content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import operator
def create_judgment_matrix(N,T,layers,v_r=[],actions=[],judgment_type="OPTIMISTIC"):
"""Creates a functionality map for input into the functionality parameter in the indp function.
:param N: An InfrastructureNetwork instance (created in infrastructure.py)
:param T: Number of timesteps to o... | cead11f406918ed290e845b4cd33a955783069f1 | 3,614,036 |
def vertically_partition_data(X, X_test, A_idx, B_idx):
"""
Vertically partition feature for party A
and B
:param X: train feature
:param X_test: test feature
:param A_idx: feature index of party A
:param B_idx: feature index of party B
:return: train data for A, B; test data for A, B
... | 58a9c3869ca9189af7c3e387cdab988cb283e07f | 3,614,037 |
from typing import Type
from typing import Any
def type_instantiate(attr_type: Type, **kwargs) -> Any:
"""
Instantiate a nominated type.
"""
while hasattr(attr_type, "__origin__"):
attr_type = attr_type.__origin__
return attr_type(**kwargs) | a42893824f52ae2bff583014f3e824634e6417e2 | 3,614,038 |
import scipy
def eval_tau(J, r, chieff, q, chi1, chi2, precomputedroots=None):
"""
Period of S as it oscillates from S- to S+ and back to S-.
Call
----
tau = eval_tau(J,r,chieff,q,chi1,chi2,precomputedroots=None)
Parameters
----------
J: float
Magnitude of the total angular m... | 04eea453e8c124c405a9e801bfba88fc691fba16 | 3,614,039 |
def make_change_dep_eval(dep,):
"""Produce an evaluation function that returns True if any change has happened on any occurence of the given dep"""
def change_dep_eval(orig,modif):
s1 = get_pairs(orig, dep)
s2 = get_pairs(modif, dep)
return s1 != s2, bool(s1)
return change_dep_eval | 0f3799832c24ce1d9021727f2917d5bb3e5ed1a9 | 3,614,040 |
from typing import Optional
def get_verse_id(book: Book, chapter: int, verse: int) -> int:
"""
Given the Book enum, chapter number int, and verse number int return the verse id if it exists.
:param book:
:param chapter:
:param verse:
:return: the integer verse id for the given book, chapter, ... | f736a39a640c97473d110be214da534e0fc06010 | 3,614,041 |
def get_fitness(cell_type,cell_neighbour_types,DELTA,game,game_params):
"""returns fitness of single cell"""
return 1+DELTA*game(cell_type,cell_neighbour_types,*game_params) | bfac50ecbe64911c145a9e6cbc9e872add774cbf | 3,614,042 |
def patch_resource(url, body):
"""
Patch resource with the given json body
:returns: http response data
"""
timer = Timer()
response = Bridge_DAO().patchURL(url, PHEADER, body)
log_data = "PATCH %s %s ==status==> %s" % (url, body, response.status)
if not response.status == 200:
... | 0dc2d2f47fc453d2902bed28158bc27be0f40101 | 3,614,043 |
def fetch_core_sketch(X, ss, **kwargs_rg):
"""
:param X: the tensor of dimension N
:param ks: array of size N
:param tensor_proj: True: use tensor random projection,
otherwise, use normal one
:return: [core_sketch:s_n\times s_n ...\times s_n,
list of sketches phis, s_n\times I_n]
"""
... | e197a823757634a5587d2aac21ad73a2be8266bb | 3,614,044 |
def test_simplify():
"""Test simplification of expr according to manual rules"""
h1 = LocalSpace("h1")
a = OperatorSymbol("a", hs=h1)
b = OperatorSymbol("b", hs=h1)
c = OperatorSymbol("c", hs=h1)
d = OperatorSymbol("d", hs=h1)
expr = 2 * (a * b * c - b * c * a)
A_ = wc('A', head=Operat... | 30e128cda58a4173fccc5f6507e6fd9926703373 | 3,614,045 |
import torch
def linear_quantize_callback(
inp: torch.Tensor,
bits: int = 8,
decimal: TensorOrInt = 5,
channel_index: int = 1,
) -> torch.Tensor:
"""quantization function with type signature of [QuantizeCallback][qsparse.common.QuantizeCallback].
Args:
inp (torch.Tensor): input tensor... | 7e40b94c665135b3a95612992280a0902144ec99 | 3,614,046 |
from bs4 import BeautifulSoup
import re
from datetime import datetime
def parse_post(content):
"""
parse response content
:param content: string
:return: Dict
"""
# parse content
soup = BeautifulSoup(content, 'lxml')
# get title
mainTitle = soup.find('div', {'id': 'mainTitle'}) ... | 352407882081cee1dbfd55a41d3beebe3ccb2bfa | 3,614,047 |
from typing import Optional
def get_ocean_token_address(
address_file: str, network: Optional[str] = None, web3: Optional[Web3] = None
) -> str:
"""Returns the Ocean token address for given network or web3 instance
Requires either network name or web3 instance.
"""
addresses = get_contracts_addres... | bf97f5de1e7258a9f8eef9f3c7277bd860f16928 | 3,614,048 |
def _get_relevant_items_by_timestamp(
dataframe,
col_user=DEFAULT_USER_COL,
col_item=DEFAULT_ITEM_COL,
col_rating=DEFAULT_RATING_COL,
col_timestamp=DEFAULT_TIMESTAMP_COL,
col_prediction=PREDICTION_COL,
k=DEFAULT_K
):
"""Get relevant items for each customer def... | 1ee48e1152d53bcf39017a1d667c2492af96599e | 3,614,049 |
def check_encryption(value):
"""
check for the --???-encryption argument
raise an exception if the given encryption is invalid
"""
value = value.lower()
if value not in ['ssl', 'tls', 'starttls', 'none']:
raise ArgumentTypeError(f'{value} is an unknown encryption. Use can use ssl... | bfb6c18de43c7cd8db6529717950231c327b808d | 3,614,050 |
from typing import Union
from typing import Dict
from typing import Any
import typing
def FloatSlider(
continuous_update: bool = True,
description: str = "",
description_tooltip: str = None,
disabled: bool = False,
layout: Union[Dict[str, Any], Element[ipywidgets.widgets.widget_layout.Layout]] = {... | 6533130c79d4a3e108f454c94dd1e203272ce3d3 | 3,614,051 |
def _apply_feature_constraints(feature, min_value, max_value):
"""Constrains `feature` to be between `min_value` and `max_value`."""
if min_value is not None:
feature = tf.math.maximum(feature, min_value)
if max_value is not None:
feature = tf.math.minimum(feature, max_value)
return feature | 85352d537cddf8409b02fdaa97b385dcc8a928c2 | 3,614,052 |
def configure_global_stackwise_virtual(device, domain=None):
""" Enables global stackwise-virtual on target device
Args:
device ('obj'): Device object
domain ('str'): Stackwise-virtual domain
Returns:
None
Raises:
SubCommandFailure
"""
... | 6f37c07ec94a488b29df909cf5fc826741a43b74 | 3,614,053 |
import six
import hashlib
def run_server(locker, register=True):
"""Runs tickets server."""
_LOGGER.info('Tickets server starting.')
# no __init__ method.
#
# pylint: disable=W0232
class TicketLockerServer(gssapiprotocol.GSSAPILineServer):
"""Ticket locker server."""
@utils.e... | ed9ee1f0f8c0be63e9476f16c5fb4ecd26d15871 | 3,614,055 |
def verify_incall_state(log, ads, expected_status):
"""Verify phones in incall state or not.
Verify if all phones in the array <ads> are in <expected_status>.
Args:
log: Log object.
ads: Array of Android Device Object. All droid in this array will be tested.
expected_status: If Tru... | a20f88770e92a6f61ac5376e3a7827cf3c82c1f2 | 3,614,056 |
from typing import Tuple
import math
def euclidean_distance(
point: Tuple[float, float], origin: Tuple[float, float] = None
) -> float:
"""Calculate euclidean distance from the origin"""
if origin is None:
return math.sqrt(sum((p ** 2 for p in point)))
else:
assert len(origin) == len(p... | b248122c6700d90182d68a35a43c7ad47b968667 | 3,614,058 |
def perspective_edit(request, perspective_id, response_format='html'):
"""Perspective edit"""
perspective = get_object_or_404(Perspective, pk=perspective_id)
# Don't let users delete their last perspective
other_perspectives = Perspective.objects.filter(
trash=False).exclude(id=perspective_id)
... | 353dcb3f963cc3aa82e69b42d83fb0f6d901927d | 3,614,059 |
def _extract_key(obj):
"""Convert a handle or Event handle into a Database Event ID."""
if isinstance(obj, Event):
return obj.id
elif isinstance(obj, str):
return obj
raise TypeError('Must provide an Event or Event handle (string)') | 1b4a3fb64d77ddc196238739f483246a7bf67cb1 | 3,614,060 |
def convolve_adjoint_filter(x, y, ndim, input_multi_channel=False,
output_multi_channel=False, mode='full'):
"""Convolution adjoint.
Args:
x (array): input array with shape batch_shape + input_shape
if input_multi_channel=False.
Otherwise with shape ... | ec8e26c0a199600fec21ce0a400f9685054e0032 | 3,614,061 |
def getCompletedJobs(jobs):
"""
Gets all completed jobs
"""
completed_jobs = []
for job in jobs:
if 'result' in job:
completed_jobs.append(job)
return completed_jobs | 7193cae304fb0498f9fe50f0302e50699d7e96e3 | 3,614,062 |
def read_pergene_file(pergene_insertions_file,chrom):
"""Reading the pergene file , the information per gene , related to where it starts and ends in the genome.
Parameters
----------
pergene_insertions_file : str
absolute path of the per gene file location
chrom : str
Name of the ... | e9629c5a9621784be6eb6efbd1e8793f2ac5b67e | 3,614,063 |
import math
def gam_a98rgb(rgb):
"""Convert an array of linear-light a98-rgb in the range 0.0-1.0 to gamma corrected form."""
return [math.copysign(math.pow(abs(val), 256 / 563), val) for val in rgb] | 6d2543dc28ac6533067ffe9b0a265ef093416f9e | 3,614,064 |
import socket
def conflictBetweenIPv4AndIPv6():
"""
Is there a conflict between binding an IPv6 and an IPv4 port? Return True
if there is, False if there isn't.
This is a temporary workaround until maybe Twisted starts setting
C{IPPROTO_IPV6 / IPV6_V6ONLY} on IPv6 sockets.
@return: C{True} ... | bef744d6f066e3aafbe7644662d8d87e4b139abb | 3,614,065 |
import copy
def unlock_layer(wC, uC, noise=0.0):
"""
unlock a layer of a scale invariant MERA
Args:
wC, uC (list): MERA tensors
noise (float): amplitude of noise to be added to the new layer
Returns:
wC, uC (list): new MERA tensors
"""
wC.append(copy.copy(wC[-1]))... | 9bad36a4d31e8411a14fa13d520f13e2d71167b9 | 3,614,066 |
def conformal2geodetic(conformal_lat: "ndarray", ell: Ellipsoid = None, deg: bool = True) -> "ndarray":
"""
converts from conformal latitude to geodetic latitude
like Matlab map.geodesy.ConformalLatitudeConverter.inverse()
Parameters
----------
conformal_lat : "ndarray"
conformal latit... | 5a26f3b1cd8b0b43739db2f936a6b42c79bf6e19 | 3,614,067 |
def get_frame_subframe(sfn_sf):
""" Get the frame and the subframe number from the
received bitstring
"""
sfn_sf_list = []
frame_mask = ~((1<<4) - 1)
frame = (sfn_sf & frame_mask) >> 4
sf_mask = ~(((1<<12) - 1) << 4)
subframe = (sfn_sf & sf_mask)
sfn_sf_list.append(frame)
sf... | d623ef8c1fa97dfbd5b5ef2a99e52e045d5dd205 | 3,614,068 |
def make_renderer(nodes, use_binary_transport=False):
"""Creates the pydeck visualization for rendering"""
view_state = pydeck.ViewState(
offset=[0, 0],
latitude=None,
longitude=None,
bearing=None,
pitch=None,
zoom=10,
)
views = [pydeck.View(type="OrbitVi... | dc6438f4e48d5fc6fcd4eaca46603e1b0d022874 | 3,614,069 |
def get_secret_value(secret_name):
"""
get secret value from AWS Secrets Manager
:param secret_name: name of the secret passed
:return secret_value: value of the secret passed
"""
client = session.client(service_name='secretsmanager')
secret_value = ''
try:
get_secret_value_respo... | 70af6ce869ad816de15e99259868cc020071c217 | 3,614,070 |
import torch
def true_positive_fraction(output, target):
"""True positive fraction of binary segmentation."""
output, target, was_numpy = _convert_to_torch(output, target)
result = _true_positives(output, target) / (torch.sum(output) + torch.sum(target))
return _convert_to_scalar(result, was_numpy) | 5c6a7f7df36213da5383c8105910e59fee539e97 | 3,614,071 |
def backend_parameter(func):
"""Decorator for parameters reading data from the backend.
Errors are handled in a default way.
"""
def _func_wrapper(self: 'VehicleState', *args, **kwargs):
# pylint: disable=protected-access
if self._attributes is None:
raise ValueError('No dat... | c12baada4759e475eb554eafffc0aff620f049ac | 3,614,072 |
import re
def _build_freetext_query(querystring):
"""
Parses the freetext argument 'nyckelord' in the following ways:
'word1 AND word2' => word1 and word2
'"word1"AND"word2"' => word1 and word2
'"word1 word2"' => word1 and word2
'word1 OR word2' => word1 or word2
'"word1"OR"word2"' => word... | 53a717351c85323bf02df47ce87daab8b9497ae4 | 3,614,073 |
def get_course_list(only_active=True, sortedby="name"):
""" Return a list of courses.
By default only active courses.
will be ordered by given field.
[{id:, name:, title:}, ]
"""
clist = []
reload_if_needed()
for course in COURSES:
if only_active:
if COURS... | ef0b4ef4606e9d3cb157efb34decb144caf8e8a7 | 3,614,074 |
def covars_for_custom_models_simple_training_data_4elements():
"""
defines initial covars compatible with custom_models_simple_training_data_4elements above
:return: covars (list of tuple)
"""
covars = [(0.0, -2.0, 2.0)]
return covars | f21cfa472c03811758dfb5196594f93f6e8247c6 | 3,614,075 |
import six
def create(ctxt, name, source_instance_id, description=None):
"""Creates migration.
Raises:
MigrationCreateFailed: If there is error during migration creation.
InstanceNotReadyForMigration: Migrating instance failed
pre-migration validations
... | 25402f56013cc5da7d3483200f0ab94532332624 | 3,614,076 |
def get_asgi_application():
"""
The public interface to Django's ASGI support. Return an ASGI 3 callable.
Avoids making django.core.handlers.ASGIHandler a public API, in case the
internal implementation changes or moves in the future.
"""
django.setup(set_prefix=False)
return ASGIHandler() | 5e3c760f58005ea84a623305661294f5e9724504 | 3,614,077 |
from typing import List
from typing import Dict
from typing import Union
def generate_html(d: List[Dict[str, Union[str, bool]]]) -> str:
"""
Pass in a dict with a list of rows to include in a formatted table. This will return the HTML for the table.
:param d:
:return:
html: HTML formatted tab... | f874c63735443bb3b68355905e59f5efbc5b50af | 3,614,078 |
from typing import List
from typing import Union
def flip_random_flippable(reconstructed_edges: List[Edge],
initial_weight: int) -> Union[int, None]:
"""
Flips a random flippable edge in the provided solution.
Args:
initial_weight: - Initial solution weight.
reco... | 0f7b4ebc5f99487e171d422554871b3d20833f33 | 3,614,079 |
import typing
def _de_bruijn(k: int, n: int) -> typing.List[int]:
"""Generate a De Bruijn sequence.
This is a piece of mathematical heavy machinery needed for O(1) ctz on
integers of bounded size. The algorithm is adapted from chapter 7 of
Frank Ruskey's "Combinatorial Generation".
Args:
... | bbb86a4f0a7ef03bbce29126cc56e4fb3e41e288 | 3,614,080 |
def preprocess_data(x):
"""Preprocess data. Ensure x is 2d ndarray, and scale so that the mean absolute
amplitude of each column is one.
:param x: ndarray, shape (n_samples,) or (n_samples, n_features)
:returns: float ndarray, shape (n_samples, n_features)
"""
x = np.array(x, dtype=np.float64)... | 1d696d754db5849c7b092b3a70913ebf164b4df2 | 3,614,082 |
def left_edge_vertical_ids(shape):
"""Link IDs of left edge vertical links.
Parameters
----------
shape : tuple of int
Shape of grid, given as (rows, columns) of nodes.
Returns
-------
ndarray :
Link IDs of left edge vertical links. Length is
(rmg.number_of_rows - 1... | 9ff1e8caa66b27deae5b2086de5b40a03917a8ad | 3,614,083 |
def guess_dim_transition_linebyline(filename):
"""get number of histogram bins from transition matrix file (one line per entry!!!)"""
#print "Reading...", filename
with open(filename,"r") as f:
count = 0
for line in f: # skip lines starting with #
if not line.startswith("#"):
... | f0cb5bb788195c0b2369d588e2e9d8e9caa3c5f1 | 3,614,084 |
from typing import List
from typing import Dict
def deduplicate(new_data: List[Dict]) -> List[Dict]:
""" Checks for duplicates and omits them """
old_data = load_data()
data = []
for new in new_data:
if all(new['tweet_id'] != old[2] for old in old_data):
data.append(new)
return... | b648ea4cfc9a8d14e6eff822e56680fdcb1e17eb | 3,614,085 |
def identify_necessary_covariates(dependents, definitions):
"""Identify covariates necessary to compute `dependents`.
This function can be used if only a specific subset of covariates is necessary and
not all covariates.
See also
--------
respy.likelihood._compute_x_beta_for_type_probability
... | 08f6db315a1c1281ef2ffae4efc1ccda78f3e95e | 3,614,086 |
def delete_event(current_user, event_id):
"""
Deleting a User Event from the database if it exists.
:param current_user:
:param event_id:
:return:
"""
try:
int(event_id)
except ValueError:
return response('failed', 'Please provide a valid Event Id', 400)
user_event = ... | eb4977198c87294eb0980932dfd17e572d950bbf | 3,614,087 |
def make_meeting():
""" Generate a new dummy meeting and save it. """
meeting = frappe.get_doc({
"doctype": "Meeting",
"title": "Test Meeitng",
"status": "Planned",
"date": "2017-07-20",
"from_time": "09:00",
"to_time": "09:30",
"minutes": [
{
"description": "Test minute 1",
"status": "Open",... | 047c3ed250e5cda64bea859ddcfd0a3c3a7a8b3c | 3,614,089 |
def test_authorize_scalar_attribute_eq(post_fixtures):
"""Test authorization rules on a relationship with one object equaling another."""
# Object equals another object
Oso.load_str(
"""
allow(actor: test_app2::User, "read", _: test_app2::Post{created_by: actor, access_level: "private"});
... | 0b3727b4bcc4e3f61d53f3b06228f1e05f7287d1 | 3,614,091 |
def load_template(template_file_path):
"""
Load a Jinja2 template and return it
Args:
template_file_path (str): path to the Jinja2 template file
Returns:
Template: contains jinja2 template
"""
return Template(open(template_file_path).read()) | 7841065523262a2c049d783df1c06b27c65b3cf6 | 3,614,092 |
def template_used(response, template_name):
"""Asserts a given template was used (with caveats)
First off, this is a gross simplification of what the Django
assertTemplateUsed() TestCase method does. This does not work as a
context manager and it doesn't handle a lot of the pseudo-response
cases.
... | f8a878d27c5379b0b2f2fac2a08fbeee91607858 | 3,614,093 |
def _sign_trace(s11, s22, s33):
"""Calculate sign of trace. Sign of 0 is set to 1.
Parameters
----------
s11: array_like
Component 11 of 3D tensor.
s22: array_like
Component 22 of 3D tensor.
s33: array_like
Component 33 of 3D tensor.
Returns
-------
numpy.nd... | d0557995bd5662e84939536b2e220acf6e0ce460 | 3,614,094 |
def read2dlv(filename):
"""Read LabView 2D array and return as numpy array.
Big-endian version.
"""
if isinstance(filename, str):
f = open(filename, 'rb')
else:
f = filename
dims = np.fromstring(f.read(8), dtype=np.dtype('>u4'))
ccd_temp = np.fromstring(f.read(), dtype=np.dt... | 911a62eac2b43fca607f95aefdd845d7c67877bb | 3,614,095 |
import click
def ensure_remote(ctx, param, value):
""" Ensure --remote is used. """
# pylint: disable=unused-argument
if value and ctx.params.get('remote') == (None, None):
raise click.BadParameter('Invalid without "-r" / "--remote" option')
return value | d22f8d73e4b5ec57cc18607918775778d09efc67 | 3,614,096 |
def edit_draft_service(draft_id):
"""
Edit a draft service
:param draft_id:
:return:
"""
updater_json = validate_and_return_updater_request()
update_json = validate_and_return_draft_request()
page_questions = get_request_page_questions()
draft = DraftService.query.filter(
D... | db734fb9bf2b3cdaa9f89162e08875215cd4dfad | 3,614,097 |
def is_lisp_like(view):
""" Check for a lisp like file using the current language/syntax setting """
return get_dialect(view) != '' | c6b6f4df062173421b8300bf9e82e1240213f692 | 3,614,098 |
from typing import Callable
import types
import json
def _execute(cls, app_engine: AppKernelEngine, provisioner_method: Callable, model_class: Model):
"""
The main view function for flask routes.
:param app_engine: the app engine instance
:param provisioner_method: the method on our service object whi... | 8b2ffd71bc512afad0657ea5695b7a281cde5f86 | 3,614,099 |
import tqdm
def get_all_mask_volumes():
"""
Purpose:
Returns all masks for dataset in a single numpy array of 32 bit floats.
Shape will be 259x240x240x155x1
"""
all_patient_paths = get_each_hgg_folder()
# preallocate empty np array to hold all the masks
# dim 0 ... | 661e64bdd550f98ae4861384da558981bb2e887e | 3,614,100 |
def prepare_training_data(sessions):
"""
Convert extracted session into training data
:param sessions: list of sessions
:return:
"""
purchase_sessions = []
abandon_sessions = []
for s in sessions:
# check that purchase action occurs after add action
if Actions.purchase... | 41ae799dcc815a1da5b89d6718bad7c0f84b375c | 3,614,101 |
import torch
def nx_to_graph_data_obj_simple(G, partial_charge=False):
"""
Converts nx graph to pytorch geometric Data object. Assume node indices
are numbered from 0 to num_nodes - 1. NB: Uses simplified atom and bond
features, and represent as indices. NB: possible issues with
recapitulating rel... | e080aec34468e4948ca38dd162d864e8dc5dd4ba | 3,614,102 |
def after_replace(func, target=None):
"""Request `func` be invoked as `func(self, old)` when `model` is about to
replace an older version of itself. Alternatively when applied to a
collection, request `func(key, old, new)` be invoked.
::
@acid.events.after_replace
def after_replace(sel... | a1c84c1c6a9cc04bd46c04b68410f33d5a26dd13 | 3,614,103 |
def construct_sequence(seq_dict):
"""Construct RnaSequence from dict of {pos:residue}.
seq_dict -- dictionary of {position: residue}
Checks whether the first residue is 0. Checks whether all residues
between min and max index are present. No checking on validity of
residue symbols.
"""
... | cb150f3400807dd22ca1044a68f4a62faa279c1c | 3,614,105 |
def _cauchy_ ( self , mu , gamma ) :
"""Generate Cauchy random numbers
- rely on the distribution of the ratio for two Gaussian variables
- see https://en.wikipedia.org/wiki/Cauchy_distribution
"""
g1 = self.gauss ( 0.0 , 1.0 )
while abs ( g1 ) < _fmin : g1 = self.gauss ( 0.0 , 1.0 )
g2 = ... | 724afa6a7bf733227ae1fa03614785ba6f622b8c | 3,614,106 |
def get_group_cpu_name(ifamily, category, device):
"""
Abstract layer to group i3, i5, i7 families.
:param ifamily: which series of cpu we want to group
:param category: category to make sure the input is processor
:param device: device to check
:return: grouped device name
"""
ifamily_... | 46b3bf00540e9147f6e4bab3a1431bd8497009a6 | 3,614,107 |
def median(values):
"""Return median value for the list of values.
@param values: list of values for processing.
@return: median value.
"""
values.sort()
n = int(len(values) / 2)
return values[n] | c40b9e0b2cdd2b00ae6692aed2cfe9787bc8f9df | 3,614,108 |
def remove_default_create_options(options):
""" Return only non default create options """
_options = options.copy()
for opt in IPSET_DEFAULT_CREATE_OPTIONS:
if opt in _options and \
IPSET_DEFAULT_CREATE_OPTIONS[opt] == _options[opt]:
del _options[opt]
return _options | cbfdbbfab149cea698e912db0d3271ddcb97a20e | 3,614,109 |
import numpy
def _grid_3d(dx, dy, dz, order):
"""Generate 3D structured grid."""
# Internal functions
def meshgrid(x, y, z, indexing="ij", order=order):
X, Y, Z = numpy.meshgrid(x, y, z, indexing=indexing)
return X.ravel(order), Y.ravel(order), Z.ravel(order)
def mesh_vertices(i, j, k... | 4204f54c0629fa17d4f8ffff997cfce735e4307c | 3,614,110 |
def title_keywords(title):
"""Given a title, returns every author assigned keyword"""
q = """ SELECT GROUP_CONCAT(keyword)
FROM OriginalKeywords
WHERE ArticleID='{t}'""".format(t=title)
curr.execute(q)
return curr.fetchall()[0][0].split(',') | 2560ca23e91f3347c6bbb77c285b5f9a6fac7a75 | 3,614,111 |
import torch
def collate_fn(batch, transforms):
"""Collate function to be passed to the PyTorch dataloader.
Parameters
----------
batch : list
Uncollated batch of size `batch_size`.
device : str or torch.device
Current working device.
transforms : callable
Transformati... | 89daebd2f58d9a7b83c7bd7c14cdde2ed16d8b3d | 3,614,112 |
def persistence_function_from_model(model, G_interlayer, layer_vec=None, N=None, T=None, Nt=None):
"""
Returns a function to calculate persistence according to a given multilayer model
:param model: network layer topology (temporal, multilevel, multiplex)
:param G_interlayer: input graph containing all... | 9e3998ac4beb0ed653f6482a550fbde5e6c75eeb | 3,614,113 |
def sanitizer(name):
"""
Sanitizes a string supposed to be an entity name. That is,
invalid characters like slashes are substituted with underscores.
:param name: A string representing the name.
:returns: The sanitized name.
:rtype: str
"""
return name.replace("/", "_") | f59aa75a40067068c711a4ca01b643c69d43cd0c | 3,614,114 |
def fget_wcs(fitsfile_path):
"""Get the World coordinate system (wcs) from the fits header for plotting.
Parameters
==========
fitsfile_path: str
The input fits path
Return
======
wcs: `astropy.wcs.wcs.WCS`
Image coordinates in WCS format
"""
hdu = fits.getheade... | e85e903a0dc3ff624fa2e1d053f7225932601c8d | 3,614,115 |
def is_repository_setup():
"""Indicates if base repository is setup or not.
"""
return repository_cache.get_value() is not None | 0ab19dba941fe5af6359a3ed6b725a751dca3b41 | 3,614,116 |
def ISURL(value):
"""
Checks whether a value is a valid URL. It does not need to be fully qualified, or to include
"http://" and "www". It does not follow a standard, but attempts to work similarly to ISURL in
Google Sheets, and to return True for text that is likely a URL.
Valid protocols include ftp, http,... | e1362d9cfe97b35e935d072da1aa1791acd24371 | 3,614,117 |
def transaction_class(cls):
"""
Return the associated transaction class for given versioned SQLAlchemy
declarative class or version class.
::
from sqlalchemy_continuum import transaction_class
transaction_class(Article) # Transaction class
:param cls: SQLAlchemy versioned decla... | 054bf2e31b7c4132928192c21317ad898ed13dde | 3,614,118 |
def _GenerateRootGradle(jinja_processor):
"""Returns the data for the root project's build.gradle."""
variables = {'template_type': 'root'}
return jinja_processor.Render(_JINJA_TEMPLATE_PATH, variables) | cfb28ff7fe2dffb1e451bce9e94b51ef17286209 | 3,614,120 |
def measure_display_label(src_type):
"""update label upon modification of Radio Items"""
source_label, measure_label = get_source_labels(src_type)
source_unit, measure_unit = get_source_units(src_type)
return 'Measured %s (%s)' % (measure_label, measure_unit) | 70e7ffc3dddc7b92cce79d66985b283d088759f3 | 3,614,121 |
def only_choice(values):
"""Apply the only choice strategy to a Sudoku puzzle
The only choice strategy says that if only one box in a unit allows a certain
digit, then that box must be assigned that digit.
Parameters
----------
values(dict)
a dictionary of the form {'box_name': '123456... | c8760594858a48aaa97e62ffbbb2f290bcff4e1f | 3,614,122 |
def get_xml_storage_model():
"""
Return the configured xml storage model class using apps.get_model()
"""
app, model = acs_settings.XML_STORAGE_MODEL.split(".")
return apps.get_model(
app_label=app,
model_name=model
) | 03285f7c8ad7f781c4a82ac22d86cbbe0291c96b | 3,614,123 |
def _get_deployments_digest_by_uid(uid):
""" Get list of deployments for a reference designator; return digests.
(See also event_tools.py, get_deployment_events. Supports asset management Deployment tab.)
"""
results = []
try:
# Get vocabulary dictionary once.
vocab_dict = get_vocab(... | ab3b689e9b6d47b0bb10a06cfc105f03493a15f4 | 3,614,124 |
def layout_arc_with_drc_exclude(
cell, layer, drc_layer, center, r, w, theta_start, theta_end, ex=None, **kwargs
):
""" Layout arc with drc exclude squares on sharp corners"""
dpoly = layout_arc(cell, layer, center, r, w, theta_start, theta_end, ex, **kwargs)
dpoly.layout_drc_exclude(cell, drc_layer, ex... | 38bfe0f29f0a9e2a4ea3b7ad0ca43fdb5ee6ce5e | 3,614,125 |
def create_fake_user():
"""
Generate new user and saves to database
"""
user = User.objects.create(username=faker.first_name_male())
return user | 71e141e6b2f34f4cc1453dffee113117125ce782 | 3,614,126 |
def control_brightness(how, level):
"""Control brightness level."""
_change_brightness(how, level)
_send_notification()
return 0 | 624e69d94c4d763699aff93d46482ecaa5c664df | 3,614,127 |
def has_negative_control(cmd):
"""Return whether a command has negatively controlled qubits."""
return get_control_count(cmd) > 0 and '0' in cmd.control_state | 94c5ab2773f946dc6c598e64c91ea7d90ec83b08 | 3,614,128 |
def qg8_graph_load(filename: str):
""""
Load a QG8 graph from file chunk by chunk
"""
f = qg8_file_open(filename, QG8_MODE_READ)
if f is None:
return None
graph = qg8_graph([]) # create empty graph object
i = qg8_file_iterator(f)
while qg8_file_has_next(i): # EOF check
... | 6c6b2ab78131fb9454c782aade283f59e223400a | 3,614,129 |
def all_reduce(tensor, op=dist.ReduceOp.SUM, group=dist.group.WORLD):
"""
Reduces the tensor data across all machines in such a way that all get
the final result.
After the call the returned tensor is going to be bitwise
identical in all processes.
Arguments:
tensor (Tensor): Input of ... | ecdd395272ff314a77b8e765d0f825cf7329fad2 | 3,614,130 |
def _get_stock_ledger_entries(filters):
"""
Get data from Stock Ledger Entries with the following fields:
(1) date, (2) item_code, (3) actual_qty, (4) qty_after_transaction,
(5) project, (6) stock_uom, (7) item_name
:param filters:
:return: Stock Ledger Entries
"""
item_code = filters.ge... | 6ed2ce915876b1232c695619c4823db789be0a61 | 3,614,131 |
def parse(tokens):
"""Parses the infix permission ``tokens`` into a postfix instruction list.
:param tokens: The token list produced by :func:`~pwh_permissions.tokenise`
:type tokens: ``list``
:return: The token list in postfix notation
:rtype: ``list``
"""
result = []
stack = []
bu... | 1e4bc897ec205112004aca56d49606e0726de27a | 3,614,132 |
def roots_legendre_interval(n, a, b):
"""
Computes the sample points and weights for Gauss-Legendre quadrature
on interval `[a, b]`.
The sample points are the roots of the n-th degree Legendre polynomial
`P_n(x)`. These sample points and weights correctly integrate
polynomials of degree `2n - 1... | 2e0e09785ec9557dbe4cc1c368d7401c581f947e | 3,614,133 |
from typing import Optional
from typing import List
from typing import Tuple
from pathlib import Path
def get_physical_dependencies(obj: str, lib: str, include_self: bool, job: Optional[IBMJob]=None, verbose: bool=False) -> List[Tuple[str, str, str]]:
"""Get the dependencies for a given physical file object
... | 8e358ef3a2b0210668ce1a4c88235c7975005138 | 3,614,134 |
def compute_counters(data):
"""
Returns the number of times a separator is in each line.
"""
counters = np.zeros((len(data), len(SEPARATORS)))
for i, line in enumerate(data):
counters[i] = [get_character_count(line, sep) for sep in SEPARATORS]
return counters | 9c115cad6a543939ca6601183bf31d976abd7a80 | 3,614,136 |
def mishActivation(x):
""" Mish Activation Function """
return x * tf.math.tanh(tf.math.softplus(x)) | d66dd5a2ee371e7937aa69ddf00ffc7481dc0d32 | 3,614,137 |
from clawpack.geoclaw import topotools
from numpy import array
import netCDF4
import xarray
def read_netcdf(path, zvar=None, extent='all', coarsen=1, return_topo=True,
return_xarray=False, verbose=False):
"""
:Input:
- *path* (str) - Path to the file to read, or url to remote file,
... | 9f28f25e7c7f9be856825843421f42a2f37027bf | 3,614,139 |
def quantize(v, unit):
"""Quantize value `v` to a multiple of `unit`. When `unit` is an integer,
the return value will be integer as well, otherwise the function will
return a float.
Parameters
----------
v : ndarray or number
Number to be quantized
unit : number
The quantiz... | 55f3b88d28dc94430cd7741f6f1e2603b208054e | 3,614,140 |
def next(dist, median, d1, d2, p, N):
"""
INPUT
dist: distance matrix
median: list of integers for selected vertices
d1: list of nearest facility for each vertex
d2: list of second nearest facility
p: number of facilities to locate
N: number of vertices on the nextwork
OU... | 00bb21f286b29659358c91144567940ba4cbf758 | 3,614,141 |
def stop():
"""
Stop the currently running recipe.
:return:
object
response
One of:
ok
error
message
Only present if response is "error" and there is a message to present to the user.
"""
recipes.stop()
return jsonify({... | 2c7dd7ff86d373877c9493b2027d0134624428f1 | 3,614,142 |
import textwrap
def loadings_histograms(
pca, feature_labels, n_components='all', bins=50,
n_features_to_label=10, max_text_len=35,
text_kws={'color': 'white',
'bbox': {'facecolor': 'k', 'alpha': 0.7, 'pad': 1}},
save_fig=None):
"""Plot histograms of the loadings ... | 70e0248b76f543100704445467be7c52f760e16a | 3,614,143 |
import re
def password_string(value):
"""密码输入类型"""
if len(value) < 8 or len(value) > 20 or re.match(r'^(?![0-9]+$)(?![a-zA-Z]+$)[0-9A-Za-z]{6,20}$', value) is None:
raise ValueError('密码至少包含 数字和英文，长度6-20,不能出现非法字符')
return value | e6bfcc473c164cd06e3acd65165f6fb9dcd251cf | 3,614,144 |
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