content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import os
def get_img_full_path(path):
""" Checks if file can be found by path specified in the input. Returns the same as input
if can find, otherwise joins current directory full path with path from input and returns it.
:param path: Relative of full path to the image.
:return: Relative of full path... | d549cd09035ebd6213f1b31c1c2eee4e64dcdce8 | 3,654,200 |
def max_pool_2x2(input_):
""" Perform max pool with 2x2 kelner"""
return tf.nn.max_pool(input_, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME') | b85ccfaafbdcf5d703dffab65e188ffab52ebce9 | 3,654,201 |
import tqdm
def remove_numerals(df, remove_mixed_strings=True):
"""Removes rows from an ngram table with words that are numerals. This
does not include 4-digit numbers which are interpreted as years.
Arguments:
df {Pandas dataframe} -- A dataframe of with columns 'word', 'count'.
Keyword ... | 4c3d0468456e08b1a0579a8b73a21221cae17676 | 3,654,202 |
def generate_json(args, df, num_changes, start_dt, finish_dt,
projects, projects_map,
not_found_proj, group=None, groups=[]):
"""
Returns json report from a dataframe for a specific project
"""
log.debug('Generating %s report for %s', args.report_format, group)
lo... | 1f90e73ad26f87cea0052f157ac3167f54f8b027 | 3,654,203 |
def b32_ntop(*args):
"""LDNS buffer."""
return _ldns.b32_ntop(*args) | b43bc9b1b112f7815ec3c280d055676e7255adcc | 3,654,204 |
import logging
import sys
import os
def get_logger(filename, logger_name=None):
"""set logging file and format
Args:
filename: str, full path of the logger file to write
logger_name: str, the logger name, e.g., 'master_logger', 'local_logger'
Return:
logger: python logger
"""
... | e549cdd7198961662f28390e09480d05f5ad14b4 | 3,654,205 |
from typing import Callable
from typing import Dict
import torch
def infer_feature_extraction_pytorch(
model: PreTrainedModel, run_on_cuda: bool
) -> Callable[[Dict[str, torch.Tensor]], torch.Tensor]:
"""
Perform Pytorch inference for feature extraction task
:param model: Pytorch model (sentence-trans... | 18f935607c824c2122f68ea1ec9a7bcb50604ac8 | 3,654,206 |
def editRole(userSource, oldName, newName):
"""Renames a role in the specified user source.
When altering the Gateway System User Source, the Allow User Admin
setting must be enabled.
Args:
userSource (str): The user source in which the role is found.
Blank will use the default use... | f72796de14ff5f8c4314a5d31fe4fcf42cb883ec | 3,654,207 |
def compute_bspline_dot_product_derivatives(basis_features, basis_dimension):
"""
Compute dot products of B-splines and their derivatives.
Input:
- basis_features: dict
Contain information on the basis for each state
- basis_dimension: dict
Give the number of basis f... | a8ba13b23bb009eb81d57792abeced6fb8715b07 | 3,654,208 |
import os
def validate_table(config, table):
"""Run VALVE validation on a table.
:param config: valve config dictionary
:param table: path to table
:return: list of errors
"""
errors = []
table_name = os.path.splitext(os.path.basename(table))[0]
table_details = config["table_details"]... | 3b8a1517219d4b8b0db5042200f1c62700cabe94 | 3,654,209 |
def beam_hardening_correction(mat, q, n, opt=True):
"""
Correct the grayscale values of a normalized image using a non-linear
function.
Parameters
----------
mat : array_like
Normalized projection image or sinogram image.
q : float
Positive number. Recommended range [0.005, ... | d113ff33c2d688f460cf2bac62cdd8a26b890ce5 | 3,654,210 |
def cargar_recursos_vectores_transpuestos():
"""
Se carga la informacion para poder calcular los vectores transpuestos
"""
# Se crea el df
filename = 'csv/' + conf.data['env']['path'] + '/vectores_transpuestos.csv'
recursos_v_transpuestos = pd.read_csv(filename)
# Se cambia el nombre de los ... | f982fd22bbdfd2d7d389787bf7f923feb9abf66f | 3,654,211 |
def read_pdb(file_name, exclude=('SOL',), ignh=False, modelidx=1):
"""
Parse a PDB file to create a molecule.
Parameters
----------
filename: str
The file to read.
exclude: collections.abc.Container[str]
Atoms that have one of these residue names will not be included.
ignh: ... | d7412b96adef5505676a80e5cdf3fe5e63a3b096 | 3,654,212 |
def sao_isomorficas(texto1: str, texto2: str) -> bool:
"""
>>> sao_isomorficas('egg', 'add')
True
>>> sao_isomorficas('foo', 'bar')
False
>>> sao_isomorficas('eggs', 'add')
False
"""
# Algoritmo O(n) em tempo e memória
letras_encontradas = {}
if len(texto1) != len(texto2):
... | a1f2c00a50b69cb18c32a299d50cbd3a35dcbe5e | 3,654,213 |
def _is_no_args(fn):
"""Check if function has no arguments.
"""
return getargspec(fn).args == [] | 29cb096323c69dd067bf4759a557734443a82ed5 | 3,654,214 |
def failure(parsed_args):
"""
:param :py:class:`argparse.Namespace` parsed_args:
:return: Nowcast system message type
:rtype: str
"""
logger.critical(
f"{parsed_args.model_config} {parsed_args.run_type} FVCOM VH-FR run for "
f'{parsed_args.run_date.format("YYYY-MM-DD")} '
... | e6744bfd61458497b5a70d7d28712385a8488a98 | 3,654,215 |
def good_AP_finder(time,voltage):
"""
This function takes the following input:
time - vector where each element is a time in seconds
voltage - vector where each element is a voltage at a different time
We are assuming that the two vectors are in correspondance (meaning
t... | c13897b7bf5335cae20f65db853e7a214ec570c5 | 3,654,216 |
from typing import Dict
from typing import Any
import tqdm
def parse(excel_sheets: Dict[Any, pd.DataFrame],
dictionary: Dict[str, Any],
verbose: bool = False) -> pd.DataFrame:
"""Parse sheets of an excel file according to instructions in `dictionary`.
"""
redux_dict = recursive_traver... | 88028fef19eda993680e89c58954c04a215a2fdd | 3,654,217 |
def build_LAMP(prob,T,shrink,untied):
"""
Builds a LAMP network to infer x from prob.y_ = matmul(prob.A,x) + AWGN
return a list of layer info (name,xhat_,newvars)
name : description, e.g. 'LISTA T=1'
xhat_ : that which approximates x_ at some point in the algorithm
newvars : a tuple of layer-... | 392050992846aeb1a16e70fe6e43c386e11915e5 | 3,654,218 |
def coeffVar(X, precision=3):
"""
Coefficient of variation of the given data (population)
Argument:
X: data points, a list of int, do not mix negative and positive numbers
precision (optional): digits precision after the comma, default=3
Returns:
float, the cv (measure of dispers... | e92505e79c4d10a5d56ec35cd2b543872f6be59c | 3,654,219 |
def tostring(node):
"""
Generates a string representation of the tree, in a format determined by the user.
@ In, node, InputNode or InputTree, item to turn into a string
@ Out, tostring, string, full tree in string form
"""
if isinstance(node,InputNode) or isinstance(node,InputTree):
return node.p... | 8e6cab92b898bd99b5c738b26fc9f8d79aef0750 | 3,654,220 |
from typing import Dict
import random
def pick_char_from_dict(char: str, dictionary: Dict[str, str]) -> str:
"""
Picks a random format for the givin letter in the dictionary
"""
return random.choice(dictionary[char]) | c593166ef7cb8c960b8c4be8fa0f8a20ec616f00 | 3,654,221 |
from typing import List
def bmeow_to_bilou(tags: List[str]) -> List[str]:
"""Convert BMEOW tags to the BILOU format.
Args:
tags: The BMEOW tags we are converting
Raises:
ValueError: If there were errors in the BMEOW formatting of the input.
Returns:
Tags that produce the sam... | 0081b7691a743fe3e28118cbb571708809fbd485 | 3,654,222 |
def site_sold_per_category(items):
"""For every category, a (site, count) pair with the number of items sold by the
site in that category.
"""
return [(site,
[(cat, total_sold(cat_items)) for cat, cat_items in
categories])
for site, categories in
categ... | 7b224f3e0a786aef497fad99359e525896eb8441 | 3,654,223 |
from typing import List
import ctypes
def swig_py_object_2_list_int(object, size : int) -> List[int]:
"""
Converts SwigPyObject to List[float]
"""
y = (ctypes.c_float * size).from_address(int(object))
new_object = []
for i in range(size):
new_object += [int(y[i])]
return new_ob... | 064a9a1e43884a9f989bec0b31d6d19705764b64 | 3,654,224 |
def ParseAttributesFromData(attributes_data, expected_param_names):
"""Parses a list of ResourceParameterAttributeConfig from yaml data.
Args:
attributes_data: dict, the attributes data defined in
command_lib/resources.yaml file.
expected_param_names: [str], the names of the API parameters that the A... | 73cfc67dddd4d1385bebd0297bd84233c9546dd4 | 3,654,225 |
from typing import Tuple
from typing import Union
async def reactionFromRaw(payload: RawReactionActionEvent) -> Tuple[Message, Union[User, Member], emojis.BasedEmoji]:
"""Retrieve complete Reaction and user info from a RawReactionActionEvent payload.
:param RawReactionActionEvent payload: Payload describing ... | 36ae16e2b1ffb3df1d5c68ae903b95556446138f | 3,654,226 |
import array
def poisson2d(N,dtype='d',format=None):
"""
Return a sparse matrix for the 2d poisson problem
with standard 5-point finite difference stencil on a
square N-by-N grid.
"""
if N == 1:
diags = asarray( [[4]],dtype=dtype)
return dia_matrix((diags,[0]), shape=(1,1)).a... | 089088f468e84dce865bbb26707714617e16f3f6 | 3,654,227 |
import random
def get_factory():
"""随机获取一个工厂类"""
return random.choice([BasicCourseFactory, ProjectCourseFactory])() | c71401a2092618701966e5214f85c67a6520b1c9 | 3,654,228 |
def delay_class_factory(motor_class):
"""
Create a subclass of DelayBase that controls a motor of class motor_class.
Used in delay_instace_factory (DelayMotor), may be useful for one-line
declarations inside ophyd Devices.
"""
try:
cls = delay_classes[motor_class]
except KeyError:
... | 264d68f7d3db164c5c133e68f943b789db52fc8b | 3,654,229 |
import os
def check_and_makedir(folder_name):
""" Does a directory exist? if not create it. """
if not os.path.isdir(folder_name):
os.mkdir(folder_name)
return False
else:
return True | 2f2632fc245c04add6a680fa755932d3a082168b | 3,654,230 |
import os
import fnmatch
def _get_all_files_in_directory(dir_path, excluded_glob_patterns):
"""Recursively collects all files in directory and
subdirectories of specified path.
Args:
dir_path: str. Path to the folder to be linted.
excluded_glob_patterns: set(str). Set of all glob patterns... | 42a7f1220fd54b08b83dc9d89beef0c63c9d5cd0 | 3,654,231 |
def lonlat2px_gt(img, lon, lat, lon_min, lat_min, lon_max, lat_max):
"""
Converts a pair of lon and lat to its corresponding pixel value in an
geotiff image file.
Parameters
----------
img : Image File, e.g. PNG, TIFF
Input image file
lon : float
Longitude
lat : float
... | 39c1aeb63d38fdac383c510913f50f177d274a04 | 3,654,232 |
import torch
def patchwise_contrastive_metric(image_sequence: torch.Tensor,
kpt_sequence: torch.Tensor,
method: str = 'norm',
time_window: int = 3,
patch_size: tuple = (7, 7),
... | 8591d9359773a9b0445974da3926b3cade64d830 | 3,654,233 |
import scipy
def array_wishart_rvs(df, scale, **kwargs):
""" Wrapper around scipy.stats.wishart to always return a np.array """
if np.size(scale) == 1:
return np.array([[
scipy.stats.wishart(df=df, scale=scale, **kwargs).rvs()
]])
else:
return scipy.stats.wishart(df... | d14b26d8f1b05de1ac961499d96c604028fca379 | 3,654,234 |
def get_mpl_colors():
"""
==================
Colormap reference
==================
Reference for colormaps included with Matplotlib.
This reference example shows all colormaps included with Matplotlib. Note that
any colormap listed here can be reversed by appending "_r" (e.g., "pin... | 5926f878b59f3f41282968c67020f611ad928f28 | 3,654,235 |
async def async_setup_entry(hass, entry):
"""Set up Jenkins from a config entry."""
hass.async_create_task(
hass.config_entries.async_forward_entry_setup(entry, "sensor")
)
return True | c46912d11630c36effc07eed3273e42325c9b2b8 | 3,654,236 |
import math
def signal_to_dataset(raw, fsamp, intvs, labels):
"""Segmentize raw data into list of epochs.
returns dataset and label_array : a list of data, each block is 1
second, with fixed size. width is number of channels in certain standard
order.
Args:
raw: EEG signals. Shap... | 340bbb91bd6a36d1d3a20d0689e25c29e5b879c5 | 3,654,237 |
def project_dynamic_property_graph(graph, v_prop, e_prop, v_prop_type, e_prop_type):
"""Create project graph operation for nx graph.
Args:
graph (:class:`nx.Graph`): A nx graph.
v_prop (str): The node attribute key to project.
e_prop (str): The edge attribute key to project.
v_p... | 6e54180a4ef257c50a02104cc3a4cbbae107d233 | 3,654,238 |
def eqfm_(a, b):
"""Helper for comparing floats AND style names."""
n1, v1 = a
n2, v2 = b
if type(v1) is not float:
return eq_(a, b)
eqf_(v1, v2)
eq_(n1, n2) | 1ee53203baa6c8772a4baf240f68bb5898a5d516 | 3,654,239 |
def flatten_comment(seq):
"""Flatten a sequence of comment tokens to a human-readable string."""
# "[CommentToken(value='# Extra settings placed in ``[app:main]`` section in generated production.ini.\\n'), CommentToken(value='# Example:\\n'), CommentToken(value='#\\n'), CommentToken(value='# extra_ini_settings... | 56104eb6e0109b6c677964cd1873244ff05f27fc | 3,654,240 |
def get_community(community_id):
"""
Verify that a community with a given id exists.
:param community_id: id of test community
:return: Community instance
:return: 404 error if doesn't exist
"""
try:
return Community.objects.get(pk=community_id)
except Community.DoesNotExist:
... | 33d16db86c53b7dd68dec8fe80639b560e41f457 | 3,654,241 |
import csv
import pprint
def load_labeled_info(csv4megan_excell, audio_dataset, ignore_files=None):
"""Read labeled info from spreat sheet
and remove samples with no audio file, also files given in ignore_files
"""
if ignore_files is None:
ignore_files = set()
with open(csv4megan_excel... | f196b02c8667ebe5e8d2d89a79be78c6eb838afe | 3,654,242 |
def de_dupe_list(input):
"""de-dupe a list, preserving order.
"""
sam_fh = []
for x in input:
if x not in sam_fh:
sam_fh.append(x)
return sam_fh | bbf1936f21c19195369e41b635bf0f99704b3210 | 3,654,243 |
def donwload_l10ns():
"""Download all l10ns in zip archive."""
url = API_PREFIX + 'download/' + FILENAME + KEY_SUFFIX
l10ns_file = urllib2.urlopen(url)
with open('all.zip','wb') as f:
f.write(l10ns_file.read())
return True | 26770dfc8f32947c1a32a287f811e95ffe314822 | 3,654,244 |
def _constant_velocity_heading_from_kinematics(kinematics_data: KinematicsData,
sec_from_now: float,
sampled_at: int) -> np.ndarray:
"""
Computes a constant velocity baseline for given kinematics data, time window
... | 2b6781ceb9e012486d3063b8f3cff29164ff8743 | 3,654,245 |
def arg_int(name, default=None):
""" Fetch a query argument, as an integer. """
try:
v = request.args.get(name)
return int(v)
except (ValueError, TypeError):
return default | 110088655bc81363e552f31d9bbd8f4fa45abd1b | 3,654,246 |
import os
def db(app, request):
"""Session-wide test database."""
if os.path.exists(os.path.join(INSTANCE_FOLDER_PATH, 'test.sqlite')):
os.unlink(os.path.join(INSTANCE_FOLDER_PATH, 'test.sqlite'))
def teardown():
_db.drop_all()
os.unlink(os.path.join(INSTANCE_FOLDER_PATH, 'test.sq... | c14b929a9fac6978a7dcb5b0815297598c8a94e1 | 3,654,247 |
def adapter_rest(request, api_module_rest, api_client_rest):
"""Pass."""
return {
"adapter": request.param,
"api_module": api_module_rest,
"api_client": api_client_rest,
} | 8b96313cb190f6f8a97a853e24a5fcfade291d76 | 3,654,248 |
import numpy
import os
import shutil
def extract(lon, lat, dep, prop=['rho', 'vp', 'vs'], **kwargs):
"""
Simple CVM-S extraction
lon, lat, dep: Coordinate arrays
prop: 'rho', 'vp', or 'vs'
nproc: Optional, number of processes
Returns: (rho, vp, vs) material arrays
"""
lon = numpy.asa... | 1503faebece8accb380ad47c0e7108a3313a2080 | 3,654,249 |
def remove_quotes(string):
"""Function to remove quotation marks surrounding a string"""
string = string.strip()
while len(string) >= 3 and string.startswith('\'') and string.endswith('\''):
string = string[1:-1]
string = quick_clean(string)
string = quick_clean(string)
return string | c6585c054abaef7248d30c1814fb13b6b9d01852 | 3,654,250 |
def compute_list_featuretypes(
data,
list_featuretypes,
fourier_n_largest_frequencies,
wavelet_depth,
mother_wavelet,
):
"""
This function lets the user choose which combination of features they
want to have computed.
list_featuretypes:
"Basic" - min, max, mean, kurt ,skew, ... | f1c8fea04a01f6b7a3932434e27aba7ea2e17948 | 3,654,251 |
def select(locator):
"""
Returns an :class:`Expression` for finding selects matching the given locator.
The query will match selects that meet at least one of the following criteria:
* the element ``id`` exactly matches the locator
* the element ``name`` exactly matches the locator
* the elemen... | a3cd093a62d6c926fd9f782cdec35eadc34eba67 | 3,654,252 |
def send_image(filename):
"""Route to uploaded-by-client images
Returns
-------
file
Image file on the server (see Flask documentation)
"""
return send_from_directory(app.config['UPLOAD_FOLDER'], filename) | 68b99ca59d6d4b443a77560d3eb1913422407764 | 3,654,253 |
def swissPairings():
"""Returns a list of pairs of players for the next round of a match.
Assuming that there are an even number of players registered, each player
appears exactly once in the pairings. Each player is paired with another
player with an equal or nearly-equal win record, that is, a playe... | f83a8a108f2d926c948999014f0dbb79a3b1c428 | 3,654,254 |
import torch
def split(data, batch):
"""
PyG util code to create graph batches
"""
node_slice = torch.cumsum(torch.from_numpy(np.bincount(batch)), 0)
node_slice = torch.cat([torch.tensor([0]), node_slice])
row, _ = data.edge_index
edge_slice = torch.cumsum(torch.from_numpy(np.bincount(batch[row])), 0)
edge_... | 69af8b969d7f0da28a1f7fda951f64974c238da0 | 3,654,255 |
def _get_shadowprice_data(scenario_id):
"""Gets data necessary for plotting shadow price
:param str/int scenario_id: scenario id
:return: (*tuple*) -- interconnect as a str, bus data as a data frame, lmp data
as a data frame, branch data as a data frame and congestion data as a data
frame
... | 57488b7ff6984cc292dce3bf76d18d0b2585b7ff | 3,654,256 |
import json
def get_city_reviews(city):
"""
Given a city name, return the data for all reviews.
Returns a pandas DataFrame.
"""
with open(f"{DATA_DIR}/{city}/review.json", "r") as f:
review_list = []
for line in f:
review = json.loads(line)
review_list.appen... | e0723ab90dafc53059677928fb553cf197abecc1 | 3,654,257 |
def extract_rows_from_table(dataset, col_names, fill_null=False):
""" Extract rows from DB table.
:param dataset:
:param col_names:
:return:
"""
trans_dataset = transpose_list(dataset)
rows = []
if type(col_names).__name__ == 'str':
col_names = [col_names]
for col_name in col... | 91371215f38a88b93d08c467303ccbd45f57b369 | 3,654,258 |
def CalculateHydrogenNumber(mol):
"""
#################################################################
Calculation of Number of Hydrogen in a molecule
---->nhyd
Usage:
result=CalculateHydrogenNumber(mol)
Input: mol is a molecule object.
... | 0b9fbad14c8e9f46beab5208ab0f929fef1ab263 | 3,654,259 |
def check_update ():
"""Return the following values:
(False, errmsg) - online version could not be determined
(True, None) - user has newest version
(True, (version, url string)) - update available
(True, (version, None)) - current version is newer than online version
"""
version... | 8bba3e7fbe11ce6c242f965450628dc94b6c2c0b | 3,654,260 |
import torch
def count_regularization_baos_for_both(z, count_tokens, count_pieces, mask=None):
"""
Compute regularization loss, based on a given rationale sequence
Use Yujia's formulation
Inputs:
z -- torch variable, "binary" rationale, (batch_size, sequence_length)
percentage -- the ... | 7925c8621866a20f0c6130cd925afffe144e1c7c | 3,654,261 |
def unsqueeze_samples(x, n):
"""
"""
bn, d = x.shape
x = x.reshape(bn//n, n, d)
return x | 0c7b95e97df07aea72e9c87996782081763664cf | 3,654,262 |
def f_snr(seq):
"""compute signal to noise rate of a seq
Args:
seq: input array_like sequence
paras: paras array, in this case should be "axis"
"""
seq = np.array(seq, dtype=np.float64)
result = np.mean(seq)/float(np.std(seq))
if np.isinf(result):
print "marker"
result = 0
return result | b018b5e4c249cfafcc3ce8b485c917bfcdd19ce2 | 3,654,263 |
def _lorentzian_pink_beam(p, x):
"""
@author Saransh Singh, Lawrence Livermore National Lab
@date 03/22/2021 SS 1.0 original
@details the lorentzian component of the pink beam peak profile
obtained by convolution of gaussian with normalized back to back
exponentials. more details can be found in... | 7de93743da63ab816133e771075a8e8f0386ad35 | 3,654,264 |
def get_q_HPU_ave(Q_HPU):
"""1時間平均のヒートポンプユニットの平均暖房出力 (7)
Args:
Q_HPU(ndarray): 1時間当たりのヒートポンプユニットの暖房出力 (MJ/h)
Returns:
ndarray: 1時間平均のヒートポンプユニットの平均暖房出力 (7)
"""
return Q_HPU * 10 ** 6 / 3600 | fdf339d7f8524f69409711d4daefd1e2aaccbc76 | 3,654,265 |
def particles(t1cat):
"""Return a list of the particles in a T1 catalog DataFrame.
Use it to find the individual particles involved in a group of events."""
return particles_fromlist(t1cat.particles.tolist()) | 38f9a077b7bab55b76a19f467f596ddb28e40c60 | 3,654,266 |
def interp_coeff_lambda3(i2,dx2,nx):
"""
NOTE:
input and output index from 0 to nx-1 !!!
"""
i2=i2+1 # TODO, waiting for script to be updated
# Find index of other cells
i1 = i2 - 1
i3 = i2 + 1
i4 = i2 + 2
# Find normalised distance to other cells
dx1 = dx2 + 1.0
dx3 = ... | 560125921588e6302da8ab16e2d7394169fdcbea | 3,654,267 |
def prime_list(num):
"""
This function returns a list of prime numbers less than natural number entered.
:param num: natural number
:return result: List of primes less than natural number entered
"""
prime_table = [True for _ in range(num+1)]
i = 2
while i ** 2 <= num:
if prime_... | c8e05aae2a59c229cfafb997469dd8ccacdda0fc | 3,654,268 |
import time
def check_deadline_exceeded_and_store_partial_minimized_testcase(
deadline, testcase_id, job_type, input_directory, file_list,
file_to_run_data, main_file_path):
"""Store the partially minimized test and check the deadline."""
testcase = data_handler.get_testcase_by_id(testcase_id)
store_min... | 443c09a8b5bcd8141f721b8ea90348879bc3b8c5 | 3,654,269 |
import ipaddress
def _item_to_python_repr(item, definitions):
"""Converts the given Capirca item into a typed Python object."""
# Capirca comments are just appended to item strings
s = item.split("#")[0].strip()
# A reference to another network
if s in definitions.networks:
return s
... | 9881e304e923eb2cea8223224273f4c9ef81696b | 3,654,270 |
import numpy
def floor_divide(x1, x2, out=None, where=True, **kwargs):
"""
Return the largest integer smaller or equal to the division of the inputs.
It is equivalent to the Python ``//`` operator and pairs with the
Python ``%`` (`remainder`), function so that ``a = a % b + b * (a // b)``
up to r... | 9269d088c0893b9b6b4c3b27e8dc83c4493ac2c9 | 3,654,271 |
from typing import Callable
import click
def node_args_argument(command: Callable[..., None]) -> Callable[..., None]:
"""
Decorate a function to allow choosing arguments to run on a node.
"""
function = click.argument(
'node_args',
type=str,
nargs=-1,
required=True,
... | 89365a41b7665cf291f5c15852db81e89aeef9a7 | 3,654,272 |
import functools
import unittest
def _tag_error(func):
"""Decorates a unittest test function to add failure information to the TestCase."""
@functools.wraps(func)
def decorator(self, *args, **kwargs):
"""Add failure information to `self` when `func` raises an exception."""
self.test_faile... | a2818c63647410abea3fde0b7f4fdae667b558bf | 3,654,273 |
import fnmatch
import sys
import traceback
import logging
import os
def create_drizzle_products(total_obj_list, custom_limits=None):
"""
Run astrodrizzle to produce products specified in the total_obj_list.
Parameters
----------
total_obj_list: list
List of TotalProduct objects, one objec... | 838ad7e0f3590e3dab4f7383f33f9c5d5c55e6d7 | 3,654,274 |
from datetime import datetime
def get_submission_praw(n, sub, n_num):
"""
Returns a list of results for submission in past:
1st list: current result from n hours ago until now
2nd list: prev result from 2n hours ago until n hours ago
"""
mid_interval = datetime.today() - timedelta(hours=n)
... | 692af49736fac07a2de51d1cd0c4abcfe7bb8ee3 | 3,654,275 |
import scipy
def memory_kernel_logspace(dt, coeffs, dim_x, noDirac=False):
"""
Return the value of the estimated memory kernel
Parameters
----------
dt: Timestep
coeffs : Coefficients for diffusion and friction
dim_x: Dimension of visible variables
noDirac: Remove the dirac at time ze... | 21e6aed08bebd91f359efa216ab1331cf9ace310 | 3,654,276 |
def _is_constant(x, atol=1e-7, positive=None):
"""
True if x is a constant array, within atol
"""
x = np.asarray(x)
return (np.max(np.abs(x - x[0])) < atol and
(np.all((x > 0) == positive) if positive is not None else True)) | 0b272dd843adbd4eaa4ebbe31efe6420de05a6dd | 3,654,277 |
def estimate_M(X, estimator, B, ratio):
"""Estimating M with Block or incomplete U-statistics estimator
:param B: Block size
:param ratio: size of incomplete U-statistics estimator
"""
p = X.shape[1]
x_bw = util.meddistance(X, subsample = 1000)**2
kx = kernel.KGauss(x_bw)
if estimator ==... | 656b83eac9e522b1feb20a4b5b56649b9553ecb0 | 3,654,278 |
def query_yes_no(question, default="yes"):
"""Queries user for confimration"""
valid = {"yes": True, "y": True, "ye": True,
"no": False, "n": False}
if default is None:
prompt = " [y/n] "
elif default == "yes":
prompt = " [Y/n] "
elif default == "no":
prompt = "... | 58e9bba831155ca9f4d4879a5e960949757b0562 | 3,654,279 |
import base64
import binascii
def decode(password, encoded, notice):
"""
:type password: str
:type encoded: str
"""
dec = []
try:
encoded_bytes = base64.urlsafe_b64decode(encoded.encode()).decode()
except binascii.Error:
notice("Invalid input '{}'".format(encoded))
... | 5cf82bfbbe7eee458914113f648dadbe7b15dee8 | 3,654,280 |
def read_file_unlabelled_data(file_name):
"""
read_file_unlabelled_data reades from file_name
These files are to be in csv-format with one token per line (see the example project).
returns text_vector:
Ex:
[['7_7', 'perhaps', 'there', 'is', 'a_a', 'better', 'way', '._.'], ['2_2', 'Why', 'are', ... | f171ac6c4728aa67ef59b523acc0a006b3b4f16a | 3,654,281 |
from functools import reduce
def replace(data, replacements):
""" Allows to performs several string substitutions.
This function performs several string substitutions on the initial ``data`` string using a list
of 2-tuples (old, new) defining substitutions and returns the resulting string.
"""
r... | 37b2ad5b9b6d50d81a8c1bcded9890de3c840722 | 3,654,282 |
def fake_kafka() -> FakeKafka:
"""Fixture for fake kafka."""
return FakeKafka() | 35fdcf2030dda1cab2be1820549f67dc246cf88f | 3,654,283 |
from typing import Union
import operator
def rr20(prec: pd.Series) -> Union[float, int]:
"""Function for count of heavy precipitation (days where rr greater equal 20mm)
Args:
prec (list): value array of precipitation
Returns:
np.nan or number: the count of icing days
"""
assert ... | 4686eccac5be53b4a888d8bf0649c72e65d81bdb | 3,654,284 |
def get_neg_label(cls_label: np.ndarray, num_neg: int) -> np.ndarray:
"""Generate random negative samples.
:param cls_label: Class labels including only positive samples.
:param num_neg: Number of negative samples.
:return: Label with original positive samples (marked by 1), negative
samples (m... | 3cd0ad5c1973eff969330f014c405f39092b733b | 3,654,285 |
def G12(x, a):
"""
Eqs 20, 24, 25 of Khangulyan et al (2014)
"""
alpha, a, beta, b = a
pi26 = np.pi ** 2 / 6.0
G = (pi26 + x) * np.exp(-x)
tmp = 1 + b * x ** beta
g = 1.0 / (a * x ** alpha / tmp + 1.0)
return G * g | 6b84d5f5978a9faf8c9d77a2b9351f73f5717f48 | 3,654,286 |
def binomial(n, k):
""" binomial coefficient """
if k < 0 or k > n:
return 0
if k == 0 or k == n:
return 1
num = 1
den = 1
for i in range(1, min(k, n - k) + 1): # take advantage of symmetry
num *= (n + 1 - i)
den *= i
c = num // den
return c | 78910202202f749f8e154b074a55f6a5ddf91f64 | 3,654,287 |
def pagination(page):
"""
Generates the series of links to the pages in a paginated list.
"""
paginator = page.paginator
page_num = page.number
#pagination_required = (not cl.show_all or not cl.can_show_all) and cl.multi_page
if False: #not pagination_required:
page_range = []
e... | 60d90adfbeceab9d159652b641e60da8fa995954 | 3,654,288 |
def bubbleSort(arr):
"""
>>> bubbleSort(arr)
[11, 12, 23, 25, 34, 54, 90]
"""
n = len(arr)
for i in range(n-1):
for j in range(0, n-i-1):
if arr[j] > arr[j+1]:
arr[j], arr[j+1] = arr[j+1], arr[j]
return arr | 28bc9d505ef44a4b403c0f91a971cccf74644c5a | 3,654,289 |
def generate_kronik_feats(fn):
"""Generates features from a Kronik output file"""
header = get_tsv_header(fn)
return generate_split_tsv_lines(fn, header) | 8b98f346ef5d833e0bfb876a7985c8bb3ced905c | 3,654,290 |
import time
import sys
def regressor_contrast(model1:RegressorMixin,
model2:RegressorMixin,
test_data:pd.DataFrame,
label_data:pd.Series,
threshold:int=10)->pd.DataFrame:
"""Compute 11 metrics to compare a Sckit-learn regress... | 18c55de497009555a30ffd9a3a2b5c5a0f1b53ee | 3,654,291 |
def delete_product(uuid: str, db: Session = Depends(auth)):
"""Delete a registered product."""
if product := repo.get_product_by_uuid(db=db, uuid=uuid):
if product.taken:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Cannot delete prod... | 97aa45eec0ae98a58984f8ca97d584b5a715cba6 | 3,654,292 |
import functools
def CreateMnemonicsC(mnemonicsIds):
""" Create the opcodes arrays for C header files. """
opsEnum = "typedef enum {\n\tI_UNDEFINED = 0, "
pos = 0
l2 = sorted(mnemonicsIds.keys())
for i in l2:
s = "I_%s = %d" % (i.replace(" ", "_").replace(",", ""), mnemonicsIds[i])
if i != l2[-1]:
s += ",... | a20a01fbefc1175c24144753264edc938258cdca | 3,654,293 |
import math
def create_windows(c_main, origin, J=None, I=None, depth=None, width=None):
"""
Create windows based on contour and windowing parameters. The first
window (at arc length = 0) is placed at the spline origin.
Note: to define the windows, this function uses pseudo-radial and
pseudo-angul... | c5e3989b8f8f0f558cdc057b6f3bb9901c4363cf | 3,654,294 |
from bs4 import BeautifulSoup
def extractsms(htmlsms) :
"""
extractsms -- extract SMS messages from BeautifulSoup tree of Google Voice SMS HTML.
Output is a list of dictionaries, one per message.
"""
msgitems = [] # accum message items here
# Extract all conversations by searching ... | e31a66ae5ee56faf4eab131044c395fcd8de3a2a | 3,654,295 |
def load_ch_wubi_dict(dict_path=e2p.E2P_CH_WUBI_PATH):
"""Load Chinese to Wubi Dictionary.
Parameters
---------
dict_path : str
the absolute path to chinese2wubi dictionary.
In default, it's E2P_CH_WUBI_PATH.
Returns
-------
dict : Dictionary
a mapping between Chine... | e9297968b5dc4d1811659084e03ef0b2156c8a00 | 3,654,296 |
def middle_flow(middle_inputs: Tensor) -> Tensor:
"""
Middle flow
Implements the second of the three broad parts of the model
:param middle_inputs: middle_inputs: Tensor output generate by the Entry Flow,
having shape [*, new_rows, new_cols, 728]
:return: Out... | 80fedffbb6da2f3e0b99a931d66d593bf627bdbe | 3,654,297 |
def feature_extraction(sample_index, labels, baf, lrr, rawcopy_pred, data_shape, margin=10000, pad_val=-2):
"""
Extract features at sample index
:param sample_index: sample index
:param labels: break point labels
:param baf: b-allele frequency values
:param lrr: ... | 2b70229d3e4021d4a0cce9bf7dce2222956e299d | 3,654,298 |
def get_filename(file_fullpath):
"""
Returns the filename without the full path
:param file_fullpath:
:return: Returns the filename
"""
filename = file_fullpath.split("/")[-1].split(".")[0]
return filename | 903cb26c89d1d18c9ebafe1a468c7fa66c51f119 | 3,654,299 |
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