content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def get_confusion_noise_robson19(f, t_obs=4 * u.yr):
"""Calculate the confusion noise using the model from Robson+19 Eq. 14 and Table 1
Also note that this fit is designed based on LISA sensitivity and so it is likely not sensible to apply
it to TianQin or other missions.
Parameters
----------
... | f58dcf51c1cb499d5bf04155c38d12263179b277 | 3,626,170 |
def default():
"""
Simply calls :func:`get` for the default endpoint.
"""
return get() | 45ed6b65d6d3191688d1f21556500dfe5bb14c48 | 3,626,171 |
import torch
def direct_1d(x, x_s, dx, dt, c, f):
"""Use the 1D Green's function to determine the wavefield at a given
location due to the given source.
"""
r = torch.abs(x - x_s).item()
t_shift = (r / c) / dt
u = dx * dt * c / 2 * torch.Tensor(np.cumsum(shift(f, t_shift)))
return u | 6eaf3754b95ad0202cbd6ef5bbdeda86acfa8ef9 | 3,626,172 |
def test_basic_state_transition(circuit):
"""Test the basic FSM function."""
class B123(edzed.FSM):
STATES = 'S1 S2 S3'.split()
EVENTS = [
('step', ['S1'], 'S2'),
['step', None, 'S3'], # default rule has lower precedence
('step', 'S3', 'S1') # single stat... | 47e9ad590e03515ac2c790a8e4b8fda071179c6e | 3,626,173 |
def home():
""" Home Page """
print("### Home Page Loaded ###")
return render_template('index.html', page="Home") | 21e47410da3113ecc56a3211a7f855c39a82cac7 | 3,626,174 |
import math
import torch
def read_alignment(
filename, format=None, *, max_taxa=math.inf, max_characters=math.inf
):
"""
Reads a single alignment file to a torch tensor of probabilites.
:param str filename: Name of input file.
:param str format: Optional input format, e.g. "nexus" or "fasta".
... | dc6d724fc9a8ece4ac9d6a06394d01310a9fa5bc | 3,626,176 |
def auto_load_processed(path):
"""Load processed BEEP .json files regardless of their class.
Enables loadfn capability for legacy BEEP files, since calling
loadfn on legacy files will return dictionaries instead of objects
or will outright fail.
Examples:
auto_load_processed("maccor_file_... | 322c501719e7c6d33b9509cb357651bec4254f55 | 3,626,177 |
def grating_linear_dispersion(
spec_inclusion_angle,
spec_focal_length,
spec_focal_length_tilt,
spec_grooves_per_mm,
spec_central_wavelength,
spec_order,
number_of_pixels,
pixel_width,
calibration_pixel,
):
"""
Parameters
----------
spec_inclusion_angle : float
... | 589044391cebea828a28927810e0c9ed15121456 | 3,626,178 |
from functools import reduce
def merge_columns_starting_positions(starting_positions, strict=True):
"""merging all lines starting positions"""
starting_positions = tuple(set(starting_positions))
# If only one is provided, or all equals, return it
if len(starting_positions) == 1:
return starti... | dc2830816ea00fc93ff4c68844500b4663acc743 | 3,626,179 |
def fin_FoM_optbd(n,d,bc,a,b,cini=None,imprecision=10**-2,bdlmax=100,alwaysbdlmax=False,lherm=True):
"""
Optimization of FoM over SLD MPO and also check of convergence in bond dimension. Function for finite size systems.
Parameters:
n: number of sites in TN
d: dimension of local Hilbert spa... | 32ccaf247614d8a5a1ec98fbc6b5bf1b616b93fd | 3,626,180 |
def create_cylinder(position, radius, height, orientation=(0,0,0), color=None, texture=None, mass=1, friction=0.1, client=0, isCollision=True):
"""
create cylinder in physical scene.
----------------------
position[3-element tuple]: Center position of the cylinder
orientation[3-element tuple]: Euler... | 413bdc1a5fcc74df2b2b04cecdfafcf1a88bd5fd | 3,626,181 |
def read_maze(file_name):
"""
Reads a maze stored in a text file and returns a 2d list containing the maze representation.
"""
try:
with open(file_name) as fh:
maze = [[char for char in line.strip("\n")] for line in fh]
num_cols_top_row = len(maze[0])
for row ... | 373e121a9dc827307fc6b56350f8b19247115651 | 3,626,182 |
def format(number):
"""Reformat the number to the standard presentation format."""
number = compact(number)
return (number[:-7] + '.' + number[-7:-4] + '.' +
number[-4:-1] + '-' + number[-1]) | c4bb448ee035c99bdbd3148be4bfef129209bd3c | 3,626,184 |
def user_register(**kwargs):
"""
swagger_from_file: Swagger/user/register.yml
"""
data = kwargs['data']
data['password'] = UserInfo.generate_hash(data['password'])
try:
obj = dynamic_modify(UserInfo(), data).create()
except Exception as e:
return response(ResponseEnum.INVALID... | c1340fca05349ce94143ca7c6f9c875c755b62c2 | 3,626,185 |
def _check(sample, data):
"""Get input sample for each chip bam file."""
if dd.get_chip_method(sample).lower() == "atac":
return [sample]
if dd.get_phenotype(sample) == "input":
return None
for origin in data:
if dd.get_batch(sample) in dd.get_batch(origin[0]) and dd.get_phenotyp... | 47c17783b852ece100e5f7c9d04e9a0f6bb69650 | 3,626,186 |
def step_update(x, P, a, b, sd):
"""
Apply 'observation' of form
a'x = b + N(0, sd^2)
to obtain new x, P, useful for building priors
:param x: n_k, n
:param P: n_k, n, n
:param a: n
:param b: n_k,
:param sd:
:return:
"""
PCt = P @ a # n_k, n
CPC_Q = PCt @ a + sd ** 2... | 91e52a0c2696e1561c558f761e8d318ca51e64b8 | 3,626,187 |
def validate_single_message(schema, input_file, verbose):
"""Validate single message stored in input file."""
processed = 0
valid = 0
invalid = 0
error = 0
try:
payload = load_json_from_file(input_file, verbose)
processed = 1
validate(schema, payload, verbose)
va... | 1ef1854c9873e4df9ff6c61303a1a8d9e35e98d4 | 3,626,188 |
def sns_certificate(*args):
""" Mock requests to retrieve the SNS signing certificate """
with open('tests/files/certificate.pem') as cert_file:
cert = cert_file.read()
return cert | 6d1198c7ea3c29be28dbecf6affe5c31ab51267a | 3,626,189 |
from scipy.spatial import cKDTree as KDTree
def kldivergence(x, y):
"""Compute the Kullback-Leibler divergence between two multivariate samples.
Parameters
----------
x : 2D array (n,d)
Samples from distribution P, which typically represents the true
distribution.
y : 2D array (m,d)
... | 55a512b6d720d065f32aa4a1877f10a8f9e03168 | 3,626,190 |
def get_municipio_near_geo(geo_points, max_meters=15e+3):
"""
Parameters
-----------
geo_points: list
List containing (latitude, longitude) coordinates.
max_meters: int, float
Max. number of meters from the geo_points to the municipio centroid
used to filter municipios.
... | 5c16ff7174eb65639ab130b0b796c770c3ef9a5e | 3,626,192 |
def replace_text_in_tables(page):
"""
Replace <p> tags with their contents because `html2text` has troubles with p
tags inside tables.
"""
tables = page.find('body').find_all('table')
has_colspan = False
for table in tables:
rows = table.find_all(["th", "tr"])
for row in rows... | eae9ba731b21bae36b018c80450d5060ed69fc35 | 3,626,193 |
def get_mirror_table (left, right, miraxis='x'):
"""
Return a mirror table between two object on chosen axis
:param str left: object to compare to slave
:param str right: object to compare to master
:param str miraxis: 'x'(default) chosen world axis on wich mirror is wanted
:return: list: return... | c35cb05282ac4486338916dfccf248e6531f30d2 | 3,626,194 |
def work_callback(ctx, param, value):
"""
Load correct work plugin and add it into the context
"""
plugin_name = plugin_callback(ctx, param, value)
plugin_cls = get_work_plugins()[plugin_name]
plugin = plugin_cls(config=ctx.obj["config"])
ctx.obj[param.name] = plugin
return plugin | 89c0a8f129c3ce450bb0d4e4534c482fea4f68c9 | 3,626,195 |
import numpy as np
import math
def wmh( flair, t1, t1seg, mmfromconvexhull = 12 ) :
"""
Outputs the WMH probability mask and a summary single measurement
Arguments
---------
flair : ANTsImage
input 3-D FLAIR brain image (not skull-stripped).
t1 : ANTsImage
input 3-D T1 brain image (not skull-st... | 70eba2400fde4bb8faa25b2ab85ce55a03ae3f2c | 3,626,196 |
def translate_delta(mat, dx, dy):
"""
Return matrix with elements translated by dx and dy, filling the would-be
empty spaces with 0. I feel this method may not be the most efficient.
"""
rows, cols = len(mat), len(mat[0])
# Filter out simple deltas
if (dx == 0 and dy == 0):
return m... | 38492c874bc7bbd59787f4b2d94c2ea0150e69f8 | 3,626,197 |
def upscale_x(
inputs,
scale=4,
scope='upscale_x'
):
"""mimic the tensorflow bilinear-upscaling for a fix ratio of x."""
with tf.variable_scope(scope):
size = tf.shape(inputs)
b = size[0]
h = size[1]
w = size[2]
c = size[3]
p_inputs = tf.concat((inputs, inputs[:, -1:, :, :]), ax... | f967d74db805d1aa04e96ef406caa56818df4080 | 3,626,198 |
import logging
import json
def audio_rttm_map(manifest):
"""
This function creates AUDIO_RTTM_MAP which is used by all diarization components to extract embeddings,
cluster and unify time stamps
input: manifest file that contains keys audio_filepath, rttm_filepath if exists, text, num_speakers if kno... | b7828393b5571c7b8ed67748ef9b188c00f90731 | 3,626,199 |
def extract_slices(img):
"""
Extract slices from images shapes
Parameters
-----------
imgs: list of n_sessions arrays of shape\
(n_voxels, n_timeframes)
Returns
--------
slices: list of slices
"""
slices = []
t_i = 0
for i in range(len(img)):
n_voxels, n... | 28376eb45e7efa19991879c9d6e4a615b6851a4c | 3,626,200 |
def _generate_meta():
"""
Generate Meta information for export
"""
d = {'root_url': request.url_root}
return d | 8f34c42183e12b36c5ae656e06d7b10b0f3d1715 | 3,626,201 |
def u2(vector):
"""
This function calculates the utility for agent 2.
:param vector: The reward vector.
:return: The utility for agent 2.
"""
utility = vector[0] * vector[1]
return utility | 93b9210db00ee9a3ddca4cd9b447a7348f63a659 | 3,626,202 |
from typing import Any
from typing import Type
from typing import Optional
from typing import TypeGuard
def assert_isinstance(
instance: Any, cls: Type[TYPE], message: Optional[str] = None
) -> TypeGuard[TYPE]:
"""
A TypeGuard function that is equivalent to `assert instance, cls, message`
that hides n... | c81390f0a409667ad1fef26e49cfb6623c8521ba | 3,626,203 |
def build_url(url):
"""Build the actual URL to use."""
f = furl(url)
return f.url | f5d2abdfc8bcb6b9d118d23c98bad371b3b7a3ed | 3,626,204 |
def create_input_file(recipe=None, input_file=None, recipe_input=None, file_name='my_test_file.txt', media_type='text/plain',
file_size=100, file_path=None, workspace=None, countries=None, is_deleted=False, data_type='',
last_modified=None, source_started=None, source_ended=N... | 7ed13eeac1edf5078fac8a1a9ab763fd2667e336 | 3,626,205 |
def mask_and_mean_loss(input_tensor, binary_tensor, axis=None):
"""
Mask a loss by using a tensor filled with 0 or 1 and average correctly.
:param input_tensor: A float tensor of shape [batch_size, ...] representing the loss/cross_entropy
:param binary_tensor: A float tensor of shape [batch_size, ...] ... | 099976441be4e50dbbd6a8fedb7a51f769c6b872 | 3,626,206 |
def counting_sort_integers(values, max_val=None, min_val=None, inplace=False):
"""
Sorts an array of integers using counting_sort.
Let n = len(values), k = max_val+1
"""
if len(values) == 0:
return values if inplace else []
#Runs in O(n) time if max_val is None or min_val is None
if... | d53b00b8753d8adc1782e5941b4b6dcce7c80ca3 | 3,626,207 |
def xfun(p,B,pv0,f):
"""
Steady state solution for x without CRISPR
"""
return f/(B*p-p/pv0) | 874d7d5a1d0d485aafa6f7298e1d214ca86ea90e | 3,626,209 |
from onnx.helper import make_node
def convert_npi_max(node, **kwargs):
"""Map MXNet's min operator attributes to onnx's ReduceMin operator
and return the created node.
"""
name, input_nodes, attrs = get_inputs(node, kwargs)
mx_axis = str(attrs.get("axis", 'None'))
axes = convert_string_to_lis... | feda0ad9c4a301581f3c97f615214b37b558d1d9 | 3,626,210 |
def pattern_matching(pattern, genome):
"""Find all occurrences of a pattern in a string.
Args:
pattern (str): pattern string to search in the genome string.
genome (str): search space for pattern.
Returns:
List, list of int, i.e. all starting positions in genome where pattern appea... | 86ae704586fbac937e044f41a8831f2669c4e7dc | 3,626,211 |
import glob
def findLblWithoutImg(pathI, pathII):
"""
:param pathI: a glob path. example: "D:/大块煤数据/大块煤第三次标注数据/images/*.jpg"
:param pathII: a glob path. example: "D:/大块煤数据/大块煤第三次标注数据/labels/*.txt"
:return: num of image which not has label
"""
num = 0
pathI = glob.glob(pathI)
pathII = g... | 30edbff244acb0014b54cf3c85d86a47d779d226 | 3,626,212 |
import math
def lcf_float(val1, val2, tolerance):
"""Finds lowest common floating point factor between two floating point numbers"""
i = 1.0
while True:
test = float(val1) / i
check = float(val2) / test
floor_check = math.floor(check)
compare = floor_check * test
if... | b4bef1a63984440f43a1b0aa9bf9805cb4bfd466 | 3,626,213 |
async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Unload a config entry."""
if await hass.config_entries.async_unload_platforms(entry, PLATFORMS):
hass.data[DOMAIN].pop(entry.entry_id)
return True
return False | 8f7e1a24098033294078d6bec2fcf768c080a398 | 3,626,214 |
def check_num_row(data):
"""
@param df: dataframe
@return: return 1 if checking condition is true
"""
return data.shape[0] > 10 | 0761c4d31bc3a14132d6c1547d03149bd10013c5 | 3,626,216 |
def blog_post_feed_richtext_filters(request, format, **kwargs):
"""
Blog posts feeds - maps format to the correct feed view.
"""
try:
return {"rss": PostsRSSRichtextFilters, "atom": PostsAtomRichtextFilters}[format](**kwargs)(request)
except KeyError:
raise Http404() | bb6798d1b2113d8d0205d5dc47b96b0fb6aae6b6 | 3,626,217 |
def _convert_text_to_logs_format(text: str) -> str:
"""Convert text into format that is suitable for logs.
Arguments:
text: text that should be formatted.
Returns:
Shape for logging in loguru.
"""
max_log_text_length = 50
start_text_index = 15
end_text_index = 5
return... | 4f7ff95a5cd74bdccd41559f58292cc9b1003ba2 | 3,626,218 |
def force_langston_contact_agent_agent(r_tot, d, n, v, t, mu, kappa, damping):
"""Frictional contact force between agent and agent (Helbing, 2000)."""
return mu * (r_tot - d) * n + kappa * (r_tot -d) * dot2d(v, t) * t + damping * dot2d(v, n) * n | b04500bf0ecc2c4e97803a3bca1b7f7bbc0aa435 | 3,626,219 |
def glossary():
"""Generates glossary data"""
data = []
for item in sorted(reference.ACRONYMS.items()):
data.append({
"type": "Acronym",
"code": item[1],
"definition": item[0]
})
for item in sorted(reference.ABBREVIATIONS.items()):
data.appen... | 7172c6f727ee1e9a6fe035d185f0e0e03537f65a | 3,626,220 |
import random
def generate_random_slug(length=40, prefix=None):
"""
This function is used, for example, to create Coupon code mechanically
when a customer pays for the subscriptions of an organization which
does not yet exist in the database.
"""
if prefix:
length = length - len(prefix... | add5e68d0ed6d3831993410afc5ec7900eb212c4 | 3,626,221 |
import re
def get_easy_variables(website_rules, url, settings):
"""Stuff that can be found without parsing the DOM -- its easy"""
website_variables = {}
website_variables["URL"] = {
'content': url.full_url,
'strength': 'high',
'type': 'attr'
}
website_variables["DOMAIN"] =... | 9bec73093c3408c0616269054ce511239b15f4cd | 3,626,222 |
def order_of_magnitude(x):
"""Determine the order of magnitude of the numeric input (`int`, `float`, :meth:`numpy.array` or :meth:`pandas.Series`).
Examples
--------
>>> order_of_magnitude(11)
array(1.)
>>> order_of_magnitude(234)
array(2.)
>>> order_of_magnitude(1)
array(0.)
>>... | f8a5a8f0dad2fc86c2cb00c4af6f9c970cd99fce | 3,626,223 |
def lines_of_words(S, W, text_words):
"""Convert index of first words to list of lines
Take the "S" that's computed by a line breaking algorithm and
converts it to a list of lines, where each line is a list of
words.
"""
assert sorted(S.keys()) == list(range(1, 1+max(S.keys()))), [
sort... | 07d3adfcf0e6cb292e30fd829ded2fafd80ebe50 | 3,626,224 |
def digits_to_num(L, reverse=False):
"""Returns a number from a list of digits, given by the lowest power of 10 to the highest, or
the other way around if `reverse` is True"""
digits = reversed(L) if reverse else L
n = 0
for i, d in enumerate(digits):
n += d * (10 ** i)
return n | 1648073d46411fd430afea4f40f7fa9f4567793c | 3,626,226 |
def dynamics(q, u, p):
"""
Returns state derivative qdot.
Takes current state q, motor input torque u, and disturbance torque p.
See <http://renaissance.ucsd.edu/courses/mae143c/MIPdynamics.pdf> (rederived with incline).
"""
# Angle of pendulum in incline frame
ang = q[2] - incline
# M... | 9d36bdb0218b15f91d6d49a489dd39cc2785becd | 3,626,227 |
def escape_and_join(args):
"""Creates a shell-escaped string from a list of arguments."""
escaped = []
for x in args:
if x.startswith("$"):
# This is a hack because a rule in //fpga/defs.bzl wants to pass
# $XCELIUM_PATH as an argument, and have the shell expand it correctly.... | 0b11fe4268ed3b2e6b7756faeaeace8dcfd248dd | 3,626,229 |
import torch
def mean_shift_smart_init(X, kappa, num_seeds=100, max_iters=10, metric='cosine'):
""" Runs mean shift with carefully selected seeds
@param X: a [n x d] torch.FloatTensor of d-dim unit vectors
@param dist_threshold: parameter for the von Mises-Fisher distribution
@param num_s... | a4661dbad7c415a75aa5ba06a2f1a69df5b79a97 | 3,626,230 |
def mergesort(*tables, **kwargs):
"""
Combine multiple input tables into one sorted output table. E.g.::
>>> import petl as etl
>>> table1 = [['foo', 'bar'],
... ['A', 9],
... ['C', 2],
... ['D', 10],
... ['A', 6],
... | 724fb395f77e680b0641d3f953d926e41a0fe7c9 | 3,626,231 |
def _normalizeGlifPointAttributesFormat2(element):
"""
- Follow same rules as Format 1, but allow an identifier attribute.
"""
attrs = _normalizeGlifPointAttributesFormat1(element)
identifier = element.attrib.get("identifier")
if identifier is not None:
attrs["identifier"] = identifier
... | 60e7411c84cf45c255116d12e56ef449ee2aac37 | 3,626,232 |
def fetch_account_balance(pubKey: str = REWARD_PUBLIC_KEY) -> float:
"""
Returns the balance of the given account available to be send
"""
try:
acc = server.accounts().account_id(pubKey).call()
except Exception as e:
print(f"Specified account ({pubKey}) does not exists:", e)
... | c1283b9d3e079a1168286ca6e5f4e73a22dca9f9 | 3,626,233 |
def identify_formation_channels(seeds, file):
"""Identify the formation channel that produced each seed. We consider 5
main channels: classic, only stable, single core CEE, double core CEE and
other. We define the channels as follows (the numbers are what is put in
the ``channels`` output):
Classic... | d245f08a6d3192ea56117f9e2a9440029ce60f66 | 3,626,234 |
def _read_stimtime_FSL(stimtime_files, n_C, n_S, scan_onoff):
""" Utility called by gen_design. It reads in one or more
stimulus timing file comforming to FSL style,
and return a list (size of [#run \\* #condition])
of dictionary including onsets, durations and weights of each event.
Pa... | d83c27a3e3f1b80c224ec4b93c514a82eced6964 | 3,626,235 |
import collections
def parse_map(map_file):
"""
Parse a given map file (compilation output).
"""
sections = [
"Preamble",
"Allocating common symbols",
"Discarded input sections",
"Memory Configuration",
"Linker script and memory map",
"OUTPUT",
... | 2aec206820540445e476cb4d4333e95e5b76d7e4 | 3,626,236 |
def parse_sge_script(local_script_path):
"""
Parse the SGE script
:returns: A dictionary of the options for constructing AiiDAJobFirework
"""
with open(local_script_path) as handle:
lines = handle.readlines()
options = {
'stdout_fname': '_scheduler-stdout.txt',
'stderr... | df130f5af9d46dd2803cf04b833500aabb276856 | 3,626,237 |
from typing import Union
from pathlib import Path
from typing import Tuple
from unittest.mock import Mock
import unittest
def run_using_a_configuration_file(
configuration_path: Union[Path, str], file_to_lint: str = __file__
) -> Tuple[Mock, Mock, Run]:
"""Simulate a run with a configuration without really la... | 0d66f10f0b8cbe176aeca6c3ec4fdd04e0bc6cfb | 3,626,238 |
import re
from pathlib import Path
def get_gromacs_version(gmx: str = "gmx") -> int:
""" Gets the GROMACS installed version and returns it as an int(3) for
versions older than 5.1.5 and an int(5) for 20XX versions filling the gaps
with '0' digits.
Args:
gmx (str): ('gmx') Path to the GROMACS ... | 0a1760ecd50ffb7fc0838e6eb7d0c82b10cb3c07 | 3,626,239 |
def StepToGeom_MakeConic2d_Convert(*args):
"""
:param SC:
:type SC: Handle_StepGeom_Conic &
:param CC:
:type CC: Handle_Geom2d_Conic &
:rtype: bool
"""
return _StepToGeom.StepToGeom_MakeConic2d_Convert(*args) | 96e7da2ba814bdc2123217fff24784978eabe476 | 3,626,240 |
def AllNames():
"""(read-only) Array of all Monitor Names"""
return get_string_array(lib.Monitors_Get_AllNames) | 86ae2263d6ded5a376da48288f40170801f32e5f | 3,626,241 |
def k2_mean(success_tag, ms_results):
""" Returns the expectation of k2, the rate constant for the
unimolecular step of a resting-set reaction. """
success_kcolls = np.ma.array(ms_results['kcoll'], mask=(ms_results['tags']!=success_tag))
success_t2s = np.ma.array(ms_results['times'], mask=(ms_results['tags']!=s... | b328bd479c81412a86a902d8c4899240b9ae5ad9 | 3,626,242 |
def json_network(user, raw=True, callback=None):
"""
callback=NAME wrap the object definition in a function call NAME(...)
?raw a raw JSON object is returned, instead of an object named
Delicious.posts
"""
url = 'http://del.icio.us/feeds/json/network/' +... | 3f0598180b0865ea1624c3cb1cae591022700475 | 3,626,243 |
def implode(space, w_arg1, w_arg2=None):
"""Join array elements with a string."""
if w_arg2 is None:
if w_arg1.tp != space.tp_array:
space.ec.warn("implode(): Argument must be an array")
return space.w_Null
else:
w_arr = w_arg1
string = ""
else... | 90e78c0f2266b3396606eec50cf5378b2079fba6 | 3,626,246 |
def fill_matrix(X: np.ndarray, mixture: GaussianMixture) -> np.ndarray:
"""Fills an incomplete matrix according to a mixture model
Args:
X: (n, d) array of incomplete data (incomplete entries =0)
mixture: a mixture of gaussians
Returns
np.ndarray: a (n, d) array with completed data... | 18318c0b781706966a787a2a0d53e52714d43628 | 3,626,247 |
import torch
import tqdm
def get_pseudo(t_model, unlabeled_dataset):
"""
params:
t_model: teacher model
unlabeled_dataset: unlabeled dataset
return:
pseudo_label: ndarray[N, C], N=len(dataloader), C for num of class, dim C is output of softmax
"""
t_model.eval()
device ... | fdb880925be00da5007b921ee8e8e0dbdb0caddc | 3,626,248 |
def CountDictCall(keyfunc):
""" Decorator for counting memoizer hits/misses while accessing
dictionary values with a key-generating function. Like
CountMethodCall above, it wraps the given method
fn and uses a CountDict object to keep track of the
caching statistics. The dict-key fun... | 537a7595eb9cd1752e80e2a4694ec694ef569440 | 3,626,250 |
def _group_map_list(_data, _f, *args, _keep=False, **kwargs):
"""List version of group_map"""
return list(
regcall(
group_map,
_data,
_f,
*args,
**kwargs,
_keep=_keep,
)
) | 7c28ddc689b896d96c31898c790e23da1c0ad302 | 3,626,252 |
def clean_zeros(a, b, M):
""" Remove all components with zeros weights in a and b
"""
M2 = M[a > 0, :][:, b > 0].copy() # copy force c style matrix (froemd)
a2 = a[a > 0]
b2 = b[b > 0]
return a2, b2, M2 | 3e2def6e88a7ac5a67b9849a9dcd2f5f5156fb00 | 3,626,253 |
def compare(gene, classes):
""" Compare the distribution of two or more groups and automatically selects
the proper statistical test
Args:
gene (string): feature to be compared.
classes (list of pandas dataframe): list of groups (classes) to compare.
Re... | 0aae0446b75be80d3b63eb1411599297bf5bba54 | 3,626,254 |
def get_powersph_errorbars(k, psph, params):
"""
Calculate the error bars on spherically-averaged P(k) (1-sigma uncertainty) as a function of k.
This is a convenience method, which calls the internal method.
Parameters
----------
k : 1D array
Values of k at which to calculate error bar... | 6ba2e75bbe7245e423cefe80addf313e8b868a98 | 3,626,255 |
from typing import List
def sum_poly_areas(lop: List[shapely.geometry.Polygon],) -> float:
"""
Returns a float representing the total area of all polygons
in 'lop', the list of polygons.
"""
sum_acc = 0
for poly in lop:
sum_acc += poly.area
return sum_acc | 643df866d4a6548af85811549dcf895d50e09fcc | 3,626,256 |
def build_importer_component_spec(
importer_base_name: str,
input_name: str,
input_type_schema: pipeline_spec_pb2.ArtifactTypeSchema,
) -> pipeline_spec_pb2.ComponentSpec:
"""Builds an importer component spec.
Args:
importer_base_name: The base name of the importer node.
dependent_task: The tas... | f3fc23129c4e68599032115c62405ed2bdadeca2 | 3,626,257 |
import types
def hpat_pandas_series_max(self, axis=None, skipna=None, level=None, numeric_only=None):
"""
Intel Scalable Dataframe Compiler User Guide
********************************************
Pandas API: pandas.Series.max
Limitations
-----------
Parameters ``axis``, ``level`` and ``n... | c5a88afb0baead19c950de46eb0694b467fb1bb7 | 3,626,258 |
def train_predictor(predictor,
train_data,
train_target,
hyperparameter,
metric='accuracy',
n_folds=5):
"""
Cross validation training in order to find best parameter.
:param predictor:
:param train_data:... | 8109d76d246388e30265da24f7ea64281777f146 | 3,626,259 |
from typing import Callable
def make_vector_laplace(bcs: Boundaries) -> Callable:
"""make a discretized vector laplace operator for a cylindrical grid
{DESCR_CYLINDRICAL_GRID}
Args:
bcs (:class:`~pde.grids.boundaries.axes.Boundaries`):
{ARG_BOUNDARIES_INSTANCE}
Returns:
... | dcb126a941fab660c0fae209df8959fbb9ed1e3c | 3,626,260 |
import hashlib
def extract_keys(key: bytes) -> str:
"""Derive a key1,key2, key3 from a password str and returns a hex tuple (key1, key2, key3) """
digest = hashlib.sha256(key).digest()
key1 = hexlify(digest)
key2 = hashlib.sha256(digest).hexdigest()
key3 = hashlib.sha256(hashlib.sha256(digest).dig... | 085c889c979949d92f6f887e1cddf4f3e2587041 | 3,626,261 |
def add_user(user):
""" Add a user in the database
return Boolean
"""
try:
with session_scope() as session:
u = User(**user)
session.add(u)
return True, None
except exc.IntegrityError as e:
return False, str(e) | 1dfb33feda4ec68d7e4518229334da137806621e | 3,626,262 |
def _port_speed_prices_table(port_speeds, prices=False):
"""Shows Server Port Speeds prices cost and capacity restriction.
:param [] port_speeds: List of Hardware Server Port Speeds.
:param prices: Create a price table or not
"""
if prices:
table = formatting.Table(['Key', 'Speed', 'Hourly'... | 50b437041d83606ccd547c56fa5898b6a38079a5 | 3,626,263 |
def conversion(pid, offset, sequences, directory, file_count):
"""
This function calls all functions required for the full latex to png conversion for a subset of the sequences.
It is meant to be called for a single process. The respective subset depends on the given offset.
:param pid: The identifier ... | a9cc2efbc0f99c240e59af336c08192ef06d2bb2 | 3,626,264 |
def conv_nested(image, kernel):
"""A naive implementation of convolution filter.
This is a naive implementation of convolution using 4 nested for-loops.
This function computes convolution of an image with a kernel and outputs
the result that has the same shape as the input image.
Args:
ima... | 92f88cd82370de680ea10ebe3e50355e2be6e1d1 | 3,626,265 |
import re
def get_cheque_code(cheque: str):
"""Get code"""
if (
re.search(r'BTC_CHANGE_BOT\?start=', cheque)
or not re.search(r'BTC_CHANGE_BOT\?start=', cheque)
and re.search(r'Chatex_bot\?start=', cheque)
):
return re.findall(r'c_\S+', cheque)[0]
elif re.se... | 97d0b3cadfb6010b48ed6fb148083060c50720ff | 3,626,266 |
def findKthLargest(nums, k):
"""
:type nums: List[int]
:type k: int
:rtype: int
"""
# sol 1
# nums.sort()
# return nums[-k]
# sol 2
# return select(nums, 0, len(nums)-1, k)
# sol 3
return search(nums,k) | af5af39c4f0634f57ad4f9c26b8022611bd2ee9e | 3,626,267 |
def check_round_change(fromBlock, toBlock):
"""Checks for round initilized txs between blockOld and block.
If an event exists, get the blocknumber of this tx and the round number
"""
round_filter = w3.eth.filter({
"fromBlock": fromBlock,
"toBlock": toBlock,
"address": ROUND_MANAGER_PROX... | b5e2033918dd22b5ecf59ca131a32bc7cbdde53f | 3,626,268 |
def dice_coef_loss(target, prediction, axis=(1,2,3), smooth=1.0):
"""
Sorenson Dice loss
Using -log(Dice) as the loss since it is better behaved.
Also, the log allows avoidance of the division which
can help prevent underflow when the numbers are very small.
"""
intersection = tf.reduce_sum(... | 4bf384be1e9fe2073f412a7682f89f18403ccd2c | 3,626,270 |
def option_names_not_in_cfg(cfg, options):
"""
Returns names of *options* not seen in the *cfg* dictionary, typically
parsed from an external configuration file.
Parameters
----------
cfg : dict
options : :py:class:`~enrich2.plugins.options.Options`
Returns
-------
`list`
... | 30f707d8420cef4d2021cf305e0065fe9649ea22 | 3,626,271 |
def fit_mgauss(x, y, x0, n, c=(-np.inf, np.inf), thresh=-1, ftol=1e-4, xtol=1e-4, scale=0, maxiter=100, verbose=False):
"""
Fit a symmetric multigauss to the provided 1-D data.
*Arguments*:
- x = x values of data to fit.
- y = y values of data to fit.
- x0 = the initial guess as a stacked (1... | 9b67725a9c61be0c8cc06cb7d5347f591109469f | 3,626,273 |
def list_files_with_extension(root_path, extension, full_path=True,
recursively=True):
"""List all files paths in a folder, filtered by a given suffix.
Parameters
----------
root_path : Path
Top level folder, start search here.
extension : str
Extension... | 5bd9d44573250c84ce7bcafb7c90b68fcd57d896 | 3,626,274 |
import torch
def get_power_online(signal: ComplexTensor) -> torch.Tensor:
"""Calculates power for `signal`
Args:
signal : Single frequency signal
with shape (F, C, T).
axis: reduce_mean axis
Returns:
Power with shape (F, )
"""
power = signal.real ** 2 + signal... | f7c1ad0dbdee60b7a0db14ea1d87fadeb8778f9e | 3,626,275 |
def transform(model, pretrained=False, gamma=0.9, mem=False):
"""Return the MomentumNet counterpart of the model
Parameters
----------
model : a torchvision model
The resnet one desires to turn into a momentumnet
pretrained : bool (default: False)
Whether using a pretrained resnet ... | 849c076b25ceb27ae17dbf9f2743c5b0cfe1c5be | 3,626,276 |
def getListArrayDim(self, ainput, dim=0):
"""
get the dimension of a list
returns -1 if it is no list at all, 0 if list is empty
and otherwise the dimensions of it
"""
if isinstance(ainput, (list, np.ndarray)):
if ainput == []:
return dim
dim = dim + 1
dim =... | c1c336b66f7a9412ed22877f1ac683c617f58280 | 3,626,277 |
def exp_two(arg1, arg2):
""" (float, float) -> float
Exponentiates two numbers (arg1 ** arg2)
Returns the exponent
"""
try:
return arg1 ** arg2
except TypeError:
return 'Unsupported operation: {0} ** {1} '.format(type(arg1), type(arg2)) | ec63d4d8d4e45590918a53ddc8654bc93bd4a435 | 3,626,278 |
def parse_problems(lines):
""" Given a list of lines, parses them and returns a list of problems. """
return [len(p) for p in lines] | 83747e57bddf24484633e38ce27c51c7c8fce971 | 3,626,280 |
def standard_lv(env_name, remove_q=True, static_feeds_new=None, clear_loads_sgen=False, clear_gen=True,
battery_locations=None, percent_battery_buses=0.5, batteries_on_leaf_nodes_only=True, init_soc=0.5,
energy_capacity=20.0, gen_locations=None, gen_p_max=0.0, gen_p_min=-50.0,
... | dbe1d0cf30cc6c677daae0c74016e9841ac1a323 | 3,626,282 |
from .authorize import oauth
from typing import Callable
from typing import Any
def oauth_require_read_schema_scope(f: 'Callable[..., Any]'):
"""(User以外の）メタデータを読むだけのScopeデコレータ.
:param Callable f: Function
"""
return oauth.require_oauth(CRScope.SCHEMA_R.value, CRScope.SCHEMA_RW.value)(f) | 908818816d696177ce761f453e0893d4777d241a | 3,626,283 |
import urllib3
import certifi
def load_content(site, host, links):
"""Tests a site."""
# Security: Verified HTTPS with SSL/TLS
http = urllib3.PoolManager(
cert_reqs='CERT_REQUIRED', # Force certificate check.
ca_certs=certifi.where(), # Path to the Certifi bundle.
)
start_page_sea... | 5a599579133297c2e6ab3231b466f1b6184d22cc | 3,626,284 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.