content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
from sympy import Rational
def RK44_family(w):
"""
Construct a 4-stage fourth order Runge-Kutta method
**Input**: w -- family parameter
**Output**: An ExplicitRungeKuttaMethod
**Examples**::
>>> from nodepy import rk
>>> print(rk.RK44_family(1))
... | 18782206cbc77c5b64d188169fa6fea362177e29 | 3,607,400 |
import sys
def callersContext():
""" get context of caller of a function """
return sys._getframe(2).f_code | d849326202c0062da076f54c379fe5f35b4d35b5 | 3,607,401 |
def upload_data_db_for_creat_pass():
"""Загружает данные по отцам из базы для паспартов."""
logger.debug("Старт upload_data_db_for_creat_pass")
list_col = [
'name', 'number', 'name_number', 'BM1818', 'BM1824',
'BM2113', 'CSRM60', 'CSSM66', 'CYP21', 'ETH10',
'ETH225', 'ETH3', 'ILSTS6'... | 8628d0374b9742367f57f85f77d6a75e3aa0478e | 3,607,402 |
import scipy
def arbitrary_rotation_matrix(axis, theta):
"""
Return the rotation matrix associated with counterclockwise rotation about
the given axis by theta radians.
# Kudos to
# https://stackoverflow.com/questions/6802577/rotation-of-3d-vector
#import math
#
# axis = np.asarray(ax... | e5416f1874820dfbdb5685fdf2daa099edee25df | 3,607,403 |
def Gaussian(shape=(3, 3), sigma=0.5):
"""
2D gaussian mask - should give the same result as MATLAB's
fspecial('gaussian',[shape],[sigma])
"""
m, n = [(ss - 1.) / 2. for ss in shape]
y, x = np.ogrid[-m:m + 1, -n:n + 1]
h = np.exp(-(x * x + y * y) / (2. * sigma * sigma))
h[h < np.finfo(h.... | 2f168af07d7b9787f78d9fa413cd6f723cb871cd | 3,607,404 |
import os
def loadImage(img_path: str) -> pygame.Surface:
"""
Load image from File system
Parameters:
img_path -> Path of image
"""
if os.path.isfile(img_path):
return pygame.image.load(img_path)
else:
return None | bdcb6053d1f5b798887592b17fff465e96ea0d03 | 3,607,405 |
def enableDisableEquipment(enable, names):
# type: (bool, Tuple[String, ...]) -> List[unicode]
"""Enables or disables a Tuple of equipment connections from a
script.
Args:
enable: Set to True to enable equipment connections, or set to
False to disable them.
names: A Tuple of... | 6bb1eca2db62cdabf2748bbe6dcec163e0cf806b | 3,607,406 |
from sys import path
def _quote_and_validate_dir(dirpath):
"""
Checking that the directory exists and is absolute
Return quoted directory
:param dirpath: path to directory
"""
assert path.isabs(dirpath)
return quote(dirpath) | a3e68cce22834adf5db27ee9796c311895ba654f | 3,607,407 |
import struct
def get_arg() -> bytes:
"""
This function returns the (pre-encoded) `password` argument to be sent to
the `sudo` program.
This data should cause the program to execute our ROP-chain for printing our
message in an endless loop. Make sure to return a `bytes` object and not an
`str` objec... | 829fbde5c8202ec170850b0e9cff891f9e0f27cc | 3,607,408 |
def delay_frame (delay):
"""Construct a spacer frame with no content that serves as a delay."""
return ( graphics_control_block(delay) +
image_descriptor_block(0, 0, 1, 1) +
chr(LZW_palette_bits) +
chr(1) +
chr(trans_index) +
chr(0) ) | 03b227ad66d8125402f040504c16069747faa152 | 3,607,409 |
def get_latest_version(package_name, test_database=False):
"""
Retrieve the latest version of the given package name from PyPi. Return a version of 0.0.0
if no package version information is found.
:param package_name: A string specifying the package name to interrogate.
:param test_database: A boo... | c977f95a42399d40e6d9e3571f9d945bc726ff5d | 3,607,410 |
import logging
def calc_regional_services(
enduse,
uk_techs_service_p,
regions,
spatial_factors,
fuel_disaggregated,
techs_affected_spatial_f,
capping_val=1
):
"""Calculate regional specific end year service shares
of technologies (rs_reg_enduse_tech... | 7fb703fca501b441fa985d7a0a778905cdbf30cb | 3,607,411 |
import os
import struct
def load_mnist(path, kind='train'):
"""Load MNIST data from `path`"""
labels_path = os.path.join(path,
'%s-labels-idx1-ubyte' % kind)
images_path = os.path.join(path,
'%s-images-idx3-ubyte' % kind)
# ファイルを読み込む
... | 4e00474dc6585f049fb57514d7a7ce6d2c05aa30 | 3,607,412 |
from datetime import datetime
def get_daily_demographics_age(tiles: np.array(int), day=datetime(year=2020, month=1, day=27)) -> pd.DataFrame:
"""Fetches daily demographics of age categories
Fetches the daily demographics, age distribution, of the tiles and creates a dataframe of the fetched data.
... | 095395e5ac2529bd502d798d9afaaa2643eaf76f | 3,607,413 |
def estimate_magnitude(paz, amplitude, timespan, h_dist):
"""
Estimates local magnitude from poles and zeros or full response of given
instrument, the peak to peak amplitude and the time span from peak to peak.
Readings on two components can be used in magnitude estimation by providing
lists for ``p... | e79fed699599d665dceb06772173f6768e4486ae | 3,607,414 |
def extract_keypoint_index(scoremap):
""" Extract Scoremap.
# Arguments
scoremap: Numpy aray of shape (crop_size, crop-size).
# Returns
max_index_vec: List of Max Indices.
"""
keypoint_index = np.argmax(scoremap)
return keypoint_index | 3c78c64218b3089b85f151e4328ede6c6ca1ffe2 | 3,607,415 |
def transpose(incoming, conv, nonlinearity, *args, **kwargs):
""" Convenience function to transpose a convolutional layer
and use weight tying
"""
return TransposedConv2DLayer(incoming, conv.input_shape[1],
conv.filter_size, stride=conv.stride,
... | 66489060e981f66a36fabc625ff729135b7f577f | 3,607,416 |
def downbin_spec_err(specHR, errHR, lamHR, lamLR, dlam=None):
"""
Re-bin spectum and errors to lower resolution using :py:obj:`scipy.binned_statistic`.
This function calculates the noise weighted mean of the points within a bin such that
:math:`\sqrt{\sum_i \mathrm{SNR}_i}` within each :math:`i` bin is ... | 9a884ea2e3b9c7136f8f20b1ac8f909f9ca8051b | 3,607,417 |
def timebin_dur_from_vec(time_bins, n_decimals_trunc=5):
"""compute duration of a time bin, given the
vector of time bin centers associated with a spectrogram
Parameters
----------
time_bins : numpy.ndarray
vector of times in spectrogram, where each value is a bin center.
n_decimals_tru... | 00b9b31a3edff1ceeacb389a1f2331e8ae3034c4 | 3,607,418 |
def rgb_to_hex(color):
"""Helper function for converting RGB color to hex code
Args:
color (list): List of R,G,B value
Returns:
str: Hex code for the RGB value
"""
r,g,b = color
#print('%02x%02x%02x' % (r,g,b))
return '#%02x%02x%02x' % (r,g,b) | 9308fa029cb2bfd75495c92a2e145f3439e3b60b | 3,607,419 |
def at(seq, msg, cmd=None, *args, **kwargs):
"""Push a new command"""
return translator(seq + 1, msg + clformat("AT*~a=~s,~{~s~^,~}\r",
cmd, seq, map(iso_str, globals()[cmd.lower()](*args, **kwargs)))) | 1080fb5d044556a31e8a5f3d4786334944c6af7d | 3,607,420 |
def L2(v, *args):
"""Returns the L2 norm of a vector v
INPUTS
=======
v: list
Vector of which the L2 norm to be calculated
*arg: list, optional
Weight vector
RETURNS
========
L2_norm: float
float unless len(v) != len(args[0])
in which case a Value... | fe95415fdfdb433dcf75087b943575bf2b7cee5d | 3,607,421 |
def plot_importances(experiment, n_best=15, sort_by='max', calculator=BuiltinImportance(), fontsize=12):
"""
Visualize feature importances (max, mean and std) of an experiment using a given calculator.
:param experiment: Experiment instance, like lb['012ABC']
:param sort_by: one of 'max', 'mean' and 'st... | 1a51bb609a325e92dab1e5f02f81580f7e58f9de | 3,607,422 |
def sort_queryset(queryset, request, allowed_sorts, default=None):
""" Sorts the queryset by one of allowed_sorts based on parameters
'sort' and 'dir' from request """
sort = request.GET.get('sort', None)
if sort in allowed_sorts:
direction = request.GET.get('dir', 'asc')
sort = ('-' if ... | 7d4ef00e0d345d4636caaa9ca69ade0a09e33ea4 | 3,607,423 |
def privacy(request):
"""
The RMG privacy policy.
"""
return render(request, 'privacy.html', {'admins': settings.ADMINS}) | 218f1f24691420e76d562a0251cfce983036ed60 | 3,607,424 |
from typing import Union
import requests
from bs4 import BeautifulSoup
def get_schedule(day: str, format_: Union[pd.DataFrame, set] = set):
"""
Return NBA matchups on queried date.
Arguments:
----------
day: str
Date for which to get schedule.
Format = YYYY-MM-DD
format_: Uni... | 8b29d175d1a1afab302a054793a101941f4027c6 | 3,607,425 |
def match(text):
"""
Parse calendar entry
:param text: The entry to parse
:return: A pair of description, project key
"""
return MATCHER.match(text) | 6e5124cf13656661adb8e2f952ea65542f65197e | 3,607,426 |
def partial_pullback(b, c, d, b_d, c_d):
"""Find partail pullback."""
check_homomorphism(b, d, b_d, total=False)
check_homomorphism(c, d, c_d, total=False)
bd_dom = subgraph(b, b_d.keys())
cd_dom = subgraph(c, c_d.keys())
bd_b = {n: n for n in bd_dom.nodes()}
cd_c = {n: n for n in cd_dom.n... | 2e71a8f7f7664e294380cf446ac425f2766ef595 | 3,607,427 |
def get_colormap_lut(name='flame'):
"""Get lookup table from one of pyqtgraph's gradient editor's presets.
Result is suitable for ImageItem.setLookupTable. Gradient names listed in
Gradients.keys(). Not sure how 'hsv' mode works.
"""
gradient=Gradients[name]
ticks=gradient['ticks']
v=np... | d6bc069c8a54538389995e6dd902ab309b2f7c69 | 3,607,428 |
import tempfile
import subprocess
def make_runner_dir(version):
"""Extract the runner tar to a temporary directory"""
dir = tempfile.TemporaryDirectory()
tar = _get_runner_tar(version)
subprocess.check_call(
["tar", "-xzf", tar],
cwd=dir.name,
)
return dir | e452fda7b2dd5d1243141cf177e090bade265e93 | 3,607,429 |
from typing import Any
import json
async def get_messages(number: str) -> Any:
"""
get messages
"""
response = await run_signal_cli_command(["-u", quote(number), "--output=json", "receive"])
return [json.loads(m) for m in response.split("\n") if m != ""] | 8ec57bff19abce43bd96b48391e3d1f0470e70f0 | 3,607,430 |
import gzip
import pickle
def read_pickle(fname, compress=True):
"""
read analysis from pickle file
"""
if compress:
with gzip.open(fname, "rb") as f0:
return pickle.load(f0)
else:
with open(fname, "rb") as f0:
return pickle.load(f0) | 040976647b637ee08f33094e13d3a19605495463 | 3,607,431 |
import random
def _k_init(X: np.ndarray, n_clusters: int, random_state=None) -> np.ndarray:
"""Initialize kmeans centers by picking a random point as the center"""
return np.array([X[random.randint(0, len(X) - 1)]
for i in range(n_clusters)]) | b1e117c8dbe6d3c3392dd76f7d10872f343a2795 | 3,607,432 |
def post_create(request):
"""
View function for post-create page of site.
Param request post form data.
Return post create view.
"""
user = get_object_or_404(User, pk=request.user.id)
formData = None
form = PostForm()
check_route("post", request.META.get("HTTP_REFERER"), request)
... | 6f5c4caeebbbace23dc5a91c25fbb8c385c3a561 | 3,607,433 |
def extract_path_from_filepath(file_path):
"""
ex: 'folder/to/file.txt' returns 'folder/to/'
:param file_path:
:return:
"""
st_ind=file_path.rfind('/')
foldern = file_path[0:st_ind]+'/'
return foldern | 7014ac6d4fa47edff3315f7e23688cfe2e28a820 | 3,607,434 |
def flip_coordinate_system(q):
"""
as far as i understand it is assumed that we are already in a different coordinate system
so we first flip the coordinate system to the original coordinate system to do the original transformation
then flip coordinate system again to go back to the flipped coordinate s... | a15fe27e507d8129d2ad0d7cc28c0a033dcf9e5e | 3,607,435 |
def fname_to_string(fname):
"""Return given file as sring
Parameters
----------
fname : str
absolute path to file.
"""
with open(fname) as fid:
string = fid.read()
return string | f9a3f94dc4a63c27cadb5c5f9a41eaa942332937 | 3,607,436 |
import argparse
def parse_args():
"""
Parse muCLIar args
:return:
"""
parser = argparse.ArgumentParser(description='muCLIar - Music from CLI')
parser.add_argument('-s', '--song', type=str, help='Song name', required=True)
parser.add_argument('-c', '--config', action='store_true')
return parser.parse_args() | ee55696b68927a6c0ff05ab4536a57f7ece91108 | 3,607,437 |
def index():
"""
Display the home page.
:return: Index template.
"""
user = g.user # get the currently logged in user
return render_template("index.html",
title='Home',
user=user) | a1356d31270bdfd79e6259eb88b563a786902f90 | 3,607,438 |
import os
import tqdm
def read_labeled_image_list(image_dir, data_set="LIP"):
"""Reads txt file containing paths to images and ground truth masks.
Args:
data_dir: path to the directory with images and masks.
data_list: path to the file with lines of the form '/path/to/image /path/to/mask'.
R... | 6741cc7f88ef8db3cd321bc94c5f552140466b4e | 3,607,439 |
from typing import Tuple
def create_pca_features(x: pd.DataFrame,
x_train: pd.DataFrame,
x_test: pd.DataFrame) -> Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame, pd.DataFrame]:
""" Compute PCA of given full/training/test data
PCA is fitted on the full dataset x ... | 866453fa63aa8181c6d2d48166d55d641fe3b038 | 3,607,440 |
import pandas as pd
import os
def aids(path):
"""Delay in AIDS Reporting in England and Wales
The `aids` data frame has 570 rows and 6 columns.
Although all cases of AIDS in England and Wales must be reported to the
Communicable Disease Surveillance Centre, there is often a considerable
delay between the ... | 2e508fcf8b59e1c589e043d3e3e25650c99bbecb | 3,607,441 |
def global_color_table(color_depth, palette):
"""
Return a valid global color table.
The global color table of a GIF image is a 1-d bytearray of the form
[r1, g1, b1, r2, g2, b2, ...] with length equals to 2**n where n is
the color depth of the image.
----------
Parameters
color_depth:... | 4fc8b0cad668724b0a6d5735f70dcb16b6b9b140 | 3,607,442 |
def feature_extraction_Step(all_s,all_id,all_label,config):
"""
Extract features for all signals included in all_s
Args:
all_s (list of numpy arrays): list of signals from which features are extracted.
all_id (list of strings): corresponding list of IDs for signals in all_s.
all_labe... | 729d942e1a5d9b9774594506949aaa918192e944 | 3,607,443 |
def match_rule_based():
"""
- Create Keyword RuleBased
:return:
"""
item = request.get_json(force=True)
key = CutId(_id=ObjectId()).dict()['id']
item['access_token'] = mango_channel
item['id'] = key
db.insert_one(collection, item)
del item['_id']
return jsonify(item) | 41c615912f505c15b2a12d0992e361e32a47f6c4 | 3,607,444 |
def _create_installation(iid):
"""Send a request to create an installation (ID: iid). Return the object
ID associated with it"""
data = {
"deviceType": "android",
"appVersion": settings.YIKYAK_VERSION,
"parseVersion": settings.PARSE_VERSION,
"appName": "Yik Ya... | 0ca2d19083f7b7d0c1d200bef99b8ad1c1efa6e6 | 3,607,445 |
def _optimize_shape(count, width_height_aspect_ratio=1.0):
"""Computes the optimal X by Y shape of count objects given a desired
width-to-height aspect ratio.
"""
N = count
W = np.arange(1, N).astype(np.uint32)
H = np.ceil(N / W).astype(np.uint32)
closest = np.argmin(np.abs((W / H) - width_h... | 3ddc8b636e8d0d1d51bfa7a2e4e2ae915bf9a8a8 | 3,607,446 |
def parcellate_func_combine_hemis(lh_func, rh_func, lh_parcel_path, rh_parcel_path):
"""
#Function that takes functional data in the form <num_verts, num_timepoints> for
#both the left and right hemisphere, and averages the functional time series across
#all vertices defined in a given parcel, for ... | 5e81489c7b961af38e02ea3490afc03549a7b845 | 3,607,447 |
import numpy
def grpCompose(f1,f2):
"""
compose two elements of group SE(3).
f1.f2 = [R1*R2, (R1*t2)+t1]
where, R1,R2 are rotation matrices and t1,t2 are translation vectors.
But note that the function expects f1 to contain rotation vector instead
of rotation matrix.
Inputs:
f1 -> Elem... | c807eba92c0b8f1504e2f4229be8b2ac7e564020 | 3,607,448 |
def get_rfmid_loaders(
size,
batch_size=64,
num_workers=8,
):
"""get dataloaders for RFMiD dataset, and also return number of labels"""
loaders = []
for split in ["train", "valid", "test"]:
tfms = get_tfms(size=size, augmentation=split == "train")
D = RFMiD(
split=spl... | d632e57aafb4ae16e90b3a36753f5d62a590f4b5 | 3,607,449 |
def repos(request):
"""/repos - Show the list of known Subversion repositories."""
# Clean up garbage created by buggy edits
bad_branches = models.Branch.gql('WHERE owner = :1', None).fetch(100)
if bad_branches:
db.delete(bad_branches)
repo_map = {}
for repo in models.Repository.all().fetch(1000, batch_... | 116b3f58068befaf3ef40a69e5db6307fd8165ce | 3,607,450 |
import torch
def upsample_flow(flow, mask):
""" upsample a flow field """
flow = flow * torch.as_tensor([8.0, 8.0, 1.0]).to(flow.device)
return cvx_upsample(flow, mask) | 5eb436d902b778d99079287439d123c6506b689b | 3,607,451 |
def get_workspace_attribute(ns: str, ws: str, attribute_name: str):
"""
Get value of an existing attribute.
:param ns:
:param ws:
:param attribute_name:
:return:
"""
attributes = _query_workspace(ns, ws)['attributes']
if attribute_name not in attributes:
logger.error(f"Queri... | bef84c2996b4494e6869e4690eee63c0a1b02852 | 3,607,452 |
import httpx
def parse_url(client: httpx.Client, url: str, *, parse_seperate_2p: bool = False) -> Level:
"""
Parses the level data from an url, uses download_level to download with parse_rdzip to parse.
Args:
client (httpx.Client): httpx client to use for the request
url (str): Url for th... | 9621b7967dfb4bb100250f866e91ac249e8f0330 | 3,607,453 |
import math
def arclen(angle, radius, rad=False):
"""Calculates the size of an arc of a circle"""
if rad:
angle = math.degrees(angle)
return (angle / 360) * (2 * math.pi * radius) | c94e3a0f838a4ee635da4997da3ac89867d03366 | 3,607,454 |
def testapp_with_base64(settings, user_format):
"""Fixture for setting up a Swagger 2.0 version of the test testapp."""
settings['pyramid_swagger.swagger_versions'] = ['2.0']
settings['pyramid_swagger.user_formats'] = [user_format]
return App(main({}, **settings)) | 8fdd5b835206f6f943d83243bbf1ea21705278b9 | 3,607,455 |
from typing import Callable
from typing import List
def search_result(_: Callable, result: List[FAMovie]) -> Keyboard:
"""
Keyboard for results of a movie query.
"""
buttons = [
[
Button.inline(
movie['title'],
b'film_' + movie['id'].encode('utf8')
... | 6bc6c903a1dd4817929b4d864ff30a52cb995649 | 3,607,456 |
def fastqs_from_unit(unit):
"""FIXME is this really needed?
"""
if unit['fq2']:
return objectify_remote(unit['fq1']), objectify_remote(unit['fq2'])
else:
return objectify_remote(unit['fq1']) | 5bd8c53bc0b20f8fb8d1899a1e88ef04c013d92a | 3,607,457 |
def import_obj_file(file_path, force=True, **kwargs):
"""
Imports OBJ file into current DCC scene
:param file_path: str
:param force: bool
:param kwargs: keyword arguments
:return:
"""
if not is_plugin_loaded('objexport.mll'):
load_plugin('objexport.mll', quiet=True)
kwargs... | bfd8f56855c6da9695d9498aabaaba1aed9aa306 | 3,607,458 |
def translate(seq):
""" Translate a DNA sequence into protein. """
# Make sure sequence is upper case
seq = seq.upper()
# Find start codon
i = 0
while i < len(seq) + 2 and seq[i:i+3] != 'ATG':
i += 1
# Translate until the stop codon or end of string
prot = []
while i < len... | 2c04af772a3b6bda6b77d3c6ae1c4f507e6292af | 3,607,459 |
def get_number_of_elements(scaledArr, threshold=2e-4):
"""
Computes the number of elements displayed on a image, using a threshold.
Parameters
---------
scaledArr : ScaledArray
Contains the data of interest
Returns
---------
NdArray, Number :
Returns the number of e... | 1e8ca4f871c7cc2347cb495374cdba443439b18b | 3,607,460 |
from typing import Callable
def prepare_image(img_array: npt.ArrayLike, _model_preprocess: Callable) -> npt.ArrayLike:
"""Prepare any image so that it can be fed into a model predict() function.
This includes:
- converting to RGB channels
- resizing to the appropriate image size expected by the model... | 536660fed746e40b76fbaa87a5e86d1f5beb2e35 | 3,607,461 |
import torch
def precision(label_pred, label_gt) -> float:
"""
Computes the precision
"""
with torch.no_grad():
prediction_bin = torch.argmax(label_pred, dim=1)
TP = torch.mul(prediction_bin, label_gt).sum()
FP = torch.mul(prediction_bin, 1 - label_gt).sum()
PC = float(... | 039e4c938d5ef6fd27ecda1d1bf027863b973060 | 3,607,462 |
from typing import Tuple
def _normalize(img: np.ndarray, result_range: Tuple[int, int] = (0, 255)) -> np.ndarray:
""" Normalizes given image by performing simple interpolation to given range. """
return np.interp(img, (img.min(), img.max()), result_range).astype(np.uint8) | 8d28c4ba21f3e32a1be994f6838bc49d5feb90d9 | 3,607,463 |
import hashlib
def get_hashes(binary):
"""Return md5, sha1 and sha256 hashes of input byte string."""
hash_dict = dict()
for hash_type in ['md5', 'sha1', 'sha256']:
if hash_type == 'md5':
hash_alg = hashlib.md5()
elif hash_type == 'sha256':
hash_alg = hashlib.sha256... | 0005a1446b6f58bb6cc6227428a304b0894e6947 | 3,607,464 |
def attach_xunit_results(file: str) -> BuiltInCommand:
"""
Create an Evergreen command to parse results in XUnit test results format.
:param file: A .json file to parse and upload.
"""
params = {"file": file}
return BuiltInCommand("attach.xunit_results", params) | e8b305a083707dadcfd5b23733c1a94252cc1732 | 3,607,465 |
from typing import Optional
from typing import Any
def age_to_delete(age: Optional[Any]) -> Optional[dict]:
"""
TODO: Delete this function once we remove age from details
Given an *age*, return a dict containing its 'value' and a boolean for
'ninetyOrAbove'.
Currently applys math.ceil() to age to ... | 3ff9eb6e7eb9def712fd54bfd698767202a28f0d | 3,607,466 |
def zr_wr_dem(x):
"""
Real Name: b'Zr wr dem'
Original Eqn: b'( [(1,0)-(365,0.04)],(1,0),(2,0),(3,0),(4,0),(5,0),(6,0),(7,0),(8,0),(9,0),(10,0),(11,\\\\ 0),(12,0),(13,0),(14,0),(15,0),(16,0),(17,0),(18,0),(19,0),(20,0),(21,0),(22,0),(23\\\\ ,0),(24,0),(25,0),(26,0),(27,0),(28,0),(29,0),(30,0),(31,0),(32,0),... | 20a4fba212b0b950b75e2c048c063db2840ed949 | 3,607,467 |
import sys
def download_file(file: str):
"""
Download file from s3 storage
:param file: str - path in s3 storage
:return: S3 Object
"""
try:
file = remove_start(strip_str(file))
response = s3client.get_object(Bucket=settings.AWS_STORAGE_BUCKET_NAME, Key=file)
return res... | ea5fe2635956d4993a42211d05534faa4de2dcc2 | 3,607,468 |
import os
def getMachineFacts():
"""Gets some facts about this machine we use to determine if a given
installer is applicable to this OS or hardware"""
# pylint: disable=C0103
machine = dict()
machine['hostname'] = unicode_or_str(os.uname()[1])
machine['arch'] = os.uname()[4]
machine['os_v... | 6c03cf15c97e83cbed60c3f605bd665bcbb83fd0 | 3,607,469 |
import os
import pathlib
def get_downloads_dir():
"""Returns the downloads directory path"""
env_value = os.environ.get(_ENV_PREFIX + "DOWNLOADS_DIR")
if env_value:
path = pathlib.Path(env_value)
if not path.is_dir():
raise NotADirectoryError(env_value)
return path
... | 35dc1db26c18102ddb741581ae4e878b1d9a5f3f | 3,607,470 |
def parse_json(data, collection):
""" Calls the appropriate json parser based on the collection,
returns whatever the parser returns, along with the query and
num_responses, which it gets from the json response. If there
are no results, it returns ([], query, 0)"""
# FIRST (only applies to reference... | 7a84729e7d907325a10d469ac720069a633426e5 | 3,607,471 |
def inner_func_float():
"""
Обертка для lambda (двухуровневая, float)
"""
return defaultdict(inner_lambda_float) | 76c8695cfa567dc198af343a75969d65236eab3c | 3,607,472 |
def _reachablerootspure(pfunc, minroot, roots, heads, includepath):
"""See revlog.reachableroots"""
if not roots:
return []
roots = set(roots)
visit = list(heads)
reachable = set()
seen = {}
# prefetch all the things! (because python is slow)
reached = reachable.add
dovisit =... | 08364dd59bab0136e41893d13328e6665269230a | 3,607,473 |
def Go_NoGo(loaded_file, i):
"""
:param loaded_file: file output from operant box
:param i: number of days analyzing
:return: data frame of all analysis extracted from file (one animal)
"""
(timecode, eventcode) = extract_info_from_file(loaded_file, 500)
(dippers, dippers_retrieved, retrieva... | 36d56142ffae3d6b42f18760418c6f069a045f27 | 3,607,474 |
def read_sfmlearn(ego_path, flip):
"""
Right-hand coordinate (following SfMLearn paper).
X: Pitch, Y: Yaw, Z: Roll
"""
ego_dict = {}
with open(ego_path, "r") as f:
for line in f:
strings = line.strip("\r\n").split(",")
key = strings[0]
vx, vy, vz, rx, ... | 38d708334f70c3a2abdf8bc28edd3700b9476498 | 3,607,475 |
def get_links(soup, artist):
"""Get the complete link for each song of the artist"""
links = f'links_{artist}'
links = []
for td in soup.find_all('td'):
if "tal" in td.get('class',[]):
links.append('https://www.lyrics.com'+td.find('a')['href'])
return links | 0587286e3bd15abdee0403745b5fc6d5af81ce5c | 3,607,476 |
def colorize_profit(profit):
"""
Colorize the profit depending on its value.
:param profit: Profit.
:return: console_colored, html_colored
"""
color = {
'html': {
profit <= -10: RED_HTML,
-10 < profit <= 0: YELLOW_HTML,
0 < profit < 10: GREEN_HTML,
... | 886823f7aed0fdd9279b487e2dd7f0dabcaa889a | 3,607,477 |
from typing import BinaryIO
def _read_ft_cfg(file: BinaryIO) -> Metadata:
"""
Constructs metadata from fastText config.
"""
cfg = list(_read_required_binary(file, "<12id"))
losses = ['HierarchicalSoftmax', 'NegativeSampling', 'Softmax']
cfg[6] = losses[cfg[6] - 1]
models = ['CBOW', 'SkipGr... | 8b63714ceb3dd96be5351ea55ba83f93faf1970b | 3,607,478 |
from typing import Callable
def named(name: str) -> Callable[[C], C]:
"""
Change the name of a function to the given name.
"""
def decorator(original):
# type: (C) -> C
original.__name__ = str(name)
original.__qualname__ = str(name)
return original
return decorato... | 44f755872f627f528964669508072a6f37defe91 | 3,607,479 |
def getQuarter(date):
"""Extracts the quarter from a date, ranging from 1-4.
Args:
date (Date): The date to use.
Returns:
int: An integer that is representative of the extracted value.
"""
return ((date.month - 1) // 3) + 1 | 26868a8dc6e4fd9e58daccf44b2357529dfdd1fd | 3,607,480 |
def dup_mul(f, g, K):
"""
Multiply dense polynomials in ``K[x]``.
**Examples**
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.densearith import dup_mul
>>> f = ZZ.map([1, -2])
>>> g = ZZ.map([1, 2])
>>> dup_mul(f, g, ZZ)
[1, 0, -4]
"""
if f == g:
ret... | f10628d9054b7dae1a303e841ec69ea5684f53c3 | 3,607,481 |
from typing import Type
def norm_param(arr_t):
"""
Returns a transformation that calculates the ``order``-norm
(1 output, 1 input, 1 param): ``output = abs(input) ** order``.
"""
if dtypes.is_complex(arr_t.dtype):
out_dtype = dtypes.real_for(arr_t.dtype)
else:
out_dtype = arr_t... | 376741b651f0d3efa572b3fd14baadc9bfb84cfc | 3,607,482 |
def _get_filenames_glob(variable, drs):
"""Return patterns that can be used to look for input files."""
path_template = _select_drs('input_file', drs, variable['project'])
filenames_glob = _replace_tags(path_template, variable)
return filenames_glob | 13441ed29b7516be09f6855dff10d0f2d19f794e | 3,607,483 |
def _LoadGclientFile(path):
"""Load a gclient file and return the solutions defined by the gclient file.
Args:
path: The gclient file to load.
Returns:
A list of solutions defined by the gclient file or an empty list if no
solutions exists.
"""
global_scope = {}
# Similar to depot_tools, we us... | 0142ad9b4c87eca35c8b1e5fae30c19c5d8d05a5 | 3,607,484 |
def find_closet_match(color, tile_colors):
"""在tile_colors中寻找与颜色color最接近的颜色,返回下标和差异值"""
diff = float('inf')
index = 0
for i, c in enumerate(tile_colors):
d = get_color_diff(color, c)
if d < diff:
diff = d
index = i
return index, diff | d68ead2b8d24114b2f29a77e97c90c93df5a1a64 | 3,607,485 |
from enum import Enum
from typing import Tuple
from typing import Callable
from typing import Any
def load_conf(
conf_type: Enum,
conf_data: Tuple[str, FileConfig] = CONFIGS_DATA,
load_func: Callable[[FileConfig], Any] = dispatcher
):
"""
Универсальный кэшируемый загрузчик конфигураций... | 8a575c85d375af24cde7b2812ea7d271e004d797 | 3,607,486 |
def LicenseFromPath(path):
"""Try to figure out the license for a given path.
Splits path and looks for known license dirs in segments.
Args:
path: A filesystem path, hopefully including a license dir.
Returns:
The name of the license, eg OFL, UFL, etc.
Raises:
ValueError: if 0 or >1 licenses ma... | 89f6fee5f0869640ae51f10fb5298930b6be8d9d | 3,607,487 |
def _get_dyson_purecool_device():
"""Return a valid device as provided by the Dyson web services."""
device = mock.Mock(spec=DysonPureCool)
device.serial = "XX-XXXXX-XX"
device.name = "Living room"
device.connect = mock.Mock(return_value=True)
device.auto_connect = mock.Mock(return_value=True)
... | d4af0ba642bea2fce2bdef222b1b7dfae94b59a0 | 3,607,488 |
def list_quicklinks():
"""
Returns a list of QuickLinks
:return: list<String> list of quick links
"""
quicklinks_list = []
with open(DEFAULT_FILE) as file:
for line in file:
quicklinks_list.append(line.strip())
return quicklinks_list | 5e3ab8d1840e53fd0218e347961b8217c34eafa6 | 3,607,489 |
import hashlib
def hash_seqs(sequences):
"""
Generates hexdigest of Sha1 hash for each sequence in a list of sequences.
This function is useful for generating sequence specific identifiers that allow for easier comparison of features
from multiple sequencing runs or sequence processing runs.
"""... | 35c3291a58ebc7e053250f7234faacd0356f7df5 | 3,607,490 |
def add_myst(original: str) -> str:
"""Change docs/conf.py to use MyST-Parser, enabling md files"""
# add myst_parser extension and its own extensions configuration
content = original.splitlines()
myst = '\n# Enable markdown\nextensions.append("myst_parser")\n'
myst_extensions = template("myst_exten... | 64d13a78b12ff856333a65e42de855bfc3eaf33e | 3,607,491 |
def get_paths(link, nb):
"""
Generate a list containing all URLs
Args:
link [str]: Base HTML link
nb [int]: Number of pages usingHTML link
Returns:
url [str]: [List containing all URLs]
"""
url = []
for si in range(2000, 2020):
for ti in range(1, nb+1):
... | 8fd0a947eeb5435f0df48dc928feb3a10786c2cc | 3,607,492 |
def heaviside(x, bias=0):
"""
Heaviside function Theta(x - bias)
returns 1 if x >= bias else 0
:param x:
:param bias:
:return:
"""
indicator = 1 if x >= bias else 0
return indicator | b325a862cbc2cac97b8e4808c6d77b54a0f1d643 | 3,607,493 |
def register(message_array, device, auto_mode):
"""
Message: register
"""
pwd = pwgen(10, no_symbols=True)
if (device.contributor.status == Contributor.UNKNOWN) or (device.contributor.status == Contributor.INACTIVE):
device.contributor.status = Contributor.ACTIVE
device.contribu... | c4776ad2fe1f953253b0ed6194e89c71f14dc0a8 | 3,607,494 |
def lsubstr(view, point, length=1):
""" Return the character(s) to the left of the point on the same line. """
col = view.rowcol(point)[1]
region = Region(point - min(length, col), point)
return view.substr(region) | 874511493cf71c508984404780751fc4f59c35c6 | 3,607,495 |
def biggest_differences_words(prunedTable):
""" Finds the words that are most different from their most frequent alternative across each semantic dimension
Parameters
----------
prunedTable : a data frame
The data frame representing arousal, valence, and dominance ratings for words and their mo... | 2b39a717fbdf7d823a381ff3320e2ac487f65ec3 | 3,607,496 |
def centos8(function):
"""Decorator to set the Linux distribution to CentOS 8"""
def wrapper(*args, **kwargs):
hpccm.config.g_linux_distro = linux_distro.CENTOS
hpccm.config.g_linux_version = StrictVersion('8.0')
return function(*args, **kwargs)
return wrapper | 4fbdc47e00bff3b8967cfa8ba9c422b4586915de | 3,607,497 |
def stats(state):
"""Return the statistics for given state.
Parameters
----------
state : RunningState
Returns
-------
Stats named tuple
"""
if not state.count:
return Stats(0, 0, 0, 0, 0, 0)
mean = state.sum / state.count
std = (float(state.sum2 - 2.0 * state.sum ... | 731dc9c40db2f459f0bf7419277e9bc4106c2578 | 3,607,498 |
import asyncio
import concurrent
async def get_async_multiprocess():
"""Multi Process"""
loop = asyncio.get_running_loop()
with concurrent.futures.ProcessPoolExecutor() as pool:
task1 = loop.run_in_executor(pool, syncFn1, 1)
task2 = loop.run_in_executor(pool, syncFn2, 2)
res1 = awa... | b1609c2582ff9022bccb15f7d16bb299a991f26a | 3,607,499 |
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