content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import cplex
import io
def run_and_read_cplex(n, problem_fn, solution_fn, solver_logfile,
solver_options, warmstart=None, store_basis=True):
"""
Solving function. Reads the linear problem file and passes it to the cplex
solver. If the solution is successful it returns variable solu... | 77a9e12509cde2e40287bab49ffb7f226ce3c2e2 | 3,633,500 |
def deharmonize(audio_data, sfreq, shift, high=False,
audio_min_freq=200.0, decompose="none"):
"""Deharmonize audio data using full signal FFT
Args:
audio_data(numpy.ndarray): Audio data in a NumPy array
sfreq(float): Sampling frequency in Hz
shift(float): Linear shift i... | 4e7f05d42673ca7cb9c468a9de14d35d83166ee0 | 3,633,501 |
def get_max_sushi(m, features, combs, rank_dict):
"""
Specifically for DTS
:param model: gpflow model
:param features: sushi features
:param rank_dict: dictionary from sushi idx to place in ranking
:return: tuple (index of max sushi, rank)
"""
y_vals = m.predict_y(combs)[0]
num_discr... | a1e214c00db7df45d231e9a3f4aa8da544037dc9 | 3,633,502 |
import os
import logging
import time
def get_multi_media(shelter_id=0, category_id=2, section = 'Identification'):
"""
Get pictures for the shelter sent by Dropzone via a POST
request.
"""
first = True
ImageFile.LOAD_TRUNCATED_IMAGES = True
imgwidth = 1280
shelter = Shelter.query.fil... | 2d70f9318d062e9b98ff3413fa76c1e683ef20a4 | 3,633,503 |
def is_watchman_supported():
""" Return ``True`` if watchman is available."""
if WIN:
# for now we aren't bothering with windows sockets
return False
try:
sockpath = get_watchman_sockpath()
return bool(sockpath)
except Exception:
return False | 7681ba911456196ad01774e0607bd81872e4b82a | 3,633,504 |
def geolocation(data_base, year, latitude, longitude, geofunc):
"""
Function for geolocating points from database and calculating distance from them to
the given user point.
>>> 33.5 <= geolocation(pd.DataFrame([["Film1", 2020, "Some info",\
"Los Angeles California USA"]], columns \
= ["name",... | ecd619b23d0f72c29b164f7fdbf498b41f25c0f0 | 3,633,505 |
import os
def get_clip_details(file_path: str) -> (int, float, int, int):
"""
Gets a clip's duration, frame rate and dimensions (width, height).
:param file_path: The absolute path to a clip.
:return: Duration in seconds, frame rate in FPS and width and height in pixels.
This is given in... | 9c49a79cbf93481f68ea34b43b550842598bbca1 | 3,633,506 |
import shutil
import os
def notebook(live_mock_server, test_dir):
"""This launches a live server, configures a notebook to use it, and enables
devs to execute arbitrary cells. See tests/test_notebooks.py
"""
@contextmanager
def notebook_loader(nb_path, kernel_name="wandb_python", save_code=True,... | 1930792965a3b3492cefca8f1a583754164b103f | 3,633,507 |
from typing import OrderedDict
def read_dig_polhemus_isotrak(fname, ch_names=None, unit='m'):
"""Read Polhemus digitizer data from a file.
Parameters
----------
fname : str
The filepath of Polhemus ISOTrak formatted file.
File extension is expected to be '.hsp', '.elp' or '.eeg'.
... | d048f1f83844bc591a301c046f3c25494ffd0339 | 3,633,508 |
def gt_comparison_plot(data, mu=None, sig=None, k=3.3e11, x_c = None):
"""
Generate the comparison Zipf plot for the data.
Parameters
----------
data : array_like
Size of each firm, where size is measured by sales, value added,
number of employees or some other variable.
k : f... | 64a30fd6bf77edbd89ed3194838e518a1022cc11 | 3,633,509 |
def make_cache_key(instance):
"""Construct a cache key for the instance."""
prefix = '{}:{}:{}'.format(
instance._meta.app_label,
instance._meta.model_name,
instance.pk
)
return '{}:{}'.format(prefix, str(uuid4())) | 6a83d20c94e26ece5ca3d98ad8cb70dd17fa5ea7 | 3,633,510 |
import os
import pickle
def load_model(filename: str, model_dir=config.MODEL_DIR) -> nn.Module:
"""
Load the model from a pickle.
:param filename: name of the file
:param model_dir: directory in which the file is located
:return:
"""
with open(os.path.join(model_dir, filename), 'rb') as f:... | 02bdefdaf5ba24bcd9174ad57cd895a6bcf0a551 | 3,633,511 |
def CalculateMediationPEEffect(PointEstimate2, PointEstimate3):
"""Calculate derived effects from simple mediation model.
Given parameter estimates from a simple mediation model,
calculate the indirect effect, the total effect and the indirect effects
Parameters
----------
PointEstimate2 : ... | d2247985e46a78bc3333983e09a1030fd59f139d | 3,633,512 |
def get_engine(db_dir_name, echo=False, path_str=None):
"""数据库引擎"""
if path_str:
path = path_str
else:
path = db_path(db_dir_name)
engine = create_engine('sqlite:///' + path, echo=echo)
return engine | c3f35e7a52619c9ef5e1414efdbebcaebb8b8bd3 | 3,633,513 |
def init_websauna(config_uri: str, sanity_check: bool=False, console_app=False, extra_options=None) -> Request:
"""Initialize Websauna WSGI application for a command line oriented script.
:param config_uri: Path to config INI file
:param sanity_check: Perform database sanity check on start
:param con... | 2d56ce6afa1ede2c69c92422cb360e856d84b007 | 3,633,514 |
def ts_glm_ridge_pipeline():
"""
Return pipeline with the following structure:
glm \
-> ridge -> final forecast
lagged - ridge /
Where glm - Generalized linear model
"""
node_glm = PrimaryNode("glm")
node_lagged = PrimaryNode("lagged")
node_ridge_1 = S... | 41a6ce2e280ca6a89ba482715ab9bcdc807c0d29 | 3,633,515 |
import os
def read_validation_annotations(validation_dir):
"""Reads validation data annotations."""
return read_tiny_imagenet_annotations(
os.path.join(validation_dir, 'val_annotations.txt'),
os.path.join(validation_dir, 'images')) | 6e586a1321db4c13c3ca0d2fb34f92ebfbd62c7b | 3,633,516 |
def norm1to1(operator, n_samples=10000, mxBasis="gm", return_list=False):
"""
Returns the Hermitian 1-to-1 norm of a superoperator represented in
the standard basis, calculated via Monte-Carlo sampling. Definition
of Hermitian 1-to-1 norm can be found in arxiv:1109.6887.
"""
if mxBasis == 'gm':
... | f0ad0d6a89ab9c3ec275c5ea5ce1a343d275f625 | 3,633,517 |
def _load_image_gdal(image_path, value_scale=1.0):
""" using gdal to read image, especially for remote sensing multi-spectral images
:param image_path: string, image path
:param value_scale: float, default 1.0. the data array will divided by the 'value_scale'
:return: array of shape (height, width, ban... | 94d8ce48f069bc311637237d805fd140604cffc2 | 3,633,518 |
def f1_chantler(element, energy, _larch=None, **kws):
"""returns real part of anomalous x-ray scattering factor for
a selected element and input energy (or array of energies) in eV.
Data is from the Chantler tables.
Values returned are in units of electrons
arguments
---------
element: at... | 76b5143e3d9be69ae6f7f8ee246669ee3da9fe08 | 3,633,519 |
def rgb_to_hex(red_component=None, green_component=None, blue_component=None):
"""Return color as #rrggbb for the given color tuple or component
values. Can be called as
TUPLE VERSION:
rgb_to_hex(COLORS['white']) or rgb_to_hex((128, 63, 96))
COMPONENT VERSION
rgb_to_hex(64, 183, 22)
... | 37f5216f7f22f82072db6980541a815d87d02ef3 | 3,633,520 |
def remove(predicate, seq):
""" Return those items of sequence for which predicate(item) is False
>>> def iseven(x):
... return x % 2 == 0
>>> list(remove(iseven, [1, 2, 3, 4]))
[1, 3]
"""
return filterfalse(predicate, seq) | 2953386f289894e4f5a052d1f67087dcf4631a3a | 3,633,521 |
def average_coords(coords_list):
"""Calculate average coords
Parameters
----------
coords_list : list[skrobot.coordinates.Coordinates]
Returns
-------
coords_average : skrobot.coordinates.Coordinates
"""
q_list = [c.quaternion for c in coords_list]
q_average = averageQuaternion... | 3a3e59685311042a91295760ec025e12916c34d5 | 3,633,522 |
def lowpassfilter(input_vect, width=101):
"""
Computes a low-pass filter of an input vector.
This is done while properly handling NaN values, but at the same time
being reasonably fast.
Algorithm:
provide an input vector of an arbitrary length and compute a running NaN
median over a box o... | 1b71ac8f0a2fc61b0cd3d5ab9e1f218471b3569c | 3,633,523 |
def n_keywords(data):
"""Return the number of keywords.
Arguments
---------
data: asreview.data.ASReviewData
An ASReviewData object with the records.
Return
------
int:
The statistic
"""
if data.keywords is None:
return None
return np.average([len(keywor... | d2692c1e040cf659dcc6eb1aa7c5718d52a345d8 | 3,633,524 |
def flatten_reshape(variable, name=''):
"""Reshapes high-dimension input to a vector.
[batch_size, mask_row, mask_col, n_mask] ---> [batch_size, mask_row * mask_col * n_mask]
Parameters
----------
variable : a tensorflow variable
name : a string or None
An optional name to attach to thi... | 933ec231c15f91122db755f9bac98679cdf9864e | 3,633,525 |
def register_command(data):
"""Remote command registration service.
This has to be enabled by liquer.commands.enable_remote_registration()
WARNING: Remote command registration allows to deploy arbitrary python code on LiQuer server,
therefore it is a HUGE SECURITY RISK and it only should be used if oth... | c9b764e6f2758ad4cc90aced854421d7d83ece9e | 3,633,526 |
import json
def add_noise(dgen_list, noise):
"""Add noise decorators to the DataGenerators from `dgen_list` list.
Parameters
----------
dgen_list : list of IDataGenerator
A list of DataGenerators to be decorated.
noise : list of dict or dict or None
Noise configuration.
If... | f716211ad9f1d35e66845e0887aafa5955575b4b | 3,633,527 |
import random
import json
def index():
"""
Web app index page. It renders two pictures about the data. One bar chart and word cloud.
"""
# extract data needed for visuals
# TODO: Below is an example - modify to extract data for your own visuals
genre_counts = df.groupby('genre').coun... | 10509856618e9f09c273d20b617e948448623a8e | 3,633,528 |
from pathlib import Path
def open(table_file: str, table_map_file: str = None) -> pd.DataFrame:
"""
Opens a dynamo table file, returning a DynamoTable object
:param table_file:
:return: dataframe
"""
# Read into dataframe
df = pd.read_csv(table_file, header=None, delim_whitespace=True)
... | 7dca5cfc2c3c6201730b99db13680bed81b51a4b | 3,633,529 |
def _evaluate_tags(pcluster_config, preferred_tags=None):
"""
Merge given tags to the ones defined in the configuration file and convert them into the Key/Value format.
:param pcluster_config: PclusterConfig, it can contain tags
:param preferred_tags: tags that must take the precedence before the confi... | d23e4c29b463736fa23a65c977e16734b235c4c9 | 3,633,530 |
def dict_view(request):
"""
字典管理
"""
return render_mako_context(request, '/system_permission/dictmgr.html') | 56b8b80fb56c032f319f23754c3926cadf74ddc6 | 3,633,531 |
def rot_ETA(eta: float) -> np.ndarray:
"""Return rotation matrix corresponding to eta axis.
Parameters
----------
eta: float
eta axis angle
Returns
-------
np.ndarray
Rotation matrix as a NumPy array.
"""
return z_rotation(-eta) | 07e3c42f40bba0d73b4718eaa2d56b17e3dffd8e | 3,633,532 |
def show_lists(chat_id):
"""
It shows all the lists of the given user
:param chat_id:
:return:
"""
lists = notelistmodel.find_all_lists(mongodb, chat_id)
return {"text": monkeyview.lists_view(lists), "parse_mode": "Markdown"} | b72df596357e0174294589eab413fa1f8f8da840 | 3,633,533 |
import logging
def test_params_from_fw_spec(tempdir, files, dtool_config,
default_create_dataset_task_spec,
default_freeze_dataset_task_spec):
"""Will create dataset with some task parameters pulled from fw_spec."""
logger = logging.getLogger(__name__)... | 16bff2b0c79b332211283c53e9ca6630b0ce809a | 3,633,534 |
from re import T
def import_string(path: str) -> T.Any:
"""
Import a dotted Python path to a class or other module attribute.
``import_string('foo.bar.MyClass')`` will return the class ``MyClass`` from
the package ``foo.bar``.
"""
name, attr = path.rsplit('.', 1)
return getattr(import_modu... | 3475a6081d64f656ec2c50b74f9314d519d18dee | 3,633,535 |
from re import T
def inbox():
"""
RESTful CRUD controller for the Inbox
- all Inbound Messages are visible here
"""
if not auth.s3_logged_in():
session.error = T("Requires Login!")
redirect(URL(c="default", f="user",
args = "login",
... | 486640ebdb1a142f22ac146479fa36c289a8e1be | 3,633,536 |
def glorot_uniform_sigm(shape):
"""
Glorot style weight initializer for sigmoid activations.
Like keras.initializations.glorot_uniform(), but with uniform random interval like in
Deeplearning.net tutorials.
They claim that the initialization random interval should be
+/- sqrt(6 / (fan_in... | 4cd3a3f40e276aba5b16726af4ce28adefe25748 | 3,633,537 |
def pytest_report_header(config):
"""Display cachedir with --cache-show and if non-default."""
if config.option.verbose > 0 or config.getini("cache_dir") != ".pytest_cache":
cachedir = config.cache._cachedir
# TODO: evaluate generating upward relative paths
# starting with .., ../.. if s... | d859b89b11015623a9dd2bc159c855b896d27ee7 | 3,633,538 |
def params(kernels, time, target, target_frame, observer, corr):
"""Input parameters from WGC API example."""
return {
'kernels': kernels,
'times': time,
'target': target,
'target_frame': target_frame,
'observer': observer,
'aberration_correction': corr,
} | d030ad459b294a268c8bc3a851a32495dcbf5c02 | 3,633,539 |
import re
import os
def extract_thresholds_of_intensity_criteria(data_path, sub_ses_test, patch_side, new_spacing, out_folder, n_parallel_jobs, overlapping, prints=True):
"""This function computes the threshold to use for the extraction of the vessel-like negative patches (i.e. the
negative patches that rough... | 8da250d5c25b338d19d1e68b1b27b12a8221b467 | 3,633,540 |
def group_activity_list(
group_id: str,
limit: int,
offset: int,
include_hidden_activity: bool = False,
) -> list[Activity]:
"""Return the given group's public activity stream.
Returns activities where the given group or one of its datasets is the
object of the activity, e.g.:
"{USER}... | aaab03202571e3eb562fc3b8ec663ac58cc69ab0 | 3,633,541 |
def rotMatrixfromXYZ(station, mode='LBA'):
"""Return a rotation matrix which will rotate a station to (0,0,1)"""
loc = station.antField.location[mode]
longRotMat = rotationMatrix(0., 0., -1.*np.arctan(loc[1]/loc[0]))
loc0 = np.dot(longRotMat, loc)
latRotMat = rotationMatrix(0., np.arctan(loc0[0,2]/l... | a6df1bc5bc0cd8752cbd71c025a1b5208d1b8a34 | 3,633,542 |
import logging
def geo_info_for_geo_name(
geo_name: str, username: str = CONFIG["geonames_username"]
) -> GeoInfo:
"""Get geo information (latitude and longitude) for given region name."""
logging.info("Decoding latitude and longitude of '{}'...".format(geo_name))
gn = geocoders.GeoNames(username=user... | e6827ae4b0e3297311dd16fc3a98865bcc7fc252 | 3,633,543 |
def char_accuracy(predictions, targets, rej_char, streaming=False):
"""Computes character level accuracy.
Both predictions and targets should have the same shape
[batch_size x seq_length].
Args:
predictions: predicted characters ids.
targets: ground truth character ids.
rej_char: the character id use... | caccf28fab0aa4127da7b30d95f380452b713974 | 3,633,544 |
import json
def read_cities_db(fname="world-cities_json.json"):
"""Read a database file containing names of cities from different countries.
Source: https://pkgstore.datahub.io/core/world-cities/world-cities_json/data/5b3dd46ad10990bca47b04b4739a02ba/world-cities_json.json
"""
with open(fname) as f:
... | 1edb970e329e7781cebb61853a13a6f45d349250 | 3,633,545 |
def ConcatWith(x, dim, tensor):
"""
A wrapper around `tf.concat` to support `LinearWrap`
:param x: the input tensor
:param dim: the dimension along which to concatenate
:param tensor: a tensor or list of tensor to concatenate with x. x will be
at the beginning
:return: tf.concat(dim, [x]... | 8d15e008f8e2ec70c2d875a9bb5dcb1786d011ed | 3,633,546 |
def strip_df(data: pd.DataFrame) -> np.ndarray:
"""Strip dataframe from all index levels to only contain values.
Parameters
----------
data : :class:`~pandas.DataFrame`
input dataframe
Returns
-------
:class:`~numpy.ndarray`
array of stripped dataframe without index
""... | 3cd04b6b6cf144ac63854fbbab5ffa3784ccd707 | 3,633,547 |
def isRef(obj):
""" """
if isinstance(obj, dict) == True and '_REF' in obj:
return obj['_REF']
else:
return False | 0f1ad92cfafff5dcbc9e90e8544956b05c3452ec | 3,633,548 |
from pathlib import Path
from typing import Dict
from typing import Tuple
import pickle
def collect_genes_with_confidence(
query: str,
*,
cache_file: Path = None,
client: Neo4jClient,
) -> Dict[Tuple[str, str], Dict[str, Tuple[float, int]]]:
"""Collect gene sets based on the given query.
Para... | 18f949c1613f05b242a27dff7d16722af4d6bbf6 | 3,633,549 |
import copy
def intervals_disjoint(intvs):
"""
Given a list of complex intervals, check whether they are pairwise
disjoint.
EXAMPLES::
sage: from sage.rings.polynomial.complex_roots import intervals_disjoint
sage: a = CIF(RIF(0, 3), 0)
sage: b = CIF(0, RIF(1, 3))
sage... | ebe3208f1af22f7001d3dee10a2dca6a68558cc8 | 3,633,550 |
def _get_registered_typelibs(match='HEC River Analysis System'):
"""
adapted from pywin32
# Copyright (c) 1996-2008, Greg Stein and Mark Hammond.
"""
# Explicit lookup in the registry.
result = []
key = win32api.RegOpenKey(win32con.HKEY_CLASSES_ROOT, "TypeLib")
try:
num = 0
... | 88d5cf576454793678b275826d4087e5bcd263e4 | 3,633,551 |
def head(content, accesskey:str ="", class_: str ="", contenteditable: str ="",
data_key: str="", data_value: str="", dir_: str="", draggable: str="",
hidden: str="", id_: str="", lang: str="", spellcheck: str="",
style: str="", tabindex: str="", title: str="", transla... | 6ed2622a53b3e3df8254cd6bfbc41cad296dea8c | 3,633,552 |
def standardize(dataset, verbose=True):
""" remove all source-specific columns, keeping only those that occur in all repo sources.
also adds extra columns with default values """
found = False
for source, extra_features in EXTRA_FEATURES.items():
if all(feat in dataset.features for feat in extr... | f057c9d98c0525f4536053c20c0467ae2e8b6287 | 3,633,553 |
def mark(tv,stars=None,rad=3,auto=False,color='m',new=False,exit=False):
""" Interactive mark stars on TV, or recenter current list
Args :
tv : TV instance from which user will mark stars
stars = : existing star table
auto= (bool) : if True, recentroid from existing posit... | 66a291c564329a878aea7658cd9fc071cc303d0b | 3,633,554 |
def result_summary_info(request,object_id):
"""Present a result summary"""
object = get_object_or_404(Results.ResultSummaryList, pk=object_id)
protocolfields={}
for (fieldname, text, cond) in [("version_intolerant", "Version Intolerant", Results.ResultCondition.RESULTC_VERSION_INTOLERANT),
("extension... | 1036fad0d52435912579e9680f5037a8aa052e53 | 3,633,555 |
def stackplot(data, add, xlabel='', ylabel='', cmap='Spectral',
figsize=(3, 4.5), lw=1, plot=True):
"""
Plots a stack plot of selected spectras.
:type data: list[float]
:param data: Data to in the plot.
:type add: float
:param add: displacement, or difference, between each curve... | 959118905abbfada9d4af3ac0a8ab414b00a9ffe | 3,633,556 |
import torch
def batch_detect(net, img_batch, device):
"""
Inputs:
- img_batch: a numpy array of shape (Batch size, Channels, Height, Width)
"""
B, C, H, W = img_batch.shape
orig_size = min(H, W)
# BB, HH, WW = img_batch.shape
# if img_batch
if isinstance(img_batch, torch.Tens... | e20de1e4f3915e2e377e790f7e6cb3df5d76b5cb | 3,633,557 |
def int_to_binary(x, n):
"""Convert an integer into its binary representation
Args:
x (int): input integer
n (int): number of leading zeros to display
Returns:
(str) binary representation
"""
if type(x) != int:
raise ValueError('x must be an integer.')
return f... | c3d68a798f84988290bd4e845a5bcc015872b054 | 3,633,558 |
import os
def read_requirements():
"""Parse requirements from requirements.txt."""
requirements_path = os.path.join('.', 'requirements.txt')
with open(requirements_path, 'r') as f:
requirements = [line.rstrip() for line in f]
return requirements | bc4282532c74d5c2f2bd9cd225b7604d0924035d | 3,633,559 |
def convert_examples_to_features(examples,
tokenizer,
max_seq_length,
max_program_length,
is_training,
op_list,
op_list_si... | d7024a0ff97d94a5c2aa32e63230e972584fb1d2 | 3,633,560 |
def negative_mean_successiness(c):
"""Negative mean successiness over the course of the trial."""
if c.needed_control_arm_events.size > 1:
center = float(c.needed_control_arm_events.mean())
width = float(c.needed_control_arm_events.std())
else:
center = float(c.needed_control_arm_events)
width = c... | ac6e07076c422ef524f46583edd41eff48f6733e | 3,633,561 |
def determina_putere(n):
"""
Determina ce putere a lui 2 este prima cea mai mare
decat n
:param (int) n: numarul de IP-uri necesare
citit de la tastatura
:return (int) putere: puterea lui 2 potrivita
"""
putere = 1
while 2**putere < n+2:
putere += 1
return put... | 85e2c1dcd2ea5d86b5db3c6ced28dd65e244c467 | 3,633,562 |
def attribute_rename_cmd(oldattr, newattr):
"""
Rename an attribute.
If it's not present nothing is done, and its value is kept.
That's it.
$ cjio myfile.city.json attribute_rename oldAttr newAttr info
"""
def processor(cm):
utils.print_cmd_status('Rename attribute: "%s" =>... | b48e0e90bbb75cdf9828e21c115b758250f433e2 | 3,633,563 |
from datetime import datetime
def editItemInCategory(item_id):
""" Edit an item in a given category."""
if 'username' not in login_session:
sMsg = "You are not authorized to perform this '%s' " % ('edit item category')
sMsg += "action because you are not logged in. You are being redirected to login."
flash... | ed2f51eea2713271f82440599edd90f015820b24 | 3,633,564 |
def factorial(n, show=False):
"""
-> Calcula o Fatorial de um número.
:param n: O número a ser calculado.
:param show: (opcional) Mostra ou não a conta.
:return: O valor do Fatorial de um número n.
"""
f = 1
for c in range(n, 0, -1):
if show:
print(c, end='')
... | 4e2928b2e2b197e40aacd8ec1b18c9afee42e229 | 3,633,565 |
def parse_commands(log_content):
"""
parse cwl commands from the line-by-line generator of log file content and
returns the commands as a list of command line lists, each corresponding to a step run.
"""
command_list = []
command = []
in_command = False
line = next(log_content)
wh... | dff555cd0ec84619425fc05e4c8892c603bcc994 | 3,633,566 |
from datetime import datetime
import ssl
import logging
import time
def wait_for_operation(client,
project,
op_id,
timeout=datetime.timedelta(hours=1),
polling_interval=datetime.timedelta(seconds=5),
sta... | a7487beda110d1b5d52d8073d58fb6a33b0997a2 | 3,633,567 |
import re
def regex_closest_match(regex: str, string: str) -> str:
"""Find the longest version of regex that matches something in string."""
no_match = True
modified_regex = regex
while no_match:
# TODO: there may be a better way to do this rather than a try-except (perhaps using sre_parse to... | 2154fe51c874fd910e8f5da8b1c687cc598e5cab | 3,633,568 |
def bij_connected_comps(components):
"""Set of connected planar graphs (possibly derived) to nx.PlanarEmbedding."""
res = nx.PlanarEmbedding()
for g in components:
g = g.underive_all()
g = g.to_planar_embedding()
res = nx.PlanarEmbedding(nx.compose(res, g))
return res | 7f705f25756e114c91bbff9a09880d5bfb8d37ee | 3,633,569 |
from typing import Tuple
def render_responses(intent: Intent, language_data: IntentLanguageData) -> Tuple[IntentResponseDict, str]:
"""
Return a copy of responses in `language_data` where intent parameter references are
replaced with their values from the given :class:`Intent` instance.
Args:
... | 4e83d1b75b25d8e3ab7d030890744f0081c02c10 | 3,633,570 |
import os
def sp_cpu(file):
"""Read single-point output for cpu time."""
spe, program, data, cpu = None, None, [], None
if os.path.exists(os.path.splitext(file)[0] + '.log'):
with open(os.path.splitext(file)[0] + '.log') as f:
data = f.readlines()
elif os.path.exists(os.path.split... | ca9cb22b0981b3a14eafdd2637eccbe448597432 | 3,633,571 |
def cropseq(indexes, l, stride):
"""generate chunked silencer sequence according to loaded index"""
print('Generating silencer samples with length {} bps...'.format(l))
silencers = list()
i = 0
for index in indexes:
try:
[sampleid, chrkey, startpos, endpos, _] = index
exc... | 09bac76a6209398cdb5cb230be7aa18f5f895204 | 3,633,572 |
import tqdm
def generate_claims(model, gen_dset, dl, tokenizer, device):
"""
Run generation using the given model on the given dataset
:param model: BART model to use for generation
:param gen_dset: The original dataset
:param dl: A dataloader to use for generation
:param tokenizer: A tokenize... | 0f042101ca6c864249c62e1934a9c58f0b21f9e7 | 3,633,573 |
def to_geojson(series):
"""Return a GeoJSON geometry collection from the series (must be in EPSG:4326).
Did not use the builtin for the series since it introduces a lot of bloat.
"""
return {
"type": "GeometryCollection",
"geometries": series.apply(lambda x: x.__geo_interface__).to_list... | 2ebdc001ed7a6fb3ee6e6cac9fc7722e19518e20 | 3,633,574 |
import os
import subprocess
def check_kafka_ready(expected_brokers, timeout, config, bootstrap_broker_list=None, zookeeper_connect=None, security_protocol=None):
"""Waits for a Kafka cluster to be ready and have at least the
expected_brokers to present. This commands uses the Java docker-utils
libra... | ca8aa8a1c8a51b0885bd887bb4a8bc8854160c3c | 3,633,575 |
import copy
async def copy_context(ctx: commands.Context, *, author=None, channel=None, **kwargs):
"""
Returns a new Context with changed message properties.
"""
# copy the message and update the attributes
alt_message: discord.Message = copy.copy(ctx.message)
alt_message._update(kwargs)
... | 78a82922a7740cfcdad0e17a0f85a16ee53a068e | 3,633,576 |
def getConstraintWeightAttr(leader, constraint):
"""
Return the weight attribute from a constraint that
corresponds to a specific leader node.
Args:
leader (PyNode): A node that is one of the leaders of a constraint
constraint (PyNode): A constraint node
"""
for i, target in enu... | e53ef981f505f1c8fc21fff7b71605764d6da3e0 | 3,633,577 |
import sys
def load_data(dataset_str):
"""
Loads input data from gcn/data directory
ind.dataset_str.x => the feature vectors of the training instances as scipy.sparse.csr.csr_matrix object;
ind.dataset_str.tx => the feature vectors of the test instances as scipy.sparse.csr.csr_matrix object;
ind.... | d629e3ceb8f8b030526f15294309b95636e90838 | 3,633,578 |
def approximate_mds(dists):
"""Approximate multidimensional scaling (MDS)
Estimate the inter-node distance matrix from source node distances as
described in "Iterative Geometry Calibration from Distance Estimates for
Wireless Acoustic Sensor Networks" (https://arxiv.org/abs/2012.06142).
Subsequentl... | 6f2aef5e71c439990840143089fa9cc941a81c2c | 3,633,579 |
def build_resnet_fpnindi_backbone(cfg, input_shape: ShapeSpec):
"""
Args:
cfg: a detectron2 CfgNode
Returns:
backbone (Backbone): backbone module, must be a subclass of :class:`Backbone`.
"""
bottom_up = build_resnet_backbone(cfg, input_shape)
in_features = cfg.MODEL.FPN.IN_FEAT... | 40329cfb0d414305e7d38966b41e352cc44c6535 | 3,633,580 |
from typing import Tuple
from typing import Any
def _get_min_max_outputs(node: BaseNode,
fw_info: FrameworkInfo) -> Tuple[Any, Any]:
"""
Return the min/max output values of a node if known.
If one of them (or both of them) is unknown - return None instead of a value.
Args:
... | c43992c9b2cd64b9970766fe06d6d0c6af3a6954 | 3,633,581 |
def remove_stop_words(document):
"""Returns document without stop words"""
document = ' '.join([i for i in document.split() if i not in stop])
return document | c4385790901f09eadeac67dc1035a12bedf8cb45 | 3,633,582 |
def Ion_Flux_Relabeling(h,q):
"""
Oh no! Commander Lambda's latest experiment to improve the efficiency of her LAMBCHOP
doomsday device has backfired spectacularly. She had been improving the structure of
the ion flux converter tree, but something went terribly wrong and the flux chains
exploded. ... | 8d8694722c8a8d6dcf4aabad3d677fb059d252d9 | 3,633,583 |
def process_line(line, previous_state):
"""
Read line, split it before opening brackets if not in quotes nor escaped
and add '\n' in the end of new lines.
"""
# opening bracket and/or quote can start in other line
brackets = previous_state.brackets
in_quotes = pr... | 24b997f61263563a67f58a65f2e070c1b21ee478 | 3,633,584 |
def parse_tape6(tape6="TAPE6.OUT"):
"""Parses an ORIGEN 2.2 TAPE6.OUT file.
Parameters
----------
tape6 : str or file-like object
Path or file to read the tape6 file from.
Returns
-------
results : dict
Dictionary of parsed values.
Warnings
--------
This method... | 5082ee35ce8198db680c0b7be86d703c4c349402 | 3,633,585 |
def property_values_to_string(pv,extra_indentation = 0):
"""
Parameters
----------
pv : OrderedDict
Keys are properties, values are values
"""
# Max length
keys = pv[::2]
values = pv[1::2]
values = ['"%s"' %x if isinstance(x,_Quotes) else x for x in values]
key_lengths... | 0a8f5b188f74d1779c871a843eb7394631162fc4 | 3,633,586 |
def parse_cmdline():
"""parse command line arguments"""
parser = ArgumentParser(
description="dtbTool version " + str(QCDT_VERSION))
parser.add_argument("input_dir",
help="Input directory")
parser.add_argument("-o", "--output-file", type=FileType('wb'), required=True,
... | 4f2cf506c4463b19859403de0aac0707d4ad5050 | 3,633,587 |
def __build_vocab(nlp, datasets):
"""
Generates the encoder vocabulary (natural language tokens),
decoder vocabulary (programming language tokens) and stack
vocabulary (terminal and non-terminal symbols, tokens) by
parsing each source and target example in each split.
:param nlp: nl pro... | d162169874a1f82779641615658aa5be52aafb81 | 3,633,588 |
import os
def file_contains_exact_text(filename, text):
"""Returns True iff the file exists and it already contains the given text."""
if not os.path.isfile(filename):
return False
with open(filename, "r") as infile:
intext = infile.read()
return text == intext
return False | 49bbb86c30a5df5d41e78cd64ddb58d44eaaf899 | 3,633,589 |
from typing import Optional
from typing import Dict
def get_profile(key: str) -> Optional[Dict]:
"""Fetch user profile.
Arguments:
---------
key: User's database key.
Returns:
---------
Profile dictionary if exists else None.
"""
return BASE_PROFILE.get(key=key) | 0bf1d86707b14735afb6b832d41b63a25650985e | 3,633,590 |
def rectangle_centered(
w: int = 1, h: int = 1, x: None = None, y: None = None, layer: int = 0
) -> Component:
""" a rectangle size (x, y) in layer
bad naming with x and y. Replaced with w and h. Keeping x and y
for now for backwards compatibility
.. plot::
:include-source:
imp... | a61c07a87c6b1a6d347ddc104863657eafd305ad | 3,633,591 |
from datetime import datetime
def sched_time_to_dt(timeStr, targetDate):
"""Converts a GTFS schedule time string to a datetime
Note that a GTFS time may be more than 24 hours, in which case
the function removes 24 from the hours part of the time and increases
the date part of the datetime by 1
Args:
t... | 9fb43c4e19d050480649b39f1ac9a79f617338b7 | 3,633,592 |
def get_arxiv_csl(*, arxiv_id):
"""
Generate a CSL Item for an unversioned arXiv identifier
using arXiv's OAI_PMH v2.0 API <https://arxiv.org/help/oa>.
This endpoint does not support versioned `arxiv_id`.
"""
# XML namespace prefixes
ns_oai = "{http://www.openarchives.org/OAI/2.0/}"
ns_a... | 54fcf1df4b6963a95788a1cdf3306d583fe0b8e6 | 3,633,593 |
from typing import Mapping
from typing import Sequence
import math
def _equivalent_data_structures(reference, struct_2):
"""Compare arbitrary data structures for equality.
``reference`` is expected to be the reference data structure. Cannot handle
set like data structures.
"""
if isinstance(refer... | 57ecaa315a1f9a516b4ac2c2528f0f207fffab6f | 3,633,594 |
def _find_line_bounding_boxes(line_segmentation: np.ndarray):
"""Given a line segmentation, find bounding boxes for connected-component regions corresponding to non-0 labels."""
def _find_line_bounding_boxes_in_channel(line_segmentation_channel: np.ndarray) -> np.ndarray:
line_activation_image = cv2.di... | f0a41d5b569601db6eaa4ca061bddbfe6b6c88fa | 3,633,595 |
def split_items(items, num_groups):
"""Splits a list of items into ``num_groups`` groups fairly (i.e. every
item is assigned to exactly one group and no group is more than one item
larger than any other)."""
per_set = len(items) / float(num_groups)
assert per_set >= 1, "At least one set will be empt... | 0e5af3c5d3e394b328bef63b5287bd673fef0241 | 3,633,596 |
from typing import OrderedDict
import json
def generate_tool_flow(tool: GladierBaseTool, modifiers):
"""Generate a flow definition for a Gladier Tool based on the defined ``funcx_functions``.
Accepts modifiers for funcx functions"""
flow_moder = FlowModifiers([tool], modifiers, cls=tool)
flow_states... | 1ae457676ee2bfaa872f237036261bbfbdc644fb | 3,633,597 |
def paralellLines(M,axis=1,labels=(), interactive=True, title="",show=True):
"""
Makes an optionally interactive paralell Lines plot.
M: Matrix to visualise.
axis: Axis of data values to plot. Needs to be either 1 or 0. Defaults to 1.
labels: Labels of the axes to plot.
inte... | a3ff1f1faa0e1704df24aac0024330458b037027 | 3,633,598 |
import types
import pandas
def hpat_pandas_series_dropna(self, axis=0, inplace=False):
"""
Intel Scalable Dataframe Compiler User Guide
********************************************
Pandas API: pandas.Series.dropna
Limitations
-----------
- Parameter ``inplace`` is currently unsupported b... | 9389f3cb90d22435133f04b3c48f761c65eceee3 | 3,633,599 |
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