content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import time
def split_cp(model, Xtrain, Ytrain, Xtest, labels = [0,1], out_file = None, validation_split = 0.2, seed = 42):
"""Runs split/inductive CP for all points in Xtest
"""
# Split data in training and calibration set
Xtrain, Xval, Ytrain, Yval = train_test_split(Xtrain, Ytrain, test_s... | b4d37eecf7afc6e4c4c3c40adb414c72de09124c | 76,557 |
from typing import Union
def np_sample_stratified(
X: np.ndarray,
y: np.ndarray,
n: int = None, # Like df.sample and np.random.choice
frac: float = None, # Like df.sample, unlike np.random.choice
replace: bool = False, # Like df.sample, unlike np.random.choice
random_state: Union[int, np.ra... | 6171e457f529c7dcd59cce1087963660d0ba0078 | 76,558 |
from typing import Union
from typing import Callable
def get_shortname(x: Union[FuncBase, SymbolNode]) -> str:
"""Compatibility helper for mypy 0.750 vs older."""
fn: Union[str, Callable[..., str]] = x.name
if callable(fn):
return fn()
return fn | 7e1ea2370555cb7fa9a40f2bf731d6f0e426f7b4 | 76,560 |
def read_netrc(ctx, filename):
"""Utility function to parse at least a basic .netrc file.
Args:
ctx: The repository context of the repository rule calling this utility
function.
filename: the name of the .netrc file to read
Returns:
dict mapping a machine names to a dict with the... | 3f80ffa81a58b7a49c323e7deae116c84f57b174 | 76,561 |
from re import T
from operator import ne
def tanh(x: T.Tensor) -> T.Tensor:
"""
Elementwise hyperbolic tangent of a tensor.
Args:
x: A tensor.
Returns:
tensor: Elementwise hyperbolic tangent.
"""
return ne.evaluate('tanh(x)') | f844998b6ea87f0d0b530c5a3a57c2a40a115b64 | 76,562 |
import json
async def list_devices(websocket, ide):
"""
:param websocket:
:param ide:
:return:
"""
payload = json.dumps({
"id" : ide,
"type": "hassbrain/device/list"
})
res = await _send(websocket, payload)
return res['device_list'] | c975b235c283c4847aab747d83160e067861bff4 | 76,564 |
def compute_neighbours_matrix(src, d_matrix, radius, n_simil):
"""Compute the set of neighbours of each point in the brain discretization.
Parameters
-----------
src : :py:class:`~numpy.ndarray` of :py:class:`~float`, shape (n_verts, 3)
The coordinates of the points in the brain discretization... | 6ea0367897d76ac25a06a3f50d3a42176f0345bc | 76,565 |
def team_rm_from_repository_payload(team_default_payload):
"""Provide a team payload for removing a team from a repository."""
removed_from_repository_payload = team_default_payload
removed_from_repository_payload["action"] = "removed_from_repository"
return removed_from_repository_payload | 9ffd60f86fa0e4daee0b5c4d73890653e64a47c7 | 76,568 |
async def fetch_installations(
requester=Security(get_current_access, scopes=[AccessType.admin, AccessType.user]),
session=Depends(get_session)
):
"""
Retrieves the list of all installations and their information
"""
if await is_admin_access(requester.id):
return await crud.fetch_all(ins... | 854d6113f86aa31f93d0ece2ece3cd0bc0e6d7f9 | 76,570 |
def extract_parts(note):
"""Search a given chunk of markup for specific references.
:param note: the `BeautifulSoup` version of the markup to parse
:returns: a tuple of the title, headers, and content
"""
parts = note.find_all('div')
if len(parts) == 3:
title, headers, content = parts
... | cfda6dc2a8ebe51dd5c72e4bdcf2125bc1e9f60a | 76,572 |
import json
def pdf_to_html_retrieve_view(request): # pdfToHtmlRetrieve
"""
return a URL to a s3 file that contains the html rough equivalent of the PDF
:param request:
:return:
"""
voter_device_id = get_voter_device_id(request) # We standardize how we take in the voter_device_id
pdf_url... | 911c95808e69c59cf76450f343b36246edc1904a | 76,573 |
from typing import Dict
def delete_workflow(user: User, workflow: Workflow) -> Dict[str, str]:
"""
Delete a workflow from the database and filesystem
:param user:
:param workflow:
:return:
"""
if is_write_permitted(user, workflow):
workflow_id = workflow.id
db.session.delet... | a20aa19370f0c7730f22582d73b9b018fb4e94c1 | 76,574 |
def get_diffs(routes1, routes2, route_ids):
"""Get difference in number of routes using each segment.
params
- routes1: Dict{str : List[(lon, lat)]} - first set of routes
- routes2: Dict{str : List[(lon, lat)]} - second set of routes
- route_ids: List[str] - IDs of routes to consider
return... | 08853ca746adc459d5d094a4d81af4358f58607f | 76,575 |
from pathlib import Path
from typing import List
def get_packages_from_requirements(basedirpath: Path,) -> List:
"""Extract packages from requirements.txt as Python list"""
with open(basedirpath, "r") as f:
lines = f.readlines()
return lines | ca0c85e6175f7026781607bce06ed42d6344db1a | 76,576 |
def setup_subscription_last_run(
client, first_fetch_time, last_run, sub_name, ack_incidents
):
"""
Setups the subscription last run data, and seeks the subscription to a previous time if relevant
:param client: PubSub client
:param first_fetch_time: First fetch time provided by the user
:param ... | 55bb40be123c8797e965f0978a5f17f6c8880572 | 76,579 |
def get_bgp_status():
"""Get BGP statuses"""
cpu_status = GetThisDataFromDevice.get_bgp_status(request.json.get('ip'), request.json.get('port'), request.json.get('username'), request.json.get('password'))
return {'data': cpu_status} | cdd40dd6ebc8fa519ecf69c57fe8c52481c2bb71 | 76,580 |
import binascii
def create_request(version, buffer):
""" Creates a request packet and returns it as a byte string.
buffer is a command to be sent, version should be 2 for current versions of NRPE. """
p1 = _create_packet(version, NRPE_REQUEST, 0, NRPE_OK, buffer)
crc = binascii.crc32(p1) & 0xffffffff
... | 3756df012459cc46dd40041f49885eaa8f359354 | 76,581 |
def group_refs(refs):
"""
Group all adjecent x/y references.
>>> group_refs([(0, 0), (0, 2)])
[[(0, 0)], [(0, 2)]]
>>> group_refs([(0, 0), (0, 2), (0, 1)])
[[(0, 0), (0, 1), (0, 2)]]
"""
if not refs:
return []
grouped = [[refs[0]]]
for ref in refs[1:]:
added_... | 44110715690b47c875efc6d50011a49e0b0e7d50 | 76,582 |
def get_attributes_and_labels(data):
"""
:param data: The dataset to be divided
:return: Two panda frames which are in order of classes and attributes
"""
# Here we divide our attributes and classes features for a given dataset
return [data.iloc[:, -1], data.iloc[:, :-1]] | c383dad4720093b4002415b48d793bab5834c3fd | 76,583 |
import random
def get_random_user_agent():
"""
Get a random user agent string.
:return: Random user agent string.
"""
return random.choice(get_data('user_agents.txt', USER_AGENT)) | aabb09773da3c1c2438717edd4546e96883c1cb6 | 76,584 |
def _read_fzx(instream):
"""Read FZX binary file and return as properties."""
data = instream.read()
header = _FZX_HEADER.from_bytes(data)
n_chars = header.lastchar - 32 + 1
# read glyph table
char_table = _CHAR_ENTRY.array(n_chars).from_bytes(data, _FZX_HEADER.size)
# > Notice that offsets ... | 4b171d48e574dfe4f519f2b6a8d687b6c1094f45 | 76,585 |
def _code_snippet(snippet: str) -> str:
"""Generates a markdown code snippet based on python code.
Args:
snippet (str): Python code.
Returns:
str: Markdown code snippet.
"""
result = "```python\n"
result += snippet + "\n"
result += "```\n\n"
return result | 5c44bccba225dbd6d60f19c712393b291fe065b5 | 76,586 |
from scipy.optimize import leastsq
def planckfit(wave, fluxd, err, guess, covar=False, epsfcn=1e-3, **kwargs):
"""A quick scaled Planck fitting function.
The scale factor includes a factor of pi for the conversion from
specific surface brightness to flux density.
Parameters
----------
wave, ... | 8f407198873d444efb2de657387437c0e20abdbc | 76,588 |
def calculate_mixing_params(asm_obj):
"""Calculate the eddy diffusivity and swirl velocity based
on the Cheng-Todreas 1986 correlation with flow regime boundaries
and flow split parameters from the 2018 upgrade.
Parameters
----------
asm_obj : DASSH Assembly object
Contains the geometry... | 4a78a4cd07dfd5943dba11e1cc03506a287cf497 | 76,589 |
def check_data(data: dict, validator: Draft7Validator) -> list:
"""
Проверка значения data на соответствие схеме.
:param data: Словарь данных из JSON файла.
:param validator: Объект Draft7Validator.
:return: result Возвращает список найденных ошибок.
"""
result = [
error.message
... | 07ad82a8e96bfdd5a2bd7a63090a30c1199aac77 | 76,590 |
def ldap_ocf():
"""Context manager that provides an ldap3 Connection to OCF's LDAP server.
Example usage:
with ldap_ocf() as c:
c.search(OCF_LDAP_PEOPLE, '(uid=ckuehl)', attributes=['uidNumber'])
"""
return ldap_connection(OCF_LDAP) | d588e8dbbf7e9efa24bb60d6c0907fa1e0a4850d | 76,591 |
def check_data(X, y=None, objective='regression'):
"""
Make sure the data is valid.
"""
X = check_input_data(X)
if y is not None:
if objective == 'regression':
y = check_regression_targets(y)
elif objective in 'binary':
y = check_binary_targets(y)
... | c00e8bb21426a329d69f2bd387dd710a53229f47 | 76,592 |
def preprocessed_test_dataset() -> pd.DataFrame:
"""A pd.DataFrame with the Amazon-Best-Sellers-Books preprocessed
test dataset.
"""
return pd.read_csv("./tests/test_data/preprocessed_test_dataset.csv") | 7081fd5962c8f99f097c42bd40333f6648cc6052 | 76,593 |
def create(url):
""" Creates a webdriver.
Args:
url: The URL the webdriver will open on startup.
"""
driver = webdriver.Firefox()
driver.get(url)
return driver | 823ae66db331d9d58538a3eb8b44dd3cead4f66e | 76,594 |
from django.contrib.auth.views import redirect_to_login
def login_and_perm_required(perm, login_url=None, unprivileged_url=None, redirect_field_name=REDIRECT_FIELD_NAME):
"""
Decorator for views that checks that the user is authenticated and has permission,
redirecting to the log-in page if necessary.
... | 759b05186e7749cf2f08ab066a460877e3184747 | 76,595 |
def identity_decoder(
grid: grids.Grid,
dt: float,
physics_specs: physics_specifications.BasePhysicsSpecs,
) -> DecodeFn:
"""Identity decoder module that returns model state as is."""
del grid, dt, physics_specs # unused.
def decode_fn(inputs):
return inputs
return decode_fn | 440e0fe84d4f9e3ab47699367d0d969b30ab30e2 | 76,597 |
import logging
def build_lexicon(
words: list,
lang: str,
depth: int,
nlp_model_paths: list = [],
wolf_path: str = None,
wordnet: bool = False,
web: bool = True,
strict=False,
):
"""This is the main function to build lexicons.
Args:
words ([str]): List of words
lan... | 3855a6487d688216082b83eb253983023520e692 | 76,598 |
def has_tool(string_file, tool_type):
"""Returns true if string_file has at least one tool of type tool_type
Parameters
----------
string_file : str
Full path to an Adams Drill string file
tool_type : str
Adams Drill tool type
Returns
-------
bool
... | 26fd4264888db4da53d3b96941b07cbd20bb1e09 | 76,599 |
def registration(father, gender):
"""
>>> f = registration('Donkey', 'F')
>>> f("coco")
'coco-Elizabeth Donkey'
>>> f = registration('Donkey', 'm')
>>> f('Will')
'Will Donkey'
"""
def inner(name):
if gender.lower() == 'f':
return name + '-Elizabeth ' + father
... | 6b529d556d5c8cb8658f7a7086ee6905d7e53976 | 76,601 |
def remove_conflicts(applicant, potential_editors):
"""
Remove editors from potential editors who might be sources of conflict of
interest. These are typically by name or university.
"""
return [editor for editor in potential_editors if
not (editor["name"] in applicant["conflicts-fac... | 49fe7dc482e7f53114f78cf9ed353eded87ecba4 | 76,602 |
def _matmul_act(x):
"""Matmul followed by activation."""
i = array_ops.reshape(x, [8, 8])
f = _weight([8, 8])
x = math_ops.matmul(i, f)
y = nn.relu(x)
return y | f4b33062fb1a949ecfdec81725d745d5d5a45f54 | 76,604 |
from typing import Union
import torch
def whole_graph_rows_to_batch(
similarity_matrix: Union[Tensor, ndarray],
indecies: Union[Tensor, ndarray, list],
norm_rows: bool = True,
) -> Tensor:
"""
Sorts matrix according to indecies and row-normalizes if desired
Parameters
----------
simil... | 336e86d9eb12b3a7e29090bf137f5f127f530cf9 | 76,605 |
import collections
def _mechanic_re_processor_factory(re_pattern, attribute_name, attribute_mod=None):
"""
Generic function factory to generate regular expression based processors.
:param re_pattern: Regular expression pattern object to match with.
:param attribute_name: Attribute name to save the va... | be5b9ec16259d5f24d0eda809511cbb71a2be6fe | 76,606 |
def identity_xf(N):
"""
Construct N identity 2x3 transformation matrices
:return: array of shape (N, 2, 3)
"""
xf = np.zeros((N, 2, 3), dtype=np.float32)
xf[:, 0, 0] = xf[:, 1, 1] = 1.0
return xf | 9c778f11cc32d1ecd60a9d39e24fddf88665ee3c | 76,607 |
def seq_one_hot(sequence, characters):
"""One-hot encode a sequence of characters. Each column is one character."""
# Create dictionary linking characters to indices
char_to_ind = dict(zip(characters, range(len(characters))))
# Set up matrix of zeros
M = np.zeros((len(characters),len(sequence)))
... | 82cca2dd247350e74684c4de3bb751b8eab1edaa | 76,608 |
import math
def solve(X, Y, D):
"""
https://app.codility.com/demo/results/trainingP7B888-UFF/
For example, given:
X = 10
Y = 85
D = 30
the function should return 3, because the frog will be positioned as follows:
after the first jump, at position 10 + 30 = 40
after the seco... | 842d18b2dd1b93e0edeaf1f39937abbcba464084 | 76,609 |
def compute_fundamental(x1, x2):
"""
正規化8点法を使って対応点群(x1, x2: 3*n の配列)から基礎行列を計算
各列は以下のような並び
[x'*xm x'*y, y'*x, y'*y, y', x, y, 1]
"""
n: number = x1.shape[1]
if x2.shape[1] != n:
raise ValueError("Number of points do not match.")
# 方程式の行列を作成
A: np.ndarray = np.zeros((n, 9))
for i in ra... | e252280703cff987a4c396456bdebad44a7375c4 | 76,610 |
def create_lifetime_tech(connector, technology_list):
"""
This function writes the lifetime tech table in Temoa.
TO DO: Update this function to handle technologies with
technology lifetimes that vary by region.
"""
table_command = """CREATE TABLE "LifetimeTech" (
"regions" ... | 86f33ecdd2a8db4a0bdceccd0ab8131b175aba14 | 76,611 |
from typing import Iterable
import textwrap
def replace(template: str, **replacements) -> Iterable:
"""A simple templating system.
Rules:
* Replaces `Name` nodes with either the nodes that are the replacements, or if
the replacement is a string replaces the id of the `Name`.
* R... | 7dbe0e125b8fb8a32f3b4733a9263c302ae1297a | 76,612 |
def balance_conversion_plus_primary_constraint_rule(backend_model, loc_tech, timestep):
"""
Balance energy carrier consumption and production for carrier_in and carrier_out
.. container:: scrolling-wrapper
.. math::
\\sum_{loc::tech::carrier \\in loc::tech::carriers_{out}}
... | 5feac80f6690673cdc52f76811ea9591e687fcd0 | 76,614 |
def create_mult_token():
"""Creates token for multiplication operation."""
return OperationToken("*", parser_utils.SUPPORTED_OPERATIONS.get("*", 0)) | 04891bfee83aef0cf4dcc7743909e149aaea95c9 | 76,615 |
import random
def data_generation(
lower_range=None,
higher_range=None,
number_of_variables=None,
generation_type=None
):
"""Data generation method"""
if generation_type == 'linear':
x_value = np.linspace(lower_range,higher_range,number_of_variables)
elif ge... | ee0376042eb9f0ec4198d01484bf19b58eaf3474 | 76,616 |
def adjust_learning_rate(optimizer, global_step, steps_per_epoch, args):
"""Sets the learning rate to the initial LR decayed by 10 every 30 epochs"""
# lr = args.lr * (0.98 ** (epoch / 2.5))
lr = args.lr * (0.98 ** (global_step // int(steps_per_epoch * 2.5)))
for param_group in optimizer.param_groups:
... | cfbb54d5cc9b9023fd0b4af9ddafd6b37c546e91 | 76,617 |
def do_dice_check(*args, **kwargs):
"""
Sending stuff to Roll class for dice checks; assumed to already be run through get_partial_match.
"""
roll = Roll(*args, **kwargs)
roll.roll()
return roll.result | 1710a980ebfd8a98d2daf109f1a3cc03d4821eb5 | 76,618 |
from typing import Optional
def create_mapping_network(latent_code_dimension: int = 128,
output_dimension: Optional[int] = None,
normalize_latent_code: bool = True,
relu_leakiness: float = 0.2,
num_layers: int ... | 3cc89cf61f94ded44d02929f964dd0c7b3b165c7 | 76,619 |
def remove_glyph_from_jp_font(_font, jp_font_name):
"""
JuliaMono を採用したいグリフを源柔ゴシックから削除
"""
if jp_font_name == "GenJyuuGothicL-Monospace-Heavy.ttf":
over_finish = 0x110618
else:
over_finish = 0x11061a
glyphs = (
list(range(0x0000, 0x2E7F + 0x1))
# + list(range(0x32... | 0770eae9187a370e6631adf35adcefd9ea0e45ee | 76,620 |
def del_xact(crs,environ):
"""delete transaction"""
# get arguments
qs=environ["wsgi.input"].readline().decode()
q=parse_qs(qs)
try:
xid=q["xid"][0]
aid=q["aid"][0]
except KeyError as e:
raise ValueError("Wrong access") from e
# check accounts
crs.execute("SELECT ... | a8516e36b893f4fd2fa3620c314e874b61024a90 | 76,621 |
def mat_diff(mat_a, mat_b):
"""
Function that subtracts two matrices: mat_a and mat_b. The
subtraction can be carried out if the two matrices have same
dimension, i.e. same number of rows and columns. The elements of
the resulting matrix, mat_c, are c_ij = a_ij - b_ij
:param mat_a: list of list... | 0441ea751a3a6c9fb64e9b3a33420fd4b0f8aa3a | 76,622 |
from typing import Union
from typing import Sequence
from typing import Optional
def polyfit(
x: Union[None, str, pd.Series, Sequence] = None,
y: Union[None, str, pd.Series, Sequence] = None,
data: Optional[pd.DataFrame] = None,
dropna: bool = True,
order: int = 1,
logx: bool = False,
with... | f666b739a9ffceb15eece8bccb57c9d4742932b3 | 76,623 |
def _check_and_coerce_cfg_value_type(replacement, original, key, full_key):
"""Checks that `replacement`, which is intended to replace `original` is of
the right type. The type is correct if it matches exactly or is one of a few
cases in which the type can be easily coerced.
"""
original_type = type... | 8b4e750406742fdd4788fdaf73c0c44d95f043d4 | 76,625 |
import time
def get_capture_filename_by_timestamp(start_time, stop_time):
"""Generate capture filename based on the specified timestamp."""
filename = 'cap-%s-%s.btt' % (
time.strftime('%y%m%d_%H%M%S', time.localtime(start_time)),
time.strftime('%y%m%d_%H%M%S', time.localtime(stop_time)))
return filenam... | c40f779886cf395bd6ea5cbe91d19fd5c7952b37 | 76,626 |
def skipgram(currentWord, C, contextWords, tokens, inputVectors, outputVectors,
dataset, word2vecCostAndGradient = softmaxCostAndGradient):
""" Skip-gram model in word2vec """
# Implement the skip-gram model in this function.
# Inputs:
# - ... | ec3b05fb3a62a6d51351d0fdacbcc3106d6e4573 | 76,627 |
from typing import MutableMapping
def merge_hash(a, b):
"""
Recursively merges hash b into a so that keys from b take precedence over keys from a
"""
_validate_mutable_mappings(a, b)
# if a is empty or equal to b, return b
if a == {} or a == b:
return b.copy()
# if b is empty th... | 7effa4f1ca834b52df9a6b962ffb3c73cb0cffc9 | 76,628 |
def get_confirm_token(response):
"""
Returns the confirm token from the response.
Args:
response: response object from the request
"""
for key, value in response.cookies.items():
if key.startswith('download_warning'):
return value
return None | da8b11c306c00056a367f35ebe2b0ffa7ff1ffe6 | 76,629 |
def default_route():
"""Default route to return a simple message"""
return jsonify('Please use /std URI to view content') | 8467adf89a3d264e9619ab84ef4327997467f243 | 76,630 |
import re
def _regex_attr(node, attr, gens, container):
"""
Calcs fitness based on the fact that node's target node shall have an attr
with a value smaller than the given one.
"""
trg_nd = container.nodes[gens[node]]
if attr[0] not in trg_nd:
return 10.1
if not re.search(attr[1], t... | 2e6e5844522cbcbfa78f87b71beb488747c4b86b | 76,631 |
def _get_owner_identity(provider, created_by=None):
"""
This private method is intended to ensure that a valid identity exists
for the 'owner' of an Application.
If the identity cannot be found, the AccountProvider will be the author.
"""
if created_by:
return _user_identity_lookup(str(p... | 37d5af8596b97a718ee54dec32b302431db9dd5a | 76,632 |
def get_mv_pattern(s2n):
"""Simple multivariate dataset"""
return multiple_chunks(pure_multivariate_signal, 6,
5, s2n, 1) | 175238ed32b2ca386dbb52826f7641311b76a673 | 76,633 |
def instant_process_statistics(pid):
""" Return the instant jiffies and memory values for the process identified by pid. """
work = memory = 0
try:
proc = Process(pid)
for p in [proc] + proc.children(recursive=True):
work += sum(p.cpu_times())
memory += p.memory_perce... | b21e5e1175642f605085039e89eb14ac128fa2ad | 76,636 |
import torch
def _generate_bboxes(probs, offsets, scale, threshold):
"""Generate bounding boxes at places
where there is probably a face.
Arguments:
probs: a float numpy array of shape [n, m].
offsets: a float numpy array of shape [1, 4, n, m].
scale: a float number,
w... | 2097f69c1e6cf2665010a6dfdebb180e6c9064bd | 76,637 |
def feq(a, b):
"""Test if two floating point values are 'equal'."""
t = Float("1.0E-10")
return -t < a - b < t | d3183ef4eff1b7eea78e16e2533b68f6123ec416 | 76,639 |
import logging
def get_pending_jobs_info(max_slots_filter=None, skip_if_state=None):
"""
Retrieve the list of pending jobs.
:param max_slots_filter: discard jobs that require a number of slots bigger than the given value
:param skip_if_state: discard jobs that are in the given state
:return: the ... | 4be6c029e5959b5240520479f6806353f8599eb3 | 76,640 |
def run_retrive_model(tags, database_list, base_directory):
"""
Retrive the real final model from the model perturbation.
"""
# target basedir is the last interpolated model
target_basedir = join(base_directory, "interpolation",
"__and__".join(database_list[:, 0]))
# we... | 515130d5a10ae981b8bff17c54cdc588d6009c8d | 76,641 |
import requests
def requests_post(url, expected_sc=201, **kwargs):
"""
Calls our above requests wrapper for a POST request, and sets the default expected status code to 201.
"""
return do_request_with_auth_retry(url=url, method=requests.post, expected_sc=expected_sc, **kwargs) | 1ef9d2025142c346fe4440ca1b9afffeefe930da | 76,643 |
def PorodGuinierPorod(q, a, alpha, Rg, beta):
"""Empirical Porod-Guinier-Porod scattering
Inputs:
-------
``q``: independent variable
``a``: factor of the first power-law branch
``alpha``: exponent of the first power-law branch
``Rg``: radius of gyration
``beta``: ex... | 0b081149b626865d100e489b1d88e442e8c1836e | 76,644 |
def get_mac():
"""Returns the device mac address in unix format
@rtype: string
@return: The mac address in unix format
"""
mac = EUI(getnode())
mac.dialect = mac_unix
return str(mac) | 6fd733c8fbdbae775a83d2c4643906f43486cc80 | 76,645 |
from datetime import datetime
def build_results_list(pages, is_json):
"""Takes a paginated search and returns results List
Handles wiki documents, questions and contributor forum posts.
:arg pages: paginated S
:arg is_json: whether or not this is generated results for json output
:returns: list... | 5758fc57b56a30b71f6b8b3511f00fc09ede8648 | 76,647 |
import logging
def diff2(old_file, new_file, dest_file=None):
"""Do a 2-way diff, between `old_file` and `new_file`, where the
differences are shown with markers like what SVN makes for a file
with merge conflicts, e.g.:
'''
<<<<<<< old_file
old stuff
=======
new stuff
>>>>>>> new... | 95a79f4e9dc2c392a11840ac30d396105e9590cb | 76,648 |
def calc_woba_weights(oba,mlb):
"""
oba: instance of wOBAWeightSim
mlb: instance of BattingSim
-----------------------------------------
returns: DataFrame with columns [woba,woba_Scale,BB,HBP,S,D,T,HR]
"""
# Calc adjusted linear weights
adjlw = oba.adjWeights()
# League OBP (On Base... | 87e1039416de61e60b68a94f7683de6f351cf957 | 76,650 |
def potential_from_Greens(boundary_potential, n=10, G=Greens_function_approxRW(n=10, nwalks=200, start_position=[5,5]), nwalks=200):
"""Computes the potential at a the position start_position. G is a Greens
function computed by Greens_function_approxRW. The potential at
start_position is returned."""
... | e4c530c15ce575e4bde57132d6e7af636920aa62 | 76,651 |
def MutualInfo(labels_true, labels_pred):
"""Normalized Mutual Information between two clusterings.
This code is modified from sklearn.
Parameters
----------
labels_true : int array, shape = [n_samples]
A clustering of the data into disjoint subsets.
labels_pred : array, shape = [n_... | 546bb1e2f9cf2913c6dbb971096a2fd90987a3e8 | 76,652 |
def _add_replication(bucket_name):
"""
Configures a second bucket with `-dr` suffix and replicates the primary
bucket to it.
Adds a lifecycle policy to the dr bucket to immediately roll data into
glacier for cold storage
"""
logger = current_app.logger
dr_bucket_name = f"{bucket_name}-dr... | b33e014ed87ccc60f104a873b6ca0fa8a5ac313c | 76,653 |
import functools
def union(*windows):
"""
Union windows and return the outermost extent they cover.
Parameters
----------
windows: sequence
One or more Windows.
Returns
-------
Window
"""
return functools.reduce(_union, windows) | d112b81c130b7b4a346a77a2d1a3b437644e214a | 76,654 |
import torch
def lne_to_nel(tensor: torch.Tensor) -> torch.Tensor:
"""
Convert data layout. This conversion is required to use convolution layer.
Parameters
----------
tensor: torch.Tensor
(L, N, E) where L is the sequence length, N is the batch size, E is
the embedding dimension.... | c2375a2a424f56a7d889660d20b29b244fe0328b | 76,655 |
from functools import reduce
def lcmm(args):
"""Computes the lowest common multiple of a list of numbers.
Example:
>>> lcmm([5, 15, 12])
60
Args:
args (list(int)): The list of numbers on which to compute the lowest common multiple.
Returns:
int: T... | e49563a0061c1d0fd958ac1f6ab01cbc9811f9aa | 76,656 |
def cvedetails_all():
"""从本地数据库中取出全部exp标记的CVE
:return exist_exp:list, e.g. ['CVE-xxx','CVE-xxx']
"""
so,exist_exp=cve_exists_where(db='exp',table='cvedetails',key=['cve_id'],where='label in (3,4,7)')
print('[+] Searched all exp from local cve details database')
return exist_exp | b41f5a9136663d269bcb0ebf794f8ad5d97c4d2e | 76,657 |
def im_translate(im, shifts):
"""
Translate image by shifts
:param im: An array of size L-by-L-by-n containing images to be translated.
:param shifts: An array of size 2-by-n specifying the shifts in pixels.
Alternatively, it can be a column vector of length 2, in which case the same shifts is a... | 2d140fc742079e477090289b41b452854ff4dadb | 76,658 |
import itertools
def grouper(iterable, n, fillvalue=None):
"""Group lists into lists of items.
grouper(3, 'ABCDEFG', 'x') --> ABC DEF Gxx"""
args = [iter(iterable)] * n
return itertools.zip_longest(*args, fillvalue=fillvalue) | 6ec8efc9d7bafe2cc09ab407fe44ed8f38e90f10 | 76,660 |
def cancel_order(shop_id: int, order_id: int):
"""
取消订单
:param shop_id:
:param order_id:
:return:
"""
order = get_order_by_shop_id_and_id(shop_id, order_id)
if not order:
return False, "订单不存在"
elif order.order_status != OrderStatus.UNPAID:
return False, "订单状态已改变"
... | 494b7b44d11a8322ced71cafc990c8e0853e4576 | 76,661 |
def product_detail(request, product_id):
""" A view to show individual product details """
product = get_object_or_404(Product, pk=product_id)
form = ReviewForm
reviews = product.reviews.filter(active=True) # doesn't allow drafts
new_review = None
if request.method == 'POST':
form = R... | 66a8febedd28ffe62d892bdcc68dd6b3b59efd6e | 76,662 |
import types
from typing import NoReturn
import pkgutil
import importlib
import inspect
def walk_extensions(module: types.ModuleType) -> frozenset[str]:
"""
Return all extension names from the given module.
Args:
module (types.ModuleType): The module to look for extensions in.
Returns:
... | 84387bc14931a6d7d9fd798ec1aac3915ae2fd79 | 76,663 |
def frictional_resistance_coef(length, speed, **kwargs):
"""
Flat plate frictional resistance of the ship according to ITTC formula.
ref: https://ittc.info/media/2021/75-02-02-02.pdf
:param length: metres length of the vehicle
:param speed: m/s speed of the vehicle
:param kwargs: optional could... | 02355ae2e4b6a7437f008d3edf15b1f691df3ba7 | 76,664 |
import yaml
def BqTableSchemaFileProcessor(file_arg):
"""Convert Input JSON file into TableSchema message."""
table_schema_type = GetApiMessage('TableSchema')
schema_field_type = GetApiMessage('TableFieldSchema')
try:
schema_json = yaml.load(file_arg)
schema_json = schema_json.get('schema', None)
... | a3c981cb2333157c9456f785b96d1b931699fc9e | 76,665 |
def return_xarray_dataset(filename,chunks=None,**kwargs):
"""Return an xarray dataset corresponding to filename.
Parameters
----------
filename : str
path to the netcdf file from which to create a xarray dataset
chunks : dict-like
dictionnary of sizes of chunk for creating xarray.Da... | 8b9db56d1b2a5b1032c6a8ce74fbe9d9befa0989 | 76,666 |
from datetime import datetime
def activate_all_records(task):
"""Activate all submitted task records and enqueue it for processing."""
with db.atomic():
try:
status = "The record was activated at " + datetime.now().isoformat(timespec="seconds")
count = task.record_model.update(... | 446292c545c62b87534928eb43f1c889326b49c9 | 76,667 |
def _tag_most_likely(examples):
"""
Return a list of date elements by choosing the most likely element for a token within examples
(context-free).
"""
tokenized_examples = [_tokenize_by_character_class(example) for example in examples]
# We currently need the tokenized_examples to all have the ... | ac96daffc92811fd266518b53fb6712090a127e7 | 76,668 |
def decode_modified_utf8(s: bytes) -> str:
"""
Decodes a bytestring containing modified UTF-8 as defined in section
4.4.7 of the JVM specification.
:param s: bytestring to be converted.
:returns: A unicode representation of the original string.
"""
s_out = []
s_len = len(s)
s_ix = 0... | bb51073289d8592eb71c8132f8350bad1b36bf27 | 76,669 |
def _ReferenceStaticUnroll(theta, state0, inputs, cell_fn):
"""Statically unrolls a `cell_fn` wrt inputs as `recurrent.Recurrent()` does.
This is not a complete implementation but should work reasonably for
calls that do not have a custom cell_grad, extras or accumulators and
can help check expectations.
Ar... | 5e173c2962782880f4b394fa02b8531668fe2de7 | 76,670 |
def get_drugbank_id_from_chembl_id(chembl_id):
"""Return DrugBank ID from a CHEMBL ID.
Parameters
----------
chembl_id : str
CHEMBL ID to map.
Returns
-------
str or None
The mapped DrugBank ID or None if not available.
"""
return get_drugbank_id_from_db_id('CHEMBL'... | 6e812d9011840a4591fe6d9e199afea8bc455714 | 76,671 |
def has_group(user, group_name) -> bool:
"""
Check that a user has a specific group applied, and return
either True if so, or False.
"""
group = Group.objects.filter(name=group_name)
if not group:
return False
return True if group[0] in user.groups.all() else False | 4085dda66e713f77924b3338a77b4cea44efe618 | 76,672 |
from pathlib import Path
def check_distribution(all_methods_df, path=None, test="kstest"):
"""
Tests wether the data is distributed normally or not and creates different distribution plots.
Parameters
----------
all_methods_df : Pandas.DataFrame
path: str, Optional
Path where the fig... | f7950bfb394032021be5568a31093e8ba9810d05 | 76,673 |
def add_mpc_to_vds(hail_context, vds, genome_version, root="va.mpc", info_fields=MPC_INFO_FIELDS, subset=None, verbose=True):
"""Add MPC annotations [Samocha 2017] to the vds"""
expr = convert_vds_schema_string_to_annotate_variants_expr(
root=root,
other_source_fields=info_fields,
other... | 1f063b1785068d41bedd5a4ea78e40f1762e1960 | 76,674 |
def disagreement(map1, map2):
"""
"Disagreement" from Carpin et al.
# of pairs which are occupied/free in each map, and vice-versa
"""
disagree = np.count_nonzero((map1 == OCCUPIED) & (map2 == FREE))
disagree += np.count_nonzero((map1 == FREE) & (map2 == OCCUPIED))
return disagree | e7473f95fd75b929b7b7deedba983cedf1953f3c | 76,675 |
from typing import Optional
def full_like(a: ArrayLike, fill_value: AnyScalar, shape: Optional[ShapeLike] = None,
dtype: Optional[DataTypeLike] = None) -> ShapeletsArray:
"""
Return a full array with the same shape and type as a given array.
Parameters
----------
a: ArrayLike
... | 78341fe297f58d9b2dd258b5a44b71088301e87a | 76,676 |
def get_higher_type(a: type, b: type) -> type:
"""
Returns the higher of the two given Number types.
The types are ordered bool -> int -> float -> complex.
"""
# Type checking
assert a in _ordered_types
assert b in _ordered_types
if a is b:
return a
for typ in _ordered_typ... | 996e8f219900c75bcc9fa5b79d61dcd7488a7cb8 | 76,677 |
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