content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def invalid_entitlements_fixture(request):
"""A parameterized pytest fixture which returns invalid entitlements.
Args:
request : Built-in pytest fixture
Returns:
[String]: A string containing invalid Entitlements.
"""
return request.param | 7f98b101bd8db303bb62a8c392689694f3a46805 | 73,561 |
def returns(*args):
""" The decorator is used to allow us to specify the keys of the
dict that the task returns.
This is used only to signal to the user the inputs and outputs
of a task, and deduce what arguments are required for a chain.
"""
if not args or len(args) != len(set(args... | 96f7056b7bb30188d63b650c62d9932ba06c2996 | 73,562 |
def build_regionvit_fpn_backbone(cfg, input_shape: ShapeSpec):
"""
Args:
cfg: a detectron2 CfgNode
Returns:
backbone (Backbone): backbone module, must be a subclass of :class:`Backbone`.
"""
bottom_up = build_regionvit_backbone(cfg, input_shape)
in_features = cfg.MODEL.FPN.IN_FE... | c9e2872f15916df02051cf001482927fcaea183a | 73,563 |
from typing import Any
def circuit_regions(
draw: Any,
max_max_cycle: int = 1000,
max_num_qudits: int = 20,
max_volume: int = 200,
max_qudit: int = 1000,
empty: bool | None = None,
) -> CircuitRegion:
"""Hypothesis strategy for generating `CircuitRegion`'s."""
if empty is True:
... | 7e4c53ce36c2e4070964574227aa208ac6d22e70 | 73,566 |
def surface_area(r):
""" this is a test to see how to combine two versions """
return np.pi*r**2 | 3fb0475124ee65ea37386c7a9ea7d4f04a3bf25a | 73,567 |
def __get_time_weight_in_list(d: dict) -> timedelta:
"""Returns the minimum time weight from the time list contained in the dict values
ex: {'key': [time(hour=12), time(hour=9)]} => timedelta(hour=9)
"""
weights = [__get_time_weight(t) for t in d[1]]
return min(weights) | e13c0240c5cf716f0023e831ecdd3dcf70a36270 | 73,568 |
import re
def compute_word_freq(filename):
""" Computa a frequencia de ocorrencia de palavras em um dado arquivo
de texto.
Devolve um dicionario mapeando cada palavra com pelo menos 5 caracteres
(ignorando caixa alta e baixa) na sua frequencia de ocorrencia.
Considere uma palavra como qualqu... | 97b142281453a36a04e96345d91c67f052fd98c2 | 73,569 |
def pairwise_distance_np(feature, squared=False):
"""Computes the pairwise distance matrix in numpy.
Args:
feature: 2-D numpy array of size [number of data, feature dimension]
squared: Boolean. If true, output is the pairwise squared euclidean
distance matrix; else, output is th... | 8c8e512da171fa8626dab58a031463e44ab7cf1c | 73,570 |
def _get_triplet_ipsative_score(pair_score, trait_size, item_dt, item_sign):
"""
配对比较分数转自比分数
:param pair_score: list(int), 配对比较分数
:param trait_size: int, 特质的数量
:param item_dt: dict(int: int), 试题维度字典
:param item_sign: list(1|-1), 试题正反向列表
:return: list(int), 自比分数列表
"""
score = np.zeros... | 7dc57f1148d65f4822c499418ab8470c0d04ae29 | 73,571 |
import requests
def coinbase_price_check(coinbase_api_key, coinbase_api_secret,
coin):
"""Check the price of a cryptocurrency against Coinbase to see
if it fell below the minimum price
Args:
coinbase_api_key: An API key for Coinbase APIv2
coinbase_api_secret: An A... | 622785a111e7019244479d4e520b119f873d7aa9 | 73,572 |
def _tensor_apply_decay_with_sparse(weight_decay, if_apply, weight, gradient):
"""Get grad with weight_decay."""
if if_apply:
indices = gradient.indices
values = op_add((op_gather(weight, indices, 0) * weight_decay, gradient.values))
shape = gradient.dense_shape
return RowTensor(... | d8dfa894f085d2b23300bdb25b787375453b325a | 73,574 |
def cal_performance(pred, gold,IGNORE_ID,normalize_length=False,smoothing=0.0):
"""Calculate cross entropy loss, apply label smoothing if needed.
Args: pred: N x T x C, score before softmax ;;;; gold: N x T """
pred = pred.view(-1, pred.size(2))
gold = gold.contiguous().view(-1)
loss = cal_loss(p... | a859c97a20bf643b6a580ce6cc50acb674339dc8 | 73,576 |
def exponential(x, halflife):
""" Returns a decay factor based on the exponential function
.. math::
f(x) = 2^(-x/halflife).
:param x: The function argument.
:param halflife: The half-life of the decay process.
"""
return 2 ** (-x / halflife) | 2561d42f87c2818e82c2cc065592acf9ac8202fe | 73,577 |
def down_sample(u_fine, grid_fine, grid_coarse):
"""Compute cell-averages of `u_fine` on the coarse grid."""
if grid_fine.n_dims == 2:
raise Exception("Needs to be implemented.")
ngf = grid_fine.n_ghost
ngc = grid_coarse.n_ghost
ncf = grid_fine.n_cells[0] - 2*ngf
ncc = grid_coarse.n_ce... | 6b1bc6b59fb698f992e21ca0817551e4c4ee9d0b | 73,578 |
from ssd_util import SsdUtil
from sonic_platform_base.sonic_ssd.ssd_generic import SsdUtil
def import_ssd_api(diskdev):
"""
Loads platform specific or generic ssd_util module from source
Raises an ImportError exception if none of above available
Returns:
Instance of the class with SSD API imp... | 8e457604b28a4ba7e2c141751dce96c966edae8b | 73,579 |
def get_cpu_part():
"""Get the CPU part.
:returns: The CPU part.
:rtype: string
"""
return get_cpu_info("CPU part") | 7faa09c02ce895752a8f97cc74a023fe729a0ef4 | 73,580 |
def keywithmaxval(dict):
""" a) create a list of the dict's keys and values;
b) return the key with the max value"""
if len(dict) > 0:
v=list(dict.values())
k=list(dict.keys())
return k[v.index(max(v))]
else:
return "Check" | 56bc272c1ed65c60ddd0cea51a46736885796d9b | 73,581 |
import pickle
def decache(name, msg='', silent=False):
""" decache a file """
try:
with open(DIR_CACHE + name + '.pkl', 'rb') as f:
obj = pickle.load(f)
if not msg:
msg = name
msg = str(msg).ljust(30) + ' (loaded from cache)'
if not silent:
p... | b4792db83eb31f25649091d1f54f5e7453b31180 | 73,582 |
from typing import Iterable
from pathlib import Path
from typing import Optional
from typing import Dict
def to_lwpolylines(
paths: Iterable[Path], *,
distance: float = MAX_DISTANCE,
segments: int = MIN_SEGMENTS,
extrusion: 'Vertex' = Z_AXIS,
dxfattribs: Optional[Dict] = None) ... | 5d167e77e76fd6327a24fe4e24ee618302ddd875 | 73,583 |
import torch
def augment_and_mix(image, trans, cfg):
"""Perform AugMix augmentations and compute mixture.
Args:
image: PIL.Image input image
preprocess: Preprocessing function which should return a torch tensor.
Returns:
mixed: Augmented and mixed image.
"""
aug_list ... | e3503547e2dfe990b85cf91c3f947901c7cd799d | 73,585 |
from typing import Dict
from typing import Callable
from typing import Optional
def qualys_command_flow_manager(
client: Client, args: Dict[str, str],
command_name: str,
command_methods: Dict[str, Callable]) -> Optional[CommandResults]:
"""
Args:
client: Client object for makin... | f9a763708d503ac89efa1d0673fae7959966d7db | 73,586 |
def rm_strheader(images):
"""
Remove the header of the images base64 string from front-end
:param images: the input should be the base64 string of the image
:raises TypeError: if input is not a string
:returns: base64 string without data header
:rtype: string
"""
if type(images) is not... | 7466621dfa0a5bb31eb8735da89d68b885cb04ea | 73,587 |
def glmfit(X, y, c=None, tail='both'):
"""
Linear estimation using GLM models
-----------------------------------
Paramters:
X: sample*feature. Independent matrix
y: sample*yfeature. Dependent matrix
c: contrast matrix
tail: tails for significance
Returns:
--------
cope: ... | 4ff2f7902a132c8b5f1a91a2752b8d76d7aa0a26 | 73,588 |
def test_structure_hook_func(converter):
""" testing the hook_func method """
def can_handle(cls):
return cls.__name__.startswith("F")
def handle(obj, cls):
return "hi"
class Foo(object):
pass
class Bar(object):
pass
converter.register_structure_hook_func(can... | c61be290b3c7cbb2af87d47b76f09a662ada2fb5 | 73,589 |
def box_to_rect(box, width, height):
"""
:param box: center_x, center_y, bbox_w, bbox_h
:param width: image width
:param height: image height
:return: x1, y1, x2, y2(in pixel)
"""
x, y, w, h = box
x1 = (x - w * 0.5) * width
y1 = (y - h * 0.5) * height
x2 = (x + w * 0.5) * width... | 32413d14e242f2d790c5ae9c93418abb4152df46 | 73,590 |
def __get_profile_from_points(voters, cands, voter_points, cand_points, approval_threshold):
"""Generates a list of approval sets from 2d points according to
approval_threshold."""
profile = {}
for v in voters:
distances = {cand: __euclidean(voter_points[v], cand_points[cand]) for cand in cands}... | efbd633e669cae71a6774e3f1656346b8f06cb19 | 73,591 |
def calc_mean_std(features):
"""
:param features: shape of features -> [batch_size, c, h, w]
:return: features_mean, feature_s: shape of mean/std ->[batch_size, c, 1, 1]
"""
batch_size, c = features.size()[:2]
features_mean = features.reshape(batch_size, c, -1).mean(dim=2).reshape(batch_size, c... | fea325f57491cf06a4c2ffec4fb0a187ddea4a0a | 73,592 |
import pickle
def loadDownloader(tickerType):
"""loads from intermediate pickle file
"""
with open(tickerType + ".pickle", "rb") as f:
return pickle.load(f) | 2032e856cfc0e1d0048d1aa61dfc66a4ef9fa486 | 73,593 |
def _generate_one_ephemeris(
cmd):
"""generate one orbfit ephemeris
**Key Arguments:**
- ``cmd`` -- the command to execute [cmd, object]
**Return:**
- ``results`` -- the single ephemeris results
"""
global cmdList
cmd = cmdList[cmd]
results = []
for c in cmd:
... | dfd25a0942b094f0e5034ac06192983f35e4ae43 | 73,594 |
def setbreak(depth = 0):
"""
Pause the script for inspection at next script statement.
"""
return __setbreak(depth + 2) | 142d5fec24652a4afb484120bd8a0c647e649077 | 73,595 |
def PGD(S, cov, rho, criterion=None):
""" PGD algorithm """
n = cov.shape[0]
# Implement the PGD algorithm
d_k, V_k = np.linalg.eigh(cov)
s_k, U_k = np.linalg.eigh(cov)
t_k = np.linalg.eigh(S)[0]
cov_sqrt = np.dot(np.sqrt(d_k) * V_k, V_k.T)
prec_sqrt = np.dot(np.sqrt(1 / d_k) * V_k, V_k.... | ba11f8a6138437b0025dab7fd83dd003da41cec3 | 73,596 |
def route(command):
"""
:param command: a RemoteCommand
:return: route string
"""
return "/api/v1/{}/{}/".format(service_constants.API_NAME, command.value) | 1a6d477771815959d026fa20f56fdf21d4913baf | 73,597 |
def compute_roi_pool(attrs, inputs, _):
"""Compute definition of roi_pool"""
assert attrs.layout == "NCHW"
return [topi.vision.rcnn.roi_pool_nchw(
inputs[0], inputs[1], pooled_size=get_const_tuple(attrs.pooled_size),
spatial_scale=attrs.spatial_scale)] | 62aee416f8417274bc1d729b791dc5325fef1e23 | 73,598 |
import copy
import datasets
def average_validation(records, weights):
""" This is for population shift datasets
Args:
records (dict): Dictionary of records from a single training run
weight (list): List of domains weights
Returns:
float: validation accuracy of the best checkpoint... | 80d9e6e7ba336b430d4f17e60f3a2409aa6dd49d | 73,599 |
def gomc_sim_completed_properly(job, control_filename_str):
"""General check to see if the gomc simulation was completed properly."""
job_run_properly_bool = False
output_log_file = "out_{}.dat".format(control_filename_str)
if job.isfile(output_log_file):
with open(job.fn(f"{output_log_file}"), ... | 542c22836e22a3cc97a38744959dcb21b833c7a0 | 73,600 |
from pathlib import Path
from typing import Dict
from typing import Any
import warnings
def fetch_openml_dataset(dataset_id: int,
data_directory: Path = get_data_dir(),
) -> Dict[str, Any]:
"""
Gets a dataset from OpenML (https://www.openml.org),
or from t... | b26eea4057bbe45d72314de43b20756aec8e10ad | 73,601 |
import json
def build(**kwargs):
""" build message, return dict """
t = Template(template())
content = t.substitute(**kwargs)
return json.loads(content) | 1e9dd75f385e0cb8f5cfe92f04a4823c98dd70a4 | 73,602 |
import torch
def gcxgcywh_to_cxcywh(boxes, anchors):
"""
Decode bounding box coordinates predicted by the model, since they are encoded in the form mentioned in the encoding function.
They are decoded into center-size XYWH coordinates.
:param boxes: encoded bounding boxes, i.e. output of the mod... | c4dda7ea9696fb4620079f06a59e7e672e29d8d3 | 73,603 |
import sqlite3
def connect_db():
"""Connects to the specific database."""
rv = sqlite3.connect(db_uri, uri=True)
rv.row_factory = sqlite3.Row
return rv | 79734752d6fbae92f736f59fa40d9b5ab0090ca6 | 73,604 |
from unittest.mock import patch
async def setup_unifi_integration(
hass, config, options, clients_response, devices_response, clients_all_response
):
"""Create the UniFi controller."""
hass.data[UNIFI_CONFIG] = []
hass.data[UNIFI_WIRELESS_CLIENTS] = unifi.UnifiWirelessClients(hass)
config_entry = ... | d031e0244cfe315c66b137fd7967d40cfef7a385 | 73,605 |
def mean(data, key=None):
"""
mean with data type check
:param data: points
:param key: key function
:return:
"""
if key is not None:
data = [key(point) for point in data]
data = filter(lambda x: isinstance(x, (int, float, long)), data)
if len(data) < 1:
return None
... | 92e7142628706a467875b03d88dcb1a748e85068 | 73,606 |
def SqrNorm(x):
"""Square of the norm.
:param x: return sum(x*x)
:return: return sum(x*x)
"""
return sum(x*x) | 03f35a7395ba74981eace38b634a14210932cffd | 73,607 |
from pathlib import Path
def create_h5temp_global() -> Path:
"""Create temporary global HDF5 rawfile.
Returns:
Path: Path object of filename.
"""
fn = Path("/tmp/data/MXD13A2.006.VIM.h5")
rows = 2000
cols = 7200
with h5py.File(fn, "a", driver="core", backing_store=True) as h5f... | 02f884b613f2da23ce2344adf70e9f9707cab3a9 | 73,608 |
from typing import Tuple
from typing import Sequence
def sample_text_elements(workspace_id: str, dataset_name: str, sample_size: int, filter_func, remove_duplicates=False,
random_state=None) -> Tuple[Sequence, int]:
"""
:param sample_size: if None, return all elements without samplin... | a603cd188bc5d593abb20b51fd99286bf49ac53d | 73,609 |
import socket
def create_connection(server=None, port=None, timeout=None, use_ssl=False):
"""Create a socket or a secure ssl socket.
Hopefully some day such functionality will be included in python3.
:returns socket
:rtype socket.SocketType
"""
# based on socket.create_connection()
if us... | 8596d3dc7c0cf7e75933618c0c302f5ddb63a420 | 73,610 |
def build_cudnn_layers(layers, units, activation, memory_cell, direction, dropout, name):
"""
Builds layers optimized for CuDNN if hparams.use_cudnn_layers is True.
Args:
layers: The number of layers.
units: The number of units per layer.
activation: Activation function to ... | 872b86984d2771e0b9c6425534ef567789a28e7d | 73,612 |
from typing import Union
from datetime import datetime
def get_next_trading_date(date: Union[str, datetime.date, datetime.datetime, pd.Timestamp], n:int=1) -> pd.Timestamp:
"""
获取指定日期之后的第 n 个交易日
:param date: 指定日期
:param n: 第 n 个交易日
:example:
.. code-block:: python3
... | e177529697377be8c5c86c7bd05b75419a65e9f4 | 73,613 |
def new_superuser(db, new_superuser_factory):
"""Return a new superuser"""
return new_superuser_factory() | 7b0751788c9aea1cd37b7e26deb5a7f6e1d6a35f | 73,614 |
def _parse_numpy_pixeltype_from_string(s):
"""
example: "image_FLOAT_3D.nii.gz" -> 'float32'
"""
if 'UNSIGNEDCHAR' in s:
return 'uint8'
elif 'CHAR' in s:
return 'int8'
elif 'UNSIGNEDSHORT' in s:
return 'uint16'
elif 'SHORT' in s:
return 'int16'
elif 'UNSIG... | 8066c9eab8b31fa290ac68d44b6bd448a3a689de | 73,615 |
def _compute_distance(x1, x2, mean_vector, epsilon=0.0000001):
"""
Compute distances between data points by using L1 on normalized data : sum(abs(x1-x2)/(mean_vector+epsilon))
Parameters
----------
x1 : array
First vector
x2 : array
Second vector
mean_vector : array
... | 358c728862703dd4b83ec423caf69910a51bc1f7 | 73,616 |
def scan(name, work_queue, result_queue):
"""Loads data into work_queue, then gets results from result_queue."""
try:
with open(name, 'rb') as f:
for i in read_in_chunks(f):
work_queue.put(i)
except IOError:
return 'Error'
else:
work_queue.join()
... | efcc9309ea7c3b229489df209e2a797cf8d62ba2 | 73,617 |
from vtk import vtkImageBlend
def combine_images(*images):
"""
Layer images onto each other (centered) and return the output
"""
width, height = 0, 0
for i in images:
new_w, new_h, _ = i.GetDimensions()
if new_w > width:
width = new_w
if new_h > height:
... | 630a141f26a2347710f9eb851fa04ffe700a1a0f | 73,618 |
def calc_dist_folded(x,y,z,unitcells,shifts=None,matrix=False,npt=False):
"""New: take into account pbc
danger of accumulative error
x -- x-coordinates of positions, ntime x natom
y -- y-coordinates of positions, ntime x natom
z -- z-coordinates of positions, ntime x natom
unitcells -- array wi... | 29b9f925df52c5a548be2224d680005a9691a25a | 73,619 |
def ortho(modes):
"""\
Orthogonalize the given list of modes.
"""
N = len(modes)
A = np.array([[np.vdot(p2,p1) for p1 in modes] for p2 in modes])
print 'A.shape ',A.shape
e,v = np.linalg.eig(A)
print 'e', e
print 'v', v
print v[:,0]
ei = (-e).argsort()
print 'ei', ei
... | 1aa604023614fe0415cf4bb20bdcb600bf18e791 | 73,620 |
def get_databases_list(server_uri, query):
"""
List databases on a specified MySQL server
Arguments:
server_uri : URI of MySQL server e.g. mysql://user@host:3306/
query : optional regular expression to filter databases e.g. .*_core_.*
"""
if db_uri.startswith('mysql') is False:
r... | 7ebd266b08712d3ba1b5bcaac4271e0e669140cf | 73,621 |
import re
def remove_superscripts(word: str) -> str:
"""
This function removes all superscripts from a given word.
:param word: A given word
:return: The given word stripped from superscripts.
"""
rx = '[' + re.escape(''.join(SUPERSCRIPTS_TO_UNICODE_CHARS.keys())) + ']'
return re.sub(rx, ... | 6cfbb0d4cbe64c9ec488c64adad8d1f6941afaa7 | 73,622 |
import urllib
import json
def get_articles(id):
"""Function to retrieve news sources list from the News api"""
get_articles_url ='https://newsapi.org/v1/articles?source={}&apiKey={}'.format(id,api_key)
with urllib.request.urlopen(get_articles_url) as url:
get_articles_data = url.read()
... | dfcbfcc48d8739cb6e9a69692604704cbf7333c4 | 73,623 |
def set_zenangle(profs, zen=None):
"""Set zenith angles to a new value. If zen is missing, angles cycle in
steps of 10 degrees between 0 and 70 over the profile set."""
if zen:
zenlist = [zen]
else:
zenlist = range(0, 71, 10)
for p in range(profs['nprof']):
profs[p]['zena... | 41d7099e7eb7ac9da1532c28be00b1a574e84e6e | 73,625 |
def preprocess(X):
"""
Optional preprocessing for secondary data format.
@param X: list of lists of lists (glogs, function calls, function call + attributes)
"""
for i in range(len(X)):
for j in range(len(X[i])):
X[i][j] = ' '.join([str(x) for x in X[i][j]])
X[i] = '\n'.j... | b759c0353dfeb5c2d4292fd541c8dba507c1ccea | 73,626 |
import requests
from bs4 import BeautifulSoup
def question_info_get(qid):
"""
获取问题的标签
Parameters
----------
qid : int
question id.
Returns
-------
keywords：list
问题关键词
"""
headers = {
"User-Agent": "",
"Connection": "",
"Accept": "",
"Accept-La... | fb5f1d6bf41a267237f24d677e43c51c474a90f7 | 73,627 |
def initialize_logger(options):
"""Initialize logger instance."""
# Default of None means to use colorama's autodetection to determine whether or not to use color
color = None
if options.get("force_color"):
color = True
if options.get("no_color"):
color = False
enable_logging(ve... | 041b9df2be0ce015aa79650b4eb0599c1ef5ae12 | 73,628 |
def get_registration_extension_form(*args, **kwargs):
"""
Convenience function for getting the custom form set in settings.REGISTRATION_EXTENSION_FORM.
An example form app for this can be found at http://github.com/open-craft/custom-form-app
"""
if not getattr(settings, 'REGISTRATION_EXTENSION_FORM... | d07155c013ea62ce1c8aa96bbab2b2fa66b15633 | 73,630 |
def _add_one_hot_encoding(df, skip_one_hot_columns=None, one_hot_columns=None):
"""
integer columns are converted to onehot columns. This is helpful in gradient based models LR,NN.
Returns a dict mapping old column to new column names.
"""
new_columns_dict = {}
dtypes_df = df.dtypes
if one... | 4ea21a4383ef921848594e387ba650c72234850e | 73,631 |
import yaml
def read_config(filename):
"""Read configuration file.
:param filename: Path to configuration file.
"""
with open(filename) as f:
params = yaml.safe_load(f)
return params | 7fb88e746c7cdc234a648a3a6216fa49f682f9d9 | 73,632 |
def reverse_dict(d):
"""Reverses direction of dependence dict
>>> d = {'a': (1, 2), 'b': (2, 3), 'c':()}
>>> reverse_dict(d) # doctest: +SKIP
{1: ('a',), 2: ('a', 'b'), 3: ('b',)}
:note: dict order are not deterministic. As we iterate on the
input dict, it make the output of this function d... | 95bd1f427a4e6635b678e129c8f2d69b4b083f9f | 73,633 |
def compute_absolute_power(freqs, powers, band, method='sum'):
"""Compute absolute power for a given frequency band.
Parameters
----------
freqs : 1d array
Frequency values.
powers : 1d array
Power spectrum power values.
band : list of [float, float]
Band definition.
... | 92db5c6b62bd778b708168de85277265682c5da8 | 73,634 |
from typing import Optional
def get_server_trust_group(location_name: Optional[str] = None,
resource_group_name: Optional[str] = None,
server_trust_group_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> Awaitab... | 8e84a2d0d0b0ac3a93bb9bec1cd54c3bfaadf455 | 73,635 |
def get_csr(ttl=None, common_name=None, locality=None,
country=None, province=None,
organization=None, organizational_unit=None):
"""Generate a csr for the vault Intermediate Authority
Depending on the configuration of the CA signing this CR some of the
fields embedded in the CSR ma... | f3362a7ba941e2f625da2badd3dd1fddb2894062 | 73,637 |
def set_unauthorized(nxt: HTTPFunc, ctx: HTTPContext) -> Future[HTTPContext | None]:
"""Sets response status code to UNAUTHORIZED.
Args:
nxt (HTTPFunc): to run next.
ctx (HTTPContext): to process.
"""
return set_status(UNAUTHORIZED)(nxt, ctx) | 60b9bda0b1db5426f7ec6d535c5ab4b5fe458ed8 | 73,638 |
from typing import List
from typing import Dict
def flatten_dict(d) -> List[Dict]:
"""
Use this helper functon to flatten a dict holding API response data
and namespace the attributes.
"""
def expand(key, val):
if isinstance(val, dict):
return [(key + "." + k, v) for k, v in f... | be0f0df42048276e1c16cfcf117de4c7d096e7be | 73,639 |
def argmax(array):
"""Return the index of the minimum element of an array.
Examples
--------
>>> _argmin(np.array([1,-1,2,3]))
(3,)
>>> _argmin(np.array([[0,1],[2,1]]))
(1, 0)
"""
return np.unravel_index(np.argmax(array), array.shape) | d3e4914fd00eb13cc91c53159f7b95c9d92359b8 | 73,640 |
def spectroscopic2name(el,roman):
"""
Convert from spectroscopic notation, e.g. Fe XI to 'fe_11'.
Parameters
----------
el : `str`
Elemental symbol, e.g. Fe for iron
roman : `str`
Roman numeral spectroscopic symbol
"""
elu = el.lower()
romanu = roman.upper()
idx... | ca48b58f525333b4a9c1d5ae475a2c752dcc4c10 | 73,641 |
def poly_fit(traj, traj_len=30, threshold=0.002):
"""
Input:
- traj: Numpy array of shape (2, traj_len)
- traj_len: Len of trajectory
- threshold: Minimum error to be considered for non linear traj
Output:
- int: 1 -> Non Linear 0-> Linear
"""
t = np.linspace(0, traj_len - 1, traj_le... | 16daa3f38fd8b0c073dbe014585e29aade3e04b9 | 73,642 |
def get_all_classes_properties_numerical(endpoint=None):
"""
search for all class/property combinations with numerical objects. here we are relying on the defined
structure using rdfs:range and rdfs:domain (TBOX) and not on the data level
:param endpoint:
:return: a list of class/property combinatio... | 3ab48c9b38ce29a5f63295750fe5130a2cb75ec4 | 73,643 |
def dup(integer): # real signature unknown; restored from __doc__
"""
dup(integer) -> integer
Duplicate an integer socket file descriptor. This is like os.dup(), but for
sockets; on some platforms os.dup() won't work for socket file descriptors.
"""
return 0 | aac98f8c767d2224b3949aea4aafcb83d0c0ee1c | 73,644 |
def evaluate(session, loss_op, accuracy_op, feed_dict):
"""Evaluate the model.
Computes the loss and accuracy with repeated calls with the specified
feed_dict. Halts, when session.run raises an tf.errors.OutOfRangeError (i.e.
the whole dataset was iterated trough once and returns the average loss and
accurac... | 0d01b28f11ef054f6319bfa27ec9107c9cc6d853 | 73,645 |
import torch
def communities_to_labels(n_nodes, communities):
"""
For n_nodes nad a communties dictionary or list of lists returns a list with size 'n_nodes'
assigning to each node index the corresponding node community.
:param n_nodes:
:param communities:
:return:
"""
comm_labels = t... | e961568fff8959e909f0b44469a745d33ff5233d | 73,646 |
import torch
def to_q(mod, dim=0, CHUNK_SIZE=128):
"""Var approx distribution generator for a convolutional layer."""
assert isinstance(mod, ConvNdGaussianMixin)
def q(mean, log_var, dim=1 + len(mod.kernel_size)):
r"""Reinterpret fully factorized Gaussian `q` as factorized by slice.
Deta... | 0d47ce2d71ad7aa5ea20b707ddc995d0a0057b23 | 73,647 |
def build_orthogonalizer(S):
"""
Form the orthogonalization matrix A = S^{-1/2} using pure NumPy.
"""
# Application of a function to a matrix requires transforming to
# the diagonal basis, applying the function to the diagonal form,
# then backtransformation to the original basis.
eigval, ei... | fbed8405fddb8857d98219ba1c10841e0f00b404 | 73,648 |
def process_raw(procstatus, dscfg, radar_list=None):
"""
Dummy function that returns the initial input data set
Parameters
----------
procstatus : int
Processing status: 0 initializing, 1 processing volume,
2 post-processing
dscfg : dictionary of dictionaries
data set co... | 42af295ccb30a521f1c0502628d66826a550558a | 73,649 |
def load_data(filename: str):
"""
Load house prices dataset and preprocess data.
Parameters
----------
filename: str
Path to house prices dataset
Returns
-------
Design matrix and response vector (prices) - either as a single
DataFrame or a Tuple[DataFrame, Series]
"""
... | c1120d155f784f0ea17dbaf7afe2f2545c2a591f | 73,650 |
def check_intensifiers(text, INTENSIFIER_MAP):
"""
Utility function to check intensifiers of an emotion
:param text: text chunk with the emotion term
:return: boolean value and booster value for intensifiers
"""
# BOOSTER_MAP = {"B_INCR": 2,
# "B_DECR": 0.5}
intensity_word... | 2c35b6b66395bc7105b9fb1b9cf7f04b5686cb8d | 73,652 |
def create_email_message(to_emails, from_email, subject, text, html):
"""
Create the appropriate plaintext or html email object.
Returns:
email - an instance of either `django.core.mail.EmailMessage` or
`django.core.mail.EmailMulitiAlternatives` based on whether or
not `html_message` ... | 45049b4230e761487383879b5a3a65ca2c1260d5 | 73,654 |
def get_next_code(last_code):
"""Generate next code based on the last_code."""
return (last_code * 252533) % 33554393 | 9fcf416df3448a8ca46a55073f66d12cd8fc2593 | 73,656 |
from typing import Optional
def get_app_sec_security_policy(config_id: Optional[int] = None,
security_policy_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetAppSecSecurityPolicyResult:
"""
Use this data sou... | 9ee579e5d116aef2bdf915030de1de93f847efe7 | 73,658 |
def mixer_b32_224(pretrained=False, **kwargs):
""" Mixer-B/32 224x224
Paper: 'MLP-Mixer: An all-MLP Architecture for Vision' - https://arxiv.org/abs/2105.01601
"""
model_args = dict(patch_size=32, num_blocks=12, hidden_dim=768, **kwargs)
model = _create_mixer('mixer_b32_224', pretrained=pretrained,... | da7283d4286ec3f900a6abc2a39d3b386857ef1d | 73,659 |
from typing import List
def read_data(file: str) -> List[LabeledSentence]:
"""
Reads a dataset in the CoNLL format from a file
The format is one token per line:
[word] [POS] [syntactic chunk] *potential junk column* [NER tag]
One blank line appears after each sentence
:param file: string filen... | c89bad6fd011722daa5e6b7c92a97b5947296590 | 73,660 |
import requests
def get_histogram(ID, filename):
"""
GET request to get histogram image from server/database
Args:
ID (str): user name
filename (str): filename
Returns:
i (nparray) : array of histogram image
"""
djson = {
"username": ID,
"filename": fi... | ebbabb5847dea64c46daa0f802c15a3816b98b09 | 73,661 |
def detach_flc_policy(session, lc_policy_id, volume_id,
return_type=None, **kwargs):
"""
Detach a volume from a file lifecycle policy.
:type session: zadarapy.session.Session
:param session: A valid zadarapy.session.Session object. Required.
:type lc_policy_id: str
:para... | bd2a944eba3f999f7c132d2292448dfd6506298a | 73,662 |
import base64
def decode(b64):
"""
Decode given attribute encoded by using Base64 encoding.
The result is returned as regular Python string. Note that TypeError might
be thrown when the input data are not encoded properly.
"""
barray = base64.b64decode(b64)
return barray.decode('ascii') | 5c04c43247d1415ca8f1398c3b8206c50a7e0fa4 | 73,663 |
from unittest.mock import patch
async def async_setup_sdm(hass, config=CONFIG, with_config=True):
"""Prepare test setup."""
if with_config:
create_config_entry(hass)
with patch(
"homeassistant.helpers.config_entry_oauth2_flow.async_get_config_entry_implementation"
):
return awa... | e5e649e7bdc4428f578a85c2979077152e635902 | 73,664 |
def get_date(s):
"""Returns date object from string."""
if s.find(".") != -1:
# DD.MM.YYYY(.) format
args = s.split(".")
if args[len(args) - 1] == "":
args.pop()
args.reverse()
else:
# YYYY-MM-DD format
args = s.split("-")
args = list(map(int,... | 83145a9775685808aaf4855265dcdd37e37fb746 | 73,665 |
def _get_x_ranges(obs_mean, obs_cov):
"""Get integration limits (8 sigma interval, includes > 99.99% of area)."""
x_ranges = []
for (idx, var) in enumerate(np.diag(obs_cov)):
std = np.sqrt(var)
x_range = [obs_mean[0][idx] - 4.0 * std, obs_mean[0][idx] + 4.0 * std]
x_ranges.append(x_r... | 0d2174acfa264079e688db75e38f7ce4ff342570 | 73,666 |
def _strip(value):
""" Strip the input value if it is a string and returns None
if it had only whitespaces """
if isinstance(value, basestring):
value = value.strip()
if len(value) == 0:
return None
return value | 958d385d20260dc61d7b069911365242bcc73463 | 73,668 |
from typing import Union
from typing import Tuple
from typing import Any
from typing import Dict
def _tupleize_compound_item(k: Union[Tuple, str], v: Any) -> Dict:
""" converts a JSON-input compound key/value pair into a dictionary of tuples """
if _is_compound_key(k):
return {_tupleize_compound_key(k): _tupl... | 63ec7fc8eae7a6240cd633143851ed422e951e6c | 73,669 |
def norm_minmax(pixspec, vmin=None, vmax=None, axis=0):
"""Normalize features in the [0,1] range.
Parameters
----------
pixspec: ndarray
the set of spectra to normalize
vmin: float
custom minimum value; if None, computed from data
vmax: float
custom maximum value; if Non... | f2c00fa6f5211d14129d09f00f557e05358cb796 | 73,670 |
def read_traj_clusters(filename):
"""
Parses a textfile of online clusters, where each line contains
the space-separated values of one cluster-center.
"""
read_line = lambda s: [float(p) for p in s.split(" ")]
with open(filename, "r") as infile:
traj_clusters = np.array([read_line(line) ... | 4dcb0fc538b72a9dc2f3b91512b82348259712f1 | 73,671 |
import requests
def get_multizone_status(host, services=None, zconf=None):
"""
:param host: Hostname or ip to fetch status from
:type host: str
:return: The multizone status as a named tuple.
:rtype: pychromecast.dial.MultizoneStatus or None
"""
try:
status = status = _get_status(... | 59c7be58cf276ec5e5b1bb2352563494f87f3d06 | 73,673 |
import json
def load_global(what):
"""
Load data that is not specific to a single issue/MR.
For example users, milestones, issue list or MR list.
"""
path = DIR / f"{what}.json"
if not path.exists():
return fetch_global(what)
with open(path) as f:
return json.load(f) | fa9718d6111a091758bae38c6147586b6deaa5fe | 73,674 |
def pdvec(data, Nint, epsmax=1):
"""make persistence vector with the top Nint persistences using rips complex"""
digs, ints0, ints1 = gettree_int(data, edgelen=edgelen)
out1 = _pdproc(ints1, Nint)
out0 = _pdproc(ints0, Nint)
return (out0, out1) | cfd719eb7f3f4d877499ad6d2779424fec9b03fd | 73,675 |
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