content stringlengths 35 416k | sha1 stringlengths 40 40 | id int64 0 710k |
|---|---|---|
def get_start_timestamp_mapping(file_path):
"""Get mapping of video name id to star timestamp."""
mapping = {}
with open(file_path) as f_in:
for line in f_in.readlines():
if line.strip() == '':
continue
video_name, time_txt = line.strip().split(',')
... | 15a9ea922c60d018ffde0e407db097027c034057 | 651,544 |
from typing import Any
def is_iterate(value: Any) -> bool:
"""Return `True` if `value` is an "iterate" directive."""
return type(value) is dict and "iterate" in value | 3d436eb22c6e8bcb3a2429b91cf274c07c000873 | 651,545 |
def judgeWhetherNULL(param, lastOne=False):
"""
判断前台传过来的数据，如果是null则将SQL字串改为NULL，否则插入对应类型的数据
:param param: SQL参数
:param lastOne: 是否是最后一个参数
:return:
"""
if not lastOne:
if param is None:
return 'NULL, '
else:
if isinstance(param, int):
return '%d, ' % param
else:
return "'%s', " % param
else:... | f77f2a21a6b81295a3cd196944672333b050c67f | 651,547 |
import re
def add_datepart(df, fieldname):
"""
Adds date related features to dataframe df inplace
df: dataframe
fieldname: name of the date field in df
"""
new_df = df.copy()
field = df[fieldname]
target_prefix = re.sub('[Dd]atetime$', '', fieldname)
date_features = (
... | 7774056dd856553501f288c9c97dbc04d359ae59 | 651,549 |
def _apply_signed_threshold(value, min_thr=None, max_thr=None):
"""
Apply threshold on signed value.
usage examples :
>>> _apply_signed_threshold(0.678, min_thr=0.5)
0.5
>>> _apply_signed_threshold(-0.678, min_thr=0.5)
-0.5
>>> _apply_signed_threshold(0.678, max_thr=2.0)
0.678
>>> _apply_signed_thres... | 098a37ec49930634475868c12ffe8bf28b252a48 | 651,550 |
def list_sorted(words):
""" Check if a Tuple of words are Anagrams using Sorted
:param words: Tuple
:return: bool
"""
word_one, word_two = words
return sorted(word_one) == sorted(word_two) | e6449769d51571a8faaab0cbcf51aa7800d766e8 | 651,551 |
def select_hannover_from_metadata(metadata):
"""Select entries from Hannover"""
return metadata.query('doi == "10.6084/m9.figshare.12275009"') | 0400073dcd9a752df4352f4d3e1195fe23fae6d5 | 651,552 |
import hashlib
def get_fd_hash(fd):
"""
Compute the sha256 hash of the bytes in a file-like
"""
BLOCKSIZE = 1 << 16
hasher = hashlib.sha256()
old_pos = fd.tell()
fd.seek(0)
buf = fd.read(BLOCKSIZE)
while buf:
hasher.update(buf)
buf = fd.read(BLOCKSIZE)
fd.seek(o... | 2607d44feeeabe38e3ea240f800e8e42add3ff7a | 651,553 |
def decline_weak_neuter_noun(ns: str, gs: str, np: str):
"""
Gives the full declension of weak neuter nouns.
>>> decline_weak_neuter_noun("auga", "auga", "augu")
[['auga', 'auga', 'auga', 'auga'], ['augu', 'augu', 'augum', 'augna']]
>>> decline_weak_neuter_noun("hjarta", "hjarta", "hjörtu")
[[... | 2589aa79afa240c65b3bd6b4334f52fc2c9f66db | 651,554 |
def crop(img, left=None, right=None, top=None, bottom=None):
"""Crop image.
Automatically limits the crop if bounds are outside the image.
:param numpy.ndarray img: Input image.
:param int left: Left crop.
:param int right: Right crop.
:param int top: Top crop.
:param int bottom: Bottom cr... | e4d18b959c9f0f55f9c6d24a41658922e34b53c0 | 651,556 |
import yaml
def open_yaml(path):
"""Open yaml file and return as a dictionary"""
data = {}
with open(path) as open_file:
data = yaml.safe_load(open_file)
return data | 81cc6a046566ec4a9d365ed14d26036e5b6c1005 | 651,557 |
import logging
def getLogger(name):
"""
Returns a logger. Wrapper of logging.getLogger
"""
logger = logging.getLogger(name)
return logger | 85ea7245ff87a26d127b54a20b5e852d6d09d7d6 | 651,558 |
def isPerfectSquare(num: int) -> bool:
"""Okay. Solution is O(1)."""
r = int(num ** 0.5)
return r * r == num | 9531efd2433711803d35fa6ddce4cd34e691ec8a | 651,559 |
import numpy
def isempty(s):
"""
checks that a string is empty, returns also True if s is ``NaN``
@param s ``str`` or ``numpy.NaN``
@return boolean
The function imports :epkg:`numpy` (delayed import).
"""
if s is None:
return True
if isinstance(s, str):... | a615538a1e5aa0ec27e51a7f768d77277f57fd18 | 651,560 |
def find_missing_keywords(keywords, text):
"""
Return the subset of keywords which are missing from the given text
"""
found = set()
for key in keywords:
if key in text:
found.add(key)
return list(set(keywords) - found) | 4612511654aae93104c6a1edc98b1b4927619539 | 651,561 |
def build_complement(dna):
"""
This function find A to T, T to A, C to G, Gto C.
"""
ans = ''
for base in dna:
if base == 'A':
ans += 'T'
elif base == 'T':
ans += 'A'
elif base == 'C':
ans += 'G'
elif base == 'G':
ans +=... | e08d7331b8390057faba470ce1e7c7283a0ff378 | 651,562 |
def remove_readonly_fields(patron):
""" remove readonly fields from patron dict
must run patron records through this fn before PUTting to Koha """
read_only_patron_fields = ("anonymized", "restricted", "updated_on")
for field in read_only_patron_fields:
patron.pop(field, None)
return patron | 980d936278726ed17567c543f22130cba117c009 | 651,563 |
import subprocess
def get_db2_inst_fmp_user():
"""
Retrieve the db2 instance and fmp user names
"""
instusr = subprocess.Popen(
["ps", "-o", "user", "-C", "db2sysc"],
stdout=subprocess.PIPE
).communicate()[0].strip().splitlines()[1].strip()
fmpusr = [x for x in subprocess.Popen... | 6ed6ed6189939b3d49474a58e02584544c66b108 | 651,565 |
import configparser
def readConfig(file="config.ini"):
"""Extract IP addresses and CMDS from config file and returns tuple"""
ips = []
cmds = []
Config = configparser.ConfigParser()
Config.read(file)
machines = Config.items("MACHINES")
commands = Config.items("COMMANDS")
for ip in mach... | e22d5f85a0f4dfbbcf76cc5de269bee5a7a863de | 651,567 |
import re
def file_path(f_name):
"""
find path of file
"""
list_path = re.findall("(.*/).*", f_name)
file_path = list_path[0] if not list_path == [] else f_name
return file_path | 5687921b573bcaad1f760945cb57dc41f142310e | 651,568 |
def samplesheet_headers_to_dict(samplesheet_headers: list) -> dict:
"""
Given a list of headers extracted with extract_samplesheet_header_fields, will parse them into a dictionary
:param samplesheet_headers: List of header lines
:return: Dictionary containing data that can be fed directly into the RunSa... | 2df9d99d0971ce182e8e62453c5b7006918806d0 | 651,569 |
from typing import Dict
from typing import Any
from typing import List
import yaml
def insert_worker(worker: Dict[str, Any], workers: List[Dict[str,
Any]]) -> None:
"""Inserts client or server into a list, without inserting duplicates."""
def dump(... | 35d9e908dbc2f706034ab70ca78e890ea79736e7 | 651,571 |
def spin_forward(time, co, particles=[], **kwargs):
"""A function that continues to
simulate the galaxy without graphing,
so we can check long term behaviour more frugally"""
for i in range(0, int(time / co.tstep)):
for j in range(0, len(particles)):
particles[j].sim(particles, co)
... | d36d29e8f97c310959062b0956d8872dfb27d8f6 | 651,572 |
from typing import Any
import requests
import json
def stateful_json_request(page_url: str, api_url: str) -> Any:
"""Query SEPAQ API.
SEPAQ API requires to get a cookie from a main page to disambiguate
the API (park, cabin, ...).
"""
# Aquire cookies on main page
page_response = requests.get(... | e0234447d60b4b9be807c205b9dfcb5285972869 | 651,575 |
def solve_5bd6f4ac(x):
"""
- Problem : 5bd6f4ac \n
*General Description* (Problem and solving it visually - intuition):
I get the zoomed in grid, only containing the top right third of the original input grid.\n
*Algorithm* (to guide understandiing of the code)
- Fi... | 07e9de65e2284fa3a3c6a6dc5165af44440cda17 | 651,576 |
def calc_score(res):
"""
#res --> array formato così
#0: [true_razza1, true_razza2, Cane] #--> Cane è il cane predetto dalla rete!
#1: [true_razza1, true_razza2, Cane] #--> Cane è il cane predetto dalla rete!
# ...
#Se true_razza2 = None --> cane puro altrimenti incrocio
-- Punteggio alla ... | 30b9870e41be825207cf4752c869dd7e2ed2cf89 | 651,577 |
def set_windows_slashes(directory):
"""
Set all the slashes in a name so they use Windows slashes (\)
:param directory: str
:return: str
"""
return directory.replace('/', '\\').replace('//', '\\') | dcca256d71133d1d394df30177bd151ae059a065 | 651,578 |
def parse_google_events_for_nav_apt(event_objects, rqst_apt_datetime):
"""
This function takes a list of Google event objects from the navigator's 'Navigator-Consumer Appointments (DO NOT CHANGE)'
calendar and returns the appointment id whose start time matches the given datetime.
:param event_objects:... | a1bcb4ba8e39279273274976f62b52e210b4b683 | 651,579 |
def to_str(s):
"""Parse a string and strip the extra characters."""
return str(s).strip() | 1e978481b926e82e1f72c16ca15c3bf2a6db1b53 | 651,580 |
def remove_prefix(text: str, prefix: str) -> str:
"""
Removes the prefix if it is present, otherwise returns the original string.
"""
if text.startswith(prefix):
return text[len(prefix):]
return text | acd31410ef982adba2eb69d2553a0eaa0df9b5f9 | 651,581 |
def classesByCredits (theDictionary, credits):
"""Lists the courses worth a specific credit value.
:param dict[str, int] theDictionary: The student's class information
with the class as the key and the number or credits as the value
:param int credits: The credit value by which classes are queried
... | 1169d8d52977d808d73993b135beef2daa64e89b | 651,582 |
import math
def _score_flops(tree):
"""Score by flops but split ties with size.
"""
return math.log2(tree.total_flops()) + math.log2(tree.max_size()) / 1000 | c24323d4f270eb0886091fead65660e9509175c2 | 651,583 |
import pandas
import logging
def convert_to_floats(datalist):
""" Converts a list of data into floats, if possible. Returns the indices
of all values that cannot be casted as float.
:param datalist: The list of data (either time or voltage)
:return: Lists containing float values and indices of non-f... | 74cdc0fcf0b7ccbb696dd06f0e827ad1ec2b66a8 | 651,584 |
def revise_ksize(ksize, moltype, input_is_protein):
"""If input is protein, then divide the ksize by three"""
if moltype == "DNA":
return ksize
elif input_is_protein:
# Ksize includes codons
return int(ksize / 3)
else:
return ksize | 42877f3a00d5bf95066c7482552a74f873faf145 | 651,585 |
import base64
def _decode_string(text):
"""Decode value of the given string.
:param text: Encoded string
:return: Decoded value
"""
base64_bytes = text.encode('ascii')
message_bytes = base64.b64decode(base64_bytes)
return message_bytes.decode('ascii') | b7ab66e032ac9560a6b0c55add022f26840e2a18 | 651,587 |
def svg_line_join_style(obj):
"""Returns an SVG style string describing the linejoin for the passed
in Faint object.
"""
join = obj.get_settings().join
return "stroke-linejoin:%s;" % join | e7f11caf0020af29d7c899df9f0443cc040163c0 | 651,588 |
import os
def in_path(name):
"""
Check whether a command line tool
exists in the system path.
"""
for dirname in os.environ['PATH'].split(os.pathsep):
if os.path.exists(os.path.join(dirname, name)):
return True
return False | 323d3455ea8289354e5e3b412165a2fb4ad222c7 | 651,589 |
def _gc_commands_to_rmfiles(hsize, files):
"""Return the history files to remove to get under the command limit."""
rmfiles = []
n = 0
ncmds = 0
for ts, fcmds, f in files[::-1]:
if fcmds == 0:
# we need to make sure that 'empty' history files don't hang around
rmfiles... | 77fc0b6d279ceb907d004ddcd5d07752a7379613 | 651,590 |
def highlight_series(s):
"""
Highlight a series or datafragme with background color light gray.
An apply function for pandas styler.
Maps Series/DataFrame -> Series/Dataframe of identical
Parameters
----------
s : pandas Series or Dataframe
Returns
-------
str
css text... | 6bb27c2a6186c05b68134fca84c97418432d9e99 | 651,591 |
def create_occurence_dict(text):
"""Create the occurence dict of characters for a given text.
:text: str, ascii text
:returns: Dict[char:int], occurence dict
"""
result = {}
for c in text:
if c in result:
result[c] += 1
else:
result[c] = 1
return resu... | 827edad4ea226ddebdab1e8ec4a72895fef8497d | 651,592 |
import numpy as np
from copy import deepcopy
def make_4dshape(predictor_1d, predictor_raw, degree=4, neighbors_only=False):
"""This function makes a 2~4D polynoimal transformed version of the nucleotide predictor."""
pred_wide = np.shape(predictor_1d)[1]
predictor_out = deepcopy(predictor_1d)
Labels_... | b6023a65ba189fdb1067815f2a985e968e06457e | 651,593 |
def data_init():
"""
初始化数据和属性集。
Returns:
train_set (list): 训练集
test_set (list): 测试集
attributes (list): 属性集
is_discrete (list): 属性是否离散
"""
train_set = [['青绿', '蜷缩', '浊响', '清晰', '凹陷', '硬滑', 0.697, 0.460, '好瓜'],
['乌黑', '蜷缩', '沉闷', '清晰', '凹陷', '硬滑', 0.77... | 876dbd78ea0a480e3cc68da13aae7bfe3c9cb9db | 651,594 |
import torch
def gaussian_smearing(distances, offset, widths, centered=False):
"""
Perform gaussian smearing on interatomic distances.
Args:
distances (torch.Tensor): Variable holding the interatomic distances (B x N_at x N_nbh)
offset (torch.Tensor): torch tensor of offsets
cente... | 5efd0093bd9705ea6752517a06de5392db6f7476 | 651,595 |
def search_roles_by_name(api, configuration, api_version, api_exception, role_name):
""" Searches for a role by name and returns the ID.
:param api: The Deep Security API modules.
:param configuration: Configuration object to pass to the api client.
:param api_version: The version of the API to use.
... | e5ea95316f56a3fe742a5c71b50428c58bcf459c | 651,596 |
def get_relevant_features(features,
diff_threshold = 0.05,
active_threshold = 0.1,
inactive_threshold = 0.1):
"""
-- DESCRIPTION --
Extract "relevant" features from a set of given features. Relevant in this
case means that th... | 2ae3a49786f8d4e5e80c158add6fb2fdc85f412e | 651,598 |
def group_weights(weights):
"""
Group each layer weights together, initially all weights are dict of 'layer_name/layer_var': np.array
Example:
input: {
...: ...
'conv2d/kernel': <np.array>,
'conv2d/bias': <np.array>,
.... | 357b9eacda4fad058ffb5b1bec96ed4f030486b1 | 651,599 |
def _merging_small_segments(segment_list: list, threshold: float):
"""
merging the small voice segments that may from an utterance
:param segment_list: a list of segments
:param threshold: threshold to do the merge
:return: a merged segment list
"""
merged_list = []
merging_buffer_pos = ... | 9b60c6729d5d9c698680dfa2b6ea753830509db2 | 651,600 |
def get_leaf_certificate(chain):
"""
:param chain: certificate chain
:return: leaf certificate
"""
leaf_cert = chain[0]
for cert in chain:
for cert2 in chain:
if leaf_cert.get_subject() == cert2.get_issuer():
leaf_cert = cert2
return leaf_cert | 5962cd03ef6db9ba3d5581c8af5713752329384b | 651,601 |
def from_local_name(acs, attr, name_format):
"""
:param acs: List of AttributeConverter instances
:param attr: attribute name as string
:param name_format: Which name-format it should be translated to
:return: An Attribute instance
"""
for aconv in acs:
#print(ac.format, name_format)... | 1ffeba9bfae41f4c863a83c9854743a0a954ab32 | 651,602 |
def get_knapsack_0_1_solution(w, wt, vt, n):
"""
Print solution of 0-1 knapsack problem
:param w: total capacity
:type w: int
:param wt: weight of each element
:type wt: list[int]
:param vt: value of each element
:type vt: list[int]
:param n: number of elements
:type n: int
... | 47e3b0d5916ce6249f0c9751f6523fe710e53376 | 651,603 |
from typing import Dict
from typing import List
def dict2args(data: Dict) -> List[str]:
"""Convert a dictionary of options to command like arguments."""
result = []
# keep sorting in order to achieve a predictable behavior
for k, v in sorted(data.items()):
if v is not False:
prefix... | ef2d30a1ceeb95929b5a8e5ed2ef2af750aaaa44 | 651,604 |
def merge_np_arrays(arr1, arr2):
"""
Merges two numpy arrays containing boolean values using the logical OR operator.
:param arr1:
:param arr2:
:return:
"""
arr1[arr2] = True
return arr1 | ae022ef6f81ad8d702457ef1217b455339bf6a09 | 651,605 |
import hashlib
def _hash(example_with_id) -> str:
"""Hashes a single example."""
key = example_with_id[0], example_with_id[1]["text"]
key_bytes = str(key).encode("utf8")
return hashlib.sha256(key_bytes).hexdigest() | 112736cec9566633cabd6cfe74b8fe4780b5c861 | 651,606 |
import pickle
def reference(infile):
"""
Load the given reference profile file.
:params infile: The input filename or file object
:returns: The reference list
"""
# If the input is a string then open and read from that file
if isinstance(infile, str):
with open(infile, "rb") as i... | 550a8fdc1295e249c23a0ae3c21fb2e9c7570573 | 651,607 |
def add_element_wise(list1, list2):
"""Adds the two lists interleaved by eachother"""
return [a + b for a, b in zip(list1, list2)] | cfd3964cb12ea35b04d7252ed1666ece37c6431e | 651,608 |
import os
def get_version():
"""
Read the version.txt file to get the new version string
Generate it if version.txt is not available. Generation
is required for pip installs
"""
try:
f = open('version.txt')
except IOError:
os.system("./version.sh > version.txt")... | 64216905221b8b8874951584939b17e32d08d40e | 651,609 |
from typing import Optional
def _text_compare(t1: Optional[str], t2: Optional[str]) -> bool:
"""Compare two text strings, ignoring wrapping whitespaces.
Args:
t1:
First text.
t2:
Second text.
Returns:
True if they are equal, False otherwise.
"""
... | 965c61e565aa2608742bcd291fcdf04b26d3ff38 | 651,610 |
def load_categories():
"""Loads a csv containing all the unique categories for restaurants in the database"""
with open('data/categories.csv') as f:
categories = [cat.strip() for cat in f.readlines()]
return categories | e7c71eb524c7df69c1780091bdcc4ff9ae23a074 | 651,611 |
def invert_y_and_z_axis(input_matrix_or_vector):
"""
This Function inverts the y and the z coordinates in the corresponding matrix and vector entries
(invert y and z axis <==> rotation by 180 degree around the x axis)
For the matrix multiplication holds:
|m11 m12 m13| |x| |m11 x + m12 y + ... | 76e71af3c4ed8bae98c69ccf8fd52d383ddb0ce3 | 651,612 |
import ast
def binop(x, op, y, lineno=None, col=None):
"""Creates the AST node for a binary operation."""
lineno = x.lineno if lineno is None else lineno
col = x.col_offset if col is None else col
return ast.BinOp(left=x, op=op, right=y, lineno=lineno, col_offset=col) | cf8f0320b71ffee0f3e4916c73e7feccf8ec0160 | 651,613 |
import math
def quadratic_limb_darkening(impact, l1, l2):
"""Quadratic limb darkening. Kopal 1950, Harvard Col. Obs. Circ., 454, 1"""
impact = math.cos(impact)
return 1 - l1 * (1 - impact) - l2 * (1 - impact) ** 2 | e5305ede25a31e5e26f6138b3f35688c505857af | 651,614 |
import argparse
def parse_arguments(args):
"""
Parse the arguments from the user
"""
parser = argparse.ArgumentParser(
description= "HUMAnN2 Test\n",
formatter_class=argparse.RawTextHelpFormatter,
prog="humann2_test")
parser.add_argument(
"--run-functional-tests-to... | 3751aaae3846b348910f46384442f92c5d99fe4c | 651,616 |
def cargar_matriz_puestos(ruta_archivo: str) -> list:
"""
Esta funcion carga la informacion de la matriz de puestos estudiante
a partir de un archivo CSV.
ruta_archivo (str): la ruta del archivo que se quiere cargar
Retorno: list
La matriz con los puestos estudiante de cada facultad
... | aab3c9aadeef42983c2ebd539a0f64f64e337f5e | 651,618 |
import torch.__config__
from torch.utils.collect_env import get_pretty_env_info
def collect_torch_env():
"""
If torch is available, print the torch config.
"""
try:
return torch.__config__.show()
except ImportError:
# compatible with older versions of pytorch
return get_p... | bfc74c433c49b58cef0b3c335cc65b341ca5f775 | 651,619 |
def strtobool(value):
"""
This method convert string to bool.
Return False for values of the keywords "false" "f" "no" "n" "off" "0" or 0.
Or, return True for values of the keywords "true" "t" "yes" "y" "on" "1" or 1.
Or, othres return None.
Args:
value : string value
Return:
Return False for va... | a56d1317aa7b5767875841499c88f498f5dd7989 | 651,620 |
def no_of_replicates_per_cpd(df, df_lvl4):
"""This function computes the numbers of replicates for each compound"""
dose_list = list(set(df_lvl4['Metadata_dose_recode'].unique().tolist()))[1:7]
cpds_no_of_reps = {}
for cpd in df.index:
num_of_reps = 0
df_cpd = df_lvl4[df_lvl4['pert_... | ba6ba79e8315ba2d4dbd06ace443d4b57f5d6d27 | 651,621 |
import numpy
def ts_zeros(sz, d=1):
"""Returns a time series made of zero values.
Parameters
----------
sz : int
Time series size.
d : int (optional, default: 1)
Time series dimensionality.
Returns
-------
numpy.ndarray
A time series made of zeros.
Exampl... | ed733b3b34a13ff4f7e13560c270da16fee57ee6 | 651,622 |
import os
import subprocess
def in_repository(path, ignore=True):
"""Return True if path is inside a repository, False if not.
If <in_ignore> is set to False, will also return False if the path is inside a repository but
is ignored by a .gitignore.
"""
cwd = os.getcwd()
try:
... | eed974d98714db73fb51001c8c3afae496676fe7 | 651,624 |
from datetime import datetime
def extract_date_place(date_born_place):
""" extract date born and place born """
start_date = date_born_place.find(": ") + 2
end_date = start_date + 10
date_born_scraped = date_born_place[start_date:end_date]
date_born = datetime.strptime(date_born_scraped, "%d/%m/%Y... | 852ebbd7a8fab152346377c21aa8d316d8783f6f | 651,625 |
import re
import os
def build_submission_list(dir,SUBMISSIION_PATTERN):
"""SCan the directory dir and find all submission description files."""
pattern=re.compile(SUBMISSIION_PATTERN)
files=list()
for f in sorted(os.listdir(dir)):
if pattern.match(f) is not None:
print("{} Matched ... | 59ccf4413a5293d3009437c88320d3533068684d | 651,626 |
def _fetch_ignorable_policy_topics(client, googleads_exception):
"""Collects all ignorable policy topics to be sent for exemption request.
Args:
client: The GoogleAds client instance.
googleads_exception: The exception that contains the policy
violation(s).
Returns:
A l... | 4bfb539e468af02d81e0cfc2bac8aead42d67ccf | 651,627 |
def toStringVer(version):
"""Converts a semantic version string to a string with leading zeros"""
split = version.split(".")
fullversion = ""
for i, v in enumerate(split, start=0):
fullversion += v.rjust(2, "0")
return fullversion | 5e5b4b395cc0d9539f066c0ec68fb257572576af | 651,628 |
def ranges_overlap(x1, x2, y1, y2):
"""Returns true if the ranges `[x1, x2]` and `[y1, y2]` overlap,
where `x1 <= x2` and `y1 <= y2`.
Raises:
AssertionError : If `x1 > x2` or `y1 > y2`.
"""
assert x1 <= x2
assert y1 <= y2
return x1 <= y2 and y1 <= x2 | b83699379e9036f5e7981bf2c541cf3931a54638 | 651,629 |
def and_between_sentence(sentence):
"""
separate sentences if between them there is 'and'
Input=sentence Output=sentence
"""
# init
i = 0
while i < len(sentence):
j = 0
while j < len(sentence[i]):
if sentence[i][j] == 'and' and sentenc... | a97ed987924a1e63153050a1d79a31ad6e03833d | 651,630 |
from sys import stdin
def ReadAllLines():
"""Read all non-empty lines from stdin.
Returns:
A list of strings.
"""
lines = []
for line in stdin:
if len(line.strip()) == 0:
break
lines.append(line.strip())
return lines | 3ade97a40038b7a21affdd93caaf99a4cbf70031 | 651,631 |
def cursors_of_view(view):
"""Locates points of all cursors of the view.
Args:
view - an instance of sublime.View where to look for cursors
Returns:
[point] - a list of cursor points, sorted
"""
return [region.begin() for region in view.sel() if region.empty()] | 8c0c1f8e271bb3f3f251df797db5695184364234 | 651,633 |
def compute_offset(name):
"""Return byte array with offsets of component separators
Parameters
----------
name : str
The content name
Returns
-------
offsets : str
String of offsets
"""
offsets = [i for i, ch in enumerate(name) if ch == '/']
return "".join(chr(i... | 7afe25976e1f3146d5d56a950436873bf94c488d | 651,635 |
import re
def initialize_record(fields, shape_record):
"""Initializes a dictionary that stores a shapefile record.
Args:
fields: List that stores the shapefile record names
shape_record: Object that contains a shapefile record
and associated shape
Returns:
... | 4343c4622069afdac34a3939e90bb089d322cf00 | 651,636 |
def get_default_feepoints(sim, numpoints=20):
"""Returns a list of sensible default feepoints.
This is basically equispaced feerates from stablefeerate to 0.05
utilization.
"""
minfeepoint = sim.stablefeerate
maxfeepoint = sim.cap.inv_util(0.05)
assert maxfeepoint >= minfeepoint
spacing... | beb393cf5fc7402ee301cce8f4dc83e3dd0b2716 | 651,638 |
def pull_answers(surveys, all_questions):
""" Runs through questions and pull out answers, append them to the lists in the container
constructed by compile_question_data. """
for survey in surveys:
for question in survey:
question_id = question['question id']
answer = questio... | ea458fb27b01a0fae57c53374dbbe40a6d656e7b | 651,639 |
from pathlib import Path
def collect_filepaths(main_path, format="png"):
"""
Collect a set of files using a determined location on disk and a known list
of file formats. This is useful to get the full path of files encountered
on a disk folder.
Parameters
----------
main_path : str
... | 171cffe20611924acf3c6879433550a97f10622e | 651,640 |
import sys
import os
def get_editable_dallinger_path():
"""In case dallinger was installed as editable package
(for instance with `pip install -e`) it returns its location.
Otherwise returns None.
"""
for path_item in sys.path:
egg_link = os.path.join(path_item, "dallinger.egg-link")
... | 63b14d155903f52d58b4996801c3a29a0e7e526c | 651,642 |
import re
def natural_sort(values, case_sensitive=False):
"""
Returns a human readable list with integers accounted for in the sort.
items = ['xyz.1001.exr', 'xyz.1000.exr', 'abc11.txt', 'xyz.0999.exr', 'abc10.txt', 'abc9.txt']
natural_sort(items) = ['abc9.txt', 'abc10.txt', 'abc11.txt', 'xyz.0999.exr... | 9ed1ef665912e0b820f9cb001909bd95fd23ee26 | 651,643 |
def python_name(cmd_name):
"""Convert ``-`` to ``_`` in command name, to make a valid identifier."""
return cmd_name.replace("-", "_") | f79dfec66310b19d667f0799a0fc3eedbe771152 | 651,644 |
def _preprocess_segmentation_dict(segmentation_dict):
"""help to preprocess the indexs to list."""
final_dict = {}
for k in segmentation_dict:
final_dict[k] = [[]]
final_part_indexs = final_dict[k]
part_indexs = segmentation_dict[k]
part_indexs.sort()
for index in ran... | d8cf1bc146fa1288f344972c7e93c162533d9af1 | 651,645 |
def name(name):
"""Give a command a alternate name."""
def _decorator(func):
func.__dict__['_cmd_name'] = name
return func
return _decorator | f03f80f1022b87380ba2a15b2ff783885b722556 | 651,646 |
def get_words(filename):
"""Сегментация текста на слова"""
with open(filename, encoding="utf8") as file:
text = file.read()
text = text.replace("\n", " ")
text = text.replace(",", "").replace(".", "").replace("?", "".replace("!", ""))
text = text.lower()
words = text.split()
words.so... | e97284f23484fa9f36b6cb48124498647f719155 | 651,647 |
def do_stuff3():
"""This is not right."""
first, second = range(100)
return first + second | cce6e4ba8b56f1f42f70275c9d4b739e49b9aa70 | 651,648 |
import inspect
def params(func):
"""Shorthand to get the parameter spec for a function."""
return list(inspect.signature(func).parameters.values()) | f1666b0d5cc27fb9d0612bb84b0f18e449a6a836 | 651,650 |
import random
def random_class_ids(lower, upper):
"""
Get two random integers that are not equal.
Note: In some cases (such as there being only one sample of a class) there may be an endless loop here. This
will only happen on fairly exotic datasets though. May have to address in future.
:param lo... | dcb351efbf772f2408213b362b9a5af4bfabc8cb | 651,651 |
import torch
def blur_with_zeros(image, blur):
"""Blur an image ignoring zeros.
"""
# Create binary weight image with 1s where valid data exists.
mask = torch.ones(image.shape, device=image.device)
mask[image <= 0] = 0
# Compute blurred image that ignores zeros using ratio of blurred images.
... | d747f5bf8c8b53f37d735963990b935a02604535 | 651,652 |
import re
def cleanhtml(raw_html):
"""
This function is for creating filenames from the HTML returned from the API call.
It takes in a string containing HTML tags as an argument, and returns a string without HTML tags or any
characters that can't be used in a filename.
"""
# Created a regular... | 51a0bd1ce37e3bc59d0b457b398acbcd518b2fdd | 651,653 |
from typing import List
from typing import Optional
import os
import functools
def concatenate_files(fname_l: List[str],
out_fname: Optional[str] = None,
chunk_size: int = 128 * 1024) -> str:
"""Concatenate multiple files into a single file. This is used to recover a la... | 8a0fb940217c1f3705cefbf4d6d8b40508f3e452 | 651,654 |
def endfSENDLineNumber( ) :
"""Indicates the end of an ENDF data section for one (MF, MT) pair."""
return( 99999 ) | bd910343d6800bbb608774cdf6a62585d32dc54f | 651,655 |
def partition_at_level(dendrogram, level) :
"""Return the partition of the nodes at the given level
A dendrogram is a tree and each level is a partition of the graph nodes.
Level 0 is the first partition, which contains the smallest communities, and the best is len(dendrogram) - 1.
The higher the level... | fd8e12fd60e2f8c399a87aaf62d24864e5380f9c | 651,656 |
def _extract_data(spark, input_fname, app_config):
"""
Read the input data in the form of csv file.
:param spark : Active spark session
:param input_fname : Input filename as in the storage directory
:param app_config : loaded json object with app configuration
:returns : spark dataframe of inp... | 1103bdcad1fa9d8b5b018882cc43b9c5917b3937 | 651,657 |
def venv(virtualenv):
"""Create a virtualenv for each test"""
return virtualenv | 123fe15e38bca6954f51949213e18d9a9c4a0819 | 651,658 |
def adjust_fg_positions(fg_id, positions):
"""
Adjusts a prospect's position given their fangraphs player_id (fg_id).
Not heavily necessary unless a player has been mis-classified as a pitcher when they should be a hitter or vice versa.
"""
positions_dict = {
}
if fg_id in positions_dict:
... | 60ca9571106b4664658671ae4a5c055c83af7182 | 651,660 |
def admin_persona(personas, posted_personas):
"""
This fixture is intended to be an arbitrary choice among persona users that IS a group administrator.
"""
for key, persona in personas.items():
groups = persona.get("groups", [])
if "admin" in groups:
return posted_personas[ke... | 1d597b00bc7e0d96a09f1b9f63bffff9c8b0e6b9 | 651,661 |
def inc_key(text):
""" increment the last letter of text by one. Used to replace key in SQL LIKE case with less than """
return text[0:-1] + chr(ord(text[-1]) + 1) | e8753ef1cd5018a73427ec3cca7778a9034939bf | 651,662 |
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