content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def network_alignment(network_a, network_b):
"""combines two networks into a new network
| Arguments:
| :-
| network_a (networkx object): biosynthetic network from construct_network
| network_b (networkx object): biosynthetic network from construct_network\n
| Returns:
| :-
| Returns combined network as... | e1aa0fdbbd74d63fe85028339ef9402a21f566b4 | 3,635,402 |
def grab_cpu_scalar(v, nd):
"""
Get a scalar variable value from the tree at `v`.
This function will dig through transfers and dimshuffles to get
the constant value. If no such constant is found, it returns None.
Parameters
----------
v
Aesara variable to extract the constant value... | b842b59f903b23146cbcec5d391e8ecd7db67604 | 3,635,403 |
def _get_interface_name_index(dbapi, host):
"""
Builds a dictionary of interfaces indexed by interface name.
"""
interfaces = {}
for iface in dbapi.iinterface_get_by_ihost(host.id):
interfaces[iface.ifname] = iface
return interfaces | 0217f6ef8d4e5e32d76a4fc0d66bf74aa45f8c36 | 3,635,404 |
def generate_data(shape, num_seed_layers=3, avg_bkg_tracks=3,
noise_prob=0.01, verbose=True, seed=1234):
"""
Top level function to generate a dataset.
Returns arrays (events, sig_tracks, sig_params)
"""
np.random.seed(seed)
num_event, num_det_layers, det_layer_size, _ = shape
... | 74116397ced9085794416a7c2c191e3a4fac135a | 3,635,405 |
import xml
from typing import List
from typing import Optional
from typing import Tuple
import pathlib
def create_project(
root: xml.etree.ElementTree.Element,
include: List[str],
exclude: Optional[List[str]] = None
) -> Tuple[List[str], List[str], List[pathlib.Path], List[pathlib.Path],
List[p... | dda783efec500750dec65823701f186234bbc5dc | 3,635,406 |
import torch
def to_data(x):
"""Converts variable to numpy"""
if torch.cuda.is_available():
x = x.cpu()
return x.data.numpy() | b91f755d43fde06db1bd38158881eb2f84e43d10 | 3,635,407 |
def levmar_bc(func, p0, y, bc, args=(), jacf=None,
mu=1.0e-03, eps1=1.5e-08, eps2=1.5e-08, eps3=1.5e-08,
maxit=1000, cdiff=False):
"""
Parameters
----------
func: callable
Function or method computing the model function, `y = func(p, *args)`.
p0: array_like, shape... | 6d861988290c00b846a8ff35bc36beca778985f7 | 3,635,408 |
import json
def set_name_filter(request):
"""
Sets product filters given by passed request.
"""
product_filters = request.session.get("product_filters", {})
if request.POST.get("name", "") != "":
product_filters["product_name"] = request.POST.get("name")
else:
if product_filte... | a36e9e46a58b71926bafee248312abddaba6ce90 | 3,635,409 |
def select(
da,
longitude=None,
latitude=None,
T=None,
Z=None,
iT=None,
iZ=None,
extrap=False,
extrap_val=None,
locstream=False,
):
"""Extract output from da at location(s).
Parameters
----------
da: DataArray
Property to take gradients of.
longitude,... | 91fbf82ca99ddc3eb6328b1c435cdb70f706c9a3 | 3,635,411 |
def afsluitmiddel_regelbaarheid(damo_gdf=None, obj=None):
""""
Zet naam van AFSLUITREGELBAARHEID om naar attribuutwaarde
"""
data = [_afsluitmiddel_regelbaarheid(name) for name in damo_gdf['SOORTREGELBAARHEID']]
df = pd.Series(data=data, index=damo_gdf.index)
return df | 66bb59b2cea9e84faafe54adf114a73571f6fd05 | 3,635,412 |
import copy
def generate(i):
"""
Input: {
(output_txt_file) - if !='', generate text file for a given conference
(conf_id) - record names for this conf
}
Output: {
return - return code = 0, if successful
... | ec2de19931fa527cba88baec8775b21c7bcbf88c | 3,635,413 |
def calc_solidangle_particle(
pts=None,
part_traj=None,
part_radius=None,
config=None,
approx=None,
aniso=None,
block=None,
):
""" Compute the solid angle subtended by a particle along a trajectory
The particle has radius r, and trajectory (array of points) traj
It is observed f... | 46a9700c12bc8d734678795a0cb989d025f02685 | 3,635,414 |
def fields_view(arr, fieldNameLst=None):
"""
Return a view of a numpy record array containing only the fields names in
the fields argument. 'fields' should be a list of column names.
"""
# Default to all fields
if not fieldNameLst:
fieldNameLst = arr.dtype.names
dtype2 = np.dtyp... | 5d4e6629c3acf26619033d9d7e103c9e817bea78 | 3,635,415 |
from typing import List
from typing import Tuple
def image_detach_with_id_color_list(
color_img: np.ndarray,
id_color_list: List[Tuple[int, Tuple[int, int, int]]],
bin_num: int,
mask_value: float = 1.0,
) -> np.ndarray:
"""
컬러 이미지 `color_img`를 색상에 따른 각 인스턴스 객체로 분리합니다.
Parameters
----... | 941100eb6fed342b4a89a10115ee55350c58ae6e | 3,635,417 |
from typing import Dict
from typing import Any
from typing import List
import copy
def defaultArgs(options: Dict = None, **kwargs: Any) -> List[str]: # noqa: C901,E501
"""Get the default flags the chromium will be launched with.
``options`` or keyword arguments are set of configurable options to set on
... | 3f43e3505b77f232e7f797caff318ffe5f466f7d | 3,635,418 |
from typing import List
def process_v3_fields(fields: List[str], endpoint: str) -> str:
"""
Filter v3 field list to only include valid fields for a given endpoint.
Logs a warning when fields get filtered out.
"""
valid_fields = [field for field in fields if field in FIELDS_V3]
if len(valid_f... | 87f21c58a4a5613dc0c319cf4adcc29a42cd2054 | 3,635,419 |
def getManifestFsLayers(manifest):
""" returns hashes pointing to layers for manifest"""
return manifest["manifest"]["fsLayers"] | a3449c2828222c2b806df8621dd6a24375778ed2 | 3,635,420 |
def Jones_METIS(c, tau, w, q):
""" Returns Jones polynomial evaluated at t(q) via METIS
contraction of the tensor network of the knot encoded
in edgelist c. w is the writhe of the knot. """
nc = len(c) # number of crossings
if nc > 0:
nv = cnf_nvar(c)
ekpotts = -tpotts(q)
... | 77b16bd2737ea3b9628d52c9fa2eea014644af37 | 3,635,421 |
def screen_name_filter(tweet_list, stoplist):
"""
Filter list of tweets by screen_names in stoplist.
Pulls original tweets out of retweets.
stoplist may be a list of usernames, or a string name of a configured
named stoplist.
"""
tweets = []
id_set = set()
if isinstance(stoplist, ba... | da8f292e496503cb70c3cf7f33ba7f87ed874cbb | 3,635,422 |
def insert_into(table_name, values, column_names, create_if_not_exists=False, inspect=True, engine=None):
"""
Inserts a list of values into an existing table
:param table_name: the name of the table into which to insert records
:param values: a list of lists containing literal values to insert into the... | ac9f299da13cb12446e1ac14c1962deb93a1d233 | 3,635,423 |
def delchars(str, chars):
"""Returns a string for which all occurrences of characters in
chars have been removed."""
# Translate demands a mapping string of 256 characters;
# whip up a string that will leave all characters unmolested.
identity = "".join([chr(x) for x in range(256)])
return str... | a220202a05e0ead7afa6226ef309c56940a1d153 | 3,635,424 |
from typing import Optional
from typing import cast
import collections
from typing import Set
from typing import Type
from typing import Union
from typing import List
def normalize_typed_substitution(
value: SomeValueType, data_type: Optional[AllowedTypesType]
) -> NormalizedValueType:
"""
Normalize a mix... | 40250403240d591734770b146dd8253fe24c5083 | 3,635,425 |
def index(request):
"""
View for the static index page
"""
return render(request, 'public/home.html', _get_context('Home')) | 3598ef8776943c63f49787f63f69d8a22536805e | 3,635,426 |
def bytes2hex(bytes_array):
"""
Converts byte array (output of ``pickle.dumps()``) to spaced hexadecimal string representation.
Parameters
----------
bytes_array: bytes
Array of bytes to be converted.
Returns
-------
str
Hexadecimal representation of the byte array.
... | 19019ee1e3cd45d671f53e0ae4fd92b283c3b38d | 3,635,427 |
def atan2(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.arctan2 <numpy.arctan2>`.
See its docstring for more information.
"""
if x1.dtype not in _floating_dtypes or x2.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allow... | 8a0621bfd0ad8ac4ce9e14cc939e5a8b9e3e511c | 3,635,428 |
def authorizer(*args, **kwargs):
"""
decorator to register an authorizer.
:param object args: authorizer class constructor arguments.
:param object kwargs: authorizer class constructor keyword arguments.
:keyword bool replace: specifies that if there is another registered
... | 5af038c7e1bebee228bffc24c72aa54e03a8d28e | 3,635,430 |
def option_getter(config_model):
"""Returns a get_option() function using the given config_model and data"""
def get_option(option, x=None, default=None, ignore_inheritance=False):
def _get_option(opt, fail=False):
try:
result = config_model.get_key('techs.' + opt)
... | ad5726bc957e1c5902960ebc0e51af43f0ab31eb | 3,635,431 |
def is_core_dump(file_path):
"""
Determine whether given file is a core file. Works on CentOS and Ubuntu.
Args:
file_path: full path to a possible core file
"""
file_std_out = exec_local_command("file %s" % file_path)
return "core file" in file_std_out and 'ELF' in file_std_out | 33c9974888857f913de1702117a0add2c686c252 | 3,635,432 |
from pathlib import Path
def to_posix(d):
"""Convert the Path objects to string."""
if isinstance(d, dict):
for k, v in d.items():
d[k] = to_posix(v)
elif isinstance(d, list):
return [to_posix(x) for x in d]
elif isinstance(d, Path):
return d.as_posix()
return... | 91dbda7738308dd931b58d59dad8e04a277034ea | 3,635,433 |
import traceback
def list_entities(currency, ids=None, page=None, pagesize=None): # noqa: E501
"""Get entities
# noqa: E501
:param currency: The cryptocurrency (e.g., btc)
:type currency: str
:param ids: Restrict result to given set of comma separated IDs
:type ids: List[str]
:param pa... | 7956ab50da50811785be9fd1c834984500460378 | 3,635,435 |
def sensor(request):
"""HTTP/GET /sensor コール時の処理
ADC以外のセンサー値を読んで返す
Args:
request (QueryDict): リクエストパラメータ
Returns:
dict: クライアントに返すjson形式の値
"""
params = request.GET.copy()
api_response = ApiResponse()
params["ids"] = params.getlist("ids")
parse = ParseApiParams(param... | d9df39aeeeb6077c6bf2b6c0019d682f3a05e78f | 3,635,436 |
def stat(lst):
"""Calculate mean and std deviation from the input list."""
n = float(len(lst))
mean = sum(lst) / n
stdev = sqrt((sum(x * x for x in lst) / n) - (mean * mean))
return mean, stdev | c1983fc9da96397a5f55e45d0eac9cbc921a91fc | 3,635,437 |
import attr
def _recursive_generic_validator(typed):
"""Recursively assembles the validators for nested generic types
Walks through the nested type structure and determines whether to recurse all the way to a base type. Once it
hits the base type it bubbles up the correct validator that is nested within ... | dcc89a9c358da848d56d3c031e3967402ef70a28 | 3,635,438 |
def get_posts(di, po, syn):
"""
Gets the postings list for each unique token in the query
"""
words = {}
#goes through each token in the query and returns its postings list
for i in range(len(syn)):
word = syn[i][0]
#goes through each synonym for each word
for k i... | 8a45df246bf6bb19baf570b133427f937d36f5d9 | 3,635,440 |
def need_food(board, bad_positions, snake):
""" Determines if we need food and returns potential food that we can get """
potential_food = []
# food that is not contested (we are the closest)
safe_food = [fud for fud in board.food if board.get_cell(fud) != SPOILED]
# always go for safe food even i... | 73359fa082feda5a2e3efb8d9d7f091d9d23a8bb | 3,635,441 |
def categoriesJSON():
"""Return JSON for all the categories"""
categorys = session.query(Category).all()
return jsonify(categories=[c.serialize for c in categorys]) | 2f300dca846d2c01dca1ea80798fbcf258e459e8 | 3,635,442 |
def rescale_column(img, gt_bboxes, gt_label, gt_num, img_shape):
"""rescale operation for image"""
img_data, scale_factor = rescale_with_tuple(img, (config.img_width, config.img_height))
if img_data.shape[0] > config.img_height:
img_data, scale_factor2 = rescale_with_tuple(img_data, (config.img_heig... | 1f765b69b65ab34b1d272223a2344e6068f3f4ab | 3,635,443 |
def ausc_trapazoidal(mean_df, doses):
"""Performs numerical integration using the trapazoidal rule
to determine the area under the survival curve (AUSC)
for the drug respose.
The only argument, mean_df, is a data frame made from make_mean_std().
"""
y = mean_df.normalized_mean
x = doses
... | fad1c30d6996ea7ea3e4d6cf0d6546f76647e459 | 3,635,444 |
def psu_info_table(psu_name):
"""
:param: psu_name: psu name
:return: psu info entry for this psu
"""
return "PSU_INFO" + TABLE_NAME_SEPARATOR_VBAR + psu_name | e3894e0ae5735d8f096cfa72ac50bc6fd3d966da | 3,635,446 |
def delete_rds(rds_client, rds_instances) -> list:
"""Deletes all instances in the instances parameter.
Args:
rds_client: A RDS boto3 client.
rds_instances: A list of instances you want deleted.
Returns:
A count of deleted instances
"""
terminated_instances = []
for ins... | f1e66cce8e2d98c53bc247c2e2b8fd57c195b86c | 3,635,447 |
import itertools
def all_preferences(candidates, concentrate=False):
"""
Generates all possible preferences given a list of candidates
"""
permutations_tuple = list(itertools.permutations(candidates))
permutations_list = list(map(list, list(permutations_tuple)))
if concentrate:
return ... | 53f078a9fd3f66696cc5bc64de9b41d4ccbe2c8c | 3,635,448 |
import torch
def div_reg(net, data, ref):
"""
Regulize the second term of the loss function
"""
mean_f = net(data).mean()
log_mean_ef_ref = torch.logsumexp(net(ref), 0) - np.log(ref.shape[0])
return mean_f - log_mean_ef_ref - log_mean_ef_ref**2 | 04d28e11df8f7b5e723d1930372afca317e1c349 | 3,635,449 |
def action_list():
""" Prints all the available actions present in this file. """
rospy.loginfo(color.BOLD + color.PURPLE + '|-------------------|' + color.END)
rospy.loginfo(color.BOLD + color.PURPLE + '| AVAILABLE ACTIONS |' + color.END)
rospy.loginfo(color.BOLD + color.PURPLE + '| 1: MOVE TO POINT ... | 2c5e80c9e2ddcc127812491e4bfd8ed0a4765b53 | 3,635,450 |
def firstLetterCipher(ciphertext):
"""
Returns the first letters of each word in the ciphertext
Example:
Cipher Text: Horses evertime look positive
Decoded text: Help """
return "".join([i[0] for i in ciphertext.split(" ")]) | 87f37d1a428bde43c07231ab2e5156c680c96f91 | 3,635,451 |
def polar_decode(N, K, P0):
"""
Decode a (N, K) polar code.
P0 must be 1-normalized probabilities
"""
n = np.log2(N).astype(int)
A = polar_hpw(N)[-K:]
# We're not using all the elements in the P array, as each layer lamb
# only uses 2**(n-lamb) elements. Given the current indexing it's ... | c305aaaa124faec73145a87cdbafe35965e26ec6 | 3,635,452 |
from pathlib import Path
from typing import Tuple
import re
def parse_samtools_flagstat(p: Path) -> Tuple[int, int]:
"""Parse total and mapped number of reads from Samtools flagstat file"""
total = 0
mapped = 0
with open(p) as fh:
for line in fh:
m = re.match(r'(\d+)', line)
... | 60c6f9b227cefdea9877b05bb2fe66e4c82b4dd1 | 3,635,453 |
def get_country(country_id=None, incomelevel=None, lendingtype=None, cache=True):
"""
Retrieve information on a country or regional aggregate. Can specify
either country_id, or the aggregates, but not both
:country_id: a country id or sequence thereof. None returns all countries
and aggregates... | b798667f1bd1c0c8649986b948201392eae1f165 | 3,635,455 |
def _PmapWalkARMLevel2(tte, vaddr, verbose_level = vSCRIPT):
""" Pmap walk the level 2 tte.
params:
tte - value object
vaddr - int
returns: str - description of the tte + additional informaiton based on verbose_level
"""
pte_base = kern.PhysToKernelVirt(tte & 0xFFFFFC00)
... | bb4a7dcd70abf5f3f451c5ce56d10673bdb803b4 | 3,635,456 |
def mel_spectrogram_feature(wav, hparams=None):
"""
Derives a mel spectrogram ready to be used by the encoder from a preprocessed audio waveform.
Note: this not a log-mel spectrogram.
"""
hparams = hparams or default_hparams
frames = librosa.feature.melspectrogram(
wav,
hparams.s... | 5f1541109b81b535ca9a263a954ce82b067fe3eb | 3,635,457 |
def getRdkitAtomXYZbyId(rdkitMol,atomId, confId=0):
"""Returns an xyz atom position given atom's id."""
conf = rdkitMol.GetConformer(confId)
return np.array(list(conf.GetAtomPosition(atomId))) | 6a28646e7c7275c2c43da5fea512273e68e4a9e4 | 3,635,458 |
def _mn_minos_ ( self , *args ) :
"""Get MINOS errors for parameter:
>>> m = ... # TMinuit object
>>> result = m.minos( 1 , 2 )
"""
ipars = []
for i in args :
if not i in self : raise IndexError
ipars.append ( i )
return _mn_exec_ ( self , 'MINOS' , 200 , *... | cd99344cb7af2bca3db1abb576ec63ffff2df032 | 3,635,459 |
def app_files(proj_name):
"""Create a list with the project files
Args:
proj_name (str): the name of the project, where the code will be hosted
Returns:
files_list (list): list containing the file structure of the app
"""
files_list = [
"README.md",
"setup.py",
... | 2c6cbf112c7939bea12672668c8a5db1656b6edd | 3,635,460 |
def periodic_name(userword):
"""Generate a sequence of periodic elements from a word or sentence."""
# split up into individual words
sentence = userword.split()
output = []
# match each word with the periodic system
for word in sentence:
sequencer = ElementalWord(word)
basescore... | bfd7b2aa26baa193ac055afc64334058860d9a16 | 3,635,461 |
import json
def presentationRequestApiCallback():
""" This method is called by the VC Request API when the user scans a QR code and presents a Verifiable Credential to the service """
presentationResponse = request.json
print(presentationResponse)
if request.headers['api-key'] != apiKey:
print... | f45e4580d73ec9679679c801aaeaf664011c340a | 3,635,462 |
def process_table(data: document.TableNode, caption: str) -> NoEscape:
"""
Returns a Latex formatted Table Item, wrapped with a NoEscape Command
"""
rows = [
tuple(
" ".join(process(c) for c in table_cell["children"])
for table_cell in table_row["children"]
)
... | bd9b8e450a5c872a83d0d146d7256f581fa4bc39 | 3,635,463 |
def getTracksForArtist(artistName, tracks = None):
"""
Return a Track object for each track found with the specified artistName.
"""
tracksToSearch = tracks or getTracks()
return filter(lambda x:x.artist == artistName, tracksToSearch) | 5df8ead4d3c5f47810ccbb55a9f442e542d9c454 | 3,635,464 |
import torch
def log_safe(x):
"""The same as torch.log(x), but clamps the input to prevent NaNs."""
x = torch.as_tensor(x)
return torch.log(torch.min(x, torch.tensor(33e37).to(x))) | 98c73b316d22ebe9ef4b322b1ba984a734422e7a | 3,635,465 |
def index(request):
"""Redirect to the index page."""
context = {'form': LoginForm() }
return render(request, 'index.htm', context) | f2181aa02dd8709350be8675e5da21e2a94bdf27 | 3,635,466 |
def summarize_chrom_classif_by_sample(psd_list, sample_list):
""" Summarize chromosome classification by sample
Inputs:
psd_list: list of SamplePSD AFTER calc_chrom_props() has been run
sample_list: list of samples in same order as psd_list
Returns:
data frame w... | 64b77680d8e5a3170d4bd8a0680e979d0e3f8e89 | 3,635,467 |
def fake_quant_with_min_max_vars_per_channel_gradient(input_gradients, input_data,
input_min, input_max,
num_bits=8, narrow_range=False):
"""
Computes gradients of Fake-quantize on the 'input_data' tenso... | 36452b2783b35280f87dcbd260fad4f11d95f73a | 3,635,468 |
def test_split(data, test_size=0.3):
"""
Split data to train and test subsets.
:param data: Array like list.
:param test_size: Size of test subset.
:return: Returns tuple of matrix like subsets (train_subset, test_subset).
"""
return sklearn.model_selection.train_test_split(data, test_size) | d53d5957960046e09c6e2fcdf88dc24251689af8 | 3,635,469 |
def xscontrol_Vars(*args):
"""
Args:
pilot(Handle_IFSelect_SessionPilot)
Returns:
static Handle_XSControl_Vars
Returns the Vars of a SessionPilot, it is brought by Session
it provides access to external variables
"""
return _XSControl.xscontrol_Vars(*args) | 280e0d6823fa86adbff02ce633075b5b6c4a4e4e | 3,635,471 |
def swing_twist_decomposition(q, twist_axis):
""" code by janis sprenger based on
Dobrowsolski 2015 Swing-twist decomposition in Clifford algebra. https://arxiv.org/abs/1506.05481
"""
q = normalize(q)
#twist_axis = np.array((q * offset))[0]
projection = np.dot(twist_axis, np.array([q[1], q[2... | 555b7897aafc3085c875513274c44abc3f06fbb4 | 3,635,472 |
import requests
def resolve_s1_slc(identifier, download_url, project):
"""Resolve S1 SLC using ASF datapool (ASF or NGAP). Fallback to ESA."""
# determine best url and corresponding queue
vertex_url = "https://datapool.asf.alaska.edu/SLC/SA/{}.zip".format(
identifier)
r = requests.head(vertex... | cf489b0d65a83dee3f87887a080d67acd180b0b3 | 3,635,474 |
def equivalent_gaussian_Nsigma_from_logp(logp):
"""Number of Gaussian sigmas corresponding to tail log-probability.
This function computes the value of the characteristic function of a
standard Gaussian distribution for the tail probability equivalent to the
provided p-value, and turns this value into ... | 8dde13e19fe15d2dbdfdc3c1902edcf220672796 | 3,635,475 |
import tempfile
from pathlib import Path
import logging
import zipfile
def fetch_ratings():
"""Fetches ratings from the given URL."""
url = "http://files.grouplens.org/datasets/movielens/ml-25m.zip"
with tempfile.TemporaryDirectory() as tmp_dir:
tmp_path = Path(tmp_dir, "download.zip")
l... | 439b9603a849d822d30e93e663a3e9195651cd06 | 3,635,476 |
def _window_view(a, window, step = None, axis = None, readonly = True):
"""
Create a windowed view over `n`-dimensional input that uses an
`m`-dimensional window, with `m <= n`
Parameters
-------------
a : Array-like
The array to create the view on
... | 2e083a105be37e1fe9e784c0378c3a0bb667601e | 3,635,478 |
def approveReport(id):
"""
Function to approve a report
"""
# Approve the doc source entity record
sgtable = s3db.stats_group
sgt_table = s3db.stats_group_type
resource = s3db.resource("stats_group", id=id, unapproved=True)
resource.approve()
# find the type of report that we ha... | 25a87f20870b5ac90dea6c5013a337ffabfd9e04 | 3,635,479 |
def _maybe_promote_geometry(geom):
""" Either promote the geometry to a Multi-geometry, or return input"""
promoter = _promotion_dispatch.get(geom.type, lambda x: x[0])
return promoter([geom]) | 4b6f5805049025cb3692dff77af708350e3ccc8f | 3,635,480 |
def preprocess_input(frames):
"""Resize and subtract mean from video input
Args:
frames (tf.Tensor): Video frames to preprocess. Expected shape
(frames, rows, columns, channels).
Returns:
A TF Tensor.
"""
# Reshape to 128x171
frames = tf.ima... | 8bbede3ef2d8f131ee09f46bddfd4b66ad868f27 | 3,635,481 |
from pathlib import Path
def get_cache_info(path: Path) -> CacheInfo:
"""Return the information used to check if a file is already formatted or not."""
stat = path.stat()
return stat.st_mtime, stat.st_size | 4559d5e0179c803c7a4b23c9bd15a7317c84a2a7 | 3,635,482 |
def validate(request):
"""Method for validating a common request."""
validation = versioning.validate(request)
if validation['status'] != 'ok':
return validation
cursor = mysql.connection.cursor()
validation = player.validate(request, cursor)
if validation['status'] != 'ok':
re... | 5f4a0205dc002b994b3b49582f82594f84fcc64b | 3,635,484 |
def text_to_list(text):
""" Convert the paper into a list of preformatted sentences. """
s = symbol.substitute_symbol(text)
# Convert all characters to lowercase
s = s.lower()
# Convert text into list of paragraphs
a = s.split("\r\n")
b = ignoretopics.ignore_topics(a)
b = accenter.deacc... | c971423eaa7dcecd3f36019a852cfb400ab014c6 | 3,635,485 |
def make_anagram_dict(filename):
"""Takes a text file containing one word per line.
Returns a dictionary:
Key is an alphabetised duple of letters in each word,
Value is a list of all words that can be formed by those letters"""
result = {}
fin = open(filename)
for line in fin:
w... | c6c0ad29fdf63c91c2103cefc506ae36b64a40ec | 3,635,486 |
def test_hierarchical_seeding(RefSimulator):
"""Changes to subnetworks shouldn't affect seeds in top-level network"""
def create(make_extra, seed):
objs = []
with nengo.Network(seed=seed, label='n1') as model:
objs.append(nengo.Ensemble(10, 1, label='e1'))
with nengo.Net... | 108cc8b05f5ea30a2d8b2892e77bc0b42b880500 | 3,635,487 |
def group_property_types(row : str) -> str:
"""
This functions changes each row in the dataframe to have the one
of five options for building type:
- Residential
- Storage
- Retail
- Office
- Other
this was done to reduce the dimensionality down to the top building
types.
... | 44aa5d70baaa24b0c64b7464b093b59ff39d6d1c | 3,635,488 |
def parseLbannLayer(l, tensorShapes, knownNodes=[]):
"""
Parses a given LBANN layer and returns the equivalent ONNX expressions needed to be represent the layer.
Args:
l (lbann_pb2.Layer): A LBANN layer to be converted.
tensorShapes (dict): Shapes of known named tensors.
knownNodes ... | c915b175ecf7c99dbc675302d055393e90bf8b12 | 3,635,489 |
def write_simple_templates(n_rules, body_predicates=1, order=1):
"""Generate rule template of form C < A ^ B of varying size and order"""
text_list = []
const_term = "("
for i in range(order):
const_term += chr(ord('X') + i) + ","
const_term = const_term[:-1] + ")"
write_string = "{0} ... | 3a911702be9751b0e674171ec961029f5b10a9e7 | 3,635,490 |
def get_datatoken_minter(datatoken_address):
"""
:return: Eth account address of the Datatoken minter
"""
dt = get_dt_contract(get_web3(), datatoken_address)
publisher = dt.caller.minter()
return publisher | da71e8e05569a6cdc2661fd3f8b937510d5e037f | 3,635,491 |
def symplectic_map_personal(x, px, step_values, n_iterations, epsilon, alpha, beta, x_star, delta, omega_0, omega_1, omega_2, action_radius, gamma=0.0):
"""computation for personal noise symplectic map
Parameters
----------
x : ndarray
x initial condition
px : ndarray
px initial... | a7f71eb1e160069adbe18a3d2792310fc3c58517 | 3,635,493 |
def line_center(p0, p1):
"""
given two points p0, p1 inside a poincare disk
find the centre and radius of the arc that defines a line through them
https://en.wikipedia.org/wiki/Poincar%C3%A9_disk_model#Analytic_geometry_constructions_in_the_hyperbolic_plane
"""
u1, u2, u3 = p0
v1, v2, v3 = p... | f8af690c30423621041244ae0cb8da2eebd45063 | 3,635,496 |
import math
import decimal
def infer_decimals(value):
"""
Devuelve la cantidad de cifras decimales del valor, aplicando una heurística de corrección
previa.
Para valores del estilo 1.0000000000000001, (común al serializar números en punto flotante),
se los trunca a 17 - N dígitos, siendo N la can... | b813d5baa2c8fa6e5697a5502a1a5d299f2167a2 | 3,635,497 |
def desalt_smiles(row, smilesfield, desalter):
"""This function creates desalted smiles for a pandas dataframe row
row : row of the dataframe
smilesfiel : str (name of the smiles field in the row)
desalter : instance of Smiles_desalter class
reaction_list : list of dictionaries (rdkit reaction named... | cf722c51a6f5b01a946b2ecabe6e10f9abda6c79 | 3,635,498 |
def mesh_vertex_2_coloring(mesh):
"""Try to color the vertices of a mesh with two colors only without adjacent vertices with the same color.
Parameters
----------
mesh : Mesh
A mesh.
Returns
-------
dict, None
A dictionary with vertex keys pointing to colors, if two-colorab... | 4ba963b94e9db024c2012d8b565e5af9fb838d80 | 3,635,499 |
from typing import List
def tokens_to_smiles(tokens: List[str], special_tokens: List[str] = BAD_TOKS) -> str:
"""Combine tokens into valid SMILES string, filtering out special tokens
Args:
tokens: Tokenized SMILES
special_tokens: Tokens to not count as atoms
Returns:
SMILES repres... | ac266d84808bd20cc80e4828372c1591bef63591 | 3,635,500 |
def _get_port_by_uuid(client, port_uuid, **params):
"""Return a neutron port by UUID.
:param client: A Neutron client object.
:param port_uuid: UUID of a Neutron port to query.
:param params: Additional parameters to pass to the neutron client
show_port method.
:returns: A dict describing t... | d6857d5c6902043a1baebf582024490e70a01bd3 | 3,635,501 |
def is_unit_by_year(text: str) -> bool:
"""
是否是以年为计量单位
@param text:
@return:
@rtype: bool
"""
log.info(f'invoke method -> is_unit_by_year(), time unit text: {text}')
try:
unit = DateUnit(text.strip())
except ValueError as e:
log.error(str(e))
return False
... | 7be058b4be02a07da0ae88f7414f58f7f0eba605 | 3,635,502 |
def merge_leading_dims(array_or_tensor, n_dims=2):
"""Merge the first dimensions of a tensor.
Args:
array_or_tensor: Tensor to have its first dimensions merged. Can also
be an array or numerical value, which will be converted to a tensor
for batch application, if needed.
n_dims: Number of d... | dcf80aaa00cad4b49ecdddbe137ce9d5d8fccec8 | 3,635,503 |
def ootf_inverse_HLG_BT2100_1(F_D, L_B=0, L_W=1000, gamma=None):
"""
Defines *Recommendation ITU-R BT.2100* *Reference HLG* inverse opto-optical
transfer function (OOTF / OOCF) as given in *ITU-R BT.2100-1*.
Parameters
----------
F_D : numeric or array_like
:math:`F_D` is the luminance ... | 419a7e2f21745849bc63a7491fc144b7714065a4 | 3,635,504 |
def get_categories_for_area(area_id):
"""
Return a list of rows from the category table that all contain the given area.
"""
return request_or_fail("/area/" + str(area_id) + "/category") | 4841d072d41eae51e4d943207935f79ca9e67b57 | 3,635,505 |
def iou(box1, box2, x1y1x2y2=True):
""" iou = intersection / union """
if x1y1x2y2:
# min and max of 2 boxes
mx = min(box1[0], box2[0])
Mx = max(box1[2], box2[2])
my = min(box1[1], box2[1])
My = max(box1[3], box2[3])
w1 = box1[2] - box1[0]
h1 = box1[3] -... | 6ad0d3d7dd3a3031d28f8a0b9d0075ecf9362792 | 3,635,506 |
def mock_get_data(mocker, remote_path):
"""Mock the get_data funcion of SegmentClient class.
Arguments:
mocker: The mocker fixture.
remote_path: The remote path of data.
Returns:
The patched mocker and response data.
"""
response_data = [RemoteData(remote_path=remote_path)... | 586493a65f6428ccbd2f904a87c9c39609cddec2 | 3,635,507 |
def gen_string(**kwargs) -> str:
"""
Generates the string to put in the secrets file.
"""
return f"""\
apiVersion: v1
kind: Secret
metadata:
name: keys
namespace: {kwargs['namespace']}
type: Opaque
data:
github_client_secret: {kwargs.get('github_client_secret')}
... | ed2702c171f20b9f036f07ec61e0a4d74424ba03 | 3,635,508 |
import random
def draw_one_group_members(applications, winners_num, set_just=True,
**kwargs):
"""internal function
decide win (waiting) or lose for each group
"""
target_status = \
kwargs['target_status'] if 'target_status' in kwargs else "pending"
win_status... | 02c3f0edefea004ad731df0eae7b6aedb95a5ad2 | 3,635,509 |
def get_props_from_row(row):
"""Return a dict of key/value pairs that are props, not links."""
return {k: v for k, v in row.iteritems() if "." not in k and v != ""} | a93dfbd1ef4dc87414492b7253b1ede4e4cc1888 | 3,635,510 |
def generate_url(resource, bucket_name, object_name, expire=3600):
"""Generate URL for bucket or object."""
client = resource.meta.client
url = client.generate_presigned_url(
"get_object",
Params={"Bucket": bucket_name, "Key": object_name},
ExpiresIn=expire,
)
return url | 8a74618d5cfcd39c8394577035b497ecb5835765 | 3,635,511 |
from datetime import datetime
def get_current_time(tzinfo=timezone.utc):
"""Get current time."""
return datetime.utcnow().replace(tzinfo=tzinfo) | b77b32e1e11060dd3a5a68c7fba0b391d92f864d | 3,635,513 |
import math
def F7(x):
"""Easom function"""
s = -math.cos(x[0])*math.cos(x[1])*math.exp(-(x[0] - math.pi)**2 - (x[1]-math.pi)**2)
return s | a17060f046df9c02690e859e789b7ef2591d1a3c | 3,635,514 |
def get_local_real_format():
"""
Returns : char **rf,int *rflen
*args :
C prototype: int cbf_get_local_real_format (char ** real_format );
CBFLib documentation:
DESCRIPTION
cbf_get_local_integer_byte_order returns the byte order of integers
on the machine on which the API is being... | b35ad022544c1ec8614bed8b87cb1ce786fafa7e | 3,635,515 |
import torch
def zaxis_to_world(kpt: torch.Tensor):
"""Transform kpt from 2D+Z to 3D Real World Coordinates (RWC) for ITOP Dataset
Args:
kpt (np.ndarray): Array containing keypoints to transform
Returns:
np.ndarray: Converted keypoints
"""
tmp = kpt.clone()
tmp[..., 0] = (tm... | d925382c62d370a991fa2dfd4c51cb43d051423e | 3,635,516 |
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