content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_role():
"""Get the role of the current process"""
return CUR_ROLE | dc4908bd5287952bd6ecd6a58f84e5e3007464e2 | 67,300 |
def generos():
"""
Muestra las configuraciones para los generos
"""
grid = webgrid.WebGrid(crud)
grid.datasource = db(db.generos).select()
grid.pagesize = 20
#grid.fields = ['db.catmod.id', 'db.catmod.nombre', 'db.catmod.posicion']
#grid.filters = ['db.catmod.catmod', 'db.catmod.nombre']... | 880ec4d7b5f9f7f848cc8d33c1a97a30adf72e99 | 67,301 |
def searcher(nlp: Language) -> TokenSearcher:
"""It returns a token searcher."""
return TokenSearcher(vocab=nlp.vocab) | 26ec606d6eb2792be668f2fc0eb0ae09629591fc | 67,302 |
def replace_value(data, value=0):
"""Replace specific values in array with NaN
:param data: Array where values should be replaced
:type data: NumPy.Array
:param value: value inside array to be replaced with NaN, defaults to 0
:type value: int, optional
:return: array with new values
:rtype:... | 501f7daca3942a9d28ebf95fb3285af77a4230d0 | 67,303 |
def random_csr(shape, density, sorted_):
"""
Generate a random qutip CSR matrix with the given shape, nnz density, and
with indices that are either sorted or unsorted. The nnz elements will
always be at least one (use data.csr.zeros otherwise).
"""
return qutip.core.data.CSR(random_scipy_csr(sh... | effe8ceb67e45ab08ff258f071c8109bc49dd853 | 67,304 |
import pickle
def getScores(imgURLs, captionTexts, sep='\n'):
"""
The function
"""
modelpath = 'models/xgbr_1.pkl'
model = pickle.load(open(modelpath, 'rb'))
imgURLs = imgURLs.replace('\r','')
captionTexts = captionTexts.replace('\r','')
imgURLs = imgURLs.split(sep)
captionTexts ... | 5dd97f8c036cffbe31d1d954a12026e340c2126b | 67,305 |
import socket
def _get_vault_path(device_uuid, config):
"""Generate full vault path for a given block device UUID
:param: device_uuid: String of the device UUID
:param: config: configparser object of vaultlocker config
:returns: str: Path to vault resource for device
"""
return '{}/{}/{}'.for... | d6b1aab6036f348560b8549584a4e0f4b51cb4bd | 67,306 |
def prompt_timestamp(msg: str) -> NychthemeronTime:
"""Prompts the user to enter a timestamp to get a NychthemeronTime."""
while True: # Enter input loop.
timestamp = input(msg)
try:
nt = parse_timestamp(timestamp)
break # Exit the input loop if successful.
exce... | 161b93336fd97ea1f756de193a679716d5c26ea0 | 67,307 |
def slice2limits(slices):
"""
Create a tuple of min,max limits from a set of slices
Parameters:
* slices: list of slices
Returns: Tuple of minimum and maximum indices
"""
mins = [s.start for s in slices]
maxs = [s.stop-1 for s in slices]
return mins,maxs | 1196e67fea135fb3c363def9d5fe53a0ada9b0af | 67,308 |
def get_element(traj_frag_molid, frame_idx, index):
"""
Parse atom label and return element
Parameters
----------
traj_frag_molid: int
Denotes trajectory id in VMD
frame_idx: int
Frame of simulation in trajectory fragment
index: string
VMD atom index
Returns
... | 90a73dab6a3c28d6d3338ebd61f742eab61fba2d | 67,309 |
def init_correlation_wf(name="correlation_wf"):
"""
This workflow calculates betaseries correlations using a parcellation
from an atlas.
.. workflow::
:graph2use: orig
:simple_form: yes
from nibetaseries.workflows.analysis import init_correlation_wf
wf = init_correlatio... | c35345fc0621a4bd3aa15c757f718d21b09f9e99 | 67,310 |
def solution(array, n_rotations):
"""
Returns the Cyclic Rotation of array with n_rotations positions to the right.
"""
n = len(array)
n_rotations = n_rotations % n if n > 0 else 0
return array[n - n_rotations:] + array[:n - n_rotations] | 6f5edc0c8ec3d0e58830466e61577e80a725a624 | 67,311 |
def lin_fall(x, max):
"""f(0)=1. Linear fall off. Hits 0 at max."""
return clip01((max - x) / x) | 1f231f733551a61f34b7f94bcc3c09150a5e76f4 | 67,312 |
import uuid
def get_promotion_lock(replica_set):
""" Take a promotion lock
Args:
replica_set - The replica set to take the lock against
Returns:
A unique identifer for the lock
"""
lock_identifier = str(uuid.uuid4())
log.info('Promotion lock identifier is '
'{lock_identi... | e454a75ce7f85d28c1dcd42867bbc28ae967c121 | 67,313 |
import re
def check_question(msg):
"""
提问
:param msg:
:return:
"""
return re.search('\?', msg) or re.search('？', msg) or re.search('吗?', msg) | 3ac884d153a32586d5dfe197b597f6e125bed8eb | 67,314 |
def count_all_problems_for_admin():
"""Returns the number of all problems.
Returns:
The count.
"""
return _db.problems.find({}).count() | f80e032989735a75111dc3ab8c1db660ad72b2f7 | 67,315 |
def search_optimal_strike(
table,
v_cue=1,
dt=0.02,
dang=0.5,
return_once_find=False,
event_based=False,
):
"""Search optimal strike."""
simulate_func = simulate_event_based if event_based else simulate
simulate_args = ({'return_once_pocket': True}
if event_based... | 8b04087c2470c0c5fd9f1f32cdd11c82b56de20f | 67,316 |
import urllib
def is_local():
"""Returns True if called on a local development machine.
Returns False if called on Google Cloud."""
global _is_local # pylint: disable=invalid-name
if _is_local is not None:
return _is_local
try:
# TODO(github.com/google/fuzzbench/issues/82): Get r... | c4f45483d82d14f183a7285492121d48c08dade1 | 67,317 |
def check_color(board: list, num=9) -> bool:
"""
Function check if in each color of board are unique elements.
It there are function return True. False otherwise.
>>> check_horizontal(["**** ****",\
"***1 ****",\
"** 3****",\
"* 4 1****",\
" 9 5 ",\
" 6 83 *",\
"3 1 **",\
" 8 2***",\
" 12 *... | 3a6e8418b227e8101f9a8d1338c79193da285bff | 67,318 |
import yaml
import json
def load_data(file_path, use_yaml=True):
"""Load data from a given YAML file into a Python dictionary.
:param file_path: path to your YAML file.
:param use_yaml: use yaml or json
:return: contents of the file as Python dict.
"""
with open(file_path, "r") as f:
... | b136e16cd614cfdb3ca791a6d64d513cf52dbf7c | 67,319 |
import gettext
def update(id):
"""Change user settings.
---
post:
summary: Change user settings
description: >
Update a role to change its display name, or to define a
new login password. Users can only update roles they have
write access to, i.e. their own.
param... | 8a084ac0a58a421e92447a51997ed3815df34a24 | 67,320 |
def load_n_z(block, sample='wl_number_density'):
""" Load the n(z) profile in each bin as a 2d array """
num_den = sample
n_z = []
N_zbins = block[num_den, 'nbin']
for i in range(1, N_zbins + 1):
n_z += [block.get_double_array_1d(num_den, 'bin_%d' % i)]
n_z = np.array(n_z)
z = bloc... | a2a2db598f31bd3f931042e5bb5dfee1f356f322 | 67,321 |
import time
def retry_on_exception_exponential_backoff(exceptions, initial_delay=0.1, total_delay=15, exponential_factor=2):
"""
Retries with exponential backoff.
:param exceptions: The exceptions that we will catch and retry on.
:type exceptions: list[Exception]
:param initial_delay: num seconds... | c642c383e1f9ef6b82bb01761abd1b1efda1ce4f | 67,322 |
def parallax_to_scale(p_meas, p_err, snr_lim=4.):
"""
Convert parallax flux density scalefactor `s ~ p**2`.
Parameters
----------
p_meas : float
Measured parallax.
p_std : float
Measured parallax error.
snr_lim : float, optional
The signal-to-noise ratio limit used... | 64aa4290e5166787ac8f2f1de96e421fc9e183c4 | 67,323 |
def install_msaccess(dataset,
file='access.mdb',
table_name='[{db} {table}]',
data_dir=DATA_DIR,
debug=False,
use_cache=True,
force=False,
hash_value=None):
"""Install d... | b157f6376e2080648fc8adc30a29864eac165e3d | 67,324 |
def levenshtein_distance(s1: str, s2: str) -> int:
"""Returns the levenshtein distance between two strings"""
# https://stackoverflow.com/a/32558749
if len(s1) > len(s2):
s1, s2 = s2, s1
distances = range(len(s1) + 1)
for i2, c2 in enumerate(s2):
distances_ = [i2 + 1]
for i1... | 1b70d6e2b6241e8b0296c3698aae322bb081fe8c | 67,325 |
from typing import Iterable
def validate_multiple_choice_param(
params: RequestParams, key: str, choices: Iterable
) -> RequestParams:
"""Verify that a multiple-choice request parameter contains valid value(s);
if not, raise an error.
**Used for endpoint-specific params.**
Returns:
Parame... | 5986b2fbed3756137d11462a9c9551418342f926 | 67,326 |
def mqtt_client(axis_device) -> MqttClient:
"""Returns the mqtt_client mock object."""
return MqttClient(axis_device.vapix.request) | 00568fe250132b5ec5fbcef87b3515780ed85cbf | 67,327 |
import os
def scm_install_package(source, for_qc=False, override=False):
"""
Compile the source code and generate a skeleton for production use.
This method will take your active directory and
:param source: s
:param for_qc:
:param override: `bool` ... | d2f6d494d48eaf7ff780848379004cae52920d41 | 67,328 |
from typing import Dict
def loads(text: str) -> Dict:
"""
Parses a text in Gura format
:param text: Text to be parsed
:raise: ParseError if the syntax of text is invalid
:return: Dict with all the parsed values
"""
return GuraParser().loads(text) | b7c9dc4d6a1c4fadba47b562c0a026d68e46acd3 | 67,329 |
def allocate_lan_networks(root, service, username, logger):
""" Main logic for allocating lan networks for remote sites"""
lan_pool = service.lan_pool # 10.16.0.0/16
pool_name = get_lan_pool_name(service)
prefix = lan_pool.split('/')[0] # 10.16.0.0
prefix_len = lan_pool.split('/')[1] # 16
v... | 8a973c8f78f4685311df643c813e3af2bbea464a | 67,330 |
import math
def flinn(stream, noise_thres=0):
"""
Computes the azimuth, incidence, rectilinearity and planarity after the
eigenstructure decomposition method of [Flinn1965b]_.
:param stream: ZNE sorted trace data
:type stream: List of ZNE sorted numpy arrays
:param noise_tresh: Variance of th... | 63b6895ff3945be93494b2e4db801dc6d356dd3c | 67,331 |
def _to_bool(value):
"""Simplified version of the bool filter.
Avoids having a dependency on Ansible in unit tests.
"""
if value == 'yes':
return True
if value == 'no':
return False
return bool(value) | 6e0da8b211ce638e19764a966c417841fafe2a5b | 67,332 |
import click
from datetime import datetime
def upload(conf):
"""
Upload to remote and wipe out the local data.
"""
click.secho('UPLOAD SYNC IN PROGRESS - PLEASE DO NOT INTERRUPT - %s' % datetime.now(), fg='yellow')
outcome = _clone(True, confDir = conf.confDir, confFiles = conf.confFiles, verbose = conf.v... | b3faf09469ad294071d09aaaa55b39653b88687f | 67,333 |
import os
def _process_single_file(file_path, language):
"""
Processes only one file from file_path and takes all items marked with
language. Creates a .vtt file.
Arguments:
file_path: Path of file to process.
language: The language of the file to process.
Returns:
None
... | d5d28ea48fa19a3038637695b6acf60deb3e7961 | 67,334 |
def get_mel(filename):
"""Process loaded audio to mel-spectrogram."""
audio, _ = load_wav_to_array(filename)
audio_norm = audio / config.au_max_wav_value
audio_norm = np.expand_dims(audio_norm, 0)
melspec = _stft.mel_spectrogram(audio_norm)
melspec = np.squeeze(melspec, 0)
return melspec | f621821d61696d5f97a6ad203e9d31cd737fec70 | 67,335 |
import math
def tan(x):
"""tan(x)
Return the tangent of x."""
x = complex(x, 0)
sr = math.sin(x.real)
cr = math.cos(x.real)
shi = math.sinh(x.imag)
chi = math.cosh(x.imag)
rs = sr * chi
is_ = cr * shi
rc = cr * chi
ic = -sr * shi
d = rc*rc + ic * ic
real = (rs*rc ... | f2aedcff8f7fbce85169dab263163aa461367a53 | 67,336 |
from typing import Union
from typing import Optional
from typing import List
from typing import Dict
from pathlib import Path
import json
def compose_config(
config_path: Union[str, PathLike],
config_name: str,
job_name: str,
serialization_dir: Optional[Union[str, PathLike]] = None,
config_overrid... | 0284e10e9ef78e0c5a1c21b9619a95bb30c18440 | 67,337 |
def melted_power_ratio(index_df:PandasDf, power_df:PandasDf, freqs:list, selected_categories:list):
"""
Get power ratio and melt dataframe for seaborn plotting.
Parameters
----------
index_df : PandasDf, experiment index
power_df : PandasDf, contains pmat and frequency vectors for every row of ... | f427c2b5cab256f1101634d9f06e8bca6e3a9c46 | 67,338 |
def CreateInstanceDrbd8(nodes, fail=False):
"""Creates an instance using disk template 'drbd' on the given nodes.
@type nodes: list of nodes
@param nodes: nodes to be used by the instance
@return: the created instance
"""
assert len(nodes) > 1
return _CreateInstanceByDiskTemplateRaw(
":".join(n.prim... | 14205ca5d1a871247a3fd17ab946b3e6d8f8d037 | 67,339 |
def get_fn_at_x(xgrid, fn, at_x):
"""
Returns function at x
Args:
xgrid np.array(n_grid): Grid where function was evaluated
fn np.array((n_samples,n_grid)): Multiple function evaluations at xgrid
at_x float: Value closest to the desired function evaluation
Returns:
... | 5d70e4d720340c156a2c3987f2506523cb1c514e | 67,340 |
def getNet(chrom, loops, genes, pdis=2000, gap=1):
"""
Get the enhancer/promoter network for one chromosome.
"""
#step 1 get merged anchors
anchors = stichAnchors(chrom, loops, margin=gap)
#step 2 annotate anchors
nanchors = {}
ts = np.array([[tss] for tss in genes.keys()])
tree = ... | ce367e200c0156302db7fd5e4f56e14f7c220be8 | 67,341 |
import requests
def get_day_prices(date, rate=None):
""" Get PVPC prices for specific date.
Args:
date: Datetime obj of date to recover information for.
rate: Optional string. If None all available rates will be added to the
answer. If one is selected just that will be return.
... | 556431f368d14b24af7df1290b37359d08109d25 | 67,342 |
import random
def get_best_move(board, scores):
"""
Function that computes the best move for the machine given
the actual board state
"""
max_score = max(scores[row][col] for row, col in board.get_empty_squares())
candidates = [(row, col) for row, col in board.get_empty_squares()
... | afabd281ad1547b118cab10ccc912bdf4956f9c4 | 67,343 |
def kalman_filter(protein_at_observations,model_parameters,measurement_variance,derivative=True):
"""
Perform Kalman-Bucy filter based on observation of protein
copy numbers. This implements the filter described by Calderazzo et al., Bioinformatics (2018).
Parameters
----------
protein_at_obse... | 68c0ee11edea65ddea3d6596887f0d0d5d8297b8 | 67,344 |
import requests
def get_data(coin, currency, exchange):
"""
Fetch all time data from cryptocompare API
:param coin: crypto coin (BTC, XRP...)
:param currency: fiat (CAD, USD, EUR...)
:param exchange: name of the exchange
:return list[dict]: returns the all time data from the coin/currency prov... | 5b6d48399974b2872e22b8e98b92c779799b1955 | 67,345 |
def recognize_speech_from_mic(recognizer, microphone,language):
"""Transcribe speech from recorded from `microphone`.
Returns a dictionary with three keys:
"success": a boolean indicating whether or not the API request was
successful
"error": `None` if no error occured, otherwise a str... | 05156544e1c69fee866e17508e19b10dbee27faf | 67,346 |
from typing import Dict
def handle_response(res: Response) -> Dict[str, object]:
"""
Returns the sdk JSON response
:param res: A string url endpoint.
:type: str
:return: Dict[str, object]
"""
try:
json = res.json()
except ValueError as e:
handle_parse_error(e)
if ... | 2d326d81926ba2fbb44612bb76f56bc7406c6bba | 67,347 |
def encode_tag_ref_str(self, node, parent=None, attr_index=None):
"""This function is the same as encode_string, except that
when a halo reference string has zero length, the string doesnt
actually exist. It's not just a delimiter character, the string
isn't stored at all. To make it work, we instead re... | e6a3acc3691f122e3325fa70eb9ab427456e0edb | 67,348 |
def vapour_pressure_deficit(es, ea):
"""
VPD - Vapour Pressure Deficit
:param es:
:param ea: calculated by vp_from_rhmin_rhmax()
:return:
"""
return es - ea | cb1d22a236081b3de3f080f8f2e2acb64543620f | 67,349 |
def get_pca_mean_and_pre_whitener_epochs(epochs, picks, decim, pre_whitener):
"""Aux method based on ica._fit_epochs from mne v0.15"""
if picks is None:
picks = _pick_data_channels(epochs.info, exclude='bads', with_ref_meg=False)
# filter out all the channels the raw wouldn't have initialized
... | ed27c41fb68b83d2897dcd9ca7c3a6044ec454eb | 67,350 |
def _run_vagrant_command(node_id, args=[], creds={}):
"""
args: A tuple of arguments to a vagrant command line.
e.g. ['up', 'my_vm_name', '--no-provision']
"""
cd = 'cd "{}/{}"'.format(HOST_NODES_DIR, node_id)
command = ['vagrant'] + [arg for arg in args if arg is not None]
return _host_ssh... | 91822162ba28a4c6b9bbe9ba4328a2d956223696 | 67,351 |
async def _deleteIEXCloudAsync(
url, token="", version="stable", filter="", format="json"
):
"""for iex cloud"""
return await _deleteIEXCloudBaseAsync(
base_url=_URL_PREFIX_CLOUD, url=url, token=token, version=version, format=format
) | 85bb12c86dbf2537cd8a129b31aad2644e79ddf2 | 67,352 |
def evolve_lindblad_discrete(evolution_time, initial_densities,
system_eval_count,
controls=None,
cost_eval_step=1,
costs=list(),
hamiltonian=None,
... | f52b9bd15c6fd137f1f9b504f78c32577f2db198 | 67,353 |
import asyncio
def get_next_valid_seq_number(address: str, client: SyncClient) -> int:
"""
Query the ledger for the next available sequence number for an account.
Args:
address: the account to query.
client: the network client used to make network calls.
Returns:
The next val... | c3dd4d0427a39ba8e612a5689a1648567fd4276b | 67,354 |
from pathlib import Path
import logging
def readMad_hdf5 (filename, paramstr): #timelims=None
"""@author: Michael Hirsch / Anna Stuhlmacher
madrigal h5 read in function for the python implementation of GeoData for Madrigal Sondrestrom data
Input:
filename path to hdf5 file
list of parameters to lo... | ed22f485e1cd9a7f155c03fa353250843534d1d7 | 67,355 |
from operator import concat
def gumbel_sigmoid(logits, temperature, dtype=tf.float32, seed=0):
"""Gumbel Sigmoid Layer."""
logits = concat([logits, tf.zeros_like(logits)], 1)
prob = gumbel_softmax(logits, temperature, dtype=dtype, seed=seed)
return prob[:, 0] | 57871305349c8582e67f156f497c2cf9f4370f22 | 67,356 |
def rfft(data, **kargs):
""" rfft wrapper """
interface = fft_interface_select()
return fft_interface_format(interface.rfft, data, **kargs) | e8a0bfa89e02a956a07c5701386a3b9b1455ec93 | 67,357 |
def purefa_argument_spec():
"""Return standard base dictionary used for the argument_spec argument in AnsibleModule"""
return dict(
fa_url=dict(),
api_token=dict(no_log=True),
) | bc8302564bb397b523fde20a986465f3ecb496dd | 67,358 |
def get_release_id(request):
"""Get the environment ID to release, from request.
:param request: The falcon request object.
:type request: :obj:`falcon.request`
:return: The ID of the environment to release.
:rtype: str
"""
return request.get_param("release") | c6d9aa4907ea0f150ac86930560fca59b7388484 | 67,359 |
def get_submission_relations(doc_id, submission_id):
"""
Get suggested mentions for a document.
"""
relations = []
for row in db.select("""
SELECT subject, relation, object, provenances, confidence
FROM submission_relation
WHERE doc_id = %(doc_id)s
A... | 0b3b3c8fa8766690d9abf4c942ccbe2eb85b63cf | 67,360 |
def random_sense(ambiguous_word, pos=None):
""" Returns a random sense. """
if pos is None:
return custom_random.choice(wn.synsets(ambiguous_word))
else:
return custom_random.choice(wn.synsets(ambiguous_word, pos)) | 5f06ba50a29d680e992fcffc813d374eb6da4867 | 67,361 |
def train_GMM(data, cluster_num):
"""
训练混合高斯模型
"""
model = GaussianMixture(n_components=cluster_num, covariance_type='full')
model.fit(data)
return model | e58325939fbe8e3394b19528eb783cb87eb8938e | 67,362 |
def pf_rcc():
"""
pf(failed test t) is determined by the root cause param in the change where t fails
root cause is localized through manual inspection
"""
freq = {}
failures, misconfs = parsing_utils.failure_map()
for img in failures:
for t, rootcauses in failures[img][C_EFFECTIVE]... | e7cbf6b64b5c0d677be7bce0c3826c87f1c78c73 | 67,363 |
import logging
def get_markers(img, mode):
"""Get initial labels for segmentation."""
assert img.ndim == 4
markers = np.zeros(img.shape[0:3], dtype=np.int16)
if mode == 'DWI':
# Based on absolute value thresholds (non-scaled image).
bg, fg1, fg2 = np.percentile(img, 50), 1400, 1600
... | eb31fa5a2549eba2bf03b3a3b86689c0808558e9 | 67,364 |
def sum_fun(x, backend):
"""
Base function for summing all elements in a tensor
"""
func = "sum"
if backend == "tensorflow":
backend = "tensorflow.math"
func = "reduce_sum"
return get_func(func, backend)(x) | 6c5231f67ed3f464dd7bf3bbbe3b0ed6c6fb6740 | 67,365 |
import os
def upload():
"""Page for uploading of images"""
form = UploadForm()
if form.validate_on_submit() and 'upload' in request.files:
for f in request.files.getlist('upload'):
filename = secure_filename(f.filename)
f.save(os.path.join(app.config['UPLOAD_PATH'], filenam... | e8c45b9bc02d088007c1a7a5271bfc8ffa5ec9d6 | 67,366 |
def measure_naptan_groups(gdf, naptan_column_name="LocalityName"):
"""[summary] this function measures the number of groups present within
the given geodataframe, when groupbed the [default LocalityNames]
Args:
gdf ([type]): [description]
naptan_column_name ([type]): [description]
Ret... | 725ce929fb19f0e2fdf051f6daf9c1d86e125d0f | 67,367 |
def CreateParser():
"""Expose _CreateParser publicly."""
# Name _CreateParser is needed for commandline library.
return _CreateParser() | 888ec2237c0e4bda8c44f5fece4f184f1e870e2c | 67,368 |
def update_dataset(dataset_id: int,
request: schemas.DatasetUpdate,
db: Session = Depends(deps.get_db),
current: model.User = Depends(deps.get_current_user)):
"""
Update a dataset.
"""
dataset = crud.dataset.get(db=db, id=dataset_id)
if datase... | 5a72a30b0a27cd9df97c6131cd76785fc5050504 | 67,369 |
def calculate_ts_stability_index_batch(ts, **kwargs):
"""Returns series with stability index calculated for every point of ts, where possible"""
si_values = []
timestamps = []
for time, row in ts.iterrows():
ts_history = ts[:time].iloc[:-1]
try:
si_value = calculate_ts_stabil... | a9bfaa3e3d8393443c1113d5356616067795ca0b | 67,370 |
import click
import functools
def ip_lookup_command(function):
"""Decorator that groups decorators common to ip and quick subcommand."""
@click.command()
@click.argument("ip_address", callback=ip_addresses_parameter, nargs=-1)
@click.option("-k", "--api-key", help="Key to include in API requests")
... | 1da900e8fd96e486f58e10708c99e797a818905a | 67,371 |
from sklearn.model_selection import GridSearchCV, RandomizedSearchCV
def _is_parameter_search_estimator(estimator):
"""
:return: `True` if the specified scikit-learn estimator is a parameter search estimator,
such as `GridSearchCV`. `False` otherwise.
"""
parameter_search_estimators = [
... | 24a1c51cea98b36923d6ac827d1c4481d75bb460 | 67,372 |
from typing import Dict
from typing import List
import re
def clean_utterance(utterance: Dict[str, str],
remove_english: bool = False,
english_words: set = None,
punctuation: str = None,
special_cases: List[str] = None) -> (List[str], int... | 362b835ec894495d74c984b082bb173ca2e27e1a | 67,373 |
def get_all_functiondef(root):
"""
Get all FunctionDef nodes
:param root:
:return:
"""
if root['name']=='FunctionDef':
# block(FunctionDef) begin id
begin_id=root['id']
end_id=get_end_id(root)
return 'begin:%s,end:%s'%(begin_id,begin_id+end_id-1)
else:
... | b6687059c958d49795f0d2fb521bd8ca488c5507 | 67,374 |
def bookmark_json(userkey, urlhash):
""" Serialise bookmark to json """
try:
bookmark = Bookmark.get(
Bookmark.url_hash == urlhash,
Bookmark.userkey == userkey,
Bookmark.status == Bookmark.VISIBLE
)
return jsonify(bookmark.to_dict())
except Bookmar... | 30321366ee5a32484664599d9223ff56ee0768e9 | 67,375 |
from typing import Mapping
def betaReduce(lhs, lhsEnv, rhs, rhsEnv):
"""β-reduction: (λV.M)N → M[V := N]"""
exp = lhs.exp
if isinstance(exp, Mapping):
return (exp.exp, Env(Mapping(exp.var, clos(rhs, rhsEnv)), lhsEnv))
else:
return (exp, Env(clos(rhs, rhsEnv), lhsEnv)) | 1bd36a551280721596e502be0db2e5aa0a0b6d8b | 67,376 |
def _check_for_iocs(loop, context, indent):
"""
Check the variables modified in a loop to see if they were
set to interesting IOCs.
"""
indent_str = " " * indent
lhs_visitor = lhs_var_visitor()
loop.accept(lhs_visitor)
lhs_var_names = lhs_visitor.variables
ioc_str = indent_str + "# C... | f9d4a8fa2e1953314cb422882a2eb6d1e1f7b7eb | 67,377 |
import ssl
import concurrent
async def patch(
uri: str,
headers: t.Dict[str, str] = {},
body: t.Optional[bytes] = None,
json: t.Union[t.Dict[str, t.Any], JsonApiData] = None,
query: t.Dict[str, t.List[str]] = {},
timeout: t.Optional[float] = None,
blocksize: int = 8192,
datacls: t.Type... | 32101f2a036ee846fdd8a0c5ed7873f5726a3bfe | 67,378 |
def edit_orcid(request):
"""
Send a user to orcid.org for authorization to link to their ORCID account, then redirect them to
views/auth_orcid to save their iD and other token information. Also provide the option to unlink their
ORCID account from their account.
"""
if request.method == 'POST'... | 2305ac8e38430919a807bdd0612115992b416065 | 67,379 |
import math
def calculate_distance(psi, angle_in_degrees):
""" Calculate the distance the mudball flies. """
angle_in_radians = math.radians(angle_in_degrees)
distance = .5 * psi ** 2 * math.sin(angle_in_radians) * math.cos(angle_in_radians)
return distance | 47eb9acb71f5c11b26002ec38e37410db62c2e05 | 67,380 |
import json
def clear_dataflow_run(dataflow_run_id:str):
"""
Clear an orphaned dataflow run.
:param dataflow_run_id:
:return:
"""
payload = {"orchAction": "clear_dataflow_run",
"dataflow_run_id": dataflow_run_id}
json_payload = json.dumps(payload)
pickledJsonObj = __bo... | 453fee04e72c54b7f2891f5e7f5b89d913778f42 | 67,381 |
def custom_path_fs_io_manager(init_context):
"""Built-in IO manager that allows users to custom output file path per output definition.
It requires users to specify a base directory where all the step output will be stored in. It
serializes and deserializes output values (assets) using pickling and stores ... | 04aeaa321d0b998959401ca6190cc45385edae79 | 67,382 |
def sghmc_naive_nomh_noresample_multi(du_hat_func, epsilon, nt, m, M, V, theta_init, r_init, formula):
"""
This is a function to realize Naive Stochastic Gradient Hamiltonian Monte Carlo
without Metropolis-Hastings correction in multidimensional cases without resampling
procedure.
"""
B = 1/2*... | e704394e1f7f8960bea804e6f1a9188acc069ff5 | 67,383 |
import pathlib
import json
def load_json(filepath):
"""
Loads the metrics in a dictionary.
:param log_dir: The directory in which the log is saved
:param metrics_file_name: The name of the metrics file
:return: A dict with the metrics
"""
if isinstance(filepath, pathlib.Path):
fil... | 1dd8ff7822228bc0173a66df626902a723338d55 | 67,384 |
def super_scrub(data):
"""Run words through a comprehensive list of filtering functions.
Expects a dictionary with key "words"
"""
for technique in data['words']:
data['words'][technique] = normalization.uniquify(
normalization.remove_odd_sounding_words(
normalizatio... | d81557232ac99b89d24144c5d44bd94d41340d87 | 67,385 |
from typing import Callable
import random
def choose(option1: Callable = lambda: None, option2: Callable = lambda: None):
"""
Randomly run either option 1 or option 2
:param option1: a possible function to run
:param option2: another possible function to run
:return: the result of the function
... | 0f0ecbc945de9f6d5698cd86103265eccf5708e6 | 67,386 |
def compute_embeddings(encoder, data_batches):
"""Computes sequence embeddings according to a specified encoder."""
vectors = []
for batch in iter(data_batches):
X, Y = batch
X_embedded = encoder(X)
for vec in np.array(X_embedded):
vectors.append(vec)
vectors = np.ar... | 5c9d6e9bb617e43522044255948639c01d6b06a4 | 67,387 |
def while_array_parser(self, desc, node=None, parent=None, attr_index=None,
rawdata=None, root_offset=0, offset=0, **kwargs):
"""
"""
try:
orig_offset = offset
if node is None:
parent[attr_index] = node = desc.get(NODE_CLS, self.node_cls)\
... | 365d8d115f4b677177f1214c78d4957a78745252 | 67,388 |
def get_all() -> [User]:
"""
Helper function to return all users
:returns: all users.
"""
return User.objects.all() | 79864d2a862610bed414f2ad7cebbee20055e638 | 67,389 |
def get_category(id):
""" Get category. """
category = Category.query.get(id)
if category is not None:
response = {"category": category.to_dict()}
return make_response(jsonify(response), 200)
abort(404) | 15e1030b4c3b6e5d00f7697cd7e392a5bc5fcd8d | 67,390 |
def get_repo_service():
"""Factory method that returns configured RepoService instance.
If the service is not configured, returns None. Also acts as a mocking point
for unit tests.
"""
cas_service = cas.get_cas_service()
if not cas_service: # pragma: no cover
return None
return RepoService(
ca... | 75966851961208486c1d28e5051f30266dfe7d0d | 67,391 |
from typing import List
def search_etfs(to_search) -> List[str]:
"""Search for an etf string in list of ETFs
Parameters
----------
to_search: str
String to match
Returns
-------
matching_etfs: List[str]
List of matching ETF names
"""
all_symbols, all_names = get_a... | f56972605a45c5308a311eef1dac5ea34736aa2d | 67,392 |
def separable_hnn_siren(input_h_s=None, input_model=None):
"""
Separable Hamiltonian network using Siren network.
:return:
"""
if input_h_s:
h_s = input_h_s
model = input_model
else:
network = SirenNet(
dim_in=2,
dim_hidden=100,
dim_ou... | 08a1ef7d25304fcbd1d5ef568a420b70e0da0464 | 67,393 |
async def update_password(username: str = Form(...), old_password: str = Form(...), new_password: str = Form(...)):
"""パスワードの更新"""
res = search_username(cur=cur,username=username)
if res == None:
raise HTTPException(status_code = 400,detail="ユーザーが登録されていません。")
if not verify_password(old_pass... | bbec78a71eaf91fa92eeb1dd6d0f19fb7b767f63 | 67,394 |
import time
def num_to_str_data(str_date: int) -> str:
"""
num to str format
:param str_date: time of int format
:type str_date: int
:return: format time
:rtype: str
"""
str_date = str_date / 1000
str_date = time.localtime(str_date)
strp_time = time.strftime("%Y-%m-%d %H:%M:%S"... | e3fb56132a9d365d7bbc89e11e010d0d1ed19ea9 | 67,395 |
def transform_response_to_context_format(data: dict, keys: list) -> dict:
"""
Transform API response data to suitable XSOAR context data.
Remove 'x-ms' prefix and replace '-' to '_' for more readable and conventional variables.
Args:
data (dict): Data to exchange.
keys (list): Keys to fi... | 34f1a613654deb71581bcd33757b8741840ae44f | 67,396 |
def GetsoftwareVersions(node, layers='core') :
"""Get the schema:softwareVersion(s) we find on this node (or [] ), within any of the specified layers."""
return GetTargets(Unit.GetUnit("softwareVersion", True), node, layers=layers ) | 851678659540482c4b289410f1e9407c97990fbc | 67,397 |
from typing import List
import re
from typing import Iterator
def txt_channel_finder(bot: Red, chaninfo: str) -> List[discord.TextChannel]:
"""
custom text channel finder
"""
_id_regex = re.compile(r"([0-9]{15,21})$")
def _get_id_match(argument):
return _id_regex.match(argument)
matc... | f751af05bdcdf207a42fd08e77fc780e14478fef | 67,398 |
import torch
def calculate_gradcam_metrics(no_norm_gc_mask_numpy: torch.Tensor, segm: torch.Tensor):
"""
Measure gradcam metric
@param segm - true mask, shape B x 3 x H x W
@param no_norm_gc_mask_numpy - Grad-CAM output w/o normalization, shape B x 1 x H x W
@return sum of gradcam attention of ev... | 4d3ab9c9a694b88ef83efcc94271d21d0c1f8e17 | 67,399 |
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