content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_social_profile_provider_list(profile):
""" """
sp = None
sp = SocialProfileProvider.objects.filter(user=profile.user).order_by('provider', 'website',)
return sp | 9e157c97dfd0d7daa1a2d0ad80bd84add3dcc281 | 33,288 |
import socket
import struct
def ip2long(ip):
""" Convert an IP string to long """
packedIP = socket.inet_aton(ip)
return struct.unpack("!L", packedIP)[0] | fbcd7e6255590fa5f67c90bb077d2aa9858abf0a | 33,290 |
def item_link_copy(request, op):
""" Objekt zum Einblenden markieren """
if request.GET.has_key('id'):
item_container = get_item_container_by_id(request.GET['id'])
else:
item_container = get_my_item_container(request, op)
if item_container.parent_item_id != -1:
#request.session['dms_link_copy_id'] =... | 1696eaa219193f80d4f61a9b573d00c4a06f077b | 33,291 |
def get_aggregation_fn_cls(rng):
"""Sample aggregation function for feature"""
return rng.choice(AGGREGATION_OPERATORS) | 843fc97c7216148e2bdfb40009da5a56f77b7008 | 33,292 |
def resnet_mvgcnn(depth, pretrained=False, **kwargs):
"""Constructs a MVGCNN based on ResNet-18 model."""
model = ResNetMVGCNN(BasicBlock,
resnet_layers[depth],
**kwargs)
if pretrained:
pretrained_dict = model_zoo.load_url(
model_urls['re... | 433b028c8af6c99a17b4cb35fc217bffaeee1439 | 33,293 |
def _smooth_samples_by_weight(values, samples):
"""Add Gaussian noise to each bootstrap replicate.
The result is used to compute a "smoothed bootstrap," where the added noise
ensures that for small samples (e.g. number of bins in the segment) the
bootstrapped CI is close to the standard error of the me... | 470c2263f81212daf56450e43f64b56d32b654a0 | 33,294 |
def lpc_ref(signal, order):
"""Compute the Linear Prediction Coefficients.
Return the order + 1 LPC coefficients for the signal. c = lpc(x, k) will
find the k+1 coefficients of a k order linear filter:
xp[n] = -c[1] * x[n-2] - ... - c[k-1] * x[n-k-1]
Such as the sum of the squared-error e[i] = ... | bd148dd367fa179933b7f318e071e1017fd707ce | 33,295 |
def make_mpo_networks(
action_spec,
policy_layer_sizes = (300, 200),
critic_layer_sizes = (400, 300),
):
"""Creates networks used by the agent."""
num_dimensions = np.prod(action_spec.shape, dtype=int)
critic_layer_sizes = list(critic_layer_sizes) + [1]
policy_network = snt.Sequential([
netw... | c52cb76f96390ab633ca05f33e1e40b20d78ae93 | 33,296 |
from typing import Callable
from typing import Any
def numgrad_x(f: Callable[[Any], Any], x: Tensor, eps: float = 1e-6) -> Tensor:
"""get numgrad with the same shape of x
Args:
f (Callable[[Any], Any]): the original function
x (Tensor): the source x
eps (float, optional): default error. Default... | fd8b680e122de3adaa3a3246f8d7f786bffd24a2 | 33,297 |
def throw_darts_serial(n_darts):
"""Throw darts at a square. Execute serially! Count
how many end up in an inscribed circle. Approximate pi.
Parameters
----------
n_darts : int
Number of darts to throw
Returns
-------
pi_approx : float
Approximation of pi
... | 1aee3692af97eb2ac6d68ccfd573fa55e9e98a6c | 33,298 |
def sample_category(user, name='Movie', slug='film'):
"""Create and return a sample ingredient"""
return Category.objects.create(user=user, name=name, slug=slug) | c7291808b63244a74e97700819584d3630fd2f04 | 33,299 |
def get_all():
"""
gets all genres.
:rtype: list[GenreEntity]
"""
return get_component(GenresPackage.COMPONENT_NAME).get_all() | 091ecec08926542df9d923a180a359c2adaa7a1c | 33,300 |
def dist(node1, node2):
"""Calculate the distance between two vertices
"""
return np.sqrt(np.sum((node1 - node2)**2)) | 54458b1f32fc9af2bd426fa91711f802bdfb5d2c | 33,301 |
def propagate_errors(f, x, dx, jac=None, n_samples=1e4, seed=42):
"""Propagates the errors over all the elements of the array x
To see how the error propagation is performed see the documentation
of dy
Returns:
[array]: Array with the same size of x with the errors
"""
return np.sqrt([... | cc0f790293fbfdccafded53cf182ab296df183a8 | 33,303 |
def getFibonacciIterative(n: int) -> int:
"""
Calculate the fibonacci number at position n iteratively
"""
a = 0
b = 1
for _ in range(n):
a, b = b, a + b
return a | 19920a0dfc83f6dc17b5445294c206003ebe04f7 | 33,304 |
def louvain(graph, min_progress=1000, progress_tries=1):
"""Compute best partition on the `graph` by louvain.
Args:
graph (:class:`Graph`): A projected simple undirected graph.
min_progress: The minimum delta X required to be considered progress, where X is the number of nodes
... | a79fee324f3f7a79cb568166f91adfa5af095ab4 | 33,305 |
def compat(data):
"""
Check data type, transform to string if needed.
Args:
data: The data.
Returns:
The data as a string, trimmed.
"""
if not isinstance(data, str):
data = data.decode()
return data.rstrip() | 51d2d37b427e77b038d8f18bebd22efa4b4fdcce | 33,306 |
from typing import Tuple
def cascade(u: np.ndarray, balanced: bool = True, phase_style: str = PhaseStyle.TOP,
error_mean_std: Tuple[float, float] = (0., 0.), loss_mean_std: Tuple[float, float] = (0., 0.)):
"""Generate an architecture based on our recursive definitions programmed to implement unitary :... | 20fc298b8bd2c68ad46570c2815e674deb2d7020 | 33,307 |
def rsa_decrypt(cipher: int, d: int, n: int) -> int:
"""
decrypt ciphers with the rsa cryptosystem
:param cipher: the ciphertext
:param d: your private key
:param n: your public key (n)
:return: the plaintext
"""
return pow(cipher, d, n) | 33822a0a683eca2f86b0e2b9b319a42806ae56cc | 33,308 |
import json
def ajax_update_report_findings(request):
"""
Update the ``position`` and ``severity`` fields of all :model:`reporting.ReportFindingLink`
attached to an individual :model:`reporting.Report`.
"""
data = {"result": "error"}
if request.method == "POST" and request.is_ajax():
p... | 61c62d76e458bc7f752d6e9cecedd4cf5b941b91 | 33,309 |
def head_pos_to_trans_rot_t(quats):
"""Convert Maxfilter-formatted head position quaternions.
Parameters
----------
quats : ndarray, shape (N, 10)
MaxFilter-formatted position and quaternion parameters.
Returns
-------
translation : ndarray, shape (N, 3)
Translations at eac... | 9244452c59d132240a0b040effd35f68f80891df | 33,311 |
def geo_to_h3(lats, lngs, res):
"""
Convert arrays describing lat/lng paris to cells.
Parameters
----------
lats, lngs : arrays of floats
res: int
Resolution for output cells.
Returns
-------
array of H3Cells
"""
assert len(lats) == len(lngs)
out = np.zeros(le... | acc004b6ecbc861e17e7e6421040fb3d36ca1e24 | 33,312 |
def create_roads(roads):
""" Create roads information from roads reference data
Args:
roads: dataframe from roads reference data
Returns:
list of road curves for all roads
"""
road_curves = []
for _, row in roads.iterrows():
splitcoords = row["coordinates"].split(",")
... | 764c8f77edb3603824c0de2bd50d71147b2e8abe | 33,313 |
def set_extentions(doc):
"""No-param function. Sets 'frequency' and 'instance_list' variable for each token.
The frequency is calculated by lemma_.lower() word of the noun phrase.
And lemma_.lower() is used to add instance to instance list.
Returns: None
"""
freq_count = defaultdict(int)
i... | 485f2afe1947144da38bb5cf5cf1c788a1a3adb1 | 33,314 |
import time
def stream_occurrences(read_token, project_slug, last_id=None):
"""
read_token: Rollbar project_access_token with read_scope
project_slug: The name of the project that this token is for
last_id: The lowest occurence_id we are interested in
returns:
Occurrence list
... | 9ede2738c9485047b807bb0917ac5c18f4d7a0a5 | 33,315 |
def git_describe(repos):
"""Try running git describe on the given repos"""
return run(["git", "-C", str(repos), "describe", "--tags", "--abbrev=8"]) | 46faa032e08f09df3aeaa7c07478125fdac6b66f | 33,316 |
def convertToModelZ(z):
""" scale Z-axis coordinate to the model
"""
return z * SCALE_2_MODEL | b6a48f434bd9bebe57f724474bcc462647d55659 | 33,318 |
def opt_get_model_rest_api(model_id):
"""Retrieve model data
"""
model_id = Markup.escape(model_id)
return retrieve_model_data(model_id) | 2c69c4573736a455284df1098ef9b397588a7c35 | 33,319 |
import torch
def tokenize(texts, context_length=77, truncate=False) -> Tensor:
"""
Returns the tokenized representation of given input string(s)
Parameters
----------
texts : Union[str, List[str]]
An input string or a list of input strings to tokenize
context_length : int
The c... | d6fbe8b863e4a1153a84f39851482f7211153dd9 | 33,320 |
import yaml
def config_get_timesteps(filepath):
"""Get list of time steps from YAML configuration file.
Parameters
----------
filepath : pathlib.Path or str
Path of the YAML configuration file.
Returns
-------
list
List of time-step indices (as a list of integers).
"... | 8a51e1437edbf2d73884cb633dbf05e9cfe5a98d | 33,321 |
def join_expressions(positions, labels, sep="\t"):
"""Join mean expressions.
Join expressions from different time points and return only those that are
in all samples.
"""
dfs = []
for position, replicates in positions:
dfs.append(
get_mean_expression(
replic... | 48cc69bf02add561c3d5297b4d90f6e148117d18 | 33,322 |
def current_snapshot(id_or_symbol):
"""
获得当前市场快照数据。只能在日内交易阶段调用，获取当日调用时点的市场快照数据。
市场快照数据记录了每日从开盘到当前的数据信息，可以理解为一个动态的day bar数据。
在目前分钟回测中，快照数据为当日所有分钟线累积而成，一般情况下，最后一个分钟线获取到的快照数据应当与当日的日线行情保持一致。
需要注意，在实盘模拟中，该函数返回的是调用当时的市场快照情况，所以在同一个handle_bar中不同时点调用可能返回的数据不同。
如果当日截止到调用时候对应股票没有任何成交，那么snapshot中的close, hig... | 25c7493fdd380504854d4eb6be17af440966b639 | 33,323 |
def infection_rate_symptomatic_50x40():
"""
Real Name: b'infection rate symptomatic 50x40'
Original Eqn: b'Susceptible 40*Infected symptomatic 40x50*contact infectivity symptomatic 40x50*(self quarantine policy SWITCH self 40\\\\ * self quarantine policy 40+(1-self quarantine policy SWITCH self 40))/non con... | 0ae1831493e02e413b0bd67d78f4fd88163ecd7e | 33,324 |
def cut_limits(x_data: tuple, y_data: tuple, x_lims: tuple):
"""Selecting range of x/y data based on x_lims.
Args:
x_data (tuple): x axis data
y_data (tuple): y axis values
x_lims (tuple): limits to select range from x and y
Raises:
ValueError: If x_lims have wrong shape
... | 144f47231e80c7bc00e6d7ea9038c2040748ff3b | 33,327 |
import re
def str_to_number_with_uncert(representation):
"""
Given a string that represents a number with uncertainty, returns the
nominal value and the uncertainty.
See the documentation for ufloat_fromstr() for a list of accepted
formats.
When no numerical error is given, an uncertainty of... | fbdafed553697c3052765afc5127fdfcc75e03f6 | 33,328 |
import json
def saveRecipe():
"""
Processing POST method from local for saving the new generated recipe
:return:
"""
method = request.method
if(method == "POST" and checkPassword(request, app.admin_password)):
j = json.loads(request.json)
fields = ['name','url', 'ingredients','... | 922d4c1ec66e43bd0aa254ac561e5436cf9002ee | 33,329 |
from typing import Dict
from typing import Any
def list_queues_command(client: Client, args: Dict[str, Any]) -> CommandResults:
"""
List queues in Azure storage account.
Args:
client (Client): Azure Queue Storage API client.
args (dict): Command arguments from XSOAR.
Returns:
... | 7a54a290795d00d6c3594a78ace03fc3c3001961 | 33,330 |
def isUnsaturated(mol):
"""
Does the molecule have a bond that's not single?
Eg. a bond that is double or triple or benzene
"""
cython.declare(atom1=Atom,
atom2=Atom,
bonds=dict,
bond=Bond)
for atom1 in mol.atoms:
bonds = mol.getBo... | eaf58e2d958b02055e0eb969aec2fd983fcdd7cd | 33,331 |
import random
def run_with_fixed_seeds(count=128, master_seed=0x243F6A8885A308D3):
"""
decorator run test method w/ multiple fixed seeds.
"""
def builder(func):
@wraps(func)
def wrapper(*args, **kwds):
rng = random.Random(master_seed)
for _ in irange(count):
... | 1b2c75b8e57e5c090cf25307189e86ba99a13589 | 33,332 |
def merge_cv_results(cv_results):
"""
Means across CV
"""
dtypes = ["train", "dev", "test"]
props_l1 = ["mean_loss", "mean_accuracy", "mean_positive_f1", "UL-A", "Joint-A"]
props_l2 = ["accuracy", "positive_f1"]
merged_results = {}
for dtype in dtypes:
merged_results[dt... | 854b0672ec31103136ad3c7285311f865a098159 | 33,333 |
from typing import List
from typing import Tuple
def _broads_cores(sigs_in: List[Tuple[str]],
shapes: Tuple[Tuple[int, ...]],
msg: str
) -> Tuple[List[Tuple[int, ...]], List[Tuple[int, ...]]]:
"""Extract broadcast and core shapes of arrays
Parameters
... | 228cbe06e4bc1e092cf92034255bfd60f01664c1 | 33,334 |
def batch_iou(boxes, box):
"""Compute the Intersection-Over-Union of a batch of boxes with another
box.
Args:
box1: 2D array of [cx, cy, width, height].
box2: a single array of [cx, cy, width, height]
Returns:
ious: array of a float number in range [0, 1].
"""
lr = np.maximum(np.min... | e7064a2f04370b5b3ffa78a585ab9341cd2321be | 33,335 |
import random
def createRandomIntID(length):
"""
Creates a random number.\n
Useful for identifiers.
"""
global dict_of_ids
final_id = ''
for _ in range(length):
final_id += str(random.randint(0,10))
if int(final_id) in dict_of_ids:
final_id = createRandomIntID(length)
... | aebd025cf3275a5a07b303c1c296e86f1f17aac5 | 33,336 |
def get_all_colors():
"""
:return: Color Options
"""
return color | 2104c1195c6e70c20e595d25f369d99c6f00269f | 33,337 |
import getpass
def get_username():
"""Get Windows username
Get current logged in user's username
:return: Username
:Example:
>>> get_username()
'Automagica'
Keywords
windows, login, logged in, lockscreen, user, password, account, lock, locked, freeze, hibernate, sleep
Icon
... | 91e5713317d72577d236e45963c7037446dad572 | 33,338 |
import json
import logging
def _ParseStepLogIfAppropriate(data, log_name):
"""PConditionally parses the contents of data, based on the log type."""
if not data:
return None
if log_name.lower() == 'json.output[ninja_info]':
# Check if data is malformatted.
try:
json.loads(data)
except Valu... | 4f2ef1f451c271adf0285ae90f88cf10b6e8d9be | 33,339 |
def RSIZJ(df, N=3, LL=6, LH=6):
"""
相对强弱专家系统
:param df:
:param N:
:param LL:
:param LH:
:return:
"""
CLOSE = df['close']
LC = REF(CLOSE, 1)
WRSI = SMA(MAX(CLOSE - LC, 0), N, 1) / SMA(ABS(CLOSE - LC), N, 1) * 100
ENTERLONG = CROSS(WRSI, LL)
EXITLONG = CROSS(LH, WRSI)
... | 563f4866ecb76dd732c9da192dc8a00a1ea44126 | 33,340 |
def autocomplete_service_env(actions, objects):
"""
Returns current service_env for object. Used as a callback for
`default_value`.
Args:
actions: Transition action list
objects: Django models objects
Returns:
service_env id
"""
service_envs = [obj.service_env_id fo... | 04d75c96619cc60433d3df51c44f621c2a86df25 | 33,341 |
def SoftwareProvenanceConst_get_decorator_type_name():
"""SoftwareProvenanceConst_get_decorator_type_name() -> std::string"""
return _RMF.SoftwareProvenanceConst_get_decorator_type_name() | eda72a471a2baf9ecfc5937ec5f9a4151be1ef6d | 33,342 |
import torch
def collate_fn(batch, train=True):
""" list of tensors to a batch tensors """
premise_batch, _ = pad_batch([row['premise'] for row in batch])
hypothesis_batch, _ = pad_batch([row['hypothesis'] for row in batch])
label_batch = torch.stack([row['label'] for row in batch])
# PyTorch RNN... | 980beccc7eb84165a625ad1d58c28e00a095ac4f | 33,343 |
def weights_and_neighbours(graph):
"""Compute weight and neighbors matrices from graph
Parameters
----------
graph : scipy.sparse.csr_matrix
sparse distance matrix representing an undirected graph
Returns
-------
weights : array_like (N,M)
corresponding weights for N nodes
... | 78c563fa52652d25f3bc408b8eff6c418a897aa6 | 33,344 |
def aabb_with_result(a: Rectangle, b: Rectangle, result: Rectangle) -> bool:
"""
Does Axis Aligned Bounding Box collision detection between two rectangles a and b.
Also calculates the intersection rectangle.
:param a:
:param b:
:param result:
:return:
"""
# Horizontal
amin = a.x
... | 799348704e400ecc6b79ca15b76eee352062a7fe | 33,346 |
from typing import List
import pickle
def make_visualizations_from_config(config: Config,
extension: str = 'pdf') -> List[Figure]:
"""
Used to generate the embedding visualizations from a given Config object
:param config: the Config used
:param extension: the exten... | 687bfa06bd18112ebc01b032c9f3b6f377c7b401 | 33,347 |
import re
def get_intervals(bin_type, thresholds):
""" Returns a list of interval objects. If bin_type is *within*, then
intervals are formed by using each pair of consecutive thresholds. For
bin_type below* the interval [-np.inf, threshold] is used and for bin_type
above* the inveral [threshold, np.inf] ... | 847c99e295c3200a1c10895b373083a49698d1ef | 33,348 |
def shapely_formatter(_, vertices, codes=None):
"""`Shapely`_ style contour formatter.
Contours are returned as a list of :class:`shapely.geometry.LineString`,
:class:`shapely.geometry.LinearRing`, and :class:`shapely.geometry.Point`
geometry elements.
Filled contours return a list of :class:`shap... | d6e0951f2ed75c37ffcbd9d18ebaa65ca2e2368b | 33,350 |
def _patch_redirect(session):
# type: (requests.Session) -> None
"""Whether redirect policy should be applied based on status code.
HTTP spec says that on 301/302 not HEAD/GET, should NOT redirect.
But requests does, to follow browser more than spec
https://github.com/requests/requests/blob/f6e13cc... | fc3e79475c86c9aeee6c780dc25ddd83d373a27b | 33,351 |
def cal_rank_from_proc_loc(pnx: int, pi: int, pj: int):
"""Given (pj, pi), calculate the rank.
Arguments
---------
pnx : int
Number of MPI ranks in x directions.
pi, pj : int
The location indices of this rank in x and y direction in the 2D Cartesian topology.
Returns
------... | 97146de9f69dd2f62173c19dfdb98d8281036697 | 33,352 |
import numpy
def width_trailing(sdf):
"""Return the FWHM width in arcmin for the trailing tail"""
# Go out to RA=245 deg
trackRADec_trailing=\
bovy_coords.lb_to_radec(sdf._interpolatedObsTrackLB[:,0],
sdf._interpolatedObsTrackLB[:,1],
... | a9fd52c584252470422fb39f555a64fe37a208e7 | 33,354 |
from typing import Optional
def load_report_fn(report_path: gpath.GPath) -> Optional[ExperimentReport]:
"""Tries to load report from path, if it exists. Returns None otherwise."""
report = None
if not gfile.Exists(report_path):
print(f'File {report_path} does not exist.')
return report
try:
repor... | a859751c3065eb03029c7fa11885421cfe025b29 | 33,355 |
from io import StringIO
import csv
from datetime import datetime
def get_proposal_statistics_report(from_date, to_date, all_fields=False):
"""Gets the proposal statistics report from Cayuse"""
# List of fields we want to retrieve from Cayuse and include in the CSV
REPORT_FIELDS = (
'application_t... | 08148bd1dcc763d73477e13df56327c3bf639051 | 33,356 |
def emitter_for_format(construct_format):
""" Creates a factory method for the relevant construct format. """
def _factory():
return ConstructEmitter(construct_format)
return _factory | 4472d4790f7469cc556a0c958003ec65673d0653 | 33,357 |
def get_client(settings):
"""Return a client for the Elasticsearch index."""
host = settings["elasticsearch_url"]
kwargs = {}
# nb. No AWS credentials here because we assume that if using AWS-managed
# ES, the cluster lives inside a VPC.
return Elasticsearch([host], **kwargs) | 65260462e9154ee911b686ee66405fe7009f4add | 33,358 |
def merge_model_predict(
predict: TModelPredict, predict_append: TModelPredict
) -> TModelPredict:
"""Append model predictions to an existing set of model predictions.
TModelPredict is of the form:
{metric_name: [mean1, mean2, ...],
{metric_name: {metric_name: [var1, var2, ...]}})
This... | bddff5101bd85de3a02087a48aa89f9acc4ebf52 | 33,359 |
def voucher_objects(states=voucher_states()):
"""
Build ``Voucher`` instances.
"""
return builds(
Voucher,
number=vouchers(),
created=one_of(none(), datetimes()),
expected_tokens=integers(min_value=1),
state=states,
) | 4ffd0c9071fc375dd369f8c89e0312d0eeb4e346 | 33,360 |
from bs4 import BeautifulSoup
import requests
def fetch_events_sciencehistory(base_url='https://www.sciencehistory.org'):
"""
Fetch events from Science History Institute, https://www.sciencehistory.org/events
"""
events = []
page_soup = BeautifulSoup(requests.get(
urljoin(base_url, '/event... | 571586136255973baeb00598afddfb6f309e82b0 | 33,364 |
def _create_buffer(size):
"""Create a ctypes buffer of a given size."""
buftype = (CHAR * size)
return buftype() | 8aa09592ebea8d799c1cfa69edc35dd0b6f93ff9 | 33,366 |
from typing import Optional
from typing import List
from typing import Dict
def collect_files(config: Config,
files: Optional[List[str]] = None,
method: Optional[str] = None) -> DFs:
"""Read a filtered memory map from a set of files."""
filenames = files if files else confi... | 3870e4da457ba2a1780e262acdfd8aad81990115 | 33,367 |
def ModelInfoAddShader(builder, shader):
"""This method is deprecated. Please switch to AddShader."""
return AddShader(builder, shader) | 69e21b53cc3c01b977115fd46f09d77f1499f3ef | 33,368 |
def configuration(request):
"""Various things stored in settings.py"""
return {"version": VERSION,
"current_url": request.get_full_path(),
"project_long_name": settings.project_long_name,
"project_short_name": settings.project_short_name,
"project_description": se... | 02a0727c93c786305c1aa019fc79c624e7dd3f91 | 33,369 |
def percentile(event_collection, target_property, percentile, timeframe=None, timezone=None, interval=None,
filters=None, group_by=None, max_age=None):
""" Performs a percentile query
Finds the percentile of a target property for events that meet the given criteria.
:param event_collection:... | 36208dae6b19b28b00ba311b5d15bef856fb0992 | 33,370 |
def MolAsMolWithQueryAtoms(
mol: rdChem.Mol, strict: bool = False, includeIsotopes: bool = True
) -> rdChem.Mol:
"""If Mol contains Chem.Atoms, convert to Mol with Chem.QueryAtoms
If Mol already is composed of QueryAtoms, returns the same object
"""
if all(isinstance(atom, rdChem.QueryAtom) for ato... | 1a2d0e159294efa19686d2f442e8a8e223eb96d1 | 33,372 |
import pathlib
from typing import Tuple
from typing import List
def find_images(
directory: pathlib.Path,
specs: specsmod.Specs) -> Tuple[List[pathlib.Path], List[str]]:
"""
Find all the sample images beneath the directory.
:param directory: where to search
:param specs: specification... | 360743837c3da3142cb7060590102149adca24c4 | 33,373 |
def login():
"""
Log in user
---
tags:
- Auth
requestBody:
content:
application/x-www-form-urlencoded:
schema:
type: object
properties:
pin:
description: Redirects to next page if login successful
typ... | f89e9190c5e9a29e0629e16011c4332d16874996 | 33,374 |
def T_asy(x, beta):
"""Symmetry breaking transformation.
.. math::
T_{asy}^{\\beta} (x_i) =
\\begin{cases}x_i^{
1 + \\beta \\frac{i-1}{D-1}\sqrt{x_i}} & \\text{if } x_i > 0\\\\
x_i & \\text{otherwise}
\\end{cases}
Parameters
----------
... | 671925fdbfc7d3fbc76acb1da3e9ff591207d131 | 33,375 |
def commonChecks(L0: float, Rtot: np.ndarray, KxStar: float, Kav: np.ndarray, Ctheta: np.ndarray):
""" Check that the inputs are sane. """
Kav = jnp.array(Kav, dtype=float)
Rtot = jnp.array(Rtot, dtype=float)
Ctheta = jnp.array(Ctheta, dtype=float)
assert Rtot.ndim <= 1
assert Rtot.size == Kav.s... | 9007db3f77e2036d2db7af28d24ba40234e09168 | 33,376 |
def _threed_extract(step, var, walls=False):
"""Return suitable slices and coords for 3D fields."""
is_vector = not valid_field_var(var)
hwalls = is_vector or walls
i_x = conf.field.ix
i_y = conf.field.iy
i_z = conf.field.iz
if i_x is not None or i_y is not None:
i_z = None
if i_... | a71310b0e735fabbee13ce1d4b71e3a8dbd9c809 | 33,377 |
def calc_temps(session,start_date, end_date):
"""TMIN, TAVG, and TMAX for a list of dates.
Args:
start_date (string): A date string in the format %Y-%m-%d
end_date (string): A date string in the format %Y-%m-%d
Returns:
TMIN, TAVE, and TMAX
"""
return sessi... | e82dcfe895e39c37fceb490bb9fb7c832bc7a6c5 | 33,378 |
from typing import List
def get_react_score(reactions: List[dict]) -> float:
"""
Returns score of the post according to reactions weights.
:reactions: list of dictionaries containing post info
"""
react_score = 0
for react in reactions:
react_score += reactions_dict[react.get("name"... | 0ca3ce2abeed8f151e607dfec16591e5e3bae79a | 33,379 |
import ast
def _get_collections_abc_obj_id(node: ast.expr | None) -> str | None:
"""
If the node represents a subscripted object from collections.abc or typing,
return the name of the object.
Else, return None.
>>> _get_collections_abc_obj_id(_ast_node_for('AsyncIterator[str]'))
'AsyncIterato... | f5cb701df687b90a0f3a247526cf5349e7b94d3e | 33,380 |
def show_index():
"""
main site, generating sections
"""
title = "Homepage"
sql_query = 'SELECT categoryId, title FROM category'
output = myDB.execute_sql(sql_query)
sections = dict(output)
return render_template("index.html", title=title,sections = sections) | b64d532810fc96e985b0291654e62e7d4e0e4b89 | 33,381 |
def generate_packed_decoder(wrapped_decoder):
"""Generate an decoder for a packer type from a base type decoder"""
def length_wrapper(buf, pos):
"""Decode repeat values prefixed with the length"""
length, pos = varint.decode_varint(buf, pos)
end = pos+length
output = []
w... | c213dcb49f63055dcd7ecf7ff75187c997f2a5e7 | 33,383 |
def create_ik_handle(name, start_joint, end_joint, solver_type=None, curve=None, **kwargs):
"""
Creates a new IK handle
:param name: str
:param start_joint: str
:param end_joint: str
:param solver_type: str
:param curve: str
:param kwargs:
:return: str
"""
if solver_type is ... | b5f56cbea793201467146475ac266b95c4469982 | 33,384 |
import math
def FinalFitness4(intermediate_outputs):
"""
Function: FinalFitness3
========================
Compute global fitness of an individual. Intended when wanting to refine
the fitness score.
@param intermediate_outputs: the fitnesses of the tree over several s... | 0e7337424a15439fbe1951b66fdfe52bc47edbbf | 33,385 |
def create_with_deletion_protection(ledger_name):
"""
Create a new ledger with the specified name and with deletion protection enabled.
:type ledger_name: str
:param ledger_name: Name for the ledger to be created.
:rtype: dict
:return: Result from the request.
"""
logger.info("Let's cr... | 2832988d222ab835984b2aeeabc4e9fc726e53c5 | 33,386 |
def run(command):
"""Execute command as user:<command>"""
with hide('everything'), settings(warn_only=True):
result = api.run(command)
print("["+env.host+"] " + command)
if result != '':
print(result)
return result | 339b8d674da1962383314c66e3f8644f1427552e | 33,387 |
def dummy_request():
"""Fixture to return a single dummy request."""
return testing.DummyRequest() | 7a4382ec76c2047a0b8cc7be4a6408c4000b5493 | 33,388 |
def refill(pop):
"""Get rid of duplicates."""
for lst in pop:
lst[9] = sgn(lst[9])
lst[-1] = abs(lst[-1])
pop.sort()
newpop = [0] * Npop
i = 0
last = None
for lst in pop:
if lst != last:
newpop[i] = lst
i += 1
last = lst
for j in ... | 701fec91d9e59085bb0d9d1d26dfd0803f9dc42b | 33,389 |
def parse_code(body):
"""
Parse the code from the body
"""
# Regex to match code block reddit comment
regex = ur"^((?:(?:(?:[ ]{4}).*|)(?:[\r\n]+|$))+)"
matches = re.findall(regex, body, re.MULTILINE)
# remove all empty lines
matches = [match for match in matches if match != "\n"]
... | 3e978cfb55186946c1f6c577054349ff50914ec9 | 33,390 |
from polaris.integrations import registered_deposit_integration as rdi
from typing import Tuple
from typing import Optional
def get_or_create_transaction_destination_account(
transaction: Transaction,
) -> Tuple[Optional[Account], bool, bool]:
"""
Returns:
Tuple[Optional[Account]: The account(s) f... | 2bea36fbeed6a6cf1c6f95f46eb2f2220571cf81 | 33,392 |
from pathlib import Path
def test_loading(tmpdir):
"""
Load an object.
"""
class A(FSObject):
_config_file = 'a.json'
def __init__(self,**kwargs):
super().__init__(**kwargs)
@property
def state(self) -> dict:
return {}
@classmethod
... | add506c113f7fb518541a7151aa20a9d64c69097 | 33,393 |
from datetime import datetime
import random
def random_date(start=None, end=None):
"""Get a random date between two dates"""
if start is None and end is None:
end = datetime.datetime.now()
start = end - datetime.timedelta(days=365)
stime = date_to_timestamp(start)
etime = date_to_tim... | 67e4338808ccf6195fd786c50635371bdfcb49a4 | 33,394 |
def _chg_float(something):
"""
floatに変換できたらfloatに変換する
"""
try:
f = float(something)
return f
except ValueError:
pass
return something | d0119c255b0842b2de4e60293c8037ff6f75b181 | 33,395 |
def get_seeding_programs():
"""Returns the list of seeding program names"""
try:
seed_catalogs = read_plist(SEED_CATALOGS_PLIST)
return list(seed_catalogs.keys())
except (OSError, IOError, ExpatError, AttributeError, KeyError) as err:
log.warn(err)
return "" | aad36b6ea85fa2d8a723a958281e8711e8d12af0 | 33,396 |
import re
import requests
import time
def query_ols(iri):
""" Gets the name field of measurementTechnique, infectiousAgent, infectiousDisease, and species in our nde schema
ols api doc here: https://www.ebi.ac.uk/ols/docs/api
Returns the formatted dictionary {name: ####, url: ####} if an url was ... | 03f6a1d6088f74b9b8a13528d5e4709c236cfd5e | 33,397 |
def cylinder( **named ):
"""Create a cylinder, adding to current scene"""
return _newNode( geometry.VPCylinder, named ) | 5e012725d5787ffd802215f2ddbe549150a0429b | 33,398 |
def mrr_finesse(a, r):
"""
description: Calculate the finesse of the MRR, i.e., finesse=FSR/FWHM=pi*sqrt(ra)/(1-ra) (Bogaerts et al., Silicon microring resonators, Laser and Photonics Review 2011, Eq.(21))\\
a {float} Attention coefficient\\
r {float} Self-coupling coefficient\\
return finesse {floa... | 718bfe5a0a3d8a727a604bff7d21c1b6e3cb1715 | 33,399 |
import decimal
def is_numeric(value):
"""
Check whether *value* is a numeric value (i.e. capable of being represented as a floating point value without loss
of information).
:param value: The value to check. This value is a native Python type.
:return: Whether or not the value is numeric.
:rtype: bool
"""
if... | 4224e3a1af56e75256d5c6d7f7d990ea3ae9343a | 33,400 |
def _position_to_features(sam_reader, allele_counter, region, position,
exclude_contig):
"""Extracts the AlleleCount data from a given position."""
# We build the AlleleCount at the position.
reads = sam_reader.query(region)
for read in reads:
allele_counter.add(read)
counts = al... | 7b430c6488a7f21661505a8ac9212f2fe2289744 | 33,401 |
def p_name(username):
"""
根据用户名获取昵称
:param username: 用户名
:return:
"""
friend = itchat.search_friends(userName=username)
if not friend:
return ''
return friend.get('RemarkName') or friend.get('NickName') | 4a07df0a973f533bd740b6d8d11ca2eb981617d5 | 33,402 |
def user_profile(self):
"""Return this user's UserProfile, or None if one doesn't exist."""
try:
return self.userprofile
except UserProfile.DoesNotExist:
return None | 7ca38535ed779c591d7dc76b52861e6a9a126c8f | 33,403 |
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