content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import tqdm
def adjust_contrast_with_mask(img, img_mask=None, contrast=-1, mu=-1, img_min=0, img_max=255, force=True, verbose=False,
mu_steps=500, gain_steps=500):
"""
A version of the contrast adjustment that is mindful of the mask
Performs contrast adjustment of the image,... | 3980737a222d8618d42fe1e2add4f4af78289091 | 73,334 |
def get_minimum_n_cores_for_only_LSNN_placement_no_ws(LSNN_size, input_dim, n_relay_copies, use_cores_for_input=False):
"""
Unlike the function get_minimum_n_cores_for_LSNN_placement_no_ws, this function
only calculates the parameters for the placement of the input and LSNN layers
given the number of re... | c51eec344ecaa579c882c6b24a10fede2842bc65 | 73,335 |
def attack(url):
"""Implement timing attack on given url."""
guess = ''
found = True
while found:
c, found = next_guess(url, guess)
guess += c if found else ''
valid = check_valid(url, gen_params(guess))
return valid, guess | c21de994600de346024950b0a8bb9d551c65836f | 73,336 |
from typing import List
def get_macro_recall(executions: List[RevisionResults]) -> float:
"""
Calculate macro-averaged recall for a list of tool executions.
:param executions: list of RevisionResults objects
:return: macro-recall value
"""
red_tests_recall = [
res.score[1] / res.score... | 7ad1a564f3e1ebe674dbf52e193c48943848741a | 73,337 |
import types
import keyword
def invalidPythonNames():
""" Creates a list of valid Java identifiers that are invalid in Python. """
ts = [getattr(types, n) for n in dir(types) if not n.startswith('_')]
ns = [t.__name__ for t in ts if isinstance(t, type)]
return ['None', 'True', 'False', ] + ns + keywor... | 0eaf0f7188d3e821bb37faa5e5f698cbcdc9e0e0 | 73,338 |
def return_obs_RA_DEC():
"""
Return OM10's lensed system's position
"""
return SkyCoord('03h 32m 30s', '10d 00m 24s') | 8b19ee8f1f83816246918284033bc98670223894 | 73,339 |
def delete_object_property(object_type, property_name):
"""
Delete a property from Hubspot
Args:
object_type (str): The object type of the property (ie "deals")
property_name (str): The property name
Returns:
dict: the result of the delete request in JSON format
"""
re... | 29f5b8d83e45ae052d1946abbf21d21a8b96f3f6 | 73,340 |
def populate_table(parsed_header, parsed_line, file, data_dict):
"""Appends parsed sample metadata to a nested dictionary where
dictionary['Sample_Name']['QC_Attribute'] = QC_Metadata.
Returns an updated dictionary containing new information for N-th line."""
sample_index = parsed_header.index('Sample'... | fe12a867bf2a6893580eb05f1e8d6bdb284786ae | 73,341 |
def get_report(query, page_len):
"""
Extract user's reports from the website based on query and page number.
Here, we want to extract reports from user, institute destination, and category of the reports.
In the HTML code, the reports element is in the <p> (paragraph) tag with class attribute `readmore`... | bdf8141c9bed1e85c49a00bcddbbc926bc589a4a | 73,342 |
def get_object_id(path):
"""Read, if present an object_id
if not available -- would simply raise a corresponding exception
"""
with h5py.File(path, "r") as f:
return f.attrs["object_id"] | b1457dcd5d3e7bc393a78e0bd1cdf47a40fbacd1 | 73,343 |
def split_sql(sql):
"""Splits given SQL into list of statements, stripping comments."""
sql = sqlparse.format(sql, strip_comments=True)
return sqlparse.split(sql) | d6627568afb28fb27b5f43d8635ea1d764a2990a | 73,344 |
def generalised_dice_loss(prediction,
ground_truth,
weight_map=None,
type_weight='Square'):
"""
Function to calculate the Generalised Dice Loss defined in
Sudre, C. et. al. (2017) Generalised Dice overlap as a deep learning
... | 05adfcaf5e86b8fa6861d4a29e1d2cb89680d92b | 73,345 |
def calc_best_fit_n_param_fast(ndim,flatchain_path,output_file_path=None):
"""Description:
-Input :
-Output : a numpy array with [best params, chi2]
Plots and txt files:
txt files:
pdf files:
Tested : ?
By : Maayane T. Soumagnac Nov 2016
URL :... | f922ac74527e03087d3522623528ad9a661cce4b | 73,346 |
def maximum_leja(next_point, z, lower_bound, upper_bound, weight=lambda x : 1):
"""
the maximums function for the leja points
the next leja point is the input so that this function returns
its maximum
"""
if (next_point[0] < lower_bound or next_point[0] > upper_bound):
return -100
pr... | 079c312787a0d0e8704985f0f8ffd146754b2c59 | 73,347 |
def submit_metadata(metadata_modal, name, description=None, version=None, load_workspace=False):
"""
Submits metadata for a project
Returns ``(projects_page, data)``
"""
metadata_modal.submit_metadata(name, description, version)
workspace_page = WorkspacePage.verify(metadata_modal.browser, TEST... | 7e49169c8ede637b060f7c59e8feba03bed9d281 | 73,348 |
def calculate_individual_geo_mean(lines, index, geo_mean, num):
""" Calculate an individual line of parse results goe_mean """
previous_value = None
for line in lines:
line = line.split("\t")[4:]
current_value = line[index]
try:
if float(current_value) > 0:
... | 765b03379d11d2622d07086e1858ee51807bc293 | 73,349 |
def sendDataToMDB():
"""
Parses array of items from frontend, sends to mongoDB
:input: array of json objs - name, price, need vs want
"""
feData = request.get_json()
for i in feData:
post = {
"_id" : dataIndex.count_documents({}) + 1 ,
"ItemName" : i['name'],
... | b937303ff45a33911b78e289e794555e572c4003 | 73,350 |
def regenerated_pyconfig_h_in(file_paths):
"""Check if pyconfig.h.in has been regenerated."""
if 'configure.ac' in file_paths:
return "yes" if 'pyconfig.h.in' in file_paths else "no"
else:
return "not needed" | d5d180a5a9d149cbbcdccb3d72ef69647908678f | 73,351 |
def not_equal(a,b):
""" return 1 if True, else 0 """
if(a != b):
return 1
else:
return 0 | a37ae9177a450b11412c82898e1dade68b97416f | 73,353 |
def check_square():
"""
Checks the square of the board the mouse is currently over,
selecting a piece if there is one
Returns:
selection: The object that was under the mouse at the time of checking
"""
x, y = pygame.mouse.get_pos()
selection = the_board.board_[y // 100][x // 100]
... | 900ced25a99a2a65b3b2914b602b3a386f94778e | 73,355 |
from operator import and_
def view_codec_list():
"""
admin: codec list
not admin: query by productID
"""
if g.tenant_uid is None:
query = Codec.query \
.join(Tenant, Tenant.tenantID == Codec.tenantID) \
.join(Product, Product.productID == Codec.productID) \
... | f3913555025434a74579e7f434fc0b7bd171911b | 73,356 |
from datetime import datetime
def get_latest_one_piece_chapter_jb():
"""Retrieves the latest chapter number on Jaimini's box."""
today = datetime.date.today()
jb_page = "https://jaiminisbox.com/reader/series/one-piece-2"
jb_request = urllib2.Request(jb_page, headers=get_headers())
jb_response = ur... | 9937346367b65b55b3908c432c6e8fa56458aa88 | 73,357 |
def active_view():
"""Return currently active view"""
return sublime.active_window().active_view() | e19348dc249b63aab1350b8a2362ee24db9f930d | 73,358 |
import pathlib
import shutil
def cache_audio_local(path, max_audio_length, cache_dir=pathlib.Path('./audio')):
"""
Copies the file specified by `path` to cache_dir in the same folder
structure that is present at the source. The file should be in an audio
format readable by `nt.io.audioread.load_audio`... | 07b2eb61e842b8c603416313f3c1c2a472d8ab66 | 73,359 |
def centerdc_2_twosided(data):
"""Convert a center-dc PSD to a twosided PSD"""
N = len(data)
newpsd = np.concatenate((data[N//2:], (cshift(data[0:N//2], -1))))
return newpsd | 28d712a16f5118e73081ef857194f39488fcd027 | 73,360 |
def getCount(board):
"""gets counts for all pieces and empty moves present on the board"""
#For fast counting Implemented this Idea
#https://stackoverflow.com/questions/10741346/numpy-most-efficient-frequency-counts-for-unique-values-in-an-array
unique, counts = np.unique(np.array(board), return_counts... | 274d5cfe6a593a78752d775a08a0bb27ea638eaf | 73,361 |
def src_gauss(l, m, sigma_lm, A=1., i=0., pa=0., l0=0., m0=0.):
"""
A 2D Gaussian model on the source emission.
Parameters
----------
l : array like
The l axis coordinate.
m : array like
The m axis coordinate.
sigma_lm : float
The sigma of a Gaussian profile of the s... | 8ca8f5f7521ec605f3bb6db1ef3cdeed4a2241ce | 73,362 |
def sort_hsvs(hsv_list):
"""
Sort the list of HSV values
:param hsv_list: List of HSV tuples
:return: List of indexes, sorted by hue, then saturation, then value
"""
bars_with_indexes = []
for index, hsv_val in enumerate(hsv_list):
bars_with_indexes.append((index, hsv_val[0], hsv_val... | 49a0936a04156ef1d785dea7efc95d5fffb368e0 | 73,363 |
def GetCcIds(issue):
"""Get the Cc's of an issue, whether they are explicit or derived."""
return issue.cc_ids + issue.derived_cc_ids | c5d558c4bfac4da5e501bc834e6218a44c49fbd9 | 73,366 |
import cmd
def kill_remote_process(pids, instance):
"""Kill processes in remote device (`instance`)
Parameters
----------
pids : list
A list of process id's to kill
instance : instance.Instance
Instance object corresponding to remote device
Returns
-------
str
Result of `kill` command
... | 81b272a099ffa9f0815526abbad66647ababf13e | 73,367 |
def sortedArrayToBST(nums):
"""
:type nums: List[int]
:rtype: TreeNode
"""
if len(nums) == 0:
return None
mid_idx = int(len(nums) / 2)
root = TreeNode(nums[mid_idx])
root.left = sortedArrayToBST(nums[:mid_idx])
root.right = sortedArrayToBST(nums[mid_idx + 1 :])
return root | 9f842a9818da7bc5de6c136d4ea46c099ce79711 | 73,368 |
def render_md(full_path, format):
"""
Render a given markdown file
"""
with open(full_path, encoding="utf-8") as file_handle:
text = file_handle.read()
html = markdown.markdown(text)
return Response(html, mimetype="text/html") | f65ea879c1c501b28c27d2c369645a60c323fffa | 73,369 |
import urllib
def extract_params(qs, known_params, object_type, object_name):
"""
Extract parameters from a query string to a dict while ensuring there is no unknown parameter
qs: the query string
known_params: a list of known parameters, any unknown parameter found will fail an "ensure" check
object_type: stri... | 2b836ebb1a826c9d0ab17dbb472acb7ca5690fcc | 73,370 |
import torch
from typing import Sequence
from typing import Any
def clamp_n(tensor: torch.Tensor, min_values: Sequence[Any], max_values: Sequence[Any]) -> torch.Tensor:
"""
Clamp a tensor with axis dependent values.
Args:
tensor: a N-d torch.Tensor
min_values: a 1D torch.Tensor. Min value... | bc3f486d04c55d92b001239d1f9e2496a7d201d0 | 73,371 |
import time
def login():
"""
A form (GET) and the assocaited handler (POST) for validation of user
credentials.
It is possible to put the application in testing mode, so that password
checks are not enforced and the user only need supply a username. This
should never be enabled in production.... | 447610c550da1fed231577d7819574548d408605 | 73,373 |
import shlex
import click
def parse_parameters(_filter):
"""Return parsed filter parameters."""
try:
parsed_filters = []
filters = ' '.join(_filter).replace(',', ' ')
for item in shlex.split(filters):
if '=' in item:
filter_item = {
'colu... | 174841c52303dc73a3ef0b598c025d8b97760461 | 73,374 |
def admin_auth(f):
"""Creates the admin guard decorator"""
@wraps(f)
def decorated(*args, **kwargs):
data, status = Auth.get_logged_in_user(get_jwt_identity())
user = data.get('data')
if not user:
return data, status
if not user['admin'] == store.is_admin():
... | 80ccaea73fc168b1bdc5e6d84ea160e29508c4f3 | 73,375 |
def load(test=False, cols=None):
"""Loads data from FTEST if *test* is True, otherwise from FTRAIN.
Pass a list of *cols* if you're only interested in a subset of the
target columns.
"""
f_name = FTEST if test else FTRAIN
df = pd.read_csv(f_name)
df['Image'] = df['Image'].apply(lambda im: np... | eb92ac8ee57b961118c37788915ca90b02a40cc9 | 73,376 |
import types
def do(f):
"""
A decorator which allows you to use ``do`` notation in your functions, for
imperative-looking code::
@do
def foo():
thing = yield Effect(Constant(1))
return 'the result was %r' % (thing,)
eff = foo()
return eff.on(...)
... | c2408d4d546047098eb92979729b33395b41adca | 73,377 |
def check_data_id(data_id):
"""检查DataId是否合法
:param dataId:
:return:
"""
return check_param_isvalid(data_id) | 1101c7f4a2bffd7bb1342640dd5fc22cbfadd080 | 73,378 |
from typing import List
def BruteCollinearPoints(points: List[Point2D]):
"""
Examines 4 points at at a time
Checks whether all 4 points lie on the same
line, returning all such line segments
"""
segments = []
for p in range(0, len(points)):
pp = points[p]
for q in range(p +... | e6cd0099af7fe314eb1be1ba0693bfa357945d6b | 73,379 |
def cleanupFilename( fname ):
""": Make the filename usable.
= INPUT VARIABLES
- fname Given a filename, clean-it up to make sure we can use it with
the file system.
= RETURN VALUE
- Returns a cleaned up form of the input file name.
"""
fname = fname.replace( ' ', '_' )
fname = ... | 25f727172ed9438c49510fd6703d2d56c61f85f2 | 73,381 |
from paraview.modules.vtkPVVTKExtensionsFiltersGeneral import vtkCellIntegrator
def IntegrateCell(dataset, cellId):
"""
This functions uses vtkCellIntegrator's Integrate method that calculates
the length/area/volume of a 1D/2D/3D cell. The calculation is exact for
lines, polylines, triangles, triangle... | a2eeb687d48fbab73aeb4de39726e93fdb0be6bd | 73,382 |
def get_PS_embeddings(_files, params):
"""
Computes the Patchy-San embeddings for all functions in _files
"""
CNN_input = {}
for function, acfgs in _files.items():
CNN_input[function] = list(map(lambda acfg: get_CNN_input(np.array(acfg['A']), np.array(acfg['X']), params),acfgs))
return C... | 0b1d447d9176bb77261d40f6dd456b49dc60dcd1 | 73,383 |
import json
import ast
def parseJsonDatum(js):
"""Parse a JSON string, return parsed object or None
:rtype:
:param js A valid JSON string
:return parsed JSON as a dict
"""
if isinstance(js, dict):
return js
if not isinstance(js, str):
return None
try:
# prin... | 29d334038b9275fc822576f9670966768d02060e | 73,384 |
def randomly_resort(x, sigma, seed=None):
""" Function randomizes the entries of ``x``
with an input level of stochasticity ``sigma``.
Parameters
-----------
x : ndarray
Input array of shape (npts, ) that will be randomly reordered
sigma : float
Input level of stochasticity in ... | ea73a296cdcaa7ec28c7f8b6106ba2e95092b12f | 73,385 |
def FullCopy(obj):
"""
* Return full copy of passed object.
Inputs:
* obj: Any object.
"""
if hasattr(obj, '__enum__'):
if isinstance(obj, dict):
copyObj = {}
for key in obj:
copyObj[deepcopy(key)] = FullCopy(obj)
else:
copyObj ... | 717e70e28b1cdd803225c774304010a87a3ece3c | 73,386 |
def model_from_sklearn(sk_model, name, accuracy):
"""Loads a model from the given sklearn data structure.
Args:
sk_model: A model previously fitted via scikit-learn.
name (str): The name of the model. This name will later be used during code-generation for naming functions.
accuracy (fl... | 8f2904b471234bf65ffc947208166526649e9966 | 73,387 |
def tokenizer_encode(texts, tokenizer, maxlen=512):
"""
Let Transformers Tokenizer API prepare the input data and encode, precisely tokenizing
Parameters:
------------
texts : list of str
A list of string to be encoded by the tokenizer.
tokenizer : Transformers AutoTokenizer
... | c28ee490a8d2e8efd473d25ed9b58b3b209dafa3 | 73,388 |
def is_tlog(filename):
"""Boolean specifying if filename is a Trajectory log file."""
return _is_log(filename, ('VOSTL',)) | 707a4b62bb9cb85fc279662b3910bafe382e48df | 73,389 |
def continue_or_stop(question):
"""
n or y is parsed from inputs first character so it's the only part that matters
"""
while "answer not y or n":
reply = str(input(question + " (y/n): " )).lower().strip()
if reply[:1] == 'y':
return True
elif reply[:1] == 'n':
return False
else:
print("ERROR: Not ... | 3447a3b205e71270ccede9fa5608c823afa10062 | 73,390 |
def get_default_if():
""" Returns the default interface """
f = open('/proc/net/route', 'r')
for line in f:
words = line.split()
dest = words[1]
try:
if int(dest) == 0:
interf = words[0]
break
except ValueError:
pass
... | b9c046aa02cd5e7df4f1ca7506c1d01ebf93f19e | 73,392 |
def _get_mro(obj):
"""Get the method resolution order for an object.
In other words, get the list of classes what are used to look up methods
on the given object, in the order in which they'll be consulted.
"""
try:
return obj.__class__.__mro__
except AttributeError:
return _get... | 3e7dbd7d4210726e5834c8a95a9b9086e16aad7d | 73,393 |
import json
def jsonify(val):
"""Perform a naive JSON dump."""
return json.dumps(val) | 0b52203062c031ad10fd660c96daa0459f81d367 | 73,394 |
def linregress(x, y, weights=None):
""" fit a line to y(x) using least squares. """
if weights is None:
weights = np.ones(x.shape)
weights /= np.sum(weights)
μx = np.sum(weights*x)
μy = np.sum(weights*y)
m = np.sum(weights*(x - μx)*(y - μy))/np.sum(weights*(x - μx)**2)
b = μy - m*μx
return m, b | 934a9734c92a2052ff038578781902a51378bdf2 | 73,395 |
import math
def opacMg1(numDeps, temp, lambda2, logGroundPops):
"""//c******************************************************************************
//c This routine computes the bound-free absorption due to Mg I.
//c******************************************************************************"""
#//... | c97da4bf667163bc73c95da43b6300a4be9a38be | 73,396 |
def find_road_building_relations(voronoi, pts_line, pts_left, pts_right, road_crds):
"""
Find all road IDs facing the current road segment. Makes use of the indices
of the points between which a voronoi ridge lies. This can be used to check
if a road and building are facing each other.
"""
r_fi... | 4c023d6a93bb8a6fbdcd7565e4b191fe2b63a66a | 73,398 |
def create_sqlalchemy_url(drivername, username=None, password=None, host=None,
port=None, database=None, **kwargs):
"""
输出一个 sqlalchemy的 url，有一些额外的优化。
:param drivername:
:param username:
:param password:
:param host:
:param port:
:param database:
:param kwa... | 1516d6c97ba8272dd3d2fe3829e64b8beb668e15 | 73,399 |
async def subnet_present(
hub,
ctx,
name,
address_prefix,
virtual_network,
resource_group,
security_group=None,
route_table=None,
connection_auth=None,
**kwargs,
):
"""
.. versionadded:: 1.0.0
Ensure a subnet exists.
:param name:
Name of the subnet.
... | 66ab96df63a1a4e0d6ba0e5380360d06afe079d4 | 73,400 |
from typing import Dict
def get_files_modified_since_fork(repo_dir, base_sha, head_sha, log, project_dir) -> Dict:
"""Get changed files and their status in head tree compared to base tree.
Skip submodule changes. They require further processing to find out which
files have actually been changed under the... | 99e625833c58aff79af7ec8f5913bbfdc8d49269 | 73,401 |
from typing import Type
def loadenv_into_dataclass(dataklass: Type[DataClass]) -> DataClass:
"""Return dataklass, instantiated with values from the environment"""
dataklass_envfields = {}
for var_in_env, var_in_dataklass in dataklass.__dataclass_fields__.items():
if not isinstance(var_in_dataklass... | 8036af916da73250d4eb7a897438845b5029ab35 | 73,402 |
def random_sign(shape, dtype=tf.float32, seed=None):
"""Draw values from {-1, 1} uniformly, i.e., Rademacher distribution."""
random_bernoulli = tf.random_uniform(shape, minval=0, maxval=2,
dtype=tf.int32,
seed=seed)
return tf.cast(2 * ... | db4b3b4fabede101186ba7f3500bf5b87fb39aba | 73,403 |
def _lucas_test_sequence(n, a, b):
"""
Return x_0, x_1, x_m, x_{m+1} of Lucas sequence of parameter a, b,
where m = (n - (a**2 - 4*b / n)) >> 1.
"""
d = a**2 - 4*b
if (d >= 0 and arith1.floorsqrt(d) ** 2 == d) \
or not(gcd.coprime(n, 2*a*b*d)):
raise ValueError("Choose another parame... | e412efcc088ea2a3ed8d548c873f234d62d5d24e | 73,404 |
def _timestamp_date(arg: ir.TimestampValue) -> ir.DateValue:
"""Return the date component of `arg`.
Parameters
----------
arg
A timestamp expression
Returns
-------
DateValue
The date component of `arg`
"""
return ops.Date(arg).to_expr() | 6ba110d0d076253d22d34ec2dc11bd5c3ac7e582 | 73,405 |
import torch
import tqdm
def train_one_epoch(model,train_loader:DataLoader,optimizer:AdamW,scheduler:torch.optim.lr_scheduler.LambdaLR,epoch:int,max_epoch:int):
"""Loops through the dataloader and trains the model and optimizer
Args:
model ([BertForSequenceClassification]): [description]
data... | f05fe3a2fb5d392a8cf5f3e0abecb9956e42a23b | 73,407 |
def generate_2D_reflection(angle):
""" Given an angle generate a 2D rotation matrix"""
angle_rad = angle/180.*np.pi
return np.array([[np.cos(2.*angle_rad),np.sin(2.*angle_rad)],[np.sin(2.*angle_rad),-np.cos(2.*angle_rad)]]) | 80aa26eb16e9146e8f6b4f192c6be9afcf389106 | 73,408 |
from operator import index
def compute_expected_obs_counts_jax(gamma, obs, n_states, n_obs):
"""
Computes the expected observation count for each observation o by summing the probability of being at any of the
states for each time t.
Parameters
----------
gamma : array
A matrix of shap... | 3cbe9625ad16c14a743382ba5a54b111082dedfe | 73,409 |
def STOCH(data: xr.DataArray, fastk_period: int = 5, slowk_period: int = 3, slowk_matype: int = 0,
slowd_period: int = 3, slowd_matype: int = 0) -> xr.DataArray:
"""
Stochastic (Momentum Indicators)
Input:
data: [high, low, close]
Parameters:
fastk_period: 5... | bb497649d36008b3cbd3df34caed13e0a1aa964a | 73,410 |
from ecommerce.models import Product
from hubspot.serializers import ProductSerializer
def make_product_sync_message(product_id):
"""
Create the body of a sync message for a product.
Args:
product_id (int): Product id
Returns:
list: dict containing serializable sync-message data for ... | ed9f5512fd3f15169b829f57fee3334bb3e7a5fe | 73,411 |
def generate_xy(number_pixels, center=0.0 * u.arcsec, pixel_size=1.0 * u.arcsec):
"""
Generate the x or y coordinates given the number of pixels, center and pixel size.
Parameters
----------
number_pixels : `int`
Number of pixels
center : `float`, optional
Center coordinates
... | e43d9fe3d0601453472c335db29ab240ee8c7652 | 73,412 |
def matched_modifiers(g, n, modifiers):
"""
returns the set of predecessors of node 'n' that are of a
category contained in 'modifiers'
"""
pred = g.predecessors(n)
if not pred:
return False
pcats = []
for p in pred:
pcats.extend(p.getCategory())
return set(pcats).in... | d58453fa40271cad95ba9845026c17c2cc1025af | 73,413 |
def new_matrix_input():
"""Логика генерации новой матрицы"""
n = int(input("Введите кол-во строк в матрице -> "))
m = int(input("Введите кол-во столбцов в матрице -> "))
# Генерируем
matrix1 = matrix_gen(n, m)
matrix2 = matrix_gen(m, n)
# Пишем в файлы
matrix_writer(matrix1, MATRIX1_FI... | 0a3bc38edd90eb104e5a53252e1caeb2c1f53499 | 73,414 |
def _layout_to_matrix(layout):
"""Create the adjacency matrix for the tree specified by the
given layout (level sequence)."""
result = [[0] * len(layout) for i in range(len(layout))]
stack = []
for i in range(len(layout)):
i_level = layout[i]
if stack:
j = stack[-1]
... | cd27cad3a7ab6f34ea2be13e5617a34dbbba834f | 73,415 |
from typing import Type
def get_alg_dataset(alg_cls: Type[Algorithm]) -> Dataset:
"""Return an instance of the dataset for an algorithm."""
settings = _get_alg_settings(alg_cls)['dataset']
if isinstance(settings, tuple):
(cls, kwargs) = settings
else:
(cls, kwargs) = (settings, {})
... | 1e4814f59abb85bb3918ae63a5562a20fad78a10 | 73,416 |
import click
def email_arg(required, email="email", metavar="[EMAIL]", nargs=1):
"""
Email positional argument standard definition.
Use as decorator for commands.
"""
return click.argument(email, metavar=metavar, nargs=nargs, type=str, required=required) | 26e51c44f1109c0f690f243ee9d40de959570b08 | 73,417 |
def simplify_dataset_name(dataset_name):
"""In a couple of cases (BraTS and MURA) the dataset name is not quite correct
because of a mistake made earlier in the pipeline.
This function transforms the dataset names into a more readable format.
Args:
dataset_name (string): name of dataset to sim... | af0e504df0af2f250c716fb4f797970f31cbb1e1 | 73,418 |
def read_graph(filepath, format='edgelist') -> Graph:
"""Reads a graph from an edge list file and returns an igraph Graph object.
Parameters
----------
filepath : str
Path to the edge list file.
format : str
Format of the input file, e.g. 'edgelist', 'pajek',...
Returns
---... | 2db0a5d6af99eb76aeec84a2085f88e54084879e | 73,420 |
def read_img(components):
"""
Loads image from meta.img_path. Assigns the image to
the field img of the same meta instance.
:param components: components
:return: updated components
"""
img_buf = open(components[0], 'rb').read()
if not img_buf:
raise Exception('image not read,... | 016628a0f167cac7a4efa6da20e8e6d8c0504523 | 73,421 |
import requests
from bs4 import BeautifulSoup
def get_problems() -> list:
"""Get the list of problems
Returns:
list: Problems
"""
problems = []
website = requests.get(view_url)
soup = BeautifulSoup(website.text, 'lxml')
for i in soup.find_all('span'):
try:
... | 3a2ceb643edb22d09dee76a62e7c23269986af01 | 73,422 |
import logging
def NN_aggregate_model_updates(clients_model_updates, global_model_parameters, update_rate, verbose, aggregation_type):
"""
For each layer average the gradient and add it to the global model layer with some update_rate
"""
agg_weights = []
clients_model_updates_copy = list(clients_m... | 9fdcdc0ccd539345708a41f0c6f170c7bb2ee86c | 73,423 |
from datetime import datetime
def report_top_month(request):
"""
TOP 30 users-downloaders
"""
today = datetime.datetime.combine(datetime.date.today(), datetime.time())
last_mon = today - datetime.timedelta(days=today.weekday(), weeks=1)
last_mon = int(datetime.datetime.timestamp(last_mon))
... | 35201f0a0509bc1d78d58cf5d90407b16dbb0720 | 73,424 |
import json
def api_products_delete(barcode):
"""
API method : Deletes an item from the products table.
Outputs JSON.
Returns the latest version of the grocery list.
JSON format :
- {"status": ...}
Possible return status :
- OK (200)
- DELETE ERROR (400)
"""
# AJAX Auth che... | 5a32d5e203e7d4a76c6a12d6bb2375d030bf6022 | 73,425 |
def cpu_mandel(x, y, max_iters):
"""
Given the real and imaginary parts of a complex number,
determine if it is a candidate for membership in the Mandelbrot
set given a fixed number of iterations.
"""
c = complex(x, y)
z = 0.0j
for i in range(max_iters):
z = z * z + c
if ... | 30d0b637a924670e4038ba9f68c20c943de0e009 | 73,427 |
def get_model(model_class):
"""This functio nis for building the model for mlp and lstm"""
model = Sequential()
if model_class == 'mlp' or model_class == 'mlp_angle' :
# Add a hidden layer with ReLU activation
model.add(Dense(1024, input_dim=input_dim, activation='rel... | 5a2b568ea1f02d9b007bc92d59e8535bf478b275 | 73,428 |
def get_test_data_path():
"""
Returns the path to test datasets, terminated with separator. Test-related
data are kept in tests folder in "data".
Based on function by Yaroslav Halchenko used in Neurosynth Python package.
"""
return abspath(join(dirname(__file__), "data") + sep) | 22325d16fd6eafb6acfa7564918cf3941dec803d | 73,429 |
from typing import Tuple
def load_dataset(dataset_path: str, mode: str) -> Tuple[list, list, list, list]:
"""
Divide all audio paths and transcripts into train and validate
Args:
dataset_path (str): path with audio and transcript
mode (str): flag indication train or eval
Returns: tra... | af18885c5cf9bc7b6831fae7574b520e5a55046f | 73,430 |
def single_recurrence_goal(target, z_next, within, players, ij, aut):
"""Development harness for parameterized assumption construction."""
assert 'scheduler' not in players
print('single recurrence goal: {ij}'.format(ij=ij))
i, j = ij
assert i >= 0, i
assert j >= 0, j
phase = '{i}_{j}'.forma... | 5082ee4c4e07be296e7bd15d03e3930ebc0c6b20 | 73,431 |
def upload_file(project_id):
"""Upload file (POST) - Upload a data file to the project's filestore.
"""
# The upload request may contain a file object or an Url from where to
# download the data.
if request.files and 'file' in request.files:
file = request.files['file']
# A browser m... | a9ab038b9e65e8abc0a71904a9c75a282bc13df6 | 73,432 |
def colormap_to_rgb(raster):
""""
The function is designed to work with single band image service that has
internal colormap. It will convert the image into a three-band 8-bit RGB
raster. This function takes no arguments except an input raster. For
qualified image service, there are two situations ... | 6174c519a854ff15cf5bc8cc17cafee6ebacb4df | 73,433 |
import numpy
def filled_circle(shape, radius, center=None):
"""
creates a circle mask of defined radius and center
in an array of the provided shape
with value of 0 inside the circle and 1 outside the circle
"""
r2 = radius*radius
if center is None:
### set to center of array
center = (shape[0]-1)/2.0,(sh... | ad7f252d5b225ccd4496843ee8ebbd71ab2196da | 73,434 |
def binary_labelisation_from_markers(tree, object_marker, background_marker, leaf_graph=None):
"""
Given two binary markers :math:`o` (object) and :math:`b` (background) (given by their indicator functions)
on the leaves of a tree :math:`T`, the corresponding binary labelization of the leaves of :math:`T` i... | 6861b2411f99f5accc02726eb132afde3c3ce442 | 73,435 |
def get_pointcloud_bbox(pointcloud: np.ndarray) -> AABB:
"""
Create a mitsuba bounding box by using min and max on the input ndarray
:param pointcloud: The pointcloud (Nx3) to calculate the bounding box from
:return: The bounding box around the given pointcloud
"""
min_values = np.min(pointcloud... | f0070a2ff339a7bd72052f7933ac29cca05bd949 | 73,436 |
def arange(start, stop=None, step=1, dtype=None, ctx=None):
"""Return evenly spaced values within a given interval.
Values are generated within the half-open interval ``[start, stop)``
(in other words, the interval including `start` but excluding `stop`).
For integer arguments the function is equivalen... | 93c2698032b9f0864bcf3b3537cbba2914a02c61 | 73,437 |
def U_np(angle1, angle2, angle3, invert):
"""Return numpy array with U gate (IBM)."""
gate = np.zeros(4, dtype=complex).reshape(2, 2)
cosan = np.cos(angle1/2)
sinan = np.sin(angle1/2)
mult = 1
if invert:
mult = -1
gate[0, 0] = cosan
if not invert:
gate[0, 1] = -sinan * np... | eaf81ac490d9cdb8d97410737bae2caa4ff370cc | 73,438 |
def log_log(xarr, yarr, *args):
"""Given x and y, returns log(x) and log(y) arrays.
"""
x = np.array(list(map(lambda xi: np.log(abs(xi)), xarr)))
y = np.array(list(map(lambda yi: np.log(abs(yi)), yarr)))
return (x, y) + args | 5a3dcc7340468cfed5bbfb06c300769ac5eb2460 | 73,439 |
import google
def get_local_user(network, site_id):
"""Get the local user_instance from the social details."""
network_check = models.User.oauth_site == network
id_check = models.User.social_id == site_id
existing_user = (models.User.query
.filter(network_check)
... | 56b8b0851f27d12b73948fb7bc9f72405a71ce65 | 73,440 |
def insertTensor(tree, graph, dims=[2, 2, 2], dtype='VX_TYPE_UINT8', fpp="0"):
"""
Insert a tensor
"""
tensor = etree.Element(etree.QName(tree, stensor))
ref = getNewRef()
updateAttributes(tensor, dict(reference=ref, number_of_dims=len(dims),
data_type=dtype, fi... | deb628d797d26714bd5e11602e3b1695268b8a10 | 73,441 |
import random
def seq_aleatoire(l_ascii):
"""Mélange une liste.
Cette fonction permet de générer une séquence alétoire de même
composition que celle passée en argument.
Parameters
----------
l_ascii : list
`l_ascii` est une liste d'entiers.
Returns
-------
l_ascii : list... | eb9c3e1d5182c4a359566e8efd1174934f415c4b | 73,442 |
def pos_wise_FFN_module(x,
n_inner=2048,
keep_prob=0.9,
is_training=False,
scope='PW_FNN_module'):
""" postion wise Feed forward networks sublayer module """
with tf.variable_scope(scope):
n_hidds = x.get_sh... | b4cd7173337c3bb3a4ebf8ae49a3a58f87cd8e95 | 73,443 |
def maketrans(fromstr, tostr):
"""maketrans(frm, to) -> string
Return a translation table (a string of 256 bytes long)
suitable for use in string.translate. The strings frm and to
must be of the same length.
"""
if len(fromstr) != len(tostr):
raise ValueError, "maketrans arguments mus... | 38be4d42c1e671fb04b693055b355b501490422d | 73,444 |
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