content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import os
def skip_check():
""" Check if an environment variable was used to skip this actor """
if os.getenv('LEAPP_SKIP_CHECK_OS_RELEASE'):
reporting.create_report([
reporting.Title('Skipped OS release check'),
reporting.Summary('Source RHEL release check skipped via LEAPP_SK... | a0e538d0e7013897f9324445d0cdbda1def5c234 | 41,300 |
def triagToNormal(triag, M):
"""Convert triangular matrix to a regular matrix"""
ar = np.arange(M)
mask = ar[:, None] <= ar[None, :]
x, y = np.nonzero(mask)
new = np.zeros((M, M), dtype=triag.dtype)
new[x, y] = triag
return new + new.T | fd1a4419983c4546ec1befd821200e0df9257cb1 | 41,301 |
def search_users_by_id(dataset_path: str, users: list):
"""
Searches the number of movies and genres that a given user or a group of users watched.
The number of movies watched are calculated by counting the number of movies that the user rated.
The number of genres watched are calculated by counting a... | a0eed8dc370e0849fdbb3bea239d42920ca31911 | 41,302 |
import os
def get_fsl_metrics(datadir, subject_list):
"""
Calculates both dice similarity coefficients between FNIRT masks and
ground truth lesionmasks as well as SSIM between FNIRT and FLIRT images.
Input: data directory, subjects to calculate DSC and SSIM
Output: list of DSCs and SSIM for each ... | 38cd389a1f0c2f87b22f121cce1a2818a2a48b74 | 41,303 |
from typing import Deque
from typing import List
from typing import Tuple
import concurrent
def execute_parallel_functions_in_threads(tasks_groups: Deque[List[ThreadedFunctionData]], max_workers, timeout=None)\
-> List[Tuple[Future, str, str]]:
"""
This function takes a Queue (tasks_groups: Deque[List... | b91a1768ac85aeeac955bc5abc6faaf817b89741 | 41,304 |
import requests
def _download(pep_number):
"""
Fetches PEP files as HTML from python.org.
"""
# PEP URLs look like https://www.python.org/dev/peps/pep-0123/
url = f'https://www.python.org/dev/peps/pep-{_format_pep_number(pep_number)}/'
response = requests.get(url)
if response.status_code ... | 46640e6522595b97c0629f894b0acf50c62ac2b6 | 41,305 |
def stretched_flow_para_function(
x, beta, relaxation_rate, alpha, flow_velocity, baseline=1
):
"""
flow_velocity: q.v (q vector dot v vector = q*v*cos(angle) )
"""
Diff_part = np.exp(-2 * (relaxation_rate * x) ** alpha)
Flow_part = (
np.pi ** 2
/ (16 * x * flow_velocity)
... | f02a23886721f24a72ddca8a042e06ec67a4a68b | 41,306 |
def svn_path_is_url(path):
"""svn_path_is_url(char const * path) -> svn_boolean_t"""
return _core.svn_path_is_url(path) | 94b6a0cfa4e438bce113fd266d57d3eb70c729a1 | 41,307 |
import os
def random_key_generator(key_length):
"""
Creates a random key with key_length written
in hexadecimal as string
Paramaters
----------
key_length : int
Key length in bits
Returns
-------
key : string
Key in hexadecimal as string
"""
return bytes... | 80c8e9e6949cfd1e5ead274c0b89bc0d40e1f926 | 41,308 |
def process_error(err):
"""Special handling for consent_required"""
body = err.body.decode('utf8')
if "consent_required" in body:
consent_scopes = ' '.join(DsConfig.permission_scopes())
consent_url = f"{DsConfig.auth_server()}/oauth/auth?response_type=code&scope={consent_scopes}&client_id={D... | 0cec9d39bd9726c0700a45fc194babcecb82d133 | 41,309 |
import logging
import io
import csv
def get_sheet(sheet_id, gid=None, use_cache=True):
"""Returns a list of rows from a sheet."""
query_dict = get_query_dict()
force_cache = RELOAD_ACL_QUERY_PARAM in query_dict
cache_key = 'google_sheet:{}:{}'.format(sheet_id, gid)
logging.info('Loading Google She... | 6130fafbe1f586ada863e74b08a424e7b07ff836 | 41,310 |
def _make_geometry_1_file(filename):
"""See n.comment for details."""
n = netCDF4.Dataset(filename, "w", format="NETCDF3_CLASSIC")
n.Conventions = "CF-" + VN
n.featureType = "timeSeries"
n.comment = (
"Make a netCDF file with 2 node coordinates variables, each of "
"which has a corr... | 430e978060b741a1460000ff66c7fa4bf67bca7c | 41,311 |
def conv_forward_im2col(x, w, b, conv_param):
"""
A fast implementation of the forward pass for a convolutional layer
based on im2col and col2im.
"""
N, C, H, W = x.shape
num_filters, _, filter_height, filter_width = w.shape
stride, pad = conv_param["stride"], conv_param["pad"]
# Check ... | 0b7ac991415fdbbbc6a31f92370c3561cefb9a0f | 41,312 |
def get_model(pretrained=True):
"""Function to obtain a pytorch resnet50 model with modified final layer
Args:
pretrained (bool): whether to use pretrained weights of the resnet50 model
Returns:
model (pytorch model): a pytorch model with resnet50 architecture with ... | 9809bd57a700dbf78847b9ec0dd09da8d2623353 | 41,313 |
import torch
from typing import Optional
from typing import Union
from typing import List
def dilation_dependent(input_tensor: torch.Tensor,
structuring_element: torch.Tensor,
origin: Optional[Union[tuple, List[int]]] = None,
border_value: Union[int... | 5e7af35cf37c41ffaf9afffe978c73521856e10b | 41,314 |
def audio_process(songname: str) -> pd.DataFrame:
"""
:rtype: DataFrame of all the features
"""
y, sr = librosa.load(songname, mono=True, duration=30)
rmse = librosa.feature.rms(y=y)
chroma_stft = librosa.feature.chroma_stft(y=y, sr=sr)
spec_cent = librosa.feature.spectral_centroid(y=y, s... | e1f517c588e42ac0381065d4fde5f331e528061d | 41,315 |
def estimate_fundamental_matrix(points_a, points_b):
"""
Calculates the fundamental matrix. Try to implement this function as
efficiently as possible. It will be called repeatedly in part 3.
You must normalize your coordinates through linear transformations as
described on the project webpage befor... | fc569386cd300b948adb876ef01d389d1cea5395 | 41,316 |
def qg8_chunk_get_type(chunk: qg8_chunk):
"""
Return the chunk type as an integer
"""
if not isinstance(chunk, qg8_chunk):
raise TypeError("Argument is not a qg8_chunk")
return chunk.type | 7dc2bbc77d152f4727dcf951a4ba897b0606d9ba | 41,317 |
def agg_func(data:pd.DataFrame, object_column:str, agg_list=['nunique', 'count'])->pd.DataFrame:
"""
Parameters
----------
data:pd.DataFrame :
object_column:str :
agg_list :
(Default value = ['nunique', 'count'] :
Returns
-------
A dataframe with... | 41448ed189311bd121aac9ef37bde4ef20c47c8c | 41,318 |
def get_audits():
"""Get OS hardening login.defs audits.
:returns: dictionary of audits
"""
audits = [TemplatedFile('/etc/login.defs', LoginContext(),
template_dir=TEMPLATES_DIR,
user='root', group='root', mode=0o0444)]
return audits | cbc12d52fde5d9ec92536799a46d3b0a9fd0d242 | 41,319 |
import os
def draw_component_loss_barchart_s3(ctype_resp_sorted,
scenario_tag,
hazard_type,
output_path,
fig_name):
""" Plots bar charts of direct economic losses for com... | 93c59cea545a7e4015b87dad2d538decb6ddb6bf | 41,320 |
def username_exists(username):
""" Checks if a username aldready exists
:param username: username to be checked
:return: Boolean indicating whether the username exists or not
:rtype: boolean
"""
return not User.query.filter_by(
username=username).first() is None | 717dc8cd2f5807c49c892ffd98e4e35f79886094 | 41,321 |
def buy_ticket(email,price,name,quantity):
"""
Update user balance
:param email: email of user
:param price: price of ticket
:param name: name of ticket
:param quantity: quantity to buy
"""
user=User.query.filter_by(email=email).first()
user.balance=int(float(user.balance)-float(pric... | bf8b5378243b9c3fd8caff7e52a71c985ca47c4f | 41,322 |
from operator import truth
def test_validators():
"""Tests of validatorfuncs.py that aren't covered elsewhere"""
# PercentageString
with raises(Invalid, match="Not a valid percentage string"):
validatorfuncs.PercentageString("mess%")
# ListOfType
testfunc = validatorfuncs.ListOfType(int)
... | 20707f0eae6491d4acd1b16c59380d5f90d54e01 | 41,323 |
import libpysal
import warnings
def rand_precision_mat(lat_row, lat_col, max_neighbors=8, rho=1):
"""Generate a random spatial precision matrix.
The spatial precision matrix is generated using a rectengular lattice
of dimensions `lat_row` x `lat_col`, and thus the row and colum size of
the matrix is ... | 8afffaee98a07a95ad6e5e0ad2f69cc9d51169ef | 41,324 |
from typing import List
def generate_df(cols_to_keep: List[str]) -> pd.DataFrame:
"""Generates the cleaned dataframe."""
df = pd.read_csv(CSV_URL)
for col in INTEGRAL_COLS:
df[col] = df[col].astype('Int64')
if col.endswith('_flag'):
assert get_unique_values(df[col]) == [0, 1, p... | f3c2ed950e09e2d6f52a90fd66035a6067a90a01 | 41,325 |
import logging
import requests
from bs4 import BeautifulSoup
def scrape_attackdex(
save_csv: bool = True,
file_path: str = 'data/attackdex.csv'
) -> pd.DataFrame:
"""Return dataframe of scraped attack data from serebii.net"""
gen_dict = {
1: '-rby',
2: '-gs',
3: '',
... | e634b4a0dd1d36811a408d09ee88b9c92e1b30cf | 41,326 |
def get_ppm_df():
"""Get a pandas dataframe containing all PPM data.
Returns:
pd.DataFrame: PPM Pandas dataframe
"""
if app.mongo is None:
return None
docs = app.mongo.get("PPM")
if docs is None:
return None
ppm_dict = {
"date": [],
"total": [],
... | 0f894522cd489b792c68d9935e4c998d08ad1b69 | 41,327 |
from datetime import datetime
def utc2local(utc_dtm):
"""
UTC 时间转本地时间（ +8:00 ）
:param utc_dtm:
:return:
"""
local_tm = datetime.fromtimestamp(0)
utc_tm = datetime.utcfromtimestamp(0)
offset = local_tm - utc_tm
return utc_dtm + offset | 0070c3ae1e37071cbf57806ca18576f81abb64e0 | 41,328 |
def make_serviceitem_servicedll(servicedll, condition='contains', negate=False, preserve_case=False):
"""
Create a node for ServiceItem/serviceDLL
:return: A IndicatorItem represented as an Element node
"""
document = 'ServiceItem'
search = 'ServiceItem/serviceDLL'
content_type = 'strin... | 96513dafa74e7a59b602a4087528794aa540f681 | 41,329 |
import math
def load_dataset_with_augmentation(source_dir, augmentation=None, min_count=None):
"""
Wczytanie sampli z opcjonalną augmentacją. Użyć parametru augmentation albo min_count, nie obu na raz.
:param source_dir: katalog źródłowy z plikami PNG.
:param augmentation: krotność augmentacji.
:... | 03e8487a7894a651954c2db635c337fe6e8c8c9d | 41,330 |
def get_mse(prices, predictions):
"""Get the mean squared error of a network by analysing actual price and the network's corresponding predictions.
:rtype: float64
:param prices: the prices that the predictions aim to mimic
:param predictions: the predictions
:return: the mean-squared error of the c... | ec1fbe8e053d29ea95c9ccb268e9590f1a640f45 | 41,331 |
import json
def find_k_neighbors():
"""Receiving input and returning closest neighbors"""
input_dict = json.loads(request.get_json())
# print(pd.json_normalize(input_dict).info())
result = KNN.kneighbors(
TRANSFORMER.transform(pd.json_normalize(input_dict)),
return_distance=False)
... | 4001322aa054c623a29fa61e60ada0e7182084d9 | 41,332 |
def get_databases(task=None):
"""Get list of databases
Parameters
----------
task : str, optional
Only returns databases providing protocols for this task.
Defaults to returning every database.
Returns
-------
databases : list
List of database, sorted in alphabetica... | a1ff0e6e6b4cf3282bcc61ff7e52538bd057c19c | 41,333 |
def dimensions(image: np.ndarray, kernel: np.ndarray, padding:int, strides:int) -> np.ndarray:
"""
See https://medium.com/analytics-vidhya/2d-convolution-using-python-numpy-43442ff5f381
:param image:
:param kernel:
:param padding:
:param strides:
:return:
"""
x_kern_shape = kernel.sh... | 007cc47f76a253adaf2f02ade01082670119ae8a | 41,334 |
from operator import add
def intcode_comp(puzzle_input, phase_setting, input_signal):
"""Compute based on the intcode instructions below
# position mode:
# 1: positional add
# 2: positional multiply
# 3: get input and save it at location of parameter
# 4: output value located a... | dfeab35af6210994d846d1d79916700b6e0e959b | 41,335 |
import ctypes
def copy(cell: SpiceCell) -> SpiceCell:
"""
Copy the contents of a SpiceCell of any data type to another
cell of the same type.
https://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/cspice/copy_c.html
:param cell: Cell to be copied.
:return: New cell
"""
assert isinstance(c... | 39f82d10170190b209e8a0fe5061e9aba6877317 | 41,336 |
import glob
import collections
import sys
def get_list_of_audios(folder_path, audio_extension = 'wav',
confirm_with_transcript = True,
verbose = False):
"""
Confirm_with_transcript requires: file path in first column
To-do: check if in csv file the header_none... | 0314dc6c9dd0afd509fb51235dbe74fc35b5fb15 | 41,337 |
def get_hash_hex(raw_hash):
"""Creates a nice hex representation of a raw req"""
return raw_hash.encode('iso-8859-1').encode('hex') | a7c0e873617cae2481fecc32a2051ad1fc6a9519 | 41,338 |
from typing import Any
import copy
def new_document(source_path: str, settings: Any = None) -> nodes.document:
"""Return a new empty document object. This is an alternative of docutils'.
This is a simple wrapper for ``docutils.utils.new_document()``. It
caches the result of docutils' and use it on seco... | 5bda163d426a9a7c2f419a282ab4c4e4907700cf | 41,339 |
def guild_only() -> AC:
"""A :func:`.check` that indicates this command must only be used in a
guild context only. Basically, no private messages are allowed when
using the command.
This check raises a special exception, :exc:`.ApplicationNoPrivateMessage`
that is inherited from :exc:`.ApplicationC... | a61f3e0f05acfb51842982dd41cd63d82345ed0b | 41,340 |
def importable_name(cls):
"""
>>> class Example(object):
... pass
>>> ex = Example()
>>> importable_name(ex.__class__)
'jsonpickle.util.Example'
>>> importable_name(type(25))
'__builtin__.int'
>>> importable_name(None.__class__)
'__builtin__.NoneType'
>>> importable_n... | 96fe43ab1c47b506c21bcb938ea34eeefaedac5a | 41,341 |
import os
def loadDictDDIs(path_file:str):
"""
load the ddi source if the pickle file already existe
:param path_file: path of the picke file
:type path_file: str
:return: dictionary with the ddis sources ids
:rtype: dict[(domain_id_a, domain_id_b)] : id sources
"""
dict_ddis_sour... | 6ffeb86eb867b6605ec77097b8d68a4a0526971b | 41,342 |
def gen_client(api_id: str, api_hash: str) -> Client:
"""Generates Client instance, nothing special
Args:
api_id (str): Telegram App API ID
api_hash (str): Telegram App API Hash key
Returns:
Pyrogram::Client
"""
return Client(
"tgresender",
api_id=api_id,
... | 7bd70964c3bb098cc70d2efc178cb038d04321e3 | 41,343 |
from typing import Iterable
from typing import List
def encode_argument_text_from_spans(arguments: Iterable[Argument], tokens: List[str]) -> str:
""" Return a string for the CSV field 'answer' """
return SPAN_SEPARATOR.join([span_to_text(span, tokens) for span in arguments]) | 9421a6a0f9aad8f9a8c33046a207d9ae941cf218 | 41,344 |
def get_folder_size_human(path, container: DockerContainer):
"""disk usage in human readable format (e.g. '2,1GB')"""
cmd_folder_size = "du -sh {}".format(path)
result = DockerUtils.run_cmd(cmd=cmd_folder_size, container=container)
return result.split()[0].decode('utf-8') | 8945627c13c841ec8b42896f8285b8d600518598 | 41,345 |
def is_input_type(graphql_type: "GraphQLType") -> bool:
"""
Determines whether or not the "GraphQLType" is an input type.
:param graphql_type: schema type to test
:type graphql_type: GraphQLType
:return: whether or not the "GraphQLType" is an input type.
:rtype: bool
"""
return isinstanc... | ff21d013848159cfa9a286af991fd79267c930e7 | 41,346 |
import json
def cartao_trello(request, pedido=None, desc=None):
"""Responsavel por enviar ao cartao trello."""
cliente = TrelloClient(api_key=API_KEY, api_secret=API_TOKEN)
my_boards = cliente.get_board('kyL57xiF')
lista = my_boards.all_lists()
pedido = json.dumps(pedido, cls=UUIDEncoder)
des... | ce558a948a747488cd6ef020e4f4e0174e2da91e | 41,347 |
from typing import OrderedDict
import math
def data_reorg_half_daily(instrument_type) -> pd.DataFrame:
"""
将每一个交易日主次合约合约行情信息进行展示
:param instrument_type:
:return:
"""
# engine = Config.get_db_engine(Config.DB_SCHEMA_PROD)
engine = Config.get_db_engine(Config.DB_SCHEMA_DEFAULT)
sql_str... | e765b5a7041d59012c1006588fe7daf265bd4325 | 41,348 |
import sys
import math
def assign_boxes_to_levels(boxlist,
min_level,
max_level,
canonical_box_size,
canonical_level):
"""
Map each box in `box_lists` to a feature map level index and return
the ass... | c8ff3c468f7411eea5a2b069ca29dc803d844beb | 41,349 |
def spectral_maxpeaks(sign, FS):
"""Compute number of peaks along the specified axes.
Parameters
----------
sig: ndarray
input from histogram is computed.
fs: int
sampling frequency of the signal
Returns
-------
num_p: float
total number of peaks
"""
f, ... | 2f61e97daf08e177a13a2b98c0dec43e4ea421fb | 41,350 |
import inspect
def get_calling_module(point=2):
"""
Return a module at a different point in the stack.
:param point: the number of calls backwards in the stack.
:return:
"""
frm = inspect.stack()[point]
function = str(frm[3])
line = str(frm[2])
modulepath = str(frm[1]).split('/')
... | 638006a14fb062810db34beefcd906b898ba45a5 | 41,351 |
def _pad_keys_tabular(data, sort):
"""Pad only the key fields in data (i.e. the strs) in a tabular way, such that they
all take the same amount of characters
Args:
data: list of tuples. The first member of the tuple must be str, the rest can be anything.
Returns:
list with the strs padded with space cha... | eba58694354a89e0a6d808c08f964755f3b11822 | 41,352 |
from typing import Optional
def depth_based_median(
X: FDataGrid,
depth_method: Optional[Depth] = None,
) -> FDataGrid:
"""Compute the median based on a depth measure.
The depth based median is the deepest curve given a certain
depth measure.
Args:
X: Object containing different samp... | 07025e781693c213c715aed5a8eac47fdbbb51af | 41,353 |
def get_read_only_permission_name(model: str) -> str:
"""
Create read only permission human readable name.
:param model: model name
:type model: str
:return: read only permission human readable name
:rtype: str
"""
return f"{settings.READ_ONLY_ADMIN_PERMISSION_NAME_PREFIX.capitalize()}... | 81e02b47079fc41fc5e4148a811aad12b2e5646a | 41,354 |
from typing import OrderedDict
def _determine_colnums_to_yield(colnames, fname, dtype_fname):
"""Return a list of integers storing the column numbers of the ASCII history file
corresponding to the ordered sequence determined by the input ``colnames``.
"""
colnames = np.atleast_1d(colnames)
colname... | 6a5c9d16f64fa5b067885aff9d95b3df5eccbe27 | 41,355 |
def get_all_countries():
"""Returns all countries"""
url = BASE_URL + "all"
return _get(url=url) | c3c6bb17e1191635a022d0a119defcaf0daff944 | 41,356 |
async def find_channel(ctx, userstr, interactive=False, collection=None, chan_type=None):
"""
Find a guild channel given a partial matching string,
allowing custom channel collections and several behavioural switches.
Parameters
----------
userstr: str
String obtained from a user, expec... | c07ce7c31e7c99cce0517901dcd7d3abb18720ac | 41,357 |
def df_params_generator(number_of_facilities, number_of_tasks, seed=0):
"""
Generate instance parameters for the df problem set mentioned in [1].
Parameters
----------
number_of_facilities: int
the number of facilities to schedule on
number_of_tasks: int
the number of tasks to a... | 370cba6ce19e5a5a9a556df165d554e4445da7e5 | 41,358 |
from typing import Counter
def mass_timeseries(cur, facility, flux):
"""Returns dictionary of mass timeseries of each isotope at a facility.
Parameters
----------
cur : sqlite cursor
sqlite cursor
facility : str
name of facility
flux : str
direction of flux
Returns... | 4cd53bab4918cd3558b61b4353957da40ccf99a2 | 41,359 |
import os
def get_credentials(account_id):
"""
Using STS assume role to obtain the temporary credentials of another AWS account
returns dict:
'error' : None if credentials is acquired successfully. Otherwise, it contains error message
"""
# get the cross account role name
cross_ac... | ffa367702c5ecffb6a5117bac5407ede5cdc4b13 | 41,360 |
def generate_config(context):
""" Creates the Cloud SQL instance, databases, and user. """
properties = context.properties
res_name = properties.get('name', context.env['name'])
project_id = properties.get('project', context.env['project'])
instance = get_instance(res_name, project_id, properties)... | df624472b40bf983329ca8e1a58e9b9d55e95e65 | 41,361 |
import uuid
import os
import time
def post_exposure():
"""
Upload an exposure resource
---
description: Uploads an exposure resource by posting an exposure tar file.
The tar file can be compressed or uncompressed.
produces:
- application/json
responses:
200:
... | c803c1c618e340f64df7df45556cc29ea62fd7a2 | 41,362 |
def loads(strng, root_name=DEFAULT_ROOT_NAME,
single_root_node=False, id_mapper=None):
"""load a config from a string.
Args:
strng: the string containing the config file
root_name: the tag for the top-level node that is added implicitly
single_root_node: if true, no implicit t... | 0c8fdb9886b051161cdb321abbad150e453d69b2 | 41,363 |
from pathlib import Path
def create_server_arguments(
configuration: configuration_module.Configuration,
start_arguments: command_arguments.StartArguments,
) -> Arguments:
"""
Translate client configurations and command-line flags to server
configurations.
This API is not pure since it needs ... | 0bf2d8c34b81e9b7800b1c6b95a044f1c11b13bf | 41,364 |
def getLabels(kmeans, options):
"""@brief Labels all centroids of kmeans object to their color names
@param kmeans KMeans object of the class KMeans
@param options DICTIONARY options necessary for labeling
@return colors LIST colors labels of centroids of kmeans object
@return ind ... | 8b5be98b82c0bc47369e3b980a81e512f84e31e9 | 41,365 |
def replace_surrogate_encode(mystring, exc):
"""
Returns a (unicode) string, not the more logical bytes, because the codecs
register_error functionality expects this.
"""
decoded = []
for ch in mystring:
# if PY3:
# code = ch
# else:
code = ord(ch)
# ... | e56d0267378ca5e29cc5ed55e359c384c84400a0 | 41,366 |
def _heom_state_dictionaries(dims, excitations):
"""
Return the number of states, and lookup-dictionaries for translating
a state tuple to a state index, and vice versa, for a system with a given
number of components and maximum number of excitations.
Parameters
----------
dims: list
... | 819c4e63f389ec8755e0ea92a98ee1c1e8749c08 | 41,367 |
import os
def get_file_names(path):
"""
Given a dir path, returns a list of files in this dir, not includes its child dir
:param path:
:return:
"""
names = []
if os.path.exists(path):
for (dirpath, dirnames, filenames) in os.walk(path):
names.extend(filenames)
... | 574cbe862f16347809675895bddeb1d5c3b6cfff | 41,368 |
def _get_num_els_in_scene_range(zarr_dataset: ChunkedDataset, scene_index_start: int, scene_index_end: int) -> dict:
"""
Get numbers of scenes, frames, agents, tl_lights in a set of scene in a zarr
Args:
zarr_dataset (ChunkedDataset): zarr dataset to use for computing number of elements
scen... | 561c9c58c9627bc56902ca6a9a904b6bfa063f22 | 41,369 |
def fill_nulls_w_own_distribution(column: Series) -> Series:
"""Finds the distribution of filled values in a column and fill its nulls with the same distribution
:param pandas.Series column: column to fill nulls
:return pandas.Series: column with nulls filled
"""
# Copy to avoid direct changes in ... | c1168b39b380c21758d6c1700a7d020fd1fbf008 | 41,370 |
def compute_data_term_gradient_vectorized(warped_live_field, canonical_field, live_gradient_x, live_gradient_y,
scaling_factor=10.0):
"""
Vectorized method to compute the data term gradient
:param live_gradient_x: x-component of the gradient of the warped_live_field... | 42861bc4a357e533c78a397b788228eca26b216a | 41,371 |
from pathlib import Path
def find_mount(path: Path):
"""Given a path, derive its mountpoint path"""
mount_path = path
while not mount_path.is_mount():
mount_path = mount_path.parent
logger.debug(f"Found mount for {path}: {mount_path}")
return mount_path | 4a5b3716fa22fdb6d2fd941024ea46db77e579be | 41,372 |
def pid(db, record):
"""File system location."""
return recid_minter(record.id, record) | 5757419926629dc3862914202b2a37ff0c6777f4 | 41,373 |
from typing import Tuple
def find_start_end(cus_list, pattern) -> Tuple:
"""
Find the start & end of pattern in cus_list. If none, return 0,0.
:param cus_list:
:param pattern:
:return:
"""
for i in range(len(cus_list)):
if cus_list[i] == pattern[0] and cus_list[i:i + len(pattern)] ... | e4d9c30c9050cb35a0123e7467d3c68c48c7887d | 41,374 |
def timecoverage():
"""
Time intervals of GLDAS data
"""
return [
('All Available Times', 'alltimes'),
(2019, 2019),
(2018, 2018),
(2017, 2017),
(2016, 2016),
(2015, 2015),
(2014, 2014),
(2013, 2013),
(2012, 2012),
(2011, 20... | f6f279c8f223a361785cc3a72cebfa02101f099f | 41,375 |
from ..jupyter.pv_ipygany import check_colormap
import sys
import logging
def make_mapper(mapper_class):
"""Wrap a mapper.
This makes a mapper wrapped with a few convenient tools for managing
mappers with scalar bars in a consistent way since not all mapper classes
have scalar ranges and lookup table... | 47ff9763ebe91c052d9b8ca54f605283f0ea06b6 | 41,376 |
def CDL3LINESTRIKE(data: xr.DataArray) -> xr.DataArray:
"""
Three-Line Strike (Pattern Recognition)
Inputs:
data:['open', 'high', 'low', 'close']
Outputs:
double series (values are -1, 0 or 1)
"""
return multiple_series_call(talib.CDL3LINESTRIKE, data, ds.TIME, ds.FIELD, [f.OPEN... | e6e240952ba8e81f1c0ef3bd4e10e0b9186ca5eb | 41,377 |
from typing import Union
def check_ess_certid(cert: x509.Certificate,
certid: Union[tsp.ESSCertID, tsp.ESSCertIDv2]):
"""
Match an ``ESSCertID`` value against a certificate.
:param cert:
The certificate to match against.
:param certid:
The ``ESSCertID`` value.
... | 268af8462decec09ab2a20be14f5319439b55bb3 | 41,378 |
import bz2
import base64
def passx_decode(passx):
"""decode the obfuscated plain text password, returns plain text password"""
return bz2.decompress(base64.b64decode(passx.encode("ascii"))).decode("ascii") | b8b2138c55dd28734661484a231128e6f3ccbbb7 | 41,379 |
def cloudfront_restriction_type(restriction_type):
"""
Property: GeoRestriction.RestrictionType
"""
valid_values = ["none", "blacklist", "whitelist"]
if restriction_type not in valid_values:
raise ValueError(
'RestrictionType must be one of: "%s"' % (", ".join(valid_values))
... | d8f7a248800d0b93f0ceee60cd40227d92614341 | 41,380 |
def variance_scaling_initializer(tensor, factor=2.0):
""" Variance scaling initializing using FAN_AVG, similar to the one in TF
:param tensor: A tensor of arbitrary shape.
:param fan_in: int
:param fan_out: int
:param factor: A scalar, the scaling factor.
:returns: A tensor with the same shape ... | ed5b2f278cfd33858f59cd8ebdf48814426f5436 | 41,381 |
import tokenize
import collections
import random
def convert_single_example(example, tokenizer, is_training):
"""Converts a single NqExample into a list of InputFeatures."""
tok_to_orig_index = []
orig_to_tok_index = []
all_doc_tokens = []
features = []
for (i, token) in enumerate(example.doc_tokens):
... | 04eaa4652246803bb8a96ac2f2eac7a8b188ee92 | 41,382 |
from typing import Union
from typing import Tuple
def calcCog(argument: Union[str, list]) -> Tuple[float, float, float]:
"""
calculates the Center of Geometry of a given selection or list of atoms
Args:
argument (str or list): either a PyMOL-selection name or a List of atoms
Returns:
... | 8694f5949c21ced81b8a7d7e8dc4c89842a1ea2c | 41,383 |
import subprocess as subp
from typing import OrderedDict
import sys
import os
def IMcleaner(dpath, site, scheck, coords, verbose, test = False, dsinfom = "LANDSAT_5_7_8"):
"""
Function to clean the data up and make the visualisation better
"""
# ========== setup the key params ==========
SF = 0.0001 # Scal... | 9c2a7dcfdeaac2490cd3dbc038742a20d3d81d27 | 41,384 |
import sys
import subprocess
def isort(
config: c2cciutils.configuration.ChecksIsortConfig,
full_config: c2cciutils.configuration.Configuration,
args: Namespace,
) -> bool:
"""
Run isort check on all files including Python files without .py extension.
config is like:
ignore_patterns_re:... | f33dc30254d36a429f8e2e6dfc3eba36f4ce54b2 | 41,385 |
import threading
def create_image_server():
"""
Create flask image debug server.
Warning! This is a very hacky flask server. Make sure to only run this once as it uses global stare
Returns:
Dictionary into which you can insert images with string keys
"""
threading.Thread(target=lambd... | 4d78f3733923a17252c6163616918dd09961f416 | 41,386 |
import scipy
def find_peaks(signal, fs, min_separation=270, window_width=2500, noise_level=1.25):
"""Find peaks from pulse oximeter or ECG.
Args:
signal: Pulse oximeter or ECG data.
fs: Sampling frequency (Hz) of the signal.
min_separation: Strict minimum time between peaks (ms).
... | c892561960c5ebe299de30fa67012b12d5dcd743 | 41,387 |
def evaluate_rm_gold(prediction, ground_truth):
"""
Evaluation matrix.
:param prediction: a dictionary of labels. e.g {0:[1,0],1:[2],2:[3,4],3:[5,6,7]}
:param ground_truth: a dictionary of labels
:return:
"""
pos_gt = 0.0
pos_pred = 0.0
true_pos = 0.0
for i in ground_truth:
... | 98eeb3fa0ffe4f9b3d0863a41bd3ca5d6c4a036f | 41,388 |
from pathlib import Path
def is_git_bundle(path: Path) -> bool:
"""Indicate if a path is a valid git bundle."""
with TemporaryDirectory(prefix=f"{__name__}.is_git_bundle.") as dirname:
with local.cwd(dirname):
git("init")
return bool(git["bundle", "verify", path] & TF) | b1120f27111ed4f31bb408ee31b230e6cefaa733 | 41,389 |
import os
def find_file(path, ext, index=0, sort='getctime'): # unused
""" Search files by extension, sort by time created and return indexed file. """
files = [x for x in os.listdir(path) if x.endswith(ext)]
files = sorted(files, key=lambda x: os.path.getctime(os.path.join(path, x)), reverse=True)
n... | 70788d966294e8886148e16114b698f1786db48d | 41,390 |
def checksum_file(summer, path):
"""
Calculates the checksum of the file 'path' using the provided hashlib
digest implementation. Returns the hex form of the digest.
"""
with open(path, "rb") as f:
# Read the file in 4KB chunks until EOF.
while True:
chunk = f.read(4096)
if not chunk:
... | 729b8f895fe74856e83046d0fd5177e584f835f2 | 41,391 |
def camel_case(value):
"""Convert an identifier to CamelCase"""
return "".join(ele.title() for ele in value.split("_")) | e7c74ebe7611eb567f3eae8f16fb01aadd201252 | 41,392 |
def parallelize (imgs, func, cores=2):
"""
Execute a function for each image in parallel.
This function assumes 'imgs' is multi-frames of grayscale
images for the current version.
Parameters
----------
imgs : numpy.ndarray (3d) or list of numpy.ndarray(2d)
Input multi-frame images. ... | acd5f64501dbe13d46b7b4fafe6df4f3300c7e56 | 41,393 |
def getter_function_spectrum(filename):
"""
partial does not use kwargs so our options are limitted here
"""
return Spectrum(filename=filename, is_ucd=False) | 6e3f547378cf8bbbd9b67f9031380870c23040ef | 41,394 |
def cov_cluster_robust(jac, hess, design_info):
"""Cluster robust standard errors.
A cluster is a group of observations that correlate amongst each other,
but not between groups. Each cluster is seen as independent. As the number
of clusters increase, the standard errors approach robust standard errors... | 98cc96890597e336d5b43b24e8d30fd1893ae9ed | 41,395 |
import re
from datetime import datetime
def fix_time_units( timeunits ):
"""Sometimes we get time units which aren't compatible with cdtime.
This function will (try to) fix them. The input argument is a string, e.g.
"months since Jan 1979" and the return value is another string, e.g.
"months since 19... | 64f452b35857c741a04689d670f8c3502dd2d82d | 41,396 |
def binary_encoding(string, encoding = 'utf-8'):
"""
This helper function will allow compatibility with Python 2 and 3
"""
try:
return bytes(string, encoding)
except TypeError: # We are in Python 2
return str(string) | 7982f27c266479b757e3a73e9463acd88b98abcf | 41,397 |
def get_all_overlays_config(self) -> list:
"""Get all configured overlays in Orchestrator
.. list-table::
:header-rows: 1
* - Swagger Section
- Method
- Endpoint
* - overlays
- GET
- /gms/overlays/config
:return: Returns list of dictionaries... | 3c77c14096373792bdaf5c39ffdc3f9d58b0af0d | 41,398 |
def load_densityoperator(filename):
"""
Load a C++QED state vector file from the given location.
Returns a tuple with a list of densityoperators and a list of times.
*Usage*
>>> svs,times = load_statevector("ring.sv")
:param filename:
Path to the C++QED state vector file that should be loade... | c1a3ba6484b86adfa76c8abd28f580f89d2103c8 | 41,399 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.