content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import logging
def main():
"""Send test metric to AWS CloudWatch"""
logging.basicConfig(level=logging.DEBUG)
cloud_watch = create_cloud_watch(
'Test Namespace',
asynchronous=False,
buffered=False,
dummy=False,
dimensions={'By intent': 'Test'},
)
cloud_watch.... | 3b0e4b01a544b9e4edd7b3ffe32418651ea6a7e1 | 46,200 |
def pdf(X, m, S):
"""
Calculates the probability density function of a Gaussian distribution:
X is a numpy.ndarray of shape (n, d) containing the data points whose PDF
should be evaluated
m is a numpy.ndarray of shape (d,) containing the mean of the distribution
S is a numpy.ndarray of shape (d... | 56d53f34c3d58e359f0f19279f8db125aebe2e3f | 46,201 |
def find_correct_weight(program_weights, program, correction):
"""Return new weight for node."""
return program_weights[program] + correction | 994c25efef10fa37971372f444a879e816708830 | 46,202 |
from typing import Optional
def segment_mask(segment_ids: JTensor,
source_segment_ids: Optional[JTensor] = None,
dtype: jnp.dtype = jnp.float32) -> JTensor:
"""Computes (non-causal) segment mask.
Args:
segment_ids: a JTensor of shape [B, T], the segment that each token belon... | 3ea357746326b6a88c5017e1fe6d4b0141b69519 | 46,203 |
def handle_keys():
"""
This version use keypad (hence KP?). Not tested.
"""
global fov_recompute
global mouse_coord
keypress = False
for event in tdl.event.get():
if event.type == 'KEYDOWN':
user_input = event
keypress = True
if event.type == 'MOU... | 04be0066018da8d5ac52ceeeb83c357734bccbf1 | 46,204 |
def test_for(item, min_version=None, callback=extract_version):
"""Test to see if item is importable, and optionally check against a minimum
version.
If min_version is given, the default behavior is to check against the
`__version__` attribute of the item, but specifying `callback` allows you to
ex... | 3c6b8ffbff46914bc348494ab77295a6debd6d41 | 46,205 |
import ctypes
def errcheck_object(result, func, args):
"""Checks the return value of NormFileEnqueue and NormDataEnqueue"""
if result == ctypes.c_void_p.in_dll(libnorm, "NORM_OBJECT_INVALID"):
raise NormError(
"Error creating object from function '%s'" % func.__name__)
return resul... | 5d654f34937ae0784470ba6264afc9a5bfc8774b | 46,206 |
import argparse
def parseArgs():
"""
CLI inputs
"""
log.info('Parsing command-line arguments...')
parser = argparse.ArgumentParser(description='Explore enzyme-screening variability historically')
subparsers = parser.add_subparsers(help='Choose mode of operation')
plot_parser = subparsers.a... | 3d15a104adceed9543c97fac4ee0a42237b4f993 | 46,207 |
def encode(delta_str, n_vertices, base, m=False):
"""Encodes delta string as a big integer.
Args:
delta_str: A string with delta coordinates in reference to min_x and min_y, min_x and min_y also included
n_vertices: Number of vertices in the polygon
base
Returns:
A dict map... | 35353910c61610add5df138934caa2ad94c63daf | 46,208 |
def get_most_common_elements(iterator):
"""Returns a generator containing a descending list of most common elements."""
if not isinstance(iterator, list):
raise TypeError("iterator must be a list.")
grouped = [(key, len(list(group))) for key, group in groupby(sorted(iterator))]
return sorted(gr... | c259560a3ca8e8c2e8b0666a67f866a2a8c736c0 | 46,209 |
import starlette
def build_starlette_request(scope, serialized_body: bytes):
"""Build and return a Starlette Request from ASGI payload.
This function is intended to be used immediately before task invocation
happens.
"""
# Simulates receiving HTTP body from TCP socket. In reality, the body has
... | 76e7ed35ab1ecb8375696bcb474deeaec75a03dc | 46,210 |
from typing import Mapping
import os
def expand_environment_variables(config):
"""Expand environment variables in a nested config dictionary
This function will recursively search through any nested dictionaries
and/or lists.
Parameters
----------
config : dict, iterable, or str
Input... | 6990c5092ece4436e41e619f3c8f68dee066dbcd | 46,211 |
import yaml
def create_namespace_with_name_from_yaml(v1: CoreV1Api, name, yaml_manifest) -> str:
"""
Create a namespace with a specific name based on a yaml manifest.
:param v1: CoreV1Api
:param name: name
:param yaml_manifest: an absolute path to file
:return: str
"""
print(f"Create ... | 11f06eabefdf3b8ba9c4354345896fed076b98a8 | 46,212 |
def sd_generate_state(model, n_steps, n_targets, init_state, birth, death,
noise=True):
"""Generate synthetic data on target states
Provide with a model, number of steps to generate, number of targets,
initial state of each of the targets and the time of the birth and death
of eac... | 4b26ad19a565f5a105ca827f71aec22235a167b6 | 46,213 |
def value_of_ace(card_one, card_two):
"""Calculate the most advantageous value for the ace card.
:param card_one, card_two: str - card dealt. See below for values.
:return: int - either 1 or 11 value of the upcoming ace card.
1. 'J', 'Q', or 'K' (otherwise known as "face cards") = 10
2. 'A' (ace... | 90ff26e76c116fd1cb803b56362d28aec1d642e4 | 46,214 |
from typing import Dict
def autoapi_skip_member(app: Sphinx, what: str, name: str, obj: PythonPythonMapper, would_skip: bool, options: Dict):
"""Project specific skip function for AutoAPI."""
if '__init__' in name:
return False
return would_skip | 9ec70eeec97c3713ac10f2beb27a63b96ecadb3f | 46,215 |
async def post_settings(update: AdvancedSettingRequest) -> AdvancedSettingsResponse:
"""Update advanced setting (feature flag)"""
try:
await advanced_settings.set_adv_setting(update.id, update.value)
except ValueError as e:
raise LegacyErrorResponse(message=str(e)).as_error(status.HTTP_400_B... | ff558558089ccbdd9e5c94d0a2be5558fbcfe672 | 46,216 |
def safe_log10(data):
""" A safe function for LOG10 in cases of too small values (close or equal to 0 ) """
prob_tmp = np.where(data > 1.0e-10, data, 1.0e-10)
result = np.where(data > 1.0e-10, np.log10(prob_tmp), -10)
return result | 861030069dad485188d3b23750e6395b11ff4ff2 | 46,217 |
def offset(point, direction, distance=1):
"""Offsets a point in a given direction some distance,
E.g. (0, 0) offset 'R' by 2 => (2, 0)
Args:
point (Point): the point to use for the offset point
direction (str): a valid direction ('U', 'R', 'D' or 'L')
distance (Optional[int]): the d... | 3998cbb0bf2f4af3930677fd991967404a1c173d | 46,218 |
def property_entropy(col, sim_matrix, bg_distr, seq_weights, gap_penalty=1):
"""Calculate the entropy of a column col relative to a partition of the
amino acids. Similar to Mirny '99. sim_matrix and bg_distr are ignored, but
could be used to define the sets. """
# Mirny and Shakn. '99
property_pa... | af8e4ded39ec68f7d9c282b327d8ed3245d70bb8 | 46,219 |
from re import T
def set_p_to_zero(pvect, i):
""" Provided utility function: given a symbolic vector of
probabilities and an index 'i', set the probability of the
i-th element to 0 and renormalize the probabilities so they
sum to 1.
"""
new_pvect = T.set_subtensor(pvect[i], 0.)
new_pvect =... | da7287606ed7e62c1c30adc165b74c6794da7c2b | 46,220 |
import requests
def get_cards(session: requests.sessions.Session, dni: str) -> list:
"""Returns cards list and details using the session provided."""
endpoint = GET_CARDS_ENDPOINT
data = {
"dni": dni,
}
json_response = session_post(session, endpoint, data)
card_list = json_response["re... | f96d24149c481228e4edb39c6dbf633828adea8c | 46,221 |
def define_systems(cube, verbose=True, MinNSpax=0, return_first=False,
return_second=False):
"""
Args:
cube:
verbose:
MinNSpax:
Returns:
"""
#!..make sure that undefined variance pixels that are defined in the datacube have a dummy high value
#WHER... | 41c4f99ae7b5ceba95f9eabf8fa9bc7e2190ee72 | 46,222 |
def configure_i18n(app):
""" ๅฝ้
ๅๆฏๆ. """
babel = Babel(app)
@babel.localeselector
def get_locale():
if has_request_context() and request:
# Request a locale and save to session
rl = request.args.get('_locale', None)
if rl:
accept_languages = ap... | a3fadcb4ef107e56bfd630ef0182115b7f9348b1 | 46,223 |
from datetime import datetime
def process_articles_results(articles_results_list):
"""
Function that process the list of article from the request.
"""
articles_results = []
for individual_article in articles_results_list:
title = individual_article.get('title')
description = indivi... | 0af29222fd77e742a1f59049877f2892fb57c6c0 | 46,224 |
import networkx
import itertools
import random
def _compute_diagram_component(Primes, Update, Subspaces, EdgeData, Silent):
"""
Also computes the commitment diagram but without removing out-DAGs or considering connected components separately.
Not meant for general use. Use compute_diagram(..) instead.
... | 1d6a5c979bc40bfc8363e8dfc3d69df575fbd1a8 | 46,225 |
def translate_english_to_chinese(target_str):
""" translate English to Chinese
Args:
target_str (str): target string
"""
translator = Translator(to_lang="chinese")
result = translator.translate(target_str)
return result | c6d78feff9d6c18b8966160775bb8ff4f2900ad2 | 46,226 |
def div(a,b):
"""Elementwise division with another vector, or with a scalar."""
if hasattr(b,'__iter__'):
if len(a)!=len(b):
raise RuntimeError('Vector dimensions not equal')
return [ai/bi for ai,bi in zip(a,b)]
else:
return [ai/b for ai in a] | c12511e47a4366efc8d248b7abfac2eea02644c5 | 46,227 |
def part2(grid):
"""
A basin is all locations that eventually flow downward to a single low point.
Therefore, every low point has a basin
Locations of height 9 do not count as being in any basin
All other locations will always be part of exactly one basin.
The size of a basin is the number of lo... | 7876ab48d5290654919f396b04b5146310d53b37 | 46,228 |
import re
def normalize_twitter_hashtag(text):
"""hashtagใๅ
ฑ้ใฎๆๅญๅใซ็ฝฎใๆใใ๏ผๅซใใงใใใใจใ่กจใใใ๏ผ"""
return re.sub(r"#\w+", "#hashtag", text) | bccff4f413732b5d401e5dd362b299998f707f1c | 46,229 |
def get_market_price_change_by_ticker(fromdate: str, todate: str, market: str="KOSPI", adjusted: bool=True) -> DataFrame:
"""์
๋ ฅ๋ ๊ธฐ๊ฐ๋์์ ์ ์ข
๋ชฉ ์์ต๋ฅ ๋ฐํ
Args:
fromdate (str ): ์กฐํ ์์ ์ผ์ (YYYYMMDD)
todate (str ): ์กฐํ ์ข
๋ฃ ์ผ์ (YYYYMMDD)
market (str , optional): ์กฐํ ์์ฅ (KOSPI/... | 0bb2775baef9436c19a8edbbd6f72aea212ca7a1 | 46,230 |
from typing import Optional
def deserialize_environment_from_cluster(cluster: Cluster,
path: Optional[
str] = None) -> Environment: # noqa, pylint: disable=line-too-long,bad-whitespace
"""Loads the environment from remote file.... | 6bc133c4ab5761320fbabd5c01b1aa4fe6a8e408 | 46,231 |
import scipy.signal as sig
def filter(data, low=300, high=6000, rate=30000):
""" Filter the data with a 3-pole Butterworth bandpass filter.
This is used to remove LFP from the signal. Also reduces noise due
to the decreased bandwidth. You will typically filter the raw data,
then extract... | 59801cbd04878a6a5049262c283e4d18b042a53d | 46,232 |
def load_config(filepath: str) -> ConfigFile:
"""Load configuration
Arguments:
filepath {str}
Returns:
{ConfigFile} -- query parameters
"""
config = ConfigFile.from_filename(filepath)
validate(config.content, config.version)
return config | 328907c370308369436e7ff55cd0a11ee5c55572 | 46,233 |
def szudzik_pair(pairs: np.ndarray) -> np.ndarray:
"""
Numpy implementation of a pairing function by Matthew Szudzik
Args:
pairs (np.ndarray): n x 2 integer array of pairs.
Returns:
hash_list (np.ndarray): n x 1 integer array of hashes.
"""
xy = np.array(pairs)
x = xy[..., ... | 5eaa4f9c8fd62f0409bf7e01e2609220c6f336cf | 46,234 |
def relu(x):
"""
Compute the relu of x
Arguments:
x -- A scalar or numpy array of any size.
Return:
s -- relu(x)
"""
s = np.maximum(0,x)
return s | 9531d5cc64e4721d25482e0f5f3257d2255e2a5b | 46,235 |
import os
def SearchForExecutableOnPath(executable, path=None):
"""Tries to find all 'executable' in the directories listed in the PATH.
This is mostly copied from distutils.spawn.find_executable() but with a
few differences. It does not check the current directory for the
executable. We only want to find ... | a21e97d3f1d90e11a594f5d712a236cf362e5aa8 | 46,236 |
import re
import requests
def get_enumeration_sparql(rq, v, endpoint, auth=None):
"""
Returns a list of enumerated values for variable 'v' in query 'rq'
"""
glogger.info('Retrieving enumeration for variable {}'.format(v))
vcodes = []
# tpattern_matcher = re.compile(".*(FROM\s+)?(?P<gnames>.*)\... | bfe59b7131ab74cf230e92ce6f2f609d7c0a76cd | 46,237 |
def get_instance_id(finding):
"""
Given a finding, go find and return the corresponding AWS Instance ID
:param finding:
:return:
"""
for kv in finding['attributes']:
if kv['key'] == 'INSTANCE_ID':
return kv['value']
return None | f4f6826dc02664b95ca8fdc91d89a6429192b871 | 46,238 |
from typing import Optional
def get_winning(process_id: int) -> Optional[list[Version]]:
"""Get a dict of the winning process versions per customer category.
Format of dict:
[{
'customer_category': str,
'winning_version': Version.A or Version.B
}]
:param process_id: specify proces... | 322299b7e28ca5429695d5b310b269853279f09e | 46,239 |
def BackwardFoldScaleAxis():
"""Backward fold axis scaling into weights of conv2d/dense.
Returns
-------
ret : tvm.relay.Pass
The registered pass to backward fold expressions.
Note
----
It is recommended to call backward_fold_scale_axis
before using forward_fold_scale_axis as b... | dc9bb99fa02920a643c8fa59d4e08c29e4a3826f | 46,240 |
def refresh(request):
"""Endpoint that'll use the database information to update running
process"""
ips_from_database = [x.ip for x in Machine.objects.all()]
database_machines_found = LocalNetworkScanner().refresh(ips_from_database, PORTS)
# if machine in database found on netowkr
ips_from_fou... | ed0c28a1c02525c7396ee04cb9d92e7a10f1a349 | 46,241 |
def triple(subject, relation, obj):
"""Builds a simple triple in PyParsing that has a ``subject relation object`` format"""
return And([Group(subject)(SUBJECT), relation(RELATION), Group(obj)(OBJECT)]) | b4c3a1bf4192fbf7a5c0c155551633cd7eb34678 | 46,242 |
def get_article_sentiment(article):
"""
Extracts sentiment analysis for article.
@param article: article dictionary (retrieved from the Data Lake)
@returns: (article_level_polarity, article_level_subjectivity)
"""
if language_dict[article['media']] == 'DE':
blob = TextBlobDE(article['tex... | d07fba0a706571d6e3f22793e99f3ae5890c995c | 46,243 |
def frame_to_yaml_safe(frame):
"""
Convert a pandas DataFrame to a dictionary that will survive
YAML serialization and re-conversion back to a DataFrame.
Parameters
----------
frame : pandas.DataFrame
Returns
-------
safe : dict
"""
return {col: series_to_yaml_safe(series)... | f33f0ca3b0c4fe689639a99b2f4bf44fc06e9973 | 46,244 |
import sys
def hgcmd():
"""Return the command used to execute current hg
This is different from hgexecutable() because on Windows we want
to avoid things opening new shell windows like batch files, so we
get either the python call or current executable.
"""
if mainfrozen():
if getattr... | a3a4a5356f85467156975e9b74d0805ab83cb8fb | 46,245 |
def coach_or_competitor(username):
"""converts a string to bytes
Args:
username: the user whose should be checked
Returns:
renders the competiotr template if user is comeptitor or the coach one if coach
"""
if is_coach(username):
print "This user is a coach"
return... | 98750b1cb80ee59c2481672350867b429e660746 | 46,246 |
def taint_name(rawtxt):
"""check the interface arguments"""
tainted_input = str(rawtxt).lower()
for test_username in get_user_list():
if tainted_input in test_username:
return test_username
return None | 4407508960ddfcdd267ab427227db0d009183221 | 46,247 |
def cdlsticksandwich(opn, high, low, close):
"""Stick Sandwich๏ผ
A stick sandwich is a technical trading pattern in which three candlesticks form what appears
to resemble a sandwich on a trader's screen. Stick sandwiches will have the middle candlestick
oppositely colored of the candlesticks on either s... | 192f85c1de98f4095fad9a5d3a1cbc2d7df53e49 | 46,248 |
def sample_bounded_multicoal_tree(stree, n, T, leaf_counts=None, namefunc=None,
sroot=None, sleaves=None, stimes=None,
gene_counts=None):
"""
Returns a gene tree from a bounded multi-species coalescence process
stree -- species tree
... | b5cc1bd53d86ef588ab36ebe0ffc54ed7e7e5e2b | 46,249 |
def collect_inventory_license_expression(location, scancode=False):
"""
Read the inventory file at location and return a list of ABOUT objects without
validation. The purpose of this is to speed up the process for `gen_license` command.
"""
abouts = []
if scancode:
inventory = gen.load_... | cb2020b2e89aa2294d46fe890d846548e1f88b32 | 46,250 |
def node_hist_fig(
node_color_distribution,
title="Graph Node Distribution",
width=400,
height=300,
top=60,
left=25,
bottom=60,
right=25,
bgcolor="rgb(240,240,240)",
y_gridcolor="white",
):
"""Define the plotly plot representing the node histogram
Parameters
--------... | 35ad64446612a98db6df49d364679d0a890eca1e | 46,251 |
def analytic_solution_modes(dx, p, nx, ny, x, y, c, t, n):
"""
Analytic solution for acoustic modes in 2D rectangular domains.
:param dx spatial step after discretization, scalar (m).
:param p numerical acoustic pressure used for the sizes, 2D-array (Pa).
:param nx mode number (... | b2b69cb4bb8b4a827cbb8818750a9f86e0c33773 | 46,252 |
from typing import Dict
def encode_images(format_dict: Dict) -> Dict[str, str]:
"""b64-encodes images in a displaypub format dict
Perhaps this should be handled in json_clean itself?
Parameters
----------
format_dict : dict
A dictionary of display data keyed by mime-type
Returns
... | c1dd645767d272a257cdd257d9854c2abad82353 | 46,253 |
import os
def initialise_fleet_data(fleet_file_path=None, reset=False):
"""
Uses the provided file path to load the fleet file csv file.
If no fleet file is found we return false.
Reset=True Remove all records and replace with this file.
Reset=False Add these fleet entries to the fleet table.
... | 9c961014ff8a25bc5d9e5c3f9fbd9b8244b179b2 | 46,254 |
def read_catl(path_to_file):
"""
Reads survey catalog from file
Parameters
----------
path_to_file: `string`
Path to survey catalog file
survey: `string`
Name of survey
Returns
---------
catl: `pandas.DataFrame`
Survey catalog with grpcz, abs rmag and stell... | 6013689b4d6f8558dba11cac5ece8d41bd38da8c | 46,255 |
def deconv(in_planes, out_planes, upscale_factor=2):
"""2d deconv"""
kernel_size, stride, opad = get_deconv_params(upscale_factor)
# print("DECONV", kernel_size, stride, opad)
return nn.ConvTranspose2d(in_planes, out_planes,
kernel_size=kernel_size,
... | 7b1f32915aee14b64564c92e20cb372935b3c759 | 46,256 |
import types
def OR(r1, r2):
"""Or/Union
Equates to union (both relations have same heading)
"""
if r1.heading() != r2.heading():
raise RelationInvalidOperationException(r1, "OR can only handle same reltypes so far: %s" % str(r2._heading))
#assert r1._heading == r2._heading, "OR can onl... | 2a430a721904382ea313609916199a3d63f5fdf2 | 46,257 |
from cntk.cntk_py import bernoulli_random_like
def bernoulli_like(x, mean=0.5, seed=auto_select, name=''):
"""bernoulli_like(x, mean=0.5, seed=auto_select, name='')
Generates samples from the Bernoulli distribution with success probability `mean`.
Args:
x: cntk variable (input, output, parameter,... | 943804bcb7725533242fa674c7357b9b56cc0655 | 46,258 |
def dVdc_calc(Vdc,Ppv,S,C):
"""Calculate derivative of Vdc"""
dVdc = (Ppv - S.real)/(Vdc*C)
return dVdc | 59d2708726e078efb74efce0bac2e397ba846d89 | 46,259 |
def percentile_spectrogram(spg, f_axis, rank_freqs=(8., 12.), pct=(0, 25, 50, 75), sum_log_power=True, show=True):
""" Compute percentile power spectra using the spectrogram, ranked by power within
a specific band. Essentially a different way of visualizing correlation between freqs.
Parameters
-------... | 44154d001479b82b14d4b9e794b56f49500ec4bf | 46,260 |
import math
def _get_cold_progression(age, rng, carefulness, preexisting_conditions, really_sick, extremely_sick):
"""
[summary]
Args:
age ([type]): [description]
rng ([type]): [description]
carefulness ([type]): [description]
preexisting_conditions ([type]): [description]... | 6fad1e52bddba28ca4045ed79e8838441ec32483 | 46,261 |
def project_to_image_space(anchors, stereo_calib_p2, image_shape):
"""
Projects 3D anchors into image space
Args:
anchors: list of anchors in anchor format N x [x, y, z,
dim_x, dim_y, dim_z]
stereo_calib_p2: stereo camera calibration p2 matrix
image_shape: dimensions of ... | 927267f0c4a75a5fdf5f0f52456c7e7ac48931f7 | 46,262 |
def define_model(quant_features, qual_features):
"""Define model
Args:
quant_features (list of str): corresponding to column names of training data
qual_features (list of str): corresponding to column names of training data
Returns:
model (sklearn obj)
"""
# transf... | 6cb132f0c7d58655afd8f3779712e62e8842bdef | 46,263 |
def check_order(df, topcol, basecol, raise_error=True):
"""
Check that all rows are either depth ordered or elevation_ordered.
Returns 'elevation' or 'depth'.
"""
assert basecol in df.columns, f'`basecol` {basecol} not present in {df.columns}'
if (df[topcol] > df[basecol]).all():
return... | 9b4e7b9938bb2fe14ab99d5c111883a0f6d73337 | 46,264 |
import os
def environment(request):
"""
A JavaScript snippet that initializes the environment
"""
# Capture all REACT_APP_ variables into a dictionary for context
environment = {
k: v
for k, v in os.environ.items()
if k.startswith('REACT_APP_')
}
# Add Environment ... | 39969dfc161f5009c081aa200665f57c6e68a4fa | 46,265 |
import os
import pickle
def search(results_path, network_type, num_layers,
num_neurons, batch_size, num_epochs,
training_method, regularization):
"""Search relevant files.
based on input arguments and return a list of filename
Parameters
----------
results_path : string
... | db6f7d79fb9e4b8998f5eb6e39e82cd2db2222a9 | 46,266 |
async def list_keys(hub, ctx, name, resource_group, **kwargs):
"""
.. versionadded:: 2.0.0
Retrieve a Redis cache's access keys. This operation requires write permission to the cache resource.
:param name: The name of the Redis cache.
:param resource_group: The name of the resource group.
CL... | 410ee854ae90de02f1b41dc32eaccd74d202462e | 46,267 |
from typing import Tuple
def new_simple_controller_config(
config: dict = None,
options: dict = None,
config_from_file=False,
serial_number="1111",
devices: Tuple[pv.VeraDevice, ...] = (),
scenes: Tuple[pv.VeraScene, ...] = (),
setup_callback: SetupCallback = None,
) -> ControllerConfig:
... | 8353cc001d7527afeb475e7b293812df7adf26e9 | 46,268 |
import torch
def online_mean_and_std(loader):
"""Compute the mean and sd in an online fashion
Var[x] = E[X^2] - E^2[X]
"""
cnt = 0
fst_moment = torch.empty(3)
snd_moment = torch.empty(3)
for x, y in loader:
b, c, h, w = x.shape
nb_pixels = b * h * w
sum_ = to... | 25479de7b88385d0714e3bf26ce6cbb151bf04f1 | 46,269 |
def GetDevice(serial=None):
"""Returns and ADBDevice given its serial.
The first connected device is returned if serial is None.
"""
devices = [d for d in ListDevices() if not serial or serial == d.serial]
return devices[0] if devices else None | ccf6451aa48b98efba03be4fa4438920b0fc5374 | 46,270 |
def api_demo_data_project(): # noqa: F401
"""Get info on the article"""
subset = request.args.get('subset', None)
if subset == "plugin":
result_datasets = get_dataset_metadata(exclude="builtin")
elif subset == "test":
result_datasets = get_dataset_metadata(include="builtin")
else:... | ca63c2803d9e0720cde7142eef8074bbef3eec40 | 46,271 |
import argparse
def parse_args():
"""set and check parameters."""
parser = argparse.ArgumentParser()
parser.add_argument("--result_path", type=str, default="", help="root path of predicted images")
args_opt = parser.parse_args()
return args_opt | 9d417966f4ec71f9e25f16c88a8178dc519686b8 | 46,272 |
def nonmax_supression(x):
"""Nonmaximum suppression finds crests of a signal.
All other non-maxima found from thresholding are suppressed.
Args:
x (1D numpy array): a signal which has been thresholded to only
contain maximum peaks.
Returns:
1D numpy array: an array indexes ... | cee150df2fb53dc8ad2fd1a0949dcf2e81608588 | 46,273 |
def pyth_backward_induction(num_periods, max_states_period, periods_draws_emax,
num_draws_emax, states_number_period, periods_payoffs_systematic,
edu_max, edu_start, mapping_state_idx, states_all, delta, is_debug,
is_interpolated, num_points_interp, shocks_cholesky):
""" Backward induction p... | 1ce52bb3059dfa61e2a6b04bb84716ccdecf1c07 | 46,274 |
def ipv4_subnet_details(addr, mask):
"""
Function that prints the subnet related details- Network, Broadcast, Host IP range and number of host addresses
:param addr: IP address
:param mask: subnet mask
:return: result dictionary containing the details
"""
network_address = []
broadcast_a... | 7d872a63b9a0968eabbe9af7ccfbfda311346bc8 | 46,275 |
def _get_sdk_name(platform):
"""Returns the SDK name for the provided platform.
Args:
platform: The `apple_platform` value describing the target platform.
Returns:
A `string` value representing the SDK name.
"""
return platform.name_in_plist.lower() | 0bc7f446472f44e52ea0b11cda7397e48848f0ef | 46,276 |
def myplus(a, b=0):
"""
Parameters
----------
a : float
the first number
b : float
the second number
defaults to zero
Returns
-------
a + b
"""
return a + b | c9efbff1babaae75c51401f56d830e8b7a543286 | 46,277 |
def read_data_from_fp_numpy(fp):
"""
Read the data from a single Silixa xml file. Using a simple approach
Parameters
----------
fp : file, str, or pathlib.Path
File path
Returns
-------
data : ndarray
The data of the file as numpy array of shape (nx, ncols)
Notes
... | 5b06e049df52abd262add9e1f449a1317df2d67e | 46,278 |
import tqdm
def schedule_jobs(
fns, concurrency=DEFAULT_THREADS,
progress=None, total=None, green=False
):
"""
Given a list of functions, execute them concurrently until
all complete.
fns: iterable of functions
concurrency: number of threads
progress: Falsey (no progress), String: Progress + ... | b4ae40ba37709f7f323b9dcf6bfa7ffce174fa9e | 46,279 |
def Hamming_bit_decoder(N,kind='bit',read=True,name='decoder'):
"""Hamming Gate resistant to bit-fips"""
circ=HammingCircuit(N, ancillas=N)
if kind=='phase':
circ.h([*range(2**N)])
circ.append(syndrome(N),[*range(2**N+N)])
circ.append(apply_syndrome(N),[*range(2**N+N)])
if read==True: ci... | 9b9e44d1708c57b7c218fe4b5f1e66928942ab30 | 46,280 |
import re
def _does_string_pass_simple_jndi_regex(input_string: str) -> bool:
"""Returns True/False if string contains at least one JNDI match, based on a simple regex"""
result = re.search(SIMPLE_JNDI_REGEX_PATTERN, input_string)
if result:
logger.debug(f"String passes simple JNDI regex: `{input_... | 35749a404027fb8aca9006956a8421646f4f4f66 | 46,281 |
def KeycodeToDIK(keycode):
"""
Convert a (Tkinter) keycode to a DirectInput Key code
If not in table, return keycode as hex
"""
_res = f'0x{keycode:02x}'
for dik, entry in DirectInputKeyCodeTable.items():
if entry[1] == keycode:
_res = dik
break
return _res | 608931cae3f47b80b9048aa5532d0b6fb95a8719 | 46,282 |
import logging
def tts_request(announcement="Text to speech example announcement!") ->str:
"""Test function to check that the text to speech is working appropriately"""
engine = pyttsx3.init()
engine.say(announcement)
engine.runAndWait()
logging.info('tts test run')
return "Hello text-to-speec... | 24e6b9680dc8e6d3160995d690b9b16defbe52a0 | 46,283 |
from typing import List
import random
def roll_relationships(relationship_points: int, min_icons: int) -> List[IconRelationship]:
"""
:param relationship_points:
How many points are spent to relationship.
:param min_icons:
Minimum number of different icons to have a relationship to.
:... | d951fa6676c8db9bbf3213379aa824d83fd96a12 | 46,284 |
import re
def ALMAUVFITSTab(inUV, filename, outDisk, err, \
exclude=["AIPS HI", "AIPS AN", "AIPS FQ", "AIPS SL", "AIPS PL"], \
include=[], logfile=""):
"""
Write Tables on UV data as FITS file
Write Tables from a UV data set (but no data) as a FITAB format file
His... | 54ffa1a38b8ae37949b2e2ae9b92eea7ba9f7316 | 46,285 |
def create_children(input_node, node_holder, max_frag=0, smiles=None, log_file=None, recurse=True):
"""
Create a series of edges from an input molecule. Iteratively
:param input_node:
:param max_frag: Max initial fragments (or no limit if 0)
:param smiles: A SMILES string, for log/diagnostics only.
... | fe36b1b81fc7668498f8da318a9864b31a272a70 | 46,286 |
import re
def typify(node):
"""Convert the input into the appropriate
type of ExpressionBase-derived Node. Will
apply pattern matching to determine if a
passed string looks like a numerical constant
or if the input is a numerical constant, return
the appropriate node type.
Parameters
... | 4024effbe9176acc10cdf25ce398b6cb2826b8ba | 46,287 |
import pathlib
def file_exists(file_path):
""" Returns true if file exists, false if it doesnt """
file = pathlib.Path(file_path)
return file.is_file() | d8219f71cf891d2d4e9c95670bd90b957becfdc5 | 46,288 |
import hashlib
import json
def hasher(obj):
"""Returns non-cryptographic hash of a JSON-serializable object."""
h = hashlib.md5(json.dumps(obj).encode())
return h.hexdigest() | 967ba4a1513bbe4a191900458dfce7a1001a8125 | 46,289 |
def long_word_pct(df):
"""
Get percentage of long words.
Long words are defined as having more than 8 chars.
Needs features:
Words
Adds features:
Long_word_percent: percentage of long words
:param: the dataframe with the dataset
:returns: the dataframe with the added f... | 2d80ea6e93f70ac2d5d68d472a75c0a1b13d6dee | 46,290 |
def check_answer(question_id, answers_list):
"""
Check answers for question.
Convert answers to boolean values for comparing with correct answers.
Answer wil get point if correct, not empty and all correct choices was chosen.
@param question_id: Question object id --> int
@param answers_list: ... | a092646d38e608f88b3191368dcf23c5770323e6 | 46,291 |
def _to_float(expr):
"""Converts a sympy expression to a Python float
The given expression must be a sympy ``Number`` isinstance, or ValueError
will be raised.
"""
res = expr.evalf()
if isinstance(res, Number):
return float(res)
else:
raise ValueError(
'Expressi... | cb0a0fbca7410d4d32c003e29f86b946a84d69e6 | 46,292 |
def atom_count(gra, dummy=False, with_implicit=True):
""" count the number of atoms in this molecule
by default, this includes implicit hydrogens and excludes dummy atoms
"""
if not dummy:
gra = without_dummy_atoms(gra)
natms = len(atoms(gra))
if with_implicit:
atm_imp_hyd_vlc_d... | 66ff22f6ff7785200ecca8f20bc1247120bb565a | 46,293 |
import numpy
def isstarboard(ctx, scene, node1, node2):
""" Returns True if node1 is on the right of node2 based on a view matrix
calculated from the 'face' of node 2.
For node1 to be on the right of node2:
- node2 to must be considered to have a front face.
- the view transformed... | f4d545ce98ae032d3116b814e3470b5fc514659e | 46,294 |
import glob
def get_tls_path(opts, id_type, namespace, release):
"""Get path to the directory containing TLS materials for a node
Args:
opts (dict): Nephos options dict.
id_type (str): Type of ID we use.
namespace (str): Name of namespace.
release (str): Nam... | cf4c35163e5852109deed7aa7aa611b41b7a9e54 | 46,295 |
def _length_hint(obj):
"""Returns the length hint of an object."""
try:
return len(obj)
except TypeError:
try:
get_hint = type(obj).__length_hint__
except AttributeError:
return None
try:
hint = get_hint(obj)
except TypeError:
... | 267f6242b5e0c901c30ebaa01b2c39472d3ae07e | 46,296 |
def _root_sort_key(root):
"""
Allow root comparison when sorting.
Args:
root (str or re.Pattern): Root.
Returns:
str: Comparable root string.
"""
try:
return root.pattern
except AttributeError:
return root | 51a7e51b58cbdf8c3277844903950282a5368815 | 46,297 |
from medis.Telescope.coronagraph import apodization
def optics_propagate(empty_lamda, grid_size, PASSVALUE):
"""
#TODO pass complex datacube for photon phases
propagates instantaneous complex E-field through the optical system in loop over wavelength range
this function is called as a 'prescription'... | 0f286ceff8027564b553851412c79ee056841507 | 46,298 |
def get_layer(keras_tensor):
"""
Returns the corresponding layer to a keras tensor.
"""
layer = keras_tensor._keras_history[0]
return layer | 6b3c950d9bf9c81895c4e7d4d436cd48359143bd | 46,299 |
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