content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def getPublishersBooksIDs(publisher, base=ALEPH_DEFAULT_BASE):
"""
Get list of :class:`DocumentID` objects of documents with given
`publisher`.
Args:
publisher (str): Name of publisher which will be used to search Aleph.
base (str, optional): base on which will be search performed. Defa... | 887e4b608f74e03d1a7eb0c022e39d22f688c4ca | 54,610 |
def czt(x, m=None, w=1.0, a=1, axis=-1):
"""
Compute the frequency response around a spiral.
Parameters:
----------
x: array
The set of data to transform.
m: int
The number of points desired. Default is the length of the input data.
a: complex
The starting point in the com... | a28e49c58270b8c8019f896593e62c822528a55d | 54,611 |
def gettitle():
"""Return title string to be used in the timeline"""
return "%s [ %s, %s - %s ]" % (
params['TIMELINE.pretitle'], params['TIMELINE.title'],
gettimelinestartdate().toString(),
gettimelineenddate().toString()) | e7462cffb6e08fe59fb67f0fb3da0dba599e0f7e | 54,612 |
def refresh_token(token) -> dict or None:
"""
JWT access token refresh method.
Args:
token: payload containing jwt access token to refresh and refresh token.
Returns:
refreshed jwt token payload.
"""
user = token['user']
user_refresh_token = token['refresh_token']
try:... | 3604d34b8ee9d76cae2f537c02c84b343f9a1f84 | 54,613 |
def resume():
"""
Resume a paused timer, re-activating it. Subsequent time accumulates in
the total.
Returns:
float: The current time.
Raises:
PausedError: If timer was not in paused state.
StoppedError: If timer was already stopped.
"""
t = timer()
if f.t.stop... | afdf7969d62427ee0b9d527d756ca4f3e77f4018 | 54,615 |
def encode_side(side):
"""
Return side index by letter
:param side: 'n' | 'o' | 's' | 'w'
:return: 0 | 1 | 2 | 3
"""
if side and isinstance(side, str):
side = str.lower(side)
else:
raise SideValueError
side_list = ['n', 'o', 's', 'w']
try:
retur... | 92d031bff824ff897ba489bc700c71b3bbaee3b0 | 54,616 |
def mmr_df_filter(df, years, start_date, end_date):
"""Return dataframe filtered by given years, start_date and end_date.
df is mmr dataframe (mandatory)
years is a list of Workout_date years to include in plot (mandatory)
e.g. years=[2020, 2021]
- if no value is given (years=No... | 6fb939b01731f6c3d4153a6fbcbcca7e64af9696 | 54,617 |
def loggedReactor(reactor):
"""
Construct and return a wrapper around the given C{reactor} which provides
all of the same interfaces, but which will log all traffic over outgoing
TCP connections it establishes.
"""
bases = []
for iface in providedBy(reactor):
if iface is IReactorTCP:... | 0948f9f070bab308ad4acc97f762633e48c7efec | 54,618 |
def process_head_element_content(placeholder_storage, markup):
"""
Process content for elements inside <head>.
Processes CMD syntax which does not produce new elements,
i.e. escapes, line continuations, and whitespace,
and then protects the content with a placeholder.
"""
markup = process_escapes(pl... | 27ac55590fb62ae9194b5a1549268e412c03f701 | 54,621 |
def central_derivative(xs, ys):
""" central derivative at x[1] """
return (ys[2]-ys[0])/(xs[2]-xs[0]) | ef3e397eda004f9f2afbd2a5bd5c8c23b72755c5 | 54,622 |
def print_from_tests(pav_cfg, tests, outfile, json=False):
"""Print the statuses given a list of test objects or a single test object.
:param dict pav_cfg: Base pavilion configuration.
:param Union(test_run.TestRun,list(test_run.TestRun) tests:
Single or list of test objects.
:param bool json: ... | 4ed044189bf9fa3c9c418956cc80414580294471 | 54,623 |
def plot_boxplot(data, ylabel, title, log_scaling=True):
"""
Args:
data: Dict of list of numbers.
"""
fig, ax = plt.subplots(1, 1, figsize=(8, 6), dpi=300)
plt.xticks(rotation=90)
ax.boxplot(data.values(), labels=data.keys())
ax.set_ylabel(ylabel)
ax.set_title(title)
if log... | 1e08ac5415edfff41432445189652d135827906b | 54,624 |
def submit_dataframe_operation(comms, coroutine, df_list, extra_args=()):
"""Submit an operation on a list of Dask dataframe
Parameters
----------
coroutine: coroutine
The function to run on each worker.
df_list: list of Dask.dataframe.Dataframe
Input dataframes
extra_args: tupl... | 33173645ed1b71eb0f6d4cc7d2ceed44dbf76358 | 54,625 |
from typing import Union
def encode(message: Union[str, bytes]) -> bytes:
"""Encodes a message (str or bytes) to zbase32."""
if isinstance(message, str):
message = message.encode('ASCII')
elif not isinstance(message, bytes):
raise TypeError("message must be string or bytes")
barr = _m... | 5c278e16822fc721b4219dda28c0b154eeaf7020 | 54,626 |
from typing import Callable
def linear_adjoint(fun: Callable, *primals) -> Callable:
"""Conjugate transpose a function that is promised to be linear.
:func:`scico.linear_adjoint` differs from :func:`jax.linear_transpose`
for complex inputs in that the conjugate transpose (adjoint) of `fun` is returned.
... | 8c3f3d8db725bd107c5236e352c240df010b0f01 | 54,627 |
def parse_sra(path_to_config):
"""
Parses genetorrent config file. Returns list of samples: [ [id1, id1 ], [id2, id2], ... ]
Returns duplicate of ids to follow UUID/URL standard.
"""
samples = []
with open(path_to_config, 'r') as f:
for line in f.readlines():
if not line.iss... | 59c5ddc2e2efca6cada28db4ea225bc0590f1fb2 | 54,628 |
def queryTagHistory(
paths, # type: List[String]
startDate=None, # type: Optional[Date]
endDate=None, # type: Optional[Date]
returnSize=-1, # type: Optional[int]
aggregationMode="Average", # type: Optional[String]
returnFormat="Wide", # type: Optional[String]
columnNames=None, # type:... | b9bc9fdda65dcd5e8b5918b75bd38b20e514b0a7 | 54,629 |
import torch
def hard_sigmoid(tensor: torch.Tensor, inplace: bool = False) -> torch.Tensor:
"""
Applies HardSigmoid function element-wise.
See :class:`torchlayers.activations.HardSigmoid` for more details.
Arguments:
tensor :
Tensor activated element-wise
inplace :
... | 5f4d87749ddca014076f46e0af6e9b3c4308ddf7 | 54,630 |
def define_ns_gnn_encoder(gnn_name):
"""
return specified model class for GNNs with node-sampling.
"""
if gnn_name == 'gat':
return SamplingGAT
elif gnn_name == 'sage':
return SAGE
elif gnn_name == 'mpnn':
return SamplingMPNN
else:
raise NotImplementedError("n... | 2f89a708e8c417b246291cffa0eaee21eb9f56c7 | 54,631 |
def egaussian(p, x, y, e=None):
""" Compute the deviation between the values y and the gaussian defined by p, x:
p is a three- or four-component array, list, or tuple.
Returns: y - p3 - p0/(p1*sqrt(2pi)) * exp(-(x-p2)**2 / (2*p1**2))
if an error array, e (typ. one-sigma) is entered, the returned va... | 80b155783eb27de52f2553047c505cf9c8e0203e | 54,632 |
from typing import Optional
def _get_html_tree(html_content: str) -> Optional[lxml.html.HtmlElement]:
"""Obtain the HTML parse tree for the given HTML content.
Args:
html_content: The content to parse.
Returns:
The corresponding HTML parse tree.
"""
html_content = html_content.st... | 842805b6b364d7cc277633daca6a42999b9d7972 | 54,635 |
from typing import Callable
def get_int(prompt: str | None = None,
min_value: int | None = None,
max_value: int | None = None,
condition: Callable[[int], bool] | None = None,
default: int | None = None) -> int:
"""Gets an int from the command line.
:param promp... | e1c2beada06088804709d572a848f827a3946fb2 | 54,637 |
from typing import Tuple
def _normalize_array(array_data: Array, normalizer: Tuple[Array,
Array]) -> Array:
"""Helper function for normalize_graph()."""
shift, scale = normalizer
return (array_data - shift) / scale | 2a206eb871dc40cc29d064b64e26b8e89f4979e1 | 54,638 |
def linear_gauss_policy_fit_with_prior(train_data, prior_mean, prior_cov,
niw_prior_m, niw_prior_n0, cov_reg,
action_size, observation_size):
""" @brief: pi = p_x.dot(x) + f_c, cov(f) = f_cov
"""
cov_reg_matrix = np.zeros([action_... | 2a00bb1c386212f85c1cf2f14fbefdb1552fa377 | 54,639 |
import copy
def get_action_dict_junc(observation_builder, obs):
"""
Takes an agent handle and returns next action for that agent following shortest path:
- if agent status == READY_TO_DEPART => agent moves forward;
- if agent status == ACTIVE => pick action using shortest_path.py() fun available in pr... | 62fefab9f18c300989df8ba1fbf212592c0fe755 | 54,640 |
import re
def scan(file, blocksize=10000):
"""Get the number of molecules in an sd file"""
pat = re.compile("^[$][$][$][$]", re.MULTILINE)
text = file.read(blocksize)
count = 0
while text:
g = pat.findall(text)
count += len(g)
if text[-1] == "$" and text[-4]!='$':
... | e3b1af1e65e28146d609a0c2841f195ad783b59e | 54,641 |
from fontTools.ufoLib.filenames import userNameToFileName
from robofab.tools.glyphNameSchemes import glyphNameToShortFileName
def testGLIFFileName(rangeName, toFile=None):
"""
test on glif file name
"""
# support both UFO2 as UFO3
try:
# UFO3 ufoLib
def nameToFileName(name):
... | c2b6d83e4372baf3895b3647d07404686230418a | 54,642 |
def Checksum(bbytes: bytes, length: int) -> bytes:
"""Checksum Create checksum of [length] bytes from the 256 bit hash of the byte slice.
Returns the lower [length] bytes of the hash
Errors if length > 32."""
hash = ComputeHash256Array(bbytes)
return hash[len(hash)-length:] | c0993c3252a8794b7762068f27a44dbb3dbcb724 | 54,643 |
def peters_g(n, e):
"""
Compute g(n, e) from Peters and Mathews (1963) Eq.20
### Parameters:
n (`int/array`): Harmonic(s) of interest
e (`float/array`): Eccentricity
### Returns:
g (`array`): Relative power of gravitational radiation at the nth harmonic
"""... | f13d2b8222d74a0e3e45a264e84149bd0f37a460 | 54,644 |
def normalized_sat_value_difference_index(Blue, Green, Red):
"""transform red, green, blue arrays to normalized sat-value difference
Parameters
----------
Blue : np.array, size=(m,n)
blue band of satellite image
Green : np.array, size=(m,n)
green band of satellite image
Red : np... | 41ba01231db8252b77defaae62698c042b461a98 | 54,645 |
def make_game(environment_data, level):
"""Initialises the game.
Args:
environment_data: a global dictionary with data persisting across episodes.
level: which game level to play.
Returns:
A game engine.
"""
sprites = {SUSHI_CHR: [SushiSprite], AGENT_CHR: [AgentSprite]}
upda... | 57d1ddaba3ebe4b083506f3bba03dcdaced256de | 54,646 |
import pickle
def filter_by_freq(word_list, chained_words, min_freq):
""" Replaces words occuring less than min_freq with the unknown tag <unk>
and dumps the replaced words to a file (via pickle)
"""
unk_list = []
print("Filtering words occuring less than %d times..." % min_freq)
for word in w... | 76186e9cb0dcc494575bc00c6994601e4a891483 | 54,647 |
def score_tile(
tile_cij,
clr,
expected_indexed,
expected_value_col,
clr_weight_name,
kernels,
max_nans_tolerated,
band_to_cover,
):
"""
The main working function that given a tile of a heatmap, applies kernels to
perform convolution to calculate locally-adjusted expected and... | 4597a4a929d610c9316b5e40a80696ed46e94c61 | 54,648 |
def display_time(seconds, granularity=1):
""" Turns seconds into weeks, days, hours, minutes and seconds.
Granularity determines how many time units should be returned. EG:
# 2 time unites, week and day
1934815, 2 = '3 weeks, 1 day'
# 4 time units
1934815, 4 = '3 weeks, 1 day, 9 hours, 26 minute... | d4b94ffafcdbda99526ecc906ed8379d7fc5edab | 54,649 |
import torch
def euler2mat(angle):
"""Convert euler angles to rotation matrix.
Reference: https://github.com/pulkitag/pycaffe-utils/blob/master/rot_utils.py#L174
Args:
angle: rotation angle along 3 axis (in radians) -- size = [B, 3]
Returns:
Rotation matrix corresponding to the euler a... | 4b503e13948b68c8961796c4aa8cee687740e3b3 | 54,650 |
from typing import List
from typing import Optional
from typing import Any
def execute_cli_command(args: List[str], input_data: Optional[str] = None, ret_val: int = 0, output_string: bool = True) -> Any:
"""Execute a Nessie CLI command."""
if output_string:
return _run(args, input_data, ret_val).outpu... | 054a3fc9f2b9d1de33b347c94a4ac4b7bd62900f | 54,651 |
def transformer_latent_decoder(x,
encoder_output,
ed_attention_bias,
hparams,
name=None):
"""Transformer decoder over latents using latent_attention_type.
Args:
x: Tensor of shape [batch,... | 51e82f5ceea3c6a3a1e473208936f1fdb5f63303 | 54,653 |
def errorbar(*args, **kwargs):
"""
Plot curves with error bars
Example::
import numpy as np
x = np.linspace(-5, 5, 1000)
errorbar(x, -1+x**2/20+.2*np.random.rand(len(x)), x/20)
show()
"""
axe = gca()
curve = make.merror(*args, **kwargs)
axe.add_p... | 09130681d4c205008083b101d152664131ee83ed | 54,654 |
def privkey_to_wif(privkey, netcode="BTC"):
""" Get private key from bitcoin wif.
Args:
privkey (str): Hex encoded private key
Return:
str: Private key encode in bitcoin wif format.
"""
prefix = networks.wif_prefix_for_netcode(netcode)
secret_exponent = encoding.from_bytes_32(h... | 055125ac7e76341366ad5c9ea5289f44427260fd | 54,655 |
def join_values(values):
"""Return the values as a space-delimited string."""
return " ".join((str(v) for v in values)) | 60fd4acbafc4619c134ae67d224df408cad12ab0 | 54,656 |
def get_cookie_opener( gs_username, gs_token, gs_toolname=None ):
""" Create a GenomeSpace cookie opener """
cj = http_cookiejar.CookieJar()
for cookie_name, cookie_value in [ ( 'gs-token', gs_token ), ( 'gs-username', gs_username ) ]:
# create a super-cookie, valid for all domains
cookie = ... | 7e9fd52ebccd8fc5065673f727d2cff720f53246 | 54,657 |
def translate(im,trans):
"""translates 3d images"""
shape_ = im.shape
zmax=shape_[0]
xmax=shape_[1]
ymax=shape_[2]
zmin,xmin,ymin=0,0,0
trans_=np.array(np.round(trans),dtype=int)
zmin-=trans_[0]
zmax-=trans_[0]
xmin-=trans_[1]
xmax-=trans_[1]
ymin-=trans_[2]
ymax-=tra... | b2f438b20ff2d7cca65e7dd410c5826790f7224d | 54,658 |
def add_base32_padding(base32_input_no_padding):
"""Return a base32 string with the correct padding
Parameters:
base32_input_no_padding (str): base32 string without padding
"""
result = base32_input_no_padding
while ((len(result) % 8) != 0):
result += '='
return result | 9f98d4c705b5932171954aee3fb90c34681ea7fc | 54,659 |
import torch
def compute_similarities(audio_embeds, query_embeds, audio_lens):
"""
Compute a batch of audio-text alignment matrices.
:param audio_embeds: tensor, (N, T, E).
:param query_embeds: tensor, (N, Q, E).
:param audio_lens: numpy 1D-array, (N,).
:return: tensor, (N, T, Q).
"""
... | 52d8180a99426408c767f50c78acade3f217a74d | 54,660 |
from re import T
def T_inv(e, d, b):
"""Inverse transform b."""
return T(rotate_right(e, d+1), N-d-2, b) | 64da217aac3e63a29aa56b089fedd937c47fc6ca | 54,662 |
def magic(num_lst, n, k):
"""对 num_lst 使用 k 次魔力"""
a = num_lst[:]
for j in range(k):
b = a[1:] # 又一种“移动”方法
b.append(a[0])
for i in range(n):
a[i] = (a[i] + b[i]) % 100 # 无差别对 100 取余
return a | 1f8e1e766add89e0f03a6ef778fe6c1100886125 | 54,663 |
import asyncio
import aiohttp
async def test_timeout(aresponses):
"""Test request timeout from AdGuard Home."""
# Faking a timeout by sleeping
async def response_handler(_):
"""Response handler for this test."""
await asyncio.sleep(2)
return aresponses.Response(body="Goodmorning!")... | 5e1ddf44797bd23badb180a2fc99897286cfad1d | 54,664 |
def format_number(number):
"""
Round number to two decimals
:param number: input number
:return: number rounded to two decimals
"""
return format(float(number), '.2f') | 621e48e46aef43c6ede38b62a3608b8e193d7df7 | 54,665 |
def apply_sort(query, sort_spec):
"""Apply sorting to a :class:`sqlalchemy.orm.Query` instance.
:param sort_spec:
A list of dictionaries, where each one of them includes
the necesary information to order the elements of the query.
Example::
sort_spec = [
{'... | 26ae50a733b41b78dfe1ddf77ac0f0957ffa38bc | 54,666 |
def _find(searchable_models, tupls):
"""
# start with the output of the _dice doctest
>>> p = [('a', 'b', 'c'), ('a', 'b'), ('b', 'c'), ('a',), ('b',), ('c',)]
>>> class MockModel_A(object):
...
... def __repr__(self):
... return "<MM:A>"
...
... @classmethod
...... | 75b58b4377abe5f42e9611f44140a9034d930d0e | 54,667 |
def tags_index():
"""Show a page with info on all tags"""
tags = Tag.query.all()
return render_template('tags/index.html', tags=tags) | 9ee801d9ad80bf4b72825791a6e985536399de04 | 54,668 |
def build_estimator(model_dir, model_type):
"""Build an estimator."""
if model_type == "wide":
m = tf.estimator.LinearClassifier(
model_dir=model_dir, feature_columns=feature_columns)
elif model_type == "deep":
m = tf.estimator.DNNClassifier(
model_dir=model_dir,
feature_columns=fe... | 807d092211d7c4a112a4cdfe31b3db853a347f07 | 54,669 |
def double_variants(word):
"""get variants for the variants for a word"""
return set(s for w in variants(word) for s in variants(w)) | a9cfd85508b2d3f035ae918411725e94faa57860 | 54,670 |
def callBigDlFunc(bigdl_type, name, *args):
""" Call API in PythonBigDL """
jinstance = JavaCreator.instance(bigdl_type=bigdl_type).value
sc = get_spark_context()
api = getattr(jinstance, name)
return callJavaFunc(sc, api, *args) | 0a3ce4b3045f932b6c3452b948c7216d55fe8f26 | 54,672 |
def k_fold_cross_valid(k, epochs, verbose_epoch, X_train, y_train,
learning_rate, weight_decay, batch_size):
"""Conducts k-fold cross validation for the model."""
assert k > 1
fold_size = X_train.shape[0] // k
train_loss_sum = 0.0
test_loss_sum = 0.0
for test_idx in range... | ee760d69ea9489525f7ad9313bf0f49e92e748f7 | 54,673 |
def format_indentation(string):
"""
Replace indentation (4 spaces) with '\t'
Args:
string: A string.
Returns:
string: A string.
"""
return string.replace(" ", " ") | 501f8b3a11f03fef295df771d76ac3a63f8209f3 | 54,674 |
from typing import Optional
def get_sync_group(database_name: Optional[str] = None,
resource_group_name: Optional[str] = None,
server_name: Optional[str] = None,
sync_group_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = No... | 84e7adb466efd34377542361cf0e5bfde7b4320e | 54,676 |
def kneel_down(score_diff, timd, secs_left, dwn):
"""Return 1 if the offense can definitely kneel out the game,
else return 0."""
if score_diff <= 0 or dwn == 4:
return 0
if timd == 0 and secs_left <= 120 and dwn == 1:
return 1
if timd == 1 and secs_left <= 87 and dwn == 1:
... | 2865d32484015f0e4a8f1cd28d68ec1a57847ce4 | 54,677 |
from typing import Union
from typing import TextIO
from typing import Collection
from pathlib import Path
import logging
def create_wrappers_for_header_file(path: Union[str, PathLike[str]],
out_dir: str,
include_dir: Union[str, PathLike[str]],
... | 7610e71cba6bac96ea04123a43c904ed02220715 | 54,678 |
def get_top_ngrams(vectorizer, top_n=5):
"""
Get highest ranking ngrams of a feature matrix
:param vectorizer: vectorizer object
:param top_n: amount of top n-grams to return
:return: top n-grams
"""
indices = np.argsort(vectorizer.idf_)[::-1]
features = vectorizer.get_feature_names()
... | 2b391b7aba863ad576e445731d9ca8be4fd0c203 | 54,679 |
def variational_kmeans(mesh, vector_field, n_clusters, iters, tol):
"""
An instance of VariationalKMeans.
"""
return VariationalKMeans(mesh, vector_field, n_clusters, iters, tol) | 8562c39ee35c24514c5526d900df16dd64bd7db5 | 54,680 |
def get_contours(image):
"""
For input image use `cv2.findContours` function to get a list of contour objects.
Args:
image (numpy.ndarray):
Input image.
Returns:
list of contour objects:
List of contour objects extracted from the image.
""" # NOQA E501
#... | afa929c6ca9c9c0ab52d18617c7e4d5d1b0552b5 | 54,685 |
def encode(n, b=58):
"""
:param n: 压缩的数字
:param b: 进制 最大58
:return: 对应进制字符串
"""
result = ''
x = int(n)
while True:
x, y = divmod(x, b)
result = baseList[y] + result
if x <= 0:
break
return result | 9f2af45ef63297ed6774c75d382fe1984edf6f84 | 54,686 |
import math
def quantity_string(quantity, unit, computer_prefix=False):
"""Return a human-friendly string representing a quantity by adding
prefixes and keeping the number of significant figures low.
'computer_prefix' determines whether each prefix step represents 1024
or 1000.
Examples:
>>> ... | 04aa8743e045c2aaf80115984c30f091d695de77 | 54,689 |
def populate_context(dbot_scores: list, domain_entries: list, file_entries: list,
url_entries: list, email_entries: list = None) -> dict:
"""
Populate the context object with entries as tuples -
the first element contains global objects and the second contains PhishLabs objects
:par... | 3c72887e7d508a5e449b74da096165ed7d0229c3 | 54,692 |
import pytz
def round_datetime(dt, period, tzinfo=pytz.UTC, force=False):
"""
Rounds a datetime to the nearest period.
Valid periods are:
minute, minute-15, hour, day, week
:type dt: datetime
:param dt: A naive or aware datetime object.
:type period: str
:param period: Options are mi... | ec856a37d7e9bb7c4077e753327287ac3048b9b0 | 54,693 |
def force_categorical_determination(table):
""" Find string columns using 'computationally expensive' approach """
source_shape = table.shape
columns_number = source_shape[1] if len(source_shape) > 1 else 1
categorical_ids = []
non_categorical_ids = []
# For every column in table make check for... | 012fb261c39e2bd5106df4e88af9703821158146 | 54,694 |
def _apply_words(nums):
"""
Get the corresponding words for a list of 11-bit numbers.
Args:
nums (int[]): list of 11-bit numbers
Returns:
str[]: list of words
"""
return [index_to_word[n] for n in nums] | 626fab36ea86b7b22e17b6d924dfa72f4437dbb7 | 54,695 |
def FCN_32s(input_shape,
n_class,
encoder_name,
encoder_weights=None,
fc_num=4096,
weight_decay=1e-4,
kernel_initializer="he_normal",
bn_epsilon=1e-3,
bn_momentum=0.99,
dropout=0.5):
""" implementation of FCN... | 4baac4a8472a7cddb938fa0f69fa5f9f68863999 | 54,696 |
import numpy
def L2d1(x):
"""
First derivative of the quadratic lagrange basis function.
:param x: points to interpolate
:type x: numpy array (npoints)
:return: basis weights
:rtype: numpy array(npoints, 3)
"""
L1 = 1-x
return numpy.array([
1.0 - 4.0 * L1,
4.0 ... | d74adfa7c22d9686a1428f21777f1d3bc3cda4d7 | 54,698 |
def vector_to_dictionary(vector, layers):
"""
Convert the parameter vector of a model into a dictionary used by the model
Arguments:
vector -- one-dimensional vector in orders: "W1", "W2", "WL", "b1", "b2", "bL"
layers -- list of (n_uints, activations) pairs that define network structure,... | 33f628463546892ae8127cad25bda1e7ae19a78a | 54,700 |
def compute_vanderwaals(traj_frag_molid, frame_idx, index_to_label, sele_id, VDW_EPSILON, VDW_RES_DIFF):
"""
Compute all vanderwaals interactions in a frame of simulation
Parameters
----------
traj_frag_molid: int
Identifier to simulation fragment in VMD
frame_idx: int
Frame num... | 05749204946124e87f8413d2bd1845c93cb568b8 | 54,702 |
def load_text(filepath):
"""Loads text from a file and returns it as a string.
Args:
filepath (str): The path to the file to be loaded.
Returns:
text (str): The text loaded from the file.
Examples
--------
>>> load_text('text.txt')
"""
with open(filepath, encoding='utf... | 66a925216a33f8b9e7abab4b7ada6ad2716cefd6 | 54,703 |
def f_call_one_optional_kwd(a, /, *, b=2):
"""
>>> f_call_one_optional_kwd(1)
(1, 2)
>>> f_call_one_optional_kwd(1, b=3)
(1, 3)
"""
return (a,b) | 4bcbc58d90f093775c4f52dcdfce0d0deb5d6686 | 54,704 |
import requests
import json
def send_post_request(url, data: dict = None, **kwargs) -> dict:
"""
发起post请求
:param url: 请求目标地址
:param data: 请求参数
:param kwargs:
:return:
"""
try:
resp_dict = requests.post(url, data=json.dumps(data), **kwargs).json()
except Exception as e:
... | 95de52e6005e7f00078a6e682512450a0367ee70 | 54,705 |
def _data_type_filter(x, y):
"""Filter data types into acceptable format."""
if HAS_DASK:
x = extract_dask_data(x)
if y is not None:
y = extract_dask_labels(y)
if HAS_PANDAS:
x = extract_pandas_data(x)
if y is not None:
y = extract_pandas_labels(y)
return x, y | de9bf7141d82655a4c202d8baed80cecb1ac94aa | 54,706 |
def area(int_pts, num_of_inter):
"""area"""
area_val = 0.0
for i in range(num_of_inter - 2):
area_val += abs(trangle_area(int_pts[:2], int_pts[2 * i + 2:2 * i + 4],
int_pts[2 * i + 4:2 * i + 6]))
return area_val | 78519de4802bbd76c376af1e2bec71ed106eca34 | 54,707 |
def unique(it):
"""Return a list of unique elements in the iterable, preserving the order.
Usage::
>>> unique([None, "spam", 2, "spam", "A", "spam", "spam", "eggs", "spam"])
[None, 'spam', 2, 'A', 'eggs']
"""
seen = set()
ret = []
for elm in it:
if elm not in seen:
... | 8e182467eb8179c2b9168470f8b683710ad37b56 | 54,708 |
def _quaternionAdd(quat0, quat1):
""" Multiplies 2 lists of quaternions
"""
# Find the maximum indices to use for clipping purposes
max0, max1 = quat0.shape[0]-1, quat1.shape[0]-1
maxsize = max(max0, max1) + 1
quat = np.empty((maxsize,4))
for ii in range(maxsize):
index0 = min(ii, ... | f3124f38955d728efbe8e9b467a7164e8024b888 | 54,709 |
from numpy import where
def image_numbers(logfile,name="",repeat_count=[]):
"""Select a subset of a dataset based on critria, such a file name and repeat counts
logfile: table object, must have attributes "file",Temperature","Delay"
name: part of the image filname, e.g. "_offWT"
repeat_count: e.g. [["... | e4ed486792eab4091016599ec09cf3a219df14b2 | 54,710 |
import scipy
def optimize_epsilon(data_train, labels_train, data_test, labels_test, num_markers, method='centers', fixed_parameters={}, bounds=[(0.2 , 10)], x0=[1], max_fun_evaluations=20, n_experiments=5, clf=None, hierarchy=False, verbose=True):
"""
Finds the optimal value of epsilon using scipy.optimize.du... | d8089bf5059bbcb3b1650ea3adcf24a39365c3e4 | 54,712 |
def census_vip_call(*, resp, **_):
"""
Convert response for calling url to pandas dataframe,
begin parsing df into FBA format
:param resp: df, response from url call
:return: pandas dataframe of original source data
"""
# Convert response to dataframe
df = pd.read_excel(resp.content,
... | c7e63b569b317cc9bdae2eb6064fea437ac03f49 | 54,713 |
def model_field_slugify(
model_class,
instance,
string,
filter_keys=None,
exclude_keys=None,
slug_field='slug'):
"""Slugify string based on another string and saves slug in model"""
if str(string).lower() in reserved_slugs:
raise ReservedSlugException('Es... | 1520deee2a8ba5b2cb78372c5f00ab63306f0e0c | 54,714 |
def create_read_fmt(read_id: str) -> str:
"""create a bitstruct format for any given read it up to 512 bits"""
if len(read_id) > 64:
raise ValueError("Read ID is too large")
padding = 512 - len(read_id)*8
r_fmt = "t{0}p{1}".format(len(read_id)*8, padding)
return r_fmt + ("u3" * 150) + ("u6" ... | f7319ffc62b55859ed8af3e6b7e044d9481f7384 | 54,715 |
from typing import Optional
import tempfile
from pathlib import Path
def get_job_log_file(run: Run, index: Optional[int] = None) -> str:
"""
Reads the job log file (70_driver_log.txt or std_log.txt) of the given job. If an index is provided, get
the matching file from a multi-node job.
:return: The co... | 5675a9e08a499cd99c765e1e76009c0ad3cbdc55 | 54,718 |
import warnings
from typing import cast
def _is_compatible(program: Loop, min_len: int, quantum: int, sample_rate: TimeType) -> _CompatibilityLevel:
""" check whether program loop is compatible with awg requirements
possible reasons for incompatibility:
program shorter than minimum length
... | 38cc5f639b54bbfc5602d4f5e3c25909a9a06014 | 54,719 |
def get_data_for_tpu(tpu_name, economic_dataframe, marry_dataframe, edu_dataframe, population_dataframe):
"""
:param tpu_name: the name of the tpu
:param economic_dataframe: the dataframe contains median income and employment rate
:param marry_dataframe: the dataframe which saves the marrital status
... | fe71fd15fab28684f848b80e68746fe1e3a73f51 | 54,720 |
def gridaspoints(*arrs):
"""Creates an N-dimensional grid form arrs and returns grid points sequence
of point coordinate pairs
"""
# there is a small gotcha here.
# with the convention following the 2013-08-30 sprint in Potsdam it was
# agreed upon that arrays should have shapes (...,z,y,x) simi... | ba907705965bf9f432d127126c784eb5b1c84873 | 54,721 |
def download_powermeter_csv(agent):
"""
Method to download a CSV list of mains sensor readings for all configured power meters and panels
**parameters**
:param agent: An agent instance from the device where the pmc data should be downloaded
:return: returns the pmc data in csv format
**Exampl... | d1c2b10ca89de98fd029388882e91b2264c0d235 | 54,722 |
def get_learner(case, *args, **kwargs):
"""Generator function for test"""
data = Data(*args, is_learner=True, **kwargs)
p = getattr(data.indexer, 'partitions', 1)
X, y = data.get_data((12, 4), 2)
(F, wf), (H, wh) = data.ground_truth(X, y, p)
data.indexer.fit(X)
learner, transformer = Estima... | 104317d0a5e7daf0272178b54595c33068fb844c | 54,723 |
def cleaned(cls):
"""Call individual cleaning methods and collect all of their ValidationErrors
Purpose:
This decorator allows you to write individual methods that do some
validation or cleaning without having to worry about collecting all
of their ValidationErrors together into a list ... | d502bfb2070d6a5578a5d7bb502383513f816ee0 | 54,726 |
def check_framescene(scene, frame, cameras, quality, check_green_frames,
check_empty_frame, min_nbr_people):
"""
Checks a frame for all cameras in one scene.
Returns True if all frame is good.
Returns False if any frame was bad.
"""
for camera in cameras:
bad, ids = ... | 05843c8b022fae658076232be709d295dd42cd84 | 54,728 |
def _get_consecutive_and_overlapping_fronts(onset_fronts, offset_fronts, onset_front_id, offset_front_id):
"""
Gets an onset_front and an offset_front such that they both occupy at least some of the same
frequency channels, then returns the portion of each that overlaps with the other.
"""
# Get the... | 14314dc10d896807a3d10ef57a1a4abaab28de5c | 54,729 |
import statistics
def time_formatted(event:str, mode:str, t: float, dnf: bool=False) -> str:
""" Reverses parse_time """
if t == statistics.DNF:
return "DNF" if dnf else ""
if event in ["3x3x3 Fewest Moves", "3x3x3 Multi-Blind"]:
if event == "3x3x3 Fewest Moves" and mode == "average":
... | fb39e88e3e790b2338288cc31f4e6b0c7e9b299c | 54,731 |
from re import T
import numpy
def tsum(x: T.Tensor, axis: int=None, keepdims: bool=False) -> T.FloatingPoint:
"""
Return the sum of the elements of a tensor along the specified axis.
Args:
x: A float or tensor.
axis (optional): The axis for taking the sum.
keepdims (optional): If ... | a8004051ed0258396366e075bd5b4f3cdebcdd5d | 54,732 |
def ask_multi_choices(prompt="Add to choices : ", choices_list=[], to_save="s", to_quit="q"):
"""Collect multi choices from list
Keyword Arguments:
prompt {str} -- the question method (default: {"Add to choices : "})
choices_list {list} -- the available options (default: {[]})
to_sa... | 0ece08fd561b770445af1e9a778f3dbaf0c1ba6a | 54,733 |
def DtypeToType(dtype):
"""Converts a Numpy dtype to the FeatureNameStatistics.Type proto enum."""
if dtype.char in np.typecodes['AllFloat']:
return GetFeatureStatsProtoDef().FLOAT
elif (dtype.char in np.typecodes['AllInteger'] or dtype == np.bool or
np.issubdtype(dtype, np.datetime64) or
np.i... | b448192a2bd50cf1b45a29c3f29e1be53c4cab08 | 54,734 |
def register_prelu_func(graph):
"""Register Prelu op with function def, this is need for importing graph_def
with unregistered Prelu op.
Args:
graph: A tf.Graph object to insert prelu function into.
"""
# Create a function for Prelu op
@function.Defun(tf.float32, tf.float32, func_name='Prelu')
def pr... | 6884288e62489e8e27f1b9bf7aac911c13f005c4 | 54,735 |
def _parseSteps(raw_steps, lang=None):
"""
:type raw_steps: Iterable[dict]
:param lang: (Optional) Descriptor of the language to query the step,
without any specification of encoding or modifiers.
:type lang: str | None
:rtype: Iterable[TutorialStep]
"""
def getI18nStringForStepKey(... | 7a9b2cc7cf3c805d38db6c1ae21ea20062ba7ca4 | 54,736 |
def legendre_P(n,x):
"""
Returns the Legendre polynomial of the first kind for integers
`n > -1`.
REFERENCE:
- AS 22.5.35 page 779.
EXAMPLES::
sage: P.<t> = QQ[]
sage: legendre_P(2,t)
3/2*t^2 - 1/2
sage: legendre_P(3, 1.1)
1.67750000000000
sage... | 45b60b0ad5874a3bf54e83cad6037e72e8f363fd | 54,737 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.