content stringlengths 39 14.9k | sha1 stringlengths 40 40 | id int64 0 710k |
|---|---|---|
def hash_key(key: int, size: int) -> int:
"""
Return an integer for the given key to be used as an index to a table of
the given size.
>>> hash_key(10, 7)
3
"""
return key % size | 212d1c74aa7882695fbe3cd15ca62301386344b6 | 672,117 |
def isWord(s):
"""
See if a passed-in value is an identifier. If the value passed in is not a
string, False is returned. An identifier consists of alphanumerics or
underscore characters.
Examples::
isWord('a word') ->False
isWord('award') -> True
isWord(9) -> False
... | 84df75643db356fb583e4bbc20fc887779dfdb74 | 672,119 |
def is_better_sol(best_f, best_K, sol_f, sol_K, minimize_K):
"""Compares a solution against the current best and returns True if the
solution is actually better accordint to minimize_K, which sets the primary
optimization target (True=number of vehicles, False=total cost)."""
if sol_f is None or so... | 15ab7dd0294226870e476731066130253ae2986a | 672,121 |
def lineAtPos ( s, pos ):
"""
lineAtPos: return the line of a string containing the given index.
s a string
pos an index into s
"""
# find the start of the line containing the match
if len(s) < 1:
return ""
if pos > len(s):
pos = len(s)-1
while pos > 0:
if s[pos] == '\n':
pos = pos + 1
break
... | f78b52947573ebc4cb6dfb8b88bd75a4bac7fb62 | 672,123 |
import inspect
def wants_args(f):
"""Check if the function wants any arguments
"""
argspec = inspect.getfullargspec(f)
return bool(argspec.args or argspec.varargs or argspec.varkw) | bf34e92240e5580edd32cfec7f21e10b53851371 | 672,129 |
from typing import Tuple
def split_templated_class_name(class_name: str) -> Tuple:
"""
Example:
"OctreePointCloud<PointT, LeafContainerT, BranchContainerT>::Ptr"
("OctreePointCloud", (PointT, LeafContainerT, BranchContainerT), "::Ptr")
"""
template_types = tuple()
pos = class_name.... | a2f0ee818a1985ee943cc975928be4e18470882b | 672,130 |
def validate_type(data_dict: dict, type_name: str) -> dict:
"""Ensure that dict has field 'type' with given value."""
data_dict_copy = data_dict.copy()
if 'type' in data_dict_copy:
if data_dict_copy['type'] != type_name:
raise Exception(
"Object type must be {}, but was i... | cbb492d3ed27beba5e24f78c5f526585d7b47585 | 672,134 |
from typing import List
from typing import Any
def all_same(list: List[Any]) -> bool:
"""Decide whether or not a list's values are all the same"""
return len(set(list)) == 1 | 1a3f22c2b2d1a5b114712bcf39e9ef50a3e10555 | 672,138 |
import torch
def linear_2_oklab(x):
"""Converts pytorch tensor 'x' from Linear to OkLAB colorspace, described here:
https://bottosson.github.io/posts/oklab/
Inputs:
x -- pytorch tensor of size B x 3 x H x W, assumed to be in linear
srgb colorspace, scaled between 0. and 1.
Re... | f732e2b268c8bd1ffae92197b100cfd265033baa | 672,140 |
def point_in_polygon(S, q):
"""determine if a point is within a polygon
The code below is from Wm. Randolph Franklin <wrf@ecse.rpi.edu>
(see URL below) with some minor modifications for integer. It returns
true for strictly interior points, false for strictly exterior, and ub
for points on the boun... | 81f73ded677991552927914ef478b0ce308c2d35 | 672,141 |
def query(question, default_answer="", help=""):
"""Ask user a question
:param question: question text to user
:param default_answer: any default answering text string
:param help: help text string
:return: stripped answer string
"""
prompt_txt = "{question} [{default_answer}] ".format(que... | ecfc894091cc3a77d07712ee3d74fcc46ae8a9df | 672,145 |
def path_to_major_minor(node_block_devices, ndt, device_path):
""" Return device major minor for a given device path """
return node_block_devices.get(ndt.normalized_device_path(device_path)) | a229ad002912678cfe7f54c484218069f2fbc6ae | 672,146 |
def except_text(value):
"""
Creates messages that will appear if the task number is entered incorrectly
:param value: 'список', 'задача', 'цифра'. Depends on what messages are needed
:return: 2 messages that will appear if the task number is entered incorrectly
"""
if value == 'список':
... | 8394ca2f2cb5b513069877d29d070adf79709ac3 | 672,147 |
def RemoveAllJetPtCuts(proc):
"""
Remove default pt cuts for all jets set in jets_cff.py
"""
proc.finalJets.cut = "" # 15 -> 10
proc.finalJetsAK8.cut = "" # 170 -> 170
proc.genJetTable.cut = "" # 10 -> 8
proc.genJetFlavourTable.cut = "" # 10 -> 8
proc.genJetAK8Table.c... | 1f73ccfc1d81c6af449fe45990bc9097dbc91252 | 672,157 |
import importlib
def validate_external_function(possible_function):
"""
Validate string representing external function is a callable
Args:
possible_function: string "pointing" to external function
Returns:
None/Callable: None or callable function
Raises:
N/A # noqa
... | 47b1584fbca601a67ff495b45d8f634a3bd412cd | 672,158 |
from pathlib import Path
def get_mirror_path(path_from: Path, path_to: Path) -> Path:
"""Return the mirror path from a path to another one.
The mirrored path is determined from the current working directory (cwd)
and the path_from. The path_from shall be under the cwd. The mirrored
relative path is t... | e617e58c426f91499ba6ec85e842513b19b98ce2 | 672,161 |
def htk_int_to_float(value):
""" Converts an integer value (time in 100ns units) to floating
point value (time in seconds)...
"""
return float(value) / 10000000.0 | 54546e9d980ad0bcc488d086daa50a8bfb51821d | 672,170 |
def parse_name(name):
""" Parse name of the form 'namespace_name.unit_name' into tuple ('namespace_name', 'unit_name'). """
if '.' not in name:
raise ValueError('`func` parameter must be provided or name must be "namespace_name.unit_name"')
name_components = name.split('.')
if len(name_component... | 97a81e27e9b9c5eaea1a13b1c9a28cddf549c7f6 | 672,172 |
def loglinear_rule_weight(feature_dict, feature_weights_dict):
"""
Compute log linear feature weight of a rule by summing the products of feature values and feature weights.
:param feature_dict: Dictionary of features and their values
:param feature_weights_dict: Dictionary of features and their weights... | 5db1edec2a3218144972434f6a7512484a3b71cc | 672,173 |
def folder_from_egtb_name(name: str) -> str:
"""
Determine EGTB folder (Xvy_pawn(less|ful)) from EGTB name
:param name: EGTB name
"""
l, r = name.split('v')
prefix = f'{len(l)}v{len(r)}'
suffix = '_pawnful' if ('P' in l or 'P' in r) else '_pawnless'
return prefix + suffix | 4c4838bcbaa20ac422102526162d44bf1422fcf2 | 672,178 |
import torch
def householder_matrix(v, size=None):
"""
householder_matrix(Tensor, size=None) -> Tensor
Arguments
v: Tensor of size [Any,]
size: `int` or `None`. The size of the resulting matrix.
size >= v.size(0)
Output
I - 2 v^T * v / v*v^T: Tensor of size [size, ... | 8b00a552bed7f22b671a4e4fa0a6b6df67b3aadc | 672,185 |
def count_first_word(str_list):
"""Count the first word of each string in the list.
Args:
str_list: List of strings
Returns:
{"word": count, ...}
"""
ret_count = dict()
for phrase in str_list:
words = phrase.split("-")
ret_count[words[0]] = ret_count.get(words[... | 3350441d38daec4bb9f659d780886efd4af7dd4f | 672,188 |
def quantify(iterable, pred=bool):
"""Count the number of items in iterable for which pred is true."""
return sum(1 for item in iterable if pred(item)) | f43fbd0459db90615bd019e3afd9417abf7d8e88 | 672,195 |
def windows_low_high_to_int(windows_int_low, windows_int_high):
"""Returns an int given the low and high integers"""
return (windows_int_high << 32) + windows_int_low | ead6e4d19022f49e9bde7600f13399d3e236d10a | 672,197 |
import time
def filename_stamped(filename, number):
"""Create a time-stamped filename"""
time_str = time.strftime("%Y%m%d-%H%M%S")
return '{}_{}_{}'.format(filename, number, time_str) | cf97aad13edbc1657f328725f2351d2ca1481ce6 | 672,198 |
def say_hello() -> str:
"""Say hello function."""
return "Hello" | 42c2de62056246c01f4e0072e073d1fa944c406c | 672,199 |
def parse_hash_id(seq):
"""Return a list of protein numbers within the given string.
Example
-------
"#10,41,43,150#" -> ["10", "41", "43", "150"]
"""
ans = seq.strip("#").split(",")
return ans | 26e196be40c741dca9c09c79ec6e4352c48952e9 | 672,200 |
def shorten_dfs(dfs, plot_start=None, plot_end=None):
"""Shorten all incidence DataFrames.
All DataFrames are shortened to the shortest. In addition, if plot_start is given
all DataFrames start at or after plot_start.
Args:
dfs (dict): keys are the names of the scenarios, values are the incide... | a059d0a27ec521d816679aeba1e5bf355cb5dc16 | 672,201 |
def nt2over_gn_groupings(nt):
"""Return the number of grouping ``over'' a note.
For beamings trees this is the number of beams over each note.
Args:
nt (NotationTree): A notation tree, either beaming tree or tuplet tree.
Returns:
list: A list of length [number_of_leaves], with integer... | 7f2c2a281a55d8dd3b837b7510be4dcc93f74779 | 672,202 |
def center_crop(data, shape):
"""
Apply a center crop to the input real image or batch of real images.
Args:
data (torch.Tensor): The input tensor to be center cropped. It should
have at least 2 dimensions and the cropping is applied along the
last two dimensions.
sh... | c1f220e555333d38a83271d5e9254c4b1178d3c1 | 672,205 |
def fetch_method(obj, method):
"""
fetch object attributes by name
Args:
obj: class object
method: name of the method
Returns:
function
"""
try:
return getattr(obj, method)
except AttributeError:
raise NotImplementedError(f"{obj.__class__} has not impl... | 49f823c4f8fd2296f6fd17dcfd5fc72b8835b42a | 672,208 |
def extend_dict(dict_1: dict, dict_2: dict) -> dict:
"""Assumes that dic_1 and dic_2 are both dictionaries. Returns the merged/combined dictionary of the two
dictionaries."""
return {**dict_1, **dict_2} | 88e2f1c613181046b388092677b8ee627c432d4d | 672,211 |
import requests
def download_zip(url:str, dest_path:str, chunk_size:int = 128)->bool:
"""Download zip file
Downloads zip from the specified URL and saves it to the specified file path.
see https://stackoverflow.com/questions/9419162/download-returned-zip-file-from-url
Args:
url (str): sl... | a4f6024695976f422bc6dc3979c8438cfff9c70e | 672,212 |
def trash_file(drive_service, file_id):
"""
Move file to bin on google drive
"""
body = {"trashed": True}
try:
updated_file = drive_service.files().update(fileId=file_id, body=body).execute()
print(f"Moved old backup file to bin.")
return updated_file
except Exception:
... | f9a2a331a74cdb4050dc6bb788fc398d7db90ec1 | 672,214 |
import inspect
def extract_kwargs(docstring):
"""Extract keyword argument documentation from a function's docstring.
Parameters
----------
docstring: str
The docstring to extract keyword arguments from.
Returns
-------
list of (str, str, list str)
str
The name of the... | 3ec2442fbe3ec3984d6c5462f1c0006c4b723f2f | 672,215 |
def get_total_interconnector_violation(model):
"""Total interconnector violation"""
# Total forward and reverse interconnector violation
forward = sum(v.value for v in model.V_CV_INTERCONNECTOR_FORWARD.values())
reverse = sum(v.value for v in model.V_CV_INTERCONNECTOR_REVERSE.values())
return forw... | cbe6c1e3e1424623064e9d906d143e1ae728a141 | 672,216 |
import hashlib
def Many_Hash(filename):
""" calculate hashes for given filename """
with open(filename, "rb") as f:
data = f.read()
md5 = hashlib.md5(data).hexdigest()
sha1 = hashlib.sha1(data).hexdigest()
sha256 = hashlib.sha256(data).hexdigest()
sha512 = hashlib.sha512(data).hexdiges... | 7805ab4e72726026a4fb21f754964d02fba857a0 | 672,218 |
def grad_likelihood(*X, Y=0, W=1):
"""Gradient of the log-likelihood of NMF assuming Gaussian error model.
Args:
X: tuple of (A,S) matrix factors
Y: target matrix
W: (optional weight matrix MxN)
Returns:
grad_A f, grad_S f
"""
A, S = X
D = W * (A.dot(S) - Y)
... | 4a52389764b9d52cc5dd4dae9f72fbdd46dba174 | 672,219 |
from typing import Sequence
from typing import List
def chain(items: Sequence, cycle: bool = False) -> List:
"""Creates a chain between items
Parameters
----------
items : Sequence
items to join to chain
cycle : bool, optional
cycle to the start of the chain if True, default: Fals... | d47e834b152c061011ec6278220777a5c3d04146 | 672,220 |
def _ensure_list_of_lists(entries):
"""Transform input to being a list of lists."""
if not isinstance(entries, list):
# user passed in single object
# wrap in a list
# (next transformation will make this a list of lists)
entries = [entries]
if not any(isinstance(element, list... | a1866fdd62861f40e7f5aa9ce491ba14fc5a6cc9 | 672,222 |
def get_daily_returns(df):
"""Compute and return the daily return values."""
daily_returns = df.copy()
daily_returns[1:] = (df[1:] / df[:-1].values) - 1
daily_returns.iloc[0] = 0 # set daily returns for row 0 to 0
return daily_returns | 8b72e3bb446f77d0ccdd63d664da4f9a48f45cf0 | 672,225 |
def bitarray2dec(in_bitarray):
"""
Converts an input NumPy array of bits (0 and 1) to a decimal integer.
Parameters
----------
in_bitarray : 1D ndarray of ints
Input NumPy array of bits.
Returns
-------
number : int
Integer representation of input bit array.
"""
... | ae4cbb907c13d92a5dde734e7bb9d11ab4aa6225 | 672,226 |
def set_state_dict(model, state_dict):
"""Load state dictionary whether or not distributed training was used"""
if hasattr(model, "module"):
return model.module.load_state_dict(state_dict)
return model.load_state_dict(state_dict) | fab8c5e73d0efa3df480e692697c865977066804 | 672,229 |
import re
def _parse_line(cpuid, match):
"""Search a line with the content <match>: <value> in the given
StringIO instance and return <value>
"""
cpuid.seek(0)
for l in cpuid.readlines():
m = re.match('^(%s.*):\s+(.+)' % match, l)
if m:
return (m.group(1), m.group(2).r... | d83fcc1e79b13e5ed11e79e3dad47eb99d0e2371 | 672,230 |
def other_options(options):
"""
Replaces None with an empty dict for plotting options.
"""
return dict() if options is None else options.copy() | b2f22bc681ed633445a7a984e3c9f3da9dc975ab | 672,231 |
from typing import Any
def make_safe(element: Any) -> str:
"""
Helper function to make an element a string
Parameters
----------
element: Any
Element to recursively turn into a string
Returns
-------
str
All elements combined into a string
"""
if isinstance(el... | ea104f847323c8b56ec20df57f28c98fce784cd7 | 672,235 |
import re
def demo_id(filename):
"""Get the demo_number from a test macro"""
b1 = re.match('.*/test_demo\d{2}\.py', filename)
found = re.findall('.*/test_demo(\d{2})\.py', filename)
b2 = len(found) == 1
is_test_file = b1 and b2
assert is_test_file, 'Not a test file: "%s"' % filename
return... | 9402586f92ea9d95eee10c9047efc6b43c25abac | 672,236 |
def read_classification_from_file(filename):
""" Return { <filename> : <classification> } dict """
with open(filename, "rt") as f:
classification = {}
for line in f:
key, value = line.split()
classification[key] = value
return classification | 8e3d30e55efd289fa98d0d28acf0d8d857ace835 | 672,239 |
def truncate(message, limit=500):
"""
Truncates the message to the given limit length. The beginning and the
end of the message are left untouched.
"""
if len(message) > limit:
trc_msg = ''.join([message[:limit // 2 - 2],
' .. ',
message[... | 93d117c475e4a198b60a387f6911c9cbbc246e64 | 672,241 |
def findDataStart(lines, delin = ' '):
"""
Finds the line where the data starts
input:
lines = list of strings (probably from a data file)
delin = optional string, tells how the data would be separated, default is a space (' ')
output:
i = integer where the data stops being... | b9e2aa79d9eae1616412491763cfdde3e6e37672 | 672,247 |
def pa_bbm_hash_mock(url, request):
"""
Mock for Android autoloader lookup, new site.
"""
thebody = "http://54.247.87.13/softwareupgrade/BBM/bbry_qc8953_autoloader_user-common-AAL093.sha512sum"
return {'status_code': 200, 'content': thebody} | 4d1909fef728aa2adec2b418796747a7b789add1 | 672,250 |
import itertools
import random
def generate_comparison_pairs(condition_datas):
"""
Generate all stimulus comparison pairs for a condition and return in a random order for a paired comparison test.
Parameters
----------
condition_datas: list of dict
List of dictionary of condition data as ... | f850da7cfd9edbecf22bdabe7dff1e1a325cc1fb | 672,255 |
def alltrue(seq):
"""
Return *True* if all elements of *seq* evaluate to *True*. If
*seq* is empty, return *False*.
"""
if not len(seq):
return False
for val in seq:
if not val:
return False
return True | ecfc0a2a88d4bac16144e676e9c141624ec15c9e | 672,256 |
def test(classifier, data, labels):
"""
Test a classifier.
Parameters
----------
classifier : sklearn classifier
The classifier to test.
data : numpy array
The data with which to test the
classifier.
labels : numpy array
The labels with which to test the
the classifier.
Returns
... | ab26442225b9a97fea27ad7d86cd2c4251dd4a3f | 672,258 |
def reverse_complement(s):
"""Return reverse complement sequence"""
ret = ''
complement = {"A": "T", "T": "A", "C": "G", "G": "C", "N": "N", "a": "t", "t": "a", "c": "g", "g": "c", "n": "n"}
for base in s[::-1]:
ret += complement[base]
return ret | dff5b4597596be93973c143a0e3fc110d23f132f | 672,262 |
def hex_to_rgb(col_hex):
"""Convert a hex colour to an RGB tuple."""
col_hex = col_hex.lstrip('#')
return bytearray.fromhex(col_hex) | 2a38fe4fbd9231231a0ddcc595d27d71b0718ba3 | 672,267 |
def page_query_with_skip(query, skip=0, limit=100, max_count=None, lazy_count=False):
"""Query data with skip, limit and count by `QuerySet`
Args:
query(mongoengine.queryset.QuerySet): A valid `QuerySet` object.
skip(int): Skip N items.
limit(int): Maximum number of items returned.
... | 2aef61019b67f2d9262ad8f671a9991e0915ddcf | 672,272 |
def nvt_cv(e1, e2, kt, volume = 1.0):
"""Compute (specific) heat capacity in NVT ensemble.
C_V = 1/kT^2 . ( <E^2> - <E>^2 )
"""
cv = (1.0/(volume*kt**2))*(e2 - e1*e1)
return cv | 12d8cee877ef2a6eee1807df705ba5f193c84f52 | 672,274 |
def rectangle_to_cv_bbox(rectangle_points):
"""
Convert the CVAT rectangle points (serverside) to a OpenCV rectangle.
:param tuple rectangle_points: Tuple of form (x1,y1,x2,y2)
:return: Form (x1, y1, width, height)
"""
# Dimensions must be ints, otherwise tracking throws a exception
return (int(rectangle_points[... | 47548d4098d057625ebfd846164946481222559d | 672,275 |
def dijkstra(g, source):
"""Return distance where distance[v] is min distance from source to v.
This will return a dictionary distance.
g is a Graph object.
source is a Vertex object in g.
"""
unvisited = set(g)
distance = dict.fromkeys(g, float('inf'))
distance[source] = 0
whi... | aa28bb28c581fc6f3651f1a7ae704b56ac3f1525 | 672,276 |
def calc_gross_profit_margin(revenue_time_series, cogs_time_series): # Profit and Cost of Goods Sold - i.e. cost of materials and director labour costs
"""
Gross Profit Margins Formula
Notes
------------
Profit Margins = Total revenue - Cost of goods sold (COGS) / revenue
... | d7fe1352278423b048cc456adba3580647cff0f4 | 672,277 |
import asyncio
def event_loop() -> asyncio.AbstractEventLoop:
"""Returns an event loop for the current thread"""
return asyncio.get_event_loop_policy().get_event_loop() | 19d1e4544eba04b2b8d99c7efa3427021d2d95e8 | 672,283 |
def set_discover_targets(discover: bool) -> dict:
"""Controls whether to discover available targets and notify via
`targetCreated/targetInfoChanged/targetDestroyed` events.
Parameters
----------
discover: bool
Whether to discover available targets.
"""
return {"method": "Target.... | 31de0937b68af4b6492f4c49d67d5f4c481a5c6b | 672,284 |
def notas(*nt, sit=False):
"""
-> Função para analisar notas e situação de vários alunos.
:param nt: recebe uma ou mais notas dos alunos.
:param sit: valor opcional, mostrando ou não a situação do aluno(True/False).
:return: dicionário com várias informações sobre a situação da turma.
"""
pr... | 4854c5941f57e5775a504fd9ad24b96886dd2bfd | 672,286 |
def _get_binary(value, bits):
"""
Provides the given value as a binary string, padded with zeros to the given
number of bits.
:param int value: value to be converted
:param int bits: number of bits to pad to
"""
# http://www.daniweb.com/code/snippet216539.html
return ''.join([str((value >> y) & 1) for... | 4b4312026cef9fbdca228b1db7205825c5353450 | 672,289 |
def count_null_values_for_each_column(spark_df):
"""Creates a dictionary of the number of nulls in each column
Args:
spark_df (pyspark.sql.dataframe.DataFrame): The spark dataframe for which the nulls need to be counted
Returns:
dict: A dictionary with column name as key and null count as ... | ff27c3bad5a0578bb51b0ef6d71659360ab5b11e | 672,293 |
def __version_compare(v1, v2):
"""
Compare two Commander version versions and will return:
1 if version 1 is bigger
0 if equal
-1 if version 2 is bigger
"""
# This will split both the versions by '.'
arr1 = v1.split(".")
arr2 = v2.split(".")
n = len(arr1)
m =... | fe1a563d26a5dabdae968c8502049fc1333acdd9 | 672,294 |
def create_vocab_item(vocab_class, row, row_key):
"""gets or create a vocab entry based on name and name_reverse"""
try:
name_reverse = row[row_key].split("|")[1]
name = row[row_key].split("|")[0]
except IndexError:
name_reverse = row[row_key]
name = row[row_key]
temp_ite... | 3f8fd941e02b857279f1a4961d35cfd36bf7cb5b | 672,297 |
import json
def _load_repo_configs(path):
"""
load repository configs from the specified json file
:param path:
:return: list of json objects
"""
with open(path) as f:
return json.loads(f.read()) | f96e2d78b2614d07b2b1b1edc71eb10a9c2709a3 | 672,301 |
def get_if_all_equal(data, default=None):
"""Get value of all are the same, else return default value.
Arguments:
data {TupleTree} -- TupleTree data.
Keyword Arguments:
default {any} -- Return if all are not equal (default: {None})
"""
if data.all_equal():
return da... | 30e7186ae835ba3ba9ac110c2f55b316346bdc1a | 672,302 |
def convert_compartment_id(modelseed_id, format_type):
""" Convert a compartment ID in ModelSEED source format to another format.
No conversion is done for unknown format types.
Parameters
----------
modelseed_id : str
Compartment ID in ModelSEED source format
format_type : {'modelseed... | 8856858637b2f655ac790e026e7fe88c6e83e364 | 672,304 |
import torch
def dirichlet_common_loss(alphas, y_one_hot, lam=0):
"""
Use Evidential Learning Dirichlet loss from Sensoy et al. This function follows
after the classification and multiclass specific functions that reshape the
alpha inputs and create one-hot targets.
:param alphas: Predicted para... | c6c5749e9a24b8d5d2d9df8a3567f0c1d967f84e | 672,306 |
def merge_dicts(base, updates):
"""
Given two dicts, merge them into a new dict as a shallow copy.
Parameters
----------
base: dict
The base dictionary.
updates: dict
Secondary dictionary whose values override the base.
"""
if not base:
base = dict()
if not u... | 8f5cfc3805cd94809648a64311239b6bdc04adea | 672,308 |
def get_hashes_from_file_manifest(file_manifest):
""" Return a string that is a concatenation of the file hashes provided in the bundle manifest entry for a file:
{sha1}{sha256}{s3_etag}{crc32c}
"""
sha1 = file_manifest.sha1
sha256 = file_manifest.sha256
s3_etag = file_manifest.s3_etag
c... | d86d979fb5266f5a5b3027ddc6cf03548d4bf3a1 | 672,309 |
def lowerColumn(r, c):
"""
>>> lowerColumn(5, 4)
[(5, 4), (6, 4), (7, 4), (8, 4)]
"""
x = range(r, 9)
y = [c, ] * (9-r)
return zip(x, y) | a51dcefed097f09315be21ec1aca958799f05d6b | 672,311 |
def summarize_filetypes(dir_map):
"""
Given a directory map dataframe, this returns a simple summary of the
filetypes contained therein and whether or not those are supported or not
----------
dir_map: pandas dictionary with columns path, extension, filetype, support;
this is the ouput o... | b825402d123b48354607e8fd76319b45bc586e32 | 672,312 |
def staticTunnelTemplate(user, device, ip, aaa_server, group_policy):
"""
Template for static IP tunnel configuration for a user.
This creates a unique address pool and tunnel group for a user.
:param user: username id associated with static IP
:type user: str
:param device:... | 0367205462157fe8b242095f19cf936a24b9afd8 | 672,315 |
from typing import Tuple
def _build_label_attribute_names(
should_include_handler: bool,
should_include_method: bool,
should_include_status: bool,
) -> Tuple[list, list]:
"""Builds up tuple with to be used label and attribute names.
Args:
should_include_handler (bool): Should the `handler... | 52b704767b69a8a75e1824489c39e3b59c994a17 | 672,320 |
def constructQuery(column_lst, case_id):
"""
Construct the query to public dataset: aketari-covid19-public.covid19.ISMIR
Args:
column_lst: list - ["*"] or ["column_name1", "column_name2" ...]
case_id: str - Optional e.g "case1"
Returns:
query object
"""
# Public dataset
... | e2107800565b10b3ee21ab15db04fadc8b167f42 | 672,321 |
def batch_unflatten(x, shape):
"""Revert `batch_flatten`."""
return x.reshape(*shape[:-1], -1) | 0cbde13e3621336a6571d7a047eafcf20124e1b6 | 672,323 |
def prepend_batch_seq_axis(tensor):
"""
CNTK uses 2 dynamic axes (batch, sequence, input_shape...).
To have a single sample with length 1 you need to pass (1, 1, input_shape...)
This method reshapes a tensor to add to the batch and sequence axis equal to 1.
:param tensor: The tensor to be reshaped
... | 2433b8ddf2ed9f5854b8c527e7e39b869939360d | 672,325 |
def dms2dd(d, m, s):
"""
Convert degrees minutes seconds to decimanl degrees
:param d: degrees
:param m: minutes
:param s: seconds
:return: decimal
"""
return d+((m+(s/60.0))/60.0) | e8285ada31a1b8316e1d9563992475a197fdb76a | 672,327 |
def transpose_dataframe(df): # pragma: no cover
"""
Check if the input is a column-wise Pandas `DataFrame`. If `True`, return a
transpose dataframe since stumpy assumes that each row represents data from a
different dimension while each column represents data from the same dimension.
If `False`, re... | 9ef8f30337467fe256042389e03c4e052feb6a12 | 672,328 |
def write_data(f, grp, name, data, type_string, options):
""" Writes a piece of data into an open HDF5 file.
Low level function to store a Python type (`data`) into the
specified Group.
.. versionchanged:: 0.2
Added return value `obj`.
Parameters
----------
f : h5py.File
Th... | 748dbc7d646ec33c31f9ef393ae998b76b317d41 | 672,330 |
def find_collection(client, dbid, id):
"""Find whether or not a CosmosDB collection exists.
Args:
client (obj): A pydocumentdb client object.
dbid (str): Database ID.
id (str): Collection ID.
Returns:
bool: True if the collection exists, False otherwise.
"""
... | 96f6bb66797b40daf137ed2d7920b6cd30697aa0 | 672,332 |
import json
def load_dicefile(file):
""" Load the dicewords file from disk. """
with open(file) as f:
dicewords_dict = json.load(f)
return dicewords_dict | 42da982410dfc1ac39a1f40766ba6f7a2824d088 | 672,333 |
def get_soup_search(x, search):
"""Searches to see if search is in the soup content and returns true if it is (false o/w)."""
if len(x.contents) == 0:
return False
return x.contents[0] == search | 402a9cf0523c0022d86f8c7eb7d502acb45a9291 | 672,334 |
def EVLACalModel(Source,
CalDataType=" ", CalFile=" ", CalName=" ", CalClass=" ", CalSeq=0, CalDisk=0, \
CalNfield=0, CalCCVer=1, CalBComp=[1], CalEComp=[0], CalCmethod=" ", CalCmode=" ", CalFlux=0.0, \
CalModelFlux=0.0, CalModelSI=0.0,CalModelPos=[0.,0.], CalModelPar... | 0aa7ef72d7a379868b2edba1ffea6aa2eee8f559 | 672,335 |
def split(children):
"""Returns the field that is used by the node to make a decision.
"""
field = set([child.predicate.field for child in children])
if len(field) == 1:
return field.pop() | 798ae7e7e82cb62b9b71f2e7453a7ceb77c07fae | 672,340 |
def reverse_str(input_str):
"""
Reverse a string
"""
return input_str[::-1] | df53f8e4ff65731865b3c9ef86fcb3a040c98677 | 672,346 |
def drop_suffix_from_str(item: str, suffix: str, divider: str = '') -> str:
"""Drops 'suffix' from 'item' with 'divider' in between.
Args:
item (str): item to be modified.
suffix (str): suffix to be added to 'item'.
Returns:
str: modified str.
"""
suffix = ''.join([suf... | 68ed4d44ef30243558b482964108bfe3a1f87552 | 672,349 |
def compute_reporting_interval(item_count):
"""
Computes for a given number of items that will be processed how often the
progress should be reported
"""
if item_count > 100000:
log_interval = item_count // 100
elif item_count > 30:
log_interval = item_count // 10
else:
... | e82a1210e235afe9da1cd368900b7ac688488353 | 672,366 |
def _preprocess_graphql_string(graphql_string):
"""Apply any necessary preprocessing to the input GraphQL string, returning the new version."""
# HACK(predrag): Workaround for graphql-core issue, to avoid needless errors:
# https://github.com/graphql-python/graphql-core/issues/98
return g... | df2ef81ef8fc5311686cbfcc644ce187dce8e02f | 672,367 |
def get_yn_input(prompt):
"""
Get Yes/No prompt answer.
:param prompt: string prompt
:return: bool
"""
answer = None
while answer not in ["y", "n", ""]:
answer = (input(prompt + " (y/N): ") or "").lower() or "n"
return answer == "y" | 8957f6a77716fb7ad85063dddf5921e108827ab5 | 672,373 |
def form_clean_components(rmsynth_pixel, faraday_peak, rmclean_gain):
"""Extract a complex-valued clean component.
Args:
rmsynth_pixel (numpy array): the dirty RM data for a specific pixel.
faraday_peak (int): the index of the peak of the clean component.
rmclean_gain (float): loop gain for cle... | 2bac5a50fff2e593e5aeab26a15f5dd814b61079 | 672,375 |
import re
import json
def fix_hunspell_json(badjson_path='en_us.json', goodjson_path='en_us_fixed.json'):
"""Fix the invalid hunspellToJSON.py json format by inserting double-quotes in list of affix strings
Args:
badjson_path (str): path to input json file that doesn't properly quote
goodjson_pat... | 1339c0f900f1c6162866983f2a575dc30b4820cd | 672,377 |
def get_axe_names(image, ext_info):
"""
Derive the name of all aXe products for a given image
"""
# make an empty dictionary
axe_names = {}
# get the root of the image name
pos = image.rfind('.fits')
root = image[:pos]
# FILL the dictionary with names of aXe products
#
# th... | 6c97970149d8eefa35eb3887fc3071f5160c6a53 | 672,382 |
from typing import List
def arrayToFloatList(x_array) -> List[float]:
"""Convert array to list of float.
Args:
x_array: array[Any] --
Returns:
List[float]
"""
return [float(x_item) for x_item in x_array] | 617377ae4bf5e55db2882451d91d6839df0bec3d | 672,391 |
def fetch_neighbours(matrix, y, x):
"""Find all neigbouring values and add them together"""
neighbours = []
try:
neighbours.append(matrix[y-1][x-1])
except IndexError:
neighbours.append(0)
try:
neighbours.append(matrix[y-1][x])
except IndexError:
neighb... | 7ec775f44b3f12d3693e77e73283fa9783cb5f58 | 672,394 |
def maybe_unsorted(start, end):
"""Tells if a range is big enough to potentially be unsorted."""
return end - start > 1 | 5b7de3e159418a3aa4b3bf0e524e41e11b6455e2 | 672,395 |
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