content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def as_singleton_instance(cls):
"""
This is where the magic happens. This defines a
class decorator that returns an *instance* of a class
with the name "_<original_name>__class" that has
the same member functions, etc as the cls argument.
The type of the returned value is not accessible to the
... | 3fc00dbfb24cd87401214806ddd93ff2ba15be50 | 3,623,200 |
def set_size(width, fraction=1, subplots=(1, 1)):
""" Set figure dimensions to avoid scaling in LaTeX.
Parameters
----------
width: float or string
Document width in points, or string of predined document type
fraction: float, optional
Fraction of the width which you wish th... | 2cbc82e17baceffcb81249d5dde99b6e10c4afa9 | 3,623,201 |
import argparse
def parse_options():
"""Parses command line options and returns an option dictionary."""
options = {}
parser = argparse.ArgumentParser(
description='Recursively apply Review Board reviews'
' and GitHub pull requests.')
parser.add_argument('-d', '--dry-run'... | 6d35277fe508ef43e4631904f5b07d2cc5b947fd | 3,623,202 |
def create_keras_model():
"""
create model
"""
model = Sequential()
model.add(Conv1D(500,
input_shape=(1280, 1),
kernel_size=128,
strides=128,
activation='relu',
padding='same'))
model.add(De... | 043b3db24bb4b24932d1fad50acc72f9354a154d | 3,623,203 |
def ndgrid(*args,**kwargs):
"""
Same as calling meshgrid with indexing='ij' (see meshgrid for
documentation).
"""
kwargs['indexing'] = 'ij'
return meshgrid(*args,**kwargs) | 342530125f045d36a7c49baff72904ed90877452 | 3,623,204 |
def _wass_gen_loss_fn(gen_images, discriminator: tf.keras.Model,
generator: tf.keras.Model):
"""Calculate the Wasserstein (generator) loss."""
disc_gen_output = discriminator(
gen_images, training=TRAINING_KWARG_FOR_SECOND_MODEL)
gen_loss = tf.reduce_mean(-disc_gen_output)
# Now add... | caaacb970476a38364ffc9e1b82566c6cda1481a | 3,623,205 |
from typing import List
def _get_create_repo(request) -> List[str]:
"""
Retrieves the list of all GIT repositories to be created.
Args:
request: The pytest requests object from which to retrieve the marks.
Returns: The list of GIT repositories to be created.
"""
names = request.confi... | 4ac8cefefb75af3bb86fcc16f5c8b79953b136bf | 3,623,206 |
def read_in_posterior(date):
"""
read in samples from posterior from inference
"""
df = pd.read_hdf("results/soc_mob_posterior"+date+".h5", key='samples')
return df | f5754628f17de8629e3d197a73645e6fa541722b | 3,623,207 |
def wrap_dtype(func):
""" Check the dtype of the `X` array.
Convert dtype of X to np.float64 before to pass to cython function and
convert to specified dtype at the end.
"""
@wraps(func)
def check_dtype(X, *args, dtype=None, **kwargs):
X, dtype = _check_dtype(X, dtype)
if dtyp... | 2ace06e7f6447e71d3b7f586fde1cf853400d4d1 | 3,623,208 |
def dirdiff(HEADING,Nmin,loffset):
"""
Function to calculate the maximum difference of a [0, 360) direction during specified time averging intervals
:param HEADING: time series of a direction in degrees [0, 360)
:param Nmin: integer specifying the number of minutes to average
... | e552018dbdfc0dd83f9ac5e25116a9144133d9fc | 3,623,209 |
def update_outputs(region, resource_type, name, outputs):
""" update outputs with appropriate results """
element = {
"op": "remove",
"path": "/%s/%s" % (resource_type, name)
}
outputs[region].append(element)
return outputs | 97858e5d183af9974bd31be180dfe05c26048ab3 | 3,623,210 |
def generate_inputs_1d_spherical():
"""Return inputs that parser will expect for the 1D case with spherical averaging."""
inputs = {
'parent_folder':
orm.FolderData().store(),
'parameters':
orm.Dict(
dict={
'INPUTPP': {
'plot_num':... | 633fb78031eaeaf0067479d5aa600ed8fd462f90 | 3,623,211 |
def _check_electrification_scenarios_for_download(es):
"""Checks the electrification scenarios input to :py:func:`download_demand_data`
and :py:func:`download_flexibility_data`.
:param set/list es: The input electrification scenarios that will be checked. Can
be any of: *'Reference'*, *'Medium'*, *... | ccd1ec8f0b1349267ba1334f7744056bc43e32ec | 3,623,212 |
from typing import Sequence
from typing import List
def bubble_sort(nums: Sequence) -> List:
"""Sort a list in non-descending order using bubble sort.
Return a new list, leaving the original `nums` intact.
"""
# Bubble sort compares each element with the next element, and if the previous one
... | 0cc60f00fd7fb55098e34745e3bad76be7fcdf5f | 3,623,213 |
def image_to_byte_array(image: Image):
"""
Converts an image into a byte array
"""
imgByteArr = BytesIO()
image.save(imgByteArr, format=image.format if image.format else 'JPEG')
imgByteArr = imgByteArr.getvalue()
return imgByteArr | 82e6413978ee07d1d2cd434e144c1f1732133dab | 3,623,214 |
import logging
def crawling_tweet():
"""
Twitter APIを利用して対象ユーザーのツイートを収集する
収集したツイートはGoogle Cloud Text to Speech APIへ連携し、
音声読み上げデータとしてmp3に変換し、保存する
:return:
"""
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tw... | 008bf8a4c08cdce18c1fbea0dc053b8e5a974025 | 3,623,215 |
from typing import Optional
def is_subject_condition_dataframe(
data: SubjectConditionDataFrame, raise_exception: Optional[bool] = True
) -> Optional[bool]:
"""Check whether dataframe is a :obj:`~biopsykit.utils.datatype_helper.SubjectConditionDataFrame`.
Parameters
----------
data : :class:`~pan... | 993065496e7fff951986fd2141af7a222060433b | 3,623,216 |
def _update_earned_request(player_id, achievement_id, current_value, max_value):
"""
Create the DynamoDB update_item parameter request to update earned attribute
"""
now = ddb.timestamp()
return {
'Key': {
'player_id': player_id,
'achievement_id': achievement_id
... | f9c1cd62f537bcd6841ee33d59645fba976c82f9 | 3,623,217 |
def mosaic(*rasters):
"""
Mosaic rasters covering different areas together into one file.
Parts of the rasters may overlap each other, in which case we use the value
from the last listed raster (the "last" overlap rule).
"""
# align all rasters, ie resampling to the same dimensions as the first... | fd43edbafc4173129614dcc8ced6aa01390f0d3a | 3,623,218 |
def typing_loop(options, add, atom_type_dict):
"""
types atoms in ambiguous cases, options should be ordered correctly
"""
ty = None
for option in options:
try:
ty = atom_type_dict[add + option]
break
except KeyError:
continue
if ty !=... | 5198375c775cdbf1819998dca4d7c05287ba273d | 3,623,219 |
def enable_func_trace(*args):
"""
enable_func_trace(enable=True) -> bool
"""
return _ida_dbg.enable_func_trace(*args) | f2e9944f9651c56ab19fa1b444395d5ccf0df036 | 3,623,220 |
def get_exp_or_package_from_repo_name(repo_name):
"""Helper function to retrieve experiment or InternalPackage DB object based on repository name
Useful for tasks that do not have a session or other information"""
git_repo = GitRepository.objects.filter(name=repo_name)
if git_repo:
git_repo = gi... | 32403e7b223e55583959e0cd0be556e476be591a | 3,623,221 |
import re
def text_to_pronounceable_text(text,
symbols_for_base_idx=vowels_and_consonants,
captured_alphabet=alpha_numerics,
case_sensitive=False,
max_word_length=30,
... | d7f60bfc784975b166793edc1e8baee09036c5db | 3,623,222 |
def is_shuffle(s1, s2, s3):
"""
Runtime: O(n)
"""
if len(s3) != len(s1) + len(s2):
return False
i1 = i2 = i3 = 0
while i1 < len(s1) and i2 < len(s2):
c = s3[i3]
if s1[i1] == c:
i1 += 1
elif s2[i2] == c:
i2 += 1
else:
return False
i3 += 1
return True | 3b88d117efde1d6b8ea8e0266a9c3ac7ae039458 | 3,623,223 |
def header_is_sorted_by_coordinate(header):
"""Return True if bam header indicates that this file is sorted by coordinate.
"""
return 'HD' in header and 'SO' in header['HD'] and header['HD']['SO'].lower() == 'coordinate' | b656770806818abe742be32bc14c31a8a8e3e535 | 3,623,224 |
def delete(
name,
endpoint="incidents",
id=None,
api_url=None,
page_id=None,
api_key=None,
api_version=None,
):
"""
Remove an entry from an endpoint.
endpoint: incidents
Request a specific endpoint.
page_id
Page ID. Can also be specified in the config file.
... | 900126d08761793a4f97c1b4acbda224218103da | 3,623,225 |
import re
def name_conversion(caffe_layer_name):
""" Convert a caffe parameter name to a tensorflow parameter name as
defined in the above model """
# beginning & end mapping
NAME_MAP = {'bn_conv1/beta': 'conv0/bn/beta',
'bn_conv1/gamma': 'conv0/bn/gamma',
'bn_conv1... | c9025c01eeb8d319a4e76db167f65bac99adf396 | 3,623,226 |
def square(x, name=None):
"""Computes square of x element-wise.
I.e., \\(y = x * x = x^2\\).
Args:
x: An `Output` or `SparseTensor`. Must be one of the following types:
`half`, `float32`, `float64`, `int32`, `int64`, `complex64`, `complex128`.
name: A name for the operation (optional).
Returns:... | 666e4b272b454561d2474229ed12ff94b8a629ef | 3,623,227 |
def manually_adjust_data(pnid, sc_entry):
"""Returns a modified version of sc_entry to fix some issues manually.
Args:
pnid: string, ProteinNet ID
sc_entry: dictionary containing "seq", "ang", "crd" data
Returns:
If sc_entry must be modified, then it is corrected and returned.
... | 90d801a5549b87e15e0c8e45f11de92ab2ad6cea | 3,623,228 |
def get_network_container_hostnames(name):
"""Returns a list of every container hostname in the specified network."""
for network in get_networks():
if network["Name"] == name:
return [get_container_hostname(container) for container in network["Containers"]] | f7b1f176f2c0e5a879930c2189f36f933075664e | 3,623,229 |
def spearmanr_no_pval_vec(X, Y):
"""Returns spearmans correlation, vectorized version
Parameters
----------
X : ndarray (n_samples, n_observations)
Y : ndarray (n_samples, 1)
Returns
-------
R : array (n_observations,)
spearmans correlation between each column of X and Y
""... | 9a4aeae514d80963ba1d12a574c3aebb8bdc30d4 | 3,623,230 |
import json
async def surprise_communities(request):
"""
---
description: This end-point allows to compute surprise_communities Community Discovery algorithm to a network dataset.
tags:
- surprise_communities
produces:
- application/json
responses:
... | 785c2b6e14516b0f5ddd140310fe75fb4759900f | 3,623,231 |
def set_case(words, method="lower", testing=False):
"""
Perform capitalization on some or all of the strings in `words`.
Default method is "lower".
Args:
words (list): word list generated by `choose_words()` or
`find_acrostic()`.
method (str): one of {"alter... | 92465688c8a7e2e85d2631b8acd8496fab5d0c33 | 3,623,232 |
def button(channel, red, blue):
"""Returns the button for a Combo PWM Mode command."""
return (pf_rc.CHANNEL[channel], PWM_STEP[red], PWM_STEP[blue]) | 821ce8c5684bb7634281b95960607537de15b4a4 | 3,623,233 |
def mini_xception(input_shape, num_classes, regularization = l2(0.01)):
"""
This function architects the mini_xception model network. This is the best
performing model in the facial emotion analysis
input_shape: input shape of the image
num_classes: number of classes in the output
return: Ret... | a7003277cc25e4029cfcf0dea580833f68916af5 | 3,623,234 |
def calc_node_size(self):
"""
calculate minimum node size.
"""
title_width = self._text_item.boundingRect().width()
port_names_width = 0.0
port_height = 0.0
if self._input_items:
input_widths = []
for port, text in self._input_items.items():
input_width = port.bo... | 9d6b8a37ef13a9698d6523baeacc2da0686c9c4d | 3,623,235 |
def page_osr_vieworder():
"""Return everything."""
query = f'SELECT DISTINCT orderdate FROM orderlog'
g.cur.execute(query)
rows = g.cur.fetchall()
return render_template('vieworder.html', dates=rows) | a28ce95ae9930d1da19cd1af817b6376d3dc4f83 | 3,623,236 |
def eval_metric_fns():
"""Returns a dict from name to metric functions.
This can be customized as follows. Care must be taken when handling padded
lists. (only takes labels >= 0.
def _auc(labels, predictions, features):
is_label_valid = tf_reshape(tf.greater_equal(labels, 0.), [-1, 1])
clean_l... | cfa13913bd7132fc558b0e3b4ab71fd8dc9328c7 | 3,623,237 |
from typing import List
from typing import Dict
from typing import Optional
from typing import Union
def combine_score_weights(
weights: List[Dict[str, float]],
overrides: Dict[str, Optional[Union[float, int]]] = SimpleFrozenDict(),
) -> Dict[str, float]:
"""Combine and normalize score weights defined by ... | f75b444a013087350412b1bb65780b42496632af | 3,623,238 |
def calc_ideal_vel(traj_ref, dt):
"""
Parameters
------------
traj_ref : numpy.ndarray, shape (2, N)
these points should follow subseqently
dt : float
sampling time of system
"""
# end point and start point
diff = traj_ref[:, -1] - traj_ref[:, 0]
distance = np.sqrt(n... | 45c4ae252c9689d57733ffc4fb0b976999e2b583 | 3,623,239 |
import requests
def getImport(accessToken: str, groupId: str, importId: str) -> dict:
"""
:param accessToken
:param groupId
:param importId
"""
url = 'https://api.powerbi.com/v1.0/myorg/groups/{groupId}/imports/{importId}'.format(
groupId=groupId,
importId=importId,
)
... | c3609f555511d2d9c04733d002a2c2f3ed26cbd2 | 3,623,240 |
def make_rgba(grid2D, levels, colorlist, mask=None,
mercator=False):
"""
Make an rgba (red, green, blue, alpha) grid out of raw data values and
provide extent and limits needed to save as an image file
Args:
grid2D: Mapio Grid2D object of result to mape
levels (list): list... | f337ac86909d0941d513648f309602e76dd56374 | 3,623,241 |
import binascii
def AES_encryption(enc,server=False):
"""
Performs AES encryption using the globablly declared AES key.
"""
enc = str(enc)
enc = enc + ((16 - len(enc) % 16) * ' ')
iv = enc[:16]
aes_cipher = None
if server:
aes_cipher = AES.new(login_server_key, AES.MODE_CBC, iv... | 00f89db237a746a6a72cc7f168d14d616aded659 | 3,623,242 |
def named_cache_page(cache_timeout):
"""
Decorator for views that tries getting the page from the cache and
populates the cache if the page isn't in the cache yet.
The cache is keyed by view name and arguments.
"""
def wrapper(func):
def foo(*args, **kwargs):
key = func.__na... | 1c946370640bd76c3a4a3d3a6a3c0fe5a76d0215 | 3,623,243 |
def get_product(location, product_id, quantity):
""" Used by the movement route to get a product from a location. """
product_array = []
db = get_db()
b_id = session.get("user_id")
if location == "product_factory":
# Get product from product table, deduct the quantity
ogquantity = d... | cda91efeb3bbc280a609bc560e4a9b9867d6d1ed | 3,623,244 |
def calc_psi_r(qr, r1, r2, r3, r4):
"""
radial geodesic angle
Parameters:
qr (float)
r1 (float): radial root
r2 (float): radial root
r3 (float): radial root
r4 (float): radial root
Returns:
psi_r (float)
"""
kr = ((r1 - r2) * (r3 - r4)) / ((r1 - ... | 2d9744361739db19e1c347b902a5844f1a23c655 | 3,623,245 |
def mse(tensor_true, tensor_pred):
""" Mean squared error
Parameters
----------
tensor_true : Tensor
tensor_pred : {Tensor, TensorCPD, TensorTKD, TensorTT}
Returns
-------
float
"""
tensor_res = residual_tensor(tensor_true, tensor_pred)
return np.mean(tensor_res.data ** 2) | afc7bce6515bfc656da3fdb15f5605184bcc10a7 | 3,623,246 |
def covered_cv_skills_from_course(user_id, course_id):
"""This function is used find the relation of a course to a user cv"""
fetch_cv_command = """SELECT DISTINCT id FROM "CVs" WHERE user_id={user_id}""""".format(**{'user_id': user_id})
cv_df = get_table(sql_command=fetch_cv_command)
if len(cv_df) > 0:... | 6befec8d8e15e759ac24718176fcf516d851d3ae | 3,623,247 |
def processRHS(rhs):
"""
Depending on the type of the argument, calls the corresponding
function to deal with that type.
:param rhs: portion of JSGF rule
:type rhs: either a JSGF Expression, list, or string
:returns: list of strings
"""
if type(rhs) is list:
return processSequen... | 412def2461fcfa3cc3ae48f8bcb2e4a4c18bb9e9 | 3,623,248 |
def svn_prop_name_is_valid(prop_name):
"""svn_prop_name_is_valid(char const * prop_name) -> svn_boolean_t"""
return _core.svn_prop_name_is_valid(prop_name) | 50c9c833f5d1935d6f411530700bb28ce60f0ca7 | 3,623,249 |
def factory():
"""
A factory that creates clustering algorithms.
"""
return ClusteringFactory | 4b4e81e4e32b9bf1e0b69b499e4f748f4a4836d3 | 3,623,250 |
import pycountry
def subdivision_type(country_code):
"""Returns the name of the most common country subdivision type for
the given country code."""
ensure_definition(country_code)
counts = dict()
for subdivision in pycountry.subdivisions.get(country_code=country_code):
if subdivision.paren... | e8268095cea3eb8e0e48772dd2b257f78fc4d314 | 3,623,251 |
def get_fans(tp):
""" Get fan_in and fan_out with corresponding slices """
slices_fan_in = {} # fan_in per slice
slices_fan_out = {}
for weight, instr in zip(tp.weight_views(), tp.instructions):
slice_idx = instr[2]
mul_1, mul_2, mul_out = weight.shape
fan_in = mul_1 * mul_2
... | 7fdff84c5129bd22a738653b6676d48c2a5f073d | 3,623,252 |
import numpy as np
import xarray as xr
from pandas import Timestamp
def download_noaa_mbl(
noaa_mbl_url,
download_dest="../data/raw/co2_GHGreference_surface.txt",
target_lat=None,
target_lon=None,
interp_method="linear",
):
"""
Downloads the NOAA marine boundary layer xCO2 and grids it
... | ba13bce93174bf3fbf3b47de2855f7fd3ff7dee3 | 3,623,253 |
import math
def get_pier_nodes(bridge: Bridge, ctx: BuildContext) -> PierNodes:
"""All the nodes for a bridge's piers.
NOTE: This function assumes that 'get_deck_nodes' has already been called
with the same 'BuildContext'.
"""
pier_nodes = []
for pier_i, pier in enumerate(bridge.supports):
... | 4f2ca233c4c58538c5074f168c52d086614e71b7 | 3,623,254 |
def secret_token():
"""
Fixture that yields a usable secret token.
"""
return 'super-secret-token-string'.encode() | 90e6c54a18387c64e27fea93912278c126df1585 | 3,623,255 |
def gf_from_int_poly(f, p):
"""
Create ``GF(p)[x]`` polynomial from ``Z[x]``.
**Examples**
>>> from sympy.polys.domains import ZZ
>>> from sympy.polys.galoistools import gf_from_int_poly
>>> gf_from_int_poly([7, -2, 3], 5)
[2, 3, 3]
"""
return gf_trunc(f, p) | 8716d08286b49310953a5d00d2d0c7f8a98a540d | 3,623,256 |
import requests
def macro_uk_halifax_yearly():
"""
东方财富-经济数据-英国-Halifax 房价指数年率
http://data.eastmoney.com/cjsj/foreign_4_1.html
:return: Halifax房价指数年率
:rtype: pandas.DataFrame
"""
url = "http://datainterface.eastmoney.com/EM_DataCenter/JS.aspx"
params = {
"type": "GJZB",
... | 09214bda60da565865c24e82f831466844fac92e | 3,623,257 |
def fock_state(state, device_wires, params):
"""Computes the expectation value of the ``qml.FockStateProjector``
observable in Strawberry Fields.
Args:
state (strawberryfields.backends.states.BaseState): the quantum state
device_wires (Wires): the measured mode
params (Sequence): se... | 955d59f3edcb8c6d0fbdfebb0fe1beca534df957 | 3,623,258 |
from datetime import datetime
def datetime_from_filetime(filetime):
"""return a :class:`datetime.datetime` from a ``windows`` FILETIME int"""
# Manual non-approx rounding as filetime will not have a perfect representation as Python float
# We do some sort of "manual rounding cause of py2 vs py3
# PY2:... | fc63e7a1072adff64bc8da3548285fed2e0add44 | 3,623,259 |
def forward_one_to_one_with_sr(request):
"""
Return all the publishers with associated owner, using select_related.
53ms overall
1ms on queries
1 queries
SELECT "bookstore_publisher"."id",
"bookstore_publisher"."name",
"bookstore_publisher"."owner_id",
"auth_us... | 70b991a56b30e8ba0847ca6a69b64c8d44647bd1 | 3,623,260 |
import types
def is_variable(tup):
""" Takes (name, object) tuple, returns True if it is a variable.
"""
name, item = tup
# callable()
# 函数用于检查一个对象是否是可调用的。如果返回True，object仍然可能调用失败；
# 但如果返回False，调用对象ojbect绝对不会成功。
# 对于函数, 方法, lambda 函式, 类, 以及实现了 __call__
# 方法的类实例, 它都返回 True。
if callab... | 81055d1ed252160c417b386c875e818b87780f14 | 3,623,261 |
import os
import errno
def _IsOnDevice(path, st_dev):
"""Checks if a given path belongs to a FS on a given device.
Args:
path: a filesystem path, possibly to a non-existent file or directory.
st_dev: the ID of a device with a filesystem, as in os.stat(...).st_dev.
Returns:
True if the path or (if ... | 391843553ea49ae7c0998dac5601d5d525890265 | 3,623,262 |
def _Solve_Amplitude(data, ufit, error=None) :
""" Compute the amplitude needed to normalise the 1d profile which minimises
the Chi2, given a x array, data and an error array
The calculation follows a simple linear optimisation using
Ioptimal = (dn x dn / dn x fn)
where dn i... | ccf513130dd8631acc61e88a328645243bdf7f94 | 3,623,263 |
def generate_ethmac(peripheral, shadow_base, **kwargs):
""" Generates definition of 'ethmac' peripheral.
Args:
peripheral (dict): peripheral description
shadow_base (int or None): shadow base address
kwargs (dict): additional parameters, including 'buffer'
Returns:
string: ... | e0c34117c972fb007ec9b322a48f54fcdad6c8ab | 3,623,264 |
def pix_centers(geoTransform, rows, cols, make_grid=True):
""" provide the pixel coordinate from the axis, or the whole grid
Parameters
----------
geoTransform : tuple, size=(6,1)
georeference transform of an image.
rows : integer
amount of rows in an image.
cols : integer
... | 05ad408b99c70c554eb42300e0d7cdd19630817f | 3,623,265 |
from typing import List
def rhymes(input_val: str_or_list_of_str, sample_size=None) -> List[str]:
"""Return a list of rhymes in randomized order for a given word if at least one can be found using the pronouncing
module (which uses the CMU rhyming dictionary).
:param input_val: the word or words in relat... | 71366876027efaf5ab43f7fe1e765aaad068825d | 3,623,266 |
async def logout():
"""Clear the current session, including the stored user id."""
logout_user()
return redirect(url_for("index")) | cc944f1069cf87d7b6cc94a44dde94e91efba369 | 3,623,267 |
from typing import Any
def delete_user_class(user_class_id: int) -> flask.Response:
"""
Create a new user class. Requires the ``userclasses_modify`` permission.
.. :quickref: UserClass; Delete user class.
**Example request**:
.. parsed-literal::
PUT /user_classes HTTP/1.1
{
... | acb7327231ff15473ada1906da75452c04c1a555 | 3,623,268 |
def ajax_form_errors(errors):
""" returns form errors as python list """
errs = [{'key': k, 'msg': unicode(errors[k])} for k in errors.keys()]
#equivalent to
#for k in form.errors.keys():
# errors.append({'key': k, 'msg': unicode(form.errors[k])})
return errs | 678c47de36d3f72c37acb394aff02b6c3f1253b6 | 3,623,269 |
import os
def load_data_file(name, skip_header=None) -> np.recarray:
"""Load a data file.
Returns
-------
data : :class:`numpy.recarray`
data values
"""
fname = os.path.join(os.path.dirname(__file__), 'data', name)
return np.recfromcsv(
fname, skip_header=skip_header, case... | a1fd6b1a02a5bbffdddb6c7fcf3e11b431e10e23 | 3,623,270 |
def sanitize_html(html, bad_tags=['body']):
"""Removes identified malicious HTML content from the given string."""
if html is None or html == '':
return html
cleaner = Cleaner(style=False, page_structure=True, remove_tags=bad_tags,
safe_attrs_only=False)
return cleaner.clea... | 260f01804b720de97406c3f277a91c17c360ccab | 3,623,271 |
from typing import Optional
def create_base_map(
move_data: DataFrame,
lat_origin: Optional[float] = None,
lon_origin: Optional[float] = None,
tile: Optional[Text] = TILES[0],
default_zoom_start: Optional[float] = 12,
) -> Map:
"""
Generates a folium map.
Parameters
----------
... | f5be52152234747469bb20357cba65f9c2b2f7cd | 3,623,272 |
from typing import Callable
import operator
def when(condition: Callable, f_true: Callable) -> Callable:
"""Returns `f_true(args)` if `condition(args)` returns true, else returns args.
>>> f = when(gamla.greater_than(5), lambda i: -i)
>>> f(6)
'-6'
>>> f(3)
'3'
"""
return ternary(cond... | 0fa5b4ae94910624a42f2da86d7c45be516f9cc4 | 3,623,273 |
from typing import Dict
def check_use_speech_in_inference(tts: AbsTTS, decode_config: Dict) -> bool:
"""Check whether to require speech in inference.
Args:
tts (AbsTTS): TTS model instance.
decode_config (Dict): Decoding config dictionary.
Returns:
bool: True if speech is require... | 147a144dc326a3eea3017f288dde24111dc44569 | 3,623,274 |
def f56a():
"""Return a unit-distance embedding of the F56A graph.
Note that MathWorld's LCF notation for this is incorrect;
it should be [11, 13, -13, -11]^14."""
t = tan(pi/14)
u = sqrt(polyval([-21, 98, 71], t*t))
z1 = 2*sqrt(14*polyval([31*u, -20, -154*u, 104, 87*u, -68], t))
z2 = 7*t*(t... | c5c0b0ac623858fc23005b82e81a9d3ca21834c4 | 3,623,275 |
def _nova_to_osvif_route(route):
"""Convert Nova route object into os_vif object
:param route: nova.network.model.Route instance
:returns: os_vif.objects.route.Route instance
"""
obj = objects.route.Route(
cidr=route['cidr'])
if route['interface'] is not None:
obj.interface =... | 2c6c3ae48f7c58e5b88404844e8a7ad4bc24fde7 | 3,623,276 |
import torch
def recall(pred, target):
"""Calculate macro-averaged recall according to the prediction and target
Args:
pred (torch.Tensor | np.array): The model prediction.
target (torch.Tensor | np.array): The target of each prediction.
Returns:
float: The function will return a... | a4b0852f4a66fdabee0ef2fee8f29fdb8ceda7db | 3,623,277 |
def send_ui_notification(error_message, success_message,
error_event_type=EVENT_TYPE_ERROR,
migrate_op=False, log_exception=False):
"""
Send a notification to the GUI. If the decorated method throws an
exception, an error notification will be sent, else a su... | 5095cb2b2dd847a861b872a535bf806b498f0ddc | 3,623,278 |
from typing import Union
def fetch_dataset_as_namedtuple(dataset_id: int, target: str,
read_csv_kwargs: dict,
load_dataframe: bool,
) -> Union[DatasetAll, DatasetInfoOnly]:
"""
Takes a dataset identifier, a target ... | 489106701c5f016cd6c25ff1a60b44491990ef8d | 3,623,279 |
def mps_to_kmph(mps):
"""
Transform a value from meters-per-second to kilometers-per-hour
"""
return mps * 3.6 | fee133def1727801e5e473d3ffb2df6c7e733a04 | 3,623,280 |
from typing import List
def get_comparison_data(data_type: str, similar: List[str]):
"""Screener Overview
Parameters
----------
data_type : str
Data type between: overview, valuation, financial, ownership, performance, technical
Returns
----------
pd.DataFrame
Dataframe w... | 7d736b666a98edacdfaa69e8894ba5782158901f | 3,623,281 |
def common_params(task_instance, task_cls):
"""
Grab all the values in task_instance that are found in task_cls.
"""
if not isinstance(task_cls, task.Register):
raise TypeError("task_cls must be an uninstantiated Task")
task_instance_param_names = dict(task_instance.get_params()).keys()
... | 3d9fd8e4d6aad9a04841fe1338d51bcf9b968a96 | 3,623,282 |
def two_ammonia_fake_print(ammonia_fake) -> (oechem.OEMol, oechem.OEMol):
"""
Returns two fingerprints for ammonia molecules with fake Wiberg bond
orders
"""
fingerprint1 = danceprops.DanceFingerprint(ammonia_fake[1], 0.05)
fingerprint2 = danceprops.DanceFingerprint(ammonia_fake[1], 0.05)
re... | e7e7ccc44b7beea1f78a33ea7779438e02473574 | 3,623,283 |
def imread(path, grayscale=False, size=None, interpolate="bilinear",
channel_first=False, as_uint16=False, num_channels=-1, **kwargs):
"""
Read image from ``path``.
If you specify the ``size``, the output array is resized.
Default output shape is (height, width, channel) for RGB image and (he... | d647b8248a40de6a254303db9ac06046fbbd5e23 | 3,623,284 |
import logging
import ssl
def get_client(project_id, cloud_region, registry_id, device_id, private_key_file,
algorithm, ca_certs, mqtt_bridge_hostname, mqtt_bridge_port):
"""Create our MQTT client. The client_id is a unique string that identifies
this device. For Google Cloud IoT Core, it must be i... | 7e135739b7eaf87f8a761a1b7eebea61febef727 | 3,623,285 |
def mutAddConn(self, connG, nodeG, innov, gen):
"""Add new connection to genome.
To avoid creating recurrent connections all nodes are first sorted into
layers, connections are then only created from nodes to nodes of the same or
later layers.
Todo: check for preexisting innovations to avoid duplicates in s... | 583cc8764aef0eca857be18adc0d924a66d9473b | 3,623,286 |
def heat_diffusion(heat, laplacian, start=0, end=0.1):
"""Heat diffusion
Iterative matrix multiplication between the graph laplacian and heat
"""
out_vector=expm_multiply(
-laplacian,
heat,
start=start,
stop=end,
endpoint=True
)[-1]
return out_vect... | a308f8719ec340435751ac32fd7ca1fb176b8374 | 3,623,287 |
import inspect
def behavior(instance_mode="session", instance_creator=None):
"""
Decorator to specify the server behavior of your Pyro class.
"""
def _behavior(clazz):
if not inspect.isclass(clazz):
raise TypeError("behavior decorator can only be used on a class")
if instan... | 748817411f58cdbce66b2cacdaf0a642183c7963 | 3,623,288 |
import torch
def gt2out(gt_bboxes_list, gt_labels_list, inp_shapes_list, stride, categories):
"""transform ground truth into output format"""
batch_size = len(gt_bboxes_list)
inp_shapes = gt_bboxes_list[0].new_tensor(inp_shapes_list, dtype=torch.int)
output_size = inp_shapes[0] / stride
height_rat... | da3636776f75abc53cc790e0ffd6871fc6a1d7ca | 3,623,289 |
def lstm_step_forward(x, prev_h, prev_c, Wx, Wh, b):
"""
Forward pass for a single timestep of an LSTM.
The input data has dimension D, the hidden state has dimension H, and we
use a minibatch size of N.
Inputs:
- x: Input data, of shape (N, D)
- prev_h: Previous hidden state, of shape (N,... | 7d898c35b2f50248f98a511a50c6dab5bef8d756 | 3,623,290 |
import time
import hashlib
def get_wx_js_sdk_config():
"""
获取微信JS-SDK权限验证配置
:return:
"""
url = request.args.get('url')
claim_args(1201, url)
appid = current_app.config['INTERVAL_APPID']
wx_authorizer = WXAuthorizer.query_by_appid(appid)
jsapi_ticket = wx_authorizer.get_jsapi_ticket... | 46daffecd53d08945dc601368a3a0291c85bd7fc | 3,623,291 |
def get_reviewer_by_id(reviewerID): # noqa: E501
"""Get a Reviewer by ID
# noqa: E501
:param reviewerID: ID of Reviewer
:type reviewerID: int
:rtype: List[Reviewer]
"""
results = _globals.pgapi.get(
'Reviewers',
clause=f'WHERE reviewerID={reviewerID}'
)
if type... | 72564cd627c1ccc3c384e5df2539c893b67e931d | 3,623,292 |
def get_quats(tpf=None, camera=None, sector=None, time=None, dt=None):
"""Get an array of the quaternions, at the time resolution of the input TPF"""
if (tpf is None) and (camera is None) and (sector is None):
raise ValueError('set either TPF or camera/sector')
if camera is None:
camera = tp... | 99f6b9093e24528a353618ac1f2fbe4606bc02c0 | 3,623,293 |
def create_list_id_title(sheets: list) -> list:
"""
Args:
this function gets a list of all the sheets of a spreadsheet
a sheet is represented as a dict format with the following fields
"sheets" : [
{
"properties": {
... | a32d2cbfce6f06d326f49e69983e05e67bfc1697 | 3,623,294 |
import types
import scipy
def qng(qc: qiskit.QuantumCircuit, thetas: np.ndarray, create_circuit_func: types.FunctionType, **kwargs):
"""Calculate G matrix in qng
Args:
- qc (qiskit.QuantumCircuit)
- thetas (np.ndarray): parameters
- create_circuit_func (FunctionType)
- num_lay... | 4c7433f96c7a4ce36ea6e20d0c82e189e725e611 | 3,623,295 |
def horizontal_projection(img_matrix):
"""
Function that calculate the angle rotation according to the Hough Transform technique
:param img_matrix: A list of ints with the matrix of pixels of the image
:return: rotateAngle: angle of rotation
"""
try:
img_grey = cv2.cvtColor(img_matrix... | 3eb7596a4f082300216fa4d7b3a87983aeee2b11 | 3,623,296 |
from matplotlib.ticker import AutoMinorLocator
def set_minor_tick(ax: Axes, n: int = 2):
"""Set one minor tick between major ticks."""
ax.xaxis.set_minor_locator(AutoMinorLocator(n))
ax.yaxis.set_minor_locator(AutoMinorLocator(n))
return ax | c41f72c4417a49d89b5c94c9d4b2185f69281403 | 3,623,297 |
def fit_lfm_pcfp(x, p, sig2, k_):
"""For details, see here.
Parameters
----------
x : array, shape (t_, n_)
p : array, shape (t_,)
sig2 : array, shape (t_, t_)
k_ : scalar
Returns
-------
alpha_PC : array, shape (n_,)
beta_PC : array, shape (n_, k_)
... | 9154045af81561b20a83394f0f03bcb9b27719c3 | 3,623,298 |
def _generate_is_in_range(message):
"""Generate range checks for all signals in given message.
"""
signals = []
for signal in message.signals:
scale = signal.decimal.scale
offset = (signal.decimal.offset / scale)
minimum = signal.decimal.minimum
maximum = signal.decima... | 2fc3e9939cb6225d4e6fb405efb4dd323e698179 | 3,623,299 |
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