code stringlengths 4 4.48k | docstring stringlengths 1 6.45k | _id stringlengths 24 24 |
|---|---|---|
def get_strategies(self): <NEW_LINE> <INDENT> return | 获取系统的所有策略。 | 625941c86e29344779a62676 |
def cap_test(text): <NEW_LINE> <INDENT> return text.capitalize() | Input text | 625941c8de87d2750b85fdf6 |
def terminal_test(self, game): <NEW_LINE> <INDENT> if not game.get_legal_moves(): <NEW_LINE> <INDENT> return True <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> return False | Return True if the game is over for the active player
and False otherwise. | 625941c85f7d997b87174afb |
@shared_task <NEW_LINE> def create_sip_for_record(recid, agent=None, user_id=432): <NEW_LINE> <INDENT> pid = PersistentIdentifier.get('recid', recid) <NEW_LINE> rec = ZenodoRecord.get_record(pid.object_uuid) <NEW_LINE> recsip = RecordSIP.query.filter_by( pid_id=pid.id).order_by(RecordSIP.created.desc()).first() <NEW_LI... | Create a new SIP if the record's files diverged from last SIPFiles.
:param agent: Agent JSON passed to the SIP.
:param user_id: ID of the user resposible for the SIP
(by default, user ID of info@zenodo.org) | 625941c838b623060ff0ae52 |
def getMethods(jclass): <NEW_LINE> <INDENT> return jclass.class_.getMethods()[:] | Returns an array containing Method objects reflecting all the public
member methods of the class or interface represented by this Class object,
including those declared by the class or interface and those inherited
from superclasses and superinterfaces. | 625941c83d592f4c4ed1d0d4 |
def print_error(msg: str, loc: Optional[str] = None) -> None: <NEW_LINE> <INDENT> if loc is None: <NEW_LINE> <INDENT> print(f"{col('[1;31m')}error:{col('[m')} {msg}", file=sys.stderr) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> print(f"{col('[1m')}{loc}: {col('[1;31m')}error:{col('[m')} {msg}", file=sys.stderr) | Prints a message with a (possibly colored) 'error: ' prefix. | 625941c85fcc89381b1e1722 |
def _setup_head_shape(fname, use_hpi=True): <NEW_LINE> <INDENT> idx_points, dig_points = _read_head_shape(fname) <NEW_LINE> idx_points, dig_points, t = _convert_head_shape(idx_points, dig_points) <NEW_LINE> all_points = np.r_[idx_points, dig_points].astype('>f4') <NEW_LINE> idx_idents = list(range(1, 4)) + list(range(1... | Read index points and dig points from BTi head shape file
Parameters
----------
fname : str
The absolute path to the head shape file
Returns
-------
dig : list of dicts
The list of dig point info structures needed for the fiff info
structure.
use_hpi : bool
Whether to treat additional hpi coils as dig... | 625941c829b78933be1e5711 |
def test_is_milestone_argument_is_skipped(self): <NEW_LINE> <INDENT> kwargs = copy.copy(self.kwargs) <NEW_LINE> kwargs.pop("is_milestone") <NEW_LINE> new_task = Task(**kwargs) <NEW_LINE> assert new_task.is_milestone is False | testing if the default value of the is_milestone attribute is going
to be False when the is_milestone argument is skipped | 625941c8f548e778e58cd5e1 |
def create_parser(): <NEW_LINE> <INDENT> parser = argparse.ArgumentParser(description=__doc__) <NEW_LINE> parser.add_argument('-d', '--dictionary', nargs='?', default='dictionaries/all_en_US.dict', help='Specify a non-default word dictionary to use.') <NEW_LINE> parser.add_argument('-c', '--count', help='Specify the nu... | Creates the Namespace object to be used by the rest of the tool | 625941c83346ee7daa2b2dcf |
def logp_xnext(self, particles, next_part, u, t): <NEW_LINE> <INDENT> N = len(particles) <NEW_LINE> return numpy.zeros((N,)) | Return the log-pdf value for the possible future state 'next'
given input u.
Always returns zeros since all particles are always equivalent for this
type of model
Args:
- particles (array-like): Model specific representation
of all particles, with first dimension = N (number of particles)
- next_part: Unused
... | 625941c8dd821e528d63b20e |
def get_message(url, initial_price, current_price, delta): <NEW_LINE> <INDENT> config = Configuration() <NEW_LINE> message = MESSAGE_TEMPLATE.format( url=url, initial_price=initial_price, current_price=current_price, delta=delta) <NEW_LINE> msg = MIMEText(message) <NEW_LINE> msg['To'] = ", ".join(formataddr(('Recipient... | Return the email message (body + headers). | 625941c8f7d966606f6aa067 |
def __init__(self, executable, args=None, cwd=None, env=None, stdout_handler=None, stderr_handler=None, output_encoding=None): <NEW_LINE> <INDENT> super().__init__() <NEW_LINE> self.executable = executable <NEW_LINE> self.args = args <NEW_LINE> self.cwd = cwd <NEW_LINE> self.envmerge = True <NEW_LINE> self._env = env <... | :param executable:
full path of the tool executable or just the tool program
name if it is in the system search path
:param args:
default args for command (list of strings)
:type args:
list
:param cwd:
program working directory
:param env:
environment dictionary
:param envmerge:
if set to Tr... | 625941c89b70327d1c4e0e39 |
def test_append_line_with_tab_data(self): <NEW_LINE> <INDENT> data = 'chr1\t10000\t20000\t+' <NEW_LINE> tabfile = TabFile('test',self.fp) <NEW_LINE> self.assertEqual(len(tabfile),3) <NEW_LINE> line = tabfile.append(tabdata=data) <NEW_LINE> self.assertEqual(len(tabfile),4) <NEW_LINE> self.assertTrue(str(line) == data) | Append line to a TabFile populated from tabbed data
| 625941c8566aa707497f45cf |
def preview_fees_public_api_using_post(self, wrapper_type_for_preview_conditions, **kwargs): <NEW_LINE> <INDENT> kwargs['_return_http_data_only'] = True <NEW_LINE> return self.preview_fees_public_api_using_post_with_http_info(wrapper_type_for_preview_conditions, **kwargs) | Preview offer fees # noqa: E501
This endpoint calculates fees for a provided offer conditions. The quotation is estimated and based on the current configuration of the Allegro price list and the data entered in this API. The stated price does not include package discounts. The rules of charging and amount of charges ... | 625941c86aa9bd52df036e08 |
def get_behaviour_data(self, behaviour_name): <NEW_LINE> <INDENT> behaviour_path = self._behaviours[behaviour_name] <NEW_LINE> module = __import__(behaviour_path, fromlist=[behaviour_path]) <NEW_LINE> behaviour = getattr(module, behaviour_name) <NEW_LINE> return behaviour, module | Returns the class and module of the given behaviour
Args:
behaviour_name: The name of the behaviour | 625941c8009cb60464c63416 |
def overload(func: Callable) -> Callable: <NEW_LINE> <INDENT> if not hasattr(func, '__annotations__'): <NEW_LINE> <INDENT> raise TypeError("Not type annotations found {}".format(func)) <NEW_LINE> <DEDENT> param_types: Dict[str, type] = {k: v for k, v in func.__annotations__.items() if k != 'return'} <NEW_LINE> args = _... | Decorator to allow overloading parameters of different types in python.
Be careful with this as python duck typing us awkward and this may not account for everything.
Useful for the visitor pattern.
Motivations:
Take this inheritance hierarchy as an example:
class A():
...
class B(... | 625941c88e7ae83300e4b030 |
def crop_cmap(cmapin, vmin, vmax, pivot=0): <NEW_LINE> <INDENT> cmapin = plt.get_cmap(cmapin) <NEW_LINE> return cmocean.tools.crop(cmapin, vmin, vmax, pivot) | Crop a colormap so that it is centered around pivot
This is a wrapper for :func:`cmocean.tools.crop`.
Parameters
----------
cmap: colormap
Compatible with :func:`matplotlib.pyplot.get_cmap`.
vmin: float
Min data value
vmax: float
Max data value
pivot: float
The colormap will be centered on this value.... | 625941c899fddb7c1c9de3f5 |
def check_config_values(keys, config): <NEW_LINE> <INDENT> missing = list() <NEW_LINE> for key in keys: <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> config[key] <NEW_LINE> <DEDENT> except KeyError: <NEW_LINE> <INDENT> missing.append(key) <NEW_LINE> logger.critical("'{:s}' missing from configuration".format(key)) <NEW_L... | Raise an exception if all keys in `keys` are not represented in `config`.
>>> check_config_values(['foo', 'bar'], {'foo': 'value'})
Traceback (most recent call last):
...
KeyError: "Missing configuration value(s): ['bar']"
>>> check_config_values(['foo'], {'foo': 'value'}) | 625941c8d268445f265b4ed2 |
def svn_delta_noop_window_handler(*args): <NEW_LINE> <INDENT> return _delta.svn_delta_noop_window_handler(*args) | svn_delta_noop_window_handler(svn_txdelta_window_t window, void * baton) -> svn_error_t | 625941c8236d856c2ad4483d |
def init_two_layer_convnet(weight_scale=1e-7, bias_scale=0, input_shape=(6, 8, 8), num_classes=64, num_filters=64, filter_size=3): <NEW_LINE> <INDENT> C, H, W = input_shape <NEW_LINE> assert filter_size % 2 == 1, 'Filter size must be odd; got %d' % filter_size <NEW_LINE> model = {} <NEW_LINE> model['W1'] = weight_scale... | Initialize the weights for a two-layer ConvNet.
Inputs:
- weight_scale: Scale at which weights are initialized. Default 1e-3.
- bias_scale: Scale at which biases are initialized. Default is 0.
- input_shape: Tuple giving the input shape to the network; default is
(3, 32, 32) for CIFAR-10.
- num_classes: The number o... | 625941c8a17c0f6771cbe0b6 |
def get_tensors(self, node_name, output_slot, debug_op, device_name=None): <NEW_LINE> <INDENT> watch_key = _get_tensor_watch_key(node_name, output_slot, debug_op) <NEW_LINE> try: <NEW_LINE> <INDENT> device_name = self._infer_device_name(device_name, node_name) <NEW_LINE> return [datum.get_tensor() for datum in self._wa... | Get the tensor value from for a debug-dumped tensor.
The tensor may be dumped multiple times in the dump root directory, so a
list of tensors (`numpy.ndarray`) is returned.
Parameters
----------
node_name: (`str`) name of the node that the tensor is produced by.
output_slot: (`int`) output slot index of tensor.
... | 625941c8be7bc26dc91cd666 |
def register_custom_filters(jinjaenv): <NEW_LINE> <INDENT> jinjaenv.filters['authorize'] = authorize <NEW_LINE> jinjaenv.filters['onlystaff'] = onlystaff <NEW_LINE> jinjaenv.filters['attrencode'] = _attrencode <NEW_LINE> jinjaenv.filters['cssencode'] = cssencode <NEW_LINE> jinjaenv.filters['to_json'] = _to_json <NEW_LI... | Register the filters to the given Jinja environment. | 625941c8a05bb46b383ec886 |
def is_state_equivalent(self, state1, state2): <NEW_LINE> <INDENT> return IAMRole.equivalent_states.get(state1) == IAMRole.equivalent_states.get(state2) | Determines if states are equivalent. Uses equivalent_states defined in the IAMRole class.
Args:
state1 (State):
state1 (State):
Returns:
bool | 625941c88e71fb1e9831d80e |
def remove_num_threads_option(args: List[str]) -> None: <NEW_LINE> <INDENT> for i in range(0, len(args)): <NEW_LINE> <INDENT> if args[i] == "-n": <NEW_LINE> <INDENT> del args[i : i + 2] <NEW_LINE> break | Remove -n <n> from argument list | 625941c863d6d428bbe44554 |
def decode(self, serialized_example, items=None): <NEW_LINE> <INDENT> context, sequence = tf.parse_single_sequence_example( serialized_example, self._context_keys_to_features, self._sequence_keys_to_features) <NEW_LINE> example = {} <NEW_LINE> example.update(context) <NEW_LINE> example.update(sequence) <NEW_LINE> all_f... | Decodes the given serialized TF-example. | 625941c84e4d5625662d443d |
def word_bank (word): <NEW_LINE> <INDENT> return r | randomly selects a string from a word bank | 625941c8d53ae8145f87a2d6 |
def add_isl_child(name, isl_device=ROOT_ISL_DEVICE): <NEW_LINE> <INDENT> if isl_device: <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> if not isl_device.started: <NEW_LINE> <INDENT> log = isl_device.start() <NEW_LINE> <DEDENT> <DEDENT> except AttributeError: <NEW_LINE> <INDENT> raise InvalidLogDeviceError() <NEW_LINE> <D... | Manage using an InspyLogger device with Inspyre Toolbox.
Args:
name:
The name you'd like for your log-device.
isl_device (inspy_logger.InspyLogger.device | None):
An instantiated inspy-logger device.
Returns:
The log device. | 625941c8fff4ab517eb2f4a0 |
def Insert(self, request, global_params=None): <NEW_LINE> <INDENT> config = self.GetMethodConfig('Insert') <NEW_LINE> return self._RunMethod( config, request, global_params=global_params) | Creates a new table.
Args:
request: (Table) input message
global_params: (StandardQueryParameters, default: None) global arguments
Returns:
(Table) The response message. | 625941c8442bda511e8be47e |
def setTPX(self,temperature:float=-1,pressure:float=-1,conditions_perturb:dict={}): <NEW_LINE> <INDENT> if temperature== -1: <NEW_LINE> <INDENT> temperature = self.temperature <NEW_LINE> <DEDENT> if pressure == -1: <NEW_LINE> <INDENT> pressure = self.pressure <NEW_LINE> <DEDENT> if conditions_perturb == {}: <NEW_LINE> ... | Set solution object for a simulation
Parameters
----------
temperature : float, optional
Temperature for simulation [K]. The default is -1.
pressure : float, optional
Pressure for simulation [P]. The default is -1.
conditions_perturb : dict, optional
Initial mole fractions for species in simulation. The de... | 625941c88c3a87329515841e |
def finalize(self): <NEW_LINE> <INDENT> self._close_output() <NEW_LINE> return | Finalize the simulation. | 625941c85510c4643540f44b |
def primal_lifting_cdf2x(decomp_src, decomp_wav): <NEW_LINE> <INDENT> decomp_wav -= div_ceil((decomp_src + numpy.append(decomp_src[1:], decomp_src[-1])), 2) <NEW_LINE> decomp_src += div_ceil((numpy.append(decomp_src[0], decomp_src[:-1]) + decomp_wav), 4) <NEW_LINE> return [decomp_src, decomp_wav] | CDF2/X基底によるPrimal Lifting | 625941c8d4950a0f3b08c3b4 |
def bitter_rivals(voting_dict): <NEW_LINE> <INDENT> ln = [ (policy_compare(name,least_similar(name,voting_dict),voting_dict),least_similar(name,voting_dict),name) for name in voting_dict ] <NEW_LINE> return (min(ln)[1],min(ln)[2]) | Input: a dictionary mapping senator names to lists representing
their voting records
Output: a tuple containing the two senators who most strongly
disagree with one another.
Example:
>>> voting_dict = {'Klein': [-1,0,1], 'Fox-Epstein': [-1,-1,-1], 'Ravella': [0,0,1]}
>>> bitter_rivals(voting_dic... | 625941c8cc40096d615959b5 |
def test_was_published_recently_with_old_question(self): <NEW_LINE> <INDENT> time = timezone.now() + datetime.timedelta(days=30) <NEW_LINE> old_question = Question(pub_date=time) <NEW_LINE> self.assertIs(old_question.was_published_recently(), False) | was_published_recently() should return False for questions whose
pub_date is older than 1 days | 625941c83c8af77a43ae3804 |
def format_single(self, element): <NEW_LINE> <INDENT> status = element[0:3] <NEW_LINE> channel = element[3] <NEW_LINE> data_name = element[4] <NEW_LINE> data_name = self.data_names[data_name] <NEW_LINE> if data_name in self.data_names_int: <NEW_LINE> <INDENT> value = int(float(element[5:])) <NEW_LINE> <DEDENT> else: <N... | Format single measurement value
:param element: Single measurement value read from the instrument
:type element: str
:return: Status (three digits), channel, data name, value
:rtype: (str, str, str, float) | 625941c8d10714528d5ffd47 |
def __init__(self): <NEW_LINE> <INDENT> self.ts = 0 <NEW_LINE> self.users = {} | Initialize your data structure here. | 625941c8e5267d203edcdd03 |
def is_in_cone(idx_a, idx_b, vllist): <NEW_LINE> <INDENT> n = len(vllist) <NEW_LINE> idx_a0 = idx_a - 1 <NEW_LINE> idx_a1 = (idx_a + 1) % n <NEW_LINE> a = vllist[idx_a] <NEW_LINE> b = vllist[idx_b] <NEW_LINE> a0 = vllist[idx_a0] <NEW_LINE> a1 = vllist[idx_a1] <NEW_LINE> if is_left_on(a, a1, a0): <NEW_LINE> <INDENT> ret... | returns true iff diagonal (idx_a, idx_b) is strictly internal to
the polygon in sht neighborhood of the endpoint | 625941c84e696a04525c94b0 |
def getRandom(self) -> int: <NEW_LINE> <INDENT> while True: <NEW_LINE> <INDENT> ch = random.choice(self.nums) <NEW_LINE> if ch is not None: <NEW_LINE> <INDENT> return ch | Get a random element from the set. | 625941c8e64d504609d748a4 |
def random_eye_type(): <NEW_LINE> <INDENT> mods = ["evil", "gay", "snek", "high", "ogre", "emoji", "small"] <NEW_LINE> eye_type = "" <NEW_LINE> for number_of_mods in range(0, random.randrange(0, len(mods))): <NEW_LINE> <INDENT> mod = random.choice(mods) <NEW_LINE> eye_type += mod <NEW_LINE> mods.remove(mod) <NEW_LINE> ... | A random eye type pos + mods | 625941c815baa723493c3fda |
def _get_conn2(service='cloudformation'): <NEW_LINE> <INDENT> if DEBUG: <NEW_LINE> <INDENT> print('[debug] Created conn2:resource:client.') <NEW_LINE> <DEDENT> return boto3.resource( service, aws_access_key_id=AWS_KEYID, aws_secret_access_key=AWS_KEY, region_name=AWS_REGION, ) | Generates a boto3 resource for the given service.
:param str service: The service to generate resource for.
Defaults to AWS CloudFormation.
Inherits Gitlab CI/CD environment variables:
- `AWS_KEYID`
- `AWS_KEY`
- `AWS_REGION` | 625941c82eb69b55b151c913 |
def isPalindrome(self, x): <NEW_LINE> <INDENT> if x < 0: <NEW_LINE> <INDENT> return False <NEW_LINE> <DEDENT> if x < 10: <NEW_LINE> <INDENT> return True <NEW_LINE> <DEDENT> length = int(math.log(x, 10) + 1) <NEW_LINE> while (length > 0): <NEW_LINE> <INDENT> first = x / 10 ** (length - 1) <NEW_LINE> last = x % 10 <NEW_L... | :type x: int
:rtype: bool | 625941c8097d151d1a222ebf |
def select(self): <NEW_LINE> <INDENT> warnings.filterwarnings("ignore", category=DeprecationWarning) <NEW_LINE> tgtScore, tgtModel = float("inf"), None <NEW_LINE> for components in range(self.min_n_components, self.max_n_components + 1): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> chModel = self.base_model(components)... | select the best model for self.this_word based on
BIC score for n between self.min_n_components and self.max_n_components
:return: GaussianHMM object | 625941c85e10d32532c5ef8c |
def getSourceSetAccessors(): <NEW_LINE> <INDENT> return zip(*getSourceSetNameList())[0] | Get a list of all accessor names for Source objects. | 625941c87cff6e4e811179eb |
def process_response(self, request, response): <NEW_LINE> <INDENT> s_id = request.session.get("YH_SID", None) <NEW_LINE> if s_id is None: <NEW_LINE> <INDENT> s_id = request.session["YH_SID"] = uuid.uuid4().hex <NEW_LINE> response.set_cookie( key="YH_SID", value=s_id, expires=datetime.now() + timedelta(days=common_const... | 用作用户统计
:param request:
:param response:
:return: | 625941c8656771135c3eb8d3 |
def char_map_eta_s_deriv(self, increment_filter, k): <NEW_LINE> <INDENT> f = self.char_map_eta_s_func <NEW_LINE> if not increment_filter[0, 0]: <NEW_LINE> <INDENT> self.jacobian[k, 0, 0] = self.numeric_deriv(f, 'm', 0) <NEW_LINE> <DEDENT> if not increment_filter[0, 1]: <NEW_LINE> <INDENT> self.jacobian[k, 0, 1] = self.... | Partial derivatives for compressor map characteristic.
Parameters
----------
increment_filter : ndarray
Matrix for filtering non-changing variables.
k : int
Position of derivatives in Jacobian matrix (k-th equation). | 625941c84527f215b584c4bd |
def _mouse_scroll_h(self, event): <NEW_LINE> <INDENT> args = (int(-1 * (event.delta / 120)), "units") <NEW_LINE> self._canvas_scroll.xview_scroll(*args) <NEW_LINE> self._canvas_ticks.xview_scroll(*args) | Callback for <Shift-MouseWheel> event for horizontal scrolling | 625941c8435de62698dfdcb1 |
def getPositionPdf(i): <NEW_LINE> <INDENT> return [int(i/5), i%5] | Return the position of the square on the pdf page | 625941c8b7558d58953c4f7b |
@testing.requires_testing_data <NEW_LINE> def test_source_psd_epochs(): <NEW_LINE> <INDENT> raw = read_raw_fif(fname_data) <NEW_LINE> inverse_operator = read_inverse_operator(fname_inv) <NEW_LINE> label = read_label(fname_label) <NEW_LINE> event_id, tmin, tmax = 1, -0.2, 0.5 <NEW_LINE> lambda2, method = 1. / 9., 'dSPM'... | Test multi-taper source PSD computation in label from epochs. | 625941c8091ae35668666fc5 |
def impulse(self, key): <NEW_LINE> <INDENT> self.key_impulses.add(key) | Ask for impulses to be emitted for a specific key. | 625941c826068e7796caed42 |
def get_wikipathways_reactome_df() -> pd.DataFrame: <NEW_LINE> <INDENT> return pd.read_csv(WIKIPATHWAYS_REACTOME_PATH, sep='\t') | Get WikiPathways-Reactome data. | 625941c83617ad0b5ed67f5d |
def ghash(self, nouce): <NEW_LINE> <INDENT> header_hash = self.header_hash() <NEW_LINE> token = ''.join((header_hash, str(nouce))).encode('utf-8') <NEW_LINE> return hashlib.sha256(token).hexdigest() | Block hash generate. | 625941c86fb2d068a760f101 |
def _generate_all_variables(self): <NEW_LINE> <INDENT> columns_larger_zero = get_columns_larger_zero(self.X) <NEW_LINE> columns_boolean = get_boolean_columns(self.X) <NEW_LINE> all_variables = [] <NEW_LINE> for exponent in range(2, self.max_exponent + 1): <NEW_LINE> <INDENT> for variable in self.variables: <NEW_LINE> <... | Generates all additional variables (exponents, roots, logs, interactions). Exponents are only generated for
non-boolean columns. Roots and logs are only generated for columns with every value larger than zero.
Overwrites self.variables with the new variables. | 625941c891af0d3eaac9ba7d |
def OnHelpButtonClicked(self,*args): <NEW_LINE> <INDENT> pass | OnHelpButtonClicked(self: Form,e: CancelEventArgs)
Raises the System.Windows.Forms.Form.HelpButtonClicked event.
e: A System.ComponentModel.CancelEventArgs that contains the event data. | 625941c810dbd63aa1bd2c09 |
def add_image(name,img_array): <NEW_LINE> <INDENT> detections, shapes, descriptors = detect_faces(person_database,img_array) <NEW_LINE> if len(descriptors)==0: <NEW_LINE> <INDENT> print("No people found.") <NEW_LINE> <DEDENT> elif len(descriptors)>1: <NEW_LINE> <INDENT> print("Multiple people detected. Picture can only... | Given a name and image of one person, logs person in database.
If person already exists, it updates, taking the average of the
current and given descriptor vectors.
:param:
name:str
name of person in image
file_path:str
path to file of image of person | 625941c86fece00bbac2d7a3 |
def _email_entry_changed(self, x, y): <NEW_LINE> <INDENT> ok_button = self.get_widget_for_response(gtk.RESPONSE_OK) <NEW_LINE> if self.email_entry.is_valid(): <NEW_LINE> <INDENT> ok_button.set_sensitive(True) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> ok_button.set_sensitive(False) | Disable the OK button if the email is invalid | 625941c885dfad0860c3aec0 |
def write_issues(r, csvout, repo): <NEW_LINE> <INDENT> if not r.status_code == 200: <NEW_LINE> <INDENT> raise Exception(r.status_code) <NEW_LINE> <DEDENT> for issue in r.json(): <NEW_LINE> <INDENT> labels = [] <NEW_LINE> for label in issue['labels']: <NEW_LINE> <INDENT> labels.append(label.get(u'name')) <NEW_LINE> <DED... | output a list of issues to csv | 625941c826068e7796caed43 |
def _trans_subdomain(data): <NEW_LINE> <INDENT> dname, sname = parse_name(data['DOMAIN'][0]) <NEW_LINE> subdomains.append({'name': sname, 'domain__name': dname}) <NEW_LINE> for role in ROLES & set(data.keys()): <NEW_LINE> <INDENT> sr = {'role': role, 'subdomain__name': sname, 'subdomain__domain__name': dname} <NEW_LINE... | transform subdomain item | 625941c81d351010ab855b81 |
@restricted <NEW_LINE> def check_result(bot, update): <NEW_LINE> <INDENT> user = update.message.from_user <NEW_LINE> area = [] <NEW_LINE> row = list(set(update.message.text.replace(' ', '').split(',')))[:10] <NEW_LINE> for i in row: <NEW_LINE> <INDENT> area_tmp = re.search(r'^[a-zA-Z]$', i) <NEW_LINE> if area_tmp is no... | Get the check results | 625941c8eab8aa0e5d26dbbd |
def variance(marks): <NEW_LINE> <INDENT> mean_mark = mean(marks) <NEW_LINE> num_total = 0 <NEW_LINE> for m in marks: <NEW_LINE> <INDENT> num_total += (m - mean_mark) ** 2 <NEW_LINE> <DEDENT> return num_total/len(marks) | Calculate the variance of the marks. | 625941c8cc0a2c11143dcef6 |
def gsw(self, X, Y, theta=None, p=1, L=1000): <NEW_LINE> <INDENT> N, dn = X.shape <NEW_LINE> M, dm = Y.shape <NEW_LINE> assert dn == dm and M == N <NEW_LINE> if theta is None: <NEW_LINE> <INDENT> theta = self.random_slice(dn, L) <NEW_LINE> <DEDENT> Xslices = self.get_slice(X, theta) <NEW_LINE> Yslices = self.get_slice(... | Calculates GSW between two empirical distributions.
Note that the number of samples is assumed to be equal
(This is however not necessary and could be easily extended
for empirical distributions with different number of samples) | 625941c8377c676e9127220e |
def safe_lower(p_str): <NEW_LINE> <INDENT> new_str = None <NEW_LINE> if p_str is not None: <NEW_LINE> <INDENT> if isinstance(p_str, str): <NEW_LINE> <INDENT> new_str = p_str.lower() <NEW_LINE> <DEDENT> <DEDENT> return new_str | Convert str to lower case | 625941c8046cf37aa974cdae |
def add(self, price): <NEW_LINE> <INDENT> self.__price[self.__count] = price <NEW_LINE> self.__count += 1 <NEW_LINE> if self.__count < self.__period: <NEW_LINE> <INDENT> return False <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> self.__count = 0 <NEW_LINE> cs_open = self.__price[0] <NEW_LINE> cs_high = max(self.__price... | 仮想通貨のカレントプライスを追加し、ローソク足情報ができたらTrueを戻す
:param price: カレントプライス
:return: １ローソク足が作れたらTrue | 625941c88a43f66fc4b540cb |
def get_fieldnames(host, index): <NEW_LINE> <INDENT> mappings = elsec.actions.get_mappings(host, index) <NEW_LINE> _temp = dict() <NEW_LINE> for m in mappings.values(): <NEW_LINE> <INDENT> _temp.update(m) <NEW_LINE> <DEDENT> return _collapse_mapping(_temp) | Return a list of names of all fields in mappings for the index.
Calls elsec.actions.get_mappings(), and then dot-collapses the field names
into mapping.object.fieldname format, returning a list of all the fields.
(This is later used for tab completions)
Input:
- host, index: str
Returns:
List of str, each element a... | 625941c8ff9c53063f47c259 |
def retract_bindings(self, bindings): <NEW_LINE> <INDENT> return retract_bindings(self, bindings) | :see: ``nltk.featstruct.retract_bindings()`` | 625941c8be383301e01b54ed |
def get_environment(self, environment_id, **kwargs): <NEW_LINE> <INDENT> if environment_id is None: <NEW_LINE> <INDENT> raise ValueError('environment_id must be provided') <NEW_LINE> <DEDENT> headers = {} <NEW_LINE> if 'headers' in kwargs: <NEW_LINE> <INDENT> headers.update(kwargs.get('headers')) <NEW_LINE> <DEDENT> pa... | Get environment info.
:param str environment_id: The ID of the environment.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse | 625941c83cc13d1c6d3c73e0 |
def __init__(__self__, *, backup_vault_arn: Optional[pulumi.Input[str]] = None, backup_vault_events: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, backup_vault_name: Optional[pulumi.Input[str]] = None, sns_topic_arn: Optional[pulumi.Input[str]] = None): <NEW_LINE> <INDENT> if backup_vault_arn is not None:... | Input properties used for looking up and filtering VaultNotifications resources.
:param pulumi.Input[str] backup_vault_arn: The ARN of the vault.
:param pulumi.Input[Sequence[pulumi.Input[str]]] backup_vault_events: An array of events that indicate the status of jobs to back up resources to the backup vault.
:param pul... | 625941c8004d5f362079a399 |
def dropout_forward(x, dropout_param): <NEW_LINE> <INDENT> p, mode = dropout_param['p'], dropout_param['mode'] <NEW_LINE> if 'seed' in dropout_param: <NEW_LINE> <INDENT> np.random.seed(dropout_param['seed']) <NEW_LINE> <DEDENT> mask = None <NEW_LINE> out = None <NEW_LINE> if mode == 'train': <NEW_LINE> <INDENT> pass <N... | Performs the forward pass for (inverted) dropout.
Inputs:
- x: Input data, of any shape
- dropout_param: A dictionary with the following keys:
- p: Dropout parameter. We keep each neuron output with probability p.
- mode: 'test' or 'train'. If the mode is train, then perform dropout;
if the mode is test, then ... | 625941c86aa9bd52df036e09 |
def get_gosubdagplot(self, godag, kws_plt): <NEW_LINE> <INDENT> goids, go2color = CliGetGOs(godag).get_go_color(**kws_plt) <NEW_LINE> assert goids, "GO IDs NEEDED" <NEW_LINE> kws_dag = self._get_kwsdag(goids, godag, **kws_plt) <NEW_LINE> relationships = self._get_relationships(kws_plt, hasattr(next(iter(godag.values())... | Get GoSubDagPlot | 625941c8b545ff76a8913e7c |
def get_synset(line): <NEW_LINE> <INDENT> original = line.strip() <NEW_LINE> pos = original[0] <NEW_LINE> offset = int(original[1:]) <NEW_LINE> synset = wn.synset_from_pos_and_offset(pos, offset) <NEW_LINE> return original, pos, offset, synset | Produce synset from a line containing offset ID. | 625941c801c39578d7e74ea1 |
def changeColor(id, newColor): <NEW_LINE> <INDENT> _canvas.itemconfigure(id, fill=newColor) | Change the color of an item. | 625941c894891a1f4081bb0e |
def remove_item(self, kernel_name: str) -> Optional[CacheItemType]: <NEW_LINE> <INDENT> cache_item = None <NEW_LINE> if self.cache_enabled: <NEW_LINE> <INDENT> if kernel_name.lower() in self.cache_items: <NEW_LINE> <INDENT> cache_item = self.cache_items.pop(kernel_name.lower()) <NEW_LINE> self.log.info("KernelSpecCache... | Removes the cache item corresponding to kernel_name from the cache. | 625941c855399d3f05588719 |
def srwl_uti_write_data_cols(_file_path, _cols, _str_sep, _str_head=None, _i_col_start=0, _i_col_end=-1): <NEW_LINE> <INDENT> f = open(_file_path, 'w') <NEW_LINE> if(_str_head != None): <NEW_LINE> <INDENT> lenStrHead = len(_str_head) <NEW_LINE> if(lenStrHead > 0): <NEW_LINE> <INDENT> strHead = _str_head <NEW_LINE> if(_... | Auxiliary function to write tabulated data (columns, i.e 2D table) to ASCII file
:param _file_path: full path (including file name) to the file to be (over-)written
:param _cols: array of data columns to be saves to file
:param _str_sep: column separation symbol(s) (string)
:param _str_head: header (string) to write be... | 625941c86fb2d068a760f102 |
def compare_sessions_to_text(pathserv, pathserv_other): <NEW_LINE> <INDENT> count_bads = ins.CountBads() <NEW_LINE> comparison = extractors.CollectSessionComparisonData(pathserv, pathserv_other, count_bads.count_bads) <NEW_LINE> text = reports.report_session_comparison(comparison) <NEW_LINE> return text | compares two sessions, returns text | 625941c8d53ae8145f87a2d7 |
def isInBoundsHalf(self, x, y, Color): <NEW_LINE> <INDENT> if Color == WHITE: <NEW_LINE> <INDENT> if y >= 0 and y <= 4 and x >= 0 and x < 9: <NEW_LINE> <INDENT> return True <NEW_LINE> <DEDENT> return False <NEW_LINE> <DEDENT> elif Color == BLACK: <NEW_LINE> <INDENT> if y >= 5 and y <= 9 and x >= 0 and x < 9: <NEW_LINE>... | checks if a position is on the half board | 625941c8a4f1c619b28b00a1 |
def Digitization(sTree, SmearedHits): <NEW_LINE> <INDENT> Hits = [] <NEW_LINE> for i in range(len(SmearedHits)): <NEW_LINE> <INDENT> xtop=SmearedHits[i]['xtop'] <NEW_LINE> xbot=SmearedHits[i]['xbot'] <NEW_LINE> ytop=SmearedHits[i]['ytop'] <NEW_LINE> ybot=SmearedHits[i]['ybot'] <NEW_LINE> ztop=SmearedHits[i]['z'] <NEW_L... | Digitizes hit for the track pattern recognition.
Parameters
----------
sTree : root file
Events in raw format.
SmearedHits : list of dicts
List of smeared hits. A smeared hit is a dictionary:
{'digiHit':key,'xtop':top x,'ytop':top y,'z':top z,'xbot':bot x,'ybot':bot y,'dist':smeared dist2wire}
Retruns
---... | 625941c830dc7b76659019cd |
def updateStatusBar(self): <NEW_LINE> <INDENT> if not hasattr(self, 'size_label'): <NEW_LINE> <INDENT> return <NEW_LINE> <DEDENT> df = self.table.model.df <NEW_LINE> meminfo = self.table.getMemory() <NEW_LINE> s = '{r} rows x {c} columns | {m}'.format(r=len(df), c=len(df.columns),m=meminfo) <NEW_LINE> self.size_label.s... | Update the table details in the status bar | 625941c8167d2b6e31218bfc |
def _run_container(self, docker_client) -> docker.models.containers.Container: <NEW_LINE> <INDENT> base_image = self._get_base_image() <NEW_LINE> try: <NEW_LINE> <INDENT> container = docker_client.containers.run( base_image, command="sleep {}".format(TIME_OUT), auto_remove=True, remove=True, detach=True) <NEW_LINE> <DE... | Build the container which contains a Python interpreter. | 625941c8956e5f7376d70ed4 |
def toString( obj ): <NEW_LINE> <INDENT> return obj.toString() if hasattr( obj, 'toString' ) else obj | Use this on QString objects if you can't force PyQt4 into APIv2 mode. | 625941c892d797404e3041ef |
def fully_connected(inputs, num_outputs, scope, use_xavier=True, stddev=1e-3, weight_decay=0.0, activation_fn=tf.nn.relu, bn=False, bn_decay=None, is_training=None): <NEW_LINE> <INDENT> with tf2.variable_scope(scope) as sc: <NEW_LINE> <INDENT> num_input_units = inputs.get_shape()[-1].value <NEW_LINE> weights = _variabl... | Fully connected layer with non-linear operation.
Args:
inputs: 2-D tensor BxN
num_outputs: int
Returns:
Variable tensor of size B x num_outputs. | 625941c8187af65679ca5184 |
def totalFruit(self, tree): <NEW_LINE> <INDENT> dic = collections.Counter() <NEW_LINE> start, res =0,0 <NEW_LINE> for i in range(len(tree)): <NEW_LINE> <INDENT> dic[tree[i]] += 1 <NEW_LINE> while len(dic) > 2: <NEW_LINE> <INDENT> dic[tree[start]] -= 1 <NEW_LINE> if dic[tree[start]] == 0: <NEW_LINE> <INDENT> del dic[tre... | :type tree: List[int]
:rtype: int | 625941c82c8b7c6e89b35827 |
def all_results(self): <NEW_LINE> <INDENT> if self.test_session_setup: <NEW_LINE> <INDENT> yield self.test_session_setup <NEW_LINE> <DEDENT> for result in flatten_results(self.get_suites()): <NEW_LINE> <INDENT> yield result <NEW_LINE> <DEDENT> if self.test_session_teardown: <NEW_LINE> <INDENT> yield self.test_session_t... | An iterator over all results (tests, setups, teardowns) contained in the report. | 625941c8ad47b63b2c509fe5 |
def run(): <NEW_LINE> <INDENT> if FLAGS.enable_mlir_bridge: <NEW_LINE> <INDENT> tf.config.experimental.enable_mlir_bridge() <NEW_LINE> <DEDENT> strategy = distribute_utils.get_distribution_strategy( distribution_strategy=FLAGS.distribution_strategy, tpu_address=FLAGS.tpu) <NEW_LINE> if strategy: <NEW_LINE> <INDENT> log... | Runs NHNet using Keras APIs. | 625941c8e5267d203edcdd04 |
def test_update_counter(self): <NEW_LINE> <INDENT> hostname = '10.72.168.3' <NEW_LINE> nmap_xml = NmapXML(self.printer_file) <NEW_LINE> host = nmap_xml.parse_xml() <NEW_LINE> assert host <NEW_LINE> printer = nmap_xml.identify_host(hostname) <NEW_LINE> self.assertIsInstance(printer, Printer) <NEW_LINE> printer_counter =... | Testa inserção dos parâmetros do contador em impressora existente | 625941c84a966d76dd551074 |
def checkBlacklist(client, message): <NEW_LINE> <INDENT> rowCount, retval, exists = lib.db.queryDatabase( "SELECT is_blacklisted FROM chronicles_info WHERE channel_id={id}". format(id=str(message.channel.id)), client, message.channel, tablename="chronicles_info", getResult=True, closeConn=True) <NEW_LINE> if exists == ... | Functions That Checks the Database to See if the Channel is Blacklisted
Parameters:
-----------
client (discord.Client)
The Chronicler Client
message (discord.Message)
The Message of the Channel to Check | 625941c84e696a04525c94b1 |
def VVI(image): <NEW_LINE> <INDENT> return (1 - abs((image[:,:,R] - 30) / (image[:,:,R] + 30))) * (1 - abs((image[:,:,G] - 50) / (image[:,:,G] + 50))) * (1 - abs((image[:,:,B] - 1) / (image[:,:,B] + 1))) | Returns Visible Vegetation Index
http://phl.upr.edu/projects/visible-vegetation-index-vvi | 625941c832920d7e50b28235 |
def build_centre(gene, condi): <NEW_LINE> <INDENT> center_list = [] <NEW_LINE> for i in range(len(gene.junctionL)): <NEW_LINE> <INDENT> column_values = [] <NEW_LINE> for sample in gene.conditions[condi]: <NEW_LINE> <INDENT> column_values.append(gene.conditions[condi][sample][i]) <NEW_LINE> <DEDENT> if len(column_values... | build centre
:type gene: Gene
:type condi: str
:rtype : list | 625941c8925a0f43d2549edc |
def getAttrs(self): <NEW_LINE> <INDENT> return self.attrs | Returns attr | 625941c816aa5153ce3624de |
def __init__(self, bucket=None): <NEW_LINE> <INDENT> self.s3_conn = boto.connect_s3() <NEW_LINE> if bucket is not None: <NEW_LINE> <INDENT> self.bucket = bucket <NEW_LINE> <DEDENT> get_required_env_variable('AWS_ACCESS_KEY_ID') <NEW_LINE> get_required_env_variable('AWS_SECRET_ACCESS_KEY') | Establish connections.
Assume credentials are in environment or
in a config file. | 625941c86e29344779a62678 |
def isUnique(attr, value): <NEW_LINE> <INDENT> pass | Determine whether a given LDAP attribute (attr) and its value (value)
are unique in the LDAP tree branch set as the user record base in the
LDAPUserFolder. This method should be called before inserting a new
user record with attr being the attribute chosen as the login name in
your LDAPUserFolder because that attribu... | 625941c8ff9c53063f47c25a |
def lists(): <NEW_LINE> <INDENT> n = "Stevens is awesome" <NEW_LINE> p = n.split(' ') <NEW_LINE> r = p[2][1:] <NEW_LINE> import numpy as np <NEW_LINE> c = np.array([[1,4,5], [6,10,11], [12,17,38]]) <NEW_LINE> print(c[:,2]) <NEW_LINE> d = [x for x in c.diagonal() if x % 2 == 0] <NEW_LINE> o = [ord(x) for x in (p[0])] <N... | This is to review basic operations with lists. | 625941c8baa26c4b54cb1186 |
def to_dict(self, convert=True): <NEW_LINE> <INDENT> attrlist = [a for a in list(self.__dict__.keys()) if not a.startswith('_')] <NEW_LINE> data = {} <NEW_LINE> for name in attrlist: <NEW_LINE> <INDENT> attr_data = getattr(self, name, None) <NEW_LINE> if not convert: <NEW_LINE> <INDENT> data[name] = attr_data <NEW_LINE... | Extend Ablity To Dict Orm Object Data | 625941c838b623060ff0ae54 |
def munge_source(v): <NEW_LINE> <INDENT> lines = v.split('\n') <NEW_LINE> if not lines: <NEW_LINE> <INDENT> return tuple(), '' <NEW_LINE> <DEDENT> firstline = lines[0].lstrip() <NEW_LINE> while firstline == '' or firstline[0] == '@': <NEW_LINE> <INDENT> del lines[0] <NEW_LINE> firstline = lines[0].lstrip() <NEW_LINE> <... | Take Python source code, return a pair of its parameters and the rest of it dedented | 625941c891f36d47f21ac558 |
def set_value(slack_username, channel, charval): <NEW_LINE> <INDENT> character, key, value = charval[0], charval[1], charval[2] <NEW_LINE> character_channel = character.lower() + channel.lower() <NEW_LINE> try: <NEW_LINE> <INDENT> response = dbot.update_item( Key={ 'character_channel': character_channel }, UpdateExpres... | Sets a stat of the character record passed | 625941c8460517430c3941ed |
def parse_time(self, time_string): <NEW_LINE> <INDENT> parssed_time = re.findall(r'(\d+)(\s?)(\D+)', time_string) <NEW_LINE> if len(parssed_time) > 0: <NEW_LINE> <INDENT> inTime = int(parssed_time[0][0]) <NEW_LINE> inUnit = parssed_time[0][2] <NEW_LINE> if 's' in inUnit[0] or 'S' in inUnit[0]: <NEW_LINE> <INDENT> timeM... | Parses a <number><unit> i.e. 60s to a fncs timestep number.
:param time_string:
:return: | 625941c83eb6a72ae02ec541 |
def _metadata_db_name(self): <NEW_LINE> <INDENT> my_metadata_dir = os.path.join( self.global_conf['metadata']['metadata_path'], self.METADATA_SUBDIR ) <NEW_LINE> if not os.path.isdir(my_metadata_dir): <NEW_LINE> <INDENT> os.makedirs(my_metadata_dir) <NEW_LINE> <DEDENT> return os.path.join(my_metadata_dir, self.source_n... | Figure out where to keep this source's Metadata | 625941c8f9cc0f698b140662 |
def parse_args(): <NEW_LINE> <INDENT> parser = argparse.ArgumentParser() <NEW_LINE> parser.add_argument( "--file", type=str, default="train.jsonl", ) <NEW_LINE> args = parser.parse_args() <NEW_LINE> return args | Parse args. | 625941c87c178a314d6ef4c4 |
def __init__(self, model_file=None, do_lower_case=True, normalize_text=True, never_split=None): <NEW_LINE> <INDENT> self.tokenizer = sp.SentencePieceProcessor() <NEW_LINE> if self.tokenizer.Load(model_file): <NEW_LINE> <INDENT> print("Loaded a trained SentencePiece model.") <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT>... | Constructs a SentencePieceTokenizer. | 625941c8283ffb24f3c55968 |
def __init__(self): <NEW_LINE> <INDENT> self.data = [] <NEW_LINE> self.min_stack = [] <NEW_LINE> self.min_value = 0 | initialize your data structure here. | 625941c896565a6dacc8f732 |
def findKthLargest(self, nums, k): <NEW_LINE> <INDENT> nums.sort() <NEW_LINE> print(nums) <NEW_LINE> print(nums[len(nums)-k]) <NEW_LINE> return (nums[len(nums)-k]) | :type nums: List[int]
:type k: int
:rtype: int | 625941c8be383301e01b54ee |
def change_baudrate(self, baudrate_for_ids): <NEW_LINE> <INDENT> self._change_baudrate(baudrate_for_ids) <NEW_LINE> for motor_id in baudrate_for_ids.iterkeys(): <NEW_LINE> <INDENT> if motor_id in self._known_models: <NEW_LINE> <INDENT> del self._known_models[motor_id] <NEW_LINE> <DEDENT> if motor_id in self._known_mode... | Changes the baudrate of the specified motors. | 625941c85e10d32532c5ef8d |
def serialize_numpy(self, buff, numpy): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> length = len(self.costs) <NEW_LINE> buff.write(_struct_I.pack(length)) <NEW_LINE> pattern = '<%sd'%length <NEW_LINE> buff.write(self.costs.tostring()) <NEW_LINE> length = len(self.gradient) <NEW_LINE> buff.write(_struct_I.pack(length))... | serialize message with numpy array types into buffer
:param buff: buffer, ``StringIO``
:param numpy: numpy python module | 625941c88e7ae83300e4b033 |
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