content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
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 image_can_fit_message(image, message):
"""Returns whether or not the given image can accommodate the given message"""
# Get the number of bands per pixel. This is how many bytes are used to represent each pixel.
# For example, an RGBA pixel will have 4 bands, giving us four pixels to update.
pixel_... | f23a17234b9575fbca702a918f8f257ebb29e927 | 73,611 |
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 |
import os
def execute(args):
"""Executes the ``delete`` command."""
def stdout(message, end='\n'):
# print a message to stdout only if not in quiet mode
if args.quiet:
return
print(message, end=end)
def proceed():
# returns a bool for whether to proceed with t... | 8971fb3fbbb74376c5bada17f666da51b98a9ea4 | 73,624 |
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 |
from typing import Tuple
def filter_gaussian_mean(X: np.ndarray,
eps: float = 0.1,
tau: float = 0.1,
cher: float = 2.5,
use_randomized_svd: bool = True,
debug: bool = False,
... | 20ec94381d1f86640c7f20f921e23be843b60dca | 73,629 |
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 |
import os
def load_model(path, run_id=None):
"""
Load a H2O model from a local file (if run_id is None) or a run.
This function expects there is a h2o instance initialised with
`h2o.init()`.
"""
if run_id is not None:
path = mlflow.tracking._get_model_log_dir(model_name=path, run_id=r... | 29e6ceee62901aa093ee409adf4295d40f6ce207 | 73,636 |
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 |
import os
def get_linked_libraries(exes, libs=[]):
"""
Get a list of libraries linked to the list of executables
and (optional) find realpath to libraries
"""
_linked_libs = []
for exe in exes:
output = None
exe = os.path.realpath(exe)
if not os.path.exists(exe):
... | 5a65339ea37bed8d860e2f4f20d65ea97eda6568 | 73,651 |
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 |
from mlp.utils import check_path
import logging
import math
import time
def generate_wholebody_tsid(cfg, cs_ref, fullBody=None, viewer=None, robot=None, queue_qt = None):
"""
Generate the whole body motion corresponding to the given contactSequence
:param cs: Contact sequence containing the references,
... | d2c8d45c68e426a63740507ddb4727ad00261954 | 73,653 |
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 |
import yaml
import os
def create_dataset(config_file, output_run=None):
""" create data structure from input data files """
with open(config_file) as config_fh:
data_config = yaml.load(config_fh)
data_root = data_config['data_root']
if not os.path.isabs(data_root):
# relati... | cd5308f38c2acbee93369945bd7ac1770fa8d749 | 73,655 |
def get_next_code(last_code):
"""Generate next code based on the last_code."""
return (last_code * 252533) % 33554393 | 9fcf416df3448a8ca46a55073f66d12cd8fc2593 | 73,656 |
import shutil
from pathlib import Path
import os
def is_ffmpeg_installed(ffmpeg: str = "ffmpeg") -> bool:
"""
Check if ffmpeg is installed.
"""
if ffmpeg == "ffmpeg":
# use shutil.which to find ffmpeg in system path
return shutil.which("ffmpeg") is not None
abs_path = str(Path(ff... | 16fc862ab68313e6df9d41156856bf68b26b9192 | 73,657 |
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 |
import subprocess
def run_with_logging(cmd, logger):
"""
Run cmd and wait for it to finish. While cmd is running, we read it's
output and print it to a logger.
"""
process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
output_lines = []
while True:
line =... | eceffe7417a445d2b3adb7605b3a4e2679cfcca6 | 73,667 |
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 os
def create(output, result, output_format=None, output_style=None):
"""Create a status badge.
The badge file will only be written if it doesn't exist, or if the
existing badge file does not require any updates.
.. versionchanged:: 1.3.1 Only generate badge file if its contents
chang... | 80f8266fae1ae3fdd8483f01e34c4f6778db97b5 | 73,672 |
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 |
def glsl_parse_flow(source):
"""Parse flow block."""
(name, terminator, remaining) = extract_tokens(source, ("?n", "?;"))
if name in ("break", "continue"):
(statement, discarded) = glsl_parse_statement([name, terminator])
if discarded:
raise RuntimeError("discarded elements after... | 908e1d3d2a998527ffffa1e0ef75555cc70a6d94 | 73,676 |
import sounddevice as sd
def configure_sounddevice(sd=None, output='sysdefault', samplerate=44100):
"""
Will import, configure, and return sounddevice module to
play sounds using onboard sound card.
:param sd: sounddevice module to be configured,
defaults to None, will import new module i... | b05546018479f6606f6938c5066eb2951199913a | 73,677 |
def upload_role_chef_server(chef_conn_obj, file_name="sonic.json"):
"""
:param chef_conn_obj:
:param file_name:
:return:
"""
if not chef_conn_obj:
return False
command = "sudo knife role from file {}".format(file_name)
st.log("Remote Command: {}".format(command))
console_log ... | f796c275dd8f19ab748c094bbc4afd95ab0eb894 | 73,678 |
def as_torch(dt, upcast=True):
"""Convert a generic data type to a torch type
Parameters
----------
dt : dtype_like
Input data type
upcast : bool, default=True
If True, authorize upcasting the input type
Returns
-------
torch.dtype
Torch data type
"""
r... | f64b17f9f4590fdef8adb25fbf61b02beba714a5 | 73,679 |
def _MatchCharClassEsc(text, position):
"""Parse a U{charClassEsc<http://www.w3.org/TR/xmlschema-2/#nt-charClassEsc>} term.
This is one of:
- U{SingleCharEsc<http://www.w3.org/TR/xmlschema-2/#nt-SingleCharEsc>},
an escaped single character such as C{E{\}n}
- U{MultiCharEsc<http://www.w3.org... | 3e3c6a7cbe94122fbbd97c3f434447b459ed6ec6 | 73,680 |
def compute_sd_of_dist(dist, pgrid, Nitem):
""" Compute SD of probability distribution"""
m = compute_mean_of_dist(dist, pgrid)
v = dist.transpose().dot(pgrid**2) - m**2
return np.sqrt(v) | 444df144d172f8a1d130ef3b7ceb4933c0badb20 | 73,681 |
import torch
def load_proposal_obj(obj):
"""
Load a set of proposals into memory
:param obj: Object to load proposals off of
:return: BBoxes object denoted proposal
"""
if obj['proposals'] is None:
return None
np_arr = np.array(obj['proposals'])
bbox_absolute = torch.from_numpy... | 42d839a3453d81e495fe8d556a74dbc4abe8a917 | 73,682 |
import argparse
def parse_args():
"""
Parse command line arguments.
"""
parser = argparse.ArgumentParser(formatter_class=argparse.RawDescriptionHelpFormatter, add_help=False)
group_general = add_general_parameters(parser)
group_instance = parser.add_argument_group('Instance Selection')
... | 7d840db620c1c2212d1e504a703c7fba460ba088 | 73,683 |
def api_get_all_categories():
"""
returns all categories as JSON
"""
categories = session.query(Category).all()
results = [category.serialize for category in categories]
return jsonify({"categories": results}) | 698bd218bc1334b430649de6e822aaabb650eec4 | 73,684 |
import argparse
def parse_args():
"""Parse arguments.
Returns:
args: The parsed arguments.
"""
parser = argparse.ArgumentParser()
parser.add_argument(
'--data',
dest='data_dir',
type=str,
help='Path to the training set.',
required=True)
args =... | bb589e28bfcfce372740cee45786c2ff4fa62b60 | 73,685 |
def spatialresolutions_id_put(id, user=None, spatial_resolution=None): # noqa: E501
"""Update an existing SpatialResolution
Updates an existing SpatialResolution (more information in https://w3id.org/okn/o/sdm#SpatialResolution) # noqa: E501
:param id: The ID of the SpatialResolution to be retrieved
... | 3998b1ac3371e3df4e6e6d8775204b229cc4dfbe | 73,686 |
import pdb
def debug(func):
"""debug is a method decorator that invokes the python integrated
debugger in a given method. Use it to step through tricky
code. Note that pdb is not integrated with emacs or anything like
that, so you'll need a shell to see what's going on.
"""
def method(*args,... | 76ed776b8f43a02f719d9101e480d41d958c9d91 | 73,687 |
def prony(t, F, m):
"""Input : real arrays t, F of the same size (ti, Fi): integer m - the number of modes in the exponential fit
Output : arrays a and b such that F(t) ~ sum ai exp(bi*t)
"""
# Solve LLS problem in step 1
# Amat is (N-m)*m and bmat is N-m*1
N = len(t)
Amat = np.zeros((N - ... | 7a4ae656f6d049661310ff12f769fc3467a34092 | 73,688 |
def g_MAD(w, x, y):
"""Compute gradient of Minimum Absolute Deviation (MAD) loss
g = 1/n * d/dw \sum{ |y - x.w| }
= 1/n * \sum{ sign(e) * (-x) } where e = y - x.w
"""
e = y - x.dot(w)
grad = np.multiply(-x, np.transpose([np.sign(e)]))
mean_grad = np.mean(grad, axis=0)
# logger.debug(m... | eb2d59c361beb0b9f1ca31a3012f723c02a92bc4 | 73,689 |
def plot_outlier(spark, idf, col, split_var=None, sample_size=500000):
"""
Parameters
----------
spark
Spark Session
idf
Input dataframe which would be referred for capturing the outliers in form of violin charts
col
Analysis column
split_var
Column which is ... | e5a7c232653e1b895595ef32ab67bc0b427d9dcb | 73,690 |
import pathlib
def _rename_destination_blob(blob_name: str, src: _GCSURL,
dst: _GCSURL) -> pathlib.Path:
"""
Rename destination blob name to achieve gsutil-like cp -r behaviour.
Gsutil behavior for recursive copy commands on Google cloud depends on
trailing slash.
| e... | 85fa9a7758f696b9820528d7d81af5326327af34 | 73,691 |
from re import U
def press2alt(P, press_units=default_press_units,
alt_units=default_alt_units):
"""
Return the altitude corresponding to the specified pressure, with
pressure in inches of HG, mm of HG, psi, psf (lb per sq. ft), pa, hpa or
mb.
The altitude is in units of feet (... | e68ad74d7993df1fcb85127106f649876228bef9 | 73,692 |
import os
from datetime import datetime
import requests
def get_sos(xml_file=None):
"""Return a SensorObservationService instance"""
if xml_file is None:
data_dir = ircelsos_data_dir()
if not os.path.exists(data_dir):
os.makedirs(data_dir)
xml_file = os.path.join(data_dir,... | 5a71931f8c36f011a67fddfb8c62381b40f6382a | 73,693 |
def gluNurbsSurface( baseFunction, nurb, sKnots, tKnots, control, type ):
"""Pythonic version of gluNurbsSurface
Calculates knotCount, stride, and order automatically
"""
sKnots = arrays.GLfloatArray.asArray( sKnots )
sKnotCount = arrays.GLfloatArray.arraySize( sKnots )
tKnots = arrays.GLfloatA... | 127c733a6058c74af62a9990ff2a770a9e287cee | 73,694 |
from typing import Counter
def session_referer_class(session):
"""Most common referer class in session (categorical)."""
referer_class = Counter([r['referer_class'] for r in session]).most_common(1)[0][0]
return referer_class | 0b4047ea63063b7535bbaea7c67756de15561522 | 73,695 |
def _get_Is_from_Imidval(reflections, Imid):
"""Intepret the Imid value to extract and return the Icomb and Vcomb values."""
if Imid == 0: # special value to trigger prf
Int = reflections["intensity.prf.value"]
Var = reflections["intensity.prf.variance"]
elif Imid == 1: # special value to ... | 1b23a8218fbdd15ede2f27a6ca0fb531befe18ae | 73,696 |
import argparse
def parse_arguments():
"""Parse arguments"""
parser = argparse.ArgumentParser()
parser.add_argument(
"-i",
"--input",
type=str,
default="output/optimized_timetable",
help="Input directory",
)
parser.add_argument(
"-or",
"--ori... | ea7e944a5a07f29bb52217d0aeaafa287f0b6c47 | 73,697 |
import warnings
import atexit
import os
import time
def optimize_stellar_parameters_2(initial_guess, transitions, EWs=None,
alphafe=0.4,
expot_balance_species=26.0,
ionization_balance_species_1=26.0,
... | 7bde5d12859a5ada88e9bbd864d20727e28c8869 | 73,698 |
import json
def lambda_handler(event, context):
"""
注文情報を登録する
Parameters
----------
event : dict
フロントより渡されたパラメータ
context : dict
コンテキスト内容
Returns
-------
payment_id : dict
会計ID
"""
# パラメータログ
logger.info(event)
if event['body'] is None:
... | ef7f718a7ef216b49865d93f1d1888c132609ab8 | 73,699 |
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