content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def message(**properties):
"""Convenience to create a proton.Message with properties set"""
m = Message()
for name, value in dict_iteritems(properties):
getattr(m, name) # Raise exception if not a valid message attribute.
setattr(m, name, value)
return m | b34a01f6c20dba44f7d05c8bdfc7ba733726f689 | 79,937 |
def replace_url_el(url: str, props: PropertySet, allow_no_schema=False) -> str:
"""
Replaces all EL variables in the url, validates schema and returns the url.
"""
url_with_var = replace_el_with_var(url, props=props, quote=False)
if not is_allowed_schema(allow_no_schema, url_with_var):
raise... | 59a012da7cfb902c26addb807b5f97e9827819b8 | 79,938 |
def dist(p,q):
""" Calculates the distance between the points p and q.
Parameters
---------
p : Point
the first point
q : Point
the second point
Returns
----------
Float
The distance between the points p and q.
"""
return (sum((p.array()-q.array())*... | 97c0beb7f8c22e59da9551e35e66a7d8e39bf667 | 79,939 |
import six
import random
import numpy
def predictive_columns(M_c, X_L, X_D, columns_list, optional_settings=False, seed=0):
""" Generates rows of data from the inferred distributions
Inputs:
- M_c: crosscat metadata (See documentation)
- X_L: crosscat metadata (See documentation)
- X_D: crosscat metadata (See... | a4731b0f3c7ce8882b83b7cb06c7eaf92c389ed4 | 79,940 |
from datetime import datetime
def datetimeformat(date_str: str) -> str:
"""日付フォーマット変更
Args:
date_str (str): 時刻文字列(YYYY-MM-DD HH:mm:ss+hh:mmZ)
Returns:
str: 変換後時刻文字列
"""
if not isinstance(date_str, datetime.datetime):
return "-"
dt = arrow.get(date_str)
local = dt... | 5f3e94fbd9b306cbb68cad8dfba229753f90bd5d | 79,941 |
import array
def analytical_value_k_ejr2(distr1, distr2, u, par1, par2):
""" Analytical value of the Jensen-Renyi kernel-2.
Parameters
----------
distr1, distr2 : str-s
Names of distributions.
u : float, >0
Parameter of the Jensen-Renyi kernel-2 (alpha = 2: fixe... | 864a232568fece4a9c598a39d7998eae2f7ed0ee | 79,942 |
def _to_system(sab):
"""Converts an SAB to a system.
Args:
sab: a UMLS source name abbreviation
Returns:
the identity of the terminology system
"""
return _SAB_TO_SYSTEM.get(sab, 'http://www.nlm.nih.gov/research/umls/%s' % sab.lower()) | 8cd05f19aef06ddbf9f5b0f7735d08334634a3b2 | 79,943 |
def _shorten_ops(a, b):
"""Shorten two ops by the part that cancels each other out."""
len_a = _op_len(a)
len_b = _op_len(b)
if len_a == len_b:
return (None, None)
if len_a > len_b:
return (_shorten(a, len_b), None)
return (None, _shorten(b, len_a)) | 1000f89c0b9464aacaa2516bc4547da7e452f3fd | 79,944 |
from datetime import datetime
def makedatetimestamp(t):
"""Like util.makedate() but for time t instead of current time"""
delta = (datetime.datetime.utcfromtimestamp(t) -
datetime.datetime.fromtimestamp(t))
tz = delta.days * 86400 + delta.seconds
return t, tz | 5126eac899a323475262dbdf07d82edc0d4f7469 | 79,945 |
def reward_binary_goal_based(navenv):
""" Reward of 1 is given when close enough to the goal. """
curpos = navenv.current_pos
if (dist(curpos, navenv.goalPos) <= navenv.goalRadius):
return 1.
else:
return 0. | 036cfc6b173d8581fb0e17bef3b6356f50de8fed | 79,946 |
def sync_synchronize(repository_id, user_id=None, manual=False):
"""
Run all tasks for a repository, to be called from scheduler
"""
auth.s3_impersonate(user_id)
rtable = s3db.sync_repository
query = (rtable.deleted != True) & \
(rtable.id == repository_id)
repository = db(... | b9ee37505ab2b42f4520fe9c9d32f33f642b3d7e | 79,947 |
import uuid
def _generate_id() -> str:
"""Generate the image identifier.
Returns:
The image identifier as a string.
"""
hw = hw_info.HWInfo()
return ('%s-%s' %
(str(hw.BiosSerial()), str(uuid.uuid4())[:7])).upper() | 968eed7b8eff293141b96cec40a76418fb3f2d72 | 79,948 |
def build_feature_summary(data, information_level, feature_description, missing_values, generate_excel=False):
"""
Build new dataset describing each column more precisely to support decision making and analytics
All columns from the main dataset is merged datasets `information levels` and `feature desc... | 48ea2c0aedaebcb59ff0500a12af201056b35543 | 79,949 |
from datalad.consts import DATASETS_TOPURL
def get_datasets_topdir():
"""Delayed parsing so it could be monkey patched etc"""
return RI(DATASETS_TOPURL).hostname | a2cf782729855ba087d125b4d51844d553a2c5e0 | 79,950 |
def create_min_ndvi_mosaic(dataset_in, clean_mask=None, no_data=-9999, dtype=None, intermediate_product=None, **kwargs):
"""
Method for calculating the pixel value for the min ndvi value.
Parameters
----------
dataset_in: xarray.Dataset
A dataset retrieved from the Data Cube; should contain... | 61cd2934f3faac6b781af0dd0b46b9d0d3e506dd | 79,951 |
def compute_binary_classification_loss(scores, labels, weight):
""" Compute classification loss
:param scores Shape=[batch_size]
:param labels Shape=[batch_size]
:param weight Shape=[batch_size]
"""
# Binary classification loss
return tf.compat.v1.losses.sigmoid_cross_entropy(logits=tf.expa... | 3a2112ec6cb66fb5a9eccdd5ba04dcd9a191a892 | 79,953 |
def bulk_lag_estimate(y, shift, x=None, poly=None, log=False):
"""Create estimates for a specific time horizon for an entire data frame.
No missing values permitted.
Args:
y (pandas.DataFrame): a dataframe where each row is a time period and each column is a metric to be predicted.
shift (... | cd90704bc89971d5fb9a1dd1452373ad80c7fa6f | 79,954 |
def check_is_executable(program):
"""Check whether a program is executable.
Parameters
----------
program : str
Program name.
Returns
-------
str
Human-readable message.
"""
check_message = '%s is executable...' % program
return result_message(_is_executable(pr... | 233828b81f8dd634178b2d98ed008ff0f2f70121 | 79,955 |
import traceback
def request(path):
"""Send a request to a given URL accepting JSON format and return a \
deserialized Python object. If no "http://" protocol is specified, \
BASE_URL is used in the request.
Args:
path (str): The URI to be requested.
Returns:
response: Deserial... | e913060238abcf6508ffd03fd95f393e40932b41 | 79,956 |
def parse_transformers(transformers):
"""
Parse the list of transformers, given by configuration, into a list of
tuple of the transformers name and a dictionary containing additional args.
The transformer is assumed to be of the form 'name/arg1=value/arg2=value'
:raw_transformers: list of strings ... | 7812f9929d75c1e6b496821eb0566ead2f57f812 | 79,957 |
def try_int(text, default=0):
"""Try to parse an integer but return a default if it fails."""
try:
return int(text)
except ValueError:
return default | b699bbd7209a88e1df3d2b941d581904bf30e737 | 79,958 |
from typing import IO
from typing import Any
from typing import Sequence
import struct
def read_bytes_as_tuple(f: IO[Any], fmt: str) -> Sequence[Any]:
"""Read bytes using a `struct` format string and return the unpacked data values.
Parameters
----------
f : IO[Any]
The IO stream to read byte... | b2622d5aad02c528163cb3318b5c70ea0510ea01 | 79,959 |
def mask_to_signal(lst):
"""将持仓蒙板转化为交易信号.
转换的规则为比较前后两个交易时间点的持仓比率，如果持仓比率提高，
则产生相应的补仓买入信号；如果持仓比率降低，则产生相应的卖出信号将仓位降低到目标水平。
生成的信号范围在(-1, 1)之间，负数代表卖出，正数代表买入，且具体的买卖信号signal意义如下：
signal > 0时，表示用总资产的 signal * 100% 买入该资产， 如0.35表示用当期总资产的35%买入该投资产品，如果
现金总额不足，则按比例调降买入比率，直到用尽现金。
... | cd541c9afbc65c584dace4e2fd64c7056869d235 | 79,960 |
import json
def extract_request_from_record(record):
"""extract refresh credential request from record"""
payload = json.loads(record['body'])
request = RefreshCredentialRequest(**payload)
if not request.email:
request.email = common.find_user_tag(iam_client, request.user_name,'IamRotateCreden... | 50e985f221685f7a8707e56df22f12c56b94b3aa | 79,961 |
import re
def getLevelFromServerProps():
"""Search the server props file for the configured security level"""
pattern = r"RoutesSecurityLevel=(\d+)"
file = open(CONF_FILE, "r")
for line in file:
result = re.match(pattern, line)
if result:
return int(result.group(1)) | c0f043df6afa274b83c4c369c836afaed17f5f82 | 79,963 |
def find_silver_token(angle,length):
"""
Function to find the closest silver token
Returns:
dist (float): distance of the closest silver token (-1 if no silver token is detected)
rot_y (float): angle between the robot and the silver token (-1 if no silver token is detected)
"""
#angle signifies the a... | 4ff3a52769c8a02381a206cd581a8277de4c9694 | 79,965 |
def clean_record(rec: list, field_names: list) -> dict:
"""
Parses the record supplied by the calling function and returns a dictionary
that can be transformed into a database record.
:param rec: record extracted from file
:ptype rec: list
:param field_names: field names for the record
:pty... | a76974cb8f7e12aec80404df85b90001df2a69f4 | 79,966 |
import warnings
def train_segmentor(model,
dataset,
cfg,
distributed=False,
validate=False,
timestamp=None,
meta=None,
compression_ctrl=None,
val_dataloader=N... | 5e6f14bf214e54c00db49a701946c86d18e8748d | 79,968 |
def virtual(func: "callable"):
"""
mark a function as "virtual", which means that this function can be override.
any base class should use this or @abstractmethod to decorate all functions
that can be (re)implemented by subclasses.
"""
return func | 46b31f828c19c3288028eb485bfe78795c632148 | 79,969 |
def get_template(template: str) -> Template:
"""Read template from file
:param template: path to template
:return: Template
"""
template_file_content: str = read_file(template)
return Template(template_file_content) | 38b1046cb9097d1dbe419385e520d53bf2ff09c8 | 79,970 |
import asyncio
async def main(argv: list[str]):
"""Restart a KNX device."""
if len(argv) != 2:
print(f"{argv[0]}: missing target address.")
return 1
address = IndividualAddress(argv[1])
xknx = XKNX()
await xknx.start()
await xknx.telegrams.put(Telegram(address, payload=Resta... | 47614d167e8901bd1092efac6c75a2315f8a84bf | 79,971 |
import re
def _get_changelist(perforce_str):
"""Extract change list from p4 str"""
rx = re.compile(r'Change: (\d+)')
match = rx.search(perforce_str)
if match is None:
v = 'UnknownChangelist'
else:
try:
v = int(match.group(1))
except (TypeError, IndexError):
... | 26b08d8ccf6251e0d3a9698147093e2bb6e89919 | 79,972 |
from pycsw.plugins.profiles.apiso.apiso import APISO
def caps2iso(record, caps, context):
"""Creates ISO metadata from Capabilities XML"""
apiso_obj = APISO(context.model, context.namespaces, context)
apiso_obj.ogc_schemas_base = 'http://schemas.opengis.net'
apiso_obj.url = context.url
queryable... | 83e1f460a956b5de2231a8e8eab39bfc9c4db6f1 | 79,973 |
def get_top_k_trigrams(poi_gdf, names, k):
"""
Creates a features array. Firstly, the top *k* % trigrams among *names* \
are considered (e.g. a set of trigrams *T*). Then, for each poi *p* (each \
row) the array will contain 1 (True) in column *c*, if trigram *T[c]* \
appears in *p*'s name.
Arg... | bea2046ae61e7fd2e4907ec81f903b5336e659b0 | 79,974 |
def read_recs(con, tbl, q="", qwhere="", qorder=""):
""" Read recs matching where clause.
con: sqlite connection
tbl: table name
qwhere: sql where clause
"""
if qwhere == "":
qwhere = "1"
if qorder == "":
qorder = "_id"
if not tbl in all_tables(con):
return []
... | 60d7a4a82bd54c3d2b7dfc81d46c888cb17442ce | 79,975 |
def LoadEcgPipeline(batch_size=20, annot_ext="pu1"):
"""Preprocessing pipeline for Hidden Markov Model.
This pipeline prepares data for ``hmm_train_pipeline``.
It works with dataset that generates batches of class ``EcgBatch``.
Parameters
----------
batch_size : int
Number of samples i... | 65c746f95dd74140b5d8034d776089a94f74ea42 | 79,976 |
async def me(request: web.Request, auth: SpotifyAuth) -> web.Response:
"""View to show the authorized user's Spotify user information"""
response = await request.app["spotify_app"]["spotify_client"].request(
request.app["client_session"], auth, "/me"
)
# Don't forget to update the authorization... | 1f223c9c95a53b059ae29444e02581a886b41cdd | 79,978 |
def parse_step_id_from_sacct(output, step_name):
"""Parse and return the step id from a sacct command
:param output: output of sacct --noheader -p
--format=jobname,jobid --job <alloc>
:type output: str
:param step_name: the name of the step to query
:type step_name: str
:retu... | 2ed06aba82665ad2a42c12a39c589d10258883f4 | 79,979 |
def parse_namespace_uri(uri):
"""Get the prefix and namespace of a given URI (without identifier, only with a namspace at last position).
:param str uri: URI
:returns: prefix (ex: http://purl.org/dc/terms/...)
:returns: namespace (ex: .../isPartOf)
:rtype: tuple[str,str]
"""
# Split the uri... | 9d883db067720cfa37eeec2d986a84506e6aaff8 | 79,981 |
def validate_course_policy(module_store, course_id):
"""
Validate that the course explicitly sets values for any fields
whose defaults may have changed between the export and the import.
Does not add to error count as these are just warnings.
"""
# is there a reliable way to get the module loca... | 5725d03bd3b3823f0c6dc6f5d6d4a1cb94692420 | 79,982 |
def best_fit_decreasing_no_overload(last_n_vm_cpu, hosts_cpu, total_threshold_cpu,
hosts_ram, total_threshold_ram,
inactive_hosts_cpu, inactive_hosts_ram,
vms_cpu, vms_ram,
cpu_weight, ram_weight, overload_threshold):
"... | d34ffae2eb0904a46f2e396cb64f2fa07c887081 | 79,983 |
def cors_header(func):
""" @cors_header decorator adds CORS headers """
@wraps(func)
def wrapper(self, request, *args, **kwargs):
res = func(self, request, *args, **kwargs)
request.setHeader('Access-Control-Allow-Origin', '*')
request.setHeader('Access-Control-Allow-Headers', 'Conte... | b7900d771f0c6c9ef088873f9fc28a3b235a319c | 79,984 |
import array
def qpoases_solve_qp(P, q, G=None, h=None, A=None, b=None, initvals=None,
verbose=False, max_wsr=1000):
"""
Solve a Quadratic Program defined as:
.. math::
\\begin{split}\\begin{array}{ll}
\\mbox{minimize} &
\\frac{1}{2} x^T P x + q^T x \\\\
... | 3e8143d68337735ae76ab605c0c0ec9fbd46d4bc | 79,985 |
def verify_input_data(function):
"""
Check that all input data is present in JSON file for each step
:param function: function to populate ui
:return: None
"""
def check(*args):
try:
function(*args)
except ValueError:
msg = "Please verify that integer numb... | 8374d14e3db687c9013aeabfd41f22fbbd4a8851 | 79,987 |
def detectLanguage(pathToFile):
"""
Detects the language of a code file (based on the extension)
Parameters:
pathToFile - The path to the file
Returns:
language - The language used in the file
"""
try:
assert isinstance(pathToFile, str)
except AssertionError:
... | 2f690fa942c5f90d1c56fe6c6ce117a3fd1115b1 | 79,988 |
def t_test_p_value(sample1, sample2):
""" Performs pairwise t-test for computing the p-value given two samples"""
if(len(sample1) > 1 and len(sample2 > 1)):
res = stats.ttest_rel(sample1, sample2)
return res.pvalue
else:
return 1.0 | 93044f0f196b2cff03fd6311349a1b4aa8d67bd6 | 79,989 |
def drop_observations(
dataset: timeseries.MultiRegionDataset, filter_: Filter
) -> timeseries.MultiRegionDataset:
"""Drops observations according to `filter_` from every region in `dataset`."""
assert filter_.drop_observations
# wide-dates DataFrames that will be concat-ed to produce the result MultiR... | 1bda28828eed99df3700470b2feb8c3ecda73b5e | 79,990 |
def read_stock(ticker: str, folder_path: str) -> pd.DataFrame:
"""
Function that read the history of a stock from the stocks folder.
@param ticker: ticker to read the data from.
@folder_path: folder of the stocks.
@return: df with the data.
"""
try:
df_stock = pd.read_csv(folder_pat... | e566710808ea88ad9de36b1972fa4f072145fad3 | 79,992 |
def snapshot(self, label, snap_type='statevector'):
"""Take a snapshot of the internal simulator representation (statevector)
Works on all qubits, and prevents reordering (like barrier).
Args:
label (str): a snapshot label to report the result
snap_type (str): a snapshot type (only supports... | cb7f1b7d8013c08092e8acf3ff98bd405e52801d | 79,994 |
def to_hpr(dcm):
"""Convert a direction cosine matrix to heading, pitch and roll angles.
The returned heading is within [0, 360], the pitch is within [-90, 90]
and the roll is within [-90, 90].
If ``90 - abs(pitch) < np.rad2deg(1e-3)`` then the roll is set to 0 and
the heading is computed accordin... | 13415b2f5f06a94d3f4274788e6d9302d8c05046 | 79,995 |
def InverseStudentT(degree_of_freedom, probability):
"""Inverse of Student's T distribution CDF. Returns the value x such that CDF(x) = probability.
Ported from Java: http://jsci.sourceforge.net/
This is not the best algorithm in the world. SciPy has a Fortran version
(see special.stdtrit):
http:/... | de8ef2075f814ea2fe39159a025d308454d1357c | 79,996 |
def init_seq(VCFFileName, maxskip=100, name=None):
"""Open a (gzipped) VCF4.1 file.
Try to open the given VCF file, checks if it is in VCF format.
Initialize a :class:`VCFStream` object that contains the first
base.
Please close the associated file object with
:func:`VCFStream.close` when you ... | db35f9c404c6cc7a0ae1e3c58f3df817e2bd2ad0 | 79,998 |
def prism_layer(
coordinates,
surface,
reference,
properties=None,
):
"""
Create a layer of prisms of equal size
Build a regular grid of prisms of equal size on the horizontal directions
with variable top and bottom boundaries and properties like density,
magnetization, etc. The fun... | f0a003544e722ad33c72b29431c928d8b05d88f4 | 79,999 |
import pickle
def loadPop(filename="popSaved045_long.dat"):
"""
Loads a saved population
"""
fin=open(filename,'r')
b=pickle.load(fin)
fin.close()
return b | 712408bdc6f8bc354db399287e298ccf4010df30 | 80,000 |
def extract_items(topitems_or_libraryitems):
"""
Extracts a sequence of items from a sequence of TopItem or
LibraryItem objects.
"""
seq = []
for i in topitems_or_libraryitems:
seq.append(i.item)
return seq | 6a6918b4fc8153f4c98f5df906ce584422b3df78 | 80,001 |
def lda():
"""LDA vectorizer."""
return [LDAVectorizer()] | 2bf6e1f0a688eeb40e285617b4afc5eff1eab8a7 | 80,002 |
def morphAnnList(AIs,winCounterList):
"""
Takes the top half of the ANNs and gives
them 2 children each.
"""
surviving = findTheMostFit(AIs,winCounterList)
new_generation_ann = []
for ann_nr in surviving:
for child_nr in range(2):
child = AIs[ann_nr].spawnChild()
... | bf72efb08143687beb0af5115b278f5fb44e0cb7 | 80,003 |
def construct_federated_getitem_call(arg, idx):
"""Constructs computation building block passing getitem to federated value.
Args:
arg: Instance of `computation_building_blocks.ComputationBuildingBlock` of
`computation_types.FederatedType` with member of type
`computation_types.NamedTupleType` from... | afaca4648975b207eed88ca8ee85e63ab84c2130 | 80,004 |
import pdb
import torch
def cal_si_snr(source, estimate_source, source_lengths=None):
"""Calculate SI-SNR with PIT training.
Args:
source: [B, C, T], B is batch size
estimate_source: [B, C, T]
source_lengths: [B], each item is between [0, T]
"""
pdb.set_trace()
assert sourc... | f1e4ed6474868a3da2fd6ad16564cf962c0f37f0 | 80,005 |
def match_candidates_by_time(images, exifs, max_neighbors, use_capture_time=True):
"""Find candidate matching pairs by time difference."""
if max_neighbors <= 0:
return set()
k = min(len(images), max_neighbors + 1)
times = np.zeros((len(images), 1))
for i, image in enumerate(images):
... | ce85e8a87ac43f43bca71a81de98692be8c56d9e | 80,006 |
def city_data():
"""The data for the one and only `City` object as a `dict`."""
return {
'id': 1,
'name': 'Paris',
'kml': "<?xml version='1.0' encoding='UTF-8'?> ...",
'center_latitude': 48.856614,
'center_longitude': 2.3522219,
'northeast_latitude': 48.9021449,
... | 346e067ecb48e8f3c56eb0834af92a78867ce9f5 | 80,007 |
def start_data_service():
"""
Get application of data
:return: APPLICATION FLASK
"""
logger.info("Start data service")
return DATA_SERVICE.run(host=env.DATA_SERVICE_ADD, port=env.DATA_SERVICE_PORT) | 8cba9185d154e80ec9dafd1cca0435c48f07fbb9 | 80,008 |
def combine_translations(accept_language, domain="nbjs"):
"""Combine translations for multiple accepted languages.
Returns data re-packaged in jed1.x format.
"""
lang_codes = parse_accept_lang_header(accept_language)
combined: dict = {}
for language in lang_codes:
if language == "en":
... | e182418a68728f0071b0ffed2f2cfa6a107543d8 | 80,009 |
def print_model(text: str = '', model: ModelType = []):
"""
It prints sqlmodel responses for complex relationship models.
"""
return print(text, jsonable_encoder(model)) | 048bf63e19d6d421e15237b7b852c8770047b8eb | 80,010 |
def gaussin(nsigma=1):
"""FRACTION WITHIN nsigma"""
return erf(nsigma / sqrt(2)) | 3372b4fdccfc2ee4a895f55bc06487a496f937ac | 80,011 |
def get_custom_module_description(name):
"""Return string with description for custom modules."""
return "Custom module from corpus directory ({}.py).".format(name.split(".")[1]) | 647e2df266a25b888558c34b4d425e09b0f58ca1 | 80,012 |
def _showcompatlist(
context, mapping, name, values, plural=None, separator=b' '
):
"""Return a generator that renders old-style list template
name is name of key in template map.
values is list of strings or dicts.
plural is plural of name, if not simply name + 's'.
separator is used to join v... | a0e717c645aa00a8dd239a435cdec42593d58411 | 80,013 |
def _current_groups(request, authority):
"""
Return a list of the groups the current user is a member of.
This list is meant to be returned to the client in the "session" model.
"""
user = request.user
svc = request.find_service(name="group_list")
groups = svc.session_groups(user=user, aut... | ca21c322eadc01c21478c96a61ca608e620b61b2 | 80,015 |
def evaluate_hist_multi_x_multi_y_product(x, row, bins, vals, derivs=None): #pragma: no cover
"""
Evaluate a set of values from histograms
Parameters
----------
x : array_like (npts)
X values to interpolate at
row : array_like (npdf, 1)
Which rows to interpolate at
bins : a... | 14ee6bbd94d21ee8dfdc5e0554d816c5e0cfc83f | 80,016 |
def get_pixdist_ratio(m_size, ant_rad):
"""Get the ratio between pixel number and physical distance
Returns the pixel-to-distance ratio (physical distance, in meters)
Parameters
----------
m_size : int
The number of pixels used along one-dimension for the model
(the model is assume... | b307ee5da49b9cd92958aa6d94c4e3ffa860bf1d | 80,017 |
def sstrip(s, suffix):
"""Suffix strip
>>> sstrip('foo.oof', '.oof')
'foo'
>>> sstrip('baroof', '.oof')
'baroof'
"""
i = - len(suffix)
if s[i:] == suffix:
return s[:i]
return s | 7f4d0f118caa48d68ae826813b65e3d452c2c1e8 | 80,018 |
def affine_map( T, P, t=None , get_inverse=True):
"""
Returns the affine map of a polytope.
"""
if type(t)==type(None):
t=np.zeros((T.shape[0],1))
if P.type=='AH_polytope':
return pp.AH_polytope(t=t+np.dot(T,P.t),T=np.dot(T,P.T),P=P.P)
elif P.type=='zonotope':
... | 47af53524b50d8e468151074c393b0c3ff99a51b | 80,019 |
def make_view(robot):
"""
为一个 BaseRoBot 生成 Django view。
:param robot: 一个 BaseRoBot 实例。
:return: 一个标准的 Django view
"""
assert isinstance(robot, BaseRoBot),\
"RoBot should be an BaseRoBot instance."
def werobot_view(request):
timestamp = request.GET.get("timestamp", "")
... | 2c3f51a10bff6f31640bc28ea30ef79c215e3ce0 | 80,020 |
def play_action_logic():
"""
Executes an action for the current player in the game and accordingly updates the state of the game. The action
is passed as an argument to the application call.
:return:
"""
position_index = Btoi(Txn.application_args[1])
state_x = App.globalGet(AppVariables.Pla... | c2111c72c09c2136d768cdf10fdd0dea42f54d6e | 80,022 |
def usersitedata_update(user_id, site_id, data=None): # noqa: E501
"""usersitedata_update
# noqa: E501
:param user_id: A UUID value identifying the user.
:type user_id: dict | bytes
:param site_id: A unique integer value identifying the site.
:type site_id: int
:param data:
:type dat... | 9946334f73974d7adc6f50e3fab40590dc03c405 | 80,023 |
def median_absolute_error(y_true, y_pred):
"""
Returns the median absolute error.
Parameters
----------
y_true : array_like
The correct targets.
y_pred : array_like
The estimated targets.
Returns
-------
float
The median absolute error.
"""
y_true, y... | 06510ce4276828af2000c8a8e83a9014051f4cfe | 80,024 |
def bottleneck_block(filters, init_strides=1, is_first_block_of_first_layer=False):
"""bottleneck blocks for use on resnets with layers > 34.
Follows improved proposed scheme in http://arxiv.org/pdf/1603.05027v2.pdf
"""
def f(input):
if is_first_block_of_first_layer:
# don't repeat ... | f28b7ad6d095feba37a8f141d37067fd7238b620 | 80,026 |
def add_test(args=list(), solutions=list()):
"""
Adds a new `TestCase` object to `tests` for function `fn` with paramaters
`args` and expected return values `solutions`.
"""
def wrap(fn):
global tests
new_test = TestCase(fn, args, solutions)
tests = tests >> new_test if te... | 9c076294b808019946adff9ae3b03627828fb2f2 | 80,027 |
def get_processed_mnist_data(group_size, class0=0, class1=1):
"""Creates a set of bags, each containing a number of samples and the proportion of a certain label in that bag. The propotion is the number of class1 items in the bag, divided by the total number of items in the bag.
Keyword arguments:
group_si... | cf7c8af70f0cbec62b4cb1a693dcb30fca12bd76 | 80,028 |
import pyarrow as pa
def to_arrow_type(dt):
""" Convert Spark data type to pyarrow type
"""
if type(dt) == BooleanType:
arrow_type = pa.bool_()
elif type(dt) == ByteType:
arrow_type = pa.int8()
elif type(dt) == ShortType:
arrow_type = pa.int16()
elif type(dt) == Integer... | 18146e22dde47ef014b26fb32424e94af3127145 | 80,029 |
def to_int(domain: Domain) -> int:
"""
Convert Domain to big endian int since
sigp/milagro_bls use big endian int on hash to g2.
"""
return int.from_bytes(domain, "big") | 66bc5131205e22bef8e4d5b5c2e3566cf37990a1 | 80,030 |
from datetime import datetime
def rpt_tickets_partner():
"""Lista os items do Relatorio agrupando por tipo e com count decrescente"""
report_set = db.session.query(ServiceTicket.id_partner, func.count(ServiceTicket.id).label("Total")).filter(ServiceTicket.id_partner != 0).\
group_by(Se... | 9ba75f65d0b2b87492f0a8f62db1e54f5aecf9c0 | 80,031 |
def __dive(state_machine, state_index, character_n, passed_state_list, CharacterToCount):
"""Once the distance to the acceptance state is determined, we store it in a cache database.
Note, that the distance is only stored after all possible pathes starting from the state
have been investigated. Note a... | cb7123f48279661f7f4721a5c2c9a106eb03ec70 | 80,032 |
import colorsys
def colorPalette(path, view, max_number_of_colors, hue_separation, sq, vq, space):
""" Generates a color palette for an image.
Args:
path (str): Path to the image.
view (bool): Choice to view the color palette.
max_number_of_colors (int): The maximum number of colors ... | 655609f7a6e6622eb2ae88165959022a47c5b40b | 80,033 |
import textwrap
def wrap_string(data, width=40, indent=32, indentAll=False, followingHeader=None):
"""
Print a option description message in a nicely
wrapped and formatted paragraph.
followingHeader -> text that also goes on the first line
"""
data = str(data)
if len(data) > width:
... | 4e983e4116058da1fa263e65aa3516a275d89001 | 80,034 |
def initial(x, idx):
"""
Get first value of series.
"""
if idx is None:
return x.iloc[0]
return x.iloc[idx.start or 0] | 28d364329af3f579868807773efb8a074e2c3cb5 | 80,035 |
def _potential_sadpt(evals, ethresh=0.3):
""" Determine points on a 1D-grid that could correspond to
a saddle point
"""
# Determine the idxs for all of the local extrema
loc_max, loc_min = _local_extrema(evals)
# Find min1-max-min2 triplets for each local maxima
final_idx = len(evals) -... | 5b8e63ec7377f4f3d1a139c79614a9193c0b9dfd | 80,036 |
def zeros_like(t: Tensor):
"""
Return zero-tensor with the same shape as the input tensor.
## Parameters
t: `Tensor` - input parameter
## Example usage
```python
from beacon.tensor import Tensor
from beacon.tensor import functinos as fn
t = Tensor([1, 2, 3])
x = fn.zeros_like(t... | a26832f09dac69497efe2a89bc1544e9318738ee | 80,037 |
import logging
import pickle
def load_cached_mode(s, l, m, n):
"""Read a KerrSpinSeq from disk.
Path is determined by :meth:`mode_pickle_path(s, l, m, n)`.
Parameters
----------
s: int
Spin-weight of field of interest.
l: int
Multipole number of mode. l >= angular.l_min(s, m)
... | 57d20a6d878df556c58f64a913cfb50af56f4286 | 80,038 |
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import LSTM
from tensorflow.keras.constraints import NonNeg
def create_lstm(train_shape: tuple, depth: int=1,
n_nodes: int=10, loss='mse', compilation_kwargs={}):
"""
Helper fu... | 708f5d907cf28e31c283d3f2fe6d4b4f722c59e3 | 80,039 |
def _quote(filename, protect = "="):
"""Quote the filename, by escaping = by \\= and \\ by \\"""
return filename.replace("\\", "\\\\").replace(protect, "\\" + protect) | 649d27f261ce37601ab432699885fb346df23931 | 80,040 |
import six
def create_hkl_group(py_obj, h_group, call_id=0):
""" Create a new group within the hickle file
Args:
h_group (h5.File.group): group to dump data into.
call_id (int): index to identify object's relative location in the iterable.
"""
h_subgroup = h_group.create_group('data_... | eb0b79503dbfb224b65e5080df14978dd6051329 | 80,041 |
def precompute_size_scattering(J, Q, max_order=2, detail=False):
"""Get size of the scattering transform
The number of scattering coefficients depends on the filter
configuration and so can be calculated using a few of the scattering
transform parameters.
Parameters
----------
J : int
... | 9549e35605943416323e63369535e88643df1e5c | 80,042 |
def _get_pole(ds):
"""returns the first pole we find in the dataset"""
pol_names = ["rotated_latitude_longitude", "rotated_pole"]
for pol in pol_names:
if pol in ds:
return ds[pol]
return None | c9969287a87c1e0c43aee02c407f5ee06fac9169 | 80,043 |
import torch
def _conjugate_gradient(f_Ax, b, cg_iters, residual_tol=1e-10):
"""Use Conjugate Gradient iteration to solve Ax = b. Demmel p 312.
Args:
f_Ax (callable): A function to compute Hessian vector product.
b (torch.Tensor): Right hand side of the equation to solve.
cg_iters (in... | ab8aa89ae15bef9214dbecfcff2b587993d550f9 | 80,044 |
def _applyColormap(colormap,
values,
minVal=None,
maxVal=None,
clip=True):
"""
Converts an array (values) to a rgba array.
:param colormap: An Xsocs2DColormap instance
:param values: Values to convert to color values.
:param... | 16580a22eaa410b63622c7d38d2da47bb7bb2e9e | 80,045 |
def supplierMetafieldsUpdate(supplierId):
"""
Update supplier metafield mapping.
:param supplierId: The supplier id.
"""
supplierId = escape(supplierId)
supplier = None
if supplierId in thk.suppliers:
supplier = thk.suppliers[supplierId]
unsuccessful_count = 0
successful_co... | ab4f5b3200e7d2881af38e3ef39fb2501105c7bb | 80,046 |
def expectation(q, weights=None):
"""
the expectation (or expected value or first moment) refers, to the value of
a random variable one would "expect" to find if one could repeat the random
variable process an infinite number of times and take the average of the
values obtained.
Formally, the ex... | cdc12eb10f3aa8ddcd7008b702bc8dd8782b02e9 | 80,047 |
def get_repo_auth_string(user, password):
# type: (Text, Text) -> Text
"""
Return user:password only if user and password are valid
:param user: username
:param password:
:return: URL authentication string
"""
if not (user and password):
return ""
return ":".join(map(quote, (... | f61df0793c517325761299ab241960af3b076919 | 80,050 |
import time
import json
def sendemail(request):
"""
发邮件
:param request:
:return:
"""
data=''
if request.method=='GET':
#获取当前周
year_week= int(time.strftime("%W"))+1
#获取当前session id
try:
pid=request.session.get('id')
except:
dat... | db20b38acccc75d3138f96871abc286606d798cc | 80,051 |
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