content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def is_stable(A, domain='z'):
"""Determines if a linear state-space model is stable from eigenvalues of `A`
Parameters
----------
A : ndarray(n,n)
state matrix
domain : str, optional {'z', 's'}
'z' for discrete-time, 's' for continuous-time state-space models
returns
------... | 8b073fa021b0f50363d4f5f1a7bf3722a62ae71b | 3,640,700 |
def email_sent_ipn(path: str) -> tuple:
"""
**email_sent_ipn**
Delivered ipn for mailgun
:param path: organization_id
:return: OK, 200
"""
# NOTE: Delivered ipn will end up here
if path == "delivered":
pass
elif path == "clicks":
pass
elif path == "op... | 4bbfed4f86916ddc2b68ade0c8739e25a562bbda | 3,640,701 |
import sys
def decode(path: str) -> str:
"""
utility fct to encode/decode
"""
return path.encode(sys.stdout.encoding, 'ignore').decode(sys.stdout.encoding) | 9e75e04928e7df4646feaed85a799a137693fa77 | 3,640,702 |
import json
def load_posts_view(request):
"""Load posts view, handles asynchronous queries to retrieve more posts.
"""
if request.method == 'GET':
results, start = get_more_posts(request.GET)
json_result = json.dumps({'posts': results,
'start': start
... | 832f2a04b23eb78ad25ad7db2d3cabfdaa61b075 | 3,640,703 |
def create_dataset(m, timestep, var='all', chunks=(10, 300, 300)):
"""
Create xarray Dataset from binary model data
for one time step. This also incorporates all model
grid information and dimensions, regardless of the variable selected.
Parameters
----------
m : LLCRegion
Model cla... | 02dd6a4e7ff520e5ae65c7a3a9e3bd2b92d58629 | 3,640,704 |
def fetchnl2bash(m:Manager, shuffle:bool=True)->DRef:
"""
FIXME: Unhardcode '3rdparty'-based paths
"""
allnl=fetchlocal(m,
path=join('3rdparty','nl2bash_essence','src','data','bash','all.nl'),
sha256='1db0c529c350b463919624550b8f5882a97c42ad5051c7d49fbc496bc4e8b770',
mode='asis',
output=[promise... | d99376bbe2dbc2250281eccb9b5d7108cf9f9c84 | 3,640,705 |
def mummer_cmds_four(path_file_four):
"""Example MUMmer commands (four files)."""
return MUMmerExample(
path_file_four,
[
"nucmer --mum -p nucmer_output/file1_vs_file2 file1.fna file2.fna",
"nucmer --mum -p nucmer_output/file1_vs_file3 file1.fna file3.fna",
"n... | 65262a16f47b952796f79dcb9bba37c5dcbaed0b | 3,640,706 |
def Exponweibull(a=1, c=1, scale=1, shift=0):
"""
Expontiated Weibull distribution.
Args:
a (float, Dist) : First shape parameter
c (float, Dist) : Second shape parameter
scale (float, Dist) : Scaling parameter
shift (float, Dist) : Location parameter
"""
dist = core... | 64871830101df96f8148ef6ee0b8735813793306 | 3,640,707 |
def authed_request_for_id(gplus_id, request):
"""Adds the proper access credentials for the specified user and then makes an HTTP request."""
# Helper method to make retry easier
def make_request(retry=True):
token = get_access_token_for_id(gplus_id)
request.headers['Authorization'] = 'Bear... | f727cc818fd3d5b70fba80b00dfb09cf1f182275 | 3,640,708 |
def _bool_method_SERIES(op, name, str_rep):
"""
Wrapper function for Series arithmetic operations, to avoid
code duplication.
"""
def na_op(x, y):
try:
result = op(x, y)
except TypeError:
if isinstance(y, list):
y = lib.list_to_object_array(y)
... | d6dec673d9a0f8384c3510bdda449f8e4157c96e | 3,640,709 |
def get_playlist_by_id(playlist_id):
""" Returns a playlist by playlist id """
return Playlist.query.filter(Playlist.playlist_id == playlist_id).first() | 28fd295a5d096b1da40391193e6333cc48b14ea2 | 3,640,710 |
def section_cfield(xs, x_a, c_field, rmax = 60e3):
"""
extract a section of a sound speed transcet for use in xmission calculation
"""
x_i = np.bitwise_and(x_a >= xs, x_a <= xs + rmax)
return x_a[x_i], c_field[:, x_i] | c4c213293f7aee7735a9a6209f671aae6d8e3989 | 3,640,711 |
def shared_dropout(shape, use_noise, trng, value):
"""
Shared dropout mask (pervasive dropout)
:param shape:
:param use_noise:
:param trng:
:param value:
:return:
"""
return tensor.switch(use_noise,
trng.binomial(shape, p=value, n=1,
... | 51373285b3c708cedd1ebf2a613237deaa7b6dab | 3,640,712 |
def setup_flow_assembler(gb, method, data_key=None, coupler=None):
"""Setup a standard assembler for the flow problem for a given grid bucket.
The assembler will be set up with primary variable name 'pressure' on the
GridBucket nodes, and mortar_flux for the mortar variables.
Parameters:
gb: G... | 6e1baaf91e06679ef760932f6ae27e0c606e4f21 | 3,640,713 |
def get_article(article_id: str, db: Session = Depends(deps.get_db),
current_user: schemas.UserVerify = Depends(
deps.get_current_user)) -> JSONResponse:
""" Return Single Article"""
data = crud_articles.get_article(article_id=article_id, db=db)
if data is None:
r... | e78af6052b112c5da5811a0c92fe462743bb5c7e | 3,640,714 |
def _get_sp_instance():
"""Create an spotify auth_manager and check whether the current user has
a token (has been authorized already). If the user has a token, then they
are authenticated -- return their spotipy instance. If the user does not have
a token, then they are not authenticated -- raise an ex... | b2117c709169192626efdf2b699a9a1c2c501ecc | 3,640,715 |
def get_func_global(op_type, dtype):
"""Generate function for global address space
Used as `generator(op_type, dtype)`.
"""
op = getattr(dppy.atomic, op_type)
def f(a):
op(a, 0, 1)
return f | 72816c78bc36f7aa630551ae161fa0870acefe36 | 3,640,716 |
def klucb(x, d, div, upperbound, lowerbound=-float("inf"), precision=1e-6):
"""The generic klUCB index computation.
Input args.:
x,
d,
div:
KL divergence to be used.
upperbound,
lowerbound=-float('inf'),
precision=1e-6,
"""
l = max(x, lowerbound)
u = upperbound
while... | 82aa51e248568d201e0d9d5621bf043532df8572 | 3,640,717 |
def convert_pk_to_index(pk_tuples, indices):
"""
For a list of tuples with elements referring to pk's of indices,
convert pks to 0-index values corresponding to order of queryset
:param pk_tuples: list of tuples [(row_pk, col_pk), ... ]
:param indices: list of querysets
:return: list of tuples [... | 81837ded50d4cd086b9330ea5c709fb3bd93ca0f | 3,640,718 |
from typing import Union
def device_path_to_str(path: Union[bytes, str]) -> str:
"""
Converts a device path as returned by the fido2 library to a string.
Typically, the path already is a string. Only on Windows, a bytes object
using an ANSI encoding is used instead. We use the ISO 8859-1 encoding t... | 76d0d3d50e978d998ef68e0c509c3933f94778d9 | 3,640,719 |
def empirical(X):
"""Compute empirical covariance as baseline estimator.
"""
print("Empirical")
cov = np.dot(X.T, X) / n_samples
return cov, np.linalg.inv(cov) | 67c8c1f42590ee6c8d56f5f1e53253c5eff74376 | 3,640,720 |
def emitir_extrato(contas, numero_conta, movimentacoes, data_inicial):
"""
Retorna todas as movimentações de <movimentacoes> feitas pela conta
com o <numero_conta> a partir da <data_inicial>
"""
historico_movimentacoes = []
if numero_conta in contas:
minhas_movimentacoes = movimentac... | 0caa46aaed0ccfa506f8caa9b82625649d116ce1 | 3,640,721 |
def wavelength_to_energy(wavelength):
"""
Converts wavelength (A) to photon energy (keV)
"""
return 12.39842/wavelength | 4e2d11f2de8ed4890df5d885801cd492644817d8 | 3,640,722 |
def calculate_hash_512(filepath, verbose):
"""
SHA512 Hash Digest
"""
if verbose:
print 'Calculating hash...'
sha512_hash = hashlib.sha512()
with open(filepath, 'rb') as f:
statinfo = os.stat(filepath)
block_size = 100 * (2**20) #Magic number: 100 * 1MB blocks
... | 4bf153275d9791112f39d3629e9cc94f54177dc4 | 3,640,723 |
def _crop_after_rotation(im, angle, xres, yres, surroundings):
"""Crop image to the bounding box of bite's surroundings.
Arguments:
im: PIL.Image, rotated map part
angle: by which the map has been rotated, in degrees (counterclockwise)
xres: width of one tile in pixels
yres: height of one tile... | eeeda2c5c8d868e813a67584c72561560409e1b3 | 3,640,724 |
import copy
def get_custom_scorer(metric, gib=True, needs_proba=False, needs_threshold=False):
"""Get a scorer from a str, func or scorer.
Scorers used by ATOM have a name attribute.
Parameters
----------
metric: str, func or scorer
Name, metric or scorer to get ATOM's scorer from.
... | a698798302ec0ed7ad469b76d6893e85e669905e | 3,640,725 |
def julian_day(t='now'):
"""
Wrap a UTC -> JD conversion from astropy.
"""
return Time(parse_time(t)).jd | fa2f0d707798227e8e7f67b21cf2e4dc42308093 | 3,640,726 |
from typing import Counter
def add_stop_words(dataframe: pd.DataFrame,
k_words: int) -> list:
"""
Получить список стоп-слов, которые наиболее часто встречаются в документе
:param dataframe:
:param k_words: кол-во наиболее часто повторяющихся уникальных слов
:return:
"""
... | 3ca7fbe1221b55e2a072d49f01c553af1786ca8f | 3,640,727 |
import torch
def get_batch(data_iterator):
"""Build the batch."""
# Items and their type.
keys = ['text', 'types', 'labels', 'is_random', 'loss_mask', 'padding_mask']
datatype = torch.int64
# Broadcast data.
data = next(data_iterator) if data_iterator is not None else None
data_b = mpu.b... | fad3b181c685e3e57fa185c1eb790517536527ec | 3,640,728 |
import os
def outcomes_by_resected_lobe(directory='L:\\', filename='All_Epilepsy_Ops_CROSSTAB_Statistics_YAY_2019.xlsx',
lobes=['T Lx', 'T Lesx']):
"""
Creates the list of Gold_standard post-operative ILAE 1 at all follow up years MRNs in patients who had only
specific lobe r... | 30c35d288beadc15be31d19bab8f8ce7e28ee599 | 3,640,729 |
def pool(sparkdf, start_column, end_column, var):
"""
Generate pools and calculate maximum var unpooled.
:param sparkdf: Input Spark dataframe.
:param start_column: Start time column name.
:param end_column: End time column name.
:param var: Variable for which to calculate metric.
:return: A... | 913094bebc6f91ad023d83186084d858a7332531 | 3,640,730 |
def jwt_response_payload_handler(token, user=None, request=None):
"""
自定义jwt返回
def jwt_response_payload_handler(token, user=None, request=None):
return {
'token': token,
'user': UserSerializer(user, context={'request': request}).data
}
:param token:
:param... | 972f4cbd39d9bd049fcd7a99bfc168e6c825572a | 3,640,731 |
import requests
def query_yelp_lookup(biz_id):
""" Lookup resturant using id """
headers = {'Authorization': ('Bearer '
'w5JFtwCUKq05GlSpm8cKo51dBYDQ6r9tyzo-qRsKt4wDyB5'
'_ro6gW5gnG9hS6bvnNHNxOQLHfw7o_9S1e86nkvgcU7DQI_'
'sM6GVt9rqcq_rRYKtagQrexuH0zsU0WXYx')}
ur... | ab2087d42833f0092229870ab3208a24bd041b95 | 3,640,732 |
def dashboard(request, condition='recent'):
"""Dashboard"""
post_count = settings.DASHBOARD_POST_COUNT
comment_count = settings.DASHBOARD_COMMENT_COUNT
if condition == 'recent':
order = '-id'
elif condition == 'view':
order = '-view_count'
elif condition == 'like':
order... | fc5422bf580a4608e921b7d59caf7f0ea58a50fd | 3,640,733 |
def read_manifest(path):
"""Read dictionary of workflows from the Packal manifest.xml file."""
workflows = {}
tree = ET.parse(path)
root = tree.getroot()
for workflow in root:
data = {"packal": True}
for child in workflow:
if child.tag == "short":
data["de... | 8f91126f4a48c0b1af357487ffe791ba790c7745 | 3,640,734 |
def _load_v1_txt(path):
"""Parses a SIF V1 text file, returning numpy arrays.
Args:
path: string containing the path to the ASCII file.
Returns:
A tuple of 4 elements:
constants: A numpy array of shape (element_count). The constant
associated with each SIF element.
centers: A n... | 9f7ea3f0059ef3688cc962e9836a558debebf80f | 3,640,735 |
def split_model_name(model):
"""
Split model names by _
Takes into account packages with _ and processor types with _
"""
model = model[:-3].replace('.', '_')
# sort by key length so that nertagger is checked before tagger, for example
for processor in sorted(ending_to_processor.keys(), key... | 305a70899eb8eb3c5beca4c7e7403010a008a80d | 3,640,736 |
from .divine1983 import JupiterD4Field
from .distributions import DG83Distribution
from .integrate import FormalRTIntegrator
from .synchrotron import NeuroSynchrotronCalculator
def dg83_setup(
ghz = 95,
lat_of_cen = 10,
cml = 20,
n_alpha = 10,
n_E = 10,
E0 = 0.1,
... | 94aea682df900d600e922ff560109255e2b69ac7 | 3,640,737 |
def compute() -> int:
"""
Returns the sum of all numbers whose
sum of the factorials of all digits
add up to the number itself.
>>> compute()
40730
"""
return sum(
num
for num in range(3, 7 * factorial(9) + 1)
if sum_of_digit_factorial(num) == num
) | c2460158eb7d32142b4f59801bdc307a0ba1d4ff | 3,640,738 |
import heapq
def dijkstra(matrix, start=None, end=None):
"""
Implementation of Dijkstra algorithm to find the (s,t)-shortest path between top-left and bottom-right nodes
on a nxn grid graph (with 8-neighbourhood).
NOTE: This is an vertex variant of the problem, i.e. nodes carry weights, not edges.
... | 96338e6c65e1ff88025971361e2b36c0f1efe2af | 3,640,739 |
def is_finally_visible_segm(*args):
"""is_finally_visible_segm(segment_t s) -> bool"""
return _idaapi.is_finally_visible_segm(*args) | 9050bd583208824859e71e84f02169237b3ac9f2 | 3,640,740 |
from vivofoundation import vivo_sparql_query
def make_course_dictionary(debug=False):
"""
Make a course dictionary from VIVO contents. Key is course number
such as ABF2010C. Value is URI.
"""
query = """
SELECT ?x ?label ?coursenum
WHERE {
?x a ufVivo:Course .
?x ufVivo:cours... | cfe014f41aeac18116f6650cb2cb8b1200469eb9 | 3,640,741 |
def get_undisbursed_principal(loan):
"""Gets undisbursed principal"""
principal = frappe.get_value("Microfinance Loan", loan, "loan_principal")
if not principal:
raise frappe.DoesNotExistError("Loan: {} not found".format(loan))
return principal - get_disbursed(loan) | 7829b93eb1e6298e8640290c94b2b2aacb0de8bd | 3,640,742 |
def northing_and_easting(dictionary):
"""
Retrieve and return the northing and easting strings to be used as
dictionary keys
Parameters
----------
dictionary : dict
Returns
-------
northing, easting : tuple
"""
if not 'x' and 'y' in dictionary.keys():
northing = 'l... | 2f41d8b681d27f6ef29265c1945591ea18bba79f | 3,640,743 |
import sys
def decode_path(name):
""" Attempt to decode path with correct encoding """
return name.decode(sys.getfilesystemencoding()) | 14da12b60c1f734e59ee5daec249c3658f3a23e4 | 3,640,744 |
import os
import pickle
def save_account(account):
"""
Function that serializes the account such
that it can be saved.
"""
root_dir = "./accounts/"+account.name+"/"
if not os.path.exists(root_dir):
os.makedirs(root_dir)
with open(root_dir+account.name, "wb+") as f:
pickle.... | 08e0253764695dd71e767190c70dd32189839988 | 3,640,745 |
import math
def affine(p, scale, theta, offset):
""" Scale, rotate and translate point """
return arcpy.Point((p.X * math.cos(theta) - p.Y * math.sin(theta)) * scale.X + offset.X,
(p.X * math.sin(theta) + p.Y * math.cos(theta)) * scale.Y + offset.Y) | 2d1cd34ed94ee0c4e7ecbb786510c0165b9fca9d | 3,640,746 |
def GetMarkedPos(slot):
"""
Get marked position
@param slot: slot number: 1..1024 if the specifed value is <= 0
range, IDA will ask the user to select slot.
@return: BADADDR - the slot doesn't contain a marked address
otherwise returns the marked address
"""
curlo... | 2c6fc7bac4a389c0cafd119fbef537e135b7f745 | 3,640,747 |
def elslib_CylinderParameters(*args):
"""
* parametrization P (U, V) = Location + V * ZDirection + Radius * (Cos(U) * XDirection + Sin (U) * YDirection)
:param Pos:
:type Pos: gp_Ax3
:param Radius:
:type Radius: float
:param P:
:type P: gp_Pnt
:param U:
:type U: float &
:param... | 5fa697d09866747be2ef98b1b913b7aeb59fcf79 | 3,640,748 |
def totaled_no_review_url(cc, sql_time_specification): # pragma: no cover
"""Counts the number of commits with no review url in a given timeframe
Args:
cc(cursor)
sql_time_specification(str): a sql command to limit the dates of the
returned results
Return:
count(in... | 027f49b13316ecb36eed3e7dde880848b261e3b4 | 3,640,749 |
import warnings
def is_sat(formula, solver_name=None, logic=None, portfolio=None):
""" Returns whether a formula is satisfiable.
:param formula: The formula to check satisfiability
:type formula: FNode
:param solver_name: Specify the name of the solver to be used
:type solver_name: string
:... | 9121747de68aa531c7c7e9c9f683cd1f1518e54b | 3,640,750 |
import math
def bounds(*tile):
"""Returns the bounding box of a tile
Parameters
----------
tile : Tile or tuple
May be be either an instance of Tile or 3 ints (X, Y, Z).
Returns
-------
LngLatBbox
"""
tile = _parse_tile_arg(*tile)
xtile, ytile, zoom = tile
Z2 = ... | ed2eb5865d21033029ddfcdd133663c9d222687d | 3,640,751 |
from typing import Tuple
def http(func: str, arg: Tuple[str]) -> int:
"""Summary.
Args:
func (str): Path to a function.
arg (Tuple[str]): Description
Returns:
int: Description
"""
return ERGO_CLI.http(func, *list(arg)) | 1e46eefa4101ff63d2d3851bacbfd472e1d3c7ce | 3,640,752 |
import time
def isMWS_bhb(primary=None, objtype=None,
gaia=None, gaiaaen=None, gaiadupsource=None, gaiagmag=None,
gflux=None, rflux=None, zflux=None,
w1flux=None, w1snr=None, maskbits=None,
gnobs=None, rnobs=None, znobs=None,
gfracmasked=None, rfra... | 1a4f4287263ee64497ebdf882cbe3b782840b8f3 | 3,640,753 |
def bernpoly(n, z):
"""
Evaluates the Bernoulli polynomial `B_n(z)`.
The first few Bernoulli polynomials are::
>>> from sympy.mpmath import *
>>> mp.dps = 15
>>> for n in range(6):
... nprint(chop(taylor(lambda x: bernpoly(n,x), 0, n)))
...
[1.0]
... | 60da6461246e48f8b5ff7172f7d244c59b9ad7ed | 3,640,754 |
def sort(obs, pred):
"""
Return sorted obs and pred time series'
"""
obs = obs.sort_values(ascending=True)
pred = pred.sort_values(ascending=True)
return obs,pred | 11c44c1fd605611a2722321b3c3d58a822b9c643 | 3,640,755 |
import random
def random_point_of_triangle(vertices):
"""Compute a random point of the triangle with given vertices"""
p, q, r = vertices
pq = q-p
pr = r-p
while True:
x = random.random()
y = random.random()
if x + y <= 1:
return p + pq*x + pr*y | ba3bf9183ddae4a16561a06b6f2455ce0ede6c8f | 3,640,756 |
import time
def get_minutes(hour:str) -> int:
""" Get total number of minutes from time in %H:%M .
Args:
hour (str): String containing time in 24 hour %H:%M format
Returns:
int: Returns total number of minutes
"""
t = time.strptime(hour, '%H:%M')
minutes = t[3] * 60 + t[4]
... | 069835bdb6b0919d6206e0379a1933986ad2d5bd | 3,640,757 |
from typing import Tuple
import logging
def get_rotation_scale_from_transformation(matrix: np.array) -> Tuple[np.array,np.array] :
"""
This function breaks the given transformation matrix into a Rotation matrix and a Scale matrix
as described in "As-Rigid-As-Possible Shape Interpolation" by Alexa et al
... | c48ed5d1e880c7caf79e009bfeb84c95de8007e3 | 3,640,758 |
def calc_check_digit(number):
"""Calculate the check digit."""
weights = (7, 9, 8, 6, 5, 4, 3, 2)
check = sum(w * int(n) for w, n in zip(weights, number)) % 11
return str((10 - check) % 9 + 1) | eec82a1e6cec8baf513db16e672294df79ce4b9f | 3,640,759 |
import json
def leave_studygroup(request):
"""
Remove a student from the list of participants of a study group.
"""
body = json.loads(request.body)
group_id = body['id']
token = body['token']
rcs = Student.objects.get(token=token).rcs
group = Studygroup.objects.get(id=group_id)
p... | 705c63640c11485dc68ce69d7757642a84c5798c | 3,640,760 |
def list_revisions_courses(request_ctx, course_id, url, per_page=None, **request_kwargs):
"""
List the revisions of a page. Callers must have update rights on the page in order to see page history.
:param request_ctx: The request context
:type request_ctx: :class:RequestContext
:param c... | c6ef2cd08b1a98c5204dd0e6a52b55ef57dbc78a | 3,640,761 |
def snr2Ivar(flux, snr):
"""
Estimate the inverse variance given flux and S/N.
Parameters
----------
flux : scalar or array of float
Flux of the obejct.
snr : scalar or array of float
Signal to noise ratio
"""
return 1.0 / ((flux / snr) ** 2.0) | 91c76cd942a8f37f57a227ccb35cf4968a16193b | 3,640,762 |
def revision_to_cashflows(rev, end_date):
"""Converts a revision to a list of cashflows
end_date -- the date from which we want to stop computing
"""
if rev.end_date is not None:
end_date = next_month(rev.end_date)
result = []
for first_of_month in first_of_month_range(rev.start_date, en... | 51778e5c389420101d3ef6afab0e28b6aa708689 | 3,640,763 |
def filter_verified_user(path, community_user_dataFrame,verified_user_file,sep = ',',header = None):
"""
根据已经认证的用户文件，过滤到保留社区中的认证用户。
:param path:认证用户文件的保存路径。
:param community_user_dataFrame:社区用户数据框，两列，列名（user_id, community_id）。
:param verified_user_file:认证用户的文件，为CSV文件，格式为(user_id, is_verified, name)，... | a571f72000e0a52e8f5aa0d5ae61cd07e2d7189d | 3,640,764 |
from datetime import datetime
def calculate(series):
"""
:param series: a list of lists of [[(),()], [(),()]] for every swc tube in the pixel
:return:
"""
# gets every dates tuple in the list
dates = [t for t, v in series]
# define the dates as a set
ds = set(dates[0])
# get the i... | 136fa5fd72bad6c1cb2938e25adc44d768caf43b | 3,640,765 |
from typing import Tuple
def load_dataset(filename: str) -> Tuple[np.ndarray, np.ndarray]:
"""
Load dataset for comparing the Gaussian Naive Bayes and LDA classifiers. File is assumed to be an
ndarray of shape (n_samples, 3) where the first 2 columns represent features and the third column the class
... | 15b6c7422fa397e13fc19de2a1e7681b73e3638c | 3,640,766 |
import csv
def readCSV(name,shape = [None], delimiter = ","):
""" Lectura de archivo csv name
Devuelve matriz con los datos y cabecera
"""
data = []
with open(name, 'r') as f:
reader = csv.reader(f,delimiter = delimiter)
for row in reader:
data.append(row[slice(*sha... | 789341daf51b2f1e92086a42698ea0fef1130505 | 3,640,767 |
from gdata.media import Category
def build_category(category):
"""Build a single-item list of a YouTube category.
This refers to the Category of a video entry, such as "Film" or "Comedy",
not the atom/gdata element. This does not check if the category provided
is valid.
Keyword arguments:
category: St... | 6906e30fcf1d72d7842ec5d7381a12842a9ded3e | 3,640,768 |
def all(event, context):
""" retrieves all experiment results from redis
params:
- namespace (optional)
- scope (optional, comma-separated list of experiments)
"""
r = _redis()
namespace = event.get('namespace', 'alephbet')
scope = event.get('scope')
if scope:
... | 583cc6a0101fbb6ef1ca12d6ddcfe76626bdd8dd | 3,640,769 |
import os
import time
def wait_for_save(filename, timeout=5):
"""Waits for FILENAME to update, waiting up to TIMEOUT seconds.
Returns True if a save was detected, and False otherwise.
"""
modification_time = os.path.getmtime(filename)
start_time = time.time()
while time.time() < start_time + t... | fa65a638188d32dba9904bb19e2327f5b0390996 | 3,640,770 |
def check_submodule_update(job, position):
"""
Checks to see if certain submodules have been updated and post a comment to the PR if so.
"""
output = get_output_by_position(job, position)
modules = find_in_output(output, "CIVET_CLIENT_SUBMODULE_UPDATES")
if not modules:
return False
... | ca6772b516fca899d6196cea47aa4185d958ec48 | 3,640,771 |
def _compute_subseq_errors_direct(series, weights):
"""
Subsequence errors (using one pass formulation)
:param Array{Float64,1} series
:param Array{Float64,1} weights
The subsequence errors is:
$$\begin{align}
E[i,j] &= Q[i,j] - \frac{S[i,j]^2}{W[i,j]}
\end{align}$$
Were W, S, ... | d8083b2b19102d51ee10baf2907890663f1d2b82 | 3,640,772 |
def preprocess_dataframe(data):
"""Helper method to preprocess the dataframe.
Creates new columns for year,month,recalls and percentage change.
Limits the date range for the experiment (these data are trustworthy)."""
data['recalls'] = data['doc_count'] + 1
data.drop(columns=['product', 'Unnam... | f6670cac1319108c88ee9ee409ce0ecdd1eca746 | 3,640,773 |
def is_solution(x:int, y:int) -> bool:
"""Returns try if (x, y) is a solution."""
# x and y are the values in a sequence of 15 terms of the following form:
# xxxxyxxxxxyxxxx
# x must be a positive integer
if x <= 0:
return False
# y must be a negative integer
if y >= 0:
re... | 5e620fc390f6a79fd25d00c8c8b51d0af788d48c | 3,640,774 |
def load_crl(file):
# type: (AnyStr) -> CRL
"""
Load CRL from file.
:param file: Name of file containing CRL in PEM format.
:return: M2Crypto.X509.CRL object.
"""
with BIO.openfile(file) as f:
cptr = m2.x509_crl_read_pem(f.bio_ptr())
return CRL(cptr, 1) | d711503c78edbb722189d7a06340ab9f719f853f | 3,640,775 |
def clean_and_lemmatize(text):
"""
Clean and lemmatize the text of a Tweet
Returns:
cleaned_text (string): The cleaned and lemmatized text.
"""
wnl = WordNetLemmatizer() # NLTK lemmatizer
converted_tweet = clean_and_tokenize(
text) # cleans the text and tokenize it
... | 0635e08aca69191d77ad652dcf752254fbfc2ea6 | 3,640,776 |
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
"""3x3 convolution with padding
Arguments:
in_planes {int} -- Number of channels in the input image
out_planes {int} -- Number of channels produced by the convolution
Keyword Arguments:
stride {int or tuple, option... | 1f55153bb35dd56b7cca2b00e13a0f4e5a963248 | 3,640,777 |
def task_finish(request, pk):
"""タスクを完了するＡＰＩ
:param request:
:param pk:
:return:
"""
task = get_object_or_404(models.Task, pk=pk)
prev_task = task.get_prev_task()
if prev_task is None or prev_task.can_continue():
task.status = '99'
task.updated_user = request.user
... | b995edd022e27b6101c9c79874af4fc78a01afe2 | 3,640,778 |
import sys
import argparse
def add_parser(subparsers):
"""Add reduction parser"""
parser = subparsers.add_parser(
'reduce', aliases=['red'], help="""Reduce games""",
description="""Create reduced game files from input game files.""")
parser.add_argument(
'--input', '-i', metavar='<... | d1629ba58fd17f89b6f8646b92a251fbcdba0a67 | 3,640,779 |
def fine_tune():
"""recreates top model architecture/weights and fine tunes with image augmentation and optimizations"""
# reconstruct vgg16 model
model = Sequential()
model.add(ZeroPadding2D((1, 1), input_shape=(3, img_width, img_height)))
model.add(Convolution2D(64, 3, 3, activation='relu', ... | 69982c739927fca8f1c8e3779a7358a7fc646a5f | 3,640,780 |
def normalize(a, seqlength=None, rv=None):
"""
Normalize the VSA vector
:param a: input VSA vector
:param seqlength: Optional, for BSC vectors must be set to a valid.
:param rv: Optional random vector, used for splitting ties on binary and ternary VSA vectors.
:return: new VSA vector
"""
... | ef8ec307add55a56be5991bb13579bc989726d3c | 3,640,781 |
def MACD(df, n_fast, n_slow):
"""Calculate MACD, MACD Signal and MACD difference
:param df: pandas.DataFrame
:param n_fast:
:param n_slow:
:return: pandas.DataFrame
"""
EMAfast = pd.Series(df['Close'].ewm(span=n_fast, min_periods=n_slow).mean())
EMAslow = pd.Series(df['Close'].ewm... | 368f80feb27bd67a387b0b9abb652d53205d22ac | 3,640,782 |
def ecef2map(xyz, spatialRef):
""" transform 3D cartesian Earth Centered Earth fixed coordinates, to
map coordinates (that is 2D) in a projection frame
Parameters
----------
xyz : np.array, size=(m,3), float
np.array with 3D coordinates, in WGS84. In the following form:
[[x, y, z], ... | f7177912c931cfe6c2cee5737ed6bd2afedeba08 | 3,640,783 |
def dis2speed(t, dis):
"""
Return speed in distance travelled per hour.
Args:
t (datetime64[ms]): 1D array with time.
dis (float ): 1D array with distance travelled.
Returns:
float: 1D array with speed data.
"""
# divide by one hour (=3600 x 1... | 4dae87509ad44604949f1d3f925f3b28947b9952 | 3,640,784 |
def default_context(plugin, context):
"""
Return the default context for plugins rendered with a template, which
simply is a single variable named ``plugin`` containing the plugin
instance.
"""
return {"plugin": plugin} | 5f7a88c02b6c11a150197e50a5be1847cba422b0 | 3,640,785 |
def get_model_from_key(model_name):
"""
Gets the model from a given key.
param:
model_name: name of model
return:
object
"""
_known_models = {}
#populate
for klass in Model.__subclasses__():
_known_models[klass.__name__] = klass
for sub in klass._... | 488c52635bfdf10c79936b0f33b84d0222d1ae5b | 3,640,786 |
def default_fields(
coll_id=None, type_id=None, entity_id=None,
width=12, **kwargs):
"""
Returns a function that accepts a field width and returns a dictionary of entity values
for testing. The goal is to isolate default entity value settings from the test cases.
"""
def_label = kwar... | 1670f95a8e95f84ca5f08aab8ee0a8effb1e6f76 | 3,640,787 |
import traceback
def predict_using_broadcasts(feature1, feature2, feature3, feature4):
"""
Scale the feature values and use the model to predict
:return: 1 if normal, -1 if abnormal 0 if something went wrong
"""
prediction = 0
x_test = [[feature1, feature2, feature3, feature4]]
try:
... | 4f766002e11fbe34f3479769db752c0df08b2df5 | 3,640,788 |
import torch
def make_positions(tensor, padding_idx, left_pad):
"""Replace non-padding symbols with their position numbers.
Position numbers begin at padding_idx+1.
Padding symbols are ignored, but it is necessary to specify whether padding
is added on the left side (left_pad=True) or right side (left... | 8e65c68daae2e40710c777d6e74f048b8b0ad547 | 3,640,789 |
def teq(state, *column_values):
"""Tag-Equals filter. Expects, that a first row contains tags and/or metadata
Tag row is ignored in comparison, but prepended to the result (in order to maintain the first row in the results).
Accepts one or more column-value pairs. Keep only rows where value in the column eq... | 7fd2786dcbe8705b48081c6bc96dcdc7452e35d3 | 3,640,790 |
def adjust_labels(data_y, dataset, pred_type='actions'):
"""
Transforms original labels into the range [0, nb_labels-1]
:param data_y: numpy integer array
Sensor labels
:param pred_type: string, ['gestures', 'locomotion', 'actions', 'tasks']
Type of activities to be recognized
:retu... | 1d201a20a8865cd505c0ee6b5385622a0ae28817 | 3,640,791 |
def is_str_or_bytes(x):
""" True if x is str or bytes.
This doesn't use rpartial to avoid infinite recursion.
"""
return isinstance(x, (str, bytes, bytearray)) | ff4bf19177ffe62f24713e077824e48ec45f8587 | 3,640,792 |
def _type_convert(new_type, obj):
"""
Convert type of `obj` to `force`.
"""
return new_type(obj) | fc47c100508d41caa7ffc786746b58e3d6f684e2 | 3,640,793 |
def create_tokenizer(corpus_file, vocab_size):
"""Create a tokenizer from a corpus file
Args:
corpus_file (Pathlib path): File containng corpus i.e. all unique words for
vocab_size (int): Vocabulary size of the tokenizer
Returns:
hugging_face tokenizer: Byte pair tokenizer used to ... | 6de30b057d920d650f065af0f9083130fbb6df77 | 3,640,794 |
def get_readings(tag):
"""Get sensor readings and collate them in a dictionary."""
try:
enable_sensors(tag)
readings = {}
# IR sensor
readings["ir_temp"], readings["ir"] = tag.IRtemperature.read()
# humidity sensor
readings["humidity_temp"], readings["humidity"] =... | 481aae840d9ab41995086e3ef98c500abf4ec82e | 3,640,795 |
import binascii
def digita_gw(request):
"""
Digita GW endpoint implementation
"""
identifier = request.data['DevEUI_uplink']['DevEUI']
apsen = core.models.apartment_sensor_models.ApartmentSensor.objects.get_or_create(identifier=identifier)[0]
payload = binascii.unhexlify(request.data['DevEUI_u... | e6bf45c92ea61278dd47e52ed945e91aa514d21b | 3,640,796 |
def resize_img(_img, maxdims=(1000, 700)):
"""
Resize a given image. Image can be either a Pillow Image, or a NumPy array. Resizing is done automatically such
that the entire image fits inside the given maxdims box, keeping aspect ratio intact
:param _img:
:param maxdims:
:return:
"""
tr... | 54716e4ce030a675a0655b06d7121d4c38bd7c43 | 3,640,797 |
def natural_key(s):
"""Converts string ``s`` into a tuple that will sort "naturally"
(i.e., ``name5`` will come before ``name10`` and ``1`` will come
before ``A``). This function is designed to be used as the ``key``
argument to sorting functions.
:param s: the str/unicode string to convert.
... | d0eb51bdd3e7c6caa5b13c38269bc9c07e3834d2 | 3,640,798 |
import os
import re
def query_props(path):
"""
Extracts a QueryProps object from a file name.
:param path: Path to a query file
:return: QueryProps of the file
"""
basename = os.path.basename(path)
match = re.match(r'''
(?P<topic>[^-]+?)
(\s*-\s*)
(?P<contributor>[... | d91406d724f98db063c5f2fe54ec4d5bd5ed325c | 3,640,799 |
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