content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def wpr(c_close, c_high, c_low, period):
"""
William %R
:type c_close: np.ndarray
:type c_high: np.ndarray
:type c_low: np.ndarray
:type period: int
:rtype: (np.ndarray, np.ndarray)
"""
size = len(c_close)
out = np.array([np.nan] * size)
for i in range(period - 1, size):
... | 0f1d8d46464be81daa6308df97a7a8d12a90274b | 17,400 |
def delete_action_log(request, log_id):
"""
View for delete the action log.
This view can only access by superuser and staff.
"""
action = get_object_or_404(ActionLog, id=log_id)
if action.status == 0 or action.status == 1:
messages.error(request, "Cannot delete the Action log that is r... | 8560e5280a57ddc8158b811fac29763bbaa8ef37 | 17,401 |
def hsla_to_rgba(h, s, l, a):
""" 0 <= H < 360, 0 <= s,l,a < 1
"""
h = h % 360
s = max(0, min(1, s))
l = max(0, min(1, l))
a = max(0, min(1, a))
c = (1 - abs(2*l - 1)) * s
x = c * (1 - abs(h/60%2 - 1))
m = l - c/2
if h<60:
r, g, b = c, x, 0
elif h<120:
r, g,... | 55e546756d4dd2a49581a5f950beb286dd73f3f9 | 17,402 |
from typing import Dict
from pathlib import Path
from typing import Optional
def prioritize(paths: Dict[int, Path], purpose: str) -> Optional[Path]:
"""Returns highest-priority and existing filepath from ``paths``.
Finds existing configuration or data file in ``paths`` with highest
priority and returns i... | 2c00d0bfe696040c2c19dc1d8b3393b7be124e11 | 17,403 |
def traverse(d, path):
"""Return the value at the given path from the given nested dict/list"""
for k in path.split('.'):
if k.isdigit():
k = int(k)
d = d[k]
return d | ba832a008073da5d97ba0a237a8e0ded17e4694e | 17,404 |
def _bundle_name_with_extension(ctx):
"""Returns the name of the bundle with its extension.
Args:
ctx: The Skylark context.
Returns:
The bundle name with its extension.
"""
return _bundle_name(ctx) + _bundle_extension(ctx) | 51f9c84fa2dd0ef9c5736a59ca2cd3c2d76aa108 | 17,405 |
import subprocess
def call(args):
"""
Call args in a subprocess and display output on the fly.
Return or raise stdout, stderr, returncode
"""
if TRACE: print('Calling:', ' '.join(args))
with subprocess.Popen(
args,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
... | 7837a8e807bc7e3cda56b1f5e8625f936cc4bee0 | 17,406 |
def cvt_axisang_t_o2i(axisang, trans):
"""-correction: t_r, R_rt_r. outer to inner"""
trans -= get_offset(axisang)
return axisang, trans | ef263052e91ecc2fb8e668bca89a9d5622b75ff2 | 17,407 |
import pytz
import numpy
import dateutil
def processData(dict, valuename, timename='Aika', multiplier=1.0):
"""Process "raw" OData dict and strip only the time and value.
Also convert time to UTC and hydrodynamics model (COHERENS) format.
Parameters
----------
dict: dictionary
Data dictionary a... | df452a703a3afface12dc76abb647a5e38b808c3 | 17,408 |
from datetime import datetime
def get_current_year():
"""Returns current year
"""
return str(datetime.date.today().year) | f019e7f2462a4d8db0db294fade6ca737e87a24c | 17,409 |
def parse_ans(text):
"""
Parses the given text as an answer set, i.e., a sequence of predicate
statements. Returns a (possibly empty) tuple of Predicate objects.
"""
return parser.parse_completely(
text,
parser.Rep(PredicateStatement),
devour=devour_asp
) | 44479668629b142115c27476242cbdf23b6657cc | 17,410 |
def get_xyz(data):
"""
:param data: 3D data
:return: 3D data coordinates
第1,2,3维数字依次递增
"""
nim = data.ndim
if nim == 3:
size_x, size_y, size_z = data.shape
x_arange = np.arange(1, size_x+1)
y_arange = np.arange(1, size_y+1)
z_arange = np.arange(1, size_z+1)
... | b1bd78fee6ca4a8fc2a33430c4ea5e922d696381 | 17,411 |
def wc_proximal_gradient(L, mu, gamma, n, verbose=1):
"""
Consider the composite convex minimization problem
.. math:: F_\\star \\triangleq \\min_x \\{F(x) \\equiv f_1(x) + f_2(x)\\},
where :math:`f_1` is :math:`L`-smooth and :math:`\\mu`-strongly convex,
and where :math:`f_2` is closed convex and... | ff8b67b963a2301e9b49870ffa9b6736a23420a4 | 17,412 |
import re
import os
def basic_output_filter(
filtered_prefixes=None,
filtered_patterns=None,
):
"""
Create a line filtering function to help output testing.
:param filtered_prefixes: A list of byte strings representing prefixes that will cause
output lines to be ignored if they start with one... | 8db044d7d9d94ad7c4137762336d7a4b80f7a53c | 17,413 |
def all_asset_types_for_shot(shot, client=default):
"""
Args:
shot (str / dict): The shot dict or the shot ID.
Returns:
list: Asset types from assets casted in given shot.
"""
path = "shots/%s/asset-types" % shot["id"]
return sort_by_name(raw.fetch_all(path, client=client)) | a7d06e49d564dbd294636e29f488703f5027026e | 17,414 |
from typing import Iterable
def train(x_mat: ndarray, k: int, *, max_iters: int = 10, initial_centroids: Iterable = None, history: bool = False):
"""
进行k均值训练
:param x_mat: 特征向量组，行数 m 表示样本数，列数 n 表示特征数
:param k: 聚类数目
:param max_iters: 最大迭代次数
:param initial_centroids: 初始聚类中心，不提供别的话将随机挑选聚类中心
... | 3a27cb709d6b267c8da19312f634f6003e2ba9a3 | 17,415 |
def download4(url, user_agent='wswp', num_retries=2):
"""Download function that includes user agent support"""
# wswp: web scraping with python
print 'Downloading:', url
headers = {'User-agent': user_agent}
request = urllib2.Request(url, headers=headers)
try:
html = urllib2.urlopen(reque... | 1381e64e93b373e68a1a07eaab1688462f905374 | 17,416 |
import unittest
def testv1():
"""Runs the unit tests without test coverage."""
tests = unittest.TestLoader().discover('./tests/api/v1', pattern='test*.py')
result = unittest.TextTestRunner(verbosity=2).run(tests)
if result.wasSuccessful():
return 0
return 1 | 519835d59ce7d370e8099e94a48b1e7309274d99 | 17,417 |
def get_third_order_displacements(cell,
symmetry,
is_plusminus='auto',
is_diagonal=False):
"""Create dispalcement dataset
Note
----
Atoms 1, 2, and 3 are defined as follows:
Atom 1: The first disp... | 6ae03dbd10ffec75bc274b4a4115b81d28cefc40 | 17,418 |
def get_result_type(action):
"""Gets the corresponding ROS action result type.
Args:
action: ROS action name.
Returns:
Result message type. None if not found.
"""
msg_type = rostopic.get_topic_type("{}/result".format(action))[0]
# Replace 'ActionResult' with 'Result'.
retu... | f5612ac116357000106f7ff24f0d2bebb6789547 | 17,419 |
import statistics
import math
def get_turbulence(sequence):
"""
Computes turbulence for a given sequence, based on `Elzinga & Liefbroer's 2007 definition <https://www.researchgate.net/publication/225402919_De-standardization_of_Family-Life_Trajectories_of_Young_Adults_A_Cross-National_Comparison_Using_Sequence_An... | 9900d377240b609de1cb7a5284752457947ef6c3 | 17,420 |
def reflect(array, holder=1):
"""
Reflects a np array across the y-axis
Args:
array: array to be reflected
holder: a holder variable so the function can be used in optimization algorithms. If <0.5, does not reflect.
Returns:
Reflected array
"""
c = array.copy()
if ... | c39cbf0bb3a949254e4f0c35b20bdf84766d2084 | 17,421 |
import os
from datetime import datetime
import time
import logging
import sys
def create_and_return_logger(logger_name, filename="log"):
"""
Function to create a custom logger that will print to terminal
as well as write to a log file
Accepts: Logger name for script that is calling logger, and fil... | 5860e00fe3fd52e11afd4daa27554c2e070afe06 | 17,422 |
from sys import path
def _get_all_entries(entry_list, keep_top_dir):
"""
Returns a list of all entries (files, directories) that should be copied.
The main purpose of this function is to evaluate 'keep_top_dir' and in case
it should not be kept use all the entries below the top-level directories.
... | fbd12ef87cdc21307908ad7013167559da6fc051 | 17,423 |
import os
def process_exclude_items(exclude_items=[]):
"""
Process the exclude items to get list of directories to NOT be scanned
:return: a list of directories to not be scanned if any, otherwise an empty list
"""
logger.debug("Parsing exclude items ...")
parsed_list = []
for item in excl... | 36374faa3182aa1db0ba0d12b6a4f3ce23a69a95 | 17,424 |
def absolute_name_scope(scope, reuse=tf.AUTO_REUSE):
"""Builds an absolute tf.name_scope relative to the current_scope.
This is helpful to reuse nested name scopes.
E.g. The following will happen when using regular tf.name_scope:
with tf.name_scope('outer'):
with tf.name_scope('inner'):
prin... | b9bd9e801603472c3e7e1db7a8768387b9942f3c | 17,425 |
def regina_edge_orientation_agrees(tet, vert_pair):
"""
Given tet and an ordered pair of (regina) vert nums of that tet, does this ordering
agree with regina's ordering of the verts of that edge of the triangulation
"""
edge_num = vert_pair_to_edge_num[tuple(vert_pair)]
mapping = tet.faceMapping... | a70f08f56754eee24b9c4c71d5b6b537388a4ca4 | 17,426 |
from typing import Optional
from datetime import datetime
async def populate_challenge(
challenge_status: str = "process",
is_public: bool = True,
user_id: Optional[UUID] = USER_UUID,
challenge_id: UUID = POPULATE_CHALLENGE_ID,
) -> Challenge:
"""Populate challenge for routes testi... | fa47e65c7615af8dfebed4dd66fd92141d50e130 | 17,427 |
from typing import List
def is_common_prefix(words: List[str], length: int) -> bool:
"""Binary Search"""
word: str = words[0][:length]
for next_word in words[1:]:
if not next_word.startswith(word):
return False
return True | f57c7309f725baba0b65c92181a6f1ab2827558a | 17,428 |
def freq_upsample(s, upsample):
""" padding in frequency domain, should be used with ifft so that
signal is upsampled in time-domain.
Args:
s : frequency domain signal
upsample : an integer indicating factor of upsampling.
Returns:
padded signal
"""
if upsample =... | 78377f6c552fe4f6d764a33b3e6ee555b4aabe71 | 17,429 |
def streaming_parsing_covering(groundtruth_categories,
groundtruth_instances,
predicted_categories,
predicted_instances,
num_classes,
max_instances_per_category,
... | 7c41f5b0c1111287759cc03cdc2a0c8a932aba11 | 17,430 |
from typing import Union
def get_rxn_lookup(medObj:Union[m.Medication, m.LocalMed, m.NDC]):
"""
DEPRECATED
Lookup RxCUI for codes from a different source
:param medObj:
:return:
"""
if isinstance(medObj, m.RxCUI):
smores_error('TBD')
return 0, []
success_count, errors ... | bba03aa380666b13db89497c720a62570a2918d0 | 17,431 |
def identity(dims):
"""
Create an identity linear operator
:param dims: array of dimensions
"""
dims = expand_dims(dims)
return identity_create(dims) | 4d57c5a0da628c8f24de4f621728176714a4ab54 | 17,432 |
def _gen_samples_2d(enn_sampler: testbed_base.EpistemicSampler,
x: chex.Array,
num_samples: int,
categorical: bool = False) -> pd.DataFrame:
"""Generate posterior samples at x (not implemented for all posterior)."""
# Generate the samples
data = []
rng... | 19fc06700ae42b015694fc9389c05ad0caebf54d | 17,433 |
def rules(r_index, c_index, lives, some_board, duplicate_board):
"""Apply Conway's Rules to a board
Args:
r_index (int): Current row index
c_index (int): Current column index
lives (int): Number of ALIVE cells around current position
some_board (List of lists of strings): Board ... | f654a134be3eccad122720cd58f577a2d7e580d8 | 17,434 |
def get_describe_tasks(cluster_name, tasks_arns):
"""Get information about a list of tasks."""
return (
ecs_client()
.describe_tasks(cluster=cluster_name, tasks=tasks_arns)
.get("tasks", [])
) | 663cc2d2241aa3d75c8f2de35780ebe9a5d4ae31 | 17,435 |
def make_bcc110(latconst=1.0):
"""
Make a cell of bcc structure with z along [110].
"""
s= NAPSystem(specorder=_default_specorder)
#...lattice
a1= np.array([ 1.0, 0.0, 0.0 ])
a2= np.array([ 0.0, 1.414, 0.0 ])
a3= np.array([ 0.0, 0.0, 1.41... | 187556e30b4e89718d4c8d1179579ba498062d26 | 17,436 |
def mode_mods_to_int(mode: str) -> int:
"""Converts mode_mods (str) to mode_mods (int)."""
# NOTE: This is a temporary function to convert the leaderboard mode to an int.
# It will be removed when the site is fully converted to use the new
# stats table.
for mode_num, mode_str in enumerate((
... | 0bfaa8cf04bcee9395dff719067be9753be075c4 | 17,437 |
def ntu_tranform_skeleton(test):
"""
:param test: frames of skeleton within a video sample
"""
remove_frame = False
test = np.asarray(test)
transform_test = []
d = test[0, 0:3]
v1 = test[0, 1 * 3:1 * 3 + 3] - test[0, 0 * 3:0 * 3 + 3]
v1 = v1 / np.linalg.norm(v1)
v2_ = test[0, ... | 6f8e9e3ff0b6fa95b5f3b8c22aef2de05730a78c | 17,438 |
import random
import time
import requests
def request_to_dataframe(UF):
"""Recebe string do estado, retona DataFrame com faixa de CEP do estado"""
#Try to load the proxy list. If after several attempts it still doesn't work, raise an exception and quit.
proxy_pool = proxy_list_to_cycle()
#Set i... | f71de0ec169f375fff1fba87d55aa8021b851990 | 17,439 |
import csv
def read_sto_mot_file(filename):
"""
Read sto or mot file from Opensim
----------
filename: path
Path of the file witch have to be read
Returns
-------
Data Dictionary with file informations
"""
data = {}
data_row = []
first_li... | 584cff26cb217d5fadfcea025ad58e431f46676a | 17,440 |
def verify_cef_labels(device, route, expected_first_label, expected_last_label=None, max_time=90,
check_interval=10):
""" Verify first and last label on route
Args:
device ('obj'): Device object
route ('str'): Route address
expected_first_label ('str'): Expected fir... | c082920d0c93ec0c2897dc5a06c9d9d9452151af | 17,441 |
def fcat(*fs):
"""Concatenate a sequence of farrays.
The variadic *fs* input is a homogeneous sequence of functions or arrays.
"""
items = list()
for f in fs:
if isinstance(f, boolfunc.Function):
items.append(f)
elif isinstance(f, farray):
items.extend(f.flat... | 440a850ed17b8fc844cafaa765b24620a29fa0fd | 17,442 |
def get_path_to_spix(
name: str,
data_directory: str,
thermal: bool,
error: bool = False,
file_ending: str = "_6as.fits",
) -> str:
"""Get the path to the spectral index
Args:
name (str): Name of the galaxy
data_directory (str): dr2 data directory
thermal (bool): non... | bf8fdff001049ed0738ed856e8234c43ce4511b7 | 17,443 |
def hexpos (nfibres,diam) :
"""
Returns a list of [x,y] positions for a classic packed hex IFU configuration.
"""
positions = [[np.nan,np.nan] for i in range(nfibres)]
# FIND HEX SIDE LENGTH
nhex = 1
lhex = 1
while nhex < nfibres :
lhex += 1
nhex = 3*lhex**2-3*lhex+1
if nhex != nfibres:
lhex -= 1
nhex ... | 4dbf1209d7021c6a4defd1c58e420b362bdbf84c | 17,444 |
from bs4 import BeautifulSoup
def parse_object_properties(html):
"""
Extract key-value pairs from the HTML markup.
"""
if isinstance(html, bytes):
html = html.decode('utf-8')
page = BeautifulSoup(html, "html5lib")
propery_ps = page.find_all('p', {'class': "list-group-item-text"})
o... | 8eb2d15cb5f46075ec44ff61265a8f70123a8646 | 17,445 |
def rgb2hex(r, g, b, normalised=False):
"""Convert RGB to hexadecimal color
:param: can be a tuple/list/set of 3 values (R,G,B)
:return: a hex vesion ofthe RGB 3-tuple
.. doctest::
>>> from colormap.colors import rgb2hex
>>> rgb2hex(0,0,255, normalised=False)
'#0000FF'
... | 03afd09cc280d7731ca6b28098cf3f5605fddda7 | 17,446 |
def test_hookrelay_registry(pm):
"""Verify hook caller instances are registered by name onto the relay
and can be likewise unregistered."""
class Api:
@hookspec
def hello(self, arg):
"api hook 1"
pm.add_hookspecs(Api)
hook = pm.hook
assert hasattr(hook, "hello")
... | 5f7733efbdbaf193b483c108838d2571ff686e52 | 17,447 |
def model_choices_from_protobuf_enum(protobuf_enum):
"""Protobufs Enum "items" is the opposite order djagno requires"""
return [(x[1], x[0]) for x in protobuf_enum.items()] | d3f5431293a9ab3fdf9a92794b1225a0beec40cc | 17,448 |
import os
def load_boxes_and_labels(cfg, mode):
"""
Loading boxes and labels from csv files.
Args:
cfg (CfgNode): config.
mode (str): 'train', 'val', or 'test' mode.
Returns:
all_boxes (dict): a dict which maps from `video_name` and
`frame_sec` to a list of `box`. ... | 9ea7f476474f834fcfb70700cc269b4abf8d5c33 | 17,449 |
def kmeans(boxes, k):
"""
Group into k clusters the BB in boxes.
http://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html#sklearn.cluster.KMeans
:param boxes: The BB in format Nx4 where (x1,y1,x2,y2)
:param k: the number of clusters.
:return: k clusters with the element in... | 0d2bcfb2fb7d5639f95db92ac5aa5e73b1b27498 | 17,450 |
def observation_min_max_in_hex_grid_json(request: HttpRequest):
"""Return the min, max observations count per hexagon, according to the zoom level. JSON format.
This can be useful to dynamically color the grid according to the count
"""
zoom = extract_int_request(request, "zoom")
species_ids, datas... | 24a3f4846aceea2df0b724d6bada88315b815ee2 | 17,451 |
import os
def is_path(value, default="", expand=None):
"""Parse a value as a path
Parameters
----------
expand:
expandvars and expandhome on loaded path
**Warning: expand currently can't work with interpolation**
"""
# TODO: fix interpolation and expand !
if str(value) == "No... | d2d369f35e6cc71dbdc3cd955456aeecb375fee6 | 17,452 |
import subprocess
import os
def find_suites():
"""
Return a dict of suitename and path, e.g.
{"heat_equation": /home/safl/bechpress/suites/cpu/heat_equation.py"}
"""
p = subprocess.Popen(
["bp-info", "--suites"],
stdout = subprocess.PIPE,
stderr = subprocess.PIPE
)
... | f3303f48b79d3ca4d172f272b7243629557bb9cc | 17,453 |
from bs4 import BeautifulSoup
def parseHtml(html):
"""
BeautifulSoup でパースする
Parameters
----------
html : str
HTML ソース文字列
Returns
-------
soup : BeautifulSoup
BeautifulSoup オブジェクト
"""
soup = BeautifulSoup(html, 'html.parser')
return soup | e8d7a39a9881606d1dfee810ab1c2cecd11eaba2 | 17,454 |
def am_score(probs_data, probs_gen):
"""
Calculate AM Score
"""
mean_data = np.mean(probs_data, axis=0)
mean_gen = np.mean(probs_gen, axis=0)
entropy_gen = np.mean(entropy(probs_gen, axis=1))
am_score = entropy(mean_data, mean_gen) + entropy_gen
return am_score | 5e3c3f42ed2402dd2e48ab1ff4f9ff13754d5c31 | 17,455 |
import torch
def load_image(path_image, size=None, bgr_mean=[103.939, 116.779, 123.68]):
"""
Loads and pre-process the image for SalGAN model.
args:
path_image: abs path to image
size: size to input to the network (it not specified, uses SalGAN predifined)
bgr_mean: mean values (B... | 3a9ca220bb48f26d76ae35fd58897c8e59cdae0c | 17,456 |
def GetWsdlNamespace(version):
""" Get wsdl namespace from version """
return "urn:" + serviceNsMap[version] | bc75fa0e45c4ce4750898db75571de84aa302fc2 | 17,457 |
def is_PC(parcels):
"""
Dummy for Pinal County.
"""
return (parcels.county == 'PC').astype(int) | 60aa7dcc7adaefee177406c7e6bb963a5a4567d9 | 17,458 |
import hashlib
import requests
def check_password(password: str) -> int:
"""Use Have I Been Pwned to determine whether a password is bad.
If the request fails, this function will assume the password is fine, but
log an error so that administrators can diagnose it later.
:param password: The password... | 609dd29ee2b252452e31d64b18e835a39e1cbf22 | 17,459 |
def rqpos(A):
"""
RQ decomp. of A, with phase convention such that R has only positive
elements on the main diagonal.
If A is an MPS tensor (d, chiL, chiR), it is reshaped and
transposed appropriately
before the throughput begins. In that case, Q will be a tensor
of the same size, while R ... | 026629b6638265daee83e8d8b5ab5b47b61e64d8 | 17,460 |
import torch
from typing import OrderedDict
def load_checkpoint(model,
filename,
map_location=None,
strict=False,
logger=None,
show_model_arch=True,
print_keys=True):
""" Note that official pre-... | 1d948f45f81c93af73394c891dc7e692c24378b3 | 17,461 |
def basic_image_2():
"""
A 10x10 array with a square (3x3) feature
Equivalent to results of rasterizing basic_geometry with all_touched=True.
Borrowed from rasterio/tests/conftest.py
Returns
-------
numpy ndarray
"""
image = np.zeros((20, 20), dtype=np.uint8)
image[2:5, 2:5] = 1... | 8e83070721b38f2a886c7affb4aadc9a053f1748 | 17,462 |
def download(url, verbose, user_agent='wswp', num_retries=2, decoding_format='utf-8', timeout=5):
"""
Function to download contents from a given url
Input:
url: str
string with the url to download from
user_agent: str
Default 'wswp'
num_retries:... | 31592018b6f6f62154444dfc44b723efc1bd7f47 | 17,463 |
from typing import Union
from typing import List
def _write_deform(model: Union[BDF, OP2Geom], name: str,
loads: List[AEROS], ncards: int,
op2_file, op2_ascii, endian: bytes, nastran_format: str='nx') -> int:
"""
(104, 1, 81)
NX 2019.2
Word Name Type Description
... | 55f2cb18336a940c550ee68bd5148c8d74f5bb93 | 17,464 |
def polygonize(geometries, **kwargs):
"""Creates polygons formed from the linework of a set of Geometries.
Polygonizes an array of Geometries that contain linework which
represents the edges of a planar graph. Any type of Geometry may be
provided as input; only the constituent lines and rings will be u... | 20b883734a1acedb1df3241e1815687640cac8cd | 17,465 |
def slerp(input_latent1, input_latent2, interpolation_frames=100):
"""Spherical linear interpolation ("slerp", amazingly enough).
Parameters
----------
input_latent1, input_latent2 : NumPy arrays
Two arrays which will be interpolated between.
interpolation_frames : int, optional
... | 392b2e61f3369cf1e4038fac4240dca36f848dce | 17,466 |
from datetime import datetime
def parent_version_config():
"""Return a configuration for an experiment."""
config = dict(
_id="parent_config",
name="old_experiment",
version=1,
algorithms="random",
metadata={
"user": "corneauf",
"datetime": datet... | ff1f123ce06d687eb3b0031d6bc82c808918c46e | 17,467 |
import re
def sanitize_k8s_name(name):
"""From _make_kubernetes_name
sanitize_k8s_name cleans and converts the names in the workflow.
"""
return re.sub('-+', '-', re.sub('[^-0-9a-z]+', '-', name.lower())).lstrip('-').rstrip('-') | edaf6dc3083f0b57aeb1d95a66b5a7f8c1347b55 | 17,468 |
def main():
""" Process command line arguments and run x86 """
run = X86Run()
result = run.Run()
return result | 7de61875207aa17bcf2ef87ff138540626fc7d2b | 17,469 |
def gen_key(uid, section='s'):
"""
Generate store key for own user
"""
return f'cs:{section}:{uid}'.encode() | 5e6386650f6bbaef681636424fd813f2df93fe58 | 17,470 |
def convert_atom_to_voxel(coordinates: np.ndarray, atom_index: int,
box_width: float, voxel_width: float) -> np.ndarray:
"""Converts atom coordinates to an i,j,k grid index.
This function offsets molecular atom coordinates by
(box_width/2, box_width/2, box_width/2) and then divides by
... | 6f08b594f2012aa0ba4a7985d5f4e2049c4629d3 | 17,471 |
import platform
import sys
def get_toolset_url():
"""URL of a platform specific Go toolset archive."""
# TODO(vadimsh): Support toolset for cross-compilation.
arch = {
'amd64': 'x86-64',
'x86_64': 'x86-64',
'i386': 'x86-32',
'x86': 'x86-32',
}.get(platform.machine().lower())
variant = TOOLSE... | d88d8407775e9d0ca1ee80fee076046ae7ca7e44 | 17,472 |
def plot_det_curve(y_true_arr, y_pred_proba_arr, labels_arr, pos_label=None, plot_thres_for_idx=None,
log_wandb=False):
"""Function for plotting DET curve
Args:
y_true_arr (list/np.array): list of all GT arrays
y_pred_proba_arr (list/np.array): list of all predicted probabili... | 0437d700a9555b48b84cbb6e225bc88f1a57e34d | 17,473 |
def harmonic_separation(audio, margin=3.0):
"""
Wraps librosa's `harmonic` function, and returns a new Audio object.
Note that this folds to mono.
Parameters
---------
audio : Audio
The Audio object to act on.
margin : float
The larger the margin, the larger the separation.... | 3ac3e0d87f719814ca021f594a21dde08e9fd02f | 17,474 |
def merge(
left,
right,
how: str = "inner",
on=None,
left_on=None,
right_on=None,
left_index: bool = False,
right_index: bool = False,
sort: bool = False,
suffixes=("_x", "_y"),
copy: bool = True,
indicator: bool = False,
validate=None,
): # noqa: PR01, RT01, D200
... | da07b44fb80ee28cc8320c071876ef6ad573d974 | 17,475 |
def generate_modal(title, callback_id, blocks):
"""
Generate a modal view object using Slack's BlockKit
:param title: Title to display at the top of the modal view
:param callback_id: Identifier used to help determine the type of modal view in future responses
:param blocks: Blocks to add to the mo... | e0caeec1ab1cf82ed6f02ec77a984dcb25e329f5 | 17,476 |
def dir_thresh(img, sobel_kernel=3, thresh=(0.7, 1.3)):
"""
#---------------------
# This function applies Sobel x and y,
# then computes the direction of the gradient,
# and then applies a threshold.
#
"""
# Take the gradient in x and y separately
sobelx = cv2.Sobel(img, cv2.CV_64F... | 0f5aefdbc9ffbe8e3678145e2926a4fbd7e01629 | 17,477 |
from datetime import datetime, timedelta
def seconds_to_time( time ):
"""
Get a datetime object or a int() Epoch timestamp and return a
pretty string like 'an hour ago', 'Yesterday', '3 months ago',
'just now', etc
"""
if not time:
return "0s"
if isinstance( time, timedelta ) or is... | 407fa93f782c8cff142be1ab721969d3e4c2b42f | 17,478 |
import os
def bq_use_legacy_sql():
"""
Returns BIGQUERY_LEGACY_SQL if env is set
"""
return os.environ.get('BIGQUERY_LEGACY_SQL', 'TRUE') | 53d51c5eb1caa9b6041e9b2d29bde068199bba52 | 17,479 |
def load_txt_into_set(path, skip_first_line=True):
"""Load a txt file (one value per line) into a set."""
result = set()
file = open_file_dir_safe(path)
with file:
if skip_first_line:
file.readline()
for line in file:
line = line.strip()
result.add(li... | 17ad3c15820595b72254dbe4c9097a8857511599 | 17,480 |
def failed(obj):
"""Returns True if ``obj`` is an instance of ``Fail``."""
return isinstance(obj, Fail) | 715fe3ae1154e3e5712b6f4535021b44e8020146 | 17,481 |
def linkCount(tupleOfLists, listNumber, lowerBound, upperBound):
"""Counts the number of links in one of the lists passed.
This function is a speciality function to aid in calculating
statistics involving the number of links that lie in a given
range. It is primarily intended as a private helper functi... | 239fd8d3c01fe6c88444cfa7369459e3c76005dc | 17,482 |
def encode_md5(plain_text):
"""
Encode the plain text by md5
:param plain_text:
:return: cipher text
"""
plain_text = plain_text + EXT_STRING
encoder = md5()
encoder.update(plain_text.encode('utf-8'))
return encoder.hexdigest() | ad88ebc12334c9438c38719cd7c836edb9736d3c | 17,483 |
import warnings
def delta(x, y, assume_normal=True, percentiles=[2.5, 97.5],
min_observations=20, nruns=10000, relative=False, x_weights=1, y_weights=1):
"""
Calculates the difference of means between the samples (x-y) in a
statistical sense, i.e. with confidence intervals.
NaNs are ignored... | 37b742775777b5a0bd26f7e8fdf7a189a69b199f | 17,484 |
def CircleCircumference(curve_id, segment_index=-1):
"""Returns the circumference of a circle curve object
Parameters:
curve_id = identifier of a curve object
segment_index [opt] = identifies the curve segment if
curve_id identifies a polycurve
Returns:
The circumference of the circl... | 7a9200b089cebab93cbea387a4dd92590157dc45 | 17,485 |
def generate_handshake(info_hash, peer_id):
"""
The handshake is a required message and must be the first message
transmitted by the client. It is (49+len(pstr)) bytes long in the form:
<pstrlen><pstr><reserved><info_hash><peer_id>
Where:
pstrlen: string length of <pstr>, as a single raw byte
... | ae13462608f3e2ec47abdb12e87a3bc08faa1cba | 17,486 |
def tokenizer_decorator(func, **kwargs):
"""
This decorator wraps around a tokenizer function.
It adds the token to the info dict and removes the found token from the given name.
"""
if not callable(func):
raise TypeError(f"func {func} not callable")
@wraps(func)
def wrapper(name, i... | d1827ab75a12f923c6da69927323d9c5013124c0 | 17,487 |
def reverse_complement( seq ):
"""
Biological reverse complementation. Case in sequences are retained, and
IUPAC codes are supported. Code modified from:
http://shootout.alioth.debian.org/u32/program.php?test=revcomp&lang=python3&id=4
"""
return seq.translate(_nt_comp_table)[::-1] | 86229dfeceecb7e0d2e1215b25074c35fbd38792 | 17,488 |
def computeLPS(s, n):
"""
Sol with better comle
"""
prev = 0 # length of the previous longest prefix suffix
lps = [0]*(n)
i = 1
# the loop calculates lps[i] for i = 1 to n-1
while i < n:
if s[i] == s[prev]:
prev += 1
lps[i] = prev
i += 1
... | 8b4374c9ac29f59cf1f4b0e6e07628776828c11a | 17,489 |
def roundedCorner(pc, p1, p2, r):
"""
Based on Stackoverflow C# rounded corner post
https://stackoverflow.com/questions/24771828/algorithm-for-creating-rounded-corners-in-a-polygon
"""
def GetProportionPoint(pt, segment, L, dx, dy):
factor = float(segment) / L if L != 0 else segment
... | e77497918025deba211469616d210c23483e2152 | 17,490 |
def synthetic_data(n_points=1000, noise=0.05,
random_state=None, kind="unit_cube",
n_classes=None, n_occur=1, legacy_labels=False, **kwargs):
"""Make a synthetic dataset
A sample dataset generators in the style of sklearn's
`sample_generators`. This adds other function... | 740b5d2f708e177ce703f2124806ab7bd0079a09 | 17,491 |
import argparse
def parse_args():
"""
Argument Parser
"""
parser = argparse.ArgumentParser(description="Wiki Text Extractor")
parser.add_argument("-i", "--input_dir", dest="input_dir", type=str, metavar="PATH",
default="./extracted",help="Input directory path ")
... | af9149f893bb652c7e86a731749b3e2a5e4c1c8f | 17,492 |
def _load_default_profiles():
# type: () -> Dict[str, Any]
"""Load all the profiles installed on the system."""
profiles = {}
for path in _iter_default_profile_file_paths():
name = _get_profile_name(path)
if _is_abstract_profile(name):
continue
definition = _read_p... | b53411dce6bdf3baba876a626b023a2b93e48c99 | 17,493 |
import torch
def train_model(model, train_loader, valid_loader, learning_rate, device,
epochs):
"""Trains a model with train_loader and validates it with valid_loader
Arguments:
model -- Model to train
train_loader -- Data to train
valid_loader -- Data to validate the ... | 3addd258adddcbb43d846dae09d943d9a7016b69 | 17,494 |
def get_weapon_techs(fighter=None):
"""If fighter is None, return list of all weapon techs.
If fighter is given, return list of weapon techs fighter has."""
if fighter is None:
return weapon_tech_names
else:
return [t for t in fighter.techs if get_tech_obj(t).is_weapon_tech] | bbda76e55fdbe80e9883ff05746256fb56767136 | 17,495 |
def xml_to_values(l):
"""
Return a list of values from a list of XML data potentially including null values.
"""
new = []
for element in l:
if isinstance(element, dict):
new.append(None)
else:
new.append(to_float(element))
return new | 30b6af4101f45697e0f074ddedcd051aba37cb99 | 17,496 |
def _get_options(raw_options, apply_config):
"""Return parsed options."""
if not raw_options:
return parse_args([''], apply_config=apply_config)
if isinstance(raw_options, dict):
options = parse_args([''], apply_config=apply_config)
for name, value in raw_options.items():
... | e88014f0f5497e72973afbdf669cf14bf4537051 | 17,497 |
def csvdir_equities(tframes=None, csvdir=None):
"""
Generate an ingest function for custom data bundle
This function can be used in ~/.zipline/extension.py
to register bundle with custom parameters, e.g. with
a custom trading calendar.
Parameters
----------
tframes: tuple, optional
... | 6dc4b76e52f7512074eb044d5505c904a323eb69 | 17,498 |
def normalize_skeleton(joints):
"""Normalizes joint positions (NxMx2 or NxMx3, where M is 14 or 16) from parent to child order. Each vector from parent to child is normalized with respect to it's length.
:param joints: Position of joints (NxMx2) or (NxMx3)
:type joints: numpy.ndarray
:retur... | 579862d05814eaa9b04f3e1a4812e727b02175aa | 17,499 |
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