content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def export_ruptures_csv(ekey, dstore):
"""
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object
"""
oq = dstore['oqparam']
if 'scenario' in oq.calculation_mode:
return []
dest = dstore.export_path('ruptures.csv')
header = ('rupid multiplicity ... | b23f6b9fea092822d9700017bf92aab322577da6 | 3,634,800 |
import argparse
def get_arguments():
"""Parse all the arguments provided from the CLI.
Returns:
A list of parsed arguments.
"""
parser = argparse.ArgumentParser(description="DeepLabLFOV NetworkEv")
parser.add_argument("--pred-path", type=str, default='',
help="Path t... | 12e8f214e5ef97e0a5a5e3aafaa8395a9e845601 | 3,634,801 |
def get_google_auth(state=None, token=None):
"""Helper function to create OAuth2Session object."""
if token:
return requests_oauthlib.OAuth2Session(Auth.CLIENT_ID, token=token)
if state:
return requests_oauthlib.OAuth2Session(Auth.CLIENT_ID,
state=state,
... | 70f60828f6ad7c6a7658a217f98a22cfd07067ae | 3,634,802 |
def _normalize_dataframe(dataframe, index):
"""Take a pandas DataFrame and count the element present in the
given columns, return a hierarchical index on those columns
"""
#groupby the given keys, extract the same columns and count the element
# then collapse them with a mean
data = dataframe[in... | fdc49912f538694048560f1c1453714791a7c6e4 | 3,634,803 |
import json
def load_network_from_checkpoint(checkpoint, model_json, input_shape=None):
"""Function to read the weights from checkpoint based on json description.
Args:
checkpoint: tensorflow checkpoint with trained model to
verify
model_json: path of json file with model description of
... | 75c877c66c7397366c1f88aaa218487aa11c08d4 | 3,634,804 |
def get_indicator_plugin_manager():
"""
Import all Hook classes that are in the plugins package
and make this availables for be called from master sources
"""
pm = pluggy.PluginManager("indicator")
pm.add_hookspecs(IndicatorSpec)
for class_imported in indicatorPluginClasses: # noqa: F405
... | 610d21bab6f58a0b43539b5b382233b71937e764 | 3,634,805 |
def run(command, **kwargs):
"""Run and return the output of a command.
Raise CalledProcessError on error.
Pass in any kind of shell-executable line you like, with one or more
commands, pipes, etc. Any kwargs will be shell-escaped and then subbed into
the command using ``format()``::
>>> r... | 5022e5cb1fe4863e1bd2293385eb8f13fe763e58 | 3,634,806 |
from datetime import datetime
def to_date(string, format="%d/%m/%Y"):
"""Converts a string to datetime
:param string: String containing the date.
:type string: str
:param format: The date format. Use %Y for year, %m for months and %d for daus, defaults to "%d/%m/%Y"
:type format: str, optional
... | 83fa8e8a0cdfae9546c7a83e55ddcf84ec667646 | 3,634,807 |
def invert_apply_grouping2(grouped_items, groupxs, dtype=None):
"""use only when ungrouping will be complete"""
maxval = _max(list(map(_max, groupxs)))
ungrouped_items = np.zeros((maxval + 1,), dtype=dtype)
for itemgroup, ix_list in zip(grouped_items, groupxs):
ungrouped_items[ix_list] = itemgro... | c1e7d46ddf57bc7bf1f7123fbd18061b63fb8a8d | 3,634,808 |
def make_aware_assuming_local(dt):
"""
Just a wrapper for Django's method, which will takes a naive datetime, and makes it timezone
aware, assuming the current timezone if none is passed (which it isn't from this wrapper
function). It will also raise an exception if the passed datetime is already timezo... | 3b9f142f11bc918a7faebcb0309f43dc6e9a5d2b | 3,634,809 |
def pad_word_array(word_array, MAX_SEQUENCE_LENGTH, padding='pre', truncating='pre'):
"""Return a word array that is of a length MAX_SEQUENCE_LENGTH by truncating the original array or padding it
Args:
word_array:
MAX_SEQUENCE_LENGTH:
padding:
truncating:
Returns:
"""
... | 33d33284eb347f9f4b242932c42b7b8b68219135 | 3,634,810 |
def nbconvert(code):
"""Create Jupyter Notebook code
Return dict in ipynb format
Arguments:
code -- code string separated by \\n
"""
cells = []
for cell in code.split("\n# <codecell>\n"):
cells.append({
"cell_type": "code",
"execution_count": None,
... | f7e895e107f07850652e762a4b382ec299e6d352 | 3,634,811 |
def add_box(width, height, depth):
"""
This function takes inputs and returns vertex and face arrays.
no actual mesh data creation is done here.
"""
verts = [
(+1.0, +1.0, 0.0),
(+1.0, -1.0, 0.0),
(-1.0, -1.0, 0.0),
(-1.0, +1.0, 0.0),
(+1.0, +1.0, +2.0),
... | 930dedbba8a1c11999d4ffdb98b0032bae743498 | 3,634,812 |
import time
def pixmap(randoms, targets, rand_density, nside=256, gaialoc=None):
"""HEALPix map of useful quantities for a Legacy Surveys Data Release
Parameters
----------
randoms : :class:`~numpy.ndarray` or `str`
Catalog or file of randoms as made by :func:`select_randoms()` or
:fu... | cda21bb679c84d1842ca1de675db0daf3ed79534 | 3,634,813 |
from typing import Union
from typing import Callable
from typing import Sequence
from typing import Tuple
def filter_keys(data: dict, keys: Union[Callable, Sequence],
return_popped=False) -> Union[dict, Tuple[dict, dict]]:
"""
Filters keys from a given data dict
Args:
data: the di... | ecfd6985242d802401c25046745afade16ceec24 | 3,634,814 |
def beta_ion(T_rad, species):
"""Case-B photoionization coefficient.
Parameters
----------
T_rad : float
The radiation temperature.
species : {'HI', 'HeI_21s', 'HeI_23s'}
The relevant species.
Returns
-------
float
Case-B photoionization coefficient in s\ :sup:`... | d82b37fcfd4852722260a7b4f6c92e58e8588b11 | 3,634,815 |
from pathlib import Path
def load_template(template_path, template_name):
"""Loads a Jinja template from a given path and name
Arguments:
template_file {PathToDir: Path/String}
template_name {Filename: String}
Raises:
IOError: This path does not exist
"""
if isinstance(te... | 8e935d2f0ab41174237d4b7c803d5e16687d3bd0 | 3,634,816 |
def html(string):
"""Return inline html element."""
return RawInline('html', string) | 980b409f769a38102398c81006dfd220b8865715 | 3,634,817 |
def mock_user_moira_lists(mocker):
"""Return a fake moira client"""
mocked = mocker.patch("ui.utils.user_moira_lists")
mocked.return_value = set()
return mocked | 8dedab7071deae4f1e5fa3ffc7b79149fc49e795 | 3,634,818 |
def translateAllIndex(text):
"""
This is the translator API
Call this api passing a piece of text and get back the Swedish translation
---
tags:
- Translation API
parameters:
- name: text
in: path
type: string
required: true
description: The text
r... | e7740738d112c64a6dfa30be7825e4db9b89f6f0 | 3,634,819 |
import os
import logging
def get_network_config(net_topology, ignore_env_vars=False,
net_topology_file="network.yaml"):
"""Get network info from environment.
Get network info from network.yaml, override the values if specific
environment variables are set for the undercloud.
T... | 2fd063de58cabbfcd42be8efe30dd0a7fd4fd826 | 3,634,820 |
import imp
import os
def get_testbeds_dict():
"""Return a dictionary containing mapping from dut hostname to testbed name."""
testbed = imp.load_source('testbed', os.path.join(SONIC_MGMT_DIR, 'tests/common/testbed.py'))
testbeds_dict = testbed.TestbedInfo(TESTBED_FILE).testbed_topo
return testbeds_dic... | f04902b0f599ed0c9acc6fec6da5883b3924652e | 3,634,821 |
def AIHT(x, A, AT, m, M, thresh, proximalProjection=None):
"""
Accelerated Iterative Hard thresholding algorithm that keeps exactly M elements
in each iteration. This algorithm includes an additional double
overrelaxation step that significantly improves convergence speed without
destroying any of the theoretical... | a4eed242acddf61059d3a77367a89d6966b16c63 | 3,634,822 |
def permutate(array: list, permutation: list):
""" permutate a fixed array with a given permutation list
Args:
array: An array of random elements
permutation: The permutation of the given array
Returns:
"""
_swapped_array = []
_counter = 0
for i in permutation:
... | 5b4f603c030276dcd78b6334ec00c901ca003c63 | 3,634,823 |
def has_collided_with_wall(
width: int, height: int, segments: list[SnakeSegment]
) -> bool:
"""Return True if the snake has collided with a wall."""
head = segments[0]
return (
head.x <= 1 or head.x > width - 3 or head.y < 1 or head.y >= height - 2
) | 54f96b2a28f56e440f647316fe9e9e0dac356c34 | 3,634,824 |
def plot_heatmap_max_val(env, value):
"""
Generate heatmap showing maximum value at each state (not for n-armed
bandit).
"""
if env.name == 'n_armed_bandit':
print("Heatmap can only be generated for grid worlds.")
return None
if value.ndim == 1:
value_max = np.reshape(v... | b39c43aa87bbae78b519e5f1042a63359a0c9f48 | 3,634,825 |
def separate_lines(lines,imshape):
"""
separate_lines(lines)
Classifies left and right lines based on slope
---------------------------------------------------------------------------
INPUT:
lines: line points [[x1,y1,x2,y2]]
OUTPUT:
right{}: right line dictionary with the follo... | 3d7ee319456202cc7478a97afc78922761a9e86e | 3,634,826 |
def p_climo_one_season( seasonname, datafilenames, omit_files, varnames, fileout_template,
time_units, calendar, dt, force_scalar_avg1,
input_global_attributes, filerank={}, filetag={},
outseasons=None, queue1=None, lock1=None, comm1=None ):
"""cli... | dfd41e9cce28fbca51a4a838df831aa95c62b3af | 3,634,827 |
def two_view_reconstruction_rotation_only(p1, p2, camera1, camera2, threshold):
"""Find rotation between two views from point correspondences.
Args:
p1, p2: lists points in the images
camera1, camera2: Camera models
threshold: reprojection error threshold
Returns:
rotation ... | 25bc0038970eae23cf8443f4de1a7f89e5ff4f34 | 3,634,828 |
def state_lookup():
"""Look up state from given zipcode.
Once state is found, redirect to call_senators for forwarding.
"""
zip_digits = request.values.get('Digits', None)
# NB: We don't do any error handling for a missing/erroneous zip code
# in this sample application. You, gentle reader, sho... | 13219025777e50422ab30902f0f3d35f7b73afed | 3,634,829 |
def vmtkmeshtosurface(mesh, cleanoutput=1):
"""Convert a mesh to a surface by throwing out volume elements and (optionally) the relative points
Args:
mesh: Volumetric mesh.
cleanoutput (bool): Remove unused points.
Returns:
vtkPolyData object.
"""
extractor = vmtkscripts.v... | 78b311d8523b495b36be5f64767389bf3c71a13a | 3,634,830 |
def time_delta_calc(contiguous_trajectory,order = 2):
"""Computes the time derivatives of a contiguous trajectory.
INPUT
contiguous_trajectory An array of space-time cordinates
order The order up to which the time derivatives are calculated. If
order=1, the velo... | 17352f37f69e9947c0cea8e9fd7cf54ea3ff6e2e | 3,634,831 |
def tasks_page():
""" Tasks and completions page
"""
return flask.render_template(
'tasks.html',
config=g.project.config,
project=g.project,
version=label_studio.__version__,
**find_editor_files()
) | 56656a8571e33fb40f3790a207faa2fccc7315a0 | 3,634,832 |
def outformathtml(pandasdf):
"""
change a few formating things to prettify and make it match
"""
pandas_table = pandasdf.to_html()
pandas_table = pandas_table.replace(""" border="1" """, " ")
pandas_table = pandas_table.replace("""<tr style="text-align: right;">\n <th></th>\n <th></th>... | 5f8abf88a2aead4f095f52c1f49ab4ad609c04a5 | 3,634,833 |
def list_catalogs(**kwargs):
"""
Return the available Cone Search catalogs as a list of strings.
These can be used for the ``catalog_db`` argument to
:func:`conesearch`.
Parameters
----------
cache : bool
Use caching for VO Service database. Access to actual VO
websites refe... | b539746edb4b6aa256bcbac3153b9a323bb41882 | 3,634,834 |
def rot_decode(data: str, n: int = 13) -> str:
"""Decode a ROT-encoded string that was shifted by `n` places."""
if not 1 <= n < 26:
raise ValueError('n must be in range [1, 26)')
return rot_encode(data, 26 - n) | f001f15684cc77e8ea52cf481626c6bdaf97c071 | 3,634,835 |
from datetime import datetime
def searchlight(x, y, m=None, groups=None, cv=None,
write=False, logger=None, permutations=0, random_state=42, **searchlight_args):
"""
Wrapper to launch searchlight
:param x: Data
:param y: labels
:param m: mask
:param groups: group labels
:pa... | 799f2496c0609050e6914576cfbdaba972320723 | 3,634,836 |
def codegen_reload_data():
"""Parameters to codegen used to generate the fn_ioc_parser_v2 package"""
reload_params = {"package": u"fn_ioc_parser_v2",
"incident_fields": [],
"action_fields": [],
"function_params": [u"ioc_parser_v2_artifact_id", u"ioc_... | 9c279e24b2e05adc5b1573393368216483307071 | 3,634,837 |
def Pattern2(s):
""" Compute the correlator for this pattern:
↓
↓ ↑ ↑
and symmetry-equivalent patterns
"""
res = 0.0
s = np.pad(s, ((0, 0), (2, 2), (2, 2)))
L = s.shape[-1]
for i in range(L-2):
for j in range(L-2):
res += s[1, i, j] * s[0, i+1,... | 390cf6b8262f00d396235fb8ef5d4acc72d1df9e | 3,634,838 |
import math
def gauss(x, x0, sigma):
"""
This function returns a Gaussian distribution.
"""
return (1/(sigma*math.sqrt(2 * math.pi))) * np.exp(-(x - x0)**2 / (2 * sigma**2)) | c4ebd141e68e59567b21355fb3b813c7f4ff914b | 3,634,839 |
import math
def distance():
"""
Calculate the distance between two points.
return:
Distance.
"""
return lambda a, b: math.sqrt((a.x-b.x)*(a.x-b.x)+(a.y-b.y)*+(a.y-b.y)+(a.z-b.z)*(a.z-b.z)) | ab3a14e7033afab66db7c283aefda745158bad65 | 3,634,840 |
import numpy
def rational_sum(numerator, denominator, *argv):
"""Sum of rational numbers."""
if len(argv) < 2:
gcd = numpy.gcd(numerator, denominator)
num_out, den_out = numerator//gcd, denominator//gcd
else:
num_2 = argv[0]
den_2 = argv[1]
num_3 = numerator*den_2 +... | b34d01ea2bcfd072430501828401d5b492b2bae5 | 3,634,841 |
import time
def nonce() -> str:
"""Return a nounce counter (monotonic clock).
References:
* https://support.kraken.com/hc/en-us/articles/360000906023-What-is-a-nonce-
""" # pylint: disable=line-too-long
return str(time.monotonic_ns()) | fb6221fef4c2c8af66200c4c9da8f6253854b186 | 3,634,842 |
def fetch_single_equity(stock_code, start, end):
"""
从本地数据库读取股票期间日线交易数据
注
--
1. 除OHLCV外，还包括涨跌幅、成交额、换手率、流通市值、总市值、流通股本、总股本
2. 添加后复权价格，使用复权价在图中去除间隙断层
3. 使用bcolz格式写入时，由于涨跌幅存在负数，必须剔除该列
Parameters
----------
stock_code : str
要获取数据的股票代码
start_date : datetime-like
自... | 04e63665fe9b05dfcca8387519d2a178d117acb5 | 3,634,843 |
import os
import re
def generate():
"""Generates a dictionary of all the known CRC formats from:
https://reveng.sourceforge.io/crc-catalogue/all.htm
See pwnlib/data/crcsum.txt for more information.
"""
curdir, _ = os.path.split(__file__)
path = os.path.join(curdir, '..', '..', 'data', 'crcsu... | bac4d66babe3e01c703fb6f10d78b85021c62f3b | 3,634,844 |
import string
def base62_encode(number):
"""Encode a number in base62 (all digits + a-z + A-Z)."""
base62chars = string.digits + string.ascii_letters
l = []
while number > 0:
remainder = number % 62
number = number // 62
l.insert(0, base62chars[remainder])
return ''.join(l)... | b1f10fe69b6263d54f2e00a32b8260cbb3c42747 | 3,634,845 |
import json
def handle_update(config_path):
"""
handle changes in globalConfig.json
Args:
config_path : path to globalConfig.json
Returns:
dictionary : schema_content (globalConfig.json)
"""
with open(config_path) as config_file:
schema_content = json.load(config_file... | f51f52f9353339ba1cf080b10ad8f28691deefe9 | 3,634,846 |
from typing import Sequence
from typing import Tuple
import urllib
def encode(s: Sequence[Tuple[str, str]], similar_to: str=None) -> str:
"""
Takes a list of (key, value) tuples and returns a urlencoded string.
If similar_to is passed, the output is formatted similar to the provided urlencoded str... | c0153b77ec03708d54574062d15c7f81df59510b | 3,634,847 |
def gis_ellipse_polygon(origin, a, b, orientation=0.0, complexity=128):
"""
Generate a polygon of an ellipse suitable for GIS applications.
:param origin: the center of the ellipse (expected to be UTM, m)
:param a: the a/semi-major axis length (expected to be UTM, m)
:param b: the b/semi-minor axis... | 48df0adbc7fd04508a6d3a8288c6b46fe9f9bdb0 | 3,634,848 |
def activate_lesson():
"""
{
"id": 51,
"active": "A"
}
"""
domain = request.get_json()
return lesson_service.activate_lesson(domain) | a4e48ca2c8e65e9ff0e2fb95b61ef776573a9649 | 3,634,849 |
def split(labels, n_per_class=20, seed=0):
"""
Randomly split the training data.
Parameters
----------
labels: array-like [n_nodes]
The class labels
n_per_class : int
Number of samples per class
seed: int
Seed
Returns
-------
split_train: array-like [n_p... | 69c7510f9be494afe7bb0c1492870c1d7c2d6694 | 3,634,850 |
from setfilter.setfilter import Setfilter
def base():
"""test Setfilter """
# build fixture
# initialization
center = np.array([0, 0, 0, 0.])
body = np.array([[1., 0., 0., 0.],
[0., 1., 0., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]])
... | b306d6425a6e1e329e0af006585c06be4585972e | 3,634,851 |
def stack(*cons):
"""
Combine constraints into a large constaint
by intersection.
Parameters
----------
cons : [`selection.affine.constraints`_]
A sequence of constraints.
Returns
-------
intersection : `selection.quasi_affine.constraints`_
Notes
-----
Res... | 8ddc52aa41c2ef4ec784067692efa1f3643a130c | 3,634,852 |
def _create_poi_gdf(
tags,
polygon=None,
north=None,
south=None,
east=None,
west=None,
timeout=180,
memory=None,
custom_settings=None,
):
"""
Create GeoDataFrame from POIs json returned by Overpass API.
Parameters
----------
tags : dict
Dict of tags used ... | 4d88c0bb60ee836131bf5197c0caad17c0358f5b | 3,634,853 |
def prepare_data(seqs, labels, maxlen=None, x_dim = 3, mapping=None, max_mapping=None):
"""Create the matrices from the datasets.
This pad each sequence to the same length: the length of the
longest sequence or maxlen.
if maxlen is set, we will cut all sequence to this maximum
length.
This sw... | e2582ce07fa770b78bcd02dae26b345059c051c0 | 3,634,854 |
import types
def _get_prediction_tensor(
predictions_dict):
"""Returns prediction Tensor for a specific Estimators.
Returns the prediction Tensor for some regression Estimators.
Args:
predictions_dict: Predictions dictionary.
Returns:
Predictions tensor, or None if none of the expected keys are... | 0bd509d4021e0f0622b0cf685e5bf8682f47daa0 | 3,634,855 |
def gen_confirm_code():
""" Generate a new email confirmation code and return it
"""
return generate_uuid_readable(9) | 992844a42886892cfa7eebc44e8efb61aa547725 | 3,634,856 |
from typing import List
from typing import Dict
from typing import cast
import json
from datetime import datetime
def make_event_crawl_jobs(entries: List[BugoutSearchResult]) -> List[EventCrawlJob]:
"""
Create EventCrawlJob objects from bugout entries.
"""
crawl_job_by_hash: Dict[str, EventCrawlJob] ... | 3aba2871df1cf35bb6337cbe8d8482437c3c91e0 | 3,634,857 |
def update_profile():
"""
Update profile page
"""
form = UpdateProfileForm() # Update profile form
if form.validate_on_submit(): # If form is submitted and validated
if form.picture.data: # If picture is uploaded
picture = save_picture(form.picture.data) # Save picture
... | ad2b427487cc63aa64068b86254c2d5b6b363c2c | 3,634,858 |
def get_version_info(pe):
"""Return version information"""
res = {}
for fileinfo in pe.FileInfo:
if fileinfo.Key == 'StringFileInfo':
for st in fileinfo.StringTable:
for entry in st.entries.items():
res[entry[0]] = entry[1]
if fileinfo.Key == '... | 8a01062de92cd4887f5cc7a292ffb644a701b43c | 3,634,859 |
import torch
def data_prepare(coord, feat, label, split='train', voxel_size=0.04, voxel_max=None, transform=None, shuffle_index=False, origin='min'):
""" coord, feat, label - an entire cloud
"""
if transform:
coord, feat, label = transform(coord, feat, label)
if voxel_size:
# voxelize ... | 988a7068d0fc383f86c853b0593189633a87a53d | 3,634,860 |
def add_wsl_blobs(blobs, im_scales, im_crops, roidb):
"""Add blobs needed for training Fast R-CNN style models."""
# Sample training RoIs from each image and append them to the blob lists
for im_i, entry in enumerate(roidb):
frcn_blobs = _sample_rois(entry, im_scales[im_i], im_crops[im_i], im_i)
... | 296ae92af7656be15963508e1562afc5e62fb05b | 3,634,861 |
def _right_branching(nodes):
"""
Parameters
----------
nodes: list[T], where T denotes NonTerminal or Terminal
Returns
-------
list[T], where T denotes NonTerminal or Terminal
"""
if len(nodes) == 2:
return nodes
lhs = nodes[0] # The left-most child node is head
ind... | 9bfa47daa95be30b7f9a9ada882e1fdceb1295e5 | 3,634,862 |
import random
def random_swap(o_a, o_b):
"""
Randomly swap elements of two observation vectors and return new vectors.
:param o_a: observation vector a
:param o_b: observation vector b
:return: shuffled vectors
"""
X, Y = [], []
tf = [True, False]
for x, y in zip(o_a, o_b):
... | f243e91e5b281c682601fdb8df49bd7e6209274c | 3,634,863 |
def parse_multiplicative(index):
"""Parse multiplicative expression."""
return parse_series(
index, parse_unary,
{token_kinds.star: expr_nodes.Mult,
token_kinds.slash: expr_nodes.Div,
token_kinds.mod: expr_nodes.Mod}) | e314ca44735db31d00fe55268be8a7f69816db45 | 3,634,864 |
def return_factorized_dict(ls):
"""
###### Factorize any list of values in a data frame using this neat function
if your data has any NaN's it automatically marks it as -1 and returns that for NaN's
Returns a dictionary mapping previous values with new values.
"""
factos = pd.unique(pd.factoriz... | 7804f12f953eabcdc7bb398121500c2c8f2e278f | 3,634,865 |
def _strip_asserts(source):
"""
Remove assert method calls from source code.
Using RedBaron, replace some assert calls with print statements that print the actual
value given in the asserts. Depending on the calls, the actual value can be the first or second
argument.
Parameters
----------... | 4c484635328e9610bd07004cfba63acc4ae039d1 | 3,634,866 |
def _index_clusters(feat_mat, init_mat):
"""Creates a hierarchical binary tree till the top-level clusters supplied."""
cluster_feat = init_mat.T.dot(feat_mat)
cluster_feat = cluster_feat.tocsr()
cluster_feat = skprep.normalize(cluster_feat, "l2", axis=1)
init_cluster = HierarchicalKMeans.gen(
... | f48e32507e298c4b089c9358c14727c4b8444ee5 | 3,634,867 |
from functools import reduce
def gcd(numbers):
"""Return greatest common divisor of integer numbers.
Using Euclid's algorithm.
Examples
--------
>>> gcd([4])
4
>>> gcd([3, 6])
3
>>> gcd([6, 7])
1
"""
def _gcd(a, b):
"""Return greatest common divisor of two i... | da7ae2a24649bc05e233533735baf850a37dcc5a | 3,634,868 |
def normal_attention(tensor_base, tensor_to_attend,
mask_for_tensor_base,
mask_for_tensor_to_attend,
similarity_method='inner', hn=100,
use_pooling=False, pooling_method='max',
reverse=False, scope=None):
"""
... | 93df4d084bb76cba4ab227928de6eb72e7f5af76 | 3,634,869 |
from bs4 import BeautifulSoup
def getPageNum(html):
"""解析第一页网页，返回该用户的书评页数
"""
soup=BeautifulSoup(html,'html.parser')
paginator=soup.find('div','paginator')
pas=paginator.findAll('a')
num=int(pas[-2].text)
return num | 626a6f580e5634ba741d0794f6fc4c020aecabd0 | 3,634,870 |
async def get_user(api_management_name=None,resource_group_name=None,user_id=None,opts=None):
"""
Use this data source to access information about an existing API Management User.
> This content is derived from https://github.com/terraform-providers/terraform-provider-azurerm/blob/master/website/docs/d/api... | c5bdf6aa7d0c69a59b9b8f6a93f63a9cba9a00cd | 3,634,871 |
def makeCC_allpair(spikes, Begin, End, N_thred):
"""
全てのCCをBegin~Endの間で計算する
args:
spikes: list型
Begin, End: int型
N_thred: 並列計算をするときに与えるスレッド数
return:
X: ペアごとに計算したCC. X.shape = (ニューロンのペア数、CCの幅)
index: ペアのニューロンの番号. index.shape = (ニューロンのペア数、2). index[i][0]は結合先ニューロン、in... | e9e5b9bd805251b4244ab89e6a1e11316617101d | 3,634,872 |
def move_position(facility, cur_position, direction):
"""Move position from cur_position in the direction on facility."""
changes = DIRECTIONS[direction]
doors = DIRECTION_TO_DOOR[direction]
for cell in (doors, ROOM):
next_position = []
for coordinate, change in zip(cur_position, changes... | 64601f07378da56eaa03d896987491cd6f93182b | 3,634,873 |
from typing import Callable
import itertools
from typing import OrderedDict
import pprint
def search_for_improvements(
targets : [Exp],
wf_solver : ModelCachingSolver,
context : Context,
examples : [{str:object}],
cost_model : CostModel,
stop_cal... | 374a5a16f6ec4e69e983613aedbb298df1411cca | 3,634,874 |
def down_sample(fft_vec, freq_ratio):
"""
Downsamples the provided data vector
Parameters
----------
fft_vec : 1D complex numpy array
Waveform that is already FFT shifted
freq_ratio : float
new sampling rate / old sampling rate (less than 1)
Returns
-------
... | 1ddfaa075c1d8bc68f9348d4f49807b61eceb60c | 3,634,875 |
import os
import json
def main(args=None):
"""This is the Main Method.
"""
# loads setting file set parameters
settings = os.path.join(get_package_share_directory('ros2_camera_publish'),
"settings.json")
with open(settings) as fp:
content = json.l... | 96e34fc4e4283fbe5f33050cf97969a6f1bba446 | 3,634,876 |
import torch
def set_device(cuda: bool) -> int:
"""Set the device for computation.
Args:
cuda (bool): Determine whether to use GPU or not (if available).
Returns:
int: Index of a currently selected device, CPU or GPU.
"""
device = torch.device("cuda" if (torch.cuda.is_available() a... | f65fc5e38f14b8de78d14ac150ac14e5c8788e26 | 3,634,877 |
import torch
def hsic_regular(x, y, sigma=None, use_cuda=True, to_numpy=False):
"""
"""
Kxc = kernelmat(x, sigma)
Kyc = kernelmat(y, sigma)
KtK = torch.mul(Kxc, Kyc.t())
Pxy = torch.mean(KtK)
return Pxy | 551ed76c2f902b662ffe2c693da4474b6eb3958e | 3,634,878 |
def random_correlation(size, n_factors, random_seed=None):
"""
Generates a random correlation matrix with 'size' lines and columns and
'n_factors' factors in the underlying structure of correlation.
:param size: int. Size of the correlation matrix
:param n_factors: int. number of factors in the corr... | 92cd98bdf95e0ffef51c016c1c9ef05391c483dd | 3,634,879 |
import urllib
import requests
def http_get_request(url, params, add_to_headers=None, _async=False):
"""
from 火币demo, get方法
:param url:
:param params:
:param add_to_headers:
:return:
"""
headers = {
'Content-type':
'application/x-www-form-urlencoded',
'User-Agent... | b9274adeae67f9509fa5926d404866716b0d775e | 3,634,880 |
def eigendecompose(S):
"""Eigendecompose the input matrix."""
eigvals, V = np.linalg.eig(S)
return eigvals, V | 0658d3b83d54a7435862b89d0a1fa3e82f4082fd | 3,634,881 |
def _CreateSampleDirectoryCoverageData(builder='linux-code-coverage',
modifier_id=0):
"""Returns a sample directory SummaryCoverageData for testing purpose.
Note: only use this method if the exact values don't matter.
"""
return SummaryCoverageData.Create(
server_ho... | 3edebb67f0b4dafa837c14b99fd0b2b241da784d | 3,634,882 |
def sched_time(update_time) -> int:
""" Return interval between the current time and the update time in
seconds
"""
current_time_ss = hhmm_to_seconds(current_time_hhmm())
update = hhmm_to_seconds(update_time)
interval = update-current_time_ss
return interval | 5a57f591550a9f72dc7e9aa87a75c7aacf624cbe | 3,634,883 |
def http_jsonrpc_post(hostname, port, uri, method, params):
"""Perform a plain HTTP JSON RPC post (for task farming)"""
url = "http://%s:%s%s" % (hostname, port, uri)
data = simplejson.dumps({ 'method': method, 'params': params,
'jsonrpc': '2.0', 'id': 1 })
req = urllib2.Request(url, data, {'... | 8ac5e836564c4ddc2a277c4aea8bf0ff6b8836c2 | 3,634,884 |
def get_user_event(current_user, event_id):
"""
Query the user to find and return the event specified by the event Id
:param event_id: Event Id
:param current_user: User
:return:
"""
user_event = User.get_by_id(current_user.id).events.filter_by(event_id=event_id).first()
return user_even... | d65e3a65cb4400a9b4173b8ea4d45f6f94e0993c | 3,634,885 |
def get_distances(scr_data_dict, distance_keys, data_centroid=None):
"""
@param scr_data_dict:
@param distance_keys:
@param data_centroid: Do not provide if calculating distances for establishing s thresholding
@return:
"""
dataset_keys = scr_data_dict.keys()
# Extracting dataset point o... | c0aec2de89bd7c7150d3f5fcbc3161f9f2d441c0 | 3,634,886 |
def compare_numeric_abundances(values_in_taxa_list_1, values_in_taxa_list_2):
"""Retun a Pandas Series with [abundance-in, abundance-out, p-value]."""
mean1 = mean_ignore_nans(values_in_taxa_list_1)
mean2 = mean_ignore_nans(values_in_taxa_list_2)
keyslist1 = list(values_in_taxa_list_1.keys())
keysli... | f2e6e4326b12242a8493b82e37190a47d60b44e6 | 3,634,887 |
def parse_folder(folder, start_time=None, grepcmd=None, tmp_folder=None, force_grep=False):
"""
Args:
grepcmd, tmp_folder, force_grep's default value should be the same with parse_single_log_with_pregrep
Yields:
[[yield], []]: nested yields
"""
def get_first_last_line(filepath):
... | b8d233ba8ad579d38e3353b841ea03d52bb83962 | 3,634,888 |
def search(request):
"""
search function which reads get data from a requests and uses it to find stuff in elasticsearch
"""
context = {"table": []}
if "subject" in request.GET or "predicate" in request.GET or "object" in request.GET:
es = elasticsearch.Elasticsearch(settings.ELASTICSEARCH)
... | 85b1daba7d6a815f3e465b23ef369d439834de9c | 3,634,889 |
import os
def Write_data(data_name,parameters,metrics_name_list,length_input,metrics_mean_list,metrics_std_dev_list):
"""Writes the metrics of a given simulation in a datasheet in .txt format.
Parameters
----------
data_name: string
Desired name of data_sheet archive.
metrics... | 83478d88f45203b22373dfb42ae0e4a1338b2355 | 3,634,890 |
from typing import Dict
def parse_measurement_lines(xml_root: Element) -> Dict[int, LineString]:
"""Parses the measurement line from the given xml root
Args:
xml_root (ET.ElementTree): root of the xml file
Returns:
measurement lines to use in the analysis (id, line)
"""
measureme... | 8e7ff2a75189e8f6c1960f6849c1b63bc1ff4821 | 3,634,891 |
from typing import Any
from typing import Optional
def compute_and_apply_approximate_vocabulary(
x: common_types.ConsistentTensorType,
default_value: Any = -1,
top_k: Optional[int] = None,
num_oov_buckets: int = 0,
vocab_filename: Optional[str] = None,
weights: Optional[tf.Tensor] = None,
... | 9662796984852ff255ca923e1048121427debfe6 | 3,634,892 |
import io
def album_cover():
"""Get the current song's album cover."""
cover = app.config["player"].album_cover()
image = io.BytesIO(cover) if cover else "static/no_cover.jpg"
return send_file(image, mimetype="image/jpeg") | 3c2c7b9513bd36e49f27d4b58ca1408932402d72 | 3,634,893 |
def verify_bgp_community(
tgen,
addr_type,
router,
network,
input_dict=None,
vrf=None,
bestpath=False,
expected=True,
):
"""
API to veiryf BGP large community is attached in route for any given
DUT by running "show bgp ipv4/6 {route address} json" command.
Parameters
... | 12190c76f9d2bae40c8c2859de9813d3c8af38a4 | 3,634,894 |
def create_new_filename(original_filename: str,
user_response: str):
"""
Creates new file name depending on the users response
:param original_filename: str
:param user_response: str
:return: str | new filename
"""
if user_response == "1":
time = str(today.time())[:8].repla... | 789bf9f73b4647c534859a2ae97b9ec806b02d1c | 3,634,895 |
from typing import Optional
import os
from pathlib import Path
import shutil
def get_maestral_command_path() -> str:
"""
Returns the path to the maestral executable. May be an empty string if the
executable cannot be found.
"""
try:
dist_files = files("maestral")
except PackageNotFoun... | 6291cc4da5771d60d3fdfbe3abceb4c76733fef6 | 3,634,896 |
from typing import OrderedDict
def genertate_info_tree(traces, trace_events, level="module"):
"""
"""
assert level in ["module", "operator", "mixed"]
tree = OrderedDict()
for trace in traces:
path, module = trace
# unwrap all of the events, in case model is called multiple times
... | cc885b41df2d2ecf0484c55a07f9b8ef381263d8 | 3,634,897 |
def interpolate(x, ratio):
"""Interpolate data in time domain. This is used to compensate the
resolution reduction in downsampling of a CNN.
Args:
x: (batch_size, time_steps, classes_num)
ratio: int, ratio to interpolate
Returns:
upsampled: (batch_size, time_steps * ratio, classes_num... | 54ceb6aee15de3c775d3be93bbc48422dc542641 | 3,634,898 |
from astroquery.mast import MastClass
def _resolve_object(target):
"""Ask MAST to resolve an object string to a set of coordinates."""
# Note: `_resolve_object` was renamed `resolve_object` in astroquery 0.3.10 (2019)
return MastClass().resolve_object(target) | bf9c0bb3a09fac1622cc107cf3f9532888b3a4f9 | 3,634,899 |
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