content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import json
def solve_with_log(board, out_fname):
"""Wrapper for solve: write log to out_fname"""
log = []
ret = solve(board, log)
with open(out_fname, 'w') as f:
f.write(json.dumps({'model': log}, indent=4))
return ret | c550980f252df724d68f9eb22159463e361997bc | 3,650,800 |
def discrepancy(sample, bounds=None):
"""Discrepancy.
Compute the centered discrepancy on a given sample.
It is a measure of the uniformity of the points in the parameter space.
The lower the value is, the better the coverage of the parameter space is.
Parameters
----------
sample : array_... | f54cf5efa3cf12410d5522971983d41ea767767f | 3,650,801 |
def rz(psi, r):
"""
Wrapper for ERFA function ``eraRz``.
Parameters
----------
psi : double array
r : double array
Returns
-------
r : double array
Notes
-----
The ERFA documentation is below.
- - - - - -
e r a R z
- - - - - -
Rotate an r-matrix abou... | 1ea4e9322ba187e91d3b976d74d416ae99a74ee6 | 3,650,802 |
import locale
def _get_ticklabels(band_type, kHz, separator):
"""
Return a list with all tick labels for octave or third octave bands cases.
"""
if separator is None:
separator = locale.localeconv()['decimal_point']
if band_type == 'octave':
if kHz is True:
ticklabels ... | 95ebdc670a23fdb8561a431e863901df6734fdb9 | 3,650,803 |
def SpearmanP(predicted, observed):
"""abstracts out p from stats.spearmanr"""
if np.isnan(np.min(predicted)) or np.isnan(np.min(observed)):
return np.asarray([np.nan])
coef, p = stats.spearmanr(np.squeeze(predicted).astype(float), np.squeeze(observed).astype(float))
return p | 41986483ea3d466d94af5c86cedee62165d81d98 | 3,650,804 |
def get_zebra_route_type_by_name(route_type='BGP'):
"""
Returns the constant value for Zebra route type named "ZEBRA_ROUTE_*"
from its name.
See "ZEBRA_ROUTE_*" constants in "ryu.lib.packet.zebra" module.
:param route_type: Route type name (e.g., Kernel, BGP).
:return: Constant value for Zebra... | 8cdc3a8384f71c4c04172a8c37f51e3789929e42 | 3,650,805 |
def preprocess(arr):
"""Preprocess image array with simple normalization.
Arguments:
----------
arr (np.array): image array
Returns:
--------
arr (np.array): preprocessed image array
"""
arr = arr / 255.0
arr = arr * 2.0 - 1.0
return arr | 3bccf2f4433c4da62954db4f25f5e9bfabc03c3a | 3,650,806 |
def remove_const(type):
"""removes const from the type definition
If type is not const type, it will be returned as is
"""
nake_type = remove_alias(type)
if not is_const(nake_type):
return type
else:
return nake_type.base | b00d7cca79222d5ac2b6a12019b73a8169df96b7 | 3,650,807 |
def populate_institute_form(form, institute_obj):
"""Populate institute settings form
Args:
form(scout.server.blueprints.institutes.models.InstituteForm)
institute_obj(dict) An institute object
"""
# get all other institutes to populate the select of the possible collaborators
insti... | 836850a55a02b199b2c7607a236f77e6b95051e0 | 3,650,808 |
def closestMedioidI(active_site, medioids, distD):
"""
returns the index of the closest medioid in medioids to active_site
input: active_site, an ActiveSite instance
medioids, a list of ActiveSite instances
distD, a dictionary of distances
output: the index of the ActiveSite close... | 379f98a84751c0a392f8f9b1703b89b299979676 | 3,650,809 |
from typing import Dict
from typing import Any
import traceback
import sys
def watchPoint(filename, lineno, event="call"):
"""whenever we hit this line, print a stack trace. event='call'
for lines that are function definitions, like what a profiler
gives you.
Switch to 'line' to match lines inside fu... | 5c7017a180e254f5651c6cf737ca798d570d669c | 3,650,810 |
def no_op_job():
"""
A no-op parsl.python_app to return a future for a job that already
has its outputs.
"""
return 0 | ad8d6379ba35dae14ce056d9900fb6e62c769d85 | 3,650,811 |
def identity(dim, shape=None):
"""Return identity operator with appropriate shape.
Parameters
----------
dim : int
Dimension of real space.
shape : int (optional)
Size of the unitary part of the operator.
If not provided, U is set to None.
Returns
-------
id : P... | 0cd40246f4ccf2805a852dcea09d451e7f8c63a5 | 3,650,812 |
def configure_checkout_session(request):
"""
Configure the payment session for Stripe.
Return the Session ID.
Key attributes are:
- mode: payment (for one-time charge) or subscription
- line_items: including price_data because users configure the donation
price.
TODOs
... | f53bd6ecd488d214d3ebc43a2c049bf4315c1494 | 3,650,813 |
import os
import json
def load_schemas():
"""Return all of the schemas in this directory in a dictionary where
the keys are the filename (without the .json extension) and the values
are the JSON schemas (in dictionary format)
:raises jsonschema.exceptions.SchemaError if any of the JSON files in this
... | cbd14a4cdcc37f7fc861e00de84928abd3f8a557 | 3,650,814 |
from typing import Optional
from typing import Union
import torch
from pathlib import Path
import json
def load_separator(
model_str_or_path: str = "umxhq",
targets: Optional[list] = None,
niter: int = 1,
residual: bool = False,
wiener_win_len: Optional[int] = 300,
device: Union[str, torch.dev... | bb9d0ecf47174ebac9181710a1bc4689ca122ecf | 3,650,815 |
from datetime import datetime
def transform_datetime(date_str, site):
"""
根据site转换原始的date为正规的date类型存放
:param date_str: 原始的date
:param site: 网站标识
:return: 转换后的date
"""
result = None
if site in SITE_MAP:
if SITE_MAP[site] in (SiteType.SINA, SiteType.HACKERNEWS):
try:
... | 647ab633b0d5ce0887042ef42a762f1bc3196242 | 3,650,816 |
import re
import numpy
def ParseEventsForTTLs(eventsFileName, TR = 2.0, onset = False, threshold = 5.0):
"""
Parses the events file from Avotec for TTLs. Use if history file is not available.
The events files does not contain save movie start/stops, so use the history file if possible
@param eventsFileName: name... | 59fa31df066424df3625e55496f0ccefa39f2d64 | 3,650,817 |
def _to_native_string(string, encoding='ascii'):
"""Given a string object, regardless of type, returns a representation of
that string in the native string type, encoding and decoding where
necessary. This assumes ASCII unless told otherwise.
"""
if isinstance(string, str):
out = string
... | b50fd0fc62b2cfc024c847b98e1f85b4b67d07e3 | 3,650,818 |
def load(path: str) -> model_lib.Model:
"""Deserializes a TensorFlow SavedModel at `path` to a `tff.learning.Model`.
Args:
path: The `str` path pointing to a SavedModel.
Returns:
A `tff.learning.Model`.
"""
py_typecheck.check_type(path, str)
if not path:
raise ValueError('`path` must be a non-... | 1bd16ed7b4a7955f2a78fc638e896bbd6d1ee5ac | 3,650,819 |
import os
def plot_feature_importance(obj, top_n=None, save_path=None):
"""
输出LGBM模型的feature importance，并绘制条形图
Parameters
----------
obj: lgbm object or DataFrame
训练好的Lightgbm模型，或是已经计算好的feature importan DataFrame
top_n: int, default None
展示TOP N的变量，若不填则展示全部变量，为保证显示效果，建议当变量个数多于3... | e1d8fc6d05693ad4381281d21e0e5672b54a863e | 3,650,820 |
def parameters_from_object_schema(schema, in_='formData'):
"""Convert object schema to parameters."""
# We can only extract parameters from schema
if schema['type'] != 'object':
return []
properties = schema.get('properties', {})
required = schema.get('required', [])
parameters = []
... | 7508fb066d6924fc0af4a10338636b70ef64b9b2 | 3,650,821 |
import os
def env_vars(request):
"""Sets environment variables to use .env and config.json files."""
os.environ["ENV"] = "TEST"
os.environ["DOTENV_FILE"] = str(DOTENV_FILE)
os.environ["CONFIG_FILE"] = str(CONFIG_FILE)
os.environ["DATABASE_URL"] = get_db_url()
return True | 22f4953d9f2defd4f2af159b821e408bb60e7db7 | 3,650,822 |
def any_toggle_enabled(*toggles):
"""
Return a view decorator for allowing access if any of the given toggles are
enabled. Example usage:
@toggles.any_toggle_enabled(REPORT_BUILDER, USER_CONFIGURABLE_REPORTS)
def delete_custom_report():
pass
"""
def decorator(view_func):
@w... | 25f48e9227f5c6ff74ae9874ac0b3b7ad010861b | 3,650,823 |
def moguls(material, height, randomize, coverage, det, e0=20.0, withPoisson=True, nTraj=defaultNumTraj, dose=defaultDose, sf=True, bf=True, optimize=True, xtraParams=defaultXtraParams):
"""moguls(material, radius, randomize, det, [e0=20.0], [withPoisson=True], [nTraj=defaultNumTraj], [dose = 120.0], [sf=True], [bf=... | 182aa248962877636e18860b46d20335eb535074 | 3,650,824 |
def link_datasets(yelp_results, dj_df, df_type="wages"):
"""
(Assisted by Record Linkage Toolkit library and documentation)
This functions compares the Yelp query results to database results and
produces the best matches based on computing the qgram score. Depending
on the specific database table c... | 326857d5060ac5cedcac3de90ce284048b2d2fa7 | 3,650,825 |
def hello():
"""Say Hello, so that we can check shared code."""
return b"hello" | 7197ed31c5fde419d4607ca1b5dbec7f8cb20608 | 3,650,826 |
def loglog_mean_lines(x, ys, axis=0, label=None, alpha=0.1):
""" Log-log plot of lines and their mean. """
return _plot_mean_lines(partial(plt.loglog, x), ys, axis, label, alpha) | 2f4461ca21c2f8db9ddfd763f474ebc73f3bf636 | 3,650,827 |
import osgeo.ogr
def read_lines_from_shapefile(fpath):
""" Read coordinates of cutting line segments from a ESRI Shapefile
containing line features.
Parameters
----------
fpath
Name of a file containing coordinates of cutting lines
Returns
--------
... | 9eca9204a577dc0f7d675703c75ba5d407a0338b | 3,650,828 |
def generate_identifier(endpoint_description: str) -> str:
"""Generate ID for model."""
return (
Config.fdk_publishers_base_uri()
+ "/fdk-model-publisher/catalog/"
+ sha1(bytes(endpoint_description, encoding="utf-8")).hexdigest() # noqa
) | 30bfc15c12b47f637627391a45bb9b5f9355c4f7 | 3,650,829 |
def depthFirstSearch(problem):
"""Search the deepest nodes in the search tree first."""
stack = util.Stack() # Stack used as fringe list
stack.push((problem.getStartState(),[],0))
return genericSearch(problem,stack) | 67452934a29e9857f90b88f3fead67d101468471 | 3,650,830 |
import argparse
def parse_cli_args() -> argparse.Namespace:
"""
Parse arguments passed via Command Line Interface (CLI).
:return:
namespace with arguments
"""
parser = argparse.ArgumentParser(description='Algorithmic composition of dodecaphonic music.')
parser.add_argument(
'-... | 9014ee342b810ec1b63f7ed80811f55b7ed4d00f | 3,650,831 |
def create_app():
"""
Method to init and set up the Flask application
"""
flask_app = MyFlask(import_name="dipp_app")
_init_config(flask_app)
_setup_context(flask_app)
_register_blueprint(flask_app)
_register_api_error(flask_app)
return flask_app | bfb64ac71fcd076fe26c3b342c33af30370be8db | 3,650,832 |
def find_consumes(method_type):
"""
Determine mediaType for input parameters in request body.
"""
if method_type in ('get', 'delete'):
return None
return ['application/json'] | 785e70e41629b0386d8b86f247afaf5bff3b7ba9 | 3,650,833 |
def preprocess(text):
""" Simple Arabic tokenizer and sentencizer. It is a space-based tokenizer. I use some rules to handle
tokenition exception like words containing the preposition 'و'. For example 'ووالدته' is tokenized to 'و والدته'
:param text: Arabic text to handle
:return: list of tokenized sen... | 48a44391413045a49d6d9f2dff20dcd89734b4f2 | 3,650,834 |
def login(client, password="pass", ):
"""Helper function to log into our app.
Parameters
----------
client : test client object
Passed here is the flask test client used to send the request.
password : str
Dummy password for logging into the app.
Return
-------
post re... | 5adca2e7d54dabe47ae92f0bcebb93e0984617b1 | 3,650,835 |
def define_dagstermill_solid(
name,
notebook_path,
input_defs=None,
output_defs=None,
config_schema=None,
required_resource_keys=None,
output_notebook=None,
output_notebook_name=None,
asset_key_prefix=None,
description=None,
tags=None,
):
"""Wrap a Jupyter notebook in a s... | 48097a7bed7ef84ad8d9df4eeef835f3723cb391 | 3,650,836 |
import torch
def denormalize_laf(LAF: torch.Tensor, images: torch.Tensor) -> torch.Tensor:
"""De-normalizes LAFs from scale to image scale.
B,N,H,W = images.size()
MIN_SIZE = min(H,W)
[a11 a21 x]
[a21 a22 y]
becomes
[a11*MIN_SIZE a21*MIN_SIZE x*W]
[a21*MIN_... | 51b8c81359237a9e102c1cd33bb7d1ab16c39893 | 3,650,837 |
import os
import shutil
def project_main(GIS_files_path, topath):
""" This main function reads the GIS-layers in GIS_files_path and separates them by raster and vector data.
Projects the data to WGS84 UMT37S
Moves all files to ../Projected_files
Merges the files named 'kV' to two merged shape file of ... | a686608a7c82aed75e7a8606e2ca1ca5b3bc7f02 | 3,650,838 |
import re
def parse_regex_flags(raw_flags: str = 'gim'):
"""
parse flags user input and convert them to re flags.
Args:
raw_flags: string chars representing er flags
Returns:
(re flags, whether to return multiple matches)
"""
raw_flags = raw_flags.lstrip('-') # compatibilit... | 71816c57f4e4f6dac82b4746b534a680745bc730 | 3,650,839 |
import argparse
def create_parser():
""" Create argparse object for this CLI """
parser = argparse.ArgumentParser(
description="Remove doubled extensions from files")
parser.add_argument("filename", metavar="file",
help="File to process")
return parser | c5acd1d51161d7001d7a6842fa87ff0cf61a03ef | 3,650,840 |
def has_answer(answers, retrieved_text, match='string', tokenized: bool = False):
"""Check if retrieved_text contains an answer string.
If `match` is string, token matching is done between the text and answer.
If `match` is regex, we search the whole text with the regex.
"""
if not isinstance(answe... | f0107006d2796e620cd1a47ef9e79c1c5cc1fd7a | 3,650,841 |
def get_utm_zone(srs):
"""
extracts the utm_zone from an osr.SpatialReference object (srs)
returns the utm_zone as an int, returns None if utm_zone not found
"""
if not isinstance(srs, osr.SpatialReference):
raise TypeError('srs is not a osr.SpatialReference instance')
if srs.IsProjec... | 3ee1f9780ce0fbfd843ea6b72627e90e16fd1549 | 3,650,842 |
def get_documents_meta_url(project_id: int, limit: int = 10, host: str = KONFUZIO_HOST) -> str:
"""
Generate URL to load meta information about the Documents in the Project.
:param project_id: ID of the Project
:param host: Konfuzio host
:return: URL to get all the Documents details.
"""
re... | b538d028844a2f769e8700995d1052b440592046 | 3,650,843 |
def parse_params_from_string(paramStr: str) -> dict:
""" Create a dictionary representation of parameters in PBC format
"""
params = dict()
lines = paramStr.split('\n')
for line in lines:
if line:
name, value = parse_param_line(line)
add_param(params, name, value)
... | fbf8c8cfffd0c411cc4a83760f373dd4e02eec1e | 3,650,844 |
def hstack(gctoos, remove_all_metadata_fields=False, error_report_file=None, fields_to_remove=[], reset_ids=False):
""" Horizontally concatenate gctoos.
Args:
gctoos (list of gctoo objects)
remove_all_metadata_fields (bool): ignore/strip all common metadata when combining gctoos
error_... | 5da84b3db052dd54c8f3a41ecf0cc20dd3d2f187 | 3,650,845 |
def number_fixed_unused_variables(block):
"""
Method to return the number of fixed Var components which do not appear
within any activated Constraint in a model.
Args:
block : model to be studied
Returns:
Number of fixed Var components which do not appear within any activated
... | a6432160bc52ac3e5682b255c951388242bbc2b0 | 3,650,846 |
def tunnelX11( node, display=None):
"""Create an X11 tunnel from node:6000 to the root host
display: display on root host (optional)
returns: node $DISPLAY, Popen object for tunnel"""
if display is None and 'DISPLAY' in environ:
display = environ[ 'DISPLAY' ]
if display is None:
... | a0e824bef4d23dd3a8a5c25653bf778731de180e | 3,650,847 |
import os
def static_docs(file_path):
"""Serve the 'docs' folder static files and redirect folders to index.html.
:param file_path: File path inside the 'docs' folder.
:return: Full HTTPResponse for the static file.
"""
if os.path.isdir(os.path.join(document_root, 'docs', file_path)):
ret... | 14af4c310d09756e3dcd63335bc3d03d2be28dca | 3,650,848 |
import collections
def get_aws_account_id_file_section_dict() -> collections.OrderedDict:
"""~/.aws_accounts_for_set_aws_mfa から Section 情報を取得する"""
# ~/.aws_accounts_for_set_aws_mfa の有無を確認し、なければ生成する
prepare_aws_account_id_file()
# 該当 ini ファイルのセクション dictionary を取得
return Config._sections | 51eb94857d62b91c5fcfe978b3cd2a32cbefb6ae | 3,650,849 |
from datetime import datetime
def profile(request, session_key):
"""download_audio.html renderer.
:param request: rest API request object.
:type request: Request
:param session_key: string representing the session key for the user
:type session_key: str
:return: Just another django mambo... | ba39b5a69c062ab62f83f46f7044f403120016ca | 3,650,850 |
import requests
def pipFetchLatestVersion(pkg_name: str) -> str:
"""
Fetches the latest version of a python package from pypi.org
:param pkg_name: package to search for
:return: latest version of the package or 'not found' if error was returned
"""
base_url = "https://pypi.org/pypi"
reques... | f1a49d31f4765a1a2ddc5942792a74be211fef49 | 3,650,851 |
import subprocess
def _GetLastAuthor():
"""Returns a string with the author of the last commit."""
author = subprocess.check_output(['git', 'log',
'-1',
'--pretty=format:"%an"']).splitlines()
return author | 82159cf4d882d6cace29802892dacda1bfe6b6b2 | 3,650,852 |
def mock_datasource_http_oauth2(mock_datasource):
"""Mock DataSource object with http oauth2 credentials"""
mock_datasource.credentials = b"client_id: FOO\nclient_secret: oldisfjowe84uwosdijf"
mock_datasource.location = "http://foo.com"
return mock_datasource | 8496f6b9ac60af193571f762eb2ea925915a1223 | 3,650,853 |
def find_certificate_name(file_name):
"""Search the CRT for the actual aggregator name."""
# This loop looks for the collaborator name in the key
with open(file_name, 'r') as f:
for line in f:
if 'Subject: CN=' in line:
col_name = line.split('=')[-1].strip()
... | 853ec62b69feebd86c7a56e1d47b2c12e7f56d63 | 3,650,854 |
import sys
import os
import imp
def _find_module(module):
"""Find module using imp.find_module.
While imp is deprecated, it provides a Python 2/3 compatible
interface for finding a module. We use the result later to load
the module with imp.load_module with the '__main__' name, causing
it to exec... | b76b72cfc666e78b5b880c95bdc196b469722822 | 3,650,855 |
from typing import List
def float2bin(p: float, min_bits: int = 10, max_bits: int = 20, relative_error_tol=1e-02) -> List[bool]:
""" Converts probability `p` into binary list `b`.
Args:
p: probability such that 0 < p < 1
min_bits: minimum number of bits before testing relative error.
... | 1b25f84255ace0503f06ae2ab9f8dc650206176c | 3,650,856 |
def bin_thresh(img: np.ndarray, thresh: Number) -> np.ndarray:
"""
Performs binary thresholding of an image
Parameters
----------
img : np.ndarray
Image to filter.
thresh : int
Pixel values >= thresh are set to 1, else 0.
Returns
-------
np.ndarray :
Binariz... | 9064fb5f50c22aabc73bf63d3a818b6898a19a58 | 3,650,857 |
from mathutils import Matrix, Vector, Euler
def add_object_align_init(context, operator):
"""
Return a matrix using the operator settings and view context.
:arg context: The context to use.
:type context: :class:`bpy.types.Context`
:arg operator: The operator, checked for location and rotation pr... | 6bd32226c7024245b1252c3a51f5ae713f43a1b2 | 3,650,858 |
import pickle
def load_dataset():
"""
load dataset
:return: dataset in numpy style
"""
data_location = 'data.pk'
data = pickle.load(open(data_location, 'rb'))
return data | 9467826bebfc9ca3ad1594904e9f3195e345c065 | 3,650,859 |
def video_feed():
"""Return camera live feed."""
return Response(gen(Camera()),
mimetype='multipart/x-mixed-replace; boundary=frame') | 87c9ae8aa84fe17a16b040d56fbdaac6351e0706 | 3,650,860 |
def area_in_squaremeters(geodataframe):
"""Calculates the area sizes of a geo dataframe in square meters.
Following https://gis.stackexchange.com/a/20056/77760 I am choosing equal-area projections
to receive a most accurate determination of the size of polygons in the geo dataframe.
Instead of Gall-Pet... | 47a2ae042c8cda7fa6b66ccd011d0293afb36504 | 3,650,861 |
import scipy
def add_eges_grayscale(image):
""" Edge detect.
Keep original image grayscale value where no edge.
"""
greyscale = rgb2gray(image)
laplacian = np.array([[0, -1, 0], [-1, 4, -1], [0, -1, 0]])
edges = scipy.ndimage.filters.correlate(greyscale, laplacian)
for index,value in np.nd... | 0cba5152578722693d0d796252a99973e980b365 | 3,650,862 |
def generateFromSitePaymentObject(signature: str, account_data: dict, data: dict)->dict:
"""[summary]
Creates object for from site chargment request
Args:
signature (str): signature hash string
account_data (dict): merchant_account: str
merchant_domain: str
... | 149434694e985956dede9bf8b6b0da1215ac9963 | 3,650,863 |
def deal_weights(node, data=None):
""" deal the weights of the custom layer
"""
layer_type = node.layer_type
weights_func = custom_layers[layer_type]['weights']
name = node.layer_name
return weights_func(name, data) | a2a271ea0aeb94a1267dbc06da8997985b81633e | 3,650,864 |
def label_brand_generic(df):
""" Correct the formatting of the brand and generic drug names """
df = df.reset_index(drop=True)
df = df.drop(['drug_brand_name', 'drug_generic_name'], axis=1)
df['generic_compare'] = df['generic_name'].str.replace('-', ' ')
df['generic_compare'] = df['generic_compare']... | a421eece6e595159847821abcaf2cf7dd8dc88c5 | 3,650,865 |
def RMSRE(
image_true: np.ndarray,
image_test: np.ndarray,
mask: np.ndarray = None,
epsilon: float = 1e-9,
) -> float:
"""Root mean squared relative error (RMSRE) between two images within the
specified mask. If not mask is specified the entire image is used.
Parameters
----------
i... | 6b377b2588ef0c02f059248d3214e0d7960ca25b | 3,650,866 |
import PIL
import logging
def getImage(imageData, flag):
"""
Returns the PIL image object from imageData based on the flag.
"""
image = None
try:
if flag == ENHANCED:
image = PIL.Image.open(imageData.enhancedImage.file)
elif flag == UNENHANCED:
image = PIL.... | a3aaa80bc396fcdf099d5963706d21d63a6dcf0d | 3,650,867 |
def save_record(record_type,
record_source,
info,
indicator,
date=None):
"""
A convenience function that calls 'create_record' and also saves the resulting record.
:param record_type: The record type, which should be a value from the RecordTyp... | 903eb7333cfd2cc534812c5417e5e32a7769ffe4 | 3,650,868 |
def update_product_price(pid: str, new_price: int):
""" Update product's price
Args:
pid (str): product id
new_price (int): new price
Returns:
dict: status(success, error)
"""
playload = {'status': ''}
try:
connection = create_connection()
with connectio... | fff3723a9138724f1957cd9a669cdcf79e4ed4e5 | 3,650,869 |
def select_n_products(lst, n):
"""Select the top N products (by number of reviews)
args:
lst: a list of lists that are (key,value) pairs for (ASIN, N-reviews)
sorted on the number of reviews in reverse order
n: a list of three numbers,
returns:
a list of... | ed052708010512758845186ae9e4fb33b41bc511 | 3,650,870 |
def load_vanHateren(params):
"""
Load van Hateren data and format as a Dataset object
Inputs:
params [obj] containing attributes:
data_dir [str] directory to van Hateren data
rand_state (optional) [obj] numpy random state object
num_images (optional) [int] how many images to extract. Default... | ca32f182f5534da89df0bd5454e74a586c6ca4d6 | 3,650,871 |
import argparse
def build_parser() -> argparse.ArgumentParser:
"""Builds and returns the CLI parser."""
# Help parser
help_parser = argparse.ArgumentParser(add_help=False)
group = help_parser.add_argument_group('Help and debug')
group.add_argument('--debug',
help='Enable d... | 0be83ee2e497f2c5ccfd21c4a4414c587304e6ee | 3,650,872 |
import argparse
import sys
def parse_args():
"""Parse command-line args.
"""
parser = argparse.ArgumentParser(description = 'Upload (JSON-encoded) conformance resources from FHIR IGPack tar archive.', add_help = False)
parser.add_argument('-h', '--help', action = 'store_true', help = 'show this help ... | 7c0ae02e07706ef212417ee7d0c4dd11a1de945c | 3,650,873 |
import torch
def wrap_to_pi(inp, mask=None):
"""Wraps to [-pi, pi)"""
if mask is None:
mask = torch.ones(1, inp.size(1))
if mask.dim() == 1:
mask = mask.unsqueeze(0)
mask = mask.to(dtype=inp.dtype)
val = torch.fmod((inp + pi) * mask, 2 * pi)
neg_mask = (val * mask) < 0
va... | 7aca43bb2146c1cad07f9a070a7099e6fb8ad857 | 3,650,874 |
import pandas
def if_pandas(func):
"""Test decorator that skips test if pandas not installed."""
@wraps(func)
def run_test(*args, **kwargs):
try:
except ImportError:
pytest.skip('Pandas not available.')
else:
return func(*args, **kwargs)
return run_test | b39f88543559c4f4f1b9bb5bb30768916d3708d6 | 3,650,875 |
def handle_front_pots(pots, next_pots):
"""Handle front, additional pots in pots."""
if next_pots[2] == PLANT:
first_pot = pots[0][1]
pots = [
[next_pots[2], first_pot - 1]] + pots
return pots, next_pots[2:]
return pots, next_pots[3:] | 53ec905a449c0402946cb8c28852e81da80a92ef | 3,650,876 |
import types
def environment(envdata):
"""
Class decorator that allows to run tests in sandbox against different Qubell environments.
Each test method in suite is converted to <test_name>_on_environemnt_<environment_name>
:param params: dict
"""
#assert isinstance(params, dict), "@environment ... | 9ce82ff8ee3627f8795b7bc9634c298e8ff195bc | 3,650,877 |
def get_domain_name(url):
""" Returns the domain name from a URL """
parsed_uri = urlparse(url)
return parsed_uri.netloc | 00160285a29a4b2d1fe42fb8ec1648ca4c31fa8b | 3,650,878 |
def get_answer_str(answers: list, scale: str):
"""
:param ans_type: span, multi-span, arithmetic, count
:param ans_list:
:param scale: "", thousand, million, billion, percent
:param mode:
:return:
"""
sorted_ans = sorted(answers)
ans_temp = []
for ans in sorted_ans:
ans... | 734015503ccec63265a0531aa05e8bd8514c7c15 | 3,650,879 |
def user_0post(users):
"""
Fixture that returns a test user with 0 posts.
"""
return users['user2'] | 5401e7f356e769b5ae68873f2374ef74a2d439c6 | 3,650,880 |
import os
def initialize():
"""
Initialize some parameters, such as API key
"""
api_key = os.environ.get("api_key") # None when not exist
if api_key and len(api_key) == 64: # length of a key should be 64
return api_key
print("Please set a valid api_key in the environment variables.")... | 2589aeea4db2d1d1f20de03bc2425e1835eb2f69 | 3,650,881 |
def plot_tuning_curve_evo(data, epochs=None, ax=None, cmap='inferno_r',
linewidth=0.3, ylim='auto',
include_true=True,
xlabel='Bandwidths',
ylabel='Average Firing Rate'):
"""
Plot evolution of TC averaged ove... | f571339b8a306304e1807ef3dd0f4b93e6856dd5 | 3,650,882 |
import json
def transportinfo_decoder(obj):
"""Decode programme object from json."""
transportinfo = json.loads(obj)
if "__type__" in transportinfo and transportinfo["__type__"] == "__transportinfo__":
return TransportInfo(**transportinfo["attributes"])
return transportinfo | 8a311cb419e9985ef0a184b82888220c0f3258b2 | 3,650,883 |
def group_events_data(events):
"""
Group events according to the date.
"""
# e.timestamp is a datetime.datetime in UTC
# change from UTC timezone to current seahub timezone
def utc_to_local(dt):
tz = timezone.get_default_timezone()
utc = dt.replace(tzinfo=timezone.utc)
lo... | de2f2031bdcaaf2faffdb99c67bbbb1e15828ef8 | 3,650,884 |
def create_matrix(PBC=None):
"""
Used for calculating distances in lattices with periodic boundary conditions. When multiplied with a set of points, generates additional points in cells adjacent to and diagonal to the original cell
Args:
PBC: an axis which does not have periodic boundary condition.... | 7470803fe8297ef2db1ce4bd159e9d9c93d34787 | 3,650,885 |
def get_additive_seasonality_linear_trend() -> pd.Series:
"""Get example data for additive seasonality tutorial"""
dates = pd.date_range(start="2017-06-01", end="2021-06-01", freq="MS")
T = len(dates)
base_trend = 2
state = np.random.get_state()
np.random.seed(13)
observations = base_trend *... | 034b4ca9e086e95fa1663704fda91ae3986694b4 | 3,650,886 |
def is_client_trafic_trace(conf_list, text):
"""Determine if text is client trafic that should be included."""
for index in range(len(conf_list)):
if text.find(conf_list[index].ident_text) != -1:
return True
return False | 0b7fdf58e199444ea52476d5621ea9353475b0a0 | 3,650,887 |
def isinf(x):
"""
For an ``mpf`` *x*, determines whether *x* is infinite::
>>> from sympy.mpmath import *
>>> isinf(inf), isinf(-inf), isinf(3)
(True, True, False)
"""
if not isinstance(x, mpf):
return False
return x._mpf_ in (finf, fninf) | 4d5ca6ac2f8ed233a70c706b7fff97bf171c4f21 | 3,650,888 |
def formalize_switches(switches):
"""
Create all entries for the switches in the topology.json
"""
switches_formal=dict()
for s, switch in enumerate(switches):
switches_formal["s_"+switch]=formalize_switch(switch, s)
return switches_formal | 8dbb9987e5bc9c9f81afc0432428a746e2f05fc4 | 3,650,889 |
def arp_scores(run):
"""
This function computes the Average Retrieval Performance (ARP) scores according to the following paper:
Timo Breuer, Nicola Ferro, Norbert Fuhr, Maria Maistro, Tetsuya Sakai, Philipp Schaer, Ian Soboroff.
How to Measure the Reproducibility of System-oriented IR Experiments.
... | 0e23eb1d6ee3c2502408585b1d0dbb0993ca7628 | 3,650,890 |
from typing import Tuple
from typing import Optional
import scipy
def bayesian_proportion_test(
x:Tuple[int,int],
n:Tuple[int,int],
prior:Tuple[float,float]=(0.5,0.5),
prior2:Optional[Tuple[float,float]]=None,
num_samples:int=1000,
seed:int=8675309) -> Tuple[float,floa... | 5f63424b9dcb6e235b13a9e63f0b9a2dc1e95b31 | 3,650,891 |
import torch
def _create_triangular_filterbank(
all_freqs: Tensor,
f_pts: Tensor,
) -> Tensor:
"""Create a triangular filter bank.
Args:
all_freqs (Tensor): STFT freq points of size (`n_freqs`).
f_pts (Tensor): Filter mid points of size (`n_filter`).
Returns:
fb (... | 1ad5bd58d673626a15e27b6d9d68829299fe7636 | 3,650,892 |
def convert_millis(track_dur_lst):
""" Convert milliseconds to 00:00:00 format """
converted_track_times = []
for track_dur in track_dur_lst:
seconds = (int(track_dur)/1000)%60
minutes = int(int(track_dur)/60000)
hours = int(int(track_dur)/(60000*60))
converted_time = '%... | 3d5199da01529f72b7eb6095a26e337277f3c2c9 | 3,650,893 |
def sync_xlims(*axes):
"""Synchronize the x-axis data limits for multiple axes. Uses the maximum
upper limit and minimum lower limit across all given axes.
Parameters
----------
*axes : axis objects
List of matplotlib axis objects to format
Returns
-------
out : yxin, xmax
... | a377877a9647dfc241db482f8a2c630fe3eed146 | 3,650,894 |
def algo_config_to_class(algo_config):
"""
Maps algo config to the IRIS algo class to instantiate, along with additional algo kwargs.
Args:
algo_config (Config instance): algo config
Returns:
algo_class: subclass of Algo
algo_kwargs (dict): dictionary of additional kwargs to pa... | 884ab7a91d9d8c901d078f9b477d5d21cba3e5ff | 3,650,895 |
def group_by_key(dirnames, key):
"""Group a set of output directories according to a model parameter.
Parameters
----------
dirnames: list[str]
Output directories
key: various
A field of a :class:`Model` instance.
Returns
-------
groups: dict[various: list[str]]
... | b291cd889c72fb198400b513e52ff9417c8d93b7 | 3,650,896 |
def redistrict_grouped(df, kind, group_cols, district_col=None,
value_cols=None, **kwargs):
"""Redistrict dataframe by groups
Args:
df (pandas.DataFrame): input dataframe
kind (string): identifier of redistrict info (e.g. de/kreise)
group_cols (list): List of colu... | 21f6514ca15d5fff57d03dab9d0bb7693c132e95 | 3,650,897 |
from typing import Tuple
from typing import List
import torch
def count_wraps_rand(
nr_parties: int, shape: Tuple[int]
) -> Tuple[List[ShareTensor], List[ShareTensor]]:
"""Count wraps random.
The Trusted Third Party (TTP) or Crypto provider should generate:
- a set of shares for a random number
... | b16e21be2d421e134866df8929a319a19bdd304a | 3,650,898 |
from typing import Sequence
def text_sim(
sc1: Sequence,
sc2: Sequence,
) -> float:
"""Returns the Text_Sim similarity measure between two pitch class sets.
"""
sc1 = prime_form(sc1)
sc2 = prime_form(sc2)
corpus = [text_set_class(x) for x in sorted(allClasses)]
vectorizer = Tfidf... | 6479ad4916fb78d69935fb9b618c5eb02951f05a | 3,650,899 |
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