content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def performance_metric(y_true, y_predict):
""" Calculates and returns the coefficient of determination R2.
R2 captures the percentage of squared correlation between the predicted
and actual values of the targets.
Parameters:
y_true - Array, the actual target values
y_predict - Array, the... | e5bc397e25e5e3c0a97742dbc85250bed092c74a | 58,000 |
def formatstr(text):
"""Extract all letters from a string and make them uppercase"""
return "".join([t.upper() for t in text if t.isalpha()]) | 749aeec962e3e39760c028bfb3e3a27ad8c10188 | 58,001 |
from datetime import datetime
import json
def update_local_db_based_on_record(eox_record, create_missing=False):
"""
update a database entry based on an EoX record provided by the Cisco EoX API
:param eox_record: JSON data from the Cisco EoX API
:param create_missing: set to True, if the product shou... | 0790c82966ca8ad2444fdffeecda2db131c24db4 | 58,002 |
def move_in(library, session, space, offset, length, width, extended=False):
"""Moves a block of data to local memory from the specified address space and offset.
Corresponds to viMoveIn* functions of the VISA library.
:param library: the visa library wrapped by ctypes.
:param session: Unique logical ... | 4e5b6b7231a786659d54482a70ca091e9f44b3f3 | 58,003 |
import os
from datetime import datetime
def evaluate(args, mode, appcfg):
"""prepare the report configuration like paths, report names etc. and calls the report generation function
"""
log.debug("evaluate---------------------------->")
subset = args.eval_on
iou_threshold = args.iou
log.debug("subset: {}"... | 80e4db931a9675e121466732f296b024b5bee35a | 58,004 |
def reflexive_missing_elements(relation, set):
"""Returns missing elements to a reflexive relation"""
missingElements = []
for element in set:
if [element, element] not in relation:
missingElements.append((element,element))
return missingElements | c31ce237c9156f17cc87a12ac80e595f81b08889 | 58,005 |
def cosine_groups(structure='fine'):
""" Returns cosine group bounds in increasing order.
Parameters
----------
structure : str
Named structure. Options currently include fine.
"""
if structure == 'fine':
""" A fine cosine group structure I created
"""
cb = np.... | 2a9497597650f96c11b9cf658e3d61f5422d7454 | 58,006 |
def form2_list_comprehension(items):
"""
Remove duplicates using list comprehension.
:return: list with unique items.
"""
return [i for n, i in enumerate(items) if i not in items[n + 1:]] | 02d095c86de1b7d52d53cdb4bfe77db08523ea3a | 58,007 |
from verticapy.plot import range_curve
from tqdm.auto import tqdm
from typing import Union
def learning_curve(
estimator,
input_relation: Union[str, vDataFrame],
X: list,
y: str,
sizes: list = [0.1, 0.33, 0.55, 0.78, 1.0],
method="efficiency",
metric: str = "auto",
cv: int = 3,
pos... | 1f1bbf7c307a134ef512cd0cb0d597bbe3ce2199 | 58,008 |
import os
import glob
def _DetectVisualStudioVersions(versions_to_check, force_express):
"""Collect the list of installed visual studio versions.
Returns:
A list of visual studio versions installed in descending order of
usage preference.
Base this on the registry and a quick check if devenv.exe exis... | b69e7d32035f5a589275f317d0930b9cc1fb2974 | 58,009 |
def route_image_next():
"""
Shows the next image.
"""
result = image_viewer.next()
return jsonify({'next' : result}) | 81f8ce34287a80dfc6e505a296fbdd4f3f70ee7a | 58,010 |
from prophet import Prophet
from typing import Union
import logging
def _prophet_fit_and_predict( # pylint: disable=too-many-arguments
df: DataFrame,
confidence_interval: float,
yearly_seasonality: Union[bool, str, int],
weekly_seasonality: Union[bool, str, int],
daily_seasonality: Union[bool, st... | cf2d0e640fe4be67a913a82b94d1177477b3122a | 58,011 |
def _beta_cont_frac(x, a, b, tol=1e-6, max_iter=200):
"""
Calculates continued fraction of the incomplete beta function.
NOTE:
Inspired by: https://malishoaib.wordpress.com/2014/04/15/the-beautiful-beta-functions-in-raw-python/
Parameters
----------
x : array_like, shape (n,)
Varia... | f7cf6dfc7b4f2e235b6f8557f63902a66f7cbec4 | 58,012 |
def calcMass(volume, density):
"""
Calculates the mass of a given volume from its density
Args:
volume (float): in m^3
density (float): in kg/m^3
Returns:
:class:`float` mass in kg
"""
mass = volume * density
return mass | 38f0ef780704c634e572c092eab5b92347edccd3 | 58,013 |
def update_Lambda(Lambda, L, Lx, X, G, Sigma, track_fval=False):
""" Update function for dual variables Lambda.
! Needs to be checked.
"""
n = len(Lx)
temp = [L-G[i] for i in range(n)]
Lambda[0], val_lam_change = up_Lam(Lambda[0], temp)
temp = [L-Lx[i] for i in range(n)]
Lambda[1], tem... | 44cffb5d198ca54618979f6f7e9ff4cf7b4e2759 | 58,014 |
def train_NB1(train_matrix, train_category):
"""
train_NB0函数的改进
:param train_matrix: 训练文档矩阵（准确来说只是python原生二维数组）
:param train_category: 训练文档矩阵对应的分类（一维向量）
:return: (在非侮辱性文档类别下词汇表中单词的出现概率向量, 在侮辱性文档类别下词汇表中单词的出现概率向量, 任意文档属于侮辱性文档的概率)
"""
# 训练文档的数目
num_train_docs = len(train_matrix)
num... | a936a91b21239bfc0a2150519764b5f169f19c2b | 58,015 |
def index():
"""renders the html form and listens for user trying to delete an object."""
json_handler.get_user_input()
# deleting alarm/notification
if "alarm_item" in str(request.url) or "notif" in str(request.url):
delete_an_object()
return fill_out_the_form() | dc2c84b76555462d05452b77d235f305e2f4a91c | 58,016 |
from io import StringIO
def make_summary_tables( res ):
""" takes a summary from statsmodel fitting results and turn it into 2 dataFrame.
- result_general_df : contains general info and fit quality metrics
- result_fit_df : coefficient values and confidence intervals
"""
# transfo... | cbb18ae56c2bf8cbe48486a4f047287a9b0c0681 | 58,017 |
def novelty_vector(convo):
"""
Returns the novelty vector measured from the convo text.
Parameters
----------
convo : Conversation
Returns
-------
np.array
"""
freq = type_frequency_distribution(convo)
if len(freq) == 0:
return []
return novelty(freq) | 67558a6129ce5e4c882ad1dc26af7baa6b1ad45c | 58,018 |
def rescale(arr, vmin, vmax):
""" Rescale uniform values
Rescale the sampled values between 0 and 1 towards the real boundaries
of the parameter.
Parameters
-----------
arr : array
array of the sampled values
vmin : float
minimal value to rescale to
vmax : float
... | d6debc0eeccd9fe19ed72d869d0de270559c9ce8 | 58,019 |
def get_write_in_model():
"""
Retrieves the model class (specified in
``settings.NOTORHOT_SETTINGS['WRITE_IN_MODEL']``) to be used to store
write-in submissions. See :func:`get_write_in_model_name` for details
:returns: write-in storage model class (**not** an instance)
:rtype: :class:`d... | 9dbeaa0c892ec46864acd98a3a4da4c5d91913c1 | 58,020 |
def get_extreme(extreme, range_minimum, range_maximum):
"""
extreme : should be min or max
range_minimum::int : minimum value you want your extreme to be
range_maximum::int : maximum value you want your extreme to be
"""
if isinstance(extreme, str):
if extreme == "":
e... | d44d15310c83b1e2fcf03939cd1e7625f68f0b11 | 58,021 |
import os
import getpass
def synapse_login():
"""
This function logs into synapse for you if credentials are saved.
If not saved, then user is prompted username and password.
:returns: Synapseclient object
"""
try:
syn = synapseclient.login(silent=True)
except Exception as e... | 16b32f562898e7d54dff7f6eafdbc834b3171b81 | 58,022 |
import torch
def predict(image_path, model, limit=5, gpu=False):
"""
Predict the class (or classes) of an image using a trained deep learning model.
:param image_path: string
:param model: model
:param limit: int Top K results that should be returned
:param gpu: bool
:returns: np.array, li... | e1da70ce9868139270dbf7772bbda0df0b402330 | 58,023 |
import tqdm
def morph_stc(stcs, subject_ids, subject_dir):
"""Morph stc inplace onto generic brain"""
morphed_stcs = []
for i, (stc, subject_id) in tqdm(enumerate(zip(stcs, subject_ids)),
total=len(stcs)):
try:
morph = mne.compute_source_morph(stc, ... | b26b0b73ebd214b6896bba132c8b43baae350230 | 58,024 |
def py2_strencode(s):
"""Encode a unicode string to a byte string by using the default fs
encoding + "replace" error handler.
"""
if PY3:
return s
else:
if isinstance(s, str):
return s
else:
return s.encode(ENCODING, ENCODING_ERRS) | 9aa76af9e96e69cb1cd7765ad22cb9ccd5a46d79 | 58,025 |
import shutil
def rename(path: str, target: str):
"""Copy path to target."""
return shutil.move(path, target) | 00f46f2557f4e0e7bd07610889a8c2deb028f24a | 58,026 |
def compute_moments(log_both, logit_rho, log_scale, phi, pi, theta, psi):
"""Compute the means and variances implied by the paramters."""
rho = special.expit(logit_rho)
vol_mean = np.exp(log_both) / (1 - rho)
vol_var = ((2 * np.exp(log_scale) * rho * vol_mean + np.exp(log_scale)**2
* np... | 0eea3c59c6d6d4be21ac0860c987760f40cd98af | 58,027 |
def render_latex(root_node, width=0, **options):
"""Render a node tree as a LaTeX document.
"""
options = make_options(**options)
return _cmark.render_latex(root_node, options, width) | a4f18f9474cd0d0aa56f51d3525c51d26c7fc9be | 58,028 |
import socket
def check_port_occupied(port, address="127.0.0.1"):
"""
Check if a port is occupied by attempting to bind the socket
:return: socket.error if the port is in use, otherwise False
"""
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
s.bind((address, port))
ex... | 5919e228c835ceb96e62507b9891c6a1ce5948fa | 58,029 |
import timeit
def heap_remove(N, num):
"""Run a single trial of num heap remove requests. Make sure that num < N."""
return 1000*min(timeit.repeat(stmt='''
for _ in range({}):
heapq.heappop(h)'''.format(num),
setup = '''
import heapq
h = []
for i in range(0,2*{},2):
heapq.heappush(h, i)'''.for... | 19101cd920904a2384aaec62b23dc169bdfe6dae | 58,030 |
def commit(msg=None):
"""
Commit your changes to git
:msg: @todo
:returns: @todo
"""
print '---Commiting---'
print
msg = msg or prompt('Commit message: ')
commit = False
commit = prompt('Confirm commit? [y/n]') == 'y'
if commit:
with settings(warn_only=True)... | c0d111c2354f8db5348c1750eb4c8456b689741f | 58,031 |
def inverseExtend(boundMethod, *args, **kargs):
"""Iterate downward through a hierarchy calling a method at each step.
boundMethod -- This is the bound method of the object you're interested in.
args, kargs -- The arguments and keyword arguments to pass to the
top-level method.
You can call t... | a511470f6cd3d86de19cc95e489498e649bea7a5 | 58,032 |
import gettext
def p_sign_up(
username,
password,
password2,
code,
email=None,
mobile_phone_number=None):
"""
普通用户注册函数
:return:
"""
data = {}
if current_user.is_authenticated:
data['msg'] = gettext("Is logged in")
data["msg_type"]... | 5b8ccd13ebb483c9198e7576816d89b4d6898b1a | 58,033 |
def is_intent_completed(
s_i: int,
option_id: option_utils.Options,
s_f: int,
intent_id: Intents,
) -> IntentStatus:
"""Determines if a (state, option, state) transition completes an intent.
Args:
s_i: (Unused) The integer representing the taxi state.
option_id: (Unused) The integer rep... | 96ab19f7527b8cadfdbaf148c2871a80d984c418 | 58,034 |
def inv_monitor_nonlinearity(x, x_gamma_function):
"""Monitor colour displaying is not linear but follows x^gamma function.
Convert monitor scale back to linear image float values.
parameters:
- x: image as numpy.ndarray (floats in [0,1])"""
# clip values that are too small or too large
x[... | 4969a49da207abaa0e17847f9bc5381608416a03 | 58,035 |
def jpg_image_to_array(image_path):
"""
Loads JPEG image into 3D Numpy array of shape
(width, height, channels)
"""
with Image.open(image_path) as image:
im_arr = np.fromstring(image.tobytes(), dtype=np.uint8)
im_arr = im_arr.reshape((image.size[1], image.size[0], 1))
return im_... | 8c188c2199dd1a074d1c1eb9ac032280ab6cd713 | 58,036 |
def dict2func(d):
"""Converts all strings in a dictionary to their
corresponding functions (if applicable)"""
res = dict()
for k, v in d.items():
if isinstance(v, dict):
res[k] = dict2func(v)
else:
res[k] = str2func(v)
return res | ddb74e6d6e877a85d6881354e0064596efd2f27d | 58,037 |
def _midpoints_1d(arr, frac=0.5, axis=-1):
"""Return the midpoints between values in the given array.
If the given array is N-dimensional, midpoints are calculated from the last dimension.
Arguments
---------
arr : ndarray of scalars,
Input array.
frac : float,
Fraction of the ... | b95d376a98dbfa5fc98a5892686f39df557cc65b | 58,038 |
def _run_once_sucessfully(f):
"""
Decorator that uses a cache to flag an action as already executed, and check to
ensure that it hasn't been executed before running (in the event of retries,
multiple failures).
:param f: a function/method to run only once.
"""
def inner(self, *args, **kwarg... | bf1cc23ca7dd7f8aac994acdc15778dd520d02cc | 58,039 |
def get_source_tag (aligned_dict, src_word_tag_dict):
"""Get the aligned (source) tag for each word in each sentence of target language from a source language"""
tar_tag_dict = {} # create a dict to store predicted tag for tar language
print("get source tag")
for sentence_cnt in aligned_dict.keys():
... | ccd4fe0a2a0d1a13c553c7392f7876979729de1c | 58,040 |
import torch
import math
def cal_GauProb(mu, sigma, x):
"""
Arguments:
mu (BxMxC) - The means of the Gaussians.
sigma (BxMxC) - The standard deviation of the Gaussians.
x (BxC) - A batch of data points (coordinates of position).
Return:
probabilities (BxM): proba... | 6625878d6dd199b106bbb48336fc52f52e8c1f4f | 58,041 |
from typing import Dict
def determine_postAST_from_filename(filenamesplit) -> Dict:
"""determine postAST from filenamesplit"""
basepf_split, postAST = filenamesplit, ""
if all([i in basepf_split for i in ("post", "AST")]):
if any(s in basepf_split for s in ["LC"]):
if "postAST_LC" in ... | 3787dcef3ae65538f2fe66f98be60cc0f71f7790 | 58,042 |
def getPrivacyList(disp, listname):
"""
Requests specific privacy list listname. Returns list of XML nodes (rules)
taken from the server responce.
"""
try:
resp = disp.SendAndWaitForResponse(Iq("get", NS_PRIVACY, payload=[Node("list", {"name": listname})]))
if isResultNode(resp):
return resp.getQueryPayload... | 3c8dc760df11907793b768459b16f62499c0709a | 58,043 |
def modified_fisher_transform(r: float, n: int) -> float:
"""Returns a Fisher's z modified by dividing it by the standard error."""
z = atanh(r)
inverse_standard_error = sqrt(n - 3)
return z * inverse_standard_error | 8b4b652c87be85536459f9aa4a93f9e8f89880a5 | 58,044 |
import html
def indicator(color, text, id_value):
"""
Builds a new Dash div styled as a container, with borders and background.
:param str color: background color of the container (RGB or Hex colors).
:param str text: name to be plotted inside the container.
:param str id_value: identifier of the... | 7cbb68cbe09b07eb8a549825f80129c3b6720fc6 | 58,045 |
def pack(fmt, *args):
"""
Return string containing values v1, v2, ... packed according to fmt.
See struct.__doc__ for more on format strings.
"""
try:
o = _cache[fmt]
except KeyError:
o = _compile(fmt)
return o.pack(*args) | 61d8bbfe5c210045bfc3fb2196b5a5291f47aa6a | 58,046 |
def require_context(f):
"""Decorator to require *any* user or admin context.
This does no authorization for user or project access matching, see
:py:func:`authorize_project_context` and
:py:func:`authorize_user_context`.
The first argument to the wrapped function must be the context.
"""
... | 83fac830883968bf62b4e04ea3dad3ef4c619caf | 58,047 |
def get_reg_info(*args):
"""get_reg_info(char regname, ulonglong mask) -> char"""
return _idaapi.get_reg_info(*args) | 77790803e8b21b1a6b063f9f496579b64757b5a3 | 58,048 |
def pretty(data, corner = '+', separator='|', joins='-'):
"""
Parameters :
~ data : Accepts a dataframe object.
~ corner : Accepts character to be shown on corner points (default value is "+").
~ separator : Accepts character to be shown in place to the line separating two values (default value... | 812fb5d255c5e44c1d026d307e2a39c7b3c31f14 | 58,049 |
import torch
def double_observation(f: torch.Tensor) -> torch.Tensor:
"""Double observation vector as (A, B, C, D) --> (A, A, B, B, C, C, D, D)
Args:
f: Observation vectors (n_batch, ...)
Returns:
Observation vectors (2*n_batch, ...)
"""
return torch.repeat_interleave(f, 2, dim=0... | 06f8e9acf3f62cd0d75a0a69451625fe4bdc8659 | 58,050 |
import csv
def write_rows(rows, filename, sep="\t"):
"""Given a list of lists, write to a tab separated file"""
with open(filename, "w", newline="") as csvfile:
writer = csv.writer(
csvfile, delimiter=sep, quotechar="|", quoting=csv.QUOTE_MINIMAL
)
for row in rows:
... | 41e04ee6203baf7db2d08722aed76dfacbc9e838 | 58,051 |
import collections
def context():
"""A mock for the lambda_handler context parameter."""
Context = collections.namedtuple('Context', 'function_name function_version')
return Context('TestFunction', '1') | b7d65ca7ff87aea1bd22e87dba4cb2d0e5ec411d | 58,052 |
def get_pa_type_factory(pa_type):
"""return type factory"""
if pt.is_int8(pa_type):
return pa.int8
elif pt.is_int16(pa_type):
return pa.int16
elif pt.is_int32(pa_type):
return pa.int32
elif pt.is_int64(pa_type):
return pa.int64
elif pt.is_uint8(pa_type):
... | 01063af85f556fdd2e67d1935c75b54532d25b84 | 58,053 |
def iscircular(linked_list):
"""
Determine wether the Linked List is circular or not
Args:
linked_list(obj): Linked List to be checked
Returns:
bool: Return True if the linked list is circular, return False otherwise
"""
if linked_list.head is None:
return False
... | 874073d433f1a3069ca250379b4855303f5a6510 | 58,054 |
def controller_encryption_exists(handle, controller_type, controller_slot,
server_id=1):
"""
Checks if encryption is enabled on the controller
Args:
handle (ImcHandle)
controller_type (str): Controller type
'SAS'
contro... | 02d17aebbf7508a94308f37c524bd056b96d531f | 58,055 |
import torch
def make_one_mask_target(cfg, mode, input, sampled_proposal, sampled_assign, truth_box, truth_mask):
"""
Deprecated.
Was used for generating mask for MaskRcnn
"""
sampled_mask = []
mask_crop_size = cfg['mask_crop_size']
for i in range(len(sampled_proposal)):
_, D, H, ... | 0e9ddf14b5fe8c4d0b453b6c64b9859ae5e8dcc8 | 58,056 |
import tqdm
def chamfer_hausdorff_dists_block_wise(X0, X1, sub_batch_size=10000):
"""
Compute one-sided Chamfer and Hausedorf distances and Chamfer and Hausedorf distances in the block-wise manner.
"""
def chamfer_hausdorff_oneside_dists(X0, X1):
b0 = X0.shape[0]
b1 = X1.shape[0]
... | ce047cf3e61965d5e5c9a08cf5fe64b5b3c7a2a5 | 58,057 |
def sample_with_replacement(population, k, n=None):
"""
Return a sample of size k with replacements chosen from the population.
If n is set, an array of size n containing samples of size k is returned.
:param population:
:param k: size of the sample
:param n: number of samples
:return: n (o... | 00a2f17276812c4e775e13d8e3391aece9c65047 | 58,058 |
def cartesian_regions_to_slices(regions):
"""
Convert a sample region(s) string, consisting of a comma-separated list
of (colon-or-hyphen-separated) pixel ranges into Python slice objects.
These ranges may describe either multiple 1D regions or a single higher-
dimensional region (with one range pe... | b1ec8ec783f5ea380fd665888131733d0b4b1833 | 58,059 |
import typing
def build_charge_table(charges: typing.List[Charge], page_number: int)\
-> FlexibleColumnWidthTable:
"""
This function builds a Table containing itemized billing information
:param typing.List[Charge] charges: the rows on the invoice
:param int page_number: Current page number... | 79039651de64081662350b2cc27e0bbe77958c1d | 58,060 |
def view_processing( request ):
""" If shib headers ok, logs user in & redirects to admin view. """
log.debug( 'starting view_processing()' )
user = user_grabber.get_user( request.META )
if user:
log.debug( 'logging in user' )
django_login(request, user )
url = reverse('admin:iip_pro... | a1af48233d3e993539f25b02e01ef632fa4eacac | 58,061 |
def count_occurence_of_character_in_neighbour_squares(x, y, board, character):
"""
returns the number of neighbours of (x,y) that are bombs. Max is 8, min is 0.
"""
num_rows = len(board[0])
num_cols = len(board)
squares = neighbour_squares(x, y, num_rows, num_cols)
character_found ... | 1d9e2ef22e1f61c51845417e9c036943e66283a5 | 58,062 |
from typing import Sequence
from typing import List
from typing import Set
def remove_overlapping_lane_seq(lane_seqs: Sequence[Sequence[int]]) -> List[Sequence[int]]:
"""
Remove lane sequences which are overlapping to some extent
Args:
lane_seqs (list of list of integers): List of sequence of lan... | b9489dfd7c592c1a41a323627bb974b92f3257ab | 58,063 |
import tqdm
import torch
def evaluate_encoder(model, tokenizer, eval_dataset, device="cpu", batch_size=16,
output_predictions=True, output_topk=0, progress_bar=True):
"""
Evaluates any HuggingFace Encoder model.
A model's prediction is determined by the probabilities assigned to the ... | a6bfb2e9be190a2003a42aa9052b052d8fdf9037 | 58,064 |
def _generate(n, pi, mu, random_state=None):
"""
Generate samples from an EMM.
Parameters
----------
n : int
Sample size.
pi : array
Mixing weight of the individual exponential distribution in the EMM.
mu : array
Mean of the individual exponential distribution in the... | e8a78b16d1b84669189a986fa51c1d2b71fca6c4 | 58,065 |
def _auth_handler():
"""
Requrired JWT method
"""
return None | 9ec5301d6e32c7b3016a92ba9ae89d22fed3bad5 | 58,066 |
def validate_experimental(context, param, value):
"""Load and validate an experimental data configuration."""
if value is None:
return
config = ExperimentConfiguration(value)
config.validate()
return config | a486f76a5c9006fbdd765c7c682bea237a445d90 | 58,067 |
def todatadict(data):
"""Reorganize tuple of dicts into single dict where keys are defined by ID
and NAME, values are numerical data corresponding to RPKM values
:param data: tuple of dicts from loaded cleaned data
:returns: dict containing reorganized data
"""
full = nest(get(0), dict.keys, tu... | 5b95ac1030cccf405a38bd8e00114c53598ca317 | 58,068 |
def HKL2string(hkl):
"""
convert hkl into string
[-10.0,-0.0,5.0] -> '-10,0,5'
"""
res = ""
for elem in hkl:
ind = int(elem)
strind = str(ind)
if strind == "-0": # removing sign before 0
strind = "0"
res += strind + ","
return res[:-1] | 325ddfcb2243ce9a30328c5b21626a4c93a219de | 58,069 |
def evaluate_models(dataset,
p_values,
d_values,
q_values,
training_portion=0.66):
"""
Fucntion to tune hyperparameters of arima model
Parameters
----------
dataset : array or list
All dataset.
p_values : in... | 931129f351fcd749b2e9c80c61a4ec5632285e14 | 58,070 |
import plan2scene.texture_prop.graph_generators as graph_generators
def get_graph_generator(conf: ConfigManager, graph_generator_def: Config, include_target: bool):
"""
Creates graph generator given the graph generator configuration.
:param conf: Config manager.
:param graph_generator_def: Graph gener... | 4b60d7e00fd16a447a956db8e77c7847cde65966 | 58,071 |
import logging
import sys
def getLogger(nm):
"""Get a basic-configured trace-enabled logger."""
logging.basicConfig(stream=sys.stdout, level=logging.INFO, format='%(levelname).1s: %(message)s')
log = logging.getLogger(nm)
return log | a6fc4f0fe6d2104c0e2487d6038401306ad3e3ba | 58,072 |
import json
def returnBook():
"""returnBook sara' attivato dopo una richiesta HTTP asincrona (AJAX);
l'utente informera' il db che il libro sia stato restituito mediante
il metodo managedb.returnBookDB().
La risposta sara' in formato JSON
"""
# Flask salvera' un item logged_in se l'utente
... | 7aa6959aa2ea468a096ff1062a6034e93705a14b | 58,073 |
import base64
import six
import requests
import json
from datetime import datetime
def fetch_refreshed_token(refresh_token):
""" Fetches a new access token using refresh token """
payload = {'grant_type': 'refresh_token', 'refresh_token': refresh_token}
auth_headers = base64.b64encode(six.text_type(CLIENT... | c3a42504c345b630728cab253e6de2ee0e4d3937 | 58,074 |
import re
def splitAtUppercase(a_string):
"""assumes a_string is a string
returns a list of strings, a_string split at each uppercase letter"""
pattern = "([A-Z])"
string_list = re.split(pattern, a_string)
return string_list | 5cbf4673ee46db81b8acfb30bfe64a44d10d0d9a | 58,075 |
def send_sms(destination, message):
"""
Sends an sms message using AWS SNS.
Args:
destination (str): Required. The sms number to send to.
message (str): Required. The message to be sent.
Returns:
The AWS response.
"""
client = boto3.client('sns', region_name='eu-west-1... | 50bbfa763c11e57de378a819a107c3b7a4720706 | 58,076 |
from typing import List
def should_expand_range(numbers: List[int], street_is_even_odd: bool) -> bool:
"""Decides if an x-y range should be expanded."""
if len(numbers) != 2:
return False
if numbers[1] < numbers[0]:
# E.g. 42-1, -1 is just a suffix to be ignored.
numbers[1] = 0
... | fcd5a8e027120ef5cc52d23f67de4ab149b19a2c | 58,077 |
def get_all_bababooeys() -> list:
"""
Returns all permutations of "bababooey" with acceptable character substitutions.
:return: list of all bababooeys
"""
substitutions = {
'b': '🅱️',
'o': '0',
'e': '3',
}
char_possibilities = []
for c in 'bababooey':
su... | a6275d64cf3c498a5472d594941615575b86b25f | 58,078 |
def from_inches(unit, val):
"""Convert val in inches to unit."""
return _FROM_INCHES[unit](val) | 1ac86745f83e333fc6eff27c2fcc980521ad1727 | 58,079 |
def zyx_to_yxz_dimension_only(data, z=0, y=0, x=0):
"""
Creates a tuple containing the shape of a conversion if it were to happen.
:param data:
:param z:
:param y:
:param x:
:return:
"""
z = data[0] if z == 0 else z
y = data[1] if y == 0 else y
x = data[2] if x == 0 else x
... | 2477976f795f5650e45214c24aaf73e40d9fa4eb | 58,080 |
def _get_params(deep: bool) -> str:
"""
Get parameters for this estimator.
:param deep: If True, will return the parameters for this estimator and
contained subobjects that are estimators.
:type deep: bool
:param return: Parameter names mapped to their values.
:type return... | f8904a8db8f791b97f485a5cd98285aee9eed6b9 | 58,081 |
def mse_l1_sparsity(x, x_hat, concepts, sparsity_reg):
"""Sum of Mean Squared Error and L1 norm weighted by sparsity regularization parameter
Parameters
----------
x : torch.tensor
Input data to the encoder.
x_hat : torch.tensor
Reconstructed input by the decoder.
concepts : tor... | cabb269caf826348909ccf42f3d26582ae02777b | 58,082 |
def CalculateChi10p(mol):
"""
#################################################################
Calculation of molecular connectivity chi index for path order 10
---->Chi10
Usage:
result=CalculateChi10p(mol)
Input: mol is a molecule object.
... | 340227613b9e561802c0fbc40bfe8e4c6d49af31 | 58,083 |
def binary_log_loss(Y, P):
"""
Compute negative log loss
"""
N = len(Y)
# Clip values very close to 1 or 0
P = np.clip(P, EPS, 1 - EPS)
# Negative log likelihood function
mask0 = (Y == 0) # label = 0 observations
mask1 = (Y == 1) # label = 1 observations
nll = -(np.log(P[mask1]... | 1f2a5d6b714d32851e8388e1162f9c37e9169ac4 | 58,084 |
def run_policy(
policy_and_value_net_apply,
observations,
lengths,
params,
state,
rng,
vocab_size,
observation_space,
action_space,
rewards_to_actions,
):
"""Runs the policy network."""
policy_input = _prepare_policy_input(
observations, vocab_size, observation_space, a... | be76524d40758f0083657e62b7a9230b81cddd41 | 58,085 |
def make_vagrant_unit_factory(branch):
"""
This returns the factory that runs the Vagrant unit tests.
"""
f = BuildFactory()
f.addStep(Git(repourl="git://github.com/mitchellh/vagrant.git",
branch=branch,
mode="full",
method="fresh",
... | 74b058410fcecafeabee3589d96730849a522a79 | 58,086 |
def _find_non_suppressed_predicates(predicates, validity_intervals):
"""Returns the predicates that are left after suppression operations.
:param predicates: A sequence of predicates in the form of TimedPropertyGraph objects.
:param validity_intervals: The intervals during which corresponding predicates ho... | 69aa7b419624e911ca9dc05bc071989f78ee6cfb | 58,087 |
def handle_market_cap(request):
"""
Generate response to intent type MarketCapIntent with the current market cap of the ticker.
:type request AlexaRequest
:return: JSON response including market cap of the ticker
"""
ticker = request.get_slot_value(slot_name="stockTicker").upper()
# Query D... | a46d9aee35581abd8766fd59c7cc207ac0376687 | 58,088 |
from datetime import datetime
import math
def prepare_fetch_hourlies_query(raw_station: dict, start_timestamp: datetime, end_timestamp: datetime):
""" Prepare url and params to fetch hourly readings from the WFWX Fireweather API.
"""
base_url = config.get('WFWX_BASE_URL')
logger.debug('requesting his... | 7430fd07cdeb1dd760272d904fffe72d4b7910a8 | 58,089 |
import six
import json
def _safe_match_string(value):
"""Sanitize and represent a string argument in MATCH."""
if not isinstance(value, six.string_types):
if isinstance(value, bytes): # should only happen in py3
value = value.decode('utf-8')
else:
raise GraphQLInvalidA... | 7e6c06af244379b274fcf71ce97d1291808ace84 | 58,090 |
def first_supported_filter(test, runner):
"""Get the first filter supported by the server
Arguments:
test (Node): reference to Node object
runner (Runner): reference to Runner object
Returns:
(dict): single (first) request filter
"""
return single_supported_filter(test... | a5b00124ad48f429ba9ef435661fcb2f63ad9d52 | 58,091 |
import functools
def remotable_classmethod(fn):
"""Decorator for remotable classmethods."""
@functools.wraps(fn)
def wrapper(cls, context, *args, **kwargs):
if NovaObject.indirection_api:
result = NovaObject.indirection_api.object_class_action(
context, cls.obj_name(), ... | 5f5e25b294df7e755c8ed6b921150552474be7dd | 58,092 |
def gen_anonymous_varname(column_number: int) -> str:
"""Generate a Stata varname based on the column number.
Stata columns are 1-indexed.
"""
return f'v{column_number}' | f0e150300f7d767112d2d9e9a1b139f3e0e07878 | 58,093 |
from typing import Optional
import os
from datetime import datetime
import asyncio
async def make_rzd_request(url) -> Optional[str]:
"""Get response from rzd with Selenium.
Args:
url: Search url.
Returns:
response: Page data.
"""
# ChromeBrowser (heroku offical supports it) easy ... | 2f8b9dff66d7f75afcc992a1ba8b152fe5f2ac73 | 58,094 |
def min_version(the_module, min_version_str: str = "") -> bool:
"""
Convert version strings into tuples of int and compare them.
Returns True if the module's version is greater or equal to the 'min_version'.
When min_version_str is not provided, it always returns True.
"""
if min_version_str:
... | 2ab3d5c3a9b2fd1c938ddd3f7967d8df7c5b6c77 | 58,095 |
def graph_from_place(query, network_type='all_private', simplify=True,
retain_all=False, truncate_by_edge=False, name='unnamed',
which_result=1, buffer_dist=None, timeout=180, memory=None,
max_query_area_size=50*1000*50*1000, clean_periphery=True,
... | c4a981aa0f7c68e183593e4c985f899ceb038aca | 58,096 |
def inspect_file_attrs(f_path_or_f_obj):
"""
List out the attributes of some HDF5 file object.
If a path is provided, then it will open the file in
read mode.
Examples:
.. code-block:: python
import h5py
from support.hdf5_util import inspect_file_attrs
file_path = "e... | a7ede3aac50c93a048bc188e2e6795586ec3eac2 | 58,097 |
def strip_name(s):
""" Strips the name per RE_STRIP_NAME regex.
>>> strip_name('Login')
'Login'
>>> strip_name('LoginHandler')
'Login'
>>> strip_name('LoginController')
'Login'
>>> strip_name('LoginPage')
'Login'
>>> strip_name('LoginView')
... | 6cc3956bcb9e4696a1a434ccb654ac519d24b443 | 58,098 |
def api_queuelist():
""" Api Method that return the number of remaining itens in queue """
return str(len(link_queue)) + '\n' | 48d21f6420dd8065f796f0697cad26dd416592a1 | 58,099 |
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