content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def _all(itr):
"""Similar to Python's all, but returns the first value that doesn't match."""
any_iterations = False
val = None
for val in itr:
any_iterations = True
if not val:
return val
return val if any_iterations else True | bb1145abaaaa1c6910371178ca5ebe68600bb287 | 49,738 |
def list_plot3d_array_of_arrays(v, interpolation_type, texture, **kwds):
"""
A 3-dimensional plot of a surface defined by a list of lists ``v``
defining points in 3-dimensional space. This is done by making the
list of lists into a matrix and passing back to :func:`list_plot3d`.
See :func:`list_plo... | d3099b55a37f57a9df111b3f8b55033732b1ebcc | 49,739 |
import six
def volume(input, copyFrom=None, rescale=True, voltype=None):
"""
Read an existing geoprobe volue or make a new one based on input data
Input:
input: Either the path to a geoprobe volume file or data to
create a geoprobe object from (either a numpy array or
... | c04a5d5060a0afd25d9b3f12b5d6a207582739ea | 49,740 |
def view_related_developers(request, tag, slug):
"""
Tutorial > View Related Developers
"""
namespace = CacheHelper.ns('tutorial:views:view_related_developers', tag=tag, slug=slug)
response_data = CacheHelper.io.get(namespace)
if response_data is None:
response_data, tutorial = RelatedH... | f36355eb0635dd29edd1fe548ff88f22ec51ffdb | 49,741 |
def compute_neuron_head_importance(task_name,
model,
data_loader,
num_layers,
num_heads,
loss_fct=nn.loss.CrossEntropyLoss(),
... | be0d52c34539db4650aba53c0bb41a958af17ab9 | 49,742 |
def no_init(_data, weights):
"""
Return the entered weights.
Parameters
----------
_data: ndarray
Data to pick to initialize weights.
weights: ndarray
Previous weight values.
Returns
-------
weights: ndarray
New weight values
Notes
-----
Useful ... | f120b49ab26fa1051360b4e4ae85dd07025ae5cc | 49,743 |
def primeFactors(someInt):
"""
return a list of the prime factors of
someInt.
e.g.
primeFactors(24)=[2,2,2,3]
primeFactors(23)=[23]
primeFactors(25)=[5,5]
"""
return "stub" | 4afe8491585721852571ecda89c7cd33fb05d1f7 | 49,744 |
def create_local_gateway_route(client, local_cidr, **route_kwargs):
"""[summary]
Arguments:
client {[type]} -- [description]
local_cidr {[type]} -- [description]
Keyword Arguments:
gateway {[type]} -- [description] (default: {None})
Returns:
OperationResult
"""
... | e7f07f133be40d7eb71a6c40ec610f3ceba3e6c8 | 49,745 |
def validate_ui(self, value):
"""Validate EngineUI objects."""
if not isinstance(value, EngineUI):
reason = 'not an EngineUI object'
raise ValueError(self.msg.format(reason))
return value | dbe3eb7377164a2c98dd875f1e5715a84d613176 | 49,746 |
import uuid
def is_valid_uuid(val):
"""
Check if a string is a valid uuid
:param val: uuid String
:return: Returns true if is a string is a valid uuid else False
"""
try:
uuid.UUID(str(val))
return True
except ValueError:
return False | d04f658d3ae2fa85377e110b0a6716bc34ee9df0 | 49,747 |
def generate_stat_string(stat_distribution, name):
"""generates the gear rating string based on the count of the stat"""
count = stat_distribution.count(name)
extra_line = "\n" if name == "versatility" else ""
return "gear_{0}_rating={1}{2}".format(name, count * config["stats"]["steps"], extra_line) | bab062276be57fbc134bc49c70eda1d96513de86 | 49,748 |
from typing import Tuple
from typing import List
def pad_dialog(
dialog: Dialog, max_dialog_size: int, max_utterance_size: int
) -> Tuple[List[List[int]], List[List[int]], List[List[int]], List[List[int]]]:
"""Pads utterances in a dialog up to max dialog sizes."""
dialog_usr_input, dialog_usr_mask, dialog_sy... | 2456716cd0ffc9b0d8613adb04ff206c250cc0c8 | 49,749 |
from pathlib import Path
import warnings
import shlex
def _make_sbatch_string(
command: str,
folder: tp.Union[str, Path],
job_name: str = "submitit",
partition: tp.Optional[str] = None,
time: int = 5,
nodes: int = 1,
ntasks_per_node: tp.Optional[int] = None,
cpus_per_task: tp.Optional[... | bde05036f280d2cf9b88e2b768bb2b93806682dd | 49,750 |
import warnings
import urllib
def parse_redis_url(url):
"""
Given a url like redis://localhost:6379/0, return a dict with host, port,
and db members.
"""
warnings.warn(
"Use redis.StrictRedis.from_url instead", DeprecationWarning,
stacklevel=2)
parsed = urllib.parse.urlsplit(ur... | 6d24b885feadf58a6f9a17486ba71e4473bce100 | 49,751 |
import numpy
def Torque(cc1,cc2,ccp,g,mass=1.0):
"""
cc1: origin of axis, cc2 head of axis
ccp: point
g: Gradients in Cartasian coordinate, [dx,dy,dz]
"""
torque=0.0
x21=cc2[0]-cc1[0]; y21=cc2[1]-cc1[1]; z21=cc2[2]-cc1[2]
xp1=ccp[0]-cc1[0]; yp1=ccp[1]-cc1[1]; zp1=ccp[2]-cc1[2]
dnom... | d4974f3e5997e44530ad7a1988fe36800d3dad4b | 49,752 |
import io
import tarfile
def write_tar_from_contents(contents, filter=None):
"""Writes a tar file from a dict of archive names to bytes that represent the
contents of each file.
"""
digest = io.BytesIO()
with tarfile.TarFile(mode="w", fileobj=digest) as tar:
for filename, content in conten... | c7918a131ca0038647f0de24198609b1f1e28363 | 49,753 |
def eliminate(values, s, d):
"""Eliminate d from values[s]; propagate when values or places <= 2.
Return values, except return False if a contradiction is detected."""
global counttotalsearches # DGTEMP
counttotalsearches += 1 # DGTEMP
if d not in values[s]:
return values ## Already elim... | 7df68c13c1088933a8601eecbcb3b8bd9aba5d03 | 49,754 |
def non_zero_uniform(shape):
"""Samples in open range (0, 1).
This avoids the value 0, which can be returned by tf.random.uniform, by
replacing all 0 values with 0.5.
Args:
shape: a list or tuple of integers.
Returns:
A Tensor of the given shape, a dtype of float32, and all values in the open
i... | c3c50d26d6c1e87e2c1049c5d2931e73f4c7dd86 | 49,755 |
def _format_moving_cutoff_predictions(y_preds, cutoffs):
"""Format moving-cutoff predictions"""
if not isinstance(y_preds, list):
raise ValueError(f"`y_preds` must be a list, but found: {type(y_preds)}")
if len(y_preds[0]) == 1:
# return series for single step ahead predictions
retu... | f52d70c72a00a84bcbb35eacf952eaee1e7dbb44 | 49,757 |
import re
def get_possible_modes():
"""Get the set of possible modes."""
modes = set()
with open("web/src/helpers/constants.js", encoding="utf-8") as file_:
# The call to `eval` is a hack to parse the `modeOrder` array from the
# JavaScript source file.
for mode in eval(re.search(r... | 062159e1dffd24296264792fd8cf6e53441fb141 | 49,760 |
def convert_to_hexadecimal(bits, padding):
"""
Converts bits to a hexadecimal character with padding.
E.g.
Converts [False, False, False, True], 0 to "1".
Converts [True, False, False, False], 2 to "08"
Args:
bits: List of boolean values.
padding: Integer of number of ... | b8cd1647a24072278aca65f7734934acd93d8f12 | 49,761 |
import fastapi
from typing import List
async def read_patron_list(
session: aio_session.AsyncSession = fastapi.Depends(
dependencies.get_session),
offset: int = 0,
limit: int = fastapi.Query(default=100, le=100),
current_patron: patron_model.Patron = fastapi.Depends( # pylint: disable=unused-... | 522407fd8b448564d80957b66df58feef3252f99 | 49,762 |
def beta_table(stocks_weights, start, end):
"""
Returns an attribution table for portfolio beta
:param stocks_weights: table of the name of equities in one column, weights in another
:param start: start date
:param end: end date
:return: table
"""
# Due to the nature of the percentchange... | 9cfb5f6658dc1a3d4960bc7451be06c9e48ac9fb | 49,763 |
def sepconv_relu_sepconv(inputs,
filter_size,
output_size,
first_kernel_size=(1, 1),
second_kernel_size=(1, 1),
padding="LEFT",
nonpadding_mask=None,
... | a7f94ec286df89e252262d6ada7031a92d133342 | 49,764 |
import wheel
def convert(context, base_path, rule):
"""
Convert the python representation of a targets file into a python
representation of a buck file.
"""
converters = [
discard.DiscardingConverter(context, 'cpp_binary_external'),
discard.DiscardingConverter(context, 'haskell_ge... | dcaa320255dc4286b73ab3750d465898060a4008 | 49,765 |
import json
def set_review_filters(request):
"""Sets review filters given by passed request.
"""
review_filters = request.session.get("review-filters", {})
if request.POST.get("name", "") != "":
review_filters["name"] = request.POST.get("name")
else:
if review_filters.get("name"):... | 9d9f7e1544e3eea9767f0f85677bcb2b23cdd81c | 49,766 |
import string
def _sanitize_title(title):
""" Remove all non alphanumeric characters from title and lowercase """
alphanumeric = string.ascii_lowercase + string.digits + ' '
title = title.lower()
title = "".join(filter(lambda x: x in alphanumeric, title))
return title | 6f0d1818140bc2a50b160f73b8b4590be8f31891 | 49,767 |
def IsBefore(version, major, minor, revision):
"""Decide if a given version is strictly before a given version.
@param version: (major, minor, revision) or None, with None being
before all versions
@type version: (int, int, int) or None
@param major: major version
@type major: int
@param minor: minor... | 3fe9f995b90d7406d0b0366b0bbe5a940f975893 | 49,768 |
def generateRules(L, supportData, minConf=0.7):
"""
生成关联规则
Args:
L 频繁项集列表
supportData 频繁项集支持度的字典
minConf 最小置信度
Returns:
bigRuleList 可信度规则列表（关于 (A->B+置信度) 3个字段的组合）
"""
bigRuleList = []
for i in range(1, len(L)):
# 获取频繁项集中每个组合的所有元素
for freqSet in... | 2ab2c23450cfff8c80f6b2bd9783e73186f1d064 | 49,771 |
def domain_check(f, symbol, p):
"""Returns False if point p is infinite or any subexpression of f
is infinite or becomes so after replacing symbol with p. If none of
these conditions is met then True will be returned.
Examples
========
>>> from sympy import Mul, oo
>>> from sympy.abc impor... | 057665c5de32747a92b09f83831db36665f127c3 | 49,772 |
import math
def makePyramid(elem, graph, levels=4, scale=0.5):
"""
Create a pyramid of num images based upon elem, which becomes the
first child of the new pyramid
"""
p = elem.getparent()
minDim = round(levels / scale)
width = max(int(elem.get(swidth, str(minDim))), minDim)
height = m... | 822f54fcb78673101390d8aaa7bb8aefb022d90c | 49,773 |
def parse_negline(neg_line):
"""
Parse the THIRD line of the .mmo file, where the negations are stored.
Why does it not do this per-phrase? Mystery.
We connect the negated-CUI to its appearance in the text using the
ConceptPositionalInfo which _appears_ to correspond to the PosInfo field
which ... | a412add79370a58f6bd00c0139a9fe334e808432 | 49,775 |
import json
def validate_cohort_project_allowed():
"""
Returns true if a valid project is provided. Remote call is set up in
static/js/cohortUpload.js.
"""
project = request.args.get('project')
valid = project in db.get_mw_projects()
return json.dumps(valid) | 79e568d2a8ec8f5541aa5c6ea97aac5d42d80bb5 | 49,776 |
def depthwise_2d_fast(feat, weights):
"""
"""
feat = tf.convert_to_tensor(feat)
weights = tf.convert_to_tensor(weights)
kernel_size = weights.shape.as_list()[0]
return graphics_tf_module.depthwise_conv_fast(feat, weights, kernel_size) | f3aa9989a7c7f4559a1184f19d303187d2d2e594 | 49,777 |
def handle_trace_length(state_trace_length):
"""
transform format of trace length
:return:
"""
trace_length_record = []
for length in state_trace_length:
for sub_length in range(0, int(length)):
trace_length_record.append(sub_length + 1)
return trace_length_record | 39631247d10dbaa024a0e8d553024718150ccc51 | 49,778 |
from time import time
from scipy.signal import fftconvolve
def compute_ts_map(counts, background, exposure, kernel, mask=None, flux=None,
method='root brentq', optimizer='Brent', parallel=True,
threshold=None):
"""
Compute TS map using different optimization methods.
... | ebfc3dada9e0e39ba8bea0c3e36948f5d6ffe134 | 49,779 |
import sound
def audio_duration(filename):
"""
duration of a audio file (usually mp3)
Parameters
----------
filename : str
must be a valid audio file (usually mp3)
Returns
-------
duration in seconds : float
Note
----
Only supported on Windows and Pythonista. On ... | 6d51619957c6a6dc96eb1b3647bfe2176ae080fd | 49,781 |
def is_moderator(request, view):
"""
Helper function to check if a user is a moderator
Args:
request (HTTPRequest): django request object
view (APIView): a DRF view object
Returns:
bool: True if user is moderator on the channel
"""
user_api = request.channel_api
cha... | 31c8b53c28b3972a731b87b13177b3c01c45ade4 | 49,782 |
def monkeypatch(monkeypatch):
"""Adapt pytest's monkeypatch to support stdlib's pathlib."""
class Monkeypatcher:
"""Middle man for chdir."""
def _chdir(self, value):
"""Change dir, but converting to str first.
This is because Py35 monkeypatch doesn't support stdlib's p... | d7da33204cd0a2f07f51b47b95f106e053c28c1f | 49,783 |
def binom(n, k):
"""
Obtain the binomial coefficient, using a definition that is mathematically
equivalent but numerically stable to avoid arithmetic overflow.
The result of this method is "n choose k", the number of ways choose an
(unordered) subset of k elements from a fixed set of n elements.
... | b322712d1757df543ccdc92ffc7f883504804346 | 49,784 |
def no_auth(request):
"""
Use this if no auth is desired
"""
return request | 5871518399aee8204d2ece4c8bad575527270627 | 49,785 |
def bilstm_layer_cudnn(input_data, num_layers, rnn_size, keep_prob=1.):
"""Multi-layer BiLSTM cudnn version, faster
Args:
input_data: float32 Tensor of shape [seq_length, batch_size, dim].
num_layers: int64 scalar, number of layers.
rnn_size: int64 scalar, hidden size for undirectional L... | 6f55275787e7e5f68004cb5b5173008ab34ae6f1 | 49,786 |
from typing import Tuple
def calculate_smoothed_trends(
case_counts: np.ndarray,
death_counts: np.ndarray,
hosp_counts: np.ndarray,
smoothing_window: int) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
"""
Calculates the smoothed trends with the given smoothing window
:param case_counts: Cases per day
:par... | c8fc0ef3a071bb04c86bbed1e27d04a505b094ea | 49,787 |
def generate_swagger_params(crown: ViewCrown, swagger_params: dict) -> dict:
"""
assemble params for swagger_auto_schema by crown
"""
default_params = {}
if crown.body_in:
default_params = {"request_body": crown.get_in_serializer_instance()}
elif crown.query_in:
default_params = ... | dc91db1a6e9317a4b45346e6829df1d4d195a18c | 49,788 |
def total_size(metainfo):
"""
Compute sum of all files' size
"""
if metainfo.has_key('files'):
total = 0
for infile in metainfo['files']:
if infile.has_key('length'):
total += infile['length']
return total
else:
return None | 84deea16534e35f2c3c86c9674a8e83f880bd5a5 | 49,789 |
def diffmap(adata, **kwargs):
"""\
Scatter plot in diffmap basis.
Parameters
----------
{scatter}
Returns
-------
If `show==False` a :class:`~matplotlib.axes.Axes` or a list of it.
"""
return scatter(adata, basis="diffmap", **kwargs) | f304e66f76fa143ff7102eec5388749c6e6014fe | 49,790 |
import random
import string
def makeHTMLword(body, fontsize):
"""take words and fontsize, and create an HTML word in that fontsize."""
#num = str(random.randint(0,255))
# return random color for every tags
color = 'rgb(%s, %s, %s)' % (str(random.randint(0, 255)), str(random.randint(0, 255)), str(rando... | 00bb65217f4b75344a38100cee88c1e928aa0698 | 49,791 |
def sigma_x_rk_new(
thickness,
radius,
length,
f_y_k,
fab_quality=None,
flex_kapa=None
):
"""
Meridional characteristic buckling stress.
Calculates the characteristic meridional buckling stress for a cylindrical shell according to EN1993-1-6 [1].
Paramet... | fc79d852b8878757d7e5e2eb794a1507986bb0cb | 49,792 |
def ts_grismc_sim(pixels):
"""
Simple analytic wavelength calibration for Simulated GRISMC data
"""
disp = 0.0010035 ## microns per pixel (toward positive X in raw detector pixels, used in pynrc)
undevWav = 4.0 ## undeviated wavelength
undevPx = 1638.33
wavelengths = (pixels - undevPx) ... | f3491fea1fa1e8833384711076e6187f0f6cb42b | 49,794 |
from typing import Callable
def get_admin_principal_by(authentication_manager: AuthenticationManager) -> Callable[[Request], PrincipalService]:
"""
admin only
"""
return get_principal_by(authentication_manager, [UserRole.ADMIN]) | 8737f6a271d766560cb2f5c17e271d297c520195 | 49,795 |
def get_profile_avatar_upload_to(instance, filename):
""" Returns a valid upload path for the avatar associated with a forum profile. """
return instance.get_avatar_upload_to(filename) | 840e7482b225c0a456dbc8cd967203aa542945f8 | 49,796 |
from typing import Optional
def calc_r(alphas: np.ndarray, colvars: np.ndarray,
calc_jac: bool) -> tuple[np.ndarray, Optional[np.ndarray]]:
"""
Calculate linear combination of reaction coordinates given a weights vector
and colvars matrix. Also returns the jacobian with respect to the alphas if... | 2e14ddd98c296eb0250ff59cc84597594873c383 | 49,797 |
def discretized_exponential(lamb, up_bound, steps):
""" Exponential distribution on discretized interval [0, up_bound] """
return discretized_state(lambda x: stats.expon.pdf(x, scale=1 / lamb),
0, up_bound, steps) | 8ed948c7e7652fa15aefd41f02470864dfd5d1df | 49,798 |
def timedelta_to_string(dt):
"""
Return hh:min:sec from a timedelta64.
There doesn't seem to be a standard pandas or numpy function to
do this strangely.
"""
total_sec = dt / np.timedelta64(1, 's')
hours = int(total_sec // 3600)
minutes = int((total_sec // 60) % 60)
seconds = int(to... | 2615dc0f54272183325ddc441d8f489f323c1cfb | 49,799 |
def funex(c):
"""
Compile a function by 'exec'
:param c: function to compile
:type c: string
:return: the function 'f' declared in the input string
:rtype: function
"""
dc = {}
exec(c, dc)
return dc['f'] | 79fac0aad493d47fc9fecbf30bfe4bc09a2f9908 | 49,800 |
import threading
import time
def get_fingerprint_batch(input_list, default_port=443,
delay_time=0.5, max_threads=100):
"""
This is a parallel version of the TLS fingerprint primitive.
Params:
input_list- the input is a list of host:ports.
default_port- default port to ... | 6276e23290b35762eeeddb98a6d60e97135d29c2 | 49,801 |
def even_fib(ceiling):
"""
Returns the sum of all even Fibonacci numbers not exceeding ceiling.
"""
total = 0
fg = Fibonacci()
n = next(fg)
while n <= ceiling:
if n % 2 == 0:
total += n
n = next(fg)
return total | ad9163d34bc57767336fef5171d26e2cd3339a08 | 49,802 |
import json
def get_table_columns(etcd_client, db, tbl):
"""
Get primary key column for table db.tbl.
:param etcd_client: Etcd client.
:param db: database name.
:param tbl: table name.
:return: Primary key column.
:rtype: ColumnSet
:raise ProgrammingError: if table or database doesn't... | 091fe315cc7ad83af93e710cdf18526640fd6ed2 | 49,803 |
def _flatten_multiplicand_list(kernels):
"""Flatten a list of kernels which may contain _ProductKernel instances.
Args:
kernels: Python list of `PositiveSemidefiniteKernel` instances
Returns:
Python list containing the elements of kernels, with any _ProductKernel
instances replaced by their `kernels... | d5a2700795b634fb2861998bc842df653456258b | 49,804 |
def parse_bool_token(token):
"""
Parses a string token to convert it to its equivalent boolean value ignoring
the case of the string token or leaves the token intact if it cannot.
:param token:
String to convert to ``True`` or ``False``.
:type token:
``str``
:return:
``T... | bd9de30ee85921ba72a46e83eb96a0af104f998d | 49,805 |
from typing import Union
import abc
def dictionary_writable(
model: Union[type, abc.Dictionary]
) -> abc.DictionaryHooks:
"""
Retrieve a metadata instance. If the instance currently inherits its
metadata from a class or superclass, this function will copy that
metadata and assign it directly to th... | e0f60c42ae8d9a2eabc3b2ec4fb24bef52fcf8b3 | 49,806 |
import torch
def log_prb_1l_per_smpl(x, ls):
"""
x=log(P) is a list of log probability tensors, and it has shape
(batch_size, number_of_classes + 1, other dimensions like time, ...)
ls is a list of labels with the same length as x.
Each sample has one label in range [0, number_of_classes)
... | ad71c0fca4dea7e830db343acba296123e8e277d | 49,807 |
def func_PS_Level(HA_Open, HA_Close, PS_pct_level=[0.35, 0.5, 0.95, 0.97], combine=False):
"""
0. This function is for calculating the HA bars' bar size level, or called Price Status(PS).
1. This function has 4 arguments and return 2 arrays as output.
2. Input arguments including:
(1) HA_Open: D... | 3a2f9a9d200e800b0e314df7f01e4a3affa155d7 | 49,808 |
def angle(x0, x1):
"""Compute the angle between two vectors x0, x1 using the dot product"""
mx0 = np.dot(x0, x0)
mx1 = np.dot(x1, x1)
return np.arccos(np.dot(x0,x1)/np.sqrt(mx0*mx1)) | 18b43c43e41d3ffb27c985f7338ea635f4f80cd8 | 49,809 |
import scipy
def grubbs(timeseries, end_timestamp, full_duration):
"""
A timeseries is anomalous if the Z score is greater than the Grubb's score.
"""
try:
series = scipy.array([x[1] for x in timeseries])
stdDev = scipy.std(series)
# Issue #27 - Handle z_score agent.py Runtim... | 14d05c35e65880ff7bdee9afc571ba173a814741 | 49,811 |
def _spatial_proximity(data, group_pop_var, total_pop_var, alpha=0.6, beta=0.5):
"""Calculate Spatial Proximity index.
Parameters
----------
data : a geopandas DataFrame with a geometry column.
group_pop_var : string
The name of variable in data that contains the popula... | ba365819e1eef61c1042587a0e9370989752354b | 49,812 |
def video_content_to_dict(vid_info_list):
"""Convert YouTube metadata list to dictionary."""
video_dict = {}
for video in vid_info_list:
if not video:
continue
title = video["title"]
video_dict[title] = {"id": video["id"], "duration": video["duration"]}
return video_d... | e56b211e9879ce783a8b145f267778dcaa0550b9 | 49,813 |
import requests
def getwcs(dataset, applyomega=True, service="https://hla.stsci.edu/cgi-bin/fitscut.cgi"):
"""Return dictionary with WCS information for an image.
Parameters
----------
dataset : str
dataset name
applyomega : bool, optional
Apply HSC correction? Default value = Tr... | 43d22dba3e8d882961deff5856361900f9ec8e68 | 49,814 |
import six
def get_redis_from_settings(settings):
"""Returns a redis client instance from given Scrapy settings object.
This function uses ``get_client`` to instantiate the client and uses
``defaults.REDIS_PARAMS`` global as defaults values for the parameters. You
can override them using the ``REDIS_... | 03c555612aa67be6c3197cfd4c51a7145184436e | 49,815 |
import wget
async def download(uri):
"""
Guarda en el disco duro un archivo indicado por una URI
Parámetro:
> uri (str, por ejemplo 'http://www.inspyration.org/logo.png')
Retorno:
> contenido de un archivo (bytes, archivo de texto o binario)
"""
content = wget(uri)
if content is ... | a2668b3182267bf2264bac382013f7fd9c0d4294 | 49,816 |
def print_symbol_table_node_to_dot(node, cur_id):
"""
Print the node of a symbol table as html table
:param node: symbol table
:param cur_id: current node id
:return: dot string
"""
dot = "\t{} [\n\t shape=plaintext \n \tlabel=< <table border=\'0\' cellborder=\'1\' cellspacing=\'0\'\n\t>".fo... | d4a1b2dcb8bbc971d8100e74f2c887ce452cd1b9 | 49,817 |
def create_getter(var_name):
""" Given the string name of a variable, creates a getter function for that
variable and returns it.
Args:
var_name the name of the variable for which a getter should be created.
"""
def getter(self):
""" The getter function to be returned."""
return geta... | 7091280d2a804d818247ffcfa9e55c0d98bfe761 | 49,818 |
def James_Stein_estimator(data, std_noise):
"""
See Large-scale inference: empirical Bayes methods for estimation, testing, and prediction (Efron, 2010, page 6)
"""
mean_data = np.mean(data)
dev = sum((data - mean_data) ** 2)
return mean_data + (1 - (len(data) - 3) * (std_noise ** 2) / dev) * (d... | 69db35bbeb65047b4c301bce673d11f7ddf51759 | 49,819 |
def predict_by_moving_avg_growth(stock, s, **_):
"""Returns predicted value of a stock
Predicts the next price of a stock by extrapolating the moving average and its growth.
Parameters
----------
stock : :obj:`stock`
Stock to be predicted.
s : int
Number of data points used to... | c8e02b9c55bd339ff6f1793b697ba46647331326 | 49,820 |
from typing import Union
import types
def get_admin_log(peer: Union[int, str] = None) -> list:
"""
Get a list of logs from the admin-logs. This method gets 'Join' and 'Leave' events by default, but you can
uncomment the commented items and add them to your result list.
:param peer: Union: [id, usern... | 704a277eb9e1fde3cd119d5e3b7f73ffcc4e578a | 49,822 |
def from_networkx(G):
"""
Convert a NetworkX graph into a Zen graph object.
In creating the object, the NetworkX node object and node/edge data will be copied over (a shallow copy).
**Returns**:
The return type depends on the input type.
* :py:class:`zen.Graph` if the input graph was a :py:class:`network... | e320a20749be2b9b99d90a1f8164706073f0593b | 49,823 |
def find_subpixel_peak_position(corr, subpixel_method='gaussian'):
"""
Find subpixel approximation of the correlation peak.
This function returns a subpixels approximation of the correlation
peak by using one of the several methods available. If requested,
the function also returns the signal ... | b915e6a2e1c71aa36d8423bb31ce2b625878ae38 | 49,824 |
def _vec_to_triu(vec):
"""Take vec and forms strictly upper triangular matrix.
Parameters
----------
vec : array_like, shape[..., n]
Returns
-------
tril : array_like, shape=[..., k, k] where
k is (1 + sqrt(1 + 8 * n)) / 2
"""
n = vec.shape[-1]
triu_shape = vec.shape + ... | 8c5af1ad5089614280c048a84c572c04a958369e | 49,826 |
import zlib
import base64
def _compress(s: bytes):
"""
Compresses bytes for the payload.
"""
co = zlib.compressobj(wbits=-zlib.MAX_WBITS)
b = co.compress(s) + co.flush()
return base64.b64encode(''.join(map(chr, b)).encode()) | 6c6f1b04670c55f0417991fd3f9ab19ad42fefec | 49,827 |
def render_Board_members_list_overlay(self, h, comp, *args):
"""Overlay to list all members"""
h << h.h2(_('All members'))
with h.form:
with h.div(class_="members"):
h << [m.on_answer(self.handle_event, comp).render(h) for m in self.all_members]
return h.root | b818413dd28bac3043e1b83b83b1d7abf07416f3 | 49,828 |
def _token_to_int(t, token_list, token_cache, size_limit=float('inf')):
"""Return the int which represents a token, with caching.
Throws a ValueError if token t is not in the token_list. There MUST
be a _UNK token at the beginning of your vocab, or this may not halt.
"""
if t not in token_cache:
... | d2a46135197c38ff6ab08336fba9a4970fe6952f | 49,829 |
def select_data(df, countries_list, regions_list, ages_list, genders_list):
"""Extracts from the dataset the data corresponding to many criterias.
Parameters:
-----------
df : Pandas DataFrame
dataset
countries_list : list of str
countries to be selected
regions_list : ... | de6e24966f3060728657a4cc6685c8203bfa85e7 | 49,831 |
def revescape(text):
"""Any text. Escapes all "special" characters, except @.
Forward slashes are escaped twice to prevent web servers from prematurely
unescaping them. For example, "@foo bar/baz" becomes "@foo%20bar%252Fbaz".
"""
return urlreq.quote(text, safe=b'/@').replace(b'/', b'%252F') | 227f420bb6f6c625f5f3b9be2d8142240a2c726d | 49,832 |
from typing import cast
def intersect1d(pda1 : pdarray, pda2 : pdarray,
assume_unique : bool=False) -> pdarray:
"""
Find the intersection of two arrays.
Return the sorted, unique values that are in both of the input arrays.
Parameters
----------
pda1 : pda... | 8062173a51ecbec1933787de94e451c9f668165f | 49,833 |
import re
import io
def _remove_unicode_encoding(xml_file):
"""
attempts to remove the "encoding='unicode'" from an xml file
as lxml does not support that on a windows node currently
see issue #38100 (Search.adml)
For some reason this file is encoded 'utf-16'
"""
with salt.utils.files.fo... | b40cf886dca7932ccfeb75738d4ced2db6909bea | 49,834 |
def add_data_reference(enc_key, enc_data):
"""Add DataReference to ``enc_data`` in ReferenceList of ``enc_key``.
``enc_data`` should be an EncryptedData node; ``enc_key`` an EncryptedKey
node.
Add a wsu:Id attribute to the EncryptedData if it doesn't already have one,
so the EncryptedKey's URI att... | 7d3d9cfabe9a645782ec58224a7824f7ec159fa8 | 49,835 |
from typing import Sequence
from typing import Any
from typing import List
from typing import Dict
def _get_items_as_rows(items_to_add: Sequence[Any], batch_number: int,
result: str, operation: str,
timestamp: str) -> List[Dict[str, Any]]:
"""Adds Content API results to... | 70bc2976b0c47f7a66dea472599ba54a60702268 | 49,836 |
from ba import _error
def get_available_purchase_count(tab: str = None) -> int:
"""(internal)"""
try:
if _ba.get_account_state() != 'signed_in':
return 0
count = 0
our_tickets = _ba.get_account_ticket_count()
store_data = get_store_layout()
if tab is not Non... | 1b0d6afc0b9ba6a5d7ace211082d63dccefe8cae | 49,838 |
def textops_rawtexttolines(text, linedelimiter="\n"):
"""
<Purpose>
Converts raw text (a string) into lines that can be processed by the
functions in this module.
<Arguments>
text:
The text to convert into lines (basically, a sequence of strings).
linedelimiter (optional, defaults to... | e146180f3dc02a036e84cbb04b5a4fd90b85abe8 | 49,839 |
import re
def get_display_name(skill_name: str):
"""Splits camelcase and removes leading/trailing "skill"."""
skill_name = skill_name.replace("_", " ").replace("-", " ")
skill_name = re.sub(r'(^[Ss]kill|[Ss]kill$)', '', skill_name)
return camel_case_split(skill_name).title().strip() | 8e0cbfde49b6b6d7568084711bea31b7c75af05f | 49,840 |
import pathlib
from typing import Tuple
def generate_images(*, path: pathlib.Path) -> Tuple[files.File, ...]:
"""
Get the assets images to create.
Args:
path: the destination path for the images.
Returns:
A tuple of the images to create.
"""
images = assets.get_images()
r... | 72ca85feaf1dbe1fdb6128b194683d7e46f0a260 | 49,841 |
from datetime import datetime
def timestamp2datetime(value):
"""
将一个时间戳值转换为系统所在时区的日期时间实例
"""
return timezone.make_aware(datetime.fromtimestamp(value)) | e4fd2eaf7c8404ee0d1c9f817ebbcc0c2367d22e | 49,842 |
from typing import List
def generate_eagle_track(
conductivity: np.ndarray,
potential: np.ndarray,
start_loc: List[int],
dirn_restrict: int,
nu_par: float
):
""" Generate an eagle track """
num_rows, num_cols = conductivity.shape
burnin = 200
max_moves = num_ro... | 47a82e40ca85031c93b37999fdf75558fbb6eb0e | 49,843 |
def _expm_vjp(exp_matrix, matrix):
"""
Construct the left-multiplying vector jacobian product function
for the matrix exponential.
Intuition:
`dfinal_dexpm` is the jacobian of `final` with respect to each element `expmij`
of `exp_matrix`. `final` is the output of the first function in the
b... | f2e75e92aa0877bab8788015f079d58ba07e5fa0 | 49,844 |
def precook(s, n=4, out=False):
"""
Takes a string as input and returns an object that can be given to
either cook_refs or cook_test. This is optional: cook_refs and cook_test
can take string arguments as well.
:param s: string : sentence to be converted into ngrams
:param n: int : number of ... | 72d75158a21ae84b9c76ef09663a1db866821c9e | 49,845 |
def motorcycle_data():
"""
The motorcycle dataset where the targets are normalised to zero mean and unit variance.
Returns a tuple of input features with shape [N, 1] and corresponding targets with shape [N, 1].
"""
df = pd.read_csv("./data/motor.csv", index_col=0)
X, Y = df["times"].values.resh... | 07312be5992029aa5bdd8951ba257944ce4b6f45 | 49,846 |
def get_class_distribution(y):
"""Calculate number of samples per class."""
# y_cls can be one of [OH label, index of class, class label name string]
# convert OH to index of class
y_cls = flatten_y_if_onehot(y)
# y_cls can be one of [index of class, class label name]
classset = sorted(list(set(... | 2005c17361d971dbb5f04e767fe6896c7cea1d0e | 49,847 |
from re import S
def gamma_at_2_coefficient(k):
"""Reference: https://dlmf.nist.gov/5.7#E3"""
if k == 0:
return S(0)
elif k == 1:
return S(1 + digamma(1))
else:
return ((-1)**k*(zeta(k) - 1)/k) | 4779e30a55ea0a90a501b8f6db1df141e7fe3f2f | 49,848 |
def unverified_user(error):
"""Displays the front page with an error that the user must verify their
email before accessing data.
"""
messages = {
"Email Unverified": [
"Please complete the sign up process by verifying your "
"email account. You should receive a verificat... | a1127547f0d7bcf08a63f67f42c07170a04c8ecf | 49,850 |
import torch
def initialize_sampler_lp_(g, batch_size, args, target_idx, evaluate_panrep =False):
""" When lp is used different loader is required """
full_node_list = torch.arange(g.number_of_nodes())
target_uns = torch.arange(g.number_of_nodes())
val_pct = 0.1
use_cuda = args.gpu >= 0 and torch... | 15c86f3057b1099195dd873e6fecbe4fd840fae7 | 49,851 |
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