content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def separable_hnn(num_points, input_h_s=None, input_model=None,
save_path='temp_save_path', train=True, epoch_save=100):
"""
Separable Hamiltonian network.
:return:
"""
if input_h_s:
h_s = input_h_s
model = input_model
else:
h_s = HNN1DWaveSeparable(nn.... | c9912f69b4367a2ed83ce367970551f31e0cb087 | 28,671 |
def get_n_largest(n, lst, to_compare=lambda x: x):
"""
This returns largest n elements from list in descending order
"""
largests = [lst[0]]*n # this will be in descending order
for x in lst[1:]:
if to_compare(x) <= to_compare(largests[-1]):
continue
else:
fo... | 4ef85d8656ae152ecab65d3a01bce7f885c47577 | 28,672 |
from natsort import natsorted
import collections
from typing import Optional
from typing import Union
def base_scatter(
x: Optional[Union[np.ndarray, list]],
y: Optional[Union[np.ndarray, list]],
hue: Optional[Union[np.ndarray, list]] = None,
ax=None,
title: str = None,
... | 72e159af3ffad86e66b53789368edbb3a7bc406a | 28,673 |
def lambda_sum_largest_canon(expr, real_args, imag_args, real2imag):
"""Canonicalize nuclear norm with Hermitian matrix input.
"""
# Divide by two because each eigenvalue is repeated twice.
real, imag = hermitian_canon(expr, real_args, imag_args, real2imag)
real.k *= 2
if imag_args[0] is not Non... | 41e2d460fc5d18d65e1d7227093ecaf88a925151 | 28,674 |
def dp_palindrome_length(dp, S, i, j):
"""
Recursive function for finding the length
of the longest palindromic sequence
in a string
This is the algorithm covered in the lecture
It uses memoization to improve performance,
dp "dynamic programming" is a Python dict
containing previously computed values
... | 10a8ac671674ba1ef57cd473413211a339f94e62 | 28,675 |
def ellip_enclose(points, color, inc=1, lw=2, nst=2):
"""
Plot the minimum ellipse around a set of points.
Based on:
https://github.com/joferkington/oost_paper_code/blob/master/error_ellipse.py
"""
def eigsorted(cov):
vals, vecs = np.linalg.eigh(cov)
order = vals.argsort()[::-1... | c6f3fabfb306f29c5c09ffee732d5afea2c1fe33 | 28,676 |
def catalog_dictionary_per_observation(cats, obs_nums, targets, defaults):
"""Translate a dictionary of catalogs from a case of either:
1. Separate catalogs for each target name
2. Separate catalogs for each target name and instrument
into a dictionary of catalogs for each instrument and observation
... | b418e0315b242c251d6796636fdd3fdbcfefbfa5 | 28,677 |
def sierpinkspi(p1, p2, p3, degree, draw, image, colors):
"""
Draw Sierpinksi Triangles.
"""
colour = colors
draw.polygon(((p1[0], p1[1]), (p2[0], p2[1]), (p3[0], p3[1])), fill=colour[degree])
if degree > 0:
sierpinkspi(p1, mid(p1, p2), mid(p1, p3), degree-1, draw, image, colors)
... | c43662d50a655eed4298e34d2f9830e678a0ca96 | 28,678 |
def generate_depth_map(camera, Xw, shape):
"""Render pointcloud on image.
Parameters
----------
camera: Camera
Camera object with appropriately set extrinsics wrt world.
Xw: np.ndarray (N x 3)
3D point cloud (x, y, z) in the world coordinate.
shape: np.ndarray (H, W)
O... | f219d2128bdecf56e8e03aef7d6249b518d55f06 | 28,679 |
def create_own_child_column(X):
"""
Replaces the column 'relationship' with a binary one called own-child
"""
new_column = X['relationship'] == 'own-child'
X_transformed = X.assign(own_child=new_column)
X_transformed = X_transformed.drop('relationship', axis=1)
return X_transformed | 303ec8f073920f0bba6704740b200c7f3306b7bd | 28,681 |
def find_next_gate(wires, op_list):
"""Given a list of operations, finds the next operation that acts on at least one of
the same set of wires, if present.
Args:
wires (Wires): A set of wires acted on by a quantum operation.
op_list (list[Operation]): A list of operations that are implement... | 287a3b2905f86dff0c75027bcba6bd00bab82fd8 | 28,682 |
def FDilatedConv1d(xC, xP, nnModule):
"""1D DILATED CAUSAL CONVOLUTION"""
convC = nnModule.convC # current
convP = nnModule.convP # previous
output = F.conv1d(xC, convC.weight, convC.bias) + \
F.conv1d(xP, convP.weight, convP.bias)
return output | 900065f6618f1b4c12191b1363ce6706ec28d222 | 28,683 |
def load_spans(file):
"""
Loads the predicted spans
"""
article_id, span_interval = ([], [])
with open(file, 'r', encoding='utf-8') as f:
for line in f.readlines():
art_id, span_begin, span_end = [int(x) for x in line.rstrip().split('\t')]
span_interval.append((span_b... | 8f8de31e1d1df7f0d2a44d8f8db7f846750bd89f | 28,684 |
def is_stupid_header_row(row):
"""returns true if we believe row is what the EPN-TAP people used
as section separators in the columns table.
That is: the text is red:-)
"""
try:
perhaps_p = row.contents[0].contents[0]
perhaps_span = perhaps_p.contents[0]
if perhaps_span.get("style")=='color: rgb(... | 124108520486c020d2da64a8eb6f5d266990ae02 | 28,685 |
def get_cli_parser() -> ArgumentParser:
"""Return an ArgumentParser instance."""
parser = ArgumentParser(description="CLI options for Alice and Bob key share")
parser.add_argument('-p', help='Prime p for information exchange', type=int)
parser.add_argument('-g', help='Prime g for information exchange', ... | 2ca9feff2940064163d8b5724b647ab56f4ea5e6 | 28,686 |
import re
def _get_http_and_https_proxy_ip(creds):
"""
Get the http and https proxy ip.
Args:
creds (dict): Credential information according to the dut inventory
"""
return (re.findall(r'[0-9]+(?:\.[0-9]+){3}', creds.get('proxy_env', {}).get('http_proxy', ''))[0],
re... | b18d89718456830bdb186b3b1e120f4ae7c673c7 | 28,687 |
def geometric_expval(p):
"""
Expected value of geometric distribution.
"""
return 1. / p | 3afb3adb7e9dafa03026f22074dfcc1f81c58ac8 | 28,689 |
def make_ticc_dataset(
clusters=(0, 1, 0), n_dim=3, w_size=5, break_points=None,
n_samples=200, n_dim_lat=0, sparsity_inv_matrix=0.5, T=9,
rand_seed=None, **kwargs):
"""Generate data as the TICC method.
Library implementation of `generate_synthetic_data.py`, original can be
found at... | 7c77d5ea4ff9e87681b0494333c49e24360b7072 | 28,690 |
from dustmaps import sfd
from dustmaps import planck
def get_dustmap(sourcemap, useweb=False):
""" get the dustmap (from the dustmaps package) of the given source.
Parameters
---------
sourcemap: [string]
origin of the MW extinction information.
currently implemented: planck, sfd
... | a5daec02601c968d25942afe1577ad301bbb6a55 | 28,692 |
def make_retro_pulse(x, y, z, zenith, azimuth):
"""Retro pulses originate from a DOM with an (x, y, z) coordinate and
(potentially) a zenith and azimuth orientation (though for now the latter
are ignored).
"""
pulse = I3CLSimFlasherPulse()
pulse.type = I3CLSimFlasherPulse.FlasherPulseType.retro... | de6fa8905276122c501b5a80842a12abfa2a81f1 | 28,693 |
def shiftLeft(col, numBits):
"""Shift the given value numBits left.
>>> spark.createDataFrame([(21,)], ['a']).select(shiftLeft('a', 1).alias('r')).collect()
[Row(r=42)]
"""
sc = SparkContext._active_spark_context
return Column(sc._jvm.functions.shiftLeft(_to_java_column(col), numBits)) | 769cbcb4f66473bdeb789c1326aa58e763c4f320 | 28,694 |
def lerp(x0: float, x1: float, p: float) -> float:
"""
Interplates linearly between two values such that when p=0
the interpolated value is x0 and at p=1 it's x1
"""
return (1 - p) * x0 + p * x1 | c4114dcb5636e70b30cd72a6e7ceab1cd683fa8d | 28,695 |
def discard_events(library, session, event_type, mechanism):
"""Discards event occurrences for specified event types and mechanisms in a session.
Corresponds to viDiscardEvents function of the VISA library.
:param library: the visa library wrapped by ctypes.
:param session: Unique logical identifier t... | 72010fae64bb0a1e615ce859d150f7f24f2c7171 | 28,696 |
def getSpeed(spindle=0):
"""Gets the interpreter's speed setting for the specified spindle.
Args:
spindle (int, optional) : The number of the spindle to get the speed
of. If ``spindle`` is not specified spindle 0 is assumed.
Returns:
float: The interpreter speed setting, with a... | a7c759ff91c079aacd77d7aa0141f42aa9ca60af | 28,697 |
def appointment() -> any:
"""
Defines route to appointment booking page.
:return: String of HTML template for appointment booking page or homepage if booking was successful.
"""
if request.method == 'POST':
user_input = request.form.to_dict()
try:
request_is_valid(request... | 5c55c0387300f21cfea45809bdf534ace4137fc6 | 28,698 |
def wait_for_task(task, actionName='job', hideResult=False):
"""
Waits and provides updates on a vSphere task
"""
while task.info.state == vim.TaskInfo.State.running:
time.sleep(2)
if task.info.state == vim.TaskInfo.State.success:
if task.info.result is not None and not hideResult:... | c750238117579236b159bf2389e947e08c8af979 | 28,700 |
def _get_candidate_names():
"""Common setup sequence for all user-callable interfaces."""
global _name_sequence
if _name_sequence is None:
_once_lock.acquire()
try:
if _name_sequence is None:
_name_sequence = _RandomNameSequence()
finally:
_on... | bc42c4af0822fcaa419047644e9d4b9d064a42fd | 28,701 |
def relative_difference(x: np.array, y: np.array) -> np.array:
""" Returns the relative difference estimator for two Lagrange multipliers.
"""
maximum = np.max([x, y])
minimum = np.min([x, y])
difference = maximum-minimum
return np.abs(difference) / np.max(np.abs([x, y, difference, 1.])) | 6b169a3deb3f6ed91958744521aa8028451fb3d8 | 28,702 |
def ConvertPngToYuvBarcodes(input_directory='.', output_directory='.'):
"""Converts PNG barcodes to YUV barcode images.
This function reads all the PNG files from the input directory which are in
the format frame_xxxx.png, where xxxx is the number of the frame, starting
from 0000. The frames should be consecut... | 43cc0dd4126b0699212064e445608c82123ad7b9 | 28,703 |
from pathlib import Path
def _ignore_on_copy(directory, contents): # pylint: disable=unused-argument
"""Provides list of items to be ignored.
Args:
directory (Path): The path to the current directory.
contents (list): A list of files in the current directory.
Returns:
list: A li... | 3a551f6a252406b88fb19c0dc8180631cd5996ce | 28,704 |
def registDeptUser(request):
"""
ํํ์ค ํ๊ธ์์์ฆ ๋ถ์์ฌ์ฉ์ ๊ณ์ ์ ๋ฑ๋กํฉ๋๋ค.
- https://docs.popbill.com/htcashbill/python/api#RegistDeptUser
"""
try:
# ํ๋นํ์ ์ฌ์
์๋ฒํธ
CorpNum = settings.testCorpNum
# ํํ์ค ๋ถ์์ฌ์ฉ์ ๊ณ์ ์์ด๋
DeptUserID = "deptuserid"
# ํํ์ค ๋ถ์์ฌ์ฉ์ ๊ณ์ ๋น๋ฐ๋ฒํธ
DeptUserPW... | e5f923ac4290fd029eafdf6e408d7847be9d0c6b | 28,705 |
import torch
def generate_fake_data_loader():
"""" Generate fake-DataLoader with four batches, i.e. a list with sub-lists of samples and labels.
It has four batches with three samples each. """
samples1 = torch.tensor([[2., 2., 2., 2.], [2., 2., 0., 0.], [0., 0., 2., 2.]])
samples2 = torch.tensor([[1.... | 4d86ab464653f5766a44f03e41fd2c26714cabf1 | 28,709 |
def get_RV_K(
P_days,
mp_Mearth,
Ms_Msun,
ecc=0.0,
inc_deg=90.0,
nsamples=10000,
percs=[50, 16, 84],
return_samples=False,
plot=False,
):
"""Compute the RV semiamplitude in m/s via Monte Carlo
P_days : tuple
median and 1-sigma error
mp_Mearth : tuple
media... | 11cdb7bfeef27d5a05638d74232e105a22fa0222 | 28,711 |
def arc(color, start_angle, stop_angle, width, height,
x=None, y=None, thickness=1, anchor='center', **kwargs):
"""
Function to make an arc.
:param color: color to draw arc
:type color: str or List[str]
:param start_angle: angle to start drawing arc at
:type start_angle: int
:param ... | 42c0a53632315ff03b92c53cbc172a0cfd08f5a7 | 28,712 |
def calculate_shapley_value(g, prob_vals, maxIter=20000):
"""
This algorithm is based on page 29 of the following paper:
https://arxiv.org/ftp/arxiv/papers/1402/1402.0567.pdf
:param g: the graph
:param prob_vals: a list. it contains the weight of each node in the graph
:param maxIter: maximum ... | 41329a17f0914597bcf457ea04e9dc0a7053ae62 | 28,713 |
from typing import List
from typing import Dict
from typing import Any
async def complete_multipart_upload(bucket: str, s3_key: str, parts: List, upload_id: str) -> Dict[str, Any]:
"""Complete multipart upload to s3.
Args:
bucket (str): s3 bucket
s3_key (str): s3 prefix
parts (List): ... | 01441cbc196f594bead4dd9a9b17fe1a3c8bfa4d | 28,714 |
def build_mask(module='A', pixscale=0.03):
"""Create coronagraphic mask image
Return a truncated image of the full coronagraphic mask layout
for a given module.
+V3 is up, and +V2 is to the left.
"""
if module=='A':
names = ['MASK210R', 'MASK335R', 'MASK430R', 'MASKSWB', 'MASKLWB']
... | 97e068fe8eef6e8fdd65b1e426428001cf549332 | 28,715 |
async def update_login_me(
*,
password: str = Body(...),
new_email: tp.Optional[EmailStr] = Body(None, alias='newEmail'),
new_password: tp.Optional[str] = Body(None, alias='newPassword'),
current_user: models.User = Depends(common.get_current_user),
uow: IUnitOfWork = Depends(common.get_uow),
) ... | ec3f56ee474d19a4fd89c51940f3a198322672a1 | 28,716 |
def comp_sharpness(is_stationary, signal, fs, method='din', skip=0):
""" Acoustic sharpness calculation according to different methods:
Aures, Von Bismarck, DIN 45692, Fastl
Parameters:
----------
is_stationary: boolean
True if the signal is stationary, false if it is time varying
... | a8ae39740c90e824081e3979d5ff2b5c96a8ad75 | 28,717 |
def load_hobbies(path='data', extract=True):
"""
Downloads the 'hobbies' dataset, saving it to the output
path specified and returns the data.
"""
# name of the dataset
name = 'hobbies'
data = _load_file_data(name, path, extract)
return data | e60e024d0fe1766c599a3b693f51522cb7d7303a | 28,718 |
def is_viable(individual):
"""
evaluate.evaluate() will set an individual's fitness to NaN and the
attributes `is_viable` to False, and will assign any exception triggered
during the individuals evaluation to `exception`. This just checks the
individual's `is_viable`; if it doesn't have one, this a... | c1e5c839f362e99800dcd1a996be9345cabb4261 | 28,719 |
def combine_counts(hits1,
hits2,
multipliers=None,
total_reads=0,
unmatched_1="Unknown",
unmatched_2="Unknown",
):
""" compile counts into nested dicts """
total_counted = 0
counts = {}
# ke... | 505e91f6538267e40f438926df201cf25cb1a3f9 | 28,720 |
def root():
"""Serves the website home page"""
return render_template("index.html") | 676c966da523108bd9802c2247cf320993815124 | 28,721 |
import string
import random
def getCookie():
"""
This function will return a randomly generated cookie
:return: A cookie
"""
lettersAndDigits = string.ascii_lowercase + string.digits
cookie = 'JSESSIONID='
cookie += ''.join(random.choice(lettersAndDigits) for ch in range(31))
return co... | 6fff76d37921174030fdaf9d4cb8a39222c8906c | 28,722 |
def get_authenticated_igramscraper(username: str, password: str):
"""Gets an authenticated igramscraper Instagram client instance."""
client = Instagram()
client.with_credentials(username, password)
#client.login(two_step_verificator=True)
client.login(two_step_verificator=False)
return client | c8f7cf4500aa82f11cf1b27a161d75a7261ee84a | 28,723 |
def read_in_nn_path(path):
"""
Read in NN from a specified path
"""
tmp = np.load(path)
w_array_0 = tmp["w_array_0"]
w_array_1 = tmp["w_array_1"]
w_array_2 = tmp["w_array_2"]
b_array_0 = tmp["b_array_0"]
b_array_1 = tmp["b_array_1"]
b_array_2 = tmp["b_array_2"]
x_min = tmp["x... | 3f2366ab9fd4b4625c8b7d00b1191429678b466b | 28,724 |
def crop_zeros(array, remain=0, return_bound=False):
"""
Crop the edge zero of the input array.
Parameters
----------
array : numpy.ndarray
2D numpy array.
remain : int
The number of edges of all zeros which you want to remain.
return_bound : str or bool
Select the m... | 13cb5a0a289ef622d3dd663777e6a0d2814b5104 | 28,725 |
def go_info_running(data, info_name, arguments):
"""Returns "1" if go is running, otherwise "0"."""
return '1' if 'modifier' in hooks else '0' | 8027d0106e379156225c87db1959110fcfac6777 | 28,726 |
def letra_mas_comun(cadena: str) -> str:
""" Letra
Parรกmetros:
cadena (str): La cadena en la que se quiere saber cuรกl es la letra mรกs comรบn
Retorno:
str: La letra mรกs comรบn en la cadena que ingresa como parรกmetro, si son dos es la letra alfabรฉticamente
posterior.
"""
letras_e... | c36a753717365164ca8c3089b398d9b6e358ef3f | 28,727 |
def dwt2(image, wavelet, mode="symmetric", axes=(-2, -1)):
"""Computes single level wavelet decomposition for 2D images
"""
wavelet = ensure_wavelet_(wavelet)
image = promote_arg_dtypes(image)
dec_lo = wavelet.dec_lo
dec_hi = wavelet.dec_hi
axes = tuple(axes)
if len(axes) != 2:
r... | 4ee7e1f3c19bb1b0bf8670598f1744b7241b235d | 28,728 |
def recommended_global_tags_v2(release, base_tags, user_tags, metadata):
"""
Determine the recommended set of global tags for the given conditions.
This function is called by b2conditionsdb-recommend and it may be called
by conditions configuration callbacks. While it is in principle not limited
to... | 8396dcc2d54a5e36dfe5485d33ef439059a944c6 | 28,729 |
def plot_corelation_matrix(data):
"""
Plotting the co-relation matrix on the dataset
using the numeric columns only.
"""
corr = data.select_dtypes(include=['float64', 'int64']).iloc[:, 1:].corr()
# Generate a mask for the upper triangle
mask = np.zeros_like(corr, dtype=np.bool)
mask[np.... | 49e89f3ba844f0bf9676bca4051c72ad1305294f | 28,730 |
import urllib
from bs4 import BeautifulSoup
def product_by_id(product_id):
"""
Get Product description by product id
:param product_id: Id of the product
:return:
"""
host = "https://cymax.com/"
site_data = urllib.urlopen(host + str(product_id) + '--C0.htm').read()
soup = BeautifulSou... | 2f2f3abfd0dcf5a124ae4a1bd3975734fbac7783 | 28,731 |
def overlap(X, window_size, window_step):
"""
Create an overlapped version of X
Parameters
----------
X : ndarray, shape=(n_samples,)
Input signal to window and overlap
window_size : int
Size of windows to take
window_step : int
Step size between windows
Returns
... | 4f53be9c87d0ce9800a6e1b1d96ae4786eace78b | 28,732 |
def may_ozerov_depth_3_complexity(n, k, w, mem=inf, hmap=1, memory_access=0):
"""
Complexity estimate of May-Ozerov algorithm in depth 3 using Indyk-Motwani for NN search
[MayOze15] May, A. and Ozerov, I.: On computing nearest neighbors with applications to decoding of binary linear codes.
In: Annual I... | b390a515626185912cbc234fbebd492a0e154bbb | 28,733 |
import json
import copy
def unpack_single_run_meta(storage, meta, molecules):
"""Transforms a metadata compute packet into an expanded
QC Schema for multiple runs.
Parameters
----------
db : DBSocket
A live connection to the current database.
meta : dict
A JSON description of ... | 3a3237067b4e52a5f7cb7d5ecc314061eaaa2b15 | 28,734 |
def getKey(event):
"""Returns the Key Identifier of the given event.
Available Codes: https://www.w3.org/TR/2006/WD-DOM-Level-3-Events-20060413/keyset.html#KeySet-Set
"""
if hasattr(event, "key"):
return event.key
elif hasattr(event, "keyIdentifier"):
if event.keyIdentifier in ["Es... | 0935ad4cb1ba7040565647b2e26f265df5674e1d | 28,735 |
def get_long_season_name(short_name):
"""convert short season name of format 1718 to long name like 2017-18.
Past generations: sorry this doesn't work for 1999 and earlier!
Future generations: sorry this doesn't work for the 2100s onwards!
"""
return '20' + short_name[:2] + '-' + short_name[2:] | 314ef85571af349e2e31ab4d08497a04e19d4118 | 28,736 |
from typing import List
from typing import Any
from typing import Dict
def make_variables_snapshots(*, variables: List[Any]) -> str:
"""
Make snapshots of specified variables.
Parameters
----------
variables : list
Variables to make snapshots.
Returns
-------
snapshot_name : ... | d6a7bf5be51ebe7f4fb7985b2a440548c502d4ec | 28,737 |
def sext_to(value, n):
"""Extend `value` to length `n` by replicating the msb (`value[-1]`)"""
return sext(value, n - len(value)) | 683316bd7259d624fddb0d9c947c7a06c5f28c7e | 28,738 |
def parse_matching_pairs(pair_txt):
"""Get list of image pairs for matching
Arg:
pair_txt: file contains image pairs and essential
matrix with line format
image1 image2 sim w p q r x y z ess_vec
Return:
list of 3d-tuple contains (q=[wpqr], t=[xyz], essential matrix)
... | 6697e63a091b23701e0751c59f8dc7fe0e582a97 | 28,739 |
import threading
from typing import OrderedDict
def compile_repo_info(repos, all=False, fetch=False):
"""Compiles all the information about found repos."""
# global to allow for threading work
global git_info
git_info = {}
max_ = len(repos)
threads = []
for i, repo in enumerate(repos):
... | b3cbdcdd53ce2c5274990520756390f396156aaa | 28,740 |
def histogram2d(x, y, bins=10, range=None, weights=None, density=False): # pylint: disable=redefined-builtin
"""
Computes the multidimensional histogram of some data.
Note:
Deprecated numpy argument `normed` is not supported.
Args:
x (Union[list, tuple, Tensor]): An array with shape `(... | 8b537168cb7248ccd2959c95ae4fb742b81aa225 | 28,741 |
def get_project_arg_details():
"""
**get_project_arg_details**
obtains project details from arguments and then returns them
:return:
"""
project_id = request.args.get('project_id')
names = request.args.get('names')
cell = request.args.get('cell')
email = request.args.get(... | 5efcaebf0efe89a5d8fa5f52d50777041b545177 | 28,742 |
def vibronic_ls(x, s, sigma, gamma, e_vib, kt=0, n_max=None, m_max=None):
"""
Produce a vibronic (Frank-Condom) lineshape.
The vibronic transition amplitude computed relative to 0 (ie: relative to
the electronic transition energy). Lines are broadened using a voigt
profile.
Parameter... | 428f0c44566cf3a824902fc9f7fb8012089d1b89 | 28,743 |
import re
import requests
def handleFunction(command,func):
"""
Function to calculate, Translate
"""
try:
# re.search(r"(?i)"+func,' '.join(SET_OF_FUNCTIONS))
if("calculate" == func.lower()):
func,command = command.split()
try:
return eval(command)
except:
return "Sorry! We are unable to cal... | c5ff05b0b31a7441f7efaf9ce76c496f3f708eea | 28,744 |
import json
def auth():
"""returns worker_id !!!currently!!! does not have auth logic"""
response_body = {}
status_code = 200
try:
auth_token = request.args.get("auth_token", None)
resp = fl_events_auth({"auth_token": auth_token}, None)
resp = json.loads(resp)["data"]
excep... | bbbeb0dbf7401b11e56399890f43a799f859eb87 | 28,745 |
def get_templates_environment(templates_dir):
"""Create and return a Jinja environment to deal with the templates."""
env = Environment(
loader=PackageLoader('charmcraft', 'templates/{}'.format(templates_dir)),
autoescape=False, # no need to escape things here :-)
keep_trailin... | 9f3571ce4cb8f18f64912e6c259bc2f1022698f2 | 28,747 |
import numpy as np
def return_U_given_sinusoidal_u1(i,t,X,u1,**kwargs):
"""
Takes in current step (i), numpy.ndarray of time (t) of shape (N,), state numpy.ndarray (X) of shape (8,), and previous input scalar u1 and returns the input U (shape (2,)) for this time step.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
... | b5faba122af139f29f20dbce983b84fe5c0c277c | 28,748 |
def verify(s):
"""
Check if the cube definition string s represents a solvable cube.
@param s is the cube definition string , see {@link Facelet}
@return 0: Cube is solvable<br>
-1: There is not exactly one facelet of each colour<br>
-2: Not all 12 edges exist exactly once<br>
... | d3e765af153a7400d84e59c72d292a9ccd9170f5 | 28,749 |
from typing import cast
import copy
def copy_jsons(o: JSONs) -> MutableJSONs:
"""
Make a new, mutable copy of a JSON array.
>>> a = [{'a': [1, 2]}, {'b': 3}]
>>> b = copy_jsons(a)
>>> b[0]['a'].append(3)
>>> b
[{'a': [1, 2, 3]}, {'b': 3}]
>>> a
[{'a': [1, 2]}, {'b': 3}]
"""
... | c9fffefe0dd541e20a7a3bef503e0b1af847909d | 28,750 |
def string_to_dot(typed_value):
# type: (TypedValue) -> Tuple[List[str], List[str]]
"""Serialize a String object to Graphviz format."""
string = f'{typed_value.value}'.replace('"', r'\"')
dot = f'_{typed_value.name} [shape="record", color="#A0A0A0", label="{{{{String | {string}}}}}"]'
return [dot], ... | 287d2c886aca5ca940b323b751af91e33ed54fc4 | 28,751 |
def resolve_country_subdivisions(_, info, alpha_2):
"""
Country resolver
:param info: QraphQL request context
:param alpha_2: ISO 3166 alpha2 code
:param code: ISO 3166-2 code
"""
return CountrySubdivision.list_for_country(country_code=alpha_2) | 56ffa7343f1da686819c85dee54770cd4d1564d3 | 28,752 |
from typing import Tuple
def bool2bson(val: bool) -> Tuple[bytes, bytes]:
"""Encode bool as BSON Boolean."""
assert isinstance(val, bool)
return BSON_BOOLEAN, ONE if val else ZERO | 3d4456f6db88939966997b8a49c3d766b1ef4ba1 | 28,753 |
def isbn13_to_isbn10 (isbn_str, cleanse=True):
"""
Convert an ISBN-13 to an ISBN-10.
:Parameters:
isbn_str : string
The ISBN as a string, e.g. " 0-940016-73-6 ". It should be 13
digits after normalisation.
cleanse : boolean
If true, formatting will be stripped from the ISBN before
conversion.
:Re... | b39d6d9f7a850a8b0edbb6b9502f4d6bb73f8848 | 28,754 |
import json
def import_data():
"""Import datasets to internal memory"""
with open('data/names.json') as f:
data_names = json.load(f)
with open('data/issues.json') as f:
data_issues = json.load(f)
with open('data/disasters.json') as f:
data_disasters = json.load(f)
with open... | 11db10c2c56b6b714ecffa57510c9a79abfa1d86 | 28,755 |
def synthesize_ntf_dunn(order=3, osr=64, H_inf=1.5):
"""
Alias of :func:`ntf_dunn`
.. deprecated:: 0.11.0
Function has been moved to the :mod:`NTFdesign` module with
name :func:`ntf_dunn`.
"""
warn("Function superseded by ntf_dunn in "
"NTFdesign module", PyDsmDeprecationWarn... | 2920ec676ab070ebb5f7c95e245baf078b723fae | 28,756 |
def schedule_notification() -> str:
"""Randomly select either news or covid stats to add to the notifcation column,
if there is already a 'news' item in the notificaitons column then it will
update the item with a newer piece of news"""
#NEWS
news_title, news_content = get_news()
notif_exists =... | 9aed44251170dc124f71b11bf482ef009ebe973e | 28,757 |
def _parse_hexblob(blob: str) -> bytes:
"""
Binary conversions from hexstring are handled by bytes(hstr2bin()).
:param blob:
:return:
"""
return bytes(hstr2bin(blob)) | e49348f7cb15bbba850dbf05c0a3625427d0ac2d | 28,758 |
from typing import List
from typing import Dict
def _row_to_col_index_dict(headers: List[Cell]) -> Dict[str, int]:
"""Calculate a mapping of cell contents to column index.
Returns:
dict[str, int]: {MFP nutrient name: worksheet column index} mapping.
int: N
"""
return {h.value: h.col - ... | 11f7a68cd211b216d2a27850be99291cc830d52f | 28,759 |
def preprocess_cat_cols(X_train, y_train, cat_cols=[], X_test=None,
one_hot_max_size=1, learning_task=LearningTask.CLASSIFICATION):
"""Preprocess categorial columns(cat_cols) in X_train
and X_test(if specified) with cat-counting(the same as in catboost)
or with one-hot-encoding,
depends ... | 10402fe0fd534eb73598fa99a1202b970202f2c0 | 28,760 |
def get_start_time(period, time_zone=None):
"""Doc."""
today = pd.Timestamp.today(tz=time_zone or 'Europe/Stockholm')
if period == 'thisyear':
return pd.Timestamp(f'{today.year}0101').strftime('%Y-%m-%d %H:%M:%S')
elif period in DAYS_MAPPER:
return (today - pd.Timedelta(days=DAYS_MAPPER.... | c5e9ab4543f813f7210bc278e83d9c4a554d242b | 28,761 |
def setup_textbox(parent,
font="monospace",
width=70, height=12):
"""Setup for the textboxes, including scrollbars and Text widget."""
hsrl = ttk.Scrollbar(parent, orient="horizontal")
hsrl.pack(side=tk.BOTTOM, fill=tk.X)
vsrl = ttk.Scrollbar(parent)
vsrl.pack(sid... | 674bc72eefacc16485a4b369535f1253187e5ded | 28,762 |
def generate_mock_statuses(naive_dt=True, datetime_fixtures=None):
"""
A dict of statuses keyed to their id. Useful for mocking an API response.
These are useful in``Timeline`` class testing.
May be set to have a utc timezone with a ``False`` value for the ``naive_dt`` argument.
"""
mock_status... | aca7bd235ef6fd404f8da894b6917636d7895dcb | 28,763 |
import hashlib
def hashlib_mapper(algo):
"""
:param algo: string
:return: hashlib library for specified algorithm
algorithms available in python3 but not in python2:
sha3_224 sha3_256, sha3_384, blake2b, blake2s, sha3_512, shake_256, shake_128
"""
algo = algo.lower()
if algo == "... | 56830caccd0b3f88982bfe09a8789002af99c1e7 | 28,765 |
def partition_cells(config, cells, edges):
""" Partition a set of cells
- cells -- A DataFrame of cells
- edges -- a list of edge times delimiting boundaries between cells
Returns a DataFrame of combined cells, with times and widths adjusted to account for missing cells
"""
# get indices of... | c8532cbf148802b482380f8978dbc8d9d3b1b35f | 28,766 |
from typing import List
from typing import Union
def timing_stats(results: List[Result]) -> List[str]:
"""Calculate and format lines with timings across completed results."""
def percentile(data: List[float], percent: int) -> Union[float, str]:
if not data:
return '-'
data_sorted =... | 08d671b2866674924dc070dda2e7e85a4c56c064 | 28,767 |
import logging
def analyse_gamma(
snps_object,
output_summary_filename,
output_logger,
SWEEPS,
TUNE,
CHAINS,
CORES,
N_1kG,
fix_intercept=False,
):
"""
Bayesian hierarchical regression on the dataset with the gamma model.
:param snps_object: snps instance
:param ou... | fac6111e4ad87d63d89d2942e5cfc28023950117 | 28,768 |
def dpc_variant_to_string(variant: _DV) -> str:
"""Convert a Basix DPCVariant enum to a string.
Args:
variant: The DPC variant
Returns:
The DPC variant as a string.
"""
return variant.name | 2eb7eeff47eb36bea47714b9e233f3d286925d3b | 28,769 |
import secrets
from datetime import datetime
async def refresh_token(request: web.Request) -> web.Response:
""" Refresh Token endpoints """
try:
content = await request.json()
if "token" not in content:
return web.json_response({"error": "Wrong data. Provide token."}, status=400)
... | a8008a33793ccb7b34900724b62fb3add061fa30 | 28,770 |
def get_my_choices_projects():
""" Retrieves all projects in the system
for the project management page
"""
proj_list = Project.objects.all()
proj_tuple = []
counter = 1
for proj in proj_list:
proj_tuple.append((counter, proj))
counter = counter + 1
return proj_tuple | f35563adb12aff32ac1b60152b3085c63dc839f0 | 28,771 |
import math
def normalDistributionBand(collection, band, mean=None, std=None,
name='normal_distribution'):
""" Compute a normal distribution using a specified band, over an
ImageCollection. For more see:
https://en.wikipedia.org/wiki/Normal_distribution
:param band: the nam... | 57b0d6beb590126253c4934e403487bd69c7c094 | 28,773 |
import torch
def compute_ctrness_targets(reg_targets):
"""
:param reg_targets:
:return:
"""
if len(reg_targets) == 0:
return reg_targets.new_zeros(len(reg_targets))
left_right = reg_targets[:, [0, 2]]
top_bottom = reg_targets[:, [1, 3]]
ctrness = (left_right.min(dim=-1)[0] / l... | 538a63b6adcd73fbd601d6e61eea5f27642746fa | 28,774 |
import hashlib
import hmac
import base64
def create_hmac_signature(key:bytes, data_to_sign:str, hashmech:hashlib=hashlib.sha256) -> str:
"""
Creates an HMAC signature for the provided data string
@param key: HMAC key as bytes
@param data_to_sign: The data that needs to be signed
@param hashmech: ... | 0c3f5b8bef6e3330e8c24fca62ce2707b0de5286 | 28,775 |
def CV_range(
bit_depth: Integer = 10, is_legal: Boolean = False, is_int: Boolean = False
) -> NDArray:
"""
Returns the code value :math:`CV` range for given bit depth, range legality
and representation.
Parameters
----------
bit_depth
Bit depth of the code value :math:`CV` range.
... | e1eb079e4e75cb7b8353d88e13bb7eb82d15428c | 28,776 |
import torch
def bw_transform(x):
"""Transform rgb separated balls to a single color_channel."""
x = x.sum(2)
x = torch.clamp(x, 0, 1)
x = torch.unsqueeze(x, 2)
return x | 3ecec3ada4b75486ff96c30890e8a3e173ca7d31 | 28,777 |
def fom(A, b, x0=None, maxiter=None, residuals=None, errs=None):
"""Full orthogonalization method
Parameters
----------
A : {array, matrix, sparse matrix, LinearOperator}
n x n, linear system to solve
b : {array, matrix}
right hand side, shape is (n,) or (n,1)
x0 : {array, matri... | b95ac8b383150e57ffd599fb2e77608dd7503d9d | 28,778 |
def get_gprMax_materials(fname):
"""
Returns the soil permittivities. Fname is an .in file.
"""
materials = {'pec': 1.0, # Not defined, usually taken as 1.
'free_space': 1.000536}
for mat in get_lines(fname, 'material'):
props = mat.split()
materials[props[-1]] = f... | f56e720c5c2209b67ca521b779ce9472665beb6a | 28,779 |
import random
def generate_utt_pairs(librispeech_md_file, utt_pairs, n_src):
"""Generate pairs of utterances for the mixtures."""
# Create a dict of speakers
utt_dict = {}
# Maps from speaker ID to list of all utterance indices in the metadata file
speakers = list(librispeech_md_file["speaker_ID"]... | 9079fa35b961de053c86b08527085e8eb84609b8 | 28,780 |
def simpson(so, spl: str, attr: str, *, local=True, key_added=None, graph_key='knn', inplace=True) -> None:
"""Computes the Simpson Index on the observation or the sample level
Args:
so: SpatialOmics instance
spl: Spl for which to compute the metric
attr: Categorical feature in SpatialO... | d10fd40305f384d75f8c33d391a87f6b5c8adcd5 | 28,781 |
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