content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
import csv
def get_first_last_onset(csv_file):
"""Gets the first and last onset times."""
with open(csv_file) as f:
full_track = list(csv.reader(f))
first_onset = float(full_track[0][0])
if first_onset < 0:
first_onset = abs(first_onset) # we only store the first onset if it is
... | d567530abf15fa5e256f7f826a813ad5982e3b0e | 3,610,567 |
def extractBivectorParameters_complicated(B):
"""
B must be a general rotation object on the format $ \phi*P + t n_{\inf}} $
"""
omega = float(B | E0)
phi, P, t_par, t_nor = extractBivectorParameters(B - omega * E0)
return phi, P, t_par, t_nor, omega | cede286088241caf8a2e28b009ae23a7295a85ec | 3,610,568 |
def ionic_strength(c,z):
"""Compute ionic strength from charges and concentrations
Arguments:
c: bulk concentrations [concentration unit, i.e. mol m^-3]
z: number charges [number charge unit, i.e. 1]
Returns:
float: I, ionic strength ( 1/2 * sum(z_i^2*c_i) ) [concentration unit, i.e. mol m^-3]... | 4abe692e499f17d1d38feac48842cc2f3494becb | 3,610,570 |
from typing import Type
def sign_extend_3(val, width, tmp):
""" Sign extension. High-order bit of val is left extended.
:param val: VexValue
:param width: VexValue
:param tmp: VexValue of 0xffffffff
"""
mask_sign_bit = (1 << (width-1)).cast_to(Type.int_32)
cond_sign_bit_1 = ex... | 6bd958e700a25eee3b7dfdaafbab49ede8ca0b45 | 3,610,571 |
def __check_if_alive(processes):
"""
Quickly check if at least one of the list of processes is alive.
Returns True if at least one process is still running.
"""
c = set([x.exitcode for x in processes])
return None in c | 22458fa4b2ca07fe8c1c21a60eac87d6546f8abd | 3,610,572 |
def previous_next_placement(doc_filter: DocumentFilter) -> pd.DataFrame:
"""
Calculate mu teamPlacement before and after a teamPlacement.
:param doc_filter: Input DocumentFilter.
:type doc_filter: DocumentFilter
:return: Previous and next expected placement based on current placement.
:rtype: p... | a8585550ec39e6572c5a447d2c17787d821616d0 | 3,610,573 |
def prices_to_returns(prices: pd.DataFrame, log: bool = False):
"""
Calculate the returns given prices.
Parameters
----------
:param prices: pd.DataFrame
A pandas DataFrame with asset prices
:param log: bool
Whether to compute logarithmic returns
Default is False -> line... | ce01815e530e634daa9500913d073afee1f1fdb9 | 3,610,574 |
def check_array(arr: Data) -> np.ndarray:
"""
Utility function for checking and validating input arrays.
"""
# Check array type
if isinstance(arr, (pd.DataFrame, pd.Series)):
arr = arr.to_numpy()
elif sparse.issparse(arr):
arr = arr.toarray()
elif isinstance(arr, np.nd... | 8bdb541c1cc92a3c1c22d0570aa5cc773f0ef13a | 3,610,575 |
def _SeriesFactory(ser):
"""
Return an instance of the appropriate subclass of _BaseSeries based on the
xChart element *ser* appears in.
"""
xChart_tag = ser.getparent().tag
try:
SeriesCls = {
qn("c:areaChart"): AreaSeries,
qn("c:barChart"): BarSeries,
... | e0ca78113a68e363c4f3de7acb9086a156fddf47 | 3,610,576 |
from typing import Union
from typing import Any
from datetime import datetime
def create_access_token(
subject: Union[str, Any], expires_delta: timedelta = None
) -> str:
"""Encodes a JWT
Args:
subject (Union[str, Any]): The content of the JWT.
expires_delta (timedelta, optional): The JWT... | e4301ca6eed32e5bd417d65fd5caf0483fcd17fb | 3,610,577 |
def n_mat_propostas(votadas = True):
""" Recebe um boleano que define se o retorno.
Se votadas for verdadeiro retorna um dicionário cuja chave é o nome do parlamentar
e o conteudo é o número de matérias propostas, pelo parlamentar, que foram votadas.
Se votadas for falso retorna um dicionário cuja chave é o nome... | 12c06ed57e0608ad27af555ac5de7d54f1e32ef3 | 3,610,579 |
def CreateDictionary(name_fmt, codeset, src_dir, out_dir, wrapper=None):
"""Creates a dictionary used for configs."""
exports = {}
if wrapper is None:
wrapper = lambda c: c
for code_class in registry.classes.values():
def Closure(code_class):
def Registerer(src, *args, **kwargs):
codeset.a... | 47bd7c991a5b044b517c023d4199f6700079f0e8 | 3,610,580 |
import glob
def test_data_list() -> list:
"""Return the list of paths to the test input data files
Parameters:
None
Returns:
list: The list of paths to the test input data files
"""
return glob.glob("test_data/*.rws.gz") | da3362910d0727fb21f433b34a77ad437ea0ccb1 | 3,610,581 |
def test_module(client, params):
"""
Returning 'ok' indicates that the integration works like it is supposed to. \
Connection to the service is successful. Anything else will fail the test.
:param client: client to use
:param params: parameters obtained from demisto.params()
"""
res = clien... | ddf10c97b841f00044d9cc11d04b8725e134d8cf | 3,610,582 |
def _url(data={}):
"""Helper method to generate URLs."""
data = "&".join(["{}={}".format(name, value) for
name, value in data.items()])
return "{}{}locative?{}".format(HTTP_BASE_URL, const.URL_API, data) | 09fa191aa45ab4c90390eb99962ba40930531f32 | 3,610,583 |
def model_from_json(json_string, custom_objects=None):
"""Parses a JSON model configuration string and returns a model instance.
Usage:
>>> model = tf.keras.Sequential([
... tf.keras.layers.Dense(5, input_shape=(3,)),
... tf.keras.layers.Softmax()])
>>> config = model.to_json()
>>> loaded_model ... | ea22de5736876edd252d25713ffc02a0abffce57 | 3,610,584 |
def route_vm_logic(logicFn):
"""
Decorates a function to indicate the viewmodel logic that should be executed after security checks and business
logic passes.
:param logicFn: The viewmodel logic function to assign.
:return: The decorated function.
"""
def decorator(fn):
fn.route_vm_... | 6dcbd274bd35b34f9faffb455d121940821cfa04 | 3,610,585 |
def format_obs_ensemble(obs_ensemble, obgnme):
"""
Reformat observation ensemble.
Parameters:
===========
obs_ensemble: pd.DataFrame, the observation ensemble
Returns:
===========
obs_ensemble: pd.DataFrame, the observation ensemble after new format.
"""
obs_ensemble.index =... | 898e6022297616dbd91d96067d883666c932bfa1 | 3,610,586 |
from typing import Iterable
def to_ideogram_html_str(gene_symbols: Iterable[str]) -> str:
"""Get an Ideogram HTML document as a string."""
annotations = get_ideogram_annotations(gene_symbols)
logger.info("using %d annotations in ideogram", len(annotations))
return get_ideogram_template().render(annota... | 27977573f3d64d5c35bd0f69c61e0c3aff82a75e | 3,610,587 |
import struct
def read2byte(i2cBus: SMBus, i2cAddr: int, lowByteAddr: int, highByteAddr: int) -> int:
"""
Read two byte from i2c Bus by using SMBus library
:param i2cBus: SMBus instance
:type i2cBus: SMBus
:param i2cAddr: i2c address, a one byte address
:type i2cAddr: int
:param lowByteAd... | 9a97dd7242930d10298834bb24702da21c29f019 | 3,610,588 |
import inspect
def typechecked(f):
"""
Use the @typechecked decorator on a function to perform run-time typechecking.
The docstring for `check_type` describes how type annotations should look.
"""
argspec = inspect.getfullargspec(f)
annotations = f.__annotations__
@wraps(f)
def g(*args... | 0801bb4e418fdc06c9293e6118ffc002b6bbc23f | 3,610,589 |
def top_k_incidence_decision(k: int = 3) -> IncidenceDecisionFunctionType:
"""Select exactly k subjects with highest probabilities.
Chooses random subjects if less than k subjects have positive probability.
Parameters
----------
k: int
the maximum number of subjects that are selected and r... | 56197f0254292be06c285f63bd3c6eb24045dde8 | 3,610,590 |
def draw_turn(row, column, input_list, user):
"""
Draw the game board after user typing a choice.
Arguments:
row -- the row index.
column -- the column index.
input_list -- a two dimensional list for game board.
user -- the user who type the choice
Returns:
input_list -- a two ... | 6f44e770a2fa04b5992ffd21cad5a799c3423de5 | 3,610,591 |
import math
def normal_vec(triplet):
"""
Return the unit normal vector to the plane defined by a triplet of atom positions [[x1,y1,z1],[x2,y2,z2],[x3,y3,z3]]
"""
p1 = [triplet[0][0], triplet[0][1], triplet[0][2]]
p2 = [triplet[1][0], triplet[1][1], triplet[1][2]]
p3 = [triplet[2][0], triplet[2... | 0d4a13814f75a1747544f348b5e78a0d758b480c | 3,610,592 |
def t_from_CT(SA, CT, p):
"""
Calculates *in-situ* temperature from Conservative Temperature of
seawater.
Parameters
----------
SA : array_like
Absolute salinity [g kg :sup:`-1`]
CT : array_like
Conservative Temperature [:math:`^\circ` C (ITS-90)]
p : array_like
... | 5ddd89c39ee100c3c114f1886d39284feda6587d | 3,610,593 |
import socket
def is_open_port(port):
"""
Check if a port is open (listening) or not on localhost.
It returns true if the port is actually listening, false
otherwise.
:param port: The port to check.
"""
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
result = sock.connect_ex... | 4eb8f52744cc7f330dd101b613d5db4ab8d0d0fc | 3,610,594 |
def hashid(obj, suffix=""):
"""
Returns a per-class unique hash that combines the object's
class name with its idnum and creation time. This makes this id unique also
between different typeclassed entities such as scripts and
objects (which may still have the same id).
"""
if not obj:
... | 511403801d81576e8f07999e4b27befd5b7429a6 | 3,610,595 |
def window_indices(frame, window=30, center=None, **kwargs):
"""
Get the linear indices for each satellite spot
Parameters
----------
frame : ArrayLike
image frame
window : float, Tuple, optional
window size, or tuple for each axis, by default 30
center : Tuple, optional
... | 646b92c0a2b057ffb8bc50c6f4d9adc9542c43c8 | 3,610,596 |
def open_pbobject(path, pb_class, verbose=True):
"""Load JSON as a protobuf (pb2) object.
Any calls to load protobuf objects from JSON in this repository should be through this function.
Returns `None` if the loading failed.
Parameters
----------
path: str
JSON file path to load
p... | d920919086ebd40f9d0e711b8475ebd2ac8d259e | 3,610,597 |
def _is_table(client, dataset_id, table_id, project_id):
"""Check whether a `table_id` is a view or not."""
if (dataset_id is None) or (table_id is None):
return False
dataset_ref = bigquery.DatasetReference(project_id, dataset_id)
table_ref = dataset_ref.table(table_id)
table = client["b... | cf355e9d3d332b30e0cb11f6c9880960de431567 | 3,610,598 |
def class_name(n):
"""
Formats a valid C# class name from the name format used in the XML.
@param n: The class name to format in C# style.
@type n: string
@return The resulting valid C# class name
@rtype: string
"""
if n == None: return None
try:
return native_types[n]
ex... | 4bd999c25ee2a51192668bee6534d300241652d9 | 3,610,599 |
import torch
def batched_soft_nms(boxes, scores, idxs, method, sigma, threshold):
"""
Performs soft non-maximum suppression in a batched fashion.
Each index value correspond to a category, and NMS
will not be applied between elements of different categories.
Args:
boxes (Tensor[N, 4]):
... | ebe231fe2114fa437b01ac8fc0e05ddd10fe20a1 | 3,610,600 |
import re
def match_id(url):
"""匹配歌单ID"""
try:
res = re.findall('id=(\d{4,12})', url)
return res[0]
except Exception as e:
pass
return None | 8a84cfe0ca0ebea154c451064ce838d4816e62d6 | 3,610,601 |
def decompress_files(filepaths, remove=False):
"""
This function ...
:param filepaths:
:param remove:
:return:
"""
# Initialize a list for the decompressed file paths
new_paths = []
# Loop over the files
for filepath in filepaths:
# Get the name of the file
fi... | a17134badfe9b259fdc599ec47ee294b40060951 | 3,610,603 |
def new_combo_column(title,
data_func=None,
changed_callback=None,
edited_callback=None,
editing_started_callback=None,
editing_canceled_callback=None,
spacing=0,
visible=True,
resizable=True,
sizing=1,
fixed_width=-1,
min_width=-1,... | 035fc4ebee4cc8cefe163c94ddaf4569da2facfb | 3,610,604 |
import contextlib
import sqlite3
def query_summary(fname):
"""Query and opsim database for visits
Args:
- fname :: the name of the sqlite3 database file
Returns:
a named tuple with the summary and proposal tables
"""
table_contents = []
with contextlib.closing(sqlite3.connect(f... | d2ae294e35ce6ccc5815a9a812a5e24d9ed7f0ac | 3,610,605 |
def prepare_pcoa(pcoa, number_of_features):
"""Selects top N biplot features by magnitude (coped from q2-emperor).
Parameters
----------
pcoa : skbio.stats.ordination.OrdinationResults
number_of_features : int
Returns
-------
skbio.stats.ordination.OrdinationResults
"""
feats =... | c5403b554ae40a1740733a2b6d9e6a61d8794b2b | 3,610,607 |
def _jupyter_bundlerextension_paths():
"""
Entrypoint for Jupyter Notebook Bundler
Shows up in the 'Download' menu on Jupyter Classic Notebook
"""
return [{
'name': 'chrome_pdf_export',
'label': 'PDF via Chrome (.pdf)',
'module_name': 'nbpdfexport.bundler',
'group': ... | 1d948a5eed6f4240e760c52bec776c3fbf291f14 | 3,610,608 |
def DecodeVigenereLongueurCle(message, mot=3):
"""
Cette fonction determine la longueur de la clé, elle
repère les groupes de trois lettres qui se répète dans le message codé
et suppose qu'il y a une très forte probabilité qu'un même groupe de trois
lettres soit codé avec les mêmes trois lettres du ... | 3ee2f974e82e9cb30d049bfd4550305605950815 | 3,610,609 |
def median(data_list):
"""
Finds the median in a list of numbers.
:type data_list list
"""
data_list = list(map(float, data_list))
length = len(data_list)
data_list.sort()
# Test whether the length is odd
if length & 1:
# If is is, get the index simply by dividing it in half... | c41a1336d17e5e991101bd91c9c56cb59624dc82 | 3,610,610 |
import functools
def on_package_attributes(**attr_dict):
"""Decorator: executes instance function only if object has attr valuses.
Executes the decorated method only if at the moment of calling the
instance has attributes that are equal to certain values.
Args:
attr_dict (dict): dictionary m... | 9c3f4be4bbe02d0d70b97ae5d9437480262b5e79 | 3,610,611 |
def filelineno():
"""
Return the line number in the current file. Before the first line
has been read, returns 0. After the last line of the last file has
been read, returns the line number of that line within the file.
"""
if not _state:
raise RuntimeError("no active input()")
retur... | d5c86e0c2232b35fa5b714226f832449b60c5b63 | 3,610,612 |
def create_dual_point_kernel(size, distance_apart, padding=0):
"""Generates a square float image with two, single-pixel point sources.
The top source has double the intensity of the bottom source. The sources
are distributed along the vertical center and are spaced a set distance apart.
:param size... | ebbfdc6d3843ba3f4b05f2c616ba1d123dd86a55 | 3,610,613 |
def auc(actual, posterior):
"""
auc
"""
r = tied_rank(posterior)
num_positive = len([0 for x in actual if x == 1])
num_negative = len(actual)-num_positive
sum_positive = sum([r[i] for i in range(len(r)) if actual[i] == 1])
auc = ((sum_positive - num_positive * (num_positive + 1) / 2.0) /... | cc3822ede98c25e89cabd9d25fc2218ff42b4e4e | 3,610,614 |
from django.test import SimpleTestCase as TestCase
from django.test import TestCase
def is_django_unittest(item):
"""Returns True if the item is a Django test case, otherwise False"""
try:
except ImportError:
if sys.version_info < (3, 0):
return (hasattr(item.obj, 'im_class') and
... | 13702023578bf029ea9d130114b13dff26592f3e | 3,610,615 |
def parametrized(f):
"""Is this function or object decorated with @parametrize or @matrix?"""
return Mark.marked(f, PARAMETRIZED) or Mark.marked(f, MATRIX) or Mark.marked(f, DEFAULTS) | b4cf00ab71a365a477678a11a276ece8248e5fcb | 3,610,616 |
import asyncio
def analyze_body(sdf, address=("127.0.0.1", 11346)):
"""
Single body analyzer. Opens a new connection, analyzes the
body, and returns the result. If you already have a manager
running doing other things, create an instance of `BodyAnalyzer`
instead.
:param sdf: SDF object consi... | 2b75241c6aedd0bac524eadbcd3968caf57f021a | 3,610,617 |
def cmd_trade_info(strategy: Strategy, strategy_trader: StrategyTrader, data: dict) -> dict:
"""
Get trade info according data on given strategy_trader.
@note If trade-id is -1 assume the last trade.
"""
results = {
'messages': [],
'error': False
}
trade_id = -1
... | eb89294444f28a80eff8f1527a048341d17bc88c | 3,610,618 |
def drift_confidence(df_resample, out_path, fps, pca=1, save_fig=0):
"""
Args:
df_resample:
out_path:
fps:
pca:
save_fig:
Returns:
"""
if pca:
flow_key = 'diffflow_pca'
acc_key = 'acc_pca'
else:
flow_key = 'diff_flowx'
ac... | e3dce48e9747c4f22ee71f4029faa16cd6864c75 | 3,610,619 |
def power_factor(s: np.ndarray) -> np.ndarray:
"""Given a numpy array of complex values, compute power factor.
If the power factor is lagging, a positive value will be returned.
If the power factor is leading, a negative value will be returned.
Reference:
Power System Analysis and Design, 5th Edit... | 0cc50fdeaa485e1194c2ab897322963a9b1a39a1 | 3,610,620 |
def pad_factor(input_image, spatial_dims, factor):
"""Pad `input_image` (N,C,H,W) such that H and W are divisible by `factor`."""
if isinstance(factor, int) is True:
factor_H = factor
factor_W = factor_H
else:
factor_H, factor_W = factor
H, W = spatial_dims[0], spatial_dims[1]
... | 7b07bf7fcca5f05ecdd47420ac2493b7aed37277 | 3,610,621 |
def zeropad(data, m=2):
"""Pad with zeros to make an array with an even multiple of m voxels in all dimensions
"""
if data.ndim < 2 or data.ndim > 3:
raise RuntimeError('Unsupported number of dimensions {}. We only supports 2 or 3D arrays.'.format(data.ndim))
if data.ndim == 2:
... | 43cf2e5974b4ad0b64e998d33bd9faf724d51300 | 3,610,622 |
def h2fk5(rh, dh, drh, ddh, pxh, rvh):
"""
Wrapper for ERFA function ``eraH2fk5``.
Parameters
----------
rh : double array
dh : double array
drh : double array
ddh : double array
pxh : double array
rvh : double array
Returns
-------
r5 : double array
d5 : double... | 108e3f241bce70ed5dc6a6d6c36ca44b13d352d1 | 3,610,624 |
def Connect(*args, **kwargs):
"""Factory function for connection.Connection."""
return connection.Connection(*args, **kwargs) | 9b65dcd4fb73af1e52fa4dffa7b91cfc58532730 | 3,610,625 |
def solve_lp_puzzle(lp, boxsize):
"""Solve a linear program Sudoku and return puzzle dictionary."""
lp.simplex()
for col in lp.cols:
col.kind = int
lp.integer()
return lp_to_dict(lp, boxsize) | b4ceee41dddbb74adc6be96ae31b762cd46ce582 | 3,610,627 |
def show_error_info(title, message, unknown_error=False, netflix_error=False):
"""Show a dialog that displays the error message"""
prefix = (30104, 30102, 30101)[unknown_error + netflix_error]
return xbmcgui.Dialog().ok(title, (common.get_local_string(prefix) + '\r\n' +
... | a0e2f5971debf94d0cbc6032126a9966ad3dd840 | 3,610,628 |
def is_token_expired(token):
"""Checks if given token is valid"""
try:
decoding = jwt.decode(token, config['jwt_secret'], config['jwt_algorithm'])
return False
except jwt.ExpiredSignatureError:
return True | 30bfc86d5b4d516b0257fa58755c51264dd2ec24 | 3,610,629 |
import re
import csv
def _getIdsFromQuery(queryString, syn, downloadLocation):
"""Helper function that extracts the ids out of returned query."""
if re.search('from syn\\d', queryString.lower()):
tbl = syn.tableQuery(queryString, downloadLocation=downloadLocation)
check_for_id_col = filter(l... | 3f38f02c01c87932317d1241645dca6fac3b484e | 3,610,630 |
def get_sshkey(sshkey):
"""
Get start ip for ip range
CLI Example:
.. code-block:: bash
salt 'maas-node' maasng.get_sshkey sshkey
salt-call maasng.get_sshkey sshkey
"""
try:
return list_sshkeys()[sshkey]
except KeyError:
return {"error": "SSH key not found ... | 774edde0d7f3e63b81d5365b7226599e979e1de7 | 3,610,631 |
from pathlib import Path
from typing import Dict
def process_image(in_img_path: Path, out_img_dir: Path) -> Dict[Path, Path]:
""" Extract EXIF data from image and return path mapping """
with open(in_img_path, "rb") as image_file_stream:
image = Image(image_file_stream)
if hasattr(image, "date... | 454f8a5ffec9ea06435bfd7bc9bbfcbc0de82687 | 3,610,632 |
def get_vars_maybe_avg(var_names, ema, **kwargs):
"""utility for retrieving polyak averaged params."""
vars_tf = []
for vn in var_names:
vars_tf.append(get_var_maybe_avg(vn, ema, **kwargs))
return vars_tf | 0e35821d8883031dceca0e05d31b792c92adbd78 | 3,610,633 |
from typing import List
from typing import Tuple
def open_files(
file_names: List[str], mode: str = "readonly"
) -> Tuple[List[fits.HDUList], List[np.ndarray]]:
"""Gets the HDULS and data handles for all the files in file_names.
This is a convience function to opening multiple FITS files using
m... | c26a9f9d6348c6279851aeb4993f79682c7c0838 | 3,610,636 |
def multi_to_single(y, combinations):
"""Convert multilabel indices to singlelabel strings."""
single = []
for y_i in y:
y_i_str = ", ".join([str(i) for i in y_i])
single.append(combinations.index(y_i_str))
return single | 7e8839173b047cb0bb89d143ce2b30b928630f2d | 3,610,637 |
def _parse_taxa_report(local_path, **kwargs):
"""Return a dict of taxa_name to read_counts."""
out, abundance_sum = {}, 0
with open(local_path) as taxa_file:
for line_num, line in enumerate(taxa_file):
line = line.strip()
tkns = line.split('\t')
if not line or len... | b3b18010820dbc409b66c8c1d5636430c052382d | 3,610,640 |
def build_conservation_status_message(data: list[str]) -> str:
"""
Builds a string describing the conservation status of the species.
:param data: Data containing conservation status information
:return: Description of the conservation status (or empty if no data)
"""
if data:
return CON... | 7457234d64300baa42047067d81799881a406ff8 | 3,610,641 |
def get_col_reduced_right(A, symb, T = None, return_internals = False):
"""
Takes a polynomial matrix A(s) and returns a unimod Transformation T(s)
such that A(s)*T(s) (i.e. right multiplication) is col_reduced.
Approach is taken from appendix of the PHD-Thesis of S. O. Lindert (2009)
:args:
... | 77a499f272848afedd6a6869fa6166c993e4e9ae | 3,610,642 |
def ivarName(value, position):
"""A name of a class."""
if not value[0] == '_' or not value[1].islower():
return Error(
'BadInstanceVariableName', 'Instance variable names start with _ and not be capitalized', position, LINES)
return None | 1ba3d34a949aaf6d2bee235fe8885fac827f0f9a | 3,610,643 |
def verilog_value_to_int(verilog_value):
""" Convert VerilogValue model to width, value, value_format """
width = None
if verilog_value.plain_decimal:
return width, int(verilog_value.plain_decimal), ValueFormat.PLAIN
if verilog_value.width:
width = int(verilog_value.width)
if veri... | e8d1c938cea56b8cd3277f445dd5d6eb85de60eb | 3,610,644 |
import random
def create_quiz_form(quiz):
"""Create quiz form with all its question choices,
shuffle the choices for quiz page"""
form = QuizForm()
for i in range(10):
form.questions[i].answers.choices = [
quiz.questions[i].correct_answer,
quiz.questions[i].wrong_... | 56c73d48532df049aec2f2c78d0ae35c89351cd7 | 3,610,645 |
from typing import Tuple
def drop_zeros_ctg(fhr: np.array, uc: np.array, time: np.array) -> Tuple[np.array, np.array, np.array]:
"""
Removes all missingvalues, encoded as zeros
Args:
uc, fhr signals: (np.arrays) 1D signals
time: (np.array) 1D time signal
Output: Tuple(n... | 19f0d90a5cf08057b08186754c262afe9d16d294 | 3,610,646 |
def report_and_reset_timings():
"""Returns the pass timings report and resets the LLVM internal timers.
Pass timers are enabled by ``set_time_passes()``. If the timers are not
enabled, this function will return an empty string.
Returns
-------
res : str
LLVM generated timing report.
... | 76fabaca3e99823182d1c6623e7c01126966c856 | 3,610,647 |
from typing import Union
from typing import Iterable
def transform_coords(x: Union[DataArray, Dataset],
targets: Union[str, Iterable[str]],
graph: GraphDict,
*,
rename_dims: bool = True,
keep_aliases: bool = True,... | b8777248c7ff4313f239a91a5ec5c6001ba0835c | 3,610,648 |
def Answer_f(text):
"""
:param text: The "text" of this Answer
"""
return '\\begin{block}{Answer}\n' + text + '\n\\end{block}\n' | 2de98b286d31e31f2b934760f715af1ecda83daa | 3,610,649 |
def gather_states(ii):
"""
Return the current state (position/probability/bias) of walkers in a given window.
Parameters
----------
ii : integer
The index of the umbrella to get the state of.
Returns
-------
state : list
The state of window ii.
"""
retu... | 46b2f3db3ff71fbca2f1b54b39f627f32e3a5ff5 | 3,610,650 |
def word_embeddings_rbo(list1, list2, p, index2word, word2vec, norm):
"""Complete RBO analysis (lower bound, residual, point estimate).
``list`` arguments should be already correctly sorted iterables and each
item should either be an atomic value or a set of values tied for that
rank. ``p`` is the proba... | 5fc29129d4722dc7381c6edbc6df465d993f0528 | 3,610,651 |
def drop_na_inputs(*, input_data: pd.DataFrame) -> pd.DataFrame:
"""
Check model inputs for na values and filter them
based on the ones the model knows how to handle.
"""
validated_data = input_data.copy()
new_vars_with_na = [
var
for var in config.model_config.inputs
if... | 0b757add023c34c8f081d58e56f01da59dc87ca4 | 3,610,652 |
import re
import json
def geojsonfeature(source, params=''):
"""
:params: A string with the following optional tokens:
"properties:field:srid"
"""
parse = re.search(r'(?P<properties>((\w+)(,\w+)*)?)(:(?P<field>(\w+)?))?(:(?P<srid>(\d+)?))?', params)
if parse:
parse = parse.gro... | 4fd0e2e8d9d461ff2775dd21ce39fceca1905118 | 3,610,653 |
def expected_return_time(M, backward=False):
"""Find the expected returning time.
Parameters
----------
M: :class:`~numpy.ndarray` (dimension n x n, where n is the cell number)
The transition matrix.
backward: bool (default False)
Whether the backward transition will... | 2a0963e20c09f92f7e1ae2177d4277f589052620 | 3,610,654 |
def att_moment_metric(mass, att_moment):
"""
This function calculates the metric for the attitude moment. It does not consider moments of inertia for the
satellite, nor passive sources of moment
:param mass:
:param att_moment:
:return:
"""
return np.float64(1.25 * (att_moment / mass)).cl... | 87ac22c1ddd58aa257fa4485fbd48189599215ce | 3,610,655 |
from typing import Sequence
from typing import Dict
def get_largest_area(rect: Rect, points: Sequence[Point]) -> int:
"""Find the largest bounded area around all the points.
This basically is creating a voronai using the manhattan distance, and throwing out any ties.
If any of the cells are on the edge o... | 0f6b3e0085b963435e2da40a399d12d5704a9acc | 3,610,656 |
import json
def body_part_to_headers_and_data(part):
"""
convert part (of multi-part body) to headers dict and content. de-serializes json if content-type is
application/json.
:param part: BodyPart decoded by MultipartDecoder
:return: tuple pair of headers dict and content
"""
if b'applic... | edd95f6dba9f4157c6a51b2dd6a6c4fb8a34e9db | 3,610,657 |
def flip_marker_states(aut):
"""
Return an automaton that has all marker states flipped
@param aut: Input automaton
@type aut: L{Automaton}
@return: Flipped automaton of L{aut}
@rtype: L{Automaton}
"""
new_aut = aut.copy()
for state in new_aut.get_states():
flip_single_ma... | e7fd6e539cb1dc3a35b41779fd4a6823a454a806 | 3,610,658 |
def find_all_presented_sfs(stim_df, ecc_step=1, ecc_range=(1, 12), size=1080,
max_visual_angle=24, stimulus_mask=None):
"""Find average spatial frequency presented in eccentricity bands for each stimulus.
Only works on square images.
Returns a dataframe with the average spatial ... | 67398f4fdfb01178acd38f676846943ef3c155dc | 3,610,659 |
def encapsulateTable(string_table,column_labels, caption,ttype=None):
"""Uses the output of makeTables to render a complete latex table"""
if ttype in ("kolmDiff3","kolmDiff3_","kolmSamp_","kolmSamp","textCorr","allFloat"):
header="\\begin{table*}[h!]\n\\begin{center}\n\\begin{tabular}{| l |"+" c |"*(st... | 63af2164b79ca73c3362cd535c4a98855495e18f | 3,610,660 |
from twistdb.sampletrack import Sample, PlateType
def bulk_to_temp_transform( db, bulk_plate_barcode, pca_plates ):
"""
returns a transform for consumption by echo_csv
"""
pd = primer_dict( db, pca_plates )
rows = []
primer_ct = defaultdict(int)
layout = db.query(PlateType).get('SPTT_000... | 331799b500b4d342a8bb58b6744210cae1485614 | 3,610,662 |
def gaussian1d_variant1(x, *p):
"""
Create a normalised gaussian (Area == 1) from mean and variance
:param x: [numpy array] x axis data (array/list)
:param p: [Tuple] (mean , variance)
Area of gaussian is 1 --> A = 1/(c*sqrt(2pi))
Returns a Gaussian array one value for each x valu... | 876b8b62ce4a6d632efc94539d0dfc54900b1e29 | 3,610,663 |
import urllib
import traceback
def evtimer(request, ettype, config_id, query=''):
"""
[メソッド概要]
タイマー管理するイベントを管理する
[引数]
ettype : イベント管理種別('cron' or 'timer')
config_id : イベント管理するシステム設定ID
"""
logger.logic_log('LOSI00001', 'ettype=%s, config_id=%s' % (ettype, config_id))
re... | 595f7508cbcfd2434636e78b3a9d71de0603761c | 3,610,664 |
def dc_node(request, hostname, data=None):
"""
Show (:http:get:`GET </dc/(dc)/node/(hostname)>`),
create (:http:post:`POST </dc/(dc)/node/(hostname)>`),
change (:http:put:`PUT </dc/(dc)/node/(hostname)>`) or
remove (:http:delete:`DELETE </dc/(dc)/node/(hostname)>`)
a compute node (hostname) asso... | 0cd7725319ea944c0a3da99c62610a669ee60550 | 3,610,665 |
from datetime import datetime
def parseDateTag(tag: bs4.element.Tag) -> str:
"""Parse date tag.
:param tag: html table data element
:return: date string
"""
date = datetime.strptime(tag.text, '%m/%d/%Y').strftime(DATE_FORMAT)
return date | 9be00eafe72b251e19ca480f1eb058da03ea7b1c | 3,610,667 |
def get_utm_zone(lon):
""" Calculate UTM zone.
Arguments:
lon: float
Longitude, in degrees. West: negative, East: positive.
Returns:
zone: int
UTM zone number.
"""
zone = int(1+(lon+180.0)/6.0)
return zone | cf8c0d596f146417ebf0d3a18cd0b70e825388aa | 3,610,668 |
def create_eyelid_follicle_system(driver_object="", selected_vertices=(), surface_mesh_name=""):
"""
creates follicle drivens that drives the joints that are driven by the driver controllers.
This is a complicated system that requires these steps:
1. select vertices.
2. get the closest UV from the s... | a580d4aa955511b05d33fabdefd664f5111b83c5 | 3,610,669 |
from typing import List
def create_chassis(world: b2World, vertices: List[b2Vec2], densities: List[float]) -> b2Body:
"""
Creates a chassis to be the body of the car.
"""
if len(vertices) != len(densities):
raise Exception('vertices and densities must be same length')
# Create body defini... | bd8ac60df9c9e217923099c3f8d7c2476f3360eb | 3,610,670 |
def napalm_cli(task, commands, hostname=None, username=None, password=None,
driver=None, timeout=60, optional_args=None):
"""
Run commands on remote devices using napalm
Arguments:
commands (list): list of commands to execute on the device
hostname (string, optional): default... | 00abff61eddfac22d3f867252c403ca70ffb43cf | 3,610,671 |
import torch
def _create_zero_states(model: RecurrentLM) -> ActivationDict:
"""Zero-initialized states if no init state is provided.
Returns
-------
init_states : ActivationTensors
Dictionary mapping (layer, name) tuple to zero-tensor.
"""
init_states: ActivationDict = {
a_nam... | 8ece9f249099b2de678e2f173f1428f8b635bb0d | 3,610,672 |
def append_iqa_scores(df):
"""Load image quality assessment scores and append to a dataframe of observation records"""
# Sort user IDs by number of observations (in the current dataset) per user
scores = load_iqa_scores()
first_result = list(scores.values())[0]
for key in first_result.keys():
... | 2f04bd2e2c8b440fd5159cddff9b1205eb4d974b | 3,610,673 |
from typing import List
def _setup_entities(hass, device_ids: List):
"""Set up Tuya Climate."""
device_manager = hass.data[DOMAIN][TUYA_DEVICE_MANAGER]
entities = []
for device_id in device_ids:
device = device_manager.deviceMap[device_id]
if device is None:
continue
... | bee211a1b67690ad064b05189b73d05e8a9841db | 3,610,674 |
import collections
def _iterateOverDicts(ob, func):
"""
This function iterates a function over a nested dict/list
see https://stackoverflow.com/questions/32935232/python-apply-function-to-values-in-nested-dictionary
"""
assert type(ob) == dict, '**** _iterateOverDicts requires a dict input'
fo... | 04aacf2513dd0a702379ec3506943255a9dce137 | 3,610,675 |
def mask_rcnn_functional(config: dict) -> tf.keras.Model:
"""
Construct a model in functional API
Args:
config: General MaskRCNN config, dict
Returns: tf.keras.Model:
"""
# Prevent creating keras names with index increment.
# It is important for weights setting from training to infe... | 1c73e43b3980e957c5a774d87da85997760a9e69 | 3,610,676 |
def ast_from_input(input, mode, transformer, parser):
"""converts a source input into an AST
- input : the source to be converted
- mode : 'exec', 'eval' or 'single'
- transformer : the transfomer instance to use to convert
the nested tuples into the AST
XXX: transformer co... | 23c8884736559f3b6334e288af2e6cc751b09045 | 3,610,677 |
def CvSepFilter_init_gaussian_kernel(*args):
"""
init_gaussian_kernel(CvMat kernel, double sigma=-1)
CvSepFilter_init_gaussian_kernel(CvMat kernel)
"""
return _cv.CvSepFilter_init_gaussian_kernel(*args) | e45f3cd87f17e3a2dfecbcf92bed7e7ff512ad7b | 3,610,678 |
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