content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
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 |
def is_func_ptr(dis: Disassembler, address: int) -> bool:
"""Returns true if the given offset is a function pointer."""
# As a first check, simply see if the offset is the start of a function.
try:
func = dis.get_function(address)
if func.start == address:
return True
except ... | 42be0b05e7f2724b8610a5afc6ce80757fe3a78b | 73,406 |
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 |
import click
from pathlib import Path
import os
def edit_inputs(client, workflow):
"""Edit workflow inputs."""
for input_ in workflow.inputs:
new_path = click.prompt(
'{0._id}'.format(input_),
default=input_.consumes.path,
)
input_.consumes.path = str(
... | e9668f717b50786ddd3fe6375f56d17bad5ada05 | 73,419 |
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 |
import argparse
def get_parser():
"""
Returns the CLI parser to get the YAML file for the EC2 instance configuration.
Retrieve the YAML configuration file using the 'file' argument.
"""
parser = argparse.ArgumentParser(description='Creates EC2 instances from a basic YAML configuration file')
... | 2f57a88db79529e89d685a84dcdcf8101f38a833 | 73,426 |
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 |
from typing import Tuple
def _load_feature_metadata(feature_file: str, format_type: str, sep: str = "\t") -> Tuple[pd.DataFrame, str]:
""" Load feature information """
feature_metadata = pd.read_csv(feature_file, sep=sep, header=None)
if format_type == "HCA DCP":
# HCA DCP format genes.tsv.gz
... | c02599e0bac9fca6cadfafdd6835ce578b10dcb3 | 73,445 |
import warnings
def compute_err_score(true_positives, n_ref, n_est):
"""Compute error score metrics.
Parameters
----------
true_positives : np.ndarray
Array containing the number of true positives at each time point.
n_ref : np.ndarray
Array containing the number of reference freq... | b215fc28609bc6584912dc5d87172eb3b9c909cd | 73,446 |
def fibonacci_recursive(nth_nmb: int) -> int:
"""An recursive approach to find Fibonacci sequence value.
YOU MAY NOT MODIFY ANYTHING IN THIS FUNCTION!!"""
cache = {0: 0, 1: 1}
def fib(_n):
return _n if _n in cache else fib(_n - 1) + fib(_n - 2)
return fib(nth_nmb) | a6efe2a984e743d580d04a106a04463fa5d329c3 | 73,447 |
def api_core_myself():
"""自身のCcInfoのCRUD."""
if request.method == 'GET':
return _get_core_myself()
abort(405) | 4c983a5a2c27b7bc11c3ef16b21b1dce50a45252 | 73,448 |
import os
import numpy as np
import h5py
def psf_maker(file_name, wl_endpoints=(350, 1100), f=1, size=101, res=(100, 100)):
"""
Creates a new file containing the full-color PSF, without interpolating as with psf_maker
Parameters
----------
file_name : str
Desired name of the file.
wl_... | aaa24f6145e6796d4d4fb2267350c524b42d7554 | 73,449 |
def AC(obs, mod, axis=None):
""" Anomaly Correlation """
obs_bar = obs.mean(axis=axis)
if not axis is None:
obs_bar = np.expand_dims(obs_bar, axis=axis)
p1 = ((mod - obs_bar) * (obs - obs_bar)).sum(axis=axis)
p2 = (((mod - obs_bar) ** 2).sum(axis=axis) * ((obs - obs_bar) ** 2).sum(axis=axis)... | 07c6891769793729eafa6b72cfed281153a9c46e | 73,450 |
def table_to_data_frame(table):
"""Converts a vtkTable to a pandas DataFrame"""
if not isinstance(table, vtk.vtkTable):
raise _helpers.PVGeoError('Input is not a vtkTable')
if not isinstance(table, pv.Table):
table = pv.Table(table)
return table.to_pandas() | 0219cb28d766ea7ae3aaee27f83b672c4d2eae01 | 73,451 |
def ode_solutions(t,tsteps,M,S,gamma):
"""
Solve the differentials with an array of initial conditions and returns lists of positions and velocities.
Parameters
----------
t: float
The current time t[i].
tsteps: int
The number of times between [0,t] the solution is calculate... | aeb10534620852042f9dae0492976e358d444c2b | 73,452 |
import time
def test_main2():
"""Tests buckets containing multiple matches for traffic."""
b = [] # counting buckets
for i in range(0,2):
b.append(QueryTest())
time.sleep(0.2)
pol1 = match(srcip=ip1) >> b[0]
pol2 = match(srcip=ip2) >> b[1]
pol3 = match(srcip=ip3) >> b[0]
... | 61a43a7586aaa4ad548b97a0e6cbaa342aec37ea | 73,453 |
def recall_from_cfg(cfg):
""" Runs MCQ from julia based on the passed configuration
Params
cfg: Configuration (ConfigSpace.ConfigurationSpace.Configuration)
Configuration containing the parameters.
Configurations are indexable!
Returns:
scores: A crossvalidated mean score for the ... | 27ab71d4486d5bc084e2419546c6e64c03b22f46 | 73,454 |
import keyword
def is_valid_implicit_namespace_package_name(s):
"""
Checks whether provided string could represent implicit namespace package name.
:param s: string to check
:return: True if provided string could represent implicit namespace package name and False otherwise
"""
return isidenti... | 2ded9b0c20913d5a440169532d064b2691671a35 | 73,455 |
import logging
from datetime import datetime
def _load_listing_from_file(dir: WindowsPath = project_dir / 'data/raw',
**kwargs) -> pd.DataFrame:
"""
Loads the data from file, drops some null rows, add `execution_date` and
then upload to Postgres.
:param dir: The directory t... | ccfb91e733e7db887907962e02b33d220e89b2f9 | 73,456 |
def get_maps_nested(models, cases, varList, from_time, to_time,
avg_over_lev=False,
pmin=None,
p_level=None,
pressure_adjust=True,
raw_data_path=get_input_datapath(),
recalculate=False,
... | f7f8960a6a455c5fa33ffd0555fef4c66a2fb5e8 | 73,457 |
async def login_post(request: Request, user: str = Form(...), db: Session = Depends(get_db)):
"""
POST route handler for the login page of the webapp
:param user: The form data for the user name to use to login.
:param db: Dependency for the db session.
:return: The response to the user based on the... | df97fffb0e9cc25fc681400edef29b19e0d7e6df | 73,458 |
import numpy
def _raw_fftnd(x, s, axes, direction, overwrite_x, work_function):
""" Internal auxiliary function for fftnd, ifftnd."""
if s is None:
if axes is None:
s = x.shape
else:
s = numpy.take(x.shape, axes)
s = tuple(s)
if axes is None:
noaxes = T... | 6341f5f49ef23fd773e285a845b39cf74332498f | 73,459 |
def check_apikey(name, query_type):
"""Verifies API Key."""
if not config.get(f"{name}", "api_key"):
print(f"Please add {name} api key to the '{settings.name}' file")
else:
api_key = config.get(f"{name}", "api_key")
name = query_type(api_key)
return name
return None | 38716627628b31094660b70b3da3e655f1150219 | 73,460 |
def delete():
"""
Deletes a system settings from list.
:return: 200 on successful delete, 404 if not found
"""
user = security.get_valid_user_from_token(dbsession=db.session)
logger.debug(f"Logged in user {user}")
if not (user and user.isLZAdmin):
return abort(401, "JWT not valid... | 4c4661b91d6574adcb395f5fd661dfc1b9e4f4e8 | 73,461 |
from typing import List
def motion_annotation(ephemerides: List[Ephemeris], wcs: WCS) -> GroupAnnotation:
"""Return an annotation showing the motion of an object on the sky.
If the motion is sufficiently large, it is shown as an arrow from the initial to the
final position. Labels for the initial and fin... | 39dcf46898b6c730ec1a1e452321c8f63c5620cf | 73,462 |
def select_k_best(points, scores, k, H=None, shape=None, margin=0):
""" Select the k best scoring points. If H and shape are defined,
additionally keep only the keypoints that once warped by H are
still inside shape within a given margin to the border. """
if H is None:
mask = np.ze... | 5072e9542acea5cdd65f9df29ef6e3e24d970243 | 73,463 |
def predict_linear_regression_labaled_features(fitted_model, dict_features):
"""
Calculates y ~ const + sum( parameter*value )
essentially the inner product
{ 'feature name' : value }
Does not assume you have all features present, so prediction may be off.
Assumes const parameter is not p... | b86fa00ff80e528080e473f849721a16e6f9f2a8 | 73,464 |
import json
def get_store_username():
""" 如果存储了用户名，就获取它 """
filename = 'username.json'
try:
with open(filename) as f_obj:
username = json.load(f_obj)
except FileNotFoundError:
return None
else:
return username | 68197999c12d0fdc5574dde45e92ef09f4a37d58 | 73,465 |
def group_documents_by_owner(documents):
"""Groups documents by owner."""
grouped = defaultdict(lambda: [])
for doc in documents:
grouped[doc.evergreen_owner].append(doc)
return grouped | e1b7bc9c571d3d376dea7811923f0e665120a37c | 73,466 |
def parse_time(text):
""" parse time of slurm output """
# check for days
tokens = text.split('-', 1)
if len(tokens) > 1:
days = int(tokens[0])
rest = tokens[1]
else:
days = 0
rest = tokens[0]
# check for time
tokens = rest.split(':')
return days*24*60 + ... | 91a07479f02a6d428a2c45fe6b701e009a9675cf | 73,467 |
def sigmaclip_inf(a, sigma_lower=3., sigma_upper=3.,
cenfunc='median', ddof=1, outfunc='median'):
""" Infinite loop sigma-clip.
copy from `scipy`_.
.. _scipy: https://github.com/scipy/scipy/blob/4c0fd79391e3b2ec2738bf85bb5dab366dcd12e4/scipy/stats/stats.py#L3159-L3225
"""
# bn.me... | 7ac94c1857f69c55c294e41f6a5a92c8b9fd94e3 | 73,468 |
import gzip
import json
import hashlib
def labeled(token, feature, frame):
""" """
project = Project.get(token)
if not project:
return jsonify({'error': f'project {token} not found'}), 404
labeled_array = project.get_labeled_array(feature, frame).astype(np.int32)
content = gzip.compress(js... | 800604821c15055cf9440e7e914d97744cf5fe14 | 73,469 |
def get_video_name(image_name):
""" Extracts the video name from an image filename.
Args:
image_name: The name of the image file.
Returns:
The name of the video that the image belongs to. """
video_name = image_name.split("_")[0:3]
video_name = "%s_%s_%s" % (video_name[0], video_name[1], video_name[2]... | d2e5254dfaa650455b346cec43273cd50004b335 | 73,470 |
def pretrain_model(albert_config,
seq_length,
max_predictions_per_seq,
initializer=None):
"""Returns model to be used for pre-training.
Args:
albert_config: Configuration that defines the core ALBERT model.
seq_length: Maximum sequence length of t... | 070e2b57487d130be823cee5924f522e2c48217a | 73,471 |
import keyword
def is_identifier(string):
"""Check if string could be a valid python identifier
:param string: string to be tested
:returns: True if string can be a python identifier, False otherwise
:rtype: bool
"""
val = PYTHON_IDENTIFIER_RE.match(string) and not keyword.iskeyword(string)
... | e0a2360909fb14a851711780051319c77cd27d22 | 73,472 |
def create_tf1_call_model_function(graph,
session,
y,
x,
conv_layer=None):
"""Creates a call_model_function which calls the TF1 model specified.
Args:
graph: The TensorFlo... | 041db914ece83ae0f58162bc625ebf213207d62a | 73,473 |
def check_orthogonality(modes, num_modes):
"""
Check orthogonality of modes.
:param np.ndarray modes: modes.
:param int num_modes: number of modes.
:return: True if orthogonality check passes.
:rtype: bool
"""
for m1 in range(num_modes):
for m2 in range(num_modes):
if m1 == m2:
s_ = np.sum(modes[:,m1... | 07c2fadf7ead843aee0a1e2f5048b84dd345a207 | 73,474 |
def Mce3(m, q, ξ, *, p=0):
"""
v = Mce3(m, q, ξ, *, p=0)
Compute the value of the even Radial Mathieu function of the third kind
Mce⁽³⁾ₘ(q, ξ).
Parameters
----------
m : array_like
interger order of the Mathieu function
q : array_like
positive parameter in the Mathieu d... | 349a3de477bb9c7913e18b3848db9ded040b776b | 73,475 |
import os
import tempfile
import shutil
def _get_metrics(
datadriftdetector,
start_time,
end_time,
run_id,
daily_latest_only=True,
with_adhoc=False,
logger=None,
):
"""
:param datadriftdetector:
:param start_time:
:param end_time:
:param run_id:
:param daily_latest... | c3584637ebad2e6142c22db35118083abe17f925 | 73,476 |
from loopy.isl_helpers import static_max_of_pw_aff
from loopy.symbolic import pw_aff_to_expr
from loopy.kernel.data import VectorizeTag
from pymbolic import var
import six
def privatize_temporaries_with_inames(
kernel, privatizing_inames, only_var_names=None):
"""This function provides each loop iteration... | ef83a9b3fa00bfebcbeaf1c4dc2004e2e4ab5b60 | 73,477 |
def task(func):
"""A decorator for a task function
The k2phot model is that you write wrapper code around your pipeline functions
that extract values from a clipboard to pass as input arguments,
and store the return values back in the clipboard. This wrapper code
is called a "task".
This decor... | 6a2ce615585ca1af8418e7d674c2ddae15946448 | 73,478 |
import argparse
import os
def parse_args():
"""Parse the command-line arguments and canonicalize file path arguments"""
parser = argparse.ArgumentParser(description="Script to incrementally " +
"upload an Illumina run directory (HiSeq 2500, HiSeq X, NextSeq, " +
"MiSeq). This script c... | 2575228903983b7d36e8dddc33d0f318a9013161 | 73,479 |
def estimate_reasonable_max(df, x):
"""Estimate a reasonable maximum value for the plot y axis."""
# Use 1.5 IQR of the largest group.
group = df.groupby(x)
q1 = group.Time.quantile(0.25)
q3 = group.Time.quantile(0.75)
iqr = (q3 - q1).max()
return q3.max() + 1.5*iqr | a5fd4be194ca938c7cebd1ad31128ccffcfd44bd | 73,480 |
def multilabel_precision(y_true, y_pred):
"""
Macro-precision, with thresholds defined by by argmax F1
"""
values = list()
for i in range(y_true.get_shape()[1]):
pr, rec, thresholds = precision_recall_curve(y_true[:, i], y_pred[:, i])
f1 = 2.0 * pr * rec / (pr + rec)
values.a... | 25895da1a32085aa1f737d9afd13be3cbc6c06c6 | 73,481 |
def _add_members_to_obj(obj, data, columns):
"""Add members to obj.members
"""
i = 0
for member in obj.members:
name = 'member_' + str(i + 1)
data += ('\n'.join((f'{a}={v}' for a, v in member[i])),)
columns = columns + (name, )
i += 1
return data, columns | 6fd03824f3a17bb92fd7a42e16d3951222451cc2 | 73,482 |
def Compounds2Scaffolds(db,cids):
""" Return list of ScafIDs for selected compounds.
"""
cur=db.cursor()
sql='''\
SELECT DISTINCT
scaffold.id AS scafid
FROM
scaffold
JOIN
scafid2cid ON (scafid2cid.scaffold_id=scaffold.id)
JOIN
compound ON (compound.id=scafid2cid.compound_id)
WHERE
compound.id IN ( %(CIDS)s... | 7001628b0e9c4bc0ef569ae94857bafd02cfc430 | 73,483 |
def toggle_values_by_name(username=None, domain=None):
"""
Loads all toggles into a dictionary for use in JS
all toggles (including those not enabled) are included
"""
return {toggle_name: (toggle.enabled(username, NAMESPACE_USER) or
toggle.enabled(domain, NAMESPACE_DOMAIN... | a81efbccc5c0305a9d9bcd5b59bce9ac948cb151 | 73,484 |
import math
def get_exp(quantizer):
"""get max/min exp value for relu_po2 or quantized_po2."""
if quantizer.is_signed:
non_sign_bits = quantizer.bits - 1
else:
non_sign_bits = quantizer.bits
min_exp = -2 ** (non_sign_bits - 1)
max_exp_orig = 2 ** (non_sign_bits - 1) - 1
max_exp = max_exp_orig
... | b8a6e0f090c065e34350ee064f9b37bd09064b4b | 73,485 |
def scale_df_X_to_range(df_X, a, b):
"""
Given df_X (a pd.DataFrame containing just X values where each row is a
time series and each column is a voltage), scale each row to the range [a, b].
Take the min and max values for the sequence to be -40 and 40 (found by
inspecting all time series individu... | abe59ed3a7f17d4f74a5d74ab948e3abb2a77044 | 73,486 |
from typing import Type
def count_field(instance: Type[Model], field: str) -> int:
"""
Returns count of a related field. if `{field}_count`
exists in instance, then it's value will be returned
"""
count = getattr(instance, f'{field}_count', None)
if count is None:
count = getattr(insta... | 8c6723f725f37c27d3df9d604671244eebd7f16f | 73,487 |
def parse_number(value, locale=None):
"""Take localized number string and return a long integer.
Throws ValueError if bad format.
"""
return long(value.replace(get_group_format(locale), "")) | b30ee5ec347710a5a81e2ff78eb1885deef98294 | 73,488 |
import gzip
def load(filename):
"""Loads a compressed object from disk
"""
file = gzip.GzipFile(filename, 'rb')
object = cPickle.load(file)
file.close()
return object | c381d24517a73fc2aac08d29a340718bb442680c | 73,489 |
def _correct_background(v_raw_score, mat_ctrl_raw_score, v_var_ratio_c2t):
"""Cell-wise and gene-wise background correction
Args
----
v_raw_score (n_cell,n_ctrl) : np.ndarray
Trait raw score
mat_ctrl_raw_score (n_cell,n_ctrl) : np.ndarray
Control raw scores ... | 0ab76890f69bf6db1f8b05c6e462f82405330817 | 73,490 |
def get_points(file,img_shape,mirror=False):
"""
Read wp from a YOLO style file: each wp are the upper-left and the lower-right points of the bounding box
"""
points = []
img_shape = img_shape[:-1][::-1]
file = open(file).read().split('\n')[:-1]
for r in file:
r = r.split()
... | 9648edc2aa065aceadf2128c28b5ff71ded2cb92 | 73,491 |
import os
import traceback
def delete_recpie():
"""Remove recipe from data base."""
try:
recipe_id = request.args.get("id")
recipe = recipemodel.Recipe.get(recipemodel.Recipe.id == recipe_id)
if recipe.image:
utils.remove_file(os.path.join(current_app.config.get("IMAGE_PATH... | 619f04220ed2a86928aabc6dba55bf9b2d578532 | 73,492 |
import os
import sys
import json
def load_alias(path="alias.json"):
"""Load alias, return empty dict if file not found
Keyword Arguments:
path {str} -- path or filename of Alias JSON (default: {"alias.json"})
Returns:
dict -- loaded dictionary of alias
Raises:
UnknownPythonE... | e3c5cc730388757d8c20d6be4e1f736d22b54cc0 | 73,493 |
def orjson_dumps(v, *, default):
"""
orjson.dumps returns bytes, to match standard json.dumps we need to decode.
orjson.dumps option arguments provide many options such as `option=orjson.OPT_SERIALIZE_UUID` to natively encode UUID instances.
"""
return orjson.dumps(v, default=default).decode() | 450473c8a4af546114aa453dcdead5530d7e6534 | 73,494 |
def definition():
"""
Cost information, for use in TT administration.
Seperate to v_c_cost for performance reasons - the other is used
for the curriculum model interface.
"""
acad_week_list = text_concat(
"acad_week", "x.acad_week FROM c_cost_week x WHERE x.cost_id = c.cost_id", ", ")
... | 3ae36d32a066b8280a409d44c7e51f62ddfc7e4f | 73,495 |
from typing import Optional
from typing import Union
from typing import Sequence
from typing import Dict
from pathlib import Path
def prepare_mtedx(
corpus_dir: Pathlike,
output_dir: Optional[Pathlike] = None,
languages: Optional[Union[str, Sequence[str]]] = "all",
num_jobs: int = 1,
) -> Dict[str, Di... | 0cc2790354ac008685061539de448468662eeb3d | 73,496 |
import json
import os
def build_feature_dict(args, examples):
"""Index features (one hot) from fields in examples and options."""
# if not args.create_vocab:
return json.load(open(os.path.join(args.vocab_dir, 'feat_dict.json')))
def _insert(feature):
if feature not in feature_dict:
... | 7be12c092f369587429e7ff0af9c05b2e6200c55 | 73,497 |
def get_label_mask(labelPath, params, mode):
"""
Loads the ground truth image (semantic or depth)
:param labelPath: Path to the ground truth file (CLS or AGL file)
:param params: input parameters from params.py
:param mode: either SEMANTIC_MODE or SINGLEVIEW_MODE from params (0 or 1)
:return: nu... | 049e9c0195f840c3a62e2db9e31eae75c67e02cd | 73,498 |
def _is_url(filename):
"""Check if the file is a url link.
Args:
filename (str): the file name or url link.
Returns:
bool: is url or not.
"""
prefixes = ['http://', 'https://']
for p in prefixes:
if filename.startswith(p):
return True
return False | cfffb3db75de4f613097c081f950d3feff079f63 | 73,499 |
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