content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import base64
def int_to_base64(i: int) -> str:
""" Returns a 12 char length representation of i in base64 """
return base64.b64encode(i.to_bytes(8, 'big')) | 5bd7bb032926a8f429d766632c2ef2af9ee01edc | 16,514 |
def payment_provider(provider_base_config):
"""When it doesn't matter if request is contained within provider the fixture can still be used"""
return TurkuPaymentProviderV3(config=provider_base_config) | d6439a5ef097350682a2e17ccc41aeba1310a78a | 16,515 |
import re
def gradle_extract_data(build_gradle):
"""
Extract the project name and dependencies from a build.gradle file.
:param Path build_gradle: The path of the build.gradle file
:rtype: dict
"""
# Content for dependencies
content_build_gradle = extract_content(build_gradle)
match =... | dd802b8fedb682493a1978ae6cd60be9706580ff | 16,516 |
from typing import Sequence
import torch
def stack_batch_img(
img_tensors: Sequence[torch.Tensor], divisible: int = 0, pad_value: float = 0
) -> torch.Tensor:
"""
Args
:param img_tensors (Sequence[torch.Tensor]):
:param divisible (int):
:param pad_value (float): value to pad
:return: ... | 9952965a89688d742a3342804062cb8051f47f54 | 16,517 |
from evo.core import lie_algebra as lie
def convert_rel_traj_to_abs_traj(traj):
""" Converts a relative pose trajectory to an absolute-pose trajectory.
The incoming trajectory is processed elemente-wise. Poses at each
timestamp are appended to the absolute pose from the previous timestamp.
... | 57e4972f5bc4ea67bf62b88ea87fc5df8dda0d7c | 16,518 |
def remove(handle):
"""The remove action allows users to remove a roommate."""
user_id = session['user']
roommate = model.roommate.get_roommate(user_id, handle)
# Check if roommate exists
if not roommate:
return abort(404)
if request.method == 'POST':
model.roommate.delete_roo... | b1a279989d3cb463d54c8559352f2ae67f198b40 | 16,519 |
def maxsubarray(list):
"""
Find a maximum subarray following this idea:
Knowing a maximum subarray of list[0..j]
find a maximum subarray of list[0..j+1] which is either
(I) the maximum subarray of list[0..j]
(II) or is a maximum subarray list[i..j+1] for some 0 <= i <= j
... | a991ca09c0594b0d47eb4dd8be44d093d593cd36 | 16,520 |
def get_merged_threadlocal(bound_logger: BindableLogger) -> Context:
"""
Return a copy of the current thread-local context merged with the context
from *bound_logger*.
.. versionadded:: 21.2.0
"""
ctx = _get_context().copy()
ctx.update(structlog.get_context(bound_logger))
return ctx | 03c2689fd71542c7c007512fb4c2bf76a841a7bc | 16,521 |
def sort_cipher_suites(cipher_suites, ordering):
"""Sorts the given list of CipherSuite instances in a specific order."""
if ordering == 'asc':
return cipher_suites.order_by('name')
elif ordering == 'desc':
return cipher_suites.order_by('-name')
else:
return cipher_suites | 5a554ba1e2e4d82f53f29c5a1c2f4d311f538889 | 16,522 |
def make_1D_distributions(lims, n_points, all_shifts, all_errs, norm=None, max_shifts=None, seed=None):
"""
Generate 1D distributions of chemical shifts from arrays of shifts and errors of each distribution
Inputs: - lims Limits of the distributions
- n_points Number o... | 87c48b80dc395b4423b88fcbb3307dd53655333e | 16,523 |
def fill_column_values(df, icol=0):
"""
Fills empty values in the targeted column with the value above it.
Parameters
----------
df: pandas.DataFrame
icol: int
Returns
-------
pandas.DataFrame
"""
v = df.iloc[:,icol].fillna('').values.tolist()
vnew = fill_gaps(v)
d... | 158939f6436a4c9b5a13a18567ee6061e71df51c | 16,524 |
import torch
def reward(static, tour_indices):
"""
Euclidean distance between all cities / nodes given by tour_indices
"""
# Convert the indices back into a tour
idx = tour_indices.unsqueeze(1).expand(-1, static.size(1), -1)
tour = torch.gather(static.data, 2, idx).permute(0, 2, 1)
# Ens... | f7197bcfb3699cafa4df3c1430b4f9ee1bf53242 | 16,525 |
def valid_review_queue_name(request):
"""
Given a name for a queue, validates the correctness for our review system
:param request:
:return:
"""
queue = request.matchdict.get('queue')
if queue in all_queues:
request.validated['queue'] = queue
return True
else:
_t... | fc6ef2fb728b18ce84669736f0e4ec1f020ea2bf | 16,526 |
def get_best_straight(possible_straights, hand):
""" get list of indices of hands that make the strongest straight
if no one makes a straight, return empty list
:param possible_straights: ({tuple(str): int})
map tuple of connecting cards --> best straight value they make
:param hand: (set(s... | f2a470ef3033cac27cb406702daead42d59683aa | 16,528 |
from django.shortcuts import render_to_response, RequestContext
def stats(request):
"""
Display statistics for the web site
"""
views = list(View.objects.all().only('internal_url', 'browser'))
urls = {}
mob_vs_desk = { 'desktop': 0, 'mobile': 0 }
for view in views:
if is_mobi... | 3b63250e6ce3c9ddd09ec8d19c9961b22bfab62a | 16,529 |
def build_argparser():
"""
Builds argument parser.
:return argparse.ArgumentParser
"""
banner = "%(prog)s - generate a static file representation of a PEP data repository."
additional_description = "\n..."
parser = _VersionInHelpParser(
description=banner,
epilog=a... | f33679c82a1499db83caf3473b0e5403ebfa52fe | 16,530 |
def abc19():
"""Solution to exercise C-1.19.
Demonstrate how to use Python’s list comprehension syntax to produce
the list [ a , b , c , ..., z ], but without having to type all 26 such
characters literally.
"""
a_idx = 97
return [chr(a_idx + x) for x in range(26)] | c9bb948ad57ddbc138dfbc0c481fabb45de620ba | 16,531 |
def filter_words(data: TD_Data_Dictionary):
"""This function removes all instances of Key.ctrl from the list of keys and
any repeats because of Press and Realese events"""
# NOTE: We may just want to remove all instances of Key.ctrl from the list and anything that follows that
keys = data.get_letters()
... | fb34e1758c83af0e30b5ae807a3f852ab7e3be29 | 16,533 |
from typing import Dict
def check_url_secure(
docker_ip: str,
public_port: int,
*,
auth_header: Dict[str, str],
ssl_context: SSLContext,
) -> bool:
"""
Secure form of lovey/pytest/docker/compose.py::check_url() that checks when the secure docker registry service is
operational.
Ar... | ebdc8f4d175f3be70000022424382f71d9fd73b5 | 16,534 |
def ResNet101(pretrained=False, use_ssld=False, **kwargs):
"""
ResNet101
Args:
pretrained: bool=False or str. If `True` load pretrained parameters, `False` otherwise.
If str, means the path of the pretrained model.
use_ssld: bool=False. Whether using distillation pretrain... | 0277c59f9b60d5c6127fb1021eb71b10691bd0f8 | 16,535 |
def LineTextInCurrentBuffer( line_number ):
""" Returns the text on the 1-indexed line (NOT 0-indexed) """
return vim.current.buffer[ line_number - 1 ] | 8c3b51a48e25e8955a00d89619da9e191612861a | 16,536 |
def imported_instrumentor(library):
"""
Convert a library name to that of the correlated auto-instrumentor
in the libraries package.
"""
instrumentor_lib = "signalfx_tracing.libraries.{}_".format(library)
return get_module(instrumentor_lib) | db26277b23f989d8d5323c7c6bde0905b1e2f5ef | 16,537 |
from datetime import datetime
def parse_runtime(log_file):
""" Parse the job run-time from a log-file
"""
with open(log_file, 'r') as f:
for line in f:
l0 = line.rstrip("\n")
break
l1 = tail(log_file, 1)[0].rstrip("\n")
l0 = l0.split()[:2]
l1 = l1.split()[:2]
... | 75a5a80409918779173eb1e80d6b3f95abf242cb | 16,539 |
def calculateEMA(coin_pair, period, unit):
"""
Returns the Exponential Moving Average for a coin pair
"""
closing_prices = getClosingPrices(coin_pair, period, unit)
previous_EMA = calculateSMA(coin_pair, period, unit)
constant = (2 / (period + 1))
current_EMA = (closing_prices[-1] * (2 / (1... | ec884f89c2e8e64ada4384767251d6722c7b63c8 | 16,540 |
def euler_method(r0, N):
"""
euler_method function description:
This method computes the vector r(t)'s using Euler's method.
Args:
r0 - the initial r-value
N - the number of steps in each period
"""
delta_t = (2*np.pi)/N # delta t
r = np.zeros((5*N, 2)) # 5Nx... | 6ac3deae5cdb5ce84fa19433b55de80bf04ddf47 | 16,541 |
def main_menu(found_exists):
"""prints main menu and asks for user input
returns task that is chosen by user input"""
show_main_menu(found_exists)
inp = input(">> ")
if inp == "1":
return "update"
elif inp == "2":
return "show_all"
elif inp == "3":
return "s... | 61d0bda6a1ddf8bf70a79ff6e7488601d781c5fc | 16,542 |
def fromPsl(psl, qCdsRange=None, inclUnaln=False, projectCds=False, contained=False):
"""generate a PairAlign from a PSL. cdsRange is None or a tuple. In
inclUnaln is True, then include Block objects for unaligned regions"""
qCds = _getCds(qCdsRange, psl.qStrand, psl.qSize)
qSeq = _mkPslSeq(psl.qName, p... | f1da225d53f36abf5d10589077de934f13c1ca2a | 16,543 |
from typing import Optional
def get_graph(identifier: str, *, rows: Optional[int] = None) -> pybel.BELGraph:
"""Get the graph surrounding a given GO term and its descendants."""
graph = pybel.BELGraph()
enrich_graph(graph, identifier, rows=rows)
return graph | fc004ebd3cdfa70edd01b611987dfd48306ceb80 | 16,545 |
def root_histogram_shape(root_hist, use_matrix_indexing=True):
"""
Return a tuple corresponding to the shape of the histogram.
If use_matrix_indexing is true, the tuple is in 'reversed' zyx
order. Matrix-order is the layout used in the internal buffer
of the root histogram - keep True if reshaping t... | 8df83a84f0a3b12bab248949042cd2df5df6f53e | 16,548 |
from typing import Union
def get_weather_sensor_by(
weather_sensor_type_name: str, latitude: float = 0, longitude: float = 0
) -> Union[WeatherSensor, ResponseTuple]:
"""
Search a weather sensor by type and location.
Can create a weather sensor if needed (depends on API mode)
and then inform the r... | b4feb0a75709d1bf27378df6d90420c74e36646c | 16,550 |
import six
def _npy_loads(data):
"""
Deserializes npy-formatted bytes into a numpy array
"""
logger.info("Inside _npy_loads fn")
stream = six.BytesIO(data)
return np.load(stream,allow_pickle=True) | 5e9ee0a0d41403af0a8e1ed41f6d15a677d82c44 | 16,551 |
import dateutil
def parse_string(string):
"""Parse the string to a datetime object.
:param str string: The string to parse
:rtype: `datetime.datetime`
:raises: :exc:`InvalidDateFormat` when date format is invalid
"""
try:
# Try to parse string as a date
value = dateutil.parser... | 6db2edad31f1febced496c92bfb2d7d76761850a | 16,552 |
def get_elfs_oriented(atoms, density, basis, mode, view = serial_view()):
"""
Outdated, use get_elfs() with "mode='elf'/'nn'" instead.
Like get_elfs, but returns real, oriented elfs
mode = {'elf': Use the ElF algorithm to orient fingerprint,
'nn': Use nearest neighbor algorithm}
"""
... | 36b5abe66e9054ab49a25eca753d4a61148a1b1c | 16,553 |
def error_logger(param=None):
"""
Function to get an error logger, object of Logger class.
@param param : Custom parameter that can be passed to the logger.
@return: custom logger
"""
logger = Logger('ERROR_LOGGER', param)
return logger.get_logger() | ca6449c2e63ebdccbd7bd3993dc1d11375e66e29 | 16,555 |
def get_iou(mask, label):
"""
:param mask: predicted mask with 0 for background and 1 for object
:param label: label
:return: iou
"""
# mask = mask.numpy()
# label = labels.numpy()
size = mask.shape
mask = mask.flatten()
label = label.flatten()
m = mask + label
i = len(np... | 9322d0184a3e28bdd1d5bf3214b7fbe8936d6a21 | 16,557 |
from typing import List
from typing import Set
from typing import Any
def mean_jaccard_distance(sets: List[Set[Any]]) -> float:
"""
Compute the mean Jaccard distance for sets A_1, \dots A_n:
d = \frac{1}{n} \sum_{i=1}^{n-1} \sum_{j=i+1}^n (1 - J(A_i, A_j))
where J(A, B) is the Jaccard index betwee... | efbfce8092e2e3a9b5b076c46a636dfa17e2d266 | 16,558 |
def nx_find_connected(graph, start_set, end_set, cutoff=np.inf):
"""Return the nodes in end_set connected to start_set."""
reachable = []
for end in end_set:
if nx_is_reachable(graph, end, start_set):
reachable.append(end)
if len(reachable) >= cutoff:
break
... | a3feb8a172bb610fa4416c6f4a4c0558540d2190 | 16,559 |
def svn_client_proplist(*args):
"""
svn_client_proplist(char target, svn_opt_revision_t revision, svn_boolean_t recurse,
svn_client_ctx_t ctx, apr_pool_t pool) -> svn_error_t
"""
return _client.svn_client_proplist(*args) | 1cc82161292df7b9ba284397a0dcd55da9d0d7c1 | 16,560 |
def dev_transform(signal, input_path='../data/', is_denoised=True):
"""
normalization function that transforms each fature based on the
scaling of the trainning set. This transformation should be done on
test set(developmental set), or any new input for a trained neural
network. Due to existence of ... | ce6dfe780bb724ae8036502d2b1d1828fce675dc | 16,561 |
def moveTo(self, parent):
"""Move this element to new parent, as last child"""
self.getParent().removeChild(self)
parent.addChild(self)
return self | 40caa9681346db9a6cfb5c95fdb761a9f98e607a | 16,562 |
from datetime import datetime
def coerce_to_end_of_day_datetime(value):
"""
gets the end of day datetime equivalent of given date object.
if the value is not a date, it returns the same input.
:param date value: value to be coerced.
:rtype: datetime | object
"""
if not isinstance(value... | 374e7decf543e5fb40fb7714d4472cf4cfa48cb1 | 16,563 |
def greybody(nu, temperature, beta, A=1.0, logscale=0.0,
units='cgs', frequency_units='Hz', kappa0=4.0, nu0=3000e9,
normalize=max):
"""
Same as modified blackbody... not sure why I have it at all, though the
normalization constants are different.
"""
h,k,c = unitdict[units]... | 89cca39acf5659e8ab7b403c5747b19c119d0e51 | 16,564 |
import copy
def GCLarsen_v0(WF, WS, WD, TI,
pars=[0.435449861, 0.797853685, -0.124807893, 0.136821858, 15.6298, 1.0]):
"""Computes the WindFarm flow and Power using GCLarsen
[Larsen, 2009, A simple Stationary...]
Inputs
----------
WF: WindFarm
Windfarm instance
WS: list
Ro... | a075074b0cee9b36fdf3411804ff4eff2f5fe63b | 16,565 |
def guess_table_address(*args):
"""
guess_table_address(insn) -> ea_t
Guess the jump table address (ibm pc specific)
@param insn (C++: const insn_t &)
"""
return _ida_ua.guess_table_address(*args) | 073773e33b5cf4c59f3a3c892d5a53320c2c1f4b | 16,566 |
def get_elbs(account, region):
""" Get elastic load balancers """
elb_data = []
aws_accounts = AwsAccounts()
if not account:
session = boto3.session.Session(region_name=region)
for account_rec in aws_accounts.all():
elb_data.extend(
query_elbs_for_account(acc... | 32b059c7929b0adae3df7b8393fd062f5a281cc3 | 16,568 |
def likelihood_params(ll_mode, mode, behav_tuple, num_induc, inner_dims, inv_link, tbin, jitter,
J, cutoff, neurons, mapping_net, C):
"""
Create the likelihood object.
"""
if mode is not None:
kernel_tuples_, ind_list = kernel_used(mode, behav_tuple, num_induc, inner_dims)... | 2e817c4fdfdd9a65d138f61166ef8fbb3154460b | 16,570 |
def is_num_idx(k):
"""This key corresponds to """
return k.endswith("_x") and (k.startswith("tap_x") or k.startswith("sig")) | bd4ed2c9c4a24ae423ec6c738d99b31ace6ec267 | 16,571 |
def convert_to_boolarr(int_arr, cluster_id):
"""
:param int_arr: array of integers which relate to no, one or multiple clusters
cluster_id: 0=Pleiades, 1=Meingast 1, 2=Hyades, 3=Alpha Per, 4=Coma Ber
"""
return np.array((np.floor(int_arr/2**cluster_id) % 2), dtype=bool) | c769ca07ea32a9e0ab0d230cd3574e5b71434de4 | 16,572 |
def serialize(root):
#
"""Serialization is the process of converting a data structure or object
into a sequence of bits so that it can be stored in a file or memory buffer,
or transmitted across a network connection link to be reconstructed later in
the same or another computer environment.
Des... | a2bec43b384302d5218e8c62c83bc069be3bcbd3 | 16,573 |
def ensure_daemon(f):
"""A decorator for running an integration test with and without the daemon enabled."""
def wrapper(self, *args, **kwargs):
for enable_daemon in [False, True]:
enable_daemon_str = str(enable_daemon)
env = {
"HERMETIC_ENV": "PANTS_PANTSD,PANTS... | d9005c48d489b8b5da1f9687b78d1f455aaf3d62 | 16,574 |
from adaptivefiltering.pdal import execute_pdal_pipeline
from adaptivefiltering.pdal import PDALInMemoryDataSet
import json
def reproject_dataset(dataset, out_srs, in_srs=None):
"""Standalone function to reproject a given dataset with the option of forcing an input reference system
:param out_srs:
Th... | 0380442a837f89bbf06d0d1b5e9917e7309876ad | 16,575 |
def conditional(condition, decorator):
""" Decorator for a conditionally applied decorator.
Example:
@conditional(get_config('use_cache'), ormcache)
def fn():
pass
"""
if condition:
return decorator
else:
return lambda fn: fn | 7c17ad3aaacffd0008ec1cf66871ea6755f7869a | 16,576 |
import statistics
def variance(data, mu=None):
"""Compute variance over a list."""
if mu is None:
mu = statistics.mean(data)
return sum([(x - mu) ** 2 for x in data]) / len(data) | 92f89d35c2ae5abf742b10ba838a381d6f74e92c | 16,577 |
def make_note(outfile, headers, paragraphs, **kw):
"""Builds a pdf file named outfile based on headers and
paragraphs, formatted according to parameters in kw.
:param outfile: outfile name
:param headers: <OrderedDict> of headers
:param paragraphs: <OrderedDict> of paragraphs
:param kw: keyword... | d9bc331167649210cf18e76bcff4099817c28458 | 16,578 |
import stat
def output_file_exists(filename):
"""Check if a file exists and its size is > 0"""
if not file_exists(filename):
return False
st = stat(filename)
if st[stat_module.ST_SIZE] == 0:
return False
return True | ad2f3a7451feefd32fe98da7fc3bfca9852b080c | 16,579 |
def IMF_N(m,a=.241367,b=.241367,c=.497056):
"""
returns number of stars with mass m
"""
# a,b,c = (.241367,.241367,.497056)
# a=b=c=1/3.6631098624
if .1 <= m <= .3:
res = c*( m**(-1.2) )
elif .3 < m <= 1.:
res = b*( m**(-1.8) )
elif 1. < m <= 100.:
# res = a*( m*... | 4d120af2840a793468335cddd867f6d29940d415 | 16,580 |
def features_disable(partial_name, partial_name_field, force, **kwargs):
"""Disable a feature"""
mode = "disable"
params = {"mode": "force"} if force else None
feature = _okta_get("features", partial_name,
selector=_selector_field_find(partial_name_field, partial_name))
featu... | 5477a43ad2f849669a6a209abfc835f0f4ee453a | 16,581 |
def _get_images():
"""Get the official AWS public AMIs created by Flambe
that have tag 'Creator: [email protected]'
ATTENTION: why not just search the tags? We need to make sure
the AMIs we pick were created by the Flambe team. Because of tags
values not being unique, anyone can create a public AMI ... | 975596ff9eb1c9c0864cadb41edc2b1a4d009790 | 16,582 |
def ar_coefficient(x, param):
"""
This feature calculator fits the unconditional maximum likelihood
of an autoregressive AR(k) process.
The k parameter is the maximum lag of the process
.. math::
X_{t}=\\varphi_0 +\\sum _{{i=1}}^{k}\\varphi_{i}X_{{t-i}}+\\varepsilon_{t}
For the config... | a7a7171a44055d23457fd622d7e893f839f17bcf | 16,583 |
from faker import Faker
import random
def address_factory(sqla):
"""Create a fake address."""
fake = Faker() # Use a generic one; others may not have all methods.
addresslines = fake.address().splitlines()
areas = sqla.query(Area).all()
if not areas:
create_multiple_areas(sqla, random.ran... | 91f4558887025841d99ab6e65795111bbc804238 | 16,585 |
from pm4py.util import constants
from pm4py.algo.discovery.dfg.adapters.pandas.df_statistics import get_dfg_graph
from pm4py.statistics.start_activities.pandas import get as start_activities_module
from pm4py.statistics.end_activities.pandas import get as end_activities_module
from pm4py.algo.discovery.dfg.variants imp... | df8d9669c7e2a4cd3170cb1c5a1ecc7e7811649e | 16,586 |
import warnings
def mifs(data, target_variable, prev_variables_index, candidate_variable_index, **kwargs):
"""
This estimator computes the Mutual Information Feature Selection criterion.
Parameters
----------
data : np.array matrix
Matrix of data set. Columns are variables, rows are obser... | 058ebdbb831d7fb52c4b5f053ba7bb8a1ce7f144 | 16,587 |
def input_thing():
"""输入物品信息"""
name_str, price_str, weight_str = input('请输入物品信息(名称 价格 重量)：').split()
return name_str, int(price_str), int(weight_str) | 2a986e9479e8e4262cfab89f258af3536c5fefe3 | 16,588 |
def extract_features_mask(img, mask):
"""Computes law texture features for masked area of image."""
preprocessed_img = laws_texture.preprocess_image(img, size=15)
law_images = laws_texture.filter_image(preprocessed_img, LAW_MASKS)
law_energy = laws_texture.compute_energy(law_images, 10)
energy_feat... | e184695fb2879cf9fd418e7110498717585b4878 | 16,589 |
def construct_grid_with_k_connectivity(n1,n2,k,figu = False):
"""Constructs directed grid graph with side lengths n1 and n2 and neighborhood connectivity k"""
"""For plotting the adjacency matrix give fig = true"""
def feuclidhorz(u , v):
return np.sqrt((u[0] - (v[0]-n2))**2+(u[1] - v[... | 46b690f02c4f025719424582acecff43580543da | 16,590 |
import array
def _optimal_shift(pos, r_pad, log):
"""
Find the shift for the periodic unit cube that would minimise the padding.
"""
npts, ndim = pos.shape
# +1 whenever a region starts, -1 when it finishes
start_end = empty(npts*2, dtype=np.int32)
start_end[:npts] = 1
start_end[... | cac3c56307ea3d240ebe838ea4d26bb38c62dc3c | 16,592 |
def ShowActStack(cmd_args=None):
""" Routine to print out the stack of a specific thread.
usage: showactstack <activation>
"""
if cmd_args == None or len(cmd_args) < 1:
print "No arguments passed"
print ShowAct.__doc__.strip()
return False
threadval = kern.GetValueFromA... | 43b0eca326465fe9dc7b0207ba448d75da7e9889 | 16,593 |
import json
def load_request(possible_keys):
"""Given list of possible keys, return any matching post data"""
pdata = request.json
if pdata is None:
pdata = json.loads(request.body.getvalue().decode('utf-8'))
for k in possible_keys:
if k not in pdata:
pdata[k] = None
# ... | b21c503fac56398be6745a10fb95889128c6e2b2 | 16,595 |
import random
def get_random_tcp_start_pos():
""" reachability area:
x = [-0.2; 0.4]
y = [-0.28; -0.1] """
z_up = 0.6
tcp_x = round(random.uniform(-0.2, 0.4), 4)
tcp_y = round(random.uniform(-0.28, -0.1), 4)
start_tcp_pos = (tcp_x, tcp_y, z_up)
# start_tcp_pos = (-0.2, -0.28, ... | adf87dec45bf5a81c321f94c93d45a67f0aeff0d | 16,596 |
def CalculateChiv3p(mol):
"""
#################################################################
Calculation of valence molecular connectivity chi index for
path order 3
---->Chiv3
Usage:
result=CalculateChiv3p(mol)
Input: mol is a molecule object... | 27405fce52540a0de9c4c1c2d5a35454681554fa | 16,597 |
from typing import Tuple
from typing import Optional
def coerce(version: str) -> Tuple[Version, Optional[str]]:
"""
Convert an incomplete version string into a semver-compatible Version
object
* Tries to detect a "basic" version string (``major.minor.patch``).
* If not enough components can be fou... | e712533aa05444ad47403fc10e7f2ec29b8132ec | 16,598 |
def choose_wyckoff(wyckoffs, number):
"""
choose the wyckoff sites based on the current number of atoms
rules
1, the newly added sites is equal/less than the required number.
2, prefer the sites with large multiplicity
"""
for wyckoff in wyckoffs:
if len(wyckoff[0]) <= number:
... | 14b276d8aa50e84f47d77f6796e193cc96ddd0a9 | 16,599 |
def _to_system(abbreviation):
"""Converts an abbreviation to a system identifier.
Args:
abbreviation: a `pronto.Term.id`
Returns:
a system identifier
"""
try:
return {
'HP': 'http://www.human-phenotype-ontology.org/'
}[abbreviation]
except KeyError:
... | f43942b242e67866028a385e6614133dc25b31b0 | 16,600 |
from typing import Union
def apply_gate(circ: QuantumCircuit, qreg: QuantumRegister, gate: GateObj,
parameterise: bool = False, param: Union[Parameter, tuple] = None):
"""Applies a gate to a quantum circuit.
More complicated gates such as RXX gates should be decomposed into single qubit
ga... | 0babd68efb8bae67c5f610bcca3eb9f3b67630ad | 16,601 |
from typing import Tuple
import codecs
def preprocess_datasets(data: str, seed: int = 0) -> Tuple:
"""Load and preprocess raw datasets (Yahoo! R3 or Coat)."""
if data == 'yahoo':
with codecs.open(f'../data/{data}/train.txt', 'r', 'utf-8', errors='ignore') as f:
data_train = pd.read_csv(f, ... | 78a7bfe7968ad47f797728ffb43c804ab8af6298 | 16,602 |
def loadSentimentVector(file_name):
"""
Load sentiment vector
[Surprise, Sorrow, Love, Joy, Hate, Expect, Anxiety, Anger]
"""
contents = [
line.strip('\n').split() for line in open(file_name, 'r').readlines()
]
sentiment_dict = {
line[0].decode('utf-8'): [float(w) for w in li... | 5d0d1f4598eeed455d080236720adcae357b6485 | 16,603 |
def unique_boxes(boxes, scale=1.0):
"""Return indices of unique boxes."""
v = np.array([1, 1e3, 1e6, 1e9])
hashes = np.round(boxes * scale).dot(v)
_, index = np.unique(hashes, return_index=True)
return np.sort(index) | fc9ab64356192828659f025af6aa112205fc838c | 16,604 |
def HEX2DEC(*args) -> Function:
"""
Converts a signed hexadecimal number to decimal format.
Learn more: https//support.google.com/docs/answer/3093192
"""
return Function("HEX2DEC", args) | b4741d02acae7169854d1193ae5b43f6736257dc | 16,606 |
def find_edges(mesh, key):
""" Temp replacement for mesh.findEdges().
This is painfully slow.
"""
for edge in mesh.edges:
v = edge.vertices
if key[0] == v[0] and key[1] == v[1]:
return edge.index | 98247b64a0e5671a7dbbf314f314cef2c5c8aae3 | 16,607 |
def thumbnail(link):
"""
Returns the URL to a thumbnail for a given identifier.
"""
targetid, service = _targetid(link), _service(link)
if targetid:
if service in _OEMBED_MAP:
try:
return _embed_json(service, targetid)["thumbnail_url"]
except (ValueEr... | 9ca78af2a65a41a70fef73c35383ae9214fb2d96 | 16,608 |
def valve_gas_cv(m_dot, p_1, p_2, m_molar, T):
"""Find the required valve Cv for a given mass flow and pressure drop.
Assumes that a compressible gas is flowing through the valve.
Arguments:
m_dot (scalar): Mass flow rate [units: kilogram second**-1].
p_1 (scalar): Inlet pressure [units: p... | 07bd3f45392e03eb6744b98a3fde022aa517c4fc | 16,609 |
def frequency_based_dissim(record, modes):
"""
Frequency-based dissimilarity function
inspired by "Improving K-Modes Algorithm Considering Frequencies of Attribute Values in Mode" by He et al.
"""
list_dissim = []
for cluster_mode in modes:
sum_dissim = 0
for i in range(len(recor... | 80e21763d6f90ddc5a448f46247fd12253de5dbb | 16,610 |
def _process_create_group(event: dict) -> list:
""" Process CreateGroup event. This function doesn't set tags. """
return [event['responseElements']['group']['groupName']] | 978b3ffc3c4aa72165914b79dc06cb7691c5c5a5 | 16,611 |
from typing import Any
from typing import List
def tree_labels(t: Node):
"""Collect all labels of a tree into a list."""
def f(label: Any, folded_subtrees: List) -> List:
return [label] + folded_subtrees
def g(folded_first: List, folded_rest: List) -> List:
return folded_first + folded_r... | 7ad1703a090cd761a99cd5323c9258e8d2d551b8 | 16,612 |
def find_best_split(rows):
"""Find the best question to ask by iterating over every feature / value
and calculating the information gain."""
best_gain = 0 # keep track of the best information gain
best_question = None # keep train of the feature / value that produced it
current_uncertainty = gini(... | 9b197c99b41e64e37b499b5d4b3c7758cda3b56e | 16,613 |
def pad_data(data, context_size, target_size, pad_at_begin= False):
"""
Performs data padding for both target and aggregate consumption
:param data: The aggregate power
:type data: np.array
:param context_size: The input sequence length
:type context_size: int
:param target_size: The target... | 1b698a849a4ca82d87ce6c5711220b61cd21252b | 16,614 |
def egg_translator(cell):
"""If the cell has the DNA for harboring its offspring inside it, granting it additional food
and protection at the risk of the parent cell, it is an egg.
Active DNA: x,A,(C/D),x,x,x
"""
dna = cell.dna.split(',')
if dna[1] == 'A' and dna[2] == 'C':
return True
... | af0d9097c8a0b5002722c79d6ec8262a66cc375d | 16,617 |
def all_different_cst(xs, cst):
"""
all_different_cst(xs, cst)
Ensure that all elements in xs + cst are distinct
"""
return [AllDifferent([(x + c) for (x,c) in zip(xs,cst)])] | dfc75a54a92a4c8c2ef76af74250b9125c9bb647 | 16,618 |
def processing(task, region: dict, raster: str, parameters: dict):
"""
Cuts the raster according to given region and applies some filters
in order to find the district heating potentials and
related indicators.
Inputs :
* region : selected zone where the district heating potential is studi... | 63a5548e886b575011e716e05a589715f027c316 | 16,619 |
import random
def randbit():
"""Returns a random bit."""
return random.randrange(2) | 4b47101df7368b7cb423920e6a5338b76ab4ecaa | 16,620 |
def calc_points(goals, assists):
"""
Calculate the total traditional and weighted points for all
players, grouped by player id.
Author: Rasmus Säfvenberg
Parameters
----------
goals : pandas.DataFrame
A data frame with total goals and weighted assists per player.
assist... | 1801cf2602a473bdf532e1c0ee58b883dc3e79d1 | 16,621 |
import io
import base64
def file_to_base64(path):
"""
Convert specified file to base64 string
Args:
path (string): path to file
Return:
string: base64 encoded file content
"""
with io.open(path, 'rb') as file_to_convert:
return base64.b64encode(file_to_convert.read()) | 0c942f8f4d29943c5a3aac6c954d9e2b1b2898a3 | 16,623 |
def get_simverb(subset=None):
"""
Get SimVerb-3500 data
:return: (pairs, scores)
"""
simverb = []
if subset == 'dev':
name = '500-dev'
elif subset == 'test':
name = '3000-test'
else:
name = '3500'
with open('../data/SimVerb-3500/SimVerb-{}.txt'.format(name)) a... | 5cec49bd232a883836029b8b011f09f360176910 | 16,624 |
def sample_image(size, min_r, max_r, circles, squares, pixel_value):
"""Generate image with geometrical shapes (circles and squares).
"""
img = np.zeros((size, size, 2))
loc = []
if pixel_value is None:
vals = np.random.randint(0, 256, circles + squares)
else:
vals = [pixel_value... | 25ab1afcd7256bc07ee55ac2e12cf9d834cb798c | 16,625 |
def host_allocations(auth):
"""Retrieve host allocations"""
response = API.get(auth, '/os-hosts/allocations')
return response.json()['allocations'] | 505eeb0502f6480445ec5dff1cd3203eda96d475 | 16,626 |
def rosenbrock_grad(x, y):
"""Gradient of Rosenbrock function."""
return (-400 * x * (-(x ** 2) + y) + 2 * x - 2, -200 * x ** 2 + 200 * y) | c7acf0bbe11a6d1cbb38b6853eb1b508e3846657 | 16,627 |
def extractYoujinsite(item):
"""
"""
vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title'])
if '[God & Devil World]' in item['tags'] and (chp or vol):
return buildReleaseMessageWithType(item, 'Shenmo Xitong', vol, chp, frag=frag, postfix=postfix)
if '[LBD&A]' in item['tags'] and (chp or vol):... | 11463288cdcc7268b0b4657934dd8872a7d36580 | 16,629 |
def get_logger() -> Logger:
""" This function returns the logger for this project """
return getLogger(LOGGER_NAME) | 33e11a06c357552c35f9ef089fd303ad15db0884 | 16,632 |
import json
def write_guess_json(guesser, filename, fold, run_length=200, censor_features=["id", "label"], num_guesses=5):
"""
Returns the vocab, which is a list of all features.
"""
vocab = [kBIAS]
print("Writing guesses to %s" % filename)
num = 0
with open(filename, 'w') as outfil... | 9f0055289ff462b0b3c067ea1e0a68c66a74136c | 16,633 |
def upgrade_to_4g(region, strategy, costs, global_parameters,
core_lut, country_parameters):
"""
Reflects the baseline scenario of needing to build a single dedicated
network.
"""
backhaul = '{}_backhaul'.format(strategy.split('_')[2])
sharing = strategy.split('_')[3]
geotype = region['... | 947afef6d550b9022109c665fc311511f428e9f8 | 16,634 |
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