content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def show_cmaps(*args, **kwargs):
"""
Generate a table of the registered colormaps or the input colormaps
categorized by source. Adapted from `this example \
<http://matplotlib.org/stable/gallery/color/colormap_reference.html>`__.
Parameters
----------
*args : colormap-spec, optional
Col... | c5b8fa3fa3cbb131250be5b813e10c4ff45e0752 | 50,000 |
import logging
def Run(benchmark_spec):
"""Measure the boot time for all VMs.
Args:
benchmark_spec: The benchmark specification. Contains all data that is
required to run the benchmark.
Returns:
A list of sample.Sample objects with individual machine boot times.
"""
vm = benchmark_spec.vms... | 97176dc9e27d9f1f756769bef3966efa5c4e627c | 50,001 |
import os
def inputs(n_devices, dataset_name, data_dir=None, input_name=None,
n_chunks=0, append_targets=False):
"""Make Inputs for built-in datasets.
Args:
n_devices: how many devices to build the inputs for.
dataset_name: a TFDS or T2T dataset name. If it's a T2T dataset name, prefix
w... | ab06140ec4a735c0e932a0d90d338a9d7242a1fe | 50,002 |
def ansi_render_approx(s, width = 80, height = 2000):
"""
Does an approximated render of how a string would look on a vt100
terminal
The string can contain ANSI escape sequences, which the
:module:`pyte` engine can render so a string such as
>>> s = '\x1b[23;08Hi\x1b[23;09H\x1b[23;09Hf\x1b[23;... | c6db54b85780137e75dcc04e43c04ef1f4abe873 | 50,003 |
def ycbcr2rgb(ycbcr, *, channel_axis=-1):
"""YCbCr to RGB color space conversion.
Parameters
----------
ycbcr : (..., 3, ...) array_like
The image in YCbCr format. By default, the final dimension denotes
channels.
channel_axis : int, optional
This parameter indicates which a... | d5a27283f257c76c683426f5bb307c300756a464 | 50,004 |
import requests
def confirm_licenses_package(access_token, resource_server, pickup_number):
# type: (str, str, str) -> int
"""
Sends the confirmation to the server that the license package was retrieved.
Returns the response code in case of success.
"""
response = requests.post(
resour... | 575e524efebcf4e89141362102488b087ca48fbf | 50,005 |
def loss(logits, labels):
"""Calculates the loss from the logits and the labels.
Args:
logits: Logits tensor, float - [batch_size, NUM_CLASSES].
labels: Labels tensor, int32 - [batch_size].
Returns:
loss: Loss tensor of type float.
"""
# Convert from sparse integer labels in the range [0, NUM_CL... | 5e034179193ebb7343264a837f3dd3aeee151729 | 50,006 |
import os
def import_data(directory, only_main_ipc):
"""Imports preprocessed patent files with patent text and ipcs from txt files in given hierarchical directory.
Parameters
----------
directory : string
Path of hierarchical directory with preprocessed patent txt files
Returns
-------
result_df : pandas... | 5876193a9102bc14d569cf160423aba652af2306 | 50,007 |
def get_douban_url(detail_soup):
"""-"""
detail_soup = detail_soup.find('a', title='豆瓣链接')
if detail_soup:
return detail_soup['href']
return '' | 3f4cb56876da722883e3386d7af7ce41726456ac | 50,008 |
import os
import io
def generate_gitlab_yaml_for_noop(rust_workspace: str) -> str:
"""Return a string with the Gitlab YAML pipeline config for no-op builds."""
rust_workspace = os.path.abspath(rust_workspace)
gitlab_ci_config = load_gitlab_ci_config(rust_workspace)
out = io.StringIO()
generate_g... | df490acc8b8fcf5a7e00086bfb70c987aa96b645 | 50,009 |
import os
def all_recording_days(path, day_format):
"""
Iterates through the provided directory path and returns an array of all
day directories that match the provided format.
"""
dirpath, dirnames, filenames = next(os.walk(path))
return __dirnames_matching_format(dirnames, day_format) | 08df38387205257ed79654188f3b52726fb4f0a3 | 50,010 |
def truncate_out_cert_raw(origin_raw_str: str):
"""truncate the original ssl certificate raw str like:\n
-----BEGIN CERTIFICATE-----
raw_str_data...
-----END CERTIFICATE-----\n
and split out the raw_str_data"""
if not isinstance(origin_raw_str, str) or origin_raw_str == "":
raise Excepti... | 0513a927ab74ac8d6df4e379319eb3516c2f0c14 | 50,011 |
from datetime import datetime
def addNewUser(db: Connection, userID: int) -> bool:
"""
Add new user to database
:param db: database object instance
:param userID: User ID
:return: Boolean True if no error
"""
if db is None:
return False
now: datetime = datetime.utcnow()
cur... | 13ac827c703a30a96d416850b5380c2e89592a96 | 50,012 |
def dv_dlogdp(dp, n, gm, gsd):
"""The volume weighted PDF of a lognormal distribution as calculated
using equation 8.20 from Seinfeld and Pandis.
.. math::
n_V^o(log D_p)=log(10)*D_p n_V(D_p)
Parameters
----------
dp : float or array of floats
Particle diameter in microns.
... | 88617ab744e86ef8a6d2b3b589c8620e87b80e61 | 50,013 |
def cmp_char(a, b):
"""Returns '<', '=', '>' depending on whether a < b, a = b, or a > b
Examples
--------
>>> from misc_utils import cmp_char
>>> cmp_char(1, 2)
'<'
>>> print('%d %s %d' % (1, cmp_char(1,2), 2))
1 < 2
Parameters
----------
a
Value to be compare... | 7e8183564f888df3cce65f2bbbeb659aec43928c | 50,014 |
def retrieve_context_topology_node_owned_node_edge_point_available_capacity_bandwidth_profile_committed_burst_size_committed_burst_size(uuid, node_uuid, owned_node_edge_point_uuid): # noqa: E501
"""Retrieve committed-burst-size
Retrieve operation of resource: committed-burst-size # noqa: E501
:param uuid... | f299772ba3cab3ca0d508971d45d1ba0a5272b6e | 50,015 |
def get_command_name(cmd, default=''):
"""Extracts command name."""
# Check if command object exists.
# Return the expected name property or replace with default.
if cmd:
return cmd.name
return default | f77a73d1ff24ec74b1c7cf10f89c45fab41fed20 | 50,016 |
import os
def ref_ad_factory(path_to_refs):
"""
Read the reference file.
Parameters
----------
path_to_refs : pytest.fixture
Fixture containing the root path to the reference files.
Returns
-------
function : function that loads the reference file.
"""
def _reference... | 451cc1603fa2390ff4e8487e20604629356d3d1a | 50,017 |
def _getText(node):
"""
Obtains the text from the node provided.
@param node Node to obtain the text from.
@retval Text from the node provided.
"""
return " ".join(child.data.strip() for child in node.childNodes
if child.nodeType == child.TEXT_NODE) | ebd23a28073104e81cd7a1d38323ac2a1c49355b | 50,018 |
from typing import Union
import sqlite3
def make_connection_plus_from(conn: Union[sqlite3.Connection, ConnectionPlus]
) -> ConnectionPlus:
"""
Makes a ConnectionPlus connection object out of a given argument.
If the given connection is already a ConnectionPlus, then it is re... | b66ce558d9515d57ecfee066900a5b3150d90c81 | 50,019 |
from ._fine_cal import read_fine_calibration
def _update_sensor_geometry(info, fine_cal, ignore_ref):
"""Replace sensor geometry information and reorder cal_chs."""
logger.info(' Using fine calibration %s' % op.basename(fine_cal))
fine_cal = read_fine_calibration(fine_cal) # filename -> dict
ch_na... | 7b22f9b42adff0f73a2a8b5fa71a9edbcf260eb2 | 50,020 |
def polygonOffsetWithMinimumDistanceToPoint(point, polygon, perpendicular=False):
"""Return the offset from the polygon start where the distance to the point is minimal"""
return polygonOffsetAndDistanceToPoint(point, polygon, perpendicular)[0] | b84ca6bf40563c5663490d3c28806ee3b3226500 | 50,021 |
def get_package_versions(sha1, os_type, package_versions=None):
"""
Will retrieve the package versions for the given sha1 and os_type
from gitbuilder.
Optionally, a package_versions dict can be provided
from previous calls to this function to avoid calling gitbuilder for
information we've alrea... | 24cdcf0641fd0a0bd16c39e7a79c0d2c69f6692f | 50,022 |
from typing import List
import os
def get_configs_from_model_files(state: 'State', model_root = None, ignore_files: list = None) -> List[dict]:
"""
Assumes that all configs are defined within the model files:
models/m_{name}.py
and that each model file has a get_config() option which returns an a... | 98d3026fe88b0f13c067071da948f36dbdebfb66 | 50,023 |
def get_arrdepth(arr):
"""
USAGE
-----
arr_depths = get_arrdepth(arr)
Determine number of nested levels in each
element of an array of arrays of arrays...
(or other array-like objects).
"""
arr = np.array(arr) # Make sure first level is an array.
all_nlevs = []
for i in ran... | 4d06fdf10f6b3bfb590da86c6627b546db29dbea | 50,024 |
def get_ocid(prefix, tenderID):
"""greates unique contracting identifier"""
return "{}-{}".format(prefix, tenderID) | 309e8a07dcdf787fd2dd6a41abb4f4d26f1baa63 | 50,025 |
import hashlib
def md5(fileName):
"""Compute md5 hash of the specified file"""
m = hashlib.md5()
try:
fd = open(fileName,"rb")
except IOError:
print("Reading file has problem:", filename)
return
x = fd.read()
fd.close()
m.update(x)
return m.hexdigest() | a502ada56c934e7b66155b261a23a283e9b65bf7 | 50,026 |
def Kernel(x,f,theta):
"""
build square kernel matrix for inputs x with kernel function f and
parameters theta
Inputs
-------
x : vector
values to evaluate the kenrel function at, pairwise
f: kernel function
function that accepts inputs as (x1,x2,theta)
theta: vector
... | e0bb80f2c90e72bdbf2405f4d96dfaa0f6d3f03c | 50,027 |
from typing import Union
def drop_duplicated_indices(df: Union[pd.Series, pd.DataFrame]) -> Union[pd.Series, pd.DataFrame]:
"""If one concatenates dataframes there might be duplicated
indices. This can lead to problems, e.g., in interpolation steps.
One easy solution can be to just drop the duplicated row... | 5f14965e5cbb7fa859db74588b5880d1b24e8bf3 | 50,028 |
import json
def report_response(params, runner=None, cache=DEFAULT_CACHE):
"""
This frontend helper function is meant to be used in your
request-processing code to handle all AJAX responses to the Blingalytics
JavaScript frontend.
In its most basic usage, you just pass in the request's GET parame... | 7568ff0e80afcea319ceace1c9f10f807903ce3e | 50,029 |
def median( y, mask):
"""Return the median of the array y, ignoring masked elements.
Parameters
-----------
y : ndarray
array of values
mask : ndarray
array of (int32) ones or zeros (0 indicates a good value)
Returns
--------
med... | e5ff3c249f7246caa94b61aa3586c1e79b01f8fa | 50,030 |
import torch
import copy
def train_model(x_train, y_train_e, x_val, y_val_e, num_epochs, learning_rate):
"""
Train the model using the data given, along with the parameters given.
@param x_train is the training dataset.
@param y_train_e is an np.array of the training labels.
@param x_va... | 96c8675816178362100082d5911b977ae192d14e | 50,031 |
def polynomial(a0,a1,a2,a3,a4,x):
"""
Up to x4
"""
return a0 + x*(a1+x*(a2+x*(a3+x*a4))) | 81ad200df9b6e9d7cd00e1ced8bae8dacec303b1 | 50,032 |
def time_round(time, delta, epoch=None):
"""From https://stackoverflow.com/a/57877961/13775459"""
mod = time_mod(time, delta, epoch)
if mod < (delta / 2):
return time - mod
return time + (delta - mod) | a6d6a7e8beb60013c01d0512f5dc0ccf7c2fa0b2 | 50,033 |
def resnet(info, depth=28, width=1):
"""Resnets of varying width and depth."""
N = (depth - 4) // 6
inputs = Input(shape=info.features['image'].shape)
x = Conv2D(16, (3, 3), padding='same')(inputs)
x = BatchNormalization()(x)
x = Activation('relu')(x)
for _ in range(N):
x = _residu... | 7d8e0fc707549d39010db3f9cad2e92496b52d2e | 50,034 |
import hashlib
def get_str_md5(content):
"""
Calculate the MD5 for the str file
:param content:
:return:
"""
m = hashlib.md5(content) # 创建md5对象
return m.hexdigest() | c0e864288d8d6af2fe31b5cb5afe54bfe83e2fb3 | 50,035 |
def cv_personal_info(request):
"""Add information about person to CV requests"""
return {'cv_personal_info': CV_PERSONAL_INFO} | 8f7aa458747dcffc20247926b01ac36f536e6bd9 | 50,036 |
def make_test(row):
"""
Generate a test method
"""
def row_test(self):
actual = row.get("_actual")
if actual in ("P", "F"):
if actual == "P":
self.assertMeansTest("eligible", row)
else:
self.assertMeansTest("ineligible", row)
... | 083117f44687c56a7a33cfa74776baea6b40048c | 50,037 |
def replace_german_umlaute(unicode_string):
"""."""
utf8_string = unicode_string.encode("utf-8")
print("xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
print("{}".format(utf8_string))
print(u"{}".format(utf8_string))
print("xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
for k in umlaute_dict.keys():
utf8_string ... | f1d88056b3166443a6cc4989d3b4f4106573cd65 | 50,038 |
import os
import uuid
import json
def audio_conversion():
"""Convert audio file to MP3 and update metadata on mp3.
:return: Converted audio
"""
# For whatever reason temporary file was workable with subprocess.
tmp_path = os.path.join("/tmp", "audio_" + uuid.uuid4().hex + ".mp3")
try:
... | 634706fef38f13ccf4d66e75ea5b954ac004f70f | 50,039 |
import posixpath
def populate(contents_mgr):
"""
Populate a test directory with a ContentsManager.
"""
dirs_nbs = [
('', 'inroot.ipynb'),
('Directory with spaces in', 'inspace.ipynb'),
('unicodé', 'innonascii.ipynb'),
('foo', 'a.ipynb'),
('foo', 'name with space... | d2d3479e36c102d8d7d98819d2aeb5b40d1cca4c | 50,040 |
def running_mean(clazz=None, batch_size=50, step_size=10, dim=None):
"""The :func:`running_mean` decorator is used to add a :class:`.RunningMean` to the :class:`.MetricTree`. If the
inner class is not a :class:`.MetricTree` then one will be created. The :class:`.RunningMean` will be wrapped in a
:class:`.To... | 1dd99ce8a33bc66e3b69da5611bb6e405cb4b360 | 50,041 |
def min_value(state, depth, max_depth, alpha, beta, transposition_table):
"""
Acting as the minimizer for the min_max search with alpha beta
"""
state.depth = depth
# checking entry in transposition table
table_check = transposition_table.table_lookup(state)
if(len(table_check) > 0):
... | ee28fcb8a18cf2aff60fdea3f963ce8a3404f9a0 | 50,042 |
def api_client(cluster_name: str, api_class: str) -> k8s.client.apis:
"""
Creates and returns a python k8s api client of the specified class and pointing to the specified cluster.
Usage: Use this function whenever you want a python k8s api client.
Python k8s api documentation: https://github.com/kubernetes-clie... | c9c857093dad701fa9a3a745da2c403137191e2d | 50,043 |
def plot_intensity(tc, ax=None, figsize=(10,5), fontsize=15):
"""
Plot the intensity of the given TC.
Parameters
----------
tc: TC
A single TC.
ax: Axe
Axe for plotting
figsize: tuple
Figure size of (12, 6)
fontsize: int
Size of the font (title, label and... | 6a76018f29de6e08b0715fe67bd94c30ee10e28e | 50,044 |
import PIL.Image as Image
def fig_2_Image(fig):
"""
Ref: https://panjinquan.blog.csdn.net/article/details/104179723
fig = plt.figure()
image = fig2data(fig)
@brief Convert a Matplotlib figure to a 4D numpy array with RGBA channels and return it
@param fig a matplotlib figure
@return a... | 6dda76db1c976005bca0814fd512d747790ff45d | 50,045 |
import math
def binary_sigmoid(n: float, lmbda: float = 1.0) -> float:
"""
Binary Sigmoidal (Unipolar Continuous) Activation Function
"""
return 1 / (1 + (math.exp(-lmbda * n))) | dec3380311c5bb1130e8455254d55b44ab416d21 | 50,046 |
from .collections import store
def user_is_valid(data):
"""user error handling"""
resp = "The username you provided already exists"
body = store.get_by_field(key='username', value=data.get('username')) is not None
errors = {}
if store.get_by_field(key='email', value=data.get('email')) is not None... | 185e290afe74492d190c4adb336629a38c06c377 | 50,047 |
def create_new_ap_hostname(country_code, ap_macs: list(), mgmt_subnet: str) -> dict:
"""
"WAP<COUNTRY_CODE><2nd_OCTET>3rd_OCTET>_<ascending index starting from 001>"
start index will be the lowest management IP address
Args:
mgmt_subnet: IP network portion (without prefix)
ap_macs: list... | ad10091981a3f404d1e5805049e3bcf6e6d18899 | 50,048 |
def ldns_tsig_keydata_clone(*args):
"""LDNS buffer."""
return _ldns.ldns_tsig_keydata_clone(*args) | ccda3684f6611333fe0db77c4eacb325f6c6fa0a | 50,049 |
def log_variance(locations):
"""
Compute location variance feature from location data.
Logarithm of combined variance of latitude and longitude values.
:param locations: dataframe of location data with columns latitude and longitude.
:return: location variance.
"""
if len(locations) < 2:
... | d0fbf61ad8154d2ebf4f992682ebfcb1cc77472c | 50,050 |
def client(app):
""" Fixture to emulate client"""
return app.test_client() | 555e43501347e257ea9b0eeb95ba80e99e1a6ce9 | 50,051 |
def first_discoverable(targets, cat, kwargs):
"""A target chooser: the first target for which discover() succeeds
This may be useful where some drivers are not importable, or some
sources can be available only sometimes.
"""
for t in targets:
try:
if cat:
s = cat... | 592d738d943578929d69d4d98ca98cdda16f96b9 | 50,052 |
def _centralize(shape):
"""Create a shape which is just like the input, but aligned to origin.
The origin is (0; 0) in 2D case.
The input shape stays unchanged. It's expected to be a numpy.array.
"""
centroid = shape.mean(0)
return shape - centroid | 0c65ac55d3dbad9d540d73e2480c0d71ad703302 | 50,053 |
import torch
import random
def evaluate_model(Net, seeds, mini_batch_size=100, optimizer = optim.Adam, criterion = nn.CrossEntropyLoss(), n_epochs=40, eta = 1e-3,
lambda_l2 = 0, alpha=0.5, beta=0.5, plot=True,statistics = True ,rotate = False,translate=False,swap_channel = False,
... | 7a7e4438eaf81337894cd10454254e368060fb27 | 50,054 |
def factory(_context, request):
"""Return a AuthCookieService instance for the passed context and request."""
cookie = SignedCookieProfile(
# This value is set in `h.auth` at the moment
secret=request.registry.settings["h_auth_cookie_secret"],
salt="authsanity",
cookie_name="aut... | 1d8191a1202c9493af47d947b5f95c7fc471624d | 50,055 |
def get_fcn_resnet50_model_instance(num_classes):
"""
This method gets an instance of FCN-Resnet-50 model given num_classes.
0 < num_classes <= 21
:param num_classes: number of classes
:return: instance of FCN-Resnet-50 model.
"""
# Checks constraint on num_classes
if num_classes <= 0 ... | 594c1f34822ba648a35392bcb4fe8e07bb7bb514 | 50,056 |
def projC(gamma,q):
"""return the KL projection on the column constrints """
return np.multiply(gamma,q/np.maximum(np.sum(gamma,axis=0),1e-10)) | 9199a9d746a4d1cb1cfb9c074f333289ac9365b1 | 50,057 |
def read_file(file_name, package_level=True):
"""Get file content given file path.
:param: [package_level] - Wheather the file is in/out side the
`gmail_api_wrapper` package
"""
file_path = get_absolute_path(file_name, package_level=package_level)
with open(file_path) as file_descriptor:
... | 2feac46a49acb7a804b7527512e1dfd9d7b98c04 | 50,058 |
def fit_vfa_nonlinear(s, fa_rad, tr):
"""Return T1 based on VFA signals using NLLS fitting.
Parameters
----------
s: ndarray
1D array of signals.
fa_rad: ndarray
1D array of flip angles (rad).
tr: float
Repetition time (s).
Returns
---... | f8fccfd1e1e61a2da1c8be93eef6f241e8370a7f | 50,059 |
import random
def GenerateRandomName():
"""Generates a random string.
Returns:
The returned string will be 12 characters long and will begin with
a lowercase letter followed by 10 characters drawn from the set
[-a-z0-9] and finally a character drawn from the set [a-z0-9].
"""
buf = cStringIO.Stri... | 96810577d5c12f97bf3854baee1ff66484b71782 | 50,060 |
from saq.database import get_db_connection
import logging
def get_restoration_targets(message_ids):
"""Given a list of message-ids, return a list of tuples of (message_id, recipient)
suitable for the unremediate_emails command. The values are discovered by
querying the remediation table in the data... | b6121a0c3daa39139ebda23930203a2a4775ac33 | 50,061 |
def _check_fit_params(x_data, fit_params, indices=None):
"""Check and validate the parameters passed during ``fit``."""
fit_params_validated = {}
for param_key, param_value in fit_params.items():
if (not _is_arraylike(param_value) or
_num_samples(param_value) != _num_samples(x_data))... | bcf7535af55662130b559b04970fabaa5b7e1ccf | 50,062 |
def filter_wrong_poses(
skel_ours_2d, skel_ours_3d,
d_thresh=Conf.get().optimize_path.head_ank_dthresh,
l_torso_thresh=Conf.get().optimize_path.torso_length_thresh,
show=False):
"""Attempts to filter poses, where ankles are too close to the head.
Remember, up is -y, so lower y coordinate means "higher" ... | ba4540a05992871c375513d452cafac10ccb1af1 | 50,063 |
def read_binary_file(
bbseries, comps, station_names=None, wave_type=None, file_type=None, units="g"
):
"""
read all stations into a list of waveforms
:param input_path:
:param comp:
:param station_names:
:param wave_type:
:param file_type:
:return: [(waveform_acc, waveform_vel])
... | 142b8cef3fae056b26dd2ee81f87b4b37a10a852 | 50,064 |
def is_html_needed(user_agent):
"""
Basing on `user_agent`, return whether it needs HTML or ANSI
"""
plaintext_clients = ['curl', 'wget', 'fetch', 'httpie', 'lwp-request', 'python-requests']
if any([x in user_agent for x in plaintext_clients]):
return False
return True | 67a75c34dca4672534058729875dc5ee98696590 | 50,065 |
def open_hansen_biomass_tile(tile_id, version):
"""
Open single tile from the Hansen 2020 dataset and then
massage it into a format for use by the rest of the routines.
Parameters
----------
tile_id : str
The latitude/longitude of the northwest corner of the tile (e.g. 50N_130W)
ver... | 5f6bb87a90f9506af9e90d29ec11fda2f7c6b8c3 | 50,066 |
def process_entry(base_url, i, entry):
"""
Given a base URL, an index, and an entry dictionary,
ensure that the entry is valid,
and return an Apache RedirectMatch directive string.
"""
source = ''
replacement = ''
# Check entry data type
if type(entry) is not dict:
raise ValueError('Entry %d is n... | 1dd3074fbca9d7c1f646ae348ceb992c027bb1fb | 50,067 |
import unicodedata
def _normalize(string_to_convert, normalize=False):
"""
a utility method for normalizing string
"""
try:
return unicodedata.normalize('NFC', string_to_convert) if normalize else string_to_convert
except TypeError:
return string_to_convert | 2c4edc31741d8b87165996339c8b9231f5ed6aa5 | 50,068 |
def pipe(*args, **kwargs):
"""An aggregator that eagerly sums fields of items in a stream.
Note that this pipe is not lazy if `group_key` is specified.
Args:
items (Iter[dict]): The source.
kwargs (dict): The keyword arguments passed to the wrapper
Kwargs:
conf (dict): The pipe... | dd0b6433793d40c1710cdf2ce72ff627af623279 | 50,069 |
def __xor_bytes(bytes1, bytes2):
"""xor of a list of bytes"""
assert len(bytes1) == len(bytes2)
return [bytes1[i] ^ bytes2[i] for i in range(len(bytes1))] | 0b576cd877839cd2191fee57f6b5f270a37726de | 50,070 |
def plugins_help() -> str:
"""
Gets the help text for the 'plugins' sub-command.
"""
return PluginsOptions.get_configured_parser(prog="wai-annotations plugins").format_help() | 7d88e2e397fe6d1ddf6298901f7d7fece9a1e91b | 50,071 |
def report_issue() -> str: # pragma: no cover
"""Used when errors are really f*cked up"""
return ('Report an issue please? '
'( https://github.com/agamm/comeback/issues )') | 9b6015a12f252341f63bb988d2bb5b46c3c66318 | 50,072 |
def get_distro():
""" factory to return the right Distro object """
return distro_instance | bd188dcb27c8f541988a3209453a92cfca34b59d | 50,073 |
def compute_coefficients(temperature_resistance_pairs):
"""Computes Steinhart-Hart model coefficients.
Equations taken from
https://www.dataloggerinc.com/wp-content/uploads/2016/10/self-calibrate-thermistors.pdf.
Args:
temperature_resistance_pairs: sequence of three (temperature, resistance)
tuples.... | 15e7a68281eb5a9b879c1bdd82522630b2d25846 | 50,074 |
from datetime import datetime
import functools
def timed_cache(**timed_cache_kwargs):
"""LRU cache decorator with timeout.
Parameters
----------
days: int
seconds: int
microseconds: int
milliseconds: int
minutes: int
hours: int
weeks: int
maxsise: int [default: 128]
ty... | 0cdad8fcb7f76303b73e883d71e0c055c136f453 | 50,075 |
def _get_orthologous_imodulons(M1, M2, method, cutoff):
"""
Given two M matrices, returns the dot graph and name links of the various
connected ICA components
Parameters
----------
M1 : ~pandas.DataFrame
M matrix from the first organism
M2 : ~pandas.DataFrame
M matrix from t... | 85aa4ba43b74b6b102f062a6aa131e7596ef9b69 | 50,076 |
def cont6():
"""
1 cluster (2 shared contours) with 2 subclusters (those from <cont4>).
Contains 3 minima (subclusters contain 1 and 2, resp.).
"""
cont_min = [
cncc(5, (6.00, 3.00), 0.2, (1, 1)),
cncc(2, (7.00, 4.00), 0.1, (4, 1), rmin=0.15),
cncc(2, (6.25, 3.25), 0.3, (6, 1... | 4ce2406b6bb6eb26341b64e853b3451003410a53 | 50,077 |
def _get_raw_parts_helper(response, http_response_type):
"""Helper for _get_raw_parts
Assuming this body is multipart, return the iterator or parts.
If parts are application/http use http_response_type or HttpClientTransportResponse
as enveloppe.
"""
body_as_bytes = response.body()
# In or... | 755b33a9141e9ec62170f50e278f72fa20c7de2b | 50,078 |
def mom2mag_nm(mom):
"""Converts moment to magnitude - newtonmetre"""
return (np.log10(mom) - 9.05) / 1.5 | 83da75adb534f6e3e7ed6afa067c111f0688344b | 50,079 |
def mergeWindows(data, dimOrder, maxWindowSize, overlapPercent, batchSize, transform, progressCallback=None):
"""
Generates sliding windows for the specified dataset and applies the specified
transformation function to each window. Where multiple overlapping windows
include an element of the input datas... | 3775c7c4e5a49921af8ac8cd8a2b7cb37c5e3385 | 50,080 |
def UDPOS(*args, **kwargs):
""" Universal Dependencies English Web Treebank
Separately returns the training and test dataset
Arguments:
root: Directory where the datasets are saved. Default: ".data"
Examples:
>>> from torchtext.datasets.raw import UDPOS
>>> train_dataset, vali... | cea4db2bba5e97fd6ecb34c4ceda89ee899e0c71 | 50,081 |
def _load_global_signal(confounds_raw, global_signal):
"""Load the regressors derived from the global signal."""
global_params = _add_suffix(["global_signal"], global_signal)
_check_params(confounds_raw, global_params)
return confounds_raw[global_params] | e904077af687083f0e2135744172a36b4ae38a41 | 50,082 |
from bifrostrpc.typing import DictTypeSpec, ScalarTypeSpec
from typing import Callable
from typing import Any
def DictTester(
value_test: Callable[[Any], bool],
) -> Callable[[Any], bool]:
"""
Return a callable that tests whether a given TypeSpec is a DictTypeSpec
with the expected valueSpec.
It ... | b7edca7701bce11b155c9c351a5eb0b5a8241810 | 50,083 |
def isHarmonic(field, sphericalMask, shellMask):
"""Checks if the extrema of the field are in the shell."""
fullField = np.multiply(field, sphericalMask) # [T]
reducedField = np.multiply(field, shellMask)
if int(ptpPPM(fullField)) > int(ptpPPM(reducedField)):
print(
"ptpPPM of field... | 66170697c6a468e31d7badbd0a4cca277c74ca6c | 50,084 |
def _as_list(arr):
"""Make sure input is a list of mxnet NDArray"""
if not isinstance(arr, (list, tuple)):
return [arr]
return arr | be489c8d1be314c8b34df25546228f855c223b57 | 50,085 |
import random
def random_number():
"""Generate a random string of fixed length """
return random.randint(0, 9999) | f3d448b3118d82fd88946ddddadaa1941ffd7d41 | 50,086 |
def eh_posicao(pos):
"""
Verifica se um determinado valor e uma posicao valida
Parametros:
pos (universal): Possivel posicao.
Retorna:
(bool): True se for numero valido e False se nao for.
"""
return False if type(pos) != int or pos < 1 or pos > 9 else True | af0f73f8e4513a679b34795d7be43c26bbc6b586 | 50,087 |
def get_channel_row(*args, **kwargs):
"""
获取信息
:param args:
:param kwargs:
:return: None/object
"""
return db_instance.get_row(Channel, *args, **kwargs) | 40c66c1c633a92f9cad6d60f01206e82020483cd | 50,088 |
import os
def parse(filepath):
"""
Simple method for fully specified path which split the string into three parts:
folders, filename without suffix and suffix
e.g. for ./myfolder/myfile.ext method returns ./myfolder/, myfile, ext
:param filepath: str
any form of os.path (relative or absolu... | 66fc5f1228361962687116d8c921e859ef03401f | 50,089 |
def calc_hole(first_map, second_map, min_size=419430400):
"""
Calcul hole between 2 mappings.
format of a Mapping Tuple:
2 integers :
- physical_address
- mapping_size
formated as following
( physical_address, mapping_size )
Input :
- first_map :... | c035d23eff6e73295d0421e1cfb63f992caf9673 | 50,090 |
def eval_ctx(*args, **kwargs) -> EmbeddingCtx:
"""Get the ``EmbeddingCtx`` with the ``PreprocessMode.EVAL`` mode."""
return EmbeddingCtx(PreprocessMode.EVAL, *args, **kwargs) | 150847a06ae737deee18b45fd549c70b09d67232 | 50,091 |
def Snu_rescale_axion(ma, ga, ma_ref, ga_ref, source_input=default_source_input):
"""
Computes the rescale factor for different axion parameters.
Parameters
----------
ma : axion mass [eV]
ga : axion-photon coupling [GeV^-1]
ma_ref : reference axion mass [eV]
ga_ref : reference axion-ph... | 63b2fa358c2eca3fcc0d8d6ac989410fe2893380 | 50,092 |
import json
def _generate_screen_id_and_captions_pair(json_file_path):
"""Generates pair of screen id and MTurk labels for each screen."""
with tf.gfile.GFile(json_file_path) as f:
screens = json.load(f)
return list(screens.items()) | 041ea2f4f41b8a37d4877307341b6facbaffdc3f | 50,093 |
def to_image(X, filters=2, n=None):
""" 1x1 convolution layer to convert output to an image """
output = weighted_conv2d(inputs=X,
filters=filters,
kernel_size=[1, 1],
activation=None, #tf.nn.tanh,
... | e8330805e42e131ffa183e77dac2ee8c8c763206 | 50,094 |
def summarize_ranges(addrlist):
""" Convert a list like [1,2,3,5] to ["1-3", "5"], but with IP addresses """
ranges = []
start = None
prev_range_class = None
for addr in addrlist:
if start is None:
start = addr.ip
end = addr.ip
prev_range_class = addr.rang... | 5c4183099b4be31ac73a80cba802cc2e942dc25e | 50,095 |
def sphankel1(n, kr):
"""Spherical Hankel (first kind) of order n at kr.
Parameters
----------
n : array_like
Order
kr: array_like
Argument
Returns
-------
hn1 : complex float
Spherical Hankel function hn (first kind)
"""
n, kr = scalar_broadcast_match(n... | b0951a744f50fa86ad419fecc7d06100dc53e309 | 50,096 |
import test
def init_news_overview() -> OverviewDatabase:
"""
init the news overview
Will store news overview -- number of hits, corresponding colour and other info
:return: database.Database object
"""
if test() == 0:
raise DatabaseError
res = OverviewDatabase()
init_db("publ... | a1f9b48915102b97c50e2a4b4a5cb784f20ba701 | 50,097 |
def get_obs_route(value):
""" obs-route = obs-domain-list ":"
obs-domain-list = *(CFWS / ",") "@" domain *("," [CFWS] ["@" domain])
Returns an obs-route token with the appropriate sub-tokens (that is,
there is no obs-domain-list in the parse tree).
"""
obs_route = ObsRoute()
whi... | d1c319712dbf64c4aa48d70e8fc916dee4c3276d | 50,098 |
def del_gloabls_var(key):
"""删除值"""
try:
GLOBALS_DICT.pop(key)
return True
except KeyError:
return "Not Found" | 5acb5ef300cceb2fe7ebe78e5b6dd2f0015267a0 | 50,099 |
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