content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def openl1(*args, **kwargs):
"""
Open(*args, **kwargs)
Returns a file object opened with UTF-8 encoding.
"""
kwargs["encoding"] = "latin1"
return _open(*args, **kwargs) | cdb9cf8b1edf3dee8a50ba4d2c18a0c2a0ec91c2 | 70,900 |
import threading
import os
import time
import sys
def print_stacktraces (signum=None, sigframe=None) :
"""
signum, sigframe exist to satisfy signal handler signature requirements
"""
this_tid = threading.currentThread().ident
# if multiple processes (ie. a process group) get the signal, then all... | ec396901f2e04e07b8899a535d482cab9f80fc0c | 70,901 |
import warnings
import tqdm
def read_edf(edf_file, ch_nrs=None, ch_names=None, digital=False, verbose=False):
"""
Convenience function for reading EDF+/BDF data with pyedflib.
Will load the edf and return the signals, the headers of the signals
and the header of the EDF. If all signals have the same ... | e236c051babe8f291fe91b4b339e11f79801324b | 70,902 |
def check_num_samples(beta, delta, std_dev, alpha=0.05, n=4, num_iter=1000,
tol=1e-6, num_cycles=10000, m=5):
"""
This function is an implementation of the "Calculation of Number of Samples
Required to Detect a Trend" section written by Sat Kumar Tomer
(satkumartomer@gmail.com) whi... | 9445a6fbcaf38a2d2119706e98e1b3bc6f2b5dd6 | 70,903 |
def calc_OR_from_list(dict_node_age, infected_nodelist):
""" Calculate OR from list of infected nodes. Return OR as 1.0 if numerator or denominator are 0.
"""
main(calc_OR_from_list)
infected_child = sum([1 for node in infected_nodelist if dict_node_age[node] == '3'])
infected_adult = sum([1 for node in infected... | 59c580c439236b042dbf0127ef70ecb8b48f2e03 | 70,904 |
def __validate_username(username: str, error_msg: str) -> str:
"""Validate the tweet's name.
Parameters
----------
username : str
Tweet's username.
error_msg : str
Error message to display for an invalid username.
Returns
-------
str
Validated username.
Rai... | b829251070b8ba657a60597547601376fa051607 | 70,905 |
def frequency(per_core=True, scale="mhz", precision=3):
"""Returns current cpu frequency
:Params:
:per_core (bool): When per_core is True it returns a list with values per logical cpu,
if it's set to False returns a float with arithmetic mean of cores
... | 6077478802e6257eb62fff1e95b04254db1458f8 | 70,906 |
from typing import List
from typing import Tuple
from textwrap import dedent
def get_rt_object_to_complete_texts() -> List[Tuple[str, str]]:
"""Returns a list of tuples of riptable code object text with associated completion text."""
return [
(
dedent(
'''Dataset({_k: list(... | 007d2291fd922aab5627783897a56cd5fd715f98 | 70,907 |
import token
import requests
def create_mirror(gitlab_repo, github_token, github_user):
"""Creates a push mirror of GitLab repository.
For more details see:
https://docs.gitlab.com/ee/user/project/repository/repository_mirroring.html#pushing-to-a-remote-repository-core
Args:
- gitlab_repo: Git... | 2a5d7e01ca04a6dcb09d42b5fc85092c3476af0d | 70,908 |
def abordar_nave():
"""
-Ubica dentro de la nave a los tripulantes y al robot
-Devuelve la nave con todos abordo
"""
nave = [TRIPULANTE for tripulante in range(CANTIDAD_TRIPULANTES)]
nave.insert(randint(0, CANTIDAD_TRIPULANTES - 1), ROBOT)
return nave | a1ecf63cb92a25d897d1ca3597e22624e1d9b59e | 70,909 |
def STYPP(data):
"""
Swing Typical Price
Previous Typical Price
:param pd.DataFrame data: pandas DataFrame with open, high, low, close data
:return pd.Series: with indicator data calculation results
"""
stypp_list = []
typical_price = TYPPRICE(data)
i = 0
while i < len(data['cl... | 36bacb8f77c8645483da0cf3dddb10dc23dd6eef | 70,910 |
def log_encoding_Log2(lin,
middle_grey=0.18,
min_exposure=0.18 * 2 ** -6.5,
max_exposure=0.18 * 2 ** 6.5):
"""
Defines the common *Log2* encoding function.
Parameters
----------
lin : numeric or array_like
Linear data to un... | 24549942553a792073cf059a9e1057df4dd4e10d | 70,911 |
import uuid
import json
from datetime import datetime
def add(queue_name, payload=None, content_type=None,
source=None, task_id=None):
"""Adds a work item to a queue.
Args:
queue_name: Name of the queue to add the work item to.
payload: Optional. Payload that describes the work to do ... | 9dbdc0fc384732b47f857fa65edc2302ed6f110b | 70,912 |
def index():
"""
Test the compatibility
This is just a test for flasgger 0.5.14 compat
---
parameters:
- in: body
name: body
schema:
id: alert
properties:
message:
type: string
produces:
application/json
responses:
... | 9757e42a61d11c4b5cea2ea4adb13c93b57fbbcc | 70,913 |
def is_permutation(a, b):
"""
Test if the digits of a are a permutation of the digits of b
"""
digits_a = sorted(get_digits(a))
digits_b = sorted(get_digits(b))
if len(digits_a) != len(digits_b):
return False
for da, db in zip(digits_a, digits_b):
if da != db:
re... | 4216e55cfad2a80ffb68f9420e02eec255d6af5a | 70,914 |
def get_tcga_id( string_to_check , get_full_tcga_id):
""" will either return the TCGA-12-3456 or the entire TCGA sample ID which is much much longer... TCGA-12-3456-12-23-232-32"""
if(get_full_tcga_id):
m = parse_full_TCGA_ID.match(string_to_check)
if m:
TCGA_FULL_ID = m.group(1)+'-'+m.group(2)+m.grou... | 14c16a9899c9bd31a7b883391c13850ccf0ef752 | 70,915 |
import json
def make_lld(msa, component, sessionkey, pretty=False):
"""
Form LLD JSON for Zabbix server.
:param msa: MSA DNS name and IP address.
:type msa: tuple
:param sessionkey: Session key.
:type sessionkey: str
:param pretty: Print output in pretty format
:type pretty: int
:... | fd458ef492e9ee5b5d5496325a0c7efadd717d29 | 70,916 |
def stats_for_chapter_levels(chapter_id):
"""
Return a list of level names in a chapter and a list of students and their progress for all
levels in requirement chapter. The data is meant to be displayed in a table.
Since there's a unique entry for every student->level match we first need to create a cle... | 6c360640921eaa4fb626362db5d3d3ac0aaa43eb | 70,917 |
import random
def generate_mac_address():
""" randomly generate a mac address, the first three bytes identify a manufacturer"""
prefix = manufacturer_mac_address[random.randint(0, len(manufacturer_mac_address)-1)]
mac = prefix+\
[random.randint(0x00, 0xff),
random.randint(0x00, 0xff),
random... | 5369c6c3a0f9ddbc19c109ce50ab870ff5aa3a3a | 70,918 |
def drop_info(df: pd.DataFrame) -> pd.DataFrame:
"""Takes a dataframe and drop rows whitout an splitted `info`
length diferrent than four.
Parameters
----------
df :
The dataframe to search.
Returns
-------
The dataframe processed.
"""
before = df.shape
print(f'Shap... | b3701830b6310ece2ace3138e531be044bc19d4b | 70,919 |
def read_CSET_data(fname, var_list=None,
start_date=None, end_date=None):
"""read in CSET UHSAS .nc file and returns requested variables
"""
with nc4.Dataset(fname, 'r') as nc:
timevar = nc.variables['Time']
date = nc4.num2date(timevar[:], units=timevar.units)
if ... | 940d7740e8105b11c5d3ce94cc2b42c821779ea3 | 70,920 |
def expon_round(a: float, prec: int = None) -> float:
"""Rounds the left part of a two-part float."""
if type(a) != float:
return a
if "e" not in str(a):
return round(a, prec)
sig, exp = str(a).split("e")
return float("%se%s" % (round(float(sig), prec), exp)) | 8ccafd58dd674c2351e02f50dc5bd65d88b4fd63 | 70,921 |
def genelist_mask(candidates, genelist, whitelist=True, split_on_dot=True):
"""Get a mask for genes on or off a list
Parameters
----------
candidates : pd.Series
Candidate genes (from matrix)
genelist : pd.Series
List of genes to filter against
whitelist : bool, default True
... | 53e1f80de097311faddd4bfbff636729b076c984 | 70,922 |
def add_polynomials(indices_list, coeffs_list):
"""
Add many polynomials together.
Example:
p1 = x1**2+x2+x3, p2 = x2**2+2*x3
p3 = p1+p2
return the degrees of each term in the the polynomial
p3 = x1**2+x2+3*x3+x2**2
[2, 1, 1, 2]
and the coefficients of eac... | 53227650c983c846fb3b53751fe301480086f27d | 70,923 |
def softmax_with_cross_entropy(preds, target_index):
"""
Computes softmax and cross-entropy loss for model predictions,
including the gradient
Arguments:
predictions, np array, shape is either (N) or (batch_size, N) -
classifier output
target_index: np array of int, shape is (1) or ... | 32665f7ffecc003814a80083d887def033c95ffd | 70,924 |
from datetime import datetime
def writenow():
"""Return utcnow() as ISO foramat string"""
return datetime.isoformat(datetime.utcnow()) | 19a0e4653bfa7cfab2528e81317fd2399ca630d5 | 70,925 |
def plate_msup():
"""Resolve the path of the "msup/plate1.rst" result file.
Originally:
UnitTestDataFiles/DataProcessing/expansion/msup/Transient/plate1/file.rst
"""
return examples.msup_transient | 3052ff7b5a2399cf80da91266daeae1bede0fb49 | 70,926 |
def _drop_noisy(points: DataFrame) -> DataFrame:
"""
Filter the outlier points in the data by delete the points lower than a certain area.
"""
df_copy = points.copy()
df_describe = df_copy.describe()
for column in points.columns:
mean = df_describe.loc["mean", column]
std = df_de... | 9da845e0b03622486d5cb1cfd2272c874dbbc58f | 70,927 |
from django.contrib.gis.utils import GeoIP
def location(request):
"""
Location selection of the user profile
"""
profile, created = Profile.objects.get_or_create(user=request.user)
geoip = hasattr(settings, "GEOIP_PATH")
if geoip and request.method == "GET" and request.GET.get('ip') == "1":
... | 85a9138b6f9fc3f13d1bf3f5789865fac0e5d82b | 70,928 |
def parse_releases(list):
"""
Parse releases from a MangaUpdate's search results page.
Parameters
----------
list : BeautifulSoup
BeautifulSoup object of the releases section of the search page.
Returns
-------
releases : list of dicts
List of recent releases found by t... | e7e93130732998b919bbd2ac69b7fc36c20dd62d | 70,929 |
def generate_ignore_database_tables():
"""
Generate the ignore tables options for the mysqldump command by the given table list
# ToDo: Too much conditional nesting
:return: String
"""
_ignore_tables = []
if 'ignore_table' in system.config:
for table in system.config['ignore_table']:... | aa802819e20caff4b885420560a92d96c49574cb | 70,930 |
def remMap(matrizX, matrizY, l_1, l_2, tmax):
"""
Esta funcion implementa el algoritmo remap considerando lambda2 diferente de cero.
Args:
:param matrizX: matriz de datos de tamano n x p.
:param matrizY: matriz de variables respuesta de tamano n x q.
:param l_1: parametro de regularizacion lamb... | cd5d3b5928db66f7cf6e7e9a5ffdaf6c9fd88e0f | 70,931 |
def cal_fuquan_price(input_stock_data, fuquan_type='后复权'):
"""
计算复权价
:param input_stock_data:
:param fuquan_type:复权类型, 可以是'后复权'或者'前复权'
:return:
"""
# 创建空的df
df = pd.DataFrame()
# 计算复权收盘价
num = {'后复权': 0, '前复权': -1}
price1 = input_stock_data['收盘价'].iloc[num[fuquan_type]]
... | bcfc5a7f506eebcb7d793b95c9387f6cda4e41e2 | 70,932 |
def read_data_with_ref(source_path, target_path, ref_path):
"""Read sentences and parallel sentence references."""
with open(source_path, "r", encoding="utf-8") as source_file,\
open(target_path, "r", encoding="utf-8") as target_file:
source_lines = [l for l in source_file]
targ... | 1ce3d768ddb5d4de0f72cbe0633dfafe20bdc2c0 | 70,933 |
import http
def update_draft_registration(auth, node, draft, *args, **kwargs):
"""Update an existing draft registration
:return: serialized draft registration
:rtype: dict
:raises: HTTPError
"""
check_draft_state(draft)
data = request.get_json()
schema_data = data.get('schema_data', ... | d614214ca420ae97a7290e57f888e1d96bd3b631 | 70,934 |
def user_repository_spy():
"""Fixture para montar o objeto UserRepository"""
return UserRepositorySpy() | b184a2485a46a6e7615b4c931b8279f6f1f5de96 | 70,935 |
def to_rates(trace, kmin, kmax):
"""covert a trace of normalized values into kinetic rates in log space which are wihtin kmin and kmax"""
lkmin = np.log10(kmin)
lkmax = np.log10(kmax)
x = (lkmax - lkmin) / 100
log_rates = trace*x + lkmin
rates = 10**log_rates
return rates | a4d44fef877ce95cd254eb13af4d4bbc09a1ffd2 | 70,936 |
import requests
def get_req(url, referer, arg_proxy_local, proxies={}):
"""Get binary data from URL"""
print('url= '+ url)
#data = ''
#or chunk in requests.get(url, headers={'User-agent': 'Mozilla/5.0'}, stream=True):
# data += chunk
parsed_uri=urlparse(url)
domain = '{uri.netloc}'.form... | 5883ec11901ccdcd3c6f795349267f6b284c838a | 70,937 |
def dummy_rng_source(seed, num_elements):
"""Dummy TensorFlow random number generator.
We need a custom random source, which would be always deterministic given a
random seed. That is not currently available available in TensorFlow. This
simple function serves an illustrative purpose. It is *not* a useful rand... | 45bec9a89d4b0e66f2fff3ef011c13bf0855523d | 70,938 |
def softmax(x):
""" Softmax function with input vector x """
exp_x = npexp(x)
exp_sum = sum(exp_x)
smax = exp_x / exp_sum
return smax | 4c5d25f43cddbaf18c36ef0f04392f9a35708abb | 70,939 |
import os
import shutil
def multiprocess_move_and_filter_reads(in_dir, out_dir, alignment_file, readdb, trim=False,
quality_threshold=7, worker_count=1, debug=False):
"""Multiprocess for filtering reads
:param in_dir: input directory with subdirectories assumed to have f... | 36dfcfd27c722ace30158a612b5b62ea19f1ee2b | 70,940 |
def PinpointParamsFromPerfTryParams(params):
"""Takes parameters from Dashboard's pinpoint-perf-job-dialog and returns
a dict with parameters for a new Pinpoint job.
Args:
params: A dict in the following format:
{
'test_path': Test path for the metric being bisected.
'start_commit': Git h... | 2ab36846aa2a6416fccd4f5edd0c92dbdf31d675 | 70,941 |
def _linkify(value):
"""create link format"""
out = []
for link in value:
out.append(','.join(list(link)))
return '^'.join(out) | 1fa2020148ef1fd7ba7f10eecb54836517ff0abd | 70,942 |
import json
def objects_processing(target: str) -> Response:
"""
Apply object detection or segmentation on on image
Parameters
----------
target: str
'segmentation' for semantic segmentation. Return response with RLE masks.
'detection' for object detection. Return respo... | 05ae8cc42bd4187a08a3833a7c7e7b81827da270 | 70,943 |
def date_to_month_st(date):
"""Returns a string representing the month with MONTH_FORMAT."""
return date.strftime(MONTH_FORMAT) | c132475e895f826493ff5c1d139a237add82b934 | 70,944 |
def butter_lowpass(cutoff, fs, order=5):
"""
Design lowpass filter.
Args:
- cutoff (float) : the cutoff frequency of the filter.
- fs (float) : the sampling rate.
- order (int) : order of the filter, by default defined to 5.
"""
# calculate the Nyquist frequency
n... | 6befd134b069154f6fd40c840dbb4fee032e2103 | 70,945 |
def shape9(tik_instance, input_x_shape, input_x, res):
"""shape9"""
total_elements9 = 1
for val in input_x_shape:
total_elements9 *= val
blocks = 32
each_block_element = total_elements9 // blocks
with tik_instance.for_range(0, blocks, block_num=blocks) as block_index:
input_x_ub ... | ae18605bd1309f30d4f8c506bbe3c6fa5cef8a1c | 70,946 |
def remove_arena_env_prefix(env):
"""Remove ARENA_ENV_PREFIX from a env (possibly a grid_search).
"""
env = dcopy(env)
if is_grid_search(env):
if is_all_arena_env(env):
for i in range(len(env["grid_search"])):
env["grid_search"][i] = remove_arena_env_prefix(
... | 63c3f23af41583e2c941f154a9347b204a4ed400 | 70,947 |
import sys
def getsize(obj):
"""sum size of object & members."""
if isinstance(obj, BLACKLIST):
raise TypeError('getsize() does not take argument of type: '+ str(type(obj)))
seen_ids = set()
size = 0
objects = [obj]
while objects:
need_referents = []
for obj in objects:... | 8bbbdb781a394aced808c3a81db210f65c59cc34 | 70,948 |
from scipy.ndimage import convolve1d
def move_nansum_filter(arr, window, axis=-1):
"""
Moving sum (ignoring NaNs) along specified axis using the filter method.
Parameters
----------
arr : array_like
Input array.
window : int
The number of elements in the moving window.
axi... | e53a0b48326a34f2faf9af000ea5fbff027c7ded | 70,949 |
def dict_raise_on_duplicates(ordered_pairs):
"""Reject duplicate keys."""
d = {}
for k, v in ordered_pairs:
if k in d:
# raise ValueError("duplicate key: %r" % (k,))
pass
else:
d[k] = v
return d | b1b539b137f70291332f949339501cc5b8e35397 | 70,950 |
import torch
def get_packed_sequence_info(packed):
"""Get `batch_sizes` and `sorted_indices` of `PackedSequence`.
Args:
packed (object): Packed sequences. If it contains multiple
`PackedSequence`s, then only one of them are sampled assuming that
all of them have same `batch_si... | f3540bfe63d5ef72ecb1df20e09dd249310508b7 | 70,951 |
import textwrap
def multisample_vcf():
"""Return string with multi-sample VCF"""
return textwrap.dedent(
"""
##fileformat=VCFv4.3
##contig=<ID=20,length=62435964,assembly=B36,md5=f126cdf8a6e0c7f379d618ff66beb2da,species="Homo sapiens",taxonomy=x>
##FORMAT=<ID=GT,Number=1,Type=S... | f7190d79580cba75a906aa06d29850bf32acf8b2 | 70,952 |
def _make_time_major(policy, tensor, drop_last=False):
"""Swaps batch and trajectory axis.
Arguments:
policy: Policy reference
tensor: A tensor or list of tensors to reshape.
drop_last: A bool indicating whether to drop the last
trajectory item.
Returns:
res: A tens... | b1b0933eeb7b99ddd07a52e3629fc83246723942 | 70,953 |
def ouverture_image(largeur, hauteur):
"""
génère la balise ouvrante pour décrire une image SVG des
dimensions indiquées. Les paramètres sont des entiers.
Remarque : l’origine est en haut à gauche et l’axe des Y est
orienté vers le bas.
"""
balise = "<svg xmlns='http://www.w3.org/2000/svg' v... | da53a8d8e45df8d54bb63dcf8f88b2465af486aa | 70,954 |
def get_pp_id(pp_id: PowerPlantIDT) -> PowerPlantID:
""" Unify format of provided power-plant identifier. """
if isinstance(pp_id, PowerPlantID):
return pp_id
elif isinstance(pp_id, tuple) or isinstance(pp_id, list):
return PowerPlantID(
pp_id=int(pp_id[0]),
inv_id=-1... | 56183f811e21539ee3ef3682e11149809725c0c8 | 70,955 |
import os
def subset_bed_by_chrom(in_file, chrom, data, out_dir=None):
"""Subset a BED file to only have items from the specified chromosome.
"""
if out_dir is None:
out_dir = os.path.dirname(in_file)
base, ext = os.path.splitext(os.path.basename(in_file))
out_file = os.path.join(out_dir, ... | 1102c62c08093b44a0093ae8b71cd131e4f04994 | 70,956 |
def productversion_details(request, productversion_id):
"""Get details snippet for a productversion."""
productversion = get_object_or_404(
model.ProductVersion, pk=productversion_id)
return TemplateResponse(
request,
"manage/productversion/list/_productversion_details.html",
... | cd196e9bee29d30088c6569c08d3cec5cb15f9a2 | 70,957 |
import numpy
def gen_doc_embedding(model, text):
"""
:param model:
:param text:
:return: 向量 [float] 注意它不能保证是float32 因为float32在python中是不存在的
当前实际值是 numpy.array(dtype=float32)
"""
words = [x for x in jieba.lcut(text) if x not in stopwords]
# print(words)
# vec = model.infer_vector... | 80777131a367b4f3bda3d9a7c5963776c80fc40a | 70,958 |
def not_found_error_handler(e: Exception) -> Response:
"""
Error handling function for HTTP 404 (NOT FOUND); raised when a nonexistent
resource is requested
:param e: exception instance
:return: JSON response object
"""
# noinspection PyUnresolvedReferences
return json_response(
... | 1b1c7559d9a4631c1fc70e84a4e465075243d022 | 70,959 |
import math
def get_box_transformation_matrix(box):
"""Create a transformation matrix for a given label box pose."""
tx,ty,tz = box.center_x,box.center_y,box.center_z
c = math.cos(box.heading)
s = math.sin(box.heading)
sl, sh, sw = box.length, box.height, box.width
return np.array([
... | f7a175180c7baa8918dd4d66e1fa6035fe8c5f1d | 70,960 |
def create_model(
input_shape=(224, 224, 3),
conv_list=[(2, 64), (2, 128), (3, 256), (3, 512), (3, 512)],
dense_list=[4096, 4096, 1000],
kernel_size=3,
strides=1,
pool_size=2,
dropout_rate=0.1,
output_activation='sigmoid',
layer_activation='relu'):... | 47841d07f7257726639b50ac14cca865938b46df | 70,961 |
def _forward_one_ova(tr_class_idx, multi_ova, test_x, verbose):
"""Perform forward on an OVA classifier.
Parameters
----------
tr_class_idx : int
Index of the OVA classifier.
multi_ova : CClassifierMulticlassOVA
Instance of the multiclass OVA classifier.
test_x : CArray
... | 12b9fc29cbfa531465ad9c4e88d3b7c3bd2d2dad | 70,962 |
def GetMappingByKeyName(key_name):
"""Returns a str used to uniquely identify a mapping."""
return RunSiteMap.get_by_key_name(key_name) | f3106def7ef6830ce5adad7ea6853c56965e36e4 | 70,963 |
def bot_has_role(item: int) -> AC:
"""Similar to :func:`.has_role` except checks if the bot itself has the
role.
This check raises one of two special exceptions,
:exc:`.ApplicationBotMissingRole` if the bot is missing the role,
or :exc:`.ApplicationNoPrivateMessage` if it is used in a private messa... | b75c96f8b119610abf9d6992e2bbd46a32e4d983 | 70,964 |
def rotate_vector_with_rpy(orientation_rpy, vec):
"""Rotate a vector with a given rpy orientation (roll, pitch, yaw)"""
quat = convert_rpy_to_quat(orientation_rpy)
return rotate_vector_with_quaternion(quat, vec) | af1b726dec5571e0a914f01d5ea79630dfe9a3c7 | 70,965 |
import torch
def signed_scaled_shift(x, x_ref, dev='cpu', topology='torus', iters=1000, lr=1e-2, learn_scale=True):
"""
Shift trajectory, with scaling, reflection and translation.
Shift trajectories to be as close as possible to each other, including
switches in sign.
:param np.array th... | e423828ef900e0ba9cb1616b69c4e72f17876abb | 70,966 |
def theoretical_arrhenius(
data_arrhenius,
loaded_files,
column_t_name,
column_r_name,
theoretical_p_list,
):
"""Function that calculates r^2, T0, R0 parameters for theoretical p values from user's input.
Args:
data_arrhenius (list): list of DataFrames with calculated data for each ... | 191843b1c083966200a2469e00442ccbc1dcc2be | 70,967 |
def LHS(n,loc,upc,dist):
"""
Latin hypercube sampling.
Parameters:
n: integer; size of desired sampling
loc: scalar; lower bound of desired distribution
upc: scalar; upper bound of desired distribution
dist: string; either 'uniform' or 'normal'
Returns:
lhs:... | b7d65c64573ea4825850e4c306ec50a11c1bf885 | 70,968 |
def list_size_reducer(reduction_factor, your_list):
"""_summary_
Parameters:
reduction_factor (int): _description_
your_list (list): _description_
Returns:
reduced_list (_type_): _description_
"""
# input type checking
assert type(reduction_factor) == int, 'reduction_fact... | 0ed7dbff4a0b27146ffa1f44ce9e517bc4c632b0 | 70,969 |
from typing import Union
def create_doc_from_template(
template_url: str,
service_account_key: Union[str, dict],
copy_title: str = None,
**template_vars,
) -> str:
"""Create a doc and render it from the template Google document."""
# Step 1: Define the transaction
requests = []
for key... | 297b57770812b524cc754cb2d091a38034c667fd | 70,970 |
def optimize_helix_simple(n_particle_bb, sigma, epsilon, sidechain=True, DE_popsize=50,
pdbfile='LJ_helix.pdb', plotfile='LJ_helix.pdf'):
"""
Optimize backbone particle positions along a helix and helical radius, vertical rise,
with equal spacing of particles.
:param n_particle_bb: Number of ba... | d1886bff0b621c71a48569de91986486e1ecda07 | 70,971 |
from terracotta.expressions import evaluate_expression
from typing import Sequence
from typing import Mapping
from typing import Tuple
from typing import BinaryIO
def compute(expression: str,
some_keys: Sequence[str],
operand_keys: Mapping[str, str],
stretch_range: Tuple[Number, Nu... | 0a64618cea50fab5e69c288c9453df969275bbbd | 70,972 |
def bad_neighbours(values):
""" Maximize the values choosen from a circular list such that no two
values are neighbours.
See: http://community.topcoder.com/stat?c=problem_statement&pm=2402&rd=5009
for problem statement and test cases.
Params:
values: list, of integers
Returns:
... | 2410ca896bb36198e3df4a68de88d932a05b0c61 | 70,973 |
import re
def convert_parameters(child, text=False, tail=False, **kwargs):
"""
Get child text or tail
:param child:
:param text:
:param tail:
:return:
"""
p = re.compile(r'\S')
# Remove empty info
child_text = child.text if child.text else ''
child_tail = child.tail if chil... | de9ba60931516c7a51c5dd7411c914a110295fb2 | 70,974 |
def VectorObserver(vector, ofdate):
"""Calculates the geographic location corresponding to an equatorial vector.
This is the inverse function of #ObserverVector.
Given a geocentric equatorial vector, it returns the geographic
latitude, longitude, and elevation for that vector.
Parameters
-----... | aaf663ec398014d43e1df14707c2b7931fbc925f | 70,975 |
def QDA_g(x, means, covariances):
""" Determines the label of observation x using the K estimations of the mean
and covariance matrix of each cluster using Quadratic Discriminant Analysis
decision rule.
Parameters
----------
x : m-dimensional vector
... | 18346f75dbe4979269801b909ca767a2ed130ccc | 70,976 |
import os
def get_Y(path, wordset):
"""assume captche text is at the beginning of path
"""
basename = os.path.basename(path)
text = basename[0]
vec = text2int(text, wordset)
return vec | b827508538ac61d53e597104029e994eddf68f74 | 70,977 |
def window(timeColumn, windowDuration, slideDuration=None, startTime=None):
"""Bucketize rows into one or more time windows given a timestamp specifying column. Window
starts are inclusive but the window ends are exclusive, e.g. 12:05 will be in the window
[12:05,12:10) but not in [12:00,12:05). Windows can... | e18b030d6938f1e4bceef914e7bc4a4dfc2782f5 | 70,978 |
import requests
import json
def request_data(url: str, where_clause: str = "1=1") -> dict:
"""
Requests data from the ArcGIS api and retuens the response in JSON format.
"""
params = {
"referer": "https://www.mywebapp.com",
"user-agent": "python-requests/2.9.1",
"where": where... | 61ce82eb38f48805d62cdf8c9927f2607411281e | 70,979 |
def get_node_array(node, repo_path, name):
"""Retrieve a numpy array from a node."""
return utils.load_numpy_array_from_repository(repo_path, node.uuid, name) | fb526b429f6b7a09f7c9a7d3baab4377fcd2ea9d | 70,980 |
import struct
def _apple_bundle_version_impl(ctx):
"""Implementation of the apple_bundle_version rule."""
build_label_pattern = ctx.attr.build_label_pattern
capture_groups = ctx.attr.capture_groups
if (build_label_pattern and not capture_groups or
not build_label_pattern and capture_groups):
... | 763f57a850618de70d4c1a63f0f7f6c49f5afbcc | 70,981 |
def Sqrt(x):
"""Square root function."""
return x ** 0.5 | e726dfad946077826bcc19f44cd6a682c3b6410c | 70,982 |
def create_json_dataset(dic, sample_rate, window_size):
"""Creates JSON file for Voice Activity Detection.
Data are chunked in shorter clips of duration window_size"""
sessions_iteration = dic.keys()
example_counter = 1
json_dataset = {}
for sessions in sessions_iteration:
speech_timings... | 23cd1afd1f1fa009567127eccc0e7e3253bb15a0 | 70,983 |
def get_xml_root():
""" Gets the root of the arxiv xml tree and returns it."""
xml_filepath = '/home/ashwath/Files/arxiv-cs-all-until201712031.xml'
# xml_filepath = 'D:\\Coursework\\HiWi\\arxiv-cs-all-until201712031.xml'
doc = etree.parse(xml_filepath)
root = doc.getroot()
return root | 146e5436f494b24b5933fb9bf7bb3a96dda6ff5d | 70,984 |
import math
def _slerp(leds_xyz, n_led):
"""Interpolate positions from the xyz positon of the first and last LED
leds_xyz: np.array of shape(2,3)
n_led : total n LED on the stripe"""
p0, p1 = leds_xyz[0], leds_xyz[1]
omega = math.acos(np.dot(p0/np.linalg.norm(p0), p1/np.linalg.norm(p1)))
s... | b05bbfa7caa642c7d741d166cc4fa7ec21f64f50 | 70,985 |
def hello(friend_name):
"""Says 'Hello!' to a friend."""
return "Hello, {}!".format(friend_name.title()) | 706c5a2d3f7ebdf9c7b56e49bb0541655c191505 | 70,986 |
from typing import Optional
from pathlib import Path
import os
import shutil
import errno
def set_logger_dir(dir_name: Pathlike, action: Optional[str] = None) -> None:
"""
Set the directory for global logging.
:param dir_name: log directory
:param action: an action of ["k","d","q"] to be performed
... | 90999bacdbe232615205f5af87ac4a8b9027fc10 | 70,987 |
import os
from bs4 import BeautifulSoup
def view_list(request, category, language_code=None):
"""
Display all the available deeds and legal code for the given category.
"""
request.path, language_code = normalize_path_and_lang(
request.path, None, language_code
)
if language_code not i... | 36f5b49be0463a1826b56dbf860a6b7ba16feec3 | 70,988 |
import random
import string
import pathlib
import requests
import shutil
def proxy():
"""Proxies requests to the given OpenFaaS url
"""
error = False
url = request.cookies.get("openfaasurl")
if url is not None:
url = unquote(url)
url = urljoin(url, "function/")
url = urlj... | 85f29542f3cb0f6e508222bd37a55443f7f2a672 | 70,989 |
def _get_story_duration(story_tag):
"""
Return the sum of the text time and media time, or return None if not found
"""
try:
metadata = story_tag.find('mosExternalMetadata')
payload = metadata.find('mosPayload')
except AttributeError:
return 0
try:
return float(p... | df7f90eb6a02c0e8f9e6deaa45770fdc03c79a50 | 70,990 |
from sklearn.preprocessing import LabelEncoder
def plot_decision_function(fitted_classifier, range_features, ax=None):
"""Plot the boundary of the decision function of a classifier."""
feature_names = list(range_features.keys())
# create a grid to evaluate all possible samples
plot_step = 0.02
xx... | cbd792fe0af8f8032c5bb3ea2753c73be61414d7 | 70,991 |
import numpy
def array2image(arr, mode):
"""NumPy array to PIL Image"""
arr = arr.swapaxes(1,2).swapaxes(0,2)
arr[arr < 0] = 0
arr[arr > 255] = 255
arr = numpy.fix(arr).astype(numpy.uint8)
return Image.fromstring(mode, arr.shape[1::-1], arr.tostring()) | 9231df1d2d7310830545631e0fb953f8a66cec89 | 70,992 |
def default_file_reader(filename, varname, land):
"""
Read data from a netCDF file and return it in an array with shape
(NTIME,NLAND).
Parameters
----------
filename : str
Input netCDF filename.
varname : str
Name of input variable in the netCDF file: e.g., "tas", "pr", etc... | 2f1583d8bcd41c9c2072a5869dbc13e5dd94a5e5 | 70,993 |
import requests
from typing import Optional
from typing import Tuple
from typing import Sequence
from typing import Mapping
from typing import Any
import base64
import binascii
def list_results(
http_session: requests.AuthorizedSession,
operation_id: str,
page_size: int = 0,
page_token: Optional[str] ... | c80d0ad57e6f32550be33995a694736f914531c1 | 70,994 |
def spectralGraphPartition23(A, Bin='bNG', L=1.0, finetune=False, n_cutoff=4):
"""
"""
# Prep work
if Bin == 'bNG':
B = lambda v, A, indx: bNG(v, A, indx, L)
elif Bin == 'bRandUni':
B = lambda v, A, indx: bRandUni(v, A, indx, L)
else:
err_msg = 'Invalid specification for... | 5d0a33081686c07c04fd1b7203606a05345b6ac7 | 70,995 |
import signal
def prominant_curvature_features(local_curvatures, show_plot=False,min_prominance=0.1,min_width=5,dist_bwt_peaks=10):
"""Obtain prominant (peaks) local curvature
This function finds peaks for a given list of local curvatures using scipy's signal module.
Args:
local_curvatures:(Arr... | 964945c2f19b0349f08e0a292cd8a3d4fb1db715 | 70,996 |
def cached(s):
"""
**Deprecated**, use :func:`cachedio` instead, where ``backend="memory"``.
Usage as follows:
.. code-block:: python
@cached("20170101")
def get_daily(*args, **kws):
return xa.get_daily(*args, **kws)
Automatically cache the result in memory and avoid refe... | d3dbf99701392f98bb570fc053ecf11bd85dc33b | 70,997 |
def query_renumber(args):
"""
Gets renumber information from user
"""
if args.station_name is None:
args.station_name = raw_input('Station name for which to renumber: ')
args.date = cm_utils._query_default('date', args)
return args | b939c5dc3b93e007c5d0f9c1804fe10e38b81ccf | 70,998 |
from re import T
def xentropy_loss(x, y, epsilon=1e-6):
"""
cross-entropy loss
"""
fx = T.softmax(x)
y = T.one_hot(y, np.max(y)+1)
xentropy = - np.sum(y * np.log(fx+epsilon))/len(y)
return xentropy | 4a27e1a4d3ca6387f5ca85ccf80a2be1e42b1bec | 70,999 |
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