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def python(self, cmd):
"""Execute a python script using the virtual environment python."""
python_bin = self.cmd_path('python')
cmd = '{0} {1}'.format(python_bin, cmd)
return self._execute(cmd) | [
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def put_file(self, remote_path, local_source_file, **kwargs):
"""Upload a file
:param remote_path: path to the target file. A target directory can
also be specified instead by appending a "/"
:param local_source_file: path to the local file to upload
:param chunked: (optiona... | [
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def impact_table_extractor(impact_report, component_metadata):
"""Extracting impact summary of the impact layer.
:param impact_report: the impact report that acts as a proxy to fetch
all the data that extractor needed
:type impact_report: safe.report.impact_report.ImpactReport
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def _build_callback(self, config):
''' Apply plugins to a route and return a new callable. '''
wrapped = config['callback']
plugins = self.plugins + config['apply']
skip = config['skip']
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def process_from_webservice(id_val, id_type='pmcid', source='pmc',
with_grounding=True):
"""Return an output from RLIMS-p for the given PubMed ID or PMC ID.
Parameters
----------
id_val : str
A PMCID, with the prefix PMC, or pmid, with no prefix, of the paper to
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def command(self, verb, args=None):
"""Call a command on the server.
If the user has not authenticated then authentication will be done
as part of calling the command on the server.
For commands that don't return a status message the status message
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def parse_dash(string, width):
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n = len(string)
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def difference(self, sig: Scope) -> Scope:
""" Create a new Set produce by a Set subtracted by another Set """
new = Scope(sig=self._hsig.values(), state=self.state)
new -= sig
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def match_events(ref, est, window, distance=None):
"""Compute a maximum matching between reference and estimated event times,
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Given two lists of event times ``ref`` and ``est``, we seek the largest set
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def run_module(mod_name, init_globals=None,
run_name=None, alter_sys=False):
"""Execute a module's code without importing it
Returns the resulting top level namespace dictionary
"""
mod_name, loader, code, fname = _get_module_details(mod_name)
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def get(self, project):
"""Query the project status. Returns a ``CLAMData`` instance or raises an exception according to the returned HTTP Status code"""
try:
data = self.request(project + '/')
except:
raise
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def format(self, **kwargs):
"""Apply formatting."""
attrs = self._attrs.copy()
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def _get_user_class(self, name):
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def getvector(d,s):
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Get a vector flds data.
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d -- flds data.
s -- key for the data.
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def copy_files(files_type, class_dir, output):
"""Copies the files from the input folder to the output folder
"""
# get the last part within the file
class_name = path.split(class_dir)[1]
for (files, folder_type) in files_type:
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def _sentiment(self, distance=True):
"""Calculates the sentiment of an entity as it appears in text."""
sum_pos = 0
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def _find_first_of(line, substrings):
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def make_batches(paths: Sequence[Path], batch_size: int) -> List[Sequence[Path]]:
""" Group utterances into batches for decoding. """
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def output(self):
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def str_count(x, pat, regex=False):
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def set_state(self, state):
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def new() -> ulid.ULID:
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def move_page_bottom(self):
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Move the cursor to the last item on the page.
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def project(*args, **kwargs):
"""
Build a projection for MongoDB.
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def init_db(self):
'''这个任务数据库只在程序开始时读入, 在程序关闭时导出.
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def _make_expand_x_fn_for_batch_interpolation(y_ref, axis):
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def upload_job_chunk_list(self, upload_job_id, **kwargs): # noqa: E501
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def _get_env(self):
"""this returns an environment dictionary we want to use to run the command
this will also create a fake pgpass file in order to make it possible for
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if hasattr(self, 'env'): return self.env
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def _from_timeseries(ts1, ts2, stride, fftlength=None, overlap=None,
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"""Generate a time-frequency coherence
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def lock_access(repository_path, callback):
""" Synchronise access to the user file between processes, this specifies
which user is allowed write access at the current time """
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def _get_key_info(self):
"""Get key info appropriate for signing: either from the ssh agent
or from a private key.
"""
if self._key_info_cache is not None:
return self._key_info_cache
errors = []
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def _download_datasets():
"""Utility to download datasets into package source"""
def filepath(*args):
return abspath(join(dirname(__file__), '..', 'vega_datasets', *args))
dataset_listing = {}
for name in DATASETS_TO_DOWNLOAD:
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url = data.url
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def busmap_from_psql(network, session, scn_name):
""" Retrieves busmap from `model_draft.ego_grid_pf_hv_busmap` on the
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def set_depth_range(self, near=0., far=1.):
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Near clipping plane.
far : float
Far clipping plane.
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def plugin_privileges(self, name):
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Retrieve list of privileges to be granted to a plugin.
Args:
name (string): Name of the remote plugin to examine. The
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def parse_typing_status_message(p):
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def print_solution(solution):
"""Prints a solution
Arguments
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solution : BaseSolution
Example
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::
[8, 9, 10, 7]: 160
[5, 6]: 131
[3, 4, 2]: 154
Total cost: 445
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def set_style(self, *args, **kwargs):
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def __delete_represented_points(self, cluster):
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@brief Remove representation points of clusters from the k-d tree
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def dynamic_number_format(self, rb=1, align=1, **fmt_args):
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fct = fmt.DynamicNumberFormatter(**fmt_args)
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def map_peaks_to_image(peaks, r=4, vox_dims=(2, 2, 2), dims=(91, 109, 91),
header=None):
""" Take a set of discrete foci (i.e., 2-D array of xyz coordinates)
and generate a corresponding image, convolving each focus with a
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def _handle_match(client, channel, nick, message, matches):
""" Match stores all channel info. If helga is asked something to
stimulate a markov response about channel data, then we shall graciously
provide it.
"""
generate_interrogative = _CHANNEL_GENERATE_REGEX.match(message)
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def modeled_savings(
baseline_model,
reporting_model,
result_index,
temperature_data,
with_disaggregated=False,
confidence_level=0.90,
predict_kwargs=None,
):
""" Compute modeled savings, i.e., savings in which baseline and reporting
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def object_build_methoddescriptor(node, member, localname):
"""create astroid for a living method descriptor object"""
# FIXME get arguments ?
func = build_function(
getattr(member, "__name__", None) or localname, doc=member.__doc__
)
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def run_check_kind(_):
'''
Running the script.
'''
for kindv in router_post:
for rec_cat in MCategory.query_all(kind=kindv):
catid = rec_cat.uid
catinfo = MCategory.get_by_uid(catid)
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def parse_setup(filepath):
'''Get the kwargs from the setup function in setup.py'''
# TODO: Need to parse setup.cfg and merge with the data from below
# Monkey patch setuptools.setup to capture keyword arguments
setup_kwargs = {}
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def _func_addrs_from_symbols(self):
"""
Get all possible function addresses that are specified by the symbols in the binary
:return: A set of addresses that are probably functions
:rtype: set
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def start_processes(self, max_restarts=-1):
"""
Start processes and check their status. When some process crashes,
start it again. *max_restarts* is maximum amount of the restarts
across all processes. *processes* is a :class:`list` of the
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def set_result(self, result):
"""Sets the return value of work associated with the future.
Should only be used by Task and unit tests.
"""
self._result = result
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def reduced_to_matrix(shape, degree, vals_by_weight):
r"""Converts a reduced values dictionary into a matrix.
.. note::
This is a helper used only by :func:`_specialize_surface`.
The ``vals_by_weight`` mapping has keys of the form:
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def make_field(self, **kwargs):
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def pathFromHere_explore(self, astr_startPath = '/'):
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Return a list of paths from "here" in the stree, using the
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def _calculatePredictedCells(self, activeBasalSegments, activeApicalSegments):
"""
Calculate the predicted cells, given the set of active segments.
An active basal segment is enough to predict a cell.
An active apical segment is *not* enough to predict a cell.
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def log_transition(self, transition, from_state, instance, *args, **kwargs):
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Args:
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def walk(self, address):
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def join(*vectors):
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Takes an arbitrary number of aligned vectors of the same length and combines
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def dump(type, exc):
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"""
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def main():
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# Initialize logging to the terminal.
coloredlogs.install()
# Command line option defaults.
repository = None
revision = None
actions = []
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def get_feats(self, doc):
'''
Parameters
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doc, Spacy Docs
Returns
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Counter noun chunk -> count
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Start the given node VM.
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log.debug("_start_node: working on node `%s`", node.name)
# FIXME: the following check is not optimal yet. When a node is still
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def rest_api_exists(self, rest_api_id):
# type: (str) -> bool
"""Check if an an API Gateway REST API exists."""
client = self._client('apigateway')
try:
client.get_rest_api(restApiId=rest_api_id)
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def publications(columns, n_results, queries):
"""Search for publications"""
if not isinstance(queries, dict):
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for q in queries:
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def defaulted_config(modules, params=None, yaml=None, filename=None,
config=None, validate=True):
"""Context manager version of :func:`set_default_config()`.
Use this with a Python 'with' statement, like
>>> config_yaml = '''
... toplevel:
... param: value
... '''
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def save_method(elements, module_path):
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for elem, signature in elements.items():
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def external_metadata(self, datasource_type=None, datasource_id=None):
"""Gets column info from the source system"""
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datasource = ConnectorRegistry.get_datasource(
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def update(cls, id, params):
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cls.echo('Updating your vlan.')
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def applet_remove_tags(object_id, input_params={}, always_retry=True, **kwargs):
"""
Invokes the /applet-xxxx/removeTags API method.
For more info, see: https://wiki.dnanexus.com/API-Specification-v1.0.0/Tags#API-method%3A-%2Fclass-xxxx%2FremoveTags
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def get(self, study_id, content=None, schema=None, **kwargs):
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def user_absent(name, htpasswd_file=None, runas=None):
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Make sure the user is not in the specified htpasswd file
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User name
htpasswd_file
Path to the htpasswd file
runas
The system user to run htpasswd command with
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def get_sdk_version(self) -> str:
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output, _ = self._execute(
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def create_tags(filesystemid,
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key=None,
profile=None,
region=None,
**kwargs):
'''
Creates or overwrites tags associated with a file system.
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def authorize_application(
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redirect_uri = 'https://%s/%s' % (FACEBOOK_APPLICATION_DOMAIN, FACEBOOK_APPLICATION_NAMESPACE),
permissions = FACEBOOK_APPLICATION_INITIAL_PERMISSIONS
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Redirect the user to authorize the application.
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def sigOmega(self,dangle):
"""
NAME:
sigmaOmega
PURPOSE:
calculate the 1D sigma in frequency as a function of angle, assuming a uniform time distribution up to a maximum time
INPUT:
dangle - angle offset
OUTPUT:
sigma Omega
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def _merge_configuration(self, parent_config, child_options):
"""Merge parent config into the child options.
The migration process requires an `options` object for the child in
order to distinguish between mutually exclusive codes, add-select and
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def _do_filter(cnf, args):
"""
:param cnf: Mapping object represents configuration data
:param args: :class:`argparse.Namespace` object
:return: 'cnf' may be updated
"""
if args.query:
cnf = API.query(cnf, args.query)
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def out_of_bounds(self, index):
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if type(index) is int:
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def _pad_arrays(t, arrays, indices, span, period):
"""Internal routine to pad arrays for periodic models."""
N = len(t)
if indices is None:
indices = np.arange(N)
pad_left = max(0, 0 - np.min(indices - span // 2))
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def find_logs(
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parameter,
pagination):
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Search all logs, filtering by the given parameters.
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def get_br(self):
"""Returns the bottom right border of the cell"""
cell_below = CellBorders(self.cell_attributes,
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def _spot_check_that_elements_produced_by_this_generator_have_attribute(self, name):
"""
Helper function to spot-check that the items produces by this generator have the attribute `name`.
"""
g_tmp = self.values_gen.spawn()
sample_element = next(g_tmp)[0]
try:
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def basis_function_ders(degree, knot_vector, span, knot, order):
""" Computes derivatives of the basis functions for a single parameter.
Implementation of Algorithm A2.3 from The NURBS Book by Piegl & Tiller.
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def product(pc, service, attrib, sku):
"""
Get a list of a service's products.
The list will be in the given region, matching the specific terms and
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"""
pc.service = service.lower()
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Build a translate mapping that replaces halfwidth and fullwidth forms
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def get_ordering_field_columns(self):
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def cartesian_product(arrays, flat=True, copy=False):
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def attempt_open_query_permutations(url, orig_file_path, is_header_file):
"""
Attempt to open a given mock data file with different permutations of the
query parameters
"""
directory = dirname(convert_to_platform_safe(orig_file_path)) + "/"
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def get_variable_ddi(name, shape, initial_value, dtype=tf.float32, init=False,
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def alter_and_get(self, function):
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def get_interval(ticker, session) -> Session:
"""
Get interval from defined session
Args:
ticker: ticker
session: session
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Session of start_time and end_time
Examples:
>>> get_interval('005490 KS Equity', 'day_open_30')
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def register_middleware(self, middleware, attach_to="request"):
"""
Register an application level middleware that will be attached
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async def update_data_status(self, **kwargs):
"""Update (PATCH) Data object.
:param kwargs: The dictionary of
:class:`~resolwe.flow.models.Data` attributes to be changed.
"""
await self._send_manager_command(ExecutorProtocol.UPDATE, extra_fields={
ExecutorProtoco... | [
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def _path_from_module(module):
"""Attempt to determine bot's filesystem path from its module."""
# Convert paths to list because Python's _NamespacePath doesn't support
# indexing.
paths = list(getattr(module, '__path__', []))
if len(paths) != 1:
filename = getattr(mo... | [
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"paths",... | 49.25 | 0.00166 |
def dpss(npts, fw, number_of_tapers, auto_spline=True, npts_max=None):
"""
Calculates DPSS also known as Slepian sequences or Slepian tapers.
Calculation of the DPSS (Discrete Prolate Spheroidal Sequences) and the
correspondent eigenvalues. The (1 - eigenvalue) terms are also calculated.
Wraps the... | [
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"number_o... | 36.166667 | 0.00032 |
def get_commit_bzs(self, from_revision, to_revision=None):
"""
Return a list of tuples, one per commit. Each tuple is (sha1, subject,
bz_list). bz_list is a (possibly zero-length) list of numbers.
"""
rng = self.rev_range(from_revision, to_revision)
GIT_COMMIT_FIELDS = ['... | [
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"'body'"... | 44.73913 | 0.001903 |
def fingerprint_correlation(P, obs1, obs2=None, tau=1, k=None, ncv=None):
r"""Compute dynamical fingerprint crosscorrelation.
The dynamical fingerprint autocorrelation is the timescale
amplitude spectrum of the autocorrelation of the given observables
under the action of the dynamics P
Parameters
... | [
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"tau... | 34.617647 | 0.000826 |
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