnr2cgid(self, llnr):\n possible = self.phenotypes[self.phenotypes.LLnr == llnr].cgID.values\n if len(possible) > 0:\n return possible[0]\n #fi\n return None","def __loadFromFile(self):\n try:\n f=open(self.__fileR, \"r\")\n line =f.readline().strip()\n rez=[]\n while line!=\"\":\n attrs=line.split(\",\")\n rt=Rent(attrs[0], attrs[1], attrs[2], attrs[3])\n rez.append(rt)\n line=f.readline().strip()\n f.close()\n return rez\n #the file cannot be reached\n except IOError:\n return None","def annToRLE(self, ann):\n t = self.imgs[ann['image_id']]\n h, w = t['height'], t['width']\n segm = ann['segmentation']\n if type(segm) == list:\n # polygon -- a single object might consist of multiple parts\n # we merge all parts into one mask rle code\n rles = maskUtils.frPyObjects(segm, h, w)\n rle = maskUtils.merge(rles)\n elif type(segm['counts']) == list:\n # uncompressed RLE\n rle = maskUtils.frPyObjects(segm, h, w)\n else:\n # rle\n rle = ann['segmentation']\n return rle","def load_gt_roidb(dataset_name, image_set_name, root_path, dataset_path,\n flip=False, verbose=False):\n imdb = retinaface(image_set_name, root_path, dataset_path)\n roidb = imdb.gt_roidb()\n if verbose:\n print('roidb size', len(roidb))\n if flip:\n roidb = imdb.append_flipped_images(roidb)\n if verbose:\n print('flipped roidb size', len(roidb))\n return roidb","def armlengte(self):\n return self._armlengte.get_waarde()","def armlengte(self):\n return self._armlengte.get_waarde()","def site2nrml(model, params_dict): \n \"\"\"\n # Some XML definitions\n NAMESPACE = 'http://openquake.org/xmlns/nrml/0.4'\n GML_NAMESPACE = 'http://www.opengis.net/gml'\n SERIALIZE_NS_MAP = {None: NAMESPACE, 'gml': GML_NAMESPACE} \n gml_ns = SERIALIZE_NS_MAP['gml']\n \"\"\"\n \n # Head matter \n root = etree.Element(_tag='nrml', nsmap={'gml': 'http://www.opengis.net/gml'})\n root.set('xmlns', 'http://openquake.org/xmlns/nrml/0.4')\n root.append(etree.Comment('%s' % '%s site model' %(model)))\n \n\n # Define Site Model Name \n sMod = etree.SubElement(root, \"siteModel\")\n sMod.set('name', model + ' Site Model')\n \n # Define sub element\n \n for key in params_dict:\n \n site = etree.SubElement(sMod, \"site\")\n site.set('lon', '%s' % key[0])\n site.set('lat', '%s' % key[1])\n site.set('vs30', '%s' % params_dict[key][0])\n site.set('vs30Type', '%s' % 'inferred')\n site.set('z1pt0', '%s' % '%3.3f' % float(params_dict[key][1]))\n site.set('z2pt5', '%s' % '%3.3f' % float(params_dict[key][2]))\n \n #print(getMinMax(params_dict))\n \n # Form tree and write to xml\n root_tree = etree.ElementTree(root)\n outFile = open((out_directory + '/' + out_filename), 'wb')\n root_tree.write(outFile, encoding=\"utf-8\", xml_declaration=True, pretty_print=True)","def selective_search_roidb(self):\n cache_file = os.path.join(self.cache_path,\n self.name + '_proposal_roidb.pkl')\n\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} ss roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n if self._image_set != 'test':\n gt_roidb = self.gt_roidb()\n ss_roidb = self._load_selective_search_roidb(gt_roidb)\n roidb = imdb.merge_roidbs(gt_roidb, ss_roidb)\n else:\n roidb = self._load_selective_search_roidb(None)\n with open(cache_file, 'wb') as fid:\n cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print 'wrote ss roidb to {}'.format(cache_file)\n\n return roidb","def get_training_roidb(imdb):\n if cfg.TRAIN.USE_FLIPPED:\n print 'Appending horizontally-flipped training examples...'\n imdb.append_flipped_images()\n print 'done'\n\n print 'Preparing training data...'\n rdl_roidb.prepare_roidb(imdb)\n print 'done'\n\n return imdb.roidb","def __local_rn(soup):\n return __get_local_g1_news(soup)","def __local_rn(soup):\n return __get_local_g1_news(soup)","def generate_ROI_file(FreeSurfer_ROI_file):\n\tfrom nipype.interfaces.freesurfer import MRIConvert\n\tmc = MRIConvert()\n\tmc.inputs.in_file = FreeSurfer_ROI_file\n\tmc.inputs.out_type = 'niigz'\n\tmc.run()\n\n\timport nipype.interfaces.cmtk as cmtk\n\trg = cmtk.ROIGen()\n\trg.inputs.aparc_aseg_file = FreeSurfer_ROI_file.split('.')[0] + '_out.nii.gz'\n\trg.inputs.use_freesurfer_LUT = True\n\tout_file = rg.run()\n\n\treturn out_file","def rms_str(self):\n if self.image_status == 'match':\n return '< tolerance' # self.rms is None\n elif self.image_status == 'diff':\n return self.rms\n else: # Missing baseline image\n return 'None'","def to_rna(self):\n thymidine = 'T'\n uracil = 'U'\n return self.dna.replace(thymidine, uracil)","def prepare_roidb(self):\n # for pascal_voc dataset\n roidb = self.gt_roidb()\n # data argument\n if self.cfg.if_flipped is True:\n print('append flipped images to training')\n roidb = self.append_flipped_images(roidb)\n\n sizes = [PIL.Image.open(self.image_path_at(i)).size\n for i in range(self.num_images)]\n\n for i in range(len(self.image_index)):\n roidb[i]['image'] = self.image_path_at(i)\n roidb[i]['width'] = sizes[i][0]\n roidb[i]['height'] = sizes[i][1]\n # need gt_overlaps as a dense array for argmax\n gt_overlaps = roidb[i]['gt_overlaps'].toarray()\n # max overlap with gt over classes (columns)\n max_overlaps = gt_overlaps.max(axis=1)\n # gt class that had the max overlap\n max_classes = gt_overlaps.argmax(axis=1)\n roidb[i]['max_classes'] = max_classes\n roidb[i]['max_overlaps'] = max_overlaps\n # sanity checks\n # max overlap of 0 => class should be zero (background)\n zero_inds = np.where(max_overlaps == 0)[0]\n assert all(max_classes[zero_inds] == 0)\n # max overlap > 0 => class should not be zero (must be a fg class)\n nonzero_inds = np.where(max_overlaps > 0)[0]\n assert all(max_classes[nonzero_inds] != 0)\n\n self.roi_data = ROIGenerator(roidb, self.num_classes, self.cfg)\n return self.roi_data","def mamajek08_logRpHK_Ro_edge():\n Ro_edge = 0.31935816876122064\n return Ro_edge","def write_gro(strucC,data_file):\n #\n latvec = strucC.getLatVec()\n\n gro_lines = \" com2gro \\n\"\n gro_lines += \" %-2i \\n\" %( int(len(strucC.ptclC)) )\n atom_indx = 0 \n for pid, pt_i in strucC.ptclC:\n atom_indx += 1\n if( atom_indx > 10000): atom_indx = 1\n r_i = pt_i.position\n r_i_nm = [units.convert_angstroms_nm(r_i[0]) ,units.convert_angstroms_nm(r_i[1]) ,units.convert_angstroms_nm(r_i[2]) ]\n gro_lines += \"%5d%-5s%5s%5d%8.3f%8.3f%8.3f\\n\" % (atom_indx,pt_i.tagsDict[\"resname\"][:5],pt_i.tagsDict[\"label\"][:5],atom_indx,r_i_nm[0],r_i_nm[1],r_i_nm[2] )\n if( atom_indx > 99999 ):\n atom_indx = 1\n \n gro_lines += \" %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f \\n\" % (units.convert_angstroms_nm(latvec[0][0]),units.convert_angstroms_nm(latvec[1][1]),units.convert_angstroms_nm(latvec[2][2]),units.convert_angstroms_nm(latvec[0][1]),units.convert_angstroms_nm(latvec[0][2]),units.convert_angstroms_nm(latvec[1][0]),units.convert_angstroms_nm(latvec[1][2]),units.convert_angstroms_nm(latvec[2][0]),units.convert_angstroms_nm(latvec[2][1])) \n\n F = open( data_file, 'w' )\n F.write(gro_lines)\n F.close()","def write_gro(strucC,data_file):\n #\n latvec = strucC.getLatVec()\n\n gro_lines = \" com2gro \\n\"\n gro_lines += \" %-2i \\n\" %( int(len(strucC.ptclC)) )\n atom_indx = 0 \n for pid, pt_i in strucC.ptclC:\n atom_indx += 1\n if( atom_indx > 10000): atom_indx = 1\n r_i = pt_i.position\n r_i_nm = [units.convert_angstroms_nm(r_i[0]) ,units.convert_angstroms_nm(r_i[1]) ,units.convert_angstroms_nm(r_i[2]) ]\n gro_lines += \"%5d%-5s%5s%5d%8.3f%8.3f%8.3f\\n\" % (atom_indx,pt_i.tagsDict[\"resname\"][:5],pt_i.tagsDict[\"label\"][:5],atom_indx,r_i_nm[0],r_i_nm[1],r_i_nm[2] )\n if( atom_indx > 99999 ):\n atom_indx = 1\n \n gro_lines += \" %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f \\n\" % (units.convert_angstroms_nm(latvec[0][0]),units.convert_angstroms_nm(latvec[1][1]),units.convert_angstroms_nm(latvec[2][2]),units.convert_angstroms_nm(latvec[0][1]),units.convert_angstroms_nm(latvec[0][2]),units.convert_angstroms_nm(latvec[1][0]),units.convert_angstroms_nm(latvec[1][2]),units.convert_angstroms_nm(latvec[2][0]),units.convert_angstroms_nm(latvec[2][1])) \n\n F = open( data_file, 'w' )\n F.write(gro_lines)\n F.close()","def test_rocket():\n ring = [(0,0), (10, 0), (15,5), (10,9), (1,7), (6,4), (0,0)]\n conv = ToPointsAndSegments()\n conv.add_polygon([ring])\n skel = calc_skel(conv, output=True, pause=True)\n print \"DONE\"","def __repr__(self):\n return f'ResidenciaModel(name={self.neighbourhood_group}, neighbourhood={self.room_type})'","def model(self):\r\n\t\tif self.connect != None:\r\n\t\t\tcommandMD = b'#10MD<CR>\\r'\r\n\t\t\twrite = self.connect.write(commandMD) \r\n\t\t\treadData = self.connect.readline()\r\n\t\t\treturn (readData.decode('utf-8')[6:])\r\n\t\treturn('pyrometer is disconected')","def selective_search_roidb(self):\n cache_file = os.path.join(self.cache_path,\n self.name + '_selective_search_roidb.pkl')\n\n if os.path.exists(cache_file):\n with open(cache_file, 'rb') as fid:\n roidb = cPickle.load(fid)\n print '{} ss roidb loaded from {}'.format(self.name, cache_file)\n return roidb\n\n if int(self._year) == 2007 or self._image_set != 'test':\n gt_roidb = self.gt_roidb()\n ss_roidb = self._load_selective_search_roidb(gt_roidb)\n roidb = imdb.merge_roidbs(gt_roidb, ss_roidb)\n else:\n roidb = self._load_selective_search_roidb(None)\n with open(cache_file, 'wb') as fid:\n cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)\n print 'wrote ss roidb to {}'.format(cache_file)\n\n return roidb","def __str__(self):\n if self.hocr is None:\n return ''\n body = self.hocr.find(\".//%sbody\"%(self.xmlns))\n if body:\n return self._get_element_text(body).encode('utf-8') # XML gives unicode\n else:\n return ''","def code() -> str:\n return \"\"\"\n G91 G17\n G0 Y10 X-10\n G0 Y0 X-5\n G0 Y5 X0\n G0 Y0 X5\n G0 Y0 X-5\n G0 Y-5 X0\n G3 Y-5 X5 J0 I5\n G0 Y0 X5\n G0 Y5 X0\n G3 Y5 X-5 J0 I-5\n G0 Y-5 X0\n G0 Y-10 X10\n G0 Y0 X-5\n G0 Y-15 X-15\n G0 Y0 X5\n G0 Y5 X0\n G0 Y0 X-5\n G0 Y-5 X0\n G0 Y5 X0\n G2 Y5 X5 J0 I5\n G0 Y0 X5\n G0 Y-5 X0\n G2 Y-5 X-5 J0 I-5\n G0 Y5 X0\n G0 Y10 X10\n G0 Y0 X-30\n G3 Y0 X-10 J0 I-5\n G3 Y0 X10 J0 I5\n\n G0 Y0 X5\n G3 Y5 X5 J5 I0\n G3 Y10 X-10 J0 I-10\n G3 Y-5 X-5 J-5 I0\n G0 Y-5 X0\n\n G0 Y5 X0\n G3 Y5 X-5 J0 I-5\n G3 Y-10 X-10 J-10 I0\n G3 Y-5 X5 J0 I5\n G0 Y0 X5\n\n G0 Y0 X-5\n G3 Y-5 X-5 J-5 I0\n G3 Y-10 X10 J0 I10\n G3 Y5 X5 J5 I0\n G0 Y5 X0\n\n G0 Y-5 X0\n G3 Y-5 X5 J0 I5\n G3 Y10 X10 J10 I0\n G3 Y5 X-5 J0 I-5\n G0 Y0 X-5\n \"\"\"","def reckon(self):","def get_kgml_obj(pathway_id):\r\n\r\n if pathway_id.startswith('path:'):\r\n pathway_id = pathway_id.replace('path:', '')\r\n resp = requests.get(''.join([Kegg.BASE_URL,\r\n 'get/',\r\n pathway_id,\r\n '/kgml']))\r\n if resp.status_code == 200:\r\n return kgml_read(resp.text)\r\n return None","def test_get_robax_tostring_correct(self):\n got_var, const_jtar = rapid_datatypes.get_rapid_data(self.controller, 'T_ROB1', 'MainModule', 'const_jtarget')\n if not got_var:\n print 'Couldn\\'t get variable. Test will not run.'\n sys.exit()\n robax = rapid_jointtarget.get_robax_tostring(const_jtar)\n self.assertEqual(robax, 'RobAx: [Rax_1,Rax_2,Rax_3,Rax_4,Rax_5,Rax_6] = [0,0,0,10,0,0]')","def ROCKSTAR_ASCII_list():\n \n dt= [\n ('haloid' , np.int64), #ID\n ('descIndex' , np.int64), #DescID\n ('mhalo' , np.float32), #Mvir\n ('vmax' , np.float32), #Vmax\n ('vrms' , np.float32), #Vrms \n ('rvir' , np.float32), #Rvir\n ('rscale' , np.float32), #Rs\n ('n_particles' , np.int64), #Np \n ('x_pos' , np.float32), #x\n ('y_pos' , np.float32), #y\n ('z_pos' , np.float32), #z\n ('x_vel' , np.float32), #vx\n ('y_vel' , np.float32), #vy\n ('z_vel' , np.float32), #vz\n ('x_ang' , np.float32), #Jx\n ('y_ang' , np.float32), #Jy\n ('z_ang' , np.float32), #Jz\n ('spinParameter' , np.float32), #Spin\n ('rscale_Klypin' , np.float32), #rs_Klypin \n ('mbasic' , np.float32), #Mvir_all\n ('mhalo_200b' , np.float32), #m200b \n ('mhalo_200c' , np.float32), #m200c\n ('mhalo_500c' , np.float32), #m500c\n ('mhalo_2500c' , np.float32), #m2500c\n ('x_off' , np.float32), #Xoff\n ('v_off' , np.float32), #Yoff\n ('spin_Bullock' , np.float32), #spin_bullock\n ('b_to_a' , np.float32), #b_to_a \n ('c_to_a' , np.float32), #c_to_a\n ('x_a' , np.float32), #A[x]\n ('y_a' , np.float32), #A[y]\n ('z_a' , np.float32), #A[z] \n ('b_to_a_500c' , np.float32), #b_to_a(500c)\n ('c_to_a_500c' , np.float32), #c_to_a(500c) \n ('x_a_500c' , np.float32), #A[x](500c) \n ('y_a_500c' , np.float32), #A[y](500c) \n ('z_a_500c' , np.float32), #A[z](500c)\n ('T_U' , np.float32), #T/|U|\n ('Mpseudo_Behroozi', np.float32), #M_pe_Behroozi\n ('Mpseudo_Diemer' , np.float32), #M_pe_Diemer\n ('rhalf_mass' , np.float32) #Halfmass_Radius \n ] \n return dt","def test_ModelRnaCodonSequence(self):\n r = ArrayRnaCodonSequence(\"UUUCGU\")\n self.assertEqual(str(r), \"UUUCGU\")\n self.assertEqual(r._data, array([0, 28]))\n self.assertEqual(str(r.to_rna()), \"UUUCGU\")\n self.assertEqual(str(r.to_dna()), \"TTTCGT\")","def __str__(self):\n return self.idLancamentosReceber","def presenetCar():","def RA(self):\n return self.meta[\"header\"][\"OBJRA\"] * u.deg","def pyramida(zakladna, orientacia, centrovanie):\n nova_pyramida = []\n if orientacia not in [\"normalna\", 'obratena']:\n print(\"Pyramida moze byt iba [normalna] alebo [obratena]\")\n return False\n\n if centrovanie != \"center\" and centrovanie != \"vlavo\":\n print(\"Centrovanie pyramidy moze byt iba [center] alebo [vlavo]\")\n return False\n\n if centrovanie == \"center\":\n if orientacia == \"normalna\":\n\n cislo_riadka = -1\n for i in range(1, zakladna + 1, 2): #pocet hviezdiciek rastie po 2\n #print(f\"{'*' * i:^{zakladna}}\")\n cislo_riadka +=1\n riadok = []\n for j in range(cislo_riadka,zakladna//2): #vyska pyramidy = polovica zakladne\n riadok.append(\" \") #kolky riadok, tolko medzier vlavo\n for j in range(0, i):\n riadok.append(\"*\")\n for j in range(cislo_riadka,zakladna//2): # aj v pravo\n riadok.append(\" \")\n nova_pyramida.append(riadok)\n else:\n cislo_riadka = -1\n for i in range(zakladna, 0, -2): #pocet hviezdiciek\n #print(f\"{'*' * i:^{zakladna}}\")\n cislo_riadka +=1\n riadok = []\n for j in range(0,cislo_riadka):\n riadok.append(\" \")\n for j in range(0,i):\n riadok.append(\"*\")\n for j in range(0,cislo_riadka):\n riadok.append(\" \")\n nova_pyramida.append(riadok)\n else:\n if orientacia == \"normalna\":\n for i in range(zakladna):\n #print(f\"{'*' * (i + 1)}\")\n riadok = []\n for j in range(0,i):\n riadok.append(\"*\")\n nova_pyramida.append(riadok)\n else:\n for i in range(zakladna):\n riadok = []\n #print(f\"{'*' * (zakladna - i)}\")\n for j in range(zakladna, i, -1):\n riadok.append(\"*\")\n nova_pyramida.append(riadok)\n return nova_pyramida","def __str__(self):\n \n s = \"(R: \" + str(self.r) + \", G: \" + str(self.g) + \", B: \" + str(self.b) + \")\"\n return s","def __init__(self, rouge_types):\n\n self.rouge_types = rouge_types","def make_m2_crv(TSUGITE_list, SHIGUCHI_list):\n \"\"\"\n 1 Get information from TSUGITE_list and SHIGUCHI_list.\n \"\"\"\n # TSUGITE\n # Left----------------------------------------------------------------------\n # material2\n m2_left_list = TSUGITE_list[0]\n m2_left_upper = m2_left_list[0]\n m2_left_middle = m2_left_list[1]\n m2_left_lower = m2_left_list[2]\n\n # SHIGUCHI\n m2_KUMIKI_points1 = SHIGUCHI_list[4]\n m2_KUMIKI_points2 = SHIGUCHI_list[5]\n\n m2_KUMIKI_points1.reverse()\n\n m2_left_upper.extend(m2_KUMIKI_points1)\n m2_left_upper.append(m2_left_upper[0])\n m2_left_upper_crv = rs.AddPolyline(m2_left_upper)\n\n m2_left_middle.extend(m2_KUMIKI_points1)\n m2_left_middle.append(m2_left_middle[0])\n m2_left_middle_crv = rs.AddPolyline(m2_left_middle)\n\n m2_left_lower.extend(m2_KUMIKI_points1)\n m2_left_lower.append(m2_left_lower[0])\n m2_left_lower_crv = rs.AddPolyline(m2_left_lower)\n\n m2_left_crvs = [m2_left_upper_crv, m2_left_middle_crv, m2_left_lower_crv]\n\n # Right---------------------------------------------------------------------\n m2_right_list = TSUGITE_list[1]\n m2_right_upper = m2_right_list[0]\n m2_right_middle = m2_right_list[1]\n m2_right_lower = m2_right_list[2]\n\n # SHIGUCHI\n m2_KUMIKI_points1 = SHIGUCHI_list[0]\n m2_KUMIKI_points2 = SHIGUCHI_list[1]\n\n # Extend\n # material2\n m2_right_upper.reverse()\n m2_right_middle.reverse()\n m2_right_lower.reverse()\n\n # m2_KUMIKI_points1.reverse()\n\n m2_right_upper.extend(m2_KUMIKI_points1)\n m2_right_upper.append(m2_right_upper[0])\n m2_right_upper_crv = rs.AddPolyline(m2_right_upper)\n\n m2_right_middle.extend(m2_KUMIKI_points1)\n m2_right_middle.append(m2_right_middle[0])\n m2_right_middle_crv = rs.AddPolyline(m2_right_middle)\n\n m2_right_lower.extend(m2_KUMIKI_points1)\n m2_right_lower.append(m2_right_lower[0])\n m2_right_lower_crv = rs.AddPolyline(m2_right_lower)\n\n m2_right_crvs = [m2_right_upper_crv, m2_right_middle_crv, m2_right_lower_crv]\n\n return m2_left_crvs, m2_right_crvs","def callback_rocm_bitcode_path(rocdl_dir=None):\n # seems link order matters.\n\n if rocdl_dir is None:\n if exists(\"/opt/rocm/amdgcn/bitcode/\"):\n rocdl_dir = \"/opt/rocm/amdgcn/bitcode/\" # starting with rocm 3.9\n else:\n rocdl_dir = \"/opt/rocm/lib/\" # until rocm 3.8\n\n bitcode_names = [\n \"oclc_daz_opt_on\",\n \"ocml\",\n \"irif\", # this does not exist in rocm 3.9, drop eventually\n \"oclc_correctly_rounded_sqrt_off\",\n \"oclc_correctly_rounded_sqrt_on\",\n \"oclc_daz_opt_off\",\n \"oclc_finite_only_off\",\n \"oclc_finite_only_on\",\n # todo (t-vi): an alternative might be to scan for the\n \"oclc_isa_version_803\",\n \"oclc_isa_version_900\", # isa version files (if the linker throws out\n \"oclc_isa_version_906\", # the unneeded ones or we filter for the arch we need)\n \"oclc_isa_version_1030\",\n \"oclc_unsafe_math_off\",\n \"oclc_unsafe_math_on\",\n \"oclc_wavefrontsize64_on\",\n \"oclc_abi_version_500\",\n ]\n\n bitcode_files = []\n for n in bitcode_names:\n p = join(rocdl_dir, n + \".bc\") # rocm >= 3.9\n if not exists(p): # rocm <= 3.8\n p = join(rocdl_dir, n + \".amdgcn.bc\")\n if exists(p):\n bitcode_files.append(p)\n elif \"isa_version\" not in n and n not in {\"irif\"}:\n raise RuntimeError(\"could not find bitcode \" + n)\n\n return tvm.runtime.convert(bitcode_files)","def gm_robe(self):\n self.name = \"Grand Mage's Robe\"\n self.rarity = \"Uncommon\"\n self.pdef_value = 8\n self.mdef_value = 30\n self.increase_crit = 0\n self.desc = \"The robe of an accomplished mage, has many enchantments.\"","def test_visualize_rdkit(self):\n import rdkit\n\n mol = Molecule().from_smiles(\"CCO\")\n\n assert isinstance(mol.visualize(backend=\"rdkit\"), rdkit.Chem.rdchem.Mol)","def railway(osm_path): \n return (retrieve(osm_path,'lines',['railway'],**{'railway':[\"='rail' or \",\"='tram' or \",\"='subway' or \",\"='construction' or \",\"='funicular' or \",\"='light_rail' or \",\"='narrow_gauge'\"]})).rename(columns={'railway': 'asset'})","def get_rechnung(rechnungsnr):\n\n if str(rechnungsnr).startswith('RG'):\n rechnungsnr = str(rechnungsnr)[2:]\n kopf = get_connection().query(['AFK00'],\n condition=\"FKRGNR = %s\" % sql_escape(rechnungsnr))\n if len(kopf) < 1:\n raise RuntimeError('inkonsistente Kopfdaten in AFK00: %r' % kopf)\n if len(kopf) > 1:\n print 'warning: inkonsistente Kopfdaten in AFK00: FKRGNR = %s' % rechnungsnr\n print kopf\n kopf = kopf[0]\n # TODO: der code schient nciht zu klappen, wenn gar keine Auftragstexte vorhanden sind.\n postmp = get_connection().query(['AFU00', 'AAT00'],\n condition=\"FURGNR=%s AND FUAUFN=ATAUFN AND FUAUPO=ATAUPO AND ATTART=8\" % sql_escape(rechnungsnr))\n\n # wenn eine Rechnungsposition mehr als einen Rechnungstext hat, ist sie jetzt mehrfach in positionen\n # dedupen und spezial felder auseinanderklamuesern\n positionen = {}\n texte = {}\n for line in postmp:\n positionen.setdefault(line['auftragsposition'], {}).update(line)\n text = line['text'].strip()\n if not text.startswith('#:'):\n texte.setdefault(line['auftragsposition'], []).append(line['text'])\n if text.startswith('#:guid:'):\n positionen[line['auftragsposition']]['guid'] = text[7:]\n for posnr, textlines in texte.items():\n positionen[posnr]['text'] = ' '.join(textlines)\n\n return kopf, positionen.values()","def birch(args):\n p = OptionParser(birch.__doc__)\n opts, args, iopts = p.set_image_options(args, figsize=\"8x6\")\n\n if len(args) != 2:\n sys.exit(not p.print_help())\n\n seqids, layout = args\n fig = plt.figure(1, (iopts.w, iopts.h))\n root = fig.add_axes([0, 0, 1, 1])\n\n K = Karyotype(fig, root, seqids, layout)\n L = K.layout\n\n xs = 0.79\n dt = dict(rectangle=False, circle=False)\n # Embed a phylogenetic tree to the right\n coords = {}\n coords[\"Amborella\"] = (xs, L[0].y)\n coords[\"Vitis\"] = (xs, L[1].y)\n coords[\"Prunus\"] = (xs, L[2].y)\n coords[\"Betula\"] = (xs, L[3].y)\n coords[\"Populus\"] = (xs, L[4].y)\n coords[\"Arabidopsis\"] = (xs, L[5].y)\n coords[\"fabids\"] = join_nodes(root, coords, \"Prunus\", \"Betula\", xs, **dt)\n coords[\"malvids\"] = join_nodes(root, coords, \"Populus\", \"Arabidopsis\", xs, **dt)\n coords[\"rosids\"] = join_nodes(root, coords, \"fabids\", \"malvids\", xs, **dt)\n coords[\"eudicots\"] = join_nodes(root, coords, \"rosids\", \"Vitis\", xs, **dt)\n coords[\"angiosperm\"] = join_nodes(root, coords, \"eudicots\", \"Amborella\", xs, **dt)\n\n # Show branch length\n branch_length(root, coords[\"Amborella\"], coords[\"angiosperm\"], \">160.0\")\n branch_length(root, coords[\"eudicots\"], coords[\"angiosperm\"], \">78.2\", va=\"top\")\n branch_length(root, coords[\"Vitis\"], coords[\"eudicots\"], \"138.5\")\n branch_length(root, coords[\"rosids\"], coords[\"eudicots\"], \"19.8\", va=\"top\")\n branch_length(\n root, coords[\"Prunus\"], coords[\"fabids\"], \"104.2\", ha=\"right\", va=\"top\"\n )\n branch_length(root, coords[\"Arabidopsis\"], coords[\"malvids\"], \"110.2\", va=\"top\")\n branch_length(\n root, coords[\"fabids\"], coords[\"rosids\"], \"19.8\", ha=\"right\", va=\"top\"\n )\n branch_length(root, coords[\"malvids\"], coords[\"rosids\"], \"8.5\", va=\"top\")\n\n root.set_xlim(0, 1)\n root.set_ylim(0, 1)\n root.set_axis_off()\n\n pf = \"birch\"\n image_name = pf + \".\" + iopts.format\n savefig(image_name, dpi=iopts.dpi, iopts=iopts)","def updateRoboPos(self,deltaL,deltaR,KompassCourse=None):\r\n #RoboSchwerpunkt bis Rad cm\r\n Radstand= 30.2\r\n countsRadGross= 288\r\n\r\n #Werte Uebernehmen: Counts in (cm) umrechnen\r\n deltaL=deltaL*((5.5*pi)/countsRadGross) #(Radumfang)/counts\r\n deltaR=deltaR*((5.5*pi)/countsRadGross) #(Radumfang)/counts\r\n WinkelDiff=degrees((deltaR-deltaL)/Radstand) #Raddist/Radstandbreite\r\n \r\n self.global_kurs=self.global_kurs+WinkelDiff #Global Kurs anhand Weg berechnen\r\n if self.global_kurs>360:\r\n self.global_kurs=self.global_kurs-360\r\n if self.global_kurs<0:\r\n self.global_kurs=360-abs(self.global_kurs) \r\n global_kurs_radiant=radians(self.global_kurs)\r\n #global_kurs_radiant=0\r\n #self.global_kurs=KompassCourse \r\n\r\n if deltaL != deltaR:\r\n da=(deltaR-deltaL)/Radstand #Drehwinkel in [rad]\r\n ds=(deltaL+deltaR)/2 #Mittler Strecke von L und R\r\n\r\n #delta X und Y berechnen nach einer Kurve Dx->Waagerecht Dy->senkrecht\r\n dx=(ds/da)*(cos((pi/2)+global_kurs_radiant-da)+cos(global_kurs_radiant-(pi/2)))\r\n dy=(ds/da)*(sin((pi/2)+global_kurs_radiant-da)+sin(global_kurs_radiant-(pi/2)))\r\n \r\n #Position des Robo auf Karte updaten\r\n self.drehmatrix(dx,dy)\r\n else: \r\n dx=deltaR*cos(global_kurs_radiant)\r\n dy=deltaL*sin(global_kurs_radiant)\r\n\r\n #Position des Robo auf Karte updaten\r\n self.drehmatrix(dx,dy)","def leerIRsiguelineas() -> int:\n pass","def parseRel(relfile):\n\trelf = open(relfile, \"r\")\n\trelfline = relf.readlines()\n\trelf.close()\n\t\n\t# First line is GRB\n\tgrb = relfline[0].replace(\"\\n\",\"\").split(\" \")\n\tGRBDict = {}\n\tGRBDict[\"RA\"] = float(grb[0])\n\tGRBDict[\"DEC\"] = float(grb[0])\n\t\n\tStarArray = []\n\t# Other lines are magnitudes\n\tfor i in relfline[1:]:\n\t\t starline = i.replace(\"\\n\",\"\").split(\" \")\n\t\t StarDict = {}\n\t\t StarDict[\"RA\"] = float(starline[0])\n\t\t StarDict[\"DEC\"] = float(starline[1])\n\t\t StarDict[\"MAG_ABSOLUTE\"] = float(starline[2])\n\t\t StarDict[\"MAG_ABSOLUTE_ERR\"] = float(starline[3])\n\t\t \n\t\t StarArray.append(StarDict)\n\t\t \n\treturn GRBDict, StarArray","def localizeLP(img):\n\t# preprocess\n\tgray_img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\n\t# using cascade classifier to detect license plate\n\t# the trained classifier is not good, retrain to get better results.\n\t# pre-trained classifier at: https://github.com/openalpr/openalpr/tree/master/runtime_data/region\n\tcascade = cv2.CascadeClassifier(\"localization/cascade_model.xml\")\n\trects = cascade.detectMultiScale(gray_img, scaleFactor=1.1, minNeighbors=3, minSize=(30, 30),flags=cv2.CASCADE_SCALE_IMAGE)\n\tif len(rects)==0:\n\t\treturn None,None\n\n\trect_list=[(rect[0],rect[1],rect[2],rect[3]) for rect in rects]\n\timg_height=gray_img.shape[0]\n\timg_width=gray_img.shape[1]\n\tmin_height, max_height, min_width, max_width = (0.1*img_height, 0.7*img_height, 0.1*img_width, 0.7*img_width)\n\thorizontal_min, horizontal_max = (0.1*img_width, 0.9*img_width)\n\tfor obj_rect in rect_list:\n\t\tmin_col, min_row, w, h=obj_rect\n\t\tmax_col = min_col+w\n\t\tmax_row=min_row+h\n\t\tif h >= min_height and h <= max_height and w >= min_width and w <= max_width and min_col>horizontal_min and max_col<horizontal_max:\n\t\t\tplate=gray_img[min_row:max_row,min_col:max_col]\n\t\t\treturn plate,(min_row,min_col,max_row,max_col)","def grass_drass():","def __init__(self, \n xml_path=cfg.PERSON_REID_XML,\n bin_path=cfg.PERSON_REID_BIN):\n self.__net = cv.dnn.readNet(xml_path, bin_path)\n self.__net.setPreferableTarget(cv.dnn.DNN_TARGET_MYRIAD)","def ramraddrrst(self):\n return 0"],"string":"[\n \"def rop():\\n return\",\n \"def lro(self) -> global___Snippet.Lro:\",\n \"def get_rouge(ref_path, pred_path):\\n print(\\\"###########cal rouge###############\\\")\\n source_lines = [line.strip() for line in codecs.open(ref_path, \\\"r\\\", \\\"utf-8\\\").readlines()]\\n pred_lines = [ pred.strip() for pred in codecs.open(pred_path, \\\"r\\\", \\\"utf-8\\\").readlines() ]\\n assert len(source_lines) == len(pred_lines)\\n rou = rouge.Rouge()\\n scores = rou.get_scores(pred_lines, source_lines)\\n ave_scores = rou.get_scores(pred_lines, source_lines, avg=True)\\n result = OrderedDict()\\n result[\\\"ave_scores\\\"] = ave_scores\\n result[\\\"detail_scores\\\"] = scores\\n print(ave_scores)\\n print(\\\"############end rouge#############\\\\n\\\")\\n return result\",\n \"def _regr_basic():\",\n \"def to_ir(self):\",\n \"def gt_roidb(self):\\n # cache_path: data/cache/Actions/\\n # self.name: rcnn_<>_<>\\n print \\\"cache_path:\\\", self.cache_path\\n\\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n # Get image_index and gt_roidb\\n # self._anno_filepath: data/Actions/${datatype}/anno_file.txt\\n self._image_index, gt_roidb = self._load_action_annotation(self._anno_filepath)\\n\\n print \\\"cache_file:\\\", cache_file\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print\\n print 'wrote gt roidb to {}'.format(cache_file)\\n\\n return gt_roidb\\n\\n\\n # ##################################################\\n # \\n # ##################################################\",\n \"def gt_roidb(self):\\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):# and False:\\n with open(cache_file, 'rb') as fid:\\n try:\\n roidb = pickle.load(fid)\\n except:\\n roidb = pickle.load(fid, encoding='bytes')\\n print('{} gt roidb loaded from {}'.format(self.name, cache_file))\\n return roidb\\n\\n gt_roidb = [self._load_pascal_annotation(index)\\n for index in self.image_index]\\n #with open(cache_file, 'wb') as fid:\\n # pickle.dump(gt_roidb, fid, pickle.HIGHEST_PROTOCOL)\\n #print('wrote gt roidb to {}'.format(cache_file))\\n\\n return gt_roidb\",\n \"def gt_roidb(self):\\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n num_image = len(self.image_index)\\n if cfg.MNC_MODE:\\n gt_roidb = [self._load_sbd_annotations(index) for index in xrange(num_image)]\\n else:\\n gt_roidb = [self._load_pascal_annotations(index) for index in xrange(num_image)]\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print 'wrote gt roidb to {}'.format(cache_file)\\n return gt_roidb\",\n \"def get_roidb(self):\\n # get all the images_ids in this dataset\\n img_ids = self._COCO.getImgIds()\\n # sort the ids, make each time the same order\\n img_ids.sort()\\n # load the 'image' of the COCO dataset\\n roidb = copy.deepcopy(self._COCO.loadImgs(img_ids))\\n for entry in roidb:\\n # predefine some attribute of each image\\n self._prep_roidb_entry(entry)\\n\\n # for cahce_dir\\n if not os.path.exists(self.cache_dir):\\n os.mkdir(self.cache_dir)\\n cache_file = os.path.join(self.cache_dir, self.annFile + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n self._read_roidb_from_cachefile(roidb, cache_file)\\n print('{} gt roidb loaded from {}'.format(self.annFile, cache_file))\\n else:\\n for entry in roidb:\\n self._add_roidb_from_annotations(entry)\\n with open(cache_file, 'wb') as f:\\n pickle.dump(roidb, f, pickle.HIGHEST_PROTOCOL)\\n print('wrote gt roidb to {}'.format(cache_file))\\n return roidb\",\n \"def gt_roidb(self):\\n cache_file = os.path.join(self.cfg.cache_path, self.cfg.name + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print('{} gt roidb loaded from {}'.format(self.cfg.name, cache_file))\\n return roidb\\n\\n # self.image_index = self._load_image_set_index()\\n gt_roidb = [self._load_pascal_annotation(index)\\n for index in self.image_index]\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(gt_roidb, fid, protocol=-1)\\n print('wrote gt roidb to {}'.format(cache_file))\\n\\n return gt_roidb\",\n \"def residue_ramachandran_type(residue) :\\n if residue_amino(residue)==\\\"GLY\\\" :\\n return rama_GLYCINE\\n elif residue_amino(residue)==\\\"PRO\\\" :\\n return rama_PROLINE\\n elif residue_amino(next_residue(residue))==\\\"PRO\\\" :\\n #exlcudes those that are Pro or Gly\\n return rama_PRE_PRO\\n else :\\n return rama_GENERAL\",\n \"def load_proposal_roidb(dataset_name, image_set_name, root_path, dataset_path, result_path=None,\\n proposal='rpn', append_gt=True, flip=False):\\n imdb = eval(dataset_name)(image_set_name, root_path, dataset_path, result_path)\\n\\n gt_roidb = imdb.gt_roidb()\\n roidb = eval('imdb.' + proposal + '_roidb')(gt_roidb, append_gt)\\n if flip:\\n roidb = imdb.append_flipped_images(roidb)\\n return roidb\",\n \"def load_proposal_roidb(dataset_name, image_set_name, root_path, dataset_path, result_path=None,\\n proposal='rpn', append_gt=True, flip=False,proposal_path='proposals', only_gt=False,\\n get_imdb=False, load_mask=False):\\n imdb = eval(dataset_name)(image_set_name, root_path, dataset_path, result_path,load_mask=load_mask)\\n\\n roidb = imdb.gt_roidb()\\n #roidb = roidb[:1000]\\n if not only_gt:\\n roidb = eval('imdb.' + proposal + '_roidb')(roidb, append_gt,proposal_path=proposal_path)\\n else:\\n # Make sure boxes are converted to float\\n for r in roidb:\\n r['boxes'] = r['boxes'].astype(np.float32)\\n if flip:\\n roidb = imdb.append_flipped_images(roidb)\\n\\n if get_imdb:\\n return roidb, imdb\\n\\n return roidb\",\n \"def findROICentres(smt_file): #{\\n rois = []\\n ary = None\\n state = 0\\n roi_centres = { \\n 'head_ct': None,\\n 'neck_cb': None,\\n 'shoulder_l': None,\\n 'shoulder_r': None,\\n 'elbow_l': None,\\n 'elbow_r': None,\\n 'pelvis_c': None,\\n 'wrist_l': None,\\n 'wrist_r': None,\\n 'hip_l': None,\\n 'hip_r': None,\\n 'knee_l': None,\\n 'knee_r': None,\\n 'ankle_l': None,\\n 'ankle_r': None,\\n 'toes_e': None}\\n\\n vrbMsg(1, 'findROICentres() smt_file = ' + smt_file)\\n # Read the smoothed Woolz object and create a NumPy array from it\\n err_num, smt_obj = readWoolzObj(smt_file)\\n if(not bool(err_num)): #{\\n\\t err_num, org, ary = wlzObjToNP(smt_obj)\\n #}\\n sz = np.shape(ary)\\n vrbMsg(5, 'findROICentres() object size = ' + str(sz))\\n # Work down the scan finding coordinates, ordering has dependency\\n # but this is checked in the individual functions\\n if((sz[0] >= img_size_min) and (sz[1] >= img_size_min)): #{\\n findProfileHeadCT(roi_centres, ary)\\n findProfileToes(roi_centres, ary)\\n #}\\n if(bool(roi_centres['toes_e']) and bool(roi_centres['head_ct'])): #{\\n findProfileShoulders(roi_centres, ary)\\n findProfilePelvis(roi_centres, ary)\\n findProfileHip(roi_centres, ary)\\n findProfileElbow(roi_centres, ary)\\n findProfileWrist(roi_centres, ary)\\n findProfileKnee(roi_centres, ary)\\n findProfileAnkle(roi_centres, ary)\\n rois = roi_centres\\n for cen in rois: #{\\n # numpy gives int64 which is not always handled (eg by json) so convert\\n pos = rois[cen]\\n if(not (pos is None)): #{\\n rois[cen] = [int(pos[0]), int(pos[1])]\\n #}\\n #}\\n #}\\n vrbMsg(1, 'findROICentres() rois = ' + str(rois))\\n return rois\",\n \"def gt_roidb(self):\\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n gt_roidb = [self._load_pascal_annotation(index)\\n for index in self.image_index]\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print 'wrote gt roidb to {}'.format(cache_file)\\n\\n return gt_roidb\",\n \"def gt_roidb(self):\\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n raw_annotations = self._load_annotations()\\n gt_roidb = self._format_raw_annotations(raw_annotations)\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print 'wrote gt roidb to {}'.format(cache_file)\\n\\n return gt_roidb\",\n \"def toRadString(self):\\r\\n pass\",\n \"def gt_roidb(self):\\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n gt_roidb = [self._load_nimble_annotation(index)\\n for index in self.image_index]\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print 'wrote gt roidb to {}'.format(cache_file)\\n\\n return gt_roidb\",\n \"def mezclar_bolsa(self):\",\n \"def risePen(gcode):\\r\\n gcode.append(\\\"M300 S46\\\")\\r\\n #gcode.append(\\\"G0 Z0.1000\\\")\\r\",\n \"def ROCKSTAR_ASCII():\\n dt= [\\n ('haloid' , np.int64), #id\\n ('n_particles' , np.int64), #num_p\\n ('mhalo' , np.float32), #mvir \\n ('mbasic' , np.float32), #mbound_vir \\n ('rvir' , np.float32), #rvir\\n ('vmax' , np.float32), #vmax\\n ('rvmax' , np.float32), #rvmax\\n ('vrms' , np.float32), #vrms \\n ('x_pos' , np.float32), #x\\n ('y_pos' , np.float32), #y\\n ('z_pos' , np.float32), #z\\n ('x_vel' , np.float32), #vx\\n ('y_vel' , np.float32), #vy\\n ('z_vel' , np.float32), #vz\\n ('x_ang' , np.float32), #Jx\\n ('y_ang' , np.float32), #Jy\\n ('z_ang' , np.float32), #Jz\\n ('engery' , np.float32), #E\\n ('spinParameter' , np.float32), #Spin\\n ('unc_pos' , np.float32), #PosUncertainty\\n ('unc_vel' , np.float32), #VelUncertainty\\n ('x_vel_bulk' , np.float32), #bulx_vx\\n ('y_vel_bulk' , np.float32), #bulx_vy\\n ('z_vel_bulk' , np.float32), #bulx_vz\\n ('unc_vel_bulk' , np.float32), #BulkVelUnc\\n ('n_core' , np.int64), #n_core\\n ('mhalo_200b' , np.float32), #m200b \\n ('mhalo_200c' , np.float32), #m200c\\n ('mhalo_500c' , np.float32), #m500c\\n ('mhalo_2500c' , np.float32), #m2500c\\n ('x_off' , np.float32), #Xoff\\n ('v_off' , np.float32), #Yoff\\n ('spin_Bullock' , np.float32), #spin_bullock\\n ('b_to_a' , np.float32), #b_to_a \\n ('c_to_a' , np.float32), #c_to_a\\n ('x_a' , np.float32), #A[x]\\n ('y_a' , np.float32), #A[y]\\n ('z_a' , np.float32), #A[z] \\n ('b_to_a_500c' , np.float32), #b_to_a(500c)\\n ('c_to_a_500c' , np.float32), #c_to_a(500c) \\n ('x_a_500c' , np.float32), #A[x](500c) \\n ('y_a_500c' , np.float32), #A[y](500c) \\n ('z_a_500c' , np.float32), #A[z](500c)\\n ('rscale' , np.float32), #rs \\n ('rscale_Klypin' , np.float32), #rs_Klypin\\n ('T_U' , np.float32), #T/|U|\\n ('Mpseudo_Behroozi', np.float32), #M_pe_Behroozi\\n ('Mpseudo_Diemer' , np.float32), #M_pe_Diemer\\n ('rhalf_mass' , np.float32), #Halfmass_Radius\\n ('idx' , np.int64), #internal debugging quantity\\n ('i_so' , np.int64), #internal debugging quantity\\n ('i_ph' , np.int64), #internal debugging quantity\\n ('n_particle_child', np.int64), #internal debugging quantity\\n ('mmetric' , np.float32) #internal debugging quantity \\n ] \\n return dt\",\n \"def constroi(self):\\n\\n #---------------------------------------------------------\\n # nnos = numero de nos\\n # ngl = numero de graus de liberdade\\n # ID entra como matriz de zeros e uns e sai com uma matriz\\n # contendo os indices dos graus de liberdade e\\n # zeros nas restriçoes\\n # con = contem a conectividade de cada elemento\\n # --------------------------------------------------------\\n nnos = len(self.ID)\\n ngl = 0.0\\n\\n for i in range(nnos):\\n for j in range(2):\\n n = self.ID[i][j]\\n if n >= 1:\\n self.ID[i][j]=0.0\\n else:\\n ngl = ngl + 1\\n self.ID[i][j] = ngl\\n\\n self.LD = np.zeros((self.nelm,4))\\n for i in range(self.nelm):\\n for j in range(2):\\n self.LD[i][j] = self.ID[self.conect[i][0]][j]\\n self.LD[i][j+2] = self.ID[self.conect[i][1]][j]\\n return np.transpose(self.LD)\",\n \"def rauzy_diagram(self, **args):\\n return LabelledRauzyDiagram(self, **args)\",\n \"def rauzy_diagram(self, **kargs):\\n return LabelledRauzyDiagram(self, **kargs)\",\n \"def parse_R(self, line: str):\\n\\n # R node1 node2 __value\\n # R name node1 node2 __value\\n name, node1, node2, value = self.parse_two_node_component(line,\\\"ohm\\\")\\n return IComponent.R(node1, node2, value, name)\",\n \"def make_rat():\\n rats_path = os.path.dirname(__file__)\\n models_path = os.path.join(rats_path, '..', 'models')\\n recon22_path = os.path.join(models_path, 'recon_2.2.xml')\\n rambo_path = os.path.join(rats_path, 'rambo.xml')\\n sbml = read_sbml(recon22_path)\\n\\n# v_sol, f_opt = optimize_cobra_model(sbml, 1000)\\n# print 'optimal growth rate:\\\\t%g\\\\n'%(f_opt)\\n\\n # map hgnc to rat\\n hgnc_map = {}\\n hgnc_map_file = os.path.join(rats_path, 'ensembl_hgnc_to_rat.txt')\\n with open(hgnc_map_file, 'rU') as csvfile:\\n reader = csv.reader(csvfile, delimiter='\\\\t')\\n for row in reader:\\n # ensembl = row[0].strip()\\n hgnc = row[1].strip()\\n hgnc = hgnc.replace('HGNC:','')\\n if len(row) > 2:\\n rat = row[2].strip()\\n else:\\n rat = ''\\n\\n if hgnc not in hgnc_map:\\n hgnc_map[hgnc] = ''\\n if not hgnc_map[hgnc]:\\n hgnc_map[hgnc] = rat\\n\\n model = sbml.getModel()\\n to_remove = []\\n for reaction in model.getListOfReactions().clone():\\n rID = reaction.getId()\\n ga_human = get_notes_field(rID, 'GENE_ASSOCIATION', sbml)\\n if ga_human:\\n ga_human = ga_human.replace('HGNC:', '') \\n ga_rat = ga_human\\n for hgnc in re.findall(r'\\\\b\\\\S+\\\\b', ga_human):\\n if (hgnc not in ['and', 'or', 'AND', 'OR']):\\n if hgnc in hgnc_map:\\n rat = hgnc_map[hgnc]\\n else:\\n print 'HGNC:%s\\\\tnot found'%hgnc\\n rat = ''\\n if not rat:\\n rat = 'False'\\n ga_rat = re.sub(r'\\\\b' + hgnc + r'\\\\b', rat, ga_rat)\\n ga_rat = to_dnf(ga_rat)\\n set_notes_field(rID, 'GENE_ASSOCIATION', ga_rat, sbml)\\n\\n# if not ga_rat:\\n# to_remove.append(rID)\\n# print '%s\\\\t[%s]\\\\n%s\\\\n'%(rID, reaction.getName(), ga_human)\\n# print '%s of %s reactions removed\\\\n'%(len(to_remove), model.getNumReactions())\\n\\n for rID in to_remove:\\n model.removeReaction(rID)\\n\\n model.setName('rambo')\\n model.setId('rambo')\\n model.setMetaId('meta_' + model.getId())\\n model.setAnnotation(model.getAnnotation())\\n\\n write_sbml(sbml, rambo_path)\\n\\n v_sol, f_opt = optimize_cobra_model(sbml, 1000)\\n print 'optimal growth rate:\\\\t%g\\\\n'%(f_opt)\",\n \"def ridgelen(id,ir,jr,fr):\\n\\n\\n\\tlr=ridgelenloop(id,ir,jr,fr)\\n\\n\\treturn lr\",\n \"def getRoverImage(self):\\n # Your code goes here, this code is just an example\\n return 'mario.ppm'\",\n \"def selective_search_roidb(self):\\n # cache_path: data/cache/Actions/\\n # self.name: rcnn_<>_<>\\n # cache_file: data/cache/Actions/rcnn_<datatype>_<imageset>_selective_search_roidb.pkl\\n cache_file = None\\n if cfg.LESSEN_DEBUG_TIME:\\n lessen_debug_str = cfg.LESSEN_DEBUG_STR\\n cache_file = os.path.join(self.cache_path, self.name + \\\"_\\\" + \\n lessen_debug_str + '_selective_search_roidb.pkl')\\n else:\\n cache_file = os.path.join(self.cache_path, self.name + '_selective_search_roidb.pkl')\\n\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} ss roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n if self._image_set != 'test':\\n gt_roidb = self.gt_roidb()\\n gt_roidb, ss_roidb = self._load_selective_search_roidb(gt_roidb)\\n roidb = action_datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)\\n else:\\n roidb = self._load_selective_search_roidb(None)\\n\\n\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print 'wrote ss roidb to {}'.format(cache_file)\\n\\n return roidb\",\n \"def obtenerRecorrido(nodo, dist):\\n\\n recorrido = []\\n #Obtenemos el recorrido siguiendo la referencia al padre desde el ultimo nodo.\\n while(nodo.getPadre() is not None):\\n recorrido.append(nodo.getId())\\n nodo = nodo.getPadre()\\n #El ciclo termina antes de agregar al padre, por lo que se agrega.\\n recorrido.append(nodo.getId())\\n camino = \\\"\\\"\\n #Se recorre el arreglo a la inversa para empezar con la primera ciudad\\n for i in range(len(recorrido)-1, 0, -1):\\n #Por cada ciudad se calcula la distancia con la siguiente\\n camino += \\\"[C\\\" + str(recorrido[i]) + \\\"] -> \\\" + str(dist[recorrido[i]][recorrido[i-1]]) + \\\" -> \\\"\\n #La ultima ciudad no tiene siguiente\\n camino += \\\"[C\\\" + str(recorrido[0]) + \\\"]\\\"\\n return camino\",\n \"def generar_red_neuronal (codigo, estadisticas=True):\\n \\n path = \\\"../data/entrenamiento/\\\" + str(codigo) + \\\"/\\\"\\n \\n f = open(path + \\\"data_neural_network_\\\" + str(codigo) + \\\".txt\\\")\\n cab = str(f.readline())[:-1]\\n cab = cab.replace(\\\"'\\\",\\\"\\\")\\n cab = cab.replace(\\\" \\\",\\\"\\\")\\n cabeceras = cab[1:-1].split(\\\",\\\")\\n l_etiquetas = str(f.readline())[:-1].split(\\\",\\\")\\n atributos = str(f.readline())[:-1].split(\\\",,\\\")\\n f.close()\\n\\n l_atributos = []\\n for atributo in atributos:\\n l_atributos.append(atributo.split(\\\",\\\"))\\n\\n etiquetas = set(l_etiquetas) \\n clases = sorted(list(etiquetas))\\n \\n l_atributos = np.array(l_atributos, \\\"float32\\\")\\n l_etiquetas = np.array(l_etiquetas, \\\"float32\\\")\\n \\n\\n #Separamos los datos que vamos a utilizar de entrenamiento y para realizar el test\\n #datos de pruebas (0.25) de los de entrenamiento (0.75)\\n X_train, X_test, y_train, y_test = train_test_split(l_atributos,l_etiquetas,test_size = 0.25,random_state = 0)\\n\\n #Creamos la red neuronal \\n red = MLPClassifier(max_iter=100000, hidden_layer_sizes=(50,25))\\n #Entrenamos la red neuronal\\n red.fit(X_train, y_train)\\n\\n #Predicion de los resultados del bloque test\\n y_pred = red.predict(X_test)\\n #Matriz de confusion\\n cm = confusion_matrix(y_test, y_pred)\\n #Reportes\\n report = classification_report(y_test, y_pred) \\n\\n\\n\\n if estadisticas == True:\\n f=open(path + \\\"export_neural_network_statistics_\\\" + str(codigo) + \\\".txt\\\",\\\"w\\\") \\n f.write(\\\"************************ CLASS *************************\\\\n\\\")\\n for i in range(len(clases)):\\n f.write(str(clases[i]) + \\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\\n\\\")\\n f.write(\\\"********************** FEATURES **********************\\\\n\\\")\\n for i in range(len(cabeceras[:-1])):\\n f.write(str(cabeceras[i]) + \\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\\n\\\")\\n f.write(\\\"************************ SCORE *************************\\\\n\\\")\\n f.write(\\\"With Test data: \\\" + str(red.score(X_test, y_test)) + \\\"\\\\n\\\")\\n f.write(\\\"With Training data: \\\" + str(red.score(X_train, y_train)) + \\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\\n\\\")\\n f.write(\\\"****************** CONFUSION MATRIX ********************\\\\n\\\")\\n if len(clases)==2:\\n f.write(\\\"\\\\t0\\\\t1\\\\n\\\")\\n f.write(\\\"---------------------\\\\n\\\")\\n f.write(\\\"0 |\\\\t\\\"+ str(cm[0][0]) +\\\"\\\\t\\\"+ str(cm[0][1]) +\\\"\\\\n\\\")\\n f.write(\\\"1 |\\\\t\\\"+ str(cm[1][0]) +\\\"\\\\t\\\"+ str(cm[1][1]) +\\\"\\\\n\\\")\\n if len(clases)==3:\\n f.write(\\\"\\\\t0\\\\t1\\\\t2\\\\n\\\")\\n f.write(\\\"--------------------------------\\\\n\\\")\\n f.write(\\\"0 |\\\\t\\\"+ str(cm[0][0]) +\\\"\\\\t\\\"+ str(cm[0][1]) +\\\"\\\\t\\\"+ str(cm[0][2]) +\\\"\\\\n\\\")\\n f.write(\\\"1 |\\\\t\\\"+ str(cm[1][0]) +\\\"\\\\t\\\"+ str(cm[1][1]) +\\\"\\\\t\\\"+ str(cm[1][2]) +\\\"\\\\n\\\")\\n f.write(\\\"2 |\\\\t\\\"+ str(cm[2][0]) +\\\"\\\\t\\\"+ str(cm[2][1]) +\\\"\\\\t\\\"+ str(cm[2][2]) +\\\"\\\\n\\\")\\n if len(clases)==4:\\n f.write(\\\"\\\\t0\\\\t1\\\\t2\\\\t3\\\\n\\\")\\n f.write(\\\"----------------------------------------------\\\\n\\\")\\n f.write(\\\"0 |\\\\t\\\"+ str(cm[0][0]) +\\\"\\\\t\\\"+ str(cm[0][1]) +\\\"\\\\t\\\"+ str(cm[0][2]) +\\\"\\\\t\\\"+ str(cm[0][3]) +\\\"\\\\n\\\")\\n f.write(\\\"1 |\\\\t\\\"+ str(cm[1][0]) +\\\"\\\\t\\\"+ str(cm[1][1]) +\\\"\\\\t\\\"+ str(cm[1][2]) +\\\"\\\\t\\\"+ str(cm[1][3]) +\\\"\\\\n\\\")\\n f.write(\\\"2 |\\\\t\\\"+ str(cm[2][0]) +\\\"\\\\t\\\"+ str(cm[2][1]) +\\\"\\\\t\\\"+ str(cm[2][2]) +\\\"\\\\t\\\"+ str(cm[2][3]) +\\\"\\\\n\\\")\\n f.write(\\\"3 |\\\\t\\\"+ str(cm[3][0]) +\\\"\\\\t\\\"+ str(cm[3][1]) +\\\"\\\\t\\\"+ str(cm[3][2]) +\\\"\\\\t\\\"+ str(cm[3][3]) +\\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\\n\\\")\\n f.write(\\\"************************ REPORT ***********************\\\\n\\\")\\n f.write(report)\\n f.close()\\n \\n print(str(codigo) + \\\": neural network created\\\") \\n return (red, red.score(X_test, y_test))\",\n \"def abstract(res):\\n o = r'\\\\begin{center}'\\n #o += r'\\\\begin{tikzpicture}[x={(-0.5cm,-0.5cm)}, y={(0.966cm,-0.2588cm)}, z={(0cm,1cm)}, scale=0.6, color={lightgray},opacity=.5]'\\n #o += r'\\\\tikzset{facestyle/.style={fill=lightgray,draw=black,very thin,line join=round}}'\\n o += r'\\\\begin{tikzpicture}' + '\\\\n'\\n o += r'\\\\draw[blue!40!white] (0,0) rectangle (6,4); \\\\fill[blue!10!white] (2.4,4) rectangle (3.6,4.15);' + '\\\\n'\\n for i in range(res[7]):\\n x,y = random.randrange(2,538)/100.0,random.randrange(2,300)/100.0\\n o += r'\\\\filldraw[fill=green!30!white,draw=white] (%s,%s) rectangle (%s,%s);'%(x,y,(x+0.58),(y+0.38)) + '\\\\n'\\n o += r'\\\\filldraw[white] (%s,%s) -- (%s,%s);'%((x+0.29),(y+0.19),(x+0.58),(y+0.38)) + '\\\\n'\\n o += r'\\\\filldraw[white] (%s,%s) -- (%s,%s);'%(x,(y+0.38),(x+0.29),(y+0.19)) + '\\\\n'\\n o += r'\\\\end{tikzpicture}\\\\end{center}' + '\\\\n'\\n\\n o += r'\\\\begin{tabular}{|l|l|}' + '\\\\n' + r'\\\\hline' + '\\\\n'\\n o += r'Election name& \\\\texttt{\\\"%s\\\"}\\\\\\\\'%res[1]\\n o += r'Box number& \\\\texttt{%s}\\\\\\\\'%res[2]\\n o += r'State& \\\\texttt{%s}\\\\\\\\'%('closed' if res[5] == cloSt else ('vote' if res[5] == votSt else 'register'))\\n o += r'Registration end& \\\\textit{%s}\\\\\\\\'%res[3]\\n o += r'Vote closing& \\\\textit{%s}\\\\\\\\'%res[4]\\n o += r'Casted/registered& $%s/%s$\\\\\\\\'%(res[7],res[6]) +'\\\\n'\\n o += r'\\\\hline\\\\end{tabular}' + '\\\\n'\\n o += r'\\\\quad' + '\\\\n'\\n o += r'\\\\begin{tabular}{|l|l|}\\\\hline'\\n l = res[8].items()\\n l.sort(key = operator.itemgetter(1),reverse=True)\\n n = 0\\n for x in l:\\n o += r'%s & %s\\\\\\\\'%(r'\\\\textit{%s}'%x[0] if x[0] == 'White Ballot' else r'\\\\texttt{%s}'%x[0],x[1]) \\n if n == 0:\\n o += r'\\\\hline' + '\\\\n'\\n n += 1\\n o += r'\\\\hline\\\\end{tabular}' + '\\\\n'\\n\\n\\n #o += r'\\\\item The designer\\\\textquoteright s digital signature of this document (the source file \\\\texttt{oeu.py}) is: \\\\tiny $$\\\\verb!%s!$$ \\\\normalsize'%rsa(IKey).sign(open(__file__).read()) + '\\\\n'\\n\\n return r'\\\\begin{abstract}' + abstract.__doc__ + r'\\\\end{abstract}' + o\",\n \"def rond(self):\\n return self._rond.get_waarde()\",\n \"def genotype(rsid):\\n if rsid[0] == 'I' or rsid[0] == 'i':\\n return { 'error': 'Cannot find indicators, must use rs #s'}\\n soup = BeautifulSoup(urllib.urlopen('http://snpedia.com/index.php/Special:Browse/' + rsid).read())\\n trows = soup('table')[1].find_all('tr')\\n if len(trows) < 2:\\n return { 'error': 'That rsid does not have any data/does not exist.' }\\n locations = getLocations(soup)\\n genotypeData = getData(locations, soup)\\n genotypeData['rsid'] = rsid\\n return genotypeData\",\n \"def mainRoads(osm_path): \\n return retrieve(osm_path,'lines',['highway','oneway','lanes','maxspeed'],**{'highway':[\\\"='primary' or \\\",\\\"='trunk' or \\\",\\\"='motorway' or \\\",\\\"='motorway_link' or \\\",\\\"='trunk_link' or \\\",\\\"='primary_link' or \\\", \\\"='secondary' or \\\",\\\"='tertiary' or \\\",\\\"='tertiary_link'\\\"]})\",\n \"def buildRomaniagraph(Graph):\\n \\n g=Graph()\\n for name in ('Oradea','Zerind','Arad','Timisoara', 'Lugoj','Mehadia', \\n 'Dobreta','Sibiu','Fagaras','Rimnicu Vilcea','Pitesti','Craiova',\\n 'Bucharest','Giurgiu','Urziceni','Hirsova','Eforie','Vaslui',\\n 'Iasi','Nearnt'):\\n g.addNode(Node(name))\\n \\n \\n g.addEdge(Edge(g.getNode('Oradea'),g.getNode('Zerind')))\\n g.addEdge(Edge(g.getNode('Oradea'),g.getNode('Sibiu')))\\n g.addEdge(Edge(g.getNode('Zerind'),g.getNode('Arad')))\\n g.addEdge(Edge(g.getNode('Arad'),g.getNode('Timisoara')))\\n g.addEdge(Edge(g.getNode('Lugoj'),g.getNode('Timisoara')))\\n g.addEdge(Edge(g.getNode('Lugoj'),g.getNode('Mehadia')))\\n g.addEdge(Edge(g.getNode('Mehadia'),g.getNode('Dobreta')))\\n g.addEdge(Edge(g.getNode('Dobreta'),g.getNode('Craiova')))\\n g.addEdge(Edge(g.getNode('Craiova'),g.getNode('Pitesti')))\\n g.addEdge(Edge(g.getNode('Craiova'),g.getNode('Rimnicu Vilcea')))\\n g.addEdge(Edge(g.getNode('Rimnicu Vilcea'),g.getNode('Sibiu')))\\n g.addEdge(Edge(g.getNode('Sibiu'),g.getNode('Fagaras')))\\n g.addEdge(Edge(g.getNode('Pitesti'),g.getNode('Bucharest')))\\n g.addEdge(Edge(g.getNode('Bucharest'),g.getNode('Giurgiu')))\\n g.addEdge(Edge(g.getNode('Bucharest'),g.getNode('Urziceni')))\\n g.addEdge(Edge(g.getNode('Arad'),g.getNode('Sibiu')))\\n g.addEdge(Edge(g.getNode('Rimnicu Vilcea'),g.getNode('Pitesti')))\\n g.addEdge(Edge(g.getNode('Bucharest'),g.getNode('Fagaras')))\\n g.addEdge(Edge(g.getNode('Vaslui'),g.getNode('Urziceni')))\\n g.addEdge(Edge(g.getNode('Hirsova'),g.getNode('Urziceni')))\\n g.addEdge(Edge(g.getNode('Hirsova'),g.getNode('Eforie')))\\n g.addEdge(Edge(g.getNode('Vaslui'),g.getNode('Iasi')))\\n g.addEdge(Edge(g.getNode('Iasi'),g.getNode('Nearnt')))\\n \\n return g\",\n \"def test_RUMI():\\r\\n\\r\\n start = 11051\\r\\n end = 11902\\r\\n read_poems(start, end)\",\n \"def gt_roidb(self):\\n \\\"\\\"\\\"\\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n \\\"\\\"\\\"\\n gt_roidb = [self._load_kitti_annotation(index)\\n for index in self.image_index]\\n \\\"\\\"\\\"\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print 'wrote gt roidb to {}'.format(cache_file)\\n \\\"\\\"\\\"\\n\\n return gt_roidb\",\n \"async def get_roi(self):\",\n \"def _repr_(self):\\n return \\\"Lie algebra %s over %s\\\" % (self._classification,\\n self.base_ring())\",\n \"def test_visualize_rdkit(self):\\n import IPython\\n\\n mol = Molecule().from_smiles(\\\"CCO\\\")\\n\\n assert isinstance(mol.visualize(backend=\\\"rdkit\\\"), IPython.core.display.SVG)\",\n \"def get_training_roidb(self,imdb):\\n if self.config.TRAIN.USE_FLIPPED:\\n print('Appending horizontally-flipped training examples...')\\n imdb.append_flipped_images()\\n print('done')\\n \\n print('Preparing training data...')\\n if self.config.TRAIN.HAS_RPN:\\n self.prepare_roidb(imdb)\\n else:\\n self.prepare_roidb(imdb)\\n print('done')\\n \\n return imdb.roidb\",\n \"def validateRaxmlModels(self, input): \\n filename=input+\\\".mg.modelFromMG.txt\\\"\\n arq = open(filename, \\\"r\\\")\\n output = \\\"\\\"\\n conteudo = arq.readlines()\\n seqcont = 0\\n output = \\\"True\\\"\\n modelogerado = \\\"\\\"\\n listamodelos = ['DAYHOFF', 'DCMUT', 'JTT', 'MTREV', 'WAG', 'RTREV', 'CPREV',\\n 'VT', 'BLOSUM62', 'MTMAM', 'MTART', 'MTZOA', 'LG', 'PMB',\\n 'HIVB', 'HIVW', 'JTTDCMUT', 'FLU','GTR']\\n\\n if len(conteudo) == 0 or len(conteudo) > 1:\\n output = \\\"False\\\"\\n else:\\n modelogerado = conteudo[0].strip()\\n if modelogerado.upper() not in listamodelos:\\n print \\\"Teste\\\"\\n output = \\\"False\\\" \\n \\n return {\\\"MG_MODEL\\\":modelogerado, \\\"MG_MODEL_VALID\\\":output}\",\n \"def pyradigms_from_adj(main_data):\\n # names are not in files. Hard code here instead\\n roi_names = [\\n 'L_ant_med_OFC_1', 'L_post_med_OFC_1', 'L_ant_VMPFC', 'L_post_med_OFC_2', 'L_ant_med_OFC_2',\\n 'L_vent_ACC', 'L_subg_cingulate', 'L_rostr_ACC', 'R_ant_med_OFC_1', 'R_post_med_OFC_1', 'R_ant_VMPFC',\\n 'R_post_med_OFC_2','R_ant_med_OFC_2','R_vent_ACC', 'R_subg_cingulate', 'R_rostr_ACC', 'L_caudate',\\n 'L_NAC', 'L_putamen', 'R_caudate', 'R_NAC', 'R_putamen', 'VTA']\\n\\n # output of ROI_TempCor.R nested inside visit directories\\n prefix=\\\"vmpfc_striatal_vta_mean_gsr_pearson_adj_pearson.txt\\\"\\n\\n # each connectivity set has their own path to the adjacency matrix\\n fc_globs = {'bkgrd': f'/Volumes/Hera/Projects/mMR_PETDA/subjs/1*_2*/func/*{prefix}',\\n 'rest1': f'/Volumes/Zeus/preproc/petrest_rac1/MHRest_FM_ica/1*_2*/*{prefix}',\\n 'rest2': f'/Volumes/Zeus/preproc/petrest_rac2/MHRest_FM_ica/1*_2*/*{prefix}'}\\n\\n # 'Regr' b/c age is continuous.\\n # allow_nan_inf might be a mistake. easy for now (20201208)\\n FCds = {k: RegrDataset(allow_nan_inf=True) for k in fc_globs.keys()}\\n FCds['bkgrd'].description = \\\"Functional connectivity w/23 ROIs from task chunked background timeseries\\\"\\n FCds['rest1'].description = \\\"Functional connectivity w/23 ROIs from first rest timeseries\\\"\\n FCds['rest2'].description = \\\"Functional connectivity w/23 ROIs from second rest timeseries\\\"\\n\\n # 253 roi-roi pairs for each of background, rest1, and rest1\\n # use info stored in the super wide dataframe to get age and session id from each file\\n # to create each samplet that composes each (bkgrd,rest1,2) of the connectivity datasets\\n for k in fc_globs.keys():\\n roi = ROI_FC(fc_globs[k], roi_names)\\n main_data.all_adj_into(FCds[k], roi, f'data/conn_adj_{k}.csv')\\n \\n return FCds\",\n \"def get_rlp(self, rlp):\\n xyz = cm.sphere_to_cart(r=rlp[0], lam=rlp[1], phi=rlp[2])\\n return self.get_xyz(xyz=xyz)\",\n \"def gt_roidb(self):\\n cache_file = os.path.join(self.cache_path, self.name + '_gt_roidb.pkl')\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} gt roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n annotations_data = open(self.annotations_file, 'r')\\n #self.ann_json_data = json.load(annotations_data)\\n gt_roidb = [self._load_hover_annotation(line)\\n for line in annotations_data]\\n annotations_data.close()\\n# pdb.set_trace()\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(gt_roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print 'wrote gt roidb to {}'.format(cache_file)\\n\\n return gt_roidb\",\n \"def radrad(rxn_class):\\n return rxn_class[2]\",\n \"def selective_search_roidb(self):\\n cache_file = os.path.join(self.cache_path,\\n self.name + '_selective_search_roidb.pkl')\\n\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} ss roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n # if int(self._year) == 2007 or self._image_set != 'test':\\n gt_roidb = self.gt_roidb()\\n ss_roidb = self._load_selective_search_roidb(gt_roidb)\\n roidb = datasets.imdb.merge_roidbs(gt_roidb, ss_roidb)\\n # else:\\n # roidb = self._load_selective_search_roidb(None)\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print 'wrote ss roidb to {}'.format(cache_file)\\n\\n return roidb\",\n \"def load_gt_roidb(dataset_name, image_set_name, root_path, dataset_path, result_path=None,\\n flip=False):\\n imdb = eval(dataset_name)(image_set_name, root_path, dataset_path, result_path)\\n roidb = imdb.gt_roidb()\\n if flip:\\n roidb = imdb.append_flipped_images(roidb)\\n return roidb\",\n \"def load_gt_roidb(dataset_name, image_set_name, root_path, dataset_path, result_path=None,\\n flip=False):\\n imdb = eval(dataset_name)(image_set_name, root_path, dataset_path, result_path)\\n roidb = imdb.gt_roidb()\\n if flip:\\n roidb = imdb.append_flipped_images(roidb)\\n return roidb\",\n \"def get_rz(self):\\n return self.rz\",\n \"def llnr2cgid(self, llnr):\\n possible = self.phenotypes[self.phenotypes.LLnr == llnr].cgID.values\\n if len(possible) > 0:\\n return possible[0]\\n #fi\\n return None\",\n \"def __loadFromFile(self):\\n try:\\n f=open(self.__fileR, \\\"r\\\")\\n line =f.readline().strip()\\n rez=[]\\n while line!=\\\"\\\":\\n attrs=line.split(\\\",\\\")\\n rt=Rent(attrs[0], attrs[1], attrs[2], attrs[3])\\n rez.append(rt)\\n line=f.readline().strip()\\n f.close()\\n return rez\\n #the file cannot be reached\\n except IOError:\\n return None\",\n \"def annToRLE(self, ann):\\n t = self.imgs[ann['image_id']]\\n h, w = t['height'], t['width']\\n segm = ann['segmentation']\\n if type(segm) == list:\\n # polygon -- a single object might consist of multiple parts\\n # we merge all parts into one mask rle code\\n rles = maskUtils.frPyObjects(segm, h, w)\\n rle = maskUtils.merge(rles)\\n elif type(segm['counts']) == list:\\n # uncompressed RLE\\n rle = maskUtils.frPyObjects(segm, h, w)\\n else:\\n # rle\\n rle = ann['segmentation']\\n return rle\",\n \"def load_gt_roidb(dataset_name, image_set_name, root_path, dataset_path,\\n flip=False, verbose=False):\\n imdb = retinaface(image_set_name, root_path, dataset_path)\\n roidb = imdb.gt_roidb()\\n if verbose:\\n print('roidb size', len(roidb))\\n if flip:\\n roidb = imdb.append_flipped_images(roidb)\\n if verbose:\\n print('flipped roidb size', len(roidb))\\n return roidb\",\n \"def armlengte(self):\\n return self._armlengte.get_waarde()\",\n \"def armlengte(self):\\n return self._armlengte.get_waarde()\",\n \"def site2nrml(model, params_dict): \\n \\\"\\\"\\\"\\n # Some XML definitions\\n NAMESPACE = 'http://openquake.org/xmlns/nrml/0.4'\\n GML_NAMESPACE = 'http://www.opengis.net/gml'\\n SERIALIZE_NS_MAP = {None: NAMESPACE, 'gml': GML_NAMESPACE} \\n gml_ns = SERIALIZE_NS_MAP['gml']\\n \\\"\\\"\\\"\\n \\n # Head matter \\n root = etree.Element(_tag='nrml', nsmap={'gml': 'http://www.opengis.net/gml'})\\n root.set('xmlns', 'http://openquake.org/xmlns/nrml/0.4')\\n root.append(etree.Comment('%s' % '%s site model' %(model)))\\n \\n\\n # Define Site Model Name \\n sMod = etree.SubElement(root, \\\"siteModel\\\")\\n sMod.set('name', model + ' Site Model')\\n \\n # Define sub element\\n \\n for key in params_dict:\\n \\n site = etree.SubElement(sMod, \\\"site\\\")\\n site.set('lon', '%s' % key[0])\\n site.set('lat', '%s' % key[1])\\n site.set('vs30', '%s' % params_dict[key][0])\\n site.set('vs30Type', '%s' % 'inferred')\\n site.set('z1pt0', '%s' % '%3.3f' % float(params_dict[key][1]))\\n site.set('z2pt5', '%s' % '%3.3f' % float(params_dict[key][2]))\\n \\n #print(getMinMax(params_dict))\\n \\n # Form tree and write to xml\\n root_tree = etree.ElementTree(root)\\n outFile = open((out_directory + '/' + out_filename), 'wb')\\n root_tree.write(outFile, encoding=\\\"utf-8\\\", xml_declaration=True, pretty_print=True)\",\n \"def selective_search_roidb(self):\\n cache_file = os.path.join(self.cache_path,\\n self.name + '_proposal_roidb.pkl')\\n\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} ss roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n if self._image_set != 'test':\\n gt_roidb = self.gt_roidb()\\n ss_roidb = self._load_selective_search_roidb(gt_roidb)\\n roidb = imdb.merge_roidbs(gt_roidb, ss_roidb)\\n else:\\n roidb = self._load_selective_search_roidb(None)\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print 'wrote ss roidb to {}'.format(cache_file)\\n\\n return roidb\",\n \"def get_training_roidb(imdb):\\n if cfg.TRAIN.USE_FLIPPED:\\n print 'Appending horizontally-flipped training examples...'\\n imdb.append_flipped_images()\\n print 'done'\\n\\n print 'Preparing training data...'\\n rdl_roidb.prepare_roidb(imdb)\\n print 'done'\\n\\n return imdb.roidb\",\n \"def __local_rn(soup):\\n return __get_local_g1_news(soup)\",\n \"def __local_rn(soup):\\n return __get_local_g1_news(soup)\",\n \"def generate_ROI_file(FreeSurfer_ROI_file):\\n\\tfrom nipype.interfaces.freesurfer import MRIConvert\\n\\tmc = MRIConvert()\\n\\tmc.inputs.in_file = FreeSurfer_ROI_file\\n\\tmc.inputs.out_type = 'niigz'\\n\\tmc.run()\\n\\n\\timport nipype.interfaces.cmtk as cmtk\\n\\trg = cmtk.ROIGen()\\n\\trg.inputs.aparc_aseg_file = FreeSurfer_ROI_file.split('.')[0] + '_out.nii.gz'\\n\\trg.inputs.use_freesurfer_LUT = True\\n\\tout_file = rg.run()\\n\\n\\treturn out_file\",\n \"def rms_str(self):\\n if self.image_status == 'match':\\n return '< tolerance' # self.rms is None\\n elif self.image_status == 'diff':\\n return self.rms\\n else: # Missing baseline image\\n return 'None'\",\n \"def to_rna(self):\\n thymidine = 'T'\\n uracil = 'U'\\n return self.dna.replace(thymidine, uracil)\",\n \"def prepare_roidb(self):\\n # for pascal_voc dataset\\n roidb = self.gt_roidb()\\n # data argument\\n if self.cfg.if_flipped is True:\\n print('append flipped images to training')\\n roidb = self.append_flipped_images(roidb)\\n\\n sizes = [PIL.Image.open(self.image_path_at(i)).size\\n for i in range(self.num_images)]\\n\\n for i in range(len(self.image_index)):\\n roidb[i]['image'] = self.image_path_at(i)\\n roidb[i]['width'] = sizes[i][0]\\n roidb[i]['height'] = sizes[i][1]\\n # need gt_overlaps as a dense array for argmax\\n gt_overlaps = roidb[i]['gt_overlaps'].toarray()\\n # max overlap with gt over classes (columns)\\n max_overlaps = gt_overlaps.max(axis=1)\\n # gt class that had the max overlap\\n max_classes = gt_overlaps.argmax(axis=1)\\n roidb[i]['max_classes'] = max_classes\\n roidb[i]['max_overlaps'] = max_overlaps\\n # sanity checks\\n # max overlap of 0 => class should be zero (background)\\n zero_inds = np.where(max_overlaps == 0)[0]\\n assert all(max_classes[zero_inds] == 0)\\n # max overlap > 0 => class should not be zero (must be a fg class)\\n nonzero_inds = np.where(max_overlaps > 0)[0]\\n assert all(max_classes[nonzero_inds] != 0)\\n\\n self.roi_data = ROIGenerator(roidb, self.num_classes, self.cfg)\\n return self.roi_data\",\n \"def mamajek08_logRpHK_Ro_edge():\\n Ro_edge = 0.31935816876122064\\n return Ro_edge\",\n \"def write_gro(strucC,data_file):\\n #\\n latvec = strucC.getLatVec()\\n\\n gro_lines = \\\" com2gro \\\\n\\\"\\n gro_lines += \\\" %-2i \\\\n\\\" %( int(len(strucC.ptclC)) )\\n atom_indx = 0 \\n for pid, pt_i in strucC.ptclC:\\n atom_indx += 1\\n if( atom_indx > 10000): atom_indx = 1\\n r_i = pt_i.position\\n r_i_nm = [units.convert_angstroms_nm(r_i[0]) ,units.convert_angstroms_nm(r_i[1]) ,units.convert_angstroms_nm(r_i[2]) ]\\n gro_lines += \\\"%5d%-5s%5s%5d%8.3f%8.3f%8.3f\\\\n\\\" % (atom_indx,pt_i.tagsDict[\\\"resname\\\"][:5],pt_i.tagsDict[\\\"label\\\"][:5],atom_indx,r_i_nm[0],r_i_nm[1],r_i_nm[2] )\\n if( atom_indx > 99999 ):\\n atom_indx = 1\\n \\n gro_lines += \\\" %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f \\\\n\\\" % (units.convert_angstroms_nm(latvec[0][0]),units.convert_angstroms_nm(latvec[1][1]),units.convert_angstroms_nm(latvec[2][2]),units.convert_angstroms_nm(latvec[0][1]),units.convert_angstroms_nm(latvec[0][2]),units.convert_angstroms_nm(latvec[1][0]),units.convert_angstroms_nm(latvec[1][2]),units.convert_angstroms_nm(latvec[2][0]),units.convert_angstroms_nm(latvec[2][1])) \\n\\n F = open( data_file, 'w' )\\n F.write(gro_lines)\\n F.close()\",\n \"def write_gro(strucC,data_file):\\n #\\n latvec = strucC.getLatVec()\\n\\n gro_lines = \\\" com2gro \\\\n\\\"\\n gro_lines += \\\" %-2i \\\\n\\\" %( int(len(strucC.ptclC)) )\\n atom_indx = 0 \\n for pid, pt_i in strucC.ptclC:\\n atom_indx += 1\\n if( atom_indx > 10000): atom_indx = 1\\n r_i = pt_i.position\\n r_i_nm = [units.convert_angstroms_nm(r_i[0]) ,units.convert_angstroms_nm(r_i[1]) ,units.convert_angstroms_nm(r_i[2]) ]\\n gro_lines += \\\"%5d%-5s%5s%5d%8.3f%8.3f%8.3f\\\\n\\\" % (atom_indx,pt_i.tagsDict[\\\"resname\\\"][:5],pt_i.tagsDict[\\\"label\\\"][:5],atom_indx,r_i_nm[0],r_i_nm[1],r_i_nm[2] )\\n if( atom_indx > 99999 ):\\n atom_indx = 1\\n \\n gro_lines += \\\" %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f %8.5f \\\\n\\\" % (units.convert_angstroms_nm(latvec[0][0]),units.convert_angstroms_nm(latvec[1][1]),units.convert_angstroms_nm(latvec[2][2]),units.convert_angstroms_nm(latvec[0][1]),units.convert_angstroms_nm(latvec[0][2]),units.convert_angstroms_nm(latvec[1][0]),units.convert_angstroms_nm(latvec[1][2]),units.convert_angstroms_nm(latvec[2][0]),units.convert_angstroms_nm(latvec[2][1])) \\n\\n F = open( data_file, 'w' )\\n F.write(gro_lines)\\n F.close()\",\n \"def test_rocket():\\n ring = [(0,0), (10, 0), (15,5), (10,9), (1,7), (6,4), (0,0)]\\n conv = ToPointsAndSegments()\\n conv.add_polygon([ring])\\n skel = calc_skel(conv, output=True, pause=True)\\n print \\\"DONE\\\"\",\n \"def __repr__(self):\\n return f'ResidenciaModel(name={self.neighbourhood_group}, neighbourhood={self.room_type})'\",\n \"def model(self):\\r\\n\\t\\tif self.connect != None:\\r\\n\\t\\t\\tcommandMD = b'#10MD<CR>\\\\r'\\r\\n\\t\\t\\twrite = self.connect.write(commandMD) \\r\\n\\t\\t\\treadData = self.connect.readline()\\r\\n\\t\\t\\treturn (readData.decode('utf-8')[6:])\\r\\n\\t\\treturn('pyrometer is disconected')\",\n \"def selective_search_roidb(self):\\n cache_file = os.path.join(self.cache_path,\\n self.name + '_selective_search_roidb.pkl')\\n\\n if os.path.exists(cache_file):\\n with open(cache_file, 'rb') as fid:\\n roidb = cPickle.load(fid)\\n print '{} ss roidb loaded from {}'.format(self.name, cache_file)\\n return roidb\\n\\n if int(self._year) == 2007 or self._image_set != 'test':\\n gt_roidb = self.gt_roidb()\\n ss_roidb = self._load_selective_search_roidb(gt_roidb)\\n roidb = imdb.merge_roidbs(gt_roidb, ss_roidb)\\n else:\\n roidb = self._load_selective_search_roidb(None)\\n with open(cache_file, 'wb') as fid:\\n cPickle.dump(roidb, fid, cPickle.HIGHEST_PROTOCOL)\\n print 'wrote ss roidb to {}'.format(cache_file)\\n\\n return roidb\",\n \"def __str__(self):\\n if self.hocr is None:\\n return ''\\n body = self.hocr.find(\\\".//%sbody\\\"%(self.xmlns))\\n if body:\\n return self._get_element_text(body).encode('utf-8') # XML gives unicode\\n else:\\n return ''\",\n \"def code() -> str:\\n return \\\"\\\"\\\"\\n G91 G17\\n G0 Y10 X-10\\n G0 Y0 X-5\\n G0 Y5 X0\\n G0 Y0 X5\\n G0 Y0 X-5\\n G0 Y-5 X0\\n G3 Y-5 X5 J0 I5\\n G0 Y0 X5\\n G0 Y5 X0\\n G3 Y5 X-5 J0 I-5\\n G0 Y-5 X0\\n G0 Y-10 X10\\n G0 Y0 X-5\\n G0 Y-15 X-15\\n G0 Y0 X5\\n G0 Y5 X0\\n G0 Y0 X-5\\n G0 Y-5 X0\\n G0 Y5 X0\\n G2 Y5 X5 J0 I5\\n G0 Y0 X5\\n G0 Y-5 X0\\n G2 Y-5 X-5 J0 I-5\\n G0 Y5 X0\\n G0 Y10 X10\\n G0 Y0 X-30\\n G3 Y0 X-10 J0 I-5\\n G3 Y0 X10 J0 I5\\n\\n G0 Y0 X5\\n G3 Y5 X5 J5 I0\\n G3 Y10 X-10 J0 I-10\\n G3 Y-5 X-5 J-5 I0\\n G0 Y-5 X0\\n\\n G0 Y5 X0\\n G3 Y5 X-5 J0 I-5\\n G3 Y-10 X-10 J-10 I0\\n G3 Y-5 X5 J0 I5\\n G0 Y0 X5\\n\\n G0 Y0 X-5\\n G3 Y-5 X-5 J-5 I0\\n G3 Y-10 X10 J0 I10\\n G3 Y5 X5 J5 I0\\n G0 Y5 X0\\n\\n G0 Y-5 X0\\n G3 Y-5 X5 J0 I5\\n G3 Y10 X10 J10 I0\\n G3 Y5 X-5 J0 I-5\\n G0 Y0 X-5\\n \\\"\\\"\\\"\",\n \"def reckon(self):\",\n \"def get_kgml_obj(pathway_id):\\r\\n\\r\\n if pathway_id.startswith('path:'):\\r\\n pathway_id = pathway_id.replace('path:', '')\\r\\n resp = requests.get(''.join([Kegg.BASE_URL,\\r\\n 'get/',\\r\\n pathway_id,\\r\\n '/kgml']))\\r\\n if resp.status_code == 200:\\r\\n return kgml_read(resp.text)\\r\\n return None\",\n \"def test_get_robax_tostring_correct(self):\\n got_var, const_jtar = rapid_datatypes.get_rapid_data(self.controller, 'T_ROB1', 'MainModule', 'const_jtarget')\\n if not got_var:\\n print 'Couldn\\\\'t get variable. Test will not run.'\\n sys.exit()\\n robax = rapid_jointtarget.get_robax_tostring(const_jtar)\\n self.assertEqual(robax, 'RobAx: [Rax_1,Rax_2,Rax_3,Rax_4,Rax_5,Rax_6] = [0,0,0,10,0,0]')\",\n \"def ROCKSTAR_ASCII_list():\\n \\n dt= [\\n ('haloid' , np.int64), #ID\\n ('descIndex' , np.int64), #DescID\\n ('mhalo' , np.float32), #Mvir\\n ('vmax' , np.float32), #Vmax\\n ('vrms' , np.float32), #Vrms \\n ('rvir' , np.float32), #Rvir\\n ('rscale' , np.float32), #Rs\\n ('n_particles' , np.int64), #Np \\n ('x_pos' , np.float32), #x\\n ('y_pos' , np.float32), #y\\n ('z_pos' , np.float32), #z\\n ('x_vel' , np.float32), #vx\\n ('y_vel' , np.float32), #vy\\n ('z_vel' , np.float32), #vz\\n ('x_ang' , np.float32), #Jx\\n ('y_ang' , np.float32), #Jy\\n ('z_ang' , np.float32), #Jz\\n ('spinParameter' , np.float32), #Spin\\n ('rscale_Klypin' , np.float32), #rs_Klypin \\n ('mbasic' , np.float32), #Mvir_all\\n ('mhalo_200b' , np.float32), #m200b \\n ('mhalo_200c' , np.float32), #m200c\\n ('mhalo_500c' , np.float32), #m500c\\n ('mhalo_2500c' , np.float32), #m2500c\\n ('x_off' , np.float32), #Xoff\\n ('v_off' , np.float32), #Yoff\\n ('spin_Bullock' , np.float32), #spin_bullock\\n ('b_to_a' , np.float32), #b_to_a \\n ('c_to_a' , np.float32), #c_to_a\\n ('x_a' , np.float32), #A[x]\\n ('y_a' , np.float32), #A[y]\\n ('z_a' , np.float32), #A[z] \\n ('b_to_a_500c' , np.float32), #b_to_a(500c)\\n ('c_to_a_500c' , np.float32), #c_to_a(500c) \\n ('x_a_500c' , np.float32), #A[x](500c) \\n ('y_a_500c' , np.float32), #A[y](500c) \\n ('z_a_500c' , np.float32), #A[z](500c)\\n ('T_U' , np.float32), #T/|U|\\n ('Mpseudo_Behroozi', np.float32), #M_pe_Behroozi\\n ('Mpseudo_Diemer' , np.float32), #M_pe_Diemer\\n ('rhalf_mass' , np.float32) #Halfmass_Radius \\n ] \\n return dt\",\n \"def test_ModelRnaCodonSequence(self):\\n r = ArrayRnaCodonSequence(\\\"UUUCGU\\\")\\n self.assertEqual(str(r), \\\"UUUCGU\\\")\\n self.assertEqual(r._data, array([0, 28]))\\n self.assertEqual(str(r.to_rna()), \\\"UUUCGU\\\")\\n self.assertEqual(str(r.to_dna()), \\\"TTTCGT\\\")\",\n \"def __str__(self):\\n return self.idLancamentosReceber\",\n \"def presenetCar():\",\n \"def RA(self):\\n return self.meta[\\\"header\\\"][\\\"OBJRA\\\"] * u.deg\",\n \"def pyramida(zakladna, orientacia, centrovanie):\\n nova_pyramida = []\\n if orientacia not in [\\\"normalna\\\", 'obratena']:\\n print(\\\"Pyramida moze byt iba [normalna] alebo [obratena]\\\")\\n return False\\n\\n if centrovanie != \\\"center\\\" and centrovanie != \\\"vlavo\\\":\\n print(\\\"Centrovanie pyramidy moze byt iba [center] alebo [vlavo]\\\")\\n return False\\n\\n if centrovanie == \\\"center\\\":\\n if orientacia == \\\"normalna\\\":\\n\\n cislo_riadka = -1\\n for i in range(1, zakladna + 1, 2): #pocet hviezdiciek rastie po 2\\n #print(f\\\"{'*' * i:^{zakladna}}\\\")\\n cislo_riadka +=1\\n riadok = []\\n for j in range(cislo_riadka,zakladna//2): #vyska pyramidy = polovica zakladne\\n riadok.append(\\\" \\\") #kolky riadok, tolko medzier vlavo\\n for j in range(0, i):\\n riadok.append(\\\"*\\\")\\n for j in range(cislo_riadka,zakladna//2): # aj v pravo\\n riadok.append(\\\" \\\")\\n nova_pyramida.append(riadok)\\n else:\\n cislo_riadka = -1\\n for i in range(zakladna, 0, -2): #pocet hviezdiciek\\n #print(f\\\"{'*' * i:^{zakladna}}\\\")\\n cislo_riadka +=1\\n riadok = []\\n for j in range(0,cislo_riadka):\\n riadok.append(\\\" \\\")\\n for j in range(0,i):\\n riadok.append(\\\"*\\\")\\n for j in range(0,cislo_riadka):\\n riadok.append(\\\" \\\")\\n nova_pyramida.append(riadok)\\n else:\\n if orientacia == \\\"normalna\\\":\\n for i in range(zakladna):\\n #print(f\\\"{'*' * (i + 1)}\\\")\\n riadok = []\\n for j in range(0,i):\\n riadok.append(\\\"*\\\")\\n nova_pyramida.append(riadok)\\n else:\\n for i in range(zakladna):\\n riadok = []\\n #print(f\\\"{'*' * (zakladna - i)}\\\")\\n for j in range(zakladna, i, -1):\\n riadok.append(\\\"*\\\")\\n nova_pyramida.append(riadok)\\n return nova_pyramida\",\n \"def __str__(self):\\n \\n s = \\\"(R: \\\" + str(self.r) + \\\", G: \\\" + str(self.g) + \\\", B: \\\" + str(self.b) + \\\")\\\"\\n return s\",\n \"def __init__(self, rouge_types):\\n\\n self.rouge_types = rouge_types\",\n \"def make_m2_crv(TSUGITE_list, SHIGUCHI_list):\\n \\\"\\\"\\\"\\n 1 Get information from TSUGITE_list and SHIGUCHI_list.\\n \\\"\\\"\\\"\\n # TSUGITE\\n # Left----------------------------------------------------------------------\\n # material2\\n m2_left_list = TSUGITE_list[0]\\n m2_left_upper = m2_left_list[0]\\n m2_left_middle = m2_left_list[1]\\n m2_left_lower = m2_left_list[2]\\n\\n # SHIGUCHI\\n m2_KUMIKI_points1 = SHIGUCHI_list[4]\\n m2_KUMIKI_points2 = SHIGUCHI_list[5]\\n\\n m2_KUMIKI_points1.reverse()\\n\\n m2_left_upper.extend(m2_KUMIKI_points1)\\n m2_left_upper.append(m2_left_upper[0])\\n m2_left_upper_crv = rs.AddPolyline(m2_left_upper)\\n\\n m2_left_middle.extend(m2_KUMIKI_points1)\\n m2_left_middle.append(m2_left_middle[0])\\n m2_left_middle_crv = rs.AddPolyline(m2_left_middle)\\n\\n m2_left_lower.extend(m2_KUMIKI_points1)\\n m2_left_lower.append(m2_left_lower[0])\\n m2_left_lower_crv = rs.AddPolyline(m2_left_lower)\\n\\n m2_left_crvs = [m2_left_upper_crv, m2_left_middle_crv, m2_left_lower_crv]\\n\\n # Right---------------------------------------------------------------------\\n m2_right_list = TSUGITE_list[1]\\n m2_right_upper = m2_right_list[0]\\n m2_right_middle = m2_right_list[1]\\n m2_right_lower = m2_right_list[2]\\n\\n # SHIGUCHI\\n m2_KUMIKI_points1 = SHIGUCHI_list[0]\\n m2_KUMIKI_points2 = SHIGUCHI_list[1]\\n\\n # Extend\\n # material2\\n m2_right_upper.reverse()\\n m2_right_middle.reverse()\\n m2_right_lower.reverse()\\n\\n # m2_KUMIKI_points1.reverse()\\n\\n m2_right_upper.extend(m2_KUMIKI_points1)\\n m2_right_upper.append(m2_right_upper[0])\\n m2_right_upper_crv = rs.AddPolyline(m2_right_upper)\\n\\n m2_right_middle.extend(m2_KUMIKI_points1)\\n m2_right_middle.append(m2_right_middle[0])\\n m2_right_middle_crv = rs.AddPolyline(m2_right_middle)\\n\\n m2_right_lower.extend(m2_KUMIKI_points1)\\n m2_right_lower.append(m2_right_lower[0])\\n m2_right_lower_crv = rs.AddPolyline(m2_right_lower)\\n\\n m2_right_crvs = [m2_right_upper_crv, m2_right_middle_crv, m2_right_lower_crv]\\n\\n return m2_left_crvs, m2_right_crvs\",\n \"def callback_rocm_bitcode_path(rocdl_dir=None):\\n # seems link order matters.\\n\\n if rocdl_dir is None:\\n if exists(\\\"/opt/rocm/amdgcn/bitcode/\\\"):\\n rocdl_dir = \\\"/opt/rocm/amdgcn/bitcode/\\\" # starting with rocm 3.9\\n else:\\n rocdl_dir = \\\"/opt/rocm/lib/\\\" # until rocm 3.8\\n\\n bitcode_names = [\\n \\\"oclc_daz_opt_on\\\",\\n \\\"ocml\\\",\\n \\\"irif\\\", # this does not exist in rocm 3.9, drop eventually\\n \\\"oclc_correctly_rounded_sqrt_off\\\",\\n \\\"oclc_correctly_rounded_sqrt_on\\\",\\n \\\"oclc_daz_opt_off\\\",\\n \\\"oclc_finite_only_off\\\",\\n \\\"oclc_finite_only_on\\\",\\n # todo (t-vi): an alternative might be to scan for the\\n \\\"oclc_isa_version_803\\\",\\n \\\"oclc_isa_version_900\\\", # isa version files (if the linker throws out\\n \\\"oclc_isa_version_906\\\", # the unneeded ones or we filter for the arch we need)\\n \\\"oclc_isa_version_1030\\\",\\n \\\"oclc_unsafe_math_off\\\",\\n \\\"oclc_unsafe_math_on\\\",\\n \\\"oclc_wavefrontsize64_on\\\",\\n \\\"oclc_abi_version_500\\\",\\n ]\\n\\n bitcode_files = []\\n for n in bitcode_names:\\n p = join(rocdl_dir, n + \\\".bc\\\") # rocm >= 3.9\\n if not exists(p): # rocm <= 3.8\\n p = join(rocdl_dir, n + \\\".amdgcn.bc\\\")\\n if exists(p):\\n bitcode_files.append(p)\\n elif \\\"isa_version\\\" not in n and n not in {\\\"irif\\\"}:\\n raise RuntimeError(\\\"could not find bitcode \\\" + n)\\n\\n return tvm.runtime.convert(bitcode_files)\",\n \"def gm_robe(self):\\n self.name = \\\"Grand Mage's Robe\\\"\\n self.rarity = \\\"Uncommon\\\"\\n self.pdef_value = 8\\n self.mdef_value = 30\\n self.increase_crit = 0\\n self.desc = \\\"The robe of an accomplished mage, has many enchantments.\\\"\",\n \"def test_visualize_rdkit(self):\\n import rdkit\\n\\n mol = Molecule().from_smiles(\\\"CCO\\\")\\n\\n assert isinstance(mol.visualize(backend=\\\"rdkit\\\"), rdkit.Chem.rdchem.Mol)\",\n \"def railway(osm_path): \\n return (retrieve(osm_path,'lines',['railway'],**{'railway':[\\\"='rail' or \\\",\\\"='tram' or \\\",\\\"='subway' or \\\",\\\"='construction' or \\\",\\\"='funicular' or \\\",\\\"='light_rail' or \\\",\\\"='narrow_gauge'\\\"]})).rename(columns={'railway': 'asset'})\",\n \"def get_rechnung(rechnungsnr):\\n\\n if str(rechnungsnr).startswith('RG'):\\n rechnungsnr = str(rechnungsnr)[2:]\\n kopf = get_connection().query(['AFK00'],\\n condition=\\\"FKRGNR = %s\\\" % sql_escape(rechnungsnr))\\n if len(kopf) < 1:\\n raise RuntimeError('inkonsistente Kopfdaten in AFK00: %r' % kopf)\\n if len(kopf) > 1:\\n print 'warning: inkonsistente Kopfdaten in AFK00: FKRGNR = %s' % rechnungsnr\\n print kopf\\n kopf = kopf[0]\\n # TODO: der code schient nciht zu klappen, wenn gar keine Auftragstexte vorhanden sind.\\n postmp = get_connection().query(['AFU00', 'AAT00'],\\n condition=\\\"FURGNR=%s AND FUAUFN=ATAUFN AND FUAUPO=ATAUPO AND ATTART=8\\\" % sql_escape(rechnungsnr))\\n\\n # wenn eine Rechnungsposition mehr als einen Rechnungstext hat, ist sie jetzt mehrfach in positionen\\n # dedupen und spezial felder auseinanderklamuesern\\n positionen = {}\\n texte = {}\\n for line in postmp:\\n positionen.setdefault(line['auftragsposition'], {}).update(line)\\n text = line['text'].strip()\\n if not text.startswith('#:'):\\n texte.setdefault(line['auftragsposition'], []).append(line['text'])\\n if text.startswith('#:guid:'):\\n positionen[line['auftragsposition']]['guid'] = text[7:]\\n for posnr, textlines in texte.items():\\n positionen[posnr]['text'] = ' '.join(textlines)\\n\\n return kopf, positionen.values()\",\n \"def birch(args):\\n p = OptionParser(birch.__doc__)\\n opts, args, iopts = p.set_image_options(args, figsize=\\\"8x6\\\")\\n\\n if len(args) != 2:\\n sys.exit(not p.print_help())\\n\\n seqids, layout = args\\n fig = plt.figure(1, (iopts.w, iopts.h))\\n root = fig.add_axes([0, 0, 1, 1])\\n\\n K = Karyotype(fig, root, seqids, layout)\\n L = K.layout\\n\\n xs = 0.79\\n dt = dict(rectangle=False, circle=False)\\n # Embed a phylogenetic tree to the right\\n coords = {}\\n coords[\\\"Amborella\\\"] = (xs, L[0].y)\\n coords[\\\"Vitis\\\"] = (xs, L[1].y)\\n coords[\\\"Prunus\\\"] = (xs, L[2].y)\\n coords[\\\"Betula\\\"] = (xs, L[3].y)\\n coords[\\\"Populus\\\"] = (xs, L[4].y)\\n coords[\\\"Arabidopsis\\\"] = (xs, L[5].y)\\n coords[\\\"fabids\\\"] = join_nodes(root, coords, \\\"Prunus\\\", \\\"Betula\\\", xs, **dt)\\n coords[\\\"malvids\\\"] = join_nodes(root, coords, \\\"Populus\\\", \\\"Arabidopsis\\\", xs, **dt)\\n coords[\\\"rosids\\\"] = join_nodes(root, coords, \\\"fabids\\\", \\\"malvids\\\", xs, **dt)\\n coords[\\\"eudicots\\\"] = join_nodes(root, coords, \\\"rosids\\\", \\\"Vitis\\\", xs, **dt)\\n coords[\\\"angiosperm\\\"] = join_nodes(root, coords, \\\"eudicots\\\", \\\"Amborella\\\", xs, **dt)\\n\\n # Show branch length\\n branch_length(root, coords[\\\"Amborella\\\"], coords[\\\"angiosperm\\\"], \\\">160.0\\\")\\n branch_length(root, coords[\\\"eudicots\\\"], coords[\\\"angiosperm\\\"], \\\">78.2\\\", va=\\\"top\\\")\\n branch_length(root, coords[\\\"Vitis\\\"], coords[\\\"eudicots\\\"], \\\"138.5\\\")\\n branch_length(root, coords[\\\"rosids\\\"], coords[\\\"eudicots\\\"], \\\"19.8\\\", va=\\\"top\\\")\\n branch_length(\\n root, coords[\\\"Prunus\\\"], coords[\\\"fabids\\\"], \\\"104.2\\\", ha=\\\"right\\\", va=\\\"top\\\"\\n )\\n branch_length(root, coords[\\\"Arabidopsis\\\"], coords[\\\"malvids\\\"], \\\"110.2\\\", va=\\\"top\\\")\\n branch_length(\\n root, coords[\\\"fabids\\\"], coords[\\\"rosids\\\"], \\\"19.8\\\", ha=\\\"right\\\", va=\\\"top\\\"\\n )\\n branch_length(root, coords[\\\"malvids\\\"], coords[\\\"rosids\\\"], \\\"8.5\\\", va=\\\"top\\\")\\n\\n root.set_xlim(0, 1)\\n root.set_ylim(0, 1)\\n root.set_axis_off()\\n\\n pf = \\\"birch\\\"\\n image_name = pf + \\\".\\\" + iopts.format\\n savefig(image_name, dpi=iopts.dpi, iopts=iopts)\",\n \"def updateRoboPos(self,deltaL,deltaR,KompassCourse=None):\\r\\n #RoboSchwerpunkt bis Rad cm\\r\\n Radstand= 30.2\\r\\n countsRadGross= 288\\r\\n\\r\\n #Werte Uebernehmen: Counts in (cm) umrechnen\\r\\n deltaL=deltaL*((5.5*pi)/countsRadGross) #(Radumfang)/counts\\r\\n deltaR=deltaR*((5.5*pi)/countsRadGross) #(Radumfang)/counts\\r\\n WinkelDiff=degrees((deltaR-deltaL)/Radstand) #Raddist/Radstandbreite\\r\\n \\r\\n self.global_kurs=self.global_kurs+WinkelDiff #Global Kurs anhand Weg berechnen\\r\\n if self.global_kurs>360:\\r\\n self.global_kurs=self.global_kurs-360\\r\\n if self.global_kurs<0:\\r\\n self.global_kurs=360-abs(self.global_kurs) \\r\\n global_kurs_radiant=radians(self.global_kurs)\\r\\n #global_kurs_radiant=0\\r\\n #self.global_kurs=KompassCourse \\r\\n\\r\\n if deltaL != deltaR:\\r\\n da=(deltaR-deltaL)/Radstand #Drehwinkel in [rad]\\r\\n ds=(deltaL+deltaR)/2 #Mittler Strecke von L und R\\r\\n\\r\\n #delta X und Y berechnen nach einer Kurve Dx->Waagerecht Dy->senkrecht\\r\\n dx=(ds/da)*(cos((pi/2)+global_kurs_radiant-da)+cos(global_kurs_radiant-(pi/2)))\\r\\n dy=(ds/da)*(sin((pi/2)+global_kurs_radiant-da)+sin(global_kurs_radiant-(pi/2)))\\r\\n \\r\\n #Position des Robo auf Karte updaten\\r\\n self.drehmatrix(dx,dy)\\r\\n else: \\r\\n dx=deltaR*cos(global_kurs_radiant)\\r\\n dy=deltaL*sin(global_kurs_radiant)\\r\\n\\r\\n #Position des Robo auf Karte updaten\\r\\n self.drehmatrix(dx,dy)\",\n \"def leerIRsiguelineas() -> int:\\n pass\",\n \"def parseRel(relfile):\\n\\trelf = open(relfile, \\\"r\\\")\\n\\trelfline = relf.readlines()\\n\\trelf.close()\\n\\t\\n\\t# First line is GRB\\n\\tgrb = relfline[0].replace(\\\"\\\\n\\\",\\\"\\\").split(\\\" \\\")\\n\\tGRBDict = {}\\n\\tGRBDict[\\\"RA\\\"] = float(grb[0])\\n\\tGRBDict[\\\"DEC\\\"] = float(grb[0])\\n\\t\\n\\tStarArray = []\\n\\t# Other lines are magnitudes\\n\\tfor i in relfline[1:]:\\n\\t\\t starline = i.replace(\\\"\\\\n\\\",\\\"\\\").split(\\\" \\\")\\n\\t\\t StarDict = {}\\n\\t\\t StarDict[\\\"RA\\\"] = float(starline[0])\\n\\t\\t StarDict[\\\"DEC\\\"] = float(starline[1])\\n\\t\\t StarDict[\\\"MAG_ABSOLUTE\\\"] = float(starline[2])\\n\\t\\t StarDict[\\\"MAG_ABSOLUTE_ERR\\\"] = float(starline[3])\\n\\t\\t \\n\\t\\t StarArray.append(StarDict)\\n\\t\\t \\n\\treturn GRBDict, StarArray\",\n \"def localizeLP(img):\\n\\t# preprocess\\n\\tgray_img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\\n\\t# using cascade classifier to detect license plate\\n\\t# the trained classifier is not good, retrain to get better results.\\n\\t# pre-trained classifier at: https://github.com/openalpr/openalpr/tree/master/runtime_data/region\\n\\tcascade = cv2.CascadeClassifier(\\\"localization/cascade_model.xml\\\")\\n\\trects = cascade.detectMultiScale(gray_img, scaleFactor=1.1, minNeighbors=3, minSize=(30, 30),flags=cv2.CASCADE_SCALE_IMAGE)\\n\\tif len(rects)==0:\\n\\t\\treturn None,None\\n\\n\\trect_list=[(rect[0],rect[1],rect[2],rect[3]) for rect in rects]\\n\\timg_height=gray_img.shape[0]\\n\\timg_width=gray_img.shape[1]\\n\\tmin_height, max_height, min_width, max_width = (0.1*img_height, 0.7*img_height, 0.1*img_width, 0.7*img_width)\\n\\thorizontal_min, horizontal_max = (0.1*img_width, 0.9*img_width)\\n\\tfor obj_rect in rect_list:\\n\\t\\tmin_col, min_row, w, h=obj_rect\\n\\t\\tmax_col = min_col+w\\n\\t\\tmax_row=min_row+h\\n\\t\\tif h >= min_height and h <= max_height and w >= min_width and w <= max_width and min_col>horizontal_min and max_col<horizontal_max:\\n\\t\\t\\tplate=gray_img[min_row:max_row,min_col:max_col]\\n\\t\\t\\treturn plate,(min_row,min_col,max_row,max_col)\",\n \"def grass_drass():\",\n \"def __init__(self, \\n xml_path=cfg.PERSON_REID_XML,\\n bin_path=cfg.PERSON_REID_BIN):\\n self.__net = cv.dnn.readNet(xml_path, bin_path)\\n self.__net.setPreferableTarget(cv.dnn.DNN_TARGET_MYRIAD)\",\n \"def ramraddrrst(self):\\n return 0\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6016394","0.598565","0.5746635","0.5739094","0.55431193","0.55244523","0.5518214","0.543907","0.54066896","0.53700364","0.5345745","0.5305402","0.52925533","0.5265397","0.5254321","0.5248294","0.52093405","0.5157794","0.5145444","0.51160425","0.5107024","0.5101872","0.50988984","0.508634","0.5063627","0.5062915","0.5055626","0.5054821","0.5050078","0.50471383","0.5035271","0.5012867","0.5012288","0.5005102","0.50032115","0.49887317","0.49795437","0.49774325","0.49738196","0.49627745","0.49581805","0.49559224","0.49528593","0.49442816","0.493883","0.4937875","0.49347007","0.49344873","0.49190974","0.49190974","0.4918599","0.49154833","0.4902487","0.48901117","0.48881462","0.48841742","0.48841742","0.48826107","0.4875928","0.48727557","0.4870937","0.4870937","0.4869782","0.48486608","0.48461533","0.48414454","0.4839765","0.4834037","0.4834037","0.48296615","0.4826533","0.4822081","0.48158893","0.48131943","0.48130375","0.4812516","0.4811529","0.47885832","0.47816265","0.47800088","0.47763735","0.47759816","0.4762818","0.476227","0.47558472","0.4754275","0.47524175","0.47457075","0.47450346","0.4740928","0.47339633","0.47336435","0.4725927","0.47255176","0.4721665","0.4719643","0.47138608","0.47114682","0.470953","0.47086373"],"string":"[\n \"0.6016394\",\n \"0.598565\",\n \"0.5746635\",\n \"0.5739094\",\n \"0.55431193\",\n \"0.55244523\",\n \"0.5518214\",\n \"0.543907\",\n \"0.54066896\",\n \"0.53700364\",\n \"0.5345745\",\n \"0.5305402\",\n \"0.52925533\",\n \"0.5265397\",\n \"0.5254321\",\n \"0.5248294\",\n \"0.52093405\",\n \"0.5157794\",\n \"0.5145444\",\n \"0.51160425\",\n \"0.5107024\",\n \"0.5101872\",\n \"0.50988984\",\n \"0.508634\",\n \"0.5063627\",\n \"0.5062915\",\n \"0.5055626\",\n \"0.5054821\",\n \"0.5050078\",\n \"0.50471383\",\n \"0.5035271\",\n \"0.5012867\",\n \"0.5012288\",\n \"0.5005102\",\n \"0.50032115\",\n \"0.49887317\",\n \"0.49795437\",\n \"0.49774325\",\n \"0.49738196\",\n \"0.49627745\",\n \"0.49581805\",\n \"0.49559224\",\n \"0.49528593\",\n \"0.49442816\",\n \"0.493883\",\n \"0.4937875\",\n \"0.49347007\",\n \"0.49344873\",\n \"0.49190974\",\n \"0.49190974\",\n \"0.4918599\",\n \"0.49154833\",\n \"0.4902487\",\n \"0.48901117\",\n \"0.48881462\",\n \"0.48841742\",\n \"0.48841742\",\n \"0.48826107\",\n \"0.4875928\",\n \"0.48727557\",\n \"0.4870937\",\n \"0.4870937\",\n \"0.4869782\",\n \"0.48486608\",\n \"0.48461533\",\n \"0.48414454\",\n \"0.4839765\",\n \"0.4834037\",\n \"0.4834037\",\n \"0.48296615\",\n \"0.4826533\",\n \"0.4822081\",\n \"0.48158893\",\n \"0.48131943\",\n \"0.48130375\",\n \"0.4812516\",\n \"0.4811529\",\n \"0.47885832\",\n \"0.47816265\",\n \"0.47800088\",\n \"0.47763735\",\n \"0.47759816\",\n \"0.4762818\",\n \"0.476227\",\n \"0.47558472\",\n \"0.4754275\",\n \"0.47524175\",\n \"0.47457075\",\n \"0.47450346\",\n \"0.4740928\",\n \"0.47339633\",\n \"0.47336435\",\n \"0.4725927\",\n \"0.47255176\",\n \"0.4721665\",\n \"0.4719643\",\n \"0.47138608\",\n \"0.47114682\",\n \"0.470953\",\n \"0.47086373\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.50784093"},"document_rank":{"kind":"string","value":"24"}}},{"rowIdx":18690,"cells":{"query":{"kind":"string","value":"Gera o codigo rml que define o estilo dos paragrafos"},"document":{"kind":"string","value":"def paraStyle():\n\n tmp=''\n tmp+='\\t<stylesheet>\\n'\n tmp+='\\t\\t<blockTableStyle id=\"Standard_Outline\">\\n'\n tmp+='\\t\\t\\t<blockAlignment value=\"LEFT\"/>\\n'\n tmp+='\\t\\t\\t<blockValign value=\"TOP\"/>\\n'\n tmp+='\\t\\t</blockTableStyle>\\n'\n tmp+='\\t\\t<initialize>\\n'\n tmp+='\\t\\t\\t<paraStyle name=\"all\" alignment=\"justify\"/>\\n'\n tmp+='\\t\\t</initialize>\\n'\n tmp+='\\t\\t<paraStyle name=\"P0\" fontName=\"Helvetica-Bold\" fontSize=\"11\" leading=\"13\" alignment=\"CENTER\"/>\\n'\n tmp+='\\t\\t<paraStyle name=\"P1\" fontName=\"Helvetica\" fontSize=\"10.0\" leading=\"11\" alignment=\"CENTER\"/>\\n'\n tmp+='\\t\\t<paraStyle name=\"P2\" fontName=\"Helvetica\" fontSize=\"9.0\" leading=\"10\" alignment=\"LEFT\"/>\\n'\n tmp+='\\t\\t<paraStyle name=\"P3\" fontName=\"Helvetica\" fontSize=\"10\" leading=\"12\" alignment=\"JUSTIFY\"/>\\n'\n tmp+='\\t\\t<paraStyle name=\"P4\" fontName=\"Helvetica\" fontSize=\"10.0\" leading=\"13\" alignment=\"CENTER\"/>\\n'\n tmp+='\\t</stylesheet>\\n'\n return tmp"},"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 define_parameters(self):","def parameters(self):","def doParametersOfInterest(self):\n\n self.modelBuilder.doVar(\"Afb[0.6,-0.70,0.70]\");\n self.modelBuilder.doSet(\"POI\",\"Afb\")\n\n # ss templates\n self.modelBuilder.doVar(\"Rdy_mumu_ss[1.0,0.0,10.0]\");\n self.modelBuilder.doVar(\"Rdy_ee_ss[1.0,0.0,10.0]\");\n \n self.modelBuilder.factory_('expr::Rpl(\"(1.+@0)\",Afb)')\n self.modelBuilder.factory_('expr::Rmn(\"(1.-@0)\",Afb)')","def parar():\n pass","def doParametersOfInterest(self):\n\n self.modelBuilder.doVar(\"eAfb[0.6,-0.75,0.75]\");\n self.modelBuilder.doVar(\"eA0[0.05, -1.0, 1.0]\");\n self.modelBuilder.doVar(\"mAfb[0.6,-0.75,0.75]\");\n self.modelBuilder.doVar(\"mA0[0.05, -1.0, 1.0]\");\n self.modelBuilder.doSet(\"POI\",\"eAfb,mAfb\")\n\n \n self.modelBuilder.factory_('expr::eAlph(\"2.0*@0/(2.0-@0)\",eA0)')\n self.modelBuilder.factory_('expr::eNorm(\"3.0/4.0/(2.0+@0)\",eAlph)')\n self.modelBuilder.factory_('expr::eRAlph(\"@0*@1\",eAlph,eNorm)')\n self.modelBuilder.factory_('expr::eRpl(\"(@0+@1)\",eNorm,eAfb)')\n self.modelBuilder.factory_('expr::eRmn(\"(@0-@1)\",eNorm,eAfb)')\n\n self.modelBuilder.factory_('expr::mAlph(\"2.0*@0/(2.0-@0)\",mA0)')\n self.modelBuilder.factory_('expr::mNorm(\"3.0/4.0/(2.0+@0)\",mAlph)')\n self.modelBuilder.factory_('expr::mRAlph(\"@0*@1\",mAlph,mNorm)')\n self.modelBuilder.factory_('expr::mRpl(\"(@0+@1)\",mNorm,mAfb)')\n self.modelBuilder.factory_('expr::mRmn(\"(@0-@1)\",mNorm,mAfb)')","def __init__(self, parant):\n pass","def doParametersOfInterest(self):\n\n self.modelBuilder.doVar(\"Rdy[1.,0.0,10.0]\");\n self.modelBuilder.doVar(\"Rbk[1.,0.0,10.0]\");\n self.modelBuilder.doVar(\"Rqcd_emu[1,0.0,10.0]\");\n self.modelBuilder.doSet(\"POI\",\"Rbk,Rdy,Rqcd_emu\")","def doParametersOfInterest(self):\n\n self.modelBuilder.doVar(\"Afb[0.6,-0.75,0.75]\");\n self.modelBuilder.doVar(\"A0[0.05, -1.0, 1.0]\");\n self.modelBuilder.doSet(\"POI\",\"Afb,A0\")\n\n \n self.modelBuilder.factory_('expr::Alph(\"2.0*@0/(2.0-@0)\",A0)')\n self.modelBuilder.factory_('expr::Norm(\"3.0/4.0/(2.0+@0)\",Alph)')\n self.modelBuilder.factory_('expr::RAlph(\"@0*@1\",Alph,Norm)')\n self.modelBuilder.factory_('expr::Rpl(\"(@0+@1)\",Norm,Afb)')\n self.modelBuilder.factory_('expr::Rmn(\"(@0-@1)\",Norm,Afb)')","def doParametersOfInterest(self):\n\n self.modelBuilder.doVar(\"eAfb[0.6,-0.75,0.75]\");\n self.modelBuilder.doVar(\"eA0[0.05, -1.0, 1.0]\");\n self.modelBuilder.doVar(\"rAfb[1.0,-5.0, 5.0]\");\n self.modelBuilder.doVar(\"rA0[1.0, -5.0, 5.0]\");\n self.modelBuilder.doSet(\"POI\",\"rAfb,rA0\")\n self.modelBuilder.factory_('expr::mAfb(\"@0*@1\",eAfb,rAfb)')\n self.modelBuilder.factory_('expr::mA0(\"(@0*@1)\",eA0,rA0)')\n\n \n self.modelBuilder.factory_('expr::eAlph(\"2.0*@0/(2.0-@0)\",eA0)')\n self.modelBuilder.factory_('expr::eNorm(\"3.0/4.0/(2.0+@0)\",eAlph)')\n self.modelBuilder.factory_('expr::eRAlph(\"@0*@1\",eAlph,eNorm)')\n self.modelBuilder.factory_('expr::eRpl(\"(@0+@1)\",eNorm,eAfb)')\n self.modelBuilder.factory_('expr::eRmn(\"(@0-@1)\",eNorm,eAfb)')\n\n self.modelBuilder.factory_('expr::mAlph(\"2.0*@0/(2.0-@0)\",mA0)')\n self.modelBuilder.factory_('expr::mNorm(\"3.0/4.0/(2.0+@0)\",mAlph)')\n self.modelBuilder.factory_('expr::mRAlph(\"@0*@1\",mAlph,mNorm)')\n self.modelBuilder.factory_('expr::mRpl(\"(@0+@1)\",mNorm,mAfb)')\n self.modelBuilder.factory_('expr::mRmn(\"(@0-@1)\",mNorm,mAfb)')","def doParametersOfInterest(self):\n\n self.modelBuilder.doVar(\"Rdy[1.,0.0,10.0]\");\n self.modelBuilder.doVar(\"Rqcd[1,0.0,10.0]\");\n self.modelBuilder.doSet(\"POI\",\"Rdy,Rqcd\")","def doParametersOfInterest(self):\r\n if self.fg4fixed:\r\n self.modelBuilder.doVar(\"CMS_zz4l_fg4[0]\")\r\n self.modelBuilder.doVar(\"r[1,0,4]\")\r\n print \"Fixing CMS_zz4l_fg4\"\r\n poi = \"r\"\r\n else:\r\n if self.modelBuilder.out.var(\"CMS_zz4l_fg4\"):\r\n print \"have fg4 inside\"\r\n else:\r\n self.modelBuilder.doVar(\"CMS_zz4l_fg4[0.,-1,1]\")\r\n poi = \"CMS_zz4l_fg4\"\r\n if self.cPOI:\r\n if self.modelBuilder.out.var(\"cww_zz\"):\r\n print \"have czz_ww inside\"\r\n else:\r\n self.modelBuilder.doVar(\"cww_zz[0.5,-10,10]\")\r\n poi += \",cww_zz\"\r\n\r\n if self.fg2POI:\r\n if self.modelBuilder.out.var(\"CMS_zz4l_fg2\"):\r\n print \"have fg2 inside\"\r\n else:\r\n self.modelBuilder.doVar(\"CMS_zz4l_fg2[0.,0,1]\")\r\n poi += \",CMS_zz4l_fg2\"\r\n if self.muFloating:\r\n self.modelBuilder.doVar(\"r[1,0,2000]\")\r\n if self.muAsPOI:\r\n print \"Treating r as a POI\"\r\n poi += \",r\"\r\n else:\r\n self.modelBuilder.out.var(\"r\").setAttribute(\"flatParam\")\r\n if self.phiFloating:\r\n if self.modelBuilder.out.var(\"CMS_zz4l_fg4phi\"):\r\n print \"have fg4phi inside\"\r\n else: \r\n self.modelBuilder.doVar(\"CMS_zz4l_fg4phi[0.,-3.1415926,3.1415926]\")\r\n if self.phiPOI:\r\n poi += \",CMS_zz4l_fg4phi\"\r\n else:\r\n self.modelBuilder.out.var(\"CMS_zz4l_fg4phi\").setAttribute(\"flatParam\")\r\n if self.phi2Floating:\r\n #self.modelBuilder.doVar(\"CMS_zz4l_fg4phi[0.,-math.pi,math.pi]\")\r\n if self.modelBuilder.out.var(\"CMS_zz4l_fg2phi\"):\r\n print \"have fg2phi inside\"\r\n else: \r\n self.modelBuilder.doVar(\"CMS_zz4l_fg2phi[0.,-3.1415926,3.1415926]\")\r\n self.modelBuilder.out.var(\"CMS_zz4l_fg2phi\").setAttribute(\"flatParam\")\r\n \r\n self.modelBuilder.doSet(\"POI\",poi)","def doParametersOfInterest(self):\n\n self.modelBuilder.doVar(\"eAfb[0.6,-0.75,0.75]\");\n self.modelBuilder.doVar(\"eA0[0.05, -1.0, 1.0]\");\n self.modelBuilder.doVar(\"dAfb[0.,-0.75,0.75]\");\n self.modelBuilder.doVar(\"dA0[0.0, -1.0, 1.0]\");\n #self.modelBuilder.doSet(\"POI\",\"dAfb,dA0\")\n self.modelBuilder.doSet(\"POI\",\"dAfb\")\n self.modelBuilder.factory_('expr::mAfb(\"@0+@1\",eAfb,dAfb)')\n self.modelBuilder.factory_('expr::mA0(\"(@0+@1)\",eA0,dA0)')\n\n \n self.modelBuilder.factory_('expr::eAlph(\"2.0*@0/(2.0-@0)\",eA0)')\n self.modelBuilder.factory_('expr::eNorm(\"3.0/4.0/(2.0+@0)\",eAlph)')\n self.modelBuilder.factory_('expr::eRAlph(\"@0*@1\",eAlph,eNorm)')\n self.modelBuilder.factory_('expr::eRpl(\"(@0+@1)\",eNorm,eAfb)')\n self.modelBuilder.factory_('expr::eRmn(\"(@0-@1)\",eNorm,eAfb)')\n\n self.modelBuilder.factory_('expr::mAlph(\"2.0*@0/(2.0-@0)\",mA0)')\n self.modelBuilder.factory_('expr::mNorm(\"3.0/4.0/(2.0+@0)\",mAlph)')\n self.modelBuilder.factory_('expr::mRAlph(\"@0*@1\",mAlph,mNorm)')\n self.modelBuilder.factory_('expr::mRpl(\"(@0+@1)\",mNorm,mAfb)')\n self.modelBuilder.factory_('expr::mRmn(\"(@0-@1)\",mNorm,mAfb)')","def main(model,pmap):\n\n addPppParams(model)\n\n# addTransportParams(model,pmap)\n\n #translationSources(model)\n\n #addLipidMetabs(model)\n\n return","def doParametersOfInterest(self):\n\n self.modelBuilder.doVar(\"Afb[0.6,-0.75,0.75]\");\n self.modelBuilder.doSet(\"POI\",\"Afb\")\n\n # ss templates\n self.modelBuilder.doVar(\"Dilu_ratio[1.0,0.0,10.0]\");\n self.modelBuilder.doVar(\"Rdy_mumu_ss[1.0,0.0,10.0]\");\n self.modelBuilder.doVar(\"Rdy_ee_ss[1.0,0.0,10.0]\");\n \n self.modelBuilder.factory_('expr::Rpl(\"0.5*(1.+@0*@1)\",Afb, Dilu_ratio)')\n self.modelBuilder.factory_('expr::Rmn(\"0.5*(1.-@0*@1)\",Afb, Dilu_ratio)')","def _load_parameter(self):","def getDefaultParams():\n defpar = [\n # coordinate system\n ['crd_sys', \"'sph'\", 'Coordinate system'],\n ['nx', '[60, 40, 30]', 'Number of grid points in the first dimension'],\n ['xbound', '[0.1*au, 30.*au, 110.*au, 250.*au]', 'Number of radial grid points'],\n ['ny', '[10,30, 30, 10]',\n 'Number of grid points in the second dimension'],\n ['ybound', '[0.1, pi/6., pi/2., 5.*pi/6., 3.04]',\n 'Number of radial grid points'],\n ['nz', '[361]', 'Number of grid points in the third dimension'],\n ['zbound', '[0., 2.0*pi]', 'Number of radial grid points'],\n # star related\n ['tstar', '[3900.0]', 'Temperature of star'],\n ['mstar', '[1.0*ms]', 'Mass of the star(s)'],\n ['rstar', '[2.5*rs]', 'Radius of star'],\n # gas density \n ['Rin', '[0.1*au, 80*au]', 'inner bounding edge'],\n ['Rin_w', '[0, 1*au]', 'gaussian taper before inner edge'], \n ['Rout', '[30*au, 120*au]', 'outer bounding edge'],\n ['Rout_w', '[1*au, 1*au]', 'gaussian taper after outer edge'], \n ['sigp', '[-1.0, -1.5]', 'power-law surface density'],\n ['sig0', '[1e2, 1e1]', 'surface density at Rin in g/cm^2'], \n ['ring_r', '[50*au]', 'location of gaussian ring'], \n ['ring_win', '[5*au]', 'width of gaussian ring in inner radius'],\n ['ring_wout', '[5*au]', 'width of gaussian ring in outer radius'], \n ['ring_a', '[1e2]', 'surface density at center of ring in g/cm^2]'], \n ['cutgdens', '1e-30', 'cut for density'], \n ['Rt', '100*au', 'radius for scale height'], \n ['Ht', '10*au', 'scale height'], \n ['qheight', '1.25', 'height power-law'], \n # gas species\n ['gasspec_mol_name', \"['12co']\", 'name of molecule'],\n ['gasspec_mol_abun', '[5e-5]', 'mass abundance '],\n ['gasspec_mol_dbase_type', \"['leiden']\", ''],\n ['gasspec_mol_freezeout_dfact', '[1e-3]',\n 'Factor by which the molecular abundance should be decreased in the freeze-out zone'],\n ['mol_freeze_Ht', '[24*au]', 'Height at Rt, with index=qheight, for freeze out to happen'],\n ['mol_freeze_del_hfrac', '0.2', 'Gaussian taper for freeze-out. del H = h * hfrac'],\n ['mol_snowR', '[20*au]', 'Radius when freeze out begins to happen'],\n # dust density\n # flat power-law parts\n ['dRin', '[0.1*au, 80*au]', 'inner bounding edge'],\n ['dRin_w', '[0, 1*au]', 'gaussian taper before inner edge'], \n ['dRout', '[30*au, 120*au]', 'outer bounding edge'],\n ['dRout_w', '[1*au, 1*au]', 'gaussian taper after outer edge'], \n ['dsigp', '[-1.0, -1.5]', 'power-law surface density'],\n ['dsig0', '[1e2, 1e1]', 'surface density at Rin'],\n # Lynden-Bell parts\n ['dLB_Rin', '[0.1*au]', 'inner bounding radius'], \n ['dLB_Rsig', '[30*au]', 'charcteristic radius'],\n ['dLB_sigp', '[-1.0]', 'power-law exponent. Careful, the sign is different from the usual function by a negative sign for consistency with flat power-law'], \n ['dLB_sig0', '[1e2]', 'surface density'], \n # ring parts\n ['dring_r', '[50*au]', 'location of gaussian ring'],\n ['dring_win', '[5*au]', 'width of gaussian ring in inner radius'],\n ['dring_wout', '[5*au]', 'width of gaussian ring in outer radius'], \n ['dring_a', '[1e2]', 'surface density at center of ring in g/cm^2]'],\n ['cutddens', '1e-30', 'cut for dust density'],\n ['dRt', '[100*au]', 'radius for scale height for each grain size'], \n ['dHt', '[10*au]', 'scale height for each grain size'], \n ['dqheight', '[1.25]', 'scale height power-law for dust'], \n # temperature\n ['T0mid', '50', 'mid plane temperature at Rt'],\n ['T0atm', '50', 'atmosphere temperature at Rt'],\n ['zqratio', '3', 'factor of Ht of where temperature transition occurs'],\n ['qmid', '-0.5', 'midplane temperature exponent'],\n ['qatm', '-0.5', 'atmosphere temperature exponent'],\n ['hdel', '2', 'temperature transition exponent '],\n ['cuttemp', '10', 'temperature cut'], \n # alignment\n ['altype', \"'toroidal'\", 'alignment type']\n ]\n\n return defpar","def get_params(self):","def default_pypeit_par(cls):\n par = super().default_pypeit_par()\n\n # Wavelengths\n # 1D wavelength solution with arc lines\n par['calibrations']['wavelengths']['rms_threshold'] = 1.0\n par['calibrations']['wavelengths']['sigdetect']=3\n par['calibrations']['wavelengths']['fwhm'] = 20\n par['calibrations']['wavelengths']['n_first']=2\n par['calibrations']['wavelengths']['n_final']=4\n par['calibrations']['wavelengths']['lamps'] = ['ArI', 'ArII', 'ThAr', 'NeI']\n #par['calibrations']['wavelengths']['nonlinear_counts'] = self.detector[0]['nonlinear'] * self.detector[0]['saturation']\n par['calibrations']['wavelengths']['method'] = 'full_template'\n par['calibrations']['wavelengths']['reid_arxiv'] = 'magellan_fire_long.fits'\n par['calibrations']['wavelengths']['match_toler']=5.0\n\n # Set slits and tilts parameters\n par['calibrations']['tilts']['tracethresh'] = 5\n par['calibrations']['slitedges']['trace_thresh'] = 10.\n par['calibrations']['slitedges']['sync_predict'] = 'nearest'\n\n # Processing steps\n turn_off = dict(use_illumflat=False, use_biasimage=False, use_overscan=False,\n use_darkimage=False)\n par.reset_all_processimages_par(**turn_off)\n\n # Scienceimage parameters\n par['reduce']['findobj']['snr_thresh'] = 5\n #par['reduce']['maxnumber'] = 2\n par['reduce']['findobj']['find_trim_edge'] = [50,50]\n par['flexure']['spec_method'] = 'skip'\n\n par['sensfunc']['IR']['telgridfile'] = 'TelFit_LasCampanas_3100_26100_R20000.fits'\n\n # Set the default exposure time ranges for the frame typing\n par['calibrations']['standardframe']['exprng'] = [None, 60]\n par['calibrations']['arcframe']['exprng'] = [1, 50]\n par['calibrations']['darkframe']['exprng'] = [20, None]\n par['scienceframe']['exprng'] = [20, None]\n return par","def default_pypeit_par(cls):\n par = super().default_pypeit_par()\n\n # Wavelengths\n # 1D wavelength solution with OH lines\n par['calibrations']['wavelengths']['rms_threshold'] = 1.0\n par['calibrations']['wavelengths']['sigdetect']=[5,10,10,10,10,20,30,30,30,30,30,10,30,30,60,30,30,10,20,30,10]\n par['calibrations']['wavelengths']['n_first']=2\n par['calibrations']['wavelengths']['n_final']=[3,3,3,2,4,4,4,3,4,4,4,3,4,4,4,4,4,4,6,6,4]\n par['calibrations']['wavelengths']['lamps'] = ['OH_FIRE_Echelle']\n #par['calibrations']['wavelengths']['nonlinear_counts'] = self.detector[0]['nonlinear'] * self.detector[0]['saturation']\n par['calibrations']['wavelengths']['method'] = 'reidentify'\n par['calibrations']['wavelengths']['cc_thresh'] = 0.35\n par['calibrations']['wavelengths']['reid_arxiv'] = 'magellan_fire_echelle.fits'\n par['calibrations']['wavelengths']['match_toler']=30.0\n\n # Echelle parameters\n par['calibrations']['wavelengths']['echelle'] = True\n# par['calibrations']['wavelengths']['ech_fix_format'] = True\n par['calibrations']['wavelengths']['ech_nspec_coeff'] = 4\n par['calibrations']['wavelengths']['ech_norder_coeff'] = 6\n par['calibrations']['wavelengths']['ech_sigrej'] = 3.0\n\n # Always correct for flexure, starting with default parameters\n par['scienceframe']['process']['sigclip'] = 20.0\n par['scienceframe']['process']['satpix'] ='nothing'\n\n # Set slits and tilts parameters\n par['calibrations']['tilts']['tracethresh'] = 5\n par['calibrations']['slitedges']['edge_thresh'] = 3.\n par['calibrations']['slitedges']['trace_thresh'] = 10.\n par['calibrations']['slitedges']['fit_order'] = 5\n par['calibrations']['slitedges']['max_shift_adj'] = 0.5\n par['calibrations']['slitedges']['fit_min_spec_length'] = 0.5\n par['calibrations']['slitedges']['left_right_pca'] = True\n par['calibrations']['slitedges']['pca_order'] = 3\n\n # Model entire slit\n par['reduce']['extraction']['model_full_slit'] = True # local sky subtraction operates on entire slit\n par['reduce']['findobj']['maxnumber_sci'] = 2 # Slit is narrow so allow one object per order\n par['reduce']['findobj']['maxnumber_std'] = 1 # Slit is narrow so allow one object per order\n\n # Processing steps\n turn_off = dict(use_illumflat=False, use_biasimage=False, use_overscan=False,\n use_darkimage=False)\n par.reset_all_processimages_par(**turn_off)\n # Do not correct for flexure\n par['flexure']['spec_method'] = 'skip'\n\n # Set the default exposure time ranges for the frame typing\n par['calibrations']['standardframe']['exprng'] = [None, 60]\n par['calibrations']['arcframe']['exprng'] = [20, None]\n par['calibrations']['darkframe']['exprng'] = [20, None]\n par['scienceframe']['exprng'] = [20, None]\n\n # Sensitivity function parameters\n # Sensitivity function parameters\n par['sensfunc']['algorithm'] = 'IR'\n par['sensfunc']['polyorder'] = 5\n par['sensfunc']['IR']['maxiter'] = 2\n # place holder for telgrid file\n par['sensfunc']['IR']['telgridfile'] = 'TelFit_LasCampanas_3100_26100_R20000.fits'\n\n return par","def parameters(self):\n pass","def mezclar_bolsa(self):","def doParametersOfInterest(self):\n\n self.modelBuilder.doVar(\"Afb[0.6,-0.7,0.7]\");\n self.modelBuilder.doVar(\"A0[0.05, -1.0, 1.0]\");\n self.modelBuilder.doSet(\"POI\",\"Afb,A0\")\n\n # ss templates\n self.modelBuilder.doVar(\"R_ee_os_fakes[0.6,0.0,1.0]\");\n self.modelBuilder.doVar(\"ee16_fakes_norm[1.0, 0.01, 10.]\");\n self.modelBuilder.doVar(\"ee17_fakes_norm[1.0, 0.01, 10.]\");\n self.modelBuilder.doVar(\"ee18_fakes_norm[1.0, 0.01, 10.]\");\n #Remember, cant use spaces in these formulas!\n #self.modelBuilder.options.verbose = 10\n self.modelBuilder.factory_('expr::R_ee16_qcd_os(\"@0*@1\",ee16_fakes_norm,R_ee_os_fakes)')\n self.modelBuilder.factory_('expr::R_ee17_qcd_os(\"@0*@1\",ee17_fakes_norm,R_ee_os_fakes)')\n self.modelBuilder.factory_('expr::R_ee18_qcd_os(\"@0*@1\",ee18_fakes_norm,R_ee_os_fakes)')\n self.modelBuilder.factory_('expr::R_ee16_qcd_ss(\"@0*(1.0-@1)\",ee16_fakes_norm,R_ee_os_fakes)')\n self.modelBuilder.factory_('expr::R_ee17_qcd_ss(\"@0*(1.0-@1)\",ee17_fakes_norm,R_ee_os_fakes)')\n self.modelBuilder.factory_('expr::R_ee18_qcd_ss(\"@0*(1.0-@1)\",ee18_fakes_norm,R_ee_os_fakes)')\n \n self.modelBuilder.factory_('expr::Alph(\"2.0*@0/(2.0-@0)\",A0)')\n self.modelBuilder.factory_('expr::Norm(\"3.0/4.0/(2.0+@0)\",Alph)')\n self.modelBuilder.factory_('expr::RAlph(\"@0*@1\",Alph,Norm)')\n self.modelBuilder.factory_('expr::Rpl(\"(@0+@1)\",Norm,Afb)')\n self.modelBuilder.factory_('expr::Rmn(\"(@0-@1)\",Norm,Afb)')","def doParametersOfInterest(self):\n self.modelBuilder.doVar(\"mu[1,0,100]\") ##mu is what we want to return (in string) name[starting_value,min,max] \n self.modelBuilder.doSet(\"POI\",\"mu\")\n self.modelBuilder.factory_('expr::ggH_s_func(\"@0-sqrt(@0)\", mu)')\n self.modelBuilder.factory_( 'expr::ggH_b_func(\"1-sqrt(@0)\", mu)')\n self.modelBuilder.factory_( 'expr::ggH_sbi_func(\"sqrt(@0)\", mu)')","def presenetCar():","def doParametersOfInterest(self):\n self.modelBuilder.doVar(\"mu[0,0,1000]\") ##mu is what we want to return (in string) name[starting_value,min,max] \n self.modelBuilder.doSet(\"POI\",\"mu\")\n self.modelBuilder.factory_('expr::vbfH_s_func(\"@0-sqrt(@0)\", mu)')\n self.modelBuilder.factory_( 'expr::vbfH_b_func(\"1-sqrt(@0)\", mu)')\n self.modelBuilder.factory_( 'expr::vbfH_sbi_func(\"sqrt(@0)\", mu)')","def params():\n raise NotImplementedError","def __init__(self,manager,name):\n Online.DatapointLoader.DatapointLoader.__init__(self,manager,name)\n self.dpName = self.name\n self.runType = self.dp('general.runType')\n self.partitionName = self.dp('general.partName')\n self.partitionID = self.dp('general.activePartId')\n self.nSubFarm = self.dp('HLTFarm.nSubFarms')\n self.subfarms = self.dp('HLTFarm.subFarms')\n self.addDp(self.reader)","def doParametersOfInterest(self):\n ''' ref : physicsmodel -> rvf\n self.modelBuilder.out.var(\"MH\").setRange(float(self.mHRange[0]),float(self.mHRange[1]))\n self.modelBuilder.out.var(\"MH\").setConstant(False)\n '''\n\n self.modelBuilder.doVar(\"mu[0,0,1000]\") ##mu is what we want to return (in string) name[starting_value,min,max] \n self.modelBuilder.doVar(\"Fvbf[0,0,1]\") ##mu is what we want to return (in string) name[starting_value,min,max] \n self.modelBuilder.doSet(\"POI\",\"mu,Fvbf\")\n self.modelBuilder.doVar(\"\")\n self.modelBuilder.factory_('expr::ggH_s_func(\"(@0-sqrt(@0))*(1.-@1)\", mu,Fvbf)')\n self.modelBuilder.factory_( 'expr::ggH_b_func(\"(1-sqrt(@0))*(1.-@1)\", mu,Fvbf)')\n self.modelBuilder.factory_( 'expr::ggH_sbi_func(\"sqrt(@0)*(1.-@1)\", mu,Fvbf)')\n\n self.modelBuilder.factory_('expr::vbfH_s_func(\"(@0-sqrt(@0))*(@1)\", mu,Fvbf)')\n self.modelBuilder.factory_( 'expr::vbfH_b_func(\"(1-sqrt(@0))*(@1)\", mu,Fvbf)')\n self.modelBuilder.factory_( 'expr::vbfH_sbi_func(\"sqrt(@0)*(@1)\", mu,Fvbf)')","def setupParachutes(self):\r\n # references to all the Parachute objects created\r\n # YAML config\r\n parConfNode = self.config.parachute\r\n #----------------------------\r\n robotTex = loader.loadTexture(parConfNode.texture[0].textureName)\r\n robotTex.setWrapU(Texture.WMClamp)\r\n robotTex.setWrapV(Texture.WMClamp)\r\n robotTex.setMinfilter(Texture.FTLinearMipmapLinear)\r\n robotTex.setAnisotropicDegree(2)\r\n #----------------------------\r\n paraTex = loader.loadTexture(parConfNode.parachuteTex)\r\n paraTex.setMinfilter(Texture.FTLinearMipmapLinear)\r\n paraTex.setAnisotropicDegree(2)\r\n #----------------------------\r\n baseNode = NodePath(\"parachute\")\r\n baseNode.setTransparency(1)\r\n baseNode.setScale(float(parConfNode.scale))\r\n\r\n cam = self.config.world.camera\r\n camLookAt = Vec3(cam.lookAt[0]-cam.pos[0],\r\n cam.lookAt[1]-cam.pos[1],\r\n cam.lookAt[2]-cam.pos[2])\r\n camLookAt.normalize()\r\n camLookAt = camLookAt * self.config.parDistCam\r\n\r\n # in Panda by default Y points away from the camera\r\n #Ypos = cam.pos[1] + cam.parDistCam\r\n # base node at cam.parDistCam distance from the camera\r\n baseNode.setPos(camLookAt[0],camLookAt[1],camLookAt[2])\r\n\r\n # this is the PARACHUTE part\r\n paraModel = loader.loadModel(parConfNode.modelname)\r\n paraModel.setScale(Vec3(0.3, 0.000001, 0.2))\r\n paraModel.setPos(Vec3(0, 0.15, 1.2))\r\n paraModel.setName(\"parachute\")\r\n paraModel.setTexture(paraTex)\r\n paraModel.reparentTo(baseNode)\r\n #----------------------------\r\n # bill board (plane) model, the actual robot\r\n robotModel = loader.loadModel(\"PilotData/models/plane\")\r\n robotModel.setName(\"body\")\r\n robotModel.setPos(Vec3(0, 0, -0.5))\r\n robotModel.setTransparency(1)\r\n robotModel.setTexture(robotTex, 1)\r\n robotModel.reparentTo(baseNode)\r\n #----------------------------\r\n baseNode.setBillboardPointEye()\r\n baseNode.reparentTo(self.sceneNP)\r\n self.baseNode = baseNode","def params(self):\n pass","def __init__(self):\n self.params = arcpy.GetParameterInfo()","def rip1_to_parp():\n Monomer('MLKL', ['bRHIM', 'state'], {'state':['unmod', 'active', 'inactive']})\n Parameter('MLKL_0' , 1.0e6) # molecules per cell\n alias_model_components()\n Initial(MLKL(bRHIM = None, state = 'unmod'), MLKL_0) # MLKL\n \n Rule('Rip_PO4lation', RIP1(bRHIM=ANY, state = 'unmod')%RIP3(bRHIM=ANY, state='unmod') >> RIP1(bRHIM=ANY, state = 'po4')%RIP3(bRHIM=ANY, state = 'po4'), Parameter('k19', 1e-1))\n Rule('Rip_PO4lation_alt', RIP1(bRHIM=ANY, state = 'deub')%RIP3(bRHIM=ANY, state='unmod') >> RIP1(bRHIM=ANY, state = 'po4')%RIP3(bRHIM=ANY, state = 'po4'), Parameter('k19a', 1e-1))\n \n catalyze_state(RIP1(state='po4'), 'bPARP', MLKL(), 'bRHIM', 'state', 'unmod', 'active', [1e-6,1e-3, 1e-1])\n catalyze_state(MLKL(state='active'), 'bRHIM', MLKL(), 'bRHIM', 'state', 'unmod', 'active', [1e-7, 0.2, 0.01])","def _initialize_params(self, parnames, sep=\".\"):\n for name in parnames:\n self.get_pvobj(name, sep)","def _read_custom_pars(self):\n if self.use_defaults:\n param_set = \"default_values\"\n else:\n param_set = \"parameters\"\n self.outpars = self.input_cfg_json_data[param_set][self.step_title]","def set_parameters(self):\n params = {}\n if self.modelname == 'SI':\n # N1: Pop 1 size after split\n # N2: Pop 2 size after splot\n # Ts: Time from split to present, in 2*Na generation units\n names = ['N1', 'N2', 'Ts']\n values = [1, 1, 1]\n upper_bounds = [20, 20, 10]\n lower_bounds = [0.01, 0.01, 0]\n elif self.modelname == 'IM':\n # N1: Pop 1 size after split\n # N2: Pop 2 size after split\n # m21: Migration from 1 to 2 (2*Na*mm21)\n # m12: Migration from 2 to 1 (2*Na*m12)\n # Ts: Time from split to present, in 2*Na generations\n names = ['N1', 'N2', 'm21', 'm12', 'Ts']\n values = [1, 1, 1, 1, 1]\n upper_bounds = [20, 20, 20, 20, 10]\n lower_bounds = [0.01, 0.01, 0, 0, 0]\n elif self.modelname == 'AM':\n # N1: Pop 1 size after split\n # N2: Pop 2 size after split\n # m21: Migration from 1 to 2 (2*Na*mm21)\n # m12: Migration from 2 to 1 (2*Na*m12)\n # Tam: Time from end of anc migration to split, in 2*Na gens\n # Ts: Time from split to present, in 2*Na generations\n names = ['N1', 'N2', 'm21', 'm12', 'Tam', 'Ts']\n values = [1, 1, 1, 1, 0.1, 1]\n upper_bounds = [20, 20, 20, 20, 2, 10]\n lower_bounds = [0.01, 0.01, 0, 0, 0, 0]\n elif self.modelname == 'SC':\n # N1: Pop 1 size after split\n # N2: Pop 2 size after split\n # m21: Migration from 1 to 2 (2*Na*mm21)\n # m12: Migration from 2 to 1 (2*Na*m12)\n # Ts: Time from split to secondary contact, in 2*Na generations\n # Tsc: Time from secondary contact to presesnt, in 2*Na gens\n names = ['N1', 'N2', 'm21', 'm12', 'Ts', 'Tsc']\n values = [1, 1, 1, 1, 1, 0.1]\n upper_bounds = [20, 20, 20, 20, 10, 2]\n lower_bounds = [0.01, 0.01, 0, 0, 0, 0]\n elif self.modelname == 'IM2M':\n # N1: Pop 1 size after split\n # N2: Pop 2 size after split\n # m21: Migration from 1 to 2 (2*Na*mm21)\n # m12: Migration from 2 to 1 (2*Na*m12)\n # mi21: Migration from 1 to 2 in \"islands\" (2*Na*mi21)\n # mi12: Migration from 1 to 2 in \"islands\" (2*Na*mi12)\n # Ts: Time from split to present, in 2*Na generations\n # p: Porpotion of genome evoloving in \"islands\"\n names = ['N1', 'N2', 'm21', 'm12', 'mi21', 'mi12', 'Ts', 'p']\n values = [1, 1, 5, 5, 0.5, 0.5, 1, 0.5]\n upper_bounds = [20, 20, 30, 30, 5, 5, 10, 0.95]\n lower_bounds = [0.01, 0.01, 0, 0, 0, 0, 0, 0.05]\n elif self.modelname == 'AM2M':\n # N1: Pop 1 size after split\n # N2: Pop 2 size after split\n # m21: Migration from 1 to 2 (2*Na*mm21)\n # m12: Migration from 2 to 1 (2*Na*m12)\n # mi21: Migration from 1 to 2 in \"islands\" (2*Na*mi21)\n # mi12: Migration from 1 to 2 in \"islands\" (2*Na*mi12)\n # Tam: Time from end of anc migration to split, in 2*Na gens\n # Ts: Time from split to present, in 2*Na generations\n # p: Porpotion of genome evoloving in \"islands\"\n names = ['N1', 'N2', 'm21', 'm12', 'mi21', 'mi12', 'Tam', 'Ts', 'p']\n values = [1, 1, 5, 5, 0.5, 0.5, 0.1, 1, 0.5]\n upper_bounds = [20, 20, 30, 30, 5, 5, 2, 10, 0.95]\n lower_bounds = [0.01, 0.01, 0, 0, 0, 0, 0, 0, 0.05]\n elif self.modelname == 'SC2M':\n # N1: Pop 1 size after split\n # N2: Pop 2 size after split\n # m21: Migration from 1 to 2 (2*Na*mm21)\n # m12: Migration from 2 to 1 (2*Na*m12)\n # mi21: Migration from 1 to 2 in \"islands\" (2*Na*mi21)\n # mi12: Migration from 1 to 2 in \"islands\" (2*Na*mi12)\n # Ts: Time from split to secondary contact, in 2*Na generations\n # Tsc: Time from secondary contact to presesnt, in 2*Na gens\n # p: Porpotion of genome evoloving in \"islands\"\n names = ['N1', 'N2', 'm21', 'm12', 'mi21', 'mi12', 'Ts', 'Tsc', 'p']\n values = [1, 1, 5, 5, 0.5, 0.5, 1, 0.1, 0.5]\n upper_bounds = [20, 20, 30, 30, 5, 5, 10, 2, 0.95]\n lower_bounds = [0.01, 0.01, 0, 0, 0, 0, 0, 0, 0.05]\n params['Names'] = names\n params['Values'] = values\n params['Upper'] = upper_bounds\n params['Lower'] = lower_bounds\n return params","def __init__(self, name, config):\n self.name = name\n self.config = config\n LineBuilder.__init__(self, name, config)\n \n etaprimeppg_name = '{0}EtaPrimePPG'.format(name)\n etaprime3hr_name = '{0}EtaPrime3HR'.format(name)\n \n d2pietaprimeppg_name = '{0}D2PiEtaPrimePPG'.format(name)\n d2pietaprime3hr_name = '{0}D2PiEtaPrime3HR'.format(name)\n \n d2ketaprimeppg_name = '{0}D2KEtaPrimePPG'.format(name)\n d2ketaprime3hr_name = '{0}D2KEtaPrime3HR'.format(name)\n \n self.selEtaPrimePPG = makeResonance(\n etaprimeppg_name,\n config,\n inputSel=[StdAllNoPIDsPions,StdLooseAllPhotons],\n decDescriptors=self.EtaPrimePPG\n )\n \n self.selEtaPrime3HR = makeResonance(\n etaprime3hr_name,\n config,\n inputSel=[StdAllNoPIDsPions,StdLooseResolvedEta],\n decDescriptors=self.EtaPrime3H\n )\n \n self.selD2PiEtaPrimePPG = makeD(\n d2pietaprimeppg_name,\n config,\n inputSel=[self.selEtaPrimePPG, StdAllNoPIDsPions],\n decDescriptors=self.D2PiEtaPrime,\n useBachelorPID=False,\n )\n \n self.selD2KEtaPrimePPG = makeD(\n d2ketaprimeppg_name,\n config,\n inputSel=[self.selEtaPrimePPG, StdAllNoPIDsKaons],\n decDescriptors=self.D2KEtaPrime,\n useBachelorPID=False,\n )\n \n self.selD2PiEtaPrime3HR = makeD(\n d2pietaprime3hr_name,\n config,\n inputSel=[self.selEtaPrime3HR, StdAllNoPIDsPions],\n decDescriptors=self.D2PiEtaPrime,\n useBachelorPID=False, \n )\n \n self.selD2KEtaPrime3HR = makeD(\n d2ketaprime3hr_name,\n config,\n inputSel=[self.selEtaPrime3HR, StdAllNoPIDsKaons],\n decDescriptors=self.D2KEtaPrime,\n useBachelorPID=False,\n )\n \n self.line_D2PiEtaPrimePPG = make_line(\n self,\n name='{0}Line'.format(d2pietaprimeppg_name),\n prescale=config['PrescaleD2PiEtaPrimePPG'],\n postscale=config['PostscaleD2PiEtaPrimePPG'],\n selection=self.selD2PiEtaPrimePPG,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n \n self.line_D2PiEtaPrime3HR = make_line(\n self,\n name='{0}Line'.format(d2pietaprime3hr_name),\n prescale=config['PrescaleD2PiEtaPrime3HR'],\n postscale=config['PostscaleD2PiEtaPrime3HR'],\n selection=self.selD2PiEtaPrime3HR,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n \n self.line_D2KEtaPrimePPG = make_line(\n self,\n name='{0}Line'.format(d2ketaprimeppg_name),\n prescale=config['PrescaleD2KEtaPrimePPG'],\n postscale=config['PostscaleD2KEtaPrimePPG'],\n selection=self.selD2KEtaPrimePPG,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n \n self.line_D2KEtaPrime3HR = make_line(\n self,\n name='{0}Line'.format(d2ketaprime3hr_name),\n prescale=config['PrescaleD2KEtaPrime3HR'],\n postscale=config['PostscaleD2KEtaPrime3HR'],\n selection=self.selD2KEtaPrime3HR,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )","def Parametros_(name_path):\n\n\tp = pathlib.Path(name_path)\n\tZ22 = []\n\tfor f in p.glob('*.csv'):\n\t\tZ = pd.read_csv(f, header = 0)\n\t\tZ = np.array(Z, dtype = np.float64 )\n\t\tZ22.append(Z)\n \n\tA = np.array(Z22)\n \n \n\tZ2 = A[0,:,:]\n\t## Adición de parámetros\n\tV_sys = np.append(Z2[:, 0], Z2[:, 1])\n\tPA = np.append(Z2[:, 2], Z2[:, 3])\n\ti = np.append(Z2[:, 4], Z2[:, 5])\n\n\tx_0 = 4*random.rand(346) + 78\n\ty_0 = 4*random.rand(346) + 78\n\n\tR_0 = 10*random.rand(346) + 5\n\tV_t = 200*random.rand(346) + 50\n\ta = random.rand(346) + 0.5\n\tg = random.rand(346) + 0.5\n\n\tParams_Bek = np.vstack([x_0, y_0, V_sys, i, PA, V_t, R_0, a, g]).T\n\n\tp = [\"x0\", \"y0\", \"v_sys\", \"i\", \"phi_0\", \"V_t\", \"R_0\", \"a\", \"g\"] \n\tfor j in range(len(Params_Bek.T)):\n\t\tsb.displot((Params_Bek.T[j]).ravel(), color='#F2AB6D', bins=10, kde=False)\n\t\tplt.xlabel(p[j])\n\t\tplt.ylabel('Cuentas')\n\t\tplt.show()\n\n\treturn Params_Bek","def sequence_params(self):","def parse(self):","def doParametersOfInterest(self):\n \n self.modelBuilder.doVar('expr::cosW(\"0.87681811112\",)')\n self.modelBuilder.doVar('expr::sinW(\"0.48082221247\",)')\n self.modelBuilder.doVar('expr::mZ(\"91.2\",)')\n self.modelBuilder.doVar('expr::Lambda1(\"100.0\",)')\n self.modelBuilder.doVar('expr::e2(\"0.0917\",)')\n self.modelBuilder.doVar('expr::gs2(\"1.533\",)')\n\n # EFT Higgs basis couplings\n\n self.modelBuilder.doVar('cZ[0,-1,1]') \n self.modelBuilder.doVar(\"cZZ[0,-2,2]\") \n self.modelBuilder.doVar(\"cZZt[0,-2,2]\") \n self.modelBuilder.doVar(\"cZB[0,-6,6]\") \n\n poi='cZ,cZZ,cZZt,cZB'\n\n # Amplitude couplings from EFT couplings \n\n self.modelBuilder.doVar('expr::a1(\"@0+1\",cZ)') # (\"2*(@0+1)\",cZ) in AN/Paper but a1 = 1 for signal model and width calculation\n self.modelBuilder.doVar('expr::a2(\"-1*@0*(@1/(2*pow(@2,2)*pow(@3,2)))\",cZZ,e2,sinW,cosW)')\n self.modelBuilder.doVar('expr::a3(\"-1*@0*(@1/(2*pow(@2,2)*pow(@3,2)))\",cZZt,e2,sinW,cosW)')\n self.modelBuilder.doVar('expr::k1(\"@0*(@1*pow(@2,2)/(pow(@3,2)*pow(@4,2)))\",cZB,e2,Lambda1,sinW,mZ)')\n self.modelBuilder.doVar('expr::k1L1(\"@0/pow(@1,2)\",k1,Lambda1)')\n\n ###### gamma_H ########\n\n # SMEFT relationships for VV couplings (Expressed using amplitude couplings)\n\n self.modelBuilder.doVar('expr::kappa(\"1.0\",)')\n self.modelBuilder.doVar('expr::kappa_tilde(\"0.0\",)') \n\n self.modelBuilder.doVar('expr::a1_WW(\"@0\",a1)')\n self.modelBuilder.doVar('expr::a2_WW(\"@0*@0*@1\",cosW,a2)')\n self.modelBuilder.doVar('expr::a3_WW(\"@0*@0*@1\",cosW,a3)')\n self.modelBuilder.doVar('expr::k1_WW(\"(@2 / (@0*@0 - @1*@1) - 2*@1*@1*@3*@4*@4 /(@5*@5*(@0*@0 - @1*@1)))\",cosW,sinW,k1,a2,Lambda1,mZ)')\n self.modelBuilder.doVar('expr::k2_k1(\"2*@0*@1*@2/(@0*@0 - @1*@1)\",cosW,sinW,k1)')\n self.modelBuilder.doVar('expr::k2_a2(\"-2*@0*@1*@3*@4*@4/((@2*@2)*(@0*@0 - @1*@1))\",cosW,sinW,mZ,a2,Lambda1)')\n self.modelBuilder.doVar('expr::k2(\"@0 + @1\",k2_k1,k2_a2)')\n\n # Determine gamma_H from VV couplings\n\n zz_expr = '\"4*(@0*@0/4. + 0.1695*@3*@3 + 0.09076*@1*@1 + 0.03809*@2*@2 + 0.8095*@0*@3/2. + 0.5046*@0*@1/2. + 0.2092*@1*@3 + 0.1023*@4*@4 + 0.1901*@0*@4/2. + 0.07429*@3*@4 + 0.04710*@1*@4) \",a1,a2,a3,k1,k2'\n ww_expr = '\"4*(@0*@0/4. + 0.1320*@3*@3 + 0.1944*@1*@1 + 0.08075*@2*@2 + 0.7204*@0*@3/2. + 0.7437*@0*@1/2. + 0.2774*@3*@1) \",a1_WW,a2_WW,a3_WW,k1_WW'\n zgamma_expr = '\"4*(1.118600*@0*@0/4. +0.0035*@1*@1 - 0.125010*@0*@1/2. + 0.000003*@1*@1 - 0.00018*@1*@1 + 0.003100*@0*@1/2. +0.00126*@2*@2 + 0.000005*@2*@2 -0.00047*@2*@2)\",a1_WW,kappa,kappa_tilde'\n gg_expr = '\"(1.1068*@0*@0 + 0.0082*@0*@0 - 0.1150*@0*@0 + 2.5717*@1*@1 + 0.0091*@1*@1 - 0.1982*@1*@1)\",kappa,kappa_tilde'\n bb_expr = '\"(@0*@0 + @1*@1)\",kappa,kappa_tilde'\n cc_expr = '\"(@0*@0 + @1*@1)\",kappa,kappa_tilde'\n tautau_expr = '\"(@0*@0 + @1*@1)\",kappa,kappa_tilde'\n mumu_expr = '\"(@0*@0 + @1*@1)\",kappa,kappa_tilde'\n gmgm_expr = '\"4*(1.6054*@0*@0/4. + 0.07312*@1*@1 - 0.6854*@0*@1/2. + 0.00002*@1*@1 - 0.0018*@1*@1 + 0.0085*@0*@1/2. + 0.1699*@2*@2 + 0.00002*@2*@2 - 0.0031*@2*@2)\",a1_WW,kappa,kappa_tilde'\n \n self.modelBuilder.doVar('expr::R_WW('+str(ww_expr)+')')\n self.modelBuilder.doVar('expr::R_ZZ('+str(zz_expr)+')')\n self.modelBuilder.doVar('expr::R_Zgamma('+str(zgamma_expr)+')')\n self.modelBuilder.doVar('expr::R_gg('+str(gg_expr)+')')\n self.modelBuilder.doVar('expr::R_bb('+str(bb_expr)+')')\n self.modelBuilder.doVar('expr::R_cc('+str(cc_expr)+')')\n self.modelBuilder.doVar('expr::R_tautau('+str(tautau_expr)+')')\n self.modelBuilder.doVar('expr::R_mumu('+str(mumu_expr)+')')\n self.modelBuilder.doVar('expr:R_gammagamma('+str(gmgm_expr)+')')\n\n self.modelBuilder.doVar('expr::gammaH(\"(0.5824*@0 + 0.2137*@1 + 0.08187*@2 + 0.06272*@3 + 0.02891*@4 + 0.02619*@5 + 0.002270*@6 + 0.001533*@7 + 0.0002176*@8 )/0.9998\",R_bb,R_WW,R_gg,R_tautau,R_cc,R_ZZ,R_gammagamma,R_Zgamma,R_mumu)') \n\n ###########################\n\n self.g1V = GetCoupTerms(1,1,1,-0.0001,\"1V\") # Compensate for scaling of k1 templates \n self.g2V = GetCoupTerms(1,1,1,-0.0001,\"2V\") \n \n self.modelBuilder.doVar(\"expr::g2V_1(\\\"\"+str(self.g2V[0])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T1(\\\"((pow(@0,4))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_1)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T1_Neg(\\\"-1*((pow(@0,4))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_1)\") \n self.modelBuilder.doVar(\"expr::g2V_2(\\\"\"+str(self.g2V[1])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T2(\\\"((pow(@0,3)*@1)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_2)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T2_Neg(\\\"-1*((pow(@0,3)*@1)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_2)\") \n self.modelBuilder.doVar(\"expr::g2V_3(\\\"\"+str(self.g2V[2])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T3(\\\"((pow(@0,2)*pow(@1,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_3)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T3_Neg(\\\"-1*((pow(@0,2)*pow(@1,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_3)\") \n self.modelBuilder.doVar(\"expr::g2V_4(\\\"\"+str(self.g2V[3])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T4(\\\"((@0*pow(@1,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_4)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T4_Neg(\\\"-1*((@0*pow(@1,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_4)\") \n self.modelBuilder.doVar(\"expr::g2V_5(\\\"\"+str(self.g2V[4])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T5(\\\"((pow(@1,4))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_5)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T5_Neg(\\\"-1*((pow(@1,4))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_5)\") \n self.modelBuilder.doVar(\"expr::g2V_6(\\\"\"+str(self.g2V[5])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T6(\\\"((pow(@0,3)*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_6)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T6_Neg(\\\"-1*((pow(@0,3)*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_6)\") \n self.modelBuilder.doVar(\"expr::g2V_7(\\\"\"+str(self.g2V[6])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T7(\\\"((pow(@0,2)*pow(@2,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_7)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T7_Neg(\\\"-1*((pow(@0,2)*pow(@2,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_7)\") \n self.modelBuilder.doVar(\"expr::g2V_8(\\\"\"+str(self.g2V[7])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T8(\\\"((@0*pow(@2,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_8)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T8_Neg(\\\"-1*((@0*pow(@2,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_8)\") \n self.modelBuilder.doVar(\"expr::g2V_9(\\\"\"+str(self.g2V[8])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T9(\\\"((pow(@2,4))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_9)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T9_Neg(\\\"-1*((pow(@2,4))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_9)\") \n self.modelBuilder.doVar(\"expr::g2V_10(\\\"\"+str(self.g2V[9])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T10(\\\"((pow(@0,3)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_10)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T10_Neg(\\\"-1*((pow(@0,3)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_10)\") \n self.modelBuilder.doVar(\"expr::g2V_11(\\\"\"+str(self.g2V[10])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T11(\\\"((pow(@0,2)*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_11)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T11_Neg(\\\"-1*((pow(@0,2)*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_11)\") \n self.modelBuilder.doVar(\"expr::g2V_12(\\\"\"+str(self.g2V[11])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T12(\\\"((@0*pow(@3,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_12)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T12_Neg(\\\"-1*((@0*pow(@3,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_12)\") \n self.modelBuilder.doVar(\"expr::g2V_13(\\\"\"+str(self.g2V[12])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T13(\\\"((pow(@3,4))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_13)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T13_Neg(\\\"-1*((pow(@3,4))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_13)\") \n self.modelBuilder.doVar(\"expr::g2V_14(\\\"\"+str(self.g2V[13])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T14(\\\"((pow(@1,3)*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_14)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T14_Neg(\\\"-1*((pow(@1,3)*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_14)\") \n self.modelBuilder.doVar(\"expr::g2V_15(\\\"\"+str(self.g2V[14])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T15(\\\"((pow(@1,2)*pow(@2,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_15)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T15_Neg(\\\"-1*((pow(@1,2)*pow(@2,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_15)\") \n self.modelBuilder.doVar(\"expr::g2V_16(\\\"\"+str(self.g2V[15])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T16(\\\"((@1*pow(@2,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_16)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T16_Neg(\\\"-1*((@1*pow(@2,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_16)\") \n self.modelBuilder.doVar(\"expr::g2V_17(\\\"\"+str(self.g2V[16])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T17(\\\"((pow(@1,3)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_17)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T17_Neg(\\\"-1*((pow(@1,3)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_17)\") \n self.modelBuilder.doVar(\"expr::g2V_18(\\\"\"+str(self.g2V[17])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T18(\\\"((pow(@1,2)*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_18)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T18_Neg(\\\"-1*((pow(@1,2)*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_18)\") \n self.modelBuilder.doVar(\"expr::g2V_19(\\\"\"+str(self.g2V[18])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T19(\\\"((@1*pow(@3,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_19)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T19_Neg(\\\"-1*((@1*pow(@3,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_19)\") \n self.modelBuilder.doVar(\"expr::g2V_20(\\\"\"+str(self.g2V[19])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T20(\\\"((pow(@2,3)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_20)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T20_Neg(\\\"-1*((pow(@2,3)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_20)\") \n self.modelBuilder.doVar(\"expr::g2V_21(\\\"\"+str(self.g2V[20])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T21(\\\"((pow(@2,2)*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_21)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T21_Neg(\\\"-1*((pow(@2,2)*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_21)\") \n self.modelBuilder.doVar(\"expr::g2V_22(\\\"\"+str(self.g2V[21])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T22(\\\"((@2*pow(@3,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_22)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T22_Neg(\\\"-1*((@2*pow(@3,3))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_22)\") \n self.modelBuilder.doVar(\"expr::g2V_23(\\\"\"+str(self.g2V[22])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T23(\\\"((@0*@1*pow(@2,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_23)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T23_Neg(\\\"-1*((@0*@1*pow(@2,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_23)\") \n self.modelBuilder.doVar(\"expr::g2V_24(\\\"\"+str(self.g2V[23])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T24(\\\"((@0*pow(@1,2)*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_24)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T24_Neg(\\\"-1*((@0*pow(@1,2)*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_24)\") \n self.modelBuilder.doVar(\"expr::g2V_25(\\\"\"+str(self.g2V[24])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T25(\\\"((pow(@0,2)*@1*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_25)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T25_Neg(\\\"-1*((pow(@0,2)*@1*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_25)\") \n self.modelBuilder.doVar(\"expr::g2V_26(\\\"\"+str(self.g2V[25])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T26(\\\"((@0*@1*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_26)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T26_Neg(\\\"-1*((@0*@1*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_26)\") \n self.modelBuilder.doVar(\"expr::g2V_27(\\\"\"+str(self.g2V[26])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T27(\\\"((@0*pow(@1,2)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_27)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T27_Neg(\\\"-1*((@0*pow(@1,2)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_27)\") \n self.modelBuilder.doVar(\"expr::g2V_28(\\\"\"+str(self.g2V[27])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T28(\\\"((pow(@0,2)*@1*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_28)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T28_Neg(\\\"-1*((pow(@0,2)*@1*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_28)\") \n self.modelBuilder.doVar(\"expr::g2V_29(\\\"\"+str(self.g2V[28])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T29(\\\"((@0*@2*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_29)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T29_Neg(\\\"-1*((@0*@2*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_29)\") \n self.modelBuilder.doVar(\"expr::g2V_30(\\\"\"+str(self.g2V[29])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T30(\\\"((@0*pow(@2,2)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_30)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T30_Neg(\\\"-1*((@0*pow(@2,2)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_30)\") \n self.modelBuilder.doVar(\"expr::g2V_31(\\\"\"+str(self.g2V[30])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T31(\\\"((pow(@0,2)*@2*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_31)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T31_Neg(\\\"-1*((pow(@0,2)*@2*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_31)\") \n self.modelBuilder.doVar(\"expr::g2V_32(\\\"\"+str(self.g2V[31])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T32(\\\"((@1*@2*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_32)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T32_Neg(\\\"-1*((@1*@2*pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_32)\") \n self.modelBuilder.doVar(\"expr::g2V_33(\\\"\"+str(self.g2V[32])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T33(\\\"((@1*pow(@2,2)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_33)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T33_Neg(\\\"-1*((@1*pow(@2,2)*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_33)\") \n self.modelBuilder.doVar(\"expr::g2V_34(\\\"\"+str(self.g2V[33])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T34(\\\"((pow(@1,2)*@2*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_34)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T34_Neg(\\\"-1*((pow(@1,2)*@2*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_34)\") \n self.modelBuilder.doVar(\"expr::g2V_35(\\\"\"+str(self.g2V[34])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T35(\\\"((@0*@1*@2*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_35)\") \n self.modelBuilder.factory_(\"expr::scale_Ewk_T35_Neg(\\\"-1*((@0*@1*@2*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g2V_35)\") \n \n self.modelBuilder.doVar(\"expr::g1V_1(\\\"\"+str(self.g1V[0])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T1(\\\"((pow(@0,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_1)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T1_Neg(\\\"-1*((pow(@0,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_1)\") \n self.modelBuilder.doVar(\"expr::g1V_2(\\\"\"+str(self.g1V[1])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T2(\\\"((@0*@1)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_2)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T2_Neg(\\\"-1*((@0*@1)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_2)\") \n self.modelBuilder.doVar(\"expr::g1V_3(\\\"\"+str(self.g1V[2])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T3(\\\"((pow(@1,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_3)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T3_Neg(\\\"-1*((pow(@1,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_3)\") \n self.modelBuilder.doVar(\"expr::g1V_4(\\\"\"+str(self.g1V[3])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T4(\\\"((@0*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_4)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T4_Neg(\\\"-1*((@0*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_4)\") \n self.modelBuilder.doVar(\"expr::g1V_5(\\\"\"+str(self.g1V[4])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T5(\\\"((pow(@2,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_5)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T5_Neg(\\\"-1*((pow(@2,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_5)\") \n self.modelBuilder.doVar(\"expr::g1V_6(\\\"\"+str(self.g1V[5])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T6(\\\"((@0*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_6)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T6_Neg(\\\"-1*((@0*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_6)\") \n self.modelBuilder.doVar(\"expr::g1V_7(\\\"\"+str(self.g1V[6])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T7(\\\"((pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_7)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T7_Neg(\\\"-1*((pow(@3,2))/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_7)\") \n self.modelBuilder.doVar(\"expr::g1V_8(\\\"\"+str(self.g1V[7])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T8(\\\"((@1*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_8)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T8_Neg(\\\"-1*((@1*@2)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_8)\") \n self.modelBuilder.doVar(\"expr::g1V_9(\\\"\"+str(self.g1V[8])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T9(\\\"((@1*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_9)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T9_Neg(\\\"-1*((@1*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_9)\") \n self.modelBuilder.doVar(\"expr::g1V_10(\\\"\"+str(self.g1V[9])+\"\\\",)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T10(\\\"((@2*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_10)\") \n self.modelBuilder.factory_(\"expr::scale_ggH_T10_Neg(\\\"-1*((@2*@3)/@4)*@5\\\", a1, a2, a3, k1L1, gammaH, g1V_10)\") \n \n self.modelBuilder.doSet(\"POI\",poi)","def lro(self) -> global___Snippet.Lro:","def read_params():\n parser = ArgumentParser(description=\"export2graphlan.py (ver. \" + __version__ +\n \" of \" + __date__ + \"). Convert MetaPhlAn, LEfSe, and/or HUMAnN output to GraPhlAn input format. Authors: \"\n + __author__ + \" (\" + __email__ + \")\")\n\n # input parameters group\n group = parser.add_argument_group(title='input parameters',\n description=\"You need to provide at least one of the two arguments\")\n group.add_argument('-i', '--lefse_input',\n type=str,\n required=False,\n help=\"LEfSe input data. A file that can be given to LEfSe for biomarkers analysis. It can be the result of a \"\n \"MetaPhlAn or HUMAnN analysis\")\n group.add_argument('-o', '--lefse_output',\n type=str,\n required=False,\n help=\"LEfSe output result data. The result of LEfSe analysis performed on the lefse_input file\")\n\n # output parameters group\n group = parser.add_argument_group(title='output parameters')\n group.add_argument('-t', '--tree',\n type=str,\n required=True,\n help=\"Output filename where save the input tree for GraPhlAn\")\n group.add_argument('-a', '--annotation',\n type=str,\n required=True,\n help=\"Output filename where save GraPhlAn annotation\")\n\n # annotations\n parser.add_argument('--annotations',\n default=None,\n type=str,\n required=False,\n help=\"List which levels should be annotated in the tree. Use a comma separate values form, e.g., \"\n \"--annotation_levels 1,2,3. Default is None\")\n parser.add_argument('--external_annotations',\n default=None,\n type=str,\n required=False,\n help=\"List which levels should use the external legend for the annotation. Use a comma separate values form, \"\n \"e.g., --annotation_levels 1,2,3. Default is None\")\n # shaded background\n parser.add_argument('--background_levels',\n default=None,\n type=str,\n required=False,\n help=\"List which levels should be highlight with a shaded background. Use a comma separate values form, e.g., \"\n \"--background_levels 1,2,3. Default is None\")\n parser.add_argument('--background_clades',\n default=None,\n type=str,\n required=False,\n help=\"Specify the clades that should be highlight with a shaded background. Use a comma separate values form \"\n \"and surround the string with \\\" if there are spaces. Example: --background_clades \\\"Bacteria.Actinobacteria, \"\n \"Bacteria.Bacteroidetes.Bacteroidia, Bacteria.Firmicutes.Clostridia.Clostridiales\\\". Default is None\")\n parser.add_argument('--background_colors',\n default=None,\n type=str,\n required=False,\n help=\"Set the color to use for the shaded background. Colors can be either in RGB or HSV (using a semi-colon to \"\n \"separate values, surrounded with ()) format. Use a comma separate values form and surround the string with \"\n \"\\\" if it contains spaces. Example: --background_colors \\\"#29cc36, (150; 100; 100), (280; 80; 88)\\\". Default \"\n \"is None\")\n # title\n parser.add_argument('--title',\n type=str,\n required=False,\n help=\"If specified set the title of the GraPhlAn plot. Surround the string with \\\" if it contains spaces, e.g., \"\n \"--title \\\"Title example\\\"\")\n # title font size\n parser.add_argument('--title_font_size',\n default=15,\n type=int,\n required=False,\n help=\"Set the title font size. Default is 15\")\n # clade size\n parser.add_argument('--def_clade_size',\n default=10.,\n type=float,\n required=False,\n help=\"Set a default size for clades that are not found as biomarkers by LEfSe. Default is 10\")\n parser.add_argument('--min_clade_size',\n default=20.,\n type=float,\n required=False,\n help=\"Set the minimum value of clades that are biomarkers. Default is 20\")\n parser.add_argument('--max_clade_size',\n default=200.,\n type=float,\n required=False,\n help=\"Set the maximum value of clades that are biomarkers. Default is 200\")\n # font size\n parser.add_argument('--def_font_size',\n default=10,\n type=int,\n required=False,\n help=\"Set a default font size. Default is 10\")\n parser.add_argument('--min_font_size',\n default=8,\n type=int,\n required=False,\n help=\"Set the minimum font size to use. Default is 8\")\n parser.add_argument('--max_font_size',\n default=12,\n type=int,\n required=False,\n help=\"Set the maximum font size. Default is 12\")\n # legend font size\n parser.add_argument('--annotation_legend_font_size',\n default=10,\n type=int,\n required=False,\n help=\"Set the font size for the annotation legend. Default is 10\")\n # abundance threshold\n parser.add_argument('--abundance_threshold',\n default=20.,\n type=float,\n required=False,\n help=\"Set the minimun abundace value for a clade to be annotated. Default is 20.0\")\n # ONLY lefse_input provided\n parser.add_argument('--most_abundant',\n default=10,\n type=int,\n required=False,\n help=\"When only lefse_input is provided, you can specify how many clades highlight. Since the biomarkers are \"\n \"missing, they will be chosen from the most abundant. Default is 10\")\n parser.add_argument('--least_biomarkers',\n default=3,\n type=int,\n required=False,\n help=\"When only lefse_input is provided, you can specify the minimum number of biomarkers to extract. The \"\n \"taxonomy is parsed, and the level is choosen in order to have at least the specified number of biomarkers. \"\n \"Default is 3\")\n # decide to keep the OTU id or to merger at the above taxonomic level\n parser.add_argument('--discard_otus',\n default=True,\n action='store_false',\n help=\"If specified the OTU ids will be discarde from the taxonmy. Default is True, i.e. keep OTUs IDs in taxonomy\")\n # decide to keep the OTU id or to merger at the above taxonomic level\n parser.add_argument('--internal_levels',\n default=False,\n action='store_true',\n help=\"If specified sum-up from leaf to root the abundances values. Default is False, i.e. do not sum-up abundances \"\n \"on the internal nodes\")\n\n DataMatrix.input_parameters(parser)\n args = parser.parse_args()\n\n # check if at least one of the input params is given\n if (not args.lefse_input) and (not args.lefse_output):\n raise Exception(\"[read_params()] You must provide at least one of the two input parameters: \")\n\n # check that min_clade_size is less than max_clade_size\n if args.min_clade_size > args.max_clade_size:\n print \"[W] min_clade_size cannot be greater than max_clade_size, assigning their default values\"\n args.min_clade_size = 20.\n args.max_clade_size = 200.\n\n # check that min_font_size is less than max_font_size\n if args.min_font_size > args.max_font_size:\n print \"[W] min_font_size cannot be greater than max_font_size, assigning their default values\"\n args.min_font_size = 8\n args.max_font_size = 12\n\n return args","def preprocess(self):","def parliament(parl):\n\tglobal PARLIAMENT\n\tPARLIAMENT = parl","def __init__(self, source, filenum, linenum, param_list, ops_raw_list, ops_list):\n self.gate_definition = {\n 'source': source,\n 'filenum': filenum,\n 'linenum': linenum,\n 'param_list': param_list,\n 'ops_raw_list': ops_raw_list,\n 'ops_list': ops_list}","def __init__(self):\n mi_parqueo = list()","def __init__(self, r=1, p=3):\n self.p = p\n self.r = r","def __init__(self, espectro, Npicos):\r\n self.Npicos = Npicos\r\n self.spec = espectro.real\r\n self.ppmGridDir = espectro.ppmGridDir\r\n self.ppmGridInd = espectro.ppmGridInd \r\n self.regiones = self.crear_regiones(Npicos)\r\n self.integrales = None","def initParms(self):\n self.parmVal = []\n self.parmName = []\n (nvect, npt) = self.data.shape\n if self.model == 0:\n self.parmVal.append(2.0)\n self.parmName.append('Order')\n if self.model == 1:\n self.parmVal.append(1.0)\n self.parmName.append('A')\n self.parmVal.append(1.0)\n self.parmName.append('B')\n if self.model == 2:\n self.parmVal.append(self.data[1][0])\n self.parmName.append('A')\n self.parmVal.append(self.data[1][npt-1])\n self.parmName.append('B')\n if self.model == 3:\n self.parmVal.append(self.data[1][0])\n self.parmName.append('Ao')\n self.parmVal.append(100.0)\n self.parmName.append('Ea')\n if self.model == 4:\n self.parmVal.append(0.001)\n self.parmName.append('A')\n self.parmVal.append(1.0)\n self.parmName.append('B')\n if self.model == 5:\n self.parmVal.append(0.001)\n self.parmName.append('A')\n self.parmVal.append(0.0)\n self.parmName.append('B')\n self.parmVal.append(1.0)\n self.parmName.append('C')\n if self.model == 6:\n self.parmVal.append(self.data[0][0])\n self.parmName.append('xo')\n self.parmVal.append(self.data[1][0])\n self.parmName.append('yo')\n yspan = getSpan(self.data[1])\n if self.data[1][0] > 0.0:\n v = self.data[1][0] + yspan/2.0\n else:\n v = self.data[1][npt-1] + yspan/2.0\n self.parmVal.append(v)\n self.parmName.append('H')\n if self.data[1][0] > self.data[1][npt-1]:\n self.parmVal.append(-1.0)\n else:\n self.parmVal.append(1.0)\n self.parmName.append('S')","def init_params(self):\n blah","def __init__(self, parameter_set):\n self.parameter_set = parameter_set.to_parameterization('Meijaard2007')","def __init__(self, stage_dir, points=[],lines=[],polygons=[]):\n self.points = points\n self.lines = lines\n self.polygons = polygons\n self.output_ini = stage_dir + \"/osmconf.ini\"","def __init__():\n self.placa = placa","def __init__(self,manager,name):\n Online.DatapointLoader.DatapointLoader.__init__(self,manager,name)\n self.dpName = self.name\n self.activityName = self.dp('Name')\n self.farmInfrastructure = self.dp('Farm.Infrastructure')\n self.farmWorker = self.dp('Farm.Worker')\n self.ctrlInfrastructure = self.dp('Control.Infrastructure')\n self.inputInfrastructure = self.dp('Storage.streamInfrastructure')\n self.inputTypes = self.dp('Storage.streamTypes')\n self.outputInfrastructure = self.dp('Storage.recvInfrastructure')\n self.outputTypes = self.dp('Storage.recvTypes')\n self.addDp(self.reader)","def __init__(self, name, p, a, b, q, gx, gy, oid=None):\n self.name = name\n self.p = p\n self.a = a\n self.b = b\n self.q = q\n self.gx = gx\n self.gy = gy\n self.oid = oid","def schema(self):","def __init__(self):\n self.nombre_roues = 4\n self.nombre_fauteils = 1\n self.moteur = False\n self.volant = True","def define_parameters(parser):\n parser.add_argument(\"--bson\", help=\"If the language supports add bson tags or bson representation to the structure\", action=\"store_true\")\n parser.add_argument(\"--csv\", help=\"If the language supports add CSV tags or CSV representation to the structure\", action=\"store_true\")\n parser.add_argument(\"--db\", help=\"adds db tags to Go structs.\" , action=\"store_true\")\n parser.add_argument(\"--input\", default=\"\", help=\"the path to the input CSV file\",type=str )\n parser.add_argument(\"--input-dir\", default=\"\", help=\"the path to the directory that contains the CSV files to parse\",type=str )\n parser.add_argument(\"--json\", help=\"If the language supports add JSON tags or JSON representation to the structure\", action=\"store_true\")\n parser.add_argument(\"--package\", help=\"sets the package to the correct name for Go structs\", action=\"store_true\")\n parser.add_argument(\"--language\", choices=[LANG_GO], default=LANG_GO, help=\"create language specific data structures\", required=True, type=str)\n parser.add_argument(\"--name\", help=\"name of the data structure being created\", type=str)\n parser.add_argument(\"--output-dir\", help=\"the directory where the generated file should be written. If not provided file will be written to stdout\")\n parser.add_argument(\"--verbose\", help=\"more output during the parsing and creation of the data structures\", action=\"store_true\")","def __init__(self, traindf, params):\n default_args = {\n \"seqin\": 0,\n \"smode\": \"positional\", #site mode\n \"direction\": \"inout\",\n \"positive_cores\" : [],\n \"poscols\": [],\n \"namecol\":\"Name\",\n \"seqcol\":\"Sequence\",\n }\n self.df = traindf\n self.set_attrs(params, default_args)\n if self.smode != \"relative\" and self.smode != \"positional\":\n raise TypeError(\"Smode can only be 'relative' or 'positional'\")\n if self.direction != \"inout\" and self.direction != \"orientation\":\n raise TypeError(\"Direction can only be 'inout' or 'orientation'\")\n if self.direction == \"orientation\" and (\"positive_cores\" not in params or not params[\"positive_cores\"]):\n raise TypeError(\"Positive cores are needed when direction is 'orientation'\")\n\n if self.namecol in self.df:\n fastadict = dict(zip(self.df[self.namecol], self.df[self.seqcol]))\n shapeobj = ds.DNAShape(fastadict)\n else:\n shapeobj = ds.DNAShape(self.df[self.seqcol].tolist())\n self.shapes = {k:getattr(shapeobj,k.lower()) for k in shapeobj.shapetypes}\n # make a dictionary of list instead of nested dictionary since we use this\n # as features\n if self.namecol in self.df:\n namelist = self.df[self.namecol].tolist()\n else:\n namelist = next(iter(self.shapes.values())).keys()\n self.shapes = {k:[v[str(n)] for n in namelist] for k, v in self.shapes.items()}\n if self.direction == \"orientation\":\n ori = Orientation(self.df, {\"positive_cores\":self.positive_cores}).get_feature()\n self.df[\"orientation\"] = [o[\"ori\"] for o in ori]","def _regr_basic():","def get_parameters(self):\n # Get the parameters from the parent class\n params = super(LPEvalSplit, self).get_parameters()\n\n # Add the LP specific parameters\n params.update({\"owa\": self._owa, \"fe_ratio\": self._fe_ratio})\n return params","def default_pypeit_par(cls):\n par = super().default_pypeit_par()\n\n par['rdx']['detnum'] = [(1,2,3)]\n\n # Adjustments to parameters for Keck HIRES\n turn_on = dict(use_biasimage=False, use_overscan=True, overscan_method='median',\n use_darkimage=False, use_illumflat=False, use_pixelflat=False,\n use_specillum=False)\n par.reset_all_processimages_par(**turn_on)\n par['calibrations']['traceframe']['process']['overscan_method'] = 'median'\n\n # Right now we are using the overscan and not biases becuase the\n # standards are read with a different read mode and we don't yet have\n # the option to use different sets of biases for different standards,\n # or use the overscan for standards but not for science frames\n # TODO testing\n par['scienceframe']['process']['use_biasimage'] = False\n par['scienceframe']['process']['use_illumflat'] = False\n par['scienceframe']['process']['use_pixelflat'] = False\n par['calibrations']['standardframe']['process']['use_illumflat'] = False\n par['calibrations']['standardframe']['process']['use_pixelflat'] = False\n # par['scienceframe']['useframe'] ='overscan'\n\n par['calibrations']['slitedges']['edge_thresh'] = 8.0\n par['calibrations']['slitedges']['fit_order'] = 8\n par['calibrations']['slitedges']['max_shift_adj'] = 0.5\n par['calibrations']['slitedges']['trace_thresh'] = 10.\n par['calibrations']['slitedges']['left_right_pca'] = True\n par['calibrations']['slitedges']['length_range'] = 0.3\n par['calibrations']['slitedges']['max_nudge'] = 0.\n par['calibrations']['slitedges']['overlap'] = True\n par['calibrations']['slitedges']['dlength_range'] = 0.25\n\n # These are the defaults\n par['calibrations']['tilts']['tracethresh'] = 15\n par['calibrations']['tilts']['spat_order'] = 3\n par['calibrations']['tilts']['spec_order'] = 5 # [5, 5, 5] + 12*[7] # + [5]\n\n # 1D wavelength solution\n par['calibrations']['wavelengths']['lamps'] = ['ThAr']\n # This is for 1x1 binning. TODO GET BINNING SORTED OUT!!\n par['calibrations']['wavelengths']['rms_threshold'] = 0.50\n par['calibrations']['wavelengths']['sigdetect'] = 5.0\n par['calibrations']['wavelengths']['n_final'] = 4 #[3] + 13 * [4] + [3]\n # This is for 1x1 binning. Needs to be divided by binning for binned data!!\n par['calibrations']['wavelengths']['fwhm'] = 8.0\n # Reidentification parameters\n par['calibrations']['wavelengths']['method'] = 'echelle'\n # TODO: the arxived solution is for 1x1 binning. It needs to be\n # generalized for different binning!\n #par['calibrations']['wavelengths']['reid_arxiv'] = 'vlt_xshooter_vis1x1.fits'\n par['calibrations']['wavelengths']['cc_thresh'] = 0.50\n par['calibrations']['wavelengths']['cc_local_thresh'] = 0.50\n# par['calibrations']['wavelengths']['ech_fix_format'] = True\n # Echelle parameters\n par['calibrations']['wavelengths']['echelle'] = True\n par['calibrations']['wavelengths']['ech_nspec_coeff'] = 4\n par['calibrations']['wavelengths']['ech_norder_coeff'] = 4\n par['calibrations']['wavelengths']['ech_sigrej'] = 3.0\n par['calibrations']['wavelengths']['ech_separate_2d'] = True\n\n # Flats\n par['calibrations']['flatfield']['tweak_slits_thresh'] = 0.90\n par['calibrations']['flatfield']['tweak_slits_maxfrac'] = 0.10\n\n # Extraction\n par['reduce']['skysub']['bspline_spacing'] = 0.6\n par['reduce']['skysub']['global_sky_std'] = False\n # local sky subtraction operates on entire slit\n par['reduce']['extraction']['model_full_slit'] = True\n # Mask 3 edges pixels since the slit is short, insted of default (5,5)\n par['reduce']['findobj']['find_trim_edge'] = [3, 3]\n # Continnum order for determining thresholds\n\n # Sensitivity function parameters\n par['sensfunc']['algorithm'] = 'IR'\n par['sensfunc']['polyorder'] = 11 #[9, 11, 11, 9, 9, 8, 8, 7, 7, 7, 7, 7, 7, 7, 7]\n par['sensfunc']['IR']['telgridfile'] = 'TelFit_MaunaKea_3100_26100_R20000.fits'\n return par","def Parameters():\n\n raise NotImplementedError()","def __init__(self, name, typing, reflection, year):#Taking in parameters\n self.n = name#Assigning variables\n self.t = typing\n self.r = reflection\n self.y = year","def __init__(self):\n self.name = ''\n self.variables = []\n self.assumptions = []\n self.guarantees = []","def create_type_area_object(): \n RefValues()\n RefValues().add_ref_parameter_from_file('DIN_winter', 'D:/Utveckling/g_EKOSTAT_tool/test_data/din_vinter.txt')\n RefValues().add_ref_parameter_from_file('TOTN_winter', 'D:/Utveckling/g_EKOSTAT_tool/test_data/totn_vinter.txt')","def __init__(self, manager, name):\n Online.DatapointLoader.DatapointLoader.__init__(self,manager,name)\n self.strerror = ''\n self.sfName = self.dp('Name')\n self.nodes = self.dp('Nodes')\n self.usedby = self.dp('UsedBy')\n self.setup = self.dp('Activity')\n self.runInfo = self.dp('RunInfo')\n self.writer = self.manager.devWriter()\n self.addDp(self.reader)","def __init__(self, name, config):\n self.name = name\n self.config = config\n LineBuilder.__init__(self, name, config)\n \n phi3hm_name = '{0}Phi3HM'.format(name)\n phi3hr_name = '{0}Phi3HR'.format(name)\n \n d2piphi3hm_name = '{0}D2PiPhi3HM'.format(name)\n d2piphi3hr_name = '{0}D2PiPhi3HR'.format(name)\n \n d2kphi3hm_name = '{0}D2KPhi3HM'.format(name)\n d2kphi3hr_name = '{0}D2KPhi3HR'.format(name)\n \n\n self.selPhi3HM = makeResonance(\n phi3hm_name,\n config,\n inputSel=[StdAllNoPIDsPions,StdLooseMergedPi0],\n decDescriptors=self.Phi3H\n )\n\n self.selPhi3HR = makeResonance(\n phi3hr_name,\n config,\n inputSel=[StdAllNoPIDsPions,StdLooseResolvedPi0],\n decDescriptors=self.Phi3H\n )\n \n self.selD2PiPhi3HM = makeD(\n d2piphi3hm_name,\n config,\n inputSel=[self.selPhi3HM, StdAllNoPIDsPions],\n decDescriptors=self.D2PiPhi,\n useBachelorPID=False,\n )\n \n self.selD2KPhi3HM = makeD(\n d2kphi3hm_name,\n config,\n inputSel=[self.selPhi3HM, StdAllNoPIDsKaons],\n decDescriptors=self.D2KPhi,\n useBachelorPID=False,\n )\n \n self.selD2PiPhi3HR = makeD(\n d2piphi3hr_name,\n config,\n inputSel=[self.selPhi3HR, StdAllNoPIDsPions],\n decDescriptors=self.D2PiPhi,\n useBachelorPID=False,\n )\n \n self.selD2KPhi3HR = makeD(\n d2kphi3hr_name,\n config,\n inputSel=[self.selPhi3HR, StdAllNoPIDsKaons],\n decDescriptors=self.D2KPhi,\n useBachelorPID=False,\n )\n \n self.line_D2PiPhi3HM = make_line(\n self,\n name='{0}Line'.format(d2piphi3hm_name),\n prescale=config['PrescaleD2PiPhi3HM'],\n postscale=config['PostscaleD2PiPhi3HM'],\n selection=self.selD2PiPhi3HM,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n \n self.line_D2PiPhi3HR = make_line(\n self,\n name='{0}Line'.format(d2piphi3hr_name),\n prescale=config['PrescaleD2PiPhi3HR'],\n postscale=config['PostscaleD2PiPhi3HR'],\n selection=self.selD2PiPhi3HR,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n self.line_D2KPhi3HM = make_line(\n self,\n name='{0}Line'.format(d2kphi3hm_name),\n prescale=config['PrescaleD2KPhi3HM'],\n postscale=config['PostscaleD2KPhi3HM'],\n selection=self.selD2KPhi3HM,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n \n self.line_D2KPhi3HR = make_line(\n self,\n name='{0}Line'.format(d2kphi3hr_name),\n prescale=config['PrescaleD2KPhi3HR'],\n postscale=config['PostscaleD2KPhi3HR'],\n selection=self.selD2KPhi3HR,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )","def __init__(self, main_params, projs):\n self.__dict__ = vars(main_params)\n self.projs = projs\n self.proj, self.model, self.var, self.region = (\n self.str_to_aospy_iterable(main_params.proj, main_params.model,\n main_params.var, main_params.region)\n )\n self.run = self.create_child_run_obj(self.model, self.run, self.proj)\n self.region = [aospy.utils.io.dict_name_keys(self.region)]","def parlist(model_info, pars, is2d):\n if is2d:\n exclude = lambda n: False\n else:\n partype = model_info['partype']\n par1d = set(partype['fixed-1d']+partype['pd-1d'])\n exclude = lambda n: n not in par1d\n lines = []\n for p in model_info['parameters']:\n if exclude(p.name): continue\n fields = dict(\n value=pars.get(p.name, p.default),\n pd=pars.get(p.name+\"_pd\", 0.),\n n=int(pars.get(p.name+\"_pd_n\", 0)),\n nsigma=pars.get(p.name+\"_pd_nsgima\", 3.),\n type=pars.get(p.name+\"_pd_type\", 'gaussian'))\n lines.append(_format_par(p.name, **fields))\n return \"\\n\".join(lines)\n\n #return \"\\n\".join(\"%s: %s\"%(p, v) for p, v in sorted(pars.items()))","def add_parameters(params):\n\n items = [\n ('x', 'X manual', ''),\n ('z', 'Z manual', ''),\n ('automatic', 'Automatic', '')\n ]\n\n params.rotation_axis = bpy.props.EnumProperty(\n items = items,\n name = \"Rotation Axis\",\n default = 'automatic'\n )\n\n params.auto_align_extremity = bpy.props.BoolProperty(\n name='auto_align_extremity',\n default=False,\n description=\"Auto Align Extremity Bone\"\n )\n\n params.segments = bpy.props.IntProperty(\n name = 'limb segments',\n default = 2,\n min = 1,\n description = 'Number of segments'\n )\n\n params.bbones = bpy.props.IntProperty(\n name = 'bbone segments',\n default = 10,\n min = 1,\n description = 'Number of segments'\n )\n\n # Setting up extra layers for the FK and tweak\n params.tweak_extra_layers = bpy.props.BoolProperty(\n name = \"tweak_extra_layers\",\n default = True,\n description = \"\"\n )\n\n params.tweak_layers = bpy.props.BoolVectorProperty(\n size = 32,\n description = \"Layers for the tweak controls to be on\",\n default = tuple( [ i == 1 for i in range(0, 32) ] )\n )\n\n # Setting up extra layers for the FK and tweak\n params.fk_extra_layers = bpy.props.BoolProperty(\n name = \"fk_extra_layers\",\n default = True,\n description = \"\"\n )\n\n params.fk_layers = bpy.props.BoolVectorProperty(\n size = 32,\n description = \"Layers for the FK controls to be on\",\n default = tuple( [ i == 1 for i in range(0, 32) ] )\n )","def __init__(self, number, title, paragraphs):\n self.number = number\n self.title = title\n self.paragraphs = []\n for paragraph_lines in paragraphs:\n new_pragraph = Paragraph.Paragraph(paragraph_lines)\n self.paragraphs.append(new_pragraph)","def __init__(self,paramFile='yaml/grism_example.yaml'):\n self.pandeia_params = yaml.load(open(paramFile))\n self.prep_and_run()","def write_parameters(par, version='git-devel'):\n # read template\n file = findpath('sesiflows.seistools') + '/' + 'specfem2d/par-' + version\n with open(file, 'r') as f:\n lines = f.readlines()\n lines[-1] = ' '.join(['1', str(par.NX), '1', str(par.NZ), '1'])\n\n # write parameter file\n file = 'DATA/Par_file'\n _writelines(file, lines)\n setpar('xmin', str(par.XMIN))\n setpar('xmax', str(par.XMAX))\n setpar('nx', str(par.NX))\n setpar('nt', str(par.NT))\n setpar('deltat', str(par.DT))\n setpar('nsources', str(1))\n\n # write interfaces file\n file = 'DATA/interfaces.dat'\n lines = []\n lines.extend('2\\n')\n lines.extend('2\\n')\n lines.extend('%f %f\\n'%(par.XMIN, par.ZMIN))\n lines.extend('%f %f\\n'%(par.XMAX, par.ZMIN))\n lines.extend('2\\n')\n lines.extend('%f %f\\n'%(par.XMIN, par.ZMAX))\n lines.extend('%f %f\\n'%(par.XMAX, par.ZMAX))\n lines.extend(str(par.NZ))\n _writelines(file, lines)","def poseReaderRig(objs,space=1,name=None, nameOverride=0):\n if not pm.pluginInfo(\"poseReader\",q=1,loaded=1):\n pm.loadPlugin(\"poseReader.so\")\n if len(objs)<=0:\n pm.error((\"poseReaderUI: You must select one or more objects to create a poseReader node for!\"),sl=0)\n poses=[]\n # Store created nodes for sel at end\n obj=''\n for obj in objs:\n Obj=pm.util.capitalize(obj)\n # new to maya 6, tho it is a script....\n if name == None:\n pose=pm.createNode(\"poseReader\",n=(\"poseReader_\" + Obj + \"Shape#\"))\n else:\n if nameOverride==0:\n pose=pm.createNode(\"poseReader\",n=(\"poseReader_\" + Obj+name+'Shape'))\n elif nameOverride==1:\n if name[-5:]=='Shape':\n pose=pm.createNode(\"poseReader\",n=name)\n else:\n pose=pm.createNode(\"poseReader\",n=name+'Shape')\n attr=\"worldMatrix\"\n if space == 2:\n attr=\"matrix\"\n\n pm.connectAttr((obj + \".\" + attr),(pose + \".worldMatrixLiveIn\"),f=1)\n xform=pm.listRelatives(pose,p=1)[0]\n pm.connectAttr((xform + \".\" + attr),(pose + \".worldMatrixPoseIn\"),f=1)\n poses.append(xform)\n # Actually store xform for sel.\n # Make a keyable attr people can actually see and use.\n pm.addAttr(pose,ln=\"weight\",k=1)\n pm.connectAttr((pose + \".outWeight\"),(pose + \".weight\"),f=1)\n # Parent to same parent that object has.\n # Very important if using local space.\n parent=pm.listRelatives(obj,p=1)[0]\n if parent != \"\":\n pm.parent(xform,parent)\n # match rotate order of obj\n rotOrder = pm.getAttr(obj+'.rotateOrder')\n xform.attr('rotateOrder').set(rotOrder)\n # Snap xform to same as obj\n pCons=pm.pointConstraint(obj,xform,w=1)\n oCons=pm.orientConstraint(obj,xform,w=1)\n pm.delete(pCons,oCons)\n # Also make up animCurve for animCurve mode\n animCurve=pm.createNode('animCurveUU')\n pm.setKeyframe(animCurve,itt=\"flat\",v=1.0,ott=\"flat\",f=0.0)\n pm.setKeyframe(animCurve,itt=\"spline\",v=0.85,ott=\"spline\",f=0.25)\n pm.setKeyframe(animCurve,itt=\"spline\",v=0.15,ott=\"spline\",f=0.75)\n pm.setKeyframe(animCurve,itt=\"flat\",v=0.0,ott=\"flat\",f=1.0)\n pm.connectAttr((animCurve + \".message\"),(pose + \".msgAnimCurve\"),f=1)\n pm.connectAttr((animCurve + \".output\"),(pose + \".animCurveOutput\"),f=1)\n\n pm.select(poses,r=1)\n # Now if we have more than one pose...connect them up to a multiTrigger node\n nPoses=len(poses)\n if nPoses>1:\n trig=pm.createNode(\"multiTrigger\")\n # Make a keyable attr people can actually see and use.\n pm.addAttr(trig,ln=\"weight\",k=1)\n pm.connectAttr((trig + \".outWeight\"),(trig + \".weight\"),f=1)\n i=0\n for i in range(0,nPoses):\n pm.connectAttr((poses[i] + \".weight\"),(trig + \".inputValues[\" + str(i) + \"]\"),f=1)\n pm.select(poses,trig,r=1)\n return pose","def load(self, p):\n return","def __init__(self):\n Page.__init__(self, u\"Paraboloide Elíptico<br><br>F(x,y)=(x, y, x<sup>2</sup>/a<sup>2</sup> + y<sup>2</sup>/b<sup>2</sup>)\")\n\n z = 0.5\n par = RevolutionPlot3D(lambda r, t: r ** 2 + z, (0, 1), (0, 2 * pi))\n\n x, y, z2, u, v, cose, sen, t = createVars(['x', 'y', 'z', 'u', 'v', 'cos', 'sen', 't'])\n\n mesh1 = Plot3D(lambda x, y, h: h * (x ** 2 + y ** 2 + z - .01), (-1, 1), (-1, 1))\n mesh1.addEqn(x**2+y**2 - z2**2 == 1)\n mesh1.addFunction(lambda x, y, h: h * (x ** 2 + y ** 2 + z + .01))\n mesh1.setLinesVisible(True)\n mesh1.setMeshVisible(False)\n mesh1.setBoundingBox(zrange=(-1, 1.5))\n par.setAmbientColor(_1(145, 61, 74))\n par.setDiffuseColor(_1(145, 61, 74))\n par.setSpecularColor(_1(145, 61, 74))\n baseplane = BasePlane()\n baseplane.setHeight(0)\n baseplane.setRange((-2, 2, 7))\n\n self.addChild(par)\n self.addChild(mesh1)\n self.addChild(baseplane)","def load_standard_parameters(self):\n paradic = {'x':'0',\n 'y':'0',\n 'n_oct':'8',\n 'n_spo':'3',\n 'sigma_min':'0.8',\n 'delta_min':'0.5',\n 'sigma_in':'0.5',\n 'C_DoG':'0.015',\n 'C_edge':'10',\n 'n_bins':'36',\n 'lambda_ori':'1.5',\n 't':'0.8',\n 'n_hist':'4',\n 'n_ori':'8',\n 'lambda_descr':'6',\n 'flag_match':'1',\n 'C_match':'0.6'}\n self.cfg['param']['paradic'] = paradic\n self.cfg.save()","def __init__(self, p1_proba=0.5):\n self.p1_proba = p1_proba","def __init__(self, path):\n # load ptv_par\n ptvParams = par.PtvParams(path=path)\n ptvParams.read()\n self.n_img = ptvParams.n_img\n\n # load cal_ori\n calOriParams = par.CalOriParams(self.n_img, path=path)\n calOriParams.read()\n\n for i in range(self.n_img):\n self.oriEditors.append(\n oriEditor(calOriParams.img_ori[i])\n )","def attributes(self):","def __init__(self):\n\n # The object is already initialised.\n if self._initialised: return\n\n # Execute the base class __init__ method.\n Param_list.__init__(self)\n\n # Add the model variables.\n self._add_model_info()\n\n # Add the base data.\n self._add_align_data()\n\n # Add the parameters of all models.\n self._add(\n 'pivot_x',\n scope = 'global',\n units = 'Angstrom',\n desc = 'The pivot point position x coordinate',\n py_type = float,\n set = 'params',\n scaling = 1e2,\n grid_lower = pivot_x_lower,\n grid_upper = pivot_x_upper,\n err = True,\n sim = True\n )\n self._add(\n 'pivot_y',\n scope = 'global',\n units = 'Angstrom',\n desc = 'The pivot point position y coordinate',\n py_type = float,\n set = 'params',\n scaling = 1e2,\n grid_lower = pivot_y_lower,\n grid_upper = pivot_y_upper,\n err = True,\n sim = True\n )\n self._add(\n 'pivot_z',\n scope = 'global',\n units = 'Angstrom',\n desc = 'The pivot point position z coordinate',\n py_type = float,\n set = 'params',\n scaling = 1e2,\n grid_lower = pivot_z_lower,\n grid_upper = pivot_z_upper,\n err = True,\n sim = True\n )\n self._add(\n 'ave_pos_x',\n scope = 'global',\n units = 'Angstrom',\n desc = 'The average position x translation',\n py_type = float,\n set = 'params',\n grid_lower = -5,\n grid_upper = 5,\n err = True,\n sim = True\n )\n self._add(\n 'ave_pos_y',\n scope = 'global',\n units = 'Angstrom',\n desc = 'The average position y translation',\n py_type = float,\n set = 'params',\n grid_lower = -5,\n grid_upper = 5,\n err = True,\n sim = True\n )\n self._add(\n 'ave_pos_z',\n scope = 'global',\n units = 'Angstrom',\n desc = 'The average position z translation',\n py_type = float,\n set = 'params',\n grid_lower = -5,\n grid_upper = 5,\n err = True,\n sim = True\n )\n self._add(\n 'ave_pos_alpha',\n scope = 'global',\n units = 'rad',\n desc = 'The average position alpha Euler angle',\n py_type = float,\n set = 'params',\n grid_lower = 0.0,\n grid_upper = angle_upper_excluding_bound,\n err = True,\n sim = True\n )\n self._add(\n 'ave_pos_beta',\n scope = 'global',\n units = 'rad',\n desc = 'The average position beta Euler angle',\n py_type = float,\n set = 'params',\n grid_lower = 0.0,\n grid_upper = pi,\n err = True,\n sim = True\n )\n self._add(\n 'ave_pos_gamma',\n scope = 'global',\n units = 'rad',\n desc = 'The average position gamma Euler angle',\n py_type = float,\n set = 'params',\n grid_lower = 0.0,\n grid_upper = angle_upper_excluding_bound,\n err = True,\n sim = True\n )\n self._add(\n 'eigen_alpha',\n scope = 'global',\n units = 'rad',\n desc = 'The Eigenframe alpha Euler angle',\n py_type = float,\n set = 'params',\n grid_lower = 0.0,\n grid_upper = angle_upper_excluding_bound,\n err = True,\n sim = True\n )\n self._add(\n 'eigen_beta',\n scope = 'global',\n units = 'rad',\n desc = 'The Eigenframe beta Euler angle',\n py_type = float,\n set = 'params',\n grid_lower = 0.0,\n grid_upper = pi,\n err = True,\n sim = True\n )\n self._add(\n 'eigen_gamma',\n scope = 'global',\n units = 'rad',\n desc = 'The Eigenframe gamma Euler angle',\n py_type = float,\n set = 'params',\n grid_lower = 0.0,\n grid_upper = angle_upper_excluding_bound,\n err = True,\n sim = True\n )\n self._add(\n 'axis_theta',\n scope = 'global',\n units = 'rad',\n desc = 'The cone axis polar angle (for the isotropic cone model)',\n py_type = float,\n set = 'params',\n grid_lower = 0.0,\n grid_upper = pi,\n err = True,\n sim = True\n )\n self._add(\n 'axis_phi',\n scope = 'global',\n units = 'rad',\n desc = 'The cone axis azimuthal angle (for the isotropic cone model)',\n py_type = float,\n set = 'params',\n grid_lower = 0.0,\n grid_upper = angle_upper_excluding_bound,\n err = True,\n sim = True\n )\n self._add(\n 'axis_alpha',\n scope = 'global',\n units = 'rad',\n desc = 'The rotor axis alpha angle (the rotation angle out of the xy plane)',\n py_type = float,\n set = 'params',\n grid_lower = -pi,\n grid_upper = axis_alpha_upper,\n err = True,\n sim = True\n )\n self._add(\n 'cone_theta_x',\n scope = 'global',\n units = 'rad',\n desc = 'The pseudo-ellipse cone opening half-angle for the x-axis',\n py_type = float,\n set = 'params',\n grid_lower = cone_angle_lower,\n grid_upper = cone_angle_upper,\n err = True,\n sim = True\n )\n self._add(\n 'cone_theta_y',\n scope = 'global',\n units = 'rad',\n desc = 'The pseudo-ellipse cone opening half-angle for the y-axis',\n py_type = float,\n set = 'params',\n grid_lower = cone_angle_lower,\n grid_upper = cone_angle_upper,\n err = True,\n sim = True\n )\n self._add(\n 'cone_theta',\n scope = 'global',\n units = 'rad',\n desc = 'The isotropic cone opening half-angle',\n py_type = float,\n set = 'params',\n grid_lower = cone_angle_lower,\n grid_upper = cone_angle_upper,\n err = True,\n sim = True\n )\n self._add(\n 'cone_s1',\n scope = 'global',\n units = '',\n desc = 'The isotropic cone order parameter',\n py_type = float,\n set = 'params',\n grid_lower = -0.125,\n grid_upper = 1.0,\n err = True,\n sim = True\n )\n self._add(\n 'cone_sigma_max',\n scope = 'global',\n units = 'rad',\n desc = 'The torsion angle',\n py_type = float,\n set = 'params',\n grid_lower = cone_angle_lower,\n grid_upper = cone_angle_upper,\n err = True,\n sim = True\n )\n\n # Add minimisation structures.\n self._add_min_data(min_stats_global=True)\n\n # Set up the user function documentation.\n self._set_uf_title(\"Frame order parameters\")\n self._uf_param_table(label=\"table: frame order parameters\", caption=\"Frame order parameters.\", scope='global')\n self._uf_param_table(label=\"table: frame order parameter value setting with defaults\", caption=\"Frame order parameter value setting.\", scope='global', default=True)","def init_params() -> Tuple[TeamDict, int, int, int, str, str, List[str]]:\n with io.open('dados.txt', 'r', encoding='utf-8') as params:\n params_strategies = {}\n PARAMS_LEAGUES, STAKE, PATH, RISK_UPPER, RISK_LOWER, j = [], 0, '', 0, 0, 0\n global_vars = [STAKE, RISK_UPPER, RISK_LOWER, PATH, PARAMS_LEAGUES]\n for i, line in enumerate(params.readlines()):\n line = line.strip(\" \\n\")\n if i <= 24:\n if '*' in line:\n if i == 0:\n pass\n else:\n params_strategies[strategy[:-1]] = params_strategy #dict of dicts\n params_strategy = {} #dict \n strategy = line #key of params_strategies\n params_strategy['name'] = strategy[:-1]\n \n else:\n params_strategy[line.split(':')[0]] = float(line.split(':')[1])\n if i == 24:\n params_strategies[strategy[:-1]] = params_strategy\n\n else:\n if '$' in line:\n j += 1\n continue\n if j < 4:\n global_vars[j-1] = float(line)/100 #stake, risk_upper, risk_lower\n elif j == 4:\n global_vars[j-1] = str(line) #path\n else:\n global_vars[4].append(line) #param_leagues\n \n params_strategies['e11'] = params_strategies['e1']\n return (params_strategies, global_vars[0], global_vars[1], global_vars[2], global_vars[3], global_vars[4])","def __init__(self,manager,name):\n Online.DatapointLoader.DatapointLoader.__init__(self,manager,name)\n self.dpName = self.name\n self.inuse = self.dp('InUse')\n self.slice = self.dp('FSMSlice')\n self.info = self.dp('RunInfo')\n self.addDp(self.reader)","def read_from_pln(self, path):\n\n # Read the .pln file contents to a dictionary.\n pln_dict = read_pln_file(path)\n\n # Look for each attribute listed in self.attributes in the results\n # dictionary.\n for attr in self.attributes:\n\n # Get the corresponding ExoParameter object.\n current = getattr(self, attr)\n\n # Look for this attribute in the results dictionary and set\n # ExoParameter.value.\n key_str = attr\n try:\n current.value = pln_dict[key_str]\n del pln_dict[key_str]\n except KeyError:\n current.value = current.default\n\n # Look for reference and URL information in the results dictionary,\n # and use this to set ExoParameter.reference and ExoParameter.url.\n # Skip 'transit' since 'transitref' and 'transiturl', are separate\n # fields in the references section.\n if not attr == \"transit\":\n\n key_str = \"\".join([attr, \"ref\"])\n try:\n current.reference = pln_dict[key_str]\n del pln_dict[key_str]\n except KeyError:\n current.reference = None\n\n key_str = \"\".join([attr, \"url\"])\n try:\n current.url = pln_dict[key_str]\n del pln_dict[key_str]\n except KeyError:\n current.url = None\n\n # If this attribute can take uncertainty values, look for these in\n # the results dictionary, then set ExoParameter.uncertainty and\n # ExoParameter.uncertainty_upper.\n if current.uncertain_flag:\n\n key_str = \"\".join([\"u\", attr])\n try:\n current.uncertainty = pln_dict[key_str]\n del pln_dict[key_str]\n except KeyError:\n current.uncertainty = None\n\n key_str = \"\".join([\"u\", attr, \"d\"])\n try:\n current.uncertainty_upper = pln_dict[key_str]\n del pln_dict[key_str]\n except KeyError:\n current.uncertainty_upper = None\n\n # If there are still keyword / value pairs in pln_dict, these fields\n # are not in the self.attributes list, which is built from\n # self.template_file.\n \"\"\"\n if len(pln_dict.keys()) > 0:\n print(\"{0} contains unknown .pln fields: {1}\".format(\n path, pln_dict.keys()))\n print(\"Add fields to {0} to include.\".format(self.template_file))\n \"\"\"\n\n # Trigger uncertainty calculations.\n self._populate_uncertainties()","def __init__(**params):","def properties(self):","def properties(self):","def properties(self):","def para_loader(self, stdpath=True):\n if stdpath is True:\n path = self.lineEdit_params.text()\n else:\n path = \"./data/parameters/parameters_blur.pcl\"\n self.lineEdit_params.setText(path)\n\n file = open(path, 'rb')\n loaded_p_list = pickle.load(file)\n file.close()\n counter = 0\n\n radio_is_image = self.radioButton_circle.isChecked()\n\n if radio_is_image:\n self.radioButton_image.setChecked(True)\n\n for clazz in SliderClass.all_sliders:\n\n # ## if you added a new sliderclass and want to load your old parameters, you can use this little hack\n # classname = 'linefinder'\n # #print(loaded_p_list[counter])\n # #print(f\"the latest keyword = {clazz.keyword}\")\n # if clazz.keyword == [classname]:\n # warnings.warn(\"parameters are messed up! save new ones\")\n # break\n\n try:\n clazz.settr(loaded_p_list[counter])\n counter += 1\n if clazz.radio_image is not None:\n clazz._params_circle = loaded_p_list[counter]\n counter += 1\n except IndexError:\n # again a small hack for when you add an extra element to the class and this is not yet implemented\n # in your parameter saves.\n warnings.warn(\"parameters are messed up! save new ones\")\n counter += 1\n print(f\"should be morph: {loaded_p_list[counter]}\")\n # in the save, manually set the morph_state as the final thing to load in\n self.morph_state = loaded_p_list[counter]\n self.checkBox_morph.setChecked(self.morph_state[0][0])\n self.textEdit_morph.setText(self.morph_state[0][1])\n\n self.coords = loaded_p_list[counter + 1]\n self.checkBox_segment.setChecked(loaded_p_list[counter + 2])\n self.lineEdit_coords.setText(str(self.coords))\n radio_is_circle = loaded_p_list[counter + 3]\n\n if radio_is_circle:\n self.radioButton_circle.setChecked(True)\n self.radioButton_circle.click()","def _init_parameters(self,diameterInd):\n\n\t\t# topological parameters\n\t\tself.nNodes = 21\n\t\tself._axonNodes=self.nNodes\n\t\tself._paraNodes1=40\n\t\tself._paraNodes2=40\n\t\tself._axonInter=120\n\t\tself._axonTotal=221\n\t\t# morphological parameters\n\t\tpossibleDiameters = [5.7, 7.3, 8.7, 10.0, 11.5, 12.8, 14.0, 15.0, 16.0]\n\t\tself._fiberD=possibleDiameters[diameterInd]\n\t\tself._paraLength1=3 \n\t\tself._nodeLength=1.0\n\t\tself._spaceP1=0.002 \n\t\tself._spaceP2=0.004\n\t\tself._spaceI=0.004\n\t\t# electrical parameters\n\t\tself._rhoa=0.7e6 #Ohm-um\n\t\tself._mycm=0.1 #uF/cm2/lamella membrane\n\t\tself._mygm=0.001 #S/cm2/lamella membrane\n\n\t\tif self._fiberD==5.7:\n\t\t\tself._g=0.605 \n\t\t\tself._axonD=3.4\n\t\t\tself._nodeD=1.9\n\t\t\tself._paraD1=1.9\n\t\t\tself._paraD2=3.4\n\t\t\tself._deltax=500\n\t\t\tself._paraLength2=35\n\t\t\tself._nl=80\n\t\tif self._fiberD==8.7:\n\t\t\tself._g=0.661\n\t\t\tself._axonD=5.8\n\t\t\tself._nodeD=2.8\n\t\t\tself._paraD1=2.8\n\t\t\tself._paraD2=5.8\n\t\t\tself._deltax=1000\n\t\t\tself._paraLength2=40\n\t\t\tself._nl=110\n\t\tif self._fiberD==10.0:\n\t\t\tself._g=0.690\n\t\t\tself._axonD=6.9\n\t\t\tself._nodeD=3.3\n\t\t\tself._paraD1=3.3\n\t\t\tself._paraD2=6.9\n\t\t\tself._deltax=1150\n\t\t\tself._paraLength2=46\n\t\t\tself._nl=120\n\t\tif self._fiberD==11.5:\n\t\t\tself._g=0.700\n\t\t\tself._axonD=8.1\n\t\t\tself._nodeD=3.7\n\t\t\tself._paraD1=3.7\n\t\t\tself._paraD2=8.1\n\t\t\tself._deltax=1250\n\t\t\tself._paraLength2=50\n\t\t\tself._nl=130\n\t\tif self._fiberD==12.8:\n\t\t\tself._g=0.719\n\t\t\tself._axonD=9.2\n\t\t\tself._nodeD=4.2\n\t\t\tself._paraD1=4.2\n\t\t\tself._paraD2=9.2\n\t\t\tself._deltax=1350\n\t\t\tself._paraLength2=54\n\t\t\tself._nl=135\n\t\tif self._fiberD==14.0:\n\t\t\tself._g=0.739\n\t\t\tself._axonD=10.4\n\t\t\tself._nodeD=4.7\n\t\t\tself._paraD1=4.7\n\t\t\tself._paraD2=10.4\n\t\t\tself._deltax=1400\n\t\t\tself._paraLength2=56\n\t\t\tself._nl=140\n\t\tif self._fiberD==15.0:\n\t\t\tself._g=0.767\n\t\t\tself._axonD=11.5\n\t\t\tself._nodeD=5.0\n\t\t\tself._paraD1=5.0\n\t\t\tself._paraD2=11.5\n\t\t\tself._deltax=1450\n\t\t\tself._paraLength2=58\n\t\t\tself._nl=145\n\t\tif self._fiberD==16.0:\n\t\t\tself._g=0.791\n\t\t\tself._axonD=12.7\n\t\t\tself._nodeD=5.5\n\t\t\tself._paraD1=5.5\n\t\t\tself._paraD2=12.7\n\t\t\tself._deltax=1500\n\t\t\tself._paraLength2=60\n\t\t\tself._nl=150\n\n\t\tself._Rpn0=(self._rhoa*.01)/(np.pi*((((self._nodeD/2)+self._spaceP1)**2)-((self._nodeD/2)**2)))\n\t\tself._Rpn1=(self._rhoa*.01)/(np.pi*((((self._paraD1/2)+self._spaceP1)**2)-((self._paraD1/2)**2)))\n\t\tself._Rpn2=(self._rhoa*.01)/(np.pi*((((self._paraD2/2)+self._spaceP2)**2)-((self._paraD2/2)**2)))\n\t\tself._Rpx=(self._rhoa*.01)/(np.pi*((((self._axonD/2)+self._spaceI)**2)-((self._axonD/2)**2)))\n\t\tself._interLength=(self._deltax-self._nodeLength-(2*self._paraLength1)-(2*self._paraLength2))/6","def load_cls_params(self):\n with open('models/Final/linear_svc.p', 'rb') as model_file:\n model = pickle.load(model_file)\n self.svc = model['svc']\n self.X_scaler = model['X_scaler']\n self.parameters = model['parameters']\n\n print(self.parameters)","def __init__(self):\r\n\t\tself.label = \"Linked Data Batch No Functional Property Merge\"\r\n\t\tself.description = \"\"\"The related seperated tables from Linked Data Location Entities Property Enrichment Tool have multivalue for each wikidata location because the coresponding property is not functional property. \r\n\t\tThis Tool helps user to merge these multivalue to a single record and add it to original feature class sttribute table by using merge rules which are specified by users.\"\"\"\r\n\t\tself.canRunInBackground = False","def test_meta(self):\n self.assertEqual([\"test\", [[\"c1\", \"INT\"], [\"c2\", \"VARCHAR(200)\"]], \"returns\", \"union\"],\n grammar._PROCEDURE_COMMENT_FORMAT.parseString(\"test(c1 INT, c2 VARCHAR(200)); returns union\").asList())\n self.assertEqual([\"returns\", \"union\"],\n grammar._PROCEDURE_COMMENT_FORMAT.parseString(\"returns union\").asList())","def __init__(self, rouge_types):\n\n self.rouge_types = rouge_types","def __init__(self, name, config):\n self.name = name\n self.config = config\n LineBuilder.__init__(self, name, config)\n \n etappg_name = '{0}EtaPPG'.format(name)\n eta3hr_name = '{0}Eta3HR'.format(name)\n eta3hm_name = '{0}Eta3HM'.format(name)\n \n d2pietappg_name = '{0}D2PiEtaPPG'.format(name)\n d2pieta3hr_name = '{0}D2PiEta3HR'.format(name)\n d2pieta3hm_name = '{0}D2PiEta3HM'.format(name)\n \n d2ketappg_name = '{0}D2KEtaPPG'.format(name)\n d2keta3hr_name = '{0}D2KEta3HR'.format(name)\n d2keta3hm_name = '{0}D2KEta3HM'.format(name)\n\n self.selEtaPPG = makeResonance(\n etappg_name,\n config,\n inputSel=[StdAllNoPIDsPions,StdLooseAllPhotons],\n decDescriptors=self.EtaPPG\n )\n\n self.selEta3HR = makeResonance(\n eta3hr_name,\n config,\n inputSel=[StdAllNoPIDsPions,StdLooseResolvedPi0],\n decDescriptors=self.Eta3H\n )\n\n self.selEta3HM = makeResonance(\n eta3hm_name,\n config,\n inputSel=[StdAllNoPIDsPions,StdLooseMergedPi0],\n decDescriptors=self.Eta3H\n )\n\n self.selD2PiEtaPPG = makeD(\n d2pietappg_name,\n config,\n inputSel=[self.selEtaPPG, StdAllNoPIDsPions],\n decDescriptors=self.D2PiEta,\n useBachelorPID=False,\n )\n\n self.selD2KEtaPPG = makeD(\n d2ketappg_name,\n config,\n inputSel=[self.selEtaPPG, StdAllNoPIDsKaons],\n decDescriptors=self.D2KEta,\n useBachelorPID=False,\n )\n \n self.selD2PiEta3HR = makeD(\n d2pieta3hr_name,\n config,\n inputSel=[self.selEta3HR, StdAllNoPIDsPions],\n decDescriptors=self.D2PiEta,\n useBachelorPID=False,\n )\n\n self.selD2KEta3HR = makeD(\n d2keta3hr_name,\n config,\n inputSel=[self.selEta3HR, StdAllNoPIDsKaons],\n decDescriptors=self.D2KEta,\n useBachelorPID=False,\n )\n \n self.selD2PiEta3HM = makeD(\n d2pieta3hm_name,\n config,\n inputSel=[self.selEta3HM, StdAllNoPIDsPions],\n decDescriptors=self.D2PiEta,\n useBachelorPID=False,\n )\n \n\n self.selD2KEta3HM = makeD(\n d2keta3hm_name,\n config,\n inputSel=[self.selEta3HM, StdAllNoPIDsKaons],\n decDescriptors=self.D2KEta,\n useBachelorPID=False,\n )\n \n\n self.line_D2PiEtaPPG = make_line(\n self,\n name='{0}Line'.format(d2pietappg_name),\n prescale=config['PrescaleD2PiEtaPPG'],\n postscale=config['PostscaleD2PiEtaPPG'],\n selection=self.selD2PiEtaPPG,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n\n self.line_D2PiEta3HM = make_line(\n self,\n name='{0}Line'.format(d2pieta3hm_name),\n prescale=config['PrescaleD2PiEta3HM'],\n postscale=config['PostscaleD2PiEta3HM'],\n selection=self.selD2PiEta3HM,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n\n self.line_D2PiEta3HR = make_line(\n self,\n name='{0}Line'.format(d2pieta3hr_name),\n prescale=config['PrescaleD2PiEta3HR'],\n postscale=config['PostscaleD2PiEta3HR'],\n selection=self.selD2PiEta3HR,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n\n self.line_D2KEtaPPG = make_line(\n self,\n name='{0}Line'.format(d2ketappg_name),\n prescale=config['PrescaleD2KEtaPPG'],\n postscale=config['PostscaleD2KEtaPPG'],\n selection=self.selD2KEtaPPG,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n \n self.line_D2KEta3HM = make_line(\n self,\n name='{0}Line'.format(d2keta3hm_name),\n prescale=config['PrescaleD2KEta3HM'],\n postscale=config['PostscaleD2KEta3HM'],\n selection=self.selD2KEta3HM,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )\n \n self.line_D2KEta3HR = make_line(\n self,\n name='{0}Line'.format(d2keta3hr_name),\n prescale=config['PrescaleD2KEta3HR'],\n postscale=config['PostscaleD2KEta3HR'],\n selection=self.selD2KEta3HR,\n HLT1=config['Hlt1Filter'],\n HLT2=config['Hlt2Filter']\n )","def updateParameters(self, parameters):\r\n\t\tin_wikiplace_IRI = parameters[0]\r\n\t\tin_relation_degree = parameters[1]\r\n\t\tin_first_property_dir = parameters[2]\r\n\t\tin_first_property = parameters[3]\r\n\t\tin_second_property_dir = parameters[4]\r\n\t\tin_second_property = parameters[5]\r\n\t\tin_third_property_dir = parameters[6]\r\n\t\tin_third_property = parameters[7]\r\n\t\tin_fourth_property_dir = parameters[8]\r\n\t\tin_fourth_property = parameters[9]\r\n\t\tout_location = parameters[10]\r\n\t\tout_table_name = parameters[11]\r\n\t\tout_points_name = parameters[12]\r\n\r\n\t\t\r\n\r\n\t\tif in_relation_degree.altered:\r\n\t\t\trelationDegree = int(in_relation_degree.valueAsText)\r\n\t\t\tif relationDegree == 1:\r\n\t\t\t\tin_first_property.enabled = True\r\n\t\t\t\tin_first_property_dir.enabled = True\r\n\t\t\t\tin_second_property.enabled = False\r\n\t\t\t\tin_second_property_dir.enabled = False\r\n\t\t\t\tin_third_property.enabled = False\r\n\t\t\t\tin_third_property_dir.enabled = False\r\n\t\t\t\tin_fourth_property.enabled = False\r\n\t\t\t\tin_fourth_property_dir.enabled = False\r\n\t\t\telif relationDegree == 2:\r\n\t\t\t\tin_first_property.enabled = True\r\n\t\t\t\tin_first_property_dir.enabled = True\r\n\t\t\t\tin_second_property.enabled = True\r\n\t\t\t\tin_second_property_dir.enabled = True\r\n\t\t\t\tin_third_property.enabled = False\r\n\t\t\t\tin_third_property_dir.enabled = False\r\n\t\t\t\tin_fourth_property.enabled = False\r\n\t\t\t\tin_fourth_property_dir.enabled = False\r\n\t\t\telif relationDegree == 3:\r\n\t\t\t\tin_first_property.enabled = True\r\n\t\t\t\tin_first_property_dir.enabled = True\r\n\t\t\t\tin_second_property.enabled = True\r\n\t\t\t\tin_second_property_dir.enabled = True\r\n\t\t\t\tin_third_property.enabled = True\r\n\t\t\t\tin_third_property_dir.enabled = True\r\n\t\t\t\tin_fourth_property.enabled = False\r\n\t\t\t\tin_fourth_property_dir.enabled = False\r\n\t\t\telif relationDegree == 4:\r\n\t\t\t\tin_first_property.enabled = True\r\n\t\t\t\tin_first_property_dir.enabled = True\r\n\t\t\t\tin_second_property.enabled = True\r\n\t\t\t\tin_second_property_dir.enabled = True\r\n\t\t\t\tin_third_property.enabled = True\r\n\t\t\t\tin_third_property_dir.enabled = True\r\n\t\t\t\tin_fourth_property.enabled = True\r\n\t\t\t\tin_fourth_property_dir.enabled = True\r\n\t\t\r\n\t\t\tif in_wikiplace_IRI.value:\r\n\t\t\t\tinputFeatureClassName = in_wikiplace_IRI.valueAsText\r\n\t\t\t\tlastIndexOFGDB = inputFeatureClassName.rfind(\"\\\\\")\r\n\t\t\t\tfeatureClassName = inputFeatureClassName[(lastIndexOFGDB+1):]\r\n\t\t\t\tcurrentWorkspace = inputFeatureClassName[:lastIndexOFGDB]\r\n\r\n\t\t\t\tarcpy.env.workspace = currentWorkspace\r\n\t\t\t\tout_location.value = currentWorkspace\r\n\r\n\t\t\t\tout_table_name.value = featureClassName + \"PathQueryTripleStore\"\r\n\r\n\t\t\t\tout_points_name.value = featureClassName + \"PathQueryLocation\"\r\n\r\n\r\n\t\t\t\toutLocation = out_location.valueAsText\r\n\t\t\t\toutTableName = out_table_name.valueAsText\r\n\t\t\t\toutputTableName = os.path.join(outLocation,outTableName)\r\n\t\t\t\tif arcpy.Exists(outputTableName):\r\n\t\t\t\t\tarcpy.AddError(\"The output table already exists in current workspace!\")\r\n\t\t\t\t\traise arcpy.ExecuteError\r\n\r\n\t\t\t\toutFeatureClassName = out_points_name.valueAsText\r\n\t\t\t\toutputFeatureClassName = os.path.join(outLocation,outFeatureClassName)\r\n\t\t\t\tif arcpy.Exists(outputFeatureClassName):\r\n\t\t\t\t\tarcpy.AddError(\"The output Feature Class already exists in current workspace!\")\r\n\t\t\t\t\traise arcpy.ExecuteError\r\n\r\n\r\n\t\t\t\t# get all the IRI from input point feature class of wikidata places\r\n\t\t\t\tinplaceIRIList = []\r\n\t\t\t\tcursor = arcpy.SearchCursor(inputFeatureClassName)\r\n\t\t\t\tfor row in cursor:\r\n\t\t\t\t\tinplaceIRIList.append(row.getValue(\"URL\"))\r\n\r\n\r\n\r\n\t\t\t\t# get the first property URL list and label list\r\n\t\t\t\tif in_first_property_dir.value:\r\n\t\t\t\t\tfristDirection = in_first_property_dir.valueAsText\r\n\t\t\t\t\t# get the first property URL list\r\n\t\t\t\t\tfirstPropertyURLListJsonBindingObject = SPARQLQuery.relFinderCommonPropertyQuery(inplaceIRIList, relationDegree, [fristDirection], [\"\", \"\", \"\"])\r\n\t\t\t\t\tfirstPropertyURLList = []\r\n\t\t\t\t\tfor jsonItem in firstPropertyURLListJsonBindingObject:\r\n\t\t\t\t\t\tfirstPropertyURLList.append(jsonItem[\"p1\"][\"value\"])\r\n\r\n\t\t\t\t\tfirstPropertyLabelJSON = SPARQLQuery.locationCommonPropertyLabelQuery(firstPropertyURLList)\r\n\t\t\t\t\t# firstPropertyLabelJSON = firstPropertyLabelJSONObj[\"results\"][\"bindings\"]\r\n\r\n\t\t\t\t\t# get the first property label list\r\n\t\t\t\t\tfirstPropertyURLList = []\r\n\t\t\t\t\tfirstPropertyLabelList = []\r\n\t\t\t\t\tfor jsonItem in firstPropertyLabelJSON:\r\n\t\t\t\t\t\tpropertyURL = jsonItem[\"p\"][\"value\"]\r\n\t\t\t\t\t\tfirstPropertyURLList.append(propertyURL)\r\n\t\t\t\t\t\tpropertyName = jsonItem[\"propertyLabel\"][\"value\"]\r\n\t\t\t\t\t\tfirstPropertyLabelList.append(propertyName)\r\n\r\n\t\t\t\t\tRelFinder.firstPropertyLabelURLDict = dict(zip(firstPropertyLabelList, firstPropertyURLList))\r\n\r\n\t\t\t\t\tin_first_property.filter.list = firstPropertyLabelList\r\n\r\n\t\t\t\t\t# get the second property URL list and label list\r\n\t\t\t\t\tif in_second_property_dir.value:\r\n\t\t\t\t\t\tfristDirection = in_first_property_dir.valueAsText\r\n\t\t\t\t\t\tfirstProperty = in_first_property.valueAsText\r\n\r\n\t\t\t\t\t\tif firstProperty == None:\r\n\t\t\t\t\t\t\tfirstProperty = \"\"\r\n\t\t\t\t\t\telse:\r\n\t\t\t\t\t\t\tfirstProperty = RelFinder.firstPropertyLabelURLDict[firstProperty]\r\n\r\n\t\t\t\t\t\tsecondDirection = in_second_property_dir.valueAsText\r\n\t\t\t\t\t\t\r\n\t\t\t\t\t\t# get the second property URL list\r\n\t\t\t\t\t\tsecondPropertyURLListJsonBindingObject = SPARQLQuery.relFinderCommonPropertyQuery(inplaceIRIList, relationDegree, [fristDirection, secondDirection], [firstProperty, \"\", \"\"])\r\n\t\t\t\t\t\tsecondPropertyURLList = []\r\n\t\t\t\t\t\tfor jsonItem in secondPropertyURLListJsonBindingObject:\r\n\t\t\t\t\t\t\tsecondPropertyURLList.append(jsonItem[\"p2\"][\"value\"])\r\n\r\n\t\t\t\t\t\tsecondPropertyLabelJSON = SPARQLQuery.locationCommonPropertyLabelQuery(secondPropertyURLList)\r\n\t\t\t\t\t\t# secondPropertyLabelJSON = secondPropertyLabelJSONObj[\"results\"][\"bindings\"]\r\n\r\n\t\t\t\t\t\t# get the second property label list\r\n\t\t\t\t\t\tsecondPropertyURLList = []\r\n\t\t\t\t\t\tsecondPropertyLabelList = []\r\n\t\t\t\t\t\tfor jsonItem in secondPropertyLabelJSON:\r\n\t\t\t\t\t\t\tpropertyURL = jsonItem[\"p\"][\"value\"]\r\n\t\t\t\t\t\t\tsecondPropertyURLList.append(propertyURL)\r\n\t\t\t\t\t\t\tpropertyName = jsonItem[\"propertyLabel\"][\"value\"]\r\n\t\t\t\t\t\t\tsecondPropertyLabelList.append(propertyName)\r\n\r\n\t\t\t\t\t\tRelFinder.secondPropertyLabelURLDict = dict(zip(secondPropertyLabelList, secondPropertyURLList))\r\n\r\n\t\t\t\t\t\tin_second_property.filter.list = secondPropertyLabelList\r\n\r\n\t\t\t\t\t\t# get the third property URL list and label list\r\n\t\t\t\t\t\tif in_third_property_dir.value:\r\n\t\t\t\t\t\t\tfristDirection = in_first_property_dir.valueAsText\r\n\t\t\t\t\t\t\tfirstProperty = in_first_property.valueAsText\r\n\r\n\t\t\t\t\t\t\tsecondDirection = in_second_property_dir.valueAsText\r\n\t\t\t\t\t\t\tsecondProperty = in_second_property.valueAsText\r\n\r\n\t\t\t\t\t\t\tif firstProperty == None:\r\n\t\t\t\t\t\t\t\tfirstProperty = \"\"\r\n\t\t\t\t\t\t\telse:\r\n\t\t\t\t\t\t\t\tfirstProperty = RelFinder.firstPropertyLabelURLDict[firstProperty]\r\n\t\t\t\t\t\t\tif secondProperty == None:\r\n\t\t\t\t\t\t\t\tsecondProperty = \"\"\r\n\t\t\t\t\t\t\telse:\r\n\t\t\t\t\t\t\t\tsecondProperty = RelFinder.secondPropertyLabelURLDict[secondProperty]\r\n\r\n\t\t\t\t\t\t\tthirdDirection = in_third_property_dir.valueAsText\r\n\t\t\t\t\t\t\t\r\n\t\t\t\t\t\t\t# get the third property URL list\r\n\t\t\t\t\t\t\tthirdPropertyURLListJsonBindingObject = SPARQLQuery.relFinderCommonPropertyQuery(inplaceIRIList, relationDegree, [fristDirection, secondDirection, thirdDirection], [firstProperty, secondProperty, \"\"])\r\n\t\t\t\t\t\t\tthirdPropertyURLList = []\r\n\t\t\t\t\t\t\tfor jsonItem in thirdPropertyURLListJsonBindingObject:\r\n\t\t\t\t\t\t\t\tthirdPropertyURLList.append(jsonItem[\"p3\"][\"value\"])\r\n\r\n\t\t\t\t\t\t\tthirdPropertyLabelJSON = SPARQLQuery.locationCommonPropertyLabelQuery(thirdPropertyURLList)\r\n\t\t\t\t\t\t\t# thirdPropertyLabelJSON = thirdPropertyLabelJSONObj[\"results\"][\"bindings\"]\r\n\r\n\t\t\t\t\t\t\t# get the third property label list\r\n\t\t\t\t\t\t\tthirdPropertyURLList = []\r\n\t\t\t\t\t\t\tthirdPropertyLabelList = []\r\n\t\t\t\t\t\t\tfor jsonItem in thirdPropertyLabelJSON:\r\n\t\t\t\t\t\t\t\tpropertyURL = jsonItem[\"p\"][\"value\"]\r\n\t\t\t\t\t\t\t\tthirdPropertyURLList.append(propertyURL)\r\n\t\t\t\t\t\t\t\tpropertyName = jsonItem[\"propertyLabel\"][\"value\"]\r\n\t\t\t\t\t\t\t\tthirdPropertyLabelList.append(propertyName)\r\n\r\n\t\t\t\t\t\t\tRelFinder.thirdPropertyLabelURLDict = dict(zip(thirdPropertyLabelList, thirdPropertyURLList))\r\n\r\n\t\t\t\t\t\t\tin_third_property.filter.list = thirdPropertyLabelList\r\n\r\n\t\t\t\t\t\t\t# get the fourth property URL list and label list\r\n\t\t\t\t\t\t\tif in_fourth_property_dir.value:\r\n\t\t\t\t\t\t\t\tfristDirection = in_first_property_dir.valueAsText\r\n\t\t\t\t\t\t\t\tfirstProperty = in_first_property.valueAsText\r\n\r\n\t\t\t\t\t\t\t\tsecondDirection = in_second_property_dir.valueAsText\r\n\t\t\t\t\t\t\t\tsecondProperty = in_second_property.valueAsText\r\n\r\n\t\t\t\t\t\t\t\tthirdDirection = in_third_property_dir.valueAsText\r\n\t\t\t\t\t\t\t\tthirdProperty = in_third_property.valueAsText\r\n\r\n\t\t\t\t\t\t\t\tif firstProperty == None:\r\n\t\t\t\t\t\t\t\t\tfirstProperty = \"\"\r\n\t\t\t\t\t\t\t\telse:\r\n\t\t\t\t\t\t\t\t\tfirstProperty = RelFinder.firstPropertyLabelURLDict[firstProperty]\r\n\t\t\t\t\t\t\t\tif secondProperty == None:\r\n\t\t\t\t\t\t\t\t\tsecondProperty = \"\"\r\n\t\t\t\t\t\t\t\telse:\r\n\t\t\t\t\t\t\t\t\tsecondProperty = RelFinder.secondPropertyLabelURLDict[secondProperty]\r\n\t\t\t\t\t\t\t\tif thirdProperty == None:\r\n\t\t\t\t\t\t\t\t\tthirdProperty = \"\"\r\n\t\t\t\t\t\t\t\telse:\r\n\t\t\t\t\t\t\t\t\tthirdProperty = RelFinder.thirdPropertyLabelURLDict[thirdProperty]\r\n\r\n\t\t\t\t\t\t\t\tfourthDirection = in_fourth_property_dir.valueAsText\r\n\t\t\t\t\t\t\t\t\r\n\t\t\t\t\t\t\t\t# get the fourth property URL list\r\n\t\t\t\t\t\t\t\tfourthPropertyURLListJsonBindingObject = SPARQLQuery.relFinderCommonPropertyQuery(inplaceIRIList, relationDegree, [fristDirection, secondDirection, thirdDirection, fourthDirection], [firstProperty, secondProperty, thirdProperty])\r\n\t\t\t\t\t\t\t\tfourthPropertyURLList = []\r\n\t\t\t\t\t\t\t\tfor jsonItem in fourthPropertyURLListJsonBindingObject:\r\n\t\t\t\t\t\t\t\t\tfourthPropertyURLList.append(jsonItem[\"p4\"][\"value\"])\r\n\r\n\t\t\t\t\t\t\t\tfourthPropertyLabelJSON = SPARQLQuery.locationCommonPropertyLabelQuery(fourthPropertyURLList)\r\n\t\t\t\t\t\t\t\t# fourthPropertyLabelJSON = fourthPropertyLabelJSONObj[\"results\"][\"bindings\"]\r\n\r\n\t\t\t\t\t\t\t\t# get the fourth property label list\r\n\t\t\t\t\t\t\t\tfourthPropertyURLList = []\r\n\t\t\t\t\t\t\t\tfourthPropertyLabelList = []\r\n\t\t\t\t\t\t\t\tfor jsonItem in fourthPropertyLabelJSON:\r\n\t\t\t\t\t\t\t\t\tpropertyURL = jsonItem[\"p\"][\"value\"]\r\n\t\t\t\t\t\t\t\t\tfourthPropertyURLList.append(propertyURL)\r\n\t\t\t\t\t\t\t\t\tpropertyName = jsonItem[\"propertyLabel\"][\"value\"]\r\n\t\t\t\t\t\t\t\t\tfourthPropertyLabelList.append(propertyName)\r\n\r\n\t\t\t\t\t\t\t\tRelFinder.fourthPropertyLabelURLDict = dict(zip(fourthPropertyLabelList, fourthPropertyURLList))\r\n\r\n\t\t\t\t\t\t\t\tin_fourth_property.filter.list = fourthPropertyLabelList\r\n\r\n\r\n\t\treturn","def parameterNode(self):\n #framework\n profbox()\n return self.parameterNode","def __init__(self):\n\n self.prim_parser = parser.Parser()","def __init__(self,particle):\n self.par = particle","def default_pypeit_par(cls):\n par = super().default_pypeit_par()\n\n # Ignore PCA\n par['calibrations']['slitedges']['sync_predict'] = 'nearest'\n par['calibrations']['slitedges']['bound_detector'] = True\n\n # Set pixel flat combination method\n par['calibrations']['pixelflatframe']['process']['combine'] = 'median'\n # Wavelength calibration methods\n par['calibrations']['wavelengths']['method'] = 'full_template'\n par['calibrations']['wavelengths']['lamps'] = ['XeI,HgI,NeI,ArI']\n\n # Set the default exposure time ranges for the frame typing\n par['scienceframe']['exprng'] = [90, None]\n par['calibrations']['biasframe']['exprng'] = [None, 1]\n par['calibrations']['darkframe']['exprng'] = [999999, None] # No dark frames\n par['calibrations']['pinholeframe']['exprng'] = [999999, None] # No pinhole frames\n par['calibrations']['arcframe']['exprng'] = [None, None] # Long arc exposures\n par['calibrations']['arcframe']['process']['clip'] = False\n par['calibrations']['standardframe']['exprng'] = [None, 180]\n # Multiple arcs with different lamps, so can't median combine nor clip, also need to remove continuum\n par['calibrations']['arcframe']['process']['combine'] = 'mean'\n par['calibrations']['arcframe']['process']['subtract_continuum'] = True\n par['calibrations']['tiltframe']['process']['clip'] = False\n par['calibrations']['tiltframe']['process']['combine'] = 'mean'\n par['calibrations']['tiltframe']['process']['subtract_continuum'] = True\n\n # Increase the wave tilts order, given the longish slit\n par['calibrations']['tilts']['spat_order'] = 5\n par['calibrations']['tilts']['spec_order'] = 5\n\n #Only extract one object per standard frame\n par['reduce']['findobj']['maxnumber_std']=1\n\n # Turn off the 2D fit - this seems to be giving bad results for OSIRIS\n par['reduce']['skysub']['no_poly'] = True\n return par"],"string":"[\n \"def define_parameters(self):\",\n \"def parameters(self):\",\n \"def doParametersOfInterest(self):\\n\\n self.modelBuilder.doVar(\\\"Afb[0.6,-0.70,0.70]\\\");\\n self.modelBuilder.doSet(\\\"POI\\\",\\\"Afb\\\")\\n\\n # ss templates\\n self.modelBuilder.doVar(\\\"Rdy_mumu_ss[1.0,0.0,10.0]\\\");\\n self.modelBuilder.doVar(\\\"Rdy_ee_ss[1.0,0.0,10.0]\\\");\\n \\n self.modelBuilder.factory_('expr::Rpl(\\\"(1.+@0)\\\",Afb)')\\n self.modelBuilder.factory_('expr::Rmn(\\\"(1.-@0)\\\",Afb)')\",\n \"def parar():\\n pass\",\n \"def doParametersOfInterest(self):\\n\\n self.modelBuilder.doVar(\\\"eAfb[0.6,-0.75,0.75]\\\");\\n self.modelBuilder.doVar(\\\"eA0[0.05, -1.0, 1.0]\\\");\\n self.modelBuilder.doVar(\\\"mAfb[0.6,-0.75,0.75]\\\");\\n self.modelBuilder.doVar(\\\"mA0[0.05, -1.0, 1.0]\\\");\\n self.modelBuilder.doSet(\\\"POI\\\",\\\"eAfb,mAfb\\\")\\n\\n \\n self.modelBuilder.factory_('expr::eAlph(\\\"2.0*@0/(2.0-@0)\\\",eA0)')\\n self.modelBuilder.factory_('expr::eNorm(\\\"3.0/4.0/(2.0+@0)\\\",eAlph)')\\n self.modelBuilder.factory_('expr::eRAlph(\\\"@0*@1\\\",eAlph,eNorm)')\\n self.modelBuilder.factory_('expr::eRpl(\\\"(@0+@1)\\\",eNorm,eAfb)')\\n self.modelBuilder.factory_('expr::eRmn(\\\"(@0-@1)\\\",eNorm,eAfb)')\\n\\n self.modelBuilder.factory_('expr::mAlph(\\\"2.0*@0/(2.0-@0)\\\",mA0)')\\n self.modelBuilder.factory_('expr::mNorm(\\\"3.0/4.0/(2.0+@0)\\\",mAlph)')\\n self.modelBuilder.factory_('expr::mRAlph(\\\"@0*@1\\\",mAlph,mNorm)')\\n self.modelBuilder.factory_('expr::mRpl(\\\"(@0+@1)\\\",mNorm,mAfb)')\\n self.modelBuilder.factory_('expr::mRmn(\\\"(@0-@1)\\\",mNorm,mAfb)')\",\n \"def __init__(self, parant):\\n pass\",\n \"def doParametersOfInterest(self):\\n\\n self.modelBuilder.doVar(\\\"Rdy[1.,0.0,10.0]\\\");\\n self.modelBuilder.doVar(\\\"Rbk[1.,0.0,10.0]\\\");\\n self.modelBuilder.doVar(\\\"Rqcd_emu[1,0.0,10.0]\\\");\\n self.modelBuilder.doSet(\\\"POI\\\",\\\"Rbk,Rdy,Rqcd_emu\\\")\",\n \"def doParametersOfInterest(self):\\n\\n self.modelBuilder.doVar(\\\"Afb[0.6,-0.75,0.75]\\\");\\n self.modelBuilder.doVar(\\\"A0[0.05, -1.0, 1.0]\\\");\\n self.modelBuilder.doSet(\\\"POI\\\",\\\"Afb,A0\\\")\\n\\n \\n self.modelBuilder.factory_('expr::Alph(\\\"2.0*@0/(2.0-@0)\\\",A0)')\\n self.modelBuilder.factory_('expr::Norm(\\\"3.0/4.0/(2.0+@0)\\\",Alph)')\\n self.modelBuilder.factory_('expr::RAlph(\\\"@0*@1\\\",Alph,Norm)')\\n self.modelBuilder.factory_('expr::Rpl(\\\"(@0+@1)\\\",Norm,Afb)')\\n self.modelBuilder.factory_('expr::Rmn(\\\"(@0-@1)\\\",Norm,Afb)')\",\n \"def doParametersOfInterest(self):\\n\\n self.modelBuilder.doVar(\\\"eAfb[0.6,-0.75,0.75]\\\");\\n self.modelBuilder.doVar(\\\"eA0[0.05, -1.0, 1.0]\\\");\\n self.modelBuilder.doVar(\\\"rAfb[1.0,-5.0, 5.0]\\\");\\n self.modelBuilder.doVar(\\\"rA0[1.0, -5.0, 5.0]\\\");\\n self.modelBuilder.doSet(\\\"POI\\\",\\\"rAfb,rA0\\\")\\n self.modelBuilder.factory_('expr::mAfb(\\\"@0*@1\\\",eAfb,rAfb)')\\n self.modelBuilder.factory_('expr::mA0(\\\"(@0*@1)\\\",eA0,rA0)')\\n\\n \\n self.modelBuilder.factory_('expr::eAlph(\\\"2.0*@0/(2.0-@0)\\\",eA0)')\\n self.modelBuilder.factory_('expr::eNorm(\\\"3.0/4.0/(2.0+@0)\\\",eAlph)')\\n self.modelBuilder.factory_('expr::eRAlph(\\\"@0*@1\\\",eAlph,eNorm)')\\n self.modelBuilder.factory_('expr::eRpl(\\\"(@0+@1)\\\",eNorm,eAfb)')\\n self.modelBuilder.factory_('expr::eRmn(\\\"(@0-@1)\\\",eNorm,eAfb)')\\n\\n self.modelBuilder.factory_('expr::mAlph(\\\"2.0*@0/(2.0-@0)\\\",mA0)')\\n self.modelBuilder.factory_('expr::mNorm(\\\"3.0/4.0/(2.0+@0)\\\",mAlph)')\\n self.modelBuilder.factory_('expr::mRAlph(\\\"@0*@1\\\",mAlph,mNorm)')\\n self.modelBuilder.factory_('expr::mRpl(\\\"(@0+@1)\\\",mNorm,mAfb)')\\n self.modelBuilder.factory_('expr::mRmn(\\\"(@0-@1)\\\",mNorm,mAfb)')\",\n \"def doParametersOfInterest(self):\\n\\n self.modelBuilder.doVar(\\\"Rdy[1.,0.0,10.0]\\\");\\n self.modelBuilder.doVar(\\\"Rqcd[1,0.0,10.0]\\\");\\n self.modelBuilder.doSet(\\\"POI\\\",\\\"Rdy,Rqcd\\\")\",\n \"def doParametersOfInterest(self):\\r\\n if self.fg4fixed:\\r\\n self.modelBuilder.doVar(\\\"CMS_zz4l_fg4[0]\\\")\\r\\n self.modelBuilder.doVar(\\\"r[1,0,4]\\\")\\r\\n print \\\"Fixing CMS_zz4l_fg4\\\"\\r\\n poi = \\\"r\\\"\\r\\n else:\\r\\n if self.modelBuilder.out.var(\\\"CMS_zz4l_fg4\\\"):\\r\\n print \\\"have fg4 inside\\\"\\r\\n else:\\r\\n self.modelBuilder.doVar(\\\"CMS_zz4l_fg4[0.,-1,1]\\\")\\r\\n poi = \\\"CMS_zz4l_fg4\\\"\\r\\n if self.cPOI:\\r\\n if self.modelBuilder.out.var(\\\"cww_zz\\\"):\\r\\n print \\\"have czz_ww inside\\\"\\r\\n else:\\r\\n self.modelBuilder.doVar(\\\"cww_zz[0.5,-10,10]\\\")\\r\\n poi += \\\",cww_zz\\\"\\r\\n\\r\\n if self.fg2POI:\\r\\n if self.modelBuilder.out.var(\\\"CMS_zz4l_fg2\\\"):\\r\\n print \\\"have fg2 inside\\\"\\r\\n else:\\r\\n self.modelBuilder.doVar(\\\"CMS_zz4l_fg2[0.,0,1]\\\")\\r\\n poi += \\\",CMS_zz4l_fg2\\\"\\r\\n if self.muFloating:\\r\\n self.modelBuilder.doVar(\\\"r[1,0,2000]\\\")\\r\\n if self.muAsPOI:\\r\\n print \\\"Treating r as a POI\\\"\\r\\n poi += \\\",r\\\"\\r\\n else:\\r\\n self.modelBuilder.out.var(\\\"r\\\").setAttribute(\\\"flatParam\\\")\\r\\n if self.phiFloating:\\r\\n if self.modelBuilder.out.var(\\\"CMS_zz4l_fg4phi\\\"):\\r\\n print \\\"have fg4phi inside\\\"\\r\\n else: \\r\\n self.modelBuilder.doVar(\\\"CMS_zz4l_fg4phi[0.,-3.1415926,3.1415926]\\\")\\r\\n if self.phiPOI:\\r\\n poi += \\\",CMS_zz4l_fg4phi\\\"\\r\\n else:\\r\\n self.modelBuilder.out.var(\\\"CMS_zz4l_fg4phi\\\").setAttribute(\\\"flatParam\\\")\\r\\n if self.phi2Floating:\\r\\n #self.modelBuilder.doVar(\\\"CMS_zz4l_fg4phi[0.,-math.pi,math.pi]\\\")\\r\\n if self.modelBuilder.out.var(\\\"CMS_zz4l_fg2phi\\\"):\\r\\n print \\\"have fg2phi inside\\\"\\r\\n else: \\r\\n self.modelBuilder.doVar(\\\"CMS_zz4l_fg2phi[0.,-3.1415926,3.1415926]\\\")\\r\\n self.modelBuilder.out.var(\\\"CMS_zz4l_fg2phi\\\").setAttribute(\\\"flatParam\\\")\\r\\n \\r\\n self.modelBuilder.doSet(\\\"POI\\\",poi)\",\n \"def doParametersOfInterest(self):\\n\\n self.modelBuilder.doVar(\\\"eAfb[0.6,-0.75,0.75]\\\");\\n self.modelBuilder.doVar(\\\"eA0[0.05, -1.0, 1.0]\\\");\\n self.modelBuilder.doVar(\\\"dAfb[0.,-0.75,0.75]\\\");\\n self.modelBuilder.doVar(\\\"dA0[0.0, -1.0, 1.0]\\\");\\n #self.modelBuilder.doSet(\\\"POI\\\",\\\"dAfb,dA0\\\")\\n self.modelBuilder.doSet(\\\"POI\\\",\\\"dAfb\\\")\\n self.modelBuilder.factory_('expr::mAfb(\\\"@0+@1\\\",eAfb,dAfb)')\\n self.modelBuilder.factory_('expr::mA0(\\\"(@0+@1)\\\",eA0,dA0)')\\n\\n \\n self.modelBuilder.factory_('expr::eAlph(\\\"2.0*@0/(2.0-@0)\\\",eA0)')\\n self.modelBuilder.factory_('expr::eNorm(\\\"3.0/4.0/(2.0+@0)\\\",eAlph)')\\n self.modelBuilder.factory_('expr::eRAlph(\\\"@0*@1\\\",eAlph,eNorm)')\\n self.modelBuilder.factory_('expr::eRpl(\\\"(@0+@1)\\\",eNorm,eAfb)')\\n self.modelBuilder.factory_('expr::eRmn(\\\"(@0-@1)\\\",eNorm,eAfb)')\\n\\n self.modelBuilder.factory_('expr::mAlph(\\\"2.0*@0/(2.0-@0)\\\",mA0)')\\n self.modelBuilder.factory_('expr::mNorm(\\\"3.0/4.0/(2.0+@0)\\\",mAlph)')\\n self.modelBuilder.factory_('expr::mRAlph(\\\"@0*@1\\\",mAlph,mNorm)')\\n self.modelBuilder.factory_('expr::mRpl(\\\"(@0+@1)\\\",mNorm,mAfb)')\\n self.modelBuilder.factory_('expr::mRmn(\\\"(@0-@1)\\\",mNorm,mAfb)')\",\n \"def main(model,pmap):\\n\\n addPppParams(model)\\n\\n# addTransportParams(model,pmap)\\n\\n #translationSources(model)\\n\\n #addLipidMetabs(model)\\n\\n return\",\n \"def doParametersOfInterest(self):\\n\\n self.modelBuilder.doVar(\\\"Afb[0.6,-0.75,0.75]\\\");\\n self.modelBuilder.doSet(\\\"POI\\\",\\\"Afb\\\")\\n\\n # ss templates\\n self.modelBuilder.doVar(\\\"Dilu_ratio[1.0,0.0,10.0]\\\");\\n self.modelBuilder.doVar(\\\"Rdy_mumu_ss[1.0,0.0,10.0]\\\");\\n self.modelBuilder.doVar(\\\"Rdy_ee_ss[1.0,0.0,10.0]\\\");\\n \\n self.modelBuilder.factory_('expr::Rpl(\\\"0.5*(1.+@0*@1)\\\",Afb, Dilu_ratio)')\\n self.modelBuilder.factory_('expr::Rmn(\\\"0.5*(1.-@0*@1)\\\",Afb, Dilu_ratio)')\",\n \"def _load_parameter(self):\",\n \"def getDefaultParams():\\n defpar = [\\n # coordinate system\\n ['crd_sys', \\\"'sph'\\\", 'Coordinate system'],\\n ['nx', '[60, 40, 30]', 'Number of grid points in the first dimension'],\\n ['xbound', '[0.1*au, 30.*au, 110.*au, 250.*au]', 'Number of radial grid points'],\\n ['ny', '[10,30, 30, 10]',\\n 'Number of grid points in the second dimension'],\\n ['ybound', '[0.1, pi/6., pi/2., 5.*pi/6., 3.04]',\\n 'Number of radial grid points'],\\n ['nz', '[361]', 'Number of grid points in the third dimension'],\\n ['zbound', '[0., 2.0*pi]', 'Number of radial grid points'],\\n # star related\\n ['tstar', '[3900.0]', 'Temperature of star'],\\n ['mstar', '[1.0*ms]', 'Mass of the star(s)'],\\n ['rstar', '[2.5*rs]', 'Radius of star'],\\n # gas density \\n ['Rin', '[0.1*au, 80*au]', 'inner bounding edge'],\\n ['Rin_w', '[0, 1*au]', 'gaussian taper before inner edge'], \\n ['Rout', '[30*au, 120*au]', 'outer bounding edge'],\\n ['Rout_w', '[1*au, 1*au]', 'gaussian taper after outer edge'], \\n ['sigp', '[-1.0, -1.5]', 'power-law surface density'],\\n ['sig0', '[1e2, 1e1]', 'surface density at Rin in g/cm^2'], \\n ['ring_r', '[50*au]', 'location of gaussian ring'], \\n ['ring_win', '[5*au]', 'width of gaussian ring in inner radius'],\\n ['ring_wout', '[5*au]', 'width of gaussian ring in outer radius'], \\n ['ring_a', '[1e2]', 'surface density at center of ring in g/cm^2]'], \\n ['cutgdens', '1e-30', 'cut for density'], \\n ['Rt', '100*au', 'radius for scale height'], \\n ['Ht', '10*au', 'scale height'], \\n ['qheight', '1.25', 'height power-law'], \\n # gas species\\n ['gasspec_mol_name', \\\"['12co']\\\", 'name of molecule'],\\n ['gasspec_mol_abun', '[5e-5]', 'mass abundance '],\\n ['gasspec_mol_dbase_type', \\\"['leiden']\\\", ''],\\n ['gasspec_mol_freezeout_dfact', '[1e-3]',\\n 'Factor by which the molecular abundance should be decreased in the freeze-out zone'],\\n ['mol_freeze_Ht', '[24*au]', 'Height at Rt, with index=qheight, for freeze out to happen'],\\n ['mol_freeze_del_hfrac', '0.2', 'Gaussian taper for freeze-out. del H = h * hfrac'],\\n ['mol_snowR', '[20*au]', 'Radius when freeze out begins to happen'],\\n # dust density\\n # flat power-law parts\\n ['dRin', '[0.1*au, 80*au]', 'inner bounding edge'],\\n ['dRin_w', '[0, 1*au]', 'gaussian taper before inner edge'], \\n ['dRout', '[30*au, 120*au]', 'outer bounding edge'],\\n ['dRout_w', '[1*au, 1*au]', 'gaussian taper after outer edge'], \\n ['dsigp', '[-1.0, -1.5]', 'power-law surface density'],\\n ['dsig0', '[1e2, 1e1]', 'surface density at Rin'],\\n # Lynden-Bell parts\\n ['dLB_Rin', '[0.1*au]', 'inner bounding radius'], \\n ['dLB_Rsig', '[30*au]', 'charcteristic radius'],\\n ['dLB_sigp', '[-1.0]', 'power-law exponent. Careful, the sign is different from the usual function by a negative sign for consistency with flat power-law'], \\n ['dLB_sig0', '[1e2]', 'surface density'], \\n # ring parts\\n ['dring_r', '[50*au]', 'location of gaussian ring'],\\n ['dring_win', '[5*au]', 'width of gaussian ring in inner radius'],\\n ['dring_wout', '[5*au]', 'width of gaussian ring in outer radius'], \\n ['dring_a', '[1e2]', 'surface density at center of ring in g/cm^2]'],\\n ['cutddens', '1e-30', 'cut for dust density'],\\n ['dRt', '[100*au]', 'radius for scale height for each grain size'], \\n ['dHt', '[10*au]', 'scale height for each grain size'], \\n ['dqheight', '[1.25]', 'scale height power-law for dust'], \\n # temperature\\n ['T0mid', '50', 'mid plane temperature at Rt'],\\n ['T0atm', '50', 'atmosphere temperature at Rt'],\\n ['zqratio', '3', 'factor of Ht of where temperature transition occurs'],\\n ['qmid', '-0.5', 'midplane temperature exponent'],\\n ['qatm', '-0.5', 'atmosphere temperature exponent'],\\n ['hdel', '2', 'temperature transition exponent '],\\n ['cuttemp', '10', 'temperature cut'], \\n # alignment\\n ['altype', \\\"'toroidal'\\\", 'alignment type']\\n ]\\n\\n return defpar\",\n \"def get_params(self):\",\n \"def default_pypeit_par(cls):\\n par = super().default_pypeit_par()\\n\\n # Wavelengths\\n # 1D wavelength solution with arc lines\\n par['calibrations']['wavelengths']['rms_threshold'] = 1.0\\n par['calibrations']['wavelengths']['sigdetect']=3\\n par['calibrations']['wavelengths']['fwhm'] = 20\\n par['calibrations']['wavelengths']['n_first']=2\\n par['calibrations']['wavelengths']['n_final']=4\\n par['calibrations']['wavelengths']['lamps'] = ['ArI', 'ArII', 'ThAr', 'NeI']\\n #par['calibrations']['wavelengths']['nonlinear_counts'] = self.detector[0]['nonlinear'] * self.detector[0]['saturation']\\n par['calibrations']['wavelengths']['method'] = 'full_template'\\n par['calibrations']['wavelengths']['reid_arxiv'] = 'magellan_fire_long.fits'\\n par['calibrations']['wavelengths']['match_toler']=5.0\\n\\n # Set slits and tilts parameters\\n par['calibrations']['tilts']['tracethresh'] = 5\\n par['calibrations']['slitedges']['trace_thresh'] = 10.\\n par['calibrations']['slitedges']['sync_predict'] = 'nearest'\\n\\n # Processing steps\\n turn_off = dict(use_illumflat=False, use_biasimage=False, use_overscan=False,\\n use_darkimage=False)\\n par.reset_all_processimages_par(**turn_off)\\n\\n # Scienceimage parameters\\n par['reduce']['findobj']['snr_thresh'] = 5\\n #par['reduce']['maxnumber'] = 2\\n par['reduce']['findobj']['find_trim_edge'] = [50,50]\\n par['flexure']['spec_method'] = 'skip'\\n\\n par['sensfunc']['IR']['telgridfile'] = 'TelFit_LasCampanas_3100_26100_R20000.fits'\\n\\n # Set the default exposure time ranges for the frame typing\\n par['calibrations']['standardframe']['exprng'] = [None, 60]\\n par['calibrations']['arcframe']['exprng'] = [1, 50]\\n par['calibrations']['darkframe']['exprng'] = [20, None]\\n par['scienceframe']['exprng'] = [20, None]\\n return par\",\n \"def default_pypeit_par(cls):\\n par = super().default_pypeit_par()\\n\\n # Wavelengths\\n # 1D wavelength solution with OH lines\\n par['calibrations']['wavelengths']['rms_threshold'] = 1.0\\n par['calibrations']['wavelengths']['sigdetect']=[5,10,10,10,10,20,30,30,30,30,30,10,30,30,60,30,30,10,20,30,10]\\n par['calibrations']['wavelengths']['n_first']=2\\n par['calibrations']['wavelengths']['n_final']=[3,3,3,2,4,4,4,3,4,4,4,3,4,4,4,4,4,4,6,6,4]\\n par['calibrations']['wavelengths']['lamps'] = ['OH_FIRE_Echelle']\\n #par['calibrations']['wavelengths']['nonlinear_counts'] = self.detector[0]['nonlinear'] * self.detector[0]['saturation']\\n par['calibrations']['wavelengths']['method'] = 'reidentify'\\n par['calibrations']['wavelengths']['cc_thresh'] = 0.35\\n par['calibrations']['wavelengths']['reid_arxiv'] = 'magellan_fire_echelle.fits'\\n par['calibrations']['wavelengths']['match_toler']=30.0\\n\\n # Echelle parameters\\n par['calibrations']['wavelengths']['echelle'] = True\\n# par['calibrations']['wavelengths']['ech_fix_format'] = True\\n par['calibrations']['wavelengths']['ech_nspec_coeff'] = 4\\n par['calibrations']['wavelengths']['ech_norder_coeff'] = 6\\n par['calibrations']['wavelengths']['ech_sigrej'] = 3.0\\n\\n # Always correct for flexure, starting with default parameters\\n par['scienceframe']['process']['sigclip'] = 20.0\\n par['scienceframe']['process']['satpix'] ='nothing'\\n\\n # Set slits and tilts parameters\\n par['calibrations']['tilts']['tracethresh'] = 5\\n par['calibrations']['slitedges']['edge_thresh'] = 3.\\n par['calibrations']['slitedges']['trace_thresh'] = 10.\\n par['calibrations']['slitedges']['fit_order'] = 5\\n par['calibrations']['slitedges']['max_shift_adj'] = 0.5\\n par['calibrations']['slitedges']['fit_min_spec_length'] = 0.5\\n par['calibrations']['slitedges']['left_right_pca'] = True\\n par['calibrations']['slitedges']['pca_order'] = 3\\n\\n # Model entire slit\\n par['reduce']['extraction']['model_full_slit'] = True # local sky subtraction operates on entire slit\\n par['reduce']['findobj']['maxnumber_sci'] = 2 # Slit is narrow so allow one object per order\\n par['reduce']['findobj']['maxnumber_std'] = 1 # Slit is narrow so allow one object per order\\n\\n # Processing steps\\n turn_off = dict(use_illumflat=False, use_biasimage=False, use_overscan=False,\\n use_darkimage=False)\\n par.reset_all_processimages_par(**turn_off)\\n # Do not correct for flexure\\n par['flexure']['spec_method'] = 'skip'\\n\\n # Set the default exposure time ranges for the frame typing\\n par['calibrations']['standardframe']['exprng'] = [None, 60]\\n par['calibrations']['arcframe']['exprng'] = [20, None]\\n par['calibrations']['darkframe']['exprng'] = [20, None]\\n par['scienceframe']['exprng'] = [20, None]\\n\\n # Sensitivity function parameters\\n # Sensitivity function parameters\\n par['sensfunc']['algorithm'] = 'IR'\\n par['sensfunc']['polyorder'] = 5\\n par['sensfunc']['IR']['maxiter'] = 2\\n # place holder for telgrid file\\n par['sensfunc']['IR']['telgridfile'] = 'TelFit_LasCampanas_3100_26100_R20000.fits'\\n\\n return par\",\n \"def parameters(self):\\n pass\",\n \"def mezclar_bolsa(self):\",\n \"def doParametersOfInterest(self):\\n\\n self.modelBuilder.doVar(\\\"Afb[0.6,-0.7,0.7]\\\");\\n self.modelBuilder.doVar(\\\"A0[0.05, -1.0, 1.0]\\\");\\n self.modelBuilder.doSet(\\\"POI\\\",\\\"Afb,A0\\\")\\n\\n # ss templates\\n self.modelBuilder.doVar(\\\"R_ee_os_fakes[0.6,0.0,1.0]\\\");\\n self.modelBuilder.doVar(\\\"ee16_fakes_norm[1.0, 0.01, 10.]\\\");\\n self.modelBuilder.doVar(\\\"ee17_fakes_norm[1.0, 0.01, 10.]\\\");\\n self.modelBuilder.doVar(\\\"ee18_fakes_norm[1.0, 0.01, 10.]\\\");\\n #Remember, cant use spaces in these formulas!\\n #self.modelBuilder.options.verbose = 10\\n self.modelBuilder.factory_('expr::R_ee16_qcd_os(\\\"@0*@1\\\",ee16_fakes_norm,R_ee_os_fakes)')\\n self.modelBuilder.factory_('expr::R_ee17_qcd_os(\\\"@0*@1\\\",ee17_fakes_norm,R_ee_os_fakes)')\\n self.modelBuilder.factory_('expr::R_ee18_qcd_os(\\\"@0*@1\\\",ee18_fakes_norm,R_ee_os_fakes)')\\n self.modelBuilder.factory_('expr::R_ee16_qcd_ss(\\\"@0*(1.0-@1)\\\",ee16_fakes_norm,R_ee_os_fakes)')\\n self.modelBuilder.factory_('expr::R_ee17_qcd_ss(\\\"@0*(1.0-@1)\\\",ee17_fakes_norm,R_ee_os_fakes)')\\n self.modelBuilder.factory_('expr::R_ee18_qcd_ss(\\\"@0*(1.0-@1)\\\",ee18_fakes_norm,R_ee_os_fakes)')\\n \\n self.modelBuilder.factory_('expr::Alph(\\\"2.0*@0/(2.0-@0)\\\",A0)')\\n self.modelBuilder.factory_('expr::Norm(\\\"3.0/4.0/(2.0+@0)\\\",Alph)')\\n self.modelBuilder.factory_('expr::RAlph(\\\"@0*@1\\\",Alph,Norm)')\\n self.modelBuilder.factory_('expr::Rpl(\\\"(@0+@1)\\\",Norm,Afb)')\\n self.modelBuilder.factory_('expr::Rmn(\\\"(@0-@1)\\\",Norm,Afb)')\",\n \"def doParametersOfInterest(self):\\n self.modelBuilder.doVar(\\\"mu[1,0,100]\\\") ##mu is what we want to return (in string) name[starting_value,min,max] \\n self.modelBuilder.doSet(\\\"POI\\\",\\\"mu\\\")\\n self.modelBuilder.factory_('expr::ggH_s_func(\\\"@0-sqrt(@0)\\\", mu)')\\n self.modelBuilder.factory_( 'expr::ggH_b_func(\\\"1-sqrt(@0)\\\", mu)')\\n self.modelBuilder.factory_( 'expr::ggH_sbi_func(\\\"sqrt(@0)\\\", mu)')\",\n \"def presenetCar():\",\n \"def doParametersOfInterest(self):\\n self.modelBuilder.doVar(\\\"mu[0,0,1000]\\\") ##mu is what we want to return (in string) name[starting_value,min,max] \\n self.modelBuilder.doSet(\\\"POI\\\",\\\"mu\\\")\\n self.modelBuilder.factory_('expr::vbfH_s_func(\\\"@0-sqrt(@0)\\\", mu)')\\n self.modelBuilder.factory_( 'expr::vbfH_b_func(\\\"1-sqrt(@0)\\\", mu)')\\n self.modelBuilder.factory_( 'expr::vbfH_sbi_func(\\\"sqrt(@0)\\\", mu)')\",\n \"def params():\\n raise NotImplementedError\",\n \"def __init__(self,manager,name):\\n Online.DatapointLoader.DatapointLoader.__init__(self,manager,name)\\n self.dpName = self.name\\n self.runType = self.dp('general.runType')\\n self.partitionName = self.dp('general.partName')\\n self.partitionID = self.dp('general.activePartId')\\n self.nSubFarm = self.dp('HLTFarm.nSubFarms')\\n self.subfarms = self.dp('HLTFarm.subFarms')\\n self.addDp(self.reader)\",\n \"def doParametersOfInterest(self):\\n ''' ref : physicsmodel -> rvf\\n self.modelBuilder.out.var(\\\"MH\\\").setRange(float(self.mHRange[0]),float(self.mHRange[1]))\\n self.modelBuilder.out.var(\\\"MH\\\").setConstant(False)\\n '''\\n\\n self.modelBuilder.doVar(\\\"mu[0,0,1000]\\\") ##mu is what we want to return (in string) name[starting_value,min,max] \\n self.modelBuilder.doVar(\\\"Fvbf[0,0,1]\\\") ##mu is what we want to return (in string) name[starting_value,min,max] \\n self.modelBuilder.doSet(\\\"POI\\\",\\\"mu,Fvbf\\\")\\n self.modelBuilder.doVar(\\\"\\\")\\n self.modelBuilder.factory_('expr::ggH_s_func(\\\"(@0-sqrt(@0))*(1.-@1)\\\", mu,Fvbf)')\\n self.modelBuilder.factory_( 'expr::ggH_b_func(\\\"(1-sqrt(@0))*(1.-@1)\\\", mu,Fvbf)')\\n self.modelBuilder.factory_( 'expr::ggH_sbi_func(\\\"sqrt(@0)*(1.-@1)\\\", mu,Fvbf)')\\n\\n self.modelBuilder.factory_('expr::vbfH_s_func(\\\"(@0-sqrt(@0))*(@1)\\\", mu,Fvbf)')\\n self.modelBuilder.factory_( 'expr::vbfH_b_func(\\\"(1-sqrt(@0))*(@1)\\\", mu,Fvbf)')\\n self.modelBuilder.factory_( 'expr::vbfH_sbi_func(\\\"sqrt(@0)*(@1)\\\", mu,Fvbf)')\",\n \"def setupParachutes(self):\\r\\n # references to all the Parachute objects created\\r\\n # YAML config\\r\\n parConfNode = self.config.parachute\\r\\n #----------------------------\\r\\n robotTex = loader.loadTexture(parConfNode.texture[0].textureName)\\r\\n robotTex.setWrapU(Texture.WMClamp)\\r\\n robotTex.setWrapV(Texture.WMClamp)\\r\\n robotTex.setMinfilter(Texture.FTLinearMipmapLinear)\\r\\n robotTex.setAnisotropicDegree(2)\\r\\n #----------------------------\\r\\n paraTex = loader.loadTexture(parConfNode.parachuteTex)\\r\\n paraTex.setMinfilter(Texture.FTLinearMipmapLinear)\\r\\n paraTex.setAnisotropicDegree(2)\\r\\n #----------------------------\\r\\n baseNode = NodePath(\\\"parachute\\\")\\r\\n baseNode.setTransparency(1)\\r\\n baseNode.setScale(float(parConfNode.scale))\\r\\n\\r\\n cam = self.config.world.camera\\r\\n camLookAt = Vec3(cam.lookAt[0]-cam.pos[0],\\r\\n cam.lookAt[1]-cam.pos[1],\\r\\n cam.lookAt[2]-cam.pos[2])\\r\\n camLookAt.normalize()\\r\\n camLookAt = camLookAt * self.config.parDistCam\\r\\n\\r\\n # in Panda by default Y points away from the camera\\r\\n #Ypos = cam.pos[1] + cam.parDistCam\\r\\n # base node at cam.parDistCam distance from the camera\\r\\n baseNode.setPos(camLookAt[0],camLookAt[1],camLookAt[2])\\r\\n\\r\\n # this is the PARACHUTE part\\r\\n paraModel = loader.loadModel(parConfNode.modelname)\\r\\n paraModel.setScale(Vec3(0.3, 0.000001, 0.2))\\r\\n paraModel.setPos(Vec3(0, 0.15, 1.2))\\r\\n paraModel.setName(\\\"parachute\\\")\\r\\n paraModel.setTexture(paraTex)\\r\\n paraModel.reparentTo(baseNode)\\r\\n #----------------------------\\r\\n # bill board (plane) model, the actual robot\\r\\n robotModel = loader.loadModel(\\\"PilotData/models/plane\\\")\\r\\n robotModel.setName(\\\"body\\\")\\r\\n robotModel.setPos(Vec3(0, 0, -0.5))\\r\\n robotModel.setTransparency(1)\\r\\n robotModel.setTexture(robotTex, 1)\\r\\n robotModel.reparentTo(baseNode)\\r\\n #----------------------------\\r\\n baseNode.setBillboardPointEye()\\r\\n baseNode.reparentTo(self.sceneNP)\\r\\n self.baseNode = baseNode\",\n \"def params(self):\\n pass\",\n \"def __init__(self):\\n self.params = arcpy.GetParameterInfo()\",\n \"def rip1_to_parp():\\n Monomer('MLKL', ['bRHIM', 'state'], {'state':['unmod', 'active', 'inactive']})\\n Parameter('MLKL_0' , 1.0e6) # molecules per cell\\n alias_model_components()\\n Initial(MLKL(bRHIM = None, state = 'unmod'), MLKL_0) # MLKL\\n \\n Rule('Rip_PO4lation', RIP1(bRHIM=ANY, state = 'unmod')%RIP3(bRHIM=ANY, state='unmod') >> RIP1(bRHIM=ANY, state = 'po4')%RIP3(bRHIM=ANY, state = 'po4'), Parameter('k19', 1e-1))\\n Rule('Rip_PO4lation_alt', RIP1(bRHIM=ANY, state = 'deub')%RIP3(bRHIM=ANY, state='unmod') >> RIP1(bRHIM=ANY, state = 'po4')%RIP3(bRHIM=ANY, state = 'po4'), Parameter('k19a', 1e-1))\\n \\n catalyze_state(RIP1(state='po4'), 'bPARP', MLKL(), 'bRHIM', 'state', 'unmod', 'active', [1e-6,1e-3, 1e-1])\\n catalyze_state(MLKL(state='active'), 'bRHIM', MLKL(), 'bRHIM', 'state', 'unmod', 'active', [1e-7, 0.2, 0.01])\",\n \"def _initialize_params(self, parnames, sep=\\\".\\\"):\\n for name in parnames:\\n self.get_pvobj(name, sep)\",\n \"def _read_custom_pars(self):\\n if self.use_defaults:\\n param_set = \\\"default_values\\\"\\n else:\\n param_set = \\\"parameters\\\"\\n self.outpars = self.input_cfg_json_data[param_set][self.step_title]\",\n \"def set_parameters(self):\\n params = {}\\n if self.modelname == 'SI':\\n # N1: Pop 1 size after split\\n # N2: Pop 2 size after splot\\n # Ts: Time from split to present, in 2*Na generation units\\n names = ['N1', 'N2', 'Ts']\\n values = [1, 1, 1]\\n upper_bounds = [20, 20, 10]\\n lower_bounds = [0.01, 0.01, 0]\\n elif self.modelname == 'IM':\\n # N1: Pop 1 size after split\\n # N2: Pop 2 size after split\\n # m21: Migration from 1 to 2 (2*Na*mm21)\\n # m12: Migration from 2 to 1 (2*Na*m12)\\n # Ts: Time from split to present, in 2*Na generations\\n names = ['N1', 'N2', 'm21', 'm12', 'Ts']\\n values = [1, 1, 1, 1, 1]\\n upper_bounds = [20, 20, 20, 20, 10]\\n lower_bounds = [0.01, 0.01, 0, 0, 0]\\n elif self.modelname == 'AM':\\n # N1: Pop 1 size after split\\n # N2: Pop 2 size after split\\n # m21: Migration from 1 to 2 (2*Na*mm21)\\n # m12: Migration from 2 to 1 (2*Na*m12)\\n # Tam: Time from end of anc migration to split, in 2*Na gens\\n # Ts: Time from split to present, in 2*Na generations\\n names = ['N1', 'N2', 'm21', 'm12', 'Tam', 'Ts']\\n values = [1, 1, 1, 1, 0.1, 1]\\n upper_bounds = [20, 20, 20, 20, 2, 10]\\n lower_bounds = [0.01, 0.01, 0, 0, 0, 0]\\n elif self.modelname == 'SC':\\n # N1: Pop 1 size after split\\n # N2: Pop 2 size after split\\n # m21: Migration from 1 to 2 (2*Na*mm21)\\n # m12: Migration from 2 to 1 (2*Na*m12)\\n # Ts: Time from split to secondary contact, in 2*Na generations\\n # Tsc: Time from secondary contact to presesnt, in 2*Na gens\\n names = ['N1', 'N2', 'm21', 'm12', 'Ts', 'Tsc']\\n values = [1, 1, 1, 1, 1, 0.1]\\n upper_bounds = [20, 20, 20, 20, 10, 2]\\n lower_bounds = [0.01, 0.01, 0, 0, 0, 0]\\n elif self.modelname == 'IM2M':\\n # N1: Pop 1 size after split\\n # N2: Pop 2 size after split\\n # m21: Migration from 1 to 2 (2*Na*mm21)\\n # m12: Migration from 2 to 1 (2*Na*m12)\\n # mi21: Migration from 1 to 2 in \\\"islands\\\" (2*Na*mi21)\\n # mi12: Migration from 1 to 2 in \\\"islands\\\" (2*Na*mi12)\\n # Ts: Time from split to present, in 2*Na generations\\n # p: Porpotion of genome evoloving in \\\"islands\\\"\\n names = ['N1', 'N2', 'm21', 'm12', 'mi21', 'mi12', 'Ts', 'p']\\n values = [1, 1, 5, 5, 0.5, 0.5, 1, 0.5]\\n upper_bounds = [20, 20, 30, 30, 5, 5, 10, 0.95]\\n lower_bounds = [0.01, 0.01, 0, 0, 0, 0, 0, 0.05]\\n elif self.modelname == 'AM2M':\\n # N1: Pop 1 size after split\\n # N2: Pop 2 size after split\\n # m21: Migration from 1 to 2 (2*Na*mm21)\\n # m12: Migration from 2 to 1 (2*Na*m12)\\n # mi21: Migration from 1 to 2 in \\\"islands\\\" (2*Na*mi21)\\n # mi12: Migration from 1 to 2 in \\\"islands\\\" (2*Na*mi12)\\n # Tam: Time from end of anc migration to split, in 2*Na gens\\n # Ts: Time from split to present, in 2*Na generations\\n # p: Porpotion of genome evoloving in \\\"islands\\\"\\n names = ['N1', 'N2', 'm21', 'm12', 'mi21', 'mi12', 'Tam', 'Ts', 'p']\\n values = [1, 1, 5, 5, 0.5, 0.5, 0.1, 1, 0.5]\\n upper_bounds = [20, 20, 30, 30, 5, 5, 2, 10, 0.95]\\n lower_bounds = [0.01, 0.01, 0, 0, 0, 0, 0, 0, 0.05]\\n elif self.modelname == 'SC2M':\\n # N1: Pop 1 size after split\\n # N2: Pop 2 size after split\\n # m21: Migration from 1 to 2 (2*Na*mm21)\\n # m12: Migration from 2 to 1 (2*Na*m12)\\n # mi21: Migration from 1 to 2 in \\\"islands\\\" (2*Na*mi21)\\n # mi12: Migration from 1 to 2 in \\\"islands\\\" (2*Na*mi12)\\n # Ts: Time from split to secondary contact, in 2*Na generations\\n # Tsc: Time from secondary contact to presesnt, in 2*Na gens\\n # p: Porpotion of genome evoloving in \\\"islands\\\"\\n names = ['N1', 'N2', 'm21', 'm12', 'mi21', 'mi12', 'Ts', 'Tsc', 'p']\\n values = [1, 1, 5, 5, 0.5, 0.5, 1, 0.1, 0.5]\\n upper_bounds = [20, 20, 30, 30, 5, 5, 10, 2, 0.95]\\n lower_bounds = [0.01, 0.01, 0, 0, 0, 0, 0, 0, 0.05]\\n params['Names'] = names\\n params['Values'] = values\\n params['Upper'] = upper_bounds\\n params['Lower'] = lower_bounds\\n return params\",\n \"def __init__(self, name, config):\\n self.name = name\\n self.config = config\\n LineBuilder.__init__(self, name, config)\\n \\n etaprimeppg_name = '{0}EtaPrimePPG'.format(name)\\n etaprime3hr_name = '{0}EtaPrime3HR'.format(name)\\n \\n d2pietaprimeppg_name = '{0}D2PiEtaPrimePPG'.format(name)\\n d2pietaprime3hr_name = '{0}D2PiEtaPrime3HR'.format(name)\\n \\n d2ketaprimeppg_name = '{0}D2KEtaPrimePPG'.format(name)\\n d2ketaprime3hr_name = '{0}D2KEtaPrime3HR'.format(name)\\n \\n self.selEtaPrimePPG = makeResonance(\\n etaprimeppg_name,\\n config,\\n inputSel=[StdAllNoPIDsPions,StdLooseAllPhotons],\\n decDescriptors=self.EtaPrimePPG\\n )\\n \\n self.selEtaPrime3HR = makeResonance(\\n etaprime3hr_name,\\n config,\\n inputSel=[StdAllNoPIDsPions,StdLooseResolvedEta],\\n decDescriptors=self.EtaPrime3H\\n )\\n \\n self.selD2PiEtaPrimePPG = makeD(\\n d2pietaprimeppg_name,\\n config,\\n inputSel=[self.selEtaPrimePPG, StdAllNoPIDsPions],\\n decDescriptors=self.D2PiEtaPrime,\\n useBachelorPID=False,\\n )\\n \\n self.selD2KEtaPrimePPG = makeD(\\n d2ketaprimeppg_name,\\n config,\\n inputSel=[self.selEtaPrimePPG, StdAllNoPIDsKaons],\\n decDescriptors=self.D2KEtaPrime,\\n useBachelorPID=False,\\n )\\n \\n self.selD2PiEtaPrime3HR = makeD(\\n d2pietaprime3hr_name,\\n config,\\n inputSel=[self.selEtaPrime3HR, StdAllNoPIDsPions],\\n decDescriptors=self.D2PiEtaPrime,\\n useBachelorPID=False, \\n )\\n \\n self.selD2KEtaPrime3HR = makeD(\\n d2ketaprime3hr_name,\\n config,\\n inputSel=[self.selEtaPrime3HR, StdAllNoPIDsKaons],\\n decDescriptors=self.D2KEtaPrime,\\n useBachelorPID=False,\\n )\\n \\n self.line_D2PiEtaPrimePPG = make_line(\\n self,\\n name='{0}Line'.format(d2pietaprimeppg_name),\\n prescale=config['PrescaleD2PiEtaPrimePPG'],\\n postscale=config['PostscaleD2PiEtaPrimePPG'],\\n selection=self.selD2PiEtaPrimePPG,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n \\n self.line_D2PiEtaPrime3HR = make_line(\\n self,\\n name='{0}Line'.format(d2pietaprime3hr_name),\\n prescale=config['PrescaleD2PiEtaPrime3HR'],\\n postscale=config['PostscaleD2PiEtaPrime3HR'],\\n selection=self.selD2PiEtaPrime3HR,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n \\n self.line_D2KEtaPrimePPG = make_line(\\n self,\\n name='{0}Line'.format(d2ketaprimeppg_name),\\n prescale=config['PrescaleD2KEtaPrimePPG'],\\n postscale=config['PostscaleD2KEtaPrimePPG'],\\n selection=self.selD2KEtaPrimePPG,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n \\n self.line_D2KEtaPrime3HR = make_line(\\n self,\\n name='{0}Line'.format(d2ketaprime3hr_name),\\n prescale=config['PrescaleD2KEtaPrime3HR'],\\n postscale=config['PostscaleD2KEtaPrime3HR'],\\n selection=self.selD2KEtaPrime3HR,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\",\n \"def Parametros_(name_path):\\n\\n\\tp = pathlib.Path(name_path)\\n\\tZ22 = []\\n\\tfor f in p.glob('*.csv'):\\n\\t\\tZ = pd.read_csv(f, header = 0)\\n\\t\\tZ = np.array(Z, dtype = np.float64 )\\n\\t\\tZ22.append(Z)\\n \\n\\tA = np.array(Z22)\\n \\n \\n\\tZ2 = A[0,:,:]\\n\\t## Adición de parámetros\\n\\tV_sys = np.append(Z2[:, 0], Z2[:, 1])\\n\\tPA = np.append(Z2[:, 2], Z2[:, 3])\\n\\ti = np.append(Z2[:, 4], Z2[:, 5])\\n\\n\\tx_0 = 4*random.rand(346) + 78\\n\\ty_0 = 4*random.rand(346) + 78\\n\\n\\tR_0 = 10*random.rand(346) + 5\\n\\tV_t = 200*random.rand(346) + 50\\n\\ta = random.rand(346) + 0.5\\n\\tg = random.rand(346) + 0.5\\n\\n\\tParams_Bek = np.vstack([x_0, y_0, V_sys, i, PA, V_t, R_0, a, g]).T\\n\\n\\tp = [\\\"x0\\\", \\\"y0\\\", \\\"v_sys\\\", \\\"i\\\", \\\"phi_0\\\", \\\"V_t\\\", \\\"R_0\\\", \\\"a\\\", \\\"g\\\"] \\n\\tfor j in range(len(Params_Bek.T)):\\n\\t\\tsb.displot((Params_Bek.T[j]).ravel(), color='#F2AB6D', bins=10, kde=False)\\n\\t\\tplt.xlabel(p[j])\\n\\t\\tplt.ylabel('Cuentas')\\n\\t\\tplt.show()\\n\\n\\treturn Params_Bek\",\n \"def sequence_params(self):\",\n \"def parse(self):\",\n \"def doParametersOfInterest(self):\\n \\n self.modelBuilder.doVar('expr::cosW(\\\"0.87681811112\\\",)')\\n self.modelBuilder.doVar('expr::sinW(\\\"0.48082221247\\\",)')\\n self.modelBuilder.doVar('expr::mZ(\\\"91.2\\\",)')\\n self.modelBuilder.doVar('expr::Lambda1(\\\"100.0\\\",)')\\n self.modelBuilder.doVar('expr::e2(\\\"0.0917\\\",)')\\n self.modelBuilder.doVar('expr::gs2(\\\"1.533\\\",)')\\n\\n # EFT Higgs basis couplings\\n\\n self.modelBuilder.doVar('cZ[0,-1,1]') \\n self.modelBuilder.doVar(\\\"cZZ[0,-2,2]\\\") \\n self.modelBuilder.doVar(\\\"cZZt[0,-2,2]\\\") \\n self.modelBuilder.doVar(\\\"cZB[0,-6,6]\\\") \\n\\n poi='cZ,cZZ,cZZt,cZB'\\n\\n # Amplitude couplings from EFT couplings \\n\\n self.modelBuilder.doVar('expr::a1(\\\"@0+1\\\",cZ)') # (\\\"2*(@0+1)\\\",cZ) in AN/Paper but a1 = 1 for signal model and width calculation\\n self.modelBuilder.doVar('expr::a2(\\\"-1*@0*(@1/(2*pow(@2,2)*pow(@3,2)))\\\",cZZ,e2,sinW,cosW)')\\n self.modelBuilder.doVar('expr::a3(\\\"-1*@0*(@1/(2*pow(@2,2)*pow(@3,2)))\\\",cZZt,e2,sinW,cosW)')\\n self.modelBuilder.doVar('expr::k1(\\\"@0*(@1*pow(@2,2)/(pow(@3,2)*pow(@4,2)))\\\",cZB,e2,Lambda1,sinW,mZ)')\\n self.modelBuilder.doVar('expr::k1L1(\\\"@0/pow(@1,2)\\\",k1,Lambda1)')\\n\\n ###### gamma_H ########\\n\\n # SMEFT relationships for VV couplings (Expressed using amplitude couplings)\\n\\n self.modelBuilder.doVar('expr::kappa(\\\"1.0\\\",)')\\n self.modelBuilder.doVar('expr::kappa_tilde(\\\"0.0\\\",)') \\n\\n self.modelBuilder.doVar('expr::a1_WW(\\\"@0\\\",a1)')\\n self.modelBuilder.doVar('expr::a2_WW(\\\"@0*@0*@1\\\",cosW,a2)')\\n self.modelBuilder.doVar('expr::a3_WW(\\\"@0*@0*@1\\\",cosW,a3)')\\n self.modelBuilder.doVar('expr::k1_WW(\\\"(@2 / (@0*@0 - @1*@1) - 2*@1*@1*@3*@4*@4 /(@5*@5*(@0*@0 - @1*@1)))\\\",cosW,sinW,k1,a2,Lambda1,mZ)')\\n self.modelBuilder.doVar('expr::k2_k1(\\\"2*@0*@1*@2/(@0*@0 - @1*@1)\\\",cosW,sinW,k1)')\\n self.modelBuilder.doVar('expr::k2_a2(\\\"-2*@0*@1*@3*@4*@4/((@2*@2)*(@0*@0 - @1*@1))\\\",cosW,sinW,mZ,a2,Lambda1)')\\n self.modelBuilder.doVar('expr::k2(\\\"@0 + @1\\\",k2_k1,k2_a2)')\\n\\n # Determine gamma_H from VV couplings\\n\\n zz_expr = '\\\"4*(@0*@0/4. + 0.1695*@3*@3 + 0.09076*@1*@1 + 0.03809*@2*@2 + 0.8095*@0*@3/2. + 0.5046*@0*@1/2. + 0.2092*@1*@3 + 0.1023*@4*@4 + 0.1901*@0*@4/2. + 0.07429*@3*@4 + 0.04710*@1*@4) \\\",a1,a2,a3,k1,k2'\\n ww_expr = '\\\"4*(@0*@0/4. + 0.1320*@3*@3 + 0.1944*@1*@1 + 0.08075*@2*@2 + 0.7204*@0*@3/2. + 0.7437*@0*@1/2. + 0.2774*@3*@1) \\\",a1_WW,a2_WW,a3_WW,k1_WW'\\n zgamma_expr = '\\\"4*(1.118600*@0*@0/4. +0.0035*@1*@1 - 0.125010*@0*@1/2. + 0.000003*@1*@1 - 0.00018*@1*@1 + 0.003100*@0*@1/2. +0.00126*@2*@2 + 0.000005*@2*@2 -0.00047*@2*@2)\\\",a1_WW,kappa,kappa_tilde'\\n gg_expr = '\\\"(1.1068*@0*@0 + 0.0082*@0*@0 - 0.1150*@0*@0 + 2.5717*@1*@1 + 0.0091*@1*@1 - 0.1982*@1*@1)\\\",kappa,kappa_tilde'\\n bb_expr = '\\\"(@0*@0 + @1*@1)\\\",kappa,kappa_tilde'\\n cc_expr = '\\\"(@0*@0 + @1*@1)\\\",kappa,kappa_tilde'\\n tautau_expr = '\\\"(@0*@0 + @1*@1)\\\",kappa,kappa_tilde'\\n mumu_expr = '\\\"(@0*@0 + @1*@1)\\\",kappa,kappa_tilde'\\n gmgm_expr = '\\\"4*(1.6054*@0*@0/4. + 0.07312*@1*@1 - 0.6854*@0*@1/2. + 0.00002*@1*@1 - 0.0018*@1*@1 + 0.0085*@0*@1/2. + 0.1699*@2*@2 + 0.00002*@2*@2 - 0.0031*@2*@2)\\\",a1_WW,kappa,kappa_tilde'\\n \\n self.modelBuilder.doVar('expr::R_WW('+str(ww_expr)+')')\\n self.modelBuilder.doVar('expr::R_ZZ('+str(zz_expr)+')')\\n self.modelBuilder.doVar('expr::R_Zgamma('+str(zgamma_expr)+')')\\n self.modelBuilder.doVar('expr::R_gg('+str(gg_expr)+')')\\n self.modelBuilder.doVar('expr::R_bb('+str(bb_expr)+')')\\n self.modelBuilder.doVar('expr::R_cc('+str(cc_expr)+')')\\n self.modelBuilder.doVar('expr::R_tautau('+str(tautau_expr)+')')\\n self.modelBuilder.doVar('expr::R_mumu('+str(mumu_expr)+')')\\n self.modelBuilder.doVar('expr:R_gammagamma('+str(gmgm_expr)+')')\\n\\n self.modelBuilder.doVar('expr::gammaH(\\\"(0.5824*@0 + 0.2137*@1 + 0.08187*@2 + 0.06272*@3 + 0.02891*@4 + 0.02619*@5 + 0.002270*@6 + 0.001533*@7 + 0.0002176*@8 )/0.9998\\\",R_bb,R_WW,R_gg,R_tautau,R_cc,R_ZZ,R_gammagamma,R_Zgamma,R_mumu)') \\n\\n ###########################\\n\\n self.g1V = GetCoupTerms(1,1,1,-0.0001,\\\"1V\\\") # Compensate for scaling of k1 templates \\n self.g2V = GetCoupTerms(1,1,1,-0.0001,\\\"2V\\\") \\n \\n self.modelBuilder.doVar(\\\"expr::g2V_1(\\\\\\\"\\\"+str(self.g2V[0])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T1(\\\\\\\"((pow(@0,4))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_1)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T1_Neg(\\\\\\\"-1*((pow(@0,4))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_1)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_2(\\\\\\\"\\\"+str(self.g2V[1])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T2(\\\\\\\"((pow(@0,3)*@1)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_2)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T2_Neg(\\\\\\\"-1*((pow(@0,3)*@1)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_2)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_3(\\\\\\\"\\\"+str(self.g2V[2])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T3(\\\\\\\"((pow(@0,2)*pow(@1,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_3)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T3_Neg(\\\\\\\"-1*((pow(@0,2)*pow(@1,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_3)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_4(\\\\\\\"\\\"+str(self.g2V[3])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T4(\\\\\\\"((@0*pow(@1,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_4)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T4_Neg(\\\\\\\"-1*((@0*pow(@1,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_4)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_5(\\\\\\\"\\\"+str(self.g2V[4])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T5(\\\\\\\"((pow(@1,4))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_5)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T5_Neg(\\\\\\\"-1*((pow(@1,4))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_5)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_6(\\\\\\\"\\\"+str(self.g2V[5])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T6(\\\\\\\"((pow(@0,3)*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_6)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T6_Neg(\\\\\\\"-1*((pow(@0,3)*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_6)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_7(\\\\\\\"\\\"+str(self.g2V[6])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T7(\\\\\\\"((pow(@0,2)*pow(@2,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_7)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T7_Neg(\\\\\\\"-1*((pow(@0,2)*pow(@2,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_7)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_8(\\\\\\\"\\\"+str(self.g2V[7])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T8(\\\\\\\"((@0*pow(@2,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_8)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T8_Neg(\\\\\\\"-1*((@0*pow(@2,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_8)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_9(\\\\\\\"\\\"+str(self.g2V[8])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T9(\\\\\\\"((pow(@2,4))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_9)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T9_Neg(\\\\\\\"-1*((pow(@2,4))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_9)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_10(\\\\\\\"\\\"+str(self.g2V[9])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T10(\\\\\\\"((pow(@0,3)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_10)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T10_Neg(\\\\\\\"-1*((pow(@0,3)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_10)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_11(\\\\\\\"\\\"+str(self.g2V[10])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T11(\\\\\\\"((pow(@0,2)*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_11)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T11_Neg(\\\\\\\"-1*((pow(@0,2)*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_11)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_12(\\\\\\\"\\\"+str(self.g2V[11])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T12(\\\\\\\"((@0*pow(@3,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_12)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T12_Neg(\\\\\\\"-1*((@0*pow(@3,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_12)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_13(\\\\\\\"\\\"+str(self.g2V[12])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T13(\\\\\\\"((pow(@3,4))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_13)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T13_Neg(\\\\\\\"-1*((pow(@3,4))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_13)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_14(\\\\\\\"\\\"+str(self.g2V[13])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T14(\\\\\\\"((pow(@1,3)*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_14)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T14_Neg(\\\\\\\"-1*((pow(@1,3)*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_14)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_15(\\\\\\\"\\\"+str(self.g2V[14])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T15(\\\\\\\"((pow(@1,2)*pow(@2,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_15)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T15_Neg(\\\\\\\"-1*((pow(@1,2)*pow(@2,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_15)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_16(\\\\\\\"\\\"+str(self.g2V[15])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T16(\\\\\\\"((@1*pow(@2,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_16)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T16_Neg(\\\\\\\"-1*((@1*pow(@2,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_16)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_17(\\\\\\\"\\\"+str(self.g2V[16])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T17(\\\\\\\"((pow(@1,3)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_17)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T17_Neg(\\\\\\\"-1*((pow(@1,3)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_17)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_18(\\\\\\\"\\\"+str(self.g2V[17])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T18(\\\\\\\"((pow(@1,2)*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_18)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T18_Neg(\\\\\\\"-1*((pow(@1,2)*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_18)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_19(\\\\\\\"\\\"+str(self.g2V[18])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T19(\\\\\\\"((@1*pow(@3,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_19)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T19_Neg(\\\\\\\"-1*((@1*pow(@3,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_19)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_20(\\\\\\\"\\\"+str(self.g2V[19])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T20(\\\\\\\"((pow(@2,3)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_20)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T20_Neg(\\\\\\\"-1*((pow(@2,3)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_20)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_21(\\\\\\\"\\\"+str(self.g2V[20])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T21(\\\\\\\"((pow(@2,2)*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_21)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T21_Neg(\\\\\\\"-1*((pow(@2,2)*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_21)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_22(\\\\\\\"\\\"+str(self.g2V[21])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T22(\\\\\\\"((@2*pow(@3,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_22)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T22_Neg(\\\\\\\"-1*((@2*pow(@3,3))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_22)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_23(\\\\\\\"\\\"+str(self.g2V[22])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T23(\\\\\\\"((@0*@1*pow(@2,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_23)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T23_Neg(\\\\\\\"-1*((@0*@1*pow(@2,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_23)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_24(\\\\\\\"\\\"+str(self.g2V[23])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T24(\\\\\\\"((@0*pow(@1,2)*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_24)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T24_Neg(\\\\\\\"-1*((@0*pow(@1,2)*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_24)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_25(\\\\\\\"\\\"+str(self.g2V[24])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T25(\\\\\\\"((pow(@0,2)*@1*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_25)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T25_Neg(\\\\\\\"-1*((pow(@0,2)*@1*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_25)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_26(\\\\\\\"\\\"+str(self.g2V[25])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T26(\\\\\\\"((@0*@1*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_26)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T26_Neg(\\\\\\\"-1*((@0*@1*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_26)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_27(\\\\\\\"\\\"+str(self.g2V[26])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T27(\\\\\\\"((@0*pow(@1,2)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_27)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T27_Neg(\\\\\\\"-1*((@0*pow(@1,2)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_27)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_28(\\\\\\\"\\\"+str(self.g2V[27])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T28(\\\\\\\"((pow(@0,2)*@1*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_28)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T28_Neg(\\\\\\\"-1*((pow(@0,2)*@1*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_28)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_29(\\\\\\\"\\\"+str(self.g2V[28])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T29(\\\\\\\"((@0*@2*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_29)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T29_Neg(\\\\\\\"-1*((@0*@2*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_29)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_30(\\\\\\\"\\\"+str(self.g2V[29])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T30(\\\\\\\"((@0*pow(@2,2)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_30)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T30_Neg(\\\\\\\"-1*((@0*pow(@2,2)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_30)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_31(\\\\\\\"\\\"+str(self.g2V[30])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T31(\\\\\\\"((pow(@0,2)*@2*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_31)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T31_Neg(\\\\\\\"-1*((pow(@0,2)*@2*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_31)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_32(\\\\\\\"\\\"+str(self.g2V[31])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T32(\\\\\\\"((@1*@2*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_32)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T32_Neg(\\\\\\\"-1*((@1*@2*pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_32)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_33(\\\\\\\"\\\"+str(self.g2V[32])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T33(\\\\\\\"((@1*pow(@2,2)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_33)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T33_Neg(\\\\\\\"-1*((@1*pow(@2,2)*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_33)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_34(\\\\\\\"\\\"+str(self.g2V[33])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T34(\\\\\\\"((pow(@1,2)*@2*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_34)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T34_Neg(\\\\\\\"-1*((pow(@1,2)*@2*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_34)\\\") \\n self.modelBuilder.doVar(\\\"expr::g2V_35(\\\\\\\"\\\"+str(self.g2V[34])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T35(\\\\\\\"((@0*@1*@2*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_35)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_Ewk_T35_Neg(\\\\\\\"-1*((@0*@1*@2*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g2V_35)\\\") \\n \\n self.modelBuilder.doVar(\\\"expr::g1V_1(\\\\\\\"\\\"+str(self.g1V[0])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T1(\\\\\\\"((pow(@0,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_1)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T1_Neg(\\\\\\\"-1*((pow(@0,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_1)\\\") \\n self.modelBuilder.doVar(\\\"expr::g1V_2(\\\\\\\"\\\"+str(self.g1V[1])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T2(\\\\\\\"((@0*@1)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_2)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T2_Neg(\\\\\\\"-1*((@0*@1)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_2)\\\") \\n self.modelBuilder.doVar(\\\"expr::g1V_3(\\\\\\\"\\\"+str(self.g1V[2])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T3(\\\\\\\"((pow(@1,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_3)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T3_Neg(\\\\\\\"-1*((pow(@1,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_3)\\\") \\n self.modelBuilder.doVar(\\\"expr::g1V_4(\\\\\\\"\\\"+str(self.g1V[3])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T4(\\\\\\\"((@0*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_4)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T4_Neg(\\\\\\\"-1*((@0*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_4)\\\") \\n self.modelBuilder.doVar(\\\"expr::g1V_5(\\\\\\\"\\\"+str(self.g1V[4])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T5(\\\\\\\"((pow(@2,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_5)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T5_Neg(\\\\\\\"-1*((pow(@2,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_5)\\\") \\n self.modelBuilder.doVar(\\\"expr::g1V_6(\\\\\\\"\\\"+str(self.g1V[5])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T6(\\\\\\\"((@0*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_6)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T6_Neg(\\\\\\\"-1*((@0*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_6)\\\") \\n self.modelBuilder.doVar(\\\"expr::g1V_7(\\\\\\\"\\\"+str(self.g1V[6])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T7(\\\\\\\"((pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_7)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T7_Neg(\\\\\\\"-1*((pow(@3,2))/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_7)\\\") \\n self.modelBuilder.doVar(\\\"expr::g1V_8(\\\\\\\"\\\"+str(self.g1V[7])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T8(\\\\\\\"((@1*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_8)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T8_Neg(\\\\\\\"-1*((@1*@2)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_8)\\\") \\n self.modelBuilder.doVar(\\\"expr::g1V_9(\\\\\\\"\\\"+str(self.g1V[8])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T9(\\\\\\\"((@1*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_9)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T9_Neg(\\\\\\\"-1*((@1*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_9)\\\") \\n self.modelBuilder.doVar(\\\"expr::g1V_10(\\\\\\\"\\\"+str(self.g1V[9])+\\\"\\\\\\\",)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T10(\\\\\\\"((@2*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_10)\\\") \\n self.modelBuilder.factory_(\\\"expr::scale_ggH_T10_Neg(\\\\\\\"-1*((@2*@3)/@4)*@5\\\\\\\", a1, a2, a3, k1L1, gammaH, g1V_10)\\\") \\n \\n self.modelBuilder.doSet(\\\"POI\\\",poi)\",\n \"def lro(self) -> global___Snippet.Lro:\",\n \"def read_params():\\n parser = ArgumentParser(description=\\\"export2graphlan.py (ver. \\\" + __version__ +\\n \\\" of \\\" + __date__ + \\\"). Convert MetaPhlAn, LEfSe, and/or HUMAnN output to GraPhlAn input format. Authors: \\\"\\n + __author__ + \\\" (\\\" + __email__ + \\\")\\\")\\n\\n # input parameters group\\n group = parser.add_argument_group(title='input parameters',\\n description=\\\"You need to provide at least one of the two arguments\\\")\\n group.add_argument('-i', '--lefse_input',\\n type=str,\\n required=False,\\n help=\\\"LEfSe input data. A file that can be given to LEfSe for biomarkers analysis. It can be the result of a \\\"\\n \\\"MetaPhlAn or HUMAnN analysis\\\")\\n group.add_argument('-o', '--lefse_output',\\n type=str,\\n required=False,\\n help=\\\"LEfSe output result data. The result of LEfSe analysis performed on the lefse_input file\\\")\\n\\n # output parameters group\\n group = parser.add_argument_group(title='output parameters')\\n group.add_argument('-t', '--tree',\\n type=str,\\n required=True,\\n help=\\\"Output filename where save the input tree for GraPhlAn\\\")\\n group.add_argument('-a', '--annotation',\\n type=str,\\n required=True,\\n help=\\\"Output filename where save GraPhlAn annotation\\\")\\n\\n # annotations\\n parser.add_argument('--annotations',\\n default=None,\\n type=str,\\n required=False,\\n help=\\\"List which levels should be annotated in the tree. Use a comma separate values form, e.g., \\\"\\n \\\"--annotation_levels 1,2,3. Default is None\\\")\\n parser.add_argument('--external_annotations',\\n default=None,\\n type=str,\\n required=False,\\n help=\\\"List which levels should use the external legend for the annotation. Use a comma separate values form, \\\"\\n \\\"e.g., --annotation_levels 1,2,3. Default is None\\\")\\n # shaded background\\n parser.add_argument('--background_levels',\\n default=None,\\n type=str,\\n required=False,\\n help=\\\"List which levels should be highlight with a shaded background. Use a comma separate values form, e.g., \\\"\\n \\\"--background_levels 1,2,3. Default is None\\\")\\n parser.add_argument('--background_clades',\\n default=None,\\n type=str,\\n required=False,\\n help=\\\"Specify the clades that should be highlight with a shaded background. Use a comma separate values form \\\"\\n \\\"and surround the string with \\\\\\\" if there are spaces. Example: --background_clades \\\\\\\"Bacteria.Actinobacteria, \\\"\\n \\\"Bacteria.Bacteroidetes.Bacteroidia, Bacteria.Firmicutes.Clostridia.Clostridiales\\\\\\\". Default is None\\\")\\n parser.add_argument('--background_colors',\\n default=None,\\n type=str,\\n required=False,\\n help=\\\"Set the color to use for the shaded background. Colors can be either in RGB or HSV (using a semi-colon to \\\"\\n \\\"separate values, surrounded with ()) format. Use a comma separate values form and surround the string with \\\"\\n \\\"\\\\\\\" if it contains spaces. Example: --background_colors \\\\\\\"#29cc36, (150; 100; 100), (280; 80; 88)\\\\\\\". Default \\\"\\n \\\"is None\\\")\\n # title\\n parser.add_argument('--title',\\n type=str,\\n required=False,\\n help=\\\"If specified set the title of the GraPhlAn plot. Surround the string with \\\\\\\" if it contains spaces, e.g., \\\"\\n \\\"--title \\\\\\\"Title example\\\\\\\"\\\")\\n # title font size\\n parser.add_argument('--title_font_size',\\n default=15,\\n type=int,\\n required=False,\\n help=\\\"Set the title font size. Default is 15\\\")\\n # clade size\\n parser.add_argument('--def_clade_size',\\n default=10.,\\n type=float,\\n required=False,\\n help=\\\"Set a default size for clades that are not found as biomarkers by LEfSe. Default is 10\\\")\\n parser.add_argument('--min_clade_size',\\n default=20.,\\n type=float,\\n required=False,\\n help=\\\"Set the minimum value of clades that are biomarkers. Default is 20\\\")\\n parser.add_argument('--max_clade_size',\\n default=200.,\\n type=float,\\n required=False,\\n help=\\\"Set the maximum value of clades that are biomarkers. Default is 200\\\")\\n # font size\\n parser.add_argument('--def_font_size',\\n default=10,\\n type=int,\\n required=False,\\n help=\\\"Set a default font size. Default is 10\\\")\\n parser.add_argument('--min_font_size',\\n default=8,\\n type=int,\\n required=False,\\n help=\\\"Set the minimum font size to use. Default is 8\\\")\\n parser.add_argument('--max_font_size',\\n default=12,\\n type=int,\\n required=False,\\n help=\\\"Set the maximum font size. Default is 12\\\")\\n # legend font size\\n parser.add_argument('--annotation_legend_font_size',\\n default=10,\\n type=int,\\n required=False,\\n help=\\\"Set the font size for the annotation legend. Default is 10\\\")\\n # abundance threshold\\n parser.add_argument('--abundance_threshold',\\n default=20.,\\n type=float,\\n required=False,\\n help=\\\"Set the minimun abundace value for a clade to be annotated. Default is 20.0\\\")\\n # ONLY lefse_input provided\\n parser.add_argument('--most_abundant',\\n default=10,\\n type=int,\\n required=False,\\n help=\\\"When only lefse_input is provided, you can specify how many clades highlight. Since the biomarkers are \\\"\\n \\\"missing, they will be chosen from the most abundant. Default is 10\\\")\\n parser.add_argument('--least_biomarkers',\\n default=3,\\n type=int,\\n required=False,\\n help=\\\"When only lefse_input is provided, you can specify the minimum number of biomarkers to extract. The \\\"\\n \\\"taxonomy is parsed, and the level is choosen in order to have at least the specified number of biomarkers. \\\"\\n \\\"Default is 3\\\")\\n # decide to keep the OTU id or to merger at the above taxonomic level\\n parser.add_argument('--discard_otus',\\n default=True,\\n action='store_false',\\n help=\\\"If specified the OTU ids will be discarde from the taxonmy. Default is True, i.e. keep OTUs IDs in taxonomy\\\")\\n # decide to keep the OTU id or to merger at the above taxonomic level\\n parser.add_argument('--internal_levels',\\n default=False,\\n action='store_true',\\n help=\\\"If specified sum-up from leaf to root the abundances values. Default is False, i.e. do not sum-up abundances \\\"\\n \\\"on the internal nodes\\\")\\n\\n DataMatrix.input_parameters(parser)\\n args = parser.parse_args()\\n\\n # check if at least one of the input params is given\\n if (not args.lefse_input) and (not args.lefse_output):\\n raise Exception(\\\"[read_params()] You must provide at least one of the two input parameters: \\\")\\n\\n # check that min_clade_size is less than max_clade_size\\n if args.min_clade_size > args.max_clade_size:\\n print \\\"[W] min_clade_size cannot be greater than max_clade_size, assigning their default values\\\"\\n args.min_clade_size = 20.\\n args.max_clade_size = 200.\\n\\n # check that min_font_size is less than max_font_size\\n if args.min_font_size > args.max_font_size:\\n print \\\"[W] min_font_size cannot be greater than max_font_size, assigning their default values\\\"\\n args.min_font_size = 8\\n args.max_font_size = 12\\n\\n return args\",\n \"def preprocess(self):\",\n \"def parliament(parl):\\n\\tglobal PARLIAMENT\\n\\tPARLIAMENT = parl\",\n \"def __init__(self, source, filenum, linenum, param_list, ops_raw_list, ops_list):\\n self.gate_definition = {\\n 'source': source,\\n 'filenum': filenum,\\n 'linenum': linenum,\\n 'param_list': param_list,\\n 'ops_raw_list': ops_raw_list,\\n 'ops_list': ops_list}\",\n \"def __init__(self):\\n mi_parqueo = list()\",\n \"def __init__(self, r=1, p=3):\\n self.p = p\\n self.r = r\",\n \"def __init__(self, espectro, Npicos):\\r\\n self.Npicos = Npicos\\r\\n self.spec = espectro.real\\r\\n self.ppmGridDir = espectro.ppmGridDir\\r\\n self.ppmGridInd = espectro.ppmGridInd \\r\\n self.regiones = self.crear_regiones(Npicos)\\r\\n self.integrales = None\",\n \"def initParms(self):\\n self.parmVal = []\\n self.parmName = []\\n (nvect, npt) = self.data.shape\\n if self.model == 0:\\n self.parmVal.append(2.0)\\n self.parmName.append('Order')\\n if self.model == 1:\\n self.parmVal.append(1.0)\\n self.parmName.append('A')\\n self.parmVal.append(1.0)\\n self.parmName.append('B')\\n if self.model == 2:\\n self.parmVal.append(self.data[1][0])\\n self.parmName.append('A')\\n self.parmVal.append(self.data[1][npt-1])\\n self.parmName.append('B')\\n if self.model == 3:\\n self.parmVal.append(self.data[1][0])\\n self.parmName.append('Ao')\\n self.parmVal.append(100.0)\\n self.parmName.append('Ea')\\n if self.model == 4:\\n self.parmVal.append(0.001)\\n self.parmName.append('A')\\n self.parmVal.append(1.0)\\n self.parmName.append('B')\\n if self.model == 5:\\n self.parmVal.append(0.001)\\n self.parmName.append('A')\\n self.parmVal.append(0.0)\\n self.parmName.append('B')\\n self.parmVal.append(1.0)\\n self.parmName.append('C')\\n if self.model == 6:\\n self.parmVal.append(self.data[0][0])\\n self.parmName.append('xo')\\n self.parmVal.append(self.data[1][0])\\n self.parmName.append('yo')\\n yspan = getSpan(self.data[1])\\n if self.data[1][0] > 0.0:\\n v = self.data[1][0] + yspan/2.0\\n else:\\n v = self.data[1][npt-1] + yspan/2.0\\n self.parmVal.append(v)\\n self.parmName.append('H')\\n if self.data[1][0] > self.data[1][npt-1]:\\n self.parmVal.append(-1.0)\\n else:\\n self.parmVal.append(1.0)\\n self.parmName.append('S')\",\n \"def init_params(self):\\n blah\",\n \"def __init__(self, parameter_set):\\n self.parameter_set = parameter_set.to_parameterization('Meijaard2007')\",\n \"def __init__(self, stage_dir, points=[],lines=[],polygons=[]):\\n self.points = points\\n self.lines = lines\\n self.polygons = polygons\\n self.output_ini = stage_dir + \\\"/osmconf.ini\\\"\",\n \"def __init__():\\n self.placa = placa\",\n \"def __init__(self,manager,name):\\n Online.DatapointLoader.DatapointLoader.__init__(self,manager,name)\\n self.dpName = self.name\\n self.activityName = self.dp('Name')\\n self.farmInfrastructure = self.dp('Farm.Infrastructure')\\n self.farmWorker = self.dp('Farm.Worker')\\n self.ctrlInfrastructure = self.dp('Control.Infrastructure')\\n self.inputInfrastructure = self.dp('Storage.streamInfrastructure')\\n self.inputTypes = self.dp('Storage.streamTypes')\\n self.outputInfrastructure = self.dp('Storage.recvInfrastructure')\\n self.outputTypes = self.dp('Storage.recvTypes')\\n self.addDp(self.reader)\",\n \"def __init__(self, name, p, a, b, q, gx, gy, oid=None):\\n self.name = name\\n self.p = p\\n self.a = a\\n self.b = b\\n self.q = q\\n self.gx = gx\\n self.gy = gy\\n self.oid = oid\",\n \"def schema(self):\",\n \"def __init__(self):\\n self.nombre_roues = 4\\n self.nombre_fauteils = 1\\n self.moteur = False\\n self.volant = True\",\n \"def define_parameters(parser):\\n parser.add_argument(\\\"--bson\\\", help=\\\"If the language supports add bson tags or bson representation to the structure\\\", action=\\\"store_true\\\")\\n parser.add_argument(\\\"--csv\\\", help=\\\"If the language supports add CSV tags or CSV representation to the structure\\\", action=\\\"store_true\\\")\\n parser.add_argument(\\\"--db\\\", help=\\\"adds db tags to Go structs.\\\" , action=\\\"store_true\\\")\\n parser.add_argument(\\\"--input\\\", default=\\\"\\\", help=\\\"the path to the input CSV file\\\",type=str )\\n parser.add_argument(\\\"--input-dir\\\", default=\\\"\\\", help=\\\"the path to the directory that contains the CSV files to parse\\\",type=str )\\n parser.add_argument(\\\"--json\\\", help=\\\"If the language supports add JSON tags or JSON representation to the structure\\\", action=\\\"store_true\\\")\\n parser.add_argument(\\\"--package\\\", help=\\\"sets the package to the correct name for Go structs\\\", action=\\\"store_true\\\")\\n parser.add_argument(\\\"--language\\\", choices=[LANG_GO], default=LANG_GO, help=\\\"create language specific data structures\\\", required=True, type=str)\\n parser.add_argument(\\\"--name\\\", help=\\\"name of the data structure being created\\\", type=str)\\n parser.add_argument(\\\"--output-dir\\\", help=\\\"the directory where the generated file should be written. If not provided file will be written to stdout\\\")\\n parser.add_argument(\\\"--verbose\\\", help=\\\"more output during the parsing and creation of the data structures\\\", action=\\\"store_true\\\")\",\n \"def __init__(self, traindf, params):\\n default_args = {\\n \\\"seqin\\\": 0,\\n \\\"smode\\\": \\\"positional\\\", #site mode\\n \\\"direction\\\": \\\"inout\\\",\\n \\\"positive_cores\\\" : [],\\n \\\"poscols\\\": [],\\n \\\"namecol\\\":\\\"Name\\\",\\n \\\"seqcol\\\":\\\"Sequence\\\",\\n }\\n self.df = traindf\\n self.set_attrs(params, default_args)\\n if self.smode != \\\"relative\\\" and self.smode != \\\"positional\\\":\\n raise TypeError(\\\"Smode can only be 'relative' or 'positional'\\\")\\n if self.direction != \\\"inout\\\" and self.direction != \\\"orientation\\\":\\n raise TypeError(\\\"Direction can only be 'inout' or 'orientation'\\\")\\n if self.direction == \\\"orientation\\\" and (\\\"positive_cores\\\" not in params or not params[\\\"positive_cores\\\"]):\\n raise TypeError(\\\"Positive cores are needed when direction is 'orientation'\\\")\\n\\n if self.namecol in self.df:\\n fastadict = dict(zip(self.df[self.namecol], self.df[self.seqcol]))\\n shapeobj = ds.DNAShape(fastadict)\\n else:\\n shapeobj = ds.DNAShape(self.df[self.seqcol].tolist())\\n self.shapes = {k:getattr(shapeobj,k.lower()) for k in shapeobj.shapetypes}\\n # make a dictionary of list instead of nested dictionary since we use this\\n # as features\\n if self.namecol in self.df:\\n namelist = self.df[self.namecol].tolist()\\n else:\\n namelist = next(iter(self.shapes.values())).keys()\\n self.shapes = {k:[v[str(n)] for n in namelist] for k, v in self.shapes.items()}\\n if self.direction == \\\"orientation\\\":\\n ori = Orientation(self.df, {\\\"positive_cores\\\":self.positive_cores}).get_feature()\\n self.df[\\\"orientation\\\"] = [o[\\\"ori\\\"] for o in ori]\",\n \"def _regr_basic():\",\n \"def get_parameters(self):\\n # Get the parameters from the parent class\\n params = super(LPEvalSplit, self).get_parameters()\\n\\n # Add the LP specific parameters\\n params.update({\\\"owa\\\": self._owa, \\\"fe_ratio\\\": self._fe_ratio})\\n return params\",\n \"def default_pypeit_par(cls):\\n par = super().default_pypeit_par()\\n\\n par['rdx']['detnum'] = [(1,2,3)]\\n\\n # Adjustments to parameters for Keck HIRES\\n turn_on = dict(use_biasimage=False, use_overscan=True, overscan_method='median',\\n use_darkimage=False, use_illumflat=False, use_pixelflat=False,\\n use_specillum=False)\\n par.reset_all_processimages_par(**turn_on)\\n par['calibrations']['traceframe']['process']['overscan_method'] = 'median'\\n\\n # Right now we are using the overscan and not biases becuase the\\n # standards are read with a different read mode and we don't yet have\\n # the option to use different sets of biases for different standards,\\n # or use the overscan for standards but not for science frames\\n # TODO testing\\n par['scienceframe']['process']['use_biasimage'] = False\\n par['scienceframe']['process']['use_illumflat'] = False\\n par['scienceframe']['process']['use_pixelflat'] = False\\n par['calibrations']['standardframe']['process']['use_illumflat'] = False\\n par['calibrations']['standardframe']['process']['use_pixelflat'] = False\\n # par['scienceframe']['useframe'] ='overscan'\\n\\n par['calibrations']['slitedges']['edge_thresh'] = 8.0\\n par['calibrations']['slitedges']['fit_order'] = 8\\n par['calibrations']['slitedges']['max_shift_adj'] = 0.5\\n par['calibrations']['slitedges']['trace_thresh'] = 10.\\n par['calibrations']['slitedges']['left_right_pca'] = True\\n par['calibrations']['slitedges']['length_range'] = 0.3\\n par['calibrations']['slitedges']['max_nudge'] = 0.\\n par['calibrations']['slitedges']['overlap'] = True\\n par['calibrations']['slitedges']['dlength_range'] = 0.25\\n\\n # These are the defaults\\n par['calibrations']['tilts']['tracethresh'] = 15\\n par['calibrations']['tilts']['spat_order'] = 3\\n par['calibrations']['tilts']['spec_order'] = 5 # [5, 5, 5] + 12*[7] # + [5]\\n\\n # 1D wavelength solution\\n par['calibrations']['wavelengths']['lamps'] = ['ThAr']\\n # This is for 1x1 binning. TODO GET BINNING SORTED OUT!!\\n par['calibrations']['wavelengths']['rms_threshold'] = 0.50\\n par['calibrations']['wavelengths']['sigdetect'] = 5.0\\n par['calibrations']['wavelengths']['n_final'] = 4 #[3] + 13 * [4] + [3]\\n # This is for 1x1 binning. Needs to be divided by binning for binned data!!\\n par['calibrations']['wavelengths']['fwhm'] = 8.0\\n # Reidentification parameters\\n par['calibrations']['wavelengths']['method'] = 'echelle'\\n # TODO: the arxived solution is for 1x1 binning. It needs to be\\n # generalized for different binning!\\n #par['calibrations']['wavelengths']['reid_arxiv'] = 'vlt_xshooter_vis1x1.fits'\\n par['calibrations']['wavelengths']['cc_thresh'] = 0.50\\n par['calibrations']['wavelengths']['cc_local_thresh'] = 0.50\\n# par['calibrations']['wavelengths']['ech_fix_format'] = True\\n # Echelle parameters\\n par['calibrations']['wavelengths']['echelle'] = True\\n par['calibrations']['wavelengths']['ech_nspec_coeff'] = 4\\n par['calibrations']['wavelengths']['ech_norder_coeff'] = 4\\n par['calibrations']['wavelengths']['ech_sigrej'] = 3.0\\n par['calibrations']['wavelengths']['ech_separate_2d'] = True\\n\\n # Flats\\n par['calibrations']['flatfield']['tweak_slits_thresh'] = 0.90\\n par['calibrations']['flatfield']['tweak_slits_maxfrac'] = 0.10\\n\\n # Extraction\\n par['reduce']['skysub']['bspline_spacing'] = 0.6\\n par['reduce']['skysub']['global_sky_std'] = False\\n # local sky subtraction operates on entire slit\\n par['reduce']['extraction']['model_full_slit'] = True\\n # Mask 3 edges pixels since the slit is short, insted of default (5,5)\\n par['reduce']['findobj']['find_trim_edge'] = [3, 3]\\n # Continnum order for determining thresholds\\n\\n # Sensitivity function parameters\\n par['sensfunc']['algorithm'] = 'IR'\\n par['sensfunc']['polyorder'] = 11 #[9, 11, 11, 9, 9, 8, 8, 7, 7, 7, 7, 7, 7, 7, 7]\\n par['sensfunc']['IR']['telgridfile'] = 'TelFit_MaunaKea_3100_26100_R20000.fits'\\n return par\",\n \"def Parameters():\\n\\n raise NotImplementedError()\",\n \"def __init__(self, name, typing, reflection, year):#Taking in parameters\\n self.n = name#Assigning variables\\n self.t = typing\\n self.r = reflection\\n self.y = year\",\n \"def __init__(self):\\n self.name = ''\\n self.variables = []\\n self.assumptions = []\\n self.guarantees = []\",\n \"def create_type_area_object(): \\n RefValues()\\n RefValues().add_ref_parameter_from_file('DIN_winter', 'D:/Utveckling/g_EKOSTAT_tool/test_data/din_vinter.txt')\\n RefValues().add_ref_parameter_from_file('TOTN_winter', 'D:/Utveckling/g_EKOSTAT_tool/test_data/totn_vinter.txt')\",\n \"def __init__(self, manager, name):\\n Online.DatapointLoader.DatapointLoader.__init__(self,manager,name)\\n self.strerror = ''\\n self.sfName = self.dp('Name')\\n self.nodes = self.dp('Nodes')\\n self.usedby = self.dp('UsedBy')\\n self.setup = self.dp('Activity')\\n self.runInfo = self.dp('RunInfo')\\n self.writer = self.manager.devWriter()\\n self.addDp(self.reader)\",\n \"def __init__(self, name, config):\\n self.name = name\\n self.config = config\\n LineBuilder.__init__(self, name, config)\\n \\n phi3hm_name = '{0}Phi3HM'.format(name)\\n phi3hr_name = '{0}Phi3HR'.format(name)\\n \\n d2piphi3hm_name = '{0}D2PiPhi3HM'.format(name)\\n d2piphi3hr_name = '{0}D2PiPhi3HR'.format(name)\\n \\n d2kphi3hm_name = '{0}D2KPhi3HM'.format(name)\\n d2kphi3hr_name = '{0}D2KPhi3HR'.format(name)\\n \\n\\n self.selPhi3HM = makeResonance(\\n phi3hm_name,\\n config,\\n inputSel=[StdAllNoPIDsPions,StdLooseMergedPi0],\\n decDescriptors=self.Phi3H\\n )\\n\\n self.selPhi3HR = makeResonance(\\n phi3hr_name,\\n config,\\n inputSel=[StdAllNoPIDsPions,StdLooseResolvedPi0],\\n decDescriptors=self.Phi3H\\n )\\n \\n self.selD2PiPhi3HM = makeD(\\n d2piphi3hm_name,\\n config,\\n inputSel=[self.selPhi3HM, StdAllNoPIDsPions],\\n decDescriptors=self.D2PiPhi,\\n useBachelorPID=False,\\n )\\n \\n self.selD2KPhi3HM = makeD(\\n d2kphi3hm_name,\\n config,\\n inputSel=[self.selPhi3HM, StdAllNoPIDsKaons],\\n decDescriptors=self.D2KPhi,\\n useBachelorPID=False,\\n )\\n \\n self.selD2PiPhi3HR = makeD(\\n d2piphi3hr_name,\\n config,\\n inputSel=[self.selPhi3HR, StdAllNoPIDsPions],\\n decDescriptors=self.D2PiPhi,\\n useBachelorPID=False,\\n )\\n \\n self.selD2KPhi3HR = makeD(\\n d2kphi3hr_name,\\n config,\\n inputSel=[self.selPhi3HR, StdAllNoPIDsKaons],\\n decDescriptors=self.D2KPhi,\\n useBachelorPID=False,\\n )\\n \\n self.line_D2PiPhi3HM = make_line(\\n self,\\n name='{0}Line'.format(d2piphi3hm_name),\\n prescale=config['PrescaleD2PiPhi3HM'],\\n postscale=config['PostscaleD2PiPhi3HM'],\\n selection=self.selD2PiPhi3HM,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n \\n self.line_D2PiPhi3HR = make_line(\\n self,\\n name='{0}Line'.format(d2piphi3hr_name),\\n prescale=config['PrescaleD2PiPhi3HR'],\\n postscale=config['PostscaleD2PiPhi3HR'],\\n selection=self.selD2PiPhi3HR,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n self.line_D2KPhi3HM = make_line(\\n self,\\n name='{0}Line'.format(d2kphi3hm_name),\\n prescale=config['PrescaleD2KPhi3HM'],\\n postscale=config['PostscaleD2KPhi3HM'],\\n selection=self.selD2KPhi3HM,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n \\n self.line_D2KPhi3HR = make_line(\\n self,\\n name='{0}Line'.format(d2kphi3hr_name),\\n prescale=config['PrescaleD2KPhi3HR'],\\n postscale=config['PostscaleD2KPhi3HR'],\\n selection=self.selD2KPhi3HR,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\",\n \"def __init__(self, main_params, projs):\\n self.__dict__ = vars(main_params)\\n self.projs = projs\\n self.proj, self.model, self.var, self.region = (\\n self.str_to_aospy_iterable(main_params.proj, main_params.model,\\n main_params.var, main_params.region)\\n )\\n self.run = self.create_child_run_obj(self.model, self.run, self.proj)\\n self.region = [aospy.utils.io.dict_name_keys(self.region)]\",\n \"def parlist(model_info, pars, is2d):\\n if is2d:\\n exclude = lambda n: False\\n else:\\n partype = model_info['partype']\\n par1d = set(partype['fixed-1d']+partype['pd-1d'])\\n exclude = lambda n: n not in par1d\\n lines = []\\n for p in model_info['parameters']:\\n if exclude(p.name): continue\\n fields = dict(\\n value=pars.get(p.name, p.default),\\n pd=pars.get(p.name+\\\"_pd\\\", 0.),\\n n=int(pars.get(p.name+\\\"_pd_n\\\", 0)),\\n nsigma=pars.get(p.name+\\\"_pd_nsgima\\\", 3.),\\n type=pars.get(p.name+\\\"_pd_type\\\", 'gaussian'))\\n lines.append(_format_par(p.name, **fields))\\n return \\\"\\\\n\\\".join(lines)\\n\\n #return \\\"\\\\n\\\".join(\\\"%s: %s\\\"%(p, v) for p, v in sorted(pars.items()))\",\n \"def add_parameters(params):\\n\\n items = [\\n ('x', 'X manual', ''),\\n ('z', 'Z manual', ''),\\n ('automatic', 'Automatic', '')\\n ]\\n\\n params.rotation_axis = bpy.props.EnumProperty(\\n items = items,\\n name = \\\"Rotation Axis\\\",\\n default = 'automatic'\\n )\\n\\n params.auto_align_extremity = bpy.props.BoolProperty(\\n name='auto_align_extremity',\\n default=False,\\n description=\\\"Auto Align Extremity Bone\\\"\\n )\\n\\n params.segments = bpy.props.IntProperty(\\n name = 'limb segments',\\n default = 2,\\n min = 1,\\n description = 'Number of segments'\\n )\\n\\n params.bbones = bpy.props.IntProperty(\\n name = 'bbone segments',\\n default = 10,\\n min = 1,\\n description = 'Number of segments'\\n )\\n\\n # Setting up extra layers for the FK and tweak\\n params.tweak_extra_layers = bpy.props.BoolProperty(\\n name = \\\"tweak_extra_layers\\\",\\n default = True,\\n description = \\\"\\\"\\n )\\n\\n params.tweak_layers = bpy.props.BoolVectorProperty(\\n size = 32,\\n description = \\\"Layers for the tweak controls to be on\\\",\\n default = tuple( [ i == 1 for i in range(0, 32) ] )\\n )\\n\\n # Setting up extra layers for the FK and tweak\\n params.fk_extra_layers = bpy.props.BoolProperty(\\n name = \\\"fk_extra_layers\\\",\\n default = True,\\n description = \\\"\\\"\\n )\\n\\n params.fk_layers = bpy.props.BoolVectorProperty(\\n size = 32,\\n description = \\\"Layers for the FK controls to be on\\\",\\n default = tuple( [ i == 1 for i in range(0, 32) ] )\\n )\",\n \"def __init__(self, number, title, paragraphs):\\n self.number = number\\n self.title = title\\n self.paragraphs = []\\n for paragraph_lines in paragraphs:\\n new_pragraph = Paragraph.Paragraph(paragraph_lines)\\n self.paragraphs.append(new_pragraph)\",\n \"def __init__(self,paramFile='yaml/grism_example.yaml'):\\n self.pandeia_params = yaml.load(open(paramFile))\\n self.prep_and_run()\",\n \"def write_parameters(par, version='git-devel'):\\n # read template\\n file = findpath('sesiflows.seistools') + '/' + 'specfem2d/par-' + version\\n with open(file, 'r') as f:\\n lines = f.readlines()\\n lines[-1] = ' '.join(['1', str(par.NX), '1', str(par.NZ), '1'])\\n\\n # write parameter file\\n file = 'DATA/Par_file'\\n _writelines(file, lines)\\n setpar('xmin', str(par.XMIN))\\n setpar('xmax', str(par.XMAX))\\n setpar('nx', str(par.NX))\\n setpar('nt', str(par.NT))\\n setpar('deltat', str(par.DT))\\n setpar('nsources', str(1))\\n\\n # write interfaces file\\n file = 'DATA/interfaces.dat'\\n lines = []\\n lines.extend('2\\\\n')\\n lines.extend('2\\\\n')\\n lines.extend('%f %f\\\\n'%(par.XMIN, par.ZMIN))\\n lines.extend('%f %f\\\\n'%(par.XMAX, par.ZMIN))\\n lines.extend('2\\\\n')\\n lines.extend('%f %f\\\\n'%(par.XMIN, par.ZMAX))\\n lines.extend('%f %f\\\\n'%(par.XMAX, par.ZMAX))\\n lines.extend(str(par.NZ))\\n _writelines(file, lines)\",\n \"def poseReaderRig(objs,space=1,name=None, nameOverride=0):\\n if not pm.pluginInfo(\\\"poseReader\\\",q=1,loaded=1):\\n pm.loadPlugin(\\\"poseReader.so\\\")\\n if len(objs)<=0:\\n pm.error((\\\"poseReaderUI: You must select one or more objects to create a poseReader node for!\\\"),sl=0)\\n poses=[]\\n # Store created nodes for sel at end\\n obj=''\\n for obj in objs:\\n Obj=pm.util.capitalize(obj)\\n # new to maya 6, tho it is a script....\\n if name == None:\\n pose=pm.createNode(\\\"poseReader\\\",n=(\\\"poseReader_\\\" + Obj + \\\"Shape#\\\"))\\n else:\\n if nameOverride==0:\\n pose=pm.createNode(\\\"poseReader\\\",n=(\\\"poseReader_\\\" + Obj+name+'Shape'))\\n elif nameOverride==1:\\n if name[-5:]=='Shape':\\n pose=pm.createNode(\\\"poseReader\\\",n=name)\\n else:\\n pose=pm.createNode(\\\"poseReader\\\",n=name+'Shape')\\n attr=\\\"worldMatrix\\\"\\n if space == 2:\\n attr=\\\"matrix\\\"\\n\\n pm.connectAttr((obj + \\\".\\\" + attr),(pose + \\\".worldMatrixLiveIn\\\"),f=1)\\n xform=pm.listRelatives(pose,p=1)[0]\\n pm.connectAttr((xform + \\\".\\\" + attr),(pose + \\\".worldMatrixPoseIn\\\"),f=1)\\n poses.append(xform)\\n # Actually store xform for sel.\\n # Make a keyable attr people can actually see and use.\\n pm.addAttr(pose,ln=\\\"weight\\\",k=1)\\n pm.connectAttr((pose + \\\".outWeight\\\"),(pose + \\\".weight\\\"),f=1)\\n # Parent to same parent that object has.\\n # Very important if using local space.\\n parent=pm.listRelatives(obj,p=1)[0]\\n if parent != \\\"\\\":\\n pm.parent(xform,parent)\\n # match rotate order of obj\\n rotOrder = pm.getAttr(obj+'.rotateOrder')\\n xform.attr('rotateOrder').set(rotOrder)\\n # Snap xform to same as obj\\n pCons=pm.pointConstraint(obj,xform,w=1)\\n oCons=pm.orientConstraint(obj,xform,w=1)\\n pm.delete(pCons,oCons)\\n # Also make up animCurve for animCurve mode\\n animCurve=pm.createNode('animCurveUU')\\n pm.setKeyframe(animCurve,itt=\\\"flat\\\",v=1.0,ott=\\\"flat\\\",f=0.0)\\n pm.setKeyframe(animCurve,itt=\\\"spline\\\",v=0.85,ott=\\\"spline\\\",f=0.25)\\n pm.setKeyframe(animCurve,itt=\\\"spline\\\",v=0.15,ott=\\\"spline\\\",f=0.75)\\n pm.setKeyframe(animCurve,itt=\\\"flat\\\",v=0.0,ott=\\\"flat\\\",f=1.0)\\n pm.connectAttr((animCurve + \\\".message\\\"),(pose + \\\".msgAnimCurve\\\"),f=1)\\n pm.connectAttr((animCurve + \\\".output\\\"),(pose + \\\".animCurveOutput\\\"),f=1)\\n\\n pm.select(poses,r=1)\\n # Now if we have more than one pose...connect them up to a multiTrigger node\\n nPoses=len(poses)\\n if nPoses>1:\\n trig=pm.createNode(\\\"multiTrigger\\\")\\n # Make a keyable attr people can actually see and use.\\n pm.addAttr(trig,ln=\\\"weight\\\",k=1)\\n pm.connectAttr((trig + \\\".outWeight\\\"),(trig + \\\".weight\\\"),f=1)\\n i=0\\n for i in range(0,nPoses):\\n pm.connectAttr((poses[i] + \\\".weight\\\"),(trig + \\\".inputValues[\\\" + str(i) + \\\"]\\\"),f=1)\\n pm.select(poses,trig,r=1)\\n return pose\",\n \"def load(self, p):\\n return\",\n \"def __init__(self):\\n Page.__init__(self, u\\\"Paraboloide Elíptico<br><br>F(x,y)=(x, y, x<sup>2</sup>/a<sup>2</sup> + y<sup>2</sup>/b<sup>2</sup>)\\\")\\n\\n z = 0.5\\n par = RevolutionPlot3D(lambda r, t: r ** 2 + z, (0, 1), (0, 2 * pi))\\n\\n x, y, z2, u, v, cose, sen, t = createVars(['x', 'y', 'z', 'u', 'v', 'cos', 'sen', 't'])\\n\\n mesh1 = Plot3D(lambda x, y, h: h * (x ** 2 + y ** 2 + z - .01), (-1, 1), (-1, 1))\\n mesh1.addEqn(x**2+y**2 - z2**2 == 1)\\n mesh1.addFunction(lambda x, y, h: h * (x ** 2 + y ** 2 + z + .01))\\n mesh1.setLinesVisible(True)\\n mesh1.setMeshVisible(False)\\n mesh1.setBoundingBox(zrange=(-1, 1.5))\\n par.setAmbientColor(_1(145, 61, 74))\\n par.setDiffuseColor(_1(145, 61, 74))\\n par.setSpecularColor(_1(145, 61, 74))\\n baseplane = BasePlane()\\n baseplane.setHeight(0)\\n baseplane.setRange((-2, 2, 7))\\n\\n self.addChild(par)\\n self.addChild(mesh1)\\n self.addChild(baseplane)\",\n \"def load_standard_parameters(self):\\n paradic = {'x':'0',\\n 'y':'0',\\n 'n_oct':'8',\\n 'n_spo':'3',\\n 'sigma_min':'0.8',\\n 'delta_min':'0.5',\\n 'sigma_in':'0.5',\\n 'C_DoG':'0.015',\\n 'C_edge':'10',\\n 'n_bins':'36',\\n 'lambda_ori':'1.5',\\n 't':'0.8',\\n 'n_hist':'4',\\n 'n_ori':'8',\\n 'lambda_descr':'6',\\n 'flag_match':'1',\\n 'C_match':'0.6'}\\n self.cfg['param']['paradic'] = paradic\\n self.cfg.save()\",\n \"def __init__(self, p1_proba=0.5):\\n self.p1_proba = p1_proba\",\n \"def __init__(self, path):\\n # load ptv_par\\n ptvParams = par.PtvParams(path=path)\\n ptvParams.read()\\n self.n_img = ptvParams.n_img\\n\\n # load cal_ori\\n calOriParams = par.CalOriParams(self.n_img, path=path)\\n calOriParams.read()\\n\\n for i in range(self.n_img):\\n self.oriEditors.append(\\n oriEditor(calOriParams.img_ori[i])\\n )\",\n \"def attributes(self):\",\n \"def __init__(self):\\n\\n # The object is already initialised.\\n if self._initialised: return\\n\\n # Execute the base class __init__ method.\\n Param_list.__init__(self)\\n\\n # Add the model variables.\\n self._add_model_info()\\n\\n # Add the base data.\\n self._add_align_data()\\n\\n # Add the parameters of all models.\\n self._add(\\n 'pivot_x',\\n scope = 'global',\\n units = 'Angstrom',\\n desc = 'The pivot point position x coordinate',\\n py_type = float,\\n set = 'params',\\n scaling = 1e2,\\n grid_lower = pivot_x_lower,\\n grid_upper = pivot_x_upper,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'pivot_y',\\n scope = 'global',\\n units = 'Angstrom',\\n desc = 'The pivot point position y coordinate',\\n py_type = float,\\n set = 'params',\\n scaling = 1e2,\\n grid_lower = pivot_y_lower,\\n grid_upper = pivot_y_upper,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'pivot_z',\\n scope = 'global',\\n units = 'Angstrom',\\n desc = 'The pivot point position z coordinate',\\n py_type = float,\\n set = 'params',\\n scaling = 1e2,\\n grid_lower = pivot_z_lower,\\n grid_upper = pivot_z_upper,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'ave_pos_x',\\n scope = 'global',\\n units = 'Angstrom',\\n desc = 'The average position x translation',\\n py_type = float,\\n set = 'params',\\n grid_lower = -5,\\n grid_upper = 5,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'ave_pos_y',\\n scope = 'global',\\n units = 'Angstrom',\\n desc = 'The average position y translation',\\n py_type = float,\\n set = 'params',\\n grid_lower = -5,\\n grid_upper = 5,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'ave_pos_z',\\n scope = 'global',\\n units = 'Angstrom',\\n desc = 'The average position z translation',\\n py_type = float,\\n set = 'params',\\n grid_lower = -5,\\n grid_upper = 5,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'ave_pos_alpha',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The average position alpha Euler angle',\\n py_type = float,\\n set = 'params',\\n grid_lower = 0.0,\\n grid_upper = angle_upper_excluding_bound,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'ave_pos_beta',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The average position beta Euler angle',\\n py_type = float,\\n set = 'params',\\n grid_lower = 0.0,\\n grid_upper = pi,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'ave_pos_gamma',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The average position gamma Euler angle',\\n py_type = float,\\n set = 'params',\\n grid_lower = 0.0,\\n grid_upper = angle_upper_excluding_bound,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'eigen_alpha',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The Eigenframe alpha Euler angle',\\n py_type = float,\\n set = 'params',\\n grid_lower = 0.0,\\n grid_upper = angle_upper_excluding_bound,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'eigen_beta',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The Eigenframe beta Euler angle',\\n py_type = float,\\n set = 'params',\\n grid_lower = 0.0,\\n grid_upper = pi,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'eigen_gamma',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The Eigenframe gamma Euler angle',\\n py_type = float,\\n set = 'params',\\n grid_lower = 0.0,\\n grid_upper = angle_upper_excluding_bound,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'axis_theta',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The cone axis polar angle (for the isotropic cone model)',\\n py_type = float,\\n set = 'params',\\n grid_lower = 0.0,\\n grid_upper = pi,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'axis_phi',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The cone axis azimuthal angle (for the isotropic cone model)',\\n py_type = float,\\n set = 'params',\\n grid_lower = 0.0,\\n grid_upper = angle_upper_excluding_bound,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'axis_alpha',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The rotor axis alpha angle (the rotation angle out of the xy plane)',\\n py_type = float,\\n set = 'params',\\n grid_lower = -pi,\\n grid_upper = axis_alpha_upper,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'cone_theta_x',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The pseudo-ellipse cone opening half-angle for the x-axis',\\n py_type = float,\\n set = 'params',\\n grid_lower = cone_angle_lower,\\n grid_upper = cone_angle_upper,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'cone_theta_y',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The pseudo-ellipse cone opening half-angle for the y-axis',\\n py_type = float,\\n set = 'params',\\n grid_lower = cone_angle_lower,\\n grid_upper = cone_angle_upper,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'cone_theta',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The isotropic cone opening half-angle',\\n py_type = float,\\n set = 'params',\\n grid_lower = cone_angle_lower,\\n grid_upper = cone_angle_upper,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'cone_s1',\\n scope = 'global',\\n units = '',\\n desc = 'The isotropic cone order parameter',\\n py_type = float,\\n set = 'params',\\n grid_lower = -0.125,\\n grid_upper = 1.0,\\n err = True,\\n sim = True\\n )\\n self._add(\\n 'cone_sigma_max',\\n scope = 'global',\\n units = 'rad',\\n desc = 'The torsion angle',\\n py_type = float,\\n set = 'params',\\n grid_lower = cone_angle_lower,\\n grid_upper = cone_angle_upper,\\n err = True,\\n sim = True\\n )\\n\\n # Add minimisation structures.\\n self._add_min_data(min_stats_global=True)\\n\\n # Set up the user function documentation.\\n self._set_uf_title(\\\"Frame order parameters\\\")\\n self._uf_param_table(label=\\\"table: frame order parameters\\\", caption=\\\"Frame order parameters.\\\", scope='global')\\n self._uf_param_table(label=\\\"table: frame order parameter value setting with defaults\\\", caption=\\\"Frame order parameter value setting.\\\", scope='global', default=True)\",\n \"def init_params() -> Tuple[TeamDict, int, int, int, str, str, List[str]]:\\n with io.open('dados.txt', 'r', encoding='utf-8') as params:\\n params_strategies = {}\\n PARAMS_LEAGUES, STAKE, PATH, RISK_UPPER, RISK_LOWER, j = [], 0, '', 0, 0, 0\\n global_vars = [STAKE, RISK_UPPER, RISK_LOWER, PATH, PARAMS_LEAGUES]\\n for i, line in enumerate(params.readlines()):\\n line = line.strip(\\\" \\\\n\\\")\\n if i <= 24:\\n if '*' in line:\\n if i == 0:\\n pass\\n else:\\n params_strategies[strategy[:-1]] = params_strategy #dict of dicts\\n params_strategy = {} #dict \\n strategy = line #key of params_strategies\\n params_strategy['name'] = strategy[:-1]\\n \\n else:\\n params_strategy[line.split(':')[0]] = float(line.split(':')[1])\\n if i == 24:\\n params_strategies[strategy[:-1]] = params_strategy\\n\\n else:\\n if '$' in line:\\n j += 1\\n continue\\n if j < 4:\\n global_vars[j-1] = float(line)/100 #stake, risk_upper, risk_lower\\n elif j == 4:\\n global_vars[j-1] = str(line) #path\\n else:\\n global_vars[4].append(line) #param_leagues\\n \\n params_strategies['e11'] = params_strategies['e1']\\n return (params_strategies, global_vars[0], global_vars[1], global_vars[2], global_vars[3], global_vars[4])\",\n \"def __init__(self,manager,name):\\n Online.DatapointLoader.DatapointLoader.__init__(self,manager,name)\\n self.dpName = self.name\\n self.inuse = self.dp('InUse')\\n self.slice = self.dp('FSMSlice')\\n self.info = self.dp('RunInfo')\\n self.addDp(self.reader)\",\n \"def read_from_pln(self, path):\\n\\n # Read the .pln file contents to a dictionary.\\n pln_dict = read_pln_file(path)\\n\\n # Look for each attribute listed in self.attributes in the results\\n # dictionary.\\n for attr in self.attributes:\\n\\n # Get the corresponding ExoParameter object.\\n current = getattr(self, attr)\\n\\n # Look for this attribute in the results dictionary and set\\n # ExoParameter.value.\\n key_str = attr\\n try:\\n current.value = pln_dict[key_str]\\n del pln_dict[key_str]\\n except KeyError:\\n current.value = current.default\\n\\n # Look for reference and URL information in the results dictionary,\\n # and use this to set ExoParameter.reference and ExoParameter.url.\\n # Skip 'transit' since 'transitref' and 'transiturl', are separate\\n # fields in the references section.\\n if not attr == \\\"transit\\\":\\n\\n key_str = \\\"\\\".join([attr, \\\"ref\\\"])\\n try:\\n current.reference = pln_dict[key_str]\\n del pln_dict[key_str]\\n except KeyError:\\n current.reference = None\\n\\n key_str = \\\"\\\".join([attr, \\\"url\\\"])\\n try:\\n current.url = pln_dict[key_str]\\n del pln_dict[key_str]\\n except KeyError:\\n current.url = None\\n\\n # If this attribute can take uncertainty values, look for these in\\n # the results dictionary, then set ExoParameter.uncertainty and\\n # ExoParameter.uncertainty_upper.\\n if current.uncertain_flag:\\n\\n key_str = \\\"\\\".join([\\\"u\\\", attr])\\n try:\\n current.uncertainty = pln_dict[key_str]\\n del pln_dict[key_str]\\n except KeyError:\\n current.uncertainty = None\\n\\n key_str = \\\"\\\".join([\\\"u\\\", attr, \\\"d\\\"])\\n try:\\n current.uncertainty_upper = pln_dict[key_str]\\n del pln_dict[key_str]\\n except KeyError:\\n current.uncertainty_upper = None\\n\\n # If there are still keyword / value pairs in pln_dict, these fields\\n # are not in the self.attributes list, which is built from\\n # self.template_file.\\n \\\"\\\"\\\"\\n if len(pln_dict.keys()) > 0:\\n print(\\\"{0} contains unknown .pln fields: {1}\\\".format(\\n path, pln_dict.keys()))\\n print(\\\"Add fields to {0} to include.\\\".format(self.template_file))\\n \\\"\\\"\\\"\\n\\n # Trigger uncertainty calculations.\\n self._populate_uncertainties()\",\n \"def __init__(**params):\",\n \"def properties(self):\",\n \"def properties(self):\",\n \"def properties(self):\",\n \"def para_loader(self, stdpath=True):\\n if stdpath is True:\\n path = self.lineEdit_params.text()\\n else:\\n path = \\\"./data/parameters/parameters_blur.pcl\\\"\\n self.lineEdit_params.setText(path)\\n\\n file = open(path, 'rb')\\n loaded_p_list = pickle.load(file)\\n file.close()\\n counter = 0\\n\\n radio_is_image = self.radioButton_circle.isChecked()\\n\\n if radio_is_image:\\n self.radioButton_image.setChecked(True)\\n\\n for clazz in SliderClass.all_sliders:\\n\\n # ## if you added a new sliderclass and want to load your old parameters, you can use this little hack\\n # classname = 'linefinder'\\n # #print(loaded_p_list[counter])\\n # #print(f\\\"the latest keyword = {clazz.keyword}\\\")\\n # if clazz.keyword == [classname]:\\n # warnings.warn(\\\"parameters are messed up! save new ones\\\")\\n # break\\n\\n try:\\n clazz.settr(loaded_p_list[counter])\\n counter += 1\\n if clazz.radio_image is not None:\\n clazz._params_circle = loaded_p_list[counter]\\n counter += 1\\n except IndexError:\\n # again a small hack for when you add an extra element to the class and this is not yet implemented\\n # in your parameter saves.\\n warnings.warn(\\\"parameters are messed up! save new ones\\\")\\n counter += 1\\n print(f\\\"should be morph: {loaded_p_list[counter]}\\\")\\n # in the save, manually set the morph_state as the final thing to load in\\n self.morph_state = loaded_p_list[counter]\\n self.checkBox_morph.setChecked(self.morph_state[0][0])\\n self.textEdit_morph.setText(self.morph_state[0][1])\\n\\n self.coords = loaded_p_list[counter + 1]\\n self.checkBox_segment.setChecked(loaded_p_list[counter + 2])\\n self.lineEdit_coords.setText(str(self.coords))\\n radio_is_circle = loaded_p_list[counter + 3]\\n\\n if radio_is_circle:\\n self.radioButton_circle.setChecked(True)\\n self.radioButton_circle.click()\",\n \"def _init_parameters(self,diameterInd):\\n\\n\\t\\t# topological parameters\\n\\t\\tself.nNodes = 21\\n\\t\\tself._axonNodes=self.nNodes\\n\\t\\tself._paraNodes1=40\\n\\t\\tself._paraNodes2=40\\n\\t\\tself._axonInter=120\\n\\t\\tself._axonTotal=221\\n\\t\\t# morphological parameters\\n\\t\\tpossibleDiameters = [5.7, 7.3, 8.7, 10.0, 11.5, 12.8, 14.0, 15.0, 16.0]\\n\\t\\tself._fiberD=possibleDiameters[diameterInd]\\n\\t\\tself._paraLength1=3 \\n\\t\\tself._nodeLength=1.0\\n\\t\\tself._spaceP1=0.002 \\n\\t\\tself._spaceP2=0.004\\n\\t\\tself._spaceI=0.004\\n\\t\\t# electrical parameters\\n\\t\\tself._rhoa=0.7e6 #Ohm-um\\n\\t\\tself._mycm=0.1 #uF/cm2/lamella membrane\\n\\t\\tself._mygm=0.001 #S/cm2/lamella membrane\\n\\n\\t\\tif self._fiberD==5.7:\\n\\t\\t\\tself._g=0.605 \\n\\t\\t\\tself._axonD=3.4\\n\\t\\t\\tself._nodeD=1.9\\n\\t\\t\\tself._paraD1=1.9\\n\\t\\t\\tself._paraD2=3.4\\n\\t\\t\\tself._deltax=500\\n\\t\\t\\tself._paraLength2=35\\n\\t\\t\\tself._nl=80\\n\\t\\tif self._fiberD==8.7:\\n\\t\\t\\tself._g=0.661\\n\\t\\t\\tself._axonD=5.8\\n\\t\\t\\tself._nodeD=2.8\\n\\t\\t\\tself._paraD1=2.8\\n\\t\\t\\tself._paraD2=5.8\\n\\t\\t\\tself._deltax=1000\\n\\t\\t\\tself._paraLength2=40\\n\\t\\t\\tself._nl=110\\n\\t\\tif self._fiberD==10.0:\\n\\t\\t\\tself._g=0.690\\n\\t\\t\\tself._axonD=6.9\\n\\t\\t\\tself._nodeD=3.3\\n\\t\\t\\tself._paraD1=3.3\\n\\t\\t\\tself._paraD2=6.9\\n\\t\\t\\tself._deltax=1150\\n\\t\\t\\tself._paraLength2=46\\n\\t\\t\\tself._nl=120\\n\\t\\tif self._fiberD==11.5:\\n\\t\\t\\tself._g=0.700\\n\\t\\t\\tself._axonD=8.1\\n\\t\\t\\tself._nodeD=3.7\\n\\t\\t\\tself._paraD1=3.7\\n\\t\\t\\tself._paraD2=8.1\\n\\t\\t\\tself._deltax=1250\\n\\t\\t\\tself._paraLength2=50\\n\\t\\t\\tself._nl=130\\n\\t\\tif self._fiberD==12.8:\\n\\t\\t\\tself._g=0.719\\n\\t\\t\\tself._axonD=9.2\\n\\t\\t\\tself._nodeD=4.2\\n\\t\\t\\tself._paraD1=4.2\\n\\t\\t\\tself._paraD2=9.2\\n\\t\\t\\tself._deltax=1350\\n\\t\\t\\tself._paraLength2=54\\n\\t\\t\\tself._nl=135\\n\\t\\tif self._fiberD==14.0:\\n\\t\\t\\tself._g=0.739\\n\\t\\t\\tself._axonD=10.4\\n\\t\\t\\tself._nodeD=4.7\\n\\t\\t\\tself._paraD1=4.7\\n\\t\\t\\tself._paraD2=10.4\\n\\t\\t\\tself._deltax=1400\\n\\t\\t\\tself._paraLength2=56\\n\\t\\t\\tself._nl=140\\n\\t\\tif self._fiberD==15.0:\\n\\t\\t\\tself._g=0.767\\n\\t\\t\\tself._axonD=11.5\\n\\t\\t\\tself._nodeD=5.0\\n\\t\\t\\tself._paraD1=5.0\\n\\t\\t\\tself._paraD2=11.5\\n\\t\\t\\tself._deltax=1450\\n\\t\\t\\tself._paraLength2=58\\n\\t\\t\\tself._nl=145\\n\\t\\tif self._fiberD==16.0:\\n\\t\\t\\tself._g=0.791\\n\\t\\t\\tself._axonD=12.7\\n\\t\\t\\tself._nodeD=5.5\\n\\t\\t\\tself._paraD1=5.5\\n\\t\\t\\tself._paraD2=12.7\\n\\t\\t\\tself._deltax=1500\\n\\t\\t\\tself._paraLength2=60\\n\\t\\t\\tself._nl=150\\n\\n\\t\\tself._Rpn0=(self._rhoa*.01)/(np.pi*((((self._nodeD/2)+self._spaceP1)**2)-((self._nodeD/2)**2)))\\n\\t\\tself._Rpn1=(self._rhoa*.01)/(np.pi*((((self._paraD1/2)+self._spaceP1)**2)-((self._paraD1/2)**2)))\\n\\t\\tself._Rpn2=(self._rhoa*.01)/(np.pi*((((self._paraD2/2)+self._spaceP2)**2)-((self._paraD2/2)**2)))\\n\\t\\tself._Rpx=(self._rhoa*.01)/(np.pi*((((self._axonD/2)+self._spaceI)**2)-((self._axonD/2)**2)))\\n\\t\\tself._interLength=(self._deltax-self._nodeLength-(2*self._paraLength1)-(2*self._paraLength2))/6\",\n \"def load_cls_params(self):\\n with open('models/Final/linear_svc.p', 'rb') as model_file:\\n model = pickle.load(model_file)\\n self.svc = model['svc']\\n self.X_scaler = model['X_scaler']\\n self.parameters = model['parameters']\\n\\n print(self.parameters)\",\n \"def __init__(self):\\r\\n\\t\\tself.label = \\\"Linked Data Batch No Functional Property Merge\\\"\\r\\n\\t\\tself.description = \\\"\\\"\\\"The related seperated tables from Linked Data Location Entities Property Enrichment Tool have multivalue for each wikidata location because the coresponding property is not functional property. \\r\\n\\t\\tThis Tool helps user to merge these multivalue to a single record and add it to original feature class sttribute table by using merge rules which are specified by users.\\\"\\\"\\\"\\r\\n\\t\\tself.canRunInBackground = False\",\n \"def test_meta(self):\\n self.assertEqual([\\\"test\\\", [[\\\"c1\\\", \\\"INT\\\"], [\\\"c2\\\", \\\"VARCHAR(200)\\\"]], \\\"returns\\\", \\\"union\\\"],\\n grammar._PROCEDURE_COMMENT_FORMAT.parseString(\\\"test(c1 INT, c2 VARCHAR(200)); returns union\\\").asList())\\n self.assertEqual([\\\"returns\\\", \\\"union\\\"],\\n grammar._PROCEDURE_COMMENT_FORMAT.parseString(\\\"returns union\\\").asList())\",\n \"def __init__(self, rouge_types):\\n\\n self.rouge_types = rouge_types\",\n \"def __init__(self, name, config):\\n self.name = name\\n self.config = config\\n LineBuilder.__init__(self, name, config)\\n \\n etappg_name = '{0}EtaPPG'.format(name)\\n eta3hr_name = '{0}Eta3HR'.format(name)\\n eta3hm_name = '{0}Eta3HM'.format(name)\\n \\n d2pietappg_name = '{0}D2PiEtaPPG'.format(name)\\n d2pieta3hr_name = '{0}D2PiEta3HR'.format(name)\\n d2pieta3hm_name = '{0}D2PiEta3HM'.format(name)\\n \\n d2ketappg_name = '{0}D2KEtaPPG'.format(name)\\n d2keta3hr_name = '{0}D2KEta3HR'.format(name)\\n d2keta3hm_name = '{0}D2KEta3HM'.format(name)\\n\\n self.selEtaPPG = makeResonance(\\n etappg_name,\\n config,\\n inputSel=[StdAllNoPIDsPions,StdLooseAllPhotons],\\n decDescriptors=self.EtaPPG\\n )\\n\\n self.selEta3HR = makeResonance(\\n eta3hr_name,\\n config,\\n inputSel=[StdAllNoPIDsPions,StdLooseResolvedPi0],\\n decDescriptors=self.Eta3H\\n )\\n\\n self.selEta3HM = makeResonance(\\n eta3hm_name,\\n config,\\n inputSel=[StdAllNoPIDsPions,StdLooseMergedPi0],\\n decDescriptors=self.Eta3H\\n )\\n\\n self.selD2PiEtaPPG = makeD(\\n d2pietappg_name,\\n config,\\n inputSel=[self.selEtaPPG, StdAllNoPIDsPions],\\n decDescriptors=self.D2PiEta,\\n useBachelorPID=False,\\n )\\n\\n self.selD2KEtaPPG = makeD(\\n d2ketappg_name,\\n config,\\n inputSel=[self.selEtaPPG, StdAllNoPIDsKaons],\\n decDescriptors=self.D2KEta,\\n useBachelorPID=False,\\n )\\n \\n self.selD2PiEta3HR = makeD(\\n d2pieta3hr_name,\\n config,\\n inputSel=[self.selEta3HR, StdAllNoPIDsPions],\\n decDescriptors=self.D2PiEta,\\n useBachelorPID=False,\\n )\\n\\n self.selD2KEta3HR = makeD(\\n d2keta3hr_name,\\n config,\\n inputSel=[self.selEta3HR, StdAllNoPIDsKaons],\\n decDescriptors=self.D2KEta,\\n useBachelorPID=False,\\n )\\n \\n self.selD2PiEta3HM = makeD(\\n d2pieta3hm_name,\\n config,\\n inputSel=[self.selEta3HM, StdAllNoPIDsPions],\\n decDescriptors=self.D2PiEta,\\n useBachelorPID=False,\\n )\\n \\n\\n self.selD2KEta3HM = makeD(\\n d2keta3hm_name,\\n config,\\n inputSel=[self.selEta3HM, StdAllNoPIDsKaons],\\n decDescriptors=self.D2KEta,\\n useBachelorPID=False,\\n )\\n \\n\\n self.line_D2PiEtaPPG = make_line(\\n self,\\n name='{0}Line'.format(d2pietappg_name),\\n prescale=config['PrescaleD2PiEtaPPG'],\\n postscale=config['PostscaleD2PiEtaPPG'],\\n selection=self.selD2PiEtaPPG,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n\\n self.line_D2PiEta3HM = make_line(\\n self,\\n name='{0}Line'.format(d2pieta3hm_name),\\n prescale=config['PrescaleD2PiEta3HM'],\\n postscale=config['PostscaleD2PiEta3HM'],\\n selection=self.selD2PiEta3HM,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n\\n self.line_D2PiEta3HR = make_line(\\n self,\\n name='{0}Line'.format(d2pieta3hr_name),\\n prescale=config['PrescaleD2PiEta3HR'],\\n postscale=config['PostscaleD2PiEta3HR'],\\n selection=self.selD2PiEta3HR,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n\\n self.line_D2KEtaPPG = make_line(\\n self,\\n name='{0}Line'.format(d2ketappg_name),\\n prescale=config['PrescaleD2KEtaPPG'],\\n postscale=config['PostscaleD2KEtaPPG'],\\n selection=self.selD2KEtaPPG,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n \\n self.line_D2KEta3HM = make_line(\\n self,\\n name='{0}Line'.format(d2keta3hm_name),\\n prescale=config['PrescaleD2KEta3HM'],\\n postscale=config['PostscaleD2KEta3HM'],\\n selection=self.selD2KEta3HM,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\\n \\n self.line_D2KEta3HR = make_line(\\n self,\\n name='{0}Line'.format(d2keta3hr_name),\\n prescale=config['PrescaleD2KEta3HR'],\\n postscale=config['PostscaleD2KEta3HR'],\\n selection=self.selD2KEta3HR,\\n HLT1=config['Hlt1Filter'],\\n HLT2=config['Hlt2Filter']\\n )\",\n \"def updateParameters(self, parameters):\\r\\n\\t\\tin_wikiplace_IRI = parameters[0]\\r\\n\\t\\tin_relation_degree = parameters[1]\\r\\n\\t\\tin_first_property_dir = parameters[2]\\r\\n\\t\\tin_first_property = parameters[3]\\r\\n\\t\\tin_second_property_dir = parameters[4]\\r\\n\\t\\tin_second_property = parameters[5]\\r\\n\\t\\tin_third_property_dir = parameters[6]\\r\\n\\t\\tin_third_property = parameters[7]\\r\\n\\t\\tin_fourth_property_dir = parameters[8]\\r\\n\\t\\tin_fourth_property = parameters[9]\\r\\n\\t\\tout_location = parameters[10]\\r\\n\\t\\tout_table_name = parameters[11]\\r\\n\\t\\tout_points_name = parameters[12]\\r\\n\\r\\n\\t\\t\\r\\n\\r\\n\\t\\tif in_relation_degree.altered:\\r\\n\\t\\t\\trelationDegree = int(in_relation_degree.valueAsText)\\r\\n\\t\\t\\tif relationDegree == 1:\\r\\n\\t\\t\\t\\tin_first_property.enabled = True\\r\\n\\t\\t\\t\\tin_first_property_dir.enabled = True\\r\\n\\t\\t\\t\\tin_second_property.enabled = False\\r\\n\\t\\t\\t\\tin_second_property_dir.enabled = False\\r\\n\\t\\t\\t\\tin_third_property.enabled = False\\r\\n\\t\\t\\t\\tin_third_property_dir.enabled = False\\r\\n\\t\\t\\t\\tin_fourth_property.enabled = False\\r\\n\\t\\t\\t\\tin_fourth_property_dir.enabled = False\\r\\n\\t\\t\\telif relationDegree == 2:\\r\\n\\t\\t\\t\\tin_first_property.enabled = True\\r\\n\\t\\t\\t\\tin_first_property_dir.enabled = True\\r\\n\\t\\t\\t\\tin_second_property.enabled = True\\r\\n\\t\\t\\t\\tin_second_property_dir.enabled = True\\r\\n\\t\\t\\t\\tin_third_property.enabled = False\\r\\n\\t\\t\\t\\tin_third_property_dir.enabled = False\\r\\n\\t\\t\\t\\tin_fourth_property.enabled = False\\r\\n\\t\\t\\t\\tin_fourth_property_dir.enabled = False\\r\\n\\t\\t\\telif relationDegree == 3:\\r\\n\\t\\t\\t\\tin_first_property.enabled = True\\r\\n\\t\\t\\t\\tin_first_property_dir.enabled = True\\r\\n\\t\\t\\t\\tin_second_property.enabled = True\\r\\n\\t\\t\\t\\tin_second_property_dir.enabled = True\\r\\n\\t\\t\\t\\tin_third_property.enabled = True\\r\\n\\t\\t\\t\\tin_third_property_dir.enabled = True\\r\\n\\t\\t\\t\\tin_fourth_property.enabled = False\\r\\n\\t\\t\\t\\tin_fourth_property_dir.enabled = False\\r\\n\\t\\t\\telif relationDegree == 4:\\r\\n\\t\\t\\t\\tin_first_property.enabled = True\\r\\n\\t\\t\\t\\tin_first_property_dir.enabled = True\\r\\n\\t\\t\\t\\tin_second_property.enabled = True\\r\\n\\t\\t\\t\\tin_second_property_dir.enabled = True\\r\\n\\t\\t\\t\\tin_third_property.enabled = True\\r\\n\\t\\t\\t\\tin_third_property_dir.enabled = True\\r\\n\\t\\t\\t\\tin_fourth_property.enabled = True\\r\\n\\t\\t\\t\\tin_fourth_property_dir.enabled = True\\r\\n\\t\\t\\r\\n\\t\\t\\tif in_wikiplace_IRI.value:\\r\\n\\t\\t\\t\\tinputFeatureClassName = in_wikiplace_IRI.valueAsText\\r\\n\\t\\t\\t\\tlastIndexOFGDB = inputFeatureClassName.rfind(\\\"\\\\\\\\\\\")\\r\\n\\t\\t\\t\\tfeatureClassName = inputFeatureClassName[(lastIndexOFGDB+1):]\\r\\n\\t\\t\\t\\tcurrentWorkspace = inputFeatureClassName[:lastIndexOFGDB]\\r\\n\\r\\n\\t\\t\\t\\tarcpy.env.workspace = currentWorkspace\\r\\n\\t\\t\\t\\tout_location.value = currentWorkspace\\r\\n\\r\\n\\t\\t\\t\\tout_table_name.value = featureClassName + \\\"PathQueryTripleStore\\\"\\r\\n\\r\\n\\t\\t\\t\\tout_points_name.value = featureClassName + \\\"PathQueryLocation\\\"\\r\\n\\r\\n\\r\\n\\t\\t\\t\\toutLocation = out_location.valueAsText\\r\\n\\t\\t\\t\\toutTableName = out_table_name.valueAsText\\r\\n\\t\\t\\t\\toutputTableName = os.path.join(outLocation,outTableName)\\r\\n\\t\\t\\t\\tif arcpy.Exists(outputTableName):\\r\\n\\t\\t\\t\\t\\tarcpy.AddError(\\\"The output table already exists in current workspace!\\\")\\r\\n\\t\\t\\t\\t\\traise arcpy.ExecuteError\\r\\n\\r\\n\\t\\t\\t\\toutFeatureClassName = out_points_name.valueAsText\\r\\n\\t\\t\\t\\toutputFeatureClassName = os.path.join(outLocation,outFeatureClassName)\\r\\n\\t\\t\\t\\tif arcpy.Exists(outputFeatureClassName):\\r\\n\\t\\t\\t\\t\\tarcpy.AddError(\\\"The output Feature Class already exists in current workspace!\\\")\\r\\n\\t\\t\\t\\t\\traise arcpy.ExecuteError\\r\\n\\r\\n\\r\\n\\t\\t\\t\\t# get all the IRI from input point feature class of wikidata places\\r\\n\\t\\t\\t\\tinplaceIRIList = []\\r\\n\\t\\t\\t\\tcursor = arcpy.SearchCursor(inputFeatureClassName)\\r\\n\\t\\t\\t\\tfor row in cursor:\\r\\n\\t\\t\\t\\t\\tinplaceIRIList.append(row.getValue(\\\"URL\\\"))\\r\\n\\r\\n\\r\\n\\r\\n\\t\\t\\t\\t# get the first property URL list and label list\\r\\n\\t\\t\\t\\tif in_first_property_dir.value:\\r\\n\\t\\t\\t\\t\\tfristDirection = in_first_property_dir.valueAsText\\r\\n\\t\\t\\t\\t\\t# get the first property URL list\\r\\n\\t\\t\\t\\t\\tfirstPropertyURLListJsonBindingObject = SPARQLQuery.relFinderCommonPropertyQuery(inplaceIRIList, relationDegree, [fristDirection], [\\\"\\\", \\\"\\\", \\\"\\\"])\\r\\n\\t\\t\\t\\t\\tfirstPropertyURLList = []\\r\\n\\t\\t\\t\\t\\tfor jsonItem in firstPropertyURLListJsonBindingObject:\\r\\n\\t\\t\\t\\t\\t\\tfirstPropertyURLList.append(jsonItem[\\\"p1\\\"][\\\"value\\\"])\\r\\n\\r\\n\\t\\t\\t\\t\\tfirstPropertyLabelJSON = SPARQLQuery.locationCommonPropertyLabelQuery(firstPropertyURLList)\\r\\n\\t\\t\\t\\t\\t# firstPropertyLabelJSON = firstPropertyLabelJSONObj[\\\"results\\\"][\\\"bindings\\\"]\\r\\n\\r\\n\\t\\t\\t\\t\\t# get the first property label list\\r\\n\\t\\t\\t\\t\\tfirstPropertyURLList = []\\r\\n\\t\\t\\t\\t\\tfirstPropertyLabelList = []\\r\\n\\t\\t\\t\\t\\tfor jsonItem in firstPropertyLabelJSON:\\r\\n\\t\\t\\t\\t\\t\\tpropertyURL = jsonItem[\\\"p\\\"][\\\"value\\\"]\\r\\n\\t\\t\\t\\t\\t\\tfirstPropertyURLList.append(propertyURL)\\r\\n\\t\\t\\t\\t\\t\\tpropertyName = jsonItem[\\\"propertyLabel\\\"][\\\"value\\\"]\\r\\n\\t\\t\\t\\t\\t\\tfirstPropertyLabelList.append(propertyName)\\r\\n\\r\\n\\t\\t\\t\\t\\tRelFinder.firstPropertyLabelURLDict = dict(zip(firstPropertyLabelList, firstPropertyURLList))\\r\\n\\r\\n\\t\\t\\t\\t\\tin_first_property.filter.list = firstPropertyLabelList\\r\\n\\r\\n\\t\\t\\t\\t\\t# get the second property URL list and label list\\r\\n\\t\\t\\t\\t\\tif in_second_property_dir.value:\\r\\n\\t\\t\\t\\t\\t\\tfristDirection = in_first_property_dir.valueAsText\\r\\n\\t\\t\\t\\t\\t\\tfirstProperty = in_first_property.valueAsText\\r\\n\\r\\n\\t\\t\\t\\t\\t\\tif firstProperty == None:\\r\\n\\t\\t\\t\\t\\t\\t\\tfirstProperty = \\\"\\\"\\r\\n\\t\\t\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\t\\t\\tfirstProperty = RelFinder.firstPropertyLabelURLDict[firstProperty]\\r\\n\\r\\n\\t\\t\\t\\t\\t\\tsecondDirection = in_second_property_dir.valueAsText\\r\\n\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\t# get the second property URL list\\r\\n\\t\\t\\t\\t\\t\\tsecondPropertyURLListJsonBindingObject = SPARQLQuery.relFinderCommonPropertyQuery(inplaceIRIList, relationDegree, [fristDirection, secondDirection], [firstProperty, \\\"\\\", \\\"\\\"])\\r\\n\\t\\t\\t\\t\\t\\tsecondPropertyURLList = []\\r\\n\\t\\t\\t\\t\\t\\tfor jsonItem in secondPropertyURLListJsonBindingObject:\\r\\n\\t\\t\\t\\t\\t\\t\\tsecondPropertyURLList.append(jsonItem[\\\"p2\\\"][\\\"value\\\"])\\r\\n\\r\\n\\t\\t\\t\\t\\t\\tsecondPropertyLabelJSON = SPARQLQuery.locationCommonPropertyLabelQuery(secondPropertyURLList)\\r\\n\\t\\t\\t\\t\\t\\t# secondPropertyLabelJSON = secondPropertyLabelJSONObj[\\\"results\\\"][\\\"bindings\\\"]\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t# get the second property label list\\r\\n\\t\\t\\t\\t\\t\\tsecondPropertyURLList = []\\r\\n\\t\\t\\t\\t\\t\\tsecondPropertyLabelList = []\\r\\n\\t\\t\\t\\t\\t\\tfor jsonItem in secondPropertyLabelJSON:\\r\\n\\t\\t\\t\\t\\t\\t\\tpropertyURL = jsonItem[\\\"p\\\"][\\\"value\\\"]\\r\\n\\t\\t\\t\\t\\t\\t\\tsecondPropertyURLList.append(propertyURL)\\r\\n\\t\\t\\t\\t\\t\\t\\tpropertyName = jsonItem[\\\"propertyLabel\\\"][\\\"value\\\"]\\r\\n\\t\\t\\t\\t\\t\\t\\tsecondPropertyLabelList.append(propertyName)\\r\\n\\r\\n\\t\\t\\t\\t\\t\\tRelFinder.secondPropertyLabelURLDict = dict(zip(secondPropertyLabelList, secondPropertyURLList))\\r\\n\\r\\n\\t\\t\\t\\t\\t\\tin_second_property.filter.list = secondPropertyLabelList\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t# get the third property URL list and label list\\r\\n\\t\\t\\t\\t\\t\\tif in_third_property_dir.value:\\r\\n\\t\\t\\t\\t\\t\\t\\tfristDirection = in_first_property_dir.valueAsText\\r\\n\\t\\t\\t\\t\\t\\t\\tfirstProperty = in_first_property.valueAsText\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\tsecondDirection = in_second_property_dir.valueAsText\\r\\n\\t\\t\\t\\t\\t\\t\\tsecondProperty = in_second_property.valueAsText\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\tif firstProperty == None:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfirstProperty = \\\"\\\"\\r\\n\\t\\t\\t\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfirstProperty = RelFinder.firstPropertyLabelURLDict[firstProperty]\\r\\n\\t\\t\\t\\t\\t\\t\\tif secondProperty == None:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tsecondProperty = \\\"\\\"\\r\\n\\t\\t\\t\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tsecondProperty = RelFinder.secondPropertyLabelURLDict[secondProperty]\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\tthirdDirection = in_third_property_dir.valueAsText\\r\\n\\t\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\t\\t# get the third property URL list\\r\\n\\t\\t\\t\\t\\t\\t\\tthirdPropertyURLListJsonBindingObject = SPARQLQuery.relFinderCommonPropertyQuery(inplaceIRIList, relationDegree, [fristDirection, secondDirection, thirdDirection], [firstProperty, secondProperty, \\\"\\\"])\\r\\n\\t\\t\\t\\t\\t\\t\\tthirdPropertyURLList = []\\r\\n\\t\\t\\t\\t\\t\\t\\tfor jsonItem in thirdPropertyURLListJsonBindingObject:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tthirdPropertyURLList.append(jsonItem[\\\"p3\\\"][\\\"value\\\"])\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\tthirdPropertyLabelJSON = SPARQLQuery.locationCommonPropertyLabelQuery(thirdPropertyURLList)\\r\\n\\t\\t\\t\\t\\t\\t\\t# thirdPropertyLabelJSON = thirdPropertyLabelJSONObj[\\\"results\\\"][\\\"bindings\\\"]\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\t# get the third property label list\\r\\n\\t\\t\\t\\t\\t\\t\\tthirdPropertyURLList = []\\r\\n\\t\\t\\t\\t\\t\\t\\tthirdPropertyLabelList = []\\r\\n\\t\\t\\t\\t\\t\\t\\tfor jsonItem in thirdPropertyLabelJSON:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tpropertyURL = jsonItem[\\\"p\\\"][\\\"value\\\"]\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tthirdPropertyURLList.append(propertyURL)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tpropertyName = jsonItem[\\\"propertyLabel\\\"][\\\"value\\\"]\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tthirdPropertyLabelList.append(propertyName)\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\tRelFinder.thirdPropertyLabelURLDict = dict(zip(thirdPropertyLabelList, thirdPropertyURLList))\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\tin_third_property.filter.list = thirdPropertyLabelList\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\t# get the fourth property URL list and label list\\r\\n\\t\\t\\t\\t\\t\\t\\tif in_fourth_property_dir.value:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfristDirection = in_first_property_dir.valueAsText\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfirstProperty = in_first_property.valueAsText\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tsecondDirection = in_second_property_dir.valueAsText\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tsecondProperty = in_second_property.valueAsText\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tthirdDirection = in_third_property_dir.valueAsText\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tthirdProperty = in_third_property.valueAsText\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif firstProperty == None:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tfirstProperty = \\\"\\\"\\r\\n\\t\\t\\t\\t\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tfirstProperty = RelFinder.firstPropertyLabelURLDict[firstProperty]\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif secondProperty == None:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tsecondProperty = \\\"\\\"\\r\\n\\t\\t\\t\\t\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tsecondProperty = RelFinder.secondPropertyLabelURLDict[secondProperty]\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tif thirdProperty == None:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tthirdProperty = \\\"\\\"\\r\\n\\t\\t\\t\\t\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tthirdProperty = RelFinder.thirdPropertyLabelURLDict[thirdProperty]\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfourthDirection = in_fourth_property_dir.valueAsText\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t# get the fourth property URL list\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfourthPropertyURLListJsonBindingObject = SPARQLQuery.relFinderCommonPropertyQuery(inplaceIRIList, relationDegree, [fristDirection, secondDirection, thirdDirection, fourthDirection], [firstProperty, secondProperty, thirdProperty])\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfourthPropertyURLList = []\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfor jsonItem in fourthPropertyURLListJsonBindingObject:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tfourthPropertyURLList.append(jsonItem[\\\"p4\\\"][\\\"value\\\"])\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfourthPropertyLabelJSON = SPARQLQuery.locationCommonPropertyLabelQuery(fourthPropertyURLList)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t# fourthPropertyLabelJSON = fourthPropertyLabelJSONObj[\\\"results\\\"][\\\"bindings\\\"]\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t# get the fourth property label list\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfourthPropertyURLList = []\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfourthPropertyLabelList = []\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tfor jsonItem in fourthPropertyLabelJSON:\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tpropertyURL = jsonItem[\\\"p\\\"][\\\"value\\\"]\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tfourthPropertyURLList.append(propertyURL)\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tpropertyName = jsonItem[\\\"propertyLabel\\\"][\\\"value\\\"]\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tfourthPropertyLabelList.append(propertyName)\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tRelFinder.fourthPropertyLabelURLDict = dict(zip(fourthPropertyLabelList, fourthPropertyURLList))\\r\\n\\r\\n\\t\\t\\t\\t\\t\\t\\t\\tin_fourth_property.filter.list = fourthPropertyLabelList\\r\\n\\r\\n\\r\\n\\t\\treturn\",\n \"def parameterNode(self):\\n #framework\\n profbox()\\n return self.parameterNode\",\n \"def __init__(self):\\n\\n self.prim_parser = parser.Parser()\",\n \"def __init__(self,particle):\\n self.par = particle\",\n \"def default_pypeit_par(cls):\\n par = super().default_pypeit_par()\\n\\n # Ignore PCA\\n par['calibrations']['slitedges']['sync_predict'] = 'nearest'\\n par['calibrations']['slitedges']['bound_detector'] = True\\n\\n # Set pixel flat combination method\\n par['calibrations']['pixelflatframe']['process']['combine'] = 'median'\\n # Wavelength calibration methods\\n par['calibrations']['wavelengths']['method'] = 'full_template'\\n par['calibrations']['wavelengths']['lamps'] = ['XeI,HgI,NeI,ArI']\\n\\n # Set the default exposure time ranges for the frame typing\\n par['scienceframe']['exprng'] = [90, None]\\n par['calibrations']['biasframe']['exprng'] = [None, 1]\\n par['calibrations']['darkframe']['exprng'] = [999999, None] # No dark frames\\n par['calibrations']['pinholeframe']['exprng'] = [999999, None] # No pinhole frames\\n par['calibrations']['arcframe']['exprng'] = [None, None] # Long arc exposures\\n par['calibrations']['arcframe']['process']['clip'] = False\\n par['calibrations']['standardframe']['exprng'] = [None, 180]\\n # Multiple arcs with different lamps, so can't median combine nor clip, also need to remove continuum\\n par['calibrations']['arcframe']['process']['combine'] = 'mean'\\n par['calibrations']['arcframe']['process']['subtract_continuum'] = True\\n par['calibrations']['tiltframe']['process']['clip'] = False\\n par['calibrations']['tiltframe']['process']['combine'] = 'mean'\\n par['calibrations']['tiltframe']['process']['subtract_continuum'] = True\\n\\n # Increase the wave tilts order, given the longish slit\\n par['calibrations']['tilts']['spat_order'] = 5\\n par['calibrations']['tilts']['spec_order'] = 5\\n\\n #Only extract one object per standard frame\\n par['reduce']['findobj']['maxnumber_std']=1\\n\\n # Turn off the 2D fit - this seems to be giving bad results for OSIRIS\\n par['reduce']['skysub']['no_poly'] = True\\n return par\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.64564425","0.6269693","0.604923","0.6017091","0.59432966","0.5927661","0.5904071","0.58930105","0.5876353","0.58385175","0.58262694","0.5811515","0.57941467","0.57618046","0.5759846","0.5745511","0.5650662","0.5646204","0.5636251","0.5623941","0.56101626","0.55938125","0.55811906","0.55428815","0.54973066","0.5485281","0.547604","0.54596573","0.5370219","0.5355713","0.534965","0.5345883","0.5307936","0.53038365","0.53038204","0.5299688","0.52929556","0.52917004","0.52698433","0.5268415","0.5266514","0.5262471","0.52607226","0.5254051","0.5251715","0.52435577","0.5242001","0.52418584","0.5240626","0.52338487","0.5229596","0.52060384","0.5201917","0.5197324","0.5191839","0.51909035","0.5186648","0.51840633","0.51825655","0.51785785","0.5177557","0.5170037","0.51699525","0.51693517","0.51639104","0.5162698","0.51623785","0.5156135","0.5154131","0.5152394","0.515105","0.5145825","0.51454365","0.5141609","0.5136859","0.51334864","0.51323533","0.5122562","0.5105517","0.5104073","0.5096837","0.50913376","0.508319","0.50762576","0.50719666","0.50695133","0.5068691","0.5068691","0.5068691","0.50594634","0.50527185","0.50521576","0.50518376","0.5047911","0.5047645","0.5045984","0.5045596","0.50443673","0.504209","0.503971","0.50367767"],"string":"[\n \"0.64564425\",\n \"0.6269693\",\n \"0.604923\",\n \"0.6017091\",\n \"0.59432966\",\n \"0.5927661\",\n \"0.5904071\",\n \"0.58930105\",\n \"0.5876353\",\n \"0.58385175\",\n \"0.58262694\",\n \"0.5811515\",\n \"0.57941467\",\n \"0.57618046\",\n \"0.5759846\",\n \"0.5745511\",\n \"0.5650662\",\n \"0.5646204\",\n \"0.5636251\",\n \"0.5623941\",\n \"0.56101626\",\n \"0.55938125\",\n \"0.55811906\",\n \"0.55428815\",\n \"0.54973066\",\n \"0.5485281\",\n \"0.547604\",\n \"0.54596573\",\n \"0.5370219\",\n \"0.5355713\",\n \"0.534965\",\n \"0.5345883\",\n \"0.5307936\",\n \"0.53038365\",\n \"0.53038204\",\n \"0.5299688\",\n \"0.52929556\",\n \"0.52917004\",\n \"0.52698433\",\n \"0.5268415\",\n \"0.5266514\",\n \"0.5262471\",\n \"0.52607226\",\n \"0.5254051\",\n \"0.5251715\",\n \"0.52435577\",\n \"0.5242001\",\n \"0.52418584\",\n \"0.5240626\",\n \"0.52338487\",\n \"0.5229596\",\n \"0.52060384\",\n \"0.5201917\",\n \"0.5197324\",\n \"0.5191839\",\n \"0.51909035\",\n \"0.5186648\",\n \"0.51840633\",\n \"0.51825655\",\n \"0.51785785\",\n \"0.5177557\",\n \"0.5170037\",\n \"0.51699525\",\n \"0.51693517\",\n \"0.51639104\",\n \"0.5162698\",\n \"0.51623785\",\n \"0.5156135\",\n \"0.5154131\",\n \"0.5152394\",\n \"0.515105\",\n \"0.5145825\",\n \"0.51454365\",\n \"0.5141609\",\n \"0.5136859\",\n \"0.51334864\",\n \"0.51323533\",\n \"0.5122562\",\n \"0.5105517\",\n \"0.5104073\",\n \"0.5096837\",\n \"0.50913376\",\n \"0.508319\",\n \"0.50762576\",\n \"0.50719666\",\n \"0.50695133\",\n \"0.5068691\",\n \"0.5068691\",\n \"0.5068691\",\n \"0.50594634\",\n \"0.50527185\",\n \"0.50521576\",\n \"0.50518376\",\n \"0.5047911\",\n \"0.5047645\",\n \"0.5045984\",\n \"0.5045596\",\n \"0.50443673\",\n \"0.504209\",\n \"0.503971\",\n \"0.50367767\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":18691,"cells":{"query":{"kind":"string","value":"Funcao que gera o codigo rml da sessao plenaria"},"document":{"kind":"string","value":"def pauta(lst_splen, lst_pauta):\n\n tmp=''\n\n #inicio do bloco \n tmp+='\\t<story>\\n'\n\n for dicsp in lst_splen:\n\n #sessao plenaria\n if dicsp['sessao']!=None:\n tmp+='\\t\\t<para style=\"P0\">' + dicsp['sessao'].replace('&','&') +', EM ' + dicsp['datasessao'].replace('&','&')+ '</para>\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"4\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n if dicsp['ind_audiencia'] == 1:\n tmp+='\\t\\t<para style=\"P1\"></para>\\n'\n else:\n tmp+='\\t\\t<para style=\"P1\">(Pauta da Ordem do Dia)</para>\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"12\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n\n\n #inicio do bloco que contem os flowables\n \n for dic in lst_pauta:\n #espaco inicial\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"10\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n\n #condicao para a quebra de pagina\n tmp+='\\t\\t<condPageBreak height=\"5mm\"/>\\n'\n\n #pauta\n if dic['num_ordem']!=None:\n tmp+='\\t\\t<para style=\"P4\"><font color=\"#222\"><b>Item nº ' + str(dic['num_ordem']) + '</b></font></para>\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"4\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n if dic['id_materia']!=None:\n if dic['cod_materia']!='':\n tmp+='\\t\\t<para style=\"P4\"><b><font color=\"#126e90\"><u>' + dic['link_materia']+'</u></font> - '+ dic['nom_autor'] + '</b></para>\\n'\n if dic['cod_parecer']!='': \n tmp+='\\t\\t<para style=\"P4\"><b><font color=\"#126e90\"><u>' + dic['link_materia']+'</u></font> - '+ dic['nom_autor'] + ', que '+ dic['txt_materia'] + '</b></para>\\n'\n tmp+='\\t\\t<para style=\"P3\" spaceAfter=\"4\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n if dic['txt_ementa']!=None:\n tmp+='\\t\\t<para style=\"P3\">' + dic['txt_ementa'].replace('&','&') + '</para>\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"4\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n\n if dic['des_turno']!='':\n tmp+='\\t\\t<para style=\"P3\"><b>Turno</b>: '+ dic['des_turno'] +' | <b>Quorum</b>: '+ dic['des_quorum']+' | <b>Tipo de Votação</b>: '+ dic['tip_votacao'] + '' + '</para>\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"8\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n\n if dic['parecer']!= 0 and dic['parecer']!= '':\n tmp+='\\t\\t<para style=\"P3\"><b><u>PARECERES:</u></b></para>\\n\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"4\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n for item in dic['pareceres']:\n tmp+='\\t\\t<para style=\"P3\"><b><font color=\"#126e90\">' + item[\"link_materia\"] + '</font> - ' + item[\"conclusao\"] + '</b> ' + item[\"relatoria\"] + '</para>\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"4\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n\n if dic['substitutivo']!= 0 and dic['substitutivo']!= '':\n tmp+='\\t\\t<para style=\"P3\"><b><u>SUBSTITUTIVOS:</u></b></para>\\n\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"4\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n' \n for substitutivo in dic['substitutivos']:\n tmp+='\\t\\t<para style=\"P3\"><b><font color=\"#126e90\">' + substitutivo[\"id_substitutivo\"] + '</font> - ' + substitutivo[\"autoria\"] + '</b> - ' + substitutivo[\"txt_ementa\"] + '</para>\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"4\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n\n if dic['emenda']!= 0 and dic['emenda']!= '':\n tmp+='\\t\\t<para style=\"P3\"><b><u>EMENDAS:</u></b></para>\\n\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"4\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n' \n for emenda in dic['emendas']:\n tmp+='\\t\\t<para style=\"P3\"><b><font color=\"#126e90\">' + emenda[\"id_emenda\"] + '</font> - ' + emenda[\"autoria\"] + '</b> - ' + emenda[\"txt_ementa\"] + '</para>\\n'\n tmp+='\\t\\t<para style=\"P2\" spaceAfter=\"4\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n return tmp"},"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 session(self):","def get_or_create_session(db):","def save_inscription():\n user = None\n f = InscriptionForm()\n if f.validate_on_submit() and f.uniq_Username() and f.passwd_confirmed():\n from hashlib import sha256\n m = sha256()\n m.update(f.get_mdp().encode())\n user = Utilisateur(\n idU = f.get_id(),\n mdpU = m.hexdigest(),\n nomU = f.get_name(),\n prenomU = f.get_surname())\n db.session.add(user)\n i = Actions(\n contenu = \"Bienvenue à \"+f.get_id(),\n liste = 1\n )\n db.session.add(i)\n db.session.commit()\n return redirect(url_for('login'))\n return render_template(\n\t\t\"inscription.html\",\n\t\tform = f,\n title = \"Inscription\")","def login():\n # try:\n # if g.user != None:\n # user_ID = \"Logged \" + str(g.user['_id'])\n # print \"insideNone\",user_ID\n # except ValueError:\n # print \"try again\"\n # if g.user:\n # print \"insideLog\"\n # return redirect(url_for('timeline'))\n user_ID = \"\"\n if g.user != None:\n user_ID = \"Logged \" + str(g.user['_id'])\n print \"insideNone\", user_ID\n\n ############### REDIS SESSION CODE #####################\n if redis_obj.get(user_ID):\n pKey = pickle.loads(redis_obj.get(user_ID))\n print \"insideLog\", user_ID\n return redirect(url_for('timeline'), pKey)\n error = None\n if request.method == 'POST':\n user = userdetails_query()\n if user is None:\n error = 'Invalid username'\n # abort(status.HTTP_401_UNAUTHORIZED)\n elif not check_password_hash(user['pw_hash'],\n request.form['password']):\n error = 'Invalid password'\n # abort(status.HTTP_401_UNAUTHORIZED)\n else:\n flash('You were logged in')\n session['user_id'] = user['_id']\n logUser = pickle.dumps(list(user))\n # print \"logUser\", logUser\n redis_obj.setex(\"Logged \" + str(session['user_id']), logUser, 60)\n return redirect(url_for('timeline'))\n return render_template('login.html', error=error)","def load_token(token):\n\n #The Token itself was generated by User.get_auth_token. So it is up to \n #us to known the format of the token data itself. \n\n #The Token was encrypted using itsdangerous.URLSafeTimedSerializer which \n #allows us to have a max_age on the token itself. When the cookie is stored\n #on the users computer it also has a exipry date, but could be changed by\n #the user, so this feature allows us to enforce the exipry date of the token\n #server side and not rely on the users cookie to exipre. \n #max_age = app.config[\"REMEMBER_COOKIE_DURATION\"].total_seconds()\n\n #Decrypt the Security Token, data = [username, hashpass]\n data = login_serializer.loads(token)\n\n #Find the User\n user = User.query.filter_by(email = data[0]).first()\n\n #Check Password and return user or None\n if user and data[1] == user.pwd:\n \t#On update la derniere connection du user\n \tuser.update_last_connection()\n return user\n return None\n\n\n\n\n\n\n\n #######################################################\n ################# REQUETES ############################\n #######################################################","def login(self):","def login():","def login():","def test_create_session(self):\n finder = FinderInsidePro(self.test_key)\n session_id = finder.create_session(2811)\n assert isinstance(session_id, str)\n assert session_id == finder.session_id\n assert len(session_id)","def save_token(self):\n db.session.add(self)\n db.session.commit()","def UserToken(self) -> object:","def logininfo():\n\n email = request.form.get(\"email\")\n password = request.form.get(\"password\")\n\n user = User.query.filter_by(email=email).first()\n # import pdb; pdb.set_trace()\n if not user:\n return redirect(\"/register\")\n\n if user.password != password:\n flash('Invalid password, please try again!')\n return redirect(\"/\")\n\n session[\"user_id\"] = user.user_id\n\n return redirect(\"/feedpage\")","def clave_unica_login(request):\n clave_unica = ClaveUnicaSettings()\n state = clave_unica.generate_token()\n request.session['state'] = state\n clave_unica_url = clave_unica.get_csrf_redirect_url(state)\n return redirect(clave_unica_url)","def get_posession(self, s):\r\n return 1","def get_session(id):\n session = Session.query.get(id)\n result = session_schema.dump(session).data\n return jsonify({'status': 'success', 'message': None, 'data': result}), 200","def authentUser(login, password, pcID):\n\n serverDatetime = datetime.now()\n\n serverDatetime = str(serverDatetime)\n\n db = DataBaseConnection()\n\n if db:\n query = f\"SELECT * FROM {Account.tablename} WHERE {Account.loginCol} = ?\"\n\n try:\n db.cursor.execute(query, login)\n except Exception as error:\n return {\"flag\": \"queryError\", \"message\": f\"{error} | {query}\"}\n else:\n row = db.cursor.fetchone()\n\n if row:\n accountObj = Account(*row)\n\n if password == accountObj.password:\n if not accountObj.firstPCID:\n status, message = accountObj.modifyColumn(column=accountObj.firstPCIDCol, newValue=pcID)\n\n return {\"flag\": \"activated\", \"message\": f\"activated first succefuul | {status} | {message} | {row}\"} if status else {\"flag\": \"updateError\", \"message\": \"error to update first user infos\"}\n\n elif not accountObj.secondPCID:\n status, message = accountObj.modifyColumn(column=accountObj.secondPCIDCol, newValue=pcID)\n\n return {\"flag\": \"activated\", \"message\": f\"activated second succefuul | {status} | {message} | {row}\"} if status else {\"flag\": \"updateError\", \"message\": \"error to update second user infos\"}\n\n\n else: # all keys are used\n return {\"flag\": \"allKeysUsed\", \"Userinfos\": [accountObj.firstPCID, accountObj.secondPCID]}\n \n else: # invalide password\n return {\"flag\": f\"invalidPassword\", \"message\": \" {query} | {row}\"}\n \n else:\n return {\"flag\": f\"invalidLogin\", \"message\": f\"{query}\"}","def test_set_session():","def identificacion(payload):\n if (payload['identity']):\n # el identity me devuelve el id del usuario que se ha logeado entonces gracias a ello yo puedo almacenar otros campos\n resultado = UsuarioModel.query.filter_by(id=payload['identity']).first()\n if resultado:\n return (resultado.id, resultado.correo)\n else:\n return None\n else:\n return None","def api_check_cod_verificacion(request):\n cod_verificacion = request.matchdict['cod_verificacion']\n user = RepositorioUsario.check_cod_verificacion(request, cod_verificacion)\n if user is not None: \n # cambiar estado del atributo user.activo\n user.set_activo(True)\n user.remove_cod_verificacion()\n # Logueo de usuario\n request.session['user'] = user\n headers = remember(request, user.id)\n response = Response(json_body=user.__json__(request))\n response.headers.extend(headers)\n return response\n else:\n return Response(status=400, json_body={'titulo': 'Usuario no encontrado',\n 'msg': 'Revisa el código de verificación del enlace'})","def refresh_token(self, subid):\n from expfactory.database.models import Participant\n\n p = Participant.query.filter(Participant.id == subid).first()\n if p is not None:\n p.token = str(uuid.uuid4())\n self.session.commit()\n return p","def nuevopermiso(): \n if not current_user.is_authenticated():\n flash('Debe loguearse primeramente!!!!', 'loggin')\n return render_template('index.html')\n \n permission = UserRol('ADMINISTRADOR')\n if permission.can():\n form = PermisoFormulario(request.form)\n form.id_recurso.choices= [(r.id, r.nombre) for r in db_session.query(Recurso).order_by(Recurso.nombre)]\n if request.method == 'POST' and form.validate():\n try:\n permiso = Permiso(form.codigo.data, form.descripcion.data, form.id_recurso.data)\n db_session.add(permiso)\n db_session.commit()\n flash('El permiso ha sido registrado con exito','info')\n return redirect('/permiso/administrarpermiso')\n except DatabaseError, e:\n if e.args[0].find('duplicate key value violates unique') != -1:\n flash('Clave unica violada por favor ingrese otra combinacion de permiso con recurso unica' , 'error')\n else:\n flash('Error en la Base de Datos' + e.args[0], 'error')\n return render_template('permiso/nuevopermiso.html', form=form)\n return render_template('permiso/nuevopermiso.html', form=form)\n else:\n flash('Sin permisos para agregar permisos', 'permiso')\n return render_template('index.html')","def test_session_promotion(self):\r\n cursor = self.db.cursor()\r\n cursor.execute(\"INSERT INTO session VALUES ('123456', 0, 0)\")\r\n incookie = Cookie()\r\n incookie['trac_session'] = '123456'\r\n outcookie = Cookie()\r\n req = Mock(authname='john', base_path='/', incookie=incookie,\r\n outcookie=outcookie)\r\n session = Session(self.env, req)\r\n self.assertEqual('john', session.sid)\r\n session.save()\r\n\r\n cursor.execute(\"SELECT sid,authenticated FROM session\")\r\n self.assertEqual(('john', 1), cursor.fetchone())\r\n self.assertEqual(None, cursor.fetchone())","def get_session(_id):\n token = get_token()\n headers = {'Content-Type': 'application/json', 'Authorization': f'Bearer {token}'}\n endpoint = f\"https://api.signicat.io/identification/v2/sessions/{_id}\" \n \n response = requests.get(endpoint, headers=headers).json()\n identification = response['identity']\n print(identification)\n return response['identity']","def auth_token(self):","def test_new_session_promotion(self):\r\n cursor = self.db.cursor()\r\n incookie = Cookie()\r\n incookie['trac_session'] = '123456'\r\n outcookie = Cookie()\r\n req = Mock(authname='john', base_path='/', incookie=incookie,\r\n outcookie=outcookie)\r\n session = Session(self.env, req)\r\n self.assertEqual('john', session.sid)\r\n session.save()\r\n\r\n cursor.execute(\"SELECT sid,authenticated FROM session\")\r\n self.assertEqual(('john', 1), cursor.fetchone())\r\n self.assertEqual(None, cursor.fetchone())","def token(db):\n user = User.find_by_identity('admin@localhost.com')\n return user.serialize_token()","def get_token(self, session, **kwargs):\n return None","def token(db):\n token = TokenFactory()\n db.session.commit()\n return token","def login():\n pass","def check_google_token():\n #get token from login page and google's token rigamorole\n gtoken = request.form.get(\"idtoken\")\n #validate token\n g_profile = apiapijoyjoy.validate_google_token(gtoken)\n #collect user info from google\n name = g_profile['given_name']\n lname = g_profile['family_name']\n email = g_profile['email']\n # start a session\n session[\"user_id\"] = email\n user = User.query.filter_by(email=email).first()\n #create flags for Flask to return to google's scripts and take frontend action accordingly\n if user:\n return \"FLASK SEES USER\"\n else:\n #create new user in SQLAlchemy using info above from Google. BUT WAIT WHAT?! CODE REVIEW PLS!\n new_user = User(email=email, name=name, lname=lname)\n db.session.add(new_user)\n db.session.commit()\n return \"FLASK SEES NO USER\"","def session(rq):\n rq.session['username']='wxy'\n return HttpResponse(__file__ + '::session and first user is my daugter:' + rq.session['username'])","def test_valid_session_key(self, db_mock):\n repo = Repository()\n db_instance = db_mock.return_value\n\n db_instance.get_session.return_value = (\"1234\", 1, 4321)\n self.assertTrue(repo.valid_session_key(\"1234\"))\n\n db_instance.get_session.return_value = None\n self.assertFalse(repo.valid_session_key(\"1234\"))","def sessio_changed(session, event):\n # si passem estat a convocat cal enviar mail de convocatoria...\n try:\n # old = _GW(event.status['review_state'])\n new = _GW(event.transition.new_state_id)\n # message = (old) + ' →2 ' + (new)\n addEntryLog(session, None, _(u'Changed workflow state'), new) # add log\n except:\n addEntryLog(session, None, _(u'New session created'), session.Title()) # add log\n\n if event.transition is None:\n # Quan crees element també executa aquesta acció, i ID no existeix\n # Fem el bypass\n pass\n else:\n \"\"\" Previ a l'enviament del missatge et troves en un estat intermig,\n creat només per això, que es diu Convocant (no es veu enlloc)\n \"\"\"\n if event.transition.id == 'convocant':\n raise Redirect(session.absolute_url() + '/mail_convocar')\n\n if event.transition.id == 'tancar':\n member = api.user.get(username='admin')\n user = member.getUser()\n session.changeOwnership(user, recursive=False)\n owners = session.users_with_local_role(\"Owner\")\n session.manage_delLocalRoles(owners)\n if user.getId() == 'admin':\n session.manage_setLocalRoles(user.getId(), [\"Owner\"])\n else:\n session.manage_setLocalRoles(user._id, [\"Owner\"])\n session.reindexObjectSecurity()\n transaction.commit()","def temp_getToken():\n # First check if query is okay or not\n data = json.loads(request.data)\n username = data.get(\"username\",None)\n password = data.get(\"password\",None)\n \n if request.headers.get('X-VITASK-API') != \"2020_Mar_25\" or username is None or password is None:\n return jsonify({\n \"error\" : \"Incorrect API Request\",\n \"code\" : \"400\" # Bad request\n })\n \n # Now began actual work\n username = username.upper()\n \n # This API is only to get user token and get personal details. For syncing details, there will be a seperate API\n # This assumes that token is None just like previous authenticate\n valid = True\n try:\n sess, valid = generate_session(username, password)\n except Exception as e:\n return jsonify({\n \"error\" : \"Something broke\",\n \"code\" : \"500\"\n })\n if not valid:\n # Password incorrect\n return jsonify({\n \"error\" : \"Incorrect Password\"\n })\n ref = db.reference('vitask')\n try:\n profile = {}\n profile, check_profile = get_student_profile(sess, username)\n session['id'] = profile['appNo']\n session['name'] = profile['name']\n session['reg'] = profile['regNo']\n session['loggedin'] = 1\n if(check_profile == False):\n return jsonify({\"Error\": \"Internal Error in fetching profile.Please try again.\"})\n finally:\n name, school, branch, program, regno, appno, email, proctoremail, proctorname, api = ProfileFunc()\n # Timetable,Attendance,Acadhistory and Marks fetching in parallel\n try:\n runInParallel(parallel_timetable(sess, username, session['id']), parallel_attendance(sess, username, session['id']), parallel_acadhistory(sess, username, session['id']), parallel_marks(sess, username, session['id'])) \n finally:\n return jsonify({'Name': name,'School': school,'Branch': branch,'Program': program,'RegNo': regno,'AppNo': appno,'Email': email,'ProctorEmail': proctoremail,'ProctorName': proctorname,'APItoken': api})","def save(self):\n\n self.curr.execute(\n ''' INSERT INTO revoked_tokens(jti)\\\n VALUES('{}')\\\n RETURNING jti''' \\\n .format(self.jti))\n revoked_token = self.curr.fetchone()\n self.conn.commit()\n self.curr.close()\n return json.dumps(revoked_token, default=str)","def user():","def login_success(user_id):\n session['user'] = {}\n u_obj = User.query.filter(User.user_id == user_id).first()\n saved_events = UserEvent.query.filter_by(user_id = user_id).all()\n user = session['user']\n user['user_id'] = user_id\n user['name'] = u_obj.fname\n user['saved'] = [event.eventbrite_id for event in saved_events]","def get_stulogin():\n\n rows = db.engine.execute(f\"SELECT * FROM stulogin WHERE STULOGINID = {g.user.STULOGINID} \")\n res = []\n for row in rows:\n res.append(dict(row))\n return jsonify(res)","def getCruSession(user: str, password: str, url: str) -> Session:\n \n payload = {\n 'Username': user,\n 'Password': password,\n 'ufprt': 'CAF8477BDE81160B023359032A131EBA8ED2EFCCA369B1D4406ABA090A186F53D289629E6B2901EADF92F7200C4504C4EC8DA6A8AE05FD4C6298C6E3A5B090CF7AFEEC6E47030ACB04698860352BD8EA3914830C3D6099400102E9B87AD1389C568A810357BDE2D5BF115952F6B1B1D8C4E8783B',\n 'RememberMe': 'false'\n }\n \n session = HTMLSession()\n \n res = session.post(\"https://cruonline.crugroup.com/login\", data=payload)\n assert res.status_code == 200\n \n # POST a different ufprt value so that if site detects that another user has logged on,\n # we force a log off\n logoff_payload = {\n 'ufprt': '7674E654A97C61E8335D82E3E72CB21E3B8BC67B82C4A2C28B5359C474B3E5AFAAD640D57AE7CC8A40515A37EF5740681F41C249B2F85397D86C2560F38BD27A43B4401FFB761DFEB88F3E34BAC675CA9AEADA14AD076EB02A85EAADD50D4678BE783B30BF67E11B6394BEE63C522175658A6BAD34B4EEA8982EC0C59790667556CC29D0'\n }\n res_final = session.post(\"https://cruonline.crugroup.com/login\", data=logoff_payload)\n assert res_final.status_code == 200\n \n return res_final.session","def __generate_session_token(self):\n\n return get_random_string(length=32)","def login(request, session):\n\n if 'tid' in session: # we assume that if there is a tid in the session dict then the user is authenticated\n return {\"success\": 1, \"message\": \"你已经登录了.\"}\n teamname = request.form.get('teamname', None) # get the teamname and password from the POSTed form\n password = request.form.get('password', None)\n if teamname is None or teamname == '':\n return {'success': 0, 'message': \"用户名不能为空.\"}\n if password is None or password == '': # No password submitted\n return {\"success\": 0, \"message\": \"密码不能为空.\"}\n if len(teamname) > 250:\n return {\"success\": 0, \"message\": \"STAHP!\"}\n teamname = teamname.encode('utf8').strip()\n password = password.encode('utf8')\n teamCurr = db.teams.find({'teamname': teamname})\n if teamCurr.count() == 0: # No results returned from mongo when searching for the user\n return {\"success\": 0, \"message\": \"未找到用户名'%s'.\" % teamname}\n if teamCurr.count() > 1:\n return {\"success\": 0, \"message\": \"查找用户信息失败. 请联系管理员.\"}\n checkTeam = teamCurr[0]\n if checkTeam['email_verified'] == False:\n return {\"success\": 0, \"message\": \"请先访问邮箱查收验证邮件.\"}\n pwhash = checkTeam['pwhash'] # The pw hash from the db\n if bcrypt.hashpw(password, pwhash) == pwhash:\n if checkTeam.get('debugaccount', None):\n session['debugaccount'] = True\n if debug_disable_general_login:\n if 'debugaccount' not in checkTeam or not checkTeam['debugaccount']:\n return {'success': 2, \"message\": \"Correct credentials! But the game has not started yet...\"}\n if checkTeam['tid'] is not None:\n session['tid'] = checkTeam['tid']\n session['teamname'] = checkTeam['teamname']\n session['is_zju_user'] = utilities.is_zju_email(checkTeam['email'])\n else: # SET THE 'tid' TO str('_id') FOR MIGRATION PURPOSES AND ADD THE 'tid' TO THE DOCUMENT\n session['tid'] = checkTeam['_id']\n session['teamname'] = checkTeam['teamname']\n session['is_zju_user'] = utilities.is_zju_email(checkTeam['email'])\n db.teams.update({'_id': checkTeam['_id']}, {'tid': checkTeam['_id']})\n return {\"success\": 1, \"message\": \"用户'%s'登录成功.\" % teamname,\n 'teamname': session['teamname'], 'is_zju_user': session['is_zju_user']}\n return {\"success\": 0, \"message\": \"密码错误.\"}","def login(user_name,password,cur):\n check=False\n id=None\n \n psql=(\n f\"\"\"select id,password from users where user_name='{user_name}'\"\"\")\n cur.execute(psql)\n record=cur.fetchone()\n \n\n if not record:\n flash('nom utilisateur non valide!')\n \n else:\n id=record[0]\n password_record=record[1].tobytes() \n\n if bcrypt.checkpw(password.encode('utf-8'),password_record):\n check=True\n flash(\"Connexion Réussi!\")\n else:\n flash(\"Svp verifiez vos coordonnees et reessayer !\")\n\n return [check,id]","def getSession():\n return call(\"getSession\")","def login_user():\n pass","def login(request):\n\n print('login')\n if request.method == 'POST':\n md5_pwd = ''\n admin = False\n\n username = request.POST.get('username', False)\n mode1 = 'Human'\n mode = NameSpace.objects.get(ns_id=mode1)\n password = request.POST.get('password', False)\n if username:\n username = username.replace(\"\\\"\", \"\").replace(\"'\", \"\")\n if password:\n password = password.replace(\"\\\"\", \"\").replace(\"'\", \"\")\n md5_pwd = hashlib.md5(password.encode()).hexdigest()\n if (username != False and password != False):\n user = User.objects.filter(username = username,ns_id=mode, password = md5_pwd)\n\n\n if user.exists():\n # print('LOGGATO')\n mode1 = 'Human'\n mode = NameSpace.objects.get(ns_id=mode1)\n user = User.objects.get(username=username, password=md5_pwd,ns_id=mode)\n print(\"username: \" + username)\n request.session['username'] = username\n request.session['mode'] = mode1\n admin = User.objects.filter(profile='Admin')\n if admin.exists():\n admin = admin.first()\n admin_name = admin.username\n request.session['team_member'] = admin_name\n else:\n request.session['team_member'] = 'Test'\n\n request.session['profile'] = user.profile\n return redirect('MedTAG_sket_dock_App:index')\n #return redirect('MedTAG_sket_dock_App:select_options')\n\n profile_list = User.objects.values_list('profile', flat=True).distinct()\n if 'Admin' in profile_list:\n admin = True\n context = {'errorMessage': \"Your username and password didn't match.\",\"admin\":admin}\n return render(request, 'MedTAG_sket_dock_App/login.html', context)\n\n else:\n username = request.session.get('username', False)\n admin = False\n profile_list = User.objects.values_list('profile', flat=True).distinct()\n if 'Admin' in profile_list:\n admin = True\n context = {'admin': admin}\n\n if username:\n return redirect('MedTAG_sket_dock_App:index')\n\n return render(request, 'MedTAG_sket_dock_App/login.html',context)","def session(get_session):\n return get_session()","def login_form():\n\n # retrieving email and password from user\n email = request.form.get(\"email\")\n form_password = request.form.get(\"password\")\n\n if not email or not form_password:\n flash(\"Please resubmit your information correctly.\")\n return redirect(\"/\")\n\n # hash the password provided\n hash_object = hashlib.md5(form_password.encode())\n\n # querying by the password provided by the user\n user = User.query.filter_by(email=email).first()\n password = user.password\n\n # if the hash password matches the password in the database then\n # log user in and create a session\n if hash_object.hexdigest() == password:\n\n # created a session to store the user id\n session[\"user_id\"] = user.user_id\n return redirect(f\"/user/{user.user_id}\")\n\n else:\n flash(\"Sorry, wrong password!\")\n return redirect(\"/\")","def index():\n \n nombre_rol='SIN ROL' #ingresa sin rol\n if auth.user_id: #variable que contiene el id del usuario logueado\n reg_id_grupo_del_logueado=db(auth.user.id==db.auth_membership.user_id).select(db.auth_membership.group_id)\n id_grupo_del_logueado=reg_id_grupo_del_logueado[0].group_id #esta variable contiene el id del grupo, es decir solo el número (limpiamos la variable anterior)\n reg_nombre_rol=db(db.auth_group.id==id_grupo_del_logueado).select(db.auth_group.role)\n nombre_rol=reg_nombre_rol[0].role #limpiamos variable anterior para que solo busque el rol (la palabra)\n # se asigna un rol\n \n if nombre_rol=='Administrador':\n redirect(URL('principal_administrador'))\n elif nombre_rol=='vendedor':\n redirect(URL('principal_vendedor'))\n else:\n redirect(URL('principal_cliente'))\n\n response.flash = T(\"For sale\") \n return dict(message=T('Bienvenido al Sistema de ventas online'))","def user_return():\n\n #take csrf-token from cookies\n token = request.cookies.get('token')\n #decoding token\n uuid = jwt.decode(token, app.config['SECRET_KEY'], algorithms=[\"HS256\"])['user_id']\n #get current user\n user = User.query.filter_by(uuid=uuid).first()\n return user","def get_token(request):\n try:\n ft_session = request.session['ft_token']\n token = OAuthAccessToken.objects.get(session_key=ft_session)\n # invalidate any token > 24 hours old\n now = datetime.now()\n diff = now - token.created\n if diff.days:\n token.delete()\n return False\n # TODO check ip address matches\n #oauthorize\n return token\n except KeyError:\n print 'no session token..'\n except OAuthAccessToken.DoesNotExist:\n print 'no access token ...'\n return False","def login_core(self, usuario_model) -> bool:\n usuario_json = eval(json.dumps(usuario_model.__dict__))\n result = self.database.select_db(name_object=\"Usuario\", filter_data=usuario_json)\n if isinstance(result, object) and result is not None:\n Constant.USUARIO = self.encrypt.decrypt(eval(result[\"usuario\"]))\n return True\n return False","def login(request):\n msg=\"\"\n if(request.POST):\n email=request.POST.get(\"txtEmail\")\n pwd=request.POST.get(\"txtPassword\")\n s=\"select count(*) from tbllogin where username='\"+email+\"'\"\n c.execute(s)\n i=c.fetchone()\n if(i[0]>0):\n s=\"select * from tbllogin where username='\"+email+\"'\"\n c.execute(s)\n i=c.fetchone()\n if(i[1]==pwd):\n request.session['email'] = email\n if(i[3]==\"1\"):\n if(i[2]==\"admin\"):\n return HttpResponseRedirect(\"/adminhome\")\n elif(i[2]==\"eventmanager\"):\n return HttpResponseRedirect(\"/emhome\")\n elif(i[2]==\"alumni\"):\n return HttpResponseRedirect(\"/alumnihome\")\n elif(i[3]==\"inactive\"):\n msg=\"Your registration is incomplete. Please register\"\n else:\n msg=\"You are not authenticated to login\"\n else:\n msg=\"Incorrect password\"\n else:\n msg=\"User doesnt exist\"\n return render(request,\"login.html\",{\"msg\":msg})","def handle_session_mgt(request):\n db = cloud_db.DbManager()\n try:\n if request.method == 'POST':\n ### login(signin) ###\n if len(request.body) == 0:\n raise Exception(MSG_NODATA)\n data = json.loads(request.body)\n\n if not data.get('user_id') or not data.get('password'):\n raise Exception(MSG_INVALID_PARAMS)\n if request.session.get('user'):\n raise Exception(MSG_ALREADY_LOGGEDIN)\n user_id = data['user_id']\n password = data['password']\n\n authenticated = db.check_authentication(user_id)\n if authenticated is None:\n raise Exception(MSG_UNKNOWN_ERROR)\n elif authenticated is False:\n return JsonResponse(constants.CODE_NEED_AUTH)\n\n user = {}\n intpr_session = {}\n user_type = db.retrieve_user_type(user_id, password)\n if user_type is None:\n raise Exception(MSG_INVALID_IDPW)\n elif user_type == 'patient':\n user = db.retrieve_patient(user_id, password)\n intpr_session['sessions'] = db.retrieve_patient_session(data['user_id'])\n elif user_type == 'physician':\n user = db.retrieve_physician(user_id, password)\n intpr_session['sessions'] = db.retrieve_physician_session(data['user_id'])\n else:\n raise Exception(MSG_INVALID_IDPW)\n if not user.get('user_id'):\n raise Exception(MSG_INVALID_IDPW)\n\n # intpr session check\n new_flag = 0\n for session in intpr_session['sessions']:\n if session['status'] == 0:\n new_flag = 1\n intpr_session['new'] = new_flag\n\n # set sessions\n request.session['user'] = user\n # pprint(user)\n request.session['intpr_session'] = intpr_session\n # request.session['medical_image'] = {}\n # request.session.create('medical_image')\n logger.info('user %s logged in.' % user['user_id'])\n\n return JsonResponse(constants.CODE_SUCCESS)\n\n elif request.method == 'DELETE':\n ### Logout ###\n if request.session.get('user'):\n # del request.session['user']\n request.session.clear()\n return JsonResponse(constants.CODE_SUCCESS)\n else:\n raise Exception(MSG_NO_USER_LOGGEDIN)\n\n except Exception as e:\n logger.exception(e)\n return JsonResponse(dict(constants.CODE_FAILURE, **{'msg': str(e)}))\n\n return JsonResponse(dict(constants.CODE_FAILURE, **{'msg': MSG_UNKNOWN_ERROR}))","def save_session(self, session):\n db = self.open()\n db[session.id] = session","def authorize():\n\n google = oauth.create_client('google') # create the google oauth client\n # Access token from google (needed to get user info)\n token = google.authorize_access_token()\n # userinfo contains stuff u specificed in the scrope\n resp = google.get('userinfo')\n user_info = resp.json()\n email = user_info['email']\n first_name = user_info['given_name'].capitalize()\n last_name = user_info['family_name'].capitalize()\n image_url = User.image_url.default.arg\n if user_info['picture'] != '' and user_info['picture']:\n image_url = user_info['picture']\n user = oauth.google.userinfo() # uses openid endpoint to fetch user info\n # Here you use the profile/user data that you got and query your database find/register the user\n # and set ur own data in the session not the profile from google\n\n # compare with database;\n user = User.query.filter_by(email=email).first()\n print(user)\n\n if not user:\n user = User.signup(email=email, password='password1', username='temporary',\n first_name=first_name, last_name=last_name, image_url=image_url, cover_url=User.cover_url.default.arg)\n db.session.commit()\n do_login(user)\n return redirect(f'/user/{user.id}/force-reset')\n else:\n do_login(user)\n return redirect('/')","def generate_session(db, useremail):\n user = db.cursor().execute('SELECT email FROM users WHERE email IS ?', [useremail]).fetchone()\n if user:\n existing_session = db.cursor().execute('SELECT sessionid FROM sessions WHERE useremail IS ?',\n [user[0]]).fetchone()\n if existing_session:\n cookie = SimpleCookie()\n cookie[COOKIE_NAME] = existing_session[0]\n return cookie\n else:\n key = str(uuid.uuid4())\n db.cursor().execute('INSERT INTO sessions VALUES (?, ?)', [key, useremail])\n db.commit()\n cookie = SimpleCookie()\n cookie[COOKIE_NAME] = key\n return cookie\n return None","def get_id():\n token = get_token()\n # Endpoint url\n endpoint = \"https://api.idfy.io/identification/v2/sessions\"\n # Setting headers with the authorization bearer\n headers = {'Content-Type': 'application/json', 'Authorization': f'Bearer {token}'}\n data = {\n \"languages\": \"en\",\n \"flow\": \"redirect\",\n \"allowedProviders\": [\n \"no_bankid_netcentric\",\n \"no_bankid_mobile\"\n ],\n \"include\": [\n \"name\",\n \"date_of_birth\",\n \"phone_number\",\n \"nin\",\n \"email\"\n ],\n \"redirectSettings\": {\n \"successUrl\": \"https://example.com/success\",\n \"abortUrl\": \"https://example.com/abort\",\n \"errorUrl\": \"https://example.com/error\"\n }\n }\n # Converting the data into a json string and sending a post request \n response = requests.post(endpoint, data=json.dumps(data), headers=headers).json()\n # Opening the browser and to authenticate the user\n webbrowser.open(response['url'])\n # returning the session id\n return response['id']","def user(self):","def get_session_id(self):\n raise NotImplementedError()","def log_in():\n\n user = request.form.get(\"username\")\n #password = request.form.get(\"password\")\n\n try:\n\n current_user = User.query.filter_by(email=user).one()\n flash('You were successfully logged in')\n session[\"user_id\"] = current_user.user_id\n\n return render_template('homepage.html')\n\n except sqlalchemy.orm.exc.NoResultFound:\n\n return render_template('/registration_form.html')","def get_current_session(self) -> SessionType:","def check(user,passwd):\n myvars=dict(id=user)\n try:\n table=model.db.select('manager',myvars,where=web.db.sqlwhere(myvars))\n real_passwd=table[0]['passwd']\n if real_passwd==passwd:\n session.login=1\n session.id=user\n else:\n pass\n except:\n pass","def getToken():\n # First check if query is okay or not\n data = json.loads(request.data)\n username = data.get(\"username\",None)\n password = data.get(\"password\",None)\n \n if username is None or password is None:\n return jsonify({\n \"error\" : \"Incorrect API Request\",\n \"code\" : \"400\" # Bad request\n })\n check_header = magiccheck(request.headers.get('X-VITASK-API'))\n if(check_header == False):\n return jsonify({\n \"error\" : \"Invalid Header\",\n \"code\" : \"403\" # Unauthorised\n })\n # Now began actual work\n username = username.upper()\n \n # This API is only to get user token and get personal details. For syncing details, there will be a seperate API\n # This assumes that token is None just like previous authenticate\n valid = True\n try:\n sess, valid = generate_session(username, password)\n except Exception as e:\n return jsonify({\n \"error\" : \"Something broke\",\n \"code\" : \"500\"\n })\n if( valid == False ):\n # Password incorrect\n return jsonify({\n \"error\" : \"Incorrect Password\"\n })\n ref = db.reference('vitask')\n try:\n profile = {}\n profile, status = get_student_profile(sess, username)\n if( status == False ):\n print(\"Failed at profile.\")\n return jsonify({\"Error\": \"Internal Error in fetching profile.Please try again.\"})\n session['id'] = profile['appNo']\n session['name'] = profile['name']\n session['reg'] = profile['regNo']\n session['loggedin'] = 1\n except Exception as e:\n print(e)\n return jsonify({\"Error\": \"Internal Error in fetching profile.Please try again.\"})\n finally:\n # Timetable,Attendance,Acadhistory and Marks fetching\n try:\n status = parallel_timetable(sess, username, session['id'])\n if( status == False ):\n print(\"Failed at timetable.\")\n return jsonify({\"Error\": \"Internal Error in fetching timetable.Please try again.\"})\n except Exception as e:\n print(e)\n print(\"Exception at timetable.\")\n return jsonify({\"Error\": \"Internal Error in fetching timetable.Please try again.\"})\n finally:\n try:\n status = parallel_attendance(sess, username, session['id'])\n if( status == False ):\n print(\"Failed at attendance.\")\n return jsonify({\"Error\": \"Internal Error in fetching attendance.Please try again.\"})\n except Exception as e:\n print(e)\n print(\"Exception at attendance.\")\n return jsonify({\"Error\": \"Internal Error in fetching attendance.Please try again.\"})\n finally:\n try:\n status = parallel_acadhistory(sess, username, session['id'])\n if( status == False ):\n print(\"Failed at acadhistory.\")\n return jsonify({\"Error\": \"Internal Error in fetching academic history.Please try again.\"})\n except Exception as e:\n print(e)\n print(\"Exception at acadhistory.\")\n return jsonify({\"Error\": \"Internal Error in fetching academic history.Please try again.\"})\n finally:\n try:\n status = parallel_marks(sess, username, session['id'])\n if( status == False ):\n print(\"Failed at marks.\")\n return jsonify({\"Error\": \"Internal Error in fetching marks.Please try again.\"})\n except Exception as e:\n print(e)\n print(\"Exception at marks.\")\n return jsonify({\"Error\": \"Internal Error in fetching marks.Please try again.\"})\n finally:\n # API Calls logging\n temp = ref.child(\"account\").child('account-'+profile['appNo']).child(profile['appNo']).get()\n count = int(temp['API-Calls']) + 1\n tut_ref = ref.child(\"account\")\n new_ref = tut_ref.child('account-'+profile['appNo'])\n new_ref.set({\n profile['appNo']: {\n 'X-VITASK-API': temp['X-VITASK-API'],\n 'Name': temp['Name'],\n 'RegNo': temp['RegNo'],\n 'Account-Type': temp['Account-Type'],\n 'API-Calls': count,\n 'Start-Date': temp['Start-Date'],\n 'End-Date': temp['End-Date']\n }\n })\n return jsonify({'Name': profile['name'],'School': profile['school'],'Branch': profile['branch'],'Program': profile['program'],'RegNo': profile['regNo'],'AppNo': profile['appNo'],'Email': profile['email'],'ProctorEmail': profile['proctorEmail'],'ProctorName': profile['proctorName'],'APItoken': profile['token']})","def next_identity(self) -> UserId:\n ...","def login_confirmation():\n\n email = request.form['email']\n password = request.form['password']\n\n user = User.query.filter_by(email=email, password=password).first()\n\n if user:\n session['user_id']=user.user_id\n # return redirect(\"/users/<int:user.user_id>\")\n return redirect(\"/users/%s\" % user.user_id)\n else:\n flash(\"Incorrect username or password\")\n return redirect(\"/login\")","def getcsrf(session):\n session.get(\"http://anichart.net\")","def auth_create_session(self) -> str:\n self.__logger.debug('Eva.auth_create_session called')\n return self.__http_client.auth_create_session()","def _generate_token(self):\n return sha1(\"%s#%s\" % (time(),\n self.app.cfg['sessions/secret'])).hexdigest()","def save_admin():\n user = users.get_current_user()\n if user:\n if users.is_current_user_admin() or is_local_admin():\n added_admin_mail = request.forms.get('mail')\n added_admin = users.User(added_admin_mail)\n if added_admin:\n #return added_admin.user_id()\n #output = added_admin.nickname()+ ' ' + added_admin.user_id()\n #return output\n new_admin = Admins(parent=admin_base)\n new_admin.ref_nick = user.nickname()\n new_admin.admin_nick = added_admin.nickname()\n new_admin.admin_id = 'no id'#added_admin.user_id()\n new_admin.put()\n redirect('/admin')\n \n else:\n #return \"Не получилось\"\n output = template('admin', name=g_name, log_in_out = users.create_logout_url('/'), opt = 'Выход', user = user.nickname(), admins = admins, error=\"Неверный email\")\n return output\n else:\n redirect('/')\n else:\n redirect('/')","def login(cls, identifient, password, methode=\"username\"):\n db = database.db_connection()\n cursor = db.cursor()\n\n if methode == \"username\":\n sql_query = \"SELECT password FROM user WHERE username=?\"\n elif methode == \"email\":\n sql_query = \"SELECT password FROM user WHERE email=?\"\n\n cursor.execute(sql_query, (identifient, ))\n row = cursor.fetchone()\n cursor.close()\n if row == None:\n raise ValueError(\"useranme or email inexistent\")\n else:\n # I'm gonna change this part to add some security to the password\n if row[0] == password:\n print(\"authantication confirmed\")\n # charging the user data and if the account is deleted we must change that\n user_data = User.search(identifient, by=methode, type_retrun=\"dict\")\n return User( **user_data, conected=True)\n else:\n print(\"wait, you're an impostor\")\n return False","def admin_login():\r\n try:\r\n admin_mail =valid.email_validation(input('enter admin mail '))\r\n password = input(\"Enter you password\")\r\n encoded_pwd = base64.b64encode(password.encode('ascii'))\r\n query = \"select user_id from user \\\r\n where mail_id =%s and password =%s and is_admin_flag = %s;\"\r\n if cursor.execute(query,(admin_mail, encoded_pwd, '1')):\r\n print('admin login')\r\n admin_uid = cursor.fetchone()\r\n return admin_uid[0]\r\n print('invalid credentials')\r\n except Exception as exception_e:\r\n print('Error',exception_e)","def get_ags_token(url,username,password,client,referer,session,token_name):\n #if token_name not in session:\n params = {\n 'username': username,\n 'password': password,\n 'client': client,\n 'referer': referer,\n 'expiration': 720,\n 'f': 'json',\n }\n response = requests.post(\n url ,\n # app.config['ROK_AUTH_URL'],\n data=params\n )\n token = response.json()\n session[token_name] = token\n print(\"{0} token acquired: {1}\".format(token_name, token))\n return token\n # else:\n # print(\"Using existing {0} token: {1}\".format(token_name, session[token_name]))\n # return session[token_name]","def serialize(self):\n return {\n 'user_id' : self.user_id,\n 'session_id' : self.session_id,\n }","def _create_user_session(url: str, netid: str = 'superuser', new: bool = False, add_to_os: bool = True):\n\n # Create requests session\n session = requests.session()\n\n if new:\n netid = create_user(netid, add_to_os)\n\n session.get(url + f'/admin/auth/token/{netid}')\n r = session.get(url + \"/public/auth/whoami\")\n\n try:\n assert r.status_code == 200\n data = r.json()\n assert data[\"success\"] is True\n assert data[\"data\"] is not None\n assert data[\"error\"] is None\n data = copy.deepcopy(data)\n admin_for = data['data']['user']['admin_for']\n for i in admin_for:\n if i['name'] == 'Intro to OS':\n session.cookies['course'] = base64.urlsafe_b64encode(json.dumps(i).encode()).decode()\n except AssertionError as e:\n print_full_error(e, r)\n return session, netid","def do_user_login(user):\n conn.register([model.Rule])\n admindb = conn[current_app.config[\"CONFIGDB\"]]\n user.update_last_login()\n user.save()\n\n session['user'] = {\n 'id': str(user[\"_id\"]),\n 'label': user[\"label\"],\n 'email' : user[\"name\"],\n }\n session['site_admin'] = False\n session['last_activity'] = user[\"last_login\"]\n # Also add the rules information to the session\n if not (ObjectId(current_app.config[\"DEMO_RULE\"]) in user[\"rules\"]):\n user[\"rules\"].append(ObjectId(current_app.config[\"DEMO_RULE\"]))\n\n user.save()\n\n # Loop over the rules\n accesses = { }\n\n if user[\"type\"] == \"passwd\" and (user[\"name\"].endswith(\"brown.edu\") or user[\"name\"].endswith(\"kitware.com\")):\n # Here grant the user with the demo_brown rule\n # flash(\"You used password login, and you get donut ! \")\n # ObjectId(\"529d244959a3aee20f8a00ae\")\n brownrule = ObjectId(\"529d244959a3aee20f8a00ae\")\n if brownrule in user[\"rules\"]:\n # flash(\"You already have the rule\")\n pass\n else:\n # flash(\"Rule must be added\")\n user[\"rules\"].append(ObjectId(\"529d244959a3aee20f8a00ae\"))\n user.save()\n\n for arule in user[\"rules\"]:\n ruleobj = admindb[\"rules\"].Rule.find_one({\"_id\" : arule})\n if ruleobj == None:\n flash(\"Rule not found !! \" + str(arule), \"error\")\n continue\n\n # Create empty DBAccess for that db\n if not str(ruleobj[\"db\"]) in accesses.keys():\n accesses[str(ruleobj[\"db\"])] = DBAccess()\n\n if 'db_admin' in ruleobj and ruleobj[\"db_admin\"] == True:\n accesses[str(ruleobj[\"db\"])].db_admin = True\n if 'can_see_all' in ruleobj and ruleobj[\"can_see_all\"] == True:\n accesses[str(ruleobj[\"db\"])].can_see_all = True\n if 'can_see' in ruleobj:\n if len(ruleobj[\"can_see\"]) > 0:\n accesses[str(ruleobj[\"db\"])].can_see.append(ruleobj[\"can_see\"])\n if 'site_admin' in ruleobj and ruleobj[\"site_admin\"] == True:\n session[\"site_admin\"] = True\n\n # Insert that information in the session\n # In future, session may contain only session it,\n # and this could get into database\n\n# For debugging\n# for adb in accesses.keys():\n# flash(adb + \": \" + str(accesses[adb]), \"info\")\n#\n# flash(\"Site admin : \" + str(session[\"site_admin\"]), \"info\")\n\n\n flash('You are successfully logged in.', 'success')","def save_login(mobile):\n mobile = Mobile(mobile)\n ktt = KTT(mobile)\n ktt.gen_device_code()\n ktt.get_api_start()\n time.sleep(4)\n ktt.post_login()\n time.sleep(4)\n ktt.get_user_info()\n user_info = (\n ktt.user_info[\"uid\"], ktt.user_info[\"name\"], ktt.user_info[\"mobile\"],\n ktt.user_info[\"father\"], ktt.user_info[\"balance\"], ktt.user_info[\"coin\"],\n ktt.device_code, ktt.token, ktt.mobile.os, ktt.mobile.brand, ktt.mobile.mac,\n ktt.mobile.android_id\n )\n print(user_info)\n\n # save one user info record and one user flag\n uis.save([user_info])\n read_flag = [(user_info[0],)]\n uis.save_flag(read_flag)","def getUser():\n\n if 'token' in session:\n return \"Authenticated\"\n else:\n return \"Unauthenticated\"","async def save_session(request, response):\n try:\n await request.app.session_interface.save(request, response)\n except Exception as e:\n if isinstance(e, Exception):\n pass","def login():\n entity = user.User(\n account = request.json['account']\n , password = request.json['password'])\n u = user.User.query.filter(user.User.account == entity.account).first()\n if not u or not u.is_active:\n abort(404)\n if entity.password == u.password:\n if u.token is None:\n u.generate_token()\n db.session.merge(u)\n db.session.commit()\n return jsonify(u.to_dict())\n abort(500)","def user(func) :\n def redirectlogin(session, self) :\n setSessionMessage(session, \"Student Login required\", True)\n return self.redirect('/login')\n\n def checkauth(*args, **kwargs) : \n self = args[0]\n session = getSessionByRequest(self)\n user = getSessionUser(session)\n\n if not user :\n return redirectlogin(session, self)\n\n if user.userType == 'STUDENT' : \n return func(*args, **kwargs)\n\n return redirectlogin(session, self)\n return checkauth","def loginUser(request):\n if request.method == 'POST':\n data = request.data\n userEmail = data['email']\n password = data['password']\n try:\n User = UserInformation.objects.get(email=userEmail)\n if User.password == password:\n loginHash = ''.join(random.choice(letters) for i in range(10))\n User.loginSessionHash = loginHash\n User.save()\n return Response({'login': 'verified', 'hash': loginHash})\n else:\n return Response({'login': 'not verified'})\n except UserInformation.DoesNotExist:\n return Response({'login': 'user undefined'})\n else:\n return Response({'error': 'request type not specified'})","def test_generate_session_key(self, db_mock):\n repo = Repository()\n\n db_instance = db_mock.return_value\n\n db_instance.get_user_info_by_google_id.return_value = (1, {\"id\": 12345})\n db_instance.new_session.return_value = \"1234abcd\"\n \n self.assertEquals(repo.generate_session_key({\"id\": 12345}), \"1234abcd\")\n\n db_instance.new_session.assert_called_once()\n db_instance.create_user.assert_not_called()","def join_session(username, password, application_type=\"EDITOR\",\n api_endpoint=(\"https://engine.tygron.com/api/event/io/get_my_joinable_sessions/?f=JSON\")):\n try:\n sessions_data = requests.post(url=api_endpoint, json=[],\n auth=(username, password))\n except requests.exceptions.ConnectionError:\n print(\"There appears to be no internet connection.\")\n return None\n session_id = -1\n print(sessions_data)\n sessions = sessions_data.json()\n for item in sessions:\n if item[\"name\"] == \"virtual_river_salti\":\n session_id = item[\"id\"]\n break\n print(session_id)\n if session_id > -1:\n join_url = (\"https://engine.tygron.com/api/event/io/join/?f=JSON\")\n \"\"\"\n r = requests.post(url=join_url, json=[session_id, application_type,\n \"Virtual River application script\"],\n auth=(username, password))\n \"\"\"\n r = requests.post(url=join_url, json=[session_id, application_type,\n \"Virtual River application script\"],\n auth=(username, password))\n try:\n pastebin_url = r.json()\n return pastebin_url[\"apiToken\"]\n except UnboundLocalError:\n print(\"LOGIN FAILED: Received no content from Tygron.\")\n return None\n except json.decoder.JSONDecodeError:\n print(\"LOGIN FAILED: Received faulty response from Tygron.\")\n return None","def index():\n '''cookie_user_id = request.get_cookie('uid', 'none')\n if (cookie_user_id == 'none') || (!cookie_user_id.isdigit()):\n response.set_cookie('uid', 'none')\n return template('index', name=g_name, log_in_out = '/login', opt = 'Войти')\n else:\n user = AppUsers.query(AppUsers.local_id==cookie_user_id).fetch()\n if user:\n if user[0].login_type == 1 && user[0].google_id:\n g_user = users.get_current_user()\n if g_user.user_id() == user[0].google_id:\n return template('index', name=g_name, user = user[0].nick, log_in_out = '/exit', opt = 'Выход')\n elif user[0].login_type == 2 && user[0].vk_id:\n vk_cookie = request.get_cookie(\"vk_app_\"+vk_client_id)\n vk_user_id = user[0].vk_id\n if vk_cookie:\n vk_session_info = vk_cookie.split('&')\n vk_cookies = {}\n for i in vk_session_info:\n param = i.split('=')\n vk_cookies[param[0]]=param[1]\n if vk_cookies[mid] == vk_user_id:\n m = hashlib.md5()\n hashstring = 'expire='+vk_cookies['expire']+'mid='+vk_cookies['mid']+'secret'+vk_cookies['secret']+'sid='+vk_cookies['sid']+vk_client_secret\n m.update(hashstring)\n if vk_cookies['sig']==m.hexdigest():\n return template('index', name=g_name, user = user[0].nick, log_in_out = '/exit', opt = 'Выход')\n else:\n response.set_cookie('uid', 'none')\n return template('index', name=g_name, log_in_out = '/login', opt = 'Войти') \n else:\n response.set_cookie('uid', 'none')\n return template('index', name=g_name, log_in_out = '/login', opt = 'Войти') \n else:\n response.set_cookie('uid', 'none')\n return template('index', name=g_name, log_in_out = '/login', opt = 'Войти')\n vk_user_id\n else:\n return \"Invalid database value, please contact admin. UID: \"+user[0].local_id\n else:\n response.set_cookie('uid', 'none')\n return template('index', name=g_name, log_in_out = '/login', opt = 'Войти')'''\n user = users.get_current_user()\n if user:\n return template('index', name=g_name, user = user.nickname(), log_in_out = users.create_logout_url('/'), opt = 'Выход')\n else:\n return template('index', name=g_name, log_in_out = users.create_login_url('/'), opt = 'Войти')","def user_login(TTL=60):\n # auth = request.authorization\n # username = auth.username\n # password = auth.password\n username = request.args.get('username')\n password = request.args.get('password')\n print 'user', username\n print 'pass', password\n\n if g.user:\n print \"g.user:\", g.user\n # return jsonify(URL=url_for('home_timeline'))\n # Create a hash key\n message_json = \"\"\n hash = hashlib.sha224(message_json).hexdigest()\n key = \"Login_API_Cache\" + hash\n print \"Created Key\\t : %s\" % key\n\n # Check if data is in cache.\n if (R_SERVER.get(key)):\n print \"** Messages returned from Redis Cache **\"\n return cPickle.loads(R_SERVER.get(key))\n\n if username != None:\n print \"session\"\n error = None\n if request.method == 'GET':\n print g.user\n print username\n user = userdetails_API_query(username)\n print \"query\", user\n if user is None:\n error = 'Invalid username'\n return jsonify(Status_code=status.HTTP_401_UNAUTHORIZED, username=username, error=error)\n elif not check_password_hash(user['pw_hash'],\n password):\n error = 'Invalid password'\n return jsonify(Status_code=status.HTTP_401_UNAUTHORIZED, username=username, error=error)\n else:\n print \"** Messages returned from MongoDB **\"\n flash('You were logged in')\n session['user_id'] = user['_id']\n username = {'Username_logged_in': username}\n\n ############### REDIS SESSION CODE #####################\n\n message_json = jsonify(\n Status_code=status.HTTP_200_OK, username=username)\n R_SERVER.set(key, cPickle.dumps(message_json))\n R_SERVER.expire(key, TTL)\n\n return message_json\n else:\n print\"logout\", g.user[1]\n flash('You were logged out')\n session.pop('user_id', None)\n username = {'Username_logged_out': g.user[1]}\n return jsonify(URL=url_for('newpublic_timeline'), Username=username, Status_code=status.HTTP_200_OK)","def auth_login(request, user):\n\n ri = rest_interface(opensso_url=OPEN_AM_SERVER_URL)\n\n token_logged_in = ri.do_login(request.REQUEST.get('username'),request.REQUEST.get('password'))\n\n if (ri.isErrorable(token_logged_in)):\n if request.COOKIES.has_key(OPENAM_COOKIE_NAME_FOR_TOKEN):\n del request.COOKIES[OPENAM_COOKIE_NAME_FOR_TOKEN]\n return None\n\n token_logged_in = ri.clear_token(token_logged_in)\n\n \"\"\"\n if user is None:\n user = request.user\n # TODO: It would be nice to support different login methods, like signed cookies.\n if SESSION_KEY in request.session:\n if request.session[SESSION_KEY] != user.pk:\n # To avoid reusing another user's session, create a new, empty\n # session if the existing session corresponds to a different\n # authenticated user.\n request.session.flush()\n else:\n request.session.cycle_key()\n\n \"\"\"\n\n #ssouser = SSOUser(True)\n\n\n ###########ssouser_logged_in.send(sender=ssouser.__class__, request=request, ssouser=ssouser)\n #request.session['somekey'] = 'test'\n\n \"\"\"\n request.ssouser = ssouser\n if request.COOKIES.has_key(OPENAM_COOKIE_NAME_FOR_TOKEN):\n del request.COOKIES[OPENAM_COOKIE_NAME_FOR_TOKEN]\n request.COOKIES[OPENAM_COOKIE_NAME_FOR_TOKEN] = token_logged_in\n \"\"\"\n\n #ri.save_token()\n\n return token_logged_in","def register():\n\n if current_user.is_authenticated:\n return redirect(url_for('general.show_dash'))\n\n form = RegistrationForm()\n\n if form.validate_on_submit():\n\n #Continua con la creacion de un usuario\n hashed_password = user_manager.hash_password(form.password.data)\n new_user = User(\n username=form.username.data,\n email=form.email.data,\n password=hashed_password,\n confirmed_at=datetime.datetime.utcnow(),\n is_enabled=True,\n )\n\n\n role='User'\n role_default = Role.query.filter_by(name=role).first()\n\n if not role_default:\n new_role_default = Role(name = 'User')\n new_user.roles.add(new_role_default)\n else:\n new_user.roles.add(role_default)\n\n try:\n correct = True\n db.session.add(new_user)\n db.session.commit()\n\n except Exception as e:\n # Catch anything unknown\n print(e)\n correct = False\n\n finally:\n if not correct:\n # Cleanup and show error\n db.session.rollback()\n flash('Error creating user, make sure username and email are unique','error')\n\n else:\n flash('Congratulations, you are now a registered user!','success')\n return redirect(url_for('user.login'))\n return render_template('extensions/flask_user/register.html', title='Register', form=form)","def _create_session_data(self, abs_path, sess_root):\n sess_path = os.path.join(abs_path, sess_root)\n if not os.path.exists(sess_path):\n os.makedirs(sess_path)\n sess_id = len(os.listdir(sess_path))\n sess_path = os.path.join(sess_path, str(sess_id))\n print(\"SESSION PATH:\", sess_path)\n print(\"SESSION ID:\", sess_id) \n return sess_id, sess_path","def generate_csrf_token():\n if '_csrf_token' not in login_session:\n login_session['_csrf_token'] = b64encode(urandom(64)).decode() # Cryptographically secure random key\n print(\"_csrf_token:\" + login_session['_csrf_token'])\n return login_session['_csrf_token']","def make_new_session():\n session = Session.objects.create(uuid=str(uuid4()), container_id=None)\n return session.id","def token_browser_profile(request): # URL: 'quest-token-profile'\n m = hashlib.md5()\n m.update('%s |*| %s |*| %s |*| %s' % ( request.POST.get('os', ''),\n request.POST.get('display', ''),\n request.POST.get('software', ''),\n request.POST.get('browser', '')))\n\n profile = Profile(ua_string=request.POST.get('browser', '')[0:255],\n software=request.POST.get('software', '')[0:10000],\n os=request.POST.get('os', '')[0:50],\n display=request.POST.get('display', '')[0:255])\n profile.hashid = m.hexdigest()\n profile.save()\n\n request.session['profile'] = profile.hashid\n request.session.save()\n return HttpResponse('K')","def session_success_data(self):\n return {\n 'id_token': self.encoded_token,\n }","def unique_id() -> bytes:\n ...","def game_id():\n\n # Use new_game method to start a new game\n session.clear()\n session[\"game_id\"] = new_game(engine)\n print \"Creating new game with game_id =\", session[\"game_id\"]\n\n # Redirect to home page\n return redirect(url_for(\"index\"))","def profile():\n github = OAuth2Session(client_id, token=session['oauth_token'])\n print(session['oauth_token'])\n # print(github.get('https://www.goodreads.com/api/auth_user').json())\n return \"hello expedia!! Here is your access_token : \" + session['oauth_token']['access_token']","def returnIdLogin(self):\r\n self.cursor.execute(\"SELECT USUARIO FROM LOGIN;\")\r\n self.__result = self.cursor.fetchall()\r\n self.__lista = []\r\n try:\r\n for self.__i in self.__result:\r\n self.__lista.append(self.__i[0])\r\n return self.__lista\r\n except:\r\n return []","def rpc_senha(self,usuario,senha):\n try:\n retorno,permissao=self.senha_auth.login(usuario,senha)\n print(retorno)\n if(retorno):\n #devolve a resposta de login sucesso\n user=self.sucess_login(usuario,permissao)\n return True,user\n else:\n return False,False\n except xmlrpc.client.Fault as err:\n print(\"Ocorreu um erro\")\n print(\"Código de erro %d\" % err.faultCode)\n print(\"Fault string: %s\" % err.faultString)","def carregarLogin(self, loginId):\r\n try:\r\n self.cursor.execute(\"SELECT * FROM LOGIN WHERE USUARIO = %s;\" %(loginId))\r\n if self.cursor.rowcount == 1:\r\n return self.cursor.fetchone()\r\n else:\r\n return None\r\n except:\r\n return None","def get_user_id(self, session, **kwargs):\n return None","def save(self)->None:\n database.cursor.execute(\n \"INSERT INTO users(firstname,lastname,othernames,email,phone,username,password,role) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) RETURNING id\", (\n self.first_name,\n self.last_name,\n self.other_name,\n self.email,\n self.phone_number,\n self.user_name,\n self.password,\n self.is_admin\n ))\n super().save()","def register():\n session.clear()\n\n \"\"\"Register user\"\"\"\n\n if request.method == \"POST\":\n\n # Ensure username was submitted\n if not request.form.get(\"username\"):\n return apology(\"must provide username\", 400)\n\n # Ensure password was submitted\n elif not request.form.get(\"password\"):\n return apology(\"must provide password\", 400)\n\n # Make sure password and confirmation match\n elif request.form.get(\"password\") != request.form.get(\"confirmation\"):\n return apology(\"password does not match\", 400)\n\n\n # add username and pw to the DB\n\n hash = generate_password_hash(request.form.get(\"password\"))\n result = db.execute(\"INSERT INTO users (username, hash) VALUES(:username, :hash)\", username=request.form.get(\"username\"), hash=hash)\n\n if not result:\n return apology(\"username already exists\", 400)\n\n # Log user in\n # Query database for username\n rows = db.execute(\"SELECT * FROM users WHERE username = :username\", username=request.form.get(\"username\"))\n\n\n session[\"user_id\"] = rows[0][\"id\"]\n\n\n # Redirect user to home page\n return redirect(\"/\")\n\n # User reached route via GET (as by clicking a link or via redirect)\n else:\n return render_template(\"register.html\")"],"string":"[\n \"def session(self):\",\n \"def get_or_create_session(db):\",\n \"def save_inscription():\\n user = None\\n f = InscriptionForm()\\n if f.validate_on_submit() and f.uniq_Username() and f.passwd_confirmed():\\n from hashlib import sha256\\n m = sha256()\\n m.update(f.get_mdp().encode())\\n user = Utilisateur(\\n idU = f.get_id(),\\n mdpU = m.hexdigest(),\\n nomU = f.get_name(),\\n prenomU = f.get_surname())\\n db.session.add(user)\\n i = Actions(\\n contenu = \\\"Bienvenue à \\\"+f.get_id(),\\n liste = 1\\n )\\n db.session.add(i)\\n db.session.commit()\\n return redirect(url_for('login'))\\n return render_template(\\n\\t\\t\\\"inscription.html\\\",\\n\\t\\tform = f,\\n title = \\\"Inscription\\\")\",\n \"def login():\\n # try:\\n # if g.user != None:\\n # user_ID = \\\"Logged \\\" + str(g.user['_id'])\\n # print \\\"insideNone\\\",user_ID\\n # except ValueError:\\n # print \\\"try again\\\"\\n # if g.user:\\n # print \\\"insideLog\\\"\\n # return redirect(url_for('timeline'))\\n user_ID = \\\"\\\"\\n if g.user != None:\\n user_ID = \\\"Logged \\\" + str(g.user['_id'])\\n print \\\"insideNone\\\", user_ID\\n\\n ############### REDIS SESSION CODE #####################\\n if redis_obj.get(user_ID):\\n pKey = pickle.loads(redis_obj.get(user_ID))\\n print \\\"insideLog\\\", user_ID\\n return redirect(url_for('timeline'), pKey)\\n error = None\\n if request.method == 'POST':\\n user = userdetails_query()\\n if user is None:\\n error = 'Invalid username'\\n # abort(status.HTTP_401_UNAUTHORIZED)\\n elif not check_password_hash(user['pw_hash'],\\n request.form['password']):\\n error = 'Invalid password'\\n # abort(status.HTTP_401_UNAUTHORIZED)\\n else:\\n flash('You were logged in')\\n session['user_id'] = user['_id']\\n logUser = pickle.dumps(list(user))\\n # print \\\"logUser\\\", logUser\\n redis_obj.setex(\\\"Logged \\\" + str(session['user_id']), logUser, 60)\\n return redirect(url_for('timeline'))\\n return render_template('login.html', error=error)\",\n \"def load_token(token):\\n\\n #The Token itself was generated by User.get_auth_token. So it is up to \\n #us to known the format of the token data itself. \\n\\n #The Token was encrypted using itsdangerous.URLSafeTimedSerializer which \\n #allows us to have a max_age on the token itself. When the cookie is stored\\n #on the users computer it also has a exipry date, but could be changed by\\n #the user, so this feature allows us to enforce the exipry date of the token\\n #server side and not rely on the users cookie to exipre. \\n #max_age = app.config[\\\"REMEMBER_COOKIE_DURATION\\\"].total_seconds()\\n\\n #Decrypt the Security Token, data = [username, hashpass]\\n data = login_serializer.loads(token)\\n\\n #Find the User\\n user = User.query.filter_by(email = data[0]).first()\\n\\n #Check Password and return user or None\\n if user and data[1] == user.pwd:\\n \\t#On update la derniere connection du user\\n \\tuser.update_last_connection()\\n return user\\n return None\\n\\n\\n\\n\\n\\n\\n\\n #######################################################\\n ################# REQUETES ############################\\n #######################################################\",\n \"def login(self):\",\n \"def login():\",\n \"def login():\",\n \"def test_create_session(self):\\n finder = FinderInsidePro(self.test_key)\\n session_id = finder.create_session(2811)\\n assert isinstance(session_id, str)\\n assert session_id == finder.session_id\\n assert len(session_id)\",\n \"def save_token(self):\\n db.session.add(self)\\n db.session.commit()\",\n \"def UserToken(self) -> object:\",\n \"def logininfo():\\n\\n email = request.form.get(\\\"email\\\")\\n password = request.form.get(\\\"password\\\")\\n\\n user = User.query.filter_by(email=email).first()\\n # import pdb; pdb.set_trace()\\n if not user:\\n return redirect(\\\"/register\\\")\\n\\n if user.password != password:\\n flash('Invalid password, please try again!')\\n return redirect(\\\"/\\\")\\n\\n session[\\\"user_id\\\"] = user.user_id\\n\\n return redirect(\\\"/feedpage\\\")\",\n \"def clave_unica_login(request):\\n clave_unica = ClaveUnicaSettings()\\n state = clave_unica.generate_token()\\n request.session['state'] = state\\n clave_unica_url = clave_unica.get_csrf_redirect_url(state)\\n return redirect(clave_unica_url)\",\n \"def get_posession(self, s):\\r\\n return 1\",\n \"def get_session(id):\\n session = Session.query.get(id)\\n result = session_schema.dump(session).data\\n return jsonify({'status': 'success', 'message': None, 'data': result}), 200\",\n \"def authentUser(login, password, pcID):\\n\\n serverDatetime = datetime.now()\\n\\n serverDatetime = str(serverDatetime)\\n\\n db = DataBaseConnection()\\n\\n if db:\\n query = f\\\"SELECT * FROM {Account.tablename} WHERE {Account.loginCol} = ?\\\"\\n\\n try:\\n db.cursor.execute(query, login)\\n except Exception as error:\\n return {\\\"flag\\\": \\\"queryError\\\", \\\"message\\\": f\\\"{error} | {query}\\\"}\\n else:\\n row = db.cursor.fetchone()\\n\\n if row:\\n accountObj = Account(*row)\\n\\n if password == accountObj.password:\\n if not accountObj.firstPCID:\\n status, message = accountObj.modifyColumn(column=accountObj.firstPCIDCol, newValue=pcID)\\n\\n return {\\\"flag\\\": \\\"activated\\\", \\\"message\\\": f\\\"activated first succefuul | {status} | {message} | {row}\\\"} if status else {\\\"flag\\\": \\\"updateError\\\", \\\"message\\\": \\\"error to update first user infos\\\"}\\n\\n elif not accountObj.secondPCID:\\n status, message = accountObj.modifyColumn(column=accountObj.secondPCIDCol, newValue=pcID)\\n\\n return {\\\"flag\\\": \\\"activated\\\", \\\"message\\\": f\\\"activated second succefuul | {status} | {message} | {row}\\\"} if status else {\\\"flag\\\": \\\"updateError\\\", \\\"message\\\": \\\"error to update second user infos\\\"}\\n\\n\\n else: # all keys are used\\n return {\\\"flag\\\": \\\"allKeysUsed\\\", \\\"Userinfos\\\": [accountObj.firstPCID, accountObj.secondPCID]}\\n \\n else: # invalide password\\n return {\\\"flag\\\": f\\\"invalidPassword\\\", \\\"message\\\": \\\" {query} | {row}\\\"}\\n \\n else:\\n return {\\\"flag\\\": f\\\"invalidLogin\\\", \\\"message\\\": f\\\"{query}\\\"}\",\n \"def test_set_session():\",\n \"def identificacion(payload):\\n if (payload['identity']):\\n # el identity me devuelve el id del usuario que se ha logeado entonces gracias a ello yo puedo almacenar otros campos\\n resultado = UsuarioModel.query.filter_by(id=payload['identity']).first()\\n if resultado:\\n return (resultado.id, resultado.correo)\\n else:\\n return None\\n else:\\n return None\",\n \"def api_check_cod_verificacion(request):\\n cod_verificacion = request.matchdict['cod_verificacion']\\n user = RepositorioUsario.check_cod_verificacion(request, cod_verificacion)\\n if user is not None: \\n # cambiar estado del atributo user.activo\\n user.set_activo(True)\\n user.remove_cod_verificacion()\\n # Logueo de usuario\\n request.session['user'] = user\\n headers = remember(request, user.id)\\n response = Response(json_body=user.__json__(request))\\n response.headers.extend(headers)\\n return response\\n else:\\n return Response(status=400, json_body={'titulo': 'Usuario no encontrado',\\n 'msg': 'Revisa el código de verificación del enlace'})\",\n \"def refresh_token(self, subid):\\n from expfactory.database.models import Participant\\n\\n p = Participant.query.filter(Participant.id == subid).first()\\n if p is not None:\\n p.token = str(uuid.uuid4())\\n self.session.commit()\\n return p\",\n \"def nuevopermiso(): \\n if not current_user.is_authenticated():\\n flash('Debe loguearse primeramente!!!!', 'loggin')\\n return render_template('index.html')\\n \\n permission = UserRol('ADMINISTRADOR')\\n if permission.can():\\n form = PermisoFormulario(request.form)\\n form.id_recurso.choices= [(r.id, r.nombre) for r in db_session.query(Recurso).order_by(Recurso.nombre)]\\n if request.method == 'POST' and form.validate():\\n try:\\n permiso = Permiso(form.codigo.data, form.descripcion.data, form.id_recurso.data)\\n db_session.add(permiso)\\n db_session.commit()\\n flash('El permiso ha sido registrado con exito','info')\\n return redirect('/permiso/administrarpermiso')\\n except DatabaseError, e:\\n if e.args[0].find('duplicate key value violates unique') != -1:\\n flash('Clave unica violada por favor ingrese otra combinacion de permiso con recurso unica' , 'error')\\n else:\\n flash('Error en la Base de Datos' + e.args[0], 'error')\\n return render_template('permiso/nuevopermiso.html', form=form)\\n return render_template('permiso/nuevopermiso.html', form=form)\\n else:\\n flash('Sin permisos para agregar permisos', 'permiso')\\n return render_template('index.html')\",\n \"def test_session_promotion(self):\\r\\n cursor = self.db.cursor()\\r\\n cursor.execute(\\\"INSERT INTO session VALUES ('123456', 0, 0)\\\")\\r\\n incookie = Cookie()\\r\\n incookie['trac_session'] = '123456'\\r\\n outcookie = Cookie()\\r\\n req = Mock(authname='john', base_path='/', incookie=incookie,\\r\\n outcookie=outcookie)\\r\\n session = Session(self.env, req)\\r\\n self.assertEqual('john', session.sid)\\r\\n session.save()\\r\\n\\r\\n cursor.execute(\\\"SELECT sid,authenticated FROM session\\\")\\r\\n self.assertEqual(('john', 1), cursor.fetchone())\\r\\n self.assertEqual(None, cursor.fetchone())\",\n \"def get_session(_id):\\n token = get_token()\\n headers = {'Content-Type': 'application/json', 'Authorization': f'Bearer {token}'}\\n endpoint = f\\\"https://api.signicat.io/identification/v2/sessions/{_id}\\\" \\n \\n response = requests.get(endpoint, headers=headers).json()\\n identification = response['identity']\\n print(identification)\\n return response['identity']\",\n \"def auth_token(self):\",\n \"def test_new_session_promotion(self):\\r\\n cursor = self.db.cursor()\\r\\n incookie = Cookie()\\r\\n incookie['trac_session'] = '123456'\\r\\n outcookie = Cookie()\\r\\n req = Mock(authname='john', base_path='/', incookie=incookie,\\r\\n outcookie=outcookie)\\r\\n session = Session(self.env, req)\\r\\n self.assertEqual('john', session.sid)\\r\\n session.save()\\r\\n\\r\\n cursor.execute(\\\"SELECT sid,authenticated FROM session\\\")\\r\\n self.assertEqual(('john', 1), cursor.fetchone())\\r\\n self.assertEqual(None, cursor.fetchone())\",\n \"def token(db):\\n user = User.find_by_identity('admin@localhost.com')\\n return user.serialize_token()\",\n \"def get_token(self, session, **kwargs):\\n return None\",\n \"def token(db):\\n token = TokenFactory()\\n db.session.commit()\\n return token\",\n \"def login():\\n pass\",\n \"def check_google_token():\\n #get token from login page and google's token rigamorole\\n gtoken = request.form.get(\\\"idtoken\\\")\\n #validate token\\n g_profile = apiapijoyjoy.validate_google_token(gtoken)\\n #collect user info from google\\n name = g_profile['given_name']\\n lname = g_profile['family_name']\\n email = g_profile['email']\\n # start a session\\n session[\\\"user_id\\\"] = email\\n user = User.query.filter_by(email=email).first()\\n #create flags for Flask to return to google's scripts and take frontend action accordingly\\n if user:\\n return \\\"FLASK SEES USER\\\"\\n else:\\n #create new user in SQLAlchemy using info above from Google. BUT WAIT WHAT?! CODE REVIEW PLS!\\n new_user = User(email=email, name=name, lname=lname)\\n db.session.add(new_user)\\n db.session.commit()\\n return \\\"FLASK SEES NO USER\\\"\",\n \"def session(rq):\\n rq.session['username']='wxy'\\n return HttpResponse(__file__ + '::session and first user is my daugter:' + rq.session['username'])\",\n \"def test_valid_session_key(self, db_mock):\\n repo = Repository()\\n db_instance = db_mock.return_value\\n\\n db_instance.get_session.return_value = (\\\"1234\\\", 1, 4321)\\n self.assertTrue(repo.valid_session_key(\\\"1234\\\"))\\n\\n db_instance.get_session.return_value = None\\n self.assertFalse(repo.valid_session_key(\\\"1234\\\"))\",\n \"def sessio_changed(session, event):\\n # si passem estat a convocat cal enviar mail de convocatoria...\\n try:\\n # old = _GW(event.status['review_state'])\\n new = _GW(event.transition.new_state_id)\\n # message = (old) + ' →2 ' + (new)\\n addEntryLog(session, None, _(u'Changed workflow state'), new) # add log\\n except:\\n addEntryLog(session, None, _(u'New session created'), session.Title()) # add log\\n\\n if event.transition is None:\\n # Quan crees element també executa aquesta acció, i ID no existeix\\n # Fem el bypass\\n pass\\n else:\\n \\\"\\\"\\\" Previ a l'enviament del missatge et troves en un estat intermig,\\n creat només per això, que es diu Convocant (no es veu enlloc)\\n \\\"\\\"\\\"\\n if event.transition.id == 'convocant':\\n raise Redirect(session.absolute_url() + '/mail_convocar')\\n\\n if event.transition.id == 'tancar':\\n member = api.user.get(username='admin')\\n user = member.getUser()\\n session.changeOwnership(user, recursive=False)\\n owners = session.users_with_local_role(\\\"Owner\\\")\\n session.manage_delLocalRoles(owners)\\n if user.getId() == 'admin':\\n session.manage_setLocalRoles(user.getId(), [\\\"Owner\\\"])\\n else:\\n session.manage_setLocalRoles(user._id, [\\\"Owner\\\"])\\n session.reindexObjectSecurity()\\n transaction.commit()\",\n \"def temp_getToken():\\n # First check if query is okay or not\\n data = json.loads(request.data)\\n username = data.get(\\\"username\\\",None)\\n password = data.get(\\\"password\\\",None)\\n \\n if request.headers.get('X-VITASK-API') != \\\"2020_Mar_25\\\" or username is None or password is None:\\n return jsonify({\\n \\\"error\\\" : \\\"Incorrect API Request\\\",\\n \\\"code\\\" : \\\"400\\\" # Bad request\\n })\\n \\n # Now began actual work\\n username = username.upper()\\n \\n # This API is only to get user token and get personal details. For syncing details, there will be a seperate API\\n # This assumes that token is None just like previous authenticate\\n valid = True\\n try:\\n sess, valid = generate_session(username, password)\\n except Exception as e:\\n return jsonify({\\n \\\"error\\\" : \\\"Something broke\\\",\\n \\\"code\\\" : \\\"500\\\"\\n })\\n if not valid:\\n # Password incorrect\\n return jsonify({\\n \\\"error\\\" : \\\"Incorrect Password\\\"\\n })\\n ref = db.reference('vitask')\\n try:\\n profile = {}\\n profile, check_profile = get_student_profile(sess, username)\\n session['id'] = profile['appNo']\\n session['name'] = profile['name']\\n session['reg'] = profile['regNo']\\n session['loggedin'] = 1\\n if(check_profile == False):\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching profile.Please try again.\\\"})\\n finally:\\n name, school, branch, program, regno, appno, email, proctoremail, proctorname, api = ProfileFunc()\\n # Timetable,Attendance,Acadhistory and Marks fetching in parallel\\n try:\\n runInParallel(parallel_timetable(sess, username, session['id']), parallel_attendance(sess, username, session['id']), parallel_acadhistory(sess, username, session['id']), parallel_marks(sess, username, session['id'])) \\n finally:\\n return jsonify({'Name': name,'School': school,'Branch': branch,'Program': program,'RegNo': regno,'AppNo': appno,'Email': email,'ProctorEmail': proctoremail,'ProctorName': proctorname,'APItoken': api})\",\n \"def save(self):\\n\\n self.curr.execute(\\n ''' INSERT INTO revoked_tokens(jti)\\\\\\n VALUES('{}')\\\\\\n RETURNING jti''' \\\\\\n .format(self.jti))\\n revoked_token = self.curr.fetchone()\\n self.conn.commit()\\n self.curr.close()\\n return json.dumps(revoked_token, default=str)\",\n \"def user():\",\n \"def login_success(user_id):\\n session['user'] = {}\\n u_obj = User.query.filter(User.user_id == user_id).first()\\n saved_events = UserEvent.query.filter_by(user_id = user_id).all()\\n user = session['user']\\n user['user_id'] = user_id\\n user['name'] = u_obj.fname\\n user['saved'] = [event.eventbrite_id for event in saved_events]\",\n \"def get_stulogin():\\n\\n rows = db.engine.execute(f\\\"SELECT * FROM stulogin WHERE STULOGINID = {g.user.STULOGINID} \\\")\\n res = []\\n for row in rows:\\n res.append(dict(row))\\n return jsonify(res)\",\n \"def getCruSession(user: str, password: str, url: str) -> Session:\\n \\n payload = {\\n 'Username': user,\\n 'Password': password,\\n 'ufprt': 'CAF8477BDE81160B023359032A131EBA8ED2EFCCA369B1D4406ABA090A186F53D289629E6B2901EADF92F7200C4504C4EC8DA6A8AE05FD4C6298C6E3A5B090CF7AFEEC6E47030ACB04698860352BD8EA3914830C3D6099400102E9B87AD1389C568A810357BDE2D5BF115952F6B1B1D8C4E8783B',\\n 'RememberMe': 'false'\\n }\\n \\n session = HTMLSession()\\n \\n res = session.post(\\\"https://cruonline.crugroup.com/login\\\", data=payload)\\n assert res.status_code == 200\\n \\n # POST a different ufprt value so that if site detects that another user has logged on,\\n # we force a log off\\n logoff_payload = {\\n 'ufprt': '7674E654A97C61E8335D82E3E72CB21E3B8BC67B82C4A2C28B5359C474B3E5AFAAD640D57AE7CC8A40515A37EF5740681F41C249B2F85397D86C2560F38BD27A43B4401FFB761DFEB88F3E34BAC675CA9AEADA14AD076EB02A85EAADD50D4678BE783B30BF67E11B6394BEE63C522175658A6BAD34B4EEA8982EC0C59790667556CC29D0'\\n }\\n res_final = session.post(\\\"https://cruonline.crugroup.com/login\\\", data=logoff_payload)\\n assert res_final.status_code == 200\\n \\n return res_final.session\",\n \"def __generate_session_token(self):\\n\\n return get_random_string(length=32)\",\n \"def login(request, session):\\n\\n if 'tid' in session: # we assume that if there is a tid in the session dict then the user is authenticated\\n return {\\\"success\\\": 1, \\\"message\\\": \\\"你已经登录了.\\\"}\\n teamname = request.form.get('teamname', None) # get the teamname and password from the POSTed form\\n password = request.form.get('password', None)\\n if teamname is None or teamname == '':\\n return {'success': 0, 'message': \\\"用户名不能为空.\\\"}\\n if password is None or password == '': # No password submitted\\n return {\\\"success\\\": 0, \\\"message\\\": \\\"密码不能为空.\\\"}\\n if len(teamname) > 250:\\n return {\\\"success\\\": 0, \\\"message\\\": \\\"STAHP!\\\"}\\n teamname = teamname.encode('utf8').strip()\\n password = password.encode('utf8')\\n teamCurr = db.teams.find({'teamname': teamname})\\n if teamCurr.count() == 0: # No results returned from mongo when searching for the user\\n return {\\\"success\\\": 0, \\\"message\\\": \\\"未找到用户名'%s'.\\\" % teamname}\\n if teamCurr.count() > 1:\\n return {\\\"success\\\": 0, \\\"message\\\": \\\"查找用户信息失败. 请联系管理员.\\\"}\\n checkTeam = teamCurr[0]\\n if checkTeam['email_verified'] == False:\\n return {\\\"success\\\": 0, \\\"message\\\": \\\"请先访问邮箱查收验证邮件.\\\"}\\n pwhash = checkTeam['pwhash'] # The pw hash from the db\\n if bcrypt.hashpw(password, pwhash) == pwhash:\\n if checkTeam.get('debugaccount', None):\\n session['debugaccount'] = True\\n if debug_disable_general_login:\\n if 'debugaccount' not in checkTeam or not checkTeam['debugaccount']:\\n return {'success': 2, \\\"message\\\": \\\"Correct credentials! But the game has not started yet...\\\"}\\n if checkTeam['tid'] is not None:\\n session['tid'] = checkTeam['tid']\\n session['teamname'] = checkTeam['teamname']\\n session['is_zju_user'] = utilities.is_zju_email(checkTeam['email'])\\n else: # SET THE 'tid' TO str('_id') FOR MIGRATION PURPOSES AND ADD THE 'tid' TO THE DOCUMENT\\n session['tid'] = checkTeam['_id']\\n session['teamname'] = checkTeam['teamname']\\n session['is_zju_user'] = utilities.is_zju_email(checkTeam['email'])\\n db.teams.update({'_id': checkTeam['_id']}, {'tid': checkTeam['_id']})\\n return {\\\"success\\\": 1, \\\"message\\\": \\\"用户'%s'登录成功.\\\" % teamname,\\n 'teamname': session['teamname'], 'is_zju_user': session['is_zju_user']}\\n return {\\\"success\\\": 0, \\\"message\\\": \\\"密码错误.\\\"}\",\n \"def login(user_name,password,cur):\\n check=False\\n id=None\\n \\n psql=(\\n f\\\"\\\"\\\"select id,password from users where user_name='{user_name}'\\\"\\\"\\\")\\n cur.execute(psql)\\n record=cur.fetchone()\\n \\n\\n if not record:\\n flash('nom utilisateur non valide!')\\n \\n else:\\n id=record[0]\\n password_record=record[1].tobytes() \\n\\n if bcrypt.checkpw(password.encode('utf-8'),password_record):\\n check=True\\n flash(\\\"Connexion Réussi!\\\")\\n else:\\n flash(\\\"Svp verifiez vos coordonnees et reessayer !\\\")\\n\\n return [check,id]\",\n \"def getSession():\\n return call(\\\"getSession\\\")\",\n \"def login_user():\\n pass\",\n \"def login(request):\\n\\n print('login')\\n if request.method == 'POST':\\n md5_pwd = ''\\n admin = False\\n\\n username = request.POST.get('username', False)\\n mode1 = 'Human'\\n mode = NameSpace.objects.get(ns_id=mode1)\\n password = request.POST.get('password', False)\\n if username:\\n username = username.replace(\\\"\\\\\\\"\\\", \\\"\\\").replace(\\\"'\\\", \\\"\\\")\\n if password:\\n password = password.replace(\\\"\\\\\\\"\\\", \\\"\\\").replace(\\\"'\\\", \\\"\\\")\\n md5_pwd = hashlib.md5(password.encode()).hexdigest()\\n if (username != False and password != False):\\n user = User.objects.filter(username = username,ns_id=mode, password = md5_pwd)\\n\\n\\n if user.exists():\\n # print('LOGGATO')\\n mode1 = 'Human'\\n mode = NameSpace.objects.get(ns_id=mode1)\\n user = User.objects.get(username=username, password=md5_pwd,ns_id=mode)\\n print(\\\"username: \\\" + username)\\n request.session['username'] = username\\n request.session['mode'] = mode1\\n admin = User.objects.filter(profile='Admin')\\n if admin.exists():\\n admin = admin.first()\\n admin_name = admin.username\\n request.session['team_member'] = admin_name\\n else:\\n request.session['team_member'] = 'Test'\\n\\n request.session['profile'] = user.profile\\n return redirect('MedTAG_sket_dock_App:index')\\n #return redirect('MedTAG_sket_dock_App:select_options')\\n\\n profile_list = User.objects.values_list('profile', flat=True).distinct()\\n if 'Admin' in profile_list:\\n admin = True\\n context = {'errorMessage': \\\"Your username and password didn't match.\\\",\\\"admin\\\":admin}\\n return render(request, 'MedTAG_sket_dock_App/login.html', context)\\n\\n else:\\n username = request.session.get('username', False)\\n admin = False\\n profile_list = User.objects.values_list('profile', flat=True).distinct()\\n if 'Admin' in profile_list:\\n admin = True\\n context = {'admin': admin}\\n\\n if username:\\n return redirect('MedTAG_sket_dock_App:index')\\n\\n return render(request, 'MedTAG_sket_dock_App/login.html',context)\",\n \"def session(get_session):\\n return get_session()\",\n \"def login_form():\\n\\n # retrieving email and password from user\\n email = request.form.get(\\\"email\\\")\\n form_password = request.form.get(\\\"password\\\")\\n\\n if not email or not form_password:\\n flash(\\\"Please resubmit your information correctly.\\\")\\n return redirect(\\\"/\\\")\\n\\n # hash the password provided\\n hash_object = hashlib.md5(form_password.encode())\\n\\n # querying by the password provided by the user\\n user = User.query.filter_by(email=email).first()\\n password = user.password\\n\\n # if the hash password matches the password in the database then\\n # log user in and create a session\\n if hash_object.hexdigest() == password:\\n\\n # created a session to store the user id\\n session[\\\"user_id\\\"] = user.user_id\\n return redirect(f\\\"/user/{user.user_id}\\\")\\n\\n else:\\n flash(\\\"Sorry, wrong password!\\\")\\n return redirect(\\\"/\\\")\",\n \"def index():\\n \\n nombre_rol='SIN ROL' #ingresa sin rol\\n if auth.user_id: #variable que contiene el id del usuario logueado\\n reg_id_grupo_del_logueado=db(auth.user.id==db.auth_membership.user_id).select(db.auth_membership.group_id)\\n id_grupo_del_logueado=reg_id_grupo_del_logueado[0].group_id #esta variable contiene el id del grupo, es decir solo el número (limpiamos la variable anterior)\\n reg_nombre_rol=db(db.auth_group.id==id_grupo_del_logueado).select(db.auth_group.role)\\n nombre_rol=reg_nombre_rol[0].role #limpiamos variable anterior para que solo busque el rol (la palabra)\\n # se asigna un rol\\n \\n if nombre_rol=='Administrador':\\n redirect(URL('principal_administrador'))\\n elif nombre_rol=='vendedor':\\n redirect(URL('principal_vendedor'))\\n else:\\n redirect(URL('principal_cliente'))\\n\\n response.flash = T(\\\"For sale\\\") \\n return dict(message=T('Bienvenido al Sistema de ventas online'))\",\n \"def user_return():\\n\\n #take csrf-token from cookies\\n token = request.cookies.get('token')\\n #decoding token\\n uuid = jwt.decode(token, app.config['SECRET_KEY'], algorithms=[\\\"HS256\\\"])['user_id']\\n #get current user\\n user = User.query.filter_by(uuid=uuid).first()\\n return user\",\n \"def get_token(request):\\n try:\\n ft_session = request.session['ft_token']\\n token = OAuthAccessToken.objects.get(session_key=ft_session)\\n # invalidate any token > 24 hours old\\n now = datetime.now()\\n diff = now - token.created\\n if diff.days:\\n token.delete()\\n return False\\n # TODO check ip address matches\\n #oauthorize\\n return token\\n except KeyError:\\n print 'no session token..'\\n except OAuthAccessToken.DoesNotExist:\\n print 'no access token ...'\\n return False\",\n \"def login_core(self, usuario_model) -> bool:\\n usuario_json = eval(json.dumps(usuario_model.__dict__))\\n result = self.database.select_db(name_object=\\\"Usuario\\\", filter_data=usuario_json)\\n if isinstance(result, object) and result is not None:\\n Constant.USUARIO = self.encrypt.decrypt(eval(result[\\\"usuario\\\"]))\\n return True\\n return False\",\n \"def login(request):\\n msg=\\\"\\\"\\n if(request.POST):\\n email=request.POST.get(\\\"txtEmail\\\")\\n pwd=request.POST.get(\\\"txtPassword\\\")\\n s=\\\"select count(*) from tbllogin where username='\\\"+email+\\\"'\\\"\\n c.execute(s)\\n i=c.fetchone()\\n if(i[0]>0):\\n s=\\\"select * from tbllogin where username='\\\"+email+\\\"'\\\"\\n c.execute(s)\\n i=c.fetchone()\\n if(i[1]==pwd):\\n request.session['email'] = email\\n if(i[3]==\\\"1\\\"):\\n if(i[2]==\\\"admin\\\"):\\n return HttpResponseRedirect(\\\"/adminhome\\\")\\n elif(i[2]==\\\"eventmanager\\\"):\\n return HttpResponseRedirect(\\\"/emhome\\\")\\n elif(i[2]==\\\"alumni\\\"):\\n return HttpResponseRedirect(\\\"/alumnihome\\\")\\n elif(i[3]==\\\"inactive\\\"):\\n msg=\\\"Your registration is incomplete. Please register\\\"\\n else:\\n msg=\\\"You are not authenticated to login\\\"\\n else:\\n msg=\\\"Incorrect password\\\"\\n else:\\n msg=\\\"User doesnt exist\\\"\\n return render(request,\\\"login.html\\\",{\\\"msg\\\":msg})\",\n \"def handle_session_mgt(request):\\n db = cloud_db.DbManager()\\n try:\\n if request.method == 'POST':\\n ### login(signin) ###\\n if len(request.body) == 0:\\n raise Exception(MSG_NODATA)\\n data = json.loads(request.body)\\n\\n if not data.get('user_id') or not data.get('password'):\\n raise Exception(MSG_INVALID_PARAMS)\\n if request.session.get('user'):\\n raise Exception(MSG_ALREADY_LOGGEDIN)\\n user_id = data['user_id']\\n password = data['password']\\n\\n authenticated = db.check_authentication(user_id)\\n if authenticated is None:\\n raise Exception(MSG_UNKNOWN_ERROR)\\n elif authenticated is False:\\n return JsonResponse(constants.CODE_NEED_AUTH)\\n\\n user = {}\\n intpr_session = {}\\n user_type = db.retrieve_user_type(user_id, password)\\n if user_type is None:\\n raise Exception(MSG_INVALID_IDPW)\\n elif user_type == 'patient':\\n user = db.retrieve_patient(user_id, password)\\n intpr_session['sessions'] = db.retrieve_patient_session(data['user_id'])\\n elif user_type == 'physician':\\n user = db.retrieve_physician(user_id, password)\\n intpr_session['sessions'] = db.retrieve_physician_session(data['user_id'])\\n else:\\n raise Exception(MSG_INVALID_IDPW)\\n if not user.get('user_id'):\\n raise Exception(MSG_INVALID_IDPW)\\n\\n # intpr session check\\n new_flag = 0\\n for session in intpr_session['sessions']:\\n if session['status'] == 0:\\n new_flag = 1\\n intpr_session['new'] = new_flag\\n\\n # set sessions\\n request.session['user'] = user\\n # pprint(user)\\n request.session['intpr_session'] = intpr_session\\n # request.session['medical_image'] = {}\\n # request.session.create('medical_image')\\n logger.info('user %s logged in.' % user['user_id'])\\n\\n return JsonResponse(constants.CODE_SUCCESS)\\n\\n elif request.method == 'DELETE':\\n ### Logout ###\\n if request.session.get('user'):\\n # del request.session['user']\\n request.session.clear()\\n return JsonResponse(constants.CODE_SUCCESS)\\n else:\\n raise Exception(MSG_NO_USER_LOGGEDIN)\\n\\n except Exception as e:\\n logger.exception(e)\\n return JsonResponse(dict(constants.CODE_FAILURE, **{'msg': str(e)}))\\n\\n return JsonResponse(dict(constants.CODE_FAILURE, **{'msg': MSG_UNKNOWN_ERROR}))\",\n \"def save_session(self, session):\\n db = self.open()\\n db[session.id] = session\",\n \"def authorize():\\n\\n google = oauth.create_client('google') # create the google oauth client\\n # Access token from google (needed to get user info)\\n token = google.authorize_access_token()\\n # userinfo contains stuff u specificed in the scrope\\n resp = google.get('userinfo')\\n user_info = resp.json()\\n email = user_info['email']\\n first_name = user_info['given_name'].capitalize()\\n last_name = user_info['family_name'].capitalize()\\n image_url = User.image_url.default.arg\\n if user_info['picture'] != '' and user_info['picture']:\\n image_url = user_info['picture']\\n user = oauth.google.userinfo() # uses openid endpoint to fetch user info\\n # Here you use the profile/user data that you got and query your database find/register the user\\n # and set ur own data in the session not the profile from google\\n\\n # compare with database;\\n user = User.query.filter_by(email=email).first()\\n print(user)\\n\\n if not user:\\n user = User.signup(email=email, password='password1', username='temporary',\\n first_name=first_name, last_name=last_name, image_url=image_url, cover_url=User.cover_url.default.arg)\\n db.session.commit()\\n do_login(user)\\n return redirect(f'/user/{user.id}/force-reset')\\n else:\\n do_login(user)\\n return redirect('/')\",\n \"def generate_session(db, useremail):\\n user = db.cursor().execute('SELECT email FROM users WHERE email IS ?', [useremail]).fetchone()\\n if user:\\n existing_session = db.cursor().execute('SELECT sessionid FROM sessions WHERE useremail IS ?',\\n [user[0]]).fetchone()\\n if existing_session:\\n cookie = SimpleCookie()\\n cookie[COOKIE_NAME] = existing_session[0]\\n return cookie\\n else:\\n key = str(uuid.uuid4())\\n db.cursor().execute('INSERT INTO sessions VALUES (?, ?)', [key, useremail])\\n db.commit()\\n cookie = SimpleCookie()\\n cookie[COOKIE_NAME] = key\\n return cookie\\n return None\",\n \"def get_id():\\n token = get_token()\\n # Endpoint url\\n endpoint = \\\"https://api.idfy.io/identification/v2/sessions\\\"\\n # Setting headers with the authorization bearer\\n headers = {'Content-Type': 'application/json', 'Authorization': f'Bearer {token}'}\\n data = {\\n \\\"languages\\\": \\\"en\\\",\\n \\\"flow\\\": \\\"redirect\\\",\\n \\\"allowedProviders\\\": [\\n \\\"no_bankid_netcentric\\\",\\n \\\"no_bankid_mobile\\\"\\n ],\\n \\\"include\\\": [\\n \\\"name\\\",\\n \\\"date_of_birth\\\",\\n \\\"phone_number\\\",\\n \\\"nin\\\",\\n \\\"email\\\"\\n ],\\n \\\"redirectSettings\\\": {\\n \\\"successUrl\\\": \\\"https://example.com/success\\\",\\n \\\"abortUrl\\\": \\\"https://example.com/abort\\\",\\n \\\"errorUrl\\\": \\\"https://example.com/error\\\"\\n }\\n }\\n # Converting the data into a json string and sending a post request \\n response = requests.post(endpoint, data=json.dumps(data), headers=headers).json()\\n # Opening the browser and to authenticate the user\\n webbrowser.open(response['url'])\\n # returning the session id\\n return response['id']\",\n \"def user(self):\",\n \"def get_session_id(self):\\n raise NotImplementedError()\",\n \"def log_in():\\n\\n user = request.form.get(\\\"username\\\")\\n #password = request.form.get(\\\"password\\\")\\n\\n try:\\n\\n current_user = User.query.filter_by(email=user).one()\\n flash('You were successfully logged in')\\n session[\\\"user_id\\\"] = current_user.user_id\\n\\n return render_template('homepage.html')\\n\\n except sqlalchemy.orm.exc.NoResultFound:\\n\\n return render_template('/registration_form.html')\",\n \"def get_current_session(self) -> SessionType:\",\n \"def check(user,passwd):\\n myvars=dict(id=user)\\n try:\\n table=model.db.select('manager',myvars,where=web.db.sqlwhere(myvars))\\n real_passwd=table[0]['passwd']\\n if real_passwd==passwd:\\n session.login=1\\n session.id=user\\n else:\\n pass\\n except:\\n pass\",\n \"def getToken():\\n # First check if query is okay or not\\n data = json.loads(request.data)\\n username = data.get(\\\"username\\\",None)\\n password = data.get(\\\"password\\\",None)\\n \\n if username is None or password is None:\\n return jsonify({\\n \\\"error\\\" : \\\"Incorrect API Request\\\",\\n \\\"code\\\" : \\\"400\\\" # Bad request\\n })\\n check_header = magiccheck(request.headers.get('X-VITASK-API'))\\n if(check_header == False):\\n return jsonify({\\n \\\"error\\\" : \\\"Invalid Header\\\",\\n \\\"code\\\" : \\\"403\\\" # Unauthorised\\n })\\n # Now began actual work\\n username = username.upper()\\n \\n # This API is only to get user token and get personal details. For syncing details, there will be a seperate API\\n # This assumes that token is None just like previous authenticate\\n valid = True\\n try:\\n sess, valid = generate_session(username, password)\\n except Exception as e:\\n return jsonify({\\n \\\"error\\\" : \\\"Something broke\\\",\\n \\\"code\\\" : \\\"500\\\"\\n })\\n if( valid == False ):\\n # Password incorrect\\n return jsonify({\\n \\\"error\\\" : \\\"Incorrect Password\\\"\\n })\\n ref = db.reference('vitask')\\n try:\\n profile = {}\\n profile, status = get_student_profile(sess, username)\\n if( status == False ):\\n print(\\\"Failed at profile.\\\")\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching profile.Please try again.\\\"})\\n session['id'] = profile['appNo']\\n session['name'] = profile['name']\\n session['reg'] = profile['regNo']\\n session['loggedin'] = 1\\n except Exception as e:\\n print(e)\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching profile.Please try again.\\\"})\\n finally:\\n # Timetable,Attendance,Acadhistory and Marks fetching\\n try:\\n status = parallel_timetable(sess, username, session['id'])\\n if( status == False ):\\n print(\\\"Failed at timetable.\\\")\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching timetable.Please try again.\\\"})\\n except Exception as e:\\n print(e)\\n print(\\\"Exception at timetable.\\\")\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching timetable.Please try again.\\\"})\\n finally:\\n try:\\n status = parallel_attendance(sess, username, session['id'])\\n if( status == False ):\\n print(\\\"Failed at attendance.\\\")\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching attendance.Please try again.\\\"})\\n except Exception as e:\\n print(e)\\n print(\\\"Exception at attendance.\\\")\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching attendance.Please try again.\\\"})\\n finally:\\n try:\\n status = parallel_acadhistory(sess, username, session['id'])\\n if( status == False ):\\n print(\\\"Failed at acadhistory.\\\")\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching academic history.Please try again.\\\"})\\n except Exception as e:\\n print(e)\\n print(\\\"Exception at acadhistory.\\\")\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching academic history.Please try again.\\\"})\\n finally:\\n try:\\n status = parallel_marks(sess, username, session['id'])\\n if( status == False ):\\n print(\\\"Failed at marks.\\\")\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching marks.Please try again.\\\"})\\n except Exception as e:\\n print(e)\\n print(\\\"Exception at marks.\\\")\\n return jsonify({\\\"Error\\\": \\\"Internal Error in fetching marks.Please try again.\\\"})\\n finally:\\n # API Calls logging\\n temp = ref.child(\\\"account\\\").child('account-'+profile['appNo']).child(profile['appNo']).get()\\n count = int(temp['API-Calls']) + 1\\n tut_ref = ref.child(\\\"account\\\")\\n new_ref = tut_ref.child('account-'+profile['appNo'])\\n new_ref.set({\\n profile['appNo']: {\\n 'X-VITASK-API': temp['X-VITASK-API'],\\n 'Name': temp['Name'],\\n 'RegNo': temp['RegNo'],\\n 'Account-Type': temp['Account-Type'],\\n 'API-Calls': count,\\n 'Start-Date': temp['Start-Date'],\\n 'End-Date': temp['End-Date']\\n }\\n })\\n return jsonify({'Name': profile['name'],'School': profile['school'],'Branch': profile['branch'],'Program': profile['program'],'RegNo': profile['regNo'],'AppNo': profile['appNo'],'Email': profile['email'],'ProctorEmail': profile['proctorEmail'],'ProctorName': profile['proctorName'],'APItoken': profile['token']})\",\n \"def next_identity(self) -> UserId:\\n ...\",\n \"def login_confirmation():\\n\\n email = request.form['email']\\n password = request.form['password']\\n\\n user = User.query.filter_by(email=email, password=password).first()\\n\\n if user:\\n session['user_id']=user.user_id\\n # return redirect(\\\"/users/<int:user.user_id>\\\")\\n return redirect(\\\"/users/%s\\\" % user.user_id)\\n else:\\n flash(\\\"Incorrect username or password\\\")\\n return redirect(\\\"/login\\\")\",\n \"def getcsrf(session):\\n session.get(\\\"http://anichart.net\\\")\",\n \"def auth_create_session(self) -> str:\\n self.__logger.debug('Eva.auth_create_session called')\\n return self.__http_client.auth_create_session()\",\n \"def _generate_token(self):\\n return sha1(\\\"%s#%s\\\" % (time(),\\n self.app.cfg['sessions/secret'])).hexdigest()\",\n \"def save_admin():\\n user = users.get_current_user()\\n if user:\\n if users.is_current_user_admin() or is_local_admin():\\n added_admin_mail = request.forms.get('mail')\\n added_admin = users.User(added_admin_mail)\\n if added_admin:\\n #return added_admin.user_id()\\n #output = added_admin.nickname()+ ' ' + added_admin.user_id()\\n #return output\\n new_admin = Admins(parent=admin_base)\\n new_admin.ref_nick = user.nickname()\\n new_admin.admin_nick = added_admin.nickname()\\n new_admin.admin_id = 'no id'#added_admin.user_id()\\n new_admin.put()\\n redirect('/admin')\\n \\n else:\\n #return \\\"Не получилось\\\"\\n output = template('admin', name=g_name, log_in_out = users.create_logout_url('/'), opt = 'Выход', user = user.nickname(), admins = admins, error=\\\"Неверный email\\\")\\n return output\\n else:\\n redirect('/')\\n else:\\n redirect('/')\",\n \"def login(cls, identifient, password, methode=\\\"username\\\"):\\n db = database.db_connection()\\n cursor = db.cursor()\\n\\n if methode == \\\"username\\\":\\n sql_query = \\\"SELECT password FROM user WHERE username=?\\\"\\n elif methode == \\\"email\\\":\\n sql_query = \\\"SELECT password FROM user WHERE email=?\\\"\\n\\n cursor.execute(sql_query, (identifient, ))\\n row = cursor.fetchone()\\n cursor.close()\\n if row == None:\\n raise ValueError(\\\"useranme or email inexistent\\\")\\n else:\\n # I'm gonna change this part to add some security to the password\\n if row[0] == password:\\n print(\\\"authantication confirmed\\\")\\n # charging the user data and if the account is deleted we must change that\\n user_data = User.search(identifient, by=methode, type_retrun=\\\"dict\\\")\\n return User( **user_data, conected=True)\\n else:\\n print(\\\"wait, you're an impostor\\\")\\n return False\",\n \"def admin_login():\\r\\n try:\\r\\n admin_mail =valid.email_validation(input('enter admin mail '))\\r\\n password = input(\\\"Enter you password\\\")\\r\\n encoded_pwd = base64.b64encode(password.encode('ascii'))\\r\\n query = \\\"select user_id from user \\\\\\r\\n where mail_id =%s and password =%s and is_admin_flag = %s;\\\"\\r\\n if cursor.execute(query,(admin_mail, encoded_pwd, '1')):\\r\\n print('admin login')\\r\\n admin_uid = cursor.fetchone()\\r\\n return admin_uid[0]\\r\\n print('invalid credentials')\\r\\n except Exception as exception_e:\\r\\n print('Error',exception_e)\",\n \"def get_ags_token(url,username,password,client,referer,session,token_name):\\n #if token_name not in session:\\n params = {\\n 'username': username,\\n 'password': password,\\n 'client': client,\\n 'referer': referer,\\n 'expiration': 720,\\n 'f': 'json',\\n }\\n response = requests.post(\\n url ,\\n # app.config['ROK_AUTH_URL'],\\n data=params\\n )\\n token = response.json()\\n session[token_name] = token\\n print(\\\"{0} token acquired: {1}\\\".format(token_name, token))\\n return token\\n # else:\\n # print(\\\"Using existing {0} token: {1}\\\".format(token_name, session[token_name]))\\n # return session[token_name]\",\n \"def serialize(self):\\n return {\\n 'user_id' : self.user_id,\\n 'session_id' : self.session_id,\\n }\",\n \"def _create_user_session(url: str, netid: str = 'superuser', new: bool = False, add_to_os: bool = True):\\n\\n # Create requests session\\n session = requests.session()\\n\\n if new:\\n netid = create_user(netid, add_to_os)\\n\\n session.get(url + f'/admin/auth/token/{netid}')\\n r = session.get(url + \\\"/public/auth/whoami\\\")\\n\\n try:\\n assert r.status_code == 200\\n data = r.json()\\n assert data[\\\"success\\\"] is True\\n assert data[\\\"data\\\"] is not None\\n assert data[\\\"error\\\"] is None\\n data = copy.deepcopy(data)\\n admin_for = data['data']['user']['admin_for']\\n for i in admin_for:\\n if i['name'] == 'Intro to OS':\\n session.cookies['course'] = base64.urlsafe_b64encode(json.dumps(i).encode()).decode()\\n except AssertionError as e:\\n print_full_error(e, r)\\n return session, netid\",\n \"def do_user_login(user):\\n conn.register([model.Rule])\\n admindb = conn[current_app.config[\\\"CONFIGDB\\\"]]\\n user.update_last_login()\\n user.save()\\n\\n session['user'] = {\\n 'id': str(user[\\\"_id\\\"]),\\n 'label': user[\\\"label\\\"],\\n 'email' : user[\\\"name\\\"],\\n }\\n session['site_admin'] = False\\n session['last_activity'] = user[\\\"last_login\\\"]\\n # Also add the rules information to the session\\n if not (ObjectId(current_app.config[\\\"DEMO_RULE\\\"]) in user[\\\"rules\\\"]):\\n user[\\\"rules\\\"].append(ObjectId(current_app.config[\\\"DEMO_RULE\\\"]))\\n\\n user.save()\\n\\n # Loop over the rules\\n accesses = { }\\n\\n if user[\\\"type\\\"] == \\\"passwd\\\" and (user[\\\"name\\\"].endswith(\\\"brown.edu\\\") or user[\\\"name\\\"].endswith(\\\"kitware.com\\\")):\\n # Here grant the user with the demo_brown rule\\n # flash(\\\"You used password login, and you get donut ! \\\")\\n # ObjectId(\\\"529d244959a3aee20f8a00ae\\\")\\n brownrule = ObjectId(\\\"529d244959a3aee20f8a00ae\\\")\\n if brownrule in user[\\\"rules\\\"]:\\n # flash(\\\"You already have the rule\\\")\\n pass\\n else:\\n # flash(\\\"Rule must be added\\\")\\n user[\\\"rules\\\"].append(ObjectId(\\\"529d244959a3aee20f8a00ae\\\"))\\n user.save()\\n\\n for arule in user[\\\"rules\\\"]:\\n ruleobj = admindb[\\\"rules\\\"].Rule.find_one({\\\"_id\\\" : arule})\\n if ruleobj == None:\\n flash(\\\"Rule not found !! \\\" + str(arule), \\\"error\\\")\\n continue\\n\\n # Create empty DBAccess for that db\\n if not str(ruleobj[\\\"db\\\"]) in accesses.keys():\\n accesses[str(ruleobj[\\\"db\\\"])] = DBAccess()\\n\\n if 'db_admin' in ruleobj and ruleobj[\\\"db_admin\\\"] == True:\\n accesses[str(ruleobj[\\\"db\\\"])].db_admin = True\\n if 'can_see_all' in ruleobj and ruleobj[\\\"can_see_all\\\"] == True:\\n accesses[str(ruleobj[\\\"db\\\"])].can_see_all = True\\n if 'can_see' in ruleobj:\\n if len(ruleobj[\\\"can_see\\\"]) > 0:\\n accesses[str(ruleobj[\\\"db\\\"])].can_see.append(ruleobj[\\\"can_see\\\"])\\n if 'site_admin' in ruleobj and ruleobj[\\\"site_admin\\\"] == True:\\n session[\\\"site_admin\\\"] = True\\n\\n # Insert that information in the session\\n # In future, session may contain only session it,\\n # and this could get into database\\n\\n# For debugging\\n# for adb in accesses.keys():\\n# flash(adb + \\\": \\\" + str(accesses[adb]), \\\"info\\\")\\n#\\n# flash(\\\"Site admin : \\\" + str(session[\\\"site_admin\\\"]), \\\"info\\\")\\n\\n\\n flash('You are successfully logged in.', 'success')\",\n \"def save_login(mobile):\\n mobile = Mobile(mobile)\\n ktt = KTT(mobile)\\n ktt.gen_device_code()\\n ktt.get_api_start()\\n time.sleep(4)\\n ktt.post_login()\\n time.sleep(4)\\n ktt.get_user_info()\\n user_info = (\\n ktt.user_info[\\\"uid\\\"], ktt.user_info[\\\"name\\\"], ktt.user_info[\\\"mobile\\\"],\\n ktt.user_info[\\\"father\\\"], ktt.user_info[\\\"balance\\\"], ktt.user_info[\\\"coin\\\"],\\n ktt.device_code, ktt.token, ktt.mobile.os, ktt.mobile.brand, ktt.mobile.mac,\\n ktt.mobile.android_id\\n )\\n print(user_info)\\n\\n # save one user info record and one user flag\\n uis.save([user_info])\\n read_flag = [(user_info[0],)]\\n uis.save_flag(read_flag)\",\n \"def getUser():\\n\\n if 'token' in session:\\n return \\\"Authenticated\\\"\\n else:\\n return \\\"Unauthenticated\\\"\",\n \"async def save_session(request, response):\\n try:\\n await request.app.session_interface.save(request, response)\\n except Exception as e:\\n if isinstance(e, Exception):\\n pass\",\n \"def login():\\n entity = user.User(\\n account = request.json['account']\\n , password = request.json['password'])\\n u = user.User.query.filter(user.User.account == entity.account).first()\\n if not u or not u.is_active:\\n abort(404)\\n if entity.password == u.password:\\n if u.token is None:\\n u.generate_token()\\n db.session.merge(u)\\n db.session.commit()\\n return jsonify(u.to_dict())\\n abort(500)\",\n \"def user(func) :\\n def redirectlogin(session, self) :\\n setSessionMessage(session, \\\"Student Login required\\\", True)\\n return self.redirect('/login')\\n\\n def checkauth(*args, **kwargs) : \\n self = args[0]\\n session = getSessionByRequest(self)\\n user = getSessionUser(session)\\n\\n if not user :\\n return redirectlogin(session, self)\\n\\n if user.userType == 'STUDENT' : \\n return func(*args, **kwargs)\\n\\n return redirectlogin(session, self)\\n return checkauth\",\n \"def loginUser(request):\\n if request.method == 'POST':\\n data = request.data\\n userEmail = data['email']\\n password = data['password']\\n try:\\n User = UserInformation.objects.get(email=userEmail)\\n if User.password == password:\\n loginHash = ''.join(random.choice(letters) for i in range(10))\\n User.loginSessionHash = loginHash\\n User.save()\\n return Response({'login': 'verified', 'hash': loginHash})\\n else:\\n return Response({'login': 'not verified'})\\n except UserInformation.DoesNotExist:\\n return Response({'login': 'user undefined'})\\n else:\\n return Response({'error': 'request type not specified'})\",\n \"def test_generate_session_key(self, db_mock):\\n repo = Repository()\\n\\n db_instance = db_mock.return_value\\n\\n db_instance.get_user_info_by_google_id.return_value = (1, {\\\"id\\\": 12345})\\n db_instance.new_session.return_value = \\\"1234abcd\\\"\\n \\n self.assertEquals(repo.generate_session_key({\\\"id\\\": 12345}), \\\"1234abcd\\\")\\n\\n db_instance.new_session.assert_called_once()\\n db_instance.create_user.assert_not_called()\",\n \"def join_session(username, password, application_type=\\\"EDITOR\\\",\\n api_endpoint=(\\\"https://engine.tygron.com/api/event/io/get_my_joinable_sessions/?f=JSON\\\")):\\n try:\\n sessions_data = requests.post(url=api_endpoint, json=[],\\n auth=(username, password))\\n except requests.exceptions.ConnectionError:\\n print(\\\"There appears to be no internet connection.\\\")\\n return None\\n session_id = -1\\n print(sessions_data)\\n sessions = sessions_data.json()\\n for item in sessions:\\n if item[\\\"name\\\"] == \\\"virtual_river_salti\\\":\\n session_id = item[\\\"id\\\"]\\n break\\n print(session_id)\\n if session_id > -1:\\n join_url = (\\\"https://engine.tygron.com/api/event/io/join/?f=JSON\\\")\\n \\\"\\\"\\\"\\n r = requests.post(url=join_url, json=[session_id, application_type,\\n \\\"Virtual River application script\\\"],\\n auth=(username, password))\\n \\\"\\\"\\\"\\n r = requests.post(url=join_url, json=[session_id, application_type,\\n \\\"Virtual River application script\\\"],\\n auth=(username, password))\\n try:\\n pastebin_url = r.json()\\n return pastebin_url[\\\"apiToken\\\"]\\n except UnboundLocalError:\\n print(\\\"LOGIN FAILED: Received no content from Tygron.\\\")\\n return None\\n except json.decoder.JSONDecodeError:\\n print(\\\"LOGIN FAILED: Received faulty response from Tygron.\\\")\\n return None\",\n \"def index():\\n '''cookie_user_id = request.get_cookie('uid', 'none')\\n if (cookie_user_id == 'none') || (!cookie_user_id.isdigit()):\\n response.set_cookie('uid', 'none')\\n return template('index', name=g_name, log_in_out = '/login', opt = 'Войти')\\n else:\\n user = AppUsers.query(AppUsers.local_id==cookie_user_id).fetch()\\n if user:\\n if user[0].login_type == 1 && user[0].google_id:\\n g_user = users.get_current_user()\\n if g_user.user_id() == user[0].google_id:\\n return template('index', name=g_name, user = user[0].nick, log_in_out = '/exit', opt = 'Выход')\\n elif user[0].login_type == 2 && user[0].vk_id:\\n vk_cookie = request.get_cookie(\\\"vk_app_\\\"+vk_client_id)\\n vk_user_id = user[0].vk_id\\n if vk_cookie:\\n vk_session_info = vk_cookie.split('&')\\n vk_cookies = {}\\n for i in vk_session_info:\\n param = i.split('=')\\n vk_cookies[param[0]]=param[1]\\n if vk_cookies[mid] == vk_user_id:\\n m = hashlib.md5()\\n hashstring = 'expire='+vk_cookies['expire']+'mid='+vk_cookies['mid']+'secret'+vk_cookies['secret']+'sid='+vk_cookies['sid']+vk_client_secret\\n m.update(hashstring)\\n if vk_cookies['sig']==m.hexdigest():\\n return template('index', name=g_name, user = user[0].nick, log_in_out = '/exit', opt = 'Выход')\\n else:\\n response.set_cookie('uid', 'none')\\n return template('index', name=g_name, log_in_out = '/login', opt = 'Войти') \\n else:\\n response.set_cookie('uid', 'none')\\n return template('index', name=g_name, log_in_out = '/login', opt = 'Войти') \\n else:\\n response.set_cookie('uid', 'none')\\n return template('index', name=g_name, log_in_out = '/login', opt = 'Войти')\\n vk_user_id\\n else:\\n return \\\"Invalid database value, please contact admin. UID: \\\"+user[0].local_id\\n else:\\n response.set_cookie('uid', 'none')\\n return template('index', name=g_name, log_in_out = '/login', opt = 'Войти')'''\\n user = users.get_current_user()\\n if user:\\n return template('index', name=g_name, user = user.nickname(), log_in_out = users.create_logout_url('/'), opt = 'Выход')\\n else:\\n return template('index', name=g_name, log_in_out = users.create_login_url('/'), opt = 'Войти')\",\n \"def user_login(TTL=60):\\n # auth = request.authorization\\n # username = auth.username\\n # password = auth.password\\n username = request.args.get('username')\\n password = request.args.get('password')\\n print 'user', username\\n print 'pass', password\\n\\n if g.user:\\n print \\\"g.user:\\\", g.user\\n # return jsonify(URL=url_for('home_timeline'))\\n # Create a hash key\\n message_json = \\\"\\\"\\n hash = hashlib.sha224(message_json).hexdigest()\\n key = \\\"Login_API_Cache\\\" + hash\\n print \\\"Created Key\\\\t : %s\\\" % key\\n\\n # Check if data is in cache.\\n if (R_SERVER.get(key)):\\n print \\\"** Messages returned from Redis Cache **\\\"\\n return cPickle.loads(R_SERVER.get(key))\\n\\n if username != None:\\n print \\\"session\\\"\\n error = None\\n if request.method == 'GET':\\n print g.user\\n print username\\n user = userdetails_API_query(username)\\n print \\\"query\\\", user\\n if user is None:\\n error = 'Invalid username'\\n return jsonify(Status_code=status.HTTP_401_UNAUTHORIZED, username=username, error=error)\\n elif not check_password_hash(user['pw_hash'],\\n password):\\n error = 'Invalid password'\\n return jsonify(Status_code=status.HTTP_401_UNAUTHORIZED, username=username, error=error)\\n else:\\n print \\\"** Messages returned from MongoDB **\\\"\\n flash('You were logged in')\\n session['user_id'] = user['_id']\\n username = {'Username_logged_in': username}\\n\\n ############### REDIS SESSION CODE #####################\\n\\n message_json = jsonify(\\n Status_code=status.HTTP_200_OK, username=username)\\n R_SERVER.set(key, cPickle.dumps(message_json))\\n R_SERVER.expire(key, TTL)\\n\\n return message_json\\n else:\\n print\\\"logout\\\", g.user[1]\\n flash('You were logged out')\\n session.pop('user_id', None)\\n username = {'Username_logged_out': g.user[1]}\\n return jsonify(URL=url_for('newpublic_timeline'), Username=username, Status_code=status.HTTP_200_OK)\",\n \"def auth_login(request, user):\\n\\n ri = rest_interface(opensso_url=OPEN_AM_SERVER_URL)\\n\\n token_logged_in = ri.do_login(request.REQUEST.get('username'),request.REQUEST.get('password'))\\n\\n if (ri.isErrorable(token_logged_in)):\\n if request.COOKIES.has_key(OPENAM_COOKIE_NAME_FOR_TOKEN):\\n del request.COOKIES[OPENAM_COOKIE_NAME_FOR_TOKEN]\\n return None\\n\\n token_logged_in = ri.clear_token(token_logged_in)\\n\\n \\\"\\\"\\\"\\n if user is None:\\n user = request.user\\n # TODO: It would be nice to support different login methods, like signed cookies.\\n if SESSION_KEY in request.session:\\n if request.session[SESSION_KEY] != user.pk:\\n # To avoid reusing another user's session, create a new, empty\\n # session if the existing session corresponds to a different\\n # authenticated user.\\n request.session.flush()\\n else:\\n request.session.cycle_key()\\n\\n \\\"\\\"\\\"\\n\\n #ssouser = SSOUser(True)\\n\\n\\n ###########ssouser_logged_in.send(sender=ssouser.__class__, request=request, ssouser=ssouser)\\n #request.session['somekey'] = 'test'\\n\\n \\\"\\\"\\\"\\n request.ssouser = ssouser\\n if request.COOKIES.has_key(OPENAM_COOKIE_NAME_FOR_TOKEN):\\n del request.COOKIES[OPENAM_COOKIE_NAME_FOR_TOKEN]\\n request.COOKIES[OPENAM_COOKIE_NAME_FOR_TOKEN] = token_logged_in\\n \\\"\\\"\\\"\\n\\n #ri.save_token()\\n\\n return token_logged_in\",\n \"def register():\\n\\n if current_user.is_authenticated:\\n return redirect(url_for('general.show_dash'))\\n\\n form = RegistrationForm()\\n\\n if form.validate_on_submit():\\n\\n #Continua con la creacion de un usuario\\n hashed_password = user_manager.hash_password(form.password.data)\\n new_user = User(\\n username=form.username.data,\\n email=form.email.data,\\n password=hashed_password,\\n confirmed_at=datetime.datetime.utcnow(),\\n is_enabled=True,\\n )\\n\\n\\n role='User'\\n role_default = Role.query.filter_by(name=role).first()\\n\\n if not role_default:\\n new_role_default = Role(name = 'User')\\n new_user.roles.add(new_role_default)\\n else:\\n new_user.roles.add(role_default)\\n\\n try:\\n correct = True\\n db.session.add(new_user)\\n db.session.commit()\\n\\n except Exception as e:\\n # Catch anything unknown\\n print(e)\\n correct = False\\n\\n finally:\\n if not correct:\\n # Cleanup and show error\\n db.session.rollback()\\n flash('Error creating user, make sure username and email are unique','error')\\n\\n else:\\n flash('Congratulations, you are now a registered user!','success')\\n return redirect(url_for('user.login'))\\n return render_template('extensions/flask_user/register.html', title='Register', form=form)\",\n \"def _create_session_data(self, abs_path, sess_root):\\n sess_path = os.path.join(abs_path, sess_root)\\n if not os.path.exists(sess_path):\\n os.makedirs(sess_path)\\n sess_id = len(os.listdir(sess_path))\\n sess_path = os.path.join(sess_path, str(sess_id))\\n print(\\\"SESSION PATH:\\\", sess_path)\\n print(\\\"SESSION ID:\\\", sess_id) \\n return sess_id, sess_path\",\n \"def generate_csrf_token():\\n if '_csrf_token' not in login_session:\\n login_session['_csrf_token'] = b64encode(urandom(64)).decode() # Cryptographically secure random key\\n print(\\\"_csrf_token:\\\" + login_session['_csrf_token'])\\n return login_session['_csrf_token']\",\n \"def make_new_session():\\n session = Session.objects.create(uuid=str(uuid4()), container_id=None)\\n return session.id\",\n \"def token_browser_profile(request): # URL: 'quest-token-profile'\\n m = hashlib.md5()\\n m.update('%s |*| %s |*| %s |*| %s' % ( request.POST.get('os', ''),\\n request.POST.get('display', ''),\\n request.POST.get('software', ''),\\n request.POST.get('browser', '')))\\n\\n profile = Profile(ua_string=request.POST.get('browser', '')[0:255],\\n software=request.POST.get('software', '')[0:10000],\\n os=request.POST.get('os', '')[0:50],\\n display=request.POST.get('display', '')[0:255])\\n profile.hashid = m.hexdigest()\\n profile.save()\\n\\n request.session['profile'] = profile.hashid\\n request.session.save()\\n return HttpResponse('K')\",\n \"def session_success_data(self):\\n return {\\n 'id_token': self.encoded_token,\\n }\",\n \"def unique_id() -> bytes:\\n ...\",\n \"def game_id():\\n\\n # Use new_game method to start a new game\\n session.clear()\\n session[\\\"game_id\\\"] = new_game(engine)\\n print \\\"Creating new game with game_id =\\\", session[\\\"game_id\\\"]\\n\\n # Redirect to home page\\n return redirect(url_for(\\\"index\\\"))\",\n \"def profile():\\n github = OAuth2Session(client_id, token=session['oauth_token'])\\n print(session['oauth_token'])\\n # print(github.get('https://www.goodreads.com/api/auth_user').json())\\n return \\\"hello expedia!! Here is your access_token : \\\" + session['oauth_token']['access_token']\",\n \"def returnIdLogin(self):\\r\\n self.cursor.execute(\\\"SELECT USUARIO FROM LOGIN;\\\")\\r\\n self.__result = self.cursor.fetchall()\\r\\n self.__lista = []\\r\\n try:\\r\\n for self.__i in self.__result:\\r\\n self.__lista.append(self.__i[0])\\r\\n return self.__lista\\r\\n except:\\r\\n return []\",\n \"def rpc_senha(self,usuario,senha):\\n try:\\n retorno,permissao=self.senha_auth.login(usuario,senha)\\n print(retorno)\\n if(retorno):\\n #devolve a resposta de login sucesso\\n user=self.sucess_login(usuario,permissao)\\n return True,user\\n else:\\n return False,False\\n except xmlrpc.client.Fault as err:\\n print(\\\"Ocorreu um erro\\\")\\n print(\\\"Código de erro %d\\\" % err.faultCode)\\n print(\\\"Fault string: %s\\\" % err.faultString)\",\n \"def carregarLogin(self, loginId):\\r\\n try:\\r\\n self.cursor.execute(\\\"SELECT * FROM LOGIN WHERE USUARIO = %s;\\\" %(loginId))\\r\\n if self.cursor.rowcount == 1:\\r\\n return self.cursor.fetchone()\\r\\n else:\\r\\n return None\\r\\n except:\\r\\n return None\",\n \"def get_user_id(self, session, **kwargs):\\n return None\",\n \"def save(self)->None:\\n database.cursor.execute(\\n \\\"INSERT INTO users(firstname,lastname,othernames,email,phone,username,password,role) VALUES (%s,%s,%s,%s,%s,%s,%s,%s) RETURNING id\\\", (\\n self.first_name,\\n self.last_name,\\n self.other_name,\\n self.email,\\n self.phone_number,\\n self.user_name,\\n self.password,\\n self.is_admin\\n ))\\n super().save()\",\n \"def register():\\n session.clear()\\n\\n \\\"\\\"\\\"Register user\\\"\\\"\\\"\\n\\n if request.method == \\\"POST\\\":\\n\\n # Ensure username was submitted\\n if not request.form.get(\\\"username\\\"):\\n return apology(\\\"must provide username\\\", 400)\\n\\n # Ensure password was submitted\\n elif not request.form.get(\\\"password\\\"):\\n return apology(\\\"must provide password\\\", 400)\\n\\n # Make sure password and confirmation match\\n elif request.form.get(\\\"password\\\") != request.form.get(\\\"confirmation\\\"):\\n return apology(\\\"password does not match\\\", 400)\\n\\n\\n # add username and pw to the DB\\n\\n hash = generate_password_hash(request.form.get(\\\"password\\\"))\\n result = db.execute(\\\"INSERT INTO users (username, hash) VALUES(:username, :hash)\\\", username=request.form.get(\\\"username\\\"), hash=hash)\\n\\n if not result:\\n return apology(\\\"username already exists\\\", 400)\\n\\n # Log user in\\n # Query database for username\\n rows = db.execute(\\\"SELECT * FROM users WHERE username = :username\\\", username=request.form.get(\\\"username\\\"))\\n\\n\\n session[\\\"user_id\\\"] = rows[0][\\\"id\\\"]\\n\\n\\n # Redirect user to home page\\n return redirect(\\\"/\\\")\\n\\n # User reached route via GET (as by clicking a link or via redirect)\\n else:\\n return render_template(\\\"register.html\\\")\"\n]","isConversational":false},"negative_scores":{"kind":"list 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\"0.62706566\",\n \"0.58388746\",\n \"0.5836526\",\n \"0.57945734\",\n \"0.57002115\",\n \"0.56958556\",\n \"0.56462306\",\n \"0.56462306\",\n \"0.5479111\",\n \"0.54686075\",\n \"0.544465\",\n \"0.543805\",\n \"0.5410522\",\n \"0.5397467\",\n \"0.53923786\",\n \"0.5386921\",\n \"0.5382159\",\n \"0.5382095\",\n \"0.53573304\",\n \"0.53492916\",\n \"0.53322214\",\n \"0.53316796\",\n \"0.5325293\",\n \"0.53126377\",\n \"0.530673\",\n \"0.53059417\",\n \"0.5288012\",\n \"0.52872694\",\n \"0.52870744\",\n \"0.52408785\",\n \"0.52386016\",\n \"0.5236569\",\n \"0.5221762\",\n \"0.520836\",\n \"0.5207962\",\n \"0.52057654\",\n \"0.5190381\",\n \"0.51863956\",\n \"0.5186291\",\n \"0.5185207\",\n \"0.5140684\",\n \"0.51399255\",\n \"0.51308215\",\n \"0.5122714\",\n \"0.5120806\",\n \"0.51150554\",\n \"0.5109439\",\n \"0.51084936\",\n \"0.5103471\",\n \"0.51004785\",\n \"0.50928766\",\n \"0.5091295\",\n \"0.50851476\",\n \"0.5068842\",\n \"0.5066758\",\n \"0.5057877\",\n \"0.5050113\",\n \"0.5030595\",\n \"0.50228\",\n \"0.5021731\",\n \"0.50188357\",\n \"0.50060546\",\n \"0.5001294\",\n \"0.49987832\",\n \"0.4996261\",\n \"0.49962497\",\n \"0.49755976\",\n \"0.4969473\",\n \"0.49632946\",\n \"0.49602425\",\n \"0.49565282\",\n \"0.49456665\",\n \"0.49390128\",\n \"0.49378642\",\n \"0.4927412\",\n \"0.4925323\",\n \"0.49252602\",\n \"0.492447\",\n \"0.49226525\",\n \"0.491889\",\n \"0.491767\",\n \"0.49126053\",\n \"0.4912508\",\n \"0.4908026\",\n \"0.49065155\",\n \"0.4901077\",\n \"0.48977554\",\n \"0.4890763\",\n \"0.48845387\",\n \"0.48842442\",\n \"0.487642\",\n \"0.48678684\",\n \"0.48638308\",\n \"0.4857607\",\n \"0.48522165\",\n \"0.48492405\",\n \"0.48464924\",\n \"0.4841875\",\n \"0.48392066\",\n \"0.4837889\",\n \"0.48378655\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":18692,"cells":{"query":{"kind":"string","value":"Gera o codigo rml da assinatura"},"document":{"kind":"string","value":"def presidente(lst_presidente):\n tmp=''\n tmp+='\\t\\t<para style=\"P3\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n tmp+='\\t\\t<para style=\"P3\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n tmp+='\\t\\t<para style=\"P3\" spaceAfter=\"40\">\\n'\n tmp+='\\t\\t\\t<font color=\"white\"> </font>\\n'\n tmp+='\\t\\t</para>\\n'\n tmp+='\\t\\t<para style=\"P1\"><b>' + str(lst_presidente) + '</b></para>\\n'\n tmp+='\\t\\t<para style=\"P4\">Presidente </para>\\n'\n tmp+='\\t</story>\\n'\n return tmp"},"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 to_ir(self):","def mezclar_bolsa(self):","def __str__(self):\n return self.idBaixasReceber","def cliquer_sur_unité(self):","def encode(category_main : ):","def __init__(self,obj):\n self.nature_libelle = obj['NatureLibelle']\n self.ins_nom = obj['InsNom']\n self.ins_numero_install = obj['InsNumeroInstall']\n self.equipement_id = obj['EquipementId']","def __str__(self):\r\n return self.afficherOBJ()","def serialize(self):","def convert(self) -> dict:\n def get_triples_linker():\n \"\"\"\n Retrieve all of the triples linking phrases from the AMR object.\n We use the Framenet words that are found in the AMR Object as the linker.\n \"\"\"\n triples_linkers = []\n concepts = list(self.amr_obj.concepts())\n\n # Retrieve all concept that has the word ARG in it\n for concept in concepts:\n triple = self.amr_obj.triples(head=concept[0])\n items = [item for item in triple if 'ARG' in item[1]]\n if len(items) > 0:\n triples_linkers.append(triple)\n return triples_linkers\n\n def generate_triples():\n\n def fixing_annotation(key, n):\n \"\"\"\n Fixing some inconsistency in the annotation\n \"\"\"\n if key + '.' + n not in self.propbank:\n key = key.replace('-', '_')\n return key + '.' + n\n\n def is_agent(f_rel, rel_var):\n \"\"\"\n Checking whether the role is an agent (denoted by 'pag') or not\n \"\"\"\n # TODO: beside 'pag' is there any other role?\n m = re.match(r'(.*)-(\\d*)$', rel_var)\n key = m.group(1)\n n = m.group(2)\n\n # some annotation does not have the correspondence frameset, just put false if found\n if n == '00':\n return False\n\n concept = fixing_annotation(key, n)\n roleset = self.propbank[concept]\n\n m = re.match(r':ARG(.).*', f_rel[1])\n n = int(m.group(1))\n roles = roleset.getElementsByTagName('role')\n\n for role in roles:\n if dict(role.attributes)['n'].value == str(n) and dict(role.attributes)['f'].value.lower() == 'pag':\n return True\n return False\n\n # Case 1: ARG\n for triple_linker in self.triples_linkers:\n triple = [None, triple_linker[0][0], []]\n for rel in triple_linker:\n if 'ARG' in rel[1] and 'of' not in rel[1]:\n # check whether the propbank verb rel[0] and its argument rel[2] is an agent or not\n if is_agent(rel, self.var2c[rel[0]].__str__()):\n triple[0] = rel[2]\n else:\n triple[2].append(rel[2])\n if not (triple[0] is None and triple[2] == []):\n self.triples[triple[1]] = triple\n\n # Case 2: ARG-of\n for triple_linker in self.triples_linkers:\n for rel in triple_linker:\n if 'ARG' in rel[1] and 'of' in rel[1]:\n if rel[2] not in self.triples:\n self.triples[rel[2]] = [None, rel[2], []]\n if is_agent(rel, self.var2c[rel[2]].__str__()):\n self.triples[rel[2]][0] = rel[0]\n else:\n self.triples[rel[2]][2].append(rel[0])\n return self.triples\n\n self.triples_linkers = get_triples_linker()\n return generate_triples()","def cod(self):\n raise NotImplementedError(\"base class called\")","def load(self):","def get_encoded(self):\n pass","def presenetCar():","def afficherOBJ(self):\r\n str_abr = self.abr.afficher()## appel de l'affichage d'un ABR\r\n return str(self.debut)+':'+str(self.fin)+';'+str_abr ##concaténation du resultat\r","def __generate_code(self):\n vouels = [\"A\", \"E\", \"I\", \"O\", \"U\"]\n coding = self.surname\n fiscal_code = \"\"\n\n # Generate first 6 letters of surname and name\n for i in range(2):\n for letter in coding:\n if len(fiscal_code) == 3 * (i+1):\n break\n elif not letter in vouels:\n #Use all upper letters\n fiscal_code += letter.upper()\n for letter in coding:\n if len(fiscal_code) == 3 * (i+1):\n break\n elif letter in vouels:\n fiscal_code += letter\n while len(fiscal_code) < 3 * (i+1):\n fiscal_code += \"X\"\n coding = self.name\n\n # Add last 2 digits of year\n fiscal_code += str(self.date.year)[-2:]\n\n # Associate month and letter\n months = [\"A\", \"B\", \"C\", \"D\", \"E\",\n \"H\", \"L\", \"M\", \"P\", \"R\", \"S\", \"T\"]\n fiscal_code += months[self.date.month - 1]\n\n # Add day, plus 40 if female\n if self.sex == \"FEMALE\":\n fiscal_code += str(self.date.day + 40)\n elif self.date.day < 10:\n fiscal_code += \"0\" + str(self.date.day)\n else:\n fiscal_code += str(self.date.day)\n\n # Add some other characters to rappresent\n fiscal_code += \"X\"\n for i in range(3):\n fiscal_code += str(i)\n fiscal_code += \"X\"\n\n self.value = fiscal_code","def __init__(self, code, codeInfo):\r\n self.Code = code #IRCode\r\n self.CodeInfo = codeInfo #IRCodeInfo\r","def encode(self): # pragma: no cover\n pass","def __str__(self):\n return self.identificacao","def __str__(self):\n return self.identificacao","def __str__(self):\n return self.identificacao","def _serialise(self):\n # TODO (M Foley)\n pass","def ler_gne_framework(self, tag):\r\n if not tag:\r\n raise Exception(\"709 - Parametros insuficientes!\")\r\n\r\n value = \" \"*40\r\n key_tag = self.carrega_endereco_tag_gne(tag.upper())\r\n if not key_tag:\r\n raise Exception(\"-40: Tag XML nao encontrada.\")\r\n\r\n status = self.dll.regRetornarValor_NFCe_Daruma(key_tag, value)\r\n\r\n\tif status !=1:\r\n if status == -40:\r\n raise Exception(\"-40: Tag XML nao encontrada.\")\r\n return {tag: value}","def __repr__(self):\n return f'ResidenciaModel(name={self.neighbourhood_group}, neighbourhood={self.room_type})'","def __init__(self, marqueur, allele, hauteur, informatif):\n\n self.marqueur = marqueur\n self.allele = allele\n self.hauteur = hauteur\n self.informatif = informatif","def __str__(self):\n line = ''\n for linea in self.lista:\n for atributo in linea:\n if linea[atributo] != \"\":\n line += atributo + \"=\" + \"'\" + linea[atributo] + \"'\" + '\\t'\n line += '\\n'\n return line","def __str__(self):\n return self.idLancamentosReceber","def __str__(self):\n return self.idBaixasPagar","def mapping_stratum(download_files =True):\r\n # get code description _index \r\n ix_= AGSO_PROPERTIES['props_codes'].index('name')\r\n def mfunc_(d): \r\n \"\"\" Set individual layer in dict of properties \"\"\"\r\n _p= {c: k.lower() if c not in ('code', 'label', 'name') else k \r\n for c, k in zip(AGSO_PROPERTIES['props_codes'], d) }\r\n id_= d[ix_].replace('/', '_').replace(\r\n ' ', '_').replace('\"', '').replace(\"'\", '').lower()\r\n return id_, _p \r\n rock_and_structural_props =list()\r\n for agso_data in tuple(set_agso_properties(download_files)): \r\n # remove the header of the property file\r\n rock_and_structural_props.append(\r\n dict(map( lambda x: mfunc_(x), agso_data[1:])))\r\n \r\n return tuple(rock_and_structural_props)","def comunicacion():\n global dsgraph\n global mss_cnt\n\n #Extraemos el mensaje y creamos un grafo con el\n message= request.args['content']\n gm = Graph()\n gm.parse(data=message)\n\n msgdic = get_message_properties(gm)\n\n # Comprobamos que sea un mensaje FIPA ACL\n if msgdic is None:\n # Si no es, respondemos que no hemos entendido el mensaje\n gr = build_message(Graph(), ACL['not-understood'], sender=InfoAgent.uri, msgcnt=mss_cnt)\n else:\n # Obtenemos la performativa\n perf = msgdic['performative']\n\n if perf != ACL.request:\n # Si no es un request, respondemos que no hemos entendido el mensaje\n gr = build_message(Graph(), ACL['not-understood'], sender=InfoAgent.uri, msgcnt=mss_cnt)\n else:\n #Extraemos el objeto del contenido que ha de ser una accion de la ontologia de acciones del agente\n # de registro\n\n # Averiguamos el tipo de la accion\n if 'content' in msgdic:\n content = msgdic['content']\n accion = gm.value(subject=content, predicate= RDF.type)\n\n # Aqui realizariamos lo que pide la accion\n\n gt = buscar_transport(gm)\n # Por ahora simplemente retornamos un Inform-done\n gr = build_message(gt,\n ACL['inform-done'],\n sender=InfoAgent.uri,\n msgcnt=mss_cnt,\n receiver=msgdic['sender'],)\n mss_cnt += 1\n return gr.serialize(format='xml')","def encoding(self) -> 'layout.Encoding':","def exo2():","def __init__(self):\n self.aeropuertos = {}","def agregar_bolsa(self, letra, cantidad):","def init_podataka_sa_REST(self):\n urlUredjaj = self.cfg.get_konfig_element('REST', 'uredjaj')\n listaUredjaja = helper_funkcije.get_uredjaje_sa_REST(urlUredjaj)\n #inicijalizacija svih dostupnih uredjaja\n if listaUredjaja:\n for uredjaj in listaUredjaja:\n UNIT = Uredjaj(serial=uredjaj)\n tekst = helper_funkcije.get_podatke_za_uredjaj_sa_REST(urlUredjaj, uredjaj)\n #ako postoje podaci za uredjaj\n if tekst:\n try:\n root = ET.fromstring(tekst)\n #OSNOVNI PODACI UREDJAJA\n try:\n lokacija = helper_funkcije.get_lokaciju_uredjaja(urlUredjaj, uredjaj)\n UNIT.set_lokacija(lokacija)\n self.add_postaju(lokacija)\n except Exception:\n pass\n try:\n proizvodjac = root.find('modelUredjajaId/proizvodjacId/naziv').text\n UNIT.set_proizvodjac(proizvodjac)\n except Exception:\n pass\n try:\n oznakaModela = root.find('modelUredjajaId/oznakaModela').text\n UNIT.set_oznakaModela(oznakaModela)\n except Exception:\n pass\n #ANALITICKA METODA\n METODA = AnalitickaMetoda()\n try:\n ID = root.find('./modelUredjajaId/analitickeMetodeId/id').text\n METODA.set_ID(ID)\n except Exception:\n pass\n try:\n norma = root.find('./modelUredjajaId/analitickeMetodeId/norma').text\n METODA.set_norma(norma)\n except Exception:\n pass\n try:\n naziv = root.find('./modelUredjajaId/analitickeMetodeId/naziv').text\n METODA.set_naziv(naziv)\n except Exception:\n pass\n #elementi za racunanje...(Srz, Srs, rz, rmax...)\n try:\n metode = root.find('./modelUredjajaId/analitickeMetodeId')\n for granica in metode.findall('dozvoljeneGraniceCollection'):\n try:\n oznaka = granica.find('./ispitneVelicine/oznaka').text\n value = granica.find('max').text\n if oznaka == 'o':\n METODA.set_o(value)\n #pokusaj dolaska do mjerne jedinice\n jedinica = granica.find('./mjerneJediniceId/oznaka').text\n jedinica = helper_funkcije.adapt_mjernu_jedinicu(jedinica)\n METODA.set_jedinica(jedinica)\n elif oznaka == 'Ec':\n #za efikasnost konvertera treba i min granica\n METODA.set_Ec_max(value)\n minvalue = granica.find('min').text\n METODA.set_Ec_min(minvalue)\n else:\n METODA.set_member[oznaka](value)\n except Exception:\n pass\n except Exception:\n pass\n #ako metoda ne postoji na popisu... dodaj ju\n self.set_novu_analiticku_metodu(ID, METODA)\n #postavi analiticku metodu u uredjaj\n UNIT.set_analitickaMetoda(METODA)\n #KOMPONENTE UREDJAJA\n try:\n komponente = root.find('modelUredjajaId')\n for komponenta in komponente.findall('komponentaCollection'):\n KOMPONENTA = Komponenta()\n try:\n formula = komponenta.find('formula').text\n KOMPONENTA.set_formula(formula)\n naziv = komponenta.find('naziv').text\n KOMPONENTA.set_naziv(naziv)\n mjernaJedinica = komponenta.find('./mjerneJediniceId/oznaka').text\n mjernaJedinica = helper_funkcije.adapt_mjernu_jedinicu(mjernaJedinica)\n KOMPONENTA.set_jedinica(mjernaJedinica)\n kv = komponenta.find('konvVUM').text\n KOMPONENTA.set_kv(kv)\n #dodaj komponentu u mapu\n self.set_novu_komponentu(formula, KOMPONENTA)\n #dodaj komponentu u uredjaj\n UNIT.dodaj_komponentu(KOMPONENTA)\n except Exception:\n pass\n except Exception:\n pass\n #postavi uredjaj u mapu sa serijskim uredjajima\n self.dodaj_uredjaj(uredjaj, UNIT)\n except Exception as err:\n logging.warning(str(err))\n self.create_local_cache()\n else:\n self.load_local_cache()","def getArchivoVotacion():","def encode(self, decoded):","def _blob(self):\n self.__rewrite_sldIdLst()\n # # at least the following needs to be added before using\n # # _reltype_ordering again for Presentation\n # self.__rewrite_notesMasterIdLst()\n # self.__rewrite_handoutMasterIdLst()\n # self.__rewrite_sldMasterIdLst()\n return super(Presentation, self)._blob","def __unicode__(self):\n return self.parroquia","def __init__(self):\n self.nombre_roues = 4\n self.nombre_fauteils = 1\n self.moteur = False\n self.volant = True","def convertion_binaire_arbre(self):\r\n binary_code = self.root.conversion_binaire('')\r\n binary_dict = {}\r\n binary_code = binary_code.strip().split(\"\\n\")\r\n for element in binary_code:\r\n binary_dict[element.split(\":\")[0]] = element.split(\":\")[1]\r\n return binary_dict","def _encode_supplement(self):","def _encode_supplement(self):","def data(self):","def decode(self): # pragma: no cover\n pass","def getRestricaoPlacaFinal(self):\n import ast\n restricao_placa_final = ast.literal_eval(self.soup.text).get('Rotation').get('desc')\n return restricao_placa_final","def comunicacion():\n global dsgraph\n global mss_cnt\n\n #Extraemos el mensaje y creamos un grafo con el\n message= request.args['content']\n gm = Graph()\n gm.parse(data=message)\n\n msgdic = get_message_properties(gm)\n\n # Comprobamos que sea un mensaje FIPA ACL\n if msgdic is None:\n # Si no es, respondemos que no hemos entendido el mensaje\n gr = build_message(Graph(), ACL['not-understood'], sender=InfoAgent.uri, msgcnt=mss_cnt)\n else:\n # Obtenemos la performativa\n perf = msgdic['performative']\n\n if perf != ACL.request:\n # Si no es un request, respondemos que no hemos entendido el mensaje\n gr = build_message(Graph(), ACL['not-understood'], sender=InfoAgent.uri, msgcnt=mss_cnt)\n else:\n #Extraemos el objeto del contenido que ha de ser una accion de la ontologia de acciones del agente\n # de registro\n\n # Averiguamos el tipo de la accion\n if 'content' in msgdic:\n content = msgdic['content']\n accion = gm.value(subject=content, predicate= RDF.type)\n\n # Aqui realizariamos lo que pide la accion\n\n #Extraiem els parametres necessaris per realitzar la busqueda\n paq = paquet[\"vacances\"]\n\n destination = gm.value(subject= paq, predicate= paquet.desti)\n departureDate = gm.value(subject= paq, predicate= paquet.dep_date)\n returnDate = gm.value(subject= paq, predicate= paquet.ret_date)\n numAdults = gm.value(subject= paq, predicate= paquet.num_adults)\n numChildren = gm.value(subject= paq, predicate= paquet.num_child)\n centric = gm.value(subject= paq, predicate = paquet.centric)\n category = gm.value(subject= paq, predicate = paquet.category)\n minStars = gm.value(subject= paq, predicate = paquet.min_stars)\n\n gh = buscar_hotels(destination, departureDate, returnDate, numAdults, numChildren, centric, category, minStars)\n\n # Por ahora simplemente retornamos un Inform-done\n gr = build_message(gh,\n ACL['inform-done'],\n sender=InfoAgent.uri,\n msgcnt=mss_cnt,\n receiver=msgdic['sender'],)\n mss_cnt += 1\n return gr.serialize(format='xml')","def __init__():\n self.placa = placa","def CL(self):","def __init__(self, nombre, socios):\n self.__nombre = nombre\n self.__socios = socios\n self.__resultados = {'p1': '', 'p2': '', 'p3': '', 'p4': '', 'p5': '', 'p6': '', 'p7': ''}","def load_data(self):","def cargar_atril(self,lista,bolsa):\n self.atril = lista\n self.bolsa = bolsa","def __init__(self, nom, prenom):\n \n self.nom = nom\n self.prenom = prenom\n self.age = 33\n self._lieu_residence = \"Paris\" # Notez le souligné _ devant le nom","def convert(self):\n return","def generate(self):","def archivos_de_texto():\n palabra = \"\" \n palabras_candidatas = [] #lista donde se guardara las palabras candidatas de cada linea\n palabra_cantidad = {} #diccionario con la palabra candidata de clave y las veces que esta repetida en cada texto de valor\n with open(\"Cuentos.txt\",\"r\") as Cuentos: \n for linea_Cuentos in Cuentos: #cada ciclo del for es una linea del texto\n for caracter in linea_Cuentos: #cada ciclo del for es una caracter de la linea \n if caracter.isalpha():\n caracter = quitar_tilde_y_may(caracter) #se transformas caracteres mayusculas y tildes\n palabra += caracter #cada caracter ira formando la palabra\n if not caracter.isalpha():\n if len(palabra) >= 5: #se analiza que la palabra tenga 5 o mas caracteres\n palabras_candidatas.append(palabra) \n palabra = \"\" #se vacia la palabra ya analizada\n for palabra_en_lista in palabras_candidatas: #se introduce las palabras candidatas a un diccionario\n if palabra_en_lista not in palabra_cantidad:\n palabra_cantidad[palabra_en_lista] = [1,0,0]\n else:\n palabra_cantidad[palabra_en_lista] = [int(palabra_cantidad[palabra_en_lista][0]) + 1 , 0, 0]\n palabras_candidatas = []\n with open(\"La araña negra - tomo 1.txt\",\"r\") as La_arana_negra:#se repite el mismo proceso con los otros dos textos\n for linea_Cuentos in La_arana_negra:\n for caracter in linea_Cuentos:\n if caracter.isalpha():\n caracter = quitar_tilde_y_may(caracter)\n palabra += caracter\n if not caracter.isalpha():\n if len(palabra) >= 5:\n palabras_candidatas.append(palabra)\n palabra = \"\"\n for palabra_en_lista in palabras_candidatas:\n if palabra_en_lista not in palabra_cantidad:\n palabra_cantidad[palabra_en_lista] = [0,1,0]\n else:\n palabra_cantidad[palabra_en_lista] = [palabra_cantidad[palabra_en_lista][0] , int(palabra_cantidad[palabra_en_lista][1]) + 1, 0]\n palabras_candidatas = [] \n with open(\"Las 1000 Noches y 1 Noche.txt\",\"r\") as muchas_noches: \n for linea_Cuentos in muchas_noches:\n for caracter in linea_Cuentos:\n if caracter.isalpha():\n caracter = quitar_tilde_y_may(caracter)\n palabra += caracter\n if not caracter.isalpha():\n if len(palabra) >= 5:\n palabras_candidatas.append(palabra)\n palabra = \"\"\n for palabra_en_lista in palabras_candidatas:\n if palabra_en_lista not in palabra_cantidad:\n palabra_cantidad[palabra_en_lista] = [0,0,1]\n else:\n palabra_cantidad[palabra_en_lista] = [palabra_cantidad[palabra_en_lista][0] ,palabra_cantidad[palabra_en_lista][1], int(palabra_cantidad[palabra_en_lista][2]) + 1]\n palabras_candidatas = [] \n palabra_cantidad = dict(sorted(palabra_cantidad.items())) #se ordena el diccionario alfabeticamente\n with open(\"palabras.csv\",\"w\") as palabras_csv: # se agrga el diccionario a un arcivo .csv\n for palabra in palabra_cantidad:\n palabras_csv.write(palabra)\n palabras_csv.write(\",\")\n palabras_csv.write(str(palabra_cantidad[palabra][0]))\n palabras_csv.write(\",\")\n palabras_csv.write(str(palabra_cantidad[palabra][1]))\n palabras_csv.write(\",\")\n palabras_csv.write(str(palabra_cantidad[palabra][2]))\n palabras_csv.write(\"\\n\")\n return palabra_cantidad","def __init__(self, rouge_types):\n\n self.rouge_types = rouge_types","def representarArbolAutomatico(self):\n if not self.stepByStep:\n print(\"Pintar paredes en auto\")\n # Reinicio la matrix\n self.reiniciarMatrix()\n if self.arbol.raiz != None:\n # Capturo todos los valores\n for i in self.arbol.returnArbolComoVector():\n \n # Esta variable captura si se debe de pintar en x o y\n xy = int(i[1])\n cordenadas = i[0]\n print(\"===========NODOS DEL ARBOL=============\")\n print(i)\n print(\"===========NODOS DEL ARBOL=============\")\n # Se pinta en x o y?\n if xy == 0:\n self.crearParedX(int(cordenadas[0]), int(cordenadas[1]))\n else:\n self.crearParedY(int(cordenadas[0]), int(cordenadas[1]))\n\n self.esperarUnRato()\n\n print(\"========LISTO PARA PINTAR EL SIGUIENTE================\")\n \n else:\n print(\"Arbol vacio\")","def encode(rosMsg): #@NoSelf","def entrada_aluno(matricula):\n cod_curso = entrada_curso()\n print('> Em que ano, mês e dia você entrou na UFC? (YYYY-MM-DD)')\n data_de_ingresso = check.entrada('>>> ', check.data)\n print('> Em que data você vai concluir seu curso? (YYYY-MM-DD)')\n data_de_conclusao = check.entrada('>>> ', check.data)\n\n aluno = database.Aluno(matricula, data_de_conclusao,\n data_de_ingresso, cod_curso)\n return aluno","def generar_red_neuronal (codigo, estadisticas=True):\n \n path = \"../data/entrenamiento/\" + str(codigo) + \"/\"\n \n f = open(path + \"data_neural_network_\" + str(codigo) + \".txt\")\n cab = str(f.readline())[:-1]\n cab = cab.replace(\"'\",\"\")\n cab = cab.replace(\" \",\"\")\n cabeceras = cab[1:-1].split(\",\")\n l_etiquetas = str(f.readline())[:-1].split(\",\")\n atributos = str(f.readline())[:-1].split(\",,\")\n f.close()\n\n l_atributos = []\n for atributo in atributos:\n l_atributos.append(atributo.split(\",\"))\n\n etiquetas = set(l_etiquetas) \n clases = sorted(list(etiquetas))\n \n l_atributos = np.array(l_atributos, \"float32\")\n l_etiquetas = np.array(l_etiquetas, \"float32\")\n \n\n #Separamos los datos que vamos a utilizar de entrenamiento y para realizar el test\n #datos de pruebas (0.25) de los de entrenamiento (0.75)\n X_train, X_test, y_train, y_test = train_test_split(l_atributos,l_etiquetas,test_size = 0.25,random_state = 0)\n\n #Creamos la red neuronal \n red = MLPClassifier(max_iter=100000, hidden_layer_sizes=(50,25))\n #Entrenamos la red neuronal\n red.fit(X_train, y_train)\n\n #Predicion de los resultados del bloque test\n y_pred = red.predict(X_test)\n #Matriz de confusion\n cm = confusion_matrix(y_test, y_pred)\n #Reportes\n report = classification_report(y_test, y_pred) \n\n\n\n if estadisticas == True:\n f=open(path + \"export_neural_network_statistics_\" + str(codigo) + \".txt\",\"w\") \n f.write(\"************************ CLASS *************************\\n\")\n for i in range(len(clases)):\n f.write(str(clases[i]) + \"\\n\")\n f.write(\"\\n\\n\")\n f.write(\"********************** FEATURES **********************\\n\")\n for i in range(len(cabeceras[:-1])):\n f.write(str(cabeceras[i]) + \"\\n\")\n f.write(\"\\n\\n\")\n f.write(\"************************ SCORE *************************\\n\")\n f.write(\"With Test data: \" + str(red.score(X_test, y_test)) + \"\\n\")\n f.write(\"With Training data: \" + str(red.score(X_train, y_train)) + \"\\n\")\n f.write(\"\\n\\n\")\n f.write(\"****************** CONFUSION MATRIX ********************\\n\")\n if len(clases)==2:\n f.write(\"\\t0\\t1\\n\")\n f.write(\"---------------------\\n\")\n f.write(\"0 |\\t\"+ str(cm[0][0]) +\"\\t\"+ str(cm[0][1]) +\"\\n\")\n f.write(\"1 |\\t\"+ str(cm[1][0]) +\"\\t\"+ str(cm[1][1]) +\"\\n\")\n if len(clases)==3:\n f.write(\"\\t0\\t1\\t2\\n\")\n f.write(\"--------------------------------\\n\")\n f.write(\"0 |\\t\"+ str(cm[0][0]) +\"\\t\"+ str(cm[0][1]) +\"\\t\"+ str(cm[0][2]) +\"\\n\")\n f.write(\"1 |\\t\"+ str(cm[1][0]) +\"\\t\"+ str(cm[1][1]) +\"\\t\"+ str(cm[1][2]) +\"\\n\")\n f.write(\"2 |\\t\"+ str(cm[2][0]) +\"\\t\"+ str(cm[2][1]) +\"\\t\"+ str(cm[2][2]) +\"\\n\")\n if len(clases)==4:\n f.write(\"\\t0\\t1\\t2\\t3\\n\")\n f.write(\"----------------------------------------------\\n\")\n f.write(\"0 |\\t\"+ str(cm[0][0]) +\"\\t\"+ str(cm[0][1]) +\"\\t\"+ str(cm[0][2]) +\"\\t\"+ str(cm[0][3]) +\"\\n\")\n f.write(\"1 |\\t\"+ str(cm[1][0]) +\"\\t\"+ str(cm[1][1]) +\"\\t\"+ str(cm[1][2]) +\"\\t\"+ str(cm[1][3]) +\"\\n\")\n f.write(\"2 |\\t\"+ str(cm[2][0]) +\"\\t\"+ str(cm[2][1]) +\"\\t\"+ str(cm[2][2]) +\"\\t\"+ str(cm[2][3]) +\"\\n\")\n f.write(\"3 |\\t\"+ str(cm[3][0]) +\"\\t\"+ str(cm[3][1]) +\"\\t\"+ str(cm[3][2]) +\"\\t\"+ str(cm[3][3]) +\"\\n\")\n f.write(\"\\n\\n\")\n f.write(\"************************ REPORT ***********************\\n\")\n f.write(report)\n f.close()\n \n print(str(codigo) + \": neural network created\") \n return (red, red.score(X_test, y_test))","def _regr_basic():","def parse(self):","def init_data():\n ps = Planete_Solidaire(name=\"Planète Solidaire\").save()\n\n maya = Human4j(\n firstname='Maya',\n lastname='Hannachi',\n number='0620902819',\n email='maya.hannachi@epita.fr',\n school='EPITA'\n ).save()\n mailinh = Human4j(\n firstname='Mai-Linh',\n lastname='Lannes',\n number='0612632032',\n email='mai-linh.lannes@epita.fr',\n school='EPITA'\n ).save()\n michel = Human4j(\n firstname='Michel',\n lastname='Sasson',\n number='0662739612',\n email='michel.sasson@epita.fr',\n school='EPITA'\n ).save()\n cedric = Human4j(\n firstname='Cédric',\n lastname='Joly',\n number='',\n email='cedric.joly@epita.fr',\n school='EPITA'\n ).save()\n caroline = Human4j(\n firstname='Caroline',\n lastname='De Paoli',\n number='',\n email='caroline.depaoli@isg.fr',\n school='ISG'\n ).save()\n\n binome = Binome4j().save()\n binome.human1.connect(mailinh)\n binome.human2.connect(maya)\n\n ps.binome.connect(binome)\n ps.cedric.connect(cedric)\n ps.michel.connect(michel)\n ps.caroline.connect(caroline)","def test_serialize(self):\n r = self.RNA(\"ugagg\")\n assert dumps(r)","def result(self):","def result(self):","def identifier(self):","def __repr__(self):\t\n\t\treturn arabicRepr.repr(self.__dict__);","def lro(self) -> global___Snippet.Lro:","def entrer(self):\n valeur = getattr(self.objet, self.attribut, None)\n if valeur is None:\n setattr(self.objet, self.attribut, [])","def get_aa (tRNA):\n\tpass","def custo(EstadoRestaUm, resultante):\n return 1","def __str__(self):\n return self.idPlanodeContas","def transform(self):","def decode(self, coded_set):","def carrega_endereco_tag_gne(self, tag):\r\n gne_dict = {\"EMPPK\":\"CONFIGURACAO\\EmpPK\",\r\n \"EMPCK\":\"CONFIGURACAO\\EmpCK\",\r\n \"MODELO\":\"CONFIGURACAO\\Modelo\",\r\n \"TIPONF\":\"CONFIGURACAO\\TipoNF\",\r\n \"TIPOAMBIENTE\":\"CONFIGURACAO\\TipoAmbiente\",\r\n \"TOKENSEFAZ\":\"CONFIGURACAO\\TokenSefaz\",\r\n \"IMPRESSAOCOMPLETA\":\"CONFIGURACAO\\ImpressaoCompleta\",\r\n \"CUF\":\"IDE\\cUF\",\r\n \"NNF\":\"IDE\\\\nNF\",\r\n \"SERIE\":\"IDE\\Serie\",\r\n \"CMUNFG\":\"IDE\\cMunFG\",\r\n \"INDPRES\":\"IDE\\indPres\",\r\n \"CNPJ\":\"EMIT\\CNPJ\",\r\n \"XNOME\":\"EMIT\\\\xNome\",\r\n \"XLGR\":\"EMIT\\ENDEREMIT\\\\xLgr\",\r\n \"NRO\":\"EMIT\\ENDEREMIT\\Nro\",\r\n \"XBAIRRO\":\"EMIT\\ENDEREMIT\\\\xBairro\",\r\n \"CMUN\":\"EMIT\\ENDEREMIT\\cMun\",\r\n \"XMUN\":\"EMIT\\ENDEREMIT\\\\xMun\",\r\n \"UF\":\"EMIT\\ENDEREMIT\\UF\",\r\n \"CEP\":\"EMIT\\ENDEREMIT\\CEP\",\r\n \"IE\":\"EMIT\\IE\",\r\n \"IMPRIMIR\":\"NFCE\\MSGPROMOCIONAL\\Imprimir\",\r\n \"TITULO\":\"NFCE\\MSGPROMOCIONAL\\Titulo\",\r\n \"MSGIMPOSTO\":\"NFCE\\MsgLeiDoImposto\"\r\n }\r\n\r\n if tag not in gne_dict:\r\n raise Exception(\"-40: Tag XML GNE_Framework nao encontrada.\")\r\n return gne_dict[tag]","def carrega_endereco_tag_daruma(self, tag):\r\n daruma_dict = {\"LOCALARQUIVOS\":['START','LocalArquivos'],\r\n \"LOCALARQUIVOSRELATORIOS\":['START','LocalArquivosRelatorios'],\r\n \"LOGTAMMAXMB\":['START','LogTamMaxMB'],\r\n\t\t \"MODOOBSERVER\":['START','ModoObserver'],\r\n \"PATHBIBLIOTECASAUXILIARES\":['START','PathBibliotecasAuxiliares'],\r\n \"PRODUTO\":['START','Produto'],\r\n \"THREADAOINICIAR\":['START','ThreadAoIniciar'],\r\n \"TIPOREGISTRO\":['START','TipoRegistro'],\r\n \"TERMICA\":['DUAL','Termica'],\r\n \"DUALTAMANHOBOBINA\":['DUAL','TamanhoBobina'],\r\n \"DUALPORTACOMUNICACAO\":['DUAL','PortaComunicacao'],\r\n \"DUALVELOCIDADE\":['DUAL','Velocidade'],\r\n \"ROTA1\":['DUAL','Rota1'],\r\n \"ROTA2\":['DUAL','Rota2'],\r\n \"ROTA3\":['DUAL','Rota3'],\r\n \"ROTA4\":['DUAL','Rota4'],\r\n \"ROTA5\":['DUAL','Rota5'],\r\n \"ATIVAROTA\":['DUAL','AtivaRota'],\r\n \"AJUSTARDATAHORA\":['NFCE','AjustarDataHora'],\r\n \"AVISOCONTINGENCIA\":['NFCE','AvisoContingencia'],\r\n \"AUDITORIA\":['NFCE','Auditoria'],\r\n \"ENCONTRARIMPRESSORA\":['NFCE','EncontrarImpressora'],\r\n\t\t \"PATHARQUIVOSCTGOFFLINE\":['NFCE','PathArquivosCtgOffline'],\r\n \"MARCAIMPRESSORA\":['NFCE','IMPRESSORA\\MarcaImpressora'],\r\n \"NFCETAMANHOBOBINA\":['NFCE','IMPRESSORA\\TamanhoBobina'], \r\n \"NFCEPORTACOMUNICACAO\":['NFCE','IMPRESSORA\\PortaComunicacao'], \r\n \"NFCEVELOCIDADE\":['NFCE','IMPRESSORA\\Velocidade']\r\n }\r\n #\"ENDERECOSERVIDOR\":['NFCE','EnderecoServidor'],\r\n\r\n #if tag.upper() not in [x.upper() for x in daruma_dict.keys()]:\r\n if tag.upper() not in daruma_dict:\r\n raise Exception(\"-40: Tag XML DarumaFramework nao encontrada.\")\r\n return daruma_dict[tag.upper()]","def decode(self, encoded):","def __init__(self, name_map):\n self.name_map = name_map\n self.read = gpd.read_file(self.name_map)\n self.read = self.read.replace({self.read[\"NOMBRE_DPT\"][32]:'SAN ANDRES',\n self.read[\"NOMBRE_DPT\"][2]:'BOGOTA'})\n self.ordenado = ordenar(self.read,\"NOMBRE_DPT\")","def __init__(self,couleur):\n if couleur == \"R\":\n self.couleur = 0\n if couleur == \"V\":\n self.couleur = 1\n if couleur == \"B\":\n self.couleur = 2\n if couleur not in {\"R\",\"V\",\"B\"}:\n raise Exception(\"La couleur doit être R, V ou B\")","def es_satisfecho_por(self, candidata):","def search_id(self,obj):\r\n ##### create the new id ###########\r\n #for x in self.objectValues('Image'):\r\n for x in obj:\r\n liste_id.append(str(x.id())[0:6])\r\n for digit0 in liste_digit:\r\n for digit1 in liste_digit:\r\n for digit2 in liste_digit:\r\n for digit3 in liste_digit:\r\n for digit4 in liste_digit:\r\n for digit5 in liste_digit:\r\n searched_dict=0\r\n searched=str(digit0)+str(digit1)+str(digit2)+str(digit3)+str(digit4)+str(digit5)\r\n if(self.toolbox.hasProperty('eigene_formate')):\r\n self_val=self.toolbox.getProperty('eigene_formate').split(',')\r\n for x in self_val:\r\n liste_val.append('_'+x+'.jpeg')\r\n for extension in liste_val:\r\n searched_extension=str(searched)\r\n if searched_extension in liste_id:\r\n searched_dict=searched_dict+1\r\n if searched_dict==0:\r\n return searched\r\n return ''","def build_allegato(self, **kw):\n\n # Image parameter value is required to be base64 encoded\n # I don't know how to verify if it's already encoded so DO NOT ENCODE! I do.\n #if 'Image' in kw:\n # kw['Image'] = b64encode(kw['Image'].data or '')\n\n return self.build_xml('AllegatoIn', **kw)","def degibber(self):","def __init__(self, nome):\n\n super().__init__(nome)\n self.preferencias = []\n self.qtd_preferencias_atendidas = 0","def alterar_gne_framework(self, tag, value):\r\n value = str(value)\r\n if not value:\r\n raise Exception(\"709 - Parametros insuficientes!\")\r\n\r\n key_tag = self.carrega_endereco_tag_gne(tag.upper())\r\n self.dll.regAlterarValor_NFCe_Daruma.argstypes = [\r\n c_char_p, c_char_p]\r\n self.dll.regAlterarValor_NFCe_Daruma.restype = c_int\r\n status = self.dll.regAlterarValor_NFCe_Daruma(key_tag, value)\r\n\r\n\tif status !=1:\r\n\t if status == -40:\r\n\t\traise Exception(\"-40: Tag XML GNE_Framework nao encontrada.\")\r\n return {tag: value}","def acquisizioneParametri(self):\n\n messaggio =''\n\n try: \n self.__rete = slugify(self.ui.nomeRete.text())\n # controllo se la lunghezza del nome inserito sia > di 5 caratteri\n if(len(self.__rete) < 5 or len(self.__rete) > 30):\n\n messaggio = 'err: inserimento Nome'\n raise NameError\n \n # controllo che il nome scelto sia univoco\n isPresent = self.__NNNameCheck()\n if(isPresent):\n messaggio = 'err: nome già utilizzato'\n raise NameError\n\n # controlli su numero layer e numero nodi che siano >= 1\n # e che siano rispettivamente <= 20 e <= 50\n self.__layer = int(self.ui.nLayer.text())\n if(self.__layer < 1):\n messaggio = 'err: numero layer < 1'\n raise ValueError\n elif(self.__layer >= 20):\n messaggio = 'err: numero layer > 20'\n raise ValueError\n\n self.__nodi = int(self.ui.nNodi.text())\n if(self.__nodi < 1):\n messaggio = 'err: numero nodi < 1'\n raise ValueError\n if(self.__nodi >= 50):\n messaggio = 'err: numero nodi > 50'\n raise ValueError\n\n # salvataggio della funzione scelta\n self.__funzione = self.ui.funzione.currentText()\n \n # controllo che la percentuale di Vs sia < 25%\n # e che la percentuale di Ts sia > 75%\n if(self.__percentuale < 25):\n messaggio = 'err: suddivisione'\n raise ValueError\n if (self.__percentuale > 75):\n messaggio = 'err: suddivisione'\n raise ValueError\n\n # controllo che sia stato scelto effettivamente un dataset\n if(len(self.__dataSet) == 0):\n messaggio = 'err: dataSet errato'\n raise NameError\n\n # setto il tasto caricamento di una rete non cliccabile\n self.ui.but_caricaRete.setEnabled(False)\n\n # cambio nome del tasto convalida\n self.ui.but_convalida.setText('confermato')\n self.ui.comunicazione.setText('')\n #abilito salvataggio\n self.ui.but_salva.setEnabled(True)\n\n # settandola a True permetto che il training venga effettuato\n # dato che i dati inseriti sono validi\n self.__convalida = True\n return True\n except:\n # in caso di eccezzioni faccio comparire il messaggio\n self.ui.comunicazione.setText(messaggio)\n return False","def marshal(self):\n ...","def autoid(self) -> str:","def autoid(self) -> str:","def __init__(self, nome, tipo):\n self.restaurant_name = nome\n self.cuisine_type = tipo","def fim_da_rodada(self, recompensa, m, numero_de_cacadores):\n #print('Jogador 4 {}'.format(self.historico[-1]))\n pass","def agregar_al_atril(self):\n self.atril.append(self.bolsa.tomar_bolsa())","def read_acbr(self):\n return self.ACBR","def _encode_structure(self):\n pass","def _encode_structure(self):\n pass","def __init__(self, ambiente, nome, img_aeronave=None):\n self.ambiente = ambiente\n self.nome = nome\n self.adicionar_aeronave(img_aeronave)","def make_codes(self):\n\t\troot = heapq.heappop(self.heap)#obtenemos la raiz del arbol\n\t\tcurrent_code = \"\"\n\t\tself.make_codes_helper(root, current_code)","def __init__(self,cont_acc):\n self.Mecanisme = cont_acc[0]\n self.Intentionnalite = cont_acc[1]\n self.Activite_trauma = cont_acc[2]\n self.Detail_activite = cont_acc[3]\n self.Lieu = cont_acc[4]\n self.Type_lieu = cont_acc[5]\n self.Detail_Type_lieu = cont_acc[6]\n self.Ejection_vehicule = cont_acc[7]\n self.Passager_decede_mm_vehicule = cont_acc[8]\n self.AGV = cont_acc[9]\n self.Incarceration = cont_acc[10]\n self.Duree_incarceration = cont_acc[11]\n self.Cin_NSP = cont_acc[12]\n self.Ecrase_projete = cont_acc[13]\n self.Chute = cont_acc[14]\n self.Blast = cont_acc[15]\n self.Isch_du_membre = cont_acc[16]\n self.Amputation = cont_acc[17]\n self.Bassin = cont_acc[18]","def inscricao(self):\n\n return True","def serialize(self):\n pass"],"string":"[\n \"def to_ir(self):\",\n \"def mezclar_bolsa(self):\",\n \"def __str__(self):\\n return self.idBaixasReceber\",\n \"def cliquer_sur_unité(self):\",\n \"def encode(category_main : ):\",\n \"def __init__(self,obj):\\n self.nature_libelle = obj['NatureLibelle']\\n self.ins_nom = obj['InsNom']\\n self.ins_numero_install = obj['InsNumeroInstall']\\n self.equipement_id = obj['EquipementId']\",\n \"def __str__(self):\\r\\n return self.afficherOBJ()\",\n \"def serialize(self):\",\n \"def convert(self) -> dict:\\n def get_triples_linker():\\n \\\"\\\"\\\"\\n Retrieve all of the triples linking phrases from the AMR object.\\n We use the Framenet words that are found in the AMR Object as the linker.\\n \\\"\\\"\\\"\\n triples_linkers = []\\n concepts = list(self.amr_obj.concepts())\\n\\n # Retrieve all concept that has the word ARG in it\\n for concept in concepts:\\n triple = self.amr_obj.triples(head=concept[0])\\n items = [item for item in triple if 'ARG' in item[1]]\\n if len(items) > 0:\\n triples_linkers.append(triple)\\n return triples_linkers\\n\\n def generate_triples():\\n\\n def fixing_annotation(key, n):\\n \\\"\\\"\\\"\\n Fixing some inconsistency in the annotation\\n \\\"\\\"\\\"\\n if key + '.' + n not in self.propbank:\\n key = key.replace('-', '_')\\n return key + '.' + n\\n\\n def is_agent(f_rel, rel_var):\\n \\\"\\\"\\\"\\n Checking whether the role is an agent (denoted by 'pag') or not\\n \\\"\\\"\\\"\\n # TODO: beside 'pag' is there any other role?\\n m = re.match(r'(.*)-(\\\\d*)$', rel_var)\\n key = m.group(1)\\n n = m.group(2)\\n\\n # some annotation does not have the correspondence frameset, just put false if found\\n if n == '00':\\n return False\\n\\n concept = fixing_annotation(key, n)\\n roleset = self.propbank[concept]\\n\\n m = re.match(r':ARG(.).*', f_rel[1])\\n n = int(m.group(1))\\n roles = roleset.getElementsByTagName('role')\\n\\n for role in roles:\\n if dict(role.attributes)['n'].value == str(n) and dict(role.attributes)['f'].value.lower() == 'pag':\\n return True\\n return False\\n\\n # Case 1: ARG\\n for triple_linker in self.triples_linkers:\\n triple = [None, triple_linker[0][0], []]\\n for rel in triple_linker:\\n if 'ARG' in rel[1] and 'of' not in rel[1]:\\n # check whether the propbank verb rel[0] and its argument rel[2] is an agent or not\\n if is_agent(rel, self.var2c[rel[0]].__str__()):\\n triple[0] = rel[2]\\n else:\\n triple[2].append(rel[2])\\n if not (triple[0] is None and triple[2] == []):\\n self.triples[triple[1]] = triple\\n\\n # Case 2: ARG-of\\n for triple_linker in self.triples_linkers:\\n for rel in triple_linker:\\n if 'ARG' in rel[1] and 'of' in rel[1]:\\n if rel[2] not in self.triples:\\n self.triples[rel[2]] = [None, rel[2], []]\\n if is_agent(rel, self.var2c[rel[2]].__str__()):\\n self.triples[rel[2]][0] = rel[0]\\n else:\\n self.triples[rel[2]][2].append(rel[0])\\n return self.triples\\n\\n self.triples_linkers = get_triples_linker()\\n return generate_triples()\",\n \"def cod(self):\\n raise NotImplementedError(\\\"base class called\\\")\",\n \"def load(self):\",\n \"def get_encoded(self):\\n pass\",\n \"def presenetCar():\",\n \"def afficherOBJ(self):\\r\\n str_abr = self.abr.afficher()## appel de l'affichage d'un ABR\\r\\n return str(self.debut)+':'+str(self.fin)+';'+str_abr ##concaténation du resultat\\r\",\n \"def __generate_code(self):\\n vouels = [\\\"A\\\", \\\"E\\\", \\\"I\\\", \\\"O\\\", \\\"U\\\"]\\n coding = self.surname\\n fiscal_code = \\\"\\\"\\n\\n # Generate first 6 letters of surname and name\\n for i in range(2):\\n for letter in coding:\\n if len(fiscal_code) == 3 * (i+1):\\n break\\n elif not letter in vouels:\\n #Use all upper letters\\n fiscal_code += letter.upper()\\n for letter in coding:\\n if len(fiscal_code) == 3 * (i+1):\\n break\\n elif letter in vouels:\\n fiscal_code += letter\\n while len(fiscal_code) < 3 * (i+1):\\n fiscal_code += \\\"X\\\"\\n coding = self.name\\n\\n # Add last 2 digits of year\\n fiscal_code += str(self.date.year)[-2:]\\n\\n # Associate month and letter\\n months = [\\\"A\\\", \\\"B\\\", \\\"C\\\", \\\"D\\\", \\\"E\\\",\\n \\\"H\\\", \\\"L\\\", \\\"M\\\", \\\"P\\\", \\\"R\\\", \\\"S\\\", \\\"T\\\"]\\n fiscal_code += months[self.date.month - 1]\\n\\n # Add day, plus 40 if female\\n if self.sex == \\\"FEMALE\\\":\\n fiscal_code += str(self.date.day + 40)\\n elif self.date.day < 10:\\n fiscal_code += \\\"0\\\" + str(self.date.day)\\n else:\\n fiscal_code += str(self.date.day)\\n\\n # Add some other characters to rappresent\\n fiscal_code += \\\"X\\\"\\n for i in range(3):\\n fiscal_code += str(i)\\n fiscal_code += \\\"X\\\"\\n\\n self.value = fiscal_code\",\n \"def __init__(self, code, codeInfo):\\r\\n self.Code = code #IRCode\\r\\n self.CodeInfo = codeInfo #IRCodeInfo\\r\",\n \"def encode(self): # pragma: no cover\\n pass\",\n \"def __str__(self):\\n return self.identificacao\",\n \"def __str__(self):\\n return self.identificacao\",\n \"def __str__(self):\\n return self.identificacao\",\n \"def _serialise(self):\\n # TODO (M Foley)\\n pass\",\n \"def ler_gne_framework(self, tag):\\r\\n if not tag:\\r\\n raise Exception(\\\"709 - Parametros insuficientes!\\\")\\r\\n\\r\\n value = \\\" \\\"*40\\r\\n key_tag = self.carrega_endereco_tag_gne(tag.upper())\\r\\n if not key_tag:\\r\\n raise Exception(\\\"-40: Tag XML nao encontrada.\\\")\\r\\n\\r\\n status = self.dll.regRetornarValor_NFCe_Daruma(key_tag, value)\\r\\n\\r\\n\\tif status !=1:\\r\\n if status == -40:\\r\\n raise Exception(\\\"-40: Tag XML nao encontrada.\\\")\\r\\n return {tag: value}\",\n \"def __repr__(self):\\n return f'ResidenciaModel(name={self.neighbourhood_group}, neighbourhood={self.room_type})'\",\n \"def __init__(self, marqueur, allele, hauteur, informatif):\\n\\n self.marqueur = marqueur\\n self.allele = allele\\n self.hauteur = hauteur\\n self.informatif = informatif\",\n \"def __str__(self):\\n line = ''\\n for linea in self.lista:\\n for atributo in linea:\\n if linea[atributo] != \\\"\\\":\\n line += atributo + \\\"=\\\" + \\\"'\\\" + linea[atributo] + \\\"'\\\" + '\\\\t'\\n line += '\\\\n'\\n return line\",\n \"def __str__(self):\\n return self.idLancamentosReceber\",\n \"def __str__(self):\\n return self.idBaixasPagar\",\n \"def mapping_stratum(download_files =True):\\r\\n # get code description _index \\r\\n ix_= AGSO_PROPERTIES['props_codes'].index('name')\\r\\n def mfunc_(d): \\r\\n \\\"\\\"\\\" Set individual layer in dict of properties \\\"\\\"\\\"\\r\\n _p= {c: k.lower() if c not in ('code', 'label', 'name') else k \\r\\n for c, k in zip(AGSO_PROPERTIES['props_codes'], d) }\\r\\n id_= d[ix_].replace('/', '_').replace(\\r\\n ' ', '_').replace('\\\"', '').replace(\\\"'\\\", '').lower()\\r\\n return id_, _p \\r\\n rock_and_structural_props =list()\\r\\n for agso_data in tuple(set_agso_properties(download_files)): \\r\\n # remove the header of the property file\\r\\n rock_and_structural_props.append(\\r\\n dict(map( lambda x: mfunc_(x), agso_data[1:])))\\r\\n \\r\\n return tuple(rock_and_structural_props)\",\n \"def comunicacion():\\n global dsgraph\\n global mss_cnt\\n\\n #Extraemos el mensaje y creamos un grafo con el\\n message= request.args['content']\\n gm = Graph()\\n gm.parse(data=message)\\n\\n msgdic = get_message_properties(gm)\\n\\n # Comprobamos que sea un mensaje FIPA ACL\\n if msgdic is None:\\n # Si no es, respondemos que no hemos entendido el mensaje\\n gr = build_message(Graph(), ACL['not-understood'], sender=InfoAgent.uri, msgcnt=mss_cnt)\\n else:\\n # Obtenemos la performativa\\n perf = msgdic['performative']\\n\\n if perf != ACL.request:\\n # Si no es un request, respondemos que no hemos entendido el mensaje\\n gr = build_message(Graph(), ACL['not-understood'], sender=InfoAgent.uri, msgcnt=mss_cnt)\\n else:\\n #Extraemos el objeto del contenido que ha de ser una accion de la ontologia de acciones del agente\\n # de registro\\n\\n # Averiguamos el tipo de la accion\\n if 'content' in msgdic:\\n content = msgdic['content']\\n accion = gm.value(subject=content, predicate= RDF.type)\\n\\n # Aqui realizariamos lo que pide la accion\\n\\n gt = buscar_transport(gm)\\n # Por ahora simplemente retornamos un Inform-done\\n gr = build_message(gt,\\n ACL['inform-done'],\\n sender=InfoAgent.uri,\\n msgcnt=mss_cnt,\\n receiver=msgdic['sender'],)\\n mss_cnt += 1\\n return gr.serialize(format='xml')\",\n \"def encoding(self) -> 'layout.Encoding':\",\n \"def exo2():\",\n \"def __init__(self):\\n self.aeropuertos = {}\",\n \"def agregar_bolsa(self, letra, cantidad):\",\n \"def init_podataka_sa_REST(self):\\n urlUredjaj = self.cfg.get_konfig_element('REST', 'uredjaj')\\n listaUredjaja = helper_funkcije.get_uredjaje_sa_REST(urlUredjaj)\\n #inicijalizacija svih dostupnih uredjaja\\n if listaUredjaja:\\n for uredjaj in listaUredjaja:\\n UNIT = Uredjaj(serial=uredjaj)\\n tekst = helper_funkcije.get_podatke_za_uredjaj_sa_REST(urlUredjaj, uredjaj)\\n #ako postoje podaci za uredjaj\\n if tekst:\\n try:\\n root = ET.fromstring(tekst)\\n #OSNOVNI PODACI UREDJAJA\\n try:\\n lokacija = helper_funkcije.get_lokaciju_uredjaja(urlUredjaj, uredjaj)\\n UNIT.set_lokacija(lokacija)\\n self.add_postaju(lokacija)\\n except Exception:\\n pass\\n try:\\n proizvodjac = root.find('modelUredjajaId/proizvodjacId/naziv').text\\n UNIT.set_proizvodjac(proizvodjac)\\n except Exception:\\n pass\\n try:\\n oznakaModela = root.find('modelUredjajaId/oznakaModela').text\\n UNIT.set_oznakaModela(oznakaModela)\\n except Exception:\\n pass\\n #ANALITICKA METODA\\n METODA = AnalitickaMetoda()\\n try:\\n ID = root.find('./modelUredjajaId/analitickeMetodeId/id').text\\n METODA.set_ID(ID)\\n except Exception:\\n pass\\n try:\\n norma = root.find('./modelUredjajaId/analitickeMetodeId/norma').text\\n METODA.set_norma(norma)\\n except Exception:\\n pass\\n try:\\n naziv = root.find('./modelUredjajaId/analitickeMetodeId/naziv').text\\n METODA.set_naziv(naziv)\\n except Exception:\\n pass\\n #elementi za racunanje...(Srz, Srs, rz, rmax...)\\n try:\\n metode = root.find('./modelUredjajaId/analitickeMetodeId')\\n for granica in metode.findall('dozvoljeneGraniceCollection'):\\n try:\\n oznaka = granica.find('./ispitneVelicine/oznaka').text\\n value = granica.find('max').text\\n if oznaka == 'o':\\n METODA.set_o(value)\\n #pokusaj dolaska do mjerne jedinice\\n jedinica = granica.find('./mjerneJediniceId/oznaka').text\\n jedinica = helper_funkcije.adapt_mjernu_jedinicu(jedinica)\\n METODA.set_jedinica(jedinica)\\n elif oznaka == 'Ec':\\n #za efikasnost konvertera treba i min granica\\n METODA.set_Ec_max(value)\\n minvalue = granica.find('min').text\\n METODA.set_Ec_min(minvalue)\\n else:\\n METODA.set_member[oznaka](value)\\n except Exception:\\n pass\\n except Exception:\\n pass\\n #ako metoda ne postoji na popisu... dodaj ju\\n self.set_novu_analiticku_metodu(ID, METODA)\\n #postavi analiticku metodu u uredjaj\\n UNIT.set_analitickaMetoda(METODA)\\n #KOMPONENTE UREDJAJA\\n try:\\n komponente = root.find('modelUredjajaId')\\n for komponenta in komponente.findall('komponentaCollection'):\\n KOMPONENTA = Komponenta()\\n try:\\n formula = komponenta.find('formula').text\\n KOMPONENTA.set_formula(formula)\\n naziv = komponenta.find('naziv').text\\n KOMPONENTA.set_naziv(naziv)\\n mjernaJedinica = komponenta.find('./mjerneJediniceId/oznaka').text\\n mjernaJedinica = helper_funkcije.adapt_mjernu_jedinicu(mjernaJedinica)\\n KOMPONENTA.set_jedinica(mjernaJedinica)\\n kv = komponenta.find('konvVUM').text\\n KOMPONENTA.set_kv(kv)\\n #dodaj komponentu u mapu\\n self.set_novu_komponentu(formula, KOMPONENTA)\\n #dodaj komponentu u uredjaj\\n UNIT.dodaj_komponentu(KOMPONENTA)\\n except Exception:\\n pass\\n except Exception:\\n pass\\n #postavi uredjaj u mapu sa serijskim uredjajima\\n self.dodaj_uredjaj(uredjaj, UNIT)\\n except Exception as err:\\n logging.warning(str(err))\\n self.create_local_cache()\\n else:\\n self.load_local_cache()\",\n \"def getArchivoVotacion():\",\n \"def encode(self, decoded):\",\n \"def _blob(self):\\n self.__rewrite_sldIdLst()\\n # # at least the following needs to be added before using\\n # # _reltype_ordering again for Presentation\\n # self.__rewrite_notesMasterIdLst()\\n # self.__rewrite_handoutMasterIdLst()\\n # self.__rewrite_sldMasterIdLst()\\n return super(Presentation, self)._blob\",\n \"def __unicode__(self):\\n return self.parroquia\",\n \"def __init__(self):\\n self.nombre_roues = 4\\n self.nombre_fauteils = 1\\n self.moteur = False\\n self.volant = True\",\n \"def convertion_binaire_arbre(self):\\r\\n binary_code = self.root.conversion_binaire('')\\r\\n binary_dict = {}\\r\\n binary_code = binary_code.strip().split(\\\"\\\\n\\\")\\r\\n for element in binary_code:\\r\\n binary_dict[element.split(\\\":\\\")[0]] = element.split(\\\":\\\")[1]\\r\\n return binary_dict\",\n \"def _encode_supplement(self):\",\n \"def _encode_supplement(self):\",\n \"def data(self):\",\n \"def decode(self): # pragma: no cover\\n pass\",\n \"def getRestricaoPlacaFinal(self):\\n import ast\\n restricao_placa_final = ast.literal_eval(self.soup.text).get('Rotation').get('desc')\\n return restricao_placa_final\",\n \"def comunicacion():\\n global dsgraph\\n global mss_cnt\\n\\n #Extraemos el mensaje y creamos un grafo con el\\n message= request.args['content']\\n gm = Graph()\\n gm.parse(data=message)\\n\\n msgdic = get_message_properties(gm)\\n\\n # Comprobamos que sea un mensaje FIPA ACL\\n if msgdic is None:\\n # Si no es, respondemos que no hemos entendido el mensaje\\n gr = build_message(Graph(), ACL['not-understood'], sender=InfoAgent.uri, msgcnt=mss_cnt)\\n else:\\n # Obtenemos la performativa\\n perf = msgdic['performative']\\n\\n if perf != ACL.request:\\n # Si no es un request, respondemos que no hemos entendido el mensaje\\n gr = build_message(Graph(), ACL['not-understood'], sender=InfoAgent.uri, msgcnt=mss_cnt)\\n else:\\n #Extraemos el objeto del contenido que ha de ser una accion de la ontologia de acciones del agente\\n # de registro\\n\\n # Averiguamos el tipo de la accion\\n if 'content' in msgdic:\\n content = msgdic['content']\\n accion = gm.value(subject=content, predicate= RDF.type)\\n\\n # Aqui realizariamos lo que pide la accion\\n\\n #Extraiem els parametres necessaris per realitzar la busqueda\\n paq = paquet[\\\"vacances\\\"]\\n\\n destination = gm.value(subject= paq, predicate= paquet.desti)\\n departureDate = gm.value(subject= paq, predicate= paquet.dep_date)\\n returnDate = gm.value(subject= paq, predicate= paquet.ret_date)\\n numAdults = gm.value(subject= paq, predicate= paquet.num_adults)\\n numChildren = gm.value(subject= paq, predicate= paquet.num_child)\\n centric = gm.value(subject= paq, predicate = paquet.centric)\\n category = gm.value(subject= paq, predicate = paquet.category)\\n minStars = gm.value(subject= paq, predicate = paquet.min_stars)\\n\\n gh = buscar_hotels(destination, departureDate, returnDate, numAdults, numChildren, centric, category, minStars)\\n\\n # Por ahora simplemente retornamos un Inform-done\\n gr = build_message(gh,\\n ACL['inform-done'],\\n sender=InfoAgent.uri,\\n msgcnt=mss_cnt,\\n receiver=msgdic['sender'],)\\n mss_cnt += 1\\n return gr.serialize(format='xml')\",\n \"def __init__():\\n self.placa = placa\",\n \"def CL(self):\",\n \"def __init__(self, nombre, socios):\\n self.__nombre = nombre\\n self.__socios = socios\\n self.__resultados = {'p1': '', 'p2': '', 'p3': '', 'p4': '', 'p5': '', 'p6': '', 'p7': ''}\",\n \"def load_data(self):\",\n \"def cargar_atril(self,lista,bolsa):\\n self.atril = lista\\n self.bolsa = bolsa\",\n \"def __init__(self, nom, prenom):\\n \\n self.nom = nom\\n self.prenom = prenom\\n self.age = 33\\n self._lieu_residence = \\\"Paris\\\" # Notez le souligné _ devant le nom\",\n \"def convert(self):\\n return\",\n \"def generate(self):\",\n \"def archivos_de_texto():\\n palabra = \\\"\\\" \\n palabras_candidatas = [] #lista donde se guardara las palabras candidatas de cada linea\\n palabra_cantidad = {} #diccionario con la palabra candidata de clave y las veces que esta repetida en cada texto de valor\\n with open(\\\"Cuentos.txt\\\",\\\"r\\\") as Cuentos: \\n for linea_Cuentos in Cuentos: #cada ciclo del for es una linea del texto\\n for caracter in linea_Cuentos: #cada ciclo del for es una caracter de la linea \\n if caracter.isalpha():\\n caracter = quitar_tilde_y_may(caracter) #se transformas caracteres mayusculas y tildes\\n palabra += caracter #cada caracter ira formando la palabra\\n if not caracter.isalpha():\\n if len(palabra) >= 5: #se analiza que la palabra tenga 5 o mas caracteres\\n palabras_candidatas.append(palabra) \\n palabra = \\\"\\\" #se vacia la palabra ya analizada\\n for palabra_en_lista in palabras_candidatas: #se introduce las palabras candidatas a un diccionario\\n if palabra_en_lista not in palabra_cantidad:\\n palabra_cantidad[palabra_en_lista] = [1,0,0]\\n else:\\n palabra_cantidad[palabra_en_lista] = [int(palabra_cantidad[palabra_en_lista][0]) + 1 , 0, 0]\\n palabras_candidatas = []\\n with open(\\\"La araña negra - tomo 1.txt\\\",\\\"r\\\") as La_arana_negra:#se repite el mismo proceso con los otros dos textos\\n for linea_Cuentos in La_arana_negra:\\n for caracter in linea_Cuentos:\\n if caracter.isalpha():\\n caracter = quitar_tilde_y_may(caracter)\\n palabra += caracter\\n if not caracter.isalpha():\\n if len(palabra) >= 5:\\n palabras_candidatas.append(palabra)\\n palabra = \\\"\\\"\\n for palabra_en_lista in palabras_candidatas:\\n if palabra_en_lista not in palabra_cantidad:\\n palabra_cantidad[palabra_en_lista] = [0,1,0]\\n else:\\n palabra_cantidad[palabra_en_lista] = [palabra_cantidad[palabra_en_lista][0] , int(palabra_cantidad[palabra_en_lista][1]) + 1, 0]\\n palabras_candidatas = [] \\n with open(\\\"Las 1000 Noches y 1 Noche.txt\\\",\\\"r\\\") as muchas_noches: \\n for linea_Cuentos in muchas_noches:\\n for caracter in linea_Cuentos:\\n if caracter.isalpha():\\n caracter = quitar_tilde_y_may(caracter)\\n palabra += caracter\\n if not caracter.isalpha():\\n if len(palabra) >= 5:\\n palabras_candidatas.append(palabra)\\n palabra = \\\"\\\"\\n for palabra_en_lista in palabras_candidatas:\\n if palabra_en_lista not in palabra_cantidad:\\n palabra_cantidad[palabra_en_lista] = [0,0,1]\\n else:\\n palabra_cantidad[palabra_en_lista] = [palabra_cantidad[palabra_en_lista][0] ,palabra_cantidad[palabra_en_lista][1], int(palabra_cantidad[palabra_en_lista][2]) + 1]\\n palabras_candidatas = [] \\n palabra_cantidad = dict(sorted(palabra_cantidad.items())) #se ordena el diccionario alfabeticamente\\n with open(\\\"palabras.csv\\\",\\\"w\\\") as palabras_csv: # se agrga el diccionario a un arcivo .csv\\n for palabra in palabra_cantidad:\\n palabras_csv.write(palabra)\\n palabras_csv.write(\\\",\\\")\\n palabras_csv.write(str(palabra_cantidad[palabra][0]))\\n palabras_csv.write(\\\",\\\")\\n palabras_csv.write(str(palabra_cantidad[palabra][1]))\\n palabras_csv.write(\\\",\\\")\\n palabras_csv.write(str(palabra_cantidad[palabra][2]))\\n palabras_csv.write(\\\"\\\\n\\\")\\n return palabra_cantidad\",\n \"def __init__(self, rouge_types):\\n\\n self.rouge_types = rouge_types\",\n \"def representarArbolAutomatico(self):\\n if not self.stepByStep:\\n print(\\\"Pintar paredes en auto\\\")\\n # Reinicio la matrix\\n self.reiniciarMatrix()\\n if self.arbol.raiz != None:\\n # Capturo todos los valores\\n for i in self.arbol.returnArbolComoVector():\\n \\n # Esta variable captura si se debe de pintar en x o y\\n xy = int(i[1])\\n cordenadas = i[0]\\n print(\\\"===========NODOS DEL ARBOL=============\\\")\\n print(i)\\n print(\\\"===========NODOS DEL ARBOL=============\\\")\\n # Se pinta en x o y?\\n if xy == 0:\\n self.crearParedX(int(cordenadas[0]), int(cordenadas[1]))\\n else:\\n self.crearParedY(int(cordenadas[0]), int(cordenadas[1]))\\n\\n self.esperarUnRato()\\n\\n print(\\\"========LISTO PARA PINTAR EL SIGUIENTE================\\\")\\n \\n else:\\n print(\\\"Arbol vacio\\\")\",\n \"def encode(rosMsg): #@NoSelf\",\n \"def entrada_aluno(matricula):\\n cod_curso = entrada_curso()\\n print('> Em que ano, mês e dia você entrou na UFC? (YYYY-MM-DD)')\\n data_de_ingresso = check.entrada('>>> ', check.data)\\n print('> Em que data você vai concluir seu curso? (YYYY-MM-DD)')\\n data_de_conclusao = check.entrada('>>> ', check.data)\\n\\n aluno = database.Aluno(matricula, data_de_conclusao,\\n data_de_ingresso, cod_curso)\\n return aluno\",\n \"def generar_red_neuronal (codigo, estadisticas=True):\\n \\n path = \\\"../data/entrenamiento/\\\" + str(codigo) + \\\"/\\\"\\n \\n f = open(path + \\\"data_neural_network_\\\" + str(codigo) + \\\".txt\\\")\\n cab = str(f.readline())[:-1]\\n cab = cab.replace(\\\"'\\\",\\\"\\\")\\n cab = cab.replace(\\\" \\\",\\\"\\\")\\n cabeceras = cab[1:-1].split(\\\",\\\")\\n l_etiquetas = str(f.readline())[:-1].split(\\\",\\\")\\n atributos = str(f.readline())[:-1].split(\\\",,\\\")\\n f.close()\\n\\n l_atributos = []\\n for atributo in atributos:\\n l_atributos.append(atributo.split(\\\",\\\"))\\n\\n etiquetas = set(l_etiquetas) \\n clases = sorted(list(etiquetas))\\n \\n l_atributos = np.array(l_atributos, \\\"float32\\\")\\n l_etiquetas = np.array(l_etiquetas, \\\"float32\\\")\\n \\n\\n #Separamos los datos que vamos a utilizar de entrenamiento y para realizar el test\\n #datos de pruebas (0.25) de los de entrenamiento (0.75)\\n X_train, X_test, y_train, y_test = train_test_split(l_atributos,l_etiquetas,test_size = 0.25,random_state = 0)\\n\\n #Creamos la red neuronal \\n red = MLPClassifier(max_iter=100000, hidden_layer_sizes=(50,25))\\n #Entrenamos la red neuronal\\n red.fit(X_train, y_train)\\n\\n #Predicion de los resultados del bloque test\\n y_pred = red.predict(X_test)\\n #Matriz de confusion\\n cm = confusion_matrix(y_test, y_pred)\\n #Reportes\\n report = classification_report(y_test, y_pred) \\n\\n\\n\\n if estadisticas == True:\\n f=open(path + \\\"export_neural_network_statistics_\\\" + str(codigo) + \\\".txt\\\",\\\"w\\\") \\n f.write(\\\"************************ CLASS *************************\\\\n\\\")\\n for i in range(len(clases)):\\n f.write(str(clases[i]) + \\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\\n\\\")\\n f.write(\\\"********************** FEATURES **********************\\\\n\\\")\\n for i in range(len(cabeceras[:-1])):\\n f.write(str(cabeceras[i]) + \\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\\n\\\")\\n f.write(\\\"************************ SCORE *************************\\\\n\\\")\\n f.write(\\\"With Test data: \\\" + str(red.score(X_test, y_test)) + \\\"\\\\n\\\")\\n f.write(\\\"With Training data: \\\" + str(red.score(X_train, y_train)) + \\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\\n\\\")\\n f.write(\\\"****************** CONFUSION MATRIX ********************\\\\n\\\")\\n if len(clases)==2:\\n f.write(\\\"\\\\t0\\\\t1\\\\n\\\")\\n f.write(\\\"---------------------\\\\n\\\")\\n f.write(\\\"0 |\\\\t\\\"+ str(cm[0][0]) +\\\"\\\\t\\\"+ str(cm[0][1]) +\\\"\\\\n\\\")\\n f.write(\\\"1 |\\\\t\\\"+ str(cm[1][0]) +\\\"\\\\t\\\"+ str(cm[1][1]) +\\\"\\\\n\\\")\\n if len(clases)==3:\\n f.write(\\\"\\\\t0\\\\t1\\\\t2\\\\n\\\")\\n f.write(\\\"--------------------------------\\\\n\\\")\\n f.write(\\\"0 |\\\\t\\\"+ str(cm[0][0]) +\\\"\\\\t\\\"+ str(cm[0][1]) +\\\"\\\\t\\\"+ str(cm[0][2]) +\\\"\\\\n\\\")\\n f.write(\\\"1 |\\\\t\\\"+ str(cm[1][0]) +\\\"\\\\t\\\"+ str(cm[1][1]) +\\\"\\\\t\\\"+ str(cm[1][2]) +\\\"\\\\n\\\")\\n f.write(\\\"2 |\\\\t\\\"+ str(cm[2][0]) +\\\"\\\\t\\\"+ str(cm[2][1]) +\\\"\\\\t\\\"+ str(cm[2][2]) +\\\"\\\\n\\\")\\n if len(clases)==4:\\n f.write(\\\"\\\\t0\\\\t1\\\\t2\\\\t3\\\\n\\\")\\n f.write(\\\"----------------------------------------------\\\\n\\\")\\n f.write(\\\"0 |\\\\t\\\"+ str(cm[0][0]) +\\\"\\\\t\\\"+ str(cm[0][1]) +\\\"\\\\t\\\"+ str(cm[0][2]) +\\\"\\\\t\\\"+ str(cm[0][3]) +\\\"\\\\n\\\")\\n f.write(\\\"1 |\\\\t\\\"+ str(cm[1][0]) +\\\"\\\\t\\\"+ str(cm[1][1]) +\\\"\\\\t\\\"+ str(cm[1][2]) +\\\"\\\\t\\\"+ str(cm[1][3]) +\\\"\\\\n\\\")\\n f.write(\\\"2 |\\\\t\\\"+ str(cm[2][0]) +\\\"\\\\t\\\"+ str(cm[2][1]) +\\\"\\\\t\\\"+ str(cm[2][2]) +\\\"\\\\t\\\"+ str(cm[2][3]) +\\\"\\\\n\\\")\\n f.write(\\\"3 |\\\\t\\\"+ str(cm[3][0]) +\\\"\\\\t\\\"+ str(cm[3][1]) +\\\"\\\\t\\\"+ str(cm[3][2]) +\\\"\\\\t\\\"+ str(cm[3][3]) +\\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\\n\\\")\\n f.write(\\\"************************ REPORT ***********************\\\\n\\\")\\n f.write(report)\\n f.close()\\n \\n print(str(codigo) + \\\": neural network created\\\") \\n return (red, red.score(X_test, y_test))\",\n \"def _regr_basic():\",\n \"def parse(self):\",\n \"def init_data():\\n ps = Planete_Solidaire(name=\\\"Planète Solidaire\\\").save()\\n\\n maya = Human4j(\\n firstname='Maya',\\n lastname='Hannachi',\\n number='0620902819',\\n email='maya.hannachi@epita.fr',\\n school='EPITA'\\n ).save()\\n mailinh = Human4j(\\n firstname='Mai-Linh',\\n lastname='Lannes',\\n number='0612632032',\\n email='mai-linh.lannes@epita.fr',\\n school='EPITA'\\n ).save()\\n michel = Human4j(\\n firstname='Michel',\\n lastname='Sasson',\\n number='0662739612',\\n email='michel.sasson@epita.fr',\\n school='EPITA'\\n ).save()\\n cedric = Human4j(\\n firstname='Cédric',\\n lastname='Joly',\\n number='',\\n email='cedric.joly@epita.fr',\\n school='EPITA'\\n ).save()\\n caroline = Human4j(\\n firstname='Caroline',\\n lastname='De Paoli',\\n number='',\\n email='caroline.depaoli@isg.fr',\\n school='ISG'\\n ).save()\\n\\n binome = Binome4j().save()\\n binome.human1.connect(mailinh)\\n binome.human2.connect(maya)\\n\\n ps.binome.connect(binome)\\n ps.cedric.connect(cedric)\\n ps.michel.connect(michel)\\n ps.caroline.connect(caroline)\",\n \"def test_serialize(self):\\n r = self.RNA(\\\"ugagg\\\")\\n assert dumps(r)\",\n \"def result(self):\",\n \"def result(self):\",\n \"def identifier(self):\",\n \"def __repr__(self):\\t\\n\\t\\treturn arabicRepr.repr(self.__dict__);\",\n \"def lro(self) -> global___Snippet.Lro:\",\n \"def entrer(self):\\n valeur = getattr(self.objet, self.attribut, None)\\n if valeur is None:\\n setattr(self.objet, self.attribut, [])\",\n \"def get_aa (tRNA):\\n\\tpass\",\n \"def custo(EstadoRestaUm, resultante):\\n return 1\",\n \"def __str__(self):\\n return self.idPlanodeContas\",\n \"def transform(self):\",\n \"def decode(self, coded_set):\",\n \"def carrega_endereco_tag_gne(self, tag):\\r\\n gne_dict = {\\\"EMPPK\\\":\\\"CONFIGURACAO\\\\EmpPK\\\",\\r\\n \\\"EMPCK\\\":\\\"CONFIGURACAO\\\\EmpCK\\\",\\r\\n \\\"MODELO\\\":\\\"CONFIGURACAO\\\\Modelo\\\",\\r\\n \\\"TIPONF\\\":\\\"CONFIGURACAO\\\\TipoNF\\\",\\r\\n \\\"TIPOAMBIENTE\\\":\\\"CONFIGURACAO\\\\TipoAmbiente\\\",\\r\\n \\\"TOKENSEFAZ\\\":\\\"CONFIGURACAO\\\\TokenSefaz\\\",\\r\\n \\\"IMPRESSAOCOMPLETA\\\":\\\"CONFIGURACAO\\\\ImpressaoCompleta\\\",\\r\\n \\\"CUF\\\":\\\"IDE\\\\cUF\\\",\\r\\n \\\"NNF\\\":\\\"IDE\\\\\\\\nNF\\\",\\r\\n \\\"SERIE\\\":\\\"IDE\\\\Serie\\\",\\r\\n \\\"CMUNFG\\\":\\\"IDE\\\\cMunFG\\\",\\r\\n \\\"INDPRES\\\":\\\"IDE\\\\indPres\\\",\\r\\n \\\"CNPJ\\\":\\\"EMIT\\\\CNPJ\\\",\\r\\n \\\"XNOME\\\":\\\"EMIT\\\\\\\\xNome\\\",\\r\\n \\\"XLGR\\\":\\\"EMIT\\\\ENDEREMIT\\\\\\\\xLgr\\\",\\r\\n \\\"NRO\\\":\\\"EMIT\\\\ENDEREMIT\\\\Nro\\\",\\r\\n \\\"XBAIRRO\\\":\\\"EMIT\\\\ENDEREMIT\\\\\\\\xBairro\\\",\\r\\n \\\"CMUN\\\":\\\"EMIT\\\\ENDEREMIT\\\\cMun\\\",\\r\\n \\\"XMUN\\\":\\\"EMIT\\\\ENDEREMIT\\\\\\\\xMun\\\",\\r\\n \\\"UF\\\":\\\"EMIT\\\\ENDEREMIT\\\\UF\\\",\\r\\n \\\"CEP\\\":\\\"EMIT\\\\ENDEREMIT\\\\CEP\\\",\\r\\n \\\"IE\\\":\\\"EMIT\\\\IE\\\",\\r\\n \\\"IMPRIMIR\\\":\\\"NFCE\\\\MSGPROMOCIONAL\\\\Imprimir\\\",\\r\\n \\\"TITULO\\\":\\\"NFCE\\\\MSGPROMOCIONAL\\\\Titulo\\\",\\r\\n \\\"MSGIMPOSTO\\\":\\\"NFCE\\\\MsgLeiDoImposto\\\"\\r\\n }\\r\\n\\r\\n if tag not in gne_dict:\\r\\n raise Exception(\\\"-40: Tag XML GNE_Framework nao encontrada.\\\")\\r\\n return gne_dict[tag]\",\n \"def carrega_endereco_tag_daruma(self, tag):\\r\\n daruma_dict = {\\\"LOCALARQUIVOS\\\":['START','LocalArquivos'],\\r\\n \\\"LOCALARQUIVOSRELATORIOS\\\":['START','LocalArquivosRelatorios'],\\r\\n \\\"LOGTAMMAXMB\\\":['START','LogTamMaxMB'],\\r\\n\\t\\t \\\"MODOOBSERVER\\\":['START','ModoObserver'],\\r\\n \\\"PATHBIBLIOTECASAUXILIARES\\\":['START','PathBibliotecasAuxiliares'],\\r\\n \\\"PRODUTO\\\":['START','Produto'],\\r\\n \\\"THREADAOINICIAR\\\":['START','ThreadAoIniciar'],\\r\\n \\\"TIPOREGISTRO\\\":['START','TipoRegistro'],\\r\\n \\\"TERMICA\\\":['DUAL','Termica'],\\r\\n \\\"DUALTAMANHOBOBINA\\\":['DUAL','TamanhoBobina'],\\r\\n \\\"DUALPORTACOMUNICACAO\\\":['DUAL','PortaComunicacao'],\\r\\n \\\"DUALVELOCIDADE\\\":['DUAL','Velocidade'],\\r\\n \\\"ROTA1\\\":['DUAL','Rota1'],\\r\\n \\\"ROTA2\\\":['DUAL','Rota2'],\\r\\n \\\"ROTA3\\\":['DUAL','Rota3'],\\r\\n \\\"ROTA4\\\":['DUAL','Rota4'],\\r\\n \\\"ROTA5\\\":['DUAL','Rota5'],\\r\\n \\\"ATIVAROTA\\\":['DUAL','AtivaRota'],\\r\\n \\\"AJUSTARDATAHORA\\\":['NFCE','AjustarDataHora'],\\r\\n \\\"AVISOCONTINGENCIA\\\":['NFCE','AvisoContingencia'],\\r\\n \\\"AUDITORIA\\\":['NFCE','Auditoria'],\\r\\n \\\"ENCONTRARIMPRESSORA\\\":['NFCE','EncontrarImpressora'],\\r\\n\\t\\t \\\"PATHARQUIVOSCTGOFFLINE\\\":['NFCE','PathArquivosCtgOffline'],\\r\\n \\\"MARCAIMPRESSORA\\\":['NFCE','IMPRESSORA\\\\MarcaImpressora'],\\r\\n \\\"NFCETAMANHOBOBINA\\\":['NFCE','IMPRESSORA\\\\TamanhoBobina'], \\r\\n \\\"NFCEPORTACOMUNICACAO\\\":['NFCE','IMPRESSORA\\\\PortaComunicacao'], \\r\\n \\\"NFCEVELOCIDADE\\\":['NFCE','IMPRESSORA\\\\Velocidade']\\r\\n }\\r\\n #\\\"ENDERECOSERVIDOR\\\":['NFCE','EnderecoServidor'],\\r\\n\\r\\n #if tag.upper() not in [x.upper() for x in daruma_dict.keys()]:\\r\\n if tag.upper() not in daruma_dict:\\r\\n raise Exception(\\\"-40: Tag XML DarumaFramework nao encontrada.\\\")\\r\\n return daruma_dict[tag.upper()]\",\n \"def decode(self, encoded):\",\n \"def __init__(self, name_map):\\n self.name_map = name_map\\n self.read = gpd.read_file(self.name_map)\\n self.read = self.read.replace({self.read[\\\"NOMBRE_DPT\\\"][32]:'SAN ANDRES',\\n self.read[\\\"NOMBRE_DPT\\\"][2]:'BOGOTA'})\\n self.ordenado = ordenar(self.read,\\\"NOMBRE_DPT\\\")\",\n \"def __init__(self,couleur):\\n if couleur == \\\"R\\\":\\n self.couleur = 0\\n if couleur == \\\"V\\\":\\n self.couleur = 1\\n if couleur == \\\"B\\\":\\n self.couleur = 2\\n if couleur not in {\\\"R\\\",\\\"V\\\",\\\"B\\\"}:\\n raise Exception(\\\"La couleur doit être R, V ou B\\\")\",\n \"def es_satisfecho_por(self, candidata):\",\n \"def search_id(self,obj):\\r\\n ##### create the new id ###########\\r\\n #for x in self.objectValues('Image'):\\r\\n for x in obj:\\r\\n liste_id.append(str(x.id())[0:6])\\r\\n for digit0 in liste_digit:\\r\\n for digit1 in liste_digit:\\r\\n for digit2 in liste_digit:\\r\\n for digit3 in liste_digit:\\r\\n for digit4 in liste_digit:\\r\\n for digit5 in liste_digit:\\r\\n searched_dict=0\\r\\n searched=str(digit0)+str(digit1)+str(digit2)+str(digit3)+str(digit4)+str(digit5)\\r\\n if(self.toolbox.hasProperty('eigene_formate')):\\r\\n self_val=self.toolbox.getProperty('eigene_formate').split(',')\\r\\n for x in self_val:\\r\\n liste_val.append('_'+x+'.jpeg')\\r\\n for extension in liste_val:\\r\\n searched_extension=str(searched)\\r\\n if searched_extension in liste_id:\\r\\n searched_dict=searched_dict+1\\r\\n if searched_dict==0:\\r\\n return searched\\r\\n return ''\",\n \"def build_allegato(self, **kw):\\n\\n # Image parameter value is required to be base64 encoded\\n # I don't know how to verify if it's already encoded so DO NOT ENCODE! I do.\\n #if 'Image' in kw:\\n # kw['Image'] = b64encode(kw['Image'].data or '')\\n\\n return self.build_xml('AllegatoIn', **kw)\",\n \"def degibber(self):\",\n \"def __init__(self, nome):\\n\\n super().__init__(nome)\\n self.preferencias = []\\n self.qtd_preferencias_atendidas = 0\",\n \"def alterar_gne_framework(self, tag, value):\\r\\n value = str(value)\\r\\n if not value:\\r\\n raise Exception(\\\"709 - Parametros insuficientes!\\\")\\r\\n\\r\\n key_tag = self.carrega_endereco_tag_gne(tag.upper())\\r\\n self.dll.regAlterarValor_NFCe_Daruma.argstypes = [\\r\\n c_char_p, c_char_p]\\r\\n self.dll.regAlterarValor_NFCe_Daruma.restype = c_int\\r\\n status = self.dll.regAlterarValor_NFCe_Daruma(key_tag, value)\\r\\n\\r\\n\\tif status !=1:\\r\\n\\t if status == -40:\\r\\n\\t\\traise Exception(\\\"-40: Tag XML GNE_Framework nao encontrada.\\\")\\r\\n return {tag: value}\",\n \"def acquisizioneParametri(self):\\n\\n messaggio =''\\n\\n try: \\n self.__rete = slugify(self.ui.nomeRete.text())\\n # controllo se la lunghezza del nome inserito sia > di 5 caratteri\\n if(len(self.__rete) < 5 or len(self.__rete) > 30):\\n\\n messaggio = 'err: inserimento Nome'\\n raise NameError\\n \\n # controllo che il nome scelto sia univoco\\n isPresent = self.__NNNameCheck()\\n if(isPresent):\\n messaggio = 'err: nome già utilizzato'\\n raise NameError\\n\\n # controlli su numero layer e numero nodi che siano >= 1\\n # e che siano rispettivamente <= 20 e <= 50\\n self.__layer = int(self.ui.nLayer.text())\\n if(self.__layer < 1):\\n messaggio = 'err: numero layer < 1'\\n raise ValueError\\n elif(self.__layer >= 20):\\n messaggio = 'err: numero layer > 20'\\n raise ValueError\\n\\n self.__nodi = int(self.ui.nNodi.text())\\n if(self.__nodi < 1):\\n messaggio = 'err: numero nodi < 1'\\n raise ValueError\\n if(self.__nodi >= 50):\\n messaggio = 'err: numero nodi > 50'\\n raise ValueError\\n\\n # salvataggio della funzione scelta\\n self.__funzione = self.ui.funzione.currentText()\\n \\n # controllo che la percentuale di Vs sia < 25%\\n # e che la percentuale di Ts sia > 75%\\n if(self.__percentuale < 25):\\n messaggio = 'err: suddivisione'\\n raise ValueError\\n if (self.__percentuale > 75):\\n messaggio = 'err: suddivisione'\\n raise ValueError\\n\\n # controllo che sia stato scelto effettivamente un dataset\\n if(len(self.__dataSet) == 0):\\n messaggio = 'err: dataSet errato'\\n raise NameError\\n\\n # setto il tasto caricamento di una rete non cliccabile\\n self.ui.but_caricaRete.setEnabled(False)\\n\\n # cambio nome del tasto convalida\\n self.ui.but_convalida.setText('confermato')\\n self.ui.comunicazione.setText('')\\n #abilito salvataggio\\n self.ui.but_salva.setEnabled(True)\\n\\n # settandola a True permetto che il training venga effettuato\\n # dato che i dati inseriti sono validi\\n self.__convalida = True\\n return True\\n except:\\n # in caso di eccezzioni faccio comparire il messaggio\\n self.ui.comunicazione.setText(messaggio)\\n return False\",\n \"def marshal(self):\\n ...\",\n \"def autoid(self) -> str:\",\n \"def autoid(self) -> str:\",\n \"def __init__(self, nome, tipo):\\n self.restaurant_name = nome\\n self.cuisine_type = tipo\",\n \"def fim_da_rodada(self, recompensa, m, numero_de_cacadores):\\n #print('Jogador 4 {}'.format(self.historico[-1]))\\n pass\",\n \"def agregar_al_atril(self):\\n self.atril.append(self.bolsa.tomar_bolsa())\",\n \"def read_acbr(self):\\n return self.ACBR\",\n \"def _encode_structure(self):\\n pass\",\n \"def _encode_structure(self):\\n pass\",\n \"def __init__(self, ambiente, nome, img_aeronave=None):\\n self.ambiente = ambiente\\n self.nome = nome\\n self.adicionar_aeronave(img_aeronave)\",\n \"def make_codes(self):\\n\\t\\troot = heapq.heappop(self.heap)#obtenemos la raiz del arbol\\n\\t\\tcurrent_code = \\\"\\\"\\n\\t\\tself.make_codes_helper(root, current_code)\",\n \"def __init__(self,cont_acc):\\n self.Mecanisme = cont_acc[0]\\n self.Intentionnalite = cont_acc[1]\\n self.Activite_trauma = cont_acc[2]\\n self.Detail_activite = cont_acc[3]\\n self.Lieu = cont_acc[4]\\n self.Type_lieu = cont_acc[5]\\n self.Detail_Type_lieu = cont_acc[6]\\n self.Ejection_vehicule = cont_acc[7]\\n self.Passager_decede_mm_vehicule = cont_acc[8]\\n self.AGV = cont_acc[9]\\n self.Incarceration = cont_acc[10]\\n self.Duree_incarceration = cont_acc[11]\\n self.Cin_NSP = cont_acc[12]\\n self.Ecrase_projete = cont_acc[13]\\n self.Chute = cont_acc[14]\\n self.Blast = cont_acc[15]\\n self.Isch_du_membre = cont_acc[16]\\n self.Amputation = cont_acc[17]\\n self.Bassin = cont_acc[18]\",\n \"def inscricao(self):\\n\\n return True\",\n \"def serialize(self):\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5959136","0.5499816","0.54604596","0.5433409","0.53827584","0.52883506","0.5285676","0.5262863","0.5205403","0.5198016","0.51858664","0.5181811","0.5152689","0.51158124","0.5115277","0.510677","0.5100671","0.50992584","0.50992584","0.50992584","0.5079031","0.5058076","0.50558406","0.50501984","0.5040804","0.5021594","0.50180304","0.5015311","0.5010569","0.50104636","0.50025856","0.499602","0.4984474","0.49542898","0.49535805","0.49327064","0.49240816","0.49185354","0.4905114","0.4902317","0.49014595","0.49014595","0.48692596","0.48683077","0.48570922","0.48465705","0.4838257","0.4833745","0.4825244","0.48121887","0.4808683","0.48050612","0.48000827","0.47957018","0.4795273","0.47943455","0.47914264","0.47865534","0.477258","0.47694573","0.47594205","0.47565743","0.47542658","0.47520074","0.47519404","0.47519404","0.47467768","0.47462806","0.4742574","0.47414863","0.47376645","0.47355875","0.4727351","0.47269782","0.47261584","0.47187555","0.47095498","0.4707949","0.4707029","0.47066423","0.4702868","0.47006476","0.47004184","0.46907073","0.46898994","0.4686547","0.46840474","0.46718577","0.4666892","0.4666892","0.46666095","0.4666055","0.466449","0.46641842","0.46580973","0.46580973","0.4655204","0.4653906","0.46499592","0.46478617","0.46478"],"string":"[\n \"0.5959136\",\n \"0.5499816\",\n \"0.54604596\",\n \"0.5433409\",\n \"0.53827584\",\n \"0.52883506\",\n \"0.5285676\",\n \"0.5262863\",\n \"0.5205403\",\n \"0.5198016\",\n \"0.51858664\",\n \"0.5181811\",\n \"0.5152689\",\n \"0.51158124\",\n \"0.5115277\",\n \"0.510677\",\n \"0.5100671\",\n \"0.50992584\",\n \"0.50992584\",\n \"0.50992584\",\n \"0.5079031\",\n \"0.5058076\",\n \"0.50558406\",\n \"0.50501984\",\n \"0.5040804\",\n \"0.5021594\",\n \"0.50180304\",\n \"0.5015311\",\n \"0.5010569\",\n \"0.50104636\",\n \"0.50025856\",\n \"0.499602\",\n \"0.4984474\",\n \"0.49542898\",\n \"0.49535805\",\n \"0.49327064\",\n \"0.49240816\",\n \"0.49185354\",\n \"0.4905114\",\n \"0.4902317\",\n \"0.49014595\",\n \"0.49014595\",\n \"0.48692596\",\n \"0.48683077\",\n \"0.48570922\",\n \"0.48465705\",\n \"0.4838257\",\n \"0.4833745\",\n \"0.4825244\",\n \"0.48121887\",\n \"0.4808683\",\n \"0.48050612\",\n \"0.48000827\",\n \"0.47957018\",\n \"0.4795273\",\n \"0.47943455\",\n \"0.47914264\",\n \"0.47865534\",\n \"0.477258\",\n \"0.47694573\",\n \"0.47594205\",\n \"0.47565743\",\n \"0.47542658\",\n \"0.47520074\",\n \"0.47519404\",\n \"0.47519404\",\n \"0.47467768\",\n \"0.47462806\",\n \"0.4742574\",\n \"0.47414863\",\n \"0.47376645\",\n \"0.47355875\",\n \"0.4727351\",\n \"0.47269782\",\n \"0.47261584\",\n \"0.47187555\",\n \"0.47095498\",\n \"0.4707949\",\n \"0.4707029\",\n \"0.47066423\",\n \"0.4702868\",\n \"0.47006476\",\n \"0.47004184\",\n \"0.46907073\",\n \"0.46898994\",\n \"0.4686547\",\n \"0.46840474\",\n \"0.46718577\",\n \"0.4666892\",\n \"0.4666892\",\n \"0.46666095\",\n \"0.4666055\",\n \"0.466449\",\n \"0.46641842\",\n \"0.46580973\",\n \"0.46580973\",\n \"0.4655204\",\n \"0.4653906\",\n \"0.46499592\",\n \"0.46478617\",\n \"0.46478\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":18693,"cells":{"query":{"kind":"string","value":"Initializes a storage manager instance."},"document":{"kind":"string","value":"def __init__(self, app):\n self.app = app\n self.config = app.config['FILE_STORAGE']\n self.secur = app.config['SECURITY_MANAGEMENT']['content']\n if self.config['type'] == 's3':\n # Boto s3 instance\n if self.config['id'] != '' and self.config['key'] != '':\n self.s3 = boto3.resource('s3', aws_access_key_id=self.config['id'], aws_secret_access_key=self.config['key'], region_name=self.config['location'])\n else:\n self.s3 = boto3.resource('s3')\n # S3 bucket location\n try:\n self.bucket = self.config['name']\n except:\n self.bucket = \"\"\n elif self.config['type'] == 'filesystem':\n self.storage_path = '{0}{1}'.format(self.config['location'], self.config['name'])\n if not os.path.exists(self.storage_path):\n os.makedirs(self.storage_path)\n os.makedirs('{0}/corr-bundles'.format(self.storage_path))\n os.makedirs('{0}/corr-files'.format(self.storage_path))\n os.makedirs('{0}/corr-logos'.format(self.storage_path))\n os.makedirs('{0}/corr-outputs'.format(self.storage_path))\n os.makedirs('{0}/corr-pictures'.format(self.storage_path))\n os.makedirs('{0}/corr-resources'.format(self.storage_path))\n elif self.config['type'] == 'mdcs': # TODO\n pass\n elif self.config['type'] == 'ftp' or self.config['type'] == 'sftp' : # TODO\n pass"},"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 __init__(self):\n config = self.read_config()\n self.deployment = config['deployment']\n self.deployment_config = config[self.deployment]\n logger.info(f'Initializing storage client with the {self.deployment} deployment config {pformat(self.deployment_config)}')\n\n # get the MLOS config from the user else default it from the deployment config file\n # self.mlos_config = config['MLOS']\n # logger.info(f'Initializing storage client with the MLOS config {pformat(self.mlos_config)}')\n\n # setup the mount path\n if self.deployment == \"LOCAL\":\n self.mount_dir = self.setup_mount()\n logger.info(f'Mount directory setup completed: {self.mount_dir}')","def init(self):\n self._service_store = ServiceStore(self.driver, self.network)\n self._emulator = NetworkEmulator(self.store, self.driver)","def __init__(\n self, storage_path: str, block_size: Tuple[int, int, int], **kwargs\n ) -> None:\n self.name = \"FilesystemStorageManager\"\n if \"next_layer\" in kwargs:\n self._next = kwargs[\"next_layer\"]\n self.is_terminal = False\n else:\n self.is_terminal = True\n self.storage_path = storage_path\n self.block_size = block_size\n self._cache = kwargs.get(\"cache\", True)\n\n self.fs = ({\"h5\": H5FileInterface}.get(kwargs.get(\"preferred_format\", \"h5\")))(\n self.storage_path\n )","def __init__(self, agent = None, region = None, settings = None, message_handler = None, events_handler = None):\n super(ObjectManager, self).__init__(agent, settings)\n self.region = region\n\n # the object store consists of a list\n # of Object() instances\n self.object_store = []\n\n # the avatar store consists of a list\n # of Avatar() instances\n self.avatar_store = []\n\n # other useful things\n self.helpers = Helpers()\n\n self.message_handler = message_handler\n\n if self.settings.LOG_VERBOSE: logger.info(\"Initializing object storage\")","def __init_subclass__(cls):\n available_storages.append({\n \"name\": cls.__name__,\n \"extensions\": cls.extensions,\n \"storage\": cls,\n })","def _init_storage(self):\n if self._ is None:\n self._ = Parameters(self)","def __init__(self):\n\n self.storage: list = Storage()\n\n # Start for get data in API and set in storage\n self._set_proxies_in_storage()","def initialize_storage(cfg: ElasticBlastConfig, query_files: List[str] = [], wait=ElbExecutionMode.WAIT) -> None:\n use_local_ssd = cfg.cluster.use_local_ssd\n if use_local_ssd:\n initialize_local_ssd(cfg, query_files, wait)\n else:\n initialize_persistent_disk(cfg, query_files, wait)","def storage_factory():\n return storage(transaction.manager, **kwargs)","def __init__(self, path):\n super().__init__()\n self.__cache = StorageCache()\n self.__db = InternalStorage(path)\n self.__serializer = Serializer()","def __init__(self,dir):\n self.__storage = None\n self.__handle = None\n self.__dir = dir","def initialize_provider_datastore(self, storage_path: str) -> Any:\n return MTurkDatastore(datastore_root=storage_path)","def _configure_manager(self):\n self._manager = CloudDatabaseManager(self,\n resource_class=CloudDatabaseInstance, response_key=\"instance\",\n uri_base=\"instances\")\n self._flavor_manager = BaseManager(self,\n resource_class=CloudDatabaseFlavor, response_key=\"flavor\",\n uri_base=\"flavors\")\n self._backup_manager = CloudDatabaseBackupManager(self,\n resource_class=CloudDatabaseBackup, response_key=\"backup\",\n uri_base=\"backups\")","def setUpClass(cls):\n cls.inst = storage","def __init__(self, storage_config: Dict[str, Any], storage_paths: List[str], local_dir: str):\n _ = storage_config\n self.local_dir = local_dir\n self.storage_paths = storage_paths\n self._file_records = {} # type: Dict[str, datetime.datetime]","def __init__(self, wm) -> None:\n conf_dict = wm.context.config.arango_storage._to_dict()\n\n log.debug(conf_dict)\n client = ArangoClient(hosts=conf_dict['hosts'])\n db = client.db(conf_dict['database'],\n username=conf_dict['username'],\n password=conf_dict['password'])\n\n self.db = db\n self.client = client","def set_storage(self):\n pass","def initialize(self):\n self.population.initialize()\n self.cache.initialize()\n if self.storage:\n self.storage.initialize()","def init(config_file_path=None, **kwargs):\n if __debug__:\n logger.debug(HEADER + \"Initializing the storage client.\")\n global redis_connection\n global hosts\n # If config_file_path is None we will assume that we only have localhost\n # as storage node\n if config_file_path is None:\n try:\n import StringIO as sio\n except ImportError:\n from io import StringIO as sio\n config_file_handler = sio.StringIO('localhost\\n')\n else:\n config_file_handler = open(config_file_path)\n # As accorded in the API standar, this file must contain all the hosts\n # names with no port, one per line\n hosts = [x.strip() for x in config_file_handler.readlines()]\n config_file_handler.close()\n # If we have more than one host then we will assume that our backend is a\n # Redis cluster. If not, we will assume that we are dealing with a Redis\n # standalone instance\n if len(hosts) > 1:\n # Given that cluster clients are capable to perform master\n # slave hierarchy discovery, we will simply connect to the first\n # node we got\n redis_connection = \\\n rediscluster.RedisCluster(host=hosts[0], port=REDIS_PORT)\n else:\n # We are in standalone mode\n redis_connection = \\\n redis.StrictRedis(host=hosts[0], port=REDIS_PORT)\n # StrictRedis is not capable to know if we had success when connecting by\n # simply calling the constructor. We need to perform an actual query to\n # the backend\n # If we had no success this first line should crash\n redis_connection.set('PYCOMPSS_TEST', 'OK')\n # Beware py2 vs py3 - b'string' works for both.\n assert redis_connection.get('PYCOMPSS_TEST') == b'OK'\n redis_connection.delete('PYCOMPSS_TEST')\n if __debug__:\n logger.debug(HEADER + \"Initialization finished successfully.\")","def __init__(self):\n self.backends = {}\n self.timeout = 5.0\n self._credentials = {}\n self._s3_folder = []","def __init__(self, prefix, db_name='local.json'):\n self._transaction_count = 0\n try:\n util.mkdirp(prefix)\n LOGGER.debug(\"Created '%s'\" % prefix)\n except:\n raise StorageError('Cannot create directory %r' % path, 'Check that you have `write` access')\n self.dbfile = os.path.join(prefix, db_name)\n try:\n self.db = TinyDB(self.dbfile)\n except:\n raise StorageError('Cannot create %r' % path, 'Check that you have `write` access')\n LOGGER.debug(\"Opened '%s' for read/write\" % self.dbfile)","def test_init(self, _s3):\n ps = PersistenceStore(s3_client=None)\n assert ps.s3_client is not None","def initialize():\n manager.initialize()\n logs.exit_great_success()","def __init__(self, name='TemporaryStorage'):\n\n BaseStorage.__init__(self, name)\n\n self._index = {}\n self._referenceCount = {}\n self._oreferences = {}\n self._opickle = {}\n self._tmp = []\n self._conflict_cache = {}\n self._last_cache_gc = 0\n self._recently_gc_oids = [None for x in range(RECENTLY_GC_OIDS_LEN)]\n self._oid = z64\n self._ltid = z64\n\n # Alow overrides for testing.\n self._conflict_cache_gcevery = CONFLICT_CACHE_GCEVERY\n self._conflict_cache_maxage = CONFLICT_CACHE_MAXAGE","def __init__(self, helper=None):\n self.helper = helper\n self.sp_manager = SPManager(helper.handle, helper.service_profile)","def test_sm_initial_attrs(self):\n\n storage_group_mgr = self.console.storage_groups\n\n assert isinstance(storage_group_mgr, StorageGroupManager)\n\n # Verify all public properties of the manager object\n assert storage_group_mgr.resource_class == StorageGroup\n assert storage_group_mgr.session == self.session\n assert storage_group_mgr.parent == self.console\n assert storage_group_mgr.console == self.console","def __init__(__self__, *,\n storage_space_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\n if storage_space_ids is not None:\n pulumi.set(__self__, \"storage_space_ids\", storage_space_ids)","def _swift_storage_setup(self):\n with settings(hide('running', 'stdout', 'stderr', 'warnings')):\n self._pull_configs('storage')\n self._swift_install('storage')\n self._set_onhold('storage')\n self._final_install_touches('storage')","def initialize_storage_method(self):\n if self.options['storage_method'] == 'hdf5':\n import h5py\n import numpy as np\n global h5py, np\n elif self.options['storage_method'] == 'none':\n # save command for later processing\n self.clear_storage_commands()\n else:\n raise Exception('Invalid storage_method (%s)' % storage_method)","def storage_factory(self):\n return load_or_import_from_config(\n 'SIPSTORE_FILE_STORAGE_FACTORY', app=self.app\n )","def __init__(self):\n self._datastore = dict()","def __init__(self, base_path):\n super(FileSystemDatastore, self).__init__(base_path)","def __init__(self):\n self.storage = None\n self.user = None\n self.master_collection = None\n self.current_collection = None","def __init__(self):\r\n self.__storage = {}","def __init__(self, storage_path: str):\n self._storage_path = storage_path\n if not os.path.exists(storage_path):\n os.makedirs(storage_path)\n\n self._archive_full_path = os.path.join(storage_path, self.archive_name)\n self._file_full_path = os.path.join(storage_path, self.file_name)","def initialize(self):\n super(self.__class__, self).initialize()\n\n self.__volume = cinder_utils.get_volume(\n self._cinder, self._keystone,\n volume_settings=self.volume_settings,\n project_name=self._os_creds.project_name)\n return self.__volume","def build(config: Dict[str, Any]) -> StorageManager:\n check_in(\"type\", config, \"Missing 'type' parameter of storage configuration\")\n\n # Make a deep copy of the config because we are removing items to\n # pass to the constructor of the `StorageManager`.\n config = copy.deepcopy(config)\n identifier = config.pop(\"type\")\n check_type(identifier, str, \"`type` parameter of storage configuration must be a string\")\n\n try:\n subclass = _STORAGE_MANAGERS[identifier]\n except KeyError:\n raise TypeError(\"Unknown storage type: {}\".format(identifier))\n\n # Remove configurations that should not be directly passed to\n # subclasses. Keeping these would result in the subclass __init__()\n # function failing to a TypeError with an unexpected keyword.\n config.pop(\"save_experiment_best\", None)\n config.pop(\"save_trial_best\", None)\n config.pop(\"save_trial_latest\", None)\n\n # For shared_fs maintain backwards compatibility by folding old keys into\n # storage_path.\n if identifier == \"shared_fs\" and \"storage_path\" not in config:\n if \"tensorboard_path\" in config:\n config[\"storage_path\"] = config.get(\"tensorboard_path\", None)\n else:\n config[\"storage_path\"] = config.get(\"checkpoint_path\", None)\n\n config.pop(\"tensorboard_path\", None)\n config.pop(\"checkpoint_path\", None)\n\n try:\n return subclass(**config)\n except TypeError as e:\n raise TypeError(\n \"Failed to instantiate {} checkpoint storage: {}\".format(identifier, str(e))\n )","def __init__(self, task_manager, num_samples, num_shards, kernel, scale,\n bucket, directory):\n # Task parameters\n self.task_manager = task_manager\n self.num_samples = num_samples\n self.num_shards = num_shards\n\n # Patches paramters\n self.kernel = kernel\n self.scale = scale\n\n # Storage location\n self.bucket = bucket\n self.directory = directory","def __init__(self):\n AUTHORIZATION_SCOPES = [\n 'https://www.googleapis.com/auth/devstorage.full_control']\n\n creds = None\n # The file token.pickle stores the user's access and refresh tokens, and is\n # created automatically when the authorization flow completes for the first\n # time.\n if os.path.exists('token_cloud_storage.pickle'):\n with open('token_cloud_storage.pickle', 'rb') as token:\n creds = pickle.load(token)\n\n # If not successful, collecting new Token to access Calendar\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file(\n 'credentials_google.json', AUTHORIZATION_SCOPES)\n creds = flow.run_local_server(port=0)\n\n # Save the credentials for the next run\n with open('token_cloud_storage.pickle', 'wb') as token:\n pickle.dump(creds, token)\n\n # Instantiates a client\n self.storage_client = storage.Client(\n project=\"piot-assignment2-287110\", credentials=creds)\n\n # Connect to bucket on Cloud Storage\n self.bucket = self.storage_client.get_bucket(\"facial_img\")","def __init__(self, path: PathType, **kwargs):\n if(not globals().get(\"auto_convert_to_pathlib\", False) or\n locals().get(\"auto_convert_to_pathlib\", False)):\n from . import auto_convert_to_pathlib\n\n current_path = auto_convert_to_pathlib(path)\n\n self.path = current_path\n\n MemoryStorage.__init__(self)\n JSONStorage.__init__(self, current_path, **kwargs)","def __int__(self, storage):\r\n self._storage = storage\r\n self.tables={}","def init(_config, _run):\n sacred.commands.print_config(_run)\n dump_config_and_makefile()\n\n print()\n print('Initialized storage dir. Now run these commands:')\n print(f\"cd {_config['trainer']['storage_dir']}\")\n print(f\"make train\")\n print()\n print('or')\n print()\n print(f\"cd {_config['trainer']['storage_dir']}\")\n print('make ccsalloc')","def create_storage(conf):\n _name = conf.get(\"name\", \"\")\n _cls = importer(conf['class'])\n _kwargs = conf['kwargs']\n _io = importer(_kwargs['io_class'])\n return _cls(_kwargs[\"storage_config\"], name=_name, io_class=_io)","def __init__(self):\r\n ms_cli_root = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))\r\n self._working_dir = os.path.join(\".localdata\")\r\n self._db = None\r\n self._db_name = \"ms-cli.db\"\r\n self._db_models = db_base\r\n self._conf_file_name = \"ms-cli.conf\"\r\n self._db_map = {}\r\n\r\n self._appconfig = None\r\n self._session = None\r\n self._current_user_guid = None\r\n\r\n self.init_dir()","def _init(self):\n if os.path.exists(self.fname):\n with open(self.fname, \"rb\") as fh:\n self.db = pickle.load(fh)\n else:\n self.db = {}\n print(\"DB loaded, len\", len(self.db))","def __init__(self, datastore_root: str):\n self.session_storage: Dict[str, ProlificClient] = {}\n self.agent_data: Dict[str, Dict[str, Any]] = {}\n self.table_access_condition = threading.Condition()\n self.conn: Dict[int, sqlite3.Connection] = {}\n self.db_path = os.path.join(datastore_root, f\"{PROVIDER_TYPE}.db\")\n self.init_tables()\n self.datastore_root = datastore_root\n self._last_study_mapping_update_times: Dict[str, float] = defaultdict(\n lambda: time.monotonic()\n )","def __init__(self, database_manager=DataBaseManager()):\n self.database_manager = database_manager","def __init__(self, quota_driver_class=None):\n\n self._resources = {}\n self._driver = DbQuotaDriver()","def _get_storage(self, path, storage_id=None):\n if storage_id is None:\n fields = path.split(':', 1)\n if len(fields) == 2 and len(fields[0]) > 1:\n storage_id = fields[0]\n path = fields[1]\n\n if storage_id is not None:\n if storage_id not in self._storages:\n if self._config is None or storage_id not in self._config:\n raise ValueError('unknown storage identifier %s' % storage_id)\n config = self._config[storage_id]\n if config['type'] == 's3':\n credentials = config.get('aws_credentials', {})\n client = storages.S3Storage(\n storage_id,\n config['bucket'],\n access_key_id=credentials.get('access_key_id'),\n secret_access_key=credentials.get('secret_access_key'),\n region_name=credentials.get('region_name'),\n assume_role=credentials.get('assume_role'),\n transfer_config=credentials.get('transfer_config'))\n elif config['type'] == 'swift':\n client = storages.SwiftStorage(\n storage_id,\n config['container'],\n auth_config=config.get('auth_config'),\n transfer_config=config.get('transfer_config'))\n elif config['type'] == 'ssh':\n client = storages.RemoteStorage(\n storage_id,\n config['server'],\n config['user'],\n config.get('password'),\n config.get('pkey'),\n port=config.get('port', 22),\n basedir=config.get('basedir'))\n elif config['type'] == 'http':\n client = storages.HTTPStorage( # pylint: disable=abstract-class-instantiated\n storage_id,\n config['get_pattern'],\n pattern_push=config.get('post_pattern'),\n pattern_list=config.get('list_pattern'))\n elif config['type'] == 'systran_corpusmanager':\n client = storages.CMStorages(\n storage_id,\n config.get('host_url'),\n account_id=config.get('account_id'),\n root_folder=config.get('root_folder'))\n elif config['type'] == 'local':\n client = storages.LocalStorage(\n storage_id,\n basedir=config.get(\"basedir\"))\n else:\n raise ValueError(\n 'unsupported storage type %s for %s' % (config['type'], storage_id))\n self._storages[storage_id] = client\n else:\n client = self._storages[storage_id]\n else:\n client = storages.LocalStorage()\n\n return client, client._internal_path(path)","def storage(self) -> storage.Storage:\n raise ValueError('Not implemented.')","def init():\n safe_call(backend.get().af_init())","def __init__(self):\n self.store_list = []\n self.store_dict = {}","def __init__(self):\r\n raise BotoClientError('Attempt to instantiate abstract StorageUri '\r\n 'class')","def initialize_local_storage(conn_string):\n\n if DEBUG:\n print(\"Initializing local storage module\")\n\n blob_service_client = BlobServiceClient.from_connection_string(conn_string)\n containers = list(blob_service_client.list_containers())\n\n if len(list(filter(lambda x: x['name'] == LOCAL_STORAGE_CONTAINER, containers))) == 0:\n if DEBUG:\n print(\"Creating container '%s' in local storage account '%s'\" % (LOCAL_STORAGE_CONTAINER, LOCAL_STORAGE_ACCOUNT))\n blob_service_client.create_container(LOCAL_STORAGE_CONTAINER)\n else:\n if DEBUG:\n print(\"Container '%s' already exists in local storage account '%s'\" % (LOCAL_STORAGE_CONTAINER, LOCAL_STORAGE_ACCOUNT))","def __init__(self, *args, **kwargs):\n # First we call the super function to initialize the initial attributes\n # given by the StorageShare class.\n super().__init__(*args, **kwargs)\n\n self.storageprotocol = \"DAV\"\n\n self.validators.update({\n 'cli_certificate': {\n 'required': True,\n 'status_code': '003',\n },\n 'cli_private_key': {\n 'required': True,\n 'status_code': '004',\n },\n 'storagestats.api': {\n 'default': 'rfc4331',\n 'required': False,\n 'status_code': '070',\n 'valid': ['generic', 'list-objects', 'rfc4331'],\n },\n })\n\n # Invoke the validate_plugin_settings() method\n self.validate_plugin_settings()\n\n # Invoke the validate_schema() method\n self.validate_schema()","def __init__(self):\n self.policy_store = PolicyStore()\n self.service_store = {}\n\n from ranger_performance_tool import perf_globals\n enabled_services = perf_globals.CONFIG_READER.get_config_value(\"secondary\", \"enabled_services\")\n service_type_mapping = perf_globals.CONFIG_READER.get_config_value(\"secondary\", \"service_type_mapping\")\n for service_name in enabled_services:\n if service_name not in service_type_mapping:\n raise Exception(f\"Unknown service name:{service_name}. \"\n f\"Add it to service_type_mapping in secondary config file\")\n service_type = service_type_mapping[service_name]\n random_type = perf_globals.CONFIG_READER.get_config_value(\"secondary\", \"services\",\n service_type, \"random_type\")\n self.service_store[service_type] = RangerAPIObjectStore.service_store_def[service_type](random_type=random_type)","def initialize_database():\n # TODO: Refactor the funtime library\n this.db = Store(this.host).create_lib(this.store_name).get_store()","def __init__(self, storage=default_storage, prefix=\"assets\", cache_name=\"optimizations.assetcache\"):\n self._storage = storage\n self._prefix = prefix\n self._cache = resolve_namespaced_cache(cache_name)","def __init__(self, processManager, clientManager):\n self.processManager = processManager\n self.clientManager = clientManager\n self.engine_types = {}\n self.engine_allocations = {}\n self.engine_instances = {}","def test_init_with_client(self):\n ps = PersistenceStore(s3_client=S3NotConnected())\n assert ps.s3_client is not None","def __init__(self, backend, path, url, storage):\n self.backend = backend\n self.path = path\n self.url = url\n self.storage = storage\n self.platforms = {}","def __init__(self):\n\t\tself._logger = None\n\t\tself._instanciate_logger()\n\t\tself._video_manager = VideoManager(self, self._logger)\n\t\tself._video_thread = None\n\t\tself._audio_manager = AudioManager(self, self._logger)\n\t\tself._audio_thread = None\n\t\tself._input_thread = None\n\t\tself._trigger_manager = None\n\t\tself.is_running = False","def __init__ ( self, datadir, emulator_home, resample_opts=None ):\n ObservationStorage.__init__ ( self, datadir, resample_opts )\n self.sensor = \"ETM+\"\n if not os.path.exists ( datadir ):\n raise IOError, \"%s does not appear to exist in the filesystem?!\" % datadir\n\n self.metadata = []\n for root, dirnames, filenames in os.walk( datadir ):\n for filename in fnmatch.filter(filenames, '*.xml'):\n self.metadata.append(os.path.join(root, filename))\n\n self.datadir = datadir\n\n if len ( self.metadata ) < 0:\n raise IOError, \"No xml metadatafiles in %s\" % self.datadir\n\n self._setup_sensor()\n self._parse_metadata ()\n self._get_emulators ( emulator_home )\n self._sort_data ( resample_opts )","def __init__(self, memory=4000):\n self.session = boto3.Session()\n self.batch_client = self.session.client(\"batch\")\n self.logs_client = self.session.client(\"logs\")\n self.memory = memory","def __init__(self, store):\n assert store is not None\n self.store = store","async def init(self) -> None:","async def init(self) -> None:","def init_storage(self):\n\n # Create the average rotation matrix (first order).\n self.first_frame_order = zeros((INC+1, 3, 3), float64)\n\n # Create the frame order matrix (each element is ensemble averaged and corresponds to a different time step).\n self.second_frame_order = zeros((INC+1, 9, 9), float64)\n\n # Init the rotation matrix.\n self.rot = zeros((3, 3), float64)\n\n # Some data arrays.\n self.full = zeros(INC+1)\n self.count = zeros(INC+1)","def __init__(self, handler):\n self._handler = handler\n self._storage = []","def get_storage():\n settings = get_settings()\n sources = sum([source is not None for source in (settings.attach_dir,\n settings.attach_s3_bucket,\n settings.attach_gcs_bucket)])\n if sources < 1:\n raise Error(\"At least of the parameters must be set:\",\n \"attach_dir, attach_gcs_bucket, attach_s3_bucket\")\n elif sources > 1:\n raise Error(\"Only one of the parameters must be set:\",\n \"attach_dir, attach_gcs_bucket, attach_s3_bucket\")\n if settings.attach_dir is not None:\n storage = LocalStorage(settings.attach_dir)\n if settings.attach_s3_bucket is not None:\n storage = S3Storage(name=settings.attach_s3_bucket,\n endpoint=settings.attach_s3_endpoint,\n region=settings.attach_s3_region,\n access_key=settings.attach_s3_access_key,\n secret_key=settings.attach_s3_secret_key)\n if settings.attach_gcs_bucket is not None:\n storage = GCSStorage(name=settings.attach_gcs_bucket,\n key=settings.attach_gcs_key)\n return storage","def __init__(__self__, *,\n account_key: pulumi.Input[str],\n account_name: pulumi.Input[str],\n storage_type: pulumi.Input[str]):\n pulumi.set(__self__, \"account_key\", account_key)\n pulumi.set(__self__, \"account_name\", account_name)\n pulumi.set(__self__, \"storage_type\", 'StorageAccount')","def __init__(self):\n super(GconfStore, self).__init__()\n self._client = gconf.client_get_default()\n self.__connect_notifications()","def __init__ ( self, datadir, emulator_home, resample_opts=None, ):\n \n ObservationStorage.__init__ ( self, datadir, resample_opts=None )\n self.sensor = \"SPOT4\"\n if not os.path.exists ( datadir ):\n raise IOError, \"%s does not appear to exist in the filesystem?!\"\n\n self.metadata = []\n for root, dirnames, filenames in os.walk( datadir ):\n for filename in fnmatch.filter(filenames, '*.xml'):\n self.metadata.append(os.path.join(root, filename))\n\n self.datadir = datadir\n \n if len ( self.metadata ) < 0:\n raise IOError, \"No xml metadatafiles in %s\" % self.datadir\n\n self._setup_sensor()\n self._parse_metadata ()\n self._get_emulators ( emulator_home )\n self._sort_data ( resample_opts )","def __init__(self):\n self.s3_resource = boto3.resource('s3')\n self.s3_client = boto3.client('s3')","def _initialize(self, boto_session, sagemaker_client, sagemaker_runtime_client):\n\n self.boto_session = boto_session or boto3.Session()\n self._region_name = self.boto_session.region_name\n\n if self._region_name is None:\n raise ValueError('Must setup local AWS configuration with a region supported by SageMaker.')\n\n self.sagemaker_client = LocalSagemakerClient(self)\n self.sagemaker_runtime_client = LocalSagemakerRuntimeClient(self.config)\n self.local_mode = True","def get_swift_storage():\n\n return SwiftStorage(\n os_tenant_id=\"os_tenant_id\",\n os_tenant_name=\"os_tenant_name\",\n os_username=\"os_username\",\n os_password=\"os_password\",\n os_region_name=\"os_region_name\",\n os_storage_url=\"os_storage_url/ralph_logs_container\",\n )","def __init__(self, key, active=True, **kwargs):\n # Support multiple inheritance\n super(Store, self).__init__()\n \n # Make key safe and set it\n key = key.lower()\n if not is_filename_safe(key):\n raise ValueError('Key is not safe for filename')\n self.key = key\n \n # Set filename (if service has started)\n if self.manager._started:\n self._pre_start()\n \n # Tell fields to initialise themselves\n for field_name, field in self._fields.items():\n field.contribute_to_instance(self, field_name)\n \n # Now set any field values\n for field_name, value in kwargs.items():\n if field_name not in self._fields:\n raise TypeError(\n \"__init__() got an unexpected keyword argument '%s'\" %\n field_name\n )\n setattr(self, field_name, value)\n \n # Ensure manager knows about it\n if active:\n self.manager.add_active(self)","def initialise(self):\n\n\t\t# Init the sync module\n\t\tSync.init(Conf.get(('redis', 'sync'), {\n\t\t\t\"host\": \"localhost\",\n\t\t\t\"port\": 6379,\n\t\t\t\"db\": 1\n\t\t}))","def storage_factory(cls, prefix, storage_cls=None, storage_uri=None):\n\n key_prefix = '{}_{}_'.format(cls.__name__.upper(), prefix.upper())\n attr = '_{}_storage'.format(prefix)\n if not storage_cls and not storage_uri:\n if not hasattr(cls, attr):\n setattr(cls, attr, cls.storage_cls(cls.storage_uri, key_prefix))\n return getattr(cls, attr)\n return (storage_cls or cls.storage_cls)(storage_uri or cls.storage_uri, key_prefix)","def _init(self, **kwargs):\n self.queries: FoldersQueries = FoldersQueries(auth=self.auth, **kwargs)\n self.enforcements: FoldersEnforcements = FoldersEnforcements(auth=self.auth, **kwargs)","def kv_esx_init():\n disk_lib_init()","def init(self):\n # Initialize runtime and MDK:\n self.runtime = fakeRuntime()\n self.runtime.getEnvVarsService().set(\"DATAWIRE_TOKEN\", \"somevalue\")\n self.runtime.dependencies.registerService(\"failurepolicy_factory\",\n RecordingFailurePolicyFactory())\n self.mdk = MDKImpl(self.runtime)\n self.mdk.start()\n self.disco = self.mdk._disco\n # Create a session:\n self.session = self.mdk.session()","def __init__(self):\n super(MemoryPersistence, self).__init__(descriptor)","def __init__(self):\n self.store = {}","def __init__(self, album_store, artist_store, genre_store,\n track_store, trie_factory):\n self._album_store = album_store\n self._artist_store = artist_store\n self._genre_store = genre_store\n self._track_store = track_store\n self._trie_factory = trie_factory\n\n self._album_search = None\n self._artist_search = None\n self._genre_search = None\n self._track_search = None","def __init__(self):\n logger.debug(\"VMPoolManager: _init_()\")\n self.system = State.Instance()\n \n self.VMPools = []\n e = EnvSetUp()\n config_spec = json.loads(open(e.get_ovpl_directory_path() + \"/config/config.json\").read())\n pools = config_spec[\"VMPOOL_CONFIGURATION\"][\"VMPOOLS\"]\n create_uri = config_spec[\"API_ENDPOINTS\"][\"CREATE_URI_ADAPTER_ENDPOINT\"]\n destroy_uri = config_spec[\"API_ENDPOINTS\"][\"DESTROY_URI_ADAPTER_ENDPOINT\"]\n\n for pool in pools:\n self.add_vm_pool( pool[\"POOLID\"], \\\n pool[\"DESCRIPTION\"], \\\n pool[\"ADAPTERIP\"], \\\n pool[\"PORT\"], \\\n create_uri, \\\n destroy_uri)\n\n logger.debug(\"VMPoolManager: _init_(); vm_pools = %s\" % (str(self.VMPools)))","def _initialize(self):\n configured_providers = self.domain.config[\"DATABASES\"]\n provider_objects = {}\n\n if configured_providers and isinstance(configured_providers, dict):\n if \"default\" not in configured_providers:\n raise ConfigurationError(\"You must define a 'default' provider\")\n\n for provider_name, conn_info in configured_providers.items():\n provider_full_path = conn_info[\"PROVIDER\"]\n provider_module, provider_class = provider_full_path.rsplit(\n \".\", maxsplit=1\n )\n\n provider_cls = getattr(\n importlib.import_module(provider_module), provider_class\n )\n provider = provider_cls(provider_name, self.domain, conn_info)\n\n provider_objects[provider_name] = provider\n\n self._providers = provider_objects","def startManager(self):\n\t\tlogging.info(\"----->>>The DeviceDataManager will be started\")\n\t\tself.sysPerfManager.startManager()\n\t\tself.sensorAdapterManager.startManager()\n\t\tif self.enableRedis:\n\t\t\tself.redisClient.connectClient()\n\t\t\n\t\tif self.enableMqtt:\n\t\t\tself.mqttClient.connectClient()","def __init__(self):\n self._store: ObservationStore = {}\n self._memory_lower_bound = 0","def _CreateStorageFile(self):\n return sqlite_file.SQLiteStorageFile(storage_type=self._storage_type)","def store(self):\n\t\timport shelve\n\n\t\td = shelve.open(\".storedmanager\",writeback=True)\n\t\td[\"storedmanager\"] = self\n\n\t\td.close()","def init(market_manager_):\n global market_manager\n market_manager = market_manager_","def open(self):\n super(DiskCache, self).open()\n if self.__env:\n return\n try:\n os.makedirs(self.__path)\n except OSError:\n pass # Directory already exists\n\n logging.info(\n \"Opening cache %s (ttl: %s, sync: %s)\", self.__path, self.__ttl, self.__sync\n )\n self.__env = lmdb.open(\n self.__path,\n map_size=self.__size,\n # Only one sync per transaction, system crash can undo a transaction.\n metasync=False,\n # Actually, don't sync at all.\n sync=self.__sync,\n map_async=not self.__sync,\n # Use mmap()\n writemap=True,\n # Max number of concurrent readers, see _MAX_READERS for details\n max_readers=self._MAX_READERS,\n # How many DBs we may create (until we increase version prefix).\n max_dbs=8,\n # A cache of read-only transactions, should match max number of threads.\n # Only transactions that are actually used concurrently allocate memory,\n # so setting a high number doesn't cost much even if thread count is low.\n max_spare_txns=128,\n )\n\n # Clean stale readers. This can be needed if a previous instance crashed or\n # was killed abruptly (HUP, TERM, KILL...) and the lock file was always used\n # typically by other UWSGI workers.\n cleaned_stale_reader = self.__env.reader_check()\n logging.info(\"%d stale readers cleared.\" % cleaned_stale_reader)\n\n databases = {}\n for name in self.__databases:\n databases[name] = self.__env.open_db(name.encode())\n self.__databases = databases\n\n self.__metric_to_metadata_db = databases[\"metric_to_meta\"]","def __init__(self,\n checkpoint_path=None,\n max_state_size=None,\n j_jobmanager_checkpoint_storage=None):\n if j_jobmanager_checkpoint_storage is None:\n gateway = get_gateway()\n JJobManagerCheckpointStorage = gateway.jvm.org.apache.flink.runtime.state.storage\\\n .JobManagerCheckpointStorage\n JPath = gateway.jvm.org.apache.flink.core.fs.Path\n\n if checkpoint_path is not None:\n checkpoint_path = JPath(checkpoint_path)\n if max_state_size is None:\n max_state_size = JJobManagerCheckpointStorage.DEFAULT_MAX_STATE_SIZE\n j_jobmanager_checkpoint_storage = JJobManagerCheckpointStorage(checkpoint_path,\n max_state_size)\n\n super(JobManagerCheckpointStorage, self).__init__(j_jobmanager_checkpoint_storage)","def get_storage_factory(settings, prefix='filestore'):\n # Pull prefix.key out of the config object\n kwargs = {}\n plen = len(prefix)\n for key, val in settings.iteritems():\n if key[0:plen] == prefix and len(key) > plen:\n kwargs[ key[plen+1:] ] = val\n\n # Resolve the data manager\n resolver = DottedNameResolver(None)\n manager = settings[prefix]\n name = 'floof.model.filestore.' + manager + '.FileStorage'\n try:\n storage = resolver.resolve(name)\n except ImportError:\n storage = resolver.resolve(manager)\n\n def storage_factory():\n \"\"\"Returns an instance of the chosen data manager for attachement to a\n request object and use over the life of a single request. The instance\n must be manually joined to a Zope-style transaction.\"\"\"\n return storage(transaction.manager, **kwargs)\n\n return storage_factory","def init_managers(endpoints_file: Optional[Text]) -> None:","def __init__(self):\n self._url_base = None\n self._keystone = None\n self._auth_token = None\n self._auth_lock = threading.Lock()\n self._failed_auth = False","def __init__(self, fileStore, sqlStore, uid=None, gid=None, merge=False):\n\n self.fileStore = fileStore\n self.sqlStore = sqlStore\n self.uid = uid\n self.gid = gid\n self.merge = merge","def __init__(self, source_path, output_path):\n self.storage_type = 's3' if 's3' in source_path else 'local'\n self.source_path = source_path\n self.output_path = output_path","def __init__(self, filter: Filter, matcher: Matcher, storage_manager: StorageManager):\n super().__init__()\n self.filter = filter\n self.matcher = matcher\n self.storage_manager = storage_manager","def __init__(__self__,\n resource_name: str,\n args: ObjectStorageKeyArgs,\n opts: Optional[pulumi.ResourceOptions] = None):\n ..."],"string":"[\n \"def __init__(self):\\n config = self.read_config()\\n self.deployment = config['deployment']\\n self.deployment_config = config[self.deployment]\\n logger.info(f'Initializing storage client with the {self.deployment} deployment config {pformat(self.deployment_config)}')\\n\\n # get the MLOS config from the user else default it from the deployment config file\\n # self.mlos_config = config['MLOS']\\n # logger.info(f'Initializing storage client with the MLOS config {pformat(self.mlos_config)}')\\n\\n # setup the mount path\\n if self.deployment == \\\"LOCAL\\\":\\n self.mount_dir = self.setup_mount()\\n logger.info(f'Mount directory setup completed: {self.mount_dir}')\",\n \"def init(self):\\n self._service_store = ServiceStore(self.driver, self.network)\\n self._emulator = NetworkEmulator(self.store, self.driver)\",\n \"def __init__(\\n self, storage_path: str, block_size: Tuple[int, int, int], **kwargs\\n ) -> None:\\n self.name = \\\"FilesystemStorageManager\\\"\\n if \\\"next_layer\\\" in kwargs:\\n self._next = kwargs[\\\"next_layer\\\"]\\n self.is_terminal = False\\n else:\\n self.is_terminal = True\\n self.storage_path = storage_path\\n self.block_size = block_size\\n self._cache = kwargs.get(\\\"cache\\\", True)\\n\\n self.fs = ({\\\"h5\\\": H5FileInterface}.get(kwargs.get(\\\"preferred_format\\\", \\\"h5\\\")))(\\n self.storage_path\\n )\",\n \"def __init__(self, agent = None, region = None, settings = None, message_handler = None, events_handler = None):\\n super(ObjectManager, self).__init__(agent, settings)\\n self.region = region\\n\\n # the object store consists of a list\\n # of Object() instances\\n self.object_store = []\\n\\n # the avatar store consists of a list\\n # of Avatar() instances\\n self.avatar_store = []\\n\\n # other useful things\\n self.helpers = Helpers()\\n\\n self.message_handler = message_handler\\n\\n if self.settings.LOG_VERBOSE: logger.info(\\\"Initializing object storage\\\")\",\n \"def __init_subclass__(cls):\\n available_storages.append({\\n \\\"name\\\": cls.__name__,\\n \\\"extensions\\\": cls.extensions,\\n \\\"storage\\\": cls,\\n })\",\n \"def _init_storage(self):\\n if self._ is None:\\n self._ = Parameters(self)\",\n \"def __init__(self):\\n\\n self.storage: list = Storage()\\n\\n # Start for get data in API and set in storage\\n self._set_proxies_in_storage()\",\n \"def initialize_storage(cfg: ElasticBlastConfig, query_files: List[str] = [], wait=ElbExecutionMode.WAIT) -> None:\\n use_local_ssd = cfg.cluster.use_local_ssd\\n if use_local_ssd:\\n initialize_local_ssd(cfg, query_files, wait)\\n else:\\n initialize_persistent_disk(cfg, query_files, wait)\",\n \"def storage_factory():\\n return storage(transaction.manager, **kwargs)\",\n \"def __init__(self, path):\\n super().__init__()\\n self.__cache = StorageCache()\\n self.__db = InternalStorage(path)\\n self.__serializer = Serializer()\",\n \"def __init__(self,dir):\\n self.__storage = None\\n self.__handle = None\\n self.__dir = dir\",\n \"def initialize_provider_datastore(self, storage_path: str) -> Any:\\n return MTurkDatastore(datastore_root=storage_path)\",\n \"def _configure_manager(self):\\n self._manager = CloudDatabaseManager(self,\\n resource_class=CloudDatabaseInstance, response_key=\\\"instance\\\",\\n uri_base=\\\"instances\\\")\\n self._flavor_manager = BaseManager(self,\\n resource_class=CloudDatabaseFlavor, response_key=\\\"flavor\\\",\\n uri_base=\\\"flavors\\\")\\n self._backup_manager = CloudDatabaseBackupManager(self,\\n resource_class=CloudDatabaseBackup, response_key=\\\"backup\\\",\\n uri_base=\\\"backups\\\")\",\n \"def setUpClass(cls):\\n cls.inst = storage\",\n \"def __init__(self, storage_config: Dict[str, Any], storage_paths: List[str], local_dir: str):\\n _ = storage_config\\n self.local_dir = local_dir\\n self.storage_paths = storage_paths\\n self._file_records = {} # type: Dict[str, datetime.datetime]\",\n \"def __init__(self, wm) -> None:\\n conf_dict = wm.context.config.arango_storage._to_dict()\\n\\n log.debug(conf_dict)\\n client = ArangoClient(hosts=conf_dict['hosts'])\\n db = client.db(conf_dict['database'],\\n username=conf_dict['username'],\\n password=conf_dict['password'])\\n\\n self.db = db\\n self.client = client\",\n \"def set_storage(self):\\n pass\",\n \"def initialize(self):\\n self.population.initialize()\\n self.cache.initialize()\\n if self.storage:\\n self.storage.initialize()\",\n \"def init(config_file_path=None, **kwargs):\\n if __debug__:\\n logger.debug(HEADER + \\\"Initializing the storage client.\\\")\\n global redis_connection\\n global hosts\\n # If config_file_path is None we will assume that we only have localhost\\n # as storage node\\n if config_file_path is None:\\n try:\\n import StringIO as sio\\n except ImportError:\\n from io import StringIO as sio\\n config_file_handler = sio.StringIO('localhost\\\\n')\\n else:\\n config_file_handler = open(config_file_path)\\n # As accorded in the API standar, this file must contain all the hosts\\n # names with no port, one per line\\n hosts = [x.strip() for x in config_file_handler.readlines()]\\n config_file_handler.close()\\n # If we have more than one host then we will assume that our backend is a\\n # Redis cluster. If not, we will assume that we are dealing with a Redis\\n # standalone instance\\n if len(hosts) > 1:\\n # Given that cluster clients are capable to perform master\\n # slave hierarchy discovery, we will simply connect to the first\\n # node we got\\n redis_connection = \\\\\\n rediscluster.RedisCluster(host=hosts[0], port=REDIS_PORT)\\n else:\\n # We are in standalone mode\\n redis_connection = \\\\\\n redis.StrictRedis(host=hosts[0], port=REDIS_PORT)\\n # StrictRedis is not capable to know if we had success when connecting by\\n # simply calling the constructor. We need to perform an actual query to\\n # the backend\\n # If we had no success this first line should crash\\n redis_connection.set('PYCOMPSS_TEST', 'OK')\\n # Beware py2 vs py3 - b'string' works for both.\\n assert redis_connection.get('PYCOMPSS_TEST') == b'OK'\\n redis_connection.delete('PYCOMPSS_TEST')\\n if __debug__:\\n logger.debug(HEADER + \\\"Initialization finished successfully.\\\")\",\n \"def __init__(self):\\n self.backends = {}\\n self.timeout = 5.0\\n self._credentials = {}\\n self._s3_folder = []\",\n \"def __init__(self, prefix, db_name='local.json'):\\n self._transaction_count = 0\\n try:\\n util.mkdirp(prefix)\\n LOGGER.debug(\\\"Created '%s'\\\" % prefix)\\n except:\\n raise StorageError('Cannot create directory %r' % path, 'Check that you have `write` access')\\n self.dbfile = os.path.join(prefix, db_name)\\n try:\\n self.db = TinyDB(self.dbfile)\\n except:\\n raise StorageError('Cannot create %r' % path, 'Check that you have `write` access')\\n LOGGER.debug(\\\"Opened '%s' for read/write\\\" % self.dbfile)\",\n \"def test_init(self, _s3):\\n ps = PersistenceStore(s3_client=None)\\n assert ps.s3_client is not None\",\n \"def initialize():\\n manager.initialize()\\n logs.exit_great_success()\",\n \"def __init__(self, name='TemporaryStorage'):\\n\\n BaseStorage.__init__(self, name)\\n\\n self._index = {}\\n self._referenceCount = {}\\n self._oreferences = {}\\n self._opickle = {}\\n self._tmp = []\\n self._conflict_cache = {}\\n self._last_cache_gc = 0\\n self._recently_gc_oids = [None for x in range(RECENTLY_GC_OIDS_LEN)]\\n self._oid = z64\\n self._ltid = z64\\n\\n # Alow overrides for testing.\\n self._conflict_cache_gcevery = CONFLICT_CACHE_GCEVERY\\n self._conflict_cache_maxage = CONFLICT_CACHE_MAXAGE\",\n \"def __init__(self, helper=None):\\n self.helper = helper\\n self.sp_manager = SPManager(helper.handle, helper.service_profile)\",\n \"def test_sm_initial_attrs(self):\\n\\n storage_group_mgr = self.console.storage_groups\\n\\n assert isinstance(storage_group_mgr, StorageGroupManager)\\n\\n # Verify all public properties of the manager object\\n assert storage_group_mgr.resource_class == StorageGroup\\n assert storage_group_mgr.session == self.session\\n assert storage_group_mgr.parent == self.console\\n assert storage_group_mgr.console == self.console\",\n \"def __init__(__self__, *,\\n storage_space_ids: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\\n if storage_space_ids is not None:\\n pulumi.set(__self__, \\\"storage_space_ids\\\", storage_space_ids)\",\n \"def _swift_storage_setup(self):\\n with settings(hide('running', 'stdout', 'stderr', 'warnings')):\\n self._pull_configs('storage')\\n self._swift_install('storage')\\n self._set_onhold('storage')\\n self._final_install_touches('storage')\",\n \"def initialize_storage_method(self):\\n if self.options['storage_method'] == 'hdf5':\\n import h5py\\n import numpy as np\\n global h5py, np\\n elif self.options['storage_method'] == 'none':\\n # save command for later processing\\n self.clear_storage_commands()\\n else:\\n raise Exception('Invalid storage_method (%s)' % storage_method)\",\n \"def storage_factory(self):\\n return load_or_import_from_config(\\n 'SIPSTORE_FILE_STORAGE_FACTORY', app=self.app\\n )\",\n \"def __init__(self):\\n self._datastore = dict()\",\n \"def __init__(self, base_path):\\n super(FileSystemDatastore, self).__init__(base_path)\",\n \"def __init__(self):\\n self.storage = None\\n self.user = None\\n self.master_collection = None\\n self.current_collection = None\",\n \"def __init__(self):\\r\\n self.__storage = {}\",\n \"def __init__(self, storage_path: str):\\n self._storage_path = storage_path\\n if not os.path.exists(storage_path):\\n os.makedirs(storage_path)\\n\\n self._archive_full_path = os.path.join(storage_path, self.archive_name)\\n self._file_full_path = os.path.join(storage_path, self.file_name)\",\n \"def initialize(self):\\n super(self.__class__, self).initialize()\\n\\n self.__volume = cinder_utils.get_volume(\\n self._cinder, self._keystone,\\n volume_settings=self.volume_settings,\\n project_name=self._os_creds.project_name)\\n return self.__volume\",\n \"def build(config: Dict[str, Any]) -> StorageManager:\\n check_in(\\\"type\\\", config, \\\"Missing 'type' parameter of storage configuration\\\")\\n\\n # Make a deep copy of the config because we are removing items to\\n # pass to the constructor of the `StorageManager`.\\n config = copy.deepcopy(config)\\n identifier = config.pop(\\\"type\\\")\\n check_type(identifier, str, \\\"`type` parameter of storage configuration must be a string\\\")\\n\\n try:\\n subclass = _STORAGE_MANAGERS[identifier]\\n except KeyError:\\n raise TypeError(\\\"Unknown storage type: {}\\\".format(identifier))\\n\\n # Remove configurations that should not be directly passed to\\n # subclasses. Keeping these would result in the subclass __init__()\\n # function failing to a TypeError with an unexpected keyword.\\n config.pop(\\\"save_experiment_best\\\", None)\\n config.pop(\\\"save_trial_best\\\", None)\\n config.pop(\\\"save_trial_latest\\\", None)\\n\\n # For shared_fs maintain backwards compatibility by folding old keys into\\n # storage_path.\\n if identifier == \\\"shared_fs\\\" and \\\"storage_path\\\" not in config:\\n if \\\"tensorboard_path\\\" in config:\\n config[\\\"storage_path\\\"] = config.get(\\\"tensorboard_path\\\", None)\\n else:\\n config[\\\"storage_path\\\"] = config.get(\\\"checkpoint_path\\\", None)\\n\\n config.pop(\\\"tensorboard_path\\\", None)\\n config.pop(\\\"checkpoint_path\\\", None)\\n\\n try:\\n return subclass(**config)\\n except TypeError as e:\\n raise TypeError(\\n \\\"Failed to instantiate {} checkpoint storage: {}\\\".format(identifier, str(e))\\n )\",\n \"def __init__(self, task_manager, num_samples, num_shards, kernel, scale,\\n bucket, directory):\\n # Task parameters\\n self.task_manager = task_manager\\n self.num_samples = num_samples\\n self.num_shards = num_shards\\n\\n # Patches paramters\\n self.kernel = kernel\\n self.scale = scale\\n\\n # Storage location\\n self.bucket = bucket\\n self.directory = directory\",\n \"def __init__(self):\\n AUTHORIZATION_SCOPES = [\\n 'https://www.googleapis.com/auth/devstorage.full_control']\\n\\n creds = None\\n # The file token.pickle stores the user's access and refresh tokens, and is\\n # created automatically when the authorization flow completes for the first\\n # time.\\n if os.path.exists('token_cloud_storage.pickle'):\\n with open('token_cloud_storage.pickle', 'rb') as token:\\n creds = pickle.load(token)\\n\\n # If not successful, collecting new Token to access Calendar\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file(\\n 'credentials_google.json', AUTHORIZATION_SCOPES)\\n creds = flow.run_local_server(port=0)\\n\\n # Save the credentials for the next run\\n with open('token_cloud_storage.pickle', 'wb') as token:\\n pickle.dump(creds, token)\\n\\n # Instantiates a client\\n self.storage_client = storage.Client(\\n project=\\\"piot-assignment2-287110\\\", credentials=creds)\\n\\n # Connect to bucket on Cloud Storage\\n self.bucket = self.storage_client.get_bucket(\\\"facial_img\\\")\",\n \"def __init__(self, path: PathType, **kwargs):\\n if(not globals().get(\\\"auto_convert_to_pathlib\\\", False) or\\n locals().get(\\\"auto_convert_to_pathlib\\\", False)):\\n from . import auto_convert_to_pathlib\\n\\n current_path = auto_convert_to_pathlib(path)\\n\\n self.path = current_path\\n\\n MemoryStorage.__init__(self)\\n JSONStorage.__init__(self, current_path, **kwargs)\",\n \"def __int__(self, storage):\\r\\n self._storage = storage\\r\\n self.tables={}\",\n \"def init(_config, _run):\\n sacred.commands.print_config(_run)\\n dump_config_and_makefile()\\n\\n print()\\n print('Initialized storage dir. Now run these commands:')\\n print(f\\\"cd {_config['trainer']['storage_dir']}\\\")\\n print(f\\\"make train\\\")\\n print()\\n print('or')\\n print()\\n print(f\\\"cd {_config['trainer']['storage_dir']}\\\")\\n print('make ccsalloc')\",\n \"def create_storage(conf):\\n _name = conf.get(\\\"name\\\", \\\"\\\")\\n _cls = importer(conf['class'])\\n _kwargs = conf['kwargs']\\n _io = importer(_kwargs['io_class'])\\n return _cls(_kwargs[\\\"storage_config\\\"], name=_name, io_class=_io)\",\n \"def __init__(self):\\r\\n ms_cli_root = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))\\r\\n self._working_dir = os.path.join(\\\".localdata\\\")\\r\\n self._db = None\\r\\n self._db_name = \\\"ms-cli.db\\\"\\r\\n self._db_models = db_base\\r\\n self._conf_file_name = \\\"ms-cli.conf\\\"\\r\\n self._db_map = {}\\r\\n\\r\\n self._appconfig = None\\r\\n self._session = None\\r\\n self._current_user_guid = None\\r\\n\\r\\n self.init_dir()\",\n \"def _init(self):\\n if os.path.exists(self.fname):\\n with open(self.fname, \\\"rb\\\") as fh:\\n self.db = pickle.load(fh)\\n else:\\n self.db = {}\\n print(\\\"DB loaded, len\\\", len(self.db))\",\n \"def __init__(self, datastore_root: str):\\n self.session_storage: Dict[str, ProlificClient] = {}\\n self.agent_data: Dict[str, Dict[str, Any]] = {}\\n self.table_access_condition = threading.Condition()\\n self.conn: Dict[int, sqlite3.Connection] = {}\\n self.db_path = os.path.join(datastore_root, f\\\"{PROVIDER_TYPE}.db\\\")\\n self.init_tables()\\n self.datastore_root = datastore_root\\n self._last_study_mapping_update_times: Dict[str, float] = defaultdict(\\n lambda: time.monotonic()\\n )\",\n \"def __init__(self, database_manager=DataBaseManager()):\\n self.database_manager = database_manager\",\n \"def __init__(self, quota_driver_class=None):\\n\\n self._resources = {}\\n self._driver = DbQuotaDriver()\",\n \"def _get_storage(self, path, storage_id=None):\\n if storage_id is None:\\n fields = path.split(':', 1)\\n if len(fields) == 2 and len(fields[0]) > 1:\\n storage_id = fields[0]\\n path = fields[1]\\n\\n if storage_id is not None:\\n if storage_id not in self._storages:\\n if self._config is None or storage_id not in self._config:\\n raise ValueError('unknown storage identifier %s' % storage_id)\\n config = self._config[storage_id]\\n if config['type'] == 's3':\\n credentials = config.get('aws_credentials', {})\\n client = storages.S3Storage(\\n storage_id,\\n config['bucket'],\\n access_key_id=credentials.get('access_key_id'),\\n secret_access_key=credentials.get('secret_access_key'),\\n region_name=credentials.get('region_name'),\\n assume_role=credentials.get('assume_role'),\\n transfer_config=credentials.get('transfer_config'))\\n elif config['type'] == 'swift':\\n client = storages.SwiftStorage(\\n storage_id,\\n config['container'],\\n auth_config=config.get('auth_config'),\\n transfer_config=config.get('transfer_config'))\\n elif config['type'] == 'ssh':\\n client = storages.RemoteStorage(\\n storage_id,\\n config['server'],\\n config['user'],\\n config.get('password'),\\n config.get('pkey'),\\n port=config.get('port', 22),\\n basedir=config.get('basedir'))\\n elif config['type'] == 'http':\\n client = storages.HTTPStorage( # pylint: disable=abstract-class-instantiated\\n storage_id,\\n config['get_pattern'],\\n pattern_push=config.get('post_pattern'),\\n pattern_list=config.get('list_pattern'))\\n elif config['type'] == 'systran_corpusmanager':\\n client = storages.CMStorages(\\n storage_id,\\n config.get('host_url'),\\n account_id=config.get('account_id'),\\n root_folder=config.get('root_folder'))\\n elif config['type'] == 'local':\\n client = storages.LocalStorage(\\n storage_id,\\n basedir=config.get(\\\"basedir\\\"))\\n else:\\n raise ValueError(\\n 'unsupported storage type %s for %s' % (config['type'], storage_id))\\n self._storages[storage_id] = client\\n else:\\n client = self._storages[storage_id]\\n else:\\n client = storages.LocalStorage()\\n\\n return client, client._internal_path(path)\",\n \"def storage(self) -> storage.Storage:\\n raise ValueError('Not implemented.')\",\n \"def init():\\n safe_call(backend.get().af_init())\",\n \"def __init__(self):\\n self.store_list = []\\n self.store_dict = {}\",\n \"def __init__(self):\\r\\n raise BotoClientError('Attempt to instantiate abstract StorageUri '\\r\\n 'class')\",\n \"def initialize_local_storage(conn_string):\\n\\n if DEBUG:\\n print(\\\"Initializing local storage module\\\")\\n\\n blob_service_client = BlobServiceClient.from_connection_string(conn_string)\\n containers = list(blob_service_client.list_containers())\\n\\n if len(list(filter(lambda x: x['name'] == LOCAL_STORAGE_CONTAINER, containers))) == 0:\\n if DEBUG:\\n print(\\\"Creating container '%s' in local storage account '%s'\\\" % (LOCAL_STORAGE_CONTAINER, LOCAL_STORAGE_ACCOUNT))\\n blob_service_client.create_container(LOCAL_STORAGE_CONTAINER)\\n else:\\n if DEBUG:\\n print(\\\"Container '%s' already exists in local storage account '%s'\\\" % (LOCAL_STORAGE_CONTAINER, LOCAL_STORAGE_ACCOUNT))\",\n \"def __init__(self, *args, **kwargs):\\n # First we call the super function to initialize the initial attributes\\n # given by the StorageShare class.\\n super().__init__(*args, **kwargs)\\n\\n self.storageprotocol = \\\"DAV\\\"\\n\\n self.validators.update({\\n 'cli_certificate': {\\n 'required': True,\\n 'status_code': '003',\\n },\\n 'cli_private_key': {\\n 'required': True,\\n 'status_code': '004',\\n },\\n 'storagestats.api': {\\n 'default': 'rfc4331',\\n 'required': False,\\n 'status_code': '070',\\n 'valid': ['generic', 'list-objects', 'rfc4331'],\\n },\\n })\\n\\n # Invoke the validate_plugin_settings() method\\n self.validate_plugin_settings()\\n\\n # Invoke the validate_schema() method\\n self.validate_schema()\",\n \"def __init__(self):\\n self.policy_store = PolicyStore()\\n self.service_store = {}\\n\\n from ranger_performance_tool import perf_globals\\n enabled_services = perf_globals.CONFIG_READER.get_config_value(\\\"secondary\\\", \\\"enabled_services\\\")\\n service_type_mapping = perf_globals.CONFIG_READER.get_config_value(\\\"secondary\\\", \\\"service_type_mapping\\\")\\n for service_name in enabled_services:\\n if service_name not in service_type_mapping:\\n raise Exception(f\\\"Unknown service name:{service_name}. \\\"\\n f\\\"Add it to service_type_mapping in secondary config file\\\")\\n service_type = service_type_mapping[service_name]\\n random_type = perf_globals.CONFIG_READER.get_config_value(\\\"secondary\\\", \\\"services\\\",\\n service_type, \\\"random_type\\\")\\n self.service_store[service_type] = RangerAPIObjectStore.service_store_def[service_type](random_type=random_type)\",\n \"def initialize_database():\\n # TODO: Refactor the funtime library\\n this.db = Store(this.host).create_lib(this.store_name).get_store()\",\n \"def __init__(self, storage=default_storage, prefix=\\\"assets\\\", cache_name=\\\"optimizations.assetcache\\\"):\\n self._storage = storage\\n self._prefix = prefix\\n self._cache = resolve_namespaced_cache(cache_name)\",\n \"def __init__(self, processManager, clientManager):\\n self.processManager = processManager\\n self.clientManager = clientManager\\n self.engine_types = {}\\n self.engine_allocations = {}\\n self.engine_instances = {}\",\n \"def test_init_with_client(self):\\n ps = PersistenceStore(s3_client=S3NotConnected())\\n assert ps.s3_client is not None\",\n \"def __init__(self, backend, path, url, storage):\\n self.backend = backend\\n self.path = path\\n self.url = url\\n self.storage = storage\\n self.platforms = {}\",\n \"def __init__(self):\\n\\t\\tself._logger = None\\n\\t\\tself._instanciate_logger()\\n\\t\\tself._video_manager = VideoManager(self, self._logger)\\n\\t\\tself._video_thread = None\\n\\t\\tself._audio_manager = AudioManager(self, self._logger)\\n\\t\\tself._audio_thread = None\\n\\t\\tself._input_thread = None\\n\\t\\tself._trigger_manager = None\\n\\t\\tself.is_running = False\",\n \"def __init__ ( self, datadir, emulator_home, resample_opts=None ):\\n ObservationStorage.__init__ ( self, datadir, resample_opts )\\n self.sensor = \\\"ETM+\\\"\\n if not os.path.exists ( datadir ):\\n raise IOError, \\\"%s does not appear to exist in the filesystem?!\\\" % datadir\\n\\n self.metadata = []\\n for root, dirnames, filenames in os.walk( datadir ):\\n for filename in fnmatch.filter(filenames, '*.xml'):\\n self.metadata.append(os.path.join(root, filename))\\n\\n self.datadir = datadir\\n\\n if len ( self.metadata ) < 0:\\n raise IOError, \\\"No xml metadatafiles in %s\\\" % self.datadir\\n\\n self._setup_sensor()\\n self._parse_metadata ()\\n self._get_emulators ( emulator_home )\\n self._sort_data ( resample_opts )\",\n \"def __init__(self, memory=4000):\\n self.session = boto3.Session()\\n self.batch_client = self.session.client(\\\"batch\\\")\\n self.logs_client = self.session.client(\\\"logs\\\")\\n self.memory = memory\",\n \"def __init__(self, store):\\n assert store is not None\\n self.store = store\",\n \"async def init(self) -> None:\",\n \"async def init(self) -> None:\",\n \"def init_storage(self):\\n\\n # Create the average rotation matrix (first order).\\n self.first_frame_order = zeros((INC+1, 3, 3), float64)\\n\\n # Create the frame order matrix (each element is ensemble averaged and corresponds to a different time step).\\n self.second_frame_order = zeros((INC+1, 9, 9), float64)\\n\\n # Init the rotation matrix.\\n self.rot = zeros((3, 3), float64)\\n\\n # Some data arrays.\\n self.full = zeros(INC+1)\\n self.count = zeros(INC+1)\",\n \"def __init__(self, handler):\\n self._handler = handler\\n self._storage = []\",\n \"def get_storage():\\n settings = get_settings()\\n sources = sum([source is not None for source in (settings.attach_dir,\\n settings.attach_s3_bucket,\\n settings.attach_gcs_bucket)])\\n if sources < 1:\\n raise Error(\\\"At least of the parameters must be set:\\\",\\n \\\"attach_dir, attach_gcs_bucket, attach_s3_bucket\\\")\\n elif sources > 1:\\n raise Error(\\\"Only one of the parameters must be set:\\\",\\n \\\"attach_dir, attach_gcs_bucket, attach_s3_bucket\\\")\\n if settings.attach_dir is not None:\\n storage = LocalStorage(settings.attach_dir)\\n if settings.attach_s3_bucket is not None:\\n storage = S3Storage(name=settings.attach_s3_bucket,\\n endpoint=settings.attach_s3_endpoint,\\n region=settings.attach_s3_region,\\n access_key=settings.attach_s3_access_key,\\n secret_key=settings.attach_s3_secret_key)\\n if settings.attach_gcs_bucket is not None:\\n storage = GCSStorage(name=settings.attach_gcs_bucket,\\n key=settings.attach_gcs_key)\\n return storage\",\n \"def __init__(__self__, *,\\n account_key: pulumi.Input[str],\\n account_name: pulumi.Input[str],\\n storage_type: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"account_key\\\", account_key)\\n pulumi.set(__self__, \\\"account_name\\\", account_name)\\n pulumi.set(__self__, \\\"storage_type\\\", 'StorageAccount')\",\n \"def __init__(self):\\n super(GconfStore, self).__init__()\\n self._client = gconf.client_get_default()\\n self.__connect_notifications()\",\n \"def __init__ ( self, datadir, emulator_home, resample_opts=None, ):\\n \\n ObservationStorage.__init__ ( self, datadir, resample_opts=None )\\n self.sensor = \\\"SPOT4\\\"\\n if not os.path.exists ( datadir ):\\n raise IOError, \\\"%s does not appear to exist in the filesystem?!\\\"\\n\\n self.metadata = []\\n for root, dirnames, filenames in os.walk( datadir ):\\n for filename in fnmatch.filter(filenames, '*.xml'):\\n self.metadata.append(os.path.join(root, filename))\\n\\n self.datadir = datadir\\n \\n if len ( self.metadata ) < 0:\\n raise IOError, \\\"No xml metadatafiles in %s\\\" % self.datadir\\n\\n self._setup_sensor()\\n self._parse_metadata ()\\n self._get_emulators ( emulator_home )\\n self._sort_data ( resample_opts )\",\n \"def __init__(self):\\n self.s3_resource = boto3.resource('s3')\\n self.s3_client = boto3.client('s3')\",\n \"def _initialize(self, boto_session, sagemaker_client, sagemaker_runtime_client):\\n\\n self.boto_session = boto_session or boto3.Session()\\n self._region_name = self.boto_session.region_name\\n\\n if self._region_name is None:\\n raise ValueError('Must setup local AWS configuration with a region supported by SageMaker.')\\n\\n self.sagemaker_client = LocalSagemakerClient(self)\\n self.sagemaker_runtime_client = LocalSagemakerRuntimeClient(self.config)\\n self.local_mode = True\",\n \"def get_swift_storage():\\n\\n return SwiftStorage(\\n os_tenant_id=\\\"os_tenant_id\\\",\\n os_tenant_name=\\\"os_tenant_name\\\",\\n os_username=\\\"os_username\\\",\\n os_password=\\\"os_password\\\",\\n os_region_name=\\\"os_region_name\\\",\\n os_storage_url=\\\"os_storage_url/ralph_logs_container\\\",\\n )\",\n \"def __init__(self, key, active=True, **kwargs):\\n # Support multiple inheritance\\n super(Store, self).__init__()\\n \\n # Make key safe and set it\\n key = key.lower()\\n if not is_filename_safe(key):\\n raise ValueError('Key is not safe for filename')\\n self.key = key\\n \\n # Set filename (if service has started)\\n if self.manager._started:\\n self._pre_start()\\n \\n # Tell fields to initialise themselves\\n for field_name, field in self._fields.items():\\n field.contribute_to_instance(self, field_name)\\n \\n # Now set any field values\\n for field_name, value in kwargs.items():\\n if field_name not in self._fields:\\n raise TypeError(\\n \\\"__init__() got an unexpected keyword argument '%s'\\\" %\\n field_name\\n )\\n setattr(self, field_name, value)\\n \\n # Ensure manager knows about it\\n if active:\\n self.manager.add_active(self)\",\n \"def initialise(self):\\n\\n\\t\\t# Init the sync module\\n\\t\\tSync.init(Conf.get(('redis', 'sync'), {\\n\\t\\t\\t\\\"host\\\": \\\"localhost\\\",\\n\\t\\t\\t\\\"port\\\": 6379,\\n\\t\\t\\t\\\"db\\\": 1\\n\\t\\t}))\",\n \"def storage_factory(cls, prefix, storage_cls=None, storage_uri=None):\\n\\n key_prefix = '{}_{}_'.format(cls.__name__.upper(), prefix.upper())\\n attr = '_{}_storage'.format(prefix)\\n if not storage_cls and not storage_uri:\\n if not hasattr(cls, attr):\\n setattr(cls, attr, cls.storage_cls(cls.storage_uri, key_prefix))\\n return getattr(cls, attr)\\n return (storage_cls or cls.storage_cls)(storage_uri or cls.storage_uri, key_prefix)\",\n \"def _init(self, **kwargs):\\n self.queries: FoldersQueries = FoldersQueries(auth=self.auth, **kwargs)\\n self.enforcements: FoldersEnforcements = FoldersEnforcements(auth=self.auth, **kwargs)\",\n \"def kv_esx_init():\\n disk_lib_init()\",\n \"def init(self):\\n # Initialize runtime and MDK:\\n self.runtime = fakeRuntime()\\n self.runtime.getEnvVarsService().set(\\\"DATAWIRE_TOKEN\\\", \\\"somevalue\\\")\\n self.runtime.dependencies.registerService(\\\"failurepolicy_factory\\\",\\n RecordingFailurePolicyFactory())\\n self.mdk = MDKImpl(self.runtime)\\n self.mdk.start()\\n self.disco = self.mdk._disco\\n # Create a session:\\n self.session = self.mdk.session()\",\n \"def __init__(self):\\n super(MemoryPersistence, self).__init__(descriptor)\",\n \"def __init__(self):\\n self.store = {}\",\n \"def __init__(self, album_store, artist_store, genre_store,\\n track_store, trie_factory):\\n self._album_store = album_store\\n self._artist_store = artist_store\\n self._genre_store = genre_store\\n self._track_store = track_store\\n self._trie_factory = trie_factory\\n\\n self._album_search = None\\n self._artist_search = None\\n self._genre_search = None\\n self._track_search = None\",\n \"def __init__(self):\\n logger.debug(\\\"VMPoolManager: _init_()\\\")\\n self.system = State.Instance()\\n \\n self.VMPools = []\\n e = EnvSetUp()\\n config_spec = json.loads(open(e.get_ovpl_directory_path() + \\\"/config/config.json\\\").read())\\n pools = config_spec[\\\"VMPOOL_CONFIGURATION\\\"][\\\"VMPOOLS\\\"]\\n create_uri = config_spec[\\\"API_ENDPOINTS\\\"][\\\"CREATE_URI_ADAPTER_ENDPOINT\\\"]\\n destroy_uri = config_spec[\\\"API_ENDPOINTS\\\"][\\\"DESTROY_URI_ADAPTER_ENDPOINT\\\"]\\n\\n for pool in pools:\\n self.add_vm_pool( pool[\\\"POOLID\\\"], \\\\\\n pool[\\\"DESCRIPTION\\\"], \\\\\\n pool[\\\"ADAPTERIP\\\"], \\\\\\n pool[\\\"PORT\\\"], \\\\\\n create_uri, \\\\\\n destroy_uri)\\n\\n logger.debug(\\\"VMPoolManager: _init_(); vm_pools = %s\\\" % (str(self.VMPools)))\",\n \"def _initialize(self):\\n configured_providers = self.domain.config[\\\"DATABASES\\\"]\\n provider_objects = {}\\n\\n if configured_providers and isinstance(configured_providers, dict):\\n if \\\"default\\\" not in configured_providers:\\n raise ConfigurationError(\\\"You must define a 'default' provider\\\")\\n\\n for provider_name, conn_info in configured_providers.items():\\n provider_full_path = conn_info[\\\"PROVIDER\\\"]\\n provider_module, provider_class = provider_full_path.rsplit(\\n \\\".\\\", maxsplit=1\\n )\\n\\n provider_cls = getattr(\\n importlib.import_module(provider_module), provider_class\\n )\\n provider = provider_cls(provider_name, self.domain, conn_info)\\n\\n provider_objects[provider_name] = provider\\n\\n self._providers = provider_objects\",\n \"def startManager(self):\\n\\t\\tlogging.info(\\\"----->>>The DeviceDataManager will be started\\\")\\n\\t\\tself.sysPerfManager.startManager()\\n\\t\\tself.sensorAdapterManager.startManager()\\n\\t\\tif self.enableRedis:\\n\\t\\t\\tself.redisClient.connectClient()\\n\\t\\t\\n\\t\\tif self.enableMqtt:\\n\\t\\t\\tself.mqttClient.connectClient()\",\n \"def __init__(self):\\n self._store: ObservationStore = {}\\n self._memory_lower_bound = 0\",\n \"def _CreateStorageFile(self):\\n return sqlite_file.SQLiteStorageFile(storage_type=self._storage_type)\",\n \"def store(self):\\n\\t\\timport shelve\\n\\n\\t\\td = shelve.open(\\\".storedmanager\\\",writeback=True)\\n\\t\\td[\\\"storedmanager\\\"] = self\\n\\n\\t\\td.close()\",\n \"def init(market_manager_):\\n global market_manager\\n market_manager = market_manager_\",\n \"def open(self):\\n super(DiskCache, self).open()\\n if self.__env:\\n return\\n try:\\n os.makedirs(self.__path)\\n except OSError:\\n pass # Directory already exists\\n\\n logging.info(\\n \\\"Opening cache %s (ttl: %s, sync: %s)\\\", self.__path, self.__ttl, self.__sync\\n )\\n self.__env = lmdb.open(\\n self.__path,\\n map_size=self.__size,\\n # Only one sync per transaction, system crash can undo a transaction.\\n metasync=False,\\n # Actually, don't sync at all.\\n sync=self.__sync,\\n map_async=not self.__sync,\\n # Use mmap()\\n writemap=True,\\n # Max number of concurrent readers, see _MAX_READERS for details\\n max_readers=self._MAX_READERS,\\n # How many DBs we may create (until we increase version prefix).\\n max_dbs=8,\\n # A cache of read-only transactions, should match max number of threads.\\n # Only transactions that are actually used concurrently allocate memory,\\n # so setting a high number doesn't cost much even if thread count is low.\\n max_spare_txns=128,\\n )\\n\\n # Clean stale readers. This can be needed if a previous instance crashed or\\n # was killed abruptly (HUP, TERM, KILL...) and the lock file was always used\\n # typically by other UWSGI workers.\\n cleaned_stale_reader = self.__env.reader_check()\\n logging.info(\\\"%d stale readers cleared.\\\" % cleaned_stale_reader)\\n\\n databases = {}\\n for name in self.__databases:\\n databases[name] = self.__env.open_db(name.encode())\\n self.__databases = databases\\n\\n self.__metric_to_metadata_db = databases[\\\"metric_to_meta\\\"]\",\n \"def __init__(self,\\n checkpoint_path=None,\\n max_state_size=None,\\n j_jobmanager_checkpoint_storage=None):\\n if j_jobmanager_checkpoint_storage is None:\\n gateway = get_gateway()\\n JJobManagerCheckpointStorage = gateway.jvm.org.apache.flink.runtime.state.storage\\\\\\n .JobManagerCheckpointStorage\\n JPath = gateway.jvm.org.apache.flink.core.fs.Path\\n\\n if checkpoint_path is not None:\\n checkpoint_path = JPath(checkpoint_path)\\n if max_state_size is None:\\n max_state_size = JJobManagerCheckpointStorage.DEFAULT_MAX_STATE_SIZE\\n j_jobmanager_checkpoint_storage = JJobManagerCheckpointStorage(checkpoint_path,\\n max_state_size)\\n\\n super(JobManagerCheckpointStorage, self).__init__(j_jobmanager_checkpoint_storage)\",\n \"def get_storage_factory(settings, prefix='filestore'):\\n # Pull prefix.key out of the config object\\n kwargs = {}\\n plen = len(prefix)\\n for key, val in settings.iteritems():\\n if key[0:plen] == prefix and len(key) > plen:\\n kwargs[ key[plen+1:] ] = val\\n\\n # Resolve the data manager\\n resolver = DottedNameResolver(None)\\n manager = settings[prefix]\\n name = 'floof.model.filestore.' + manager + '.FileStorage'\\n try:\\n storage = resolver.resolve(name)\\n except ImportError:\\n storage = resolver.resolve(manager)\\n\\n def storage_factory():\\n \\\"\\\"\\\"Returns an instance of the chosen data manager for attachement to a\\n request object and use over the life of a single request. The instance\\n must be manually joined to a Zope-style transaction.\\\"\\\"\\\"\\n return storage(transaction.manager, **kwargs)\\n\\n return storage_factory\",\n \"def init_managers(endpoints_file: Optional[Text]) -> None:\",\n \"def __init__(self):\\n self._url_base = None\\n self._keystone = None\\n self._auth_token = None\\n self._auth_lock = threading.Lock()\\n self._failed_auth = False\",\n \"def __init__(self, fileStore, sqlStore, uid=None, gid=None, merge=False):\\n\\n self.fileStore = fileStore\\n self.sqlStore = sqlStore\\n self.uid = uid\\n self.gid = gid\\n self.merge = merge\",\n \"def __init__(self, source_path, output_path):\\n self.storage_type = 's3' if 's3' in source_path else 'local'\\n self.source_path = source_path\\n self.output_path = output_path\",\n \"def __init__(self, filter: Filter, matcher: Matcher, storage_manager: StorageManager):\\n super().__init__()\\n self.filter = filter\\n self.matcher = matcher\\n self.storage_manager = storage_manager\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: ObjectStorageKeyArgs,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6641924","0.6619307","0.6612643","0.6593752","0.6475286","0.6464472","0.63604945","0.63438195","0.62690544","0.62511116","0.6243224","0.6091188","0.6026038","0.60204107","0.6006953","0.5971609","0.59692246","0.59356165","0.592682","0.59250253","0.5923123","0.5903536","0.58808064","0.58246404","0.57939684","0.5789716","0.578825","0.57870394","0.5781331","0.5771884","0.5767617","0.5741206","0.5735246","0.5717038","0.5714614","0.5688668","0.5684262","0.5679611","0.56554586","0.5636577","0.5633526","0.5624645","0.56204075","0.5617532","0.55999684","0.55990016","0.5592287","0.5562807","0.5562761","0.5548433","0.5511258","0.55054724","0.54999036","0.54974216","0.54788005","0.5471618","0.54674035","0.5464201","0.54543066","0.543749","0.5433115","0.5429036","0.5426133","0.5421064","0.5420358","0.54165876","0.54165876","0.541546","0.5412969","0.53943354","0.5388529","0.53822905","0.53724766","0.5370996","0.53624475","0.5351589","0.53485954","0.53485286","0.53438747","0.5343714","0.5338692","0.53385156","0.53376037","0.53341687","0.53226304","0.5311877","0.53069264","0.53033984","0.5298586","0.52954954","0.5286265","0.5284369","0.52791137","0.5274211","0.5274166","0.5274165","0.5273465","0.5261535","0.52582234","0.525422","0.5253634"],"string":"[\n \"0.6641924\",\n \"0.6619307\",\n \"0.6612643\",\n \"0.6593752\",\n \"0.6475286\",\n \"0.6464472\",\n \"0.63604945\",\n \"0.63438195\",\n \"0.62690544\",\n \"0.62511116\",\n \"0.6243224\",\n \"0.6091188\",\n \"0.6026038\",\n \"0.60204107\",\n \"0.6006953\",\n \"0.5971609\",\n \"0.59692246\",\n \"0.59356165\",\n \"0.592682\",\n \"0.59250253\",\n \"0.5923123\",\n \"0.5903536\",\n \"0.58808064\",\n \"0.58246404\",\n \"0.57939684\",\n \"0.5789716\",\n \"0.578825\",\n \"0.57870394\",\n \"0.5781331\",\n \"0.5771884\",\n \"0.5767617\",\n \"0.5741206\",\n \"0.5735246\",\n \"0.5717038\",\n \"0.5714614\",\n \"0.5688668\",\n \"0.5684262\",\n \"0.5679611\",\n \"0.56554586\",\n \"0.5636577\",\n \"0.5633526\",\n \"0.5624645\",\n \"0.56204075\",\n \"0.5617532\",\n \"0.55999684\",\n \"0.55990016\",\n \"0.5592287\",\n \"0.5562807\",\n \"0.5562761\",\n \"0.5548433\",\n \"0.5511258\",\n \"0.55054724\",\n \"0.54999036\",\n \"0.54974216\",\n \"0.54788005\",\n \"0.5471618\",\n \"0.54674035\",\n \"0.5464201\",\n \"0.54543066\",\n \"0.543749\",\n \"0.5433115\",\n \"0.5429036\",\n \"0.5426133\",\n \"0.5421064\",\n \"0.5420358\",\n \"0.54165876\",\n \"0.54165876\",\n \"0.541546\",\n \"0.5412969\",\n \"0.53943354\",\n \"0.5388529\",\n \"0.53822905\",\n \"0.53724766\",\n \"0.5370996\",\n \"0.53624475\",\n \"0.5351589\",\n \"0.53485954\",\n \"0.53485286\",\n \"0.53438747\",\n \"0.5343714\",\n \"0.5338692\",\n \"0.53385156\",\n \"0.53376037\",\n \"0.53341687\",\n \"0.53226304\",\n \"0.5311877\",\n \"0.53069264\",\n \"0.53033984\",\n \"0.5298586\",\n \"0.52954954\",\n \"0.5286265\",\n \"0.5284369\",\n \"0.52791137\",\n \"0.5274211\",\n \"0.5274166\",\n \"0.5274165\",\n \"0.5273465\",\n \"0.5261535\",\n \"0.52582234\",\n \"0.525422\",\n \"0.5253634\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":18694,"cells":{"query":{"kind":"string","value":"Retreive a file from the file storage."},"document":{"kind":"string","value":"def storage_get_file(self, group='', key=''):\n try:\n obj = None\n content = None\n if key != '':\n if self.config['type'] == 's3':\n obj = self.s3.Object(bucket_name=self.bucket, key='corr-{0}s/{1}'.format(group,key))\n res = obj.get()\n content = res['Body'].read()\n elif self.config['type'] == 'filesystem':\n with open('{0}/corr-{1}s/{2}'.format(self.storage_path, group, key), \"rb\") as obj:\n content = obj.read()\n else:\n content = None\n\n except:\n print(traceback.print_exc())\n content = None\n\n try:\n if self.config['type'] == 's3':\n file_buffer = BytesIO()\n elif self.config['type'] == 'filesystem':\n file_buffer = BytesIO()\n file_buffer.write(content)\n file_buffer.seek(0)\n return file_buffer\n except:\n self.app.logger.error(traceback.print_exc())\n print(traceback.print_exc())\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(self, filename, **kw):\n\n file_path = os.path.join(self.storage_path, filename)\n try:\n file_obj = open(file_path, \"r\")\n except IOError:\n return\n else:\n return file_obj.read()","def get_file(URI):\n return file_fabric.get_class(URI).get_content(URI)","def file(self):\n if self.state == self.STATE_COMPLETED:\n return default_storage.open(self.path)\n return None","def get_file(self, path):\n file = self.get('data_request?id=file¶meters=%s' % path)\n return file","def get(self, filename=None):\n try:\n return self.storage.get(filename)\n except FileNotFoundError:\n abort(404, message='File %s does not exist' % filename)\n except BaseException:\n message = 'Failed to list the files of storage'\n if filename:\n message = 'Failed to get the file ' + filename\n\n abort(500, message=message)\n\n LOGGER.error('A generic exception has occurred.', exc_info=True)","def getFile(self, resource):\n resource = self.parseUrl(resource, 'files')\n\n res = self.getRequest(resource)\n fObj = vsdModels.File(**res)\n return fObj","def get(self, filepath):\n try:\n collname = '%s.files' % self.bucketname\n coll = Collection(self.db, collname)\n if coll:\n doc = coll.find_one({'filename': str(filepath)}, sort=[('uploadDate', -1)])\n if doc:\n id = doc['_id']\n gout = self.gridfs.get(ObjectId(id))\n if gout:\n content = gout.read()\n gout.close()\n return content\n except Exception, e:\n print e\n return None","def get_file(self, path):\n return self._files.get(self._get_rel_path(path))","def get_file(self, name):\n return self.files[name]","def get_file(service, file_id):\n return service.files().get(fileId=file_id).execute()","def get_file(self, file_name: str) -> BytesIO:\n fl = BytesIO()\n self.client.download_fileobj(self.bucket, file_name, fl)\n fl.seek(0)\n return fl","def get_file(self):\n return self.theFile","def get_file():\n fname = get_var(request, \"fname\")\n return open(fname).read()","def get_file(self, sys_id):\n url = \"{}/file\".format(self._target(sys_id))\n r = self._client.session.get(url, stream=True)\n return r","def get_file(self, path):\n return self.client._perform_raw(\n \"GET\", \"/projects/%s/managedfolders/%s/contents/%s\" % (self.project_key, self.odb_id, utils.quote(path)))","async def get_file(self, file_id: base.String) -> types.File:\n payload = generate_payload(**locals())\n result = await self.request(api.Methods.GET_FILE, payload)\n\n return types.File(**result)","def GetFile(file_name):\n\n the_file = None\n\n try:\n the_file = open(file_name, 'rb')\n \n except IOError:\n the_file = None\n \n return the_file","def get_file(self, filename, handler=False):\n result = None\n if self.exists(filename):\n file_path = join_paths(self.path, filename)\n if handler:\n result = open(file_path, 'rb')\n else:\n result = file_path\n return result","def get(self, resource_id, file_id):\n d = Deposition.get(resource_id, user=current_user)\n df = d.get_file(file_id)\n if df is None:\n abort(404, message=\"File does not exist\", status=404)\n return d.type.marshal_file(df)","def get_file(cls, url, working_dir):\n if url.lower().startswith(\"s3://\"):\n return cls._s3_get_file(url)\n elif url.lower().startswith(\"http\"):\n return cls._http_get_file(url)\n else:\n return cls._fs_get_file(url, working_dir)","def get(self, id):\n file = (\n self.drive.files()\n .get(\n fileId=id,\n fields=\"id, name\",\n supportsAllDrives=self.shared_drive[0],\n )\n .execute()\n )\n return file","def get_file(self, key):\n result = (None, None)\n path = os.path.join(self.directory, self.subdirectory, key)\n if os.path.isfile(path):\n content_type, _ = mimetypes.guess_type(path)\n with open(path, \"rb\") as file:\n result = content_type, file.read()\n return result","def get_file(self, file_path):\n try:\n return self._files[file_path]\n except KeyError:\n file = File()\n self._files[file_path] = file\n return file","def _fs_get_file(url, working_dir):\n if not os.path.isabs(url) and working_dir:\n url = os.path.join(working_dir, url)\n\n try:\n with codecs.open(url, 'r', encoding='utf-8') as f:\n return f.read()\n except Exception as e:\n raise ScrBaseException(\"Could not load file from {0}: {1}\".format(url, e))","def get_file(self, file_id):\n LOG.debug(\"Getting a file from mattermost\")\n url = '%s/api/v4/files/%s' % (self.server_url, file_id)\n LOG.debug(\"Sending: %s\", url)\n response = self._request(self._session.get, url)\n\n if response.status_code != 200:\n raise RuntimeError(\"Server unhappy. (%s)\", response)\n\n return response.content","def get_file(self, remote_path, local_path, storage_id=None):\n return self.get(remote_path, local_path, directory=False, storage_id=storage_id)","def get_file(self, filename):\r\n\r\n return File.from_name(self, filename)","def _get_file(self, path: str) -> Tuple[str, bytes]:\n self._trace(\"fetching: %s\" % path)\n meta, resp = self._connection.files_download(path)\n return (meta.rev, resp.content)","def file(self) :\n\t\ttry :\n\t\t\treturn self._file\n\t\texcept Exception as e:\n\t\t\traise e","def web_get_file(self, url):\n try:\n print(url)\n response = requests.get(url, verify=False)\n file_buffer = BytesIO(response.content)\n file_buffer.seek(0)\n return file_buffer\n except:\n print(traceback.print_exc())\n return None","def get_file(self, filename):\n log.debug('[%s]: reading: //%s/%s', self.name, self.name, filename)\n try:\n blob = self.repo.head.commit.tree/filename\n return blob.data_stream\n except KeyError as err:\n raise GitError(err)","def get_file_object(self):\n try:\n # FieldFile.open() and File.open() don't return file objects, so\n # accessing it directly\n return self.datafile.file.file # FileStoreItem.FieldFile.File.file\n except ValueError as exc:\n logger.error(\"Error opening %s: %s\", self.datafile, exc)\n return None","def get_content(self, filename):\n f_id = self.face.FACES.files.find_one({ \"filename\" : filename }, { \"_id\" : 1 })\n return self.face_fs.get(f_id['_id']).read()","def open(self):\n return File(open(self.get_path()), \"rb\")","def get_file(self, **kwargs) -> File:\n file_name = self._get_file_name()\n file_data = self._download_from_url()\n return File(file_name, BytesIO(file_data))","def get(self, filepath: str) -> bytes:\n if self.isfile(filepath):\n return storage_services.get(\n self._bucket_name, self._get_gcs_file_url(filepath))\n else:\n raise IOError('File %s not found.' % (filepath))","def get_file(self, path):\n path = os.path.normpath(path)\n cmd = [\"ls\", \"-lZ\", \"'\" + path + \"'\"]\n listing = subprocess.check_output(self.shell + cmd).decode().split('\\n')\n line = listing[0].strip(\"\\r\")\n # Parse ls -lZ output for a single file\n try:\n f = File(line, os.path.dirname(path), self.android_version)\n except ValueError as e:\n self.log.error(e)\n return None\n else:\n return {f.absname: f}","def retreive(self, mode=\"rb\"):\n\t\tif DBF_SETTINGS[\"DATABASE_FILES_CACHE\"]:\n\t\t\testring = cache.get(self.get_cache_key())\n\t\t\tif not estring:\n\t\t\t\testring = self._decode_string(self._retreive_string())\n\t\t\t\tif not DBF_SETTINGS[\"DATABASE_FILES_CACHE_UNENCRYPTED\"]:\n\t\t\t\t\testring = self._process_string(estring)\n\t\t\t\tcache.set(self.get_cache_key(), estring)\n\t\t\telse:\n\t\t\t\testring = self._decode_string(self._retreive_string())\n\t\t\t\testring = self._process_string(estring)\n\t\telse:\n\t\t\testring = self._retreive_string()\n\t\t\testring = self._decode_string(estring)\n\t\t\testring = self._process_string(estring)\n\n\t\tstring_file = StringIO(estring)\n\t\tdjango_file = DBFile(string_file)\n\t\tdjango_file.name = self.filepath\n\t\tdjango_file.mode = mode\n\t\tdjango_file.size = self.size\n\t\tdjango_file.url = self.get_absolute_url()\n\t\tdjango_file.label = self.nicename\n\n\t\tself.accessed_time = datetime.now()\n\t\tself.save()\n\t\treturn django_file","def get_file(self, path):\n _url = f\"{self.connector.base_url}/projects/{self.project_id}/files/{path}\"\n\n return self.connector.http_call(\"get\", _url).text","def file(self, file_id):\r\n return files.File(self, file_id)","def get_file(_file):\n _file = pathlib.Path(_file)\n if not _file.is_file():\n _file = None\n return _file","def get_file(self, path):\n b_file = self.get_b_file(path)\n if b_file:\n return b_file\n return self.get_a_file(path)","def getFile(self, file_name: str) -> bytes:\n obj = self.driver.get_object(self.container_name, file_name)\n gen = self.driver.download_object_as_stream(obj)\n file_as_bytes = next(gen)\n return file_as_bytes","def get_uploaded_file(filename):\n client = _get_client()\n key = client.key(_FILE_ENTITY, filename)\n entity = client.get(key)\n if entity:\n return UploadedFile(filename, entity['url'])\n return None","def read_file(self, entity):\n\n return self.cache.read_file(\n entity.objects['project'],\n entity.objects['ref'],\n entity.objects['file']['path']\n )","def get_local_file(self, no_copy=False):\n return self.get_file(uri_type=URI_LOCAL, no_copy=no_copy)","def getFile(filename):\n filename = os.path.join(os.path.dirname(__file__), filename)\n return open(filename, 'r')","def getFile(filename):\n filename = os.path.join(os.path.dirname(__file__), filename)\n return open(filename, 'r')","def file_by_file_name(self, file_name):\n ls = self.files.filter_by(file_name=file_name)\n return ls[0] if 0 < len(ls) else None","def storage_get(context, storage_id):\n return _storage_get(context, storage_id)","def get_gcs_file(self, no_copy=False):\n return self.get_file(uri_type=URI_GCS, no_copy=no_copy)","def GetOpenedFile(self,file):\n\t\tif isinstance(file,str):\n\t\t\tindex = self.OpenedFilenames.index(file)\n\t\telif isinstance(file,int):\n\t\t\tindex=file\n\t\telse:\n\t\t\traise PycomError('Type of file in GetOpenedFile is wrong ')\n\t\treturn self.acad.Documents.Item(index)","def get_file(self, uri_type, no_copy=False):\n return self.copy(target_uri_type=uri_type, no_copy=no_copy)","def get(self, fp, off=0, size=-1):\n self.log.debug(\"GET [%r]: %s:%s\", fp, off, size)\n\n obj_size, _ = self.ioctx.stat(fp)\n\n compression_id = CAS._convert_meta(self.ioctx.get_xattr(fp, \"cas.meta.compression\"))\n decompressor = Compressor.select(compression_id)\n\n self.log.debug(\"GET [%r]: size %d compressed with %r\", fp, obj_size, compression_id)\n\n compressed_data = self.ioctx.read(fp, obj_size, 0)\n data = decompressor.decompress(compressed_data)\n\n if size < 0:\n size = len(data)\n\n return data[off:off+size]","def get_file(self, name, internal=True, fieldids=None, fieldnames=None):\n if self.remote:\n return DBSFileRemote(self.remote, name, internal=internal, fieldnames=fieldnames, fieldids=fieldids)\n\n if name.find('::') >= 0:\n # This is a full path name to a subfile. \n dd = DD(subfile_path=name)\n else:\n # top-level file - dd entry defines the storage.\n dd = DD(name)\n\n if dd.fileid is None:\n raise FilemanError(\"\"\"DBS.get_file() : File not found [%s]\"\"\" % name)\n return DBSFile(dd, internal=internal, fieldids=fieldids, fieldnames=fieldnames, ext_filename=name)","def readFile(self, path):\n return self.session.request('diag/files/?q=%s'\n % (path))","def get(name):\n\n filename = find(name)\n if filename == None:\n return name\n return open(filename).read()","def get_file(self):\n return self.dir + self.file_name + self.extension","def get_file(self, repo, file_name):\n DataHubManager.has_repo_file_privilege(\n self.username, self.repo_base, repo, 'read')\n\n file_path = user_data_path(self.repo_base, repo, file_name)\n file = open(file_path).read()\n return file","def read_file(self, path):\n with open(path) as f:\n return self.read_file_obj(f)","def get_file(self, file_id: str) -> GDriveFile:\n r = requests.get(\n f\"https://www.googleapis.com/drive/v3/files/{file_id}\",\n headers=self._auth_headers\n )\n if r.status_code in self._errors:\n raise ApiResponseException(\n r.status_code, r.json()[\"error\"][\"message\"])\n return GDriveFile(r.json())","def get(self, cls, id):\n\n return FileStorage.__objects[key(cls, id)]","def get_file(self) -> int:\r\n return self.file","def get_file_obj(self, file):\n repository = \"{}/{}\".format(self.org, self.repo)\n ghrepo = self.github.get_repo(repository)\n obj = ghrepo.get_contents(file)\n return obj","def storage_get_report_file(self, report_pk):\n return self._get_queryset(pk=report_pk).get()","def file(self):\n return self._file","def file(self):\n return self._file","def file(self):\n return self._file","def getFile( self, par, path ):\n\n return self.db.getFilePar( par, path )","def _retrieve_filename(file: Union[str, FileStorage]) -> str:\n if isinstance(file, FileStorage):\n return file.filename\n return file","def get(self, resource_id):\n d = Deposition.get(resource_id, user=current_user)\n return map(lambda f: d.type.marshal_file(f), d.files)","def get_file(filename, result):\n return next((f for f in result if f['filename'] == filename), None)","def getInFile( self ):\n return self.file","def _get_file_object(inputfile=None):\n if type(inputfile) == str:\n return open(inputfile, 'r')\n return inputfile","def get_file(self, path):\n _url = (\n f\"{self.connector.base_url}/projects/{self.project_id}/nodes/{self.node_id}\"\n f\"/files/{path}\"\n )\n\n return self.connector.http_call(\"get\", _url).text","def get_file(self, c_path):\n raise NotImplementedError","def file(self):\r\n return self._get_instantiation()[0]","def get_file(self, filename):\n if not filename in self.files:\n raise IOError('File %s Not Found' % filename)\n\n nodename = _random_pick(self.files[filename])\n return self.datanodes[nodename]","def get_remote_file(sid, path):\n with slycat.web.server.remote.get_session(sid) as session:\n return session.get_file(path)","def get_file_content(*args, **kwargs):\n return get_file_content_async(*args, **kwargs).get_result()","def get_demo_file(fname):\n\n d = download_demo_files()\n if fname in d:\n return d[fname]\n else:\n return None","def read(self, mode='rb'):\n\n path = self.get_resource().get_target().fspath\n\n with open(path, mode=mode) as f:\n return f.read()","def request_file(self, path: str, token: str) -> Tuple[IO[bytes], dict]:\n response = self.request('get', path, token, stream=True)\n stream = ReadWrapper(response.iter_content,\n int(response.headers['Content-Length']))\n return stream, response.headers","def getfile(self, name):\n try:\n datname = self.getname(name, \"dat\")\n tadname = self.getname(name, \"tad\")\n if datname and tadname:\n return Datafile(name, open(datname, \"rb\"), open(tadname, \"rb\"), self.kod)\n except IOError:\n return","def get_file(self, file_id, filename=''):\n method = 'getFile?' + 'file_id=' + str(file_id)\n res = requests.post(self.api_url + method, file_id)\n try:\n file_path = res.json()['result']['file_path']\n # Determine the fileName. Use modified file_path if none given.\n if not filename:\n filename = file_path[file_path.rfind('/') + 1:]\n except (KeyError, ValueError):\n return \"500 - Failed parsing the file link from API response.\"\n\n if not os.path.exists(self.dirDownloads):\n os.mkdir(self.dirDownloads)\n\n local_path = os.path.join(self.dirDownloads, filename)\n\n # Download file as stream.\n res = requests.get(self.file_url + file_path, stream=True)\n if res.status_code == 200:\n try:\n with open(local_path, 'wb') as f:\n for chunk in res:\n f.write(chunk)\n except IOError:\n pass\n return '200 - {} written.'.format(local_path)\n else:\n return '404 - Error accessing {}'.format(file_path)","def read(self, path, filename=None, offset=None, size=-1):\n storageScheme, key = self.getkey(path, filename=filename)\n\n if offset or (size > -1):\n if not offset:\n offset = 0\n if size > -1:\n sizeStr = offset + size - 1 # range header is inclusive\n else:\n sizeStr = \"\"\n headers = {\"Range\": \"bytes=%d-%s\" % (offset, sizeStr)}\n return key.get_contents_as_string(headers=headers)\n else:\n return key.get_contents_as_string()","def GetFromStore(self, file_path):\n resp_data = None\n file_itr = iter(self.zipfilenames)\n\n # check the index, if we have one, to see what archive the file is in\n archive_name = self.MapFileToArchive(file_path)\n if not archive_name:\n archive_name = file_itr.next()[0]\n\n while resp_data is None and archive_name:\n zip_archive = self.LoadZipFile(archive_name)\n if zip_archive:\n\n # we expect some lookups will fail, and that's okay, 404s will deal\n # with that\n try:\n resp_data = zip_archive.read(file_path)\n except (KeyError, RuntimeError), err:\n # no op\n x = False\n if resp_data is not None:\n logging.info('%s read from %s', file_path, archive_name)\n \n try:\n archive_name = file_itr.next()[0]\n except (StopIteration), err:\n archive_name = False\n\n return resp_data","def GetFromStore(self, file_path):\n resp_data = None\n file_itr = iter(self.zipfilenames)\n\n # check the index, if we have one, to see what archive the file is in\n archive_name = self.MapFileToArchive(file_path)\n if not archive_name:\n archive_name = file_itr.next()[0]\n\n while resp_data is None and archive_name:\n zip_archive = self.LoadZipFile(archive_name)\n if zip_archive:\n\n # we expect some lookups will fail, and that's okay, 404s will deal\n # with that\n try:\n resp_data = zip_archive.read(file_path)\n except (KeyError, RuntimeError), err:\n # no op\n x = False\n if resp_data is not None:\n logging.info('%s read from %s', file_path, archive_name)\n\n try:\n archive_name = file_itr.next()[0]\n except (StopIteration), err:\n archive_name = False\n\n return resp_data","def get_file(self, path):\n tarstream = io.BytesIO()\n for chunk in self.container.get_archive(path=path)[0]:\n tarstream.write(chunk)\n tarstream.seek(0)\n with tarfile.open(fileobj=tarstream) as tarfile_:\n for tarinfo in tarfile_.getmembers():\n return tarfile_.extractfile(tarinfo).read().decode()","def get(self, save=False, filename=None):\n page, content = self._get_file_helper()\n\n filename = _negotiate_filename(page, filename, save)\n\n if save and filename:\n with open(filename, 'wb') as fh:\n fh.write(content)\n\n return content, filename","def get_file(self, file_path, container_name, blob_name, **kwargs):\n return self.connection.get_blob_to_path(container_name, blob_name,\n file_path, **kwargs)","def get_file_entry(self):\n pass","def read_file(self):\n self._apply_shared_lock()\n\n self.handle = self._open_file_r()\n out = self._deserialize(self.handle)\n self.handle.close()\n\n self._release_lock()\n\n return out","def retrieve_document(self, format):\n self._validate_extension(format.upper(), self.ALLOWED_DOCUMENT_EXT)\n return self.client.service.RetrieveDocument(format=format.upper()).decode('base64')","def retrieve(self, file_name):\n ret = os.path.join(self.path, file_name)\n temp = (self.path + file_name).find(self.path, 1, -1)\n if os.path.exists(ret):\n return os.path.join(self.path, file_name)\n elif temp != -1:\n if os.name == \"posix\":\n return os.getcwd() + '/' + file_name\n else:\n return os.getcwd() + '\\\\' + file_name\n else:\n return None","def get_file(filename):\n content = Tree.file_content(filename)\n file_name = \"attachment;filename={0}\".format(filename)\n return Response(content, mimetype=\"text/plain\",\n headers={\"Content-Disposition\": file_name})","def get_blob(self, blob_name):\n return self.bucket.get_blob(blob_name)","def _metadata_get(self, path):\n fd = self.fs.open(path, \"r\")\n # TODO iterate instead of assuming file < 4MB\n read_bytes = self.fs.read(fd, 0, 4096 * 1024)\n self.fs.close(fd)\n if read_bytes:\n return json.loads(read_bytes.decode())\n else:\n return None","def get_file(object_name: str, **kwargs) -> HTTPResponse:\n data = client.get_object(DATASETS_BUCKET, object_name, **kwargs)\n return data","def retrieve_object(self, name: str):\n file_path = self.__get_file_path(name)\n return self.__deserialize_object(file_path)"],"string":"[\n \"def get(self, filename, **kw):\\n\\n file_path = os.path.join(self.storage_path, filename)\\n try:\\n file_obj = open(file_path, \\\"r\\\")\\n except IOError:\\n return\\n else:\\n return file_obj.read()\",\n \"def get_file(URI):\\n return file_fabric.get_class(URI).get_content(URI)\",\n \"def file(self):\\n if self.state == self.STATE_COMPLETED:\\n return default_storage.open(self.path)\\n return None\",\n \"def get_file(self, path):\\n file = self.get('data_request?id=file¶meters=%s' % path)\\n return file\",\n \"def get(self, filename=None):\\n try:\\n return self.storage.get(filename)\\n except FileNotFoundError:\\n abort(404, message='File %s does not exist' % filename)\\n except BaseException:\\n message = 'Failed to list the files of storage'\\n if filename:\\n message = 'Failed to get the file ' + filename\\n\\n abort(500, message=message)\\n\\n LOGGER.error('A generic exception has occurred.', exc_info=True)\",\n \"def getFile(self, resource):\\n resource = self.parseUrl(resource, 'files')\\n\\n res = self.getRequest(resource)\\n fObj = vsdModels.File(**res)\\n return fObj\",\n \"def get(self, filepath):\\n try:\\n collname = '%s.files' % self.bucketname\\n coll = Collection(self.db, collname)\\n if coll:\\n doc = coll.find_one({'filename': str(filepath)}, sort=[('uploadDate', -1)])\\n if doc:\\n id = doc['_id']\\n gout = self.gridfs.get(ObjectId(id))\\n if gout:\\n content = gout.read()\\n gout.close()\\n return content\\n except Exception, e:\\n print e\\n return None\",\n \"def get_file(self, path):\\n return self._files.get(self._get_rel_path(path))\",\n \"def get_file(self, name):\\n return self.files[name]\",\n \"def get_file(service, file_id):\\n return service.files().get(fileId=file_id).execute()\",\n \"def get_file(self, file_name: str) -> BytesIO:\\n fl = BytesIO()\\n self.client.download_fileobj(self.bucket, file_name, fl)\\n fl.seek(0)\\n return fl\",\n \"def get_file(self):\\n return self.theFile\",\n \"def get_file():\\n fname = get_var(request, \\\"fname\\\")\\n return open(fname).read()\",\n \"def get_file(self, sys_id):\\n url = \\\"{}/file\\\".format(self._target(sys_id))\\n r = self._client.session.get(url, stream=True)\\n return r\",\n \"def get_file(self, path):\\n return self.client._perform_raw(\\n \\\"GET\\\", \\\"/projects/%s/managedfolders/%s/contents/%s\\\" % (self.project_key, self.odb_id, utils.quote(path)))\",\n \"async def get_file(self, file_id: base.String) -> types.File:\\n payload = generate_payload(**locals())\\n result = await self.request(api.Methods.GET_FILE, payload)\\n\\n return types.File(**result)\",\n \"def GetFile(file_name):\\n\\n the_file = None\\n\\n try:\\n the_file = open(file_name, 'rb')\\n \\n except IOError:\\n the_file = None\\n \\n return the_file\",\n \"def get_file(self, filename, handler=False):\\n result = None\\n if self.exists(filename):\\n file_path = join_paths(self.path, filename)\\n if handler:\\n result = open(file_path, 'rb')\\n else:\\n result = file_path\\n return result\",\n \"def get(self, resource_id, file_id):\\n d = Deposition.get(resource_id, user=current_user)\\n df = d.get_file(file_id)\\n if df is None:\\n abort(404, message=\\\"File does not exist\\\", status=404)\\n return d.type.marshal_file(df)\",\n \"def get_file(cls, url, working_dir):\\n if url.lower().startswith(\\\"s3://\\\"):\\n return cls._s3_get_file(url)\\n elif url.lower().startswith(\\\"http\\\"):\\n return cls._http_get_file(url)\\n else:\\n return cls._fs_get_file(url, working_dir)\",\n \"def get(self, id):\\n file = (\\n self.drive.files()\\n .get(\\n fileId=id,\\n fields=\\\"id, name\\\",\\n supportsAllDrives=self.shared_drive[0],\\n )\\n .execute()\\n )\\n return file\",\n \"def get_file(self, key):\\n result = (None, None)\\n path = os.path.join(self.directory, self.subdirectory, key)\\n if os.path.isfile(path):\\n content_type, _ = mimetypes.guess_type(path)\\n with open(path, \\\"rb\\\") as file:\\n result = content_type, file.read()\\n return result\",\n \"def get_file(self, file_path):\\n try:\\n return self._files[file_path]\\n except KeyError:\\n file = File()\\n self._files[file_path] = file\\n return file\",\n \"def _fs_get_file(url, working_dir):\\n if not os.path.isabs(url) and working_dir:\\n url = os.path.join(working_dir, url)\\n\\n try:\\n with codecs.open(url, 'r', encoding='utf-8') as f:\\n return f.read()\\n except Exception as e:\\n raise ScrBaseException(\\\"Could not load file from {0}: {1}\\\".format(url, e))\",\n \"def get_file(self, file_id):\\n LOG.debug(\\\"Getting a file from mattermost\\\")\\n url = '%s/api/v4/files/%s' % (self.server_url, file_id)\\n LOG.debug(\\\"Sending: %s\\\", url)\\n response = self._request(self._session.get, url)\\n\\n if response.status_code != 200:\\n raise RuntimeError(\\\"Server unhappy. (%s)\\\", response)\\n\\n return response.content\",\n \"def get_file(self, remote_path, local_path, storage_id=None):\\n return self.get(remote_path, local_path, directory=False, storage_id=storage_id)\",\n \"def get_file(self, filename):\\r\\n\\r\\n return File.from_name(self, filename)\",\n \"def _get_file(self, path: str) -> Tuple[str, bytes]:\\n self._trace(\\\"fetching: %s\\\" % path)\\n meta, resp = self._connection.files_download(path)\\n return (meta.rev, resp.content)\",\n \"def file(self) :\\n\\t\\ttry :\\n\\t\\t\\treturn self._file\\n\\t\\texcept Exception as e:\\n\\t\\t\\traise e\",\n \"def web_get_file(self, url):\\n try:\\n print(url)\\n response = requests.get(url, verify=False)\\n file_buffer = BytesIO(response.content)\\n file_buffer.seek(0)\\n return file_buffer\\n except:\\n print(traceback.print_exc())\\n return None\",\n \"def get_file(self, filename):\\n log.debug('[%s]: reading: //%s/%s', self.name, self.name, filename)\\n try:\\n blob = self.repo.head.commit.tree/filename\\n return blob.data_stream\\n except KeyError as err:\\n raise GitError(err)\",\n \"def get_file_object(self):\\n try:\\n # FieldFile.open() and File.open() don't return file objects, so\\n # accessing it directly\\n return self.datafile.file.file # FileStoreItem.FieldFile.File.file\\n except ValueError as exc:\\n logger.error(\\\"Error opening %s: %s\\\", self.datafile, exc)\\n return None\",\n \"def get_content(self, filename):\\n f_id = self.face.FACES.files.find_one({ \\\"filename\\\" : filename }, { \\\"_id\\\" : 1 })\\n return self.face_fs.get(f_id['_id']).read()\",\n \"def open(self):\\n return File(open(self.get_path()), \\\"rb\\\")\",\n \"def get_file(self, **kwargs) -> File:\\n file_name = self._get_file_name()\\n file_data = self._download_from_url()\\n return File(file_name, BytesIO(file_data))\",\n \"def get(self, filepath: str) -> bytes:\\n if self.isfile(filepath):\\n return storage_services.get(\\n self._bucket_name, self._get_gcs_file_url(filepath))\\n else:\\n raise IOError('File %s not found.' % (filepath))\",\n \"def get_file(self, path):\\n path = os.path.normpath(path)\\n cmd = [\\\"ls\\\", \\\"-lZ\\\", \\\"'\\\" + path + \\\"'\\\"]\\n listing = subprocess.check_output(self.shell + cmd).decode().split('\\\\n')\\n line = listing[0].strip(\\\"\\\\r\\\")\\n # Parse ls -lZ output for a single file\\n try:\\n f = File(line, os.path.dirname(path), self.android_version)\\n except ValueError as e:\\n self.log.error(e)\\n return None\\n else:\\n return {f.absname: f}\",\n \"def retreive(self, mode=\\\"rb\\\"):\\n\\t\\tif DBF_SETTINGS[\\\"DATABASE_FILES_CACHE\\\"]:\\n\\t\\t\\testring = cache.get(self.get_cache_key())\\n\\t\\t\\tif not estring:\\n\\t\\t\\t\\testring = self._decode_string(self._retreive_string())\\n\\t\\t\\t\\tif not DBF_SETTINGS[\\\"DATABASE_FILES_CACHE_UNENCRYPTED\\\"]:\\n\\t\\t\\t\\t\\testring = self._process_string(estring)\\n\\t\\t\\t\\tcache.set(self.get_cache_key(), estring)\\n\\t\\t\\telse:\\n\\t\\t\\t\\testring = self._decode_string(self._retreive_string())\\n\\t\\t\\t\\testring = self._process_string(estring)\\n\\t\\telse:\\n\\t\\t\\testring = self._retreive_string()\\n\\t\\t\\testring = self._decode_string(estring)\\n\\t\\t\\testring = self._process_string(estring)\\n\\n\\t\\tstring_file = StringIO(estring)\\n\\t\\tdjango_file = DBFile(string_file)\\n\\t\\tdjango_file.name = self.filepath\\n\\t\\tdjango_file.mode = mode\\n\\t\\tdjango_file.size = self.size\\n\\t\\tdjango_file.url = self.get_absolute_url()\\n\\t\\tdjango_file.label = self.nicename\\n\\n\\t\\tself.accessed_time = datetime.now()\\n\\t\\tself.save()\\n\\t\\treturn django_file\",\n \"def get_file(self, path):\\n _url = f\\\"{self.connector.base_url}/projects/{self.project_id}/files/{path}\\\"\\n\\n return self.connector.http_call(\\\"get\\\", _url).text\",\n \"def file(self, file_id):\\r\\n return files.File(self, file_id)\",\n \"def get_file(_file):\\n _file = pathlib.Path(_file)\\n if not _file.is_file():\\n _file = None\\n return _file\",\n \"def get_file(self, path):\\n b_file = self.get_b_file(path)\\n if b_file:\\n return b_file\\n return self.get_a_file(path)\",\n \"def getFile(self, file_name: str) -> bytes:\\n obj = self.driver.get_object(self.container_name, file_name)\\n gen = self.driver.download_object_as_stream(obj)\\n file_as_bytes = next(gen)\\n return file_as_bytes\",\n \"def get_uploaded_file(filename):\\n client = _get_client()\\n key = client.key(_FILE_ENTITY, filename)\\n entity = client.get(key)\\n if entity:\\n return UploadedFile(filename, entity['url'])\\n return None\",\n \"def read_file(self, entity):\\n\\n return self.cache.read_file(\\n entity.objects['project'],\\n entity.objects['ref'],\\n entity.objects['file']['path']\\n )\",\n \"def get_local_file(self, no_copy=False):\\n return self.get_file(uri_type=URI_LOCAL, no_copy=no_copy)\",\n \"def getFile(filename):\\n filename = os.path.join(os.path.dirname(__file__), filename)\\n return open(filename, 'r')\",\n \"def getFile(filename):\\n filename = os.path.join(os.path.dirname(__file__), filename)\\n return open(filename, 'r')\",\n \"def file_by_file_name(self, file_name):\\n ls = self.files.filter_by(file_name=file_name)\\n return ls[0] if 0 < len(ls) else None\",\n \"def storage_get(context, storage_id):\\n return _storage_get(context, storage_id)\",\n \"def get_gcs_file(self, no_copy=False):\\n return self.get_file(uri_type=URI_GCS, no_copy=no_copy)\",\n \"def GetOpenedFile(self,file):\\n\\t\\tif isinstance(file,str):\\n\\t\\t\\tindex = self.OpenedFilenames.index(file)\\n\\t\\telif isinstance(file,int):\\n\\t\\t\\tindex=file\\n\\t\\telse:\\n\\t\\t\\traise PycomError('Type of file in GetOpenedFile is wrong ')\\n\\t\\treturn self.acad.Documents.Item(index)\",\n \"def get_file(self, uri_type, no_copy=False):\\n return self.copy(target_uri_type=uri_type, no_copy=no_copy)\",\n \"def get(self, fp, off=0, size=-1):\\n self.log.debug(\\\"GET [%r]: %s:%s\\\", fp, off, size)\\n\\n obj_size, _ = self.ioctx.stat(fp)\\n\\n compression_id = CAS._convert_meta(self.ioctx.get_xattr(fp, \\\"cas.meta.compression\\\"))\\n decompressor = Compressor.select(compression_id)\\n\\n self.log.debug(\\\"GET [%r]: size %d compressed with %r\\\", fp, obj_size, compression_id)\\n\\n compressed_data = self.ioctx.read(fp, obj_size, 0)\\n data = decompressor.decompress(compressed_data)\\n\\n if size < 0:\\n size = len(data)\\n\\n return data[off:off+size]\",\n \"def get_file(self, name, internal=True, fieldids=None, fieldnames=None):\\n if self.remote:\\n return DBSFileRemote(self.remote, name, internal=internal, fieldnames=fieldnames, fieldids=fieldids)\\n\\n if name.find('::') >= 0:\\n # This is a full path name to a subfile. \\n dd = DD(subfile_path=name)\\n else:\\n # top-level file - dd entry defines the storage.\\n dd = DD(name)\\n\\n if dd.fileid is None:\\n raise FilemanError(\\\"\\\"\\\"DBS.get_file() : File not found [%s]\\\"\\\"\\\" % name)\\n return DBSFile(dd, internal=internal, fieldids=fieldids, fieldnames=fieldnames, ext_filename=name)\",\n \"def readFile(self, path):\\n return self.session.request('diag/files/?q=%s'\\n % (path))\",\n \"def get(name):\\n\\n filename = find(name)\\n if filename == None:\\n return name\\n return open(filename).read()\",\n \"def get_file(self):\\n return self.dir + self.file_name + self.extension\",\n \"def get_file(self, repo, file_name):\\n DataHubManager.has_repo_file_privilege(\\n self.username, self.repo_base, repo, 'read')\\n\\n file_path = user_data_path(self.repo_base, repo, file_name)\\n file = open(file_path).read()\\n return file\",\n \"def read_file(self, path):\\n with open(path) as f:\\n return self.read_file_obj(f)\",\n \"def get_file(self, file_id: str) -> GDriveFile:\\n r = requests.get(\\n f\\\"https://www.googleapis.com/drive/v3/files/{file_id}\\\",\\n headers=self._auth_headers\\n )\\n if r.status_code in self._errors:\\n raise ApiResponseException(\\n r.status_code, r.json()[\\\"error\\\"][\\\"message\\\"])\\n return GDriveFile(r.json())\",\n \"def get(self, cls, id):\\n\\n return FileStorage.__objects[key(cls, id)]\",\n \"def get_file(self) -> int:\\r\\n return self.file\",\n \"def get_file_obj(self, file):\\n repository = \\\"{}/{}\\\".format(self.org, self.repo)\\n ghrepo = self.github.get_repo(repository)\\n obj = ghrepo.get_contents(file)\\n return obj\",\n \"def storage_get_report_file(self, report_pk):\\n return self._get_queryset(pk=report_pk).get()\",\n \"def file(self):\\n return self._file\",\n \"def file(self):\\n return self._file\",\n \"def file(self):\\n return self._file\",\n \"def getFile( self, par, path ):\\n\\n return self.db.getFilePar( par, path )\",\n \"def _retrieve_filename(file: Union[str, FileStorage]) -> str:\\n if isinstance(file, FileStorage):\\n return file.filename\\n return file\",\n \"def get(self, resource_id):\\n d = Deposition.get(resource_id, user=current_user)\\n return map(lambda f: d.type.marshal_file(f), d.files)\",\n \"def get_file(filename, result):\\n return next((f for f in result if f['filename'] == filename), None)\",\n \"def getInFile( self ):\\n return self.file\",\n \"def _get_file_object(inputfile=None):\\n if type(inputfile) == str:\\n return open(inputfile, 'r')\\n return inputfile\",\n \"def get_file(self, path):\\n _url = (\\n f\\\"{self.connector.base_url}/projects/{self.project_id}/nodes/{self.node_id}\\\"\\n f\\\"/files/{path}\\\"\\n )\\n\\n return self.connector.http_call(\\\"get\\\", _url).text\",\n \"def get_file(self, c_path):\\n raise NotImplementedError\",\n \"def file(self):\\r\\n return self._get_instantiation()[0]\",\n \"def get_file(self, filename):\\n if not filename in self.files:\\n raise IOError('File %s Not Found' % filename)\\n\\n nodename = _random_pick(self.files[filename])\\n return self.datanodes[nodename]\",\n \"def get_remote_file(sid, path):\\n with slycat.web.server.remote.get_session(sid) as session:\\n return session.get_file(path)\",\n \"def get_file_content(*args, **kwargs):\\n return get_file_content_async(*args, **kwargs).get_result()\",\n \"def get_demo_file(fname):\\n\\n d = download_demo_files()\\n if fname in d:\\n return d[fname]\\n else:\\n return None\",\n \"def read(self, mode='rb'):\\n\\n path = self.get_resource().get_target().fspath\\n\\n with open(path, mode=mode) as f:\\n return f.read()\",\n \"def request_file(self, path: str, token: str) -> Tuple[IO[bytes], dict]:\\n response = self.request('get', path, token, stream=True)\\n stream = ReadWrapper(response.iter_content,\\n int(response.headers['Content-Length']))\\n return stream, response.headers\",\n \"def getfile(self, name):\\n try:\\n datname = self.getname(name, \\\"dat\\\")\\n tadname = self.getname(name, \\\"tad\\\")\\n if datname and tadname:\\n return Datafile(name, open(datname, \\\"rb\\\"), open(tadname, \\\"rb\\\"), self.kod)\\n except IOError:\\n return\",\n \"def get_file(self, file_id, filename=''):\\n method = 'getFile?' + 'file_id=' + str(file_id)\\n res = requests.post(self.api_url + method, file_id)\\n try:\\n file_path = res.json()['result']['file_path']\\n # Determine the fileName. Use modified file_path if none given.\\n if not filename:\\n filename = file_path[file_path.rfind('/') + 1:]\\n except (KeyError, ValueError):\\n return \\\"500 - Failed parsing the file link from API response.\\\"\\n\\n if not os.path.exists(self.dirDownloads):\\n os.mkdir(self.dirDownloads)\\n\\n local_path = os.path.join(self.dirDownloads, filename)\\n\\n # Download file as stream.\\n res = requests.get(self.file_url + file_path, stream=True)\\n if res.status_code == 200:\\n try:\\n with open(local_path, 'wb') as f:\\n for chunk in res:\\n f.write(chunk)\\n except IOError:\\n pass\\n return '200 - {} written.'.format(local_path)\\n else:\\n return '404 - Error accessing {}'.format(file_path)\",\n \"def read(self, path, filename=None, offset=None, size=-1):\\n storageScheme, key = self.getkey(path, filename=filename)\\n\\n if offset or (size > -1):\\n if not offset:\\n offset = 0\\n if size > -1:\\n sizeStr = offset + size - 1 # range header is inclusive\\n else:\\n sizeStr = \\\"\\\"\\n headers = {\\\"Range\\\": \\\"bytes=%d-%s\\\" % (offset, sizeStr)}\\n return key.get_contents_as_string(headers=headers)\\n else:\\n return key.get_contents_as_string()\",\n \"def GetFromStore(self, file_path):\\n resp_data = None\\n file_itr = iter(self.zipfilenames)\\n\\n # check the index, if we have one, to see what archive the file is in\\n archive_name = self.MapFileToArchive(file_path)\\n if not archive_name:\\n archive_name = file_itr.next()[0]\\n\\n while resp_data is None and archive_name:\\n zip_archive = self.LoadZipFile(archive_name)\\n if zip_archive:\\n\\n # we expect some lookups will fail, and that's okay, 404s will deal\\n # with that\\n try:\\n resp_data = zip_archive.read(file_path)\\n except (KeyError, RuntimeError), err:\\n # no op\\n x = False\\n if resp_data is not None:\\n logging.info('%s read from %s', file_path, archive_name)\\n \\n try:\\n archive_name = file_itr.next()[0]\\n except (StopIteration), err:\\n archive_name = False\\n\\n return resp_data\",\n \"def GetFromStore(self, file_path):\\n resp_data = None\\n file_itr = iter(self.zipfilenames)\\n\\n # check the index, if we have one, to see what archive the file is in\\n archive_name = self.MapFileToArchive(file_path)\\n if not archive_name:\\n archive_name = file_itr.next()[0]\\n\\n while resp_data is None and archive_name:\\n zip_archive = self.LoadZipFile(archive_name)\\n if zip_archive:\\n\\n # we expect some lookups will fail, and that's okay, 404s will deal\\n # with that\\n try:\\n resp_data = zip_archive.read(file_path)\\n except (KeyError, RuntimeError), err:\\n # no op\\n x = False\\n if resp_data is not None:\\n logging.info('%s read from %s', file_path, archive_name)\\n\\n try:\\n archive_name = file_itr.next()[0]\\n except (StopIteration), err:\\n archive_name = False\\n\\n return resp_data\",\n \"def get_file(self, path):\\n tarstream = io.BytesIO()\\n for chunk in self.container.get_archive(path=path)[0]:\\n tarstream.write(chunk)\\n tarstream.seek(0)\\n with tarfile.open(fileobj=tarstream) as tarfile_:\\n for tarinfo in tarfile_.getmembers():\\n return tarfile_.extractfile(tarinfo).read().decode()\",\n \"def get(self, save=False, filename=None):\\n page, content = self._get_file_helper()\\n\\n filename = _negotiate_filename(page, filename, save)\\n\\n if save and filename:\\n with open(filename, 'wb') as fh:\\n fh.write(content)\\n\\n return content, filename\",\n \"def get_file(self, file_path, container_name, blob_name, **kwargs):\\n return self.connection.get_blob_to_path(container_name, blob_name,\\n file_path, **kwargs)\",\n \"def get_file_entry(self):\\n pass\",\n \"def read_file(self):\\n self._apply_shared_lock()\\n\\n self.handle = self._open_file_r()\\n out = self._deserialize(self.handle)\\n self.handle.close()\\n\\n self._release_lock()\\n\\n return out\",\n \"def retrieve_document(self, format):\\n self._validate_extension(format.upper(), self.ALLOWED_DOCUMENT_EXT)\\n return self.client.service.RetrieveDocument(format=format.upper()).decode('base64')\",\n \"def retrieve(self, file_name):\\n ret = os.path.join(self.path, file_name)\\n temp = (self.path + file_name).find(self.path, 1, -1)\\n if os.path.exists(ret):\\n return os.path.join(self.path, file_name)\\n elif temp != -1:\\n if os.name == \\\"posix\\\":\\n return os.getcwd() + '/' + file_name\\n else:\\n return os.getcwd() + '\\\\\\\\' + file_name\\n else:\\n return None\",\n \"def get_file(filename):\\n content = Tree.file_content(filename)\\n file_name = \\\"attachment;filename={0}\\\".format(filename)\\n return Response(content, mimetype=\\\"text/plain\\\",\\n headers={\\\"Content-Disposition\\\": file_name})\",\n \"def get_blob(self, blob_name):\\n return self.bucket.get_blob(blob_name)\",\n \"def _metadata_get(self, path):\\n fd = self.fs.open(path, \\\"r\\\")\\n # TODO iterate instead of assuming file < 4MB\\n read_bytes = self.fs.read(fd, 0, 4096 * 1024)\\n self.fs.close(fd)\\n if read_bytes:\\n return json.loads(read_bytes.decode())\\n else:\\n return None\",\n \"def get_file(object_name: str, **kwargs) -> HTTPResponse:\\n data = client.get_object(DATASETS_BUCKET, object_name, **kwargs)\\n return data\",\n \"def retrieve_object(self, name: str):\\n file_path = self.__get_file_path(name)\\n return self.__deserialize_object(file_path)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.78756535","0.7461347","0.7436858","0.7395782","0.7368263","0.7213877","0.72103053","0.713844","0.7136062","0.7094323","0.7046528","0.70224756","0.6999044","0.6987379","0.6954168","0.6929677","0.6907303","0.6901869","0.68689317","0.6859872","0.6847875","0.68420213","0.6820236","0.67702436","0.6764525","0.6763935","0.6757334","0.6752592","0.6728733","0.672774","0.6721465","0.6712028","0.6690639","0.6682257","0.6629222","0.66181916","0.66153723","0.66028976","0.65708137","0.656002","0.6545474","0.65397775","0.6477121","0.6443795","0.6400704","0.6397295","0.63881","0.63881","0.63786685","0.6371489","0.63479525","0.63443476","0.6305094","0.62982535","0.62820023","0.6281113","0.62603074","0.62514526","0.6245419","0.6238962","0.6212413","0.620919","0.62078017","0.6207008","0.62021714","0.6196713","0.6196713","0.6196713","0.61955863","0.61930513","0.61927724","0.61900353","0.6183129","0.6181607","0.61646867","0.61642784","0.6161014","0.6155313","0.61488014","0.6145907","0.61295","0.61287594","0.61232144","0.6122199","0.61211276","0.6119275","0.611615","0.61126477","0.6095836","0.60613126","0.6049258","0.60426164","0.6030252","0.6025629","0.602388","0.6023285","0.6017267","0.60160965","0.6007072","0.6006757"],"string":"[\n \"0.78756535\",\n \"0.7461347\",\n \"0.7436858\",\n \"0.7395782\",\n \"0.7368263\",\n \"0.7213877\",\n \"0.72103053\",\n \"0.713844\",\n \"0.7136062\",\n \"0.7094323\",\n \"0.7046528\",\n \"0.70224756\",\n \"0.6999044\",\n \"0.6987379\",\n \"0.6954168\",\n \"0.6929677\",\n \"0.6907303\",\n \"0.6901869\",\n \"0.68689317\",\n \"0.6859872\",\n \"0.6847875\",\n \"0.68420213\",\n \"0.6820236\",\n \"0.67702436\",\n \"0.6764525\",\n \"0.6763935\",\n \"0.6757334\",\n \"0.6752592\",\n \"0.6728733\",\n \"0.672774\",\n \"0.6721465\",\n \"0.6712028\",\n \"0.6690639\",\n \"0.6682257\",\n \"0.6629222\",\n \"0.66181916\",\n \"0.66153723\",\n \"0.66028976\",\n \"0.65708137\",\n \"0.656002\",\n \"0.6545474\",\n \"0.65397775\",\n \"0.6477121\",\n \"0.6443795\",\n \"0.6400704\",\n \"0.6397295\",\n \"0.63881\",\n \"0.63881\",\n \"0.63786685\",\n \"0.6371489\",\n \"0.63479525\",\n \"0.63443476\",\n \"0.6305094\",\n \"0.62982535\",\n \"0.62820023\",\n \"0.6281113\",\n \"0.62603074\",\n \"0.62514526\",\n \"0.6245419\",\n \"0.6238962\",\n \"0.6212413\",\n \"0.620919\",\n \"0.62078017\",\n \"0.6207008\",\n \"0.62021714\",\n \"0.6196713\",\n \"0.6196713\",\n \"0.6196713\",\n \"0.61955863\",\n \"0.61930513\",\n \"0.61927724\",\n \"0.61900353\",\n \"0.6183129\",\n \"0.6181607\",\n \"0.61646867\",\n \"0.61642784\",\n \"0.6161014\",\n \"0.6155313\",\n \"0.61488014\",\n \"0.6145907\",\n \"0.61295\",\n \"0.61287594\",\n \"0.61232144\",\n \"0.6122199\",\n \"0.61211276\",\n \"0.6119275\",\n \"0.611615\",\n \"0.61126477\",\n \"0.6095836\",\n \"0.60613126\",\n \"0.6049258\",\n \"0.60426164\",\n \"0.6030252\",\n \"0.6025629\",\n \"0.602388\",\n \"0.6023285\",\n \"0.6017267\",\n \"0.60160965\",\n \"0.6007072\",\n \"0.6006757\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.74737984"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":18695,"cells":{"query":{"kind":"string","value":"Make sure a content is free of malicious data. It called the antivirus ClamAV through its python interface to do the job."},"document":{"kind":"string","value":"def is_safe(self, content=None):\n if not self.secur:\n return [True, \"Security is not required.\"]\n else:\n if content is not None:\n cd = clamd.ClamdUnixSocket()\n if cd.ping() == 'PONG':\n cd.reload()\n file_buffer = BytesIO()\n try:\n file_buffer.write(content)\n except:\n file_buffer.write(content.encode())\n file_buffer.seek(0)\n result = cd.instream(file_buffer)\n if result['stream'] == ('OK', None):\n return [True, \"The uploaded contents are safe.\"]\n else:\n return [False, \"At least one of the uploaded contents looks malicious. They have been discarded by the anti-malware module.\"]\n else:\n return [False, \"Clamd Cannot be reached.\"]\n else:\n return [True, \"No content. So it is very safe.\"]"},"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 check_vulnerability(self):\n\t\tpass","def test_verifyDamaged(self):\n self.testObject.content.setContent('garbage!')\n self.assertRaises(CorruptObject, self.testObject.verify)","def malicious(self):\n return self.probably_malicious","def test_kyc_post_legal_share_holder(self):\n pass","def _post_decrypt_checks(self, aad, plaintext, protected_message, request_id):","def DoMaliciousThings():\r\n\tprint(\"You are infected\")","def is_content_malformed(self):\n return self._tag == 'content_malformed'","def is_content_malformed(self):\n return self._tag == 'content_malformed'","def verify_hack_key(self):\r\n\t\tself.percent_english = Dict_Control(self.my_code).check_key()\r\n\t\t#If more than half the words are english, the key will pass. \r\n\t\tif self.percent_english > 50:\r\n\t\t\tself.hack_plausible = True","def test_itar_restrict_asset(self):\n pass","def is_file_containing_malicious_content(self, content: str, file_name: str):\n\n for suspicious_string in self.stringsCausingSuspicions:\n # if it's a regexp\n if str(suspicious_string.__class__) == \"<class '_sre.SRE_Pattern'>\":\n if len(suspicious_string.findall(content)) > 0:\n return True\n\n continue\n\n # regular, simple string check\n if suspicious_string in content:\n return True\n\n return False","def test_kyc_put_legal_share_holder(self):\n pass","def test_kyc_post_legal(self):\n pass","def test_itar_restrict_software_asset(self):\n pass","def validate(self, content_retriever):\n pass","def validate(self, content_retriever):\n pass","def test_itar_restrict_test_asset(self):\n pass","def test_sandbox_exclusion(self):\r\n self.assertFalse(can_execute_unsafe_code(SlashSeparatedCourseKey('edX', 'notful', 'empty')))","def verify():","def test_blind_sig_expiration(self):\n signer_obj = ECCBlind(year=2020, month=1)\n point_r = signer_obj.signer_init()\n requester_obj = ECCBlind(pubkey=signer_obj.pubkey())\n msg = os.urandom(64)\n msg_blinded = requester_obj.create_signing_request(point_r, msg)\n signature_blinded = signer_obj.blind_sign(msg_blinded)\n signature = requester_obj.unblind(signature_blinded)\n verifier_obj = ECCBlind(pubkey=signer_obj.pubkey())\n self.assertFalse(verifier_obj.verify(msg, signature))","def clean_content(self) -> str:","def known_safes(self):\n self.safes","def test_link_safety(self):\n attack_vectors = (\n # \"standard\" javascript pseudo protocol\n ('javascript:alert`1`', ''),\n # bypass attempt\n ('jAvAsCrIpT:alert`1`', ''),\n # javascript pseudo protocol with entities\n ('javascript:alert`1`', ''),\n # javascript pseudo protocol with prefix (dangerous in Chrome)\n ('\\x1Ajavascript:alert`1`', ''),\n # data-URI (dangerous in Firefox)\n ('data:text/html,<script>alert`1`</script>', ''),\n # vbscript-URI (dangerous in Internet Explorer)\n ('vbscript:msgbox', ''),\n # breaking out of the attribute\n ('\"<>', ''),\n )\n\n for vector, expected in attack_vectors:\n # Image\n self.assertEqual(\n Markdown().render('' % vector),\n '<p><img src=\"%s\" alt=\"atk\"></p>' % expected)\n # Link\n self.assertEqual(\n Markdown().render('[atk](%s)' % vector),\n '<p><a rel=\"nofollow\" href=\"%s\">atk</a></p>' % expected)","def test_kyc_delete_legal_share_holder_natural(self):\n pass","def declare_malicious_member(self, member, packets):\n if __debug__:\n assert isinstance(member, Member)\n assert not member.must_blacklist, \"must not already be blacklisted\"\n assert isinstance(packets, list)\n assert len(packets) > 0\n assert all(isinstance(packet, Packet) for packet in packets)\n assert all(packet.meta == packets[0].meta for packet in packets)\n\n if __debug__: dprint(\"proof based on \", len(packets), \" packets\")\n\n # notify the community\n community = packets[0].community\n community.dispersy_malicious_member_detected(member, packets)\n\n # set the member blacklisted tag\n member.must_blacklist = True\n\n # store the proof\n self._database.executemany(u\"INSERT INTO malicious_proof (community, member, packet) VALUES (?, ?, ?)\",\n ((community.database_id, member.database_id, buffer(packet.packet)) for packet in packets))\n\n # remove all messages created by the malicious member\n self._database.execute(u\"DELETE FROM sync WHERE community = ? AND member = ?\",\n (community.database_id, member.database_id))\n\n # TODO: if we have a address for the malicious member, we can also remove her from the\n # candidate table","async def altcheck(self, ctx: Context):\n\t\tauthormsg = ctx.author\n\t\t#authormsg = await self.convertuser(ctx.author.id)\n\t\tif authormsg.id == ownerid:\n\t\t\tpass\n\t\telif authormsg.room_permissions.is_mod or authormsg.room_permissions.is_admin == True:\n\t\t\tpass\n\t\telse:\n\t\t\treturn await self.send(\"You don't have permission to do that.\", whisper=[ctx.author.id])\n\t\tawait self.send(\"This may take a while, be patient.\", whisper=[ctx.author.id])\n\t\tusers = []\n\t\tprint(\"before for loop\")\n\t\tfor user in self.room.users:\n\t\t\tuserdata = await self.returnavinfo(user)\n\t\t\tif userdata['message'] == \"Twitter\":\n\t\t\t\tcontinue\n\t\t\telse:\n\t\t\t\tif \"Marked as spam\" in userdata['message']:\n\t\t\t\t\tusers.append(userdata['message'])\n\t\t\t\t\tcontinue\n\t\t\t\tdtm = userdata['crdate']\n\t\t\t\trntime = datetime.now()\n\t\t\t\td = datetime.fromisoformat(dtm[:-1])\n\t\t\t\td.strftime('%Y-%m-%d %H:%M:%S.%f')\n\t\t\t\ttimedeltuh = rntime - d\n\t\t\t\tif timedeltuh.days >= 14:\n\t\t\t\t\tappusdata = userdata['message'] + f\"- {timedeltuh} • \"\n\t\t\t\t\tusers.append(appusdata)\n\t\t\t\telse:\n\t\t\t\t\tcontinue\n\t\t\n\t\tprint(\"before lencheck\")\n\t\tuserssend = \"\".join(users)\n\t\tprint(userssend)\n\t\tprint(len(userssend))\n\t\ttry:\n\t\t\tif len(userssend) >= 520:\n\t\t\t\tstrround = round(len(userssend))\n\t\t\t\tstrlen = round(strround) / 2\n\t\t\t\tfirst_half = userssend[:int(strlen)]\n\t\t\t\tsecond_half = userssend[int(strlen):]\n\t\t\t\tawait self.send(first_half, whisper=[ctx.author.id])\n\t\t\t\tawait asyncio.sleep(2)\n\t\t\t\tawait self.send(second_half, whisper=[ctx.author.id])\n\t\t\t\treturn\n\t\t\tprint(\"done\")\n\t\t\tawait self.send(userssend, whisper=[ctx.author.id])\n\t\texcept Exception as e:\n\t\t\tprint(e)","def collect_allowed(message):\n return True","def verify_text(self, text):\n pass","def check_request(self, request):\n\n # Prima di tutto verifichiamo che non esistano ban attivi\n check = Ban.objects.filter(ip=Ban.get_client_ip(request), expires__gte=now()).first()\n\n if check:\n logger.warning(\"Accesso da parte di un ip bannato: %r. Scadenza ban: %s\",\n check.ip, check.expires)\n raise PermissionDenied('IP Bannato')\n\n if not 'HTTP_X_KEY' in request.META:\n logger.warning(\"Non e' stata passata la chiave pubblica\")\n raise PermissionDenied('Key non presente')\n\n if not 'HTTP_X_CHARID' in request.META:\n logger.warning(\"Non e' stato passato il charid\")\n raise PermissionDenied('CharId non presente')\n\n if not 'SERVER_PROTOCOL' in request.META or request.META['SERVER_PROTOCOL'] != 'HTTP/1.0':\n logger.warning(\"Il server protocol non corrisponde\")\n raise PermissionDenied('Server protocol non valido')\n\n if not 'HTTP_X_RANDOM_ID' in request.META:\n logger.warning('Non e\\' stato passato l\\'hash dello script')\n raise PermissionDenied('Hash script non valido')\n\n if not 'HTTP_X_DECODE' in request.META or not 'HTTP_X_SHARD' in request.META:\n logger.warning('Missing char info')\n raise PermissionDenied('Missing char info')\n\n try:\n decrypted_char_id = decrypt(request.META['HTTP_X_KEY'], settings.PUBLIC_KEY)\n char_id = request.META['HTTP_X_CHARID']\n script_hash = codecs.decode(request.META['HTTP_X_RANDOM_ID'], 'rot_13')\n\n if decrypted_char_id != char_id:\n logger.warning(\"La chiave pubblica non corrisponde con il charid: cid %s chiave %s\",\n char_id, decrypted_char_id)\n raise PermissionDenied('La chiave pubblica non corrisponde con il charid')\n\n return decrypted_char_id, script_hash\n except TypeError:\n logger.exception('Errore di decodifica del base64')\n raise ValueError()","async def check_virus(self, ctx: commands.Context, target: discord.Member) -> None:\n\n answer: discord.PartialMessageable = None\n if isinstance(ctx, commands.Context):\n answer = ctx.send\n else:\n answer = ctx.respond\n\n infected = ctx.author\n\n hack = await self.get_skill_action_by_target_id_and_skill_type(target.id, skill_type='hack')\n if hack[8] != 'virus' or hack[0] == infected.id:\n return\n\n effects = await self.get_user_effects(infected)\n if 'hacked' in effects:\n return\n\n if 'protected' in effects:\n return\n\n if 'reflect' in effects:\n attacker = await discord.utils.get(ctx.guild.members, id=hack[0])\n await self.reflect_attack(ctx, attacker, target, 'hack')\n \n try:\n current_timestamp = await utils.get_timestamp()\n # Don't need to store it, since it is forever\n await self.insert_skill_action(\n user_id=hack[0], skill_type=\"hack\", skill_timestamp=current_timestamp,\n target_id=infected.id, channel_id=ctx.channel.id, content=\"virus\"\n ) \n\n except Exception as e:\n print('Failed virus', e)\n else:\n virus_embed = await self.get_virus_embed(\n channel=ctx.channel, perpetrator_id=hack[0], target_id=target.id, infected_id=infected.id)\n await answer(embed=virus_embed)","def test_kyc_get_legal_share_holders(self):\n pass","def __is_item_vulnerable(self, queue_item):\n\n try:\n HTTPHandler(None, queue_item)\n except Exception:\n return False\n\n if not \"html\" in queue_item.response.headers.get(\"content-type\"):\n return False\n\n if not queue_item.get_soup_response():\n return False\n\n if not self.__should_payload_execute(queue_item):\n return False\n\n if self.__verify_payload:\n if not self.__verify_queue_item(queue_item.verify_item):\n return False\n\n return True","async def update_hacks_content(self, attacker_id: int) -> None:\n\n mycursor, db = await the_database()\n await mycursor.execute(\"UPDATE SlothSkills SET content = 'virus' WHERE user_id = %s\", (attacker_id,))\n await db.commit()\n await mycursor.close()","def __sanitize_input(self):\n self.__check_for_video_file()\n self.__manage_output_folder()","def test_lack_of_sanitization_function(self, mock_function):\n for (broken, clean) in self.needSanitization:\n self.assertNotEqual(clean, sanitizeFeedback(broken))","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_forbidden_blocked_conanmanifest():\n server = TestServer()\n servers = {\"default\": server}\n client = TestClient(servers=servers, inputs=[\"admin\", \"password\"])\n client.save({\"conanfile.py\": GenConanfile()})\n client.run(\"create . --name=lib --version=1.0\")\n client.run(\"upload lib/1.0* -c -r default\")\n\n class DownloadForbidden(TestRequester):\n def get(self, url, **kwargs):\n if \"conanmanifest.txt\" in url:\n r = Response()\n r._content = \"Forbidden because of security!!!\"\n r.status_code = 403\n return r\n else:\n return super(DownloadForbidden, self).get(url, **kwargs)\n\n client = TestClient(servers=servers, inputs=[\"admin\", \"password\"],\n requester_class=DownloadForbidden)\n client.run(\"download lib/1.0 -r=default\", assert_error=True)\n assert \"Forbidden because of security!!!\" in client.out\n\n client.run(\"list *\")\n assert \"lib/1.0\" not in client.out\n\n client.run(\"install --requires=lib/1.0\", assert_error=True)\n assert \"Forbidden because of security!!!\" in client.out\n\n client.run(\"list *\")\n assert \"lib/1.0\" not in client.out","def violated(self) -> bool:\n ...","def _verify(self):\n pass","def ConfirmAllowedCopyrightHolder(holder):\n return holder in ALLOWED_COPYRIGHT_HOLDERS","def test_real_world_malware(self):\n key = bytes.fromhex('0394d550fb286dda')\n data = bytes.fromhex('6bdb2c294e7e031c38e4adecaa8dc755')\n unit = self.load(key, raw=True)\n self.assertEqual(unit.decrypt(data).hex(), '4c5a495001b30026968e700017f7ec05')","async def badman(self, ctx):\n await ctx.message.edit(content=\"̿̿ ̿̿ ̿̿ ̿'̿'\\̵͇̿̿\\з= ( ▀ ͜͞ʖ▀) =ε/̵͇̿̿/’̿’̿ ̿ ̿̿ ̿̿ ̿̿\")","def isSpam(textLine):\n\treturn True","def test_forbidden_words(self) -> None:\n pad_open: bool = False\n words: List[Word] = self.report.get_words()\n forbidden_words: List[Word] = []\n last_error: bool = False\n\n for word in words:\n if word.text in self.rules.citation_delimiters:\n pad_open = not pad_open\n continue\n if pad_open:\n continue\n if (word.text in self.rules.forbidden_words) or any(\n [b in self.rules.forbidden_words for b in word.baseform]\n ):\n forbidden_words.append(word)\n last_error = True\n continue\n if last_error:\n last_error = False\n combo = \" \".join([w.text for w in forbidden_words])\n start, _ = self.report.get_word_postion(forbidden_words[0])\n _, end = self.report.get_word_postion(forbidden_words[-1])\n self.add_error(\n f\"Ordet {combo} får endast förekomma i citat.\", position=(start,end)\n )","def immobilized(self, owner):\n messages = []\n immobilized = False\n \n if self.checkOver(owner, messages):\n immobilized = False\n \n elif self.confused(random.randint(0, 1)):\n self.doDamage(owner, messages)\n immobilized = True\n \n return immobilized, messages","def hack_text_file(self):\r\n\t\t#Ensures that the file has something that can be hacked.\r\n\t\tfile_contains_message = True\r\n\t\twhile file_contains_message:\r\n\t\t\tfile_exists = True\r\n\t\t\t#Checks to see if the file exists.\r\n\t\t\twhile file_exists:\r\n\t\t\t\tself.text_file_name = input(\"Please enter the name of the text file you wish to decrypt in format |file_name.txt|.--> \")\r\n\t\t\t\tif \".txt\" in self.text_file_name:\r\n\t\t\t\t\tfile_exists = Doc_Control().check_for_file(self.text_file_name)\r\n\t\t\t\telse: \r\n\t\t\t\t\tcontinue\r\n\t\t\t#Verifys file contains a message before before running through hack and giving user their list of decryption hits.\r\n\t\t\twhile True: \r\n\t\t\t\tself.message = Doc_Control().open_file(self.text_file_name)\r\n\t\t\t\tif self.message != \"\" and len(self.message) > 4:\r\n\t\t\t\t\tfile_contains_message = False\r\n\t\t\t\t\tbreak\r\n\t\t\t\telse:\r\n\t\t\t\t\tprint(\"Your file does not contain a hackable message.\")\r\n\t\t\t\t\tbreak\t\t\t\r\n\t\tmax_key = len(self.message)\r\n\t\tself.i = 1\r\n\t\tpotential_hits = []\r\n\t\t#Runs through all potential keys. \r\n\t\tfor self.i in range(1, max_key):\r\n\t\t\tprint(f\"Trying key #{self.i} of {max_key} possible keys\")\t\t\t\r\n\t\t\tself.my_code = Decryptor(self.message, self.i).transfer_decrypt()\r\n\t\t\tself.hack_plausible = False\r\n\t\t\tself.verify_hack_key()\r\n\t\t\tif self.hack_plausible:\r\n\t\t\t\tpotential_hits.append(f\"Key #{self.i} yeilded {self.percent_english}% english words after decryption.\\n\" + \"\\t\" + self.my_code[:50])\r\n\t\tprint(\"~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\n\")\r\n\t\tprint(\"Hacking results:\\n\")\r\n\t\tfor hit in potential_hits:\r\n\t\t\tprint(\"\\t\" + hit + \"|\\n\")","def verify(self):\r\n self.title = self.title and self.title or '' \r\n self.descr = self.descr and self.descr or '' \r\n self.link = self.link and self.link or ''\r\n self.channelURL = self.channelURL and self.channelURL or ''","def test_allow_noquote(self):\n val = DwcaValidator(yaml.load(self.yaml_allow1, Loader=yaml.FullLoader),\n error_handler=WhipErrorHandler)\n document = {'sex': 'male'}\n self.assertTrue(val.validate(document))\n\n document = {'sex': 'female'}\n self.assertFalse(val.validate(document))","def test_kyc_get_legal(self):\n pass","def sanitize(cls):","def test_store_inline_bad_digest(self):\n namespace = 'default-gzip'\n request = self.store_request(namespace, 'anseres sacri')\n request.content = ':)' + request.content[2:]\n with self.call_should_fail('400'):\n self.call_api('store_inline', self.message_to_dict(request), 200)","def test_courses_with_unsafe_code_default(self):\r\n self.assertFalse(can_execute_unsafe_code(SlashSeparatedCourseKey('edX', 'full', '2012_Fall')))\r\n self.assertFalse(can_execute_unsafe_code(SlashSeparatedCourseKey('edX', 'full', '2013_Spring')))","def send_malicious_proof(self, community, member, candidate):\n if __debug__:\n from .community import Community\n assert isinstance(community, Community)\n assert isinstance(member, Member)\n assert member.must_blacklist, \"must be blacklisted\"\n assert isinstance(candidate, Candidate)\n\n packets = [str(packet) for packet, in self._database.execute(u\"SELECT packet FROM malicious_proof WHERE community = ? AND member = ?\",\n (community.database_id, member.database_id))]\n if packets:\n self._statistics.dict_inc(self._statistics.outgoing, u\"-malicious-proof\", len(packets))\n self._endpoint.send([candidate], packets)","def test_block_bad_signature(self):\n pass","def test_kyc_put_legal(self):\n pass","def test_lessthan(self):\r\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.text_lessthan_noencd), self.text_lessthan_encode)","def test_mixed_verfication(self):\n\n lists_map = ima.process_allowlists(ALLOWLIST, '')\n lists_map_wrong = ima.process_allowlists(ALLOWLIST_WRONG, '')\n lists_map_empty = ima.process_allowlists(ALLOWLIST_EMPTY, '')\n lists_map_exclude = ima.process_allowlists(ALLOWLIST, EXCLUDELIST)\n lists_map_exclude_wrong = ima.process_allowlists(ALLOWLIST_WRONG, EXCLUDELIST)\n empty_keyring = ima_file_signatures.ImaKeyring()\n\n # every entry is covered by the allowlist and there's no keyring -> this should pass\n self.assertTrue(ima.process_measurement_list(COMBINED.splitlines(), str(lists_map)) is not None)\n\n curdir = os.path.dirname(os.path.abspath(__file__))\n keydir = os.path.join(curdir, \"data\", \"ima_keys\")\n keyring = ima_file_signatures.ImaKeyring()\n\n rsakeyfile = os.path.join(keydir, \"rsa2048pub.pem\")\n pubkey, keyidv2 = ima_file_signatures.get_pubkey_from_file(rsakeyfile)\n keyring.add_pubkey(pubkey, keyidv2)\n\n eckeyfile = os.path.join(keydir, \"secp256k1.pem\")\n pubkey, keyidv2 = ima_file_signatures.get_pubkey_from_file(eckeyfile)\n keyring.add_pubkey(pubkey, keyidv2)\n\n # entries are not covered by a exclude list -> this should fail\n self.assertTrue(ima.process_measurement_list(COMBINED.splitlines(), ima_keyring=keyring) is None)\n\n # all entries are either covered by allow list or by signature verification -> this should pass\n self.assertTrue(ima.process_measurement_list(COMBINED.splitlines(), str(lists_map), ima_keyring=keyring) is not None)\n\n # the signature is valid but the hash in the allowlist is wrong -> this should fail\n self.assertTrue(ima.process_measurement_list(SIGNATURES.splitlines(), str(lists_map_wrong), ima_keyring=keyring) is None)\n\n # the signature is valid and the file is not in the allowlist -> this should pass\n self.assertTrue(ima.process_measurement_list(SIGNATURES.splitlines(), str(lists_map_empty), ima_keyring=keyring) is not None)\n\n # the signature is invalid but the correct hash is in the allowlist -> this should fail\n self.assertTrue(ima.process_measurement_list(SIGNATURES.splitlines(), str(lists_map), ima_keyring=empty_keyring) is None)\n\n # the file has no signature but the hash is correct -> this should pass\n self.assertTrue(ima.process_measurement_list(MEASUREMENTS.splitlines(), str(lists_map)))\n\n # All files are in the exclude list but hashes are invalid -> this should pass\n self.assertTrue(ima.process_measurement_list(MEASUREMENTS.splitlines(), str(lists_map_exclude_wrong)) is not None)\n\n # All files are in the exclude list and their signatures are invalid -> this should pass\n self.assertTrue(ima.process_measurement_list(SIGNATURES.splitlines(), str(lists_map_exclude), ima_keyring=empty_keyring) is not None)\n\n # All files are in the exclude list but hashes or signatures are invalid -> this should pass\n self.assertTrue(ima.process_measurement_list(MEASUREMENTS.splitlines(), str(lists_map_exclude_wrong), ima_keyring=empty_keyring) is not None)","def generateBroSafetyCheck(self):\n pass","def check_spam(self, request=None):\n key = self._get_key()\n\n if not key:\n # TODO: log a warning\n return False\n\n domain = self._get_domain()\n\n try:\n if verify_key(key, domain):\n data = self.get_spam_data(request)\n return comment_check(key, domain, **data)\n except AkismetError, e:\n # TODO: log a warning with the exception\n print e.response, e.statuscode\n return False","def test_auth_sharable_cannot_share(self):\n self.do_sharable(False, 'pattieblack', FakeMembership(False),\n tenant='froggy')","def safe_to_dance(self):\n # check for all fail/early-termination conditions\n for _ in range(4):\n if self.read_distance() < 300:\n print(\"NOT SAFE TO DANCE!\")\n return False\n else: \n self.turn_by_deg(90) \n\n #after all checks have been done. We deduce it's safe\n print(\"SAFE TO DANCE!\")\n return True\n\n for x in range(3): \n self.shake()","def VulnerableBy(self):\n\n print TextColor.WARNING + '[!] Please wait for check the site for vulnerability ...'\n print\n\n with open(\"./WebAttack/sqlinjection/payloads/InjectionChars.json\") as jsonFile:\n payloads = json.load(jsonFile)\n\n for item in payloads[\"defInjectionChars\"]:\n\n resposne = requests.get(url=self.url + str(item), headers=define_headerdata, verify=False)\n result = self.__CheckVulnerability__(content=resposne.text)\n\n if result != 'none':\n print TextColor.RED + '\\t[+] %s ' % (self.url + str(item)) + \" => vulnerable\" + TextColor.WHITE\n return {'database': result, 'char': item}\n else:\n print TextColor.GREEN + '\\t[+] %s ' % (self.url + str(item)) + \" => clear\" + TextColor.WHITE\n continue\n\n sleep(.5)","def clean_request_allowance(self):\n data = self.cleaned_data['request_allowance']\n # Comparing GB form field to bytes model field\n if data * 1024 ** 3 <= self.project.core_project.storage_allowance:\n raise forms.ValidationError('Project already has the requested allowance.',\n code='already_has_allowance')\n\n return data","def is_spam(code):\n urlfind = re.compile(\"[A-Za-z]+://.*?\")\n urls = urlfind.findall(code)\n url_count = len(urls)\n\n if url_count > URLS_LIMIT:\n return True\n else:\n word_count = len(code.split())\n urls_percentage = (url_count * 100) / word_count\n\n if urls_percentage > URLS_PERCENTAGE:\n return True\n else:\n return False","def clean_content(self):\n content = self.cleaned_data.get('content', None)\n if '<script' in content:\n raise forms.ValidationError(\"These tags are not allowed\")\n return content","def test_allowed_string(self):\n val = DwcaValidator(yaml.load(self.yaml_allowed_string, Loader=yaml.FullLoader),\n error_handler=WhipErrorHandler)\n document = {'abundance': 'many'}\n self.assertTrue(val.validate(document))\n document = {'abundance': 'female'}\n self.assertFalse(val.validate(document))","def test_blind_sig_value(self):\n signer_obj = ECCBlind(value=5)\n point_r = signer_obj.signer_init()\n requester_obj = ECCBlind(pubkey=signer_obj.pubkey())\n msg = os.urandom(64)\n msg_blinded = requester_obj.create_signing_request(point_r, msg)\n signature_blinded = signer_obj.blind_sign(msg_blinded)\n signature = requester_obj.unblind(signature_blinded)\n verifier_obj = ECCBlind(pubkey=signer_obj.pubkey())\n self.assertFalse(verifier_obj.verify(msg, signature, value=8))","def test_removeIllegalCharacters(self):\n data = \"Contains\\x03 control\\x06 characters\\x12 some\\x0a\\x09allowed\\x0d\"\n after, changed = removeIllegalCharacters(data)\n self.assertEquals(after, \"Contains control characters some\\x0a\\x09allowed\\x0d\")\n self.assertTrue(changed)\n\n data = \"Contains\\x09only\\x0a legal\\x0d\"\n after, changed = removeIllegalCharacters(data)\n self.assertEquals(after, \"Contains\\x09only\\x0a legal\\x0d\")\n self.assertFalse(changed)","def _verify_content(state_content_list):\n CONTENT_ITEM_SCHEMA = [\n ('type', basestring), ('value', basestring)]\n ALLOWED_CONTENT_TYPES = ['text', 'image', 'video']\n\n for content_item in state_content_list:\n utils.verify_dict_keys_and_types(content_item, CONTENT_ITEM_SCHEMA)\n if content_item['type'] not in ALLOWED_CONTENT_TYPES:\n raise Exception('Unsupported content type %s.' %\n content_item['type'])","def check_validity(self):","def test_forbidden(self):\n self._error_test(fitbit_exceptions.HTTPForbidden)","def verify(self):\r\n pass","def enSilencio(self,data_chunk):\n return max(data_chunk) < self.THRESHOLD","def test_embed(self):\r\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.embed_dirty), self.embed_clean)","def _verify_page(self):","def test_kyc_get_legal_share_holder_natural(self):\n pass","def verify(self):","def test_oneStoreDamaged(self):\n contentStore = self._store()\n obj = self._storeObject(\n contentStore=contentStore,\n content='somecontent',\n contentType=u'application/octet-stream')\n obj.content.setContent('damaged')\n f = self.failureResultOf(self._verify(contentStore, obj), NoGoodCopies)\n self.assertEqual(f.value.objectId, obj.objectId)","def check_embed(embed: Embed) -> bool:\n if len(embed) <= 6000:\n if hasattr(embed, \"title\"):\n if len(embed.title) <= 256:\n pass\n else:\n return False\n if len(embed.fields) <= 25:\n for field in embed.fields:\n if len(field.name) <= 69420:\n pass","def hasVeryTrustedValue(self):","def can_execute_unsafe_code(course_id):\r\n # To decide if we can run unsafe code, we check the course id against\r\n # a list of regexes configured on the server.\r\n # If this is not defined in the environment variables then default to the most restrictive, which\r\n # is 'no unsafe courses'\r\n # TODO: This should be a database configuration, where we can mark individual courses as being\r\n # safe/unsafe. Someone in the future should switch us over to that rather than using regexes\r\n # in a settings file\r\n # To others using this: the code as-is is brittle and likely to be changed in the future,\r\n # as per the TODO, so please consider carefully before adding more values to COURSES_WITH_UNSAFE_CODE\r\n for regex in getattr(settings, 'COURSES_WITH_UNSAFE_CODE', []):\r\n if re.match(regex, course_id.to_deprecated_string()):\r\n return True\r\n return False","def hasVeryTrustedValue():\n return False","def hasVeryTrustedValue():\n return False","def hasVeryTrustedValue():\n return False","def hasVeryTrustedValue():\n return False","def hasVeryTrustedValue():\n return False","def verify(self):\n pass","def verify(self):\n pass","def test_idempotent():\n dirty = u'<span>invalid & </span> < extra http://link.com<em>'\n\n clean = bl.clean(dirty)\n eq_(clean, bl.clean(clean))\n\n bleached = bl.bleach(dirty)\n eq_(bleached, bl.bleach(bleached))\n\n linked = bl.linkify(dirty)\n eq_(linked, bl.linkify(linked))","def hasVeryTrustedValue():\n return True","def check_for_no_privates(context):\n json_data = context.response.json()\n\n if \"component_analyses\" in json_data:\n vulnerabilities = json_data['component_analyses']['vulnerability']\n for v in vulnerabilities:\n assert \"cvss\" in v\n assert \"is_private\" in v\n assert \"vendor_cve_ids\" in v\n if v[\"is_private\"]:\n raise Exception(\"Private vulnerability found\")","def _check_validity(self):\n pass","def verify(self, ta):\n\n self.decode(CMS_object.verify(self, ta))\n return self.get_content()","def verify(self):\n self.verify_checksums()\n self.verify_apk_signature()\n self.verify_apk_signature_fprs()","def check():\n suspicious_telemarketers = get_suspicious_telemarketers(calls, texts)\n outgoing = set()\n non_tele = set()\n for c in calls:\n outgoing.add(c[0])\n non_tele.add(c[1])\n for t in texts:\n non_tele.add(t[0])\n non_tele.add(t[1])\n telemarketers = sorted(outgoing - non_tele)\n if len(suspicious_telemarketers) == len(telemarketers):\n print('Pass')","def _check_protects(self, p4user, blobs):\n pc = ProtectsChecker(self.ctx, p4user, self.ctx.authenticated_p4user,\n self.ctx.foruser)\n pc.filter_paths(blobs)\n if pc.has_error():\n raise PreflightException(pc.error_message())","def allow(self, comment, content_object, request):\n # Tests for cookie:\n if settings.COOKIE_KEY not in request.COOKIES \\\n and (settings.DISCARD_SPAM or settings.DISCARD_NO_COOKIE):\n return False\n elif settings.COOKIE_KEY not in request.COOKIES:\n comment.is_removed = True\n comment.is_public = False\n return True\n return True","def mark_safe(self, cell):\n self.safes.add(cell)\n for sentence in self.knowledge:\n sentence.mark_safe(cell)","def mark_safe(self, cell):\n self.safes.add(cell)\n for sentence in self.knowledge:\n sentence.mark_safe(cell)","def mark_safe(self, cell):\n self.safes.add(cell)\n for sentence in self.knowledge:\n sentence.mark_safe(cell)"],"string":"[\n \"def check_vulnerability(self):\\n\\t\\tpass\",\n \"def test_verifyDamaged(self):\\n self.testObject.content.setContent('garbage!')\\n self.assertRaises(CorruptObject, self.testObject.verify)\",\n \"def malicious(self):\\n return self.probably_malicious\",\n \"def test_kyc_post_legal_share_holder(self):\\n pass\",\n \"def _post_decrypt_checks(self, aad, plaintext, protected_message, request_id):\",\n \"def DoMaliciousThings():\\r\\n\\tprint(\\\"You are infected\\\")\",\n \"def is_content_malformed(self):\\n return self._tag == 'content_malformed'\",\n \"def is_content_malformed(self):\\n return self._tag == 'content_malformed'\",\n \"def verify_hack_key(self):\\r\\n\\t\\tself.percent_english = Dict_Control(self.my_code).check_key()\\r\\n\\t\\t#If more than half the words are english, the key will pass. \\r\\n\\t\\tif self.percent_english > 50:\\r\\n\\t\\t\\tself.hack_plausible = True\",\n \"def test_itar_restrict_asset(self):\\n pass\",\n \"def is_file_containing_malicious_content(self, content: str, file_name: str):\\n\\n for suspicious_string in self.stringsCausingSuspicions:\\n # if it's a regexp\\n if str(suspicious_string.__class__) == \\\"<class '_sre.SRE_Pattern'>\\\":\\n if len(suspicious_string.findall(content)) > 0:\\n return True\\n\\n continue\\n\\n # regular, simple string check\\n if suspicious_string in content:\\n return True\\n\\n return False\",\n \"def test_kyc_put_legal_share_holder(self):\\n pass\",\n \"def test_kyc_post_legal(self):\\n pass\",\n \"def test_itar_restrict_software_asset(self):\\n pass\",\n \"def validate(self, content_retriever):\\n pass\",\n \"def validate(self, content_retriever):\\n pass\",\n \"def test_itar_restrict_test_asset(self):\\n pass\",\n \"def test_sandbox_exclusion(self):\\r\\n self.assertFalse(can_execute_unsafe_code(SlashSeparatedCourseKey('edX', 'notful', 'empty')))\",\n \"def verify():\",\n \"def test_blind_sig_expiration(self):\\n signer_obj = ECCBlind(year=2020, month=1)\\n point_r = signer_obj.signer_init()\\n requester_obj = ECCBlind(pubkey=signer_obj.pubkey())\\n msg = os.urandom(64)\\n msg_blinded = requester_obj.create_signing_request(point_r, msg)\\n signature_blinded = signer_obj.blind_sign(msg_blinded)\\n signature = requester_obj.unblind(signature_blinded)\\n verifier_obj = ECCBlind(pubkey=signer_obj.pubkey())\\n self.assertFalse(verifier_obj.verify(msg, signature))\",\n \"def clean_content(self) -> str:\",\n \"def known_safes(self):\\n self.safes\",\n \"def test_link_safety(self):\\n attack_vectors = (\\n # \\\"standard\\\" javascript pseudo protocol\\n ('javascript:alert`1`', ''),\\n # bypass attempt\\n ('jAvAsCrIpT:alert`1`', ''),\\n # javascript pseudo protocol with entities\\n ('javascript:alert`1`', ''),\\n # javascript pseudo protocol with prefix (dangerous in Chrome)\\n ('\\\\x1Ajavascript:alert`1`', ''),\\n # data-URI (dangerous in Firefox)\\n ('data:text/html,<script>alert`1`</script>', ''),\\n # vbscript-URI (dangerous in Internet Explorer)\\n ('vbscript:msgbox', ''),\\n # breaking out of the attribute\\n ('\\\"<>', ''),\\n )\\n\\n for vector, expected in attack_vectors:\\n # Image\\n self.assertEqual(\\n Markdown().render('' % vector),\\n '<p><img src=\\\"%s\\\" alt=\\\"atk\\\"></p>' % expected)\\n # Link\\n self.assertEqual(\\n Markdown().render('[atk](%s)' % vector),\\n '<p><a rel=\\\"nofollow\\\" href=\\\"%s\\\">atk</a></p>' % expected)\",\n \"def test_kyc_delete_legal_share_holder_natural(self):\\n pass\",\n \"def declare_malicious_member(self, member, packets):\\n if __debug__:\\n assert isinstance(member, Member)\\n assert not member.must_blacklist, \\\"must not already be blacklisted\\\"\\n assert isinstance(packets, list)\\n assert len(packets) > 0\\n assert all(isinstance(packet, Packet) for packet in packets)\\n assert all(packet.meta == packets[0].meta for packet in packets)\\n\\n if __debug__: dprint(\\\"proof based on \\\", len(packets), \\\" packets\\\")\\n\\n # notify the community\\n community = packets[0].community\\n community.dispersy_malicious_member_detected(member, packets)\\n\\n # set the member blacklisted tag\\n member.must_blacklist = True\\n\\n # store the proof\\n self._database.executemany(u\\\"INSERT INTO malicious_proof (community, member, packet) VALUES (?, ?, ?)\\\",\\n ((community.database_id, member.database_id, buffer(packet.packet)) for packet in packets))\\n\\n # remove all messages created by the malicious member\\n self._database.execute(u\\\"DELETE FROM sync WHERE community = ? AND member = ?\\\",\\n (community.database_id, member.database_id))\\n\\n # TODO: if we have a address for the malicious member, we can also remove her from the\\n # candidate table\",\n \"async def altcheck(self, ctx: Context):\\n\\t\\tauthormsg = ctx.author\\n\\t\\t#authormsg = await self.convertuser(ctx.author.id)\\n\\t\\tif authormsg.id == ownerid:\\n\\t\\t\\tpass\\n\\t\\telif authormsg.room_permissions.is_mod or authormsg.room_permissions.is_admin == True:\\n\\t\\t\\tpass\\n\\t\\telse:\\n\\t\\t\\treturn await self.send(\\\"You don't have permission to do that.\\\", whisper=[ctx.author.id])\\n\\t\\tawait self.send(\\\"This may take a while, be patient.\\\", whisper=[ctx.author.id])\\n\\t\\tusers = []\\n\\t\\tprint(\\\"before for loop\\\")\\n\\t\\tfor user in self.room.users:\\n\\t\\t\\tuserdata = await self.returnavinfo(user)\\n\\t\\t\\tif userdata['message'] == \\\"Twitter\\\":\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\telse:\\n\\t\\t\\t\\tif \\\"Marked as spam\\\" in userdata['message']:\\n\\t\\t\\t\\t\\tusers.append(userdata['message'])\\n\\t\\t\\t\\t\\tcontinue\\n\\t\\t\\t\\tdtm = userdata['crdate']\\n\\t\\t\\t\\trntime = datetime.now()\\n\\t\\t\\t\\td = datetime.fromisoformat(dtm[:-1])\\n\\t\\t\\t\\td.strftime('%Y-%m-%d %H:%M:%S.%f')\\n\\t\\t\\t\\ttimedeltuh = rntime - d\\n\\t\\t\\t\\tif timedeltuh.days >= 14:\\n\\t\\t\\t\\t\\tappusdata = userdata['message'] + f\\\"- {timedeltuh} • \\\"\\n\\t\\t\\t\\t\\tusers.append(appusdata)\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tcontinue\\n\\t\\t\\n\\t\\tprint(\\\"before lencheck\\\")\\n\\t\\tuserssend = \\\"\\\".join(users)\\n\\t\\tprint(userssend)\\n\\t\\tprint(len(userssend))\\n\\t\\ttry:\\n\\t\\t\\tif len(userssend) >= 520:\\n\\t\\t\\t\\tstrround = round(len(userssend))\\n\\t\\t\\t\\tstrlen = round(strround) / 2\\n\\t\\t\\t\\tfirst_half = userssend[:int(strlen)]\\n\\t\\t\\t\\tsecond_half = userssend[int(strlen):]\\n\\t\\t\\t\\tawait self.send(first_half, whisper=[ctx.author.id])\\n\\t\\t\\t\\tawait asyncio.sleep(2)\\n\\t\\t\\t\\tawait self.send(second_half, whisper=[ctx.author.id])\\n\\t\\t\\t\\treturn\\n\\t\\t\\tprint(\\\"done\\\")\\n\\t\\t\\tawait self.send(userssend, whisper=[ctx.author.id])\\n\\t\\texcept Exception as e:\\n\\t\\t\\tprint(e)\",\n \"def collect_allowed(message):\\n return True\",\n \"def verify_text(self, text):\\n pass\",\n \"def check_request(self, request):\\n\\n # Prima di tutto verifichiamo che non esistano ban attivi\\n check = Ban.objects.filter(ip=Ban.get_client_ip(request), expires__gte=now()).first()\\n\\n if check:\\n logger.warning(\\\"Accesso da parte di un ip bannato: %r. Scadenza ban: %s\\\",\\n check.ip, check.expires)\\n raise PermissionDenied('IP Bannato')\\n\\n if not 'HTTP_X_KEY' in request.META:\\n logger.warning(\\\"Non e' stata passata la chiave pubblica\\\")\\n raise PermissionDenied('Key non presente')\\n\\n if not 'HTTP_X_CHARID' in request.META:\\n logger.warning(\\\"Non e' stato passato il charid\\\")\\n raise PermissionDenied('CharId non presente')\\n\\n if not 'SERVER_PROTOCOL' in request.META or request.META['SERVER_PROTOCOL'] != 'HTTP/1.0':\\n logger.warning(\\\"Il server protocol non corrisponde\\\")\\n raise PermissionDenied('Server protocol non valido')\\n\\n if not 'HTTP_X_RANDOM_ID' in request.META:\\n logger.warning('Non e\\\\' stato passato l\\\\'hash dello script')\\n raise PermissionDenied('Hash script non valido')\\n\\n if not 'HTTP_X_DECODE' in request.META or not 'HTTP_X_SHARD' in request.META:\\n logger.warning('Missing char info')\\n raise PermissionDenied('Missing char info')\\n\\n try:\\n decrypted_char_id = decrypt(request.META['HTTP_X_KEY'], settings.PUBLIC_KEY)\\n char_id = request.META['HTTP_X_CHARID']\\n script_hash = codecs.decode(request.META['HTTP_X_RANDOM_ID'], 'rot_13')\\n\\n if decrypted_char_id != char_id:\\n logger.warning(\\\"La chiave pubblica non corrisponde con il charid: cid %s chiave %s\\\",\\n char_id, decrypted_char_id)\\n raise PermissionDenied('La chiave pubblica non corrisponde con il charid')\\n\\n return decrypted_char_id, script_hash\\n except TypeError:\\n logger.exception('Errore di decodifica del base64')\\n raise ValueError()\",\n \"async def check_virus(self, ctx: commands.Context, target: discord.Member) -> None:\\n\\n answer: discord.PartialMessageable = None\\n if isinstance(ctx, commands.Context):\\n answer = ctx.send\\n else:\\n answer = ctx.respond\\n\\n infected = ctx.author\\n\\n hack = await self.get_skill_action_by_target_id_and_skill_type(target.id, skill_type='hack')\\n if hack[8] != 'virus' or hack[0] == infected.id:\\n return\\n\\n effects = await self.get_user_effects(infected)\\n if 'hacked' in effects:\\n return\\n\\n if 'protected' in effects:\\n return\\n\\n if 'reflect' in effects:\\n attacker = await discord.utils.get(ctx.guild.members, id=hack[0])\\n await self.reflect_attack(ctx, attacker, target, 'hack')\\n \\n try:\\n current_timestamp = await utils.get_timestamp()\\n # Don't need to store it, since it is forever\\n await self.insert_skill_action(\\n user_id=hack[0], skill_type=\\\"hack\\\", skill_timestamp=current_timestamp,\\n target_id=infected.id, channel_id=ctx.channel.id, content=\\\"virus\\\"\\n ) \\n\\n except Exception as e:\\n print('Failed virus', e)\\n else:\\n virus_embed = await self.get_virus_embed(\\n channel=ctx.channel, perpetrator_id=hack[0], target_id=target.id, infected_id=infected.id)\\n await answer(embed=virus_embed)\",\n \"def test_kyc_get_legal_share_holders(self):\\n pass\",\n \"def __is_item_vulnerable(self, queue_item):\\n\\n try:\\n HTTPHandler(None, queue_item)\\n except Exception:\\n return False\\n\\n if not \\\"html\\\" in queue_item.response.headers.get(\\\"content-type\\\"):\\n return False\\n\\n if not queue_item.get_soup_response():\\n return False\\n\\n if not self.__should_payload_execute(queue_item):\\n return False\\n\\n if self.__verify_payload:\\n if not self.__verify_queue_item(queue_item.verify_item):\\n return False\\n\\n return True\",\n \"async def update_hacks_content(self, attacker_id: int) -> None:\\n\\n mycursor, db = await the_database()\\n await mycursor.execute(\\\"UPDATE SlothSkills SET content = 'virus' WHERE user_id = %s\\\", (attacker_id,))\\n await db.commit()\\n await mycursor.close()\",\n \"def __sanitize_input(self):\\n self.__check_for_video_file()\\n self.__manage_output_folder()\",\n \"def test_lack_of_sanitization_function(self, mock_function):\\n for (broken, clean) in self.needSanitization:\\n self.assertNotEqual(clean, sanitizeFeedback(broken))\",\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_forbidden_blocked_conanmanifest():\\n server = TestServer()\\n servers = {\\\"default\\\": server}\\n client = TestClient(servers=servers, inputs=[\\\"admin\\\", \\\"password\\\"])\\n client.save({\\\"conanfile.py\\\": GenConanfile()})\\n client.run(\\\"create . --name=lib --version=1.0\\\")\\n client.run(\\\"upload lib/1.0* -c -r default\\\")\\n\\n class DownloadForbidden(TestRequester):\\n def get(self, url, **kwargs):\\n if \\\"conanmanifest.txt\\\" in url:\\n r = Response()\\n r._content = \\\"Forbidden because of security!!!\\\"\\n r.status_code = 403\\n return r\\n else:\\n return super(DownloadForbidden, self).get(url, **kwargs)\\n\\n client = TestClient(servers=servers, inputs=[\\\"admin\\\", \\\"password\\\"],\\n requester_class=DownloadForbidden)\\n client.run(\\\"download lib/1.0 -r=default\\\", assert_error=True)\\n assert \\\"Forbidden because of security!!!\\\" in client.out\\n\\n client.run(\\\"list *\\\")\\n assert \\\"lib/1.0\\\" not in client.out\\n\\n client.run(\\\"install --requires=lib/1.0\\\", assert_error=True)\\n assert \\\"Forbidden because of security!!!\\\" in client.out\\n\\n client.run(\\\"list *\\\")\\n assert \\\"lib/1.0\\\" not in client.out\",\n \"def violated(self) -> bool:\\n ...\",\n \"def _verify(self):\\n pass\",\n \"def ConfirmAllowedCopyrightHolder(holder):\\n return holder in ALLOWED_COPYRIGHT_HOLDERS\",\n \"def test_real_world_malware(self):\\n key = bytes.fromhex('0394d550fb286dda')\\n data = bytes.fromhex('6bdb2c294e7e031c38e4adecaa8dc755')\\n unit = self.load(key, raw=True)\\n self.assertEqual(unit.decrypt(data).hex(), '4c5a495001b30026968e700017f7ec05')\",\n \"async def badman(self, ctx):\\n await ctx.message.edit(content=\\\"̿̿ ̿̿ ̿̿ ̿'̿'\\\\̵͇̿̿\\\\з= ( ▀ ͜͞ʖ▀) =ε/̵͇̿̿/’̿’̿ ̿ ̿̿ ̿̿ ̿̿\\\")\",\n \"def isSpam(textLine):\\n\\treturn True\",\n \"def test_forbidden_words(self) -> None:\\n pad_open: bool = False\\n words: List[Word] = self.report.get_words()\\n forbidden_words: List[Word] = []\\n last_error: bool = False\\n\\n for word in words:\\n if word.text in self.rules.citation_delimiters:\\n pad_open = not pad_open\\n continue\\n if pad_open:\\n continue\\n if (word.text in self.rules.forbidden_words) or any(\\n [b in self.rules.forbidden_words for b in word.baseform]\\n ):\\n forbidden_words.append(word)\\n last_error = True\\n continue\\n if last_error:\\n last_error = False\\n combo = \\\" \\\".join([w.text for w in forbidden_words])\\n start, _ = self.report.get_word_postion(forbidden_words[0])\\n _, end = self.report.get_word_postion(forbidden_words[-1])\\n self.add_error(\\n f\\\"Ordet {combo} får endast förekomma i citat.\\\", position=(start,end)\\n )\",\n \"def immobilized(self, owner):\\n messages = []\\n immobilized = False\\n \\n if self.checkOver(owner, messages):\\n immobilized = False\\n \\n elif self.confused(random.randint(0, 1)):\\n self.doDamage(owner, messages)\\n immobilized = True\\n \\n return immobilized, messages\",\n \"def hack_text_file(self):\\r\\n\\t\\t#Ensures that the file has something that can be hacked.\\r\\n\\t\\tfile_contains_message = True\\r\\n\\t\\twhile file_contains_message:\\r\\n\\t\\t\\tfile_exists = True\\r\\n\\t\\t\\t#Checks to see if the file exists.\\r\\n\\t\\t\\twhile file_exists:\\r\\n\\t\\t\\t\\tself.text_file_name = input(\\\"Please enter the name of the text file you wish to decrypt in format |file_name.txt|.--> \\\")\\r\\n\\t\\t\\t\\tif \\\".txt\\\" in self.text_file_name:\\r\\n\\t\\t\\t\\t\\tfile_exists = Doc_Control().check_for_file(self.text_file_name)\\r\\n\\t\\t\\t\\telse: \\r\\n\\t\\t\\t\\t\\tcontinue\\r\\n\\t\\t\\t#Verifys file contains a message before before running through hack and giving user their list of decryption hits.\\r\\n\\t\\t\\twhile True: \\r\\n\\t\\t\\t\\tself.message = Doc_Control().open_file(self.text_file_name)\\r\\n\\t\\t\\t\\tif self.message != \\\"\\\" and len(self.message) > 4:\\r\\n\\t\\t\\t\\t\\tfile_contains_message = False\\r\\n\\t\\t\\t\\t\\tbreak\\r\\n\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\tprint(\\\"Your file does not contain a hackable message.\\\")\\r\\n\\t\\t\\t\\t\\tbreak\\t\\t\\t\\r\\n\\t\\tmax_key = len(self.message)\\r\\n\\t\\tself.i = 1\\r\\n\\t\\tpotential_hits = []\\r\\n\\t\\t#Runs through all potential keys. \\r\\n\\t\\tfor self.i in range(1, max_key):\\r\\n\\t\\t\\tprint(f\\\"Trying key #{self.i} of {max_key} possible keys\\\")\\t\\t\\t\\r\\n\\t\\t\\tself.my_code = Decryptor(self.message, self.i).transfer_decrypt()\\r\\n\\t\\t\\tself.hack_plausible = False\\r\\n\\t\\t\\tself.verify_hack_key()\\r\\n\\t\\t\\tif self.hack_plausible:\\r\\n\\t\\t\\t\\tpotential_hits.append(f\\\"Key #{self.i} yeilded {self.percent_english}% english words after decryption.\\\\n\\\" + \\\"\\\\t\\\" + self.my_code[:50])\\r\\n\\t\\tprint(\\\"~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\\\n\\\")\\r\\n\\t\\tprint(\\\"Hacking results:\\\\n\\\")\\r\\n\\t\\tfor hit in potential_hits:\\r\\n\\t\\t\\tprint(\\\"\\\\t\\\" + hit + \\\"|\\\\n\\\")\",\n \"def verify(self):\\r\\n self.title = self.title and self.title or '' \\r\\n self.descr = self.descr and self.descr or '' \\r\\n self.link = self.link and self.link or ''\\r\\n self.channelURL = self.channelURL and self.channelURL or ''\",\n \"def test_allow_noquote(self):\\n val = DwcaValidator(yaml.load(self.yaml_allow1, Loader=yaml.FullLoader),\\n error_handler=WhipErrorHandler)\\n document = {'sex': 'male'}\\n self.assertTrue(val.validate(document))\\n\\n document = {'sex': 'female'}\\n self.assertFalse(val.validate(document))\",\n \"def test_kyc_get_legal(self):\\n pass\",\n \"def sanitize(cls):\",\n \"def test_store_inline_bad_digest(self):\\n namespace = 'default-gzip'\\n request = self.store_request(namespace, 'anseres sacri')\\n request.content = ':)' + request.content[2:]\\n with self.call_should_fail('400'):\\n self.call_api('store_inline', self.message_to_dict(request), 200)\",\n \"def test_courses_with_unsafe_code_default(self):\\r\\n self.assertFalse(can_execute_unsafe_code(SlashSeparatedCourseKey('edX', 'full', '2012_Fall')))\\r\\n self.assertFalse(can_execute_unsafe_code(SlashSeparatedCourseKey('edX', 'full', '2013_Spring')))\",\n \"def send_malicious_proof(self, community, member, candidate):\\n if __debug__:\\n from .community import Community\\n assert isinstance(community, Community)\\n assert isinstance(member, Member)\\n assert member.must_blacklist, \\\"must be blacklisted\\\"\\n assert isinstance(candidate, Candidate)\\n\\n packets = [str(packet) for packet, in self._database.execute(u\\\"SELECT packet FROM malicious_proof WHERE community = ? AND member = ?\\\",\\n (community.database_id, member.database_id))]\\n if packets:\\n self._statistics.dict_inc(self._statistics.outgoing, u\\\"-malicious-proof\\\", len(packets))\\n self._endpoint.send([candidate], packets)\",\n \"def test_block_bad_signature(self):\\n pass\",\n \"def test_kyc_put_legal(self):\\n pass\",\n \"def test_lessthan(self):\\r\\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.text_lessthan_noencd), self.text_lessthan_encode)\",\n \"def test_mixed_verfication(self):\\n\\n lists_map = ima.process_allowlists(ALLOWLIST, '')\\n lists_map_wrong = ima.process_allowlists(ALLOWLIST_WRONG, '')\\n lists_map_empty = ima.process_allowlists(ALLOWLIST_EMPTY, '')\\n lists_map_exclude = ima.process_allowlists(ALLOWLIST, EXCLUDELIST)\\n lists_map_exclude_wrong = ima.process_allowlists(ALLOWLIST_WRONG, EXCLUDELIST)\\n empty_keyring = ima_file_signatures.ImaKeyring()\\n\\n # every entry is covered by the allowlist and there's no keyring -> this should pass\\n self.assertTrue(ima.process_measurement_list(COMBINED.splitlines(), str(lists_map)) is not None)\\n\\n curdir = os.path.dirname(os.path.abspath(__file__))\\n keydir = os.path.join(curdir, \\\"data\\\", \\\"ima_keys\\\")\\n keyring = ima_file_signatures.ImaKeyring()\\n\\n rsakeyfile = os.path.join(keydir, \\\"rsa2048pub.pem\\\")\\n pubkey, keyidv2 = ima_file_signatures.get_pubkey_from_file(rsakeyfile)\\n keyring.add_pubkey(pubkey, keyidv2)\\n\\n eckeyfile = os.path.join(keydir, \\\"secp256k1.pem\\\")\\n pubkey, keyidv2 = ima_file_signatures.get_pubkey_from_file(eckeyfile)\\n keyring.add_pubkey(pubkey, keyidv2)\\n\\n # entries are not covered by a exclude list -> this should fail\\n self.assertTrue(ima.process_measurement_list(COMBINED.splitlines(), ima_keyring=keyring) is None)\\n\\n # all entries are either covered by allow list or by signature verification -> this should pass\\n self.assertTrue(ima.process_measurement_list(COMBINED.splitlines(), str(lists_map), ima_keyring=keyring) is not None)\\n\\n # the signature is valid but the hash in the allowlist is wrong -> this should fail\\n self.assertTrue(ima.process_measurement_list(SIGNATURES.splitlines(), str(lists_map_wrong), ima_keyring=keyring) is None)\\n\\n # the signature is valid and the file is not in the allowlist -> this should pass\\n self.assertTrue(ima.process_measurement_list(SIGNATURES.splitlines(), str(lists_map_empty), ima_keyring=keyring) is not None)\\n\\n # the signature is invalid but the correct hash is in the allowlist -> this should fail\\n self.assertTrue(ima.process_measurement_list(SIGNATURES.splitlines(), str(lists_map), ima_keyring=empty_keyring) is None)\\n\\n # the file has no signature but the hash is correct -> this should pass\\n self.assertTrue(ima.process_measurement_list(MEASUREMENTS.splitlines(), str(lists_map)))\\n\\n # All files are in the exclude list but hashes are invalid -> this should pass\\n self.assertTrue(ima.process_measurement_list(MEASUREMENTS.splitlines(), str(lists_map_exclude_wrong)) is not None)\\n\\n # All files are in the exclude list and their signatures are invalid -> this should pass\\n self.assertTrue(ima.process_measurement_list(SIGNATURES.splitlines(), str(lists_map_exclude), ima_keyring=empty_keyring) is not None)\\n\\n # All files are in the exclude list but hashes or signatures are invalid -> this should pass\\n self.assertTrue(ima.process_measurement_list(MEASUREMENTS.splitlines(), str(lists_map_exclude_wrong), ima_keyring=empty_keyring) is not None)\",\n \"def generateBroSafetyCheck(self):\\n pass\",\n \"def check_spam(self, request=None):\\n key = self._get_key()\\n\\n if not key:\\n # TODO: log a warning\\n return False\\n\\n domain = self._get_domain()\\n\\n try:\\n if verify_key(key, domain):\\n data = self.get_spam_data(request)\\n return comment_check(key, domain, **data)\\n except AkismetError, e:\\n # TODO: log a warning with the exception\\n print e.response, e.statuscode\\n return False\",\n \"def test_auth_sharable_cannot_share(self):\\n self.do_sharable(False, 'pattieblack', FakeMembership(False),\\n tenant='froggy')\",\n \"def safe_to_dance(self):\\n # check for all fail/early-termination conditions\\n for _ in range(4):\\n if self.read_distance() < 300:\\n print(\\\"NOT SAFE TO DANCE!\\\")\\n return False\\n else: \\n self.turn_by_deg(90) \\n\\n #after all checks have been done. We deduce it's safe\\n print(\\\"SAFE TO DANCE!\\\")\\n return True\\n\\n for x in range(3): \\n self.shake()\",\n \"def VulnerableBy(self):\\n\\n print TextColor.WARNING + '[!] Please wait for check the site for vulnerability ...'\\n print\\n\\n with open(\\\"./WebAttack/sqlinjection/payloads/InjectionChars.json\\\") as jsonFile:\\n payloads = json.load(jsonFile)\\n\\n for item in payloads[\\\"defInjectionChars\\\"]:\\n\\n resposne = requests.get(url=self.url + str(item), headers=define_headerdata, verify=False)\\n result = self.__CheckVulnerability__(content=resposne.text)\\n\\n if result != 'none':\\n print TextColor.RED + '\\\\t[+] %s ' % (self.url + str(item)) + \\\" => vulnerable\\\" + TextColor.WHITE\\n return {'database': result, 'char': item}\\n else:\\n print TextColor.GREEN + '\\\\t[+] %s ' % (self.url + str(item)) + \\\" => clear\\\" + TextColor.WHITE\\n continue\\n\\n sleep(.5)\",\n \"def clean_request_allowance(self):\\n data = self.cleaned_data['request_allowance']\\n # Comparing GB form field to bytes model field\\n if data * 1024 ** 3 <= self.project.core_project.storage_allowance:\\n raise forms.ValidationError('Project already has the requested allowance.',\\n code='already_has_allowance')\\n\\n return data\",\n \"def is_spam(code):\\n urlfind = re.compile(\\\"[A-Za-z]+://.*?\\\")\\n urls = urlfind.findall(code)\\n url_count = len(urls)\\n\\n if url_count > URLS_LIMIT:\\n return True\\n else:\\n word_count = len(code.split())\\n urls_percentage = (url_count * 100) / word_count\\n\\n if urls_percentage > URLS_PERCENTAGE:\\n return True\\n else:\\n return False\",\n \"def clean_content(self):\\n content = self.cleaned_data.get('content', None)\\n if '<script' in content:\\n raise forms.ValidationError(\\\"These tags are not allowed\\\")\\n return content\",\n \"def test_allowed_string(self):\\n val = DwcaValidator(yaml.load(self.yaml_allowed_string, Loader=yaml.FullLoader),\\n error_handler=WhipErrorHandler)\\n document = {'abundance': 'many'}\\n self.assertTrue(val.validate(document))\\n document = {'abundance': 'female'}\\n self.assertFalse(val.validate(document))\",\n \"def test_blind_sig_value(self):\\n signer_obj = ECCBlind(value=5)\\n point_r = signer_obj.signer_init()\\n requester_obj = ECCBlind(pubkey=signer_obj.pubkey())\\n msg = os.urandom(64)\\n msg_blinded = requester_obj.create_signing_request(point_r, msg)\\n signature_blinded = signer_obj.blind_sign(msg_blinded)\\n signature = requester_obj.unblind(signature_blinded)\\n verifier_obj = ECCBlind(pubkey=signer_obj.pubkey())\\n self.assertFalse(verifier_obj.verify(msg, signature, value=8))\",\n \"def test_removeIllegalCharacters(self):\\n data = \\\"Contains\\\\x03 control\\\\x06 characters\\\\x12 some\\\\x0a\\\\x09allowed\\\\x0d\\\"\\n after, changed = removeIllegalCharacters(data)\\n self.assertEquals(after, \\\"Contains control characters some\\\\x0a\\\\x09allowed\\\\x0d\\\")\\n self.assertTrue(changed)\\n\\n data = \\\"Contains\\\\x09only\\\\x0a legal\\\\x0d\\\"\\n after, changed = removeIllegalCharacters(data)\\n self.assertEquals(after, \\\"Contains\\\\x09only\\\\x0a legal\\\\x0d\\\")\\n self.assertFalse(changed)\",\n \"def _verify_content(state_content_list):\\n CONTENT_ITEM_SCHEMA = [\\n ('type', basestring), ('value', basestring)]\\n ALLOWED_CONTENT_TYPES = ['text', 'image', 'video']\\n\\n for content_item in state_content_list:\\n utils.verify_dict_keys_and_types(content_item, CONTENT_ITEM_SCHEMA)\\n if content_item['type'] not in ALLOWED_CONTENT_TYPES:\\n raise Exception('Unsupported content type %s.' %\\n content_item['type'])\",\n \"def check_validity(self):\",\n \"def test_forbidden(self):\\n self._error_test(fitbit_exceptions.HTTPForbidden)\",\n \"def verify(self):\\r\\n pass\",\n \"def enSilencio(self,data_chunk):\\n return max(data_chunk) < self.THRESHOLD\",\n \"def test_embed(self):\\r\\n self.assertHtmlEqual(OpenEndedChild.sanitize_html(self.embed_dirty), self.embed_clean)\",\n \"def _verify_page(self):\",\n \"def test_kyc_get_legal_share_holder_natural(self):\\n pass\",\n \"def verify(self):\",\n \"def test_oneStoreDamaged(self):\\n contentStore = self._store()\\n obj = self._storeObject(\\n contentStore=contentStore,\\n content='somecontent',\\n contentType=u'application/octet-stream')\\n obj.content.setContent('damaged')\\n f = self.failureResultOf(self._verify(contentStore, obj), NoGoodCopies)\\n self.assertEqual(f.value.objectId, obj.objectId)\",\n \"def check_embed(embed: Embed) -> bool:\\n if len(embed) <= 6000:\\n if hasattr(embed, \\\"title\\\"):\\n if len(embed.title) <= 256:\\n pass\\n else:\\n return False\\n if len(embed.fields) <= 25:\\n for field in embed.fields:\\n if len(field.name) <= 69420:\\n pass\",\n \"def hasVeryTrustedValue(self):\",\n \"def can_execute_unsafe_code(course_id):\\r\\n # To decide if we can run unsafe code, we check the course id against\\r\\n # a list of regexes configured on the server.\\r\\n # If this is not defined in the environment variables then default to the most restrictive, which\\r\\n # is 'no unsafe courses'\\r\\n # TODO: This should be a database configuration, where we can mark individual courses as being\\r\\n # safe/unsafe. Someone in the future should switch us over to that rather than using regexes\\r\\n # in a settings file\\r\\n # To others using this: the code as-is is brittle and likely to be changed in the future,\\r\\n # as per the TODO, so please consider carefully before adding more values to COURSES_WITH_UNSAFE_CODE\\r\\n for regex in getattr(settings, 'COURSES_WITH_UNSAFE_CODE', []):\\r\\n if re.match(regex, course_id.to_deprecated_string()):\\r\\n return True\\r\\n return False\",\n \"def hasVeryTrustedValue():\\n return False\",\n \"def hasVeryTrustedValue():\\n return False\",\n \"def hasVeryTrustedValue():\\n return False\",\n \"def hasVeryTrustedValue():\\n return False\",\n \"def hasVeryTrustedValue():\\n return False\",\n \"def verify(self):\\n pass\",\n \"def verify(self):\\n pass\",\n \"def test_idempotent():\\n dirty = u'<span>invalid & </span> < extra http://link.com<em>'\\n\\n clean = bl.clean(dirty)\\n eq_(clean, bl.clean(clean))\\n\\n bleached = bl.bleach(dirty)\\n eq_(bleached, bl.bleach(bleached))\\n\\n linked = bl.linkify(dirty)\\n eq_(linked, bl.linkify(linked))\",\n \"def hasVeryTrustedValue():\\n return True\",\n \"def check_for_no_privates(context):\\n json_data = context.response.json()\\n\\n if \\\"component_analyses\\\" in json_data:\\n vulnerabilities = json_data['component_analyses']['vulnerability']\\n for v in vulnerabilities:\\n assert \\\"cvss\\\" in v\\n assert \\\"is_private\\\" in v\\n assert \\\"vendor_cve_ids\\\" in v\\n if v[\\\"is_private\\\"]:\\n raise Exception(\\\"Private vulnerability found\\\")\",\n \"def _check_validity(self):\\n pass\",\n \"def verify(self, ta):\\n\\n self.decode(CMS_object.verify(self, ta))\\n return self.get_content()\",\n \"def verify(self):\\n self.verify_checksums()\\n self.verify_apk_signature()\\n self.verify_apk_signature_fprs()\",\n \"def check():\\n suspicious_telemarketers = get_suspicious_telemarketers(calls, texts)\\n outgoing = set()\\n non_tele = set()\\n for c in calls:\\n outgoing.add(c[0])\\n non_tele.add(c[1])\\n for t in texts:\\n non_tele.add(t[0])\\n non_tele.add(t[1])\\n telemarketers = sorted(outgoing - non_tele)\\n if len(suspicious_telemarketers) == len(telemarketers):\\n print('Pass')\",\n \"def _check_protects(self, p4user, blobs):\\n pc = ProtectsChecker(self.ctx, p4user, self.ctx.authenticated_p4user,\\n self.ctx.foruser)\\n pc.filter_paths(blobs)\\n if pc.has_error():\\n raise PreflightException(pc.error_message())\",\n \"def allow(self, comment, content_object, request):\\n # Tests for cookie:\\n if settings.COOKIE_KEY not in request.COOKIES \\\\\\n and (settings.DISCARD_SPAM or settings.DISCARD_NO_COOKIE):\\n return False\\n elif settings.COOKIE_KEY not in request.COOKIES:\\n comment.is_removed = True\\n comment.is_public = False\\n return True\\n return True\",\n \"def mark_safe(self, cell):\\n self.safes.add(cell)\\n for sentence in self.knowledge:\\n sentence.mark_safe(cell)\",\n \"def mark_safe(self, cell):\\n self.safes.add(cell)\\n for sentence in self.knowledge:\\n sentence.mark_safe(cell)\",\n \"def mark_safe(self, cell):\\n self.safes.add(cell)\\n for sentence in self.knowledge:\\n sentence.mark_safe(cell)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6266415","0.606212","0.5981505","0.58764136","0.56155235","0.5567562","0.5503536","0.5503536","0.54759705","0.54505795","0.53994906","0.5343958","0.53100395","0.52728504","0.52579534","0.52579534","0.51845664","0.5134979","0.5133656","0.5132123","0.5127079","0.5107603","0.51056945","0.51031727","0.5093199","0.5086791","0.50786644","0.5041849","0.50371313","0.5027101","0.50253373","0.5021586","0.5003352","0.49912125","0.4983748","0.4975451","0.49640328","0.49439287","0.4941112","0.49266726","0.49201065","0.49102697","0.49016154","0.48987553","0.48972055","0.48702505","0.4852019","0.48465985","0.48437867","0.4838589","0.4836804","0.48319978","0.4827246","0.48232412","0.4822109","0.48062178","0.48050073","0.47976673","0.47975513","0.47966233","0.4778359","0.47779608","0.47744384","0.475868","0.47581705","0.475676","0.47452602","0.47421217","0.47414735","0.47395006","0.47368222","0.47328344","0.47306627","0.47271985","0.47256947","0.47237656","0.47204822","0.47155958","0.47063896","0.47016364","0.46937296","0.46890068","0.46890068","0.46890068","0.46890068","0.46890068","0.46868926","0.46868926","0.46856368","0.46822768","0.46671605","0.46598977","0.46569556","0.46540213","0.46536043","0.4650637","0.46475723","0.4647313","0.4647313","0.4647313"],"string":"[\n \"0.6266415\",\n \"0.606212\",\n \"0.5981505\",\n \"0.58764136\",\n \"0.56155235\",\n \"0.5567562\",\n \"0.5503536\",\n \"0.5503536\",\n \"0.54759705\",\n \"0.54505795\",\n \"0.53994906\",\n \"0.5343958\",\n \"0.53100395\",\n \"0.52728504\",\n \"0.52579534\",\n \"0.52579534\",\n \"0.51845664\",\n \"0.5134979\",\n \"0.5133656\",\n \"0.5132123\",\n \"0.5127079\",\n \"0.5107603\",\n \"0.51056945\",\n \"0.51031727\",\n \"0.5093199\",\n \"0.5086791\",\n \"0.50786644\",\n \"0.5041849\",\n \"0.50371313\",\n \"0.5027101\",\n \"0.50253373\",\n \"0.5021586\",\n \"0.5003352\",\n \"0.49912125\",\n \"0.4983748\",\n \"0.4975451\",\n \"0.49640328\",\n \"0.49439287\",\n \"0.4941112\",\n \"0.49266726\",\n \"0.49201065\",\n \"0.49102697\",\n \"0.49016154\",\n \"0.48987553\",\n \"0.48972055\",\n \"0.48702505\",\n \"0.4852019\",\n \"0.48465985\",\n \"0.48437867\",\n \"0.4838589\",\n \"0.4836804\",\n \"0.48319978\",\n \"0.4827246\",\n \"0.48232412\",\n \"0.4822109\",\n \"0.48062178\",\n \"0.48050073\",\n \"0.47976673\",\n \"0.47975513\",\n \"0.47966233\",\n \"0.4778359\",\n \"0.47779608\",\n \"0.47744384\",\n \"0.475868\",\n \"0.47581705\",\n \"0.475676\",\n \"0.47452602\",\n \"0.47421217\",\n \"0.47414735\",\n \"0.47395006\",\n \"0.47368222\",\n \"0.47328344\",\n \"0.47306627\",\n \"0.47271985\",\n \"0.47256947\",\n \"0.47237656\",\n \"0.47204822\",\n \"0.47155958\",\n \"0.47063896\",\n \"0.47016364\",\n \"0.46937296\",\n \"0.46890068\",\n \"0.46890068\",\n \"0.46890068\",\n \"0.46890068\",\n \"0.46890068\",\n \"0.46868926\",\n \"0.46868926\",\n \"0.46856368\",\n \"0.46822768\",\n \"0.46671605\",\n \"0.46598977\",\n \"0.46569556\",\n \"0.46540213\",\n \"0.46536043\",\n \"0.4650637\",\n \"0.46475723\",\n \"0.4647313\",\n \"0.4647313\",\n \"0.4647313\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.57496166"},"document_rank":{"kind":"string","value":"4"}}},{"rowIdx":18696,"cells":{"query":{"kind":"string","value":"Upload a file into the s3 bucket."},"document":{"kind":"string","value":"def storage_upload_file(self, file_meta=None, file_obj=None):\n if file_meta != None and file_obj != None:\n m = hashlib.md5()\n if file_meta.location == 'local':\n dest_filename = file_meta.storage\n try:\n group = 'corr-resources'\n if file_meta.group != 'descriptive':\n group = 'corr-%ss'%file_meta.group\n print(group)\n content = file_obj.read()\n safety = self.is_safe(content)\n if not safety[0]:\n return [False, safety[1]]\n else:\n if self.config['type'] == 's3':\n s3_files = self.s3.Bucket(self.bucket)\n s3_files.put_object(Key='{0}/{1}'.format(group, dest_filename), Body=content)\n elif self.config['type'] == 'filesystem':\n self.app.logger.info('{0}/{1}/{2}'.format(self.storage_path, group, dest_filename))\n print('{0}/{1}/{2}'.format(self.storage_path, group, dest_filename))\n with open('{0}/{1}/{2}'.format(self.storage_path, group, dest_filename), \"wb\") as obj:\n obj.write(content)\n\n m.update(content)\n file_meta.checksum = m.hexdigest()\n file_meta.save()\n return [True, \"File uploaded successfully\"]\n except:\n self.app.logger.error(traceback.print_exc())\n return [False, traceback.format_exc()]\n else:\n file_obj = self.web_get_file(file_meta.storage)\n safety = self.is_safe(content)\n if file_obj and safety[0]:\n m.update(file_obj.getvalue())\n file_meta.checksum = m.hexdigest()\n file_meta.save()\n if safety[0]:\n return [True, \"Cannot upload a file that is remotely set. It has to be local targeted.\"]\n else:\n return [False, safety[1]]\n else:\n return [False, \"file meta data does not exist or file content is empty.\"]"},"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 upload_object(self, file_path, s3_path):\n logging.info(\"Uploading file to \\\"{}\\\" to S3\".format(s3_path))\n bucket_name, key = S3Util.get_bucket_and_key(s3_path)\n self.s3_resource.Bucket(bucket_name).upload_file(file_path, key)","def _upload_s3(self, filename, bucket, objectKey):\n return s3_client.upload_file(filename, bucket, objectKey)","def upload_file(file_name, bucket):\r\n object_name = file_name\r\n s3_client = boto3.client('s3')\r\n response = s3_client.upload_file(file_name, bucket, object_name)\r\n\r\n return response","def upload_s3_file(key, bucket, filename):\n s3_client = boto3.client('s3')\n s3_client.upload_file(filename, bucket, key)\n return True","def upload(self, file_path, bucket_name, file_name):\n\n self.client.upload_file(file_path, bucket_name, file_name)","def upload(\n bucket: str, key: str, filename: str, session: Optional[boto3.Session] = None\n) -> None:\n s3_client = _get_client(session)\n LOGGER.info(\"uploading %s to s3://%s/%s...\", filename, bucket, key)\n s3_client.upload_file(Filename=filename, Bucket=bucket, Key=key)","def upload_file_s3(file_name, bucket):\n\n # If S3 object_name was not specified, use file_name \n try:\n response = s3_client.upload_file(file_name,\n bucket, \n file_name.replace('../',''))\n print(\"Uploaded \" + file_name)\n except ClientError as e:\n print(\"Failed to upload \" + file_name)\n logging.error(e)\n return False\n return True","def upload(filename, bucket):\n print(\"Uploading {} to S3\".format(filename.lower().replace('_', '-')))\n url = \"https://s3.ca-central-1.amazonaws.com/{}/{}\".format(bucket,\n filename.lower().replace('_', '-'))\n with open('{}/{}'.format(WORK_DIR, filename), 'rb') as data:\n requests.put(url, data=data)","def upload_file(self, file_name, bucket, object_name=None):\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name\n\n # Upload the file\n s3_client = boto3.client('s3', aws_access_key_id=self.aws_access_key_id, aws_secret_access_key=self.aws_secret_access_key)\n try:\n s3_client.upload_file(file_name, bucket, object_name)\n except ClientError as e:\n logging.exception(e)\n return False\n logging.info(\"Upload to S3 bucket complete!\")\n\n return True","def upload_to_s3(file_name, bucket, key): \n s3 = boto3.resource('s3') \n try:\n s3.meta.client.upload_file(file_name, bucket, key)\n print(\"s3 upload success -- uploaded \" + file_name + \" to the bucket: \" + bucket)\n except ClientError as e:\n logging.error(e)\n return False\n print(\"s3 upload error occurs\", e)\n return True","def upload_to_s3(file_from_machine, bucket, file_to_s3):\n s3.upload_file(file_from_machine, bucket, file_to_s3)\n print(file_to_s3, \" : is upoaded to s3\")","def upload_to_s3(file_path, config):\n logging.info(\"Uploading file to S3 bucket: %s\", config['s3_bucket_name'])\n s3 = boto3.resource('s3')\n s3_filename = config['s3_bucket_path'] + config['rendered_filename']\n s3.Bucket(config['s3_bucket_name']).upload_file(\n file_path, s3_filename, ExtraArgs={\n 'ContentType': 'text/html', 'ACL': 'public-read'})","def upload_file(file_name: str, bucket: str, object_name: str =None) -> None:\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name\n\n # Upload the file\n s3_client = boto3.client(\"s3\")\n try:\n s3_client.upload_file(file_name, bucket, object_name)\n except ClientError as e:\n logging.error(e)","def upload(file_path, aws_path, access_key, secret_key) -> None:\n # bucket = \"dev-com-courtlistener-storage\"\n bucket = \"seals.free.law\"\n client = boto3.client(\n \"s3\",\n aws_access_key_id=access_key,\n aws_secret_access_key=secret_key,\n )\n transfer = S3Transfer(client)\n if \".png\" in file_path:\n content_type = \"image/png\"\n else:\n content_type = \"image/svg+xml\"\n transfer.upload_file(\n file_path,\n bucket,\n aws_path,\n extra_args={\"ContentType\": content_type, \"ACL\": \"public-read\"},\n )\n print(f\"http://{bucket}.s3-us-west-2.amazonaws.com/{aws_path}\")","def upload_file(file_name, bucket, object_name=None):\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name\n\n # Upload the file\n try:\n response = s3_client.upload_file(file_name, bucket, object_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_file(file_name, bucket, object_name='patients.log'):\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name\n # Upload the file\n s3_client = boto3.client('s3')\n try:\n response = s3_client.upload_file(file_name, bucket, object_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_file_to_s3(file_path, bucket, object_name=None, access_key_id=None,\n secret_access_key=None):\n if object_name is None:\n object_name = Path(file_path).name\n\n try:\n s3_client = boto3.client(\n \"s3\",\n aws_access_key_id=access_key_id,\n aws_secret_access_key=secret_access_key\n )\n\n s3_client.upload_file(file_path, bucket, object_name)\n except ClientError:\n raise","def upload_file(self, bucket_name, file_path, key):\n self._client.upload_file(Filename=file_path, Bucket=bucket_name, Key=key)","def upload_file(file_name, bucket, object_name=None):\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name\n\n # Upload the file\n s3_client = boto3.client('s3', aws_access_key_id='', aws_secret_access_key='')\n try:\n response = s3_client.upload_file(file_name, bucket, object_name, ExtraArgs={'ACL':'public-read'})\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_file(file_name, s3_key):\n # Upload the file\n s3_connection = boto.connect_s3(aws_access_key_id, aws_secret_access_key)\n bucket = s3_connection.get_bucket(predator_bucket_name)\n try:\n key = boto.s3.key.Key(bucket, s3_key)\n key.set_contents_from_filename(file_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_to_s3(channel, file):\n s3_resource = boto3.resource('s3')\n data = open(file, \"rb\")\n key = channel + '/' + file\n s3_resource.Bucket(BUCKET).put_object(Key=key, Body=data)","def _upload_file(file_name, bucket, object_name):\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name\n\n # Upload the file\n try:\n s3.upload_file(file_name, bucket, object_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_to_s3(self, name, file_name):\n f = open(file_name, \"r\")\n path = \"cluster/\" + name + \"/\" + os.path.basename(file_name)\n bucket = self.s3.get_bucket(self.__secrets_bucket__)\n k = Key(bucket)\n k.name = path\n\n try:\n k.set_contents_from_file(f)\n except Exception as e:\n print \"[-] Error uploading file to s3\"\n print e\n\n print \"[+] Uploaded {0}\".format(\"s3://\" + self.__secrets_bucket__ + \"/\" + path)\n\n return","def upload_file(file_name, bucket_name, object_name=None):\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = os.path.basename(file_name)\n\n try:\n # Upload the file\n response = s3.upload_file(file_name, bucket_name, object_name)\n # Get list of files in bucket to confirm\n describe_objects(bucket_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_file(file_name, bucket, object_name=None):\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name\n\n # Upload the file\n s3_client = boto3.client(\"s3\")\n try:\n response = s3_client.upload_file(file_name, bucket, object_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_file(file_name, bucket, object_name=None):\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name\n\n # Upload the file\n s3_client = boto3.client('s3')\n try:\n response = s3_client.upload_file(file_name, bucket, object_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_file(file_name, bucket, object_name=None):\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name\n\n # Upload the file\n s3_client = boto3.client('s3')\n try:\n response = s3_client.upload_file(file_name, bucket, object_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_file(file_name, bucket, object_name=None):\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = os.path.basename(file_name)\n\n # Upload the file\n s3_client = boto3.client('s3')\n try:\n response = s3_client.upload_file(file_name, bucket, object_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_file(\n self, bucket_id: uplink.Path, filename: uplink.Path, file: uplink.Body\n ):\n pass","def upload_file(bucket_name, filename, file):\n client = get_client()\n bucket = client.get_bucket(bucket_name)\n blob = bucket.blob(filename)\n blob.upload_from_file(file)","def upload_file(file_name, object_name=None, bucket = BUCKET_NAME):\n\n # Upload the file\n s3_client = boto3.client('s3')\n try:\n response = s3_client.upload_file(file_name, bucket, object_name) if type(file_name) == str else s3_client.upload_fileobj(file_name, BUCKET_NAME, object_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_fileobj(self, bucket_name, file_obj, key):\n self._client.upload_fileobj(Fileobj=file_obj, Bucket=bucket_name, Key=key)","def upload_file(local_path, s3_path):\n with open(local_path, 'rb') as binary_data:\n s3.Bucket(bucket_name).put_object(Key=s3_path, Body=binary_data)","def upload_file(self, file_name, bucket, destination_name):\n try:\n not self.client.upload_file(file_name, bucket, destination_name)\n except Exception as ex:\n raise ex","def upload_file(s3_client, file_name, object_name=None):\n\n # read bucket name from cfg file\n bucket = config.get('S3', 'LANDING_ZONE')\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name.split('\\\\')[-1]\n\n # Upload the file\n try:\n response = s3_client.upload_file(file_name, bucket, object_name, Callback=ProgressPercentage(file_name))\n# logger.debug(f\"Got response from s3 client for uploading file: {response}\")\n except Exception as e:\n logger.error(f\"Error occurred while upload {file_name} : {e}\")\n return False\n return True","def upload_file_to_s3(self, file_data):\r\n\r\n file_key = file_data.name + datetime.now(UTC).strftime(\r\n xqueue_interface.dateformat\r\n )\r\n\r\n file_data.seek(0)\r\n s3_public_url = upload_to_s3(\r\n file_data, file_key, self.s3_interface\r\n )\r\n\r\n return s3_public_url","def upload_to_s3(bucket, file_path, prefix, timestamp):\n upload_name = f'{prefix}_{timestamp or \"\"}{basename(file_path)}'\n\n try:\n bucket.upload_file(file_path, upload_name)\n syslog.syslog(syslog.LOG_INFO,\n f'Uploaded {file_path} to S3 Bucket - {bucket.name}')\n return True\n except S3UploadFailedError as s3ex:\n syslog.syslog(\n syslog.LOG_ERR, f'Failed to upload {file_path} to S3 Bucket - {bucket_name} - {s3ex}')\n return False\n finally:\n rm(file_path)","def _upload_to_bucket(self, filename, ext_filename):\n if ext_filename is None:\n return\n\n if self.s3:\n self.bucket.upload_file(filename, ext_filename)\n logging.info('Uploaded {} to S3 with name {}'.format(filename, ext_filename))\n if self.gs:\n try:\n client = storage.Client()\n bucket = client.get_bucket(self.bucket_name)\n blob = storage.Blob(ext_filename, bucket)\n blob.upload_from_filename(filename)\n logging.info('Uploaded to {}'.format(ext_filename))\n except:\n logging.warning('Uploading file to bucket failed')","def upload_file_to_bucket(s3_client, file_obj, bucket, folder, object_name=None):\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_obj\n\n # Upload the file\n try:\n response = s3_client.upload_fileobj(file_obj, bucket, f\"{folder}/{object_name}\")\n print(response)\n except ClientError:\n return False\n return True","def upload_to_aws(local_file, bucket, s3_file, access_key, secret_key):\n s3 = boto3.client('s3', aws_access_key_id=access_key,\n aws_secret_access_key=secret_key)\n \n try:\n s3.upload_file(local_file, bucket, s3_file)\n print(f'Upload of {local_file} to {bucket} as {s3_file} successful.')\n return True\n except FileNotFoundError:\n print(f'File {local_file} not found.')\n return False\n except NoCredentialsError:\n print('Credentials invalid or not available.')\n return False","def upload_file_to_s3(bucket_name, input_filepath, output_filename):\n s3 = boto3.client(\"s3\")\n with open(input_filepath, \"rb\") as f:\n s3.upload_fileobj(f, bucket_name, output_filename)","def _put(conn, remote_file, contents, bucket_name=BUCKET_NAME, headers=None):\n error_msg = 'Failed to upload to %s' % remote_file\n try:\n reply = conn.put(bucket_name, remote_file,\n S3.S3Object(contents), headers)\n if reply.http_response.status != 200:\n print error_msg\n except:\n print error_msg","def upload_file(file, bucket_path, bucket=S3_BUCKET):\n # Bucket path should be somedir/name_of_file.ext\n try:\n if isinstance(file, str):\n resource.upload_file(file, bucket, bucket_path)\n else:\n resource.upload_fileobj(file, bucket, bucket_path)\n except:\n raise ChildProcessError('Something broke, Cap\\'n')","def pushToS3()-> None:\n logging.info(f\"Connecting to s3 {getTime()}\")\n s3 = boto3.client(\"s3\",endpoint_url=\"http://localhost:4566\")\n if(not s3.head_bucket(Bucket=\"demo\")):\n s3.create_bucket(Bucket='demo')\n try:\n logging.info(f\"Uploading to s3 {getTime()}\")\n s3.upload_file(\"result.csv\",\"demo\",\"result.csv\")\n logging.info(f\"Finished uploding to s3 {getTime()}\")\n except ClientError as e:\n logging.error(f\"Error uploading file to S3 {getTime()}\")","def upload_to_s3(file_contents: bytes, path: str, content_type: str = None, tags: dict = None):\n client = S3BucketClient()\n client.upload(\n file_contents=file_contents,\n path=path,\n content_type=content_type,\n tags=tags,\n )","def store_to_s3():\n\n try:\n # establish aws/s3 connection\n s3 = boto3.client('s3',\n aws_access_key_id=ACCESS_KEY,\n aws_secret_access_key=SECRET_KEY\n )\n logger.info(\"S3 connection established!\")\n except Exception as e:\n logger.error('Fail to connect to aws s3. Please check your credentials!')\n logger.error(e)\n else:\n try:\n # upload local file to S3 bucket\n logger.info(\"Uploading {} to {} bucket as {}\".format(config.Local_File_To_Upload,\n config.Bucket_Name,\n config.S3_Filename))\n s3.upload_file(config.Local_File_To_Upload,\n config.Bucket_Name,\n config.S3_Filename)\n logger.info('File successfully uploaded to S3 bucket!')\n except FileNotFoundError:\n logger.error('File not found, pleas check the file path.')\n except Exception as e:\n logger.error(e)","def upload_file(self, keyUrl='', body='', ContentType='', bucket=None):\n \n if bucket is None:\n bucket = self.AWS_S3_BUCKET\n \n #Verificamos si existe body\n if body is None:\n body=''\n \n try:\n self.get_s3_client().put_object(Bucket=bucket, Key=keyUrl, Body=body, ACL='public-read', ContentType=ContentType)\n return True\n \n except ClientError as e:\n return False","def _upload_to_s3(s3_uploader, relative_path, file_path, filename):\n try:\n key = os.path.join(s3_uploader[\"key_prefix\"], relative_path, filename)\n s3_uploader[\"transfer\"].upload_file(file_path, s3_uploader[\"bucket\"], key)\n except FileNotFoundError: # noqa ignore=F821\n # Broken link or deleted\n pass\n except Exception: # pylint: disable=broad-except\n logger.exception(\"Failed to upload file to s3.\")\n finally:\n # delete the original file\n if os.path.exists(file_path):\n os.remove(file_path)","def upload_to_bucket(bucket_name, path_to_source_file, upload_file_name):\r\n\r\n try:\r\n # initialize client & get blob\r\n _, _, blob = create_client(bucket_name, upload_file_name)\r\n\r\n # set the path to source file\r\n blob.upload_from_filename(path_to_source_file)\r\n \r\n except Exception as err:\r\n raise err\r\n sys.exit(1)\r\n \r\n else:\r\n print(f\"upload file '{path_to_source_file}' succeed\")\r\n\r\n return None","def upload_file(file_name, bucket, object_name=None):\n\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = file_name\n\n # Upload the file\n s3_client = boto3.client('s3')\n try:\n response = s3_client.upload_file(file_name, bucket, 'keypoints_descriptor/'+file_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def upload_file_to_bucket(self, bucket_id, filename):\n url = self.upload_endpoint + \"/\" + bucket_id + \"/files\"\n\n headers = {\"Authorization\": \"Bearer \" + self.bearer_token}\n\n files = {\"file\": open(filename, \"rb\")}\n\n r = requests.post(url, headers=headers, files=files)\n\n if r.status_code == 200:\n logging.info(\"Successfully uploaded file to the bucket\")\n else:\n logging.warning(\"HTTP Error {}\".format(r.status_code))","def test_upload_file_to_s3_bucket(self):\n conn = boto3.resource('s3', region_name='us-east-1')\n # We need to create the bucket since this is all in Moto's 'virtual' AWS account\n conn.create_bucket(Bucket='foobucket')\n\n s3_connector = S3Connector()\n s3_connector.connect(\"default\")\n s3_connector.upload_file(\n file_path=\"test/test_resources/test_file\", file_name=\"foofile\", bucket_name=\"foobucket\")\n\n # get bucket contents\n response = boto3.client('s3').list_objects(Bucket=\"foobucket\")\n contents = []\n for content in response.get('Contents', []):\n contents.append(content.get('Key'))\n\n self.assertEqual(contents, [\"foofile\"])","def upload(self, path, key, extra_args={}):\n if key.endswith(\"/\"):\n key += os.path.basename(path)\n if key.startswith(\"/\"):\n key = key[1:]\n remote_path = self.base.full_cell + \"/\" + key\n self.s3.meta.client.upload_file(path, self.bucket, remote_path, ExtraArgs=extra_args)\n print \"UPLOADED {} to s3://{}/{}\".format(path, self.bucket, remote_path)","def upload_file(Filename=None, Bucket=None, Key=None, ExtraArgs=None, Callback=None, Config=None):\n pass","def upload_from_path_to_s3(file_path):\n bucket_name = \"alp-reports-lambda\"\n environment = \"dev\" if os.environ.get('LOCAL') else \"prod\"\n object_key = f\"{environment}/835/{file_path.split('/')[-1]}\"\n\n s3 = boto3.resource('s3')\n s3.Object(bucket_name, object_key).upload_file(file_path, ExtraArgs={'ACL': 'public-read'})\n\n return f\"https://s3.amazonaws.com/{bucket_name}/{object_key}\"","def upload(self, bucket_name, key_name, fname):\n bucket = self.s3_.get_bucket(bucket_name)\n key = boto.s3.key.Key(bucket)\n with open(fname, 'rb') as infile:\n key.key = key_name\n return key.set_contents_from_file(infile)","def upload(self, bucket, obj, s3_client=None):\n\n s3_client = s3_client or self.s3_client\n transfer_config = boto3.s3.transfer.TransferConfig(multipart_threshold=1024, use_threads=True, max_concurrency=10)\n s3_transfer = boto3.s3.transfer.S3Transfer(client=s3_client, config=transfer_config)\n\n try:\n logging.debug(\"Uploading {} to {}\".format(obj, bucket))\n s3_transfer.upload_file(obj, bucket, helpers.strip_path(obj)[1])\n\n return True\n except botocore.exceptions.EndpointConnectionError:\n logging.error(\"Couldn't connect to an S3 endpoint. If you're using an S3 compatible provider other than AWS, remember to set --s3-endpoint-url\")\n return False\n except Exception as e:\n logging.error(\"Error uploading: {}\".format(e))\n return False","def upload_blob(self, bucket_name, file_name, contents):\n\n bucket = self.storage_client.bucket(bucket_name)\n blob = bucket.blob(file_name)\n blob.upload_from_string(contents)\n print(\n \"File {} uploaded to bucket {} as file {}.\".format(\n file_name, bucket_name, file_name\n )\n )","def upload_file(conn, filename_local, filename_s3, gzip=False):\n\n filename_s3 = filename_s3.lstrip('./')\n\n file_descriptor = open(filename_local, 'rb')\n content = file_descriptor.read()\n\n content_type = _get_content_type(file_descriptor)\n headers = _get_headers(content_type)\n\n #should compress if the file is compressable and gzip is enabled\n can_be_gzipped = _file_can_be_compressed(filename_local)\n if gzip and can_be_gzipped:\n content = _compress_string(content)\n headers['Content-Length'] = str(len(content))\n headers['Content-Encoding'] = 'gzip'\n extension = mimetypes.guess_extension(content_type)\n #we should not overwrite the original file in the server.\n #We change extensions: style.css --> style.gz.css, for instance\n filename_s3 = filename_s3.rstrip(extension) + '.gz' + extension\n\n #if gzip is enabled and it is not compressable, don't upload nothing at all\n elif gzip and not can_be_gzipped:\n return\n\n #upload\n print 'Uploading %s to %s' % (filename_local, filename_s3)\n _put(conn, filename_s3, content, headers=headers)\n file_descriptor.close()","async def put_file(object_name: str, file: File, **kwargs) -> str:\n # TODO: Do not read file but rather stream content as it comes\n await file.read()\n # Get the synchronous file interface from the asynchronous file\n file_obj = file.file\n # Store position of cursor (number of bytes read)\n file_size = file_obj.tell()\n # Reset cursor at start of file\n file_obj.seek(0)\n # Trace file upload with its size\n logger.debug(f\"Uploading file: {object_name} with {file_size} bytes\")\n # Time file upload for debug\n start = time.time()\n # Store object on s3 storage\n client.put_object(\n bucket_name=DATASETS_BUCKET,\n object_name=object_name,\n length=file_size,\n data=file_obj,\n )\n end = time.time()\n # Log time spent\n logger.debug(f\"Took {end - start} seconds to upload {file_size} bytes\")","def _cloud_storage_upload(local_file, bucket, filename_on_bucket):\n client = storage.Client()\n\n bucket = client.get_bucket(bucket)\n blob = bucket.blob(filename_on_bucket)\n blob.upload_from_filename(local_file)\n print('uploaded ', bucket, filename_on_bucket)","def upload_to_s3(self, file: str, force_upload: bool = False) -> str:\n if self.aws_access_key_id is None:\n raise Exception(\n 'To use `upload_to_s3` you need to pass '\n '`aws_access_key_id` and '\n '`aws_secret_access_key`'\n )\n\n filename = file.split('/')[-1]\n\n s3 = boto3.client(\n 's3',\n aws_access_key_id=self.aws_access_key_id,\n aws_secret_access_key=self.aws_secret_access_key\n )\n # Check if exists\n if not force_upload:\n try:\n session = boto3.Session(\n aws_access_key_id=self.aws_access_key_id,\n aws_secret_access_key=self.aws_secret_access_key\n )\n\n session.resource('s3').Object(self.bucket_name, filename).load()\n except botocore.exceptions.ClientError as e:\n if e.response['Error']['Code'] != \"404\":\n raise e\n else:\n # The object does exist\n return filename\n\n # Progress bar\n size = os.stat(file).st_size\n progress_bar = self._progress(size)\n\n # Uploading file\n s3.upload_file(file, self.bucket_name, filename, Callback=progress_bar)\n\n return filename","def put_upload(self):\n # print \"starting upload...\", self.current_upload['filepath']\n self.touch()\n self.log(\"STARTING_UPLOAD\", level=INFO)\n try:\n Backend.put_file(self.fileobj, self.current_upload[\"gcs_url\"])\n except exceptions.FilePutError as err:\n self.handle_put_error(err, self.fileobj)\n raise","def upload(filename, bucket):\n k = Key(bucket)\n k.key = uuid.uuid1().hex\n print \"Uploading batch to {}, key: {}...\".format(bucket.name, k.key)\n k.set_contents_from_filename(filename, reduced_redundancy=True)\n print \" Done.\"\n \n\n\n bucket = openBucket(dest)","def _upload_to_s3(filename):\n if not app.config.get('UPLOAD_SCREENSHOTS_TO_S3', False):\n return\n\n import boto\n from boto.s3.key import Key\n conn = boto.connect_s3()\n b = conn.get_bucket(app.config['S3_BUCKET'])\n k = Key(b)\n k.key = '{}/{}'.format(\n app.config.get('S3_FILES_PREFIX', 'sleepypuppy'),\n filename\n )\n k.set_contents_from_filename(\n \"{}/{}\".format(\n app.config['UPLOAD_FOLDER'],\n filename\n )\n )\n os.remove(\n \"{}/{}\".format(\n app.config['UPLOAD_FOLDER'],\n filename\n )\n )","def upload(self, bucket, object, filename, mime_type='application/octet-stream'):\n service = self.get_conn()\n media = MediaFileUpload(filename, mime_type)\n response = service \\\n .objects() \\\n .insert(bucket=bucket, name=object, media_body=media) \\\n .execute()","def upload_object(self, file_path, destination, use_original_name=True, ExtraArgs=None):\n assert os.path.exists(file_path), \"File path does not exist {}\".format(file_path)\n bucket_name, save_path = self.split_name(destination)\n if use_original_name:\n save_path = os.path.join(save_path, os.path.basename(file_path))\n\n self.s3_client.upload_file(file_path, bucket_name, save_path, ExtraArgs=ExtraArgs)\n return os.path.join(bucket_name, save_path)","def upload_file_to_s3(bucket, artefact, bucket_key):\n try:\n client = boto3.client('s3')\n\n except ClientError as err:\n print(\"Failed to create boto3 client.\\n\" + str(err))\n return False\n\n try:\n kwargs = {\n \"Body\": open(artefact, 'rb'),\n \"Bucket\": bucket,\n \"Key\": bucket_key\n }\n\n mime_type, encoding = mimetypes.guess_type(artefact)\n\n if mime_type is None:\n file_name, file_ext = os.path.splitext(artefact)\n\n if file_ext == \".icon\" :\n kwargs[\"ContentType\"] = \"image/vnd.microsoft.icon\"\n\n elif file_ext == \".woff2\" :\n kwargs[\"ContentType\"] = \"application/font-woff\"\n \n else:\n kwargs[\"ContentType\"] = mime_type\n\n client.put_object(**kwargs)\n\n except ClientError as err:\n print(\"Failed to upload artefact to S3.\\n\" + str(err))\n return False\n\n except IOError as err:\n print(\"Failed to access artefact in this directory.\\n\" + str(err))\n return False\n\n return True","def upload(bucket_name, source_file, destination_blob_name):\n storage_client = storage.Client()\n bucket = storage_client.get_bucket(bucket_name)\n blob = bucket.blob(destination_blob_name)\n\n try:\n blob.upload_from_file(source_file)\n except:\n return None\n else:\n return('File {} uploaded to {}.'.format(\n source_file,\n destination_blob_name))","def upload_package(self, filename=None):\n logger.info(\"Uploading the package to S3\")\n s3f = S3FunctionUploader(self.function_config['Code']['S3Bucket'])\n self.s3_filename = path.join(\n self.function_config['Code']['S3KeyPath'],\n path.basename(filename or self.local_filename)\n )\n s3f.upload(filename or self.local_filename,\n self.s3_filename)","def put(self, path: str, filename: str) -> None:\n\n payload_hash, content_md5, length = _hash(path)\n\n now = datetime.datetime.utcnow()\n timestamp = now.strftime('%Y%m%dT%H%M%SZ')\n headers = [\n ('Connection', 'keep-alive'),\n ('Content-Length', str(length)),\n ('Content-MD5', content_md5),\n ('Content-Type', 'application/zip'),\n ('Date', now.strftime('%a, %d %b %Y %H:%M:%S GMT')),\n ('Host', '%s.s3.amazonaws.com' % self.bucket),\n ('x-amz-content-sha256', payload_hash),\n ('x-amz-date', timestamp),\n ]\n signed_headers = ';'.join(header[0].lower() for header in headers)\n canonical_request = 'PUT\\n%s\\n\\n%s\\n\\n%s\\n%s' % (filename, '\\n'.join(\n ('%s:%s' % (header[0].lower(), header[1])\n for header in headers)), signed_headers, payload_hash)\n logging.debug('canonical request %r',\n canonical_request.encode('utf-8'))\n string_to_sign = 'AWS4-HMAC-SHA256\\n%s\\n%s\\n%s' % (\n timestamp, self.scope,\n hashlib.sha256(canonical_request.encode('utf-8')).hexdigest())\n logging.debug('string to sign %r', string_to_sign.encode('utf-8'))\n\n signature = hmac.new(self.signing_key,\n string_to_sign.encode('utf-8'),\n digestmod='sha256').hexdigest()\n headers.append((\n 'Authorization',\n 'AWS4-HMAC-SHA256 Credential=%s/%s,SignedHeaders=%s,Signature=%s' %\n (self.aws_access_key, self.scope, signed_headers, signature)))\n with open(path, 'rb') as file_stream:\n if not self.conn:\n self.conn = http.client.HTTPSConnection('%s.s3.amazonaws.com' %\n self.bucket)\n try:\n self.conn.request('PUT',\n filename,\n file_stream,\n headers=dict(headers))\n res = self.conn.getresponse()\n payload = res.read()\n except (http.client.BadStatusLine, http.client.ResponseNotReady,\n http.client.CannotSendRequest):\n self.conn.close()\n raise\n if res.status != 200:\n raise Exception(payload.decode('utf-8'))","def test_put_file(self):\n self.prepare_uploads()\n backend = BackendS3(**self.config)\n uploads = self.upload_path\n src = os.path.join(uploads, 'demo-test.tar.gz')\n id = utils.generate_id('demo-test.tar.gz')\n backend.put(src, id)\n path = '/'.join(backend.id_to_path(id)) + '/demo-test.tar.gz'\n self.assertTrue(backend.exists(path))","def put_object(self, bucket, key, local_file_path=None, file_bytes=None) -> None:\n def upload_to_s3(byte_array):\n self.resource.Object(bucket, key).put(Body=byte_array)\n\n if file_bytes:\n upload_to_s3(file_bytes)\n else:\n with open(local_file_path, 'rb') as local_file:\n self.resource.Object(bucket, key).put(Body=local_file)","def upload_from_file(self, file_obj, name_on_storage, **keyword_args):\n blob = self.bucket.blob(name_on_storage)\n blob.upload_from_file(file_obj, **keyword_args)\n print(f\"Upload object {name_on_storage}\")","def put_file(self, file_name: str, value: BytesIO):\n value.seek(0)\n self.client.upload_fileobj(value, self.bucket, file_name)","def s3(ctx, bucket_name, data_file, region):\n ctx.obj['BUCKET_NAME'] = bucket_name\n ctx.obj['DATA_FILE'] = data_file\n ctx.obj['TYPE'] = 's3'\n ctx.obj['REGION'] = region","def put_data_in_s3(data, filename):\n s3_client.put_object(Body=data, Bucket=CLIMATE_DATA_BUCKET, Key=filename)","def put(self, file_path, key=None):\n try:\n key_name = key if key else os.path.basename(file_path)\n size = os.stat(file_path).st_size\n if size < 104857600: #100 mb\n k = Key(self.bucket)\n k.key = key_name\n sent = k.set_contents_from_filename(file_path)\n log.info('Uploading %s to S3 (%s)' % (key_name, self.bucket_name))\n return sent == size\n else:\n log.info('Multipart Uploading %s to S3 (%s)' % (key_name, self.bucket_name))\n mp = self.bucket.initiate_multipart_upload(key_name)\n chunk_size = 52428800\n chunk_count = int(math.ceil(size / float(chunk_size)))\n #Send the file parts, using FileChunkIO to create a file-like object\n # that points to a certain byte range within the original file. We\n # set bytes to never exceed the original file size.\n for i in range(chunk_count):\n offset = chunk_size * i\n bytes = min(chunk_size, size - offset)\n with FileChunkIO(file_path, 'r', offset=offset, bytes=bytes) as fp:\n mp.upload_part_from_file(fp, part_num=i + 1)\n # Finish the upload\n mp.complete_upload()\n return True\n except Exception, e:\n log.error('Failed to upload to S3 (%s)' % (self.bucket_name), exc_info=True)\n return False","def aws_s3_upload(self):\n\n # absolute path to the csv file to create\n csv_file = os.path.join(self.csvfile, \"DLTINS_20210117_01of01.csv\")\n\n # Test for correct data\n self.assertTrue(\n aws_s3_upload(\n csv_file,\n self.region_name,\n self.aws_access_key_id,\n self.aws_secret_access_key,\n self.bucket_name,\n )\n )\n\n # Test for non existent bucket\n self.assertFalse(\n aws_s3_upload(\n csv_file,\n \"useast\",\n self.aws_access_key_id,\n self.aws_secret_access_key,\n self.bucket_name,\n )\n )\n\n # Test for non existent region\n self.assertFalse(\n aws_s3_upload(\n csv_file,\n self.region_name,\n self.aws_access_key_id,\n self.aws_secret_access_key,\n \"nonexistentbucketname\",\n )\n )\n\n # Test for incorrect keys\n self.assertFalse(\n aws_s3_upload(\n csv_file,\n self.region_name,\n \"xjvachiahvlchabo;jvbo\",\n \"khkc vah haaih aih ika\",\n self.bucket_name,\n )\n )","def upload(self, filename, file_path):\n return","def upload_blob(bucket_name, source_file_name, destination_blob_name):\n # bucket_name = \"your-bucket-name\"\n # source_file_name = \"local/path/to/file\"\n # destination_blob_name = \"storage-object-name\"\n\n storage_client = storage.Client()\n bucket = storage_client.bucket(bucket_name)\n blob = bucket.blob(destination_blob_name)\n\n blob.upload_from_filename(source_file_name)\n print(\"File {} uploaded to {}.\".format(\n source_file_name, destination_blob_name\n )\n )","def upload_file_by_url(s3_file_name, filename):\n full_path = os.path.join(CONFIG_BROKER['path'], \"tests\", \"integration\", \"data\", filename)\n\n if CONFIG_BROKER['local']:\n # If not using AWS, put file submission in location\n # specified by the config file\n broker_file_path = CONFIG_BROKER['broker_files']\n copy(full_path, broker_file_path)\n submitted_file = os.path.join(broker_file_path, filename)\n return {'bytesWritten': os.path.getsize(submitted_file), 's3FileName': full_path}\n else:\n # Use boto to put files on S3\n s3conn = boto.s3.connect_to_region(CONFIG_BROKER[\"aws_region\"])\n bucket_name = CONFIG_BROKER['aws_bucket']\n key = Key(s3conn.get_bucket(bucket_name))\n key.key = s3_file_name\n bytes_written = key.set_contents_from_filename(full_path)\n return {'bytesWritten': bytes_written, 's3FileName': s3_file_name}","def upload_files_s3(files, bucket):\n \n print('************************************')\n print('Uploading files to s3 bucket...')\n print('************************************')\n \n for i in range(len(files)):\n upload_file_s3(files[i], bucket)\n \n print('************************************')\n print('Upload complete')\n print('************************************')","def upload_blob(bucket_name, source_file_name, destination_blob_name):\n storage_client = storage.Client()\n bucket = storage_client.get_bucket(bucket_name)\n blob = bucket.blob(destination_blob_name)\n\n blob.upload_from_filename(source_file_name)\n\n print('File {} uploaded to {}.'.format(\n source_file_name,\n destination_blob_name))","def upload_file(cls, uri, fobj):\n # Breaks the URI into usable componenents.\n values = get_values_from_media_uri(uri)\n logger.debug(\"S3Backend.upload_file(): Received: %s\" % values)\n\n conn = cls._get_aws_s3_connection(values['username'],\n values['password'])\n bucket = conn.create_bucket(values['host'])\n key = bucket.new_key(values['path'])\n\n logger.debug(\"S3Backend.upload_file(): \"\\\n \"Settings contents of '%s' key from %s\" % (\n values['path'], fobj.name))\n key.set_contents_from_filename(fobj.name)\n\n logger.debug(\"S3Backend.upload_file(): Upload complete.\")\n return key","def upload_chain(s3_path, local_path, bucket_name='lwr-inverse-us-east'):\n s3 = boto3.resource(\"s3\")\n lwr_AIES = s3.Bucket(bucket_name)\n file_content = open(local_path, 'rb')\n lwr_AIES.put_object(Key=s3_path, Body=file_content)","def upload_blob(bucket_name, source_file_name, destination_blob_name):\n\n storage_client = storage.Client()\n bucket = storage_client.get_bucket(bucket_name)\n blob = bucket.blob(destination_blob_name)\n\n blob.upload_from_filename(source_file_name)\n\n print('File {} uploaded to {}.'.format(\n source_file_name,\n destination_blob_name))","def upload_blob(bucket_name, source_file_name, destination_blob_name):\n\n storage_client = storage.Client()\n bucket = storage_client.bucket(bucket_name)\n blob = bucket.blob(destination_blob_name)\n\n blob.upload_from_filename(source_file_name)\n\n print(\n \"File {} uploaded to {}.\".format(\n source_file_name, destination_blob_name\n )\n )","def save_image_to_s3(filename, file):\n \n s3_path = f\"s3://shopifyimagerepository/{filename}\"\n \n s3_client.put_object(Body=file,\n Bucket=\"shopifyimagerepository\",\n Key=filename,\n ACL=\"public-read\")","def upload_blob(bucket_name, source_file_name, destination_blob_name):\n # bucket_name = \"your-bucket-name\"\n # source_file_name = \"local/path/to/file\"\n # destination_blob_name = \"storage-object-name\"\n\n storage_client = storage.Client()\n bucket = storage_client.bucket(bucket_name)\n blob = bucket.blob(destination_blob_name)\n\n blob.upload_from_filename(source_file_name)\n\n print(\n \"File {} uploaded to {}.\".format(\n source_file_name, destination_blob_name\n )\n )","def upload_file(bucket, local_file_path, remote_destination_path):\n bucket = get_bucket(bucket)\n k = Key(bucket)\n k.key = remote_destination_path\n k.set_contents_from_filename(local_file_path)","def upload_blob(bucket_name, source_file_name, destination_blob_name):\n storage_client = storage.Client()\n bucket = storage_client.get_bucket(bucket_name)\n blob = bucket.blob(destination_blob_name)\n\n blob.upload_from_filename(source_file_name)\n\n print('File {} uploaded to {}.'.format(\n Crabbie.queue_file,\n destination_blob_name))","def upload_file(self, bucket_name, object_name, filepath, metadata=None):\n try:\n _metadata = {}\n if metadata is not None:\n for key in metadata.keys():\n _metadata[self.__metadata_prefix + key] = metadata[key]\n self.client.fput_object(\n bucket_name, object_name, filepath, metadata=_metadata\n )\n except ResponseError as _err:\n logging.exception(\"Could not upload file\")\n return False\n return True","def upload_file_to_s3(local_path: Path, s3_path: Path, overwrite: bool = False) -> None:\n import warnings\n\n warnings.filterwarnings(\n action=\"ignore\", message=\"unclosed\", category=ResourceWarning\n )\n\n s3_args, unknown = get_s3_args().parse_known_args()\n s3_client = get_s3_client(s3_args)\n log = get_logger(\"upload_file_to_s3\")\n\n try:\n # only write files to s3 that don't already exist unless overwrite is passed\n if s3_object_exists(s3_path) and not overwrite:\n log.debug(\n f\"s3://{s3_args.s3_bucket}/{s3_path} already exists in s3, not overwriting\"\n )\n return\n\n s3_client.put_object(\n Body=local_path.read_bytes(), Bucket=s3_args.s3_bucket, Key=str(s3_path)\n )\n log.debug(f\"uploaded s3://{s3_args.s3_bucket}/{s3_path}\")\n\n except s3_client.exceptions.ClientError as exc:\n # catch and raise any errors generated while attempting to communicate with s3\n s3_client_attributes = {\n attr: getattr(s3_client, attr) for attr in s3_client.__dict__.keys()\n }\n s3_client_attributes.update(\n {\"bucket\": s3_args.s3_bucket, \"object_path\": s3_path,}\n )\n raise S3Error(f\"{s3_client_attributes} S3 ClientError\") from exc","def upload_to_s3(site, bucket, directory=None, files=None, prefix=None):\n if bucket is None:\n print red('Error: Bucket must be specified.')\n return\n if directory is None and files is None:\n print red('Error: Directory and/or files must be specified.')\n return\n # Setup boto\n import boto\n from boto.s3.bucket import Bucket\n from boto.s3.key import Key\n import mimetypes\n import fnmatch\n\n setup_aws_access_key(site)\n\n # Connect to S3\n c = boto.connect_s3()\n b = Bucket(c, bucket)\n\n # Fix the prefix\n # prefix itself shouldn't have a / prefix itself but should end with /\n if prefix:\n prefix = prefix.lstrip('/')\n if prefix and not prefix.endswith('/'):\n prefix = prefix + '/'\n\n def __upload(key, filename):\n k = Key(b)\n k.key = key\n headers = {}\n content_type = mimetypes.guess_type(filename)[0]\n if site.has_key('webapp') and site['webapp'].get('cache_control'):\n for pattern in site['webapp']['cache_control']:\n if fnmatch.fnmatch(filename, pattern):\n headers['Cache-Control'] = site['webapp']['cache_control'][pattern]\n break\n if site.has_key('webapp') and site['webapp'].get('gzip_types') and content_type in site['webapp']['gzip_types']:\n from gzip import GzipFile\n from StringIO import StringIO\n # Need to specify content_type when uploading from a string!\n headers['Content-Type'] = content_type\n headers['Content-Encoding'] = 'gzip'\n s = StringIO()\n g = GzipFile(fileobj=s, mode='wb')\n with open(filename, 'rb') as f:\n g.write(f.read())\n g.close()\n k.set_contents_from_string(s.getvalue(), headers)\n else:\n k.set_contents_from_filename(filename, headers)\n\n if files:\n # Upload individual files\n if directory:\n keys = [filename.lstrip('/') for filename in files]\n files = [os.path.join(directory, filename) for filename in files]\n else:\n keys = [os.path.split(filename)[1] for filename in files]\n for i, filename in enumerate(files):\n print 'Uploading %s' % keys[i]\n if prefix:\n key = prefix + keys[i]\n else:\n key = keys[i]\n __upload(key, filename)\n elif directory:\n # Upload an entire directory\n def __upload_dir(arg, dirname, names):\n # arg is the starting directory\n for name in names:\n filename = os.path.join(dirname, name)\n if not os.path.isdir(filename) and not os.path.islink(filename) and not name.startswith('.'):\n key = filename[len(arg):]\n if key.startswith('/'):\n key = key[1:]\n if prefix:\n key = prefix + key\n print 'Uploading %s' % key\n __upload(key, filename)\n os.path.walk(directory, __upload_dir, directory)","def upload(iid, file_obj, content_type):\n if AWS_CLIENT_CONFIG and BUCKET_NAME:\n try:\n s3 = boto3.resource('s3', **AWS_CLIENT_CONFIG)\n s3.Bucket(BUCKET_NAME).put_object(Key=iid,\n Body=file_obj,\n ContentType=content_type)\n return StorageType.S3\n except botocore.exceptions.ClientError as e:\n logger.error(e)\n else:\n # store locally in temp dir (tests, local development)\n store_temp_file(iid, file_obj)\n return StorageType.TMP\n return None","def upload(self, path, data, headers={}):\n\n client = AsyncHTTPClient()\n method = 'PUT'\n url = self.generate_url(path)\n url_object = urlparse(url)\n params = {\n 'SignatureMethod': 'AWS4-HMAC-SHA256'\n }\n\n headers.update({\n 'Content-Length': str(len(data)),\n 'Content-Type': self._guess_mimetype(path),\n 'Date': self._rfc822_datetime(),\n 'Host': url_object.hostname,\n 'X-Amz-Content-sha256': hashlib.sha256(data).hexdigest(),\n })\n\n try:\n response = yield client.fetch(\n self.sign_request(\n url_object.hostname,\n url_object.path,\n params,\n headers,\n method,\n data\n ),\n method=method,\n body=data,\n connect_timeout=AWS_S3_CONNECT_TIMEOUT,\n request_timeout=AWS_S3_REQUEST_TIMEOUT,\n headers=headers\n )\n except HTTPError as error:\n log.error(error)\n if error.response:\n log.error(error.response.body)\n raise Return(None)\n\n raise Return(response)","def upload_file(self, key, filepath, access, keep_original=True,\n verbose=False):\n\n # file entry\n try:\n file_entry = self.bucket.new_key(key)\n file_entry.set_metadata('filepath', filepath)\n file_entry.set_contents_from_filename(filepath)\n file_entry.set_acl(access) # access control\n except Exception as error:\n print str(error)\n return False\n else:\n if verbose:\n print \"{} uploaded to amazon s3.\".format(key)\n\n # original file removal\n if not keep_original and os.access(filepath, os.W_OK):\n try:\n os.remove(filepath)\n except (IOError, OSError):\n print \"I/O error, could not remove file.\"\n else:\n if verbose:\n print \"{} (original) removed\".format(filepath)\n\n return True","def upload_to_s3(bucket_name, sourceDir):\n try:\n client = boto3.client('s3')\n resource = boto3.resource('s3')\n except ClientError as err:\n print(\"Failed to create boto3 client.\\n\" + str(err))\n return False\n try:\n # clean the bucket\n bucket = resource.Bucket(bucket_name)\n for key in bucket.objects.all():\n key.delete()\n\n # upload the new files\n uploadFileNames = getFiles(sourceDir)\n print(\"Found \" + len(uploadFileNames).__str__() + ' files')\n\n for filename in uploadFileNames:\n destName = os.path.join(*(filename.split('/')[1:]))\n print(\"Uploading file \" + filename + ' to ' + destName)\n resource.Object(bucket_name, destName).put(Body=open(filename, 'rb'),\n ContentType=get_contenttype_from_filename(filename))\n\n except ClientError as err:\n print(\"Failed to upload artefact to S3.\\n\" + str(err))\n return False\n except IOError as err:\n print(\"Failed to access artefact in this directory.\\n\" + str(err))\n return False\n\n return True","def upload_file(self, bucket_name, object_name, filepath, metadata=None):\n try:\n _metadata = {}\n if metadata is not None:\n for key in metadata.keys():\n _metadata[self.__metadata_prefix+key] = metadata[key]\n self.client.fput_object(bucket_name, object_name, filepath,\n metadata=_metadata)\n except ResponseError as _err:\n logging.exception(\"Could not upload file\")\n return False\n return True","def upload_fileobj(Fileobj=None, Bucket=None, Key=None, ExtraArgs=None, Callback=None, Config=None):\n pass"],"string":"[\n \"def upload_object(self, file_path, s3_path):\\n logging.info(\\\"Uploading file to \\\\\\\"{}\\\\\\\" to S3\\\".format(s3_path))\\n bucket_name, key = S3Util.get_bucket_and_key(s3_path)\\n self.s3_resource.Bucket(bucket_name).upload_file(file_path, key)\",\n \"def _upload_s3(self, filename, bucket, objectKey):\\n return s3_client.upload_file(filename, bucket, objectKey)\",\n \"def upload_file(file_name, bucket):\\r\\n object_name = file_name\\r\\n s3_client = boto3.client('s3')\\r\\n response = s3_client.upload_file(file_name, bucket, object_name)\\r\\n\\r\\n return response\",\n \"def upload_s3_file(key, bucket, filename):\\n s3_client = boto3.client('s3')\\n s3_client.upload_file(filename, bucket, key)\\n return True\",\n \"def upload(self, file_path, bucket_name, file_name):\\n\\n self.client.upload_file(file_path, bucket_name, file_name)\",\n \"def upload(\\n bucket: str, key: str, filename: str, session: Optional[boto3.Session] = None\\n) -> None:\\n s3_client = _get_client(session)\\n LOGGER.info(\\\"uploading %s to s3://%s/%s...\\\", filename, bucket, key)\\n s3_client.upload_file(Filename=filename, Bucket=bucket, Key=key)\",\n \"def upload_file_s3(file_name, bucket):\\n\\n # If S3 object_name was not specified, use file_name \\n try:\\n response = s3_client.upload_file(file_name,\\n bucket, \\n file_name.replace('../',''))\\n print(\\\"Uploaded \\\" + file_name)\\n except ClientError as e:\\n print(\\\"Failed to upload \\\" + file_name)\\n logging.error(e)\\n return False\\n return True\",\n \"def upload(filename, bucket):\\n print(\\\"Uploading {} to S3\\\".format(filename.lower().replace('_', '-')))\\n url = \\\"https://s3.ca-central-1.amazonaws.com/{}/{}\\\".format(bucket,\\n filename.lower().replace('_', '-'))\\n with open('{}/{}'.format(WORK_DIR, filename), 'rb') as data:\\n requests.put(url, data=data)\",\n \"def upload_file(self, file_name, bucket, object_name=None):\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name\\n\\n # Upload the file\\n s3_client = boto3.client('s3', aws_access_key_id=self.aws_access_key_id, aws_secret_access_key=self.aws_secret_access_key)\\n try:\\n s3_client.upload_file(file_name, bucket, object_name)\\n except ClientError as e:\\n logging.exception(e)\\n return False\\n logging.info(\\\"Upload to S3 bucket complete!\\\")\\n\\n return True\",\n \"def upload_to_s3(file_name, bucket, key): \\n s3 = boto3.resource('s3') \\n try:\\n s3.meta.client.upload_file(file_name, bucket, key)\\n print(\\\"s3 upload success -- uploaded \\\" + file_name + \\\" to the bucket: \\\" + bucket)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n print(\\\"s3 upload error occurs\\\", e)\\n return True\",\n \"def upload_to_s3(file_from_machine, bucket, file_to_s3):\\n s3.upload_file(file_from_machine, bucket, file_to_s3)\\n print(file_to_s3, \\\" : is upoaded to s3\\\")\",\n \"def upload_to_s3(file_path, config):\\n logging.info(\\\"Uploading file to S3 bucket: %s\\\", config['s3_bucket_name'])\\n s3 = boto3.resource('s3')\\n s3_filename = config['s3_bucket_path'] + config['rendered_filename']\\n s3.Bucket(config['s3_bucket_name']).upload_file(\\n file_path, s3_filename, ExtraArgs={\\n 'ContentType': 'text/html', 'ACL': 'public-read'})\",\n \"def upload_file(file_name: str, bucket: str, object_name: str =None) -> None:\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name\\n\\n # Upload the file\\n s3_client = boto3.client(\\\"s3\\\")\\n try:\\n s3_client.upload_file(file_name, bucket, object_name)\\n except ClientError as e:\\n logging.error(e)\",\n \"def upload(file_path, aws_path, access_key, secret_key) -> None:\\n # bucket = \\\"dev-com-courtlistener-storage\\\"\\n bucket = \\\"seals.free.law\\\"\\n client = boto3.client(\\n \\\"s3\\\",\\n aws_access_key_id=access_key,\\n aws_secret_access_key=secret_key,\\n )\\n transfer = S3Transfer(client)\\n if \\\".png\\\" in file_path:\\n content_type = \\\"image/png\\\"\\n else:\\n content_type = \\\"image/svg+xml\\\"\\n transfer.upload_file(\\n file_path,\\n bucket,\\n aws_path,\\n extra_args={\\\"ContentType\\\": content_type, \\\"ACL\\\": \\\"public-read\\\"},\\n )\\n print(f\\\"http://{bucket}.s3-us-west-2.amazonaws.com/{aws_path}\\\")\",\n \"def upload_file(file_name, bucket, object_name=None):\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name\\n\\n # Upload the file\\n try:\\n response = s3_client.upload_file(file_name, bucket, object_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_file(file_name, bucket, object_name='patients.log'):\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name\\n # Upload the file\\n s3_client = boto3.client('s3')\\n try:\\n response = s3_client.upload_file(file_name, bucket, object_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_file_to_s3(file_path, bucket, object_name=None, access_key_id=None,\\n secret_access_key=None):\\n if object_name is None:\\n object_name = Path(file_path).name\\n\\n try:\\n s3_client = boto3.client(\\n \\\"s3\\\",\\n aws_access_key_id=access_key_id,\\n aws_secret_access_key=secret_access_key\\n )\\n\\n s3_client.upload_file(file_path, bucket, object_name)\\n except ClientError:\\n raise\",\n \"def upload_file(self, bucket_name, file_path, key):\\n self._client.upload_file(Filename=file_path, Bucket=bucket_name, Key=key)\",\n \"def upload_file(file_name, bucket, object_name=None):\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name\\n\\n # Upload the file\\n s3_client = boto3.client('s3', aws_access_key_id='', aws_secret_access_key='')\\n try:\\n response = s3_client.upload_file(file_name, bucket, object_name, ExtraArgs={'ACL':'public-read'})\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_file(file_name, s3_key):\\n # Upload the file\\n s3_connection = boto.connect_s3(aws_access_key_id, aws_secret_access_key)\\n bucket = s3_connection.get_bucket(predator_bucket_name)\\n try:\\n key = boto.s3.key.Key(bucket, s3_key)\\n key.set_contents_from_filename(file_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_to_s3(channel, file):\\n s3_resource = boto3.resource('s3')\\n data = open(file, \\\"rb\\\")\\n key = channel + '/' + file\\n s3_resource.Bucket(BUCKET).put_object(Key=key, Body=data)\",\n \"def _upload_file(file_name, bucket, object_name):\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name\\n\\n # Upload the file\\n try:\\n s3.upload_file(file_name, bucket, object_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_to_s3(self, name, file_name):\\n f = open(file_name, \\\"r\\\")\\n path = \\\"cluster/\\\" + name + \\\"/\\\" + os.path.basename(file_name)\\n bucket = self.s3.get_bucket(self.__secrets_bucket__)\\n k = Key(bucket)\\n k.name = path\\n\\n try:\\n k.set_contents_from_file(f)\\n except Exception as e:\\n print \\\"[-] Error uploading file to s3\\\"\\n print e\\n\\n print \\\"[+] Uploaded {0}\\\".format(\\\"s3://\\\" + self.__secrets_bucket__ + \\\"/\\\" + path)\\n\\n return\",\n \"def upload_file(file_name, bucket_name, object_name=None):\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = os.path.basename(file_name)\\n\\n try:\\n # Upload the file\\n response = s3.upload_file(file_name, bucket_name, object_name)\\n # Get list of files in bucket to confirm\\n describe_objects(bucket_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_file(file_name, bucket, object_name=None):\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name\\n\\n # Upload the file\\n s3_client = boto3.client(\\\"s3\\\")\\n try:\\n response = s3_client.upload_file(file_name, bucket, object_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_file(file_name, bucket, object_name=None):\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name\\n\\n # Upload the file\\n s3_client = boto3.client('s3')\\n try:\\n response = s3_client.upload_file(file_name, bucket, object_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_file(file_name, bucket, object_name=None):\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name\\n\\n # Upload the file\\n s3_client = boto3.client('s3')\\n try:\\n response = s3_client.upload_file(file_name, bucket, object_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_file(file_name, bucket, object_name=None):\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = os.path.basename(file_name)\\n\\n # Upload the file\\n s3_client = boto3.client('s3')\\n try:\\n response = s3_client.upload_file(file_name, bucket, object_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_file(\\n self, bucket_id: uplink.Path, filename: uplink.Path, file: uplink.Body\\n ):\\n pass\",\n \"def upload_file(bucket_name, filename, file):\\n client = get_client()\\n bucket = client.get_bucket(bucket_name)\\n blob = bucket.blob(filename)\\n blob.upload_from_file(file)\",\n \"def upload_file(file_name, object_name=None, bucket = BUCKET_NAME):\\n\\n # Upload the file\\n s3_client = boto3.client('s3')\\n try:\\n response = s3_client.upload_file(file_name, bucket, object_name) if type(file_name) == str else s3_client.upload_fileobj(file_name, BUCKET_NAME, object_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_fileobj(self, bucket_name, file_obj, key):\\n self._client.upload_fileobj(Fileobj=file_obj, Bucket=bucket_name, Key=key)\",\n \"def upload_file(local_path, s3_path):\\n with open(local_path, 'rb') as binary_data:\\n s3.Bucket(bucket_name).put_object(Key=s3_path, Body=binary_data)\",\n \"def upload_file(self, file_name, bucket, destination_name):\\n try:\\n not self.client.upload_file(file_name, bucket, destination_name)\\n except Exception as ex:\\n raise ex\",\n \"def upload_file(s3_client, file_name, object_name=None):\\n\\n # read bucket name from cfg file\\n bucket = config.get('S3', 'LANDING_ZONE')\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name.split('\\\\\\\\')[-1]\\n\\n # Upload the file\\n try:\\n response = s3_client.upload_file(file_name, bucket, object_name, Callback=ProgressPercentage(file_name))\\n# logger.debug(f\\\"Got response from s3 client for uploading file: {response}\\\")\\n except Exception as e:\\n logger.error(f\\\"Error occurred while upload {file_name} : {e}\\\")\\n return False\\n return True\",\n \"def upload_file_to_s3(self, file_data):\\r\\n\\r\\n file_key = file_data.name + datetime.now(UTC).strftime(\\r\\n xqueue_interface.dateformat\\r\\n )\\r\\n\\r\\n file_data.seek(0)\\r\\n s3_public_url = upload_to_s3(\\r\\n file_data, file_key, self.s3_interface\\r\\n )\\r\\n\\r\\n return s3_public_url\",\n \"def upload_to_s3(bucket, file_path, prefix, timestamp):\\n upload_name = f'{prefix}_{timestamp or \\\"\\\"}{basename(file_path)}'\\n\\n try:\\n bucket.upload_file(file_path, upload_name)\\n syslog.syslog(syslog.LOG_INFO,\\n f'Uploaded {file_path} to S3 Bucket - {bucket.name}')\\n return True\\n except S3UploadFailedError as s3ex:\\n syslog.syslog(\\n syslog.LOG_ERR, f'Failed to upload {file_path} to S3 Bucket - {bucket_name} - {s3ex}')\\n return False\\n finally:\\n rm(file_path)\",\n \"def _upload_to_bucket(self, filename, ext_filename):\\n if ext_filename is None:\\n return\\n\\n if self.s3:\\n self.bucket.upload_file(filename, ext_filename)\\n logging.info('Uploaded {} to S3 with name {}'.format(filename, ext_filename))\\n if self.gs:\\n try:\\n client = storage.Client()\\n bucket = client.get_bucket(self.bucket_name)\\n blob = storage.Blob(ext_filename, bucket)\\n blob.upload_from_filename(filename)\\n logging.info('Uploaded to {}'.format(ext_filename))\\n except:\\n logging.warning('Uploading file to bucket failed')\",\n \"def upload_file_to_bucket(s3_client, file_obj, bucket, folder, object_name=None):\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_obj\\n\\n # Upload the file\\n try:\\n response = s3_client.upload_fileobj(file_obj, bucket, f\\\"{folder}/{object_name}\\\")\\n print(response)\\n except ClientError:\\n return False\\n return True\",\n \"def upload_to_aws(local_file, bucket, s3_file, access_key, secret_key):\\n s3 = boto3.client('s3', aws_access_key_id=access_key,\\n aws_secret_access_key=secret_key)\\n \\n try:\\n s3.upload_file(local_file, bucket, s3_file)\\n print(f'Upload of {local_file} to {bucket} as {s3_file} successful.')\\n return True\\n except FileNotFoundError:\\n print(f'File {local_file} not found.')\\n return False\\n except NoCredentialsError:\\n print('Credentials invalid or not available.')\\n return False\",\n \"def upload_file_to_s3(bucket_name, input_filepath, output_filename):\\n s3 = boto3.client(\\\"s3\\\")\\n with open(input_filepath, \\\"rb\\\") as f:\\n s3.upload_fileobj(f, bucket_name, output_filename)\",\n \"def _put(conn, remote_file, contents, bucket_name=BUCKET_NAME, headers=None):\\n error_msg = 'Failed to upload to %s' % remote_file\\n try:\\n reply = conn.put(bucket_name, remote_file,\\n S3.S3Object(contents), headers)\\n if reply.http_response.status != 200:\\n print error_msg\\n except:\\n print error_msg\",\n \"def upload_file(file, bucket_path, bucket=S3_BUCKET):\\n # Bucket path should be somedir/name_of_file.ext\\n try:\\n if isinstance(file, str):\\n resource.upload_file(file, bucket, bucket_path)\\n else:\\n resource.upload_fileobj(file, bucket, bucket_path)\\n except:\\n raise ChildProcessError('Something broke, Cap\\\\'n')\",\n \"def pushToS3()-> None:\\n logging.info(f\\\"Connecting to s3 {getTime()}\\\")\\n s3 = boto3.client(\\\"s3\\\",endpoint_url=\\\"http://localhost:4566\\\")\\n if(not s3.head_bucket(Bucket=\\\"demo\\\")):\\n s3.create_bucket(Bucket='demo')\\n try:\\n logging.info(f\\\"Uploading to s3 {getTime()}\\\")\\n s3.upload_file(\\\"result.csv\\\",\\\"demo\\\",\\\"result.csv\\\")\\n logging.info(f\\\"Finished uploding to s3 {getTime()}\\\")\\n except ClientError as e:\\n logging.error(f\\\"Error uploading file to S3 {getTime()}\\\")\",\n \"def upload_to_s3(file_contents: bytes, path: str, content_type: str = None, tags: dict = None):\\n client = S3BucketClient()\\n client.upload(\\n file_contents=file_contents,\\n path=path,\\n content_type=content_type,\\n tags=tags,\\n )\",\n \"def store_to_s3():\\n\\n try:\\n # establish aws/s3 connection\\n s3 = boto3.client('s3',\\n aws_access_key_id=ACCESS_KEY,\\n aws_secret_access_key=SECRET_KEY\\n )\\n logger.info(\\\"S3 connection established!\\\")\\n except Exception as e:\\n logger.error('Fail to connect to aws s3. Please check your credentials!')\\n logger.error(e)\\n else:\\n try:\\n # upload local file to S3 bucket\\n logger.info(\\\"Uploading {} to {} bucket as {}\\\".format(config.Local_File_To_Upload,\\n config.Bucket_Name,\\n config.S3_Filename))\\n s3.upload_file(config.Local_File_To_Upload,\\n config.Bucket_Name,\\n config.S3_Filename)\\n logger.info('File successfully uploaded to S3 bucket!')\\n except FileNotFoundError:\\n logger.error('File not found, pleas check the file path.')\\n except Exception as e:\\n logger.error(e)\",\n \"def upload_file(self, keyUrl='', body='', ContentType='', bucket=None):\\n \\n if bucket is None:\\n bucket = self.AWS_S3_BUCKET\\n \\n #Verificamos si existe body\\n if body is None:\\n body=''\\n \\n try:\\n self.get_s3_client().put_object(Bucket=bucket, Key=keyUrl, Body=body, ACL='public-read', ContentType=ContentType)\\n return True\\n \\n except ClientError as e:\\n return False\",\n \"def _upload_to_s3(s3_uploader, relative_path, file_path, filename):\\n try:\\n key = os.path.join(s3_uploader[\\\"key_prefix\\\"], relative_path, filename)\\n s3_uploader[\\\"transfer\\\"].upload_file(file_path, s3_uploader[\\\"bucket\\\"], key)\\n except FileNotFoundError: # noqa ignore=F821\\n # Broken link or deleted\\n pass\\n except Exception: # pylint: disable=broad-except\\n logger.exception(\\\"Failed to upload file to s3.\\\")\\n finally:\\n # delete the original file\\n if os.path.exists(file_path):\\n os.remove(file_path)\",\n \"def upload_to_bucket(bucket_name, path_to_source_file, upload_file_name):\\r\\n\\r\\n try:\\r\\n # initialize client & get blob\\r\\n _, _, blob = create_client(bucket_name, upload_file_name)\\r\\n\\r\\n # set the path to source file\\r\\n blob.upload_from_filename(path_to_source_file)\\r\\n \\r\\n except Exception as err:\\r\\n raise err\\r\\n sys.exit(1)\\r\\n \\r\\n else:\\r\\n print(f\\\"upload file '{path_to_source_file}' succeed\\\")\\r\\n\\r\\n return None\",\n \"def upload_file(file_name, bucket, object_name=None):\\n\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = file_name\\n\\n # Upload the file\\n s3_client = boto3.client('s3')\\n try:\\n response = s3_client.upload_file(file_name, bucket, 'keypoints_descriptor/'+file_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def upload_file_to_bucket(self, bucket_id, filename):\\n url = self.upload_endpoint + \\\"/\\\" + bucket_id + \\\"/files\\\"\\n\\n headers = {\\\"Authorization\\\": \\\"Bearer \\\" + self.bearer_token}\\n\\n files = {\\\"file\\\": open(filename, \\\"rb\\\")}\\n\\n r = requests.post(url, headers=headers, files=files)\\n\\n if r.status_code == 200:\\n logging.info(\\\"Successfully uploaded file to the bucket\\\")\\n else:\\n logging.warning(\\\"HTTP Error {}\\\".format(r.status_code))\",\n \"def test_upload_file_to_s3_bucket(self):\\n conn = boto3.resource('s3', region_name='us-east-1')\\n # We need to create the bucket since this is all in Moto's 'virtual' AWS account\\n conn.create_bucket(Bucket='foobucket')\\n\\n s3_connector = S3Connector()\\n s3_connector.connect(\\\"default\\\")\\n s3_connector.upload_file(\\n file_path=\\\"test/test_resources/test_file\\\", file_name=\\\"foofile\\\", bucket_name=\\\"foobucket\\\")\\n\\n # get bucket contents\\n response = boto3.client('s3').list_objects(Bucket=\\\"foobucket\\\")\\n contents = []\\n for content in response.get('Contents', []):\\n contents.append(content.get('Key'))\\n\\n self.assertEqual(contents, [\\\"foofile\\\"])\",\n \"def upload(self, path, key, extra_args={}):\\n if key.endswith(\\\"/\\\"):\\n key += os.path.basename(path)\\n if key.startswith(\\\"/\\\"):\\n key = key[1:]\\n remote_path = self.base.full_cell + \\\"/\\\" + key\\n self.s3.meta.client.upload_file(path, self.bucket, remote_path, ExtraArgs=extra_args)\\n print \\\"UPLOADED {} to s3://{}/{}\\\".format(path, self.bucket, remote_path)\",\n \"def upload_file(Filename=None, Bucket=None, Key=None, ExtraArgs=None, Callback=None, Config=None):\\n pass\",\n \"def upload_from_path_to_s3(file_path):\\n bucket_name = \\\"alp-reports-lambda\\\"\\n environment = \\\"dev\\\" if os.environ.get('LOCAL') else \\\"prod\\\"\\n object_key = f\\\"{environment}/835/{file_path.split('/')[-1]}\\\"\\n\\n s3 = boto3.resource('s3')\\n s3.Object(bucket_name, object_key).upload_file(file_path, ExtraArgs={'ACL': 'public-read'})\\n\\n return f\\\"https://s3.amazonaws.com/{bucket_name}/{object_key}\\\"\",\n \"def upload(self, bucket_name, key_name, fname):\\n bucket = self.s3_.get_bucket(bucket_name)\\n key = boto.s3.key.Key(bucket)\\n with open(fname, 'rb') as infile:\\n key.key = key_name\\n return key.set_contents_from_file(infile)\",\n \"def upload(self, bucket, obj, s3_client=None):\\n\\n s3_client = s3_client or self.s3_client\\n transfer_config = boto3.s3.transfer.TransferConfig(multipart_threshold=1024, use_threads=True, max_concurrency=10)\\n s3_transfer = boto3.s3.transfer.S3Transfer(client=s3_client, config=transfer_config)\\n\\n try:\\n logging.debug(\\\"Uploading {} to {}\\\".format(obj, bucket))\\n s3_transfer.upload_file(obj, bucket, helpers.strip_path(obj)[1])\\n\\n return True\\n except botocore.exceptions.EndpointConnectionError:\\n logging.error(\\\"Couldn't connect to an S3 endpoint. If you're using an S3 compatible provider other than AWS, remember to set --s3-endpoint-url\\\")\\n return False\\n except Exception as e:\\n logging.error(\\\"Error uploading: {}\\\".format(e))\\n return False\",\n \"def upload_blob(self, bucket_name, file_name, contents):\\n\\n bucket = self.storage_client.bucket(bucket_name)\\n blob = bucket.blob(file_name)\\n blob.upload_from_string(contents)\\n print(\\n \\\"File {} uploaded to bucket {} as file {}.\\\".format(\\n file_name, bucket_name, file_name\\n )\\n )\",\n \"def upload_file(conn, filename_local, filename_s3, gzip=False):\\n\\n filename_s3 = filename_s3.lstrip('./')\\n\\n file_descriptor = open(filename_local, 'rb')\\n content = file_descriptor.read()\\n\\n content_type = _get_content_type(file_descriptor)\\n headers = _get_headers(content_type)\\n\\n #should compress if the file is compressable and gzip is enabled\\n can_be_gzipped = _file_can_be_compressed(filename_local)\\n if gzip and can_be_gzipped:\\n content = _compress_string(content)\\n headers['Content-Length'] = str(len(content))\\n headers['Content-Encoding'] = 'gzip'\\n extension = mimetypes.guess_extension(content_type)\\n #we should not overwrite the original file in the server.\\n #We change extensions: style.css --> style.gz.css, for instance\\n filename_s3 = filename_s3.rstrip(extension) + '.gz' + extension\\n\\n #if gzip is enabled and it is not compressable, don't upload nothing at all\\n elif gzip and not can_be_gzipped:\\n return\\n\\n #upload\\n print 'Uploading %s to %s' % (filename_local, filename_s3)\\n _put(conn, filename_s3, content, headers=headers)\\n file_descriptor.close()\",\n \"async def put_file(object_name: str, file: File, **kwargs) -> str:\\n # TODO: Do not read file but rather stream content as it comes\\n await file.read()\\n # Get the synchronous file interface from the asynchronous file\\n file_obj = file.file\\n # Store position of cursor (number of bytes read)\\n file_size = file_obj.tell()\\n # Reset cursor at start of file\\n file_obj.seek(0)\\n # Trace file upload with its size\\n logger.debug(f\\\"Uploading file: {object_name} with {file_size} bytes\\\")\\n # Time file upload for debug\\n start = time.time()\\n # Store object on s3 storage\\n client.put_object(\\n bucket_name=DATASETS_BUCKET,\\n object_name=object_name,\\n length=file_size,\\n data=file_obj,\\n )\\n end = time.time()\\n # Log time spent\\n logger.debug(f\\\"Took {end - start} seconds to upload {file_size} bytes\\\")\",\n \"def _cloud_storage_upload(local_file, bucket, filename_on_bucket):\\n client = storage.Client()\\n\\n bucket = client.get_bucket(bucket)\\n blob = bucket.blob(filename_on_bucket)\\n blob.upload_from_filename(local_file)\\n print('uploaded ', bucket, filename_on_bucket)\",\n \"def upload_to_s3(self, file: str, force_upload: bool = False) -> str:\\n if self.aws_access_key_id is None:\\n raise Exception(\\n 'To use `upload_to_s3` you need to pass '\\n '`aws_access_key_id` and '\\n '`aws_secret_access_key`'\\n )\\n\\n filename = file.split('/')[-1]\\n\\n s3 = boto3.client(\\n 's3',\\n aws_access_key_id=self.aws_access_key_id,\\n aws_secret_access_key=self.aws_secret_access_key\\n )\\n # Check if exists\\n if not force_upload:\\n try:\\n session = boto3.Session(\\n aws_access_key_id=self.aws_access_key_id,\\n aws_secret_access_key=self.aws_secret_access_key\\n )\\n\\n session.resource('s3').Object(self.bucket_name, filename).load()\\n except botocore.exceptions.ClientError as e:\\n if e.response['Error']['Code'] != \\\"404\\\":\\n raise e\\n else:\\n # The object does exist\\n return filename\\n\\n # Progress bar\\n size = os.stat(file).st_size\\n progress_bar = self._progress(size)\\n\\n # Uploading file\\n s3.upload_file(file, self.bucket_name, filename, Callback=progress_bar)\\n\\n return filename\",\n \"def put_upload(self):\\n # print \\\"starting upload...\\\", self.current_upload['filepath']\\n self.touch()\\n self.log(\\\"STARTING_UPLOAD\\\", level=INFO)\\n try:\\n Backend.put_file(self.fileobj, self.current_upload[\\\"gcs_url\\\"])\\n except exceptions.FilePutError as err:\\n self.handle_put_error(err, self.fileobj)\\n raise\",\n \"def upload(filename, bucket):\\n k = Key(bucket)\\n k.key = uuid.uuid1().hex\\n print \\\"Uploading batch to {}, key: {}...\\\".format(bucket.name, k.key)\\n k.set_contents_from_filename(filename, reduced_redundancy=True)\\n print \\\" Done.\\\"\\n \\n\\n\\n bucket = openBucket(dest)\",\n \"def _upload_to_s3(filename):\\n if not app.config.get('UPLOAD_SCREENSHOTS_TO_S3', False):\\n return\\n\\n import boto\\n from boto.s3.key import Key\\n conn = boto.connect_s3()\\n b = conn.get_bucket(app.config['S3_BUCKET'])\\n k = Key(b)\\n k.key = '{}/{}'.format(\\n app.config.get('S3_FILES_PREFIX', 'sleepypuppy'),\\n filename\\n )\\n k.set_contents_from_filename(\\n \\\"{}/{}\\\".format(\\n app.config['UPLOAD_FOLDER'],\\n filename\\n )\\n )\\n os.remove(\\n \\\"{}/{}\\\".format(\\n app.config['UPLOAD_FOLDER'],\\n filename\\n )\\n )\",\n \"def upload(self, bucket, object, filename, mime_type='application/octet-stream'):\\n service = self.get_conn()\\n media = MediaFileUpload(filename, mime_type)\\n response = service \\\\\\n .objects() \\\\\\n .insert(bucket=bucket, name=object, media_body=media) \\\\\\n .execute()\",\n \"def upload_object(self, file_path, destination, use_original_name=True, ExtraArgs=None):\\n assert os.path.exists(file_path), \\\"File path does not exist {}\\\".format(file_path)\\n bucket_name, save_path = self.split_name(destination)\\n if use_original_name:\\n save_path = os.path.join(save_path, os.path.basename(file_path))\\n\\n self.s3_client.upload_file(file_path, bucket_name, save_path, ExtraArgs=ExtraArgs)\\n return os.path.join(bucket_name, save_path)\",\n \"def upload_file_to_s3(bucket, artefact, bucket_key):\\n try:\\n client = boto3.client('s3')\\n\\n except ClientError as err:\\n print(\\\"Failed to create boto3 client.\\\\n\\\" + str(err))\\n return False\\n\\n try:\\n kwargs = {\\n \\\"Body\\\": open(artefact, 'rb'),\\n \\\"Bucket\\\": bucket,\\n \\\"Key\\\": bucket_key\\n }\\n\\n mime_type, encoding = mimetypes.guess_type(artefact)\\n\\n if mime_type is None:\\n file_name, file_ext = os.path.splitext(artefact)\\n\\n if file_ext == \\\".icon\\\" :\\n kwargs[\\\"ContentType\\\"] = \\\"image/vnd.microsoft.icon\\\"\\n\\n elif file_ext == \\\".woff2\\\" :\\n kwargs[\\\"ContentType\\\"] = \\\"application/font-woff\\\"\\n \\n else:\\n kwargs[\\\"ContentType\\\"] = mime_type\\n\\n client.put_object(**kwargs)\\n\\n except ClientError as err:\\n print(\\\"Failed to upload artefact to S3.\\\\n\\\" + str(err))\\n return False\\n\\n except IOError as err:\\n print(\\\"Failed to access artefact in this directory.\\\\n\\\" + str(err))\\n return False\\n\\n return True\",\n \"def upload(bucket_name, source_file, destination_blob_name):\\n storage_client = storage.Client()\\n bucket = storage_client.get_bucket(bucket_name)\\n blob = bucket.blob(destination_blob_name)\\n\\n try:\\n blob.upload_from_file(source_file)\\n except:\\n return None\\n else:\\n return('File {} uploaded to {}.'.format(\\n source_file,\\n destination_blob_name))\",\n \"def upload_package(self, filename=None):\\n logger.info(\\\"Uploading the package to S3\\\")\\n s3f = S3FunctionUploader(self.function_config['Code']['S3Bucket'])\\n self.s3_filename = path.join(\\n self.function_config['Code']['S3KeyPath'],\\n path.basename(filename or self.local_filename)\\n )\\n s3f.upload(filename or self.local_filename,\\n self.s3_filename)\",\n \"def put(self, path: str, filename: str) -> None:\\n\\n payload_hash, content_md5, length = _hash(path)\\n\\n now = datetime.datetime.utcnow()\\n timestamp = now.strftime('%Y%m%dT%H%M%SZ')\\n headers = [\\n ('Connection', 'keep-alive'),\\n ('Content-Length', str(length)),\\n ('Content-MD5', content_md5),\\n ('Content-Type', 'application/zip'),\\n ('Date', now.strftime('%a, %d %b %Y %H:%M:%S GMT')),\\n ('Host', '%s.s3.amazonaws.com' % self.bucket),\\n ('x-amz-content-sha256', payload_hash),\\n ('x-amz-date', timestamp),\\n ]\\n signed_headers = ';'.join(header[0].lower() for header in headers)\\n canonical_request = 'PUT\\\\n%s\\\\n\\\\n%s\\\\n\\\\n%s\\\\n%s' % (filename, '\\\\n'.join(\\n ('%s:%s' % (header[0].lower(), header[1])\\n for header in headers)), signed_headers, payload_hash)\\n logging.debug('canonical request %r',\\n canonical_request.encode('utf-8'))\\n string_to_sign = 'AWS4-HMAC-SHA256\\\\n%s\\\\n%s\\\\n%s' % (\\n timestamp, self.scope,\\n hashlib.sha256(canonical_request.encode('utf-8')).hexdigest())\\n logging.debug('string to sign %r', string_to_sign.encode('utf-8'))\\n\\n signature = hmac.new(self.signing_key,\\n string_to_sign.encode('utf-8'),\\n digestmod='sha256').hexdigest()\\n headers.append((\\n 'Authorization',\\n 'AWS4-HMAC-SHA256 Credential=%s/%s,SignedHeaders=%s,Signature=%s' %\\n (self.aws_access_key, self.scope, signed_headers, signature)))\\n with open(path, 'rb') as file_stream:\\n if not self.conn:\\n self.conn = http.client.HTTPSConnection('%s.s3.amazonaws.com' %\\n self.bucket)\\n try:\\n self.conn.request('PUT',\\n filename,\\n file_stream,\\n headers=dict(headers))\\n res = self.conn.getresponse()\\n payload = res.read()\\n except (http.client.BadStatusLine, http.client.ResponseNotReady,\\n http.client.CannotSendRequest):\\n self.conn.close()\\n raise\\n if res.status != 200:\\n raise Exception(payload.decode('utf-8'))\",\n \"def test_put_file(self):\\n self.prepare_uploads()\\n backend = BackendS3(**self.config)\\n uploads = self.upload_path\\n src = os.path.join(uploads, 'demo-test.tar.gz')\\n id = utils.generate_id('demo-test.tar.gz')\\n backend.put(src, id)\\n path = '/'.join(backend.id_to_path(id)) + '/demo-test.tar.gz'\\n self.assertTrue(backend.exists(path))\",\n \"def put_object(self, bucket, key, local_file_path=None, file_bytes=None) -> None:\\n def upload_to_s3(byte_array):\\n self.resource.Object(bucket, key).put(Body=byte_array)\\n\\n if file_bytes:\\n upload_to_s3(file_bytes)\\n else:\\n with open(local_file_path, 'rb') as local_file:\\n self.resource.Object(bucket, key).put(Body=local_file)\",\n \"def upload_from_file(self, file_obj, name_on_storage, **keyword_args):\\n blob = self.bucket.blob(name_on_storage)\\n blob.upload_from_file(file_obj, **keyword_args)\\n print(f\\\"Upload object {name_on_storage}\\\")\",\n \"def put_file(self, file_name: str, value: BytesIO):\\n value.seek(0)\\n self.client.upload_fileobj(value, self.bucket, file_name)\",\n \"def s3(ctx, bucket_name, data_file, region):\\n ctx.obj['BUCKET_NAME'] = bucket_name\\n ctx.obj['DATA_FILE'] = data_file\\n ctx.obj['TYPE'] = 's3'\\n ctx.obj['REGION'] = region\",\n \"def put_data_in_s3(data, filename):\\n s3_client.put_object(Body=data, Bucket=CLIMATE_DATA_BUCKET, Key=filename)\",\n \"def put(self, file_path, key=None):\\n try:\\n key_name = key if key else os.path.basename(file_path)\\n size = os.stat(file_path).st_size\\n if size < 104857600: #100 mb\\n k = Key(self.bucket)\\n k.key = key_name\\n sent = k.set_contents_from_filename(file_path)\\n log.info('Uploading %s to S3 (%s)' % (key_name, self.bucket_name))\\n return sent == size\\n else:\\n log.info('Multipart Uploading %s to S3 (%s)' % (key_name, self.bucket_name))\\n mp = self.bucket.initiate_multipart_upload(key_name)\\n chunk_size = 52428800\\n chunk_count = int(math.ceil(size / float(chunk_size)))\\n #Send the file parts, using FileChunkIO to create a file-like object\\n # that points to a certain byte range within the original file. We\\n # set bytes to never exceed the original file size.\\n for i in range(chunk_count):\\n offset = chunk_size * i\\n bytes = min(chunk_size, size - offset)\\n with FileChunkIO(file_path, 'r', offset=offset, bytes=bytes) as fp:\\n mp.upload_part_from_file(fp, part_num=i + 1)\\n # Finish the upload\\n mp.complete_upload()\\n return True\\n except Exception, e:\\n log.error('Failed to upload to S3 (%s)' % (self.bucket_name), exc_info=True)\\n return False\",\n \"def aws_s3_upload(self):\\n\\n # absolute path to the csv file to create\\n csv_file = os.path.join(self.csvfile, \\\"DLTINS_20210117_01of01.csv\\\")\\n\\n # Test for correct data\\n self.assertTrue(\\n aws_s3_upload(\\n csv_file,\\n self.region_name,\\n self.aws_access_key_id,\\n self.aws_secret_access_key,\\n self.bucket_name,\\n )\\n )\\n\\n # Test for non existent bucket\\n self.assertFalse(\\n aws_s3_upload(\\n csv_file,\\n \\\"useast\\\",\\n self.aws_access_key_id,\\n self.aws_secret_access_key,\\n self.bucket_name,\\n )\\n )\\n\\n # Test for non existent region\\n self.assertFalse(\\n aws_s3_upload(\\n csv_file,\\n self.region_name,\\n self.aws_access_key_id,\\n self.aws_secret_access_key,\\n \\\"nonexistentbucketname\\\",\\n )\\n )\\n\\n # Test for incorrect keys\\n self.assertFalse(\\n aws_s3_upload(\\n csv_file,\\n self.region_name,\\n \\\"xjvachiahvlchabo;jvbo\\\",\\n \\\"khkc vah haaih aih ika\\\",\\n self.bucket_name,\\n )\\n )\",\n \"def upload(self, filename, file_path):\\n return\",\n \"def upload_blob(bucket_name, source_file_name, destination_blob_name):\\n # bucket_name = \\\"your-bucket-name\\\"\\n # source_file_name = \\\"local/path/to/file\\\"\\n # destination_blob_name = \\\"storage-object-name\\\"\\n\\n storage_client = storage.Client()\\n bucket = storage_client.bucket(bucket_name)\\n blob = bucket.blob(destination_blob_name)\\n\\n blob.upload_from_filename(source_file_name)\\n print(\\\"File {} uploaded to {}.\\\".format(\\n source_file_name, destination_blob_name\\n )\\n )\",\n \"def upload_file_by_url(s3_file_name, filename):\\n full_path = os.path.join(CONFIG_BROKER['path'], \\\"tests\\\", \\\"integration\\\", \\\"data\\\", filename)\\n\\n if CONFIG_BROKER['local']:\\n # If not using AWS, put file submission in location\\n # specified by the config file\\n broker_file_path = CONFIG_BROKER['broker_files']\\n copy(full_path, broker_file_path)\\n submitted_file = os.path.join(broker_file_path, filename)\\n return {'bytesWritten': os.path.getsize(submitted_file), 's3FileName': full_path}\\n else:\\n # Use boto to put files on S3\\n s3conn = boto.s3.connect_to_region(CONFIG_BROKER[\\\"aws_region\\\"])\\n bucket_name = CONFIG_BROKER['aws_bucket']\\n key = Key(s3conn.get_bucket(bucket_name))\\n key.key = s3_file_name\\n bytes_written = key.set_contents_from_filename(full_path)\\n return {'bytesWritten': bytes_written, 's3FileName': s3_file_name}\",\n \"def upload_files_s3(files, bucket):\\n \\n print('************************************')\\n print('Uploading files to s3 bucket...')\\n print('************************************')\\n \\n for i in range(len(files)):\\n upload_file_s3(files[i], bucket)\\n \\n print('************************************')\\n print('Upload complete')\\n print('************************************')\",\n \"def upload_blob(bucket_name, source_file_name, destination_blob_name):\\n storage_client = storage.Client()\\n bucket = storage_client.get_bucket(bucket_name)\\n blob = bucket.blob(destination_blob_name)\\n\\n blob.upload_from_filename(source_file_name)\\n\\n print('File {} uploaded to {}.'.format(\\n source_file_name,\\n destination_blob_name))\",\n \"def upload_file(cls, uri, fobj):\\n # Breaks the URI into usable componenents.\\n values = get_values_from_media_uri(uri)\\n logger.debug(\\\"S3Backend.upload_file(): Received: %s\\\" % values)\\n\\n conn = cls._get_aws_s3_connection(values['username'],\\n values['password'])\\n bucket = conn.create_bucket(values['host'])\\n key = bucket.new_key(values['path'])\\n\\n logger.debug(\\\"S3Backend.upload_file(): \\\"\\\\\\n \\\"Settings contents of '%s' key from %s\\\" % (\\n values['path'], fobj.name))\\n key.set_contents_from_filename(fobj.name)\\n\\n logger.debug(\\\"S3Backend.upload_file(): Upload complete.\\\")\\n return key\",\n \"def upload_chain(s3_path, local_path, bucket_name='lwr-inverse-us-east'):\\n s3 = boto3.resource(\\\"s3\\\")\\n lwr_AIES = s3.Bucket(bucket_name)\\n file_content = open(local_path, 'rb')\\n lwr_AIES.put_object(Key=s3_path, Body=file_content)\",\n \"def upload_blob(bucket_name, source_file_name, destination_blob_name):\\n\\n storage_client = storage.Client()\\n bucket = storage_client.get_bucket(bucket_name)\\n blob = bucket.blob(destination_blob_name)\\n\\n blob.upload_from_filename(source_file_name)\\n\\n print('File {} uploaded to {}.'.format(\\n source_file_name,\\n destination_blob_name))\",\n \"def upload_blob(bucket_name, source_file_name, destination_blob_name):\\n\\n storage_client = storage.Client()\\n bucket = storage_client.bucket(bucket_name)\\n blob = bucket.blob(destination_blob_name)\\n\\n blob.upload_from_filename(source_file_name)\\n\\n print(\\n \\\"File {} uploaded to {}.\\\".format(\\n source_file_name, destination_blob_name\\n )\\n )\",\n \"def save_image_to_s3(filename, file):\\n \\n s3_path = f\\\"s3://shopifyimagerepository/{filename}\\\"\\n \\n s3_client.put_object(Body=file,\\n Bucket=\\\"shopifyimagerepository\\\",\\n Key=filename,\\n ACL=\\\"public-read\\\")\",\n \"def upload_blob(bucket_name, source_file_name, destination_blob_name):\\n # bucket_name = \\\"your-bucket-name\\\"\\n # source_file_name = \\\"local/path/to/file\\\"\\n # destination_blob_name = \\\"storage-object-name\\\"\\n\\n storage_client = storage.Client()\\n bucket = storage_client.bucket(bucket_name)\\n blob = bucket.blob(destination_blob_name)\\n\\n blob.upload_from_filename(source_file_name)\\n\\n print(\\n \\\"File {} uploaded to {}.\\\".format(\\n source_file_name, destination_blob_name\\n )\\n )\",\n \"def upload_file(bucket, local_file_path, remote_destination_path):\\n bucket = get_bucket(bucket)\\n k = Key(bucket)\\n k.key = remote_destination_path\\n k.set_contents_from_filename(local_file_path)\",\n \"def upload_blob(bucket_name, source_file_name, destination_blob_name):\\n storage_client = storage.Client()\\n bucket = storage_client.get_bucket(bucket_name)\\n blob = bucket.blob(destination_blob_name)\\n\\n blob.upload_from_filename(source_file_name)\\n\\n print('File {} uploaded to {}.'.format(\\n Crabbie.queue_file,\\n destination_blob_name))\",\n \"def upload_file(self, bucket_name, object_name, filepath, metadata=None):\\n try:\\n _metadata = {}\\n if metadata is not None:\\n for key in metadata.keys():\\n _metadata[self.__metadata_prefix + key] = metadata[key]\\n self.client.fput_object(\\n bucket_name, object_name, filepath, metadata=_metadata\\n )\\n except ResponseError as _err:\\n logging.exception(\\\"Could not upload file\\\")\\n return False\\n return True\",\n \"def upload_file_to_s3(local_path: Path, s3_path: Path, overwrite: bool = False) -> None:\\n import warnings\\n\\n warnings.filterwarnings(\\n action=\\\"ignore\\\", message=\\\"unclosed\\\", category=ResourceWarning\\n )\\n\\n s3_args, unknown = get_s3_args().parse_known_args()\\n s3_client = get_s3_client(s3_args)\\n log = get_logger(\\\"upload_file_to_s3\\\")\\n\\n try:\\n # only write files to s3 that don't already exist unless overwrite is passed\\n if s3_object_exists(s3_path) and not overwrite:\\n log.debug(\\n f\\\"s3://{s3_args.s3_bucket}/{s3_path} already exists in s3, not overwriting\\\"\\n )\\n return\\n\\n s3_client.put_object(\\n Body=local_path.read_bytes(), Bucket=s3_args.s3_bucket, Key=str(s3_path)\\n )\\n log.debug(f\\\"uploaded s3://{s3_args.s3_bucket}/{s3_path}\\\")\\n\\n except s3_client.exceptions.ClientError as exc:\\n # catch and raise any errors generated while attempting to communicate with s3\\n s3_client_attributes = {\\n attr: getattr(s3_client, attr) for attr in s3_client.__dict__.keys()\\n }\\n s3_client_attributes.update(\\n {\\\"bucket\\\": s3_args.s3_bucket, \\\"object_path\\\": s3_path,}\\n )\\n raise S3Error(f\\\"{s3_client_attributes} S3 ClientError\\\") from exc\",\n \"def upload_to_s3(site, bucket, directory=None, files=None, prefix=None):\\n if bucket is None:\\n print red('Error: Bucket must be specified.')\\n return\\n if directory is None and files is None:\\n print red('Error: Directory and/or files must be specified.')\\n return\\n # Setup boto\\n import boto\\n from boto.s3.bucket import Bucket\\n from boto.s3.key import Key\\n import mimetypes\\n import fnmatch\\n\\n setup_aws_access_key(site)\\n\\n # Connect to S3\\n c = boto.connect_s3()\\n b = Bucket(c, bucket)\\n\\n # Fix the prefix\\n # prefix itself shouldn't have a / prefix itself but should end with /\\n if prefix:\\n prefix = prefix.lstrip('/')\\n if prefix and not prefix.endswith('/'):\\n prefix = prefix + '/'\\n\\n def __upload(key, filename):\\n k = Key(b)\\n k.key = key\\n headers = {}\\n content_type = mimetypes.guess_type(filename)[0]\\n if site.has_key('webapp') and site['webapp'].get('cache_control'):\\n for pattern in site['webapp']['cache_control']:\\n if fnmatch.fnmatch(filename, pattern):\\n headers['Cache-Control'] = site['webapp']['cache_control'][pattern]\\n break\\n if site.has_key('webapp') and site['webapp'].get('gzip_types') and content_type in site['webapp']['gzip_types']:\\n from gzip import GzipFile\\n from StringIO import StringIO\\n # Need to specify content_type when uploading from a string!\\n headers['Content-Type'] = content_type\\n headers['Content-Encoding'] = 'gzip'\\n s = StringIO()\\n g = GzipFile(fileobj=s, mode='wb')\\n with open(filename, 'rb') as f:\\n g.write(f.read())\\n g.close()\\n k.set_contents_from_string(s.getvalue(), headers)\\n else:\\n k.set_contents_from_filename(filename, headers)\\n\\n if files:\\n # Upload individual files\\n if directory:\\n keys = [filename.lstrip('/') for filename in files]\\n files = [os.path.join(directory, filename) for filename in files]\\n else:\\n keys = [os.path.split(filename)[1] for filename in files]\\n for i, filename in enumerate(files):\\n print 'Uploading %s' % keys[i]\\n if prefix:\\n key = prefix + keys[i]\\n else:\\n key = keys[i]\\n __upload(key, filename)\\n elif directory:\\n # Upload an entire directory\\n def __upload_dir(arg, dirname, names):\\n # arg is the starting directory\\n for name in names:\\n filename = os.path.join(dirname, name)\\n if not os.path.isdir(filename) and not os.path.islink(filename) and not name.startswith('.'):\\n key = filename[len(arg):]\\n if key.startswith('/'):\\n key = key[1:]\\n if prefix:\\n key = prefix + key\\n print 'Uploading %s' % key\\n __upload(key, filename)\\n os.path.walk(directory, __upload_dir, directory)\",\n \"def upload(iid, file_obj, content_type):\\n if AWS_CLIENT_CONFIG and BUCKET_NAME:\\n try:\\n s3 = boto3.resource('s3', **AWS_CLIENT_CONFIG)\\n s3.Bucket(BUCKET_NAME).put_object(Key=iid,\\n Body=file_obj,\\n ContentType=content_type)\\n return StorageType.S3\\n except botocore.exceptions.ClientError as e:\\n logger.error(e)\\n else:\\n # store locally in temp dir (tests, local development)\\n store_temp_file(iid, file_obj)\\n return StorageType.TMP\\n return None\",\n \"def upload(self, path, data, headers={}):\\n\\n client = AsyncHTTPClient()\\n method = 'PUT'\\n url = self.generate_url(path)\\n url_object = urlparse(url)\\n params = {\\n 'SignatureMethod': 'AWS4-HMAC-SHA256'\\n }\\n\\n headers.update({\\n 'Content-Length': str(len(data)),\\n 'Content-Type': self._guess_mimetype(path),\\n 'Date': self._rfc822_datetime(),\\n 'Host': url_object.hostname,\\n 'X-Amz-Content-sha256': hashlib.sha256(data).hexdigest(),\\n })\\n\\n try:\\n response = yield client.fetch(\\n self.sign_request(\\n url_object.hostname,\\n url_object.path,\\n params,\\n headers,\\n method,\\n data\\n ),\\n method=method,\\n body=data,\\n connect_timeout=AWS_S3_CONNECT_TIMEOUT,\\n request_timeout=AWS_S3_REQUEST_TIMEOUT,\\n headers=headers\\n )\\n except HTTPError as error:\\n log.error(error)\\n if error.response:\\n log.error(error.response.body)\\n raise Return(None)\\n\\n raise Return(response)\",\n \"def upload_file(self, key, filepath, access, keep_original=True,\\n verbose=False):\\n\\n # file entry\\n try:\\n file_entry = self.bucket.new_key(key)\\n file_entry.set_metadata('filepath', filepath)\\n file_entry.set_contents_from_filename(filepath)\\n file_entry.set_acl(access) # access control\\n except Exception as error:\\n print str(error)\\n return False\\n else:\\n if verbose:\\n print \\\"{} uploaded to amazon s3.\\\".format(key)\\n\\n # original file removal\\n if not keep_original and os.access(filepath, os.W_OK):\\n try:\\n os.remove(filepath)\\n except (IOError, OSError):\\n print \\\"I/O error, could not remove file.\\\"\\n else:\\n if verbose:\\n print \\\"{} (original) removed\\\".format(filepath)\\n\\n return True\",\n \"def upload_to_s3(bucket_name, sourceDir):\\n try:\\n client = boto3.client('s3')\\n resource = boto3.resource('s3')\\n except ClientError as err:\\n print(\\\"Failed to create boto3 client.\\\\n\\\" + str(err))\\n return False\\n try:\\n # clean the bucket\\n bucket = resource.Bucket(bucket_name)\\n for key in bucket.objects.all():\\n key.delete()\\n\\n # upload the new files\\n uploadFileNames = getFiles(sourceDir)\\n print(\\\"Found \\\" + len(uploadFileNames).__str__() + ' files')\\n\\n for filename in uploadFileNames:\\n destName = os.path.join(*(filename.split('/')[1:]))\\n print(\\\"Uploading file \\\" + filename + ' to ' + destName)\\n resource.Object(bucket_name, destName).put(Body=open(filename, 'rb'),\\n ContentType=get_contenttype_from_filename(filename))\\n\\n except ClientError as err:\\n print(\\\"Failed to upload artefact to S3.\\\\n\\\" + str(err))\\n return False\\n except IOError as err:\\n print(\\\"Failed to access artefact in this directory.\\\\n\\\" + str(err))\\n return False\\n\\n return True\",\n \"def upload_file(self, bucket_name, object_name, filepath, metadata=None):\\n try:\\n _metadata = {}\\n if metadata is not None:\\n for key in metadata.keys():\\n _metadata[self.__metadata_prefix+key] = metadata[key]\\n self.client.fput_object(bucket_name, object_name, filepath,\\n metadata=_metadata)\\n except ResponseError as _err:\\n logging.exception(\\\"Could not upload file\\\")\\n return False\\n return True\",\n \"def upload_fileobj(Fileobj=None, Bucket=None, Key=None, ExtraArgs=None, Callback=None, Config=None):\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.86530435","0.8389777","0.8361179","0.8325962","0.8258803","0.825059","0.8241126","0.82018214","0.8064815","0.8038341","0.80270815","0.79748935","0.7933823","0.78858334","0.78781134","0.7859663","0.7847567","0.78461665","0.783782","0.7817148","0.7810306","0.7807648","0.7807208","0.780025","0.77815026","0.77796495","0.77796495","0.77781576","0.7765932","0.77574027","0.7709971","0.7685064","0.7675691","0.76725334","0.76553786","0.76434463","0.7643053","0.76029205","0.7585839","0.7583744","0.75632817","0.75483876","0.75444555","0.75228935","0.7494005","0.7491995","0.7487729","0.7450458","0.74368846","0.7389816","0.7349025","0.7343912","0.73226374","0.73130447","0.7302274","0.7251133","0.72476816","0.7244955","0.714324","0.71153474","0.7064639","0.70633173","0.7058372","0.70436573","0.7043471","0.70396507","0.70342153","0.70029414","0.69782716","0.6970334","0.69432783","0.6936179","0.691318","0.69107157","0.69019204","0.6892148","0.6888758","0.68598664","0.6844915","0.6843034","0.6815527","0.68056667","0.67871","0.67811495","0.6774042","0.6770357","0.67690766","0.676824","0.6758794","0.6755805","0.6754093","0.67537636","0.67452186","0.6743714","0.67366016","0.6734711","0.6730331","0.671894","0.67130643","0.6701074","0.6696187"],"string":"[\n \"0.86530435\",\n \"0.8389777\",\n \"0.8361179\",\n \"0.8325962\",\n \"0.8258803\",\n \"0.825059\",\n \"0.8241126\",\n \"0.82018214\",\n \"0.8064815\",\n \"0.8038341\",\n \"0.80270815\",\n \"0.79748935\",\n \"0.7933823\",\n \"0.78858334\",\n \"0.78781134\",\n \"0.7859663\",\n \"0.7847567\",\n \"0.78461665\",\n \"0.783782\",\n \"0.7817148\",\n \"0.7810306\",\n \"0.7807648\",\n \"0.7807208\",\n \"0.780025\",\n \"0.77815026\",\n \"0.77796495\",\n \"0.77796495\",\n \"0.77781576\",\n \"0.7765932\",\n \"0.77574027\",\n \"0.7709971\",\n \"0.7685064\",\n \"0.7675691\",\n \"0.76725334\",\n \"0.76553786\",\n \"0.76434463\",\n \"0.7643053\",\n \"0.76029205\",\n \"0.7585839\",\n \"0.7583744\",\n \"0.75632817\",\n \"0.75483876\",\n \"0.75444555\",\n \"0.75228935\",\n \"0.7494005\",\n \"0.7491995\",\n \"0.7487729\",\n \"0.7450458\",\n \"0.74368846\",\n \"0.7389816\",\n \"0.7349025\",\n \"0.7343912\",\n \"0.73226374\",\n \"0.73130447\",\n \"0.7302274\",\n \"0.7251133\",\n \"0.72476816\",\n \"0.7244955\",\n \"0.714324\",\n \"0.71153474\",\n \"0.7064639\",\n \"0.70633173\",\n \"0.7058372\",\n \"0.70436573\",\n \"0.7043471\",\n \"0.70396507\",\n \"0.70342153\",\n \"0.70029414\",\n \"0.69782716\",\n \"0.6970334\",\n \"0.69432783\",\n \"0.6936179\",\n \"0.691318\",\n \"0.69107157\",\n \"0.69019204\",\n \"0.6892148\",\n \"0.6888758\",\n \"0.68598664\",\n \"0.6844915\",\n \"0.6843034\",\n \"0.6815527\",\n \"0.68056667\",\n \"0.67871\",\n \"0.67811495\",\n \"0.6774042\",\n \"0.6770357\",\n \"0.67690766\",\n \"0.676824\",\n \"0.6758794\",\n \"0.6755805\",\n \"0.6754093\",\n \"0.67537636\",\n \"0.67452186\",\n \"0.6743714\",\n \"0.67366016\",\n \"0.6734711\",\n \"0.6730331\",\n \"0.671894\",\n \"0.67130643\",\n \"0.6701074\",\n \"0.6696187\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":18697,"cells":{"query":{"kind":"string","value":"Agent function that deletes a file in the storage."},"document":{"kind":"string","value":"def agent_delete(self, group, path, key):\n found = False\n for file_path in glob.glob('{0}/corr-{1}s'.format(path, group)):\n if key in file_path:\n os.remove(file_path)\n found = True\n break\n return found"},"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(self, filename, **kw):\n\n file_path = os.path.join(self.storage_path, filename)\n\n try:\n os.remove(file_path)\n except OSError:\n pass","def delete(self, filename):\n pass","def delete(self, host, file):","def delete_file(filename):\n\tprint client.file_delete(filename)","async def delete_file(location_id: LocationID, file_id: StorageFileID, user_id: UserID):","def delete(self, *args, **kwargs):\n self.file.storage.delete(self.file.name)\n super().delete(*args, **kwargs)","def delete(self, filename):\n raise NotImplementedError","def delete(self, remote):\n self.target.ttbd_iface_call(\"store\", \"file\", method = \"DELETE\",\n file_path = remote)","def flow_file_delete(sender, instance, **kwargs):\n if FLOWJS_REMOVE_FILES_ON_DELETE:\n try:\n default_storage.delete(instance.path)\n except NotImplementedError:\n pass","def delete(self):\n\n try:\n remove(self.file)\n except OSError:\n pass","def _delete(filename):\n return os.remove(filename)","def delete(self):\n if not pdbox._args.get(\"dryrun\"):\n result = execute(pdbox.dbx.files_delete_v2, self.path)\n pdbox.debug(\"Metadata response: %s\" % result.metadata)\n pdbox.info(\"Deleted %s\" % self.uri)","def remove(args):\n osf = _setup_osf(args)\n if osf.username is None or osf.password is None:\n sys.exit('To remove a file you need to provide a username and'\n ' password.')\n\n project = osf.project(args.project)\n\n storage, remote_path = split_storage(args.target)\n\n store = project.storage(storage)\n for f in store.files:\n if norm_remote_path(f.path) == remote_path:\n f.remove()","def delete_file(sender, instance, *args, **kwargs):\n if instance.file:\n _delete_file(instance.file.path)","def delete_file(self, lfile):\n raise NotImplementedError('delete_file')","def delete_file(file_id):\n file_obj = Data.objects.get(id=file_id)\n print(\"Removing file: \", file_obj.name)\n print(file_obj.file.path)\n file_dir = file_obj.file.path\n os.remove(file_dir)\n print(\"Done.\")","def do_destroy(self, arg):\n args = shlex.split(arg)\n stored_objects = models.storage.all()\n\n if self.basic_errs(args):\n '''check if instance exists'''\n instance = self.check_instance(args[0], args[1], stored_objects)\n if instance:\n \"\"\"delete from FileStorage.__objects\"\"\"\n del stored_objects[instance]\n \"\"\"overwrite the new data to file.json\"\"\"\n models.storage.save()","def delete(self, *route, **req_data):\n # Read the file ID from the request, with safety.\n try:\n file_id = UUID(req_data['file_id']).hex\n except ValueError:\n return Response(status='400 Bad Request')\n\n # Retrieve and delete the file.\n stored_files = StoredFile.collection()\n to_delete = stored_files.first(id=file_id)\n\n log_activity('%s deleted file %s'%(\n context.user.link, to_delete.filename\n ))\n\n stored_files.delete(to_delete)\n get_bucket().delete(to_delete.data_id)\n\n return Response(status='200 OK')","def delete_file(path):\n return files.delete_file(path)","def remove_file(self, path):\n pass","def _delete(self, remote_filename):\n\n file_id = self.get_file_id(remote_filename)\n if file_id is None:\n raise BackendException(\n 'File \"%s\" cannot be deleted: it does not exist' % (\n remote_filename))\n response = self.http_client.put(self.metadata_url + 'trash/' + file_id)\n response.raise_for_status()\n del self.names_to_ids[remote_filename]","def delete(self, args):\n try:\n assert len(args) > 0\n file_name = args[0]\n try:\n if should('Delete %s?' % file_name):\n self.s3.Object(self.bucket_name, file_name).load()\n self.s3.Object(self.bucket_name, file_name).delete()\n print('File %s deleted!' % file_name)\n except ClientError:\n print('File %s not found in bucket %s' % (file_name, self.bucket_name))\n except AssertionError:\n print('I need a file name!')","def delete_file(self, path):\n raise HTTPError(\n 501,\n \"Narrative deletion not implemented here. Deletion is handled elsewhere.\",\n )","def delete_file(mapper, connection, target):\n if target.filename and app.config['CLEANUP_FILES']:\n try:\n os.remove(join(app.config['FILE_PATH'], str(target.talk.id),\n str(target.version), target.filename))\n except OSError:\n # We don't care if wasn't deleted because it does not exist\n pass","def delete_file(self, filepath):\n self.ftp.delete(filepath)","def rm_file(file_):\n Path(file_).unlink(missing_ok=True)","def delete(self):\n request_data = request.get_json(force=True)\n current_path = self.get_current_path()\n file_name = request_data.get('file_name')\n\n if not file_name:\n abort(400, message=\"File name must not be empty!\")\n\n full_path = os.path.join(current_path, file_name)\n\n if not os.path.exists(full_path):\n abort(400, message=\"File was not found in current path!\")\n\n if not os.path.isfile(full_path):\n abort(400, message=\"File name is not a file!\")\n\n if not self.is_allowed(full_path):\n abort(403, message=\"You are not allowed to this path\")\n\n os.remove(full_path)\n\n return {\"message\": \"OK\"}","def flow_file_chunk_delete(sender, instance, **kwargs):\n instance.file.delete(False)","def test_file_deleted(self):\n try:\n with get_temp_file() as (fd, name):\n os.unlink(name)\n except Exception as err:\n self.fail('Failed with exception \"{}\"'.format(err))","def predio_delete(sender, instance, **kwargs):\n instance.dataFile.delete(False)","def delete(self):\n if os.path.exists(self.file_path):\n os.remove(self.file_path)","def delete(self, file_id: str):\n file_path = self._path_to_file(file_id)\n os.remove(file_path)\n del self.index[file_id]","def delete_file(client, file_id):\n\n try:\n client.file(file_id=file_id).delete()\n print(f\"File with {file_id} has been deleted\")\n return True\n\n except Exception as e:\n print(f\"an error has occurred: {e}\")\n return False","def delete_local_file(file_path):\r\n try:\r\n os.remove(file_path)\r\n except OSError as e:\r\n print(f\"Error deleting file {file_path}: {e}\")","def delete(self, filepath: str) -> None:\n if self.isfile(filepath):\n storage_services.delete(\n self._bucket_name, self._get_gcs_file_url(filepath))\n else:\n raise IOError('File does not exist: %s' % filepath)","def delete(self):\n\t\t#self.log.info(\"Deleting file {}\".format(self._filepath))\n\t\tos.remove(self._filepath)","def test_6d_delete_file(self):\n if (not GST.logged_in) or (not GST.data_testing_swift_mounted):\n raise unittest.SkipTest(\"Skipped for failed login or failed mounting container.\")\n elif not GST.deleting_data_test_ready:\n raise unittest.SkipTest(\"Skipped for failed to prepare deleting test.\")\n self.dismiss_dialogs()\n function = js_func[\"delete\"] % GST.gs_file_paths[\"file_to_delete_path\"]\n try:\n self.send_request(function, \"delete_data()\")\n except Exception as e:\n raise DeleteException(e.__str__()) \n try:\n response = self.get_response()\n assert \"Success\" in response\n self.refresh_page()\n except AssertionError:\n raise DeleteException(response)","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def _delete_file(self, path):\n if not self.mount():\n return False\n uri = self.path_to_uri(path)\n return self.gvfs.delete_file(uri)","def delete_file(self, path):\n return self.client._perform_empty(\n \"DELETE\", \"/projects/%s/managedfolders/%s/contents/%s\" % (self.project_key, self.odb_id, utils.quote(path)))","def delete_file(self, filename: str, directory: str = 'gcodes') -> Dict:\n raise NotImplementedError","def delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def tests_ti_file_delete_action(self):\n file = cast(File, self.ti_helper.create_indicator())\n action = 'traffic'\n indicator_data = {\n 'confidence': randint(0, 100),\n 'ip': self.ti_helper.rand_ip(),\n 'owner': self.owner,\n 'rating': randint(0, 5),\n }\n target = self.ti.address(**indicator_data)\n target.create()\n file.add_action(action, target)\n response = file.delete_action(action, target)\n assert response.ok\n target.delete()","def node_file_remove(ctx, filename):\n try:\n ctx.obj['node'].remove_file(filename)\n except TimeoutError as e:\n logger.error('Error: %s' % e)\n exit(1)","def delete(self, filename):\n try:\n self.storage.delete(filename)\n return {\n 'filename': filename,\n 'message': 'The file was deleted with success'\n }\n except FileNotFoundError:\n abort(404, message='File %s does not exist' % filename)\n except BaseException:\n abort(500, message='Failed to delete the file ' + filename)\n LOGGER.error('A generic exception has occurred.', exc_info=True)","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete_file(input_fn):\r\n if os.path.isfile(input_fn):\r\n os.remove(input_fn)","def gcloud_delete_file(file_name, gcloud_bucket_name):\n bucket = gce_storage_client.get_bucket(gcloud_bucket_name)\n blob = bucket.blob(file_name)\n\n blob.delete()","def delete_file(filename):\n if os.path.isfile(filename):\n return os.remove(filename)","def delete_file(sender, instance, *args, **kwargs):\n if instance.photo:\n _delete_file(instance.photo.path)","def delete_file(self, name):\n del self.files[name]","def delete_file(sender, instance, *args, **kwargs):\n if instance.image:\n _delete_file(instance.image.path)","def delete_file(self, path):\n if not path_exists(path, self._store_folder):\n raise NotFoundException(\"\")\n os.remove(path)","def delete(self, filename, threadID):\n self.lock.acquire()\n removed_file = self.files_on_disk.pop(filename)\n\n # remove file from the directory\n if not os.path.exists(\".storage/\" + filename):\n self.lock.release()\n return \"ERROR: NO SUCH FILE\\n\"\n else:\n os.remove(\".storage/\" + filename)\n i = 0\n j = 0\n while(i<self.size and j<removed_file.num_blocks):\n if(self.disk_mem[i]==removed_file.letter):\n self.disk_mem[i] = \".\"\n j+=1\n i += 1\n print(\"[thread %d] Deleted %s file '%c' (deallocated %d blocks)\" %\n (threadID, removed_file.name, removed_file.letter, removed_file.num_blocks))\n self.show(threadID)\n self.lock.release()\n return \"ACK\\n\"","def delete(self, store, uuid):\n\n session = get_session()\n session.begin()\n\n stored_file = self._retrieve(store.object_type, uuid)\n\n try:\n session.delete(stored_file)\n session.commit()\n finally:\n session.close()","def delete_file(file: str) -> None:\n\tuux.show_info(\"Deleting \" + file)\n\n\tif not os.path.exists(file):\n\t\t# Files does not exist\n\t\treturn\n\n\tos.remove(file)","def safe_delete(self, filename):\n try:\n os.remove(filename)\n except OSError:\n pass","def sorl_delete(**kwargs):\n from sorl.thumbnail import delete\n delete(kwargs['file'])","def delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete():","def delete(filename):\n storeapps = APP.config[\"storage\"]\n extension = os.path.basename(filename).split(\".\")[-1].upper()\n dirname = \".\".join(os.path.basename(filename).split(\".\")[:-1])\n directory = os.path.join(storeapps, extension, dirname)\n\n try:\n directory = directory.encode(\"utf-8\")\n except UnicodeDecodeError:\n pass\n\n if os.path.isdir(directory):\n shutil.rmtree(directory)\n if os.path.isdir(directory):\n return \"Unable to remove application (check server logs): %s\" % (filename), 500\n return \"Removed: %s\" % (filename), 200\n\n return \"File not found: %s\" % (filename), 404","def file_delete(self, path):\n params = {'root': self.session.root, 'path': format_path(path)}\n\n url, params, headers = self.request(\"/fileops/delete\", params)\n\n return self.rest_client.POST(url, params, headers)","def delete_file(va_bucket, uuid):\n key = va_bucket.get_key(uuid)\n print(\" {0} deleted from VA\".format(uuid))\n va_bucket.delete_key(uuid)","def delete_file(name):\n subprocess.check_output(cmd_preamble + [\"rm\", name])","def delete_file(self):\n if (not self.exists()):\n raise IOError(\"File at '{}' does not exist.\".format(self.location))\n os.remove(self.location)","def delete_file(self, name, container):\r\n try:\r\n cnt = self.get_container(container)\r\n obj = cnt.get_object(name)\r\n obj.delete()\r\n return True\r\n except:\r\n return False","def _delete_datafile(sender, instance, **kwargs):\n instance.delete_datafile(save_instance=False)","def test_delete_with_file(self):\n langpack = LangPack.objects.create(version='0.1')\n file_path = langpack.file_path\n with public_storage.open(file_path, 'w') as f:\n f.write('sample data\\n')\n assert public_storage.exists(file_path)\n try:\n langpack.delete()\n assert not public_storage.exists(file_path)\n finally:\n if public_storage.exists(file_path):\n public_storage.delete(file_path)","def delete_file(request, page_id, file_id):\n record = models.FileStore.get_by_id(int(file_id))\n if record:\n if not record.user_can_write(request.profile):\n return utility.forbidden(request)\n\n record.delete()\n return utility.edit_updated_page(page_id, tab_name='files')\n else:\n return utility.page_not_found(request)","def test_delete_file(self):\n # put file\n self.prepare_uploads()\n backend = BackendS3(**self.config)\n uploads = self.upload_path\n src = os.path.join(uploads, 'test.tar.gz')\n\n id1 = utils.generate_id('test.tar.gz')\n backend.put(src, id1)\n\n # regression testing (only delete what requested)\n id2 = id1.split('-')\n id2[4] += 'ZZZ'\n id2 = '-'.join(id2)\n\n backend.put(src, id1, True)\n backend.put_variant(src, id1, 'demo.txt')\n backend.put(src, id2, True)\n backend.delete(id1)\n\n path1 = '/'.join(backend.id_to_path(id1)) + '/test.tar.gz'\n path2 = '/'.join(backend.id_to_path(id1)) + '/demo.txt'\n self.assertFalse(backend.exists(path1))\n self.assertFalse(backend.exists(path2))\n\n # assume only proper file deleted\n path3 = '/'.join(backend.id_to_path(id2)) + '/test.tar.gz'\n self.assertTrue(backend.exists(path3))","def rm(self, path):\n try:\n basedir, item = os.path.split(path)\n postdata = codecs.encode(json.dumps({ 'baseDir': basedir, 'items': [ item ] }), 'utf-8')\n self._urlopen('/api/fileops/delete', postdata).read()\n except HTTPError as err:\n raise RuntimeError(\"Unable to delete '{}'\".format(path))","def delete_file(sender, instance, **kwargs):\n if bool(instance.exam_file): # check if exam file exists\n try:\n instance.exam_file.delete()\n except OSError:\n pass\n # if exam file has already been deleted, then do nothing and continue\n # with deleting the exam model","def delete_file(self, msg_parameters):\n reg = self.get_regex_file_name(msg_parameters[0])\n for file_part in self.files.keys():\n if reg.search(file_part) is not None:\n # remove from computer\n os.remove(self.files[file_part])\n # do not save that the data server has it\n del self.files[file_part]","def delete( self ):\n if os.path.exists(self.filename):\n os.remove(self.filename)","def delete_file(self, filename=None):\n return self._service.delete_object(self._datasets_id, filename)","def delete_file(self, path, prefixed_path, source_storage):\n if isinstance(self.storage, SwiftclientStorage):\n if self.storage.exists(prefixed_path):\n try:\n etag = self.storage._get_cloud_obj(prefixed_path).etag\n digest = \"{0}\".format(hashlib.md5(source_storage.open(path).read()).hexdigest())\n print etag, digest\n if etag == digest:\n self.log(u\"Skipping '{0}' (not modified based on file hash)\".format(path))\n return False\n except:\n raise\n return super(Command, self).delete_file(path, prefixed_path, source_storage)","def do_destroy(self, arg):\n obj = self.verify(arg, 2)\n if obj:\n del storage.all()[obj]\n storage.save()","def Delete_File(self,txn,filename):\n opid = self.new_opid()\n xaction = DeleteFile_Operation(os.path.join(self.home,filename),opid)\n self._add_operation(txn,xaction)","def delete_file(self, instance, file, where):\n\n instance = self.get_instance(instance)\n try:\n if instance.get('address'):\n username = instance.get('address') + \"@\" + instance.get('credentials').get('username')\n key = instance.get('credentials').get('publickey')\n subprocess.check_output([\"ssh\", key, username, 'rm', self.default_path_aws + where + file])\n else:\n username = 'ubuntu@' + instance.get('credentials').get('EC2_ACCESS_ID')\n key = instance.get('credentials').get('EC2_SECRET_KEY')\n # output = os.popen(\"ls\"+ \" | \" + \"ssh\"+ \" -i \"+ key +\" \"+ username).read()\n subprocess.check_output([\"ssh\", \"-i\", key, username, 'rm', self.default_path_aws + where + file])\n return \"Success to delete the file \" + file + \" from \" + self.default_path_aws + where\n except:\n return \"Fail to access the instance\"","def delete(self, resource_id, file_id):\n d = Deposition.get(resource_id, user=current_user)\n\n # Sort files raise ForbiddenAction if not authorized\n df = d.remove_file(file_id)\n if df is None:\n abort(404, message=\"File does not exist\", status=404)\n df.delete()\n d.save()\n return \"\", 204","def test_delete(client: FlaskClient):\n file = get_example_file(ExampleFileType.Txt)\n response_upload = util.upload_file(client, DEFAULT_USER, file)\n response_delete = util.delete_file(client, DEFAULT_USER, response_upload.json[\"id\"])\n assert response_delete.status == \"204 NO CONTENT\"\n response_download = util.download_file(\n client, DEFAULT_USER, response_upload.json[\"id\"]\n )\n assert response_download.status == \"404 NOT FOUND\"","def delete_file(self, filename):\n if not filename in self.files:\n raise IOError('File %s Not Found' % filename)\n\n for nodename in self.files[filename]:\n node = self.datanodes[nodename]\n node.delete_file(filename)\n del self.files[filename]\n logging.info('file %s deleted' % filename)","def delete_data_file(path):\n cprint(f\"### Function Name:-> {inspect.stack()[0][3]} ###\", 'yellow', 'on_grey', attrs=['bold'])\n try:\n os.remove(path)\n except FileNotFoundError:\n pass","def delete_file(self, timeout=None, **kwargs):\n # type: (Optional[int], Optional[Any]) -> None\n try:\n self._client.file.delete(timeout=timeout, **kwargs)\n except StorageErrorException as error:\n process_storage_error(error)","def test_cannot_remove_file(self):\n self.api.remove_file('/some-fake/path/to-delete-file.json')","def deleteSingleFile(filename):\n os.popen('rm {}'.format(filename))","def delete(self):\n os.remove(self.file_path)\n super(VideoFile, self).delete()","def delete_file(_oid, attachmentId=None):\n md = Metadata.objects.get_or_404(pk=_oid)\n attachment = ''\n test_upload_path_prefix = \"uploadedfiles\"\n test_environment = False\n\n username = _authenticate_user_from_session(request)\n\n if username:\n try:\n try:\n md = Metadata.objects.get(id=_oid)\n \n try:\n # if developing locally we'll also want to remove file\n url = filter(\n lambda a: str(a.id) == attachmentId, md.attachments\n ).pop().url\n if str(os.environ['FLASKCONFIG']) == 'testing' or str(os.environ['FLASKCONFIG']) == 'development':\n test_environment = True\n os.remove(\n os.path.join(\n app.config['UPLOADS_DEFAULT_DEST'],\n test_upload_path_prefix,\n _oid,\n os.path.basename(url)\n )\n )\n else:\n os.remove(\n os.path.join(\n app.config['UPLOADS_DEFAULT_DEST'],\n _oid,\n os.path.basename(url)\n )\n )\n except Exception:\n #Throw exception specific for test or non-test enviroment\n if test_environment:\n file_path = app.config['UPLOADS_DEFAULT_DEST'] + \"/\" + test_upload_path_prefix + \"/\" + _oid + \"/\" + os.path.basename(url)\n else:\n file_path = app.config['UPLOADS_DEFAULT_DEST'] + \"/\" + _oid + \"/\" + os.path.basename(url)\n\n print \"There was a problem deleting the file! Tried to reach path: \" + file_path \n \n # don't need to save after this since we're updating existing\n Metadata.objects(id=_oid).update_one(\n pull__attachments__id=attachmentId\n )\n \n md = Metadata.objects.get(id=_oid)\n \n # we'll just go ahead and not care if it doesn't exist\n except ValueError:\n pass\n\n\n except KeyError:\n try:\n keys = request.json.keys()\n keys_str = ', '.join(keys)\n except Exception as e:\n print \"Error: \" + str(e)\n return Response(\"Server error deleting file...\", status=500)\n\n return jsonify(\n {\n 'message':\n 'Key(s) ' + keys_str + ' not recognized. ' +\n 'Must contain \\'attachment\\''\n },\n status=400\n )\n\n return jsonify(dict(message=attachment + ' successfully (at/de)tached!', record=md))\n \n else:\n return Response('Bad or missing session id.', status=401)","def test_rm(self, client, remote_mock_dir):\n\n file_path = posixpath.join(remote_mock_dir, \"test.txt\")\n assert client.exists(file_path)\n\n with HdfsHook() as hook:\n hook.rm(file_path)\n\n assert not client.exists(file_path)","def storage_delete_file(self, group='', key=''):\n deleted = False\n if key not in [\"default-logo.png\", \"default-picture.png\"]:\n if self.config['type'] == 's3':\n s3_files = self.s3.Bucket(self.bucket)\n for _file in s3_files.objects.all():\n if _file.key == 'corr-{0}s/{1}'.format(group, key):\n _file.delete()\n print(\"File deleted!\")\n deleted = True\n break\n elif self.config['type'] == 'filesystem':\n found = self.agent_delete(group, self.storage_path, key)\n if found:\n deleted = True\n if not deleted:\n print(\"File not deleted\")\n return deleted","def delete_file(filename, sudo=True):\n LOG.info(\"Deleting file {}\".format(filename))\n cmd = \"rm {}\".format(filename)\n _exec_cmd(cmd=cmd, sudo=sudo, fail_ok=False)","def delFile(self, file_name):\n ret = self.rest.delete(self.ngx_server, self.getUrl() + '/' + file_name, {}, [200, 404])\n if ret == False:\n self.logger.error('delete file:%s from tfs failed.' % file_name)\n raise Exception, 'delete file:%s from tfs failed.' % file_name\n self.logger.info('Delete Tfs file: %s' % file_name)\n return True","def delete(self, src):\n\n if self.noop:\n logger.info(\"No-Op Delete: %s.tar\" % self.bucket + src)\n else:\n logger.info(\"Trying to delete %s.tar\" % self.bucket + src)\n self.client.delete(self.bucket + src + \".tar\")","def delete_file_from_datastore(content, datastore_name, path):\n try:\n datastore = get_obj(content, [vim.Datastore], datastore_name)\n datastore.browser.DeleteFile('[{0}] {1}'.format(datastore_name, path))\n except vim.fault.FileNotFound as e:\n return e\n return None","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.file:\n if os.path.isfile(instance.file.path):\n os.remove(instance.file.path)","def delete(self):\r\n if self.provider.readonly:\r\n raise DAVError(HTTP_FORBIDDEN)\r\n\r\n self.provider.cache_fs.remove(self.path)\r\n if self.nibbler.find(self.path):\r\n self.nibbler.remove_file(self.path)\r\n\r\n self.removeAllProperties(True)\r\n self.removeAllLocks(True)","def delete_file(filename: str):\n\t\tif filename == \"ALL\":\n\t\t\tfor file in os.listdir(\"data/music/\"):\n\t\t\t\tdeleted = False\n\t\t\t\twhile not deleted:\n\t\t\t\t\ttry:\n\t\t\t\t\t\tos.remove(f\"data/music/{file}\")\n\t\t\t\t\t\tdeleted = True\n\t\t\t\t\texcept Exception as e:\n\t\t\t\t\t\tprint(\"Not removed, waiting 1 second...\")\n\t\t\t\t\t\tasyncio.sleep(1)\n\t\telse:\n\t\t\tprint(\"File--: \", filename)","def delete_file(self, repo, file_name):\n DataHubManager.has_repo_file_privilege(\n self.username, self.repo_base, repo, 'write')\n\n file_path = user_data_path(self.repo_base, repo, file_name)\n os.remove(file_path)","def delete_file(fileName):\n os.remove(fileName)\n print (\"Deleteing file: \" + str(fileName))\n write_log()\n read_log()","def auto_delete_file_on_delete(sender, instance, **kwargs):\n\n if instance.file:\n if os.path.isfile(instance.file.path):\n os.remove(instance.file.path)"],"string":"[\n \"def delete(self, filename, **kw):\\n\\n file_path = os.path.join(self.storage_path, filename)\\n\\n try:\\n os.remove(file_path)\\n except OSError:\\n pass\",\n \"def delete(self, filename):\\n pass\",\n \"def delete(self, host, file):\",\n \"def delete_file(filename):\\n\\tprint client.file_delete(filename)\",\n \"async def delete_file(location_id: LocationID, file_id: StorageFileID, user_id: UserID):\",\n \"def delete(self, *args, **kwargs):\\n self.file.storage.delete(self.file.name)\\n super().delete(*args, **kwargs)\",\n \"def delete(self, filename):\\n raise NotImplementedError\",\n \"def delete(self, remote):\\n self.target.ttbd_iface_call(\\\"store\\\", \\\"file\\\", method = \\\"DELETE\\\",\\n file_path = remote)\",\n \"def flow_file_delete(sender, instance, **kwargs):\\n if FLOWJS_REMOVE_FILES_ON_DELETE:\\n try:\\n default_storage.delete(instance.path)\\n except NotImplementedError:\\n pass\",\n \"def delete(self):\\n\\n try:\\n remove(self.file)\\n except OSError:\\n pass\",\n \"def _delete(filename):\\n return os.remove(filename)\",\n \"def delete(self):\\n if not pdbox._args.get(\\\"dryrun\\\"):\\n result = execute(pdbox.dbx.files_delete_v2, self.path)\\n pdbox.debug(\\\"Metadata response: %s\\\" % result.metadata)\\n pdbox.info(\\\"Deleted %s\\\" % self.uri)\",\n \"def remove(args):\\n osf = _setup_osf(args)\\n if osf.username is None or osf.password is None:\\n sys.exit('To remove a file you need to provide a username and'\\n ' password.')\\n\\n project = osf.project(args.project)\\n\\n storage, remote_path = split_storage(args.target)\\n\\n store = project.storage(storage)\\n for f in store.files:\\n if norm_remote_path(f.path) == remote_path:\\n f.remove()\",\n \"def delete_file(sender, instance, *args, **kwargs):\\n if instance.file:\\n _delete_file(instance.file.path)\",\n \"def delete_file(self, lfile):\\n raise NotImplementedError('delete_file')\",\n \"def delete_file(file_id):\\n file_obj = Data.objects.get(id=file_id)\\n print(\\\"Removing file: \\\", file_obj.name)\\n print(file_obj.file.path)\\n file_dir = file_obj.file.path\\n os.remove(file_dir)\\n print(\\\"Done.\\\")\",\n \"def do_destroy(self, arg):\\n args = shlex.split(arg)\\n stored_objects = models.storage.all()\\n\\n if self.basic_errs(args):\\n '''check if instance exists'''\\n instance = self.check_instance(args[0], args[1], stored_objects)\\n if instance:\\n \\\"\\\"\\\"delete from FileStorage.__objects\\\"\\\"\\\"\\n del stored_objects[instance]\\n \\\"\\\"\\\"overwrite the new data to file.json\\\"\\\"\\\"\\n models.storage.save()\",\n \"def delete(self, *route, **req_data):\\n # Read the file ID from the request, with safety.\\n try:\\n file_id = UUID(req_data['file_id']).hex\\n except ValueError:\\n return Response(status='400 Bad Request')\\n\\n # Retrieve and delete the file.\\n stored_files = StoredFile.collection()\\n to_delete = stored_files.first(id=file_id)\\n\\n log_activity('%s deleted file %s'%(\\n context.user.link, to_delete.filename\\n ))\\n\\n stored_files.delete(to_delete)\\n get_bucket().delete(to_delete.data_id)\\n\\n return Response(status='200 OK')\",\n \"def delete_file(path):\\n return files.delete_file(path)\",\n \"def remove_file(self, path):\\n pass\",\n \"def _delete(self, remote_filename):\\n\\n file_id = self.get_file_id(remote_filename)\\n if file_id is None:\\n raise BackendException(\\n 'File \\\"%s\\\" cannot be deleted: it does not exist' % (\\n remote_filename))\\n response = self.http_client.put(self.metadata_url + 'trash/' + file_id)\\n response.raise_for_status()\\n del self.names_to_ids[remote_filename]\",\n \"def delete(self, args):\\n try:\\n assert len(args) > 0\\n file_name = args[0]\\n try:\\n if should('Delete %s?' % file_name):\\n self.s3.Object(self.bucket_name, file_name).load()\\n self.s3.Object(self.bucket_name, file_name).delete()\\n print('File %s deleted!' % file_name)\\n except ClientError:\\n print('File %s not found in bucket %s' % (file_name, self.bucket_name))\\n except AssertionError:\\n print('I need a file name!')\",\n \"def delete_file(self, path):\\n raise HTTPError(\\n 501,\\n \\\"Narrative deletion not implemented here. Deletion is handled elsewhere.\\\",\\n )\",\n \"def delete_file(mapper, connection, target):\\n if target.filename and app.config['CLEANUP_FILES']:\\n try:\\n os.remove(join(app.config['FILE_PATH'], str(target.talk.id),\\n str(target.version), target.filename))\\n except OSError:\\n # We don't care if wasn't deleted because it does not exist\\n pass\",\n \"def delete_file(self, filepath):\\n self.ftp.delete(filepath)\",\n \"def rm_file(file_):\\n Path(file_).unlink(missing_ok=True)\",\n \"def delete(self):\\n request_data = request.get_json(force=True)\\n current_path = self.get_current_path()\\n file_name = request_data.get('file_name')\\n\\n if not file_name:\\n abort(400, message=\\\"File name must not be empty!\\\")\\n\\n full_path = os.path.join(current_path, file_name)\\n\\n if not os.path.exists(full_path):\\n abort(400, message=\\\"File was not found in current path!\\\")\\n\\n if not os.path.isfile(full_path):\\n abort(400, message=\\\"File name is not a file!\\\")\\n\\n if not self.is_allowed(full_path):\\n abort(403, message=\\\"You are not allowed to this path\\\")\\n\\n os.remove(full_path)\\n\\n return {\\\"message\\\": \\\"OK\\\"}\",\n \"def flow_file_chunk_delete(sender, instance, **kwargs):\\n instance.file.delete(False)\",\n \"def test_file_deleted(self):\\n try:\\n with get_temp_file() as (fd, name):\\n os.unlink(name)\\n except Exception as err:\\n self.fail('Failed with exception \\\"{}\\\"'.format(err))\",\n \"def predio_delete(sender, instance, **kwargs):\\n instance.dataFile.delete(False)\",\n \"def delete(self):\\n if os.path.exists(self.file_path):\\n os.remove(self.file_path)\",\n \"def delete(self, file_id: str):\\n file_path = self._path_to_file(file_id)\\n os.remove(file_path)\\n del self.index[file_id]\",\n \"def delete_file(client, file_id):\\n\\n try:\\n client.file(file_id=file_id).delete()\\n print(f\\\"File with {file_id} has been deleted\\\")\\n return True\\n\\n except Exception as e:\\n print(f\\\"an error has occurred: {e}\\\")\\n return False\",\n \"def delete_local_file(file_path):\\r\\n try:\\r\\n os.remove(file_path)\\r\\n except OSError as e:\\r\\n print(f\\\"Error deleting file {file_path}: {e}\\\")\",\n \"def delete(self, filepath: str) -> None:\\n if self.isfile(filepath):\\n storage_services.delete(\\n self._bucket_name, self._get_gcs_file_url(filepath))\\n else:\\n raise IOError('File does not exist: %s' % filepath)\",\n \"def delete(self):\\n\\t\\t#self.log.info(\\\"Deleting file {}\\\".format(self._filepath))\\n\\t\\tos.remove(self._filepath)\",\n \"def test_6d_delete_file(self):\\n if (not GST.logged_in) or (not GST.data_testing_swift_mounted):\\n raise unittest.SkipTest(\\\"Skipped for failed login or failed mounting container.\\\")\\n elif not GST.deleting_data_test_ready:\\n raise unittest.SkipTest(\\\"Skipped for failed to prepare deleting test.\\\")\\n self.dismiss_dialogs()\\n function = js_func[\\\"delete\\\"] % GST.gs_file_paths[\\\"file_to_delete_path\\\"]\\n try:\\n self.send_request(function, \\\"delete_data()\\\")\\n except Exception as e:\\n raise DeleteException(e.__str__()) \\n try:\\n response = self.get_response()\\n assert \\\"Success\\\" in response\\n self.refresh_page()\\n except AssertionError:\\n raise DeleteException(response)\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def _delete_file(self, path):\\n if not self.mount():\\n return False\\n uri = self.path_to_uri(path)\\n return self.gvfs.delete_file(uri)\",\n \"def delete_file(self, path):\\n return self.client._perform_empty(\\n \\\"DELETE\\\", \\\"/projects/%s/managedfolders/%s/contents/%s\\\" % (self.project_key, self.odb_id, utils.quote(path)))\",\n \"def delete_file(self, filename: str, directory: str = 'gcodes') -> Dict:\\n raise NotImplementedError\",\n \"def delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def tests_ti_file_delete_action(self):\\n file = cast(File, self.ti_helper.create_indicator())\\n action = 'traffic'\\n indicator_data = {\\n 'confidence': randint(0, 100),\\n 'ip': self.ti_helper.rand_ip(),\\n 'owner': self.owner,\\n 'rating': randint(0, 5),\\n }\\n target = self.ti.address(**indicator_data)\\n target.create()\\n file.add_action(action, target)\\n response = file.delete_action(action, target)\\n assert response.ok\\n target.delete()\",\n \"def node_file_remove(ctx, filename):\\n try:\\n ctx.obj['node'].remove_file(filename)\\n except TimeoutError as e:\\n logger.error('Error: %s' % e)\\n exit(1)\",\n \"def delete(self, filename):\\n try:\\n self.storage.delete(filename)\\n return {\\n 'filename': filename,\\n 'message': 'The file was deleted with success'\\n }\\n except FileNotFoundError:\\n abort(404, message='File %s does not exist' % filename)\\n except BaseException:\\n abort(500, message='Failed to delete the file ' + filename)\\n LOGGER.error('A generic exception has occurred.', exc_info=True)\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete_file(input_fn):\\r\\n if os.path.isfile(input_fn):\\r\\n os.remove(input_fn)\",\n \"def gcloud_delete_file(file_name, gcloud_bucket_name):\\n bucket = gce_storage_client.get_bucket(gcloud_bucket_name)\\n blob = bucket.blob(file_name)\\n\\n blob.delete()\",\n \"def delete_file(filename):\\n if os.path.isfile(filename):\\n return os.remove(filename)\",\n \"def delete_file(sender, instance, *args, **kwargs):\\n if instance.photo:\\n _delete_file(instance.photo.path)\",\n \"def delete_file(self, name):\\n del self.files[name]\",\n \"def delete_file(sender, instance, *args, **kwargs):\\n if instance.image:\\n _delete_file(instance.image.path)\",\n \"def delete_file(self, path):\\n if not path_exists(path, self._store_folder):\\n raise NotFoundException(\\\"\\\")\\n os.remove(path)\",\n \"def delete(self, filename, threadID):\\n self.lock.acquire()\\n removed_file = self.files_on_disk.pop(filename)\\n\\n # remove file from the directory\\n if not os.path.exists(\\\".storage/\\\" + filename):\\n self.lock.release()\\n return \\\"ERROR: NO SUCH FILE\\\\n\\\"\\n else:\\n os.remove(\\\".storage/\\\" + filename)\\n i = 0\\n j = 0\\n while(i<self.size and j<removed_file.num_blocks):\\n if(self.disk_mem[i]==removed_file.letter):\\n self.disk_mem[i] = \\\".\\\"\\n j+=1\\n i += 1\\n print(\\\"[thread %d] Deleted %s file '%c' (deallocated %d blocks)\\\" %\\n (threadID, removed_file.name, removed_file.letter, removed_file.num_blocks))\\n self.show(threadID)\\n self.lock.release()\\n return \\\"ACK\\\\n\\\"\",\n \"def delete(self, store, uuid):\\n\\n session = get_session()\\n session.begin()\\n\\n stored_file = self._retrieve(store.object_type, uuid)\\n\\n try:\\n session.delete(stored_file)\\n session.commit()\\n finally:\\n session.close()\",\n \"def delete_file(file: str) -> None:\\n\\tuux.show_info(\\\"Deleting \\\" + file)\\n\\n\\tif not os.path.exists(file):\\n\\t\\t# Files does not exist\\n\\t\\treturn\\n\\n\\tos.remove(file)\",\n \"def safe_delete(self, filename):\\n try:\\n os.remove(filename)\\n except OSError:\\n pass\",\n \"def sorl_delete(**kwargs):\\n from sorl.thumbnail import delete\\n delete(kwargs['file'])\",\n \"def delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete():\",\n \"def delete(filename):\\n storeapps = APP.config[\\\"storage\\\"]\\n extension = os.path.basename(filename).split(\\\".\\\")[-1].upper()\\n dirname = \\\".\\\".join(os.path.basename(filename).split(\\\".\\\")[:-1])\\n directory = os.path.join(storeapps, extension, dirname)\\n\\n try:\\n directory = directory.encode(\\\"utf-8\\\")\\n except UnicodeDecodeError:\\n pass\\n\\n if os.path.isdir(directory):\\n shutil.rmtree(directory)\\n if os.path.isdir(directory):\\n return \\\"Unable to remove application (check server logs): %s\\\" % (filename), 500\\n return \\\"Removed: %s\\\" % (filename), 200\\n\\n return \\\"File not found: %s\\\" % (filename), 404\",\n \"def file_delete(self, path):\\n params = {'root': self.session.root, 'path': format_path(path)}\\n\\n url, params, headers = self.request(\\\"/fileops/delete\\\", params)\\n\\n return self.rest_client.POST(url, params, headers)\",\n \"def delete_file(va_bucket, uuid):\\n key = va_bucket.get_key(uuid)\\n print(\\\" {0} deleted from VA\\\".format(uuid))\\n va_bucket.delete_key(uuid)\",\n \"def delete_file(name):\\n subprocess.check_output(cmd_preamble + [\\\"rm\\\", name])\",\n \"def delete_file(self):\\n if (not self.exists()):\\n raise IOError(\\\"File at '{}' does not exist.\\\".format(self.location))\\n os.remove(self.location)\",\n \"def delete_file(self, name, container):\\r\\n try:\\r\\n cnt = self.get_container(container)\\r\\n obj = cnt.get_object(name)\\r\\n obj.delete()\\r\\n return True\\r\\n except:\\r\\n return False\",\n \"def _delete_datafile(sender, instance, **kwargs):\\n instance.delete_datafile(save_instance=False)\",\n \"def test_delete_with_file(self):\\n langpack = LangPack.objects.create(version='0.1')\\n file_path = langpack.file_path\\n with public_storage.open(file_path, 'w') as f:\\n f.write('sample data\\\\n')\\n assert public_storage.exists(file_path)\\n try:\\n langpack.delete()\\n assert not public_storage.exists(file_path)\\n finally:\\n if public_storage.exists(file_path):\\n public_storage.delete(file_path)\",\n \"def delete_file(request, page_id, file_id):\\n record = models.FileStore.get_by_id(int(file_id))\\n if record:\\n if not record.user_can_write(request.profile):\\n return utility.forbidden(request)\\n\\n record.delete()\\n return utility.edit_updated_page(page_id, tab_name='files')\\n else:\\n return utility.page_not_found(request)\",\n \"def test_delete_file(self):\\n # put file\\n self.prepare_uploads()\\n backend = BackendS3(**self.config)\\n uploads = self.upload_path\\n src = os.path.join(uploads, 'test.tar.gz')\\n\\n id1 = utils.generate_id('test.tar.gz')\\n backend.put(src, id1)\\n\\n # regression testing (only delete what requested)\\n id2 = id1.split('-')\\n id2[4] += 'ZZZ'\\n id2 = '-'.join(id2)\\n\\n backend.put(src, id1, True)\\n backend.put_variant(src, id1, 'demo.txt')\\n backend.put(src, id2, True)\\n backend.delete(id1)\\n\\n path1 = '/'.join(backend.id_to_path(id1)) + '/test.tar.gz'\\n path2 = '/'.join(backend.id_to_path(id1)) + '/demo.txt'\\n self.assertFalse(backend.exists(path1))\\n self.assertFalse(backend.exists(path2))\\n\\n # assume only proper file deleted\\n path3 = '/'.join(backend.id_to_path(id2)) + '/test.tar.gz'\\n self.assertTrue(backend.exists(path3))\",\n \"def rm(self, path):\\n try:\\n basedir, item = os.path.split(path)\\n postdata = codecs.encode(json.dumps({ 'baseDir': basedir, 'items': [ item ] }), 'utf-8')\\n self._urlopen('/api/fileops/delete', postdata).read()\\n except HTTPError as err:\\n raise RuntimeError(\\\"Unable to delete '{}'\\\".format(path))\",\n \"def delete_file(sender, instance, **kwargs):\\n if bool(instance.exam_file): # check if exam file exists\\n try:\\n instance.exam_file.delete()\\n except OSError:\\n pass\\n # if exam file has already been deleted, then do nothing and continue\\n # with deleting the exam model\",\n \"def delete_file(self, msg_parameters):\\n reg = self.get_regex_file_name(msg_parameters[0])\\n for file_part in self.files.keys():\\n if reg.search(file_part) is not None:\\n # remove from computer\\n os.remove(self.files[file_part])\\n # do not save that the data server has it\\n del self.files[file_part]\",\n \"def delete( self ):\\n if os.path.exists(self.filename):\\n os.remove(self.filename)\",\n \"def delete_file(self, filename=None):\\n return self._service.delete_object(self._datasets_id, filename)\",\n \"def delete_file(self, path, prefixed_path, source_storage):\\n if isinstance(self.storage, SwiftclientStorage):\\n if self.storage.exists(prefixed_path):\\n try:\\n etag = self.storage._get_cloud_obj(prefixed_path).etag\\n digest = \\\"{0}\\\".format(hashlib.md5(source_storage.open(path).read()).hexdigest())\\n print etag, digest\\n if etag == digest:\\n self.log(u\\\"Skipping '{0}' (not modified based on file hash)\\\".format(path))\\n return False\\n except:\\n raise\\n return super(Command, self).delete_file(path, prefixed_path, source_storage)\",\n \"def do_destroy(self, arg):\\n obj = self.verify(arg, 2)\\n if obj:\\n del storage.all()[obj]\\n storage.save()\",\n \"def Delete_File(self,txn,filename):\\n opid = self.new_opid()\\n xaction = DeleteFile_Operation(os.path.join(self.home,filename),opid)\\n self._add_operation(txn,xaction)\",\n \"def delete_file(self, instance, file, where):\\n\\n instance = self.get_instance(instance)\\n try:\\n if instance.get('address'):\\n username = instance.get('address') + \\\"@\\\" + instance.get('credentials').get('username')\\n key = instance.get('credentials').get('publickey')\\n subprocess.check_output([\\\"ssh\\\", key, username, 'rm', self.default_path_aws + where + file])\\n else:\\n username = 'ubuntu@' + instance.get('credentials').get('EC2_ACCESS_ID')\\n key = instance.get('credentials').get('EC2_SECRET_KEY')\\n # output = os.popen(\\\"ls\\\"+ \\\" | \\\" + \\\"ssh\\\"+ \\\" -i \\\"+ key +\\\" \\\"+ username).read()\\n subprocess.check_output([\\\"ssh\\\", \\\"-i\\\", key, username, 'rm', self.default_path_aws + where + file])\\n return \\\"Success to delete the file \\\" + file + \\\" from \\\" + self.default_path_aws + where\\n except:\\n return \\\"Fail to access the instance\\\"\",\n \"def delete(self, resource_id, file_id):\\n d = Deposition.get(resource_id, user=current_user)\\n\\n # Sort files raise ForbiddenAction if not authorized\\n df = d.remove_file(file_id)\\n if df is None:\\n abort(404, message=\\\"File does not exist\\\", status=404)\\n df.delete()\\n d.save()\\n return \\\"\\\", 204\",\n \"def test_delete(client: FlaskClient):\\n file = get_example_file(ExampleFileType.Txt)\\n response_upload = util.upload_file(client, DEFAULT_USER, file)\\n response_delete = util.delete_file(client, DEFAULT_USER, response_upload.json[\\\"id\\\"])\\n assert response_delete.status == \\\"204 NO CONTENT\\\"\\n response_download = util.download_file(\\n client, DEFAULT_USER, response_upload.json[\\\"id\\\"]\\n )\\n assert response_download.status == \\\"404 NOT FOUND\\\"\",\n \"def delete_file(self, filename):\\n if not filename in self.files:\\n raise IOError('File %s Not Found' % filename)\\n\\n for nodename in self.files[filename]:\\n node = self.datanodes[nodename]\\n node.delete_file(filename)\\n del self.files[filename]\\n logging.info('file %s deleted' % filename)\",\n \"def delete_data_file(path):\\n cprint(f\\\"### Function Name:-> {inspect.stack()[0][3]} ###\\\", 'yellow', 'on_grey', attrs=['bold'])\\n try:\\n os.remove(path)\\n except FileNotFoundError:\\n pass\",\n \"def delete_file(self, timeout=None, **kwargs):\\n # type: (Optional[int], Optional[Any]) -> None\\n try:\\n self._client.file.delete(timeout=timeout, **kwargs)\\n except StorageErrorException as error:\\n process_storage_error(error)\",\n \"def test_cannot_remove_file(self):\\n self.api.remove_file('/some-fake/path/to-delete-file.json')\",\n \"def deleteSingleFile(filename):\\n os.popen('rm {}'.format(filename))\",\n \"def delete(self):\\n os.remove(self.file_path)\\n super(VideoFile, self).delete()\",\n \"def delete_file(_oid, attachmentId=None):\\n md = Metadata.objects.get_or_404(pk=_oid)\\n attachment = ''\\n test_upload_path_prefix = \\\"uploadedfiles\\\"\\n test_environment = False\\n\\n username = _authenticate_user_from_session(request)\\n\\n if username:\\n try:\\n try:\\n md = Metadata.objects.get(id=_oid)\\n \\n try:\\n # if developing locally we'll also want to remove file\\n url = filter(\\n lambda a: str(a.id) == attachmentId, md.attachments\\n ).pop().url\\n if str(os.environ['FLASKCONFIG']) == 'testing' or str(os.environ['FLASKCONFIG']) == 'development':\\n test_environment = True\\n os.remove(\\n os.path.join(\\n app.config['UPLOADS_DEFAULT_DEST'],\\n test_upload_path_prefix,\\n _oid,\\n os.path.basename(url)\\n )\\n )\\n else:\\n os.remove(\\n os.path.join(\\n app.config['UPLOADS_DEFAULT_DEST'],\\n _oid,\\n os.path.basename(url)\\n )\\n )\\n except Exception:\\n #Throw exception specific for test or non-test enviroment\\n if test_environment:\\n file_path = app.config['UPLOADS_DEFAULT_DEST'] + \\\"/\\\" + test_upload_path_prefix + \\\"/\\\" + _oid + \\\"/\\\" + os.path.basename(url)\\n else:\\n file_path = app.config['UPLOADS_DEFAULT_DEST'] + \\\"/\\\" + _oid + \\\"/\\\" + os.path.basename(url)\\n\\n print \\\"There was a problem deleting the file! Tried to reach path: \\\" + file_path \\n \\n # don't need to save after this since we're updating existing\\n Metadata.objects(id=_oid).update_one(\\n pull__attachments__id=attachmentId\\n )\\n \\n md = Metadata.objects.get(id=_oid)\\n \\n # we'll just go ahead and not care if it doesn't exist\\n except ValueError:\\n pass\\n\\n\\n except KeyError:\\n try:\\n keys = request.json.keys()\\n keys_str = ', '.join(keys)\\n except Exception as e:\\n print \\\"Error: \\\" + str(e)\\n return Response(\\\"Server error deleting file...\\\", status=500)\\n\\n return jsonify(\\n {\\n 'message':\\n 'Key(s) ' + keys_str + ' not recognized. ' +\\n 'Must contain \\\\'attachment\\\\''\\n },\\n status=400\\n )\\n\\n return jsonify(dict(message=attachment + ' successfully (at/de)tached!', record=md))\\n \\n else:\\n return Response('Bad or missing session id.', status=401)\",\n \"def test_rm(self, client, remote_mock_dir):\\n\\n file_path = posixpath.join(remote_mock_dir, \\\"test.txt\\\")\\n assert client.exists(file_path)\\n\\n with HdfsHook() as hook:\\n hook.rm(file_path)\\n\\n assert not client.exists(file_path)\",\n \"def storage_delete_file(self, group='', key=''):\\n deleted = False\\n if key not in [\\\"default-logo.png\\\", \\\"default-picture.png\\\"]:\\n if self.config['type'] == 's3':\\n s3_files = self.s3.Bucket(self.bucket)\\n for _file in s3_files.objects.all():\\n if _file.key == 'corr-{0}s/{1}'.format(group, key):\\n _file.delete()\\n print(\\\"File deleted!\\\")\\n deleted = True\\n break\\n elif self.config['type'] == 'filesystem':\\n found = self.agent_delete(group, self.storage_path, key)\\n if found:\\n deleted = True\\n if not deleted:\\n print(\\\"File not deleted\\\")\\n return deleted\",\n \"def delete_file(filename, sudo=True):\\n LOG.info(\\\"Deleting file {}\\\".format(filename))\\n cmd = \\\"rm {}\\\".format(filename)\\n _exec_cmd(cmd=cmd, sudo=sudo, fail_ok=False)\",\n \"def delFile(self, file_name):\\n ret = self.rest.delete(self.ngx_server, self.getUrl() + '/' + file_name, {}, [200, 404])\\n if ret == False:\\n self.logger.error('delete file:%s from tfs failed.' % file_name)\\n raise Exception, 'delete file:%s from tfs failed.' % file_name\\n self.logger.info('Delete Tfs file: %s' % file_name)\\n return True\",\n \"def delete(self, src):\\n\\n if self.noop:\\n logger.info(\\\"No-Op Delete: %s.tar\\\" % self.bucket + src)\\n else:\\n logger.info(\\\"Trying to delete %s.tar\\\" % self.bucket + src)\\n self.client.delete(self.bucket + src + \\\".tar\\\")\",\n \"def delete_file_from_datastore(content, datastore_name, path):\\n try:\\n datastore = get_obj(content, [vim.Datastore], datastore_name)\\n datastore.browser.DeleteFile('[{0}] {1}'.format(datastore_name, path))\\n except vim.fault.FileNotFound as e:\\n return e\\n return None\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.file:\\n if os.path.isfile(instance.file.path):\\n os.remove(instance.file.path)\",\n \"def delete(self):\\r\\n if self.provider.readonly:\\r\\n raise DAVError(HTTP_FORBIDDEN)\\r\\n\\r\\n self.provider.cache_fs.remove(self.path)\\r\\n if self.nibbler.find(self.path):\\r\\n self.nibbler.remove_file(self.path)\\r\\n\\r\\n self.removeAllProperties(True)\\r\\n self.removeAllLocks(True)\",\n \"def delete_file(filename: str):\\n\\t\\tif filename == \\\"ALL\\\":\\n\\t\\t\\tfor file in os.listdir(\\\"data/music/\\\"):\\n\\t\\t\\t\\tdeleted = False\\n\\t\\t\\t\\twhile not deleted:\\n\\t\\t\\t\\t\\ttry:\\n\\t\\t\\t\\t\\t\\tos.remove(f\\\"data/music/{file}\\\")\\n\\t\\t\\t\\t\\t\\tdeleted = True\\n\\t\\t\\t\\t\\texcept Exception as e:\\n\\t\\t\\t\\t\\t\\tprint(\\\"Not removed, waiting 1 second...\\\")\\n\\t\\t\\t\\t\\t\\tasyncio.sleep(1)\\n\\t\\telse:\\n\\t\\t\\tprint(\\\"File--: \\\", filename)\",\n \"def delete_file(self, repo, file_name):\\n DataHubManager.has_repo_file_privilege(\\n self.username, self.repo_base, repo, 'write')\\n\\n file_path = user_data_path(self.repo_base, repo, file_name)\\n os.remove(file_path)\",\n \"def delete_file(fileName):\\n os.remove(fileName)\\n print (\\\"Deleteing file: \\\" + str(fileName))\\n write_log()\\n read_log()\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n\\n if instance.file:\\n if os.path.isfile(instance.file.path):\\n os.remove(instance.file.path)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.78285897","0.7648353","0.7642585","0.760645","0.76037663","0.74779713","0.74424183","0.7431991","0.7220687","0.7075886","0.7070949","0.7070422","0.70667434","0.7064232","0.7057947","0.7055706","0.70467263","0.703922","0.7017835","0.69733405","0.69544697","0.692348","0.6880436","0.6877434","0.6835751","0.6825381","0.68199503","0.68122286","0.67864746","0.6783696","0.67811435","0.6777707","0.67726016","0.6750919","0.6747317","0.67472994","0.6743948","0.6737742","0.6736733","0.67363054","0.67266417","0.67257226","0.6715496","0.6710832","0.6695104","0.6688375","0.6688375","0.6685299","0.6680806","0.66799647","0.6676699","0.66742605","0.66695565","0.6666479","0.6652278","0.6649496","0.66424716","0.66424274","0.6612411","0.66035306","0.6591064","0.6591056","0.65846455","0.65628695","0.65577877","0.6556128","0.65485156","0.6537327","0.6532917","0.65316033","0.6521206","0.65140456","0.6494687","0.64922726","0.6485977","0.6466318","0.6459421","0.64554274","0.6451868","0.64493316","0.644848","0.64442384","0.642901","0.64192456","0.64184606","0.64102274","0.64078975","0.6407607","0.64025724","0.6391169","0.63909113","0.6386002","0.6384815","0.63772625","0.6369275","0.63669384","0.63663363","0.6366111","0.636207","0.6342812","0.6342687"],"string":"[\n \"0.78285897\",\n \"0.7648353\",\n \"0.7642585\",\n \"0.760645\",\n \"0.76037663\",\n \"0.74779713\",\n \"0.74424183\",\n \"0.7431991\",\n \"0.7220687\",\n \"0.7075886\",\n \"0.7070949\",\n \"0.7070422\",\n \"0.70667434\",\n \"0.7064232\",\n \"0.7057947\",\n \"0.7055706\",\n \"0.70467263\",\n \"0.703922\",\n \"0.7017835\",\n \"0.69733405\",\n \"0.69544697\",\n \"0.692348\",\n \"0.6880436\",\n \"0.6877434\",\n \"0.6835751\",\n \"0.6825381\",\n \"0.68199503\",\n \"0.68122286\",\n \"0.67864746\",\n \"0.6783696\",\n \"0.67811435\",\n \"0.6777707\",\n \"0.67726016\",\n \"0.6750919\",\n \"0.6747317\",\n \"0.67472994\",\n \"0.6743948\",\n \"0.6737742\",\n \"0.6736733\",\n \"0.67363054\",\n \"0.67266417\",\n \"0.67257226\",\n \"0.6715496\",\n \"0.6710832\",\n \"0.6695104\",\n \"0.6688375\",\n \"0.6688375\",\n \"0.6685299\",\n \"0.6680806\",\n \"0.66799647\",\n \"0.6676699\",\n \"0.66742605\",\n \"0.66695565\",\n \"0.6666479\",\n \"0.6652278\",\n \"0.6649496\",\n \"0.66424716\",\n \"0.66424274\",\n \"0.6612411\",\n \"0.66035306\",\n \"0.6591064\",\n \"0.6591056\",\n \"0.65846455\",\n \"0.65628695\",\n \"0.65577877\",\n \"0.6556128\",\n \"0.65485156\",\n \"0.6537327\",\n \"0.6532917\",\n \"0.65316033\",\n \"0.6521206\",\n \"0.65140456\",\n \"0.6494687\",\n \"0.64922726\",\n \"0.6485977\",\n \"0.6466318\",\n \"0.6459421\",\n \"0.64554274\",\n \"0.6451868\",\n \"0.64493316\",\n \"0.644848\",\n \"0.64442384\",\n \"0.642901\",\n \"0.64192456\",\n \"0.64184606\",\n \"0.64102274\",\n \"0.64078975\",\n \"0.6407607\",\n \"0.64025724\",\n \"0.6391169\",\n \"0.63909113\",\n \"0.6386002\",\n \"0.6384815\",\n \"0.63772625\",\n \"0.6369275\",\n \"0.63669384\",\n \"0.63663363\",\n \"0.6366111\",\n \"0.636207\",\n \"0.6342812\",\n \"0.6342687\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":18698,"cells":{"query":{"kind":"string","value":"Agent function that prepares a dictionary for storage in a compressed files."},"document":{"kind":"string","value":"def agent_prepare(self, zf, group, object_dict):\n object_buffer = StringIO()\n object_buffer.write(json.dumps(object_dict, sort_keys=True, indent=4, separators=(',', ': ')))\n object_buffer.seek(0)\n data = zipfile.ZipInfo(\"{0}.json\".format(group))\n data.date_time = time.localtime(time.time())[:6]\n data.compress_type = zipfile.ZIP_DEFLATED\n data.external_attr |= 0o777 << 16 # -rwx-rwx-rwx\n return zf.writestr(data, object_buffer.read())"},"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 _files_from_json(self, file_json):\n self.compressed_file_json = zlib.compress(json.dumps(file_json).encode('utf-8'))\n self.compression_algorithm = 'gzip'\n self.compressed_content_hash = hashlib.sha256(self.compressed_file_json).hexdigest()","def file_to_dictionary():\n\n return;","def __init__(self):\n self.keyingMethod=fileSize\n self.keyToFile=dict()","def read_archive(self):\n print '------------------------------------'\n print ' Archiving the simulation results'\n print ' '\n self.archive = {}\n with open(self.archive_data, 'r') as f:\n for line in f:\n (key, val) = line.split()\n self.archive[(key)] = val","def dosomething(file_dict2, path, buf):\n file_dict2[path] = {\"Extension\": 1, \"Hash value\": 1}\n return file_dict2","def _generate_inventory(self, datapath):\n \n files = [file for file in listdir(datapath) if '.nc' in file and not 'xyz' in file]\n # file_prefixes = list(set([ file.split('_')[0] for file in files ]))\n # file_prefixes = list(set([ \"_\".join(file.split('_')[0:2]) for file in files ]))\n if self.extra_pref:\n file_prefixes = list(set([ \"_\".join(file.split('_')[0:2] + [self.extra_pref]) for file in files ]))\n else:\n file_prefixes = list(set([ \"_\".join(file.split('_')[0:2]) for file in files ]))\n \n inventory = {}\n for file_prefix in file_prefixes:\n fname = path.join(datapath,f'{file_prefix}{self.first_suffix}')\n if not self.metafile:\n self.metafile = fname\n vars = [ var for var in list(Dataset(fname).variables) if var not in self.skip_vars ]\n for var in vars:\n inventory[var] = {'files': sorted([path.join(datapath,file) \n for file in listdir(datapath) if file_prefix in file])}\n return inventory","def init() -> None:\n init_dict()\n parse_file(\"alphabet.txt\", letters)\n parse_file(\"numbers.txt\", numbers)\n parse_file(\"symbols.txt\", symbols)","def run(self):\n self.compress(\n self.__config.public_key(),\n self.__config.input_dir(),\n self.__config.output_dir(),\n self.__config.suffix()\n )","def zip_files(dict_files, compression=zipfile.ZIP_DEFLATED):\n in_memory = StringIO()\n\n with zipfile.ZipFile(in_memory, 'w', compression) as zf:\n for fname, fp in dict_files.iteritems():\n zf.writestr(fname, fp.read())\n\n zf.close()\n\n in_memory.seek(0)\n\n return in_memory","def init(sFileName, sDescription):\n \n try:\n with open(sFileName) as f:\n my_dict = json.load(f)\n \n \n except:\n \n #assume there was an error, possibly the file does not exist\n my_dict = {'descriptor':sDescription ,'measurements':[]}\n with open (sFileName, 'w') as f:\n json.dump(my_dict,f)\n \n return my_dict","def read_archive(self):\n print '------------------------------------'\n print ' Archiving the simulation results'\n print '----------------------------------- '\n\n if self.Simulation_area.lower() == 'barrow':\n os.chdir(self.control['Run_dir']+self.Input_directory+'/Barrow/')\n elif self.Simulation_area.lower() == 'tanana':\n os.chdir(self.control['Run_dir']+self.Input_directory+'/Tanana/')\n elif self.Simulation_area.lower() == 'yukon':\n os.chdir(self.control['Run_dir']+self.Input_directory+'/Yukon/')\n \n self.archive = {}\n with open(self.archive_data, 'r') as f:\n for line in f:\n if line.startswith('#'):\n continue\n else:\n (key, val) = line.split()\n self.archive[(key)] = val","def _build_dictionary(self):\n print(\"Building Dictionary...\")\n self.dictionary = Dictionary(self.load_files())","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 compress_file(map_, name, save_path):\n size = os.path.getsize(save_path)\n temp = subprocess.run([\"gzip\", \"-k\", save_path])\n cr_size = os.path.getsize(save_path+\".gz\")\n try:\n map_[name] = cr_size / size\n except Exception as e:\n print(f\"File: {save_path}, Ori:{size}, Compr:{cr_size}\")\n print(e)\n raise ZeroDivisionError\n temp = subprocess.run([\"rm\", save_path])\n temp = subprocess.run([\"rm\", save_path+\".gz\"])","def reinit(self):\n self.keys = {}\n fh = open(self.path, \"w\")\n json.dump(self.keys, fh)\n fh.close()\n os.chmod(self.path, 0o600)","def __init__(\n self, basedir: str, primary_key: Optional[List[int]] = None,\n replace: Optional[bool] = False, serializer: Optional[ArchiveSerializer] = None,\n compression: Optional[str] = None, encoder: Optional[json.JSONEncoder] = None,\n decoder: Optional[Callable] = None\n ):\n self.basedir = util.createdir(basedir)\n self._primary_key = primary_key\n self.serializer = serializer if serializer else DefaultSerializer()\n self.compression = compression\n self.encoder = encoder if encoder is not None else DefaultEncoder\n self.decoder = decoder if decoder is not None else default_decoder\n # Initialize the file names\n self.datafile = os.path.join(self.basedir, 'rows.dat')\n self.metafile = os.path.join(self.basedir, 'metadata.dat')\n self.tmpdatafile = os.path.join(self.basedir, 'rows.tmp')\n self.tmpmetafile = os.path.join(self.basedir, 'metadata.tmp')\n if not replace and os.path.isfile(self.metafile):\n # Read schema and snapshot information from disk if the metadata\n # file exists.\n with open(self.metafile, 'r') as f:\n doc = json.load(f, object_hook=self.decoder)\n # Deserialize schema columns.\n columns = list()\n for c in doc.get(META_SCHEMA, []):\n columns.append(self.serializer.deserialize_column(c))\n self.schema = ArchiveSchema(columns=columns)\n # Deserialize snapshot descriptors\n snapshots = list()\n for s in doc.get(META_SNAPSHOTS, []):\n snapshots.append(self.serializer.deserialize_snapshot(s))\n self.snapshots = SnapshotListing(snapshots=snapshots)\n # Deserialize row counter.\n self.row_counter = doc.get(META_ROWCOUNT, 0)\n # Overwrite primary key if it is present in the metadata file.\n if self._primary_key:\n doc[META_PRIMARYKEY] = self._primary_key\n with open(self.tmpmetafile, 'w') as f:\n json.dump(doc, f, cls=self.encoder)\n else:\n self._primary_key = doc[META_PRIMARYKEY]\n else:\n # Create an empty archive.\n self.schema = ArchiveSchema()\n self.snapshots = SnapshotListing()\n self.row_counter = 0\n # Remove any previous files that may exist in the base folder.\n for f in [self.datafile, self.metafile]:\n if os.path.isfile(f):\n os.remove(f)\n # Write primary key to metadata file.\n with open(self.metafile, 'w') as f:\n json.dump({META_PRIMARYKEY: self._primary_key}, f)","def prepare(self):\n\t\tif len(os.listdir(self.storagedir)):\n\t\t\traise Exception(\"There are already files in\", self.storagedir + \".\", \"Delete manually!\")\n\t\t\n\t\tself.worddict = {\"__pad__\": 0, \"__oov__\": 1}\n\t\tself.classdict = {}\n\t\tself.raw_documents, self.tokenized_documents = {}, {}\n\t\tself.X, self.Y = {}, {}\n\n\t\tfor dataset in self.DATASETS_TMP:\n\t\t\tself.get_raw_data(dataset)\n\t\t\tself.delete_empty_documents(dataset)\n\t\t\tself.tokenize_documents(dataset)\n\n\t\tself.make_classdict()\n\t\tself.make_worddict()\n\t\tself.make_embeddings()\n\t\tself.reverse_dicts()\n\n\t\tfor dataset in self.DATASETS_TMP:\n\t\t\tself.make_X(dataset)\n\t\t\tself.shuffle_dataset(dataset)\n\n\t\tif not \"dev\" in self.X:\n\t\t\tself.split_dev()\t\t\n\t\tself.make_hybrid()\n\t\tself.store()","def store_harvest(self, file_prefix, data):\n compressed = bz2.compress(data)\n k = f\"{self.harvest_key_prefix}/{self.harvest_date}/{file_prefix}.bz2\"\n self.s3_client.put_object(\n Body=compressed,\n Bucket=self.s3_bucket,\n Key=k,\n )","def preload(self):\n # load the objects\n for otype, fname in self.TYPE2NAME.items():\n if fname:\n path = os.path.join(self.anodir, fname + \".gz\")\n if os.path.isfile(path):\n with gzip.open(path, \"rt\") as handler:\n for line in handler:\n omap = json.loads(line)\n cls = self.TYPE2CLASS[otype]\n item = cls.from_map(omap, self)\n self.caches[otype][item.id] = item","def create_zip_dict() -> dict:\n with open('zip_coordinates.json', 'r') as zip_map:\n return json.loads(zip_map.read())","def prepare_fastq(self) -> dict:\r\n\r\n fastq = {}\r\n for organism, data in self.composition.items():\r\n file = data['file']\r\n file_path = Path(file)\r\n if not file_path.exists():\r\n raise ValueError(f'File {file_path} does not exist.')\r\n else:\r\n fastq[organism] = pyfastx.Fastq(file)\r\n\r\n self.logger.info('Prepared read files - proceeding')\r\n\r\n return fastq","def __init__(self, filename,chainlen,encoding = None):\n self.encoding=encoding\n dict.__init__(self)\n self.chainlen = chainlen\n self.filename = filename\n self.populate()","def make_file_dict():\r\n fileDict = {'pageUrls': [],\r\n 'pageFileNames': [],\r\n 'pageIds': [],\r\n 'fileUrls': [],\r\n 'fileIds': [],\r\n 'fileNames': [],\r\n 'cssUrls': [],\r\n 'cssFileNames': [],\r\n 'imgUrls': [],\r\n 'imgFileNames': []}\r\n return fileDict","def pre_lookup(self, file):\n return {}","def create(self):\n\n for sample_name, sample_info in self.samples.items():\n if not sample_info[\"use_it\"]:\n continue\n process_name = sample_info[\"process_name_specific\"]\n sample_category = sample_info[\"sample_category\"]\n is_mc = (sample_info[\"type\"] == \"mc\")\n\n logging.info(\"Building dictionaries for sample %s...\" % process_name)\n for charge_selection in self.charge_selections:\n central_or_shift_extensions = [\"\", \"hadd\", \"addBackgrounds\"]\n central_or_shifts_extended = central_or_shift_extensions + self.central_or_shifts\n for central_or_shift_or_dummy in central_or_shifts_extended:\n process_name_extended = [ process_name, \"hadd\" ]\n for process_name_or_dummy in process_name_extended:\n if central_or_shift_or_dummy in [ \"hadd\" ] and process_name_or_dummy in [ \"hadd\" ]:\n continue\n if central_or_shift_or_dummy != \"central\" and central_or_shift_or_dummy not in central_or_shift_extensions:\n if not is_mc:\n continue\n if not self.accept_central_or_shift(central_or_shift_or_dummy, sample_info):\n continue\n\n key_dir = getKey(process_name_or_dummy, charge_selection, central_or_shift_or_dummy)\n for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES ]:\n initDict(self.dirs, [ key_dir, dir_type ])\n if dir_type in [ DKEY_CFGS, DKEY_LOGS ]:\n self.dirs[key_dir][dir_type] = os.path.join(self.get_dir_type(dir_type), dir_type, self.channel,\n \"_\".join([ charge_selection ]), process_name_or_dummy, central_or_shift_or_dummy)\n else:\n self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel,\n \"_\".join([ charge_selection ]), process_name_or_dummy)\n for subdirectory in [ \"comp_jetToTauFakeRate\", \"makePlots\" ]:\n key_dir = getKey(subdirectory)\n for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT ]:\n initDict(self.dirs, [ key_dir, dir_type ])\n if dir_type in [ DKEY_CFGS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT ]:\n self.dirs[key_dir][dir_type] = os.path.join(self.get_dir_type(dir_type), dir_type, self.channel, subdirectory)\n else:\n self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel, subdirectory)\n for dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT ]:\n initDict(self.dirs, [ dir_type ])\n if dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT ]:\n self.dirs[dir_type] = os.path.join(self.get_dir_type(dir_type), dir_type, self.channel)\n else:\n self.dirs[dir_type] = os.path.join(self.outputDir, dir_type, self.channel)\n\n numDirectories = 0\n for key in self.dirs.keys():\n if type(self.dirs[key]) == dict:\n numDirectories += len(self.dirs[key])\n else:\n numDirectories += 1\n logging.info(\"Creating directory structure (numDirectories = %i)\" % numDirectories)\n numDirectories_created = 0;\n frac = 1\n for key in self.dirs.keys():\n if type(self.dirs[key]) == dict:\n for dir_type in self.dirs[key].keys():\n create_if_not_exists(self.dirs[key][dir_type])\n numDirectories_created += len(self.dirs[key])\n else:\n create_if_not_exists(self.dirs[key])\n numDirectories_created = numDirectories_created + 1\n while 100*numDirectories_created >= frac*numDirectories:\n logging.info(\" %i%% completed\" % frac)\n frac = frac + 1\n logging.info(\"Done.\")\n\n inputFileLists = {}\n for sample_name, sample_info in self.samples.items():\n if not sample_info[\"use_it\"]:\n continue\n logging.info(\"Checking input files for sample %s\" % sample_info[\"process_name_specific\"])\n inputFileLists[sample_name] = generateInputFileList(sample_info, self.max_files_per_job)\n\n self.inputFileIds = {}\n for sample_name, sample_info in self.samples.items():\n if not sample_info[\"use_it\"]:\n continue\n\n process_name = sample_info[\"process_name_specific\"]\n inputFileList = inputFileLists[sample_name]\n\n logging.info(\"Creating configuration files to run '%s' for sample %s\" % (self.executable_analyze, process_name))\n\n is_mc = (sample_info[\"type\"] == \"mc\")\n sample_category = sample_info[\"sample_category\"]\n\n for charge_selection in self.charge_selections:\n for central_or_shift in self.central_or_shifts:\n \n if central_or_shift != \"central\" and not is_mc:\n continue\n if not self.accept_central_or_shift(central_or_shift, sample_info):\n continue\n\n # build config files for executing analysis code\n key_analyze_dir = getKey(process_name, charge_selection, central_or_shift)\n\n for jobId in inputFileList.keys():\n\n analyze_job_tuple = (process_name, charge_selection, central_or_shift, jobId)\n key_analyze_job = getKey(*analyze_job_tuple)\n ntupleFiles = inputFileList[jobId]\n if len(ntupleFiles) == 0:\n logging.warning(\"No input ntuples for %s --> skipping job !!\" % (key_analyze_job))\n continue\n\n cfgFile_modified_path = os.path.join(self.dirs[key_analyze_dir][DKEY_CFGS], \"analyze_%s_%s_%s_%i_cfg.py\" % analyze_job_tuple)\n logFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_LOGS], \"analyze_%s_%s_%s_%i.log\" % analyze_job_tuple)\n histogramFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_HIST], \"analyze_%s_%s_%s_%i.root\" % analyze_job_tuple)\n rleOutputFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_RLES], \"rle_%s_%s_%s_%i.txt\" % analyze_job_tuple) \\\n if self.select_rle_output else \"\"\n\n self.jobOptions_analyze[key_analyze_job] = {\n 'ntupleFiles' : ntupleFiles,\n 'cfgFile_modified' : cfgFile_modified_path,\n 'histogramFile' : histogramFile_path,\n 'logFile' : logFile_path,\n 'chargeSelection' : charge_selection,\n 'jet_minPt' : self.jet_minPt,\n 'jet_maxPt' : self.jet_maxPt,\n 'jet_minAbsEta' : self.jet_minAbsEta,\n 'jet_maxAbsEta' : self.jet_maxAbsEta,\n 'hadTau_selection_tight' : self.hadTau_selection_tight,\n 'hadTauSelection_denominator' : self.hadTau_selection_denominator,\n 'hadTauSelections_numerator' : self.hadTau_selections_numerator,\n 'trigMatchingOptions' : self.trigMatchingOptions,\n 'selEventsFileName_output' : rleOutputFile_path,\n 'absEtaBins' : self.absEtaBins,\n 'decayModes' : self.decayModes,\n 'central_or_shift' : central_or_shift,\n 'central_or_shifts_local' : [],\n 'apply_hlt_filter' : self.hlt_filter,\n }\n self.createCfg_analyze(self.jobOptions_analyze[key_analyze_job], sample_info)\n\n # initialize input and output file names for hadd_stage1\n key_hadd_stage1_dir = getKey(process_name, charge_selection)\n hadd_stage1_job_tuple = (process_name, charge_selection)\n key_hadd_stage1_job = getKey(*hadd_stage1_job_tuple)\n if not key_hadd_stage1_job in self.inputFiles_hadd_stage1:\n self.inputFiles_hadd_stage1[key_hadd_stage1_job] = []\n self.inputFiles_hadd_stage1[key_hadd_stage1_job].append(self.jobOptions_analyze[key_analyze_job]['histogramFile'])\n self.outputFile_hadd_stage1[key_hadd_stage1_job] = os.path.join(self.dirs[key_hadd_stage1_dir][DKEY_HIST],\n \"hadd_stage1_%s_%s.root\" % hadd_stage1_job_tuple)\n\n # initialize input and output file names for hadd_stage2\n key_hadd_stage1_job = getKey(process_name, charge_selection)\n key_hadd_stage2_dir = getKey(\"hadd\", charge_selection)\n key_hadd_stage2_job = getKey(charge_selection)\n if not key_hadd_stage2_job in self.inputFiles_hadd_stage2:\n self.inputFiles_hadd_stage2[key_hadd_stage2_job] = []\n self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.outputFile_hadd_stage1[key_hadd_stage1_job])\n self.outputFile_hadd_stage2[key_hadd_stage2_job] = os.path.join(self.dirs[key_hadd_stage2_dir][DKEY_HIST],\n \"hadd_stage2_%s.root\" % charge_selection)\n\n logging.info(\"Creating configuration files for executing 'comp_jetToTauFakeRate'\")\n for charge_selection in self.charge_selections:\n charge_key = \"comp_%s\" % charge_selection\n self.comp_input_files[charge_key] = []\n for trigMatchingOption in self.trigMatchingOptions:\n key_hadd_stage2_job = getKey(charge_selection)\n key_comp_jetToTauFakeRate_dir = getKey(\"comp_jetToTauFakeRate\")\n key_comp_jetToTauFakeRate_job = getKey(charge_selection, trigMatchingOption)\n self.jobOptions_comp_jetToTauFakeRate[key_comp_jetToTauFakeRate_job] = {\n 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],\n 'cfgFile_modified' : os.path.join(\n self.dirs[DKEY_CFGS], \"comp_jetToTauFakeRate_%s_%s_cfg.py\" % (charge_selection, trigMatchingOption)),\n 'outputFile' : os.path.join(\n self.dirs[DKEY_HIST], \"comp_jetToTauFakeRate_%s_%s.root\" % (charge_selection, trigMatchingOption)),\n 'logFile' : os.path.join(\n self.dirs[DKEY_LOGS], \"comp_jetToTauFakeRate_%s_%s.log\" % (charge_selection, trigMatchingOption)),\n 'looseRegion' : \"jetToTauFakeRate_%s_%s/denominator/\" % (charge_selection, trigMatchingOption),\n 'tightRegion' : \"jetToTauFakeRate_%s_%s/numerator/\" % (charge_selection, trigMatchingOption),\n 'absEtaBins' : self.absEtaBins,\n 'ptBins' : self.ptBins,\n 'decayModes' : self.decayModes,\n 'hadTauSelections' : self.hadTau_selections_numerator,\n 'trigMatchingOption' : trigMatchingOption,\n 'plots_outputFileName' : os.path.join(self.dirs[key_comp_jetToTauFakeRate_dir][DKEY_PLOT], \"comp_jetToTauFakeRate_%s.png\" % trigMatchingOption)\n }\n self.createCfg_comp_jetToTauFakeRate(self.jobOptions_comp_jetToTauFakeRate[key_comp_jetToTauFakeRate_job])\n comp_output = self.jobOptions_comp_jetToTauFakeRate[key_comp_jetToTauFakeRate_job]['outputFile']\n self.targets.append(comp_output)\n self.comp_input_files[charge_key].append(comp_output)\n self.comp_output_files[charge_key] = os.path.join(self.dirs[DKEY_HIST], \"comp_jetToTauFakeRate_%s.root\" % charge_selection)\n\n logging.info(\"Creating configuration files to run 'makePlots'\")\n for charge_selection in self.charge_selections:\n key_hadd_stage2_job = getKey(charge_selection)\n key_makePlots_dir = getKey(\"makePlots\")\n key_makePlots_job = getKey(charge_selection) \n self.jobOptions_make_plots[key_makePlots_job] = {\n 'executable' : self.executable_make_plots,\n 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],\n 'cfgFile_modified' : os.path.join(\n self.dirs[key_makePlots_dir][DKEY_CFGS], \"makePlots_%s_cfg.py\" % self.channel),\n 'outputFile' : os.path.join(\n self.dirs[key_makePlots_dir][DKEY_PLOT], \"makePlots_%s.png\" % self.channel),\n 'histogramDir' : \"jetToTauFakeRate_%s\" % charge_selection,\n 'label' : None,\n 'make_plots_backgrounds' : self.make_plots_backgrounds\n }\n self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])\n for trigMatchingOption in self.trigMatchingOptions:\n self.cfgFile_make_plots = self.cfgFile_make_plots_denominator\n for absEtaBin in [ \"absEtaLt1_5\", \"absEta1_5to9_9\" ]:\n key_hadd_stage2_job = getKey(charge_selection)\n key_makePlots_job = getKey(charge_selection, trigMatchingOption, absEtaBin, \"denominator\") \n self.jobOptions_make_plots[key_makePlots_job] = {\n 'executable' : self.executable_make_plots,\n 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],\n 'cfgFile_modified' : os.path.join(\n self.dirs[key_makePlots_dir][DKEY_CFGS], \"makePlots_%s_%s_%s_denominator_%s_cfg.py\" % \\\n (self.channel, charge_selection, trigMatchingOption, absEtaBin)),\n 'outputFile' : os.path.join(\n self.dirs[key_makePlots_dir][DKEY_PLOT], \"makePlots_%s_%s_%s_denominator_%s.png\" % (self.channel, charge_selection, trigMatchingOption, absEtaBin)),\n 'histogramDir' : \"jetToTauFakeRate_%s_%s/denominator/%s\" % (charge_selection, trigMatchingOption, absEtaBin),\n 'label' : None,\n 'make_plots_backgrounds' : self.make_plots_backgrounds\n }\n self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])\n for hadTau_selection_numerator in self.hadTau_selections_numerator:\n key_hadd_stage2_job = getKey(charge_selection)\n key_makePlots_job = getKey(charge_selection, trigMatchingOption, absEtaBin, \"numerator\", hadTau_selection_numerator)\n self.jobOptions_make_plots[key_makePlots_job] = {\n 'executable' : self.executable_make_plots,\n 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],\n 'cfgFile_modified' : os.path.join(\n self.dirs[key_makePlots_dir][DKEY_CFGS], \"makePlots_%s_%s_%s_numerator_%s_%s_cfg.py\" % \\\n (self.channel, charge_selection, trigMatchingOption, hadTau_selection_numerator, absEtaBin)),\n 'outputFile' : os.path.join(\n self.dirs[key_makePlots_dir][DKEY_PLOT], \"makePlots_%s_%s_%s_numerator_%s_%s.png\" % \\\n (self.channel, charge_selection, trigMatchingOption, hadTau_selection_numerator, absEtaBin)),\n 'histogramDir' : \"jetToTauFakeRate_%s_%s/numerator/%s/%s\" % (charge_selection, trigMatchingOption, hadTau_selection_numerator, absEtaBin),\n 'label' : None,\n 'make_plots_backgrounds' : self.make_plots_backgrounds\n }\n self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])\n\n self.sbatchFile_analyze = os.path.join(self.dirs[DKEY_SCRIPTS], \"sbatch_analyze_%s.py\" % self.channel)\n self.sbatchFile_comp_jetToTauFakeRate = os.path.join(self.dirs[DKEY_SCRIPTS], \"sbatch_comp_jetToTauFakeRate.py\")\n if self.is_sbatch:\n logging.info(\"Creating script for submitting '%s' jobs to batch system\" % self.executable_analyze)\n self.createScript_sbatch_analyze(self.executable_analyze, self.sbatchFile_analyze, self.jobOptions_analyze)\n logging.info(\"Creating script for submitting '%s' jobs to batch system\" % self.executable_comp_jetToTauFakeRate)\n self.createScript_sbatch(self.executable_comp_jetToTauFakeRate, self.sbatchFile_comp_jetToTauFakeRate, self.jobOptions_comp_jetToTauFakeRate)\n\n lines_makefile = []\n self.addToMakefile_analyze(lines_makefile)\n self.addToMakefile_hadd_stage1(lines_makefile)\n self.addToMakefile_hadd_stage2(lines_makefile, make_dependency = \"phony_hadd_stage1\", max_mem = '4096M')\n self.addToMakefile_comp_jetToTauFakeRate(lines_makefile)\n self.addToMakefile_comp_hadd(lines_makefile)\n self.addToMakefile_make_plots(lines_makefile)\n self.createMakefile(lines_makefile)\n\n logging.info(\"Done.\")\n\n return self.num_jobs","def _initializeDoneDict(self):\n\t\tself.donedictfile = os.path.join(self.params['rundir'] , self.functionname+\".donedict\")\n\t\tif os.path.isfile(self.donedictfile) and self.params['continue'] == True:\n\t\t\t### unpickle previously done dictionary\n\t\t\tapDisplay.printMsg(\"Reading old done dictionary: \"+os.path.basename(self.donedictfile))\n\t\t\tf = open(self.donedictfile,'r')\n\t\t\tself.donedict = cPickle.load(f)\n\t\t\tf.close()\n\t\t\tif not 'commit' in self.donedict or self.donedict['commit'] == self.params['commit']:\n\t\t\t\t### all is well\n\t\t\t\tapDisplay.printMsg(\"Found \"+str(len(self.donedict))+\" done dictionary entries\")\n\t\t\t\treturn\n\t\t\telif self.donedict['commit'] is True and self.params['commit'] is not True:\n\t\t\t\t### die\n\t\t\t\tapDisplay.printError(\"Commit flag was enabled and is now disabled, create a new runname\")\n\t\t\telse:\n\t\t\t\t### set up fresh dictionary\n\t\t\t\tapDisplay.printWarning(\"'--commit' flag was changed, creating new done dictionary\")\n\n\t\t### set up fresh dictionary\n\t\tself.donedict = {}\n\t\tself.donedict['commit'] = self.params['commit']\n\t\tapDisplay.printMsg(\"Creating new done dictionary: \"+os.path.basename(self.donedictfile))\n\n\t\t### write donedict to file\n\t\tf = open(self.donedictfile, 'w', 0666)\n\t\tcPickle.dump(self.donedict, f)\n\t\tf.close()\n\t\treturn","def convert_gz_json(option, _, value, parser):\n setattr(\n parser.values, option.dest,\n json.loads(zlib.decompress(base64.b64decode(value))))","def savepickle(fln, dict, compress=None):\n if compress == None:\n if not os.path.exists(fln) and os.path.exists(fln + '.gz'):\n compress = True\n else:\n compress = False\n if compress:\n import gzip\n with open(fln + '.gz', 'wb') as fh:\n gzh = gzip.GzipFile(fln, 'wb', compresslevel=3, fileobj=fh)\n pickle.dump(dict, gzh, 2)\n gzh.close()\n else:\n with open(fln, 'wb') as fh:\n pickle.dump(dict, fh, 2) # 2 ... fast binary\n return","def decompress(compressed):\r\n \r\n \r\n # Build the dictionary.\r\n dict_size = 256\r\n dictionary = dict((i, chr(i)) for i in range(dict_size))\r\n # in Python 3: dictionary = {i: chr(i) for i in range(dict_size)}\r\n \r\n # use StringIO, otherwise this becomes O(N^2)\r\n # due to string concatenation in a loop\r\n result = StringIO()\r\n w = chr(compressed.pop(0))\r\n result.write(w)\r\n for k in compressed:\r\n if k in dictionary:\r\n entry = dictionary[k]\r\n elif k == dict_size:\r\n entry = w + w[0]\r\n else:\r\n raise ValueError('Bad compressed k: %s' % k)\r\n result.write(entry)\r\n \r\n # Add w+entry[0] to the dictionary.\r\n dictionary[dict_size] = w + entry[0]\r\n dict_size += 1\r\n \r\n w = entry\r\n return result.getvalue()","def prepare_gz(self, filename, *args, **kwargs):\n\n return '/vsigzip/' + filename, args, kwargs","def compress_skim_dir(directory, output=\"zarr\"):\n\n if output not in (\"zarr\", \"zarr.zip\"):\n raise NotImplementedError(output)\n\n if output == \"zarr\":\n if not os.path.exists(directory+\".zarr\"):\n os.makedirs(directory+\".zarr\")\n elif output == \"zarr.zip\":\n if os.path.exists(directory+\".zarr.zip\"):\n raise FileExistsError(directory+\".zarr.zip\")\n\n master = {}\n for f in os.walk(directory):\n for fi in f[2]:\n if \".emx\" in fi:\n arr = np.fromfile(fi, dtype='f4')\n side = int(np.sqrt(arr.size))\n arr = arr.reshape(side, side)\n tazrange = pd.RangeIndex(1, side+1)\n master[fi.replace(\".emx\", \"\")] = xr.DataArray(\n arr,\n dims=['otaz', 'dtaz'],\n coords={'otaz': tazrange, 'dtaz': tazrange}\n )\n\n master = sh.Dataset(master)\n\n if output == \"zarr\":\n master.to_zarr(directory+\".zarr\", mode='a')\n elif output == \"zarr.zip\":\n with zarr.ZipStore(directory+\".zarr.zip\", mode='w') as store:\n master.to_zarr(store)\n return master","def __init__(self,fileName,storageCode,hash):\n self.fileName = fileName\n self.storageCode = storageCode\n self.hash = hash\n self.pieces = {}","def save_compression():\n added,comp_seq, binary_seq, seq, file = binary_to_utf8()\n huffman_code, binary_seq = huffman_construction(seq)\n \n #save the number of zeroes added to the dictionnary \n huffman_code[\"add\"]= added\n created_file = os.path.splitext(file)[0]\n file_comp = open(created_file + \"_compressed.txt\", \"w\") \n \n #save the dictionnary in the file and the compressed sequence\n json.dump(huffman_code, file_comp)\n file_comp.write(\"\\n\"+comp_seq) \n file_comp.close()\n \n messagebox.showinfo(\"Information\", \"Your compression has been saved in \"+created_file +\"_compressed.txt file.\")\n return comp_seq, binary_seq, seq","def create_compressed_file(self):\n\t\tself._compressed_file_name = 'c_' + self.file_name\n\t\tself._compressed_save_path = self.full_path.replace(self.file_name, self._compressed_file_name)\n\t\tself._is_png = 'png' in self.file_extension\n\t\tself._is_jpg = 'jpg' in self.file_extension\n\n\t\timage = Image.open(self.full_path)\n\n\t\tif self._is_png:\n\t\t\timage.save(self._compressed_save_path, quality=85, optimize=False, compress_level=9)\n\t\telif self._is_jpg:\n\t\t\timage.save(self._compressed_save_path, quality=85, progressive=False)\n\t\telse:\n\t\t\tprint('Non-recognized asset format!!')\n\t\t\texit()\n\n\t\tself._compressed_file_size = ufo.get_file_size_in_bytes(self._compressed_save_path)\n\n\n\t\ttransfer_path = self._compressed_save_path.replace('c_' + self.file_name, self.file_name).replace('/configuration_files/', '/quasar_site_django/')\n\t\tufo.copy_file_to_path(self._compressed_save_path, transfer_path)","def apply_compressed_sensing(self, inputs, rng):\n print('using compressed sensing!')\n train_path = os.path.join(\n self.data_dir, 'assist{0}-{1}'.format(self.which_year, 'train'))\n\n if self.which_set == 'test':\n loaded = np.load(train_path + '-compression-matrix.npz')\n self.compress_matrix = loaded['compress_matrix']\n self.compress_dim = self.compress_matrix.shape[1]\n elif self.which_set == 'train':\n self.compress_matrix = self.make_compression_matrix(train_path, rng)\n\n inputs = self.compress_inputs(inputs)\n return inputs","def initializeFromDict(self, inputDict):\n pass","def cache_file_list_dict(self, dict_):\n try:\n dict_['DUMMYKEY'] = FileInfo()\n dict_.pop('DUMMYKEY')\n except TypeError:\n raise TypeError('incompatible type')\n else:\n self.__cache_file_list_dict = dict_","def __init__(self, dir_path= 'static/Irma data-20210525'):\n \n A=csv_to_dict(dir_path+\"\\A.csv\")\n B=csv_to_dict(dir_path+\"\\B.csv\")\n C=csv_to_dict(dir_path+\"\\C.csv\")\n D=csv_to_dict(dir_path+\"\\D.csv\")\n\n\n self.dicts_list=[A,B,C,D]\n self.image_codes=csv_to_dict(dir_path+\"\\image_codes.csv\")","def keys(self, data, installer_context):","def dict_to_files(result_dict, dest_dir):\n tempdir = tempfile.mkdtemp()\n\n # timestamp every generated dignostic file\n timestamp = datetime.datetime.now().strftime(\"%Y%m%d_%H%I%S\")\n tarball = '{0}/ceph-collect_{1}.tar.gz'.format(dest_dir, timestamp)\n\n with tarfile.open(tarball, 'w:gz') as tar:\n for filename, content in result_dict.items():\n\n for contentname, contentdata in content.items():\n tmpfile = '{0}/{1}'.format(tempdir, filename +\n \"-\" + contentname)\n\n LOGGER.debug('Writing file %s', tmpfile)\n print('Writing file %s', tmpfile)\n with open(tmpfile, 'wb') as f:\n f.write(contentdata)\n f.close()\n\n tar.add(name=tmpfile,\n arcname='ceph-collect_{0}/{1}'.format(timestamp,\n filename + \"-\" +\n contentname))\n tar.close()\n LOGGER.info(\"Diagnostics are written to : \"+ tarball)\n\n LOGGER.info(\"Cleaning up temporary directory\")\n shutil.rmtree(tempdir)","def create_dicts(self):\n \n # remove this string from filename to make output file names more manageable\n pre_output1 = self.file1.replace(\"_Guys121919_CGH_1100_Jul11\", '')\n pre_output2 = self.file2.replace(\"_Guys121919_CGH_1100_Jul11\", '')\n \n # Build the output file name.\n # if prefix is present add it\n if self.out_file_prefix is not None:\n # concatenate prefix, filenames and dyes into output filename file1_file1_dye_file2_file2_dye.txt\n self.outputfilename = self.out_file_prefix+pre_output1.replace(\".txt\", '') + \"_\" + self.file1_dye + \"_\" + pre_output2.replace(\".txt\", '') + \"_\" + self.file2_dye + \".txt\"\n # if no prefix don't add it!\n else:\n # concatenate filenames and dyes into output filename file1_file1_dye_file2_file2_dye.txt\n self.outputfilename = pre_output1.replace(\".txt\", '') + \"_\" + self.file1_dye + \"_\" + pre_output2.replace(\".txt\", '') + \"_\" + self.file2_dye + \".txt\"\n\n # add temp to end of file name to create a temporary output filename\n self.tempoutputfilename = self.outputfilename.replace(\".txt\", '') + \"temp.txt\"\n\n # open temp output file\n self.tempoutputfile = open(self.outputfolder + self.tempoutputfilename, 'w')\n\n \n # open FE files\n file1_open = open(self.chosenfolder + self.file1, 'r')\n file2_open = open(self.chosenfolder + self.file2, 'r')\n\n # open file1 and create a dict of the features.\n for linenumber, line in enumerate(file1_open):\n if linenumber >= 10:\n splitline = line.split('\\t')\n self.file1_dict[int(splitline[1])] = line\n # get n of rows in file1 (take the linenumber of the last line)\n self.file1_len = linenumber\n\n # repeat for features in second file but first writing the feparam and stats to temp file - when pairing with control this ensures the \"header\" comes from the test (file2) not control (file1), NB NEITHER ARE ACCURATE!!!!\n for linenumber, line in enumerate(file2_open):\n if linenumber < 10:\n self.tempoutputfile.write(line)\n # then add all features to a dictionary, with the unique feature number as a key\n if linenumber >= 10:\n splitline = line.split('\\t')\n self.file2_dict[int(splitline[1])] = line\n # get n of rows in file2\n self.file2_len = linenumber\n\n # close files\n file1_open.close()\n file2_open.close()","def write_snappy_dict(self):\n feature_list = []\n refinement_surface_dict = {}\n layer_dict = {}\n geom_dict = {}\n\n for part in self.geometries:\n geom = { part.filename : {'type':'triSurfaceMesh', 'name':part.name}}\n geom_dict.update(geom)\n\n file_dict = {'file' : '\"{}.eMesh\"'.format(part.name),\n 'level' : self.surfaceRefinement}\n feature_list.append(file_dict)\n\n refinement_surface = {part.name : {\n 'level' : [self.refinementSurfaceMin, self.refinementSurfaceMax]}}\n refinement_surface_dict.update(refinement_surface)\n\n layer = {part.name : {'nSurfaceLayers' : self.nSurfaceLayers}}\n layer_dict.update(layer)\n\n snappy_dict = {\n\n 'castellatedMesh' : self.castellate,\n 'snap' : self.snap,\n 'addLayers' : self.addLayers,\n 'geometry' :geom_dict,\n 'castellatedMeshControls' : {\n 'maxLocalCells' : self.maxLocalCells,\n 'maxGlobalCells' : self.maxGlobalCells,\n 'minRefinementCells' : self.minRefinementCells,\n 'maxLoadUnbalance' : self.maxLoadUnbalance,\n 'nCellsBetweenLevels' : self.nCellsBetweenLevels,\n 'features' : feature_list,\n 'refinementSurfaces': refinement_surface_dict,\n 'resolveFeatureAngle' : self.resolveFeatureAngle,\n 'refinementRegions' : {self.geometries[0].name :\n {'mode' : 'distance',\n 'levels' :([[(self.distanceRefinements[x],\\\n self.distanceLevels[x])] for x in\\\n range(len(self.distanceRefinements))])}},\n 'locationInMesh' : self.locationToKeep,\n 'allowFreeStandingZoneFaces' : self.allowFreeStandingFaces\n },\n 'snapControls' :\n {\n 'nSmoothPatch' : self.nSmoothPatch,\n 'tolerance' : self.snapTolerance,\n 'nRelaxIter' : self.nRelaxIter,\n 'nSolveIter' : self.nSolveIter,\n 'nFeatureSnapIter' : self.nFeatureSnapIter,\n 'implicitFeatureSnap' : self.implicitFeatureSnap,\n 'explicitFeatureSnap' : self.explicitFeatureSnap,\n 'multiRegionFeatureSnap' : self.multiRegionFeatureSnap,\n },\n 'addLayersControls' :\n {\n 'relativeSizes' : self.relativeSizes,\n 'expansionRatio' : self.expansionRatio,\n 'finalLayerThickness' : self.finalLayerThickness,\n 'minThickness' : self.minThickness,\n 'nGrow' : self.nGrow,\n 'layers': layer_dict,\n 'featureAngle' : self.featureAngle,\n 'slipFeatureAngle' : self.slipFeatureAngle,\n 'nRelaxIter' : self.nRelaxIter,\n 'nSmoothSurfaceNormals' : self.nSmoothSurfaceNormals,\n 'nSmoothNormals' : self.nSmoothNormals,\n 'nSmoothThickness' : self.nSmoothThickness,\n 'maxFaceThicknessRatio' : self.maxFaceThicknessratio,\n 'maxThicknessToMedialRatio' : self.maxThicknessToMedialRatio,\n 'minMedianAxisAngle' : self.minMedianAxisAngle,\n 'nBufferCellsNoExtrude' : self.nBufferCellsNoExtrude,\n 'nLayerIter' : self.nLayerIter\n },\n 'meshQualityControls' :\n {\n '#include' : '\"meshQualityDict\"'\n },\n 'mergeTolerance' : self.mergeTolerance\n }\n with self.case.mutable_data_file(FileName.SNAPPY_HEX_MESH) as d:\n d.update(snappy_dict)","def getCityCodeDict():\n\n dictionary = {}\n f = open(filename1,'rb') \n\n dictionary = pickle.load(f)\n f.close()\n return dictionary","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 initialize(self,inputDict):\n pass","def get_gzipped_s3_objects_from_dict(session, event):\n return get_s3_objects_from_dict(\n session, event, default_unzip_s3_object_handler_function\n )","def __init__(self, sorter=None):\n self.entries = dict()\n self.super_entries = dict()\n self.sort = sorter\n with open(os.path.join(ROOT, 'database', 'cjk-decomp.txt')) as f:\n for row in f:\n entry, _, components = re.match('(.+):(.+)\\((.*)\\)', row).groups()\n comp_list = components.split(',')\n self.entries[entry] = comp_list\n for comp in comp_list:\n self.super_entries.setdefault(comp, []).append(entry)","def enter_dict(update_dict, path=\"current_request.txt\"):\n\n request_dict = RequestFileCom.file_to_dict(path)\n\n # Make sure no one changes the file content before finishes to update it.\n RequestFileCom.mutex.acquire()\n\n for key in update_dict:\n\n request_dict[key] = update_dict[key]\n\n request_file_string = \"\"\n\n for key in request_dict:\n\n request_file_string += key + \"::\" + request_dict[key] + \"\\n\"\n\n # Update the file.\n with open(path, \"w\") as f:\n\n f.write(request_file_string)\n\n RequestFileCom.mutex.release()\n\n request_dict = RequestFileCom.file_to_dict(path)","def __init__(self, url=\"https://ehw.fit.vutbr.cz/izv/\",folder=\"data\", cache_filename=\"data_{}.pkl.gz\"):\n self.url = url\n self.folder = folder\n self.cache_filename = cache_filename\n self.ListOfZipFiles = []\n self.saved_data = {}\n self.headers = [\"region\", \"p1\", \"p36\", \"p37\", \"p2a\", \"weekday(p2a)\", \"p2b\", \"p6\", \"p7\", \"p8\", \"p9\", \"p10\", \"p11\", \"p12\", \"p13a\", \"p13b\", \"p13c\", \"p14\", \"p15\", \"p16\", \"p17\", \"p18\", \"p19\", \"p20\", \"p21\", \"p22\", \"p23\", \"p24\", \"p27\", \"p28\", \"p34\", \"p35\", \"p39\", \"p44\", \"p45a\", \"p47\", \"p48a\", \"p49\", \"p50a\", \"p50b\", \"p51\", \"p52\", \"p53\",\"p55a\",\"p57\",\"p58\",\"a\",\"b\",\"d\",\"e\",\"f\",\"g\",\"h\",\"i\",\"j\",\"k\",\"l\",\"n\",\"o\",\"p\",\"q\",\"r\",\"s\",\"t\",\"p5a\"]\n self.duplicate_handling = []\n if not re.search(\"^.*{}.*$\", self.cache_filename):\n self.cache_filename+=\"{}\"","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 __init__(self,dir,factory=FileInfo):\n self.dir = dir\n self.factory=factory\n self.data = {}\n self.table = Table(os.path.join(self.dir,'Mash','Table.pkl'))\n self.corrupted = {} #--errorMessage = corrupted[fileName]","def write_zip_swapped(zip, replacement_dict):\n for from_file in replacement_dict:\n with open(from_file) as file:\n contents = file.read()\n\n zip.writestr(os.path.join('data/minecraft/', replacement_dict[from_file]), contents)","def pack():\n clean_local()\n build()\n copy_json()\n optimize()\n tarball()","def preprocess(self, newpath):\n return dict()","def store(self, filename):","def construct_alphabet():\n with open('alphabet.csv', 'r') as file_handler:\n dict_reader, alphabet = csv.DictReader(file_handler, delimiter=','), list()\n for row in dict_reader:\n alphabet.append(row)\n with open('../alphabet.py', 'w') as file_handler:\n file_handler.write(f'''\n\"\"\"Script containing the alphabet \"\"\"\n\nfrom collections import OrderedDict\n\nALPHABET = {alphabet}\n \n''')","def __compress(list_events):\r\n compress_dict = {}\r\n i = 0\r\n while i < len(list_events):\r\n # create a new event where keys and values are compressed\r\n comp_ev = {}\r\n for k, v in list_events[i].items():\r\n # check if the key has already been instantiated.\r\n # in that case, use the current instantiation.\r\n if k not in compress_dict:\r\n compress_dict[k] = k\r\n else:\r\n k = compress_dict[k]\r\n # check if the value has already been instantiated.\r\n # in that case, use the current instantiation\r\n if v not in compress_dict:\r\n compress_dict[v] = v\r\n else:\r\n v = compress_dict[v]\r\n # saves the compressed keys and values in the dictionary\r\n comp_ev[k] = v\r\n list_events[i] = comp_ev\r\n i = i + 1\r\n return list_events","def _to_load_dict(self, d: dict) -> dict:\n return _to_bucket_dict(d)","def map_file_data(file_obj, file_events):\n file_as_dict = {\n \"premis:originalName\": file_obj.currentlocation,\n \"original_name\": escape(file_obj.originallocation),\n # needs investigation\n \"sanitized_file_name\": get_sanitized_file_name(\n get_file_name_cleanup(file_events)\n ),\n \"prov:generatedAtTime\": file_obj.modificationtime.strftime(\n \"%Y-%m-%dT%H:%M:%SZ\"\n ),\n \"premis:fixity\": {\n \"checksum_type\": convert_to_premis_hash_function(file_obj.checksumtype),\n \"Checksum\": file_obj.checksum,\n },\n \"premis:identifier\": file_obj.uuid,\n \"premis:size\": file_obj.size,\n \"file_name\": file_obj.label,\n # not sure if this is the file name or if we should stick with\n \"dct:FileFormat\": map_file_format_info(\n get_file_format_event(file_events), get_file_validation_event(file_events)\n ),\n \"file_validation\": map_file_validation_info(\n get_file_validation_event(file_events)\n ),\n \"file_normalization\": map_file_normalization_info(\n get_file_normalization_event(file_events)\n ),\n \"events\": list_file_events(file_events),\n }\n return file_as_dict","def get_files_io():\n if GC.conf['general']['training']:\n files_zip = {\n 'raw': os.path.join(COOKED_DATA, 'train.txt'),\n 'new': os.path.join(COOKED_DATA, 'train_new.txt'),\n 'norm': os.path.join(COOKED_DATA, 'train_norm.txt'),\n 'manu': os.path.join(RAW_DATA, 'others', 'temp_updt_manu.txt'),\n 'labels': os.path.join(TRAIN_DATA, 'train_norm.txt_labels.pkl'),\n 'segll': os.path.join(TRAIN_DATA, 'train_norm.txt_seginf_loglab.pkl'),\n 'segdl': os.path.join(TRAIN_DATA, 'train_norm.txt_seginf_deeplog.pkl'),\n 'struct': os.path.join(TRAIN_DATA, 'train_norm.txt_structured.csv'),\n 'output': TRAIN_DATA\n }\n else:\n files_zip = {\n 'raw': os.path.join(COOKED_DATA, 'test.txt'),\n 'new': os.path.join(COOKED_DATA, 'test_new.txt'),\n 'norm': os.path.join(COOKED_DATA, 'test_norm.txt'),\n 'labels': os.path.join(TEST_DATA, 'test_norm.txt_labels.pkl'),\n 'segll': os.path.join(TEST_DATA, 'test_norm.txt_seginf_loglab.pkl'),\n 'segdl': os.path.join(TEST_DATA, 'test_norm.txt_seginf_deeplog.pkl'),\n 'map_norm_raw': os.path.join(TEST_DATA, 'map_norm_raw.pkl'),\n 'map_norm_rcv': os.path.join(TEST_DATA, 'map_norm_rcv.pkl'),\n 'norm_rcv': os.path.join(TEST_DATA, 'test_norm_rcv.txt'),\n 'struct': os.path.join(TEST_DATA, 'test_norm.txt_structured.csv'),\n 'struct_rcv': os.path.join(TEST_DATA, 'test_norm_rcv.txt_structured.csv'),\n 'top': os.path.join(TEST_DATA, 'analysis_summary_top.txt'),\n 'sum': os.path.join(TEST_DATA, 'analysis_summary.csv'),\n 'rst_llab': os.path.join(TEST_DATA, 'results_loglab.csv'),\n 'rst_dlog': os.path.join(TEST_DATA, 'results_deeplog.txt'),\n 'rst_llzr': os.path.join(TEST_DATA, 'results_loglizer.csv'),\n 'dbg': os.path.join(TEST_DATA, 'debug.csv'),\n 'output': TEST_DATA\n }\n return files_zip","def save_artefact(cls, cwd, hash, objects, trial, artefact_type='MODELS', **kwargs):\n\n objects_dir = '%s/%s' % (cwd, '.mantra/objects')\n\n if os.path.isfile('%s/%s/%s' % (objects_dir, hash[:2], hash[2:])):\n return False # hash already exists, we have already stored the object\n\n for item_key, item_value in objects.items():\n \n item_loc = '%s/%s/%s' % (objects_dir, item_value['hash'][:2], item_value['hash'][2:])\n\n if os.path.isfile(item_loc):\n continue\n\n hash_path = '%s/%s' % (objects_dir, item_value['hash'][:2])\n\n if not os.path.exists(hash_path):\n os.mkdir(hash_path)\n\n if item_value['type'] == 'tree':\n f = open(item_loc, \"wb\")\n f.write(zlib.compress(bytes(item_value['content'].encode('ascii'))))\n f.close()\n else:\n try:\n content = zlib.compress(open(item_key, \"rb\").read())\n f = open(item_loc, \"wb\")\n f.write(content)\n f.close() \n except:\n # TODO: https://bugs.python.org/issue27130 : need a formal workaround for file size > 2GB\n print('Warning: File Too Big to Compress')\n content = 'toobigtofail'\n f = open(item_loc, \"w\")\n f.write(content)\n f.close() \n\n unix_ts = int((datetime.datetime.utcnow() - datetime.datetime(1970, 1, 1)).total_seconds())\n f = open('%s/%s' % (cwd, '.mantra/%s' % artefact_type), \"a\")\n\n if artefact_type == 'MODELS':\n f.write('%s %s %s %s\\n' % (hash, unix_ts, trial.model_name, 'trained on %s' % trial.dataset_name))\n elif artefact_type == 'DATA':\n f.write('%s %s %s %s\\n' % (hash, unix_ts, trial.dataset_name, 'used with model %s' % trial.model_name))\n elif artefact_type == 'TASKS':\n f.write('%s %s %s %s\\n' % (hash, unix_ts, trial.task_name, 'used with model %s trained on %s' % (trial.model_name, trial.dataset_name)))\n f.close()\n\n return True","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 __init__(self, storage_directory, backup_filepath=None):\r\n self.record = defaultdict(str)\r\n if storage_directory.endswith('\\\\') or storage_directory.endswith('/'):\r\n self.storage_directory = storage_directory\r\n else:\r\n self.storage_directory = storage_directory + '\\\\'\r\n if backup_filepath is None:\r\n self.backup = self.storage_directory + 'mover_backup.json'\r\n else:\r\n self.backup = backup_filepath\r\n if os.path.isfile(self.backup):\r\n self.load_backup()\r\n logging.info('Initialized Backup')","def __init__(self,\n allowRepetition):\n self.__fileName = \"\"\n self.__allowRepetition = allowRepetition\n self.__keyObjs = {}\n self.__keyList = []\n self.__keyCount = {}\n self.__trailer = []","def __init__( self, generator):\n DictObject.__init__( self, generator.generate_dict())","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 __init__(self, resource_storage, path=\"\"):\n self._path = os.path.join(path, self._NAME)\n self._resource_storage = resource_storage\n self._write_archive_signature()\n self._write_archive_schema()\n self._resources_written = [f\"{self._NAME}.archive\"]","def create_dicts(filelist, class_out, **kwargs):\n\n c = TwoLevelCountDict()\n d = TwoLevelCountDict()\n m = TwoLevelCountDict()\n\n def _merge_dicts(tup):\n new_c, new_d, new_m = tup\n _merge_tlcd(c, new_c)\n _merge_tlcd(d, new_d)\n _merge_tlcd(m, new_m)\n print(len(c), len(d), len(m))\n\n pool = Pool(4)\n\n for f in filelist:\n #p = Process(target=_process_file, args=(f))\n pool.apply_async(_process_file, args=[f], callback=_merge_dicts)\n #_process_file(f, c, d, m)\n\n # Close the pool...\n pool.close()\n pool.join()\n\n # Write out the dicitonaries...\n c_f = open(c_path, 'wb')\n d_f = open(d_path, 'wb')\n m_f = open(m_path, 'wb')\n\n pickle.dump(c, c_f)\n pickle.dump(d, d_f)\n pickle.dump(m, m_f)\n c_f.close()","def compression(s):","def __init__(self, directory, mode=Mode.READONLY):\n if not os.path.exists(directory):\n raise IOError(\"Directory %s for raw store does not exist\"%\n directory)\n self.directory = directory\n with open(os.path.join(directory, \"__rawformat__\"), 'rb') as rawformat:\n self.__dict__.update(pickle.load(rawformat))\n \n fname = self.fname = os.path.join(directory, \"__store___\")\n colCache = self.colCacheDir = os.path.join(directory, \"__colstore___\")\n\n self._f = None\n self.mode = mode\n self._openfile()","def assemble(self, resetLocation: bool = ..., verbose: bool = ...) -> Union[Dict[AtomKey, numpy.array], Dict[HKT, numpy.array], None]:\n ...","def new_values(basenames):\n result = {}\n for basename in basenames:\n home = os.environ['HOME']\n p = os.path.join(home, basename)\n if not os.path.isfile(p):\n continue\n size = '%d' % p.size\n mtime = '%0.8f' % p.mtime\n result[basename] = Signature(mtime, size, text_digest(p.text()))\n return pad_keys(result, basenames)","def init_objects(file_input: str) -> Dict[str, ObjectMass]:\n objects = {}\n for line in file_input:\n orbit, orbiter = line.strip().split(\")\")\n\n orbit: ObjectMass = objects.setdefault(orbit, ObjectMass(orbit))\n orbiter: ObjectMass = objects.setdefault(orbiter, ObjectMass(orbiter))\n\n orbit.orbiters.append(orbiter)\n orbiter.orbit = orbit\n\n return objects","def __init__(self, filename, unique_keys):\n self.filename = filename\n self.data = None\n self.unique_keys = sorted(list(set(unique_keys)))\n self._reload()","def init_req_objs_gradle_with_args() -> Tuple[MultiDict, List[FileStorage]]:\n gradle_file = FileStorage(stream=open(GRADLE_WITH_ARGS_PATH, 'rb'),\n filename=GRADLE_WITH_ARGS_FILENAME,\n content_type=CONTENT_TYPE_ZIP)\n\n data = MultiDict([\n ('file', gradle_file)\n ])\n\n return data, [gradle_file]","def compile_metadata(inventory_dict):\n inventory_meta = {}\n #inventory_meta['InventoryDictionary'] = inventory_dict\n for source, year in inventory_dict.items():\n inventory_meta[source] = stewi.getMetadata(source, year)\n return inventory_meta","def __init__(self, cliDict):\r\n\r\n print(\"initializing Model\")\r\n #self.filename = filename\r\n #print(\"filename is \",self.filename)\r\n self.cliDict=cliDict\r\n self.objdict = {'HOSTNAME':'','IPADDRESS':'','LOG':'','VERBOSE':'','ORIGUSERNAME':'','TESTUSERNAME':'', \\\r\n 'PASSWORD7':'','PLAINTEXT':'','SECRET8':'','CHANGE':'','VERIFIED':'','NOTES-AND-ERRORS':''} \r\n #testing\r\n #self.path = 'e:/dougsprogs/convert7to8/convert728/'\r\n \r\n\r\n ##Main checks to see if Filename is blank\r\n #if filename :#filename is not blank.\r\n #self.checkFilename()\r\n #if filename is blank, create the default dict\r\n #else: #filename is blank \"\"\r\n self.loadDictRow()\r\n #loadDictValue(key=\"IPADDRESS\", value=str(ipaddress))\r\n #now check to create the default empty file\r\n #checkFilename()\r","def __init__(self, entries):\r\n if isinstance(entries, str): # filename\r\n self.contigs = readstatsFile(entries)\r\n else:\r\n self.contigs = OrderedDict()\r\n for entry in entries:\r\n self.contigs[entry.contigName] = entry","def make_compression_matrix(self, train_path, rng):\n self.compress_dim = 100 # value used in original DKT paper\n if rng:\n compress_matrix = rng.randn(self.encoding_dim, self.compress_dim)\n else:\n compress_matrix = np.random.randn(self.encoding_dim, self.compress_dim)\n\n np.savez(train_path + '-compression-matrix', compress_matrix=compress_matrix)\n return compress_matrix","def compress(self, src, dst):\n info = readelf_get_info(src)\n starting_size = os.path.getsize(src)\n if starting_size != info[\"size\"]:\n raise RuntimeError(\"size of file '%s' differs from header claim: %i != %i\" %\n (src, starting_size, info[\"size\"]))\n rfd = open(src, \"rb\")\n wfd = open(dst, \"wb\")\n data = rfd.read(starting_size)\n wfd.write(data[info[\"entry\"]:])\n rfd.close()\n wfd.close()\n self.__uncompressed_size = len(data) - info[\"entry\"]\n if is_verbose():\n print(\"Wrote compressable program block '%s': %i bytes\" % (dst, self.__uncompressed_size))\n self.__contexts = []\n self.__weights = []\n (so, se) = run_command([self.__command, dst])\n lines = so.split(\"\\n\")\n for ii in lines:\n terms = ii.split()\n if terms and terms[0].startswith(\"Final\"):\n compressed_size = int(terms[1])\n for jj in terms[2:]:\n individual_term = jj.split(\"*\")\n self.__weights += [int(individual_term[0], 10)]\n self.__contexts += [int(individual_term[1], 16)]\n if is_verbose():\n print(\"Program block compressed into '%s': %i bytes\" % (dst + \".pack\", compressed_size))\n print(\"Compression weights: %s\" % (str(self.__weights)))\n print(\"Compression contexts: %s\" % (str(self.__contexts)))\n rfd = open(dst + \".pack\", \"rb\")\n compressed_contexts = []\n compressed_weights = []\n uncompressed_size = rfd.read(4)\n uncompressed_size = (struct.unpack(\"I\", uncompressed_size))[0]\n if uncompressed_size != self.__uncompressed_size:\n raise RuntimeError(\"size given to packer does not match size information in file: %i != %i\" %\n (self.__uncompressed_size, uncompressed_size))\n context_count = rfd.read(1)\n context_count = (struct.unpack(\"B\", context_count))[0]\n for ii in range(context_count):\n compressed_weights += struct.unpack(\"B\", rfd.read(1))\n for ii in range(context_count):\n compressed_contexts += struct.unpack(\"B\", rfd.read(1))\n if compressed_contexts != self.__contexts:\n raise RuntimeError(\"contexts reported by packer do not match context information in file: %s != %s\" %\n (str(self.__contexts), str(compressed_contexts)))\n if compressed_weights != self.__weights:\n raise RuntimeError(\"weights reported by packer do not match weight information in file: %s != %s\" %\n (str(self.__weights), str(compressed_weights)))\n read_data = rfd.read()\n rfd.close()\n if len(read_data) != compressed_size:\n raise RuntimeError(\"size reported by packer does not match length of file: %i != %i\" %\n (compressed_size, len(read_data)))\n self.__data = []\n for ii in read_data:\n self.__data += struct.unpack(\"B\", ii)","def _load_transactions(self):\r\n\t\tlogger.debug(\"Enter\")\r\n\t\ttry:\r\n\t\t\twith open(self._state_file, 'rb') as tmp:\r\n\t\t\t\tlogger.debug(\"There is a file.\")\r\n\t\t\t\ttmp_dict = pickle.load(tmp)\r\n\t\t\t\tlogger.debug(\"Dictionary loaded from file: %s\" % tmp_dict)\r\n\t\texcept IOError as e: # File doesn't exists\r\n\t\t\tlogger.debug(\"Exit - No file. Error message: %s\" % e)\r\n\t\t\ttmp_dict = {}\r\n\t\t\t\r\n\t\treturn tmp_dict","def test_add_dict_ordered(self):\n with DataArchive(self.user, DATA_DOWNLOADS_WORKING_DIR) as archive:\n data_to_write = OrderedDict((('first', \"łorld!\"), ('second', \"łup!\")))\n file_path = archive.add_dict('testfile', data_to_write)\n self.assertTrue(os.path.isfile(file_path))\n\n valid_output_path = os.path.join(archive.data_dir_path, 'testfile.txt')\n self.assertEqual(file_path, valid_output_path)\n\n with open(file_path, 'r') as fp:\n saved_data = fp.read().strip()\n self.assertEqual(saved_data, \"first: łorld!\\nsecond: łup!\")","def finalize(self, dest: OrderedDict = None):","def updateDictFile(self):\n if self.dictFile.vdata.get('version',0): return\n #--Update to version 1\n for name in self.data.keys():\n installer = self.data[name]\n if isinstance(installer,Installer):\n self.data[name] = installer.__copy__(InstallerArchive)\n self.dictFile.vdata['version'] = 1","def getAircraftCodeDict():\n\n dictionary = {}\n f = open(filename2,'rb') \n\n dictionary = pickle.load(f)\n f.close()\n return dictionary","def processfile(args, fh):\n if args.quick:\n scanner = quickScanZip(args, fh)\n else:\n scanner = findPKHeaders(args, fh)\n\n def checkarg(arg, ent):\n if not arg:\n return False\n return '*' in arg or ent.name in arg\n def checkname(a, b):\n if a and '*' in a: return True\n if b and '*' in b: return True\n l = 0\n if a: l += len(a)\n if b: l += len(b)\n return l > 1\n\n if args.verbose and not (args.cat or args.raw or args.save):\n print(\" 0304 need flgs mth stamp --crc-- compsize fullsize nlen xlen namofs xofs datofs endofs\")\n print(\" 0102 crea need flgs mth stamp --crc-- compsize fullsize nlen xlen clen dsk0 attr osattr datptr namofs xofs cmtofs endofs\")\n for ent in scanner:\n if args.cat or args.raw or args.save:\n if args.quick and isinstance(ent, CentralDirEntry) or \\\n not args.quick and isinstance(ent, LocalFileHeader):\n ent.loaditems(fh)\n do_cat = checkarg(args.cat, ent)\n do_raw = checkarg(args.raw, ent)\n do_save= checkarg(args.save, ent)\n\n do_name= checkname(args.cat, args.raw)\n\n if do_name:\n print(\"\\n===> \" + ent.name + \" <===\\n\")\n\n sys.stdout.flush()\n blks = zipraw(fh, ent)\n\n if args.password and ent.flags&1:\n blks = zip_decrypt(blks, args.password)\n if do_cat or do_save:\n blks = skipbytes(blks, 12, args)\n\n if do_cat:\n sys.stdout.buffer.writelines(zipcat(blks, ent))\n if do_raw:\n sys.stdout.buffer.writelines(blks)\n if do_save:\n savefile(args.outputdir, ent.name, zipcat(blks, ent))\n else:\n ent.loaditems(fh)\n if args.verbose or not args.quick:\n print(\"%08x: %s\" % (ent.pkOffset, ent))\n else:\n print(ent.summary())\n if hasattr(ent, \"comment\") and ent.comment and not args.dumpraw:\n print(ent.comment)\n if args.dumpraw and hasattr(ent, \"extraLength\") and ent.extraLength:\n print(\"%08x: XTRA: %s\" % (ent.extraOffset, binascii.b2a_hex(getbytes(fh, ent.extraOffset, ent.extraLength))))\n if args.dumpraw and hasattr(ent, \"comment\") and ent.comment:\n print(\"%08x: CMT: %s\" % (ent.commentOffset, binascii.b2a_hex(getbytes(fh, ent.commentOffset, ent.commentLength))))\n if args.dumpraw and isinstance(ent, LocalFileHeader):\n blks = zipraw(fh, ent)\n if args.password and ent.flags&1:\n blks = zip_decrypt(blks, args.password)\n\n blockdump(ent.dataOffset, blks)","def create_dictionary_of_old_and_new_paths(raw_dir: Path, bids_dir: Path, exclude_fieldmaps: bool) -> dict:\n\n old_and_new_paths = {}\n old_paths = list(raw_dir.rglob(\"*\"))\n print(f\"Sorting {len(old_paths)} paths into a dictionary.\") \n\n def task_name_of(path_to_func_or_json):\n \"\"\"\n Returns the task name of a func or json file. This function OVERWRITES the function\n \"task_name_of\" that we imported at the top of this script. BUT! It only overwrites it\n HERE, in \"create_dictionary_of_old_and_new_paths\".\n \"\"\"\n\n list_of_lines_containing_raw_subject_info = []\n for path in old_paths:\n if filetype_of(path) == \"subject info\":\n list_of_lines_containing_raw_subject_info = path.read_text().splitlines()\n break\n\n for line in list_of_lines_containing_raw_subject_info:\n if path_to_func_or_json.stem in line:\n return line.split(\"z\")[1]\n\n\n for old_path in old_paths:\n\n new_path = old_path\n\n if filetype_of(old_path.with_suffix(\".nii\")) == \"anat\" and acquisition_number_of(old_path) == \"14\":\n new_path = bids_dir / f\"sub-{subject_id_of(old_path)}\" / \"anat\" / f\"sub-{subject_id_of(old_path)}_T1w{old_path.suffix}\"\n\n elif filetype_of(old_path.with_suffix(\".nii\")) == \"func\" and acquisition_number_of(old_path) != \"02\":\n new_path = bids_dir / f\"sub-{subject_id_of(old_path)}\" / \"func\" / f\"sub-{subject_id_of(old_path)}_task-{task_name_of(old_path)}_acq-{acquisition_number_of(old_path)}_bold{old_path.suffix}\"\n\n elif filetype_of(old_path.with_suffix(\".nii\")) == \"fieldmap\" and not exclude_fieldmaps:\n old_affix = old_path.stem.split(\"_\")[-1]\n new_affix = \"phasediff\"\n if old_affix == \"e1\":\n new_affix = \"magnitude1\"\n if old_affix == \"e2\":\n new_affix = \"magnitude2\"\n new_path = bids_dir / f\"sub-{subject_id_of(old_path)}\" / \"fmap\" / f\"sub-{subject_id_of(old_path)}_{new_affix}{old_path.suffix}\"\n\n old_and_new_paths[old_path] = new_path\n\n print(\"Paths sorted.\")\n\n return old_and_new_paths","def create_json(case_dict):\n # ---------------------------------------------------------------------\n logger.debug(\"create_json\")\n\n if not os.path.exists(\"{0}/archive_files\".format(case_dict[\"workdir\"])):\n os.makedirs(\"{0}/archive_files\".format(case_dict[\"workdir\"]))\n\n filename = \"{0}/archive_files/json.{1}\".format(\n case_dict[\"workdir\"], datetime.datetime.now().strftime(\"%Y%m%d-%H%M%S\")\n )\n with io.open(filename, \"wb\") as fname:\n jstr = str(json.dumps(case_dict, indent=4, sort_keys=True, ensure_ascii=False))\n if isinstance(jstr, str):\n jstr = jstr.decode(\"utf-8\")\n fname.write(jstr)\n fname.close()","def Dictionary_create_from(nMarkers, markerSize, baseDictionary):\n pass","def revert(self):\n headerdump = self.file.readp(0, 16)\n if sum(headerdump):\n dictat,dictlen = struct.unpack(\"<QQ\", headerdump)\n dictblob = self.file.readp(dictat, dictlen)\n self.keys = pickle.loads(dictblob)\n self.buffered = {}\n self.cache = {}\n self.awaitingpunch = []\n\n else:\n self.keys = {}\n self.buffered = {}\n self.cache = {}\n self.awaitingpunch = []","def __init__(self, dictionary_paths):\n files = [open(path, 'r') for path in dictionary_paths]\n dictionaries = [yaml.load(dict_file) for dict_file in files]\n map(lambda x: x.close(), files)\n self.dictionary = {}\n self.max_key_size = 0\n for curr_dict in dictionaries:\n for key in curr_dict:\n if key in self.dictionary:\n self.dictionary[key].extend(curr_dict[key])\n else:\n self.dictionary[key] = curr_dict[key]\n self.max_key_size = max(self.max_key_size, len(key))","def test_add_dict(self):\n with DataArchive(self.user, DATA_DOWNLOADS_WORKING_DIR) as archive:\n data_to_write = {'first': \"łorld!\", 'second': \"łup!\"}\n file_path = archive.add_dict('testfile', data_to_write)\n self.assertTrue(os.path.isfile(file_path))\n\n valid_output_path = os.path.join(archive.data_dir_path, 'testfile.txt')\n self.assertEqual(file_path, valid_output_path)\n\n with open(file_path, 'r') as fp:\n saved_data = fp.read().strip()\n # order of dict items in py<3.6 is non-deterministic\n # making testing for exact match a mistake\n self.assertIn(\"first: łorld!\", saved_data)\n self.assertIn(\"second: łup!\", saved_data)","def _get_create_dataset_kwargs(self):\n kwargs = {}\n if self.compress_dataset():\n kwargs.update({'compression': \"gzip\", 'compression_opts': 9})\n return kwargs","def load_dictionary(cls, args, filename, source=True):\n dictionary = Dictionary.load(filename)\n dictionary.add_symbol(\"<mask>\")\n return dictionary","def __init__(self, data_file_path):\n self._inventory = Inventory(data_file_path)\n self._baskets = {}","def _initialise_handler(self, filename, host, port, key_prefix):\n \n key = os.path.split(filename)[-1] # Is there a better way to construct a unique key?\n # Perhaps take the hash *from the file contents*.\n # At present, the filename seems sufficient.\n \n if key_prefix is None:\n raise ValueError(\"A key prefix (string) must be specified for the RedisDataHandler.\")\n \n key = '{key_prefix}::{hashed_key}'.format(key_prefix=key_prefix, hashed_key=hash(key))\n \n cache = redis.StrictRedis(host=host, port=port, db=0)\n \n if cache.get(key):\n dumped = cache.get(key)\n return cPickle.loads(dumped)\n \n # If we get here, the TrecQrelsHandler does not exist in the cache; create it, dump it.\n handler = super(RedisDataHandler, self)._initialise_handler(filename)\n dumped = cPickle.dumps(handler)\n cache.set(key, dumped)\n \n return handler","def __init__(self, path):\n super(ZIPStorageFileReader, self).__init__(path)\n self._storage_file = ZIPStorageFile()\n self._storage_file.Open(path=path)","def make_json(prefix, input_dir):\n # get list of files\n file_list = os.listdir(input_dir)\n # set reference sequence\n tracklist = {'formatVersion': 1,\n 'refSeqs': '%s.ref.fa.fai' % prefix,\n 'tracks': []}\n # add reference sequence track to tracklist.json\n tracklist['tracks'].append({\"category\": \"Reference sequence\",\n \"key\": \"Reference sequence\",\n \"label\": \"Reference sequence\",\n \"type\": \"SequenceTrack\",\n \"storeClass\": \"JBrowse/Store/SeqFeature/IndexedFasta\",\n \"urlTemplate\": \"%s.ref.fa\" % prefix,\n \"refSeqOrder\": \"False\"})\n tracklist['tracks'].append({\"category\": \"Consensus sequence\",\n \"key\": \"Consensus sequence\",\n \"label\": \"Consensus sequence\",\n \"type\": \"SequenceTrack\",\n \"storeClass\": \"JBrowse/Store/SeqFeature/IndexedFasta\",\n \"urlTemplate\": \"%s.cons.fa\" % prefix,\n \"refSeqOrder\": \"False\"})\n # add bigwig track to trackList.json\n tracklist['tracks'].append({\"category\": \"Sequence data\",\n \"key\": \"Coverage\",\n \"label\": \"Coverage\",\n \"type\": \"JBrowse/View/Track/Wiggle/XYPlot\",\n \"storeClass\": \"JBrowse/Store/SeqFeature/BigWig\",\n \"autoscale\": \"local\",\n \"urlTemplate\": \"%s.sorted.bw\" % prefix\n })\n # add BAM Sequence Coverage to trackList.json\n tracklist['tracks'].append({\"category\": \"Sequence data\",\n \"key\": \"Sequence reads (SNPs/Coverage)\",\n \"label\": \"Sequence reads (SNPs/Coverage)\",\n \"type\": \"JBrowse/View/Track/SNPCoverage\",\n \"storeClass\": \"JBrowse/Store/SeqFeature/BAM\",\n \"urlTemplate\": \"%s.sorted.capped.bam\" % prefix,\n \"cacheMismatches\": \"True\",\n \"chunkSizeLimit\": \"5000000\"\n })\n # add BAM Sequence Alignments to trackList.json\n tracklist['tracks'].append({\"category\": \"Sequence data\",\n \"key\": \"Sequence reads (Alignment)\",\n \"label\": \"Sequence reads (Alignment)\",\n \"type\": \"JBrowse/View/Track/Alignments2\",\n \"storeClass\": \"JBrowse/Store/SeqFeature/BAM\",\n \"urlTemplate\": \"%s.sorted.capped.bam\" % prefix,\n # add bigwig histogram option\n \"cacheMismatches\": \"True\",\n \"chunkSizeLimit\": \"5000000\"\n })\n # add GFF3 file to trackList.json\n tracklist['tracks'].append({\"category\": \"Annotation\",\n \"key\": \"Genbank annotation\",\n \"label\": \"Genbank annotation\",\n \"type\": \"JBrowse/View/Track/CanvasFeatures\",\n \"urlTemplate\": \"%s.gff3.gz\" % prefix,\n \"style\": {\n \"_defaultHistScale\": 4,\n \"_defaultLabelScale\": 30,\n \"_defaultDescriptionScale\": 120,\n # Comma-separated list of case-insensitive feature tags to use\n # for showing the feature's label.\n # The first one found will be used. Default 'name,id'.\n \"label\": \"product,id\",\n # style→description\tComma-separated list of case-insensitive\n # feature tags to check for the feature's long description.\n # The first one found will be used. Default 'note,description'.\n # If blank no description is used.\n \"description\": \"note, description\"\n },\n })\n\n json_path = os.path.join(input_dir, 'trackList.json')\n with open(json_path, 'wt') as output_handle:\n json_raw_str = json.dumps(tracklist, indent=4)\n output_handle.write(json_raw_str)\n return 'trackList.json'","def shelve_dump(file_name: str, **kwargs):\n with shelve.open(os.path.splitext(file_name)[0]) as db:\n for k, v in kwargs.items():\n db[k] = v","def populated_archivist_dataset(archivist_dataset, tmp_path_factory):\n wpath = tmp_path_factory.mktemp(\"archivistds\")\n\n ads = archivist_dataset\n\n dscontent = (\n ('azip/file1.txt', 'zipfile1'),\n ('azip/file2.csv', 'zipfile2_muchcontent'),\n ('atar/file1.txt', 'tarfile1'),\n ('atar/file2.csv', 'tarfile2_muchcontent'),\n )\n srcds = Dataset(wpath / 'srcds').create(**nonoise)\n for fpath, fcontent in dscontent:\n fpath = srcds.pathobj / (PurePosixPath(fpath))\n fpath.parent.mkdir(parents=True, exist_ok=True)\n fpath.write_text(fcontent)\n srcds.save(**nonoise)\n\n archive_root = wpath / 'myarchive'\n #archivetype = 'zip'\n\n akeys = {}\n\n # no ZIP just yet\n # for archivetype, ext in (('zip', ''), ('tar', '.gz')):\n for archivetype, ext in (('tar', '.gz'), ):\n archive_path = Path(f\"{archive_root}.{archivetype}{ext}\")\n\n archive_path_inds = ads.pathobj / '.archives' / archive_path.name\n # create an archive, the easy way, by simply exporting the\n # entire dataset worktree\n srcds.export_archive(archive_root, archivetype=archivetype,\n **nonoise)\n assert archive_path.exists()\n\n # add the archive (in a hidden dir) to be able to reference\n # it via a key\n aurl = archive_path.as_uri()\n ads.repo.call_annex([\n 'addurl', '--file', str(archive_path_inds), aurl])\n ads.save(**nonoise)\n # get the key of the archive\n akeys[archivetype] = ads.status(\n archive_path_inds, annex='basic', return_type='item-or-list',\n **nonoise)['key']\n return ads, akeys, archive_root, dscontent"],"string":"[\n \"def _files_from_json(self, file_json):\\n self.compressed_file_json = zlib.compress(json.dumps(file_json).encode('utf-8'))\\n self.compression_algorithm = 'gzip'\\n self.compressed_content_hash = hashlib.sha256(self.compressed_file_json).hexdigest()\",\n \"def file_to_dictionary():\\n\\n return;\",\n \"def __init__(self):\\n self.keyingMethod=fileSize\\n self.keyToFile=dict()\",\n \"def read_archive(self):\\n print '------------------------------------'\\n print ' Archiving the simulation results'\\n print ' '\\n self.archive = {}\\n with open(self.archive_data, 'r') as f:\\n for line in f:\\n (key, val) = line.split()\\n self.archive[(key)] = val\",\n \"def dosomething(file_dict2, path, buf):\\n file_dict2[path] = {\\\"Extension\\\": 1, \\\"Hash value\\\": 1}\\n return file_dict2\",\n \"def _generate_inventory(self, datapath):\\n \\n files = [file for file in listdir(datapath) if '.nc' in file and not 'xyz' in file]\\n # file_prefixes = list(set([ file.split('_')[0] for file in files ]))\\n # file_prefixes = list(set([ \\\"_\\\".join(file.split('_')[0:2]) for file in files ]))\\n if self.extra_pref:\\n file_prefixes = list(set([ \\\"_\\\".join(file.split('_')[0:2] + [self.extra_pref]) for file in files ]))\\n else:\\n file_prefixes = list(set([ \\\"_\\\".join(file.split('_')[0:2]) for file in files ]))\\n \\n inventory = {}\\n for file_prefix in file_prefixes:\\n fname = path.join(datapath,f'{file_prefix}{self.first_suffix}')\\n if not self.metafile:\\n self.metafile = fname\\n vars = [ var for var in list(Dataset(fname).variables) if var not in self.skip_vars ]\\n for var in vars:\\n inventory[var] = {'files': sorted([path.join(datapath,file) \\n for file in listdir(datapath) if file_prefix in file])}\\n return inventory\",\n \"def init() -> None:\\n init_dict()\\n parse_file(\\\"alphabet.txt\\\", letters)\\n parse_file(\\\"numbers.txt\\\", numbers)\\n parse_file(\\\"symbols.txt\\\", symbols)\",\n \"def run(self):\\n self.compress(\\n self.__config.public_key(),\\n self.__config.input_dir(),\\n self.__config.output_dir(),\\n self.__config.suffix()\\n )\",\n \"def zip_files(dict_files, compression=zipfile.ZIP_DEFLATED):\\n in_memory = StringIO()\\n\\n with zipfile.ZipFile(in_memory, 'w', compression) as zf:\\n for fname, fp in dict_files.iteritems():\\n zf.writestr(fname, fp.read())\\n\\n zf.close()\\n\\n in_memory.seek(0)\\n\\n return in_memory\",\n \"def init(sFileName, sDescription):\\n \\n try:\\n with open(sFileName) as f:\\n my_dict = json.load(f)\\n \\n \\n except:\\n \\n #assume there was an error, possibly the file does not exist\\n my_dict = {'descriptor':sDescription ,'measurements':[]}\\n with open (sFileName, 'w') as f:\\n json.dump(my_dict,f)\\n \\n return my_dict\",\n \"def read_archive(self):\\n print '------------------------------------'\\n print ' Archiving the simulation results'\\n print '----------------------------------- '\\n\\n if self.Simulation_area.lower() == 'barrow':\\n os.chdir(self.control['Run_dir']+self.Input_directory+'/Barrow/')\\n elif self.Simulation_area.lower() == 'tanana':\\n os.chdir(self.control['Run_dir']+self.Input_directory+'/Tanana/')\\n elif self.Simulation_area.lower() == 'yukon':\\n os.chdir(self.control['Run_dir']+self.Input_directory+'/Yukon/')\\n \\n self.archive = {}\\n with open(self.archive_data, 'r') as f:\\n for line in f:\\n if line.startswith('#'):\\n continue\\n else:\\n (key, val) = line.split()\\n self.archive[(key)] = val\",\n \"def _build_dictionary(self):\\n print(\\\"Building Dictionary...\\\")\\n self.dictionary = Dictionary(self.load_files())\",\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 compress_file(map_, name, save_path):\\n size = os.path.getsize(save_path)\\n temp = subprocess.run([\\\"gzip\\\", \\\"-k\\\", save_path])\\n cr_size = os.path.getsize(save_path+\\\".gz\\\")\\n try:\\n map_[name] = cr_size / size\\n except Exception as e:\\n print(f\\\"File: {save_path}, Ori:{size}, Compr:{cr_size}\\\")\\n print(e)\\n raise ZeroDivisionError\\n temp = subprocess.run([\\\"rm\\\", save_path])\\n temp = subprocess.run([\\\"rm\\\", save_path+\\\".gz\\\"])\",\n \"def reinit(self):\\n self.keys = {}\\n fh = open(self.path, \\\"w\\\")\\n json.dump(self.keys, fh)\\n fh.close()\\n os.chmod(self.path, 0o600)\",\n \"def __init__(\\n self, basedir: str, primary_key: Optional[List[int]] = None,\\n replace: Optional[bool] = False, serializer: Optional[ArchiveSerializer] = None,\\n compression: Optional[str] = None, encoder: Optional[json.JSONEncoder] = None,\\n decoder: Optional[Callable] = None\\n ):\\n self.basedir = util.createdir(basedir)\\n self._primary_key = primary_key\\n self.serializer = serializer if serializer else DefaultSerializer()\\n self.compression = compression\\n self.encoder = encoder if encoder is not None else DefaultEncoder\\n self.decoder = decoder if decoder is not None else default_decoder\\n # Initialize the file names\\n self.datafile = os.path.join(self.basedir, 'rows.dat')\\n self.metafile = os.path.join(self.basedir, 'metadata.dat')\\n self.tmpdatafile = os.path.join(self.basedir, 'rows.tmp')\\n self.tmpmetafile = os.path.join(self.basedir, 'metadata.tmp')\\n if not replace and os.path.isfile(self.metafile):\\n # Read schema and snapshot information from disk if the metadata\\n # file exists.\\n with open(self.metafile, 'r') as f:\\n doc = json.load(f, object_hook=self.decoder)\\n # Deserialize schema columns.\\n columns = list()\\n for c in doc.get(META_SCHEMA, []):\\n columns.append(self.serializer.deserialize_column(c))\\n self.schema = ArchiveSchema(columns=columns)\\n # Deserialize snapshot descriptors\\n snapshots = list()\\n for s in doc.get(META_SNAPSHOTS, []):\\n snapshots.append(self.serializer.deserialize_snapshot(s))\\n self.snapshots = SnapshotListing(snapshots=snapshots)\\n # Deserialize row counter.\\n self.row_counter = doc.get(META_ROWCOUNT, 0)\\n # Overwrite primary key if it is present in the metadata file.\\n if self._primary_key:\\n doc[META_PRIMARYKEY] = self._primary_key\\n with open(self.tmpmetafile, 'w') as f:\\n json.dump(doc, f, cls=self.encoder)\\n else:\\n self._primary_key = doc[META_PRIMARYKEY]\\n else:\\n # Create an empty archive.\\n self.schema = ArchiveSchema()\\n self.snapshots = SnapshotListing()\\n self.row_counter = 0\\n # Remove any previous files that may exist in the base folder.\\n for f in [self.datafile, self.metafile]:\\n if os.path.isfile(f):\\n os.remove(f)\\n # Write primary key to metadata file.\\n with open(self.metafile, 'w') as f:\\n json.dump({META_PRIMARYKEY: self._primary_key}, f)\",\n \"def prepare(self):\\n\\t\\tif len(os.listdir(self.storagedir)):\\n\\t\\t\\traise Exception(\\\"There are already files in\\\", self.storagedir + \\\".\\\", \\\"Delete manually!\\\")\\n\\t\\t\\n\\t\\tself.worddict = {\\\"__pad__\\\": 0, \\\"__oov__\\\": 1}\\n\\t\\tself.classdict = {}\\n\\t\\tself.raw_documents, self.tokenized_documents = {}, {}\\n\\t\\tself.X, self.Y = {}, {}\\n\\n\\t\\tfor dataset in self.DATASETS_TMP:\\n\\t\\t\\tself.get_raw_data(dataset)\\n\\t\\t\\tself.delete_empty_documents(dataset)\\n\\t\\t\\tself.tokenize_documents(dataset)\\n\\n\\t\\tself.make_classdict()\\n\\t\\tself.make_worddict()\\n\\t\\tself.make_embeddings()\\n\\t\\tself.reverse_dicts()\\n\\n\\t\\tfor dataset in self.DATASETS_TMP:\\n\\t\\t\\tself.make_X(dataset)\\n\\t\\t\\tself.shuffle_dataset(dataset)\\n\\n\\t\\tif not \\\"dev\\\" in self.X:\\n\\t\\t\\tself.split_dev()\\t\\t\\n\\t\\tself.make_hybrid()\\n\\t\\tself.store()\",\n \"def store_harvest(self, file_prefix, data):\\n compressed = bz2.compress(data)\\n k = f\\\"{self.harvest_key_prefix}/{self.harvest_date}/{file_prefix}.bz2\\\"\\n self.s3_client.put_object(\\n Body=compressed,\\n Bucket=self.s3_bucket,\\n Key=k,\\n )\",\n \"def preload(self):\\n # load the objects\\n for otype, fname in self.TYPE2NAME.items():\\n if fname:\\n path = os.path.join(self.anodir, fname + \\\".gz\\\")\\n if os.path.isfile(path):\\n with gzip.open(path, \\\"rt\\\") as handler:\\n for line in handler:\\n omap = json.loads(line)\\n cls = self.TYPE2CLASS[otype]\\n item = cls.from_map(omap, self)\\n self.caches[otype][item.id] = item\",\n \"def create_zip_dict() -> dict:\\n with open('zip_coordinates.json', 'r') as zip_map:\\n return json.loads(zip_map.read())\",\n \"def prepare_fastq(self) -> dict:\\r\\n\\r\\n fastq = {}\\r\\n for organism, data in self.composition.items():\\r\\n file = data['file']\\r\\n file_path = Path(file)\\r\\n if not file_path.exists():\\r\\n raise ValueError(f'File {file_path} does not exist.')\\r\\n else:\\r\\n fastq[organism] = pyfastx.Fastq(file)\\r\\n\\r\\n self.logger.info('Prepared read files - proceeding')\\r\\n\\r\\n return fastq\",\n \"def __init__(self, filename,chainlen,encoding = None):\\n self.encoding=encoding\\n dict.__init__(self)\\n self.chainlen = chainlen\\n self.filename = filename\\n self.populate()\",\n \"def make_file_dict():\\r\\n fileDict = {'pageUrls': [],\\r\\n 'pageFileNames': [],\\r\\n 'pageIds': [],\\r\\n 'fileUrls': [],\\r\\n 'fileIds': [],\\r\\n 'fileNames': [],\\r\\n 'cssUrls': [],\\r\\n 'cssFileNames': [],\\r\\n 'imgUrls': [],\\r\\n 'imgFileNames': []}\\r\\n return fileDict\",\n \"def pre_lookup(self, file):\\n return {}\",\n \"def create(self):\\n\\n for sample_name, sample_info in self.samples.items():\\n if not sample_info[\\\"use_it\\\"]:\\n continue\\n process_name = sample_info[\\\"process_name_specific\\\"]\\n sample_category = sample_info[\\\"sample_category\\\"]\\n is_mc = (sample_info[\\\"type\\\"] == \\\"mc\\\")\\n\\n logging.info(\\\"Building dictionaries for sample %s...\\\" % process_name)\\n for charge_selection in self.charge_selections:\\n central_or_shift_extensions = [\\\"\\\", \\\"hadd\\\", \\\"addBackgrounds\\\"]\\n central_or_shifts_extended = central_or_shift_extensions + self.central_or_shifts\\n for central_or_shift_or_dummy in central_or_shifts_extended:\\n process_name_extended = [ process_name, \\\"hadd\\\" ]\\n for process_name_or_dummy in process_name_extended:\\n if central_or_shift_or_dummy in [ \\\"hadd\\\" ] and process_name_or_dummy in [ \\\"hadd\\\" ]:\\n continue\\n if central_or_shift_or_dummy != \\\"central\\\" and central_or_shift_or_dummy not in central_or_shift_extensions:\\n if not is_mc:\\n continue\\n if not self.accept_central_or_shift(central_or_shift_or_dummy, sample_info):\\n continue\\n\\n key_dir = getKey(process_name_or_dummy, charge_selection, central_or_shift_or_dummy)\\n for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES ]:\\n initDict(self.dirs, [ key_dir, dir_type ])\\n if dir_type in [ DKEY_CFGS, DKEY_LOGS ]:\\n self.dirs[key_dir][dir_type] = os.path.join(self.get_dir_type(dir_type), dir_type, self.channel,\\n \\\"_\\\".join([ charge_selection ]), process_name_or_dummy, central_or_shift_or_dummy)\\n else:\\n self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel,\\n \\\"_\\\".join([ charge_selection ]), process_name_or_dummy)\\n for subdirectory in [ \\\"comp_jetToTauFakeRate\\\", \\\"makePlots\\\" ]:\\n key_dir = getKey(subdirectory)\\n for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT ]:\\n initDict(self.dirs, [ key_dir, dir_type ])\\n if dir_type in [ DKEY_CFGS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT ]:\\n self.dirs[key_dir][dir_type] = os.path.join(self.get_dir_type(dir_type), dir_type, self.channel, subdirectory)\\n else:\\n self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel, subdirectory)\\n for dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT ]:\\n initDict(self.dirs, [ dir_type ])\\n if dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT ]:\\n self.dirs[dir_type] = os.path.join(self.get_dir_type(dir_type), dir_type, self.channel)\\n else:\\n self.dirs[dir_type] = os.path.join(self.outputDir, dir_type, self.channel)\\n\\n numDirectories = 0\\n for key in self.dirs.keys():\\n if type(self.dirs[key]) == dict:\\n numDirectories += len(self.dirs[key])\\n else:\\n numDirectories += 1\\n logging.info(\\\"Creating directory structure (numDirectories = %i)\\\" % numDirectories)\\n numDirectories_created = 0;\\n frac = 1\\n for key in self.dirs.keys():\\n if type(self.dirs[key]) == dict:\\n for dir_type in self.dirs[key].keys():\\n create_if_not_exists(self.dirs[key][dir_type])\\n numDirectories_created += len(self.dirs[key])\\n else:\\n create_if_not_exists(self.dirs[key])\\n numDirectories_created = numDirectories_created + 1\\n while 100*numDirectories_created >= frac*numDirectories:\\n logging.info(\\\" %i%% completed\\\" % frac)\\n frac = frac + 1\\n logging.info(\\\"Done.\\\")\\n\\n inputFileLists = {}\\n for sample_name, sample_info in self.samples.items():\\n if not sample_info[\\\"use_it\\\"]:\\n continue\\n logging.info(\\\"Checking input files for sample %s\\\" % sample_info[\\\"process_name_specific\\\"])\\n inputFileLists[sample_name] = generateInputFileList(sample_info, self.max_files_per_job)\\n\\n self.inputFileIds = {}\\n for sample_name, sample_info in self.samples.items():\\n if not sample_info[\\\"use_it\\\"]:\\n continue\\n\\n process_name = sample_info[\\\"process_name_specific\\\"]\\n inputFileList = inputFileLists[sample_name]\\n\\n logging.info(\\\"Creating configuration files to run '%s' for sample %s\\\" % (self.executable_analyze, process_name))\\n\\n is_mc = (sample_info[\\\"type\\\"] == \\\"mc\\\")\\n sample_category = sample_info[\\\"sample_category\\\"]\\n\\n for charge_selection in self.charge_selections:\\n for central_or_shift in self.central_or_shifts:\\n \\n if central_or_shift != \\\"central\\\" and not is_mc:\\n continue\\n if not self.accept_central_or_shift(central_or_shift, sample_info):\\n continue\\n\\n # build config files for executing analysis code\\n key_analyze_dir = getKey(process_name, charge_selection, central_or_shift)\\n\\n for jobId in inputFileList.keys():\\n\\n analyze_job_tuple = (process_name, charge_selection, central_or_shift, jobId)\\n key_analyze_job = getKey(*analyze_job_tuple)\\n ntupleFiles = inputFileList[jobId]\\n if len(ntupleFiles) == 0:\\n logging.warning(\\\"No input ntuples for %s --> skipping job !!\\\" % (key_analyze_job))\\n continue\\n\\n cfgFile_modified_path = os.path.join(self.dirs[key_analyze_dir][DKEY_CFGS], \\\"analyze_%s_%s_%s_%i_cfg.py\\\" % analyze_job_tuple)\\n logFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_LOGS], \\\"analyze_%s_%s_%s_%i.log\\\" % analyze_job_tuple)\\n histogramFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_HIST], \\\"analyze_%s_%s_%s_%i.root\\\" % analyze_job_tuple)\\n rleOutputFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_RLES], \\\"rle_%s_%s_%s_%i.txt\\\" % analyze_job_tuple) \\\\\\n if self.select_rle_output else \\\"\\\"\\n\\n self.jobOptions_analyze[key_analyze_job] = {\\n 'ntupleFiles' : ntupleFiles,\\n 'cfgFile_modified' : cfgFile_modified_path,\\n 'histogramFile' : histogramFile_path,\\n 'logFile' : logFile_path,\\n 'chargeSelection' : charge_selection,\\n 'jet_minPt' : self.jet_minPt,\\n 'jet_maxPt' : self.jet_maxPt,\\n 'jet_minAbsEta' : self.jet_minAbsEta,\\n 'jet_maxAbsEta' : self.jet_maxAbsEta,\\n 'hadTau_selection_tight' : self.hadTau_selection_tight,\\n 'hadTauSelection_denominator' : self.hadTau_selection_denominator,\\n 'hadTauSelections_numerator' : self.hadTau_selections_numerator,\\n 'trigMatchingOptions' : self.trigMatchingOptions,\\n 'selEventsFileName_output' : rleOutputFile_path,\\n 'absEtaBins' : self.absEtaBins,\\n 'decayModes' : self.decayModes,\\n 'central_or_shift' : central_or_shift,\\n 'central_or_shifts_local' : [],\\n 'apply_hlt_filter' : self.hlt_filter,\\n }\\n self.createCfg_analyze(self.jobOptions_analyze[key_analyze_job], sample_info)\\n\\n # initialize input and output file names for hadd_stage1\\n key_hadd_stage1_dir = getKey(process_name, charge_selection)\\n hadd_stage1_job_tuple = (process_name, charge_selection)\\n key_hadd_stage1_job = getKey(*hadd_stage1_job_tuple)\\n if not key_hadd_stage1_job in self.inputFiles_hadd_stage1:\\n self.inputFiles_hadd_stage1[key_hadd_stage1_job] = []\\n self.inputFiles_hadd_stage1[key_hadd_stage1_job].append(self.jobOptions_analyze[key_analyze_job]['histogramFile'])\\n self.outputFile_hadd_stage1[key_hadd_stage1_job] = os.path.join(self.dirs[key_hadd_stage1_dir][DKEY_HIST],\\n \\\"hadd_stage1_%s_%s.root\\\" % hadd_stage1_job_tuple)\\n\\n # initialize input and output file names for hadd_stage2\\n key_hadd_stage1_job = getKey(process_name, charge_selection)\\n key_hadd_stage2_dir = getKey(\\\"hadd\\\", charge_selection)\\n key_hadd_stage2_job = getKey(charge_selection)\\n if not key_hadd_stage2_job in self.inputFiles_hadd_stage2:\\n self.inputFiles_hadd_stage2[key_hadd_stage2_job] = []\\n self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.outputFile_hadd_stage1[key_hadd_stage1_job])\\n self.outputFile_hadd_stage2[key_hadd_stage2_job] = os.path.join(self.dirs[key_hadd_stage2_dir][DKEY_HIST],\\n \\\"hadd_stage2_%s.root\\\" % charge_selection)\\n\\n logging.info(\\\"Creating configuration files for executing 'comp_jetToTauFakeRate'\\\")\\n for charge_selection in self.charge_selections:\\n charge_key = \\\"comp_%s\\\" % charge_selection\\n self.comp_input_files[charge_key] = []\\n for trigMatchingOption in self.trigMatchingOptions:\\n key_hadd_stage2_job = getKey(charge_selection)\\n key_comp_jetToTauFakeRate_dir = getKey(\\\"comp_jetToTauFakeRate\\\")\\n key_comp_jetToTauFakeRate_job = getKey(charge_selection, trigMatchingOption)\\n self.jobOptions_comp_jetToTauFakeRate[key_comp_jetToTauFakeRate_job] = {\\n 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],\\n 'cfgFile_modified' : os.path.join(\\n self.dirs[DKEY_CFGS], \\\"comp_jetToTauFakeRate_%s_%s_cfg.py\\\" % (charge_selection, trigMatchingOption)),\\n 'outputFile' : os.path.join(\\n self.dirs[DKEY_HIST], \\\"comp_jetToTauFakeRate_%s_%s.root\\\" % (charge_selection, trigMatchingOption)),\\n 'logFile' : os.path.join(\\n self.dirs[DKEY_LOGS], \\\"comp_jetToTauFakeRate_%s_%s.log\\\" % (charge_selection, trigMatchingOption)),\\n 'looseRegion' : \\\"jetToTauFakeRate_%s_%s/denominator/\\\" % (charge_selection, trigMatchingOption),\\n 'tightRegion' : \\\"jetToTauFakeRate_%s_%s/numerator/\\\" % (charge_selection, trigMatchingOption),\\n 'absEtaBins' : self.absEtaBins,\\n 'ptBins' : self.ptBins,\\n 'decayModes' : self.decayModes,\\n 'hadTauSelections' : self.hadTau_selections_numerator,\\n 'trigMatchingOption' : trigMatchingOption,\\n 'plots_outputFileName' : os.path.join(self.dirs[key_comp_jetToTauFakeRate_dir][DKEY_PLOT], \\\"comp_jetToTauFakeRate_%s.png\\\" % trigMatchingOption)\\n }\\n self.createCfg_comp_jetToTauFakeRate(self.jobOptions_comp_jetToTauFakeRate[key_comp_jetToTauFakeRate_job])\\n comp_output = self.jobOptions_comp_jetToTauFakeRate[key_comp_jetToTauFakeRate_job]['outputFile']\\n self.targets.append(comp_output)\\n self.comp_input_files[charge_key].append(comp_output)\\n self.comp_output_files[charge_key] = os.path.join(self.dirs[DKEY_HIST], \\\"comp_jetToTauFakeRate_%s.root\\\" % charge_selection)\\n\\n logging.info(\\\"Creating configuration files to run 'makePlots'\\\")\\n for charge_selection in self.charge_selections:\\n key_hadd_stage2_job = getKey(charge_selection)\\n key_makePlots_dir = getKey(\\\"makePlots\\\")\\n key_makePlots_job = getKey(charge_selection) \\n self.jobOptions_make_plots[key_makePlots_job] = {\\n 'executable' : self.executable_make_plots,\\n 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],\\n 'cfgFile_modified' : os.path.join(\\n self.dirs[key_makePlots_dir][DKEY_CFGS], \\\"makePlots_%s_cfg.py\\\" % self.channel),\\n 'outputFile' : os.path.join(\\n self.dirs[key_makePlots_dir][DKEY_PLOT], \\\"makePlots_%s.png\\\" % self.channel),\\n 'histogramDir' : \\\"jetToTauFakeRate_%s\\\" % charge_selection,\\n 'label' : None,\\n 'make_plots_backgrounds' : self.make_plots_backgrounds\\n }\\n self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])\\n for trigMatchingOption in self.trigMatchingOptions:\\n self.cfgFile_make_plots = self.cfgFile_make_plots_denominator\\n for absEtaBin in [ \\\"absEtaLt1_5\\\", \\\"absEta1_5to9_9\\\" ]:\\n key_hadd_stage2_job = getKey(charge_selection)\\n key_makePlots_job = getKey(charge_selection, trigMatchingOption, absEtaBin, \\\"denominator\\\") \\n self.jobOptions_make_plots[key_makePlots_job] = {\\n 'executable' : self.executable_make_plots,\\n 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],\\n 'cfgFile_modified' : os.path.join(\\n self.dirs[key_makePlots_dir][DKEY_CFGS], \\\"makePlots_%s_%s_%s_denominator_%s_cfg.py\\\" % \\\\\\n (self.channel, charge_selection, trigMatchingOption, absEtaBin)),\\n 'outputFile' : os.path.join(\\n self.dirs[key_makePlots_dir][DKEY_PLOT], \\\"makePlots_%s_%s_%s_denominator_%s.png\\\" % (self.channel, charge_selection, trigMatchingOption, absEtaBin)),\\n 'histogramDir' : \\\"jetToTauFakeRate_%s_%s/denominator/%s\\\" % (charge_selection, trigMatchingOption, absEtaBin),\\n 'label' : None,\\n 'make_plots_backgrounds' : self.make_plots_backgrounds\\n }\\n self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])\\n for hadTau_selection_numerator in self.hadTau_selections_numerator:\\n key_hadd_stage2_job = getKey(charge_selection)\\n key_makePlots_job = getKey(charge_selection, trigMatchingOption, absEtaBin, \\\"numerator\\\", hadTau_selection_numerator)\\n self.jobOptions_make_plots[key_makePlots_job] = {\\n 'executable' : self.executable_make_plots,\\n 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],\\n 'cfgFile_modified' : os.path.join(\\n self.dirs[key_makePlots_dir][DKEY_CFGS], \\\"makePlots_%s_%s_%s_numerator_%s_%s_cfg.py\\\" % \\\\\\n (self.channel, charge_selection, trigMatchingOption, hadTau_selection_numerator, absEtaBin)),\\n 'outputFile' : os.path.join(\\n self.dirs[key_makePlots_dir][DKEY_PLOT], \\\"makePlots_%s_%s_%s_numerator_%s_%s.png\\\" % \\\\\\n (self.channel, charge_selection, trigMatchingOption, hadTau_selection_numerator, absEtaBin)),\\n 'histogramDir' : \\\"jetToTauFakeRate_%s_%s/numerator/%s/%s\\\" % (charge_selection, trigMatchingOption, hadTau_selection_numerator, absEtaBin),\\n 'label' : None,\\n 'make_plots_backgrounds' : self.make_plots_backgrounds\\n }\\n self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])\\n\\n self.sbatchFile_analyze = os.path.join(self.dirs[DKEY_SCRIPTS], \\\"sbatch_analyze_%s.py\\\" % self.channel)\\n self.sbatchFile_comp_jetToTauFakeRate = os.path.join(self.dirs[DKEY_SCRIPTS], \\\"sbatch_comp_jetToTauFakeRate.py\\\")\\n if self.is_sbatch:\\n logging.info(\\\"Creating script for submitting '%s' jobs to batch system\\\" % self.executable_analyze)\\n self.createScript_sbatch_analyze(self.executable_analyze, self.sbatchFile_analyze, self.jobOptions_analyze)\\n logging.info(\\\"Creating script for submitting '%s' jobs to batch system\\\" % self.executable_comp_jetToTauFakeRate)\\n self.createScript_sbatch(self.executable_comp_jetToTauFakeRate, self.sbatchFile_comp_jetToTauFakeRate, self.jobOptions_comp_jetToTauFakeRate)\\n\\n lines_makefile = []\\n self.addToMakefile_analyze(lines_makefile)\\n self.addToMakefile_hadd_stage1(lines_makefile)\\n self.addToMakefile_hadd_stage2(lines_makefile, make_dependency = \\\"phony_hadd_stage1\\\", max_mem = '4096M')\\n self.addToMakefile_comp_jetToTauFakeRate(lines_makefile)\\n self.addToMakefile_comp_hadd(lines_makefile)\\n self.addToMakefile_make_plots(lines_makefile)\\n self.createMakefile(lines_makefile)\\n\\n logging.info(\\\"Done.\\\")\\n\\n return self.num_jobs\",\n \"def _initializeDoneDict(self):\\n\\t\\tself.donedictfile = os.path.join(self.params['rundir'] , self.functionname+\\\".donedict\\\")\\n\\t\\tif os.path.isfile(self.donedictfile) and self.params['continue'] == True:\\n\\t\\t\\t### unpickle previously done dictionary\\n\\t\\t\\tapDisplay.printMsg(\\\"Reading old done dictionary: \\\"+os.path.basename(self.donedictfile))\\n\\t\\t\\tf = open(self.donedictfile,'r')\\n\\t\\t\\tself.donedict = cPickle.load(f)\\n\\t\\t\\tf.close()\\n\\t\\t\\tif not 'commit' in self.donedict or self.donedict['commit'] == self.params['commit']:\\n\\t\\t\\t\\t### all is well\\n\\t\\t\\t\\tapDisplay.printMsg(\\\"Found \\\"+str(len(self.donedict))+\\\" done dictionary entries\\\")\\n\\t\\t\\t\\treturn\\n\\t\\t\\telif self.donedict['commit'] is True and self.params['commit'] is not True:\\n\\t\\t\\t\\t### die\\n\\t\\t\\t\\tapDisplay.printError(\\\"Commit flag was enabled and is now disabled, create a new runname\\\")\\n\\t\\t\\telse:\\n\\t\\t\\t\\t### set up fresh dictionary\\n\\t\\t\\t\\tapDisplay.printWarning(\\\"'--commit' flag was changed, creating new done dictionary\\\")\\n\\n\\t\\t### set up fresh dictionary\\n\\t\\tself.donedict = {}\\n\\t\\tself.donedict['commit'] = self.params['commit']\\n\\t\\tapDisplay.printMsg(\\\"Creating new done dictionary: \\\"+os.path.basename(self.donedictfile))\\n\\n\\t\\t### write donedict to file\\n\\t\\tf = open(self.donedictfile, 'w', 0666)\\n\\t\\tcPickle.dump(self.donedict, f)\\n\\t\\tf.close()\\n\\t\\treturn\",\n \"def convert_gz_json(option, _, value, parser):\\n setattr(\\n parser.values, option.dest,\\n json.loads(zlib.decompress(base64.b64decode(value))))\",\n \"def savepickle(fln, dict, compress=None):\\n if compress == None:\\n if not os.path.exists(fln) and os.path.exists(fln + '.gz'):\\n compress = True\\n else:\\n compress = False\\n if compress:\\n import gzip\\n with open(fln + '.gz', 'wb') as fh:\\n gzh = gzip.GzipFile(fln, 'wb', compresslevel=3, fileobj=fh)\\n pickle.dump(dict, gzh, 2)\\n gzh.close()\\n else:\\n with open(fln, 'wb') as fh:\\n pickle.dump(dict, fh, 2) # 2 ... fast binary\\n return\",\n \"def decompress(compressed):\\r\\n \\r\\n \\r\\n # Build the dictionary.\\r\\n dict_size = 256\\r\\n dictionary = dict((i, chr(i)) for i in range(dict_size))\\r\\n # in Python 3: dictionary = {i: chr(i) for i in range(dict_size)}\\r\\n \\r\\n # use StringIO, otherwise this becomes O(N^2)\\r\\n # due to string concatenation in a loop\\r\\n result = StringIO()\\r\\n w = chr(compressed.pop(0))\\r\\n result.write(w)\\r\\n for k in compressed:\\r\\n if k in dictionary:\\r\\n entry = dictionary[k]\\r\\n elif k == dict_size:\\r\\n entry = w + w[0]\\r\\n else:\\r\\n raise ValueError('Bad compressed k: %s' % k)\\r\\n result.write(entry)\\r\\n \\r\\n # Add w+entry[0] to the dictionary.\\r\\n dictionary[dict_size] = w + entry[0]\\r\\n dict_size += 1\\r\\n \\r\\n w = entry\\r\\n return result.getvalue()\",\n \"def prepare_gz(self, filename, *args, **kwargs):\\n\\n return '/vsigzip/' + filename, args, kwargs\",\n \"def compress_skim_dir(directory, output=\\\"zarr\\\"):\\n\\n if output not in (\\\"zarr\\\", \\\"zarr.zip\\\"):\\n raise NotImplementedError(output)\\n\\n if output == \\\"zarr\\\":\\n if not os.path.exists(directory+\\\".zarr\\\"):\\n os.makedirs(directory+\\\".zarr\\\")\\n elif output == \\\"zarr.zip\\\":\\n if os.path.exists(directory+\\\".zarr.zip\\\"):\\n raise FileExistsError(directory+\\\".zarr.zip\\\")\\n\\n master = {}\\n for f in os.walk(directory):\\n for fi in f[2]:\\n if \\\".emx\\\" in fi:\\n arr = np.fromfile(fi, dtype='f4')\\n side = int(np.sqrt(arr.size))\\n arr = arr.reshape(side, side)\\n tazrange = pd.RangeIndex(1, side+1)\\n master[fi.replace(\\\".emx\\\", \\\"\\\")] = xr.DataArray(\\n arr,\\n dims=['otaz', 'dtaz'],\\n coords={'otaz': tazrange, 'dtaz': tazrange}\\n )\\n\\n master = sh.Dataset(master)\\n\\n if output == \\\"zarr\\\":\\n master.to_zarr(directory+\\\".zarr\\\", mode='a')\\n elif output == \\\"zarr.zip\\\":\\n with zarr.ZipStore(directory+\\\".zarr.zip\\\", mode='w') as store:\\n master.to_zarr(store)\\n return master\",\n \"def __init__(self,fileName,storageCode,hash):\\n self.fileName = fileName\\n self.storageCode = storageCode\\n self.hash = hash\\n self.pieces = {}\",\n \"def save_compression():\\n added,comp_seq, binary_seq, seq, file = binary_to_utf8()\\n huffman_code, binary_seq = huffman_construction(seq)\\n \\n #save the number of zeroes added to the dictionnary \\n huffman_code[\\\"add\\\"]= added\\n created_file = os.path.splitext(file)[0]\\n file_comp = open(created_file + \\\"_compressed.txt\\\", \\\"w\\\") \\n \\n #save the dictionnary in the file and the compressed sequence\\n json.dump(huffman_code, file_comp)\\n file_comp.write(\\\"\\\\n\\\"+comp_seq) \\n file_comp.close()\\n \\n messagebox.showinfo(\\\"Information\\\", \\\"Your compression has been saved in \\\"+created_file +\\\"_compressed.txt file.\\\")\\n return comp_seq, binary_seq, seq\",\n \"def create_compressed_file(self):\\n\\t\\tself._compressed_file_name = 'c_' + self.file_name\\n\\t\\tself._compressed_save_path = self.full_path.replace(self.file_name, self._compressed_file_name)\\n\\t\\tself._is_png = 'png' in self.file_extension\\n\\t\\tself._is_jpg = 'jpg' in self.file_extension\\n\\n\\t\\timage = Image.open(self.full_path)\\n\\n\\t\\tif self._is_png:\\n\\t\\t\\timage.save(self._compressed_save_path, quality=85, optimize=False, compress_level=9)\\n\\t\\telif self._is_jpg:\\n\\t\\t\\timage.save(self._compressed_save_path, quality=85, progressive=False)\\n\\t\\telse:\\n\\t\\t\\tprint('Non-recognized asset format!!')\\n\\t\\t\\texit()\\n\\n\\t\\tself._compressed_file_size = ufo.get_file_size_in_bytes(self._compressed_save_path)\\n\\n\\n\\t\\ttransfer_path = self._compressed_save_path.replace('c_' + self.file_name, self.file_name).replace('/configuration_files/', '/quasar_site_django/')\\n\\t\\tufo.copy_file_to_path(self._compressed_save_path, transfer_path)\",\n \"def apply_compressed_sensing(self, inputs, rng):\\n print('using compressed sensing!')\\n train_path = os.path.join(\\n self.data_dir, 'assist{0}-{1}'.format(self.which_year, 'train'))\\n\\n if self.which_set == 'test':\\n loaded = np.load(train_path + '-compression-matrix.npz')\\n self.compress_matrix = loaded['compress_matrix']\\n self.compress_dim = self.compress_matrix.shape[1]\\n elif self.which_set == 'train':\\n self.compress_matrix = self.make_compression_matrix(train_path, rng)\\n\\n inputs = self.compress_inputs(inputs)\\n return inputs\",\n \"def initializeFromDict(self, inputDict):\\n pass\",\n \"def cache_file_list_dict(self, dict_):\\n try:\\n dict_['DUMMYKEY'] = FileInfo()\\n dict_.pop('DUMMYKEY')\\n except TypeError:\\n raise TypeError('incompatible type')\\n else:\\n self.__cache_file_list_dict = dict_\",\n \"def __init__(self, dir_path= 'static/Irma data-20210525'):\\n \\n A=csv_to_dict(dir_path+\\\"\\\\A.csv\\\")\\n B=csv_to_dict(dir_path+\\\"\\\\B.csv\\\")\\n C=csv_to_dict(dir_path+\\\"\\\\C.csv\\\")\\n D=csv_to_dict(dir_path+\\\"\\\\D.csv\\\")\\n\\n\\n self.dicts_list=[A,B,C,D]\\n self.image_codes=csv_to_dict(dir_path+\\\"\\\\image_codes.csv\\\")\",\n \"def keys(self, data, installer_context):\",\n \"def dict_to_files(result_dict, dest_dir):\\n tempdir = tempfile.mkdtemp()\\n\\n # timestamp every generated dignostic file\\n timestamp = datetime.datetime.now().strftime(\\\"%Y%m%d_%H%I%S\\\")\\n tarball = '{0}/ceph-collect_{1}.tar.gz'.format(dest_dir, timestamp)\\n\\n with tarfile.open(tarball, 'w:gz') as tar:\\n for filename, content in result_dict.items():\\n\\n for contentname, contentdata in content.items():\\n tmpfile = '{0}/{1}'.format(tempdir, filename +\\n \\\"-\\\" + contentname)\\n\\n LOGGER.debug('Writing file %s', tmpfile)\\n print('Writing file %s', tmpfile)\\n with open(tmpfile, 'wb') as f:\\n f.write(contentdata)\\n f.close()\\n\\n tar.add(name=tmpfile,\\n arcname='ceph-collect_{0}/{1}'.format(timestamp,\\n filename + \\\"-\\\" +\\n contentname))\\n tar.close()\\n LOGGER.info(\\\"Diagnostics are written to : \\\"+ tarball)\\n\\n LOGGER.info(\\\"Cleaning up temporary directory\\\")\\n shutil.rmtree(tempdir)\",\n \"def create_dicts(self):\\n \\n # remove this string from filename to make output file names more manageable\\n pre_output1 = self.file1.replace(\\\"_Guys121919_CGH_1100_Jul11\\\", '')\\n pre_output2 = self.file2.replace(\\\"_Guys121919_CGH_1100_Jul11\\\", '')\\n \\n # Build the output file name.\\n # if prefix is present add it\\n if self.out_file_prefix is not None:\\n # concatenate prefix, filenames and dyes into output filename file1_file1_dye_file2_file2_dye.txt\\n self.outputfilename = self.out_file_prefix+pre_output1.replace(\\\".txt\\\", '') + \\\"_\\\" + self.file1_dye + \\\"_\\\" + pre_output2.replace(\\\".txt\\\", '') + \\\"_\\\" + self.file2_dye + \\\".txt\\\"\\n # if no prefix don't add it!\\n else:\\n # concatenate filenames and dyes into output filename file1_file1_dye_file2_file2_dye.txt\\n self.outputfilename = pre_output1.replace(\\\".txt\\\", '') + \\\"_\\\" + self.file1_dye + \\\"_\\\" + pre_output2.replace(\\\".txt\\\", '') + \\\"_\\\" + self.file2_dye + \\\".txt\\\"\\n\\n # add temp to end of file name to create a temporary output filename\\n self.tempoutputfilename = self.outputfilename.replace(\\\".txt\\\", '') + \\\"temp.txt\\\"\\n\\n # open temp output file\\n self.tempoutputfile = open(self.outputfolder + self.tempoutputfilename, 'w')\\n\\n \\n # open FE files\\n file1_open = open(self.chosenfolder + self.file1, 'r')\\n file2_open = open(self.chosenfolder + self.file2, 'r')\\n\\n # open file1 and create a dict of the features.\\n for linenumber, line in enumerate(file1_open):\\n if linenumber >= 10:\\n splitline = line.split('\\\\t')\\n self.file1_dict[int(splitline[1])] = line\\n # get n of rows in file1 (take the linenumber of the last line)\\n self.file1_len = linenumber\\n\\n # repeat for features in second file but first writing the feparam and stats to temp file - when pairing with control this ensures the \\\"header\\\" comes from the test (file2) not control (file1), NB NEITHER ARE ACCURATE!!!!\\n for linenumber, line in enumerate(file2_open):\\n if linenumber < 10:\\n self.tempoutputfile.write(line)\\n # then add all features to a dictionary, with the unique feature number as a key\\n if linenumber >= 10:\\n splitline = line.split('\\\\t')\\n self.file2_dict[int(splitline[1])] = line\\n # get n of rows in file2\\n self.file2_len = linenumber\\n\\n # close files\\n file1_open.close()\\n file2_open.close()\",\n \"def write_snappy_dict(self):\\n feature_list = []\\n refinement_surface_dict = {}\\n layer_dict = {}\\n geom_dict = {}\\n\\n for part in self.geometries:\\n geom = { part.filename : {'type':'triSurfaceMesh', 'name':part.name}}\\n geom_dict.update(geom)\\n\\n file_dict = {'file' : '\\\"{}.eMesh\\\"'.format(part.name),\\n 'level' : self.surfaceRefinement}\\n feature_list.append(file_dict)\\n\\n refinement_surface = {part.name : {\\n 'level' : [self.refinementSurfaceMin, self.refinementSurfaceMax]}}\\n refinement_surface_dict.update(refinement_surface)\\n\\n layer = {part.name : {'nSurfaceLayers' : self.nSurfaceLayers}}\\n layer_dict.update(layer)\\n\\n snappy_dict = {\\n\\n 'castellatedMesh' : self.castellate,\\n 'snap' : self.snap,\\n 'addLayers' : self.addLayers,\\n 'geometry' :geom_dict,\\n 'castellatedMeshControls' : {\\n 'maxLocalCells' : self.maxLocalCells,\\n 'maxGlobalCells' : self.maxGlobalCells,\\n 'minRefinementCells' : self.minRefinementCells,\\n 'maxLoadUnbalance' : self.maxLoadUnbalance,\\n 'nCellsBetweenLevels' : self.nCellsBetweenLevels,\\n 'features' : feature_list,\\n 'refinementSurfaces': refinement_surface_dict,\\n 'resolveFeatureAngle' : self.resolveFeatureAngle,\\n 'refinementRegions' : {self.geometries[0].name :\\n {'mode' : 'distance',\\n 'levels' :([[(self.distanceRefinements[x],\\\\\\n self.distanceLevels[x])] for x in\\\\\\n range(len(self.distanceRefinements))])}},\\n 'locationInMesh' : self.locationToKeep,\\n 'allowFreeStandingZoneFaces' : self.allowFreeStandingFaces\\n },\\n 'snapControls' :\\n {\\n 'nSmoothPatch' : self.nSmoothPatch,\\n 'tolerance' : self.snapTolerance,\\n 'nRelaxIter' : self.nRelaxIter,\\n 'nSolveIter' : self.nSolveIter,\\n 'nFeatureSnapIter' : self.nFeatureSnapIter,\\n 'implicitFeatureSnap' : self.implicitFeatureSnap,\\n 'explicitFeatureSnap' : self.explicitFeatureSnap,\\n 'multiRegionFeatureSnap' : self.multiRegionFeatureSnap,\\n },\\n 'addLayersControls' :\\n {\\n 'relativeSizes' : self.relativeSizes,\\n 'expansionRatio' : self.expansionRatio,\\n 'finalLayerThickness' : self.finalLayerThickness,\\n 'minThickness' : self.minThickness,\\n 'nGrow' : self.nGrow,\\n 'layers': layer_dict,\\n 'featureAngle' : self.featureAngle,\\n 'slipFeatureAngle' : self.slipFeatureAngle,\\n 'nRelaxIter' : self.nRelaxIter,\\n 'nSmoothSurfaceNormals' : self.nSmoothSurfaceNormals,\\n 'nSmoothNormals' : self.nSmoothNormals,\\n 'nSmoothThickness' : self.nSmoothThickness,\\n 'maxFaceThicknessRatio' : self.maxFaceThicknessratio,\\n 'maxThicknessToMedialRatio' : self.maxThicknessToMedialRatio,\\n 'minMedianAxisAngle' : self.minMedianAxisAngle,\\n 'nBufferCellsNoExtrude' : self.nBufferCellsNoExtrude,\\n 'nLayerIter' : self.nLayerIter\\n },\\n 'meshQualityControls' :\\n {\\n '#include' : '\\\"meshQualityDict\\\"'\\n },\\n 'mergeTolerance' : self.mergeTolerance\\n }\\n with self.case.mutable_data_file(FileName.SNAPPY_HEX_MESH) as d:\\n d.update(snappy_dict)\",\n \"def getCityCodeDict():\\n\\n dictionary = {}\\n f = open(filename1,'rb') \\n\\n dictionary = pickle.load(f)\\n f.close()\\n return dictionary\",\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 initialize(self,inputDict):\\n pass\",\n \"def get_gzipped_s3_objects_from_dict(session, event):\\n return get_s3_objects_from_dict(\\n session, event, default_unzip_s3_object_handler_function\\n )\",\n \"def __init__(self, sorter=None):\\n self.entries = dict()\\n self.super_entries = dict()\\n self.sort = sorter\\n with open(os.path.join(ROOT, 'database', 'cjk-decomp.txt')) as f:\\n for row in f:\\n entry, _, components = re.match('(.+):(.+)\\\\((.*)\\\\)', row).groups()\\n comp_list = components.split(',')\\n self.entries[entry] = comp_list\\n for comp in comp_list:\\n self.super_entries.setdefault(comp, []).append(entry)\",\n \"def enter_dict(update_dict, path=\\\"current_request.txt\\\"):\\n\\n request_dict = RequestFileCom.file_to_dict(path)\\n\\n # Make sure no one changes the file content before finishes to update it.\\n RequestFileCom.mutex.acquire()\\n\\n for key in update_dict:\\n\\n request_dict[key] = update_dict[key]\\n\\n request_file_string = \\\"\\\"\\n\\n for key in request_dict:\\n\\n request_file_string += key + \\\"::\\\" + request_dict[key] + \\\"\\\\n\\\"\\n\\n # Update the file.\\n with open(path, \\\"w\\\") as f:\\n\\n f.write(request_file_string)\\n\\n RequestFileCom.mutex.release()\\n\\n request_dict = RequestFileCom.file_to_dict(path)\",\n \"def __init__(self, url=\\\"https://ehw.fit.vutbr.cz/izv/\\\",folder=\\\"data\\\", cache_filename=\\\"data_{}.pkl.gz\\\"):\\n self.url = url\\n self.folder = folder\\n self.cache_filename = cache_filename\\n self.ListOfZipFiles = []\\n self.saved_data = {}\\n self.headers = [\\\"region\\\", \\\"p1\\\", \\\"p36\\\", \\\"p37\\\", \\\"p2a\\\", \\\"weekday(p2a)\\\", \\\"p2b\\\", \\\"p6\\\", \\\"p7\\\", \\\"p8\\\", \\\"p9\\\", \\\"p10\\\", \\\"p11\\\", \\\"p12\\\", \\\"p13a\\\", \\\"p13b\\\", \\\"p13c\\\", \\\"p14\\\", \\\"p15\\\", \\\"p16\\\", \\\"p17\\\", \\\"p18\\\", \\\"p19\\\", \\\"p20\\\", \\\"p21\\\", \\\"p22\\\", \\\"p23\\\", \\\"p24\\\", \\\"p27\\\", \\\"p28\\\", \\\"p34\\\", \\\"p35\\\", \\\"p39\\\", \\\"p44\\\", \\\"p45a\\\", \\\"p47\\\", \\\"p48a\\\", \\\"p49\\\", \\\"p50a\\\", \\\"p50b\\\", \\\"p51\\\", \\\"p52\\\", \\\"p53\\\",\\\"p55a\\\",\\\"p57\\\",\\\"p58\\\",\\\"a\\\",\\\"b\\\",\\\"d\\\",\\\"e\\\",\\\"f\\\",\\\"g\\\",\\\"h\\\",\\\"i\\\",\\\"j\\\",\\\"k\\\",\\\"l\\\",\\\"n\\\",\\\"o\\\",\\\"p\\\",\\\"q\\\",\\\"r\\\",\\\"s\\\",\\\"t\\\",\\\"p5a\\\"]\\n self.duplicate_handling = []\\n if not re.search(\\\"^.*{}.*$\\\", self.cache_filename):\\n self.cache_filename+=\\\"{}\\\"\",\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 __init__(self,dir,factory=FileInfo):\\n self.dir = dir\\n self.factory=factory\\n self.data = {}\\n self.table = Table(os.path.join(self.dir,'Mash','Table.pkl'))\\n self.corrupted = {} #--errorMessage = corrupted[fileName]\",\n \"def write_zip_swapped(zip, replacement_dict):\\n for from_file in replacement_dict:\\n with open(from_file) as file:\\n contents = file.read()\\n\\n zip.writestr(os.path.join('data/minecraft/', replacement_dict[from_file]), contents)\",\n \"def pack():\\n clean_local()\\n build()\\n copy_json()\\n optimize()\\n tarball()\",\n \"def preprocess(self, newpath):\\n return dict()\",\n \"def store(self, filename):\",\n \"def construct_alphabet():\\n with open('alphabet.csv', 'r') as file_handler:\\n dict_reader, alphabet = csv.DictReader(file_handler, delimiter=','), list()\\n for row in dict_reader:\\n alphabet.append(row)\\n with open('../alphabet.py', 'w') as file_handler:\\n file_handler.write(f'''\\n\\\"\\\"\\\"Script containing the alphabet \\\"\\\"\\\"\\n\\nfrom collections import OrderedDict\\n\\nALPHABET = {alphabet}\\n \\n''')\",\n \"def __compress(list_events):\\r\\n compress_dict = {}\\r\\n i = 0\\r\\n while i < len(list_events):\\r\\n # create a new event where keys and values are compressed\\r\\n comp_ev = {}\\r\\n for k, v in list_events[i].items():\\r\\n # check if the key has already been instantiated.\\r\\n # in that case, use the current instantiation.\\r\\n if k not in compress_dict:\\r\\n compress_dict[k] = k\\r\\n else:\\r\\n k = compress_dict[k]\\r\\n # check if the value has already been instantiated.\\r\\n # in that case, use the current instantiation\\r\\n if v not in compress_dict:\\r\\n compress_dict[v] = v\\r\\n else:\\r\\n v = compress_dict[v]\\r\\n # saves the compressed keys and values in the dictionary\\r\\n comp_ev[k] = v\\r\\n list_events[i] = comp_ev\\r\\n i = i + 1\\r\\n return list_events\",\n \"def _to_load_dict(self, d: dict) -> dict:\\n return _to_bucket_dict(d)\",\n \"def map_file_data(file_obj, file_events):\\n file_as_dict = {\\n \\\"premis:originalName\\\": file_obj.currentlocation,\\n \\\"original_name\\\": escape(file_obj.originallocation),\\n # needs investigation\\n \\\"sanitized_file_name\\\": get_sanitized_file_name(\\n get_file_name_cleanup(file_events)\\n ),\\n \\\"prov:generatedAtTime\\\": file_obj.modificationtime.strftime(\\n \\\"%Y-%m-%dT%H:%M:%SZ\\\"\\n ),\\n \\\"premis:fixity\\\": {\\n \\\"checksum_type\\\": convert_to_premis_hash_function(file_obj.checksumtype),\\n \\\"Checksum\\\": file_obj.checksum,\\n },\\n \\\"premis:identifier\\\": file_obj.uuid,\\n \\\"premis:size\\\": file_obj.size,\\n \\\"file_name\\\": file_obj.label,\\n # not sure if this is the file name or if we should stick with\\n \\\"dct:FileFormat\\\": map_file_format_info(\\n get_file_format_event(file_events), get_file_validation_event(file_events)\\n ),\\n \\\"file_validation\\\": map_file_validation_info(\\n get_file_validation_event(file_events)\\n ),\\n \\\"file_normalization\\\": map_file_normalization_info(\\n get_file_normalization_event(file_events)\\n ),\\n \\\"events\\\": list_file_events(file_events),\\n }\\n return file_as_dict\",\n \"def get_files_io():\\n if GC.conf['general']['training']:\\n files_zip = {\\n 'raw': os.path.join(COOKED_DATA, 'train.txt'),\\n 'new': os.path.join(COOKED_DATA, 'train_new.txt'),\\n 'norm': os.path.join(COOKED_DATA, 'train_norm.txt'),\\n 'manu': os.path.join(RAW_DATA, 'others', 'temp_updt_manu.txt'),\\n 'labels': os.path.join(TRAIN_DATA, 'train_norm.txt_labels.pkl'),\\n 'segll': os.path.join(TRAIN_DATA, 'train_norm.txt_seginf_loglab.pkl'),\\n 'segdl': os.path.join(TRAIN_DATA, 'train_norm.txt_seginf_deeplog.pkl'),\\n 'struct': os.path.join(TRAIN_DATA, 'train_norm.txt_structured.csv'),\\n 'output': TRAIN_DATA\\n }\\n else:\\n files_zip = {\\n 'raw': os.path.join(COOKED_DATA, 'test.txt'),\\n 'new': os.path.join(COOKED_DATA, 'test_new.txt'),\\n 'norm': os.path.join(COOKED_DATA, 'test_norm.txt'),\\n 'labels': os.path.join(TEST_DATA, 'test_norm.txt_labels.pkl'),\\n 'segll': os.path.join(TEST_DATA, 'test_norm.txt_seginf_loglab.pkl'),\\n 'segdl': os.path.join(TEST_DATA, 'test_norm.txt_seginf_deeplog.pkl'),\\n 'map_norm_raw': os.path.join(TEST_DATA, 'map_norm_raw.pkl'),\\n 'map_norm_rcv': os.path.join(TEST_DATA, 'map_norm_rcv.pkl'),\\n 'norm_rcv': os.path.join(TEST_DATA, 'test_norm_rcv.txt'),\\n 'struct': os.path.join(TEST_DATA, 'test_norm.txt_structured.csv'),\\n 'struct_rcv': os.path.join(TEST_DATA, 'test_norm_rcv.txt_structured.csv'),\\n 'top': os.path.join(TEST_DATA, 'analysis_summary_top.txt'),\\n 'sum': os.path.join(TEST_DATA, 'analysis_summary.csv'),\\n 'rst_llab': os.path.join(TEST_DATA, 'results_loglab.csv'),\\n 'rst_dlog': os.path.join(TEST_DATA, 'results_deeplog.txt'),\\n 'rst_llzr': os.path.join(TEST_DATA, 'results_loglizer.csv'),\\n 'dbg': os.path.join(TEST_DATA, 'debug.csv'),\\n 'output': TEST_DATA\\n }\\n return files_zip\",\n \"def save_artefact(cls, cwd, hash, objects, trial, artefact_type='MODELS', **kwargs):\\n\\n objects_dir = '%s/%s' % (cwd, '.mantra/objects')\\n\\n if os.path.isfile('%s/%s/%s' % (objects_dir, hash[:2], hash[2:])):\\n return False # hash already exists, we have already stored the object\\n\\n for item_key, item_value in objects.items():\\n \\n item_loc = '%s/%s/%s' % (objects_dir, item_value['hash'][:2], item_value['hash'][2:])\\n\\n if os.path.isfile(item_loc):\\n continue\\n\\n hash_path = '%s/%s' % (objects_dir, item_value['hash'][:2])\\n\\n if not os.path.exists(hash_path):\\n os.mkdir(hash_path)\\n\\n if item_value['type'] == 'tree':\\n f = open(item_loc, \\\"wb\\\")\\n f.write(zlib.compress(bytes(item_value['content'].encode('ascii'))))\\n f.close()\\n else:\\n try:\\n content = zlib.compress(open(item_key, \\\"rb\\\").read())\\n f = open(item_loc, \\\"wb\\\")\\n f.write(content)\\n f.close() \\n except:\\n # TODO: https://bugs.python.org/issue27130 : need a formal workaround for file size > 2GB\\n print('Warning: File Too Big to Compress')\\n content = 'toobigtofail'\\n f = open(item_loc, \\\"w\\\")\\n f.write(content)\\n f.close() \\n\\n unix_ts = int((datetime.datetime.utcnow() - datetime.datetime(1970, 1, 1)).total_seconds())\\n f = open('%s/%s' % (cwd, '.mantra/%s' % artefact_type), \\\"a\\\")\\n\\n if artefact_type == 'MODELS':\\n f.write('%s %s %s %s\\\\n' % (hash, unix_ts, trial.model_name, 'trained on %s' % trial.dataset_name))\\n elif artefact_type == 'DATA':\\n f.write('%s %s %s %s\\\\n' % (hash, unix_ts, trial.dataset_name, 'used with model %s' % trial.model_name))\\n elif artefact_type == 'TASKS':\\n f.write('%s %s %s %s\\\\n' % (hash, unix_ts, trial.task_name, 'used with model %s trained on %s' % (trial.model_name, trial.dataset_name)))\\n f.close()\\n\\n return True\",\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 __init__(self, storage_directory, backup_filepath=None):\\r\\n self.record = defaultdict(str)\\r\\n if storage_directory.endswith('\\\\\\\\') or storage_directory.endswith('/'):\\r\\n self.storage_directory = storage_directory\\r\\n else:\\r\\n self.storage_directory = storage_directory + '\\\\\\\\'\\r\\n if backup_filepath is None:\\r\\n self.backup = self.storage_directory + 'mover_backup.json'\\r\\n else:\\r\\n self.backup = backup_filepath\\r\\n if os.path.isfile(self.backup):\\r\\n self.load_backup()\\r\\n logging.info('Initialized Backup')\",\n \"def __init__(self,\\n allowRepetition):\\n self.__fileName = \\\"\\\"\\n self.__allowRepetition = allowRepetition\\n self.__keyObjs = {}\\n self.__keyList = []\\n self.__keyCount = {}\\n self.__trailer = []\",\n \"def __init__( self, generator):\\n DictObject.__init__( self, generator.generate_dict())\",\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 __init__(self, resource_storage, path=\\\"\\\"):\\n self._path = os.path.join(path, self._NAME)\\n self._resource_storage = resource_storage\\n self._write_archive_signature()\\n self._write_archive_schema()\\n self._resources_written = [f\\\"{self._NAME}.archive\\\"]\",\n \"def create_dicts(filelist, class_out, **kwargs):\\n\\n c = TwoLevelCountDict()\\n d = TwoLevelCountDict()\\n m = TwoLevelCountDict()\\n\\n def _merge_dicts(tup):\\n new_c, new_d, new_m = tup\\n _merge_tlcd(c, new_c)\\n _merge_tlcd(d, new_d)\\n _merge_tlcd(m, new_m)\\n print(len(c), len(d), len(m))\\n\\n pool = Pool(4)\\n\\n for f in filelist:\\n #p = Process(target=_process_file, args=(f))\\n pool.apply_async(_process_file, args=[f], callback=_merge_dicts)\\n #_process_file(f, c, d, m)\\n\\n # Close the pool...\\n pool.close()\\n pool.join()\\n\\n # Write out the dicitonaries...\\n c_f = open(c_path, 'wb')\\n d_f = open(d_path, 'wb')\\n m_f = open(m_path, 'wb')\\n\\n pickle.dump(c, c_f)\\n pickle.dump(d, d_f)\\n pickle.dump(m, m_f)\\n c_f.close()\",\n \"def compression(s):\",\n \"def __init__(self, directory, mode=Mode.READONLY):\\n if not os.path.exists(directory):\\n raise IOError(\\\"Directory %s for raw store does not exist\\\"%\\n directory)\\n self.directory = directory\\n with open(os.path.join(directory, \\\"__rawformat__\\\"), 'rb') as rawformat:\\n self.__dict__.update(pickle.load(rawformat))\\n \\n fname = self.fname = os.path.join(directory, \\\"__store___\\\")\\n colCache = self.colCacheDir = os.path.join(directory, \\\"__colstore___\\\")\\n\\n self._f = None\\n self.mode = mode\\n self._openfile()\",\n \"def assemble(self, resetLocation: bool = ..., verbose: bool = ...) -> Union[Dict[AtomKey, numpy.array], Dict[HKT, numpy.array], None]:\\n ...\",\n \"def new_values(basenames):\\n result = {}\\n for basename in basenames:\\n home = os.environ['HOME']\\n p = os.path.join(home, basename)\\n if not os.path.isfile(p):\\n continue\\n size = '%d' % p.size\\n mtime = '%0.8f' % p.mtime\\n result[basename] = Signature(mtime, size, text_digest(p.text()))\\n return pad_keys(result, basenames)\",\n \"def init_objects(file_input: str) -> Dict[str, ObjectMass]:\\n objects = {}\\n for line in file_input:\\n orbit, orbiter = line.strip().split(\\\")\\\")\\n\\n orbit: ObjectMass = objects.setdefault(orbit, ObjectMass(orbit))\\n orbiter: ObjectMass = objects.setdefault(orbiter, ObjectMass(orbiter))\\n\\n orbit.orbiters.append(orbiter)\\n orbiter.orbit = orbit\\n\\n return objects\",\n \"def __init__(self, filename, unique_keys):\\n self.filename = filename\\n self.data = None\\n self.unique_keys = sorted(list(set(unique_keys)))\\n self._reload()\",\n \"def init_req_objs_gradle_with_args() -> Tuple[MultiDict, List[FileStorage]]:\\n gradle_file = FileStorage(stream=open(GRADLE_WITH_ARGS_PATH, 'rb'),\\n filename=GRADLE_WITH_ARGS_FILENAME,\\n content_type=CONTENT_TYPE_ZIP)\\n\\n data = MultiDict([\\n ('file', gradle_file)\\n ])\\n\\n return data, [gradle_file]\",\n \"def compile_metadata(inventory_dict):\\n inventory_meta = {}\\n #inventory_meta['InventoryDictionary'] = inventory_dict\\n for source, year in inventory_dict.items():\\n inventory_meta[source] = stewi.getMetadata(source, year)\\n return inventory_meta\",\n \"def __init__(self, cliDict):\\r\\n\\r\\n print(\\\"initializing Model\\\")\\r\\n #self.filename = filename\\r\\n #print(\\\"filename is \\\",self.filename)\\r\\n self.cliDict=cliDict\\r\\n self.objdict = {'HOSTNAME':'','IPADDRESS':'','LOG':'','VERBOSE':'','ORIGUSERNAME':'','TESTUSERNAME':'', \\\\\\r\\n 'PASSWORD7':'','PLAINTEXT':'','SECRET8':'','CHANGE':'','VERIFIED':'','NOTES-AND-ERRORS':''} \\r\\n #testing\\r\\n #self.path = 'e:/dougsprogs/convert7to8/convert728/'\\r\\n \\r\\n\\r\\n ##Main checks to see if Filename is blank\\r\\n #if filename :#filename is not blank.\\r\\n #self.checkFilename()\\r\\n #if filename is blank, create the default dict\\r\\n #else: #filename is blank \\\"\\\"\\r\\n self.loadDictRow()\\r\\n #loadDictValue(key=\\\"IPADDRESS\\\", value=str(ipaddress))\\r\\n #now check to create the default empty file\\r\\n #checkFilename()\\r\",\n \"def __init__(self, entries):\\r\\n if isinstance(entries, str): # filename\\r\\n self.contigs = readstatsFile(entries)\\r\\n else:\\r\\n self.contigs = OrderedDict()\\r\\n for entry in entries:\\r\\n self.contigs[entry.contigName] = entry\",\n \"def make_compression_matrix(self, train_path, rng):\\n self.compress_dim = 100 # value used in original DKT paper\\n if rng:\\n compress_matrix = rng.randn(self.encoding_dim, self.compress_dim)\\n else:\\n compress_matrix = np.random.randn(self.encoding_dim, self.compress_dim)\\n\\n np.savez(train_path + '-compression-matrix', compress_matrix=compress_matrix)\\n return compress_matrix\",\n \"def compress(self, src, dst):\\n info = readelf_get_info(src)\\n starting_size = os.path.getsize(src)\\n if starting_size != info[\\\"size\\\"]:\\n raise RuntimeError(\\\"size of file '%s' differs from header claim: %i != %i\\\" %\\n (src, starting_size, info[\\\"size\\\"]))\\n rfd = open(src, \\\"rb\\\")\\n wfd = open(dst, \\\"wb\\\")\\n data = rfd.read(starting_size)\\n wfd.write(data[info[\\\"entry\\\"]:])\\n rfd.close()\\n wfd.close()\\n self.__uncompressed_size = len(data) - info[\\\"entry\\\"]\\n if is_verbose():\\n print(\\\"Wrote compressable program block '%s': %i bytes\\\" % (dst, self.__uncompressed_size))\\n self.__contexts = []\\n self.__weights = []\\n (so, se) = run_command([self.__command, dst])\\n lines = so.split(\\\"\\\\n\\\")\\n for ii in lines:\\n terms = ii.split()\\n if terms and terms[0].startswith(\\\"Final\\\"):\\n compressed_size = int(terms[1])\\n for jj in terms[2:]:\\n individual_term = jj.split(\\\"*\\\")\\n self.__weights += [int(individual_term[0], 10)]\\n self.__contexts += [int(individual_term[1], 16)]\\n if is_verbose():\\n print(\\\"Program block compressed into '%s': %i bytes\\\" % (dst + \\\".pack\\\", compressed_size))\\n print(\\\"Compression weights: %s\\\" % (str(self.__weights)))\\n print(\\\"Compression contexts: %s\\\" % (str(self.__contexts)))\\n rfd = open(dst + \\\".pack\\\", \\\"rb\\\")\\n compressed_contexts = []\\n compressed_weights = []\\n uncompressed_size = rfd.read(4)\\n uncompressed_size = (struct.unpack(\\\"I\\\", uncompressed_size))[0]\\n if uncompressed_size != self.__uncompressed_size:\\n raise RuntimeError(\\\"size given to packer does not match size information in file: %i != %i\\\" %\\n (self.__uncompressed_size, uncompressed_size))\\n context_count = rfd.read(1)\\n context_count = (struct.unpack(\\\"B\\\", context_count))[0]\\n for ii in range(context_count):\\n compressed_weights += struct.unpack(\\\"B\\\", rfd.read(1))\\n for ii in range(context_count):\\n compressed_contexts += struct.unpack(\\\"B\\\", rfd.read(1))\\n if compressed_contexts != self.__contexts:\\n raise RuntimeError(\\\"contexts reported by packer do not match context information in file: %s != %s\\\" %\\n (str(self.__contexts), str(compressed_contexts)))\\n if compressed_weights != self.__weights:\\n raise RuntimeError(\\\"weights reported by packer do not match weight information in file: %s != %s\\\" %\\n (str(self.__weights), str(compressed_weights)))\\n read_data = rfd.read()\\n rfd.close()\\n if len(read_data) != compressed_size:\\n raise RuntimeError(\\\"size reported by packer does not match length of file: %i != %i\\\" %\\n (compressed_size, len(read_data)))\\n self.__data = []\\n for ii in read_data:\\n self.__data += struct.unpack(\\\"B\\\", ii)\",\n \"def _load_transactions(self):\\r\\n\\t\\tlogger.debug(\\\"Enter\\\")\\r\\n\\t\\ttry:\\r\\n\\t\\t\\twith open(self._state_file, 'rb') as tmp:\\r\\n\\t\\t\\t\\tlogger.debug(\\\"There is a file.\\\")\\r\\n\\t\\t\\t\\ttmp_dict = pickle.load(tmp)\\r\\n\\t\\t\\t\\tlogger.debug(\\\"Dictionary loaded from file: %s\\\" % tmp_dict)\\r\\n\\t\\texcept IOError as e: # File doesn't exists\\r\\n\\t\\t\\tlogger.debug(\\\"Exit - No file. Error message: %s\\\" % e)\\r\\n\\t\\t\\ttmp_dict = {}\\r\\n\\t\\t\\t\\r\\n\\t\\treturn tmp_dict\",\n \"def test_add_dict_ordered(self):\\n with DataArchive(self.user, DATA_DOWNLOADS_WORKING_DIR) as archive:\\n data_to_write = OrderedDict((('first', \\\"łorld!\\\"), ('second', \\\"łup!\\\")))\\n file_path = archive.add_dict('testfile', data_to_write)\\n self.assertTrue(os.path.isfile(file_path))\\n\\n valid_output_path = os.path.join(archive.data_dir_path, 'testfile.txt')\\n self.assertEqual(file_path, valid_output_path)\\n\\n with open(file_path, 'r') as fp:\\n saved_data = fp.read().strip()\\n self.assertEqual(saved_data, \\\"first: łorld!\\\\nsecond: łup!\\\")\",\n \"def finalize(self, dest: OrderedDict = None):\",\n \"def updateDictFile(self):\\n if self.dictFile.vdata.get('version',0): return\\n #--Update to version 1\\n for name in self.data.keys():\\n installer = self.data[name]\\n if isinstance(installer,Installer):\\n self.data[name] = installer.__copy__(InstallerArchive)\\n self.dictFile.vdata['version'] = 1\",\n \"def getAircraftCodeDict():\\n\\n dictionary = {}\\n f = open(filename2,'rb') \\n\\n dictionary = pickle.load(f)\\n f.close()\\n return dictionary\",\n \"def processfile(args, fh):\\n if args.quick:\\n scanner = quickScanZip(args, fh)\\n else:\\n scanner = findPKHeaders(args, fh)\\n\\n def checkarg(arg, ent):\\n if not arg:\\n return False\\n return '*' in arg or ent.name in arg\\n def checkname(a, b):\\n if a and '*' in a: return True\\n if b and '*' in b: return True\\n l = 0\\n if a: l += len(a)\\n if b: l += len(b)\\n return l > 1\\n\\n if args.verbose and not (args.cat or args.raw or args.save):\\n print(\\\" 0304 need flgs mth stamp --crc-- compsize fullsize nlen xlen namofs xofs datofs endofs\\\")\\n print(\\\" 0102 crea need flgs mth stamp --crc-- compsize fullsize nlen xlen clen dsk0 attr osattr datptr namofs xofs cmtofs endofs\\\")\\n for ent in scanner:\\n if args.cat or args.raw or args.save:\\n if args.quick and isinstance(ent, CentralDirEntry) or \\\\\\n not args.quick and isinstance(ent, LocalFileHeader):\\n ent.loaditems(fh)\\n do_cat = checkarg(args.cat, ent)\\n do_raw = checkarg(args.raw, ent)\\n do_save= checkarg(args.save, ent)\\n\\n do_name= checkname(args.cat, args.raw)\\n\\n if do_name:\\n print(\\\"\\\\n===> \\\" + ent.name + \\\" <===\\\\n\\\")\\n\\n sys.stdout.flush()\\n blks = zipraw(fh, ent)\\n\\n if args.password and ent.flags&1:\\n blks = zip_decrypt(blks, args.password)\\n if do_cat or do_save:\\n blks = skipbytes(blks, 12, args)\\n\\n if do_cat:\\n sys.stdout.buffer.writelines(zipcat(blks, ent))\\n if do_raw:\\n sys.stdout.buffer.writelines(blks)\\n if do_save:\\n savefile(args.outputdir, ent.name, zipcat(blks, ent))\\n else:\\n ent.loaditems(fh)\\n if args.verbose or not args.quick:\\n print(\\\"%08x: %s\\\" % (ent.pkOffset, ent))\\n else:\\n print(ent.summary())\\n if hasattr(ent, \\\"comment\\\") and ent.comment and not args.dumpraw:\\n print(ent.comment)\\n if args.dumpraw and hasattr(ent, \\\"extraLength\\\") and ent.extraLength:\\n print(\\\"%08x: XTRA: %s\\\" % (ent.extraOffset, binascii.b2a_hex(getbytes(fh, ent.extraOffset, ent.extraLength))))\\n if args.dumpraw and hasattr(ent, \\\"comment\\\") and ent.comment:\\n print(\\\"%08x: CMT: %s\\\" % (ent.commentOffset, binascii.b2a_hex(getbytes(fh, ent.commentOffset, ent.commentLength))))\\n if args.dumpraw and isinstance(ent, LocalFileHeader):\\n blks = zipraw(fh, ent)\\n if args.password and ent.flags&1:\\n blks = zip_decrypt(blks, args.password)\\n\\n blockdump(ent.dataOffset, blks)\",\n \"def create_dictionary_of_old_and_new_paths(raw_dir: Path, bids_dir: Path, exclude_fieldmaps: bool) -> dict:\\n\\n old_and_new_paths = {}\\n old_paths = list(raw_dir.rglob(\\\"*\\\"))\\n print(f\\\"Sorting {len(old_paths)} paths into a dictionary.\\\") \\n\\n def task_name_of(path_to_func_or_json):\\n \\\"\\\"\\\"\\n Returns the task name of a func or json file. This function OVERWRITES the function\\n \\\"task_name_of\\\" that we imported at the top of this script. BUT! It only overwrites it\\n HERE, in \\\"create_dictionary_of_old_and_new_paths\\\".\\n \\\"\\\"\\\"\\n\\n list_of_lines_containing_raw_subject_info = []\\n for path in old_paths:\\n if filetype_of(path) == \\\"subject info\\\":\\n list_of_lines_containing_raw_subject_info = path.read_text().splitlines()\\n break\\n\\n for line in list_of_lines_containing_raw_subject_info:\\n if path_to_func_or_json.stem in line:\\n return line.split(\\\"z\\\")[1]\\n\\n\\n for old_path in old_paths:\\n\\n new_path = old_path\\n\\n if filetype_of(old_path.with_suffix(\\\".nii\\\")) == \\\"anat\\\" and acquisition_number_of(old_path) == \\\"14\\\":\\n new_path = bids_dir / f\\\"sub-{subject_id_of(old_path)}\\\" / \\\"anat\\\" / f\\\"sub-{subject_id_of(old_path)}_T1w{old_path.suffix}\\\"\\n\\n elif filetype_of(old_path.with_suffix(\\\".nii\\\")) == \\\"func\\\" and acquisition_number_of(old_path) != \\\"02\\\":\\n new_path = bids_dir / f\\\"sub-{subject_id_of(old_path)}\\\" / \\\"func\\\" / f\\\"sub-{subject_id_of(old_path)}_task-{task_name_of(old_path)}_acq-{acquisition_number_of(old_path)}_bold{old_path.suffix}\\\"\\n\\n elif filetype_of(old_path.with_suffix(\\\".nii\\\")) == \\\"fieldmap\\\" and not exclude_fieldmaps:\\n old_affix = old_path.stem.split(\\\"_\\\")[-1]\\n new_affix = \\\"phasediff\\\"\\n if old_affix == \\\"e1\\\":\\n new_affix = \\\"magnitude1\\\"\\n if old_affix == \\\"e2\\\":\\n new_affix = \\\"magnitude2\\\"\\n new_path = bids_dir / f\\\"sub-{subject_id_of(old_path)}\\\" / \\\"fmap\\\" / f\\\"sub-{subject_id_of(old_path)}_{new_affix}{old_path.suffix}\\\"\\n\\n old_and_new_paths[old_path] = new_path\\n\\n print(\\\"Paths sorted.\\\")\\n\\n return old_and_new_paths\",\n \"def create_json(case_dict):\\n # ---------------------------------------------------------------------\\n logger.debug(\\\"create_json\\\")\\n\\n if not os.path.exists(\\\"{0}/archive_files\\\".format(case_dict[\\\"workdir\\\"])):\\n os.makedirs(\\\"{0}/archive_files\\\".format(case_dict[\\\"workdir\\\"]))\\n\\n filename = \\\"{0}/archive_files/json.{1}\\\".format(\\n case_dict[\\\"workdir\\\"], datetime.datetime.now().strftime(\\\"%Y%m%d-%H%M%S\\\")\\n )\\n with io.open(filename, \\\"wb\\\") as fname:\\n jstr = str(json.dumps(case_dict, indent=4, sort_keys=True, ensure_ascii=False))\\n if isinstance(jstr, str):\\n jstr = jstr.decode(\\\"utf-8\\\")\\n fname.write(jstr)\\n fname.close()\",\n \"def Dictionary_create_from(nMarkers, markerSize, baseDictionary):\\n pass\",\n \"def revert(self):\\n headerdump = self.file.readp(0, 16)\\n if sum(headerdump):\\n dictat,dictlen = struct.unpack(\\\"<QQ\\\", headerdump)\\n dictblob = self.file.readp(dictat, dictlen)\\n self.keys = pickle.loads(dictblob)\\n self.buffered = {}\\n self.cache = {}\\n self.awaitingpunch = []\\n\\n else:\\n self.keys = {}\\n self.buffered = {}\\n self.cache = {}\\n self.awaitingpunch = []\",\n \"def __init__(self, dictionary_paths):\\n files = [open(path, 'r') for path in dictionary_paths]\\n dictionaries = [yaml.load(dict_file) for dict_file in files]\\n map(lambda x: x.close(), files)\\n self.dictionary = {}\\n self.max_key_size = 0\\n for curr_dict in dictionaries:\\n for key in curr_dict:\\n if key in self.dictionary:\\n self.dictionary[key].extend(curr_dict[key])\\n else:\\n self.dictionary[key] = curr_dict[key]\\n self.max_key_size = max(self.max_key_size, len(key))\",\n \"def test_add_dict(self):\\n with DataArchive(self.user, DATA_DOWNLOADS_WORKING_DIR) as archive:\\n data_to_write = {'first': \\\"łorld!\\\", 'second': \\\"łup!\\\"}\\n file_path = archive.add_dict('testfile', data_to_write)\\n self.assertTrue(os.path.isfile(file_path))\\n\\n valid_output_path = os.path.join(archive.data_dir_path, 'testfile.txt')\\n self.assertEqual(file_path, valid_output_path)\\n\\n with open(file_path, 'r') as fp:\\n saved_data = fp.read().strip()\\n # order of dict items in py<3.6 is non-deterministic\\n # making testing for exact match a mistake\\n self.assertIn(\\\"first: łorld!\\\", saved_data)\\n self.assertIn(\\\"second: łup!\\\", saved_data)\",\n \"def _get_create_dataset_kwargs(self):\\n kwargs = {}\\n if self.compress_dataset():\\n kwargs.update({'compression': \\\"gzip\\\", 'compression_opts': 9})\\n return kwargs\",\n \"def load_dictionary(cls, args, filename, source=True):\\n dictionary = Dictionary.load(filename)\\n dictionary.add_symbol(\\\"<mask>\\\")\\n return dictionary\",\n \"def __init__(self, data_file_path):\\n self._inventory = Inventory(data_file_path)\\n self._baskets = {}\",\n \"def _initialise_handler(self, filename, host, port, key_prefix):\\n \\n key = os.path.split(filename)[-1] # Is there a better way to construct a unique key?\\n # Perhaps take the hash *from the file contents*.\\n # At present, the filename seems sufficient.\\n \\n if key_prefix is None:\\n raise ValueError(\\\"A key prefix (string) must be specified for the RedisDataHandler.\\\")\\n \\n key = '{key_prefix}::{hashed_key}'.format(key_prefix=key_prefix, hashed_key=hash(key))\\n \\n cache = redis.StrictRedis(host=host, port=port, db=0)\\n \\n if cache.get(key):\\n dumped = cache.get(key)\\n return cPickle.loads(dumped)\\n \\n # If we get here, the TrecQrelsHandler does not exist in the cache; create it, dump it.\\n handler = super(RedisDataHandler, self)._initialise_handler(filename)\\n dumped = cPickle.dumps(handler)\\n cache.set(key, dumped)\\n \\n return handler\",\n \"def __init__(self, path):\\n super(ZIPStorageFileReader, self).__init__(path)\\n self._storage_file = ZIPStorageFile()\\n self._storage_file.Open(path=path)\",\n \"def make_json(prefix, input_dir):\\n # get list of files\\n file_list = os.listdir(input_dir)\\n # set reference sequence\\n tracklist = {'formatVersion': 1,\\n 'refSeqs': '%s.ref.fa.fai' % prefix,\\n 'tracks': []}\\n # add reference sequence track to tracklist.json\\n tracklist['tracks'].append({\\\"category\\\": \\\"Reference sequence\\\",\\n \\\"key\\\": \\\"Reference sequence\\\",\\n \\\"label\\\": \\\"Reference sequence\\\",\\n \\\"type\\\": \\\"SequenceTrack\\\",\\n \\\"storeClass\\\": \\\"JBrowse/Store/SeqFeature/IndexedFasta\\\",\\n \\\"urlTemplate\\\": \\\"%s.ref.fa\\\" % prefix,\\n \\\"refSeqOrder\\\": \\\"False\\\"})\\n tracklist['tracks'].append({\\\"category\\\": \\\"Consensus sequence\\\",\\n \\\"key\\\": \\\"Consensus sequence\\\",\\n \\\"label\\\": \\\"Consensus sequence\\\",\\n \\\"type\\\": \\\"SequenceTrack\\\",\\n \\\"storeClass\\\": \\\"JBrowse/Store/SeqFeature/IndexedFasta\\\",\\n \\\"urlTemplate\\\": \\\"%s.cons.fa\\\" % prefix,\\n \\\"refSeqOrder\\\": \\\"False\\\"})\\n # add bigwig track to trackList.json\\n tracklist['tracks'].append({\\\"category\\\": \\\"Sequence data\\\",\\n \\\"key\\\": \\\"Coverage\\\",\\n \\\"label\\\": \\\"Coverage\\\",\\n \\\"type\\\": \\\"JBrowse/View/Track/Wiggle/XYPlot\\\",\\n \\\"storeClass\\\": \\\"JBrowse/Store/SeqFeature/BigWig\\\",\\n \\\"autoscale\\\": \\\"local\\\",\\n \\\"urlTemplate\\\": \\\"%s.sorted.bw\\\" % prefix\\n })\\n # add BAM Sequence Coverage to trackList.json\\n tracklist['tracks'].append({\\\"category\\\": \\\"Sequence data\\\",\\n \\\"key\\\": \\\"Sequence reads (SNPs/Coverage)\\\",\\n \\\"label\\\": \\\"Sequence reads (SNPs/Coverage)\\\",\\n \\\"type\\\": \\\"JBrowse/View/Track/SNPCoverage\\\",\\n \\\"storeClass\\\": \\\"JBrowse/Store/SeqFeature/BAM\\\",\\n \\\"urlTemplate\\\": \\\"%s.sorted.capped.bam\\\" % prefix,\\n \\\"cacheMismatches\\\": \\\"True\\\",\\n \\\"chunkSizeLimit\\\": \\\"5000000\\\"\\n })\\n # add BAM Sequence Alignments to trackList.json\\n tracklist['tracks'].append({\\\"category\\\": \\\"Sequence data\\\",\\n \\\"key\\\": \\\"Sequence reads (Alignment)\\\",\\n \\\"label\\\": \\\"Sequence reads (Alignment)\\\",\\n \\\"type\\\": \\\"JBrowse/View/Track/Alignments2\\\",\\n \\\"storeClass\\\": \\\"JBrowse/Store/SeqFeature/BAM\\\",\\n \\\"urlTemplate\\\": \\\"%s.sorted.capped.bam\\\" % prefix,\\n # add bigwig histogram option\\n \\\"cacheMismatches\\\": \\\"True\\\",\\n \\\"chunkSizeLimit\\\": \\\"5000000\\\"\\n })\\n # add GFF3 file to trackList.json\\n tracklist['tracks'].append({\\\"category\\\": \\\"Annotation\\\",\\n \\\"key\\\": \\\"Genbank annotation\\\",\\n \\\"label\\\": \\\"Genbank annotation\\\",\\n \\\"type\\\": \\\"JBrowse/View/Track/CanvasFeatures\\\",\\n \\\"urlTemplate\\\": \\\"%s.gff3.gz\\\" % prefix,\\n \\\"style\\\": {\\n \\\"_defaultHistScale\\\": 4,\\n \\\"_defaultLabelScale\\\": 30,\\n \\\"_defaultDescriptionScale\\\": 120,\\n # Comma-separated list of case-insensitive feature tags to use\\n # for showing the feature's label.\\n # The first one found will be used. Default 'name,id'.\\n \\\"label\\\": \\\"product,id\\\",\\n # style→description\\tComma-separated list of case-insensitive\\n # feature tags to check for the feature's long description.\\n # The first one found will be used. Default 'note,description'.\\n # If blank no description is used.\\n \\\"description\\\": \\\"note, description\\\"\\n },\\n })\\n\\n json_path = os.path.join(input_dir, 'trackList.json')\\n with open(json_path, 'wt') as output_handle:\\n json_raw_str = json.dumps(tracklist, indent=4)\\n output_handle.write(json_raw_str)\\n return 'trackList.json'\",\n \"def shelve_dump(file_name: str, **kwargs):\\n with shelve.open(os.path.splitext(file_name)[0]) as db:\\n for k, v in kwargs.items():\\n db[k] = v\",\n \"def populated_archivist_dataset(archivist_dataset, tmp_path_factory):\\n wpath = tmp_path_factory.mktemp(\\\"archivistds\\\")\\n\\n ads = archivist_dataset\\n\\n dscontent = (\\n ('azip/file1.txt', 'zipfile1'),\\n ('azip/file2.csv', 'zipfile2_muchcontent'),\\n ('atar/file1.txt', 'tarfile1'),\\n ('atar/file2.csv', 'tarfile2_muchcontent'),\\n )\\n srcds = Dataset(wpath / 'srcds').create(**nonoise)\\n for fpath, fcontent in dscontent:\\n fpath = srcds.pathobj / (PurePosixPath(fpath))\\n fpath.parent.mkdir(parents=True, exist_ok=True)\\n fpath.write_text(fcontent)\\n srcds.save(**nonoise)\\n\\n archive_root = wpath / 'myarchive'\\n #archivetype = 'zip'\\n\\n akeys = {}\\n\\n # no ZIP just yet\\n # for archivetype, ext in (('zip', ''), ('tar', '.gz')):\\n for archivetype, ext in (('tar', '.gz'), ):\\n archive_path = Path(f\\\"{archive_root}.{archivetype}{ext}\\\")\\n\\n archive_path_inds = ads.pathobj / '.archives' / archive_path.name\\n # create an archive, the easy way, by simply exporting the\\n # entire dataset worktree\\n srcds.export_archive(archive_root, archivetype=archivetype,\\n **nonoise)\\n assert archive_path.exists()\\n\\n # add the archive (in a hidden dir) to be able to reference\\n # it via a key\\n aurl = archive_path.as_uri()\\n ads.repo.call_annex([\\n 'addurl', '--file', str(archive_path_inds), aurl])\\n ads.save(**nonoise)\\n # get the key of the archive\\n akeys[archivetype] = ads.status(\\n archive_path_inds, annex='basic', return_type='item-or-list',\\n **nonoise)['key']\\n return ads, akeys, archive_root, dscontent\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6145931","0.6029067","0.5845155","0.5629594","0.56274456","0.5606034","0.55619204","0.55617094","0.55312747","0.5409232","0.5396165","0.5389857","0.5363818","0.5336105","0.5334452","0.5315649","0.53133637","0.53003275","0.52949893","0.527997","0.52777815","0.5277205","0.5265289","0.525663","0.5245047","0.52206063","0.5206608","0.51939416","0.51810604","0.51789516","0.5158907","0.51453954","0.51442957","0.51378727","0.51195973","0.5109443","0.51082045","0.5101122","0.50911677","0.50816226","0.50771505","0.50738686","0.5065835","0.50551003","0.50506616","0.5047776","0.5043293","0.50276554","0.5021374","0.5019477","0.5013751","0.5012946","0.50095284","0.50060517","0.5001785","0.5000223","0.4997662","0.4996959","0.49816772","0.4979791","0.49791846","0.49783263","0.49772313","0.49759454","0.49740404","0.49708173","0.49578494","0.4955669","0.49542552","0.4946655","0.4944268","0.49431172","0.49400535","0.4936859","0.49259698","0.4917066","0.49166888","0.49157068","0.4909571","0.4908255","0.49028206","0.48935828","0.48859063","0.4885315","0.48851097","0.48850748","0.4883168","0.4878444","0.487817","0.4874943","0.4873227","0.48688218","0.4867451","0.48652297","0.48630485","0.48512572","0.4850513","0.48503214","0.4845075","0.48427606"],"string":"[\n \"0.6145931\",\n \"0.6029067\",\n \"0.5845155\",\n \"0.5629594\",\n \"0.56274456\",\n \"0.5606034\",\n \"0.55619204\",\n \"0.55617094\",\n \"0.55312747\",\n \"0.5409232\",\n \"0.5396165\",\n \"0.5389857\",\n \"0.5363818\",\n \"0.5336105\",\n \"0.5334452\",\n \"0.5315649\",\n \"0.53133637\",\n \"0.53003275\",\n \"0.52949893\",\n \"0.527997\",\n \"0.52777815\",\n \"0.5277205\",\n \"0.5265289\",\n \"0.525663\",\n \"0.5245047\",\n \"0.52206063\",\n \"0.5206608\",\n \"0.51939416\",\n \"0.51810604\",\n \"0.51789516\",\n \"0.5158907\",\n \"0.51453954\",\n \"0.51442957\",\n \"0.51378727\",\n \"0.51195973\",\n \"0.5109443\",\n \"0.51082045\",\n \"0.5101122\",\n \"0.50911677\",\n \"0.50816226\",\n \"0.50771505\",\n \"0.50738686\",\n \"0.5065835\",\n \"0.50551003\",\n \"0.50506616\",\n \"0.5047776\",\n \"0.5043293\",\n \"0.50276554\",\n \"0.5021374\",\n \"0.5019477\",\n \"0.5013751\",\n \"0.5012946\",\n \"0.50095284\",\n \"0.50060517\",\n \"0.5001785\",\n \"0.5000223\",\n \"0.4997662\",\n \"0.4996959\",\n \"0.49816772\",\n \"0.4979791\",\n \"0.49791846\",\n \"0.49783263\",\n \"0.49772313\",\n \"0.49759454\",\n \"0.49740404\",\n \"0.49708173\",\n \"0.49578494\",\n \"0.4955669\",\n \"0.49542552\",\n \"0.4946655\",\n \"0.4944268\",\n \"0.49431172\",\n \"0.49400535\",\n \"0.4936859\",\n \"0.49259698\",\n \"0.4917066\",\n \"0.49166888\",\n \"0.49157068\",\n \"0.4909571\",\n \"0.4908255\",\n \"0.49028206\",\n \"0.48935828\",\n \"0.48859063\",\n \"0.4885315\",\n \"0.48851097\",\n \"0.48850748\",\n \"0.4883168\",\n \"0.4878444\",\n \"0.487817\",\n \"0.4874943\",\n \"0.4873227\",\n \"0.48688218\",\n \"0.4867451\",\n \"0.48652297\",\n \"0.48630485\",\n \"0.48512572\",\n \"0.4850513\",\n \"0.48503214\",\n \"0.4845075\",\n \"0.48427606\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.62700593"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":18699,"cells":{"query":{"kind":"string","value":"Delete a file from the s3 bucket."},"document":{"kind":"string","value":"def storage_delete_file(self, group='', key=''):\n deleted = False\n if key not in [\"default-logo.png\", \"default-picture.png\"]:\n if self.config['type'] == 's3':\n s3_files = self.s3.Bucket(self.bucket)\n for _file in s3_files.objects.all():\n if _file.key == 'corr-{0}s/{1}'.format(group, key):\n _file.delete()\n print(\"File deleted!\")\n deleted = True\n break\n elif self.config['type'] == 'filesystem':\n found = self.agent_delete(group, self.storage_path, key)\n if found:\n deleted = True\n if not deleted:\n print(\"File not deleted\")\n return deleted"},"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_file(bucket, file_to_be_deleted):\n s3 = boto3.client('s3', aws_access_key_id=access_key, aws_secret_access_key=secret_key)\n s3.delete_object(Bucket=bucket, Key=file_to_be_deleted)\n print(file_to_be_deleted, \" : is deleted from the bucket\")","def delete_file_from_s3(bucket_name, filepath):\n if filepath not in list_files_in_s3_bucket(bucket_name):\n raise FileNotFoundError(\n f\"The filepath specified '{filepath}' does not exist in the\"\n f\" bucket '{bucket_name}'\"\n )\n s3 = boto3.client(\"s3\")\n s3.delete_object(Bucket=bucket_name, Key=filepath)","def delete_object(self, s3_path):\n logging.info(\"Deleting \\\"{}\\\" file from S3\".format(s3_path))\n bucket_name, key = S3Util.get_bucket_and_key(s3_path)\n self.s3_resource.ObjectSummary(bucket_name, key).delete()","def del_file(self, key):\n\t\t\n\t\ttry: \n\t\t\tself.s3.delete(self.bucket, key) \n\t\texcept:\n\t\t\treturn False","def gcloud_delete_file(file_name, gcloud_bucket_name):\n bucket = gce_storage_client.get_bucket(gcloud_bucket_name)\n blob = bucket.blob(file_name)\n\n blob.delete()","def delete(self, args):\n try:\n assert len(args) > 0\n file_name = args[0]\n try:\n if should('Delete %s?' % file_name):\n self.s3.Object(self.bucket_name, file_name).load()\n self.s3.Object(self.bucket_name, file_name).delete()\n print('File %s deleted!' % file_name)\n except ClientError:\n print('File %s not found in bucket %s' % (file_name, self.bucket_name))\n except AssertionError:\n print('I need a file name!')","def s3_delete_local(self, local_file, bucket, bucket_filepath):\n\n s3 = boto3.client('s3')\n with open(local_file, \"rb\") as f:\n if 'vsis3' in bucket:\n bucket = bucket.split('/')[-1]\n print(bucket, bucket_filepath)\n s3.upload_fileobj(f, bucket, bucket_filepath)\n os.remove(local_file)","def rm(self, filename: str) -> None:\n\n now = datetime.datetime.utcnow()\n timestamp = now.strftime('%a, %d %b %Y %H:%M:%S GMT')\n headers = [\n ('Connection', 'keep-alive'),\n ('Content-Length', '0'),\n ('Date', timestamp),\n ('Host', '%s.s3.amazonaws.com' % self.bucket),\n ('x-amz-content-sha256', _EMPTY_SHA256_HASH),\n ]\n signed_headers = ';'.join(header[0].lower() for header in headers)\n canonical_request = 'DELETE\\n%s\\n\\n%s\\n\\n%s\\n%s' % (\n filename, '\\n'.join(\n ('%s:%s' % (header[0].lower(), header[1])\n for header in headers)), signed_headers, _EMPTY_SHA256_HASH)\n logging.debug('canonical request %r',\n canonical_request.encode('utf-8'))\n string_to_sign = 'AWS4-HMAC-SHA256\\n%s\\n%s\\n%s' % (\n timestamp, self.scope,\n hashlib.sha256(canonical_request.encode('utf-8')).hexdigest())\n logging.debug('string to sign %r', string_to_sign.encode('utf-8'))\n\n signature = hmac.new(self.signing_key,\n string_to_sign.encode('utf-8'),\n digestmod='sha256').hexdigest()\n headers.append((\n 'Authorization',\n 'AWS4-HMAC-SHA256 Credential=%s/%s,SignedHeaders=%s,Signature=%s' %\n (self.aws_access_key, self.scope, signed_headers, signature)))\n if not self.conn:\n self.conn = http.client.HTTPSConnection('%s.s3.amazonaws.com' %\n self.bucket)\n try:\n self.conn.request('DELETE', filename, headers=dict(headers))\n res = self.conn.getresponse()\n payload = res.read()\n except (http.client.BadStatusLine, http.client.ResponseNotReady,\n http.client.CannotSendRequest):\n self.conn.close()\n raise\n if res.status != 204:\n raise Exception(payload.decode('utf-8'))","def delete(c, bucket=None):\n if bucket == None:\n bucket = \"dvc-\" + project_dir_name().replace(\"_\",\"-\")\n bucket_resource = boto3.resource('s3').Bucket(bucket)\n bucket_resource.objects.all().delete()\n s3 = boto3.client(\"s3\")\n s3.delete_bucket(Bucket=bucket)","def delete_key(bucket_name: str, path: str) -> None:\n global config\n session = config.get_session_fn()\n s3_client = session.client(\"s3\")\n try:\n s3_client.delete_object(Bucket=bucket_name, Key=path)\n except Exception as e:\n logger.warning(f\"Failed to delete {path} from s3: {e}\")","def _removeAWSS3Object(self, path: str):\n log.warning(f'Deleting AWS S3 object {path}')\n bucket, key = storage_utils.SplitStoragePath(path)\n s3_client = boto3.client('s3')\n try:\n s3_client.delete_object(Bucket=bucket, Key=key)\n except Exception as error: # pylint: disable=broad-except\n log.error(f'Failed to delete S3 Object {path}: {str(error)}')","def s3_delete_local(self, outpath, from_file, bucket, prefix_no_slash):\n\n objecta='{}/{}'.format(prefix_no_slash,outpath)\n s3 = boto3.client('s3')\n with open(from_file, \"rb\") as f:\n s3.upload_fileobj(f, bucket, objecta)\n os.remove(from_file)","def s3_delete_data(self):\n\n self.k.delete()","def delete_object_from_bucket(bucket_name, file_name, object_name):\n # If S3 object_name was not specified, use file_name\n if object_name is None:\n object_name = os.path.basename(file_name)\n\n try:\n # Delete object from bucket\n response = s3.delete_object(Bucket=bucket_name, Key=object_name)\n # List files in bucket to confirm\n describe_objects(bucket_name)\n except ClientError as e:\n logging.error(e)\n return False\n return True","def delete(self, key):\n return s3.Object(self.bucket.name, key).delete()","def delete(self, filename, **kw):\n\n file_path = os.path.join(self.storage_path, filename)\n\n try:\n os.remove(file_path)\n except OSError:\n pass","def delete_from_s3(site, bucket, prefix=None):\n if bucket is None:\n print red('Error: Bucket must be specified.')\n return\n # Setup boto\n import boto\n from boto.s3.bucket import Bucket\n from boto.s3.key import Key\n\n setup_aws_access_key(site)\n\n # Fix the prefix\n if prefix:\n prefix = prefix.lstrip('/')\n\n # Connect to S3, list the contents, and remove all of the keys\n c = boto.connect_s3()\n b = Bucket(c, bucket)\n result_set = b.list(prefix=prefix)\n result = b.delete_keys([key.name for key in result_set])","async def rm(path: str):\n _ = path.strip('/').split('/')\n bucket = _[0]\n key = '/'.join(_[1:])\n if path.endswith('/'):\n key += '/'\n async with _create_client() as client:\n try:\n await client.delete_object(Bucket=bucket, Key=key)\n logger.info(f'Delete file \"{path}\" from bucket.')\n except ClientError:\n pass","def remove_s3_object(bucket, key, access_id, access_secret):\n try:\n s3_client(access_id, access_secret).delete_object(Bucket=bucket, Key=key)\n except ClientError as error:\n LOGGER.error(error)","def delete_file(va_bucket, uuid):\n key = va_bucket.get_key(uuid)\n print(\" {0} deleted from VA\".format(uuid))\n va_bucket.delete_key(uuid)","def delete(self, filepath: str) -> None:\n if self.isfile(filepath):\n storage_services.delete(\n self._bucket_name, self._get_gcs_file_url(filepath))\n else:\n raise IOError('File does not exist: %s' % filepath)","def rm(self, s3uri, **kwargs):\n return self.exec_command('rm %s' % (s3uri), **kwargs)","def delete_file(filename):\n\tprint client.file_delete(filename)","def delete_from_s3(image_name):\n conn = S3Connection(aws_access_key_id, aws_secret_access_key)\n bucket = Bucket(conn, \"shopifyimagerepository\")\n k = Key(bucket)\n k.key = image_name\n bucket.delete_key(k)","def test_delete_file(self):\n # put file\n self.prepare_uploads()\n backend = BackendS3(**self.config)\n uploads = self.upload_path\n src = os.path.join(uploads, 'test.tar.gz')\n\n id1 = utils.generate_id('test.tar.gz')\n backend.put(src, id1)\n\n # regression testing (only delete what requested)\n id2 = id1.split('-')\n id2[4] += 'ZZZ'\n id2 = '-'.join(id2)\n\n backend.put(src, id1, True)\n backend.put_variant(src, id1, 'demo.txt')\n backend.put(src, id2, True)\n backend.delete(id1)\n\n path1 = '/'.join(backend.id_to_path(id1)) + '/test.tar.gz'\n path2 = '/'.join(backend.id_to_path(id1)) + '/demo.txt'\n self.assertFalse(backend.exists(path1))\n self.assertFalse(backend.exists(path2))\n\n # assume only proper file deleted\n path3 = '/'.join(backend.id_to_path(id2)) + '/test.tar.gz'\n self.assertTrue(backend.exists(path3))","def delete(self, filename):\n pass","def delete_bucket(s3bucket_name, Region, ACCESS_KEY, SECRET_KEY):\n s3 = boto3.resource('s3',\n region_name=Region,\n aws_access_key_id=ACCESS_KEY,\n aws_secret_access_key=SECRET_KEY)\n\n bucket = s3.Bucket(s3bucket_name)\n response = bucket.objects.all().delete()\n bucket.delete()\n if 'ResponseMetadata' in response and response[0]['ResponseMetadata']['HTTPStatusCode'] < 300:\n print('Got response to S3 bucket delete all {}'.format(response))\n return True\n else:\n return False","def delete_file(self, instance, file, where):\n\n instance = self.get_instance(instance)\n try:\n if instance.get('address'):\n username = instance.get('address') + \"@\" + instance.get('credentials').get('username')\n key = instance.get('credentials').get('publickey')\n subprocess.check_output([\"ssh\", key, username, 'rm', self.default_path_aws + where + file])\n else:\n username = 'ubuntu@' + instance.get('credentials').get('EC2_ACCESS_ID')\n key = instance.get('credentials').get('EC2_SECRET_KEY')\n # output = os.popen(\"ls\"+ \" | \" + \"ssh\"+ \" -i \"+ key +\" \"+ username).read()\n subprocess.check_output([\"ssh\", \"-i\", key, username, 'rm', self.default_path_aws + where + file])\n return \"Success to delete the file \" + file + \" from \" + self.default_path_aws + where\n except:\n return \"Fail to access the instance\"","def _delete_s3_files(self, bucket_name: str, stacks_to_delete: dict()):\n s3_keys_to_be_deleted = self._get_s3_keys_to_delete(stacks_to_delete)\n s3_objects_to_delete = []\n for f in s3_keys_to_be_deleted:\n s3_objects_to_delete.append({'Key': f})\n\n logger.info(f' Deleting [{len(s3_keys_to_be_deleted)}] cfn template(s) from s3 {s3_keys_to_be_deleted}')\n if len(s3_objects_to_delete) > 0:\n s3_bucket = self.s3_resource.Bucket(bucket_name)\n s3_bucket.delete_objects(Delete={'Objects': s3_objects_to_delete})","def _delete_blob(self, source_file_path):\n\n if os.path.exists(source_file_path) and os.path.isfile(source_file_path):\n destination_blob_name = os.path.basename(source_file_path)\n\n bucket = self._storage_client.bucket(self._bucket_name)\n blob = bucket.blob(destination_blob_name)\n\n blob.delete()\n\n print(f'Blob {destination_blob_name} deleted.')\n else:\n error_message = f'{source_file_path} does not exist.'\n raise FileNotFoundError(error_message)","def delete_file(self, filepath):\n self.ftp.delete(filepath)","def delete_object(self, object_path):\n bucket_name, save_path = self.split_name(object_path)\n self.s3_client.delete_object(Bucket=bucket_name, Key=save_path)\n return True","def remove_s3_credentials():\n params = {\"secret_key_id\": \"delete\",\n \"secret_access_key\": \"delete\"}\n h2o.api(\"DELETE /3/PersistS3\", data=params)\n print(\"Credentials successfully removed.\")","def delete(self, bucket: str, object_name: str):\n raise NotImplementedError()","def delete_file(self, filename=None):\n return self._service.delete_object(self._datasets_id, filename)","def clean_s3(self, path=None):\n backend = BackendS3(**self.config)\n backend.recursive_delete()","def delete_blob(bucket_name, blob_name):\n storage_client = storage.Client()\n bucket = storage_client.get_bucket(bucket_name)\n blob = bucket.blob(blob_name)\n\n blob.delete()\n\n print('Blob {} deleted.'.format(blob_name))","def aws_s3_rm(s3_key: str)->bool:\n client = boto3.client(\"s3\")\n #list objects\n objs_to_delete = aws_s3_ls(s3_key)\n if len(objs_to_delete) ==0: # no files to delete\n return True\n s3_bucket, _ = _extract_bucket_key(s3_key)\n #prepare s3 objects to delete\n objs_list=[]\n for obj in objs_to_delete:\n objs_list.append({\"Key\": obj})\n \n try:\n response = client.delete_objects(\n Bucket=s3_bucket,\n Delete={\n 'Objects': objs_list,\n 'Quiet': False\n }\n )\n except Exception as exc:\n raise Error(\"Cannot delete, exception {} occurred\".format(exc))\n \n return True","def delete_file(path):\n return files.delete_file(path)","def delete(self, *route, **req_data):\n # Read the file ID from the request, with safety.\n try:\n file_id = UUID(req_data['file_id']).hex\n except ValueError:\n return Response(status='400 Bad Request')\n\n # Retrieve and delete the file.\n stored_files = StoredFile.collection()\n to_delete = stored_files.first(id=file_id)\n\n log_activity('%s deleted file %s'%(\n context.user.link, to_delete.filename\n ))\n\n stored_files.delete(to_delete)\n get_bucket().delete(to_delete.data_id)\n\n return Response(status='200 OK')","def delete_folder_from_s3(s3_folder, connection=None):\n if connection:\n run_out = connection.run(f\"aws s3 rm --recursive {s3_folder}\")\n else:\n run_out = run(f\"aws s3 rm --recursive {s3_folder}\")\n\n return run_out.return_code","def delete_file(self):\n if (not self.exists()):\n raise IOError(\"File at '{}' does not exist.\".format(self.location))\n os.remove(self.location)","def delete(self, key):\n self.resource.Object(self.bucketname, key).delete()","def deleteObject(bucket:str, object:str, region:str, version:str=None) -> None:\n client = boto3.client('s3', region_name=region)\n if version:\n client.delete_object(\n Bucket=bucket,\n Key=object,\n VersionId=version,\n )\n else:\n client.delete_object(\n Bucket=bucket,\n Key=object,\n )","def delete(self, filename):\n raise NotImplementedError","def deleteBucket(bucket:str, region:str) -> None:\n client = boto3.client('s3', region_name=region)\n try:\n client.delete_bucket(Bucket=bucket)\n except ClientError as e:\n raise BucketDeletionError(e)","def delete_blob(bucket_name, blob_name):\r\n\r\n # initialize client, get bucket, & get blob\r\n _, _, blob = create_client(bucket_name, blob_name)\r\n\r\n # delete blob\r\n blob.delete()\r\n\r\n print(\"blob {} deleted\".format(blob_name))","def s3purge(bucket):\n answer = input(f\"Are you sure you want to purge bucket {bucket} [Y/N]?\")\n if answer != \"Y\":\n print(\"Aborting\")\n return\n s3 = boto3.resource('s3')\n bucket = s3.Bucket(bucket)\n bucket.object_versions.all().delete()","def delete_file(self, name):\n del self.files[name]","def delete_bucket(bucket_name):\r\n\r\n # initialize client & get bucket\r\n storage_client, bucket, _ = create_client(bucket_name)\r\n\r\n # delete bucket\r\n bucket.delete()\r\n\r\n print(\"bucket {} deleted\".format(bucket_name))","async def delete_file(location_id: LocationID, file_id: StorageFileID, user_id: UserID):","def delete_object(self, bucket_name, key):\n url = self.__key_url(bucket_name, key)\n return self.infinispan_client.delete(url, headers=self.headers, auth=self.basicAuth)","def DeleteFile(self, file_id):\n self.service.files().delete(fileId=file_id).execute()","def delete_bucket(Bucket=None):\n pass","def _delete(filename):\n return os.remove(filename)","def delete_file(sender, instance, *args, **kwargs):\n if instance.file:\n _delete_file(instance.file.path)","def delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete_file(self, file_id):\n try:\n self.drive_service.files().delete(fileId=file_id).execute()\n except errors.HttpError, error:\n print 'An error occurred: %s' % error","def test_s3_delete(self):\n keys = [self.bucket + '/another_directory/text2.txt',\n self.bucket + '/text1.txt',\n self.bucket + '/another_directory/']\n tasks = []\n for key in keys:\n tasks.append(FileInfo(\n src=key, src_type='s3',\n dest_type='local', operation_name='delete',\n size=0, client=self.client,\n source_client=self.source_client\n ))\n response = self.client.list_objects(Bucket=self.bucket)\n self.assertEqual(len(response.get('Contents', [])), 3)\n self.s3_handler.call(tasks)\n response = self.client.list_objects(Bucket=self.bucket)\n self.assertEqual(len(response.get('Contents', [])), 0)","def delete_contents_of_s3_directory(directory, bucket_name=None):\n if bucket_name is None:\n bucket_name, directory = get_bucket_and_path_from_uri(directory)\n\n if isinstance(bucket_name, Bucket):\n bucket_name = bucket_name.name\n\n logger.info(\"deleting contents of s3 bucket %s directory %s\", bucket_name, directory)\n\n assert len(directory) > 10, \"just in case don't want to delete the root of the bucket...\"\n\n # Deleting keys from s3 appears to max out at 1000 entries so we need to do this multiple times until the directory is clear.\n while _delete_1000_s3_files(bucket_name, directory):\n pass","def delete_file(file_id):\n file_obj = Data.objects.get(id=file_id)\n print(\"Removing file: \", file_obj.name)\n print(file_obj.file.path)\n file_dir = file_obj.file.path\n os.remove(file_dir)\n print(\"Done.\")","def delete_bucket(self, name):\n return","def delete(self, src):\n\n if self.noop:\n logger.info(\"No-Op Delete: %s.tar\" % self.bucket + src)\n else:\n logger.info(\"Trying to delete %s.tar\" % self.bucket + src)\n self.client.delete(self.bucket + src + \".tar\")","def delete_file(self, path):\n return self.client._perform_empty(\n \"DELETE\", \"/projects/%s/managedfolders/%s/contents/%s\" % (self.project_key, self.odb_id, utils.quote(path)))","def delete_whole_bucket(bucket):\n bucket = s3r.Bucket(bucket)\n for key in bucket.objects.all():\n key.delete()\n bucket.delete()\n print(bucket, \" : is deletd \")","def delete_file(self, upload_id: str, file_path: str, token: str) \\\n -> Upload:\n data, _, _ = self.json('delete', f'/{upload_id}/{file_path}', token)\n return self._parse_upload_status(data)","def delete(self):\n\n try:\n remove(self.file)\n except OSError:\n pass","def delete_file(self, key):\n path = os.path.join(self.directory, self.subdirectory, key)\n if os.path.isfile(path):\n os.unlink(path)\n else:\n raise ValueError(f\"No such file: {key}\")","def delete_file(filename):\n if os.path.isfile(filename):\n return os.remove(filename)","def _delete(self, remote_filename):\n\n file_id = self.get_file_id(remote_filename)\n if file_id is None:\n raise BackendException(\n 'File \"%s\" cannot be deleted: it does not exist' % (\n remote_filename))\n response = self.http_client.put(self.metadata_url + 'trash/' + file_id)\n response.raise_for_status()\n del self.names_to_ids[remote_filename]","def delete(self):\r\n return self.bucket.delete_key(self.name, version_id=self.version_id)","def safe_delete(self, filename):\n try:\n os.remove(filename)\n except OSError:\n pass","def _delete_file(file_id):\n log.warning(f\"Deleting file '{file_id}'...\")\n _drive_service.files().delete(fileId=file_id).execute()\n log.info(f\"Deleting file '{file_id}' - done.\")","def delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete_file(self, path):\n if not path_exists(path, self._store_folder):\n raise NotFoundException(\"\")\n os.remove(path)","def delete(self):\n request_data = request.get_json(force=True)\n current_path = self.get_current_path()\n file_name = request_data.get('file_name')\n\n if not file_name:\n abort(400, message=\"File name must not be empty!\")\n\n full_path = os.path.join(current_path, file_name)\n\n if not os.path.exists(full_path):\n abort(400, message=\"File was not found in current path!\")\n\n if not os.path.isfile(full_path):\n abort(400, message=\"File name is not a file!\")\n\n if not self.is_allowed(full_path):\n abort(403, message=\"You are not allowed to this path\")\n\n os.remove(full_path)\n\n return {\"message\": \"OK\"}","def delete_upload(arn=None):\n pass","def delete_file(file: str) -> None:\n\tuux.show_info(\"Deleting \" + file)\n\n\tif not os.path.exists(file):\n\t\t# Files does not exist\n\t\treturn\n\n\tos.remove(file)","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete_file(self, file_id):\n self.drive_service.files().delete(fileId=file_id).execute()\n return file_id","def delete(self, *args, **kwargs):\n self.file.storage.delete(self.file.name)\n super().delete(*args, **kwargs)","def delFile(self, file_name):\n ret = self.rest.delete(self.ngx_server, self.getUrl() + '/' + file_name, {}, [200, 404])\n if ret == False:\n self.logger.error('delete file:%s from tfs failed.' % file_name)\n raise Exception, 'delete file:%s from tfs failed.' % file_name\n self.logger.info('Delete Tfs file: %s' % file_name)\n return True","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def Delete_File(self,txn,filename):\n opid = self.new_opid()\n xaction = DeleteFile_Operation(os.path.join(self.home,filename),opid)\n self._add_operation(txn,xaction)","def delete_file(filename, sudo=True):\n LOG.info(\"Deleting file {}\".format(filename))\n cmd = \"rm {}\".format(filename)\n _exec_cmd(cmd=cmd, sudo=sudo, fail_ok=False)","def delete_blob(blob_name):\n # bucket_name = \"your-bucket-name\"\n # blob_name = \"your-object-name\"\n storage_client = storage.Client()\n bucket = storage_client.get_bucket(bucket_name)\n blob = bucket.blob(blob_name)\n blob.delete()\n print('Blob {} deleted.'.format(blob_name))","def delete_asset(location, filename):\r\n try:\r\n content = Transcript.get_asset(location, filename)\r\n contentstore().delete(content.get_id())\r\n log.info(\"Transcript asset %s was removed from store.\", filename)\r\n except NotFoundError:\r\n pass\r\n return StaticContent.compute_location(location.course_key, filename)","def delete_file(self, filename):\n if not filename in self.files:\n raise IOError('File %s Not Found' % filename)\n\n for nodename in self.files[filename]:\n node = self.datanodes[nodename]\n node.delete_file(filename)\n del self.files[filename]\n logging.info('file %s deleted' % filename)","def delete(self, filename):\n try:\n self.storage.delete(filename)\n return {\n 'filename': filename,\n 'message': 'The file was deleted with success'\n }\n except FileNotFoundError:\n abort(404, message='File %s does not exist' % filename)\n except BaseException:\n abort(500, message='Failed to delete the file ' + filename)\n LOGGER.error('A generic exception has occurred.', exc_info=True)","def purge_and_delete_bucket(\n bucket_name: str, region: str = \"us-east-1\", session: Optional[boto3.Session] = None\n) -> None:\n purge_bucket(bucket_name, region, session)\n delete_bucket(bucket_name, region, session)","def purge_bucket(\n bucket_name: str, region: str = \"us-east-1\", session: Optional[boto3.Session] = None\n) -> None:\n if does_bucket_exist(bucket_name, region, session):\n s3_resource = _get_resource(session, region)\n bucket = s3_resource.Bucket(bucket_name)\n bucket.object_versions.delete()\n else:\n LOGGER.warning('bucket \"%s\" does not exist in region \"%s\"', bucket_name, region)","def rm_file(filename):\n try:\n os.unlink(filename)\n except FileNotFoundError:\n pass","def file_delete(self, path):\n params = {'root': self.session.root, 'path': format_path(path)}\n\n url, params, headers = self.request(\"/fileops/delete\", params)\n\n return self.rest_client.POST(url, params, headers)","def delete(self):\n\t\t#self.log.info(\"Deleting file {}\".format(self._filepath))\n\t\tos.remove(self._filepath)","def delete_file(self, path):\n raise HTTPError(\n 501,\n \"Narrative deletion not implemented here. Deletion is handled elsewhere.\",\n )","def rm_file(file_):\n Path(file_).unlink(missing_ok=True)","def replay_delete(sender, instance, **kwargs):\n pass\n # Temporarily disabled\n\n #print(\"deleting file from S3\")\n # False so FileField doesn't save the model\n #instance.file.delete(False)","def remove( filename ):\n try:\n os.remove( filename )\n except OSError as e:\n if e.errno != errno.ENOENT:\n raise e","def delete_key(self, bucket_name, key_name):\n bucket = self.s3_.get_bucket(bucket_name)\n key = bucket.get_key(key_name)\n return key.delete()","def delete(self):\n if os.path.exists(self.file_path):\n os.remove(self.file_path)"],"string":"[\n \"def delete_file(bucket, file_to_be_deleted):\\n s3 = boto3.client('s3', aws_access_key_id=access_key, aws_secret_access_key=secret_key)\\n s3.delete_object(Bucket=bucket, Key=file_to_be_deleted)\\n print(file_to_be_deleted, \\\" : is deleted from the bucket\\\")\",\n \"def delete_file_from_s3(bucket_name, filepath):\\n if filepath not in list_files_in_s3_bucket(bucket_name):\\n raise FileNotFoundError(\\n f\\\"The filepath specified '{filepath}' does not exist in the\\\"\\n f\\\" bucket '{bucket_name}'\\\"\\n )\\n s3 = boto3.client(\\\"s3\\\")\\n s3.delete_object(Bucket=bucket_name, Key=filepath)\",\n \"def delete_object(self, s3_path):\\n logging.info(\\\"Deleting \\\\\\\"{}\\\\\\\" file from S3\\\".format(s3_path))\\n bucket_name, key = S3Util.get_bucket_and_key(s3_path)\\n self.s3_resource.ObjectSummary(bucket_name, key).delete()\",\n \"def del_file(self, key):\\n\\t\\t\\n\\t\\ttry: \\n\\t\\t\\tself.s3.delete(self.bucket, key) \\n\\t\\texcept:\\n\\t\\t\\treturn False\",\n \"def gcloud_delete_file(file_name, gcloud_bucket_name):\\n bucket = gce_storage_client.get_bucket(gcloud_bucket_name)\\n blob = bucket.blob(file_name)\\n\\n blob.delete()\",\n \"def delete(self, args):\\n try:\\n assert len(args) > 0\\n file_name = args[0]\\n try:\\n if should('Delete %s?' % file_name):\\n self.s3.Object(self.bucket_name, file_name).load()\\n self.s3.Object(self.bucket_name, file_name).delete()\\n print('File %s deleted!' % file_name)\\n except ClientError:\\n print('File %s not found in bucket %s' % (file_name, self.bucket_name))\\n except AssertionError:\\n print('I need a file name!')\",\n \"def s3_delete_local(self, local_file, bucket, bucket_filepath):\\n\\n s3 = boto3.client('s3')\\n with open(local_file, \\\"rb\\\") as f:\\n if 'vsis3' in bucket:\\n bucket = bucket.split('/')[-1]\\n print(bucket, bucket_filepath)\\n s3.upload_fileobj(f, bucket, bucket_filepath)\\n os.remove(local_file)\",\n \"def rm(self, filename: str) -> None:\\n\\n now = datetime.datetime.utcnow()\\n timestamp = now.strftime('%a, %d %b %Y %H:%M:%S GMT')\\n headers = [\\n ('Connection', 'keep-alive'),\\n ('Content-Length', '0'),\\n ('Date', timestamp),\\n ('Host', '%s.s3.amazonaws.com' % self.bucket),\\n ('x-amz-content-sha256', _EMPTY_SHA256_HASH),\\n ]\\n signed_headers = ';'.join(header[0].lower() for header in headers)\\n canonical_request = 'DELETE\\\\n%s\\\\n\\\\n%s\\\\n\\\\n%s\\\\n%s' % (\\n filename, '\\\\n'.join(\\n ('%s:%s' % (header[0].lower(), header[1])\\n for header in headers)), signed_headers, _EMPTY_SHA256_HASH)\\n logging.debug('canonical request %r',\\n canonical_request.encode('utf-8'))\\n string_to_sign = 'AWS4-HMAC-SHA256\\\\n%s\\\\n%s\\\\n%s' % (\\n timestamp, self.scope,\\n hashlib.sha256(canonical_request.encode('utf-8')).hexdigest())\\n logging.debug('string to sign %r', string_to_sign.encode('utf-8'))\\n\\n signature = hmac.new(self.signing_key,\\n string_to_sign.encode('utf-8'),\\n digestmod='sha256').hexdigest()\\n headers.append((\\n 'Authorization',\\n 'AWS4-HMAC-SHA256 Credential=%s/%s,SignedHeaders=%s,Signature=%s' %\\n (self.aws_access_key, self.scope, signed_headers, signature)))\\n if not self.conn:\\n self.conn = http.client.HTTPSConnection('%s.s3.amazonaws.com' %\\n self.bucket)\\n try:\\n self.conn.request('DELETE', filename, headers=dict(headers))\\n res = self.conn.getresponse()\\n payload = res.read()\\n except (http.client.BadStatusLine, http.client.ResponseNotReady,\\n http.client.CannotSendRequest):\\n self.conn.close()\\n raise\\n if res.status != 204:\\n raise Exception(payload.decode('utf-8'))\",\n \"def delete(c, bucket=None):\\n if bucket == None:\\n bucket = \\\"dvc-\\\" + project_dir_name().replace(\\\"_\\\",\\\"-\\\")\\n bucket_resource = boto3.resource('s3').Bucket(bucket)\\n bucket_resource.objects.all().delete()\\n s3 = boto3.client(\\\"s3\\\")\\n s3.delete_bucket(Bucket=bucket)\",\n \"def delete_key(bucket_name: str, path: str) -> None:\\n global config\\n session = config.get_session_fn()\\n s3_client = session.client(\\\"s3\\\")\\n try:\\n s3_client.delete_object(Bucket=bucket_name, Key=path)\\n except Exception as e:\\n logger.warning(f\\\"Failed to delete {path} from s3: {e}\\\")\",\n \"def _removeAWSS3Object(self, path: str):\\n log.warning(f'Deleting AWS S3 object {path}')\\n bucket, key = storage_utils.SplitStoragePath(path)\\n s3_client = boto3.client('s3')\\n try:\\n s3_client.delete_object(Bucket=bucket, Key=key)\\n except Exception as error: # pylint: disable=broad-except\\n log.error(f'Failed to delete S3 Object {path}: {str(error)}')\",\n \"def s3_delete_local(self, outpath, from_file, bucket, prefix_no_slash):\\n\\n objecta='{}/{}'.format(prefix_no_slash,outpath)\\n s3 = boto3.client('s3')\\n with open(from_file, \\\"rb\\\") as f:\\n s3.upload_fileobj(f, bucket, objecta)\\n os.remove(from_file)\",\n \"def s3_delete_data(self):\\n\\n self.k.delete()\",\n \"def delete_object_from_bucket(bucket_name, file_name, object_name):\\n # If S3 object_name was not specified, use file_name\\n if object_name is None:\\n object_name = os.path.basename(file_name)\\n\\n try:\\n # Delete object from bucket\\n response = s3.delete_object(Bucket=bucket_name, Key=object_name)\\n # List files in bucket to confirm\\n describe_objects(bucket_name)\\n except ClientError as e:\\n logging.error(e)\\n return False\\n return True\",\n \"def delete(self, key):\\n return s3.Object(self.bucket.name, key).delete()\",\n \"def delete(self, filename, **kw):\\n\\n file_path = os.path.join(self.storage_path, filename)\\n\\n try:\\n os.remove(file_path)\\n except OSError:\\n pass\",\n \"def delete_from_s3(site, bucket, prefix=None):\\n if bucket is None:\\n print red('Error: Bucket must be specified.')\\n return\\n # Setup boto\\n import boto\\n from boto.s3.bucket import Bucket\\n from boto.s3.key import Key\\n\\n setup_aws_access_key(site)\\n\\n # Fix the prefix\\n if prefix:\\n prefix = prefix.lstrip('/')\\n\\n # Connect to S3, list the contents, and remove all of the keys\\n c = boto.connect_s3()\\n b = Bucket(c, bucket)\\n result_set = b.list(prefix=prefix)\\n result = b.delete_keys([key.name for key in result_set])\",\n \"async def rm(path: str):\\n _ = path.strip('/').split('/')\\n bucket = _[0]\\n key = '/'.join(_[1:])\\n if path.endswith('/'):\\n key += '/'\\n async with _create_client() as client:\\n try:\\n await client.delete_object(Bucket=bucket, Key=key)\\n logger.info(f'Delete file \\\"{path}\\\" from bucket.')\\n except ClientError:\\n pass\",\n \"def remove_s3_object(bucket, key, access_id, access_secret):\\n try:\\n s3_client(access_id, access_secret).delete_object(Bucket=bucket, Key=key)\\n except ClientError as error:\\n LOGGER.error(error)\",\n \"def delete_file(va_bucket, uuid):\\n key = va_bucket.get_key(uuid)\\n print(\\\" {0} deleted from VA\\\".format(uuid))\\n va_bucket.delete_key(uuid)\",\n \"def delete(self, filepath: str) -> None:\\n if self.isfile(filepath):\\n storage_services.delete(\\n self._bucket_name, self._get_gcs_file_url(filepath))\\n else:\\n raise IOError('File does not exist: %s' % filepath)\",\n \"def rm(self, s3uri, **kwargs):\\n return self.exec_command('rm %s' % (s3uri), **kwargs)\",\n \"def delete_file(filename):\\n\\tprint client.file_delete(filename)\",\n \"def delete_from_s3(image_name):\\n conn = S3Connection(aws_access_key_id, aws_secret_access_key)\\n bucket = Bucket(conn, \\\"shopifyimagerepository\\\")\\n k = Key(bucket)\\n k.key = image_name\\n bucket.delete_key(k)\",\n \"def test_delete_file(self):\\n # put file\\n self.prepare_uploads()\\n backend = BackendS3(**self.config)\\n uploads = self.upload_path\\n src = os.path.join(uploads, 'test.tar.gz')\\n\\n id1 = utils.generate_id('test.tar.gz')\\n backend.put(src, id1)\\n\\n # regression testing (only delete what requested)\\n id2 = id1.split('-')\\n id2[4] += 'ZZZ'\\n id2 = '-'.join(id2)\\n\\n backend.put(src, id1, True)\\n backend.put_variant(src, id1, 'demo.txt')\\n backend.put(src, id2, True)\\n backend.delete(id1)\\n\\n path1 = '/'.join(backend.id_to_path(id1)) + '/test.tar.gz'\\n path2 = '/'.join(backend.id_to_path(id1)) + '/demo.txt'\\n self.assertFalse(backend.exists(path1))\\n self.assertFalse(backend.exists(path2))\\n\\n # assume only proper file deleted\\n path3 = '/'.join(backend.id_to_path(id2)) + '/test.tar.gz'\\n self.assertTrue(backend.exists(path3))\",\n \"def delete(self, filename):\\n pass\",\n \"def delete_bucket(s3bucket_name, Region, ACCESS_KEY, SECRET_KEY):\\n s3 = boto3.resource('s3',\\n region_name=Region,\\n aws_access_key_id=ACCESS_KEY,\\n aws_secret_access_key=SECRET_KEY)\\n\\n bucket = s3.Bucket(s3bucket_name)\\n response = bucket.objects.all().delete()\\n bucket.delete()\\n if 'ResponseMetadata' in response and response[0]['ResponseMetadata']['HTTPStatusCode'] < 300:\\n print('Got response to S3 bucket delete all {}'.format(response))\\n return True\\n else:\\n return False\",\n \"def delete_file(self, instance, file, where):\\n\\n instance = self.get_instance(instance)\\n try:\\n if instance.get('address'):\\n username = instance.get('address') + \\\"@\\\" + instance.get('credentials').get('username')\\n key = instance.get('credentials').get('publickey')\\n subprocess.check_output([\\\"ssh\\\", key, username, 'rm', self.default_path_aws + where + file])\\n else:\\n username = 'ubuntu@' + instance.get('credentials').get('EC2_ACCESS_ID')\\n key = instance.get('credentials').get('EC2_SECRET_KEY')\\n # output = os.popen(\\\"ls\\\"+ \\\" | \\\" + \\\"ssh\\\"+ \\\" -i \\\"+ key +\\\" \\\"+ username).read()\\n subprocess.check_output([\\\"ssh\\\", \\\"-i\\\", key, username, 'rm', self.default_path_aws + where + file])\\n return \\\"Success to delete the file \\\" + file + \\\" from \\\" + self.default_path_aws + where\\n except:\\n return \\\"Fail to access the instance\\\"\",\n \"def _delete_s3_files(self, bucket_name: str, stacks_to_delete: dict()):\\n s3_keys_to_be_deleted = self._get_s3_keys_to_delete(stacks_to_delete)\\n s3_objects_to_delete = []\\n for f in s3_keys_to_be_deleted:\\n s3_objects_to_delete.append({'Key': f})\\n\\n logger.info(f' Deleting [{len(s3_keys_to_be_deleted)}] cfn template(s) from s3 {s3_keys_to_be_deleted}')\\n if len(s3_objects_to_delete) > 0:\\n s3_bucket = self.s3_resource.Bucket(bucket_name)\\n s3_bucket.delete_objects(Delete={'Objects': s3_objects_to_delete})\",\n \"def _delete_blob(self, source_file_path):\\n\\n if os.path.exists(source_file_path) and os.path.isfile(source_file_path):\\n destination_blob_name = os.path.basename(source_file_path)\\n\\n bucket = self._storage_client.bucket(self._bucket_name)\\n blob = bucket.blob(destination_blob_name)\\n\\n blob.delete()\\n\\n print(f'Blob {destination_blob_name} deleted.')\\n else:\\n error_message = f'{source_file_path} does not exist.'\\n raise FileNotFoundError(error_message)\",\n \"def delete_file(self, filepath):\\n self.ftp.delete(filepath)\",\n \"def delete_object(self, object_path):\\n bucket_name, save_path = self.split_name(object_path)\\n self.s3_client.delete_object(Bucket=bucket_name, Key=save_path)\\n return True\",\n \"def remove_s3_credentials():\\n params = {\\\"secret_key_id\\\": \\\"delete\\\",\\n \\\"secret_access_key\\\": \\\"delete\\\"}\\n h2o.api(\\\"DELETE /3/PersistS3\\\", data=params)\\n print(\\\"Credentials successfully removed.\\\")\",\n \"def delete(self, bucket: str, object_name: str):\\n raise NotImplementedError()\",\n \"def delete_file(self, filename=None):\\n return self._service.delete_object(self._datasets_id, filename)\",\n \"def clean_s3(self, path=None):\\n backend = BackendS3(**self.config)\\n backend.recursive_delete()\",\n \"def delete_blob(bucket_name, blob_name):\\n storage_client = storage.Client()\\n bucket = storage_client.get_bucket(bucket_name)\\n blob = bucket.blob(blob_name)\\n\\n blob.delete()\\n\\n print('Blob {} deleted.'.format(blob_name))\",\n \"def aws_s3_rm(s3_key: str)->bool:\\n client = boto3.client(\\\"s3\\\")\\n #list objects\\n objs_to_delete = aws_s3_ls(s3_key)\\n if len(objs_to_delete) ==0: # no files to delete\\n return True\\n s3_bucket, _ = _extract_bucket_key(s3_key)\\n #prepare s3 objects to delete\\n objs_list=[]\\n for obj in objs_to_delete:\\n objs_list.append({\\\"Key\\\": obj})\\n \\n try:\\n response = client.delete_objects(\\n Bucket=s3_bucket,\\n Delete={\\n 'Objects': objs_list,\\n 'Quiet': False\\n }\\n )\\n except Exception as exc:\\n raise Error(\\\"Cannot delete, exception {} occurred\\\".format(exc))\\n \\n return True\",\n \"def delete_file(path):\\n return files.delete_file(path)\",\n \"def delete(self, *route, **req_data):\\n # Read the file ID from the request, with safety.\\n try:\\n file_id = UUID(req_data['file_id']).hex\\n except ValueError:\\n return Response(status='400 Bad Request')\\n\\n # Retrieve and delete the file.\\n stored_files = StoredFile.collection()\\n to_delete = stored_files.first(id=file_id)\\n\\n log_activity('%s deleted file %s'%(\\n context.user.link, to_delete.filename\\n ))\\n\\n stored_files.delete(to_delete)\\n get_bucket().delete(to_delete.data_id)\\n\\n return Response(status='200 OK')\",\n \"def delete_folder_from_s3(s3_folder, connection=None):\\n if connection:\\n run_out = connection.run(f\\\"aws s3 rm --recursive {s3_folder}\\\")\\n else:\\n run_out = run(f\\\"aws s3 rm --recursive {s3_folder}\\\")\\n\\n return run_out.return_code\",\n \"def delete_file(self):\\n if (not self.exists()):\\n raise IOError(\\\"File at '{}' does not exist.\\\".format(self.location))\\n os.remove(self.location)\",\n \"def delete(self, key):\\n self.resource.Object(self.bucketname, key).delete()\",\n \"def deleteObject(bucket:str, object:str, region:str, version:str=None) -> None:\\n client = boto3.client('s3', region_name=region)\\n if version:\\n client.delete_object(\\n Bucket=bucket,\\n Key=object,\\n VersionId=version,\\n )\\n else:\\n client.delete_object(\\n Bucket=bucket,\\n Key=object,\\n )\",\n \"def delete(self, filename):\\n raise NotImplementedError\",\n \"def deleteBucket(bucket:str, region:str) -> None:\\n client = boto3.client('s3', region_name=region)\\n try:\\n client.delete_bucket(Bucket=bucket)\\n except ClientError as e:\\n raise BucketDeletionError(e)\",\n \"def delete_blob(bucket_name, blob_name):\\r\\n\\r\\n # initialize client, get bucket, & get blob\\r\\n _, _, blob = create_client(bucket_name, blob_name)\\r\\n\\r\\n # delete blob\\r\\n blob.delete()\\r\\n\\r\\n print(\\\"blob {} deleted\\\".format(blob_name))\",\n \"def s3purge(bucket):\\n answer = input(f\\\"Are you sure you want to purge bucket {bucket} [Y/N]?\\\")\\n if answer != \\\"Y\\\":\\n print(\\\"Aborting\\\")\\n return\\n s3 = boto3.resource('s3')\\n bucket = s3.Bucket(bucket)\\n bucket.object_versions.all().delete()\",\n \"def delete_file(self, name):\\n del self.files[name]\",\n \"def delete_bucket(bucket_name):\\r\\n\\r\\n # initialize client & get bucket\\r\\n storage_client, bucket, _ = create_client(bucket_name)\\r\\n\\r\\n # delete bucket\\r\\n bucket.delete()\\r\\n\\r\\n print(\\\"bucket {} deleted\\\".format(bucket_name))\",\n \"async def delete_file(location_id: LocationID, file_id: StorageFileID, user_id: UserID):\",\n \"def delete_object(self, bucket_name, key):\\n url = self.__key_url(bucket_name, key)\\n return self.infinispan_client.delete(url, headers=self.headers, auth=self.basicAuth)\",\n \"def DeleteFile(self, file_id):\\n self.service.files().delete(fileId=file_id).execute()\",\n \"def delete_bucket(Bucket=None):\\n pass\",\n \"def _delete(filename):\\n return os.remove(filename)\",\n \"def delete_file(sender, instance, *args, **kwargs):\\n if instance.file:\\n _delete_file(instance.file.path)\",\n \"def delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete_file(self, file_id):\\n try:\\n self.drive_service.files().delete(fileId=file_id).execute()\\n except errors.HttpError, error:\\n print 'An error occurred: %s' % error\",\n \"def test_s3_delete(self):\\n keys = [self.bucket + '/another_directory/text2.txt',\\n self.bucket + '/text1.txt',\\n self.bucket + '/another_directory/']\\n tasks = []\\n for key in keys:\\n tasks.append(FileInfo(\\n src=key, src_type='s3',\\n dest_type='local', operation_name='delete',\\n size=0, client=self.client,\\n source_client=self.source_client\\n ))\\n response = self.client.list_objects(Bucket=self.bucket)\\n self.assertEqual(len(response.get('Contents', [])), 3)\\n self.s3_handler.call(tasks)\\n response = self.client.list_objects(Bucket=self.bucket)\\n self.assertEqual(len(response.get('Contents', [])), 0)\",\n \"def delete_contents_of_s3_directory(directory, bucket_name=None):\\n if bucket_name is None:\\n bucket_name, directory = get_bucket_and_path_from_uri(directory)\\n\\n if isinstance(bucket_name, Bucket):\\n bucket_name = bucket_name.name\\n\\n logger.info(\\\"deleting contents of s3 bucket %s directory %s\\\", bucket_name, directory)\\n\\n assert len(directory) > 10, \\\"just in case don't want to delete the root of the bucket...\\\"\\n\\n # Deleting keys from s3 appears to max out at 1000 entries so we need to do this multiple times until the directory is clear.\\n while _delete_1000_s3_files(bucket_name, directory):\\n pass\",\n \"def delete_file(file_id):\\n file_obj = Data.objects.get(id=file_id)\\n print(\\\"Removing file: \\\", file_obj.name)\\n print(file_obj.file.path)\\n file_dir = file_obj.file.path\\n os.remove(file_dir)\\n print(\\\"Done.\\\")\",\n \"def delete_bucket(self, name):\\n return\",\n \"def delete(self, src):\\n\\n if self.noop:\\n logger.info(\\\"No-Op Delete: %s.tar\\\" % self.bucket + src)\\n else:\\n logger.info(\\\"Trying to delete %s.tar\\\" % self.bucket + src)\\n self.client.delete(self.bucket + src + \\\".tar\\\")\",\n \"def delete_file(self, path):\\n return self.client._perform_empty(\\n \\\"DELETE\\\", \\\"/projects/%s/managedfolders/%s/contents/%s\\\" % (self.project_key, self.odb_id, utils.quote(path)))\",\n \"def delete_whole_bucket(bucket):\\n bucket = s3r.Bucket(bucket)\\n for key in bucket.objects.all():\\n key.delete()\\n bucket.delete()\\n print(bucket, \\\" : is deletd \\\")\",\n \"def delete_file(self, upload_id: str, file_path: str, token: str) \\\\\\n -> Upload:\\n data, _, _ = self.json('delete', f'/{upload_id}/{file_path}', token)\\n return self._parse_upload_status(data)\",\n \"def delete(self):\\n\\n try:\\n remove(self.file)\\n except OSError:\\n pass\",\n \"def delete_file(self, key):\\n path = os.path.join(self.directory, self.subdirectory, key)\\n if os.path.isfile(path):\\n os.unlink(path)\\n else:\\n raise ValueError(f\\\"No such file: {key}\\\")\",\n \"def delete_file(filename):\\n if os.path.isfile(filename):\\n return os.remove(filename)\",\n \"def _delete(self, remote_filename):\\n\\n file_id = self.get_file_id(remote_filename)\\n if file_id is None:\\n raise BackendException(\\n 'File \\\"%s\\\" cannot be deleted: it does not exist' % (\\n remote_filename))\\n response = self.http_client.put(self.metadata_url + 'trash/' + file_id)\\n response.raise_for_status()\\n del self.names_to_ids[remote_filename]\",\n \"def delete(self):\\r\\n return self.bucket.delete_key(self.name, version_id=self.version_id)\",\n \"def safe_delete(self, filename):\\n try:\\n os.remove(filename)\\n except OSError:\\n pass\",\n \"def _delete_file(file_id):\\n log.warning(f\\\"Deleting file '{file_id}'...\\\")\\n _drive_service.files().delete(fileId=file_id).execute()\\n log.info(f\\\"Deleting file '{file_id}' - done.\\\")\",\n \"def delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete_file(self, path):\\n if not path_exists(path, self._store_folder):\\n raise NotFoundException(\\\"\\\")\\n os.remove(path)\",\n \"def delete(self):\\n request_data = request.get_json(force=True)\\n current_path = self.get_current_path()\\n file_name = request_data.get('file_name')\\n\\n if not file_name:\\n abort(400, message=\\\"File name must not be empty!\\\")\\n\\n full_path = os.path.join(current_path, file_name)\\n\\n if not os.path.exists(full_path):\\n abort(400, message=\\\"File was not found in current path!\\\")\\n\\n if not os.path.isfile(full_path):\\n abort(400, message=\\\"File name is not a file!\\\")\\n\\n if not self.is_allowed(full_path):\\n abort(403, message=\\\"You are not allowed to this path\\\")\\n\\n os.remove(full_path)\\n\\n return {\\\"message\\\": \\\"OK\\\"}\",\n \"def delete_upload(arn=None):\\n pass\",\n \"def delete_file(file: str) -> None:\\n\\tuux.show_info(\\\"Deleting \\\" + file)\\n\\n\\tif not os.path.exists(file):\\n\\t\\t# Files does not exist\\n\\t\\treturn\\n\\n\\tos.remove(file)\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete_file(self, file_id):\\n self.drive_service.files().delete(fileId=file_id).execute()\\n return file_id\",\n \"def delete(self, *args, **kwargs):\\n self.file.storage.delete(self.file.name)\\n super().delete(*args, **kwargs)\",\n \"def delFile(self, file_name):\\n ret = self.rest.delete(self.ngx_server, self.getUrl() + '/' + file_name, {}, [200, 404])\\n if ret == False:\\n self.logger.error('delete file:%s from tfs failed.' % file_name)\\n raise Exception, 'delete file:%s from tfs failed.' % file_name\\n self.logger.info('Delete Tfs file: %s' % file_name)\\n return True\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def Delete_File(self,txn,filename):\\n opid = self.new_opid()\\n xaction = DeleteFile_Operation(os.path.join(self.home,filename),opid)\\n self._add_operation(txn,xaction)\",\n \"def delete_file(filename, sudo=True):\\n LOG.info(\\\"Deleting file {}\\\".format(filename))\\n cmd = \\\"rm {}\\\".format(filename)\\n _exec_cmd(cmd=cmd, sudo=sudo, fail_ok=False)\",\n \"def delete_blob(blob_name):\\n # bucket_name = \\\"your-bucket-name\\\"\\n # blob_name = \\\"your-object-name\\\"\\n storage_client = storage.Client()\\n bucket = storage_client.get_bucket(bucket_name)\\n blob = bucket.blob(blob_name)\\n blob.delete()\\n print('Blob {} deleted.'.format(blob_name))\",\n \"def delete_asset(location, filename):\\r\\n try:\\r\\n content = Transcript.get_asset(location, filename)\\r\\n contentstore().delete(content.get_id())\\r\\n log.info(\\\"Transcript asset %s was removed from store.\\\", filename)\\r\\n except NotFoundError:\\r\\n pass\\r\\n return StaticContent.compute_location(location.course_key, filename)\",\n \"def delete_file(self, filename):\\n if not filename in self.files:\\n raise IOError('File %s Not Found' % filename)\\n\\n for nodename in self.files[filename]:\\n node = self.datanodes[nodename]\\n node.delete_file(filename)\\n del self.files[filename]\\n logging.info('file %s deleted' % filename)\",\n \"def delete(self, filename):\\n try:\\n self.storage.delete(filename)\\n return {\\n 'filename': filename,\\n 'message': 'The file was deleted with success'\\n }\\n except FileNotFoundError:\\n abort(404, message='File %s does not exist' % filename)\\n except BaseException:\\n abort(500, message='Failed to delete the file ' + filename)\\n LOGGER.error('A generic exception has occurred.', exc_info=True)\",\n \"def purge_and_delete_bucket(\\n bucket_name: str, region: str = \\\"us-east-1\\\", session: Optional[boto3.Session] = None\\n) -> None:\\n purge_bucket(bucket_name, region, session)\\n delete_bucket(bucket_name, region, session)\",\n \"def purge_bucket(\\n bucket_name: str, region: str = \\\"us-east-1\\\", session: Optional[boto3.Session] = None\\n) -> None:\\n if does_bucket_exist(bucket_name, region, session):\\n s3_resource = _get_resource(session, region)\\n bucket = s3_resource.Bucket(bucket_name)\\n bucket.object_versions.delete()\\n else:\\n LOGGER.warning('bucket \\\"%s\\\" does not exist in region \\\"%s\\\"', bucket_name, region)\",\n \"def rm_file(filename):\\n try:\\n os.unlink(filename)\\n except FileNotFoundError:\\n pass\",\n \"def file_delete(self, path):\\n params = {'root': self.session.root, 'path': format_path(path)}\\n\\n url, params, headers = self.request(\\\"/fileops/delete\\\", params)\\n\\n return self.rest_client.POST(url, params, headers)\",\n \"def delete(self):\\n\\t\\t#self.log.info(\\\"Deleting file {}\\\".format(self._filepath))\\n\\t\\tos.remove(self._filepath)\",\n \"def delete_file(self, path):\\n raise HTTPError(\\n 501,\\n \\\"Narrative deletion not implemented here. Deletion is handled elsewhere.\\\",\\n )\",\n \"def rm_file(file_):\\n Path(file_).unlink(missing_ok=True)\",\n \"def replay_delete(sender, instance, **kwargs):\\n pass\\n # Temporarily disabled\\n\\n #print(\\\"deleting file from S3\\\")\\n # False so FileField doesn't save the model\\n #instance.file.delete(False)\",\n \"def remove( filename ):\\n try:\\n os.remove( filename )\\n except OSError as e:\\n if e.errno != errno.ENOENT:\\n raise e\",\n \"def delete_key(self, bucket_name, key_name):\\n bucket = self.s3_.get_bucket(bucket_name)\\n key = bucket.get_key(key_name)\\n return key.delete()\",\n \"def delete(self):\\n if os.path.exists(self.file_path):\\n os.remove(self.file_path)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.86315507","0.82782817","0.8190081","0.7701372","0.7638301","0.76289713","0.7577905","0.7507077","0.74693567","0.74376506","0.73432124","0.73346096","0.7309587","0.72627354","0.7256304","0.71695846","0.71298283","0.7094936","0.7075884","0.70637834","0.7034662","0.70331335","0.6980523","0.69519717","0.68304837","0.67709154","0.67611253","0.67352027","0.6707004","0.6675132","0.6652627","0.6639785","0.663752","0.6607517","0.65887237","0.6577638","0.65775126","0.65559053","0.6541544","0.6539658","0.6528289","0.6511694","0.6511292","0.6509068","0.6504866","0.6504205","0.64773536","0.64772415","0.6432885","0.64197177","0.6416346","0.6390849","0.6368072","0.6352856","0.63242644","0.6310746","0.6308451","0.63025296","0.6297451","0.62954235","0.62896585","0.6287732","0.6286358","0.6285322","0.62772375","0.6273801","0.6262295","0.6259102","0.6249192","0.6242937","0.6239625","0.6223145","0.62196624","0.62193805","0.62186253","0.6210173","0.62066114","0.6198396","0.6190772","0.61794716","0.6177969","0.61673516","0.61644","0.61644","0.61492014","0.6139591","0.6131186","0.61083496","0.61080605","0.610188","0.6085994","0.6078487","0.60759145","0.6073661","0.6071538","0.60458493","0.6045748","0.60418487","0.6026326","0.6024113","0.6003756"],"string":"[\n \"0.86315507\",\n \"0.82782817\",\n \"0.8190081\",\n \"0.7701372\",\n \"0.7638301\",\n \"0.76289713\",\n \"0.7577905\",\n \"0.7507077\",\n \"0.74693567\",\n \"0.74376506\",\n \"0.73432124\",\n \"0.73346096\",\n \"0.7309587\",\n \"0.72627354\",\n \"0.7256304\",\n \"0.71695846\",\n \"0.71298283\",\n \"0.7094936\",\n \"0.7075884\",\n \"0.70637834\",\n \"0.7034662\",\n \"0.70331335\",\n \"0.6980523\",\n \"0.69519717\",\n \"0.68304837\",\n \"0.67709154\",\n \"0.67611253\",\n \"0.67352027\",\n \"0.6707004\",\n \"0.6675132\",\n \"0.6652627\",\n \"0.6639785\",\n \"0.663752\",\n \"0.6607517\",\n \"0.65887237\",\n \"0.6577638\",\n \"0.65775126\",\n \"0.65559053\",\n \"0.6541544\",\n \"0.6539658\",\n \"0.6528289\",\n \"0.6511694\",\n \"0.6511292\",\n \"0.6509068\",\n \"0.6504866\",\n \"0.6504205\",\n \"0.64773536\",\n \"0.64772415\",\n \"0.6432885\",\n \"0.64197177\",\n \"0.6416346\",\n \"0.6390849\",\n \"0.6368072\",\n \"0.6352856\",\n \"0.63242644\",\n \"0.6310746\",\n \"0.6308451\",\n \"0.63025296\",\n \"0.6297451\",\n \"0.62954235\",\n \"0.62896585\",\n \"0.6287732\",\n \"0.6286358\",\n \"0.6285322\",\n \"0.62772375\",\n \"0.6273801\",\n \"0.6262295\",\n \"0.6259102\",\n \"0.6249192\",\n \"0.6242937\",\n \"0.6239625\",\n \"0.6223145\",\n \"0.62196624\",\n \"0.62193805\",\n \"0.62186253\",\n \"0.6210173\",\n \"0.62066114\",\n \"0.6198396\",\n \"0.6190772\",\n \"0.61794716\",\n \"0.6177969\",\n \"0.61673516\",\n \"0.61644\",\n \"0.61644\",\n \"0.61492014\",\n \"0.6139591\",\n \"0.6131186\",\n \"0.61083496\",\n \"0.61080605\",\n \"0.610188\",\n \"0.6085994\",\n \"0.6078487\",\n \"0.60759145\",\n \"0.6073661\",\n \"0.6071538\",\n \"0.60458493\",\n \"0.6045748\",\n \"0.60418487\",\n \"0.6026326\",\n \"0.6024113\",\n \"0.6003756\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":186,"numItemsPerPage":100,"numTotalItems":95772,"offset":18600,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4NjI2NTE2NiwianRpIjoiNzViY2Q5N2ItY2UxMi00NjM3LTg0YzgtNDM2MDZmMWEzMjcxIiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3ODYyNjg3NjYsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.uazo8kevAAaIPSLonUQQzt3-_vJv4Q_ScsaDaePRVUXRNy_TgLiMC4xkPG5QTbQipWmyH_Fq1zxNh-ook31XCQ","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 |
|---|---|---|---|---|---|---|
Uses git binary to get the information on the specified directory. | def get_git_status(self, more=False):
cmd_args = u'{} -c color.ui=always -c color.status=always status --branch '.format(self.git_cmd)
if not more:
cmd_args += '--short'
with ChDir(self.directory):
logger.debug('Running status command: {}'.format(cmd_args))
s... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def info(directory):\n git_dir = os.path.join(directory, '.git')\n if not os.path.exists(git_dir):\n raise IOError(errno.ENOENT, '.git not found', directory)\n\n if os.path.isfile(git_dir):\n # submodules\n with open(git_dir, 'r') as f:\n git_ref = f.read().strip()\n\n ... | [
"0.77134234",
"0.74907887",
"0.7367796",
"0.70493096",
"0.6932514",
"0.68896735",
"0.67703146",
"0.6731434",
"0.6713529",
"0.66906565",
"0.6634889",
"0.6587841",
"0.6581772",
"0.6567745",
"0.65648717",
"0.65633637",
"0.6461472",
"0.6386494",
"0.6333181",
"0.6306241",
"0.62618... | 0.0 | -1 |
Finding the commits that are not pushed to the origin remote | def get_queued_commits(self, author_filter=None):
with ChDir(self.directory):
logger.debug('Verify Dir Has an upstream branch: {}'.format(self.directory))
run_command('{} rev-parse --quiet @{{u}}..'.format(self.git_cmd), subprocess.PIPE)
cmd_args = "{} rev-list".format(self.g... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def origin(self):\n for item in os.popen('git remote -v'):\n split_item = item.strip().split()\n if split_item[0] == 'origin' and split_item[-1] == '(push)':\n return split_item[1]",
"async def fetch_commits(self):\n for repo in self.config['repos'].split(','):\... | [
"0.66369563",
"0.6598706",
"0.6432641",
"0.6345757",
"0.63035303",
"0.62276125",
"0.6117992",
"0.6060729",
"0.6056284",
"0.60144085",
"0.59753895",
"0.59223807",
"0.5909121",
"0.5904455",
"0.5857569",
"0.58364576",
"0.5828773",
"0.5821198",
"0.58123845",
"0.5805069",
"0.57896... | 0.5802054 | 20 |
Return a list of parts of speech. | def read_text(text_split):
parts_of_speech = [] # instantiate empty list
for word in text_split:
# check if the last index is the other bracket or if it's punctuation
# this prints the last letter of the prompt correctly
if word[0] == "[" and word[-1] == "]":
parts_of_speec... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def part_of_speech(text):\n temp = nltk.pos_tag(text)\n return [word for word, tag in temp if \n (tag == \"NN\") or \n (tag == \"NNS\") or\n (tag == \"NNP\") or \n (tag == \"NNPS\")]",
"def get_part_of_speech(tokens):\n\n return [e for e in nltk.chunk.ne_chunk... | [
"0.7134673",
"0.6987765",
"0.6834255",
"0.6656446",
"0.64809626",
"0.64693034",
"0.6468814",
"0.62929255",
"0.6226717",
"0.612575",
"0.60079587",
"0.59267974",
"0.5925256",
"0.5793268",
"0.5782666",
"0.57525915",
"0.57333004",
"0.56673974",
"0.5663541",
"0.5642697",
"0.564269... | 0.5832706 | 13 |
Return a list of input words from user. | def get_input(read_text):
user_input_list = [] # instantiate empty list
# call the read_text function, and make a variable with its output list
parts_of_speech = read_text(text_split)
for word in parts_of_speech:
# for each part of speech, ask user for a word of this type
input_word ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_user_words() -> List[str]:\r\n user_words = input()\r\n user_words = user_words.split()\r\n return user_words",
"def get_user_words():\n user_words = []\n while True:\n try:\n user_input = input()\n user_words.append(user_input)\n if user_input == \"... | [
"0.87324315",
"0.7559497",
"0.7193994",
"0.71016663",
"0.67820585",
"0.67741716",
"0.66742367",
"0.6617233",
"0.6617233",
"0.66086435",
"0.64847183",
"0.64559364",
"0.64380866",
"0.6425917",
"0.64247036",
"0.63515234",
"0.633357",
"0.6247313",
"0.62370324",
"0.62076485",
"0.6... | 0.7514219 | 2 |
Return a final mad lib with parts of speech replaced by user input. | def make_madlib(get_input):
# call the get_input function and make a variable from its output list
replaced_list = get_input(read_text)
index = 0
# we want both the index and the word that we want to replace in text_split
for (i, word) in enumerate(text_split):
# find the parts of speech, ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def mad_libs():\n\n # The parts of speech we are intrested in removing and replacing\n to_replace = [\"JJ\", \"JJR\", \"JJS\", \"NN\", \"NNS\", \"RB\", \"RBR\", \"RBS\"]\n done = False\n while not done:\n print(\"You're in the madlibs menu\")\n print(\"Here are your options:\")\n p... | [
"0.63713914",
"0.6036372",
"0.57943606",
"0.5604704",
"0.55267847",
"0.549841",
"0.54870534",
"0.5482093",
"0.5372294",
"0.5347282",
"0.5323033",
"0.53198546",
"0.52982825",
"0.5293129",
"0.52888864",
"0.52587306",
"0.5246758",
"0.5227932",
"0.52277255",
"0.5220096",
"0.52196... | 0.7572062 | 0 |
Given the necessary information about relationships, generates SQL database useable by our open world implementation | def generateSQL(unary, binary, names, output_file, unary_dist=None, binary_dist=None):
# Make sure we didn't mess anything up
assert (len(unary) + len(binary)) == len(names)
sql = ''
# generate drop statements
for name in names:
sql += "drop table if exists %s;\n" % name
# Create unar... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _generate_sql_parts(self, node,i=0,colNames=None,sql=None):\n\t\treferencesPersonFact = False\n\t\tif i == 0:\n\t\t\tsql=[]\n\t\t\tcolNames=[]\n\t\t\t# print('\\nSELECT *\\nFROM {}'.format(node))\n\t\tfor edge in self.DiG.out_edges(node):\n\t\t\t# print('\\tedge: {}->{} {}'.format(*edge,self.DiG.get_edge_data(... | [
"0.6268195",
"0.62161386",
"0.6120298",
"0.61085665",
"0.60339504",
"0.59221375",
"0.59038436",
"0.5902835",
"0.58226085",
"0.5819849",
"0.58148515",
"0.580935",
"0.5799963",
"0.57978106",
"0.57941604",
"0.5790598",
"0.5786547",
"0.57412314",
"0.5732473",
"0.5721076",
"0.5713... | 0.55353254 | 39 |
Generates a unary relation from our graph by first sampling a value from dist (must return a number between 1 and N, where N is the number of nodes in the graph), and then sampling that many nodes from the graph with replacement | def generateUnaryRel(graph, dist=None):
if dist is None:
dist = lambda: random.randint(1, len(graph.nodes()))
count = dist()
return random.sample(graph.nodes(), count) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def generate_regular_graph(variable_names, dist_func, num_neigh=10, **kwargs):\n shuffle(variable_names)\n num_vars = len(variable_names)\n num_neigh = min(num_neigh, num_vars-1)\n graphs = nx.random_graphs.random_regular_graph(num_neigh, num_vars)\n edges = np.array(graphs.edges())\n edges.sort(... | [
"0.6225221",
"0.6075832",
"0.57536215",
"0.5595702",
"0.55751705",
"0.5566251",
"0.5530265",
"0.54891706",
"0.5453418",
"0.5447563",
"0.5430584",
"0.5427841",
"0.54138327",
"0.5403605",
"0.54019284",
"0.53796065",
"0.5331073",
"0.5319422",
"0.53087515",
"0.5298584",
"0.529813... | 0.8003123 | 0 |
TF or Term Frequency is the ratio of number of times the word appears in a document compared to the total number of words in that document. | def tf(vector):
for line in vector:
line[0] = np.true_divide(line[0], np.sum(line[0]))
return vector | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def tf(word, document):\n return freq(word,document) / wordCount(document)",
"def get_tf(term, document):\n\n term_list = [term.lower() for term in document.split()]\n num_of_words_in_doc = len(document.split())\n term_count_in_doc = term_list.count(term)\n\n return term_count_in_doc / num_of_words_in_doc",... | [
"0.8723744",
"0.84126645",
"0.7926919",
"0.78912336",
"0.7862143",
"0.7781198",
"0.77429914",
"0.7682379",
"0.7656306",
"0.76286805",
"0.76163816",
"0.7463605",
"0.7445913",
"0.7415905",
"0.7412183",
"0.73883826",
"0.7378769",
"0.7357459",
"0.73337525",
"0.7285356",
"0.728293... | 0.0 | -1 |
Returns the theoretical probability that x_n will be between the values a and b. | def get_confidence_interval(self,a,b):
k_vals,prob_vals = self.tuple_of_probabilities
working_indices = [i for i,v in enumerate(k_vals) if (v >= a and v<= b)]
working_prob_vals = [prob_vals[i] for i in working_indices]
return sum(working_prob_vals) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def probability(s, a, b):\r\n return s.cdf(b) - s.cdf(a)",
"def theoretical_distribution(x):\n a = 0\n b = 1\n if x < a:\n return 0\n elif x > b:\n return 1\n else:\n return float(x - a) / (b - a)",
"def interval_prob(x1, x2, a, b):\n with mp.extradps(5):\n ... | [
"0.7519538",
"0.7352858",
"0.7060859",
"0.68735635",
"0.68382454",
"0.67430097",
"0.6606817",
"0.6601517",
"0.65820867",
"0.6561573",
"0.6522591",
"0.64544326",
"0.6453946",
"0.6387221",
"0.6384941",
"0.63692117",
"0.63621324",
"0.63278866",
"0.632063",
"0.6309425",
"0.630878... | 0.633067 | 17 |
Plots the theoretical probability distribution for the random walk. | def plot_distribution(self,show=True):
k_vals,prob_vals = self.tuple_of_probabilities
plt.figure("Probability distribution of Random Walk, theoretical")
plt.scatter(k_vals,prob_vals,s=4)
plt.xlim((-self.n-1,self.n+1))
plt.xlabel("x\u2099 - Position after n jumps")
plt.ylabel("Probability")
plt.supti... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def geneticAlgorithmPlot(population, popSize, fittestSize, mutationRate, generations):\n pop = GA.initialPopulation(popSize, population)\n progress = []\n progress.append(1 / GA.rankRoutes(pop)[0][1])\n \n for i in range(0, generations):\n pop = GA.nextGeneration(pop, fittestSize, mutationRat... | [
"0.6606563",
"0.6557504",
"0.6498785",
"0.641404",
"0.640985",
"0.6358938",
"0.62723446",
"0.6208371",
"0.6195964",
"0.61664635",
"0.6133573",
"0.60698766",
"0.6052493",
"0.6051445",
"0.60448354",
"0.6023211",
"0.5997611",
"0.59773487",
"0.59731567",
"0.5966449",
"0.59633803"... | 0.83731085 | 0 |
Runs a Monte Carlo simulation of the random walk for a specified number of trials. It then plots the results as a frequency distribution. Mean and variance values of the Monte Carlo simulation can be retrieved by calling mc.mean and mc.variance, respectively. Method parameters | def run_monte_carlo(self,number_of_trials=2000,plot=True,histogram=False,show=True,overlay=False):
trial_data = []
for _ in range(number_of_trials):
steps = self._random_walk_simulation()
trial_data.append( sum(steps) + self.x_initial )
x_n, counts = np.unique(trial_data, return_counts=True)
self.mc... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def simulate(self, number_of_simulations):\n self.number_of_simulations = number_of_simulations\n\n for iteration_num in range(0, number_of_simulations, 1):\n self.add_grain(0)\n self.check_pile(iteration_num)\n self.mass_when_iteration.append(self.mass_count - self.m... | [
"0.6701685",
"0.6585736",
"0.6476485",
"0.6432378",
"0.6383453",
"0.631216",
"0.625372",
"0.62430805",
"0.6218561",
"0.62165946",
"0.62092024",
"0.6172401",
"0.61608857",
"0.6157016",
"0.6096449",
"0.6096449",
"0.609388",
"0.60926163",
"0.60920125",
"0.60714257",
"0.60618424"... | 0.7543116 | 0 |
This method produces an animated simulation of a 1D random walk. | def random_walk_draw(self,num_plots,animated=False,show=True):
t_x_arrays = []
t_max = self.n
for _ in range(num_plots):
current_x = self.x_initial
x_array = [current_x]
t_array = range(t_max + 1)
steps = self._random_walk_simulation()
for s in steps:
current_x += s
x_array.append(curren... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def random_walk(turtle, distance, steps):\n turtle.color(randcolor(), randcolor())\n for step in range(0,steps):\n random_move(turtle, distance)\n gohome(turtle)",
"def animate(agent, steps, initialize=None):\n grid, r, c = random_world()\n image = plt.imshow(grid, cmap=cmap, norm=norm)\n if initi... | [
"0.6422432",
"0.6396238",
"0.636496",
"0.63317525",
"0.62908727",
"0.6250839",
"0.6221125",
"0.6113204",
"0.61060905",
"0.60530597",
"0.6004688",
"0.59976655",
"0.5970178",
"0.5949534",
"0.5910587",
"0.5881018",
"0.58617455",
"0.58095884",
"0.5787556",
"0.5768405",
"0.5759622... | 0.7161393 | 0 |
Returns the theoretical average distance from x_initial. | def _calculate_mean_distance_theoretical(self):
x_mean_distance = 0
x_vals,prob_vals = self.tuple_of_probabilities
for i in range(len(x_vals)):
x_val, prob = x_vals[i], prob_vals[i]
x_distance = abs(x_val - self.x_initial)
x_weighted = x_distance * prob
x_mean_distance += x_weighted
return x_mean_di... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def avgX(self):\n return np.mean(self.getx())",
"def _avg_sample(self):\n samples = [0] * self.num_samples\n for i in range(self.num_samples):\n samples[i] = self.sensor.measure_distance()\n time.sleep(self.sample_delay)\n if self.drop_extremes:\n samp... | [
"0.65964574",
"0.6528893",
"0.65209246",
"0.63227236",
"0.6232084",
"0.62193644",
"0.61996084",
"0.61704206",
"0.6161522",
"0.61305714",
"0.61239797",
"0.6103318",
"0.6088901",
"0.5991759",
"0.59127855",
"0.59127855",
"0.59127855",
"0.59074956",
"0.58808935",
"0.58742917",
"0... | 0.80323946 | 0 |
Calculates the probability that x_n = k delta_x. This method uses the values of n and p in its calculations. | def _calculate_probability(self,k):
if abs(k * self.delta_x) > (3 * np.sqrt(self.variance)):
return 0.0
binom_coeff = special.binom(self.n,(self.n + k)/2)
b_value = binom_coeff * ((self.p) ** ((self.n + k)/2)) * ((1-self.p) ** ((self.n - k)/2))
return b_value | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def probability(n, k, p):\n prob = 0\n power = expotentation_by_squaring((1-p), n)\n count_mult = math.log(n, 2)\n p_fraction = p/(1-p)\n count_mult += 1\n for i in range(0, k+1):\n element = newton(n, i)*power\n prob += element\n power *= p_fraction\n count_mult += 2\... | [
"0.7945974",
"0.7007212",
"0.6929289",
"0.6782928",
"0.67037106",
"0.65899515",
"0.6540211",
"0.6514137",
"0.6489262",
"0.63936114",
"0.636305",
"0.6362294",
"0.62638086",
"0.6237782",
"0.6176205",
"0.61600775",
"0.613456",
"0.613456",
"0.6123985",
"0.6123276",
"0.61229426",
... | 0.7519626 | 1 |
Gets a tuple of the form (kvalues,probabilities) in the range [n,n]. | def _get_tuple_of_probabilities(self):
k_array = np.arange(-self.n,self.n+1,2)
probability_array = []
for k in k_array:
probability_array.append(self._calculate_probability(k))
return (k_array,probability_array) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def probability(n, k, p):\n prob = 0\n power = expotentation_by_squaring((1-p), n)\n count_mult = math.log(n, 2)\n p_fraction = p/(1-p)\n count_mult += 1\n for i in range(0, k+1):\n element = newton(n, i)*power\n prob += element\n power *= p_fraction\n count_mult += 2\... | [
"0.6795796",
"0.6431642",
"0.6371308",
"0.63636243",
"0.62259746",
"0.6038752",
"0.59965384",
"0.5926337",
"0.59128183",
"0.5910087",
"0.5896185",
"0.58841133",
"0.584079",
"0.58231497",
"0.5818503",
"0.58054143",
"0.5799345",
"0.5798068",
"0.5791992",
"0.5765857",
"0.5764065... | 0.80612916 | 0 |
Fetches an URL with urlopen retries until success (to deal with ratelimits) | def request_until_succeed(url):
req = Request(url)
success = False
while success is False:
try:
response = urlopen(req)
if response.getcode() == 200:
success = True
except Exception as e:
print(e)
if e.file:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fetch_url(url, bytes=10000, retry=3):\n retry = abs(retry or 1)\n for x in range(retry - 1):\n try: # retry silently several time\n page = urllib.urlopen(url)\n return page.read(10000)\n except:\n pass\n # try one last time and fail loudly if needed\n ... | [
"0.7759101",
"0.74884486",
"0.73910856",
"0.7351973",
"0.7349828",
"0.72955513",
"0.7255797",
"0.7164698",
"0.7157121",
"0.7125055",
"0.70978093",
"0.70485735",
"0.696427",
"0.6924929",
"0.68756586",
"0.67357767",
"0.6720894",
"0.6692962",
"0.6664536",
"0.66399014",
"0.663945... | 0.7486804 | 2 |
tries to decode unicode to deal with python unicode strangeness | def unicode_decode(text):
try:
return text.encode('utf-8').decode()
except UnicodeDecodeError:
return text.encode('utf-8') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def unicode_decode(text):\n\n try:\n return text.encode('utf-8').decode()\n except UnicodeDecodeError:\n return text.encode('utf-8')",
"def escapeDecode(s: unicode) -> unicode:\n ...",
"def TryDecode(text):\n try:\n return unicode(text, \"utf8\")\n except (TypeError, UnicodeDeco... | [
"0.7843637",
"0.7709333",
"0.768689",
"0.74438226",
"0.73078275",
"0.7273341",
"0.72526544",
"0.71388495",
"0.70961183",
"0.708849",
"0.7074156",
"0.7049334",
"0.7018959",
"0.6978158",
"0.6967038",
"0.69328606",
"0.6872787",
"0.68676764",
"0.6857858",
"0.6856613",
"0.6843041"... | 0.79577845 | 0 |
Reads lines in file_id and fetches relevant facebook comments, using the facebook graph api, saving the result to result_file | def scrapeFacebookComments(file_id, result_file, access_token):
with open(file_id, 'r', encoding='utf8') as f, \
open(result_file, 'w', encoding='utf8', newline='') as o:
input_file = csv.DictReader(f)
output_file = csv.DictWriter(o,
fieldnames=[
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_comments(video_id, CLIENT_SECRETS_FILE):",
"def process_reddit_comment_file(f,\n output_folder):\n ## Output File\n if output_folder is not None:\n fname = os.path.basename(f).replace(\"comments.json\",\"processed.comments.json\")\n if not fname.endswith... | [
"0.6400023",
"0.62088317",
"0.6198404",
"0.5723124",
"0.54117316",
"0.5385133",
"0.53159404",
"0.524866",
"0.51766294",
"0.5171449",
"0.5160384",
"0.5138199",
"0.51008713",
"0.50976366",
"0.50750273",
"0.5037629",
"0.50367475",
"0.502809",
"0.5021747",
"0.50176424",
"0.501086... | 0.7850107 | 0 |
Generate an instance of the HPE OneView client. Generates an instance of the HPE OneView client using the hpOneView lib. | def get_hponeview_client():
manager_url = prepare_manager_url(CONF.oneview.manager_url)
config = {
"ip": manager_url,
"credentials": {
"userName": CONF.oneview.username,
"password": CONF.oneview.password
}
}
return hponeview_client.OneViewClient(config) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gen_heat_client(self):\n\n print \"\\t* Generating heat client\"\n # request a new auth token from keystone\n keystone = ksclient.Client(auth_url=self.auth_url,\n username=self.username,\n password=self.password,\n ... | [
"0.62012696",
"0.59542215",
"0.5604468",
"0.53502053",
"0.5333491",
"0.52706295",
"0.5257632",
"0.5231252",
"0.5147483",
"0.5104047",
"0.50083214",
"0.5004166",
"0.49704948",
"0.49391007",
"0.49293235",
"0.49172926",
"0.49049976",
"0.48713294",
"0.48525918",
"0.48477373",
"0.... | 0.78882736 | 0 |
Generate an instance of the iLORest library client. | def get_ilorest_client(server_hardware):
oneview_client = get_hponeview_client()
remote_console = oneview_client.server_hardware.get_remote_console_url(
server_hardware
)
host_ip, ilo_token = _get_ilo_access(remote_console)
base_url = "https://%s:%s" % (host_ip, ILOREST_BASE_PORT)
return... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_client(self) -> None:\n self._client = discovery.build('ml', 'v1')",
"def make_client(instance):\r\n neutron_client = utils.get_client_class(\r\n API_NAME,\r\n instance._api_version[API_NAME],\r\n API_VERSIONS,\r\n )\r\n instance.initialize()\r\n url = instance._url... | [
"0.6768092",
"0.6565448",
"0.65639997",
"0.64433366",
"0.6390451",
"0.63213104",
"0.62952775",
"0.62724704",
"0.62388724",
"0.62262815",
"0.6198003",
"0.61788833",
"0.61659384",
"0.6135776",
"0.6057306",
"0.6035382",
"0.5959817",
"0.59236896",
"0.58714986",
"0.58455396",
"0.5... | 0.6267768 | 8 |
Get the needed information to access ilo. Get the host_ip and a token of an iLO remote console instance which can be used to perform operations on that controller. | def _get_ilo_access(remote_console):
url = remote_console.get('remoteConsoleUrl')
url_parse = parse.urlparse(url)
host_ip = parse.parse_qs(url_parse.netloc).get('addr')[0]
token = parse.parse_qs(url_parse.netloc).get('sessionkey')[0]
return host_ip, token | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_details(module):\n\n login_list = [module.params['login'], os.getenv('DCI_LOGIN')]\n login = next((item for item in login_list if item is not None), None)\n\n password_list = [module.params['password'], os.getenv('DCI_PASSWORD')]\n password = next((item for item in password_list if item is not ... | [
"0.57575613",
"0.57030374",
"0.5658261",
"0.561578",
"0.55102676",
"0.5456767",
"0.54272753",
"0.54270345",
"0.53561795",
"0.53542095",
"0.5327382",
"0.5325279",
"0.5313275",
"0.5305687",
"0.528909",
"0.52887946",
"0.52811927",
"0.52711695",
"0.52711695",
"0.526446",
"0.52539... | 0.808896 | 0 |
Verify if fields and namespaces of a node are valid. Verifies if the 'driver_info' field and the 'properties/capabilities' namespace exist and are not empty. | def verify_node_info(node):
capabilities_dict = utils.capabilities_to_dict(
node.properties.get('capabilities', '')
)
driver_info = node.driver_info
_verify_node_info('properties/capabilities', capabilities_dict,
REQUIRED_ON_PROPERTIES)
_verify_node_info('driver_info'... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _verify_node_info(node_namespace, node_info_dict, info_required):\n missing_keys = set(info_required) - set(node_info_dict)\n\n if missing_keys:\n raise exception.MissingParameterValue(\n _(\"Missing the keys for the following OneView data in node's \"\n \"%(namespace)s: %(... | [
"0.62888443",
"0.5970122",
"0.5792318",
"0.5749915",
"0.57480246",
"0.5558528",
"0.555058",
"0.54527915",
"0.54470193",
"0.54410964",
"0.54384977",
"0.5430039",
"0.54069996",
"0.53724563",
"0.53724563",
"0.5347799",
"0.53438234",
"0.53368545",
"0.53343976",
"0.5322387",
"0.53... | 0.7963399 | 0 |
Get OneView information from the node. | def get_oneview_info(node):
try:
capabilities_dict = utils.capabilities_to_dict(
node.properties.get('capabilities', '')
)
except exception.InvalidParameterValue as e:
raise exception.OneViewInvalidNodeParameter(node_uuid=node.uuid,
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def node_show(self, node):\n if node.instance_uuid:\n n = self.ironic_client.node.get_by_instance_uuid(\n node.instance_uuid)\n else:\n n = self.ironic_client.node.get(node.uuid)\n return n",
"def get_node_details(self, node):\n node_details = self... | [
"0.65129185",
"0.60302633",
"0.60019517",
"0.59819186",
"0.5964509",
"0.5886509",
"0.57704425",
"0.5651187",
"0.5634503",
"0.5597397",
"0.5592938",
"0.55923563",
"0.5571141",
"0.55683917",
"0.55459785",
"0.55267394",
"0.55267394",
"0.54931307",
"0.54928416",
"0.5488017",
"0.5... | 0.797151 | 0 |
Validate if the node configuration is consistent with OneView. This method calls hpOneView functions to validate if the node configuration is consistent with the OneView resources it represents, including serverHardwareUri, serverHardwareTypeUri, serverGroupUri serverProfileTemplateUri, enclosureGroupUri and node ports... | def validate_oneview_resources_compatibility(task):
ports = task.ports
oneview_client = get_hponeview_client()
oneview_info = get_oneview_info(task.node)
_validate_node_server_profile_template(oneview_client, oneview_info)
_validate_node_server_hardware_type(oneview_client, oneview_info)
_valid... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate_node_server_hardware_type(oneview_client, oneview_info):\n node_server_hardware_type_uri = oneview_info['server_hardware_type_uri']\n server_hardware = oneview_client.server_hardware.get(\n oneview_info['server_hardware_uri'])\n server_hardware_sht_uri = server_hardware.get('serverHar... | [
"0.64884377",
"0.626606",
"0.6191199",
"0.61666006",
"0.56702393",
"0.5576689",
"0.5527156",
"0.5473364",
"0.53926665",
"0.53686446",
"0.5361794",
"0.53390706",
"0.53390706",
"0.5296695",
"0.5285889",
"0.521166",
"0.52000636",
"0.5153872",
"0.5126247",
"0.5111564",
"0.5093537... | 0.70742106 | 0 |
Verify if info_required is present in node_namespace. | def _verify_node_info(node_namespace, node_info_dict, info_required):
missing_keys = set(info_required) - set(node_info_dict)
if missing_keys:
raise exception.MissingParameterValue(
_("Missing the keys for the following OneView data in node's "
"%(namespace)s: %(missing_keys)s... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def verify_namespace_attrs(self, node):\n for cls in node.classes:\n for var in cls.variables:\n self.check_var_attrs(cls, var)\n for func in cls.functions:\n self.check_fcn_attrs(func)\n\n for func in node.functions:\n self.check_fcn_att... | [
"0.58488464",
"0.58250725",
"0.5789654",
"0.5767724",
"0.576109",
"0.5756803",
"0.57413286",
"0.56746936",
"0.55888873",
"0.55871767",
"0.55615854",
"0.55192447",
"0.54995584",
"0.5496556",
"0.54898274",
"0.5455332",
"0.54527485",
"0.54376256",
"0.5391571",
"0.5388521",
"0.53... | 0.7387368 | 0 |
Checks if the node's Server Hardware has a Server Profile associated. Decorator to execute before the function execution to check if the Server Profile is applied to the Server Hardware. | def node_has_server_profile(func):
def inner(self, *args, **kwargs):
task = args[0]
has_server_profile(task)
return func(self, *args, **kwargs)
return inner | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def has_server_profile(task):\n oneview_client = get_hponeview_client()\n try:\n profile = task.node.driver_info.get('applied_server_profile_uri')\n oneview_client.server_profiles.get(profile)\n except client_exception.HPOneViewException as exc:\n LOG.error(\n \"Failed to g... | [
"0.64625174",
"0.6329892",
"0.6047561",
"0.59693646",
"0.5888459",
"0.5794492",
"0.57879764",
"0.5742285",
"0.57172704",
"0.55384105",
"0.5498647",
"0.54914945",
"0.5441861",
"0.5415404",
"0.5377407",
"0.5358442",
"0.53436404",
"0.5326051",
"0.5309744",
"0.530064",
"0.5288293... | 0.6996314 | 0 |
Checks if the node's Server Hardware has a Server Profile associated. Function to check if the Server Profile is applied to the Server Hardware. | def has_server_profile(task):
oneview_client = get_hponeview_client()
try:
profile = task.node.driver_info.get('applied_server_profile_uri')
oneview_client.server_profiles.get(profile)
except client_exception.HPOneViewException as exc:
LOG.error(
"Failed to get server pro... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_simple_server_profile_by_server_hardware(profile_name, server_name, return_true_if_exists=False):\n logger.info(\"--> creating a server profile with name '%s' ...\" % profile_name)\n # checking if the profile is already existing\n FusionUIBase.navigate_to_section(SectionType.SERVER_PROFILES, ti... | [
"0.6275056",
"0.61501735",
"0.61437684",
"0.6112742",
"0.6090006",
"0.60501087",
"0.60271287",
"0.599908",
"0.59340584",
"0.5925858",
"0.5887888",
"0.58697414",
"0.58384514",
"0.582165",
"0.57998717",
"0.5766464",
"0.5734024",
"0.57302743",
"0.5717543",
"0.5691349",
"0.564297... | 0.7312112 | 0 |
Get the MAC of Server Hardware's iLO controller. | def _get_server_hardware_mac_from_ilo(server_hardware):
try:
client = get_ilorest_client(server_hardware)
ilo_path = "/rest/v1/systems/1"
hardware = jsonutils.loads(client.get(ilo_path).text)
hardware_mac = hardware['HostCorrelation']['HostMACAddress'][0]
except redfish.JsonDecod... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getMac(self):\n # Import netifaces here to prevent error importing this module in setup.py\n import netifaces\n interfaces = ['eth0', 'wlan0']\n try:\n interfaces.append(netifaces.gateways()['default'][netifaces.AF_INET][1])\n except:\n pass\n for... | [
"0.7558255",
"0.7499342",
"0.7251188",
"0.7216513",
"0.7197244",
"0.7197244",
"0.71224785",
"0.7062655",
"0.7039275",
"0.68878335",
"0.68746555",
"0.677884",
"0.67500824",
"0.67455614",
"0.6697018",
"0.6639741",
"0.662569",
"0.6582134",
"0.6567028",
"0.6560305",
"0.648537",
... | 0.74903506 | 2 |
Get the MAC address of the first PXE bootable port of an Ethernet port. | def _get_server_hardware_mac(server_hardware):
sh_physical_port = None
if server_hardware.get('portMap'):
for device in server_hardware.get(
'portMap', {}).get('deviceSlots', ()):
for physical_port in device.get('physicalPorts', ()):
if physical_port.get('typ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_mac_address():\n eth0_interface = 'eth0'\n addresses = netifaces.ifaddresses(eth0_interface)[netifaces.AF_LINK][0]\n mac_address = addresses['addr']\n return mac_address",
"def get_mac():\n\n interface = [x for x in netifaces.interfaces() if 'wlan' in x or 'wlp' in x][0]\n return netifa... | [
"0.69867545",
"0.6868253",
"0.6855199",
"0.67767805",
"0.6448431",
"0.6439653",
"0.641064",
"0.6402625",
"0.6315631",
"0.6301838",
"0.6258961",
"0.6156755",
"0.61553484",
"0.6115181",
"0.6087597",
"0.6040105",
"0.60321033",
"0.6030586",
"0.5961706",
"0.59339625",
"0.59106183"... | 0.5524931 | 52 |
Validate if the Server Profile Template is consistent. | def _validate_node_server_profile_template(oneview_client, oneview_info):
server_profile_template = oneview_client.server_profile_templates.get(
oneview_info['server_profile_template_uri'])
server_hardware = oneview_client.server_hardware.get(
oneview_info['server_hardware_uri'])
_validate_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate_server_profile_template_manage_boot(server_profile_template):\n manage_boot = server_profile_template.get('boot', {}).get('manageBoot')\n\n if not manage_boot:\n message = _(\"Server Profile Template: %s, does not allow to manage \"\n \"boot order.\") % server_profile_... | [
"0.7069994",
"0.68792826",
"0.66662836",
"0.6568979",
"0.623397",
"0.6207681",
"0.6184548",
"0.6091524",
"0.6008042",
"0.5996494",
"0.59735686",
"0.5967848",
"0.5924284",
"0.5894213",
"0.58178085",
"0.5812006",
"0.57749254",
"0.5769697",
"0.5671442",
"0.56670874",
"0.5555338"... | 0.7610132 | 0 |
Validate if the Server Hardware Types are the same. Validate if the Server Profile Template and the Server Hardware have the same Server Hardware Type | def _validate_server_profile_template_server_hardware_type(
server_profile_template, server_hardware):
spt_server_hardware_type_uri = (
server_profile_template.get('serverHardwareTypeUri')
)
sh_server_hardware_type_uri = server_hardware.get('serverHardwareTypeUri')
if spt_server_hardwar... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate_node_server_hardware_type(oneview_client, oneview_info):\n node_server_hardware_type_uri = oneview_info['server_hardware_type_uri']\n server_hardware = oneview_client.server_hardware.get(\n oneview_info['server_hardware_uri'])\n server_hardware_sht_uri = server_hardware.get('serverHar... | [
"0.72816855",
"0.7089422",
"0.6603946",
"0.5662966",
"0.5636588",
"0.5465046",
"0.5454747",
"0.5449822",
"0.5423557",
"0.53436553",
"0.5322769",
"0.530526",
"0.5304127",
"0.52597606",
"0.52190274",
"0.5214245",
"0.51793396",
"0.5171909",
"0.51624525",
"0.51224446",
"0.5110577... | 0.797853 | 0 |
Validate Server Profile Template's Enclosure Group and Server Hardware's. | def _validate_spt_enclosure_group(server_profile_template, server_hardware):
spt_enclosure_group_uri = server_profile_template.get('enclosureGroupUri')
sh_enclosure_group_uri = server_hardware.get('serverGroupUri')
if spt_enclosure_group_uri != sh_enclosure_group_uri:
message = _("Server profile te... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate_node_server_profile_template(oneview_client, oneview_info):\n server_profile_template = oneview_client.server_profile_templates.get(\n oneview_info['server_profile_template_uri'])\n server_hardware = oneview_client.server_hardware.get(\n oneview_info['server_hardware_uri'])\n\n ... | [
"0.760848",
"0.6779853",
"0.65984255",
"0.6223883",
"0.61876816",
"0.60283494",
"0.560771",
"0.5489887",
"0.53607535",
"0.5346088",
"0.5340885",
"0.53095055",
"0.52877337",
"0.5249136",
"0.52323705",
"0.5205969",
"0.51810074",
"0.5165089",
"0.5141421",
"0.5105114",
"0.5104925... | 0.6317872 | 3 |
Validate if the Server Profile Template allows to manage the boot order. | def _validate_server_profile_template_manage_boot(server_profile_template):
manage_boot = server_profile_template.get('boot', {}).get('manageBoot')
if not manage_boot:
message = _("Server Profile Template: %s, does not allow to manage "
"boot order.") % server_profile_template.get('... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate_node_server_profile_template(oneview_client, oneview_info):\n server_profile_template = oneview_client.server_profile_templates.get(\n oneview_info['server_profile_template_uri'])\n server_hardware = oneview_client.server_hardware.get(\n oneview_info['server_hardware_uri'])\n\n ... | [
"0.67219007",
"0.6499709",
"0.6323258",
"0.6316359",
"0.6255033",
"0.6118853",
"0.6111678",
"0.6087322",
"0.6000576",
"0.58550376",
"0.5843932",
"0.57918465",
"0.5738527",
"0.57050484",
"0.56965",
"0.5672641",
"0.56639814",
"0.56551486",
"0.564075",
"0.5627896",
"0.56241286",... | 0.8403261 | 0 |
Validate if the node's Server Hardware Type matches Server Hardware's. | def _validate_node_server_hardware_type(oneview_client, oneview_info):
node_server_hardware_type_uri = oneview_info['server_hardware_type_uri']
server_hardware = oneview_client.server_hardware.get(
oneview_info['server_hardware_uri'])
server_hardware_sht_uri = server_hardware.get('serverHardwareType... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate_server_profile_template_server_hardware_type(\n server_profile_template, server_hardware):\n spt_server_hardware_type_uri = (\n server_profile_template.get('serverHardwareTypeUri')\n )\n sh_server_hardware_type_uri = server_hardware.get('serverHardwareTypeUri')\n\n if spt_se... | [
"0.67908597",
"0.62367",
"0.5962622",
"0.5756479",
"0.56312937",
"0.55868",
"0.5542178",
"0.5457781",
"0.5441118",
"0.542971",
"0.54071677",
"0.53862107",
"0.5355715",
"0.5339024",
"0.53239506",
"0.528533",
"0.5275171",
"0.5271481",
"0.52409774",
"0.52346915",
"0.51931256",
... | 0.8271434 | 0 |
Validate if the node's Enclosure Group matches the Server Hardware's. | def _validate_node_enclosure_group(oneview_client, oneview_info):
server_hardware = oneview_client.server_hardware.get(
oneview_info['server_hardware_uri'])
sh_enclosure_group_uri = server_hardware.get('serverGroupUri')
node_enclosure_group_uri = oneview_info['enclosure_group_uri']
if node_encl... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate_node_server_hardware_type(oneview_client, oneview_info):\n node_server_hardware_type_uri = oneview_info['server_hardware_type_uri']\n server_hardware = oneview_client.server_hardware.get(\n oneview_info['server_hardware_uri'])\n server_hardware_sht_uri = server_hardware.get('serverHar... | [
"0.6324016",
"0.6095127",
"0.5762267",
"0.5492249",
"0.5368418",
"0.5298437",
"0.52928054",
"0.524873",
"0.5237448",
"0.51903677",
"0.5187325",
"0.5177885",
"0.5053734",
"0.50441307",
"0.50437135",
"0.50406593",
"0.50092286",
"0.50085694",
"0.5004797",
"0.5001447",
"0.500056"... | 0.68265074 | 0 |
Validate if a port matches the node's Server Hardware's MAC. | def _validate_node_port_mac_server_hardware(oneview_client,
oneview_info, ports):
server_hardware = oneview_client.server_hardware.get(
oneview_info['server_hardware_uri'])
if not ports:
return
# NOTE(nicodemos) If hponeview client's unable to ge... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _mac_test(mac):\n\n\t\tif re.search(r'([0-9A-F]{2}[:]){5}([0-9A-F]){2}', mac.upper()) is not None:\n\t\t\treturn True\n\t\telse:\n\t\t\treturn False",
"def isMACCommand(self):\n return self.payload.fport == 0",
"def validate_port(port_id, serial_id):\n check_port = False\n api_uri = f\"/v1/dev... | [
"0.7097071",
"0.674294",
"0.67142147",
"0.66719925",
"0.6523463",
"0.652277",
"0.6445301",
"0.64277035",
"0.618244",
"0.61718965",
"0.61240774",
"0.6104669",
"0.6086369",
"0.6079721",
"0.6074816",
"0.6058944",
"0.60415375",
"0.6036376",
"0.59993446",
"0.5959773",
"0.59428114"... | 0.7183407 | 0 |
Validate if the node's Server Profile Template's MAC type is physical. | def _validate_server_profile_template_mac_type(oneview_client, oneview_info):
server_profile_template = oneview_client.server_profile_templates.get(
oneview_info['server_profile_template_uri']
)
if server_profile_template.get('macType') != 'Physical':
message = _("The server profile template... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate_server_profile_template_server_hardware_type(\n server_profile_template, server_hardware):\n spt_server_hardware_type_uri = (\n server_profile_template.get('serverHardwareTypeUri')\n )\n sh_server_hardware_type_uri = server_hardware.get('serverHardwareTypeUri')\n\n if spt_se... | [
"0.6238729",
"0.5995228",
"0.5811483",
"0.57653874",
"0.56162757",
"0.5592679",
"0.5545467",
"0.5504423",
"0.5461139",
"0.53143936",
"0.53029996",
"0.5298736",
"0.5189293",
"0.5159756",
"0.515517",
"0.5120909",
"0.50535005",
"0.5044812",
"0.50217086",
"0.5011732",
"0.50085557... | 0.83715606 | 0 |
This method computes the results as a dictionary | def results(self):
results = {'answer':42}
return results | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_results(self) -> Dict:\n results = {}\n results['time'] = np.array(self._results['time'])\n results['norm'] = np.array(self._results['norm'])\n results['bond_dimensions'] = np.array(self._results['bond_dimensions'])\n results['dynamics'] = self._results['dynamics']\n ... | [
"0.7524411",
"0.733618",
"0.72358906",
"0.7162806",
"0.6873215",
"0.6867773",
"0.6776679",
"0.67169344",
"0.6667122",
"0.66590506",
"0.6656961",
"0.6643292",
"0.65733004",
"0.65509677",
"0.6536344",
"0.65005565",
"0.64302456",
"0.6420882",
"0.64187676",
"0.64016956",
"0.63917... | 0.64690924 | 16 |
Glib callback, to call on glib events watched | def _emited(self, *args):
debug("OnEventDeferred : event catched")
self.callback(*args)
self._clean() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def on_event(self, event):",
"def on_event_finished(self, event):",
"def on_event(self, event):\r\n pass",
"def events(self):",
"def callback(self):\n pass # pragma: no cover",
"def on_event(self, event):\n pass",
"def on_hook(self) -> None:",
"def handle_event(self, event):",
... | [
"0.59699833",
"0.58868843",
"0.58148116",
"0.5778598",
"0.5771084",
"0.56385773",
"0.5576121",
"0.5568321",
"0.55356026",
"0.5518454",
"0.5518454",
"0.5492587",
"0.5447376",
"0.5420657",
"0.53432494",
"0.53419924",
"0.53188616",
"0.5284998",
"0.5257975",
"0.52463734",
"0.5230... | 0.0 | -1 |
Glib callback, to call on glib err events | def _err_emited(self, *args):
debug("OnEventDeferred : err event catched")
self.errback(*args)
self._clean() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def on_error(self, callback):\n self.error_callback = callback",
"def handle_err(self):\n pass",
"def on_error(self, status_code, data):\n\t\tprint(\"error_code: \",status_code)",
"def ERR(self):",
"def hook_notifyerror(self,msg,subsystem=None):\n ui.notifyerror(msg,subsystem)",
"def... | [
"0.64166325",
"0.6177739",
"0.61619174",
"0.5980505",
"0.59541637",
"0.59343463",
"0.5878699",
"0.5859958",
"0.5820616",
"0.57654464",
"0.5743583",
"0.57358557",
"0.5722895",
"0.5707079",
"0.57069254",
"0.56566525",
"0.5656086",
"0.5653089",
"0.5645864",
"0.56389225",
"0.5627... | 0.57778734 | 9 |
Add event on obj which will trigger error on this Deferred | def add_error_event(self, obj, event, *args):
hid = obj.connect(event, self._err_emited, *args)
self.handlers_id.append(hid) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _err_emited(self, *args):\n\t\tdebug(\"OnEventDeferred : err event catched\")\n\t\tself.errback(*args)\n\t\tself._clean()",
"def errback(self, f):\r\n assert self.__obj is None, 'Only one object can be registered.'\r\n assert isinstance(f, Failure), \"Failure has to be of type 'Failure'.\"\r\n ... | [
"0.67899597",
"0.6495937",
"0.619477",
"0.61869735",
"0.61564225",
"0.615239",
"0.59784204",
"0.59604985",
"0.58662796",
"0.5854047",
"0.5818122",
"0.5777247",
"0.5679716",
"0.5663086",
"0.5646356",
"0.56234443",
"0.5596893",
"0.5590271",
"0.5570113",
"0.5570113",
"0.5570113"... | 0.7338435 | 0 |
To call when trigerred | def _clean(self):
for hid in self.handlers_id:
self.obj.handler_disconnect(hid) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def triggered(self, *args, **kwargs): # real signature unknown\n pass",
"def fire(self):",
"def trigger(self, type, event):",
"def __call__(self, trigger, type, event):",
"def fire(self):\n pass",
"def take_action(self, *args, **kwargs):\r\n pass",
"def act(self):\n pass",
... | [
"0.7579424",
"0.7375058",
"0.73647785",
"0.72742695",
"0.72413653",
"0.6972291",
"0.69711393",
"0.6867664",
"0.68155426",
"0.68155426",
"0.6703577",
"0.6642475",
"0.6636517",
"0.66193414",
"0.65902543",
"0.6557556",
"0.64969707",
"0.64872396",
"0.6479976",
"0.64473957",
"0.64... | 0.0 | -1 |
This function prints and plots the confusion matrix. | def plot_confusion_matrix(cm,classes,title='Confusion matrix',cmap=plt.cm.Blues):
x_classes=classes+ ['Recall']
y_classes=classes+ ['Precision']
plt.imshow(cm, interpolation='nearest', cmap=cmap)
plt.title(title,fontname='Times New Roman',fontsize = 16, y=1.03)
cbar=plt.colorbar(fraction=0.046)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def plot_confusion_matrix(self):\r\n interp = ClassificationInterpretation.from_learner(self.learn)\r\n interp.plot_confusion_matrix()",
"def showConfusionMatrix(self): \r\n sn.heatmap(self.conf_matrix, annot=True)\r\n plt.plot( label=\"Accuracy\")\r\n plt.plot( label=\"Error\"... | [
"0.80894613",
"0.80770946",
"0.79976976",
"0.7946727",
"0.7921785",
"0.78448296",
"0.7833224",
"0.7781221",
"0.7775631",
"0.77574563",
"0.77061635",
"0.77016985",
"0.7692213",
"0.76785815",
"0.76588994",
"0.7641414",
"0.7622791",
"0.7611233",
"0.7610989",
"0.7598244",
"0.7587... | 0.75652844 | 24 |
Returns a frozenset of variables used in given terms. Note that this returns all used variables, not just free ones. | def used_variables(*terms):
t = terms[0] if len(terms) == 1 else terms
if type(t) is Var:
return frozenset((t,))
elif type(t) in (tuple, Const, Apply, Eq, Ite, Not, And, Or,
Implies, Iff):
return union(*(used_variables(x) for x in t))
elif type(t) in (ForAll, Exi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def free_variables(*terms, **kwargs):\n by_name = kwargs.get('by_name', False)\n _free_variables = partial(free_variables, by_name=by_name)\n\n t = terms[0] if len(terms) == 1 else terms\n\n if type(t) is Var:\n return frozenset((t.name if by_name else t,))\n\n elif type(t) in (tuple, Const, ... | [
"0.7428986",
"0.6987549",
"0.69048446",
"0.6717069",
"0.6559568",
"0.63589525",
"0.62739486",
"0.6270176",
"0.61921215",
"0.6188963",
"0.61090964",
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"0.5938047",
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"0.589158",
"0.5881121",
"0.5876238",
"0.5858637",
"0.56572014",
"0.5639939",
"0.56199235... | 0.7920552 | 0 |
Returns a frozenset of variables free in given terms. | def free_variables(*terms, **kwargs):
by_name = kwargs.get('by_name', False)
_free_variables = partial(free_variables, by_name=by_name)
t = terms[0] if len(terms) == 1 else terms
if type(t) is Var:
return frozenset((t.name if by_name else t,))
elif type(t) in (tuple, Const, Apply, Eq, Ite... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def used_variables(*terms):\n\n t = terms[0] if len(terms) == 1 else terms\n\n if type(t) is Var:\n return frozenset((t,))\n\n elif type(t) in (tuple, Const, Apply, Eq, Ite, Not, And, Or,\n Implies, Iff):\n return union(*(used_variables(x) for x in t))\n\n elif type(t)... | [
"0.7301436",
"0.6923216",
"0.66222817",
"0.6540475",
"0.6467375",
"0.63554454",
"0.6250781",
"0.61498994",
"0.5961769",
"0.58668995",
"0.5840457",
"0.5688273",
"0.5672531",
"0.5552212",
"0.5511896",
"0.55101573",
"0.54558146",
"0.5436367",
"0.5431674",
"0.54288334",
"0.541791... | 0.7726464 | 0 |
Returns a frozenset of variables bound in given terms. | def bound_variables(*terms):
t = terms[0] if len(terms) == 1 else terms
if type(t) is Var:
return frozenset()
elif type(t) in (tuple, Const, Apply, Eq, Ite, Not, And, Or,
Implies, Iff):
return union(*(bound_variables(x) for x in t))
elif type(t) in (ForAll, Exist... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def used_variables(*terms):\n\n t = terms[0] if len(terms) == 1 else terms\n\n if type(t) is Var:\n return frozenset((t,))\n\n elif type(t) in (tuple, Const, Apply, Eq, Ite, Not, And, Or,\n Implies, Iff):\n return union(*(used_variables(x) for x in t))\n\n elif type(t)... | [
"0.72198117",
"0.70041084",
"0.6517899",
"0.59218013",
"0.5741847",
"0.57111204",
"0.5670193",
"0.5647711",
"0.5632197",
"0.5581976",
"0.55689853",
"0.55376583",
"0.54729617",
"0.5426977",
"0.5418284",
"0.5415937",
"0.5402921",
"0.53907967",
"0.5385815",
"0.53603476",
"0.5360... | 0.8032309 | 0 |
Returns a frozenset of constants used in given terms. | def used_constants(*terms):
t = terms[0] if len(terms) == 1 else terms
if type(t) is Const:
return frozenset((t,))
elif type(t) in (tuple, Var, Apply, Eq, Ite, Not, And, Or,
Implies, Iff, ForAll, Exists, Lambda, NamedBinder):
return union(*(used_constants(x) for x in ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_all_constants():\n return filter(\n lambda key: key.upper() == key and type(globals()[key]) in _ALLOWED,\n\n filter( # filter _PRIVATE variables\n lambda x: not x.startswith(\"_\"),\n globals()\n )\n )",
"def used_variables(*t... | [
"0.63245064",
"0.5992687",
"0.59890866",
"0.59641623",
"0.5806408",
"0.56888586",
"0.56451476",
"0.55847293",
"0.5571786",
"0.55393314",
"0.55284834",
"0.5504401",
"0.54954517",
"0.54566354",
"0.54400617",
"0.5428424",
"0.54196256",
"0.5411198",
"0.53967535",
"0.53961635",
"0... | 0.80427533 | 0 |
Return the term obtained from t by simultaneous substitution given by subs subs is either a dictionary or a mapping given by an iterable of (key, value) pairs Both keys and values in subs can be either Var or Const. All keys in subs will be substituted by their values in subs. For variables, only free occurances will b... | def substitute(t, subs):
if not isinstance(subs, dict):
subs = dict(subs)
if type(t) in (Var, Const):
if t in subs:
return subs[t]
else:
return t
elif type(t) in (Apply, Eq, Ite, Not, And, Or, Implies, Iff):
return type(t)(*(substitute(x, subs) for ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def substitute_apply(t, subs, by_name=False):\n\n if not isinstance(subs, dict):\n subs = dict(subs)\n\n _substitute_apply = partial(substitute_apply, subs=subs, by_name=by_name)\n\n if type(t) in (Var, Const):\n return t\n\n if type(t) is Apply and t.func in subs:\n terms = tuple(... | [
"0.6979903",
"0.6809032",
"0.68054605",
"0.67548573",
"0.6693763",
"0.6661133",
"0.65522754",
"0.65254176",
"0.6471985",
"0.62673676",
"0.6261165",
"0.6179068",
"0.6160233",
"0.61346424",
"0.6046451",
"0.5994784",
"0.5992433",
"0.5826811",
"0.58200824",
"0.5808683",
"0.574078... | 0.80016816 | 0 |
Return the term obtained from t by simultaneous substitution given by subs subs is either a dictionary or a mapping given by an iterable of (key, value) pairs Both keys and values in subs can be either Var or Const, but must be 2nd order. For any key, value in subs, Apply(key, terms) is substituted by value(terms'), so... | def substitute_apply(t, subs, by_name=False):
if not isinstance(subs, dict):
subs = dict(subs)
_substitute_apply = partial(substitute_apply, subs=subs, by_name=by_name)
if type(t) in (Var, Const):
return t
if type(t) is Apply and t.func in subs:
terms = tuple(_substitute_appl... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def substitute(t, subs):\n\n if not isinstance(subs, dict):\n subs = dict(subs)\n\n if type(t) in (Var, Const):\n if t in subs:\n return subs[t]\n else:\n return t\n\n elif type(t) in (Apply, Eq, Ite, Not, And, Or, Implies, Iff):\n return type(t)(*(substit... | [
"0.72416764",
"0.65752196",
"0.6252526",
"0.6022401",
"0.5977601",
"0.5844865",
"0.57589626",
"0.57118535",
"0.55280894",
"0.55234385",
"0.55226636",
"0.5458737",
"0.54270804",
"0.533437",
"0.5322457",
"0.53204954",
"0.52589554",
"0.51950306",
"0.5139489",
"0.50581187",
"0.50... | 0.77619237 | 0 |
Push universals inside conjunctions and existentials inside disjunctions, and flatten conjunctions and disjunctions | def normalize_quantifiers(t):
if type(t) in (Var, Const):
return t
elif type(t) in (Apply, Eq, Ite, Not, Implies, Iff):
return type(t)(*(normalize_quantifiers(x) for x in t))
elif type(t) in (And, Or):
return type(t)(*(
z
for x in t
for y in [no... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def join_conjuncts(conjuncts):\n if (len(conjuncts) == 0):\n return EmptyExpression()\n elif (len(conjuncts) == 1):\n return conjuncts[0]\n return AndExpression(conjuncts[0], join_conjuncts(conjuncts[1:]))",
"def NormalizeDisjunctions(disj,\n clause,\n ... | [
"0.6443251",
"0.64089215",
"0.6074677",
"0.5995137",
"0.58688325",
"0.5720804",
"0.5696947",
"0.5695756",
"0.5695434",
"0.5670252",
"0.56636274",
"0.56636274",
"0.5454893",
"0.5410893",
"0.54107594",
"0.53419995",
"0.5327409",
"0.5188059",
"0.51802075",
"0.5173974",
"0.516951... | 0.0 | -1 |
Returns True if t is Eq(x,x) for some x | def is_tautology_equality(t):
return type(t) is Eq and t.t1 == t.t2 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def equals(x, y):\n return x == y",
"def exact(cls, lhs, rhs):\n return lhs == rhs",
"def __eq__(self, *args):\n return _ida_hexrays.cexpr_t___eq__(self, *args)",
"def eq(self, y):\n return 1 - self.ne(y)",
"def __eq__(self, other: t.Any) -> bool:\n return self._op_bool('__eq__',... | [
"0.6527325",
"0.6335552",
"0.62206423",
"0.61665654",
"0.6158353",
"0.6072844",
"0.606981",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
"0.6037759",
... | 0.69490355 | 0 |
Returns True if t is syntactially equal to u modulo alpha conversion | def equal_mod_alpha(t,u):
def rec(t,u,m1,m2,n):
if type(t) is Var and type(u) is Var:
return m1.get(t,t) == m2.get(u,u)
if type(t) in (ForAll, Exists, Lambda, NamedBinder) and type(t) is type(u):
if len(t.variables) == len(u.variables):
for v1,v2 in zip(t.vari... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def u_exact(t):\n return a * t + b",
"def isalpha(self) -> bool:\n pass",
"def oracle(ct: int) -> bool:\n return rsa.dec(ct) & 1 == 0",
"def isAcute(trpl):\n vd = vectorFormat(trpl)\n if angle_between(*vd) < np.pi/2:\n return True\n else:\n return False",
"def check_pali... | [
"0.58734155",
"0.5778579",
"0.5749819",
"0.5632407",
"0.55852145",
"0.55829185",
"0.5546565",
"0.5520525",
"0.55134135",
"0.5501811",
"0.5460695",
"0.5449854",
"0.54210347",
"0.5412214",
"0.538456",
"0.5383626",
"0.53737104",
"0.5345897",
"0.5311306",
"0.5297979",
"0.5283892"... | 0.67610735 | 0 |
Retrieves the parameters from the User Interface and executes the appropriate commands. | def setupCentralFeature():
inputFC = ARCPY.GetParameterAsText(0)
outputFC = ARCPY.GetParameterAsText(1)
distanceMethod = ARCPY.GetParameterAsText(2).upper().replace(" ", "_")
weightField = UTILS.getTextParameter(3, fieldName = True)
potentialField = UTILS.getTextParameter(4, fieldName = True)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def user_interface() -> dict:\n args = _spawn_cli()\n\n if args['graphical_user_interface']:\n args = _spawn_gui()\n\n return args",
"def cmd_user(args):",
"def run(self):\n self._params = self.parsingcommands()\n self.start()",
"def set_by_gui(self):\n\n # Use the GetFro... | [
"0.64933056",
"0.63061106",
"0.6163773",
"0.6124755",
"0.6104701",
"0.6090645",
"0.6065398",
"0.60392755",
"0.59720314",
"0.5961228",
"0.58988",
"0.5890323",
"0.5884006",
"0.58813107",
"0.585739",
"0.5848049",
"0.58280426",
"0.5819351",
"0.58124715",
"0.58089554",
"0.5807343"... | 0.0 | -1 |
Reports the Central Feature results as a message or to a file. | def report(self, fileName = None):
header = ARCPY.GetIDMessage(84200)
columns = [ARCPY.GetIDMessage(84191), ARCPY.GetIDMessage(84201),
ARCPY.GetIDMessage(84202)]
results = [ columns ]
for case in self.uniqueCases:
if not self.caseField:
st... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def report(self, result):\n raise NotImplementedError",
"def report():\n pass",
"def report(self):\n if self.integration.channels.n_mapping_channels > 0:\n msg = f'({self.get_mean_point_response()})'\n else:\n msg = '(---)'\n self.integration.comments.ap... | [
"0.6436226",
"0.63747406",
"0.6339677",
"0.6156899",
"0.6153056",
"0.614563",
"0.6017631",
"0.6008375",
"0.6001736",
"0.59945923",
"0.59724426",
"0.5939775",
"0.58608884",
"0.58568907",
"0.5841457",
"0.5820173",
"0.581097",
"0.57991844",
"0.5720601",
"0.57149744",
"0.5708021"... | 0.5674634 | 24 |
Creates an Output Feature Class with the Directional Mean Results. | def createOutput(self, outputFC):
#### Validate Output Workspace ####
ERROR.checkOutputPath(outputFC)
#### Shorthand Attributes ####
ssdo = self.ssdo
caseField = self.caseField
#### Create Output Feature Class ####
ARCPY.SetProgressor("default", ARCPY.GetIDMess... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def GetFeatureMeansOutput(self) -> \"itkDataObjectDecoratorVCUCD const *\":\n return _itkScalarImageToRunLengthFeaturesFilterPython.itkScalarImageToRunLengthFeaturesFilterIUS2_GetFeatureMeansOutput(self)",
"def GetFeatureMeansOutput(self) -> \"itkDataObjectDecoratorVCUCD const *\":\n return _itkSca... | [
"0.6007328",
"0.5953091",
"0.5914813",
"0.58763796",
"0.5794096",
"0.5764322",
"0.56564254",
"0.5608095",
"0.55957776",
"0.55957776",
"0.55321646",
"0.52677256",
"0.5212198",
"0.5199211",
"0.51898897",
"0.5150236",
"0.5150236",
"0.5136099",
"0.5125028",
"0.5106955",
"0.507898... | 0.46067312 | 94 |
Method used to calculate the distance between each feature in the dataset. The algorithm is near 0(n2). Effort to improve algorithn is currently underway. | def nsquaredDist(points, weights = None, potent = None, dType = "EUCLIDEAN"):
n,k = NUM.shape(points)
maxMinSumDist = 3.402823466E+38
if weights == None:
weights = NUM.ones((n,), float)
if potent == None:
potent = NUM.zeros((n,), float)
weightedPotential = weights * potent
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _calc_distance_features(self):\n d = ()\n for dx, dy in DIRECTIONS:\n if dx and dy:\n d += (list(self.__calc_distance(direction_x=dx, direction_y=dy)), )\n elif dx:\n tmp, _, _ = self.__calc_distance(direction_x=dx, direction_y=dy)\n ... | [
"0.7269883",
"0.70110106",
"0.68549025",
"0.68144464",
"0.67935103",
"0.67327285",
"0.67210007",
"0.67199934",
"0.6640506",
"0.66104364",
"0.66035396",
"0.6600966",
"0.6562376",
"0.6559457",
"0.654279",
"0.6527522",
"0.65272194",
"0.6524415",
"0.65215033",
"0.6520606",
"0.650... | 0.0 | -1 |
Unzip a file (zip_file), extract the contained files, and clean the useful files name. | def unzip_oxygen_files(zip_file):
name_main_content = None
name_left_menu = None
list_img_files_to_save = list()
files_unzipped = ZipFile(zip_file)
for file_unzipped_name in files_unzipped.namelist():
if not file_unzipped_name.startswith('__MACOSX'):
if file_unzipped_name.endswi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def unzip_file(zip_file: str) -> None:\n destination = tempfile.mkdtemp(prefix='gaelo_pross_unzip_')\n with ZipFile(zip_file) as my_zip:\n for member in my_zip.namelist():\n filename = os.path.basename(member)\n # skip directories\n if not filen... | [
"0.7879227",
"0.7851471",
"0.7838017",
"0.7399866",
"0.72983783",
"0.7179027",
"0.7157811",
"0.71029925",
"0.70012826",
"0.69726837",
"0.69336355",
"0.69276774",
"0.685054",
"0.6836097",
"0.682251",
"0.6815342",
"0.68073237",
"0.67946047",
"0.67689204",
"0.6732124",
"0.671994... | 0.7050054 | 8 |
Return the body part of HTML files. | def get_body(html_file_content):
return findall("<body>(.*?)</body>", html_file_content, DOTALL)[0].decode("utf-8") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_body(html_page):\n soup = BeautifulSoup(open(html_page), 'html.parser')\n body = soup.find('body')\n return body",
"def get_body_content(self):\n\n try:\n html_tree = parse_html_string(self.content)\n except:\n return ''\n\n html_root = html_tree.getroo... | [
"0.77461666",
"0.7460988",
"0.7410468",
"0.7252582",
"0.72338134",
"0.69558644",
"0.6863169",
"0.66610724",
"0.66539806",
"0.665275",
"0.6494882",
"0.64808214",
"0.6437959",
"0.6399701",
"0.63638884",
"0.63097113",
"0.6272104",
"0.6268735",
"0.62536013",
"0.62374175",
"0.6231... | 0.7931815 | 0 |
Correct the diagram links into the main content body. | def correct_img_links(body_main_content, schema_name, list_name_image):
for name_image in list_name_image:
body_main_content = body_main_content.replace(
"src=\"" + name_image + "\"",
"src=\"{% static \"schema_viewer/oxygen/" + schema_name + "/" + name_image + "\" %}\""
)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fix_links():\n pass",
"def append_links(self, lines, lang):\n lines.append(\"verbatim \")\n lines.append(\"section Links\")\n lines.append(\"external http://polcasaglia.blogspot.com Blog\")\n lines.append(\"external http://www.uisp-fe.it/calcio.php UISP\" )\n lines... | [
"0.63308895",
"0.5643925",
"0.55043316",
"0.5476968",
"0.5352855",
"0.5346029",
"0.53028953",
"0.5257914",
"0.5252659",
"0.52249026",
"0.52183926",
"0.519567",
"0.5179021",
"0.5144104",
"0.51285285",
"0.5118393",
"0.50887305",
"0.50714946",
"0.5056446",
"0.50404006",
"0.50282... | 0.5835807 | 1 |
Correct the links to an element with a specified id within a page. | def correct_links(html_file, schema_name):
return html_file.replace(schema_name.replace(".", "_") + "_xsd.html#", "#").replace("target=\"mainFrame\"", "") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def id_click(elem_id):\r\n css_click('#{}'.format(elem_id))",
"def relink(self, link_id):",
"def update_links(self):\n for a in self.book.xpath(\"//a[@href]\"):\n href = a.xpath(\"@href\")[0]\n index_list = a.xpath(\"@data-index\")\n \n ### If there is no d... | [
"0.5732867",
"0.57129985",
"0.5561037",
"0.5431923",
"0.5380251",
"0.53681576",
"0.5339433",
"0.5337128",
"0.52954435",
"0.51980627",
"0.51771003",
"0.5171741",
"0.5160099",
"0.5103413",
"0.5056982",
"0.5039212",
"0.5028696",
"0.5026417",
"0.5026249",
"0.50201905",
"0.5015862... | 0.49036095 | 28 |
Create the final HTML oxygen files, with the common header, a specific left menu and the main body. | def create_html_file(body_left_menu, body_main_content):
# Get the header fie and get it contents
path_header = path.join(
SITE_ROOT,
'schema_viewer',
'templates',
'schema_viewer',
'oxygen',
'header_oxygen_template.html'
)
file_header = open(path_header, ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def common_header_part1(outfile: TextIO, title: str, indexpath: str = \"\") -> None:\n outfile.write(\"<!DOCTYPE HTML>\\n\")\n outfile.write(\"<html lang=\\\"en\\\">\\n\")\n outfile.write(\" <head>\\n\")\n outfile.write(\" <!-- Google tag (gtag.js) -->\\n\")\n outfile.write(\" <script async src=\... | [
"0.61840135",
"0.615706",
"0.6106681",
"0.59005207",
"0.58948696",
"0.5833731",
"0.57632947",
"0.57230896",
"0.57106525",
"0.57040775",
"0.56784046",
"0.5634475",
"0.56243837",
"0.5544781",
"0.5540921",
"0.5534541",
"0.55281717",
"0.55029094",
"0.5502361",
"0.5495124",
"0.549... | 0.7858279 | 0 |
Delete the previous version of the oxygen files in case of an update. | def delete_previous_files(schema_name, path_template, path_static):
list_file_static = listdir(path_static)
list_file_template = listdir(path_template)
if schema_name in list_file_static:
tree_path = path.join(path_static, schema_name)
rmtree(tree_path, ignore_errors=True)
html_file_name... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_version(self):\n pass",
"def cleanup(self):\n files = self.nlst()\n latest = self.latest_filename\n for filename in files:\n if filename != latest:\n result = self.delete(filename)\n logger.info(f\"Deleted old export from FTP: {resul... | [
"0.671009",
"0.6189813",
"0.6089963",
"0.60492635",
"0.5967357",
"0.5963805",
"0.59523124",
"0.58832395",
"0.5855765",
"0.58287776",
"0.5819642",
"0.5810277",
"0.5799433",
"0.579169",
"0.5766293",
"0.5758868",
"0.57391065",
"0.5717249",
"0.5716283",
"0.5714396",
"0.57026523",... | 0.5372125 | 69 |
Save the oxygen treated files. | def save_file(schema_name, unzipped_file, list_name_img, html_file_content):
# Create the different paths
base_path = path.join(SITE_ROOT, 'schema_viewer')
path_template = path.join(base_path, 'templates', 'schema_viewer', 'oxygen')
path_static = path.join(base_path, 'static', 'schema_viewer', 'oxygen'... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save(self):\n super(YacoFile, self).save(self._filename)",
"def save(self):\n # TODO: save the file",
"def save(self):\n file = open(self.path, 'w')\n self.parser.write(file)\n file.close()",
"def save(self):\n if PYTHON3:\n fileobj = open(self.filenam... | [
"0.64760363",
"0.61626124",
"0.61587566",
"0.6028327",
"0.6016403",
"0.60064465",
"0.60013676",
"0.5986529",
"0.59179187",
"0.59133315",
"0.58921486",
"0.5864421",
"0.58638525",
"0.5859094",
"0.5845023",
"0.5842954",
"0.58204085",
"0.57929534",
"0.5788086",
"0.57738835",
"0.5... | 0.0 | -1 |
Delete the drop list on the left menu. | def delete_menu(body_left_menu):
return sub("<form (.*?) </form>", "", body_left_menu, flags=DOTALL) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_menu():",
"def leftdelalllistitems(self):\n self._leftlist.delete()",
"def rightdelalllistitems(self):\n self._rightlist.delete()",
"def delete(self, *args):\n if self.cur == Win.left:\n self.commands.delpl([])\n else:\n cur_song = self.rightwin.hi... | [
"0.7733161",
"0.7365979",
"0.6736597",
"0.66517335",
"0.6495857",
"0.6299191",
"0.6218803",
"0.6123064",
"0.6118206",
"0.6067442",
"0.60464346",
"0.60106766",
"0.6008462",
"0.60053957",
"0.6001826",
"0.5995467",
"0.5929168",
"0.5919876",
"0.591443",
"0.588858",
"0.5830762",
... | 0.6306563 | 5 |
Check if the files are name the right way. | def is_correct_name(name_left_menu, name_main_content, schema_name):
return name_main_content.startswith(schema_name.replace(".", "_")) and name_left_menu.startswith(schema_name) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_valid_file_name(self, file_name, input_output):\n if self.check_file_exists (file_name):\n if self.check_file_name_extensions (file_name, input_output):\n return True\n else:\n return False\n else:\n print (\"File does not exist... | [
"0.71929294",
"0.7132529",
"0.7119266",
"0.7111831",
"0.70485663",
"0.6969248",
"0.6935903",
"0.69152814",
"0.69132406",
"0.68058664",
"0.6759821",
"0.67477936",
"0.67245626",
"0.6688093",
"0.6649612",
"0.6649612",
"0.6649612",
"0.6649267",
"0.6627869",
"0.6600657",
"0.653856... | 0.0 | -1 |
Delete the floating global control on the main content. | def del_global_control(body_main_content):
return sub("<div id=\"global_controls\" (.*?) </div>", "", body_main_content, flags=DOTALL) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def DelDiv(self):\n if self.created:\n self.CloseImage()\n command = \"\"\"$('#{}').remove();\"\"\".format(self.wid)\n get_ipython().run_cell_magic('javascript', '', command)\n self.created = False\n self.wid = uuid.uuid4().hex",
"def OnCloseFloatingP... | [
"0.6569426",
"0.6322288",
"0.6220098",
"0.61642945",
"0.6048335",
"0.6038787",
"0.599455",
"0.598732",
"0.5944671",
"0.5929435",
"0.5899441",
"0.5881212",
"0.5822167",
"0.5811097",
"0.5805517",
"0.5760576",
"0.5734409",
"0.57206446",
"0.5712142",
"0.5706464",
"0.5681028",
"... | 0.6487117 | 1 |
Is called when model is initialized. | def __init__(self,
image_channels,
num_classes):
super().__init__()
self.model = torchvision.models.resnet18(pretrained=True)
self.model.fully_connected = nn.Linear(224, 10) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def initialize_model(self):\n pass",
"def init_model(self):\n pass",
"def initialize(self, model):\n pass",
"def onInit(self):\n pass",
"def __init__(self):\n self.model = None",
"def __init__(self):\n self.model = None",
"def post_init(self):\n\t\tpass",
"def ... | [
"0.87021303",
"0.8675239",
"0.8595884",
"0.7529007",
"0.7524197",
"0.7524197",
"0.74977756",
"0.7488579",
"0.7450165",
"0.73805875",
"0.73642135",
"0.7351956",
"0.73474675",
"0.7244248",
"0.72271895",
"0.72271895",
"0.71926934",
"0.7177532",
"0.71773064",
"0.71741855",
"0.717... | 0.0 | -1 |
Performs a forward pass through the model | def forward(self, x):
#batch_size = x.shape[0]
out = self.model(x)
return out | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def forward(self):\n pass",
"def forward(self):\n pass",
"def forward(self, forward):\n\n self._forward = forward",
"def forward(self, *args, **kwargs):\n pass",
"def forward_pass(self):",
"def forward(self):\n raise NotImplemented",
"def forward(self):\n raise... | [
"0.7781306",
"0.7781306",
"0.75729156",
"0.75230056",
"0.7505109",
"0.74263227",
"0.74263227",
"0.74263227",
"0.73245245",
"0.7310507",
"0.7309029",
"0.73008585",
"0.7245502",
"0.7235511",
"0.7235511",
"0.72333467",
"0.71885544",
"0.7169972",
"0.7169972",
"0.7139009",
"0.7115... | 0.6689024 | 53 |
Test all feasible Mysql types. | def test_data_types(sdc_builder, sdc_executor, database, sql_type, insert_fragment, expected_type, expected_value, keep_data):
table_name = get_random_string(string.ascii_lowercase, 20)
connection = database.engine.connect()
try:
# Create table
connection.execute(f"""
CREATE TABL... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def meets_condition(db_type: str):\n\t\t...",
"def _check_sql_mode(self, **kwargs):\n return []",
"def test_selectable_orm(self):\n b = SQLAlchemyBuilder(selectable=self.datatypes_table)\n type_examples = \"\"\"\n [score] -> num\n score ... | [
"0.645035",
"0.63011086",
"0.6299865",
"0.61006",
"0.5945623",
"0.58826905",
"0.58359575",
"0.5807354",
"0.57903266",
"0.5706516",
"0.56834126",
"0.5640781",
"0.5626899",
"0.56115544",
"0.55312985",
"0.551172",
"0.5480632",
"0.5480241",
"0.54659134",
"0.5460469",
"0.54514587"... | 0.5347046 | 27 |
deques the frames and runs prediction network on them. | def _process(self):
while True:
with Timer() as data_timer:
frame = self._frames_q.get()
with Timer() as agent_timer:
s, frame_metadata = self._unwrap_frame(frame)
s = np.expand_dims(s, 0) # batch
act = self.pred(s)[0][0].argmax()
put_overwrite(self._actions_q, ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __predict(self):\n frame_ind = 0\n while True:\n if not self.__queue_frame.empty():\n frame_ind += 1\n frame = self.__queue_frame.get()\n self.detector_lock.acquire()\n rects, probs, classesID = self.detect_frame(frame)\n ... | [
"0.66556954",
"0.6258876",
"0.6240899",
"0.618182",
"0.61364746",
"0.61184543",
"0.6099741",
"0.60250056",
"0.60198146",
"0.5992484",
"0.598858",
"0.59394705",
"0.5863917",
"0.58249295",
"0.5809526",
"0.57778484",
"0.5756796",
"0.57393205",
"0.57242197",
"0.5709892",
"0.57000... | 0.6108806 | 6 |
Returns data, trajectories, and trajcategories | def get_all_data(self, tids=None, uids=None, cids=None):
arg_tids = tids
arg_uids = uids
arg_cids = cids
if tids is None:
tids = self.tids
if uids is None:
uids = self.uids
if cids is None:
cids = self.cids
tids = set(tids)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def generate_trajectories_feature(self):\n if self.df_feature is not None:\n return self.df_feature\n trajs_feature = [traj.get_basic_feature() for traj in self.trajectories]\n self.df_feature = pd.DataFrame(trajs_feature)\n self.df_feature[\"LABEL\"] = self.df[\"LABEL\"]\n ... | [
"0.5957784",
"0.5917458",
"0.5876374",
"0.57930994",
"0.565999",
"0.55378914",
"0.55311126",
"0.5477821",
"0.54587895",
"0.541768",
"0.54167956",
"0.5406964",
"0.5402507",
"0.5381969",
"0.5371459",
"0.53617156",
"0.53342634",
"0.53302366",
"0.5322792",
"0.5321513",
"0.5294451... | 0.49892798 | 67 |
filters data that have at least $at_least $x unique values per $per | def filter_x_per_y(df, at_least, x, per):
return df.groupby(per, as_index=False, sort=False).filter(
lambda g: g[x].nunique() >= at_least
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def filter_toofew_toolong(df, min_each_group, max_length):\n df = df[~(df.question.apply(lambda x : len(x)) > max_length)]\n\n counts = df[\"index\"].value_counts()\n idxs = np.array(counts.index)\n \n # index numbers of groups with count >= mineachgroup\n list_idx = [i for i, c in zip(idxs, coun... | [
"0.55409527",
"0.55308944",
"0.55091226",
"0.5428687",
"0.5395138",
"0.53877074",
"0.5354342",
"0.5341396",
"0.52779645",
"0.5227017",
"0.51802427",
"0.51764864",
"0.51556313",
"0.5132215",
"0.51163405",
"0.51158553",
"0.5110208",
"0.510321",
"0.50508755",
"0.5044529",
"0.503... | 0.798085 | 0 |
Receives a DBSReader object and finds out whether it's pointing to Global DBS (no matter whether it's production or the preproduction instance). | def isGlobalDBS(dbs):
try:
url = urlparse(dbs.dbsURL)
if url.hostname.startswith('cmsweb'):
if url.path.startswith('/dbs/prod/global') or url.path.startswith('/dbs/int/global'):
return True
except Exception as ex:
logging.error("Failed to find out whether DBS ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_current_gisdbase():\n global current_gisdbase\n return current_gisdbase",
"async def casino_is_global(self):\n return await self.db.Settings.Global()",
"def is_on_dbsnp(row):\n is_on_dbsnp = 1\n\n if row[\"dbsnp\"] == \"-\":\n is_on_dbsnp = 0\n\n return is_on_dbsnp",
"def... | [
"0.52581006",
"0.5185863",
"0.51744187",
"0.51528794",
"0.5043897",
"0.50279176",
"0.5004774",
"0.500209",
"0.49769497",
"0.49480417",
"0.49011204",
"0.48366022",
"0.48357213",
"0.48242038",
"0.4815816",
"0.48043567",
"0.47987908",
"0.47840345",
"0.47834823",
"0.47745487",
"0... | 0.7254706 | 0 |
Check whether we're handling a block or a dataset | def isDataset(inputData):
if '#' in inputData.split('/')[-1]:
return False
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_block(self):\n\t\treturn self.name in get_elements_collection(self.__res, 'block_level')",
"def check_block(self, block):\n pass",
"def is_dataset(self):\n return self._dataset is not None",
"def is_valid(self, dataset):\n pass",
"def _check_block_type():\n \n \n maxBlock... | [
"0.6642541",
"0.6571856",
"0.6351768",
"0.6229571",
"0.60271245",
"0.5995095",
"0.5977335",
"0.59726757",
"0.59427077",
"0.59242815",
"0.5867659",
"0.5792803",
"0.57652533",
"0.5763878",
"0.5760709",
"0.57508045",
"0.57508045",
"0.5722193",
"0.57106143",
"0.57044363",
"0.5692... | 0.5535452 | 29 |
Get data location from Rucio. Location is mapped to the actual sites associated with them, so PSNs are actually returned | def locationsFromRucio(self, dataItems, rucioAcct):
result = defaultdict(set)
self.logger.info("Fetching location from Rucio for account: %s", rucioAcct)
for dataItem in dataItems:
try:
dataLocations = self.rucio.getDataLockedAndAvailable(name=dataItem,
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_location(self):\n\t\treturn self.location",
"def location_data(self) -> pulumi.Output[Optional['outputs.LocationDataResponse']]:\n return pulumi.get(self, \"location_data\")",
"def get_location(self):\n return self.request({\n \"path\": \"/\" + UUID + \"/location\"\n })"... | [
"0.66687316",
"0.66027284",
"0.65894485",
"0.6579517",
"0.6561672",
"0.6553024",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
"0.6507655",
... | 0.6383166 | 35 |
Get data location from dbs | def locationsFromDBS(self, dbs, dataItems):
result = defaultdict(set)
for dataItem in dataItems:
try:
if isDataset(dataItem):
phedexNodeNames = dbs.listDatasetLocation(dataItem)
else:
phedexNodeNames = dbs.listFileBlockL... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def file_loc(self):\n\t\treturn self.__dbfile",
"def __get_location(self) -> str:\n\t\treturn os.getenv('SQLITE_DRIVER_LOCATION', 'db.sqlite')",
"def get_datasource_of():\n global datasource_of\n\n if not datasource_of:\n datasource_of = stixhelpers.datasource_of()\n \n return datasource_of"... | [
"0.6616532",
"0.6296066",
"0.6252961",
"0.62318724",
"0.6225313",
"0.61788684",
"0.61649096",
"0.61381984",
"0.60394216",
"0.60271424",
"0.59884375",
"0.5912525",
"0.5897254",
"0.5876116",
"0.5872178",
"0.58330953",
"0.582461",
"0.58245146",
"0.5800512",
"0.57918423",
"0.5775... | 0.6312537 | 1 |
Sort items by dbs instances return dict with DBSReader as key & data items as values | def organiseByDbs(self, dataItems):
itemsByDbs = defaultdict(list)
for item in dataItems:
if ACDCBlock.checkBlockName(item['name']):
# if it is acdc block don't update location. location should be
# inserted when block is queued and not supposed to change
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sortdb():\n return sorted(donor_db.items(), key=sumdbkey, reverse=True)",
"def read_db():\n f_result = []\n result = execute_query('select sitename, id from {} order by sitename;'.format(TABLES[0]))\n sites = [(x['sitename'], x['id']) for x in result]\n for sitename, site_id in sites:\n ... | [
"0.6100124",
"0.5767866",
"0.5482177",
"0.5375432",
"0.52297914",
"0.517466",
"0.51589227",
"0.51308376",
"0.5080761",
"0.50783294",
"0.5067629",
"0.5035221",
"0.50315094",
"0.5030121",
"0.50266075",
"0.5023428",
"0.5004768",
"0.50018305",
"0.4949546",
"0.49456415",
"0.494003... | 0.62622225 | 0 |
Initialize your data structure here. | def __init__(self, n: int):
self.rows = [[n, -1] for _ in range(n)]
self.cols = [[n, -1] for _ in range(n)]
self.diag = [[n, -1], [n, -1]] # 0 for normal, 1 for anti
def move(self, row: int, col: int, player: int) -> int:
r1, r2 = self.check(self.rows, row, player), self.che... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _init_empty(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__(self):\n self._data = []",
"def __init__... | [
"0.7765608",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7645274",
"0.7595176",
"0.75853467",
"0.7558298",
"0.7530608",
"0.7530608",
"0.7530608",
"0.7530608",
"0.7530608",
"0.74971247",
"0.74971247",
"0.7478105",
"0.7477832",
"0.7477832",
"0.7477832",
... | 0.0 | -1 |
Hjorth's Complexity and Parameters Hjorth Parameters are indicators of statistical properties initially introduced by Hjorth (1970) to describe the general characteristics of an EEG trace in a few quantitative terms, but which can applied to any time series. The parameters are activity, mobility, and complexity. NeuroK... | def complexity_hjorth(signal):
# Sanity checks
if isinstance(signal, (np.ndarray, pd.DataFrame)) and signal.ndim > 1:
raise ValueError(
"Multidimensional inputs (e.g., matrices or multichannel data) are not supported yet."
)
# Calculate derivatives
dx = np.diff(signal)
d... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def doParametersOfInterest(self):\n \n self.modelBuilder.doVar('expr::cosW(\"0.87681811112\",)')\n self.modelBuilder.doVar('expr::sinW(\"0.48082221247\",)')\n self.modelBuilder.doVar('expr::mZ(\"91.2\",)')\n self.modelBuilder.doVar('expr::Lambda1(\"100.0\",)')\n self.modelBui... | [
"0.6022703",
"0.57704234",
"0.5730367",
"0.56339955",
"0.5561419",
"0.5557344",
"0.5556481",
"0.5482355",
"0.548171",
"0.548036",
"0.54543763",
"0.5435389",
"0.5425596",
"0.5410607",
"0.5403748",
"0.5390412",
"0.537292",
"0.5371755",
"0.5351225",
"0.53323776",
"0.531349",
"... | 0.71381897 | 0 |
Initialize the Application given a system. | def __init__(self, system, *args, **kwargs):
# Initialize the application as a tkinter.Tk object
tkinter.Tk.__init__(self, *args, **kwargs)
self.title("Foveated Vision System")
self.configure(bg="lightgray", width=1200, height=800)
self.resizable(width=False, height=False)... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setup_application(self):\n pass",
"def initialize(self, application):",
"def initialize():\n environment = Environment()\n environment.setup()",
"def init_app(args, setup_logging=True):\n if setup_logging:\n pyramid.paster.setup_logging(args.config)\n settings = pyramid.past... | [
"0.6723451",
"0.6705834",
"0.62384826",
"0.622743",
"0.61934197",
"0.6075346",
"0.59855795",
"0.59793085",
"0.5969467",
"0.5965201",
"0.59624267",
"0.5955624",
"0.59332913",
"0.5872671",
"0.58487064",
"0.58303475",
"0.57860106",
"0.57808584",
"0.5745589",
"0.57177776",
"0.571... | 0.0 | -1 |
Update the images that are displayed from the video stream. | def update(self):
# Update the vision frames in the system
self._system.update()
# Create blank PIL images to hold the video streams
layered = PIL.Image.new('RGBA', (400, 400))
stacked = PIL.Image.new('RGBA', (200, 800))
control = PIL.Image.new('RGBA', (600, 800... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update(self):\n print('VIDEO: Video Stream started')\n while True:\n if self.stopped:\n return\n (self.grabbed, self.frame) = self.stream.read()",
"def viewUpdate(self):\n # Update Capture\n imgtk = self.model.capture\n self.updateImage(... | [
"0.67444074",
"0.6730207",
"0.6720518",
"0.67168564",
"0.6591318",
"0.657772",
"0.6577194",
"0.64696455",
"0.6445771",
"0.64267576",
"0.64083344",
"0.6405238",
"0.6402562",
"0.6371376",
"0.6345765",
"0.63317454",
"0.62935567",
"0.62902534",
"0.6285674",
"0.6278713",
"0.626501... | 0.7045872 | 0 |
Update the vision choices when a new device is selected. | def updateDevice(self, *args):
# Update the list of vision choices and the default vision choice
self._appChoice["vision"] = [choice[0] for choice in self._system[self._appString["device"].get()]]
self._appString["vision"].set(self._appChoice["vision"][0])
# Delete the old choice... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def updateVision(self, *args):\r\n\r\n # Update the list of frame choices and the default frame choice\r\n self._appChoice[\"frame\"] = [choice[0] for choice in self._system[self._appString[\"device\"].get()][self._appString[\"vision\"].get()]]\r\n self._appString[\"frame\"].set(self._appChoic... | [
"0.68089235",
"0.59843624",
"0.5973282",
"0.5937724",
"0.5828414",
"0.58241105",
"0.5739061",
"0.56566024",
"0.56519794",
"0.5624004",
"0.5604147",
"0.5591249",
"0.55712897",
"0.5546274",
"0.5538931",
"0.54759663",
"0.54590356",
"0.54416597",
"0.54367846",
"0.54256344",
"0.54... | 0.82246095 | 0 |
Update the frame choices whena new vision is selected. | def updateVision(self, *args):
# Update the list of frame choices and the default frame choice
self._appChoice["frame"] = [choice[0] for choice in self._system[self._appString["device"].get()][self._appString["vision"].get()]]
self._appString["frame"].set(self._appChoice["frame"][0])
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def slider_frames_changed(self):\n\n # Again, please note the difference between indexing and GUI displays.\n index = self.slider_frames.value() - 1\n\n # Differentiate between frame ordering (by quality or chronologically).\n if self.frame_ordering == \"quality\":\n self.fra... | [
"0.67221683",
"0.647668",
"0.6142463",
"0.60368323",
"0.6010365",
"0.59839",
"0.594206",
"0.5939723",
"0.5774318",
"0.57701164",
"0.5685508",
"0.56649303",
"0.5623016",
"0.5616354",
"0.5597576",
"0.55696803",
"0.5566506",
"0.5529806",
"0.5504718",
"0.54967684",
"0.5455349",
... | 0.777694 | 0 |
Creates an interactive echelle environment with a variable deltanu slider. If you're working in a Jupyter notebook/lab environment, you must call `%matplotlib notebook` before running this. | def interact_echelle(
freq,
power,
dnu_min,
dnu_max,
step=None,
cmap="BuPu",
ax=None,
smooth=False,
smooth_filter_width=50.0,
scale=None,
return_coords=False,
backend="bokeh",
notebook_url="localhost:8888",
plot_method="fast",
sampling=2,
**kwargs
):
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def editor_example():\n agent_sensors = [sensors.RGBCamera, sensors.LocationSensor, sensors.VelocitySensor]\n agent = AgentDefinition(\"uav0\", agents.UavAgent, agent_sensors)\n env = HolodeckEnvironment([agent], start_world=False)\n env.agents[\"uav0\"].set_control_scheme(1)\n command = [0, 0, 10, ... | [
"0.54224694",
"0.52515614",
"0.5237333",
"0.5127714",
"0.5104529",
"0.5093767",
"0.50813234",
"0.5066324",
"0.4892671",
"0.48902854",
"0.48725274",
"0.48507506",
"0.48250785",
"0.48107544",
"0.47614673",
"0.4716767",
"0.46999207",
"0.46977425",
"0.46767718",
"0.4671984",
"0.4... | 0.4808876 | 14 |
Creates a color palette compatible with Bokeh from a matplotlib cmap name. | def get_bokeh_palette(cmap):
from bokeh.colors import RGB
from matplotlib import cm
# Solution adapted from
# https://stackoverflow.com/questions/31883097/elegant-way-to-match-a-string-to-a-random-color-matplotlib
m_RGB = (255 * plt.get_cmap(cmap)(range(256))).astype("int")
return [RGB(*tuple(r... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def palette_from_mpl_name(name):\n if name in CMAPS:\n return CMAPS[name]\n\n rgba = plt.get_cmap(name)(np.linspace(0, 1, 256))\n palette = [to_hex(color) for color in rgba]\n return palette",
"def get_palette(palette_name):\n\n if hasattr(plt.cm, palette_name):\n cmap = getattr(plt.... | [
"0.8101128",
"0.6942909",
"0.6776598",
"0.6741528",
"0.6741528",
"0.66666794",
"0.66659963",
"0.66659963",
"0.66659963",
"0.6503461",
"0.6470813",
"0.6413775",
"0.63696545",
"0.6352337",
"0.631037",
"0.61285675",
"0.61251086",
"0.6121512",
"0.6044165",
"0.60116994",
"0.601053... | 0.6990008 | 1 |
instead of return a cursor object, find_one() returns one document. so when you look up document by it's _id (_id field is always unique), use find_one() method. | def find_one():
fmter.tpl._straightline("one document", 100)
result = users.find_one({})
print(type(result))
ppt(result)
fmter.tpl._straightline("none result", 100)
result = users.find_one({"_id": 100})
print(type(result))
ppt(result) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def find_one(self, collection, query):\n obj = getattr(self.db, collection)\n result = obj.find_one(query)\n return result",
"def first(self, **kwargs):\n return self.find(**kwargs).first()",
"def one(self):\n try:\n return self[0]\n except IndexError:\n raise self.d... | [
"0.7754107",
"0.7186727",
"0.7182808",
"0.715503",
"0.69664955",
"0.6931495",
"0.69100857",
"0.6904317",
"0.6898412",
"0.6841113",
"0.68210936",
"0.6808862",
"0.679702",
"0.6777635",
"0.67716956",
"0.6718852",
"0.6685826",
"0.66839063",
"0.66428053",
"0.6642651",
"0.66407835"... | 0.7955518 | 0 |
because document can be nested, so you can use field.sub_field.subfield. ... to access children fields | def dot_notation():
ppt(list(
users.find({"profile.enthnicity": "asian"})
)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def subfield():\n return Subfield()",
"def _get_nested(nested_dict, field):\n print(nested_dict, field)\n keys = field.split('.')\n current = nested_dict\n for k in keys:\n print('key', k, 'current', current)\n # return None for nested fields without a value i... | [
"0.7141398",
"0.6325323",
"0.628575",
"0.62599593",
"0.6144266",
"0.59896255",
"0.5943311",
"0.58616906",
"0.5857536",
"0.5824355",
"0.57983726",
"0.5751088",
"0.56624633",
"0.56524676",
"0.5632159",
"0.56152475",
"0.56012654",
"0.5580025",
"0.5523471",
"0.5508865",
"0.549159... | 0.0 | -1 |
Fills out the model by invoking C{svnlook} | def _populateModel(self):
self.repoPath = self.argv[1]
self.rev = self.argv[2]
self.model.rev = self.rev
self.model.repo = os.path.split(self.repoPath)[-1]
self.prefix = (self.addRepoPrefix() and ('/' + self.model.repo)) or ''
# First, get the user and log message
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_model(self):\n pass # TODO: Implement this.",
"def build_model():",
"def update_model(self):\n pass",
"def updateModel(self):\n pass",
"def loadAdjustedModel(self):\r\n # Load model in GUI\r\n addModel(self.trcFilePath.replace('.trc','.osim'))",
"def makeMod... | [
"0.5480063",
"0.54420656",
"0.5437654",
"0.53411984",
"0.5257772",
"0.5196333",
"0.51816934",
"0.50881743",
"0.5072814",
"0.50495183",
"0.50386804",
"0.5009755",
"0.499261",
"0.49754384",
"0.49611595",
"0.49506703",
"0.49395007",
"0.4916408",
"0.4916408",
"0.49122566",
"0.491... | 0.69316125 | 0 |
Gera o codigo rml do cabecalho | def cabecalho(dic_cabecalho,dat_ordem,imagem):
tmp=''
tmp+='\t\t\t\t<image x="4.1cm" y="26.9cm" width="74" height="60" file="' + imagem + '"/>\n'
tmp+='\t\t\t\t<lines>3.3cm 26.3cm 19.5cm 26.3cm</lines>\n'
tmp+='\t\t\t\t<setFont name="Helvetica-Bold" size="15"/>\n'
tmp+='\t\t\t\t<drawString x="6.7cm... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load(self):",
"def mezclar_bolsa(self):",
"def load_ccs9():\n ccs9 = pd.read_csv(pkg_resources.resource_filename(__name__,'$dxref 2015.csv'))\n ccs9 = ccs9.reset_index()\n for col in ccs9.columns:\n ccs9.loc[:,col]=ccs9[col].str.strip('\\'')\n ccs9.columns=ccs9.iloc[0,:]\n ccs9 = ccs9... | [
"0.55839115",
"0.55125",
"0.53216106",
"0.5215636",
"0.5121315",
"0.5116958",
"0.51138484",
"0.5088174",
"0.49747437",
"0.4962377",
"0.49491808",
"0.49370742",
"0.4935785",
"0.4934977",
"0.49025398",
"0.4889983",
"0.48558292",
"0.4849866",
"0.48489085",
"0.48460174",
"0.48455... | 0.55939573 | 0 |
Gera o codigo rml do rodape | def rodape(lst_rodape):
tmp=''
tmp=''
tmp+='\t\t\t\t<lines>3.3cm 2.2cm 19.5cm 2.2cm</lines>\n'
tmp+='\t\t\t\t<setFont name="Helvetica" size="8"/>\n'
tmp+='\t\t\t\t<drawString x="3.3cm" y="2.4cm">' + lst_rodape[2] + '</drawString>\n'
tmp+='\t\t\t\t<drawString x="18.4cm" y="2.4cm">Página <pageNum... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rop():\n return",
"def lro(self) -> global___Snippet.Lro:",
"def get_rouge(ref_path, pred_path):\n print(\"###########cal rouge###############\")\n source_lines = [line.strip() for line in codecs.open(ref_path, \"r\", \"utf-8\").readlines()]\n pred_lines = [ pred.strip() for pred in codecs.open(pred_... | [
"0.6016394",
"0.598565",
"0.5746635",
"0.5739094",
"0.55431193",
"0.55244523",
"0.5518214",
"0.543907",
"0.54066896",
"0.53700364",
"0.5345745",
"0.5305402",
"0.52925533",
"0.5265397",
"0.5254321",
"0.5248294",
"0.52093405",
"0.5157794",
"0.5145444",
"0.51160425",
"0.5107024"... | 0.50784093 | 24 |
Gera o codigo rml que define o estilo dos paragrafos | def paraStyle():
tmp=''
tmp+='\t<stylesheet>\n'
tmp+='\t\t<blockTableStyle id="Standard_Outline">\n'
tmp+='\t\t\t<blockAlignment value="LEFT"/>\n'
tmp+='\t\t\t<blockValign value="TOP"/>\n'
tmp+='\t\t</blockTableStyle>\n'
tmp+='\t\t<initialize>\n'
tmp+='\t\t\t<paraStyle name="all" alignm... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def define_parameters(self):",
"def parameters(self):",
"def doParametersOfInterest(self):\n\n self.modelBuilder.doVar(\"Afb[0.6,-0.70,0.70]\");\n self.modelBuilder.doSet(\"POI\",\"Afb\")\n\n # ss templates\n self.modelBuilder.doVar(\"Rdy_mumu_ss[1.0,0.0,10.0]\");\n self.mode... | [
"0.64564425",
"0.6269693",
"0.604923",
"0.6017091",
"0.59432966",
"0.5927661",
"0.5904071",
"0.58930105",
"0.5876353",
"0.58385175",
"0.58262694",
"0.5811515",
"0.57941467",
"0.57618046",
"0.5759846",
"0.5745511",
"0.5650662",
"0.5646204",
"0.5636251",
"0.5623941",
"0.5610162... | 0.0 | -1 |
Funcao que gera o codigo rml da sessao plenaria | def pauta(lst_splen, lst_pauta):
tmp=''
#inicio do bloco
tmp+='\t<story>\n'
for dicsp in lst_splen:
#sessao plenaria
if dicsp['sessao']!=None:
tmp+='\t\t<para style="P0">' + dicsp['sessao'].replace('&','&') +', EM ' + dicsp['datasessao'].replace('&','&')+ '</para>... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def session(self):",
"def get_or_create_session(db):",
"def save_inscription():\n user = None\n f = InscriptionForm()\n if f.validate_on_submit() and f.uniq_Username() and f.passwd_confirmed():\n from hashlib import sha256\n m = sha256()\n m.update(f.get_mdp().encode())\n u... | [
"0.62706566",
"0.58388746",
"0.5836526",
"0.57945734",
"0.57002115",
"0.56958556",
"0.56462306",
"0.56462306",
"0.5479111",
"0.54686075",
"0.544465",
"0.543805",
"0.5410522",
"0.5397467",
"0.53923786",
"0.5386921",
"0.5382159",
"0.5382095",
"0.53573304",
"0.53492916",
"0.5332... | 0.0 | -1 |
Gera o codigo rml da assinatura | def presidente(lst_presidente):
tmp=''
tmp+='\t\t<para style="P3">\n'
tmp+='\t\t\t<font color="white"> </font>\n'
tmp+='\t\t</para>\n'
tmp+='\t\t<para style="P3">\n'
tmp+='\t\t\t<font color="white"> </font>\n'
tmp+='\t\t</para>\n'
tmp+='\t\t<para style="P3" spaceAfter="40">\n'
tmp+='... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def to_ir(self):",
"def mezclar_bolsa(self):",
"def __str__(self):\n return self.idBaixasReceber",
"def cliquer_sur_unité(self):",
"def encode(category_main : ):",
"def __init__(self,obj):\n self.nature_libelle = obj['NatureLibelle']\n self.ins_nom = obj['InsNom']\n self.i... | [
"0.5959136",
"0.5499816",
"0.54604596",
"0.5433409",
"0.53827584",
"0.52883506",
"0.5285676",
"0.5262863",
"0.5205403",
"0.5198016",
"0.51858664",
"0.5181811",
"0.5152689",
"0.51158124",
"0.5115277",
"0.510677",
"0.5100671",
"0.50992584",
"0.50992584",
"0.50992584",
"0.507903... | 0.0 | -1 |
Initializes a storage manager instance. | def __init__(self, app):
self.app = app
self.config = app.config['FILE_STORAGE']
self.secur = app.config['SECURITY_MANAGEMENT']['content']
if self.config['type'] == 's3':
# Boto s3 instance
if self.config['id'] != '' and self.config['key'] != '':
s... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self):\n config = self.read_config()\n self.deployment = config['deployment']\n self.deployment_config = config[self.deployment]\n logger.info(f'Initializing storage client with the {self.deployment} deployment config {pformat(self.deployment_config)}')\n\n # get the... | [
"0.6641924",
"0.6619307",
"0.6612643",
"0.6593752",
"0.6475286",
"0.6464472",
"0.63604945",
"0.63438195",
"0.62690544",
"0.62511116",
"0.6243224",
"0.6091188",
"0.6026038",
"0.60204107",
"0.6006953",
"0.5971609",
"0.59692246",
"0.59356165",
"0.592682",
"0.59250253",
"0.592312... | 0.0 | -1 |
Retreive a file from the file storage. | def storage_get_file(self, group='', key=''):
try:
obj = None
content = None
if key != '':
if self.config['type'] == 's3':
obj = self.s3.Object(bucket_name=self.bucket, key='corr-{0}s/{1}'.format(group,key))
res = obj.ge... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get(self, filename, **kw):\n\n file_path = os.path.join(self.storage_path, filename)\n try:\n file_obj = open(file_path, \"r\")\n except IOError:\n return\n else:\n return file_obj.read()",
"def get_file(URI):\n return file_fabric.get_class(URI)... | [
"0.78756535",
"0.7461347",
"0.7436858",
"0.7395782",
"0.7368263",
"0.7213877",
"0.72103053",
"0.713844",
"0.7136062",
"0.7094323",
"0.7046528",
"0.70224756",
"0.6999044",
"0.6987379",
"0.6954168",
"0.6929677",
"0.6907303",
"0.6901869",
"0.68689317",
"0.6859872",
"0.6847875",
... | 0.74737984 | 1 |
Make sure a content is free of malicious data. It called the antivirus ClamAV through its python interface to do the job. | def is_safe(self, content=None):
if not self.secur:
return [True, "Security is not required."]
else:
if content is not None:
cd = clamd.ClamdUnixSocket()
if cd.ping() == 'PONG':
cd.reload()
file_buffer = Byte... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_vulnerability(self):\n\t\tpass",
"def test_verifyDamaged(self):\n self.testObject.content.setContent('garbage!')\n self.assertRaises(CorruptObject, self.testObject.verify)",
"def malicious(self):\n return self.probably_malicious",
"def test_kyc_post_legal_share_holder(self):\n ... | [
"0.6266415",
"0.606212",
"0.5981505",
"0.58764136",
"0.56155235",
"0.5567562",
"0.5503536",
"0.5503536",
"0.54759705",
"0.54505795",
"0.53994906",
"0.5343958",
"0.53100395",
"0.52728504",
"0.52579534",
"0.52579534",
"0.51845664",
"0.5134979",
"0.5133656",
"0.5132123",
"0.5127... | 0.57496166 | 4 |
Upload a file into the s3 bucket. | def storage_upload_file(self, file_meta=None, file_obj=None):
if file_meta != None and file_obj != None:
m = hashlib.md5()
if file_meta.location == 'local':
dest_filename = file_meta.storage
try:
group = 'corr-resources'
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def upload_object(self, file_path, s3_path):\n logging.info(\"Uploading file to \\\"{}\\\" to S3\".format(s3_path))\n bucket_name, key = S3Util.get_bucket_and_key(s3_path)\n self.s3_resource.Bucket(bucket_name).upload_file(file_path, key)",
"def _upload_s3(self, filename, bucket, objectKey):... | [
"0.86530435",
"0.8389777",
"0.8361179",
"0.8325962",
"0.8258803",
"0.825059",
"0.8241126",
"0.82018214",
"0.8064815",
"0.8038341",
"0.80270815",
"0.79748935",
"0.7933823",
"0.78858334",
"0.78781134",
"0.7859663",
"0.7847567",
"0.78461665",
"0.783782",
"0.7817148",
"0.7810306"... | 0.0 | -1 |
Agent function that deletes a file in the storage. | def agent_delete(self, group, path, key):
found = False
for file_path in glob.glob('{0}/corr-{1}s'.format(path, group)):
if key in file_path:
os.remove(file_path)
found = True
break
return found | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete(self, filename, **kw):\n\n file_path = os.path.join(self.storage_path, filename)\n\n try:\n os.remove(file_path)\n except OSError:\n pass",
"def delete(self, filename):\n pass",
"def delete(self, host, file):",
"def delete_file(filename):\n\tprint ... | [
"0.78285897",
"0.7648353",
"0.7642585",
"0.760645",
"0.76037663",
"0.74779713",
"0.74424183",
"0.7431991",
"0.7220687",
"0.7075886",
"0.7070949",
"0.7070422",
"0.70667434",
"0.7064232",
"0.7057947",
"0.7055706",
"0.70467263",
"0.703922",
"0.7017835",
"0.69733405",
"0.69544697... | 0.0 | -1 |
Agent function that prepares a dictionary for storage in a compressed files. | def agent_prepare(self, zf, group, object_dict):
object_buffer = StringIO()
object_buffer.write(json.dumps(object_dict, sort_keys=True, indent=4, separators=(',', ': ')))
object_buffer.seek(0)
data = zipfile.ZipInfo("{0}.json".format(group))
data.date_time = time.localtime(time.t... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _files_from_json(self, file_json):\n self.compressed_file_json = zlib.compress(json.dumps(file_json).encode('utf-8'))\n self.compression_algorithm = 'gzip'\n self.compressed_content_hash = hashlib.sha256(self.compressed_file_json).hexdigest()",
"def file_to_dictionary():\n\n return;",... | [
"0.6145931",
"0.6029067",
"0.5845155",
"0.5629594",
"0.56274456",
"0.5606034",
"0.55619204",
"0.55617094",
"0.55312747",
"0.5409232",
"0.5396165",
"0.5389857",
"0.5363818",
"0.5336105",
"0.5334452",
"0.5315649",
"0.53133637",
"0.53003275",
"0.52949893",
"0.527997",
"0.5277781... | 0.62700593 | 0 |
Delete a file from the s3 bucket. | def storage_delete_file(self, group='', key=''):
deleted = False
if key not in ["default-logo.png", "default-picture.png"]:
if self.config['type'] == 's3':
s3_files = self.s3.Bucket(self.bucket)
for _file in s3_files.objects.all():
if _file... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_file(bucket, file_to_be_deleted):\n s3 = boto3.client('s3', aws_access_key_id=access_key, aws_secret_access_key=secret_key)\n s3.delete_object(Bucket=bucket, Key=file_to_be_deleted)\n print(file_to_be_deleted, \" : is deleted from the bucket\")",
"def delete_file_from_s3(bucket_name, filepath... | [
"0.86315507",
"0.82782817",
"0.8190081",
"0.7701372",
"0.7638301",
"0.76289713",
"0.7577905",
"0.7507077",
"0.74693567",
"0.74376506",
"0.73432124",
"0.73346096",
"0.7309587",
"0.72627354",
"0.7256304",
"0.71695846",
"0.71298283",
"0.7094936",
"0.7075884",
"0.70637834",
"0.70... | 0.0 | -1 |
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