content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import logging
def calc_histogram_bins(value_array, bin_size=0.01):
"""Calculate histogram bins
Parameters
----------
etrf_array :
bin_size : float, optional
Histogram bin size (the default is 0.01).
Returns
-------
NumPy array
"""
bin_min = np.floor(np.nanmin(value_... | 2c33bf5f6658aa1c16f3055ed2dd6d344a88a4ad | 63,700 |
import random
def rand(plan, num=1):
"""Shuffle to generate new perm"""
def shuffle_tasks():
perm = plan.perm[:]
random.shuffle(perm)
return perm
return [shuffle_tasks() for _ in range(num)] | 5c4318e4be1330f0a78eeec30665626eb5802934 | 63,701 |
def get_mongo_conn(db="test"):
"""
use me like this:
collection = get_mongo_conn()["collection_name"]
collection.insert({})
"""
return MONGO_POOL[db] | 1ca41703988c4c60e44a2d667404cf40b3423399 | 63,702 |
def generate_manifest_header(manifest_id, key_size, manifest_type):
"""
Create a manifest header
:param manifest_id: Manifest id
:param key_size: Size of RSA key
:param manifest_type: Manifest type
:return Instance of a manifest header
"""
if manifest_type == manifest_types.PFM:
... | 08f5a05d89024a7b7067ca9005cd18e0bcd287a1 | 63,703 |
def stash_data(data, expire=None):
"""Stores data in an encrypted form and returns a key and a decryption secret."""
if expire is None:
expire = 60*60*24*90
try:
expire = int(expire)
assert expire > 0
except:
raise DAError("Invalid expire value")
return server.stash_d... | d51d649e596220957401bc4768277bef6e6c1146 | 63,704 |
import logging
def _sync_build_in_memory(build, result):
"""Syncs |build| state with swarming task |result|."""
# Task result docs:
# https://github.com/luci/luci-py/blob/985821e9f13da2c93cb149d9e1159c68c72d58da/appengine/swarming/server/task_result.py#L239
if build.status == model.BuildStatus.COMPLETED: # p... | 7246de3f925ec2740bef8d8a76baee4202d13725 | 63,705 |
def getMembershipDays(membership, onDate, houseDates=housedata.dates):
"""
Returns the number of days service in a membership up to the given date,
excluding periods when the House is in dissolution. The onDate is a
datetime.date.
"""
# Set the start date to the membership start date
startDate = convertMnisDat... | 4510cddea33a772ffa9999f26caae23dc70d67f6 | 63,706 |
def left_to_right_check(input_line: str, pivot: int):
"""
Check row-wise visibility from left to right.
Return True if number of building from the left-most hint is visible looking to the right,
False otherwise.
input_line - representing board row.
pivot - number on the left-most hint of the in... | e528f8d79f136b41fa92de5e9ac17de1fd200258 | 63,707 |
def parse_perseus_xml(files):
"""Parses the given XML files. Returns the parsed files as well as a list of files which couldn't be parsed at all."""
raw_texts = []
failed_to_parse = []
print("Parsing: ", end="")
for i, f in enumerate(files):
raw_text = ""
with open(f) as fp:
... | 8879a978a441db2fa4fc2183d627321903414693 | 63,708 |
def stetson_kernels(radius, nhalf, nbox, sigsq):
"""Stetson kernel generation."""
# Mask identifies valid pixels in convolution box
mask = np.zeros([nbox, nbox], dtype='int8')
g = np.zeros([nbox, nbox]) # Gaussian convolution kernel
row2 = (np.arange(nbox)-nhalf)**2
for i in range(nhalf+1):
... | 89acc82f196f73b0d41fdbb9f8507e05a2e32dce | 63,709 |
def good_discovery(status, device_name):
"""Checks the hdisk discovery results for a good discovery.
Acceptable LUA discovery statuses are :-
DEVICE_AVAILABLE: hdisk discovered on all the ITL paths and available.
DEVICE_IN_USE: hdisk discovered on all the ITL paths and is in-use by
the server.
... | 26e8130b39921faf84f94d6e243b09fffbee8b47 | 63,710 |
def okkOokOo(s):
""" okkookoo == PEP8, forced mixedCase by CodeWars """
return ''.join(chr(int(''.join(SCORE.get(a, '') for a in word), 2))
for word in s.split('?')) | b59b2c7d6445eb80f0d692c76943220e42c3d20a | 63,711 |
from typing import Optional
def multipletests(
srs: pd.Series,
method: Optional[str] = None,
nan_mode: Optional[str] = None,
prefix: Optional[str] = None,
) -> pd.Series:
"""
Wrap statsmodel's multipletests.
Returns results in a series indexed like srs.
Documentation at
https://ww... | 325085e348b8aae61228ca36550b8ea5871ed6b1 | 63,712 |
from unittest.mock import Mock
def _mock_channel(*, name, **kwargs):
"""Create a mock channel and associated DB record"""
if not Channel.objects.filter(name=name).exists():
ChannelFactory.create(name=name)
return Mock(display_name=name, **kwargs) | aa0003b47cc2b3382a89cb8e592df62ed91da142 | 63,713 |
from typing import List
def extract_strings(b: DeltaBytes, min_length, no_filter) -> List[DecodedString]:
"""
Extract the ASCII and UTF-16 strings from a bytestring.
"""
ret = []
for s in floss.strings.extract_ascii_strings(b.bytes):
if len(s.string) > MAX_STRING_LENGTH:
conti... | 477f33b1652e5ac25b81f9d70f35ad0aa22d302a | 63,714 |
def import_ori(filename):
""" Read in Filename for EJMT Tunnel mock model fault orientations """
#filename = 'Mock_FaultOrientations.csv'
""" Extract values and store in nested lists with filename identifier """
with open(filename, 'r') as f:
for x in range(1): # Skip header
nex... | ad9f8b5c158a372cacbe6f9449c358708af38aa2 | 63,715 |
import os
import ast
def get_version(module='win_tornado_terminals'):
"""Get version."""
with open(os.path.join(HERE, module, '__init__.py'), 'r') as f:
data = f.read()
lines = data.split('\n')
for line in lines:
if line.startswith('VERSION_INFO'):
version_tuple = ast.liter... | d862e3a2518ec60cc46f646af996b1be85c75bcd | 63,716 |
import torch
def quantile_regression_loss(input, target, tau, weight):
"""
input: (N, T)
target: (N, T)
tau: (N, T)
"""
input = input.unsqueeze(-1)
target = target.detach().unsqueeze(-2)
tau = tau.detach().unsqueeze(-1)
weight = weight.detach().unsqueeze(-2)
expanded_input, exp... | 808749c54df36a150c18fccd638bf0e85272a458 | 63,717 |
from typing import Tuple
def settings_credit_callback(update: Update, context: CallbackContext) -> Tuple[str, InlineKeyboardMarkup, int]:
"""Handles the settings_foto_cane callback.
Adds the user_id to the table of credited users, if it wasn't already there
Args:
update (Update): update event
... | 0e90285a52230260d778fe2f0300af21ece802a9 | 63,718 |
def get_spotting(ID):
"""
Function to get one spotting document from Elasticsearch
Params:
ID::str
id of the spotting document
Returns:
doc::dict
The document retrieved from ES
"""
if not ID:
return False
try:
global INDEX
ref... | 4d511758cb270f4cf023e40baabc534efadc8d98 | 63,719 |
def collect_to(to):
"""Collect audience to send email to from to object
Arguments:
to {dict} -- AppInterfaceEmailAudience_v1 object
Raises:
AttributeError: Unknown alias
Returns:
set -- Audience to send email to
"""
audience = set()
aliases = to.get('aliases')
... | 5525b6fae83ee54cad2f7fb716dbb394774f42ce | 63,720 |
import os
def rawdata_root():
"""Returns directory root for raw data, i.e. ``$LVM_SPECTRO_DATA``
Raises:
AssertionError: if these environment variables aren't set.
"""
assert 'LVM_SPECTRO_DATA' in os.environ, 'Missing $LVM_SPECTRO_DATA environment variable'
return os.environ['LVM_SPECTRO_... | 30dee82f52075e49d457eeb00d7e87d0a67935af | 63,721 |
def view_item(key):
""" View existing kanji """
kanji = unicode(key, 'utf-8')
# TODO: test if such item|kanji exists
radicals = store.get_radicals(kanji)
session = request.environ.get('beaker.session')
return render(
'home',
kanji=Peon(db).get_item(kanji),
radicals=radica... | 55628da11a5de7225a20795d6b3dd9db7e9cb17c | 63,722 |
from typing import List
from typing import Callable
def parametrize_over_experiments(models: List) -> Callable:
"""Parametrize a TestCase over different kind of experiments.
Args:
models: list of model descriptions. The ``TestCase`` will be
repeated for each of the entries in the list.
... | 351e2a7c8be2e5af61bcd8e06bee288e4504dac6 | 63,723 |
def open_opencart_admin_url(driver, request):
"""Get base URL and attend admin link"""
url = 'admin/'
return driver.get("".join([request.config.getoption("--address2"), url])) | 0c1d0493833b98869324bcbe65ee8f8888fd6c5c | 63,724 |
import copy
def GetFilteredEvents(events, filteredIndex):
"""
returns a class of filered events by index's wanted
:param events: class of events in current time
:param filteredIndex: indexs of events watned
:return: class of filtered events
"""
eventsPos = copy.deepcopy(events.po... | 0e5b93afd95cba439a620a85d8e88ec4ddc90f82 | 63,725 |
import copy
def build_single_tree(data, data_oob, y_i, y_nn_i, d_i, x_i, w_i, x_type,
x_values, x_ind, x_ai_ind, c_dict, mmm, n_min, alpha_reg,
node_table, pen_mult, regrf=False):
"""Build single tree given random sample split.
Parameters
----------
data : ... | 058858ce2df1be1f5e460ed1b54bd3b94acced52 | 63,726 |
import random
import base64
def password_encrypt(text: str, key: str):
"""translate from encrypt.js"""
_rds = lambda length: ''.join([random.choice('ABCDEFGHJKMNPQRSTWXYZabcdefhijkmnprstwxyz2345678') for _ in range(length)])
pad = lambda s: s + (len(key) - len(s) % len(key)) * chr(len(key) - len(s) % len(... | 17af8d702a536d48e67c40fab3455761746ae1f3 | 63,727 |
import json
def load_config(path: str):
"""
Loads a config file as a spec_config object
:param path: The path to the config file
:return: A loaded spec_config or None
"""
try:
with open(path, 'r') as f:
return json.load(f, cls=spec_decoder)
except:
return None | 06d77f27a10872cde047bb96ebcc28733fc763f7 | 63,728 |
from re import T
def index_fn(model_predict, input_var, target_var):
"""
Theano function returns an array containing boolean values that indicate
whether predicted label matches target_var
"""
index_temp = T.eq(T.argmax(model_predict, axis=1), target_var)
return theano.function([input_var,ta... | dc2ebcc25a5d61f5c12c661a91e12519336f9672 | 63,729 |
def change_encoding_improve(infile, outfile, enc1, enc2="utf-8",
process=None, fLOG=noLOG):
"""
Changes the encoding of a text file, removes quotes.
By default *process* is @see fn process_line
but the function has access to the distribution of the number of columns
in th... | 829aff6c56d765300a238d4d7c1b754793db4ed7 | 63,730 |
import torch
def compute_feature(block: torch.Tensor) -> list:
"""Compute features.
Args:
block (torch.Tensor): 2D image block.
Returns:
list: Features with length of 18.
"""
feat = []
alpha, beta_l, beta_r = estimate_aggd_param(block)
feat.extend([alpha, (beta_l + beta_r... | 0302d51a07050e516f92120181bc86912b20eaab | 63,731 |
def stop_es(bot, update):
"""Ends the automaton"""
logger.info('%s (@%s) stopped the bot', update.message.from_user.first_name, update.message.chat.username)
update.message.reply_markdown(st.strings["force_end"])
return bot.ConversationHandler.END | d920bbfc9986834fa5f869197d592ffc380a6538 | 63,732 |
import inspect
def get_caller_name(skip: int =3):
"""Get a name of a caller in the format module.class.method.
`skip` specifies how many levels of stack to skip while getting caller
name. skip=1 means "who calls me", skip=2 "who calls my caller" etc.
An empty string is returned if skipped levels exc... | c5e26ee7533f6686712ec1a6e5088eeb67a8e0af | 63,733 |
def pdf_gaussian_algebraic(
returns: np.ndarray, K: float, L: float, N: float, Lambda: float
) -> np.ndarray:
"""Computes de one dimensional Gaussian-Algebraic PDF.
:param returns: numpy array with the returns values.
:param K: number of companies.
:param L: shape parameter.
:param N: strength ... | 6508ee67164ce996c4502d6f710e1fb7be690a2b | 63,734 |
def documentation_tests(session):
"""Run documentation tests."""
return docs(session, batch_run=True) | 058f31d789491f392e0eee06e219298519405ac4 | 63,735 |
from typing import List
from typing import Tuple
from typing import Any
def paras_to_sents(paras: List[str],) -> Tuple[List[Any], List[Any], str]:
""" sent-segment paras sents list, slice_list and lang
"""
sents: List[str] = []
slice_list: List[slice] = []
lang: str = Text(" ".join(paras[:30])).de... | 7ea6e9123acc749d3c0de5e7744980c2ae7172e9 | 63,736 |
def export(signature, **kws):
"""
Construct a decorator that takes a function and exports one
A signature is a string with
name ret_type(arg_type, argtype, ...)
"""
name, restype, argtypes = _process_sig(signature)
return _internal_export(name=name, restype=restype, argtypes=argtypes, **kw... | faef680517a36f2759cc4c825f9e60ffe6ada335 | 63,737 |
def multi_generator(gan, z, num, share_params = True, reuse = False):
"""
Args:
gan : instance of a generative adversarial network
num: Number of the generator
reuse : Whether you want to reuse variables from previous
share_params : Whether weights are tied in initial layers... | 2c998300aa0c9331524286bf9d41b06443bae9d0 | 63,738 |
import binascii
import re
import struct
import pathlib
def ProcessPlugxXORFile(inFile,PlugxData,pos):
"""
IN: PlugX data to decrypt.
OUT: Bool True or False
Description:
Decrypts PlugX DAT file and assumes files are not compressed
"""
PlugX_Decrypted = Decrypt_XOR( PlugxData,pos )
if ... | a53a17bde0ed1942cb76f14f58cfe7fb125cda68 | 63,739 |
def count_features_type(types, include_binary=False):
""" Counts two or three different types of features
(binary (optional), categorical, continuous).
:param types: list of types from get_type
:returns a tuple (binary (optional), categorical, continuous)
"""
if include_binary:
return (
... | 4158122256c9a407f58987d278657e4a006e6a13 | 63,740 |
def CRy(control: int, target: int, angle: float) -> QCircuit:
"""
Convenience initialization CRy (controlled Pauli Y Rotation)
Parameters
----------
control: int
control qubit
target: int
target qubit
angle:
Hashable type (will be treated as Variable) or Numeric type... | e9bd8dd87a32f7ca604c0a05ebb81309176308b5 | 63,741 |
def _with_iteration(fn):
"""Uses iteration to produce vmap-like output."""
def wrapper(*args):
outputs = []
# Iterating over the first axis.
for inputs in strict_zip(*args):
outputs.append(fn(*inputs))
return jax.tree_util.tree_multimap(lambda *x: jnp.stack(x), *outputs)
return wrapper | 00855ddb1d85304af38152e7961d8b89ef5c09f8 | 63,742 |
def optimize(w_p, w_a, w_f, w_e, corpus_weights, scenario, char_set, startsolution="", fixation_constraints=1,
coherence_constraints=1, capitalization_constraints=1):
"""
Optimizes the pre-defined scenario with the given weights.
Parameters:
w_p, w_a, w_f, w_e: weights for the individu... | 34439faa3bef324d3658f64dbdc680eb39cbca7d | 63,743 |
import torch
def sequence_cross_entropy_with_logits(logits, targets, mask, label_smoothing, reduce):
# type: (Tensor, Tensor, Tensor, float, bool)-> Tensor
"""
label_smoothing : ``float``, optional (default = 0.0)
It should be smaller than 1.
"""
# shape : (batch * sequence_length, num_cla... | db05c49a15287999a8864fe8b789d671495e82b3 | 63,744 |
def raster_pixel_count(dataset_uri):
"""Determine how many of each unique pixel lies in the dataset (dataset)
dataset_uri - a GDAL raster dataset
returns - a dictionary whose keys are the unique pixel values and
whose values are the number of occurrences
"""
LOGGER.debu... | eb930ae4b1f45a49eb3900d1a91d77679d03b805 | 63,745 |
def areafiltering_remove_larger_objects_binary(image, kernel=None, n=None):
"""
Removes all objects in the image that have an area smaller than
the threshold specified.
Additional Arguments
--------------------
n : int
Specifies the threshold.
"""
nb_components, output, s... | 9e64432afa47bbb8e39455abd83ced27b2504502 | 63,746 |
import argparse
def get_args() -> argparse.Namespace:
"""Parse command-line arguments."""
parser = argparse.ArgumentParser(prog="rhasspy-profile")
parser.add_argument(
"--debug", action="store_true", help="Print DEBUG messages to the console"
)
parser.add_argument(
"--profile", "-p... | 05c408d7702cea588c910ed3afaeff1acd237268 | 63,747 |
def dsdlogdp(dp, n, gm, gsd):
"""
Discrete PDF for a surface-weighted lognormal
particle size distribution.
:param dp: Particle diameters at which to evaluate
the PDF in building the discrete model.
:type dp: numpy array
:param n: The area under the curve of the continuous PDF
... | ee268df8370a35aada1e3a03c4065e521142e2ff | 63,748 |
def is_pandas_module(fullname: str) -> bool:
"""Check if a fully qualified name is from the pandas module"""
return fullname.startswith("pandas.") | 0becdbfd7c1c4f5b7990cbc0466a6e45f25acb14 | 63,749 |
import io
def starting_metadata(overrides):
"""Fake the xdata associated with a brand new submission, adding in `overrides` to tweak test cases."""
d = io.get_default_metadata()
d["job_id"] = "fake_job_id"
d.update(overrides)
return d | 75ee436b3ef65975d04920ad75ba972af4d39294 | 63,750 |
def validate_port_operation(session, row):
"""Validate port operation based on dependencies.
Validate port operation depending on whether it's dependencies
are still in 'pending' or 'processing' state. e.g.
"""
if row.operation in (sdn_const.POST, sdn_const.PUT):
network_dict = jsonutils.lo... | 41f19871ce074535a50d50242298fa547b7ebdd0 | 63,751 |
def sigmoid(z):
"""The sigmoid function"""
try:
z=1 / (1 + np.exp(-z))
except OverflowError:
pass
# print(z)
# sys.exit()
return z | 8dbf9418b97de631fb1081f618ceabfaa2d0ef8d | 63,752 |
import os
import json
def set_json_app_argument(config_path, key, value):
"""Writes kv pair to json argument file
Arguments:
config_path {string} -- path to json config file, example: /var/run/appconfig/streaming_args.json
key {string} -- the name of the argument to set
value {any} --... | 149a013c57db130161612cd3070ceb393ec1a6e7 | 63,753 |
from datetime import datetime
import os
def time_to_string():
"""Converts the current time to string so it can be used to save the file."""
now = datetime.datetime.now() # Gives current time.
return f"C:\\Users\\{os.getlogin()}\\Pictures\\Screenshots\\{datetime.datetime.strftime(now, '%Y%m%d_%H%M%S')}.png... | 69663ef21c0f45277c90fb6fadd63e5a1d95bcd3 | 63,754 |
from functools import reduce
def unitary_to_monodromy_coordinate(unitary):
"""
Given a unitary matrix, produces its alcove coordinate.
"""
unitary = unitary * np.linalg.det(unitary) ** (-1 / 4)
sysy = np.array([
[0, 0, 0, 1],
[0, 0, -1, 0],
[0, -1, 0, 0],
[1, 0... | a3901f9f814c3bf09be213288f8cecacd4aab9b0 | 63,755 |
from typing import Mapping
def _add_empty_values(step: rlds_types.Step,
spec: Mapping[str, tf.TensorSpec]) -> rlds_types.Step:
"""Adds zero elements to step for the keys in spec not present in step.
Args:
step: Dictionary representing a Step.
spec: Tensor spec.
Returns:
Dicti... | d4aba17659aa84646d7c214b8447a16432f6b2f4 | 63,756 |
import pickle
import base64
def merge_cart_cookie_to_redis(request, response, user):
"""
用户登录时合并购物车数据到redis方法
:param request: 请求的request对象
:param response: 返回的响应response对象
:param user: 登录的用户对象
:return: response对象
"""
# 从cookie中取出购物车数据,
cookie_cart_str = request.COOKIES.get('cart')
... | 039d0e706f55ee7a4cd04361a68a33ef1f7b67bb | 63,757 |
import itertools
def _schedule_menu(update, context): # pylint: disable=unused-argument
"""Present the user the scheduling options"""
chat_id = update.callback_query.message.chat_id
comics = database_query("SELECT name FROM sources")
buttons = []
for name in itertools.chain.from_iterable(comics)... | 7cb1b81771f0ef4d60f4b31d0695aa2c9a1fd23d | 63,758 |
from re import A
import io
def pure(a: A) -> Resource[R, E, A]:
"""
A Resource that always returns the same constant.
"""
return Resource(io.pure((a, noop_close))) | 10900bd6582d0489cf63d0b9f667d6ddb6819d5a | 63,759 |
def find_func(identifier: str):
"""Find the function of an identifier that has been registered"""
return [k for k, v in _AI_REGISTRY.items() if v == identifier][0] | 3c9451ca8596d7c23ee5c360d9cd6bc9d050793a | 63,760 |
def _Scan():
"""Checks that license meta-data is present for all third-party code.
Returns:
Whether the check succeeded.
"""
third_party_dirs = _FindThirdPartyDirs()
# First, check designated third-party directories using src/tools/licenses.py.
all_licenses_valid = True
for path in sorted(third_part... | 3fb2750dcc65d6a8187e32166e4a6e155e1ee0d6 | 63,761 |
def set_mapping(joystick, mapping):
"""Set the button mapping.
Note:
Hat keys should have a set value for the proper quadrant.
Args:
joystick (Joystick/str): Joystick object or String GUID
mapping (dict): Dictionary of name: Key values to map to the joystick/game controller.
R... | 065988362e34bb25a4d3013f5a62df5abdfe7403 | 63,762 |
import os
def mkdir_slashfix_open(filename, mode):
"""Like common.slashfix_open(), but make directories as needed."""
real_filename = common.slashfix(filename)
directory = os.path.dirname(real_filename)
os.makedirs(directory, exist_ok=True)
return open(real_filename, mode) | 9c43653f0108988e63f1a290f583f9049002aa82 | 63,763 |
def create_raster(*args, **kwargs):
"""Shortcut for `Dataset().acreate_raster`
>>> help(Dataset.create_raster)
See Also
--------
- :py:func:`Dataset.create_raster`
- :py:meth:`Dataset.acreate_raster`
"""
return Dataset().acreate_raster(*args, **kwargs) | c6795876482d2c515505123a203675446ec30675 | 63,764 |
from typing import Optional
import random
import io
def random_digits(length: int = 32, base: int = 10, upper: bool = False, rnd: Optional[random.Random] = None) -> str:
"""
Overview:
Create random digits.
Arguments:
- length (:obj:`int`): Length of the digits, default is 32.
- ba... | 680a5201e183cf57e56adea1e79718026beda052 | 63,765 |
def process_manual_category(tag, manual_tag):
"""
处理category信息
"""
replace_tag = str(manual_tag)
if str(manual_tag) in ["1", "1.0"]:
replace_tag = tag
if "[" and "]" not in replace_tag:
tag_list = replace_tag.split(",")
else:
tag_list = eval(replace_tag)
return... | 8303cd69df4c5dce47a2dcc4546ef1490f2b2f1b | 63,766 |
def squeeze_first(inputs):
"""Remove the first dimension in case it is singleton."""
if len(inputs) == 1:
inputs = inputs[0]
return inputs | c2c0cabc873baf88ce7673f2c8889fedce0f05da | 63,767 |
from rpy2.robjects import numpy2ri
import copy
def pen_rf_importance(X, y, cost_vec=None, cost_param=0, num_features_to_select=None,
imp_type="impurity", min_samples_leaf=1,
n_estimators=500, rf_importance_vec=None, is_disc=None):
""" Cost-based feature ranking with pen... | 637095abac615829d5167eb9185c43ea039c4598 | 63,768 |
def estimate_best_parameters(grid, best_grid_pars=None):
"""
Estimate the best parameters by interpolating the grid
parameters:
============
- grid: pd.DataFrame
Contains the full grid. Get this by calling read_chi2_output()
- best_grid_pars: pd.Series or dict
... | 2aa1be84de6f8c8a1000d86ae6bae903743bf1fd | 63,769 |
def get_total_distance_of_path(path, table):
"""
Calculates the total distance of an individual bee's path.
Terminates at starting node to complete cycle.
"""
# Creates a copy of path, puts head at end of list.
# Zip lists to create pairs of neighbor coords,
# will create a cycle that termin... | d6c655b7bbed075dc8323d5d60ee128b8693d792 | 63,770 |
def shift_point(point, latitude_shift_km, longitude_shift_km):# -> tuple(float, float):
"""Shifts the coordinates of a given point.
Args:
point (tuple): Starting point as (latitude, longitude), in degrees
latitude_shift_km (float): Latitude offset in kilometers
longitude_shift_km (float... | 36544b82d10e3bae93f343757fdcd654f7f4a78b | 63,771 |
import time
def timing(func):
"""
Wrapper for class instance methods enabling the timing of execution.
Important for measuring speed and performance measurement.
Parameters
___________
func : func
Function to be wrapped and timed following execution.
Returns
________
wrap... | d84d51959be1def284fb7d6a6264c4c1138acd85 | 63,772 |
from typing import Dict
import torch
from typing import Tuple
def compute_accuracy(output_tensors_by_model: Dict[str, torch.Tensor],
target: torch.Tensor,
topk: Tuple = (1,),
) -> Dict[str, Dict[str, torch.Tensor]]:
"""Computes the accuracy over the k... | 68228b68e26f502f162df6fa902401c2e5cda981 | 63,773 |
def is_valid_string_minsize(param, minsize=None, required=True):
"""Checks if the parameter is a valid string and his size is more than minsize.
If the parameter minsize is None than the size is ignored
If the parameter required is True than the string can not be None
@param param: Value to be validate... | b1ed83ef3b44cf94f02fadf31f42ac9fe40679fa | 63,774 |
from typing import Counter
def removeInsignificantNodes(dataframe,filename = None,csvSeparator = ';'):
"""
Removes nodes that occur only once, as they are just the supposed ends of given tube.
Parameters
----------
dataframe : pandas.DataFrame()
Dataframe containing arranged da... | 0aa345d257aba84e67a73845a795f820de9190dd | 63,775 |
def _phaseSpaceThresh(u):
"""
Implements the Goring+Nikora2002 despiking method, with Wahl2003
correction.
"""
if u.ndim == 1:
u = u[:, None]
u = np.array(u) # Don't want to deal with marray in this function.
Lu = (2 * np.log(u.shape[0])) ** 0.5
u = u - u.mean(0)
du = np.zer... | dd70d5fae352fedc6a6e9519697747d99645aa1e | 63,776 |
import multiprocessing
def extract_slice(data, trans, pshape):
"""optional params meaning - see dice() above
Algorithm:
1. find intersections of the plane with the data box edges
2. for these pts, find axis-oriented b-box
3. find the trans (A,T) from R2 to R3, like X' = AX + T
use (0,0), (0... | 892796f0bae83538c1ea78055c7ce59e3512dd28 | 63,777 |
def run_command(cmd_name):
"""
Executes a single Waf command. Called by :py:func:`waflib.Scripting.run_commands`.
:param cmd_name: command to execute, like ``build``
:type cmd_name: string
"""
ctx = Context.create_context(cmd_name)
ctx.log_timer = Utils.Timer()
ctx.options = Options.options # provided for conv... | 6c0a6b4173b7ea5c0fb63c9a8cdd9c9687771fa5 | 63,778 |
import requests
def exists(path):
"""Makes a head request to the given path and returns a status_code"""
try:
resp = requests.head(path)
logger.debug('HEAD request to remote server. Response status_code: %s', resp.status_code)
return resp.status_code < 400
except Exception:
... | 29637cdb291e79c6c4a2c921dc6280b86727c984 | 63,779 |
from analysis_functions import unique
from numpy import median,std,cast,float32,any,where
def images_zinger_replaced(images,sigma=5.730729):
"""Returns images_zr after replacing zingers in images with median values.
Zingers are identified according to statistical criteria. Also returns the
indices for ima... | 2ece2c42f4cdcadf4d981de83b0b32d0ad504e61 | 63,780 |
def get_constant(name):
"""Use this to get the value of a VBA constant.
@param name (str) The name of the VBA enum constant to get.
@return (int) The enum value if the given name names a VBA enum
constant, None if not.
"""
name = safe_str_convert(name).lower()
if is_constant(name):
... | b8a165397fc7ac02462f5319bdc3d490c12daab6 | 63,781 |
def _create_line2d_collection(coords, indices, infos=None, picker=False, **kwargs):
"""
Generic function to create a LineCollection from coordinates.
:param coords: list of line coordinates (list should look like this: \
`[[(x11, y11), (x12, y12), (x13, y13), ...], [(x21, y21), (x22, x23), ...], ..... | d2af45a15f4d180bcca4b144173e00042e2dfd0c | 63,782 |
import os
def resize_factor(img, factors, interpolation="auto"):
"""Resize input image to a new size using resize factors along x and y axes.
Inputs:
img = RGB or grayscale image data
factors = Resizing factors (width, height). E.g. (0.5, 0.5)
interpolation = Interpolation method ... | b4b507c9de23f209d542ce8bc9a141839a06ee17 | 63,783 |
import pickle
import math
def fitting_shape_coefficients(filename, bounds='Default', n=5,
return_data=False, return_error=False,
optimize_deltaz=False, solver='gradient',
deltaz=None, objective='hausdorf',
... | d62d4186d3892af622eae1edbe5b64572197d6ae | 63,784 |
def find_executable(executable):
"""Return the full path to an executable searching PATH."""
for path in _find_executables(executable):
return path
return None | 7beca9f748fe22b0dfb982cb880e6ad858b37faf | 63,785 |
def uniformCostSearch(problem):
"""Search the node of least total cost first."""
nv = [] # Initialize empty array for visited nodes
s = util.PriorityQueue() # Initialize priority queue for fringe
s.push((problem.getStartState(), ()),... | c4769a250d618eae055d39b0fe390793f86eca36 | 63,786 |
def format_with_bold(s_format, data=None):
"""
Returns the string with all placeholders preceeded by '_b' replaced
with a bold indicator value;
:param: s_format: a string format;
if contains '_b{}b_' this term gets bolded.
:param: s: a string or value
Note 1: '... _b{}; s... | 07fd31eaeb5cfd4a39d256e3c2d48fe3a97a9564 | 63,787 |
def measure_spike_trains_correlation_coefficient_multi(spike_train_dict, std_val=5.0, sample_period=0.01):
"""
:param spike_train_dict: dictionary where every key is the name of a cell and every value is a numpy array with the
spike times in msec
:param std_val: standard deviation used to create th... | 40d9b00f240191ec587c6888928aaa2f783feee0 | 63,788 |
def readData(input_file):
""" Read data from an input file. Each line of the file contains tuples of the form
(x,y)
x is a dictionary of the form:
{ "feature1": value, "feature2":value, ...}
and y is a binary value +1 or -1.
The retu... | 73647a64259e6f1a3c5535e51f44b48fc8054ef7 | 63,789 |
from typing import Dict
from typing import Any
from typing import Union
from typing import List
import csv
def load_dataclass_dict_from_csv(
input_csv_file_path: str,
dataclass_class: type,
dict_key_field: str,
list_per_key: bool = False,
) -> Dict[Any, Union[Any, List[Any]]]:
"""
Args:
... | fb6b39b60fd15b430d4f39f07110c4f0da299ab6 | 63,790 |
def is_part_of_word(word_fragment, wordlist):
"""Returns True if word_fragment is the beginning of a word in wordlist.
Returns False otherwise. Assumes word_fragment is a string."""
for word in wordlist:
is_part_of_list = word_fragment == word[:len(word_fragment)]
if is_part_of_list == True:... | 54f572655fe7bb383cb00d732b57d85156b5f528 | 63,791 |
import re
def plot_scatter(dfc, dfm, object_level_directory,
object_level_files, filename='scatter.pdf'):
"""Plots BrdU and pH3 scatter and applies gating based on
average gating of control wells
Parameters
----------
dfc : pandas dataframe
table containing well level... | 26d3a608b283ac9cd20668cc40b72e3d1b4fb230 | 63,792 |
def render_output(data):
"""Print the formatted output for the list
"""
output = ['[Dataduct]: ']
output.extend(data)
return '\n'.join(output) | 5e3bee31890f682eca6aa03128dbf8d51e2fe473 | 63,793 |
import os
import subprocess
import sys
import re
def getSectionInfo(binaryPath, filterSections=None):
"""This function takes a path to an ELF binary as parameter, executes
readelf on it, parsing the output, building then returning a list of
sections objects
filterSections is a list of sections to consider (i.e. t... | 095605811e619c32a75417819407a1b5dc9d84b0 | 63,794 |
import torch
def processGroundTruth(bounding_box, input_shape, cell_map_shape):
"""Normalizes and computes the offset to the grid corner"""
# Construct normalized, relative ground truth
cell_corners = getGrid(input_shape, cell_map_shape)
cell_shape = input_shape / cell_map_shape
# bounding_box[0, ... | 8107a0337c36b3b3e360407ded9d782b0b5cd37e | 63,795 |
from typing import List
def simplify_linear_inequalites(iset: List[Rel]):
"""
:param iset: linear inequalities set to be simplified ( redaundent inequalities
would be removed).
:return: simplified set of inequalities.
>>> eq1 = x + y >= 10
>>> eq2 = x + y >= 20
>>> eq3 = x + y <= 30
>>... | 65a35a1921eb12c982a6d1b52843fb0a6fbcdbbc | 63,796 |
import json
def loads(string, **kwargs):
"""
reconstruct configuration object from json string
"""
dict_from = json.loads(string, **kwargs)
return _decode(dict_from) | b6db399002af5db59c8a00338d222ffd699eb189 | 63,797 |
import urllib
def remote_follow(request):
"""direct user to follow from remote account using ostatus subscribe protocol"""
remote_user = request.POST.get("remote_user")
try:
if remote_user[0] == "@":
remote_user = remote_user[1:]
remote_domain = remote_user.split("@")[1]
ex... | e49abe36f6a2da6e3b5f2378c187decc31a7304b | 63,798 |
def create_shift_permission(employee_id: str = None, permission_type: str = None, date: str = None, reason: str = None, leaving_time: str = None, arrival_time: str = None) -> dict:
"""This method creates a shift permission for a given employee.
Args:
employee (str): employee id
permission_type ... | 3e359e404847638f1d2e718588e0ad5543ad658a | 63,799 |
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