content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def add(a,b):
""" This function adds two numbers together """
return a+b | 96173657034d469ea43142179cd408e0c1f1e12d | 3,651,388 |
def decode_ADCP(data):
"""
Decodes ADCP data read in over UDP. Returns two lists: header and current.
input: Raw data string from ADCP UDP stream
Output:
header: [timestamp, nCells, nBeams, pressure]
- timestamp in unix format
- nBeams x nCells gives dimensions of current data
... | 07c5b430ac2321e4e47124e71c83bf8a2440f43f | 3,651,389 |
def RowToModelInput(row, kind):
"""
This converts a patient row into inputs for the SVR.
In this model we use RNAseq values as inputs.
"""
SampleID = row[TissueSampleRow(kind)]
TrueSampleIDs = [r for r in TissueSamples.columns
if r.startswith(SampleID)]
if not TrueSa... | 1167a7c47be7893252820087098db6e416f6c9bc | 3,651,390 |
from datetime import datetime
def str_to_timedelta(td_str):
"""Parses a human-readable time delta string to a timedelta"""
if "d" in td_str:
day_str, time_str = td_str.split("d", 1)
d = int(day_str.strip())
else:
time_str = td_str
d = 0
time_str = time_str.strip()
i... | dc3449c708ef4fbe689a9c130745d7ada6ac8f78 | 3,651,391 |
import cgi
def filter_safe_enter(s):
"""正文 换行替换"""
return '<p>' + cgi.escape(s).replace("\n", "</p><p>") + '</p>' | 6091abec0ff87361f1bbe4d146c64ddef3cc99f0 | 3,651,392 |
def _full_rank(X, cmax=1e15):
"""
This function possibly adds a scalar matrix to X
to guarantee that the condition number is smaller than a given threshold.
Parameters
----------
X: array of shape(nrows, ncols)
cmax=1.e-15, float tolerance for condition number
Returns
-------
X... | 8f24509fb921877c9f1bcff09fc035285beee69e | 3,651,393 |
from typing import Optional
def create(
session: Session,
instance: Instance,
name: str,
description: Optional[str] = None,
external_id: Optional[str] = None,
unified_dataset_name: Optional[str] = None,
) -> Project:
"""Create a Mastering project in Tamr.
Args:
instance: Tamr ... | aac88500ecd60df9a1496e38e33bc212f3e26701 | 3,651,394 |
import random
import time
def users_with_pending_lab(connection, **kwargs):
"""Define comma seperated emails in scope
if you want to work on a subset of all the results"""
check = CheckResult(connection, 'users_with_pending_lab')
# add random wait
wait = round(random.uniform(0.1, random_wait), 1)
... | 6136531c523cf344405cda42bbfcae1e4719280d | 3,651,395 |
import pandas
import types
def hpat_pandas_series_lt(self, other, level=None, fill_value=None, axis=0):
"""
Pandas Series method :meth:`pandas.Series.lt` implementation.
.. only:: developer
Test: python -m sdc.runtests sdc.tests.test_series.TestSeries.test_series_op8
Parameters
----------
... | b22497f64b711f92bbdf472feba657bc9b49115a | 3,651,396 |
def getBanner(host, port):
"""
Connects to host:port and returns the banner.
"""
try:
s = socket.socket()
s.connect((host, port))
banner = s.recv(1024)
return str(banner).strip()
except Exception, e:
error(str(host) + ':' + str(port) + ' ' + str(e)) | 46d497067790ef19521f84345adb8c8369ca8737 | 3,651,398 |
from typing import List
def create_cmd_table(table_data: List[List[str]], width: int = 15) -> BorderedTable:
"""Create a bordered table for cmd2 output.
Args:
table_data: list of lists with the string data to display
width: integer width of the columns. Default is 15 which generally works for... | 044630072f9927262673d65e9cfeadbd49d44f31 | 3,651,399 |
def get_parser(dataset_name):
"""Returns a csv line parser function for the given dataset."""
def inat_parser(line, is_train=True):
if is_train:
user_id, image_id, class_id, _ = line
return user_id, image_id, class_id
else:
image_id, class_id, _ = line
return image_id, class_id
d... | 4901dde39ef6af9cab1adeacb50fff7b90950cd6 | 3,651,400 |
import sqlite3
def one_sentence_to_ids(sentence, sentence_length=SENTENCE_LENGTH):
"""Convert one sentence to a list of word IDs."
Crop or pad to 0 the sentences to ensure equal length if necessary.
Words without ID are assigned ID 1.
>>> one_sentence_to_ids(['my','first','sentence'], 2)
([11095, 121], 2)
>>> on... | 14bb42a5bbec7e05b28601903c8732c140bf92ed | 3,651,402 |
def full_class_name(class_):
"""
Returns the absolute name of a class, with all nesting namespaces included
"""
return '::'.join(get_scope(class_) + [class_.name]) | c2e7c0df1394d76a181677fcceec424a9bec1f4b | 3,651,403 |
import math
def mul_pdf(mean1, var1, mean2, var2):
"""
Multiply Gaussian (mean1, var1) with (mean2, var2) and return the
results as a tuple (mean, var, scale_factor).
Strictly speaking the product of two Gaussian PDFs is a Gaussian
function, not Gaussian PDF. It is, however, proportional to a Gau... | 8ecb925273cd0e4276b867687e81b0a26419f35f | 3,651,404 |
def mean_squared_error(y_true, y_pred):
"""
Mean squared error loss.
:param y_true: groundtruth.
:param y_pred: prediction.
:return: loss symbolic value.
"""
P = norm_saliency(y_pred) # Normalized to sum = 1
Q = norm_saliency(y_true) # Normalized to sum = 1
return K.mean(K.square(P... | 9ecc02bfa6fc0417ea286a8f8195fdcc264c6593 | 3,651,405 |
def format_epilog():
"""Program entry point.
:param argv: command-line arguments
:type argv: :class:`list`
"""
author_strings = []
for name, email in zip(metadata.authors, metadata.emails):
author_strings.append('Author: {0} <{1}>'.format(name, email))
epilog = '''
{project} {versio... | ab1b378092006b3c4d7208e99c4a6ead41b528e4 | 3,651,406 |
from typing import List
import difflib
def text_differences(original_text: List[str], new_text_version: List[str]) -> TextDifferences:
"""
Builds text differences from input texts.
Parameters
----------
original_text: List[str]
original text (as a list of lines)
new_text_version: List... | 3f17489ac888714a2769e838e35a30384d76e961 | 3,651,408 |
import json
async def delete_port(request : VueRequest):
"""
删除端口的接口
:param:
:return: str response: 需要返回的数据
"""
try:
response = {'code': '', 'message': '', 'data': ''}
request = rsa_crypto.decrypt(request.data)
request = json.loads(request)
target = reque... | 71a90d9e14f514bb65e7d47d4a63090be70af033 | 3,651,410 |
def get_start_indices_labesl(waveform_length, start_times, end_times):
"""
Returns: a waveform_length size boolean array where the ith entry says wheter or not a frame starting from the ith
sample is covered by an event
"""
label = np.zeros(waveform_length)
for start, end in zip(start_times, end... | 39d264f837940e11b4d5e6897a93e30da234730d | 3,651,411 |
def get_function_euler_and_module():
"""
Function return tuple with value function euler and module.
This tuple is namedtuple and we can use it this way:
euler = tuple.euler
module = tuple.module
Thanks to this, we will not be mistaken.
"""
first_number_prime, second_number_prime... | 0b44391c9b38cc5f04f2e5faa212542716543883 | 3,651,412 |
def _read_host_df(host, seq=True):
"""Reads the metrics data for the host and returns a DataFrame.
Args:
host (str): Hostname, one of wally113, wally117, wally122, wally123,
wally124
seq (bool): If sequential or concurrent metrics should be read
Returns:
DataFrame: Containing all t... | 5e2872816b0e9b77ccccd1ead03e3c9660c604f2 | 3,651,413 |
def compacify(train_seq, test_seq, dev_seq, theano=False):
"""
Create a map for indices that is be compact (do not have unused indices)
"""
# REDO DICTS
new_x_dict = LabelDictionary()
new_y_dict = LabelDictionary(['noun'])
for corpus_seq in [train_seq, test_seq, dev_seq]:
for seq in... | c695022c6216b035618342c0aaecc39d8337a84c | 3,651,414 |
def obfuscate_email(email):
"""Takes an email address and returns an obfuscated version of it.
For example: test@example.com would turn into t**t@e*********m
"""
if email is None:
return None
splitmail = email.split("@")
# If the prefix is 1 character, then we can't obfuscate it
if l... | 36c230ed75fc75fc7ecd6dd2ea71a6b3310c4108 | 3,651,415 |
def list_small_kernels():
"""Return list of small kernels to generate."""
kernels1d = [
NS(length= 1, threads_per_block= 64, threads_per_transform= 1, factors=(1,)),
NS(length= 2, threads_per_block= 64, threads_per_transform= 1, factors=(2,)),
NS(length= 3, threads_per_block= 64... | 332c94c0957ddb438822574e416a37eaef09c5f6 | 3,651,416 |
def parse_boolean(arg: str):
"""Returns boolean representation of argument."""
arg = str(arg).lower()
if 'true'.startswith(arg):
return True
return False | 2f0a214212aa43a8b27d9a3be04f14af67c586bc | 3,651,417 |
def ascending_coin(coin):
"""Returns the next ascending coin in order.
>>> ascending_coin(1)
5
>>> ascending_coin(5)
10
>>> ascending_coin(10)
25
>>> ascending_coin(2) # Other values return None
"""
if coin == 1:
return 5
elif coin == 5:
return 10
elif coi... | e927d8ac3f38d4b37de71711ac90d6ca2151a366 | 3,651,418 |
def to_numpy(qg8_tensor):
"""
Convert qg8_tensor to dense numpy array
"""
dtype = dtype_to_name(qg8_tensor.dtype_id)
ndarray = np.zeros(qg8_tensor.dims, dtype=dtype)
if np.iscomplexobj(ndarray):
ndarray[tuple(qg8_tensor.indices)] = np.asfortranarray(qg8_tensor.re)\
... | 808c42fd1a6a4488cef34876674a212231fc2979 | 3,651,419 |
def _get_results(report):
"""Limit the number of documents to REPORT_MAX_DOCUMENTS so as not to crash the server."""
query = _build_query(report)
try:
session.execute(f"SET statement_timeout TO {int(REPORT_COUNT_TIMEOUT * 1000)}; commit;")
if query.count() == 0:
return None
e... | 0575ec42c3b7cd729d4bc454986e02280ae4bb68 | 3,651,420 |
import warnings
def text_match_one_hot(df, column=None, text_phrases=None, new_col_name=None, return_df=False, case=False,
supress_warnings: bool=False):
"""Given a dataframe, text column to search and a list of text phrases, return a binary
column with 1s when text is present and 0 o... | 3db69fc6459dde7b14bbd1ae1507adc0b6c9a8b4 | 3,651,421 |
import six
def pack_feed_dict(name_prefixs, origin_datas, paddings, input_fields):
"""
Args:
name_prefixs: A prefix string of a list of strings.
origin_datas: Data list or a list of data lists.
paddings: A padding id or a list of padding ids.
input_fields: The input fieds dict... | 6de17aa1235d929fee20fcddcfcfb04e3907484b | 3,651,422 |
from PyQt4 import QtGui
def get_directory(**kwargs):
"""
Wrapper function for PyQt4.QtGui.QFileDialog.getExistingDirectory().
Returns the absolute directory of the chosen directory.
Parameters
----------
None
Returns
-------
filename : string of absolute directory.
"""
f... | 8b27ec800ccaa237d79e198d23058b70f71df4b8 | 3,651,423 |
def single_particle_relative_pzbt_metafit(fitfn, exp_list, **kwargs):
"""Fit to single-particle energies plus zero body term, relative to the
first point
"""
return single_particle_metafit_int(
fitfn, exp_list,
dpath_sources=DPATH_FILES_INT, dpath_plots=DPATH_PLOTS,
transform=rel... | 81dfc60f1f27df710ccdb489ff322d576b8d9922 | 3,651,424 |
def hetmat_from_permuted_graph(hetmat, permutation_id, permuted_graph):
"""
Assumes subdirectory structure and that permutations inherit nodes but not
edges.
"""
permuted_hetmat = initialize_permutation_directory(hetmat, permutation_id)
permuted_hetmat = hetmat_from_graph(
permuted_graph... | 54728e3522f76e24d4a4107752980a57990c551d | 3,651,425 |
import types
def can_see_all_content(requesting_user: types.User, course_key: CourseKey) -> bool:
"""
Global staff, course staff, and instructors can see everything.
There's no need to run processors to restrict results for these users.
"""
return (
GlobalStaff().has_user(requesting_user)... | c4de054b235da20074841e7225123ef73e7d4a16 | 3,651,426 |
def part2(steps, workers=2, extra_time=0):
""" Time is in seconds """
workers = [Worker() for _ in range(workers)]
steps_to_time = {
step: alphabet.index(step) + 1 + extra_time
for step in alphabet
}
time = 0
graph = build_graph(steps)
chain = find_orphans(graph)
while... | 792c6ca6e5334491eb38d8549b6c9df41d101924 | 3,651,427 |
from typing import Any
from typing import List
from typing import Iterable
def to_local_df(df: Any, schema: Any = None, metadata: Any = None) -> LocalDataFrame:
"""Convert a data structure to :class:`~fugue.dataframe.dataframe.LocalDataFrame`
:param df: :class:`~fugue.dataframe.dataframe.DataFrame`, pandas D... | 12aae7869067b14f2f0f8ffcb3e393f41db5114f | 3,651,428 |
def create_local_meta(name):
"""
Create the metadata dictionary for this level of execution.
Parameters
----------
name : str
String to describe the current level of execution.
Returns
-------
dict
Dictionary containing the metadata.
"""
local_meta = {
'... | 61a2ef73e8a6f74360881b97150a79079f3f8c29 | 3,651,429 |
def matches_uri_ref_syntax(s):
"""
This function returns true if the given string could be a URI reference,
as defined in RFC 3986, just based on the string's syntax.
A URI reference can be a URI or certain portions of one, including the
empty string, and it can have a fragment component.
"""
... | 73b0dde1f76edcf4fe7f7754cc67d7604f984521 | 3,651,430 |
from datetime import datetime
def get_end_hour(dt=None):
"""根据日期、或时间取得该小时59:59的时间；参数可以是date或datetime类型"""
end = None
if not dt:
dt = datetime.date.today()
if isinstance(dt, datetime.date):
dt_str = dt.strftime("%Y-%m-%d %H") + ":59:59"
end = datetime.datetime.strptime(dt_str, "... | 73d2760cf085295e13a4699aaf3dd8aa9dd5ae49 | 3,651,431 |
def all_ped_combos_strs(num_locs=4, val_set=("0", "1")):
"""Return a list of all pedestrian observation combinations (in string format) for a vehicle under the 4 location scheme"""
res = []
lsts = all_ped_combos_lsts(num_locs, val_set)
for lst in lsts:
res.append(" ".join(lst))
return res | 4a87cf48da5fb9582c7d7284fc78471e84918256 | 3,651,432 |
def create_image(
image_request: ImageRequest,
background_tasks: BackgroundTasks,
db: Session = Depends(get_db),
):
"""
(2) add database record
(3) give background_tasks a reference of image record
"""
image = Images()
image.url = image_request.image
# image.output = "4" # <<<... | 77042168b61262b832bdad438a4d6661cfb263d6 | 3,651,433 |
def get_key(rule_tracker, value):
"""
Given an event index, its corresponding key from the dictionary is returned.
Parameters:
rule_tracker (dict): Key-value pairs specific to a rule where key is an activity, pair is an event index
value (int): Index of event in event log
Returns:
... | 1921e9a68d0df0867248ca83e2ba641101735fc7 | 3,651,434 |
def get_cxml(filename):
""" Create and return CXML object from File or LocalCache """
cxml = Cxml(filename)
return cxml | c2c440793ea4b509823dd0ad90677eb7db2696ff | 3,651,435 |
def save_layer(index, settings) -> Action:
"""Action to save layer settings"""
return {"kind": SAVE_LAYER, "payload": {"index": index, "settings": settings}} | 8fde0e1c752455e386745f428a69ae4a9936c028 | 3,651,436 |
def request_user_input(prompt='> '):
"""Request input from the user and return what has been entered."""
return raw_input(prompt) | 1c8507edb17977005e068abee90b84832354adaf | 3,651,437 |
def get_clinic_qs():
""" Returns a list of clinic uuid values for clinics whose patients
will receive follow up reminder messages
"""
q = Q()
for clinic in MESSAGE_CLINICS:
q = q | Q(name__iexact=clinic)
return list(Clinic.objects.filter(q).values_list('uuid', flat=True)) | 8224db73bd14839b8db6e2ee4a77c1404d846e34 | 3,651,438 |
def NPnm(n, m, x):
"""Eq:II.77 """
return sqrt( (2*n+1)/2 * abs(nmFactorial(n,m)) ) * lpmv(m, n, x) | 8444f8d3a56e62bf66c6c0a318641d212202438d | 3,651,439 |
def all_columns_empty():
"""All columns are empty ... test will demoonstrate this edge case can be handled"""
return [[] for i in range(0, 100)] | 77a354978f82fd61d0f4d12db57a7fc455f4af28 | 3,651,440 |
def ping(host, destination, repeat_count, vrf_name):
"""Execute Ping RPC over NETCONF."""
# create NETCONF provider
provider = NetconfServiceProvider(address=host,
port=830,
username='admin',
p... | b2486447a5c8e0c48a8420a2f8c7795d0eef68b8 | 3,651,441 |
def compute_shape_index(mesh) -> np.ndarray:
"""
Computes shape index for the patches. Shape index characterizes the shape
around a point on the surface, computed using the local curvature around each
point. These values are derived using PyMesh's available geometric
processing functionality.
P... | e7c84aeb39eaf7e752fe8e98d6519b342b22088a | 3,651,442 |
from typing import Tuple
def edit_frame(frame: ndarray, y: int) -> Tuple[ndarray, ndarray]:
"""
Parameters
----------
frame : (is row-major)
y
Returns
-------
(frame, cut)
"""
np.random.uniform(-1, 1, size=20000000) # 20000000@6cores
cut = cv.cvtColor(frame[[y], :], cv.CO... | 30f2550839067eb837f38734a761f1f06e50db27 | 3,651,443 |
def get_location(uniprot_id: str) -> Location: # pragma: no cover
"""Queries the UniProt database for a subcellular location with the id `uniprot_id`
and returns a `Location` object"""
g: LocationRDF = get_location_graph(uniprot_id)
return Location.from_location_rdf(g) | cbe77792023954095962eaa8d379518a6ee10027 | 3,651,444 |
import copy
def _gaussian2d_rot_no_bg(p,x,y):
"""
Required Arguments:
p -- (m) [A,x0,y0,FWHMx,FWHMy,theta]
x -- (n x o) ndarray of coordinate positions for dimension 1
y -- (n x o) ndarray of coordinate positions for dimension 2
Outputs:
f -- (n x o) ndarray of function values at position... | 8f9433993ff4992c1d4d7fd5b36cd1ca57003f31 | 3,651,445 |
def queue_get_all(q):
"""
Used by report builder to extract all items from a
:param q: queue to get all items from
:return: hash of merged data from the queue by pid
"""
items = {}
maxItemsToRetreive = 10000
for numOfItemsRetrieved in range(0, maxItemsToRetreive):
try:
... | 221700485ee10893bfd1e4e290523ed35cf21418 | 3,651,446 |
def sample_account(self, profile, company, **params):
"""Create and return a sample customer"""
defaults = {
"balance": 0,
"account_name": "string",
"account_color": "string"
}
defaults.update(params)
return Account.objects.create(
profile=profile,
company=c... | 6360d0b6a15592d42ffc7f9315181ae769812d4b | 3,651,447 |
def get_funghi_type_dict(funghi_dict):
"""
Parameters
----------
funghi_dict: dict {str: list of strs}
is the name: html lines dict created by get_funghi_book_entry_dict_from_html()
Return
------------
dict {str: FunghiType}
each entry contains a mushroom name and the corresponding ... | 6fe891fe4f9766b7f8a78e9bd13950d5c6af264e | 3,651,449 |
def default_error_mesg_fmt(exc, no_color=False):
"""Generate a default error message for custom exceptions.
Args:
exc (Exception): the raised exception.
no_color (bool): disable colors.
Returns:
str: colorized error message.
"""
return color_error_mesg('{err_name}: {err_mes... | 248d99d5d08f9499a2349e66b03e9ec6ab1557a4 | 3,651,450 |
def check_values_on_diagonal(matrix):
"""
Checks if a matrix made out of dictionary of dictionaries has values on diagonal
:param matrix: dictionary of dictionaries
:return: boolean
"""
for line in matrix.keys():
if line not in matrix[line].keys():
return False
return Tru... | bc7979adcfb5dc7c19b3cdb3830cf2397c247846 | 3,651,451 |
def read_quantity(string):
"""
convert a string to a quantity or vectorquantity
the string must be formatted as '[1, 2, 3] unit' for a vectorquantity,
or '1 unit' for a quantity.
"""
if "]" in string:
# It's a list, so convert it to a VectorQuantity.
# The unit part comes after... | ab36a26425a4bbc236ac84a807707431d3c9dc14 | 3,651,453 |
async def stop_service(name: str) -> None:
""" stop service """
task = TASKS.get(name)
if task is None:
raise Exception(f"No such task {name}")
return task.cancel() | 245f60e70dcce09147d83697128c525e3630f238 | 3,651,454 |
def rand_bbox(img_shape, lam, margin=0., count=None):
""" Standard CutMix bounding-box
Generates a random square bbox based on lambda value. This impl includes
support for enforcing a border margin as percent of bbox dimensions.
Args:
img_shape (tuple): Image shape as tuple
lam (float): ... | 47fd5fa1f2530c198aad50e883ec57dbd60cb4db | 3,651,455 |
from pathlib import Path
def get_current_dir():
"""
Get the directory of the executed Pyhton file (i.e. this file)
"""
# Resolve to get rid of any symlinks
current_path = Path(__file__).resolve()
current_dir = current_path.parent
return current_dir | c0e6fa1300970226fce42bf57fe2d2ed6b3e3604 | 3,651,456 |
import csv
def build_gun_dictionary(filename):
"""Build a dictionary of gun parameters from an external CSV file:
- Key: the gun designation (e.g. '13.5 in V' or '12 in XI')
- Value: a list of parameters, in the order:
* caliber (in inches)
* maxrange (maximum range in yard... | b9e38d766430d44b94ae9fa64c080416fdeb8482 | 3,651,457 |
def plot_learning_curve(estimator, title, X, y, ylim=None, cv=None,
n_jobs=1, train_sizes=np.linspace(.1, 1.0, 5)):
"""
Generate a simple plot of the test and training learning curve.
Parameters
----------
estimator : object type that implements the "fit" and "predict" metho... | 903f3119338c7886a663aa9a0e173849811365f9 | 3,651,458 |
from bs4 import BeautifulSoup
import requests
def fetch_events_AHEAD(base_url='http://www.ahead-penn.org'):
"""
Penn Events for Penn AHEAD
"""
page_soup = BeautifulSoup(requests.get(
urljoin(base_url, '/events')).content, 'html.parser')
events = []
event_table = page_soup.find('div', ... | 24dc865a1db2ff5361e8d502ab47d78de94b875b | 3,651,459 |
import string
def column_to_index(ref):
"""
カラムを示すアルファベットを0ベース序数に変換する。
Params:
column(str): A, B, C, ... Z, AA, AB, ...
Returns:
int: 0ベース座標
"""
column = 0
for i, ch in enumerate(reversed(ref)):
d = string.ascii_uppercase.index(ch) + 1
column += d * pow(len(... | 7a6f89fa238d3d47a1e45b2e83821dbd4e8b23f8 | 3,651,460 |
def cols_to_tanh(df, columns):
"""Transform column data with hyperbolic tangent and return new columns of prefixed data.
Args:
df: Pandas DataFrame.
columns: List of columns to transform.
Returns:
Original DataFrame with additional prefixed columns.
"""
for col in columns:... | b24c5467fa3c38415c8a4a0ab399a3ab44f481e9 | 3,651,461 |
import numpy as np
def stdev_time(arr1d, stdev):
"""
detects breakpoints through multiple standard deviations and divides breakpoints into timely separated sections
(wanted_parts)
- if sigma = 1 -> 68.3%
- if sigma = 2 -> 95.5%
- if sigma = 2.5 -> 99.0%
- if si... | b243f1d4ba904cbc2fb0e46b37305c857fce0be1 | 3,651,463 |
def main(_, **settings):
"""
This function returns a Pyramid WSGI application.
"""
config = Configurator(settings=settings, route_prefix="/api")
# Initialise the broadcast view before c2cwsgiutils is initialised. This allows to test the
# reconfiguration on the fly of the broadcast framework
... | f47bdb2e551aabfb5d03c4eefd52ec37f875e55d | 3,651,464 |
def GetVarLogMessages(max_length=256 * 1024,
path='/var/log/messages',
dut=None):
"""Returns the last n bytes of /var/log/messages.
Args:
max_length: Maximum characters of messages.
path: path to /var/log/messages.
dut: a cros.factory.device.device_types.Devi... | f615f60b8daf0ee21b7b932ee23a21573b5d0db5 | 3,651,466 |
def find_index(predicate, List):
"""
(a → Boolean) → [a] → [Number]
Return the index of first element that satisfy the
predicate
"""
for i, x in enumerate(List):
if predicate(x):
return i | 0c6010b8b169b7bfa780ca03c0551f189bda892a | 3,651,467 |
from typing import Callable
from typing import Any
from typing import Dict
def logger(
wrapped: Callable[..., str], instance: Any, args: Any, kwargs: Dict[str, Any]
) -> str:
"""Handle logging for :class:`anndata.AnnData` writing functions of :class:`cellrank.estimators.BaseEstimator`."""
log, time = kwar... | 6fc9d5867d2f9ebbacb3fef902d4b4d84670e449 | 3,651,468 |
def search_front():
"""
Search engine v0.1
- arguments:
- q: query to search (required)
"""
q = request.args.get('q', None)
if not q:
return flask.jsonify({'status': 'error', 'message': 'Missing query'}), 400
res = dict()
cursor = db.run(r.table(PRODUCTS_TABLE).pluck('sho... | 8230cd0b304fce767dbd19d3073e05fe1e083928 | 3,651,469 |
def insert_rare_words(sentence: str) -> str:
"""
attack sentence by inserting a trigger token in the source sentence.
"""
words = sentence.split()
insert_pos = randint(0, len(words))
insert_token_idx = randint(0, len(WORDS)-1)
words.insert(insert_pos, WORDS[insert_token_idx])
return " ".... | ca07dec0492bff7c843e073b1093a13a418052d4 | 3,651,470 |
def _can_be_quoted(loan_amount, lent_amounts):
"""
Checks if the borrower can obtain a quote. To this aim, the loan amount should be less than or
equal to the total amounts given by lenders.
:param loan_amount: the requested loan amount
:param lent_amounts: the sum of the amounts given by lenders
... | 6fd717f3d0e844752e07e9dd435ff72eaa4b34c9 | 3,651,471 |
def load_specs_from_docstring(docstring):
"""Get dict APISpec from any given docstring."""
# character sequence used by APISpec to separate
# yaml specs from the rest of the method docstring
yaml_sep = "---"
if not docstring:
return {}
specs = yaml_utils.load_yaml_from_docstring(docst... | 88c245f56bba10355e78c20eb421f865b054bdbe | 3,651,472 |
import skimage.transform
from skimage.measure import ransac
def get_transform(V1, V2, pair_ix, transform=None, use_ransac=True):
"""
Estimate parameters of an `~skimage.transform` tranformation given
a list of coordinate matches.
Parameters
----------
V1, V2 : [N,2] arrays
Coordi... | d68b0c639df48cad6278b021d7bdb347cfc0d0b0 | 3,651,474 |
def no_trajectory_dct():
""" Dictionary expected answer """
return () | 95cc96bbfb23e621511f99f4d19f1af5a31bcc0f | 3,651,475 |
import json
def transform_fn(net, data, input_content_type, output_content_type):
"""
Transform a request using the Gluon model. Called once per request.
:param net: The Gluon model.
:param data: The request payload.
:param input_content_type: The request content type.
:param output_content_t... | 756eb7093c7c56ded15d24356ead8a08d3eea7e7 | 3,651,476 |
def superuser_required(method):
"""
Decorator to check whether user is super user or not
If user is not a super-user, it will raise PermissionDenied or
403 Forbidden.
"""
@wraps(method)
def _wrapped_view(request, *args, **kwargs):
if request.user.is_superuser is False:
ra... | 7bab907af1be1e81448db660f7d05b42741015da | 3,651,477 |
def _section_data_download(course, access):
""" Provide data for the corresponding dashboard section """
course_key = course.id
show_proctored_report_button = (
settings.FEATURES.get('ENABLE_SPECIAL_EXAMS', False) and
course.enable_proctored_exams
)
section_key = 'data_download_2' i... | 159d3fb4e13979826dbf1e95baf85224b82aeba8 | 3,651,478 |
def tcache(parser, token):
"""
This will cache the contents of a template fragment for a given amount
of time with support tags.
Usage::
{% tcache [expire_time] [fragment_name] [tags='tag1,tag2'] %}
.. some expensive processing ..
{% endtcache %}
This tag also supports ... | 206bcaa5c11a33e2f2bfe19fa75f7abe07fbc9c2 | 3,651,480 |
def location_edit(type_, id_, location_name, location_type, date, user,
description=None, latitude=None, longitude=None):
"""
Update a location.
:param type_: Type of TLO.
:type type_: str
:param id_: The ObjectId of the TLO.
:type id_: str
:param location_name: The name o... | b4bd584423e66242a6919fbcf3defcdd431ae9d3 | 3,651,482 |
def G2(species_index, eta, Rs):
"""G2 function generator.
This is a radial function between an atom and atoms with some chemical
symbol. It is defined in cite:khorshidi-2016-amp, eq. 6. This version is
scaled a little differently than the one Behler uses.
Parameters
----------
species_index... | a98b6ee7f6ff602a9ac8003b4c7cf515580aa9a3 | 3,651,483 |
def convert_leg_pose_to_motor_angles(robot_class, leg_poses):
"""Convert swing-extend coordinate space to motor angles for a robot type.
Args:
robot_class: This returns the class (not the instance) for the robot.
Currently it supports minitaur, laikago and mini-cheetah.
leg_poses: A list of leg poses... | 7d71edd6dede2e523a3b61b48ff291924ce9df23 | 3,651,484 |
def get_all_records(session):
"""
return all records
"""
result = session.query(Skeleton).all()
skeletons = convert_results(result)
return skeletons | 7a5205a40afdff943e9ad15636e41563059fd8ee | 3,651,486 |
import scipy
def pwm_to_boltzmann_weights(prob_weight_matrix, temp):
"""Convert pwm to boltzmann weights for categorical distribution sampling."""
weights = np.array(prob_weight_matrix)
cols_logsumexp = []
for i in range(weights.shape[1]):
cols_logsumexp.append(scipy.special.logsumexp(weights... | f7dac6149660b230986682d6e52d5455708c1fcb | 3,651,487 |
def mutation_delete_music_composition(identifier: str):
"""Returns a mutation for deleting a MusicComposition.
Args:
identifier: The identifier of the MusicComposition.
Returns:
The string for the mutation for deleting the music composition object based on the identifier.
"""
retur... | 64f4f2cba056e96d7c63ac2672d5613e3009c380 | 3,651,488 |
from astroquery.gaia import Gaia
import warnings
def coords_from_gaia(gaia_id):
"""Returns table of Gaia DR2 data given a source_id."""
warnings.filterwarnings('ignore', module='astropy.io.votable.tree')
adql = 'SELECT gaia.source_id, ra, dec FROM gaiadr2.gaia_source AS gaia WHERE gaia.source_id={0}'.form... | 6177a846528003f56c82451622c671c100f5ea71 | 3,651,489 |
from random import shuffle, random
import numpy as np
def partition(smilist,ratio=0.7):
"""
A function to create test/ train split list
:param smilist: smiles (list)
:param ratio: test set split fraction (float)
Return type: traininglist, testlist (list)
"""
shuffle(smilist, random)
t... | 6dbfa6ecdf543c03ecac210e634aaaeee68a6979 | 3,651,490 |
def align(reference, query):
"""
do a pairwise alignment of the query to the reference, outputting up to 10000 of the highest-scoring alignments.
:param reference: a STRING of the reference sequence
:param query: a STRING of the query sequence
:return: a list of up to 10000 Alignment objects
"""... | a10d9a5ade48fb11c8a8b497c6ef764115c9843d | 3,651,491 |
import re
def output_name(ncfile):
"""output_name.
Args:
ncfile:
"""
ncfile_has_datetime = re.search('[0-9]{4}-[0-9]{2}-[0-9]{2}_[0-9]{2}', ncfile)
if ncfile_has_datetime:
forecast_time = ncfile_has_datetime.group()
else:
raise Exception("ncfile doesn't have datetime ... | 81d04e9fe572e6ba2eb97506d4690818008a1aaf | 3,651,492 |
def _replacement_func_decorator(
fn=None,
name=None,
help="",
args=None):
"""
Replaces xlo.func in jupyter but removes arguments which do not make sense
when called from jupyter
"""
def decorate(fn):
spec = _FuncDescription(fn, name or fn._... | 92ab0a28107bfb88e8cf1084e07e252bd5994388 | 3,651,493 |
def stress_x_component(coordinates, prisms, pressure, poisson, young):
"""
x-component of the stress field.
Parameters
----------
coordinates : 2d-array
2d numpy array containing ``y``, ``x`` and ``z`` Cartesian cordinates
of the computation points. All coordinates should be in mete... | f47b8e6301964454b85e5a124db642708ba7abf6 | 3,651,494 |
def process_time_data(flag, last_time, model_params_dict_raw, time_data_raw):
"""
This is a helper function that takes the raw time data from the model
file and replaces it with the correct value in the params file.
:param flag:
:param last_time:
:param model_params_dict_raw:
:param time_da... | 6684ba352f2a339029581816ac72690c26dd8a73 | 3,651,495 |
def create_pos_data(data, parser):
"""
creating the positive fh numeric dataset. performing another cleaning.
:param data: suspected fh examples
:param parser: parser used for the word tokenization
:return: all positive examples (after the cleaning), will be used
for creating the negat... | a55b43f9d953284494629b4f4bc6f6901be0f865 | 3,651,496 |
async def absent(hub, ctx, name, resource_uri, connection_auth=None, **kwargs):
"""
.. versionadded:: 2.0.0
Ensure a diagnostic setting does not exist for the specified resource uri.
:param name: The name of the diagnostic setting.
:param resource_uri: The identifier of the resource.
:param ... | ed97a9d765e8bda566b85b2bc22a585f02378dff | 3,651,497 |
def get_ngrok() -> str or None:
"""Sends a `GET` request to api/tunnels to get the `ngrok` public url.
See Also:
Checks for output from get_port function. If nothing, then `ngrok` isn't running.
However as a sanity check, the script uses port number stored in env var to make a `GET` request.
... | 51cc61f3aea7f0ffc8d21284548df50e3e77d2b6 | 3,651,498 |
def contacts_per_person_symptomatic_60x80():
"""
Real Name: b'contacts per person symptomatic 60x80'
Original Eqn: b'contacts per person normal 60x80*(symptomatic contact fraction 80+symptomatic contact fraction 60\\\\ )/2'
Units: b'contact/Day'
Limits: (None, None)
Type: component
b''
... | bf887237e77ffe0c3cb39a12285904f14ca14dd2 | 3,651,499 |
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