content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def create_attribute(representation_uuid, attribute_name):
"""create a representation of an attribute of a representation"""
try:
uuid = get_bus().create_attribute(representation_uuid, attribute_name, public=True)
return JsonResponse({'type': 'uuid', 'uuid': uuid})
except Exception as except... | f1ddfbc634b459a7e3f179125fd323beb871957d | 3,640,200 |
from typing import Optional
import subprocess
import warnings
def get_current_git_hash(raise_on_error: bool = False) -> Optional[str]:
""" Return git hash of the latest commit
Parameters
----------
raise_on_error: bool, optional
If False (default), will return None, when it fails to obtain co... | 7a17dc7e0574b7f3da91f009714226f855723427 | 3,640,201 |
def check_shift(start_time, end_time, final_minute, starting_minute, record):
"""
Função que verifica o turno da chamada e calcula o valor da ligação
:param start_time:
:param end_time:
:param final_minute:
:param starting_minute:
:return value:
"""
nem_start_time = start_time + (st... | 666883348347e8408b087ac63acd8608ff589a1c | 3,640,202 |
import hashlib
def s3_avatar_represent(user_id, tablename="auth_user", gravatar=False, **attr):
"""
Represent a User as their profile picture or Gravatar
@param tablename: either "auth_user" or "pr_person" depending on which
table the 'user_id' refers to
@param a... | 2c537a57a5d20ed8b4329338883f209fa9678fc4 | 3,640,203 |
from typing import Dict
from typing import List
import pathlib
import json
def json_loader(path_to_json_file: str) -> Dict[str, List[str]]:
"""Reads a JSON file and converts its content in a dictionary.
Parameters
----------
path_to_json_file: str
The path to the JSON file.
Returns
-... | d3f26504078e72e1522981a4d8ca5b60c3b8cf23 | 3,640,204 |
def get_region_solution_attribute(data, region_id, attribute, func, intervention):
"""Extract region solution attribute"""
regions = data.get('NEMSPDCaseFile').get('NemSpdOutputs').get('RegionSolution')
for i in regions:
if (i['@RegionID'] == region_id) and (i['@Intervention'] == intervention):
... | 0dc26e54ae5f16f8b3158ec00a5dc0bc58776408 | 3,640,205 |
def conv1x1(in_planes: int, out_planes: int) -> nn.Conv2d:
"""1x1 convolution"""
return nn.Conv2d(in_planes, out_planes, kernel_size=1, bias=True) | 2c8fcb8e04084ce35a2ae595b457fdf68fd27723 | 3,640,206 |
def make_ratio_map(amap, bmap):
"""Get the ratio of two PISA 2 style maps (amap/bmap) and return as another
PISA 2 style map."""
validate_maps(amap, bmap)
with np.errstate(divide='ignore', invalid='ignore'):
result = {'ebins': amap['ebins'],
'czbins': amap['czbins'],
... | 9497ddadd6d983b3094107aceadbdc1e2f1fb0a7 | 3,640,207 |
from typing import Collection
from typing import Mapping
from typing import Sequence
import math
def _compose_duration(
components_tags: Collection[Tags]) -> Mapping[str, Sequence[str]]:
"""Returns summed duration tags."""
duration_seconds_values = [
component_tags.one_or_none(DURATION_SECONDS... | 99bebed06628627211a117c738d89790d11adc1b | 3,640,208 |
def feature_spatial(fslDir, tempDir, aromaDir, melIC):
""" This function extracts the spatial feature scores. For each IC it determines the fraction of the mixture modeled thresholded Z-maps respecitvely located within the CSF or at the brain edges, using predefined standardized masks.
Parameters
------------------... | fb515a61bd81533b3b79f9cd500ad5b77723b527 | 3,640,209 |
from datetime import datetime
def str_to_date(date_str, fmt=DATE_STR_FMT):
"""Convert string date to datetime object."""
return datetime.datetime.strptime(date_str, fmt).date() | 102f384b479b217259c9bbfe36c8b66909daee50 | 3,640,210 |
import time
import json
def create_elasticsearch_domain(name, account_id, boto_session, lambda_role, cidr):
"""
Create Elastic Search Domain
"""
boto_elasticsearch = boto_session.client('es')
total_time = 0
resource = "arn:aws:es:ap-southeast-2:{0}:domain/{1}/*".format(account_id, name)
... | 5e33bd1454a2b3d1ce3bc1cc181b44497ce6035a | 3,640,211 |
def get_user(email):
"""
param: username
returns User instance with user data, the MySQL error handle by the try-except senteces
"""
result = {}
connection = _connect_to_db()
try:
with connection.cursor() as cursor:
row_count = 0
e = 'none'
# Read... | f05a59dc95ade5157d09d26a7d899fd9b19d3526 | 3,640,212 |
def index(request):
"""
A example of Function-based view
method:
get
request:
None
response:
type: html
"""
return HttpResponse("Hello, world. You're at the polls index.") | 1fe400e5f08728eef5834268d219a3f109325114 | 3,640,213 |
import requests
def make_https_request(logger, url, jobs_manager, download=False, timeout_attempt=0):
"""
Utility function for making HTTPs requests.
"""
try:
req = requests_retry_session().get(url, timeout=120)
req.raise_for_status()
except requests.exceptions.ConnectionError as c... | 825d1d79dc44e571fed4437fb1fbebc60bfef669 | 3,640,214 |
def info():
"""
Displays on the website of the page. @TODO - Add index.html for the site of Ubik.
:return: response for each get request on '/'.
"""
return about_response() | 1460d166c2cde36e931803b24fd235c1e100aa0d | 3,640,215 |
def falshsort():
"""
Do from here: https://en.wikipedia.org/wiki/Flashsort
:return: None
"""
return None | 359dc737a6611ebd6a73dd7761a6ade97b44b7ab | 3,640,216 |
import random
def random_word(text, label, label_map, tokenizer, sel_prob):
"""
Masking some random tokens for Language Model task with probabilities as in the original BERT paper.
:param tokens: list of str, tokenized sentence.
:param tokenizer: Tokenizer, object used for tokenization (we need it's v... | 46e7ac7d9fd0d82bbfef97a9a88efd0599bbc3b3 | 3,640,217 |
def ITERATIVETEST_Error_Of_Input_Parameter_inZSubsample():
"""Tests occurrence of an error because of an invalid input value provided at field "inZSubsample"."""
Logging.infoHTML( "<b>ToDo: Add more \"TestData\" objects to maximize variations!</b>" )
testDataVariations = {
"Invalid_Variation_1" : __getInvalid... | 8de38b2ceaf1312442f170a75f96cec7ec9fdd7b | 3,640,218 |
import numpy
def _match_storm_objects(first_prediction_dict, second_prediction_dict,
top_match_dir_name):
"""Matches storm objects between first and second prediction files.
F = number of storm objects in first prediction file
:param first_prediction_dict: Dictionary returned by... | 9c3bc60e99dc3d07cbd661b7187833e26f18d6f7 | 3,640,219 |
from typing import Optional
from typing import cast
def get_default_branch(base_url: str, auth: Optional[AuthBase], ssl_verify: bool = True) -> dict:
"""Fetch a reference.
:param base_url: base Nessie url
:param auth: Authentication settings
:param ssl_verify: ignore ssl errors if False
:return: ... | e2ac587705c82c95edeb415b79ca15746e9e9b78 | 3,640,220 |
import csv
def make_source_thesaurus(source_thesaurus=SOURCE_THESAURUS_FILE):
"""
Get dict mapping country name to `SourceObject` for the country.
Parameters
----------
source_thesaurus : str
Filepath for the source thesaurus data.
Returns
-------
Dict of {"Country": SourceObject} pairs.
"""
with open(s... | 43109eb3c9f9dedccae5bf692abebb0d66d09f7f | 3,640,221 |
import re
def extract_filter(s):
"""Extracts a filter from str `s`
Parameters
----------
s : str
* A str that may or may not have a filter identified by ', that HUMAN VALUE'
Returns
-------
s : str
* str `s` without the parsed_filter included
parsed_filter : dict
... | 2a8dad70429fdc6295a44794f0c2ac6f19150f31 | 3,640,222 |
from typing import Tuple
from typing import Union
def sigmoid(
x,
sigmoid_type: str = "tanh",
normalization_range: Tuple[Union[float, int], Union[float, int]] = (0, 1)
):
"""
A sigmoid function. From Wikipedia (https://en.wikipedia.org/wiki/Sigmoid_function):
A sigmoid function... | b9d660d20f7e398a2e57ad0b907ab52c4a88cc36 | 3,640,223 |
def interp(x, x1, y1, x2, y2):
"""Find a point along a line"""
return ((x2 - x) * y1 + (x - x1) * y2) / (x2 - x1) | 3af4575c017a32619a5bb2866a7faea5ff5c760d | 3,640,224 |
def msm_distance_measure_getter(X):
"""
generate the msm distance measure
:param X: dataset to derive parameter ranges from
:return: distance measure and parameter range dictionary
"""
n_dimensions = 1 # todo use other dimensions
return {
"distance_measure": [cython_wrapper(msm_dist... | 1185658474f3a2b9bc17be67c665bdd0a211dce7 | 3,640,225 |
def gen_cpmfgp_test_data_from_config_file(config_file_name, raw_func,
num_tr_data, num_te_data):
""" Generates datasets for CP Multi-fidelity GP fitting. """
# Generate data
def _generate_data(_proc_func, _config, _num_data):
""" Generates data. """
ZX_proc = sample_from_config_space(_config, _num_data)... | c6efaf34601f5b02153fca3ea0926115d1adb918 | 3,640,226 |
def csv_to_postgres(engine,
file: str,
table_name: str):
"""
Given a *.csv filepath, create a populated table in a database
:param engine: SQLAlchemy connection/engine for the target database
:param file: Full filepath of the *.csv file
:param table_name: ... | e8a913a32a3b0f7d9d617fa000f0b232e9824736 | 3,640,227 |
def _custom_padd(a, min_power_of_2=1024, min_zero_padd=50,
zero_padd_ratio=0.5):
""" Private helper to make a zeros-mirror-zeros padd to the next power of
two of a.
Parameters
----------
arrays : np.ndarray,
array to padd.
min_power_of_2 : int (default=512),
mi... | eb7f9d675113b8f53558d911462209c2f72c3ce3 | 3,640,228 |
def encode_multipart_formdata(fields, files):
"""
Encode multipart data to be used in data import
adapted from: http://code.activestate.com/recipes/146306/
:param fields: sequence of (name, value) elements for regular form fields.
:param files: sequence of (name, filename, value) elements for data ... | 17cd1ce08d7aac005a07b77517c4644565083cb8 | 3,640,229 |
def is_recording():
""" return current state of recording key macro """
global recording
return recording | 73f3a28d5d37bdc300768d48a6cc8f2ac81c2cf0 | 3,640,230 |
from typing import Union
from pathlib import Path
from typing import List
from typing import Dict
from typing import Optional
import asyncio
def download_image_urls(
urls_filename: Union[Path, str],
synsets: List[str],
max_concurrent: int = 50,
rewrite: bool = False
) -> Dict[str, Optional[List[str]]]... | 36bc1e2993cfd01ef9fca91354f970ffb980a919 | 3,640,231 |
def generate_new_split(lines1, lines2, rng, cutoff=14937):
"""Takes lines1 and lines2 and combines, shuffles and split again. Useful for working with random splits of data"""
lines = [l for l in lines1] # lines1 may not be a list but rather iterable
lines.extend(lines2)
perm = rng.permutation(len(lines... | cac058f44bd5cb729517a1aeb67295a30dac2eb5 | 3,640,232 |
import time
def train_classification(base_iter,
model,
dataloader,
epoch,
criterion,
optimizer,
cfg,
writer=None):
"""Task of training vide... | 8564fe2d520d54c81165adb5025aebb9916ab9b5 | 3,640,233 |
import logging
def get_top5(prediction):
"""return top5 index and value of input array"""
length = np.prod(prediction.size)
pre = np.reshape(prediction, [length])
ind = np.argsort(pre)
ind = ind[length - 5 :]
value = pre[ind]
ind = ind[::-1]
value = value[::-1]
res_str = ""
l... | 607ad0b9eee550e1bb389a9a92a76472155bea16 | 3,640,234 |
def calculate_parentheses(cases):
"""Calculate all cases in parameter 'cases'
return : case that calculate and it's 24 else return 'No Solutions'
Example and Doctest :
>>> nums = [5, 5, 9, 5]
>>> cases = generate_all_combinations(nums, '+-*/')
>>> calculate_parentheses(cases)
'( ( 5 + 5 ) +... | b8d51d677e16ed27c0b46ad0f4fe98751ea9759e | 3,640,235 |
import hashlib
import hmac
import struct
def pbkdf2(hash_algorithm, password, salt, iterations, key_length):
"""
PBKDF2 from PKCS#5
:param hash_algorithm:
The string name of the hash algorithm to use: "sha1", "sha224", "sha256", "sha384", "sha512"
:param password:
... | 8a3799a2c73b3b3be96f67252f210bc5d114d334 | 3,640,236 |
import time
def getLocalUtcTimeStamp():
"""
Get the universal timestamp for this machine.
"""
t = time.mktime(time.gmtime())
isDst = time.localtime().tm_isdst
return t - isDst * 60 * 60 | 54eed0893d03f3b6a76de0d36fc3f1ff5b35f64f | 3,640,237 |
def melt_then_pivot_query(df, inspect_result, semiology_term):
"""
if happy all are the same semiology, after insepction of QUERY_SEMIOLOGY, melt then pivot_table:
---
inspect_result is a df
Ali Alim-Marvasti July 2019
"""
# find all localisation columns present:
localisation_l... | 97ebd8f30d4b031a6b12412421ad0e4e2458c003 | 3,640,238 |
from typing import List
from typing import Tuple
def maze_solver(maze: List[List[int]]) -> List[Tuple[int, int]]:
"""
Finds the path that a light ray would take through a maze.
:param maze: 2D grid of cells, where 0 = empty cell, -1 = mirror at -45 degrees, 1 = mirror at 45 degrees
:return: The coordinates that t... | 4ea26e1dec318c9a41babf617d26662d35fe54c1 | 3,640,239 |
def looks_like_fasta(test_text):
"""Determine if text looks like FASTA formatted data.
Looks to find at least two lines. The first line MUST
start with '>' and the second line must NOT start with '>'.
Ignores any starting whitespace.
"""
text = test_text.strip()
return FASTA_START.match(... | 352cde2d0d4de692e0598a96d19107ac04a66f53 | 3,640,240 |
import signal
def firwin_kaiser_bsf(f_stop1, f_pass1, f_pass2, f_stop2, d_stop,
fs=1.0, N_bump=0, status=True):
"""
Design an FIR bandstop filter using the sinc() kernel and
a Kaiser window. The filter order is determined based on
f_stop1 Hz, f_pass1 Hz, f_pass2 Hz, f_stop2 Hz, ... | d5fccbcb9721707f0653065ad7c27d904cc05b97 | 3,640,241 |
from typing import List
def extract_text(html_text) -> List[List[str]]:
"""
:param html_text:
:return:
"""
lines = [i.text.replace("\xa0", "") for i in html_text.find("div", attrs={"class": "contentus"}).findAll("h3")]
return [line.split(" ") for line in lines if line] | 19dfdd513e48f2662dc51661bfeca4b1155762a3 | 3,640,242 |
from typing import Iterable
from typing import Tuple
from re import X
from typing import Mapping
from typing import List
def multidict(pairs: Iterable[Tuple[X, Y]]) -> Mapping[X, List[Y]]:
"""Accumulate a multidict from a list of pairs."""
rv = defaultdict(list)
for key, value in pairs:
rv[key].ap... | c94567169a8ea4e3d7fd9a8e5c2a990625181be8 | 3,640,243 |
import glob
def read_images(pathname):
"""
Read the images to a list given a path like 'images/cropped/*'
:param pathname: file path
:return: a list of color images and a list of corresponding file names
"""
images_path = sorted(glob.glob(pathname))
images = []
names = []
for path ... | 9fd4644baa2ca5db204cd7ce442e85bc0d9e3166 | 3,640,244 |
import subprocess
def cov(path):
"""
Run a test coverage report.
:param path: Test coverage path
:return: Subprocess call result
"""
cmd = "py.test --cov-report term-missing --cov {0}".format(path)
return subprocess.call(cmd, shell=True) | 521b78f712510b6438ad5bad45c951ddb0e1b623 | 3,640,245 |
def visualize_camera_movement(image1, image1_points, image2, image2_points, is_show_img_after_move=False):
"""
Plot the camera movement between two consecutive image frames
:param image1: First image at time stamp t
:param image1_points: Feature vector for the first image
:param image2: First image... | 5f92bf44885e62ebdc502e8c98ba1466cb8d5279 | 3,640,246 |
def get_rgb_masks(data, separate_green=False):
"""Get the RGGB Bayer pattern for the given data.
See `get_rgb_data` for description of data.
Args:
data (`numpy.array`): An array of data representing an image.
separate_green (bool, optional): If the two green channels should be separated,
... | cf31103ca4248ccd96fb89181d0e48d5b71201c5 | 3,640,247 |
def _parse_ax(*args, **kwargs):
""" Parse plotting *args, **kwargs for an AxesSubplot. This allows for
axes and colormap to be passed as keyword or position.
Returns AxesSubplot, colormap, kwargs with *args removed"""
axes = kwargs.pop('axes', None)
cmap = kwargs.get('cmap', None)
if ... | 78658e2cf66fad184c057b9392b918ffb48406be | 3,640,248 |
import google.colab # noqa: F401
import IPython
import IPython
def _get_context():
"""Determine the most specific context that we're in.
Implementation from TensorBoard: https://git.io/JvObD.
Returns:
_CONTEXT_COLAB: If in Colab with an IPython notebook context.
_CONTEXT_IPYTHON: If not in Colab... | b81205aedbe2222019fa6b7e9dc5fb638536869f | 3,640,249 |
def loadSHSMFCCs(IDs):
"""
Load all of the 12-dim MFCC features
"""
IDDict = getSHSIDDict()
fin = open("SHSDataset/MFCC/bt_aligned_mfccs_shs.txt")
mfccs = {}
count = 0
while True:
ID = fin.readline().rstrip()
if not ID:
break
ID = IDDict[ID]
if... | 04d82be79d6e89c5f9b6304be82d049bf6af63f5 | 3,640,250 |
def __createTransactionElement(doc,tran):
"""
Return a DOM element represents the transaction given (tran)
"""
tranEle = doc.createElement("transaction")
symbolEle = __createSimpleNodeWithText(doc, "symbol", tran.symbol)
buyEle = __createSimpleNodeWithText(doc, "buy", "true" if tran.buy else "fa... | c09fc6abf4cb9599be23bcf6c91c6cc60330df0a | 3,640,251 |
def received_information(update: Update, context: CallbackContext) -> int:
"""Store info provided by user and ask for the next category."""
text = update.message.text
category = context.user_data['choice']
context.user_data[category] = text.lower()
del context.user_data['choice']
update.message... | e7b93516975a497f6da11383969a14aeb31e6278 | 3,640,252 |
def set_payout_amount():
"""
define amount of insurance payout
NB must match what was defined in contract constructor at deployment
"""
return 500000e18 | 30ff7b07cbbe28b3150be2f1f470236875c8d0e3 | 3,640,253 |
def process_season_data(*args) -> pd.DataFrame:
"""
Takes multiple season data frames, cleans each and combines into single dataframe.
"""
return pd.concat(
map(
lambda df: basketball_reference.process_df_season_summary(
df=df, url_type="season_summary_per_game"
... | 9c2d46ba2b491382e91613e0dc0a35b68e4188cf | 3,640,254 |
def build_frame(station_num: int, snapshots_num: int):
"""Function to build citi_bike Frame.
Args:
station_num (int): Number of stations.
snapshot_num (int): Number of in-memory snapshots.
Returns:
CitibikeFrame: Frame instance for citi-bike scenario.
"""
matrices_cls = gen... | 2fd09885f488a4b42f9a2a4a19dfdd5c10743ef9 | 3,640,255 |
def rucklidge(XYZ, t, k=2, a=6.7):
"""
The Rucklidge Attractor.
x0 = (0.1,0,0)
"""
x, y, z = XYZ
x_dt = -k * x + y * (a - z)
y_dt = x
z_dt = -z + y**2
return x_dt, y_dt, z_dt | 9d10aa89fb684a95474d45399ae09a38b507913c | 3,640,256 |
import os
def resolve(dirs, *paths):
"""
Joins `paths` onto each dir in `dirs` using `os.path.join` until one of the join results is found to exist and
returns the existent result.
:param dirs: A list of dir strings to resolve against
:param paths: Path components to join onto each dir in `dirs`
... | d9f8b8e4049091ab0354b56e283f322ddd3d37e0 | 3,640,257 |
def multiext(prefix, *extensions):
"""Expand a given prefix with multiple extensions (e.g. .txt, .csv, _peaks.bed, ...)."""
if any((r"/" in ext or r"\\" in ext) for ext in extensions):
raise WorkflowError(
r"Extensions for multiext may not contain path delimiters " r"(/,\)."
)
re... | 39bda078a856cb14fc65174ff48be81909b9034a | 3,640,258 |
def sum_range(n, total=0):
"""Sum the integers from 1 to n.
Obviously the same as n(n+1)/2, but this is a test, not a demo.
>>> sum_range(1)
1
>>> sum_range(100)
5050
>>> sum_range(100000)
5000050000L
"""
if not n:
return total
else:
raise TailCall(sum_range... | 6126dd1012346a388ddc37c5a8965f3662b8ad7d | 3,640,259 |
import logging
import time
import pickle
def parallel_evaluation_mp(candidates, args):
"""
Evaluate the candidates in parallel using ``multiprocessing``.
This function allows parallel evaluation of candidate solutions.
It uses the standard multiprocessing library to accomplish the
parallelization... | 4562a976306ec8c3684d079b307a4fb1a83d09ab | 3,640,260 |
from tcrsampler.sampler import TCRsampler
def _default_tcrsampler_human_beta(default_background = None, default_background_if_missing=None):
"""
Responsible for providing the default human beta sampler 'britanova_human_beta_t_cb.tsv.sampler.tsv'
Returns
-------
t : tcrsampler.sampler.TCRsampler
... | 15b682b3e14e9496514efaf287b10ae6acb12441 | 3,640,261 |
def _dblock_to_raw(
mkh5_f, dblock_path, garv_annotations=None, apparatus_yaml=None,
):
"""convert one mkh5 datablock+header into one mne.RawArray
Ingest one mkh5 format data block and return an mne.RawArray
populated with enough data and channel information to use mne.viz
and the mne.Epochs, mne.E... | cee5823fa1ab4e3cd9be345cf83858bd61a01b51 | 3,640,262 |
def _get_positive_mask(positive_selection, cls_softmax, cls_gt):
"""Gets the positive mask based on the ground truth box classifications
Args:
positive_selection: positive selection method
(e.g. 'corr_cls', 'not_bkg')
cls_softmax: prediction classification softmax scores
cls... | 8a8e4317f99f691c038b40d7656656f532eba884 | 3,640,263 |
def max_min_index(name_index):
"""Return maximum and minimum value with country of a column from df."""
country_and_name = df_copy[["country", name_index]]
counrties_in_name_index = country_and_name.sort_values(name_index).dropna()
min_value = [
list(counrties_in_name_index[name_index])[0],
... | 7bce42a4d05b52b8e6f0a6d91cecf7775a9484a4 | 3,640,264 |
def add_bold_line(latex: str, index: int) -> str:
"""Makes a provided line number bold
"""
lines = latex.splitlines()
cells = lines[index].split("&")
lines[index] = r'\bfseries ' + r'& \bfseries '.join(cells)
return '\n'.join(lines) | 637338ea9ec576c780ccfa0b37d47a670465cdbb | 3,640,265 |
def square(V,resp,weight):
"""Computes the expansion coefficients with a least squares regression"""
if np.any(weight):
Vt = V.T
v1 = Vt.dot(np.transpose(weight*Vt))
v2 = Vt.dot(np.transpose(weight*resp.T))
coef = np.linalg.solve(v1,v2)
else: coef = np.linalg.lstsq(V,r... | 076f580a16c233a087edafb1efd57b9fa194a666 | 3,640,266 |
def _unwrap_function(func):
"""Unwrap decorated functions to allow fetching types from them."""
while hasattr(func, "__wrapped__"):
func = func.__wrapped__
return func | 8c7a9f5b08dc91b9ae2c8387fbd4860bb554d561 | 3,640,267 |
def get_data(exception: bool = True, key_form: str = "data") -> "dict or None":
"""Função captura os dados de uma rota.
A captura é feita caso a rota seja com `JSON` ou `Multipart-form` caso contrario lança um exceção.
As imagens são capturadas na função `get_files`.
`exception` campo boleano opcional ... | 15cd4257e7849d4400231d7e5c2a025b16ad7db5 | 3,640,268 |
def get_dec_log(uid):
"""Convenience method to look up inc_log for a uid."""
rv = query_db('select dec_log from user where uid = ?',
[uid], one=True)
return rv[0] if rv else None | 8927ce657cbabfd1e0f4e852e6163702ab5b3841 | 3,640,269 |
def removeItem(request):
"""
Removes item from logged in customers basket.
"""
if request.method == 'POST':
cust = User.objects.get(username=request.user.username)
item_id = request.POST["item_id"]
item = Item.objects.get(id=item_id)
b_item = Basket.objects.get(customer=cust, item=item)
if(b_item):
b_i... | 80514a322f727478311b7a1b49bd9da8ac7b0d28 | 3,640,270 |
def read_file(repo, name):
"""Read JSON files."""
with open(repo + '/' + name + '.txt') as file:
data = [d.rstrip() for d in file.readlines()]
file.close()
return data | 4d91e4c68a4f132dc6ebb41cc51df66bd555107a | 3,640,271 |
def add_end_slash(value: str):
""" Added a slash at the end of value """
if type(value) != str:
return value
return value if value.endswith("/") else value + "/" | bc8f41898c50120ad7ca8b814ff03d19c1c64c27 | 3,640,272 |
def shift_fill(a, n, axis=0, fill=0.0, reverse=False):
""" shift n spaces backward along axis, filling rest in with 0's. if n is negative, shifts forward. """
shifted = np.roll(a, n, axis=axis)
shifted[:n] = fill
return shifted | 5287eefe7491442e3192069bce4faf975e54344a | 3,640,273 |
from typing import Union
def str2bool(v:Union[str, bool]) -> bool:
""" finished, checked,
converts a "boolean" value possibly in the format of str to bool
Parameters
----------
v: str or bool,
the "boolean" value
Returns
-------
b: bool,
`v` in the format of bool
... | 2f102239ce395ece25022320443ffc6d7183968e | 3,640,274 |
def _none_or_int_or_list(val):
"""Input conversion - expecting None, int, or a list of ints"""
if val is None:
return None
elif isinstance(val, list):
return list(map(int, val))
else:
return int(val) | 1958c64175a1cd63f8a42044b40b84d7cf8baed2 | 3,640,275 |
def hour_of_day(datetime_col):
"""Returns the hour from a datetime column."""
return datetime_col.dt.hour | 18b2f6e16ccbcb488f3863968466fda14f669d8b | 3,640,276 |
def pad_lists(lists, pad_token, seq_lens_idx=[]):
"""
Pads unordered lists of different lengths to all have the same length (max length) and orders
length descendingly
Arguments:
lists : list of 1d lists with different lengths (list[list[int]])
pad_token : padding value (int)
seq... | 76a2a9934dfca478e7db43a93db7e56c181a3b3f | 3,640,277 |
def sum_naturals(n):
"""Sum the first N natural numbers
>>> sum_naturals(5)
15
"""
total = 0
k = 1
while k <= n:
total += k
k += 1
return total | 4c59057cd82083d615c72a59f682dd218a657ea0 | 3,640,278 |
def _gaussian_log_sf(x, mu, sigma):
"""Log SF of a normal distribution."""
if not isinstance(x, chainer.Variable):
x = chainer.Variable(x)
return _log_ndtr(-(x - mu) / sigma) | 3f33918bf78fc3ab4064f05d038232df218416f6 | 3,640,279 |
def sort_list_files(list_patches, list_masks):
"""
Sorts a list of patches and masks depending on their id.
:param list_patches: List of name of patches in the folder, that we want to sort.
:param list_masks: List of name of masks in the folder, that we want to sort.
:return: List of sorted lists, r... | 91557475bf145862ea88ad9f86cef82135eddd6c | 3,640,280 |
def get_model(name):
""" get_model """
if name not in __factory:
raise KeyError("unknown model:", name)
return __factory[name] | 00fff4e3596aec487b16fd1114b7d026d6790568 | 3,640,281 |
import configparser
def defaults_to_cfg():
""" Creates a blank template cfg with all accepted fields and reasonable default values
Returns:
config (ConfigParser): configuration object containing defaults
"""
config = configparser.ConfigParser(allow_no_value=True)
config.add_section("General... | f521d0caee3c9f062eb78e7d5c2562030a741aaf | 3,640,282 |
def check_sentence_for_coins(sentence: str) -> str:
"""Returns the corresponding binance pair if a string contains any words refering to a followed coins
Args:
sentence (str): the sentence
Returns:
str: the binance pair if it contains a coins, otherwise returns 'NO_PAIR'
"""
coin = n... | a9d041ff6c2bcca1c424b059956c33016f93300d | 3,640,283 |
def to24Bit(color8Bit):
"""The method allows you to convert the 8-bit index created by the color.to8Bit method to 24-bit color value."""
# We ignore first one, so we need to shift palette indexing by one
return palette[color8Bit + 1] | b84d2262883a7b3415ae46f174418dc79ef800dc | 3,640,284 |
import shlex
import sys
import json
def read_json_method(data):
"""
Reformatting Valve key/value format
to JSON and returning JSON.
"""
# default vars
parent = []
depth = 0
vdict = {}
# init json and add opening bracket
vjson = "{"
# replace tabs with spaces
data.rep... | f8b266145f44e99c83fd5e0dbe2ccd8e60e4feb2 | 3,640,285 |
def make_bag():
"""Create a bag."""
return from_sequence(
[1, 2], npartitions=2
).map(allocate_50mb).sum().apply(no_allocate) | 8c939dd389ab09811dbbf77aaf479832ab7463d0 | 3,640,286 |
def get_testdata_files(pattern="*"):
""" Return test data files from dicom3d data root directory """
data_path = join(DATA_ROOT, 'test_files')
files = walk_data(
base=data_path, pattern=pattern,
search_files=True, search_dirs=False)
return [filename for filename in files if not filename.endswith('.py')] | 9739db355914b288b2fcb29874fcc50d6a2b4487 | 3,640,287 |
def safe_text(obj):
"""Safely turns an object into a textual representation.
Calls str(), then on Python 2 decodes the result.
"""
result = qcore.safe_str(obj)
if isinstance(result, bytes):
try:
result = result.decode("utf-8")
except Exception as e:
result =... | 4d20d5c42b79b6dbb6f8282d74bfd461ffd1dc75 | 3,640,288 |
from typing import List
def evaluate_blueprints(blueprint_q: mp.Queue,
input_size: List[int]) -> List[BlueprintGenome]:
"""
Consumes blueprints off the blueprints queue, evaluates them and adds them back to the queue if all of their
evaluations have not been completed for the curre... | c87d0a37fe32d2af6594564afc44d16adf616737 | 3,640,289 |
import tempfile
import shlex
def run_noble_coder(text, noble_coder):
"""
Run Noble Coder
Args:
text: the text to feed into Noble Coder
noble_coder: the execution path of Noble Coder
Returns:
The perturbation agent
"""
pert_agent = None
with tempfile.TemporaryDirect... | 20bcee89ddda7c8abc108a42621867017a7e4d63 | 3,640,290 |
def xor(*args):
"""True if exactly one of the arguments of the iterable is True.
>>> xor(0,1,0,)
True
>>> xor(1,2,3,)
False
>>> xor(False, False, False)
False
>>> xor("kalimera", "kalinuxta")
False
>>> xor("", "a", "")
True
>>> xor("", "", "")
False
"""
retur... | 86bbe0350dd18a2508120cec9672661e1aa56ce0 | 3,640,291 |
from utils import check_dir
import coeff
from version import __version__
def proc(log_file, thread, circ_file, hisat_bam, rnaser_file, reads, outdir, prefix, anchor, lib_type):
"""
Build pseudo circular reference index and perform reads re-alignment
Extract BSJ and FSJ reads from alignment results
Re... | f0cbe9a93cf81a0177895602bc706c08841d30c0 | 3,640,292 |
def zjitter(jitter=0.0, radius=5):
"""
scan jitter is in terms of the fractional pixel difference when
moving the laser in the z-direction
"""
psfsize = np.array([2.0, 1.0, 3.0])
# create a base image of one particle
s0 = init.create_single_particle_state(imsize=4*radius,
radiu... | 7fae2f750cd80708e7cd881a05d535a00b4ecb38 | 3,640,293 |
def append_column(rec, col, name=None, format=None):
"""
Append a column to the end of a records array.
Parameters
----------
rec : recarray
Records array.
col : array_like
Array or similar object which will be converted into the new column.
name : str, optional
Name... | f851ef69946937cbb100d424ddb8502b906940bd | 3,640,294 |
import copy
def dfa2nfa(dfa):
"""Copy DFA to an NFA, so remove determinism restriction."""
nfa = copy.deepcopy(dfa)
nfa.transitions._deterministic = False
nfa.automaton_type = 'Non-Deterministic Finite Automaton'
return nfa | eed8e651a51e71599a38288665604add3d8a0a3d | 3,640,295 |
def count_related_m2m(model, field):
"""Return a Subquery suitable for annotating a m2m field count."""
subquery = Subquery(model.objects.filter(**{"pk": OuterRef("pk")}).order_by().annotate(c=Count(field)).values("c"))
return Coalesce(subquery, 0) | e772c8d55a1d9778077eaf9cbebfc51948361e1c | 3,640,296 |
def create_car(sql: Session, car: CarsCreate):
"""
Create a record of car with its Name & Price
"""
new_car = Cars(
Name=car.Name,
Price=car.Price
)
sql.add(new_car)
sql.commit()
sql.refresh(new_car)
return new_car | 33fda0b653950989bd1b61ae1ee689db05576877 | 3,640,297 |
import time
def train(train_loader, model, criterion, optimizer, args, epoch):
"""Train process"""
'''Set up configuration'''
batch_time = AverageMeter()
data_time = AverageMeter()
am_loss = AverageMeter()
vec_loss = AverageMeter()
dis_loss = AverageMeter()
ske_loss = AverageMeter()
... | fb83156f3915f34dd92d4060b62b77644dd65f8b | 3,640,298 |
import os
import yaml
def fetch_folder_config(path):
"""Fetch config file of folder.
Args:
path (str): path to the wanted folder of the config.
Returns:
dict. the loaded config file.
"""
config = {}
config_path = os.path.join(path, DOC_YML)
if os.path.exists(config_path):... | b78393e8d97147227c0648050f749e48e13a54b5 | 3,640,299 |
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