content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import os
import subprocess
import sys
import getpass
def ssh_cmd(ssh_cfg, command):
"""Returns ssh command."""
try:
binary = os.environ['SSH_BINARY']
except KeyError:
if os.name != 'nt':
binary = subprocess.check_output(
'which ssh', shell=True).decode(sys.stdo... | f7e110c76e26a462dd9929fc6fa4f2c025a2df44 | 26,300 |
import json
def test_sensor_query(cbcsdk_mock):
"""Test the sensor kit query."""
def validate_post(url, param_table, **kwargs):
assert kwargs['configParams'] == 'SampleConfParams'
r = json.loads(kwargs['sensor_url_request'])
assert r == {'sensor_types': [{'device_type': 'LINUX', 'archi... | 878a060ad7f532522b8ef81f76701fbe0c7dc11b | 26,301 |
import os
def ExtractParametersBoundaries(Basin):
"""
=====================================================
ExtractParametersBoundaries(Basin)
=====================================================
Parameters
----------
Basin : [Geodataframe]
gepdataframe of catchment polygon, ... | cb79f39380116a28307763f85e696abef0c4f3b5 | 26,302 |
def encoder_apply_one_shift(prev_layer, weights, biases, act_type, name='E', num_encoder_weights=1):
"""Apply an encoder to data for only one time step (shift).
Arguments:
prev_layer -- input for a particular time step (shift)
weights -- dictionary of weights
biases -- dictionary of bia... | 19ea3beec271e003f6d9ccadd4d508d97f6b7572 | 26,303 |
import uuid
def db_entry_generate_id():
""" Generate a new uuid for a new entry """
return str(uuid.uuid4()).lower().replace('-','') | d5e90504a1927623b267082cd228981684c84e8d | 26,304 |
import os
def get_manager_rest_service_host():
"""
Returns the host the manager REST service is running on.
"""
return os.environ[constants.REST_HOST_KEY] | 21a5cd5d8c77e1ff3f6edd7b7d80d03edb2ab974 | 26,305 |
def angle_boxplus(a, v):
"""
Returns the unwrapped angle obtained by adding v to a in radians.
"""
return angle_unwrap(a + v) | 9434d88d59956eeb4803bbee0f0fb3ad8acd1f5f | 26,306 |
def color_gradient_threshold(img, s_thresh=[(170, 255),(170, 255)], sx_thresh=(20, 100)):
"""
Apply a color threshold and a gradient threshold to the given image.
Args:
img: apply thresholds to this image
s_thresh: Color threshold (apply to S channel of HLS and B channel of LAB)
sx_... | 02bdfbd9a95dbfe726eac425e1b6efb78bfedb2b | 26,307 |
def toeplitz(c, r=None):
"""
Construct a Toeplitz matrix.
The Toeplitz matrix has constant diagonals, with c as its first column
and r as its first row. If r is not given, ``r == conjugate(c)`` is
assumed.
Parameters
----------
c : array_like
First column of the matrix. Whateve... | 00c68daef087fded65e1feee375491db559c792f | 26,308 |
def MQWS(settings, T):
"""
Generates a surface density profile as the per method used in Mayer, Quinn,
Wadsley, and Stadel 2004
** ARGUMENTS **
NOTE: if units are not supplied, assumed units are AU, Msol
settings : IC settings
settings like those contained in an IC object (see ... | bd1227f4416d093271571f0d6385c98d263c514e | 26,309 |
def predict(x, P, F=1, Q=0, u=0, B=1, alpha=1.):
"""
Predict next state (prior) using the Kalman filter state propagation
equations.
Parameters
----------
x : numpy.array
State estimate vector
P : numpy.array
Covariance matrix
F : numpy.array()
State Transitio... | fa638183a90583c47476cc7687b8702eb193dffb | 26,310 |
from typing import Dict
def footer_processor(request: HttpRequest) -> Dict[str, str]:
"""Add the footer email me message to the context of all templates since the footer is included everywhere."""
try:
message = KlanadTranslations.objects.all()[0].footer_email_me
return {"footer_email_me": mes... | 3d38c4414cf4ddab46a16d09c0dcc37c57354cb1 | 26,311 |
def genome_2_validator(genome_2):
"""
Conducts various test to ensure the stability of the Genome 2.0
"""
standard_gene_length = 27
def structure_test_gene_lengths():
"""
Check length requirements for each gene
"""
gene_anomalies = 0
for key in genome_2:
... | 7fe54b51673f3bc71cb8899f9a20b51d28d80957 | 26,312 |
import os
def product_info_from_tree(path):
"""Extract product information from a directory
Arguments:
path (str): path to a directory
"""
log.debug('Reading product version from %r', path)
product_txt = os.path.join(path, 'product.txt')
if not os.path.isfile(product_txt):
r... | 321f604e737cecadedf8f6ac34b83d55902d0bf4 | 26,313 |
def to_poly(group):
"""Convert set of fire events to polygons."""
# create geometries from events
geometries = []
for _, row in group.iterrows():
geometry = corners_to_poly(row['H'], row['V'], row['i'], row['j'])
geometries.append(geometry)
# convert to single polygon
vt_poly =... | 5482121dc57e3729695b3b3962339cb51c1613dc | 26,314 |
def get_user():
"""
Get the current logged in user to Jupyter
:return: (str) name of the logged in user
"""
uname = env_vars.get('JUPYTERHUB_USER') or env_vars.get('USER')
return uname | a7ece43874794bbc62a43085a5bf6b352a293ea2 | 26,315 |
import logging
import time
def get_top_articles(update=False):
"""
Retrieve 10 most recent wiki articles from the datastore or from memcache
:param update: when this is specified, articles are retrived from the datastore
:return: a list of 10 most recent articles
"""
# use caching to avoid run... | b5ac25e8d06acd48e3ee4157fcfcffd580cf421e | 26,316 |
def bucket(x, bucket_size):
"""'Pixel bucket' a numpy array.
By 'pixel bucket', I mean, replace groups of N consecutive pixels in
the array with a single pixel which is the sum of the N replaced
pixels. See: http://stackoverflow.com/q/36269508/513688
"""
for b in bucket_size: assert float(b).is... | 8ff3eda1876b48a8bdd4fbfe6b740ed7e3498c51 | 26,317 |
def create_msg(q1,q2,q3):
""" Converts the given configuration into a string of bytes
understood by the robot arm.
Parameters:
q1: The joint angle for the first (waist) axis.
q2: The joint angle for the second (shoulder) axis.
q3: The joint angle for the third (wrist) axis.
Returns:
The string of bytes.
... | 26f9954a55686c9bf8bd08cc7a9865f3e4e602e3 | 26,318 |
def get_config():
"""Provide the global configuration object."""
global __config
if __config is None:
__config = ComplianceConfig()
return __config | cdaa82445b4f260c7b676dc25ce4e8009488603e | 26,319 |
import array
def size(x: "array.Array") -> "array.Array":
"""Takes a tensor as input and outputs a int64 scalar that equals to the total
number of elements of the input tensor.
Note that len(x) is more efficient (and should give the same result).
The difference is that this `size` free function adds ... | 2e80223a2468f0d9363ad2aa148d14a090c0d009 | 26,320 |
def linspace(start, stop, length):
"""
Create a pdarray of linearly spaced points in a closed interval.
Parameters
----------
start : scalar
Start of interval (inclusive)
stop : scalar
End of interval (inclusive)
length : int
Number of points
Returns
-------... | 82d90c0f6dcdca87b5c92d2668b289a1db0b2e64 | 26,321 |
def _load_corpus_as_dataframe(path):
"""
Load documents corpus from file in 'path'
:return:
"""
json_data = load_json_file(path)
tweets_df = _load_tweets_as_dataframe(json_data)
_clean_hashtags_and_urls(tweets_df)
# Rename columns to obtain: Tweet | Username | Date | Hashtags | Likes | R... | 7113b51ec7e35d2b11697e8b049ba9ef7e1eb903 | 26,322 |
def UNTL_to_encodedUNTL(subject):
"""Normalize a UNTL subject heading to be used in SOLR."""
subject = normalize_UNTL(subject)
subject = subject.replace(' ', '_')
subject = subject.replace('_-_', '/')
return subject | 51c863327eec50232d83ea645d4f89f1e1829444 | 26,323 |
def parse_cigar(cigarlist, ope):
""" for a specific operation (mismach, match, insertion, deletion... see above)
return occurences and index in the alignment """
tlength = 0
coordinate = []
# count matches, indels and mismatches
oplist = (0, 1, 2, 7, 8)
for operation, length in cigarlist:
if operation... | 4eceab70956f787374b2c1cffa02ea7ce34fe657 | 26,324 |
def _decode_token_compact(token):
"""
Decode a compact-serialized JWT
Returns {'header': ..., 'payload': ..., 'signature': ...}
"""
header, payload, raw_signature, signing_input = _unpack_token_compact(token)
token = {
"header": header,
"payload": payload,
"signature": b... | e7dbe465c045828e0e7b443d01ea2daeac2d9b9a | 26,325 |
def _top_N_str(m, col, count_col, N):
"""
Example
-------
>>> df = pd.DataFrame({'catvar':["a","b","b","c"], "numvar":[10,1,100,3]})
>>> _top_N_str(df, col = 'catvar', count_col ='numvar', N=2)
'b (88.6%), a (8.8%)'
"""
gby = m.groupby(col)[count_col].agg(np.sum)
gby = 100 * gby / gb... | d80e5f7822d400e88594a96c9e1866ede7d9843e | 26,326 |
def insert_box(part, box, retries=10):
"""Adds a box / connector to a part using boolean union. Operating under the assumption
that adding a connector MUST INCREASE the number of vertices of the resulting part.
:param part: part to add connector to
:type part: trimesh.Trimesh
:param box: connector ... | 76f29f8fb4ebdd67b7385f5a81fa87df4b64d4c7 | 26,327 |
import argparse
def parse_args():
"""Parse command line arguments."""
parser = argparse.ArgumentParser()
parser.add_argument('--task', type=str, required=True)
parser.add_argument('--spacy_model', type=str, default='en_core_web_sm')
parser.add_argument('--omit_answers', action='store_true')
pa... | 905f9e46d17b45e28afeaf13769434ad75685582 | 26,328 |
def pnorm(x, p):
"""
Returns the L_p norm of vector 'x'.
:param x: The vector.
:param p: The order of the norm.
:return: The L_p norm of the matrix.
"""
result = 0
for index in x:
result += abs(index) ** p
result = result ** (1/p)
return result | 110fea5cbe552f022c163e9dcdeacddd920dbc65 | 26,329 |
import os
def get_arr(logdir_multiseed, acc_thresh_dict=None, agg_mode='median'):
"""
Reads a set of evaluation log files for multiple seeds and computes
the aggregated metrics with error bounds. Also computes the CL metrics
with error bounds.
Args:
logdir_multiseed (str): Path to the p... | 11d17378bb9824a6e112335bfa2c9c219b3d9c18 | 26,330 |
def _kneighborsclassifier(*, train, test, x_predict=None, metrics, n_neighbors=5, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_params=None, n_jobs=None, **kwargs):
"""
For more info visit :
https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsCl... | 0a8ff00a5fc4978758432df34947895688b225cd | 26,331 |
def overlap(batch_x, n_context=296, n_input=39):
"""
Due to the requirement of static shapes(see fix_batch_size()),
we need to stack the dynamic data to form a static input shape.
Using the n_context of 296 (1 second of mfcc)
"""
window_width = n_context
num_channels = n_input
batch_x =... | 75936fe9ecb0f3e278fd6c990cab297c878006b1 | 26,332 |
def eval_on_train_data_input_fn(training_dir, hyperparameters):
"""
:param training_dir: The directory where the training CSV is located
:param hyperparameters: A parameter set of the form
{
'batch_size': TRAINING_BATCH_SIZE,
'num_epochs': TRAINING_EPOCHS,
'data_downsize': DATA_D... | 07f9b33c936be5914b30697c25085baa25799d0d | 26,333 |
import json
def load_config(config_file):
"""
加载配置文件
:param config_file:
:return:
"""
with open(config_file, encoding='UTF-8') as f:
return json.load(f) | 85bab8a60e3abb8af56b0ae7483f2afe992d84b4 | 26,334 |
def decode(var, encoding):
"""
If not already unicode, decode it.
"""
if PY2:
if isinstance(var, unicode):
ret = var
elif isinstance(var, str):
if encoding:
ret = var.decode(encoding)
else:
ret = unicode(var)
els... | da59232e9e7715c5c1e87fde99f19997c8e1e890 | 26,335 |
from typing import List
import os
def read_annotation_files(annotation_files_directory: str, audio_files_directory: str,
max_audio_files: int = np.inf, exclude_classes: List[str] = None) -> List[AudioFile]:
"""
Reads annotation files in a directory specified.
:param annotation_f... | c4a89d10353c2e46be9a205d89918bc34f3a9a07 | 26,336 |
def vehicle_emoji(veh):
"""Maps a vehicle type id to an emoji
:param veh: vehicle type id
:return: vehicle type emoji
"""
if veh == 2:
return u"\U0001F68B"
elif veh == 6:
return u"\U0001f687"
elif veh == 7:
return u"\U000026F4"
elif veh == 12:
return u"\U0... | 8068ce68e0cdf7f220c37247ba2d03c6505a00fe | 26,337 |
import functools
def np_function(func=None, output_dtypes=None):
"""Decorator that allow a numpy function to be used in Eager and Graph modes.
Similar to `tf.py_func` and `tf.py_function` but it doesn't require defining
the inputs or the dtypes of the outputs a priori.
In Eager mode it would convert the tf.... | 5ed18b1575ec88fe96c27e7de38b00c5a734ee91 | 26,338 |
from typing import List
from typing import Dict
def constituency_parse(doc: List[str]) -> List[Dict]:
"""
parameter: List[str] for each doc
return: List[Dict] for each doc
"""
predictor = get_con_predictor()
results = []
for sent in doc:
result = predictor.predict(sentence=sent)
... | 30dd8eca61412083f1f11db6dc8aeb27bc171de9 | 26,339 |
import os
def ifFileExists(filePath):
"""
Cheks if the file exists; returns True/False
filePath File Path
"""
return os.path.isfile(filePath) | 2c4d6c332cff980a38d147ad0eafd1d0c3d902fc | 26,340 |
def extract_results(filename):
""" Extract intensity data from a FLIMfit results file.
Converts any fraction data (e.g. beta, gamma) to contributions
Required arguments:
filename - the name of the file to load
"""
file = h5py.File(filename,'r')
results = file['results']
keys = sorted_nicely(... | c4a9f4f66a53050ea55cb1bd266edfa285000717 | 26,341 |
async def bundle_status(args: Namespace) -> ExitCode:
"""Query the status of a Bundle in the LTA DB."""
response = await args.di["lta_rc"].request("GET", f"/Bundles/{args.uuid}")
if args.json:
print_dict_as_pretty_json(response)
else:
# display information about the core fields
p... | 2efb12b4bba3d9e920c199ad1e7262a24220d603 | 26,342 |
def determine_step_size(mode, i, threshold=20):
"""
A helper function that determines the next action to take based on the designated mode.
Parameters
----------
mode (int)
Determines which option to choose.
i (int)
the current step number.
threshold (float)
The ... | 9b59ebe5eeac13f06662e715328d2d9a3ea0e9a2 | 26,343 |
def scroll_down(driver):
"""
This function will simulate the scroll down of the webpage
:param driver: webdriver
:type driver: webdriver
:return: webdriver
"""
# Selenium supports execute JavaScript commands in current window / frame
# get scroll height
last_height = driver.execut... | 7d68201f3a49950e509a7e389394915475ed8c94 | 26,344 |
from datetime import datetime
def processing():
"""Renders the khan projects page."""
return render_template('stem/tech/processing/gettingStarted.html', title="Processing - Getting Started", year=datetime.now().year) | 53f6c69692591601dcb41c7efccad60bbfaf4cf7 | 26,345 |
def conv_unit(input_tensor, nb_filters, mp=False, dropout=0.1):
"""
one conv-relu-bn unit
"""
x = ZeroPadding2D()(input_tensor)
x = Conv2D(nb_filters, (3, 3))(x)
x = relu()(x)
x = BatchNormalization(axis=3, momentum=0.66)(x)
if mp:
x = MaxPooling2D(pool_size=(3, 3), strides=(2, ... | 7c24dae045c38c073431e4fab20687439601b141 | 26,346 |
import torch
def combine_vectors(x, y):
"""
Function for combining two vectors with shapes (n_samples, ?) and (n_samples, ?).
Parameters:
x: (n_samples, ?) the first vector.
In this assignment, this will be the noise vector of shape (n_samples, z_dim),
but you shouldn't need to know ... | 700ea418c6244dc745bf6add89ad786c4444d2fe | 26,347 |
def expandMacros(context, template, outputFile, outputEncoding="utf-8"):
"""
This function can be used to expand a template which contains METAL
macros, while leaving in place all the TAL and METAL commands.
Doing this makes editing a template which uses METAL macros easier,
becau... | 04aad464f975c5ee216e17f93167be51eea8f6e6 | 26,348 |
def graph_papers(path="papers.csv"):
"""
Spit out the connections between people by papers
"""
data = defaultdict(dict)
jkey = u'Paper'
for gkey, group in groupby(read_csv(path, key=jkey), itemgetter(jkey)):
for pair in combinations(group, 2):
for idx,row in enumerate(pair... | 43cae08f303707b75da2b225112fa0bc448306d9 | 26,349 |
def tariterator1(fileobj, check_sorted=False, keys=base_plus_ext, decode=True):
"""Alternative (new) implementation of tariterator."""
content = tardata(fileobj)
samples = group_by_keys(keys=keys)(content)
decoded = decoder(decode=decode)(samples)
return decoded | 8ea80d266dfe9c63336664aaf0fcac520e620382 | 26,350 |
def juego_nuevo():
"""Pide al jugador la cantidad de filas/columnas, cantidad de palabras y las palabras."""
show_title("Crear sopa de NxN letras")
nxn = pedir_entero("Ingrese un numero entero de la cantidad de\nfilas y columnas que desea (Entre 10 y 20):\n",10,20)
n_palabras = pedir_entero("I... | ec42615c3934fd98ca5975f99d215f597f353842 | 26,351 |
def mk_sd_graph(pvalmat, thresh=0.05):
"""
Make a graph with edges as signifcant differences between treatments.
"""
digraph = DiGraph()
for idx in range(len(pvalmat)):
digraph.add_node(idx)
for idx_a, idx_b, b_bigger, p_val in iter_all_pairs_cmp(pvalmat):
if p_val > thresh:
... | f219d964ec90d58162db5e72d272ec8138f8991e | 26,352 |
def body2hor(body_coords, theta, phi, psi):
"""Transforms the vector coordinates in body frame of reference to local
horizon frame of reference.
Parameters
----------
body_coords : array_like
3 dimensional vector with (x,y,z) coordinates in body axes.
theta : float
Pitch (or ele... | 2e0e8f6bf3432a944a350fb7df5bdfa067074448 | 26,353 |
def negloglikelihoodZTNB(args, x):
"""Negative log likelihood for zero truncated negative binomial."""
a, m = args
denom = 1 - NegBinom(a, m).pmf(0)
return len(x) * np.log(denom) + negloglikelihoodNB(args, x) | 8458cbc02a00fd2bc37d661a7e34a61afccb6124 | 26,354 |
def combine(m1, m2):
"""
Returns transform that combines two other transforms.
"""
return np.dot(m1, m2) | 083de20237f484806c356c0b29c42ff28aa801f6 | 26,355 |
import torch
def _acg_bound(nsim, k1, k2, lam, mtop = 1000):
# John T Kent, Asaad M Ganeiber, and Kanti V Mardia.
# A new unified approach forthe simulation of a wide class of directional distributions.
# Journal of Computational andGraphical Statistics, 27(2):291–301, 2018.
"""
... | 45d96fee1b61d5c020e355df76d77c78483a3a0b | 26,356 |
import os
import shutil
def anonymise_eeg(
original_file: str,
destination_file: str,
field_name: str = '',
field_surname: str = '',
field_birthdate: str = '',
field_sex: str = '',
field_folder: str = '',
field_centre: str = '',
field_comment: str = ''
):
"""Anonymise an .eeg f... | d66e62448d0372754bd5a2e83e992c0e32122994 | 26,357 |
def melspecgrams_to_specgrams(logmelmag2 = None, mel_p = None, mel_downscale=1):
"""Converts melspecgrams to specgrams.
Args:
melspecgrams: Tensor of log magnitudes and instantaneous frequencies,
shape [freq, time], mel scaling of frequencies.
Returns:
specgrams: Tensor of log magnitudes... | 34090358eff2bf803af9b56c210d5e093b1f2900 | 26,358 |
from scipy.stats.mstats import gmean
import numpy as np
def ligandScore(ligand, genes):
"""calculate ligand score for given ligand and gene set"""
if ligand.ligand_type == "peptide" and isinstance(ligand.preprogene, str):
# check if multiple genes needs to be accounted for
if isinstance(eval... | 68141e9a837619b087cf132c6ba593ba5b1ef43d | 26,359 |
def eval(x):
"""Evaluates the value of a variable.
# Arguments
x: A variable.
# Returns
A Numpy array.
# Examples
```python
>>> from keras import backend as K
>>> kvar = K.variable(np.array([[1, 2], [3, 4]]), dtype='float32')
>>> K.eval(kvar)
array(... | a9b5473cc71cd999d6e85fd760018d454c194c04 | 26,360 |
from typing import Optional
def triple_in_shape(expr: ShExJ.shapeExpr, label: ShExJ.tripleExprLabel, cntxt: Context) \
-> Optional[ShExJ.tripleExpr]:
""" Search for the label in a shape expression """
te = None
if isinstance(expr, (ShExJ.ShapeOr, ShExJ.ShapeAnd)):
for expr2 in expr.shapeEx... | a1e9ba9e7c282475c775c17f52b51a78c3dcfd71 | 26,361 |
def poly_learning_rate(base_lr, curr_iter, max_iter, power=0.9):
"""poly learning rate policy"""
lr = base_lr * (1 - float(curr_iter) / max_iter) ** power
return lr | fdb2b6ed3784deb3fbf55f6b23f6bd32dac6a988 | 26,362 |
def parent_path(xpath):
"""
Removes the last element in an xpath, effectively yielding the xpath to the parent element
:param xpath: An xpath with at least one '/'
"""
return xpath[:xpath.rfind('/')] | b435375b9d5e57c6668536ab819f40ae7e169b8e | 26,363 |
from datetime import datetime
def change_project_description(project_id):
"""For backwards compatibility: Change the description of a project."""
description = read_request()
assert isinstance(description, (str,))
orig = get_project(project_id)
orig.description = description
orig.lastUpdated =... | c6b59cfbbffb353943a0a7ba4160ffb0e2382a51 | 26,364 |
import unittest
def run_all(examples_main_path):
"""
Helper function to run all the test cases
:arg: examples_main_path: the path to main examples directory
"""
# test cases to run
test_cases = [TestExample1,
TestExample2,
TestExample3,
Tes... | 9a5176bff4e2c82561e3b0dbee467cd1dec0e63e | 26,365 |
def get_queue(queue):
"""
:param queue: Queue Name or Queue ID or Queue Redis Key or Queue Instance
:return: Queue instance
"""
if isinstance(queue, Queue):
return queue
if isinstance(queue, str):
if queue.startswith(Queue.redis_queue_namespace_prefix):
return Queue.... | 159860f2efa5c7a2643d4ed8b316e8abca85e67f | 26,366 |
def ptttl_to_samples(ptttl_data, amplitude=0.5, wavetype=SINE_WAVE):
"""
Convert a PTTTLData object to a list of audio samples.
:param PTTTLData ptttl_data: PTTTL/RTTTL source text
:param float amplitude: Output signal amplitude, between 0.0 and 1.0.
:param int wavetype: Waveform type for output si... | f4be93a315ff177cbdf69249f7efece55561b431 | 26,367 |
from typing import Union
from pathlib import Path
from typing import Tuple
import numpy
import pandas
def read_output_ascii(
path: Union[Path, str]
) -> Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray]:
"""Read an output file (raw ASCII format)
Args:
path (str): path to the file
... | ef3008f6cf988f7bd42ccb75bfd6cfd1a58e28ae | 26,368 |
def AliasPrefix(funcname):
"""Return the prefix of the function the named function is an alias of."""
alias = __aliases[funcname][0]
return alias.prefix | 771c0f665ddad2427759a5592608e5467005c26d | 26,369 |
import logging
import subprocess
def run_command(*cmd_args, **kargs):
"""
Shell runner helper
Work as subproccess.run except check is set to true by default and
stdout is not printed unless the logging level is DEBUG
"""
logging.debug("Run command: " + " ".join(map(str, cmd_args)))
if not ... | ce191b500176e263ecf1035f3ae467a334045757 | 26,370 |
from typing import Optional
from typing import Tuple
from typing import Callable
def connect(
sender: QWidget,
signal: str,
receiver: QObject,
slot: str,
caller: Optional[FormDBWidget] = None,
) -> Optional[Tuple[pyqtSignal, Callable]]:
"""Connect signal to slot for QSA."""
# Parameters e... | 2ebeca355e721c5fad5ec6aac24a59587e4e86bd | 26,371 |
import torch
def get_detection_input(batch_size=1):
"""
Sample input for detection models, usable for tracing or testing
"""
return (
torch.rand(batch_size, 3, 224, 224),
torch.full((batch_size,), 0).long(),
torch.Tensor([1, 1, 200, 200]).repeat((batch_size, 1)),
... | 710a5ed2f89610555d347af568647a8768f1ddb4 | 26,372 |
def build_tables(ch_groups, buffer_size, init_obj=None):
""" build tables and associated I/O info for the channel groups.
Parameters
----------
ch_groups : dict
buffer_size : int
init_obj : object with initialize_lh5_table() function
Returns
-------
ch_to_tbls : dict or Table
... | 964bc6a817688eb8426976cec2b0053f43c6ed79 | 26,373 |
def segmentspan(revlog, revs):
"""Get the byte span of a segment of revisions
revs is a sorted array of revision numbers
>>> revlog = _testrevlog([
... 5, #0
... 10, #1
... 12, #2
... 12, #3 (empty)
... 17, #4
... ])
>>> segmentspan(revlog, [0, 1, 2, 3, 4])
17
>>... | 51624b3eac7bba128a2e702c3387bbaab4974143 | 26,374 |
def is_stateful(change, stateful_resources):
""" Boolean check if current change references a stateful resource """
return change['ResourceType'] in stateful_resources | 055465870f9118945a9e5f2ff39be08cdcf35d31 | 26,375 |
import pwd
import os
def get_osusername():
"""Get the username of the current process."""
if pwd is None:
raise OSError("get_username cannot be called on Windows")
return pwd.getpwuid(os.getuid())[0] | db72cb393a8fd79e5d2078b5597a0c037595b3f6 | 26,376 |
def get_session_from_webdriver(driver: WebDriver, registry: Registry) -> RedisSession:
"""Extract session cookie from a Selenium driver and fetch a matching pyramid_redis_sesssion data.
Example::
def test_newsletter_referral(dbsession, web_server, browser, init):
'''Referral is tracker for... | 0faaa394c065344117cec67ec824ec5186252ee2 | 26,377 |
import sys
def parse_argv():
""" Retrieve fields from sys.argv """
if len(sys.argv) == 2:
main_file = sys.argv[1]
with open(main_file) as main_file_handle:
main_code = main_file_handle.read()
return sys.argv[0], {main_file: main_code}, main_file, main_code, None, None, None... | fdc58acbe6dc4f7ccef929da7015269746986fed | 26,378 |
from typing import Tuple
def paper() -> Tuple[str]:
"""
Use my paper figure style.
Returns
-------
Tuple[str]
Colors in the color palette.
"""
sns.set_context("paper")
style = { "axes.spines.bottom": True,
"axes.spines.left": True,
"axes.spines.righ... | 6e53247c666db62be1d5bf5ad5d77288af277d2d | 26,379 |
import difflib
def _get_diff_text(old, new):
"""
Returns the diff of two text blobs.
"""
diff = difflib.unified_diff(old.splitlines(1), new.splitlines(1))
return "".join([x.replace("\r", "") for x in diff]) | bd8a3d49ccf7b6c18e6cd617e6ad2ad8324de1cc | 26,380 |
import numpy as np
import matplotlib.pyplot as plt
from astropy.table import Table
from astropy.time import Time
import astropy.units as u
from astropy.coordinates import SkyCoord
from shapely.geometry import Polygon
from descartes import PolygonPatch
from astroquery.alma import Alma
import os
def alma_query(tab, mak... | 3c4409f35b27939f332c31a57f4450b1229b7034 | 26,381 |
def GetStatus(operation):
"""Returns string status for given operation.
Args:
operation: A messages.Operation instance.
Returns:
The status of the operation in string form.
"""
if not operation.done:
return Status.PENDING.name
elif operation.error:
return Status.ERROR.name
else:
retu... | c9630528dd9b2e331a9d387cac0798bf07646603 | 26,382 |
import argparse
from datetime import datetime
def get_args(args):
"""Get the script arguments."""
description = "tvtid - Feteches the tv schedule from client.dk"
arg = argparse.ArgumentParser(description=description)
arg.add_argument(
"-d",
"--date",
metavar="datetime",
... | 0068f54fc5660896a8ab6998de9da3909c8e1a6b | 26,383 |
def ft2m(ft):
"""
Converts feet to meters.
"""
if ft == None:
return None
return ft * 0.3048 | ca2b4649b136c9128b5b3ae57dd00c6cedd0f383 | 26,384 |
def show_colors(*, nhues=17, minsat=10, unknown='User', include=None, ignore=None):
"""
Generate tables of the registered color names. Adapted from
`this example <https://matplotlib.org/examples/color/named_colors.html>`__.
Parameters
----------
nhues : int, optional
The number of break... | 34b45185af96f3ce6111989f83d584006ebceb49 | 26,385 |
def get_all_lights(scene, include_light_filters=True):
"""Return a list of all lights in the scene, including
mesh lights
Args:
scene (byp.types.Scene) - scene file to look for lights
include_light_filters (bool) - whether or not light filters should be included in the list
Returns:
(list)... | 4570f36bdfbef287f38a250cddcdc7f8c8d8665d | 26,386 |
def get_df(path):
"""Load raw dataframe from JSON data."""
with open(path) as reader:
df = pd.DataFrame(load(reader))
df['rate'] = 1e3 / df['ms_per_record']
return df | 0e94506fcaa4bd64388eb2def4f9a66c19bd9b32 | 26,387 |
def _format_distribution_details(details, color=False):
"""Format distribution details for printing later."""
def _y_v(value):
"""Print value in distribution details."""
if color:
return colored.yellow(value)
else:
return value
# Maps keys in configuration to... | ccfa7d9b35b17ba9889f5012d1ae5aa1612d33b1 | 26,388 |
async def async_get_relation_id(application_name, remote_application_name,
model_name=None,
remote_interface_name=None):
"""
Get relation id of relation from model.
:param model_name: Name of model to operate on
:type model_name: str
:... | 2447c08c57d2ed4548db547fb4c347987f0ac88b | 26,389 |
from operator import or_
def get_timeseries_references(session_id, search_value, length, offset, column, order):
"""
Gets a filtered list of timeseries references.
This function will generate a filtered list of timeseries references belonging to a session
given a search value. The length, offset, and... | 67011d7d1956259c383cd2722ae4035c28e6a5f3 | 26,390 |
import os
import re
def get_current_version():
"""Get current version"""
base_dir = os.path.abspath(os.path.dirname(__file__))
version_file = os.path.join(base_dir, "evaluations", "__init__.py")
with open(version_file, 'r') as opened_file:
return re.search(
r'^__version__ = [\'"]([... | b1e6a9acfe59b7603c82c93868e634d93ae4cd86 | 26,391 |
def mxprv_from_bip39_mnemonic(
mnemonic: Mnemonic, passphrase: str = "", network: str = "mainnet"
) -> bytes:
"""Return BIP32 root master extended private key from BIP39 mnemonic."""
seed = bip39.seed_from_mnemonic(mnemonic, passphrase)
version = NETWORKS[network].bip32_prv
return rootxprv_from_see... | ceb5f5e853f7964015a2a69ea2fdb26680acf2b3 | 26,392 |
import os
import codecs
import sys
import platform
def setup_ebook_home(args, conf):
"""
Setup user's ebook home, config being set with this order of precedence:
- CLI params
- ENV vars
- saved values in ogre config
- automatically created in $HOME
"""
ebook_home = None
# 1) l... | 1d18e120304bb2b21df7252c6ea8c4e09fdf6314 | 26,393 |
def translate_text(
text: str, source_language: str, target_language: str
) -> str:
"""Translates text into the target language.
This method uses ISO 639-1 compliant language codes to specify languages.
To learn more about ISO 639-1, see:
https://www.w3schools.com/tags/ref_language_codes.as... | ed82dbb2fd89398340ed6ff39132f95758bfab97 | 26,394 |
def evt_cache_staged_t(ticket):
""" create event EvtCacheStaged from ticket ticket
"""
fc_keys = ['bfid' ]
ev = _get_proto(ticket, fc_keys = fc_keys)
ev['cache']['en'] = _set_cache_en(ticket)
return EvtCacheStaged(ev) | 86543ca98257cab28e4bfccef229c8d8e5b6893b | 26,395 |
from typing import Dict
def _get_setup_keywords(pkg_data: dict, keywords: dict) -> Dict:
"""Gather all setuptools.setup() keyword args."""
options_keywords = dict(
packages=list(pkg_data),
package_data={pkg: list(files)
for pkg, files in pkg_data.items()},
)
keyw... | 34f2d52c484fc4e49ccaca574639929756cfa4dc | 26,396 |
import six
def flatten(x):
"""flatten(sequence) -> list
Returns a single, flat list which contains all elements retrieved
from the sequence and all recursively contained sub-sequences
(iterables).
Examples:
>>> [1, 2, [3,4], (5,6)]
[1, 2, [3, 4], (5, 6)]
>>> flatten([[[1,2,3], (42,... | 041807c1622f644c062a5adb0404d14589cc543b | 26,397 |
from clawpack.visclaw import colormaps, geoplot
from numpy import linspace
from clawpack.visclaw.data import ClawPlotData
from clawpack.visclaw import gaugetools
import pylab
import pylab
from numpy import ma
from numpy import ma
import pylab
import pylab
from pylab import plot, xticks, floor, xlabel
def setplot(plot... | a777686f5b8fafe8c2a109e486242a16d25a463b | 26,398 |
from typing import Dict
import json
def load_spider_tables(filenames: str) -> Dict[str, Schema]:
"""Loads database schemas from the specified filenames."""
examples = {}
for filename in filenames.split(","):
with open(filename) as training_file:
examples.update(process_dbs(json.load(tr... | 1575d0afd4efbe5f53d12be1c7dd3537e54fc46c | 26,399 |
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